[
  {
    "path": ".devcontainer/devcontainer.json",
    "content": "{\n  \"name\": \"Electricity Maps Dev\",\n  \"image\": \"mcr.microsoft.com/devcontainers/python:1-3.10-bookworm\",\n  \"features\": {\n    \"ghcr.io/devcontainer-community/devcontainer-features/astral.sh-uv:1\": {}\n  },\n  \"postCreateCommand\": \"uv sync --group dev --group scripts --extra parsers\",\n  \"customizations\": {\n    \"vscode\": {\n      \"extensions\": [\n        \"ms-python.vscode-pylance\",\n        \"ms-python.python\",\n        \"esbenp.prettier-vscode\",\n        \"redhat.vscode-yaml\",\n        \"charliermarsh.ruff\"\n      ]\n    }\n  }\n}\n"
  },
  {
    "path": ".dockerignore",
    "content": ".git\n*.tar.gz\n*.json\n*secrets*\n*.env\n*.mp4\n*.mkv\n\n\ndatascience\n\nscreenshots*\n"
  },
  {
    "path": ".editorconfig",
    "content": "root = true\n\n[*]\nindent_style = space\nend_of_line = lf\ninsert_final_newline = true\ncharset = utf-8\nindent_size = 2\n\n[*.py]\nindent_size = 4\n"
  },
  {
    "path": ".gitattributes",
    "content": "# Auto-detect text vs. binary files and ensure newlines are always LF for\n# text files on check-out and check-in.\n* text=auto eol=lf\n\n# Denote all files in the `parsers/test/mocks` directory as vendored.\n# This makes GitHub ignore them for language statistics.\nelectricitymap/contrib/parsers/tests/mocks/** linguist-vendored\n"
  },
  {
    "path": ".github/CODEOWNERS",
    "content": "# Codeowners file\n\nelectricitymap/** @electricitymaps/grid-modelling-methodology\nconfig/** @electricitymaps/grid-modelling-methodology\ntests/** @electricitymaps/grid-modelling-methodology\n"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/blank-issue.md",
    "content": "---\nname: Blank issue\nabout: Anything else\ntitle: ''\nlabels: ''\nassignees: ''\n\n---\n\n## Description\n"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/config.yml",
    "content": "blank_issues_enabled: true"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/data-issue.yml",
    "content": "name: Data Issue\ndescription: Use this form if you believe there is a issue with the data on the app.\ntitle: \"[Data Issue]: \"\nlabels: [\"data\", \"needs triage\"]\nbody:\n  - type: markdown\n    attributes:\n      value: |\n        Thanks for taking the time to file this issue.\n  - type: textarea\n    id: when-did-this-happen\n    attributes:\n      label: When did this happen?\n      description: Please provide the date and time when the problem happened.\n      placeholder: e.g. \"2018-01-01 12:00\"\n    validations:\n      required: true\n  - type: textarea\n    id: what-zones-are-affected\n    attributes:\n      label: What zones are affected?\n      description: Please provide the zones affected.\n      placeholder: e.g. \"Dk-DK1, DK-DK2, SE-SE4\"\n    validations:\n      required: true\n  - type: textarea\n    id: what-is-the-problem\n    attributes:\n      label: What is the problem?\n      description: |\n        What appears to be the problem with the data?\n        Please provide as much detail as possible.\n        You can also add screenshots here if you have them.\n      placeholder: e.g. \"The data for biomass is not being displayed even though it's available at the source.\"\n    validations:\n      required: true\n"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/feature_request.md",
    "content": "---\nname: Feature request\nabout: Suggest an idea for this project\ntitle: ''\nlabels: ''\nassignees: ''\n\n---\n\n**Is your feature request related to a problem? Please describe.**\nA clear and concise description of what the problem is. Ex. I'm always frustrated when [...]\n\n**Describe the solution you'd like**\nA clear and concise description of what you want to happen.\n\n**Describe alternatives you've considered**\nA clear and concise description of any alternative solutions or features you've considered.\n\n**Additional context**\nAdd any other context or screenshots about the feature request here.\n"
  },
  {
    "path": ".github/ISSUE_TEMPLATE/frontend-bug-report.md",
    "content": "---\nname: Frontend bug report\nabout: Create a report to help us improve\ntitle: ''\nlabels: \"bug \\U0001F41E, frontend \\U0001F3A8\"\nassignees: ''\n\n---\n\n**Describe the bug**\nA clear and concise description of what the bug is.\n\n**To Reproduce**\nSteps to reproduce the behavior:\n1. Go to '...'\n2. Click on '....'\n3. Scroll down to '....'\n4. See error\n\n**Expected behavior**\nA clear and concise description of what you expected to happen.\n\n**Screenshots**\nIf applicable, add screenshots to help explain your problem.\n\n**Desktop (if relevant):**\n - OS: [e.g. iOS]\n - Browser [e.g. chrome, safari]\n - Version [e.g. 22]\n\n**Smartphone (if relevant):**\n - Device: [e.g. iPhone6]\n - OS: [e.g. iOS8.1]\n - Browser [e.g. stock browser, safari]\n - Version [e.g. 22]\n\n**Additional context**\nAdd any other context about the problem here.\n"
  },
  {
    "path": ".github/codeql-config.yml",
    "content": "name: 'CodeQL config'\npaths-ignore:\n  - 'config/**/*.yaml'\n"
  },
  {
    "path": ".github/dependabot.yml",
    "content": "# Dependabot config file\n\nversion: 2\nupdates:\n  # Maintain the workflow dependencies.\n  - package-ecosystem: 'github-actions'\n    directory: '/'\n    schedule:\n      interval: 'weekly'\n    reviewers:\n      - 'VIKTORVAV99'\n    ignore:\n      - dependency-name: '*'\n        update-types: ['version-update:semver-patch']\n\n  # Ensure ruff and tzdata is updated.\n  - package-ecosystem: 'pip'\n    directory: '/'\n    schedule:\n      interval: 'monthly'\n    allow:\n      - dependency-name: 'ruff'\n      - dependency-name: 'tzdata'\n    reviewers:\n      - 'VIKTORVAV99'\n\n  # Maintain the devcontainer dependencies.\n  - package-ecosystem: 'devcontainers'\n    directory: '/'\n    schedule:\n      interval: 'monthly'\n    reviewers:\n      - 'VIKTORVAV99'\n"
  },
  {
    "path": ".github/filter-groups.yml",
    "content": "workflows:\n  - '.github/workflows/**/*.yml'\n\nconfig:\n  - 'config/**/*.yaml'\n\nmarkdown:\n  - '**.md'\n\njson:\n  - '**.json'\n\npython:\n  - '**.py'\n  - 'pyproject.toml'\n  - 'uv.lock'\n  - '.python-version'\n"
  },
  {
    "path": ".github/labeler.yml",
    "content": "infrastructure:\n  - changed-files:\n      - any-glob-to-any-file:\n          ['.github/**/*', 'docker-compose.yml', 'parsers.dockerfile', '.dockerignore']\n\ndependencies:\n  - changed-files:\n      - any-glob-to-any-file: ['uv.lock', 'pyproject.toml']\n\ntests:\n  - changed-files:\n      - any-glob-to-any-file: ['tests/**/*', 'parsers/test/**/*']\n\njavascript:\n  - changed-files:\n      - any-glob-to-any-file: '**/*.js'\n\npython:\n  - changed-files:\n      - any-glob-to-any-file: '**/*.py'\n\nparser:\n  - all:\n      - changed-files:\n          - any-glob-to-any-file: 'parsers/**/*'\n          - all-globs-to-all-files: '!parsers/archive/**/*'\n\narchived parser:\n  - changed-files:\n      - any-glob-to-any-file: 'parsers/archive/**/*'\n\ncapacity parser:\n  - changed-files:\n      - any-glob-to-any-file: 'electricitymap/contrib/capacity_parsers/**/*'\n\nexchange config:\n  - changed-files:\n      - any-glob-to-any-file: 'config/exchanges/**/*.yaml'\n\nzone config:\n  - changed-files:\n      - any-glob-to-any-file: 'config/zones/**/*.yaml'\n"
  },
  {
    "path": ".github/pull_request_template.md",
    "content": "## Issue\n\n<!-- If you want to close an issue automatically when your PR is merged, write \"Closes X\" where X is the issue number. For example: Closes #000 -->\n\n## Description\n\n<!-- Explains the goal of this PR -->\n\n### Preview\n\n<!-- Please add screenshots and/or gif that shows visual changes (if applicable) -->\n\n### Double check\n\n- [ ] I have tested my parser changes locally with `uv run test_parser \"zone_key\"`\n- [ ] I have run `pnpx prettier@2 --write .` and `uv run format` in the top level directory to format my changes.\n"
  },
  {
    "path": ".github/workflows/CI.yml",
    "content": "name: CI\non:\n  push:\n    branches:\n      - master\n  pull_request:\n  schedule:\n    - cron: '0 7 * * 1'\n\njobs:\n  #                        #\n  # Repository wide checks #\n  #                        #\n  prettier:\n    name: Prettier\n    runs-on: ubuntu-24.04-arm\n    timeout-minutes: 5\n    steps:\n      - name: Checkout\n        uses: actions/checkout@v6\n      - name: Setup Node\n        uses: actions/setup-node@v6\n      - name: Prettier Check\n        run: |\n          npx -y prettier@2 --check .\n\n  earthly:\n    name: earthly\n    needs: [prettier]\n    uses: ./.github/workflows/earthly-contrib.yml\n    secrets: inherit\n\n  validate_local_links:\n    name: Validate\n    uses:\n      ./.github/workflows/validate_local_links_in_md.yml\n\n      # Python checks\n  python_formatting:\n    name: Python / Formatting\n    runs-on: ubuntu-24.04-arm\n    timeout-minutes: 5\n    steps:\n      - name: Checkout\n        uses: actions/checkout@v6\n      - name: Install uv\n        uses: astral-sh/setup-uv@v7\n        with:\n          enable-cache: true\n          cache-suffix: 'formatting'\n          python-version: '3.10'\n      - name: Install Dependencies\n        run: |\n          uv sync --extra parsers\n      - name: Check formatting\n        run: |\n          uv run ruff format . --check\n      - name: Check linting\n        run: |\n          uv run ruff check . --output-format=github\n\n  python_tests:\n    name: Python / Tests\n    runs-on: ubuntu-24.04-arm\n    timeout-minutes: 10\n    strategy:\n      matrix:\n        python-version: ['3.10', '3.11', '3.12']\n    steps:\n      - name: Checkout\n        uses: actions/checkout@v6\n      - name: Install uv\n        uses: astral-sh/setup-uv@v7\n        with:\n          enable-cache: true\n          cache-suffix: 'tests'\n          python-version: ${{ matrix.python-version }}\n      - name: Install libxml2-dev and tesseract-ocr\n        run: |\n          sudo apt-get update\n          sudo apt-get install libxml2-dev tesseract-ocr tesseract-ocr-eng\n      - name: Install Dependencies\n        run: |\n          uv sync --group dev --extra parsers\n      - name: Run tests\n        run: |\n          uv run test\n\n  # Config checks\n  validate_config_filenames:\n    name: Validate / Config filenames\n    runs-on: ubuntu-24.04-arm\n    timeout-minutes: 5\n    steps:\n      - name: Checkout\n        uses: actions/checkout@v6\n      - name: Validate config filenames\n        run: python scripts/validate_config_filenames.py\n\n  # Code quality checks\n  codeql:\n    needs: [prettier]\n    name: CodeQL\n    uses: ./.github/workflows/codeql.yml\n"
  },
  {
    "path": ".github/workflows/README.md",
    "content": "# CI\n\nAll CI workflows should be executed in the `CI.yml` workflow using reusable workflows and the workflow_call trigger.\n\nTo add another workflow to the CI workflow create a new job that looks like this:\n\n```yml\njob_example:\n  name: Example job\n  uses: ./.github/workflows/example.yml\n```\n"
  },
  {
    "path": ".github/workflows/codeql.yml",
    "content": "name: 'CodeQL'\n\non:\n  workflow_call:\n\njobs:\n  analyze:\n    name: Analyze\n    runs-on: ubuntu-24.04\n    permissions:\n      actions: read\n      contents: read\n      security-events: write\n\n    strategy:\n      fail-fast: false\n      matrix:\n        language: ['javascript', 'python', 'actions']\n        # CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python', 'ruby' ]\n        # Learn more about CodeQL language support at https://aka.ms/codeql-docs/language-support\n\n    steps:\n      - name: Checkout repository\n        uses: actions/checkout@v6\n\n      # Initializes the CodeQL tools for scanning.\n      - name: Initialize CodeQL\n        uses: github/codeql-action/init@v4\n        with:\n          languages: ${{ matrix.language }}\n          config-file: ./.github/codeql-config.yml\n          # If you wish to specify custom queries, you can do so here or in a config file.\n          # By default, queries listed here will override any specified in a config file.\n          # Prefix the list here with \"+\" to use these queries and those in the config file.\n          # Details on CodeQL's query packs refer to : https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs\n          # queries: security-extended,security-and-quality\n      - name: Perform CodeQL Analysis\n        uses: github/codeql-action/analyze@v4\n        with:\n          category: '/language:${{matrix.language}}'\n"
  },
  {
    "path": ".github/workflows/create-release.yml",
    "content": "name: Create release\non:\n  workflow_dispatch:\n    inputs:\n      package:\n        description: 'Package to release'\n        required: true\n        default: electricitymap-contrib\n        type: choice\n        options:\n          - electricitymap-contrib\n          - electricitymap-contrib-types\n      type:\n        description: 'Release type'\n        required: true\n        default: patch\n        type: choice\n        options:\n          - patch\n          - minor\n          - major\n          - dev\njobs:\n  create-release:\n    runs-on: ubuntu-latest\n    timeout-minutes: 10\n    # Add \"id-token\" with the intended permissions.\n    permissions:\n      contents: 'read'\n      id-token: 'write'\n    steps:\n      - name: Checkout\n        uses: actions/checkout@v6\n        with:\n          token: ${{ secrets.BOT_GITHUB_TOKEN }}\n      - name: Configure git\n        run: |\n          git config --global user.email \"engineering+github@electricitymaps.com\"\n          git config --global user.name \"electricitymapsbot\"\n      - uses: 'google-github-actions/auth@v3'\n        with:\n          project_id: 'tmrow-152415'\n          workload_identity_provider: 'projects/533362582499/locations/global/workloadIdentityPools/github/providers/electricitymaps-contrib'\n          service_account: contrib-registry-writer@tmrow-152415.iam.gserviceaccount.com\n      - name: 'Set up Cloud SDK'\n        uses: 'google-github-actions/setup-gcloud@v3'\n        with:\n          version: '>= 363.0.0'\n      - name: Install uv\n        uses: astral-sh/setup-uv@v7\n        with:\n          python-version: '3.10'\n      - name: Bump version\n        run: |\n          if [[ \"${{ inputs.type }}\" == \"dev\" ]]; then\n            # Bump patch first to ensure we are moving forward, then add dev suffix\n            # This handles 1.2.1 -> 1.2.2.dev0\n            uv version --bump patch --bump dev --package ${{ inputs.package }}\n          else\n            uv version --bump ${{ inputs.type }} --package ${{ inputs.package }}\n          fi\n      - name: Commit changes\n        run: |\n          git add .\n          git commit -m \"Bump ${{ inputs.package }} version\"\n      - name: Build package\n        run: |\n          uv build --package ${{ inputs.package }}\n      - name: Publish package\n        run: |\n          export ACCESS_TOKEN=$(gcloud auth print-access-token)\n          uv publish --publish-url https://europe-west1-python.pkg.dev/tmrow-152415/libs/ --username oauth2accesstoken --password \"$ACCESS_TOKEN\"\n      - name: Push changes\n        uses: ad-m/github-push-action@v1.1.0\n        with:\n          github_token: ${{ secrets.BOT_GITHUB_TOKEN }}\n          branch: ${{ github.ref_name }}\n"
  },
  {
    "path": ".github/workflows/earthly-contrib.yml",
    "content": "# Runs Earthly targets\n\nname: Earthly Contrib\n\non:\n  workflow_call:\n\njobs:\n  run-tests:\n    runs-on: ubuntu-24.04-arm\n    env:\n      EARTHLY_TOKEN: ${{ secrets.EARTHLY_TOKEN }}\n      DOCKERHUB_USERNAME: ${{ secrets.DOCKERHUB_USERNAME }}\n      DOCKERHUB_TOKEN: ${{ secrets.DOCKERHUB_TOKEN }}\n      FORCE_COLOR: 1\n    steps:\n      - uses: earthly/actions-setup@v1\n        with:\n          version: v0.8.15\n      - uses: actions/checkout@v6\n      - name: Put back the git branch into git (Earthly uses it for tagging)\n        run: |\n          branch=\"\"\n          if [ -n \"$GITHUB_HEAD_REF\" ]; then\n            branch=\"$GITHUB_HEAD_REF\"\n          else\n            branch=\"${GITHUB_REF##*/}\"\n          fi\n          git checkout -b \"$branch\" || true\n      - name: Docker Login\n        run: docker login --username \"$DOCKERHUB_USERNAME\" --password \"$DOCKERHUB_TOKEN\"\n      - name: Earthly version\n        run: earthly --version\n      - name: Run test\n        run: earthly --ci --secret ELECTRICITYMAP_PUBLIC_TOKEN=\"$ELECTRICITYMAP_PUBLIC_TOKEN\" --secret SENTRY_AUTH_TOKEN=\"$SENTRY_AUTH_TOKEN\" +test-all\n        env:\n          ELECTRICITYMAP_PUBLIC_TOKEN: 'test'\n          SENTRY_AUTH_TOKEN: ''\n"
  },
  {
    "path": ".github/workflows/label.yml",
    "content": "# This workflow will triage pull requests and apply a label based on the\n# paths that are modified in the pull request.\n#\n# To use this workflow, you will need to set up a .github/labeler.yml\n# file with configuration.  For more information, see:\n# https://github.com/actions/labeler/blob/master/README.md\n\nname: Labeler\non: [pull_request_target]\n\njobs:\n  label:\n    runs-on: ubuntu-24.04-arm\n\n    steps:\n      - uses: actions/labeler@v6\n        with:\n          repo-token: '${{ secrets.GITHUB_TOKEN }}'\n          sync-labels: false\n"
  },
  {
    "path": ".github/workflows/validate_local_links_in_md.yml",
    "content": "# Controls when the action will run. Triggers the workflow when called from another workflow.\non:\n  workflow_call:\n\n# A workflow run is made up of one or more jobs that can run sequentially or in parallel\njobs:\n  # This workflow contains a single job\n  check_broken_internal_links_in_md:\n    name: Markdown links\n    # The type of runner that the job will run on\n    runs-on: ubuntu-24.04\n\n    # Steps represent a sequence of tasks that will be executed as part of the job\n    steps:\n      # Checks-out your repository under $GITHUB_WORKSPACE, so your job can access it\n      - uses: actions/checkout@v6\n\n      # Runs a single command using the runners shell\n      # Install https://github.com/remarkjs/remark-validate-links\n      - name: Install remark-validate-links\n        timeout-minutes: 1\n        run: npm install remark-cli remark-validate-links\n\n      # Invoke remarks to validate INTERNAL links in md.\n      # --frail specifies to return a non-zero error code even on warning\n      # so the github action fails when a link is invalid\n      - name: Validate local links\n        timeout-minutes: 1\n        run: ./node_modules/.bin/remark --frail -u validate-links .\n"
  },
  {
    "path": ".gitignore",
    "content": "gha-creds-*.json\n*.pyc\n*.env\n**/node_modules\n.ipynb_checkpoints/\n*.pyproj\n*.sln\n*.suo\n*.user\n/.vs/config\n/App_Data/PublishProfiles\n*.publishproj\n.DS_Store\n/.vs\n/.venv\nThumbs.db\ndist\nparsers/.venv\n\n# Ignore top level vscode folder as it is symlinked\n#.vscode\n.vscode/launch.json\n\n## Pycharm IDE\n.idea\n"
  },
  {
    "path": ".pre-commit-config.yaml",
    "content": "repos:\n  - repo: https://github.com/astral-sh/ruff-pre-commit\n    # Ruff version.\n    rev: v0.11.2\n    hooks:\n      # Run the linter.\n      - id: ruff\n        args: [--fix]\n      # Run the formatter.\n      - id: ruff-format\n"
  },
  {
    "path": ".prettierignore",
    "content": "# Files and paths to ignore\n\n.prettierignore\npnpm-lock.yaml\n.earthlyignore\n\n.venv\n**/parsers/tests/mocks\n.pytest_cache/\n\n.github/ISSUE_TEMPLATE/\n\nLICENSE.md\nLICENSE\n\nnode_modules\n.DS_Store\n.eslintcache\ncoverage\n.nyc_output\ncypress/videos\ncypress/screenshots\n"
  },
  {
    "path": ".prettierrc.js",
    "content": "module.exports = {\n  semi: true,\n  singleQuote: true,\n  trailingComma: 'es5',\n  printWidth: 90,\n  overrides: [\n    {\n      files: '*.md',\n      options: {\n        printWidth: 90,\n      },\n    },\n    {\n      files: 'config/*.yaml',\n      options: {\n        printWidth: 120,\n      },\n    },\n  ],\n};\n"
  },
  {
    "path": ".python-version",
    "content": "3.10\n"
  },
  {
    "path": ".vscode/extensions.json",
    "content": "{\n  \"recommendations\": [\n    \"charliermarsh.ruff\",\n    \"ms-python.python\",\n    \"ms-python.vscode-pylance\",\n    \"esbenp.prettier-vscode\",\n    \"redhat.vscode-yaml\",\n    \"dbaeumer.vscode-eslint\",\n    \"bradlc.vscode-tailwindcss\"\n  ]\n}\n"
  },
  {
    "path": ".vscode/settings.json",
    "content": "{\n  \"editor.defaultFormatter\": \"esbenp.prettier-vscode\",\n  \"[python]\": {\n    \"editor.defaultFormatter\": \"charliermarsh.ruff\",\n    \"editor.formatOnSave\": true,\n    \"editor.codeActionsOnSave\": {\n      \"source.organizeImports\": \"explicit\"\n    }\n  },\n  \"python.testing.pytestArgs\": [\".\", \"--ignore\", \"electricitymap/contrib/parsers\"],\n  \"python.testing.unittestEnabled\": false,\n  \"python.testing.pytestEnabled\": true\n}\n"
  },
  {
    "path": "CODE_OF_CONDUCT.md",
    "content": "# Contributor Covenant Code of Conduct\n\n## Our Pledge\n\nWe as members, contributors, and leaders pledge to make participation in our\ncommunity a harassment-free experience for everyone, regardless of age, body\nsize, visible or invisible disability, ethnicity, sex characteristics, gender\nidentity and expression, level of experience, education, socio-economic status,\nnationality, personal appearance, race, caste, color, religion, or sexual\nidentity and orientation.\n\nWe pledge to act and interact in ways that contribute to an open, welcoming,\ndiverse, inclusive, and healthy community.\n\n## Our Standards\n\nExamples of behavior that contributes to a positive environment for our\ncommunity include:\n\n- Demonstrating empathy and kindness toward other people\n- Being respectful of differing opinions, viewpoints, and experiences\n- Giving and gracefully accepting constructive feedback\n- Accepting responsibility and apologizing to those affected by our mistakes,\n  and learning from the experience\n- Focusing on what is best not just for us as individuals, but for the overall\n  community\n\nExamples of unacceptable behavior include:\n\n- The use of sexualized language or imagery, and sexual attention or advances of\n  any kind\n- Trolling, insulting or derogatory comments, and personal or political attacks\n- Public or private harassment\n- Publishing others' private information, such as a physical or email address,\n  without their explicit permission\n- Other conduct which could reasonably be considered inappropriate in a\n  professional setting\n\n## Enforcement Responsibilities\n\nCommunity leaders are responsible for clarifying and enforcing our standards of\nacceptable behavior and will take appropriate and fair corrective action in\nresponse to any behavior that they deem inappropriate, threatening, offensive,\nor harmful.\n\nCommunity leaders have the right and responsibility to remove, edit, or reject\ncomments, commits, code, wiki edits, issues, and other contributions that are\nnot aligned to this Code of Conduct, and will communicate reasons for moderation\ndecisions when appropriate.\n\n## Scope\n\nThis Code of Conduct applies within all community spaces, and also applies when\nan individual is officially representing the community in public spaces.\nExamples of representing our community include using an official e-mail address,\nposting via an official social media account, or acting as an appointed\nrepresentative at an online or offline event.\n\n## Enforcement\n\nInstances of abusive, harassing, or otherwise unacceptable behavior may be\nreported to the community leaders responsible for enforcement at\ncodeofconduct@electricitymaps.com.\nAll complaints will be reviewed and investigated promptly and fairly.\n\nAll community leaders are obligated to respect the privacy and security of the\nreporter of any incident.\n\n## Enforcement Guidelines\n\nCommunity leaders will follow these Community Impact Guidelines in determining\nthe consequences for any action they deem in violation of this Code of Conduct:\n\n### 1. Correction\n\n**Community Impact**: Use of inappropriate language or other behavior deemed\nunprofessional or unwelcome in the community.\n\n**Consequence**: A private, written warning from community leaders, providing\nclarity around the nature of the violation and an explanation of why the\nbehavior was inappropriate. A public apology may be requested.\n\n### 2. Warning\n\n**Community Impact**: A violation through a single incident or series of\nactions.\n\n**Consequence**: A warning with consequences for continued behavior. No\ninteraction with the people involved, including unsolicited interaction with\nthose enforcing the Code of Conduct, for a specified period of time. This\nincludes avoiding interactions in community spaces as well as external channels\nlike social media. Violating these terms may lead to a temporary or permanent\nban.\n\n### 3. Temporary Ban\n\n**Community Impact**: A serious violation of community standards, including\nsustained inappropriate behavior.\n\n**Consequence**: A temporary ban from any sort of interaction or public\ncommunication with the community for a specified period of time. No public or\nprivate interaction with the people involved, including unsolicited interaction\nwith those enforcing the Code of Conduct, is allowed during this period.\nViolating these terms may lead to a permanent ban.\n\n### 4. Permanent Ban\n\n**Community Impact**: Demonstrating a pattern of violation of community\nstandards, including sustained inappropriate behavior, harassment of an\nindividual, or aggression toward or disparagement of classes of individuals.\n\n**Consequence**: A permanent ban from any sort of public interaction within the\ncommunity.\n\n## Attribution\n\nThis Code of Conduct is adapted from the [Contributor Covenant][homepage],\nversion 2.1, available at\n[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].\n\nCommunity Impact Guidelines were inspired by\n[Mozilla's code of conduct enforcement ladder][mozilla coc].\n\nFor answers to common questions about this code of conduct, see the FAQ at\n[https://www.contributor-covenant.org/faq][faq]. Translations are available at\n[https://www.contributor-covenant.org/translations][translations].\n\n[homepage]: https://www.contributor-covenant.org\n[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html\n[mozilla coc]: https://github.com/mozilla/diversity\n[faq]: https://www.contributor-covenant.org/faq\n[translations]: https://www.contributor-covenant.org/translations\n"
  },
  {
    "path": "CONTRIBUTING.md",
    "content": "# Welcome! 🎉\n\nWelcome to the Electricity Maps open source contribution repository. </br>\nAny and all contributions however big or small are welcome.\n\n# Links\n\n- [README][readme]\n- [Code of Conduct][code of conduct]\n- [License][license]\n- [Wiki][wiki]\n\n# Code of Conduct\n\nThis repository and by extension its community have adopted the [Contributor Covenant][contributor covenant] v2.1 as its code of conduct.\nIf you have any questions about the code of conduct or feel the need to report an incident you can do so by emailing us at codeofconduct@electricitymaps.com. For the full code of conduct see [CODE_OF_CONDUCT.md][code of conduct].\n\n# License\n\nWe use the GNU Affero General Public License v3.0 for this repository, check the [LICENSE.md][license] file details about what exactly this entails. Contributions prior to commit [cb9664f][commit cb9664f] where licensed under [MIT license][old_license]\n\n# Getting Started\n\n## Non-code contributions\n\nThere are several ways to help out without coding, these are primarily:\n\n- Opening issues for bugs.\n- Opening issues for data problems.\n- Opening and/or participating in discussions about new data sources, features, and more.\n- Opening issues when capacity data sources have been updated or changed.\n- Finding new data sources, wiki page: [Find data sources][wiki find data sources]\n- Verify existing data sources, wiki page: [Verify data sources][wiki verify data sources]\n- And more!\n\n> **Note**\n> Take a look at the wiki pages for more detailed instructions\n\n## Zone and exchange configurations\n\nStatic information about zones and exchanges are located at [config/zones][config zones] and [config/exchanges][config exchanges] respectively.\nThe zone configurations hold information such as the installed capacity, which parsers to use, fallback mixes, contributors and other keys that are required by our frontend and internal systems; and while similar the exchange configs hold the location, capacity, direction and parsers required.\n\n## Parser guidelines\n\nTo get started with editing the parsers use the following steps:\n\n1. Run `uv sync --extra parsers` to install all needed dependencies.\n2. Use `uv run test_parser ZONE_KEY` to test any parser changes.\n\nNote: This requires you to have [Python 3.10][python homepage] and [uv][uv homepage] installed, you can see their respective installation guides here:\n\n- [Downloading Python][python install guide]\n- [uv installation][uv install guide]\n\n### Parser information\n\nFor more detailed information about parsers specifically you can look at the parser [README][parser readme] located at [electricitymap/contrib/parsers/README.md][parser readme] with specific information about the parser functions located in the [electricitymap/contrib/parser/example][parser examples folder] folder\n\n#### Example parser:\n\nFor an example of how a parser can look we have an example here: </br> [electricitymap/contrib/parsers/examples/example_parser.py][example parser]\n\n### Formatting the parsers\n\nWe use [ruff][ruff homepage] as a code formatter for python which is automatically checked in the CI job `Python / Formatting`.\n\nIf this jobs fails and you need to manually format the code you can run `uv run format` in the top level of the repository.\n\nCheck the [wiki page][wiki python code formatting] for more details and tips.\n\n# Contribution lifecycle\n\nIn order for your PR to be accepted and deployed it will need to pass a series of checks, these checks will be defined and explained in the following section of this document.\n\n## Overview\n\n```mermaid\n%%{init: {\"flowchart\": {\"defaultRenderer\": \"elk\"}} }%%\nflowchart LR\n    subgraph idContrib[\"Electricity Maps contrib\"]\n    direction LR\n        id1((Open a PR))\n        id2{First time contributor?}\n        id3(Await EMaps team CI approval)\n        id4{Is the CI tests passing?}\n        id5(Make changes)\n        id6{Passing review from EMaps team member}\n        id7(PR is merged)\n        id8(Deployed to Staging)\n        id1-->id2\n        id2-->|Yes|id3\n        id2-->|No|id4\n        id3-->id4\n        id4-->|No|id5\n        id5-->id4\n        id4-->|Yes|id6\n        id6-->|No|id5\n        id6-->|Yes|id7\n        id7-->id8\n    end\n    subgraph idInternal[\"Electricity Maps internal\"]\n    direction LR\n        id9((Automatic PR created))\n        id10{Are internal CI tests passing}\n        id11(Make changes)\n        id12{Passing review from Emaps member?}\n        id13(Deployed to production)\n        id9-->id10\n        id10-->|No|id11\n        id11-->id10\n        id10-->|Yes|id12\n        id12-->|No|id11\n        id12-->|Yes|id13\n    end\n    id7-->id9\n```\n\n## Description\n\nIn order to do code changes to the Electricity Maps repository you need to fork the repo and make changes in your own fork and then open a pull request (PR) against the Electricity Maps repository.\n\nOnce this has been done the automatic and manual review process starts, this consists of manual approval of the CI pipeline if you are a first time contributor, if the CI pipeline passes a team member will review your specific code changes. If they pass all automated tests and manual review from a Electricity Maps Employee it will be merged in our contrib PR. This does not mean it will be automatically de deployed or that the changes will be instantly visible.\n\nIf there is parser changes these go on to more internal tests that includes both automated test suits and manual reviews. Once everything passes and an approval has been granted a new release will be created that updates the production environment for both the frontend and parser changes.\n\n<!-- Link definitions to keep the text clean -->\n\n[uv homepage]: https://github.com/astral-sh/uv\n[python homepage]: https://www.python.org/\n[python install guide]: https://wiki.python.org/moin/BeginnersGuide/Download\n[uv install guide]: https://docs.astral.sh/uv/getting-started/installation/\n[ruff homepage]: https://docs.astral.sh/ruff/\n[example parser]: https://github.com/electricitymaps/electricitymaps-contrib/blob/master/electricitymap/contrib/parsers/examples/example_parser.py\n[wiki python code formatting]: https://github.com/electricitymaps/electricitymaps-contrib/wiki/Format-your-code-contribution#python-code-formatting\n[readme]: https://github.com/electricitymaps/electricitymaps-contrib/blob/master/README.md\n[code of conduct]: https://github.com/electricitymaps/electricitymaps-contrib/blob/master/CODE_OF_CONDUCT.md\n[license]: https://github.com/electricitymaps/electricitymaps-contrib/blob/master/LICENSE.md\n[wiki]: https://github.com/electricitymaps/electricitymaps-contrib/wiki\n[wiki find data sources]: https://github.com/electricitymaps/electricitymaps-contrib/wiki/Find-data-sources\n[wiki verify data sources]: https://github.com/electricitymaps/electricitymaps-contrib/wiki/Verify-data-sources\n[contributor covenant]: https://www.contributor-covenant.org/\n[commit cb9664f]: https://github.com/electricitymaps/electricitymaps-contrib/commit/cb9664f43f0597bedf13e832047c3fc10e67ba4e\n[old_license]: https://github.com/electricitymaps/electricitymaps-contrib/blob/master/LICENSE_MIT.txt\n[config zones]: https://github.com/electricitymaps/electricitymaps-contrib/tree/master/config/zones\n[config exchanges]: https://github.com/electricitymaps/electricitymaps-contrib/tree/master/config/exchanges\n[parser readme]: https://github.com/electricitymaps/electricitymaps-contrib/tree/master/parsers/README.md\n[parser examples folder]: https://github.com/electricitymaps/electricitymaps-contrib/blob/master/electricitymap/contrib/parsers/examples/\n"
  },
  {
    "path": "DATA_SOURCES.md",
    "content": "## Data sources\n\n### Real-time electricity data sources\n\nReal-time electricity data is obtained using [parsers](https://github.com/electricitymaps/electricitymaps-contrib/tree/master/parsers).\n&nbsp;<details><summary>Click to see the full list of sources</summary>\n\n- Åland: [Kraftnät Åland](http://www.kraftnat.ax/text2.con?iPage=28&iLan=1)\n- Argentina: [Cammesa](http://portalweb.cammesa.com/Memnet1/default.aspx)\n- Armenia: [Armenian Energy Power System Operator](http://epso.am/poweren.htm)\n- Aruba: [WEB Aruba](https://www.webaruba.com/renewable-energy-dashboard/aruba) ([JSON](https://www.webaruba.com/renewable-energy-dashboard/app/rest/results.json))\n- Australia: [OpenNEM](https://opennem.org.au/energy/nem/)\n- Australia (King Island): [King Island Renewable Energy Integration Project (KIREIP)](https://data.ajenti.com.au/KIREIP/index.html)\n  ([CSV](http://wa.aemo.com.au/aemo/data/wa/infographic/facility-intervals-last96.csv))\n- Australia (Flinders Island): [Flinders Island Hybrid Energy Solution](https://www.hydro.com.au/clean-energy/hybrid-energy-solutions/success-stories/flinders-island)\n- Australia (Rottnest Island): [Rottnest Island Hybrid Energy Solution](https://www.hydro.com.au/clean-energy/hybrid-energy-solutions/success-stories/rottnest-island)\n- Austria: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Bahrain: [GCCIA](https://www.gccia.com.sa/)\n- Bangladesh: [PGCB](https://erp.pgcb.gov.bd/web/generations/view_generations)\n- Bosnia and Herzegovina: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Bolivia: [CNDC](http://www.cndc.bo/media/archivos/graf/gene_hora/gweb_despdia_genera.php)\n- Belgium: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Brazil: [ONS](http://www.ons.org.br/paginas/energia-agora/carga-e-geracao)\n- Bulgaria: [TSO](http://tso.bg/default.aspx/page-707/bg)\n- Canada:\n  - Alberta: [AESO](http://ets.aeso.ca/ets_web/ip/Market/Reports/CSDReportServlet)\n  - New Brunswick: [NB Power](https://tso.nbpower.com/Public/en/op/market/data.aspx)\n  - Nova Scotia: [Nova Scotia Power](https://www.nspower.ca/clean-energy/todays-energy-stats)\n  - Ontario: [IESO](http://www.ieso.ca/power-data)\n  - Québec: [Hydro-Québec](https://www.hydroquebec.com/residentiel/)\n  - Prince Edward Island: [Government of PEI](https://www.princeedwardisland.ca/en/feature/pei-wind-energy/)\n  - Saskatchewan: [Saskpower ](https://www.saskpower.com/Our-Power-Future/Our-Electricity/Electrical-System/Where-Your-Power-Comes-From)(daily avg)\n  - Yukon: [Yukon Energy](http://www.yukonenergy.ca/energy-in-yukon/electricity-101/current-energy-consumption)\n- Chile (SING/SIC): [Coordinador](https://sipub.coordinador.cl/api/v1/recursos/generacion_centrales_tecnologia_horario?)\n- Czech Republic: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Costa Rica: [ICE](https://apps.grupoice.com/CenceWeb/data/sen/json/EnergiaHorariaFuentePlanta?anno=2022&mes=12&dia=27)\n- Croatia (Exchanges): [HOPS](https://www.hops.hr/wps/portal/hr/web)\n- Cyprus: [TSO](https://tsoc.org.cy/electrical-system/total-daily-system-generation-on-the-transmission-system/)\n- Denmark: [TSO](https://www.energidataservice.dk/groups/production-and-consumption)\n- Dominican Republic: [OC](http://www.oc.org.do/Reportes/postdespacho.aspx)\n- Ecuador: [CENACE](https://www.cenace.gob.ec/info-operativa/InformacionOperativa.htm)\n- El Salvador: [Unidad de Transacciones](http://estadistico.ut.com.sv/OperacionDiaria.aspx)\n- Estonia: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Faroe Islands:\n  - Biomass: [Fjarhiti](https://www.fjarhiti.fo/kunning/biogassverki%C3%B0-roynist-vael-%C3%AD-fjarhitaskipanini/)\n  - Other: [SEV](https://www.sev.fo/framleidsla/el-orka-i-foroyum/)\n- Finland: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- France: [RTE](https://opendata.reseaux-energies.fr)\n- French Polynesia: [EDT](https://www.edt.pf/transition-energetique-innovation)\n- Germany: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Georgia: [Georgian State Electrosystem (GSE)](http://www.gse.com.ge/home)\n- Great Britain: [Elexon BMRS](https://bscdocs.elexon.co.uk/guidance-notes/bmrs-api-and-data-push-user-guide)\n- Greece: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Guatemala: [AMM](http://www.amm.org.gt)\n- Honduras: [ENTE](https://www.enteoperador.org/flujos-regionales-en-tiempo-real/)\n- Hungary: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Iceland: [LANDSNET](https://amper.landsnet.is/generation/api/Values)\n- Ireland: [Eirgrid](https://www.smartgriddashboard.com/)\n- Israel: [IEC](https://www.iec.co.il/en/pages/default.aspx)\n- Italy: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- India: [meritindia](http://meritindia.in/)\n- India: [Vidyut PRAVAH](https://vidyutpravah.in/)\n- India: [National Power Portal](https://npp.gov.in/dgrReports)\n- India: [Central Electricity Authority](https://cea.nic.in/daily-renewable-generation-report/?lang=en)\n- India (Andhra Pradesh): [CORE Dashboard](https://core.ap.gov.in/CMDashBoard/UserInterface/Power/PowerReport.aspx)\n- India (Chhattisgarh): [cspc.co.in](http://117.239.199.203/csptcl/GEN.aspx)\n- India (Delhi): [delhisldc](http://www.delhisldc.org/Redirect.aspx?Loc=0804)\n- India (Gujarat): [sldcguj](https://www.sldcguj.com/RealTimeData/RealTsimeDemand.php)\n- India (Himachal Pradesh): [HPSLDC](https://hpsldc.com/intra-state-power-transaction/)\n- India (Maharashtra) [mahasldc](https://mahasldc.in/wp-content/reports/sldc/mvrreport3.jpg)\n- India (Karnataka): [kptclsldc.in](http://kptclsldc.in/StateGen.aspx)\n- India (Punjab): [punjabsldc](http://www.punjabsldc.org/pungenrealw.asp?pg=pbGenReal)\n- India (Uttar Pradesh): [upsldc](http://www.upsldc.org/real-time-data)\n- India (Uttarakhand): [uksldc](http://uksldc.in/real-time-data.php)\n- Iraq: [Iraqi Power System](https://www.gdoco.org/generation.html)\n- Japan (Exchanges): [OCCTO](http://occtonet.occto.or.jp/public/dfw/RP11/OCCTO/SD/LOGIN_login)\n- Japan (Chūbu): [Chūden](http://denki-yoho.chuden.jp/)\n- Japan (Chūgoku): [Energia](http://www.energia.co.jp/jukyuu/)\n- Japan (Hokkaidō): [Hokuden](http://denkiyoho.hepco.co.jp/area_forecast.html)\n- Japan (Hokuriku): [Rikuden](http://www.rikuden.co.jp/denki-yoho/)\n- Japan (Kansai): [Kepco](http://www.kepco.co.jp/energy_supply/supply/denkiyoho/)\n- Japan (Kyūshū): [Kyūden](http://www.kyuden.co.jp/power_usages/pc.html)\n- Japan (Kyūshū/Genkai NPP): [Kyūden](http://www.kyuden.co.jp/php/nuclear/genkai/rename.php?A=g_power.fdat&B=ncp_state.fdat&_=1520532904073)\n- Japan (Kyūshū/Sendai NPP): [Kyūden](http://www.kyuden.co.jp/php/nuclear/sendai/rename.php?A=s_power.fdat&B=ncp_state.fdat&_=1520532401043)\n- Japan (Shikoku): [Yonden](http://www.yonden.co.jp/denkiyoho/)\n- Japan (Tōhoku-Niigata): [TH-EPCO](http://setsuden.tohoku-epco.co.jp/graph.html)\n- Japan (Tōkyō area): [TEPCO](http://www.tepco.co.jp/forecast/html/images/juyo-d1-j.csv)\n- Kosovo: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Kuwait (TSO): [Ministry of Electricity & Water](https://www.mew.gov.kw/en/)\n- Kuwait (Power Market): [GCCIA](https://www.gccia.com.sa/)\n- Latvia: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Lithuania: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Malaysia: [GSO](https://www.gso.org.my/LandingPage.aspx)\n- Moldova: [MoldElectrica](http://www.moldelectrica.md/ro/activity/system_state)\n- Montenegro: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Namibia: [NamPower](http://www.nampower.com.na/Scada.aspx)\n- Netherlands: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- New Zealand:\n  - [Transpower](https://www.transpower.co.nz/power-system-live-data)\n  - [Siesa](https://www.southlanddc.govt.nz/my-southland/siesa-2/what-sieasa-does/)\n  - [Energy Market Services](https://em6live.co.nz)\n- Nicaragua: [CNDC](http://www.cndc.org.ni/)\n- Nigeria: [TCN ISO grid data portal](https://www.niggrid.com/GenerationProfile)\n- Northern Ireland: [Eirgrid](https://www.smartgriddashboard.com/)\n- Norway: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Oman: [GCCIA](https://www.gccia.com.sa/)\n- Panama: [CND](http://sitr.cnd.com.pa/m/pub/gen.html)\n- Peru: [COES](http://www.coes.org.pe/Portal/portalinformacion/Generacion)\n- Poland: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Portugal: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Qatar: [GCCIA](https://www.gccia.com.sa/)\n- Romania: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Russia: [SO-UPS](http://br.so-ups.ru/Public/MainPageData/BR/PowerGeneration.aspx)\n- Serbia: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Singapore: [EMC](https://www.emcsg.com)\n- Singapore (Solar): [EMA](https://www.ema.gov.sg/solarmap.aspx)\n- Slovakia: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Slovenia: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- South Africa: [Eskom](https://www.eskom.co.za/dataportal/supply-side/station-build-up-for-the-last-7-days/)\n- South Korea (Nuclear): [KHNP](http://cms.khnp.co.kr/eng/kori/realTimeMgr/list.do?mnCd=EN03020201&brnchCd=BR0302)\n- South Korea (Hydro): [KHNP](http://cms.khnp.co.kr/eng/realTimeMgr/water.do?mnCd=EN040203)\n- South Korea (Load): [KPX](http://power.kpx.or.kr/powerinfo_en.php)\n- Spain: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Spain (Balearic Islands): [REE](https://demanda.ree.es/movil)\n- Spain (Canary Islands): [REE](https://demanda.ree.es/movil)\n- Spain (Ceuta): [REE](https://demanda.ree.es/visiona/sistema/ceuta5m/)\n- Spain (Melilla): [REE](https://demanda.ree.es/visiona/sistema/melilla5m/)\n- Sweden: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Saudi Arabia: [GCCIA](https://www.gccia.com.sa/)\n- Sri Lanka: [Ceylon Electricity Board](https://cebcare.ceb.lk/gensum/details)\n- Switzerland: [ENTSOE](https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html)\n- Taiwan: [TAIPOWER](http://www.taipower.com.tw/d006/loadGraph/loadGraph/genshx_.html)\n- Thailand: [EGAT](https://www.sothailand.com/sysgen/egat/)\n- Turkey: [ytbs](https://ytbsbilgi.teias.gov.tr/ytbsbilgi/frm_istatistikler.jsf)\n- Ukraine: [UKRENERGO](https://ua.energy/activity/dispatch-information/ues-operation/)\n- United Arab Emirates: [GCCIA](https://www.gccia.com.sa/)\n- United States of America\n  - Federal: [EIA](https://www.eia.gov/electricity/data.cfm#gencapacity)\n  - Alaska (Southeast Alaska Power Agency): [SEAPA](https://seapahydro.org/scada)\n  - California (US-CAL-CISO): [CAISO](http://www.caiso.com/Pages/default.aspx)\n  - Hawaii, Oahu Island (US-HI-OA): [Islandpulse](https://www.islandpulse.org/)\n  - New England (US-NE-ISNE): [NEISO](https://www.iso-ne.com/isoexpress/)\n  - New York (US-NY-NYIS): [NYISO](https://www.nyiso.com/real-time-dashboard)\n  - PJM (US-MIDA-PJM): [PJM](http://www.pjm.com/markets-and-operations.aspx)\n  - Puerto Rico (PR): [AEEPR](https://aeepr.com/#/operacion)\n  - Southwest Power Pool (US-CENT-SWPP): [SPP](https://portal.spp.org/integrated-marketplace)\n- Uruguay: [UTE](https://apps.ute.com.uy/SgePublico/ConsPotenciaGeneracionArbolXFuente.aspx)\n- Vietnam: [EVN](https://www.nldc.evn.vn/)\n  &nbsp;</details>\n\n### Production capacity data sources\n\nProduction capacities are centralized in the [config/zones](https://github.com/electricitymaps/electricitymaps-contrib/tree/master/config/zones) folder. Capacities are included in the respective zone configurations. Values in the `capacity` maps are in MW.\n\n#### International sources\n\nWhen determining the installed capacity for a country, these sources might help you get started. Note that if you end up using one of these sources, it _also_ needs to be listed with the country/region.\n\n- Renewables: [IRENA](https://www.irena.org/Search?keywords=%22Renewable+Capacity+Statistics%22&sort=date&content_type=2803e86c173c440f840aa721825b3656)\n- Nuclear: [IAEA PRIS](https://pris.iaea.org/PRIS/WorldStatistics/OperationalReactorsByCountry.aspx)\n- Coal: [Global Coal Plant Tracker](https://globalenergymonitor.org/projects/global-coal-plant-tracker/tracker/)\n- Gas: [Global Gas Plant Tracker](https://globalenergymonitor.org/projects/global-gas-plant-tracker/tracker-map/)\n- Various:\n  - [Climatescope](https://global-climatescope.org/capacity-generation)\n  - [Global Power Plant Database](https://datasets.wri.org/dataset/globalpowerplantdatabase)\n\nFor many European countries, data is available from [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n\n#### Sources by region\n\n<details><summary>Click to see the full list of sources</summary>\n\n- Åland\n  - Wind: [Finnish Wind Power Association](https://tuulivoimayhdistys.fi/en/wind-power-in-finland/map 'Note: the map states 43MW for the Långnabba project, but as [Vestas](https://www.vestas.com/en/media/company-news/2020/vestas-develops-highly-customised-power-plant-solution--c3249491) and [Kraftnat](https://kraftnat.ax/) state 42MW, the lower figure was used')\n  - Solar: [Ålands statistik- och utredningsbyrå](https://www.asub.ax/sv/ekologisk-hallbarhet-17-installerad-kapacitet-elproduktion-solpaneler-pa-aland)\n  - Oil: [Kraftnät Åland](https://kraftnat.ax/stamnatet/)\n- Albania:\n  - Biomass: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Other: [ERE](https://ere.gov.al/images/2022/04/Raporti%20Vjetor%202021%20perfundimtare.pdf)\n- Andorra: [FEDA](https://www.feda.ad/sobre-feda/memories-i-documents-oficials/memoria-de-sostenibilitat-2013)\n- Argentina: [Cammesa](https://cammesaweb.cammesa.com/informe-sintesis-mensual/)\n- Armenia\n  - Biomass, Hydro, Solar, Wind: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Nuclear, Gas: [wikipedia.org](https://en.wikipedia.org/wiki/List_of_power_stations_in_Armenia)\n- Aruba: [WEB Aruba](https://www.webaruba.com/energy-production/power-production-figures)\n- Australia\n  - Other: [OpenNEM](https://opennem.org.au/facilities/all/)\n  - Solar: [APVI](https://pv-map.apvi.org.au/historical)\n- Austria\n  - Wind: [IGWindKraft](https://www.igwindkraft.at)\n  - Other: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Bahrain: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n- Bangladesh: [BPDB](https://bpdb.portal.gov.bd/sites/default/files/files/bpdb.portal.gov.bd/annual_reports/7b792f67_bf50_4b3d_9bef_8f9b568005c9/2022-11-29-05-22-0dea17e09d8a84e72a63312df6b5bdc6.pdf)\n- Belarus: [belstat.gov.by](http://www.belstat.gov.by/upload/iblock/7f7/7f70938f51eb9e49abc4a6e62f831a2c.rar), [RenEn](http://director.by/zhurnal/arkhiv-zhurnala/arkhiv-nomerov-2017/375-7-2017-iyul-2017/5456-zelenaya-energetika-nabiraet-oboroty)\n- Belgium\n  - Nuclear: [IAEA](https://pris.iaea.org/PRIS/CountryStatistics/CountryDetails.aspx?current=BE)\n  - Nuclear: [FANC](https://afcn.fgov.be/fr/actualites/doel-3-arret-en-toute-surete)\n  - Solar: [ELIA](https://www.elia.be/en/grid-data/power-generation/solar-pv-power-generation-data)\n  - Hydro: [ELIA](https://www.elia.be/-/media/project/elia/shared/documents/elia-group/publications-pdfs/20200414_elia_annual-report-sustainability_en.pdf)\n  - Wind: [ELIA](https://www.elia.be/en/grid-data/power-generation/wind-power-generation)\n  - Battery: [ELIA](https://www.elia.be/en/publications/reports)\n  - Other: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Bolivia: [CNDC](http://www.cndc.bo/agentes/generacion.php)\n- Bosnia and Herzegovina: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Brazil: [ONS](http://www.ons.org.br/Paginas/resultados-da-operacao/historico-da-operacao/capacidade_instalada.aspx)\n- Bulgaria:\n  - Hydro: [NEK](https://nek.bg/index.php/en/our-business/electricity-generation)\n  - Other: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Canada (British Columbia, New Brunswick, Newfoundland and Labrador, Nova Scotia, Prince Edward Island):\n  [wikipedia.org](https://en.wikipedia.org/wiki/List_of_generating_stations_in_Canada)\n- Canada (Alberta): [AESO](http://ets.aeso.ca/ets_web/ip/Market/Reports/CSDReportServlet),\n  [wikipedia.org](https://en.wikipedia.org/wiki/List_of_generating_stations_in_Alberta)\n- Canada (Manitoba)\n  - Hydro & Gas: [Manitoba Hydro-Electric Board](https://www.hydro.mb.ca/corporate/ar/pdf/annual_report_2020_21.pdf), [Manitoba Hydro](https://www.hydro.mb.ca/corporate/facilities/generating_stations/#selkirk)\n  - Wind: [Province of Manitoba](https://gov.mb.ca/sd/environment_and_biodiversity/energy/wind/windfarms.html)\n- Canada (Ontario): [IESO](http://www.ieso.ca/en/Power-Data/Supply-Overview/Transmission-Connected-Generation)\n- Canada (Québec): [Hydro-Québec](https://www.hydroquebec.com/generation/generating-stations.html)\n- Canada (Saskatchewan): [SaskPower](https://www.saskpower.com/Our-Power-Future)\n- Canada (Yukon)\n  - Hydro: [YukonEnergy](https://yukonenergy.ca/energy-in-yukon/projects-facilities)\n- Chile (SEN, SEA, SEM): [energiaabierta.cl](http://energiaabierta.cl/visualizaciones/capacidad-instalada/)\n- Chile (Easter Island): [SASIPA](https://www.sasipa.cl/estado-del-suministro)\n- Croatia: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Costa Rica: [ICE](https://www.grupoice.com/wps/wcm/connect/579dfc1f-5156-41e0-807d-d6808f65d718/Fasciculo_Electricidad_2020_ingl%C3%A9s_compressed.pdf?MOD=AJPERES&CVID=m.pGzcp)\n- Cyprus:\n  - Renewable: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Other: [TSO](https://tsoc.org.cy/electrical-system/total-daily-system-generation-on-the-transmission-system/)\n- Czech Republic: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Denmark (DK1 and DK2):\n  - [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n  - [energidataservice.dk](https://energidataservice.dk/tso-electricity/capacitypermunicipality)\n- Dominican Republic:\n  - 2020 Data: [OC](https://www.dropbox.com/sh/8dec0z1ftf2nqr0/AAAbDG-6lSttxBprxhPRNkjaa/2020?dl=0&preview=OC-2020-000190-GG-SIE-INFORME+ANUAL+2019+V1.pdf&subfolder_nav_tracking=1)\n  - Other: [Climatescope](http://global-climatescope.org/en/country/dominican-republic/#/details)\n- El Salvador:\n  - Thermal: [CNE](http://estadisticas.cne.gob.sv/wp-content/uploads/2016/09/Plan_indicativo_2016_2026-1.pdf)\n  - Renewables: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n- Estonia: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Faroe Islands: [Johan Pauli Magnussen's Thesis, p44](https://setur.fo/uploads/tx_userpubrep/BScThesis_JohanPauliMagnussen.pdf)\n- Finland:\n  - Nuclear: [IAEA](https://pris.iaea.org/PRIS/CountryStatistics/CountryDetails.aspx?current=FI)\n  - Renewables: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Wind: [Fingrid](https://data.fingrid.fi/en/dataset/total-wind-production-capacity)\n  - Solar: [Fingrid](https://data.fingrid.fi/en/dataset/total-solar-production-capacity)\n  - Other: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- France:\n  - Geothermal: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Hydro storage [RTE](https://opendata.reseaux-energies.fr/explore/dataset/registre-national-installation-production-stockage-electricite-agrege/analyze/?disjunctive.epci&disjunctive.departement&disjunctive.region&disjunctive.filiere&disjunctive.combustible&disjunctive.combustiblessecondaires&disjunctive.technologie&disjunctive.regime&disjunctive.gestionnaire&sort=-puismaxcharge&refine.filiere=Hydraulique&refine.regime=En+service&refine.technologie=Pompage+turbinage&dataChart=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%3D%3D)\n  - Hydro [RTE](https://opendata.reseaux-energies.fr/explore/dataset/registre-national-installation-production-stockage-electricite-agrege/analyze/?disjunctive.epci&disjunctive.departement&disjunctive.region&disjunctive.filiere&disjunctive.combustible&disjunctive.combustiblessecondaires&disjunctive.technologie&disjunctive.regime&disjunctive.gestionnaire&sort=-puismaxcharge&refine.filiere=Hydraulique&refine.regime=En+service&refine.technologie=Lac&refine.technologie=Fil+de+l%27eau&refine.technologie=Autre&refine.technologie=Eclus%C3%A9e&refine.technologie=Hydrolien+fluvial&dataChart=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%3D)\n  - Coal, nuclear, solar, wind: [RTE](https://www.rte-france.com/eco2mix/les-chiffres-cles-de-lelectricite)\n  - Battery [CRE.FR](https://www.cre.fr/content/download/21318/271898)\n  - Other: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show?)\n- French Polynesia:\n  - Hydro & Solar: [service-public.pf](https://www.service-public.pf/sde/wp-content/uploads/sites/15/2021/02/BEPF-2019-VF_online_mail_light_compressed.pdf)\n  - Thermal: [service-public.pf](https://www.service-public.pf/sde/documentation-2/rapports-delegataires)\n- Germany:\n  - Nuclear: [IAEA](https://pris.iaea.org/PRIS/CountryStatistics/CountryDetails.aspx?current=DE)\n  - Nuclear: [BASE](https://www.base.bund.de/EN/ns/nuclear-phase-out/nuclear-phase-out_node.html)\n  - Geothermal and Unknown: [Bundesnetzagentur](https://www.bundesnetzagentur.de/DE/Sachgebiete/ElektrizitaetundGas/Unternehmen_Institutionen/Versorgungssicherheit/Erzeugungskapazitaeten/Kraftwerksliste/kraftwerksliste-node.html)\n  - Other: [Frauenhofer ISE](https://energy-charts.info/charts/installed_power/chart.htm)\n- Georgia: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Great Britain: [Elexon BMRS](https://www.bmreports.com/bmrs/?q=foregeneration/capacityaggregated)\n- Greece: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Guatemala: [AMM](http://www.amm.org.gt/pdfs2/2017/Capacidad_Instalada_2017.xls)\n- Honduras: [ENEE](http://www.enee.hn/planificacion/2018/boletines/Boletin%20Estadistico%20Mes%20de%20Septiembre%202018%20PDF.pdf)\n- Hong Kong: [CLP](https://www.clp.com.hk/en/about-clp/power-generation)\n- Hungary:\n  - Biomass: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n  - Solar: [MAVIR](https://www.mavir.hu/documents/10258/255200887/PV+STATISZTIKA_HU_20231231_ig_v2.pdf)\n  - Other: [MAVIR](https://www.mavir.hu/web/mavir/energia-mix-eromuvi-beepitett-teljesitokepesseg-adatok)\n- Iceland\n  - Oil: [Statistics Iceland](http://px.hagstofa.is/pxen/pxweb/en/Atvinnuvegir/Atvinnuvegir__orkumal/IDN02101.px)\n  - Geothermal, Wind and Hydro: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n- Ireland\n  - Non-Renewable: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n  - Renewable: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n- Indonesia\n  - Renewable: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Non-Renewable [ESDM](https://www.esdm.go.id/assets/media/content/content-laporan-kinerja-ditjen-ketenagalistrikan-2020.pdf)\n- Israel\n  - [Irena](https://pxweb.irena.org/pxweb/en/IRENASTAT)\n  - [GEM](https://globalenergymonitor.org/projects/global-gas-plant-tracker/tracker-map/)\n- Italy\n  - Coal and Oil: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedCapacityPerProductionUnit/show)\n  - Other: [Terna](https://www.terna.it/it/sistema-elettrico/statistiche/pubblicazioni-statistiche)\n- India:\n  - Renewable: [MRE](https://mnre.gov.in/img/documents/uploads/file_s-1683779844352.pdf)\n  - Non-Renewable: [NPP](https://npp.gov.in/publishedReports)\n  - (Punjab): [PUNJABSLDC](http://www.punjabsldc.org/realtimepbGen.aspx)\n  - (Tamil Nadu): [tnebsldc](https://tnebsldc.org/reports1/peakdet.pdf)\n- Japan:\n  - Tokyo: [Power-Plants](http://agora.ex.nii.ac.jp/earthquake/201103-eastjapan/energy/electrical-japan/operator/3.html.ja)\n  - Kyūshū: [TSO - Kyuden](https://www.kyuden.co.jp/library/pdf/en/ir/integratedreport/2022/en_integratedreport_2022.pdf)\n  - Tohoku\n    - Wind: [The Wind Power](https://www.thewindpower.net/country_zones_en_11_japan.php)\n  - Hokkaidō\n    - Wind: [TSO - HEPCO](https://www.hepco.co.jp/english/environment/renewable_energy.html)\n    - Hydro [TSO - HEPCO](https://www.hepco.co.jp/english/ir/datadownloads.html)\n    - Hydro storage [TSO - HEPCO](https://wwwc.hepco.co.jp/hepcowwwsite/english/ir/pdf/hepco_group_report_2022.pdf)\n    - Oil & coal & gas: [TSO - HEPCO](https://www.hepco.co.jp/english/ir/datadownloads.html)\n    - Nuclear: [TSO - HEPCO](https://www.hepco.co.jp/english/ir/datadownloads.html)\n    - Solar: [TSO - HEPCO](https://www.hepco.co.jp/english/environment/renewable_energy.html)\n    - Biomass: [TSO - HEPCO](https://www.hepco.co.jp/english/environment/renewable_energy.html)\n    - Geothermal: [TSO - HEPCO](https://wwwc.hepco.co.jp/hepcowwwsite/english/ir/pdf/hepco_group_report_2022.pdf)\n  - Hokuriku\n    - Hydro, coal, oil, gas, nuclear & solar: [TSO - Rikuden](https://www.rikuden.co.jp/csr/attach/integratedreport2021EN.pdf)\n    - Wind: [The Wind Power](https://www.thewindpower.net/developer_en_1636_hokuriku-electric-power-group.php)\n    - Biomass: [Global Energy Monitor](https://www.gem.wiki/Tsuruga_power_station)\n  - Chūbu\n    - Biomass, hydro storage & geothermal: [TSO - Chuden](https://www.chuden.co.jp/english/energy/renewable/initiatives/)\n    - Hydro & Nuclear: [TSO - Chuden](https://www.chuden.co.jp/english/corporate/outline/)\n    - Solar & Wind: [TSO - Chuden](https://www.chuden.co.jp/english/resource/corporate/ecsr_report_2022_all.pdf)\n    - Coal & gas & oil: [Power Plants](https://en.wikipedia.org/wiki/Chubu_Electric_Power)\n  - Chūgoku\n    - Nuclear, hydro & hydro storage: [TSO - Energia](https://www.energia.co.jp/e/business/int_business/skills/renewable-energy.html)\n    - Solar: [Sonnedix](https://sonnedix.jp/power-plants/list-of-plants/)\n    - Wind: [The Wind Power](https://www.thewindpower.net/country_zones_en_11_japan.php)\n    - Coal, gas & oil: [TSO - Energia](https://www.energia.co.jp/e/business/int_business/skills/thermal-pg.html)\n  - Shikoku\n    - Wind: [The Wind Power](https://www.thewindpower.net/country_zones_en_11_japan.php)\n    - Hydro & Nuclear: [TSO - Yonden](https://www.yonden.co.jp/english/profile/profile.html)\n    - Hydro storage, coal, oil & gas: [TSO - Yonden](https://www.yonden.co.jp/english/assets/pdf/ir/tools/ann_r/annual_e_2022.pdf)\n    - Biomass: [Global Energy Monitor](https://www.gem.wiki/Saijo_power_station)\n    - Solar: [ISEP](https://www.isep.or.jp/en/411/)\n  - Okinawa\n    - Wind: [The Wind Power](https://www.thewindpower.net/zones_en_11_985.php)\n    - Coal, oil & gas: [TSO - Okiden](https://www.okiden.co.jp/shared/pdf/ir/ar/ar2021/oepc_ar21_00.pdf)\n    - Biomass: [Erex](https://www.erex.co.jp/en/business/power-generation/plant/)\n- Kosovo: [TSO](https://www.kostt.com/Content/ViewFiles/Transparency/BasicMarketDataOnGeneration/EN/Installed%20capacity%20of%20production%20units.pdf)\n- Kuwait\n  - Gas & oil: [KAPSARC](https://datasource.kapsarc.org/api/datasets/1.0/kuwait-power-plants-database/attachments/power_plants_xlsx/)\n  - Solar & wind: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n- Latvia: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Lithuania:\n  - Solar & Wind: [Litgrid](https://www.litgrid.eu/index.php/power-system/power-system-information/generation-capacity/546)\n  - Other: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Luxembourg:\n  - Hydro Storage: [Société Electrique de L'Our](http://www.seo.lu/fr/Activites-principales/PSW-Vianden/Installations/Donnees-techniques)\n  - Other: [Institut luxembourgeois de régulation](https://data.public.lu/fr/datasets/la-production-denergie-electrique-au-luxembourg-1/)\n- Malaysia: [GSO](https://www.gso.org.my/SystemData/PowerStation.aspx)\n- Moldova\n  - Renewable: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Gas (CET-1 & CET-2 Chişinău): [Termoelectrica](https://www.termoelectrica.md/ro_RO/despre/informatii-tehnice/)\n  - Gas (CET-Nord): [CET-Nord](https://www.cet-nord.md/en/transparent/tep)\n  - Gas and coal (CERS Moldovenească): [MOLDGRES](http://moldgres.com/o-predpriyatii/equipment)\n  - Summary as permanent document (slightly outdated): [FAS](<http://en.fas.gov.ru/upload/other/National%20Agency%20for%20Energy%20Regulation%20(G.%20Pyrzy).pdf>)\n- Montenegro: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Morocco: [ONEE](http://www.one.org.ma/FR/pdf/Depliant%20Statistiques%20FR%202019.pdf)\n- Nagorno-Karabakh: [Artsakh HEK](http://artsakhhek.am/?lang=en)\n- Namibia\n  - Coal & Oil: [NamPower](http://www.nampower.com.na/Page.aspx?p=182)\n  - Hydro, solar & wind: [African Energy](https://www.africa-energy.com/database)\n- Nepal\n  - List of PowerStations: [PowerStations](https://en.wikipedia.org/wiki/List_of_power_stations_in_Nepal)\n  - GIS Map of Reservoir Projects: [GIS_Reservoir](https://www.doed.gov.np/download/GIS-map-of-reservoir-projects.pdf)\n- Netherlands:\n  - Solar and wind : [CBS](https://www.cbs.nl/nl-nl/cijfers/detail/82610NED)\n  - Biomass, Hydro, Wind: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Other : [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Nicaragua: [INE](https://www.ine.gob.ni/index.php/electricidad/estadisticas-anuales)\n- Nigeria\n  - [USAID](https://www.usaid.gov/powerafrica/nigeria)\n  - [TCN ISO grid data portal](https://www.niggrid.org)\n- North Macedonia: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Norway:\n  - Solar: [NVE Excel report](https://www.nve.no/media/13861/oversikt-over-solcelleanlegg-i-norge_2021.xlsx)\n  - Other: [NVE](https://www.nve.no/energiforsyning/kraftproduksjon/?ref=mainmenu)\n- Northern Ireland\n  - Thermal capacity, battery storage: [Connections Register, April 2022](https://www.soni.ltd.uk/media/documents/20220414-Connections-Register-14-April-2022.pdf)\n  - Renewables, smaller scale generation: [All-Island Generation Capacity Statement 2022-2031](https://www.soni.ltd.uk/media/documents/EirGrid_SONI_2022_Generation_Capacity_Statement_2022-2031.pdf)\n  - Coal Retirement: [BBC](https://web.archive.org/web/20231004055500/https://www.bbc.com/news/uk-northern-ireland-66957611)\n- Oman: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n- Panama:\n  - Renewables: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Oil, Gas and Coal: [CND](http://www.cnd.com.pa/index.php/estadisticas)\n  - Biomass: [Secretaría de Energía de Panamá](http://www.energia.gob.pa/mercado-energetico/?tag=84#documents-list)\n- Peru: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n- Philippines: [Philippine Department of Energy](https://www.doe.gov.ph/sites/default/files/pdf/electric_power/04_LVM-Grid-Summary-June-2023-updated.pdf)\n- Poland: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Portugal:\n  - Biomass, Hydro, Solar, Wind, Gas: [REN](https://datahub.ren.pt/en/electricity/monthly-balance/)\n  - Other: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Puerto Rico: [EIA](https://www.eia.gov/electricity/data/eia860M/)\n- Qatar: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n- Romania:\n  - Latest: [Transelectrica](https://www.transelectrica.ro/documents/10179/45096/7productie23.xls/235f8702-9890-4109-9403-36c7fa59ce16)\n  - Other: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- Russia: [Minenergo](https://minenergo.gov.ru/node/532)\n- Serbia: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show?)\n- Singapore\n  - Solar: [Energy Market Authority](https://www.ema.gov.sg/consumer-information/solar/solar-irradiance-map)\n  - Other: [Energy Market Authority](https://www.ema.gov.sg/statistic.aspx?sta_sid=20140730XofavKNX5Ti7)\n- Slovakia:\n  - Nuclear: [IAEA](https://pris.iaea.org/PRIS/CountryStatistics/CountryDetails.aspx?current=SK)\n  - Renewables: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n  - Other: [SEPS](https://www.sepsas.sk/media/4951/rocenka-sed-2020.pdf)\n- Slovenia: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)\n- South Africa:\n  - [Eskom](https://www.eskom.co.za/wp-content/uploads/2021/08/2021IntegratedReport.pdf)\n- South Korea:\n  - Nuclear: [IAEA](https://pris.iaea.org/PRIS/CountryStatistics/CountryDetails.aspx?current=KR)\n  - [KHNP](http://cms.khnp.co.kr/content/163/main.do?mnCd=FN05040101)\n  - [EPSIS](http://epsis.kpx.or.kr/epsisnew/selectEkpoBftChart.do?menuId=020100)\n- Spain\n  - Geothermal, Oil: [ENTSO-E](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show?)\n  - Other: [REE](https://www.ree.es/es/datos/generacion/potencia-instalada)\n- Spain (Balearic Islands)\n  - Coal: [wikipedia.org](https://es.wikipedia.org/wiki/Central_t%C3%A9rmica_de_Es_Murterar)\n  - Wind, Solar: [REE](http://www.ree.es/sites/default/files/11_PUBLICACIONES/Documentos/Renovables-2016-v3.pdf)\n- Spain (Canary Islands)\n  - Hydro storage: [goronadelviento.es](http://www.goronadelviento.es/)\n  - Wind, Solar: [REE](http://www.ree.es/sites/default/files/11_PUBLICACIONES/Documentos/Renovables-2016-v3.pdf)\n- Spain (Ceuta): [REE](https://www.ree.es/es/datos/generacion/potencia-instalada)\n- Spain (Melilla): [REE](https://www.ree.es/es/datos/generacion/potencia-instalada)\n- Sri Lanka: [Ceylon Electricity Board](https://ceb.lk/front_img/img_reports/1636539187LTGEP_2022-2041_Web_compressed.pdf 'Renewable installed capacity taken from Figure 1.13 (private-owned) and Table 2.1 (government-owned hydro), except for biomass, where the higher figure mentioned in the section \"5.4 Other Renewable Energy Development\" was used. Together, these add up to within 1 MW of the stated total renewable capacity of 2,447 MW (which is mentioned in e.g. \"1.4.2.1 Overview\"). Solar includes rooftop solar.  Thermal capactity taken from \"2.2 Thermal Generation\". Thermal Electricity generation is only from coal and oil, see Figure 1.14. According to [\"CEB - ANNUAL REPORT 2020\" page 18 (20 in PDF)](https://ceb.lk/front_img/img_reports/164887150703-CEB-Annual_Report-2020-English.pdf), the 900MW Lakvijaya plant is the only coal plant in Sri Lanka, implying the others are oil-fired. Installed capacity figures do not add up exactly to the 2,168 MW mentioned in the opening paragraph; I went with the combined total nameplate capacity from Table 2.5 (government-owned) and Table 2.6 (private-owned), adding up to 2197.9 MW. Then I put 900MW under coal and categorized the remainder as oil.  Pumped hydro is mentioned as being planned/investigated in several places, but currently isn\\'t deployed. The same goes for battery storage.  Sri Lanka has no nuclear power plants. A report has been commissioned to investigate the possibility, see 4.2 (v).')\n- Sweden: [SVK](https://www.svk.se/siteassets/om-oss/rapporter/2023/kraftbalansen-pa-den-svenska-elmarknaden-rapport-2023.pdf)\n- Switzerland\n  - Hydro: [BEF](https://www.bfe.admin.ch/bfe/de/home/versorgung/statistik-und-geodaten/geoinformation/geodaten/wasser/statistik-der-wasserkraftanlagen.html)\n  - Other: [UVEK](https://www.uvek-gis.admin.ch/BFE/storymaps/EE_Elektrizitaetsproduktionsanlagen/)\n- Taiwan\n  - Renewable: [TAIPOWER](https://www.taipower.com.tw/en/page.aspx?mid=4495)\n  - Other: [TAIPOWER](https://www.taipower.com.tw/en/page.aspx?mid=4488&cid=2793&cchk=4ce0ae20-8549-4207-b5e2-2f0919e749bf)\n- Thailand:\n  - EGAT's production capacity: [EGAT](https://www.egat.co.th/home/statistics-all-egat/)\n  - EGAT's purchase capacity: [EGAT](https://www.egat.co.th/home/statistics-all-3rdparty/)\n- Turkey: [TEIAS](https://www.teias.gov.tr/tr-TR/kurulu-guc-raporlari)\n- Ukraine: [UKRENERGO](https://ua.energy/vstanovlena-potuzhnist-energosystemy-ukrayiny/)\n- United Arab Emirates: [IRENA](https://www.irena.org/publications/2022/Apr/Renewable-Capacity-Statistics-2022)\n- United States of America\n  - Federal: [EIA](https://www.eia.gov/electricity/data.cfm#gencapacity)\n  - Balancing Authorities: [EIA](https://www.eia.gov/electricity/data/eia860M/)\n  - States:\n    - [EIA](https://www.eia.gov/electricity/data/state/)\n    - [EIA](https://www.eia.gov/electricity/data/eia860M/)\n  - BPA: [BPA](https://transmission.bpa.gov/business/operations/Wind/baltwg.aspx)\n  - CAISO\n    - CEC: [CEC](https://www.energy.ca.gov/data-reports/energy-almanac/california-electricity-data/electric-generation-capacity-and-energy)\n    - Renewables: [CAISO](http://www.caiso.com/informed/Pages/CleanGrid/default.aspx)\n    - Nuclear: [wikipedia.org](https://en.wikipedia.org/wiki/Diablo_Canyon_Power_Plant)\n  - Florida TECO (US-FLA-TEC)\n    - Coal: [Github|electricitymaps-contrib|PR#5297](https://github.com/electricitymaps/electricitymaps-contrib/pull/5297)\n  - Hawaii\n    - Battery storage: [Kapolei Energy Storage Project](https://www.kapoleienergystorage.com/)\n    - Coal: [The Guardian: Hawaii to close its only coal power plant in a step toward renewable energy](https://web.archive.org/web/20220902132250/https://www.theguardian.com/us-news/2022/aug/31/hawaii-close-coal-power-plant-renewable-energy)\n    - Other: [EIA](https://www.eia.gov/electricity/data/eia860M/)\n  - NYISO: [NYISO Gold Book](https://www.nyiso.com/documents/20142/2226333/2021-Gold-Book-Final-Public.pdf)\n  - PJM: [PJM](https://www.pjm.com/-/media/markets-ops/ops-analysis/capacity-by-fuel-type-2022.ashx)\n  - PNM\n    - Coal: [Github|electricitymaps-contrib|PR#4614](https://github.com/electricitymaps/electricitymaps-contrib/pull/4614)\n    - EIA: [EIA](https://www.eia.gov/electricity/data/eia860M/)\n  - Southern Company Services, Inc:\n    - Nuclear: Capacity [EIA](https://www.eia.gov/electricity/data/eia860m/)\n  - SPP: [SPP](https://www.spp.org/about-us/fast-facts/)\n- Uruguay: [UTE](https://portal.ute.com.uy/institucional/infraestructura/fuentes-de-generacion)\n- Vietnam: [EVN](https://www.nldc.evn.vn/FullNewsg/100/Thong-tin-thi-truong-dien/default.aspx)\n  &nbsp;</details>\n\n### Cross-border transmission capacity data sources\n\nCross-border transmission capacities between the zones are centralized in the [config/exchanges](https://github.com/electricitymaps/electricitymaps-contrib/tree/master/config/exchanges) folder. Capacities are included in the respective exchange configurations. Values in the `capacity` maps are in MW. The value prefaced with `-` is the export capacity and the value not prefaced is the import capacity. Direction is determined by alphabetical sorting of the zone keys.\n\n#### For the nordic and baltic countries capacities are available from [Nord Pool](https://www.nordpoolgroup.com/en/Market-data1/Dayahead/Capacities1/Capacities/key1/hourly/?view=table)\n\n<details><summary>Click to see the full list of sources</summary>\n\n- Åland ⇄ Sweden: [\"Sverigekabeln\": 80 MW](https://kraftnat.ax/stamnatet/)\n- Åland ⇄ Finland: [\"Gustavskablen\": 10 MW + \"ÅL-Link\": 100 MW](https://kraftnat.ax/stamnatet/)\n- Albania ⇄ Greece: [533 MW](https://ec.europa.eu/energy/sites/ener/files/documents/2nd_report_ic_with_neighbouring_countries_b5.pdf)\n- Andorra ⇄ Spain: [125 MW](https://www.ree.es/sites/default/files/publication/2022/05/downloadable/inf_sis_elec_ree_2020_0EN_0.pdf)\n- Australia (New South Wales) ⇄ Australia (Queensland) [\"QNI\": 700MW (NSW -> QLD) 1200MW (QLD -> NSW)](https://en.wikipedia.org/wiki/Queensland_%E2%80%93_New_South_Wales_Interconnector) and [\"N-Q-MNSP1\": 180MW](https://www.aemo.com.au/-/media/Files/Electricity/NEM/Security_and_Reliability/Congestion-Information/2017/Interconnector-Capabilities.pdf)\n- Australia (Victoria) ⇄ Australia (New South Wales) [\"VIC1-NSW1\": 1600MW (VIC -> NSW) 1350MW (NSW -> VIC)](https://www.aemo.com.au/-/media/Files/Electricity/NEM/Security_and_Reliability/Congestion-Information/2017/Interconnector-Capabilities.pdf) and [\"VNI\": 170MW](https://www.transgrid.com.au/what-we-do/projects/current-projects/Victoria%20to%20NSW%20Interconnector)\n- Australia (Victoria) ⇄ Australia (South Australia) [\"Heywood interconnector\": 650 MW](https://en.wikipedia.org/wiki/Heywood_interconnector) and [\"Murraylink\": 220MW](https://en.wikipedia.org/wiki/Murraylink)\n- Australia (Victoria) ⇄ Australia (Tasmania): [\"Basslink\": 500 MW (regular) or 630 MW (temporarily)](https://en.wikipedia.org/wiki/Basslink)\n- Belgium ⇄ Germany [\"Alegro\": 1000MW](https://www.elia.be/en/infrastructure-and-projects/infrastructure-projects/alegro?clang=en)\n- [Bosnia and Herzegovina ⇄ Croatia](https://op.europa.eu/en/publication-detail/-/publication/785f224b-93cd-11e9-9369-01aa75ed71a1/language-en?WT.mc_id=Searchresult&WT.ria_c=37085&WT.ria_f=3608&WT.ria_ev=sea)\n- Bulgaria ⇄ Greece: [700 MW](https://ibex.bg/markets/dam/cross-zonal-capacities/)\n- Bulgaria ⇄ North Macedonia [950 MW](https://ec.europa.eu/energy/sites/ener/files/documents/2nd_report_ic_with_neighbouring_countries_b5.pdf)\n- Bulgaria ⇄ Turkey [2485 MW](https://ec.europa.eu/energy/sites/ener/files/documents/2nd_report_ic_with_neighbouring_countries_b5.pdf)\n- Canada (Alberta) ⇄ Canada (British Columbia): [\"Path 1\": 1000 MW (CA-AB -> CA-BC) 800 MW (CA-BC -> CA-AB)](https://www.aeso.ca/assets/Information-Documents/2011-001R-ATC-and-Transfer-Path-Management.pdf)\n- Canada (Alberta) ⇄ Canada (Saskatchewan): [\"Path 2\": 153 MW](https://www.aeso.ca/assets/Information-Documents/2011-001R-ATC-and-Transfer-Path-Management.pdf)\n- Canada (Alberta) ⇄ United States of America (NorthWestern Energy): [\"Path 83\": 315 MW (CA-AB -> US-NW-NWMT) 310 MW (US-NW-NWMT -> CA-AB)](https://www.aeso.ca/assets/Information-Documents/2011-001R-ATC-and-Transfer-Path-Management.pdf)\n- [Denmark (West) ⇄ Norway](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Denmark (East) ⇄ Denmark (West)](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Denmark (East) ⇄ Germany](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Denmark (West) ⇄ Sweden](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Denmark (West) ⇄ Netherlands](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- Estonia ⇄ European Russia And Ural [2464 MW](https://ec.europa.eu/energy/sites/ener/files/documents/2nd_report_ic_with_neighbouring_countries_b5.pdf)\n- [Estonia ⇄ Finland](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- Finland ⇄ Norway: [\"Joint operation between the Norwegian and Finnish subsystems, Appendix 3 to SOA Annex OS (FI and NO)\": 120 MW (NO4 -> FI) 100 MW (FI -> NO4)](https://www.fingrid.fi/globalassets/dokumentit/fi/kantaverkko/sahkonsiirto/appendix-1-8-to-soa-annex-os.pdf)\n- Georgia ⇄ Turkey: [\"Black Sea Transmission Network Project (BSTN)\": 700 MW](http://www.gse.com.ge/M9Ltvi2EQCCNYg7LvHW0JQ.html 'Two additional connections are planned/under construction, Batumi-Muratli and Akhalstikhe-Tortum, to double capacity to 1400MW; see http://www.gse.com.ge/sw/static/file/TYNDP_GE-2020-2030_ENG.pdf. Another interconnector (Batumi-Khopa) is only used in emergencies, according to http://www.gse.com.ge/about-us/international-affairs')\n- [Germany ⇄ Sweden](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Germany ⇄ Norway](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- Great Britain ⇄ Belgium: [\"Nemo Link\": 1000 MW](https://en.wikipedia.org/wiki/Nemo_Link)\n- Great Britain ⇄ North Ireland: [\"Moyle\": 500 MW](http://www.wikiwand.com/en/HVDC_Moyle)\n- [Great Britain ⇄ Norway](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- Great Britain ⇄ Ireland: [\"East-West Interconnector\": 500 MW](https://en.wikipedia.org/wiki/East%E2%80%93West_Interconnector)\n- Great Britain ⇄ Ireland: [\"Greenlink Interconnector\": 500 MW](https://en.wikipedia.org/wiki/Greenlink)\n- Great Britain ⇄ France: [\"Cross-Channel\": 2000 MW](https://en.wikipedia.org/wiki/HVDC_Cross-Channel), [\"ElecLink\": 1000 MW](https://www.getlinkgroup.com/en/our-group/eleclink/) & [\"IFA2\": 1000 MW](https://en.wikipedia.org/wiki/IFA-2)\n- Great Britain ⇄ Netherlands: [\"BritNed\": 1000 MW](https://en.wikipedia.org/wiki/BritNed)\n- Greece ⇄ Italy: [\"GRITA\": 500 MW](https://en.wikipedia.org/wiki/HVDC_Italy%E2%80%93Greece)\n- Greece ⇄ Turkey: [1900 MW](https://ec.europa.eu/energy/sites/ener/files/documents/2nd_report_ic_with_neighbouring_countries_b5.pdf)\n- Italy Central South ⇄ Italy Sardinia: [\"SAPEI\": 1000 MW](https://en.wikipedia.org/wiki/SAPEI)\n- Japan-Chūbu ⇄ Japan-Tōkyō: [3x HVDC interconnectors between 60Hz/50Hz areas: 1200 MW](https://www.jepic.or.jp/pub/pdf/epijJepic2019.pdf)\n- Japan-Hokkaidō ⇄ Japan-Tōhoku: [\"HVDC Hokkaidō–Honshū\": 900 MW](https://ja.wikipedia.org/wiki/%E5%8C%97%E6%B5%B7%E9%81%93%E3%83%BB%E6%9C%AC%E5%B7%9E%E9%96%93%E9%80%A3%E7%B3%BB%E8%A8%AD%E5%82%99)\n- [Latvia ⇄ Estonia](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Latvia ⇄ European Russia And Ural](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Latvia ⇄ Lithuania](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Lithuania ⇄ Sweden](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Lithuania ⇄ Poland](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Lithuania ⇄ Russia Kaliningrad](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- Malta ⇄ Italy Sicily: [\"Malta–Sicily-Interconnector\": 200 MW](https://en.wikipedia.org/wiki/Malta%E2%80%93Sicily_interconnector)\n- Montenegro ⇄ Italy Central South: [\"MONITA\": 600MW](https://tyndp.entsoe.eu/tyndp2018/projects/projects/28)\n- [Norway ⇄ Netherlands](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- New Zealand (North Island) ⇄ New Zealand (South Island): [\"HVDC Inter-Island\": 1200 MW](https://en.wikipedia.org/wiki/HVDC_Inter-Island)\n- [North Macedonia ⇄ Greece](https://op.europa.eu/en/publication-detail/-/publication/785f224b-93cd-11e9-9369-01aa75ed71a1/language-en?WT.mc_id=Searchresult&WT.ria_c=37085&WT.ria_f=3608&WT.ria_ev=sea)\n- [Russia ⇄ Finland](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- [Serbia ⇄ Bulgaria](https://op.europa.eu/en/publication-detail/-/publication/785f224b-93cd-11e9-9369-01aa75ed71a1/language-en?WT.mc_id=Searchresult&WT.ria_c=37085&WT.ria_f=3608&WT.ria_ev=sea)\n- [Slovakia ⇄ Ukraine](https://op.europa.eu/en/publication-detail/-/publication/785f224b-93cd-11e9-9369-01aa75ed71a1/language-en?WT.mc_id=Searchresult&WT.ria_c=37085&WT.ria_f=3608&WT.ria_ev=sea)\n- Spain ⇄ France: [According to \"The Spanish electricity system 2019\" page 65: 2800 MW](https://www.ree.es/sites/default/files/11_PUBLICACIONES/Documentos/InformesSistemaElectrico/2019/ISE_2019_eng.pdf)\n- [Spain ⇄ Portugal](https://web.archive.org/web/20230516184334/https://www.erse.pt/media/kevnjc3r/portugal-spain-interconnection-analysis-and-maczt-monitoring-report-english-version-2020.pdf)\n- Spain ⇄ Spain (Balearic Islands): [\"Cometa\": 400 MW](<https://en.wikipedia.org/wiki/Cometa_(HVDC)>)\n- Spain (Mallorca) ⇄ Spain (Ibiza): [\"Romulo 2\": 200 MW](https://web.archive.org/web/20230329093513/https://www.ree.es/sites/default/files/01_ACTIVIDADES/Documentos/Romulo2_en.pdf)\n- Spain (Mallorca) ⇄ Spain (Menorca): According to [\"REE PLAN 2021-2026\"](https://web.archive.org/web/20230629182722/https://www.planificacionelectrica.es/sites/webplani/files/2022-12/REE_PLAN_DESARROLLO_EN.pdf) (Page 466, only one built yet): 100 MW\n- Spain (Ibiza) ⇄ Spain (Formentera): According to [\"REE PLAN 2021-2026\"](https://web.archive.org/web/20230629182722/https://www.planificacionelectrica.es/sites/webplani/files/2022-12/REE_PLAN_DESARROLLO_EN.pdf) (Pages 466, Page 297): 134 MW (11+17+106)\n- [Sweden ⇄ Poland](#for-the-nordic-and-baltic-countries-capacities-are-available-from-nord-pool)\n- Ukraine ⇄ Belarus, ⇄ Hungary, ⇉ Poland, ⇄ Moldova, ⇄ Slovakia, ⇄ Romania, ⇄ Russia: [Ukrenergo](https://ua.energy/activity/dispatch-information/transborder-flows/)\n\nA ⇄ B: bidirectional operation, with power flow either \"from A to B\" or \"from B to A\"\n\nA ⇉ B: unidirectional operation, only with power flow \"from A to B\"\n&nbsp;</details>\n\n### Electricity prices (day-ahead) data sources\n\n- France: [RTE](https://www.rte-france.com/en/eco2mix/market-data)\n- Japan: [JEPX](http://www.jepx.jp)\n- Nicaragua: [CNDC](http://www.cndc.org.ni/)\n- Singapore: [EMC](https://www.emcsg.com)\n- Turkey: [EPIAS](https://seffaflik.epias.com.tr/transparency/piyasalar/gop/ptf.xhtml)\n- Other: [ENTSO-E](https://transparency.entsoe.eu/transmission-domain/r2/dayAheadPrices/show)\n\n### Real-time weather data sources\n\nWe use the [US National Weather Service's Global Forecast System (GFS)](http://nomads.ncep.noaa.gov/)'s GFS 0.25 Degree Hourly data.\nForecasts are made every 6 hours, with a 1 hour time step.\nThe values extracted are wind speed and direction at 10m altitude, and ground solar irradiance (DSWRF - Downward Short-Wave Radiation Flux), which takes into account cloud coverage.\nIn order to obtain an estimate of those values at current time, an interpolation is made between two forecasts (the one at the beginning of the hour, and the one at the end of the hour).\n\n### Topology data\n\nWe use the [Natural Earth Data Cultural Vectors](http://www.naturalearthdata.com/downloads/10m-cultural-vectors/) country subdivisions (map admin subunits).\n"
  },
  {
    "path": "EMISSION_FACTORS_SOURCES.md",
    "content": "# Emission factors sources\n\nThe emission factors used by Electricity Maps depends on the specific region.\n\nOur default emission factors come from the [IPCC (2014) Fith Assessment Report](https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7) report, and are fully described in our [wiki](https://github.com/electricitymaps/electricitymaps-contrib/wiki/Default-emission-factors).\n\nFor certain areas and zones (all of Europe and US, along with a few other countries), we have more specific emission factors.\nThe actual numbers used (as well as a link to the source) can be found in the [config/zones YAML file](https://github.com/electricitymaps/electricitymaps-contrib/tree/master/config/zones) for each specific zone.\n\nFor Europe, the methodology for calculating emission factors is detailed in our [wiki page for EU emission factors](https://github.com/electricitymaps/electricitymaps-contrib/wiki/EU-emission-factors). The same applies for [US emission factors](https://github.com/electricitymaps/electricitymaps-contrib/wiki/US-emission-factors).\n"
  },
  {
    "path": "Earthfile",
    "content": "VERSION 0.8\nFROM astral/uv:python3.10-bookworm-slim\nWORKDIR /contrib\n\nlinting-files:\n  COPY .prettierignore .\n  SAVE ARTIFACT .\n\nparser-files:\n  COPY electricitymap/contrib/parsers ./parsers\n  COPY electricitymap/contrib/capacity_parsers ./capacity_parsers\n  SAVE ARTIFACT *\n\nsrc-files:\n  COPY electricitymap/contrib/config ./electricitymap/contrib/config\n  COPY electricitymap/contrib/lib ./electricitymap/contrib/lib\n  COPY electricitymap/contrib/py.typed ./electricitymap/contrib/py.typed\n  COPY libs/types ./libs/types\n  COPY ./config+src-files/* ./config\n  COPY scripts ./scripts\n  COPY __init__.py ./__init__.py\n  COPY pyproject.toml .\n  SAVE ARTIFACT .\n\nsrc-files-with-parsers:\n  COPY +src-files/* .\n  COPY +parser-files/parsers ./electricitymap/contrib/parsers\n  COPY +parser-files/capacity_parsers ./electricitymap/contrib/capacity_parsers\n  SAVE ARTIFACT .\n\napi-files:\n  COPY geo/world.geojson ./geo/world.geojson\n  COPY config/zone_names.json ./config/zone_names.json\n  SAVE ARTIFACT .\n\nuv-lock:\n  COPY uv.lock .\n  SAVE ARTIFACT .\n\nprepare:\n  FROM +src-files-with-parsers\n  RUN apt-get update && apt-get install -y python3-opencv tesseract-ocr tesseract-ocr-jpn tesseract-ocr-eng libgl1\n  COPY uv.lock .\n  RUN uv sync --frozen --group dev --extra parsers --compile-bytecode\n\nbuild:\n  FROM +prepare\n\ntest:\n  FROM +build\n  COPY tests ./tests\n  COPY geo/world.geojson ./geo/world.geojson\n  RUN uv run check\n\n# includes both test target and build target here to make sure both can work\n# we can split into two later if required\ntest-all:\n  BUILD +build\n  BUILD +test\n  BUILD ./config+test\n"
  },
  {
    "path": "LICENSE.md",
    "content": "                    GNU AFFERO GENERAL PUBLIC LICENSE\n                       Version 3, 19 November 2007\n\n Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>\n Everyone is permitted to copy and distribute verbatim copies\n of this license document, but changing it is not allowed.\n\n                            Preamble\n\n  The GNU Affero General Public License is a free, copyleft license for\nsoftware and other kinds of works, specifically designed to ensure\ncooperation with the community in the case of network server software.\n\n  The licenses for most software and other practical works are designed\nto take away your freedom to share and change the works.  By contrast,\nour General Public Licenses are intended to guarantee your freedom to\nshare and change all versions of a program--to make sure it remains free\nsoftware for all its users.\n\n  When we speak of free software, we are referring to freedom, not\nprice.  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Interpretation of Sections 15 and 16.\n\n  If the disclaimer of warranty and limitation of liability provided\nabove cannot be given local legal effect according to their terms,\nreviewing courts shall apply local law that most closely approximates\nan absolute waiver of all civil liability in connection with the\nProgram, unless a warranty or assumption of liability accompanies a\ncopy of the Program in return for a fee.\n\n                     END OF TERMS AND CONDITIONS\n\n            How to Apply These Terms to Your New Programs\n\n  If you develop a new program, and you want it to be of the greatest\npossible use to the public, the best way to achieve this is to make it\nfree software which everyone can redistribute and change under these terms.\n\n  To do so, attach the following notices to the program.  It is safest\nto attach them to the start of each source file to most effectively\nstate the exclusion of warranty; and each file should have at least\nthe \"copyright\" line and a pointer to where the full notice is found.\n\n    <one line to give the program's name and a brief idea of what it does.>\n    Copyright (C) <year>  <name of author>\n\n    This program is free software: you can redistribute it and/or modify\n    it under the terms of the GNU Affero General Public License as published\n    by the Free Software Foundation, either version 3 of the License, or\n    (at your option) any later version.\n\n    This program is distributed in the hope that it will be useful,\n    but WITHOUT ANY WARRANTY; without even the implied warranty of\n    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n    GNU Affero General Public License for more details.\n\n    You should have received a copy of the GNU Affero General Public License\n    along with this program.  If not, see <https://www.gnu.org/licenses/>.\n\nAlso add information on how to contact you by electronic and paper mail.\n\n  If your software can interact with users remotely through a computer\nnetwork, you should also make sure that it provides a way for users to\nget its source.  For example, if your program is a web application, its\ninterface could display a \"Source\" link that leads users to an archive\nof the code.  There are many ways you could offer source, and different\nsolutions will be better for different programs; see section 13 for the\nspecific requirements.\n\n  You should also get your employer (if you work as a programmer) or school,\nif any, to sign a \"copyright disclaimer\" for the program, if necessary.\nFor more information on this, and how to apply and follow the GNU AGPL, see\n<https://www.gnu.org/licenses/>.\n"
  },
  {
    "path": "LICENSE_MIT.txt",
    "content": "MIT License\r\n\r\nCopyright (c) Jan 2020 - Jan 2023 Tomorrow\r\n\r\nPermission is hereby granted, free of charge, to any person obtaining a copy\r\nof this software and associated documentation files (the \"Software\"), to deal\r\nin the Software without restriction, including without limitation the rights\r\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\r\ncopies of the Software, and to permit persons to whom the Software is\r\nfurnished to do so, subject to the following conditions:\r\n\r\nThe above copyright notice and this permission notice shall be included in all\r\ncopies or substantial portions of the Software.\r\n\r\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\r\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\r\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\r\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\r\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\r\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\r\nSOFTWARE.\r\n"
  },
  {
    "path": "README.md",
    "content": "<p align=\"center\">\n  <a href=\"https://app.electricitymaps.com\">\n    <picture>\n      <source\n        srcset=\"https://raw.githubusercontent.com/electricitymaps/electricitymaps-contrib/master/.github/images/electricity-maps-logo-dark.svg\"\n        media=\"(prefers-color-scheme: dark)\"/>\n      <img\n        alt=\"Electricity Maps\"\n        src=\"https://raw.githubusercontent.com/electricitymaps/electricitymaps-contrib/master/.github/images/electricity-maps-logo.svg\"\n        width=\"100\"/>\n    </picture>\n  </a>\n</p>\n<h1 align=\"center\">\n  Electricity Maps\n</h1>\n\n<p align=\"center\">\nA collection of parsers to collect and standardize electricity data such as production, exchanges and price from across the globe.<br>\n  <strong><a href=\"https://app.electricitymaps.com\">app.electricitymaps.com »</a></strong>\n</p>\n\n<p align=\"center\">\n  <img alt=\"GitHub last commit\" src=\"https://img.shields.io/github/last-commit/electricitymaps/electricitymaps-contrib\"/>\n    <a href=\"https://github.com/electricitymaps/electricitymaps-contrib/blob/master/LICENSE.md\">\n    <img src=\"https://img.shields.io/github/license/electricitymaps/electricitymaps-contrib\" alt=\"Electricity Maps is released under the GNU-AGPLv3 license.\" /></a>\n</p>\n\n![image](.github/images/electricity-maps-banner.png#gh-light-mode-only)\n![image](.github/images/electricity-maps-banner-dark.png#gh-dark-mode-only)\n\n## Introduction\n\nThis project aims to provide a free, open-source, and transparent way to collect electricity data.\n\nWe fetch the raw data from public, free, and official sources. They include official government and transmission system operators' data. This data powers the [Electricity Maps platform](https://electricitymaps.com), which includes [our flow-tracing algorithm](https://www.electricitymaps.com/blog/flow-tracing), estimation models, forecast engine and much more.\n\n_View it online [app.electricitymaps.com](https://app.electricitymaps.com), or download the app on [Google Play](https://play.google.com/store/apps/details?id=com.tmrow.electricitymap&utm_source=github) or the [App store](https://itunes.apple.com/us/app/electricity-map/id1224594248&utm_source=github)._\n\n## Contributing\n\nElectricity Maps collection of parsers is a community project and we welcome contributions from anyone!\n\nWe are always looking for help to build parsers for new countries, fix broken parsers, improve accuracy of data sources, discuss new potential data sources, update region capacities, and much more.\n\nRead our [contribution guidelines](/CONTRIBUTING.md) to get started.\n\n## Community & Support\n\nUse these channels to be part of the community, ask for help while using Electricity Maps, or just learn more about what's going on:\n\n- [GitHub Issues](https://github.com/electricitymaps/electricitymaps-contrib/issues): Raise any issues you encounter with the data or bugs you find while using the app.\n- [GitHub Discussions](https://github.com/electricitymaps/electricitymaps-contrib/discussions): Join discussions and share new ideas for features.\n- [GitHub Wiki](https://github.com/electricitymaps/electricitymaps-contrib/wiki): Guides on setting up the development environment, etc.\n- [Our Commercial Website](https://electricitymaps.com/): Learn more about how you or your company can use the data too.\n- [Twitter](https://twitter.com/electricitymaps): Follow for latest news\n- [LinkedIn](https://www.linkedin.com/company/electricitymaps): Follow for latest news\n\n## License\n\nThis repository is licensed under GNU-AGPLv3 since v1.5.0, find our license [here](https://github.com/electricitymaps/electricitymaps-contrib/blob/master/LICENSE.md). Contributions prior to commit [cb9664f](https://github.com/electricitymaps/electricitymaps-contrib/commit/cb9664f43f0597bedf13e832047c3fc10e67ba4e) were licensed under [MIT license](https://github.com/electricitymaps/electricitymaps-contrib/blob/master/LICENSE_MIT.txt)\n\n## Frequently asked questions\n\n**Where does the data come from?**\nThe data comes from many different sources. But we strive to only use official sources from goverments, TSOs, producers and online OpenData platforms when avaiable.\n\n**Why do you calculate the carbon intensity of _consumption_?**\nIn short, citizens should not be responsible for the emissions associated with all the products they export, but only for what they consume.\nConsumption-based accounting (CBA) is a very important aspect of climate policy and allows assigning responsibility to consumers instead of producers.\nFurthermore, this method is robust to governments relocating dirty production to neighboring countries in order to green their image while still importing from it.\nYou can read more in our blog post [here](https://electricitymaps.com/blog/flow-tracing/).\n\n**Why don't you show emissions per capita?**\nA country that has few inhabitants but a lot of factories will appear high on CO<sub>2</sub>/capita.\nThis means you can \"trick\" the numbers by moving your factory abroad and import the produced _good_ instead of the electricity itself.\nThat country now has a low CO<sub>2</sub>/capita number because we only count CO<sub>2</sub> for electricity (not for imported/exported goods).\nThe CO<sub>2</sub>/capita metric, by involving the size of the population, and by not integrating all CO<sub>2</sub> emission sources, is thus an incomplete metric.\nCO<sub>2</sub> intensity on the other hand only describes where is the best place to put that factory (and when it is best to use electricity), enabling proper decisions.\n\n**CO<sub>2</sub> emission factors look high — what do they cover exactly?**\nThe carbon intensity of each type of power plant takes into account emissions arising from the whole life cycle of the plant (construction, fuel production, operational emissions and decommissioning). Read more on the [Emissions Factor methodology section](https://www.electricitymaps.com/data/methodology#vi-precision-in-emissions-factors).\n\n**How can I get access to the API?**\nAll this and more can be found **[here](https://electricitymaps.com/)**.\nYou can also visit our **[data portal](https://www.electricitymaps.com/data-portal)** to download historical datasets.\n\n**Is the map frontend open source?**\nIn the past, the map frontend was open source, but we have since rewritten the app completely and moved it to our own platform in order to expand the available features and provide a consistent user experience across our product offerings.\n"
  },
  {
    "path": "__init__.py",
    "content": ""
  },
  {
    "path": "capacity_update.py",
    "content": "\"\"\"\nUsage: uv run update_capacity --zone FR --target_datetime \"2022-01-01\"\n\"\"\"\n\nimport logging\nfrom datetime import datetime\n\nimport click\nfrom requests import Session\n\nfrom electricitymap.contrib.types import ZoneKey\nfrom scripts.update_capacity_configuration import update_source, update_zone\nfrom scripts.utils import ROOT_PATH, run_shell_command\n\nlogger = logging.getLogger(__name__)\n\n\n@click.command()\n@click.option(\"--zone\", default=None)\n@click.option(\"--source\", default=None)\n@click.option(\"--target_datetime\")\n@click.option(\"--update_aggregate\", default=False)\ndef capacity_update(\n    zone: ZoneKey,\n    source: str,\n    target_datetime: str,\n    update_aggregate: bool = False,\n):\n    \"\"\"Parameters\n    ----------\n    zone: a two letter zone from the map or a zone group (EIA, ENTSOE, EMBER, IRENA)\n    target_datetime: ISO 8601 string, such as 2018-05-30 15:00\n    \\n\n    Examples\n    -------\n    >>> uv run capacity_update --zone FR --target_datetime \"2022-01-01\"\n    >>> uv run capacity_update --source ENTSOE --target_datetime \"2022-01-01\"\n    \"\"\"\n    logging.basicConfig(\n        level=logging.DEBUG,\n        format=\"%(asctime)s %(levelname)-8s %(name)-30s %(message)s\",\n    )\n\n    assert zone is not None or source is not None, \"Either zone or source must be set\"\n    assert not (zone is None and source is None), \"Zone and source cannot be both set\"\n\n    session = Session()\n    parsed_target_datetime = None\n    if target_datetime is None:\n        raise ValueError(\"target_datetime must be specified\")\n    parsed_target_datetime = datetime.fromisoformat(target_datetime)\n\n    if source is not None:\n        update_source(source, parsed_target_datetime, session)\n    else:\n        update_zone(zone, parsed_target_datetime, session, update_aggregate)\n\n    print(\"Running prettier...\")\n    run_shell_command(\"pnpx prettier@2 --write config/zones --cache\", cwd=ROOT_PATH)\n"
  },
  {
    "path": "config/Earthfile",
    "content": "VERSION 0.8\nFROM alpine:latest\nWORKDIR /contrib/config\n\n\nsrc-files:\n  COPY . .\n  SAVE ARTIFACT .\n\ndata-centers-files:\n  COPY data_centers/data_centers.json ./data_centers/data_centers.json\n  SAVE ARTIFACT .\n\ntest:\n  RUN echo \"tests should live here\""
  },
  {
    "path": "config/__init__.py",
    "content": ""
  },
  {
    "path": "config/data_centers/data_centers.json",
    "content": "{\n  \"gcp-us-central1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-95.8028031, 41.1755951],\n    \"displayName\": \"Southlands Campus\",\n    \"region\": \"us-central1\",\n    \"zoneKey\": \"US-CENT-SWPP\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-us-east1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-80.088472, 33.105486],\n    \"displayName\": \"Berkeley County\",\n    \"region\": \"us-east1\",\n    \"zoneKey\": \"US-CAR-SCEG\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-us-west1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-121.2009427, 45.6317898],\n    \"displayName\": \"The Dalles\",\n    \"region\": \"us-west1\",\n    \"zoneKey\": \"US-NW-PACW\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-northamerica-northeast2\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-79.3832, 43.6532],\n    \"displayName\": \"Toronto\",\n    \"region\": \"northamerica-northeast2\",\n    \"zoneKey\": \"CA-ON\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-us-east4\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-77.4875, 39.0438],\n    \"displayName\": \"Ashburn, Northern Virginia\",\n    \"region\": \"us-east4\",\n    \"zoneKey\": \"US-MIDA-PJM\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-europe-west1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [3.8580813, 50.4663049],\n    \"displayName\": \"St Ghislain\",\n    \"region\": \"europe-west1\",\n    \"zoneKey\": \"BE\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-us-west2\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-118.2437, 34.0522],\n    \"displayName\": \"Los Angeles\",\n    \"region\": \"us-west2\",\n    \"zoneKey\": \"US-CAL-CISO\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-europe-west4\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [5.0421531, 52.7954802],\n    \"displayName\": \"Middenmeer\",\n    \"region\": \"europe-west4\",\n    \"zoneKey\": \"NL\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-southamerica-west1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-70.6973317, -33.3584722],\n    \"displayName\": \"Quilicura\",\n    \"region\": 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},\n  \"azure-switzerlandnorth\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [8.8410422, 47.2744489],\n    \"displayName\": \"Switzerland North\",\n    \"region\": \"switzerlandnorth\",\n    \"zoneKey\": \"CH\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2019\"\n  },\n  \"azure-swedencentral\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [17.138836, 60.667761],\n    \"displayName\": \"Sweden Central\",\n    \"region\": \"swedencentral\",\n    \"zoneKey\": \"SE-SE3\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2021\"\n  },\n  \"azure-spaincentral\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [-3.7035825, 40.4167047],\n    \"displayName\": \"Spain Central\",\n    \"region\": \"spaincentral\",\n    \"zoneKey\": \"ES\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    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\"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2015\"\n  },\n  \"azure-centralindia\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [75.0544541, 18.521428],\n    \"displayName\": \"Central India\",\n    \"region\": \"centralindia\",\n    \"zoneKey\": \"IN-WE\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2015\"\n  },\n  \"azure-germanywestcentral\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [8.6820917, 50.2106444],\n    \"displayName\": \"Germany West Central\",\n    \"region\": \"germanywestcentral\",\n    \"zoneKey\": \"DE\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2019\"\n  },\n  \"azure-francecentral\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [2.3514616, 48.8566969],\n    \"displayName\": \"France Central\",\n    \"region\": \"francecentral\",\n 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\"zoneKey\": \"CN\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2022\"\n  },\n  \"azure-chinanorth2\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [118.3976563, 39.63107677],\n    \"displayName\": \"China North 2\",\n    \"region\": \"chinanorth2\",\n    \"zoneKey\": \"CN\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2018\"\n  },\n  \"azure-chinanorth\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [116.0912391, 40.5065084],\n    \"displayName\": \"China North\",\n    \"region\": \"chinanorth\",\n    \"zoneKey\": \"CN\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2014\"\n  },\n  \"azure-chinaeast2\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [119.9265137, 30.57015912],\n    \"displayName\": \"China East 2\",\n    \"region\": \"chinaeast2\",\n    \"zoneKey\": \"CN\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2018\"\n  },\n  \"azure-chinaeast\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [121.9692071, 31.2322758],\n    \"displayName\": \"China East\",\n    \"region\": \"chinaeast\",\n    \"zoneKey\": \"CN\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2014\"\n  },\n  \"azure-canadaeast\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [-71.2352226, 46.8259601],\n    \"displayName\": \"Canada East\",\n    \"region\": \"canadaeast\",\n    \"zoneKey\": \"CA-QC\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2016\"\n  },\n  \"azure-canadacentral\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [-79.3839347, 43.6534817],\n    \"displayName\": \"Canada Central\",\n    \"region\": \"canadacentral\",\n    \"zoneKey\": \"CA-ON\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2016\"\n  },\n  \"azure-brazilsouth\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [-46.66992188, -23.74512587],\n    \"displayName\": \"Brazil South\",\n    \"region\": \"brazilsouth\",\n    \"zoneKey\": \"BR-CS\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2014\"\n  },\n  \"azure-australiacentral\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [149.1012676, -35.2975906],\n    \"displayName\": \"Australia Central\",\n    \"region\": \"australiacentral\",\n    \"zoneKey\": \"AU-NSW\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2018\"\n  },\n  \"azure-australiasoutheast\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [144.9631608, -37.8142176],\n    \"displayName\": \"Australia 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\"displayName\": \"East Asia\",\n    \"region\": \"eastasia\",\n    \"zoneKey\": \"HK\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2010\"\n  },\n  \"azure-southafricanorth\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [28.047304, -26.204103],\n    \"displayName\": \"South Africa North\",\n    \"region\": \"southafricanorth\",\n    \"zoneKey\": \"ZA\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2019\"\n  },\n  \"aws-us-east-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [-77.4291, 39.0067],\n    \"displayName\": \"N. 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 \"aws-ap-east-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [114.1694, 22.3193],\n    \"displayName\": \"Hong Kong\",\n    \"region\": \"ap-east-1\",\n    \"zoneKey\": \"HK\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2019\"\n  },\n  \"aws-ap-south-2\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [78.476, 17.366],\n    \"displayName\": \"Hyderabad\",\n    \"region\": \"ap-south-2\",\n    \"zoneKey\": \"IN-SO\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2022\"\n  },\n  \"aws-ap-southeast-3\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [106.8229, -6.1944],\n    \"displayName\": \"Jakarta\",\n    \"region\": \"ap-southeast-3\",\n    \"zoneKey\": \"ID\",\n    \"status\": \"operational\",\n    \"source\": 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   \"region\": \"ap-southeast-5\",\n    \"zoneKey\": \"MY-WM\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2024\"\n  },\n  \"aws-ap-southeast-4\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [144.9631, -37.8136],\n    \"displayName\": \"Melbourne\",\n    \"region\": \"ap-southeast-4\",\n    \"zoneKey\": \"AU-VIC\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2023\"\n  },\n  \"aws-ap-south-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [72.8777, 19.076],\n    \"displayName\": \"Mumbai\",\n    \"region\": \"ap-south-1\",\n    \"zoneKey\": \"IN-WE\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2016\"\n  },\n  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\"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2012\"\n  },\n  \"aws-ap-southeast-7\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [100.5018, 13.7563],\n    \"displayName\": \"Thailand\",\n    \"region\": \"ap-southeast-7\",\n    \"zoneKey\": \"TH\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2025\"\n  },\n  \"aws-ap-northeast-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [139.65, 35.6764],\n    \"displayName\": \"Tokyo\",\n    \"region\": \"ap-northeast-1\",\n    \"zoneKey\": \"JP-TK\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2011\"\n  },\n  \"aws-ca-central-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [-73.5674, 45.5019],\n    \"displayName\": 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\"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2020\"\n  },\n  \"aws-eu-west-3\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [2.3514, 48.8575],\n    \"displayName\": \"Paris\",\n    \"region\": \"eu-west-3\",\n    \"zoneKey\": \"FR\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2017\"\n  },\n  \"aws-eu-south-2\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [-0.8247, 41.7737],\n    \"displayName\": \"Spain\",\n    \"region\": \"eu-south-2\",\n    \"zoneKey\": \"ES\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2022\"\n  },\n  \"aws-eu-north-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [18.0656, 59.3327],\n    \"displayName\": \"Stockholm\",\n    \"region\": 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\"provider\": \"aws\",\n    \"lonlat\": [-100.3899, 20.5888],\n    \"displayName\": \"Central\",\n    \"region\": \"mx-central-1\",\n    \"zoneKey\": \"MX\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2025\"\n  },\n  \"aws-me-central-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [55.2708, 25.2048],\n    \"displayName\": \"UAE\",\n    \"region\": \"me-central-1\",\n    \"zoneKey\": \"AE\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2022\"\n  },\n  \"aws-sa-east-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [-46.6396, -23.5558],\n    \"displayName\": \"S\\u00e3o Paulo\",\n    \"region\": \"sa-east-1\",\n    \"zoneKey\": \"BR-CS\",\n    \"status\": \"operational\",\n    \"source\": 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\"region\": \"ca-toronto\",\n    \"source\": \"https://www.ovhcloud.com/fr/datacenters-ovhcloud/\",\n    \"operationalSince\": null,\n    \"status\": \"operational\"\n  },\n  \"ovh-fr-gravelines\": {\n    \"provider\": \"ovh\",\n    \"displayName\": \"Gravelines\",\n    \"zoneKey\": \"FR\",\n    \"lonlat\": [2.15526, 51.0181],\n    \"region\": \"fr-gravelines\",\n    \"source\": \"https://www.ovhcloud.com/fr/datacenters-ovhcloud/\",\n    \"operationalSince\": null,\n    \"status\": \"operational\"\n  },\n  \"ovh-fr-paris\": {\n    \"provider\": \"ovh\",\n    \"displayName\": \"Paris\",\n    \"zoneKey\": \"FR\",\n    \"lonlat\": [2.35029, 48.8574],\n    \"region\": \"fr-paris\",\n    \"source\": \"https://www.ovhcloud.com/fr/datacenters-ovhcloud/\",\n    \"operationalSince\": null,\n    \"status\": \"operational\"\n  },\n  \"ovh-fr-roubaix\": {\n    \"provider\": \"ovh\",\n    \"displayName\": \"Roubaix\",\n    \"zoneKey\": \"FR\",\n    \"lonlat\": [3.20422, 50.6925],\n    \"region\": 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\"zoneKey\": \"ZA\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-asia-east2\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [114.1694, 22.3193],\n    \"displayName\": \"Hong Kong\",\n    \"region\": \"asia-east2\",\n    \"zoneKey\": \"HK\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-asia-northeast2\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [135.5023, 34.6937],\n    \"displayName\": \"Osaka\",\n    \"region\": \"asia-northeast2\",\n    \"zoneKey\": \"JP-KN\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-asia-northeast3\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [126.978, 37.5665],\n    \"displayName\": \"Seoul\",\n    \"region\": 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\"region\": \"asia-southeast2\",\n    \"zoneKey\": \"ID\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-asia-southeast3\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [100.5018, 13.7563],\n    \"displayName\": \"Bangkok\",\n    \"region\": \"asia-southeast3\",\n    \"zoneKey\": \"TH\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-australia-southeast1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [151.2093, -33.8688],\n    \"displayName\": \"Sydney\",\n    \"region\": \"australia-southeast1\",\n    \"zoneKey\": \"AU-NSW\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-australia-southeast2\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [144.9631, 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\"provider\": \"gcp\",\n    \"lonlat\": [9.19, 45.4642],\n    \"displayName\": \"Milan\",\n    \"region\": \"europe-west8\",\n    \"zoneKey\": \"IT-NO\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-europe-west9\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [2.3522, 48.8566],\n    \"displayName\": \"Paris\",\n    \"region\": \"europe-west9\",\n    \"zoneKey\": \"FR\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-europe-west10\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [13.405, 52.52],\n    \"displayName\": \"Berlin\",\n    \"region\": \"europe-west10\",\n    \"zoneKey\": \"DE\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-europe-west12\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [7.6869, 45.0703],\n    \"displayName\": \"Turin\",\n    \"region\": \"europe-west12\",\n    \"zoneKey\": \"IT-NO\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-me-central1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [51.531, 25.2854],\n    \"displayName\": \"Doha\",\n    \"region\": \"me-central1\",\n    \"zoneKey\": \"QA\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-me-central2\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [50.1033, 26.4207],\n    \"displayName\": \"Dammam\",\n    \"region\": \"me-central2\",\n    \"zoneKey\": \"SA\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-me-west1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [34.7818, 32.0853],\n    \"displayName\": \"Tel Aviv\",\n    \"region\": \"me-west1\",\n    \"zoneKey\": \"IL\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-northamerica-northeast1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-73.5674, 45.5019],\n    \"displayName\": \"Montréal\",\n    \"region\": \"northamerica-northeast1\",\n    \"zoneKey\": \"CA-QC\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-northamerica-south1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-100.3899, 20.5888],\n    \"displayName\": \"Querétaro\",\n    \"region\": \"northamerica-south1\",\n    \"zoneKey\": \"MX\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-southamerica-east1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-46.7916, -23.5325],\n    \"displayName\": \"Osasco, São Paulo\",\n    \"region\": \"southamerica-east1\",\n    \"zoneKey\": \"BR-CS\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-us-east5\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-82.9988, 39.9612],\n    \"displayName\": \"Columbus\",\n    \"region\": \"us-east5\",\n    \"zoneKey\": \"US-MIDA-PJM\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-us-south1\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-96.797, 32.7767],\n    \"displayName\": \"Dallas\",\n    \"region\": \"us-south1\",\n    \"zoneKey\": \"US-TEX-ERCO\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-us-west3\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-111.891, 40.7608],\n    \"displayName\": \"Salt Lake City\",\n    \"region\": \"us-west3\",\n    \"zoneKey\": \"US-NW-PACE\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"gcp-us-west4\": {\n    \"provider\": \"gcp\",\n    \"lonlat\": [-115.1398, 36.1699],\n    \"displayName\": \"Las Vegas\",\n    \"region\": \"us-west4\",\n    \"zoneKey\": \"US-NW-NEVP\",\n    \"status\": \"operational\",\n    \"source\": \"https://cloud.google.com/compute/docs/regions-zones\",\n    \"operationalSince\": null\n  },\n  \"aws-ap-southeast-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [103.8198, 1.3521],\n    \"displayName\": \"Singapore\",\n    \"region\": \"ap-southeast-1\",\n    \"zoneKey\": \"SG\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2010\"\n  },\n  \"aws-me-south-1\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [50.5577, 26.0667],\n    \"displayName\": \"Bahrain\",\n    \"region\": \"me-south-1\",\n    \"zoneKey\": \"BH\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2019\"\n  },\n  \"aws-ap-southeast-6\": {\n    \"provider\": \"aws\",\n    \"lonlat\": [174.7633, -36.8485],\n    \"displayName\": \"New Zealand\",\n    \"region\": \"ap-southeast-6\",\n    \"zoneKey\": \"NZ\",\n    \"status\": \"operational\",\n    \"source\": \"https://docs.aws.amazon.com/global-infrastructure/latest/regions/aws-regions.html\",\n    \"operationalSince\": \"2025\"\n  },\n  \"azure-koreasouth\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [129.0756, 35.1796],\n    \"displayName\": \"Korea South\",\n    \"region\": \"koreasouth\",\n    \"zoneKey\": \"KR\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2017\"\n  },\n  \"azure-francesouth\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [5.3698, 43.2965],\n    \"displayName\": \"France South\",\n    \"region\": \"francesouth\",\n    \"zoneKey\": \"FR\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2018\"\n  },\n  \"azure-germanynorth\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [13.405, 52.52],\n    \"displayName\": \"Germany North\",\n    \"region\": \"germanynorth\",\n    \"zoneKey\": \"DE\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2019\"\n  },\n  \"azure-norwaywest\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [5.7331, 58.97],\n    \"displayName\": \"Norway West\",\n    \"region\": \"norwaywest\",\n    \"zoneKey\": \"NO-NO2\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2019\"\n  },\n  \"azure-switzerlandwest\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [6.1432, 46.2044],\n    \"displayName\": \"Switzerland West\",\n    \"region\": \"switzerlandwest\",\n    \"zoneKey\": \"CH\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2019\"\n  },\n  \"azure-southafricawest\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [18.4241, -33.9249],\n    \"displayName\": \"South Africa West\",\n    \"region\": \"southafricawest\",\n    \"zoneKey\": \"ZA\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2019\"\n  },\n  \"azure-uaecentral\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [54.3773, 24.4539],\n    \"displayName\": \"UAE Central\",\n    \"region\": \"uaecentral\",\n    \"zoneKey\": \"AE\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2019\"\n  },\n  \"azure-brazilsoutheast\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [-43.1729, -22.9068],\n    \"displayName\": \"Brazil Southeast\",\n    \"region\": \"brazilsoutheast\",\n    \"zoneKey\": \"BR-CS\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2021\"\n  },\n  \"azure-australiacentral2\": {\n    \"provider\": \"azure\",\n    \"lonlat\": [149.13, -35.2809],\n    \"displayName\": \"Australia Central 2\",\n    \"region\": \"australiacentral2\",\n    \"zoneKey\": \"AU-NSW\",\n    \"status\": \"operational\",\n    \"source\": \"https://datacenters.microsoft.com\",\n    \"operationalSince\": \"2018\"\n  }\n}\n"
  },
  {
    "path": "config/defaults.yaml",
    "content": "fallbackZoneMixes:\n  powerOriginRatios:\n    _comment: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html, https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2018/Jul/IRENA_Renewable_Energy_Statistics_2018.pdf\n    _source: BP Statistical Review of World Energy 2019, values from 2018, and Electricity Maps Avg for average carbon intensity, and IRENA report for Biomass and geothermal\n    value:\n      battery charge: 0\n      battery discharge: 0\n      biomass: 0.017509\n      coal: 0.38\n      gas: 0.232\n      geothermal: 0.003081\n      hydro: 0.158\n      hydro charge: 0\n      hydro discharge: 0\n      nuclear: 0.102\n      oil: 0.03\n      solar: 0.021966\n      unknown: 0.007728\n      wind: 0.047716\nisLowCarbon:\n  battery charge:\n    _comment: Charge does not have any impact (we count emissions at discharge)\n    source: Electricity Maps\n    value: 1\n  battery discharge:\n    _comment: Battery discharge is assumed to be powered by low-carbon. Ideally this should be overriden per zone.\n    source: Electricity Maps\n    value: 1\n  biomass:\n    _comment: biomass is considered low-carbon.\n    source: Electricity Maps\n    value: 1\n  coal:\n    _comment: coal is a fossil fuel.\n    source: Electricity Maps\n    value: 0\n  gas:\n    _comment: gas is a fossil fuel.\n    source: Electricity Maps\n    value: 0\n  geothermal:\n    _comment: geothermal is considered low-carbon.\n    source: Electricity Maps\n    value: 1\n  hydro:\n    _comment: hydro is considered low-carbon.\n    source: Electricity Maps\n    value: 1\n  hydro charge:\n    _comment: Charge does not have any impact (we count emissions at discharge)\n    source: Electricity Maps\n    value: 1\n  hydro discharge:\n    _comment: Hydro discharge is assumed to be powered by low-carbon. Ideally this should be overriden per zone.\n    source: Electricity Maps\n    value: 1\n  nuclear:\n    _comment: nuclear is considered low-carbon.\n    source: Electricity Maps\n    value: 1\n  oil:\n    _comment: oil is a fossil fuel.\n    source: Electricity Maps\n    value: 0\n  solar:\n    _comment: solar is considered low-carbon.\n    source: Electricity Maps\n    value: 1\n  unknown:\n    _comment: By default unknown is assumed to be made up of fossil fuel based modes.\n    datetime: '2020-01-01'\n    source: Electricity Maps\n    value: 0\n  wind:\n    _comment: wind is considered low-carbon.\n    source: Electricity Maps\n    value: 1\nisRenewable:\n  battery charge:\n    _comment: Charge does not have any impact (we count emissions at discharge)\n    source: Electricity Maps\n    value: 1\n  battery discharge:\n    _comment: Battery discharge is assumed to be powered by renewables. Ideally this should be overriden per zone.\n    source: Electricity Maps\n    value: 1\n  biomass:\n    _comment: biomass is considered renewable.\n    source: Electricity Maps\n    value: 1\n  coal:\n    _comment: coal is a fossil fuel.\n    source: Electricity Maps\n    value: 0\n  gas:\n    _comment: gas is a fossil fuel.\n    source: Electricity Maps\n    value: 0\n  geothermal:\n    _comment: geothermal is considered renewable.\n    source: Electricity Maps\n    value: 1\n  hydro:\n    _comment: hydro is considered renewable.\n    source: Electricity Maps\n    value: 1\n  hydro charge:\n    _comment: Charge does not have any impact (we count emissions at discharge)\n    source: Electricity Maps\n    value: 1\n  hydro discharge:\n    _comment: Hydro discharge is assumed to be powered by renewables. Ideally this should be overriden per zone.\n    source: Electricity Maps\n    value: 1\n  nuclear:\n    _comment: nuclear is a not renewable.\n    source: Electricity Maps\n    value: 0\n  oil:\n    _comment: oil is a fossil fuel.\n    source: Electricity Maps\n    value: 0\n  solar:\n    _comment: solar is considered renewable.\n    source: Electricity Maps\n    value: 1\n  unknown:\n    _comment: By default unknown is assumed to be made up of fossil fuel based modes.\n    source: Electricity Maps\n    value: 0\n  wind:\n    _comment: wind is considered renewable.\n    source: Electricity Maps\n    value: 1\nemissionFactors:\n  direct:\n    battery charge:\n      _comment: Emissions are counted at discharge\n      source: Electricity Maps\n      value: 0\n    battery discharge:\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2015-01-01'\n        source: 2015 annual mean carbon intensity by Electricity Maps\n        value: 307.04\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2016-01-01'\n        source: 2016 annual mean carbon intensity by Electricity Maps\n        value: 295.25\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2017-01-01'\n        source: 2017 annual mean carbon intensity by Electricity Maps\n        value: 311.04\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2018-01-01'\n        source: 2018 annual mean carbon intensity by Electricity Maps\n        value: 331.14\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2019-01-01'\n        source: 2019 annual mean carbon intensity by Electricity Maps\n        value: 326.32\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2020-01-01'\n        source: 2020 annual mean carbon intensity by Electricity Maps\n        value: 310.58\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2021-01-01'\n        source: 2021 annual mean carbon intensity by Electricity Maps\n        value: 324.69\n    biomass:\n      source: BEIS 2021\n      value: 0\n    coal:\n      source: IPCC 2014\n      value: 760\n    gas:\n      source: IPCC 2014\n      value: 370\n    geothermal:\n      source: IPCC 2014\n      value: 0\n    hydro:\n      source: IPCC 2014\n      value: 0\n    hydro charge:\n      _comment: Emissions are counted at discharge\n      source: Electricity Maps\n      value: 0\n    hydro discharge:\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2015-01-01'\n        source: 2015 annual mean carbon intensity by Electricity Maps\n        value: 307.04\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2016-01-01'\n        source: 2016 annual mean carbon intensity by Electricity Maps\n        value: 295.25\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2017-01-01'\n        source: 2017 annual mean carbon intensity by Electricity Maps\n        value: 311.04\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2018-01-01'\n        source: 2018 annual mean carbon intensity by Electricity Maps\n        value: 331.14\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2019-01-01'\n        source: 2019 annual mean carbon intensity by Electricity Maps\n        value: 326.32\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2020-01-01'\n        source: 2020 annual mean carbon intensity by Electricity Maps\n        value: 310.58\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2021-01-01'\n        source: 2021 annual mean carbon intensity by Electricity Maps\n        value: 324.69\n    nuclear:\n      source: IPCC 2014\n      value: 0\n    oil:\n      _comment: A blended average of US and UK direct emission factor figures\n      source: EIA 2020/BEIS 2021\n      value: 406\n    solar:\n      source: IPCC 2014\n      value: 0\n    unknown:\n      _comment: assume conventional\n      source: assumes thermal (coal, gas, or oil)\n      value: 575\n    wind:\n      source: IPCC 2014\n      value: 0\n  lifecycle:\n    battery charge:\n      _comment: Emissions are counted at discharge\n      source: Electricity Maps\n      value: 0\n    battery discharge:\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2015-01-01'\n        source: 2015 annual mean carbon intensity by Electricity Maps\n        value: 363.85\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2016-01-01'\n        source: 2016 annual mean carbon intensity by Electricity Maps\n        value: 354.12\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2017-01-01'\n        source: 2017 annual mean carbon intensity by Electricity Maps\n        value: 370.7\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2018-01-01'\n        source: 2018 annual mean carbon intensity by Electricity Maps\n        value: 407.34\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2019-01-01'\n        source: 2019 annual mean carbon intensity by Electricity Maps\n        value: 391.46\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2020-01-01'\n        source: 2020 annual mean carbon intensity by Electricity Maps\n        value: 375.63\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2021-01-01'\n        source: 2021 annual mean carbon intensity by Electricity Maps\n        value: 391.33\n    biomass:\n      source: IPCC 2014\n      value: 230\n    coal:\n      source: IPCC 2014\n      value: 820\n    gas:\n      source: IPCC 2014\n      value: 490\n    geothermal:\n      source: IPCC 2014\n      value: 38\n    hydro:\n      source: IPCC 2014\n      value: 24\n    hydro charge:\n      _comment: Emissions are counted at discharge\n      source: Electricity Maps\n      value: 0\n    hydro discharge:\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2015-01-01'\n        source: 2015 annual mean carbon intensity by Electricity Maps\n        value: 363.85\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2016-01-01'\n        source: 2016 annual mean carbon intensity by Electricity Maps\n        value: 354.12\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2017-01-01'\n        source: 2017 annual mean carbon intensity by Electricity Maps\n        value: 370.7\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2018-01-01'\n        source: 2018 annual mean carbon intensity by Electricity Maps\n        value: 407.34\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2019-01-01'\n        source: 2019 annual mean carbon intensity by Electricity Maps\n        value: 391.46\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2020-01-01'\n        source: 2020 annual mean carbon intensity by Electricity Maps\n        value: 375.63\n      - _comment: As a default fallback, we use the annual mean carbon intensity of all Electricity Maps zones\n        datetime: '2021-01-01'\n        source: 2021 annual mean carbon intensity by Electricity Maps\n        value: 391.33\n    nuclear:\n      source: IPCC 2014\n      value: 12\n    oil:\n      _comment: UK Parliamentary Office of Science and Technology (2006) 'Carbon footprint of electricity generation'\n      source: UK POST 2014\n      value: 650\n    solar:\n      source: IPCC 2014\n      value: 45\n    unknown:\n      _comment: assume conventional\n      source: assumes thermal (coal, gas, oil or biomass)\n      value: 700\n    wind:\n      source: IPCC 2014\n      value: 11\n"
  },
  {
    "path": "config/exchanges/AD_ES.yaml",
    "content": "capacity:\n  - -125\n  - 125\nlonlat:\n  - 1.45\n  - 42.3\nparsers:\n  exchange: ESIOS.fetch_exchange\nrotation: 200\n"
  },
  {
    "path": "config/exchanges/AD_FR.yaml",
    "content": "lonlat:\n  - 1.7963181\n  - 42.58837\nrotation: 38\n"
  },
  {
    "path": "config/exchanges/AL_GR.yaml",
    "content": "capacity:\n  - -533\n  - 533\nlonlat:\n  - 20.689872\n  - 40.198219\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 135\n"
  },
  {
    "path": "config/exchanges/AL_ME.yaml",
    "content": "lonlat:\n  - 19.500384\n  - 42.428871\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -45\n"
  },
  {
    "path": "config/exchanges/AL_RS.yaml",
    "content": "lonlat:\n  - 20.486292\n  - 42.323472\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 45\n"
  },
  {
    "path": "config/exchanges/AL_XK.yaml",
    "content": "lonlat:\n  - 20.212\n  - 42.408\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 45\n"
  },
  {
    "path": "config/exchanges/AM_GE.yaml",
    "content": "lonlat:\n  - 44.313\n  - 41.205\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/AM_IR.yaml",
    "content": "lonlat:\n  - 46.3\n  - 38.9\nparsers: {}\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/AR_BR-S.yaml",
    "content": "lonlat:\n  - -56.407453\n  - -28.880006\nparsers:\n  exchange: ONS.fetch_exchange\nrotation: 110\n"
  },
  {
    "path": "config/exchanges/AR_BR.yaml",
    "content": "lonlat:\n  - -56.407453\n  - -28.880006\nrotation: 110\n"
  },
  {
    "path": "config/exchanges/AR_CL-SEN.yaml",
    "content": "lonlat:\n  - -69.860314\n  - -33.641822\nparsers:\n  exchange: CAMMESA.fetch_exchange\nrotation: 270\n"
  },
  {
    "path": "config/exchanges/AR_PY.yaml",
    "content": "lonlat:\n  - -59.408\n  - -24.346\nparsers:\n  exchange: CAMMESA.fetch_exchange\nrotation: 45\n"
  },
  {
    "path": "config/exchanges/AR_UY.yaml",
    "content": "lonlat:\n  - -58.150\n  - -32.199\nparsers:\n  exchange: UY.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/AT_CH.yaml",
    "content": "lonlat:\n  - 9.597882\n  - 47.079455\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/AT_CZ.yaml",
    "content": "lonlat:\n  - 15.486554\n  - 48.909846\nparsers:\n  exchange: CZ.fetch_exchange\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/AT_DE.yaml",
    "content": "lonlat:\n  - 12.679547\n  - 47.696804\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -30\n"
  },
  {
    "path": "config/exchanges/AT_HU.yaml",
    "content": "lonlat:\n  - 16.605363\n  - 47.444264\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 120\n"
  },
  {
    "path": "config/exchanges/AT_IT-NO.yaml",
    "content": "capacity:\n  - -145\n  - 325\nlonlat:\n  - 12.344464\n  - 46.741723\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  coreExternalAtcDayAhead: JAO.fetch_core_external_atc_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -140\n"
  },
  {
    "path": "config/exchanges/AT_IT.yaml",
    "content": "capacity:\n  - -145\n  - 325\nlonlat:\n  - 12.344464\n  - 46.741723\nrotation: -140\n"
  },
  {
    "path": "config/exchanges/AT_SI.yaml",
    "content": "lonlat:\n  - 15.014142\n  - 46.613582\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/AU-NSW_AU-QLD.yaml",
    "content": "capacity:\n  - -1510\n  - 957\nlonlat:\n  - 146.503228\n  - -29.054874\nparsers:\n  exchange: OPENNEM.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/AU-NSW_AU-VIC.yaml",
    "content": "capacity:\n  - -1700\n  - 1450\nlonlat:\n  - 145.308829\n  - -35.850801\nparsers:\n  exchange: OPENNEM.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/AU-SA_AU-VIC.yaml",
    "content": "capacity:\n  - -820\n  - 750\nlonlat:\n  - 140.965561\n  - -35.784766\nparsers:\n  exchange: OPENNEM.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/AU-TAS_AU-VIC.yaml",
    "content": "capacity:\n  - -478\n  - 594\nlonlat:\n  - 146.096047\n  - -39.836207\nparsers:\n  exchange: OPENNEM.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/AX_FI.yaml",
    "content": "capacity:\n  - -110\n  - 110\nlonlat:\n  - 21.193\n  - 60.386\nparsers:\n  exchange: AX.fetch_exchange\nrotation: 50\n"
  },
  {
    "path": "config/exchanges/AX_SE-SE3.yaml",
    "content": "capacity:\n  - -80\n  - 80\nlonlat:\n  - 19.239\n  - 60.063\nparsers:\n  exchange: AX.fetch_exchange\nrotation: -130\n"
  },
  {
    "path": "config/exchanges/AX_SE.yaml",
    "content": "capacity:\n  - -80\n  - 80\nlonlat:\n  - 19.239\n  - 60.063\nrotation: -130\n"
  },
  {
    "path": "config/exchanges/AZ_GE.yaml",
    "content": "lonlat:\n  - 45.153\n  - 41.398\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -35\n"
  },
  {
    "path": "config/exchanges/AZ_RU-1.yaml",
    "content": "lonlat:\n  - 48.114921\n  - 41.468606\nparsers:\n  exchange: RU.fetch_exchange\nrotation: -35\n"
  },
  {
    "path": "config/exchanges/BA_HR.yaml",
    "content": "capacity:\n  - -5429\n  - 5429\nlonlat:\n  - 16.941\n  - 45.205\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/BA_ME.yaml",
    "content": "lonlat:\n  - 18.665423\n  - 43.042137\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 120\n"
  },
  {
    "path": "config/exchanges/BA_RS.yaml",
    "content": "lonlat:\n  - 19.127873\n  - 44.377951\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/BD_IN-EA.yaml",
    "content": "lonlat:\n  - 88.717802\n  - 24.104800\nparsers:\n  exchange: ERP_PGCB.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/BD_IN-NE.yaml",
    "content": "lonlat:\n  - 91.245998\n  - 23.485682\nparsers:\n  exchange: ERP_PGCB.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/BD_IN.yaml",
    "content": "lonlat:\n  - 88.717802\n  - 24.104800\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/BD_NP.yaml",
    "content": "capacity:\n  - -40\n  - 40\nlonlat:\n  - 88.259123\n  - 26.595468\nparsers:\n  exchange: ERP_PGCB.fetch_exchange\nrotation: -60\n"
  },
  {
    "path": "config/exchanges/BE_DE.yaml",
    "content": "capacity:\n  - -1000\n  - 1000\nlonlat:\n  - 6.4\n  - 50.4\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/BE_FR.yaml",
    "content": "lonlat:\n  - 4.137165\n  - 50.255806\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -135\n"
  },
  {
    "path": "config/exchanges/BE_GB.yaml",
    "content": "capacity:\n  - -1000\n  - 1000\nlonlat:\n  - 2.052937\n  - 51.659015\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -45\n"
  },
  {
    "path": "config/exchanges/BE_LU.yaml",
    "content": "lonlat:\n  - 5.808054\n  - 49.990503\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 100\n"
  },
  {
    "path": "config/exchanges/BE_NL.yaml",
    "content": "lonlat:\n  - 5.026873\n  - 51.425174\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/BG_GR.yaml",
    "content": "capacity:\n  - -700\n  - 700\nlonlat:\n  - 24.1\n  - 41.558088\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/BG_MK.yaml",
    "content": "capacity:\n  - -950\n  - 950\nlonlat:\n  - 22.912615\n  - 41.86784\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/BG_RO.yaml",
    "content": "lonlat:\n  - 25.609385\n  - 43.674878\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  coreExternalAtcDayAhead: JAO.fetch_core_external_atc_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/BG_RS.yaml",
    "content": "capacity:\n  - -1073\n  - 1073\nlonlat:\n  - 22.978533\n  - 43.131375\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/BG_TR.yaml",
    "content": "capacity:\n  - -2485\n  - 2485\nlonlat:\n  - 26.89864\n  - 42.002181\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 135\n"
  },
  {
    "path": "config/exchanges/BR-CS_BR-N.yaml",
    "content": "lonlat:\n  - -54.908876\n  - -9.870031\nparsers:\n  exchange: ONS.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/BR-CS_BR-NE.yaml",
    "content": "lonlat:\n  - -42.362632\n  - -15.051086\nparsers:\n  exchange: ONS.fetch_exchange\nrotation: 30\n"
  },
  {
    "path": "config/exchanges/BR-CS_BR-S.yaml",
    "content": "lonlat:\n  - -49.857513\n  - -23.066549\nparsers:\n  exchange: ONS.fetch_exchange\nrotation: -150\n"
  },
  {
    "path": "config/exchanges/BR-N_BR-NE.yaml",
    "content": "lonlat:\n  - -45.610678\n  - -8.187852\nparsers:\n  exchange: ONS.fetch_exchange\nrotation: 110\n"
  },
  {
    "path": "config/exchanges/BR-S_PY.yaml",
    "content": "lonlat:\n  - -54.44926\n  - -24.749974\nparsers:\n  exchange: ONS.fetch_exchange\nrotation: 110\n"
  },
  {
    "path": "config/exchanges/BR-S_UY.yaml",
    "content": "lonlat:\n  - -54.982242\n  - -31.301863\nparsers:\n  exchange: UY.fetch_exchange\nrotation: -150\n"
  },
  {
    "path": "config/exchanges/BR_PY.yaml",
    "content": "lonlat:\n  - -54.44926\n  - -24.749974\nrotation: 110\n"
  },
  {
    "path": "config/exchanges/BR_UY.yaml",
    "content": "lonlat:\n  - -54.982242\n  - -31.301863\nrotation: -150\n"
  },
  {
    "path": "config/exchanges/BT_IN-EA.yaml",
    "content": "lonlat:\n  - 89.387672\n  - 26.847837\nparsers:\n  exchange: IN_EA.fetch_exchange\nrotation: 88\n"
  },
  {
    "path": "config/exchanges/BT_IN.yaml",
    "content": "lonlat:\n  - 89.387672\n  - 26.847837\nrotation: 88\n"
  },
  {
    "path": "config/exchanges/BY_LT.yaml",
    "content": "capacity:\n  - -4553\n  - 4553\nlonlat:\n  - 25.756061\n  - 54.789457\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/BY_RU-1.yaml",
    "content": "lonlat:\n  - 31.141039\n  - 54.483721\nparsers:\n  exchange: RU.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/BY_UA.yaml",
    "content": "capacity:\n  - -900\n  - 900\nlonlat:\n  - 29.393062\n  - 51.468916\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/BZ_MX.yaml",
    "content": "lonlat:\n  - -88.627\n  - 18.24\nparsers:\n  exchange: CENACE.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/CA-AB_CA-BC.yaml",
    "content": "capacity:\n  - -1000\n  - 800\nlonlat:\n  - -119.811359\n  - 53.797027\nparsers:\n  exchange: CA_AB.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/CA-AB_CA-SK.yaml",
    "content": "capacity:\n  - -153\n  - 153\nlonlat:\n  - -109.986644\n  - 54.883208\nparsers:\n  exchange: CA_AB.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/CA-AB_US-NW-NWMT.yaml",
    "content": "capacity:\n  - -315\n  - 310\nlonlat:\n  - -111.920238\n  - 49.016577\nparsers:\n  exchange: CA_AB.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/CA-BC_US-NW-BPAT.yaml",
    "content": "lonlat:\n  - -120.300532\n  - 49.044392\nparsers:\n  exchange: CA_BC.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/CA-MB_CA-ON.yaml",
    "content": "lonlat:\n  - -95.177354\n  - 52.802819\nparsers:\n  exchange: CA_ON.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/CA-MB_US-MIDW-MISO.yaml",
    "content": "lonlat:\n  - -97.5788\n  - 49.0\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/CA-NB_CA-NS.yaml",
    "content": "lonlat:\n  - -65.7552\n  - 45.0425\nparsers:\n  exchange: CA_NB.fetch_exchange\nrotation: 140\n"
  },
  {
    "path": "config/exchanges/CA-NB_CA-PE.yaml",
    "content": "lonlat:\n  - -64.5739\n  - 46.7349\nparsers:\n  exchange: PrinceEdwardIsland.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/CA-NB_CA-QC.yaml",
    "content": "lonlat:\n  - -67.2344\n  - 47.8871\nparsers:\n  exchange: CA_NB.fetch_exchange\nrotation: -45\n"
  },
  {
    "path": "config/exchanges/CA-NB_US-NE-ISNE.yaml",
    "content": "lonlat:\n  - -67.7771\n  - 46.139\nparsers:\n  exchange: US_NEISO.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/CA-NL_CA-NS.yaml",
    "content": "lonlat:\n  - -59.6117\n  - 47.1693\nparsers:\n  exchange: CA_NS.fetch_exchange\nrotation: 207\n"
  },
  {
    "path": "config/exchanges/CA-ON_CA-QC.yaml",
    "content": "lonlat:\n  - -79.494485\n  - 48.798268\nparsers:\n  exchange: CA_ON.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/CA-ON_US-MIDW-MISO.yaml",
    "content": "lonlat:\n  - -84.188\n  - 46.476\nparsers:\n  exchange: CA_ON.fetch_exchange\nrotation: -145\n"
  },
  {
    "path": "config/exchanges/CA-ON_US-NY-NYIS.yaml",
    "content": "lonlat:\n  - -78.9147\n  - 43.5523\nparsers:\n  exchange: CA_ON.fetch_exchange\nrotation: 135\n"
  },
  {
    "path": "config/exchanges/CA-QC_US-NE-ISNE.yaml",
    "content": "lonlat:\n  - -71.737\n  - 45.011\nparsers:\n  exchange: US_NEISO.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/CA-QC_US-NY-NYIS.yaml",
    "content": "lonlat:\n  - -73.768\n  - 45.004\nparsers:\n  exchange: US_NY.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/CA-SK_US-CENT-SWPP.yaml",
    "content": "lonlat:\n  - -105.6714\n  - 48.9838\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/CA_US.yaml",
    "content": "lonlat:\n  - -97.5788\n  - 49.0\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/CH_DE.yaml",
    "content": "lonlat:\n  - 8.806354\n  - 47.667048\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/CH_FR.yaml",
    "content": "lonlat:\n  - 6.5\n  - 46.7\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/CH_IT-NO.yaml",
    "content": "capacity:\n  - -1910\n  - 4572\nlonlat:\n  - 9.047334\n  - 46.113596\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/CH_IT.yaml",
    "content": "capacity:\n  - -1910\n  - 4572\nlonlat:\n  - 9.047334\n  - 46.113596\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/CN_RU-AS.yaml",
    "content": "lonlat:\n  - 123.275128\n  - 53.541248\nparsers:\n  exchange: RU.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/CR_NI.yaml",
    "content": "lonlat:\n  - -84.7303\n  - 11.0638\nparsers:\n  exchange: NI.fetch_exchange\nrotation: -45\n"
  },
  {
    "path": "config/exchanges/CR_PA.yaml",
    "content": "lonlat:\n  - -82.7119\n  - 8.9183\nparsers:\n  exchange: ENTE.fetch_exchange\nrotation: 130\n"
  },
  {
    "path": "config/exchanges/CZ_DE.yaml",
    "content": "lonlat:\n  - 12.321836\n  - 50.227335\nparsers:\n  exchange: CZ.fetch_exchange\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -60\n"
  },
  {
    "path": "config/exchanges/CZ_PL.yaml",
    "content": "lonlat:\n  - 16.496641\n  - 50.269487\nparsers:\n  exchange: CZ.fetch_exchange\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 45\n"
  },
  {
    "path": "config/exchanges/CZ_SK.yaml",
    "content": "lonlat:\n  - 18.100645\n  - 49.089498\nparsers:\n  exchange: CZ.fetch_exchange\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 135\n"
  },
  {
    "path": "config/exchanges/DE_DK-DK1.yaml",
    "content": "capacity:\n  - -2500\n  - 2500\nlonlat:\n  - 9.3\n  - 54.9\nparsers:\n  exchange: DK.fetch_exchange\n  coreExternalAtcDayAhead: JAO.fetch_core_external_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/DE_DK-DK2.yaml",
    "content": "capacity:\n  - -985\n  - 1000\nlonlat:\n  - 12.135031\n  - 54.486043\nparsers:\n  exchange: DK.fetch_exchange\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/DE_DK.yaml",
    "content": "lonlat:\n  - 9.3\n  - 54.9\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/DE_FR.yaml",
    "content": "lonlat:\n  - 8.048297\n  - 48.931337\nparsers:\n  exchange: ECO2MIX.fetch_exchange\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -110\n"
  },
  {
    "path": "config/exchanges/DE_LU.yaml",
    "content": "lonlat:\n  - 6.396699\n  - 49.847692\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/DE_NL.yaml",
    "content": "lonlat:\n  - 6.916521\n  - 52.159037\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/DE_NO-NO2.yaml",
    "content": "capacity:\n  - -1444\n  - 1444\nlonlat:\n  - 7.2\n  - 55.9\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -10\n"
  },
  {
    "path": "config/exchanges/DE_NO.yaml",
    "content": "capacity:\n  - -1444\n  - 1444\nlonlat:\n  - 7.2\n  - 55.9\nrotation: -10\n"
  },
  {
    "path": "config/exchanges/DE_PL.yaml",
    "content": "lonlat:\n  - 14.585163\n  - 52.410625\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/DE_SE-SE4.yaml",
    "content": "capacity:\n  - -615\n  - 615\nlonlat:\n  - 13.552264\n  - 54.925814\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/DE_SE.yaml",
    "content": "capacity:\n  - -615\n  - 615\nlonlat:\n  - 13.552264\n  - 54.925814\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/DK-DK1_DK-DK2.yaml",
    "content": "capacity:\n  - -600\n  - 590\nlonlat:\n  - 10.948508\n  - 55.407235\nparsers:\n  exchange: DK.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/DK-DK1_GB.yaml",
    "content": "capacity:\n  - -1400\n  - 1400\nlonlat:\n  - 3.4\n  - 55\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -105\n"
  },
  {
    "path": "config/exchanges/DK-DK1_NL.yaml",
    "content": "_comment: 700MW from COBRAcable https://en.wikipedia.org/wiki/COBRAcable\ncapacity:\n  - -700\n  - 700\nlonlat:\n  - 7.4\n  - 54.5\nparsers:\n  exchange: DK.fetch_exchange\n  coreExternalAtcDayAhead: JAO.fetch_core_external_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -150\n"
  },
  {
    "path": "config/exchanges/DK-DK1_NO-NO2.yaml",
    "content": "capacity:\n  - -1632\n  - 1632\nlonlat:\n  - 8.8\n  - 57.7\nparsers:\n  exchange: DK.fetch_exchange\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -25\n"
  },
  {
    "path": "config/exchanges/DK-DK1_SE-SE3.yaml",
    "content": "capacity:\n  - -715\n  - 715\nlonlat:\n  - 11.556268\n  - 56.857802\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 70\n"
  },
  {
    "path": "config/exchanges/DK-DK2_SE-SE4.yaml",
    "content": "capacity:\n  - -1300\n  - 1700\nlonlat:\n  - 12.704418\n  - 55.952282\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 70\n"
  },
  {
    "path": "config/exchanges/DK_GB.yaml",
    "content": "capacity:\n  - -1400\n  - 1400\nlonlat:\n  - 3.4\n  - 55\nrotation: -105\n"
  },
  {
    "path": "config/exchanges/DK_NL.yaml",
    "content": "capacity:\n  - -700\n  - 700\nlonlat:\n  - 7.4\n  - 54.5\nrotation: -150\n"
  },
  {
    "path": "config/exchanges/DK_NO.yaml",
    "content": "capacity:\n  - -1632\n  - 1632\nlonlat:\n  - 8.8\n  - 57.7\nrotation: -25\n"
  },
  {
    "path": "config/exchanges/DK_SE.yaml",
    "content": "lonlat:\n  - 11.556268\n  - 56.857802\nrotation: 70\n"
  },
  {
    "path": "config/exchanges/EE_FI.yaml",
    "content": "capacity:\n  - -1016\n  - 1016\nlonlat:\n  - 25.690143\n  - 59.923241\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -35\n"
  },
  {
    "path": "config/exchanges/EE_LV.yaml",
    "content": "capacity:\n  - -1259\n  - 1447\nlonlat:\n  - 26.041706\n  - 57.810982\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/EE_RU-1.yaml",
    "content": "capacity:\n  - -2462\n  - 2462\nlonlat:\n  - 27.468803\n  - 58.545189\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/ES-CN-FV_ES-CN-LZ.yaml",
    "content": "lonlat:\n  - -13.86\n  - 28.8\nparsers:\n  exchange: ES.fetch_exchange\nrotation: 25\n"
  },
  {
    "path": "config/exchanges/ES-IB-FO_ES-IB-IZ.yaml",
    "content": "capacity:\n  - -134\n  - 134\nlonlat:\n  - 0.989\n  - 38.746\nparsers:\n  exchange: ES.fetch_exchange\nrotation: -10\n"
  },
  {
    "path": "config/exchanges/ES-IB-IZ_ES-IB-MA.yaml",
    "content": "capacity:\n  - -200\n  - 200\nlonlat:\n  - 2.032\n  - 39.245\nparsers:\n  exchange: ES.fetch_exchange\nrotation: 50\n"
  },
  {
    "path": "config/exchanges/ES-IB-MA_ES-IB-ME.yaml",
    "content": "capacity:\n  - -100\n  - 100\nlonlat:\n  - 3.549\n  - 39.901\nparsers:\n  exchange: ES.fetch_exchange\nrotation: 70\n"
  },
  {
    "path": "config/exchanges/ES_ES-IB-MA.yaml",
    "content": "capacity:\n  - -400\n  - 400\nlonlat:\n  - 2.23\n  - 40.271\nparsers:\n  exchange: ES.fetch_exchange\nrotation: 135\n"
  },
  {
    "path": "config/exchanges/ES_FR.yaml",
    "content": "capacity:\n  - -2800\n  - 2800\nlonlat:\n  - 0.3\n  - 42.9\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  coreExternalAtcDayAhead: JAO.fetch_core_external_atc_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 20\n"
  },
  {
    "path": "config/exchanges/ES_MA.yaml",
    "content": "capacity:\n  - -1359\n  - 1359\nlonlat:\n  - -5.614929\n  - 35.952597\nparsers:\n  exchange: ESIOS.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/ES_PT.yaml",
    "content": "capacity:\n  - -4545\n  - 5085\nlonlat:\n  - -7\n  - 40\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/FI_NO-NO4.yaml",
    "content": "capacity:\n  - -120\n  - 100\nlonlat:\n  - 25.35158\n  - 68.862684\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -30\n"
  },
  {
    "path": "config/exchanges/FI_NO.yaml",
    "content": "lonlat:\n  - 25.35158\n  - 68.862684\nrotation: -30\n"
  },
  {
    "path": "config/exchanges/FI_RU-1.yaml",
    "content": "capacity:\n  - -1460\n  - 320\nlonlat:\n  - 28.378\n  - 60.878\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 135\n"
  },
  {
    "path": "config/exchanges/FI_SE-SE1.yaml",
    "content": "capacity:\n  - -1900\n  - 1900\nlonlat:\n  - 23.857\n  - 66.921\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/FI_SE-SE3.yaml",
    "content": "capacity:\n  - -1200\n  - 1200\nlonlat:\n  - 19.797\n  - 60.628\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -110\n"
  },
  {
    "path": "config/exchanges/FI_SE.yaml",
    "content": "capacity:\n  - -2700\n  - 2300\nlonlat:\n  - 23.857\n  - 66.921\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/FR-COR_IT-CNO.yaml",
    "content": "capacity:\n  - -300\n  - 300\nlonlat:\n  - 10.091148\n  - 42.686804\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 45\n"
  },
  {
    "path": "config/exchanges/FR-COR_IT-SAR.yaml",
    "content": "capacity:\n  - -400\n  - 325\nlonlat:\n  - 9.123283\n  - 41.293785\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/FR-COR_IT.yaml",
    "content": "lonlat:\n  - 10.091148\n  - 42.686804\nrotation: 45\n"
  },
  {
    "path": "config/exchanges/FR_GB.yaml",
    "content": "capacity:\n  - -4000\n  - 4000\nlonlat:\n  - 0\n  - 50.4\nparsers:\n  exchange: ELEXON.fetch_exchange\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -20\n"
  },
  {
    "path": "config/exchanges/FR_IT-NO.yaml",
    "content": "capacity:\n  - -2160\n  - 4485\nlonlat:\n  - 6.9\n  - 44.4\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  coreExternalAtcDayAhead: JAO.fetch_core_external_atc_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 70\n"
  },
  {
    "path": "config/exchanges/FR_IT.yaml",
    "content": "capacity:\n  - -2160\n  - 4485\nlonlat:\n  - 6.9\n  - 44.4\nrotation: 70\n"
  },
  {
    "path": "config/exchanges/FR_JE.yaml",
    "content": "capacity:\n  - -245\n  - 245\nlonlat:\n  - -1.785\n  - 49.201\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/FR_LU.yaml",
    "content": "lonlat:\n  - 6.100579\n  - 49.45306\nparsers:\n  exchange: ECO2MIX.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/GB-NIR_IE.yaml",
    "content": "lonlat:\n  - -7.4\n  - 54.2\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/GB_GB-NIR.yaml",
    "content": "capacity:\n  - -500\n  - 500\nlonlat:\n  - -5.428149\n  - 54.87826\nparsers:\n  exchange: SMARTGRIDDASHBOARD.fetch_exchange\nrotation: -110\n"
  },
  {
    "path": "config/exchanges/GB_IE.yaml",
    "content": "capacity:\n  - -1000\n  - 1000\nlonlat:\n  - -5.7\n  - 53\nparsers:\n  exchange: ELEXON.fetch_exchange\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -80\n"
  },
  {
    "path": "config/exchanges/GB_IM.yaml",
    "content": "capacity:\n  - -65\n  - 65\nlonlat:\n  - -4\n  - 53.8\nrotation: -40\n\nparsers:\n  exchange: ELEXON.fetch_exchange\n"
  },
  {
    "path": "config/exchanges/GB_NL.yaml",
    "content": "capacity:\n  - -1000\n  - 1000\nlonlat:\n  - 3.3\n  - 52.4\nparsers:\n  exchange: ELEXON.fetch_exchange\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/GB_NO-NO2.yaml",
    "content": "capacity:\n  - -1400\n  - 1400\nlonlat:\n  - 2.44819\n  - 57.266334\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 50\n"
  },
  {
    "path": "config/exchanges/GB_NO.yaml",
    "content": "lonlat:\n  - 2.44819\n  - 57.266334\nrotation: 50\n"
  },
  {
    "path": "config/exchanges/GE_RU-1.yaml",
    "content": "lonlat:\n  - 42.822242\n  - 43.158267\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/GE_TR.yaml",
    "content": "capacity:\n  - -700\n  - 700\nlonlat:\n  - 42.814\n  - 41.562\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -135\n"
  },
  {
    "path": "config/exchanges/GR_IT-SO.yaml",
    "content": "capacity:\n  - -500\n  - 500\nlonlat:\n  - 18.759248\n  - 38.902132\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/GR_IT.yaml",
    "content": "capacity:\n  - -500\n  - 500\nlonlat:\n  - 18.759248\n  - 38.902132\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/GR_MK.yaml",
    "content": "capacity:\n  - -1632\n  - 1632\nlonlat:\n  - 22.011736\n  - 41.160374\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/GR_TR.yaml",
    "content": "capacity:\n  - -1900\n  - 1900\nlonlat:\n  - 26.316812\n  - 41.1262\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/GT_HN.yaml",
    "content": "lonlat:\n  - -89.231\n  - 14.86\nparsers:\n  exchange: HN.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/GT_MX.yaml",
    "content": "lonlat:\n  - -90.967\n  - 16.035\nparsers:\n  exchange: ENTE.fetch_exchange\nrotation: -55\n"
  },
  {
    "path": "config/exchanges/GT_SV.yaml",
    "content": "lonlat:\n  - -89.731\n  - 14.094\nparsers:\n  exchange: ENTE.fetch_exchange\nrotation: 125\n"
  },
  {
    "path": "config/exchanges/HN_NI.yaml",
    "content": "lonlat:\n  - -85.5782\n  - 14.0209\nparsers:\n  exchange: HN.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/HN_SV.yaml",
    "content": "lonlat:\n  - -88.429\n  - 13.859\nparsers:\n  exchange: HN.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/HR_HU.yaml",
    "content": "lonlat:\n  - 17.407365\n  - 45.967775\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 30\n"
  },
  {
    "path": "config/exchanges/HR_RS.yaml",
    "content": "capacity:\n  - -1423\n  - 1423\nlonlat:\n  - 19.021212\n  - 45.354302\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/HR_SI.yaml",
    "content": "lonlat:\n  - 15.362\n  - 45.583\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/HU_RO.yaml",
    "content": "lonlat:\n  - 21.8074107\n  - 47.1141229\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 110\n"
  },
  {
    "path": "config/exchanges/HU_RS.yaml",
    "content": "capacity:\n  - -1054\n  - 1054\nlonlat:\n  - 19.494768\n  - 46.112673\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/HU_SI.yaml",
    "content": "lonlat:\n  - 16.39\n  - 46.69\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -125\n"
  },
  {
    "path": "config/exchanges/HU_SK.yaml",
    "content": "lonlat:\n  - 19.615617\n  - 48.204006\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/HU_UA.yaml",
    "content": "capacity:\n  - -650\n  - 650\nlonlat:\n  - 22.526994\n  - 48.240603\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 35\n"
  },
  {
    "path": "config/exchanges/IN-EA_IN-NE.yaml",
    "content": "lonlat:\n  - 88.232505\n  - 26.451620\nparsers:\n  exchange: IN_EA.fetch_exchange\nrotation: 46\n"
  },
  {
    "path": "config/exchanges/IN-EA_IN-NO.yaml",
    "content": "lonlat:\n  - 81.548111\n  - 22.532074\nparsers:\n  exchange: IN_EA.fetch_exchange\nrotation: -33\n"
  },
  {
    "path": "config/exchanges/IN-EA_IN-SO.yaml",
    "content": "lonlat:\n  - 81.073025\n  - 17.788574\nparsers:\n  exchange: IN_EA.fetch_exchange\nrotation: 40\n"
  },
  {
    "path": "config/exchanges/IN-EA_IN-WE.yaml",
    "content": "lonlat:\n  - 83.363\n  - 21.456\nparsers:\n  exchange: IN_WE.fetch_exchange\nrotation: 310\n"
  },
  {
    "path": "config/exchanges/IN-EA_NP.yaml",
    "content": "lonlat:\n  - 85.946364\n  - 26.629889\nparsers:\n  exchange: IN_EA.fetch_exchange\nrotation: 80\n"
  },
  {
    "path": "config/exchanges/IN-NO_IN-WE.yaml",
    "content": "lonlat:\n  - 75.065\n  - 24.892\nparsers:\n  exchange: IN_WE.fetch_exchange\nrotation: 150\n"
  },
  {
    "path": "config/exchanges/IN-SO_IN-WE.yaml",
    "content": "lonlat:\n  - 76.752\n  - 17.702\n\nparsers:\n  exchange: IN_WE.fetch_exchange\nrotation: -30\n"
  },
  {
    "path": "config/exchanges/IN_NP.yaml",
    "content": "lonlat:\n  - 85.946364\n  - 26.629889\nrotation: 80\n"
  },
  {
    "path": "config/exchanges/IQ_IR.yaml",
    "content": "lonlat:\n  - 47.834\n  - 31.784\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/IT-CNO_IT-CSO.yaml",
    "content": "capacity:\n  - -2800\n  - 2900\nlonlat:\n  - 13\n  - 42.6\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 135\n"
  },
  {
    "path": "config/exchanges/IT-CNO_IT-NO.yaml",
    "content": "capacity:\n  - -4300\n  - 3100\nlonlat:\n  - 11.5\n  - 44.1\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/IT-CSO_IT-SAR.yaml",
    "content": "capacity:\n  - -900\n  - 720\nlonlat:\n  - 11.189622\n  - 41.042731\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -135\n"
  },
  {
    "path": "config/exchanges/IT-CSO_IT-SO.yaml",
    "content": "capacity:\n  - -5100\n  - 2400\nlonlat:\n  - 15.4\n  - 41.0\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/IT-CSO_ME.yaml",
    "content": "capacity:\n  - -600\n  - 600\nlonlat:\n  - 16.5\n  - 42.4\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/IT-NO_SI.yaml",
    "content": "capacity:\n  - -1550\n  - 1550\nlonlat:\n  - 13.596393\n  - 46.105418\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/IT-SIC_IT-SO.yaml",
    "content": "capacity:\n  - -1500\n  - 1300\nlonlat:\n  - 15.65\n  - 38.1\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/IT-SIC_MT.yaml",
    "content": "capacity:\n  - -225\n  - 225\nlonlat:\n  - 14.675346\n  - 36.264287\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -160\n"
  },
  {
    "path": "config/exchanges/IT_ME.yaml",
    "content": "capacity:\n  - -600\n  - 600\nlonlat:\n  - 16.5\n  - 42.4\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/IT_MT.yaml",
    "content": "capacity:\n  - -225\n  - 225\nlonlat:\n  - 14.675346\n  - 36.264287\nrotation: -160\n"
  },
  {
    "path": "config/exchanges/IT_SI.yaml",
    "content": "capacity:\n  - -753\n  - 680\nlonlat:\n  - 13.596393\n  - 46.105418\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/JP-CB_JP-HR.yaml",
    "content": "capacity:\n  - -300\n  - 300\nlonlat:\n  - 136.85\n  - 36.35\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/JP-CB_JP-KN.yaml",
    "content": "capacity:\n  - -2500\n  - 2500\nlonlat:\n  - 136.42\n  - 35.04\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/JP-CB_JP-TK.yaml",
    "content": "capacity:\n  - -2100\n  - 2100\nlonlat:\n  - 138.24\n  - 35.34\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/JP-CG_JP-KN.yaml",
    "content": "capacity:\n  - -4140\n  - 4140\nlonlat:\n  - 134.27\n  - 34.98\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/JP-CG_JP-KY.yaml",
    "content": "capacity:\n  - -2470\n  - 2470\nlonlat:\n  - 130.96\n  - 33.965\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: -170\n"
  },
  {
    "path": "config/exchanges/JP-CG_JP-SK.yaml",
    "content": "capacity:\n  - -1200\n  - 1200\nlonlat:\n  - 133.81\n  - 34.4\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: 175\n"
  },
  {
    "path": "config/exchanges/JP-HKD_JP-TH.yaml",
    "content": "capacity:\n  - -900\n  - 900\nlonlat:\n  - 140.847\n  - 41.643\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: 170\n"
  },
  {
    "path": "config/exchanges/JP-HR_JP-KN.yaml",
    "content": "capacity:\n  - -1900\n  - 1900\nlonlat:\n  - 136.13\n  - 35.57\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: -170\n"
  },
  {
    "path": "config/exchanges/JP-KN_JP-SK.yaml",
    "content": "capacity:\n  - -1400\n  - 1400\nlonlat:\n  - 134.89\n  - 33.95\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: -95\n"
  },
  {
    "path": "config/exchanges/JP-TH_JP-TK.yaml",
    "content": "capacity:\n  - -5150\n  - 5150\nlonlat:\n  - 140.16\n  - 37.08\nparsers:\n  exchange: occtonet.fetch_exchange\n  exchangeForecast: occtonet.fetch_exchange_forecast\nrotation: -150\n"
  },
  {
    "path": "config/exchanges/KZ_RU-1.yaml",
    "content": "lonlat:\n  - 56.884737\n  - 50.980185\nparsers:\n  exchange: RU.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/KZ_RU-2.yaml",
    "content": "lonlat:\n  - 75.002\n  - 53.797\nparsers:\n  exchange: RU.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/LS_ZA.yaml",
    "content": "lonlat:\n  - 27.454639\n  - -29.297917\nrotation: -87\n"
  },
  {
    "path": "config/exchanges/LT_LV.yaml",
    "content": "capacity:\n  - -1201\n  - 1334\nlonlat:\n  - 24.373981\n  - 56.287428\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/LT_PL.yaml",
    "content": "capacity:\n  - -500\n  - 500\nlonlat:\n  - 23.308307\n  - 54.247411\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/LT_RU-KGD.yaml",
    "content": "capacity:\n  - -2490\n  - 2490\nlonlat:\n  - 21.963913\n  - 55.080726\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -180\n"
  },
  {
    "path": "config/exchanges/LT_SE-SE4.yaml",
    "content": "capacity:\n  - -700\n  - 700\nlonlat:\n  - 18.847674\n  - 55.910978\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/LT_SE.yaml",
    "content": "lonlat:\n  - 18.847674\n  - 55.910978\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/LV_RU-1.yaml",
    "content": "capacity:\n  - -696\n  - 696\nlonlat:\n  - 27.7336\n  - 56.87436\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 45\n"
  },
  {
    "path": "config/exchanges/MD_RO.yaml",
    "content": "lonlat:\n  - 28.009764\n  - 47.003312\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: MD.fetch_exchange_forecast\nrotation: -120\n"
  },
  {
    "path": "config/exchanges/MD_UA.yaml",
    "content": "capacity:\n  - -700\n  - 700\nlonlat:\n  - 29.218978\n  - 47.646939\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: MD.fetch_exchange_forecast\nrotation: 50\n"
  },
  {
    "path": "config/exchanges/ME_RS.yaml",
    "content": "lonlat:\n  - 19.566302\n  - 43.242543\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 45\n"
  },
  {
    "path": "config/exchanges/ME_XK.yaml",
    "content": "lonlat:\n  - 20.265\n  - 42.784\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 135\n"
  },
  {
    "path": "config/exchanges/MK_RS.yaml",
    "content": "lonlat:\n  - 22.03925\n  - 42.31702\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/MK_XK.yaml",
    "content": "lonlat:\n  - 21.315\n  - 42.153\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/MN_RU-2.yaml",
    "content": "lonlat:\n  - 100.258756\n  - 51.721212\nparsers:\n  exchange: RU.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/MX_US-CAL-CISO.yaml",
    "content": "capacity:\n  - -400\n  - 800\nlonlat:\n  - -116.027\n  - 32.607\nparsers:\n  exchange: CENACE.fetch_exchange\nrotation: -10\n"
  },
  {
    "path": "config/exchanges/MX_US-TEX-ERCO.yaml",
    "content": "lonlat:\n  - -107.292\n  - 31.709\nparsers:\n  exchange: CENACE.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/MX_US.yaml",
    "content": "lonlat:\n  - -106.4843\n  - 31.7485\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/MY-WM_SG.yaml",
    "content": "capacity:\n  - -450\n  - 450\nlonlat:\n  - 103.539048\n  - 2.016154\nparsers:\n  exchange: GSO.fetch_exchange\nrotation: 155\n"
  },
  {
    "path": "config/exchanges/MY-WM_TH.yaml",
    "content": "capacity:\n  - -330\n  - 330\nlonlat:\n  - 101.454422\n  - 5.867743\nparsers:\n  exchange: GSO.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/MY_SG.yaml",
    "content": "capacity:\n  - -450\n  - 450\nlonlat:\n  - 103.539048\n  - 2.016154\nrotation: 155\n"
  },
  {
    "path": "config/exchanges/MY_TH.yaml",
    "content": "capacity:\n  - -330\n  - 330\nlonlat:\n  - 101.454422\n  - 5.867743\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/NA_ZA.yaml",
    "content": "lonlat:\n  - 18.512\n  - -28.893\nrotation: 165\n"
  },
  {
    "path": "config/exchanges/NA_ZM.yaml",
    "content": "lonlat:\n  - 24.2441\n  - -17.4922\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/NL_NO-NO2.yaml",
    "content": "capacity:\n  - -723\n  - 723\nlonlat:\n  - 5.795449\n  - 55.859727\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/NL_NO.yaml",
    "content": "capacity:\n  - -723\n  - 723\nlonlat:\n  - 5.795449\n  - 55.859727\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/NO-NO1_NO-NO2.yaml",
    "content": "capacity:\n  - -3500\n  - 2200\nlonlat:\n  - 9.3\n  - 59.844429\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -110\n"
  },
  {
    "path": "config/exchanges/NO-NO1_NO-NO3.yaml",
    "content": "capacity:\n  - -500\n  - 500\nlonlat:\n  - 9.533218\n  - 61.731596\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -45\n"
  },
  {
    "path": "config/exchanges/NO-NO1_NO-NO5.yaml",
    "content": "capacity:\n  - -3900\n  - 600\nlonlat:\n  - 8.3\n  - 61.132896\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/NO-NO1_SE-SE3.yaml",
    "content": "capacity:\n  - -2095\n  - 2145\nlonlat:\n  - 12.254138\n  - 61.008235\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/NO-NO2_NO-NO5.yaml",
    "content": "capacity:\n  - -600\n  - 500\nlonlat:\n  - 7.461\n  - 60.0\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -10\n"
  },
  {
    "path": "config/exchanges/NO-NO3_NO-NO4.yaml",
    "content": "capacity:\n  - -1200\n  - 400\nlonlat:\n  - 12.465132\n  - 64.745638\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 30\n"
  },
  {
    "path": "config/exchanges/NO-NO3_NO-NO5.yaml",
    "content": "_comment: https://umm.nordpoolgroup.com/#/messages/3355b9ad-9ef8-48bf-8743-4b11a1a3b350/1\ncapacity:\n  - -500\n  - 800\nlonlat:\n  - 7.1\n  - 61.194118\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 140\n"
  },
  {
    "path": "config/exchanges/NO-NO3_SE-SE2.yaml",
    "content": "capacity:\n  - -1000\n  - 600\nlonlat:\n  - 12.24842\n  - 63.462916\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/NO-NO4_RU-1.yaml",
    "content": "lonlat:\n  - 30.1437\n  - 69.52\nrotation: 120\n"
  },
  {
    "path": "config/exchanges/NO-NO4_SE-SE1.yaml",
    "content": "capacity:\n  - -600\n  - 700\nlonlat:\n  - 15.656\n  - 66.609\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 130\n"
  },
  {
    "path": "config/exchanges/NO-NO4_SE-SE2.yaml",
    "content": "capacity:\n  - -300\n  - 250\nlonlat:\n  - 14.051\n  - 64.913\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 130\n"
  },
  {
    "path": "config/exchanges/NO_RU-1.yaml",
    "content": "lonlat:\n  - 30.1437\n  - 69.52\nrotation: 120\n"
  },
  {
    "path": "config/exchanges/NO_SE.yaml",
    "content": "lonlat:\n  - 14.055\n  - 64.918\nrotation: 100\n"
  },
  {
    "path": "config/exchanges/PH-LU_PH-VI.yaml",
    "content": "lonlat:\n  - 124.178978\n  - 12.544171\nparsers:\n  exchange: IEMOP.fetch_exchange\n\nrotation: 150\n"
  },
  {
    "path": "config/exchanges/PH-MI_PH-VI.yaml",
    "content": "lonlat:\n  - 125.341644\n  - 9.877123\nparsers:\n  exchange: IEMOP.fetch_exchange\n\nrotation: -30\n"
  },
  {
    "path": "config/exchanges/PL_SE-SE4.yaml",
    "content": "capacity:\n  - -600\n  - 600\nlonlat:\n  - 15.969256\n  - 55.215172\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -20\n"
  },
  {
    "path": "config/exchanges/PL_SE.yaml",
    "content": "capacity:\n  - -600\n  - 600\nlonlat:\n  - 15.969256\n  - 55.215172\nrotation: -20\n"
  },
  {
    "path": "config/exchanges/PL_SK.yaml",
    "content": "lonlat:\n  - 20.614102\n  - 49.359467\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  shadowAuctionAtcDayAhead: JAO.fetch_shadow_auction_atc_day_ahead\n  maxBexDayAhead: JAO.fetch_core_max_bex_day_ahead\n  scheduledExchangesDayAhead: JAO.fetch_core_scheduled_exchanges_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/PL_UA.yaml",
    "content": "capacity:\n  - -235\n  - 235\nlonlat:\n  - 24.097224\n  - 50.664587\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/RO_RS.yaml",
    "content": "capacity:\n  - -1132\n  - 1132\nlonlat:\n  - 21.469049\n  - 44.947107\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -140\n"
  },
  {
    "path": "config/exchanges/RO_UA.yaml",
    "content": "capacity:\n  - -650\n  - 650\nlonlat:\n  - 24.821959\n  - 47.768595\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/RS_XK.yaml",
    "content": "lonlat:\n  - 21.231\n  - 43.011\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: -135\n"
  },
  {
    "path": "config/exchanges/RU-1_RU-2.yaml",
    "content": "lonlat:\n  - 70.735\n  - 56.263\nparsers:\n  exchange: RU.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/RU-1_UA-CR.yaml",
    "content": "lonlat:\n  - 36.6\n  - 45.25\nparsers:\n  exchange: RU.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/RU-1_UA.yaml",
    "content": "capacity:\n  - -3000\n  - 3000\nlonlat:\n  - 37.730064\n  - 50.089897\nparsers:\n  exchange: RU.fetch_exchange\nrotation: -135\n"
  },
  {
    "path": "config/exchanges/SE-SE1_SE-SE2.yaml",
    "content": "capacity:\n  - -3300\n  - 3300\nlonlat:\n  - 17.869\n  - 65.469\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 205\n"
  },
  {
    "path": "config/exchanges/SE-SE2_SE-SE3.yaml",
    "content": "capacity:\n  - -7300\n  - 7300\nlonlat:\n  - 14.804\n  - 61.42\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/SE-SE3_SE-SE4.yaml",
    "content": "capacity:\n  - -2000\n  - 5400\nlonlat:\n  - 14.5\n  - 57.2\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  maxBexDayAhead: JAO.fetch_nordic_max_bex_day_ahead\n  maxBflowDayAhead: JAO.fetch_nordic_max_bflow_day_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/SK_UA.yaml",
    "content": "capacity:\n  - -789\n  - 789\nlonlat:\n  - 22.384512\n  - 48.820578\nparsers:\n  exchange: ENTSOE.fetch_exchange\n  exchangeCapacityForecastDayAhead: ENTSOE.fetch_exchange_capacity_forecasts_day_ahead\n  exchangeCapacityForecastWeekAhead: ENTSOE.fetch_exchange_capacity_forecasts_week_ahead\n  exchangeCapacityForecastMonthAhead: ENTSOE.fetch_exchange_capacity_forecasts_month_ahead\n  exchangeForecast: ENTSOE.fetch_exchange_forecast\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/US-CAL-BANC_US-CAL-CISO.yaml",
    "content": "lonlat:\n  - -121.41\n  - 38.776\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -15\n"
  },
  {
    "path": "config/exchanges/US-CAL-BANC_US-CAL-TIDC.yaml",
    "content": "lonlat:\n  - -121.25\n  - 37.48\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 165\n"
  },
  {
    "path": "config/exchanges/US-CAL-BANC_US-NW-BPAT.yaml",
    "content": "lonlat:\n  - -122.75\n  - 41.28\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 145\n"
  },
  {
    "path": "config/exchanges/US-CAL-CISO_US-CAL-IID.yaml",
    "content": "lonlat:\n  - -116\n  - 34\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/US-CAL-CISO_US-CAL-LDWP.yaml",
    "content": "lonlat:\n  - -118.23\n  - 36.6\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/US-CAL-CISO_US-CAL-TIDC.yaml",
    "content": "lonlat:\n  - -114.3\n  - 34.39\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 40\n"
  },
  {
    "path": "config/exchanges/US-CAL-CISO_US-NW-BPAT.yaml",
    "content": "lonlat:\n  - -123.7\n  - 41.42\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 160\n"
  },
  {
    "path": "config/exchanges/US-CAL-CISO_US-NW-NEVP.yaml",
    "content": "lonlat:\n  - -118.7\n  - 38.1\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -135\n"
  },
  {
    "path": "config/exchanges/US-CAL-CISO_US-NW-PACW.yaml",
    "content": "lonlat:\n  - -121.01188726250551\n  - 40.351243277236364\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -17\n"
  },
  {
    "path": "config/exchanges/US-CAL-CISO_US-SW-AZPS.yaml",
    "content": "lonlat:\n  - -114.2\n  - 34.18\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -50\n"
  },
  {
    "path": "config/exchanges/US-CAL-CISO_US-SW-SRP.yaml",
    "content": "lonlat:\n  - -114.5\n  - 33.7\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -67\n"
  },
  {
    "path": "config/exchanges/US-CAL-CISO_US-SW-WALC.yaml",
    "content": "lonlat:\n  - -114.6\n  - 33.42\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -35\n"
  },
  {
    "path": "config/exchanges/US-CAL-IID_US-SW-AZPS.yaml",
    "content": "lonlat:\n  - -114.53\n  - 32.88\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -80\n"
  },
  {
    "path": "config/exchanges/US-CAL-IID_US-SW-WALC.yaml",
    "content": "lonlat:\n  - -114.62\n  - 33.12\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -125\n"
  },
  {
    "path": "config/exchanges/US-CAL-LDWP_US-NW-BPAT.yaml",
    "content": "lonlat:\n  - -118.43\n  - 37.18\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 140\n"
  },
  {
    "path": "config/exchanges/US-CAL-LDWP_US-NW-NEVP.yaml",
    "content": "lonlat:\n  - -117.98\n  - 36.755\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 40\n"
  },
  {
    "path": "config/exchanges/US-CAL-LDWP_US-NW-PACE.yaml",
    "content": "lonlat:\n  - -117.65\n  - 36.4\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -121\n"
  },
  {
    "path": "config/exchanges/US-CAL-LDWP_US-SW-AZPS.yaml",
    "content": "lonlat:\n  - -118.235\n  - 34.05\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -70\n"
  },
  {
    "path": "config/exchanges/US-CAL-LDWP_US-SW-WALC.yaml",
    "content": "lonlat:\n  - -117.74\n  - 36.18\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -45\n"
  },
  {
    "path": "config/exchanges/US-CAR-CPLE_US-CAR-DUK.yaml",
    "content": "lonlat:\n  - -80.7699\n  - 34.37724\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -81\n"
  },
  {
    "path": "config/exchanges/US-CAR-CPLE_US-CAR-SC.yaml",
    "content": "lonlat:\n  - -78.83359112529105\n  - 33.69356865349944\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -122\n"
  },
  {
    "path": "config/exchanges/US-CAR-CPLE_US-CAR-SCEG.yaml",
    "content": "lonlat:\n  - -80.86966\n  - 34.18231\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -120\n"
  },
  {
    "path": "config/exchanges/US-CAR-CPLE_US-CAR-YAD.yaml",
    "content": "lonlat:\n  - -80.115297318\n  - 35.297960281\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -77\n"
  },
  {
    "path": "config/exchanges/US-CAR-CPLE_US-MIDA-PJM.yaml",
    "content": "lonlat:\n  - -76.4004199999999\n  - 36.30089\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -30\n"
  },
  {
    "path": "config/exchanges/US-CAR-CPLW_US-CAR-DUK.yaml",
    "content": "lonlat:\n  - -81.90756\n  - 36.27862\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -84\n"
  },
  {
    "path": "config/exchanges/US-CAR-CPLW_US-MIDA-PJM.yaml",
    "content": "lonlat:\n  - -81.90756\n  - 36.27862\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -155\n"
  },
  {
    "path": "config/exchanges/US-CAR-CPLW_US-TEN-TVA.yaml",
    "content": "lonlat:\n  - -83.31717\n  - 35.89099\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -94\n"
  },
  {
    "path": "config/exchanges/US-CAR-DUK_US-CAR-SC.yaml",
    "content": "lonlat:\n  - -82.13578916749756\n  - 34.03071845039919\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -37\n"
  },
  {
    "path": "config/exchanges/US-CAR-DUK_US-CAR-SCEG.yaml",
    "content": "lonlat:\n  - -80.82555736088426\n  - 34.26848609706126\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/US-CAR-DUK_US-CAR-YAD.yaml",
    "content": "lonlat:\n  - -80.0587501529999\n  - 35.689912796\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/US-CAR-DUK_US-MIDA-PJM.yaml",
    "content": "lonlat:\n  - -78.45649\n  - 36.5425100000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -175\n"
  },
  {
    "path": "config/exchanges/US-CAR-DUK_US-SE-SEPA.yaml",
    "content": "lonlat:\n  - -82.55661\n  - 33.94522\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -140\n"
  },
  {
    "path": "config/exchanges/US-CAR-DUK_US-SE-SOCO.yaml",
    "content": "lonlat:\n  - -82.55661\n  - 33.94522\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -128\n"
  },
  {
    "path": "config/exchanges/US-CAR-DUK_US-TEN-TVA.yaml",
    "content": "lonlat:\n  - -84.32173\n  - 34.98811\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -92\n"
  },
  {
    "path": "config/exchanges/US-CAR-SCEG_US-SE-SEPA.yaml",
    "content": "lonlat:\n  - -82.50397837180677\n  - 33.93362812571167\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -122\n"
  },
  {
    "path": "config/exchanges/US-CAR-SCEG_US-SE-SOCO.yaml",
    "content": "lonlat:\n  - -81.11441\n  - 32.11412\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -104\n"
  },
  {
    "path": "config/exchanges/US-CAR-SC_US-CAR-SCEG.yaml",
    "content": "lonlat:\n  - -81.0064260779999\n  - 32.3061781770001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -116\n"
  },
  {
    "path": "config/exchanges/US-CAR-SC_US-SE-SEPA.yaml",
    "content": "lonlat:\n  - -81.84175369226524\n  - 33.26822148267869\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -121\n"
  },
  {
    "path": "config/exchanges/US-CAR-SC_US-SE-SOCO.yaml",
    "content": "lonlat:\n  - -81.59124438556297\n  - 33.04117482449629\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -107\n"
  },
  {
    "path": "config/exchanges/US-CENT-SPA_US-CENT-SWPP.yaml",
    "content": "lonlat:\n  - -97.380583\n  - 35.030009\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -62\n"
  },
  {
    "path": "config/exchanges/US-CENT-SPA_US-MIDW-AECI.yaml",
    "content": "lonlat:\n  - -90.467778\n  - 36.800658\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -52\n"
  },
  {
    "path": "config/exchanges/US-CENT-SPA_US-MIDW-MISO.yaml",
    "content": "lonlat:\n  - -90.75005\n  - 36.2680700000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -7\n"
  },
  {
    "path": "config/exchanges/US-CENT-SWPP_US-MIDW-AECI.yaml",
    "content": "lonlat:\n  - -94.608546\n  - 38.596152\nparsers:\n  exchange: US_SPP.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/US-CENT-SWPP_US-MIDW-MISO.yaml",
    "content": "lonlat:\n  - -96.0\n  - 43.9\nparsers:\n  exchange: US_SPP.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/US-CENT-SWPP_US-NW-PSCO.yaml",
    "content": "lonlat:\n  - -102.6\n  - 37.8\nparsers:\n  exchange: US_SPP.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/US-CENT-SWPP_US-NW-WACM.yaml",
    "content": "lonlat:\n  - -100.2\n  - 42.6728426538958\nparsers:\n  exchange: US_SPP.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/US-CENT-SWPP_US-NW-WAUW.yaml",
    "content": "lonlat:\n  - -103.0\n  - 45.505475\nparsers:\n  exchange: US_SPP.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/US-CENT-SWPP_US-SW-EPE.yaml",
    "content": "lonlat:\n  - -104.81455\n  - 32.53418\nparsers:\n  exchange: US_SPP.fetch_exchange\nrotation: -120\n"
  },
  {
    "path": "config/exchanges/US-CENT-SWPP_US-SW-PNM.yaml",
    "content": "lonlat:\n  - -104.00779609494954\n  - 36.97355236583146\nparsers:\n  exchange: US_SPP.fetch_exchange\nrotation: -129\n"
  },
  {
    "path": "config/exchanges/US-CENT-SWPP_US-TEX-ERCO.yaml",
    "content": "lonlat:\n  - -100.5\n  - 36.0578100000001\nparsers:\n  exchange: US_SPP.fetch_exchange\nrotation: 180\n"
  },
  {
    "path": "config/exchanges/US-FLA-FMPP_US-FLA-FPC.yaml",
    "content": "lonlat:\n  - -81.4234908669999\n  - 28.6083593760001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -57\n"
  },
  {
    "path": "config/exchanges/US-FLA-FMPP_US-FLA-FPL.yaml",
    "content": "lonlat:\n  - -80.13694\n  - 26.97092\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -176\n"
  },
  {
    "path": "config/exchanges/US-FLA-FMPP_US-FLA-JEA.yaml",
    "content": "lonlat:\n  - -81.72209\n  - 30.1911000000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -46\n"
  },
  {
    "path": "config/exchanges/US-FLA-FMPP_US-FLA-TEC.yaml",
    "content": "lonlat:\n  - -81.959318912\n  - 28.2610770690001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -100\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPC_US-FLA-FPL.yaml",
    "content": "lonlat:\n  - -80.88566\n  - 26.95883\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -32\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPC_US-FLA-GVL.yaml",
    "content": "lonlat:\n  - -82.05551939971254\n  - 29.50778681974566\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -7\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPC_US-FLA-SEC.yaml",
    "content": "lonlat:\n  - -80.6775013747971\n  - 27.13487858194975\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -62\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPC_US-FLA-TAL.yaml",
    "content": "lonlat:\n  - -84.384234\n  - 30.5538270000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -50\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPC_US-FLA-TEC.yaml",
    "content": "lonlat:\n  - -82.1267528329999\n  - 28.243184474\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -4\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPC_US-SE-SOCO.yaml",
    "content": "lonlat:\n  - -85.49711888213565\n  - 30.09033501732437\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -37\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPL_US-FLA-GVL.yaml",
    "content": "lonlat:\n  - -82.48014491617691\n  - 29.932992988698576\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -23\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPL_US-FLA-HST.yaml",
    "content": "lonlat:\n  - -80.1213099999999\n  - 25.9004800000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 156\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPL_US-FLA-JEA.yaml",
    "content": "lonlat:\n  - -81.72209\n  - 30.1911000000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -37\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPL_US-FLA-SEC.yaml",
    "content": "lonlat:\n  - -82.15157250929833\n  - 27.64566722879262\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -38\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPL_US-FLA-TEC.yaml",
    "content": "lonlat:\n  - -82.083444633\n  - 27.64265563\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -53\n"
  },
  {
    "path": "config/exchanges/US-FLA-FPL_US-SE-SOCO.yaml",
    "content": "lonlat:\n  - -81.93616\n  - 30.8272000000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -36\n"
  },
  {
    "path": "config/exchanges/US-FLA-JEA_US-FLA-SEC.yaml",
    "content": "lonlat:\n  - -84.5694759325146\n  - 30.01138369316129\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -36\n"
  },
  {
    "path": "config/exchanges/US-FLA-SEC_US-FLA-TEC.yaml",
    "content": "lonlat:\n  - -81.817562\n  - 27.57663\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -23\n"
  },
  {
    "path": "config/exchanges/US-FLA-TAL_US-SE-SOCO.yaml",
    "content": "lonlat:\n  - -84.234874\n  - 30.623546\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -22\n"
  },
  {
    "path": "config/exchanges/US-MIDA-PJM_US-MIDW-LGEE.yaml",
    "content": "lonlat:\n  - -84.69935455639735\n  - 37.891105962229595\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -110\n"
  },
  {
    "path": "config/exchanges/US-MIDA-PJM_US-MIDW-MISO.yaml",
    "content": "lonlat:\n  - -84.8\n  - 39.21487\nparsers:\n  exchange: US_PJM.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/US-MIDA-PJM_US-NY-NYIS.yaml",
    "content": "lonlat:\n  - -77.069\n  - 42.0\nparsers:\n  exchange: US_NY.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/US-MIDA-PJM_US-TEN-TVA.yaml",
    "content": "lonlat:\n  - -81.64647784\n  - 36.611567138\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -123\n"
  },
  {
    "path": "config/exchanges/US-MIDW-AECI_US-MIDW-MISO.yaml",
    "content": "lonlat:\n  - -92.179147211\n  - 40.8997104170001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -142\n"
  },
  {
    "path": "config/exchanges/US-MIDW-AECI_US-TEN-TVA.yaml",
    "content": "lonlat:\n  - -89.21365\n  - 36.58014\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -66\n"
  },
  {
    "path": "config/exchanges/US-MIDW-LGEE_US-MIDW-MISO.yaml",
    "content": "lonlat:\n  - -87.3654617889999\n  - 37.5329061090001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -63\n"
  },
  {
    "path": "config/exchanges/US-MIDW-LGEE_US-TEN-TVA.yaml",
    "content": "lonlat:\n  - -83.9195412619999\n  - 36.587380029\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -151\n"
  },
  {
    "path": "config/exchanges/US-MIDW-MISO_US-SE-SOCO.yaml",
    "content": "lonlat:\n  - -88.13743446985477\n  - 30.31061246790728\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -37\n"
  },
  {
    "path": "config/exchanges/US-MIDW-MISO_US-TEN-TVA.yaml",
    "content": "lonlat:\n  - -89.56580767010422\n  - 36.56191297306488\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -39\n"
  },
  {
    "path": "config/exchanges/US-NE-ISNE_US-NY-NYIS.yaml",
    "content": "lonlat:\n  - -73.279\n  - 42.739\nparsers:\n  exchange: US_NY.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/US-NW-AVA_US-NW-BPAT.yaml",
    "content": "lonlat:\n  - -119.95299735574476\n  - 46.760318687994754\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -26\n"
  },
  {
    "path": "config/exchanges/US-NW-AVA_US-NW-CHPD.yaml",
    "content": "lonlat:\n  - -120.0047663015552\n  - 47.32002534773005\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -78\n"
  },
  {
    "path": "config/exchanges/US-NW-AVA_US-NW-GCPD.yaml",
    "content": "lonlat:\n  - -119.93263500986485\n  - 46.673460082726436\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -87\n"
  },
  {
    "path": "config/exchanges/US-NW-AVA_US-NW-IPCO.yaml",
    "content": "lonlat:\n  - -117.71303872767247\n  - 45.65847980648419\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -11\n"
  },
  {
    "path": "config/exchanges/US-NW-AVA_US-NW-NWMT.yaml",
    "content": "lonlat:\n  - -114.38878\n  - 45.88228\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -87\n"
  },
  {
    "path": "config/exchanges/US-NW-AVA_US-NW-PACW.yaml",
    "content": "lonlat:\n  - -119.93263500986485\n  - 46.673460082726436\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -124\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-CHPD.yaml",
    "content": "lonlat:\n  - -121.1\n  - 48\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 110\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-DOPD.yaml",
    "content": "lonlat:\n  - -120.0047663015552\n  - 47.32002534773005\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -48\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-GCPD.yaml",
    "content": "lonlat:\n  - -120.0047663015552\n  - 47.32002534773005\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -56\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-GRID.yaml",
    "content": "lonlat:\n  - -118.69791\n  - 45.34516\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -73\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-IPCO.yaml",
    "content": "lonlat:\n  - -114.6944668106769\n  - 45.19822083626128\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -153\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-NEVP.yaml",
    "content": "lonlat:\n  - -119.31738486687132\n  - 41.99427891980891\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -174\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-NWMT.yaml",
    "content": "lonlat:\n  - -111.06202\n  - 46.1928\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -110\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-PACW.yaml",
    "content": "lonlat:\n  - -124.04192\n  - 42.38771\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -96\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-PGE.yaml",
    "content": "lonlat:\n  - -123.30386139833492\n  - 45.58808586698683\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -85\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-PSEI.yaml",
    "content": "lonlat:\n  - -123.1\n  - 47\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 90\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-SCL.yaml",
    "content": "lonlat:\n  - -122.646129\n  - 47.587609\n\nrotation: 100\n\nparsers:\n  exchange: EIA.fetch_exchange\n"
  },
  {
    "path": "config/exchanges/US-NW-BPAT_US-NW-TPWR.yaml",
    "content": "lonlat:\n  - -123.45\n  - 47.5\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 108\n"
  },
  {
    "path": "config/exchanges/US-NW-CHPD_US-NW-DOPD.yaml",
    "content": "lonlat:\n  - -120\n  - 48\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 70\n"
  },
  {
    "path": "config/exchanges/US-NW-CHPD_US-NW-PSEI.yaml",
    "content": "lonlat:\n  - -120.838406192\n  - 48.550577006\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -45\n"
  },
  {
    "path": "config/exchanges/US-NW-GCPD_US-NW-PACW.yaml",
    "content": "lonlat:\n  - -119.629754\n  - 46.6440040000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -151\n"
  },
  {
    "path": "config/exchanges/US-NW-GCPD_US-NW-PSEI.yaml",
    "content": "lonlat:\n  - -120.042866\n  - 47.073453\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -80\n"
  },
  {
    "path": "config/exchanges/US-NW-IPCO_US-NW-NEVP.yaml",
    "content": "lonlat:\n  - -114.81233\n  - 42.0014600000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -179\n"
  },
  {
    "path": "config/exchanges/US-NW-IPCO_US-NW-NWMT.yaml",
    "content": "lonlat:\n  - -114.35707\n  - 46.66791\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -116\n"
  },
  {
    "path": "config/exchanges/US-NW-IPCO_US-NW-PACE.yaml",
    "content": "lonlat:\n  - -112.1088976323217\n  - 42.856560150604174\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -76\n"
  },
  {
    "path": "config/exchanges/US-NW-IPCO_US-NW-PACW.yaml",
    "content": "lonlat:\n  - -117.89347434398796\n  - 45.891672150043\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -85\n"
  },
  {
    "path": "config/exchanges/US-NW-NEVP_US-NW-PACE.yaml",
    "content": "lonlat:\n  - -112.65097215548731\n  - 41.06900007151519\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -111\n"
  },
  {
    "path": "config/exchanges/US-NW-NEVP_US-SW-WALC.yaml",
    "content": "lonlat:\n  - -114.7\n  - 35.15\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/US-NW-NWMT_US-NW-PACE.yaml",
    "content": "lonlat:\n  - -112.76591463911802\n  - 43.99253582711845\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -8\n"
  },
  {
    "path": "config/exchanges/US-NW-NWMT_US-NW-WAUW.yaml",
    "content": "lonlat:\n  - -104.04352440552584\n  - 46.14677881539246\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -96\n"
  },
  {
    "path": "config/exchanges/US-NW-PACE_US-NW-PACW.yaml",
    "content": "lonlat:\n  - -113.7981\n  - 43.5714\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -80\n"
  },
  {
    "path": "config/exchanges/US-NW-PACE_US-NW-WACM.yaml",
    "content": "lonlat:\n  - -107.91036406436295\n  - 44.99994676910954\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -80\n"
  },
  {
    "path": "config/exchanges/US-NW-PACE_US-SW-AZPS.yaml",
    "content": "lonlat:\n  - -110.75073\n  - 34.5\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -159\n"
  },
  {
    "path": "config/exchanges/US-NW-PACW_US-NW-PGE.yaml",
    "content": "lonlat:\n  - -122.91755947016952\n  - 45.703129646532744\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -45\n"
  },
  {
    "path": "config/exchanges/US-NW-PSCO_US-NW-WACM.yaml",
    "content": "lonlat:\n  - -106.148241394\n  - 38.632944407\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -135\n"
  },
  {
    "path": "config/exchanges/US-NW-PSCO_US-SW-PNM.yaml",
    "content": "lonlat:\n  - -105.17399605\n  - 36.995179334\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 0\n"
  },
  {
    "path": "config/exchanges/US-NW-PSEI_US-NW-SCL.yaml",
    "content": "lonlat:\n  - -122.336493\n  - 47.8\n\nrotation: 180\n\nparsers:\n  exchange: EIA.fetch_exchange\n"
  },
  {
    "path": "config/exchanges/US-NW-PSEI_US-NW-TPWR.yaml",
    "content": "lonlat:\n  - -122.5\n  - 47\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: 42\n"
  },
  {
    "path": "config/exchanges/US-NW-WACM_US-NW-WAUW.yaml",
    "content": "lonlat:\n  - -107.17225649844661\n  - 45.91038621067434\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -24\n"
  },
  {
    "path": "config/exchanges/US-NW-WACM_US-SW-AZPS.yaml",
    "content": "lonlat:\n  - -111.41321\n  - 37.00125\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -133\n"
  },
  {
    "path": "config/exchanges/US-NW-WACM_US-SW-PNM.yaml",
    "content": "lonlat:\n  - -105.17399632733049\n  - 36.99521455070129\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -163\n"
  },
  {
    "path": "config/exchanges/US-NW-WACM_US-SW-WALC.yaml",
    "content": "lonlat:\n  - -106.05838\n  - 36.29707\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -110\n"
  },
  {
    "path": "config/exchanges/US-SE-SEPA_US-SE-SOCO.yaml",
    "content": "lonlat:\n  - -85.02928\n  - 31.51865\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -11\n"
  },
  {
    "path": "config/exchanges/US-SE-SOCO_US-TEN-TVA.yaml",
    "content": "lonlat:\n  - -89.71069775529106\n  - 32.63725369923949\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -33\n"
  },
  {
    "path": "config/exchanges/US-SW-AZPS_US-SW-PNM.yaml",
    "content": "lonlat:\n  - -109.803538951\n  - 35.1965674240001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -99\n"
  },
  {
    "path": "config/exchanges/US-SW-AZPS_US-SW-SRP.yaml",
    "content": "lonlat:\n  - -112.12569\n  - 34.0440100000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -145\n"
  },
  {
    "path": "config/exchanges/US-SW-AZPS_US-SW-TEPC.yaml",
    "content": "lonlat:\n  - -110.891848119\n  - 32.405763591\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -61\n"
  },
  {
    "path": "config/exchanges/US-SW-AZPS_US-SW-WALC.yaml",
    "content": "lonlat:\n  - -114.35\n  - 32.71\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -125\n"
  },
  {
    "path": "config/exchanges/US-SW-EPE_US-SW-PNM.yaml",
    "content": "lonlat:\n  - -106.37266\n  - 33.4798\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -33\n"
  },
  {
    "path": "config/exchanges/US-SW-EPE_US-SW-TEPC.yaml",
    "content": "lonlat:\n  - -108.21001111984772\n  - 31.790249502661492\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -69\n"
  },
  {
    "path": "config/exchanges/US-SW-PNM_US-SW-SRP.yaml",
    "content": "lonlat:\n  - -110.765242868\n  - 33.711766337\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/US-SW-PNM_US-SW-TEPC.yaml",
    "content": "lonlat:\n  - -110.765242868\n  - 33.711766337\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -90\n"
  },
  {
    "path": "config/exchanges/US-SW-SRP_US-SW-TEPC.yaml",
    "content": "lonlat:\n  - -112.97153193543504\n  - 33.95958750828914\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -42\n"
  },
  {
    "path": "config/exchanges/US-SW-SRP_US-SW-WALC.yaml",
    "content": "lonlat:\n  - -112.12569\n  - 34.0440100000001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -40\n"
  },
  {
    "path": "config/exchanges/US-SW-TEPC_US-SW-WALC.yaml",
    "content": "lonlat:\n  - -113.939531177\n  - 36.1699836540001\nparsers:\n  exchange: EIA.fetch_exchange\nrotation: -38\n"
  },
  {
    "path": "config/retired_zones/CA-NL-LB.yaml",
    "content": "bounding_box:\n  - - -68.3084780847808\n    - 50.91899500027512\n  - - -55.14755647556471\n    - 60.80458831011339\ncountry: CA\nregion: Americas\ntimezone: America/St_Johns\n"
  },
  {
    "path": "config/retired_zones/CA-NL-NF.yaml",
    "content": "_comment: 5428 MW of hydro is Churchill Falls Generating Station, electricity from\n  which is mostly sold to Quebec and might not appear on balance sheets\nbounding_box:\n  - - -59.89879398793984\n    - 46.117712095699915\n  - - -52.12712627126267\n    - 53.850894675202525\ncountry: CA\nregion: Americas\ntimezone: America/St_Johns\n"
  },
  {
    "path": "config/retired_zones/ES-CN-FVLZ.yaml",
    "content": "bounding_box:\n  - - -15.007069464999915\n    - 27.55068594000015\n  - - -12.91779537699989\n    - 29.74331289300015\ncontributors:\n  - hectorespert\n  - systemcatch\n  - silimotion\ncountry: ES\nemissionFactors:\n  direct:\n    battery discharge:\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 791.5967283263532\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 761.5969944975305\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 778.3961748842161\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 749.5381775116632\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    hydro discharge:\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 791.5967283263532\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 761.5969944975305\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 778.3961748842161\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 749.5381775116632\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 724.189\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 722.096\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 722.005\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 709.958\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 701.966\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 726.59\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 692.712\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 692.082\n  lifecycle:\n    battery discharge:\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 1015.78\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 1009.52\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 999.7\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 959.28\n      - datetime: '2022-01-01'\n        source: Electricity Maps, 2022 average\n        value: 992.87\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 1014.01\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 1015.78\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 1009.52\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 999.7\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 959.28\n      - datetime: '2022-01-01'\n        source: Electricity Maps, 2022 average\n        value: 992.87\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 1014.01\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 968.189\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 966.096\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 966.005\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 953.958\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 945.966\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 970.59\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 936.712\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 936.082\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.059845265758820286\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8745225923363522\n        solar: 0.017023376475788467\n        unknown: 0.0\n        wind: 0.04860864453235687\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0001223858045808803\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8959703727820618\n        solar: 0.017982572537471476\n        unknown: 0.0\n        wind: 0.08592421519280115\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8871711242401354\n        solar: 0.021141820961495653\n        unknown: 0.0\n        wind: 0.0916870389490779\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.850834111187809\n        solar: 0.02154941889410463\n        unknown: 0.0\n        wind: 0.1276165615839028\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8467165136435377\n        solar: 0.02423214798360807\n        unknown: 0.0\n        wind: 0.12905134497805984\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8649911188615803\n        solar: 0.02338584139034943\n        unknown: 0.0\n        wind: 0.11162283678831304\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Canary\n"
  },
  {
    "path": "config/retired_zones/IN-AP.yaml",
    "content": "bounding_box:\n  - - 76.21948286304365\n    - 12.131916612162016\n  - - 85.28003991000008\n    - 20.391292628951703\ncapacity:\n  biomass: 506.9\n  coal: 11590\n  gas: 4898.54\n  hydro: 1610\n  nuclear: 0\n  oil: 36.8\n  solar: 4254.3\n  wind: 4096.7\ncontributors:\n  - hectorespert\n  - gopikrishna1793\nemissionFactors:\n  direct:\n    battery discharge:\n      - datetime: '2017-01-01'\n        source: electricityMap, 2017 average\n        value: 527.6148730344466\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 493.92271880824643\n      - datetime: '2019-01-01'\n        source: electricityMap, 2019 average\n        value: 497.1598334804869\n      - datetime: '2020-01-01'\n        source: electricityMap, 2020 average\n        value: 476.34868226687826\n      - datetime: '2021-01-01'\n        source: electricityMap, 2021 average\n        value: 438.39251136007215\n    hydro discharge:\n      - datetime: '2017-01-01'\n        source: electricityMap, 2017 average\n        value: 527.6148730344466\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 493.92271880824643\n      - datetime: '2019-01-01'\n        source: electricityMap, 2019 average\n        value: 497.1598334804869\n      - datetime: '2020-01-01'\n        source: electricityMap, 2020 average\n        value: 476.34868226687826\n      - datetime: '2021-01-01'\n        source: electricityMap, 2021 average\n        value: 438.39251136007215\n  lifecycle:\n    battery discharge:\n      - datetime: '2017-01-01'\n        source: electricityMap, 2017 average\n        value: 614.5380156918941\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 568.8096107384749\n      - datetime: '2019-01-01'\n        source: electricityMap, 2019 average\n        value: 571.4566047121974\n      - datetime: '2020-01-01'\n        source: electricityMap, 2020 average\n        value: 561.452892236501\n      - datetime: '2021-01-01'\n        source: electricityMap, 2021 average\n        value: 524.161418185502\n    hydro discharge:\n      - datetime: '2017-01-01'\n        source: electricityMap, 2017 average\n        value: 614.5380156918941\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 568.8096107384749\n      - datetime: '2019-01-01'\n        source: electricityMap, 2019 average\n        value: 571.4566047121974\n      - datetime: '2020-01-01'\n        source: electricityMap, 2020 average\n        value: 561.452892236501\n      - datetime: '2021-01-01'\n        source: electricityMap, 2021 average\n        value: 524.161418185502\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: electricityMap, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3148836641438855\n        gas: 0.017142271517798735\n        geothermal: 0.0\n        hydro: 0.05540336056454704\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05825079408079329\n        unknown: 0.49103869480882173\n        wind: 0.06403472514753962\n    - _source: electricityMap, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.36877179270684796\n        gas: 0.017291806321732137\n        geothermal: 0.0\n        hydro: 0.051108106663930716\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.06402375187148422\n        unknown: 0.3604488057058947\n        wind: 0.13835627769355022\n    - _source: electricityMap, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.380030685578371\n        gas: 0.013073508437479205\n        geothermal: 0.0\n        hydro: 0.043455484240912\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0688062605154022\n        unknown: 0.35391185410744574\n        wind: 0.1407221734942265\n    - _source: electricityMap, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.20471870498563047\n        gas: 0.1395445056597702\n        geothermal: 0.0\n        hydro: 0.13919694080540992\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05521178149275248\n        unknown: 0.40278846845675453\n        wind: 0.05952510785419443\nflag_file_name: in.png\nparsers:\n  consumption: IN_AP.fetch_consumption\n  production: IN_AP.fetch_production\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-AR.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 0\n  hydro: 1115\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-AS.yaml",
    "content": "capacity:\n  coal: 750\n  gas: 620.36\n  hydro: 350\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-BR.yaml",
    "content": "capacity:\n  coal: 8400\n  gas: 0\n  hydro: 0\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-CT.yaml",
    "content": "bounding_box:\n  - - 79.76055870971675\n    - 17.276072903441786\n  - - 84.85333214706088\n    - 24.640232245122036\ncapacity:\n  biomass: 269.9\n  coal: 23688\n  gas: 0\n  hydro: 120\n  nuclear: 0\n  oil: 0\n  solar: 252.5\n  wind: 0\ncontributors:\n  - hectorespert\n  - gopikrishna1793\nemissionFactors:\n  direct:\n    battery discharge:\n      - datetime: '2017-01-01'\n        source: electricityMap, 2017 average\n        value: 757.8138856382876\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 752.4566706155235\n      - datetime: '2019-01-01'\n        source: electricityMap, 2019 average\n        value: 752.7307934440681\n      - datetime: '2020-01-01'\n        source: electricityMap, 2020 average\n        value: 743.5956498164057\n      - datetime: '2021-01-01'\n        source: electricityMap, 2021 average\n        value: 748.2915362313788\n    hydro discharge:\n      - datetime: '2017-01-01'\n        source: electricityMap, 2017 average\n        value: 757.8138856382876\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 752.4566706155235\n      - datetime: '2019-01-01'\n        source: electricityMap, 2019 average\n        value: 752.7307934440681\n      - datetime: '2020-01-01'\n        source: electricityMap, 2020 average\n        value: 743.5956498164057\n      - datetime: '2021-01-01'\n        source: electricityMap, 2021 average\n        value: 748.2915362313788\n  lifecycle:\n    battery discharge:\n      - datetime: '2017-01-01'\n        source: electricityMap, 2017 average\n        value: 817.71027272355\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 812.099317183112\n      - datetime: '2019-01-01'\n        source: electricityMap, 2019 average\n        value: 812.3864676439066\n      - datetime: '2020-01-01'\n        source: electricityMap, 2020 average\n        value: 802.8186332708017\n      - datetime: '2021-01-01'\n        source: electricityMap, 2021 average\n        value: 807.7369587624755\n    hydro discharge:\n      - datetime: '2017-01-01'\n        source: electricityMap, 2017 average\n        value: 817.71027272355\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 812.099317183112\n      - datetime: '2019-01-01'\n        source: electricityMap, 2019 average\n        value: 812.3864676439066\n      - datetime: '2020-01-01'\n        source: electricityMap, 2020 average\n        value: 802.8186332708017\n      - datetime: '2021-01-01'\n        source: electricityMap, 2021 average\n        value: 807.7369587624755\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: electricityMap, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.997123481622905\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0028764676491840934\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: electricityMap, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9900538509442514\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.009925374952453984\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: electricityMap, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9904352631631581\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.009564720011031123\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: electricityMap, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9784153040384125\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.021584685632446917\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: electricityMap, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9845941382531963\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.015405860608830542\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nflag_file_name: in.png\nparsers:\n  consumption: IN_CT.fetch_consumption\n  production: IN_CT.fetch_production\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-DL.yaml",
    "content": "bounding_box:\n  - - 76.3336877786681\n    - 27.932605902840095\n  - - 77.83753299275344\n    - 29.382087511129754\ncapacity:\n  biomass: 52\n  coal: 0\n  gas: 2208.4\n  hydro: 0\n  nuclear: 0\n  oil: 0\n  solar: 193\n  wind: 0\ncontributors:\n  - hectorespert\n  - gopikrishna1793\ncountry: IN\ncountry_name: India\ncurrency: INR\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05727858148061005\n        coal: 0.17710005710979462\n        gas: 0.7656214110547845\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.3730051234790363\n        coal: 0.19533276044865067\n        gas: 0.43166214060735764\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05286220281446004\n        coal: 0.0\n        gas: 0.947137868782623\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.055193330825883534\n        coal: 0.0\n        gas: 0.9448067313625305\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06769443337999619\n        coal: 0.0\n        gas: 0.9323055233828217\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1181515449294343\n        coal: 0.0\n        gas: 0.8818484708683783\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.13414176998747177\n        coal: 0.0\n        gas: 0.8658582300125283\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: IN_DL.fetch_consumption\n  production: IN_DL.fetch_production\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Unknown\n"
  },
  {
    "path": "config/retired_zones/IN-DN.yaml",
    "content": "flag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-GA.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 48\n  hydro: 0\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-GJ.yaml",
    "content": "bounding_box:\n  - - 67.64340254000018\n    - 19.572644470095213\n  - - 74.95905236227674\n    - 25.208362942495825\ncapacity:\n  biomass: 77.3\n  coal: 16092\n  gas: 7551.41\n  hydro: 1990\n  nuclear: 440\n  oil: 0\n  solar: 5131.6\n  wind: 8758.4\ncontributors:\n  - sahitya-pavurala\n  - gopikrishna1793\nemissionFactors:\n  direct:\n    battery discharge:\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 587.3520843990214\n    hydro discharge:\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 587.3520843990214\n  lifecycle:\n    battery discharge:\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 649.8630381967355\n    hydro discharge:\n      - datetime: '2018-01-01'\n        source: electricityMap, 2018 average\n        value: 649.8630381967355\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: electricityMap, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6983766125618412\n        gas: 0.14536664919692363\n        geothermal: 0.0\n        hydro: 0.005387908835595175\n        hydro discharge: 0.0\n        nuclear: 0.006973208352765687\n        oil: 0.0\n        solar: 0.02391389959829987\n        unknown: 0.004844329355440729\n        wind: 0.11508224818233796\nflag_file_name: in.png\nparsers:\n  consumption: IN_GJ.fetch_consumption\n  production: IN_GJ.fetch_production\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-HP.yaml",
    "content": "bounding_box:\n  - - 75.07784712064807\n    - 29.88217682520036\n  - - 79.49706994002565\n    - 33.7328555360541\ncapacity:\n  biomass: 9.2\n  coal: 0\n  gas: 0\n  hydro: 10263.02\n  nuclear: 0\n  oil: 0\n  solar: 45\n  wind: 0\ncontributors:\n  - willbeaufoy\n  - gopikrishna1793\ncountry: IN\ncountry_name: India\ncurrency: INR\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.8958093644290379\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.10419063607196172\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9052572345868161\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.09474280565301471\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9195610380661258\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.08043894206875551\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9245421320577085\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.07545779933267016\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: IN_HP.fetch_production\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Unknown\n"
  },
  {
    "path": "config/retired_zones/IN-HR.yaml",
    "content": "capacity:\n  coal: 5330\n  gas: 431.59\n  hydro: 0\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-JH.yaml",
    "content": "capacity:\n  coal: 4250\n  gas: 0\n  hydro: 210\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-JK.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 175\n  hydro: 3360\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-KA.yaml",
    "content": "bounding_box:\n  - - 73.59115644600661\n    - 11.125595607751208\n  - - 79.06898237493664\n    - 18.96081146897413\ncapacity:\n  biomass: 1888.3\n  coal: 9480\n  gas: 0\n  hydro: 3689.2\n  nuclear: 880\n  oil: 25.2\n  solar: 7409.39\n  wind: 4938.6\ncontributors:\n  - hectorespert\n  - gopikrishna1793\ncountry: IN\ncountry_name: India\ncurrency: INR\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    unknown:\n      _comment: assumes 20% nuclear (0), 80% coal (760)\n      source: Souther Regional Load Dispatch Center Allocation Limits 2018-2019; SRLDC 2018-2019 derived calculation for Karnataka\n      value: 608.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\n    unknown:\n      _comment: assumes 20% nuclear (12), 80% coal (820)\n      source: Souther Regional Load Dispatch Center Allocation Limits 2018-2019; SRLDC 2018-2019 derived calculation for Karnataka\n      value: 658.4\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010639569126514778\n        coal: 0.34135559269696647\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.12714910293137743\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.028603774263534103\n        unknown: 0.43438636529018626\n        wind: 0.06744118045021583\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0009037150996385391\n        coal: 0.291444360020425\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.16043943252527013\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.08539732484758786\n        unknown: 0.3464125824487382\n        wind: 0.11540256130040494\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011159875015926338\n        coal: 0.21935233310646332\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.1912231320262483\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.1638974218625249\n        unknown: 0.3001438480539049\n        wind: 0.1142233746317484\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02833858770180252\n        coal: 0.1793514811545566\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.21279700169104443\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.1309245875818034\n        unknown: 0.3339760020277822\n        wind: 0.11461232082512168\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04013061048132367\n        coal: 0.29468639173352495\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.17586195896940404\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.11411321903698891\n        unknown: 0.30118297389939097\n        wind: 0.0740248596561391\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03540101405331797\n        coal: 0.2444658712422697\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.19881606557742182\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.11359435059370196\n        unknown: 0.30290121772116885\n        wind: 0.10482148081211963\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.021689488766784618\n        coal: 0.275131626560813\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.13230959468087589\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.1367409665303756\n        unknown: 0.3069428488851126\n        wind: 0.1271854795574422\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: IN_KA.fetch_consumption\n  production: IN_KA.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  SRLDC 2018-2019 derived calculation for Karnataka:\n    link: https://github.com/electricitymaps/electricitymaps-contrib/issues/1867\n  Souther Regional Load Dispatch Center Allocation Limits 2018-2019:\n    link: http://srldc.org/2018-19srallocation.aspx\ntimezone: Asia/Kolkata\nzone_name: Unknown\nisRenewable:\n  unknown:\n    _comment: assumes 20% nuclear (12), 80% coal (820)\n    source: Souther Regional Load Dispatch Center Allocation Limits 2018-2019; SRLDC 2018-2019 derived calculation for Karnataka\n    value: 0\nisLowCarbon:\n  unknown:\n    _comment: assumes 20% nuclear (12), 80% coal (820)\n    source: Souther Regional Load Dispatch Center Allocation Limits 2018-2019; SRLDC 2018-2019 derived calculation for Karnataka\n    value: 0.2\n"
  },
  {
    "path": "config/retired_zones/IN-KL.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 533.58\n  hydro: 1856.5\n  nuclear: 0\n  oil: 159.96\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-MH.yaml",
    "content": "bounding_box:\n  - - 72.79941\n    - 15.613079\n  - - 80.661984\n    - 22.105644\ncapacity:\n  biomass: 2597\n  coal: 23856\n  gas: 3207.08\n  hydro: 3047\n  nuclear: 1400\n  oil: 0\n  solar: 2295\n  unknown: 480.55\n  wind: 5010.8\ncontributors:\n  - GitMatze\n  - alixunderplatz\n  - systemcatch\n  - Manu1400\n  - gopikrishna1793\ncountry: IN\ncountry_name: India\ncurrency: INR\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8663973949412991\n        gas: 0.030036405287262796\n        geothermal: 0.0\n        hydro: 0.034767171278209386\n        hydro discharge: 0.0\n        nuclear: 0.020522955406662505\n        oil: 0.0\n        solar: 0.013264061548823293\n        unknown: 0.0\n        wind: 0.03501205940053345\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8675264005974712\n        gas: 0.030075546449856858\n        geothermal: 0.0\n        hydro: 0.034812471560911294\n        hydro discharge: 0.0\n        nuclear: 0.020549692165996728\n        oil: 0.0\n        solar: 0.013483689076296986\n        unknown: 0.0\n        wind: 0.0335522413133779\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8666182502651207\n        gas: 0.030044059643254014\n        geothermal: 0.0\n        hydro: 0.034776032537329374\n        hydro discharge: 0.0\n        nuclear: 0.020528180797007016\n        oil: 0.0\n        solar: 0.013677743394336982\n        unknown: 0.0\n        wind: 0.03435577622938938\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.861616350366414\n        gas: 0.02987065508113662\n        geothermal: 0.0\n        hydro: 0.034575313254121505\n        hydro discharge: 0.0\n        nuclear: 0.02040969949669196\n        oil: 0.0\n        solar: 0.013317789887388664\n        unknown: 0.0\n        wind: 0.04021024113967946\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8647809095608386\n        gas: 0.029980362868602593\n        geothermal: 0.0\n        hydro: 0.03470229934985493\n        hydro discharge: 0.0\n        nuclear: 0.02048465776663164\n        oil: 0.0\n        solar: 0.013058948298858123\n        unknown: 0.0\n        wind: 0.03699286053648009\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012869117854221141\n        coal: 0.8286959143856343\n        gas: 0.02129974558836605\n        geothermal: 0.0\n        hydro: 0.03976543507110578\n        hydro discharge: 0.0\n        nuclear: 0.03972233460564866\n        oil: 0.0\n        solar: 0.012961419118905925\n        unknown: 0.00923911862779166\n        wind: 0.03544688193022671\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02669617097224994\n        coal: 0.8297295752376328\n        gas: 0.021536733601776853\n        geothermal: 0.0\n        hydro: 0.034600319568647946\n        hydro discharge: 0.0\n        nuclear: 0.03229052146171313\n        oil: 0.0\n        solar: 0.014965327418330485\n        unknown: 0.010270868469352998\n        wind: 0.029910465330732435\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03653668880737519\n        coal: 0.8172899649142811\n        gas: 0.013606422259454562\n        geothermal: 0.0\n        hydro: 0.038349152619989835\n        hydro discharge: 0.0\n        nuclear: 0.03225291927307697\n        oil: 0.0\n        solar: 0.016434291882701003\n        unknown: 0.010262173139609457\n        wind: 0.035268381935848116\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.015422958475641076\n        coal: 0.8413485177267193\n        gas: 0.012468589767142583\n        geothermal: 0.0\n        hydro: 0.029351021063500297\n        hydro discharge: 0.0\n        nuclear: 0.033169880050444314\n        oil: 0.0\n        solar: 0.0242120664068756\n        unknown: 0.004873399116179451\n        wind: 0.039153561778823565\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.026150120648595877\n        coal: 0.8302121311222799\n        gas: 0.02344417043129855\n        geothermal: 0.0\n        hydro: 0.029014085659113103\n        hydro discharge: 0.0\n        nuclear: 0.02803986929973076\n        oil: 0.0\n        solar: 0.02944040476303649\n        unknown: 0.004691684211499119\n        wind: 0.02900752525848245\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: IN_MH.fetch_production\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Unknown\n"
  },
  {
    "path": "config/retired_zones/IN-ML.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 0\n  hydro: 322\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-MN.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 0\n  hydro: 105\n  nuclear: 0\n  oil: 36\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-MP.yaml",
    "content": "capacity:\n  coal: 21950\n  gas: 0\n  hydro: 2235\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-MZ.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 0\n  hydro: 60\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-NL.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 0\n  hydro: 75\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-OR.yaml",
    "content": "capacity:\n  coal: 9540\n  gas: 0\n  hydro: 2154.55\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-PB.yaml",
    "content": "bounding_box:\n  - - 73.34234501100013\n    - 29.059823920137802\n  - - 77.41037560365123\n    - 33.016749376582425\ncapacity:\n  biomass: 484.3\n  coal: 5680\n  gas: 0\n  hydro: 1096.3\n  nuclear: 0\n  oil: 0\n  solar: 968.6\n  wind: 0\ncontributors:\n  - corradio\n  - hectorespert\n  - gopikrishna1793\ncountry: IN\ncountry_name: India\ncurrency: INR\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8274516709402372\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.14388918754125016\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.028659201142585133\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001132727014600419\n        coal: 0.5317063325957484\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.07586263617704816\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.39129829500084207\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01088331289412373\n        coal: 0.7846952260269039\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.16336502746084736\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.04105644488616745\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.024372265061487618\n        coal: 0.6983596036093999\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.21927365660629675\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05799448360981094\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.023763668725358265\n        coal: 0.8294626195877834\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.11068189039488861\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.036091828323712785\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01423100579736268\n        coal: 0.836327325654256\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.11217514986072091\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0372665246003073\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.015043076720616036\n        coal: 0.8317053282148215\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.1250213774315918\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.02823021519189305\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.013771114315080575\n        coal: 0.8529926977667466\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.10777647128565225\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.025459760720636028\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: IN_PB.fetch_consumption\n  production: IN_PB.fetch_production\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Unknown\n"
  },
  {
    "path": "config/retired_zones/IN-PY.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 32.5\n  hydro: 0\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-RJ.yaml",
    "content": "capacity:\n  coal: 10480\n  gas: 1022.83\n  hydro: 411\n  nuclear: 1180\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-SK.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 0\n  hydro: 2282\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-TN.yaml",
    "content": "capacity:\n  biomass: 265.59\n  coal: 13685\n  gas: 516.1\n  geothermal: 4320\n  hydro: 2321.9\n  nuclear: 2440\n  oil: 211.7\n  solar: 5518.153\n  wind: 8618.07\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-TR.yaml",
    "content": "capacity:\n  coal: 0\n  gas: 1099.6\n  hydro: 0\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IN-UP.yaml",
    "content": "bounding_box:\n  - - 76.5581702012937\n    - 23.411047268416667\n  - - 85.11243777868054\n    - 30.902020574789645\ncapacity:\n  biomass: 2117.3\n  coal: 24389\n  gas: 1493.14\n  hydro: 501.6\n  nuclear: 440\n  oil: 0\n  solar: 1840.3\n  wind: 0\ncontributors:\n  - sahitya-pavurala\n  - pierresegonne\n  - gopikrishna1793\ncountry: IN\ncountry_name: India\ncurrency: INR\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.7491707335275146e-05\n        coal: 0.8522704258451176\n        gas: 0.06249441219165629\n        geothermal: 0.0\n        hydro: 0.0603967042104172\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.024780855142426905\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.637556043821551e-05\n        coal: 0.8356742877212078\n        gas: 0.061277472478525434\n        geothermal: 0.0\n        hydro: 0.05922062123143805\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.04377116129066554\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.71138157577985e-05\n        coal: 0.8462001536566379\n        gas: 0.06204930628348994\n        geothermal: 0.0\n        hydro: 0.059966596747296916\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.031726833579913245\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.04376317743153851\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.004901085092889169\n        unknown: 0.9513357355500861\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.048076222387756815\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0037114742363852423\n        unknown: 0.9482123153683726\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0566120055563359\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.008319381331478082\n        unknown: 0.9350686046344332\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.018906747695549193\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.14726885443688845\n        unknown: 0.8338243983672093\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers: {}\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Unknown\n"
  },
  {
    "path": "config/retired_zones/IN-UT.yaml",
    "content": "bounding_box:\n  - - 77.611412\n    - 28.542876\n  - - 80.940177\n    - 31.292794\ncapacity:\n  biomass: 130.2\n  coal: 0\n  gas: 450\n  hydro: 3855.35\n  nuclear: 0\n  oil: 0\n  solar: 398.3\n  wind: 0\ncontributors:\n  - alixunderplatz\n  - lorrieq\n  - gopikrishna1793\ncountry: IN\ncountry_name: India\ncurrency: INR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: IN_UT.fetch_production\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Unknown\n"
  },
  {
    "path": "config/retired_zones/IN-WB.yaml",
    "content": "capacity:\n  coal: 13697\n  gas: 80\n  hydro: 1341.2\n  nuclear: 0\n  oil: 0\ncontributors:\n  - gopikrishna1793\nflag_file_name: in.png\ntimezone: Asia/Kolkata\n"
  },
  {
    "path": "config/retired_zones/IQ-KUR.yaml",
    "content": "bounding_box:\n  - - 41.85723840300011\n    - 34.01280325000005\n  - - 46.827073608000035\n    - 37.87549753800006\ncountry: IQ\nregion: Asia\ntimezone: Asia/Baghdad\n"
  },
  {
    "path": "config/retired_zones/MX-BC.yaml",
    "content": "aggregates_displayed:\n  - none\nbounding_box:\n  - - -118.86880422899992\n    - 22.37215511800008\n  - - -108.91362465499992\n    - 33.21283640500009\ncountry: MX\nemissionFactors:\n  direct:\n    unknown:\n      - datetime: '2017-01-01'\n        source: \"Electricity Maps & Dra. Gabriela Mu\\xF1oz Mel\\xE9ndez\"\n        value: 453\n  lifecycle:\n    battery discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 341.3\n    hydro discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 341.3\n    unknown:\n      - datetime: '2017-01-01'\n        source: \"Electricity Maps & Dra. Gabriela Mu\\xF1oz Mel\\xE9ndez\"\n        value: 342\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.00043250680184585163\n        biomass: 0.0001853114848385145\n        coal: 0.00019610386524367113\n        gas: 0.006126988044698532\n        geothermal: 0.00032393116638059627\n        hydro: 0.0011129974402204494\n        hydro discharge: 8.235458490121891e-07\n        nuclear: 0.0008670511107974027\n        oil: 4.5192505614880517e-07\n        solar: 0.0028356554499964085\n        unknown: 0.9870965076517385\n        wind: 0.000821563871450251\nparsers:\n  consumption: CENACE.fetch_consumption\nregion: Americas\ntimezone: America/Tijuana\n"
  },
  {
    "path": "config/retired_zones/MX-BCS.yaml",
    "content": "aggregates_displayed:\n  - none\nbounding_box:\n  - - -118.86880422899992\n    - 22.37215511800008\n  - - -108.91362465499992\n    - 33.21283640500009\ncountry: MX\nparsers:\n  consumption: CENACE.fetch_consumption\nregion: Americas\ntimezone: America/Tijuana\n"
  },
  {
    "path": "config/retired_zones/MX-CE.yaml",
    "content": "aggregates_displayed:\n  - none\nbounding_box:\n  - - -100.01069047658422\n    - 17.392189846084534\n  - - -96.22812130395499\n    - 21.325344143417453\ncountry: MX\nemissionFactors:\n  direct:\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 305\n  lifecycle:\n    battery discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    hydro discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 411\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.4847477716070496e-06\n        coal: 3.214420670328397e-05\n        gas: 3.754750322523777e-05\n        geothermal: 3.219233056486797e-07\n        hydro: 1.2926322504941279e-05\n        hydro discharge: 0.0\n        nuclear: 1.1533516637307845e-05\n        oil: 2.006765028052312e-06\n        solar: 2.426202474279073e-06\n        unknown: 0.9998806976544481\n        wind: 1.8890388656089554e-05\nparsers:\n  consumption: CENACE.fetch_consumption\nregion: Americas\nsources:\n  IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris:\n    link: https://www.iea.org/data-and-statistics/charts/electricity-generation-mix-in-mexico-1-jan-30-sep-2019-and-2020\ntimezone: America/Mexico_City\n"
  },
  {
    "path": "config/retired_zones/MX-NE.yaml",
    "content": "aggregates_displayed:\n  - none\nbounding_box:\n  - - -101.71565100768782\n    - 21.719780991999187\n  - - -96.63927161399994\n    - 28.293549303557484\ncountry: MX\nemissionFactors:\n  direct:\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 305\n  lifecycle:\n    battery discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 410.99\n    hydro discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 410.99\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 411\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0002036154639733834\n        gas: 0.000670799321690792\n        geothermal: 0.0\n        hydro: 5.974059739928552e-07\n        hydro discharge: 0.0\n        nuclear: 0.0001267184109685156\n        oil: 0.0\n        solar: 1.591121471939949e-05\n        unknown: 0.9985936291455566\n        wind: 0.0003886936483887087\nparsers:\n  consumption: CENACE.fetch_consumption\nregion: Americas\nsources:\n  IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris:\n    link: https://www.iea.org/data-and-statistics/charts/electricity-generation-mix-in-mexico-1-jan-30-sep-2019-and-2020\ntimezone: America/Mexico_City\n"
  },
  {
    "path": "config/retired_zones/MX-NO.yaml",
    "content": "aggregates_displayed:\n  - none\nbounding_box:\n  - - -109.65359025758431\n    - 21.8191030954315\n  - - -99.30696277711047\n    - 32.277751364000025\ncountry: MX\nemissionFactors:\n  direct:\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 305\n  lifecycle:\n    battery discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    hydro discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 411\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 1.402186867881626e-05\n        gas: 4.695234762058425e-05\n        geothermal: 0.0\n        hydro: 2.745617520817753e-09\n        hydro discharge: 0.0\n        nuclear: 8.324712323119425e-06\n        oil: 0.0\n        solar: 2.3520790095005418e-07\n        unknown: 0.9999035290675828\n        wind: 2.685991860323994e-05\nparsers:\n  consumption: CENACE.fetch_consumption\nregion: Americas\nsources:\n  IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris:\n    link: https://www.iea.org/data-and-statistics/charts/electricity-generation-mix-in-mexico-1-jan-30-sep-2019-and-2020\ntimezone: America/Mexico_City\n"
  },
  {
    "path": "config/retired_zones/MX-NW.yaml",
    "content": "aggregates_displayed:\n  - none\nbounding_box:\n  - - -115.53974260094026\n    - 21.9489659687045\n  - - -104.88862626838755\n    - 32.99936330200008\ncountry: MX\nemissionFactors:\n  direct:\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 305\n  lifecycle:\n    battery discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    hydro discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 411\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 2.3398798841637265e-06\n        gas: 7.770706423479258e-06\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 1.3269002466863584e-06\n        oil: 0.0\n        solar: 2.0615681798799356e-08\n        unknown: 0.9999841367013942\n        wind: 4.332572945306765e-06\nparsers:\n  consumption: CENACE.fetch_consumption\nregion: Americas\nsources:\n  IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris:\n    link: https://www.iea.org/data-and-statistics/charts/electricity-generation-mix-in-mexico-1-jan-30-sep-2019-and-2020\ntimezone: America/Mexico_City\n"
  },
  {
    "path": "config/retired_zones/MX-OC.yaml",
    "content": "aggregates_displayed:\n  - none\nbounding_box:\n  - - -115.29857337099992\n    - 17.415988111000047\n  - - -97.5001883613038\n    - 25.66554433840048\ncountry: MX\nemissionFactors:\n  direct:\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 305\n  lifecycle:\n    battery discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    hydro discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 411\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.76550207442519e-08\n        coal: 5.714119313455745e-05\n        gas: 0.00018045255734755876\n        geothermal: 1.1869301884956474e-08\n        hydro: 7.287751357363274e-07\n        hydro discharge: 0.0\n        nuclear: 3.6074764862344366e-05\n        oil: 1.1592351507640824e-07\n        solar: 4.3801680389451044e-06\n        unknown: 0.9996108734440349\n        wind: 0.00011010122685844094\nparsers:\n  consumption: CENACE.fetch_consumption\nregion: Americas\nsources:\n  IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris:\n    link: https://www.iea.org/data-and-statistics/charts/electricity-generation-mix-in-mexico-1-jan-30-sep-2019-and-2020\ntimezone: America/Mexico_City\n"
  },
  {
    "path": "config/retired_zones/MX-OR.yaml",
    "content": "aggregates_displayed:\n  - none\nbounding_box:\n  - - -102.67957149932522\n    - 14.046279476000095\n  - - -89.87985327199993\n    - 22.98054026911808\ncountry: MX\nemissionFactors:\n  direct:\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 305\n  lifecycle:\n    battery discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 410.99\n    hydro discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 410.99\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 411\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.1501898238582426e-06\n        coal: 1.9358154811463765e-05\n        gas: 5.538840970745195e-05\n        geothermal: 4.287907663343529e-07\n        hydro: 9.82564445185782e-06\n        hydro discharge: 0.0\n        nuclear: 1.1435384404197025e-05\n        oil: 3.380900830815314e-07\n        solar: 1.7848317060968248e-06\n        unknown: 0.9998643493726297\n        wind: 3.585936955072924e-05\nparsers:\n  consumption: CENACE.fetch_consumption\nregion: Americas\nsources:\n  IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris:\n    link: https://www.iea.org/data-and-statistics/charts/electricity-generation-mix-in-mexico-1-jan-30-sep-2019-and-2020\ntimezone: America/Mexico_City\n"
  },
  {
    "path": "config/retired_zones/MX-PN.yaml",
    "content": "aggregates_displayed:\n  - none\nbounding_box:\n  - - -92.98614402599992\n    - 17.301963603000004\n  - - -86.20059160099993\n    - 22.123439846000053\ncountry: MX\nemissionFactors:\n  direct:\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 305\n  lifecycle:\n    battery discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    hydro discharge:\n      - datetime: '2023-01-01'\n        source: Electricity Maps, 2023 average\n        value: 411.0\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2%\n          coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014\n          values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and\n          2020, IEA, Paris\n        value: 411\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.3386396541103494e-06\n        coal: 2.7168893585104462e-05\n        gas: 3.215615900795001e-05\n        geothermal: 3.0607766132987135e-07\n        hydro: 1.202975231867962e-05\n        hydro discharge: 0.0\n        nuclear: 9.428992425791391e-06\n        oil: 1.6942298783024054e-06\n        solar: 1.581701326342894e-06\n        unknown: 0.9998991744174442\n        wind: 1.4996004948332344e-05\nparsers:\n  consumption: CENACE.fetch_consumption\nregion: Americas\nsources:\n  IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris:\n    link: https://www.iea.org/data-and-statistics/charts/electricity-generation-mix-in-mexico-1-jan-30-sep-2019-and-2020\ntimezone: America/Mexico_City\n"
  },
  {
    "path": "config/retired_zones/README.md",
    "content": "Those zones have been retired for now to allow for a higher level overview of certain zones.\nThey can be reused once an intermediate/state view has been implemented.\n"
  },
  {
    "path": "config/retired_zones/US-FLA-NSB.yaml",
    "content": "bounding_box:\n  - - -82.18057\n    - 28.1131300000001\n  - - -80.23297\n    - 29.92717\ncomment: New Smyrna Beach, Utilities Commission Of\ncontributors:\n  - systemcatch\n  - robertahunt\ndelays:\n  consumption: 30\n  consumptionForecast: 30\n  production: 30\ndisclaimer: Data for real-time consumption and generation mix is estimated. Real-time\n  exchanges are not available.\nemissionFactors:\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: US/Eastern\n"
  },
  {
    "path": "config/retired_zones/US-HI-HA.yaml",
    "content": "bounding_box:\n  - - -156.5601639279999\n    - 18.40611714300016\n  - - -154.31406356599993\n    - 20.763429107000178\ncountry: US\nemissionFactors:\n  direct:\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 104.45\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 785.7600688\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 776.65\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 38.0\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 142.45\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1029.7600688\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1020.65\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: Pacific/Honolulu\n"
  },
  {
    "path": "config/retired_zones/US-HI-KA.yaml",
    "content": "bounding_box:\n  - - -160.28721974299992\n    - 21.368769246000056\n  - - -158.7925919259999\n    - 22.735494671000225\ncountry: US\nemissionFactors:\n  direct:\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 779.2439369\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 741.34\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1023.2439369\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 985.34\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: Pacific/Honolulu\n"
  },
  {
    "path": "config/retired_zones/US-HI-KH.yaml",
    "content": "bounding_box:\n  - - -157.20056182399986\n    - 20.004712932000132\n  - - -156.03412841099995\n    - 21.09995670100011\ncountry: US\nemissionFactors:\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: Pacific/Honolulu\n"
  },
  {
    "path": "config/retired_zones/US-HI-LA.yaml",
    "content": "bounding_box:\n  - - -157.56313605799994\n    - 20.232387730000227\n  - - -156.30353909899995\n    - 21.427508787000193\ncountry: US\nemissionFactors:\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: Pacific/Honolulu\n"
  },
  {
    "path": "config/retired_zones/US-HI-MA.yaml",
    "content": "bounding_box:\n  - - -157.19600919699985\n    - 20.081179336000048\n  - - -155.47955290999988\n    - 21.532653273000165\ncountry: US\nemissionFactors:\n  direct:\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 783.2844717\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 774.83\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1027.2844717\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1018.83\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: Pacific/Honolulu\n"
  },
  {
    "path": "config/retired_zones/US-HI-MO.yaml",
    "content": "bounding_box:\n  - - -157.80426998599995\n    - 20.553371486000145\n  - - -156.20572493599994\n    - 21.721879885000135\ncountry: US\nemissionFactors:\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: Pacific/Honolulu\n"
  },
  {
    "path": "config/retired_zones/US-HI-NI.yaml",
    "content": "bounding_box:\n  - - -160.74803626199989\n    - 21.280209463000062\n  - - -159.55143635199994\n    - 22.507756812000167\ncountry: US\nemissionFactors:\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: Pacific/Honolulu\n"
  },
  {
    "path": "config/retired_zones/US-HI-OA.yaml",
    "content": "bounding_box:\n  - - -158.7789330139999\n    - 20.75418992400006\n  - - -157.14716739499988\n    - 22.209850429000085\ncapacity:\n  battery storage: 225.9\n  biomass: 157.7\n  coal: 0\n  gas: 0\n  geothermal: 0\n  hydro: 0\n  oil: 1528.9\n  solar: 240.9\n  unknown: 0\n  wind: 126.6\ncontributors:\n  - kepiej\n  - systemcatch\n  - KabelWlan\n  - danielmatsuda\n  - brandongalbraith\ncountry: US\ndisclaimer: Data for real-time consumption and generation mix is estimated. Real-time\n  exchanges are not available.\nemissionFactors:\n  direct:\n    battery discharge:\n      - datetime: '2015-01-01'\n        source: Electricity Maps, 2015 average\n        value: 410.39794188222544\n      - datetime: '2016-01-01'\n        source: Electricity Maps, 2016 average\n        value: 701.3131580711408\n      - datetime: '2017-01-01'\n        source: Electricity Maps, 2017 average\n        value: 701.3131343083057\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 730.0244347012316\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 725.3627752472624\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 707.875524344012\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 685.9001691120977\n    biomass:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1088.282256\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1095.15\n    hydro discharge:\n      - datetime: '2015-01-01'\n        source: Electricity Maps, 2015 average\n        value: 410.39794188222544\n      - datetime: '2016-01-01'\n        source: Electricity Maps, 2016 average\n        value: 701.3131580711408\n      - datetime: '2017-01-01'\n        source: Electricity Maps, 2017 average\n        value: 701.3131343083057\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 730.0244347012316\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 725.3627752472624\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 707.875524344012\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 685.9001691120977\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 742.1719304\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 746.36\n  lifecycle:\n    battery discharge:\n      - datetime: '2015-01-01'\n        source: Electricity Maps, 2015 average\n        value: 608.8370339321843\n      - datetime: '2016-01-01'\n        source: Electricity Maps, 2016 average\n        value: 945.1187640576029\n      - datetime: '2017-01-01'\n        source: Electricity Maps, 2017 average\n        value: 945.1187325074374\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 968.2804597073409\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 971.05\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 948.9\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 884.56\n      - datetime: '2022-01-01'\n        source: Electricity Maps, 2022 average\n        value: 879.04\n    biomass:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 980.1789569\n      - datetime: '2021-01-01'\n        source: eGrid 2021; eGrid 2021\n        value: 277.252\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1148.282256\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1155.15\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    hydro discharge:\n      - datetime: '2015-01-01'\n        source: Electricity Maps, 2015 average\n        value: 608.8370339321843\n      - datetime: '2016-01-01'\n        source: Electricity Maps, 2016 average\n        value: 945.1187640576029\n      - datetime: '2017-01-01'\n        source: Electricity Maps, 2017 average\n        value: 945.1187325074374\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 968.2804597073409\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 971.05\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 948.9\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 884.56\n      - datetime: '2022-01-01'\n        source: Electricity Maps, 2022 average\n        value: 879.04\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 986.1719304\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 990.36\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06146349507461177\n        coal: 0.1624396255143238\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7067562169754187\n        solar: 0.03961629916750147\n        unknown: 0.0\n        wind: 0.029725995100113794\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.061463497137033196\n        coal: 0.16243963096502206\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7067562406907828\n        solar: 0.03961626694160985\n        unknown: 0.0\n        wind: 0.029725996097576264\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06146349507461177\n        coal: 0.1624396255143238\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7067562169754187\n        solar: 0.03961629916750147\n        unknown: 0.0\n        wind: 0.029725995100113794\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05426059193571333\n        coal: 0.18748967287625318\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7087083605223727\n        solar: 0.02312780413094602\n        unknown: 0.0\n        wind: 0.026414284812573935\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06137047888409653\n        coal: 0.186872666569466\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7046028054259422\n        solar: 0.02686747790012586\n        unknown: 0.0\n        wind: 0.020286321020470077\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06111998815118013\n        coal: 0.17874211746869453\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.6911122691835548\n        solar: 0.04003437233497996\n        unknown: 0.0\n        wind: 0.028990929813329517\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06181462398537552\n        coal: 0.15934702552680494\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.6872143794090574\n        solar: 0.049200525149930306\n        unknown: 0.0\n        wind: 0.04242344106433257\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06156103188787083\n        coal: 0.09938471014364356\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7513025405060908\n        solar: 0.0607152139518972\n        unknown: 0.0\n        wind: 0.027036543409622936\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: Pacific/Honolulu\n"
  },
  {
    "path": "config/retired_zones/US-NW-AVRN.yaml",
    "content": "capacity:\n  battery storage: 0\n  biomass: 0\n  coal: 0\n  gas: 619.1\n  geothermal: 0\n  hydro: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 0\n  solar: 160\n  unknown: 0\n  wind: 1697.7\ncomment: Avangrid Renewables Cooperative\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ndelays:\n  production: 30\ndisclaimer: Data for real-time consumption and generation mix is estimated. Real-time\n  exchanges are not available.\nemissionFactors:\n  direct:\n    battery discharge:\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 21.056347721310882\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 207.3509981331674\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 270.8334094579008\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 0.0\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 54.92646466317582\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 166.22143140855945\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 157.38251800607716\n    gas:\n      datetime: '2021-01-01'\n      source: eGrid 2020\n      value: 410.2399164\n    hydro discharge:\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 21.056347721310882\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 207.3509981331674\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 270.8334094579008\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 0.0\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 54.92646466317582\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 166.22143140855945\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 157.38251800607716\n  lifecycle:\n    battery discharge:\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 35.39906669808514\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 279.27521841941507\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 361.53704498269894\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 11.0\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 82.05196702341827\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 221.38616496547627\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 210.19888730892356\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2021-01-01'\n      source: eGrid 2020; IPCC 2014\n      value: 530.2399164000001\n    hydro discharge:\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 35.39906669808514\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 279.27521841941507\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 361.53704498269894\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 11.0\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 82.05196702341827\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 221.38616496547627\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 210.19888730892356\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 1.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.13388861991272447\n        geothermal: 0.0\n        hydro: 0.11784705613957798\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.7482643239476976\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.40518099527640355\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.5948190047235964\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.3836354548168083\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.6163645451831917\nparsers:\n  production: EIA.fetch_production_mix\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\ntimezone: US/Pacific\n"
  },
  {
    "path": "config/retired_zones/US-SE-AEC.yaml",
    "content": "bounding_box:\n  - - -88.9596785776442\n    - 29.339638675596\n  - - -84.3581394658229\n    - 34.4502982778481\ncapacity:\n  battery storage: 0\n  biomass: 4.8\n  coal: 0\n  gas: 1330\n  geothermal: 0\n  hydro: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 0\n  solar: 0\n  unknown: 0\n  wind: 0\ncomment: Powersouth Energy Cooperative\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ndelays:\n  consumption: 30\n  consumptionForecast: 30\n  production: 30\ndisclaimer: Data for real-time consumption and generation mix is estimated. Real-time\n  exchanges are not available.\nemissionFactors:\n  direct:\n    battery discharge:\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 637.5461428543931\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 552.3948407547141\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 459.2089741767484\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 401.9975251542462\n    coal:\n      datetime: '2020-01-01'\n      source: eGrid 2020\n      value: 1196.66141\n    gas:\n      datetime: '2021-01-01'\n      source: eGrid 2020\n      value: 404.1054386\n    hydro discharge:\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 637.5461428543931\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 552.3948407547141\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 459.2089741767484\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 401.9975251542462\n  lifecycle:\n    battery discharge:\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 755.4345979007286\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 670.921113609942\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 578.5336295237561\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 521.2200312142762\n    coal:\n      datetime: '2020-01-01'\n      source: eGrid 2020; Oberschelp, Christopher, et al. \"Global emission hotspots\n        of coal power generation.\"\n      value: 1310.312319\n    gas:\n      datetime: '2021-01-01'\n      source: eGrid 2020; IPCC 2014\n      value: 524.1054386000001\n    hydro discharge:\n      - datetime: '2018-01-01'\n        source: Electricity Maps, 2018 average\n        value: 755.4345979007286\n      - datetime: '2019-01-01'\n        source: Electricity Maps, 2019 average\n        value: 670.921113609942\n      - datetime: '2020-01-01'\n        source: Electricity Maps, 2020 average\n        value: 578.5336295237561\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 521.2200312142762\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.29474525062092716\n        gas: 0.6970662105457389\n        geothermal: 0.0\n        hydro: 0.0025829374134651254\n        hydro discharge: 0.0008280134712315929\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.004777587948637279\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.18734852087481615\n        gas: 0.8026600045354034\n        geothermal: 0.0\n        hydro: 0.003308356720003904\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.006683117869776512\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.069255336108549\n        gas: 0.9198139987343975\n        geothermal: 0.0\n        hydro: 0.0028750567325007688\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.008055608424552687\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9837240945072053\n        geothermal: 0.0\n        hydro: 0.008503295011414636\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.00777261048138002\n        wind: 0.0\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\ntimezone: US/Central\n"
  },
  {
    "path": "config/retired_zones/US-SW-DEAA.yaml",
    "content": "bounding_box:\n  - - -113.397006989\n    - 32.8262615200001\n  - - -112.375976563\n    - 33.877473831\ncapacity:\n  battery storage: 0\n  biomass: 0\n  coal: 0\n  gas: 713\n  geothermal: 0\n  hydro: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 0\n  solar: 0\n  unknown: 0\n  wind: 0\ncomment: Arlington Valley, Llc - Avba\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ndelays:\n  production: 30\ndisclaimer: Data for real-time consumption and generation mix is estimated. Real-time\n  exchanges are not available.\nemissionFactors:\n  direct:\n    gas:\n      datetime: '2021-01-01'\n      source: eGrid 2020\n      value: 397.9497472\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2021-01-01'\n      source: eGrid 2020; IPCC 2014\n      value: 517.9497472\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nparsers:\n  production: EIA.fetch_production_mix\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\ntimezone: US/Arizona\n"
  },
  {
    "path": "config/retired_zones/US-SW-GRMA.yaml",
    "content": "bounding_box:\n  - - -113.26607132\n    - 31.246901321\n  - - -111.760446548\n    - 33.5380344390001\ncapacity:\n  battery storage: 0\n  biomass: 0\n  coal: 0\n  gas: 619\n  geothermal: 0\n  hydro: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 0\n  solar: 0\n  unknown: 0\n  wind: 0\ncomment: Gila River Power, Llc\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ndelays:\n  production: 30\ndisclaimer: Data for real-time consumption and generation mix is estimated. Real-time\n  exchanges are not available.\nemissionFactors:\n  lifecycle:\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nparsers:\n  production: EIA.fetch_production_mix\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: US/Arizona\n"
  },
  {
    "path": "config/retired_zones/US-SW-HGMA.yaml",
    "content": "bounding_box:\n  - - -114.158504486\n    - 32.855298996\n  - - -112.449426651\n    - 34.847730637\ncapacity:\n  battery storage: 0\n  biomass: 0\n  coal: 0\n  gas: 1325.1\n  geothermal: 0\n  hydro: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 0\n  solar: 0\n  unknown: 0\n  wind: 0\ncomment: New Harquahala Generating Company, Llc - Hgba\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ndelays:\n  production: 30\ndisclaimer: Data for real-time consumption and generation mix is estimated. Real-time\n  exchanges are not available.\nemissionFactors:\n  direct:\n    battery discharge:\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 370.0\n    hydro discharge:\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 370.0\n  lifecycle:\n    battery discharge:\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 490.0\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    hydro discharge:\n      - datetime: '2021-01-01'\n        source: Electricity Maps, 2021 average\n        value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: IPCC 2014; EIA 2020/BEIS 2021\n      value: 650.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 1.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nparsers:\n  production: EIA.fetch_production_mix\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: US/Arizona\n"
  },
  {
    "path": "config/zone_names.json",
    "content": "{\n  \"zoneShortName\": {\n    \"AD\": {\n      \"zoneName\": \"Andorra\"\n    },\n    \"AE\": {\n      \"zoneName\": \"United Arab Emirates\"\n    },\n    \"AF\": {\n      \"zoneName\": \"Afghanistan\"\n    },\n    \"AG\": {\n      \"zoneName\": \"Antigua and Barbuda\"\n    },\n    \"AL\": {\n      \"zoneName\": \"Albania\"\n    },\n    \"AM\": {\n      \"zoneName\": \"Armenia\"\n    },\n    \"AO\": {\n      \"zoneName\": \"Angola\"\n    },\n    \"AR\": {\n      \"zoneName\": \"Argentina\"\n    },\n    \"AT\": {\n      \"zoneName\": \"Austria\"\n    },\n    \"AU\": {\n      \"zoneName\": \"Australia\"\n    },\n    \"AU-LH\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"Lord Howe Island\"\n    },\n    \"AU-NSW\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"New South Wales\"\n    },\n    \"AU-NT\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"Northern Territory\"\n    },\n    \"AU-QLD\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"Queensland\"\n    },\n    \"AU-SA\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"South Australia\"\n    },\n    \"AU-TAS\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"Tasmania\"\n    },\n    \"AU-TAS-CBI\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"Cape Barren Island\"\n    },\n    \"AU-TAS-KI\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"King Island\"\n    },\n    \"AU-TAS-FI\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"Flinders Island\"\n    },\n    \"AU-VIC\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"Victoria\"\n    },\n    \"AU-WA\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"Western Australia\"\n    },\n    \"AU-WA-RI\": {\n      \"countryName\": \"Australia\",\n      \"zoneName\": \"Rottnest Island\"\n    },\n    \"AW\": {\n      \"zoneName\": \"Aruba\"\n    },\n    \"AX\": {\n      \"zoneName\": \"Åland Islands\"\n    },\n    \"AZ\": {\n      \"zoneName\": \"Azerbaijan\"\n    },\n    \"BA\": {\n      \"zoneName\": \"Bosnia and Herzegovina\"\n    },\n    \"BB\": {\n      \"zoneName\": \"Barbados\"\n    },\n    \"BD\": {\n      \"zoneName\": \"Bangladesh\"\n    },\n    \"BE\": {\n      \"zoneName\": \"Belgium\"\n    },\n    \"BF\": {\n      \"zoneName\": \"Burkina Faso\"\n    },\n    \"BG\": {\n      \"zoneName\": \"Bulgaria\"\n    },\n    \"BH\": {\n      \"zoneName\": \"Bahrain\"\n    },\n    \"BI\": {\n      \"zoneName\": \"Burundi\"\n    },\n    \"BJ\": {\n      \"zoneName\": \"Benin\"\n    },\n    \"BM\": {\n      \"zoneName\": \"Bermuda\"\n    },\n    \"BN\": {\n      \"zoneName\": \"Brunei\"\n    },\n    \"BO\": {\n      \"zoneName\": \"Bolivia\"\n    },\n    \"BR\": {\n      \"zoneName\": \"Brazil\"\n    },\n    \"BR-CS\": {\n      \"countryName\": \"Brazil\",\n      \"zoneName\": \"Central Brazil\"\n    },\n    \"BR-N\": {\n      \"countryName\": \"Brazil\",\n      \"zoneName\": \"North Brazil\"\n    },\n    \"BR-NE\": {\n      \"countryName\": \"Brazil\",\n      \"zoneName\": \"North-East Brazil\"\n    },\n    \"BR-S\": {\n      \"countryName\": \"Brazil\",\n      \"zoneName\": \"South Brazil\"\n    },\n    \"BS\": {\n      \"zoneName\": \"Bahamas\"\n    },\n    \"BT\": {\n      \"zoneName\": \"Bhutan\"\n    },\n    \"BW\": {\n      \"zoneName\": \"Botswana\"\n    },\n    \"BY\": {\n      \"zoneName\": \"Belarus\"\n    },\n    \"BZ\": {\n      \"zoneName\": \"Belize\"\n    },\n    \"CA\": {\n      \"zoneName\": \"Canada\"\n    },\n    \"CA-AB\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Alberta\"\n    },\n    \"CA-BC\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"British Columbia\"\n    },\n    \"CA-MB\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Manitoba\"\n    },\n    \"CA-NB\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"New Brunswick\"\n    },\n    \"CA-NL\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Newfoundland and Labrador\"\n    },\n    \"CA-NS\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Nova Scotia\"\n    },\n    \"CA-NT\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Northwest Territories\"\n    },\n    \"CA-NU\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Nunavut\"\n    },\n    \"CA-ON\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Ontario\"\n    },\n    \"CA-PE\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Prince Edward Island\"\n    },\n    \"CA-QC\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Québec\"\n    },\n    \"CA-SK\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Saskatchewan\"\n    },\n    \"CA-YT\": {\n      \"countryName\": \"Canada\",\n      \"zoneName\": \"Yukon\"\n    },\n    \"CD\": {\n      \"zoneName\": \"Democratic Republic of the Congo\"\n    },\n    \"CF\": {\n      \"zoneName\": \"Central African Republic\"\n    },\n    \"CG\": {\n      \"zoneName\": \"Congo\"\n    },\n    \"CH\": {\n      \"zoneName\": \"Switzerland\"\n    },\n    \"CI\": {\n      \"zoneName\": \"Ivory Coast\"\n    },\n    \"CL-CHP\": {\n      \"countryName\": \"Chile\",\n      \"zoneName\": \"Easter Island\"\n    },\n    \"CL-SEA\": {\n      \"countryName\": \"Chile\",\n      \"zoneName\": \"Sistema Eléctrico de Aysén\"\n    },\n    \"CL-SEM\": {\n      \"countryName\": \"Chile\",\n      \"zoneName\": \"Sistema Eléctrico de Magallanes\"\n    },\n    \"CL-SEN\": {\n      \"countryName\": \"Chile\",\n      \"zoneName\": \"Sistema Eléctrico Nacional\"\n    },\n    \"CM\": {\n      \"zoneName\": \"Cameroon\"\n    },\n    \"CN\": {\n      \"zoneName\": \"China\"\n    },\n    \"CO\": {\n      \"zoneName\": \"Colombia\"\n    },\n    \"CR\": {\n      \"zoneName\": \"Costa Rica\"\n    },\n    \"CU\": {\n      \"zoneName\": \"Cuba\"\n    },\n    \"CV\": {\n      \"zoneName\": \"Cabo Verde\"\n    },\n    \"CW\": {\n      \"zoneName\": \"Curaçao\"\n    },\n    \"CY\": {\n      \"zoneName\": \"Cyprus\"\n    },\n    \"CZ\": {\n      \"zoneName\": \"Czechia\"\n    },\n    \"DE\": {\n      \"zoneName\": \"Germany\"\n    },\n    \"DJ\": {\n      \"zoneName\": \"Djibouti\"\n    },\n    \"DK\": {\n      \"zoneName\": \"Denmark\"\n    },\n    \"DK-DK1\": {\n      \"countryName\": \"Denmark\",\n      \"zoneName\": \"West Denmark\"\n    },\n    \"DK-DK2\": {\n      \"countryName\": \"Denmark\",\n      \"zoneName\": \"East Denmark\"\n    },\n    \"DM\": {\n      \"zoneName\": \"Dominica\"\n    },\n    \"DO\": {\n      \"zoneName\": \"Dominican Republic\"\n    },\n    \"DZ\": {\n      \"zoneName\": \"Algeria\"\n    },\n    \"EC\": {\n      \"zoneName\": \"Ecuador\"\n    },\n    \"EE\": {\n      \"zoneName\": \"Estonia\"\n    },\n    \"EG\": {\n      \"zoneName\": \"Egypt\"\n    },\n    \"EH\": {\n      \"zoneName\": \"Western Sahara\"\n    },\n    \"ER\": {\n      \"zoneName\": \"Eritrea\"\n    },\n    \"ES\": {\n      \"zoneName\": \"Spain\"\n    },\n    \"ES-CE\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Ceuta\"\n    },\n    \"ES-IB-FO\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Formentera\"\n    },\n    \"ES-IB-IZ\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Ibiza\"\n    },\n    \"ES-IB-MA\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Mallorca\"\n    },\n    \"ES-IB-ME\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Menorca\"\n    },\n    \"ES-CN-FVLZ\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Fuerteventura/Lanzarote\"\n    },\n    \"ES-CN-FV\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Fuerteventura\"\n    },\n    \"ES-CN-LZ\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Lanzarote\"\n    },\n    \"ES-CN-GC\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Gran Canaria\"\n    },\n    \"ES-CN-HI\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"El Hierro\"\n    },\n    \"ES-CN-IG\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Isla de la Gomera\"\n    },\n    \"ES-CN-LP\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"La Palma\"\n    },\n    \"ES-CN-TE\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Tenerife\"\n    },\n    \"ES-ML\": {\n      \"countryName\": \"Spain\",\n      \"zoneName\": \"Melilla\"\n    },\n    \"ET\": {\n      \"zoneName\": \"Ethiopia\"\n    },\n    \"FI\": {\n      \"zoneName\": \"Finland\"\n    },\n    \"FJ\": {\n      \"zoneName\": \"Fiji\"\n    },\n    \"FK\": {\n      \"zoneName\": \"Falkland Islands\"\n    },\n    \"FM\": {\n      \"zoneName\": \"Micronesia\"\n    },\n    \"FO\": {\n      \"zoneName\": \"Faroe Islands\"\n    },\n    \"FO-MI\": {\n      \"countryName\": \"Faroe Islands\",\n      \"zoneName\": \"Main Islands\"\n    },\n    \"FO-SI\": {\n      \"countryName\": \"Faroe Islands\",\n      \"zoneName\": \"South Island\"\n    },\n    \"FR\": {\n      \"zoneName\": \"France\"\n    },\n    \"FR-COR\": {\n      \"countryName\": \"France\",\n      \"zoneName\": \"Corsica\"\n    },\n    \"GA\": {\n      \"zoneName\": \"Gabon\"\n    },\n    \"GB\": {\n      \"zoneName\": \"Great Britain\"\n    },\n    \"GB-NIR\": {\n      \"zoneName\": \"Northern Ireland\"\n    },\n    \"GB-ZET\": {\n      \"countryName\": \"Great Britain\",\n      \"zoneName\": \"Shetland Islands\"\n    },\n    \"GE\": {\n      \"zoneName\": \"Georgia\"\n    },\n    \"GF\": {\n      \"zoneName\": \"French Guiana\"\n    },\n    \"GG\": {\n      \"zoneName\": \"Guernsey\"\n    },\n    \"GH\": {\n      \"zoneName\": \"Ghana\"\n    },\n    \"GI\": {\n      \"zoneName\": \"Gibraltar\"\n    },\n    \"GL\": {\n      \"zoneName\": \"Greenland\"\n    },\n    \"GM\": {\n      \"zoneName\": \"Gambia\"\n    },\n    \"GN\": {\n      \"zoneName\": \"Guinea\"\n    },\n    \"GP\": {\n      \"zoneName\": \"Guadeloupe\"\n    },\n    \"GQ\": {\n      \"zoneName\": \"Equatorial Guinea\"\n    },\n    \"GR\": {\n      \"zoneName\": \"Greece\"\n    },\n    \"GS\": {\n      \"zoneName\": \"South Georgia and the South Sandwich Islands\"\n    },\n    \"GT\": {\n      \"zoneName\": \"Guatemala\"\n    },\n    \"GU\": {\n      \"zoneName\": \"Guam\"\n    },\n    \"GW\": {\n      \"zoneName\": \"Guinea-Bissau\"\n    },\n    \"GY\": {\n      \"zoneName\": \"Guyana\"\n    },\n    \"HK\": {\n      \"zoneName\": \"Hong Kong\"\n    },\n    \"HM\": {\n      \"zoneName\": \"Heard Island and McDonald Islands\"\n    },\n    \"HN\": {\n      \"zoneName\": \"Honduras\"\n    },\n    \"HR\": {\n      \"zoneName\": \"Croatia\"\n    },\n    \"HT\": {\n      \"zoneName\": \"Haiti\"\n    },\n    \"HU\": {\n      \"zoneName\": \"Hungary\"\n    },\n    \"ID\": {\n      \"zoneName\": \"Indonesia\"\n    },\n    \"IE\": {\n      \"zoneName\": \"Ireland\"\n    },\n    \"IL\": {\n      \"zoneName\": \"Israel\"\n    },\n    \"IM\": {\n      \"zoneName\": \"Isle of Man\"\n    },\n    \"IN\": {\n      \"zoneName\": \"Mainland India\",\n      \"countryName\": \"India\"\n    },\n    \"IN-EA\": {\n      \"countryName\": \"India\",\n      \"zoneName\": \"Eastern India\"\n    },\n    \"IN-NE\": {\n      \"countryName\": \"India\",\n      \"zoneName\": \"North Eastern India\"\n    },\n    \"IN-NO\": {\n      \"countryName\": \"India\",\n      \"zoneName\": \"Northern India\"\n    },\n    \"IN-SO\": {\n      \"countryName\": \"India\",\n      \"zoneName\": \"Southern India\"\n    },\n    \"IN-WE\": {\n      \"countryName\": \"India\",\n      \"zoneName\": \"Western India\"\n    },\n    \"IN-AN\": {\n      \"countryName\": \"India\",\n      \"zoneName\": \"Andaman and Nicobar Islands\"\n    },\n    \"IN-HP\": {\n      \"countryName\": \"India\",\n      \"zoneName\": \"Himachal Pradesh\"\n    },\n    \"IN-UP\": {\n      \"countryName\": \"India\",\n      \"zoneName\": \"Uttar Pradesh\"\n    },\n    \"IN-UT\": {\n      \"countryName\": \"India\",\n      \"zoneName\": \"Uttarakhand\"\n    },\n    \"IO\": {\n      \"zoneName\": \"British Indian Ocean Territory\"\n    },\n    \"IQ\": {\n      \"zoneName\": \"Iraq\"\n    },\n    \"IQ-KUR\": {\n      \"countryName\": \"Iraq\",\n      \"zoneName\": \"Kurdistan\"\n    },\n    \"IR\": {\n      \"zoneName\": \"Iran\"\n    },\n    \"IS\": {\n      \"zoneName\": \"Iceland\"\n    },\n    \"IT\": {\n      \"zoneName\": \"Italy\"\n    },\n    \"IT-CNO\": {\n      \"countryName\": \"Italy\",\n      \"zoneName\": \"Central North Italy\"\n    },\n    \"IT-CSO\": {\n      \"countryName\": \"Italy\",\n      \"zoneName\": \"Central South Italy\"\n    },\n    \"IT-NO\": {\n      \"countryName\": \"Italy\",\n      \"zoneName\": \"North Italy\"\n    },\n    \"IT-SAR\": {\n      \"countryName\": \"Italy\",\n      \"zoneName\": \"Sardinia\"\n    },\n    \"IT-SIC\": {\n      \"countryName\": \"Italy\",\n      \"zoneName\": \"Sicily\"\n    },\n    \"IT-SO\": {\n      \"countryName\": \"Italy\",\n      \"zoneName\": \"South Italy\"\n    },\n    \"JE\": {\n      \"zoneName\": \"Jersey\"\n    },\n    \"JM\": {\n      \"zoneName\": \"Jamaica\"\n    },\n    \"JO\": {\n      \"zoneName\": \"Jordan\"\n    },\n    \"JP\": {\n      \"zoneName\": \"Japan\"\n    },\n    \"JP-CB\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Chūbu\"\n    },\n    \"JP-CG\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Chūgoku\"\n    },\n    \"JP-HKD\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Hokkaidō\"\n    },\n    \"JP-HR\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Hokuriku\"\n    },\n    \"JP-KN\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Kansai\"\n    },\n    \"JP-KY\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Kyūshū\"\n    },\n    \"JP-ON\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Okinawa\"\n    },\n    \"JP-SK\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Shikoku\"\n    },\n    \"JP-TH\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Tōhoku\"\n    },\n    \"JP-TK\": {\n      \"countryName\": \"Japan\",\n      \"zoneName\": \"Tōkyō\"\n    },\n    \"KE\": {\n      \"zoneName\": \"Kenya\"\n    },\n    \"KG\": {\n      \"zoneName\": \"Kyrgyzstan\"\n    },\n    \"KH\": {\n      \"zoneName\": \"Cambodia\"\n    },\n    \"KM\": {\n      \"zoneName\": \"Comoros\"\n    },\n    \"KP\": {\n      \"zoneName\": \"North Korea\"\n    },\n    \"KR\": {\n      \"zoneName\": \"South Korea\"\n    },\n    \"KW\": {\n      \"zoneName\": \"Kuwait\"\n    },\n    \"KY\": {\n      \"zoneName\": \"Cayman Islands\"\n    },\n    \"KZ\": {\n      \"zoneName\": \"Kazakhstan\"\n    },\n    \"LA\": {\n      \"zoneName\": \"Laos\"\n    },\n    \"LB\": {\n      \"zoneName\": \"Lebanon\"\n    },\n    \"LC\": {\n      \"zoneName\": \"Saint Lucia\"\n    },\n    \"LI\": {\n      \"zoneName\": \"Liechtenstein\"\n    },\n    \"LK\": {\n      \"zoneName\": \"Sri Lanka\"\n    },\n    \"LR\": {\n      \"zoneName\": \"Liberia\"\n    },\n    \"LS\": {\n      \"zoneName\": \"Lesotho\"\n    },\n    \"LT\": {\n      \"zoneName\": \"Lithuania\"\n    },\n    \"LU\": {\n      \"zoneName\": \"Luxembourg\"\n    },\n    \"LV\": {\n      \"zoneName\": \"Latvia\"\n    },\n    \"LY\": {\n      \"zoneName\": \"Libya\"\n    },\n    \"MA\": {\n      \"zoneName\": \"Morocco\"\n    },\n    \"MC\": {\n      \"zoneName\": \"Monaco\"\n    },\n    \"MD\": {\n      \"zoneName\": \"Moldova\"\n    },\n    \"ME\": {\n      \"zoneName\": \"Montenegro\"\n    },\n    \"MG\": {\n      \"zoneName\": \"Madagascar\"\n    },\n    \"MK\": {\n      \"zoneName\": \"North Macedonia\"\n    },\n    \"ML\": {\n      \"zoneName\": \"Mali\"\n    },\n    \"MM\": {\n      \"zoneName\": \"Myanmar\"\n    },\n    \"MN\": {\n      \"zoneName\": \"Mongolia\"\n    },\n    \"MO\": {\n      \"zoneName\": \"Macao\"\n    },\n    \"MQ\": {\n      \"zoneName\": \"Martinique\"\n    },\n    \"MR\": {\n      \"zoneName\": \"Mauritania\"\n    },\n    \"MS\": {\n      \"zoneName\": \"Montserrat\"\n    },\n    \"MT\": {\n      \"zoneName\": \"Malta\"\n    },\n    \"MU\": {\n      \"zoneName\": \"Mauritius\"\n    },\n    \"MV\": {\n      \"zoneName\": \"Maldives\"\n    },\n    \"MW\": {\n      \"zoneName\": \"Malawi\"\n    },\n    \"MX\": {\n      \"zoneName\": \"Mexico\"\n    },\n    \"MX-BC\": {\n      \"countryName\": \"Mexico\",\n      \"zoneName\": \"Baja California\"\n    },\n    \"MX-BCS\": {\n      \"countryName\": \"Mexico\",\n      \"zoneName\": \"Baja California Sur\"\n    },\n    \"MX-CE\": {\n      \"countryName\": \"Mexico\",\n      \"zoneName\": \"Central\"\n    },\n    \"MX-NE\": {\n      \"countryName\": \"Mexico\",\n      \"zoneName\": \"North East\"\n    },\n    \"MX-NO\": {\n      \"countryName\": \"Mexico\",\n      \"zoneName\": \"North\"\n    },\n    \"MX-NW\": {\n      \"countryName\": \"Mexico\",\n      \"zoneName\": \"North West\"\n    },\n    \"MX-OC\": {\n      \"countryName\": \"Mexico\",\n      \"zoneName\": \"Occidental\"\n    },\n    \"MX-OR\": {\n      \"countryName\": \"Mexico\",\n      \"zoneName\": \"Oriental\"\n    },\n    \"MX-PN\": {\n      \"countryName\": \"Mexico\",\n      \"zoneName\": \"Peninsula\"\n    },\n    \"MY\": {\n      \"zoneName\": \"Malaysia\"\n    },\n    \"MY-EM\": {\n      \"countryName\": \"Malaysia\",\n      \"zoneName\": \"Borneo\"\n    },\n    \"MY-WM\": {\n      \"countryName\": \"Malaysia\",\n      \"zoneName\": \"Peninsula\"\n    },\n    \"MZ\": {\n      \"zoneName\": \"Mozambique\"\n    },\n    \"NA\": {\n      \"zoneName\": \"Namibia\"\n    },\n    \"NC\": {\n      \"zoneName\": \"New Caledonia\"\n    },\n    \"NE\": {\n      \"zoneName\": \"Niger\"\n    },\n    \"NG\": {\n      \"zoneName\": \"Nigeria\"\n    },\n    \"NI\": {\n      \"zoneName\": \"Nicaragua\"\n    },\n    \"NL\": {\n      \"zoneName\": \"Netherlands\"\n    },\n    \"NO\": {\n      \"zoneName\": \"Norway\"\n    },\n    \"NO-NO1\": {\n      \"countryName\": \"Norway\",\n      \"zoneName\": \"Eastern Norway\"\n    },\n    \"NO-NO2\": {\n      \"countryName\": \"Norway\",\n      \"zoneName\": \"Southern Norway\"\n    },\n    \"NO-NO3\": {\n      \"countryName\": \"Norway\",\n      \"zoneName\": \"Central Norway\"\n    },\n    \"NO-NO4\": {\n      \"countryName\": \"Norway\",\n      \"zoneName\": \"Northern Norway\"\n    },\n    \"NO-NO5\": {\n      \"countryName\": \"Norway\",\n      \"zoneName\": \"Western Norway\"\n    },\n    \"NP\": {\n      \"zoneName\": \"Nepal\"\n    },\n    \"NZ\": {\n      \"zoneName\": \"New Zealand\"\n    },\n    \"NZ-NZA\": {\n      \"countryName\": \"New Zealand\",\n      \"zoneName\": \"Auckland Islands\"\n    },\n    \"NZ-NZC\": {\n      \"countryName\": \"New Zealand\",\n      \"zoneName\": \"Chatham Islands\"\n    },\n    \"NZ-NZST\": {\n      \"countryName\": \"New Zealand\",\n      \"zoneName\": \"Stewart Island\"\n    },\n    \"OM\": {\n      \"zoneName\": \"Oman\"\n    },\n    \"PA\": {\n      \"zoneName\": \"Panama\"\n    },\n    \"PE\": {\n      \"zoneName\": \"Peru\"\n    },\n    \"PF\": {\n      \"zoneName\": \"French Polynesia\"\n    },\n    \"PG\": {\n      \"zoneName\": \"Papua New Guinea\"\n    },\n    \"PH\": {\n      \"zoneName\": \"Philippines\"\n    },\n    \"PH-LU\": {\n      \"countryName\": \"Philippines\",\n      \"zoneName\": \"Luzon\"\n    },\n    \"PH-MI\": {\n      \"countryName\": \"Philippines\",\n      \"zoneName\": \"Mindanao\"\n    },\n    \"PH-VI\": {\n      \"countryName\": \"Philippines\",\n      \"zoneName\": \"Visayas\"\n    },\n    \"PK\": {\n      \"zoneName\": \"Pakistan\"\n    },\n    \"PL\": {\n      \"zoneName\": \"Poland\"\n    },\n    \"PM\": {\n      \"zoneName\": \"Saint Pierre and Miquelon\"\n    },\n    \"PR\": {\n      \"zoneName\": \"Puerto Rico\"\n    },\n    \"PS\": {\n      \"zoneName\": \"State of Palestine\"\n    },\n    \"PT\": {\n      \"zoneName\": \"Portugal\"\n    },\n    \"PT-AC\": {\n      \"countryName\": \"Portugal\",\n      \"zoneName\": \"Azores\"\n    },\n    \"PT-MA\": {\n      \"countryName\": \"Portugal\",\n      \"zoneName\": \"Madeira\"\n    },\n    \"PW\": {\n      \"zoneName\": \"Palau\"\n    },\n    \"PY\": {\n      \"zoneName\": \"Paraguay\"\n    },\n    \"QA\": {\n      \"zoneName\": \"Qatar\"\n    },\n    \"RE\": {\n      \"zoneName\": \"Réunion\"\n    },\n    \"RO\": {\n      \"zoneName\": \"Romania\"\n    },\n    \"RS\": {\n      \"zoneName\": \"Serbia\"\n    },\n    \"RU\": {\n      \"zoneName\": \"Russia\"\n    },\n    \"RU-1\": {\n      \"countryName\": \"Russia\",\n      \"zoneName\": \"Europe-Ural\"\n    },\n    \"RU-2\": {\n      \"countryName\": \"Russia\",\n      \"zoneName\": \"Siberia\"\n    },\n    \"RU-AS\": {\n      \"countryName\": \"Russia\",\n      \"zoneName\": \"East\"\n    },\n    \"RU-EU\": {\n      \"countryName\": \"Russia\",\n      \"zoneName\": \"Arctic\"\n    },\n    \"RU-FE\": {\n      \"countryName\": \"Russia\",\n      \"zoneName\": \"Far East\"\n    },\n    \"RU-KGD\": {\n      \"countryName\": \"Russia\",\n      \"zoneName\": \"Kaliningrad\"\n    },\n    \"RW\": {\n      \"zoneName\": \"Rwanda\"\n    },\n    \"SA\": {\n      \"zoneName\": \"Saudi Arabia\"\n    },\n    \"SB\": {\n      \"zoneName\": \"Solomon Islands\"\n    },\n    \"SC\": {\n      \"zoneName\": \"Seychelles\"\n    },\n    \"SD\": {\n      \"zoneName\": \"Sudan\"\n    },\n    \"SE\": {\n      \"zoneName\": \"Sweden\"\n    },\n    \"SE-SE1\": {\n      \"countryName\": \"Sweden\",\n      \"zoneName\": \"North Sweden\"\n    },\n    \"SE-SE2\": {\n      \"countryName\": \"Sweden\",\n      \"zoneName\": \"North Central Sweden\"\n    },\n    \"SE-SE3\": {\n      \"countryName\": \"Sweden\",\n      \"zoneName\": \"South Central Sweden\"\n    },\n    \"SE-SE4\": {\n      \"countryName\": \"Sweden\",\n      \"zoneName\": \"South Sweden\"\n    },\n    \"SG\": {\n      \"zoneName\": \"Singapore\"\n    },\n    \"SI\": {\n      \"zoneName\": \"Slovenia\"\n    },\n    \"SJ\": {\n      \"zoneName\": \"Svalbard and Jan Mayen\"\n    },\n    \"SK\": {\n      \"zoneName\": \"Slovakia\"\n    },\n    \"SL\": {\n      \"zoneName\": \"Sierra Leone\"\n    },\n    \"SN\": {\n      \"zoneName\": \"Senegal\"\n    },\n    \"SO\": {\n      \"zoneName\": \"Somalia\"\n    },\n    \"SR\": {\n      \"zoneName\": \"Suriname\"\n    },\n    \"SS\": {\n      \"zoneName\": \"South Sudan\"\n    },\n    \"ST\": {\n      \"zoneName\": \"São Tomé and Príncipe\"\n    },\n    \"SV\": {\n      \"zoneName\": \"El Salvador\"\n    },\n    \"SY\": {\n      \"zoneName\": \"Syria\"\n    },\n    \"SZ\": {\n      \"zoneName\": \"Eswatini\"\n    },\n    \"TD\": {\n      \"zoneName\": \"Chad\"\n    },\n    \"TF\": {\n      \"zoneName\": \"French Southern Territories\"\n    },\n    \"TG\": {\n      \"zoneName\": \"Togo\"\n    },\n    \"TH\": {\n      \"zoneName\": \"Thailand\"\n    },\n    \"TJ\": {\n      \"zoneName\": \"Tajikistan\"\n    },\n    \"TL\": {\n      \"zoneName\": \"Timor-Leste\"\n    },\n    \"TM\": {\n      \"zoneName\": \"Turkmenistan\"\n    },\n    \"TN\": {\n      \"zoneName\": \"Tunisia\"\n    },\n    \"TO\": {\n      \"zoneName\": \"Tonga\"\n    },\n    \"TR\": {\n      \"zoneName\": \"Turkey\"\n    },\n    \"TT\": {\n      \"zoneName\": \"Trinidad and Tobago\"\n    },\n    \"TW\": {\n      \"zoneName\": \"Taiwan\"\n    },\n    \"TZ\": {\n      \"zoneName\": \"Tanzania\"\n    },\n    \"UA\": {\n      \"zoneName\": \"Ukraine\"\n    },\n    \"UA-CR\": {\n      \"countryName\": \"Ukraine\",\n      \"zoneName\": \"Crimea\"\n    },\n    \"UG\": {\n      \"zoneName\": \"Uganda\"\n    },\n    \"US\": {\n      \"zoneName\": \"United States\"\n    },\n    \"US-AK\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Alaska\"\n    },\n    \"US-AK-SEAPA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Southeast Alaska Power Agency\"\n    },\n    \"US-HI\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Hawaii\"\n    },\n    \"US-HI-HA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Hawaii\"\n    },\n    \"US-HI-KA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Kauai\"\n    },\n    \"US-HI-KH\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Kahoolawe\"\n    },\n    \"US-HI-LA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Lanai\"\n    },\n    \"US-HI-MA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Maui\"\n    },\n    \"US-HI-MO\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Molokai\"\n    },\n    \"US-HI-NI\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Niihau\"\n    },\n    \"US-HI-OA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Oahu\"\n    },\n    \"US-CAL-BANC\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"BANC\",\n      \"zoneName\": \"Balancing Authority of Northern California\"\n    },\n    \"US-CAL-CISO\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"California ISO\",\n      \"zoneName\": \"CAISO\"\n    },\n    \"US-CAL-IID\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Imperial Irrigation District\"\n    },\n    \"US-CAL-LDWP\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Los Angeles Department of Water and Power\"\n    },\n    \"US-CAL-TIDC\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Turlock Irrigation District\"\n    },\n    \"US-CAR-CPLE\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Duke Energy Progress East\"\n    },\n    \"US-CAR-CPLW\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Duke Energy Progress West\"\n    },\n    \"US-CAR-DUK\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Duke Energy Carolinas\"\n    },\n    \"US-CAR-SC\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"South Carolina Public Service Authority\"\n    },\n    \"US-CAR-SCEG\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"South Carolina Electric & Gas Company\"\n    },\n    \"US-CAR-YAD\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"Alcoa Power Generating\",\n      \"zoneName\": \"Alcoa Power Generating, Inc. Yadkin Division\"\n    },\n    \"US-CENT-SPA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Southwestern Power Administration\"\n    },\n    \"US-CENT-SWPP\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"SPP\",\n      \"zoneName\": \"Southwest Power Pool\"\n    },\n    \"US-FLA-FMPP\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Florida Municipal Power Pool\"\n    },\n    \"US-FLA-FPC\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Duke Energy Florida\"\n    },\n    \"US-FLA-FPL\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Florida Power and Light Company\"\n    },\n    \"US-FLA-GVL\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Gainesville Regional Utilities\"\n    },\n    \"US-FLA-HST\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"City of Homestead\"\n    },\n    \"US-FLA-JEA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Jacksonville Electric Authority\"\n    },\n    \"US-FLA-SEC\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Seminole Electric Cooperative\"\n    },\n    \"US-FLA-TAL\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"City of Tallahassee\"\n    },\n    \"US-FLA-TEC\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Tampa Electric Company\"\n    },\n    \"US-MIDA-PJM\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"PJM\",\n      \"zoneName\": \"PJM Interconnection\"\n    },\n    \"US-MIDW-AECI\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Associated Electric Cooperative\"\n    },\n    \"US-MIDW-LGEE\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"Louisville Gas And Electric Company\",\n      \"zoneName\": \"Louisville Gas and Electric Company and Kentucky Utilities\"\n    },\n    \"US-MIDW-MISO\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"MISO\",\n      \"zoneName\": \"Midcontinent ISO\"\n    },\n    \"US-NE-ISNE\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"ISO New England\"\n    },\n    \"US-NW-AVA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Avista Corporation\"\n    },\n    \"US-NW-BPAT\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Bonneville Power Administration\"\n    },\n    \"US-NW-CHPD\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Chelan County\"\n    },\n    \"US-NW-DOPD\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Douglas County\"\n    },\n    \"US-NW-GCPD\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Grant County\"\n    },\n    \"US-NW-GRID\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Gridforce Energy Management\"\n    },\n    \"US-NW-IPCO\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Idaho Power Company\"\n    },\n    \"US-NW-NEVP\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Nevada Power Company\"\n    },\n    \"US-NW-NWMT\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Northwestern Energy\"\n    },\n    \"US-NW-PACE\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Pacificorp East\"\n    },\n    \"US-NW-PACW\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Pacificorp West\"\n    },\n    \"US-NW-PGE\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Portland General Electric Company\"\n    },\n    \"US-NW-PSCO\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"PSCo\",\n      \"zoneName\": \"Public Service Company of Colorado\"\n    },\n    \"US-NW-PSEI\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Puget Sound Energy\"\n    },\n    \"US-NW-SCL\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Seattle City Light\"\n    },\n    \"US-NW-TPWR\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"City of Tacoma\"\n    },\n    \"US-NW-WACM\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"WAPA Rocky Mountains\",\n      \"zoneName\": \"Western Area Power Administration - Rocky Mountain Region\"\n    },\n    \"US-NW-WAUW\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"WAPA Upper Great Plains\",\n      \"zoneName\": \"Western Area Power Administration - Upper Great Plains West\"\n    },\n    \"US-NY-NYIS\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"New York ISO\"\n    },\n    \"US-SE-SEPA\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Southeastern Power Administration\"\n    },\n    \"US-SE-SOCO\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Southern Company Services\"\n    },\n    \"US-SW-AZPS\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Arizona Public Service Company\"\n    },\n    \"US-SW-EPE\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"El Paso Electric Company\"\n    },\n    \"US-SW-PNM\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Public Service Company of New Mexico\"\n    },\n    \"US-SW-SRP\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Salt River Project\"\n    },\n    \"US-SW-TEPC\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Tucson Electric Power Company\"\n    },\n    \"US-SW-WALC\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"WAPA Desert Southwest\",\n      \"zoneName\": \"Western Area Power Administration - Desert Southwest Region\"\n    },\n    \"US-TEN-TVA\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"TVA\",\n      \"zoneName\": \"Tennessee Valley Authority\"\n    },\n    \"US-TEX-ERCO\": {\n      \"countryName\": \"USA\",\n      \"displayName\": \"ERCOT\",\n      \"zoneName\": \"Electric Reliability Council of Texas\"\n    },\n    \"UY\": {\n      \"zoneName\": \"Uruguay\"\n    },\n    \"UZ\": {\n      \"zoneName\": \"Uzbekistan\"\n    },\n    \"VC\": {\n      \"zoneName\": \"Saint Vincent and the Grenadines\"\n    },\n    \"VE\": {\n      \"zoneName\": \"Venezuela\"\n    },\n    \"VI\": {\n      \"countryName\": \"USA\",\n      \"zoneName\": \"Virgin Islands\"\n    },\n    \"VN\": {\n      \"zoneName\": \"Vietnam\"\n    },\n    \"VU\": {\n      \"zoneName\": \"Vanuatu\"\n    },\n    \"WS\": {\n      \"zoneName\": \"Samoa\"\n    },\n    \"XK\": {\n      \"zoneName\": \"Kosovo\"\n    },\n    \"XX\": {\n      \"zoneName\": \"Northern Cyprus\"\n    },\n    \"YE\": {\n      \"zoneName\": \"Yemen\"\n    },\n    \"YT\": {\n      \"zoneName\": \"Mayotte\"\n    },\n    \"ZA\": {\n      \"zoneName\": \"South Africa\"\n    },\n    \"ZM\": {\n      \"zoneName\": \"Zambia\"\n    },\n    \"ZW\": {\n      \"zoneName\": \"Zimbabwe\"\n    }\n  }\n}\n"
  },
  {
    "path": "config/zones/AD.yaml",
    "content": "bounding_box:\n  - - 1.431014310143127\n    - 42.42893264363089\n  - - 1.722617226172275\n    - 42.60924908058364\ncenter_point:\n  - 1.5768157681577009\n  - 42.51909086210726\ncentroid:\n  - 1.593015930159325\n  - 42.53411723185333\ncontributors:\n  - Manu1400\n  - autipial\ncountry: AD\ncountry_name: Andorra\ncurrency: EUR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Europe/Andorra\nzone_name: Andorra\n"
  },
  {
    "path": "config/zones/AE.yaml",
    "content": "bounding_box:\n  - - 51.58986018039593\n    - 22.6318083973945\n  - - 56.3819638196382\n    - 26.061638283086467\ncenter_point:\n  - 54.35428314468383\n  - 23.855518564941015\ncentroid:\n  - 54.608389122127726\n  - 24.402860761486757\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 600.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1200.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 36250.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 36450.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 37280.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 37740.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 38920.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 41660.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1390.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2780.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4170.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 5570.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 350.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 600.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1940.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2330.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 3000.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3600.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 5940.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 6010.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\ncontributors:\n  - q--\n  - florianscheidl\n  - MisterClean\ncountry: AE\ncountry_name: United Arab Emirates\ncurrency: AED\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.91193148872398\n        oil: 0.0\n        solar: 0.08806834372511946\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.8802408112760882\n        oil: 0.0\n        solar: 0.11975904640299682\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.8428767238407804\n        oil: 0.0\n        solar: 0.1571230965177479\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.6773326171573966\n        oil: 0.0\n        solar: 0.32266724667885344\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.7047717265187831\n        oil: 0.0\n        solar: 0.2952281623735283\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6456891698673624\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.23727536945180464\n        oil: 0.0\n        solar: 0.11548202997847996\n        unknown: 0.0015533738033579184\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.7661878052566268\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.1702784339815322\n        oil: 0.0\n        solar: 0.061690443983189604\n        unknown: 0.001843265887442152\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6795480056248291\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.24752923194499274\n        oil: 0.0\n        solar: 0.07128789104234305\n        unknown: 0.0016348372505816842\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: GCCIA.fetch_consumption\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\nsources:\n  Climatescope:\n    link: https://www.global-climatescope.org/markets/ae/\n  IAEA PRIS:\n    link: https://pris.iaea.org/PRIS/CountryStatistics/CountryDetails.aspx?current=AE\ntimezone: Asia/Dubai\nzone_name: United Arab Emirates\n"
  },
  {
    "path": "config/zones/AF.yaml",
    "content": "bounding_box:\n  - - 60.48600486004861\n    - 29.386043704048674\n  - - 74.89334893348934\n    - 38.443366953841945\ncenter_point:\n  - 66.0540719083482\n  - 33.82887273724214\ncentroid:\n  - 67.63767919369339\n  - 34.81340519194689\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 350.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 470.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: AF\ncountry_name: Afghanistan\ncurrency: AFN\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Kabul\nzone_name: Afghanistan\n"
  },
  {
    "path": "config/zones/AG.yaml",
    "content": "bounding_box:\n  - - -61.882818828188235\n    - 17.048678601114915\n  - - -61.670416704166996\n    - 17.16459631058453\ncenter_point:\n  - -61.776617766177615\n  - 17.10663745584972\ncentroid:\n  - -61.78201782017815\n  - 17.0901800032707\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\ncountry: AG\ncountry_name: Antigua and Barbuda\ncurrency: XCD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Antigua\nzone_name: Antigua and Barbuda\n"
  },
  {
    "path": "config/zones/AL.yaml",
    "content": "bounding_box:\n  - - 19.28178498470286\n    - 39.64823065325469\n  - - 21.036810368103687\n    - 42.65504373123831\ncenter_point:\n  - 19.97935269445456\n  - 41.16342904996394\ncentroid:\n  - 19.985354537034763\n  - 41.13124064433871\ncapacity:\n  biomass:\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 0.0\n  coal:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n  gas:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n  geothermal:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n  hydro:\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1492.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2203.0\n  hydro storage:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n  nuclear:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n  oil:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 97.0\n  solar:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 5.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 195.0\n  unknown:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n  wind:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\ncontributors:\n  - corradio\n  - nessie2013\n  - autipial\ncountry: AL\ncountry_name: Albania\ncurrency: ALL\nemissionFactors:\n  lifecycle:\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\ntimezone: Europe/Tirane\nzone_name: Albania\n"
  },
  {
    "path": "config/zones/AM.yaml",
    "content": "bounding_box:\n  - - 43.439834398344004\n    - 38.86410530673169\n  - - 46.60426604266044\n    - 41.28979070859606\ncenter_point:\n  - 44.63778369870547\n  - 40.48084853967063\ncentroid:\n  - 45.282401167166356\n  - 40.04925295979527\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1570.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1830.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1330.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1340.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1350.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1360.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1350.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 410.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 450.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 400.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 490.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncontributors:\n  - tmslaine\n  - systemcatch\n  - alixunderplatz\n  - nessie2013\ncountry: AM\ncountry_name: Armenia\ncurrency: AMD\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 5.250073475843808e-07\n        gas: 0.44864691967960246\n        geothermal: 0.0\n        hydro: 0.33631257179959806\n        hydro discharge: 0.0\n        nuclear: 0.21485408635458791\n        oil: 4.647186809540268e-05\n        solar: 1.3561075398858545e-07\n        unknown: 8.440025868952448e-05\n        wind: 5.4472902580729235e-05\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.46389453736449615\n        geothermal: 0.0\n        hydro: 0.19046407822035902\n        hydro discharge: 0.0\n        nuclear: 0.3456206557298584\n        oil: 1.8951088677709353e-05\n        solar: 0.0\n        unknown: 4.115911610833948e-07\n        wind: 1.2884592868697575e-06\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Yerevan\nzone_name: Armenia\n"
  },
  {
    "path": "config/zones/AO.yaml",
    "content": "bounding_box:\n  - - 11.752317523175265\n    - -18.03145488319263\n  - - 24.060840608406096\n    - -4.40325306493046\ncenter_point:\n  - 17.907600443601794\n  - -11.939312306534951\ncentroid:\n  - 16.848673894821456\n  - -11.02809286786516\ncountry: AO\ncountry_name: Angola\ncurrency: AOA\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.10893289709207192\n        geothermal: 0.0\n        hydro: 0.70428882343253\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.1622255605690663\n        solar: 0.02455261358974591\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.10893206031944175\n        geothermal: 0.0\n        hydro: 0.7042911878765116\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.16222413992273907\n        solar: 0.024552889130142887\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Luanda\nzone_name: Angola\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/AR.yaml",
    "content": "bounding_box:\n  - - -73.5865358653586\n    - -55.05070560615871\n  - - -53.66033660336599\n    - -21.792340568207123\ncenter_point:\n  - -63.53842463864095\n  - -38.43381621684122\ncentroid:\n  - -65.46265703746403\n  - -38.10807621875977\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 330.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 360.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 500.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 17280.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 18150.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 18300.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 20180.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 20630.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 21480.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 22150.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10270.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10320.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10340.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10380.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 10390.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 9200.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1750.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 450.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 770.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1080.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1110.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1410.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1740.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4660.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 4460.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 4500.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 4540.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 4520.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4530.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4540.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 4470.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 750.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1610.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2620.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 3290.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3310.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 3710.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 4320.0\ncontributors:\n  - systemcatch\n  - corradio\n  - nessie2013\ncountry: AR\ncountry_name: Argentina\ncurrency: ARS\ndisclaimer: Unknown production is the aggregation of thermal production, mainly gas.\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 255.5\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 246.81\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 279.5\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 270.81\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00027789012343998375\n        coal: 0.005676778468881059\n        gas: 0.4945226600909888\n        geothermal: 0.0\n        hydro: 0.3277187487882064\n        hydro discharge: 0.003448843724486355\n        nuclear: 0.05149806273631078\n        oil: 0.018987686741410072\n        solar: 0.012835729711168814\n        unknown: 0.020921991059044295\n        wind: 0.0641116708717701\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00025039036123554464\n        coal: 0.01208977359454281\n        gas: 0.6053093670933865\n        geothermal: 0.0\n        hydro: 0.30567173441426626\n        hydro discharge: 7.924054943218353e-06\n        nuclear: 0.048791348410765115\n        oil: 0.016486308405175495\n        solar: 5.31884255564326e-05\n        unknown: 0.010874744944877085\n        wind: 0.00046521016866389977\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0012138587328021056\n        coal: 0.003043457378296288\n        gas: 0.57124930474678\n        geothermal: 9.153155959476518e-10\n        hydro: 0.2848728028137004\n        hydro discharge: 0.005327156130860633\n        nuclear: 0.06153218690490069\n        oil: 0.014813029168646338\n        solar: 0.0034026438346446575\n        unknown: 0.026677913687318013\n        wind: 0.02786764054688631\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010451826739823384\n        coal: 0.008157568869293353\n        gas: 0.5625853167523365\n        geothermal: 1.4557096938924618e-10\n        hydro: 0.22281253641717103\n        hydro discharge: 0.0056150549226362655\n        nuclear: 0.07751691182346167\n        oil: 0.014051847908229696\n        solar: 0.006329076014790466\n        unknown: 0.0423205436874353\n        wind: 0.05956596471550896\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010543003917456157\n        coal: 0.016208625627989144\n        gas: 0.5814542023690398\n        geothermal: 7.017843085703891e-10\n        hydro: 0.18105127606630356\n        hydro discharge: 0.011651629362349774\n        nuclear: 0.0705748161791272\n        oil: 0.01949449106370705\n        solar: 0.00826485548375743\n        unknown: 0.038960532633685825\n        wind: 0.07128526352373785\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008836784979185044\n        coal: 0.0019391538597257703\n        gas: 0.055606818075429186\n        geothermal: 2.6097065369217027e-10\n        hydro: 0.23619797668018155\n        hydro discharge: 0.002929815032777758\n        nuclear: 0.05039556862033191\n        oil: 0.0033993487354289447\n        solar: 0.019165772101836644\n        unknown: 0.5231547867368536\n        wind: 0.09837397817941206\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007687108479401486\n        coal: 0.0004044300556156979\n        gas: 0.0022530904091103243\n        geothermal: 3.3578213616355565e-06\n        hydro: 0.2970931621763669\n        hydro discharge: 2.4378016131133422e-05\n        nuclear: 0.06409624569912527\n        oil: 0.0001322299106921567\n        solar: 0.021943525861174384\n        unknown: 0.5082869934384935\n        wind: 0.09807555243219705\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008886499730726591\n        coal: 0.0003891975299504092\n        gas: 0.00023765283388701235\n        geothermal: 4.658431724300754e-06\n        hydro: 0.25001399820337483\n        hydro discharge: 0.0\n        nuclear: 0.07477519233160665\n        oil: 0.00021162434603622216\n        solar: 0.02698552858936858\n        unknown: 0.5265037188143048\n        wind: 0.11199192793014612\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.3529\n    - datetime: '2021-01-01'\n      value: 0.3697\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2752\n    - datetime: '2021-01-01'\n      value: 0.2892\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  production: CAMMESA.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: America/Argentina/Buenos_Aires\nzone_name: Argentina\n"
  },
  {
    "path": "config/zones/AT.yaml",
    "content": "bounding_box:\n  - - 9.530757016749972\n    - 46.378721262595874\n  - - 17.148771487714896\n    - 49.00762042674033\ncenter_point:\n  - 14.586486182061494\n  - 47.681668614089304\ncentroid:\n  - 13.533233667973912\n  - 47.603738593517676\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 617.9\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 640.8\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 649.8\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 647.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 600.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 585.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 629.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 677.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 598.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 246.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4465.8\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 4467.7\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4463.2\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 4015.3\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 4449.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 4349.5\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 4206.12\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 4225.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.9\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 0.25\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 8545.7\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 8589.3\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 7997.4\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 8159.7\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 8371.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 8311.82\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 8672.56\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 8336.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 8427.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 3401.1\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 3120.1\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 3459.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 3503.28\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 3362.5\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 3485.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 3512.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 177.9\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 164.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 163.61\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 120.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 125.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1031.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1193.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1192.7\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1333.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1851.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2500.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 3265.3\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 7294.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 8254.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 55.3\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 65.1\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 122.8\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 957.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 954.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 845.24\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 879.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 855.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2696.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 2887.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 3034.6\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 3133.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 3198.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 3500.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 3568.82\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 4021.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 4035.0\ncontributors:\n  - corradio\n  - brandongalbraith\ncountry: AT\ncountry_name: Austria\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 435.2364657\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 407.84\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 330.91\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 333.86\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 151.02\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 190.65\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 202.22\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 109.66\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 77.02\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 110.12\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1168.890109\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1187.127343\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 555.2364657\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 527.8399999999999\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 450.91\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 453.86\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 161.72\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 201.35\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 212.92\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 120.36\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 87.72\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 120.82\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 31.0\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.051071595089056086\n        coal: 0.17508933729535006\n        gas: 0.1210720713860492\n        geothermal: 4.018738745707861e-05\n        hydro: 0.2950083756952926\n        hydro discharge: 0.059354295377081825\n        nuclear: 0.07894175622136311\n        oil: 0.0008278344955549013\n        solar: 0.027521929090297628\n        unknown: 0.09614889594776513\n        wind: 0.09492380791184424\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.058046406194726965\n        coal: 0.14321001485471613\n        gas: 0.11704915948819578\n        geothermal: 4.9624356963156514e-05\n        hydro: 0.4133036730434246\n        hydro discharge: 0.069024690725902\n        nuclear: 0.06212226986933998\n        oil: 0.0007253083264983775\n        solar: 0.02573745866354416\n        unknown: 0.018792759839384186\n        wind: 0.09193873606209844\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05821343802583453\n        coal: 0.13843334076507885\n        gas: 0.13579929706051178\n        geothermal: 5.4114651827314045e-05\n        hydro: 0.3736330355190864\n        hydro discharge: 0.06074024262648513\n        nuclear: 0.0638251557567265\n        oil: 0.0008126498410111529\n        solar: 0.029749466006454797\n        unknown: 0.02129410636343046\n        wind: 0.11744514519748209\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05988692904423825\n        coal: 0.13470191860067782\n        gas: 0.12456793992888127\n        geothermal: 5.340422558543311e-05\n        hydro: 0.3838026673389602\n        hydro discharge: 0.06499461326188559\n        nuclear: 0.07033829473135082\n        oil: 0.0009679308166965346\n        solar: 0.0355669447732903\n        unknown: 0.01031271725647022\n        wind: 0.11480662901690958\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.052692310687495185\n        coal: 0.10066533156038646\n        gas: 0.14706677296781698\n        geothermal: 5.119352299623304e-05\n        hydro: 0.39887799076209196\n        hydro discharge: 0.05994530880212914\n        nuclear: 0.06152465060467812\n        oil: 0.0012349110019306102\n        solar: 0.03285395924600757\n        unknown: 0.008723534397521266\n        wind: 0.1363640141800476\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.048207279175885645\n        coal: 0.07082717701086534\n        gas: 0.13838244726856092\n        geothermal: 5.8308720971921614e-05\n        hydro: 0.43431945039085806\n        hydro discharge: 0.07928257916276796\n        nuclear: 0.05700380783242925\n        oil: 0.0011679798530553939\n        solar: 0.028941028232291114\n        unknown: 0.009055703203076457\n        wind: 0.13275420505947386\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0448817590531587\n        coal: 0.08849409433124993\n        gas: 0.14989025345211068\n        geothermal: 5.0296597358709414e-05\n        hydro: 0.41777054789281454\n        hydro discharge: 0.07476985408270749\n        nuclear: 0.06561085494847148\n        oil: 0.0008933552816870226\n        solar: 0.028033106197319257\n        unknown: 0.008037608124729085\n        wind: 0.12156823566568795\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03576138072515659\n        coal: 0.1078287315030764\n        gas: 0.15950215808263338\n        geothermal: 5.022624895002734e-05\n        hydro: 0.38418684571538664\n        hydro discharge: 0.07627329104886481\n        nuclear: 0.06780532015966545\n        oil: 0.0009097532014691727\n        solar: 0.029607204533975612\n        unknown: 0.008295868729614585\n        wind: 0.12977917574735126\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 5.167026400154259e-10\n        biomass: 0.041377353648945306\n        coal: 0.06997395175571769\n        gas: 0.10218100887066102\n        geothermal: 3.744251234029116e-05\n        hydro: 0.4651549847278011\n        hydro discharge: 0.07454983330533844\n        nuclear: 0.05316159269043179\n        oil: 0.0006433552410280872\n        solar: 0.04730815180697796\n        unknown: 0.004027125089097749\n        wind: 0.141585165215881\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 2.8747037788299856e-07\n        biomass: 0.04530903997258034\n        coal: 0.04461782424554579\n        gas: 0.08914198064008907\n        geothermal: 3.132168492051292e-05\n        hydro: 0.46846398896326674\n        hydro discharge: 0.07391953755441467\n        nuclear: 0.0393007961340409\n        oil: 0.0005418242689240255\n        solar: 0.08981516846705681\n        unknown: 0.0046080066740009\n        wind: 0.14425013699561962\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.7784\n    - datetime: '2021-01-01'\n      value: 0.7329\n    - datetime: '2022-01-01'\n      value: 0.7323\n    - datetime: '2023-01-01'\n      value: 0.8431\n    - datetime: '2024-01-01'\n      value: 0.8784\n    - datetime: '2025-01-01'\n      value: 0.8286\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.7071\n    - datetime: '2021-01-01'\n      value: 0.6466\n    - datetime: '2022-01-01'\n      value: 0.6487\n    - datetime: '2023-01-01'\n      value: 0.7817\n    - datetime: '2024-01-01'\n      value: 0.8394\n    - datetime: '2025-01-01'\n      value: 0.771\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Vienna\nzone_name: Austria\n"
  },
  {
    "path": "config/zones/AU-LH.yaml",
    "content": "bounding_box:\n  - - 159.03754045700703\n    - -31.599608474752188\n  - - 159.10462909730177\n    - -31.511655274959526\ncenter_point:\n  - 159.0770827681741\n  - -31.543277807327584\ncentroid:\n  - 159.07032762334973\n  - -31.545415281659476\ncapacity:\n  battery storage: 1\n  gas: 0.84\n  solar: 1\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Oceania\ntimezone: Australia/Lord_Howe\nzone_name: Lord Howe Island\n"
  },
  {
    "path": "config/zones/AU-NSW.yaml",
    "content": "bounding_box:\n  - - 141.00081000810005\n    - -37.50992332258846\n  - - 153.60453604536045\n    - -28.149210512208025\ncenter_point:\n  - 147.30297460811997\n  - -32.79160161556883\ncentroid:\n  - 148.92405021611197\n  - -32.790369209558925\ncapacity:\n  battery storage:\n    - datetime: '2024-01-01'\n      source: opennem.org.au\n      value: 346.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2131.44\n  biomass:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 101.98\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 118.79\n  coal:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 8240.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 8270.0\n  gas:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2007.0\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 2067.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2527.58\n  hydro:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2658.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2665.5\n  hydro storage:\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 910.0\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 840.0\n  oil:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 148.0\n    - datetime: '2022-01-01'\n      source: opennem.org.au\n      value: 176.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 122.5\n  solar:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 8257.99\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 8581.99\n    - datetime: '2022-01-01'\n      source: opennem.org.au\n      value: 8821.99\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 9529.31\n  wind:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 1743.82\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 2072.62\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 2472.42\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2837.13\ncontributors:\n  - brandongalbraith\n  - jarek\n  - corradio\n  - alejandranavcas\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 397.36\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 524.23\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 456.05\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 470.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 449.78\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 619.68\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 559.46\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 454.79\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 378.37\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 387.68\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 344.54\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 430.36\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 557.23\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 489.05\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 503.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 482.78\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 643.68\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 583.46\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 478.79\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 402.37\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 411.68\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 368.54\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 7.063643821582298e-05\n        biomass: 0.0\n        coal: 0.8221916109110292\n        gas: 0.028009699884670797\n        geothermal: 0.0\n        hydro: 0.038419694831549035\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00011965981485803958\n        solar: 0.04727179158764417\n        unknown: 0.0\n        wind: 0.06391701231513959\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 7.063674472651057e-05\n        biomass: 1.5378212772192232e-10\n        coal: 0.8222107619338048\n        gas: 0.0280083610666201\n        geothermal: 0.0\n        hydro: 0.03841717589016781\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00011964956934553076\n        solar: 0.04726175289637834\n        unknown: 0.0\n        wind: 0.06391176800862491\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8855619639643786\n        gas: 0.04567468649044042\n        geothermal: 0.0\n        hydro: 0.030368482311111472\n        hydro discharge: 1.0345893075816433e-08\n        nuclear: 0.0\n        oil: 9.928490335917339e-05\n        solar: 0.009036227008718669\n        unknown: 0.0\n        wind: 0.029259352851330665\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.870498806117249\n        gas: 0.02006780594023129\n        geothermal: 0.0\n        hydro: 0.04395810309469981\n        hydro discharge: 9.445682320748764e-09\n        nuclear: 0.0\n        oil: 3.3429488530848677e-05\n        solar: 0.018952441642181208\n        unknown: 0.0\n        wind: 0.046489398177437066\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8474754343804146\n        gas: 0.029903053331725812\n        geothermal: 0.0\n        hydro: 0.028451978502500343\n        hydro discharge: 1.4146294595720225e-08\n        nuclear: 0.0\n        oil: 5.903820606277707e-05\n        solar: 0.029300013497777284\n        unknown: 0.0\n        wind: 0.06481048238250411\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8311855632479336\n        gas: 0.016988541112617238\n        geothermal: 0.0\n        hydro: 0.03709946723264491\n        hydro discharge: 5.701422545737844e-09\n        nuclear: 0.0\n        oil: 2.133820736881785e-05\n        solar: 0.04274576209029661\n        unknown: 0.0\n        wind: 0.07195932842588446\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 7.93435809546971e-07\n        biomass: 2.201657218318238e-06\n        coal: 0.7842877686779857\n        gas: 0.015989187943045123\n        geothermal: 0.0\n        hydro: 0.04183519938497916\n        hydro discharge: 1.573520535760219e-08\n        nuclear: 0.0\n        oil: 1.8940736889441798e-05\n        solar: 0.07315916254392034\n        unknown: 0.0\n        wind: 0.08470675738182094\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.00029833585862328645\n        biomass: 2.8508611477086534e-05\n        coal: 0.6828335760831606\n        gas: 0.0366044896228916\n        geothermal: 0.0\n        hydro: 0.05269246326619177\n        hydro discharge: 3.668549310127415e-07\n        nuclear: 0.0\n        oil: 3.060680088325294e-05\n        solar: 0.137902921658525\n        unknown: 0.0\n        wind: 0.0896087073731296\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0006873714978485496\n        biomass: 0.0012016838898375678\n        coal: 0.637281177807374\n        gas: 0.02212743013475213\n        geothermal: 0.0\n        hydro: 0.04806952807563024\n        hydro discharge: 4.626270400250677e-06\n        nuclear: 0.0\n        oil: 5.1153437495311195e-05\n        solar: 0.19753588511588083\n        unknown: 0.0\n        wind: 0.0930411470307268\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0011171154141315137\n        biomass: 0.0024319843353879933\n        coal: 0.6319625584256338\n        gas: 0.02185619090272558\n        geothermal: 0.0\n        hydro: 0.03807791418408115\n        hydro discharge: 1.890552061356097e-05\n        nuclear: 0.0\n        oil: 0.00017241557613462545\n        solar: 0.2085011484047794\n        unknown: 0.0\n        wind: 0.09586177067488971\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.4608\n    - datetime: '2022-01-01'\n      value: 0.2954\n    - datetime: '2023-01-01'\n      value: 0.3927\n    - datetime: '2024-01-01'\n      value: 0.3744\n    - datetime: '2025-01-01'\n      value: 0.3986\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1798\n    - datetime: '2021-01-01'\n      value: 0.2609\n    - datetime: '2022-01-01'\n      value: 0.39\n    - datetime: '2023-01-01'\n      value: 0.497\n    - datetime: '2024-01-01'\n      value: 0.4859\n    - datetime: '2025-01-01'\n      value: 0.5418\nisRenewable:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.4608\n    - datetime: '2022-01-01'\n      value: 0.2954\n    - datetime: '2023-01-01'\n      value: 0.3927\n    - datetime: '2024-01-01'\n      value: 0.3744\n    - datetime: '2025-01-01'\n      value: 0.3986\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1798\n    - datetime: '2021-01-01'\n      value: 0.2609\n    - datetime: '2022-01-01'\n      value: 0.39\n    - datetime: '2023-01-01'\n      value: 0.497\n    - datetime: '2024-01-01'\n      value: 0.4859\n    - datetime: '2025-01-01'\n      value: 0.5418\nparsers:\n  consumptionForecast: AEMO.fetch_consumption_forecast\n  price: OPENNEM.fetch_price\n  production: OPENNEM.fetch_production\n  productionCapacity: OPENELECTRICITY.fetch_production_capacity\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Australia/Sydney\nzone_name: New South Wales\n"
  },
  {
    "path": "config/zones/AU-NT.yaml",
    "content": "bounding_box:\n  - - 129.00189001890018\n    - -25.99972409710461\n  - - 138.0019800198002\n    - -10.981940848039898\ncenter_point:\n  - 133.50005390545402\n  - -18.846486859209598\ncentroid:\n  - 133.39210622875467\n  - -12.992381053427186\ncapacity:\n  biomass: 1.1\n  gas: 471.4\n  solar: 158\ncontributors:\n  - unitrium\n  - amv213\n  - alejandranavcas\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\ndisclaimer: The Northern Territory power grid is not connected to the (Australian) National Electricity Market or Western Australia's grid.\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004049743326004118\n        coal: 0.0\n        gas: 0.9959422736692883\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004788824752322285\n        coal: 0.0\n        gas: 0.9952019194657983\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00430745683466228\n        coal: 0.0\n        gas: 0.9956835177498281\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005315187638489253\n        coal: 0.0\n        gas: 0.9946750893723232\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005625550562775195\n        coal: 0.0\n        gas: 0.9943652042902233\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005647638619022797\n        coal: 0.0\n        gas: 0.9943416591759038\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004599004567105944\n        coal: 0.0\n        gas: 0.9940717329269835\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0013217675287944528\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00448960362442088\n        coal: 0.0\n        gas: 0.993923909474167\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.001580552544332671\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006025746608255038\n        coal: 0.0\n        gas: 0.985530676989566\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.008444016543152163\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0056937251530382975\n        coal: 0.0\n        gas: 0.965386606333278\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.028919092948344192\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: NTESMO.fetch_consumption\n  consumptionForecast: NTESMO.fetch_consumption_forecast\n  price: NTESMO.fetch_price\n  production: NTESMO.fetch_production\nregion: Oceania\ntimezone: Australia/Darwin\nzone_name: Northern Territory\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/AU-QLD.yaml",
    "content": "bounding_box:\n  - - 137.99837998379982\n    - -29.165279323608438\n  - - 153.50733507335073\n    - -10.714328358276688\ncenter_point:\n  - 145.71528376012895\n  - -20.077823352905725\ncentroid:\n  - 146.9203489991776\n  - -20.06567744566823\ncapacity:\n  battery storage:\n    - datetime: '2024-01-01'\n      source: opennem.org.au\n      value: 336.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 1250.68\n  biomass:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 276.5\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 313.28\n  coal:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 8119.0\n  gas:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2692.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 3201.98\n  hydro:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 726.0\n  hydro storage:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 480.0\n  oil:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 449.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 453.0\n  solar:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 7691.36\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 7706.36\n    - datetime: '2022-01-01'\n      source: opennem.org.au\n      value: 8077.86\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 8416.86\n  wind:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 644.0\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 687.2\n    - datetime: '2022-01-01'\n      source: opennem.org.au\n      value: 843.2\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 1023.2\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2648.2\ncontributors:\n  - brandongalbraith\n  - jarek\n  - corradio\n  - alejandranavcas\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 509.87\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 559.06\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 486.99\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 493.14\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 484.79\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 589.24\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 532.82\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 507.06\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 382.64\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 369.82\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 392.55\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 542.87\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 592.06\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 519.99\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 526.14\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 517.79\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 613.24\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 556.82\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 531.06\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 406.64\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 393.82\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 416.55\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0001407899937208922\n        biomass: 0.0033022485263247492\n        coal: 0.7970151235577803\n        gas: 0.08839646526435874\n        geothermal: 0.0\n        hydro: 0.015462976605553626\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0005963588290596266\n        solar: 0.07398676176629146\n        unknown: 0.0\n        wind: 0.021098970320383204\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0001407897133933989\n        biomass: 0.0033022419512051177\n        coal: 0.7970152561085166\n        gas: 0.08839630659887744\n        geothermal: 0.0\n        hydro: 0.015462961824292172\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0005963576416472883\n        solar: 0.07398684321177139\n        unknown: 0.0\n        wind: 0.021098937981117463\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0004956430785209944\n        biomass: 0.0031441470345040363\n        coal: 0.7521584898023269\n        gas: 0.08122146471119707\n        geothermal: 0.0\n        hydro: 0.017075507041689197\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0006834644619258426\n        solar: 0.11702220477278823\n        unknown: 0.0\n        wind: 0.028198958385223162\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 1.2137938923767444e-06\n        biomass: 0.0037200698059053354\n        coal: 0.8388815066333775\n        gas: 0.08373939224701188\n        geothermal: 0.0\n        hydro: 0.012371471246664437\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00012563124579399168\n        solar: 0.059324328035253275\n        unknown: 0.0\n        wind: 0.0018366178880440463\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0039859192511191984\n        coal: 0.8315711434143314\n        gas: 0.08632629470646386\n        geothermal: 0.0\n        hydro: 0.016765911674002078\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.000233427461428612\n        solar: 0.05120598328054322\n        unknown: 0.0\n        wind: 0.009911272142822752\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0031473024584660137\n        coal: 0.7961773470684859\n        gas: 0.10321882408908845\n        geothermal: 0.0\n        hydro: 0.010510741630976674\n        hydro discharge: 1.23848242665786e-08\n        nuclear: 0.0\n        oil: 9.584819086057506e-05\n        solar: 0.06414609741455592\n        unknown: 0.0\n        wind: 0.022703791474475734\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 7.5222214723806224e-06\n        biomass: 0.003184687495080278\n        coal: 0.7758246326332131\n        gas: 0.08324767627772774\n        geothermal: 0.0\n        hydro: 0.017528971184076154\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0014372896159665736\n        solar: 0.08893732098786022\n        unknown: 0.0\n        wind: 0.029831891865458295\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0005044951343902474\n        biomass: 0.0026384509314843086\n        coal: 0.7314091273891948\n        gas: 0.08297625403920804\n        geothermal: 0.0\n        hydro: 0.02049548845865359\n        hydro discharge: 3.929452692762624e-05\n        nuclear: 0.0\n        oil: 0.000684705493816346\n        solar: 0.12909094196860016\n        unknown: 0.0\n        wind: 0.0321612246550634\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0008043227377559048\n        biomass: 0.002469854667521181\n        coal: 0.6684791715775124\n        gas: 0.06698748687436727\n        geothermal: 0.0\n        hydro: 0.021058644552665987\n        hydro discharge: 1.2128259571743819e-08\n        nuclear: 0.0\n        oil: 0.00032680627957081313\n        solar: 0.19891128117908102\n        unknown: 0.0\n        wind: 0.0409624037776214\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0009668088063281468\n        biomass: 0.0028533580749225814\n        coal: 0.6544404045485197\n        gas: 0.06612174536470214\n        geothermal: 0.0\n        hydro: 0.022379681653401824\n        hydro discharge: 1.845046706334242e-05\n        nuclear: 0.0\n        oil: 0.0008016694261631118\n        solar: 0.20730753084217618\n        unknown: 0.0\n        wind: 0.04511033753549817\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.2964\n    - datetime: '2022-01-01'\n      value: 0.2272\n    - datetime: '2023-01-01'\n      value: 0.3377\n    - datetime: '2024-01-01'\n      value: 0.3306\n    - datetime: '2025-01-01'\n      value: 0.3453\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1962\n    - datetime: '2021-01-01'\n      value: 0.2773\n    - datetime: '2022-01-01'\n      value: 0.3084\n    - datetime: '2023-01-01'\n      value: 0.484\n    - datetime: '2024-01-01'\n      value: 0.501\n    - datetime: '2025-01-01'\n      value: 0.4713\nisRenewable:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.2964\n    - datetime: '2022-01-01'\n      value: 0.2272\n    - datetime: '2023-01-01'\n      value: 0.3377\n    - datetime: '2024-01-01'\n      value: 0.3306\n    - datetime: '2025-01-01'\n      value: 0.3453\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1962\n    - datetime: '2021-01-01'\n      value: 0.2773\n    - datetime: '2022-01-01'\n      value: 0.3084\n    - datetime: '2023-01-01'\n      value: 0.484\n    - datetime: '2024-01-01'\n      value: 0.501\n    - datetime: '2025-01-01'\n      value: 0.4713\nparsers:\n  consumptionForecast: AEMO.fetch_consumption_forecast\n  price: OPENNEM.fetch_price\n  production: OPENNEM.fetch_production\n  productionCapacity: OPENELECTRICITY.fetch_production_capacity\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Australia/Brisbane\nzone_name: Queensland\n"
  },
  {
    "path": "config/zones/AU-SA.yaml",
    "content": "bounding_box:\n  - - 129.00189001890018\n    - -38.07090779310813\n  - - 141.00081000810005\n    - -25.99972409710461\ncenter_point:\n  - 135.00166388214717\n  - -31.868789451997117\ncentroid:\n  - 136.81441193916982\n  - -34.164091273479706\ncapacity:\n  battery storage:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 410.0\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 416.27\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 716.27\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 1074.22\n  biomass:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 10.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 18.14\n  gas:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2946.0\n    - datetime: '2022-01-01'\n      source: opennem.org.au\n      value: 3100.0\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 3228.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2748.0\n  hydro:\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2.0\n  oil:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 456.6\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 285.6\n  solar:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2686.05\n    - datetime: '2022-01-01'\n      source: opennem.org.au\n      value: 2785.05\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 2900.52\n  wind:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2140.9\n    - datetime: '2022-01-01'\n      source: opennem.org.au\n      value: 2350.9\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 2763.4\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2763.2\ncontributors:\n  - brandongalbraith\n  - jarek\n  - corradio\n  - alejandranavcas\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 161.54\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 125.83\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 96.16\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 105.59\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 114.28\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 92.12\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 194.54\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 158.83\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 129.16\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 138.59\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 147.28\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 125.12\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0012441841875993629\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.44392266438796935\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.001647547198720754\n        solar: 0.0921279565822379\n        unknown: 0.0\n        wind: 0.46105750198504725\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.001244153785664184\n        biomass: 0.0\n        coal: 2.269165430313992e-05\n        gas: 0.44391182571640486\n        geothermal: 0.0\n        hydro: 1.2631034958608364e-07\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0016475069405149038\n        solar: 0.09212688257652056\n        unknown: 0.0\n        wind: 0.46104666775934067\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0020239853878309387\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.37862769821908904\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0013157883224994209\n        solar: 0.154998817606896\n        unknown: 0.0\n        wind: 0.46303314526251516\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0022371866977428955\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.47308523386620427\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0010414766509621277\n        solar: 0.09947681417648245\n        unknown: 0.0\n        wind: 0.4241594895967854\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0030727559146749876\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.5313695468883676\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0006985699892859676\n        solar: 0.04662866046543386\n        unknown: 0.0\n        wind: 0.41823080049343486\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.004393504897215077\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.4617797670617228\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0005690649271097908\n        solar: 0.06428898198017026\n        unknown: 0.0\n        wind: 0.4689687692415629\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0071610083528132985\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.3857915493889897\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.001319332702641473\n        solar: 0.10396008088043397\n        unknown: 0.0\n        wind: 0.5017679182547047\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.004961337333845281\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.30836762614484114\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.004476128276825672\n        solar: 0.17414425567189298\n        unknown: 0.0\n        wind: 0.5080506175945515\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.005477724338481898\n        biomass: 1.1615524230752876e-06\n        coal: 0.06989599604977755\n        gas: 0.2223849910926273\n        geothermal: 0.0\n        hydro: 0.01025400271360812\n        hydro discharge: 1.4393462491639252e-09\n        nuclear: 0.0\n        oil: 0.0009492042315898845\n        solar: 0.24727176200526071\n        unknown: 0.0\n        wind: 0.443765063019379\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.006267044655573515\n        biomass: 4.324474668766488e-06\n        coal: 0.06451430923833469\n        gas: 0.2298901379941587\n        geothermal: 0.0\n        hydro: 0.007222349600236829\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0006732465209541075\n        solar: 0.2668651967564851\n        unknown: 0.0\n        wind: 0.42456316091004337\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.5635\n    - datetime: '2021-01-01'\n      value: 0.66\n    - datetime: '2022-01-01'\n      value: 0.7404\n    - datetime: '2023-01-01'\n      value: 0.7749\n    - datetime: '2024-01-01'\n      value: 0.7532\n    - datetime: '2025-01-01'\n      value: 0.7911\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.5635\n    - datetime: '2021-01-01'\n      value: 0.66\n    - datetime: '2022-01-01'\n      value: 0.7404\n    - datetime: '2023-01-01'\n      value: 0.7749\n    - datetime: '2024-01-01'\n      value: 0.7532\n    - datetime: '2025-01-01'\n      value: 0.7911\nparsers:\n  consumptionForecast: AEMO.fetch_consumption_forecast\n  price: OPENNEM.fetch_price\n  production: OPENNEM.fetch_production\n  productionCapacity: OPENELECTRICITY.fetch_production_capacity\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Australia/Adelaide\nzone_name: South Australia\n"
  },
  {
    "path": "config/zones/AU-TAS-CBI.yaml",
    "content": "bounding_box:\n  - - 148.00288002880026\n    - -40.50374860913729\n  - - 148.39888398883986\n    - -40.309121343854954\ncenter_point:\n  - 148.20088200882006\n  - -40.40643497649612\ncentroid:\n  - 148.27198271982715\n  - -40.40035287445605\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Oceania\ntimezone: Australia/Lord_Howe\nzone_name: Cape Barren Island\n"
  },
  {
    "path": "config/zones/AU-TAS-FI.yaml",
    "content": "_comment: 'Capacity data fetched from the test payload (capacity is sent in all payloads).\n  Parsing for production is done on instantaneous measurements : this is not reliable\n  at all. Battery storage is composed of 0.5 battery+0.2 of flywheel'\nbounding_box:\n  - - 147.7580775807758\n    - -40.27048210736508\n  - - 148.30888308883087\n    - -39.71235980251133\ncenter_point:\n  - 148.03348033480333\n  - -39.99142095493821\ncentroid:\n  - 148.10188101881016\n  - -39.999530424324966\ncapacity:\n  battery storage: 0.7\n  biomass: 0\n  coal: 0\n  gas: 0\n  geothermal: 0\n  hydro: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 2.1\n  solar: 4.1\n  wind: 1.5\ncontributors:\n  - chuqtas\n  - ajoga\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 150.24\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 143.31\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 173.89\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 166.43\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 159.41\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 188.56\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 183.24\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 176.31\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 206.89\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 199.43\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 192.41\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 221.56\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.008958418242889184\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.3128961469967616\n        solar: 0.022092880848218862\n        unknown: 0.0\n        wind: 0.6556168800531644\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.009709832658485218\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.409093274765538\n        solar: 0.020271465895015144\n        unknown: 0.0\n        wind: 0.5604813106972967\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.011135109728392852\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.3832921129103856\n        solar: 0.017372263318300003\n        unknown: 0.0\n        wind: 0.5876689384528726\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.003533188048876999\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.3900149418566881\n        solar: 0.01938750199323187\n        unknown: 0.0\n        wind: 0.5865180749218949\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.6299\n    - datetime: '2021-01-01'\n      value: 0.647\n    - datetime: '2022-01-01'\n      value: 0.5717\n    - datetime: '2023-01-01'\n      value: 0.5901\n    - datetime: '2024-01-01'\n      value: 0.6074\n    - datetime: '2025-01-01'\n      value: 0.5356\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.6299\n    - datetime: '2021-01-01'\n      value: 0.647\n    - datetime: '2022-01-01'\n      value: 0.5717\n    - datetime: '2023-01-01'\n      value: 0.5901\n    - datetime: '2024-01-01'\n      value: 0.6074\n    - datetime: '2025-01-01'\n      value: 0.5356\nparsers:\n  production: ajenti.fetch_production\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Australia/Hobart\nzone_name: Flinders Island\n"
  },
  {
    "path": "config/zones/AU-TAS-KI.yaml",
    "content": "_comment:\n  'Capacity data fetched from https://www.hydro.com.au/docs/default-source/clean-energy/hybrid-energy-solutions/king_island.pdf\n  . Oil capacity is said to run with blended biodiesel : hense the diesel capacity\n  is equal to the biomass capacity. Parsing for production is done on instantaneous\n  measurements : this is not reliable at all'\nbounding_box:\n  - - 143.83763837638375\n    - -40.127373824069245\n  - - 144.13644136441363\n    - -39.62649483253383\ncenter_point:\n  - 143.9870398703987\n  - -39.87693432830154\ncentroid:\n  - 143.98583985839858\n  - -39.905317471155215\ncapacity:\n  battery storage: 1.5\n  biomass: 6\n  coal: 0\n  gas: 0\n  geothermal: 0\n  hydro: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 6\n  solar: 0.47\n  wind: 5.65\ncontributors:\n  - ajoga\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 137.7\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 173.94\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 222.92\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 305.96\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 280.75\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 291.34\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 170.7\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 206.94\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 255.92\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 338.96\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 313.75\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 324.34\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.3650717343949522\n        solar: 0.011081899897343447\n        unknown: 0.0\n        wind: 0.6237562282480782\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.013174835519778237\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4390433792282261\n        solar: 0.006935215444463839\n        unknown: 0.0\n        wind: 0.5407325094488638\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.004530065328310524\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5615267644736911\n        solar: 0.010524233641872285\n        unknown: 0.0\n        wind: 0.4234136382341045\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0021662109674944877\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7465224481039286\n        solar: 0.010407381940730554\n        unknown: 0.0\n        wind: 0.24087231857114963\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0045280562830267625\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.6700376563202181\n        solar: 0.1199307309665122\n        unknown: 0.0\n        wind: 0.2054531930390045\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.6608\n    - datetime: '2021-01-01'\n      value: 0.5716\n    - datetime: '2022-01-01'\n      value: 0.4509\n    - datetime: '2023-01-01'\n      value: 0.2464\n    - datetime: '2024-01-01'\n      value: 0.3085\n    - datetime: '2025-01-01'\n      value: 0.2824\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.6608\n    - datetime: '2021-01-01'\n      value: 0.5716\n    - datetime: '2022-01-01'\n      value: 0.4509\n    - datetime: '2023-01-01'\n      value: 0.2464\n    - datetime: '2024-01-01'\n      value: 0.3085\n    - datetime: '2025-01-01'\n      value: 0.2824\nparsers:\n  production: ajenti.fetch_production\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Australia/Hobart\nzone_name: King Island\n"
  },
  {
    "path": "config/zones/AU-TAS.yaml",
    "content": "bounding_box:\n  - - 144.60444604446045\n    - -43.63925109614899\n  - - 148.33408334083336\n    - -40.72699753107879\ncenter_point:\n  - 146.52655501092056\n  - -42.17462783409918\ncentroid:\n  - 146.9092772560378\n  - -42.31763149702592\ncapacity:\n  biomass:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2.0\n  gas:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 371.6\n  hydro:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2361.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2330.6\n  oil:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 48.0\n  solar:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 303.37\n  wind:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 567.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 566.0\ncontributors:\n  - brandongalbraith\n  - jarek\n  - corradio\n  - alejandranavcas\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.38\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 33.38\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.006251202386553182\n        geothermal: 0.0\n        hydro: 0.8220362701091669\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.017750273698283935\n        unknown: 0.0\n        wind: 0.1539614486793389\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 4.209137046354714e-05\n        gas: 0.006250930266152664\n        geothermal: 0.0\n        hydro: 0.8220004964594964\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.017750193803841564\n        unknown: 0.0\n        wind: 0.15395548250199584\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.01592801320470529\n        geothermal: 0.0\n        hydro: 0.7899400705600474\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.025771849008650417\n        unknown: 0.0\n        wind: 0.16835933122123856\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.01592801320470529\n        geothermal: 0.0\n        hydro: 0.7899400705600474\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.025771849008650417\n        unknown: 0.0\n        wind: 0.16835933122123856\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.01611800146877263\n        geothermal: 0.0\n        hydro: 0.7925365218214478\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.02451437395336265\n        unknown: 0.0\n        wind: 0.16683017970049008\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.007786424343999135\n        geothermal: 0.0\n        hydro: 0.8161199864432732\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.018409795044156987\n        unknown: 0.0\n        wind: 0.15768348916760863\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.001861257519089156\n        geothermal: 0.0\n        hydro: 0.8265758030327586\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.006728512818955391\n        unknown: 0.0\n        wind: 0.16483446246331912\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.009469119232417406\n        geothermal: 0.0\n        hydro: 0.8176540950283011\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.018980340345392605\n        unknown: 0.0\n        wind: 0.15389646800246576\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.00014180959875286699\n        biomass: 2.696780731554057e-06\n        coal: 0.07853740707564373\n        gas: 0.005549880746074511\n        geothermal: 0.0\n        hydro: 0.6648369293835107\n        hydro discharge: 2.4640636125874633e-08\n        nuclear: 0.0\n        oil: 1.0714113633991415e-06\n        solar: 0.05785325857245086\n        unknown: 0.0\n        wind: 0.19307691814037176\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0002826800672351426\n        biomass: 7.791211879581738e-06\n        coal: 0.1135471786180796\n        gas: 0.04067553049145434\n        geothermal: 0.0\n        hydro: 0.5700704004749868\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 4.4341689729416803e-07\n        solar: 0.07151092912874732\n        unknown: 0.0\n        wind: 0.2039048715577342\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.999\nisRenewable:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.999\nparsers:\n  consumptionForecast: AEMO.fetch_consumption_forecast\n  price: OPENNEM.fetch_price\n  production: OPENNEM.fetch_production\n  productionCapacity: OPENELECTRICITY.fetch_production_capacity\nregion: Oceania\nsources:\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Australia/Hobart\nzone_name: Tasmania\n"
  },
  {
    "path": "config/zones/AU-VIC.yaml",
    "content": "bounding_box:\n  - - 140.96421396698537\n    - -39.13706450366208\n  - - 149.9720997209972\n    - -33.98181386823853\ncenter_point:\n  - 145.10552901241175\n  - -36.45834748983445\ncentroid:\n  - 144.78153006632593\n  - -37.08382639593836\ncapacity:\n  battery storage:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 120.0\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 500.0\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 707.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 1231.0\n  biomass:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 50.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 51.23\n  coal:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 4850.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 4690.0\n  gas:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2427.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2471.46\n  hydro:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2040.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 2322.8\n  solar:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 5268.58\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 5485.58\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 5611.58\n  wind:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2564.17\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 2744.77\n    - datetime: '2022-01-01'\n      source: opennem.org.au\n      value: 2905.77\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 3014.77\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 5487.17\ncontributors:\n  - jarek\n  - corradio\n  - alejandranavcas\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 595.22\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 539.83\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 486.12\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 420.58\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 441.97\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 408.53\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 628.22\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 572.83\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 519.12\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 453.58\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 474.97\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 441.53\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0004724463729913436\n        biomass: 0.0\n        coal: 0.7307265725069795\n        gas: 0.045936945750439266\n        geothermal: 0.0\n        hydro: 0.05550121475963325\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.038024778133161456\n        unknown: 0.0\n        wind: 0.12933842720511196\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.00047244032591252594\n        biomass: 0.0\n        coal: 0.7307495949473276\n        gas: 0.04593334584778859\n        geothermal: 0.0\n        hydro: 0.055496737073899634\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.03801756749182541\n        unknown: 0.0\n        wind: 0.12933069884403184\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8060798210968169\n        gas: 0.06948731716732398\n        geothermal: 0.0\n        hydro: 0.0500899257965081\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.07434294330212768\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.000481211706289653\n        biomass: 0.0\n        coal: 0.7464094142244575\n        gas: 0.0692004093366192\n        geothermal: 0.0\n        hydro: 0.047861724783667015\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.021536392430559093\n        unknown: 0.0\n        wind: 0.11451084617258156\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.00048811515326637497\n        biomass: 0.0\n        coal: 0.748666246764716\n        gas: 0.03200095431149287\n        geothermal: 0.0\n        hydro: 0.05249841791765642\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.02605106693385571\n        unknown: 0.0\n        wind: 0.14029515325754852\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 2.8485422054477e-05\n        biomass: 0.0\n        coal: 0.788855403432854\n        gas: 0.04612258468690455\n        geothermal: 0.0\n        hydro: 0.06138854376456541\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.008535056694716738\n        unknown: 0.0\n        wind: 0.0950699038533949\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0006979441666508258\n        biomass: 0.0\n        coal: 0.6995092472170257\n        gas: 0.01860304852707215\n        geothermal: 0.0\n        hydro: 0.058871603640483695\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.048921538689881534\n        unknown: 0.0\n        wind: 0.17339660155223605\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0026780903442635826\n        biomass: 0.0\n        coal: 0.6190910425288089\n        gas: 0.037290658067637476\n        geothermal: 0.0\n        hydro: 0.06220010045054841\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.09042895274312412\n        unknown: 0.0\n        wind: 0.1883111640210727\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0025032427419419347\n        biomass: 1.2902042762008032e-05\n        coal: 0.5861443398518874\n        gas: 0.014219285457077265\n        geothermal: 0.0\n        hydro: 0.06274460341776156\n        hydro discharge: 8.453185765808675e-08\n        nuclear: 0.0\n        oil: 4.249513212468347e-06\n        solar: 0.1269718373717699\n        unknown: 0.0\n        wind: 0.20739944203447835\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0027778404488412816\n        biomass: 3.789937368769627e-05\n        coal: 0.5745729428668062\n        gas: 0.0284031362684534\n        geothermal: 0.0\n        hydro: 0.05743032415203594\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 4.662311159509748e-06\n        solar: 0.1470457660916572\n        unknown: 0.0\n        wind: 0.18972740562986398\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2055\n    - datetime: '2021-01-01'\n      value: 0.2842\n    - datetime: '2022-01-01'\n      value: 0.3439\n    - datetime: '2023-01-01'\n      value: 0.4435\n    - datetime: '2024-01-01'\n      value: 0.4085\n    - datetime: '2025-01-01'\n      value: 0.4544\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2055\n    - datetime: '2021-01-01'\n      value: 0.2842\n    - datetime: '2022-01-01'\n      value: 0.3439\n    - datetime: '2023-01-01'\n      value: 0.4435\n    - datetime: '2024-01-01'\n      value: 0.4085\n    - datetime: '2025-01-01'\n      value: 0.4544\nparsers:\n  consumptionForecast: AEMO.fetch_consumption_forecast\n  price: OPENNEM.fetch_price\n  production: OPENNEM.fetch_production\n  productionCapacity: OPENELECTRICITY.fetch_production_capacity\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Australia/Melbourne\nzone_name: Victoria\n"
  },
  {
    "path": "config/zones/AU-WA-RI.yaml",
    "content": "_comment: 'Capacity data fetched from the test payload (capacity is sent in all payloads).\n  Parsing for production is done on instantaneous measurements : this is not reliable\n  at all'\nbounding_box:\n  - - 115.44055440554402\n    - -32.02601390669214\n  - - 115.51615516155161\n    - -31.995961167200015\ncenter_point:\n  - 115.47835478354781\n  - -32.010987536946075\ncentroid:\n  - 115.48255482554823\n  - -32.014565244028475\ncapacity:\n  battery storage: 0\n  biomass: 0\n  coal: 0\n  gas: 0\n  geothermal: 0\n  hydro: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 2.1\n  solar: 0.6\n  wind: 0.6\ncontributors:\n  - ajoga\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 310.86\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 310.86\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 310.86\n      - _comment: used non-null storage values\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 304.5\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 321.42\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 305.26\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 343.86\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 343.86\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 343.86\n      - _comment: used non-null storage values\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 337.5\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 354.42\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 338.26\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7214348874672578\n        solar: 0.09655515040514011\n        unknown: 0.0\n        wind: 0.18206372128287882\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7519217191707342\n        solar: 0.07833126006705768\n        unknown: 0.0\n        wind: 0.16976688744150792\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7931552125610936\n        solar: 0.06026681890829423\n        unknown: 0.0\n        wind: 0.1463649654920588\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2343\n    - datetime: '2021-01-01'\n      value: 0.2343\n    - datetime: '2022-01-01'\n      value: 0.2343\n    - datetime: '2023-01-01'\n      value: 0.25\n    - datetime: '2024-01-01'\n      value: 0.2083\n    - datetime: '2025-01-01'\n      value: 0.2481\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2343\n    - datetime: '2021-01-01'\n      value: 0.2343\n    - datetime: '2022-01-01'\n      value: 0.2343\n    - datetime: '2023-01-01'\n      value: 0.25\n    - datetime: '2024-01-01'\n      value: 0.2083\n    - datetime: '2025-01-01'\n      value: 0.2481\nparsers:\n  production: ajenti.fetch_production\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Australia/Perth\nzone_name: Rottnest Island\n"
  },
  {
    "path": "config/zones/AU-WA.yaml",
    "content": "bounding_box:\n  - - 112.92052920529207\n    - -35.13718798554355\n  - - 129.00189001890018\n    - -13.723895555988058\ncenter_point:\n  - 121.21840125979017\n  - -24.502907008372944\ncentroid:\n  - 120.36907193716478\n  - -23.046206513286926\ncapacity:\n  battery storage:\n    - datetime: '2024-01-01'\n      source: opennem.org.au\n      value: 100.0\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 885.0\n  biomass:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 65.13\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 102.23\n  coal:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 1371.1\n  gas:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 3430.4\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 3462.6\n  hydro:\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 1.5\n  oil:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 104.1\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 104.5\n  solar:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 2665.64\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 2765.64\n  wind:\n    - datetime: '2020-01-01'\n      source: opennem.org.au\n      value: 611.57\n    - datetime: '2021-01-01'\n      source: opennem.org.au\n      value: 1014.82\n    - datetime: '2023-01-01'\n      source: opennem.org.au\n      value: 1090.42\n    - datetime: '2025-01-01'\n      source: https://openelectricity.org.au/\n      value: 1105.87\ncontributors:\n  - jarek\n  - corradio\n  - MariusKroon\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\ndisclaimer: Western Australia's power grid is not connected to the (Australian) National\n  Electricity Market or the Northern Territory grid.\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 288.89\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 301.2\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 303.91\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 281.91\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 321.89\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 334.2\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 336.91\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 314.91\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005634299803619725\n        coal: 0.39764870006223585\n        gas: 0.36077400997106357\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0004506698609571838\n        solar: 0.1127501970321291\n        unknown: 0.0\n        wind: 0.12274193796166366\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005634482057732223\n        coal: 0.3976455012717376\n        gas: 0.36076816011761564\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.000450627548897785\n        solar: 0.11275316626050917\n        unknown: 0.0\n        wind: 0.12274787793620329\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0068250356636745686\n        coal: 0.463278270695125\n        gas: 0.39353775964515786\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 4.6724502346849226e-05\n        solar: 0.05722098145869997\n        unknown: 0.0\n        wind: 0.07909137520871565\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007026273534479898\n        coal: 0.44007205128780524\n        gas: 0.39397919097545453\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0001150792015923038\n        solar: 0.07490606160028195\n        unknown: 0.0\n        wind: 0.08390153761489438\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0057177437596818035\n        coal: 0.40634707884304605\n        gas: 0.37130443472571645\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0001248244140375717\n        solar: 0.10739372161721791\n        unknown: 0.0\n        wind: 0.10911237913512295\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0051251962373632795\n        coal: 0.363276458675794\n        gas: 0.3703607904215379\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0003269623503324662\n        solar: 0.13273551033719244\n        unknown: 0.0\n        wind: 0.12817521410996222\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004641582266558719\n        coal: 0.3776045733107258\n        gas: 0.2955604059954736\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0002204270012878005\n        solar: 0.15431131557135006\n        unknown: 0.0\n        wind: 0.1676618423490851\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004359734080492649\n        coal: 0.3063224741549013\n        gas: 0.3447572427712224\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00013920974771888702\n        solar: 0.17370337704109487\n        unknown: 0.0\n        wind: 0.17071803351215314\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0006475946940200009\n        biomass: 0.004235763380929242\n        coal: 0.2992403986590204\n        gas: 0.3488167824513507\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00028682589505083547\n        solar: 0.19255200040168485\n        unknown: 0.0\n        wind: 0.15422067611662243\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0034738676206961397\n        biomass: 0.003274161716959677\n        coal: 0.2787645649166744\n        gas: 0.3091358966303054\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0006804763292333772\n        solar: 0.23467167868922628\n        unknown: 0.0\n        wind: 0.1699992813333499\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.4461\n    - datetime: '2023-01-01'\n      value: 0.4809\n    - datetime: '2024-01-01'\n      value: 0.4567\n    - datetime: '2025-01-01'\n      value: 0.5084\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.4461\n    - datetime: '2023-01-01'\n      value: 0.4809\n    - datetime: '2024-01-01'\n      value: 0.4567\n    - datetime: '2025-01-01'\n      value: 0.5084\nparsers:\n  price: OPENNEM.fetch_price\n  production: OPENNEM.fetch_production\n  productionCapacity: OPENELECTRICITY.fetch_production_capacity\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Australia/Perth\nzone_name: Western Australia\n"
  },
  {
    "path": "config/zones/AU.yaml",
    "content": "bounding_box:\n  - - 112.92052920529207\n    - -43.63925109614899\n  - - 159.10462909730177\n    - -10.714328358276688\ncenter_point:\n  - 133.50111357697187\n  - -27.321631528353937\ncentroid:\n  - 136.08029929292996\n  - -25.012631598216576\nbypassedSubZones:\n  - AU-LH\n  - AU-TAS-CBI\n  - AU-WA-RI\n  - AU-TAS-KI\n  - AU-TAS-FI\ncapacity:\n  battery storage: 157.2\n  biomass: 384.1\n  coal: 18359\n  gas: 8488.4\n  geothermal: 0\n  hydro: 5745\n  hydro storage: 1320\n  nuclear: 0\n  oil: 1389.2\n  solar: 19988.2\n  unknown: null\n  wind: 7173.8\ncontributors:\n  - corradio\n  - unitrium\n  - MariusKroon\n  - chuqtas\n  - jarek\n  - ajoga\n  - brandongalbraith\ncountry: AU\ncountry_name: Australia\ncurrency: AUD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 545.09\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 504.14\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 459.41\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 397.33\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 408.12\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 373.33\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 527.08\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 475.05\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 425.59\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 357.1\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 363.62\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 337.53\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 578.09\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 537.14\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 492.41\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 430.33\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 441.12\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 406.33\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 551.08\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 499.05\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 449.59\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 381.1\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 387.62\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 361.53\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0002594637960231023\n        biomass: 0.00151275295955091\n        coal: 0.6914956988922271\n        gas: 0.11681363420930246\n        geothermal: 0.0\n        hydro: 0.0631406835842441\n        hydro discharge: 3.2172771468498537e-09\n        nuclear: 0.0\n        oil: 0.00030387214824768334\n        solar: 0.051029606352062266\n        unknown: 0.0\n        wind: 0.07544429210291935\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.00014355047407564232\n        biomass: 0.0017182578610384616\n        coal: 0.7052591978816757\n        gas: 0.11082227025245124\n        geothermal: 0.0\n        hydro: 0.0677326820948128\n        hydro discharge: 2.9264138109894026e-09\n        nuclear: 0.0\n        oil: 0.00011996165830000424\n        solar: 0.03848013198918248\n        unknown: 0.0\n        wind: 0.07572395574465145\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.00029185250871076844\n        biomass: 0.0016634601475480479\n        coal: 0.6816084207350457\n        gas: 0.1220140808662046\n        geothermal: 0.0\n        hydro: 0.06212212260692593\n        hydro discharge: 4.482338641572983e-09\n        nuclear: 0.0\n        oil: 0.00013818671112620425\n        solar: 0.04171746422300171\n        unknown: 0.0\n        wind: 0.09044440563966305\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.00036328248298918736\n        biomass: 0.0013885734133745164\n        coal: 0.6625402064520522\n        gas: 0.1093876766508366\n        geothermal: 0.0\n        hydro: 0.06736590809838815\n        hydro discharge: 5.081412167571266e-09\n        nuclear: 0.0\n        oil: 9.669710924369871e-05\n        solar: 0.05348370178209043\n        unknown: 0.0\n        wind: 0.1053739376846361\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0005413583827554923\n        biomass: 0.001343472936234691\n        coal: 0.6350135820869403\n        gas: 0.0874605755930383\n        geothermal: 0.0\n        hydro: 0.07422520610770694\n        hydro discharge: 4.690571207638475e-09\n        nuclear: 0.0\n        oil: 0.0004903357094244511\n        solar: 0.07756097378839584\n        unknown: 9.361066770508258e-06\n        wind: 0.12335513512613058\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0011225225963338878\n        biomass: 0.0011400051786446344\n        coal: 0.569870158176169\n        gas: 0.09819974215487416\n        geothermal: 0.0\n        hydro: 0.07468464520282539\n        hydro discharge: 1.0457616908716836e-05\n        nuclear: 0.0\n        oil: 0.00045533264848279646\n        solar: 0.12358603158197574\n        unknown: 1.0689068970155307e-05\n        wind: 0.13092041864999635\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.001354435203081272\n        biomass: 0.001458227431313655\n        coal: 0.5399693682544393\n        gas: 0.07862482421941185\n        geothermal: 0.0\n        hydro: 0.06667854838383991\n        hydro discharge: 1.5141667178907328e-06\n        nuclear: 0.0\n        oil: 0.00018759295327671713\n        solar: 0.1778970210150275\n        unknown: 5.457981705763607e-05\n        wind: 0.13377389560743355\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.00188694682777796\n        biomass: 0.0018671287738742375\n        coal: 0.5332681648583506\n        gas: 0.07860819484672399\n        geothermal: 0.0\n        hydro: 0.05795957772034905\n        hydro discharge: 1.1114753293322062e-05\n        nuclear: 0.0\n        oil: 0.00037077718062013645\n        solar: 0.19323819121037497\n        unknown: 0.00019039581980082146\n        wind: 0.13259950282926702\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2325\n    - datetime: '2021-01-01'\n      value: 0.2993\n    - datetime: '2022-01-01'\n      value: 0.3489\n    - datetime: '2023-01-01'\n      value: 0.4472\n    - datetime: '2024-01-01'\n      value: 0.432\n    - datetime: '2025-01-01'\n      value: 0.4809\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2626\n    - datetime: '2021-01-01'\n      value: 0.3429\n    - datetime: '2022-01-01'\n      value: 0.4032\n    - datetime: '2023-01-01'\n      value: 0.5038\n    - datetime: '2024-01-01'\n      value: 0.4949\n    - datetime: '2025-01-01'\n      value: 0.5307\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2325\n    - datetime: '2021-01-01'\n      value: 0.2993\n    - datetime: '2022-01-01'\n      value: 0.3489\n    - datetime: '2023-01-01'\n      value: 0.4472\n    - datetime: '2024-01-01'\n      value: 0.432\n    - datetime: '2025-01-01'\n      value: 0.4809\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2626\n    - datetime: '2021-01-01'\n      value: 0.3429\n    - datetime: '2022-01-01'\n      value: 0.4032\n    - datetime: '2023-01-01'\n      value: 0.5038\n    - datetime: '2024-01-01'\n      value: 0.4949\n    - datetime: '2025-01-01'\n      value: 0.5307\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nsubZoneNames:\n  - AU-LH\n  - AU-NSW\n  - AU-NT\n  - AU-QLD\n  - AU-SA\n  - AU-TAS\n  - AU-TAS-CBI\n  - AU-TAS-FI\n  - AU-TAS-KI\n  - AU-VIC\n  - AU-WA\n  - AU-WA-RI\ntimezone: Australia/Sydney\nzone_name: Australia\n"
  },
  {
    "path": "config/zones/AW.yaml",
    "content": "bounding_box:\n  - - -70.0585005850058\n    - 12.417694553661747\n  - - -69.8784987849878\n    - 12.6323569786055\ncenter_point:\n  - -69.9684996849968\n  - 12.525025766133624\ncentroid:\n  - -69.96789967899674\n  - 12.525025766133625\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\ncontributors:\n  - pascalheraud\ncountry: AW\ncountry_name: Aruba\ncurrency: AWG\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.830847454974291\n        solar: 0.010173009687123279\n        unknown: 0.0\n        wind: 0.15897836645149213\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.803703036421306\n        solar: 0.0158128937582308\n        unknown: 0.0\n        wind: 0.18048327996405208\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8454059505301171\n        solar: 0.016015302784506125\n        unknown: 0.0\n        wind: 0.13857838842381132\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8298272126210017\n        solar: 0.012127157143873933\n        unknown: 0.0007192733326606231\n        wind: 0.1573257926991776\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7939078589008981\n        solar: 0.014544986130697591\n        unknown: 0.001272621935162575\n        wind: 0.19027148505956717\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8609520728550746\n        solar: 0.008366461052547531\n        unknown: 0.0018877833779848713\n        wind: 0.12879356403066494\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8836829657096846\n        solar: 0.006176899034154593\n        unknown: 0.0015510181027602445\n        wind: 0.10858758715681341\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: AW.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Aruba\nzone_name: Aruba\n"
  },
  {
    "path": "config/zones/AX.yaml",
    "content": "bounding_box:\n  - - 19.647196471964747\n    - 60.0741839740071\n  - - 20.20880208802089\n    - 60.35467620926693\ncenter_point:\n  - 19.927999279992818\n  - 60.21443009163701\ncentroid:\n  - 19.951039510395123\n  - 60.201264129573794\ncan_have_zero_production: true\ncapacity:\n  coal: 0\n  gas: 0\n  nuclear: 0\n  oil: 35\n  solar: 3.67\n  wind: 63.8\ncontributors:\n  - tmslaine\n  - systemcatch\n  - VIKTORVAV99\ncountry: AX\ncountry_name: \"\\xC5land Islands\"\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 895.6862569\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 295.9885661\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 990.5340999\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1170.347843\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 415.9885661\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    wind:\n      datetime: '2020-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.37280983592511663\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0008139485070470803\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.6263976352653899\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04903220325141623\n        coal: 0.011946480867268934\n        gas: 0.005910600519210002\n        geothermal: 0.0\n        hydro: 0.24234659629609698\n        hydro discharge: 1.6296265372047404e-05\n        nuclear: 0.3335352239198415\n        oil: 0.0009228446907316732\n        solar: 0.005307162629770458\n        unknown: 0.040642263283928184\n        wind: 0.31030484270075637\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004752726038445803\n        coal: 0.007219707395243909\n        gas: 0.004508645586533524\n        geothermal: 0.0\n        hydro: 0.25928490172937557\n        hydro discharge: 1.178119081565477e-05\n        nuclear: 0.3499256719829855\n        oil: 0.0002841365006855039\n        solar: 0.005848344507066584\n        unknown: 0.041663939240299756\n        wind: 0.32648232879476674\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004029656098059488\n        coal: 0.004397968678684677\n        gas: 0.003444867293172876\n        geothermal: 3.3666597863362836e-08\n        hydro: 0.3071721199092443\n        hydro discharge: 0.001040802872945862\n        nuclear: 0.3076831115316144\n        oil: 0.00023155886010420957\n        solar: 0.005534923355128303\n        unknown: 0.03656710993568299\n        wind: 0.3298774795070577\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004354683191403903\n        coal: 0.006476893704552956\n        gas: 0.003974022013865712\n        geothermal: 0.0\n        hydro: 0.2638443423392076\n        hydro discharge: 0.001133640525110726\n        nuclear: 0.3279428744191258\n        oil: 0.0018848779260615782\n        solar: 0.0003588410040665896\n        unknown: 0.06409718741936811\n        wind: 0.3258759172303977\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0030128262353941544\n        coal: 0.005038570957416851\n        gas: 0.0015483546259291111\n        geothermal: 0.0\n        hydro: 0.23803134794685274\n        hydro discharge: 0.0002288540237688854\n        nuclear: 0.24145897000827352\n        oil: 0.00010550649157810835\n        solar: 0.002544975907733234\n        unknown: 0.036457011677915055\n        wind: 0.4715311719967027\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0034980613795349545\n        coal: 0.0035417570728201995\n        gas: 0.0016154315498119406\n        geothermal: 0.0\n        hydro: 0.20602805971131477\n        hydro discharge: 0.00028255368953519994\n        nuclear: 0.20342729912320257\n        oil: 8.51623754960213e-05\n        solar: 0.003840444556799183\n        unknown: 0.024592502278986923\n        wind: 0.5530483937763888\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0026050231118377957\n        coal: 0.001963778734693452\n        gas: 0.0010712799384635994\n        geothermal: 0.0\n        hydro: 0.17834283675778717\n        hydro discharge: 0.00022737118012299595\n        nuclear: 0.18256570910434558\n        oil: 0.0002823438077349849\n        solar: 0.0046097053247544\n        unknown: 0.01829593364522464\n        wind: 0.6099261074548099\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: AX.fetch_consumption\n  price: ENTSOE.fetch_price\n  production: AX.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Mariehamn\nzone_name: \"\\xC5land Islands\"\n"
  },
  {
    "path": "config/zones/AZ.yaml",
    "content": "bounding_box:\n  - - 44.77544775447757\n    - 38.39614122035431\n  - - 50.35910359103593\n    - 41.89084549843855\ncenter_point:\n  - 47.577673902934436\n  - 40.387467828663446\ncentroid:\n  - 47.1202900595501\n  - 40.10779693959522\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5080.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 5480.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 5860.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1130.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1140.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1150.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1160.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1300.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1410.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 290.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\ncountry: AZ\ncountry_name: Azerbaijan\ncurrency: AZN\nfallbackZoneMixes:\n  _source: https://ourworldindata.org/grapher/electricity-prod-source-stacked?time=earliest..latest&country=~AZE\n  powerOriginRatios:\n    value:\n      gas: 0.46\n      hydro: 0.07\n      oil: 0.46\n      unknown: 0.01\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Baku\nzone_name: Azerbaijan\n"
  },
  {
    "path": "config/zones/BA.yaml",
    "content": "bounding_box:\n  - - 15.737557375573772\n    - 42.5591611814301\n  - - 19.618396183961863\n    - 45.28394289538275\ncenter_point:\n  - 17.644617906102937\n  - 44.035924649703595\ncentroid:\n  - 17.840161933615803\n  - 44.16014569310636\ncapacity:\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1875.5\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1875.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1888.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1883.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2169.8\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1790.4\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1746.7\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1708.0\n  hydro storage:\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 440.0\n  solar:\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 29.9\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 50.6\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 86.6\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 145.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 134.6\ncontributors:\n  - corradio\n  - nessie2013\ncountry: BA\ncountry_name: Bosnia and Herzegovina\ncurrency: BAM\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 556.44\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 596.88\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 453.28\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 422.64\n  lifecycle:\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 567.14\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 607.58\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 463.98\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 433.34\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 28.8\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0012129075909763614\n        coal: 0.8410145765044548\n        gas: 0.006327362692174731\n        geothermal: 7.032789776781282e-05\n        hydro: 0.1284185938022832\n        hydro discharge: 0.005708916330735468\n        nuclear: 0.007288951290057417\n        oil: 0.0001153791345675018\n        solar: 0.001628217464085534\n        unknown: 0.0012445248316330778\n        wind: 0.006969759922401658\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0008549710201764943\n        coal: 0.7270808947008157\n        gas: 0.005948358556199751\n        geothermal: 6.565819576690282e-05\n        hydro: 0.2543957283466846\n        hydro discharge: 0.0010056423455618718\n        nuclear: 0.005304046279473376\n        oil: 0.00038198655760420967\n        solar: 0.000497031531616021\n        unknown: 0.0008411442278717816\n        wind: 0.003624222259524219\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0014411684571781424\n        coal: 0.6234006411274695\n        gas: 0.007250622339353023\n        geothermal: 0.00012212087341112538\n        hydro: 0.34176181088560487\n        hydro discharge: 0.0015554174509350125\n        nuclear: 0.0080018991966589\n        oil: 0.0001500721993598939\n        solar: 0.0004574463707792612\n        unknown: 0.0015379541509682188\n        wind: 0.014320500361216557\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.003825396988667987\n        coal: 0.6502184683720258\n        gas: 0.018989025130874408\n        geothermal: 0.0003817950039000822\n        hydro: 0.28262398630622415\n        hydro discharge: 0.0022124362931660486\n        nuclear: 0.015284950187312603\n        oil: 0.0001898514378378832\n        solar: 0.0026837136320591068\n        unknown: 0.002899662337264437\n        wind: 0.020690301874755932\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0017912958604173663\n        coal: 0.613322473129784\n        gas: 0.00703925995478543\n        geothermal: 0.00012751826161819273\n        hydro: 0.33030216798968653\n        hydro discharge: 0.014600931913772536\n        nuclear: 0.008269218194690196\n        oil: 0.00011202115125997596\n        solar: 0.0016569035379299945\n        unknown: 0.0016732649847972852\n        wind: 0.021104554407643715\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0020628779558946827\n        coal: 0.6602547364983326\n        gas: 0.011301343340040352\n        geothermal: 0.00011149232916199167\n        hydro: 0.27690182031746347\n        hydro discharge: 0.009973902547127135\n        nuclear: 0.009074566830126422\n        oil: 0.0003045812794137221\n        solar: 0.0021526602194516958\n        unknown: 0.0013608493381640943\n        wind: 0.026500673522492912\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002697922100849748\n        coal: 0.5571688809769189\n        gas: 0.011517407675867963\n        geothermal: 3.6935020423848706e-05\n        hydro: 0.3730878116312567\n        hydro discharge: 0.02208700027453017\n        nuclear: 0.010046793857203234\n        oil: 0.0002459444419178135\n        solar: 0.0035390831063479575\n        unknown: 0.001165420011400052\n        wind: 0.018406271770396554\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.833447160914084e-09\n        biomass: 0.005779908256009173\n        coal: 0.5544771224447967\n        gas: 0.023259641466309156\n        geothermal: 2.5859855481112698e-05\n        hydro: 0.3281883426343818\n        hydro discharge: 0.016435069853507192\n        nuclear: 0.02452557072682254\n        oil: 0.0002119767436798232\n        solar: 0.01565642226201501\n        unknown: 0.0026649035309820757\n        wind: 0.028774809119518137\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2021-01-01'\n      value: 0.2599\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 0.2086\n    - datetime: '2024-01-01'\n      value: 0.3879\n    - datetime: '2025-01-01'\n      value: 0.4357\nisRenewable:\n  hydro discharge:\n    - datetime: '2021-01-01'\n      value: 0.2476\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 0.1948\n    - datetime: '2024-01-01'\n      value: 0.3443\n    - datetime: '2025-01-01'\n      value: 0.4224\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\ntimezone: Asia/Bahrain\nzone_name: Bosnia and Herzegovina\n"
  },
  {
    "path": "config/zones/BB.yaml",
    "content": "bounding_box:\n  - - -59.61119611196108\n    - 13.084579153820329\n  - - -59.42759427594271\n    - 13.345036229418753\ncenter_point:\n  - -59.519395193951894\n  - 13.21480769161954\ncentroid:\n  - -59.548795487954834\n  - 13.196680642402066\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 300.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: BB\ncountry_name: Barbados\ncurrency: BBD\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0028357972403870034\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9828582142194107\n        solar: 0.014305633100344143\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: BB.fetch_consumption\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Barbados\nzone_name: Barbados\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/BD.yaml",
    "content": "bounding_box:\n  - - 88.0226802268023\n    - 20.76233855264178\n  - - 92.64152641526417\n    - 26.453754979317054\ncenter_point:\n  - 90.38515806873329\n  - 24.0522788218513\ncentroid:\n  - 90.50032320418202\n  - 23.52364309030219\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 520.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1850.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2860.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4770.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 6040.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 8300.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 9120.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10270.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10380.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 11350.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 11700.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 12030.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 13050.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2910.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 4860.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 6400.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 6920.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 7280.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 7560.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 7720.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 340.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 510.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 520.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 750.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 850.0\n  wind:\n    - _comment: https://en.powerchina.cn/2023-10/13/c_828590.htm\n      datetime: '2023-10-12'\n      source: POWERCHINA\n      value: 66.0\ncontributors:\n  - systemcatch\n  - alixunderplatz\n  - MuffinCompiler\n  - consideRatio\n  - VIKTORVAV99\ncountry: BD\ncountry_name: Bangladesh\ncurrency: BDT\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.019223865439698125\n        gas: 0.7063509413074716\n        geothermal: 0.0\n        hydro: 0.021956874808040126\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.17765923703065684\n        solar: 0.0\n        unknown: 0.07480900566274264\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.020665258242750766\n        gas: 0.664603464373554\n        geothermal: 0.0\n        hydro: 0.016088869637315456\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.22398666430806533\n        solar: 0.0\n        unknown: 0.07465568024265423\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.018622512550294033\n        gas: 0.6563859756492318\n        geothermal: 0.0\n        hydro: 0.017614590536109\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.22734927933157506\n        solar: 4.5572559065377614e-05\n        unknown: 0.07998201337672385\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.027806682922118898\n        gas: 0.6546710383551821\n        geothermal: 0.0\n        hydro: 0.013467415925663688\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.22537459332620308\n        solar: 0.0002594455650243976\n        unknown: 0.07842075898562935\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.028502368493508453\n        gas: 0.7012916979101751\n        geothermal: 0.0\n        hydro: 0.011639227055485878\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.15728319681354244\n        solar: 0.0008209766278389648\n        unknown: 0.10046246011345353\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.06530822178720651\n        gas: 0.6583641427014095\n        geothermal: 0.0\n        hydro: 0.01298112244140487\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.1699736878433138\n        solar: 0.0010681709934193268\n        unknown: 0.09230462720002905\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.06025470028149985\n        gas: 0.6106149908482135\n        geothermal: 0.0\n        hydro: 0.01186768345979753\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.2271658180166286\n        solar: 0.0030462873303903847\n        unknown: 0.08705050182886116\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.08861076517736648\n        gas: 0.5054189386101363\n        geothermal: 0.0\n        hydro: 0.012120940061198323\n        hydro discharge: 0.0\n        nuclear: 5.056497834676158e-09\n        oil: 0.2962161848027614\n        solar: 0.005263177576637186\n        unknown: 0.09236998792883622\n        wind: 2.3596989895155405e-09\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.5609471684274481e-06\n        coal: 0.2532058133280192\n        gas: 0.4913198470058421\n        geothermal: 2.7080660838339147e-07\n        hydro: 0.014426678213695214\n        hydro discharge: 0.0\n        nuclear: 6.771099726012816e-05\n        oil: 0.14666219681093592\n        solar: 0.008727651366069558\n        unknown: 0.08528506809141706\n        wind: 0.0003031869931473852\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.999295169438712e-06\n        coal: 0.36997276768230464\n        gas: 0.4590484049199834\n        geothermal: 3.502757155638383e-07\n        hydro: 0.015051005602341717\n        hydro discharge: 0.0\n        nuclear: 0.00010284198764791426\n        oil: 0.12302198747229955\n        solar: 0.01021179644515913\n        unknown: 0.021465682698105372\n        wind: 0.001123168509769495\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: ERP_PGCB.fetch_consumption\n  production: ERP_PGCB.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Dhaka\nzone_name: Bangladesh\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/BE.yaml",
    "content": "_comment: Biomass includes waste incineration\nbounding_box:\n  - - 2.521825218252218\n    - 49.49561967277913\n  - - 6.373863738637425\n    - 51.49627347325486\ncenter_point:\n  - 4.635704587958106\n  - 50.665927984914006\ncentroid:\n  - 4.5728798751402415\n  - 50.647047977501785\ncapacity:\n  battery storage:\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 394.16\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 959.6500000000001\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 960.28\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 981.39\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1009.53\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1034.23\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1084.1100000000001\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1113.98\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1114.46\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1059.6100000000001\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 6463.53\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 6533.63\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 6641.97\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 6798.85\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 7281.57\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 6818.77\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 6987.62\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 6994.91\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 8348.3\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 169.57\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 170.85\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 172.49\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 175.34\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 175.7\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 184.7\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 185.51\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 144.33\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1308.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 5943.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 4937.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 3929.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 224.2\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 239.13\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 242.13\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 246.28\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 275.32\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 398.47\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 449.87\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 451.51\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 589.52\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2952.78\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 3369.05\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 3886.6\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 4787.56\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 6474.96\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 8788.79\n    - datetime: '2024-06-06'\n      source: elia.be\n      value: 9986.05\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 10696.21\n  unknown:\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 18.5\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 27.05\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 27.08\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 13.67\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2621.92\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 3157.19\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 3796.2799999999997\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 4670.83\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 4883.4\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 5041.05\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 5315.28\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 5439.18\ncontributors:\n  - corradio\n  - nessie2013\n  - Fred-3000\n  - gadakast\ncountry: BE\ncountry_name: Belgium\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 75.05\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 131.51\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 395.0912361\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 388.02\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 383.38\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 385.79\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 151.33\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 120.58\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 129.86\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 116.34\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 96.76\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 117.54\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 108.05\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 164.51\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1152.0081440000001\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1170.245378\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 515.0912361000001\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 508.02\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 503.38\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 505.79\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 162.03\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 131.28\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 140.56\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 127.04\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 107.46\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 128.24\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 36.0\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.056218890536539654\n        coal: 0.06221050792073366\n        gas: 0.2737544345048052\n        geothermal: 5.905683571924522e-06\n        hydro: 0.01967110870987202\n        hydro discharge: 0.013657679782305799\n        nuclear: 0.37007928650578653\n        oil: 0.000618313580866166\n        solar: 0.037971993349603425\n        unknown: 0.09994800414858096\n        wind: 0.06586386215023736\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04819080612659378\n        coal: 0.031945390458094046\n        gas: 0.25553856231945715\n        geothermal: 3.480815158758225e-06\n        hydro: 0.011019997414251595\n        hydro discharge: 0.01250924578774438\n        nuclear: 0.47738111174099884\n        oil: 0.0002227680894862488\n        solar: 0.03389177939888846\n        unknown: 0.07606267316414166\n        wind: 0.053234158802051144\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05373310842933919\n        coal: 0.024793634882484636\n        gas: 0.2650784448630984\n        geothermal: 3.3465085440994236e-06\n        hydro: 0.00846316219277695\n        hydro discharge: 0.012415289710613365\n        nuclear: 0.45261678402124256\n        oil: 0.0002865565279083703\n        solar: 0.03342020652794594\n        unknown: 0.08177274018623479\n        wind: 0.06741670857798299\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05756962166065606\n        coal: 0.03534536876943843\n        gas: 0.29332204765792697\n        geothermal: 7.0003918516934296e-06\n        hydro: 0.020612278854107116\n        hydro discharge: 0.012450735554771076\n        nuclear: 0.3837787082210448\n        oil: 0.00046571776223786526\n        solar: 0.04583847841907627\n        unknown: 0.060912344142783466\n        wind: 0.08969769879617417\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.047316821849878656\n        coal: 0.014701564959114512\n        gas: 0.26808182760894567\n        geothermal: 2.6223203837008742e-06\n        hydro: 0.009068718591221098\n        hydro discharge: 0.009534766505959111\n        nuclear: 0.46119806515097395\n        oil: 0.00029089758665801945\n        solar: 0.03877679416490319\n        unknown: 0.058399190508512146\n        wind: 0.09262872495159424\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05097566846278856\n        coal: 0.010901486103212378\n        gas: 0.29325598711888645\n        geothermal: 3.705983681165401e-06\n        hydro: 0.011021287580001675\n        hydro discharge: 0.011829390302228775\n        nuclear: 0.3828217530564536\n        oil: 0.00017471621882864406\n        solar: 0.049929718363128504\n        unknown: 0.057774411291693355\n        wind: 0.13131187170128833\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04432958018688386\n        coal: 0.014990757863057222\n        gas: 0.21014668850671028\n        geothermal: 1.0487203384584603e-05\n        hydro: 0.00931933338608206\n        hydro discharge: 0.009215094067861094\n        nuclear: 0.5032486084751188\n        oil: 0.00028237304538970777\n        solar: 0.05116024683321427\n        unknown: 0.03801985645831479\n        wind: 0.11927693348898978\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04938497716914559\n        coal: 0.018230695276673373\n        gas: 0.23532953093621642\n        geothermal: 1.358919337888176e-05\n        hydro: 0.0046367303996868\n        hydro discharge: 0.012854389144460913\n        nuclear: 0.41997518420103436\n        oil: 0.0003191462141021785\n        solar: 0.07410994532324028\n        unknown: 0.0536666091229907\n        wind: 0.13147918665155192\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 6.696230869351308e-08\n        biomass: 0.039737079015259795\n        coal: 0.0126681363503088\n        gas: 0.19685780069999642\n        geothermal: 1.197544883109636e-05\n        hydro: 0.014508175037236146\n        hydro discharge: 0.010811833862871292\n        nuclear: 0.3872081054937377\n        oil: 0.00044303243367853026\n        solar: 0.0905093665969703\n        unknown: 0.06468194483517745\n        wind: 0.18256247446932422\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 9.746697456154453e-06\n        biomass: 0.03435602059494842\n        coal: 0.010980056751155542\n        gas: 0.1540536842762035\n        geothermal: 8.826583054065535e-06\n        hydro: 0.024214504064261802\n        hydro discharge: 0.013925442328146726\n        nuclear: 0.4243686476776474\n        oil: 0.0005749646468571695\n        solar: 0.10308608811761544\n        unknown: 0.055460468391665484\n        wind: 0.17896151273177904\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.8504\n    - datetime: '2025-01-01'\n      value: 0.7178\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.6614\n    - datetime: '2021-01-01'\n      value: 0.7439\n    - datetime: '2022-01-01'\n      value: 0.7222\n    - datetime: '2023-01-01'\n      value: 0.7489\n    - datetime: '2024-01-01'\n      value: 0.7944\n    - datetime: '2025-01-01'\n      value: 0.7513\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.4838\n    - datetime: '2025-01-01'\n      value: 0.3794\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2656\n    - datetime: '2021-01-01'\n      value: 0.2448\n    - datetime: '2022-01-01'\n      value: 0.297\n    - datetime: '2023-01-01'\n      value: 0.3644\n    - datetime: '2024-01-01'\n      value: 0.3864\n    - datetime: '2025-01-01'\n      value: 0.4253\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: BE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Brussels\nzone_name: Belgium\n"
  },
  {
    "path": "config/zones/BF.yaml",
    "content": "bounding_box:\n  - - -5.524255242552385\n    - 9.392385444787848\n  - - 2.388623886238889\n    - 15.069491043133539\ncenter_point:\n  - -1.5714554596591372\n  - 12.395099231962625\ncentroid:\n  - -1.8678342627581854\n  - 12.102744817462897\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 290.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 340.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 390.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 400.0\ncountry: BF\ncountry_name: Burkina Faso\ncurrency: XOF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Ouagadougou\nzone_name: Burkina Faso\n"
  },
  {
    "path": "config/zones/BG.yaml",
    "content": "bounding_box:\n  - - 22.343623436234395\n    - 41.23970280944252\n  - - 28.604086040860437\n    - 44.22780376465951\ncenter_point:\n  - 25.326154912268514\n  - 42.71506327473158\ncentroid:\n  - 25.124621738020682\n  - 42.667946937109235\ncapacity:\n  battery storage:\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 220.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 80.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 81.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 80.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4481.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4475.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 561.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 981.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1232.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1266.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1305.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 695.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 723.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 729.0\n  geothermal:\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2340.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 2344.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 2347.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2349.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2350.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2352.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 2347.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 864.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2000.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2080.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 2000.0\n  oil:\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1046.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1052.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1059.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1084.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1246.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1726.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 3092.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 4568.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 4873.0\n  unknown:\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 701.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 700.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 705.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 711.0\ncontributors:\n  - yurukov\n  - ultibo\n  - systemcatch\n  - bogomil\n  - Pantkowsky\n  - MindFreeze\ncountry: BG\ncountry_name: Bulgaria\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1110.9\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1136.88\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 419.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1067.4905370000001\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1085.727771\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1170.9\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1196.88\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 27.73333333\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004116843895948352\n        coal: 0.485891091160113\n        gas: 0.009672242118495794\n        geothermal: 2.0252960205889294e-07\n        hydro: 0.11224649230455917\n        hydro discharge: 0.022464241676399814\n        nuclear: 0.3043610315651058\n        oil: 1.0324367892652374e-06\n        solar: 0.026387890654927474\n        unknown: 1.789443091966909e-05\n        wind: 0.03484095220868181\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005547402690548412\n        coal: 0.4690319518066637\n        gas: 0.010369936670194684\n        geothermal: 4.5071619512471826e-07\n        hydro: 0.09182828143035204\n        hydro discharge: 0.02243052468801112\n        nuclear: 0.3364750137656216\n        oil: 3.2957624020129194e-06\n        solar: 0.02886316804226203\n        unknown: 8.341974537039722e-05\n        wind: 0.03536638652852098\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006584679256108687\n        coal: 0.47909778993474483\n        gas: 0.031243579040098658\n        geothermal: 2.4615182913261117e-05\n        hydro: 0.07113809628030592\n        hydro discharge: 0.0142451387909437\n        nuclear: 0.33117459287897266\n        oil: 8.982576317166026e-06\n        solar: 0.028806773891622273\n        unknown: 4.183988837475235e-05\n        wind: 0.03763384105872611\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004452428152891623\n        coal: 0.39625495969982866\n        gas: 0.07911910203917144\n        geothermal: 3.279775997334128e-05\n        hydro: 0.12315823989960399\n        hydro discharge: 1.1357071894824275e-05\n        nuclear: 0.3397455478047489\n        oil: 8.011048252285986e-06\n        solar: 0.026002831906721684\n        unknown: 1.6615737512768632e-05\n        wind: 0.031198035644698693\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005158452679445958\n        coal: 0.39040231935153497\n        gas: 0.0864695567009188\n        geothermal: 5.1604152052722344e-05\n        hydro: 0.09094524347920172\n        hydro discharge: 5.275228935177658e-05\n        nuclear: 0.3654182254909994\n        oil: 1.0197504270284393e-05\n        solar: 0.0276735188023184\n        unknown: 8.470600924525622e-05\n        wind: 0.033733322066500766\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005491997095228932\n        coal: 0.33167649241538666\n        gas: 0.09719857246747227\n        geothermal: 0.00020689382995389764\n        hydro: 0.0998790513106106\n        hydro discharge: 0.00012041673568094986\n        nuclear: 0.39950419064379894\n        oil: 1.5431093853614474e-05\n        solar: 0.026466865678296852\n        unknown: 0.0002519527423080095\n        wind: 0.039188009888703516\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0053551492348972675\n        coal: 0.38797096387627483\n        gas: 0.08966149105407079\n        geothermal: 0.00013435432682014676\n        hydro: 0.11833569104454031\n        hydro discharge: 3.3462061586339495e-05\n        nuclear: 0.3419296728238794\n        oil: 6.709813660144667e-06\n        solar: 0.025219986064829582\n        unknown: 5.6131429344362975e-05\n        wind: 0.03129634373707437\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005951946705042606\n        coal: 0.454520024203459\n        gas: 0.0732534851473844\n        geothermal: 6.246738320106017e-05\n        hydro: 0.08086012660847366\n        hydro discharge: 3.5214483523610994e-05\n        nuclear: 0.32389420238124844\n        oil: 5.606585914896348e-05\n        solar: 0.030676507796192704\n        unknown: 5.894219452509825e-05\n        wind: 0.030630920679091886\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005999825481596691\n        coal: 0.3006177493121059\n        gas: 0.09258960146635109\n        geothermal: 0.00025348914142809805\n        hydro: 0.10057197340096605\n        hydro discharge: 0.00024387319100831073\n        nuclear: 0.38415885377831344\n        oil: 4.675006237391663e-05\n        solar: 0.06795988149817286\n        unknown: 0.00022882999178335735\n        wind: 0.04732904904146526\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005243040501734978\n        coal: 0.2434311863985376\n        gas: 0.11025729199559865\n        geothermal: 0.0007605334550832228\n        hydro: 0.09994497965794578\n        hydro discharge: 0.0007950590840366164\n        nuclear: 0.375058152286718\n        oil: 7.767242175116086e-05\n        solar: 0.11539420850969283\n        unknown: 0.00042608502444417757\n        wind: 0.04861173432578981\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: BG.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Sofia\nzone_name: Bulgaria\n"
  },
  {
    "path": "config/zones/BH.yaml",
    "content": "bounding_box:\n  - - 50.45990459904601\n    - 25.78973254482439\n  - - 50.61830618306183\n    - 26.194728986551596\ncenter_point:\n  - 50.53910539105392\n  - 25.992230765687992\ncentroid:\n  - 50.54810548105482\n  - 26.039098728467376\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5310.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 7100.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 8600.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncontributors:\n  - q--\n  - nessie2013\ncountry: BH\ncountry_name: Bahrain\ncurrency: BHD\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.9999999999999998\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.9999999979281821\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 1.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: GCCIA.fetch_consumption\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Bahrain\nzone_name: Bahrain\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/BI.yaml",
    "content": "bounding_box:\n  - - 28.996489964899666\n    - -4.463358543914708\n  - - 30.82530825308254\n    - -2.30242346614763\ncenter_point:\n  - 29.921668191814078\n  - -3.5095918054132493\ncentroid:\n  - 29.846724554202083\n  - -3.1475712104986293\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\ncountry: BI\ncountry_name: Burundi\ncurrency: BIF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Bujumbura\nzone_name: Burundi\n"
  },
  {
    "path": "config/zones/BJ.yaml",
    "content": "bounding_box:\n  - - 0.768607686076876\n    - 6.213950472787388\n  - - 3.835838358383597\n    - 12.399090476833294\ncenter_point:\n  - 2.2836346851900076\n  - 9.290317399155198\ncentroid:\n  - 2.382090154351049\n  - 9.747409139345764\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 170.0\ncountry: BJ\ncountry_name: Benin\ncurrency: XOF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Porto-Novo\nzone_name: Benin\n"
  },
  {
    "path": "config/zones/BM.yaml",
    "content": "bounding_box:\n  - - -64.8842596183096\n    - 32.24715065573363\n  - - -64.6476046795164\n    - 32.38957682629426\ncenter_point:\n  - -64.76504745755302\n  - 32.309606494363315\ncentroid:\n  - -64.8078812642318\n  - 32.2979873622962\ncontributors:\n  - VIKTORVAV99\ncountry: BM\ncountry_name: Bermuda\ncurrency: BMD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: Atlantic/Bermuda\nzone_name: Bermuda\n"
  },
  {
    "path": "config/zones/BN.yaml",
    "content": "bounding_box:\n  - - 114.00054000540004\n    - 4.021531572695231\n  - - 115.36135361353612\n    - 5.054773378091141\ncenter_point:\n  - 114.68094680946808\n  - 4.538152475393186\ncentroid:\n  - 114.71434714347144\n  - 4.535608328134595\ncapacity:\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 980.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 990.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\ncountry: BN\ncountry_name: Brunei\ncurrency: BND\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Brunei\nzone_name: Brunei\n"
  },
  {
    "path": "config/zones/BO.yaml",
    "content": "bounding_box:\n  - - -69.66609666096656\n    - -22.89284326675208\n  - - -57.551975519755146\n    - -9.681086552880778\ncenter_point:\n  - -63.57658074636778\n  - -16.31882317007259\ncentroid:\n  - -65.04744965211675\n  - -16.514933194829595\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1490.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1500.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2180.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2390.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1620.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2650.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 600.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 730.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 740.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 720.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 170.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\ncontributors:\n  - igorarduin\n  - corradio\n  - skovhus\ncountry: BO\ncountry_name: Bolivia\ncurrency: BOB\ndisclaimer: Unknown production is the aggregation of thermal production, mainly gas, coal and oil.\nemissionFactors:\n  direct:\n    unknown:\n      _url: https://www.iea.org/fuels-and-technologies/electricity\n      source: IEA 2020; assumes 1.3% oil, 96.0% gas, 2.6% biomass\n      value: 360.478\n  lifecycle:\n    unknown:\n      _url: https://www.iea.org/fuels-and-technologies/electricity\n      source: IEA 2020; assumes 1.3% oil, 96.0% gas, 2.6% biomass\n      value: 484.83\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.2078246874985324\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.7848664392675876\n        wind: 0.007308873233880055\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.2819155108311643\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.6996776810729152\n        wind: 0.018406808095920373\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.3423013720016836\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.6318523306683219\n        wind: 0.025846297329994508\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.31263747458041574\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.652738565547545\n        wind: 0.03462395987203926\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0005477671029211332\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.3104061296985262\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0036478389888090416\n        unknown: 0.6399579154205218\n        wind: 0.04544037042048761\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.026455055307504173\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.26896197379676323\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0328273813074245\n        unknown: 0.6302950772074236\n        wind: 0.04146051238088455\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.024673269564771436\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.20597050834330496\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.03195206006828677\n        unknown: 0.694355562939673\n        wind: 0.04304859908396372\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.023769909631215735\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.24402631322202514\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.02987487302326382\n        unknown: 0.6597806473912572\n        wind: 0.04254825673223788\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  generationForecast: CNDC.fetch_generation_forecast\n  production: CNDC.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/La_Paz\nzone_name: Bolivia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nisRenewable:\n  unknown:\n    source: IEA 2020; assumes 1.3% oil, 96.0% gas, 2.6% biomass\n    value: 0.026\nisLowCarbon:\n  unknown:\n    source: IEA 2020; assumes 1.3% oil, 96.0% gas, 2.6% biomass\n    value: 0.026\n"
  },
  {
    "path": "config/zones/BR-CS.yaml",
    "content": "bounding_box:\n  - - -74.0185401854018\n    - -25.307080005952784\n  - - -39.67419674196739\n    - -7.11801719905241\ncenter_point:\n  - -56.738675265321376\n  - -16.157032956222388\ncentroid:\n  - -54.78559517672911\n  - -15.732630454134739\ncapacity:\n  hydro:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 54189.0\n  nuclear:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 1990.0\n  solar:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 17163.0\n  unknown:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 14936.0\ncontributors:\n  - alexanmtz\n  - corradio\n  - systemcatch\n  - nessie2013\ncountry: BR\ncountry_name: Brazil\ncurrency: BRL\ndisclaimer: Unknown production is the aggregation of thermal production, mainly gas, coal and oil.\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.8053490834276996\n        hydro discharge: 0.0\n        nuclear: 0.049489111332603086\n        oil: 0.0\n        solar: 0.0055506309554190685\n        unknown: 0.13959130467978306\n        wind: 1.9789358782606655e-05\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.8053489441672584\n        hydro discharge: 0.0\n        nuclear: 0.04948910277497806\n        oil: 0.0\n        solar: 0.0055508029383063325\n        unknown: 0.13959128054174522\n        wind: 1.9789355360643567e-05\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.249228188673338e-11\n        coal: 3.616448221771275e-08\n        gas: 1.5312713881561287e-06\n        geothermal: 3.083076062891113e-11\n        hydro: 0.7779321373145881\n        hydro discharge: 0.0\n        nuclear: 0.04527104001332994\n        oil: 5.84551221524155e-08\n        solar: 0.000829646920095698\n        unknown: 0.1750313324927197\n        wind: 0.0009341617187511966\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.003830338905516e-09\n        coal: 7.954575998358403e-08\n        gas: 2.174271295526525e-06\n        geothermal: 6.156792568388858e-10\n        hydro: 0.8160714468035054\n        hydro discharge: 1.1605553991412995e-08\n        nuclear: 0.046826356480134584\n        oil: 3.8787793180849806e-08\n        solar: 0.004484721299637331\n        unknown: 0.12375822629045398\n        wind: 0.008856937435363019\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.3360772872111214e-08\n        coal: 7.486668516441996e-08\n        gas: 8.788987915318254e-06\n        geothermal: 0.0\n        hydro: 0.7933707738970243\n        hydro discharge: 9.016452176148409e-08\n        nuclear: 0.03945002240768331\n        oil: 1.4122353481921765e-07\n        solar: 0.0033956228428686386\n        unknown: 0.12787574226079562\n        wind: 0.03589873063388617\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.0054926471167212e-06\n        coal: 9.103605005460571e-06\n        gas: 0.0002858042484985867\n        geothermal: 0.0\n        hydro: 0.7050090102307355\n        hydro discharge: 9.506998768153956e-06\n        nuclear: 0.039524831779328654\n        oil: 1.3093624763068962e-05\n        solar: 0.0077160571032703525\n        unknown: 0.2170794211088142\n        wind: 0.0303521622354851\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.941801681790925e-10\n        coal: 1.7941535924378236e-08\n        gas: 1.044326329365311e-06\n        geothermal: 0.0\n        hydro: 0.4407451116620336\n        hydro discharge: 0.0\n        nuclear: 0.014664093355079339\n        oil: 2.1396196111957018e-08\n        solar: 0.003992575035050802\n        unknown: 0.1268685461911173\n        wind: 0.41372858968700815\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.049548405597859e-10\n        coal: 8.793305109298208e-09\n        gas: 5.3801143102942975e-09\n        geothermal: 5.7850691508540835e-11\n        hydro: 0.797838311497004\n        hydro discharge: 0.0\n        nuclear: 0.0391723280149547\n        oil: 6.942082981024901e-10\n        solar: 0.013274226047285302\n        unknown: 0.11331442099410637\n        wind: 0.03640069464517496\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.178232401996702e-07\n        coal: 7.655207535122396e-07\n        gas: 9.75246844572048e-07\n        geothermal: 5.9921740302802376e-09\n        hydro: 0.7686003044523482\n        hydro discharge: 9.220834010065936e-09\n        nuclear: 0.03654568165775523\n        oil: 7.778881629263342e-08\n        solar: 0.06146048738992997\n        unknown: 0.09643014697164487\n        wind: 0.03696091866010207\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.05179340766536e-06\n        coal: 9.210456219545673e-08\n        gas: 5.634601839995193e-08\n        geothermal: 0.0\n        hydro: 0.6957042686480721\n        hydro discharge: 0.0\n        nuclear: 0.039281968217769206\n        oil: 1.2154824470331314e-07\n        solar: 0.10222112507742348\n        unknown: 0.11400721976581607\n        wind: 0.048779087668148355\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: ONS.fetch_production\n  productionCapacity: ONS.fetch_production_capacity\nregion: Americas\ntimezone: America/Sao_Paulo\nzone_name: Central Brazil\n"
  },
  {
    "path": "config/zones/BR-N.yaml",
    "content": "bounding_box:\n  - - -73.80613806138057\n    - -13.354676185084813\n  - - -41.78196026199298\n    - 5.266573637368978\ncenter_point:\n  - -57.81853853370403\n  - -4.152491836879543\ncentroid:\n  - -53.57735770147508\n  - -3.3948074092778744\ncapacity:\n  hydro:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 22090.0\n  solar:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 1815.0\n  unknown:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 4725.0\n  wind:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 426.0\ncontributors:\n  - alexanmtz\n  - corradio\n  - systemcatch\n  - nessie2013\ncountry: BR\ncountry_name: Brazil\ncurrency: BRL\ndisclaimer: Unknown production is the aggregation of thermal production, mainly gas, coal and oil.\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.7894126189677013\n        hydro discharge: 0.0\n        nuclear: 7.004071158656081e-05\n        oil: 0.0\n        solar: 3.793871877605378e-05\n        unknown: 0.19279720946977486\n        wind: 0.01768168459077276\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.7894126189677013\n        hydro discharge: 0.0\n        nuclear: 7.004071158656081e-05\n        oil: 0.0\n        solar: 3.7938718776053774e-05\n        unknown: 0.19279720946977486\n        wind: 0.01768168459077276\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 5.51390638417178e-10\n        gas: 4.594921986809816e-09\n        geothermal: 0.0\n        hydro: 0.5396742289857193\n        hydro discharge: 0.0\n        nuclear: 0.0009134296880705486\n        oil: 1.8379687947239265e-10\n        solar: 0.00010363184872483442\n        unknown: 0.4265247913459619\n        wind: 0.032783858765131534\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 3.728758788419825e-09\n        geothermal: 0.0\n        hydro: 0.7134231764118907\n        hydro discharge: 0.0\n        nuclear: 8.14193125245411e-05\n        oil: 0.0\n        solar: 0.001947389229510981\n        unknown: 0.21855896223525403\n        wind: 0.06598903416702569\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.6624110555859064\n        hydro discharge: 0.0\n        nuclear: 3.180359881530071e-06\n        oil: 0.0\n        solar: 0.014200149998703728\n        unknown: 0.25008810426412487\n        wind: 0.07329750989927364\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 2.4852639832730417e-09\n        gas: 3.854070915598809e-07\n        geothermal: 0.0\n        hydro: 0.6293481560441929\n        hydro discharge: 8.602836865175912e-09\n        nuclear: 1.1701769878164836e-05\n        oil: 7.455791949819125e-09\n        solar: 0.007981578412777572\n        unknown: 0.23877706101075793\n        wind: 0.12388109269383615\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.227432068185825e-12\n        coal: 1.3440381146634784e-10\n        gas: 4.240777795582025e-09\n        geothermal: 0.0\n        hydro: 0.38752796187829125\n        hydro discharge: 0.0\n        nuclear: 2.7454083537998487e-06\n        oil: 8.592024477300774e-11\n        solar: 0.001789006360875844\n        unknown: 0.17943290417968744\n        wind: 0.4312473777000295\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.6855498806568675\n        hydro discharge: 0.0\n        nuclear: 0.00018093341530418225\n        oil: 0.0\n        solar: 0.01683219169653419\n        unknown: 0.12458795761863838\n        wind: 0.17284902616597395\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.170130718458703e-09\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.6077146039910171\n        hydro discharge: 0.0\n        nuclear: 0.00027010559864405244\n        oil: 0.0\n        solar: 0.05287710910871154\n        unknown: 0.1265073413821398\n        wind: 0.2126308216912361\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.2739608888800852e-07\n        coal: 1.1676307516714172e-08\n        gas: 5.400292226480305e-09\n        geothermal: 0.0\n        hydro: 0.5375948649066086\n        hydro discharge: 0.0\n        nuclear: 0.0004353356546532282\n        oil: 0.0\n        solar: 0.07866961740716195\n        unknown: 0.16330391158139368\n        wind: 0.21999600933875574\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: ONS.fetch_production\n  productionCapacity: ONS.fetch_production_capacity\nregion: Americas\ntimezone: America/Sao_Paulo\nzone_name: North Brazil\n"
  },
  {
    "path": "config/zones/BR-NE.yaml",
    "content": "bounding_box:\n  - - -46.571865718657136\n    - -18.323395781116133\n  - - -34.79614796147959\n    - -2.74107331350884\ncenter_point:\n  - -40.61435490558871\n  - -10.47934926085047\ncentroid:\n  - -42.38474909604173\n  - -10.441985640867259\ncapacity:\n  hydro:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 10831.0\n  solar:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 9851.0\n  unknown:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 7332.0\n  wind:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 24209.0\ncontributors:\n  - alexanmtz\n  - corradio\n  - systemcatch\n  - nessie2013\ncountry: BR\ncountry_name: Brazil\ncurrency: BRL\ndisclaimer: Unknown production is the aggregation of thermal production, mainly gas, coal and oil.\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.2752383584945799\n        hydro discharge: 0.0\n        nuclear: 5.9309434182619766e-05\n        oil: 0.0\n        solar: 0.03970537167826751\n        unknown: 0.16781432490568843\n        wind: 0.5171823489682759\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.2752383887120969\n        hydro discharge: 0.0\n        nuclear: 5.9309440694008085e-05\n        oil: 0.0\n        solar: 0.03970526625066874\n        unknown: 0.16781434332947293\n        wind: 0.5171824057480303\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 7.108985915685162e-10\n        gas: 2.2274822535813507e-08\n        geothermal: 0.0\n        hydro: 0.1864629748726822\n        hydro discharge: 0.0\n        nuclear: 0.0005566603743784305\n        oil: 9.478647887580215e-10\n        solar: 0.012219591103859955\n        unknown: 0.32796393716373606\n        wind: 0.4727967272439265\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.1148903958097307e-10\n        coal: 2.6311413341109643e-08\n        gas: 9.943707440226987e-07\n        geothermal: 0.0\n        hydro: 0.33075963323354324\n        hydro discharge: 0.0\n        nuclear: 0.0014548852526241143\n        oil: 2.084845040164196e-08\n        solar: 0.018401247810126153\n        unknown: 0.23344514636749594\n        wind: 0.41593804993069733\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.3107228808886842e-09\n        coal: 1.0284133373126598e-08\n        gas: 1.4053974028236434e-06\n        geothermal: 0.0\n        hydro: 0.2726729193042122\n        hydro discharge: 2.9037553053533923e-08\n        nuclear: 0.0003450942786437991\n        oil: 2.1778164790150444e-08\n        solar: 0.039656149331192596\n        unknown: 0.20343575995736982\n        wind: 0.4838886071024582\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 2.6443896708832866e-08\n        geothermal: 0.0\n        hydro: 0.3357672231921934\n        hydro discharge: 1.0837662585587241e-10\n        nuclear: 0.0007942300827144475\n        oil: 7.586363809911069e-10\n        solar: 0.02775218086246278\n        unknown: 0.18986845797224147\n        wind: 0.4458178865401927\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.4317768191309357\n        hydro discharge: 0.0\n        nuclear: 0.0006193649286278817\n        oil: 0.0\n        solar: 0.032290123802764074\n        unknown: 0.12988336628249053\n        wind: 0.4054303292962768\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.34962819735881057\n        hydro discharge: 0.0\n        nuclear: 0.0001670293086216895\n        oil: 0.0\n        solar: 0.06229765746767236\n        unknown: 0.0497175347171999\n        wind: 0.5381895796206718\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.358342593834052e-09\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.2720517147801057\n        hydro discharge: 0.0\n        nuclear: 0.0002299029334262088\n        oil: 0.0\n        solar: 0.10822579720009357\n        unknown: 0.0359407124776811\n        wind: 0.5835518733633631\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.6946281224835998e-07\n        coal: 6.90627864486439e-09\n        gas: 3.36681083937139e-09\n        geothermal: 0.0\n        hydro: 0.2317203982745021\n        hydro discharge: 0.0\n        nuclear: 0.00044213141232439523\n        oil: 3.4531393224321947e-10\n        solar: 0.15130703599836154\n        unknown: 0.03702929035700427\n        wind: 0.5795009589558684\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: ONS.fetch_production\n  productionCapacity: ONS.fetch_production_capacity\nregion: Americas\ntimezone: America/Sao_Paulo\nzone_name: North-East Brazil\n"
  },
  {
    "path": "config/zones/BR-S.yaml",
    "content": "bounding_box:\n  - - -57.61317613176128\n    - -33.74045114057622\n  - - -48.08388083880834\n    - -22.52219281301587\ncenter_point:\n  - -52.745761934844275\n  - -27.70486322049466\ncentroid:\n  - -52.266744231674885\n  - -28.068595922217657\ncapacity:\n  hydro:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 15493.0\n  solar:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 6319.0\n  unknown:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 3608.0\n  wind:\n    - datetime: '2023-01-01'\n      source: ons.org.br\n      value: 2000.0\ncontributors:\n  - alexanmtz\n  - corradio\n  - systemcatch\n  - nessie2013\ncountry: BR\ncountry_name: Brazil\ncurrency: BRL\ndisclaimer: Unknown production is the aggregation of thermal production, mainly gas, coal and oil.\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.7746781867502254\n        hydro discharge: 0.0\n        nuclear: 7.73704515126117e-05\n        oil: 0.0\n        solar: 4.2226955328972205e-05\n        unknown: 0.1482280957610305\n        wind: 0.07697360089959956\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.7746781736885375\n        hydro discharge: 0.0\n        nuclear: 7.737045020808458e-05\n        oil: 0.0\n        solar: 4.224370209448699e-05\n        unknown: 0.14822809326178737\n        wind: 0.07697359960176368\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.647401795447639e-09\n        coal: 5.505444690272198e-07\n        gas: 2.2310805974496146e-05\n        geothermal: 4.6041770355611117e-10\n        hydro: 0.7824416222235816\n        hydro discharge: 0.0\n        nuclear: 0.0015865550912503917\n        oil: 8.378451160462332e-07\n        solar: 2.412243453356355e-05\n        unknown: 0.14014104521108015\n        wind: 0.075782947556476\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.763435318670241e-06\n        coal: 7.56970135697372e-06\n        gas: 0.0015623477896470866\n        geothermal: 4.1354494050769864e-08\n        hydro: 0.8078408670216827\n        hydro discharge: 8.68545983159658e-06\n        nuclear: 0.008742377840543528\n        oil: 2.9388515312728185e-05\n        solar: 0.0008297194984749401\n        unknown: 0.12438498804313904\n        wind: 0.056591204092434955\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00010898764191505095\n        coal: 0.0008937755867462402\n        gas: 0.05972311194428086\n        geothermal: 1.4179602086796663e-08\n        hydro: 0.6801080166352297\n        hydro discharge: 0.000582181168185931\n        nuclear: 0.03332890017336711\n        oil: 0.001521995871280592\n        solar: 0.007951874104334624\n        unknown: 0.1456243361344357\n        wind: 0.07015679321205888\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.091129302799118e-05\n        coal: 0.0005437204581470011\n        gas: 0.020094919942827857\n        geothermal: 0.0\n        hydro: 0.6927205632474635\n        hydro discharge: 0.00045587961051451716\n        nuclear: 0.012920154038582501\n        oil: 0.0006435879843416094\n        solar: 0.0021468883972746698\n        unknown: 0.20273872966400522\n        wind: 0.06769457888845896\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00011971114863225732\n        coal: 0.005801544487969207\n        gas: 0.2904776214308046\n        geothermal: 0.0\n        hydro: 0.470226848180082\n        hydro discharge: 0.00028170009122357244\n        nuclear: 0.024820228079940467\n        oil: 0.007911328560836643\n        solar: 0.0008263408008397935\n        unknown: 0.05946299633976191\n        wind: 0.14007167733312642\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.5831180856448417e-06\n        coal: 4.150730196160992e-06\n        gas: 9.02080263206607e-05\n        geothermal: 7.619027034172554e-09\n        hydro: 0.8242195165583569\n        hydro discharge: 4.728426043435594e-06\n        nuclear: 0.00938612215138508\n        oil: 4.594755518506947e-06\n        solar: 0.0025042998282864\n        unknown: 0.10580005517707093\n        wind: 0.057984722615163894\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.6207796374240122e-05\n        coal: 2.41153079638589e-05\n        gas: 2.6607034132016262e-05\n        geothermal: 1.9296840422845796e-07\n        hydro: 0.803619209598906\n        hydro discharge: 2.1858206581948142e-07\n        nuclear: 0.009191982574227165\n        oil: 2.6215263607040382e-06\n        solar: 0.04686673757882712\n        unknown: 0.08645005556390296\n        wind: 0.05380202476135251\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00023956121028118383\n        coal: 2.8825965168117348e-06\n        gas: 1.7607746981515988e-06\n        geothermal: 3.9567026852547854e-08\n        hydro: 0.7728849990619648\n        hydro discharge: 0.0\n        nuclear: 0.0034584089060956014\n        oil: 1.4034029594394467e-05\n        solar: 0.09072472765632768\n        unknown: 0.07855809321248203\n        wind: 0.05411548912071675\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: ONS.fetch_production\n  productionCapacity: ONS.fetch_production_capacity\nregion: Americas\ntimezone: America/Sao_Paulo\nzone_name: South Brazil\n"
  },
  {
    "path": "config/zones/BR.yaml",
    "content": "bounding_box:\n  - - -74.0185401854018\n    - -33.74045114057622\n  - - -34.79614796147959\n    - 5.266573637368978\ncenter_point:\n  - -54.30535431570473\n  - -13.974005841490072\ncentroid:\n  - -53.38451913043395\n  - -10.308168894524904\ncapacity:\n  hydro: 109413\n  nuclear: 1990\n  solar: 30431\n  unknown: 39584\n  wind: 25628\ncontributors:\n  - alexanmtz\n  - corradio\n  - systemcatch\n  - nessie2013\n  - VIKTORVAV99\ncountry: BR\ncountry_name: Brazil\ncurrency: BRL\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.908696548069447e-10\n        coal: 1.0855491514267656e-07\n        gas: 4.434116493659058e-06\n        geothermal: 9.090178792721199e-11\n        hydro: 0.6643281757877655\n        hydro discharge: 0.0\n        nuclear: 0.027122562957147024\n        oil: 1.6704112549504472e-07\n        solar: 0.0023787718548788092\n        unknown: 0.21786989264069193\n        wind: 0.08829588261097525\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.981954267323062e-05\n        coal: 0.0024143843357833004\n        gas: 0.12088723994181014\n        geothermal: 0.0\n        hydro: 0.42172477815362813\n        hydro discharge: 0.00011722729165100088\n        nuclear: 0.01846697531174137\n        oil: 0.0032923825123210215\n        solar: 0.0038461281447550355\n        unknown: 0.10784224038254847\n        wind: 0.32135882280917694\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.010969391665624e-07\n        coal: 1.6725935071158012e-06\n        gas: 0.00027407152185588405\n        geothermal: 1.0057058670752924e-08\n        hydro: 0.7272622048771608\n        hydro discharge: 1.5224471197296928e-06\n        nuclear: 0.028641113570637297\n        oil: 5.17578454011119e-06\n        solar: 0.007436038041477582\n        unknown: 0.14279473493122014\n        wind: 0.09358294589055349\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.989837316762633e-05\n        coal: 0.00040933251266554884\n        gas: 0.027337676693609852\n        geothermal: 8.639275064584622e-09\n        hydro: 0.7151905339680915\n        hydro discharge: 0.0002664924618493358\n        nuclear: 0.03010994437608144\n        oil: 0.0006966287053741899\n        solar: 0.015233383467608217\n        unknown: 0.1222588322936292\n        wind: 0.08844726357701199\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 7.5889426143880886e-06\n        coal: 9.841179442705718e-05\n        gas: 0.0036084393368975005\n        geothermal: 0.0\n        hydro: 0.6246398100365798\n        hydro discharge: 8.359851778245395e-05\n        nuclear: 0.025012294644159765\n        oil: 0.00011782506228331333\n        solar: 0.012079744635732628\n        unknown: 0.2142440258870572\n        wind: 0.12010825158268812\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.729267735180776e-07\n        coal: 7.225128118177375e-07\n        gas: 1.5533327983774832e-05\n        geothermal: 1.394940613052541e-09\n        hydro: 0.7190729433494978\n        hydro discharge: 8.139312412802881e-07\n        nuclear: 0.024143415964737666\n        oil: 7.915955850355778e-07\n        solar: 0.019741176672250935\n        unknown: 0.10265000620485777\n        wind: 0.13437432110632727\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.2141382459550813e-06\n        coal: 6.599853243075388e-06\n        gas: 6.343140027269196e-06\n        geothermal: 5.297552485316696e-08\n        hydro: 0.6770467842917475\n        hydro discharge: 4.254494978685338e-08\n        nuclear: 0.022352873331058024\n        oil: 6.534320671751018e-07\n        solar: 0.06583823193836316\n        unknown: 0.08770084278573435\n        wind: 0.1470443602496952\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.462040028523969e-05\n        coal: 5.499684621287519e-07\n        gas: 3.3592426390187707e-07\n        geothermal: 7.735667874695227e-09\n        hydro: 0.6157726124966463\n        hydro discharge: 0.0\n        nuclear: 0.022791441381024624\n        oil: 2.483207116641904e-06\n        solar: 0.10611495139875048\n        unknown: 0.0999112179259777\n        wind: 0.15536177833506654\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\nsubZoneNames:\n  - BR-CS\n  - BR-N\n  - BR-NE\n  - BR-S\ntimezone: America/Sao_Paulo\nzone_name: Brazil\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/BS.yaml",
    "content": "bounding_box:\n  - - -78.99738997389969\n    - 20.912602250102395\n  - - -72.75492754927544\n    - 26.907408237364848\ncenter_point:\n  - -75.42745969954076\n  - 24.153801937772545\ncentroid:\n  - -76.49795792054282\n  - 24.665920795645064\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 730.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 870.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 900.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 930.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: BS\ncountry_name: Bahamas\ncurrency: BSD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Nassau\nzone_name: Bahamas\n"
  },
  {
    "path": "config/zones/BT.yaml",
    "content": "bounding_box:\n  - - 88.73188731887316\n    - 26.69990122658588\n  - - 92.08352083520836\n    - 28.35852622998459\ncenter_point:\n  - 90.34152919009483\n  - 27.52220885550897\ncentroid:\n  - 90.69287835735499\n  - 27.326960835907283\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1610.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2330.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: BT\ncountry_name: Bhutan\ncurrency: BTN\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Thimphu\nzone_name: Bhutan\n"
  },
  {
    "path": "config/zones/BW.yaml",
    "content": "bounding_box:\n  - - 19.99864845733816\n    - -26.891288702037656\n  - - 29.349293492934947\n    - -17.788170801589715\ncenter_point:\n  - 24.53717185626963\n  - -22.35501250816072\ncentroid:\n  - 24.69984773909776\n  - -22.82359771901274\ncapacity:\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 730.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\ncountry: BW\ncountry_name: Botswana\ncurrency: BWP\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9619304874032478\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.03571381405585137\n        solar: 0.0023545054483024835\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9619291778474338\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.035714912118947006\n        solar: 0.002355337032443158\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Gaborone\nzone_name: Botswana\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/BY.yaml",
    "content": "_comment: biomass includes 24.4 MW of biogas and 6.6 MW of biomass. gas includes 1273 CHP\nbounding_box:\n  - - 23.164431644316466\n    - 51.23581639765645\n  - - 32.71892718927191\n    - 56.16068318571228\ncenter_point:\n  - 27.68373046367583\n  - 53.751740127851846\ncentroid:\n  - 28.172208782115028\n  - 53.56060161053779\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 9880.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 9810.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 9820.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 9800.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 9680.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 9720.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 9730.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1170.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2340.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\ncontributors:\n  - admetny\ncountry: BY\ncountry_name: Belarus\ncurrency: BYN\nfallbackZoneMixes:\n  _source: https://ourworldindata.org/grapher/electricity-prod-source-stacked?time=earliest..latest&country=~BLR\n  powerOriginRatios:\n    value:\n      gas: 0.98\n      hydro: 0.01\n      unknown: 0.01\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\ntimezone: Europe/Minsk\nzone_name: Belarus\n"
  },
  {
    "path": "config/zones/BZ.yaml",
    "content": "bounding_box:\n  - - -89.22869228692281\n    - 15.880915009420917\n  - - -88.09108091080905\n    - 18.484054682572108\ncenter_point:\n  - -88.70703333083586\n  - 17.106202098779413\ncentroid:\n  - -88.62680055371978\n  - 17.367810072864614\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: BZ\ncountry_name: Belize\ncurrency: BZD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Belize\nzone_name: Belize\n"
  },
  {
    "path": "config/zones/CA-AB.yaml",
    "content": "bounding_box:\n  - - -119.99819998199976\n    - 48.991878515577795\n  - - -110.00090000900003\n    - 59.99976766669326\ncenter_point:\n  - -114.97039368201439\n  - 54.51046629280081\ncentroid:\n  - -116.51992774107003\n  - 51.87658371093803\ncontributors:\n  - mlucchini\n  - alejandranavcas\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 385.61\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 354.84\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 334.83\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 313.55\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 285.67\n    unknown:\n      source: assumes 50% coal and 50% natural gas from Battle River dual fuel power\n        plant\n      value: 565\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 418.61\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 387.84\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 367.83\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 346.55\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 318.67\n    unknown:\n      source: assumes 50% coal and 50% natural gas from Battle River dual fuel power\n        plant\n      value: 655\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 1.195958555371087e-07\n        biomass: 0.00889830481051625\n        coal: 0.43945167826607345\n        gas: 0.4349421759896482\n        geothermal: 1.1473651273066203e-06\n        hydro: 0.025657439992638812\n        hydro discharge: 0.0\n        nuclear: 8.512691723004694e-05\n        oil: 2.4429462996118774e-06\n        solar: 0.007078857741698541\n        unknown: 0.03317216117620114\n        wind: 0.05071041829557307\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 3.767650920208061e-07\n        biomass: 0.0002383378816269695\n        coal: 0.34298047013473554\n        gas: 0.5324941771289313\n        geothermal: 3.36520805652629e-06\n        hydro: 0.024533888820449344\n        hydro discharge: 7.099844698884538e-10\n        nuclear: 0.0002497140811187372\n        oil: 6.158807616345385e-05\n        solar: 0.0002524382915296992\n        unknown: 0.050331005557542476\n        wind: 0.04885455687986297\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 8.738664330612742e-09\n        biomass: 0.006102178541968431\n        coal: 0.32820319852580176\n        gas: 0.5522502856743647\n        geothermal: 2.569167313200145e-07\n        hydro: 0.024968921391805832\n        hydro discharge: 2.446826012571567e-09\n        nuclear: 2.191132694257838e-05\n        oil: 0.000276258657918344\n        solar: 0.005257618559668399\n        unknown: 0.027872484764591688\n        wind: 0.05504682668335144\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 3.983771010446023e-07\n        biomass: 1.5558067966757333e-05\n        coal: 0.2781889758256393\n        gas: 0.5602817684620236\n        geothermal: 3.702939894380955e-06\n        hydro: 0.03122080797809616\n        hydro discharge: 2.4740171376596023e-08\n        nuclear: 0.00031409928485705816\n        oil: 0.00048725791662958436\n        solar: 0.0001138247011532058\n        unknown: 0.053088733315648715\n        wind: 0.07628478623868118\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 4.2865134055393065e-07\n        biomass: 0.014684024422328778\n        coal: 0.21161150296663422\n        gas: 0.6180970889185637\n        geothermal: 3.5680132321252335e-06\n        hydro: 0.027188171472472534\n        hydro discharge: 2.472309297344835e-09\n        nuclear: 0.0002874959007831547\n        oil: 0.0005274391690831506\n        solar: 0.0031427152848106155\n        unknown: 0.04900095847887815\n        wind: 0.0754565638685119\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 4.961748933123038e-07\n        biomass: 0.026008537772990743\n        coal: 0.12204221915549719\n        gas: 0.6917895824894296\n        geothermal: 3.6690340653953888e-06\n        hydro: 0.027739218007292846\n        hydro discharge: 0.0\n        nuclear: 0.0002917619404820305\n        oil: 0.0005103702372588507\n        solar: 0.013593341541024493\n        unknown: 0.030764064738946377\n        wind: 0.08725677487790753\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.3778483164947189e-07\n        biomass: 0.025487664991835086\n        coal: 0.08083712919245124\n        gas: 0.6749269782007778\n        geothermal: 8.542855049260295e-07\n        hydro: 0.022474028984387214\n        hydro discharge: 6.228802663208117e-08\n        nuclear: 6.569658519932574e-05\n        oil: 0.00027748411122305885\n        solar: 0.02658053660529694\n        unknown: 0.05313852726480508\n        wind: 0.11621074286928665\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.865632231173499e-07\n        biomass: 0.02344634646359736\n        coal: 0.022608288477437694\n        gas: 0.7340459989683934\n        geothermal: 5.227598339974988e-07\n        hydro: 0.019220915317458048\n        hydro discharge: 0.0\n        nuclear: 4.9118707658858676e-05\n        oil: 9.853690727516585e-05\n        solar: 0.03183536456739056\n        unknown: 0.024948048115312323\n        wind: 0.14374665671413908\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.1578\n    - datetime: '2022-01-01'\n      value: 0.1597\n    - datetime: '2023-01-01'\n      value: 0.1993\n    - datetime: '2024-01-01'\n      value: 0.1861\n    - datetime: '2025-01-01'\n      value: 0.2306\n  unknown:\n    source: assumes 50% coal and 50% natural gas from Battle River dual fuel power\n      plant\n    value: 0\nisRenewable:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.1577\n    - datetime: '2022-01-01'\n      value: 0.1596\n    - datetime: '2023-01-01'\n      value: 0.1992\n    - datetime: '2024-01-01'\n      value: 0.186\n    - datetime: '2025-01-01'\n      value: 0.2306\n  unknown:\n    source: assumes 50% coal and 50% natural gas from Battle River dual fuel power\n      plant\n    value: 0\nparsers:\n  gridAlerts: CA_AB.fetch_grid_alerts\n  price: CA_AB.fetch_price\n  production: CA_AB.fetch_production\n  productionPerModeForecast: CA_AB.fetch_wind_solar_forecasts\nregion: Americas\nsources:\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: America/Edmonton\nzone_name: Alberta\n"
  },
  {
    "path": "config/zones/CA-BC.yaml",
    "content": "bounding_box:\n  - - -139.0598203531421\n    - 48.32022750905118\n  - - -114.06534065340647\n    - 59.99976766669326\ncenter_point:\n  - -126.34762066188117\n  - 54.3370290002141\ncentroid:\n  - -127.28531431760742\n  - 52.721015734390924\ncapacity:\n  biomass: 838\n  gas: 507\n  hydro: 15910\n  solar: 1\n  wind: 704\ncontributors:\n  - daveachuk\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nemissionFactors:\n  direct:\n    unknown:\n      - datetime: '2019-01-01'\n        source: assumes 87% hydro, 5% biomass, 4% gas, 2% wind and 2% from various sources\n        value: 28.6\n  lifecycle:\n    unknown:\n      - datetime: '2019-01-01'\n        source: assumes 87% hydro, 5% biomass, 4% gas, 2% wind and 2% from various sources\n        value: 56\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.618280213356176e-05\n        biomass: 0.0005565384532473826\n        coal: 0.007331006468692466\n        gas: 0.023878577074405886\n        geothermal: 0.00013007675846959645\n        hydro: 0.06755360050596161\n        hydro discharge: 4.749450337088534e-10\n        nuclear: 0.009321481869692404\n        oil: 0.0002622337761868377\n        solar: 0.002537145921281953\n        unknown: 0.8682911931354651\n        wind: 0.020121937824903843\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 5.145101223398466e-05\n        biomass: 0.0010076535472723026\n        coal: 0.006493454703211018\n        gas: 0.03949552600524888\n        geothermal: 0.00015904815442854389\n        hydro: 0.08964769920069912\n        hydro discharge: 4.267365170239728e-09\n        nuclear: 0.014721031478377073\n        oil: 0.0001861432815573179\n        solar: 0.004466797839768633\n        unknown: 0.813708734346893\n        wind: 0.03006242547855752\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisLowCarbon:\n  unknown:\n    - datetime: '2019-01-01'\n      source: assumes 87% hydro, 5% biomass, 4% gas, 2% wind and 2% from various sources\n      value: 0.94\nisRenewable:\n  unknown:\n    - datetime: '2019-01-01'\n      source: assumes 87% hydro, 5% biomass, 4% gas, 2% wind and 2% from various sources\n      value: 0.94\nparsers:\n  consumption: CA_BC.fetch_consumption\nregion: Americas\ntimezone: America/Vancouver\nzone_name: British Columbia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/CA-MB.yaml",
    "content": "_comment: Coal capacity is 0MW after decomissioning of Selkirk in April 2021 (not reflected in latest report from March 2021)\nbounding_box:\n  - - -102.0016200162001\n    - 48.99852661272915\n  - - -88.94788947889474\n    - 59.99976766669326\ncenter_point:\n  - -95.7667821709945\n  - 54.50824290829774\ncentroid:\n  - -96.60629810723367\n  - 53.658709771078414\ncapacity:\n  coal: 0\n  gas: 237\n  hydro: 5234\n  oil: 13\n  wind: 258\ncontributors:\n  - felixvanoost\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nfallbackZoneMixes:\n  _source: Statistics Canada - average production in 2020\n  _url: https://docs.google.com/spreadsheets/d/1gobOiDRBsxKEKQPG2x5o2Qx17bQLXTSJLtF1JeasKWI/edit?usp=sharing\n  powerOriginRatios:\n    value:\n      gas: 0.003\n      hydro: 0.9715\n      wind: 0.0254\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: America/Winnipeg\nzone_name: Manitoba\n"
  },
  {
    "path": "config/zones/CA-NB.yaml",
    "content": "_comment: gas capacity includes an 88 MW cogeneration plant\nbounding_box:\n  - - -68.9800347396186\n    - 45.06069397344126\n  - - -63.77283772837724\n    - 48.074554419651506\ncenter_point:\n  - -66.41656952767849\n  - 46.586513047068514\ncentroid:\n  - -66.26706035317449\n  - 46.714594779409914\ncapacity:\n  biomass: 38\n  coal: 467\n  gas: 378\n  hydro: 950\n  nuclear: 660\n  oil: 1497\n  wind: 294\ncontributors:\n  - jarek\n  - VIKTORVAV99\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nemissionFactors:\n  direct:\n    unknown:\n      - datetime: '2019-01-01'\n        source: Government of Canada 2019; assumes 37.54% nuclear, 22.41% hydro, 14.53% gas, 13.71% coal, 6.65% wind, 3.78% biomass and 1.38% oil\n        value: 163.5\n  lifecycle:\n    unknown:\n      - datetime: '2019-01-01'\n        source: Government of Canada 2019; assumes 37.54% nuclear, 22.41% hydro, 14.53% gas, 13.71% coal, 6.65% wind, 3.78% biomass and 1.38% oil\n        value: 211.9\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005530268636963214\n        coal: 0.001713895849437082\n        gas: 0.0006730211889342283\n        geothermal: 0.0\n        hydro: 0.20750116625327938\n        hydro discharge: 0.0\n        nuclear: 0.0005793784613095666\n        oil: 1.9392144717153346e-09\n        solar: 1.4901570405484536e-05\n        unknown: 0.7720923622151821\n        wind: 0.01189493924479198\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 1.6347256314479893e-07\n        biomass: 0.008029728053459943\n        coal: 0.001204438804676524\n        gas: 0.0005271049886902429\n        geothermal: 0.0\n        hydro: 0.301409587898869\n        hydro discharge: 0.0\n        nuclear: 0.0005429704311344012\n        oil: 9.875955224574884e-07\n        solar: 1.9659726672940296e-05\n        unknown: 0.6708692854874592\n        wind: 0.017396149746207124\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 6.616189899234054e-07\n        biomass: 0.007883541644645579\n        coal: 0.0002532125807051915\n        gas: 0.0015693514764664428\n        geothermal: 0.0\n        hydro: 0.29384029091930586\n        hydro discharge: 0.0\n        nuclear: 0.002193113180821672\n        oil: 2.251258092114502e-06\n        solar: 3.0576778946133974e-05\n        unknown: 0.6776800202110911\n        wind: 0.016547068007254848\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 1.3041927942996742e-06\n        biomass: 0.009021079597292724\n        coal: 1.633322599965958e-05\n        gas: 0.002015920768121412\n        geothermal: 0.0\n        hydro: 0.33597834659684067\n        hydro discharge: 0.0\n        nuclear: 0.0024392712419177586\n        oil: 5.398833940987407e-06\n        solar: 4.2655109467882666e-05\n        unknown: 0.6316322895956799\n        wind: 0.018847240027643705\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 4.460835201369854e-06\n        biomass: 0.008392110379617923\n        coal: 0.00033121171831329603\n        gas: 0.0035864387785671204\n        geothermal: 0.0\n        hydro: 0.3396917702674108\n        hydro discharge: 0.0\n        nuclear: 0.0025868050076299494\n        oil: 1.1132318553339422e-05\n        solar: 3.892110485525692e-05\n        unknown: 0.6273568951287863\n        wind: 0.018000121017276594\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 6.435763009497752e-06\n        biomass: 0.008765978528191078\n        coal: 1.1233295281011421e-05\n        gas: 0.005718185810962226\n        geothermal: 0.0\n        hydro: 0.34493085834450116\n        hydro discharge: 0.0\n        nuclear: 0.003979069650772355\n        oil: 1.6006726078652008e-05\n        solar: 0.00016527585708464682\n        unknown: 0.61760241771525\n        wind: 0.01880444591988609\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.1165379044551805e-06\n        biomass: 0.007504199450386213\n        coal: 0.0005450657509586944\n        gas: 0.0031435187569135953\n        geothermal: 0.0\n        hydro: 0.2735812016097578\n        hydro discharge: 0.0\n        nuclear: 0.0034150291387916422\n        oil: 7.317933211830065e-06\n        solar: 6.243582387566049e-05\n        unknown: 0.6971368958031647\n        wind: 0.01460218239753163\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.7493282304922164e-05\n        biomass: 0.011303409601034601\n        coal: 0.00037906967106245837\n        gas: 0.030507631998615455\n        geothermal: 0.0\n        hydro: 0.3236341402248666\n        hydro discharge: 0.0\n        nuclear: 0.016788056704519043\n        oil: 2.9553917071404764e-05\n        solar: 0.0008089179786866909\n        unknown: 0.5950624478417121\n        wind: 0.02144891669855655\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisLowCarbon:\n  unknown:\n    - _comment: Sum of low carbon sources\n      datetime: '2019-01-01'\n      value: 0.7038\nisRenewable:\n  unknown:\n    - _comment: Sum of renewable sources\n      datetime: '2019-01-01'\n      value: 0.3284\nregion: Americas\nsources:\n  Government of Canada 2019:\n    link: https://open.canada.ca/data/en/dataset/5a6abd9d-d343-41ef-a525-7a1efb686300/resource/0c58139d-1811-466a-97ba-4c84b3fd83a2\ntimezone: America/Moncton\nzone_name: New Brunswick\n"
  },
  {
    "path": "config/zones/CA-NL.yaml",
    "content": "bounding_box:\n  - - -67.8084780847808\n    - 46.617712095699915\n  - - -52.62712627126267\n    - 60.30458831011339\ncenter_point:\n  - -60.59116752371763\n  - 52.78795122632599\ncentroid:\n  - -59.98706357750112\n  - 53.06951940566813\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: America/St_Johns\nzone_name: Newfoundland and Labrador\n"
  },
  {
    "path": "config/zones/CA-NS.yaml",
    "content": "_comment: http://www.nspower.ca/en/home/about-us/todayspower.aspx HTML source says available capacity is 2453 MW and wind capacity 567 MW\nbounding_box:\n  - - -66.21006210062096\n    - 43.470760946024555\n  - - -59.809198091980875\n    - 47.03415720009079\ncenter_point:\n  - -64.71289667710148\n  - 44.77812457106531\ncentroid:\n  - -62.871132159597394\n  - 45.31134730917251\ncapacity:\n  biomass: 60\n  coal: 1252\n  gas: 500\n  hydro: 418\n  oil: 300\n  wind: 600\ncontributors:\n  - jarek\n  - corradio\n  - lav-julien\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.020285335769138137\n        coal: 0.540864552113717\n        gas: 0.18672689876171963\n        geothermal: 0.0\n        hydro: 0.07300251061007185\n        hydro discharge: 0.0\n        nuclear: 1.6117048560466685e-05\n        oil: 0.0\n        solar: 1.0413504997574802e-06\n        unknown: 0.03468519735550474\n        wind: 0.1444179839511647\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 1.7506712672907034e-08\n        biomass: 0.02556150404025436\n        coal: 0.5294280541079053\n        gas: 0.15340801034397852\n        geothermal: 0.0\n        hydro: 0.08740443519853001\n        hydro discharge: 0.0\n        nuclear: 3.948975710925584e-05\n        oil: 2.0469387125245142e-07\n        solar: 1.1554430364118645e-06\n        unknown: 0.03703172576974611\n        wind: 0.16712522268504854\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 2.7685697250783867e-08\n        biomass: 0.012621785713851313\n        coal: 0.5255563542838196\n        gas: 0.12994597806175384\n        geothermal: 0.0\n        hydro: 0.10567596125788299\n        hydro discharge: 0.0\n        nuclear: 0.00019934440305824404\n        oil: 1.1443421530323998e-07\n        solar: 2.9586781795337695e-06\n        unknown: 0.05629213404361076\n        wind: 0.1697051808608871\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 6.045213280580344e-08\n        biomass: 0.026186821132183152\n        coal: 0.5194228002551721\n        gas: 0.17446986675935836\n        geothermal: 0.0\n        hydro: 0.06156233622478202\n        hydro discharge: 0.0\n        nuclear: 0.00019428408701793138\n        oil: 3.9293886323772237e-07\n        solar: 3.1737369723046804e-06\n        unknown: 0.03514963872097663\n        wind: 0.18301042620050328\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: America/Halifax\nzone_name: Nova Scotia\n"
  },
  {
    "path": "config/zones/CA-NT.yaml",
    "content": "bounding_box:\n  - - -136.44316443164425\n    - 59.99976766669326\n  - - -101.99801998019974\n    - 78.7669879381088\ncenter_point:\n  - -119.96830000283796\n  - 67.39550142373062\ncentroid:\n  - -119.85507656463537\n  - 70.03469908006356\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: America/Yellowknife\nzone_name: Northwest Territories\n"
  },
  {
    "path": "config/zones/CA-NU.yaml",
    "content": "bounding_box:\n  - - -120.68220682206815\n    - 51.91987399181053\n  - - -61.08721087210867\n    - 83.11604866746916\ncenter_point:\n  - -94.04245254083447\n  - 71.2165976625509\ncentroid:\n  - -86.71580380929173\n  - 72.22242724036938\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: America/Rankin_Inlet\nzone_name: Nunavut\n"
  },
  {
    "path": "config/zones/CA-ON.yaml",
    "content": "bounding_box:\n  - - -95.15435154351538\n    - 41.91374282376589\n  - - -74.34741210489506\n    - 56.8528165170179\ncenter_point:\n  - -85.15279214672884\n  - 49.545743876747565\ncentroid:\n  - -83.10781446353951\n  - 47.32136632232322\ncapacity:\n  biomass:\n    - datetime: '2022-12-01'\n      source: ieso.ca\n      value: 296.0\n  gas:\n    - datetime: '2023-12-01'\n      source: ieso.ca\n      value: 10470.0\n    - datetime: '2022-12-01'\n      source: ieso.ca\n      value: 10482.0\n  hydro:\n    - datetime: '2023-12-01'\n      source: ieso.ca\n      value: 8922.0\n    - datetime: '2022-12-01'\n      source: ieso.ca\n      value: 8868.0\n  nuclear:\n    - datetime: '2025-03-01'\n      source: ieso.ca\n      value: 12184.0\n    - datetime: '2023-12-01'\n      source: ieso.ca\n      value: 13144.0\n    - datetime: '2022-12-01'\n      source: ieso.ca\n      value: 13089.0\n  solar:\n    - datetime: '2022-12-01'\n      source: ieso.ca\n      value: 478.0\n  wind:\n    - datetime: '2022-12-01'\n      source: ieso.ca\n      value: 4883.0\ncontributors:\n  - corradio\n  - jarek\n  - scriptator\n  - felixvanoost\n  - misterclean\n  - christopheradlam\n  - alejandranavcas\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nemissionFactors:\n  direct: {}\n  lifecycle:\n    gas:\n      datetime: '2008-01-01'\n      source: 'Mallia, E., Lewis, G. \"Life cycle greenhouse gas emissions of electricity generation in the province of Ontario, Canada.\" Int J Life Cycle Assess 18, 377–391 (2013)'\n      value: 497\n    hydro:\n      datetime: '2008-01-01'\n      source: 'Mallia, E., Lewis, G. \"Life cycle greenhouse gas emissions of electricity generation in the province of Ontario, Canada.\" Int J Life Cycle Assess 18, 377–391 (2013)'\n      value: 22\n    nuclear:\n      datetime: '2008-01-01'\n      source: 'Mallia, E., Lewis, G. \"Life cycle greenhouse gas emissions of electricity generation in the province of Ontario, Canada.\" Int J Life Cycle Assess 18, 377–391 (2013)'\n      value: 4.8\n    wind:\n      datetime: '2008-01-01'\n      source: 'Mallia, E., Lewis, G. \"Life cycle greenhouse gas emissions of electricity generation in the province of Ontario, Canada.\" Int J Life Cycle Assess 18, 377–391 (2013)'\n      value: 10.69\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0021372333899431534\n        coal: 4.162119708056519e-05\n        gas: 0.07945883633135135\n        geothermal: 0.0\n        hydro: 0.24429247456773798\n        hydro discharge: 0.0\n        nuclear: 0.5908084439161816\n        oil: 0.0\n        solar: 0.0045278627754536315\n        unknown: 0.0\n        wind: 0.07873335574334984\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002137235334713046\n        coal: 4.162123495366381e-05\n        gas: 0.07945890863471013\n        geothermal: 0.0\n        hydro: 0.24429269686103158\n        hydro discharge: 0.0\n        nuclear: 0.5908089815207686\n        oil: 0.0\n        solar: 0.004526957006340299\n        unknown: 0.0\n        wind: 0.07873342738655946\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002459832315783152\n        coal: 1.3375148833322876e-10\n        gas: 0.10006964230007674\n        geothermal: 0.0\n        hydro: 0.2583702565830651\n        hydro discharge: 0.0\n        nuclear: 0.5538348354875826\n        oil: 0.0\n        solar: 0.00436901149286775\n        unknown: 2.7212409058837056e-06\n        wind: 0.08089351780830988\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002476631734079668\n        coal: 1.0521662263768532e-05\n        gas: 0.06816561009322376\n        geothermal: 0.0\n        hydro: 0.2548880535653494\n        hydro discharge: 0.0\n        nuclear: 0.6087205713429724\n        oil: 1.9450541311269757e-09\n        solar: 0.003936349186737902\n        unknown: 3.4798459186699463e-06\n        wind: 0.0617986786171168\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0028501906395708237\n        coal: 7.35834170111514e-07\n        gas: 0.06614898574154017\n        geothermal: 0.0\n        hydro: 0.264261962047098\n        hydro discharge: 0.0\n        nuclear: 0.5886870042892822\n        oil: 9.672238838675107e-10\n        solar: 0.004146633055302389\n        unknown: 5.058134501603758e-06\n        wind: 0.07389934990455033\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 4.496578197745171e-10\n        biomass: 0.0033046403126238432\n        coal: 3.48344666971421e-05\n        gas: 0.08659790707328359\n        geothermal: 0.0\n        hydro: 0.26842689482973536\n        hydro discharge: 7.494296996241953e-10\n        nuclear: 0.5542154990356271\n        oil: 1.2980122397491062e-07\n        solar: 0.004733710420068191\n        unknown: 2.8681424034317576e-05\n        wind: 0.08265756166898006\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0027257513138586684\n        coal: 2.8589917069232768e-06\n        gas: 0.06833893025387641\n        geothermal: 0.0\n        hydro: 0.2664809340328186\n        hydro discharge: 0.0\n        nuclear: 0.5787284409185134\n        oil: 2.3921143692946886e-08\n        solar: 0.00465524812016662\n        unknown: 5.152478521622756e-06\n        wind: 0.07906248029670293\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 3.081994678893773e-09\n        biomass: 0.002585880124966187\n        coal: 5.6019656138435604e-05\n        gas: 0.10540978534803117\n        geothermal: 0.0\n        hydro: 0.28246599866842315\n        hydro discharge: 0.0\n        nuclear: 0.5124467112030342\n        oil: 1.5674144366945477e-07\n        solar: 0.004603778936893261\n        unknown: 1.659668810749434e-05\n        wind: 0.09241495192150417\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 8.982097113224646e-09\n        biomass: 0.002386047494296383\n        coal: 0.00014677269411611562\n        gas: 0.13354659822967552\n        geothermal: 0.0\n        hydro: 0.2593695004282812\n        hydro discharge: 6.626137214673917e-10\n        nuclear: 0.5194296872390722\n        oil: 2.2219646793206538e-07\n        solar: 0.0045502155445145505\n        unknown: 2.4736474578580185e-05\n        wind: 0.0805461642603161\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.366136489909841e-08\n        biomass: 0.001981142875266852\n        coal: 0.00016639332828275374\n        gas: 0.163839265205878\n        geothermal: 0.0\n        hydro: 0.24236891876341288\n        hydro discharge: 2.891294158539346e-10\n        nuclear: 0.5029395502555983\n        oil: 8.610274004130173e-07\n        solar: 0.004465978250457551\n        unknown: 1.999178117686635e-05\n        wind: 0.08421782955516063\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumptionForecast: CA_ON.fetch_consumption_forecast\n  gridAlerts: CA_ON.fetch_grid_alerts\n  price: CA_ON.fetch_price\n  production: CA_ON.fetch_production\n  productionCapacity: CA_ON.fetch_production_capacity\n  productionPerModeForecast: CA_ON.fetch_wind_solar_forecasts\nregion: Americas\nsources:\n  'Mallia, E., Lewis, G. \"Life cycle greenhouse gas emissions of electricity generation in the province of Ontario, Canada.\" Int J Life Cycle Assess 18, 377–391 (2013)':\n    link: https://doi.org/10.1007/s11367-012-0501-0\ntimezone: America/Toronto\nzone_name: Ontario\n"
  },
  {
    "path": "config/zones/CA-PE.yaml",
    "content": "bounding_box:\n  - - -64.41724417244167\n    - 45.97229373803572\n  - - -62.00522005220047\n    - 47.06707210524884\ncenter_point:\n  - -63.33363333633332\n  - 46.498932220564384\ncentroid:\n  - -63.39876126033983\n  - 46.44090831660987\ncan_have_zero_production: true\ncapacity:\n  oil: 179\n  wind: 203.6\ncontributors:\n  - reinvented\n  - jarek\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0022106317854175238\n        coal: 0.0005031572869314671\n        gas: 0.00021000555722424673\n        geothermal: 0.0\n        hydro: 0.0843367746741822\n        hydro discharge: 0.0\n        nuclear: 0.0002738997024751277\n        oil: 0.0018552251559191088\n        solar: 6.447698808099162e-06\n        unknown: 0.22103532958277614\n        wind: 0.6895009370018117\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 1.6681807965272372e-07\n        biomass: 0.004760821175209082\n        coal: 0.00034995096749548376\n        gas: 0.00025133479152797964\n        geothermal: 0.0\n        hydro: 0.18148160905406324\n        hydro discharge: 0.0\n        nuclear: 0.0003626291415490908\n        oil: 0.0020483458546094223\n        solar: 1.2551392313070932e-05\n        unknown: 0.38026408796699024\n        wind: 0.4304624840418489\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 3.08591967927551e-07\n        biomass: 0.004710662956200616\n        coal: 8.858559215486207e-05\n        gas: 0.0011667665333744148\n        geothermal: 0.0\n        hydro: 0.17646413445333659\n        hydro discharge: 0.0\n        nuclear: 0.0014549979972052996\n        oil: 0.0005881303303640504\n        solar: 1.957917549702036e-05\n        unknown: 0.3998078207407905\n        wind: 0.41569206702693706\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 7.105440326439718e-07\n        biomass: 0.005500472676259493\n        coal: 9.658135554827322e-06\n        gas: 0.0016733706715450338\n        geothermal: 0.0\n        hydro: 0.20563662080784775\n        hydro discharge: 0.0\n        nuclear: 0.0016464357894186966\n        oil: 0.000418984131249062\n        solar: 2.9105988892749365e-05\n        unknown: 0.36039665725875664\n        wind: 0.4246807074992199\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 2.7965282676613133e-06\n        biomass: 0.005266293457647479\n        coal: 0.00017605913365097175\n        gas: 0.0024708195132870764\n        geothermal: 0.0\n        hydro: 0.21342162562381062\n        hydro discharge: 0.0\n        nuclear: 0.0016673415835845977\n        oil: 0.0014217935440827036\n        solar: 2.3805848678505388e-05\n        unknown: 0.38890113218250516\n        wind: 0.3866441731504871\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 5.659010529033063e-06\n        biomass: 0.006308855780275703\n        coal: 7.428279628859561e-06\n        gas: 0.0054779884568642995\n        geothermal: 0.0\n        hydro: 0.23800779133099756\n        hydro discharge: 0.0\n        nuclear: 0.003232501030715214\n        oil: 0.00176701609797653\n        solar: 0.00015993662544349182\n        unknown: 0.40125195601976055\n        wind: 0.34377797822426\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.4864914644001877e-06\n        biomass: 0.005551607371055158\n        coal: 0.00033895558754374645\n        gas: 0.0025172755773953327\n        geothermal: 0.0\n        hydro: 0.2019658583114239\n        hydro discharge: 0.0\n        nuclear: 0.002466965836399\n        oil: 0.0020237959448749744\n        solar: 4.866927033641731e-05\n        unknown: 0.5001841235841762\n        wind: 0.2848988931146308\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.7331475954339115e-06\n        biomass: 0.0063224888910080445\n        coal: 0.000178760750564063\n        gas: 0.005037113457983096\n        geothermal: 0.0\n        hydro: 0.21603741272301671\n        hydro discharge: 0.0\n        nuclear: 0.005369557244284258\n        oil: 0.0007211107118926344\n        solar: 0.00014838992733089316\n        unknown: 0.45975793302739665\n        wind: 0.30642071370616963\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: America/Halifax\nzone_name: Prince Edward Island\n"
  },
  {
    "path": "config/zones/CA-QC.yaml",
    "content": "bounding_box:\n  - - -79.76419764197637\n    - 44.999157411624054\n  - - -57.10197101971015\n    - 62.58859651151488\ncenter_point:\n  - -68.61549014824053\n  - 53.78714851784416\ncentroid:\n  - -69.28398389860546\n  - 53.71669211936096\ncapacity:\n  biomass: 1313\n  coal: 0\n  gas: 411\n  geothermal: 0\n  hydro: 42180\n  nuclear: 0\n  oil: 131\n  solar: 10\n  unknown: 1056\n  wind: 3508\ncontributors:\n  - jarek\n  - pjakobsen\n  - madsnedergaard\n  - KabelWlan\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022388936631379783\n        coal: 2.740371767753686e-05\n        gas: 0.0002947885426978512\n        geothermal: 2.740371767753686e-05\n        hydro: 0.9270777310105662\n        hydro discharge: 0.0\n        nuclear: 2.740371767753686e-05\n        oil: 2.740371767753686e-05\n        solar: 5.461651970564599e-05\n        unknown: 0.00022848015095033308\n        wind: 0.04984522774554802\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02238893704134847\n        coal: 2.740371817933229e-05\n        gas: 0.00029478854809578836\n        geothermal: 2.740371817933229e-05\n        hydro: 0.9270777479864881\n        hydro discharge: 0.0\n        nuclear: 2.740371817933229e-05\n        oil: 2.740371817933229e-05\n        solar: 5.459818830598987e-05\n        unknown: 0.00022848015513408278\n        wind: 0.04984522865827482\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02443076956600232\n        coal: 1.2874403974838324e-07\n        gas: 0.0002846378530970333\n        geothermal: 0.0\n        hydro: 0.9231040320549312\n        hydro discharge: 0.0\n        nuclear: 0.0018954759399200352\n        oil: 0.0\n        solar: 6.105915105642755e-05\n        unknown: 0.00016411363269439096\n        wind: 0.05005977197661833\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02442897674331876\n        coal: 3.992671055140609e-09\n        gas: 0.0001059931723227474\n        geothermal: 0.0\n        hydro: 0.9234985109990761\n        hydro discharge: 0.0\n        nuclear: 0.0017167204688230129\n        oil: 0.0\n        solar: 5.832610995700351e-05\n        unknown: 0.00017049120643240136\n        wind: 0.05002096511644345\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.024300410237108026\n        coal: 1.8054089697842913e-08\n        gas: 0.00023054470741155474\n        geothermal: 0.0\n        hydro: 0.9196941264958512\n        hydro discharge: 0.0\n        nuclear: 0.005454264297190558\n        oil: 0.0\n        solar: 8.063993852782143e-05\n        unknown: 0.00015114276360587116\n        wind: 0.050088850124655505\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.024332243165268608\n        coal: 1.2396749377814362e-08\n        gas: 0.000248092296079214\n        geothermal: 0.0\n        hydro: 0.9200935480897664\n        hydro discharge: 0.0\n        nuclear: 0.004728968908878407\n        oil: 0.0\n        solar: 8.604119572616303e-05\n        unknown: 0.0001508850255333328\n        wind: 0.050360205808659485\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02205769289796263\n        coal: 6.028146282307014e-08\n        gas: 0.00012355340066362835\n        geothermal: 0.0\n        hydro: 0.9263032248119624\n        hydro discharge: 0.0\n        nuclear: 0.002230539776074155\n        oil: 3.914380702796763e-10\n        solar: 3.0210351468320533e-05\n        unknown: 0.0006936298262878674\n        wind: 0.04856108697652621\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 8.267310663574177e-10\n        biomass: 0.021798995343283813\n        coal: 7.614296462535112e-06\n        gas: 0.0009794054041972328\n        geothermal: 0.0\n        hydro: 0.9219761337901324\n        hydro discharge: 0.0\n        nuclear: 0.004834518970143405\n        oil: 2.028591354074514e-07\n        solar: 8.019580699540176e-05\n        unknown: 3.859852336747841e-06\n        wind: 0.05031906783852495\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 5.869055243530835e-08\n        biomass: 0.02526799058569206\n        coal: 8.529994597790124e-06\n        gas: 0.004193148855739979\n        geothermal: 0.0\n        hydro: 0.9114057120446205\n        hydro discharge: 0.0\n        nuclear: 0.009991866844892101\n        oil: 1.0750781365595656e-05\n        solar: 0.00010180017071002836\n        unknown: 9.3664438529186e-05\n        wind: 0.04892646872332542\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 8.81186045412411e-07\n        biomass: 0.026143706399581346\n        coal: 0.00019373133277293304\n        gas: 0.013027421479708692\n        geothermal: 0.0\n        hydro: 0.8814931073146764\n        hydro discharge: 0.0\n        nuclear: 0.02252557354092083\n        oil: 5.427325669396725e-06\n        solar: 0.00025375135244732786\n        unknown: 0.0003068364202573618\n        wind: 0.05604954949834813\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: CA_QC.fetch_consumption\n  production: CA_QC.fetch_production\nregion: Americas\ntimezone: America/Toronto\nzone_name: 'Québec'\n"
  },
  {
    "path": "config/zones/CA-SK.yaml",
    "content": "bounding_box:\n  - - -110.00090000900003\n    - 48.99330959841075\n  - - -101.36494821324045\n    - 59.99976766669326\ncenter_point:\n  - -105.69802620167891\n  - 54.50878687352764\ncentroid:\n  - -105.9129079695164\n  - 53.11509429162273\ncapacity:\n  coal:\n    - datetime: '2024-01-01'\n      source: saskpower.com\n      value: 1389\n  gas:\n    - datetime: '2024-01-01'\n      source: saskpower.com\n      value: 2065\n  hydro:\n    - datetime: '2024-01-01'\n      source: saskpower.com\n      value: 865\n  solar:\n    - datetime: '2024-01-01'\n      source: saskpower.com\n      value: 93\n  unknown:\n    - datetime: '2024-01-01'\n      source: saskpower.com\n      value: 324\n  wind:\n    - datetime: '2024-01-01'\n      source: saskpower.com\n      value: 617\ncontributors:\n  - VIKTORVAV99\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.12113381635304e-07\n        coal: 0.3299350351174241\n        gas: 0.4427646314050988\n        geothermal: 0.0\n        hydro: 0.09639463350847492\n        hydro discharge: 0.0\n        nuclear: 0.0001096364444943272\n        oil: 2.3504198565977423e-06\n        solar: 0.0009949602326632593\n        unknown: 0.049320707377811336\n        wind: 0.08047807507611988\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.5271751287998515e-06\n        coal: 0.32959006289674025\n        gas: 0.4428567823192703\n        geothermal: 0.0\n        hydro: 0.09625845739972061\n        hydro discharge: 7.660773156758724e-10\n        nuclear: 0.0001784297488646723\n        oil: 3.474926703905757e-06\n        solar: 0.0009975422140661274\n        unknown: 0.04933261320737793\n        wind: 0.08078152532603267\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.0203858670072456e-07\n        coal: 0.34195430934054694\n        gas: 0.43475453083670046\n        geothermal: 0.0\n        hydro: 0.10243812998419786\n        hydro discharge: 0.0\n        nuclear: 6.31012372437077e-05\n        oil: 2.395654536488891e-07\n        solar: 0.000928156169880838\n        unknown: 0.04246119053202256\n        wind: 0.07739923434373075\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.38394748664253e-08\n        coal: 0.34185384321282075\n        gas: 0.4348574940726849\n        geothermal: 0.0\n        hydro: 0.10244677977532239\n        hydro discharge: 0.0\n        nuclear: 4.5752084455301556e-05\n        oil: 8.426479673981035e-07\n        solar: 0.0009253319885938225\n        unknown: 0.04248760061826115\n        wind: 0.0773817254258598\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.939343096052956e-06\n        coal: 0.34187585452065444\n        gas: 0.43469669633946245\n        geothermal: 0.0\n        hydro: 0.10244456010017247\n        hydro discharge: 0.0\n        nuclear: 6.0592904917182344e-05\n        oil: 3.3987616076884004e-07\n        solar: 0.0009272290594114357\n        unknown: 0.04246177978440422\n        wind: 0.07752276934456576\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.0939456003390905e-05\n        coal: 0.35910342006309093\n        gas: 0.40256494175458046\n        geothermal: 0.0\n        hydro: 0.10892869875510756\n        hydro discharge: 0.0\n        nuclear: 6.712812744150888e-05\n        oil: 5.397240221545534e-07\n        solar: 0.0006862279194651874\n        unknown: 0.04279106778990215\n        wind: 0.08583658007391703\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.478428377924771e-05\n        coal: 0.33741486004814\n        gas: 0.43629787482846116\n        geothermal: 0.0\n        hydro: 0.10270311138854338\n        hydro discharge: 0.0\n        nuclear: 4.505793415358722e-06\n        oil: 6.210614967977478e-07\n        solar: 0.0018108561873335643\n        unknown: 0.04231746351539971\n        wind: 0.07939582880493738\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.041288877977324e-05\n        coal: 0.3027115406265827\n        gas: 0.46038904358150873\n        geothermal: 3.8632848040167823e-10\n        hydro: 0.09194325035204644\n        hydro discharge: 0.0\n        nuclear: 1.4873646495464613e-07\n        oil: 2.4570491353546735e-07\n        solar: 0.002215298680144598\n        unknown: 0.0622375038985566\n        wind: 0.08044248483289065\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: CA_SK.fetch_consumption\nregion: Americas\ntimezone: America/Regina\nzone_name: Saskatchewan\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/CA-YT.yaml",
    "content": "bounding_box:\n  - - -141.00441004410038\n    - 59.999373418939406\n  - - -123.81783817838172\n    - 69.65385245783017\ncenter_point:\n  - -133.4063637454847\n  - 64.82479931598489\ncentroid:\n  - -132.4688653983901\n  - 64.31861763666498\ncapacity:\n  hydro: 116\ncontributors:\n  - jarek\n  - nessie2013\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.967476651899137\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.032517202004381136\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9169828307800725\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.08301560927090088\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.8462514526314489\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.15374461759092864\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.8776223943387789\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.12237477752865522\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9294644200962948\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.07053099734146236\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9199420366541917\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.08005333158071602\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9119476561348878\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.08804942933376388\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.8258501891508444\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.17414929934515255\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: YUKONENERGY.fetch_production\nregion: Americas\ntimezone: America/Whitehorse\nzone_name: Yukon\n"
  },
  {
    "path": "config/zones/CA.yaml",
    "content": "bounding_box:\n  - - -141.00441004410038\n    - 41.91374282376589\n  - - -52.62712627126267\n    - 83.11604866746916\ncenter_point:\n  - -97.1821186078896\n  - 62.57918935741333\ncentroid:\n  - -89.99438123746916\n  - 66.59224818736742\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2740.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2750.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2650.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2660.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 9980.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 9320.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 9170.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 8790.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 5310.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4880.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4260.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 3380.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 18780.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 19130.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 20240.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 22950.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 23060.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 23620.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 25640.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80660.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 81400.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 81210.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 82130.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 83140.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 83280.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 14030.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 13340.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 12510.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 11580.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3420.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3720.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 4010.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 4380.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 5260.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 5440.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 5880.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 6110.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2280.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 12250.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 12820.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 13220.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 13530.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 13720.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 15080.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 16990.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 18380.0\ncountry: CA\ncountry_name: Canada\ncurrency: CAD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 99.03\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 89.7\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 89.49\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 89.07\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 93.25\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 132.03\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 122.7\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 122.49\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 122.07\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 126.25\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.7917\n    - datetime: '2022-01-01'\n      value: 0.7982\n    - datetime: '2023-01-01'\n      value: 0.7958\n    - datetime: '2024-01-01'\n      value: 0.7862\n    - datetime: '2025-01-01'\n      value: 0.7715\nisRenewable:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.6593\n    - datetime: '2022-01-01'\n      value: 0.68\n    - datetime: '2023-01-01'\n      value: 0.6714\n    - datetime: '2024-01-01'\n      value: 0.6593\n    - datetime: '2025-01-01'\n      value: 0.6474\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nsubZoneNames:\n  - CA-AB\n  - CA-BC\n  - CA-MB\n  - CA-NB\n  - CA-NL\n  - CA-NS\n  - CA-NT\n  - CA-NU\n  - CA-ON\n  - CA-PE\n  - CA-QC\n  - CA-SK\n  - CA-YT\ntimezone: America/Toronto\nzone_name: Canada\n"
  },
  {
    "path": "config/zones/CD.yaml",
    "content": "bounding_box:\n  - - 12.209522095220962\n    - -13.43338574089752\n  - - 31.242912429124317\n    - 5.375335932673806\ncenter_point:\n  - 21.80707094504539\n  - -4.054229481119901\ncentroid:\n  - 23.859193896658155\n  - -3.729052238942586\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 480.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 530.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\ncountry: CD\ncountry_name: Democratic Republic of the Congo\ncurrency: CDF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Kinshasa\nzone_name: Democratic Republic of the Congo\n"
  },
  {
    "path": "config/zones/CF.yaml",
    "content": "bounding_box:\n  - - 14.398343983439844\n    - 2.23697127999619\n  - - 27.44127441274415\n    - 11.000922549033007\ncenter_point:\n  - 20.913020626512118\n  - 6.974944529184334\ncentroid:\n  - 20.85005850058502\n  - 6.346361411906864\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\ncountry: CF\ncountry_name: Central African Republic\ncurrency: XAF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Bangui\nzone_name: Central African Republic\n"
  },
  {
    "path": "config/zones/CG.yaml",
    "content": "bounding_box:\n  - - 11.115111151111535\n    - -5.020049765935497\n  - - 18.624786247862488\n    - 3.708124432277359\ncenter_point:\n  - 14.972389993853595\n  - -0.5365495548993182\ncentroid:\n  - 14.523959525309563\n  - -1.1205662640540501\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 480.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 530.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\ncountry: CG\ncountry_name: Congo\ncurrency: XAF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Brazzaville\nzone_name: Congo\n"
  },
  {
    "path": "config/zones/CH.yaml",
    "content": "bounding_box:\n  - - 5.959859598596012\n    - 45.82632328907397\n  - - 10.475965739913786\n    - 47.79406218439166\ncenter_point:\n  - 8.037048335634369\n  - 46.80812081210978\ncentroid:\n  - 8.414250452210126\n  - 46.6900871230039\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 14830.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 14980.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 15010.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 15030.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 15050.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 16010.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 16220.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3330.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2960.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1860.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2120.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2420.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2880.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 3520.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4530.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 6090.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 7790.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 690.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 680.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 690.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 700.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 710.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 740.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\ncontributors:\n  - corradio\n  - postronium\n  - Kikof2\n  - KabelWlan\n  - amv213\ncountry: CH\ncountry_name: Switzerland\ncurrency: EUR\ndisclaimer: Data for the electricity consumption and generation mix is based on estimates stemming from different data sources. As such, it may diverge from aggregated public statistics of the Swiss Federal Office for Energy.\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0.0\n    unknown:\n      - datetime: '2017-01-01'\n        source: SFOE, Electricity Maps\n        value: 159\n      - datetime: '2018-01-01'\n        source: SFOE, Electricity Maps\n        value: 205\n      - datetime: '2019-01-01'\n        source: SFOE, Electricity Maps\n        value: 172\n      - datetime: '2020-01-01'\n        source: SFOE, Electricity Maps\n        value: 141\n      - datetime: '2021-01-01'\n        source: SFOE, Electricity Maps\n        value: 109\n      - datetime: '2022-01-01'\n        source: SFOE, Electricity Maps\n        value: 87\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: EIA 2020/BEIS 2021; IPCC 2014\n      value: 650.0\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 29.5\n    unknown:\n      - datetime: '2017-01-01'\n        source: SFOE, Electricity Maps\n        value: 251\n      - datetime: '2018-01-01'\n        source: SFOE, Electricity Maps\n        value: 311\n      - datetime: '2019-01-01'\n        source: SFOE, Electricity Maps\n        value: 264\n      - datetime: '2020-01-01'\n        source: SFOE, Electricity Maps\n        value: 227\n      - datetime: '2021-01-01'\n        source: SFOE, Electricity Maps\n        value: 188\n      - datetime: '2022-01-01'\n        source: SFOE, Electricity Maps\n        value: 165\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.028258996118184904\n        coal: 0.09539032092563017\n        gas: 0.02103090989821941\n        geothermal: 4.9580671161570964e-05\n        hydro: 0.3182911788819652\n        hydro discharge: 0.05570550407157902\n        nuclear: 0.27770416963339906\n        oil: 0.0011857551666847163\n        solar: 0.04089181458053457\n        unknown: 0.11191955610537459\n        wind: 0.049572249968447626\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02777480301428617\n        coal: 0.08364912823281209\n        gas: 0.023381619732785536\n        geothermal: 6.35498572489115e-05\n        hydro: 0.3135254842176601\n        hydro discharge: 0.0668674272616311\n        nuclear: 0.3078104560859123\n        oil: 0.0008213052004292033\n        solar: 0.029939806239996963\n        unknown: 0.10622848205268991\n        wind: 0.03993793041326588\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08531555565235555\n        coal: 0.08833366492350408\n        gas: 0.02667407782794311\n        geothermal: 7.040684516958795e-05\n        hydro: 0.20860131535542373\n        hydro discharge: 0.08064349251238995\n        nuclear: 0.3029996449766441\n        oil: 0.001117177697938992\n        solar: 0.03859945131003369\n        unknown: 0.10920221777090545\n        wind: 0.05844297520015834\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08800922577228824\n        coal: 0.07110598536437034\n        gas: 0.027292171637717633\n        geothermal: 7.826763908081979e-05\n        hydro: 0.15992845092907865\n        hydro discharge: 0.08011017466625024\n        nuclear: 0.3672317912871093\n        oil: 0.0012687567594016787\n        solar: 0.04008316008093096\n        unknown: 0.11169485826088797\n        wind: 0.05319714563625801\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07991473764042553\n        coal: 0.041001052651868396\n        gas: 0.025403328287354168\n        geothermal: 6.881706279405633e-05\n        hydro: 0.20787402593634258\n        hydro discharge: 0.08163918107848789\n        nuclear: 0.3617973657377361\n        oil: 0.0013042137878489122\n        solar: 0.04145479156751964\n        unknown: 0.10488250536228841\n        wind: 0.05465998012736985\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08265554433642822\n        coal: 0.02746869627695358\n        gas: 0.027163471066880426\n        geothermal: 0.00014661398682770926\n        hydro: 0.24604288936501043\n        hydro discharge: 0.07523215104115842\n        nuclear: 0.34388386962063705\n        oil: 0.0010256872205831543\n        solar: 0.048371142154908404\n        unknown: 0.09254820011113556\n        wind: 0.05546172837298487\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08102887449541736\n        coal: 0.052523165092030595\n        gas: 0.03093095472202361\n        geothermal: 0.00014168882198741363\n        hydro: 0.26037681428756554\n        hydro discharge: 0.07547042106160176\n        nuclear: 0.31011690830649685\n        oil: 0.0011625299292721176\n        solar: 0.060526548639700195\n        unknown: 0.0705334785422939\n        wind: 0.05718861256480302\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07819040079430933\n        coal: 0.06631636060643921\n        gas: 0.03328367043560968\n        geothermal: 0.00014203757481075652\n        hydro: 0.23231693767871914\n        hydro discharge: 0.0681326518711739\n        nuclear: 0.33375441172719544\n        oil: 0.0013016120469685891\n        solar: 0.06621659376316164\n        unknown: 0.048320256747041684\n        wind: 0.07202505233748739\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.1439632715919773e-07\n        biomass: 0.08018138802051548\n        coal: 0.024544083736945336\n        gas: 0.019286237457646894\n        geothermal: 6.343276340977515e-05\n        hydro: 0.2784325427611253\n        hydro discharge: 0.07533025950296629\n        nuclear: 0.3409518180669206\n        oil: 0.0008588860398745921\n        solar: 0.06829200725347499\n        unknown: 0.055721774880120575\n        wind: 0.05633744244517972\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 8.853528412782097e-06\n        biomass: 0.07206560786169464\n        coal: 0.009567162876699183\n        gas: 0.014708195696197517\n        geothermal: 7.189474290884971e-05\n        hydro: 0.2604729666759766\n        hydro discharge: 0.10125034768236502\n        nuclear: 0.3676967117213611\n        oil: 0.0006816711537445452\n        solar: 0.07650531319955396\n        unknown: 0.05260567945226856\n        wind: 0.04436559558550984\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisLowCarbon:\n  hydro discharge:\n    _comment: Average share of electricity coming from low carbon sources in 2021\n    source: Electricity Maps, https://docs.google.com/spreadsheets/d/1FLHQ6e9Es08BIqX654BM3SEb_fuAk4k4O-6cmRXyw_E\n    value: 0.894\n  unknown:\n    - datetime: '2017-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.72\n    - datetime: '2018-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.64\n    - datetime: '2019-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.7\n    - datetime: '2020-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.75\n    - datetime: '2021-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.81\n    - datetime: '2022-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.85\nisRenewable:\n  hydro discharge:\n    _comment: Average share of electricity coming from renewable sources in 2021\n    source: Electricity Maps, https://docs.google.com/spreadsheets/d/1FLHQ6e9Es08BIqX654BM3SEb_fuAk4k4O-6cmRXyw_E\n    value: 0.5771\n  unknown:\n    - datetime: '2017-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.72\n    - datetime: '2018-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.64\n    - datetime: '2019-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.7\n    - datetime: '2020-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.75\n    - datetime: '2021-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.81\n    - datetime: '2022-01-01'\n      source: SFOE, Electricity Maps\n      value: 0.85\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  productionCapacity: EMBER.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  SFOE, Electricity Maps:\n    link: https://docs.google.com/spreadsheets/d/1FLHQ6e9Es08BIqX654BM3SEb_fuAk4k4O-6cmRXyw_E\ntimezone: Europe/Zurich\nzone_name: Switzerland\n"
  },
  {
    "path": "config/zones/CI.yaml",
    "content": "bounding_box:\n  - - -8.62028620286199\n    - 4.353542789941564\n  - - -2.507425074250705\n    - 10.720430313773178\ncenter_point:\n  - -5.451012429075497\n  - 7.473369509442403\ncentroid:\n  - -5.888939472413435\n  - 8.174822478541303\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 830.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1080.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 880.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\ncountry: CI\ncountry_name: Ivory Coast\ncurrency: XOF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Abidjan\nzone_name: Ivory Coast\n"
  },
  {
    "path": "config/zones/CL-CHP.yaml",
    "content": "bounding_box:\n  - - -109.43929439294386\n    - -27.20183367678961\n  - - -109.23049230492299\n    - -27.061587559159697\ncenter_point:\n  - -109.33489334893343\n  - -27.131710617974655\ncentroid:\n  - -109.3456934569345\n  - -27.11883087247803\ncapacity:\n  oil: 8.05\n  solar: 0.128\ncontributors:\n  - autipial\ncountry: CL\ncountry_name: Chile\ncurrency: CLP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: Pacific/Easter\nzone_name: Easter Island\n"
  },
  {
    "path": "config/zones/CL-SEA.yaml",
    "content": "bounding_box:\n  - - -75.70695706957065\n    - -49.2505268841786\n  - - -71.12411124111236\n    - -43.530488800844154\ncenter_point:\n  - -73.26709324643683\n  - -46.89071412072146\ncentroid:\n  - -73.87133873539291\n  - -46.406953569543056\ncapacity:\n  battery storage: 0\n  biomass: 0\n  coal: 0\n  gas: 0\n  geothermal: 0\n  hydro: 25.94\n  hydro storage: 0\n  nuclear: 0\n  oil: 39.09\n  solar: 2.96\n  wind: 1.8\ncountry: CL\ncountry_name: Chile\ncurrency: CLP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: America/Santiago\nzone_name: Sistema Eléctrico de Aysén\n"
  },
  {
    "path": "config/zones/CL-SEM.yaml",
    "content": "bounding_box:\n  - - -75.64575645756453\n    - -55.77769568530154\n  - - -67.06327063270628\n    - -48.63659234883947\ncenter_point:\n  - -71.00877094516686\n  - -52.42514372104352\ncentroid:\n  - -72.58542648152002\n  - -52.395433275809474\ncapacity:\n  battery storage: 0\n  biomass: 0\n  coal: 0\n  gas: 97.3\n  geothermal: 0\n  hydro: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 19.11\n  solar: 0\n  wind: 12.9\ncountry: CL\ncountry_name: Chile\ncurrency: CLP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: America/Punta_Arenas\nzone_name: Sistema Eléctrico de Magallanes\n"
  },
  {
    "path": "config/zones/CL-SEN.yaml",
    "content": "bounding_box:\n  - - -74.33894338943384\n    - -44.045678620709154\n  - - -67.01287012870124\n    - -17.506247483496928\ncenter_point:\n  - -70.73505081816626\n  - -30.813972238241195\ncentroid:\n  - -71.16228261519247\n  - -33.246601933796626\ncapacity:\n  geothermal:\n    - datetime: '2023-12-01'\n      source: coordinador.cl\n      value: 95.0\n    - datetime: '2022-12-01'\n      source: coordinador.cl\n      value: 82.0\n  hydro:\n    - datetime: '2023-12-01'\n      source: coordinador.cl\n      value: 7514.0\n    - datetime: '2022-12-01'\n      source: coordinador.cl\n      value: 7396.0\n  solar:\n    - datetime: '2023-12-01'\n      source: coordinador.cl\n      value: 9171.0\n    - datetime: '2022-12-01'\n      source: coordinador.cl\n      value: 8018.0\n  unknown:\n    - datetime: '2023-12-01'\n      source: coordinador.cl\n      value: 12786.0\n    - datetime: '2022-12-01'\n      source: coordinador.cl\n      value: 13394.0\n  wind:\n    - datetime: '2023-12-01'\n      source: coordinador.cl\n      value: 4710.0\n    - datetime: '2022-12-01'\n      source: coordinador.cl\n      value: 4328.0\ncontributors:\n  - systemcatch\n  - alixunderplatz\ncountry: CL\ncountry_name: Chile\ncurrency: CLP\ndisclaimer: Unknown production is the aggregation of thermal production, mainly gas, coal and oil.\nemissionFactors:\n  direct:\n    unknown:\n      - datetime: '2017-01-01'\n        source: Electricity Maps, CEN\n        value: 610.4720811\n      - datetime: '2018-01-01'\n        source: Electricity Maps, CEN\n        value: 613.650213\n      - datetime: '2019-01-01'\n        source: Electricity Maps, CEN\n        value: 606.6959655\n      - datetime: '2020-01-01'\n        source: Electricity Maps, CEN\n        value: 602.5343343\n      - datetime: '2021-01-01'\n        source: Electricity Maps, CEN\n        value: 597.8259335\n      - datetime: '2022-01-01'\n        source: Electricity Maps, CEN\n        value: 556.6130553\n  lifecycle:\n    unknown:\n      - datetime: '2017-01-01'\n        source: Electricity Maps, 2017 average.\n        value: 697.4098196\n      - datetime: '2018-01-01'\n        source: Electricity Maps, CEN\n        value: 699.7160413\n      - datetime: '2019-01-01'\n        source: Electricity Maps, CEN\n        value: 693.0054289\n      - datetime: '2020-01-01'\n        source: Electricity Maps, CEN\n        value: 689.9009504\n      - datetime: '2021-01-01'\n        source: Electricity Maps, CEN\n        value: 687.0474273\n      - datetime: '2022-01-01'\n        source: Electricity Maps, CEN\n        value: 652.4268241\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.448262358379444\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.01891962813678914\n        unknown: 0.49735955422528133\n        wind: 0.035458373089982724\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.26503013265934827\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.035089734743644935\n        unknown: 0.6686913768418871\n        wind: 0.03118871282212229\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0008578954256666087\n        hydro: 0.2931930541881064\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.052851238587104034\n        unknown: 0.604752633011456\n        wind: 0.048345132465986866\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0027813043301941746\n        hydro: 0.302597408851384\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.07118766684860892\n        unknown: 0.5704443605787091\n        wind: 0.05298920488017555\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0026054566084935233\n        hydro: 0.26916408782902307\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.08247789331119601\n        unknown: 0.5834769187538613\n        wind: 0.06227557875980308\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.934546753673279e-06\n        coal: 2.7076344211664603e-05\n        gas: 0.0016137062016760128\n        geothermal: 0.0031659846443504603\n        hydro: 0.26512458242866355\n        hydro discharge: 1.1643190962972349e-05\n        nuclear: 0.00017546675074942505\n        oil: 5.1943811551245226e-05\n        solar: 0.098065340962073\n        unknown: 0.5604871794586189\n        wind: 0.07127502187341829\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.9804704457057405e-06\n        coal: 0.00010583980954971474\n        gas: 0.00441075484810547\n        geothermal: 0.003966637314169833\n        hydro: 0.20202740341100126\n        hydro discharge: 7.148336013675965e-05\n        nuclear: 0.0005045722917857182\n        oil: 0.00014036853708807297\n        solar: 0.13108073410553409\n        unknown: 0.5690726139678652\n        wind: 0.08861448298031759\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.005614724723295743\n        hydro: 0.2436224822106043\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.17425348037145824\n        unknown: 0.4699217854763043\n        wind: 0.10658748614233722\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.6818070251046415e-06\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.005234727449613446\n        hydro: 0.28639830144967904\n        hydro discharge: 0.0\n        nuclear: 2.1452782238629655e-05\n        oil: 3.013131973455658e-08\n        solar: 0.19909377377558787\n        unknown: 0.3907161538240819\n        wind: 0.11853282856158798\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.003629047388238401\n        hydro: 0.3172697632119462\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.2168338706293335\n        unknown: 0.332478120180111\n        wind: 0.12978916493011286\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: CL.fetch_production\n  productionCapacity: CL_SEN.fetch_production_capacity\nregion: Americas\nsources:\n  Electricity Maps, CEN:\n    link: https://docs.google.com/spreadsheets/d/1-iXUGhAM_9Ft5ejlNVxaqaAwG8Octh3gSjU-dm4e96o/edit#gid=163148677 (average thermoelectric emission factors)\ntimezone: America/Santiago\nzone_name: 'Sistema Eléctrico Nacional'\nisRenewable:\n  unknown:\n    source: Unknown production is the aggregation of thermal production, mainly gas, coal and oil.\n    value: 0\nisLowCarbon:\n  unknown:\n    source: Unknown production is the aggregation of thermal production, mainly gas, coal and oil.\n    value: 0\n"
  },
  {
    "path": "config/zones/CM.yaml",
    "content": "bounding_box:\n  - - 8.508685086850903\n    - 1.734661205627823\n  - - 16.19836198361986\n    - 13.081716988154412\ncenter_point:\n  - 12.429262772287434\n  - 6.692974824163294\ncentroid:\n  - 13.090695192666242\n  - 6.768673955912862\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 730.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 810.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\ncountry: CM\ncountry_name: Cameroon\ncurrency: XAF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Douala\nzone_name: Cameroon\n"
  },
  {
    "path": "config/zones/CN.yaml",
    "content": "bounding_box:\n  - - 73.60093600936008\n    - 18.169216459321277\n  - - 134.77274772747725\n    - 53.56848141537853\ncenter_point:\n  - 104.16675282687595\n  - 35.92817723593884\ncentroid:\n  - 106.98483483977198\n  - 35.16965556919855\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 7590.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 8660.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10530.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 14190.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 16700.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 17460.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 18370.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 19140.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 954630.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 977460.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1019240.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1048340.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1073250.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1100720.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1146470.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1174540.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 74850.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 83360.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 93320.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 101930.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 111990.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 123310.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 133280.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 152990.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 314380.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 322270.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 327750.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 338670.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 354530.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 367710.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 370600.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 385000.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 35820.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 44660.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 48740.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 49890.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 53260.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 55530.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 56910.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 60810.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 130830.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 175260.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 204970.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 253860.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 306970.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 393030.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 609920.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 887930.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5610.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 6300.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 7760.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 9490.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 12530.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 13870.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 14900.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 15440.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 164370.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 184660.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 209580.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 281990.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 328970.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 365960.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 441890.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 521750.0\ncountry: CN\ncountry_name: China\ncurrency: CNY\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Shanghai\nzone_name: China\n"
  },
  {
    "path": "config/zones/CO.yaml",
    "content": "bounding_box:\n  - - -79.0225902259022\n    - -4.229086617449174\n  - - -66.87606876068756\n    - 12.464920287149383\ncenter_point:\n  - -73.04449225188162\n  - 4.39172329381876\ncentroid:\n  - -73.22878688086467\n  - 4.316577362474531\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 320.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 330.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 350.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 390.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1370.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1650.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3290.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3380.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 3480.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 3530.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3740.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4310.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 11730.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 11840.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 11930.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 11960.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 11950.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 13180.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 13220.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2090.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2180.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1490.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1470.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1480.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1500.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 480.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 720.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1390.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\ncontributors:\n  - lav-julien\n  - alixunderplatz\n  - consideRatio\ncountry: CO\ncountry_name: Colombia\ncurrency: COP\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007768660142712339\n        coal: 0.09861074221191997\n        gas: 0.17446448149539917\n        geothermal: 0.0\n        hydro: 0.6764704862348003\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.04165066098714061\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.001034600442696514\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00908021640996634\n        coal: 0.08525753742326023\n        gas: 0.14597857167711162\n        geothermal: 0.0\n        hydro: 0.715306697239968\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.043597553990719705\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0007790543394495929\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009520939099050342\n        coal: 0.04190857919142899\n        gas: 0.08068969665107571\n        geothermal: 0.0\n        hydro: 0.8661511569589018\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0016013672396665588\n        solar: 8.157177419504407e-05\n        unknown: 0.0\n        wind: 4.637926769715549e-05\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01062932720855705\n        coal: 0.05530748912249579\n        gas: 0.10237220269630473\n        geothermal: 0.0\n        hydro: 0.8272978231390834\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0035836732019085427\n        solar: 0.000175454789091397\n        unknown: 0.0\n        wind: 0.0006336856379579599\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010070052697681056\n        coal: 0.10443191767127226\n        gas: 0.08876437378623556\n        geothermal: 0.0\n        hydro: 0.7826446148247683\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.011279607849137785\n        solar: 0.0018982996152275197\n        unknown: 0.0\n        wind: 0.0009107535024432757\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010487180135500427\n        coal: 0.12469108072181362\n        gas: 0.10858689057473463\n        geothermal: 0.0\n        hydro: 0.7222346829749499\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.03108431118877373\n        solar: 0.002768397434056983\n        unknown: 0.0\n        wind: 0.00014709068965307716\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010716970177161202\n        coal: 0.05740259932284787\n        gas: 0.08618509701220496\n        geothermal: 0.0\n        hydro: 0.8182977760232482\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.022210990618612293\n        solar: 0.0043684241172256616\n        unknown: 0.0\n        wind: 0.0008177683123546229\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010051495028295464\n        coal: 0.04529124532547258\n        gas: 0.07960112922309949\n        geothermal: 0.0\n        hydro: 0.8365723219044147\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.020978458089397828\n        solar: 0.00653923921808492\n        unknown: 0.0\n        wind: 0.0009657303974362767\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010114920053532057\n        coal: 0.08657358730522631\n        gas: 0.09321990204297102\n        geothermal: 0.0\n        hydro: 0.7797911243497784\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.015353754895118149\n        solar: 0.012420257648186718\n        unknown: 0.0\n        wind: 0.0025262199681420757\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009813672672764041\n        coal: 0.0766285479693471\n        gas: 0.10553532461297077\n        geothermal: 0.0\n        hydro: 0.7772369527860702\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.025397043644766464\n        solar: 0.004379411289697945\n        unknown: 0.0\n        wind: 0.001009305470052309\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: CO.fetch_consumption\n  price: CO.fetch_price\n  production: CO.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Bogota\nzone_name: Colombia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/CR.yaml",
    "content": "bounding_box:\n  - - -85.90945909459089\n    - 8.034287836310384\n  - - -82.57222572225717\n    - 11.209860642644927\ncenter_point:\n  - -84.27575410391903\n  - 9.949824880295713\ncentroid:\n  - -84.05730980386721\n  - 9.674501408646611\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2330.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2370.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2340.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2330.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2380.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2330.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2370.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2350.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 570.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 470.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 430.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 520.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 410.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 390.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 410.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 400.0\ncontributors:\n  - corradio\n  - jarek\n  - mlucchini\n  - nessie2013\ncountry: CR\ncountry_name: Costa Rica\ncurrency: CRC\nemissionFactors:\n  direct:\n    unknown:\n      _comment: Source https://www.grupoice.com/wps/wcm/connect/579dfc1f-5156-41e0-807d-d6808f65d718/Fasciculo_Electricidad_2020_ingl%C3%A9s_compressed.pdf?MOD=AJPERES&CVID=m.pGzcp\n      source: assumes 58% thermal (coal, gas, or oil), 42% solar and biomass\n      value: 333.54639999999995\n  lifecycle:\n    unknown:\n      _comment: Source https://www.grupoice.com/wps/wcm/connect/579dfc1f-5156-41e0-807d-d6808f65d718/Fasciculo_Electricidad_2020_ingl%C3%A9s_compressed.pdf?MOD=AJPERES&CVID=m.pGzcp\n      source: assumes 58% thermal (coal, gas, or oil), 42% solar and biomass\n      value: 463.63399999999996\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006188442587248579\n        coal: 0.0005166394900425309\n        gas: 0.0005166394900425309\n        geothermal: 0.11393335865132376\n        hydro: 0.7082178988163217\n        hydro discharge: 0.0\n        nuclear: 0.0005166394900425309\n        oil: 0.006560635166729702\n        solar: 0.0008467147197919261\n        unknown: 0.025112547772634962\n        wind: 0.1375811585943997\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006188442628870984\n        coal: 0.0005166394935173596\n        gas: 0.0005166394935173596\n        geothermal: 0.11393335941762\n        hydro: 0.708217903579674\n        hydro discharge: 0.0\n        nuclear: 0.0005166394935173596\n        oil: 0.00656063521085541\n        solar: 0.0008467079062437136\n        unknown: 0.02511254794153766\n        wind: 0.13758115951974703\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0012598110066270646\n        coal: 0.0017549436029785199\n        gas: 1.8406064409674334e-05\n        geothermal: 0.08189742379049877\n        hydro: 0.7674063682963335\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.001022103505805035\n        solar: 0.0005758519739874207\n        unknown: 0.041367209249667344\n        wind: 0.10469758609848882\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00854019352452591\n        coal: 2.897682500054614e-05\n        gas: 4.356948372728054e-05\n        geothermal: 0.0851878959865998\n        hydro: 0.6850752183253423\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.01741455059419592\n        solar: 0.0012288164449912513\n        unknown: 0.03603412864450462\n        wind: 0.16644651601075142\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009343277523248917\n        coal: 0.00018093656817997462\n        gas: 3.287410701758992e-05\n        geothermal: 0.11297445707244907\n        hydro: 0.6763999183172299\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.014342935766570124\n        solar: 0.0015427561684265628\n        unknown: 0.037564426031690974\n        wind: 0.14761827552186485\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0058659150999690905\n        coal: 0.00206265892428819\n        gas: 0.00020106999713220909\n        geothermal: 0.10832150136871245\n        hydro: 0.7139805480313199\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0034069492809086686\n        solar: 0.0015078902428756734\n        unknown: 0.0449978432683965\n        wind: 0.11965547861671015\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005486808370422169\n        coal: 0.006316385285673479\n        gas: 0.004060311087933389\n        geothermal: 0.12172462184138333\n        hydro: 0.7239761056420817\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0013730421037180397\n        solar: 0.0019926909035153624\n        unknown: 0.016264994863525596\n        wind: 0.1188048824580526\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012212723079421695\n        coal: 0.004344881664261784\n        gas: 0.0011321637704887002\n        geothermal: 0.13722557740018232\n        hydro: 0.6731010755933975\n        hydro discharge: 0.0\n        nuclear: 1.2379082688877442e-07\n        oil: 0.021419744682335255\n        solar: 0.0019604939788497914\n        unknown: 0.008830369358692193\n        wind: 0.13977242104459114\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00547492786016505\n        coal: 0.0030550781532456923\n        gas: 0.003969615243305359\n        geothermal: 0.12279813283006503\n        hydro: 0.6815783559815741\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.06314074010917813\n        solar: 0.0022282346925185004\n        unknown: 0.002890182123800398\n        wind: 0.1148645695064716\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006855793489018667\n        coal: 0.0\n        gas: 0.0002036679285601743\n        geothermal: 0.11898027071322358\n        hydro: 0.6642496564974198\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.1089015737638526\n        solar: 0.0013911656652474905\n        unknown: 0.0\n        wind: 0.09941766316203218\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: CR.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Costa_Rica\nzone_name: Costa Rica\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nisRenewable:\n  unknown:\n    _comment: Source https://www.grupoice.com/wps/wcm/connect/579dfc1f-5156-41e0-807d-d6808f65d718/Fasciculo_Electricidad_2020_ingl%C3%A9s_compressed.pdf?MOD=AJPERES&CVID=m.pGzcp\n    source: assumes 58% thermal (coal, gas, or oil), 42% solar and biomass\n    value: 0.42\nisLowCarbon:\n  unknown:\n    _comment: Source https://www.grupoice.com/wps/wcm/connect/579dfc1f-5156-41e0-807d-d6808f65d718/Fasciculo_Electricidad_2020_ingl%C3%A9s_compressed.pdf?MOD=AJPERES&CVID=m.pGzcp\n    source: assumes 58% thermal (coal, gas, or oil), 42% solar and biomass\n    value: 0.42\n"
  },
  {
    "path": "config/zones/CU.yaml",
    "content": "bounding_box:\n  - - -84.94824948249477\n    - 19.85503203654619\n  - - -74.14094140941404\n    - 23.19374828583797\ncenter_point:\n  - -78.1620296443511\n  - 21.48604483075552\ncentroid:\n  - -79.67548246911036\n  - 21.690585607333905\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 440.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 460.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 480.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 440.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 580.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5300.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 5420.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 5340.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 5320.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 5400.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4900.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 5320.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\ncountry: CU\ncountry_name: Cuba\ncurrency: CUP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Havana\nzone_name: Cuba\n"
  },
  {
    "path": "config/zones/CV.yaml",
    "content": "bounding_box:\n  - - -25.31725317253168\n    - 14.816189381699914\n  - - -22.682026820268163\n    - 17.196080132909614\ncenter_point:\n  - -24.323643236432332\n  - 16.48196979926341\ncentroid:\n  - -23.90047536839001\n  - 16.028381590435295\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 170.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\ncountry: CV\ncountry_name: Cabo Verde\ncurrency: CVE\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Atlantic/Cape_Verde\nzone_name: Cabo Verde\n"
  },
  {
    "path": "config/zones/CW.yaml",
    "content": "bounding_box:\n  - - -69.15514614798195\n    - 12.037431473445437\n  - - -68.73200926588031\n    - 12.389546858796207\ncenter_point:\n  - -68.97807654009556\n  - 12.196062083734544\ncentroid:\n  - -68.99348330137373\n  - 12.201245365436082\ncapacity:\n  oil:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 165.0\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 204.2\n  solar:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 11.13\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 11.93\n    - datetime: '2020-01-01'\n      source: IRENA.org\n      value: 13.23\n    - datetime: '2023-01-01'\n      source: IRENA.org\n      value: 13.36\n  wind:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 46.5\ncontributors:\n  - VIKTORVAV99\ncountry: CW\ncountry_name: Curaçao\ncurrency: ANG\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: America/Curacao\nzone_name: Curaçao\n"
  },
  {
    "path": "config/zones/CY.yaml",
    "content": "bounding_box:\n  - - 32.27053022035746\n    - 34.5630798273339\n  - - 34.09197768705732\n    - 35.201370959568614\ncenter_point:\n  - 33.18125395370739\n  - 34.88222539345126\ncentroid:\n  - 33.244805194765405\n  - 34.98821550367324\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1850.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 420.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 580.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 720.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\ncontributors:\n  - ultibo\n  - veqtrus\n  - q--\n  - nessie2013\ncountry: CY\ncountry_name: Cyprus\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 419.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2018-01-01'\n        source: EU-ETS, CERA 2018 Report\n        value: 730.57\n      - datetime: '2019-01-01'\n        source: EU-ETS, CERA 2019 Report\n        value: 710.54\n      - datetime: '2020-01-01'\n        source: EU-ETS, CERA 2020 Report\n        value: 707.44\n      - datetime: '2021-01-01'\n        source: EU-ETS, TSOC 2021 Report\n        value: 709.61\n      - datetime: '2022-01-01'\n        source: EU-ETS, TSOC 2022 Report\n        value: 730.32\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1117.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1135.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2018-01-01'\n        source: EU-ETS, CERA 2018 Report; IPCC 2014\n        value: 974.57\n      - datetime: '2019-01-01'\n        source: EU-ETS, CERA 2019 Report; IPCC 2014\n        value: 954.54\n      - datetime: '2020-01-01'\n        source: EU-ETS, CERA 2020 Report; IPCC 2014\n        value: 951.44\n      - datetime: '2021-01-01'\n        source: EU-ETS, TSOC 2021 Report; IPCC 2014\n        value: 953.61\n      - datetime: '2022-01-01'\n        source: EU-ETS, TSOC 2022 Report; IPCC 2014\n        value: 974.32\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009083226904820607\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.916928635529501\n        solar: 0.031824945419796295\n        unknown: 0.0\n        wind: 0.04216186029944443\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009004369654995235\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9101788993041894\n        solar: 0.03722836757163676\n        unknown: 0.0\n        wind: 0.04358707042738254\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008855983537553565\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9021662111962987\n        solar: 0.04257233401971135\n        unknown: 0.0\n        wind: 0.04640435982698813\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01101074952325152\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8731852016127841\n        solar: 0.06673781579310638\n        unknown: 0.0\n        wind: 0.04906468139440815\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010382623151942843\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8545331952795239\n        solar: 0.08688020528988437\n        unknown: 0.0\n        wind: 0.048202850416375564\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010232590410633959\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8389530135594901\n        solar: 0.1081668883999263\n        unknown: 0.0\n        wind: 0.04264634130498484\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012824176962376947\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.795404124151831\n        solar: 0.15239095798362642\n        unknown: 0.0\n        wind: 0.039379560686909114\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.015283654072033765\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7659703419425117\n        solar: 0.18294657859249813\n        unknown: 0.0\n        wind: 0.035798118790591575\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  production: CY.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Asia\nsources:\n  EU-ETS, CERA 2018 Report:\n    link: https://tsoc.org.cy/files/reports/annual-reports/CERA_Annual_Report_2018_gr.pdf#page=128\n  EU-ETS, CERA 2019 Report:\n    link: https://tsoc.org.cy/files/reports/annual-reports/CERA_Annual_Report_2019_gr.pdf#page=143\n  EU-ETS, CERA 2020 Report:\n    link: https://tsoc.org.cy/files/reports/annual-reports/CERA_Annual_Report_2020_gr.pdf#page=164\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  EU-ETS, TSOC 2021 Report:\n    link: https://tsoc.org.cy/files/reports/annual-reports/TSOC_Annual_Report_2021.pdf#page=34\n  EU-ETS, TSOC 2022 Report:\n    link: https://tsoc.org.cy/files/reports/annual-reports/TSOC_Annual_Report_2022.pdf#page=32\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Asia/Nicosia\nzone_name: Cyprus\n"
  },
  {
    "path": "config/zones/CZ.yaml",
    "content": "bounding_box:\n  - - 12.076320763207661\n    - 48.55826041719142\n  - - 18.833588335883377\n    - 51.036895883875246\ncenter_point:\n  - 15.463725623630856\n  - 49.74484366663795\ncentroid:\n  - 15.5263756027391\n  - 49.77451103571735\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 450.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 500.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 510.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 9129.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 9742.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 9650.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 9350.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 8900.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 8450.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 8360.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 8400.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 8440.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1606.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1620.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1087.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1088.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1091.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1109.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1112.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1106.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1107.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1172.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4040.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2027.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 2040.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 2049.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 2061.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2054.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2053.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2083.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 3548.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 4415.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 400.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 410.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 460.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 277.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 308.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 316.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 339.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 342.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 366.0\ncontributors:\n  - corradio\n  - Frantisek12\ncountry: CZ\ncountry_name: Czechia\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1055.667306\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1055.67\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 989.37\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 989.81\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 419.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 364.25\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 370.68\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 446.17\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 490.53\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 515.37\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 434.09\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1061.99227\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1061.994964\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1049.37\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1049.81\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 484.25\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 490.68\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 456.87\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 501.23\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 526.07\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 444.79\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 34.33333333\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.030775967008316706\n        coal: 0.508990139588575\n        gas: 0.04682815190009607\n        geothermal: 6.969628377469148e-06\n        hydro: 0.02383877173283548\n        hydro discharge: 0.0151380310872164\n        nuclear: 0.2893962479735372\n        oil: 0.0013204246546895928\n        solar: 0.028287106244730117\n        unknown: 0.035394930638582046\n        wind: 0.020023226477726783\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.030123638979132294\n        coal: 0.512515033708344\n        gas: 0.06500299362507994\n        geothermal: 1.28289192997832e-05\n        hydro: 0.027924618338267728\n        hydro discharge: 0.013354781998049363\n        nuclear: 0.26492360356305455\n        oil: 0.001763408303967414\n        solar: 0.027958654790927358\n        unknown: 0.03741541915414262\n        wind: 0.019005099091007793\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.028982698823693653\n        coal: 0.4729186454471085\n        gas: 0.0620865018165055\n        geothermal: 1.6609424120172853e-05\n        hydro: 0.022196522661292576\n        hydro discharge: 0.013979944465067881\n        nuclear: 0.3004467463818309\n        oil: 0.0016924983915085608\n        solar: 0.029686299347863616\n        unknown: 0.042316958618973465\n        wind: 0.025676490287909116\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03131877339732009\n        coal: 0.45694775673566845\n        gas: 0.06275132331903704\n        geothermal: 1.635741338651803e-05\n        hydro: 0.022118134216377684\n        hydro discharge: 0.012894587231536582\n        nuclear: 0.3184937570891394\n        oil: 0.0012220762680767293\n        solar: 0.03164156109962311\n        unknown: 0.03812246421401176\n        wind: 0.024473166969749674\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.029465237819584832\n        coal: 0.41601577397793477\n        gas: 0.08569690274413569\n        geothermal: 1.9249299867692558e-05\n        hydro: 0.02461945036061207\n        hydro discharge: 0.014050555430513164\n        nuclear: 0.3290311975672596\n        oil: 0.001405608926766735\n        solar: 0.03260382312938912\n        unknown: 0.03809396162174881\n        wind: 0.02899819926171332\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03678497212399466\n        coal: 0.36252551813676925\n        gas: 0.09986678386479367\n        geothermal: 3.180282372942734e-05\n        hydro: 0.02860118815121928\n        hydro discharge: 0.016842133028581518\n        nuclear: 0.3386131281213028\n        oil: 0.002194122796379419\n        solar: 0.0361491119516833\n        unknown: 0.0387813916322862\n        wind: 0.03960980934535478\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0344784590706329\n        coal: 0.4002974658873109\n        gas: 0.10245321390762518\n        geothermal: 1.5513514222779675e-05\n        hydro: 0.03127671125222717\n        hydro discharge: 0.014163075894240179\n        nuclear: 0.3260349023506414\n        oil: 0.0015651452095072189\n        solar: 0.033447597696231415\n        unknown: 0.02815170501439487\n        wind: 0.02811619386600923\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03326886851519275\n        coal: 0.4360268426340633\n        gas: 0.06959199211720098\n        geothermal: 1.622787864006744e-05\n        hydro: 0.02631200545673555\n        hydro discharge: 0.01217295581582199\n        nuclear: 0.32275877102026423\n        oil: 0.001733662526636254\n        solar: 0.03770926258795098\n        unknown: 0.026759679181690307\n        wind: 0.033649657920964034\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 3.0055421775475295e-10\n        biomass: 0.029372440116892762\n        coal: 0.4365360121230238\n        gas: 0.038428657304146206\n        geothermal: 1.7219652797823063e-05\n        hydro: 0.029400017769697064\n        hydro discharge: 0.014187757124800141\n        nuclear: 0.3656614130080439\n        oil: 0.0012275872536481262\n        solar: 0.047435587056061365\n        unknown: 0.0008898508725064969\n        wind: 0.03684340151474339\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.5493877619002805e-07\n        biomass: 0.03273208835561961\n        coal: 0.3934275068882662\n        gas: 0.04250307780752817\n        geothermal: 2.834670431769579e-05\n        hydro: 0.034006717404404495\n        hydro discharge: 0.013533060189097681\n        nuclear: 0.36208934334737264\n        oil: 0.0012770225059991636\n        solar: 0.0697941813138505\n        unknown: 0.0021201960884986294\n        wind: 0.048488262214254355\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.5331\n    - datetime: '2021-01-01'\n      value: 0.4839\n    - datetime: '2022-01-01'\n      value: 0.4938\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.5197\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1529\n    - datetime: '2021-01-01'\n      value: 0.1677\n    - datetime: '2022-01-01'\n      value: 0.1418\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.1187\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: CZ.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Prague\nzone_name: Czechia\n"
  },
  {
    "path": "config/zones/DE.yaml",
    "content": "_comment: Hydro capacities from Fraunhofer include capacities in AT, CH, LU which\n  are directly connected to the German grid. Fraunhofer has no values for geothermal\n  and unknown - these are from BNetz\nbounding_box:\n  - - 5.920259202592064\n    - 47.301769689854\n  - - 15.021150211502146\n    - 54.90654386419456\ncenter_point:\n  - 10.407266584569143\n  - 51.055795801568294\ncentroid:\n  - 10.469326508295726\n  - 51.40418959202085\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 456.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 729.0\n    - datetime: '2019-01-01'\n      source: Fraunhofer ISE\n      value: 1017.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 1569.0\n    - datetime: '2021-01-01'\n      source: Fraunhofer ISE\n      value: 2415.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 4132.0\n    - datetime: '2023-01-01'\n      source: Fraunhofer ISE\n      value: 8232.0\n    - datetime: '2024-01-01'\n      source: Fraunhofer ISE\n      value: 12340.0\n    - datetime: '2025-01-01'\n      source: Fraunhofer ISE\n      value: 12852.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 7566.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 7993.0\n    - datetime: '2019-01-01'\n      source: Fraunhofer ISE\n      value: 8337.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 8851.0\n    - datetime: '2021-01-01'\n      source: Fraunhofer ISE\n      value: 8971.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 9027.0\n    - datetime: '2023-01-01'\n      source: Fraunhofer ISE\n      value: 9066.0\n    - datetime: '2024-01-01'\n      source: Fraunhofer ISE\n      value: 9168.0\n    - datetime: '2025-01-01'\n      source: Fraunhofer ISE\n      value: 9174.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 44901.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 44719.0\n    - datetime: '2019-01-01'\n      source: Fraunhofer ISE\n      value: 43573.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 44599.0\n    - datetime: '2021-01-01'\n      source: Fraunhofer ISE\n      value: 38917.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 37246.0\n    - datetime: '2023-01-01'\n      source: Fraunhofer ISE\n      value: 37028.0\n    - datetime: '2024-01-01'\n      source: Fraunhofer ISE\n      value: 31193.0\n    - datetime: '2024-11-11'\n      source: Fraunhofer ISE\n      value: 32600.0\n    - datetime: '2025-01-01'\n      source: Fraunhofer ISE\n      value: 31193.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 29762.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 30130.0\n    - datetime: '2019-01-01'\n      source: Fraunhofer ISE\n      value: 30072.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 32536.0\n    - datetime: '2021-01-01'\n      source: Fraunhofer ISE\n      value: 32128.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 35112.0\n    - datetime: '2023-01-01'\n      source: Fraunhofer ISE\n      value: 36639.0\n    - datetime: '2024-01-01'\n      source: Fraunhofer ISE\n      value: 36664.0\n    - datetime: '2024-11-11'\n      source: Fraunhofer ISE\n      value: 36300.0\n    - datetime: '2025-01-01'\n      source: Fraunhofer ISE\n      value: 36664.0\n  geothermal:\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 56\n  hydro:\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 6186.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 9488.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 9814.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 9688.0\n    - datetime: '2021-01-01'\n      source: Fraunhofer ISE\n      value: 9770.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 9970.0\n    - datetime: '2024-01-01'\n      source: Fraunhofer ISE\n      value: 9870.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 10800.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 9516.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 8114.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 4056.0\n    - datetime: '2023-04-15'\n      source: Fraunhofer ISE\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 4416.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 4375.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 4857.0\n    - datetime: '2021-01-01'\n      source: Fraunhofer ISE\n      value: 5094.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 5102.0\n    - datetime: '2023-01-01'\n      source: Fraunhofer ISE\n      value: 5037.0\n    - datetime: '2024-01-01'\n      source: Fraunhofer ISE\n      value: 4442.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 42293.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 45207.0\n    - datetime: '2019-01-01'\n      source: Fraunhofer ISE\n      value: 48864.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 54449.0\n    - datetime: '2021-01-01'\n      source: Fraunhofer ISE\n      value: 60162.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 67720.0\n    - datetime: '2023-01-01'\n      source: Fraunhofer ISE\n      value: 83052.0\n    - datetime: '2024-01-01'\n      source: Fraunhofer ISE\n      value: 99787.0\n    - datetime: '2024-11-11'\n      source: Fraunhofer ISE\n      value: 94300.0\n    - datetime: '2025-01-01'\n      source: Fraunhofer ISE\n      value: 100910.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 5500.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 3304.0\n    - datetime: '2019-01-01'\n      source: Fraunhofer ISE\n      value: 3322.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 2974.0\n    - datetime: '2021-01-01'\n      source: Fraunhofer ISE\n      value: 2914.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 3200.0\n    - datetime: '2024-01-01'\n      source: Fraunhofer ISE\n      value: 3171.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Fraunhofer ISE\n      value: 55580.0\n    - datetime: '2018-01-01'\n      source: Fraunhofer ISE\n      value: 58721.0\n    - datetime: '2019-01-01'\n      source: Fraunhofer ISE\n      value: 60742.0\n    - datetime: '2020-01-01'\n      source: Fraunhofer ISE\n      value: 62114.0\n    - datetime: '2021-01-01'\n      source: Fraunhofer ISE\n      value: 63745.0\n    - datetime: '2022-01-01'\n      source: Fraunhofer ISE\n      value: 66192.0\n    - datetime: '2023-01-01'\n      source: Fraunhofer ISE\n      value: 69449.0\n    - datetime: '2024-01-01'\n      source: Fraunhofer ISE\n      value: 72786.0\n    - datetime: '2024-11-11'\n      source: Fraunhofer ISE\n      value: 71700.0\n    - datetime: '2025-01-01'\n      source: Fraunhofer ISE\n      value: 72979.0\ncontributors:\n  - corradio\n  - bohne13\n  - chiefymuc\n  - nessie2013\n  - IV1T3\n  - sin\ncountry: DE\ncountry_name: Germany\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1073.03112\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1087.81\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1063.51\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1070.47\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 472.8075167\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 451.55\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 385.86\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 374.16\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 307.31\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 339.07\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 376.56\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 277.92\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 240.15\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 235.59\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1152.3866810000002\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1167.165561\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1123.51\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1130.47\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 592.8075167\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 571.55\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 505.86\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 494.16\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 318.01\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 349.77\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 387.26\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 288.62\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 250.85\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 246.29\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 35.11666667\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06822443423425736\n        coal: 0.39198386333236024\n        gas: 0.03157431710722741\n        geothermal: 0.00020773144243425417\n        hydro: 0.029805468813518508\n        hydro discharge: 0.013915672985820294\n        nuclear: 0.17043149438525243\n        oil: 0.003294290586036577\n        solar: 0.06364244279140722\n        unknown: 0.08649548813526689\n        wind: 0.14042479977885236\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07708897764813215\n        coal: 0.3827977278598596\n        gas: 0.05152664075008046\n        geothermal: 0.00030081762386774055\n        hydro: 0.03672522276589633\n        hydro discharge: 0.014527289954485342\n        nuclear: 0.1592289987002553\n        oil: 0.0032084169946244513\n        solar: 0.062710674255393\n        unknown: 0.0744186951604695\n        wind: 0.13746654028171984\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07835298977028746\n        coal: 0.35314014665296195\n        gas: 0.05498475321248953\n        geothermal: 0.00028879331641998524\n        hydro: 0.03140412726392683\n        hydro discharge: 0.014866647066019206\n        nuclear: 0.1383558715199725\n        oil: 0.0033891725203774167\n        solar: 0.06454958933609126\n        unknown: 0.07741775154121225\n        wind: 0.18325015806755096\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07900924119627038\n        coal: 0.36031215578392034\n        gas: 0.08478282258957591\n        geothermal: 0.0002941901326018241\n        hydro: 0.033011748184629486\n        hydro discharge: 0.016691563415625586\n        nuclear: 0.1439731051843356\n        oil: 0.005035723717057415\n        solar: 0.07398376747499799\n        unknown: 0.010349427193619745\n        wind: 0.19255625401396645\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08337106838587559\n        coal: 0.2799818800136177\n        gas: 0.10982710551992525\n        geothermal: 0.0003304757588095734\n        hydro: 0.03615410003432072\n        hydro discharge: 0.016174595813174826\n        nuclear: 0.15420229744691383\n        oil: 0.007388020708674489\n        solar: 0.07845016188862797\n        unknown: 0.00843118155095162\n        wind: 0.22568911262745708\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08707530342267537\n        coal: 0.23065944576205252\n        gas: 0.1231628286445281\n        geothermal: 0.00037836048102482864\n        hydro: 0.04308155976575074\n        hydro discharge: 0.01993541264649448\n        nuclear: 0.1386626193228\n        oil: 0.007514912875153696\n        solar: 0.0894190626263083\n        unknown: 0.009703466518651933\n        wind: 0.2504070271537337\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08793711683159064\n        coal: 0.28577562201345397\n        gas: 0.1059911895047725\n        geothermal: 0.0003627228586098105\n        hydro: 0.043616810948499445\n        hydro discharge: 0.01633702891126012\n        nuclear: 0.14087856906158377\n        oil: 0.006090078087134086\n        solar: 0.08829027767656393\n        unknown: 0.009890567483514249\n        wind: 0.21483001592925258\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.09097651286507295\n        coal: 0.32657451320317304\n        gas: 0.08256887732058861\n        geothermal: 0.0003728634818868725\n        hydro: 0.04074124727063704\n        hydro discharge: 0.019032029538077446\n        nuclear: 0.0745439517918397\n        oil: 0.005467953620125538\n        solar: 0.10717026626443672\n        unknown: 0.00781769218802249\n        wind: 0.24473409046633351\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.2360228234871724e-08\n        biomass: 0.09399946206557941\n        coal: 0.24528002512485228\n        gas: 0.1123302416559925\n        geothermal: 0.0003801529031173463\n        hydro: 0.058438729715757406\n        hydro discharge: 0.022607496492439875\n        nuclear: 0.042904710465673124\n        oil: 0.006194961311468286\n        solar: 0.11626124284568128\n        unknown: 0.0074727927481397765\n        wind: 0.2941301589231571\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 2.7369833899347496e-06\n        biomass: 0.09476446766058907\n        coal: 0.20655568232446983\n        gas: 0.1158765304321076\n        geothermal: 0.00038947943001685494\n        hydro: 0.07019260176827112\n        hydro discharge: 0.02689511015962647\n        nuclear: 0.044922962310730126\n        oil: 0.006848277980062988\n        solar: 0.13457764894826899\n        unknown: 0.0068592273218514585\n        wind: 0.2921152749986025\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.6353\n    - datetime: '2021-01-01'\n      value: 0.6219\n    - datetime: '2022-01-01'\n      value: 0.6031\n    - datetime: '2023-01-01'\n      value: 0.6686\n    - datetime: '2024-01-01'\n      value: 0.701\n    - datetime: '2025-01-01'\n      value: 0.7002\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4941\n    - datetime: '2021-01-01'\n      value: 0.4794\n    - datetime: '2022-01-01'\n      value: 0.5295\n    - datetime: '2023-01-01'\n      value: 0.6292\n    - datetime: '2024-01-01'\n      value: 0.6621\n    - datetime: '2025-01-01'\n      value: 0.6685\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: DE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Berlin\nzone_name: Germany\n"
  },
  {
    "path": "config/zones/DJ.yaml",
    "content": "bounding_box:\n  - - 41.747817478174795\n    - 10.940817070048752\n  - - 43.41103411034112\n    - 12.708204368752291\ncenter_point:\n  - 42.287992908122014\n  - 11.677474813498222\ncentroid:\n  - 42.65208106626521\n  - 11.778651019526176\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\ncountry: DJ\ncountry_name: Djibouti\ncurrency: DJF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Djibouti\nzone_name: Djibouti\n"
  },
  {
    "path": "config/zones/DK-DK1.yaml",
    "content": "bounding_box:\n  - - 8.09468094680949\n    - 54.72973148656037\n  - - 11.143911439114419\n    - 57.75153653611572\ncenter_point:\n  - 9.326898339873598\n  - 56.05430887934948\ncentroid:\n  - 9.555966462810545\n  - 56.14060988360049\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 900\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 907.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 904.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 905.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 906.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 902.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 902.8\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2775.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1915.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1943.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1700.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1161.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1151.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1119.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1049.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1018.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 991.2\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 9.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 6.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 7.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 5.3\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 292.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 208.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 210.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 211.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 196.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 195.4\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 421.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 664.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 672.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 878.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1086.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1701.5\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 2738.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 75.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 125.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 111.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 112.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 117.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 113.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 112.1\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 3809.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 4941.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4946.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 4922.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 5002.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 5165.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 5232.1\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 5713.0\ncontributors:\n  - corradio\n  - tmslaine\ncountry: DK\ncountry_name: Denmark\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 845.5332093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 845.53\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 798.83\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 801.08\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 336.9719859\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 336.97\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 299.26\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1193.417464\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1193.42\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1381.0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 914.3278173\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 914.324608\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 858.83\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 861.08\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 456.9719859\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 456.97\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 419.26\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1437.417464\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1437.42\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1625.0\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 37.66666667\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0425559800947321\n        coal: 0.19621121176469578\n        gas: 0.0793084499270751\n        geothermal: 1.1304304776028022e-05\n        hydro: 0.24299459536604845\n        hydro discharge: 0.00040057935374451304\n        nuclear: 0.03203354904231474\n        oil: 0.00421346727059739\n        solar: 0.01831173877642908\n        unknown: 0.010552034700766889\n        wind: 0.37340691526256514\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04399782176810459\n        coal: 0.2596574042973441\n        gas: 0.08401867556320955\n        geothermal: 3.1086538242802454e-05\n        hydro: 0.234858404646364\n        hydro discharge: 0.0008398828286082919\n        nuclear: 0.021042450172527698\n        oil: 0.004150739463819686\n        solar: 0.02566911169190922\n        unknown: 0.009209267452168716\n        wind: 0.31652502398814136\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.10195068853059433\n        coal: 0.13565323569771245\n        gas: 0.05821642678966624\n        geothermal: 2.7930760093338522e-05\n        hydro: 0.20722018781940127\n        hydro discharge: 0.0007191115433428907\n        nuclear: 0.039056586730108575\n        oil: 0.024401039763591724\n        solar: 0.025875344719133404\n        unknown: 0.011107504536645288\n        wind: 0.39577182299533253\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.09026996834445464\n        coal: 0.17188664488412275\n        gas: 0.07875295650001482\n        geothermal: 3.9937966020283617e-05\n        hydro: 0.183540587236891\n        hydro discharge: 0.001100512630442286\n        nuclear: 0.04668584434729179\n        oil: 0.003093082047523928\n        solar: 0.03503041313951011\n        unknown: 0.007082794268276612\n        wind: 0.38251717412773717\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08743996402789544\n        coal: 0.1327328220143222\n        gas: 0.09498444304865304\n        geothermal: 4.479280481747764e-05\n        hydro: 0.14154189731197533\n        hydro discharge: 0.0010730655764969318\n        nuclear: 0.052294339732868025\n        oil: 0.006063933566410995\n        solar: 0.035306084825253395\n        unknown: 0.00586770575760526\n        wind: 0.44265088026656624\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06692327929427243\n        coal: 0.10651127441191853\n        gas: 0.06691773551043777\n        geothermal: 2.3228288561282008e-05\n        hydro: 0.25315807913047267\n        hydro discharge: 0.008088950919327298\n        nuclear: 0.034403138145098745\n        oil: 0.0035811020806684707\n        solar: 0.04014456864434547\n        unknown: 0.004657468862472049\n        wind: 0.4155911636653635\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08563633327748853\n        coal: 0.14822922957255574\n        gas: 0.07002850286947418\n        geothermal: 2.7129891129159675e-05\n        hydro: 0.21506681492594826\n        hydro discharge: 0.0188071996276841\n        nuclear: 0.03769591146083028\n        oil: 0.003656547998327896\n        solar: 0.039519745929459546\n        unknown: 0.00723532983317983\n        wind: 0.37409721677945734\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08287797596049754\n        coal: 0.13562285995257736\n        gas: 0.06539862353411519\n        geothermal: 2.579494629921434e-05\n        hydro: 0.15714006182144236\n        hydro discharge: 0.002955022653989741\n        nuclear: 0.04534412320990245\n        oil: 0.003776530178146859\n        solar: 0.05976038764005032\n        unknown: 0.006473929012726921\n        wind: 0.4406246734756894\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07419507926067591\n        coal: 0.0804421910438917\n        gas: 0.06406997576836419\n        geothermal: 2.566038517891035e-05\n        hydro: 0.18314972800790405\n        hydro discharge: 0.00317735329989495\n        nuclear: 0.04042125552009426\n        oil: 0.0042834368022023695\n        solar: 0.07984936178000344\n        unknown: 0.005845303119459079\n        wind: 0.4645405069062507\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.553515199154069e-07\n        biomass: 0.06758187387309503\n        coal: 0.06773915067187355\n        gas: 0.06181442377353182\n        geothermal: 2.518397674051124e-05\n        hydro: 0.2065594939563972\n        hydro discharge: 0.003964525096617679\n        nuclear: 0.04411227716909667\n        oil: 0.0044998805571116185\n        solar: 0.0957437672837289\n        unknown: 0.004961503860134691\n        wind: 0.44299766224706716\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: DK.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_storage/disk/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdDRG9JYTJWNVNTSWhORFJ0ZDJJMWVUbG9OMll6TVRaaGEza3lkamgxZG1aM056WnZZZ1k2QmtWVU9oQmthWE53YjNOcGRHbHZia2tpQVk1cGJteHBibVU3SUdacGJHVnVZVzFsUFNKWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtSWpzZ1ptbHNaVzVoYldVcVBWVlVSaTA0SnlkWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtQmpzR1ZEb1JZMjl1ZEdWdWRGOTBlWEJsU1NJVVlYQndiR2xqWVhScGIyNHZjR1JtQmpzR1ZBPT0iLCJleHAiOiIyMDIyLTExLTAyVDE1OjU0OjAzLjEyNFoiLCJwdXIiOiJibG9iX2tleSJ9fQ==--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Copenhagen\nzone_name: West Denmark\n"
  },
  {
    "path": "config/zones/DK-DK2.yaml",
    "content": "bounding_box:\n  - - 10.96030960309605\n    - 54.56229528970156\n  - - 15.15075150751511\n    - 56.12868860354098\ncenter_point:\n  - 12.689554961621594\n  - 55.591969176610924\ncentroid:\n  - 12.161853389676326\n  - 55.23197710171024\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1173.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1202.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1351.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1350.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1352.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1236.3\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2072.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1741.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1471.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1222.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1078.5\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1241.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 665.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 663.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 620.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 605.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 603.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 576.9\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 759.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 799.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 801.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 763.7\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 180.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 338.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 342.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 341.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 422.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 450.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 620.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 992.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 13.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 21.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 24.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 25.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 24.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 23.5\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1036.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1182.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1180.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1179.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1784.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1784.1\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1793.0\ncontributors:\n  - corradio\n  - tmslaine\ncountry: DK\ncountry_name: Denmark\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 845.5332093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 845.53\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 798.83\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 801.08\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 336.9719859\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 336.97\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 299.26\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1193.417464\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1193.42\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1381.0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 914.3278173\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 914.324608\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 858.83\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 861.08\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 456.9719859\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 456.97\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 419.26\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1437.417464\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1437.42\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1625.0\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 36.0\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.059046313587698525\n        coal: 0.1905237883697111\n        gas: 0.12165687005242244\n        geothermal: 1.1378182934219265e-05\n        hydro: 0.13014214940765392\n        hydro discharge: 0.00048339291989920214\n        nuclear: 0.10539554131441396\n        oil: 0.006858873935138577\n        solar: 0.023036357013493557\n        unknown: 0.03050224886737629\n        wind: 0.3323432203884183\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06599525817827746\n        coal: 0.27081740836549345\n        gas: 0.14259309477101434\n        geothermal: 3.732924566690658e-05\n        hydro: 0.10772561666959465\n        hydro discharge: 0.0012655767018966372\n        nuclear: 0.07350704017372221\n        oil: 0.007911201929956285\n        solar: 0.03540650881590057\n        unknown: 0.022881015400034708\n        wind: 0.27185994600578745\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1884395718244603\n        coal: 0.17116982478130172\n        gas: 0.0439402355371934\n        geothermal: 2.3304604510251863e-05\n        hydro: 0.11322518828644228\n        hydro discharge: 0.0006317630193114006\n        nuclear: 0.08874489606382918\n        oil: 0.009872233407017775\n        solar: 0.031236808308146728\n        unknown: 0.02184983499431917\n        wind: 0.3308661794591233\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.17799399129771598\n        coal: 0.20351284803910513\n        gas: 0.06402342914414653\n        geothermal: 3.3215441843261725e-05\n        hydro: 0.09557820793452589\n        hydro discharge: 0.0010892838702078887\n        nuclear: 0.08044468399459577\n        oil: 0.009009113176705752\n        solar: 0.041365760903323535\n        unknown: 0.015676600382503864\n        wind: 0.31127275900133733\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.19687709234634396\n        coal: 0.11324674535514183\n        gas: 0.0626727802995632\n        geothermal: 5.650364491523119e-05\n        hydro: 0.09407055305499558\n        hydro discharge: 0.0016799650413856886\n        nuclear: 0.09972168820351406\n        oil: 0.009278338337106402\n        solar: 0.045758803069799535\n        unknown: 0.017084305120665284\n        wind: 0.3595530067256977\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.16819304889765269\n        coal: 0.08723808090209009\n        gas: 0.05272393878005872\n        geothermal: 2.9178818355533255e-05\n        hydro: 0.14156930115117236\n        hydro discharge: 0.0037339475705790498\n        nuclear: 0.08709401389378482\n        oil: 0.010846479140866434\n        solar: 0.05218651122499738\n        unknown: 0.0179666234327582\n        wind: 0.37841894509137136\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.20860007208221287\n        coal: 0.10348713136951929\n        gas: 0.06246386513861829\n        geothermal: 2.780789652228753e-05\n        hydro: 0.09888481701649286\n        hydro discharge: 0.003924208486088063\n        nuclear: 0.08840446648578446\n        oil: 0.014111399440336096\n        solar: 0.04339016319330319\n        unknown: 0.03101666381074703\n        wind: 0.3456893315608202\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1704427028499718\n        coal: 0.07674775566747495\n        gas: 0.04210681601358189\n        geothermal: 1.5594986129683777e-05\n        hydro: 0.12349929345349414\n        hydro discharge: 0.0011118637001111711\n        nuclear: 0.10972467615063516\n        oil: 0.012079080851230762\n        solar: 0.05451381303945087\n        unknown: 0.02545602712870279\n        wind: 0.38430232459689745\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.14544063503512056\n        coal: 0.07224915785746344\n        gas: 0.04284698746567894\n        geothermal: 1.5030225418970753e-05\n        hydro: 0.1308815394660542\n        hydro discharge: 0.001010318209267146\n        nuclear: 0.10586471704082535\n        oil: 0.011619573585806769\n        solar: 0.06593060787085872\n        unknown: 0.021132683160768818\n        wind: 0.4030084939358984\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.645446245289671e-08\n        biomass: 0.144644291632214\n        coal: 0.06582103189357245\n        gas: 0.04047182834088851\n        geothermal: 2.2079486441422732e-05\n        hydro: 0.12617478404830373\n        hydro discharge: 0.001193526111181387\n        nuclear: 0.11309776286303894\n        oil: 0.010801891173105956\n        solar: 0.08843372724158337\n        unknown: 0.01876231192947404\n        wind: 0.39057648626334907\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: DK.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Copenhagen\nzone_name: East Denmark\n"
  },
  {
    "path": "config/zones/DK.yaml",
    "content": "bounding_box:\n  - - 8.09468094680949\n    - 54.56229528970156\n  - - 15.15075150751511\n    - 57.75153653611572\ncenter_point:\n  - 9.326908056142866\n  - 56.054311974045376\ncentroid:\n  - 10.56109427745877\n  - 55.79013723915708\ncapacity:\n  biomass: 2139\n  coal: 3022\n  gas: 1568\n  geothermal: 0\n  hydro: 5\n  hydro storage: 0\n  nuclear: 0\n  oil: 959\n  solar: 2322\n  unknown: 136\n  wind: 7017\ncontributors:\n  - corradio\n  - Manu1400\ncountry: DK\ncountry_name: Denmark\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 845.5332093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 845.53\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 798.83\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 801.08\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 336.9719859\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 336.97\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 299.26\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1193.417464\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1193.42\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1381.0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 914.3278173\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 914.324608\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 858.83\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 861.08\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 456.9719859\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 456.97\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 419.26\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1437.417464\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1437.42\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1625.0\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 35.98888889\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.13595829899283995\n        coal: 0.1485354234126849\n        gas: 0.05225882014369051\n        geothermal: 2.597701646904838e-05\n        hydro: 0.1700428248555171\n        hydro discharge: 0.0006809174493419097\n        nuclear: 0.058943881797539205\n        oil: 0.01857427420884643\n        solar: 0.028537230653620602\n        unknown: 0.015405117863256795\n        wind: 0.3710372282782425\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1247326039089966\n        coal: 0.18302058749856767\n        gas: 0.07252350158991756\n        geothermal: 3.709680066037601e-05\n        hydro: 0.14903240950089613\n        hydro discharge: 0.0010890383146027597\n        nuclear: 0.060328836007281\n        oil: 0.005365788901631393\n        solar: 0.0377297064100585\n        unknown: 0.010578307816129163\n        wind: 0.3555621100273502\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.13034413206178677\n        coal: 0.12432657793550397\n        gas: 0.08184217879592194\n        geothermal: 4.907381787593547e-05\n        hydro: 0.12289285329715784\n        hydro discharge: 0.0013015369057485147\n        nuclear: 0.07104706020037366\n        oil: 0.00726679943892034\n        solar: 0.03983787784829738\n        unknown: 0.01034897495512764\n        wind: 0.41074292289410447\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.10534844207323642\n        coal: 0.09865955113276632\n        gas: 0.061217410725118625\n        geothermal: 2.535811024895818e-05\n        hydro: 0.2106181597256165\n        hydro discharge: 0.006413512234569999\n        nuclear: 0.054684298152625745\n        oil: 0.006290265388603747\n        solar: 0.04511815289350426\n        unknown: 0.009792765268638474\n        wind: 0.40183203873151857\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1325321476516684\n        coal: 0.1303971245305186\n        gas: 0.06674507767008472\n        geothermal: 2.7270166600510458e-05\n        hydro: 0.17056778890056448\n        hydro discharge: 0.013066274497841921\n        nuclear: 0.05743658793007631\n        oil: 0.007586245656865026\n        solar: 0.04128955505772794\n        unknown: 0.016517867437770867\n        wind: 0.3638340168299024\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.11646571983196764\n        coal: 0.11276014169512567\n        gas: 0.05628161925927549\n        geothermal: 2.1866597370709407e-05\n        hydro: 0.14430732023856824\n        hydro discharge: 0.002248364642074149\n        nuclear: 0.06982056132823157\n        oil: 0.006861950611750369\n        solar: 0.058083589997282144\n        unknown: 0.013713640667869287\n        wind: 0.41943518735950847\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.766127940282214e-10\n        biomass: 0.1014252170768069\n        coal: 0.07689580111424152\n        gas: 0.05571741554734854\n        geothermal: 2.1572201967878903e-05\n        hydro: 0.16315823699858728\n        hydro discharge: 0.0023455614224370015\n        nuclear: 0.06538646029726487\n        oil: 0.007015017187154775\n        solar: 0.07488220298253058\n        unknown: 0.01169113046859922\n        wind: 0.4414613257845362\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.2128866406600962e-07\n        biomass: 0.09667795273235628\n        coal: 0.06661401235496091\n        gas: 0.05353775760170223\n        geothermal: 2.3946995402485807e-05\n        hydro: 0.17620036021696572\n        hydro discharge: 0.0029164763756376277\n        nuclear: 0.0699715788005453\n        oil: 0.006801247324328013\n        solar: 0.0934880730481194\n        unknown: 0.010149763251266004\n        wind: 0.42361865325317705\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  production: ENTSOE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\nsubZoneNames:\n  - DK-DK1\n  - DK-DK2\ntimezone: Europe/Copenhagen\nzone_name: Denmark\n"
  },
  {
    "path": "config/zones/DM.yaml",
    "content": "bounding_box:\n  - - -61.468814688146836\n    - 15.201150663765702\n  - - -61.2564125641256\n    - 15.633337679319126\ncenter_point:\n  - -61.362613626136216\n  - 15.417244171542414\ncentroid:\n  - -61.349113491134865\n  - 15.424757356415444\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: DM\ncountry_name: Dominica\ncurrency: XCD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Dominica\nzone_name: Dominica\n"
  },
  {
    "path": "config/zones/DO.yaml",
    "content": "bounding_box:\n  - - -72.00972009720093\n    - 17.605369823135703\n  - - -68.35568355683552\n    - 19.935172675191865\ncenter_point:\n  - -70.64581908809805\n  - 19.003507168033153\ncentroid:\n  - -70.48228743156992\n  - 18.853989594891836\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 690.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1060.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1700.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1850.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2240.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 610.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 620.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 630.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 330.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 390.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 580.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 740.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1080.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1420.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1810.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1980.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1850.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1750.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1740.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 420.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 430.0\ncontributors:\n  - systemcatch\n  - nessie2013\n  - alixunderplatz\n  - consideRatio\ncountry: DO\ncountry_name: Dominican Republic\ncurrency: DOP\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011280330099424807\n        coal: 0.14362400571698894\n        gas: 0.5106890414473679\n        geothermal: 0.0\n        hydro: 0.12046500673470001\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.19501801585433304\n        solar: 0.0\n        unknown: 0.001484663707361843\n        wind: 0.01743893643982338\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012925956911795652\n        coal: 0.12732698255682406\n        gas: 0.46676545683440046\n        geothermal: 0.0\n        hydro: 0.10312081698062121\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.2536208525581716\n        solar: 0.000111026328150641\n        unknown: 0.009056554934911226\n        wind: 0.02707235289512512\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012174830228366273\n        coal: 0.1268312157085024\n        gas: 0.4183756944965807\n        geothermal: 0.0\n        hydro: 0.056027536952169214\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.25314260780094516\n        solar: 0.0060781783510567376\n        unknown: 0.0867589207197395\n        wind: 0.040611015742640026\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009707972095108715\n        coal: 0.3604811408428967\n        gas: 0.28814517998914985\n        geothermal: 0.0\n        hydro: 0.06600652679906015\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.13618933091241262\n        solar: 0.014657298807662224\n        unknown: 0.07011493066725415\n        wind: 0.05469761988645557\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010134892208187264\n        coal: 0.3013204395897952\n        gas: 0.3932114794705303\n        geothermal: 0.0\n        hydro: 0.06850952962979008\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.11564795638695256\n        solar: 0.02338202747619552\n        unknown: 0.032487597556916416\n        wind: 0.05530607768163253\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009360069753550828\n        coal: 0.30706113423428677\n        gas: 0.3663250345011476\n        geothermal: 0.0\n        hydro: 0.06593871715921543\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.15012609951512484\n        solar: 0.032883204007210086\n        unknown: 0.014951952284648079\n        wind: 0.05335378854481634\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009426605595307603\n        coal: 0.2993508136963388\n        gas: 0.25280795672244344\n        geothermal: 0.0\n        hydro: 0.04847984247103398\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.12462784019988545\n        solar: 0.04635123981672069\n        unknown: 0.17169783934403446\n        wind: 0.04725786215423553\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011463440593032665\n        coal: 0.31224070634014406\n        gas: 0.3238493612383818\n        geothermal: 0.0\n        hydro: 0.05821423573662806\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.08851449447114812\n        solar: 0.06587656603563896\n        unknown: 0.09357429549804941\n        wind: 0.04626690008697701\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: DO.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Santo_Domingo\nzone_name: Dominican Republic\n"
  },
  {
    "path": "config/zones/DZ.yaml",
    "content": "bounding_box:\n  - - -8.681486814868123\n    - 18.982071508441607\n  - - 11.968319683196853\n    - 37.08240717969856\ncenter_point:\n  - 1.5925447337166325\n  - 28.02492976863435\ncentroid:\n  - 2.9813168670991392\n  - 31.062722570726514\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 15960.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 17130.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 19680.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 19900.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 21570.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 23470.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 350.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 450.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 460.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1490.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1460.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1560.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\ncountry: DZ\ncountry_name: Algeria\ncurrency: DZD\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9889616849323075\n        geothermal: 0.0\n        hydro: 0.00017536621953407952\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0035953872632283087\n        solar: 0.007103075358023904\n        unknown: 0.0\n        wind: 0.00016441212685149015\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9889742986324795\n        geothermal: 0.0\n        hydro: 0.00017961719018977343\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0036047228087590687\n        solar: 0.0070754161021284396\n        unknown: 0.0\n        wind: 0.00016600744389401443\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Algiers\nzone_name: Algeria\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/EC.yaml",
    "content": "bounding_box:\n  - - -91.66951669516689\n    - -5.011463268937746\n  - - -75.22815228152277\n    - 1.43413381070657\ncenter_point:\n  - -78.06446953772002\n  - -1.7972333931900646\ncentroid:\n  - -81.95893882015737\n  - -1.5465502825203785\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 930.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 940.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 980.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 960.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 920.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4520.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 5070.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 5080.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 5100.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 5190.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 5220.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2410.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2470.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2480.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2470.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2500.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2470.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2490.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2690.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\ncountry: EC\ncountry_name: Ecuador\ncurrency: USD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: EC.fetch_consumption\n  production: EC.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Guayaquil\nzone_name: Ecuador\n"
  },
  {
    "path": "config/zones/EE.yaml",
    "content": "bounding_box:\n  - - 21.86841868418685\n    - 57.5154078686776\n  - - 28.18648186481866\n    - 59.666325366613975\ncenter_point:\n  - 25.56793173167626\n  - 58.607463432264865\ncentroid:\n  - 24.408274591220515\n  - 58.578411345870805\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 106.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 121.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 175.73999999999998\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 175.5\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 192.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 400\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 169.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 167.3\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1976.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1970.3\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1970.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1462.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1371.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1330.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 214.4\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 204.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 176.56\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 212.2\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 172.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 119.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 188.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 93.7\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 91.9\n  geothermal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 8.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 7.13\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 8.4\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 8.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 4.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 8.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 7.87\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 7.9\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 52.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1.4\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 33.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 122.7\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 164.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 370.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 510.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 812.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1174.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 6.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 5.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 11.83\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 11.8\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 13.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 20.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 384.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 487.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 462.4\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 328.8\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 329.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 326.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 317.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 447.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 682.0\ncontributors:\n  - corradio\n  - nessie2013\ncountry: EE\ncountry_name: Estonia\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 832.9110972\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 999.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 419.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 892.9110972\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1059.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 36.5\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08694622553183029\n        coal: 0.5339284677519908\n        gas: 0.0515833944274327\n        geothermal: 0.0\n        hydro: 0.10601284571569076\n        hydro discharge: 2.9951318374831823e-05\n        nuclear: 0.1173890925321195\n        oil: 0.0014442689869188462\n        solar: 0.00018002825770916368\n        unknown: 0.04043053969096788\n        wind: 0.06205666593252926\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05344051908183458\n        coal: 0.5047736544662191\n        gas: 0.031829662160375326\n        geothermal: 0.0\n        hydro: 0.05339251667578622\n        hydro discharge: 1.0972879788566714e-06\n        nuclear: 0.07263375654874478\n        oil: 0.0008135804542124674\n        solar: 0.00048046117314870165\n        unknown: 0.22946415802661102\n        wind: 0.05317552854125684\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06043323823646815\n        coal: 0.6583545551864324\n        gas: 0.0380989536256179\n        geothermal: 0.0\n        hydro: 0.04452732320449595\n        hydro discharge: 8.521017636814256e-06\n        nuclear: 0.041238271356891947\n        oil: 0.0006370304982375928\n        solar: 0.0007482999435954718\n        unknown: 0.08999759960653259\n        wind: 0.06595595007202072\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06519784059527511\n        coal: 0.6508049414523656\n        gas: 0.04770958866422499\n        geothermal: 0.0\n        hydro: 0.0531356414943133\n        hydro discharge: 4.036077899223171e-07\n        nuclear: 0.06599936150229051\n        oil: 0.0003669260983525079\n        solar: 0.0008044062733433512\n        unknown: 0.05061438950466644\n        wind: 0.06536623827829896\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08543753536419149\n        coal: 0.38478736856980433\n        gas: 0.06459549055864117\n        geothermal: 0.0\n        hydro: 0.10380966858129086\n        hydro discharge: 6.018184875980652e-05\n        nuclear: 0.14346915265588936\n        oil: 7.862248468828282e-05\n        solar: 0.001507939891639984\n        unknown: 0.11832373639496181\n        wind: 0.09793121991772942\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.10449644312212812\n        coal: 0.2374138349115466\n        gas: 0.07428192649227049\n        geothermal: 3.642622783792479e-09\n        hydro: 0.1823401055308618\n        hydro discharge: 0.0001869564001705544\n        nuclear: 0.1876257964600788\n        oil: 0.00011530965263614013\n        solar: 0.012307214249878162\n        unknown: 0.04623665122633341\n        wind: 0.15499585180545797\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08627265633479003\n        coal: 0.3261436950380143\n        gas: 0.059498526112405706\n        geothermal: 0.0\n        hydro: 0.14519484728692983\n        hydro discharge: 0.00015149623507385677\n        nuclear: 0.16268810810830298\n        oil: 0.00016758666448011246\n        solar: 0.025693862803800406\n        unknown: 0.07028819944316751\n        wind: 0.12390102197303536\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1259852253778548\n        coal: 0.3438429725746771\n        gas: 0.041270924249955196\n        geothermal: 3.660155958879392e-09\n        hydro: 0.12997055081217304\n        hydro discharge: 6.620246088023785e-05\n        nuclear: 0.15690433427799313\n        oil: 0.0002802178800558474\n        solar: 0.04020433894286193\n        unknown: 0.026408263153452145\n        wind: 0.13506659205398078\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0913306316848167\n        coal: 0.20566644107144785\n        gas: 0.05737032274603525\n        geothermal: 5.823249534924278e-08\n        hydro: 0.15257931584246406\n        hydro discharge: 7.890249935060007e-05\n        nuclear: 0.23509144123418238\n        oil: 7.221968754736849e-05\n        solar: 0.06231635797101853\n        unknown: 0.01477897943738938\n        wind: 0.18071532452955735\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08945140086046262\n        coal: 0.18518720059126303\n        gas: 0.0809946409563121\n        geothermal: 8.384784910478956e-08\n        hydro: 0.13402435114909558\n        hydro discharge: 0.0005343920115837377\n        nuclear: 0.14992179240220946\n        oil: 7.683171908508261e-05\n        solar: 0.09519660517241334\n        unknown: 0.040069879623022754\n        wind: 0.22454441864573693\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Tallinn\nzone_name: Estonia\n"
  },
  {
    "path": "config/zones/EG.yaml",
    "content": "bounding_box:\n  - - 24.687246872468734\n    - 21.99593195465185\n  - - 36.89496894968951\n    - 31.657172159953546\ncenter_point:\n  - 30.498232586821736\n  - 26.804007270011923\ncentroid:\n  - 31.50899318261996\n  - 28.851579751153995\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 33190.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 48840.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 51810.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 52560.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 53530.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 52660.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 52270.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2800.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2830.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 760.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1650.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1640.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1660.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1720.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1860.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2590.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 750.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1130.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1380.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1640.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1890.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2200.0\ncountry: EG\ncountry_name: Egypt\ncurrency: EGP\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.792304218151275\n        geothermal: 0.0\n        hydro: 0.07016449737964768\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.08626123105161614\n        solar: 0.023436072515245022\n        unknown: 0.0\n        wind: 0.02783393131852747\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.7923036080608923\n        geothermal: 0.0\n        hydro: 0.07016520776093255\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.08626117771017332\n        solar: 0.023436075509726206\n        unknown: 0.0\n        wind: 0.027833902166199798\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Cairo\nzone_name: Egypt\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/EH.yaml",
    "content": "bounding_box:\n  - - -17.101971019710163\n    - 20.766631801140647\n  - - -8.666969194703857\n    - 27.66158889033389\ncenter_point:\n  - -12.824445339781253\n  - 24.502323564027694\ncentroid:\n  - -14.289802950951172\n  - 24.108608948434593\ncountry: EH\ncountry_name: Western Sahara\ncurrency: MAD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Africa\ntimezone: Africa/El_Aaiun\nzone_name: Western Sahara\n"
  },
  {
    "path": "config/zones/ER.yaml",
    "content": "bounding_box:\n  - - 36.42336423364236\n    - 12.360451240343423\n  - - 43.11943119431194\n    - 18.004641933531076\ncenter_point:\n  - 38.10493660287654\n  - 16.010069637764822\ncentroid:\n  - 39.662952793911515\n  - 14.91779626283995\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: ER\ncountry_name: Eritrea\ncurrency: ERN\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Asmara\nzone_name: Eritrea\n"
  },
  {
    "path": "config/zones/ES-CE.yaml",
    "content": "bounding_box:\n  - - -5.387418011072289\n    - 35.87135845199824\n  - - -5.278463534102098\n    - 35.92262502599443\ncenter_point:\n  - -5.333376028605113\n  - 35.894970004238736\ncentroid:\n  - -5.330090241389734\n  - 35.891950896456414\ncapacity:\n  gas:\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 13.0\n  oil:\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 78.0\ncontributors:\n  - VIKTORVAV99\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 405.89\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 405.89\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 405.93\n      - _comment: used non-null storage values\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 405.96\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 405.82\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 405.86\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 438.89\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 438.89\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 438.93\n      - _comment: used non-null storage values\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 438.96\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 438.82\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 438.86\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0044350185851695905\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9955482777806223\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.001150541319566968\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9988313501042958\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.004949120084514963\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9950341454487983\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.0\n    - datetime: '2021-01-01'\n      value: 0.0\n    - datetime: '2022-01-01'\n      value: 0.0\n    - datetime: '2023-01-01'\n      value: 0.0\n    - datetime: '2024-01-01'\n      value: 0.0\n    - datetime: '2025-01-01'\n      value: 0.0\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.0\n    - datetime: '2021-01-01'\n      value: 0.0\n    - datetime: '2022-01-01'\n      value: 0.0\n    - datetime: '2023-01-01'\n      value: 0.0\n    - datetime: '2024-01-01'\n      value: 0.0\n    - datetime: '2025-01-01'\n      value: 0.0\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\n  productionCapacity: REE.fetch_production_capacity\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Europe/Madrid\nzone_name: Ceuta\n"
  },
  {
    "path": "config/zones/ES-CN-FV.yaml",
    "content": "bounding_box:\n  - - -14.463587593357897\n    - 28.06789429485049\n  - - -13.836738367383646\n    - 28.716296938224176\ncenter_point:\n  - -14.150162980370771\n  - 28.392095616537333\ncentroid:\n  - -14.091886238675462\n  - 28.34474952478045\ncontributors:\n  - hectorespert\n  - systemcatch\n  - silimotion\n  - t-couery\n  - VIKTORVAV99\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 784.591\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 781.383\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 775.822\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 748.463\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 717.273\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 794.155\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 738.986\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 741.362\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 1028.591\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 1025.383\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 1019.822\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 992.463\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 961.273\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 1038.155\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 982.986\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 985.362\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Canary\nzone_name: Fuerteventura\n"
  },
  {
    "path": "config/zones/ES-CN-GC.yaml",
    "content": "bounding_box:\n  - - -15.81675816758164\n    - 27.734574114814762\n  - - -15.377553775537734\n    - 28.166761130368172\ncenter_point:\n  - -15.597155971559687\n  - 27.950667622591467\ncentroid:\n  - -15.613356133561306\n  - 27.955914926312314\ncontributors:\n  - hectorespert\n  - systemcatch\n  - silimotion\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 712.884\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 704.616\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 703.516\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 688.459\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 692.156\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 688.248\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 689.499\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 690.396\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 956.884\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 948.616\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 947.516\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 932.459\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 936.156\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 932.248\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 933.499\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 934.396\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.95\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.3635406938755062\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5124232786503851\n        solar: 0.013664320420501374\n        unknown: 0.0\n        wind: 0.11037190538957074\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0012998622769471294\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8345114027870847\n        solar: 0.015583850159905504\n        unknown: 0.0\n        wind: 0.14860478949496442\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8251620695749571\n        solar: 0.014917290949331528\n        unknown: 0.0\n        wind: 0.1599207413310881\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7848651691552683\n        solar: 0.016829948801388127\n        unknown: 0.0\n        wind: 0.19830501455282273\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7569352640926051\n        solar: 0.0356487083837875\n        unknown: 0.0\n        wind: 0.20741615936530067\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7670962840984132\n        solar: 0.04158174682925995\n        unknown: 0.0\n        wind: 0.19132201935385834\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7427768552697082\n        solar: 0.04889212064097191\n        unknown: 0.0\n        wind: 0.20833115421534318\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Canary\nzone_name: Gran Canaria\n"
  },
  {
    "path": "config/zones/ES-CN-HI.yaml",
    "content": "bounding_box:\n  - - -18.160381603816006\n    - 27.64298481350542\n  - - -17.898047301443473\n    - 27.828569453430994\ncenter_point:\n  - -18.029214452629738\n  - 27.735777133468208\ncentroid:\n  - -18.01293623635249\n  - 27.73108287875151\ncapacity:\n  hydro storage: 11.32\n  oil: 11.78\n  wind: 11.5\ncontributors:\n  - hectorespert\n  - systemcatch\n  - silimotion\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 181.37\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 243.08\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 195.51\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 211.03\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 681.673\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 697.897\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 689.579\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 693.395\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 709.189\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 717.053\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 709.656\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 711.721\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 192.07\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 253.78\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 206.21\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 221.73\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 925.673\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 941.897\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 933.579\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 937.395\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 953.189\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 961.053\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 953.656\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 955.721\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.05031198057583127\n        nuclear: 0.0\n        oil: 0.40438669737212996\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.5453101862158201\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.04403266715087347\n        nuclear: 0.0\n        oil: 0.41524375625347787\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.540695709638694\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0364815520400542\n        nuclear: 0.0\n        oil: 0.5377108096444623\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.42576721218362756\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0349716015189203\n        nuclear: 0.0\n        oil: 0.4767118975482077\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.48829033452562287\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.03402602434651732\n        nuclear: 0.0\n        oil: 0.4804657455533628\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.4854842382621434\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.018029759077066207\n        nuclear: 0.0\n        oil: 0.6141811841786473\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.3677736527078204\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.02195398329650652\n        nuclear: 0.0\n        oil: 0.5178817428592677\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.4601475232281346\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 0.7471\n    - datetime: '2023-01-01'\n      value: 0.6575\n    - datetime: '2024-01-01'\n      value: 0.7253\n    - datetime: '2025-01-01'\n      value: 0.7035\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 0.7471\n    - datetime: '2023-01-01'\n      value: 0.6575\n    - datetime: '2024-01-01'\n      value: 0.7253\n    - datetime: '2025-01-01'\n      value: 0.7035\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Canary\nzone_name: El Hierro\n"
  },
  {
    "path": "config/zones/ES-CN-IG.yaml",
    "content": "bounding_box:\n  - - -17.334480011242956\n    - 28.02651501273826\n  - - -17.0983709837098\n    - 28.20683144969101\ncenter_point:\n  - -17.21642549747638\n  - 28.116673231214634\ncentroid:\n  - -17.227404126168764\n  - 28.1194594372202\ncapacity:\n  oil: 22.8\ncontributors:\n  - hectorespert\n  - systemcatch\n  - silimotion\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 683.958\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 696.102\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 692.636\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 697.33\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 707.279\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 693.63\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 713.29\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 684.308\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 927.958\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 940.102\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 936.636\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 941.33\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 951.279\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 937.63\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 957.29\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 928.308\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9999828032199614\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9999047041519915\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9998975884225004\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9998973391667373\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9998911646928592\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9284115678299145\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.07155506292990885\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8988179175999675\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.10116250460286508\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Canary\nzone_name: Isla de la Gomera\n"
  },
  {
    "path": "config/zones/ES-CN-LP.yaml",
    "content": "bounding_box:\n  - - -18.001980019800158\n    - 28.45583986262575\n  - - -17.721177211772073\n    - 28.84080114469154\ncenter_point:\n  - -17.861578615786115\n  - 28.648320503658645\ncentroid:\n  - -17.8543785437854\n  - 28.694115154313316\ncontributors:\n  - hectorespert\n  - systemcatch\n  - silimotion\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 680.386\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 679.71\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 685.035\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 681.021\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 678.628\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 683.252\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 677.072\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 669.797\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 924.386\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 923.71\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 929.035\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 925.021\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 922.628\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 927.252\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 921.072\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 913.797\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0016368359702573277\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.884939873865101\n        solar: 0.026022068375152942\n        unknown: 0.0\n        wind: 0.08740347881504518\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 6.23252114295731e-05\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8885452537446913\n        solar: 0.02609975248039286\n        unknown: 0.0\n        wind: 0.08529499034086195\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8964833553111414\n        solar: 0.026374097656100194\n        unknown: 0.0\n        wind: 0.07714438601957777\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8997758000899152\n        solar: 0.0209359711148945\n        unknown: 0.0\n        wind: 0.07928811279571987\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9211715042275147\n        solar: 0.012206243110458023\n        unknown: 0.0\n        wind: 0.06662036401534964\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9291200284970847\n        solar: 0.017697072042023216\n        unknown: 0.0\n        wind: 0.053184358408431054\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9132256887989368\n        solar: 0.018142231715055784\n        unknown: 0.0\n        wind: 0.0686308771428057\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Canary\nzone_name: La Palma\n"
  },
  {
    "path": "config/zones/ES-CN-LZ.yaml",
    "content": "bounding_box:\n  - - -13.858338583385802\n    - 28.859405221520007\n  - - -13.458734587345845\n    - 29.147052870944634\ncenter_point:\n  - -13.658536585365823\n  - 29.00322904623232\ncentroid:\n  - -13.63693636936366\n  - 29.021833123060777\ncontributors:\n  - hectorespert\n  - systemcatch\n  - silimotion\n  - t-couery\n  - VIKTORVAV99\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 677.295\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 675.787\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 680.581\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 682.08\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 690.044\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 675.258\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 652.743\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 650.514\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 921.295\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 919.787\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 924.581\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 926.08\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 934.044\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 919.258\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 896.742\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 894.514\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Canary\nzone_name: Lanzarote\n"
  },
  {
    "path": "config/zones/ES-CN-TE.yaml",
    "content": "bounding_box:\n  - - -16.91476914769146\n    - 27.996462273246138\n  - - -16.11916119161188\n    - 28.57175757209538\ncenter_point:\n  - -16.51696516965167\n  - 28.28410992267076\ncentroid:\n  - -16.47196471964717\n  - 28.349326411772715\ncontributors:\n  - hectorespert\n  - systemcatch\n  - silimotion\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 719.318\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 715.641\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 726.572\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 703.665\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 701.384\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 691.569\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE\n        value: 694.468\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE\n        value: 692.128\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 963.318\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 959.641\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 970.572\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 947.665\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 945.384\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 935.569\n      - datetime: '2023-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 938.468\n      - datetime: '2024-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 936.128\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.3942721762784891\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5084693207758296\n        solar: 0.05313294521769942\n        unknown: 0.0\n        wind: 0.044125319731717794\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0018267975669966272\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8058201977756733\n        solar: 0.053076215742941975\n        unknown: 0.0\n        wind: 0.13927672179980005\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7945839455118994\n        solar: 0.05416299647581524\n        unknown: 0.0\n        wind: 0.15125320517059446\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.7858116959053282\n        solar: 0.053992538480540586\n        unknown: 0.0\n        wind: 0.1601957472743555\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8057356447101643\n        solar: 0.048724063248987454\n        unknown: 0.0\n        wind: 0.1455402775411303\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8089046710861777\n        solar: 0.048765228060308745\n        unknown: 0.0\n        wind: 0.1423299486870001\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8098111936581934\n        solar: 0.04704794606775687\n        unknown: 0.0\n        wind: 0.1431409807238982\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Canary\nzone_name: Tenerife\n"
  },
  {
    "path": "config/zones/ES-IB-FO.yaml",
    "content": "bounding_box:\n  - - 1.38421384213845\n    - 38.64228746762315\n  - - 1.582215822158247\n    - 38.749618680095026\ncenter_point:\n  - 1.4832148321483485\n  - 38.69595307385909\ncentroid:\n  - 1.4778147781478097\n  - 38.68414664048718\ncan_have_zero_production: true\ncontributors:\n  - hectorespert\n  - systemcatch\n  - alixunderplatz\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.047100387132375146\n        coal: 0.3287909226511239\n        gas: 0.4561070347729369\n        geothermal: 0.0\n        hydro: 0.022650261680792542\n        hydro discharge: 0.0003944611617420095\n        nuclear: 0.03894603426423294\n        oil: 0.00165544356403204\n        solar: 0.06962562833567568\n        unknown: 0.00083203283296402\n        wind: 0.03341926694889681\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03453468235931871\n        coal: 0.20969626860433424\n        gas: 0.3292688744675957\n        geothermal: 0.0\n        hydro: 0.01760819844136997\n        hydro discharge: 0.00022728881814980216\n        nuclear: 0.040572877212077786\n        oil: 0.2690104458659111\n        solar: 0.06492909226984045\n        unknown: 0.0007806216227631576\n        wind: 0.03327107199798722\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0469291650894959\n        coal: 0.048426277555993935\n        gas: 0.5921111268960613\n        geothermal: 0.0\n        hydro: 0.03101640988578583\n        hydro discharge: 0.00041589635580591123\n        nuclear: 0.05753614303325932\n        oil: 0.08039766632755507\n        solar: 0.09366573260019125\n        unknown: 0.0013539037717661484\n        wind: 0.048238065862651225\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03874107302061008\n        coal: 0.01269418143877278\n        gas: 0.5966426359776449\n        geothermal: 0.0\n        hydro: 0.0188778760192522\n        hydro discharge: 0.0002221677125401792\n        nuclear: 0.029111306821425965\n        oil: 0.20225922075751374\n        solar: 0.07134534112871406\n        unknown: 0.0005570939123494946\n        wind: 0.029364734312615017\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.034275321371517106\n        coal: 0.011097398363273593\n        gas: 0.6397842007084057\n        geothermal: 0.0\n        hydro: 0.0055166321519324844\n        hydro discharge: 0.00021509334420828473\n        nuclear: 0.01513847441618309\n        oil: 0.20053018539628079\n        solar: 0.07597727227602796\n        unknown: 7.721299535682018e-05\n        wind: 0.0167705050139598\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.040868604171072374\n        coal: 0.015244378316868574\n        gas: 0.6961284213467871\n        geothermal: 0.0\n        hydro: 0.01654925455424307\n        hydro discharge: 0.004599716272418758\n        nuclear: 0.04374553135353414\n        oil: 0.006830735224514869\n        solar: 0.13025821223930797\n        unknown: 0.0017929657210758992\n        wind: 0.04364451476793249\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.036515886034502495\n        coal: 0.02270024526765901\n        gas: 0.5853921348164444\n        geothermal: 0.0\n        hydro: 0.02147756768393767\n        hydro discharge: 0.00569502090963447\n        nuclear: 0.03911975581312243\n        oil: 0.10728475743719992\n        solar: 0.13720299574021036\n        unknown: 0.006784750754949078\n        wind: 0.037652333529152336\nhas_day_ahead_price_license: True\nhide_day_ahead_price: False\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021):\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37, https://proceedings.windeurope.org/biplatform/rails/active_storage/disk/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdDRG9JYTJWNVNTSWhORFJ0ZDJJMWVUbG9OMll6TVRaaGEza3lkamgxZG1aM056WnZZZ1k2QmtWVU9oQmthWE53YjNOcGRHbHZia2tpQVk1cGJteHBibVU3SUdacGJHVnVZVzFsUFNKWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtSWpzZ1ptbHNaVzVoYldVcVBWVlVSaTA0SnlkWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtQmpzR1ZEb1JZMjl1ZEdWdWRGOTBlWEJsU1NJVVlYQndiR2xqWVhScGIyNHZjR1JtQmpzR1ZBPT0iLCJleHAiOiIyMDIyLTExLTAyVDE1OjU0OjAzLjEyNFoiLCJwdXIiOiJibG9iX2tleSJ9fQ==--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Madrid\nzone_name: Formentera\n"
  },
  {
    "path": "config/zones/ES-IB-IZ.yaml",
    "content": "bounding_box:\n  - - 1.211412114121174\n    - 38.8326214844066\n  - - 1.621816218162195\n    - 39.10452722266869\ncenter_point:\n  - 1.4166141661416844\n  - 38.96857435353765\ncentroid:\n  - 1.433894338943412\n  - 38.989181946332245\ncan_have_zero_production: true\ncontributors:\n  - hectorespert\n  - systemcatch\n  - alixunderplatz\n  - silimotion\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 618.289\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 590.329\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 583.131\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 635.217\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 581.127\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 570.7\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 738.289\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 710.329\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 703.131\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 755.217\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 701.127\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 690.7\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9768251107774639\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0005149749640335842\n        solar: 0.020929598379349802\n        unknown: 0.001977503861888963\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0112917258329075\n        coal: 0.08157607065119638\n        gas: 0.8807455679404854\n        geothermal: 0.0\n        hydro: 0.005548580564484378\n        hydro discharge: 0.00011696767994553189\n        nuclear: 0.0096008616487973\n        oil: 0.0004104775292249344\n        solar: 0.0028405159451156603\n        unknown: 0.00022116939787927693\n        wind: 0.007644272356256877\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04879513191181075\n        coal: 0.31131600882486776\n        gas: 0.4783351963796621\n        geothermal: 0.0\n        hydro: 0.025752178670769014\n        hydro discharge: 0.0004395892158074925\n        nuclear: 0.05794982475589046\n        oil: 0.0033878705450553015\n        solar: 0.02658548887373031\n        unknown: 0.0011294070017458526\n        wind: 0.04630931783906812\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05534432383554426\n        coal: 0.058583512551889816\n        gas: 0.674900422038957\n        geothermal: 0.0\n        hydro: 0.03910668832707259\n        hydro discharge: 0.0006056769235821019\n        nuclear: 0.06870342274194327\n        oil: 0.00232719194210302\n        solar: 0.04050479432441813\n        unknown: 0.0014525230006464931\n        wind: 0.05846960828725907\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05134066136802477\n        coal: 0.013737139785334683\n        gas: 0.7758055317085241\n        geothermal: 0.0\n        hydro: 0.02764300749559819\n        hydro discharge: 0.000387440894105207\n        nuclear: 0.041186597237440205\n        oil: 0.0014938002072788904\n        solar: 0.0452708723628487\n        unknown: 0.0009033092712146469\n        wind: 0.04222803279427872\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.047371464385007764\n        coal: 0.012914654762840384\n        gas: 0.8322483153795601\n        geothermal: 0.0\n        hydro: 0.008307952553480522\n        hydro discharge: 0.00044056996261453434\n        nuclear: 0.02257294231216907\n        oil: 0.0006846296034897201\n        solar: 0.049677472042985296\n        unknown: 0.0004244217004346928\n        wind: 0.025236689197919996\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04469560858478786\n        coal: 0.012260830541197771\n        gas: 0.7205727934349242\n        geothermal: 0.0\n        hydro: 0.019745829268170093\n        hydro discharge: 0.004812506362432892\n        nuclear: 0.0468567735762213\n        oil: 0.0004514576762126067\n        solar: 0.09810801176307876\n        unknown: 0.002351379639988687\n        wind: 0.050143787075413046\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.041927465225863075\n        coal: 0.010740122474026838\n        gas: 0.7169486251774267\n        geothermal: 0.0\n        hydro: 0.02547104336673067\n        hydro discharge: 0.005914497387727304\n        nuclear: 0.04549354498417642\n        oil: 0.0007620359293831895\n        solar: 0.09853247752804309\n        unknown: 0.009190009928075097\n        wind: 0.045019652943978444\nhas_day_ahead_price_license: True\nhide_day_ahead_price: False\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021):\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37, https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Madrid\nzone_name: Ibiza\n"
  },
  {
    "path": "config/zones/ES-IB-MA.yaml",
    "content": "bounding_box:\n  - - 2.356223562235641\n    - 39.269101748458894\n  - - 3.475834758347617\n    - 39.96890125377551\ncenter_point:\n  - 2.916029160291629\n  - 39.619001501117204\ncentroid:\n  - 2.9300693006930287\n  - 39.60798216330343\ncontributors:\n  - hectorespert\n  - systemcatch\n  - alixunderplatz\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 378.09\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 411.09\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07122152616715648\n        coal: 0.12464303900403434\n        gas: 0.7423309282453295\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05906647269796483\n        unknown: 0.0027348597549728994\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0779828345111624\n        coal: 0.5745875990810352\n        gas: 0.30533280600658397\n        geothermal: 0.0\n        hydro: 0.005451131532608672\n        hydro discharge: 0.0001147784099435192\n        nuclear: 0.008630084428583323\n        oil: 0.00039149472480271724\n        solar: 0.019386543100322836\n        unknown: 0.00021445159818918883\n        wind: 0.007906220027288167\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06348449933298395\n        coal: 0.40867670360766534\n        gas: 0.3103177616116432\n        geothermal: 0.0\n        hydro: 0.033848729815283786\n        hydro discharge: 0.0006003944996412882\n        nuclear: 0.07816460712114892\n        oil: 0.0032108301437382314\n        solar: 0.03882154513788825\n        unknown: 0.0015074853570028874\n        wind: 0.06136858957339723\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06064061594355012\n        coal: 0.062023072478291405\n        gas: 0.6344790845972432\n        geothermal: 1.622966670602271e-08\n        hydro: 0.045794420126437814\n        hydro discharge: 0.0007656345268566212\n        nuclear: 0.0779195360120061\n        oil: 0.0024327972848438425\n        solar: 0.048567580571551465\n        unknown: 0.0016464996873260039\n        wind: 0.06573084533011588\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05548427795173568\n        coal: 0.015094448787273751\n        gas: 0.7627411734645679\n        geothermal: 7.342291254988475e-09\n        hydro: 0.028253670289026842\n        hydro discharge: 0.00042218419459225565\n        nuclear: 0.04199017944070341\n        oil: 0.0010566682933920847\n        solar: 0.051818262138398276\n        unknown: 0.0009148666223844922\n        wind: 0.04222429084479915\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.054457642540701005\n        coal: 0.02092173057432375\n        gas: 0.803533465675946\n        geothermal: 0.0\n        hydro: 0.009124431009617408\n        hydro discharge: 0.00040786682870327847\n        nuclear: 0.02398774628622767\n        oil: 0.00044778627683124357\n        solar: 0.060264664142214805\n        unknown: 0.0004526765480288947\n        wind: 0.026401690305139065\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05657796804660899\n        coal: 0.019192670389106985\n        gas: 0.6475564979832881\n        geothermal: 2.219856471850028e-09\n        hydro: 0.024660718524252737\n        hydro discharge: 0.00672530824510745\n        nuclear: 0.06114652589964817\n        oil: 0.0005987530067262206\n        solar: 0.11779851728016748\n        unknown: 0.0029865327412458152\n        wind: 0.0627562015436549\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 2.2719854615300786e-07\n        biomass: 0.06116456845313932\n        coal: 0.014264431337069037\n        gas: 0.5929408301932747\n        geothermal: 1.0923007026586914e-08\n        hydro: 0.037749925391492814\n        hydro discharge: 0.009220208538205252\n        nuclear: 0.06852106076344723\n        oil: 0.0011714772113916093\n        solar: 0.1366875017345735\n        unknown: 0.010697864190356308\n        wind: 0.06758167342075513\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.119\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 1.0\nisRenewable:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.1027\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 1.0\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Madrid\nzone_name: Mallorca\n"
  },
  {
    "path": "config/zones/ES-IB-ME.yaml",
    "content": "bounding_box:\n  - - 3.821438214382169\n    - 39.821499721980814\n  - - 4.300243002430051\n    - 40.05905947225189\ncenter_point:\n  - 4.06084060840611\n  - 39.94027959711635\ncentroid:\n  - 4.069120691206939\n  - 39.96689773780937\ncapacity:\n  biomass:\n    - datetime: '2023-12-31'\n      source: ree.es\n      value: 0\n  coal:\n    - datetime: '2023-12-31'\n      source: ree.es\n      value: 0\n  gas:\n    - datetime: '2023-12-31'\n      source: ree.es\n      value: 0\n  geothermal:\n    - datetime: '2023-12-31'\n      source: ree.es\n      value: 0\n  hydro:\n    - datetime: '2023-12-31'\n      source: ree.es\n      value: 0\n  nuclear:\n    - datetime: '2023-12-31'\n      source: ree.es\n      value: 0\n  oil:\n    - datetime: '2018-05-01'\n      source: ime.cat\n      value: 271.6\n  solar:\n    - datetime: '2018-05-01'\n      source: ime.cat\n      value: 5.1\n    - datetime: '2023-05-01'\n      source: ime.cat, menorca.info\n      value: 50.8\n  wind:\n    - datetime: '2018-05-01'\n      source: ime.cat\n      value: 3.2\n    - datetime: '2023-12-31'\n      source: ree.es\n      value: 0\ncontributors:\n  - hectorespert\n  - systemcatch\n  - alixunderplatz\n  - silimotion\n  - hectodium\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE\n        value: 773.092\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE\n        value: 814.399\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE\n        value: 812.544\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE\n        value: 777.284\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE\n        value: 781.398\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE\n        value: 838.759\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1235.586989\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2017-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 1017.092\n      - datetime: '2018-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 1058.399\n      - datetime: '2019-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 1056.544\n      - datetime: '2020-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 1021.284\n      - datetime: '2021-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 1025.398\n      - datetime: '2022-01-01'\n        source: EU-ETS, REE; IPCC 2014\n        value: 1082.759\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6207486973241648\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.28966987689823204\n        solar: 0.07355103679068013\n        unknown: 0.0\n        wind: 0.016037705854312342\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9250933021176478\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.03468602527539667\n        unknown: 0.0\n        wind: 0.040304256542921586\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9418028148434132\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0035349688854402882\n        solar: 0.030714822408781168\n        unknown: 0.0\n        wind: 0.02394739386236535\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.014994493159378494\n        coal: 0.0257142889589026\n        gas: 0.8267695032618773\n        geothermal: 0.0\n        hydro: 0.010339723085439737\n        hydro discharge: 0.00018271462288974922\n        nuclear: 0.019745312431545523\n        oil: 0.005143144684220779\n        solar: 0.057796813091188955\n        unknown: 0.0004146791146905725\n        wind: 0.03884631225767675\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.018141043074065933\n        coal: 0.005543203920393808\n        gas: 0.8693813775953567\n        geothermal: 0.0\n        hydro: 0.01054033312629362\n        hydro discharge: 0.0001662947364262957\n        nuclear: 0.014718833675383925\n        oil: 0.004715505478679535\n        solar: 0.0502592692396035\n        unknown: 0.0003048736834482089\n        wind: 0.026175905669817194\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011010879749139224\n        coal: 0.002936872987338105\n        gas: 0.9341435322750186\n        geothermal: 0.0\n        hydro: 0.0021430090293537577\n        hydro discharge: 0.00012077132075191381\n        nuclear: 0.005446519603837569\n        oil: 8.003058688942293e-05\n        solar: 0.03373498164229497\n        unknown: 7.326948219571896e-05\n        wind: 0.010250357032756017\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010828480646211289\n        coal: 0.003002860457315108\n        gas: 0.6105729857307653\n        geothermal: 0.0\n        hydro: 0.004859165713499271\n        hydro discharge: 0.0012599712741476166\n        nuclear: 0.011751957582299842\n        oil: 0.2909404591382946\n        solar: 0.05125209256652933\n        unknown: 0.0005842060588349988\n        wind: 0.014924742238317957\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009642452916333841\n        coal: 0.002599544945958682\n        gas: 0.09507536077858454\n        geothermal: 0.0\n        hydro: 0.00648241679171353\n        hydro discharge: 0.001622656195062216\n        nuclear: 0.010901195312007348\n        oil: 0.6829632661733087\n        solar: 0.1665956294197355\n        unknown: 0.001631594221039395\n        wind: 0.022478089603296073\nhas_day_ahead_price_license: True\nhide_day_ahead_price: False\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, REE:\n    link: https://colab.research.google.com/github/silimotion/Emission_factors_research/blob/main/Spanish_non_peninsular_factors.ipynb\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021):\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37, https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Madrid\nzone_name: Menorca\n"
  },
  {
    "path": "config/zones/ES-ML.yaml",
    "content": "bounding_box:\n  - - -2.970256683510813\n    - 35.26572463778479\n  - - -2.926766941365234\n    - 35.3209422034335\ncenter_point:\n  - -2.9485118124380234\n  - 35.293333420609144\ncentroid:\n  - -2.9483281088581914\n  - 35.2899607062312\ncapacity:\n  biomass:\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 1.0\n  gas:\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 12.0\n  oil:\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 64.0\n  solar:\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 0.0\n  unknown:\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 1.0\ncontributors:\n  - VIKTORVAV99\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 375.83\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 375.83\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 375.01\n      - _comment: used non-null storage values\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 377.19\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 376.11\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 374.12\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 408.83\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 408.83\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 408.01\n      - _comment: used non-null storage values\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 410.19\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 409.11\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 407.12\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07502462217888135\n        coal: 0.0\n        gas: 8.917144295971451e-05\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9248783467157186\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07107893270299667\n        coal: 0.0\n        gas: 0.0002213449138309281\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9286989174925765\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07349749030325115\n        coal: 0.0\n        gas: 0.0012876318227207154\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.9252105767656325\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.0743\n    - datetime: '2021-01-01'\n      value: 0.0743\n    - datetime: '2022-01-01'\n      value: 0.0763\n    - datetime: '2023-01-01'\n      value: 0.0709\n    - datetime: '2024-01-01'\n      value: 0.0735\n    - datetime: '2025-01-01'\n      value: 0.0785\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.0743\n    - datetime: '2021-01-01'\n      value: 0.0743\n    - datetime: '2022-01-01'\n      value: 0.0763\n    - datetime: '2023-01-01'\n      value: 0.0709\n    - datetime: '2024-01-01'\n      value: 0.0735\n    - datetime: '2025-01-01'\n      value: 0.0785\nparsers:\n  consumption: ES.fetch_consumption\n  production: ES.fetch_production\n  productionCapacity: REE.fetch_production_capacity\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Europe/Madrid\nzone_name: Melilla\n"
  },
  {
    "path": "config/zones/ES.yaml",
    "content": "_comment: 'Hydro capacity from IRENA includes pumped storage generation capacity.\n  Note: ENTSO-E (not used for hydro capacity) lists 5645 MW for pumped storage CONSUMPTION\n  capacity.'\nbounding_box:\n  - - -9.293492934929333\n    - 36.00623288931391\n  - - 3.317433174331768\n    - 43.76270184394805\ncenter_point:\n  - -2.930449175092898\n  - 39.92267065800313\ncentroid:\n  - -4.034615295817258\n  - 40.571071296247744\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: ree.es\n      value: 1009.0\n    - datetime: '2018-01-01'\n      source: ree.es\n      value: 1007.0\n    - datetime: '2019-01-01'\n      source: ree.es\n      value: 1010.0\n    - datetime: '2020-01-01'\n      source: ree.es\n      value: 1210.0\n    - datetime: '2022-01-01'\n      source: ree.es\n      value: 1225.0\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 1219.0\n    - datetime: '2023-01-01'\n      source: ree.es\n      value: 1226.0\n    - datetime: '2024-01-01'\n      source: ree.es\n      value: 1230.0\n    - datetime: '2024-09-01'\n      source: ree.es\n      value: 1222.0\n    - datetime: '2025-01-01'\n      source: ree.es\n      value: 1231.0\n  coal:\n    - datetime: '2017-01-01'\n      source: ree.es\n      value: 9562.0\n    - datetime: '2020-01-01'\n      source: ree.es\n      value: 9215.0\n    - datetime: '2021-01-01'\n      source: ree.es\n      value: 5144.0\n    - datetime: '2022-01-01'\n      source: ree.es\n      value: 3523.0\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 3223.0\n    - datetime: '2024-01-01'\n      source: ree.es\n      value: 1820.0\n  gas:\n    - datetime: '2017-01-01'\n      source: ree.es\n      value: 30949.0\n    - datetime: '2018-01-01'\n      source: ree.es\n      value: 30788.0\n    - datetime: '2019-01-01'\n      source: ree.es\n      value: 30330.0\n    - datetime: '2020-01-01'\n      source: ree.es\n      value: 30222.0\n    - datetime: '2021-01-01'\n      source: ree.es\n      value: 30202.0\n    - datetime: '2022-01-01'\n      source: ree.es\n      value: 30154.0\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 30160.0\n    - datetime: '2023-01-01'\n      source: ree.es\n      value: 30140.0\n    - datetime: '2023-12-01'\n      source: ree.es\n      value: 30152.0\n    - datetime: '2024-01-01'\n      source: ree.es\n      value: 30132.0\n    - datetime: '2024-09-01'\n      source: ree.es\n      value: 30088.0\n    - datetime: '2025-01-01'\n      source: ree.es\n      value: 30076.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: ree.es\n      value: 17048.0\n    - datetime: '2018-01-01'\n      source: ree.es\n      value: 17056.0\n    - datetime: '2019-01-01'\n      source: ree.es\n      value: 17063.0\n    - datetime: '2020-01-01'\n      source: ree.es\n      value: 17097.0\n    - datetime: '2022-01-01'\n      source: ree.es\n      value: 17092.0\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 17093.0\n    - datetime: '2023-01-01'\n      source: ree.es\n      value: 17092.0\n    - datetime: '2023-12-01'\n      source: ree.es\n      value: 17096.0\n    - datetime: '2024-09-01'\n      source: ree.es\n      value: 17097.0\n    - datetime: '2025-01-01'\n      source: ree.es\n      value: 17095.0\n  hydro storage:\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 3331.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: ree.es\n      value: 7573.0\n    - datetime: '2018-01-01'\n      source: ree.es\n      value: 7117.0\n  solar:\n    - datetime: '2017-01-01'\n      source: ree.es\n      value: 6746.0\n    - datetime: '2018-01-01'\n      source: ree.es\n      value: 6748.0\n    - datetime: '2019-01-01'\n      source: ree.es\n      value: 6887.0\n    - datetime: '2020-01-01'\n      source: ree.es\n      value: 10952.0\n    - datetime: '2021-01-01'\n      source: ree.es\n      value: 13887.0\n    - datetime: '2022-01-01'\n      source: ree.es\n      value: 17758.0\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 21815.0\n    - datetime: '2023-01-01'\n      source: ree.es\n      value: 22317.0\n    - datetime: '2023-12-01'\n      source: ree.es\n      value: 26866.0\n    - datetime: '2024-01-01'\n      source: ree.es\n      value: 28155.0\n    - datetime: '2024-09-01'\n      source: ree.es\n      value: 30070.0\n    - datetime: '2025-01-01'\n      source: ree.es\n      value: 34807.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: ree.es\n      value: 410.0\n    - datetime: '2019-01-01'\n      source: ree.es\n      value: 404.0\n    - datetime: '2021-01-01'\n      source: ree.es\n      value: 394.0\n    - datetime: '2022-01-01'\n      source: ree.es\n      value: 407.0\n    - datetime: '2022-12-01'\n      source: ree.es\n      value: 387.0\n  wind:\n    - datetime: '2017-01-01'\n      source: ree.es\n      value: 22818.0\n    - datetime: '2018-01-01'\n      source: ree.es\n      value: 22856.0\n    - datetime: '2019-01-01'\n      source: ree.es\n      value: 23050.0\n    - datetime: '2020-01-01'\n      source: ree.es\n      value: 25299.0\n    - datetime: '2021-01-01'\n      source: ree.es\n      value: 27222.0\n    - datetime: '2022-01-01'\n      source: ree.es\n      value: 28147.0\n    - datetime: '2023-01-01'\n      source: ree.es\n      value: 29597.0\n    - datetime: '2024-01-01'\n      source: ree.es\n      value: 30202.0\n    - datetime: '2024-09-01'\n      source: ree.es\n      value: 30848.0\n    - datetime: '2025-01-01'\n      source: ree.es\n      value: 31558.0\ncontributors:\n  - brandongalbraith\n  - corradio\n  - JosepRey\n  - nessie2013\n  - KabelWlan\n  - gadakast\n  - silimotion\ncountry: ES\ncountry_name: Spain\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 94.75\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 971.2573613\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1156.28\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1323.69\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1474.31\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 397.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 426.61\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 391.0\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 411.76\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 127.8\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 114.03\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 161.38\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 89.35\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 66.98\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 66.6\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 127.75\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1050.5643503\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1235.586989\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1383.69\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1534.31\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 517.8527093\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 546.61\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 511.0\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 531.76\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 138.5\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 124.73\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 172.08\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 100.05\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 77.68\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 77.3\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.46666667\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.024729649400220714\n        coal: 0.1994616304155791\n        gas: 0.17218400015166174\n        geothermal: 2.198311266629953e-09\n        hydro: 0.11872036535138755\n        hydro discharge: 0.0006690508615017283\n        nuclear: 0.23362247644985304\n        oil: 0.011211442158969569\n        solar: 0.049283682351388296\n        unknown: 0.0049796422247172165\n        wind: 0.1851380786522526\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.017400934688113337\n        coal: 0.14331242065540795\n        gas: 0.16420663715253075\n        geothermal: 4.193977272960315e-08\n        hydro: 0.15796575968235974\n        hydro discharge: 0.0019735377153009864\n        nuclear: 0.23805408139777148\n        oil: 0.007506006992952079\n        solar: 0.048069953377326946\n        unknown: 0.03468219368922021\n        wind: 0.18682842995981014\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.023015091519529254\n        coal: 0.16668716475431047\n        gas: 0.22463709206003474\n        geothermal: 6.449483266451862e-08\n        hydro: 0.08581599719397405\n        hydro discharge: 0.0019789633348285015\n        nuclear: 0.2496264346030768\n        oil: 0.009991674107747659\n        solar: 0.050937004871962226\n        unknown: 0.0049316007134213415\n        wind: 0.18237892063786448\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02267357199384772\n        coal: 0.13896092256403358\n        gas: 0.20046947358321585\n        geothermal: 9.840576150165949e-08\n        hydro: 0.1461829187742981\n        hydro discharge: 0.002091950140087699\n        nuclear: 0.23977052424960207\n        oil: 0.009677599917589878\n        solar: 0.04734434788696264\n        unknown: 0.005163535750377489\n        wind: 0.1876655284088785\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.021771103950726196\n        coal: 0.05022243156408891\n        gas: 0.3016723417409685\n        geothermal: 1.4055437245550039e-07\n        hydro: 0.10802383919051498\n        hydro discharge: 0.0017960778374877034\n        nuclear: 0.24260404819576742\n        oil: 0.010267876452541808\n        solar: 0.05651426616336851\n        unknown: 0.004751562010365605\n        wind: 0.20237967698971446\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02576827866712645\n        coal: 0.023607331705812987\n        gas: 0.2526592508167033\n        geothermal: 3.0734846489594417e-07\n        hydro: 0.14329854749826237\n        hydro discharge: 0.002217640810817146\n        nuclear: 0.24710451697657643\n        oil: 0.007858895521571367\n        solar: 0.07968550207592087\n        unknown: 0.005253555420144353\n        wind: 0.21254710422988102\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.026640656060872535\n        coal: 0.023840181681251883\n        gas: 0.24311283363171848\n        geothermal: 3.5805972922516003e-07\n        hydro: 0.13366995471981147\n        hydro discharge: 0.0018254614521521313\n        nuclear: 0.23634869619778442\n        oil: 0.006093148634704813\n        solar: 0.0970068985783964\n        unknown: 0.0052135481180964\n        wind: 0.22625003432970137\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02417940102379467\n        coal: 0.03167067915640569\n        gas: 0.29359839141497335\n        geothermal: 1.3966246582519656e-07\n        hydro: 0.08560146570345804\n        hydro discharge: 0.0021860739145060115\n        nuclear: 0.21761637973263062\n        oil: 0.004806834810618121\n        solar: 0.1134580482981864\n        unknown: 0.004153899254812183\n        wind: 0.22272960812827403\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.582561381478141e-08\n        biomass: 0.02119811414731427\n        coal: 0.016498111700538474\n        gas: 0.21665544741923332\n        geothermal: 8.855329613811202e-08\n        hydro: 0.09998060227334997\n        hydro discharge: 0.02475308946481042\n        nuclear: 0.22788206649074313\n        oil: 0.0019438668082859436\n        solar: 0.1493495611633502\n        unknown: 0.003208766517987543\n        wind: 0.23853026275286915\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.974680316284894e-06\n        biomass: 0.021322223365164414\n        coal: 0.012427550821610487\n        gas: 0.1687859255264439\n        geothermal: 1.148201639768602e-07\n        hydro: 0.1328782484019404\n        hydro discharge: 0.028592418529992846\n        nuclear: 0.22669515472484764\n        oil: 0.0014104071615737561\n        solar: 0.17259103779609025\n        unknown: 0.0033878554452865988\n        wind: 0.231907080406899\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.7723\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.7211\n    - datetime: '2021-01-01'\n      value: 0.7519\n    - datetime: '2022-01-01'\n      value: 0.6802\n    - datetime: '2023-01-01'\n      value: 0.8129\n    - datetime: '2024-01-01'\n      value: 0.8709\n    - datetime: '2025-01-01'\n      value: 0.8533\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.5509\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4667\n    - datetime: '2021-01-01'\n      value: 0.5088\n    - datetime: '2022-01-01'\n      value: 0.461\n    - datetime: '2023-01-01'\n      value: 0.5891\n    - datetime: '2024-01-01'\n      value: 0.6584\n    - datetime: '2025-01-01'\n      value: 0.6595\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: REE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Madrid\nzone_name: Spain\n"
  },
  {
    "path": "config/zones/ET.yaml",
    "content": "bounding_box:\n  - - 32.9889298892989\n    - 3.404734871690188\n  - - 47.97947979479795\n    - 14.879157026350086\ncenter_point:\n  - 40.425691433080274\n  - 9.06938123819799\ncentroid:\n  - 38.221270674245226\n  - 9.428327640554063\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3820.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 4070.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4820.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4880.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 320.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 400.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 320.0\ncountry: ET\ncountry_name: Ethiopia\ncurrency: ETB\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.967351083721048\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00011531725941540038\n        solar: 0.0020188273051168775\n        unknown: 0.0\n        wind: 0.030514389273255144\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9673517111090494\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00011535583671568062\n        solar: 0.002018939705847075\n        unknown: 0.0\n        wind: 0.030513859522903735\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Addis_Ababa\nzone_name: Ethiopia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/FI.yaml",
    "content": "bounding_box:\n  - - 20.549205472874075\n    - 59.81086473274276\n  - - 31.570515705157078\n    - 70.07029756222104\ncenter_point:\n  - 26.323970083708076\n  - 64.96030393692205\ncentroid:\n  - 25.28410780108274\n  - 65.08244089552896\ncapacity:\n  biomass:\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1947.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1782.0\n  coal:\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2608.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 2454.0\n  gas:\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1780.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1742.0\n  hydro:\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 3167.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 3173.0\n  nuclear:\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2794.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 4364.0\n  oil:\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1051.0\n  solar:\n    - datetime: '2023-01-01'\n      source: fingrid.fi\n      value: 606\n    - datetime: '2023-12-31'\n      source: fingrid.fi\n      value: 1018\n    - datetime: '2024-11-17'\n      source: fingrid.fi\n      value: 1109\n    - datetime: '2025-02-10'\n      source: fingrid.fi\n      value: 1256\n    - datetime: '2025-05-09'\n      source: fingrid.fi\n      value: 1367\n    - datetime: '2025-07-07'\n      source: fingrid.fi\n      value: 1485\n    - datetime: '2025-10-15'\n      source: fingrid.fi\n      value: 1512\n    - datetime: '2026-03-13'\n      source: fingrid.fi\n      value: 1575\n  unknown:\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 828.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 840.0\n  wind:\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 5121.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 6618.0\n    - datetime: '2024-02-01'\n      source: fingrid.fi\n      value: 6931.8\n    - datetime: '2024-11-17'\n      source: fingrid.fi\n      value: 8092\n    - datetime: '2025-01-23'\n      source: fingrid.fi\n      value: 8411\n    - datetime: '2025-06-10'\n      source: fingrid.fi\n      value: 8760\n    - datetime: '2025-07-07'\n      source: fingrid.fi\n      value: 8885\n    - datetime: '2025-10-15'\n      source: fingrid.fi\n      value: 9237\n    - datetime: '2026-03-13'\n      source: fingrid.fi\n      value: 9413\ncontributors:\n  - corradio\n  - nessie2013\n  - gadakast\n  - pnook\ncountry: FI\ncountry_name: Finland\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 895.6862569\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 754.07\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 757.91\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 893.19\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 295.9885661\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 295.99\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 476.61\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 371.46\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 990.5340999\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 848.9178430000001\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 817.91\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 953.19\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 415.9885661\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 415.99\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 596.61\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 491.46\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    wind:\n      datetime: '2012-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0938821239040481\n        coal: 0.10669939402322381\n        gas: 0.06201808207489409\n        geothermal: 0.0\n        hydro: 0.2702345304269363\n        hydro discharge: 6.363999422749549e-06\n        nuclear: 0.34945959571186447\n        oil: 0.00022226400130939713\n        solar: 0.000532382186861179\n        unknown: 0.06701517114168964\n        wind: 0.0499389669479236\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07979658832193824\n        coal: 0.12230601432453067\n        gas: 0.04298119833087339\n        geothermal: 0.0\n        hydro: 0.2449003620404438\n        hydro discharge: 6.628845081447931e-06\n        nuclear: 0.34564377496195064\n        oil: 0.0002557686261622299\n        solar: 0.0005629350639445627\n        unknown: 0.10749539270237181\n        wind: 0.056064694001174496\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08794025391580078\n        coal: 0.12126421236147042\n        gas: 0.050765310731352487\n        geothermal: 3.49864431543418e-08\n        hydro: 0.27591481873164303\n        hydro discharge: 1.892071721946129e-06\n        nuclear: 0.31017196704035294\n        oil: 0.00024822893608403816\n        solar: 0.0007617606801273658\n        unknown: 0.06927001756470363\n        wind: 0.08366142971600632\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07801409727778828\n        coal: 0.1269025536027467\n        gas: 0.05940542908308375\n        geothermal: 4.372542079287888e-08\n        hydro: 0.2429689676644934\n        hydro discharge: 2.11845447791835e-06\n        nuclear: 0.31287620967344787\n        oil: 0.0002246427823109982\n        solar: 0.0006362298068672531\n        unknown: 0.08673230403452678\n        wind: 0.09223772623430179\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07412906127284172\n        coal: 0.10310914015841025\n        gas: 0.05488007971522546\n        geothermal: 7.82766215768681e-08\n        hydro: 0.24458184046571266\n        hydro discharge: 2.3442844615841525e-06\n        nuclear: 0.3394657153777757\n        oil: 0.00019317428316463337\n        solar: 0.0008488759658658023\n        unknown: 0.07993983796351463\n        wind: 0.10285042463420137\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07439408261571256\n        coal: 0.07112419572734865\n        gas: 0.05136623673811213\n        geothermal: 5.431300680591825e-08\n        hydro: 0.3099043641752685\n        hydro discharge: 0.00012992942947159393\n        nuclear: 0.3211467846062323\n        oil: 0.00021734303462775997\n        solar: 0.0007872234507755919\n        unknown: 0.03948254647744252\n        wind: 0.131447383957588\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07619530262504165\n        coal: 0.08179509626708058\n        gas: 0.0479744828131899\n        geothermal: 5.092293008236449e-08\n        hydro: 0.2752949478612634\n        hydro discharge: 8.930587285681925e-05\n        nuclear: 0.3094938886004483\n        oil: 0.00034740621632779045\n        solar: 0.00021118293955484327\n        unknown: 0.08500980708434848\n        wind: 0.12358918438344557\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07398647752681636\n        coal: 0.09039066518055783\n        gas: 0.022407024643433793\n        geothermal: 2.2023919487113752e-08\n        hydro: 0.2784278803973507\n        hydro discharge: 1.616094111203222e-05\n        nuclear: 0.32754849336283665\n        oil: 0.0005513165999759593\n        solar: 0.0004846672081771715\n        unknown: 0.04117073607548343\n        wind: 0.16501660971539792\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06521986292526186\n        coal: 0.051448471808842176\n        gas: 0.022207284673493203\n        geothermal: 5.034960502641137e-08\n        hydro: 0.2465395310815344\n        hydro discharge: 2.3468334141273796e-05\n        nuclear: 0.40720727663539685\n        oil: 9.869011544595521e-05\n        solar: 0.01063062980069732\n        unknown: 0.010701879513555073\n        wind: 0.18592282833178803\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07638071549553743\n        coal: 0.03500728593466532\n        gas: 0.015270931279160457\n        geothermal: 4.801148511938404e-08\n        hydro: 0.22058946776480864\n        hydro discharge: 2.6659738262889315e-05\n        nuclear: 0.3758105564651526\n        oil: 7.819647905125822e-05\n        solar: 0.015558684526736201\n        unknown: 0.02072893283843738\n        wind: 0.24054849102643136\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: FI.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Helsinki\nzone_name: Finland\n"
  },
  {
    "path": "config/zones/FJ.yaml",
    "content": "bounding_box:\n  - - -180\n    - -19.12909541607167\n  - - 180\n    - -16.14958095785243\ncenter_point:\n  - 177.95966237664243\n  - -17.776480004044934\ncentroid:\n  - 150.3533245858774\n  - -17.34634280695111\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 170.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\ncountry: FJ\ncountry_name: Fiji\ncurrency: FJD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Fiji\nzone_name: Fiji\n"
  },
  {
    "path": "config/zones/FK.yaml",
    "content": "bounding_box:\n  - - -61.12321123211227\n    - -52.310181981043506\n  - - -57.78237782377819\n    - -51.278371258480554\ncenter_point:\n  - -59.470794707947036\n  - -51.83792464616726\ncentroid:\n  - -59.36009360093596\n  - -51.74448144209703\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: FK\ncountry_name: Falkland Islands\ncurrency: FKP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: Atlantic/Stanley\nzone_name: Falkland Islands\n"
  },
  {
    "path": "config/zones/FM.yaml",
    "content": "bounding_box:\n  - - 158.1261812618126\n    - 6.794970102968477\n  - - 158.29178291782918\n    - 6.938078386264309\ncenter_point:\n  - 158.2089820898209\n  - 6.866524244616393\ncentroid:\n  - 158.23658236582366\n  - 6.880358045334991\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 0.73\n  oil:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 32.17\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 37.07\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 38.87\n  solar:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 1.73\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 2.5\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 2.9\n  wind:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 0.83\ncountry: FM\ncountry_name: Micronesia\ncurrency: USD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Chuuk\nzone_name: Micronesia\n"
  },
  {
    "path": "config/zones/FO-MI.yaml",
    "content": "bounding_box:\n  - - -7.463117272061591\n    - 61.748550888568346\n  - - -6.405608910181027\n    - 62.39259194164544\ncenter_point:\n  - -6.934363091121309\n  - 62.0705714151069\ncentroid:\n  - -6.87261917103823\n  - 62.14598822338982\ncapacity:\n  biomass: 1.3\n  hydro: 37.3\n  oil: 86.1\n  unknown: 0.1\n  wind: 37.5\ncontributors:\n  - corradio\n  - q--\n  - VIKTORVAV99\n  - amv213\ncountry: FO\ncountry_name: Faroe Islands\ncurrency: DKK\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 481.60707\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n    unknown:\n      comment: Data reflects Ocean (tidal) direct emissions from table A.III.2\n      source: IPCC 2014\n      value: 0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1168.890109\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1144.294608\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    unknown:\n      comment: Data reflects median Ocean (tidal) lifecycle emissions from table A.III.2\n      source: IPCC 2014\n      value: 17\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.015358770249353101\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.32013528405183933\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4716367064030261\n        solar: 0.0\n        unknown: 1.2556994099172868e-05\n        wind: 0.19285617699004856\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010851775017550648\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.23049654152193183\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5023903760386292\n        solar: 0.0\n        unknown: 1.6916288038008052e-05\n        wind: 0.25624515141645876\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01747571033546078\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.246998157847731\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.43595547729955675\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.29956949622511475\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  unknown:\n    value: 1\nisRenewable:\n  unknown:\n    value: 1\nparsers:\n  production: FO.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Faroe\nzone_name: Main Islands\n"
  },
  {
    "path": "config/zones/FO-SI.yaml",
    "content": "bounding_box:\n  - - -6.988389900229108\n    - 61.39207339559458\n  - - -6.668657472558352\n    - 61.6530567252827\ncenter_point:\n  - -6.82852368639373\n  - 61.52256506043864\ncentroid:\n  - -6.8038229048162115\n  - 61.530854520581684\ncapacity:\n  hydro: 3.3\n  oil: 13.6\n  solar: 0.24\n  wind: 6\ncontributors:\n  - corradio\n  - q--\n  - VIKTORVAV99\n  - amv213\ncountry: FO\ncountry_name: Faroe Islands\ncurrency: DKK\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 481.60707\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n    unknown:\n      comment: Data reflects median Ocean (tidal) lifecycle emissions from table A.III.2\n      source: IPCC 2014\n      value: 0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1168.890109\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1144.294608\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    unknown:\n      comment: Data reflects median Ocean (tidal) lifecycle emissions from table A.III.2\n      source: IPCC 2014\n      value: 17\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.132198084846763\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5297837798007383\n        solar: 0.0045826520006905765\n        unknown: 0.0\n        wind: 0.3334277688972878\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.11800670796717387\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4408138238297388\n        solar: 0.005933823038562434\n        unknown: 0.0\n        wind: 0.43524042559796317\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.050524812072244754\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.46860447661480964\n        solar: 0.004961919576653245\n        unknown: 0.0\n        wind: 0.475904117942365\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  production: FO.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Faroe\nzone_name: South Island\nisRenewable:\n  unknown:\n    value: 1\nisLowCarbon:\n  unknown:\n    value: 1\n"
  },
  {
    "path": "config/zones/FO.yaml",
    "content": "bounding_box:\n  - - -7.463117272061591\n    - 61.39207339559458\n  - - -6.405608910181027\n    - 62.39259194164544\ncenter_point:\n  - -6.934363091121309\n  - 61.892332668620014\ncentroid:\n  - -6.847347073242383\n  - 61.920020740725604\ncapacity:\n  biomass: 1.3\n  hydro: 40.6\n  oil: 99.7\n  solar: 0.24\n  unknown: 0.1\n  wind: 43.5\ncontributors:\n  - corradio\n  - q--\n  - amv213\ncountry: FO\ncountry_name: Faroe Islands\ncurrency: DKK\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1045.58\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 481.60707\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 449.46\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n    unknown:\n      comment: Data reflects Ocean (tidal) direct emissions from table A.III.2\n      source: IPCC 2014\n      value: 0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1168.890109\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1157.207343\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 569.46\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    unknown:\n      comment: Data reflects median Ocean (tidal) lifecycle emissions from table A.III.2\n      source: IPCC 2014\n      value: 17\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.2685630274166093\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.6178784421667692\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.1133928104338448\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01733172985203319\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.237708660836947\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.6117476901021067\n        solar: 0.0004114547212078257\n        unknown: 1.4446059177202655e-05\n        wind: 0.13272450542005115\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.014026584643601712\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.3038274056372337\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4766720066202257\n        solar: 0.0003974045924400508\n        unknown: 1.1444735403255254e-05\n        wind: 0.20506418466043658\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00998756171580095\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.22153216131807327\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.49746346910044176\n        solar: 0.0004717713489983989\n        unknown: 1.5547855248811606e-05\n        wind: 0.27053075698155554\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.016165896296414132\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.23226413273678534\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4383898553239989\n        solar: 0.000371762432307948\n        unknown: 0.0\n        wind: 0.3128075908110926\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  unknown:\n    value: 1\nisRenewable:\n  unknown:\n    value: 1\nparsers:\n  production: FO.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\nsubZoneNames:\n  - FO-MI\n  - FO-SI\ntimezone: Atlantic/Faroe\nzone_name: Faroe Islands\n"
  },
  {
    "path": "config/zones/FR-COR.yaml",
    "content": "bounding_box:\n  - - 8.559085590855943\n    - 41.372793512907634\n  - - 9.55269552695529\n    - 42.99134819698351\ncenter_point:\n  - 9.055890558905617\n  - 42.18207085494557\ncentroid:\n  - 9.053250532505347\n  - 42.16771232385489\ncapacity:\n  biomass: 2.295\n  gas: 250\n  geothermal: 0\n  hydro: 223.266\n  oil: 224\n  solar: 145.123\n  wind: 18\ncontributors:\n  - PETILLON-Sebastien\n  - VIKTORVAV99\ncountry: FR\ncountry_name: France\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 363.08\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 440.34\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 483.7\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 854.4786144\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 869.45\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 380.5979557\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 381.61\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 769.5956561\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 755.44\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 396.08\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 473.34\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 516.7\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 953.9335274\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 968.9049130000001\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 500.5979557\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 501.61\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1013.5956561\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 999.44\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0059976628024861894\n        coal: 0.0\n        gas: 0.5631649554016566\n        geothermal: 0.0\n        hydro: 0.30789349698414337\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.10113321060044624\n        unknown: 0.0\n        wind: 0.021809897668649394\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005089517683437944\n        coal: 3.856300038486876e-05\n        gas: 0.6298975420503029\n        geothermal: 0.0\n        hydro: 0.23812940521241424\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 1.5224679978619349e-06\n        solar: 0.11322428018842533\n        unknown: 4.046917982934631e-05\n        wind: 0.013572870278776452\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010600145224865382\n        coal: 0.060100976299692424\n        gas: 0.3714604399059435\n        geothermal: 0.04555052985728811\n        hydro: 0.26651083434450457\n        hydro discharge: 0.004374786589759857\n        nuclear: 0.0073942194511669\n        oil: 0.0020507467175681932\n        solar: 0.09264091986892278\n        unknown: 0.08904276171796913\n        wind: 0.050272363935094815\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.013156462350448376\n        coal: 0.08551703967600778\n        gas: 0.4914181228848665\n        geothermal: 0.029223261383844755\n        hydro: 0.19063978432739448\n        hydro discharge: 0.004078014359742053\n        nuclear: 0.005378189192351257\n        oil: 0.003123484468379402\n        solar: 0.10207054163194787\n        unknown: 0.021233551745460297\n        wind: 0.054161621075505394\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012372804355963628\n        coal: 0.0637163158759008\n        gas: 0.4710639705651329\n        geothermal: 0.022902172273343027\n        hydro: 0.2504517314569523\n        hydro discharge: 0.0038281824633156396\n        nuclear: 0.0035729530557039747\n        oil: 0.0026544112504738077\n        solar: 0.12295785390430206\n        unknown: 0.011879974638784091\n        wind: 0.03459869992458104\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012508045140722731\n        coal: 0.08146580258589414\n        gas: 0.4548520355611095\n        geothermal: 0.031435374932119134\n        hydro: 0.21958830536691729\n        hydro discharge: 0.007005558251310662\n        nuclear: 0.005555030340161698\n        oil: 0.003204664063447632\n        solar: 0.11418379426494851\n        unknown: 0.0168297549205616\n        wind: 0.05337014021778572\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012186244028996911\n        coal: 0.09196660501213032\n        gas: 0.3801482138315288\n        geothermal: 0.035145174640867714\n        hydro: 0.12204979388882331\n        hydro discharge: 0.004808646854060273\n        nuclear: 0.004246802007915289\n        oil: 0.15776053436764728\n        solar: 0.11835549271859838\n        unknown: 0.02267362273416361\n        wind: 0.050658400638399284\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.001259377328280306\n        biomass: 0.011279340968212606\n        coal: 0.0790652554732761\n        gas: 0.14969263897855914\n        geothermal: 0.03190875580508219\n        hydro: 0.21164480430235721\n        hydro discharge: 0.007325919171181966\n        nuclear: 0.008074280942068109\n        oil: 0.27942088348636035\n        solar: 0.1339264087499508\n        unknown: 0.02244353585828427\n        wind: 0.06395879454953529\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0014329491117878494\n        biomass: 0.016852798356268038\n        coal: 0.10101584152715089\n        gas: 0.15168193149651962\n        geothermal: 0.008899311796340788\n        hydro: 0.21112115213578297\n        hydro discharge: 0.009087498515642304\n        nuclear: 0.003192659769293663\n        oil: 0.25979326594409285\n        solar: 0.13984351379653193\n        unknown: 0.021942060514426275\n        wind: 0.07513672956538177\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2023-01-01'\n      value: 0.4884\n    - datetime: '2024-01-01'\n      value: 0.4103\n    - datetime: '2025-01-01'\n      value: 0.3944\nisRenewable:\n  battery discharge:\n    - datetime: '2023-01-01'\n      value: 0.4803\n    - datetime: '2024-01-01'\n      value: 0.4072\n    - datetime: '2025-01-01'\n      value: 0.3942\nparsers:\n  price: FR_O.fetch_price\n  production: FR_O.fetch_production\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Paris\nzone_name: Corsica\n"
  },
  {
    "path": "config/zones/FR.yaml",
    "content": "bounding_box:\n  - - -4.775447754477511\n    - 42.34020550798748\n  - - 8.199081990819934\n    - 51.086983783028785\ncenter_point:\n  - 1.73217371580232\n  - 46.68550997160196\ncentroid:\n  - 3.41727311067867\n  - 46.04823289827162\ncapacity:\n  battery storage:\n    - datetime: '2021-01-01'\n      source: rte-france.com\n      value: 292.0\n    - datetime: '2022-01-01'\n      source: rte-france.com\n      value: 476.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 170.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1840.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1931.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 2038.33\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2039.33\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2248.1000000000004\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2271.46\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 2370.38\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 2653.68\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2930.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 3972.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 3966.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1812.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1815.81\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1812.46\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1813.25\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 6696.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 11812.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 11952.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 12237.6\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 12217.6\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 13074.11\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 12892.82\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 13133.29\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 13112.72\n  geothermal:\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1.85\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 18557.64\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 19800.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 19234.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 20260.09\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 20285.09\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 20619.36\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 20482.63\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 20385.46\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 20427.86\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4965.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 5020.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 5023.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 5064.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 5049.96\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 5051.05\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 5064.73\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 5542.58\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 63130.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 61370.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 5300.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 6263.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 3271.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 2874.21\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2746.21\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2761.79\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2565.78\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 3042.47\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 3039.5\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 7660.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 7170.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 8188.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 9437.84\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 10212.84\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 13153.79\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 14638.79\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 17419.3\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 21237.97\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 302.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 415.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 348.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1315.85\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1365.85\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1399.5\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1388.04\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1274.99\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 371.58000000000004\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 13569.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 12518.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 13610.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 16591.88\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 17226.88\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 19535.54\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 21335.4\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 23617.06\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 24606.27\ncontributors:\n  - corradio\n  - lorrieq\n  - nessie2013\n  - gadakast\ncountry: FR\ncountry_name: France\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 20.35\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 17.88\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 15.13\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 854.4786144\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 869.45\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 921.02\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 828.47\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 380.5979557\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 381.61\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 338.39\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 363.32\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 28.86\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 32.58\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 56.67\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 24.57\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 12.59\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 10.36\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 769.5956561\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 755.44\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 590.35\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 849.33\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 53.35\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 50.88\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 48.13\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 953.9335274\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 968.9049130000001\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 981.02\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 888.47\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 500.5979557\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 501.61\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 458.39\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 483.32\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 39.56\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 43.28\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 67.37\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 35.27\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 23.29\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 21.06\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1013.5956561\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 999.44\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 834.35\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1093.33\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 30.075\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.014649714483554652\n        coal: 0.01743473927467629\n        gas: 0.042370588719523795\n        geothermal: 3.8550414322331076e-07\n        hydro: 0.09754615544021171\n        hydro discharge: 0.009731422361683338\n        nuclear: 0.7595048922765821\n        oil: 0.004889142949567012\n        solar: 0.013819388314986752\n        unknown: 0.000614813699422456\n        wind: 0.03943875386590272\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01677123156475827\n        coal: 0.01771380383168754\n        gas: 0.07228349391741931\n        geothermal: 1.1582844618221332e-06\n        hydro: 0.10832503915402875\n        hydro discharge: 0.009916686010319696\n        nuclear: 0.71078728588206\n        oil: 0.0032546299668737215\n        solar: 0.01653651106912829\n        unknown: 0.0023310125481720645\n        wind: 0.04207914464919185\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.018748294563862733\n        coal: 0.02215848847564565\n        gas: 0.08041189454266316\n        geothermal: 1.4422924001338023e-06\n        hydro: 0.08912221732888187\n        hydro discharge: 0.01057743337409941\n        nuclear: 0.7052201543171881\n        oil: 0.006640703668592956\n        solar: 0.017546504024065795\n        unknown: 0.0020677852818653353\n        wind: 0.04750507628865286\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.018037769280996516\n        coal: 0.012939070277714354\n        gas: 0.05861180757274389\n        geothermal: 2.2865554898365726e-06\n        hydro: 0.1120911816700541\n        hydro discharge: 0.010347002850245202\n        nuclear: 0.710025656144638\n        oil: 0.003893349902178269\n        solar: 0.019940007667136873\n        unknown: 0.00079497935402942\n        wind: 0.053316892019762585\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01871349690627882\n        coal: 0.004813152066729278\n        gas: 0.07366904923952437\n        geothermal: 3.1963362867079255e-06\n        hydro: 0.10127842925646478\n        hydro discharge: 0.00974334268973361\n        nuclear: 0.6983771184687934\n        oil: 0.004555502750203661\n        solar: 0.022913018269165877\n        unknown: 0.0009700559260945408\n        wind: 0.06496364747856284\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.020505234541264853\n        coal: 0.004184746619277642\n        gas: 0.07500580591548696\n        geothermal: 5.2731426160309175e-06\n        hydro: 0.11846184494358837\n        hydro discharge: 0.010207443227442466\n        nuclear: 0.6586655133804802\n        oil: 0.001934550187594299\n        solar: 0.02708828732281785\n        unknown: 0.0011960435641866754\n        wind: 0.08274526703639272\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.019904454345747044\n        coal: 0.010456212916781898\n        gas: 0.07141996557267574\n        geothermal: 1.2111377031787511e-05\n        hydro: 0.10678356687201783\n        hydro discharge: 0.009115157185193195\n        nuclear: 0.6768487309591066\n        oil: 0.0020139458662568766\n        solar: 0.027777207411741413\n        unknown: 0.0010330650764378449\n        wind: 0.07463560240854214\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022065879726485292\n        coal: 0.014509253001965783\n        gas: 0.11551944803386882\n        geothermal: 1.5633934758911427e-05\n        hydro: 0.09247885153397063\n        hydro discharge: 0.012009506769831348\n        nuclear: 0.5974180079587315\n        oil: 0.0032020579466884003\n        solar: 0.044331619225364514\n        unknown: 0.002166674570944399\n        wind: 0.09628308534800463\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 9.625582869517857e-07\n        biomass: 0.01429357717053872\n        coal: 0.0046441996046644495\n        gas: 0.06506583001088198\n        geothermal: 4.3446033086035716e-06\n        hydro: 0.10486074858093865\n        hydro discharge: 0.010841369888100943\n        nuclear: 0.6433256632290727\n        oil: 0.0034249980416440574\n        solar: 0.0478172146694561\n        unknown: 0.0010684078776343445\n        wind: 0.1046526822446214\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 5.24803239253299e-05\n        biomass: 0.012620126817696989\n        coal: 0.001530549082462334\n        gas: 0.03603334028768703\n        geothermal: 2.1041309530707855e-06\n        hydro: 0.12044394027574781\n        hydro discharge: 0.013662019445778311\n        nuclear: 0.6746800863132116\n        oil: 0.002640214353842674\n        solar: 0.04719155478803789\n        unknown: 0.00038720954386614967\n        wind: 0.09075636778437683\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2023-01-01'\n      value: 0.9447\n    - datetime: '2024-01-01'\n      value: 0.9567\n    - datetime: '2025-01-01'\n      value: 0.9626\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.9304\n    - datetime: '2021-01-01'\n      value: 0.9281\n    - datetime: '2022-01-01'\n      value: 0.8723\n    - datetime: '2023-01-01'\n      value: 0.9377\n    - datetime: '2024-01-01'\n      value: 0.9702\n    - datetime: '2025-01-01'\n      value: 0.9748\nisRenewable:\n  battery discharge:\n    - datetime: '2023-01-01'\n      value: 0.2726\n    - datetime: '2024-01-01'\n      value: 0.2734\n    - datetime: '2025-01-01'\n      value: 0.2663\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2493\n    - datetime: '2021-01-01'\n      value: 0.2301\n    - datetime: '2022-01-01'\n      value: 0.2605\n    - datetime: '2023-01-01'\n      value: 0.2894\n    - datetime: '2024-01-01'\n      value: 0.3014\n    - datetime: '2025-01-01'\n      value: 0.3025\nparsers:\n  consumption: FR.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: FR.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Paris\nzone_name: France\n"
  },
  {
    "path": "config/zones/GA.yaml",
    "content": "bounding_box:\n  - - 8.695886958869607\n    - -3.93672006138604\n  - - 14.499144991449924\n    - 2.309956504477071\ncenter_point:\n  - 11.708644369489573\n  - -0.6967646921278292\ncentroid:\n  - 11.704904283085405\n  - -1.0821513139124261\ncountry: GA\ncountry_name: Gabon\ncurrency: XAF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Libreville\nzone_name: Gabon\n"
  },
  {
    "path": "config/zones/GB-NIR.yaml",
    "content": "bounding_box:\n  - - -8.173881738817357\n    - 54.03644550175591\n  - - -5.434254342543397\n    - 55.24857266127161\ncenter_point:\n  - -6.507324449477657\n  - 54.66168556794619\ncentroid:\n  - -6.608016080160773\n  - 54.576082986683936\ncapacity:\n  battery storage: 150\n  biomass: 82\n  coal: 0\n  gas: 1008\n  hydro: 6\n  oil: 394\n  solar: 285\n  wind: 1430\ncontributors:\n  - corradio\n  - systemcatch\n  - brunolajoie\n  - alixunderplatz\n  - nessie2013\n  - msaynevirta\n  - brandongalbraith\ncountry: GB\ncountry_name: Northern Ireland\ncurrency: EUR\ndisclaimer: The complete generation mix is unavailable. It is therefore estimated\n  by Electricity Maps.\nemissionFactors:\n  direct:\n    gas:\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    gas:\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    oil:\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2731996571787163\n        gas: 0.5208424904534642\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.001187650500454946\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.20476734818604286\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.272702648819229\n        gas: 0.546145663975731\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0030721677803850164\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.1780767831357459\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0561664691222293\n        coal: 0.13378645946634526\n        gas: 0.47439835078494375\n        geothermal: 0.0\n        hydro: 0.002776863153337358\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.07185710116948833\n        solar: 0.0\n        unknown: 0.017772988881682564\n        wind: 0.24323648102209852\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07214151414673074\n        coal: 0.1433253076490959\n        gas: 0.42888185117776256\n        geothermal: 0.0\n        hydro: 0.003011039601075656\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00800763595148947\n        solar: 0.0\n        unknown: 0.029088990617660817\n        wind: 0.3155374545180556\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07939135949734241\n        coal: 0.09374709949121969\n        gas: 0.4322608115335559\n        geothermal: 0.0\n        hydro: 0.003813763746380853\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.008598009249641709\n        solar: 0.0\n        unknown: 0.028704758793921557\n        wind: 0.353477835762537\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07900957953989912\n        coal: 0.10254451441046267\n        gas: 0.4006541300869623\n        geothermal: 0.0\n        hydro: 0.0037351887391979055\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.008467020003272971\n        solar: 0.0\n        unknown: 0.02820390031873462\n        wind: 0.3773791864820577\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08871192876669518\n        coal: 0.12590938003773974\n        gas: 0.4321900803345247\n        geothermal: 0.0\n        hydro: 0.0028765602389080225\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.007603360156160388\n        solar: 0.0\n        unknown: 0.02767487613864049\n        wind: 0.3150271645789647\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08443677937205395\n        coal: 0.11984160780403448\n        gas: 0.4113619280391782\n        geothermal: 0.0\n        hydro: 0.002737951127844904\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.007236983635139479\n        solar: 0.0\n        unknown: 0.02634122064498521\n        wind: 0.3480377376737529\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.2550012395521744e-09\n        biomass: 0.0516054476601846\n        coal: 0.041018633703694324\n        gas: 0.46524408728693256\n        geothermal: 2.3845023551491307e-08\n        hydro: 0.012631778236281047\n        hydro discharge: 0.00022937030154675315\n        nuclear: 0.0473705890474571\n        oil: 0.0010500607921345437\n        solar: 0.027924928416172553\n        unknown: 0.0030082342062028432\n        wind: 0.3499154396479806\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 6.98315658157476e-07\n        biomass: 0.06629979638874206\n        coal: 0.0021132967534361127\n        gas: 0.5331136867289081\n        geothermal: 6.972749492779566e-08\n        hydro: 0.016935756361284374\n        hydro discharge: 0.0004632965347311419\n        nuclear: 0.054134168723671994\n        oil: 0.00130082781970192\n        solar: 0.02743493748522642\n        unknown: 0.004058241153559021\n        wind: 0.29414430089880955\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: SMARTGRIDDASHBOARD.fetch_consumption\n  consumptionForecast: SMARTGRIDDASHBOARD.fetch_consumption_forecast\n  generationForecast: SMARTGRIDDASHBOARD.fetch_total_generation\n  price: ENTSOE.fetch_price\n  production: SMARTGRIDDASHBOARD.fetch_production\n  productionPerModeForecast: SMARTGRIDDASHBOARD.fetch_wind_solar_forecasts\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/London\nzone_name: Northern Ireland\n"
  },
  {
    "path": "config/zones/GB-ZET.yaml",
    "content": "bounding_box:\n  - - -1.65781657816575\n    - 59.88241887439068\n  - - -0.76140761407612\n    - 60.84553762097164\ncenter_point:\n  - -1.209612096120935\n  - 60.36397824768116\ncentroid:\n  - -1.1902619026189978\n  - 60.38526560482142\ncontributors:\n  - systemcatch\n  - maxbellec\ncountry: GB\ncountry_name: Great Britain\ncurrency: GBP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Europe/London\nzone_name: Shetland Islands\n"
  },
  {
    "path": "config/zones/GB.yaml",
    "content": "_comment: Key should be GB-GBN (see https://en.wikipedia.org/wiki/ISO_3166-2:GB)\nbounding_box:\n  - - -7.543875438754355\n    - 49.959290510657624\n  - - 1.76941769417698\n    - 59.12680713858869\ncenter_point:\n  - -1.9472987018074561\n  - 54.185192184671\ncentroid:\n  - -3.839611949304168\n  - 54.74704251929902\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4930\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 6450\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 6500\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 6600\n    - datetime: '2022-01-01'\n      source: bmreports.com\n      value: 4572\n    - datetime: '2023-01-01'\n      source: bmreports.com\n      value: 4438\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 14300\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 11450\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 8730\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 5410\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 5410\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4310\n    - datetime: '2023-01-01'\n      source: bmrs.elexon.co.uk\n      value: 1998\n    - datetime: '2024-01-01'\n      source: bmrs.elexon.co.uk\n      value: 1998\n    - datetime: '2025-01-01'\n      source: bmrs.elexon.co.uk\n      value: 0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 31000\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 32000\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 33000\n    - datetime: '2022-01-01'\n      source: bmreports.com\n      value: 38985\n    - datetime: '2023-01-01'\n      source: bmreports.com\n      value: 37047\n    - datetime: '2024-01-01'\n      source: bmreports.com\n      value: 32631\n    - datetime: '2025-01-01'\n      source: bmreports.com\n      value: 40470\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3000\n    - datetime: '2022-01-01'\n      source: bmreports.com\n      value: 4190\n    - datetime: '2023-01-01'\n      source: bmreports.com\n      value: 2063\n    - datetime: '2024-01-01'\n      source: bmreports.com\n      value: 1386\n    - datetime: '2025-01-01'\n      source: bmreports.com\n      value: 1687\n  hydro storage:\n    - datetime: '2022-01-01'\n      source: bmreports.com\n      value: 1928\n    - datetime: '2023-01-01'\n      source: bmreports.com\n      value: 5603\n    - datetime: '2024-01-01'\n      source: bmreports.com\n      value: 5891\n    - datetime: '2025-01-01'\n      source: bmreports.com\n      value: 11080\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 9300\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 7830\n    - datetime: '2023-01-01'\n      source: IRENA.org\n      value: 5883\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 12750\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 13000\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 13250\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 13750\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 14000\n    - datetime: '2022-01-01'\n      source: bmreports.com\n      value: 13324\n    - datetime: '2023-01-01'\n      source: bmreports.com\n      value: 14518\n    - datetime: '2024-01-01'\n      source: bmreports.com\n      value: 15896\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5000\n    - datetime: '2022-01-01'\n      source: bmreports.com\n      value: 4906\n    - datetime: '2023-01-01'\n      source: bmreports.com\n      value: 4775\n    - datetime: '2025-01-01'\n      source: bmreports.com\n      value: 6238\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 16300\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 20940\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 21760\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 23150\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 25410\n    - datetime: '2022-01-01'\n      source: bmreports.com\n      value: 27330\n    - datetime: '2023-01-01'\n      source: bmreports.com\n      value: 26945\n    - datetime: '2024-01-01'\n      source: bmreports.com\n      value: 28535\n    - datetime: '2025-01-01'\n      source: bmreports.com\n      value: 32844\ncontributors:\n  - corradio\n  - lorrieq\n  - nessie2013\n  - AlexandreCouderc\n  - gadakast\n  - amv213\n  - VIKTORVAV99\n  - AJDelusion\ncountry: GB\ncountry_name: Great Britain\ncurrency: GBP\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 151.56\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 166.04\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 164.77\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 138.01\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 114.57\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 119.61\n  lifecycle:\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 162.26\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 176.74\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 175.47\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 148.71\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 125.27\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 130.31\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 39.72\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0011107850197998633\n        coal: 0.24923266172774305\n        gas: 0.24934595147683364\n        geothermal: 9.007109246619976e-07\n        hydro: 0.018187712408445196\n        hydro discharge: 0.007963212363838115\n        nuclear: 0.233781199387908\n        oil: 0.00029602467685045094\n        solar: 0.021975736317498214\n        unknown: 0.032475060765958276\n        wind: 0.1856307461638121\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0011344532297370199\n        coal: 0.10349447566649182\n        gas: 0.44109376507891723\n        geothermal: 1.0442593162978466e-06\n        hydro: 0.017233359580853026\n        hydro discharge: 0.010281361422326543\n        nuclear: 0.25360461754744584\n        oil: 0.0003656684902675581\n        solar: 0.03296713428260252\n        unknown: 0.05494472511254511\n        wind: 0.08487938775201209\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008872169625736686\n        coal: 0.0779018957925082\n        gas: 0.42514846009192475\n        geothermal: 8.84131857966239e-07\n        hydro: 0.01815086091076348\n        hydro discharge: 0.010550731389177113\n        nuclear: 0.2549669109329945\n        oil: 0.000302027283380607\n        solar: 0.036795810334367136\n        unknown: 0.04928676369844136\n        wind: 0.11802348219384363\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.057846944017628625\n        coal: 0.06164572193004294\n        gas: 0.4151157879556949\n        geothermal: 1.598814933231657e-06\n        hydro: 0.01752086372432556\n        hydro discharge: 0.00938230392728849\n        nuclear: 0.24659009302560758\n        oil: 0.0002610712771169756\n        solar: 0.04089123176710867\n        unknown: 0.0027738986966526842\n        wind: 0.14797048619337996\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05684552518428051\n        coal: 0.023293041915163765\n        gas: 0.38194369042138787\n        geothermal: 8.576093702308757e-07\n        hydro: 0.015930910753295686\n        hydro discharge: 0.000556661466548219\n        nuclear: 0.20360164570012954\n        oil: 0.0002519723535924055\n        solar: 0.08335496670961735\n        unknown: 0.003809217615049497\n        wind: 0.2304115083560265\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06261069842013885\n        coal: 0.017357558512858196\n        gas: 0.3367036461455283\n        geothermal: 6.568006673315476e-07\n        hydro: 0.019884981967927436\n        hydro discharge: 0.0006653291473849905\n        nuclear: 0.1900851217364905\n        oil: 0.00016429890337007236\n        solar: 0.08955887566845397\n        unknown: 0.00634806313506357\n        wind: 0.27662076327513463\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06598321690601364\n        coal: 0.019481327140621955\n        gas: 0.3703007190658074\n        geothermal: 9.1628146594246e-07\n        hydro: 0.021076821239273433\n        hydro discharge: 0.0009315490651256576\n        nuclear: 0.19038344886041156\n        oil: 0.0001277495805424543\n        solar: 0.08539929237923541\n        unknown: 0.007523998901735553\n        wind: 0.23879095756612864\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05006134296980562\n        coal: 0.016382167450082613\n        gas: 0.36722195370494953\n        geothermal: 8.697774455495046e-07\n        hydro: 0.023847369661819853\n        hydro discharge: 0.0005083817463892342\n        nuclear: 0.15434310086399147\n        oil: 9.881953307964232e-05\n        solar: 0.09389424566649993\n        unknown: 0.009435401152365247\n        wind: 0.2842063409573349\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 3.8167535665457256e-08\n        biomass: 0.04782150797636591\n        coal: 0.011298255691322368\n        gas: 0.3070129179530135\n        geothermal: 1.065091632524296e-06\n        hydro: 0.042659376360873885\n        hydro discharge: 0.0009863438811447472\n        nuclear: 0.16936753600329874\n        oil: 0.00021159454556657128\n        solar: 0.0991874459698062\n        unknown: 0.010063504658643072\n        wind: 0.3113904112774612\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.040018978413123e-06\n        biomass: 0.06529804837484905\n        coal: 0.0074103727277110565\n        gas: 0.25153643209361526\n        geothermal: 1.1707284965868286e-06\n        hydro: 0.05071748400262454\n        hydro discharge: 0.0015579171542997013\n        nuclear: 0.18003498311127875\n        oil: 0.00038104497207143857\n        solar: 0.10642708161006456\n        unknown: 0.01229548242156918\n        wind: 0.324336935214777\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.6139\n    - datetime: '2021-01-01'\n      value: 0.5776\n    - datetime: '2022-01-01'\n      value: 0.5787\n    - datetime: '2023-01-01'\n      value: 0.6458\n    - datetime: '2024-01-01'\n      value: 0.7062\n    - datetime: '2025-01-01'\n      value: 0.6883\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4101\n    - datetime: '2021-01-01'\n      value: 0.3752\n    - datetime: '2022-01-01'\n      value: 0.4125\n    - datetime: '2023-01-01'\n      value: 0.4635\n    - datetime: '2024-01-01'\n      value: 0.5119\n    - datetime: '2025-01-01'\n      value: 0.5145\nparsers:\n  consumption: ELEXON.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: GB.fetch_production\n  productionCapacity: GB.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/London\nzone_name: Great Britain\n"
  },
  {
    "path": "config/zones/GE.yaml",
    "content": "_comment: source:http://www.gse.com.ge/for-customers/data-from-the-power-system, gas incl. 13 MW of coal\nbounding_box:\n  - - 39.987399873998754\n    - 41.045075544160184\n  - - 46.62946629466296\n    - 43.575229992830515\ncenter_point:\n  - 43.77730700229085\n  - 42.16081597950481\ncentroid:\n  - 43.59067269225706\n  - 42.238123079285806\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1780.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2040.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3220.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 3300.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 3320.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 3350.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3380.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 3450.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 3410.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\ncontributors:\n  - alixunderplatz\n  - kruschk\n  - tmslaine\n  - amv213\ncountry: GE\ncountry_name: Georgia\ncurrency: GEL\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.5713149593293828\n        geothermal: 0.0\n        hydro: 0.4061106202693423\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.022574369117895777\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.4711637830986466e-05\n        coal: 0.0015877335806714172\n        gas: 0.19720144390323896\n        geothermal: 0.00010389620334833036\n        hydro: 0.7529557688872576\n        hydro discharge: 3.182801928386802e-09\n        nuclear: 0.003343442715915376\n        oil: 0.028641752079881684\n        solar: 1.5476374376780822e-06\n        unknown: 0.009303263993534608\n        wind: 0.00682644970498955\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.438950903938165e-07\n        coal: 2.6250897302550097e-05\n        gas: 0.26004855299803575\n        geothermal: 2.0020053022554316e-07\n        hydro: 0.6836334561064409\n        hydro discharge: 0.0\n        nuclear: 0.0014247254844569808\n        oil: 0.04410283816625292\n        solar: 1.0102182310904789e-05\n        unknown: 0.004326532864257665\n        wind: 0.006426998693949735\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0003912614425932152\n        coal: 0.010061261744986475\n        gas: 0.27307347549894656\n        geothermal: 0.0008703523572407531\n        hydro: 0.6746145623682301\n        hydro discharge: 1.6435309472267261e-09\n        nuclear: 0.0001370663721713409\n        oil: 0.030375093880747567\n        solar: 4.450517451995252e-05\n        unknown: 0.001053629889055268\n        wind: 0.009378725530271003\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0002198023778675047\n        coal: 0.003665595017622864\n        gas: 0.20987866816778963\n        geothermal: 0.00040760703816235396\n        hydro: 0.6996401399467271\n        hydro discharge: 3.0400909786138515e-09\n        nuclear: 0.01045928024734928\n        oil: 0.0416884757409978\n        solar: 0.00011531521095529128\n        unknown: 0.02719365788502009\n        wind: 0.006731636212830162\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.5899984971695644e-05\n        coal: 8.360272337893792e-05\n        gas: 0.26118725837157386\n        geothermal: 1.58889318017466e-08\n        hydro: 0.603180077958809\n        hydro discharge: 6.010161159791105e-08\n        nuclear: 0.021854916204543873\n        oil: 0.06500623469939906\n        solar: 7.402998737994649e-05\n        unknown: 0.04392652497017686\n        wind: 0.004670856846943255\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.1145758740051212e-05\n        coal: 0.00010952945776355116\n        gas: 0.2583396170856827\n        geothermal: 8.95125701921211e-08\n        hydro: 0.6046800958655661\n        hydro discharge: 6.496880094589436e-09\n        nuclear: 0.017221689370174178\n        oil: 0.07168360372386991\n        solar: 9.260869449497602e-05\n        unknown: 0.04345853907217085\n        wind: 0.00440271185867778\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.233114291439386e-05\n        coal: 0.0006576123564253511\n        gas: 0.20741643533880635\n        geothermal: 4.550510024695553e-06\n        hydro: 0.6894811757351528\n        hydro discharge: 1.0062048339805148e-07\n        nuclear: 0.018335948849857907\n        oil: 0.02700760829122092\n        solar: 9.334021495300608e-05\n        unknown: 0.05224346510003176\n        wind: 0.00475058940672753\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  production: ENTSOE.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Asia\ntimezone: Asia/Tbilisi\nzone_name: Georgia\n"
  },
  {
    "path": "config/zones/GF.yaml",
    "content": "bounding_box:\n  - - -54.61434614346139\n    - 2.111035990695861\n  - - -51.6515165151651\n    - 5.744555303577059\ncenter_point:\n  - -53.130423676789576\n  - 3.934857001976582\ncentroid:\n  - -53.369082077917525\n  - 3.8700214482510638\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\ncontributors:\n  - PETILLON-Sebastien\n  - VIKTORVAV99\ncountry: GF\ncountry_name: French Guiana\ncurrency: EUR\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01290589447516906\n        coal: 0.0\n        gas: 0.4527969790876527\n        geothermal: 0.0\n        hydro: 0.4771298821452508\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05716644446180697\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011220148111682027\n        coal: 0.0\n        gas: 0.32152341092693204\n        geothermal: 0.0\n        hydro: 0.6106972301380263\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05655212794349569\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011513164219639264\n        coal: 0.0\n        gas: 0.3404129517370362\n        geothermal: 0.0\n        hydro: 0.591391065007107\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.056666601841838186\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010781631028878566\n        coal: 0.0\n        gas: 0.49456569473470113\n        geothermal: 0.0\n        hydro: 0.43986786748545703\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0547848067509634\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00956301580510201\n        coal: 0.0\n        gas: 0.4673755388346576\n        geothermal: 0.0\n        hydro: 0.4635250158791718\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0595364294810685\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03641745921348665\n        coal: 0.0\n        gas: 0.29210321881625634\n        geothermal: 0.0\n        hydro: 0.6116522286445288\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.059827093325728074\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0400314393675586\n        coal: 0.0\n        gas: 0.27313026026698783\n        geothermal: 0.0\n        hydro: 0.634814898215558\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05202340214989558\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0559501875581819\n        coal: 0.0\n        gas: 0.11108404585690737\n        geothermal: 0.0\n        hydro: 0.2796028181832044\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5319543577666881\n        solar: 0.021408668481840875\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06495299663773707\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.34205537117791934\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5670083003899943\n        solar: 0.025983803372641664\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  price: FR_O.fetch_price\n  production: FR_O.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: Europe/Paris\nzone_name: French Guiana\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/GG.yaml",
    "content": "bounding_box:\n  - - -2.677970243354415\n    - 49.4084028034548\n  - - -2.342555536247872\n    - 49.50496240420853\ncenter_point:\n  - -2.536958119726989\n  - 49.4651328297851\ncentroid:\n  - -2.450818105076321\n  - 49.43914509312574\ncountry: GG\ncountry_name: Guernsey\ncurrency: GBP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Europe/Guernsey\nzone_name: Guernsey\n"
  },
  {
    "path": "config/zones/GH.yaml",
    "content": "bounding_box:\n  - - -3.263432634326307\n    - 4.737072989174393\n  - - 1.186211862118654\n    - 11.16263490915729\ncenter_point:\n  - -1.1679148936330073\n  - 7.888890683456197\ncentroid:\n  - -1.039723124503944\n  - 7.782547356149084\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2310.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2870.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 3060.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1580.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 170.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 960.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 980.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 880.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 410.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: GH\ncountry_name: Ghana\ncurrency: GHS\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6261871418950762\n        geothermal: 0.0\n        hydro: 0.3536090544623948\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.013253273113866659\n        solar: 0.006950425624501335\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6261869282985468\n        geothermal: 0.0\n        hydro: 0.35360908212088166\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.013253557917185226\n        solar: 0.006950597869928555\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Accra\nzone_name: Ghana\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/GI.yaml",
    "content": "bounding_box:\n  - - -5.363121599699786\n    - 36.109147955711094\n  - - -5.338010782916699\n    - 36.15567746511084\ncenter_point:\n  - -5.350566191308243\n  - 36.13241271041097\ncentroid:\n  - -5.348983439419028\n  - 36.13243391621028\ncountry: GI\ncountry_name: Gibraltar\ncurrency: GIP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Europe/Gibraltar\nzone_name: Gibraltar\n"
  },
  {
    "path": "config/zones/GL.yaml",
    "content": "bounding_box:\n  - - -72.89532895328948\n    - 59.79655390441317\n  - - -11.395913959139563\n    - 83.63410065300008\ncenter_point:\n  - -42.64861824852386\n  - 71.79385151132965\ncentroid:\n  - -40.026525091052136\n  - 73.17468461995857\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: GL\ncountry_name: Greenland\ncurrency: DKK\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Nuuk\nzone_name: Greenland\n"
  },
  {
    "path": "config/zones/GM.yaml",
    "content": "bounding_box:\n  - - -16.828368283682806\n    - 13.064543994158925\n  - - -13.818738187381854\n    - 13.820155729960916\ncenter_point:\n  - -15.32355323553233\n  - 13.44234986205992\ncentroid:\n  - -15.297726890312353\n  - 13.45236744189062\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: GM\ncountry_name: Gambia\ncurrency: GMD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Banjul\nzone_name: Gambia\n"
  },
  {
    "path": "config/zones/GN.yaml",
    "content": "bounding_box:\n  - - -15.082350823508193\n    - 7.189948964864968\n  - - -7.662676626766228\n    - 12.673858380761288\ncenter_point:\n  - -11.275661493527238\n  - 10.356024153476673\ncentroid:\n  - -10.952550302202026\n  - 10.23216708158073\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 360.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 590.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 810.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 430.0\ncountry: GN\ncountry_name: Guinea\ncurrency: GNF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Conakry\nzone_name: Guinea\n"
  },
  {
    "path": "config/zones/GP.yaml",
    "content": "bounding_box:\n  - - -61.77121771217708\n    - 15.949606985402909\n  - - -61.18801188011875\n    - 16.51202253875553\ncenter_point:\n  - -61.479614796147914\n  - 16.23081476207922\ncentroid:\n  - -61.53406534065335\n  - 16.243336736867608\ncapacity:\n  biomass: 5.162\n  gas: 100\n  geothermal: 14.5\n  hydro: 10.57\n  oil: 329.7\n  solar: 60.447\n  wind: 26.26\ncontributors:\n  - PETILLON-Sebastien\n  - VIKTORVAV99\ncountry: GP\ncountry_name: Guadeloupe\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 405.21\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 438.21\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.784053430923223\n        geothermal: 0.06857116680172289\n        hydro: 0.02771924203373693\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0762804983617097\n        unknown: 0.0\n        wind: 0.04337607655738929\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002248785975311423\n        coal: 0.0\n        gas: 0.7539148273635133\n        geothermal: 0.09329874780605996\n        hydro: 0.031410421619085215\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.07683174817619856\n        unknown: 0.0\n        wind: 0.042284527169144645\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009839378389552154\n        coal: 0.0\n        gas: 0.7443905343569401\n        geothermal: 0.0888891758824572\n        hydro: 0.03366461043674733\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.07928172695844372\n        unknown: 0.0\n        wind: 0.04391491751870369\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.013406333689295332\n        coal: 0.0\n        gas: 0.7415016313603688\n        geothermal: 0.08482198799858975\n        hydro: 0.034183252272102484\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.07752258045307923\n        unknown: 0.0\n        wind: 0.048564214226564255\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01198272457758311\n        coal: 0.0\n        gas: 0.7519057622320924\n        geothermal: 0.0853128492632219\n        hydro: 0.018778169137623014\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.07795723868734028\n        unknown: 0.0\n        wind: 0.05406325610213917\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1454658667134957\n        coal: 0.0\n        gas: 0.6280533787557349\n        geothermal: 0.06082490317604862\n        hydro: 0.008276491055919176\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.08032126292364207\n        unknown: 0.0\n        wind: 0.07705809737515942\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.14387146004468807\n        coal: 0.0008147273160578097\n        gas: 0.6133525254148362\n        geothermal: 0.07039822275772453\n        hydro: 0.00903547915624472\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0019159466690012417\n        solar: 0.07987987695482408\n        unknown: 0.0\n        wind: 0.08073182769861344\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0863263801273544\n        coal: 0.1670242650885789\n        gas: 0.002524579671826125\n        geothermal: 0.055473024471245316\n        hydro: 0.009860607348963393\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5665026157541078\n        solar: 0.06917119460371109\n        unknown: 0.0\n        wind: 0.04311598615929433\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.1722\nisRenewable:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.1722\nparsers:\n  price: FR_O.fetch_price\n  production: FR_O.fetch_production\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: America/Puerto_Rico\nzone_name: Guadeloupe\n"
  },
  {
    "path": "config/zones/GQ.yaml",
    "content": "bounding_box:\n  - - 8.469084690846927\n    - 0.997653546654277\n  - - 11.334713347133487\n    - 3.761074497096814\ncenter_point:\n  - 10.443030709923079\n  - 1.581719358360882\ncentroid:\n  - 9.60155315838875\n  - 2.2522020901469637\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\ncountry: GQ\ncountry_name: Equatorial Guinea\ncurrency: XAF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Malabo\nzone_name: Equatorial Guinea\n"
  },
  {
    "path": "config/zones/GR.yaml",
    "content": "bounding_box:\n  - - 19.62559625596259\n    - 34.9314896817622\n  - - 28.240482404824064\n    - 41.71339122715172\ncenter_point:\n  - 22.383812358539977\n  - 39.24364164233488\ncentroid:\n  - 23.630065921118955\n  - 38.71165837978247\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 51.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 86.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 95.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 106.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 127.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 120.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 146.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 3912.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 3362.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2561.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2001.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2650.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1800.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 5245.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4902.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 5213.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 6030.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2702.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2715.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2722.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2724.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 2730.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 2708.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 699.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2441.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 2606.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 3055.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 3820.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 5100.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 6700.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 9000.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 69.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 105.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 106.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 109.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 120.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 128.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 132.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1875.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 2228.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 2355.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 3153.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 3755.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 4150.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 4547.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 5065.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 5225.0\ncontributors:\n  - corradio\ncountry: GR\ncountry_name: Greece\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1523.652468\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1523.65\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 889.82\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 825.18\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 382.5054126\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 385.67\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 390.77\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 387.12\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 594.91\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 617.15\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 430.14\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 348.65\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 312.4\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1537.25003\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1537.247562\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 949.82\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 885.18\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 502.5054126\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 505.67\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 510.77\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 507.12\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 605.61\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 627.85\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 440.84\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 359.35\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 323.1\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.1\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001534287268805591\n        coal: 0.45985210914623603\n        gas: 0.1937162873318641\n        geothermal: 0.0006976264525694736\n        hydro: 0.13459972585707056\n        hydro discharge: 0.0202053009993969\n        nuclear: 0.02590482830293319\n        oil: 0.0006610939361944661\n        solar: 0.07529031057135882\n        unknown: 0.0034542758940163923\n        wind: 0.08408409865911688\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0009894287066611294\n        coal: 0.385883609679155\n        gas: 0.29953178820880044\n        geothermal: 0.0005519636616325637\n        hydro: 0.11785251626102022\n        hydro discharge: 0.013112013246584408\n        nuclear: 0.026358140150832286\n        oil: 0.0007506942979360167\n        solar: 0.0733273243386489\n        unknown: 0.0008895909971131916\n        wind: 0.08075295078981619\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.003453964740337809\n        coal: 0.3749752479102044\n        gas: 0.3353122439864457\n        geothermal: 0.001152893094594307\n        hydro: 0.0776745322362621\n        hydro discharge: 0.00858908168718118\n        nuclear: 0.017406882972458137\n        oil: 0.0003585687488974097\n        solar: 0.07708231776305481\n        unknown: 0.005856872921255039\n        wind: 0.09813732773374446\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0020745138874022737\n        coal: 0.35478072772869906\n        gas: 0.318614996657911\n        geothermal: 0.0014135099475074758\n        hydro: 0.11221431748855112\n        hydro discharge: 0.012457432497630025\n        nuclear: 0.020360337143613016\n        oil: 0.000877955560121018\n        solar: 0.07024388463210982\n        unknown: 0.002065686586816513\n        wind: 0.10489661250842312\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0047186556595803465\n        coal: 0.28363826884668714\n        gas: 0.37483572726653913\n        geothermal: 0.001545379998185719\n        hydro: 0.08942427411783362\n        hydro discharge: 0.00854749978591113\n        nuclear: 0.02159809497377594\n        oil: 0.0004750745939503488\n        solar: 0.0777344708888882\n        unknown: 0.0038531649729843516\n        wind: 0.13362937666779015\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005005591305061941\n        coal: 0.186209384372088\n        gas: 0.42993925641552244\n        geothermal: 0.0013056224435619838\n        hydro: 0.07841516430842461\n        hydro discharge: 0.009849346679134795\n        nuclear: 0.022635311111335286\n        oil: 0.0004473366876968619\n        solar: 0.09037688812178636\n        unknown: 0.00314672306475817\n        wind: 0.17266931785779224\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002096698090435435\n        coal: 0.15042857047583186\n        gas: 0.44333254358332097\n        geothermal: 0.0017788120642825056\n        hydro: 0.10526680998429558\n        hydro discharge: 0.013553546971959696\n        nuclear: 0.01848654792147134\n        oil: 0.000479898055158474\n        solar: 0.09099609514705884\n        unknown: 0.0006543830379136744\n        wind: 0.17292608391795639\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002883915300445624\n        coal: 0.16574530148150937\n        gas: 0.3948112765457919\n        geothermal: 0.002000098417769356\n        hydro: 0.08728603138707675\n        hydro discharge: 0.012629017145093596\n        nuclear: 0.01681143784707066\n        oil: 0.0016313009879546532\n        solar: 0.1229364907615497\n        unknown: 0.000958270891073585\n        wind: 0.19230681995597607\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.119414926845276e-10\n        biomass: 0.0020685913568995267\n        coal: 0.15292082821223166\n        gas: 0.3402263744624842\n        geothermal: 0.0008656019070549769\n        hydro: 0.09000983797226753\n        hydro discharge: 0.013663286253974076\n        nuclear: 0.025621487727572157\n        oil: 0.0034753040561082676\n        solar: 0.17422726238797673\n        unknown: 0.0007130097547424194\n        wind: 0.19620832159472415\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.9991420082329067e-10\n        biomass: 0.0014822480487824237\n        coal: 0.09345817102216071\n        gas: 0.40036386743537405\n        geothermal: 0.0004829411313252579\n        hydro: 0.06019728153071264\n        hydro discharge: 0.015793173485803363\n        nuclear: 0.018983098633728376\n        oil: 0.0005143888345999665\n        solar: 0.207991503406568\n        unknown: 0.0004729780072988275\n        wind: 0.20026030888063462\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2412\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 0.2971\n    - datetime: '2023-01-01'\n      value: 0.3338\n    - datetime: '2024-01-01'\n      value: 0.4134\n    - datetime: '2025-01-01'\n      value: 0.3915\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2131\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 0.2482\n    - datetime: '2023-01-01'\n      value: 0.2686\n    - datetime: '2024-01-01'\n      value: 0.3172\n    - datetime: '2025-01-01'\n      value: 0.2619\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Athens\nzone_name: Greece\n"
  },
  {
    "path": "config/zones/GS.yaml",
    "content": "bounding_box:\n  - - -38.01458014580143\n    - -54.88756216320146\n  - - -35.78255782557821\n    - -53.98884214410363\ncenter_point:\n  - -36.642966429664256\n  - -54.51118737813342\ncentroid:\n  - -36.85303911862644\n  - -54.32514660984883\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 0.18\n    - datetime: '2023-01-01'\n      source: IRENA.org\n      value: 0.19\n  oil:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 0.13\n  wind:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 0.01\ncountry: GS\ncountry_name: South Georgia and the South Sandwich Islands\ncurrency: GBP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Americas\ntimezone: Atlantic/South_Georgia\nzone_name: South Georgia and the South Sandwich Islands\n"
  },
  {
    "path": "config/zones/GT.yaml",
    "content": "bounding_box:\n  - - -92.24552245522449\n    - 13.731428594317492\n  - - -88.22068220682202\n    - 17.815738999580574\ncenter_point:\n  - -90.44909344570354\n  - 15.713630980259833\ncentroid:\n  - -90.35825935455026\n  - 15.608458807959188\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1030.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1080.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1040.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 870.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 520.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 440.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1440.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1500.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1580.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1570.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1580.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 810.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 680.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\ncontributors:\n  - corradio\n  - igorarduin\n  - kruschk\n  - amv213\ncountry: GT\ncountry_name: Guatemala\nemissionFactors:\n  direct:\n    unknown:\n      _url: https://docs.google.com/spreadsheets/d/1CegROfej9HqRZTfihpjPpgZTYPUHrTNgTdHWbbP3w74/edit#gid=291258352\n      source: Guatemala AMM 2021-2022; IEA 2020\n      value: 383.240577\n  lifecycle:\n    unknown:\n      _url: https://docs.google.com/spreadsheets/d/1CegROfej9HqRZTfihpjPpgZTYPUHrTNgTdHWbbP3w74/edit#gid=291258352\n      source: Guatemala AMM 2021-2022; IEA 2020\n      value: 549.9988504\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.10281174966249966\n        coal: 0.1481592866529251\n        gas: 0.00021183222375891294\n        geothermal: 0.02016698810709332\n        hydro: 0.6623828271852077\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.028604227036569348\n        solar: 0.015172797026249117\n        unknown: 0.0\n        wind: 0.022490236976010727\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.2141016115909956\n        coal: 0.3059597703791984\n        gas: 0.00014609543268142596\n        geothermal: 0.019200463897668312\n        hydro: 0.39261701031404705\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.029189643442237182\n        solar: 0.0141416865814144\n        unknown: 0.0\n        wind: 0.024643632205022217\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.10738400058152096\n        coal: 0.4259083020090625\n        gas: 0.00015175587478472328\n        geothermal: 0.021462480744336203\n        hydro: 0.35914095608246144\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.04157858547298393\n        solar: 0.017162056513368586\n        unknown: 1.4548211764004368e-05\n        wind: 0.027197364503572387\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0012660920830537574\n        coal: 0.33996932189350915\n        gas: 0.0012023232670759013\n        geothermal: 0.02525457709390598\n        hydro: 0.5629133900030246\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.025391496985978212\n        solar: 0.01742560042451506\n        unknown: 0.0009033550660467637\n        wind: 0.0256737413401755\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03817071256427866\n        coal: 0.06479463347126337\n        gas: 0.0004899639916928831\n        geothermal: 0.027578625356645545\n        hydro: 0.6578640477288608\n        hydro discharge: 0.0\n        nuclear: 4.991546771865811e-09\n        oil: 0.026041137855182292\n        solar: 0.01727716097671078\n        unknown: 0.14541912643696164\n        wind: 0.02236370187519197\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.09482534521244539\n        coal: 0.12613445490476763\n        gas: 6.78366967859269e-06\n        geothermal: 0.02478017887719151\n        hydro: 0.3887296663815155\n        hydro discharge: 0.0\n        nuclear: 1.0276191208110612e-06\n        oil: 0.05033225650865263\n        solar: 0.016593713792206324\n        unknown: 0.2735790717853744\n        wind: 0.025016169264053673\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08349673767612047\n        coal: 0.2864537323776537\n        gas: 0.005517976412560738\n        geothermal: 0.021389825056980834\n        hydro: 0.3753061281078637\n        hydro discharge: 0.0\n        nuclear: 1.8662733490476467e-06\n        oil: 0.0758059572592206\n        solar: 0.01427310682024955\n        unknown: 0.11712930277035961\n        wind: 0.02062521914028993\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: GT.fetch_consumption\n  production: GT.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\nsources:\n  Guatemala AMM 2021-2022:\n    link: https://www.amm.org.gt/portal\ntimezone: America/Guatemala\nzone_name: Guatemala\nisRenewable:\n  unknown:\n    source: assumed thermal\n    value: 0\nisLowCarbon:\n  unknown:\n    source: assumed thermal\n    value: 0\n"
  },
  {
    "path": "config/zones/GU.yaml",
    "content": "bounding_box:\n  - - 144.65484654846549\n    - 13.246291513944627\n  - - 144.95364953649536\n    - 13.639839293008166\ncenter_point:\n  - 144.80424804248042\n  - 13.443065403476396\ncentroid:\n  - 144.79344793447933\n  - 13.478126932883875\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 490.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 420.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: GU\ncountry_name: Guam\ncurrency: USD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Guam\nzone_name: Guam\n"
  },
  {
    "path": "config/zones/GW.yaml",
    "content": "bounding_box:\n  - - -16.727567275672726\n    - 10.96800764387497\n  - - -13.66393663936637\n    - 12.679582712093122\ncenter_point:\n  - -14.742429018642051\n  - 12.083543435674374\ncentroid:\n  - -15.267509431851042\n  - 11.875198126227332\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\ncountry: GW\ncountry_name: Guinea-Bissau\ncurrency: XOF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Bissau\nzone_name: Guinea-Bissau\n"
  },
  {
    "path": "config/zones/GY.yaml",
    "content": "bounding_box:\n  - - -61.37881378813783\n    - 1.200867308934363\n  - - -56.482764827648225\n    - 8.558064153173135\ncenter_point:\n  - -59.10267406380125\n  - 4.780884949347332\ncentroid:\n  - -59.103129492833325\n  - 4.639098856764174\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 320.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: GY\ncountry_name: Guyana\ncurrency: GYD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Guyana\nzone_name: Guyana\n"
  },
  {
    "path": "config/zones/HK.yaml",
    "content": "bounding_box:\n  - - 113.82621505018244\n    - 22.19333445248411\n  - - 114.3893438934389\n    - 22.555485342338557\ncenter_point:\n  - 114.10777947181067\n  - 22.374409897411333\ncentroid:\n  - 114.14769207474426\n  - 22.39112447222077\ncapacity:\n  coal: 2875\n  gas: 3225\n  oil: 210\ncontributors:\n  - nessie2013\ncountry: HK\ncountry_name: Hong Kong\ncurrency: HKD\ndisclaimer: Real-time consumption and generation mix data is not available and is fully estimated.\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.240000005422131\n        gas: 0.4799998492230482\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.2800003069760345\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.24000009547662696\n        gas: 0.4799998709491746\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.27999986570320606\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.23999990182223815\n        gas: 0.4799999679809028\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.2800001301968592\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.23999982486226049\n        gas: 0.47999998118178144\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.28000019395595815\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2400000834279275\n        gas: 0.480000150905341\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.2799997656667316\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2400000525324899\n        gas: 0.4799999259769462\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.2800000323443843\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2399999736696371\n        gas: 0.4799999308827975\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.27999959078227754\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.24000026494832005\n        gas: 0.4800000374070727\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.2800002122685371\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.23999998146597376\n        gas: 0.4799998066208824\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.27999969273710634\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.24000003301249048\n        gas: 0.47999989763692297\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.28000024359358405\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Asia\ntimezone: Asia/Hong_Kong\nzone_name: Hong Kong\n"
  },
  {
    "path": "config/zones/HM.yaml",
    "content": "bounding_box:\n  - - 73.35253352533525\n    - -53.188866840479925\n  - - 73.73413734137341\n    - -53.017136900524925\ncenter_point:\n  - 73.54333543335433\n  - -53.103001870502425\ncentroid:\n  - 73.53163531635316\n  - -53.092626519963474\ncountry: HM\ncountry_name: Heard Island and McDonald Islands\ncurrency: AUD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Oceania\ntimezone: Asia/Karachi\nzone_name: Heard Island and McDonald Islands\n"
  },
  {
    "path": "config/zones/HN.yaml",
    "content": "bounding_box:\n  - - -89.36189361893614\n    - 12.980110107014383\n  - - -83.13023130231296\n    - 16.00398813305533\ncenter_point:\n  - -86.53741620408366\n  - 14.625236890548269\ncentroid:\n  - -86.43120249384306\n  - 14.730454510161772\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 680.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 710.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 730.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 840.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 850.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 910.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 450.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 510.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 520.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 530.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 770.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 860.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 910.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\ncontributors:\n  - alixunderplatz\n  - VIKTORVAV99\ncountry: HN\ncountry_name: Honduras\nemissionFactors:\n  direct:\n    unknown:\n      _url: https://www.iea.org/fuels-and-technologies/electricity\n      source: IEA 2019; assumes 47.4% oil, 23.1% hydro, 10.6% solar, 8.3% biomass, 7.8% wind, 2.8% geothermal\n      value: 192.444\n  lifecycle:\n    unknown:\n      _url: https://www.iea.org/fuels-and-technologies/electricity\n      source: IEA 2019; assumes 47.4% oil, 23.1% hydro, 10.6% solar, 8.3% biomass, 7.8% wind, 2.8% geothermal\n      value: 339.42599999999993\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.028194620378557068\n        coal: 0.039843986951195266\n        gas: 5.039884994662711e-09\n        geothermal: 0.010125160568101444\n        hydro: 0.1395398401548059\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.22962495614257708\n        solar: 0.04312235974914798\n        unknown: 0.4770350556888918\n        wind: 0.032514243496177084\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.028920676706033852\n        coal: 0.039356811306208106\n        gas: 4.988444440781012e-09\n        geothermal: 0.01208409624486301\n        hydro: 0.13973529528841097\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.23159647068535363\n        solar: 0.04265983677998444\n        unknown: 0.4713534451184113\n        wind: 0.0342933705917044\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03395486053960545\n        coal: 0.044068473835207365\n        gas: 2.0145731833138926e-06\n        geothermal: 0.011336099667470014\n        hydro: 0.13470658547732492\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.23576618647086026\n        solar: 0.0428102356076111\n        unknown: 0.46546280939969603\n        wind: 0.031892722156145276\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004633432480585234\n        coal: 0.013556426797948308\n        gas: 2.972143262131751e-05\n        geothermal: 0.008832461919574703\n        hydro: 0.03276557727968624\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.015865138479348364\n        solar: 0.0034099851471713033\n        unknown: 0.9165989395225304\n        wind: 0.004308223972370629\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005596033538635746\n        coal: 0.0056262140891660045\n        gas: 7.080503677969307e-05\n        geothermal: 0.00813624180980979\n        hydro: 0.023335834124683024\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.010901792499591348\n        solar: 0.0009047279652933471\n        unknown: 0.9391041494167907\n        wind: 0.006324095023422031\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005484526792874092\n        coal: 0.0024835436944604574\n        gas: 0.00012275422168857777\n        geothermal: 0.00718103410559315\n        hydro: 0.028352606929175767\n        hydro discharge: 0.0\n        nuclear: 4.566642494226025e-05\n        oil: 0.009226802266760719\n        solar: 0.0032293376562794844\n        unknown: 0.9414240049983907\n        wind: 0.00244954250988334\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05536808411078644\n        coal: 0.05767135255689859\n        gas: 3.658292334968547e-06\n        geothermal: 0.0194381138581323\n        hydro: 0.23577457510468383\n        hydro discharge: 0.0\n        nuclear: 7.459597063340786e-07\n        oil: 0.4094152124449237\n        solar: 0.07679300558941253\n        unknown: 0.08802322239481493\n        wind: 0.05751164214237619\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01407914220634024\n        coal: 0.03691603584935499\n        gas: 8.431346197763277e-05\n        geothermal: 0.013755364830648445\n        hydro: 0.31991004643405974\n        hydro discharge: 0.0\n        nuclear: 1.8958923933538982e-06\n        oil: 0.45881208077409275\n        solar: 0.08937585918740454\n        unknown: 0.0017265823617785528\n        wind: 0.06533864088864909\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: HN.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Tegucigalpa\nzone_name: Honduras\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nisRenewable:\n  unknown:\n    _url: https://www.iea.org/fuels-and-technologies/electricity\n    source: IEA 2019; assumes 47.4% oil, 23.1% hydro, 10.6% solar, 8.3% biomass, 7.8% wind, 2.8% geothermal\n    value: 0.526\nisLowCarbon:\n  unknown:\n    _url: https://www.iea.org/fuels-and-technologies/electricity\n    source: IEA 2019; assumes 47.4% oil, 23.1% hydro, 10.6% solar, 8.3% biomass, 7.8% wind, 2.8% geothermal\n    value: 0.526\n"
  },
  {
    "path": "config/zones/HR.yaml",
    "content": "bounding_box:\n  - - 13.505535055350578\n    - 42.41605289813427\n  - - 19.391593915939183\n    - 46.5017943862303\ncenter_point:\n  - 16.780691453932263\n  - 45.77659997090309\ncentroid:\n  - 16.439104963733648\n  - 44.678020319727736\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 42.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 58.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 77.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 97.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 114.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 117.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 120.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 122.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 325.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 332.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 217.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 743.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 750.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 766.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 886.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 798.0\n  geothermal:\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 10.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1809.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1857.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1865.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1872.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1874.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 281.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 283.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 281.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 950.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 937.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 77.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 75.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 45.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 51.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 52.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 53.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 85.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 96.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 140.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 292.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 450.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 39.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 46.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 49.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 50.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 54.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 57.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 83.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 95.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 115.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 537.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 582.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 616.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 739.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 796.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 925.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 981.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1209.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1240.0\ncontributors:\n  - PaulCornelissen\n  - VIKTORVAV99\ncountry: HR\ncountry_name: Croatia\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 236.88\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 419.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 264.14\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 294.03\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 327.75\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 255.0\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 181.56\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 200.66\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 269.88\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1161.707429\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1179.944663\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 274.84\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 304.73\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 338.45\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 265.7\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 192.26\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 211.36\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 29.03333333\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03714358092841301\n        coal: 0.18248433288440324\n        gas: 0.18004465228542288\n        geothermal: 0.0025773008076857788\n        hydro: 0.31158380007689995\n        hydro discharge: 0.0220005803925842\n        nuclear: 0.11465508589118767\n        oil: 0.0017878854420868677\n        solar: 0.007652357831187397\n        unknown: 0.026809255886329545\n        wind: 0.11326102492109179\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03047630894940538\n        coal: 0.2713433997798753\n        gas: 0.14542783389760208\n        geothermal: 0.002264553380755183\n        hydro: 0.3384032337766896\n        hydro discharge: 0.02098532568186818\n        nuclear: 0.06701514502814651\n        oil: 0.0014621394588223155\n        solar: 0.007031385451811785\n        unknown: 0.019309381569047896\n        wind: 0.09628129199697524\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03137280739770555\n        coal: 0.18380799904505488\n        gas: 0.15747582510228023\n        geothermal: 0.0036967911264483514\n        hydro: 0.3537634729290753\n        hydro discharge: 0.030146036422878737\n        nuclear: 0.11416901508987251\n        oil: 0.003081916236556463\n        solar: 0.008428323480463065\n        unknown: 0.0269340269082182\n        wind: 0.08712370588289987\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.035221373994239344\n        coal: 0.1521541859006157\n        gas: 0.18751915593487953\n        geothermal: 0.004012439566669408\n        hydro: 0.3354966168711112\n        hydro discharge: 0.029692623383062527\n        nuclear: 0.11795184128054788\n        oil: 0.0017802647773254405\n        solar: 0.01564367022261175\n        unknown: 0.024142202805713435\n        wind: 0.09638560630281806\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03400628329515911\n        coal: 0.1928593167059878\n        gas: 0.1477839143519467\n        geothermal: 0.003386561659823904\n        hydro: 0.37260353346026154\n        hydro discharge: 0.02481586904772998\n        nuclear: 0.08548172673940971\n        oil: 0.0017936245882225602\n        solar: 0.016986173188616248\n        unknown: 0.023633136000708436\n        wind: 0.09664970932757129\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.039136295248590434\n        coal: 0.2108274019276354\n        gas: 0.187754923454704\n        geothermal: 0.002809933664613994\n        hydro: 0.2689177545164959\n        hydro discharge: 0.023699352017680593\n        nuclear: 0.10625854820775024\n        oil: 0.0010189418297773284\n        solar: 0.024240874806542526\n        unknown: 0.02165615854140667\n        wind: 0.11367974943282887\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.034699305685057545\n        coal: 0.15461055837968896\n        gas: 0.17053518554167435\n        geothermal: 0.0007193703186699413\n        hydro: 0.3834124400551386\n        hydro discharge: 0.02969293088362235\n        nuclear: 0.06951623473024222\n        oil: 0.003638262092048274\n        solar: 0.02333770114441868\n        unknown: 0.013407775908437738\n        wind: 0.11643000669710739\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.7979506565395936e-08\n        biomass: 0.03777529681329774\n        coal: 0.11434395973561551\n        gas: 0.15676293816021686\n        geothermal: 2.3421246142958878e-05\n        hydro: 0.34721918805870766\n        hydro discharge: 0.03339468603370947\n        nuclear: 0.11820623831900715\n        oil: 0.0006225589707647073\n        solar: 0.04950457002421131\n        unknown: 0.016567806203726613\n        wind: 0.12557913883108035\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.6141\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.6154\n    - datetime: '2021-01-01'\n      value: 0.6112\n    - datetime: '2022-01-01'\n      value: 0.5602\n    - datetime: '2023-01-01'\n      value: 0.6318\n    - datetime: '2024-01-01'\n      value: 0.7126\n    - datetime: '2025-01-01'\n      value: 0.6966\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.38\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4602\n    - datetime: '2021-01-01'\n      value: 0.4912\n    - datetime: '2022-01-01'\n      value: 0.4222\n    - datetime: '2023-01-01'\n      value: 0.5398\n    - datetime: '2024-01-01'\n      value: 0.5621\n    - datetime: '2025-01-01'\n      value: 0.5445\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Belgrade\nzone_name: Croatia\n"
  },
  {
    "path": "config/zones/HT.yaml",
    "content": "bounding_box:\n  - - -74.49014490144896\n    - 18.026108176025446\n  - - -71.63891638916384\n    - 19.943759172189615\ncenter_point:\n  - -72.25434199683781\n  - 19.20475271548844\ncentroid:\n  - -72.79953287337747\n  - 18.81379710996131\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 400.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: HT\ncountry_name: Haiti\ncurrency: HTG\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Port-au-Prince\nzone_name: Haiti\n"
  },
  {
    "path": "config/zones/HU.yaml",
    "content": "bounding_box:\n  - - 16.093960939609417\n    - 45.74332048476238\n  - - 22.876428764287652\n    - 48.56970907985509\ncenter_point:\n  - 19.42737645539983\n  - 47.14329197684983\ncentroid:\n  - 19.229043137889025\n  - 47.26339726541773\ncapacity:\n  battery storage:\n    - datetime: '2024-09-01'\n      source: mavir.hu\n      value: 35.3\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 274.05\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 286.49\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 305.39\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 300.09000000000003\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 262.09000000000003\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 263.28999999999996\n    - datetime: '2024-10-01'\n      source: mavir.hu\n      value: 384.5\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 363.08799999999997\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1048.87\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 828.9\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4113.72\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 4106.94\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4028.43\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 4030.29\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 4011.36\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 3974.48\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 3151.14\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 3160.86\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 2972.707\n  geothermal:\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 2.7\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 55.980000000000004\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 56.2\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 57.81\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 58.29\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 61.19\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 61.16\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 62.357\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1886.79\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1898.87\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1909.93\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1915.6\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 410.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 412.06\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 421.06\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 420.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 424.8\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 69.73\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 335.55\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 936.25\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1406.51\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1828.66\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2523.57\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 3300.37\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 3888.0\n    - datetime: '2024-10-01'\n      source: mavir.hu\n      value: 3964.8\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 8127.16\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 120\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 215\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 324.25\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 324.9\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 327.48\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 323.28\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 325.08\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 325.075\ncontributors:\n  - corradio\n  - nessie2013\n  - RolandSzep\ncountry: HU\ncountry_name: Hungary\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1144.916957\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1211.37\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1231.95\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1220.63\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 455.1593805\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 459.76\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 387.77\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 383.65\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 837.58\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 734.44\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1157.920756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1224.373799\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1291.95\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1280.63\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 575.1593805\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 579.76\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 507.77\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 503.65\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1081.58\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 978.44\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 30.66666667\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02677222961386532\n        coal: 0.23672991692037493\n        gas: 0.1192228005713514\n        geothermal: 2.720560283512618e-06\n        hydro: 0.057415051918715036\n        hydro discharge: 0.00557896325253772\n        nuclear: 0.4707830036160992\n        oil: 0.002357019357480844\n        solar: 0.006887734794729681\n        unknown: 0.04905661546109503\n        wind: 0.02522386696202215\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.026460157467515434\n        coal: 0.22209115048696362\n        gas: 0.14367645721246633\n        geothermal: 4.43828199599571e-06\n        hydro: 0.06836067575875206\n        hydro discharge: 0.006122340290549228\n        nuclear: 0.4561516923684028\n        oil: 0.002417270394168044\n        solar: 0.006402302671057955\n        unknown: 0.04385857425789696\n        wind: 0.024479133729618623\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.029541179022631352\n        coal: 0.19994026795024863\n        gas: 0.16639260962347838\n        geothermal: 7.84029985231489e-06\n        hydro: 0.07242049483385048\n        hydro discharge: 0.008663698792216366\n        nuclear: 0.4421994563077085\n        oil: 0.0025381173918891547\n        solar: 0.008139040300923278\n        unknown: 0.038597323911064046\n        wind: 0.03155993628761045\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03062603208973982\n        coal: 0.20474888497525057\n        gas: 0.1626209122012831\n        geothermal: 3.207476678349254e-05\n        hydro: 0.07566513981107871\n        hydro discharge: 0.0074212897979227446\n        nuclear: 0.44875921920865564\n        oil: 0.002029744969622291\n        solar: 0.007096601501876847\n        unknown: 0.032048555688294345\n        wind: 0.028951531683657043\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03415867006899902\n        coal: 0.16017417572981563\n        gas: 0.1928616164728739\n        geothermal: 1.5131043777749034e-05\n        hydro: 0.0839286374797521\n        hydro discharge: 0.00955684270267986\n        nuclear: 0.4383682511251654\n        oil: 0.002710154403832648\n        solar: 0.011974879652490649\n        unknown: 0.02912740586857016\n        wind: 0.03712422631904007\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.035706302061067285\n        coal: 0.1343189485479713\n        gas: 0.20674894436942884\n        geothermal: 4.046039417894029e-05\n        hydro: 0.09016245941415103\n        hydro discharge: 0.01274526346105732\n        nuclear: 0.4153496403861656\n        oil: 0.0023622915354444707\n        solar: 0.03988277201239072\n        unknown: 0.02525741634281388\n        wind: 0.03742544363411872\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03386997885848618\n        coal: 0.1385518168466154\n        gas: 0.21148812772212258\n        geothermal: 8.273325020834648e-05\n        hydro: 0.07245932718622863\n        hydro discharge: 0.007973047317468146\n        nuclear: 0.4237339187472755\n        oil: 0.0027873834566959944\n        solar: 0.05144623344909048\n        unknown: 0.02838008779631032\n        wind: 0.02922732166222213\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03341300968142968\n        coal: 0.143841960909077\n        gas: 0.1857436290914904\n        geothermal: 2.768451006155094e-05\n        hydro: 0.061779318118015944\n        hydro discharge: 0.00892921357986945\n        nuclear: 0.4377724952740761\n        oil: 0.0039791136431989805\n        solar: 0.06456463123038297\n        unknown: 0.028288692587188552\n        wind: 0.03166020919243318\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.027357307891715057\n        coal: 0.120527344334797\n        gas: 0.16268404175751272\n        geothermal: 4.2267900642947354e-05\n        hydro: 0.08472098034717733\n        hydro discharge: 0.010023168359666547\n        nuclear: 0.44590669714984715\n        oil: 0.0027684932750590622\n        solar: 0.08791998437723225\n        unknown: 0.021543370166879516\n        wind: 0.03650624789506747\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.150515447643365e-08\n        biomass: 0.03251387631961601\n        coal: 0.10598873468477134\n        gas: 0.15423690876665253\n        geothermal: 8.683260719245595e-05\n        hydro: 0.09915327861092321\n        hydro discharge: 0.014975337432650136\n        nuclear: 0.420607004117204\n        oil: 0.002845170038668794\n        solar: 0.10816140658379693\n        unknown: 0.020690707196941514\n        wind: 0.04074064310307531\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Budapest\nzone_name: Hungary\n"
  },
  {
    "path": "config/zones/ID.yaml",
    "content": "bounding_box:\n  - - 95.19755197551976\n    - -10.920404286222691\n  - - 140.97560975609755\n    - 5.650103836601815\ncenter_point:\n  - 119.23989912755863\n  - -2.839451042984239\ncentroid:\n  - 118.96890483770892\n  - -2.8660618025422737\ncapacity:\n  biomass: 3005\n  coal: 36668\n  gas: 20762\n  geothermal: 2343\n  hydro: 6689\n  nuclear: 0\n  oil: 4864\n  solar: 291\n  wind: 154\ncontributors:\n  - nessie2013\ncountry: ID\ncountry_name: Indonesia\ncurrency: IDR\ndisclaimer: Real-time consumption and generation mix data is not available and is fully estimated.\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010000418109461053\n        coal: 0.6590001862487598\n        gas: 0.18699983655721064\n        geothermal: 0.057000102626867714\n        hydro: 0.07099992778109307\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.024999904975122483\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001000178371160777\n        coal: 0.6590001971470723\n        gas: 0.18700013648643465\n        geothermal: 0.0570000570498854\n        hydro: 0.07100002671956657\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.025000126376328476\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0009999580485275375\n        coal: 0.6589998631419177\n        gas: 0.18700006395880234\n        geothermal: 0.05700001581776834\n        hydro: 0.07100011622621061\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.02499998280677359\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010000859936102158\n        coal: 0.6589998877487988\n        gas: 0.18699999803068065\n        geothermal: 0.05699997833748749\n        hydro: 0.07099986936848524\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.024999852301051163\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0009998888878791576\n        coal: 0.6589999102116081\n        gas: 0.18699993784707583\n        geothermal: 0.056999944122977\n        hydro: 0.070999957922792\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.025000047069258766\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010000090253522145\n        coal: 0.658999930805633\n        gas: 0.18699988267042125\n        geothermal: 0.0569999127549286\n        hydro: 0.07100003910985958\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.02499992478873154\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001000119852653437\n        coal: 0.6590001400687637\n        gas: 0.18699988592337807\n        geothermal: 0.056999900363456764\n        hydro: 0.07100013429273218\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.025000108300590452\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000999944185287075\n        coal: 0.6590001502276599\n        gas: 0.18700011468396235\n        geothermal: 0.05699987309789149\n        hydro: 0.07099992474732733\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.024999993057871518\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010000489328755927\n        coal: 0.658999892240717\n        gas: 0.18700005909380069\n        geothermal: 0.05700011524628079\n        hydro: 0.07099999812825067\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.02499988635807582\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0009998883746002566\n        coal: 0.6589999105288689\n        gas: 0.18700000748291276\n        geothermal: 0.05700008225333488\n        hydro: 0.07100006625639553\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.02500004510388751\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Asia\ntimezone: Asia/Jakarta\nzone_name: Indonesia\n"
  },
  {
    "path": "config/zones/IE.yaml",
    "content": "bounding_box:\n  - - -10.459904599045956\n    - 51.44618557410132\n  - - -5.995859958599567\n    - 55.38595661323561\ncenter_point:\n  - -7.972821743329928\n  - 52.93813739678835\ncentroid:\n  - -8.584698346983439\n  - 53.3427728198179\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 920.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4600.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 4490.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4430.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 4820.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 880.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 340.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 890.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1340.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3320.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3670.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 4130.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 4310.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 4340.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4540.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4740.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 4940.0\ncontributors:\n  - corradio\n  - nessie2013\ncountry: IE\ncountry_name: Ireland\ncurrency: EUR\ndisclaimer: The complete generation mix is unavailable. It is therefore estimated\n  by Electricity Maps.\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 758.4409086\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1082.54\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1198.31\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 977.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 396.8903896\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 465.78\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 403.88\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 911.7365666\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 984.56\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 830.69\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 786.9856885999999\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1111.08478\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1258.31\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1037.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 516.8903895999999\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 585.78\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 523.88\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1155.7365666\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1228.56\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1074.69\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 42.13333333\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.582612936960853e-05\n        coal: 0.29111289412171837\n        gas: 0.33294133275284055\n        geothermal: 0.0\n        hydro: 0.02926791027905611\n        hydro discharge: 0.02761871746924221\n        nuclear: 0.010706576038933888\n        oil: 0.05475903957490735\n        solar: 0.0020611278906416076\n        unknown: 0.0019041233937288002\n        wind: 0.24953819282343626\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.9632805467977483e-05\n        coal: 0.26723817430027696\n        gas: 0.36046205246518087\n        geothermal: 0.0\n        hydro: 0.023921285841728254\n        hydro discharge: 0.030127489457405433\n        nuclear: 0.0048360584642217425\n        oil: 0.08539935678395623\n        solar: 0.0012956285930447015\n        unknown: 0.0020271157775442555\n        wind: 0.2246631964147288\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.027842825536771896\n        coal: 0.10787342777227489\n        gas: 0.5535367154689157\n        geothermal: 0.0\n        hydro: 0.030135959063761222\n        hydro discharge: 0.00029625353164882805\n        nuclear: 0.004351937211275199\n        oil: 0.025593516358143997\n        solar: 0.001081973586640834\n        unknown: 0.0015707894459496422\n        wind: 0.24771631992609142\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.027282423576123083\n        coal: 0.09995457642551166\n        gas: 0.5233526744509518\n        geothermal: 0.0\n        hydro: 0.027529440451698577\n        hydro discharge: 0.00032657087412692637\n        nuclear: 0.005829896111474441\n        oil: 0.023715473184419494\n        solar: 0.0015542212074896907\n        unknown: 0.0008133733589975208\n        wind: 0.2896410041778719\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.026632954308198585\n        coal: 0.09536062677810309\n        gas: 0.5020086172461717\n        geothermal: 1.3884374630346966e-09\n        hydro: 0.02680260782891616\n        hydro discharge: 2.3422245782663814e-05\n        nuclear: 0.007178224807873673\n        oil: 0.023032441964916824\n        solar: 0.003914887213193202\n        unknown: 0.0008514075549105297\n        wind: 0.3141945035543636\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02489102705979321\n        coal: 0.09050289325762267\n        gas: 0.47338221949368436\n        geothermal: 2.0607381346453047e-09\n        hydro: 0.025037452807950434\n        hydro discharge: 1.616546029722509e-05\n        nuclear: 0.004451093738121616\n        oil: 0.021877187234183772\n        solar: 0.00245079602259639\n        unknown: 0.000837714780590932\n        wind: 0.35655319907856337\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.027079216693105906\n        coal: 0.09640251774245905\n        gas: 0.5065904910275496\n        geothermal: 2.623801637678524e-09\n        hydro: 0.026804885112878433\n        hydro discharge: 3.0377391435427817e-05\n        nuclear: 0.006431643944565802\n        oil: 0.023492616948034936\n        solar: 0.004504270104171376\n        unknown: 0.0009999626177141423\n        wind: 0.30766352448742684\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02506826888803386\n        coal: 0.09427409112262482\n        gas: 0.4906387287235398\n        geothermal: 0.0\n        hydro: 0.02576793564661516\n        hydro discharge: 5.718129146439685e-06\n        nuclear: 0.001867281501097867\n        oil: 0.022955601803114928\n        solar: 0.0018242068502549052\n        unknown: 0.0008244677302068245\n        wind: 0.33677316911674543\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 3.1715171716028265e-10\n        biomass: 0.024685585096010192\n        coal: 0.08468381952508681\n        gas: 0.45273689762797936\n        geothermal: 6.343034343205653e-09\n        hydro: 0.025887375392335144\n        hydro discharge: 5.246672572154272e-05\n        nuclear: 0.010600434593124885\n        oil: 0.020244909211778378\n        solar: 0.006646385520545423\n        unknown: 0.0012175739858328696\n        wind: 0.37324418727995884\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.542812874068128e-07\n        biomass: 0.025250695564472615\n        coal: 0.08431267995022841\n        gas: 0.44016764387180357\n        geothermal: 7.3135598996457554e-09\n        hydro: 0.02666753863803497\n        hydro discharge: 7.21621990002904e-05\n        nuclear: 0.009406918756662332\n        oil: 0.020654582180495144\n        solar: 0.004312371638404209\n        unknown: 0.0012949211543286639\n        wind: 0.38786013638875366\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: SMARTGRIDDASHBOARD.fetch_consumption\n  consumptionForecast: SMARTGRIDDASHBOARD.fetch_consumption_forecast\n  generationForecast: SMARTGRIDDASHBOARD.fetch_total_generation\n  price: ENTSOE.fetch_price\n  production: SMARTGRIDDASHBOARD.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\n  productionPerModeForecast: SMARTGRIDDASHBOARD.fetch_wind_solar_forecasts\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Dublin\nzone_name: Ireland\n"
  },
  {
    "path": "config/zones/IL.yaml",
    "content": "bounding_box:\n  - - 34.248942489424905\n    - 29.490512750854634\n  - - 35.88695886958871\n    - 33.40738646466157\ncenter_point:\n  - 34.854673528375955\n  - 30.92475608739115\ncentroid:\n  - 35.13419134191345\n  - 31.83605751407333\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4900.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4320.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 11270.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 11650.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 11720.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 11870.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 12320.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 12910.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1010.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1350.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2140.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2650.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 3590.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4630.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 5520.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 150\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 340.0\ncontributors:\n  - alixunderplatz\n  - jarek\n  - yuvalabou\ncountry: IL\ncountry_name: Israel\ncurrency: ILS\ndisclaimer: The data source (Israel Electric Corporation) has been blocking access to real-time production mix data. The data is therefore fully estimated by Electricity Maps.\nemissionFactors:\n  direct:\n    unknown:\n      _url: https://www.iea.org/fuels-and-technologies/electricity\n      source: IEA 2020; assumes 28.1% coal, 65.3% gas, 0.4% oil, 5.3% solar, 0.3% wind, 0.3% other\n      value: 459.09\n  lifecycle:\n    unknown:\n      _url: https://www.iea.org/fuels-and-technologies/electricity\n      source: IEA 2020; assumes 28.1% coal, 65.3% gas, 0.4% oil, 5.3% solar, 0.3% wind, 0.3% other\n      value: 558.188\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2893872893867389\n        gas: 0.6735874734313857\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.003978779438552887\n        solar: 0.02955271838212426\n        unknown: 0.0034936070319154357\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.28939078442017924\n        gas: 0.6735956029999322\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.003978828274212072\n        solar: 0.02954100562200617\n        unknown: 0.0034936490859755753\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.22975052304145827\n        gas: 0.7035462674701543\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0042319647618432816\n        solar: 0.059461080175140485\n        unknown: 0.0029153921982436075\n        wind: 9.474423272579382e-05\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2297506168385724\n        gas: 0.7035465497081878\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0042319673520831574\n        solar: 0.05946070252705926\n        unknown: 0.002915394141259118\n        wind: 9.474423260282848e-05\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.22648331307457528\n        gas: 0.693541342803125\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0041718433057065995\n        solar: 0.07281269326902554\n        unknown: 0.0028738901599579354\n        wind: 0.00011683429655197377\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.23160730827504733\n        gas: 0.709232212813954\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.004266198190054066\n        solar: 0.05183532401607507\n        unknown: 0.002938932624888138\n        wind: 0.0001199672648831553\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2347010059371511\n        gas: 0.7187057909580122\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.004323168269065913\n        solar: 0.039204124391915715\n        unknown: 0.002978185989163948\n        wind: 8.764081573890674e-05\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.23049115063053122\n        gas: 0.7058141923740252\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.004245626539946488\n        solar: 0.05645092737869548\n        unknown: 0.0029247867935821917\n        wind: 7.322767438978705e-05\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.22643389262343425\n        gas: 0.6933900115583163\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.004170871051940615\n        solar: 0.07303714245296632\n        unknown: 0.002873307364706397\n        wind: 9.474423246961603e-05\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.22644109548746316\n        gas: 0.6934120940756355\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.004171004131650712\n        solar: 0.07300763261212727\n        unknown: 0.0028733995131826184\n        wind: 9.474408704417814e-05\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisLowCarbon:\n  unknown:\n    _comment: Sum of renewable sources in IL unknown production\n    value: 0.056\nisRenewable:\n  unknown:\n    _comment: Sum of renewable sources in IL unknown production\n    value: 0.056\nparsers:\n  consumption: IL.fetch_consumption\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Jerusalem\nzone_name: Israel\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/IM.yaml",
    "content": "bounding_box:\n  - - -4.789847898478968\n    - 54.056480661417325\n  - - -4.311043110431086\n    - 54.414251369656895\ncenter_point:\n  - -4.550445504455027\n  - 54.23536601553711\ncentroid:\n  - -4.519125191251891\n  - 54.23736953150326\ncapacity:\n  gas:\n    - datetime: '2024-12-20'\n      source: manxutilities.im\n      value: 84.0\n  hydro:\n    - datetime: '2024-12-20'\n      source: manxutilities.im\n      value: 1.2\n  oil:\n    - datetime: '2024-12-20'\n      source: manxutilities.im\n      value: 40.0\n  unknown:\n    - datetime: '2024-12-20'\n      source: suez.co.im\n      value: 5.5\ncontributors:\n  - VIKTORVAV99\n  - AJDelusion\n  - CHirch\ncountry: IM\ncountry_name: Isle of Man\ncurrency: GBP\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: https://www.manxutilities.im/media/2830/mu_annual-report_r9.pdf\n      datetime: '2022-01-01'\n      value:\n        gas: 0.988\n        hydro: 0.007\n        oil: 0.005\n    - _source: https://www.manxutilities.im/media/3096/manx-utilities-annual-report-and-accounts-31-march-2024.pdf\n      datetime: '2024-01-01'\n      value:\n        gas: 0.95\n        hydro: 0.006\n        oil: 0.003\n        unknown: 0.041\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Europe/Isle_of_Man\nzone_name: Isle of Man\n"
  },
  {
    "path": "config/zones/IN-AN.yaml",
    "content": "bounding_box:\n  - - 92.37512375123751\n    - 6.744882203814939\n  - - 93.91953919539193\n    - 13.57114731702616\ncenter_point:\n  - 92.51192511925117\n  - 10.508630054495342\ncentroid:\n  - 92.95014768329501\n  - 11.167188354534888\ncapacity:\n  coal: 0\n  gas: 0\n  hydro: 0\n  nuclear: 0\n  oil: 40.05\ncontributors:\n  - gopikrishna1793\ncountry: IN\ncountry_name: India\ncurrency: INR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Andaman and Nicobar Islands\n"
  },
  {
    "path": "config/zones/IN-EA.yaml",
    "content": "bounding_box:\n  - - 81.39501395013949\n    - 17.79713492275212\n  - - 89.85869858698587\n    - 28.105224568550966\ncenter_point:\n  - 85.95419085014285\n  - 22.697858587070485\ncentroid:\n  - 86.06672657097921\n  - 23.549613966857926\ncapacity:\n  biomass:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 542.8\n  coal:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 36997.0\n  gas:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 80.0\n  hydro:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 6331.75\n  nuclear:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 0.0\n  oil:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 92.71\n  solar:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 1017.1\n    - datetime: '2025-06-30'\n      source: mnre.gov.in\n      value: 1562.73\n  wind:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 0.0\ncontributors:\n  - unitrium\ncountry: IN\ncountry_name: India\ncurrency: INR\nemissionFactors:\n  direct:\n    unknown:\n      source: assumes 43% solar PV and 57% wind\n      value: 0.0\n  lifecycle:\n    unknown:\n      source: assumes 43% solar PV and 57% wind\n      value: 25.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9204173419576945\n        gas: 4.663699360225228e-05\n        geothermal: 0.0\n        hydro: 0.0734560285972423\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.000900266706129403\n        solar: 0.0010170986848603396\n        unknown: 0.004162438043803982\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9204173419576945\n        gas: 4.663699360225228e-05\n        geothermal: 0.0\n        hydro: 0.0734560285972423\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.000900266706129403\n        solar: 0.0010170986848603396\n        unknown: 0.004162438043803982\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9203877317517398\n        gas: 5.473563064504961e-05\n        geothermal: 0.0\n        hydro: 0.07344527655400272\n        hydro discharge: 0.0\n        nuclear: 7.802443288585532e-06\n        oil: 0.0009000045068223704\n        solar: 0.001026629255038424\n        unknown: 0.004161597925206382\n        wind: 1.604637334548192e-05\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.418912332874674e-05\n        coal: 0.9364699008887604\n        gas: 0.0014727496209380562\n        geothermal: 9.535853201048147e-06\n        hydro: 0.05101231894800817\n        hydro discharge: 0.0\n        nuclear: 0.0015677742428984796\n        oil: 0.0007062644363796823\n        solar: 0.0005353725080770343\n        unknown: 0.0077553777690162464\n        wind: 0.00041651090860760315\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.991769434932874e-05\n        coal: 0.8955242420254453\n        gas: 0.001313225466758223\n        geothermal: 8.784184062288093e-06\n        hydro: 0.08957257384066024\n        hydro discharge: 0.0\n        nuclear: 0.0014127227759845277\n        oil: 0.000633430168193716\n        solar: 0.003258960132432804\n        unknown: 0.007341638309611919\n        wind: 0.0008844994779646481\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.78898609109752e-05\n        coal: 0.904150951137157\n        gas: 0.0009422304865436213\n        geothermal: 6.667310192959937e-06\n        hydro: 0.08257342566167789\n        hydro discharge: 0.0\n        nuclear: 0.0013896834336340669\n        oil: 0.0006737068641670865\n        solar: 0.0029251103110570454\n        unknown: 0.006595339745996945\n        wind: 0.0007049955294589873\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.097934246353394e-05\n        coal: 0.9222273469636972\n        gas: 0.001378025886779447\n        geothermal: 5.4518653767807975e-06\n        hydro: 0.06873025178723889\n        hydro discharge: 0.0\n        nuclear: 0.0017350480978251678\n        oil: 0.0013131830747187079\n        solar: 0.0028693542573660683\n        unknown: 0.0007884144941576825\n        wind: 0.0009219367351093905\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.7478165603792046e-05\n        coal: 0.9523537612970427\n        gas: 0.0013016682313202923\n        geothermal: 4.834841705459606e-06\n        hydro: 0.03930738641525212\n        hydro discharge: 0.0\n        nuclear: 0.0017694689940675394\n        oil: 0.0012792304541447755\n        solar: 0.0029855668766264275\n        unknown: 0.0002543184591433458\n        wind: 0.0007162874658442403\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: IN.fetch_consumption\n  production: IN.fetch_production\n  productionCapacity: CEA.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Eastern India\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nisRenewable:\n  unknown:\n    source: assumes 43% solar PV and 57% wind\n    value: 1\nisLowCarbon:\n  unknown:\n    source: assumes 43% solar PV and 57% wind\n    value: 1\n"
  },
  {
    "path": "config/zones/IN-NE.yaml",
    "content": "bounding_box:\n  - - 89.6570965709657\n    - 21.9773278778234\n  - - 97.33237332373321\n    - 29.368870710053173\ncenter_point:\n  - 93.46513273903494\n  - 25.965802511426382\ncentroid:\n  - 93.27572241239659\n  - 26.101683928567358\ncapacity:\n  biomass:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 15.8\n  coal:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 750.0\n  gas:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 1664.95\n  hydro:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 2348.8\n  nuclear:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 0.0\n  oil:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 36.0\n  solar:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 236.9\n    - datetime: '2025-06-30'\n      source: mnre.gov.in\n      value: 331.53\n  wind:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 0.0\ncontributors:\n  - unitrium\ncountry: IN\ncountry_name: India\ncurrency: INR\nemissionFactors:\n  direct:\n    unknown:\n      source: assumes 43% solar PV and 57% wind\n      value: 0.0\n  lifecycle:\n    unknown:\n      source: assumes 43% solar PV and 57% wind\n      value: 25.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2219556276745726\n        gas: 0.4608899247562376\n        geothermal: 0.0\n        hydro: 0.31185539898997355\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.005286594787475135\n        unknown: 8.30252782742898e-06\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2219556276745726\n        gas: 0.4608899247562376\n        geothermal: 0.0\n        hydro: 0.31185539898997355\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.005286594787475135\n        unknown: 8.30252782742898e-06\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2219556276745726\n        gas: 0.4608899247562376\n        geothermal: 0.0\n        hydro: 0.31185539898997355\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.005286594787475135\n        unknown: 8.30252782742898e-06\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1617725244877785\n        gas: 0.5784903386936044\n        geothermal: 0.0\n        hydro: 0.25822804879252004\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0015092962330757122\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.19403725923268053\n        gas: 0.4682182776529213\n        geothermal: 0.0\n        hydro: 0.30537515716326846\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.03235116253737362\n        unknown: 1.8112581206614726e-05\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.0428727480551613e-08\n        coal: 0.21209746897277876\n        gas: 0.4466830065177961\n        geothermal: 1.8136917357481066e-09\n        hydro: 0.31252616992808874\n        hydro discharge: 0.0\n        nuclear: 5.903566599860088e-07\n        oil: 4.896967686519888e-08\n        solar: 0.02867349329656134\n        unknown: 1.8944010179888975e-05\n        wind: 2.688797998246568e-07\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.945325246050424e-06\n        coal: 0.24059638737880787\n        gas: 0.4534683489088665\n        geothermal: 3.3360498069026804e-07\n        hydro: 0.27610152488988005\n        hydro discharge: 0.0\n        nuclear: 0.0001666157466287983\n        oil: 1.7514496088897787e-05\n        solar: 0.029507679601670056\n        unknown: 4.54983704255339e-05\n        wind: 9.41671611809189e-05\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.0727915338724127e-06\n        coal: 0.24256515029057707\n        gas: 0.40154424864029137\n        geothermal: 5.553706859097771e-07\n        hydro: 0.32427913720945384\n        hydro discharge: 0.0\n        nuclear: 0.00018710540623764058\n        oil: 2.4340909080610107e-05\n        solar: 0.031236037656665508\n        unknown: 2.5385940511502566e-05\n        wind: 0.0001348859595530266\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: IN.fetch_consumption\n  production: IN.fetch_production\n  productionCapacity: CEA.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: North Eastern India\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nisRenewable:\n  unknown:\n    source: assumes 43% solar PV and 57% wind\n    value: 1\nisLowCarbon:\n  unknown:\n    source: assumes 43% solar PV and 57% wind\n    value: 1\n"
  },
  {
    "path": "config/zones/IN-NO.yaml",
    "content": "bounding_box:\n  - - 69.46449464494646\n    - 23.036329174212554\n  - - 84.59904599045993\n    - 35.495336317947775\ncenter_point:\n  - 76.8475901001024\n  - 29.293433593829924\ncentroid:\n  - 77.41178232491549\n  - 27.448364557060167\ncapacity:\n  biomass:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 3377.9\n  coal:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 44285.0\n  gas:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 5994.96\n  hydro:\n    - datetime: '2023-12-01'\n      source: cea.nic.in, mnre.gov.in\n      value: 21469.8\n  nuclear:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 1620.0\n  oil:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 0.0\n  solar:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 25012.2\n    - datetime: '2025-06-30'\n      source: mnre.gov.in\n      value: 40245.36\n  wind:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 5193.4\ncontributors:\n  - corradio\n  - gopikrishna1793\n  - hectorespert\n  - pierresegonne\n  - sahitya-pavurala\n  - willbeaufoy\n  - mathilde-daugy\ncountry: IN\ncountry_name: India\ncurrency: INR\nemissionFactors:\n  direct:\n    unknown:\n      source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n      value: 45\n  lifecycle:\n    unknown:\n      source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n      value: 192\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6583105570870201\n        gas: 0.023990722146757116\n        geothermal: 0.0\n        hydro: 0.20768329821776652\n        hydro discharge: 0.0\n        nuclear: 0.028094003710777454\n        oil: 0.0\n        solar: 0.04967895825659537\n        unknown: 0.0132010881270358\n        wind: 0.01904127602599394\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6582143787658119\n        gas: 0.02399372483936023\n        geothermal: 0.0\n        hydro: 0.20759058325974514\n        hydro discharge: 0.0\n        nuclear: 0.02809091010071332\n        oil: 0.0\n        solar: 0.0498740099498704\n        unknown: 0.013187314480516578\n        wind: 0.019048989945975113\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5798938890346982\n        gas: 0.03274811591611273\n        geothermal: 0.0\n        hydro: 0.2328806323518068\n        hydro discharge: 0.0\n        nuclear: 0.03149215377158012\n        oil: 4.068070143068891e-10\n        solar: 0.10485494122097148\n        unknown: 0.0003495395704818654\n        wind: 0.017780724947693897\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.20873245281953e-07\n        coal: 0.6088875915609018\n        gas: 0.02738967033642904\n        geothermal: 2.1258361196479225e-08\n        hydro: 0.1993511904807755\n        hydro discharge: 0.0\n        nuclear: 0.02899423598980073\n        oil: 3.763029345314802e-07\n        solar: 0.12117078377259137\n        unknown: 0.013479138448900625\n        wind: 0.0007268626523638076\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.750579559547814e-08\n        coal: 0.649598671024667\n        gas: 0.016007212220965402\n        geothermal: 3.0635142292086743e-09\n        hydro: 0.18816559690650533\n        hydro discharge: 0.0\n        nuclear: 0.025009829806716708\n        oil: 1.0091576284452102e-07\n        solar: 0.10860953812648917\n        unknown: 0.011944365207907493\n        wind: 0.0006646626472946362\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.4217480068072647e-09\n        coal: 0.6620310300230235\n        gas: 0.01766954088079439\n        geothermal: 4.1221242669059816e-10\n        hydro: 0.17673538473110867\n        hydro discharge: 0.0\n        nuclear: 0.022071079785800415\n        oil: 5.7014131266643354e-08\n        solar: 0.10924628610699928\n        unknown: 0.011312647777378849\n        wind: 0.0009339684765815793\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.8472769350879873e-08\n        coal: 0.6764372202815807\n        gas: 0.017133683414565087\n        geothermal: 3.2614352667513897e-09\n        hydro: 0.16721331013943516\n        hydro discharge: 0.0\n        nuclear: 0.025669495017883813\n        oil: 1.6685502824700107e-07\n        solar: 0.10640189695651557\n        unknown: 0.006269657448041951\n        wind: 0.0008745467698962447\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisLowCarbon:\n  unknown:\n    value: 0.92\nisRenewable:\n  unknown:\n    value: 0.92\nparsers:\n  consumption: IN.fetch_consumption\n  production: IN.fetch_production\n  productionCapacity: CEA.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Northern India\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/IN-SO.yaml",
    "content": "bounding_box:\n  - - 74.09054090540906\n    - 8.075789238466186\n  - - 84.7790477904779\n    - 19.890809107370146\ncenter_point:\n  - 79.14854032908883\n  - 13.923305994389636\ncentroid:\n  - 78.66001517158028\n  - 15.356275499738286\ncapacity:\n  biomass:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 3740.7\n  coal:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 41357.5\n  gas:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 6491.8\n  hydro:\n    - datetime: '2023-12-01'\n      source: cea.nic.in, mnre.gov.in\n      value: 13675.65\n  nuclear:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 3320.0\n  oil:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 460.49\n  solar:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 26954.5\n    - datetime: '2025-06-30'\n      source: mnre.gov.in\n      value: 32702.85\n  wind:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 20312.4\ncontributors:\n  - hectorespert\n  - gopikrishna1793\n  - unitrium\ncountry: IN\ncountry_name: India\ncurrency: INR\nemissionFactors:\n  direct:\n    unknown:\n      - datetime: '2020-01-01'\n        source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n        value: 45\n  lifecycle:\n    unknown:\n      - datetime: '2020-01-01'\n        source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n        value: 192\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6730236577986359\n        gas: 0.011827544851890718\n        geothermal: 0.0\n        hydro: 0.10187884795224894\n        hydro discharge: 0.0\n        nuclear: 0.07099717567696759\n        oil: 7.648104412854824e-05\n        solar: 0.051094061890915934\n        unknown: 0.013829667045788363\n        wind: 0.07727269397030423\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6730236577986359\n        gas: 0.011827544851890718\n        geothermal: 0.0\n        hydro: 0.10187884795224894\n        hydro discharge: 0.0\n        nuclear: 0.07099717567696759\n        oil: 7.648104412854824e-05\n        solar: 0.051094061890915934\n        unknown: 0.013829667045788363\n        wind: 0.07727269397030423\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6730528048923717\n        gas: 0.011842726063005633\n        geothermal: 0.0\n        hydro: 0.10188192723746096\n        hydro discharge: 0.0\n        nuclear: 0.07097804708769762\n        oil: 7.638655967748217e-05\n        solar: 0.051143148753300165\n        unknown: 0.013832076446719601\n        wind: 0.0771930042215613\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.406190367590839e-07\n        coal: 0.7020006419111058\n        gas: 0.02640840918339795\n        geothermal: 7.748950646463959e-08\n        hydro: 0.14199720638150898\n        hydro discharge: 0.0\n        nuclear: 0.08686874595486202\n        oil: 1.294547607998929e-05\n        solar: 0.016021353910097475\n        unknown: 0.014506603271477887\n        wind: 0.012183570302426538\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.487310876697152e-10\n        coal: 0.5855616996657381\n        gas: 0.013573722979789116\n        geothermal: 9.145518127828586e-11\n        hydro: 0.10808966093561215\n        hydro discharge: 0.0\n        nuclear: 0.060658710045836284\n        oil: 6.43447865562989e-05\n        solar: 0.1339940752639298\n        unknown: 0.011386575611905437\n        wind: 0.08667120275403199\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.1517345945179635e-10\n        coal: 0.5931318987617458\n        gas: 0.008768707480807252\n        geothermal: 5.7304265354872055e-11\n        hydro: 0.10872812117615308\n        hydro discharge: 0.0\n        nuclear: 0.06423031650563892\n        oil: 1.0604154303919073e-07\n        solar: 0.12561961116893577\n        unknown: 0.02149479377562107\n        wind: 0.0780264449462944\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 7.422636504950979e-10\n        coal: 0.6559245660226933\n        gas: 0.005895429015508713\n        geothermal: 2.854860194211915e-11\n        hydro: 0.06336510862188238\n        hydro discharge: 0.0\n        nuclear: 0.06341595094127551\n        oil: 0.00012843196668883668\n        solar: 0.12228156568434956\n        unknown: 0.009545848532265352\n        wind: 0.0794430978735518\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.138656284083163e-09\n        coal: 0.6575995063816819\n        gas: 0.005693343277583411\n        geothermal: 1.4060137102070582e-09\n        hydro: 0.0797491669161583\n        hydro discharge: 0.0\n        nuclear: 0.0607297769208224\n        oil: 0.000152848399366014\n        solar: 0.11570950697748413\n        unknown: 0.004660179852160788\n        wind: 0.07570566354166786\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisRenewable:\n  unknown:\n    source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n    value: 0.92\nisLowCarbon:\n  unknown:\n    source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n    value: 0.92\nparsers:\n  consumption: IN.fetch_consumption\n  production: IN.fetch_production\n  productionCapacity: CEA.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Southern India\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/IN-WE.yaml",
    "content": "bounding_box:\n  - - 68.1828818288183\n    - 14.887743523347837\n  - - 84.35064350643509\n    - 26.85159600687946\ncenter_point:\n  - 76.348170844805\n  - 21.211082449075356\ncentroid:\n  - 76.13088455607804\n  - 22.1402600908422\ncapacity:\n  biomass:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 3167.6\n  coal:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 84386.0\n  gas:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 10806.49\n  hydro:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 8065.7\n  nuclear:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 2540.0\n  oil:\n    - datetime: '2023-12-01'\n      source: cea.nic.in\n      value: 0.0\n  solar:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 19907.4\n    - datetime: '2025-06-30'\n      source: mnre.gov.in\n      value: 41245.91\n  wind:\n    - datetime: '2023-12-01'\n      source: mnre.gov.in\n      value: 19226.1\ncontributors:\n  - GitMatze\n  - alixunderplatz\n  - systemcatch\n  - Manu1400\n  - gopikrishna1793\ncountry: IN\ncountry_name: India\ncurrency: INR\nemissionFactors:\n  direct:\n    unknown:\n      source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n      value: 45\n  lifecycle:\n    unknown:\n      source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n      value: 192\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8433577792659291\n        gas: 0.027097981779287964\n        geothermal: 0.0\n        hydro: 0.03127236521278061\n        hydro discharge: 0.0\n        nuclear: 0.024734128229007717\n        oil: 0.0\n        solar: 0.019200309015410488\n        unknown: 0.00073885914399529\n        wind: 0.053598559889581926\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8433577792659291\n        gas: 0.027097981779287964\n        geothermal: 0.0\n        hydro: 0.03127236521278061\n        hydro discharge: 0.0\n        nuclear: 0.024734128229007717\n        oil: 0.0\n        solar: 0.019200309015410488\n        unknown: 0.00073885914399529\n        wind: 0.053598559889581926\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8423091852055521\n        gas: 0.027032721398226763\n        geothermal: 0.0\n        hydro: 0.03224230307613093\n        hydro discharge: 0.0\n        nuclear: 0.024844603845287264\n        oil: 9.14621576895854e-07\n        solar: 0.019286308901214442\n        unknown: 0.0008279689113278008\n        wind: 0.053455978242283576\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.1266100125772502e-06\n        coal: 0.8050733098868523\n        gas: 0.04788626838449567\n        geothermal: 1.981608708354313e-07\n        hydro: 0.049674175720692236\n        hydro discharge: 0.0\n        nuclear: 0.026930220598704424\n        oil: 1.4522499957886976e-05\n        solar: 0.02527654320998128\n        unknown: 0.0009931945747320143\n        wind: 0.04415044020007452\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.749133008790658e-07\n        coal: 0.8872354145750095\n        gas: 0.031041764447489722\n        geothermal: 1.0106314519163543e-07\n        hydro: 0.04093242851893842\n        hydro discharge: 0.0\n        nuclear: 0.024800940495137674\n        oil: 1.024613821853252e-05\n        solar: 0.01022912816361701\n        unknown: 0.0013957768508403154\n        wind: 0.004353620110657857\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.6910244527256463e-07\n        coal: 0.9020952796933679\n        gas: 0.01192325726518226\n        geothermal: 8.254359698670669e-08\n        hydro: 0.047522322202633305\n        hydro discharge: 0.0\n        nuclear: 0.025344481514419724\n        oil: 5.930320812457567e-06\n        solar: 0.007541864784733179\n        unknown: 0.0015798479861817412\n        wind: 0.003986462882701127\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.9395911103367805e-07\n        coal: 0.8978386390358554\n        gas: 0.017695020548016072\n        geothermal: 6.898010087971744e-08\n        hydro: 0.040944169399095454\n        hydro discharge: 0.0\n        nuclear: 0.02804500483908623\n        oil: 1.5144018447294215e-05\n        solar: 0.008829042629172926\n        unknown: 0.001876897190990641\n        wind: 0.004755616436737487\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.938833569954496e-07\n        coal: 0.8808973040334591\n        gas: 0.025809891943185316\n        geothermal: 5.15957968350004e-08\n        hydro: 0.04354447779871282\n        hydro discharge: 0.0\n        nuclear: 0.033118184257477985\n        oil: 1.3624614551656041e-05\n        solar: 0.011057473179244885\n        unknown: 0.0013893975489840634\n        wind: 0.0041693000739283495\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisRenewable:\n  unknown:\n    source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n    value: 0.92\nisLowCarbon:\n  unknown:\n    source: CEA 2022; assumes 56% biomass, 36% hydro, 8% unknown\n    value: 0.92\nparsers:\n  consumption: IN_WE.fetch_consumption\n  production: IN.fetch_production\n  productionCapacity: CEA.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Kolkata\nzone_name: Western India\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/IN.yaml",
    "content": "bounding_box:\n  - - 68.1828818288183\n    - 8.075789238466186\n  - - 97.33237332373321\n    - 35.495336317947775\ncenter_point:\n  - 82.8526621756506\n  - 21.732832622653902\ncentroid:\n  - 82.604486354839\n  - 24.270677750601468\ncapacity:\n  biomass: 10682.36\n  coal: 210699.5\n  gas: 24879.21\n  hydro: 51608.52\n  nuclear: 6780\n  oil: 509.71\n  solar: 56951.33\n  wind: 40706.38\ncontributors:\n  - systemcatch\n  - gopikrishna1793\n  - unitrium\ncountry: IN\ncountry_name: India\ncurrency: INR\nemissionFactors:\n  direct:\n    unknown:\n      source: assumes 43% solar PV and 57% wind\n      value: 0.0\n  lifecycle:\n    unknown:\n      source: assumes 43% solar PV and 57% wind\n      value: 25.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.7677784706391163\n        gas: 0.0247360880975696\n        geothermal: 0.0\n        hydro: 0.09962567167394039\n        hydro discharge: 0.0\n        nuclear: 0.030526440884796266\n        oil: 0.00016786077922472357\n        solar: 0.02987446190715984\n        unknown: 0.0070184273661270695\n        wind: 0.040272585236621285\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.7677796737901701\n        gas: 0.02474162531496064\n        geothermal: 0.0\n        hydro: 0.09961688716260553\n        hydro discharge: 0.0\n        nuclear: 0.030526424418023335\n        oil: 0.0001678552774701426\n        solar: 0.02989486715596173\n        unknown: 0.00701729725905422\n        wind: 0.040255376180208\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.068362688134132e-06\n        coal: 0.7503837625336328\n        gas: 0.040184879527900966\n        geothermal: 1.5957270308899812e-06\n        hydro: 0.1085626147811119\n        hydro discharge: 0.0\n        nuclear: 0.03324176589257075\n        oil: 0.00011810763683417106\n        solar: 0.03769194944832143\n        unknown: 0.004031360167901762\n        wind: 0.025774901636667\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.413189607483215e-06\n        coal: 0.7458389123025757\n        gas: 0.02729643199213655\n        geothermal: 1.4805194853618045e-06\n        hydro: 0.10457372610070167\n        hydro discharge: 0.0\n        nuclear: 0.02984692538184953\n        oil: 0.00012133154833431564\n        solar: 0.06320881991501172\n        unknown: 0.00743161755355481\n        wind: 0.021672345960293243\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.6590510380609e-06\n        coal: 0.758513489046436\n        gas: 0.01660802023158081\n        geothermal: 1.1717780290254785e-06\n        hydro: 0.10684024142084969\n        hydro discharge: 0.0\n        nuclear: 0.029684229739384012\n        oil: 0.00011668252766613028\n        solar: 0.05930458040144998\n        unknown: 0.00956245752885104\n        wind: 0.0193624722810715\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.365920127561738e-06\n        coal: 0.7837876561416842\n        gas: 0.01813497429344078\n        geothermal: 9.443837558517989e-07\n        hydro: 0.08634644323533333\n        hydro discharge: 0.0\n        nuclear: 0.029578583439089808\n        oil: 0.0002520435360164162\n        solar: 0.05686835119975651\n        unknown: 0.0056214598823901745\n        wind: 0.019404181982341374\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.6387121642457825e-06\n        coal: 0.7889194518919712\n        gas: 0.01998610010683993\n        geothermal: 8.162010554309572e-07\n        hydro: 0.08251354908260189\n        hydro discharge: 0.0\n        nuclear: 0.03202906195091459\n        oil: 0.0002465361764196627\n        solar: 0.05470488852485778\n        unknown: 0.003025741785798069\n        wind: 0.018569211812215346\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: IN.fetch_production\nregion: Asia\nsubZoneNames:\n  - IN-NO\n  - IN-NE\n  - IN-EA\n  - IN-WE\n  - IN-SO\ntimezone: Asia/Kolkata\nzone_name: Mainland India\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nisRenewable:\n  unknown:\n    source: assumes 43% solar PV and 57% wind\n    value: 1\nisLowCarbon:\n  unknown:\n    source: assumes 43% solar PV and 57% wind\n    value: 1\n"
  },
  {
    "path": "config/zones/IQ.yaml",
    "content": "bounding_box:\n  - - 38.788648606335684\n    - 29.062618983800093\n  - - 48.53028530285303\n    - 37.36862374629024\ncenter_point:\n  - 43.44345558532116\n  - 33.21746235405574\ncentroid:\n  - 44.54713255817012\n  - 34.003316815933665\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20080.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 20330.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 21670.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 25970.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 27510.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 32560.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 34030.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1560.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10930.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10990.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 11290.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 12120.0\ncontributors:\n  - alixunderplatz\n  - systemcatch\n  - byronwilliams\ncountry: IQ\ncountry_name: Iraq\ncurrency: IQD\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6710121204328401\n        geothermal: 0.0\n        hydro: 0.01882576318584281\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.31016211133910787\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6833794239764248\n        geothermal: 0.0\n        hydro: 0.05656541075842008\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.2600551558085288\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Baghdad\nzone_name: Iraq\n"
  },
  {
    "path": "config/zones/IR.yaml",
    "content": "bounding_box:\n  - - 44.06264062640628\n    - 25.059880300015635\n  - - 63.31923319233192\n    - 39.76568749149544\ncenter_point:\n  - 53.567567572718346\n  - 32.338104428586206\ncentroid:\n  - 53.14628485010521\n  - 32.724502289243176\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 56390.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 57050.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 61730.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 63840.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 65860.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 68580.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 73500.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 74960.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10910.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 11060.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 11140.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 11150.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 11500.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 11680.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 11780.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1020.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 290.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 350.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 430.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 460.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 540.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 600.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 780.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 300.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 340.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 360.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\ncountry: IR\ncountry_name: Iran\ncurrency: IRR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Tehran\nzone_name: Iran\n"
  },
  {
    "path": "config/zones/IS.yaml",
    "content": "bounding_box:\n  - - -24.53964539645392\n    - 63.39715831213634\n  - - -13.527135271352677\n    - 66.53695404764692\ncenter_point:\n  - -17.82619692663021\n  - 64.8298913248652\ncentroid:\n  - -19.530974414221717\n  - 65.39408488941281\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1990.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2100.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2110.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2150.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 830.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 880.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 890.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 920.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncontributors:\n  - corradio\n  - SNPerkin\n  - nessie2013\ncountry: IS\ncountry_name: Iceland\ncurrency: ISK\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0.0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: EIA 2020/BEIS 2021; IPCC 2014\n      value: 650.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.28098611553654834\n        hydro: 0.7189779502921245\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 3.593417132730596e-05\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.28098611553654834\n        hydro: 0.7189779502921245\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 3.593417132730596e-05\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.30070139247145783\n        hydro: 0.6990214027404852\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0002765598699677303\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.29658338680080415\n        hydro: 0.7033620838853972\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 5.452817213448631e-05\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.27509427664605496\n        hydro: 0.7248819222166444\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 2.382154167634375e-05\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.24455822144176287\n        hydro: 0.7553568516765476\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 8.497249532180886e-05\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.2761102981801818\n        hydro: 0.7238896822920312\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.29750889698499444\n        hydro: 0.7024910885022445\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 3.2250580075461655e-09\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: amper_landsnet.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: Atlantic/Reykjavik\nzone_name: Iceland\n"
  },
  {
    "path": "config/zones/IT-CNO.yaml",
    "content": "bounding_box:\n  - - 9.689496894968983\n    - 42.374551495978466\n  - - 13.905139051390535\n    - 44.476812177594255\ncenter_point:\n  - 12.037452327037272\n  - 43.32144732948173\ncentroid:\n  - 11.634485575625009\n  - 43.387648058418115\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 200\n  gas:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 3047.3\n  geothermal:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 817.1\n  hydro:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 800\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 200\n  oil:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 100\n  solar:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1870\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 1940\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 2060\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 2250\n    - datetime: '2023-01-01'\n      source: dati.terna.it\n      value: 2590\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 2980\n  unknown:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 750\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 500\n  wind:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 165\ncontributors:\n  - corradio\n  - nessie2013\n  - PaulRoms\ncountry: IT\ncountry_name: Italy\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 351.1\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 153.09\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 997.0022828\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1017.96\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 997.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1015.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 427.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 428.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 403.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 397.71\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 257.85\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 921.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 858.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 860.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 905.42\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 384.1\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 186.09\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1082.9825388\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1103.940256\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1057.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1075.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 547.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 548.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 523.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 517.71\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 268.55\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1165.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1102.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1149.42\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.65\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012700319359008063\n        coal: 0.0018588292939964142\n        gas: 0.2922742943845392\n        geothermal: 0.3323585830005895\n        hydro: 0.13996516282923166\n        hydro discharge: 0.0016889350342343507\n        nuclear: 0.0\n        oil: 4.005333904314651e-05\n        solar: 0.12432352651759017\n        unknown: 0.08368619651703321\n        wind: 0.011104110690345845\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008638301043067939\n        coal: 0.000638422952543961\n        gas: 0.33622705276956283\n        geothermal: 0.3119171780966675\n        hydro: 0.14450654924499653\n        hydro discharge: 0.0010742872258778162\n        nuclear: 0.0\n        oil: 0.00010995338030050686\n        solar: 0.1090538479599885\n        unknown: 0.07674840579608036\n        wind: 0.011085995659617001\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0041148461369409405\n        coal: 0.0007805596816630214\n        gas: 0.33086286527129954\n        geothermal: 0.2931997348984763\n        hydro: 0.10935105233542701\n        hydro discharge: 0.0012611635147761217\n        nuclear: 0.0\n        oil: 0.00018155932813681438\n        solar: 0.12262771660685677\n        unknown: 0.12599088138848166\n        wind: 0.011629617285934604\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.015604411173753911\n        coal: 0.05918099774527862\n        gas: 0.24485053842754012\n        geothermal: 0.16079795574683173\n        hydro: 0.17304653719003685\n        hydro discharge: 0.008408236890650098\n        nuclear: 0.023458211116636936\n        oil: 0.000625147930188815\n        solar: 0.10554530139286106\n        unknown: 0.1393470129426022\n        wind: 0.06913560405305787\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01775280383582553\n        coal: 0.03729023498120157\n        gas: 0.3685417178972492\n        geothermal: 0.16437160045391963\n        hydro: 0.14440017057400376\n        hydro discharge: 0.007359942330962472\n        nuclear: 0.024667399440929792\n        oil: 0.0005641046776484951\n        solar: 0.10084691640152822\n        unknown: 0.07619047268042158\n        wind: 0.05801458096222467\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01973484976416781\n        coal: 0.028280774430846436\n        gas: 0.3633157816696252\n        geothermal: 0.18285799714450615\n        hydro: 0.14468574214159555\n        hydro discharge: 0.008243632490792378\n        nuclear: 0.023559744087052727\n        oil: 0.0004287472569554147\n        solar: 0.11134758380770024\n        unknown: 0.062226522822645784\n        wind: 0.055318585315774584\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01814523925045983\n        coal: 0.03779325099879053\n        gas: 0.3628173138255398\n        geothermal: 0.1797848079662567\n        hydro: 0.14313432560555528\n        hydro discharge: 0.011015814703592124\n        nuclear: 0.026444389698415345\n        oil: 0.000638312606476048\n        solar: 0.10044659691108644\n        unknown: 0.05511363712738784\n        wind: 0.06466622409329534\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.014624492136866441\n        coal: 0.0739709158710253\n        gas: 0.3769017589594595\n        geothermal: 0.1748296075148186\n        hydro: 0.07675981363513269\n        hydro discharge: 0.0066803730910780105\n        nuclear: 0.016478105902122914\n        oil: 0.004843988982238166\n        solar: 0.12308512989592708\n        unknown: 0.05503776941914651\n        wind: 0.0767880843399591\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.2021948612167235e-05\n        biomass: 0.01654686470251832\n        coal: 0.0389241475814982\n        gas: 0.3316798079138889\n        geothermal: 0.17129117779006225\n        hydro: 0.13690921296101446\n        hydro discharge: 0.01266485234390985\n        nuclear: 0.033790127956120054\n        oil: 0.003923677318803485\n        solar: 0.12270379177266975\n        unknown: 0.055021442406094204\n        wind: 0.07653286440016613\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 2.155289108853915e-05\n        biomass: 0.018261840008366947\n        coal: 0.011400149606800948\n        gas: 0.32805025859785714\n        geothermal: 0.16535647600855655\n        hydro: 0.16461315214399966\n        hydro discharge: 0.01831844084891487\n        nuclear: 0.05119549650422474\n        oil: 0.0048290203223529385\n        solar: 0.13076921687380502\n        unknown: 0.054046319522626465\n        wind: 0.053137961493694416\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.3357\n    - datetime: '2025-01-01'\n      value: 0.6563\n  hydro discharge:\n    - datetime: '2024-01-01'\n      value: 0.4275\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.3124\n    - datetime: '2025-01-01'\n      value: 0.6168\n  hydro discharge:\n    - datetime: '2024-01-01'\n      value: 0.3613\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Rome\nzone_name: Central North Italy\n"
  },
  {
    "path": "config/zones/IT-CSO.yaml",
    "content": "bounding_box:\n  - - 11.449914499145024\n    - 40.00467832459948\n  - - 15.784357843578448\n    - 42.901189978507134\ncenter_point:\n  - 13.467251296912782\n  - 41.73611562317008\ncentroid:\n  - 13.778849788497904\n  - 41.60608863633651\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 486.7\n  coal:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1865\n  gas:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 2500\n    - datetime: '2018-01-01'\n      source: dati.terna.it\n      value: 3000\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 3500\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 3500\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 4500\n  geothermal:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 0\n  hydro:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 2200\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 3260\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1708.7\n  nuclear:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 0\n  oil:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 96\n  solar:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 3300\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 3450\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 3700\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 4100\n    - datetime: '2023-01-01'\n      source: dati.terna.it\n      value: 4860\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 6660\n  unknown:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 2500\n    - datetime: '2018-01-01'\n      source: dati.terna.it\n      value: 1000\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 700\n  wind:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1700\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 2060\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 2010\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 2250\n    - datetime: '2023-01-01'\n      source: dati.terna.it\n      value: 2300\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 2530\ncontributors:\n  - corradio\n  - nessie2013\n  - PaulRoms\ncountry: IT\ncountry_name: Italy\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 343.72\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 198.93\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 997.0022828\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1017.96\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 997.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1015.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 427.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 428.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 403.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 397.71\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 334.44\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 327.84\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 367.56\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 268.72\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 211.51\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 197.55\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 921.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 858.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 860.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 905.42\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 376.72\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 231.93\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1082.9825388\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1103.940256\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1057.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1075.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 547.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 548.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 523.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 517.71\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 345.14\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 338.54\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 378.26\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 279.42\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 222.21\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 208.25\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1165.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1102.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1149.42\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.46666667\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004341643795531278\n        coal: 0.2748027185217786\n        gas: 0.10766095581047806\n        geothermal: 0.0\n        hydro: 0.10144359128778947\n        hydro discharge: 0.013576370395272323\n        nuclear: 0.0\n        oil: 6.250671193986181e-05\n        solar: 0.09148538898417774\n        unknown: 0.3287523659639374\n        wind: 0.07787455319888055\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0018742532338634741\n        coal: 0.22872643793221312\n        gas: 0.19662421938179703\n        geothermal: 0.0\n        hydro: 0.07714426518335098\n        hydro discharge: 0.012484881817718592\n        nuclear: 0.0\n        oil: 3.739308785980383e-05\n        solar: 0.09204515991667014\n        unknown: 0.29839672802490724\n        wind: 0.09266675331238551\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0017370639787655045\n        coal: 0.27168400215181665\n        gas: 0.2165058134231964\n        geothermal: 0.0\n        hydro: 0.06487321947445887\n        hydro discharge: 0.01142579819850511\n        nuclear: 0.0\n        oil: 6.78672380798177e-05\n        solar: 0.09928712760163112\n        unknown: 0.24329383382608924\n        wind: 0.09112537816461541\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03452464454270999\n        coal: 0.1946489792660019\n        gas: 0.1728442391281182\n        geothermal: 0.004584321939543415\n        hydro: 0.11234426650349229\n        hydro discharge: 0.010669126255225205\n        nuclear: 0.0024434997082409798\n        oil: 0.0010578609305275475\n        solar: 0.1227024004712239\n        unknown: 0.14834765709973896\n        wind: 0.19583297085459672\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03326311813735812\n        coal: 0.14361474252594988\n        gas: 0.3815051959749961\n        geothermal: 0.005416350996857978\n        hydro: 0.07682955744711924\n        hydro discharge: 0.009476333562378494\n        nuclear: 0.0022402002073810415\n        oil: 0.0008098189924124865\n        solar: 0.10386138660160232\n        unknown: 0.07595630570023\n        wind: 0.16702697931583663\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03882664177956653\n        coal: 0.14287997955496112\n        gas: 0.371366937862148\n        geothermal: 0.006107957932673459\n        hydro: 0.07366891516890983\n        hydro discharge: 0.013943040956741325\n        nuclear: 0.0025681435471755685\n        oil: 0.0008956601895849554\n        solar: 0.11609916608129277\n        unknown: 0.06605179582278943\n        wind: 0.16759173593931154\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03126412553456255\n        coal: 0.1364050347253432\n        gas: 0.38069964046236543\n        geothermal: 0.008205840289387848\n        hydro: 0.12241108634296294\n        hydro discharge: 0.013427233777362314\n        nuclear: 0.004518757477883442\n        oil: 0.0009564054625751285\n        solar: 0.10067681761255025\n        unknown: 0.050970638958299626\n        wind: 0.15046442375105615\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03081598075769944\n        coal: 0.1919418878460364\n        gas: 0.361771383986949\n        geothermal: 0.0046236110559689965\n        hydro: 0.07956268393449349\n        hydro discharge: 0.007463534144873479\n        nuclear: 0.0033939295365065813\n        oil: 0.0026535599529579636\n        solar: 0.11277650054751609\n        unknown: 0.048436521546639515\n        wind: 0.15656036476376142\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.7063302881170517e-06\n        biomass: 0.03618909665723572\n        coal: 0.1340261045148552\n        gas: 0.30363528411222873\n        geothermal: 0.013350260661219153\n        hydro: 0.13080839425840093\n        hydro discharge: 0.013799887944673822\n        nuclear: 0.008574415644407193\n        oil: 0.0025754852375485886\n        solar: 0.12553714915502587\n        unknown: 0.040521247604609976\n        wind: 0.19098093066601096\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.872923481687871e-06\n        biomass: 0.04351660826291486\n        coal: 0.04942397474915992\n        gas: 0.3888834731599418\n        geothermal: 0.020460339216476785\n        hydro: 0.11261428638117461\n        hydro discharge: 0.01731197097975358\n        nuclear: 0.015337423346195679\n        oil: 0.0013574077946602791\n        solar: 0.1515683001826803\n        unknown: 0.036306885483708785\n        wind: 0.16321543097369423\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.2611\n    - datetime: '2025-01-01'\n      value: 0.561\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4396\n    - datetime: '2021-01-01'\n      value: 0.441\n    - datetime: '2022-01-01'\n      value: 0.4288\n    - datetime: '2023-01-01'\n      value: 0.5506\n    - datetime: '2024-01-01'\n      value: 0.5641\n    - datetime: '2025-01-01'\n      value: 0.5641\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.2519\n    - datetime: '2025-01-01'\n      value: 0.5506\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4367\n    - datetime: '2021-01-01'\n      value: 0.4363\n    - datetime: '2022-01-01'\n      value: 0.4256\n    - datetime: '2023-01-01'\n      value: 0.5426\n    - datetime: '2024-01-01'\n      value: 0.5489\n    - datetime: '2025-01-01'\n      value: 0.5532\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Rome\nzone_name: Central South Italy\n"
  },
  {
    "path": "config/zones/IT-NO.yaml",
    "content": "bounding_box:\n  - - 6.604266042660441\n    - 43.75840859544918\n  - - 13.917370775527884\n    - 47.09019132836457\ncenter_point:\n  - 10.198444362697781\n  - 45.51613717207519\ncentroid:\n  - 10.577868597479094\n  - 45.268489006048526\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 2400\n  coal:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 2000\n    - datetime: '2020-01-01'\n      source: dati.terna.it\n      value: 1000\n  gas:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 27268\n  geothermal:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 0\n  hydro:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 14000\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 16700\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 17100\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 4764.8\n  oil:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 100\n  solar:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 8700\n    - datetime: '2018-01-01'\n      source: dati.terna.it\n      value: 8950\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 9250\n    - datetime: '2020-01-01'\n      source: dati.terna.it\n      value: 9650\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 10200\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 11500\n    - datetime: '2023-01-01'\n      source: dati.terna.it\n      value: 14600\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 17660\n  unknown:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 100000\n    - datetime: '2018-01-01'\n      source: dati.terna.it\n      value: 8000\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 3500\n    - datetime: '2020-01-01'\n      source: dati.terna.it\n      value: 2500\n  wind:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 120\n    - datetime: '2020-01-01'\n      source: dati.terna.it\n      value: 170\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 250\ncontributors:\n  - corradio\n  - nessie2013\ncountry: IT\ncountry_name: Italy\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 301.11\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 198.6\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 997.0022828\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1017.96\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 997.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1015.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 427.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 428.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 403.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 397.71\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 236.12\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 263.95\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 293.03\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 223.05\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 179.42\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 191.91\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 921.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 858.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 860.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 905.42\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 334.11\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 231.6\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1082.9825388\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1103.940256\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1057.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1075.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 547.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 548.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 523.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 517.71\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 246.82\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 274.65\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 303.73\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 233.75\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 190.12\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 202.61\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1165.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1102.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1149.42\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 27.3\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01418750889256113\n        coal: 0.01935256798920906\n        gas: 0.16200597713032014\n        geothermal: 8.336495060447002e-06\n        hydro: 0.27882320912126624\n        hydro discharge: 0.02417455536803403\n        nuclear: 0.11017990581306804\n        oil: 0.0006128954470947118\n        solar: 0.051622275839889764\n        unknown: 0.32569156302730656\n        wind: 0.013341206830956931\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01355769575246591\n        coal: 0.013861874762955015\n        gas: 0.19010360359649495\n        geothermal: 9.328806710302642e-06\n        hydro: 0.264614347851822\n        hydro discharge: 0.027261370905992587\n        nuclear: 0.05095709543689888\n        oil: 0.00014479687626649671\n        solar: 0.04974050257460854\n        unknown: 0.382359460659296\n        wind: 0.00738991963451529\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02144943160875644\n        coal: 0.04771316722487785\n        gas: 0.21009813771002595\n        geothermal: 1.1167452834729014e-05\n        hydro: 0.2146058532505907\n        hydro discharge: 0.024637149690952247\n        nuclear: 0.0976426618656866\n        oil: 0.0005792850214531471\n        solar: 0.049370127528796506\n        unknown: 0.3206845307037388\n        wind: 0.013208482104881852\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02215503878792769\n        coal: 0.06560862874338762\n        gas: 0.2012893926900009\n        geothermal: 0.0013604204481581256\n        hydro: 0.24795633023757804\n        hydro discharge: 0.02543718436272557\n        nuclear: 0.1096647351345014\n        oil: 0.0009788140711914726\n        solar: 0.04517011456314106\n        unknown: 0.2651721915521026\n        wind: 0.015207145476167371\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.023285548995656113\n        coal: 0.03565967563449606\n        gas: 0.36701109226709105\n        geothermal: 0.001333044147474263\n        hydro: 0.24740044868349279\n        hydro discharge: 0.025433464919204486\n        nuclear: 0.11376215243571568\n        oil: 0.0008712063923574613\n        solar: 0.0495079129828643\n        unknown: 0.1185423868651773\n        wind: 0.01719306406948114\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.024087072783307663\n        coal: 0.015797952866555928\n        gas: 0.39195191766596627\n        geothermal: 0.0019398728205839424\n        hydro: 0.2789222445476349\n        hydro discharge: 0.025488961053282893\n        nuclear: 0.10078063956979785\n        oil: 0.0006805668410475372\n        solar: 0.053763359637610565\n        unknown: 0.08686057221729317\n        wind: 0.019726838558791215\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.025283577345624957\n        coal: 0.023271612446961767\n        gas: 0.4207222807626681\n        geothermal: 0.0031070130215668313\n        hydro: 0.24375437078895065\n        hydro discharge: 0.028408064481128262\n        nuclear: 0.10162057769086433\n        oil: 0.0006431101815498493\n        solar: 0.054409897298177176\n        unknown: 0.08021886889131515\n        wind: 0.018560624630821212\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02587945651214551\n        coal: 0.042166641010810524\n        gas: 0.45442857635646944\n        geothermal: 0.004671479718165094\n        hydro: 0.17484770299953814\n        hydro discharge: 0.02432570696150226\n        nuclear: 0.09913840400990215\n        oil: 0.0010935573073469593\n        solar: 0.06471838245948174\n        unknown: 0.08254027115813706\n        wind: 0.026189824873111372\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 3.7329554655756016e-07\n        biomass: 0.02863912836835315\n        coal: 0.02569795364847865\n        gas: 0.37081435099801374\n        geothermal: 0.0032408037303317087\n        hydro: 0.23875359243433306\n        hydro discharge: 0.028871612970812838\n        nuclear: 0.12276357212821519\n        oil: 0.000967767460131986\n        solar: 0.06913120445165255\n        unknown: 0.08111590145953967\n        wind: 0.03000373001690923\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 7.260656228746818e-06\n        biomass: 0.02994934081734535\n        coal: 0.007485895931862549\n        gas: 0.31301619759849775\n        geothermal: 0.0014701175133175173\n        hydro: 0.2967859669524067\n        hydro discharge: 0.03956327784757842\n        nuclear: 0.13267045049175438\n        oil: 0.0010900035966792258\n        solar: 0.07620580040576339\n        unknown: 0.07753936277705191\n        wind: 0.02421630791921114\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.3193\n    - datetime: '2025-01-01'\n      value: 0.5497\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.5047\n    - datetime: '2021-01-01'\n      value: 0.4508\n    - datetime: '2022-01-01'\n      value: 0.4123\n    - datetime: '2023-01-01'\n      value: 0.5325\n    - datetime: '2024-01-01'\n      value: 0.6014\n    - datetime: '2025-01-01'\n      value: 0.5665\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.2248\n    - datetime: '2025-01-01'\n      value: 0.4013\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.3907\n    - datetime: '2021-01-01'\n      value: 0.3393\n    - datetime: '2022-01-01'\n      value: 0.3024\n    - datetime: '2023-01-01'\n      value: 0.3949\n    - datetime: '2024-01-01'\n      value: 0.4555\n    - datetime: '2025-01-01'\n      value: 0.4216\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Rome\nzone_name: North Italy\n"
  },
  {
    "path": "config/zones/IT-SAR.yaml",
    "content": "bounding_box:\n  - - 8.134281342813466\n    - 38.87841613506127\n  - - 9.826298262982647\n    - 41.262600134769855\ncenter_point:\n  - 9.06580682085446\n  - 40.137224984333116\ncentroid:\n  - 8.814976149761522\n  - 40.09569519277562\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 112.5\n  coal:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1000\n  gas:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 750\n  hydro:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 450\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 240\n  oil:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 145\n  solar:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 750\n    - datetime: '2018-01-01'\n      source: dati.terna.it\n      value: 790\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 870\n    - datetime: '2020-01-01'\n      source: dati.terna.it\n      value: 1000\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 1150\n    - datetime: '2023-01-01'\n      source: dati.terna.it\n      value: 1360\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 1750\n  unknown:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1000\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 100\n  wind:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1094\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 1200\ncontributors:\n  - corradio\n  - nessie2013\ncountry: IT\ncountry_name: Italy\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 408.3\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 379.86\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 997.0022828\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1017.96\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 997.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1015.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 427.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 428.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 403.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 397.71\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 528.85\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 495.51\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 507.95\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 450.79\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 431.66\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 388.93\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 921.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 858.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 860.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 905.42\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 441.3\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 412.86\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1082.9825388\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1103.940256\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1057.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1075.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 547.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 548.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 523.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 517.71\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 539.55\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 506.21\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 518.65\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 461.49\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 442.36\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 399.63\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1165.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1102.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1149.42\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02804507773078145\n        coal: 0.2040542847754825\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0145693684495988\n        hydro discharge: 0.008883543343344645\n        nuclear: 0.0\n        oil: 0.005646017506681461\n        solar: 0.06679951373200879\n        unknown: 0.5390881307708343\n        wind: 0.13291433995964522\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.027364741760628763\n        coal: 0.22026949542583707\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.013355913119954273\n        hydro discharge: 0.010005140160698228\n        nuclear: 0.0\n        oil: 8.535331557586524e-05\n        solar: 0.06687416504112446\n        unknown: 0.5003917371667518\n        wind: 0.16165348392043347\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02859307029151363\n        coal: 0.34319462146652513\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.017302462393063347\n        hydro discharge: 0.00916539521745442\n        nuclear: 0.0\n        oil: 0.00018846454256904\n        solar: 0.06351073267687926\n        unknown: 0.40205045104896125\n        wind: 0.13599491699218139\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.025394821205145895\n        coal: 0.33301197596451537\n        gas: 0.026239509553474514\n        geothermal: 0.002715267500796212\n        hydro: 0.039086605843163855\n        hydro discharge: 0.015595294664294955\n        nuclear: 0.0005621832062053968\n        oil: 0.014703168693682754\n        solar: 0.048859309674415034\n        unknown: 0.37390905186912654\n        wind: 0.11992272691094115\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03335285065148714\n        coal: 0.3518198559725169\n        gas: 0.3379098014051071\n        geothermal: 0.001237817127771104\n        hydro: 0.024292710627710632\n        hydro discharge: 0.012150647575869507\n        nuclear: 0.0002910791623641662\n        oil: 0.013383312411186078\n        solar: 0.049010409298969236\n        unknown: 0.0313306835077835\n        wind: 0.14522083789508278\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.038655622648640114\n        coal: 0.35108226713848273\n        gas: 0.3415277004546134\n        geothermal: 0.0003023350742846493\n        hydro: 0.023085972236305548\n        hydro discharge: 0.01599162012682993\n        nuclear: 0.00011184046523765533\n        oil: 0.015011706396779937\n        solar: 0.06238166312775809\n        unknown: 0.021870223635527514\n        wind: 0.1299788368150558\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03644263380016085\n        coal: 0.3147477437516714\n        gas: 0.31903163115308614\n        geothermal: 0.0023361540904249683\n        hydro: 0.04195542892695071\n        hydro discharge: 0.019521155458845203\n        nuclear: 0.0006382217676480012\n        oil: 0.014842866916895738\n        solar: 0.07483121766041322\n        unknown: 0.041003385709108456\n        wind: 0.1346493622602365\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03403343372779\n        coal: 0.3228879634167627\n        gas: 0.32975136859007925\n        geothermal: 0.0006479086815373337\n        hydro: 0.02442877676545537\n        hydro discharge: 0.012404157084511466\n        nuclear: 0.00016475302824030437\n        oil: 0.01547529919363284\n        solar: 0.0921743249904004\n        unknown: 0.05060570949837678\n        wind: 0.11742628379935073\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.1464578622598982e-05\n        biomass: 0.03395346094680498\n        coal: 0.29724017402429387\n        gas: 0.2971156417132299\n        geothermal: 0.0021588481682782313\n        hydro: 0.031845151122363684\n        hydro discharge: 0.01759053621302725\n        nuclear: 0.0007767330397962667\n        oil: 0.018697070324726985\n        solar: 0.10733041325465073\n        unknown: 0.05271328183151537\n        wind: 0.14055705737821067\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.4842666445776376e-06\n        biomass: 0.035895272468553695\n        coal: 0.2576983583397178\n        gas: 0.3458954036612332\n        geothermal: 0.001644681707163867\n        hydro: 0.01684629094717513\n        hydro discharge: 0.021766955287066923\n        nuclear: 0.0012634890491331166\n        oil: 0.005951982280099155\n        solar: 0.12462370056269007\n        unknown: 0.049733902030647925\n        wind: 0.13867825558188832\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.1984\n    - datetime: '2025-01-01'\n      value: 0.4069\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.262\n    - datetime: '2021-01-01'\n      value: 0.2958\n    - datetime: '2022-01-01'\n      value: 0.284\n    - datetime: '2023-01-01'\n      value: 0.3468\n    - datetime: '2024-01-01'\n      value: 0.3413\n    - datetime: '2025-01-01'\n      value: 0.3988\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.1983\n    - datetime: '2025-01-01'\n      value: 0.406\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2619\n    - datetime: '2021-01-01'\n      value: 0.2951\n    - datetime: '2022-01-01'\n      value: 0.2838\n    - datetime: '2023-01-01'\n      value: 0.346\n    - datetime: '2024-01-01'\n      value: 0.3399\n    - datetime: '2025-01-01'\n      value: 0.3982\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Rome\nzone_name: Sardinia\n"
  },
  {
    "path": "config/zones/IT-SIC.yaml",
    "content": "bounding_box:\n  - - 12.429124291242942\n    - 36.69887698046574\n  - - 15.582755827558287\n    - 38.2973965048802\ncenter_point:\n  - 14.20914458761521\n  - 37.48985056394818\ncentroid:\n  - 14.061226326549003\n  - 37.63904729161818\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 100\n  gas:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 2500\n  hydro:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 470\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 580\n  oil:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 866\n  solar:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1400\n    - datetime: '2020-01-01'\n      source: dati.terna.it\n      value: 1500\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 1550\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 1750\n    - datetime: '2023-01-01'\n      source: dati.terna.it\n      value: 2160\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 2700\n  unknown:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 300\n    - datetime: '2020-01-01'\n      source: dati.terna.it\n      value: 200\n  wind:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1800\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 1900\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 2000\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 2100\n    - datetime: '2023-01-01'\n      source: dati.terna.it\n      value: 2300\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 2500\ncontributors:\n  - corradio\n  - nessie2013\ncountry: IT\ncountry_name: Italy\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 263.77\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 186.61\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 997.0022828\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1017.96\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 997.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1015.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 427.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 428.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 403.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 397.71\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 298.15\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 313.08\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 349.78\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 269.88\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 215.88\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 160.4\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 921.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 858.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 860.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 905.42\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 296.77\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 219.61\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1082.9825388\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1103.940256\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1057.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1075.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 547.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 548.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 523.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 517.71\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 308.85\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 323.78\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 360.48\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 280.58\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 226.58\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 171.1\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1165.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1102.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1149.42\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.875\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007772109563749747\n        coal: 0.0\n        gas: 0.4322750233591107\n        geothermal: 0.0\n        hydro: 0.015390667912151297\n        hydro discharge: 0.0006743553948864487\n        nuclear: 0.0\n        oil: 0.13379968990870733\n        solar: 0.08875005717045491\n        unknown: 0.16729602601188256\n        wind: 0.1540420581313577\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008100921345472169\n        coal: 0.0\n        gas: 0.5607552718990462\n        geothermal: 0.0\n        hydro: 0.006989751803014524\n        hydro discharge: 0.0004918990627396742\n        nuclear: 0.0\n        oil: 0.07946648013535654\n        solar: 0.09316032526639388\n        unknown: 0.05727117139134846\n        wind: 0.19376416802542615\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009007234205188596\n        coal: 0.0009492499505280051\n        gas: 0.5177354005835781\n        geothermal: 7.700896634411001e-06\n        hydro: 0.006696007668177953\n        hydro discharge: 0.00052175188119277\n        nuclear: 0.00025478846510443976\n        oil: 0.09260612840385897\n        solar: 0.11080706477345578\n        unknown: 0.06758277994864217\n        wind: 0.19383182118250863\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03340083796453405\n        coal: 0.005908207760408552\n        gas: 0.40821702340977045\n        geothermal: 3.831454162838571e-05\n        hydro: 0.0351798889951299\n        hydro discharge: 0.0004123127142188988\n        nuclear: 0.0005056216772941673\n        oil: 0.03965041227072963\n        solar: 0.11353185329238996\n        unknown: 0.0898684526673473\n        wind: 0.2732869997340576\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.019186954243546765\n        coal: 0.025818915893841596\n        gas: 0.5078676903073841\n        geothermal: 9.523002464438987e-06\n        hydro: 0.019403339191614157\n        hydro discharge: 0.014898667069903664\n        nuclear: 0.0001141383037263549\n        oil: 0.039248929167312374\n        solar: 0.09591393705325535\n        unknown: 0.05360206700316923\n        wind: 0.22393580177130237\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.021782562123716244\n        coal: 0.02230713507464176\n        gas: 0.5420061387289993\n        geothermal: 3.392971235250735e-06\n        hydro: 0.013350804369839157\n        hydro discharge: 0.016623589037360435\n        nuclear: 4.9181851475389425e-05\n        oil: 0.037181666677487624\n        solar: 0.1101819964762154\n        unknown: 0.031128661300914705\n        wind: 0.20538482509846467\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01857515386964422\n        coal: 0.017019044077142238\n        gas: 0.5013093155126639\n        geothermal: 3.123651389947867e-05\n        hydro: 0.013547524145165144\n        hydro discharge: 0.013430870270196616\n        nuclear: 0.00032576407543846253\n        oil: 0.07823547044957428\n        solar: 0.10101737167186367\n        unknown: 0.024980752339632692\n        wind: 0.23152744096916605\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011221690397562547\n        coal: 0.015302255084295086\n        gas: 0.5444021558155809\n        geothermal: 1.1780330227978931e-05\n        hydro: 0.011110974055247289\n        hydro discharge: 0.012342946750145535\n        nuclear: 9.144992628407959e-05\n        oil: 0.10872128413407203\n        solar: 0.09373529170301285\n        unknown: 0.0198833748472761\n        wind: 0.18317668916318577\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.308652446942864e-09\n        biomass: 0.013979971592747322\n        coal: 0.01188397431716037\n        gas: 0.5218494653768685\n        geothermal: 5.617817148079591e-05\n        hydro: 0.011547670029398644\n        hydro discharge: 0.012987514804103952\n        nuclear: 0.000391374306067989\n        oil: 0.05998076562374397\n        solar: 0.14510736504214292\n        unknown: 0.0199381043122152\n        wind: 0.20227746347584563\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.3708358400280429e-08\n        biomass: 0.024558933040127996\n        coal: 0.002076221697596873\n        gas: 0.4761795062398611\n        geothermal: 0.000257469245110867\n        hydro: 0.01103500346667534\n        hydro discharge: 0.01135414318913947\n        nuclear: 0.0007799301970047549\n        oil: 0.024284594517642383\n        solar: 0.17395687933166742\n        unknown: 0.02172961125882372\n        wind: 0.25378750961633484\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.34\n    - datetime: '2025-01-01'\n      value: 0.5794\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.3866\n    - datetime: '2021-01-01'\n      value: 0.3913\n    - datetime: '2022-01-01'\n      value: 0.3201\n    - datetime: '2023-01-01'\n      value: 0.4114\n    - datetime: '2024-01-01'\n      value: 0.5046\n    - datetime: '2025-01-01'\n      value: 0.642\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.3399\n    - datetime: '2025-01-01'\n      value: 0.5792\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.3866\n    - datetime: '2021-01-01'\n      value: 0.3912\n    - datetime: '2022-01-01'\n      value: 0.32\n    - datetime: '2023-01-01'\n      value: 0.4112\n    - datetime: '2024-01-01'\n      value: 0.5038\n    - datetime: '2025-01-01'\n      value: 0.6419\nparsers:\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Rome\nzone_name: Sicily\n"
  },
  {
    "path": "config/zones/IT-SO.yaml",
    "content": "bounding_box:\n  - - 13.944739447394483\n    - 37.949643376471315\n  - - 18.516785167851708\n    - 42.0783173495561\ncenter_point:\n  - 16.250831022744418\n  - 40.32108235881455\ncentroid:\n  - 16.202396506723712\n  - 40.22962974163535\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 665\n  coal:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1815\n  gas:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 8551.7\n  hydro:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1100\n  oil:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 100\n  solar:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 3700\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 3900\n    - datetime: '2020-01-01'\n      source: dati.terna.it\n      value: 4000\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 4100\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 4250\n    - datetime: '2023-01-01'\n      source: dati.terna.it\n      value: 4750\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 5300\n  unknown:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 1000\n  wind:\n    - datetime: '2017-01-01'\n      source: dati.terna.it\n      value: 5000\n    - datetime: '2018-01-01'\n      source: dati.terna.it\n      value: 5300\n    - datetime: '2019-01-01'\n      source: dati.terna.it\n      value: 5400\n    - datetime: '2021-01-01'\n      source: dati.terna.it\n      value: 5700\n    - datetime: '2022-01-01'\n      source: dati.terna.it\n      value: 6000\n    - datetime: '2023-01-01'\n      source: dati.terna.it\n      value: 6200\n    - datetime: '2024-01-01'\n      source: dati.terna.it\n      value: 6400\ncontributors:\n  - corradio\n  - nessie2013\ncountry: IT\ncountry_name: Italy\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 997.0022828\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1017.96\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 997.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1015.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 427.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 428.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 403.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 397.71\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 921.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 858.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 860.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 905.42\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1082.9825388\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1103.940256\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1057.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1075.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 547.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 548.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 523.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 517.71\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1165.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1102.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1149.42\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.7\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02958098998528575\n        coal: 0.005279385908844516\n        gas: 0.32903383176144946\n        geothermal: 7.065416746168095e-06\n        hydro: 0.07115105562090583\n        hydro discharge: 0.00029943695919272317\n        nuclear: 0.00031424262229911676\n        oil: 5.564783832614944e-06\n        solar: 0.1582889294941509\n        unknown: 0.14543257792119857\n        wind: 0.2606069066288449\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.030671948726285495\n        coal: 3.2400457877874906e-05\n        gas: 0.30162969891789454\n        geothermal: 3.597659907156839e-08\n        hydro: 0.05196297503610688\n        hydro discharge: 6.03633535637259e-06\n        nuclear: 2.1599408638855636e-06\n        oil: 1.570193623030134e-07\n        solar: 0.1425981008726679\n        unknown: 0.19012307527296404\n        wind: 0.2829734084179526\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07067975570923263\n        coal: 0.006507646961529354\n        gas: 0.007650418309654597\n        geothermal: 2.221429585472476e-05\n        hydro: 0.06852365562010186\n        hydro discharge: 0.0003631880964247147\n        nuclear: 0.0003481146160006474\n        oil: 7.385509479986996e-06\n        solar: 0.22482612471385377\n        unknown: 0.16870588075007176\n        wind: 0.4523656077881375\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06258465618366812\n        coal: 0.012040752166729935\n        gas: 0.019174386338239775\n        geothermal: 0.00016430255623339193\n        hydro: 0.07381981789309909\n        hydro discharge: 0.0008403971491661901\n        nuclear: 0.0009678078200103724\n        oil: 0.0005282757588233093\n        solar: 0.26513018558222345\n        unknown: 0.10565536028401404\n        wind: 0.45909387113504035\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05833603121826182\n        coal: 0.10836320269117004\n        gas: 0.33960436159388635\n        geothermal: 2.1253490405458363e-05\n        hydro: 0.047165161727281434\n        hydro discharge: 0.00011303492779268793\n        nuclear: 4.776322037355697e-05\n        oil: 0.00028306746784756496\n        solar: 0.11443423325499888\n        unknown: 0.05910332677412706\n        wind: 0.27252863134708627\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06533788338290934\n        coal: 0.09435442739631857\n        gas: 0.3630800299055463\n        geothermal: 1.162387639738783e-05\n        hydro: 0.035040701378696866\n        hydro discharge: 0.000176339199383976\n        nuclear: 0.00017647732787953567\n        oil: 0.00066829983014557\n        solar: 0.13447587360457502\n        unknown: 0.04813083792816562\n        wind: 0.25854725099576104\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0524225116916516\n        coal: 0.07895765798098216\n        gas: 0.4767074331664056\n        geothermal: 9.902005608444526e-05\n        hydro: 0.03735009940629733\n        hydro discharge: 0.0005418875849499716\n        nuclear: 0.0005647349553494041\n        oil: 0.0006251604564373478\n        solar: 0.10367891784445603\n        unknown: 0.032673585497731895\n        wind: 0.21637898692434812\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04404866190920421\n        coal: 0.13961383341334593\n        gas: 0.4489940025562509\n        geothermal: 7.073447297527593e-05\n        hydro: 0.02746200650422654\n        hydro discharge: 0.0005237463105703603\n        nuclear: 0.0004964926401001979\n        oil: 0.0029730516304754245\n        solar: 0.1037536061754192\n        unknown: 0.031496518604128325\n        wind: 0.20056729643376117\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 8.611777916073363e-09\n        biomass: 0.05026220260648846\n        coal: 0.06945851947120443\n        gas: 0.43144678154744476\n        geothermal: 0.00014521219066527977\n        hydro: 0.03841321509576245\n        hydro discharge: 0.0007039783975273331\n        nuclear: 0.0011893867399891183\n        oil: 0.0023497251701784204\n        solar: 0.12317687947130605\n        unknown: 0.030574679715550942\n        wind: 0.25227930333488086\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 5.74723002344627e-08\n        biomass: 0.07130172841988824\n        coal: 0.006321393245586613\n        gas: 0.46570024500801754\n        geothermal: 0.0005432814394810253\n        hydro: 0.03200258830105704\n        hydro discharge: 0.0009096577747590193\n        nuclear: 0.002107505418111065\n        oil: 0.0005714359699198839\n        solar: 0.1405525919061412\n        unknown: 0.02761569697226704\n        wind: 0.25237370044583\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Rome\nzone_name: South Italy\n"
  },
  {
    "path": "config/zones/IT.yaml",
    "content": "bounding_box:\n  - - 6.604266042660441\n    - 36.69887698046574\n  - - 18.516785167851708\n    - 47.09019132836457\ncenter_point:\n  - 12.463097958480168\n  - 42.17713495481865\ncentroid:\n  - 12.258237064167265\n  - 42.27277579786555\ncapacity:\n  biomass: 4106.2\n  coal: 5598\n  gas: 51765.5\n  geothermal: 817.1\n  hydro: 17127.9\n  hydro storage: 7293.5\n  nuclear: 0\n  oil: 1269\n  solar: 22594.2\n  wind: 11289.8\ncontributors:\n  - corradio\ncountry: IT\ncountry_name: Italy\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 324.62\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 199.31\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 997.0022828\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1017.96\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 997.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1015.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 427.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 428.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 403.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 397.71\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 264.71\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 280.66\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 318.78\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 238.0\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 190.11\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 188.4\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 921.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 858.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 860.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 905.42\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 357.62\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 232.31\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1082.9825388\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1103.940256\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1057.84\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1075.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 547.8711931\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 548.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 523.76\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 517.71\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 275.41\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 291.36\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 329.48\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 248.7\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 200.81\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 199.1\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1165.1256533\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1102.74\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.73\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1149.42\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.26527778\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.014710931720166782\n        coal: 0.05414227020043607\n        gas: 0.1914133490560423\n        geothermal: 0.022607808223498362\n        hydro: 0.19861582318278065\n        hydro discharge: 0.016768377597225735\n        nuclear: 0.06640317298088395\n        oil: 0.009002665426120538\n        solar: 0.07538447567267975\n        unknown: 0.2904190775326813\n        wind: 0.060532050606625885\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01400302415173277\n        coal: 0.047978590896075334\n        gas: 0.22873105262684693\n        geothermal: 0.023707112226931563\n        hydro: 0.17872354602606272\n        hydro discharge: 0.01769393018998405\n        nuclear: 0.028941261102440184\n        oil: 0.004758626744437331\n        solar: 0.07436397416026594\n        unknown: 0.3110849806785099\n        wind: 0.07001389945210554\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.020808922392875982\n        coal: 0.08102998706395417\n        gas: 0.21190131304701584\n        geothermal: 0.022480173183851468\n        hydro: 0.15708671695420032\n        hydro discharge: 0.017460820839240273\n        nuclear: 0.061186575680083746\n        oil: 0.005193798264506573\n        solar: 0.07770866467960762\n        unknown: 0.27571982038913545\n        wind: 0.06942320828333481\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02440032223239749\n        coal: 0.09031115842471878\n        gas: 0.20730395794783557\n        geothermal: 0.020822624455919012\n        hydro: 0.19597485740556006\n        hydro discharge: 0.018954864560445095\n        nuclear: 0.07071071456404968\n        oil: 0.003796117315274562\n        solar: 0.07150161152003857\n        unknown: 0.22253003286655723\n        wind: 0.07369373366796554\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02596971790969793\n        coal: 0.06605392599172437\n        gas: 0.37614705097646217\n        geothermal: 0.019943719848352994\n        hydro: 0.17778592130766396\n        hydro discharge: 0.018594243114659365\n        nuclear: 0.06986318849160054\n        oil: 0.0035935057811856694\n        solar: 0.0698998770968593\n        unknown: 0.09738282995299453\n        wind: 0.07476601938651514\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.028564442915053997\n        coal: 0.05415985216801784\n        gas: 0.39181832289831664\n        geothermal: 0.021184945226707778\n        hydro: 0.1928730581484842\n        hydro discharge: 0.019588739806283416\n        nuclear: 0.061526958994401484\n        oil: 0.003502369177079338\n        solar: 0.07803288322836929\n        unknown: 0.07305909428679179\n        wind: 0.07568932801584387\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.028166784646270496\n        coal: 0.05788477894440352\n        gas: 0.4157235849038742\n        geothermal: 0.018657125118740975\n        hydro: 0.17496946352412068\n        hydro discharge: 0.020575964605030545\n        nuclear: 0.05985750968065508\n        oil: 0.005792363609234955\n        solar: 0.07432339648039434\n        unknown: 0.0640809814170447\n        wind: 0.07996804717322474\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.026792518617006742\n        coal: 0.08721320187143101\n        gas: 0.4323871547541466\n        geothermal: 0.01855383882306169\n        hydro: 0.12187986364143175\n        hydro discharge: 0.016601422578309877\n        nuclear: 0.05726149256279825\n        oil: 0.008718884759139409\n        solar: 0.08433160370593729\n        unknown: 0.06483222065249397\n        wind: 0.08142780094931112\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.200224962425098e-06\n        biomass: 0.030177439760791347\n        coal: 0.05749548282061043\n        gas: 0.3683176197580231\n        geothermal: 0.018982605407284248\n        hydro: 0.17184626303154424\n        hydro discharge: 0.02086682957553744\n        nuclear: 0.07225886679865946\n        oil: 0.005865239007974201\n        solar: 0.09465365857000872\n        unknown: 0.06231214857382586\n        wind: 0.09722164379937595\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 6.589081809533726e-06\n        biomass: 0.035037872101125536\n        coal: 0.022343130033850737\n        gas: 0.3530313028900843\n        geothermal: 0.01858756194174721\n        hydro: 0.2021758047656538\n        hydro discharge: 0.0279481524382195\n        nuclear: 0.08070447769619804\n        oil: 0.0029975456908372853\n        solar: 0.10768555146389387\n        unknown: 0.05930511903984094\n        wind: 0.09017689210992368\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.2935\n    - datetime: '2025-01-01'\n      value: 0.5567\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4883\n    - datetime: '2021-01-01'\n      value: 0.4571\n    - datetime: '2022-01-01'\n      value: 0.4167\n    - datetime: '2023-01-01'\n      value: 0.5318\n    - datetime: '2024-01-01'\n      value: 0.5933\n    - datetime: '2025-01-01'\n      value: 0.5825\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.2383\n    - datetime: '2025-01-01'\n      value: 0.4691\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4217\n    - datetime: '2021-01-01'\n      value: 0.3924\n    - datetime: '2022-01-01'\n      value: 0.3547\n    - datetime: '2023-01-01'\n      value: 0.4547\n    - datetime: '2024-01-01'\n      value: 0.5108\n    - datetime: '2025-01-01'\n      value: 0.4996\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\nsubZoneNames:\n  - IT-CNO\n  - IT-CSO\n  - IT-NO\n  - IT-SAR\n  - IT-SIC\n  - IT-SO\ntimezone: Europe/Rome\nzone_name: Italy\n"
  },
  {
    "path": "config/zones/JE.yaml",
    "content": "bounding_box:\n  - - -2.249824737558097\n    - 49.16938637874313\n  - - -2.031153763237305\n    - 49.258163422771815\ncenter_point:\n  - -2.1404892503977013\n  - 49.21377490075747\ncentroid:\n  - -2.1492769624498447\n  - 49.204571809876356\ncountry: JE\ncountry_name: Jersey\ncurrency: GBP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Europe/Jersey\nzone_name: Jersey\n"
  },
  {
    "path": "config/zones/JM.yaml",
    "content": "bounding_box:\n  - - -78.37458374583741\n    - 17.71699428410645\n  - - -76.18936189361888\n    - 18.51840067056311\ncenter_point:\n  - -77.28197281972814\n  - 18.11769747733478\ncentroid:\n  - -77.17757177571771\n  - 18.077358829980767\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 460.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 890.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\ncountry: JM\ncountry_name: Jamaica\ncurrency: JMD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Jamaica\nzone_name: Jamaica\n"
  },
  {
    "path": "config/zones/JO.yaml",
    "content": "bounding_box:\n  - - 34.9509495094951\n    - 29.189985355933374\n  - - 39.29992274590594\n    - 33.37779736975472\ncenter_point:\n  - 36.650141036611664\n  - 31.27194964593257\ncentroid:\n  - 36.8660244675459\n  - 31.46873567339284\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3310.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 4000.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 420.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 760.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 970.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1540.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1810.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1970.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 520.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 290.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 530.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 630.0\ncountry: JO\ncountry_name: Jordan\ncurrency: JOD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Amman\nzone_name: Jordan\n"
  },
  {
    "path": "config/zones/JP-CB.yaml",
    "content": "bounding_box:\n  - - 136.0039600396004\n    - 33.965508769515324\n  - - 138.71478714787148\n    - 37.00083545821994\ncenter_point:\n  - 137.4501477804337\n  - 35.64393800741493\ncentroid:\n  - 137.4042381933253\n  - 35.41724779808144\ncapacity:\n  biomass: 352.6\n  coal: 5170\n  gas: 14136\n  geothermal: 2\n  hydro: 2180\n  hydro storage: 3320\n  nuclear: 3617\n  oil: 2275\n  solar: 550\n  wind: 210\ncontributors:\n  - tmslaine\n  - lorrieq\n  - pierresegonne\n  - wobniarin\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\ndisclaimer: The data provided for solar power production is suspected to be too high\n  (source; Chubu Electric Power Co.,Inc.).\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    unknown:\n      _comment: 'Source: Derived from 2016-2019 Chubu area supply statistics and 2017-2018\n        Chubu Electric report'\n      _url:\n        - https://www.chuden.co.jp/corporate/publicity/datalist/juyo/dat_kousei/index.html\n        - http://denki-yoho.chuden.jp/denki_yoho_content_data/areabalance_current_term.csv\n      source: Chubu Electric Power 2022; assumes 26.3% coal, 2.2% oil, 62.5% gas,\n        9% hydro and wind\n      value: 440.062\n  lifecycle:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3535840908594851\n        gas: 0.43040995130148274\n        geothermal: 0.0\n        hydro: 0.07960270350025679\n        hydro discharge: 0.008679206219920943\n        nuclear: 0.0\n        oil: 0.06201605302189856\n        solar: 0.06205672511328497\n        unknown: 0.0\n        wind: 0.0036512111985253426\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000113086867845418\n        coal: 0.3482425357553068\n        gas: 0.42518861978756856\n        geothermal: 5.436936674116638e-06\n        hydro: 0.08971829660905434\n        hydro discharge: 0.006572182734637999\n        nuclear: 0.004829523637642128\n        oil: 0.047107282014527956\n        solar: 0.0729384470640303\n        unknown: 0.001478720521554769\n        wind: 0.003805833571995511\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0003252316287002105\n        coal: 0.35899573487768793\n        gas: 0.42402899856096893\n        geothermal: 9.604863350472414e-06\n        hydro: 0.07695153228995846\n        hydro discharge: 0.0055452649794120795\n        nuclear: 0.009447233245100503\n        oil: 0.038438984748773386\n        solar: 0.08016590775340902\n        unknown: 0.002329564211292626\n        wind: 0.0037619476850236514\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0007657565336649217\n        coal: 0.3381297205967208\n        gas: 0.42849480960850767\n        geothermal: 1.64379041292476e-05\n        hydro: 0.0865099242584361\n        hydro discharge: 0.0007845196260121192\n        nuclear: 0.003845880666017513\n        oil: 0.034334809491059375\n        solar: 0.09915951225800093\n        unknown: 0.003926023627817406\n        wind: 0.004032587458500368\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005259145894703494\n        coal: 0.34995731287255183\n        gas: 0.3946147020091073\n        geothermal: 4.654762157276966e-05\n        hydro: 0.09276918719480699\n        hydro discharge: 0.00025436325872475014\n        nuclear: 0.011157294813610294\n        oil: 0.03477985061178295\n        solar: 0.10349454831097993\n        unknown: 0.0034926377579043706\n        wind: 0.004174398384340804\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.013795215069672092\n        coal: 0.34414368171352605\n        gas: 0.3862690313786805\n        geothermal: 4.2837894136067565e-05\n        hydro: 0.08515718528276257\n        hydro discharge: 0.0001464690954914915\n        nuclear: 0.014782164937846603\n        oil: 0.03546415715631693\n        solar: 0.10943261943015081\n        unknown: 0.006795886338625879\n        wind: 0.003970745554062101\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.014581230553426937\n        coal: 0.3220827644527748\n        gas: 0.36184809337328083\n        geothermal: 4.527393238111154e-05\n        hydro: 0.09832256919090823\n        hydro discharge: 0.000392863786619903\n        nuclear: 0.030265660222784648\n        oil: 0.033375392961161356\n        solar: 0.12784675785742433\n        unknown: 0.007300935721930196\n        wind: 0.003938455005355565\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0145982517550128\n        coal: 0.32424405411028556\n        gas: 0.36426889211505287\n        geothermal: 3.60577970334292e-05\n        hydro: 0.09890660573881178\n        hydro discharge: 4.691653761935748e-05\n        nuclear: 0.034020188696820004\n        oil: 0.033614977239555956\n        solar: 0.12244614660850632\n        unknown: 0.003769750267899515\n        wind: 0.004048155359128435\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP.fetch_production\nregion: Asia\nsources:\n  Chubu Electric Power 2022:\n    link: https://www.chuden.co.jp/corporate/publicity/datalist/juyo/dat_kousei/index.html\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Tokyo\nzone_name: \"Ch\\u016Bbu\"\n"
  },
  {
    "path": "config/zones/JP-CG.yaml",
    "content": "bounding_box:\n  - - 130.8631086310863\n    - 33.82955590038428\n  - - 134.5063450634506\n    - 35.6012364475867\ncenter_point:\n  - 133.16002378532153\n  - 34.92074130104224\ncentroid:\n  - 132.66264662646626\n  - 34.644271357187456\ncapacity:\n  biomass: 500\n  coal: 3850\n  gas: 4000\n  geothermal: 0\n  hydro: 780\n  hydro storage: 2123\n  nuclear: 0\n  oil: 850\n  solar: 5690\n  wind: 365\ncontributors:\n  - tmslaine\n  - lorrieq\n  - PPsyrius\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.019846083696057816\n        coal: 0.3400898153425273\n        gas: 0.41496371487617345\n        geothermal: 0.0\n        hydro: 0.0685592223368076\n        hydro discharge: 0.016144595275394486\n        nuclear: 0.0\n        oil: 0.05953826324127661\n        solar: 0.07351978686444242\n        unknown: 0.0\n        wind: 0.007338398597607983\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.021539228353715696\n        coal: 0.3240976459064113\n        gas: 0.3951843932422086\n        geothermal: 0.0010801208283157564\n        hydro: 0.061676833757194294\n        hydro discharge: 0.01627682238994312\n        nuclear: 0.03324791965029956\n        oil: 0.04339747499537545\n        solar: 0.09549575029739463\n        unknown: 0.0005409715027133534\n        wind: 0.007462787024588558\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.031496516651811406\n        coal: 0.3145211494318617\n        gas: 0.3713009351753732\n        geothermal: 0.0025367109544944884\n        hydro: 0.05273487655430929\n        hydro discharge: 0.01726002617880443\n        nuclear: 0.06471504783764744\n        oil: 0.0335619237605758\n        solar: 0.10447637694372454\n        unknown: 0.0002448527879231127\n        wind: 0.00715158163247678\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03525462623620311\n        coal: 0.3046790611136666\n        gas: 0.3867438814014564\n        geothermal: 0.0025772171154329693\n        hydro: 0.05778048290240372\n        hydro discharge: 0.003635245705072587\n        nuclear: 0.05599072286182782\n        oil: 0.030944849524371133\n        solar: 0.11357431856346348\n        unknown: 0.0019861389073626387\n        wind: 0.006833443286245042\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03351790236284878\n        coal: 0.3152226285320562\n        gas: 0.35470023900862513\n        geothermal: 0.002666930063982584\n        hydro: 0.05650084728112431\n        hydro discharge: 0.00016346879591539357\n        nuclear: 0.07221614762654253\n        oil: 0.03152598343662413\n        solar: 0.12133539248547243\n        unknown: 0.00500909884147848\n        wind: 0.00714138010769232\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.030686690502486003\n        coal: 0.33683624542693696\n        gas: 0.378546203669779\n        geothermal: 0.0026276500052324495\n        hydro: 0.04194419421713922\n        hydro discharge: 0.00012792970618443302\n        nuclear: 0.044505282739643146\n        oil: 0.033476077473062096\n        solar: 0.12309652379486548\n        unknown: 0.00204546997811088\n        wind: 0.006107750756893954\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.033476892401631445\n        coal: 0.311872191821422\n        gas: 0.35051848584041295\n        geothermal: 0.00250961888000074\n        hydro: 0.06430478292062557\n        hydro discharge: 0.0005672214990833505\n        nuclear: 0.06462802126567921\n        oil: 0.03062108529980735\n        solar: 0.12992503125522772\n        unknown: 0.005523071190294526\n        wind: 0.0060535893910726845\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03325772171751817\n        coal: 0.31681198978666464\n        gas: 0.3560138230320509\n        geothermal: 0.0021967163386733424\n        hydro: 0.06549470462449189\n        hydro discharge: 7.386342493198292e-06\n        nuclear: 0.057900393603804744\n        oil: 0.031176971738347495\n        solar: 0.12844791109956524\n        unknown: 0.0022459561300016023\n        wind: 0.00644645444675968\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Tokyo\nzone_name: \"Ch\\u016Bgoku\"\n"
  },
  {
    "path": "config/zones/JP-HKD.yaml",
    "content": "bounding_box:\n  - - 139.78759787597872\n    - 41.4014151695668\n  - - 145.76725767257673\n    - 45.51005398299017\ncenter_point:\n  - 143.1943641388339\n  - 43.55878642798375\ncentroid:\n  - 142.40019543052568\n  - 43.18056914934132\ncapacity:\n  biomass: 300\n  coal: 2250\n  gas: 569\n  geothermal: 25\n  hydro: 1231\n  hydro storage: 800\n  nuclear: 2070\n  oil: 1815\n  solar: 1880\n  unknown: 0\n  wind: 577\ncontributors:\n  - tmslaine\n  - lorrieq\n  - pierresegonne\n  - wobniarin\n  - PPsyrius\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006345350472304661\n        coal: 0.3308710369175724\n        gas: 0.3906997971864568\n        geothermal: 0.0036258815029913557\n        hydro: 0.13960032335075193\n        hydro discharge: 0.007361145260587571\n        nuclear: 0.0\n        oil: 0.0353532105789568\n        solar: 0.04692673511387122\n        unknown: 0.0\n        wind: 0.039215611205948187\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006733795142491021\n        coal: 0.3297501751985624\n        gas: 0.38933635428389674\n        geothermal: 0.003663388599511089\n        hydro: 0.13886973514117554\n        hydro discharge: 0.0075255067940767015\n        nuclear: 0.0\n        oil: 0.035246678702467726\n        solar: 0.04851307419846041\n        unknown: 0.00022403208115738494\n        wind: 0.04013665906515336\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00797915741812891\n        coal: 0.32132755777276756\n        gas: 0.37925381761117133\n        geothermal: 0.0037419942546904053\n        hydro: 0.13443172107217652\n        hydro discharge: 0.009072265241639114\n        nuclear: 0.0\n        oil: 0.03439195551225215\n        solar: 0.06731515667926989\n        unknown: 0.0009929086822564688\n        wind: 0.04149344073342068\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0081473068757297\n        coal: 0.3195726253335716\n        gas: 0.4049750954714027\n        geothermal: 0.0037884438895967724\n        hydro: 0.1115799209552793\n        hydro discharge: 0.00171764219518717\n        nuclear: 0.0\n        oil: 0.03256885864420797\n        solar: 0.07988557411775227\n        unknown: 0.0008057930380726623\n        wind: 0.03695867888431371\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022195415548369197\n        coal: 0.32229781082918185\n        gas: 0.36206638184091805\n        geothermal: 0.0027881673360511568\n        hydro: 0.13950268250860579\n        hydro discharge: 0.00013918423236551237\n        nuclear: 0.0\n        oil: 0.03174291570575126\n        solar: 0.08310919043838458\n        unknown: 0.0003763087076404456\n        wind: 0.03578189405713623\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.036136610169869916\n        coal: 0.3085774776788767\n        gas: 0.3472428770947127\n        geothermal: 0.0027703923277293692\n        hydro: 0.1542907772933684\n        hydro discharge: 6.589606268238127e-05\n        nuclear: 8.895790546310542e-09\n        oil: 0.031076026218628053\n        solar: 0.08370221376202229\n        unknown: 0.000356356802968378\n        wind: 0.03578135776282418\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06339761084290749\n        coal: 0.30950472895135006\n        gas: 0.34748152322057907\n        geothermal: 0.0027895379663972603\n        hydro: 0.1125371690681065\n        hydro discharge: 0.00024976819690521976\n        nuclear: 0.0\n        oil: 0.03068546393795506\n        solar: 0.0978914549374653\n        unknown: 0.0005317692015275681\n        wind: 0.03493101922994646\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0633465681284829\n        coal: 0.3083916475015915\n        gas: 0.3462714519820547\n        geothermal: 0.002735424889703481\n        hydro: 0.11217157105672093\n        hydro discharge: 0.0\n        nuclear: 3.350463430875036e-10\n        oil: 0.030495207514530893\n        solar: 0.10087912421308973\n        unknown: 0.000405576948770854\n        wind: 0.03530341402815505\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Tokyo\nzone_name: \"Hokkaid\\u014D\"\n"
  },
  {
    "path": "config/zones/JP-HR.yaml",
    "content": "bounding_box:\n  - - 135.95715957159572\n    - 35.50106064927961\n  - - 137.73197731977316\n    - 37.53176718924749\ncenter_point:\n  - 136.84456844568444\n  - 36.51641391926355\ncentroid:\n  - 136.80818236753797\n  - 36.46346385444409\ncapacity:\n  biomass: 700\n  coal: 2900\n  gas: 1194.7\n  geothermal: 0\n  hydro: 1934\n  nuclear: 1746\n  oil: 1750\n  wind: 229.6\ncontributors:\n  - tmslaine\n  - lorrieq\n  - pierresegonne\n  - wobniarin\n  - PPsyrius\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\ndisclaimer: The data provider (Hokuriku Electric Power Co.,Inc.) provides live data\n  only for solar and unknown. We are working on improving the data quality for this\n  zone.\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.013928344030046733\n        coal: 0.2967535383135357\n        gas: 0.34763112491613124\n        geothermal: 0.0\n        hydro: 0.2605782153189564\n        hydro discharge: 0.0010476608864733495\n        nuclear: 0.0\n        oil: 0.032596344603924486\n        solar: 0.025237356469775898\n        unknown: 0.015669407187297504\n        wind: 0.006557168732252854\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.013125259727419347\n        coal: 0.2951680565202728\n        gas: 0.34627698867327217\n        geothermal: 6.989762134845823e-06\n        hydro: 0.2495307950245046\n        hydro discharge: 0.001084868304139311\n        nuclear: 0.006917420626922094\n        oil: 0.03268029258578576\n        solar: 0.032071727524726555\n        unknown: 0.016488210494261617\n        wind: 0.006648814007114302\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012680329235446467\n        coal: 0.2934686048431531\n        gas: 0.3439350029091012\n        geothermal: 6.79623799029764e-06\n        hydro: 0.2424087411667387\n        hydro discharge: 0.0010339725385863441\n        nuclear: 0.008917736998400587\n        oil: 0.03219183297972971\n        solar: 0.04266819192898654\n        unknown: 0.016408653436378474\n        wind: 0.006280143738293644\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.017151294776767686\n        coal: 0.2824572077569805\n        gas: 0.35805863548654254\n        geothermal: 2.8984473004847444e-06\n        hydro: 0.24675722135641612\n        hydro discharge: 0.000244086380293364\n        nuclear: 0.00046327258737959763\n        oil: 0.028676530378042443\n        solar: 0.043748103245817814\n        unknown: 0.016814650152754074\n        wind: 0.005626069068968885\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.015991858383019312\n        coal: 0.3039989905728657\n        gas: 0.34775287394631765\n        geothermal: 8.511357772454951e-07\n        hydro: 0.24015331268269358\n        hydro discharge: 1.9386066761936996e-05\n        nuclear: 0.0005181715297993731\n        oil: 0.03170347387897594\n        solar: 0.03742428883532812\n        unknown: 0.01706931428529475\n        wind: 0.00536748417215164\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.021156034412579863\n        coal: 0.30501265369494224\n        gas: 0.33632505765580967\n        geothermal: 3.566391513806196e-06\n        hydro: 0.22247845388725035\n        hydro discharge: 2.998471303743143e-05\n        nuclear: 0.002632732940489325\n        oil: 0.04244315896328942\n        solar: 0.04429607337496356\n        unknown: 0.020138554037338424\n        wind: 0.005483735729460718\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.020574382443580876\n        coal: 0.2981041185281297\n        gas: 0.32871436927087055\n        geothermal: 7.921986583234417e-06\n        hydro: 0.21641925135180048\n        hydro discharge: 5.5286122996899204e-05\n        nuclear: 0.008815784107593923\n        oil: 0.04147172214201565\n        solar: 0.05969048291522835\n        unknown: 0.02047979428559259\n        wind: 0.005666854920707754\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Tokyo\nzone_name: Hokuriku\n"
  },
  {
    "path": "config/zones/JP-KN.yaml",
    "content": "bounding_box:\n  - - 134.2651426514265\n    - 33.48180277197541\n  - - 136.40716407164072\n    - 35.7729663875417\ncenter_point:\n  - 135.63920071797355\n  - 34.97051644238057\ncentroid:\n  - 135.38747582597782\n  - 34.75340713020724\ncapacity:\n  biomass: 0\n  coal: 2301\n  gas: 17222\n  hydro: 3540\n  hydro storage: 5234\n  nuclear: 9768\n  oil: 7800\n  solar: 4962\n  wind: 146\ncontributors:\n  - tmslaine\n  - lorrieq\n  - kongkille\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 373.6\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 397.6\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.31192032723201996\n        gas: 0.3350255756256627\n        geothermal: 0.0\n        hydro: 0.09648190661158312\n        hydro discharge: 0.0\n        nuclear: 0.14776105708282114\n        oil: 0.04726063367657557\n        solar: 0.06155047521951693\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0027521208078778647\n        coal: 0.284455017501413\n        gas: 0.360570575457919\n        geothermal: 0.00016776732573316354\n        hydro: 0.10455972258725736\n        hydro discharge: 0.005197919934895577\n        nuclear: 0.07544055963717698\n        oil: 0.02893329651888521\n        solar: 0.0702523234798161\n        unknown: 0.06522684367235923\n        wind: 0.002443841276828605\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0031201988028509613\n        coal: 0.25394612750466367\n        gas: 0.28995368221891454\n        geothermal: 0.00021734024623361973\n        hydro: 0.1004965102641899\n        hydro discharge: 0.003481936945760932\n        nuclear: 0.20083797757824493\n        oil: 0.02635424046311294\n        solar: 0.07037617737853652\n        unknown: 0.04856063571256913\n        wind: 0.002655204867269165\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.32492840389618566\n        gas: 0.3805927345266719\n        geothermal: 0.0\n        hydro: 0.12100174025377304\n        hydro discharge: 0.011678966157177539\n        nuclear: 0.07151227797321238\n        oil: 0.035702526051316186\n        solar: 0.035127315522017415\n        unknown: 0.017147746136503748\n        wind: 0.002308088262955658\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0007914361091397227\n        coal: 0.26997972127558006\n        gas: 0.3166287581321575\n        geothermal: 8.33789898776479e-05\n        hydro: 0.10164840680673617\n        hydro discharge: 0.01670505096901968\n        nuclear: 0.17925256330503067\n        oil: 0.029854866822174995\n        solar: 0.04961613646328255\n        unknown: 0.032867984337861055\n        wind: 0.002571584969487111\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0024836277992503937\n        coal: 0.25100351312995756\n        gas: 0.2941978181288641\n        geothermal: 0.0001691741641561132\n        hydro: 0.09537788467913003\n        hydro discharge: 0.015588478646749492\n        nuclear: 0.20370654460743567\n        oil: 0.027513983657470657\n        solar: 0.05915105533315268\n        unknown: 0.047974032934233524\n        wind: 0.002833885635868913\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007485307784368473\n        coal: 0.25928972453990934\n        gas: 0.286739454089373\n        geothermal: 0.0003161186370417949\n        hydro: 0.08695329717299086\n        hydro discharge: 0.0009730893783009032\n        nuclear: 0.170710117768223\n        oil: 0.03446388643385175\n        solar: 0.0812736314467582\n        unknown: 0.06914131470727426\n        wind: 0.002654052030018681\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00648742967444149\n        coal: 0.22764243230168252\n        gas: 0.25162315514834505\n        geothermal: 0.00024844089121178785\n        hydro: 0.07914649561219841\n        hydro discharge: 0.0011686416947921862\n        nuclear: 0.2612839421412385\n        oil: 0.030446235709555704\n        solar: 0.0812794325628458\n        unknown: 0.058239450303551786\n        wind: 0.0024343421168209712\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006082162692915101\n        coal: 0.2308288455754829\n        gas: 0.2550304821563375\n        geothermal: 0.00019000633442015563\n        hydro: 0.08107783911461883\n        hydro discharge: 0.0003459494756093433\n        nuclear: 0.2882485609098048\n        oil: 0.03108945642837576\n        solar: 0.07460594186010626\n        unknown: 0.030073678811974553\n        wind: 0.002427072768801394\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.3069\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2433\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP_KN.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Tokyo\nzone_name: Kansai\n"
  },
  {
    "path": "config/zones/JP-KY.yaml",
    "content": "bounding_box:\n  - - 128.64188641886417\n    - 28.12382864537942\n  - - 132.0259202592026\n    - 34.64813528083644\ncenter_point:\n  - 131.09043016414662\n  - 32.70705256390908\ncentroid:\n  - 130.34556254653455\n  - 32.33259447019511\ncapacity:\n  geothermal: 553\n  hydro: 1247\n  hydro storage: 2350\n  nuclear: 5258\n  solar: 10910\n  wind: 630\ncontributors:\n  - tmslaine\n  - lorrieq\n  - nessie2013\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.033985956162019444\n        coal: 0.28170603461764726\n        gas: 0.3330626389526564\n        geothermal: 0.014349605181856644\n        hydro: 0.06192998279671365\n        hydro discharge: 0.015538910856105924\n        nuclear: 0.13875495200629423\n        oil: 0.03020973089231481\n        solar: 0.08393703544817312\n        unknown: 0.0\n        wind: 0.006524887364229839\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.030507003857400496\n        coal: 0.252869346864536\n        gas: 0.29896885923487737\n        geothermal: 0.012880720955439079\n        hydro: 0.055590561468817516\n        hydro discharge: 0.019144985100891618\n        nuclear: 0.20287163022142624\n        oil: 0.02711733998526308\n        solar: 0.0934833342044879\n        unknown: 0.0\n        wind: 0.006566022225949956\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.026250876299323274\n        coal: 0.217590610557113\n        gas: 0.2572586085305627\n        geothermal: 0.011083702831574\n        hydro: 0.04783493224453717\n        hydro discharge: 0.021806154489575045\n        nuclear: 0.2840613040725001\n        oil: 0.023334110034332813\n        solar: 0.10434562565633312\n        unknown: 0.0\n        wind: 0.006434060019099693\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03394897773719484\n        coal: 0.22632657220005892\n        gas: 0.2873090098066224\n        geothermal: 0.01194500543331599\n        hydro: 0.045894001247654526\n        hydro discharge: 0.0014535498433951002\n        nuclear: 0.24481052728855904\n        oil: 0.023261336772847918\n        solar: 0.11795166084263495\n        unknown: 6.823822454306038e-09\n        wind: 0.007099343743477133\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.029980656680773175\n        coal: 0.2034428315861572\n        gas: 0.2291408699669696\n        geothermal: 0.012313191688658286\n        hydro: 0.04068847020057973\n        hydro discharge: 0.0005706782834496352\n        nuclear: 0.33576216186990826\n        oil: 0.020344290025776444\n        solar: 0.12049004039136982\n        unknown: 4.648902623869007e-08\n        wind: 0.007266772492712764\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03137793612614937\n        coal: 0.26370830471228013\n        gas: 0.29642148828149034\n        geothermal: 0.01134944800687775\n        hydro: 0.03938933169949516\n        hydro discharge: 1.4890456350998663e-05\n        nuclear: 0.19245201874391707\n        oil: 0.026037025320914\n        solar: 0.13257787940397292\n        unknown: 1.4072176719601038e-08\n        wind: 0.006671659454808292\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04080813412599562\n        coal: 0.20078019353039148\n        gas: 0.22635379007972795\n        geothermal: 0.012514275416954341\n        hydro: 0.04407360592129915\n        hydro discharge: 0.0007970346676334808\n        nuclear: 0.31569313641701996\n        oil: 0.01958832361247529\n        solar: 0.13295698947047976\n        unknown: 2.5602993056442e-07\n        wind: 0.006434258264009721\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.040885288575177016\n        coal: 0.20118330213456703\n        gas: 0.2268079907902187\n        geothermal: 0.012536916358312692\n        hydro: 0.04416228528977139\n        hydro discharge: 3.161895011155409e-05\n        nuclear: 0.30967160366610286\n        oil: 0.01962788450210204\n        solar: 0.1382906879744919\n        unknown: 1.0724997702627927e-06\n        wind: 0.006801352931139955\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP_KY.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Tokyo\nzone_name: \"Ky\\u016Bsh\\u016B\"\n"
  },
  {
    "path": "config/zones/JP-ON.yaml",
    "content": "bounding_box:\n  - - 123.68463684636848\n    - 24.258473913558973\n  - - 128.33588335883357\n    - 26.801508107725923\ncenter_point:\n  - 127.65187651876519\n  - 26.084535608413802\ncentroid:\n  - 126.27640562119906\n  - 25.58028335020069\ncapacity:\n  biomass: 49\n  coal: 1629\n  gas: 326\n  geothermal: 0\n  hydro storage: 0\n  nuclear: 0\n  oil: 189.78\n  wind: 28\ncontributors:\n  - tmslaine\n  - lorrieq\n  - PPsyrius\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0028506457062307646\n        coal: 0.3953634197089307\n        gas: 0.4818493294617507\n        geothermal: 0.0\n        hydro: 0.000949800684998449\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0693782396862219\n        solar: 0.04708949409155191\n        unknown: 0.0\n        wind: 0.0025155698310505305\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0037814729651085024\n        coal: 0.39900512253691617\n        gas: 0.4869376587395054\n        geothermal: 0.0\n        hydro: 0.000944915426176835\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.05483911616362458\n        solar: 0.05186020155720745\n        unknown: 0.0\n        wind: 0.0026280500915776507\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0047433367923606015\n        coal: 0.41271095214923137\n        gas: 0.4876648448806458\n        geothermal: 0.0\n        hydro: 1.0053684209298966e-07\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.043643847447303555\n        solar: 0.04873083755682375\n        unknown: 0.0\n        wind: 0.0025033722723516428\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004762743176907086\n        coal: 0.3991602040426934\n        gas: 0.5068097993644615\n        geothermal: 0.0\n        hydro: 0.0009521593653038117\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.040963489230560805\n        solar: 0.04479201252764861\n        unknown: 0.0\n        wind: 0.0025563585654276256\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02546372987017048\n        coal: 0.4121424814429852\n        gas: 0.4640138868877303\n        geothermal: 0.0\n        hydro: 0.0009426856352779482\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.040553579105178636\n        solar: 0.054296779577972805\n        unknown: 0.0\n        wind: 0.002583605881850423\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.040821913978799314\n        coal: 0.4082237074821024\n        gas: 0.45853965357176746\n        geothermal: 0.0\n        hydro: 0.0009488484091806692\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0398726159558643\n        solar: 0.04903754630246473\n        unknown: 0.0\n        wind: 0.0025526791088268984\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04229121034147396\n        coal: 0.40318028037604\n        gas: 0.4529905069109142\n        geothermal: 0.0\n        hydro: 0.0009393086184611133\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.03947179996916049\n        solar: 0.058710877767871775\n        unknown: 0.0\n        wind: 0.00241288392871925\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04249911341264845\n        coal: 0.4051622305990068\n        gas: 0.45521728968736763\n        geothermal: 0.0\n        hydro: 0.0009438912416695306\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.03966584859850861\n        solar: 0.054360569237001784\n        unknown: 0.0\n        wind: 0.002148162038523783\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Tokyo\nzone_name: Okinawa\n"
  },
  {
    "path": "config/zones/JP-SK.yaml",
    "content": "bounding_box:\n  - - 132.01152011520114\n    - 32.74050186450299\n  - - 134.75114751147512\n    - 34.5536838138612\ncenter_point:\n  - 134.05877478419495\n  - 33.918963657891666\ncentroid:\n  - 133.49624463986575\n  - 33.682846828024886\ncapacity:\n  biomass: 406\n  coal: 950\n  gas: 935\n  geothermal: 0\n  hydro: 1153\n  hydro storage: 615\n  nuclear: 890\n  oil: 1350\n  solar: 2230\n  wind: 227\ncontributors:\n  - tmslaine\n  - lorrieq\n  - wobniarin\n  - PPsyrius\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\ndisclaimer: The data provider (Yonden Shikoku Electric Power Co.,Inc.) provides live\n  data only for solar and unknown. We are working on improving the data quality for\n  this zone.\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 380.86\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 404.86\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0017670065739433477\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0957791738379936\n        hydro discharge: 0.007872011143896315\n        nuclear: 0.09367397817234568\n        oil: 0.0\n        solar: 0.05250354218500326\n        unknown: 0.7410320173293622\n        wind: 0.007372270757455561\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001932994793126772\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.07070912197660897\n        hydro discharge: 0.008002452500712725\n        nuclear: 0.13483776005806172\n        oil: 0.0\n        solar: 0.05709965444095634\n        unknown: 0.7197594517126974\n        wind: 0.007658554274926757\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.003049768532534406\n        coal: 0.007938875379716435\n        gas: 0.009645725091666118\n        geothermal: 7.074485726964554e-05\n        hydro: 0.09785819894867925\n        hydro discharge: 0.009869676018915984\n        nuclear: 0.0310013100924916\n        oil: 0.0010382364768123104\n        solar: 0.07523260641150845\n        unknown: 0.7528468097692773\n        wind: 0.011448043806800643\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008463979043089974\n        coal: 0.030879628212266187\n        gas: 0.03645494241164602\n        geothermal: 0.000258951565875074\n        hydro: 0.07162956889603042\n        hydro discharge: 0.00964151550378777\n        nuclear: 0.17358851440270676\n        oil: 0.0032951222266845285\n        solar: 0.08144441928026754\n        unknown: 0.5753300432844124\n        wind: 0.0090132567677831\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0043054714338039545\n        coal: 0.010995026442846117\n        gas: 0.013956542765237908\n        geothermal: 8.473726271727578e-05\n        hydro: 0.02042236833550643\n        hydro discharge: 0.0013641545036965012\n        nuclear: 0.056475978710573596\n        oil: 0.0011164924186019849\n        solar: 0.10292576843063772\n        unknown: 0.7874879233909325\n        wind: 0.0008655226317445266\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0014632833096522445\n        coal: 0.012930350525976334\n        gas: 0.014550449912484989\n        geothermal: 9.896762265961738e-05\n        hydro: 0.005102399178544541\n        hydro discharge: 0.0002520143405323658\n        nuclear: 0.006681381248855223\n        oil: 0.0012934106178200055\n        solar: 0.11576846212590676\n        unknown: 0.8412683278694898\n        wind: 0.0005909065710037857\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0022460134007749304\n        coal: 0.024410886804090707\n        gas: 0.027433472824604305\n        geothermal: 0.00017374084794918984\n        hydro: 0.00399630140664376\n        hydro discharge: 9.876085705727245e-05\n        nuclear: 0.0044118582251994444\n        oil: 0.002426436589029858\n        solar: 0.12074359171205047\n        unknown: 0.8135228086687375\n        wind: 0.0005361257738893699\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0022637774197995083\n        coal: 0.01994389436875295\n        gas: 0.022414514452391922\n        geothermal: 0.00014365806742060668\n        hydro: 0.008228050565418175\n        hydro discharge: 0.0004365669906866007\n        nuclear: 0.009006787074649166\n        oil: 0.001957800954233004\n        solar: 0.1357522181667791\n        unknown: 0.7990401578264699\n        wind: 0.000812561771415958\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005708489971235517\n        coal: 0.05411516388145259\n        gas: 0.06081348036067326\n        geothermal: 0.0003519266171304085\n        hydro: 0.012581577553784837\n        hydro discharge: 0.0003111147176407504\n        nuclear: 0.09775673467049312\n        oil: 0.005318486311584602\n        solar: 0.15121531986285167\n        unknown: 0.6105501241479387\n        wind: 0.0012775695365145267\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.3375\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2581\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP_SK.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Tokyo\nzone_name: Shikoku\n"
  },
  {
    "path": "config/zones/JP-TH.yaml",
    "content": "bounding_box:\n  - - 137.61317613176132\n    - 36.73036080279081\n  - - 142.07002070020698\n    - 41.54738561852855\ncenter_point:\n  - 140.32304547985945\n  - 38.926745743272534\ncentroid:\n  - 140.11591384446015\n  - 38.727815667379986\ncapacity:\n  biomass: 600\n  coal: 6200\n  gas: 7000\n  geothermal: 188.8\n  hydro: 2000\n  hydro storage: 460\n  nuclear: 2750\n  oil: 2500\n  solar: 7000\n  unknown: 0\n  wind: 1800\ncontributors:\n  - tmslaine\n  - lorrieq\n  - PPsyrius\n  - mathilde-daugy\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03764593326241691\n        coal: 0.3256188602245305\n        gas: 0.38144187545598235\n        geothermal: 0.0073815476141916555\n        hydro: 0.1176435394724904\n        hydro discharge: 0.0007489652825544231\n        nuclear: 0.0\n        oil: 0.035800536970470496\n        solar: 0.039249783539561246\n        unknown: 0.01716211099718546\n        wind: 0.03730675609317582\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03720879013007687\n        coal: 0.3218725132026469\n        gas: 0.37705364916791956\n        geothermal: 0.0072961361711002546\n        hydro: 0.1162925346555782\n        hydro discharge: 0.0008998647364768234\n        nuclear: 0.0\n        oil: 0.03538851475966323\n        solar: 0.05395577986378438\n        unknown: 0.016962464104027655\n        wind: 0.03306969195343717\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03690415713459306\n        coal: 0.31965452384652704\n        gas: 0.37446009319183776\n        geothermal: 0.007240006841962388\n        hydro: 0.11552139670625632\n        hydro discharge: 0.0008814050839498607\n        nuclear: 0.0\n        oil: 0.035143114349214216\n        solar: 0.05981080345905751\n        unknown: 0.016819223638638064\n        wind: 0.03356529922051974\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.033361158089435336\n        coal: 0.32760117231960284\n        gas: 0.41530845559181406\n        geothermal: 0.009929425459088401\n        hydro: 0.1092545778933176\n        hydro discharge: 0.0003688168361996912\n        nuclear: 0.0\n        oil: 0.03328208612719063\n        solar: 0.028344983558882385\n        unknown: 0.019073191073038356\n        wind: 0.02347614385177979\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.030256458885341765\n        coal: 0.31858008121380094\n        gas: 0.36441553292209394\n        geothermal: 0.009495361204189156\n        hydro: 0.1143774554467616\n        hydro discharge: 8.173520094502279e-05\n        nuclear: 2.882919098580099e-09\n        oil: 0.03328704073978625\n        solar: 0.08023921362365893\n        unknown: 0.01769287150997027\n        wind: 0.03157424709126255\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03650782466272135\n        coal: 0.31684072338578595\n        gas: 0.3494877947948115\n        geothermal: 0.009804876965237134\n        hydro: 0.10969368860580067\n        hydro discharge: 1.6957503676816235e-05\n        nuclear: 1.9027172059335816e-07\n        oil: 0.044016102347221184\n        solar: 0.08249535024589032\n        unknown: 0.02013284497425742\n        wind: 0.03100365533190976\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.036500488598687666\n        coal: 0.31421716204339356\n        gas: 0.3465384349449994\n        geothermal: 0.009772117239547058\n        hydro: 0.10808427144891192\n        hydro discharge: 3.066165346151429e-05\n        nuclear: 0.0\n        oil: 0.043728292637667365\n        solar: 0.09227134205539649\n        unknown: 0.020100642712655332\n        wind: 0.028756583729499765\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03656881025725588\n        coal: 0.3139373265352168\n        gas: 0.3462524692389134\n        geothermal: 0.00973818807037935\n        hydro: 0.10800992269495781\n        hydro discharge: 0.0\n        nuclear: 4.881836630196875e-09\n        oil: 0.04364368131055737\n        solar: 0.09302782105896609\n        unknown: 0.02001169518819592\n        wind: 0.028810073378378175\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Tokyo\nzone_name: 'Tōhoku'\n"
  },
  {
    "path": "config/zones/JP-TK.yaml",
    "content": "bounding_box:\n  - - 138.16758167581676\n    - 34.595185216016986\n  - - 140.87840878408784\n    - 37.15179044338253\ncenter_point:\n  - 139.4863552841068\n  - 36.10735378706691\ncentroid:\n  - 139.54208994226607\n  - 35.99475882211827\ncapacity:\n  biomass: 440\n  coal: 8370\n  gas: 48124\n  hydro: 3150\n  hydro storage: 7150\n  nuclear: 0\n  oil: 10050\n  solar: 11900\n  wind: 440\ncontributors:\n  - tmslaine\n  - lorrieq\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012370895639882317\n        coal: 0.3853426055293789\n        gas: 0.41388649952534495\n        geothermal: 0.0\n        hydro: 0.053918260416420005\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.05838524380600273\n        solar: 0.07210803438342994\n        unknown: 0.0\n        wind: 0.003988449173393761\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011996226180391588\n        coal: 0.380914047071365\n        gas: 0.43494259096157817\n        geothermal: 0.0011562871177596096\n        hydro: 0.05976939423407587\n        hydro discharge: 7.555737043782422e-05\n        nuclear: 4.780317011741073e-05\n        oil: 0.0374279737240795\n        solar: 0.06661432998677642\n        unknown: 0.0022735369566184256\n        wind: 0.004782247765588545\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011119899407168976\n        coal: 0.3760090974593132\n        gas: 0.4241030932528087\n        geothermal: 0.0009075110252259826\n        hydro: 0.058286677206498626\n        hydro discharge: 0.00028064454153066464\n        nuclear: 0.00012157963858525248\n        oil: 0.03699902965963558\n        solar: 0.08544207988219815\n        unknown: 0.0017230525987717944\n        wind: 0.005007333077393812\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00935532858238416\n        coal: 0.3919883704990806\n        gas: 0.4415716257140104\n        geothermal: 0.0\n        hydro: 0.053325386573576064\n        hydro discharge: 0.014843572028037879\n        nuclear: 0.0\n        oil: 0.03835685850107804\n        solar: 0.04826121981944001\n        unknown: 0.0\n        wind: 0.0022975925090292265\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010070218932334415\n        coal: 0.38559099042086575\n        gas: 0.4349624301661337\n        geothermal: 0.00022385488142396474\n        hydro: 0.05489768176982327\n        hydro discharge: 0.01647566943732881\n        nuclear: 6.529647299520753e-05\n        oil: 0.03791072586966863\n        solar: 0.055935842779329205\n        unknown: 0.0005408376060012563\n        wind: 0.003326424967803098\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011665557105354935\n        coal: 0.3805469538565768\n        gas: 0.43029315791638295\n        geothermal: 0.0006684959834321141\n        hydro: 0.05883101141312595\n        hydro discharge: 0.012145290081717474\n        nuclear: 0.00014936007274681906\n        oil: 0.037641884377089485\n        solar: 0.06140723282159109\n        unknown: 0.0015901074760213602\n        wind: 0.005060943913134998\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012379568482169454\n        coal: 0.37439453711012355\n        gas: 0.4202638451430668\n        geothermal: 0.0008542784751887408\n        hydro: 0.05753353911915293\n        hydro discharge: 0.0001333861092187091\n        nuclear: 0.0003325895401583784\n        oil: 0.03780803037622701\n        solar: 0.08964952092622937\n        unknown: 0.0019145623932783529\n        wind: 0.0047361387156510506\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.013790551138107865\n        coal: 0.36551132512845863\n        gas: 0.41075161697370277\n        geothermal: 0.0011590638514077571\n        hydro: 0.05588616817339554\n        hydro discharge: 0.0004925191610828632\n        nuclear: 0.0005533549771950461\n        oil: 0.03725998358627039\n        solar: 0.10660586474618902\n        unknown: 0.0025203299900987465\n        wind: 0.005469220941016988\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.014097055380593861\n        coal: 0.3675956461150956\n        gas: 0.4130408358768425\n        geothermal: 0.0012366757869445553\n        hydro: 0.05676046343629951\n        hydro discharge: 0.0037118012335324085\n        nuclear: 0.0006673584139509615\n        oil: 0.03756657594799087\n        solar: 0.09707166612504159\n        unknown: 0.0026074670238986205\n        wind: 0.005644454624628442\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumptionForecast: JP.fetch_consumption_forecast\n  generationForecast: JP.fetch_generation_forecast\n  price: JP.fetch_price\n  production: JP.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: Asia/Tokyo\nzone_name: \"T\\u014Dky\\u014D\"\n"
  },
  {
    "path": "config/zones/JP.yaml",
    "content": "bounding_box:\n  - - 123.68463684636848\n    - 24.258473913558973\n  - - 145.76725767257673\n    - 45.51005398299017\ncenter_point:\n  - 139.19854103544216\n  - 37.570742015371266\ncentroid:\n  - 136.01390870678517\n  - 36.04844898300186\ncapacity:\n  battery storage: null\n  biomass: 2847.6\n  coal: 33620\n  gas: 92381.7\n  geothermal: 426.0\n  hydro: 17215\n  hydro storage: 22052\n  nuclear: 27019\n  oil: 28579.8\n  solar: 28577.9\n  unknown: 9976.9\n  wind: 3978.8\ncontributors:\n  - kongkille\n  - lorrieq\n  - tmslaine\n  - wobniarin\n  - pierresegonne\n  - nessie2013\n  - alejandranavcas\ncountry: JP\ncountry_name: Japan\ncurrency: JPY\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 354.18\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 378.18\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012890166231765952\n        coal: 0.3297373094572689\n        gas: 0.3851315399562788\n        geothermal: 0.002576233354606651\n        hydro: 0.08609909225463049\n        hydro discharge: 0.010891998842301588\n        nuclear: 0.032256842281156016\n        oil: 0.03984713514700535\n        solar: 0.052759691155786645\n        unknown: 0.039029123269701795\n        wind: 0.008780861800557293\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012579385219234667\n        coal: 0.317939719798783\n        gas: 0.3715240746624608\n        geothermal: 0.00243907007825665\n        hydro: 0.08485848258811383\n        hydro discharge: 0.012447051756622002\n        nuclear: 0.05416672302363694\n        oil: 0.03541426941823752\n        solar: 0.0634301200843758\n        unknown: 0.03657406715720228\n        wind: 0.008627026360518536\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012988508373644755\n        coal: 0.31165116020572337\n        gas: 0.36119139810368284\n        geothermal: 0.002257605082148037\n        hydro: 0.0795624263486067\n        hydro discharge: 0.011299020384023884\n        nuclear: 0.0743656111986386\n        oil: 0.0325723407535098\n        solar: 0.07077107684146505\n        unknown: 0.0346647988064565\n        wind: 0.008676048447415005\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01465903824457887\n        coal: 0.3159346019168975\n        gas: 0.38592384630295423\n        geothermal: 0.0029529798085520466\n        hydro: 0.08138219421061166\n        hydro discharge: 0.0015325928227609476\n        nuclear: 0.041181756512238876\n        oil: 0.031743284663153945\n        solar: 0.0759251229072427\n        unknown: 0.0409487451202268\n        wind: 0.007815834782044043\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01444660093127893\n        coal: 0.3106897402985635\n        gas: 0.35149118991450906\n        geothermal: 0.0026940061618264473\n        hydro: 0.08061336139135558\n        hydro discharge: 0.0007911772733235225\n        nuclear: 0.07241004251293315\n        oil: 0.03115956984062142\n        solar: 0.08993544012090543\n        unknown: 0.03747704290547159\n        wind: 0.008291834708808008\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01819566202729992\n        coal: 0.31733975074291015\n        gas: 0.3548325155823924\n        geothermal: 0.002630345141567221\n        hydro: 0.07510282030814988\n        hydro discharge: 0.00024122386135611262\n        nuclear: 0.05196932530032456\n        oil: 0.034904706698653136\n        solar: 0.09588677110448308\n        unknown: 0.04093027075235674\n        wind: 0.007966608525503018\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.020696070431356656\n        coal: 0.29746242116922483\n        gas: 0.33281740268070087\n        geothermal: 0.0028430919385634976\n        hydro: 0.07555456187278706\n        hydro discharge: 0.000549996614177763\n        nuclear: 0.08321651205376797\n        oil: 0.03283893320293683\n        solar: 0.10704124737108849\n        unknown: 0.039034565358988055\n        wind: 0.00794519536479448\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.020694197803047158\n        coal: 0.2998703281394674\n        gas: 0.33552132619216785\n        geothermal: 0.002823118776793938\n        hydro: 0.07542443871301358\n        hydro discharge: 0.0012834026861352611\n        nuclear: 0.09061121851842151\n        oil: 0.03308365916724243\n        solar: 0.10342626615078988\n        unknown: 0.029215896952754124\n        wind: 0.008046150827843417\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.3458\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.2874\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nsubZoneNames:\n  - JP-CB\n  - JP-CG\n  - JP-HKD\n  - JP-HR\n  - JP-KN\n  - JP-KY\n  - JP-ON\n  - JP-SK\n  - JP-TH\n  - JP-TK\ntimezone: Asia/Tokyo\nzone_name: Japan\n"
  },
  {
    "path": "config/zones/KE.yaml",
    "content": "bounding_box:\n  - - 33.91022073768978\n    - -4.678020968858455\n  - - 41.88461884618849\n    - 5.030444969930855\ncenter_point:\n  - 37.735819715673145\n  - 0.167927051183264\ncentroid:\n  - 37.41372620153136\n  - 0.9678818017858468\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 840.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 850.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 860.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 320.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1380.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1390.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1570.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1500.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1590.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1550.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1510.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 340.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 440.0\ncountry: KE\ncountry_name: Kenya\ncurrency: KES\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Nairobi\nzone_name: Kenya\n"
  },
  {
    "path": "config/zones/KG.yaml",
    "content": "bounding_box:\n  - - 69.22689226892268\n    - 39.190392192646186\n  - - 80.21060210602107\n    - 43.261822852412635\ncenter_point:\n  - 75.1427702005121\n  - 41.27352312964108\ncentroid:\n  - 73.56645493060435\n  - 41.02530296850483\ncapacity:\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 810.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3690.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3670.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2780.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 3140.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 3260.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: KG\ncountry_name: Kyrgyzstan\ncurrency: KGS\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Bishkek\nzone_name: Kyrgyzstan\n"
  },
  {
    "path": "config/zones/KH.yaml",
    "content": "bounding_box:\n  - - 102.32922329223291\n    - 10.419902918851918\n  - - 107.60687606876067\n    - 14.704564920729169\ncenter_point:\n  - 104.98856517147142\n  - 12.474528391008167\ncentroid:\n  - 105.16052484468507\n  - 12.781915212697765\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 500.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 660.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 710.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1460.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 980.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1330.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1340.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 330.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 400.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 480.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 490.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 880.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 300.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 660.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 620.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 640.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 650.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: KH\ncountry_name: Cambodia\ncurrency: KHR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Phnom_Penh\nzone_name: Cambodia\n"
  },
  {
    "path": "config/zones/KM.yaml",
    "content": "bounding_box:\n  - - 43.263432634326364\n    - -12.380108775840185\n  - - 44.53064530645307\n    - -11.379781875602312\ncenter_point:\n  - 44.20664206642067\n  - -12.161153102397563\ncentroid:\n  - 43.79551795517956\n  - -11.883379924520352\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\ncountry: KM\ncountry_name: Comoros\ncurrency: KMF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Indian/Comoro\nzone_name: Comoros\n"
  },
  {
    "path": "config/zones/KP.yaml",
    "content": "bounding_box:\n  - - 124.32184321843218\n    - 37.68632413520699\n  - - 130.7011070110701\n    - 42.98133061715281\ncenter_point:\n  - 127.14091694367448\n  - 40.004097703647005\ncentroid:\n  - 127.36051684841172\n  - 40.123284149120195\ncapacity:\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2960.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3360.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3380.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4760.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 4790.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 4860.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4890.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: KP\ncountry_name: North Korea\ncurrency: KPW\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Pyongyang\nzone_name: North Korea\n"
  },
  {
    "path": "config/zones/KR.yaml",
    "content": "bounding_box:\n  - - 126.10386103861035\n    - 33.199879453882616\n  - - 129.55629556295563\n    - 38.623683390794696\ncenter_point:\n  - 127.94887712074126\n  - 36.47203857915312\ncentroid:\n  - 127.27504275042747\n  - 35.731930087306615\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2290.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2320.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 3150.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 3540.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2640.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2650.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2680.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 37580.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 37850.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 36650.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 38070.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 39110.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 40150.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 41200.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40530.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 41720.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 43470.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 43760.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 44510.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 45080.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 47080.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 49840.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1790.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1800.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1810.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1820.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1810.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1800.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 22530.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 21850.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 23250.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 24650.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 26050.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3930.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 4080.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 3980.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 4240.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 4320.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4250.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 4030.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5630.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 7700.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10850.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 14760.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 17910.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 20520.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 23490.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 26650.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1140.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1300.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1490.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1640.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1710.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1950.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2200.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2300.0\ncontributors:\n  - systemcatch\n  - alixunderplatz\n  - IV1T3\n  - gadakast\n  - consideRatio\ncountry: KR\ncountry_name: South Korea\ncurrency: KRW\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 395.23\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 388.14\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 373.65\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 351.53\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 353.43\n  lifecycle:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 419.23\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 412.14\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 397.65\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 375.53\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 377.43\n    unknown:\n      _comment: 'Source: 2020 annual electricity production by IEA'\n      _url: https://www.iea.org/fuels-and-technologies/electricity\n      source: IEA 2020; assumes 54.1% coal, 36.1% gas, 1.5% oil, 4.4% solar, 0.8%\n        wind, 2.2% biofuels, 1.0% other\n      value: 644\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012088215643162988\n        coal: 0.4271166528414337\n        gas: 0.2578817417693911\n        geothermal: 0.0\n        hydro: 0.0050367478306313825\n        hydro discharge: 0.0\n        nuclear: 0.26090380067155367\n        oil: 0.0060441022416680285\n        solar: 0.026899347810935656\n        unknown: 0.004029413672613975\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012088360391989655\n        coal: 0.42712179271378803\n        gas: 0.2578848452931219\n        geothermal: 0.0\n        hydro: 0.005036808017031471\n        hydro discharge: 0.0\n        nuclear: 0.2609069402792454\n        oil: 0.0060441752048193634\n        solar: 0.026887636840641445\n        unknown: 0.004029461510810856\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011716871973276085\n        coal: 0.3644630544878464\n        gas: 0.27007032466083297\n        geothermal: 0.0\n        hydro: 0.005232261569814543\n        hydro discharge: 0.005726236492505157\n        nuclear: 0.2862754151521541\n        oil: 0.0052618305327118055\n        solar: 0.02049405482823824\n        unknown: 0.030759971259422855\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011716871973276085\n        coal: 0.3644630544878464\n        gas: 0.27007032466083297\n        geothermal: 0.0\n        hydro: 0.005232261569814543\n        hydro discharge: 0.005726236492505157\n        nuclear: 0.2862754151521541\n        oil: 0.0052618305327118055\n        solar: 0.02049405482823824\n        unknown: 0.030759971259422855\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012085851633007651\n        coal: 0.42703338051066464\n        gas: 0.2578314714748365\n        geothermal: 0.0\n        hydro: 0.005035771904351602\n        hydro discharge: 0.0\n        nuclear: 0.26085293528342535\n        oil: 0.006042924432066203\n        solar: 0.02708902676296785\n        unknown: 0.004028615141886627\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012067910760408326\n        coal: 0.42639948833207814\n        gas: 0.2574487448984514\n        geothermal: 0.0\n        hydro: 0.0050328568623645605\n        hydro discharge: 0.0\n        nuclear: 0.2606810244668617\n        oil: 0.006033955232642225\n        solar: 0.027655462709620944\n        unknown: 0.004680532814093565\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011686797411512923\n        coal: 0.4236187412338961\n        gas: 0.25849398909393584\n        geothermal: 0.0\n        hydro: 0.004944386764302841\n        hydro discharge: 0.0002359145163342492\n        nuclear: 0.2622175088440355\n        oil: 0.006118572641872112\n        solar: 0.026258664443736243\n        unknown: 0.006425399941252666\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.32481961990795116\n        gas: 0.2870998739838039\n        geothermal: 0.0\n        hydro: 0.005099702252579142\n        hydro discharge: 0.006488826453043251\n        nuclear: 0.30356122323757495\n        oil: 0.00503725621668324\n        solar: 0.008648519082736651\n        unknown: 0.05924497949229198\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.31696964158672425\n        gas: 0.2793854741693562\n        geothermal: 0.0\n        hydro: 0.005256161194972003\n        hydro discharge: 0.0065745038528354045\n        nuclear: 0.314805824151336\n        oil: 0.0041687726308622655\n        solar: 0.016818462031072384\n        unknown: 0.05602116015360554\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.28414636563156453\n        gas: 0.29282786831019314\n        geothermal: 0.0\n        hydro: 0.006104289039391443\n        hydro discharge: 0.007662933676723601\n        nuclear: 0.33026331297996314\n        oil: 0.004419523879319817\n        solar: 0.019400257201052595\n        unknown: 0.055175449564712\n        wind: 0.0\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2021-01-01'\n      value: 0.3322\n    - datetime: '2022-01-01'\n      value: 0.338\n    - datetime: '2023-01-01'\n      value: 0.36\n    - datetime: '2024-01-01'\n      value: 0.3815\n    - datetime: '2025-01-01'\n      value: 0.3839\n  unknown:\n    _comment: 'Source: 2020 annual electricity production by IEA'\n    _url: https://www.iea.org/fuels-and-technologies/electricity\n    source: IEA 2020; assumes 54.1% coal, 36.1% gas, 1.5% oil, 4.4% solar, 0.8% wind,\n      2.2% biofuels, 1.0% other\n    value: 0.084\nisRenewable:\n  hydro discharge:\n    - datetime: '2021-01-01'\n      value: 0.0015\n    - datetime: '2022-01-01'\n      value: 0.0143\n    - datetime: '2023-01-01'\n      value: 0.0306\n    - datetime: '2024-01-01'\n      value: 0.0389\n    - datetime: '2025-01-01'\n      value: 0.0501\n  unknown:\n    _comment: 'Source: 2020 annual electricity production by IEA'\n    _url: https://www.iea.org/fuels-and-technologies/electricity\n    source: IEA 2020; assumes 54.1% coal, 36.1% gas, 1.5% oil, 4.4% solar, 0.8% wind,\n      2.2% biofuels, 1.0% other\n    value: 0.084\nparsers:\n  consumption: KPX.fetch_consumption\n  price: KPX.fetch_price\n  production: KPX.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: Asia/Seoul\nzone_name: South Korea\n"
  },
  {
    "path": "config/zones/KW.yaml",
    "content": "bounding_box:\n  - - 46.532265322653245\n    - 28.533118335605508\n  - - 48.433084330843315\n    - 30.098722954861913\ncenter_point:\n  - 47.36852773144945\n  - 29.570845645234716\ncentroid:\n  - 47.789870743385976\n  - 29.50014299753782\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10220.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 11100.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 11650.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 11680.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 11720.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 8500.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\ncontributors:\n  - alixunderplatz\n  - nessie2013\n  - consideRatio\ncountry: KW\ncountry_name: Kuwait\ncurrency: KWD\nemissionFactors:\n  direct:\n    unknown:\n      _url: https://www.iea.org/fuels-and-technologies/electricity\n      source: IEA 2019; assumes 62.3% gas, 37.7% oil\n      value: 383.572\n  lifecycle:\n    unknown:\n      _url: https://www.iea.org/fuels-and-technologies/electricity\n      source: IEA 2019; assumes 62.3% gas, 37.7% oil\n      value: 550.3199999999999\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.9999999963920968\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.9999999967729631\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.9999999990496002\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.9999999920933934\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: KW.fetch_consumption\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Kuwait\nzone_name: Kuwait\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nisRenewable:\n  unknown:\n    source: IEA 2019; assumes 62.3% gas, 37.7% oil\n    value: 0\nisLowCarbon:\n  unknown:\n    source: IEA 2019; assumes 62.3% gas, 37.7% oil\n    value: 0\n"
  },
  {
    "path": "config/zones/KY.yaml",
    "content": "bounding_box:\n  - - -81.42729962458039\n    - 19.261071915595686\n  - - -79.72230689375876\n    - 19.755142692881883\ncenter_point:\n  - -80.11012136312443\n  - 19.661757918098214\ncentroid:\n  - -80.91321820571495\n  - 19.431235963505397\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncontributors:\n  - VIKTORVAV99\ncountry: KY\ncountry_name: Cayman Islands\ncurrency: KYD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Cayman\nzone_name: Cayman Islands\n"
  },
  {
    "path": "config/zones/KZ.yaml",
    "content": "bounding_box:\n  - - 46.47826478264784\n    - 40.584266871947605\n  - - 87.3242732427324\n    - 55.434613429556194\ncenter_point:\n  - 66.69259358749544\n  - 48.15576453417533\ncentroid:\n  - 65.54265701052896\n  - 48.73921073397628\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 13310.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 13300.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 13430.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 13550.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3750.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 4060.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4180.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2730.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2760.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2780.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2810.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2900.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2810.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 540.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 910.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1040.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1150.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1310.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1200.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 490.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 680.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1110.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1440.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1410.0\ncountry: KZ\ncountry_name: Kazakhstan\ncurrency: KZT\nfallbackZoneMixes:\n  _source: Our world in data 2019\n  _url: https://ourworldindata.org/grapher/electricity-prod-source-stacked?stackMode=relative&time=earliest..latest&country=~KAZ\n  powerOriginRatios:\n    value:\n      coal: 0.706728113937001\n      gas: 0.188180756380889\n      hydro: 0.0904234610265557\n      nuclear: 0.0\n      oil: 0.00749680842394995\n      solar: 0.00263474788812734\n      unknown: 0.00452705822702292\n      wind: 0.00449084176120673\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Almaty\nzone_name: Kazakhstan\n"
  },
  {
    "path": "config/zones/LA.yaml",
    "content": "bounding_box:\n  - - 100.10080100801005\n    - 13.917469362602077\n  - - 107.65727657276571\n    - 22.44672304703373\ncenter_point:\n  - 103.89189363748629\n  - 18.66296979024183\ncentroid:\n  - 103.97856593950556\n  - 18.164945227481375\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1880.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 5390.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 6230.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 8020.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 8960.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 9650.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 9780.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\ncountry: LA\ncountry_name: Laos\ncurrency: LAK\nfallbackZoneMixes:\n  _source: IEA 2020 (used because Our World in Data has a lot of 'other renewables' generation not broken down by type). Biomass includes waste.\n  _url: https://www.iea.org/data-and-statistics/data-browser?country=LAO&fuel=Energy%20supply&indicator=ElecGenByFuel\n  powerOriginRatios:\n    value:\n      biomass: 0.0014261409127302\n      coal: 0.28410228182546\n      hydro: 0.713395716573259\n      solar: 0.0010758606885508\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Vientiane\nzone_name: Laos\n"
  },
  {
    "path": "config/zones/LB.yaml",
    "content": "bounding_box:\n  - - 35.10575105751059\n    - 33.086823910078905\n  - - 36.603366033660365\n    - 34.64956636366941\ncenter_point:\n  - 35.854558545585476\n  - 33.86819513687416\ncentroid:\n  - 35.89103891038913\n  - 33.79158450254979\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1140.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 740.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 870.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1000.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1950.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: LB\ncountry_name: Lebanon\ncurrency: LBP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Beirut\nzone_name: Lebanon\n"
  },
  {
    "path": "config/zones/LC.yaml",
    "content": "bounding_box:\n  - - -61.07641076410759\n    - 13.72141101448679\n  - - -60.88560885608851\n    - 14.10207904805371\ncenter_point:\n  - -60.98100981009805\n  - 13.91174503127025\ncentroid:\n  - -60.96210962109616\n  - 13.90995617772905\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\ncountry: LC\ncountry_name: Saint Lucia\ncurrency: XCD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/St_Lucia\nzone_name: Saint Lucia\n"
  },
  {
    "path": "config/zones/LI.yaml",
    "content": "bounding_box:\n  - - 9.474840270001467\n    - 47.05662268643502\n  - - 9.622084772297283\n    - 47.266310486741915\ncenter_point:\n  - 9.548462521149375\n  - 47.16146658658847\ncentroid:\n  - 9.558664351995736\n  - 47.13078739327011\ncountry: LI\ncountry_name: Liechtenstein\ncurrency: CHF\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0.0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 820.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: EIA 2020/BEIS 2021; IPCC 2014\n      value: 650.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: Europe/Vaduz\nzone_name: Liechtenstein\n"
  },
  {
    "path": "config/zones/LK.yaml",
    "content": "bounding_box:\n  - - 79.73179731797316\n    - 5.923440657696858\n  - - 81.88101881018812\n    - 9.818848129009424\ncenter_point:\n  - 80.81466458315062\n  - 7.7135449000821765\ncentroid:\n  - 80.65433987673212\n  - 7.8927696450511755\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 900.0\n  gas:\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 300.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1750.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1800.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1810.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1800.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1830.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1840.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1850.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 350.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 440.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 620.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 800.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 960.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1450.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 490.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\ncontributors:\n  - q--\ncountry: LK\ncountry_name: Sri Lanka\ncurrency: LKR\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00700018286090966\n        coal: 0.3298145186613395\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.41756944446162814\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.1827423841153009\n        solar: 0.010663339703359519\n        unknown: 0.0\n        wind: 0.05220988275374178\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00700018286090966\n        coal: 0.3298145186613395\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.41756944446162814\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.1827423841153009\n        solar: 0.010663339703359519\n        unknown: 0.0\n        wind: 0.05220988275374178\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00700018286090966\n        coal: 0.3298145186613395\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.41756944446162814\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.1827423841153009\n        solar: 0.010663339703359519\n        unknown: 0.0\n        wind: 0.05220988275374178\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007000182860909659\n        coal: 0.3298145186613395\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.41756944446162814\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.18274238411530086\n        solar: 0.010663339703359519\n        unknown: 0.0\n        wind: 0.05220988275374178\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00700018286090966\n        coal: 0.3298145186613395\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.41756944446162814\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.1827423841153009\n        solar: 0.010663339703359519\n        unknown: 0.0\n        wind: 0.05220988275374178\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00700018286090966\n        coal: 0.3298145186613395\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.41756944446162814\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.1827423841153009\n        solar: 0.010663339703359519\n        unknown: 0.0\n        wind: 0.05220988275374178\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006536343860492528\n        coal: 0.28624019284956276\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.41469112152057924\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.22709918190011136\n        solar: 0.006463054105010098\n        unknown: 0.0\n        wind: 0.058969853256126574\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007301433844119725\n        coal: 0.3555810574845595\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.4225211920247607\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.15463533756001555\n        solar: 0.013187344859185718\n        unknown: 0.0\n        wind: 0.04677362839649372\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: CEB.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Colombo\nzone_name: Sri Lanka\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/LR.yaml",
    "content": "bounding_box:\n  - - -11.475114751147487\n    - 4.353542789941564\n  - - -7.385473854738507\n    - 8.50654517118663\ncenter_point:\n  - -9.398158211298103\n  - 6.480789931196075\ncentroid:\n  - -9.223243583787157\n  - 6.804600903655141\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\ncountry: LR\ncountry_name: Liberia\ncurrency: LRD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Monrovia\nzone_name: Liberia\n"
  },
  {
    "path": "config/zones/LS.yaml",
    "content": "bounding_box:\n  - - 27.016470164701673\n    - -30.659329801216934\n  - - 29.4356943569436\n    - -28.571379947930733\ncenter_point:\n  - 28.257855823214147\n  - -29.55365921123402\ncentroid:\n  - 28.269082690826927\n  - -29.57870325312974\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: LS\ncountry_name: Lesotho\ncurrency: LSL\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Maseru\nzone_name: Lesotho\n"
  },
  {
    "path": "config/zones/LT.yaml",
    "content": "bounding_box:\n  - - 21.054810548105507\n    - 53.886181804295276\n  - - 26.800468004680056\n    - 56.43923357829294\ncenter_point:\n  - 23.779440339287618\n  - 55.17010626832506\ncentroid:\n  - 24.167845933778512\n  - 55.14273342877452\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 122.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 124.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 117.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 120.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 147.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 165.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 169.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 266.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1656.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1873.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1710.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1770.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1887.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1527.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1518.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1503.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 128.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 129.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 900.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 160.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 80.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 82.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 103.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 169.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 259.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 578.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1165.0\n    - datetime: '2024-10-22'\n      source: litgrid.eu\n      value: 1878.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1787.0\n    - datetime: '2025-02-16'\n      source: litgrid.eu\n      value: 2408.0\n    - datetime: '2025-08-04'\n      source: litgrid.eu\n      value: 2725\n    - datetime: '2025-10-13'\n      source: litgrid.eu\n      value: 2936\n    - datetime: '2026-01-22'\n      source: litgrid.eu\n      value: 3040\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 119.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 37.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 140.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 144.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 37.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 426.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 509.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 525.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 534.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 540.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 671.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 814.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1288.0\n    - datetime: '2024-10-22'\n      source: litgrid.eu\n      value: 1669.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1683.0\n    - datetime: '2025-02-16'\n      source: litgrid.eu\n      value: 1832.0\n    - datetime: '2025-08-04'\n      source: litgrid.eu\n      value: 1890\n    - datetime: '2025-10-13'\n      source: litgrid.eu\n      value: 2467\n    - datetime: '2026-01-22'\n      source: litgrid.eu\n      value: 2507\ncontributors:\n  - corradio\n  - nessie2013\n  - pnook\ncountry: LT\ncountry_name: Lithuania\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 92.47\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 356.9797889\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 364.92\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 375.63\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 370.92\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 186.79\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 185.05\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 133.35\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 109.9\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 84.94\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 125.47\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1117.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1135.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 476.9797889\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 484.92\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 495.63\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 490.92\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 197.49\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 195.75\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 144.05\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 120.6\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 95.64\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 36.7\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05248411349032074\n        coal: 0.05410957136935189\n        gas: 0.5498319828891364\n        geothermal: 8.890677543935156e-08\n        hydro: 0.09958196705928497\n        hydro discharge: 0.06381532647345381\n        nuclear: 0.02292511683995068\n        oil: 0.018962654473867673\n        solar: 0.005532100620081096\n        unknown: 0.060178573091339824\n        wind: 0.07258559361999922\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03343794792536503\n        coal: 0.06796214229100345\n        gas: 0.3948300669090985\n        geothermal: 3.9011686323287086e-07\n        hydro: 0.15714578310251195\n        hydro discharge: 0.03567643266395548\n        nuclear: 0.07457517336225696\n        oil: 0.012278297484281721\n        solar: 0.006323762328486214\n        unknown: 0.08308854616171424\n        wind: 0.13468675819751547\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.040524136726138145\n        coal: 0.06179011942853122\n        gas: 0.34412162704835036\n        geothermal: 1.170729613990027e-06\n        hydro: 0.2028808100316546\n        hydro discharge: 0.04347080749967129\n        nuclear: 0.0737329628324882\n        oil: 0.008360737705869897\n        solar: 0.00996520364509855\n        unknown: 0.057008683854661485\n        wind: 0.15814330048030123\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.055446400794687566\n        coal: 0.08068442818665095\n        gas: 0.383651058869338\n        geothermal: 1.1117993135186523e-06\n        hydro: 0.15585773199696173\n        hydro discharge: 0.037016803474720916\n        nuclear: 0.07182488017669052\n        oil: 0.000621385046583624\n        solar: 0.010479269762924697\n        unknown: 0.060434597133172056\n        wind: 0.14398191265471402\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05082748486694587\n        coal: 0.038565273505017685\n        gas: 0.42115345358415485\n        geothermal: 2.7446720562004025e-06\n        hydro: 0.1319856762819108\n        hydro discharge: 0.037722596611730226\n        nuclear: 0.08483728564358439\n        oil: 0.0004722002402976221\n        solar: 0.011305876617725778\n        unknown: 0.0556435577567343\n        wind: 0.1674835721219137\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04507678603660674\n        coal: 0.02377638812927762\n        gas: 0.3875417612998455\n        geothermal: 2.469512608008812e-06\n        hydro: 0.14964038767798313\n        hydro discharge: 0.04951404250190653\n        nuclear: 0.09579798815568291\n        oil: 0.0004112515557346632\n        solar: 0.01122642063437331\n        unknown: 0.04389364005950168\n        wind: 0.19311854350862998\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.047925943878304345\n        coal: 0.04776297912426975\n        gas: 0.42477370647961976\n        geothermal: 2.6149652446671643e-06\n        hydro: 0.13257659988744355\n        hydro discharge: 0.045306533867647755\n        nuclear: 0.07696229147975046\n        oil: 0.0007338333395854026\n        solar: 0.013200091832599934\n        unknown: 0.054607840006566405\n        wind: 0.1561473919078319\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06637729612892118\n        coal: 0.06818008733608731\n        gas: 0.21196372949797992\n        geothermal: 2.0836819384971257e-06\n        hydro: 0.19781894990870744\n        hydro discharge: 0.03873234538949941\n        nuclear: 0.12314714199567293\n        oil: 0.0009310325311312035\n        solar: 0.03952004240635484\n        unknown: 0.048038964175032624\n        wind: 0.20528803541489582\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05655196401965516\n        coal: 0.04883246429477729\n        gas: 0.16348102709336995\n        geothermal: 3.300270413878182e-06\n        hydro: 0.21701709318007012\n        hydro discharge: 0.03797328764242016\n        nuclear: 0.10193877713604825\n        oil: 0.0012783940918923012\n        solar: 0.06290649370641835\n        unknown: 0.03905410407000422\n        wind: 0.27096274938468584\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06589342714295328\n        coal: 0.056309861715994815\n        gas: 0.11221310412513556\n        geothermal: 4.2501417654395745e-06\n        hydro: 0.15097814851642558\n        hydro discharge: 0.03221261763998207\n        nuclear: 0.10301244765672274\n        oil: 0.001391878206400795\n        solar: 0.11147260376627073\n        unknown: 0.03994096817220909\n        wind: 0.32657023348461944\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.8031\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 0.5664\n    - datetime: '2022-01-01'\n      value: 0.6858\n    - datetime: '2023-01-01'\n      value: 0.7743\n    - datetime: '2024-01-01'\n      value: 0.8268\n    - datetime: '2025-01-01'\n      value: 0.8259\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.6911\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 0.4172\n    - datetime: '2022-01-01'\n      value: 0.5276\n    - datetime: '2023-01-01'\n      value: 0.6457\n    - datetime: '2024-01-01'\n      value: 0.7216\n    - datetime: '2025-01-01'\n      value: 0.7566\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Vilnius\nzone_name: Lithuania\n"
  },
  {
    "path": "config/zones/LU.yaml",
    "content": "bounding_box:\n  - - 5.715057150571539\n    - 49.44123852512671\n  - - 6.499864998649997\n    - 50.17538401843433\ncenter_point:\n  - 6.107461074610768\n  - 49.80831127178052\ncentroid:\n  - 6.059460594605974\n  - 49.770864604318106\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 23.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 51.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 68.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 107.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 109.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 81.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 96.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 70.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 72.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 68.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 36.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 33.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 100.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 136.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 170.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 236.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 258.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 300.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 415.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 544.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 3.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 124.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 154.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 167.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 152.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 208.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 211.0\ncontributors:\n  - corradio\n  - clawfire\ncountry: LU\ncountry_name: Luxembourg\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 419.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1117.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1135.5\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.21456749104754422\n        coal: 0.0\n        gas: 0.4185259175872011\n        geothermal: 0.0\n        hydro: 0.12695380722496372\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.08801161206682072\n        unknown: 0.0\n        wind: 0.15193416556120712\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.21383808181150302\n        coal: 0.0\n        gas: 0.37643582893432576\n        geothermal: 0.0\n        hydro: 0.13395062018265708\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.13791457605340535\n        unknown: 0.0\n        wind: 0.1378536517973234\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.11949361258228737\n        coal: 0.24619929620596592\n        gas: 0.11917383792399038\n        geothermal: 0.00021149047279286727\n        hydro: 0.048811725292353\n        hydro discharge: 0.011250711587012676\n        nuclear: 0.11109822841835103\n        oil: 0.0023668356086947707\n        solar: 0.07757736732910861\n        unknown: 0.0537411980051304\n        wind: 0.21007476606940437\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.10689735985685489\n        coal: 0.2861901370925146\n        gas: 0.12099645367848631\n        geothermal: 0.0002316182724108953\n        hydro: 0.04191275410730669\n        hydro discharge: 0.01380047844785475\n        nuclear: 0.1342198034284611\n        oil: 0.004028389255397037\n        solar: 0.08061427730124582\n        unknown: 0.010461015958252193\n        wind: 0.20064718518757826\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.12130442948327717\n        coal: 0.21786872624479392\n        gas: 0.14042448300594898\n        geothermal: 0.0002539578448686344\n        hydro: 0.046238415536040404\n        hydro discharge: 0.012937885975010697\n        nuclear: 0.13580854506331708\n        oil: 0.005708261417265883\n        solar: 0.08395579027309823\n        unknown: 0.008758374791303772\n        wind: 0.2267408333383561\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.13891848224067577\n        coal: 0.1679189310601107\n        gas: 0.15027730950933207\n        geothermal: 0.00027308737947367084\n        hydro: 0.04779611447713042\n        hydro discharge: 0.015379140634962402\n        nuclear: 0.11966665457742459\n        oil: 0.005414645069716231\n        solar: 0.09457819546867892\n        unknown: 0.010150398770478557\n        wind: 0.2496268890642082\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.13280293567482676\n        coal: 0.17599561236142008\n        gas: 0.13844431124680057\n        geothermal: 0.00021320598479395434\n        hydro: 0.044641474065421224\n        hydro discharge: 0.011706834051457293\n        nuclear: 0.17100004640680147\n        oil: 0.0035905817797903003\n        solar: 0.09746803520923078\n        unknown: 0.012354043022982947\n        wind: 0.21178230103017712\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.14364831214036705\n        coal: 0.21144270756387973\n        gas: 0.1059082087148619\n        geothermal: 0.00023459156461679812\n        hydro: 0.0349517736614453\n        hydro discharge: 0.01486160393393248\n        nuclear: 0.11480412906225274\n        oil: 0.0034688023068582905\n        solar: 0.12287417629418598\n        unknown: 0.013399141698691303\n        wind: 0.23440642564614153\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 4.282291526566592e-09\n        biomass: 0.11094511640676172\n        coal: 0.1418255149699116\n        gas: 0.12364743153025343\n        geothermal: 0.00020290781940330487\n        hydro: 0.051412517607043066\n        hydro discharge: 0.01634613625375909\n        nuclear: 0.10950967729903625\n        oil: 0.0034234437025814496\n        solar: 0.13024347942695616\n        unknown: 0.017965257833079337\n        wind: 0.29447828804861786\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 2.7619834046278622e-06\n        biomass: 0.1279883254730636\n        coal: 0.12563072239039516\n        gas: 0.10866990957159231\n        geothermal: 0.0002185262321011272\n        hydro: 0.0653388655606905\n        hydro discharge: 0.019872182246053884\n        nuclear: 0.10596921089194933\n        oil: 0.003925383953487722\n        solar: 0.14342245350969185\n        unknown: 0.01357305789447995\n        wind: 0.28538771464591317\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Brussels\nzone_name: Luxembourg\n"
  },
  {
    "path": "config/zones/LV.yaml",
    "content": "bounding_box:\n  - - 20.968409684096855\n    - 55.666448848495435\n  - - 28.164881648816504\n    - 58.074961256364304\ncenter_point:\n  - 24.740841980259933\n  - 56.78915450258365\ncentroid:\n  - 24.680533731112973\n  - 56.77200053236797\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 105.37\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 105.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 126.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 145.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 149.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 164.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 177.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 166.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1123.79\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1124.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1110.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1026.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1021.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1162.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1157.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1112.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1538.62\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1539.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1578.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1588.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1609.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1588.0\n  solar:\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 7.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 9.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 11.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 14.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 63.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 303.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 450.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 53.15\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 53.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 59.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 74.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 84.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 87.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 165.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 136.0\ncontributors:\n  - corradio\ncountry: LV\ncountry_name: Latvia\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 107.46\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 419.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 371.24\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 349.46\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 140.46\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1117.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1135.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 491.24\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 469.46\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 36.9\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.09504488226252913\n        coal: 0.17656982454297007\n        gas: 0.22310568382372772\n        geothermal: 0.0\n        hydro: 0.2263664064858211\n        hydro discharge: 0.00012224239985325904\n        nuclear: 0.08229037657736865\n        oil: 0.00037894626480435744\n        solar: 8.876850431370061e-05\n        unknown: 0.16405280774188222\n        wind: 0.03200437266260717\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08189771321698394\n        coal: 0.1712809453959075\n        gas: 0.1990636745754738\n        geothermal: 9.417692144191098e-07\n        hydro: 0.2445436648455565\n        hydro discharge: 0.00029861780576549826\n        nuclear: 0.05388178070965694\n        oil: 0.0003854480877189986\n        solar: 0.0002979209245340262\n        unknown: 0.21724099587608078\n        wind: 0.03112948030331249\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08552327004877411\n        coal: 0.1496750955941263\n        gas: 0.14432210286145233\n        geothermal: 1.255033533359509e-08\n        hydro: 0.4085902566283227\n        hydro discharge: 0.00014812045208879298\n        nuclear: 0.03521523831372284\n        oil: 0.00023983551374329846\n        solar: 0.00036309793498135075\n        unknown: 0.14577450017930457\n        wind: 0.03014802090003997\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08364284473053937\n        coal: 0.1921991500947506\n        gas: 0.2598191640102835\n        geothermal: 4.12108574124939e-09\n        hydro: 0.22311662603962976\n        hydro discharge: 0.00012723165378483947\n        nuclear: 0.05077606500875387\n        oil: 0.00011405929006055935\n        solar: 0.000342903181272138\n        unknown: 0.15560803666667353\n        wind: 0.03425420093177749\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08545076868317923\n        coal: 0.09172167306413738\n        gas: 0.30249638623517294\n        geothermal: 2.7766739804536976e-08\n        hydro: 0.23721740431801513\n        hydro discharge: 0.0005150563633302783\n        nuclear: 0.07110788561554846\n        oil: 5.70662036462844e-05\n        solar: 0.0006316961072271966\n        unknown: 0.16465784439040873\n        wind: 0.04614484099430596\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0898126948383217\n        coal: 0.04995665509853091\n        gas: 0.2299055667647238\n        geothermal: 1.3993165637951246e-07\n        hydro: 0.33785316295911677\n        hydro discharge: 0.0027030312488021476\n        nuclear: 0.08003936534511286\n        oil: 8.987610386889827e-05\n        solar: 0.0031942242037972636\n        unknown: 0.1353622566783936\n        wind: 0.07108312963460697\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08234071697751133\n        coal: 0.08801770593874503\n        gas: 0.22938530378454994\n        geothermal: 1.2756384677520134e-07\n        hydro: 0.3217497601470483\n        hydro discharge: 0.0021879284636431955\n        nuclear: 0.07937004714847562\n        oil: 0.0001363739821282886\n        solar: 0.009580450902480473\n        unknown: 0.12337705730034124\n        wind: 0.0638544852699475\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.09292585647902754\n        coal: 0.1208972666737497\n        gas: 0.14847820274402757\n        geothermal: 1.638179584595734e-07\n        hydro: 0.3427591864646696\n        hydro discharge: 0.0013120283601649686\n        nuclear: 0.09375931945238343\n        oil: 0.00016567161031385468\n        solar: 0.019948911229690062\n        unknown: 0.09372424322338604\n        wind: 0.08602829248306244\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05207846896817518\n        coal: 0.044920953181890606\n        gas: 0.17322255957064592\n        geothermal: 2.998181005129642e-07\n        hydro: 0.419517919416186\n        hydro discharge: 0.0018609230408060517\n        nuclear: 0.10488522082976239\n        oil: 0.00016141341077307233\n        solar: 0.03106417812141424\n        unknown: 0.06886946641476197\n        wind: 0.1034190407728183\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0572098363742417\n        coal: 0.03729788923696401\n        gas: 0.20700559779989314\n        geothermal: 5.341400395094179e-07\n        hydro: 0.38026295701865964\n        hydro discharge: 0.004528413161912937\n        nuclear: 0.06391930448041454\n        oil: 0.0002909681818672423\n        solar: 0.05284467820377226\n        unknown: 0.056288524620116846\n        wind: 0.14035237273662302\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.7664\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.6684\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Riga\nzone_name: Latvia\n"
  },
  {
    "path": "config/zones/LY.yaml",
    "content": "bounding_box:\n  - - 9.286292862928661\n    - 19.495830245473655\n  - - 25.151651516515187\n    - 33.18127537705416\ncenter_point:\n  - 17.239798066171005\n  - 26.357581207474148\ncentroid:\n  - 16.397234781464054\n  - 29.556392561603673\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 9870.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 11040.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1680.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1840.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2320.0\ncountry: LY\ncountry_name: Libya\ncurrency: LYD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Tripoli\nzone_name: Libya\n"
  },
  {
    "path": "config/zones/MA.yaml",
    "content": "bounding_box:\n  - - -13.181145370926863\n    - 27.661588890001504\n  - - -1.04581045810454\n    - 35.92484053994865\ncenter_point:\n  - -6.462670406960019\n  - 31.706459352556955\ncentroid:\n  - -5.12783129851419\n  - 33.13633184283514\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2870.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 4260.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 4090.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 870.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1310.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 730.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 770.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 850.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 930.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1030.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1020.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1230.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1430.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1470.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1560.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1860.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2130.0\ncontributors:\n  - veqtrus\ncountry: MA\ncountry_name: Morocco\ncurrency: MAD\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010306354360311342\n        coal: 0.6460411407976566\n        gas: 0.02567974068347357\n        geothermal: 4.037909845698592e-09\n        hydro: 0.01992247514144871\n        hydro discharge: 0.0014164747707403162\n        nuclear: 0.011118840595286986\n        oil: 0.09302437212908383\n        solar: 0.04140740469202105\n        unknown: 0.029049155261980826\n        wind: 0.13130975196780073\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 7.114393621822565e-08\n        biomass: 0.0012889783243091681\n        coal: 0.6378568831495809\n        gas: 0.024544952734452185\n        geothermal: 3.976990223379074e-09\n        hydro: 0.022709171837901387\n        hydro discharge: 0.001755133500306001\n        nuclear: 0.013596236564253327\n        oil: 0.09184644052949957\n        solar: 0.04602936580239592\n        unknown: 0.028736370118761283\n        wind: 0.13163639894593068\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Casablanca\nzone_name: Morocco\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/MC.yaml",
    "content": "bounding_box:\n  - - 7.408986027133928\n    - 43.72474953690665\n  - - 7.439894931523015\n    - 43.75193523970334\ncenter_point:\n  - 7.424440479328471\n  - 43.738342388305\ncentroid:\n  - 7.425942965977081\n  - 43.741162498204744\ncontributors:\n  - VIKTORVAV99\ncountry: MC\ncountry_name: Monaco\ncurrency: EUR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Europe/Monaco\nzone_name: Monaco\n"
  },
  {
    "path": "config/zones/MD.yaml",
    "content": "bounding_box:\n  - - 26.616866168661716\n    - 45.461397166669585\n  - - 30.08010080100803\n    - 48.47239544721391\ncenter_point:\n  - 28.38562455797984\n  - 47.37689507165253\ncentroid:\n  - 28.585295609053674\n  - 47.05489044893901\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1400.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1380.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 340.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\ncontributors:\n  - systemcatch\n  - alixunderplatz\n  - nessie2013\n  - lgrigoryeva1\n  - Impelon\n  - amv213\ncountry: MD\ncountry_name: Moldova\ncurrency: MDL\nemissionFactors:\n  direct: {}\n  lifecycle:\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 30.25\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008716840525174937\n        coal: 0.0002759540687300226\n        gas: 0.36011946526329647\n        geothermal: 0.0\n        hydro: 0.039104137983876366\n        hydro discharge: 2.3858050069220964e-07\n        nuclear: 0.0004465593454114519\n        oil: 1.9949104012681937e-07\n        solar: 6.200397193130872e-08\n        unknown: 0.5913300511917193\n        wind: 5.51026602728674e-06\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.668706478679991e-05\n        coal: 0.049875561622420454\n        gas: 0.14418947703396315\n        geothermal: 0.0\n        hydro: 0.05813120361191743\n        hydro discharge: 1.7660446909956088e-05\n        nuclear: 0.08100880514493031\n        oil: 2.1514889969846033e-05\n        solar: 5.2273214148959246e-05\n        unknown: 0.6646049520188871\n        wind: 0.0020508643741359417\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.752076413338968e-05\n        coal: 0.03185752474641683\n        gas: 0.137514741586081\n        geothermal: 0.0\n        hydro: 0.054742915370019116\n        hydro discharge: 1.8402523314646013e-05\n        nuclear: 0.05768666768360798\n        oil: 3.113340024380469e-05\n        solar: 4.256476721883176e-05\n        unknown: 0.7173731063676382\n        wind: 0.0006744606221912076\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.6294422812787053e-05\n        coal: 0.00827796891884842\n        gas: 0.14390752822067657\n        geothermal: 0.0\n        hydro: 0.04752883646506809\n        hydro discharge: 7.817757990955192e-06\n        nuclear: 0.017919731087051603\n        oil: 8.444850877930208e-06\n        solar: 1.1904731366333694e-05\n        unknown: 0.782278690801424\n        wind: 3.1097118203166375e-05\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0020354116759184024\n        coal: 0.017005479788169443\n        gas: 0.47644842938527865\n        geothermal: 0.0\n        hydro: 0.05141278700063735\n        hydro discharge: 5.988680773354904e-06\n        nuclear: 0.04370886359227933\n        oil: 7.5715853938690655e-06\n        solar: 2.9846063469108084e-05\n        unknown: 0.40927774751756013\n        wind: 6.635470277233869e-05\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006870542912627435\n        coal: 0.04423854872400527\n        gas: 0.7787398136540892\n        geothermal: 8.169075582929427e-07\n        hydro: 0.08042931896539458\n        hydro discharge: 5.141903285849323e-05\n        nuclear: 0.06090369533876274\n        oil: 2.4813139830241076e-05\n        solar: 0.004780137995374411\n        unknown: 0.002858624443269382\n        wind: 0.021101113594369576\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007870635692543104\n        coal: 0.03043987270663597\n        gas: 0.7315091612134699\n        geothermal: 4.031803000215851e-06\n        hydro: 0.09382730506225677\n        hydro discharge: 0.00011316678430182057\n        nuclear: 0.050292957840746645\n        oil: 1.5507354100469533e-05\n        solar: 0.004694752840160269\n        unknown: 0.058162651930965974\n        wind: 0.023068726144843687\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01627946161732906\n        coal: 0.045911160555555115\n        gas: 0.7159979552350164\n        geothermal: 1.0827751976462925e-05\n        hydro: 0.09547994957878478\n        hydro discharge: 0.00036125812601598594\n        nuclear: 0.07636866395881964\n        oil: 4.3548436912188026e-05\n        solar: 0.012678326413849667\n        unknown: 0.0027065851482313144\n        wind: 0.03416068856152983\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: MD.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\ntimezone: Europe/Chisinau\nzone_name: Moldova\n"
  },
  {
    "path": "config/zones/ME.yaml",
    "content": "bounding_box:\n  - - 18.437584375843784\n    - 41.85220626194868\n  - - 20.34560345603458\n    - 43.53229750784176\ncenter_point:\n  - 19.15218054929269\n  - 42.79053342375187\ncentroid:\n  - 19.201408042781598\n  - 42.800464800493536\ncan_have_zero_production: true\ncapacity:\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 210.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 420.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 210.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 662.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 649.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 72.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 118.0\ncontributors:\n  - corradio\n  - nessie2013\n  - Pantkowsky\ncountry: ME\ncountry_name: Montenegro\ncurrency: EUR\nemissionFactors:\n  direct: {}\n  lifecycle:\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0012749064786441115\n        coal: 0.7125480452123912\n        gas: 0.012885756969304057\n        geothermal: 0.00011419068289716879\n        hydro: 0.2403041326573756\n        hydro discharge: 0.003764789259842393\n        nuclear: 0.01430228437740347\n        oil: 0.0011728765920777646\n        solar: 0.0015262645013469492\n        unknown: 0.007211730739030116\n        wind: 0.004889896472161038\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0012459914329927494\n        coal: 0.7170603545838463\n        gas: 0.013571893038551533\n        geothermal: 0.00014043975645679094\n        hydro: 0.2384725738509071\n        hydro discharge: 0.0022666725296123166\n        nuclear: 0.011960235903613173\n        oil: 0.00142174655374278\n        solar: 0.0014960549482372963\n        unknown: 0.007741451203414012\n        wind: 0.00461733619729345\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0017252352894054042\n        coal: 0.7592699003662353\n        gas: 0.013622989164626866\n        geothermal: 0.00012620460808098155\n        hydro: 0.1895606419634291\n        hydro discharge: 0.005421087732034137\n        nuclear: 0.017282173952505076\n        oil: 0.0009484601658165943\n        solar: 0.0022036485836303106\n        unknown: 0.0021684122216406713\n        wind: 0.007669405192060232\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002185397211059917\n        coal: 0.5838749959937793\n        gas: 0.02344035920156403\n        geothermal: 0.00027515105359789143\n        hydro: 0.33430334492720887\n        hydro discharge: 0.0021758776675706738\n        nuclear: 0.01622503742954775\n        oil: 0.002547254327099908\n        solar: 0.0023836402734302865\n        unknown: 0.0017297411142024718\n        wind: 0.030856854300239153\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010739454467849228\n        coal: 0.5299814475037016\n        gas: 0.004793216243180413\n        geothermal: 6.847324354980959e-05\n        hydro: 0.40151173475847596\n        hydro discharge: 0.00153711608754655\n        nuclear: 0.006836000979836344\n        oil: 8.047754403933617e-05\n        solar: 0.0004838050717408149\n        unknown: 0.0014085908848244148\n        wind: 0.05222424155141334\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008049784928441089\n        coal: 0.48456488779472867\n        gas: 0.06267581220321537\n        geothermal: 0.0008775489982885203\n        hydro: 0.30879220336481766\n        hydro discharge: 0.0030292192889958846\n        nuclear: 0.00942181318780328\n        oil: 0.00030101179322599423\n        solar: 0.02967799746874671\n        unknown: 0.011401202572390919\n        wind: 0.0812073317370202\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0032879012784574513\n        coal: 0.4381105607308502\n        gas: 0.03804574192748407\n        geothermal: 0.000584379840266285\n        hydro: 0.42986002693526426\n        hydro discharge: 0.006383657648346435\n        nuclear: 0.011060524069360814\n        oil: 0.0018680193549728103\n        solar: 0.0073297892699023875\n        unknown: 0.0035034479001890056\n        wind: 0.059964818588342725\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006110288242603766\n        coal: 0.4772048232892073\n        gas: 0.07504127516476422\n        geothermal: 0.0009835596348053983\n        hydro: 0.32239598468217817\n        hydro discharge: 0.00502436322924601\n        nuclear: 0.01553630706328073\n        oil: 0.00328016094089092\n        solar: 0.013629069150251808\n        unknown: 0.0067048464454354355\n        wind: 0.07408799032617241\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.6524788930484105e-08\n        biomass: 0.0038517441749623877\n        coal: 0.4599508511575991\n        gas: 0.028438101530406715\n        geothermal: 0.00033882433819938765\n        hydro: 0.42102866102248776\n        hydro discharge: 0.011397897423747382\n        nuclear: 0.0148580694021235\n        oil: 0.002157400338858157\n        solar: 0.00470261298547169\n        unknown: 0.002159008404187068\n        wind: 0.05111535046497391\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 5.975757652852559e-07\n        biomass: 0.007880042285881132\n        coal: 0.44580900443137933\n        gas: 0.07188227934921633\n        geothermal: 0.0015041692003238147\n        hydro: 0.3570482952154445\n        hydro discharge: 0.010369723380107441\n        nuclear: 0.02322687363298997\n        oil: 0.001645084665688161\n        solar: 0.014121937109883976\n        unknown: 0.005245002365897119\n        wind: 0.06126520397671881\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\ntimezone: Europe/Podgorica\nzone_name: Montenegro\n"
  },
  {
    "path": "config/zones/MG.yaml",
    "content": "bounding_box:\n  - - 43.22383223832239\n    - -25.584710075546695\n  - - 50.48510485104853\n    - -11.9436285117879\ncenter_point:\n  - 46.8079946111028\n  - -19.05016857783316\ncentroid:\n  - 47.02527388910254\n  - -17.62748621913637\ncountry: MG\ncountry_name: Madagascar\ncurrency: MGA\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Indian/Antananarivo\nzone_name: Madagascar\n"
  },
  {
    "path": "config/zones/MK.yaml",
    "content": "bounding_box:\n  - - 20.442804428044298\n    - 40.8490171960449\n  - - 23.00963009630098\n    - 42.36882716464663\ncenter_point:\n  - 21.724323687808077\n  - 41.593212096876016\ncentroid:\n  - 21.761443639720518\n  - 41.480223992543856\ncapacity:\n  biomass:\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 7.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 824.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 251.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 506.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 644.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 165.0\n  solar:\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 22.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 67.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 35.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 37.0\ncountry: MK\ncountry_name: North Macedonia\ncurrency: EUR\nemissionFactors:\n  direct: {}\n  lifecycle:\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0017925109549449913\n        coal: 0.5085706357746832\n        gas: 0.10677077511084236\n        geothermal: 8.955903735720778e-06\n        hydro: 0.25091375081801565\n        hydro discharge: 0.008707622314472065\n        nuclear: 0.08815379837729567\n        oil: 5.376277248125775e-05\n        solar: 0.010104459851096289\n        unknown: 0.002113953805239676\n        wind: 0.022808715123691918\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0021380348393398693\n        coal: 0.585985959328518\n        gas: 0.12519646713150492\n        geothermal: 4.6579101235585415e-05\n        hydro: 0.1542033616840566\n        hydro discharge: 0.005783717370746275\n        nuclear: 0.08810715189361547\n        oil: 4.5868763997498066e-05\n        solar: 0.01143414545719178\n        unknown: 0.001141400487018802\n        wind: 0.025916435680625256\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0016279888434563624\n        coal: 0.5152498969000772\n        gas: 0.11700911822080089\n        geothermal: 5.728168082690651e-05\n        hydro: 0.24179180933076866\n        hydro discharge: 0.0027594600005593365\n        nuclear: 0.09015845795957299\n        oil: 0.00016325227245251448\n        solar: 0.008152412390220964\n        unknown: 0.001278350259181442\n        wind: 0.021751809372201007\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0020711572665801253\n        coal: 0.5765435405808614\n        gas: 0.132372920000775\n        geothermal: 4.425396702381183e-05\n        hydro: 0.177560140274737\n        hydro discharge: 0.003645625714451785\n        nuclear: 0.07564704241179547\n        oil: 7.357216205219616e-05\n        solar: 0.00754755429833569\n        unknown: 0.002774293298200066\n        wind: 0.02171915292658826\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0030223645711199617\n        coal: 0.5327852390966615\n        gas: 0.14452110236846383\n        geothermal: 8.814084767180744e-05\n        hydro: 0.19311728256155541\n        hydro discharge: 0.005376222019080039\n        nuclear: 0.08212897992750005\n        oil: 0.00010584938435838958\n        solar: 0.00792500780291987\n        unknown: 0.0030112958224277546\n        wind: 0.02791794718329205\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002090520882539792\n        coal: 0.3961553658073497\n        gas: 0.24929921754273865\n        geothermal: 0.00015998534098630478\n        hydro: 0.18556444935827782\n        hydro discharge: 0.00266666637207234\n        nuclear: 0.09623840752912396\n        oil: 0.003710115058233197\n        solar: 0.017174613569574414\n        unknown: 0.0009979544842927462\n        wind: 0.04594202648785969\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0021727706797610535\n        coal: 0.480450362154064\n        gas: 0.16427491883065512\n        geothermal: 0.00012221437627917253\n        hydro: 0.147886580212612\n        hydro discharge: 0.0019232365389083932\n        nuclear: 0.09261424662521478\n        oil: 0.041729882765939044\n        solar: 0.023696735113227202\n        unknown: 0.00044394274611422386\n        wind: 0.04468416814267843\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0016444088909657753\n        coal: 0.4457710410975992\n        gas: 0.19414407475206896\n        geothermal: 5.55512103748395e-05\n        hydro: 0.1824306857322196\n        hydro discharge: 0.0016349044956779752\n        nuclear: 0.07054469491386146\n        oil: 0.038675823887515476\n        solar: 0.027671203365347962\n        unknown: 0.0004972561008812356\n        wind: 0.03692928432893524\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0013473637429946349\n        coal: 0.41491839260155566\n        gas: 0.24522353434134636\n        geothermal: 0.00011883778116263703\n        hydro: 0.17023873652174956\n        hydro discharge: 0.0033244944141131664\n        nuclear: 0.04888889669048293\n        oil: 0.0002289793090195852\n        solar: 0.05043191890490814\n        unknown: 0.0005426887479083481\n        wind: 0.06473512851109808\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\ntimezone: Europe/Skopje\nzone_name: North Macedonia\n"
  },
  {
    "path": "config/zones/ML.yaml",
    "content": "bounding_box:\n  - - -12.263522635226309\n    - 10.162308008919425\n  - - 4.268044213572687\n    - 24.995481572532512\ncenter_point:\n  - -3.9382750479327058\n  - 17.6355562617122\ncentroid:\n  - -5.194825934229126\n  - 14.039643699712057\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 320.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 460.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 460.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 470.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 480.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 490.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 510.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 610.0\ncountry: ML\ncountry_name: Mali\ncurrency: XOF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Bamako\nzone_name: Mali\n"
  },
  {
    "path": "config/zones/MM.yaml",
    "content": "bounding_box:\n  - - 92.18432184321844\n    - 9.987715903298508\n  - - 101.1592115921159\n    - 28.53884266693734\ncenter_point:\n  - 96.40290375955206\n  - 19.75868543584393\ncentroid:\n  - 96.90601844397696\n  - 19.148418582187293\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1400.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1730.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2100.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2730.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3040.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3260.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3270.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: MM\ncountry_name: Myanmar\ncurrency: MMK\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Yangon\nzone_name: Myanmar\n"
  },
  {
    "path": "config/zones/MN.yaml",
    "content": "bounding_box:\n  - - 87.80667806678068\n    - 41.59604243484914\n  - - 119.90459904599047\n    - 52.130243168255404\ncenter_point:\n  - 103.72665465197798\n  - 46.81891404665491\ncentroid:\n  - 103.29277632507599\n  - 47.64088239652732\ncapacity:\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 880.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 910.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 960.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1150.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\ncontributors:\n  - q--\n  - alixunderplatz\n  - MuffinCompiler\n  - consideRatio\ncountry: MN\ncountry_name: Mongolia\ncurrency: MNT\nemissionFactors:\n  direct:\n    unknown:\n      - _url: https://www.iea.org/fuels-and-technologies/electricity\n        datetime: '2020-01-01'\n        source: IEA 2020; assumes 92.85% coal, 5.78%% oil, 1.37% hydro in unknown\n        value: 729.1\n  lifecycle:\n    unknown:\n      - _url: https://www.iea.org/fuels-and-technologies/electricity\n        datetime: '2020-01-01'\n        source: IEA 2020; assumes 92.85% coal, 5.78%% oil, 1.37% hydro in unknown\n        value: 799.2\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0008970047023211626\n        gas: 0.00023905248863756158\n        geothermal: 0.0\n        hydro: 0.021838461260731995\n        hydro discharge: 0.0\n        nuclear: 6.232263775723864e-05\n        oil: 9.31594030933825e-06\n        solar: 0.025727593324883617\n        unknown: 0.8876911885022577\n        wind: 0.06354042950942215\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisLowCarbon:\n  unknown:\n    - _url: https://www.iea.org/fuels-and-technologies/electricity\n      datetime: '2020-01-01'\n      value: 0.0137\nisRenewable:\n  unknown:\n    - _url: https://www.iea.org/fuels-and-technologies/electricity\n      datetime: '2020-01-01'\n      value: 0.0137\nparsers:\n  consumption: MN.fetch_consumption\n  production: MN.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Ulaanbaatar\nzone_name: Mongolia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/MO.yaml",
    "content": "bounding_box:\n  - - 113.52779759582114\n    - 22.07645485902869\n  - - 113.63042179357811\n    - 22.21674764489182\ncenter_point:\n  - 113.57910969469962\n  - 22.146601251960256\ncentroid:\n  - 113.55852235156526\n  - 22.17149743747339\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\ncontributors:\n  - VIKTORVAV99\ncountry: MO\ncountry_name: Macao\ncurrency: MOP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Macau\nzone_name: Macao\n"
  },
  {
    "path": "config/zones/MQ.yaml",
    "content": "bounding_box:\n  - - -61.17001170011696\n    - 14.461280839126246\n  - - -60.81000810008095\n    - 14.876294860684169\ncenter_point:\n  - -60.990009900098954\n  - 14.668787849905208\ncentroid:\n  - -61.03741037410369\n  - 14.649468231660267\ncapacity:\n  battery storage:\n    - datetime: '2021-10-25'\n      source: opendata-martinique.edf.fr\n      value: 12.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: opendata-martinique.edf.fr\n      value: 8.0\n    - datetime: '2018-09-26'\n      source: opendata-martinique.edf.fr\n      value: 44.5\n  gas:\n    - datetime: '2021-01-01'\n      source: opendata-martinique.edf.fr\n      value: 0\n  geothermal:\n    - datetime: '2021-01-01'\n      source: opendata-martinique.edf.fr\n      value: 0\n  hydro:\n    - datetime: '2021-01-01'\n      source: opendata-martinique.edf.fr\n      value: 0\n  oil:\n    - datetime: '2017-01-01'\n      source: opendata-martinique.edf.fr\n      value: 428.0\n  solar:\n    - datetime: '2017-01-01'\n      source: null\n      value: 70.0\n    - datetime: '2020-01-01'\n      source: opendata-martinique.edf.fr\n      value: 79.0\n    - datetime: '2022-01-01'\n      source: opendata-martinique.edf.fr\n      value: 84.0\n  wind:\n    - datetime: '2019-01-14'\n      source: opendata-martinique.edf.fr\n      value: 14.0\ncontributors:\n  - PETILLON-Sebastien\n  - VIKTORVAV99\ncountry: MQ\ncountry_name: Martinique\ncurrency: EUR\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.018037581154105913\n        coal: 0.0\n        gas: 0.9293491860452057\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05180106897931069\n        unknown: 0.0\n        wind: 0.0008027475935538607\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.015855763567265684\n        coal: 0.0\n        gas: 0.9346625886042824\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.04902159431035597\n        unknown: 0.0\n        wind: 0.00045101715311000217\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05967459288642641\n        coal: 0.0\n        gas: 0.886303793757585\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.050158672766496736\n        unknown: 0.0\n        wind: 0.0038540488497428105\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1631953300607567\n        coal: 0.0\n        gas: 0.7549780567928813\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.051697067270874954\n        unknown: 0.0\n        wind: 0.03012954587548692\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.15125047240940298\n        coal: 0.0\n        gas: 0.768832000768264\n        geothermal: 0.0\n        hydro: 9.555521785338824e-06\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05221617533910009\n        unknown: 0.0\n        wind: 0.027691795961447635\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1689072850360248\n        coal: 0.0\n        gas: 0.7427632170828681\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05590676451155423\n        unknown: 0.0\n        wind: 0.0324227333695527\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.18470658572078466\n        coal: 0.0\n        gas: 0.7310544260016312\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.05736040412275236\n        unknown: 0.0\n        wind: 0.026878584154831818\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.13640136542248113\n        coal: 0.0\n        gas: 0.053188842396340204\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.8073994932839522\n        solar: 0.003008907522797206\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  price: FR_O.fetch_price\n  production: FR_O.fetch_production\nregion: Americas\ntimezone: Europe/Paris\nzone_name: Martinique\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/MR.yaml",
    "content": "bounding_box:\n  - - -17.080370803708007\n    - 14.73461766022129\n  - - -4.822248222482187\n    - 27.31536235784889\ncenter_point:\n  - -11.029922274992696\n  - 20.949763236203662\ncentroid:\n  - -13.251953353992638\n  - 18.658925825772442\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\ncountry: MR\ncountry_name: Mauritania\ncurrency: MRU\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Nouakchott\nzone_name: Mauritania\n"
  },
  {
    "path": "config/zones/MT.yaml",
    "content": "bounding_box:\n  - - 14.322743227432284\n    - 35.80158804420087\n  - - 14.549545495454964\n    - 35.97331798415587\ncenter_point:\n  - 14.436144361443624\n  - 35.88745301417837\ncentroid:\n  - 14.43995322316045\n  - 35.88166844223288\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 360.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: MT\ncountry_name: Malta\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 419.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1117.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1135.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Malta\nzone_name: Malta\n"
  },
  {
    "path": "config/zones/MU.yaml",
    "content": "bounding_box:\n  - - 57.37197371973721\n    - -20.50722818421054\n  - - 57.79677796777969\n    - -19.993469447178505\ncenter_point:\n  - 57.58437584375845\n  - -20.250348815694522\ncentroid:\n  - 57.569975699757\n  - -20.248202191445085\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 530.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 460.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\ncountry: MU\ncountry_name: Mauritius\ncurrency: MUR\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0962775649923246\n        coal: 0.31546804589565014\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0410783008152051\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.49293926960272944\n        solar: 0.04942187305033488\n        unknown: 0.0\n        wind: 0.004813870547433623\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.09627858643865023\n        coal: 0.3154755924220831\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.041067954331140674\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.49294075209359883\n        solar: 0.04942291741728504\n        unknown: 0.0\n        wind: 0.004813099721722564\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Indian/Mauritius\nzone_name: Mauritius\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/MV.yaml",
    "content": "bounding_box:\n  - - 73.07531291255368\n    - -0.702364251585757\n  - - 73.5538126436328\n    - 4.24016710592131\ncenter_point:\n  - 73.48630139921762\n  - 1.822984655278469\ncentroid:\n  - 73.37222347111515\n  - 1.4019136306608828\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 530.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncontributors:\n  - VIKTORVAV99\ncountry: MV\ncountry_name: Maldives\ncurrency: MVR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Indian/Maldives\nzone_name: Maldives\n"
  },
  {
    "path": "config/zones/MW.yaml",
    "content": "bounding_box:\n  - - 32.6757267572676\n    - -17.129872698428883\n  - - 35.9049590495905\n    - -9.407749731785735\ncenter_point:\n  - 34.17551417350189\n  - -13.353425614705001\ncentroid:\n  - 34.171465658318574\n  - -12.993116130752323\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 390.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\ncountry: MW\ncountry_name: Malawi\ncurrency: MWK\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Blantyre\nzone_name: Malawi\n"
  },
  {
    "path": "config/zones/MX.yaml",
    "content": "bounding_box:\n  - - -118.35658356583559\n    - 14.545714726270788\n  - - -86.74106741067405\n    - 32.713311290676785\ncenter_point:\n  - -101.83870131906288\n  - 23.864718112008\ncentroid:\n  - -103.84005941098609\n  - 24.40342302509869\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 870.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 880.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 890.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5380.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 34630.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 35870.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 38890.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 41300.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 42790.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 43620.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 44280.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 45050.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 12630.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 13080.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 13300.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 12840.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1610.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1070.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2770.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 6250.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 7160.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 8930.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 9360.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 10910.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 11990.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 18750.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 25240.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 26000.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 26190.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 40000.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 39930.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4180.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 6540.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 7000.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 7470.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 7630.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 7320.0\ncontributors:\n  - scriptator\n  - tuxity\n  - consideRatio\ncountry: MX\ncountry_name: Mexico\ncurrency: MXN\nemissionFactors:\n  direct:\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2% coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014 values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris\n        value: 305\n  lifecycle:\n    unknown:\n      - comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2% coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014 values.\n        datetime: '2020-01-01'\n        source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris\n        value: 411\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: CENACE.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\nsources:\n  IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris:\n    link: https://www.iea.org/data-and-statistics/charts/electricity-generation-mix-in-mexico-1-jan-30-sep-2019-and-2020\ntimezone: America/Mexico_City\nzone_name: Mexico\nisRenewable:\n  unknown:\n    comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2% coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014 values.\n    source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris\n    value: 0.205\nisLowCarbon:\n  unknown:\n    comment: Assumes a mix of 3.6% nuclear, 8.8% hydro, 8.4% oil, 63.4% gas, 4.2% coal, 4.3% solar, 5.9% wind, 1.5% other renewables with default IPCC 2014 values.\n    source: IEA, Electricity generation mix in Mexico, 1 Jan - 30 Sep, 2019 and 2020, IEA, Paris\n    value: 0.241\n"
  },
  {
    "path": "config/zones/MY-EM.yaml",
    "content": "bounding_box:\n  - - 109.52929529295292\n    - 0.851683097692529\n  - - 119.26739267392671\n    - 7.343074827991515\ncenter_point:\n  - 114.95590070053368\n  - 3.825095089397509\ncentroid:\n  - 114.85419187376294\n  - 3.8377512078982656\ncontributors:\n  - FelixDQ\ncountry: MY\ncountry_name: Malaysia\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022804945441936574\n        coal: 0.09418661349919273\n        gas: 0.37699350937835246\n        geothermal: 0.0\n        hydro: 0.465580200895034\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.02078299218741535\n        unknown: 0.01965390575053909\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022805388587531967\n        coal: 0.09418625486650706\n        gas: 0.37699343530599927\n        geothermal: 0.0\n        hydro: 0.4655801527961035\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.020783446545798098\n        unknown: 0.019653358093469513\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022805781185830046\n        coal: 0.09418593714117365\n        gas: 0.3769933696826919\n        geothermal: 0.0\n        hydro: 0.46558011018356626\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.020783849077899607\n        unknown: 0.019652872904773803\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022804273462351057\n        coal: 0.09418548250848827\n        gas: 0.37699262626097485\n        geothermal: 0.0\n        hydro: 0.46557922636597665\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.020782353892240597\n        unknown: 0.019652404231316332\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022804682975261305\n        coal: 0.0941852367688022\n        gas: 0.3769926087316251\n        geothermal: 0.0\n        hydro: 0.4655792355001515\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.020782771174053322\n        unknown: 0.01965374114013072\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02280505263019803\n        coal: 0.09418665477246599\n        gas: 0.37699259290841075\n        geothermal: 0.0\n        hydro: 0.46558088357075256\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.020783147841743718\n        unknown: 0.019653308101885626\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022805352314858973\n        coal: 0.09418623015829576\n        gas: 0.3769935527655242\n        geothermal: 0.0\n        hydro: 0.46558008691178554\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.02078345704997193\n        unknown: 0.01965288452366619\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02280565946423087\n        coal: 0.09418598398317375\n        gas: 0.37699349648537583\n        geothermal: 0.0\n        hydro: 0.46558005666999724\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.020782275643506914\n        unknown: 0.019652527923841243\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Asia\ntimezone: Asia/Kuala_Lumpur\nzone_name: Borneo\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/MY-WM.yaml",
    "content": "bounding_box:\n  - - 99.64359643596433\n    - 1.27099036774932\n  - - 104.29484294842948\n    - 6.701949718826185\ncenter_point:\n  - 102.27369841140032\n  - 3.742606580008735\ncentroid:\n  - 101.73300381445378\n  - 4.425161917753544\ncapacity:\n  coal: 12054\n  gas: 10114\n  hydro: 2160\n  solar: 729\ncontributors:\n  - kruschk\n  - systemcatch\n  - nessie2013\ncountry: MY\ncountry_name: Malaysia\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.537629454942522\n        gas: 0.3981806594897329\n        geothermal: 0.0\n        hydro: 0.05770777566482798\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0025736374311648063\n        solar: 0.0\n        unknown: 0.0039084672442364935\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5561588017943434\n        gas: 0.3999939852980534\n        geothermal: 0.0\n        hydro: 0.03901501077153826\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00033437833039713714\n        solar: 0.0002572683641030933\n        unknown: 0.004240541170555822\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5489750880876494\n        gas: 0.4101440049702471\n        geothermal: 0.0\n        hydro: 0.030445889562037594\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0006558218180270748\n        solar: 0.00497116572704363\n        unknown: 0.004808027374481493\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6478341112925606\n        gas: 0.29903635116697885\n        geothermal: 0.0\n        hydro: 0.04379570387629063\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00020983390466730356\n        solar: 0.006936399223663924\n        unknown: 0.002187608293729164\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5902573377228035\n        gas: 0.3428093048824919\n        geothermal: 0.0\n        hydro: 0.05467037837006277\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0010995711048544508\n        solar: 0.008800484946642841\n        unknown: 0.0023629264682509302\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5536194403916342\n        gas: 0.37104495593966696\n        geothermal: 0.0\n        hydro: 0.05206502706677329\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.006586486805512659\n        solar: 0.01234763362391835\n        unknown: 0.004336458927809604\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5689015636769541\n        gas: 0.36492212789845835\n        geothermal: 0.0\n        hydro: 0.04610068595301885\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0015658970825036035\n        solar: 0.015793804800565803\n        unknown: 0.0027159367257052268\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5641919244422988\n        gas: 0.3641893165402599\n        geothermal: 0.0\n        hydro: 0.04800986443503138\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0008625210800064971\n        solar: 0.021171527148129823\n        unknown: 0.001574858961476563\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: GSO.fetch_consumption\n  production: GSO.fetch_production\n  productionCapacity: MY_WM.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Kuala_Lumpur\nzone_name: Peninsula\n"
  },
  {
    "path": "config/zones/MY.yaml",
    "content": "bounding_box:\n  - - 99.64359643596433\n    - 0.851683097692529\n  - - 119.26739267392671\n    - 7.343074827991515\ncenter_point:\n  - 111.76221582194006\n  - 2.4672195703878406\ncentroid:\n  - 110.20276541887564\n  - 4.045986750545374\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 800.04\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 809.99\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 882.81\n    - datetime: '2020-01-01'\n      source: IRENA.org\n      value: 890.64\n    - datetime: '2021-01-01'\n      source: IRENA.org\n      value: 904.35\n  coal:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 10546.0\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 13170.0\n  gas:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 13839.95\n    - datetime: '2021-01-01'\n      source: IRENA.org\n      value: 15279.95\n    - datetime: '2022-01-01'\n      source: IRENA.org\n      value: 16121.95\n  hydro:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 6145.33\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 6165.33\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 6185.36\n    - datetime: '2020-01-01'\n      source: IRENA.org\n      value: 6197.36\n    - datetime: '2021-01-01'\n      source: IRENA.org\n      value: 6214.86\n  oil:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 370.3\n    - datetime: '2023-01-01'\n      source: IRENA.org\n      value: 1313.72\n  solar:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 393.96\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 545.26\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 893.76\n    - datetime: '2020-01-01'\n      source: IRENA.org\n      value: 1482.95\n    - datetime: '2021-01-01'\n      source: IRENA.org\n      value: 1787.1\n    - datetime: '2022-01-01'\n      source: IRENA.org\n      value: 1933.25\n  unknown:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 974.92\n    - datetime: '2023-01-01'\n      source: IRENA.org\n      value: 31.5\ncountry: MY\ncountry_name: Malaysia\ncurrency: MYR\ndisclaimer: This zone is partially using fully estimated data from MY-EM\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005661003345309563\n        coal: 0.4275369995420649\n        gas: 0.39292891353732784\n        geothermal: 0.0\n        hydro: 0.15896247101735414\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.001934824838111753\n        solar: 0.005159066994503822\n        unknown: 0.00781670611072085\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005776691633300244\n        coal: 0.4391249525314535\n        gas: 0.3941749865964774\n        geothermal: 0.0\n        hydro: 0.1470725345876711\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00024967834820161915\n        solar: 0.005456645718534151\n        unknown: 0.008144536136022649\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005922718158086157\n        coal: 0.43085082472743463\n        gas: 0.40154218852086876\n        geothermal: 0.0\n        hydro: 0.14345724305195873\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0004855021742446005\n        solar: 0.009078321026989364\n        unknown: 0.008663287725355838\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00636016222488809\n        coal: 0.49341517354401215\n        gas: 0.3207825283873505\n        geothermal: 0.0\n        hydro: 0.16143321001112665\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00015130391189839193\n        solar: 0.010798979035029962\n        unknown: 0.007058661860589683\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006558921094677964\n        coal: 0.447576263555627\n        gas: 0.3526410597052412\n        geothermal: 0.0\n        hydro: 0.17285687214608997\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0007833303550944976\n        solar: 0.012247843733914668\n        unknown: 0.0073356915270419085\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006618573636571874\n        coal: 0.42027307762519656\n        gas: 0.37277338469722965\n        geothermal: 0.0\n        hydro: 0.1720812812119634\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.004674823306158039\n        solar: 0.01479717155669829\n        unknown: 0.00878167210324847\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006728828141438\n        coal: 0.42882293147211514\n        gas: 0.36848729704390126\n        geothermal: 0.0\n        hydro: 0.16987623425489765\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0011038503434041434\n        solar: 0.01726751385734568\n        unknown: 0.0077133577376431225\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006677430415575312\n        coal: 0.42656264715151715\n        gas: 0.367942522281158\n        geothermal: 0.0\n        hydro: 0.1702800197861696\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0006099697246182323\n        solar: 0.02105938582460856\n        unknown: 0.006868112880627442\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: IRENA.fetch_production_capacity\nregion: Asia\nsubZoneNames:\n  - MY-WM\n  - MY-EM\ntimezone: Asia/Kuala_Lumpur\nzone_name: Malaysia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/MZ.yaml",
    "content": "bounding_box:\n  - - 30.213302133021358\n    - -26.85642468684171\n  - - 40.84420844208444\n    - -10.475337525172648\ncenter_point:\n  - 35.568162979898084\n  - -18.42016168090376\ncentroid:\n  - 35.21669624375571\n  - -17.531883501682522\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 410.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 660.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2190.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\ncountry: MZ\ncountry_name: Mozambique\ncurrency: MZN\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006391846142397455\n        coal: 0.0\n        gas: 0.1565248293372076\n        geothermal: 0.0\n        hydro: 0.8270095032266226\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.006442975204848462\n        solar: 0.003630665070320534\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006503774148449837\n        coal: 0.0\n        gas: 0.1575577949534047\n        geothermal: 0.0\n        hydro: 0.8259654510216987\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.006499783922426881\n        solar: 0.003473283673712482\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Maputo\nzone_name: Mozambique\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/NA.yaml",
    "content": "bounding_box:\n  - - 11.716317163171652\n    - -28.95920339566244\n  - - 25.259652596525996\n    - -16.95098734430909\ncenter_point:\n  - 16.36232295834883\n  - -22.92689159227441\ncentroid:\n  - 17.33432452315824\n  - -22.13859552069178\ncapacity:\n  coal: 120\n  hydro: 347\n  oil: 38\n  solar: 116\n  wind: 5\ncontributors:\n  - systemcatch\n  - jarek\n  - alixunderplatz\ncountry: NA\ncountry_name: Namibia\ncurrency: NAD\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.01803505384488233\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.8705440884693868\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00026907197874802605\n        solar: 0.09385330815488581\n        unknown: 0.0\n        wind: 0.01729765961938319\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.018176214280430668\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.7852276548720167\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0020082363810398013\n        solar: 0.17650734047230604\n        unknown: 0.0\n        wind: 0.018079403291716912\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Africa\ntimezone: Africa/Windhoek\nzone_name: Namibia\n"
  },
  {
    "path": "config/zones/NC.yaml",
    "content": "bounding_box:\n  - - 163.99063990639902\n    - -22.39625752371554\n  - - 168.13788137881377\n    - -20.08362766565488\ncenter_point:\n  - 165.90945909459091\n  - -21.377326546649208\ncentroid:\n  - 166.170361703617\n  - -21.211440194928787\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 440.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 640.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\ncountry: NC\ncountry_name: New Caledonia\ncurrency: XPF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Noumea\nzone_name: New Caledonia\n"
  },
  {
    "path": "config/zones/NE.yaml",
    "content": "bounding_box:\n  - - 0.153001530015331\n    - 11.696428805850758\n  - - 15.993037117916646\n    - 23.517173006086566\ncenter_point:\n  - 8.056598587736607\n  - 17.815544783954977\ncentroid:\n  - 7.178354807547548\n  - 15.189819495990177\ncapacity:\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 290.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 390.0\ncountry: NE\ncountry_name: Niger\ncurrency: XOF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Niamey\nzone_name: Niger\n"
  },
  {
    "path": "config/zones/NG.yaml",
    "content": "bounding_box:\n  - - 2.673026730267338\n    - 4.28055756546069\n  - - 14.668346683466865\n    - 13.873105794780372\ncenter_point:\n  - 8.64236105086071\n  - 9.06731066802872\ncentroid:\n  - 8.340337640664574\n  - 9.28808618747054\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10180.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10760.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10870.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 11000.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 11290.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 11340.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 11910.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2110.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2860.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\ncontributors:\n  - byronwilliams\n  - kruschk\n  - nessie2013\n  - silimotion\ncountry: NG\ncountry_name: Nigeria\ncurrency: NGN\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.7589794653377564\n        geothermal: 0.0\n        hydro: 0.24102053466224352\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.7469113807811417\n        geothermal: 0.0\n        hydro: 0.2530886192188585\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.7589681476151471\n        geothermal: 0.0\n        hydro: 0.2410318523848529\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.7515682967255825\n        geothermal: 0.0\n        hydro: 0.24843170327441758\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: NG.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Lagos\nzone_name: Nigeria\n"
  },
  {
    "path": "config/zones/NI.yaml",
    "content": "bounding_box:\n  - - -87.64827648276477\n    - 10.717568148107262\n  - - -83.13023130231296\n    - 15.030851806643668\ncenter_point:\n  - -85.20004029841722\n  - 12.915995902894023\ncentroid:\n  - -84.90224902249018\n  - 12.832867584423333\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 600.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 620.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\ncontributors:\n  - corradio\n  - systemcatch\n  - jarek\ncountry: NI\ncountry_name: Nicaragua\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.15740168150430836\n        coal: 0.0012825029623507783\n        gas: 0.0012825029623507783\n        geothermal: 0.16421381680433098\n        hydro: 0.19142518400551273\n        hydro discharge: 0.0\n        nuclear: 0.0012825029623507783\n        oil: 0.3254839175700778\n        solar: 0.004895350981291831\n        unknown: 0.0\n        wind: 0.15271465980856747\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.15740182841440722\n        coal: 0.001282504159368721\n        gas: 0.001282504159368721\n        geothermal: 0.1642139700725034\n        hydro: 0.19142536267128324\n        hydro discharge: 0.0\n        nuclear: 0.001282504159368721\n        oil: 0.32548422135891947\n        solar: 0.004894424506697263\n        unknown: 0.0\n        wind: 0.15271480234405727\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03218070499558109\n        coal: 0.00022395822795012\n        gas: 1.0758319411707935e-06\n        geothermal: 0.0847919689127955\n        hydro: 0.6059044652947044\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.21657026073444063\n        solar: 0.0023625302496715376\n        unknown: 0.002343851999422419\n        wind: 0.05562029971945963\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.10386291708430231\n        coal: 0.0004769852956415748\n        gas: 3.1276305974275812e-06\n        geothermal: 0.1701197792107363\n        hydro: 0.15884417991659103\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.37548482113502385\n        solar: 0.004730768388714839\n        unknown: 0.009674816959096303\n        wind: 0.17680050847746434\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.13284131305441957\n        coal: 0.002653986180100358\n        gas: 2.3998571855576485e-06\n        geothermal: 0.17249536208298571\n        hydro: 0.0840275098540772\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4138613536463716\n        solar: 0.0072711349450261\n        unknown: 0.027713339026715113\n        wind: 0.15913296830255616\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.11548791949118146\n        coal: 0.0020293464027453735\n        gas: 5.482586253552205e-05\n        geothermal: 0.1867303319845882\n        hydro: 0.27271942066307747\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.22153664389537786\n        solar: 0.004901426440313182\n        unknown: 0.05710003338142398\n        wind: 0.13943951537522936\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.12788394090025143\n        coal: 0.0020242947368517288\n        gas: 0.001055034713907661\n        geothermal: 0.17120120445149872\n        hydro: 0.291270583785474\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.22692722667899734\n        solar: 0.0045443904456875\n        unknown: 0.021821153561803665\n        wind: 0.1532716073153324\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.11566804363215112\n        coal: 0.001443377768950069\n        gas: 0.0002542485062434884\n        geothermal: 0.1495978322862986\n        hydro: 0.24483530331102016\n        hydro discharge: 0.0\n        nuclear: 5.552578037783488e-06\n        oil: 0.26988329840743425\n        solar: 0.004166527268651353\n        unknown: 0.09464817620122822\n        wind: 0.11949734220054986\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1342579952162413\n        coal: 0.009217063016496347\n        gas: 0.00019090349487930707\n        geothermal: 0.14421244673501518\n        hydro: 0.12871229436943246\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.42992534483857736\n        solar: 0.014719869046634181\n        unknown: 0.008594035720583669\n        wind: 0.1301696510646443\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.14313396992757216\n        coal: 0.0028705058094539875\n        gas: 2.5033967395602494e-05\n        geothermal: 0.15110165967611594\n        hydro: 0.16899569302693632\n        hydro discharge: 0.0\n        nuclear: 2.4491081750141027e-08\n        oil: 0.40724358111911807\n        solar: 0.011695191572445699\n        unknown: 4.012659652412689e-05\n        wind: 0.11489319131069319\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  price: NI.fetch_price\n  production: NI.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Managua\nzone_name: Nicaragua\ncurrency: USD\n"
  },
  {
    "path": "config/zones/NL.yaml",
    "content": "bounding_box:\n  - - 3.349833498335016\n    - 50.74924823445062\n  - - 7.194671946719495\n    - 53.46115020290665\ncenter_point:\n  - 5.942345089242051\n  - 52.31811804349822\ncentroid:\n  - 5.1619093032813215\n  - 51.90639365146702\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1164.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1172.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1243.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1280.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1340.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1335.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1201.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1088.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4608.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 4631.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 4662.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 4012.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 4006.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 4012.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 19297.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 18433.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 15570.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 15496.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 18500.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 18530.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 18351.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 18718.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 37.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 38.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 37.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 38.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 37.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 38.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 486.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 485.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 486.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2911.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 2584.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 7226.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 11108.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 14823.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 14911.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 22590.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 24261.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 27259.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4202.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 4632.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4484.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 6648.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 7674.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 7770.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 9410.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 10790.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 11706.0\ncontributors:\n  - corradio\n  - PaulCornelissen\n  - nessie2013\n  - VIKTORVAV99\ncountry: NL\ncountry_name: Netherlands\ncurrency: EUR\ndisclaimer: Solar production is collected from NED.nl and can contain their own estimations.\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0.0\n    coal:\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 781.71\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 752.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 402.3363923\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 401.09\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 379.19\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 358.31\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 841.71\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 812.41\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 522.3363922999999\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 521.0899999999999\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 499.19\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 478.31\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 36.5\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.023504727838821585\n        coal: 0.260849511137503\n        gas: 0.23162716587852436\n        geothermal: 4.174416927459995e-05\n        hydro: 0.052004098647775575\n        hydro discharge: 0.002489857025228999\n        nuclear: 0.06765508415590223\n        oil: 0.0006671760796863028\n        solar: 0.013314183782546838\n        unknown: 0.30518069870201564\n        wind: 0.042665739438717286\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.020066962191209885\n        coal: 0.2895318999761416\n        gas: 0.271483904229351\n        geothermal: 3.67963115037262e-05\n        hydro: 0.03626464462221321\n        hydro discharge: 0.001741945189944852\n        nuclear: 0.056911561078219784\n        oil: 0.0003994579250406276\n        solar: 0.02220679422296801\n        unknown: 0.26543238395471785\n        wind: 0.03592364544585461\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.017035708097567843\n        coal: 0.23058998032761252\n        gas: 0.27541181484912985\n        geothermal: 3.088117041144466e-05\n        hydro: 0.03684916619722084\n        hydro discharge: 0.0014283590461348229\n        nuclear: 0.044778610031970346\n        oil: 0.0003798630967996943\n        solar: 0.02457735836528646\n        unknown: 0.27051454584168244\n        wind: 0.09840371666530828\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.028477536722064514\n        coal: 0.29532245085431286\n        gas: 0.36539903746634045\n        geothermal: 5.750975726474563e-05\n        hydro: 0.04134571772463802\n        hydro discharge: 0.0030159518432356443\n        nuclear: 0.06629369544660633\n        oil: 0.0009200768013634042\n        solar: 0.05054488036362917\n        unknown: 0.007648601047700721\n        wind: 0.14097454416961172\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0326021732723815\n        coal: 0.18311901381075105\n        gas: 0.46039204099387027\n        geothermal: 3.181607134367278e-05\n        hydro: 0.026117101539680602\n        hydro discharge: 0.001593049132739033\n        nuclear: 0.07505058920419061\n        oil: 0.0007003022642383256\n        solar: 0.06573836956792237\n        unknown: 0.008218302228841883\n        wind: 0.14643723980145107\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03770303012272856\n        coal: 0.12288033278141416\n        gas: 0.47453557169192156\n        geothermal: 2.5760781647221165e-05\n        hydro: 0.04443270953473291\n        hydro discharge: 0.0022477597707108144\n        nuclear: 0.05354004800921138\n        oil: 0.0004759276493644122\n        solar: 0.08702293326946153\n        unknown: 0.007333931652575619\n        wind: 0.16980198630281435\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0777042511821147\n        coal: 0.121185740837749\n        gas: 0.4434116221295523\n        geothermal: 1.7874229282024673e-05\n        hydro: 0.0291889583578759\n        hydro discharge: 0.003059789472039805\n        nuclear: 0.048522115895081624\n        oil: 0.00036579272822891227\n        solar: 0.09473053946573527\n        unknown: 0.020138390130161596\n        wind: 0.1616749111685565\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07025045035644747\n        coal: 0.1224512272081736\n        gas: 0.3860479360860906\n        geothermal: 1.3260648277397828e-05\n        hydro: 0.015580515646937531\n        hydro discharge: 0.0010361555978039986\n        nuclear: 0.045594964507815895\n        oil: 0.0002527331386378342\n        solar: 0.14332606937757839\n        unknown: 0.020954180762785355\n        wind: 0.1944924983806649\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.3098323041776004e-09\n        biomass: 0.055764161071383975\n        coal: 0.06951473119041207\n        gas: 0.3655548688116137\n        geothermal: 1.6092068624981302e-05\n        hydro: 0.025380932461973905\n        hydro discharge: 0.001341955000598989\n        nuclear: 0.04129926553992152\n        oil: 0.000312841199766102\n        solar: 0.16304723451557027\n        unknown: 0.017708957812043718\n        wind: 0.2600589492231277\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.082491525579194e-07\n        biomass: 0.04885965980728353\n        coal: 0.06170402220815202\n        gas: 0.3416571777655653\n        geothermal: 1.8549619757891096e-05\n        hydro: 0.030599419617910406\n        hydro discharge: 0.0016239415326786415\n        nuclear: 0.038063059672236305\n        oil: 0.00039676277208588854\n        solar: 0.1855771978122889\n        unknown: 0.01600895762532292\n        wind: 0.275490914569801\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: NED.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: NED.fetch_production_forecast\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Amsterdam\nzone_name: Netherlands\n"
  },
  {
    "path": "config/zones/NO-NO1.yaml",
    "content": "bounding_box:\n  - - 8.109081090810946\n    - 58.896402802482385\n  - - 12.872743374997839\n    - 62.628666830837716\ncenter_point:\n  - 10.436945085082657\n  - 61.02281488314449\ncentroid:\n  - 11.128606398302905\n  - 60.2622039006174\ncapacity:\n  biomass:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 33.61\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 33.7\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 5.6\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 6.6\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 3558.39\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 3724.9100000000003\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 3883.3999999999996\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 3934.09\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 3933.5299999999997\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 3955.81\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 4000.8999999999996\n  solar:\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 9.07\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 16.7\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 111.6\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 165.6\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 221.5\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 384.7\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 405.7\ncountry: 'NO'\ncountry_name: Norway\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0.0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: EIA 2020/BEIS 2021; IPCC 2014\n      value: 650.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0003698518435261177\n        coal: 0.001706292282625254\n        gas: 0.011121394726468966\n        geothermal: 2.850256323791473e-07\n        hydro: 0.95075808874137\n        hydro discharge: 7.485151538622876e-06\n        nuclear: 0.018004812704355905\n        oil: 2.5758928726024836e-05\n        solar: 0.00030536426859985446\n        unknown: 0.003598138955017522\n        wind: 0.014102404231455097\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0006091120153680662\n        coal: 0.0028487877970473077\n        gas: 0.011410674222347655\n        geothermal: 9.591336899926512e-07\n        hydro: 0.9531424061009769\n        hydro discharge: 1.2197963079787459e-05\n        nuclear: 0.013842856186425629\n        oil: 3.3884747463243145e-05\n        solar: 0.00038074543167820104\n        unknown: 0.0034450678126587285\n        wind: 0.014273166794594757\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0014287438869453866\n        coal: 0.0018176506159486379\n        gas: 0.012049869498112476\n        geothermal: 9.63608322966253e-07\n        hydro: 0.927518684284436\n        hydro discharge: 1.394381647357198e-05\n        nuclear: 0.02948809034284649\n        oil: 0.0002416448506263541\n        solar: 0.0005331734514699057\n        unknown: 0.0051107723737893965\n        wind: 0.021796375544481425\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0016414730927959888\n        coal: 0.003880852870468317\n        gas: 0.01206092897442633\n        geothermal: 1.5538974701783807e-06\n        hydro: 0.9141196172562519\n        hydro discharge: 2.505962735772071e-05\n        nuclear: 0.03201378470601001\n        oil: 5.3192059411345575e-05\n        solar: 0.0007281378951052874\n        unknown: 0.00804903984259292\n        wind: 0.02742627547090668\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0018503326334677397\n        coal: 0.004068688972934016\n        gas: 0.014896899221554639\n        geothermal: 1.7248806608233373e-06\n        hydro: 0.858747820754413\n        hydro discharge: 2.451076969542843e-05\n        nuclear: 0.060399066895146035\n        oil: 0.00010264677211124205\n        solar: 0.0014023055871061204\n        unknown: 0.007299240156819544\n        wind: 0.05120665140537523\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0019167985702378348\n        coal: 0.0005272100445228915\n        gas: 0.00848466983530662\n        geothermal: 6.457300720133989e-07\n        hydro: 0.9083458329001869\n        hydro discharge: 0.01666014888051933\n        nuclear: 0.02000261102132487\n        oil: 1.8247602524772442e-05\n        solar: 0.0005004233798114392\n        unknown: 0.0027288375356259945\n        wind: 0.0408145344846104\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0033569952800068803\n        coal: 0.0024299214169089456\n        gas: 0.007534333161624685\n        geothermal: 3.0162929235683804e-06\n        hydro: 0.869839899669695\n        hydro discharge: 0.03259472203064946\n        nuclear: 0.027394596124533602\n        oil: 6.951681102099335e-05\n        solar: 0.0013982596084731857\n        unknown: 0.005167343769069182\n        wind: 0.05021130759395834\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004101106651193859\n        coal: 0.0031280623844478815\n        gas: 0.005360530375076971\n        geothermal: 3.824669717335912e-06\n        hydro: 0.8189755840963592\n        hydro discharge: 0.008958677400884546\n        nuclear: 0.058219469993101944\n        oil: 8.19895679463783e-05\n        solar: 0.0024687144661906545\n        unknown: 0.007575096285313371\n        wind: 0.09112681996046612\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005243828005976455\n        coal: 0.0023447889560945455\n        gas: 0.003382525210681411\n        geothermal: 4.632918570215509e-06\n        hydro: 0.8353362783803635\n        hydro discharge: 0.012051835103475404\n        nuclear: 0.04966436436325913\n        oil: 0.00011864854845221475\n        solar: 0.002207097836553305\n        unknown: 0.006172302924157986\n        wind: 0.08347361949365624\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.4449237324215755e-09\n        biomass: 0.005204035580781067\n        coal: 0.001200542914602875\n        gas: 0.0031159416168890703\n        geothermal: 2.3740096923686487e-06\n        hydro: 0.8369449207323263\n        hydro discharge: 0.012946899547286407\n        nuclear: 0.05205816564875175\n        oil: 7.782272527398661e-05\n        solar: 0.0033313057652980278\n        unknown: 0.004530321106530987\n        wind: 0.08058754580014128\nhas_day_ahead_price_license: True\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: Europe/Oslo\nzone_name: Eastern Norway\n"
  },
  {
    "path": "config/zones/NO-NO2.yaml",
    "content": "bounding_box:\n  - - 5.167851678516797\n    - 58.01771794304598\n  - - 10.481504815048169\n    - 60.23017200279955\ncenter_point:\n  - 7.826481495335166\n  - 59.12044289080393\ncentroid:\n  - 6.884960944083798\n  - 59.23982941226397\ncapacity:\n  biomass:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 21.87\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 21.9\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 5.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 8.7\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 22.7\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 23.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 10110.68\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 10849.11\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 11018.449999999999\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 11042.74\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 11197.23\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 11202.560000000001\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 11225.48\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 11386.5\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 520.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 522.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 339.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 574.6\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 933.15\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1087.25\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1444.15\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1447.35\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1452.4\ncountry: 'NO'\ncountry_name: Norway\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0.0\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 48.32\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 5.75\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 72.32\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 29.75\n    oil:\n      datetime: '2014-01-01'\n      source: EIA 2020/BEIS 2021; IPCC 2014\n      value: 650.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0014016391519342366\n        coal: 0.005636085176702246\n        gas: 0.0028305017223367126\n        geothermal: 1.3176659713496978e-06\n        hydro: 0.9501925011096608\n        hydro discharge: 2.3139405001624644e-05\n        nuclear: 0.002440416127392211\n        oil: 9.148084462649126e-05\n        solar: 0.000414703166923486\n        unknown: 0.002665286103587044\n        wind: 0.03430284496380874\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001806950609360046\n        coal: 0.007889374376759217\n        gas: 0.0041445813571164575\n        geothermal: 2.949414926865057e-06\n        hydro: 0.9470743503199226\n        hydro discharge: 3.614014197535103e-05\n        nuclear: 0.0018337911478406427\n        oil: 9.588450809981063e-05\n        solar: 0.0007126528338973025\n        unknown: 0.0026983306414196653\n        wind: 0.03370480709271806\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005028003708025002\n        coal: 0.006218804412774124\n        gas: 0.004049006285343854\n        geothermal: 3.347861135245278e-06\n        hydro: 0.9246969708128215\n        hydro discharge: 3.946867901724925e-05\n        nuclear: 0.002548133371236703\n        oil: 0.0010402361775853962\n        solar: 0.0011930902242650134\n        unknown: 0.00664665556652238\n        wind: 0.04853617572033554\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004560936178693815\n        coal: 0.010845213596739485\n        gas: 0.006654479718719073\n        geothermal: 4.855966509203015e-06\n        hydro: 0.9007737648276934\n        hydro discharge: 7.038230413221327e-05\n        nuclear: 0.004254864644942774\n        oil: 0.00016614573521264627\n        solar: 0.0017948359785402285\n        unknown: 0.010670822690705099\n        wind: 0.060203689934690705\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0072755334728611554\n        coal: 0.015046755683726121\n        gas: 0.020284414633137265\n        geothermal: 7.292800425572996e-06\n        hydro: 0.8486603420605724\n        hydro discharge: 9.276296933766324e-05\n        nuclear: 0.010066027937635195\n        oil: 0.0004374128418797716\n        solar: 0.004091494368455699\n        unknown: 0.00152082530961674\n        wind: 0.0925171381994662\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002005613794991704\n        coal: 0.0018984984955813325\n        gas: 0.002262555365659837\n        geothermal: 2.2202872039008657e-06\n        hydro: 0.89321446069303\n        hydro discharge: 0.020392355271099248\n        nuclear: 0.0011603804471560376\n        oil: 6.66894228569823e-05\n        solar: 0.0009276019898797464\n        unknown: 0.000654686174074608\n        wind: 0.07741490036673222\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005826000189154672\n        coal: 0.007744433846975755\n        gas: 0.005900457407384369\n        geothermal: 1.0164177666734585e-05\n        hydro: 0.8066264376712622\n        hydro discharge: 0.06768840123511373\n        nuclear: 0.005991964717964482\n        oil: 0.00024248618954621963\n        solar: 0.0049652080900275675\n        unknown: 0.0007803077845418923\n        wind: 0.09422406031326465\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011122725770961177\n        coal: 0.015501044831442623\n        gas: 0.020649155424674836\n        geothermal: 1.823258781250292e-05\n        hydro: 0.7484733932869989\n        hydro discharge: 0.012652738011923983\n        nuclear: 0.01624249723530086\n        oil: 0.00041697994049120384\n        solar: 0.013875710116230868\n        unknown: 0.0015202246445246402\n        wind: 0.15952726418410515\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.0764603850609404e-09\n        biomass: 0.007968054767850064\n        coal: 0.008013492160703484\n        gas: 0.00890386564634423\n        geothermal: 1.53201842001873e-05\n        hydro: 0.8066596053287444\n        hydro discharge: 0.011298584715769845\n        nuclear: 0.006809331549277861\n        oil: 0.0004043968331219024\n        solar: 0.012434270067411166\n        unknown: 0.0009040348443875527\n        wind: 0.13658894567517932\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 4.1337925632898785e-08\n        biomass: 0.005970302378487454\n        coal: 0.004461654368724378\n        gas: 0.010274478133306642\n        geothermal: 1.0395722779532695e-05\n        hydro: 0.8209718925451418\n        hydro discharge: 0.017585613640037096\n        nuclear: 0.010013266588128539\n        oil: 0.00031219957989485906\n        solar: 0.014173657554839382\n        unknown: 0.0009148912252796965\n        wind: 0.11531147882892007\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 0.9094\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.9887\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 0.8814\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.9726\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: Europe/Oslo\nzone_name: Southern Norway\n"
  },
  {
    "path": "config/zones/NO-NO3.yaml",
    "content": "bounding_box:\n  - - 4.915849158491596\n    - 60.961455330441254\n  - - 12.925676145774485\n    - 64.95274535156204\ncenter_point:\n  - 8.682747834267172\n  - 62.25785497399018\ncentroid:\n  - 8.687952888048368\n  - 63.11307283188927\ncapacity:\n  biomass:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 4.2\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 18.84\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 19.4\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 180.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4003.33\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 4475.65\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4570.37\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 4699.97\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 4851.26\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 4854.35\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 4815.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 4921.5\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 52.7\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 60.3\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 60.2\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 53.459999999999994\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 53.4\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 355.95\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 319.6\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 508.6\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1902.3\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2125.6\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2120.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 2120.4\ncountry: 'NO'\ncountry_name: Norway\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0.0\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 7.68\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 31.68\n    oil:\n      datetime: '2014-01-01'\n      source: EIA 2020/BEIS 2021; IPCC 2014\n      value: 650.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.620170800689298e-05\n        coal: 0.0002718565437094246\n        gas: 0.026779493221630285\n        geothermal: 0.0\n        hydro: 0.880547842975805\n        hydro discharge: 1.4067168038315273e-06\n        nuclear: 0.005986358438875013\n        oil: 3.829549281943457e-06\n        solar: 9.296767497856335e-05\n        unknown: 0.005270690574003915\n        wind: 0.08095880907174827\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.098251643413076e-05\n        coal: 0.00032205915315516523\n        gas: 0.02198881057766156\n        geothermal: 2.8972290222171775e-08\n        hydro: 0.9120144471174516\n        hydro discharge: 9.330664974291211e-07\n        nuclear: 0.0042031208722424045\n        oil: 3.6259019653391966e-06\n        solar: 7.273513304310624e-05\n        unknown: 0.0075467450201856055\n        wind: 0.053755988183445846\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.79775826645126e-05\n        coal: 9.329349991868588e-05\n        gas: 0.020093306090290957\n        geothermal: 6.179323814901182e-09\n        hydro: 0.9281269113541666\n        hydro discharge: 3.9045602355406843e-07\n        nuclear: 0.0008367978516901031\n        oil: 6.287461981661953e-06\n        solar: 3.0374466212146763e-05\n        unknown: 0.0018492004999675449\n        wind: 0.048895327881622326\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00014609595923795255\n        coal: 0.0003103402994691391\n        gas: 0.023466154297544502\n        geothermal: 2.5968894059472273e-08\n        hydro: 0.9018167592160906\n        hydro discharge: 1.0724765651128323e-06\n        nuclear: 0.0017612038059910359\n        oil: 3.0930115611132646e-06\n        solar: 7.108383975858261e-05\n        unknown: 0.015063263588319263\n        wind: 0.05736074009534123\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 7.901777360820838e-05\n        coal: 0.00013288607521434222\n        gas: 0.022561187863566083\n        geothermal: 9.48893450123549e-09\n        hydro: 0.8826974614808063\n        hydro discharge: 1.2107880423576487e-07\n        nuclear: 0.001567985317590977\n        oil: 2.196878115726041e-06\n        solar: 6.105825705640998e-05\n        unknown: 0.005508822559462927\n        wind: 0.08738904447028134\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000572896710959504\n        coal: 3.251600779786519e-05\n        gas: 0.010476434226755423\n        geothermal: 1.2027877116327438e-08\n        hydro: 0.8307160064221089\n        hydro discharge: 0.010521883306421623\n        nuclear: 0.0003316481476928204\n        oil: 6.751131026583787e-07\n        solar: 3.65057710361618e-05\n        unknown: 0.008534748804124343\n        wind: 0.13877648606003828\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0008820125043063828\n        coal: 3.105604144738829e-05\n        gas: 0.0003968745015182057\n        geothermal: 2.805458045468869e-08\n        hydro: 0.801833126776493\n        hydro discharge: 0.02522919683300985\n        nuclear: 0.0001984937390359643\n        oil: 9.326252421423538e-07\n        solar: 2.7556042977689836e-05\n        unknown: 0.00617144130079909\n        wind: 0.1652291458570789\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0007430812321280147\n        coal: 9.607995695670895e-06\n        gas: 0.00528418907500024\n        geothermal: 3.678264881004133e-10\n        hydro: 0.769542552713135\n        hydro discharge: 0.0064540340012434845\n        nuclear: 7.680437767429489e-05\n        oil: 1.1733664970403184e-07\n        solar: 9.497647749240771e-06\n        unknown: 0.005163299221421157\n        wind: 0.21271676527142142\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00034835008209747285\n        coal: 4.2038992457815873e-05\n        gas: 0.007855474459098382\n        geothermal: 2.6949706252790576e-08\n        hydro: 0.7601083985215286\n        hydro discharge: 0.005698045588219242\n        nuclear: 0.0006257317546304181\n        oil: 8.376260051543018e-07\n        solar: 0.00012735375037931896\n        unknown: 0.0075760293131109996\n        wind: 0.21761760916997872\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0007081639504655081\n        coal: 4.465689001285313e-05\n        gas: 0.007715427171405802\n        geothermal: 4.04199493087621e-08\n        hydro: 0.7369577416362177\n        hydro discharge: 0.0052390560531645185\n        nuclear: 0.0011090704696297975\n        oil: 1.2322719059175703e-06\n        solar: 0.0003611325736471347\n        unknown: 0.00822168167101805\n        wind: 0.23964172535285017\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.9841\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.9834\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: Europe/Oslo\nzone_name: Central Norway\n"
  },
  {
    "path": "config/zones/NO-NO4.yaml",
    "content": "bounding_box:\n  - - 11.561515615156168\n    - 64.00790244344049\n  - - 31.07731077310774\n    - 71.16078268093528\ncenter_point:\n  - 19.203395969873394\n  - 68.8673186911011\ncentroid:\n  - 20.002831855688445\n  - 68.81589156318717\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 270.2\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 252.44\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 256.4\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 5104.429999999999\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 5272.389999999999\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 5304.209999999999\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 5344.879999999999\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 5473.23\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 5487.150000000001\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 5593.219999999999\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 5636.5\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 77.28\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 77.3\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 208.65\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 226.05\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 654.45\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1150.75\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1159.95\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1160.1\ncountry: 'NO'\ncountry_name: Norway\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0.0\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    oil:\n      datetime: '2014-01-01'\n      source: EIA 2020/BEIS 2021; IPCC 2014\n      value: 650.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00030906521212729145\n        coal: 0.0004954836472521979\n        gas: 0.07487135437383471\n        geothermal: 0.0\n        hydro: 0.8627617094211997\n        hydro discharge: 1.3473375383031595e-06\n        nuclear: 0.013145688232457908\n        oil: 3.570605001229938e-06\n        solar: 2.6646034444964556e-05\n        unknown: 0.015295751604329198\n        wind: 0.03308956974049746\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0001759200306635756\n        coal: 0.0003431408087764014\n        gas: 0.07157172507807726\n        geothermal: 0.0\n        hydro: 0.895430460891778\n        hydro discharge: 3.1400091241426815e-07\n        nuclear: 0.004018669823432022\n        oil: 1.0633212715846808e-06\n        solar: 8.054429248470537e-06\n        unknown: 0.0028894593344144376\n        wind: 0.02556101081336615\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00015198075659689269\n        coal: 0.0002481714754414646\n        gas: 0.05873594805634324\n        geothermal: 0.0\n        hydro: 0.9106964290196109\n        hydro discharge: 0.0\n        nuclear: 0.0005870507891004019\n        oil: 3.038141785586984e-07\n        solar: 5.743510516063688e-06\n        unknown: 0.0012006319735257793\n        wind: 0.02837359276200133\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0003070817610382767\n        coal: 0.0005191961547785951\n        gas: 0.06419593685697327\n        geothermal: 0.0\n        hydro: 0.885602664944183\n        hydro discharge: 3.4842372982678064e-09\n        nuclear: 0.0012853421078055903\n        oil: 4.897842144993601e-07\n        solar: 1.4364514884387232e-05\n        unknown: 0.003776901783114036\n        wind: 0.04429785435186965\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0002904371086460318\n        coal: 0.0004301799608317099\n        gas: 0.06587528929160398\n        geothermal: 0.0\n        hydro: 0.8828139977371126\n        hydro discharge: 0.0\n        nuclear: 0.0013755518698951711\n        oil: 4.810760647049809e-07\n        solar: 1.2932124703130168e-05\n        unknown: 0.0014275470633277844\n        wind: 0.04777329707109834\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00013508222487813347\n        coal: 0.00015627966156186925\n        gas: 0.04615699602289525\n        geothermal: 0.0\n        hydro: 0.8657785646657983\n        hydro discharge: 2.6669746762615308e-05\n        nuclear: 0.0006233745365541501\n        oil: 2.925432088350262e-07\n        solar: 1.8243334299056866e-05\n        unknown: 0.0053249718332522965\n        wind: 0.08177931783660669\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 7.196620234449039e-05\n        coal: 6.961434483311065e-05\n        gas: 0.0008459477936284631\n        geothermal: 0.0\n        hydro: 0.9041136791296683\n        hydro discharge: 7.307386507573657e-06\n        nuclear: 0.0002701283930972016\n        oil: 2.3747013950457472e-07\n        solar: 4.0162735003458277e-07\n        unknown: 0.009493624268615674\n        wind: 0.08512696428931002\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.903160021494866e-05\n        coal: 3.5378099385842735e-05\n        gas: 0.03133099596936502\n        geothermal: 0.0\n        hydro: 0.8683090855845057\n        hydro discharge: 1.3904162305699234e-07\n        nuclear: 0.00014477139753746286\n        oil: 2.528910356646342e-07\n        solar: 3.3839921151675656e-06\n        unknown: 0.009479892257082312\n        wind: 0.09066697954100136\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00013521783313232835\n        coal: 5.931792850547562e-05\n        gas: 0.047998858796066156\n        geothermal: 0.0\n        hydro: 0.8132648544113503\n        hydro discharge: 3.532237320890014e-05\n        nuclear: 0.0010473864934381534\n        oil: 1.0126771078699105e-07\n        solar: 4.226141286978266e-05\n        unknown: 0.01063245946457785\n        wind: 0.1267841759897007\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000442820258429374\n        coal: 0.00011720201087261334\n        gas: 0.05906903904580211\n        geothermal: 0.0\n        hydro: 0.7573575109193441\n        hydro discharge: 8.57926878892112e-06\n        nuclear: 0.0022867481004593977\n        oil: 1.644859808598513e-07\n        solar: 0.00021407875406779077\n        unknown: 0.010058740193573302\n        wind: 0.17044500247243927\nhas_day_ahead_price_license: True\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: Europe/Oslo\nzone_name: Northern Norway\n"
  },
  {
    "path": "config/zones/NO-NO5.yaml",
    "content": "bounding_box:\n  - - 4.926649266492689\n    - 60.111501203936854\n  - - 9.60309603096033\n    - 61.83870910704472\ncenter_point:\n  - 7.598459867208756\n  - 60.81134941964953\ncentroid:\n  - 6.1910150943177955\n  - 60.5846601611768\ncapacity:\n  biomass:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 32.02\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 32.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 335.5\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 359.4\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 366.5\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 192.2\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 7276.740000000001\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 7577.44\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 7632.97\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 7809.87\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 7904.35\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 7925.77\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 7946.14\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 7996.4\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 469.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 449.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 482.5\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\ncountry: 'NO'\ncountry_name: Norway\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0.0\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 1.21\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490.0\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 25.21\n    oil:\n      datetime: '2014-01-01'\n      source: EIA 2020/BEIS 2021; IPCC 2014\n      value: 650.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.779731372460524e-05\n        coal: 0.00010898332375316402\n        gas: 0.023063566715259283\n        geothermal: 4.83992693986162e-09\n        hydro: 0.9723139438270403\n        hydro discharge: 3.796653799491449e-07\n        nuclear: 0.00017362969011923567\n        oil: 1.8101326755082457e-06\n        solar: 8.992584254262891e-06\n        unknown: 0.0016478042147935869\n        wind: 0.0026530500491972657\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00010120790894433295\n        coal: 0.0004385945854377286\n        gas: 0.023472910714607168\n        geothermal: 1.1015147873126482e-07\n        hydro: 0.970727910913184\n        hydro discharge: 1.3358148940062225e-06\n        nuclear: 0.00023907435172477193\n        oil: 4.681133560225905e-06\n        solar: 2.804663562877939e-05\n        unknown: 0.0026009399243937296\n        wind: 0.002384551300142246\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00024603286277320355\n        coal: 0.00031005641642171185\n        gas: 0.030392744111626166\n        geothermal: 1.311204731537418e-07\n        hydro: 0.9648547042701802\n        hydro discharge: 2.4134745035167708e-06\n        nuclear: 0.00039371679270622153\n        oil: 3.887660757759307e-05\n        solar: 5.834799784092372e-05\n        unknown: 0.0009484764857948582\n        wind: 0.0027542547751058717\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000308379803985012\n        coal: 0.0006862081774205259\n        gas: 0.030906629253567092\n        geothermal: 2.3601038421557155e-07\n        hydro: 0.9627373922427601\n        hydro discharge: 3.3573808040290325e-06\n        nuclear: 0.0005184941114563287\n        oil: 9.908887108719937e-06\n        solar: 6.986853780336669e-05\n        unknown: 0.0018886970556263663\n        wind: 0.0028706368915540057\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0004439427518568844\n        coal: 0.0009422372374996915\n        gas: 0.030379934443229454\n        geothermal: 3.6807469282233713e-07\n        hydro: 0.959837030946996\n        hydro discharge: 4.241352998829699e-06\n        nuclear: 0.0011492997008063018\n        oil: 2.275079114147502e-05\n        solar: 0.00013456496175830092\n        unknown: 0.00044853078717322714\n        wind: 0.006636801346155232\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0013120068650670415\n        coal: 0.0001120768964995111\n        gas: 0.02172189972942641\n        geothermal: 1.1226600234345852e-07\n        hydro: 0.9420629290770124\n        hydro discharge: 0.026873281130477177\n        nuclear: 0.0003164668834859804\n        oil: 4.13937224640592e-06\n        solar: 5.924152203661702e-05\n        unknown: 0.0010515158103495095\n        wind: 0.0064861737739534304\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00511589658321821\n        coal: 0.00035243826087446483\n        gas: 0.023631762757022022\n        geothermal: 5.928093790253827e-07\n        hydro: 0.8906054905729331\n        hydro discharge: 0.06566766248060525\n        nuclear: 0.0006876702579684656\n        oil: 1.3370070265331592e-05\n        solar: 0.0003263483901328861\n        unknown: 0.0004339802718978133\n        wind: 0.013164656695264737\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004909916716646425\n        coal: 0.0006696310943354995\n        gas: 0.011442325138188237\n        geothermal: 9.64675385636378e-07\n        hydro: 0.9349453082933554\n        hydro discharge: 0.019600429679937505\n        nuclear: 0.0025766209135553385\n        oil: 1.9125968111931476e-05\n        solar: 0.000796423300643228\n        unknown: 0.000769928529387511\n        wind: 0.02426923809957442\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004627946938812611\n        coal: 0.0005427304118956567\n        gas: 0.0029827012423814486\n        geothermal: 1.2490303268107974e-06\n        hydro: 0.9426022808495335\n        hydro discharge: 0.02761304038367376\n        nuclear: 0.0020738505431939173\n        oil: 2.607763846346776e-05\n        solar: 0.0006374133991371453\n        unknown: 0.0006338633653703705\n        wind: 0.01825878011095054\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0038557699594585736\n        coal: 0.0002237453667959168\n        gas: 0.0026935894404257563\n        geothermal: 6.3760865415571e-07\n        hydro: 0.9509556534349101\n        hydro discharge: 0.025570068860595048\n        nuclear: 0.0007940928606634206\n        oil: 1.7702044735170186e-05\n        solar: 0.0007275091951828923\n        unknown: 0.00041495388875751785\n        wind: 0.014746060245185884\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.9975\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.995\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\ntimezone: Europe/Oslo\nzone_name: Western Norway\n"
  },
  {
    "path": "config/zones/NO.yaml",
    "content": "bounding_box:\n  - - 4.915849158491596\n    - 58.01771794304598\n  - - 31.07731077310774\n    - 71.16078268093528\ncenter_point:\n  - 12.88936927923287\n  - 64.42937585013483\ncentroid:\n  - 15.936502402407717\n  - 66.3606573055699\ncapacity:\n  biomass: 113.3\n  coal: 0\n  gas: 473.4\n  geothermal: 0\n  hydro: 33625\n  hydro storage: 1438\n  nuclear: 0\n  oil: 0\n  solar: 160\n  unknown: 112.6\n  wind: 5056\ncontributors:\n  - corradio\ncountry: 'NO'\ncountry_name: Norway\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: EU-ETS 2021\n      value: 0\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 9.44\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230\n    gas:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 490\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 33.44\n    oil:\n      datetime: '2014-01-01'\n      source: EIA 2020/BEIS 2021; IPCC 2014\n      value: 650\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0005565487705269869\n        coal: 0.0021721437635602884\n        gas: 0.02245331654254779\n        geothermal: 4.665128836860338e-07\n        hydro: 0.9289487828510647\n        hydro discharge: 9.044961362296584e-06\n        nuclear: 0.008298630924655956\n        oil: 3.4054812103108166e-05\n        solar: 0.00021734158929004625\n        unknown: 0.005053657953297409\n        wind: 0.03225609136191832\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0007063526478787031\n        coal: 0.003069574039270809\n        gas: 0.02152580119183406\n        geothermal: 1.0996896373749893e-06\n        hydro: 0.937660963362525\n        hydro discharge: 1.3518548955287977e-05\n        nuclear: 0.0056696719040754155\n        oil: 3.627509550487631e-05\n        solar: 0.0003093432996339349\n        unknown: 0.003812366925050104\n        wind: 0.027195053551086312\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001793211547308626\n        coal: 0.0022429621709352844\n        gas: 0.02058924464055746\n        geothermal: 1.1967314178776731e-06\n        hydro: 0.9289586546514083\n        hydro discharge: 1.4665028228916554e-05\n        nuclear: 0.008947882036814672\n        oil: 0.00034888876512215807\n        solar: 0.00047630501428480885\n        unknown: 0.0038045816138848453\n        wind: 0.032822379147906644\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0017857934711154122\n        coal: 0.004196118010994991\n        gas: 0.02281490847971826\n        geothermal: 1.794519548704413e-06\n        hydro: 0.9099944390535454\n        hydro discharge: 2.6383028465519246e-05\n        nuclear: 0.010292580859570088\n        oil: 6.116290133456778e-05\n        solar: 0.0007050739864731984\n        unknown: 0.00869272510462031\n        wind: 0.041429006234932925\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0025760698823849315\n        coal: 0.005364991377164306\n        gas: 0.02715606122436144\n        geothermal: 2.51218388555383e-06\n        hydro: 0.8762799249489324\n        hydro discharge: 3.222955959975368e-05\n        nuclear: 0.01949345701602177\n        oil: 0.000149103242805717\n        solar: 0.0015111483193274676\n        unknown: 0.0037091453094843727\n        wind: 0.06372532511254035\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0013360385776377236\n        coal: 0.0006982324860430046\n        gas: 0.014502436768264036\n        geothermal: 8.029203156670505e-07\n        hydro: 0.8880945168908582\n        hydro discharge: 0.015688997089427816\n        nuclear: 0.005191451544200216\n        oil: 2.3674679021954174e-05\n        solar: 0.0003939387414065657\n        unknown: 0.0033951001833768496\n        wind: 0.07067479019736485\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0033592323756670055\n        coal: 0.0028899224836683524\n        gas: 0.006846946820385037\n        geothermal: 3.7671501889807903e-06\n        hydro: 0.8462435901460417\n        hydro discharge: 0.0408952132625497\n        nuclear: 0.00901947349806991\n        oil: 8.881517372354873e-05\n        solar: 0.0018194982149506843\n        unknown: 0.004104130706521003\n        wind: 0.08472940146359499\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004797978378811616\n        coal: 0.00506420742303078\n        gas: 0.014303972418196904\n        geothermal: 6.0175309407321376e-06\n        hydro: 0.8121682906081245\n        hydro discharge: 0.00942316049009661\n        nuclear: 0.018829409982394654\n        oil: 0.00013572690146174636\n        solar: 0.004474577159637623\n        unknown: 0.004862366590551451\n        wind: 0.1259342835071249\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 5.901220256190837e-10\n        biomass: 0.004156982569670403\n        coal: 0.0028615646977531717\n        gas: 0.012509334335359943\n        geothermal: 5.5077563956093135e-06\n        hydro: 0.8219961253675099\n        hydro discharge: 0.010654795982082757\n        nuclear: 0.014848770719755357\n        oil: 0.00014336240077257015\n        solar: 0.0040742906143517305\n        unknown: 0.005008291128523429\n        wind: 0.12374095539638996\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.4716307958738403e-08\n        biomass: 0.0036940655852340095\n        coal: 0.0016079969869265405\n        gas: 0.01417637932600794\n        geothermal: 3.6006857297287837e-06\n        hydro: 0.8149208521628072\n        hydro discharge: 0.012411303554765154\n        nuclear: 0.01649414786584905\n        oil: 0.00010937784620686774\n        solar: 0.005032172878244702\n        unknown: 0.004538204352072401\n        wind: 0.12701186508811527\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.9795\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.9498\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  production: ENTSOE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\nsubZoneNames:\n  - NO-NO1\n  - NO-NO2\n  - NO-NO3\n  - NO-NO4\n  - NO-NO5\ntimezone: Europe/Oslo\nzone_name: Norway\n"
  },
  {
    "path": "config/zones/NP.yaml",
    "content": "bounding_box:\n  - - 80.06396829477401\n    - 26.353579181009962\n  - - 88.17028170281705\n    - 30.413561178112758\ncenter_point:\n  - 84.1491471469872\n  - 28.38056009862413\ncentroid:\n  - 84.30693865487876\n  - 28.121175556033563\ncapacity:\n  biomass: 0\n  coal: 0\n  gas: 0\n  hydro: 1016\n  nuclear: 0\n  oil: 0\n  solar: 0.7804\n  wind: 0\ncontributors:\n  - Subarna578\ncountry: NP\ncountry_name: Nepal\ncurrency: NPR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Asia\ntimezone: Asia/Kathmandu\nzone_name: Nepal\n"
  },
  {
    "path": "config/zones/NZ-NZA.yaml",
    "content": "bounding_box:\n  - - 165.88785887858873\n    - -50.86049507125672\n  - - 166.24426244262438\n    - -50.552812262170676\ncenter_point:\n  - 166.06606066060655\n  - -50.7066536667137\ncentroid:\n  - 166.11826118261177\n  - -50.70236041821482\ncountry: NZ\ncountry_name: New Zealand\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Oceania\ntimezone: Pacific/Auckland\nzone_name: Auckland Islands\n"
  },
  {
    "path": "config/zones/NZ-NZC.yaml",
    "content": "bounding_box:\n  - - -176.6627666276662\n    - -44.121526010855945\n  - - -176.2847628476284\n    - -43.70794307213099\ncenter_point:\n  - -176.4737647376473\n  - -43.914734541493466\ncentroid:\n  - -176.4652789385036\n  - -43.926080983954776\ncountry: NZ\ncountry_name: New Zealand\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Oceania\ntimezone: Pacific/Auckland\nzone_name: Chatham Islands\n"
  },
  {
    "path": "config/zones/NZ-NZST.yaml",
    "content": "bounding_box:\n  - - 167.5222752227522\n    - -47.27277040903019\n  - - 168.1990819908199\n    - -46.683164281851354\ncenter_point:\n  - 167.86067860678605\n  - -46.977967345440774\ncentroid:\n  - 167.8881288812888\n  - -46.97510517977486\ncapacity:\n  biomass: 0\n  coal: 0\n  gas: 0\n  hydro: 0\n  nuclear: 0\n  oil: 1.096\n  solar: 0\n  wind: 0\ncontributors:\n  - madsnedergaard\ncountry: NZ\ncountry_name: New Zealand\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Oceania\ntimezone: Pacific/Auckland\nzone_name: Stewart Island\n"
  },
  {
    "path": "config/zones/NZ.yaml",
    "content": "bounding_box:\n  - - 166.4890648906489\n    - -46.681733199018396\n  - - 178.5635856358563\n    - -34.39731816090409\ncenter_point:\n  - 172.56697446725485\n  - -41.12631541536777\ncentroid:\n  - 173.21921104048826\n  - -40.32658932655313\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 750.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1320.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1420.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 990.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1010.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1040.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1050.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1280.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5430.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 5440.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 5680.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 360.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 570.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 690.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 910.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 990.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1060.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1260.0\ncontributors:\n  - BobGrun\n  - corradio\n  - davidcole1340\n  - drc38\ncountry: NZ\ncountry_name: New Zealand\ncurrency: NZD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 113.81\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 81.06\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 84.45\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 65.2\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 80.38\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 52.93\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 146.81\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 114.06\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 117.45\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 98.2\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 113.38\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 85.93\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 3.4270403248697153e-06\n        biomass: 0.0\n        coal: 0.023192838102588275\n        gas: 0.08781919346490825\n        geothermal: 0.188754441337166\n        hydro: 0.6064218109183618\n        hydro discharge: 0.0\n        nuclear: 0.00014187946944960614\n        oil: 0.00017383662047901625\n        solar: 0.0\n        unknown: 0.02568549588288227\n        wind: 0.06780630607976658\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 3.4270403248697153e-06\n        biomass: 0.0\n        coal: 0.02319283810258828\n        gas: 0.08781919346490825\n        geothermal: 0.188754441337166\n        hydro: 0.6064218109183618\n        hydro discharge: 0.0\n        nuclear: 0.00014187946944960612\n        oil: 0.00017383662047901625\n        solar: 0.0\n        unknown: 0.02568549588288227\n        wind: 0.06780630607976659\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 7.870902925206408e-07\n        biomass: 0.0\n        coal: 0.03293955383303492\n        gas: 0.07298338464636114\n        geothermal: 0.19069177589357655\n        hydro: 0.6002026989197703\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00012812080872697096\n        solar: 0.0018571617083233218\n        unknown: 0.0219364688159811\n        wind: 0.07926016736578241\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 7.870902925206408e-07\n        biomass: 0.0\n        coal: 0.03293955383303492\n        gas: 0.07298338464636114\n        geothermal: 0.19069177589357655\n        hydro: 0.6002026989197703\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00012812080872697096\n        solar: 0.0018571617083233218\n        unknown: 0.0219364688159811\n        wind: 0.07926016736578241\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 7.870895287405387e-07\n        biomass: 0.0\n        coal: 0.03294118350245695\n        gas: 0.0729871618176785\n        geothermal: 0.19068984176141987\n        hydro: 0.6002025537644248\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00012812068440054325\n        solar: 0.0018571599061626644\n        unknown: 0.021936622437959224\n        wind: 0.0792567671860573\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 7.870894897132341e-07\n        biomass: 0.0\n        coal: 0.032941181869090536\n        gas: 0.0729871581986592\n        geothermal: 0.1906898323061924\n        hydro: 0.6002025240037852\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00012812067804776533\n        solar: 0.0018572090959563432\n        unknown: 0.02193662135024656\n        wind: 0.07925676325616385\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 7.870895287405387e-07\n        biomass: 0.0\n        coal: 0.03294118350245695\n        gas: 0.0729871618176785\n        geothermal: 0.19068984176141987\n        hydro: 0.6002025537644248\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00012812068440054325\n        solar: 0.0018571599061626644\n        unknown: 0.021936622437959224\n        wind: 0.0792567671860573\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 6.0396195009503165e-06\n        biomass: 0.0\n        coal: 0.021692431737076304\n        gas: 0.07745045662586379\n        geothermal: 0.18773967083862436\n        hydro: 0.6198165043611087\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 6.783643069136958e-05\n        solar: 0.00019236172574681746\n        unknown: 0.025418318873807282\n        wind: 0.06761633126794162\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 4.327367258287025e-08\n        biomass: 0.0\n        coal: 0.037209063063544774\n        gas: 0.05994928881399571\n        geothermal: 0.18210292002669648\n        hydro: 0.6239158556053307\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 2.0997107165085022e-05\n        solar: 3.1548670996541563e-05\n        unknown: 0.020220760169479303\n        wind: 0.076549443453234\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 2.3593629838993124e-05\n        biomass: 0.0\n        coal: 0.04226846196193547\n        gas: 0.08250109184628247\n        geothermal: 0.20519043534047834\n        hydro: 0.5531997904739577\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0003913151033645173\n        solar: 0.0022427556771429237\n        unknown: 0.020886705386506124\n        wind: 0.09329579500153248\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.7847\n    - datetime: '2021-01-01'\n      value: 0.843\n    - datetime: '2022-01-01'\n      value: 0.8267\n    - datetime: '2023-01-01'\n      value: 0.8958\n    - datetime: '2024-01-01'\n      value: 0.8422\n    - datetime: '2025-01-01'\n      value: 0.8901\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.7847\n    - datetime: '2021-01-01'\n      value: 0.843\n    - datetime: '2022-01-01'\n      value: 0.8267\n    - datetime: '2023-01-01'\n      value: 0.8958\n    - datetime: '2024-01-01'\n      value: 0.8422\n    - datetime: '2025-01-01'\n      value: 0.8901\nparsers:\n  price: NZ.fetch_price\n  production: NZ.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Pacific/Auckland\nzone_name: New Zealand\n"
  },
  {
    "path": "config/zones/OM.yaml",
    "content": "bounding_box:\n  - - 51.97911979119792\n    - 16.642251076554743\n  - - 59.8019980199802\n    - 26.386494086168014\ncenter_point:\n  - 55.936697643349724\n  - 20.629164171585437\ncentroid:\n  - 56.60999049685969\n  - 21.551494014600596\ncapacity:\n  gas:\n    - datetime: '2020-01-01'\n      source: Climatescope\n      value: 10544\n    - datetime: '2021-01-01'\n      source: Climatescope\n      value: 9764\n    - datetime: '2022-01-01'\n      source: Climatescope\n      value: 9495\n    - datetime: '2023-01-01'\n      source: Climatescope\n      value: 9044\n  oil:\n    - datetime: '2020-01-01'\n      source: Climatescope\n      value: 150\n  solar:\n    - datetime: '2020-01-01'\n      source: Climatescope\n      value: 43\n    - datetime: '2021-01-01'\n      source: Climatescope\n      value: 329\n    - datetime: '2022-01-01'\n      source: Climatescope\n      value: 924\n    - datetime: '2023-01-01'\n      source: Climatescope\n      value: 1224\n  wind:\n    - datetime: '2020-01-01'\n      source: Climatescope\n      value: 49\ncontributors:\n  - q--\n  - nessie2013\n  - florianscheidl\ncountry: OM\ncountry_name: Oman\ncurrency: OMR\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.46536307433008217\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.010270280212057826\n        solar: 0.02343339011432368\n        unknown: 0.5009331896190804\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9241263713007266\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.020394883822319847\n        solar: 0.05139963425427532\n        unknown: 0.004078967295063173\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.9999937203899146\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.9999933095505461\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.917233551645257\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.020242781393878737\n        solar: 0.05847499902621566\n        unknown: 0.004048538876343689\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: GCCIA.fetch_consumption\nregion: Asia\nsources:\n  Climatescope:\n    link: https://www.global-climatescope.org/markets/om/\ntimezone: Asia/Muscat\nzone_name: Oman\n"
  },
  {
    "path": "config/zones/PA.yaml",
    "content": "bounding_box:\n  - - -83.0546305463054\n    - 7.218570621524137\n  - - -77.1685716857168\n    - 9.62422086372709\ncenter_point:\n  - -80.38106745074387\n  - 8.628309235992546\ncentroid:\n  - -80.40475052637844\n  - 8.451922150379353\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 430.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1650.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1770.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1790.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1810.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1840.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1850.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 500.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 530.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 650.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1160.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1120.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1090.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1040.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 620.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 650.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 780.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 340.0\ncontributors:\n  - paulotaviodr\n  - jarek\n  - systemcatch\n  - 7hibault\n  - nessie2013\n  - q--\n  - IV1T3\n  - r24mille\ncountry: PA\ncountry_name: Panama\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002707723640776714\n        coal: 0.16140501160661805\n        gas: 0.0360851216848254\n        geothermal: 0.000420518648516012\n        hydro: 0.5099593591587441\n        hydro discharge: 0.0\n        nuclear: 0.000420518648516012\n        oil: 0.0377237731575753\n        solar: 0.027295927115622134\n        unknown: 0.18399493820887403\n        wind: 0.03998279121143909\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002707723599827074\n        coal: 0.16140500916564626\n        gas: 0.03608512113910031\n        geothermal: 0.0004205186421563943\n        hydro: 0.5099593514464903\n        hydro discharge: 0.0\n        nuclear: 0.0004205186421563943\n        oil: 0.037723772587068445\n        solar: 0.02729594182608981\n        unknown: 0.18399493542626866\n        wind: 0.03998279060676849\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0028834291239132393\n        coal: 0.14518985377058863\n        gas: 0.0013729312039114695\n        geothermal: 4.448231555539313e-07\n        hydro: 0.6145281524163742\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.07118514385045442\n        solar: 0.012172256453139735\n        unknown: 0.09210956175196404\n        wind: 0.0605579290757788\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.3729741724825684e-05\n        coal: 0.0019021579130303356\n        gas: 0.0015896038069889683\n        geothermal: 8.77758998801364e-05\n        hydro: 0.7045147495577432\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0009424174629833568\n        solar: 0.01936463331265339\n        unknown: 0.21760299624903007\n        wind: 0.053941968121599404\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00013531081873512067\n        coal: 0.004496107096982775\n        gas: 0.001258044365624252\n        geothermal: 0.000248013781149604\n        hydro: 0.39681261608612317\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.002254339514280252\n        solar: 0.021218466499664808\n        unknown: 0.5209682742510083\n        wind: 0.05260872909295485\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0012039063479129086\n        coal: 0.05470073405511751\n        gas: 0.007076952993787578\n        geothermal: 0.00026946528279804505\n        hydro: 0.5789172086453932\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.007694542370855447\n        solar: 0.023817421267229702\n        unknown: 0.27957041588298737\n        wind: 0.04674936227849298\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0017652593520149369\n        coal: 0.16220829506858547\n        gas: 0.1136531808755579\n        geothermal: 0.0005859525611603872\n        hydro: 0.6089943299981692\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0334123037984747\n        solar: 0.042731688670345186\n        unknown: 0.0012551752047482345\n        wind: 0.03539383920062531\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004184380260142247\n        coal: 0.16203143771669612\n        gas: 0.09815799338460146\n        geothermal: 0.002121064718099994\n        hydro: 0.5825645630980334\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.05943973570881244\n        solar: 0.04977154248515458\n        unknown: 0.0005788166946130226\n        wind: 0.04115039516369193\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0022195089546846246\n        coal: 0.14772223104889895\n        gas: 0.1901316126789326\n        geothermal: 0.0010360771645889582\n        hydro: 0.43100442336561373\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.11260410359966123\n        solar: 0.05685999293728491\n        unknown: 7.335938103307967e-05\n        wind: 0.05834838780743917\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0032106368364583876\n        coal: 0.0\n        gas: 0.16802822254974611\n        geothermal: 0.0006172196390771122\n        hydro: 0.6035499958185314\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.10061503469597771\n        solar: 0.07582387224209039\n        unknown: 0.0\n        wind: 0.04815485711912523\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: PA.fetch_consumption\n  production: PA.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Panama\nzone_name: Panama\n"
  },
  {
    "path": "config/zones/PE.yaml",
    "content": "bounding_box:\n  - - -81.33741337413369\n    - -18.337706609445718\n  - - -68.68328683286828\n    - -0.032726093075716\ncenter_point:\n  - -75.03004352182998\n  - -9.268566468684224\ncentroid:\n  - -74.55105220330144\n  - -8.063048545075539\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 7090.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 7200.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 7100.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 6530.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 6550.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 6690.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 6700.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 5230.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 5390.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 5410.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 5500.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 5520.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 300.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 320.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 330.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 450.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 530.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1220.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1240.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1250.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1830.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1840.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2060.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1980.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 410.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 540.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1010.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1150.0\ncontributors:\n  - corradio\n  - nessie2013\ncountry: PE\ncountry_name: Peru\ncurrency: PEN\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00457261818728674\n        coal: 0.0021124201525052257\n        gas: 0.3325344755952747\n        geothermal: 0.0\n        hydro: 0.6093742795707796\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0027363174444363\n        solar: 0.014901468437436316\n        unknown: 0.0013581966325900145\n        wind: 0.032410087147406105\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004572617925456112\n        coal: 0.002112420031546888\n        gas: 0.3325344565541681\n        geothermal: 0.0\n        hydro: 0.6093742446776739\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0027363172877532607\n        solar: 0.014901524906315976\n        unknown: 0.0013581965548189298\n        wind: 0.03241008529158672\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004989440858141621\n        coal: 0.015380875244147163\n        gas: 0.30717477214422273\n        geothermal: 0.0\n        hydro: 0.6239563634600269\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.017816316486832604\n        solar: 0.006496794362782947\n        unknown: 0.0\n        wind: 0.024185411084714944\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0035136222176400914\n        coal: 0.0009209222730078529\n        gas: 0.31640827280008504\n        geothermal: 0.0\n        hydro: 0.6296352500048135\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0020755738678866482\n        solar: 0.01574994505854727\n        unknown: 0.0\n        wind: 0.0316964065407236\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006040957041037882\n        coal: 0.0007341223774800803\n        gas: 0.3330601491793424\n        geothermal: 0.0\n        hydro: 0.6112602415058382\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0006229083363671159\n        solar: 0.015286402131175087\n        unknown: 0.0\n        wind: 0.03299522606177934\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0068179739738108355\n        coal: 0.00027762721379953045\n        gas: 0.3083053778549124\n        geothermal: 0.0\n        hydro: 0.6287631889774805\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0009672289313789042\n        solar: 0.016533189721410168\n        unknown: 0.0\n        wind: 0.03833534943749397\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007405765065298139\n        coal: 0.000552663012313259\n        gas: 0.33849820835074945\n        geothermal: 0.0\n        hydro: 0.6024394455061781\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0005419490829972351\n        solar: 0.015539736948844685\n        unknown: 0.0\n        wind: 0.035022179623235734\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007209399179403766\n        coal: 0.0017711127552856468\n        gas: 0.3753430638301847\n        geothermal: 0.0\n        hydro: 0.5570495158338271\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.005593646886889595\n        solar: 0.015822853220799293\n        unknown: 0.0\n        wind: 0.0372103379265287\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006979070080912979\n        coal: 0.0\n        gas: 0.3941425191048746\n        geothermal: 0.0\n        hydro: 0.5223748840792997\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.015406352917966345\n        solar: 0.01768410110352372\n        unknown: 0.0\n        wind: 0.04341302859425622\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007320029105831322\n        coal: 0.0\n        gas: 0.34378473239714524\n        geothermal: 0.0\n        hydro: 0.5623771365162856\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.001270293832835364\n        solar: 0.022634861767733317\n        unknown: 0.0\n        wind: 0.06261290684751358\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: PE.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Lima\nzone_name: Peru\n"
  },
  {
    "path": "config/zones/PF.yaml",
    "content": "bounding_box:\n  - - -149.60489604896043\n    - -17.86974252306834\n  - - -138.83718837188366\n    - -8.786659782281824\ncenter_point:\n  - -140.2268022680226\n  - -8.926905899911738\ncentroid:\n  - -144.47754477544768\n  - -13.492537164659796\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncontributors:\n  - autipial\ncountry: PF\ncountry_name: French Polynesia\ncurrency: XPF\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.268676684368378\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.6614984662103188\n        solar: 0.0698236314028944\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.3460027205785064\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5259751744008679\n        solar: 0.12802333116592324\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.2871922962924065\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.6308824117719226\n        solar: 0.0819242574881353\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.3581810505035641\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.5455574648757916\n        solar: 0.09626067428950572\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: PF.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Tahiti\nzone_name: French Polynesia\n"
  },
  {
    "path": "config/zones/PG.yaml",
    "content": "bounding_box:\n  - - 140.84960849608493\n    - -11.635945702701854\n  - - 155.93375933759333\n    - -1.346460133731462\ncenter_point:\n  - 146.65096268127866\n  - -6.518236283438878\ncentroid:\n  - 148.9726910582177\n  - -6.664087795383831\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 150.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 320.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 540.0\ncountry: PG\ncountry_name: Papua New Guinea\ncurrency: PGK\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Port_Moresby\nzone_name: Papua New Guinea\n"
  },
  {
    "path": "config/zones/PH-LU.yaml",
    "content": "bounding_box:\n  - - 116.96336963369632\n    - 7.823918659865512\n  - - 124.4190441904419\n    - 18.64290487703049\ncenter_point:\n  - 121.17265964788953\n  - 16.186411339723\ncentroid:\n  - 121.48221482214818\n  - 13.40642968295266\ncapacity:\n  battery storage: 72\n  biomass: 175\n  coal: 8792\n  gas: 3731\n  hydro: 1806\n  hydro storage: 736\n  nuclear: 0\n  oil: 2357\n  solar: 960\n  wind: 337\ncontributors:\n  - VIKTORVAV99\n  - jarek\n  - systemcatch\n  - q--\n  - mathilde-daugy\n  - pierresegonne\n  - xomanuel\ncountry: PH\ncountry_name: Philippines\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 562.52\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 562.53\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 562.52\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 567.85\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 556.53\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 549.56\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 578.71\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 578.7\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 578.71\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 572.75\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 579.66\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 567.03\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 595.52\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 595.53\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 595.52\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 600.85\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 589.53\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 582.56\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 602.71\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 602.7\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 602.71\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 596.75\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 603.66\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 591.03\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 4.761311160831059e-07\n        biomass: 0.006289908466692412\n        coal: 0.604828087393628\n        gas: 0.21055732816857603\n        geothermal: 0.04473414882343369\n        hydro: 0.04761099066061167\n        hydro discharge: 0.010545611666890128\n        nuclear: 0.0\n        oil: 0.0029094208271492764\n        solar: 0.02055019275975529\n        unknown: 0.04049711565521398\n        wind: 0.01147657785277335\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 4.761311160831059e-07\n        biomass: 0.006289908466692412\n        coal: 0.604828087393628\n        gas: 0.21055732816857603\n        geothermal: 0.04473414882343369\n        hydro: 0.04761099066061167\n        hydro discharge: 0.010545611666890128\n        nuclear: 0.0\n        oil: 0.0029094208271492764\n        solar: 0.02055019275975529\n        unknown: 0.04049711565521398\n        wind: 0.01147657785277335\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 3.464411422089761e-07\n        biomass: 0.006155713096321846\n        coal: 0.6086640248677142\n        gas: 0.21705882000177\n        geothermal: 0.04447890387442539\n        hydro: 0.043535477491558\n        hydro discharge: 0.010305549657243509\n        nuclear: 0.0\n        oil: 0.0032841232143957567\n        solar: 0.02090369685912002\n        unknown: 0.03477992164017229\n        wind: 0.010833639500495023\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 3.4644121310579307e-07\n        biomass: 0.006155697389918645\n        coal: 0.6086645304724422\n        gas: 0.21705959523041563\n        geothermal: 0.044478880033176\n        hydro: 0.04353510199342311\n        hydro discharge: 0.010305543461106386\n        nuclear: 0.0\n        oil: 0.003284132784788004\n        solar: 0.020903722076008508\n        unknown: 0.03477910346823565\n        wind: 0.010833563175031254\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 3.464412030006809e-07\n        biomass: 0.006155697210367223\n        coal: 0.6086645131141941\n        gas: 0.21705958905734168\n        geothermal: 0.04447887881489745\n        hydro: 0.04353510072357681\n        hydro discharge: 0.010305543160510878\n        nuclear: 0.0\n        oil: 0.00328413268899533\n        solar: 0.020903750001844183\n        unknown: 0.03477910245378722\n        wind: 0.010833562859034291\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 3.9006595685411477e-07\n        biomass: 0.006171975554045922\n        coal: 0.6080932553422664\n        gas: 0.21604204119209475\n        geothermal: 0.044521672645213\n        hydro: 0.04436475354765222\n        hydro discharge: 0.010366521823641787\n        nuclear: 0.0\n        oil: 0.0032210807980299003\n        solar: 0.02083773898724136\n        unknown: 0.03548507797290176\n        wind: 0.010895775485667622\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 3.152895204828079e-05\n        biomass: 0.006646831033968585\n        coal: 0.613930634388525\n        gas: 0.2174848086934832\n        geothermal: 0.03893925624054278\n        hydro: 0.05077548177438068\n        hydro discharge: 0.012407461414081644\n        nuclear: 0.0\n        oil: 0.0023674156349578553\n        solar: 0.020471143922357854\n        unknown: 0.02418643924645213\n        wind: 0.012758888285265842\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 9.824669003734796e-05\n        biomass: 0.006327906309984232\n        coal: 0.5967251263784077\n        gas: 0.20058434759830127\n        geothermal: 0.04923497343763094\n        hydro: 0.044382822108081796\n        hydro discharge: 0.013148708054379397\n        nuclear: 0.0\n        oil: 0.0035165902591422628\n        solar: 0.020418652513402993\n        unknown: 0.054426137887670575\n        wind: 0.01113649280728119\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.1358\n    - datetime: '2021-01-01'\n      value: 0.1358\n    - datetime: '2022-01-01'\n      value: 0.1358\n    - datetime: '2023-01-01'\n      value: 0.1322\n    - datetime: '2024-01-01'\n      value: 0.146\n    - datetime: '2025-01-01'\n      value: 0.148\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1129\n    - datetime: '2021-01-01'\n      value: 0.1129\n    - datetime: '2022-01-01'\n      value: 0.1129\n    - datetime: '2023-01-01'\n      value: 0.1211\n    - datetime: '2024-01-01'\n      value: 0.118\n    - datetime: '2025-01-01'\n      value: 0.1273\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.1358\n    - datetime: '2021-01-01'\n      value: 0.1358\n    - datetime: '2022-01-01'\n      value: 0.1358\n    - datetime: '2023-01-01'\n      value: 0.1322\n    - datetime: '2024-01-01'\n      value: 0.146\n    - datetime: '2025-01-01'\n      value: 0.148\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1129\n    - datetime: '2021-01-01'\n      value: 0.1129\n    - datetime: '2022-01-01'\n      value: 0.1129\n    - datetime: '2023-01-01'\n      value: 0.1211\n    - datetime: '2024-01-01'\n      value: 0.118\n    - datetime: '2025-01-01'\n      value: 0.1273\nparsers:\n  production: IEMOP.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Manila\nzone_name: Luzon\n"
  },
  {
    "path": "config/zones/PH-MI.yaml",
    "content": "bounding_box:\n  - - 119.81099810998111\n    - 5.07480853775256\n  - - 126.58266582665826\n    - 10.457111072508837\ncenter_point:\n  - 124.76318645902569\n  - 7.602095842199491\ncentroid:\n  - 124.33077130771296\n  - 7.610529898643097\ncapacity:\n  battery storage: 49\n  biomass: 79\n  coal: 2268\n  gas: 0\n  hydro: 1191\n  nuclear: 0\n  oil: 833\n  solar: 84\ncontributors:\n  - VIKTORVAV99\n  - jarek\n  - systemcatch\n  - q--\n  - mathilde-daugy\n  - pierresegonne\n  - xomanuel\ncountry: PH\ncountry_name: Philippines\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 475.14\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 475.13\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 475.14\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 457.32\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 489.78\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 463.64\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 508.14\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 508.13\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 508.14\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 490.32\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 522.78\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 496.64\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008187892651614619\n        coal: 0.6070814065569963\n        gas: 0.0\n        geothermal: 0.037653825448227325\n        hydro: 0.28282070523014696\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.05295629726261812\n        solar: 0.00621001439259805\n        unknown: 0.005090291812708768\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008187892651614619\n        coal: 0.6070814065569963\n        gas: 0.0\n        geothermal: 0.037653825448227325\n        hydro: 0.28282070523014696\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.05295629726261812\n        solar: 0.00621001439259805\n        unknown: 0.005090291812708768\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008405977894405761\n        coal: 0.609839200268249\n        gas: 0.0\n        geothermal: 0.038123692368657466\n        hydro: 0.2804145731928696\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.05291236291691265\n        solar: 0.006212459696210904\n        unknown: 0.00409197753416331\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008406000299883474\n        coal: 0.6098394766300451\n        gas: 0.0\n        geothermal: 0.0381237444376623\n        hydro: 0.2804143298591732\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.052912399320275846\n        solar: 0.0062124129100311915\n        unknown: 0.004091879748359524\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00840600014863049\n        coal: 0.6098394656569263\n        gas: 0.0\n        geothermal: 0.038123743751684445\n        hydro: 0.2804143248135508\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.052912398368199005\n        solar: 0.006212430924382884\n        unknown: 0.0040918796747324735\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008353456080517352\n        coal: 0.6093024593060532\n        gas: 0.0\n        geothermal: 0.03801753901893002\n        hydro: 0.28094684945321613\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.052929925671506214\n        solar: 0.006220632652462962\n        unknown: 0.004229430741768089\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 8.129819116037864e-06\n        biomass: 0.008800784576922944\n        coal: 0.5712072002860988\n        gas: 2.4357913504356402e-05\n        geothermal: 0.041251095279598325\n        hydro: 0.3146568187336453\n        hydro discharge: 2.360935382750289e-06\n        nuclear: 0.0\n        oil: 0.05623795336815585\n        solar: 0.006348602559981162\n        unknown: 0.0014392509591096777\n        wind: 2.301972659419526e-05\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.0247952930802847e-05\n        biomass: 0.008013888435773548\n        coal: 0.6268067181735192\n        gas: 1.0319600982904481e-05\n        geothermal: 0.0363355851267171\n        hydro: 0.2630038986891826\n        hydro discharge: 1.004896410861563e-06\n        nuclear: 0.0\n        oil: 0.05175352747916385\n        solar: 0.006548497102706934\n        unknown: 0.007487106321175432\n        wind: 9.209647219998301e-06\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.3516\n    - datetime: '2021-01-01'\n      value: 0.3516\n    - datetime: '2022-01-01'\n      value: 0.3516\n    - datetime: '2023-01-01'\n      value: 0.3713\n    - datetime: '2024-01-01'\n      value: 0.3317\n    - datetime: '2025-01-01'\n      value: 0.367\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.3516\n    - datetime: '2021-01-01'\n      value: 0.3516\n    - datetime: '2022-01-01'\n      value: 0.3516\n    - datetime: '2023-01-01'\n      value: 0.3713\n    - datetime: '2024-01-01'\n      value: 0.3317\n    - datetime: '2025-01-01'\n      value: 0.367\nparsers:\n  production: IEMOP.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Manila\nzone_name: Mindanao\n"
  },
  {
    "path": "config/zones/PH-VI.yaml",
    "content": "bounding_box:\n  - - 121.85221852218521\n    - 9.034614736548264\n  - - 125.71145711457112\n    - 12.57797583095308\ncenter_point:\n  - 122.49356734133593\n  - 11.176332268351882\ncentroid:\n  - 123.84336786481727\n  - 10.749264155358476\ncapacity:\n  battery storage: 35\n  biomass: 326\n  coal: 1412\n  gas: 1\n  hydro: 36\n  nuclear: 0\n  oil: 644\n  solar: 487\n  wind: 90\ncontributors:\n  - VIKTORVAV99\n  - jarek\n  - systemcatch\n  - q--\n  - mathilde-daugy\n  - pierresegonne\n  - xomanuel\ncountry: PH\ncountry_name: Philippines\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 505.67\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 505.67\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 505.67\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 532.37\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 516.89\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 512.14\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 538.67\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 538.67\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 538.67\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 565.37\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 549.89\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 545.14\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 9.378920345056573e-05\n        biomass: 0.016127332115117205\n        coal: 0.5699739364281273\n        gas: 0.0\n        geothermal: 0.165620590022002\n        hydro: 0.009991335985409525\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.016530347108162213\n        solar: 0.043787962521328036\n        unknown: 0.16745272961019966\n        wind: 0.010421744854709893\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 9.378920345056573e-05\n        biomass: 0.016127332115117205\n        coal: 0.5699739364281273\n        gas: 0.0\n        geothermal: 0.165620590022002\n        hydro: 0.009991335985409525\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.016530347108162213\n        solar: 0.043787962521328036\n        unknown: 0.16745272961019966\n        wind: 0.010421744854709893\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 9.794118771064168e-05\n        biomass: 0.013283501648178604\n        coal: 0.5715256324965561\n        gas: 0.0\n        geothermal: 0.16408931259445078\n        hydro: 0.009581115151322133\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.017613996187777183\n        solar: 0.04407446919581307\n        unknown: 0.16938605184144565\n        wind: 0.010348210688620438\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 9.794049963303521e-05\n        biomass: 0.0132831802627304\n        coal: 0.5715260108149666\n        gas: 0.0\n        geothermal: 0.16408914349839612\n        hydro: 0.009581075574950552\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.01761404447881478\n        solar: 0.04407439052271267\n        unknown: 0.16938624618137907\n        wind: 0.01034819915816119\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 9.794049336996999e-05\n        biomass: 0.013283179413302182\n        coal: 0.5715259742672189\n        gas: 0.0\n        geothermal: 0.1640891330052803\n        hydro: 0.009581074962263243\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.017614043352437953\n        solar: 0.04407445165191308\n        unknown: 0.16938623534952593\n        wind: 0.010348198496418128\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 9.611613959626994e-05\n        biomass: 0.013602224638471305\n        coal: 0.5714850367691399\n        gas: 0.0\n        geothermal: 0.16417701925399986\n        hydro: 0.009659466777591344\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.017440264787535447\n        solar: 0.04405388209058178\n        unknown: 0.16920316027642165\n        wind: 0.010282827366182653\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 7.701337421764941e-05\n        biomass: 0.01013930836087358\n        coal: 0.5865495134400206\n        gas: 0.002342928523179701\n        geothermal: 0.15594028372132154\n        hydro: 0.01942170395091625\n        hydro discharge: 0.00024257361816170238\n        nuclear: 0.0\n        oil: 0.01504180640622207\n        solar: 0.03963252956663404\n        unknown: 0.16174668582148882\n        wind: 0.0088650700558212\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.00014913766508564357\n        biomass: 0.018266246961030574\n        coal: 0.5678768555241009\n        gas: 0.0037261092170626925\n        geothermal: 0.14837629468762742\n        hydro: 0.047211540443841286\n        hydro discharge: 0.0004752102353493213\n        nuclear: 0.0\n        oil: 0.02277502308039646\n        solar: 0.04010653633275602\n        unknown: 0.1408642231758758\n        wind: 0.010172876605430417\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2859\n    - datetime: '2021-01-01'\n      value: 0.2859\n    - datetime: '2022-01-01'\n      value: 0.2859\n    - datetime: '2023-01-01'\n      value: 0.2533\n    - datetime: '2024-01-01'\n      value: 0.2606\n    - datetime: '2025-01-01'\n      value: 0.2763\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2859\n    - datetime: '2021-01-01'\n      value: 0.2859\n    - datetime: '2022-01-01'\n      value: 0.2859\n    - datetime: '2023-01-01'\n      value: 0.2533\n    - datetime: '2024-01-01'\n      value: 0.2606\n    - datetime: '2025-01-01'\n      value: 0.2763\nparsers:\n  production: IEMOP.fetch_production\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Manila\nzone_name: Visayas\n"
  },
  {
    "path": "config/zones/PH.yaml",
    "content": "bounding_box:\n  - - 116.96336963369632\n    - 5.07480853775256\n  - - 126.58266582665826\n    - 18.64290487703049\ncenter_point:\n  - 122.49354924396717\n  - 11.176317324049073\ncentroid:\n  - 122.8426572175011\n  - 11.18654173327182\ncapacity:\n  battery storage: 156\n  biomass: 579\n  coal: 12473\n  gas: 3732\n  geothermal: 1952\n  hydro: 3034\n  hydro storage: 736\n  nuclear: 0\n  oil: 3834\n  solar: 1531\n  wind: 427\ncontributors:\n  - xomanuel\ncountry: PH\ncountry_name: Philippines\ncurrency: PHP\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 544.52\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 544.52\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 544.52\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 547.8\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 542.94\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 533.9\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 556.06\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 556.05\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 556.06\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 550.05\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 559.51\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 545.43\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 577.52\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 577.52\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 577.52\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 580.8\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 575.94\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 566.9\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 580.06\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 580.05\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 580.06\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 574.05\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 583.51\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 569.43\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 1.272972036029259e-05\n        biomass: 0.00789196651300694\n        coal: 0.60058174488414\n        gas: 0.14921320146498063\n        geothermal: 0.05957937548101499\n        hydro: 0.08008859087341884\n        hydro discharge: 0.0074732353982157225\n        nuclear: 0.0\n        oil: 0.012677421147728015\n        solar: 0.021337452135853315\n        unknown: 0.051634414421518664\n        wind: 0.009510041835263093\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 1.272972036029259e-05\n        biomass: 0.00789196651300694\n        coal: 0.60058174488414\n        gas: 0.14921320146498063\n        geothermal: 0.05957937548101499\n        hydro: 0.08008859087341884\n        hydro discharge: 0.0074732353982157225\n        nuclear: 0.0\n        oil: 0.012677421147728015\n        solar: 0.021337452135853315\n        unknown: 0.051634414421518664\n        wind: 0.009510041835263093\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 1.3300578404323148e-05\n        biomass: 0.007458465170360657\n        coal: 0.6039106815977704\n        gas: 0.15396352519484027\n        geothermal: 0.05938243857407482\n        hydro: 0.07637695433792842\n        hydro discharge: 0.007309902238880456\n        nuclear: 0.0\n        oil: 0.013016258785221767\n        solar: 0.021667935030871374\n        unknown: 0.04784007560110502\n        wind: 0.009060457420378224\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 1.3300497575728382e-05\n        biomass: 0.007458415280283161\n        coal: 0.6039111299925505\n        gas: 0.1539640820918178\n        geothermal: 0.05938242128380134\n        hydro: 0.07637660731099527\n        hydro discharge: 0.0073098981768682705\n        nuclear: 0.0\n        oil: 0.013016272393122806\n        solar: 0.021667939734554012\n        unknown: 0.04783952456439076\n        wind: 0.009060403386673374\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 1.3300497149230039e-05\n        biomass: 0.0074584150411190426\n        coal: 0.6039111109078491\n        gas: 0.15396407726696096\n        geothermal: 0.059382419379624136\n        hydro: 0.07637660491798089\n        hydro discharge: 0.007309897942466554\n        nuclear: 0.0\n        oil: 0.013016271975738524\n        solar: 0.02166797064276735\n        unknown: 0.047839523030352056\n        wind: 0.009060403096139352\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 1.306506802005823e-05\n        biomass: 0.007503450844692636\n        coal: 0.6034221756668612\n        gas: 0.1532195564315638\n        geothermal: 0.059386026309315554\n        hydro: 0.07712951257003922\n        hydro discharge: 0.0073520591954795884\n        nuclear: 0.0\n        oil: 0.012962295065992396\n        solar: 0.02161191327767193\n        unknown: 0.048306893304553844\n        wind: 0.009093011964637352\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 3.461297305828186e-05\n        biomass: 0.00744516132556792\n        coal: 0.6040014995262041\n        gas: 0.15625630493903678\n        geothermal: 0.05575488324019781\n        hydro: 0.08386567821371473\n        hydro discharge: 0.00892988361578852\n        nuclear: 0.0\n        oil: 0.011811070038675283\n        solar: 0.021163900778911664\n        unknown: 0.0403371629146604\n        wind: 0.010399800612539627\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 9.557677670278338e-05\n        biomass: 0.008253137539945636\n        coal: 0.5970143201508179\n        gas: 0.14385229387123766\n        geothermal: 0.06133333856978963\n        hydro: 0.07639293669113786\n        hydro discharge: 0.009462392847536688\n        nuclear: 0.0\n        oil: 0.013204871989751846\n        solar: 0.021186116587224194\n        unknown: 0.05981327473921477\n        wind: 0.009391697715065647\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.1856\n    - datetime: '2021-01-01'\n      value: 0.1856\n    - datetime: '2022-01-01'\n      value: 0.1856\n    - datetime: '2023-01-01'\n      value: 0.1825\n    - datetime: '2024-01-01'\n      value: 0.1896\n    - datetime: '2025-01-01'\n      value: 0.1965\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1697\n    - datetime: '2021-01-01'\n      value: 0.1697\n    - datetime: '2022-01-01'\n      value: 0.1697\n    - datetime: '2023-01-01'\n      value: 0.1765\n    - datetime: '2024-01-01'\n      value: 0.1686\n    - datetime: '2025-01-01'\n      value: 0.1827\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.1856\n    - datetime: '2021-01-01'\n      value: 0.1856\n    - datetime: '2022-01-01'\n      value: 0.1856\n    - datetime: '2023-01-01'\n      value: 0.1825\n    - datetime: '2024-01-01'\n      value: 0.1896\n    - datetime: '2025-01-01'\n      value: 0.1965\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1697\n    - datetime: '2021-01-01'\n      value: 0.1697\n    - datetime: '2022-01-01'\n      value: 0.1697\n    - datetime: '2023-01-01'\n      value: 0.1765\n    - datetime: '2024-01-01'\n      value: 0.1686\n    - datetime: '2025-01-01'\n      value: 0.1827\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\nsubZoneNames:\n  - PH-LU\n  - PH-MI\n  - PH-VI\ntimezone: Asia/Manila\nzone_name: Philippines\n"
  },
  {
    "path": "config/zones/PK.yaml",
    "content": "bounding_box:\n  - - 60.84600846008462\n    - 23.69605836020635\n  - - 77.049770497705\n    - 37.02230170071432\ncenter_point:\n  - 69.19541996790124\n  - 30.41085277986934\ncentroid:\n  - 69.40598196474166\n  - 29.868529783303504\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 430.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2480.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3140.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 5120.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 5150.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 6140.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 7790.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 8450.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 12690.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 16420.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 16150.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 16130.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 17390.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 7410.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 9910.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 9920.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10040.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 10640.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 11530.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1140.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2290.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3620.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 660.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 680.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 760.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 850.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1080.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1240.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1400.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4100.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3890.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 790.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1190.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1240.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1340.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1850.0\ncountry: PK\ncountry_name: Pakistan\ncurrency: PKR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Karachi\nzone_name: Pakistan\n"
  },
  {
    "path": "config/zones/PL.yaml",
    "content": "bounding_box:\n  - - 14.124741247412487\n    - 48.99330959841075\n  - - 24.129241292412956\n    - 54.83785188821257\ncenter_point:\n  - 19.17087591202222\n  - 52.06702570012759\ncentroid:\n  - 18.762998761473526\n  - 51.788526561557816\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 500.58\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 602.51\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 849.38\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 880.15\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 879.91\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 646.69\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 663.6\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 662.3\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 636.39\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 26307.89\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 28635.399999999998\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 30274.52\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 29962.769999999997\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 28521.47\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 26632.85\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 26567.88\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 26387.51\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 25482.87\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1595.87\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 2297.87\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 2377.93\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 2811.52\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2826.93\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 4091.59\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 4067.6600000000003\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 5435.99\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 5724.58\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 552.0699999999999\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 612.47\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 591.94\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 604.78\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 603.76\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 785.27\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 791.5799999999999\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 788.49\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 789.9200000000001\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1770.12\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1780.02\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1793.88\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1591.21\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1588.81\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1524.77\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 345.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 415.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 358.91\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 392.54\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 186.55\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 231.02\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 430.13\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1309.82\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 3472.78\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 6664.08\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 10643.2\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 14608.7\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 17705.36\n  unknown:\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1524.25\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1519.67\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1642.76\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1803.73\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 6026.06\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 5791.32\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 5807.67\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 5953.34\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 6570.27\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 7950.21\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 8977.73\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 9582.93\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 10292.56\ncontributors:\n  - corradio\n  - wojciej\n  - nessie2013\n  - filipc\n  - Pantkowsky\ncountry: PL\ncountry_name: Poland\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1012.451317\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1109.42\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1049.63\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 845.92\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 482.0973266\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 435.63\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 393.36\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 400.7\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 470.25\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1104.126726\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1201.095409\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1109.63\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 905.92\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 602.0973266\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 555.63\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 513.36\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 411.4\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 480.95\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 34.84\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.015546868058253565\n        coal: 0.8168785259232876\n        gas: 0.03013701389494425\n        geothermal: 1.382740951856205e-05\n        hydro: 0.017114882038897775\n        hydro discharge: 0.005649823374411959\n        nuclear: 0.018431176894942333\n        oil: 0.005444458830965293\n        solar: 0.004361801894090214\n        unknown: 0.007297093586502568\n        wind: 0.07912467799397827\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.016361473271779437\n        coal: 0.7938162440897208\n        gas: 0.04081513361608804\n        geothermal: 1.820149942373465e-05\n        hydro: 0.019096066707876246\n        hydro discharge: 0.005140470731968312\n        nuclear: 0.018628257699187908\n        oil: 0.010620293177632315\n        solar: 0.0036399358295157967\n        unknown: 0.006510904130815927\n        wind: 0.0853546496412601\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.011952251753006312\n        coal: 0.7770182990646345\n        gas: 0.04586575528535103\n        geothermal: 1.3093585653537256e-05\n        hydro: 0.022458911772492055\n        hydro discharge: 0.005241547340345336\n        nuclear: 0.01570419626478192\n        oil: 0.010711616883282834\n        solar: 0.0034902803399778125\n        unknown: 0.005384782231033652\n        wind: 0.1021592544915816\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.014982609169248404\n        coal: 0.7736214904623554\n        gas: 0.06361677155761138\n        geothermal: 1.2496175169754262e-05\n        hydro: 0.019378862658913115\n        hydro discharge: 0.00496288492361605\n        nuclear: 0.017725512139166868\n        oil: 0.009745998673573984\n        solar: 0.003879942362606787\n        unknown: 0.0026106161924470627\n        wind: 0.08946281912283592\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01882723005581452\n        coal: 0.7237414414087582\n        gas: 0.08221230648441313\n        geothermal: 2.0689189933025275e-05\n        hydro: 0.01876530745447322\n        hydro discharge: 0.007171985086506212\n        nuclear: 0.02071765603763473\n        oil: 0.010463506717425628\n        solar: 0.00551215441328297\n        unknown: 0.002770553144128706\n        wind: 0.10979716205795477\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.019963890379585344\n        coal: 0.6750578624498917\n        gas: 0.09495649555726321\n        geothermal: 2.6973545437511025e-05\n        hydro: 0.023903060970762523\n        hydro discharge: 0.008814885629358067\n        nuclear: 0.02431021181504897\n        oil: 0.010497939917238705\n        solar: 0.018199669680106858\n        unknown: 0.0036600253709854124\n        wind: 0.12060896676726428\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01570942526773333\n        coal: 0.7067024674432629\n        gas: 0.08238683216417944\n        geothermal: 1.7635301337557832e-05\n        hydro: 0.01987817093987146\n        hydro discharge: 0.006979766338107327\n        nuclear: 0.016424084496433553\n        oil: 0.012466108682665808\n        solar: 0.031569664528558534\n        unknown: 0.003841007073796216\n        wind: 0.104024818013678\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.013929223765980577\n        coal: 0.6831605341394914\n        gas: 0.060144750674265814\n        geothermal: 1.6927915756360214e-05\n        hydro: 0.020248256504228946\n        hydro discharge: 0.008434305993934339\n        nuclear: 0.015316883512920126\n        oil: 0.012657301941075744\n        solar: 0.05805724465964251\n        unknown: 0.0029657408370442843\n        wind: 0.12506880891600888\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.5401888483496926e-10\n        biomass: 0.0177051101130394\n        coal: 0.5914828912266213\n        gas: 0.0844769566816568\n        geothermal: 1.7690446682398137e-05\n        hydro: 0.025563759604678608\n        hydro discharge: 0.011214269379070607\n        nuclear: 0.013586887621014856\n        oil: 0.015419505659067037\n        solar: 0.08431432432938199\n        unknown: 0.0024374702793181573\n        wind: 0.1537811294520816\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.4423944412440079e-07\n        biomass: 0.019330132148357142\n        coal: 0.5323540428037986\n        gas: 0.10924667332180034\n        geothermal: 2.1527158200487364e-05\n        hydro: 0.02193925629972025\n        hydro discharge: 0.008321074847977731\n        nuclear: 0.012026788916253311\n        oil: 0.01227157495478754\n        solar: 0.10543720753977064\n        unknown: 0.021165400293021545\n        wind: 0.15788617303391778\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 0.4494\n    - datetime: '2025-01-01'\n      value: 0.3634\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 1.0\n    - datetime: '2024-01-01'\n      value: 0.448\n    - datetime: '2025-01-01'\n      value: 0.3533\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_storage/disk/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdDRG9JYTJWNVNTSWhORFJ0ZDJJMWVUbG9OMll6TVRaaGEza3lkamgxZG1aM056WnZZZ1k2QmtWVU9oQmthWE53YjNOcGRHbHZia2tpQVk1cGJteHBibVU3SUdacGJHVnVZVzFsUFNKWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtSWpzZ1ptbHNaVzVoYldVcVBWVlVSaTA0SnlkWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtQmpzR1ZEb1JZMjl1ZEdWdWRGOTBlWEJsU1NJVVlYQndiR2xqWVhScGIyNHZjR1JtQmpzR1ZBPT0iLCJleHAiOiIyMDIyLTExLTAyVDE1OjU0OjAzLjEyNFoiLCJwdXIiOiJibG9iX2tleSJ9fQ==--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Warsaw\nzone_name: Poland\n"
  },
  {
    "path": "config/zones/PM.yaml",
    "content": "bounding_box:\n  - - -56.39636396363959\n    - 46.89534216529384\n  - - -56.252362523625195\n    - 47.11429783873646\ncenter_point:\n  - -56.32436324363239\n  - 47.00482000201515\ncentroid:\n  - -56.30756307563072\n  - 47.02127745459418\ncapacity:\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: PM\ncountry_name: Saint Pierre and Miquelon\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Miquelon\nzone_name: Saint Pierre and Miquelon\n"
  },
  {
    "path": "config/zones/PR.yaml",
    "content": "bounding_box:\n  - - -67.2684726847268\n    - 17.92736346055132\n  - - -65.630456304563\n    - 18.522693919061993\ncenter_point:\n  - -66.4494644946449\n  - 18.225028689806656\ncentroid:\n  - -66.55326553265529\n  - 18.218231046350105\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1330.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1350.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1370.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1380.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1450.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 300.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 340.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 490.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 640.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 960.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3470.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 3610.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 3620.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3660.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 3760.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 4060.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\ncontributors:\n  - q--\n  - systemcatch\n  - veqtrus\ncountry: PR\ncountry_name: Puerto Rico\ncurrency: USD\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 995.611869962089\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1014.2941036716782\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1036.401437700579\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1026.7228249260704\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 480.12220481693174\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 527.7229942577874\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 546.0634245928852\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 544.6086048281159\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 786.0859157554912\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 769.7242211326042\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 807.9594211794373\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 755.5503294336717\n    unknown:\n      _comment: 'Source: https://indicadores.pr/dataset/generacion-consumo-costo-ingresos-y-clientes-del-sistema-electrico-de-puerto-rico/resource/fdad4f42-a4be-48bb-9478-a8fb75c000c6'\n      source: assumes 12% hydro, 57% solar, 31% wind based on average renewable generation\n        October 2019-September 2020\n      value: 0.0\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1055.611869962089\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1074.2941036716782\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1096.401437700579\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1086.7228249260704\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 600.1222048169318\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 647.7229942577874\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 666.0634245928852\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 664.6086048281159\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1030.0859157554912\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1013.7242211326042\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1051.9594211794374\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 999.5503294336717\n    unknown:\n      _comment: 'Source: https://indicadores.pr/dataset/generacion-consumo-costo-ingresos-y-clientes-del-sistema-electrico-de-puerto-rico/resource/fdad4f42-a4be-48bb-9478-a8fb75c000c6'\n      source: assumes 12% hydro, 57% solar, 31% wind based on average renewable generation\n        October 2019-September 2020\n      value: 31.939999999999998\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0005742682323169587\n        coal: 0.18427892687377626\n        gas: 0.3499544725964571\n        geothermal: 0.0\n        hydro: 0.0031429015858308127\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.44076215223572934\n        solar: 0.012578880283258412\n        unknown: 0.0008892857848935563\n        wind: 0.00781817985133559\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0005742682323169587\n        coal: 0.18427892687377628\n        gas: 0.3499544725964571\n        geothermal: 0.0\n        hydro: 0.0031429015858308127\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4407621522357294\n        solar: 0.012578880283258414\n        unknown: 0.0008892857848935564\n        wind: 0.00781817985133559\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0005742682323169587\n        coal: 0.18427892687377626\n        gas: 0.3499544725964571\n        geothermal: 0.0\n        hydro: 0.0031429015858308127\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.44076215223572934\n        solar: 0.012578880283258412\n        unknown: 0.0008892857848935563\n        wind: 0.00781817985133559\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0006837538305405383\n        coal: 0.18413403067386008\n        gas: 0.3496553838265327\n        geothermal: 0.0003086117043813385\n        hydro: 0.0032091144622262385\n        hydro discharge: 0.0\n        nuclear: 0.0003086117043813385\n        oil: 0.440393374785567\n        solar: 0.012457313839119685\n        unknown: 0.0010301965590700723\n        wind: 0.007816113220687029\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0006837538305405383\n        coal: 0.18413403067386008\n        gas: 0.3496553838265327\n        geothermal: 0.0003086117043813385\n        hydro: 0.0032091144622262385\n        hydro discharge: 0.0\n        nuclear: 0.0003086117043813385\n        oil: 0.440393374785567\n        solar: 0.012457313839119685\n        unknown: 0.0010301965590700723\n        wind: 0.007816113220687029\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.003056801711021606\n        coal: 0.20995060374384983\n        gas: 0.3142132207951985\n        geothermal: 0.0\n        hydro: 0.0033693584812000276\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4421993502836153\n        solar: 0.01723713584912138\n        unknown: 0.0008220597962560202\n        wind: 0.009151475705779812\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000588897955689813\n        coal: 0.1762597940083661\n        gas: 0.3587532208923845\n        geothermal: 0.0\n        hydro: 0.0030917180825297858\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.43894189064846695\n        solar: 0.012790315399735448\n        unknown: 0.0009000191751649909\n        wind: 0.008674031627125225\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  unknown:\n    _comment: 'Source: https://indicadores.pr/dataset/generacion-consumo-costo-ingresos-y-clientes-del-sistema-electrico-de-puerto-rico/resource/fdad4f42-a4be-48bb-9478-a8fb75c000c6'\n    source: assumes 12% hydro, 57% solar, 31% wind based on average renewable generation\n      October 2019-September 2020\n    value: 1\nisRenewable:\n  unknown:\n    _comment: 'Source: https://indicadores.pr/dataset/generacion-consumo-costo-ingresos-y-clientes-del-sistema-electrico-de-puerto-rico/resource/fdad4f42-a4be-48bb-9478-a8fb75c000c6'\n    source: assumes 12% hydro, 57% solar, 31% wind based on average renewable generation\n      October 2019-September 2020\n    value: 1\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: America/Puerto_Rico\nzone_name: Puerto Rico\n"
  },
  {
    "path": "config/zones/PS.yaml",
    "content": "bounding_box:\n  - - 34.198541985419865\n    - 31.212105398903503\n  - - 35.55935559355595\n    - 32.54301243355475\ncenter_point:\n  - 35.00855008550087\n  - 31.87612783339617\ncentroid:\n  - 34.998424984249866\n  - 31.786327385628027\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\ncountry: PS\ncountry_name: State of Palestine\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Gaza\nzone_name: State of Palestine\n"
  },
  {
    "path": "config/zones/PT-AC.yaml",
    "content": "bounding_box:\n  - - -28.46008460084596\n    - 37.706359294868406\n  - - -25.194851948519442\n    - 38.795413330749696\ncenter_point:\n  - -27.02007020070198\n  - 38.69380644960965\ncentroid:\n  - -27.140928552142633\n  - 38.39184797185544\ncountry: PT\ncountry_name: Portugal\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 372.109361\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 371.49\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1099.976527\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1118.213761\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 492.109361\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 491.49\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 32.0\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nhas_day_ahead_price_license: True\nhide_day_ahead_price: False\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021):\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37, https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Azores\nzone_name: Azores\n"
  },
  {
    "path": "config/zones/PT-MA.yaml",
    "content": "bounding_box:\n  - - -17.253172531725284\n    - 32.64748148036071\n  - - -16.691566915669114\n    - 32.84067766281008\ncenter_point:\n  - -16.9723697236972\n  - 32.744079571585395\ncentroid:\n  - -16.925569255692523\n  - 32.74880214493415\ncountry: PT\ncountry_name: Portugal\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 372.109361\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 371.49\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1099.976527\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"\n        value: 1118.213761\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 492.109361\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 491.49\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 27.0\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nhas_day_ahead_price_license: True\nhide_day_ahead_price: False\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook for 2022-2026\" Wind Europe Proceedings (2021):\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37, https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Atlantic/Madeira\nzone_name: Madeira\n"
  },
  {
    "path": "config/zones/PT.yaml",
    "content": "bounding_box:\n  - - -9.49149491494913\n    - 36.99940437538699\n  - - -6.204662046620427\n    - 42.15416473970289\ncenter_point:\n  - -7.949969732532391\n  - 39.48453516372834\ncentroid:\n  - -7.82466851755063\n  - 39.67677913177444\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 598.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 593.9\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 604.8\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 678.8\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 684.1\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 681.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 647.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 681.0\n    - datetime: '2024-03-01'\n      source: ren.pt\n      value: 700.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 687.1\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1756.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4657.1\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 4620.7\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4606.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 4606.2\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 4584.9\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 4519.5\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 4584.6\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 4432.7\n    - datetime: '2024-03-01'\n      source: ren.pt\n      value: 4434.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 4418.6\n  geothermal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 4359.4\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 4349.6\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4372.9\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 4372.1\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 4371.7\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 4489.8\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 4484.5\n    - datetime: '2024-03-01'\n      source: ren.pt\n      value: 4711.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 4644.5\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2559.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 2820.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2827.4\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 3707.4\n    - datetime: '2024-03-01'\n      source: ren.pt\n      value: 3585.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 3707.4\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 261.2\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 272.1\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 323.5\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 413.4\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 569.2\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1031.9\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1332.3\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1810.8\n    - datetime: '2024-03-01'\n      source: ren.pt\n      value: 2744.0\n    - datetime: '2024-07-01'\n      source: ren.pt\n      value: 3129.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 2588.6\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 100\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 150\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 100\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 5028.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 5072.8\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 5126.6\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 5180.8\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 5208.4\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 5353.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 5353.4\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 5357.8\n    - datetime: '2024-03-01'\n      source: ren.pt\n      value: 5374.0\n    - datetime: '2024-07-01'\n      source: ren.pt\n      value: 5380.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 5391.1\ncontributors:\n  - corradio\n  - nessie2013\n  - Musketeiro\n  - RGarrido03\ncountry: PT\ncountry_name: Portugal\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 372.109361\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 371.49\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 368.52\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 382.06\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 165.98\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 126.06\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 148.57\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 90.72\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 52.26\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 66.05\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1099.976527\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1118.213761\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 492.109361\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 491.49\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 488.52\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 502.06\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 176.68\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 136.76\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 159.27\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 101.42\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 62.96\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 76.75\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.051985274993538715\n        coal: 0.2801728001500567\n        gas: 0.20457495592228347\n        geothermal: 0.0\n        hydro: 0.15723514810918487\n        hydro discharge: 0.03268121926283023\n        nuclear: 0.02226016628036589\n        oil: 0.0010065367988757528\n        solar: 0.019701769722311305\n        unknown: 0.007078736889929003\n        wind: 0.22330339432466906\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.048249636226898304\n        coal: 0.22033441101983267\n        gas: 0.21812152605255355\n        geothermal: 0.0\n        hydro: 0.22145021586818972\n        hydro discharge: 0.046838794815913506\n        nuclear: 0.01018025083963601\n        oil: 0.0002527083376647851\n        solar: 0.01660919892366223\n        unknown: 0.007467842100440241\n        wind: 0.21049540679599393\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05052117329533785\n        coal: 0.2484571150664408\n        gas: 0.32201954372965\n        geothermal: 0.0\n        hydro: 0.08630366089447095\n        hydro discharge: 0.04092295710039871\n        nuclear: 0.014467492540619912\n        oil: 0.0005380535502229807\n        solar: 0.017811121903191337\n        unknown: 0.005884953404372062\n        wind: 0.21307392811316433\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.04389993977714783\n        coal: 0.20240756270073593\n        gas: 0.2622409945840562\n        geothermal: 5.288032158912966e-09\n        hydro: 0.18133538930717985\n        hydro discharge: 0.047985040979605216\n        nuclear: 0.014349072521267731\n        oil: 0.0005370958295816868\n        solar: 0.016837641411527764\n        unknown: 0.010171102702182473\n        wind: 0.22023619583196913\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05199072539189978\n        coal: 0.10087879585414483\n        gas: 0.3285145601684934\n        geothermal: 2.2579120132120922e-08\n        hydro: 0.13532544706053276\n        hydro discharge: 0.04857452372796824\n        nuclear: 0.0344858095406332\n        oil: 0.0013765081320482727\n        solar: 0.02776935593652228\n        unknown: 0.007478863739616342\n        wind: 0.2636059236279677\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.062368048976706024\n        coal: 0.04093691404960304\n        gas: 0.3269578206109625\n        geothermal: 6.582167010184953e-08\n        hydro: 0.2011023673079882\n        hydro discharge: 0.05679997824483418\n        nuclear: 0.030372350593738235\n        oil: 0.0009039553650597653\n        solar: 0.0357096006729426\n        unknown: 0.005089400624587102\n        wind: 0.23975959953064022\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.06755703494395461\n        coal: 0.01701567295248412\n        gas: 0.304954355104154\n        geothermal: 6.956455218060287e-08\n        hydro: 0.18831234953499904\n        hydro discharge: 0.057432212191005735\n        nuclear: 0.03771620664834096\n        oil: 0.0008890545355972688\n        solar: 0.05444142178601401\n        unknown: 0.005122097056518048\n        wind: 0.2665598081749529\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0656188682142167\n        coal: 0.006373863509585509\n        gas: 0.36225863123633767\n        geothermal: 3.215688846298021e-08\n        hydro: 0.11113519187864188\n        hydro discharge: 0.05332061132454662\n        nuclear: 0.044429386295496254\n        oil: 0.0009414353886064067\n        solar: 0.07885650582611983\n        unknown: 0.004405699563214314\n        wind: 0.2726599746936523\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 4.722594200743342e-09\n        biomass: 0.057134457632388\n        coal: 0.003673281388829696\n        gas: 0.22530829570153493\n        geothermal: 2.4990394312266853e-08\n        hydro: 0.19283990271498447\n        hydro discharge: 0.0762978639384113\n        nuclear: 0.051431270662144105\n        oil: 0.0003941530249125151\n        solar: 0.11294215850488329\n        unknown: 0.004017118911253699\n        wind: 0.2759614687915432\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 5.928610796062992e-07\n        biomass: 0.059060490344713806\n        coal: 0.0028228810646145144\n        gas: 0.12206883658283024\n        geothermal: 3.9718771835692946e-08\n        hydro: 0.22886013923945434\n        hydro discharge: 0.10010147945663161\n        nuclear: 0.05389089943743505\n        oil: 0.0002964784359691867\n        solar: 0.13810740495729207\n        unknown: 0.0050680810190587185\n        wind: 0.28972267240405203\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.6337\n    - datetime: '2021-01-01'\n      value: 0.6927\n    - datetime: '2022-01-01'\n      value: 0.6207\n    - datetime: '2023-01-01'\n      value: 0.7675\n    - datetime: '2024-01-01'\n      value: 0.8738\n    - datetime: '2025-01-01'\n      value: 0.832\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.5762\n    - datetime: '2021-01-01'\n      value: 0.6272\n    - datetime: '2022-01-01'\n      value: 0.5579\n    - datetime: '2023-01-01'\n      value: 0.6929\n    - datetime: '2024-01-01'\n      value: 0.8002\n    - datetime: '2025-01-01'\n      value: 0.7763\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Lisbon\nzone_name: Portugal\n"
  },
  {
    "path": "config/zones/PW.yaml",
    "content": "bounding_box:\n  - - 134.48834488344883\n    - 7.367403236151802\n  - - 134.64674646746468\n    - 7.719449613059552\ncenter_point:\n  - 134.56754567545676\n  - 7.543426424605677\ncentroid:\n  - 134.5759457594576\n  - 7.519098016445388\ncapacity:\n  oil:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 32.0\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 31.36\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 29.48\n    - datetime: '2020-01-01'\n      source: IRENA.org\n      value: 30.14\n  solar:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 2.1\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 2.5\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 2.62\n    - datetime: '2020-01-01'\n      source: IRENA.org\n      value: 2.92\n    - datetime: '2021-01-01'\n      source: IRENA.org\n      value: 4.34\n    - datetime: '2023-01-01'\n      source: IRENA.org\n      value: 19.62\ncountry: PW\ncountry_name: Palau\ncurrency: USD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: IRENA.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Palau\nzone_name: Palau\n"
  },
  {
    "path": "config/zones/PY.yaml",
    "content": "bounding_box:\n  - - -62.649626496264915\n    - -27.581070627523566\n  - - -54.24354243542432\n    - -19.286514527697086\ncenter_point:\n  - -58.43454198060172\n  - -23.382062451230716\ncentroid:\n  - -57.36531365313649\n  - -24.127653089170177\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 8800.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 8820.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: PY\ncountry_name: Paraguay\ncurrency: PYG\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Asuncion\nzone_name: Paraguay\n"
  },
  {
    "path": "config/zones/QA.yaml",
    "content": "_comment: Capacity calculations are available at https://docs.google.com/spreadsheets/d/1ownS3qse6zDG4gNnKEZDroIKLNiqZcULqp34LJUxrL0/edit?usp=sharing\nbounding_box:\n  - - 50.75150751507516\n    - 24.56758780547797\n  - - 51.59031590315905\n    - 26.160382998560593\ncenter_point:\n  - 51.18039101269935\n  - 25.139696266063734\ncentroid:\n  - 51.208969232549485\n  - 25.374514082861765\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 11320.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 12580.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 810.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1680.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\ncontributors:\n  - q--\n  - nessie2013\ncountry: QA\ncountry_name: Qatar\ncurrency: QAR\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002103842882819217\n        coal: 0.0\n        gas: 0.9541947132627357\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.04370130358143594\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.002111288787109396\n        coal: 0.0\n        gas: 0.9575688741718116\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.04031975933657447\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0020966688086712336\n        coal: 0.0\n        gas: 0.9509359282014922\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.04696731182387401\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: GCCIA.fetch_consumption\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Qatar\nzone_name: Qatar\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/RE.yaml",
    "content": "bounding_box:\n  - - 55.22635226352264\n    - -21.363015718319623\n  - - 55.82035820358203\n    - -20.875016472280834\ncenter_point:\n  - 55.52335523355234\n  - -21.11901609530023\ncentroid:\n  - 55.515898016123025\n  - -21.12872701452387\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: oer.energies-reunion.com\n      value: 115.0\n    - datetime: '2024-11-01'\n      source: reunion.edf.fr\n      value: 377.0\n  coal:\n    - datetime: '2017-01-01'\n      source: oer.energies-reunion.com\n      value: 211.0\n    - datetime: '2025-05-01'\n      source: reunion.edf.fr\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: oer.energies-reunion.com\n      value: 175\n    - datetime: '2020-01-01'\n      source: oer.energies-reunion.com\n      value: 150\n    - datetime: '2025-04-12'\n      source: reunion.edf.fr\n      value: 121.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: reunion.edf.fr\n      value: 138.0\n  oil:\n    - datetime: '2022-10-10'\n      source: reunion.edf.fr\n      value: 221.0\n    - datetime: '2025-05-01'\n      source: reunion.edf.fr\n      value: 0.0\n  solar:\n    - datetime: '2022-10-10'\n      source: reunion.edf.fr\n      value: 189.0\n    - datetime: '2025-04-12'\n      source: reunion.edf.fr\n      value: 210.0\n  wind:\n    - datetime: '2022-10-10'\n      source: reunion.edf.fr\n      value: 15.0\ncontributors:\n  - PETILLON-Sebastien\n  - VIKTORVAV99\n  - PaulRoms\ncountry: RE\ncountry_name: \"R\\xE9union\"\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 424.87\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 385.68\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 418.01\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 333.46\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 316.59\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 11.86\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 457.87\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 418.68\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 451.01\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 366.46\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 349.59\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 44.86\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010967952051930251\n        coal: 0.0\n        gas: 0.512305143104541\n        geothermal: 0.0\n        hydro: 0.29748690682373163\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.16741668872105242\n        unknown: 0.0\n        wind: 0.011818729647010884\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008387059655277527\n        coal: 0.0\n        gas: 0.5547664171086977\n        geothermal: 0.0\n        hydro: 0.2656481886479585\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.16237078860745494\n        unknown: 0.0\n        wind: 0.008825539481428401\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007436237299219415\n        coal: 0.0\n        gas: 0.4818155621278134\n        geothermal: 0.0\n        hydro: 0.35342691438857804\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.14977818908728702\n        unknown: 0.0\n        wind: 0.0075428385416383545\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0859186455260277\n        coal: 0.1462839720269014\n        gas: 0.30449600125458054\n        geothermal: 0.0\n        hydro: 0.18773551658133647\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.15789045757920134\n        solar: 0.11221847673266214\n        unknown: 0.0\n        wind: 0.005457035402375885\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0573605554696287\n        coal: 0.3298914414325319\n        gas: 0.1260505336965511\n        geothermal: 0.0\n        hydro: 0.16009704545773817\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.23994995609810063\n        solar: 0.0818280278419744\n        unknown: 0.0\n        wind: 0.004822394574461891\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07244806657826934\n        coal: 0.2876557932915034\n        gas: 0.10735120698421882\n        geothermal: 0.0\n        hydro: 0.1396053191576842\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.30910372106431394\n        solar: 0.082156022159244\n        unknown: 0.0\n        wind: 0.0016797036868118804\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0050966096232612935\n        coal: 0.23371262254790723\n        gas: 0.039188368394060355\n        geothermal: 0.0\n        hydro: 0.22259703471750042\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4411935310412872\n        solar: 0.05755179444914436\n        unknown: 0.0\n        wind: 0.000660010683614674\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0012798024908306364\n        biomass: 0.14521826951218264\n        coal: 0.19498700882417805\n        gas: 0.038066401186034673\n        geothermal: 0.0\n        hydro: 0.13453840041601056\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.414856209979389\n        solar: 0.064625175344868\n        unknown: 0.0\n        wind: 0.006428662904947167\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.001062669516077509\n        biomass: 0.19260900530792546\n        coal: 0.2083215249355114\n        gas: 0.046419555318433746\n        geothermal: 0.0\n        hydro: 0.13704939087690707\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.33769285053114045\n        solar: 0.0663331354651612\n        unknown: 0.0\n        wind: 0.010511245973335337\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.1048\n    - datetime: '2021-01-01'\n      value: 0.1605\n    - datetime: '2022-01-01'\n      value: 0.1354\n    - datetime: '2023-01-01'\n      value: 0.3501\n    - datetime: '2024-01-01'\n      value: 0.4024\n    - datetime: '2025-01-01'\n      value: 0.9679\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.1048\n    - datetime: '2021-01-01'\n      value: 0.1605\n    - datetime: '2022-01-01'\n      value: 0.1354\n    - datetime: '2023-01-01'\n      value: 0.3501\n    - datetime: '2024-01-01'\n      value: 0.4024\n    - datetime: '2025-01-01'\n      value: 0.9679\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  price: FR_O.fetch_price\n  production: FR_O.fetch_production\nregion: Africa\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Indian/Reunion\nzone_name: \"R\\xE9union\"\n"
  },
  {
    "path": "config/zones/RO.yaml",
    "content": "_comment: Biomass includes 19.227 MW of biogas and 6.03 MW of waste incineration\nbounding_box:\n  - - 20.241202412024137\n    - 43.65393954864322\n  - - 29.658896588965916\n    - 48.259164105103125\ncenter_point:\n  - 24.810578337505376\n  - 45.93705795182545\ncentroid:\n  - 24.914428091649352\n  - 45.74171993159395\ncapacity:\n  battery storage:\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 137.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 115.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 116.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 115.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 117.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 116.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 118.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 119.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 5854.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 5805.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 4128.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 4103.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 3469.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2673.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1909.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 2162.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 5020.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 5142.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 3033.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 2666.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2184.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2218.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1988.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 2238.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 2179.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 6481.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 6490.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 6143.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 6140.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 6134.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 6137.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 6136.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 6139.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 6132.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1300.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1210.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1211.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1150.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1163.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1145.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 1160.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1185.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1293.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1588.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2985.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 2987.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 2968.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 2972.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2957.0\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 2958.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 3027.0\ncontributors:\n  - corradio\n  - mzaharie\ncountry: RO\ncountry_name: Romania\ncurrency: EUR\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 262.12\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1169.308063\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1085.6\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 997.65\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 985.64\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 687.5901733\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 568.48\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 580.66\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 615.54\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 295.12\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1259.7512649999999\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1176.0432019999998\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1057.65\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1045.64\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 807.5901733\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 688.48\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 700.66\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 735.54\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 29.78\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008343004654539637\n        coal: 0.28259947355011633\n        gas: 0.14521389124044334\n        geothermal: 2.097521317109146e-09\n        hydro: 0.26406067699178526\n        hydro discharge: 3.620146999887294e-05\n        nuclear: 0.17983065189704023\n        oil: 9.467337258215224e-06\n        solar: 0.019114259047798038\n        unknown: 0.0001730720772648546\n        wind: 0.10061930400606996\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007118263077933529\n        coal: 0.26778204770859715\n        gas: 0.15099766120006777\n        geothermal: 2.9723386552215157e-07\n        hydro: 0.2754458659234173\n        hydro discharge: 0.0003275050271993969\n        nuclear: 0.18024869935429486\n        oil: 2.8169085990147912e-05\n        solar: 0.01876467588804454\n        unknown: 0.0007186219169696636\n        wind: 0.09856905585252346\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006825461658403413\n        coal: 0.2769614582031134\n        gas: 0.16643141549110033\n        geothermal: 7.19458618157404e-07\n        hydro: 0.22737266111279983\n        hydro discharge: 0.0003172582802437034\n        nuclear: 0.19046004414685266\n        oil: 3.7604162065188636e-05\n        solar: 0.021585301918429913\n        unknown: 0.0007776767534847649\n        wind: 0.10923025411836389\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005629121491768453\n        coal: 0.25330752627142844\n        gas: 0.16622902882714669\n        geothermal: 1.5787247438637024e-06\n        hydro: 0.27428823860507096\n        hydro discharge: 0.00014201412207653802\n        nuclear: 0.1858189423317555\n        oil: 2.166486783985229e-05\n        solar: 0.02095126475912896\n        unknown: 0.00035211214133912255\n        wind: 0.09325844101256922\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007939680325985582\n        coal: 0.24124503162848848\n        gas: 0.15704571956665747\n        geothermal: 3.025848038454537e-06\n        hydro: 0.25322754692033106\n        hydro discharge: 0.0005412169482152949\n        nuclear: 0.21125627170826994\n        oil: 0.00011296072762035609\n        solar: 0.022497155900622564\n        unknown: 0.0016879231078663034\n        wind: 0.10444337756958293\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.009178605038773888\n        coal: 0.18494705223261437\n        gas: 0.1774233019987814\n        geothermal: 7.281616647929219e-06\n        hydro: 0.2634703311253282\n        hydro discharge: 0.0008700097597341459\n        nuclear: 0.22675730155853777\n        oil: 0.00010352560817544724\n        solar: 0.02370092396059369\n        unknown: 0.0031934081759993375\n        wind: 0.11034818114410436\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010254024328423213\n        coal: 0.19741885679880353\n        gas: 0.17627324614414494\n        geothermal: 8.061389155275626e-06\n        hydro: 0.28074116804363736\n        hydro discharge: 0.00047002991698797146\n        nuclear: 0.20899170220993504\n        oil: 8.171681139932798e-05\n        solar: 0.022524077025743154\n        unknown: 0.0026666646102456496\n        wind: 0.10057037544166018\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01026442842960388\n        coal: 0.2062854169467022\n        gas: 0.1833072644339845\n        geothermal: 8.282640780515759e-06\n        hydro: 0.23832785208485235\n        hydro discharge: 0.00037671975987348875\n        nuclear: 0.22142248753268332\n        oil: 0.00010971761319203803\n        solar: 0.025473342798958302\n        unknown: 0.0021829663529330766\n        wind: 0.11224143699355767\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007309794590782469\n        coal: 0.1529650807308\n        gas: 0.1659886326152533\n        geothermal: 1.2816300180651534e-05\n        hydro: 0.31004192456027624\n        hydro discharge: 0.0007384114123891665\n        nuclear: 0.2123262462571042\n        oil: 9.488372767638713e-05\n        solar: 0.028655667129813312\n        unknown: 0.001926687996269789\n        wind: 0.11993978443345205\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.852505843018783e-10\n        biomass: 0.009527281569653618\n        coal: 0.1537033114098622\n        gas: 0.18758661602949392\n        geothermal: 3.560534755340531e-05\n        hydro: 0.2589887557591431\n        hydro discharge: 0.0014326302066822157\n        nuclear: 0.23342462380239914\n        oil: 0.0001758194770550697\n        solar: 0.0460041571694597\n        unknown: 0.003559105732333226\n        wind: 0.10556203829169036\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.6649\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.4207\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Bucharest\nzone_name: Romania\n"
  },
  {
    "path": "config/zones/RS.yaml",
    "content": "bounding_box:\n  - - 18.847988479884833\n    - 42.24575404101222\n  - - 22.980829808298097\n    - 46.164058837652135\ncenter_point:\n  - 20.877631204867136\n  - 44.38562057509567\ncentroid:\n  - 20.800230409857956\n  - 44.25770501704859\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 6.31\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 8.31\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2.38\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 34.78\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 5644.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 5668.2\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 5600.5\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 5282.5\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 5660.5\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 6010.5\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 6120.5\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 3.41\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 286.41\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 296.53\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 485.71\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 608.11\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 606.71\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 608.71\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 2363.69\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 2406.9700000000003\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 2326.68\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 2476.88\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2509.7200000000003\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 2524.67\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2535.9100000000003\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 2537.29\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 2539.44\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 642.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 639.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 642.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 3.9\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2.9\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 29.13\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 72.87\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 230\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 150\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 100\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 16.58\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 24.82\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 398.32\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 397.32\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 429.32\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 533.32\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 645.62\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 740.22\ncontributors:\n  - corradio\n  - nessie2013\ncountry: RS\ncountry_name: Serbia\ncurrency: EUR\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 539.32\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 442.29\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 553.89\n  lifecycle:\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 550.02\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 452.99\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 564.59\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 29.7\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0024308075448872942\n        coal: 0.6531465461942026\n        gas: 0.019090553342236916\n        geothermal: 3.0349570369057083e-05\n        hydro: 0.24702955969883023\n        hydro discharge: 0.01576109477652933\n        nuclear: 0.04024767806974018\n        oil: 0.0002759661088924902\n        solar: 0.0026821933938443064\n        unknown: 0.009102453459639046\n        wind: 0.01020265594451302\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0032050881982968946\n        coal: 0.6144854599351764\n        gas: 0.021046261298713967\n        geothermal: 8.098456632087447e-05\n        hydro: 0.2867675467412427\n        hydro discharge: 0.018191075291845167\n        nuclear: 0.034161865200321655\n        oil: 0.0007537794466538831\n        solar: 0.00265853990548581\n        unknown: 0.010161887813164244\n        wind: 0.008487494420623326\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004615042821076827\n        coal: 0.634872606458578\n        gas: 0.015404734276185383\n        geothermal: 6.460189071976539e-05\n        hydro: 0.2729573780978788\n        hydro discharge: 0.019281289259310833\n        nuclear: 0.029338567448209698\n        oil: 0.0002979746884225345\n        solar: 0.001967700330971023\n        unknown: 0.013224794342023822\n        wind: 0.007975300266192515\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.006413507089308437\n        coal: 0.6538838444561859\n        gas: 0.01682720468001057\n        geothermal: 0.00011583155323048236\n        hydro: 0.2562482582733608\n        hydro discharge: 0.018453421093468866\n        nuclear: 0.025233030554939626\n        oil: 0.00032792921895540824\n        solar: 0.003285746112540722\n        unknown: 0.010343722796729694\n        wind: 0.00886749534156807\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007884588609340814\n        coal: 0.5825165799548563\n        gas: 0.018083632057969996\n        geothermal: 3.826224135596702e-05\n        hydro: 0.30149974622268266\n        hydro discharge: 0.01770161749098713\n        nuclear: 0.03804996986564936\n        oil: 0.00013236023789282698\n        solar: 0.003947319187991911\n        unknown: 0.0209261404445041\n        wind: 0.009219707705946724\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.008319258943239028\n        coal: 0.6015673851406608\n        gas: 0.040138856830588016\n        geothermal: 5.336400901613953e-05\n        hydro: 0.24347290534947738\n        hydro discharge: 0.01580919202771036\n        nuclear: 0.047539411750004194\n        oil: 0.0006790516858786803\n        solar: 0.005947705397153975\n        unknown: 0.007388803691251162\n        wind: 0.029084027984076118\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007596851168707055\n        coal: 0.5594584168911445\n        gas: 0.027032461593412067\n        geothermal: 2.2147343221472073e-05\n        hydro: 0.3175217548842282\n        hydro discharge: 0.015890637612823187\n        nuclear: 0.026817248608030513\n        oil: 0.000516615312829788\n        solar: 0.007249676411635486\n        unknown: 0.006299439233580199\n        wind: 0.031594593850617254\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.3227300845351798e-09\n        biomass: 0.008378913348839185\n        coal: 0.5775744021896316\n        gas: 0.041731301640769713\n        geothermal: 4.3455651467234254e-05\n        hydro: 0.27746786498488635\n        hydro discharge: 0.009698803531882868\n        nuclear: 0.028403841027956744\n        oil: 0.00025597472595924797\n        solar: 0.01441557250678779\n        unknown: 0.006567137148345253\n        wind: 0.03546266393241745\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 0.2672\n    - datetime: '2023-01-01'\n      value: 0.3901\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.2583\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 0.2049\n    - datetime: '2023-01-01'\n      value: 0.3771\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.2188\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\ntimezone: Europe/Belgrade\nzone_name: Serbia\n"
  },
  {
    "path": "config/zones/RU-1.yaml",
    "content": "bounding_box:\n  - - 27.351273512735133\n    - 41.196770324453766\n  - - 86.02826028260282\n    - 73.57931266863486\ncenter_point:\n  - 56.65602626579258\n  - 57.08926254837107\ncentroid:\n  - 54.97928733931799\n  - 60.76254150004456\ncapacity:\n  hydro: 19500\n  nuclear: 27914\n  unknown: 125014\ncontributors:\n  - denplis\n  - systemcatch\n  - alixunderplatz\ncountry: RU\ncountry_name: Russia\ncurrency: RUB\nemissionFactors:\n  direct:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on estimated 2021 fuel consumption: 6.7% * 820 g/kWh (coal) + 0.5% * 650 g/kWh (oil) + 89.0% * 490 g/kWh (gas) + 3.8% * 700 g/kWh (other)= 517 g/kWh, Source: https://minenergo.gov.ru/node/11323 2018-06-26 Table 7.3., p.80, Sum of zones Northwest, Central, Volga, South, Ural'\n      source: assumes 89% gas, 7% coal, <1% oil, 4% other\n      value: 401.56\n  lifecycle:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on estimated 2021 fuel consumption: 6.7% * 820 g/kWh (coal) + 0.5% * 650 g/kWh (oil) + 89.0% * 490 g/kWh (gas) + 3.8% * 700 g/kWh (other)= 517 g/kWh, Source: https://minenergo.gov.ru/node/11323 2018-06-26 Table 7.3., p.80, Sum of zones Northwest, Central, Volga, South, Ural'\n      source: assumes 89% gas, 7% coal, <1% oil, 4% other\n      value: 518.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0001555323728381133\n        coal: 0.0015685079812309613\n        gas: 9.713488385023156e-05\n        geothermal: 0.0\n        hydro: 0.07080931578326138\n        hydro discharge: 2.055608360371507e-08\n        nuclear: 0.2530895393428489\n        oil: 1.7353194747742208e-06\n        solar: 0.0017623859518725075\n        unknown: 0.6723505771919459\n        wind: 0.00016525531749523665\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00010091754622259062\n        coal: 0.0013953335795884876\n        gas: 0.0005276604436479455\n        geothermal: 9.609538306031548e-09\n        hydro: 0.07019318307858129\n        hydro discharge: 9.559876609359551e-10\n        nuclear: 0.2528500127066764\n        oil: 4.7922866855572654e-05\n        solar: 0.00010330731672814381\n        unknown: 0.6746596370058938\n        wind: 0.00012494142923394198\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.3838440517482894e-05\n        coal: 0.0017971955405015419\n        gas: 0.001211102127561818\n        geothermal: 1.2201529414462902e-11\n        hydro: 0.07243697808729829\n        hydro discharge: 5.088647842301753e-07\n        nuclear: 0.24816429651197636\n        oil: 9.142987898127724e-05\n        solar: 0.0010564614933571508\n        unknown: 0.6751642925765683\n        wind: 5.126543352357192e-05\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00018255150407965192\n        coal: 0.0019643198868352575\n        gas: 0.0009586789928692324\n        geothermal: 0.0\n        hydro: 0.07592793241494589\n        hydro discharge: 8.525023318481684e-07\n        nuclear: 0.26245011700248627\n        oil: 4.8370769350601976e-05\n        solar: 0.0017189183478561272\n        unknown: 0.656469884158579\n        wind: 0.00028500830359695124\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0001597624349976184\n        coal: 0.002581768847775627\n        gas: 0.0011727970839133907\n        geothermal: 2.7921412009077015e-07\n        hydro: 0.06785572158679697\n        hydro discharge: 1.0420392783959713e-06\n        nuclear: 0.2503715538641578\n        oil: 6.876898395715103e-05\n        solar: 0.0018460972310444443\n        unknown: 0.6756844413872789\n        wind: 0.0002652023981784694\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00030312363217324954\n        coal: 0.001018101604636719\n        gas: 0.00045355273102733667\n        geothermal: 1.0646321082974101e-07\n        hydro: 0.07342504341273776\n        hydro discharge: 6.281533322539725e-07\n        nuclear: 0.2607911794376539\n        oil: 3.5805975233138535e-05\n        solar: 0.001972757144188094\n        unknown: 0.6616054039527748\n        wind: 0.0003952258949258648\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00017372914134364503\n        coal: 0.0027128772028695573\n        gas: 0.0015563903262295307\n        geothermal: 1.261806391035584e-07\n        hydro: 0.06961245855297223\n        hydro discharge: 2.727712788986674e-07\n        nuclear: 0.25492878839549776\n        oil: 7.249256616039562e-05\n        solar: 0.00237980548628417\n        unknown: 0.6681685424080399\n        wind: 0.0004092520025620557\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.529546694656989e-05\n        coal: 0.007424009054518622\n        gas: 0.002688711204816861\n        geothermal: 4.80101908775185e-07\n        hydro: 0.07450745278622957\n        hydro discharge: 1.6274499223796437e-06\n        nuclear: 0.2441131755510679\n        oil: 0.00012114000193701839\n        solar: 0.0022832634472736636\n        unknown: 0.6684971552103295\n        wind: 0.0003232508531472728\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: RU.fetch_production\nregion: Europe\nsources:\n  IEA 2015:\n    link: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\ntimezone: Europe/Moscow\nzone_name: Europe-Ural\nisLowCarbon:\n  unknown:\n    value: 0\nisRenewable:\n  unknown:\n    value: 0\n"
  },
  {
    "path": "config/zones/RU-2.yaml",
    "content": "bounding_box:\n  - - 70.42930429304295\n    - 49.08489889972009\n  - - 122.13662136621363\n    - 81.28855588978138\ncenter_point:\n  - 96.28234095583527\n  - 64.51080518966556\ncentroid:\n  - 96.36043869909395\n  - 66.9201086169314\ncapacity:\n  hydro: 25286\n  unknown: 26570\ncontributors:\n  - denplis\n  - systemcatch\n  - alixunderplatz\ncountry: RU\ncountry_name: Russia\ncurrency: RUB\nemissionFactors:\n  direct:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on estimated 2021 fuel consumption: 86.0% * 760 g/kWh (coal) + 0.3% * 406 g/kWh (oil) + 9.1% * 370 g/kWh (gas) + 4.7% * 575 g/kWh (other)= 715.5 g/kWh, Source: https://minenergo.gov.ru/node/11323 2018-06-26 Table 7.3., p.80, Siberian zone'\n      source: assumes 86% coal, 9% gas, <1% oil, 5% other\n      value: 715.5\n  lifecycle:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on estimated 2021 fuel consumption: 86.0% * 820 g/kWh (coal) + 0.3% * 650 g/kWh (oil) + 9.1% * 490 g/kWh (gas) + 4.7% * 700 g/kWh (other)= 784 g/kWh, Source: https://minenergo.gov.ru/node/11323 2018-06-26 Table 7.3., p.80, Siberian zone'\n      source: assumes 86% coal, 9% gas, <1% oil, 5% other\n      value: 784\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.177675976143623e-08\n        coal: 0.008644606154192304\n        gas: 0.0023025743182051284\n        geothermal: 0.0\n        hydro: 0.5461400989128982\n        hydro discharge: 0.0\n        nuclear: 0.0002546289612190563\n        oil: 9.175666383994496e-05\n        solar: 6.625073473403332e-05\n        unknown: 0.44246344136227794\n        wind: 5.93450071309506e-05\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.2651251270102735e-07\n        coal: 0.003068174207249747\n        gas: 0.000825130229534839\n        geothermal: 0.0\n        hydro: 0.48286279454238695\n        hydro discharge: 1.5009865299465667e-09\n        nuclear: 0.0012407960413398258\n        oil: 3.333343127043019e-05\n        solar: 0.000503122361185514\n        unknown: 0.5113924654521764\n        wind: 8.315021902611039e-05\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.212602669809118e-07\n        coal: 0.0011908712947079126\n        gas: 0.000319375552352663\n        geothermal: 0.0\n        hydro: 0.3826025230519994\n        hydro discharge: 7.440738411347627e-10\n        nuclear: 0.0006116598340412039\n        oil: 1.2766818966190258e-05\n        solar: 0.0009312781261754248\n        unknown: 0.614265704607007\n        wind: 7.290904834322812e-05\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.07842622582998e-07\n        coal: 0.003882695739011686\n        gas: 0.001035416556417683\n        geothermal: 0.0\n        hydro: 0.43318996574517016\n        hydro discharge: 7.490916598635058e-10\n        nuclear: 0.0005978543099396769\n        oil: 4.126912797330477e-05\n        solar: 0.0014729318825180847\n        unknown: 0.5597268542734414\n        wind: 7.092464529867389e-05\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.238854971816193e-08\n        coal: 0.013909468396332286\n        gas: 0.0037037839147522917\n        geothermal: 0.0\n        hydro: 0.4786656487390226\n        hydro discharge: 5.706519439046443e-11\n        nuclear: 4.91317628055245e-05\n        oil: 0.00014755661172111535\n        solar: 0.003161378100767039\n        unknown: 0.5002866471168002\n        wind: 9.086616446221312e-05\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.752166887288214e-07\n        coal: 0.011659111962814142\n        gas: 0.0031123493839631694\n        geothermal: 0.0\n        hydro: 0.4995404405030733\n        hydro discharge: 1.745510450561699e-09\n        nuclear: 0.0016781233613828365\n        oil: 0.00012392041982508715\n        solar: 0.0028857905932059454\n        unknown: 0.4808111144594904\n        wind: 0.00020861267416186333\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.0453927642340418e-06\n        coal: 0.0006927400001755594\n        gas: 0.00019304234506121385\n        geothermal: 4.30947631393372e-11\n        hydro: 0.508783856764474\n        hydro discharge: 1.3617945152030551e-08\n        nuclear: 0.002947662061329146\n        oil: 7.837860045966954e-06\n        solar: 0.0024366412571999395\n        unknown: 0.48459049819521227\n        wind: 0.00035014701905574535\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: RU.fetch_production\nregion: Europe\nsources:\n  IEA 2015:\n    link: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\ntimezone: Europe/Moscow\nzone_name: Siberia\nisLowCarbon:\n  unknown:\n    value: 0\nisRenewable:\n  unknown:\n    value: 0\n"
  },
  {
    "path": "config/zones/RU-AS.yaml",
    "content": "bounding_box:\n  - - 105.54045540455402\n    - 42.29441085733281\n  - - 162.84582845828456\n    - 76.7377124809739\ncenter_point:\n  - 133.62717028148467\n  - 59.363876837914646\ncentroid:\n  - 133.87039029402146\n  - 64.52594981083477\ncontributors:\n  - JeanBaptisteScellier\ncountry: RU\ncountry_name: Russia\nemissionFactors:\n  direct:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on estimated 2021 fuel consumption: 59.6% * 760 g/kWh (coal) + 0.3% * 406 g/kWh (oil) + 40.1% * 370 g/kWh (gas) = 602.5 g/kWh, Source: https://minenergo.gov.ru/node/11323 2018-06-26 Table 7.3., p.80, Extreme East zone'\n      source: assumes 60% coal, 40% gas, <1% oil\n      value: 602.5\n  lifecycle:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on estimated 2021 fuel consumption: 59.6% * 820 g/kWh (coal) + 0.3% * 650 g/kWh (oil) + 40.1% * 490 g/kWh (gas) = 687 g/kWh, Source: https://minenergo.gov.ru/node/11323 2018-06-26 Table 7.3., p.80, Extreme East zone'\n      source: assumes 60% coal, 40% gas, <1% oil\n      value: 687\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.4611166445604393\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.5388833384110678\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.42492744254245113\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.575072561586696\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00012849397816715088\n        coal: 0.002788675319302609\n        gas: 0.00170255828164373\n        geothermal: 2.2610388100990278e-05\n        hydro: 0.381245734752958\n        hydro discharge: 0.0\n        nuclear: 0.0007485427985507015\n        oil: 0.0002201591381808626\n        solar: 0.00016120186972724132\n        unknown: 0.6126318585565093\n        wind: 0.0003501697657526562\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0003039259231162928\n        coal: 0.0065960315340739244\n        gas: 0.00402704404435321\n        geothermal: 5.347159743513013e-05\n        hydro: 0.3571421316152572\n        hydro discharge: 0.0\n        nuclear: 0.0017705220239168712\n        oil: 0.0005207337209316853\n        solar: 0.00038128775981619397\n        unknown: 0.6283766030237664\n        wind: 0.0008282519218127808\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: RU.fetch_production\nregion: Europe\nsources:\n  IEA 2015:\n    link: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\ntimezone: Europe/Moscow\nzone_name: East\nisLowCarbon:\n  unknown:\n    value: 0\nisRenewable:\n  unknown:\n    value: 0\n"
  },
  {
    "path": "config/zones/RU-EU.yaml",
    "content": "bounding_box:\n  - - 35.883358833588346\n    - 59.2327072682276\n  - - 68.9388893888939\n    - 81.8581268572988\ncenter_point:\n  - 50.97546444155109\n  - 67.79153796298\ncentroid:\n  - 53.95683641700646\n  - 72.46044658205832\ncountry: RU\ncountry_name: Russia\nemissionFactors:\n  direct:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on 2015-TWh production: 22.7% * 820 g/kWh (coal) + 1.4% * 650 g/kWh (oil) + 75.8% * 490 g/kWh (gas)  = 567 g/kWh; 2015 production'\n      _url: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\n      source: IEA 2015; assumes 76% gas, 23% coal, 1% oil\n      value: 460.06\n  lifecycle:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on 2015-TWh production: 22.7% * 820 g/kWh (coal) + 1.4% * 650 g/kWh (oil) + 75.8% * 490 g/kWh (gas)  = 567 g/kWh; 2015 production'\n      _url: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\n      source: IEA 2015; assumes 76% gas, 23% coal, 1% oil\n      value: 567.5\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\nsources:\n  IEA 2015:\n    link: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\ntimezone: Europe/Moscow\nzone_name: Arctic\nisLowCarbon:\n  unknown:\n    value: 0\nisRenewable:\n  unknown:\n    value: 0\n"
  },
  {
    "path": "config/zones/RU-FE.yaml",
    "content": "bounding_box:\n  - - -180\n    - 43.709751779128595\n  - - 180\n    - 71.6001251106535\ncenter_point:\n  - 163.5623195535538\n  - 69.34548604297066\ncentroid:\n  - 99.73379349674866\n  - 60.634325034061945\ncountry: RU\ncountry_name: Russia\nemissionFactors:\n  direct:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on 2015-TWh production: 22.7% * 820 g/kWh (coal) + 1.4% * 650 g/kWh (oil) + 75.8% * 490 g/kWh (gas)  = 567 g/kWh; 2015 production'\n      _url: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\n      source: IEA 2015; assumes 76% gas, 23% coal, 1% oil\n      value: 460.06\n  lifecycle:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on 2015-TWh production: 22.7% * 820 g/kWh (coal) + 1.4% * 650 g/kWh (oil) + 75.8% * 490 g/kWh (gas)  = 567 g/kWh; 2015 production'\n      _url: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\n      source: IEA 2015; assumes 76% gas, 23% coal, 1% oil\n      value: 567.5\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\nsources:\n  IEA 2015:\n    link: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\ntimezone: Asia/Kamchatka\nzone_name: Far East\nisLowCarbon:\n  unknown:\n    value: 0\nisRenewable:\n  unknown:\n    value: 0\n"
  },
  {
    "path": "config/zones/RU-KGD.yaml",
    "content": "bounding_box:\n  - - 19.611196111961135\n    - 54.33228446013542\n  - - 22.80802808028082\n    - 55.28291864926261\ncenter_point:\n  - 21.775124854502042\n  - 54.71360467089119\ncentroid:\n  - 21.262060192899234\n  - 54.846283273128954\ncountry: RU\ncountry_name: Russia\nemissionFactors:\n  direct:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on 2015-TWh production: 22.7% * 820 g/kWh (coal) + 1.4% * 650 g/kWh (oil) + 75.8% * 490 g/kWh (gas)  = 567 g/kWh; 2015 production'\n      _url: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\n      source: IEA 2015; assumes 76% gas, 23% coal, 1% oil\n      value: 460.06\n  lifecycle:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on 2015-TWh production: 22.7% * 820 g/kWh (coal) + 1.4% * 650 g/kWh (oil) + 75.8% * 490 g/kWh (gas)  = 567 g/kWh; 2015 production'\n      _url: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\n      source: IEA 2015; assumes 76% gas, 23% coal, 1% oil\n      value: 567.5\nfallbackZoneMixes:\n  _comment: see http://www.centrumbalticum.org/files/1899/BSR_Policy_Briefing_2_2014.pdf and https://newsbase.com/topstories/russia-invest-us156bn-kaliningrad-power-plants. About 98% generation from gas in RU-KGD in the past. 5.1 MW wind (2002) and 1.7 MW total hydro installed. 3 gas units (1x440 + 2x156 MW) may come online in 2018, 3x65 MW coal units of Primorskaya TPP probably in 2019 due to future seperation of Baltics from BRELL synchronous area.\n  _source: Energy security in Kaliningrad and geopolitics (2/2014)\n  powerOriginRatios:\n    value:\n      gas: 0.98\n      hydro: 0.005\n      wind: 0.015\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\nsources:\n  IEA 2015:\n    link: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\ntimezone: Europe/Kaliningrad\nzone_name: Kaliningrad\nisLowCarbon:\n  unknown:\n    value: 0\nisRenewable:\n  unknown:\n    value: 0\n"
  },
  {
    "path": "config/zones/RU.yaml",
    "content": "bounding_box:\n  - - -180\n    - 41.196770324453766\n  - - 180\n    - 81.8581268572988\ncenter_point:\n  - 21.687780666148868\n  - 54.69528449606483\ncentroid:\n  - 84.39350790706435\n  - 65.2797034536478\nbypassedSubZones:\n  - RU-1\n  - RU-2\n  - RU-AS\n  - RU-EU\n  - RU-FE\n  - RU-KGD\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 41640.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 41240.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 40670.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 40140.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 38840.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 38360.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 37550.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 37310.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 108590.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 109850.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 110680.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 109940.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 109440.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 110260.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 110820.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 111680.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 47230.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 47290.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 48650.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 48700.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 48740.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 48890.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 51620.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 49100.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 27960.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 27950.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 28020.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 27910.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 540.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 830.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1430.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1770.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1990.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2150.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2190.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2550.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1040.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2050.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2280.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2530.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2570.0\ncontributors:\n  - denplis\n  - systemcatch\n  - alixunderplatz\n  - JeanBaptisteScellier\n  - aekrylov\ncountry: RU\ncountry_name: Russia\ncurrency: RUB\nemissionFactors:\n  direct:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on 2015-TWh production: 22.7% * 820 g/kWh (coal) + 1.4% * 650 g/kWh (oil) + 75.8% * 490 g/kWh (gas)  = 567 g/kWh; 2015 production'\n      _url: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\n      source: IEA 2015; assumes 76% gas, 23% coal, 1% oil\n      value: 460.06\n  lifecycle:\n    unknown:\n      _comment: 'Assumes weighted average emission factor based on 2015-TWh production: 22.7% * 820 g/kWh (coal) + 1.4% * 650 g/kWh (oil) + 75.8% * 490 g/kWh (gas)  = 567 g/kWh; 2015 production'\n      _url: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\n      source: IEA 2015; assumes 76% gas, 23% coal, 1% oil\n      value: 567.5\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.16747177244844316\n        hydro discharge: 0.0\n        nuclear: 0.20127674294052017\n        oil: 0.0\n        solar: 2.1080366515653556e-05\n        unknown: 0.6312303936946662\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.15953863405821522\n        hydro discharge: 0.0\n        nuclear: 0.19914772033089612\n        oil: 0.0\n        solar: 0.0009334124862336848\n        unknown: 0.640380218633763\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.1561175202216843\n        hydro discharge: 0.0\n        nuclear: 0.18869217320727238\n        oil: 0.0\n        solar: 0.0013765121198867185\n        unknown: 0.6538137847236439\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.16503883619817564\n        hydro discharge: 0.0\n        nuclear: 0.1839291662814617\n        oil: 0.0\n        solar: 0.001815565056483761\n        unknown: 0.6492164264563226\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.16780032075341333\n        hydro discharge: 0.0\n        nuclear: 0.19816748668236175\n        oil: 0.0\n        solar: 0.0020428248510963045\n        unknown: 0.6319893573224264\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.17166990487663167\n        hydro discharge: 0.0\n        nuclear: 0.19333188004437157\n        oil: 0.0\n        solar: 0.002289276607717642\n        unknown: 0.6327089276344565\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.17622762721165375\n        hydro discharge: 0.0\n        nuclear: 0.18627943313791046\n        oil: 0.0\n        solar: 0.0021536301209946376\n        unknown: 0.635339299328092\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: RU.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  IEA 2015:\n    link: https://www.iea.org/statistics/statisticssearch/report/?country=Russia&product=electricityandheat\nsubZoneNames:\n  - RU-1\n  - RU-2\n  - RU-AS\n  - RU-EU\n  - RU-FE\n  - RU-KGD\ntimezone: Europe/Moscow\nzone_name: Russia\nisLowCarbon:\n  unknown:\n    value: 0\nisRenewable:\n  unknown:\n    value: 0\n"
  },
  {
    "path": "config/zones/RW.yaml",
    "content": "bounding_box:\n  - - 28.859688596885974\n    - -2.826199783010381\n  - - 30.886508865088672\n    - -1.0602435671398\ncenter_point:\n  - 29.97222616568311\n  - -1.9592036155313746\ncentroid:\n  - 29.916232495658303\n  - -2.0213481971410356\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\ncountry: RW\ncountry_name: Rwanda\ncurrency: RWF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Kigali\nzone_name: Rwanda\n"
  },
  {
    "path": "config/zones/SA.yaml",
    "content": "bounding_box:\n  - - 34.64854648546486\n    - 16.370345338292665\n  - - 55.66653168245267\n    - 32.155267833754806\ncenter_point:\n  - 45.21936963272702\n  - 24.524262432832636\ncentroid:\n  - 43.41838500024943\n  - 23.38588736990934\ncontributors:\n  - q--\ncountry: SA\ncountry_name: Saudi Arabia\ncurrency: SAR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: GCCIA.fetch_consumption\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Riyadh\nzone_name: Saudi Arabia\n"
  },
  {
    "path": "config/zones/SB.yaml",
    "content": "bounding_box:\n  - - 156.45936459364592\n    - -11.844883796313773\n  - - 166.14706147061466\n    - -6.60282737918741\ncenter_point:\n  - 161.3950139501395\n  - -9.413474063117569\ncentroid:\n  - 159.4844485030216\n  - -8.918144880617279\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\ncountry: SB\ncountry_name: Solomon Islands\ncurrency: SBD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Guadalcanal\nzone_name: Solomon Islands\n"
  },
  {
    "path": "config/zones/SC.yaml",
    "content": "bounding_box:\n  - - 55.20826687574969\n    - -4.802634091088595\n  - - 55.856329489439965\n    - -4.275717804997701\ncenter_point:\n  - 55.46681685600321\n  - -4.57926331668171\ncentroid:\n  - 55.55254076336677\n  - -4.510572017234428\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\ncontributors:\n  - VIKTORVAV99\ncountry: SC\ncountry_name: Seychelles\ncurrency: SCR\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Indian/Mahe\nzone_name: Seychelles\n"
  },
  {
    "path": "config/zones/SD.yaml",
    "content": "bounding_box:\n  - - 21.81081810818111\n    - 8.689723773805298\n  - - 38.60138601386015\n    - 22.2027018585931\ncenter_point:\n  - 30.254414578262065\n  - 15.349649136996366\ncentroid:\n  - 30.076084492010274\n  - 13.377774092734752\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 810.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1320.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1480.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1190.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1340.0\ncountry: SD\ncountry_name: Sudan\ncurrency: SDG\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Khartoum\nzone_name: Sudan\n"
  },
  {
    "path": "config/zones/SE-SE1.yaml",
    "content": "bounding_box:\n  - - 15.37203343028456\n    - 64.15555442943908\n  - - 24.161641616416176\n    - 69.05991811650836\ncenter_point:\n  - 19.789837583855636\n  - 66.48761378536409\ncentroid:\n  - 20.34192165786262\n  - 66.5871066990157\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      value: 271\n  coal:\n    - datetime: '2017-01-01'\n      value: 0\n  gas:\n    - datetime: '2017-01-01'\n      value: 1\n  geothermal:\n    - datetime: '2017-01-01'\n      value: 0\n  hydro:\n    - datetime: '2017-01-01'\n      value: 5271\n  nuclear:\n    - datetime: '2017-01-01'\n      value: 0\n  oil:\n    - datetime: '2017-01-01'\n      value: 0\n  solar:\n    - datetime: '2017-01-01'\n      value: 19\n  wind:\n    - datetime: '2017-01-01'\n      source: energimyndigheten.se\n      value: 520.97\n    - datetime: '2018-01-01'\n      source: energimyndigheten.se\n      value: 830.22\n    - datetime: '2019-01-01'\n      source: energimyndigheten.se\n      value: 1254.37\n    - datetime: '2020-01-01'\n      source: energimyndigheten.se\n      value: 1648.07\n    - datetime: '2021-01-01'\n      source: energimyndigheten.se\n      value: 1947.37\n    - datetime: '2022-01-01'\n      source: energimyndigheten.se\n      value: 2872.0\n    - datetime: '2023-01-01'\n      source: energimyndigheten.se\n      value: 2999.87\n    - datetime: '2024-01-01'\n      source: energimyndigheten.se\n      value: 3066.87\ncountry: SE\ncountry_name: Sweden\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 447.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 346.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 312.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 373.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 597.49\n    unknown:\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for SE for\n          the sources in unknown\n        datetime: '2022-01-01'\n        source: Eurostat 2022; assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01%\n          coal\n        value: 28.6\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1153.629975\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1171.867209\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 567.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 466.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 432.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 617.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 841.49\n    solar:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 45.0\n    unknown:\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for SE for\n          the sources in unknown\n        datetime: '2022-01-01'\n        source: Eurostat 2022; assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01%\n          coal\n        value: 258\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0006596211766759616\n        coal: 0.0010239382579686066\n        gas: 0.005411544806178828\n        geothermal: 0.0\n        hydro: 0.7542900418120051\n        hydro discharge: 3.5123972389267287e-09\n        nuclear: 0.002765854767779047\n        oil: 1.2995869784028895e-06\n        solar: 0.00014996812243100674\n        unknown: 0.007313697580508553\n        wind: 0.22838418000519947\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0013595862671193946\n        coal: 0.0020230055243639555\n        gas: 0.0040686746277505985\n        geothermal: 0.0\n        hydro: 0.7426271017444591\n        hydro discharge: 1.998316984130682e-09\n        nuclear: 0.006430061161988353\n        oil: 4.079231070272099e-06\n        solar: 0.00015904338434431548\n        unknown: 0.008683376715407339\n        wind: 0.23464515793723265\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0013071692458709492\n        coal: 0.0015077016894436911\n        gas: 0.0033345619668297927\n        geothermal: 0.0\n        hydro: 0.7409705995358608\n        hydro discharge: 1.3374313039862462e-08\n        nuclear: 0.00650537285709342\n        oil: 2.355885241971773e-06\n        solar: 0.00019170138467252055\n        unknown: 0.008753382896232618\n        wind: 0.23742709836663933\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00017628284119234342\n        coal: 0.0002396789976860653\n        gas: 0.0024911118504167655\n        geothermal: 0.0\n        hydro: 0.7574487904131226\n        hydro discharge: 1.0171246327066873e-05\n        nuclear: 0.0010033112499844314\n        oil: 2.954985098479193e-07\n        solar: 0.0001785874168723214\n        unknown: 0.007362356317250164\n        wind: 0.23108950954117313\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 7.840069513076767e-05\n        coal: 5.1066054009689775e-05\n        gas: 7.956431366646658e-05\n        geothermal: 0.0\n        hydro: 0.7701541866983959\n        hydro discharge: 1.2023870914513197e-06\n        nuclear: 0.00033924452804296037\n        oil: 2.2811642949964295e-07\n        solar: 1.404657817116028e-07\n        unknown: 0.008350744661614963\n        wind: 0.22094498890663905\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.820192487880282e-05\n        coal: 8.100653607290969e-05\n        gas: 0.003040226240754237\n        geothermal: 0.0\n        hydro: 0.795966673419169\n        hydro discharge: 2.5118585928423596e-07\n        nuclear: 0.0005552960369919065\n        oil: 4.7436178461951024e-07\n        solar: 9.26288515692159e-05\n        unknown: 0.007110420219485841\n        wind: 0.1930546631028393\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0013020530053160018\n        coal: 0.0005797423613093825\n        gas: 0.0030127353101237096\n        geothermal: 0.0\n        hydro: 0.7466163080705286\n        hydro discharge: 3.2882488846273674e-07\n        nuclear: 0.010303424064308264\n        oil: 9.818433289309889e-07\n        solar: 0.00044348659020333877\n        unknown: 0.007638724426271847\n        wind: 0.23010227571109548\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0023984145019600774\n        coal: 0.0005883725069820578\n        gas: 0.0014512366223256934\n        geothermal: 0.0\n        hydro: 0.668940593040512\n        hydro discharge: 1.1716138986065957e-07\n        nuclear: 0.012812572173607165\n        oil: 8.4780564788934e-07\n        solar: 0.0009392238205526635\n        unknown: 0.006938947891641582\n        wind: 0.30592955546892997\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: SE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  Eurostat 2022:\n    link: https://doi.org/10.2908/NRG_BAL_C\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Stockholm\nzone_name: North Sweden\nisLowCarbon:\n  unknown:\n    - _comment: Sum of renewable sources in unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\nisRenewable:\n  unknown:\n    - _comment: Sum of renewable sources in unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\n"
  },
  {
    "path": "config/zones/SE-SE2.yaml",
    "content": "bounding_box:\n  - - 11.9732519005652\n    - 60.773964411045505\n  - - 21.00968239056497\n    - 66.34475494001927\ncenter_point:\n  - 16.187922232125675\n  - 63.628415727059114\ncentroid:\n  - 16.575893602085152\n  - 63.37094981421646\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      value: 680\n  coal:\n    - datetime: '2017-01-01'\n      value: 0\n  gas:\n    - datetime: '2017-01-01'\n      value: 2\n  geothermal:\n    - datetime: '2017-01-01'\n      value: 0\n  hydro:\n    - datetime: '2017-01-01'\n      value: 8077\n  nuclear:\n    - datetime: '2017-01-01'\n      value: 0\n  oil:\n    - datetime: '2017-01-01'\n      value: 0\n  solar:\n    - datetime: '2017-01-01'\n      value: 145\n  wind:\n    - datetime: '2017-01-01'\n      source: energimyndigheten.se\n      value: 2346.6\n    - datetime: '2018-01-01'\n      source: energimyndigheten.se\n      value: 2561.15\n    - datetime: '2019-01-01'\n      source: energimyndigheten.se\n      value: 3148.24\n    - datetime: '2020-01-01'\n      source: energimyndigheten.se\n      value: 3944.74\n    - datetime: '2021-01-01'\n      source: energimyndigheten.se\n      value: 5167.7\n    - datetime: '2022-01-01'\n      source: energimyndigheten.se\n      value: 5969.0\n    - datetime: '2023-01-01'\n      source: energimyndigheten.se\n      value: 6823.35\n    - datetime: '2024-01-01'\n      source: energimyndigheten.se\n      value: 7075.25\ncountry: SE\ncountry_name: Sweden\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 447.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 346.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 312.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 373.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 597.49\n    unknown:\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for SE for\n          the sources in unknown\n        datetime: '2022-01-01'\n        source: Eurostat 2022; assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01%\n          coal\n        value: 28.6\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1153.629975\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1171.867209\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 567.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 466.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 432.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 617.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 841.49\n    solar:\n      datetime: '2014-01-01'\n      source: IPCC 2014\n      value: 45.0\n    unknown:\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for SE for\n          the sources in unknown\n        datetime: '2022-01-01'\n        source: Eurostat 2022; assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01%\n          coal\n        value: 258\n    wind:\n      datetime: '2014-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.231123466713303e-05\n        coal: 0.0002969472346707056\n        gas: 0.000658218813533247\n        geothermal: 1.3553190190860343e-09\n        hydro: 0.6892612183449582\n        hydro discharge: 6.399816408124254e-06\n        nuclear: 0.028115852707700402\n        oil: 6.630672414375242e-06\n        solar: 0.0005365161351223912\n        unknown: 0.02216987390857723\n        wind: 0.2588657718142423\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00011994947947777691\n        coal: 0.0004113980156303095\n        gas: 0.0008577359625291733\n        geothermal: 2.8151417918955017e-08\n        hydro: 0.6835361089349843\n        hydro discharge: 4.476075449113847e-06\n        nuclear: 0.038860728661191654\n        oil: 9.444646033688974e-06\n        solar: 0.0005347785651755493\n        unknown: 0.023489736149870363\n        wind: 0.2521755760699977\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.274868101454147e-05\n        coal: 0.00012514424334486433\n        gas: 0.0014403331736496834\n        geothermal: 3.9883687680222423e-10\n        hydro: 0.7015622448441082\n        hydro discharge: 1.15662694272645e-08\n        nuclear: 0.00176563290594399\n        oil: 1.0413630853306075e-06\n        solar: 0.0006697444323488742\n        unknown: 0.01756861206745104\n        wind: 0.2767846390784711\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00013838749785221506\n        coal: 0.00022971978018822403\n        gas: 0.001184633513350402\n        geothermal: 2.207800288532415e-09\n        hydro: 0.6972707579804347\n        hydro discharge: 2.1342069455813343e-08\n        nuclear: 0.0030930259094872114\n        oil: 6.211278145071192e-07\n        solar: 0.0007243093609916819\n        unknown: 0.01816698623300225\n        wind: 0.279191627774621\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.38864560274077e-05\n        coal: 0.00011083315369754615\n        gas: 0.0010860539437394677\n        geothermal: 3.829227255995929e-09\n        hydro: 0.7047524712640333\n        hydro discharge: 4.680166646217247e-08\n        nuclear: 0.002402727779137936\n        oil: 1.5465823417272446e-06\n        solar: 0.0007813095727376778\n        unknown: 0.01928733775863541\n        wind: 0.27149358884457503\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.29633226147639e-05\n        coal: 2.558184678928465e-05\n        gas: 0.0007302219401250339\n        geothermal: 0.0\n        hydro: 0.713048238525453\n        hydro discharge: 0.0005523113910137212\n        nuclear: 0.0001400947976946217\n        oil: 3.076237767772655e-08\n        solar: 0.0007998057059944876\n        unknown: 0.01862767219664254\n        wind: 0.2660328583151507\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.478618824640477e-05\n        coal: 6.402077693847329e-06\n        gas: 2.0396698743610792e-05\n        geothermal: 0.0\n        hydro: 0.68411206481959\n        hydro discharge: 0.0005438267989009649\n        nuclear: 4.7877756279878155e-05\n        oil: 2.0553063224613734e-08\n        solar: 1.2090037190949257e-08\n        unknown: 0.02388449231663931\n        wind: 0.2913600550116036\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.886933278861103e-05\n        coal: 1.3667993521841735e-05\n        gas: 0.0009246100155225964\n        geothermal: 0.0\n        hydro: 0.7449401893594743\n        hydro discharge: 0.00019154073018231134\n        nuclear: 0.00013045995340340888\n        oil: 1.1454207583441956e-07\n        solar: 0.00048507944340917577\n        unknown: 0.017100766081630567\n        wind: 0.23617465534277235\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00031129851297193414\n        coal: 0.0001520447297578595\n        gas: 0.0009559016456568319\n        geothermal: 5.583003644697138e-09\n        hydro: 0.7154805643001112\n        hydro discharge: 6.596039656027432e-05\n        nuclear: 0.002862114256695787\n        oil: 6.587944300742622e-07\n        solar: 0.0009977713814902382\n        unknown: 0.020194946162792278\n        wind: 0.2589786609596068\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0004314545036449216\n        coal: 0.00011846328359988772\n        gas: 0.0005723486598281637\n        geothermal: 6.916917753663174e-10\n        hydro: 0.6712519195743689\n        hydro discharge: 5.431232989353861e-05\n        nuclear: 0.002741142687955049\n        oil: 3.935726201834346e-07\n        solar: 0.0013529000025004657\n        unknown: 0.014809349860570501\n        wind: 0.30866761246294394\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: SE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  Eurostat 2022:\n    link: https://doi.org/10.2908/NRG_BAL_C\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Stockholm\nzone_name: North Central Sweden\nisLowCarbon:\n  unknown:\n    - _comment: Sum of renewable sources in unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\nisRenewable:\n  unknown:\n    - _comment: Sum of renewable sources in unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\n"
  },
  {
    "path": "config/zones/SE-SE3.yaml",
    "content": "bounding_box:\n  - - 11.118711187111899\n    - 56.92056161758078\n  - - 19.373529599638907\n    - 62.26429740073408\ncenter_point:\n  - 15.211910518135229\n  - 59.44008750997199\ncentroid:\n  - 14.868951874699498\n  - 58.967141148938694\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      value: 2561\n  gas:\n    - datetime: '2017-01-01'\n      value: 950\n  hydro:\n    - datetime: '2017-01-01'\n      value: 2593\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 9076.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 8603.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 8586.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 7710.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 6871.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 6900.0\n  solar:\n    - datetime: '2017-01-01'\n      value: 1130\n  wind:\n    - datetime: '2017-01-01'\n      source: energimyndigheten.se\n      value: 2115.89\n    - datetime: '2018-01-01'\n      source: energimyndigheten.se\n      value: 2278.19\n    - datetime: '2019-01-01'\n      source: energimyndigheten.se\n      value: 2625.69\n    - datetime: '2020-01-01'\n      source: energimyndigheten.se\n      value: 2839.95\n    - datetime: '2021-01-01'\n      source: energimyndigheten.se\n      value: 3078.82\n    - datetime: '2022-01-01'\n      source: energimyndigheten.se\n      value: 3254.0\n    - datetime: '2023-01-01'\n      source: energimyndigheten.se\n      value: 3969.16\n    - datetime: '2024-01-01'\n      source: energimyndigheten.se\n      value: 4233.36\ncountry: SE\ncountry_name: Sweden\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 447.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 346.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 312.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 373.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 597.49\n    unknown:\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for SE for\n          the sources in unknown\n        datetime: '2022-01-01'\n        source: Eurostat 2022; assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01%\n          coal\n        value: 28.6\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1153.629975\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1171.867209\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 567.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 466.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 432.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 617.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 841.49\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 37.66666667\n    unknown:\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for SE for\n          the sources in unknown\n        datetime: '2022-01-01'\n        source: Eurostat 2022; assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01%\n          coal\n        value: 258\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0008265774220178043\n        coal: 0.003678571505163534\n        gas: 0.002302002305497604\n        geothermal: 4.248682154734612e-07\n        hydro: 0.3250646275054976\n        hydro discharge: 2.4554913578338443e-05\n        nuclear: 0.45564866344503013\n        oil: 6.78476864559356e-05\n        solar: 0.004879413021654606\n        unknown: 0.05459842788473321\n        wind: 0.1529088273284083\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0016753116016516019\n        coal: 0.008818374775262485\n        gas: 0.0038564531834406517\n        geothermal: 1.559590831983078e-06\n        hydro: 0.3030231370090399\n        hydro discharge: 3.558090879730497e-05\n        nuclear: 0.47334388019098\n        oil: 0.00014299025822922577\n        solar: 0.005585459927482594\n        unknown: 0.05589790085557276\n        wind: 0.14762234318559755\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001645483904794532\n        coal: 0.002370263796314717\n        gas: 0.0019796937891512845\n        geothermal: 8.209050555297472e-07\n        hydro: 0.34671299326141075\n        hydro discharge: 1.8544632349245866e-05\n        nuclear: 0.427200802840825\n        oil: 0.00032751148872558724\n        solar: 0.007189399302902068\n        unknown: 0.04772464078169215\n        wind: 0.16482981000602576\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0017021177783986198\n        coal: 0.003682948124312501\n        gas: 0.002557135319484972\n        geothermal: 1.0795648768892006e-06\n        hydro: 0.33156424857974404\n        hydro discharge: 2.5906588983944718e-05\n        nuclear: 0.4434706709593872\n        oil: 5.0541093835898906e-05\n        solar: 0.007568904362876376\n        unknown: 0.049078411863825354\n        wind: 0.1602980206541435\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0013851105736540556\n        coal: 0.0024250066742577936\n        gas: 0.0022794615638391867\n        geothermal: 1.032465341547176e-06\n        hydro: 0.3277202032638838\n        hydro discharge: 1.8612708181876857e-05\n        nuclear: 0.44526531815003584\n        oil: 9.615906730741486e-05\n        solar: 0.00792042160066271\n        unknown: 0.05034274614885329\n        wind: 0.16254586392904297\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0009766737054057863\n        coal: 0.001425607570792751\n        gas: 0.0015266073206996016\n        geothermal: 6.738579306702626e-07\n        hydro: 0.38471018151785236\n        hydro discharge: 0.0014392881785257993\n        nuclear: 0.3880566268610894\n        oil: 4.6830016436074294e-05\n        solar: 0.007309504302209839\n        unknown: 0.04576764352669368\n        wind: 0.16874032582541806\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0008115737219900107\n        coal: 0.001421793315843166\n        gas: 0.0012757582055920344\n        geothermal: 5.192634334636818e-07\n        hydro: 0.3230170156229668\n        hydro discharge: 0.0012830420035360546\n        nuclear: 0.41793077754527236\n        oil: 3.0266283429278092e-05\n        solar: 0.0005404940928425192\n        unknown: 0.07945762454238671\n        wind: 0.17423112549577366\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000952666902292815\n        coal: 0.0015041968651867152\n        gas: 0.0010561985308332623\n        geothermal: 5.800827482502393e-07\n        hydro: 0.37415446493739074\n        hydro discharge: 0.0003284357614798548\n        nuclear: 0.3941413762998981\n        oil: 3.68573208860839e-05\n        solar: 0.004638739094211139\n        unknown: 0.05357150844086794\n        wind: 0.16961495339220453\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001310951949179141\n        coal: 0.001303260622613743\n        gas: 0.0011420801591377422\n        geothermal: 9.332634286555663e-07\n        hydro: 0.3722150171277094\n        hydro discharge: 0.00041386578678747797\n        nuclear: 0.3871655380209428\n        oil: 6.130142258132387e-05\n        solar: 0.007791872453475923\n        unknown: 0.04663995636539186\n        wind: 0.18195518460974716\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0015070913086330578\n        coal: 0.0010428259940675417\n        gas: 0.0008858901377702544\n        geothermal: 7.329267542928376e-07\n        hydro: 0.34798420367658317\n        hydro discharge: 0.0003374887319241673\n        nuclear: 0.39821036282751215\n        oil: 5.285412493574413e-05\n        solar: 0.01062997963303864\n        unknown: 0.03717101809816512\n        wind: 0.2021775270304475\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: SE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  Eurostat 2022:\n    link: https://doi.org/10.2908/NRG_BAL_C\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Stockholm\nzone_name: South Central Sweden\nisLowCarbon:\n  unknown:\n    - _comment: Sum of renewable sources in unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\nisRenewable:\n  unknown:\n    - _comment: Sum of renewable sources in unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\n"
  },
  {
    "path": "config/zones/SE-SE4.yaml",
    "content": "bounding_box:\n  - - 12.352274438535977\n    - 55.34588629391277\n  - - 17.199686739075773\n    - 57.46626135885869\ncenter_point:\n  - 14.569042728056864\n  - 56.5010914354608\ncentroid:\n  - 14.59343189672335\n  - 56.78591947279688\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      value: 883\n  coal:\n    - datetime: '2017-01-01'\n      value: 0\n  gas:\n    - datetime: '2017-01-01'\n      value: 582\n  geothermal:\n    - datetime: '2017-01-01'\n      value: 0\n  hydro:\n    - datetime: '2017-01-01'\n      value: 345\n  nuclear:\n    - datetime: '2017-01-01'\n      value: 0\n  oil:\n    - datetime: '2017-01-01'\n      value: 662\n  solar:\n    - datetime: '2017-01-01'\n      value: 1091\n  wind:\n    - datetime: '2017-01-01'\n      source: energimyndigheten.se\n      value: 1627.49\n    - datetime: '2018-01-01'\n      source: energimyndigheten.se\n      value: 1630.66\n    - datetime: '2019-01-01'\n      source: energimyndigheten.se\n      value: 1652.93\n    - datetime: '2020-01-01'\n      source: energimyndigheten.se\n      value: 1649.2\n    - datetime: '2021-01-01'\n      source: energimyndigheten.se\n      value: 1921.89\n    - datetime: '2022-01-01'\n      source: energimyndigheten.se\n      value: 2183.0\n    - datetime: '2023-01-01'\n      source: energimyndigheten.se\n      value: 2431.34\n    - datetime: '2024-01-01'\n      source: energimyndigheten.se\n      value: 2443.88\ncountry: SE\ncountry_name: Sweden\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 447.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 346.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 312.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 373.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 597.49\n    unknown:\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for SE for\n          the sources in unknown\n        datetime: '2022-01-01'\n        source: Eurostat 2022; assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01%\n          coal\n        value: 28.6\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1153.629975\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1171.867209\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 567.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 466.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 432.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 617.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 841.49\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 35.6\n    unknown:\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for SE for\n          the sources in unknown\n        datetime: '2022-01-01'\n        source: Eurostat 2022; assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01%\n          coal\n        value: 258\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0029359493045969043\n        coal: 0.010850929807982433\n        gas: 0.006697188104233741\n        geothermal: 1.9458916081204937e-06\n        hydro: 0.28334478937071544\n        hydro discharge: 5.2948228117312056e-05\n        nuclear: 0.3216105986232798\n        oil: 0.00026689722539250706\n        solar: 0.013828894486485286\n        unknown: 0.08831576118466927\n        wind: 0.2720965358535611\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00833846779738401\n        coal: 0.011559481144634834\n        gas: 0.004555854961968775\n        geothermal: 3.086154936538181e-06\n        hydro: 0.29843835378537126\n        hydro discharge: 0.0001995935878165048\n        nuclear: 0.30081085363557075\n        oil: 0.0006294009190385132\n        solar: 0.019225917513530946\n        unknown: 0.07261500041151926\n        wind: 0.2836238106091918\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.004884572650574876\n        coal: 0.006277046019724963\n        gas: 0.005309220895234022\n        geothermal: 5.919487775826679e-06\n        hydro: 0.3265650937346932\n        hydro discharge: 0.0016216577702062326\n        nuclear: 0.2862972003672944\n        oil: 0.0002987140681796447\n        solar: 0.02255594854313073\n        unknown: 0.07060926069954462\n        wind: 0.2755752355382071\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.012305401169924311\n        coal: 0.025513976913648033\n        gas: 0.009744654325429909\n        geothermal: 5.132575687871965e-06\n        hydro: 0.279693145126424\n        hydro discharge: 0.00015417769379544766\n        nuclear: 0.29194917400224707\n        oil: 0.0006433833468527277\n        solar: 0.020280056819579204\n        unknown: 0.07327972026704\n        wind: 0.2864309856713906\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.015374280126298987\n        coal: 0.03444118811128335\n        gas: 0.015018023129411272\n        geothermal: 1.3417815008227478e-05\n        hydro: 0.26579257123490846\n        hydro discharge: 0.000394416939917797\n        nuclear: 0.28305925842260293\n        oil: 0.0010061999218728337\n        solar: 0.023319768230726325\n        unknown: 0.07207663225285563\n        wind: 0.28950405677749386\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0077644633216081985\n        coal: 0.011586189669500013\n        gas: 0.008602970377463935\n        geothermal: 6.139739564896537e-06\n        hydro: 0.2825765299981671\n        hydro discharge: 0.0017123870657082215\n        nuclear: 0.29143175238182206\n        oil: 0.000561576112521992\n        solar: 0.003815248245167566\n        unknown: 0.12192898242272386\n        wind: 0.270013610786769\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0040519295024818115\n        coal: 0.005974600790358764\n        gas: 0.0025460007589257236\n        geothermal: 2.85560604201288e-06\n        hydro: 0.3202596864334\n        hydro discharge: 0.00045779018946506003\n        nuclear: 0.30154673856931163\n        oil: 0.0002826037289141179\n        solar: 0.013067591590199046\n        unknown: 0.08492971099098666\n        wind: 0.266880371903528\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005754978547177921\n        coal: 0.008758062578770211\n        gas: 0.003544986985406879\n        geothermal: 6.743707267520559e-06\n        hydro: 0.32136299223512793\n        hydro discharge: 0.0005250689222721729\n        nuclear: 0.27096517967437517\n        oil: 0.0005222799145334775\n        solar: 0.02275596647649808\n        unknown: 0.06848567421007519\n        wind: 0.29731792253920175\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 4.739525081064813e-09\n        biomass: 0.005474522573443706\n        coal: 0.010071025849852274\n        gas: 0.004095521730717282\n        geothermal: 7.457642715055483e-06\n        hydro: 0.29469708160074737\n        hydro discharge: 0.00046416775857662293\n        nuclear: 0.27957341773696986\n        oil: 0.0005397612878095743\n        solar: 0.03496637189888715\n        unknown: 0.057250942025872324\n        wind: 0.3128595834430837\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: NORDPOOL.fetch_price\n  production: SE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  Eurostat 2022:\n    link: https://doi.org/10.2908/NRG_BAL_C\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Stockholm\nzone_name: South Sweden\nisLowCarbon:\n  unknown:\n    - _comment: Sum of renewable sources in unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\nisRenewable:\n  unknown:\n    - _comment: Sum of renewable sources in unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\n"
  },
  {
    "path": "config/zones/SE.yaml",
    "content": "bounding_box:\n  - - 11.118711187111899\n    - 55.34588629391277\n  - - 24.161641616416176\n    - 69.05991811650836\ncenter_point:\n  - 16.693385557382808\n  - 62.189575383409604\ncentroid:\n  - 16.568196956339914\n  - 61.64254207304956\ncontributors:\n  - augustekman\n  - RRyyas\n  - corradio\n  - VIKTORVAV99\n  - dpkruczek\ncountry: SE\ncountry_name: Sweden\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1057.262766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1075.5\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 447.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 346.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 312.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 373.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 597.49\n    unknown:\n      - _comment: Uses the 2015 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2015-01-01'\n        source: Eurostat 2022; assumes 85.46% biomass, 7.98% gas, 2.77% coal, 1.8% oil,\n          1.3% peat, 0.69% solar\n        value: 67.7\n      - _comment: Uses the 2016 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2016-01-01'\n        source: Eurostat 2022; assumes 85.52% biomass, 7.84% gas, 2.6% oil, 1.74% coal,\n          1.38% peat, 0.94% solar\n        value: 63.1\n      - _comment: Uses the 2016 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2017-01-01'\n        source: Eurostat 2022; assumes 87.2% biomass, 6.21% gas, 2.04% coal, 1.84% oil,\n          1.46% solar, 1.26% peat\n        value: 55.5\n      - _comment: Uses the 2018 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2018-01-01'\n        source: Eurostat 2022; assumes 84.38% biomass, 7.15% gas, 2.55% solar, 2.10%\n          coal, 1.92% oil, 1.90% peat\n        value: 64.6\n      - _comment: Uses the 2019 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2019-01-01'\n        source: Eurostat 2022; assumes 86.15% biomass, 6.15% gas, 3.98% solar, 1.27%\n          oil, 1.24% coal, 1.20% peat\n        value: 46.5\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2020-01-01'\n        source: Eurostat 2022; assumes 86.72% biomass, 7.17% solar, 4.58% gas, 0.96%\n          oil, 0.56% peat, 0.01% coal\n        value: 27.4\n      - _comment: Uses the 2020 values with 2021 emission factors\n        datetime: '2021-01-01'\n        source: Eurostat 2022; assumes 86.72% biomass, 7.17% solar, 4.58% gas, 0.96%\n          oil, 0.56% peat, 0.01% coal\n        value: 35.5\n      - _comment: Uses the 2020 values with 2022 emission factors minus solar and gas\n        datetime: '2022-01-01'\n        source: Eurostat 2022; assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01%\n          coal\n        value: 28.6\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1153.629975\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1171.867209\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 567.9740216\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 466.62\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 432.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 617.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 841.49\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 40.81666667\n    unknown:\n      - _comment: Uses the 2015 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2015-01-01'\n        source: assumes 85.46% biomass, 7.98% gas, 2.77% coal, 1.8% oil, 1.3% peat,\n          0.69% solar\n        value: 281\n      - _comment: Uses the 2016 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2016-01-01'\n        source: assumes 85.52% biomass, 7.84% gas, 2.6% oil, 1.74% coal, 1.38% peat,\n          0.94% solar\n        value: 277.9\n      - _comment: Uses the 2016 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2017-01-01'\n        source: assumes 87.2% biomass, 6.21% gas, 2.04% coal, 1.84% oil, 1.46% solar,\n          1.26% peat\n        value: 270.6\n      - _comment: Uses the 2018 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2018-01-01'\n        source: assumes 84.38% biomass, 7.15% gas, 2.55% solar, 2.10% coal, 1.92% oil,\n          1.90% peat\n        value: 275.5\n      - _comment: Uses the 2019 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2019-01-01'\n        source: assumes 86.15% biomass, 6.15% gas, 3.98% solar, 1.27% oil, 1.24% coal,\n          1.20% peat\n        value: 258.4\n      - _comment: Uses the 2020 (2022 edition) eurostat production values for the sources\n          in unknown\n        datetime: '2020-01-01'\n        source: assumes 86.72% biomass, 7.17% solar, 4.58% gas, 0.96% oil, 0.56% peat,\n          0.01% coal\n        value: 237.9\n      - _comment: Uses the 2020 values with 2021 emission factors\n        datetime: '2021-01-01'\n        source: assumes 86.72% biomass, 7.17% solar, 4.58% gas, 0.96% oil, 0.56% peat,\n          0.01% coal\n        value: 245.8\n      - _comment: Uses the 2020 values with 2022 emission factors minus solar and gas\n        datetime: '2022-01-01'\n        source: assumes 98.26% biomass, 1.09% oil, 0.64% peat, 0.01% coal\n        value: 258\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0008544602403404806\n        coal: 0.0030533526706254975\n        gas: 0.001922495681605918\n        geothermal: 6.442205900022875e-07\n        hydro: 0.5157980032770925\n        hydro discharge: 3.912496156542762e-05\n        nuclear: 0.31448953696475124\n        oil: 7.529063423769025e-05\n        solar: 0.0004042073266118967\n        unknown: 0.05985935476591089\n        wind: 0.10350350094651478\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0025500452276079754\n        coal: 0.0035940634609047174\n        gas: 0.0027192868507887836\n        geothermal: 1.0383511984516753e-06\n        hydro: 0.44074885833649197\n        hydro discharge: 4.792997947804278e-05\n        nuclear: 0.2857576372380286\n        oil: 0.0002951402310623945\n        solar: 0.00763121190079565\n        unknown: 0.04311577989336255\n        wind: 0.21353899167393026\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0033327328416806793\n        coal: 0.006892441847933341\n        gas: 0.003785166019481859\n        geothermal: 1.5221645586962977e-06\n        hydro: 0.4348572076771633\n        hydro discharge: 4.1985589908899797e-05\n        nuclear: 0.28559962843415143\n        oil: 0.0001459526807380495\n        solar: 0.007837032970538917\n        unknown: 0.043416301682895064\n        wind: 0.21409000475604528\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.003846321240878185\n        coal: 0.008139772665294209\n        gas: 0.004650168667270287\n        geothermal: 3.132924062565307e-06\n        hydro: 0.42822777801693673\n        hydro discharge: 8.620296182802475e-05\n        nuclear: 0.28711851344355577\n        oil: 0.00024531788280055097\n        solar: 0.008766590817249788\n        unknown: 0.044413620298272824\n        wind: 0.21450254422304119\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0015134194037580524\n        coal: 0.0020482162500784925\n        gas: 0.0022231036103447285\n        geothermal: 1.4989523530334743e-06\n        hydro: 0.44310389560310964\n        hydro discharge: 0.0012468456278938427\n        nuclear: 0.29335883863739876\n        oil: 8.325972565268254e-05\n        solar: 0.008722889784307315\n        unknown: 0.04383593626683848\n        wind: 0.20386208123814206\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.001707893300444385\n        coal: 0.002661130313560573\n        gas: 0.002112714338016048\n        geothermal: 1.271911872135281e-06\n        hydro: 0.4168199758668297\n        hydro discharge: 0.0011066927158558603\n        nuclear: 0.29278963058450597\n        oil: 0.00010589286340033665\n        solar: 0.0009171109041775911\n        unknown: 0.07044595392173544\n        wind: 0.21133171410237422\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0012933409719901162\n        coal: 0.001959776979189334\n        gas: 0.001460359435799134\n        geothermal: 8.481782423396676e-07\n        hydro: 0.4429563809003136\n        hydro discharge: 0.00030646686121659015\n        nuclear: 0.3007766233663627\n        oil: 7.056802572025835e-05\n        solar: 0.0051864326394529614\n        unknown: 0.05071443391742726\n        wind: 0.19527475706921638\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0019277128894154135\n        coal: 0.002336936320588193\n        gas: 0.0016757284568182317\n        geothermal: 1.7149557072677973e-06\n        hydro: 0.43468025985408193\n        hydro discharge: 0.00035746444442233465\n        nuclear: 0.29237392134213247\n        oil: 0.00012508940834871709\n        solar: 0.008855832879058785\n        unknown: 0.04390880154270242\n        wind: 0.21375650953095357\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.2506611788379525e-09\n        biomass: 0.0021154277242925075\n        coal: 0.0023888628263084724\n        gas: 0.0014277539419318458\n        geothermal: 1.7068398438190956e-06\n        hydro: 0.4029223539104138\n        hydro discharge: 0.00029780149926429374\n        nuclear: 0.3012984673584672\n        oil: 0.00012282391688910982\n        solar: 0.012774182149296296\n        unknown: 0.03539409961324375\n        wind: 0.2412564947378273\nhas_day_ahead_price_license: true\nhide_day_ahead_price: false\nisLowCarbon:\n  unknown:\n    - _comment: Sum of renewable sources in SE unknown production for 2015\n      datetime: '2015-01-01'\n      value: 0.8615\n    - _comment: Sum of renewable sources in SE unknown production for 2016\n      datetime: '2016-01-01'\n      value: 0.8646\n    - _comment: Sum of renewable sources in SE unknown production for 2017\n      datetime: '2017-01-01'\n      value: 0.8866\n    - _comment: Sum of renewable sources in SE unknown production for 2018\n      datetime: '2018-01-01'\n      value: 0.8693\n    - _comment: Sum of renewable sources in SE unknown production for 2019\n      datetime: '2019-01-01'\n      value: 0.9013\n    - _comment: Sum of renewable sources in SE unknown production for 2020\n      datetime: '2020-01-01'\n      value: 0.9332\n    - _comment: Sum of renewable sources in SE unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\nisRenewable:\n  unknown:\n    - _comment: Sum of renewable sources in SE unknown production for 2015\n      datetime: '2015-01-01'\n      value: 0.8615\n    - _comment: Sum of renewable sources in SE unknown production for 2016\n      datetime: '2016-01-01'\n      value: 0.8646\n    - _comment: Sum of renewable sources in SE unknown production for 2017\n      datetime: '2017-01-01'\n      value: 0.8866\n    - _comment: Sum of renewable sources in SE unknown production for 2018\n      datetime: '2018-01-01'\n      value: 0.8693\n    - _comment: Sum of renewable sources in SE unknown production for 2019\n      datetime: '2019-01-01'\n      value: 0.9013\n    - _comment: Sum of renewable sources in SE unknown production for 2020\n      datetime: '2020-01-01'\n      value: 0.9332\n    - _comment: Sum of renewable sources in SE unknown production for 2022\n      datetime: '2022-01-01'\n      value: 0.9826\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  production: ENTSOE.fetch_production\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  Eurostat 2022:\n    link: https://doi.org/10.2908/NRG_BAL_C\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_storage/disk/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdDRG9JYTJWNVNTSWhORFJ0ZDJJMWVUbG9OMll6TVRaaGEza3lkamgxZG1aM056WnZZZ1k2QmtWVU9oQmthWE53YjNOcGRHbHZia2tpQVk1cGJteHBibVU3SUdacGJHVnVZVzFsUFNKWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtSWpzZ1ptbHNaVzVoYldVcVBWVlVSaTA0SnlkWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtQmpzR1ZEb1JZMjl1ZEdWdWRGOTBlWEJsU1NJVVlYQndiR2xqWVhScGIyNHZjR1JtQmpzR1ZBPT0iLCJleHAiOiIyMDIyLTExLTAyVDE1OjU0OjAzLjEyNFoiLCJwdXIiOiJibG9iX2tleSJ9fQ==--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\nsubZoneNames:\n  - SE-SE1\n  - SE-SE2\n  - SE-SE3\n  - SE-SE4\ntimezone: Europe/Stockholm\nzone_name: Sweden\n"
  },
  {
    "path": "config/zones/SG.yaml",
    "content": "bounding_box:\n  - - 103.64683646836468\n    - 1.268128202083403\n  - - 103.96003960039602\n    - 1.426212512352693\ncenter_point:\n  - 103.80343803438035\n  - 1.347170357218048\ncentroid:\n  - 103.831737208542\n  - 1.359443451724828\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 220.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 510.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10880.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 330.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 480.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 630.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 920.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1160.0\ncontributors:\n  - corradio\n  - jarek\n  - r24mille\n  - systemcatch\n  - alixunderplatz\n  - q--\n  - nessie2013\ncountry: SG\ncountry_name: Singapore\ncurrency: SGD\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9711940580801492\n        geothermal: 0.0\n        hydro: 0.00011278782824837451\n        hydro discharge: 0.0\n        nuclear: 0.00011278782824837451\n        oil: 0.0\n        solar: 0.006468881848449212\n        unknown: 0.021997100046621844\n        wind: 0.00011278782824837451\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9711940885113769\n        geothermal: 0.0\n        hydro: 0.00011278783178244891\n        hydro discharge: 0.0\n        nuclear: 0.00011278783178244891\n        oil: 0.0\n        solar: 0.006468850799399156\n        unknown: 0.021997100735875193\n        wind: 0.00011278783178244891\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9707511878087615\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0067770024438817125\n        unknown: 0.022471723908608885\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.000801359742596653\n        gas: 0.9764803153390155\n        geothermal: 0.0\n        hydro: 5.183074203133382e-05\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 4.844156849370942e-07\n        solar: 0.001561646398215396\n        unknown: 0.02110434735030894\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0009139292843429182\n        gas: 0.9753633502522234\n        geothermal: 0.0\n        hydro: 4.699302338946407e-05\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 5.834930367264208e-07\n        solar: 0.0029497993561505187\n        unknown: 0.020725325580277395\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.001766016781402966\n        gas: 0.9738119107907736\n        geothermal: 0.0\n        hydro: 0.0001111769803351893\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 5.736125630324498e-07\n        solar: 0.004782809002571431\n        unknown: 0.01952750093008503\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0005209714131995036\n        gas: 0.9718425958575975\n        geothermal: 0.0\n        hydro: 5.596122779486973e-05\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 1.3959406744799602e-06\n        solar: 0.0069878248771033805\n        unknown: 0.020591240642205067\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0024736993670715236\n        gas: 0.9593167865433155\n        geothermal: 0.0\n        hydro: 0.0002641788319412092\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 1.4627051658300322e-05\n        solar: 0.011541491765051315\n        unknown: 0.026389214479562294\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.001563757368133233\n        gas: 0.9624928962621507\n        geothermal: 0.0\n        hydro: 0.00015128305568898873\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 4.614477622060009e-06\n        solar: 0.015930815799617755\n        unknown: 0.019856631795621648\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0009223966518099746\n        gas: 0.9565993240650125\n        geothermal: 0.0\n        hydro: 9.434755411137803e-05\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 9.020531244448798e-07\n        solar: 0.021984125166641562\n        unknown: 0.020398877413407873\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisLowCarbon:\n  unknown:\n    value: 1\nisRenewable:\n  unknown:\n    value: 1\nparsers:\n  price: SG.fetch_price\n  production: SG.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Singapore\nzone_name: Singapore\n"
  },
  {
    "path": "config/zones/SI.yaml",
    "content": "_comment: hydro incl. 180 MW pumped storage\nbounding_box:\n  - - 13.36513365133655\n    - 45.42418901301268\n  - - 16.51516515165153\n    - 46.863858342968754\ncenter_point:\n  - 14.646384201626761\n  - 46.02679251148994\ncentroid:\n  - 14.577469489788768\n  - 46.06700727134408\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 57.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 61.3\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 20.200000000000003\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 47.43\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 49.7\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 39.010000000000005\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 924.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 967.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 981.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1190.5\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 491.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 545.76\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 548.37\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 548.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 618.02\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 756.04\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 764.4\n  geothermal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1053.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1110.58\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1125.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 1128.94\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1125.24\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1145.54\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 180.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 696.0\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 700.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 58.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 58.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 266.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 275.34\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 277.62\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 459.0\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 702.4\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 1109.53\n    - datetime: '2025-01-01'\n      source: entsoe.eu\n      value: 1411.46\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 3.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 3.31\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 3.29\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 3.3\n    - datetime: '2023-01-01'\n      source: entsoe.eu\n      value: 2.39\n    - datetime: '2024-01-01'\n      source: entsoe.eu\n      value: 3.25\ncontributors:\n  - corradio\ncountry: SI\ncountry_name: Slovenia\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1046.269766\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1032.39\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1044.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 1004.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 419.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 412.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 392.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 390.45\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 278.19\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1055.8075199999998\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1041.927754\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1104.92\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1064.93\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 539.8221756\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 532.38\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 512.33\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 510.45\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 288.89\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 10.7\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 10.7\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 30.83333333\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.023083020561577544\n        coal: 0.25289458142342147\n        gas: 0.04183310201713685\n        geothermal: 1.0130766102243297e-05\n        hydro: 0.27307719076011466\n        hydro discharge: 0.029621873988402506\n        nuclear: 0.308277530881865\n        oil: 0.00021148002015264702\n        solar: 0.021527310208824552\n        unknown: 0.02575864166403666\n        wind: 0.023704958270032248\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022824011510158854\n        coal: 0.26381701263642665\n        gas: 0.03537473247260068\n        geothermal: 1.0325989812573876e-05\n        hydro: 0.31265982063416903\n        hydro discharge: 0.026675502052085208\n        nuclear: 0.2949545872766467\n        oil: 0.0001514871315727671\n        solar: 0.021750759979374642\n        unknown: 0.0038197869653427176\n        wind: 0.017961830412658183\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.025465964218228835\n        coal: 0.24407456473202355\n        gas: 0.04613304557316413\n        geothermal: 2.4868059273132453e-05\n        hydro: 0.2922241627803568\n        hydro discharge: 0.029954373590669055\n        nuclear: 0.29803286662095757\n        oil: 0.00031977833051162425\n        solar: 0.024695436925560255\n        unknown: 0.006418444509974177\n        wind: 0.03265642516584855\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.022141856601113948\n        coal: 0.255397768040327\n        gas: 0.050964418273509546\n        geothermal: 0.0002839692786382373\n        hydro: 0.3219213391759703\n        hydro discharge: 0.021965998284882358\n        nuclear: 0.26880566514067045\n        oil: 0.0004027392246349724\n        solar: 0.020178032341030633\n        unknown: 0.004277171206830682\n        wind: 0.033661007057356945\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02335223534140204\n        coal: 0.22071954620391873\n        gas: 0.06393241276184868\n        geothermal: 0.00016148874967101293\n        hydro: 0.32272975047396174\n        hydro discharge: 0.026642373497079888\n        nuclear: 0.274887372754516\n        oil: 0.0005527882156553738\n        solar: 0.02268372134148544\n        unknown: 0.00479596491136181\n        wind: 0.039542239640230285\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.020497995841035236\n        coal: 0.20437179563071228\n        gas: 0.05964018839700271\n        geothermal: 0.00018034484317066025\n        hydro: 0.323811372802907\n        hydro discharge: 0.029884119246192893\n        nuclear: 0.2996238693667422\n        oil: 0.0003648741603135132\n        solar: 0.0223718224667253\n        unknown: 0.003666338314895154\n        wind: 0.03558719312082458\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0198750994244001\n        coal: 0.20820728461256446\n        gas: 0.06270790975422591\n        geothermal: 0.00045301775421125823\n        hydro: 0.3466436136348879\n        hydro discharge: 0.029496215536916223\n        nuclear: 0.26966278866988097\n        oil: 0.0005234040705225708\n        solar: 0.020470318305617755\n        unknown: 0.004643087975190909\n        wind: 0.03731704070565446\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.021417322537494607\n        coal: 0.20153169742541624\n        gas: 0.08800993791026583\n        geothermal: 0.00038737409695244624\n        hydro: 0.2696049685930344\n        hydro discharge: 0.031729982683683725\n        nuclear: 0.3059090831358103\n        oil: 0.0006585548486074277\n        solar: 0.026269373060242757\n        unknown: 0.00600384257316677\n        wind: 0.04847772352755237\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.01853596889931821\n        coal: 0.1795627865499333\n        gas: 0.06387840703452227\n        geothermal: 0.00016678114289876304\n        hydro: 0.3400307720998869\n        hydro discharge: 0.029045819524263553\n        nuclear: 0.2892226931054213\n        oil: 0.001022496942089773\n        solar: 0.031438689944007496\n        unknown: 0.0038861103747545042\n        wind: 0.0432091340937893\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.1381408882088339e-07\n        biomass: 0.02012157268881097\n        coal: 0.16658573597911241\n        gas: 0.06286477717401952\n        geothermal: 2.490727171109678e-05\n        hydro: 0.34668278050357293\n        hydro discharge: 0.03153820334676059\n        nuclear: 0.27195725453970315\n        oil: 0.0003795691674112517\n        solar: 0.049591378558207624\n        unknown: 0.003995671216234753\n        wind: 0.04625761651149296\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 0.653\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2023-01-01'\n      value: 0.2828\n    - datetime: '2024-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_storage/disk/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdDRG9JYTJWNVNTSWhORFJ0ZDJJMWVUbG9OMll6TVRaaGEza3lkamgxZG1aM056WnZZZ1k2QmtWVU9oQmthWE53YjNOcGRHbHZia2tpQVk1cGJteHBibVU3SUdacGJHVnVZVzFsUFNKWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtSWpzZ1ptbHNaVzVoYldVcVBWVlVSaTA0SnlkWGFXNWtaWFZ5YjNCbExWZHBibVF0Wlc1bGNtZDVMV2x1TFVWMWNtOXdaUzB5TURJeExYTjBZWFJwYzNScFkzTXVjR1JtQmpzR1ZEb1JZMjl1ZEdWdWRGOTBlWEJsU1NJVVlYQndiR2xqWVhScGIyNHZjR1JtQmpzR1ZBPT0iLCJleHAiOiIyMDIyLTExLTAyVDE1OjU0OjAzLjEyNFoiLCJwdXIiOiJibG9iX2tleSJ9fQ==--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Ljubljana\nzone_name: Slovenia\n"
  },
  {
    "path": "config/zones/SJ.yaml",
    "content": "bounding_box:\n  - - 10.485104851048533\n    - 74.34780414993347\n  - - 33.64053640536406\n    - 80.5043224973202\ncenter_point:\n  - 23.95264625863929\n  - 79.75626655413785\ncentroid:\n  - 18.702710349787225\n  - 78.8667613872489\ncountry: SJ\ncountry_name: Svalbard and Jan Mayen\ncurrency: NOK\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Arctic/Longyearbyen\nzone_name: Svalbard and Jan Mayen\n"
  },
  {
    "path": "config/zones/SK.yaml",
    "content": "bounding_box:\n  - - 16.84276842768429\n    - 47.74969861656996\n  - - 22.538025380253828\n    - 49.60151980241804\ncenter_point:\n  - 19.62177258617559\n  - 48.59625061311907\ncentroid:\n  - 19.6507965079651\n  - 48.75260844679904\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 225.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 224.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 214.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 224.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 234.0\n  coal:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 554.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 566.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 541.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 309.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 277.0\n  gas:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1106.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1111.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 1153.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1152.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1183.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1623.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 1626.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 1628.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1630.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 916.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 1940.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 2003.0\n    - datetime: '2023-01-01'\n      source: IAEA\n      value: 2471.0\n  oil:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 257.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 259.0\n  solar:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 530.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 531.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 532.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 567.0\n    - datetime: '2018-01-01'\n      source: entsoe.eu\n      value: 554.0\n    - datetime: '2019-01-01'\n      source: entsoe.eu\n      value: 534.0\n    - datetime: '2020-01-01'\n      source: entsoe.eu\n      value: 756.0\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 742.0\n  wind:\n    - datetime: '2017-01-01'\n      source: entsoe.eu\n      value: 3.0\ncontributors:\n  - corradio\n  - nessie2013\ncountry: SK\ncountry_name: Slovakia\ncurrency: EUR\nemissionFactors:\n  direct:\n    biomass:\n      datetime: '2021-01-01'\n      source: BEIS 2021\n      value: 0.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 1153.673876\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 1300.76\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 1288.03\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 772.24\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 347.5807988\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 347.58\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 368.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 362.01\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 280.95\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 304.93\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 370.76\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 233.95\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 156.29\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 156.6\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021\n        value: 880.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022\n        value: 925.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023\n        value: 791.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024\n        value: 857.84\n  lifecycle:\n    biomass:\n      datetime: '2014-01-01'\n      source: BEIS 2021; IPCC 2014\n      value: 230.0\n    coal:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1163.124374\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; Oberschelp, Christopher, et al. \"Global emission\n          hotspots of coal power generation.\"\n        value: 1310.210498\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1348.03\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 832.24\n    gas:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 467.5807988\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 467.58\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 488.49\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 482.01\n    hydro:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 10.7\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; UNECE 2022\n        value: 291.65\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; UNECE 2022\n        value: 315.63\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; UNECE 2022\n        value: 381.46\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; UNECE 2022\n        value: 244.65\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; UNECE 2022\n        value: 166.99\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; UNECE 2022\n        value: 167.3\n    nuclear:\n      datetime: '2020-01-01'\n      source: UNECE 2022\n      value: 5.13\n    oil:\n      - datetime: '2021-01-01'\n        source: EU-ETS, ENTSO-E 2021; IPCC 2014\n        value: 1124.903938\n      - datetime: '2022-01-01'\n        source: EU-ETS, ENTSO-E 2022; IPCC 2014\n        value: 1169.95\n      - datetime: '2023-01-01'\n        source: EU-ETS, ENTSO-E 2023; IPCC 2014\n        value: 1035.59\n      - datetime: '2024-01-01'\n        source: EU-ETS, ENTSO-E 2024; IPCC 2014\n        value: 1101.84\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 33.0\n    wind:\n      datetime: '2021-01-01'\n      source: UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the\n        outlook for 2022-2026\" Wind Europe Proceedings (2021)\n      value: 12.62\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.020369448072457833\n        coal: 0.2686182782159849\n        gas: 0.03528957806915705\n        geothermal: 3.4672425960071942e-06\n        hydro: 0.09560811586594277\n        hydro discharge: 0.010113478212001183\n        nuclear: 0.43091772625998775\n        oil: 0.009865260918186163\n        solar: 0.020520289131325548\n        unknown: 0.09413042067882266\n        wind: 0.014564016651870064\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.018578229550623854\n        coal: 0.24729577137290087\n        gas: 0.043102088158411274\n        geothermal: 5.56619709521323e-06\n        hydro: 0.11078913117700362\n        hydro discharge: 0.008996783788041772\n        nuclear: 0.43259733906743103\n        oil: 0.012067297230474427\n        solar: 0.019523800598861822\n        unknown: 0.09282677684655785\n        wind: 0.014217771917317813\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.018513531832015952\n        coal: 0.25190688614124174\n        gas: 0.047353406544682876\n        geothermal: 5.87798838074136e-06\n        hydro: 0.0995901463233239\n        hydro discharge: 0.010563377392716466\n        nuclear: 0.4283187936015195\n        oil: 0.011313548437374397\n        solar: 0.020722339081684277\n        unknown: 0.0944814972450303\n        wind: 0.017230455750788243\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.023557522235712034\n        coal: 0.2201252352755934\n        gas: 0.05628735025457972\n        geothermal: 5.343472775036428e-06\n        hydro: 0.09225572688936054\n        hydro discharge: 0.010184804882557005\n        nuclear: 0.45558281257225264\n        oil: 0.012631833164464605\n        solar: 0.021384798864077306\n        unknown: 0.0943902280934141\n        wind: 0.01359425098699524\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.028790004637282162\n        coal: 0.1948461227249321\n        gas: 0.09378391967104914\n        geothermal: 6.860077846573294e-06\n        hydro: 0.11338404182981834\n        hydro discharge: 0.008614388304188767\n        nuclear: 0.45501412664271246\n        oil: 0.01397143460374415\n        solar: 0.02158376112207197\n        unknown: 0.053068578989940496\n        wind: 0.016936728269140035\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.03214129978920068\n        coal: 0.1597658007964095\n        gas: 0.11335439064889521\n        geothermal: 1.0663649634087268e-05\n        hydro: 0.11957332078969245\n        hydro discharge: 0.010667548142264734\n        nuclear: 0.4576875955632772\n        oil: 0.011664797983631637\n        solar: 0.02303952815894718\n        unknown: 0.05076868248375398\n        wind: 0.021326241596403762\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.029568448804018037\n        coal: 0.18390098739432428\n        gas: 0.12341746763432691\n        geothermal: 5.4375444738112686e-06\n        hydro: 0.11039780221281024\n        hydro discharge: 0.00992194381051544\n        nuclear: 0.4399302198824685\n        oil: 0.011408172691945778\n        solar: 0.022461518958980638\n        unknown: 0.05066136532982255\n        wind: 0.018326564336607294\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02823665219042905\n        coal: 0.2266170460653154\n        gas: 0.0666911020975343\n        geothermal: 6.8027469000182286e-06\n        hydro: 0.09529082819266127\n        hydro discharge: 0.010514164496739017\n        nuclear: 0.45544151016749074\n        oil: 0.014134213460755744\n        solar: 0.030556616176659238\n        unknown: 0.0454793871588247\n        wind: 0.027031418942238896\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.026340229189624406\n        coal: 0.13563975336683612\n        gas: 0.0679304144189152\n        geothermal: 4.768661348378167e-06\n        hydro: 0.12698083691929726\n        hydro discharge: 0.01190256533264873\n        nuclear: 0.5306439950981958\n        oil: 0.011951591630358993\n        solar: 0.026050310257217907\n        unknown: 0.03868593496346107\n        wind: 0.02386944220462035\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.5140288033855263e-08\n        biomass: 0.030163529218408387\n        coal: 0.1286440055774616\n        gas: 0.07711717628168348\n        geothermal: 9.855162872498711e-06\n        hydro: 0.12277411862422352\n        hydro discharge: 0.01893525325001792\n        nuclear: 0.5115883558858495\n        oil: 0.009659476978936214\n        solar: 0.03709833589359616\n        unknown: 0.03656600258990078\n        wind: 0.027443728652431654\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.6602\n    - datetime: '2021-01-01'\n      value: 0.6294\n    - datetime: '2022-01-01'\n      value: 0.6463\n    - datetime: '2023-01-01'\n      value: 0.7469\n    - datetime: '2024-01-01'\n      value: 0.7519\n    - datetime: '2025-01-01'\n      value: 0.7484\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1876\n    - datetime: '2021-01-01'\n      value: 0.1782\n    - datetime: '2022-01-01'\n      value: 0.1788\n    - datetime: '2023-01-01'\n      value: 0.204\n    - datetime: '2024-01-01'\n      value: 0.2268\n    - datetime: '2025-01-01'\n      value: 0.2022\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  EU-ETS, ENTSO-E 2021:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2022:\n    link: https://drive.google.com/file/d/15UeUHyhcjVw8fGLc0Zx_HELSx20cw_-e/view?usp=share_link\n  EU-ETS, ENTSO-E 2023:\n    link: https://colab.research.google.com/drive/1IkDXX4p1xQIuY3WicL94TUkRcZQnS9c7?usp=drive_link\n  EU-ETS, ENTSO-E 2024:\n    link: https://transparency.entsoe.eu/\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  UNECE 2022:\n    link: https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf\n  ? UNECE 2022, WindEurope \"Wind energy in Europe, 2021 Statistics and the outlook\n    for 2022-2026\" Wind Europe Proceedings (2021)\n  : link:\n      https://unece.org/sites/default/files/2022-04/LCA_3_FINAL%20March%202022.pdf#page=37,\n      https://proceedings.windeurope.org/biplatform/rails/active_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--c25280a7345257bd91bfaf6d64ddb75c55eef799/Windeurope-Wind-energy-in-Europe-2021-statistics.pdf?content_type=application%2Fpdf&disposition=inline%3B+filename%3D%22Windeurope-Wind-energy-in-Europe-2021-statistics.pdf%22%3B+filename%2A%3DUTF-8%27%27Windeurope-Wind-energy-in-Europe-2021-statistics.pdf\ntimezone: Europe/Bratislava\nzone_name: Slovakia\n"
  },
  {
    "path": "config/zones/SL.yaml",
    "content": "bounding_box:\n  - - -13.300333003329996\n    - 6.919474309435856\n  - - -10.283502835028315\n    - 9.996302400296258\ncenter_point:\n  - -11.883841963883732\n  - 8.52907881316037\ncentroid:\n  - -11.947349473494711\n  - 8.52006890395809\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\ncountry: SL\ncountry_name: Sierra Leone\ncurrency: SLE\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Freetown\nzone_name: Sierra Leone\n"
  },
  {
    "path": "config/zones/SN.yaml",
    "content": "bounding_box:\n  - - -17.537575375753732\n    - 12.306070092691002\n  - - -11.38511385113847\n    - 16.643682159387694\ncenter_point:\n  - -14.28883198821697\n  - 14.48496327825712\ncentroid:\n  - -14.368137431374285\n  - 13.913936376858215\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 230.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 570.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 690.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 680.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\ncountry: SN\ncountry_name: Senegal\ncurrency: XOF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Dakar\nzone_name: Senegal\n"
  },
  {
    "path": "config/zones/SO.yaml",
    "content": "bounding_box:\n  - - 40.9810098100981\n    - -1.695644344973296\n  - - 51.39591395913959\n    - 11.989800786607205\ncenter_point:\n  - 46.06667936446374\n  - 5.235881604609043\ncentroid:\n  - 46.41751987140127\n  - 7.710989920869788\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: SO\ncountry_name: Somalia\ncurrency: SOS\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Mogadishu\nzone_name: Somalia\n"
  },
  {
    "path": "config/zones/SR.yaml",
    "content": "bounding_box:\n  - - -58.066780667806626\n    - 1.833405921101942\n  - - -53.98793987939875\n    - 6.012167793340268\ncenter_point:\n  - -56.04307116833533\n  - 3.9837174914139037\ncentroid:\n  - -55.83299832998326\n  - 3.9176349590224575\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 180.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 470.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 510.0\ncountry: SR\ncountry_name: Suriname\ncurrency: SRD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Paramaribo\nzone_name: Suriname\n"
  },
  {
    "path": "config/zones/SS.yaml",
    "content": "bounding_box:\n  - - 24.132841328413292\n    - 3.490599841667688\n  - - 35.91935919359196\n    - 12.215911874214626\ncenter_point:\n  - 29.845297731564216\n  - 7.80912677340828\ncentroid:\n  - 30.54390543905441\n  - 7.157809229574787\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 170.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\ncountry: SS\ncountry_name: South Sudan\ncurrency: SSP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Juba\nzone_name: South Sudan\n"
  },
  {
    "path": "config/zones/ST.yaml",
    "content": "bounding_box:\n  - - 6.460264602646049\n    - 0.033103717240365\n  - - 6.741067410674134\n    - 0.406616336642493\ncenter_point:\n  - 6.6006660066600915\n  - 0.219860026941429\ncentroid:\n  - 6.5997659976600005\n  - 0.22021779764966876\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\ncountry: ST\ncountry_name: São Tomé and Príncipe\ncurrency: STN\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Sao_Tome\nzone_name: São Tomé and Príncipe\n"
  },
  {
    "path": "config/zones/SV.yaml",
    "content": "bounding_box:\n  - - -90.09990099900993\n    - 13.158995461134168\n  - - -87.70227702277018\n    - 14.415486188471576\ncenter_point:\n  - -88.84019856374907\n  - 13.716598382243662\ncentroid:\n  - -88.79891656059411\n  - 13.802846442362274\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 310.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 300.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 570.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 580.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 570.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 640.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 170.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 410.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 480.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 540.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 570.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 650.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 550.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\ncontributors:\n  - systemcatch\n  - nessie2013\n  - consideRatio\ncountry: SV\ncountry_name: El Salvador\nemissionFactors:\n  direct:\n    unknown:\n      _comment: Based on on 2022 generation from Our World in Data and IPCC 2014 emission factors\n      datetime: '2022-01-01'\n      source: Our World in Data 2022; IPCC 2014; assumes 51% gas, 49% oil\n      value: 387.6470588235294\n  lifecycle:\n    unknown:\n      _comment: Based on on 2022 generation from Our World in Data and IPCC 2014 emission factors\n      _url: https://github.com/electricitymaps/electricitymaps-contrib/pull/6412#issuecomment-1915621810\n      datetime: '2022-01-01'\n      source: Our World in Data 2022; IPCC 2014; assumes 51% gas, 49% oil\n      value: 568.4313725490196\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.11549514250351942\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.2982357203950441\n        hydro: 0.34997231397090894\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.026122144445163635\n        unknown: 0.21017467868536402\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.10223991536174029\n        coal: 4.136943445230576e-05\n        gas: 0.0\n        geothermal: 0.29877101074396234\n        hydro: 0.32245357822879284\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0005593547145704962\n        solar: 0.026721197798324305\n        unknown: 0.2491988789372324\n        wind: 1.4696870923947362e-05\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.11293882442551109\n        coal: 0.0527645433031646\n        gas: 1.9650104283156556e-05\n        geothermal: 0.23161388049231207\n        hydro: 0.2967419842637263\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.25249133402469076\n        solar: 0.03974778266043541\n        unknown: 0.008592925314023472\n        wind: 0.0050889451765757645\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0806816040538319\n        coal: 0.04360576005695785\n        gas: 0.0001123732154694195\n        geothermal: 0.22940559498076915\n        hydro: 0.3869764176176534\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.152011980031407\n        solar: 0.07932506513202425\n        unknown: 0.024270500030341882\n        wind: 0.003610377357280092\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0898394982193626\n        coal: 0.045442852111872246\n        gas: 0.00016574327607324425\n        geothermal: 0.22274164697473778\n        hydro: 0.3304226186004137\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.13514738220418096\n        solar: 0.08123571527283041\n        unknown: 0.05731366711666601\n        wind: 0.03769092591128827\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08011856264249875\n        coal: 0.006283942249432518\n        gas: 0.0003737940009702755\n        geothermal: 0.20311764754031572\n        hydro: 0.35766292319243687\n        hydro discharge: 0.0\n        nuclear: 0.00014421520789422514\n        oil: 0.21538251243626644\n        solar: 0.07798883233770086\n        unknown: 0.03703172215915958\n        wind: 0.021895509946179063\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07240153764300272\n        coal: 0.007785689164997511\n        gas: 8.754666184246322e-08\n        geothermal: 0.18832589294380003\n        hydro: 0.20521772700838853\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.4002408973192313\n        solar: 0.08345829009257795\n        unknown: 0.016469475760505926\n        wind: 0.026099783656500567\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.12189671506875104\n        coal: 0.014486789133520762\n        gas: 0.00017120176363609655\n        geothermal: 0.18521915560159302\n        hydro: 0.16272942384276287\n        hydro discharge: 0.0\n        nuclear: 1.151478098171217e-08\n        oil: 0.06379480851435952\n        solar: 0.06517101483556031\n        unknown: 0.36756974032893625\n        wind: 0.018960503204449836\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  production: ESTADISTICO_UT.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  Our World in Data 2022:\n    link: https://ourworldindata.org/grapher/electricity-prod-source-stacked?country=~SLV\ntimezone: America/El_Salvador\nzone_name: El Salvador\nisLowCarbon:\n  unknown:\n    - _comment: Based on on 2022 generation from Our World in Data and IPCC 2014 emission factors\n      _url: https://github.com/electricitymaps/electricitymaps-contrib/pull/6412#issuecomment-1915621810\n      datetime: '2022-01-01'\n      source: Our World in Data 2022; IPCC 2014; assumes 51% gas, 49% oil\n      value: 0\nisRenewable:\n  unknown:\n    - _comment: Based on on 2022 generation from Our World in Data and IPCC 2014 emission factors\n      _url: https://github.com/electricitymaps/electricitymaps-contrib/pull/6412#issuecomment-1915621810\n      datetime: '2022-01-01'\n      source: Our World in Data 2022; IPCC 2014; assumes 51% gas, 49% oil\n      value: 0\n"
  },
  {
    "path": "config/zones/SY.yaml",
    "content": "bounding_box:\n  - - 35.73575735757359\n    - 32.31690134594733\n  - - 42.3778237782378\n    - 37.32426017846852\ncenter_point:\n  - 38.643712127735434\n  - 34.71767557680492\ncentroid:\n  - 38.11334454325394\n  - 35.25252001092498\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 7470.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1490.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 680.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: SY\ncountry_name: Syria\ncurrency: SYP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Damascus\nzone_name: Syria\n"
  },
  {
    "path": "config/zones/SZ.yaml",
    "content": "bounding_box:\n  - - 30.782107821078228\n    - -27.31720455535446\n  - - 32.136354193686614\n    - -25.71775636673113\ncenter_point:\n  - 31.451074105165567\n  - -26.560341965555033\ncentroid:\n  - 31.602956886308036\n  - -26.437228417341153\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\ncountry: SZ\ncountry_name: Eswatini\ncurrency: SZL\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.3258732393934213\n        coal: 0.027153906797723504\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.6054301807207206\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.041533982994509146\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.3272845370300212\n        coal: 0.027197283162217808\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.6062884747299858\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.03922910747008666\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Mbabane\nzone_name: Eswatini\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/TD.yaml",
    "content": "bounding_box:\n  - - 13.44793447934481\n    - 7.457561454628177\n  - - 23.985239852398536\n    - 23.444187781605677\ncenter_point:\n  - 18.731206651857388\n  - 15.463777788083647\ncentroid:\n  - 18.514302692463016\n  - 12.430596048417103\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 160.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: TD\ncountry_name: Chad\ncurrency: XAF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Ndjamena\nzone_name: Chad\n"
  },
  {
    "path": "config/zones/TF.yaml",
    "content": "bounding_box:\n  - - 68.77688776887769\n    - -49.714197722057094\n  - - 70.54810548105482\n    - -48.65805859133385\ncenter_point:\n  - 69.64449644496446\n  - -49.12459159487827\ncentroid:\n  - 69.55640806408064\n  - -49.28330762532105\ncountry: TF\ncountry_name: French Southern Territories\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Africa\ntimezone: Indian/Kerguelen\nzone_name: French Southern Territories\n"
  },
  {
    "path": "config/zones/TG.yaml",
    "content": "bounding_box:\n  - - -0.167401674016702\n    - 6.100894928983678\n  - - 1.783817838178408\n    - 11.135444335331087\ncenter_point:\n  - 1.0590584557594622\n  - 8.207172911222496\ncentroid:\n  - 0.7471090104527095\n  - 8.843794993083293\ncountry: TG\ncountry_name: Togo\ncurrency: XOF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Lome\nzone_name: Togo\n"
  },
  {
    "path": "config/zones/TH.yaml",
    "content": "bounding_box:\n  - - 97.37917379173788\n    - 5.637224091105182\n  - - 105.6520565205652\n    - 20.44463816372503\ncenter_point:\n  - 101.61414036099163\n  - 13.12838638178959\ncentroid:\n  - 100.73206557308286\n  - 13.122412537841157\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3630.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3880.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 3940.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 4070.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 4490.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 4500.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4430.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 4350.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5780.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 6140.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30120.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 31030.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 31640.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 31680.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 32930.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 35260.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 36110.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 38060.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3090.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3110.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3130.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2700.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2970.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 2990.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 3070.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3190.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 3300.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 3380.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 630.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1100.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1510.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1550.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1540.0\ncontributors:\n  - PPsyrius\ncountry: TH\ncountry_name: Thailand\ncurrency: THB\nemissionFactors:\n  direct:\n    unknown:\n      _url: https://docs.google.com/spreadsheets/d/16j5BVc4L34BDqVE0GeDBv0P3zQupT6zU77Kj5UK7GjE/edit?usp=sharing\n      source: IEA 2020; assumes 9.1% biomass, 19.3% coal, 64.7% gas, 2.5% hydro, 2.6% solar, 1.7% wind, 0.1% other\n      value: 386.645\n  lifecycle:\n    unknown:\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '1998-01-01'\n        source: EPPO\n        value: 636\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '1999-01-01'\n        source: EPPO\n        value: 646\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2000-01-01'\n        source: EPPO\n        value: 634\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2001-01-01'\n        source: EPPO\n        value: 604\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2002-01-01'\n        source: EPPO\n        value: 587\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2003-01-01'\n        source: EPPO\n        value: 573\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2004-01-01'\n        source: EPPO\n        value: 581\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2005-01-01'\n        source: EPPO\n        value: 571\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2006-01-01'\n        source: EPPO\n        value: 571\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2007-01-01'\n        source: EPPO\n        value: 571\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2008-01-01'\n        source: EPPO\n        value: 570\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2009-01-01'\n        source: EPPO\n        value: 560\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2010-01-01'\n        source: EPPO\n        value: 551\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2011-01-01'\n        source: EPPO\n        value: 530\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2012-01-01'\n        source: EPPO\n        value: 530\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2013-01-01'\n        source: EPPO\n        value: 532\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2014-01-01'\n        source: EPPO\n        value: 532\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2015-01-01'\n        source: EPPO\n        value: 507\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2016-01-01'\n        source: EPPO\n        value: 493\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2017-01-01'\n        source: EPPO\n        value: 471\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2018-01-01'\n        source: EPPO\n        value: 459\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2019-01-01'\n        source: EPPO\n        value: 445\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2020-01-01'\n        source: EPPO\n        value: 442\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2021-01-01'\n        source: EPPO\n        value: 433\n      - _comment: Gross Energy Generation of EGAT and Net Energy Generation of IPP, SPP, and VSPP\n        datetime: '2022-01-01'\n        source: EPPO\n        value: 409\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.00019062279068365786\n        gas: 0.00011949183793993087\n        geothermal: 0.0\n        hydro: 1.640272240246278e-05\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 8.154954341849907e-07\n        solar: 3.943078585650569e-06\n        unknown: 0.9996687141995129\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.00018602577310054943\n        gas: 0.00011413283154735553\n        geothermal: 0.0\n        hydro: 1.2664593581843584e-05\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 2.0313229294225035e-07\n        solar: 4.161377939220945e-06\n        unknown: 0.9996828060905045\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0001241579477810437\n        gas: 8.42965397887372e-05\n        geothermal: 0.0\n        hydro: 1.3041621780993996e-05\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 1.4245980224075304e-07\n        solar: 5.013384228280907e-06\n        unknown: 0.9997733243942888\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: True\nisLowCarbon:\n  unknown:\n    _comment: Sum of renewable sources in TH unknown production\n    value: 0.159\nisRenewable:\n  unknown:\n    _comment: Sum of renewable sources in TH unknown production\n    value: 0.159\nparsers:\n  consumption: TH.fetch_consumption\n  price: TH.fetch_price\n  production: TH.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\n  productionPerModeForecast: TH.fetch_generation_forecast\nregion: Asia\nsources:\n  EPPO:\n    link: https://www.eppo.go.th/index.php/en/en-energystatistics/co2-statistic\ntimezone: Asia/Bangkok\nzone_name: Thailand\n"
  },
  {
    "path": "config/zones/TJ.yaml",
    "content": "bounding_box:\n  - - 67.35127351273513\n    - 36.69887698046574\n  - - 75.16335163351633\n    - 41.02647146733173\ncenter_point:\n  - 71.78491803058495\n  - 38.22522906505693\ncentroid:\n  - 70.80775807758079\n  - 38.71494244221951\ncapacity:\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 400.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 210.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4960.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 5720.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 5740.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: TJ\ncountry_name: Tajikistan\ncurrency: TJS\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Dushanbe\nzone_name: Tajikistan\n"
  },
  {
    "path": "config/zones/TL.yaml",
    "content": "bounding_box:\n  - - 124.03024030240303\n    - -9.500770115928027\n  - - 127.31347313473131\n    - -8.308678116073736\ncenter_point:\n  - 125.67185671856717\n  - -8.904724116000882\ncentroid:\n  - 125.71419999914285\n  - -8.89944273887925\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 350.0\ncountry: TL\ncountry_name: Timor-Leste\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Dili\nzone_name: Timor-Leste\n"
  },
  {
    "path": "config/zones/TM.yaml",
    "content": "bounding_box:\n  - - 52.44196246947864\n    - 35.147583189538906\n  - - 66.64566645666457\n    - 42.78097902053864\ncenter_point:\n  - 59.36700507005504\n  - 38.8680778703536\ncentroid:\n  - 58.39364454850762\n  - 39.427148575536116\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4940.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 6520.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 6950.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 7090.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: TM\ncountry_name: Turkmenistan\ncurrency: TMT\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Ashgabat\nzone_name: Turkmenistan\n"
  },
  {
    "path": "config/zones/TN.yaml",
    "content": "bounding_box:\n  - - 7.479074790747944\n    - 30.228951492661125\n  - - 11.565115651156532\n    - 37.33570884113219\ncenter_point:\n  - 9.490716854735648\n  - 33.894911522715674\ncentroid:\n  - 9.817171411150756\n  - 34.5145608310616\ncapacity:\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4700.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 5320.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 5770.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 510.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 770.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\ncountry: TN\ncountry_name: Tunisia\ncurrency: TND\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9581679311959953\n        geothermal: 0.0\n        hydro: 0.000653601950745065\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0013072328477531723\n        solar: 0.014893328548024278\n        unknown: 0.009991049199192015\n        wind: 0.014986784359507897\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9580032395060685\n        geothermal: 0.0\n        hydro: 0.0006531734473420515\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.001337065870002075\n        solar: 0.014851571340234765\n        unknown: 0.009993849327866806\n        wind: 0.01516080650910127\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Tunis\nzone_name: Tunisia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/TO.yaml",
    "content": "bounding_box:\n  - - -175.36315363153622\n    - -21.268564251344372\n  - - -175.06435064350634\n    - -21.114007305384874\ncenter_point:\n  - -175.21375213752128\n  - -21.191285778364623\ncentroid:\n  - -175.19155191551909\n  - -21.168865480648275\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: TO\ncountry_name: Tonga\ncurrency: TOP\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Tongatapu\nzone_name: Tonga\n"
  },
  {
    "path": "config/zones/TR.yaml",
    "content": "_comment: https://doi.org/10.1016/j.rser.2017.01.060 says pumped hydro not economically viable. http://www.hurriyetdailynews.com/turkey-plans-to-hold-new-big-tenders-for-wind-solar-plants-by-summer-2018-minister-127769 says battery will be tendered summer 2018 so below battery storage will need to be updated when built.\nbounding_box:\n  - - 25.662856628566317\n    - 35.82019212102932\n  - - 44.80784807848079\n    - 42.09835250921752\ncenter_point:\n  - 35.36795764440553\n  - 39.05209407218814\ncentroid:\n  - 33.42393423934243\n  - 39.04288107342735\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 470.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 590.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 780.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1100.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1530.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1810.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1950.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 18470.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 18800.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 19350.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 19640.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 21020.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 25690.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 26940.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1060.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1280.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1520.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1620.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1730.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1750.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 1800.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 27270.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 28290.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 28500.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 30980.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 31490.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 31570.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 31960.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 32390.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 570.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3420.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 5060.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 6000.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 6670.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 7820.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 9430.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 11290.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 19880.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 6520.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 7010.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 7590.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 8830.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 10610.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 11400.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 11810.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 12970.0\ncontributors:\n  - corradio\n  - olivierSemet\n  - lorrieq\n  - nessie2013\n  - lgrigoryeva1\ncountry: TR\ncountry_name: Turkey\ncurrency: TRY\nemissionFactors:\n  direct: {}\n  lifecycle:\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.15\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00447573668919221\n        coal: 0.29455425253480794\n        gas: 0.37610941772448897\n        geothermal: 0.011664508019186021\n        hydro: 0.2549484099779193\n        hydro discharge: 0.0002358906824377203\n        nuclear: 0.004027200534922298\n        oil: 0.007483557905129295\n        solar: 0.0004407347689209084\n        unknown: 0.0012528377189074996\n        wind: 0.04480745016009116\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.005549054159894021\n        coal: 0.3397222047127162\n        gas: 0.322224028097778\n        geothermal: 0.015342004884610608\n        hydro: 0.24555819271552934\n        hydro discharge: 0.00034113540663522203\n        nuclear: 0.005663449615526357\n        oil: 0.006218374687878498\n        solar: 0.0005742693125482187\n        unknown: 0.0022243474269209285\n        wind: 0.056582927925546325\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0064431653515594906\n        coal: 0.3318566844717485\n        gas: 0.37347897633985205\n        geothermal: 0.01806638559341962\n        hydro: 0.19916103883788258\n        hydro discharge: 7.381019486995707e-05\n        nuclear: 0.0022817444064741218\n        oil: 0.005115591225434979\n        solar: 0.000253433463225486\n        unknown: 0.0023506724546671133\n        wind: 0.060918493511586104\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007840819082204459\n        coal: 0.3812810205843188\n        gas: 0.3057747815233601\n        geothermal: 0.023384421110012734\n        hydro: 0.2045418889021285\n        hydro discharge: 5.836061618070991e-07\n        nuclear: 0.0024423723473140173\n        oil: 0.004845686034269546\n        solar: 0.00035670578799578106\n        unknown: 0.002350573582802984\n        wind: 0.067181145728177\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.010771810724503414\n        coal: 0.387523574157437\n        gas: 0.18803611332895226\n        geothermal: 0.028059113056053134\n        hydro: 0.3031933247961294\n        hydro discharge: 2.0891374289859645e-07\n        nuclear: 0.0025508269541652195\n        oil: 0.003182294184933182\n        solar: 0.0007800189489047749\n        unknown: 0.0022523648555587\n        wind: 0.07365034202328911\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.013890985564110633\n        coal: 0.3639402849464412\n        gas: 0.23257050199846696\n        geothermal: 0.03175056110163793\n        hydro: 0.2666123560303256\n        hydro discharge: 1.7484991933144762e-06\n        nuclear: 0.002340484870466009\n        oil: 0.001083094047411017\n        solar: 0.001604934601057996\n        unknown: 0.0023828476810764747\n        wind: 0.08382219491902627\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.018513689014875746\n        coal: 0.3278612307627827\n        gas: 0.3377214789960684\n        geothermal: 0.031691318333691855\n        hydro: 0.1771295449147192\n        hydro discharge: 6.16900593095202e-07\n        nuclear: 0.0011176763914933416\n        oil: 0.0012192951333321162\n        solar: 0.004927610215828671\n        unknown: 0.002750875918525015\n        wind: 0.097066664273708\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.02384534209020378\n        coal: 0.3642920354117356\n        gas: 0.2321778173903983\n        geothermal: 0.032464657686635257\n        hydro: 0.21937045796403212\n        hydro discharge: 6.707000607486468e-07\n        nuclear: 0.0025642049382941473\n        oil: 0.0032478870201411505\n        solar: 0.009042507379945263\n        unknown: 0.0028592037909918513\n        wind: 0.1101352106228162\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.026104647931286595\n        coal: 0.3807048875335822\n        gas: 0.2178821967318576\n        geothermal: 0.03247042617594666\n        hydro: 0.2133685556425156\n        hydro discharge: 5.530056529593041e-06\n        nuclear: 0.0017489030667731027\n        oil: 0.003560548398571876\n        solar: 0.012717680161991889\n        unknown: 0.0027890968499504148\n        wind: 0.10864752493444337\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.025341444823250462\n        coal: 0.3789764061489503\n        gas: 0.19713963353257527\n        geothermal: 0.03161159106536572\n        hydro: 0.23246352481785487\n        hydro discharge: 1.1808163773602935e-05\n        nuclear: 0.0006694173726364108\n        oil: 0.002481344783146319\n        solar: 0.016206573078968178\n        unknown: 0.0023705547277017153\n        wind: 0.11272769958002037\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: TR.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: TR.fetch_price\n  production: TR.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\n\nregion: Asia\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\ntimezone: Europe/Istanbul\nzone_name: Turkey\n"
  },
  {
    "path": "config/zones/TT.yaml",
    "content": "bounding_box:\n  - - -61.92961929619291\n    - 10.056407879280513\n  - - -60.52920529205288\n    - 11.351537843107792\ncenter_point:\n  - -61.229412294122895\n  - 10.703972861194153\ncentroid:\n  - -61.15621156211557\n  - 10.667480248953716\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2060.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: TT\ncountry_name: Trinidad and Tobago\ncurrency: TTD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Port_of_Spain\nzone_name: Trinidad and Tobago\n"
  },
  {
    "path": "config/zones/TW.yaml",
    "content": "bounding_box:\n  - - 120.05940059400595\n    - 21.904342653342525\n  - - 122.0070200702007\n    - 25.271680559293472\ncenter_point:\n  - 120.95077090897324\n  - 23.78286029781481\ncentroid:\n  - 121.0649474915802\n  - 23.646121101351014\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 90.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 16790.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 18440.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 19240.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 19210.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 19120.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 14770.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 16260.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 17150.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 18040.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 18550.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 17510.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 17690.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 18810.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2090.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2100.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 2120.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 5140.0\n    - datetime: '2018-12-05'\n      source: Ember, Yearly electricity data, https://en.wikipedia.org/wiki/Nuclear_power_in_Taiwan#List_of_nuclear_power_stations_in_Taiwan\n      value: 4510.0\n    - datetime: '2019-07-15'\n      source: Ember, Yearly electricity data, https://en.wikipedia.org/wiki/Nuclear_power_in_Taiwan#List_of_nuclear_power_stations_in_Taiwan\n      value: 3870.0\n    - datetime: '2021-12-27'\n      source: Ember, Yearly electricity data, https://en.wikipedia.org/wiki/Nuclear_power_in_Taiwan#List_of_nuclear_power_stations_in_Taiwan\n      value: 2890.0\n    - datetime: '2023-03-14'\n      source: Ember, Yearly electricity data, https://en.wikipedia.org/wiki/Nuclear_power_in_Taiwan#List_of_nuclear_power_stations_in_Taiwan\n      value: 1900.0\n    - datetime: '2024-07-27'\n      source: Ember, Yearly electricity data, https://en.wikipedia.org/wiki/Nuclear_power_in_Taiwan#List_of_nuclear_power_stations_in_Taiwan\n      value: 950.0\n    - datetime: '2025-05-18'\n      source: Ember, Yearly electricity data, https://en.wikipedia.org/wiki/Nuclear_power_in_Taiwan#List_of_nuclear_power_stations_in_Taiwan\n      value: 0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3340.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 3400.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 3390.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2410.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 2420.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2440.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1770.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 2740.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 4150.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 5820.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 7700.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 9720.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 12420.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 14280.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 690.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 710.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 850.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 940.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1090.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1580.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 2680.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 3890.0\ncontributors:\n  - corradio\n  - MariusKroon\n  - nessie2013\n  - Manu1400\n  - VIKTORVAV99\ncountry: TW\ncountry_name: Taiwan\ncurrency: TWD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 458.44\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 434.48\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 428.64\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 407.82\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 394.58\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 430.45\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 465.73\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 460.14\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 453.79\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 442.33\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 400.71\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 429.6\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 491.44\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 467.48\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 461.64\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 440.82\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 427.58\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 463.45\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 489.73\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 484.14\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 477.79\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 466.33\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 424.71\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 453.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3706052541102282\n        gas: 0.40778036152811137\n        geothermal: 0.0\n        hydro: 0.018084319726191907\n        hydro discharge: 0.011494245473755216\n        nuclear: 0.11340429026328654\n        oil: 0.01991767200554011\n        solar: 0.021896871257044554\n        unknown: 0.028841697275736218\n        wind: 0.007975282294229025\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.37060528568477596\n        gas: 0.4077803962851845\n        geothermal: 0.0\n        hydro: 0.01808432127437323\n        hydro discharge: 0.01149424645776658\n        nuclear: 0.11340429989541254\n        oil: 0.019917673710672965\n        solar: 0.02189678790410531\n        unknown: 0.028841699719410724\n        wind: 0.007975282976985316\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0003596578892712555\n        coal: 0.3746553541640068\n        gas: 0.3993411481992436\n        geothermal: 3.447412049312806e-05\n        hydro: 0.02423354543834702\n        hydro discharge: 0.013740494011898363\n        nuclear: 0.10053922476738113\n        oil: 0.045529854255951026\n        solar: 0.006745768039964845\n        unknown: 0.02854771353989644\n        wind: 0.006272777279103801\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.7089383950210196e-05\n        coal: 0.3913510767847105\n        gas: 0.38789934011297766\n        geothermal: 1.6415566571530344e-06\n        hydro: 0.018100534017322787\n        hydro discharge: 0.014033146545897398\n        nuclear: 0.11425726573037687\n        oil: 0.027304275799357458\n        solar: 0.009978976450179495\n        unknown: 0.03056141449389499\n        wind: 0.00649523540192735\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.68525600104535e-05\n        coal: 0.3744613342678336\n        gas: 0.3856277443494591\n        geothermal: 8.315467349067612e-06\n        hydro: 0.02193097287070084\n        hydro discharge: 0.013149882335037243\n        nuclear: 0.1332038701768708\n        oil: 0.01809821395879775\n        solar: 0.015070280446698725\n        unknown: 0.030599396699257434\n        wind: 0.007763132713793275\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.870625867900523e-07\n        coal: 0.3665202012021083\n        gas: 0.41004464890239833\n        geothermal: 5.6970699204729406e-08\n        hydro: 0.011772650266755858\n        hydro discharge: 0.012959038084840608\n        nuclear: 0.12678412599324346\n        oil: 0.011495414554899374\n        solar: 0.021499298892222372\n        unknown: 0.03029987131859305\n        wind: 0.008624100312598925\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.602692029329936e-05\n        coal: 0.3555654043482704\n        gas: 0.4268217629988942\n        geothermal: 1.5325492764897934e-06\n        hydro: 0.013354366712019783\n        hydro discharge: 0.01253669087118548\n        nuclear: 0.10752850258842009\n        oil: 0.01381954682112957\n        solar: 0.030643392043559092\n        unknown: 0.03206499678203981\n        wind: 0.007647779407983859\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.974302895641078e-05\n        coal: 0.35015697614967695\n        gas: 0.4348168067397584\n        geothermal: 3.7965248953612576e-06\n        hydro: 0.022201109795551385\n        hydro discharge: 0.01203336325405006\n        nuclear: 0.09136301342348718\n        oil: 0.013041141269349743\n        solar: 0.04006599890555345\n        unknown: 0.0238810630402633\n        wind: 0.0123969870169916\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0006333263045828865\n        coal: 0.34230576964974213\n        gas: 0.44102512442401576\n        geothermal: 5.025645592689123e-05\n        hydro: 0.01521343851484505\n        hydro discharge: 0.012472721818145627\n        nuclear: 0.06557024993694675\n        oil: 0.011556254457525155\n        solar: 0.0540555126798096\n        unknown: 0.032469315291553814\n        wind: 0.02464801290763082\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0007620468432727478\n        coal: 0.3129056504461501\n        gas: 0.474387698608467\n        geothermal: 7.901000509662672e-05\n        hydro: 0.015621533826100467\n        hydro discharge: 0.0025889135106097845\n        nuclear: 0.04639313121955526\n        oil: 0.012854592345508153\n        solar: 0.06550111905166345\n        unknown: 0.03142705539402686\n        wind: 0.037479238587619625\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2042\n    - datetime: '2021-01-01'\n      value: 0.1856\n    - datetime: '2022-01-01'\n      value: 0.1873\n    - datetime: '2023-01-01'\n      value: 0.2296\n    - datetime: '2024-01-01'\n      value: 0.2046\n    - datetime: '2025-01-01'\n      value: 0.1437\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1756\n    - datetime: '2021-01-01'\n      value: 0.1689\n    - datetime: '2022-01-01'\n      value: 0.1737\n    - datetime: '2023-01-01'\n      value: 0.1834\n    - datetime: '2024-01-01'\n      value: 0.2292\n    - datetime: '2025-01-01'\n      value: 0.1457\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.0776\n    - datetime: '2021-01-01'\n      value: 0.0922\n    - datetime: '2022-01-01'\n      value: 0.1078\n    - datetime: '2023-01-01'\n      value: 0.1217\n    - datetime: '2024-01-01'\n      value: 0.1307\n    - datetime: '2025-01-01'\n      value: 0.1437\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.0351\n    - datetime: '2021-01-01'\n      value: 0.0518\n    - datetime: '2022-01-01'\n      value: 0.0751\n    - datetime: '2023-01-01'\n      value: 0.1073\n    - datetime: '2024-01-01'\n      value: 0.1531\n    - datetime: '2025-01-01'\n      value: 0.1457\nparsers:\n  production: TAIPOWER.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Asia/Taipei\nzone_name: Taiwan\n"
  },
  {
    "path": "config/zones/TZ.yaml",
    "content": "bounding_box:\n  - - 29.320493204932063\n    - -11.731828252510063\n  - - 40.448204482044844\n    - -0.999999951214068\ncenter_point:\n  - 34.76378616239491\n  - -6.36168514408601\ncentroid:\n  - 35.36215659970235\n  - -7.420304556123768\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 620.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 890.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1020.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1100.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1150.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 590.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 600.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 680.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 120.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: TZ\ncountry_name: Tanzania\ncurrency: TZS\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0075864057233629555\n        coal: 0.0\n        gas: 0.6937543456433861\n        geothermal: 0.0\n        hydro: 0.2930479578005183\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0024941318453953606\n        solar: 0.0031174416434825414\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.007587026071223141\n        coal: 0.0\n        gas: 0.6937547839383098\n        geothermal: 0.0\n        hydro: 0.29304672506100865\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0024937785407519878\n        solar: 0.003117324755408123\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Dar_es_Salaam\nzone_name: Tanzania\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/UA-CR.yaml",
    "content": "bounding_box:\n  - - 32.513725137251384\n    - 44.38236071061901\n  - - 36.58176581765818\n    - 46.21843998530454\ncenter_point:\n  - 34.22558309572931\n  - 45.33583364209598\ncentroid:\n  - 34.533925984421145\n  - 45.25458261532593\ncountry: UA\ncountry_name: Ukraine\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Europe/Kiev\nzone_name: Crimea\n"
  },
  {
    "path": "config/zones/UA.yaml",
    "content": "bounding_box:\n  - - 22.131221312213142\n    - 45.21525091940076\n  - - 40.14220142201424\n    - 52.369234001359445\ncenter_point:\n  - 31.07915362623503\n  - 49.18913246482947\ncentroid:\n  - 31.01351219697766\n  - 48.775475185744476\ncapacity:\n  biomass: 230\n  coal: 17242\n  gas: 4600\n  hydro: 4829\n  hydro storage: 1488\n  nuclear: 13835\n  oil: 756.6\n  solar: 6226\n  wind: 1529\ncontributors:\n  - amkozlov\n  - denplis\n  - corradio\n  - MariusKroon\n  - alixunderplatz\ncountry: UA\ncountry_name: Ukraine\ncurrency: UAH\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 231.08\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 197.62\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 188.58\n    unknown:\n      _comment: estimated yearly share of solar & wind in this mixed renewable category\n        based on installed capacity in Y2018; assumes 50% solar, 50% wind renewable\n        mix\n      source: Wikipedia page for Renewable energy in Ukraine; Electricity Maps contrib\n        issue number 1809\n      value: 0.0\n  lifecycle:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 255.08\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 221.62\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 212.58\n    unknown:\n      _comment: estimated yearly share of solar & wind in this mixed renewable category\n        based on installed capacity in Y2018; assumes 50% solar, 50% wind renewable\n        mix\n      source: Wikipedia page for Renewable energy in Ukraine; Electricity Maps contrib\n        issue number 1809\n      value: 28.0\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0003207007742363035\n        coal: 0.36197749367687393\n        gas: 0.03441028126566816\n        geothermal: 5.053653651886077e-08\n        hydro: 0.06119315118308444\n        hydro discharge: 0.00017800738983977116\n        nuclear: 0.517538147598581\n        oil: 0.00021771167175741132\n        solar: 0.0003456359917361958\n        unknown: 0.015437521811214999\n        wind: 0.008381224134596929\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000291428663559246\n        coal: 0.32851664665069924\n        gas: 0.04910866540363717\n        geothermal: 3.319857488617787e-08\n        hydro: 0.07631842834340409\n        hydro discharge: 0.00010995037339205634\n        nuclear: 0.5249580456581038\n        oil: 0.00013436818975131736\n        solar: 0.0002660585374821345\n        unknown: 0.00823395511665524\n        wind: 0.012062419798608339\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0005367012629052581\n        coal: 0.2926850461913581\n        gas: 0.08111801495353033\n        geothermal: 1.045598076069642e-07\n        hydro: 0.05279596677698839\n        hydro discharge: 0.00016005638156595177\n        nuclear: 0.5386772496808447\n        oil: 0.0002691437397810854\n        solar: 0.0003801494376494432\n        unknown: 0.028702190819190617\n        wind: 0.0046753618436726685\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000741683991074143\n        coal: 0.26858395474362196\n        gas: 0.10042702803341369\n        geothermal: 3.5875438696470174e-07\n        hydro: 0.053625640644993276\n        hydro discharge: 0.00023836674894553778\n        nuclear: 0.5187925726462157\n        oil: 0.00024380577165180974\n        solar: 0.0004421171590188602\n        unknown: 0.05611170814842644\n        wind: 0.0007927279538897991\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0004007700847165575\n        coal: 0.23790902163235403\n        gas: 0.06650451137518848\n        geothermal: 6.14361665134054e-08\n        hydro: 0.06828262097908955\n        hydro discharge: 0.00014736549503653327\n        nuclear: 0.5554737027736063\n        oil: 0.0001382531417737613\n        solar: 0.0002797324282031978\n        unknown: 0.07014106420239602\n        wind: 0.0007228955699344927\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0005856419728721687\n        coal: 0.2197402850455743\n        gas: 0.075657311046996\n        geothermal: 1.1470637943463454e-07\n        hydro: 0.07490293221673931\n        hydro discharge: 0.00022645177467557376\n        nuclear: 0.5626005759244308\n        oil: 0.00024069649584799584\n        solar: 0.0003683239452081555\n        unknown: 0.06410479689732768\n        wind: 0.001572880539009946\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.6475\n    - datetime: '2021-01-01'\n      value: 0.7077\n    - datetime: '2022-01-01'\n      value: 0.7125\n  unknown:\n    value: 1\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.0958\n    - datetime: '2021-01-01'\n      value: 0.1171\n    - datetime: '2022-01-01'\n      value: 0.119\n  unknown:\n    value: 1\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  price: ENTSOE.fetch_price\n  production: UA.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\nsources:\n  Electricity Maps contrib issue number 1809:\n    link: https://github.com/electricitymaps/electricitymaps-contrib/issues/1809\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  Wikipedia page for Renewable energy in Ukraine:\n    link: https://en.wikipedia.org/wiki/Renewable_energy_in_Ukraine\ntimezone: Europe/Kiev\nzone_name: Ukraine\n"
  },
  {
    "path": "config/zones/UG.yaml",
    "content": "bounding_box:\n  - - 29.554495544955472\n    - -1.469533257365882\n  - - 34.97974979749799\n    - 4.219021003643483\ncenter_point:\n  - 32.282368350850085\n  - 1.2986888296080246\ncentroid:\n  - 32.12486145396523\n  - 1.6522897558541663\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 700.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 740.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1000.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1010.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1030.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 140.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\ncountry: UG\ncountry_name: Uganda\ncurrency: UGX\nemissionFactors:\n  lifecycle: {}\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08659463755380915\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.8619674957821306\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.026151723457783355\n        solar: 0.02528580375353232\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08659508173891416\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.8619659873381036\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.026150638258165812\n        solar: 0.02528760510767805\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Kampala\nzone_name: Uganda\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n"
  },
  {
    "path": "config/zones/US-AK-SEAPA.yaml",
    "content": "bounding_box:\n  - - -132.98290571964566\n    - 55.29253861844952\n  - - -131.5243655557632\n    - 56.82198154784774\ncenter_point:\n  - -132.35527020065993\n  - 56.423603690102524\ncentroid:\n  - -132.25451087665854\n  - 56.11769324858722\ncontributors:\n  - wrma6\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9950322513728563\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.004966263956675667\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  production: SEAPA.fetch_production\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: America/Anchorage\nzone_name: Southeast Alaska Power Agency\n"
  },
  {
    "path": "config/zones/US-AK.yaml",
    "content": "bounding_box:\n  - - -178.21438214382135\n    - 51.35030302429311\n  - - 179.780397803978\n    - 71.35397886338464\ncenter_point:\n  - -154.0273461239334\n  - 63.44731706974936\ncentroid:\n  - -145.59951380519547\n  - 59.357287708720236\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1054.5899917811341\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1040.2108414955262\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1051.2364608925723\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 549.6543077858046\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 470.79860929575693\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 442.92371913492497\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 442.8330050139731\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 454.4318787852343\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 713.1828106549987\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 663.8839597479941\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 665.4770914121948\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 682.5489198648306\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1114.5899917811341\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1100.2108414955262\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1111.2364608925723\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 609.6543077858046\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 590.7986092957569\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 562.923719134925\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 562.8330050139731\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 574.4318787852343\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 957.1828106549987\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 907.8839597479941\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 909.4770914121948\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 926.5489198648306\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: America/Anchorage\nzone_name: Alaska\n"
  },
  {
    "path": "config/zones/US-CAL-BANC.yaml",
    "content": "bounding_box:\n  - - -123.59823598235975\n    - 38.26018835122328\n  - - -121.07101071010703\n    - 41.3570516017451\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 9.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1838.1\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1865.9\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 1913.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2549.9\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 734.1\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 737.6\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 737.1\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 739.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2557.2\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 2553.7\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2557.2\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 71.2\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 120.5\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 123.0\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 125.7\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 129.2\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 130.2\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 131.5\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 133.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 145.0\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 147.4\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 149.1\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 162.1\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 164.6\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 324.6\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 325.7\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 327.0\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 337.0\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 338.6\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 388.6\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 389.6\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -123.00423004230035\n  - 39.977487750773264\ncentroid:\n  - -122.47793906510489\n  - 40.02089726337301\ncomment: Balancing Authority Of Northern California\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 389.63414386514245\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 397.3761473768025\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 422.466789435152\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 401.96410840720097\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 509.63414386514245\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 517.3761473768025\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 542.466789435152\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 521.9641084072009\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6052277234496899\n        geothermal: 0.0\n        hydro: 0.34364311682989807\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.040804343403625744\n        unknown: 0.01032493743321905\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6052307867166514\n        geothermal: 0.0\n        hydro: 0.34364485612663803\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.04079948900644817\n        unknown: 0.010324989691300584\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0005096419096147744\n        biomass: 0.0011564724463007448\n        coal: 0.002285789674731599\n        gas: 0.5646533284336857\n        geothermal: 0.0020126063368234894\n        hydro: 0.35535334865520163\n        hydro discharge: 1.063472080100037e-05\n        nuclear: 0.007382116464029082\n        oil: 0.00018102102074265614\n        solar: 0.0507876286045151\n        unknown: 0.00965145001357421\n        wind: 0.006016157264754862\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 6.769890898948189e-06\n        biomass: 0.0005775254397832327\n        coal: 0.006896109517964832\n        gas: 0.4700631273025387\n        geothermal: 0.0010543328007071586\n        hydro: 0.41964469233966306\n        hydro discharge: 2.029537570394104e-05\n        nuclear: 0.03328487895341877\n        oil: 0.0002996369067903883\n        solar: 0.022661591042147294\n        unknown: 0.01691509054463524\n        wind: 0.02857549026390245\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 1.7029555746578e-05\n        biomass: 0.0009381678103176315\n        coal: 0.015643452764050596\n        gas: 0.35793091131440996\n        geothermal: 0.0014932693807477308\n        hydro: 0.5193539358231197\n        hydro discharge: 1.5270497311533397e-06\n        nuclear: 0.027922852372277308\n        oil: 0.0007743515488217318\n        solar: 0.031654975356526366\n        unknown: 0.01857340477798842\n        wind: 0.025695772187790067\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 3.1196143164842676e-05\n        biomass: 0.001265121648808031\n        coal: 0.006529263789204688\n        gas: 0.40669735963738946\n        geothermal: 0.002389116528332279\n        hydro: 0.4463453424173102\n        hydro discharge: 4.802262070683596e-06\n        nuclear: 0.0335757568223394\n        oil: 0.0003223597653127159\n        solar: 0.035233181992805375\n        unknown: 0.032454352388855426\n        wind: 0.03515171372122809\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 7.62351056912024e-05\n        biomass: 0.0010329326889443754\n        coal: 0.010181792699240362\n        gas: 0.4806383992783561\n        geothermal: 0.0018585687015784276\n        hydro: 0.3550476833457144\n        hydro discharge: 3.927199332207977e-06\n        nuclear: 0.029524816086673168\n        oil: 0.0005563928710163021\n        solar: 0.05785144065464371\n        unknown: 0.026537209403012258\n        wind: 0.03669022786102927\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0007257703706554069\n        biomass: 0.0017602161868243264\n        coal: 0.011648701113703492\n        gas: 0.4214822722781735\n        geothermal: 0.0031650018721092734\n        hydro: 0.3904342446464654\n        hydro discharge: 5.8497930618155e-10\n        nuclear: 0.03572269144907318\n        oil: 0.0006200944439730161\n        solar: 0.06764080560120961\n        unknown: 0.02648854331483367\n        wind: 0.04031142063640155\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.001197709678106658\n        biomass: 0.0022394255196702324\n        coal: 0.006978919118923201\n        gas: 0.4598333377036999\n        geothermal: 0.004119979775482727\n        hydro: 0.3906991545618419\n        hydro discharge: 1.3237153451931838e-07\n        nuclear: 0.020392894466665944\n        oil: 0.000288460437891739\n        solar: 0.0744642800200534\n        unknown: 0.010723549179566916\n        wind: 0.029061953194061976\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0012202232799760192\n        biomass: 0.0014940580380310275\n        coal: 0.005999459225693776\n        gas: 0.47153418851480644\n        geothermal: 0.0025939173928126824\n        hydro: 0.3813171045545897\n        hydro discharge: 2.7953553589006627e-08\n        nuclear: 0.022103448453041817\n        oil: 0.0001501583367603468\n        solar: 0.07278678480519393\n        unknown: 0.008333564061770537\n        wind: 0.032467024035805404\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Balancing Authority of Northern California\nzone_short_name: BANC\n"
  },
  {
    "path": "config/zones/US-CAL-CISO.yaml",
    "content": "bounding_box:\n  - - -124.38664386643859\n    - 32.53156377089108\n  - - -114.15534155341547\n    - 41.464382814216975\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 87.5\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 95.5\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 125.5\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 127.5\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 131.1\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 136.6\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 176.6\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 179.1\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 179.6\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 183.1\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 186.8\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 188.6\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 190.1\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 196.0\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 197.0\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 199.0\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 200.5\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 201.1\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 207.1\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 208.1\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 458.5\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 478.5\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 479.5\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 479.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 604.3\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 614.3\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 729.9\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 843.4\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 1358.4\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 1473.4\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 1698.5\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 1743.5\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 1843.5\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 1938.5\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 2163.5\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 2273.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2415.0\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 2481.5\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 2562.0\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 3174.5\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 3178.4\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 3353.4\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 3426.4\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 3812.4\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 4295.3\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 4665.3\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 4818.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 4947.2\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 5003.2\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 5083.2\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 5564.2\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 6132.0\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 6419.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 6806.0\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 6975.0\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 7373.8\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 8055.8\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 8067.7\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 8471.7\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 8861.3\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 9218.7\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 9503.7\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 9896.7\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 10239.5\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 10794.0\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 10977.0\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 11150.5\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 11626.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 11673.5\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 11893.5\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 11993.0\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 12510.3\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 13060.1\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 13562.1\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 13818.6\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 14467.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 15435.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 15534.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1053.8\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 1051.2\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 1059.2\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 1058.7\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 1057.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1048.4\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 1051.4\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 1016.4\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 1023.9\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 1059.1\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 1047.1\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 1042.5\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 1044.5\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 1040.8\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 1036.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1008.6\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 1009.6\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 1020.6\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 1008.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 988.7\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 990.1\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 995.1\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 997.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 992.9\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 995.1\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 999.1\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 993.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 969.5\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 972.3\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 936.7\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 912.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 821.7\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 831.4\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 835.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 55.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 34920.7\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 34927.9\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 34817.9\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 34770.9\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 34743.9\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 33890.0\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 33316.0\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 32650.0\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 32656.6\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 32658.6\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 32649.0\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 32527.9\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 32489.6\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 32278.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 32328.2\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 32266.0\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 32268.5\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 32270.4\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 32271.5\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 32233.4\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 31738.4\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 31737.4\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 30665.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 30943.4\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 32299.6\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 32440.6\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 32438.3\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 32435.3\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 32485.2\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 32481.7\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 32478.7\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 32477.6\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 32474.8\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 32475.8\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 32473.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 32555.9\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 32554.8\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 32623.2\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 32621.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 32711.2\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 32712.7\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 32708.1\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 31886.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 31902.2\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 31950.2\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 31911.0\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 31900.2\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 31881.9\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 31883.3\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 31884.9\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2008.5\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1993.5\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 2037.9\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 2034.9\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6602.3\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 6609.2\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 6575.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 6566.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 6140.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 6136.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 6338.2\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 6333.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 6052.1\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 6042.1\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 6043.1\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 6041.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 6161.1\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 6162.0\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 6196.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 6218.3\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1367.8\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1660.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1543.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1768.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1568.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1877.8\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2077.6\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 1024.6\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2323.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 267.0\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 192.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 192.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 160.3\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 160.2\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 163.2\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 10330.2\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 10363.5\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 10403.5\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 10432.8\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 10510.1\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 10540.8\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 10563.8\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 10733.8\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 10956.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 11121.7\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 11142.8\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 11353.1\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 11359.8\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 11362.8\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 11364.0\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 11374.3\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 11376.0\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 11395.8\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 11651.1\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 11878.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 11941.1\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 12091.1\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 12092.8\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 12093.8\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 12253.9\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 12247.4\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 12348.7\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 12373.7\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 12489.0\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 12823.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 13129.2\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 13138.5\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 13140.9\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 13174.4\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 13319.6\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 13369.6\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 13374.0\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 13378.7\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 13383.7\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 13674.2\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 14616.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 14638.2\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 14681.5\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 14689.5\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 14697.0\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 14867.9\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 14885.7\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 14895.2\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 15171.8\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 15087.2\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 15248.9\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 15869.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 15866.9\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 16089.2\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 16378.1\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 16496.9\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 16515.3\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 16765.3\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 17054.5\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 17061.6\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 17166.9\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 17498.0\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 17942.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 17942.5\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 17952.0\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 17954.0\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 18062.2\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 18553.4\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 18669.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 19194.3\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 19583.0\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 19593.8\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 20397.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 20492.6\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 20962.9\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 20971.4\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 21252.3\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 21687.8\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 21699.0\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 21707.4\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 21708.9\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 21796.2\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 21811.5\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 23004.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 23127.7\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 23351.5\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 23356.7\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 23621.3\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 23659.9\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 23663.6\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 23820.4\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 24163.2\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 24348.4\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 24853.2\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 81.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 99.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 100.7\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 66.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 62.7\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 43.4\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 51.4\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 5543.9\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 5545.8\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 5591.8\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 5736.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 5723.5\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 5726.3\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 5729.9\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 5731.8\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 5925.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 5923.5\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 5925.3\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 5880.8\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 6010.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 5906.8\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 5873.7\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 5858.4\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 5781.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 5777.5\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 5949.7\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 6010.9\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 6068.4\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 6128.6\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 6063.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 6035.3\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 6040.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 6113.9\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 6084.2\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 6179.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 6162.1\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 6247.6\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 6277.6\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 6328.1\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 6361.7\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 6377.2\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 6380.8\ncenter_point:\n  - -119.07034654209747\n  - 36.502920520723094\ncentroid:\n  - -120.31387899110109\n  - 36.98846669879115\ncomment: California Independent System Operator\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\n  - alejandranavcas\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 187.8\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 178.09\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 163.12\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 164.49\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 127.78\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 105.29\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 514.474308780614\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 525.4947593257697\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 495.9798560561009\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 517.8604330816302\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 404.4721980786223\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 389.8140694590953\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 389.10232982859753\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 396.3628485714517\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 95.82104392270246\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 104.44489014797767\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 39.63105218869798\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 38.89697026267566\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 168.9\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 131.67\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 166.22\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 156.71\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 74.59\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 70.37\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 910.2232446220032\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1120.2456876211616\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 987.7827758191105\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 945.4848707544354\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 220.8\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 211.09\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 196.12\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 197.49\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 160.78\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 138.29\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 574.474308780614\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 585.4947593257697\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 555.979856056101\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 577.8604330816302\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 524.4721980786223\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 509.8140694590953\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 509.10232982859753\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 516.3628485714517\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 133.82104392270247\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 142.44489014797767\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 77.63105218869798\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 76.89697026267567\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 192.9\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 155.67\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 190.22\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 180.71\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 98.59\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 94.37\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1154.2232446220032\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1364.2456876211616\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1231.7827758191106\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1189.4848707544354\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.006172136732138123\n        biomass: 0.022851879516327767\n        coal: 0.0006894076237176295\n        gas: 0.42830493454659185\n        geothermal: 0.04603533725234542\n        hydro: 0.11222325949134329\n        hydro discharge: 0.0\n        nuclear: 0.09827297987284417\n        oil: 0.0039328447075751725\n        solar: 0.17885726724921625\n        unknown: 0.00010202406759688955\n        wind: 0.10255786296892402\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.006172283600951642\n        biomass: 0.022852423287241616\n        coal: 0.0006894240284870183\n        gas: 0.42831512625819695\n        geothermal: 0.04603643268422836\n        hydro: 0.11222592989507642\n        hydro discharge: 0.0\n        nuclear: 0.09827531832330003\n        oil: 0.003932938291411862\n        solar: 0.17883772778845736\n        unknown: 0.00010202649530619165\n        wind: 0.10256030338013089\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.008745900277298317\n        biomass: 0.01791465740923801\n        coal: 0.03935812211871065\n        gas: 0.393122135783743\n        geothermal: 0.031122072216720538\n        hydro: 0.13595445704717873\n        hydro discharge: 0.0001255819673032426\n        nuclear: 0.10796182454397649\n        oil: 0.0028019209054002342\n        solar: 0.15843506178826441\n        unknown: 0.014738516089861868\n        wind: 0.08971975114695534\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.00024779470336004866\n        biomass: 0.01887146244958759\n        coal: 0.05506129878425141\n        gas: 0.36331637095370795\n        geothermal: 0.03614471653896517\n        hydro: 0.15725559564484315\n        hydro discharge: 0.0002554376566867246\n        nuclear: 0.1435316560656351\n        oil: 0.0005658067996148073\n        solar: 0.12650194316905944\n        unknown: 0.016072441691963136\n        wind: 0.08217547954060522\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0003655786781363958\n        biomass: 0.020971047964617386\n        coal: 0.03803514436790687\n        gas: 0.35754150937906803\n        geothermal: 0.03279576393461317\n        hydro: 0.18127003018137938\n        hydro discharge: 4.660611217469498e-05\n        nuclear: 0.13883063529995024\n        oil: 0.00025593763316298854\n        solar: 0.13418074561647975\n        unknown: 0.015067130820912645\n        wind: 0.0806398736171873\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.00038063792195789774\n        biomass: 0.019093284007881444\n        coal: 0.02801236082863176\n        gas: 0.4088770781935791\n        geothermal: 0.03344028747374063\n        hydro: 0.15616291874661187\n        hydro discharge: 8.802889435916022e-05\n        nuclear: 0.10699257385868884\n        oil: 0.00018507926673506318\n        solar: 0.14109077176044946\n        unknown: 0.02131616525197883\n        wind: 0.08436081045482358\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.003787503787345547\n        biomass: 0.018940442043772522\n        coal: 0.029680562773469928\n        gas: 0.41765653725602275\n        geothermal: 0.03414134848811495\n        hydro: 0.1110908531992655\n        hydro discharge: 0.00011473167849182239\n        nuclear: 0.11393977766081624\n        oil: 0.0001454174224561264\n        solar: 0.15272724865324827\n        unknown: 0.01862850165571819\n        wind: 0.0991470633248867\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.01172713024603653\n        biomass: 0.01771720387867232\n        coal: 0.023819540471454306\n        gas: 0.40877287742962115\n        geothermal: 0.03128291423151499\n        hydro: 0.12116811033835685\n        hydro discharge: 1.2120395291930557e-06\n        nuclear: 0.1084426639990897\n        oil: 0.00013075100778864443\n        solar: 0.16003725004195615\n        unknown: 0.015736919706102484\n        wind: 0.10116342174173903\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.018870953955964668\n        biomass: 0.016928069770853472\n        coal: 0.015825801981532644\n        gas: 0.41888767628745516\n        geothermal: 0.029960095222121622\n        hydro: 0.12363922134211122\n        hydro discharge: 2.7985531196661356e-06\n        nuclear: 0.10359993565992458\n        oil: 5.839100498478209e-05\n        solar: 0.16717978392074975\n        unknown: 0.01159357682258882\n        wind: 0.0934536982380828\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0375211413658542\n        biomass: 0.01621556775190302\n        coal: 0.01641151039073374\n        gas: 0.34568596489162295\n        geothermal: 0.028152049196083762\n        hydro: 0.12204287521654139\n        hydro discharge: 1.6993466206144124e-07\n        nuclear: 0.10964515802773081\n        oil: 2.649576309463761e-05\n        solar: 0.2087720447881934\n        unknown: 0.011761931454553983\n        wind: 0.10376508129748757\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.5582\n    - datetime: '2021-01-01'\n      value: 0.5701\n    - datetime: '2022-01-01'\n      value: 0.5967\n    - datetime: '2023-01-01'\n      value: 0.5977\n    - datetime: '2024-01-01'\n      value: 0.6896\n    - datetime: '2025-01-01'\n      value: 0.7438\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.605\n    - datetime: '2021-01-01'\n      value: 0.6853\n    - datetime: '2022-01-01'\n      value: 0.5872\n    - datetime: '2023-01-01'\n      value: 0.6183\n    - datetime: '2024-01-01'\n      value: 0.825\n    - datetime: '2025-01-01'\n      value: 0.8306\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.4489\n    - datetime: '2021-01-01'\n      value: 0.4551\n    - datetime: '2022-01-01'\n      value: 0.4818\n    - datetime: '2023-01-01'\n      value: 0.494\n    - datetime: '2024-01-01'\n      value: 0.5824\n    - datetime: '2025-01-01'\n      value: 0.6461\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4731\n    - datetime: '2021-01-01'\n      value: 0.5826\n    - datetime: '2022-01-01'\n      value: 0.4891\n    - datetime: '2023-01-01'\n      value: 0.4907\n    - datetime: '2024-01-01'\n      value: 0.6999\n    - datetime: '2025-01-01'\n      value: 0.7632\nparsers:\n  consumption: US_CA.fetch_consumption\n  consumptionForecast: US_CA.fetch_consumption_forecast\n  gridAlerts: email_grid_alerts.fetch_grid_alerts_emails\n  production: US_CA.fetch_production\n  productionCapacity: EIA.fetch_production_capacity\n  productionPerModeForecast: US_CA.fetch_wind_solar_forecasts\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: CAISO\nzone_short_name: California ISO\n"
  },
  {
    "path": "config/zones/US-CAL-IID.yaml",
    "content": "bounding_box:\n  - - -116.40896408964083\n    - 32.61885982370154\n  - - -114.52614526145256\n    - 34.03563182833028\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 30.0\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 180.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 215.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 55.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 605.5\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 750.0\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 740.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 737.8\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 753.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 732.2\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 748.2\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 700.2\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 742.7\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 690.7\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 743.7\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 736.7\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 752.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 686.3\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 81.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 83.9\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 24.9\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 160.6\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 190.6\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 193.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 243.6\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 263.6\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 338.4\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 368.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 380.4\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 383.4\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 386.4\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 406.4\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 543.2\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 585.2\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -115.42496059751203\n  - 33.168988812011186\ncentroid:\n  - -115.57580797947463\n  - 33.30947172276724\ncomment: Imperial Irrigation District\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 206.01\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 98.96\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 471.372486346701\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 484.4162449973497\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 476.4590307322262\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 475.02972183973407\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 56.889446297258615\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 88.15169296086768\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 34.7206661443073\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 33.30793611464112\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 291.91\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 62.51\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 239.01\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 131.96\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 591.372486346701\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 604.4162449973496\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 596.4590307322262\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 595.0297218397341\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 94.88944629725862\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 126.15169296086768\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 72.7206661443073\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 71.30793611464112\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 315.91\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 86.51\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.15655312280809902\n        geothermal: 0.0\n        hydro: 0.03731973179904396\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.10943149631748342\n        unknown: 0.6966973265569043\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.15655396299230523\n        geothermal: 0.0\n        hydro: 0.037319932085366415\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.1094267173864797\n        unknown: 0.6967010655694501\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.00011862787235421618\n        biomass: 6.707293399807037e-05\n        coal: 0.0001555930895817752\n        gas: 0.1656641080904877\n        geothermal: 0.00011488927225379522\n        hydro: 0.03461560907263275\n        hydro discharge: 7.650614120915976e-09\n        nuclear: 0.0004012594094138011\n        oil: 1.0511943802138552e-05\n        solar: 0.14667583723679564\n        unknown: 0.6517894490605076\n        wind: 0.0003857261125436347\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 3.3370751105921407e-06\n        biomass: 0.0001249777569221489\n        coal: 0.010573973361110885\n        gas: 0.18598988149751836\n        geothermal: 0.00019835967054431523\n        hydro: 0.02889517209149121\n        hydro discharge: 2.263567492295037e-06\n        nuclear: 0.004883975051241278\n        oil: 1.0182986550703962e-06\n        solar: 0.06117240846427509\n        unknown: 0.7065323024453987\n        wind: 0.001621168264847555\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 8.720236830050215e-07\n        biomass: 4.932152483529173e-05\n        coal: 0.009209149197063823\n        gas: 0.17557088814857932\n        geothermal: 7.682562316142308e-05\n        hydro: 0.050663434607964186\n        hydro discharge: 5.22204143760922e-06\n        nuclear: 0.00947229160234931\n        oil: 3.5823675626152234e-06\n        solar: 0.04924932868148989\n        unknown: 0.7046497939084817\n        wind: 0.001045946954792629\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 5.580532593855049e-06\n        biomass: 0.00013878342700565503\n        coal: 0.005239553869771395\n        gas: 0.17535538680825066\n        geothermal: 0.00022517203538231784\n        hydro: 0.04722247990136\n        hydro discharge: 2.536605724479568e-06\n        nuclear: 0.0016700750246801915\n        oil: 8.673555057897877e-07\n        solar: 0.058213000085354315\n        unknown: 0.7102482870923419\n        wind: 0.0016761956088153875\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.00018412404717850533\n        biomass: 0.0002162788704019889\n        coal: 0.005477953835932532\n        gas: 0.23272257981554376\n        geothermal: 0.0003662370784189057\n        hydro: 0.05081717971981512\n        hydro discharge: 5.050757613642046e-06\n        nuclear: 0.004236535480322048\n        oil: 1.5145128912193973e-06\n        solar: 0.045545917601926\n        unknown: 0.6569335364590403\n        wind: 0.0034921488223233483\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0002561081382668459\n        biomass: 9.862037483198499e-05\n        coal: 0.003463242119144835\n        gas: 0.15828275722147547\n        geothermal: 0.0001565291268291446\n        hydro: 0.039234787350054534\n        hydro discharge: 0.0\n        nuclear: 0.002391920062894677\n        oil: 3.499784433567497e-07\n        solar: 0.1947552788415206\n        unknown: 0.5992356394714817\n        wind: 0.0021242727802997644\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0006323036877159791\n        biomass: 0.0001988466596943465\n        coal: 0.003350807223783281\n        gas: 0.21362446648345815\n        geothermal: 0.0003015731997595\n        hydro: 0.03185652209074322\n        hydro discharge: 6.677870906565441e-07\n        nuclear: 0.0042928102282425926\n        oil: 2.3358807697862653e-07\n        solar: 0.18798398693823837\n        unknown: 0.555007452888665\n        wind: 0.0027499307507535082\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0030960124708496735\n        biomass: 0.00038423441811694445\n        coal: 0.005210278324906109\n        gas: 0.23729711574625661\n        geothermal: 0.0005975405868859808\n        hydro: 0.03890177462846172\n        hydro discharge: 3.69046725934265e-08\n        nuclear: 0.007608287173607588\n        oil: 7.664816615557813e-07\n        solar: 0.19955958985702552\n        unknown: 0.5019581065707984\n        wind: 0.0053857770760136646\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.6587\n    - datetime: '2025-01-01'\n      value: 0.8282\n  hydro discharge:\n    - datetime: '2024-01-01'\n      value: 0.486\n    - datetime: '2025-01-01'\n      value: 0.9568\nisRenewable:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.6587\n    - datetime: '2025-01-01'\n      value: 0.8255\n  hydro discharge:\n    - datetime: '2024-01-01'\n      value: 0.486\n    - datetime: '2025-01-01'\n      value: 0.9452\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Imperial Irrigation District\n"
  },
  {
    "path": "config/zones/US-CAL-LDWP.yaml",
    "content": "bounding_box:\n  - - -118.65898658986583\n    - 33.93116278152432\n  - - -117.60417604176035\n    - 37.28132769347978\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 2.0\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 22.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2.0\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 3.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 23.5\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 173.5\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 323.5\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 23.0\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 56.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 33.0\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 34.1\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1640.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4818.1\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 4797.1\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 4795.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 4853.6\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 4854.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 4832.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 4814.5\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 4739.1\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 4594.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 4591.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 4575.9\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 4574.9\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 4591.3\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 4561.3\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 5012.8\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 5559.4\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 296.9\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 297.3\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 296.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 270.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 287.6\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1626.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1084.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 1626.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 727.2\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 730.1\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 788.3\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 792.8\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 797.5\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 878.5\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 882.5\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 884.0\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 888.7\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 978.7\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 979.6\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 988.1\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 987.0\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 988.8\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 991.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 989.3\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 991.7\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 992.5\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 994.0\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 999.1\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 1000.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 1002.6\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 1004.4\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 1204.4\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 1316.5\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 1517.3\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 1517.2\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 31.9\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 440.5\ncenter_point:\n  - -118.07218072180714\n  - 36.132168178614236\ncentroid:\n  - -118.22272435424313\n  - 35.83902890080555\ncomment: Los Angeles Department Of Water And Power\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 461.83\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 288.59\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 932.7095009354091\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 917.6944981905147\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 959.7792762377535\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 992.1244778240007\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 405.07548521687784\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 398.9672973734652\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 397.5065787395667\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 403.5204537908115\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 390.51\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 340.31\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 0.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 494.83\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 321.59\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 992.7095009354091\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 977.6944981905147\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1019.7792762377535\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1052.1244778240007\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 525.0754852168778\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 518.9672973734653\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 517.5065787395667\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 523.5204537908114\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 414.51\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 364.31\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 24.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.31022848316493384\n        gas: 0.39571506989242694\n        geothermal: 0.0\n        hydro: 0.042676268231751815\n        hydro discharge: 0.0008748457399552555\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.13437760205705762\n        unknown: 0.07739168574321482\n        wind: 0.03873627072900103\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3102334998207435\n        gas: 0.3957214689383304\n        geothermal: 0.0\n        hydro: 0.04267695834294591\n        hydro discharge: 0.0008748598869475596\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.13436360359767094\n        unknown: 0.0773929372319432\n        wind: 0.03873689712711771\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 9.351772121065762e-07\n        biomass: 5.187815671998059e-05\n        coal: 0.23674022230219624\n        gas: 0.26540278545606166\n        geothermal: 8.183497276073025e-05\n        hydro: 0.2067290397629072\n        hydro discharge: 5.87317516784689e-05\n        nuclear: 0.1280369595148015\n        oil: 0.0004242803116731728\n        solar: 0.07353299771153693\n        unknown: 0.049114232683286255\n        wind: 0.03982572394825983\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 4.167007131904551e-06\n        biomass: 2.7856682159950423e-05\n        coal: 0.2487372387801417\n        gas: 0.3376416099897817\n        geothermal: 4.774336447221214e-05\n        hydro: 0.036818602132913734\n        hydro discharge: 9.062043096049899e-06\n        nuclear: 0.00014343125927817666\n        oil: 4.3106970330047085e-06\n        solar: 0.26762030460917924\n        unknown: 0.06996702891529355\n        wind: 0.03897916180316265\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 1.6725999977811784e-07\n        biomass: 2.6916783429996963e-05\n        coal: 0.33203014908473716\n        gas: 0.26306610195319036\n        geothermal: 3.981874882804405e-05\n        hydro: 0.1285806284838692\n        hydro discharge: 0.00015156956261481677\n        nuclear: 0.09960069597574268\n        oil: 0.000427238195317715\n        solar: 0.07778335957204954\n        unknown: 0.059980362794439045\n        wind: 0.038312582191269526\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 7.867457711666467e-07\n        biomass: 6.068052695087397e-05\n        coal: 0.19012692343480309\n        gas: 0.2890810714647744\n        geothermal: 9.03614162348197e-05\n        hydro: 0.2846915497023899\n        hydro discharge: 8.441843934050194e-05\n        nuclear: 0.03923892458662715\n        oil: 0.0003185309347514496\n        solar: 0.08149853130590827\n        unknown: 0.06144454318638573\n        wind: 0.05336315155140212\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 8.154380937841836e-06\n        biomass: 0.0002587312829151692\n        coal: 0.22157351167552666\n        gas: 0.27983793420665903\n        geothermal: 0.0004471334894120491\n        hydro: 0.23171276766647914\n        hydro discharge: 0.00014522328850385055\n        nuclear: 0.059245937680078485\n        oil: 0.0004393277387987674\n        solar: 0.08993742346460609\n        unknown: 0.04843424974138791\n        wind: 0.06795919590419579\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 9.193698285645118e-05\n        biomass: 0.0004830007552354274\n        coal: 0.15198077112200922\n        gas: 0.3153494806207375\n        geothermal: 0.0008688250328448041\n        hydro: 0.2563433599285177\n        hydro discharge: 9.0120737692364e-07\n        nuclear: 0.05786484505435164\n        oil: 0.00043994668815856505\n        solar: 0.0975605128731743\n        unknown: 0.05048518665157384\n        wind: 0.06853087661549324\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0004115866081333916\n        biomass: 0.0008060013201818074\n        coal: 0.13839643210206676\n        gas: 0.3819971275332477\n        geothermal: 0.0014158747463552282\n        hydro: 0.17653156289236008\n        hydro discharge: 2.4950211355758748e-06\n        nuclear: 0.06790907633409242\n        oil: 0.0004086555176674995\n        solar: 0.11582316325712882\n        unknown: 0.04690833109731961\n        wind: 0.06938948410469403\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0010573448944582462\n        biomass: 0.0011508904909619427\n        coal: 0.1542205591539558\n        gas: 0.3351324785786678\n        geothermal: 0.001988451053662658\n        hydro: 0.15793588736961647\n        hydro discharge: 8.686400409727836e-07\n        nuclear: 0.07021496114305334\n        oil: 0.00014855113009227112\n        solar: 0.14848782977762862\n        unknown: 0.05077467246281746\n        wind: 0.07888732648126635\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.2326\n    - datetime: '2025-01-01'\n      value: 0.5013\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.3464\n    - datetime: '2021-01-01'\n      value: 0.4489\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nisRenewable:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.1878\n    - datetime: '2025-01-01'\n      value: 0.4516\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.325\n    - datetime: '2021-01-01'\n      value: 0.3958\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 1.0\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Los Angeles Department of Water and Power\n"
  },
  {
    "path": "config/zones/US-CAL-TIDC.yaml",
    "content": "bounding_box:\n  - - -121.4526145261452\n    - 37.3013628531412\n  - - -120.58860588605879\n    - 37.740705282859395\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 573.9\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 620.7\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 184.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 186.8\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -121.02061020610199\n  - 37.5210340680003\ncentroid:\n  - -121.06525065250646\n  - 37.50672323967071\ncomment: Turlock Irrigation District\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 462.36104833618134\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 480.84647966069207\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 469.4210002536843\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 463.81820538259876\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 582.3610483361813\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 600.846479660692\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 589.4210002536843\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 583.8182053825988\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.8509101066611724\n        geothermal: 0.0\n        hydro: 0.14908791226207266\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.8509101066611725\n        geothermal: 0.0\n        hydro: 0.14908791226207266\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.002387124974936698\n        biomass: 0.006272804739002275\n        coal: 0.011363939041625316\n        gas: 0.6376393419769455\n        geothermal: 0.010822604090561062\n        hydro: 0.15708013540804214\n        hydro discharge: 1.1395075405785393e-05\n        nuclear: 0.03586863734736225\n        oil: 0.00098048276724161\n        solar: 0.10453610255281968\n        unknown: 0.004297871768085698\n        wind: 0.028739664492572398\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 7.282850402368244e-05\n        biomass: 0.0055245986884757976\n        coal: 0.013990590849104522\n        gas: 0.6310533897024625\n        geothermal: 0.01039904079026985\n        hydro: 0.19261877141097822\n        hydro discharge: 2.8217323893996724e-05\n        nuclear: 0.045331783514675796\n        oil: 0.00019015695466836698\n        solar: 0.06617291573464983\n        unknown: 0.007909733013144843\n        wind: 0.026705398785084062\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0001317795529610134\n        biomass: 0.006835137039184948\n        coal: 0.01274269416528024\n        gas: 0.5283105431347425\n        geothermal: 0.010687076211689683\n        hydro: 0.2663464359072526\n        hydro discharge: 9.064990594988426e-06\n        nuclear: 0.04798516071844562\n        oil: 0.00024556325529572425\n        solar: 0.08731801705368773\n        unknown: 0.008536668933920294\n        wind: 0.030849686866982914\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.00014700015473700497\n        biomass: 0.00702931266243438\n        coal: 0.009179465802946459\n        gas: 0.5910225309009098\n        geothermal: 0.012357058621465213\n        hydro: 0.19602255721672684\n        hydro discharge: 1.8800019789494516e-05\n        nuclear: 0.04396442873448638\n        oil: 0.00012660013326329814\n        solar: 0.09079692715466016\n        unknown: 0.014256099216946545\n        wind: 0.03507664744910258\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0010744486372497016\n        biomass: 0.007803527624619071\n        coal: 0.011480705508427828\n        gas: 0.6263478643923014\n        geothermal: 0.013939631027485947\n        hydro: 0.1327181145201968\n        hydro discharge: 2.8960759288080134e-05\n        nuclear: 0.048560966092714146\n        oil: 0.00013358309167291738\n        solar: 0.10264572533762978\n        unknown: 0.01134080583012011\n        wind: 0.043924632742724457\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.003809661534058334\n        biomass: 0.006709818659618787\n        coal: 0.009226436524158567\n        gas: 0.6350022579539124\n        geothermal: 0.011955351957492387\n        hydro: 0.13738283753786415\n        hydro discharge: 3.749395120310864e-08\n        nuclear: 0.04339002159706127\n        oil: 0.00013952180950880418\n        solar: 0.10092167426335022\n        unknown: 0.009591140187511204\n        wind: 0.04186920558252485\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.003113980258688137\n        biomass: 0.0041675093650369085\n        coal: 0.003957319890208441\n        gas: 0.623280022827948\n        geothermal: 0.006986192381243895\n        hydro: 0.22541878414001146\n        hydro discharge: 6.364935356572261e-07\n        nuclear: 0.02423441270240852\n        oil: 7.195952759306752e-05\n        solar: 0.08084029304448447\n        unknown: 0.003551065375752886\n        wind: 0.02437669046246619\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.005637844834772319\n        biomass: 0.0024027941684446642\n        coal: 0.002698592851373847\n        gas: 0.6449304482785828\n        geothermal: 0.00439491047838258\n        hydro: 0.24635530021893562\n        hydro discharge: 0.0\n        nuclear: 0.015325142971686684\n        oil: 3.795479047500361e-05\n        solar: 0.05005126712516857\n        unknown: 0.002653244487787362\n        wind: 0.025510983164008797\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 1.0\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Turlock Irrigation District\n"
  },
  {
    "path": "config/zones/US-CAR-CPLE.yaml",
    "content": "bounding_box:\n  - - -80.05220052200517\n    - 33.850693872153414\n  - - -76.19296192961924\n    - 36.54432003450624\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.5\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 1.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 11.8\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 13.8\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 41.1\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 128.6\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 228.6\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 540.8\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 538.2\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 528.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 557.3\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 559.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 610.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 608.5\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 396.4\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 388.9\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 343.9\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 336.4\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 327.4\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 367.4\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 365.2\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3815.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 3787.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 3321.4\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 5987.9\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 6108.9\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 6042.1\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 6048.7\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 6043.2\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 6337.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 6212.4\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 6012.0\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 6114.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 6430.8\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 6411.8\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 226.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 224.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 225.2\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 224.0\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 223.2\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3722.7\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 729.3\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 713.0\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 646.2\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 571.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 887.2\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 558.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 242.2\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1000\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1300\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1500\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1600\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1800\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2504.4\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 2553.1\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 2563.1\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 2568.1\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 2570.1\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 2573.1\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 2586.3\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 2606.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2758.9\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 2759.9\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 2849.0\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 2851.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 2853.0\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 2911.4\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 2913.4\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 2915.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2917.4\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2918.5\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 2920.5\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 2922.5\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 2924.5\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2930.3\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 54.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -78.2582895196833\n  - 35.20504967314134\ncentroid:\n  - -77.96167450275158\n  - 35.276000004962455\ncomment: Duke Energy Progress East\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 310.96\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1021.9158971238843\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1021.5404864286071\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1035.5709252777651\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1044.133961609779\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 399.6129537439065\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 401.1166854159786\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 412.1979214448654\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 391.93702628361535\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 249.77\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 142.98\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 195.22\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 229.29\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 284.82\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 343.96\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1081.9158971238844\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1081.540486428607\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1095.5709252777651\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1104.133961609779\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 519.6129537439065\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 521.1166854159786\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 532.1979214448654\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 511.93702628361535\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 273.77\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 166.98\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 219.22\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 253.29\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 308.82\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.11190044633136831\n        gas: 0.21445566860730192\n        geothermal: 0.0\n        hydro: 0.00468587879010318\n        hydro discharge: 0.00014001536917935306\n        nuclear: 0.46563338560586043\n        oil: 0.00042441976546744333\n        solar: 0.07620366979342383\n        unknown: 0.12655674899905198\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.11190070010496238\n        gas: 0.2144561549609097\n        geothermal: 0.0\n        hydro: 0.004685889416980381\n        hydro discharge: 0.00014001568671341682\n        nuclear: 0.46563444159322825\n        oil: 0.0004244207279884413\n        solar: 0.07620157476053892\n        unknown: 0.12655703601096388\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.11612249439857504\n        gas: 0.21269511290823198\n        geothermal: 0.0\n        hydro: 0.007753313949284774\n        hydro discharge: 0.0003455356589249578\n        nuclear: 0.46871852150389537\n        oil: 0.00046816954896952576\n        solar: 0.07585729235307216\n        unknown: 0.11791792316198751\n        wind: 0.00012154187582638274\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.1045552708263043e-07\n        coal: 0.12003472821677884\n        gas: 0.2731680395142759\n        geothermal: 0.0\n        hydro: 0.010193888003973264\n        hydro discharge: 0.0018075949272547101\n        nuclear: 0.4205702514552095\n        oil: 0.0002785029072813123\n        solar: 0.04498736026376761\n        unknown: 0.1287768646333858\n        wind: 0.0001826031537093307\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.3128240866076984e-07\n        coal: 0.139721604775625\n        gas: 0.22014805085814995\n        geothermal: 0.0\n        hydro: 0.009992240686031433\n        hydro discharge: 0.0003541073701436702\n        nuclear: 0.4390441199833624\n        oil: 0.00023245588120185935\n        solar: 0.061995908723957396\n        unknown: 0.12797792759278298\n        wind: 0.0005332368027621288\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 7.547640958804125e-09\n        coal: 0.10658779803190808\n        gas: 0.20955041211644257\n        geothermal: 0.0\n        hydro: 0.011920150885755869\n        hydro discharge: 0.00032491839563555876\n        nuclear: 0.4750874902496765\n        oil: 0.0002752066132244912\n        solar: 0.0705295186491878\n        unknown: 0.12448917729523035\n        wind: 0.0012352573182898706\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1219278703960358\n        gas: 0.207408649708183\n        geothermal: 0.0\n        hydro: 0.010803068195678445\n        hydro discharge: 0.00045103353877611334\n        nuclear: 0.4782669535313155\n        oil: 0.0007658547622114129\n        solar: 0.07464100903569044\n        unknown: 0.10466080758917912\n        wind: 0.0010746695528870854\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.741094938602959e-09\n        coal: 0.11542289105448962\n        gas: 0.2362914038448136\n        geothermal: 0.0\n        hydro: 0.01058865255022853\n        hydro discharge: 1.3256257604841392e-05\n        nuclear: 0.45283272139012287\n        oil: 0.0014708201082140294\n        solar: 0.07664431911514855\n        unknown: 0.10595912904516494\n        wind: 0.0007767137594667171\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.09747776174307804\n        gas: 0.20414968405555792\n        geothermal: 0.0\n        hydro: 0.010135029036484628\n        hydro discharge: 1.4941847303274346e-05\n        nuclear: 0.4958506480750646\n        oil: 0.00016606758950279393\n        solar: 0.08067442955238947\n        unknown: 0.11130045397566458\n        wind: 0.00023088931561170226\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.13313892261808474\n        gas: 0.21795019792852804\n        geothermal: 0.0\n        hydro: 0.011599365275096833\n        hydro discharge: 1.2085962191195523e-05\n        nuclear: 0.44819441736505616\n        oil: 0.00010444487774211082\n        solar: 0.07846100156349965\n        unknown: 0.11024049856981802\n        wind: 0.00029901388079216223\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.5179\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.5802\n    - datetime: '2021-01-01'\n      value: 0.7716\n    - datetime: '2022-01-01'\n      value: 0.6106\n    - datetime: '2023-01-01'\n      value: 0.5894\n    - datetime: '2025-01-01'\n      value: 0.5331\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.0729\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.0714\n    - datetime: '2021-01-01'\n      value: 0.2827\n    - datetime: '2022-01-01'\n      value: 0.1393\n    - datetime: '2023-01-01'\n      value: 0.0003\n    - datetime: '2025-01-01'\n      value: 0.1105\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Duke Energy Progress East\n"
  },
  {
    "path": "config/zones/US-CAR-CPLW.yaml",
    "content": "bounding_box:\n  - - -83.36063360633601\n    - 35.004474906243075\n  - - -81.69381693816933\n    - 36.25094805374978\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 8.8\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 13.2\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1.5\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 11.5\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 21.5\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 23.4\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 28.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 26.9\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -82.43853257314427\n  - 35.70823719184149\ncentroid:\n  - -82.57668976689762\n  - 35.59894671505396\ncomment: Duke Energy Progress West\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 298.9\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 418.55\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 418.81\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 452.14\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 412.87\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 462.03\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 322.9\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 442.55\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 442.81\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 476.14\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 436.87\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 486.03\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.76666667\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0984771385949069\n        gas: 0.5283137448054049\n        geothermal: 0.0\n        hydro: 0.10892828273483247\n        hydro discharge: 0.002267469348745374\n        nuclear: 0.0\n        oil: 0.05415283672141139\n        solar: 0.008713651748048806\n        unknown: 0.19914805378472497\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.09847736984770877\n        gas: 0.5283149854388707\n        geothermal: 0.0\n        hydro: 0.10892853852994336\n        hydro discharge: 0.002267474673419177\n        nuclear: 0.0\n        oil: 0.05415296388793349\n        solar: 0.008711328447250663\n        unknown: 0.19914852144195064\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.14215606451641644\n        gas: 0.413268490538378\n        geothermal: 0.0\n        hydro: 0.07768279640133131\n        hydro discharge: 0.0009165283225766136\n        nuclear: 0.19626002510014043\n        oil: 0.03025757151008685\n        solar: 0.007171483444727632\n        unknown: 0.12733005827959254\n        wind: 0.0049554720830237995\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.2518395432988863e-06\n        coal: 0.34045015917292476\n        gas: 0.304208060261519\n        geothermal: 0.0\n        hydro: 0.09774613486917835\n        hydro discharge: 0.009586719995424974\n        nuclear: 0.21721528518277708\n        oil: 0.006107213135325753\n        solar: 0.010396388929459087\n        unknown: 0.008760761271935742\n        wind: 0.005525446384066287\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.3220191069453146e-06\n        coal: 0.3315225017812262\n        gas: 0.2346453823463146\n        geothermal: 0.0\n        hydro: 0.11177939242325598\n        hydro discharge: 0.010267634260889212\n        nuclear: 0.2752518908442977\n        oil: 0.0031636982600514695\n        solar: 0.013865010634955016\n        unknown: 0.015311151625566715\n        wind: 0.004189381790890738\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.048259687250331446\n        gas: 0.4925240804806091\n        geothermal: 0.0\n        hydro: 0.11531891701331068\n        hydro discharge: 0.0031007409160482423\n        nuclear: 0.15283103911679713\n        oil: 0.0013597763336049293\n        solar: 0.011534464464774812\n        unknown: 0.17282924236689215\n        wind: 0.0022410210924737116\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.04639692363103795\n        gas: 0.5232942150085858\n        geothermal: 0.0\n        hydro: 0.08020377127214894\n        hydro discharge: 0.001858866143488965\n        nuclear: 0.10633874869298691\n        oil: 0.006440445092251681\n        solar: 0.008616425234738852\n        unknown: 0.22362013765289562\n        wind: 0.003229634962035957\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.941633397231453e-09\n        coal: 0.0482287697862831\n        gas: 0.560042521693734\n        geothermal: 0.0\n        hydro: 0.06459863435913994\n        hydro discharge: 1.9445458473273002e-05\n        nuclear: 0.09999001340278468\n        oil: 0.005418718251527128\n        solar: 0.006486525363234756\n        unknown: 0.20943026332797163\n        wind: 0.005784605473801615\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.03490637068661182\n        gas: 0.5497980307132992\n        geothermal: 0.0\n        hydro: 0.06891523704412911\n        hydro discharge: 2.0322796539261947e-05\n        nuclear: 0.09689055394519087\n        oil: 0.0003706152349079936\n        solar: 0.0071135314353381815\n        unknown: 0.23971427970756837\n        wind: 0.002269815502937839\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.042994951875545286\n        gas: 0.5643339714276191\n        geothermal: 0.0\n        hydro: 0.0625352128520955\n        hydro discharge: 1.6512772228641293e-05\n        nuclear: 0.09330073938741291\n        oil: 0.0003350061779733654\n        solar: 0.007221289168419903\n        unknown: 0.22612240607665954\n        wind: 0.003138998527429385\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.3559\n    - datetime: '2021-01-01'\n      value: 0.0954\n    - datetime: '2022-01-01'\n      value: 0.1404\n    - datetime: '2023-01-01'\n      value: 0.0067\n    - datetime: '2024-01-01'\n      value: 0.154\n    - datetime: '2025-01-01'\n      value: 0.0973\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.0087\n    - datetime: '2021-01-01'\n      value: 0.0154\n    - datetime: '2022-01-01'\n      value: 0.0136\n    - datetime: '2023-01-01'\n      value: 0.0009\n    - datetime: '2024-01-01'\n      value: 0.0601\n    - datetime: '2025-01-01'\n      value: 0.0141\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Duke Energy Progress West\n"
  },
  {
    "path": "config/zones/US-CAR-DUK.yaml",
    "content": "bounding_box:\n  - - -84.31104311043104\n    - 34.04421832532803\n  - - -78.27738277382768\n    - 36.59193756016861\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 50.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 82.8\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 85.1\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 90.3\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 91.9\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 90.9\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 80.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 76.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 71.6\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 69.2\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 70.0\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 69.2\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 7317.1\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 7045.1\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 6603.9\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 2590.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 8189.5\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 9036.2\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 9580.1\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 9728.1\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 9741.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 14850.7\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 14687.5\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 15223.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 15122.7\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 13592.2\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1211.9\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 1171.9\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 1165.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1163.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1162.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1177.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1157.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1159.5\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1144.9\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 1145.7\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2070.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 2166.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2262.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2358.0\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 2454.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 7517.5\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 126.1\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 129.4\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 128.1\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 130.4\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1070.3\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 1145.7\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 1194.3\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 1294.3\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 1304.3\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 1414.7\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 1526.2\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1540.6\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 1545.5\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 1550.4\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 1551.4\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 1562.9\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 1566.7\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 1641.5\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 1691.7\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 1746.9\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 1851.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1875.3\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 1880.3\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 1885.3\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 1888.3\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 1977.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1997.2\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 2001.2\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 2023.2\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 2025.2\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 2033.1\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 2036.5\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 2043.5\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 2113.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2200.4\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 2215.3\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 2239.8\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 2243.1\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 2245.1\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 2249.1\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 2251.1\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 2383.7\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1776.2\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 1778.2\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 1855.8\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 1871.8\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 1878.8\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 1885.8\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 1955.8\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 1957.8\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 1962.8\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 1964.8\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 1969.8\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 1983.6\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 2033.6\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 2038.6\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 2038.7\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 2063.7\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 2138.1\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 2143.1\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 2148.1\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2159.6\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 2164.6\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 2329.6\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2529.6\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -80.83579689728052\n  - 35.33117133429408\ncentroid:\n  - -81.87193289087408\n  - 35.220733493557034\ncomment: Duke Energy Carolinas\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 253.48\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 850.8991772198257\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 774.4313315061296\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 746.9759392468122\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 396.0379906292856\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 399.1356021822794\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 515.1156633369592\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 502.9548744078696\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 214.41\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 225.29\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 300.31\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 238.61\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 249.02\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 249.72\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 442.79655780749437\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 286.48\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 910.8991772198257\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 834.4313315061296\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 806.9759392468122\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 516.0379906292856\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 519.1356021822794\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 635.1156633369592\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 622.9548744078696\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 238.41\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 249.29\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 324.31\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 262.61\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 273.02\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 273.72\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 686.7965578074943\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.53333333\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.16923359026548518\n        gas: 0.21273677441782107\n        geothermal: 0.0\n        hydro: 0.05479692528760984\n        hydro discharge: 0.05330204789181415\n        nuclear: 0.49963778097127637\n        oil: 0.0\n        solar: 0.009313630494309798\n        unknown: 0.0009792724862209988\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.16923363427212415\n        gas: 0.21273682973680597\n        geothermal: 0.0\n        hydro: 0.05479693953672258\n        hydro discharge: 0.05330206175220659\n        nuclear: 0.49963791089453446\n        oil: 0.0\n        solar: 0.009313372821680764\n        unknown: 0.0009792727408660172\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.18478863670367057\n        gas: 0.22423964841896088\n        geothermal: 0.0\n        hydro: 0.060505898268363015\n        hydro discharge: 0.004208222415833323\n        nuclear: 0.5099540574404652\n        oil: 3.29253561207696e-05\n        solar: 0.01282359120276417\n        unknown: 0.0032979271507371693\n        wind: 0.00014905890973227986\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.1072555484928844e-08\n        coal: 0.17872820131041056\n        gas: 0.25114672701119023\n        geothermal: 0.0\n        hydro: 0.05932678111070233\n        hydro discharge: 0.035673387002808796\n        nuclear: 0.46510671045351737\n        oil: 3.5357627979728725e-05\n        solar: 0.006437185400510145\n        unknown: 0.0034329025610674788\n        wind: 0.00011267821268755429\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.5157592251389302e-08\n        coal: 0.19209479808439392\n        gas: 0.2162959954110993\n        geothermal: 0.0\n        hydro: 0.04893806330650491\n        hydro discharge: 0.025163892988085277\n        nuclear: 0.5035049657623506\n        oil: 6.291435473487404e-06\n        solar: 0.010132128507185166\n        unknown: 0.003743679334327558\n        wind: 0.00012007709923280983\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.16012853029090054\n        gas: 0.22095329277437908\n        geothermal: 0.0\n        hydro: 0.05440881821039043\n        hydro discharge: 0.019520552609483797\n        nuclear: 0.5281937238029852\n        oil: 9.00549362529533e-06\n        solar: 0.012050655445993676\n        unknown: 0.0046195566291936975\n        wind: 0.00011577703825962111\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.8115297656033559e-10\n        coal: 0.1856874966956565\n        gas: 0.21996982389947053\n        geothermal: 0.0\n        hydro: 0.04314186686493498\n        hydro discharge: 0.024362348270456\n        nuclear: 0.509259306147688\n        oil: 7.287068692764888e-05\n        solar: 0.013414836231323547\n        unknown: 0.003922773145560302\n        wind: 0.00016845288483262013\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.284488537258341e-10\n        coal: 0.19423660434701787\n        gas: 0.23739788241158782\n        geothermal: 0.0\n        hydro: 0.043759590189026566\n        hydro discharge: 0.0002823822410124755\n        nuclear: 0.5016563511302613\n        oil: 5.123607861331867e-05\n        solar: 0.018491410093566817\n        unknown: 0.0038156295420776944\n        wind: 0.00030878537666984544\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1887104401794071\n        gas: 0.21731367842913082\n        geothermal: 0.0\n        hydro: 0.042219734327088795\n        hydro discharge: 0.00011769035537028452\n        nuclear: 0.5253783775483528\n        oil: 7.021000994672574e-06\n        solar: 0.02177030446122459\n        unknown: 0.004354052428880941\n        wind: 0.00012860945369764118\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.19680020124015796\n        gas: 0.23273830875424287\n        geothermal: 0.0\n        hydro: 0.04366598828449094\n        hydro discharge: 6.891828404921734e-05\n        nuclear: 0.500302114221077\n        oil: 1.3272514659525184e-05\n        solar: 0.022160483501947582\n        unknown: 0.004072615591024879\n        wind: 0.00017802609034428662\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.5813\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.6319\n    - datetime: '2021-01-01'\n      value: 0.6026\n    - datetime: '2022-01-01'\n      value: 0.59\n    - datetime: '2023-01-01'\n      value: 0.6088\n    - datetime: '2024-01-01'\n      value: 0.5933\n    - datetime: '2025-01-01'\n      value: 0.5905\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.0417\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.0274\n    - datetime: '2021-01-01'\n      value: 0.0227\n    - datetime: '2022-01-01'\n      value: 0.0296\n    - datetime: '2023-01-01'\n      value: 0.035\n    - datetime: '2024-01-01'\n      value: 0.0348\n    - datetime: '2025-01-01'\n      value: 0.0402\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Duke Energy Carolinas\n"
  },
  {
    "path": "config/zones/US-CAR-SC.yaml",
    "content": "bounding_box:\n  - - -81.8126181261812\n    - 32.56447867604912\n  - - -78.54289396063669\n    - 34.841331463285826\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 219.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 218.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 219.5\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3650.1\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 3727.3\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1102.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1272.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 231.2\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 229.4\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2.5\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 42.5\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 2.5\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 4.1\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 5.2\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 17.2\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 23.2\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 98.2\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 173.2\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 248.2\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 303.2\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 303.3\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -79.7836270483866\n  - 33.9804037610069\ncentroid:\n  - -80.31007833777494\n  - 34.03152822270473\ncomment: South Carolina Public Service Authority\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ndisclaimer: This zone includes a third of the nuclear related electricity production\n  from the balancing authority South Carolina Electric & Gas Company. Read more on\n  the zone definition wiki page.\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1072.534133734033\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1060.5558582806743\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1035.7452411944068\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1028.8970523880782\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 442.9124649151213\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 445.80200911803314\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 456.17959601383194\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 471.2653214613073\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 667.34\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 587.16\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 562.85\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 591.74\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 627.12\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1612.9238663414549\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1132.534133734033\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1120.5558582806743\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1095.7452411944068\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1088.8970523880782\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 562.9124649151213\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 565.8020091180331\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 576.179596013832\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 591.2653214613073\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 691.34\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 611.16\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 586.85\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 615.74\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 651.12\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1856.9238663414549\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5123968793276095\n        gas: 0.28780087700811385\n        geothermal: 0.0\n        hydro: 0.030624512227502457\n        hydro discharge: 0.0005420658206571039\n        nuclear: 0.13412876666339377\n        oil: 0.00035747561907404767\n        solar: 0.00405432692816917\n        unknown: 0.03009453495435027\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5123970056468568\n        gas: 0.28780094795856576\n        geothermal: 0.0\n        hydro: 0.030624519777246593\n        hydro discharge: 0.0005420659542905221\n        nuclear: 0.13412879972964678\n        oil: 0.00035747570720114785\n        solar: 0.004054080838434433\n        unknown: 0.03009454237344113\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.40060940366903053\n        gas: 0.322346533041176\n        geothermal: 0.0\n        hydro: 0.03395161424543094\n        hydro discharge: 0.006054265000966473\n        nuclear: 0.18255416709810784\n        oil: 0.00012587496463426016\n        solar: 0.023115588335625048\n        unknown: 0.031195416163463496\n        wind: 4.739571142606043e-05\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.4755211722318727\n        gas: 0.30787727297827616\n        geothermal: 0.0\n        hydro: 0.03738681647092161\n        hydro discharge: 0.00462844725196735\n        nuclear: 0.13875672821152546\n        oil: 3.2610972846726105e-05\n        solar: 0.006097014538091634\n        unknown: 0.029660050504784055\n        wind: 3.9768880499664725e-05\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.36916512874103485\n        gas: 0.3452915863082558\n        geothermal: 0.0\n        hydro: 0.039855683465952044\n        hydro discharge: 0.0003543446168297422\n        nuclear: 0.19858305355245195\n        oil: 3.838392137897156e-05\n        solar: 0.013283024037770045\n        unknown: 0.033321190561154804\n        wind: 0.00010725272736365158\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3365968068947738\n        gas: 0.35168508683778543\n        geothermal: 0.0\n        hydro: 0.054921368952961305\n        hydro discharge: 0.00047332126244824344\n        nuclear: 0.20278457766634994\n        oil: 5.111591247042756e-05\n        solar: 0.020410088634907037\n        unknown: 0.03287474817241908\n        wind: 0.00020254732554227036\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.39581534275447156\n        gas: 0.33696483614772754\n        geothermal: 0.0\n        hydro: 0.032550925170236875\n        hydro discharge: 0.0004360911706632489\n        nuclear: 0.18156266269234156\n        oil: 6.465966041869714e-05\n        solar: 0.02587616770741791\n        unknown: 0.026531888302825445\n        wind: 0.000195670441033537\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3545580587510276\n        gas: 0.36588937011608846\n        geothermal: 0.0\n        hydro: 0.028614315089745213\n        hydro discharge: 0.0008728280598405304\n        nuclear: 0.19524720888150177\n        oil: 0.00027231116769891364\n        solar: 0.02936711751789774\n        unknown: 0.024964564622794193\n        wind: 0.00021369761486246178\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.38826494728314703\n        gas: 0.34740160348604526\n        geothermal: 0.0\n        hydro: 0.028481483124720833\n        hydro discharge: 0.0006501933166339626\n        nuclear: 0.1766898122231121\n        oil: 2.7890341309518912e-05\n        solar: 0.03537461781673552\n        unknown: 0.023006197833984034\n        wind: 0.00010300074293403975\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.40765938808444785\n        gas: 0.3301634166371887\n        geothermal: 0.0\n        hydro: 0.028490204136569674\n        hydro discharge: 0.00040907751531923725\n        nuclear: 0.17366401749202467\n        oil: 9.915940583974472e-05\n        solar: 0.03903642520721052\n        unknown: 0.020343396555049083\n        wind: 0.00013469670798902004\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2021-01-01'\n      value: 0.1903\n    - datetime: '2022-01-01'\n      value: 0.2805\n    - datetime: '2023-01-01'\n      value: 0.2568\n    - datetime: '2024-01-01'\n      value: 0.241\n    - datetime: '2025-01-01'\n      value: 0.2137\nisRenewable:\n  hydro discharge:\n    - datetime: '2021-01-01'\n      value: 0.0147\n    - datetime: '2022-01-01'\n      value: 0.086\n    - datetime: '2023-01-01'\n      value: 0.0454\n    - datetime: '2024-01-01'\n      value: 0.0427\n    - datetime: '2025-01-01'\n      value: 0.0324\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: South Carolina Public Service Authority\n"
  },
  {
    "path": "config/zones/US-CAR-SCEG.yaml",
    "content": "bounding_box:\n  - - -82.59382593825933\n    - 32.085065927008074\n  - - -79.42939429394289\n    - 34.7354313336469\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 4.0\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 70.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 229.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 120.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 229.6\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 130.4\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1848.8\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1431.5\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3090.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 3507.7\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 3511.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 3464.7\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 3537.4\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 3510.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 3504.3\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 3440.1\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 3400.9\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 3466.3\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 3597.1\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 244.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 241.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 244.3\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 242.1\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 587.2\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1029.6\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 30.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 14.0\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 17.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 120.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 17.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 56.7\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 17.5\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6.8\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 10.2\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 25.6\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 54.9\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 198.1\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 238.1\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 248.3\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 262.4\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 266.8\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 268.4\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 314.9\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 316.9\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 336.9\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 349.9\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 428.5\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 503.4\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 575.9\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 645.9\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 720.9\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 795.9\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 868.0\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 903.2\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 978.1\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 1044.1\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -81.12491647633112\n  - 33.41858838624407\ncentroid:\n  - -81.04805138700345\n  - 33.48424702846477\ncomment: South Carolina Electric & Gas Company\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ndisclaimer: A third of the nuclear-related electricity production is attributed to\n  the balancing authority South Carolina Public Service Authority (US-CAR-SC) due\n  to an agreement between the two balancing authorities. Read more on the zone definition\n  wiki page.\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 934.0795381890217\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 946.9012095380552\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 972.0663633884146\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 978.9970212509144\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 407.41771383688\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 462.3141304645547\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 451.1888745347415\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 436.0425147557432\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1297.8346930177995\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 994.0795381890217\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1006.9012095380552\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1032.0663633884146\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1038.9970212509143\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 527.41771383688\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 582.3141304645546\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 571.1888745347414\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 556.0425147557432\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1541.8346930177995\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1919388365611012\n        gas: 0.5025520570687312\n        geothermal: 0.0\n        hydro: 0.0317146224119546\n        hydro discharge: 0.0\n        nuclear: 0.21190851534364152\n        oil: 0.0\n        solar: 0.05903604640979591\n        unknown: 0.0028507321355780903\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.19193927472676642\n        gas: 0.5025532043146995\n        geothermal: 0.0\n        hydro: 0.03171469481136514\n        hydro discharge: 0.0\n        nuclear: 0.21190899909688946\n        oil: 0.0\n        solar: 0.059033898197732804\n        unknown: 0.0028507386433436104\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1861095153878664\n        gas: 0.5019813482842593\n        geothermal: 0.0\n        hydro: 0.0337739906913919\n        hydro discharge: 0.0004111382811999255\n        nuclear: 0.21620601495538588\n        oil: 1.7025672628805448e-05\n        solar: 0.05806960113824672\n        unknown: 0.0033861308353107236\n        wind: 4.501933830788828e-05\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3214535345228188\n        gas: 0.43998483972553176\n        geothermal: 0.0\n        hydro: 0.03963220451652836\n        hydro discharge: 0.0018809358781721908\n        nuclear: 0.16459317126275555\n        oil: 1.2829080783133294e-05\n        solar: 0.01646713965898715\n        unknown: 0.01594365868762094\n        wind: 3.151044648085425e-05\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.21574271659975053\n        gas: 0.49419235893614966\n        geothermal: 0.0\n        hydro: 0.036489541629371694\n        hydro discharge: 0.00031607316272553725\n        nuclear: 0.2220572729105147\n        oil: 6.478134273846065e-06\n        solar: 0.0292242110097449\n        unknown: 0.0019394953251856367\n        wind: 3.145955511145264e-05\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1537287110111836\n        gas: 0.5187589275328074\n        geothermal: 0.0\n        hydro: 0.04469682244605413\n        hydro discharge: 0.0002832133908783794\n        nuclear: 0.21997565296993385\n        oil: 4.742599350014109e-06\n        solar: 0.0598483302731545\n        unknown: 0.002666388943781082\n        wind: 3.6892685726959914e-05\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.17491498467533734\n        gas: 0.5256518662272655\n        geothermal: 0.0\n        hydro: 0.0314458724276906\n        hydro discharge: 0.00032385086176189517\n        nuclear: 0.19594821777695592\n        oil: 5.817686353929803e-06\n        solar: 0.06890861899120676\n        unknown: 0.0027264191155270804\n        wind: 7.388819027595026e-05\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.15765207422266675\n        gas: 0.5073171961410856\n        geothermal: 0.0\n        hydro: 0.0321566055178509\n        hydro discharge: 0.0001557833235789619\n        nuclear: 0.2291097722359442\n        oil: 3.2339029259674094e-05\n        solar: 0.07035419778953284\n        unknown: 0.0030743797538514673\n        wind: 0.0001473849913931333\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.16169732280765545\n        gas: 0.5148304694076232\n        geothermal: 0.0\n        hydro: 0.03123135458885657\n        hydro discharge: 0.00015439664046229627\n        nuclear: 0.21554499469681562\n        oil: 5.381204772367882e-06\n        solar: 0.0738194347010824\n        unknown: 0.002620311606590239\n        wind: 9.609330559539754e-05\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.17383671454508898\n        gas: 0.5065781474836093\n        geothermal: 0.0\n        hydro: 0.03241643819214425\n        hydro discharge: 0.00010720387820444353\n        nuclear: 0.21469520262448658\n        oil: 9.309745576760395e-06\n        solar: 0.06997543369820834\n        unknown: 0.00226721784513369\n        wind: 0.00011411094674027499\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 1.0\nisRenewable:\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 1.0\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: South Carolina Electric & Gas Company\n"
  },
  {
    "path": "config/zones/US-CAR-YAD.yaml",
    "content": "bounding_box:\n  - - -80.825586319\n    - 34.797960281\n  - - -79.4523525239999\n    - 36.2042064670001\ncan_have_zero_production: true\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 215.2\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncomment: Alcoa Power Generating, Inc. - Yadkin Division\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0033144127275517455\n        gas: 0.004072077067971939\n        geothermal: 0.0\n        hydro: 0.9824458463300616\n        hydro discharge: 0.00014551977465504428\n        nuclear: 0.009910513988554984\n        oil: 2.185255031736368e-07\n        solar: 7.031058064611765e-05\n        unknown: 3.3343349692577415e-05\n        wind: 3.951669515723265e-06\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.005813341161593352\n        gas: 0.009248170896937946\n        geothermal: 0.0\n        hydro: 0.9627812754042092\n        hydro discharge: 0.0020285430403757564\n        nuclear: 0.018381401860717187\n        oil: 3.4775539698310903e-06\n        solar: 0.0004508174509981031\n        unknown: 0.0012797398608978413\n        wind: 7.271249209646827e-06\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.011704576775878505\n        gas: 0.016029145749835452\n        geothermal: 0.0\n        hydro: 0.9213342641417358\n        hydro discharge: 0.0006192210428970131\n        nuclear: 0.03603757272881996\n        oil: 9.790056014182026e-06\n        solar: 0.005226007208493551\n        unknown: 0.008976163472849163\n        wind: 3.275903358591678e-05\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0020397491274406505\n        gas: 0.00473785630658369\n        geothermal: 0.0\n        hydro: 0.9752283800411929\n        hydro discharge: 0.00023271934489228015\n        nuclear: 0.012810343131130992\n        oil: 1.3819438532795738e-06\n        solar: 0.0024858406032792976\n        unknown: 0.002402647583311867\n        wind: 1.1884717138204335e-05\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.01677700467192675\n        gas: 0.023620418238111316\n        geothermal: 0.0\n        hydro: 0.881083848957417\n        hydro discharge: 0.0025682121913983918\n        nuclear: 0.06222405590458933\n        oil: 5.786404011484031e-05\n        solar: 0.007573055332290197\n        unknown: 0.005912040317760774\n        wind: 2.932834909930262e-05\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.019045702788157516\n        gas: 0.028488071284851972\n        geothermal: 0.0\n        hydro: 0.8687989843824855\n        hydro discharge: 1.9162594615310915e-05\n        nuclear: 0.06827728274408354\n        oil: 6.70690811535882e-06\n        solar: 0.00886317907444668\n        unknown: 0.006280540385168153\n        wind: 2.9222956788349147e-05\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.010486397596266907\n        gas: 0.01967113920902962\n        geothermal: 0.0\n        hydro: 0.8925366602892164\n        hydro discharge: 2.87143192279983e-07\n        nuclear: 0.05772120147603086\n        oil: 3.086789317009817e-06\n        solar: 0.010799491354549195\n        unknown: 0.008758477543823076\n        wind: 1.85566288010939e-05\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.012599241362673078\n        gas: 0.023614230589435046\n        geothermal: 0.0\n        hydro: 0.8973674376095901\n        hydro discharge: 1.7026730462798738e-07\n        nuclear: 0.045944957858700224\n        oil: 8.59849888371336e-06\n        solar: 0.011377119405821593\n        unknown: 0.009028395450014926\n        wind: 5.400311345117666e-05\ngeneration_only: true\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Alcoa Power Generating, Inc. Yadkin Division\nzone_short_name: Alcoa Power Generating\n"
  },
  {
    "path": "config/zones/US-CENT-SPA.yaml",
    "content": "bounding_box:\n  - - -90.8235082350823\n    - 35.96473148715812\n  - - -90.29070290702902\n    - 36.26812104774528\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 261.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 32.8\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1497.1\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1391.1\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1343.6\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1368.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1287.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1327.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1253.2\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1403.6\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 1364.6\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 107.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 134.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 161.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 134.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 161.4\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 7.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 12.0\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 17.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 18.5\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 119.5\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 499.0\ncenter_point:\n  - -90.55710557105566\n  - 36.1164262674517\ncentroid:\n  - -90.55530555305548\n  - 36.095198538762816\ncomment: Southwestern Power Administration\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 987.9224616734189\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1062.0186382106529\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1064.67361209247\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1078.5537883747247\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.9224616734189\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1122.0186382106529\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1124.67361209247\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1138.5537883747247\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.7761125520290202\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.2238874479709796\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.7761125520290203\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.2238874479709796\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.65257628562972e-06\n        coal: 0.009458981443707336\n        gas: 0.003400072840866559\n        geothermal: 0.0\n        hydro: 0.7674520839644643\n        hydro discharge: 0.0\n        nuclear: 0.0018031393848028095\n        oil: 2.695668500498292e-05\n        solar: 2.213244711201632e-05\n        unknown: 0.2091833938299531\n        wind: 0.00864367703879659\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.000964381928596424\n        gas: 0.0004831620770427274\n        geothermal: 0.0\n        hydro: 0.8094005220568167\n        hydro discharge: 0.0\n        nuclear: 2.3156015959735656e-05\n        oil: 0.0\n        solar: 2.0091987817558054e-07\n        unknown: 0.1889945801862862\n        wind: 0.00013376240889539275\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.426582364864741e-07\n        coal: 0.003915367434002424\n        gas: 0.001984399985982489\n        geothermal: 0.0\n        hydro: 0.7693716650774006\n        hydro discharge: 0.0\n        nuclear: 0.0003525772853614765\n        oil: 8.668723797860118e-07\n        solar: 6.400100335866937e-06\n        unknown: 0.2216211251265726\n        wind: 0.002744001519793278\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.0790974069919437e-07\n        coal: 0.011688505288920617\n        gas: 0.0026363021127870437\n        geothermal: 0.0\n        hydro: 0.7225291145577424\n        hydro discharge: 0.0\n        nuclear: 0.00047603066739595985\n        oil: 2.2249622219956056e-07\n        solar: 8.287984276933633e-06\n        unknown: 0.2570148052694522\n        wind: 0.005642856480666005\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.966751165291622e-05\n        coal: 0.03971726201399013\n        gas: 0.017063767273918073\n        geothermal: 0.0\n        hydro: 0.5932482884761711\n        hydro discharge: 7.88051411393323e-08\n        nuclear: 0.003737975517539255\n        oil: 3.9807854152668435e-05\n        solar: 9.923818844903063e-05\n        unknown: 0.3300864001554848\n        wind: 0.015983934198517718\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.5000949064195783e-06\n        coal: 0.020934725772799263\n        gas: 0.009609555438586572\n        geothermal: 0.0\n        hydro: 0.7024090375442017\n        hydro discharge: 0.0\n        nuclear: 0.001745066548919884\n        oil: 4.786454572881473e-06\n        solar: 5.067658779038262e-05\n        unknown: 0.2479407550602173\n        wind: 0.01729805237667662\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.659907486189789e-05\n        coal: 0.030190793847532715\n        gas: 0.024830894609418994\n        geothermal: 0.0\n        hydro: 0.9066887069931481\n        hydro discharge: 0.0\n        nuclear: 0.005444928514226817\n        oil: 7.156096282642579e-06\n        solar: 0.0001540586011036827\n        unknown: 9.512207228531505e-05\n        wind: 0.032555782403432654\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.143271671386385e-05\n        coal: 0.06561115136832395\n        gas: 0.06759193212988396\n        geothermal: 0.0\n        hydro: 0.7617479033589687\n        hydro discharge: 0.0\n        nuclear: 0.011383675245776331\n        oil: 1.744239958122339e-05\n        solar: 0.0007941509621297181\n        unknown: 0.00020702289645406453\n        wind: 0.09255513661771894\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Central\nzone_name: Southwestern Power Administration\n"
  },
  {
    "path": "config/zones/US-CENT-SWPP.yaml",
    "content": "bounding_box:\n  - - -106.01946751397405\n    - 30.877232015991254\n  - - -92.48672486724861\n    - 48.99978910378593\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 1.2\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 2.0\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 14.0\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 24.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 25.5\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 26.9\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 27.9\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 26.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 28.5\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 198.5\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 450.5\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 329.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 346.1\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 343.7\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 342.1\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 343.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 345.8\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 344.2\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 327.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 324.2\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 323.4\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 317.8\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 25072.3\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 25017.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 25182.1\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 25100.1\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 24255.1\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 22997.1\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 22784.3\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 22064.3\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 22059.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 22088.2\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 21367.2\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 20999.3\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 20639.3\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 20279.3\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 34958.4\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 35070.4\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 35069.2\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 35267.2\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 35333.2\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 35721.2\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 35577.0\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 35586.3\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 35060.3\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 34832.3\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 34758.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 35980.3\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 35927.3\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 35922.9\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 35904.2\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 35665.1\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 35655.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 35582.7\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 35441.7\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 35430.2\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 34889.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 34696.5\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 34689.5\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 34753.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 34995.3\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 35064.3\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 34966.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 35119.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 35126.1\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 35060.7\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 35064.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 34980.9\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 35050.8\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 35376.5\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 35489.3\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 35324.7\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 36098.4\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 36458.4\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 36704.1\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 36861.9\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 36869.6\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3081.8\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 3071.0\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 3068.6\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 3103.6\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 259.2\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2068.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2097.3\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2003.6\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 2009.6\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 2010.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 2084.6\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 2090.6\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2023.3\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 2026.3\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 2023.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 2083.4\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 2087.4\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 2091.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2263.1\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 2261.5\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 2263.3\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2049.3\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 2041.3\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 2044.4\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 2050.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2224.1\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 2225.9\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 2228.9\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 2232.8\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 2229.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 2229.1\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 2231.1\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 2234.1\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 2240.1\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 2242.3\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2249.7\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2173.3\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 2215.1\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 2233.7\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 2233.9\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2223.5\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 258.0\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 259.0\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 283.5\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 287.0\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 290.5\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 305.9\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 311.7\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 321.7\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 323.0\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 331.5\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 332.5\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 338.5\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 348.5\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 350.0\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 357.2\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 361.6\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 381.6\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 383.1\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 393.1\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 395.1\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 398.4\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 400.4\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 401.4\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 402.8\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 404.8\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 409.8\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 418.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 429.3\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 430.6\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 443.6\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 445.6\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 448.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 466.6\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 467.6\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 469.2\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 499.2\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 502.0\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 503.0\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 523.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 603.0\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 607.4\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 608.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 609.7\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 812.7\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 819.4\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 869.6\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 889.6\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 1084.7\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 1157.2\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 1170.2\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 1428.2\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 62.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 15324.3\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 15954.9\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 16239.0\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 16628.7\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 16784.9\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 17417.2\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 17427.5\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 17626.1\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 17666.1\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 18766.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 19342.1\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 19541.4\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 20019.4\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 20295.0\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 20455.0\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 20557.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 20549.8\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 20955.6\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 21155.7\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 21385.7\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 21490.7\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 22489.1\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 24226.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 24703.6\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 25055.4\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 25489.4\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 25841.2\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 26295.8\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 26583.8\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 26586.5\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 26703.5\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 28017.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 28166.4\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 28461.8\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 29460.8\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 29466.4\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 30793.4\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 31064.4\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 31366.1\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 31764.1\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 32707.0\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 32908.5\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 33110.0\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 33629.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 33624.7\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 33931.9\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 34080.3\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 34273.8\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 34426.8\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 34865.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 35463.4\ncenter_point:\n  - -99.25192402528673\n  - 40.10576311189023\ncentroid:\n  - -98.17885953810394\n  - 39.49536636803802\ncomment: Southwest Power Pool\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1014.6252748901705\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1001.8898548190425\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1006.6931219669046\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1033.3040921750498\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 459.1389525209879\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 459.677150611773\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 470.80292727723975\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 491.00210113204867\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 975.0111176473947\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1315.8465789346942\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1291.2071450487374\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 473.2147534174965\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1074.6252748901707\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1061.8898548190425\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1066.6931219669045\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1093.3040921750498\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 579.1389525209879\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 579.677150611773\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 590.8029272772397\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 611.0021011320487\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1219.0111176473947\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1559.8465789346942\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1535.2071450487374\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 717.2147534174965\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.66\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0\n        biomass: 0.00035980749970720624\n        coal: 0.37406030993480177\n        gas: 0.22706130341042047\n        geothermal: 0\n        hydro: 0.04289187145125501\n        hydro discharge: 0\n        nuclear: 0.05895103173687554\n        oil: 0.0007180557036410336\n        solar: 0.002031208058277777\n        unknown: 0.0009574344892645971\n        wind: 0.29296897193376714\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0\n        biomass: 0.00035980754737542555\n        coal: 0.3740603594912699\n        gas: 0.22706133349208363\n        geothermal: 0\n        hydro: 0.04289187713368002\n        hydro discharge: 0\n        nuclear: 0.05895103954685924\n        oil: 0.0007180557987708926\n        solar: 0.0020310758606134354\n        unknown: 0.000957434616107971\n        wind: 0.292969010747047\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00038485670380757715\n        coal: 0.4599174239473165\n        gas: 0.19548289797976712\n        geothermal: 0.0\n        hydro: 0.04857262777746696\n        hydro discharge: 2.0575886644913787e-07\n        nuclear: 0.06712041945286505\n        oil: 0.0017600248468336065\n        solar: 0.00211052201053287\n        unknown: 0.0025090672336663556\n        wind: 0.22214194231887516\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00035762052730163623\n        coal: 0.42273605202585424\n        gas: 0.23379737198413494\n        geothermal: 3.725273585655814e-11\n        hydro: 0.05233505958099327\n        hydro discharge: 1.3983931985834792e-06\n        nuclear: 0.05322574153830007\n        oil: 0.0012354975272069982\n        solar: 0.0019767259040801267\n        unknown: 0.00279897123287221\n        wind: 0.23153556020572857\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00030103042480881257\n        coal: 0.34580376456761597\n        gas: 0.25734590091561266\n        geothermal: 2.2165034386113614e-09\n        hydro: 0.06294009529589224\n        hydro discharge: 4.359123429269011e-09\n        nuclear: 0.059058613839546456\n        oil: 0.000178625832555975\n        solar: 0.0019849822291618854\n        unknown: 0.0030602127018894776\n        wind: 0.26932675949011037\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0003270413384901316\n        coal: 0.31189929927157106\n        gas: 0.26781216226989085\n        geothermal: 2.79522447821207e-09\n        hydro: 0.05119457179917011\n        hydro discharge: 3.8648637118745566e-08\n        nuclear: 0.06206207991445291\n        oil: 0.00014064041518315048\n        solar: 0.002327097538453558\n        unknown: 0.003065731320810231\n        wind: 0.3011713268242183\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0003163516453908609\n        coal: 0.35590041828435176\n        gas: 0.19983612749092192\n        geothermal: 2.6127394146064475e-09\n        hydro: 0.04242061909418809\n        hydro discharge: 6.95361932773116e-08\n        nuclear: 0.057673852188265866\n        oil: 0.0005086429210816029\n        solar: 0.0022087256215997456\n        unknown: 0.002871793199411955\n        wind: 0.3382633797138772\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 1.0599359303001395e-10\n        biomass: 0.00019500644715745682\n        coal: 0.3349812281371984\n        gas: 0.21001380967558309\n        geothermal: 3.6037821630204747e-09\n        hydro: 0.03239971665722049\n        hydro discharge: 5.0876924654406705e-09\n        nuclear: 0.05111896950357818\n        oil: 0.000558798293116629\n        solar: 0.002236561019784568\n        unknown: 0.001954695720297224\n        wind: 0.3665411801334774\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 3.212976286684422e-10\n        biomass: 0.00035185592483346907\n        coal: 0.2718935845012305\n        gas: 0.26884170884474573\n        geothermal: 3.3914749692780013e-09\n        hydro: 0.033616872733455726\n        hydro discharge: 9.656778728312623e-08\n        nuclear: 0.061019680040313204\n        oil: 0.00036062838538847655\n        solar: 0.0025908683941408984\n        unknown: 0.0008761758130996569\n        wind: 0.3604485052688786\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 1.0379406242742397e-10\n        biomass: 0.00033173530337574883\n        coal: 0.24739636624205283\n        gas: 0.28540550248584345\n        geothermal: 4.2209585387152425e-09\n        hydro: 0.03373018723583877\n        hydro discharge: 3.387146237214935e-08\n        nuclear: 0.05351255150875622\n        oil: 0.0003502724731510162\n        solar: 0.005079625055022232\n        unknown: 0.0010075414538685166\n        wind: 0.3731861627814639\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: US_SPP.fetch_load_forecast\n  dayaheadLocationalMarginalPrice: US_SPP.fetch_dayahead_locational_marginal_price\n  gridAlerts: email_grid_alerts.fetch_grid_alerts_emails\n  production: US_SPP.fetch_production\n  productionCapacity: EIA.fetch_production_capacity\n  productionPerModeForecast: US_SPP.fetch_wind_solar_forecasts\n  realtimeLocationalMarginalPrice: US_SPP.fetch_realtime_locational_marginal_price\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Central\nzone_name: Southwest Power Pool\nzone_short_name: SPP\n"
  },
  {
    "path": "config/zones/US-FLA-FMPP.yaml",
    "content": "bounding_box:\n  - - -82.50742507425069\n    - 26.327819690016725\n  - - -80.04500045000445\n    - 30.18601900767237\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 45.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1292.8\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 929.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2535.8\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2506.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 2483.9\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 2487.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2502.9\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 2562.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2622.9\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2597.3\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 93.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 87.8\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 220.3\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 9.0\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 17.9\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 166.9\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -81.27621276212757\n  - 28.256919348844548\ncentroid:\n  - -81.52605526055255\n  - 28.532223908834915\ncomment: Florida Municipal Power Pool\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 768.4856555485999\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 806.7004193423496\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 763.2191822274799\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 744.4422069628371\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 446.01597200626395\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 439.9025360279061\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 399.91916460663316\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 396.92867418651286\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 791.3672765485921\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 828.4856555485999\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 866.7004193423496\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 823.2191822274799\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 804.4422069628371\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 566.015972006264\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 559.9025360279061\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 519.9191646066331\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 516.9286741865128\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1035.3672765485921\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.29949770253984176\n        gas: 0.607216900507734\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.05601559540906811\n        oil: 0.017035436173037325\n        solar: 0.012130367481323326\n        unknown: 0.00810344359367948\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.29949782223725796\n        gas: 0.6072171431883738\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.05601561779629172\n        oil: 0.0170354429814291\n        solar: 0.012129973097258556\n        unknown: 0.008103446832306195\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2734776240561849\n        gas: 0.6454578341304538\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.05730370582379923\n        oil: 0.00030257415071995226\n        solar: 0.014987948718757638\n        unknown: 0.008470442891409838\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3641178606154934\n        gas: 0.5550564513927738\n        geothermal: 0.0\n        hydro: 0.00024160466813817158\n        hydro discharge: 1.2395866220398879e-05\n        nuclear: 0.06387327960198631\n        oil: 0.00010536543937167994\n        solar: 0.003652549037572886\n        unknown: 0.012940050627756943\n        wind: 4.3237371710999716e-07\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2973894213571623\n        gas: 0.6008549274046878\n        geothermal: 0.0\n        hydro: 0.00018261088631565988\n        hydro discharge: 1.1288280000011357e-06\n        nuclear: 0.07012059593726101\n        oil: 0.00016543937427397593\n        solar: 0.0068235967197151975\n        unknown: 0.02446136735924484\n        wind: 2.6988844047646196e-07\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2598403615941424\n        gas: 0.6265408296869334\n        geothermal: 0.0\n        hydro: 0.00019896247647282068\n        hydro discharge: 9.463350814286271e-07\n        nuclear: 0.07316917711335676\n        oil: 0.0002615358075839743\n        solar: 0.01207654328171272\n        unknown: 0.02791106706673254\n        wind: 1.4429932092706015e-07\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.26424992229601063\n        gas: 0.6096662717625891\n        geothermal: 0.0\n        hydro: 0.0001349089002806099\n        hydro discharge: 7.950978632497339e-07\n        nuclear: 0.06915536091861439\n        oil: 0.00022086975935840583\n        solar: 0.0272145478284471\n        unknown: 0.029356386611274307\n        wind: 4.208054073221236e-07\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.20150531927757326\n        gas: 0.6723591624049727\n        geothermal: 0.0\n        hydro: 0.00011082154199776624\n        hydro discharge: 3.8517448507641324e-07\n        nuclear: 0.06659007580556685\n        oil: 0.0003779571540014642\n        solar: 0.028527119394667944\n        unknown: 0.0305278928062719\n        wind: 9.143755326240925e-07\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.16761275063951062\n        gas: 0.687899878073198\n        geothermal: 0.0\n        hydro: 0.0002078957300194654\n        hydro discharge: 8.463719125137084e-07\n        nuclear: 0.07954263507492554\n        oil: 0.0003316975402539143\n        solar: 0.033927873479998816\n        unknown: 0.030475120624263923\n        wind: 9.479827287500063e-07\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.14600391089901532\n        gas: 0.7315339642642004\n        geothermal: 0.0\n        hydro: 0.00015121069946508203\n        hydro discharge: 7.322136708176398e-07\n        nuclear: 0.06965895353125312\n        oil: 0.00020001279422783547\n        solar: 0.0368809604380467\n        unknown: 0.015569004071754993\n        wind: 9.010623577192186e-07\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Florida Municipal Power Pool\n"
  },
  {
    "path": "config/zones/US-FLA-FPC.yaml",
    "content": "bounding_box:\n  - - -85.99585995859952\n    - 27.442633216891252\n  - - -80.86220862208617\n    - 30.463649077266297\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 11.0\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 22.0\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 30.3\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 47.6\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 50.1\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 55.1\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 387.8\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 397.4\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 272.4\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 258.4\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 255.2\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 253.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 257.2\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 184.2\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2442.7\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 1478.4\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 8766.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 8737.9\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 9723.2\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 10708.5\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 10674.8\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 10555.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 10587.6\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 10553.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 10751.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 10774.1\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 11156.9\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 12.2\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1358.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1363.4\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 1329.7\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 1330.7\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 30.8\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 32.7\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 41.5\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 48.8\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 175.7\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 177.2\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 297.1\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 372.0\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 446.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 436.5\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 586.3\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 660.8\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 735.7\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 885.5\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 960.4\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 1039.3\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 1264.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 1264.8\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 1414.6\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 1489.5\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 1564.4\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 1787.9\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 1936.9\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 2011.8\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 2236.1\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2311.1\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 150\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 18.8\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -82.69102691026904\n  - 28.929528280334964\ncentroid:\n  - -82.856306175002\n  - 28.95372853182364\ncomment: Duke Energy Florida Inc\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 425.17\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 425.35\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 464.86\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 521.6312947097579\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 569.1649476424932\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 558.6454964558035\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 423.93468599511147\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 423.8115836376518\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 426.84458929288365\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 457.83672479746605\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1162.9400758736372\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 654.9016481509434\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1047.7402736442787\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1047.3624904149933\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 458.17\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 458.35\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 497.86\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 581.6312947097579\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 629.1649476424932\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 618.6454964558035\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 543.9346859951115\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 543.8115836376518\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 546.8445892928837\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 577.8367247974661\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1406.9400758736372\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 898.9016481509434\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1291.7402736442787\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1291.3624904149933\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.103574549421613\n        gas: 0.8561187845041084\n        geothermal: 0.0\n        hydro: 0.0049927946629394785\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0008967128878118871\n        solar: 0.016946231230295997\n        unknown: 0.017470979264185026\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.10357461431573237\n        gas: 0.8561193209010795\n        geothermal: 0.0\n        hydro: 0.00499279779115017\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0008967134496428919\n        solar: 0.01694561538424483\n        unknown: 0.017470990210540285\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0992582276665768\n        gas: 0.8389399755552575\n        geothermal: 0.0\n        hydro: 0.00656237989072391\n        hydro discharge: 0.0001118528262114915\n        nuclear: 0.008539199780249243\n        oil: 0.000860540950620173\n        solar: 0.02920673781245172\n        unknown: 0.01651223945817925\n        wind: 8.781214764180111e-06\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.11034517145751514\n        gas: 0.8323808129264919\n        geothermal: 0.0\n        hydro: 0.0047516421369919225\n        hydro discharge: 0.00010228065167879173\n        nuclear: 0.025186780165201334\n        oil: 0.0006265785896511865\n        solar: 0.0021072838266193482\n        unknown: 0.02449380508917529\n        wind: 5.57977337386054e-06\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.05438534073745743\n        gas: 0.8805781149781613\n        geothermal: 0.0\n        hydro: 0.005104189466503513\n        hydro discharge: 1.1178744829980037e-05\n        nuclear: 0.02695996784041916\n        oil: 0.0005448566320506895\n        solar: 0.0063476558307984975\n        unknown: 0.026063397754375477\n        wind: 5.189190908314686e-06\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.11497536195383407\n        gas: 0.8068564882297887\n        geothermal: 0.0\n        hydro: 0.005702355026320435\n        hydro discharge: 1.3044117780394374e-05\n        nuclear: 0.02896359155748144\n        oil: 0.0004028357363135096\n        solar: 0.016454727056140712\n        unknown: 0.02662694998101486\n        wind: 4.506745423163465e-06\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.15015004699474718\n        gas: 0.7695505275479358\n        geothermal: 0.0\n        hydro: 0.005823247084078365\n        hydro discharge: 1.2544437235447218e-05\n        nuclear: 0.027617880430930924\n        oil: 0.0007122127956249367\n        solar: 0.022903564632629343\n        unknown: 0.023218550989929195\n        wind: 1.1347587779403906e-05\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1167611631956992\n        gas: 0.7920861960048775\n        geothermal: 0.0\n        hydro: 0.004438027100015994\n        hydro discharge: 3.7135721403796805e-06\n        nuclear: 0.026638762251665997\n        oil: 0.0010972026956387537\n        solar: 0.03301282782242211\n        unknown: 0.025954795630625648\n        wind: 7.234536956047993e-06\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.09858617761804514\n        gas: 0.7874475678136441\n        geothermal: 0.0\n        hydro: 0.004123099044436697\n        hydro discharge: 2.835431395732153e-06\n        nuclear: 0.035543003293674866\n        oil: 0.00046272849452172867\n        solar: 0.04862534471532766\n        unknown: 0.025205820384800605\n        wind: 3.309659159515913e-06\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.07192514068756008\n        gas: 0.821324860654408\n        geothermal: 0.0\n        hydro: 0.0029010760615029614\n        hydro discharge: 2.2965750281605837e-06\n        nuclear: 0.028493352732321942\n        oil: 0.0007948505603240849\n        solar: 0.06154519216648502\n        unknown: 0.013010176598688486\n        wind: 2.9803827190777754e-06\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.0391\n    - datetime: '2022-01-01'\n      value: 0.0506\n    - datetime: '2025-01-01'\n      value: 0.0984\n  hydro discharge:\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\nisRenewable:\n  battery discharge:\n    - datetime: '2021-01-01'\n      value: 0.0135\n    - datetime: '2022-01-01'\n      value: 0.0256\n    - datetime: '2025-01-01'\n      value: 0.0754\n  hydro discharge:\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Duke Energy Florida\n"
  },
  {
    "path": "config/zones/US-FLA-FPL.yaml",
    "content": "bounding_box:\n  - - -82.79542795427949\n    - 25.172935843819346\n  - - -80.11340113401128\n    - 30.583860035234792\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 14.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 24.0\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 433.0\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 493.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 1014.5\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 531.5\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 622.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 620.8\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 622.4\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 620.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 617.6\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 540.6\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 543.8\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 540.6\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 535.8\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 395.4\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 21336.3\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 20293.9\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 22017.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 23743.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 24018.1\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 25465.8\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 28207.1\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 25465.8\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 28215.1\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 43.5\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3797.2\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3846.1\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 1977.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 250.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 274.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 316.3\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 148.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 189.8\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 262.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 560.7\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 858.7\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1157.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1604.8\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 1902.8\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 2275.3\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 2573.3\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 2647.8\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 2871.3\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 2945.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 3392.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 4137.4\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 4360.9\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 4584.4\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 5701.9\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 6446.9\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 7042.9\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 7192.3\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 8086.3\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 7862.8\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 8086.3\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -80.92700927009265\n  - 27.844767492952542\ncentroid:\n  - -81.44499906537523\n  - 27.88223250763076\ncomment: Florida Power & Light Company\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 248.89\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 367.48937057919414\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 365.6611442526231\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 359.44438512281965\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 367.9628636512186\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 390.05044165621\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 450.5327899842862\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 289.96851114965034\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 175.09320207293555\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 281.89\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 487.48937057919414\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 485.6611442526231\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 479.44438512281965\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 487.9628636512186\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 634.0504416562101\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 694.5327899842862\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 533.9685111496503\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 419.0932020729356\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6519385220184877\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.2202698523204888\n        oil: 4.593666138456435e-05\n        solar: 0.03268655720609928\n        unknown: 0.09505922335091438\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.6519390424823136\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.22027002816910976\n        oil: 4.593669805730223e-05\n        solar: 0.03268578494253772\n        unknown: 0.09505929923979868\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0064681295127164366\n        gas: 0.6515181312610444\n        geothermal: 0.0\n        hydro: 0.0016325961345460946\n        hydro discharge: 0.00010193209897949302\n        nuclear: 0.2162773184323933\n        oil: 3.81735964711513e-06\n        solar: 0.043819337191046276\n        unknown: 0.08017369657385313\n        wind: 5.0141388045604086e-06\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.02862502495721441\n        gas: 0.7176259312164941\n        geothermal: 0.0\n        hydro: 0.0014033604396553887\n        hydro discharge: 0.00010321557713140836\n        nuclear: 0.20324494856772676\n        oil: 3.8955294144861965e-06\n        solar: 0.012648809690371158\n        unknown: 0.036340801041191466\n        wind: 3.987123965789817e-06\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.02858891951649374\n        gas: 0.6595579932943951\n        geothermal: 0.0\n        hydro: 0.0014535635493887818\n        hydro discharge: 1.177672009167074e-05\n        nuclear: 0.210189312831756\n        oil: 3.047188680329419e-06\n        solar: 0.017432255203806726\n        unknown: 0.08275788302007701\n        wind: 5.202297097340151e-06\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.03133841615353268\n        gas: 0.6451410185289799\n        geothermal: 0.0\n        hydro: 0.0010910628609407229\n        hydro discharge: 8.914110538063108e-06\n        nuclear: 0.20327702164757888\n        oil: 2.8528002360066463e-06\n        solar: 0.024795470764602794\n        unknown: 0.09434263949671473\n        wind: 2.5550805420625587e-06\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.030835826289752424\n        gas: 0.6161344851119223\n        geothermal: 0.0\n        hydro: 0.001005573801507322\n        hydro discharge: 9.918884587904354e-06\n        nuclear: 0.2146593605421962\n        oil: 3.0052272858027465e-06\n        solar: 0.04222888390882885\n        unknown: 0.09511614403700229\n        wind: 6.761255462536685e-06\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.02505542874444403\n        gas: 0.6037015218221942\n        geothermal: 0.0\n        hydro: 0.000736116385507975\n        hydro discharge: 4.683464578846961e-06\n        nuclear: 0.2074953582286158\n        oil: 8.046730629371908e-06\n        solar: 0.050727286239249596\n        unknown: 0.11226033967594552\n        wind: 1.1189285523775224e-05\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.01853096704019643\n        gas: 0.597151331722411\n        geothermal: 0.0\n        hydro: 0.0010020820975442208\n        hydro discharge: 5.6691931740162595e-06\n        nuclear: 0.22643024450321014\n        oil: 6.615474939135388e-06\n        solar: 0.07584177515876471\n        unknown: 0.08102367036060279\n        wind: 7.610302131133911e-06\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.011703858863971833\n        gas: 0.707267099343537\n        geothermal: 0.0\n        hydro: 0.0006587990493102537\n        hydro discharge: 4.521083417839027e-06\n        nuclear: 0.18526781665147687\n        oil: 7.090184066367573e-06\n        solar: 0.08298619272945335\n        unknown: 0.012097789251635535\n        wind: 6.811091115586069e-06\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.3638\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.1193\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Florida Power and Light Company\n"
  },
  {
    "path": "config/zones/US-FLA-GVL.yaml",
    "content": "bounding_box:\n  - - -82.71982719827193\n    - 29.370301792886124\n  - - -81.96021960219596\n    - 29.928424097739878\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 116.1\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 250.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 370.5\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 377.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 328.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 579.4\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 529.4\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 574.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 478.8\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2.8\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 4.8\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -82.34002340023395\n  - 29.649362945313\ncentroid:\n  - -82.35910359103585\n  - 29.631760626467617\ncomment: Gainesville Regional Utilities\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 877.6982215318458\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 847.0060140972408\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 457.6172075069577\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 474.33858230699275\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 612.5766655496152\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 652.0530377690332\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 937.6982215318458\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 907.0060140972408\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 577.6172075069577\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 594.3385823069927\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 732.5766655496152\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 772.0530377690332\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2735765199161425\n        gas: 0.4477707896575821\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.27864523643139993\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.27357651991614257\n        gas: 0.4477707896575821\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.27864523643139993\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.18541855539797844\n        gas: 0.5650375614582197\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.24953635956679246\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.21620895904148832\n        gas: 0.5107577338248461\n        geothermal: 0.0\n        hydro: 0.0002788396577371287\n        hydro discharge: 1.3568419101402008e-05\n        nuclear: 0.023345020177017277\n        oil: 4.368102728821572e-06\n        solar: 0.0018595468327294348\n        unknown: 0.247529283931323\n        wind: 8.645203317459361e-08\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2994593717921277\n        gas: 0.3928260763006779\n        geothermal: 0.0\n        hydro: 0.00038466682871958697\n        hydro discharge: 2.3290740290762512e-07\n        nuclear: 0.023396586578975205\n        oil: 1.35288821862864e-05\n        solar: 0.0024981141715430767\n        unknown: 0.2814182884148369\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.18340280036835055\n        gas: 0.5999040531296296\n        geothermal: 0.0\n        hydro: 0.00041824397652431416\n        hydro discharge: 3.495498350312219e-07\n        nuclear: 0.02335369803917639\n        oil: 2.1869661417822964e-05\n        solar: 0.004408183101458015\n        unknown: 0.18848843131385762\n        wind: 2.532969819066825e-08\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.30024481820366333\n        gas: 0.3870046181207815\n        geothermal: 0.0\n        hydro: 0.0003189081825354003\n        hydro discharge: 2.0747393307878493e-08\n        nuclear: 0.018775462497779512\n        oil: 3.414502253644103e-05\n        solar: 0.004943688877401288\n        unknown: 0.288676004266162\n        wind: 3.630793828878737e-08\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.16425436939554477\n        gas: 0.527446568675727\n        geothermal: 0.0\n        hydro: 0.0002499591666320546\n        hydro discharge: 5.117604705526986e-08\n        nuclear: 0.016352492137363304\n        oil: 5.54134237514462e-05\n        solar: 0.005164722492050773\n        unknown: 0.28647366002634256\n        wind: 4.657020282029558e-07\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.005302149379020972\n        gas: 0.8038181400712242\n        geothermal: 0.0\n        hydro: 0.00024552836603655085\n        hydro discharge: 1.8781862286393695e-07\n        nuclear: 0.03556314485578013\n        oil: 1.0325081662178007e-05\n        solar: 0.010114878025025892\n        unknown: 0.14494213221734142\n        wind: 2.1747419489508488e-07\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.006126741619758149\n        gas: 0.8411935163702214\n        geothermal: 0.0\n        hydro: 0.00025505803801339897\n        hydro discharge: 1.689573648737407e-07\n        nuclear: 0.02536538092171669\n        oil: 4.9885868817292464e-05\n        solar: 0.013042625162602153\n        unknown: 0.11396378457777641\n        wind: 2.896411969264126e-08\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Gainesville Regional Utilities\n"
  },
  {
    "path": "config/zones/US-FLA-HST.yaml",
    "content": "bounding_box:\n  - - -80.88380883808833\n    - 25.087070873841853\n  - - -80.12420124201236\n    - 25.974342230276008\ncan_have_zero_production: true\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 35.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 33.6\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 35.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -80.50400504005034\n  - 25.53070655205893\ncentroid:\n  - -80.53880538805383\n  - 25.501846381594266\ncomment: City Of Homestead\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 1.0\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0510705212262092\n        gas: 0.6788054310453536\n        geothermal: 0.0\n        hydro: 0.002119948959390617\n        hydro discharge: 0.0001270195123628857\n        nuclear: 0.20797480421058573\n        oil: 2.75132517753543e-06\n        solar: 0.013506043656123153\n        unknown: 0.046368118490404314\n        wind: 1.375662588767715e-06\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.028351897004424954\n        gas: 0.6606452217502501\n        geothermal: 0.0\n        hydro: 0.0014674075096396484\n        hydro discharge: 5.26496041056468e-06\n        nuclear: 0.20981056365746062\n        oil: 2.334302835751978e-06\n        solar: 0.016530714824867652\n        unknown: 0.08317228347637329\n        wind: 4.941224980788859e-07\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.040738361734314416\n        gas: 0.60517999871828\n        geothermal: 0.0\n        hydro: 0.0016486592579322483\n        hydro discharge: 6.53904677221279e-06\n        nuclear: 0.21503499778107232\n        oil: 4.114080577913929e-06\n        solar: 0.028099153623247355\n        unknown: 0.10927605092683211\n        wind: 2.6758247661228814e-07\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.030732100717347593\n        gas: 0.6173161566013098\n        geothermal: 0.0\n        hydro: 0.001010278513475863\n        hydro discharge: 4.615596351832644e-06\n        nuclear: 0.21517582904502472\n        oil: 2.0812143550081736e-06\n        solar: 0.040132912390946046\n        unknown: 0.09561149098867752\n        wind: 7.888473764950337e-07\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.024917017753807315\n        gas: 0.6059949509024442\n        geothermal: 0.0\n        hydro: 0.0007449877870854577\n        hydro discharge: 1.6065310404747467e-06\n        nuclear: 0.2075874985655973\n        oil: 6.3441582924870084e-06\n        solar: 0.04852777823314372\n        unknown: 0.11220055408927723\n        wind: 4.655661382600286e-06\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.018829360639947185\n        gas: 0.5985708301001147\n        geothermal: 0.0\n        hydro: 0.0010516886525531717\n        hydro discharge: 1.7614098896024452e-06\n        nuclear: 0.22785906181913967\n        oil: 3.506951221640904e-06\n        solar: 0.07202168597076694\n        unknown: 0.08164169749133973\n        wind: 3.364134203565031e-06\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.011836824452973634\n        gas: 0.710527087021093\n        geothermal: 0.0\n        hydro: 0.0006674523044236396\n        hydro discharge: 1.1343565809821363e-06\n        nuclear: 0.18595572696391394\n        oil: 5.361000279984068e-06\n        solar: 0.07917294590011055\n        unknown: 0.011817913330246848\n        wind: 6.837217748385479e-07\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: City of Homestead\n"
  },
  {
    "path": "config/zones/US-FLA-JEA.yaml",
    "content": "bounding_box:\n  - - -85.49545495454949\n    - 29.935579511904663\n  - - -81.3446134461344\n    - 31.000305139625667\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 5.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 148.5\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1953.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 595.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2166.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2166.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2176.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2179.5\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 248.4\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 15.0\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 22.1\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 23.5\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 32.5\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 37.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 35.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 38.1\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -84.55224552245517\n  - 30.047203972875423\ncentroid:\n  - -83.7343827983734\n  - 30.427221514245534\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 612.0220146915486\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 524.9174215211997\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 539.5337755504269\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 576.2779583001487\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 732.0220146915486\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 644.9174215211997\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 659.5337755504269\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 696.2779583001487\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.4253744861572457\n        gas: 0.5642683737322164\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0007695979123000611\n        solar: 0.006620850616074635\n        unknown: 0.0029656952304433957\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.425374587629121\n        gas: 0.564268508336834\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0007695980958854568\n        solar: 0.006620613331950827\n        unknown: 0.002965695937901568\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.4041536346819033\n        gas: 0.5861141698833933\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00026788224238983384\n        solar: 0.006534351166174769\n        unknown: 0.0029311035697853556\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.35039819407541484\n        gas: 0.5632428739869481\n        geothermal: 0.0\n        hydro: 0.0006311106443782937\n        hydro discharge: 4.099544741007481e-05\n        nuclear: 0.06076905869172365\n        oil: 0.000215185866672837\n        solar: 0.007807058665573506\n        unknown: 0.016893530927321484\n        wind: 1.2308672363590809e-06\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.31031255416319337\n        gas: 0.5672281898894732\n        geothermal: 0.0\n        hydro: 0.000554665519650284\n        hydro discharge: 4.281244622493133e-06\n        nuclear: 0.07921745624908733\n        oil: 0.00014911053867498977\n        solar: 0.010546769821672903\n        unknown: 0.03198451211620193\n        wind: 1.5545285271282422e-06\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3697166883299766\n        gas: 0.5562083269132314\n        geothermal: 0.0\n        hydro: 0.0003592186724903754\n        hydro discharge: 2.4912552887869747e-06\n        nuclear: 0.040432901355233614\n        oil: 0.0001684247327631361\n        solar: 0.01087765900201646\n        unknown: 0.02223301393186026\n        wind: 4.398764731611916e-07\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2763189214398886\n        gas: 0.6186581566379036\n        geothermal: 0.0\n        hydro: 0.0002894749840279571\n        hydro discharge: 2.886816114768052e-06\n        nuclear: 0.05846051324185764\n        oil: 0.0002247476683820618\n        solar: 0.016576559860974793\n        unknown: 0.029466171329171804\n        wind: 1.716832504415604e-06\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.27404257563899403\n        gas: 0.6074501528420674\n        geothermal: 0.0\n        hydro: 0.00021503205407056238\n        hydro discharge: 1.27117176928497e-06\n        nuclear: 0.06233234205711687\n        oil: 0.0002497465994790356\n        solar: 0.019944765554343685\n        unknown: 0.03576038345203256\n        wind: 3.150433858296857e-06\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.270296142229289\n        gas: 0.6065518862975214\n        geothermal: 0.0\n        hydro: 0.00033009601351792007\n        hydro discharge: 1.9209181207735924e-06\n        nuclear: 0.06761626231980271\n        oil: 0.00012394145396030462\n        solar: 0.028966117981929065\n        unknown: 0.026111014205293527\n        wind: 2.0343273746466268e-06\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2361773281705205\n        gas: 0.6715034736843349\n        geothermal: 0.0\n        hydro: 0.00020369577644618916\n        hydro discharge: 1.5576259413242776e-06\n        nuclear: 0.05558299303693658\n        oil: 0.00014235141227941762\n        solar: 0.031205014645403553\n        unknown: 0.005181076347993189\n        wind: 1.9070981072641493e-06\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Jacksonville Electric Authority\n"
  },
  {
    "path": "config/zones/US-FLA-SEC.yaml",
    "content": "bounding_box:\n  - - -84.87624876248758\n    - 26.219057394711882\n  - - -80.70740707407069\n    - 30.726968318530623\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 17.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1.6\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1471.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1429.2\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 714.6\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 897.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 853.3\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 2036.5\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 10\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 74.5\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -83.37604999958802\n  - 30.14833963121009\ncentroid:\n  - -82.31152949827366\n  - 28.796894305433558\ncomment: Seminole Electric Cooperative\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 964.3118179231524\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 940.1477267918307\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 895.9786783369478\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 596.0092651928338\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 386.32980375424796\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 387.4041558239329\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 400.49726922891256\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 398.6011426902413\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1024.3118179231524\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.1477267918307\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 955.9786783369478\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 656.0092651928338\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 506.32980375424796\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 507.4041558239329\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 520.4972692289125\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 518.6011426902413\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.014416969634279101\n        gas: 0.9855614963288232\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 2.151871963618696e-05\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.014416969686159187\n        gas: 0.9855614998754085\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 2.1515138889387014e-05\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.44257049401155596\n        gas: 0.5570939909760182\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0003366828308859193\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6621526369032708\n        gas: 0.3331527052298563\n        geothermal: 0.0\n        hydro: 1.7593262005230038e-05\n        hydro discharge: 8.860767964496114e-07\n        nuclear: 0.0013051457319357156\n        oil: 6.727473940081793e-06\n        solar: 0.0006312182178289241\n        unknown: 0.002731833966803581\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5482004102555483\n        gas: 0.44713114646326346\n        geothermal: 0.0\n        hydro: 2.1493691309888375e-05\n        hydro discharge: 0.0\n        nuclear: 0.001182448961932077\n        oil: 6.536043816893673e-06\n        solar: 0.0011647348457659809\n        unknown: 0.002287792899845715\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5439562804746765\n        gas: 0.44756432580206607\n        geothermal: 0.0\n        hydro: 1.7252169317802387e-05\n        hydro discharge: 1.4614289976960936e-08\n        nuclear: 0.0015843059478223812\n        oil: 7.3875235833537545e-06\n        solar: 0.00435432769863551\n        unknown: 0.0025119699255449417\n        wind: 4.384286993088281e-08\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5732980145305351\n        gas: 0.41854626645572013\n        geothermal: 0.0\n        hydro: 3.703429966782468e-05\n        hydro discharge: 0.0\n        nuclear: 0.0026253806591243333\n        oil: 1.6920843813747482e-06\n        solar: 0.0015752667068190838\n        unknown: 0.003912003311377208\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5164710147740914\n        gas: 0.47896024284421373\n        geothermal: 0.0\n        hydro: 2.2284036680364155e-05\n        hydro discharge: 0.0\n        nuclear: 0.0014356908019629406\n        oil: 1.0317239055242622e-05\n        solar: 0.0012906046277485913\n        unknown: 0.0018078012233536246\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.28339773046064076\n        gas: 0.708710271372197\n        geothermal: 0.0\n        hydro: 2.9376835175522264e-05\n        hydro discharge: 0.0\n        nuclear: 0.0009280003366436627\n        oil: 4.179992144981205e-06\n        solar: 0.002355967944042342\n        unknown: 0.004573018945557239\n        wind: 0.0\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1619842306768427\n        gas: 0.8344185956841966\n        geothermal: 0.0\n        hydro: 2.1145730524378035e-05\n        hydro discharge: 0.0\n        nuclear: 0.0005487189687157279\n        oil: 3.9790104097350996e-06\n        solar: 0.0018365194344341143\n        unknown: 0.0011848510985980577\n        wind: 0.0\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Seminole Electric Cooperative\n"
  },
  {
    "path": "config/zones/US-FLA-TAL.yaml",
    "content": "bounding_box:\n  - - -84.33984339843393\n    - 30.38637060428654\n  - - -84.13104131041305\n    - 30.526616721916454\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 997.5\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 954.2\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 939.2\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 942.8\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 867.8\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 943.0\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 961.8\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 20.0\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 62.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -84.2354423544235\n  - 30.456493663101497\ncentroid:\n  - -84.24384243842432\n  - 30.454108525046568\ncomment: City Of Tallahassee\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 359.8683566148577\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 364.2664648566912\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 404.3608979577243\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 397.6026712385784\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 479.8683566148577\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 484.2664648566912\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 524.3608979577243\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 517.6026712385784\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9649769838658395\n        geothermal: 0.0\n        hydro: 0.007114899687620109\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.02790527891856134\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.9649777493327778\n        geothermal: 0.0\n        hydro: 0.007114905331506515\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.02790450549985011\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.04970960028085986\n        gas: 0.8477283826877068\n        geothermal: 0.0\n        hydro: 0.01683877424069395\n        hydro discharge: 0.0006789322099855085\n        nuclear: 0.05433008205935293\n        oil: 2.449296412193592e-05\n        solar: 0.028176323261638426\n        unknown: 0.0024561181381047696\n        wind: 5.660241833887547e-05\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.06810813410103869\n        gas: 0.8556303267647427\n        geothermal: 0.0\n        hydro: 0.01715819955908087\n        hydro discharge: 0.0008301710354649267\n        nuclear: 0.04645247588008885\n        oil: 2.5103941792837568e-05\n        solar: 0.010298077612191297\n        unknown: 0.0014534805238143366\n        wind: 4.238978202287405e-05\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.05077810843100562\n        gas: 0.8780566355121315\n        geothermal: 0.0\n        hydro: 0.012858325105494227\n        hydro discharge: 7.674013729803786e-05\n        nuclear: 0.042985926681446456\n        oil: 1.4003496436528795e-05\n        solar: 0.013360584542083815\n        unknown: 0.001829434357333603\n        wind: 3.814156117104368e-05\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.03366151465590064\n        gas: 0.8745562159053528\n        geothermal: 0.0\n        hydro: 0.012308783673431583\n        hydro discharge: 9.084366202225196e-05\n        nuclear: 0.04243429525454695\n        oil: 6.297752988093221e-06\n        solar: 0.03461306666196473\n        unknown: 0.0022952317496514954\n        wind: 3.127860236903087e-05\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.04659903451252052\n        gas: 0.8614742587007218\n        geothermal: 0.0\n        hydro: 0.010880433323181414\n        hydro discharge: 9.396528480497946e-05\n        nuclear: 0.04593124203811227\n        oil: 4.995908303796344e-06\n        solar: 0.03239237783767046\n        unknown: 0.002545493512414632\n        wind: 7.676888084012767e-05\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.03901931608278998\n        gas: 0.8721613388427143\n        geothermal: 0.0\n        hydro: 0.008818756628982233\n        hydro discharge: 5.15607440821757e-05\n        nuclear: 0.04092822974061035\n        oil: 4.003223533227796e-05\n        solar: 0.036651540507297437\n        unknown: 0.0022134413872387697\n        wind: 0.00011355563178237279\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.030895898475676174\n        gas: 0.8869074263484239\n        geothermal: 0.0\n        hydro: 0.006908333560527296\n        hydro discharge: 4.223191426751798e-05\n        nuclear: 0.03966606655584413\n        oil: 4.7417529990189375e-06\n        solar: 0.03365699887343671\n        unknown: 0.0018613437445966258\n        wind: 5.4844111171301235e-05\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.03011186320564432\n        gas: 0.8854251334968235\n        geothermal: 0.0\n        hydro: 0.005893024753519493\n        hydro discharge: 4.8471382146835576e-05\n        nuclear: 0.04564174594904067\n        oil: 7.451221193817397e-06\n        solar: 0.03144300360124301\n        unknown: 0.0013693576112433338\n        wind: 5.8680114373449385e-05\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: City of Tallahassee\n"
  },
  {
    "path": "config/zones/US-FLA-TEC.yaml",
    "content": "bounding_box:\n  - - -82.65862658626581\n    - 27.518480607038043\n  - - -81.6326163261632\n    - 28.347077567320923\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 12.6\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 27.6\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 67.6\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 107.6\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 69.1\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2015.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1124.4\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 678.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 486.0\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 486.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4916.1\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 4786.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 4644.7\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 5535.7\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 6331.3\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 6665.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 6770.4\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 6324.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 6219.7\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 6743.3\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 6123.9\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 6220.9\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 6258.5\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 133.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 10.3\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 29.3\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 174.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 344.5\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 399.9\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 449.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 452.7\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 527.2\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 602.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 661.6\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 736.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 781.9\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 782.9\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 912.0\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 913.0\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 1029.4\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 1258.9\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 1356.4\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 1430.9\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 371.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 365.8\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 325.3\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 317.8\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -82.14562145621451\n  - 27.932779087179483\ncentroid:\n  - -82.16767167671671\n  - 27.94181279756254\ncomment: Tampa Electric Company\ncontributors:\n  - brandongalbraith\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 863.1977405560416\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 820.6213620478562\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 432.8237020849235\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 360.33756303006584\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 356.13172274599776\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 424.97579700591865\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 923.1977405560416\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 880.6213620478562\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 552.8237020849235\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 480.33756303006584\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 476.13172274599776\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 544.9757970059186\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1496933178035911\n        gas: 0.6708066234639555\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.00032186813284632737\n        solar: 0.045471096710197646\n        unknown: 0.13370757381207277\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.14969362330281363\n        gas: 0.6708079924689648\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0003218687897257779\n        solar: 0.04546914867509421\n        unknown: 0.13370784668704438\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.12860177541170126\n        gas: 0.690594316989988\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 8.071430256003983e-05\n        solar: 0.05434412834794771\n        unknown: 0.1263801949480387\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.22179826190869956\n        gas: 0.6528260669867012\n        geothermal: 0.0\n        hydro: 0.0001178700353745059\n        hydro discharge: 3.898584239615773e-06\n        nuclear: 0.0031260524750977513\n        oil: 1.8553180413410424e-05\n        solar: 0.0075095178883211565\n        unknown: 0.1145992701670482\n        wind: 7.47815803806995e-08\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1659544413640187\n        gas: 0.6834142219188898\n        geothermal: 0.0\n        hydro: 0.00022179720752188854\n        hydro discharge: 3.2353404205045006e-07\n        nuclear: 0.0034230175515630318\n        oil: 5.469767706326956e-05\n        solar: 0.031129327314462597\n        unknown: 0.11580165076481842\n        wind: 7.287639110749019e-08\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.14933735002249873\n        gas: 0.6777501378557382\n        geothermal: 0.0\n        hydro: 0.0005047113826275872\n        hydro discharge: 7.730534342671894e-07\n        nuclear: 0.004484409239006881\n        oil: 0.00011783615029051071\n        solar: 0.04714047921649253\n        unknown: 0.12066368802614207\n        wind: 1.3693304315514787e-07\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.15971269211401995\n        gas: 0.6530134186118253\n        geothermal: 0.0\n        hydro: 0.00044777257996568993\n        hydro discharge: 7.37178033330974e-07\n        nuclear: 0.003211686978881818\n        oil: 0.0001242839961097661\n        solar: 0.05129503156950936\n        unknown: 0.13219336042745947\n        wind: 4.807483378536781e-07\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.12377711888360475\n        gas: 0.6963612831428487\n        geothermal: 0.0\n        hydro: 0.0004762186102167022\n        hydro discharge: 3.8801779419860667e-07\n        nuclear: 0.003804470758149816\n        oil: 0.000314741467484199\n        solar: 0.06003118293060601\n        unknown: 0.11523354029418328\n        wind: 6.710319344503199e-07\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.06905445331440273\n        gas: 0.7306318155755793\n        geothermal: 0.0\n        hydro: 0.0005652121146318724\n        hydro discharge: 2.8361326003576523e-07\n        nuclear: 0.005279756657343621\n        oil: 6.158821591525006e-05\n        solar: 0.07000116799359506\n        unknown: 0.12440514683670134\n        wind: 2.1552729529207986e-07\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.03344034757631596\n        gas: 0.8389737605051648\n        geothermal: 0.0\n        hydro: 0.000490577990877835\n        hydro discharge: 4.050132839958816e-07\n        nuclear: 0.005345087371884707\n        oil: 0.00014898929845189675\n        solar: 0.07957197028145203\n        unknown: 0.042028149676762994\n        wind: 3.5736466234930727e-07\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Tampa Electric Company\n"
  },
  {
    "path": "config/zones/US-HI.yaml",
    "content": "bounding_box:\n  - - -160.2358023580235\n    - 18.906224118294816\n  - - -154.8177481774817\n    - 22.229198456424058\ncenter_point:\n  - -155.5295148503916\n  - 19.635250025637994\ncentroid:\n  - -156.98166369418792\n  - 20.733483249805797\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1088.282255881974\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1095.1521821569359\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1071.2929245810315\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 104.44504310244231\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 40.29924039587993\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 40.29925747315513\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 753.165664537952\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 753.3092286793209\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 754.2186987590492\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 751.6602067865819\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1148.282255881974\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1155.1521821569359\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1131.2929245810315\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 38.0\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 142.4450431024423\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 78.29924039587993\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 78.29925747315514\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 997.165664537952\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 997.3092286793209\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 998.2186987590492\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 995.6602067865819\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: Pacific/Honolulu\nzone_name: Hawaii\n"
  },
  {
    "path": "config/zones/US-MIDA-PJM.yaml",
    "content": "bounding_box:\n  - - -90.29070290702902\n    - 35.309295549663204\n  - - -73.95373953739532\n    - 42.507642199443595\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 296.3\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 298.3\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 278.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 263.3\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 264.3\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 262.3\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 302.1\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 321.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 301.9\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 299.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 252.9\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 248.9\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 249.7\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 247.7\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 257.7\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 263.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 265.1\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 277.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 317.1\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 324.1\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 336.1\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 356.1\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 376.1\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 402.1\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 404.6\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 404.8\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 429.8\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 418.8\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 419.9\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 413.9\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 397.9\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2582.0\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 2580.4\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 2585.2\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 2579.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 2468.2\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 2448.2\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 2413.0\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 2410.8\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 2407.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2419.2\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 2402.5\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 2397.0\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 2387.2\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 2388.6\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 2383.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 2375.4\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 2297.2\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 2284.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2225.5\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 2224.7\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 2224.9\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 2222.5\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 2219.0\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 2215.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2216.1\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 2214.5\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 2198.3\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 2196.9\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 2197.9\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 2193.1\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 2167.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2144.9\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 2117.7\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 2113.7\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 2102.7\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 2096.1\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 2085.3\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 2025.3\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2025.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 2016.0\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 2008.5\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 2011.7\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2002.6\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 63668.4\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 63428.3\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 62775.5\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 62165.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 60622.1\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 57731.1\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 57672.1\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 58034.5\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 56189.9\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 55675.1\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 55397.1\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 54444.3\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 54329.5\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 54231.5\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 53317.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 52269.9\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 52221.9\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 51460.3\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 50482.8\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 49894.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 53128.2\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 52869.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 51233.0\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 49916.0\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 48248.1\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 45431.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 44179.0\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 43126.1\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 41432.1\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 40740.1\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 40080.1\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 39420.1\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 39191.1\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 38745.6\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 79145.8\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 79897.9\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 80751.9\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 80714.3\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 80054.6\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 81114.6\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 81957.9\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 82365.2\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 83107.2\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 85273.8\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 85365.5\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 86977.8\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 87808.4\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 88337.4\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 88858.9\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 90353.9\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 90381.9\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 93846.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 92903.5\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 93796.0\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 94321.0\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 94230.3\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 94231.8\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 95450.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 97270.8\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 97198.8\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 98233.8\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 98040.3\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 98057.6\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 98109.5\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 98111.5\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 98120.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 95496.7\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 95407.2\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 95293.6\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 95299.2\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 96133.1\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 96738.3\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 96686.1\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 97977.8\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 97989.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 99361.2\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 99427.0\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 100423.4\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 100307.5\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 101481.9\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 101483.0\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 101481.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 103273.9\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 104643.9\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 104609.5\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 105674.5\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 104792.5\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 105661.3\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 104341.3\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 104332.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 104339.0\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 104336.0\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 104337.0\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 104182.0\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 104184.0\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 104186.5\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 104189.7\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 104177.2\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 104938.7\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 104819.8\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 104806.8\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 104760.4\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 104742.5\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 104358.5\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 104356.5\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 104359.1\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 104352.8\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 104359.3\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3299.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 3288.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 3281.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 3270.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 3297.1\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 3299.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 3287.8\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 3290.3\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 3287.5\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 3291.6\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 3290.7\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 5103.3\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 5046.1\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 35947.9\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 35975.7\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 35425.7\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 35447.4\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 34466.6\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6603.8\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 6605.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 6936.0\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 6937.0\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 6851.1\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 6860.1\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 6852.9\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 6849.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 6818.4\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 6790.2\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 6788.4\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 6718.4\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 6662.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 6009.4\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 5977.4\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 5975.6\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 5981.0\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 5979.2\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 5097.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 5882.4\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 5883.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 6229.6\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 6231.1\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 6079.0\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 6081.5\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 5937.5\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 5901.5\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 5855.5\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 5863.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 5325.6\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 5323.9\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 5334.7\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 5345.5\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 5336.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 5322.0\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 5197.4\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 5195.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 5386.1\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 5395.1\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 5246.3\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 5376.3\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1705.3\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 1706.7\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 1721.2\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 1724.9\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 1764.8\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 1775.9\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 1781.2\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 1783.7\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 1808.7\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 2200.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 2266.5\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 2285.8\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 2448.1\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 2448.8\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 2458.2\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 2473.1\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 2475.8\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 2496.6\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 2524.6\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 2564.9\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 2576.8\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 2762.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2742.1\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 2743.6\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 2749.9\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 2773.3\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 2776.9\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 2830.3\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 2858.1\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 2873.7\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 2892.7\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 2978.8\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 2988.0\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 3315.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 3396.3\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 3416.3\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 3515.6\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 3519.8\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 3550.1\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 3570.5\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 3599.3\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 3642.1\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 3792.4\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 3904.5\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 4032.6\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 4556.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 4682.0\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 4835.0\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 4941.0\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 4954.3\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 5034.8\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 5174.5\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 5537.3\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 5834.9\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 5843.9\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 5987.7\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 6103.2\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 6453.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 6618.0\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 6620.0\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 6636.7\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 6649.1\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 6832.2\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 6870.5\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 6893.6\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 6897.6\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 6962.5\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 7070.4\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 7159.7\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 7411.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 7578.2\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 7728.8\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 7815.2\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 7851.3\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 7912.2\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 8234.2\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 8407.5\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 8600.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 8811.4\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 8898.7\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 9166.1\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 10991.0\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 11311.1\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 11426.6\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 11564.4\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 11711.6\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 12028.1\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 12435.2\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 12457.2\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 12531.8\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 12778.1\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 13274.1\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 13638.7\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 14659.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 15061.5\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 15287.6\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 15637.1\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 15855.9\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 15974.3\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 16051.2\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 16282.4\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 16309.7\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 16662.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 17565.4\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 211.2\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 11.2\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 17.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 113.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 107.2\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 11.2\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 7700.7\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 7800.7\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 7805.2\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 8268.9\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 8220.0\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 8332.5\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 8544.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 8726.0\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 8920.3\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 9215.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 9414.7\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 9629.7\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 9685.9\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 9694.9\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 9824.9\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 10153.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 10207.4\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 10457.2\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 10657.2\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 10772.2\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 10677.2\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 10676.2\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 10876.7\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 10964.7\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 11052.3\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 11160.6\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 11270.6\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 11459.6\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 11514.5\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 11718.5\ncenter_point:\n  - -82.09830495576169\n  - 39.25470269209093\ncentroid:\n  - -81.88014706507636\n  - 39.11895636126822\ncomment: Pjm Interconnection, Llc\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\n  - amv213\n  - VIKTORVAV99\n  - alejandranavcas\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 354.0\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 373.88\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 367.39\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 331.11\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 339.25\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 363.05\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 975.3515271166856\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 980.7263309760772\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1005.4635485098644\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1013.0108447809346\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 398.9853568004252\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 395.0916408590434\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 397.3283226131341\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 395.91087384158783\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 751.521332687618\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 970.0182040427067\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 925.272532343084\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 860.2336465682306\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 387.0\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 406.88\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 400.39\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 364.11\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 372.25\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 396.05\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1035.3515271166857\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1040.7263309760772\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1065.4635485098643\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1073.0108447809346\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 518.9853568004253\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 515.0916408590434\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 517.3283226131341\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 515.9108738415878\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 995.521332687618\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1214.0182040427067\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1169.272532343084\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1104.2336465682306\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.82\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.21777273875378175\n        gas: 0.37256625190030346\n        geothermal: 0.0\n        hydro: 0.02037657614148855\n        hydro discharge: 0.0\n        nuclear: 0.33616141851469195\n        oil: 0.0025677690061619105\n        solar: 0.005386081041623614\n        unknown: 0.01268696953089594\n        wind: 0.03248219333004439\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.21777278879166653\n        gas: 0.37256633750526613\n        geothermal: 0.0\n        hydro: 0.02037658082343715\n        hydro discharge: 0.0\n        nuclear: 0.33616149575487553\n        oil: 0.0025677695961610555\n        solar: 0.005385852512941777\n        unknown: 0.01268697244599506\n        wind: 0.032482200793514125\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 8.866512267503351e-08\n        biomass: 0.0\n        coal: 0.3164468002752186\n        gas: 0.26665277616025024\n        geothermal: 0.0\n        hydro: 0.018693833597624863\n        hydro discharge: 1.3875471005166232e-05\n        nuclear: 0.36100969577061426\n        oil: 0.0028890431784295172\n        solar: 0.0018159235058685698\n        unknown: 0.007086591277957432\n        wind: 0.02539136857437606\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 4.126898324126378e-09\n        biomass: 1.4633049957444689e-05\n        coal: 0.2895445695447844\n        gas: 0.3022177112241692\n        geothermal: 0.0\n        hydro: 0.02487265599331674\n        hydro discharge: 0.00011882545329470489\n        nuclear: 0.3415451354856891\n        oil: 0.0042607219163865555\n        solar: 0.002111894703578728\n        unknown: 0.008157160041563482\n        wind: 0.027156668922445604\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 5.75600463724557e-09\n        biomass: 1.9311672955772727e-05\n        coal: 0.24317746947071936\n        gas: 0.3581149472934172\n        geothermal: 0.0\n        hydro: 0.02311340163788409\n        hydro discharge: 0.00011883685358665792\n        nuclear: 0.33033934908933826\n        oil: 0.002031758920545236\n        solar: 0.0029589869228709275\n        unknown: 0.008281959321394639\n        wind: 0.031843909063295914\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 1.3159414321249752e-11\n        biomass: 4.852928813390484e-07\n        coal: 0.19404927502640595\n        gas: 0.39354881230385463\n        geothermal: 0.0\n        hydro: 0.021213482773334843\n        hydro discharge: 8.788004269170983e-05\n        nuclear: 0.34419807077308023\n        oil: 0.002530113730872292\n        solar: 0.004333264620916305\n        unknown: 0.00815366637421564\n        wind: 0.03188493717879585\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 1.2684291567664575e-11\n        biomass: 4.031067860203802e-08\n        coal: 0.2216289509712141\n        gas: 0.3752506338512749\n        geothermal: 0.0\n        hydro: 0.020717116046588872\n        hydro discharge: 9.782313384498122e-05\n        nuclear: 0.3308037605513134\n        oil: 0.0027630380049358944\n        solar: 0.00720159705264619\n        unknown: 0.008151886609151799\n        wind: 0.03338514091090262\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 1.0840669307572825e-09\n        biomass: 2.4538540307359965e-07\n        coal: 0.2008646285799555\n        gas: 0.39570799960930086\n        geothermal: 0.0\n        hydro: 0.01997026443011684\n        hydro discharge: 6.455431664568108e-07\n        nuclear: 0.32643784395806474\n        oil: 0.0033183503943996443\n        solar: 0.008766424539086996\n        unknown: 0.006828184452692025\n        wind: 0.03810540205531532\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.4237702911574848e-09\n        biomass: 2.1810144902598286e-08\n        coal: 0.1488913113682687\n        gas: 0.4370302630891044\n        geothermal: 0.0\n        hydro: 0.019730922592110546\n        hydro discharge: 5.747622068294778e-07\n        nuclear: 0.3367832585512994\n        oil: 0.003262155494028706\n        solar: 0.011975466320321143\n        unknown: 0.006798364354172945\n        wind: 0.035527649625593544\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.805183146760994e-09\n        coal: 0.1482026342312181\n        gas: 0.43732354037949756\n        geothermal: 0.0\n        hydro: 0.02000461781250978\n        hydro discharge: 4.523415505043214e-07\n        nuclear: 0.32685250488795764\n        oil: 0.004860564706316005\n        solar: 0.019468248300301277\n        unknown: 0.006730017008187237\n        wind: 0.03655739992719188\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.3997\n    - datetime: '2021-01-01'\n      value: 0.3905\n    - datetime: '2022-01-01'\n      value: 0.391\n    - datetime: '2023-01-01'\n      value: 0.4031\n    - datetime: '2024-01-01'\n      value: 0.3869\n    - datetime: '2025-01-01'\n      value: 0.3994\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.0571\n    - datetime: '2021-01-01'\n      value: 0.0611\n    - datetime: '2022-01-01'\n      value: 0.0665\n    - datetime: '2023-01-01'\n      value: 0.0738\n    - datetime: '2024-01-01'\n      value: 0.0837\n    - datetime: '2025-01-01'\n      value: 0.0871\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: US_PJM.fetch_consumption_forecast\n  gridAlerts: US_PJM.fetch_grid_alerts\n  production: US_PJM.fetch_production\n  productionCapacity: EIA.fetch_production_capacity\n  productionPerModeForecast: US_PJM.fetch_wind_solar_forecasts\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: America/New_York\nzone_name: PJM Interconnection\nzone_short_name: PJM\n"
  },
  {
    "path": "config/zones/US-MIDW-AECI.yaml",
    "content": "bounding_box:\n  - - -97.64197641976413\n    - 34.66817044049786\n  - - -89.08829088290878\n    - 41.279773128765356\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2481.7\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3044.6\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 27.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 30.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 31.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 54.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 44.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 97.5\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 2.5\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 4.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1.5\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 462.9\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 704.9\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 941.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 959.4\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 941.4\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 959.4\ncenter_point:\n  - -92.78449868725454\n  - 37.92824198196455\ncentroid:\n  - -93.37016403708525\n  - 37.63684336204722\ncomment: Associated Electric Cooperative, Inc.\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 950.6306844348549\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 933.8567719793567\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 937.267777658772\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 968.7795683618425\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 400.7407838539086\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 408.7406042020761\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 406.3004425342369\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 398.6815069287052\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 664.14088513536\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1010.6306844348549\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 993.8567719793567\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 997.267777658772\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1028.7795683618424\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 520.7407838539086\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 528.7406042020762\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 526.3004425342369\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 518.6815069287052\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 908.14088513536\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.66\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6072063967814186\n        gas: 0.3039511770625133\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.08884258146902137\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6072063967814186\n        gas: 0.3039511770625133\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.08884258146902135\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.7146764392264694e-05\n        coal: 0.5518869002255529\n        gas: 0.31295557983280137\n        geothermal: 0.0\n        hydro: 0.004547766570806829\n        hydro discharge: 1.0388960369899847e-08\n        nuclear: 0.008473584731200329\n        oil: 0.0007128081800163979\n        solar: 0.0001505821627438912\n        unknown: 0.0002455040158515921\n        wind: 0.12097984659914608\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.1198690586798957e-05\n        coal: 0.592976723802612\n        gas: 0.2787080089575679\n        geothermal: 0.0\n        hydro: 0.03748159306089074\n        hydro discharge: 1.6265160702954173e-07\n        nuclear: 0.005936927296958506\n        oil: 0.0003446401665405098\n        solar: 0.00011167321361283078\n        unknown: 0.019812612530910392\n        wind: 0.06459637935908911\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.2028684118077818e-05\n        coal: 0.5439895189750182\n        gas: 0.29696374150720695\n        geothermal: 0.0\n        hydro: 0.07532405087946316\n        hydro discharge: 5.364112460375718e-08\n        nuclear: 0.003794318922585106\n        oil: 5.8031583037711776e-06\n        solar: 5.049027199047766e-05\n        unknown: 0.022114588576067726\n        wind: 0.057745276915882354\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.4414172790665492e-05\n        coal: 0.49788067928327595\n        gas: 0.2961482436507086\n        geothermal: 0.0\n        hydro: 0.08080626672190104\n        hydro discharge: 7.875842111464082e-08\n        nuclear: 0.005918928397999666\n        oil: 6.604192984577981e-06\n        solar: 8.191889062159206e-05\n        unknown: 0.025985433712918445\n        wind: 0.09315716047879675\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.8034394256866286e-05\n        coal: 0.5415561443243294\n        gas: 0.22185382215546148\n        geothermal: 0.0\n        hydro: 0.07097588362764246\n        hydro discharge: 2.5089619534975713e-07\n        nuclear: 0.010041940945294998\n        oil: 2.4196724251525103e-05\n        solar: 0.0002301104439408936\n        unknown: 0.01863873977289267\n        wind: 0.13665073433865474\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.4931680625996175e-05\n        coal: 0.5316546462657766\n        gas: 0.25251021764891096\n        geothermal: 0.0\n        hydro: 0.0438196990551593\n        hydro discharge: 1.0556013813768573e-08\n        nuclear: 0.008960892130366816\n        oil: 5.0070015522423435e-05\n        solar: 0.0003428325326361375\n        unknown: 0.015002847500966284\n        wind: 0.14763361469771033\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.733841187526457e-05\n        coal: 0.417644829350899\n        gas: 0.37789064697380637\n        geothermal: 0.0\n        hydro: 0.05674630001100094\n        hydro discharge: 6.372115035228843e-08\n        nuclear: 0.012557357322339953\n        oil: 4.113069321369631e-05\n        solar: 0.0009078849839398763\n        unknown: 0.00042114093871050947\n        wind: 0.1337530335048283\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.8824678321963574e-05\n        coal: 0.42798888725627293\n        gas: 0.36449804469255875\n        geothermal: 0.0\n        hydro: 0.04802895557669535\n        hydro discharge: 2.028915336848578e-08\n        nuclear: 0.008150049617885407\n        oil: 5.6665760889692724e-05\n        solar: 0.0007432069047526604\n        unknown: 0.000170699564045901\n        wind: 0.15032435976680825\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Central\nzone_name: Associated Electric Cooperative\n"
  },
  {
    "path": "config/zones/US-MIDW-LGEE.yaml",
    "content": "bounding_box:\n  - - -89.10989109891094\n    - 36.58295927099611\n  - - -82.85302853028524\n    - 38.55212924914677\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1.0\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 2.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6545.6\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 6252.5\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 5807.2\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 5451.7\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4027.9\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 4011.6\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 3993.6\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 3977.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 3353.6\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 133.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 137.8\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 11.5\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 10.6\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 10.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 13.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 14.7\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 15.1\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 18.1\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 118.1\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -86.03546035460349\n  - 37.601890248062446\ncentroid:\n  - -85.61785617856174\n  - 37.59044158539877\ncomment: Louisville Gas And Electric Company And Kentucky Utilities\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 939.819058816272\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 942.2325199132126\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 929.2484998403622\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 972.8814209119845\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 378.18772707880396\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 388.35360393082044\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 402.09632811290464\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 377.4280726544936\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 0.0\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 771.69\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 999.819058816272\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1002.2325199132126\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 989.2484998403622\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1032.8814209119846\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 498.18772707880396\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 508.35360393082044\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 522.0963281129046\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 497.4280726544936\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 795.69\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8406943433165429\n        gas: 0.14860789399267818\n        geothermal: 0.0\n        hydro: 0.010154007445139123\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0005438115226080128\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.840694421174867\n        gas: 0.14860790775554178\n        geothermal: 0.0\n        hydro: 0.010154008385521331\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.000543719093624043\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 1.6783883345087826e-08\n        biomass: 0.0\n        coal: 0.7803036414665482\n        gas: 0.17056329011613655\n        geothermal: 0.0\n        hydro: 0.014284785019394374\n        hydro discharge: 2.1568712461433197e-05\n        nuclear: 0.0317355631679323\n        oil: 0.00022788018915563969\n        solar: 0.0009018959107056487\n        unknown: 0.00041627785734125517\n        wind: 0.0015451530324812912\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.6190454874421222e-06\n        coal: 0.7870225802008569\n        gas: 0.1371004608232321\n        geothermal: 0.0\n        hydro: 0.01478031308237552\n        hydro discharge: 9.735546601781274e-05\n        nuclear: 0.05221560781081194\n        oil: 0.0011383019146231018\n        solar: 0.0006106998895902513\n        unknown: 0.00142604746781593\n        wind: 0.005606838643030196\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.0485655176001016e-06\n        coal: 0.7741891504391143\n        gas: 0.15527583232060296\n        geothermal: 0.0\n        hydro: 0.01828150114654868\n        hydro discharge: 8.030235674803358e-05\n        nuclear: 0.04683436759856865\n        oil: 0.00010823180422270734\n        solar: 0.0007481245210164584\n        unknown: 0.0006844177145531505\n        wind: 0.0037957995161812604\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.1327124096611566e-07\n        coal: 0.7881452724080703\n        gas: 0.13887073816417583\n        geothermal: 0.0\n        hydro: 0.02297440975852274\n        hydro discharge: 0.0001423525050087293\n        nuclear: 0.04528739205357429\n        oil: 6.729413437829945e-05\n        solar: 0.000831462562777105\n        unknown: 0.0005194320104608029\n        wind: 0.0031608201595883555\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.556816730428342e-07\n        coal: 0.7623824647664494\n        gas: 0.1811530265307589\n        geothermal: 0.0\n        hydro: 0.016891741958198505\n        hydro discharge: 5.048827448684023e-05\n        nuclear: 0.03301753548194671\n        oil: 7.10690444882111e-05\n        solar: 0.0009631445674659829\n        unknown: 0.0006195541136929027\n        wind: 0.0048496744574700185\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.2499520244513203e-06\n        coal: 0.7098876446161009\n        gas: 0.22499803580851177\n        geothermal: 0.0\n        hydro: 0.016582353211128293\n        hydro discharge: 6.800760515002742e-08\n        nuclear: 0.035370311584812374\n        oil: 6.688645120226839e-05\n        solar: 0.0014783074058599584\n        unknown: 0.0009961382042413152\n        wind: 0.010618630022730027\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.4635255377875745e-06\n        coal: 0.7269560473281036\n        gas: 0.19772418261338265\n        geothermal: 0.0\n        hydro: 0.01745629484513019\n        hydro discharge: 9.604025938475985e-07\n        nuclear: 0.042440260972840746\n        oil: 5.547182739216713e-05\n        solar: 0.0021658886273990285\n        unknown: 0.0006765723443631017\n        wind: 0.012522524212326759\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.280725178889682e-07\n        coal: 0.7091453510030656\n        gas: 0.21848069352646377\n        geothermal: 0.0\n        hydro: 0.016551623316721584\n        hydro discharge: 2.0392830664429815e-07\n        nuclear: 0.038716185356420935\n        oil: 8.951525714836305e-05\n        solar: 0.0031590859818130075\n        unknown: 0.0005828551896878398\n        wind: 0.013273336745387228\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.0775\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 1.0\n    - datetime: '2022-01-01'\n      value: 1.0\n    - datetime: '2025-01-01'\n      value: 0.0563\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Central\nzone_name: Louisville Gas and Electric Company and Kentucky Utilities\nzone_short_name: Louisville Gas And Electric Company\n"
  },
  {
    "path": "config/zones/US-MIDW-MISO.yaml",
    "content": "bounding_box:\n  - - -104.60804608046074\n    - 29.07836089496263\n  - - -82.41984203397388\n    - 49.38133293345275\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 21.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 21.9\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 23.0\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 36.1\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 40.1\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 45.1\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 45.4\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 55.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 54.3\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 56.8\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 57.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 67.1\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 67.4\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 73.4\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 78.4\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 82.0\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 81.5\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 126.5\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 135.5\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 198.0\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 212.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 412.0\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 616.9\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 791.9\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2831.1\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 2827.1\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 2826.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 2850.3\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 2849.6\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 2848.9\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 2845.3\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 2782.8\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2758.5\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 2574.4\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 2568.0\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 2546.6\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 2545.8\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 2546.6\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 2478.3\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 2478.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 2341.1\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 2297.1\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 2295.1\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 2340.7\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 2342.3\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2260.3\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 2240.9\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 2232.9\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 2231.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2311.7\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 2310.3\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 2288.3\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 2285.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2240.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 2245.6\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 2244.6\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 2240.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2171.1\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2186.4\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 2202.1\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 2163.8\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 2150.5\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 68230.8\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 68040.6\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 67989.3\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 67820.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 67343.8\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 66110.6\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 65507.1\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 65156.1\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 64924.9\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 64524.9\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 64374.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 64100.5\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 63695.5\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 63076.8\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 61277.1\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 60814.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 60747.8\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 60667.8\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 60494.8\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 60154.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 60195.8\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 60145.8\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 59426.1\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 58651.1\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 57554.7\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 56834.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 56028.7\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 55988.7\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 55834.0\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 52796.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 52669.6\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 52125.6\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 51327.8\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 50797.4\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 50032.1\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 49865.5\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 49267.1\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 48025.1\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 46306.2\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 46599.2\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 46306.2\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 46291.6\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 76560.5\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 76607.0\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 77312.9\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 77358.6\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 77409.9\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 77414.2\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 77342.1\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 77323.8\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 78072.8\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 78137.1\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 79019.1\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 77879.1\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 77858.4\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 77790.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 77889.2\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 78082.2\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 79038.6\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 78891.4\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 78953.4\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 78973.0\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 78880.6\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 78662.7\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 78666.4\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 79562.7\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 79588.3\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 80561.5\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 80406.7\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 80388.7\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 80376.7\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 80776.3\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 80642.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 80456.1\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 80861.5\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 80866.5\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 80897.4\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 80928.3\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 80903.3\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 80860.1\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 80794.1\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 80792.3\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 81181.6\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 81209.8\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 81504.8\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 81506.3\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 82773.7\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 82769.2\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 82776.0\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 82455.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 82262.8\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 82820.8\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 82744.5\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 82876.1\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 82869.9\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 82831.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 82840.1\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 82394.6\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 82318.1\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 82247.1\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 81898.6\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 81987.0\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 81991.7\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 81915.2\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 81911.8\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 81755.1\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 83455.8\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 83136.6\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 83097.3\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 83449.7\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 83698.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 83743.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 84548.2\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2294.5\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 2370.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 2370.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2373.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 2385.1\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 2379.1\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 2405.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2400.2\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 2399.8\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 2427.4\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 2455.0\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 2454.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2456.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2448.6\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 2446.3\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2447.9\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2449.4\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2414.8\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2085.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 2087.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2416.8\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 13760.3\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 13080.8\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 12269.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4371.8\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 4355.8\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 4349.8\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 4335.9\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 4333.7\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 4154.5\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 4118.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 4067.1\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 4069.9\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 4059.9\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 4059.4\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 4057.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 4062.1\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 4061.0\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 4053.5\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 4061.8\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 4057.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 4183.1\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 4182.9\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 4160.3\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 4150.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 4179.5\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 4185.3\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 4189.3\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 4192.4\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 4130.4\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 3975.6\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 3977.4\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 3953.4\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 3939.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 3890.1\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 3889.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 3864.0\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 3879.2\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 3652.4\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 3648.3\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 515.2\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 532.0\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 536.0\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 539.0\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 592.8\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 604.3\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 635.3\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 654.4\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 674.2\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 706.2\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 830.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 963.9\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 984.9\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 1025.6\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 1042.6\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 1049.3\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 1071.6\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 1110.4\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 1113.4\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 1125.0\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 1146.8\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 1159.6\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 1196.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1218.9\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 1221.4\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 1242.4\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 1253.0\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 1266.0\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 1289.3\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 1301.6\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 1316.6\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 1347.1\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 1357.6\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 1365.6\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 1404.6\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1446.2\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 1457.9\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 1467.3\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 1475.3\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 1482.3\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 1499.1\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 1527.9\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 1536.1\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 1700.9\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 1730.0\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 1894.9\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 2056.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2089.2\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 2110.1\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 2215.4\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 2295.8\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 2327.2\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 2348.2\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 2457.8\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 2485.1\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 2719.3\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 2721.3\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 3084.3\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 3212.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 3472.9\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 3476.9\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 3499.6\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 3500.5\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 3526.4\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 3536.1\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 3715.6\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 3870.1\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 4024.1\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 4128.0\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 4138.7\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 4548.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 4624.2\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 4671.2\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 4672.2\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 4675.2\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 5172.3\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 5213.7\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 5273.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 5276.0\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 5800.3\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 6015.0\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 7348.2\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 7359.3\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 7380.1\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 7631.4\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 7670.3\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 8376.7\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 8380.7\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 8861.0\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 9141.8\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 9586.9\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 10222.5\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 11903.4\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 13095.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 14043.3\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 14498.5\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 15272.5\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 15442.5\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 16263.0\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 16807.3\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 17064.3\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 17475.6\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 19325.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 20251.8\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 471.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 461.7\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 456.7\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 514.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 483.7\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 487.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 458.8\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 489.8\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 495.5\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 491.7\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 495.7\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 16584.3\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 16738.1\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 16759.1\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 16857.1\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 16957.1\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 17327.1\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 17553.7\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 17672.7\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 17881.5\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 18081.9\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 19130.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 19157.4\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 19323.4\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 19955.5\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 19954.1\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 19952.1\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 20152.1\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 21734.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 22333.3\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 22393.3\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 22743.1\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 22943.1\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 23124.2\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 23326.2\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 23370.2\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 23631.1\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 23783.3\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 23985.3\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 26098.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 26424.9\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 26874.9\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 27129.0\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 27347.0\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 27730.5\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 27823.5\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 28310.5\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 29016.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 29099.1\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 29420.4\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 29428.3\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 29843.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 29930.0\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 30414.2\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 30526.3\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 30842.9\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 30841.1\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 31214.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 31514.7\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 31899.2\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 31937.9\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 32139.5\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 32433.5\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 32487.9\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 32482.1\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 32485.5\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 32629.5\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 32649.4\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 33233.2\ncenter_point:\n  - -90.25369586198931\n  - 39.13738646949346\ncentroid:\n  - -90.41123549138727\n  - 40.21390243479164\ncomment: Midcontinent Independent Transmission System Operator, Inc..\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\n  - alejandranavcas\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 428.67\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1014.3422552181058\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1003.8346495294973\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1000.9775053066439\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1011.0567303043377\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 409.30430271803226\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 409.4254165197668\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 411.3519924413645\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 408.8041544467952\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 922.7890877685242\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 624.8638460041672\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 501.6935207852357\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 419.98313946829467\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 461.67\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1074.342255218106\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1063.8346495294973\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1060.977505306644\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1071.0567303043376\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 529.3043027180322\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 529.4254165197668\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 531.3519924413645\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 528.8041544467952\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1166.789087768524\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 868.8638460041672\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 745.6935207852357\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 663.9831394682947\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.45\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3645360263350062\n        gas: 0.3003757973698458\n        geothermal: 0.0\n        hydro: 0.016948056758411878\n        hydro discharge: 0.0\n        nuclear: 0.15206559969645714\n        oil: 0.03924092846577229\n        solar: 0.0026028591830364245\n        unknown: 0.01126095447154677\n        wind: 0.11296972871934247\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3645360852974365\n        gas: 0.30037584595458294\n        geothermal: 0.0\n        hydro: 0.01694805949970092\n        hydro discharge: 0.0\n        nuclear: 0.15206562429253728\n        oil: 0.039240934812855545\n        solar: 0.0026026978505841476\n        unknown: 0.011260956292966863\n        wind: 0.11296974699180189\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.3802119720680984e-06\n        coal: 0.33092535601441087\n        gas: 0.3240785329734592\n        geothermal: 0.0\n        hydro: 0.032440595980642105\n        hydro discharge: 1.9065354266536477e-05\n        nuclear: 0.14686463327657218\n        oil: 0.024660369373326392\n        solar: 0.00675029134987411\n        unknown: 0.00958536751281621\n        wind: 0.1246718156057116\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.6799365965328262e-05\n        coal: 0.46637267342619076\n        gas: 0.2574837818486663\n        geothermal: 0.0\n        hydro: 0.027103193372942258\n        hydro discharge: 2.512746287586688e-05\n        nuclear: 0.15106235094332446\n        oil: 0.012267461173729833\n        solar: 0.0009035164381989341\n        unknown: 0.014828688533678674\n        wind: 0.06993553196119111\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.029406663670682e-05\n        coal: 0.37902286504744626\n        gas: 0.30551504590133866\n        geothermal: 0.0\n        hydro: 0.037501488137603345\n        hydro discharge: 4.932813111819062e-06\n        nuclear: 0.1731675323645628\n        oil: 4.300753591791705e-05\n        solar: 0.0010315790412722672\n        unknown: 0.011607229214715822\n        wind: 0.09206477810427008\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.9368267215475583e-05\n        coal: 0.3125001965174925\n        gas: 0.3352914036366789\n        geothermal: 0.0\n        hydro: 0.043365289962889436\n        hydro discharge: 1.1430972749997212e-05\n        nuclear: 0.1805900424420238\n        oil: 0.00016439548122173232\n        solar: 0.0015364551511778612\n        unknown: 0.011903152259306968\n        wind: 0.11459659932651513\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.966116923046127e-05\n        coal: 0.37036654538909486\n        gas: 0.29176151941105455\n        geothermal: 0.0\n        hydro: 0.029761891321926248\n        hydro discharge: 1.0084555893113064e-05\n        nuclear: 0.16763001080336526\n        oil: 0.00018244961265727352\n        solar: 0.003300402706991867\n        unknown: 0.012838271031974076\n        wind: 0.12410846638087543\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.132498369561453e-05\n        coal: 0.32313639836116265\n        gas: 0.3197993284934307\n        geothermal: 0.0\n        hydro: 0.03635450572146323\n        hydro discharge: 1.4921572107377743e-06\n        nuclear: 0.15331689325713854\n        oil: 0.00011449350622099461\n        solar: 0.007127890591949021\n        unknown: 0.011948836521069407\n        wind: 0.1481673991735708\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 7.64862250087676e-11\n        biomass: 2.6146448885367153e-05\n        coal: 0.2703868418748441\n        gas: 0.3859805988161669\n        geothermal: 0.0\n        hydro: 0.03061687778162027\n        hydro discharge: 1.7423562056997255e-06\n        nuclear: 0.15490684002009472\n        oil: 0.00014664061436640935\n        solar: 0.010328028153750439\n        unknown: 0.0070794395341052686\n        wind: 0.14052589705687518\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.5705337554851478e-05\n        coal: 0.2535535788797896\n        gas: 0.39260578356747894\n        geothermal: 0.0\n        hydro: 0.02800560794381062\n        hydro discharge: 1.8529310539884868e-06\n        nuclear: 0.15186591992240156\n        oil: 0.00022350411075090041\n        solar: 0.022179358971239873\n        unknown: 0.004320188500399502\n        wind: 0.14722782107459684\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.3682\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.2165\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: US_MISO.fetch_consumption_forecast\n  gridAlerts: US_MISO.fetch_grid_alerts\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\n  productionPerModeForecast: US_MISO.fetch_wind_solar_forecasts\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Central\nzone_name: Midcontinent ISO\nzone_short_name: MISO\n"
  },
  {
    "path": "config/zones/US-NE-ISNE.yaml",
    "content": "bounding_box:\n  - - -73.72693726937264\n    - 40.99355656217368\n  - - -66.980469804698\n    - 47.43486039331913\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 19.5\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 22.0\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 22.8\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 23.3\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 24.3\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 27.3\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 36.4\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 41.4\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 42.9\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 48.9\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 56.8\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 60.1\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 61.7\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 73.1\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 75.4\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 79.7\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 83.6\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 86.2\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 89.0\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 91.9\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 94.1\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 126.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 128.6\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 140.6\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 151.6\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 155.3\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 183.3\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 189.8\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 194.8\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 203.5\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 208.5\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 225.2\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 243.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 238.5\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 244.5\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 246.5\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 247.5\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 251.3\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 255.3\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 259.3\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 264.8\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 270.4\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 275.4\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 305.4\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 314.9\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 321.6\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 322.4\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 331.4\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 351.2\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 353.2\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 357.2\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 371.2\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 376.5\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 377.5\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 389.0\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 393.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 389.9\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 403.0\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 571.4\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 575.7\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 580.7\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 760.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 763.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1539.8\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 1538.8\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1542.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1540.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1566.1\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 1565.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1386.8\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 1370.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1380.7\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 1371.3\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 1281.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1247.5\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 1245.9\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2083.8\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 959.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 859.2\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 459.2\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 16494.3\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 16496.3\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 16510.1\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 16288.2\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 16283.4\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 18023.1\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 18025.1\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 18026.5\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 17954.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 18542.2\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 18545.9\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 18645.9\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 18648.4\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 18748.4\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 19654.7\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 19656.7\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 19890.0\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 19871.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 20033.5\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 19894.2\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 19916.4\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 19915.9\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 19802.3\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 19804.2\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 18942.5\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 18822.5\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 18824.3\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 18828.9\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 18843.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 18100.4\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 18022.4\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 18018.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 18049.8\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 16305.4\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 16370.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 16286.1\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 16699.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1902.5\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1913.7\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1905.8\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 1904.6\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 1903.1\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 1902.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1908.2\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 1903.3\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1894.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1901.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1896.3\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 1900.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 1895.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1896.1\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 1897.3\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 1891.8\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1564.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1799.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1499.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1532.0\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 1865.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4074.9\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 3404.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 3501.9\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6474.8\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 5999.3\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 6003.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 6606.1\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 6070.0\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 6086.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 5766.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 5724.6\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 5093.4\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 5089.4\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 5070.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 5944.8\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 5886.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 6141.9\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 6122.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 6121.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 6122.4\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 5708.4\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 5695.2\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 6011.7\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 616.5\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 619.0\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 623.5\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 658.9\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 674.0\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 691.7\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 716.8\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 732.1\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 766.8\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 795.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 818.3\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 821.1\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 857.7\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 859.6\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 865.8\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 869.5\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 877.4\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 881.4\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 904.2\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 909.2\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 976.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1044.6\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 1056.5\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 1058.5\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 1060.5\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 1064.5\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 1068.5\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 1071.8\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 1096.3\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 1115.2\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 1118.7\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 1212.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1319.3\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 1327.0\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 1333.0\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 1334.0\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 1353.2\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 1355.6\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 1365.1\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 1371.1\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 1374.4\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 1456.1\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 1525.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1608.7\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 1634.5\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 1652.0\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 1662.4\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 1730.0\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 1743.6\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 1753.8\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 1797.9\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 1881.7\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 1910.7\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 2073.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2119.9\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 2146.9\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 2169.0\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 2183.7\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 2194.0\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 2214.8\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 2232.0\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 2249.4\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 2264.2\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 2289.2\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 2313.8\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 2341.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2480.6\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 2484.6\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 2488.1\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 2496.1\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 2526.3\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 2532.8\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 2555.4\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 2568.7\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 2585.9\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 2605.2\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 2662.8\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 2765.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 2821.8\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 2830.0\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 2862.0\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 2869.0\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 2883.3\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 3000.7\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 3015.2\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 3027.1\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 3031.1\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 3065.3\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 3170.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 3214.3\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 3407.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 3414.5\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 3419.2\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 3479.8\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 3492.4\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 3496.9\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 3501.9\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 3552.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 3585.8\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 300.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1313.8\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 1315.3\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 1313.6\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 1336.4\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 1366.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1365.9\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 1367.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1389.4\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 1394.0\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 1427.8\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 1500.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1498.4\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 1513.7\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 1518.2\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 1538.2\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 1664.2\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 1723.0\ncenter_point:\n  - -70.39016096719396\n  - 44.260793161078574\ncentroid:\n  - -70.21819801989935\n  - 43.963232577319204\ncomment: Iso New England Inc.\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\n  - alejandranavcas\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 183.01\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 193.17\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 202.42\n      - _comment: used non-null storage values\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 204.25\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 214.88\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 223.55\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1042.1557244613366\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1049.543638320452\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1086.1257778671156\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1052.0466873316557\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 389.05687494636425\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 388.405126933921\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 392.1225766993324\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 387.8248564110828\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1257.197843003192\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 781.5574904153493\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 895.8408038663823\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 996.1835230339008\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 216.01\n      - _comment: used non-null storage values\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 226.17\n      - _comment: used non-null storage values\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 235.42\n      - _comment: used non-null storage values\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 237.25\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 247.88\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 256.55\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1102.1557244613366\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1109.543638320452\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1146.1257778671156\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1112.0466873316557\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 509.05687494636425\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 508.405126933921\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 512.1225766993324\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 507.8248564110828\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1501.197843003192\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1025.5574904153493\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1139.8408038663824\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1240.1835230339007\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 27.825\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.00048084385739457066\n        biomass: 0.054681157499140355\n        coal: 0.007996509728253222\n        gas: 0.4908440982677455\n        geothermal: 0.0\n        hydro: 0.06949196441962709\n        hydro discharge: 0.0\n        nuclear: 0.26945112839727786\n        oil: 0.01139241061681868\n        solar: 0.004028317739736292\n        unknown: 0.05769620577852697\n        wind: 0.03393717612619065\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0004808440431203622\n        biomass: 0.05468117861972057\n        coal: 0.007996512816902638\n        gas: 0.49084428785612705\n        geothermal: 0.0\n        hydro: 0.06949199126087692\n        hydro discharge: 0.0\n        nuclear: 0.2694512324726931\n        oil: 0.01139241501713377\n        solar: 0.004027933082009133\n        unknown: 0.05769622806366866\n        wind: 0.03393718923441447\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 4.281259740389673e-07\n        biomass: 0.06809071225859359\n        coal: 0.02290803043745342\n        gas: 0.4832964093548456\n        geothermal: 0.0\n        hydro: 0.07591460701060546\n        hydro discharge: 0.0\n        nuclear: 0.30908040199666564\n        oil: 0.0066334278501302595\n        solar: 0.0006934531258820894\n        unknown: 3.504056235091598e-05\n        wind: 0.03334748251451999\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0005639408411890185\n        biomass: 0.0502315961086351\n        coal: 0.005486909368998675\n        gas: 0.4693770769102801\n        geothermal: 0.0\n        hydro: 0.17712220663790101\n        hydro discharge: 3.844640747921848e-07\n        nuclear: 0.23543480768866287\n        oil: 0.001932459658294849\n        solar: 0.004497606088949904\n        unknown: 0.018029438709987636\n        wind: 0.03732354285764146\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.00017105711478900546\n        biomass: 0.05510495128492711\n        coal: 0.010450172986793235\n        gas: 0.4564873724330341\n        geothermal: 0.0\n        hydro: 0.1349196630889543\n        hydro discharge: 9.683183132629602e-09\n        nuclear: 0.28065114223236126\n        oil: 0.010134007031562201\n        solar: 0.0012448111532050905\n        unknown: 0.01592730793838658\n        wind: 0.0349095000826745\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.00030825244553047185\n        biomass: 0.047043073733948206\n        coal: 0.003939303469046331\n        gas: 0.4218371111094918\n        geothermal: 0.0\n        hydro: 0.19600629073572684\n        hydro discharge: 8.625828950711192e-08\n        nuclear: 0.26430173495155457\n        oil: 0.0013172457310757567\n        solar: 0.0018031246093816197\n        unknown: 0.025648042388984927\n        wind: 0.037795712739661536\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.00034935461878474926\n        biomass: 0.04984197735260639\n        coal: 0.0019028626175622329\n        gas: 0.45189156384126233\n        geothermal: 0.0\n        hydro: 0.1938137424678386\n        hydro discharge: 3.535378662357143e-07\n        nuclear: 0.2392589941088885\n        oil: 0.0014202559990196568\n        solar: 0.0031172653584616056\n        unknown: 0.018834874390878522\n        wind: 0.03956873006468709\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0006737601722159499\n        biomass: 0.044291575673722675\n        coal: 0.0035337158743902696\n        gas: 0.4624295147468916\n        geothermal: 0.0\n        hydro: 0.17580149240506612\n        hydro discharge: 1.6173863673621757e-09\n        nuclear: 0.2361540407377366\n        oil: 0.01576177456811505\n        solar: 0.007515449730428623\n        unknown: 0.014489576843192787\n        wind: 0.03934909022492687\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0006866042740239167\n        biomass: 0.044149660001809116\n        coal: 0.0018849114264039566\n        gas: 0.5056687681043909\n        geothermal: 0.0\n        hydro: 0.17310405817564165\n        hydro discharge: 4.4489681647655106e-10\n        nuclear: 0.21346803332946568\n        oil: 0.002837279618635759\n        solar: 0.007738089706121109\n        unknown: 0.015603163285270769\n        wind: 0.03485941944316769\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0008346185503266233\n        biomass: 0.0410511251429479\n        coal: 0.0026917046058330136\n        gas: 0.5347667341929427\n        geothermal: 0.0\n        hydro: 0.12462588169732432\n        hydro discharge: 2.611190462786013e-10\n        nuclear: 0.23961238276829877\n        oil: 0.002790275914287318\n        solar: 0.011149182093012062\n        unknown: 0.007120449441312479\n        wind: 0.035357632711841926\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.5393\n    - datetime: '2021-01-01'\n      value: 0.5179\n    - datetime: '2022-01-01'\n      value: 0.5136\n    - datetime: '2023-01-01'\n      value: 0.4846\n    - datetime: '2024-01-01'\n      value: 0.4568\n    - datetime: '2025-01-01'\n      value: 0.4474\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.2936\n    - datetime: '2021-01-01'\n      value: 0.2755\n    - datetime: '2022-01-01'\n      value: 0.2718\n    - datetime: '2023-01-01'\n      value: 0.2652\n    - datetime: '2024-01-01'\n      value: 0.2146\n    - datetime: '2025-01-01'\n      value: 0.197\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: US_NEISO.fetch_consumption_forecast\n  gridAlerts: US_NEISO.fetch_grid_alerts\n  production: US_NEISO.fetch_production\n  productionCapacity: EIA.fetch_production_capacity\n  productionPerModeForecast: US_NEISO.fetch_wind_solar_forecasts\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: ISO New England\n"
  },
  {
    "path": "config/zones/US-NW-AVA.yaml",
    "content": "bounding_box:\n  - - -119.36819368193676\n    - 45.07929805026971\n  - - -114.20214202142014\n    - 48.999551747062824\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1.2\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 179.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 173.7\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 561.5\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1176.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1235.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1251.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1170.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1170.4\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 1170.6\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 19.2\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 105.3\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 249.3\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 349.3\ncenter_point:\n  - -116.69400141761005\n  - 47.049674829537196\ncentroid:\n  - -116.3158833189545\n  - 46.901122204162334\ncomment: Avista Corporation\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 393.6395082943637\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 401.43265288031876\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 404.1241908939394\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 438.01507006284413\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 184.06\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 513.6395082943636\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 521.4326528803188\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 524.1241908939394\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 558.0150700628442\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 208.06\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.16668718021123885\n        geothermal: 0.0\n        hydro: 0.38381060937349126\n        hydro discharge: 0.3278042144278877\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0030824433312936325\n        unknown: 0.07591728504566805\n        wind: 0.04269757515255969\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.1666872895644636\n        geothermal: 0.0\n        hydro: 0.3838108611680671\n        hydro discharge: 0.32780442948010646\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0030817903778442577\n        unknown: 0.07591733485033765\n        wind: 0.04269760316381722\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.1812466160486\n        geothermal: 0.0\n        hydro: 0.3666711422009943\n        hydro discharge: 0.32772069227158745\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0029630093871566444\n        unknown: 0.0758524407772104\n        wind: 0.045542951220756925\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 2.4047109170048864e-08\n        biomass: 0.001219915313448663\n        coal: 0.05164768698841627\n        gas: 0.24313715753045778\n        geothermal: 3.0015164445888267e-06\n        hydro: 0.4686507079491347\n        hydro discharge: 0.059450092915461175\n        nuclear: 0.025209403237724422\n        oil: 0.0019726379246895326\n        solar: 0.0013017563703576736\n        unknown: 0.09502345480154492\n        wind: 0.052384014936455246\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 1.3140263562046065e-06\n        biomass: 0.0010306236032357411\n        coal: 0.05767405255713116\n        gas: 0.18680334905280718\n        geothermal: 9.289502209522274e-05\n        hydro: 0.5837493753324662\n        hydro discharge: 0.004020843958917171\n        nuclear: 0.031713129533058375\n        oil: 0.0027026391254005655\n        solar: 0.004926397078810936\n        unknown: 0.0743909828007367\n        wind: 0.05289414807003846\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 5.0536979581576145e-09\n        biomass: 0.002242949915732366\n        coal: 0.022395566944666604\n        gas: 0.16644220470652812\n        geothermal: 1.008212742652444e-06\n        hydro: 0.6301411983163174\n        hydro discharge: 0.006728311528364556\n        nuclear: 0.028861281588861348\n        oil: 0.0011004781062745278\n        solar: 0.004553963877848192\n        unknown: 0.07129409216492642\n        wind: 0.06623876270461133\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 2.958174526069302e-07\n        biomass: 0.001432993003958218\n        coal: 0.03627452908483749\n        gas: 0.18128477944637394\n        geothermal: 1.0978842742458868e-05\n        hydro: 0.582987095803555\n        hydro discharge: 0.00014769894993818156\n        nuclear: 0.026534574750530015\n        oil: 0.0014590110093258704\n        solar: 0.005743004941544504\n        unknown: 0.07236484420171571\n        wind: 0.09175979426182976\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 3.1815851005382055e-06\n        biomass: 0.001345255994917863\n        coal: 0.03537374817438959\n        gas: 0.16208588638817026\n        geothermal: 3.4351164480755944e-05\n        hydro: 0.6170123788235842\n        hydro discharge: 7.593341629096782e-05\n        nuclear: 0.028200430995513774\n        oil: 0.0015832853781900282\n        solar: 0.006004637212779023\n        unknown: 0.06448592533556254\n        wind: 0.08379502208308587\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 7.395112600625325e-05\n        biomass: 0.0002014245652374263\n        coal: 0.04865759409240826\n        gas: 0.2373550614219986\n        geothermal: 0.00028256519639540463\n        hydro: 0.4938945400546149\n        hydro discharge: 0.00020317783169383866\n        nuclear: 0.029368809841329727\n        oil: 0.0018992747673705706\n        solar: 0.013233373069032616\n        unknown: 0.07274019668392667\n        wind: 0.1020901076480728\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 0.6535\nisRenewable:\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 0.6224\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Avista Corporation\n"
  },
  {
    "path": "config/zones/US-NW-BPAT.yaml",
    "content": "bounding_box:\n  - - -124.72144721447208\n    - 41.93091581776139\n  - - -106.00948525039483\n    - 48.999551747062824\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2.0\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 4.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 2.0\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 3.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1.0\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 2.0\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 32.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 350.9\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 340.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 339.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 325.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 308.2\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 303.2\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 289.2\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 301.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 292.0\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 293.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 281.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1459.8\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 729.9\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2266.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2271.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2167.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 18.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 19303.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 19038.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 19178.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 19249.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 19010.3\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 19577.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 19732.4\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 18988.6\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 18988.2\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 314.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1200.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4.4\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 60.7\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 70.6\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 14.8\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 24.7\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 64.7\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 84.7\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 87.9\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 137.9\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 140.8\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 223.7\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4380.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 3074.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 3077.5\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 3277.5\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 3397.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 3617.1\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 3817.1\ncenter_point:\n  - -115.54847110735697\n  - 48.63996347693276\ncentroid:\n  - -119.85519147704848\n  - 46.33846108511829\ncomment: Bonneville Power Administration\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ndisclaimer:\n  This zone includes all wind related electricity production from the generation-only\n  balancing authority Avangrid Renewables, LLC. Read more on the zone definition wiki\n  page.\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1134.8989239933912\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1118.4367385399487\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1111.904552841346\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1095.145710250945\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 394.4247593706675\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 385.50001712095116\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 385.56681367424125\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 386.5988427038903\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 0.0\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1194.8989239933912\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1178.4367385399487\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1171.904552841346\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1155.145710250945\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 514.4247593706675\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 505.50001712095116\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 505.56681367424125\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 506.5988427038903\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 38.0\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 32.8\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.06791398932896388\n        geothermal: 0.0\n        hydro: 0.7382562221049005\n        hydro discharge: 0.0\n        nuclear: 0.10063685899286395\n        oil: 0.0\n        solar: 0.001463661054655146\n        unknown: 0.018573904640700974\n        wind: 0.07315532407706106\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.06791400826213059\n        geothermal: 0.0\n        hydro: 0.738256427917109\n        hydro discharge: 0.0\n        nuclear: 0.10063688704856275\n        oil: 0.0\n        solar: 0.0014633826811540872\n        unknown: 0.018573909818762762\n        wind: 0.07315534447141515\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 5.018307213827167e-08\n        biomass: 3.5875000395453743e-07\n        coal: 5.979385109738975e-06\n        gas: 0.06928463813818371\n        geothermal: 6.160856532484422e-07\n        hydro: 0.7196894061175586\n        hydro discharge: 1.453081644943689e-07\n        nuclear: 0.10083842057512037\n        oil: 5.358975588656165e-08\n        solar: 0.001872766870077591\n        unknown: 0.018257325695226045\n        wind: 0.09005023130946987\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 8.483344911671521e-08\n        biomass: 0.0015645569460365522\n        coal: 0.02429085648464653\n        gas: 0.08625356970299909\n        geothermal: 8.947046191794926e-06\n        hydro: 0.6826489078279026\n        hydro discharge: 9.146857791364977e-05\n        nuclear: 0.08975670768322201\n        oil: 0.0009595676154735572\n        solar: 0.00041069231699839145\n        unknown: 0.016871285138115522\n        wind: 0.09714318121839885\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 3.857798714956116e-06\n        biomass: 0.002182017685766855\n        coal: 0.04132375876496627\n        gas: 0.07928428845288503\n        geothermal: 0.00028216845343418236\n        hydro: 0.7099337793725427\n        hydro discharge: 1.0745741561788134e-05\n        nuclear: 0.07728907681228524\n        oil: 0.0023456395683089013\n        solar: 0.0025511209468085205\n        unknown: 0.015606523098230522\n        wind: 0.06918691984767221\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 2.5133484685183387e-08\n        biomass: 0.004361105213552228\n        coal: 0.013862129324261669\n        gas: 0.043913158616159194\n        geothermal: 3.2150913186967125e-06\n        hydro: 0.7658620359074874\n        hydro discharge: 3.0475347541288237e-06\n        nuclear: 0.07638583665822905\n        oil: 0.0009222213577766285\n        solar: 0.0012717315852508022\n        unknown: 0.014579398683812467\n        wind: 0.07883603624911537\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 6.806512038376251e-07\n        biomass: 0.0039299907408601314\n        coal: 0.024928206563594322\n        gas: 0.06442537359230265\n        geothermal: 2.9282886781403996e-05\n        hydro: 0.7279405165922407\n        hydro discharge: 3.0727409962510685e-06\n        nuclear: 0.07299800365035744\n        oil: 0.0010296412384764623\n        solar: 0.0035679695509669073\n        unknown: 0.016253525509788005\n        wind: 0.08489368249339545\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 8.449281797192528e-06\n        biomass: 0.0034385892476815104\n        coal: 0.026822405936119873\n        gas: 0.05375374060809861\n        geothermal: 9.332997591093548e-05\n        hydro: 0.7356363658402308\n        hydro discharge: 1.3589617342820965e-07\n        nuclear: 0.07902487274929974\n        oil: 0.0013519573608750711\n        solar: 0.004744228337224285\n        unknown: 0.013681982093138704\n        wind: 0.08144386286584089\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.00023505884776098957\n        biomass: 0.0005542950343377248\n        coal: 0.043385257536750536\n        gas: 0.09262771548015947\n        geothermal: 0.0008716166009211536\n        hydro: 0.6292740578623236\n        hydro discharge: 6.246878094588995e-07\n        nuclear: 0.08253258891628076\n        oil: 0.001825518387251074\n        solar: 0.01534628263467043\n        unknown: 0.01967825129629526\n        wind: 0.11366870003676838\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Bonneville Power Administration\n"
  },
  {
    "path": "config/zones/US-NW-CHPD.yaml",
    "content": "bounding_box:\n  - - -121.15741157411568\n    - 47.26026828769821\n  - - -119.91539915399147\n    - 48.57543341118692\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1988.2\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1643.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1256.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1495.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1516.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1664.2\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1601.5\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1622.2\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -120.53640536405358\n  - 47.917850849442566\ncentroid:\n  - -120.63348633486329\n  - 47.90978908281691\ncomment: Public Utility District No. 1 Of Chelan County\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.997648400476363\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0023511678790842754\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9976484004763629\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.002351167879084275\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9977240438032576\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0022746044112365816\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 3.26661539967867e-08\n        biomass: 3.4027243746652806e-06\n        coal: 0.001178643835435059\n        gas: 0.0017769353346042064\n        geothermal: 6.173903105392685e-06\n        hydro: 0.9912830313615985\n        hydro discharge: 2.722179499732225e-08\n        nuclear: 0.0013474842967264506\n        oil: 4.875967919920361e-05\n        solar: 2.3900736007648936e-05\n        unknown: 0.0008933866456581193\n        wind: 0.0034357988555870273\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.81048481037229e-08\n        coal: 0.00024338236360861953\n        gas: 0.000738151351565799\n        geothermal: 2.81048481037229e-08\n        hydro: 0.9947177162827838\n        hydro discharge: 5.058872658670121e-08\n        nuclear: 0.00042998169210847737\n        oil: 1.3361044788509867e-05\n        solar: 1.295071400619551e-05\n        unknown: 0.000472375044988133\n        wind: 0.0033706256750187283\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 2.1454929921038295e-08\n        biomass: 7.080126873942638e-07\n        coal: 0.0005673219844370553\n        gas: 0.0013241017275418387\n        geothermal: 1.1102926234137318e-06\n        hydro: 0.9926174873437503\n        hydro discharge: 0.0\n        nuclear: 0.0008262776248515071\n        oil: 1.7383856968521278e-05\n        solar: 6.923505885519057e-05\n        unknown: 0.0007371967558193561\n        wind: 0.003837573586453876\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.0421323141023725e-08\n        coal: 0.0009767825178198762\n        gas: 0.0016288353657127638\n        geothermal: 3.063198471153558e-08\n        hydro: 0.9925217523084033\n        hydro discharge: 5.110436116041187e-05\n        nuclear: 0.0009927213605314452\n        oil: 5.1196257114546467e-05\n        solar: 4.1455285976278156e-06\n        unknown: 0.0006392588889450361\n        wind: 0.0031335090867281035\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 1.7909083768715954e-07\n        biomass: 8.494022587448135e-07\n        coal: 0.00044531192634966055\n        gas: 0.0006875553102863893\n        geothermal: 1.2792202691939965e-06\n        hydro: 0.9954411864409816\n        hydro discharge: 0.0\n        nuclear: 0.0004079075256784281\n        oil: 1.6440538899681242e-05\n        solar: 5.881343109646319e-05\n        unknown: 0.0003776104728228375\n        wind: 0.0025605947453213158\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 5.3240010533154305e-06\n        biomass: 1.588832534378416e-05\n        coal: 0.001539844402879\n        gas: 0.0038130045775583246\n        geothermal: 3.354434455399329e-05\n        hydro: 0.9854861246255869\n        hydro discharge: 1.0459727020266072e-08\n        nuclear: 0.0016963009996481399\n        oil: 8.157018116754496e-05\n        solar: 0.00043354522526300836\n        unknown: 0.0009067380457963353\n        wind: 0.005984898905090942\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 7.387729080227936e-06\n        biomass: 1.6320537234021544e-05\n        coal: 0.0012261276841476914\n        gas: 0.0032223391502593087\n        geothermal: 2.8046766494327938e-05\n        hydro: 0.9864060975737285\n        hydro discharge: 0.0\n        nuclear: 0.001981916926603198\n        oil: 3.345965940768053e-05\n        solar: 0.00035588491866325164\n        unknown: 0.0008210560429239747\n        wind: 0.005898109136322696\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Chelan County\n"
  },
  {
    "path": "config/zones/US-NW-DOPD.yaml",
    "content": "bounding_box:\n  - - -120.32220322203216\n    - 47.23307771387201\n  - - -118.83628092479266\n    - 48.991878515577795\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 200.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 619.2\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 696.6\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 619.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 696.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 777.8\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 300.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -119.57924207341242\n  - 48.1124781147249\ncentroid:\n  - -119.58601792478909\n  - 48.052270415538295\ncomment: Pud No. 1 Of Douglas County\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 1.8385692879964977e-07\n        biomass: 1.1273056262972812e-05\n        coal: 0.003953832747726252\n        gas: 0.005356981550829202\n        geothermal: 1.9457316122111513e-05\n        hydro: 0.9793347701209503\n        hydro discharge: 9.980804706266703e-08\n        nuclear: 0.004966117479366473\n        oil: 0.00017234223200168313\n        solar: 6.497503863779623e-05\n        unknown: 0.002482131575456575\n        wind: 0.00363582329756416\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.6579261431408183e-07\n        coal: 0.0007645775386027906\n        gas: 0.001637265903304797\n        geothermal: 8.735346013470613e-08\n        hydro: 0.992690437162848\n        hydro discharge: 0.0\n        nuclear: 0.0016044592194329563\n        oil: 4.661399016438255e-05\n        solar: 1.4981118413102099e-05\n        unknown: 0.0012443118224800798\n        wind: 0.0019953659535357662\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 5.4753377101191954e-08\n        biomass: 2.458924389817166e-06\n        coal: 0.00157455282045845\n        gas: 0.0029245520862654388\n        geothermal: 3.0114357405655577e-06\n        hydro: 0.9867215793263193\n        hydro discharge: 1.9910318945887985e-08\n        nuclear: 0.003172171745415712\n        oil: 4.850153695218314e-05\n        solar: 0.0001607011617919984\n        unknown: 0.0019548896881222753\n        wind: 0.0034356400184469105\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.12587257238875e-07\n        coal: 0.002763418453877415\n        gas: 0.0036889249663617034\n        geothermal: 1.654873714794044e-07\n        hydro: 0.9861216314344511\n        hydro discharge: 1.6364862290741106e-06\n        nuclear: 0.0030424853246488505\n        oil: 0.00013236231595494362\n        solar: 8.605343316929029e-06\n        unknown: 0.0015752283203981509\n        wind: 0.002663059556818016\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 4.2878089203203924e-07\n        biomass: 3.2251780139801215e-06\n        coal: 0.0012416935353823468\n        gas: 0.0019031999172266453\n        geothermal: 4.805142387880788e-06\n        hydro: 0.9898149810450881\n        hydro discharge: 0.0\n        nuclear: 0.0018703422510437551\n        oil: 5.3853947906850155e-05\n        solar: 0.00017543663410728286\n        unknown: 0.0009781750525955691\n        wind: 0.003952073481859306\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.267153444903673e-05\n        biomass: 5.0565618797940854e-05\n        coal: 0.004595938376610173\n        gas: 0.008904542044000771\n        geothermal: 9.770801582689023e-05\n        hydro: 0.9656008946259467\n        hydro discharge: 4.4983203271898274e-09\n        nuclear: 0.005444132660864433\n        oil: 0.0002047950295359713\n        solar: 0.001021811455602478\n        unknown: 0.00179020553725239\n        wind: 0.01226373472145501\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.7671090479592743e-05\n        biomass: 7.083356124580737e-05\n        coal: 0.00432969251876217\n        gas: 0.009546069063649102\n        geothermal: 0.00011990411998675982\n        hydro: 0.9636200817428271\n        hydro discharge: 0.0\n        nuclear: 0.007993115895508296\n        oil: 0.0001184571676136292\n        solar: 0.0012093544053328976\n        unknown: 0.0019158823758407704\n        wind: 0.011036652293410701\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Douglas County\n"
  },
  {
    "path": "config/zones/US-NW-GCPD.yaml",
    "content": "bounding_box:\n  - - -120.08460084600839\n    - 46.624867509864714\n  - - -118.92538925389248\n    - 47.961498875847795\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1077.6\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 1095.8\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 1217.8\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 1114.0\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 1236.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -119.50499504995042\n  - 47.293183192856254\ncentroid:\n  - -119.4498868065603\n  - 47.21843663565789\ncomment: Public Utility District No. 2 Of Grant County, Washington\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9999995975691565\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 2.9920037323930077e-09\n        biomass: 0.00025469730972368725\n        coal: 0.01286541259303613\n        gas: 0.02108136807407909\n        geothermal: 5.505286867603134e-07\n        hydro: 0.9461446179857804\n        hydro discharge: 0.0005386564159501779\n        nuclear: 0.00604429035598627\n        oil: 0.00023686197547489248\n        solar: 0.00011470444708875075\n        unknown: 0.002770107759587545\n        wind: 0.00994756268114675\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 1.915702335917278e-07\n        biomass: 0.00011463036899056388\n        coal: 0.015493608878942262\n        gas: 0.02364997639178592\n        geothermal: 2.0244466155737584e-05\n        hydro: 0.9369739190273939\n        hydro discharge: 2.180707825719168e-05\n        nuclear: 0.007558690921712006\n        oil: 0.00024002247757407471\n        solar: 0.00026657373632197923\n        unknown: 0.0029245449925231265\n        wind: 0.01273528862685086\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0002809103676714268\n        coal: 0.0062407118414682505\n        gas: 0.019659306366489278\n        geothermal: 7.551252474333059e-08\n        hydro: 0.9534779719110399\n        hydro discharge: 3.694639054379307e-05\n        nuclear: 0.004330109042917449\n        oil: 7.28129519837565e-05\n        solar: 0.0001856947374094428\n        unknown: 0.0021263836136311055\n        wind: 0.013588539237582131\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 4.040083956457732e-08\n        biomass: 0.0002743533186918349\n        coal: 0.004647895265566136\n        gas: 0.022882475187297413\n        geothermal: 2.1956978024226803e-06\n        hydro: 0.9379384751423295\n        hydro discharge: 2.026365587899843e-05\n        nuclear: 0.006141689960092752\n        oil: 0.00015820090494367506\n        solar: 0.0005470976300340544\n        unknown: 0.004437893458067705\n        wind: 0.022948957403638285\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 3.681927659997519e-07\n        biomass: 0.00014245801701128454\n        coal: 0.004020588433655335\n        gas: 0.015307197178527757\n        geothermal: 6.505281923172607e-06\n        hydro: 0.9531558102555987\n        hydro discharge: 3.8269239262540586e-06\n        nuclear: 0.0056480037177173\n        oil: 0.0002255604276346533\n        solar: 0.0006901252063775438\n        unknown: 0.003203695761281301\n        wind: 0.017595342527033934\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.1730051753035573e-05\n        biomass: 0.00011028286488668079\n        coal: 0.009083473370551912\n        gas: 0.04086131111910888\n        geothermal: 0.00011746086837561148\n        hydro: 0.9008470159813434\n        hydro discharge: 1.1089187839066662e-05\n        nuclear: 0.009417085825968827\n        oil: 0.0003748968220248439\n        solar: 0.003397736152506443\n        unknown: 0.007256839403228985\n        wind: 0.02850043238030508\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Grant County\n"
  },
  {
    "path": "config/zones/US-NW-GRID.yaml",
    "content": "bounding_box:\n  - - -119.851352692\n    - 44.7463779450001\n  - - -118.363136292\n    - 46.366308212\ncan_have_zero_production: true\ncapacity:\n  battery storage:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 689.4\n  geothermal:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  unknown:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\ncomment: Gridforce Energy Management, Llc\ncontributors:\n  - systemcatch\n  - robertahunt\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 394.7851977921214\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 396.61512229656836\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 399.2745381859123\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 514.7851977921214\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 516.6151222965684\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 519.2745381859123\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.31873392873272594\n        gas: 0.4948221464533781\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.030056513355228846\n        unknown: 0.0\n        wind: 0.15638589155047006\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3187353044588863\n        gas: 0.494824282215248\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.030052326265695532\n        unknown: 0.0\n        wind: 0.1563865665465804\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.26542960677491484\n        gas: 0.5616854634354924\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.02717640264239839\n        unknown: 0.0\n        wind: 0.14570856754905329\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.3484977642534123e-09\n        coal: 0.2501214757127239\n        gas: 0.582818816146504\n        geothermal: 2.6969955285068247e-09\n        hydro: 0.0031831963974083923\n        hydro discharge: 1.6991071829592997e-07\n        nuclear: 0.0004751108232883477\n        oil: 6.043966979383795e-06\n        solar: 0.02559508360154156\n        unknown: 0.00016049820390144114\n        wind: 0.13763987089099436\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.0617759898189296e-07\n        coal: 0.0001972116539181414\n        gas: 0.9953108068711579\n        geothermal: 4.392982941914116e-07\n        hydro: 0.0035298416662451174\n        hydro discharge: 0.0\n        nuclear: 0.0003423664599746006\n        oil: 9.561393933423676e-06\n        solar: 6.409761474338324e-06\n        unknown: 0.00022753322026948956\n        wind: 0.00037492112598808835\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.0973472471599464e-08\n        coal: 0.36485939854324223\n        gas: 0.6091553820657686\n        geothermal: 0.0\n        hydro: 0.002994934974311284\n        hydro discharge: 0.0\n        nuclear: 0.00028253948246250723\n        oil: 3.8370575409026125e-06\n        solar: 0.002336334590247063\n        unknown: 0.0002645027515433549\n        wind: 0.020102265813569407\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.574501988492557e-09\n        coal: 0.21392320264763393\n        gas: 0.6078423702185539\n        geothermal: 4.5745019884925575e-09\n        hydro: 0.0008826532083476312\n        hydro discharge: 0.0\n        nuclear: 0.00010881825330226094\n        oil: 1.4905252312504915e-06\n        solar: 0.027123928579014075\n        unknown: 5.949216077734378e-05\n        wind: 0.1500578484659712\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 1.5138779607295427e-09\n        biomass: 7.569389803647713e-09\n        coal: 0.24025682564162043\n        gas: 0.5912335555555297\n        geothermal: 2.270816941094314e-08\n        hydro: 0.0008762439177549647\n        hydro discharge: 0.0\n        nuclear: 8.300290083087935e-05\n        oil: 1.3920107848908145e-06\n        solar: 0.02782434722903192\n        unknown: 5.151651006464598e-05\n        wind: 0.13967293532596634\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 2.611608189559972e-07\n        biomass: 1.524542851773588e-07\n        coal: 0.24822049061316165\n        gas: 0.6065287899365069\n        geothermal: 3.221425330269407e-07\n        hydro: 0.00020315395198016668\n        hydro discharge: 0.0\n        nuclear: 1.0639983415943316e-05\n        oil: 5.846290414192628e-07\n        solar: 0.022438546486315564\n        unknown: 8.125150555235058e-06\n        wind: 0.12258887516105073\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 6.490029290002336e-08\n        biomass: 5.715989099451599e-08\n        coal: 0.1497751019676784\n        gas: 0.710931080239046\n        geothermal: 1.1312895092664623e-07\n        hydro: 7.914144157509452e-05\n        hydro discharge: 0.0\n        nuclear: 1.2865143382484445e-05\n        oil: 3.6915762933958236e-08\n        solar: 0.021910990863054543\n        unknown: 2.204823712007215e-06\n        wind: 0.11728828923384033\ngeneration_only: true\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Gridforce Energy Management\n"
  },
  {
    "path": "config/zones/US-NW-IPCO.yaml",
    "content": "bounding_box:\n  - - -119.9439947612488\n    - 41.991031589410795\n  - - -111.58851588515878\n    - 45.700387999773625\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 100.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 227.0\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 377.0\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 459.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 24.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 27.5\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 29.1\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 24.6\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 22.2\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 19.0\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 20.3\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 23.5\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 10.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 6.2\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 770.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 768.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 770.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 774.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 776.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 779.1\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 33.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1894.4\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 1893.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1992.0\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 1990.6\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1869.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1982.4\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 1985.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1855.1\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 1857.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1827.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1811.4\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 1830.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2022.1\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2023.1\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 169.5\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 269.5\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 289.5\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 291.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 294.3\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 309.3\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 315.3\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 318.3\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 438.3\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 478.3\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 481.3\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 581.3\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 781.3\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 780.9\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 15.9\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 666.8\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 716.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 714.7\ncenter_point:\n  - -115.94702834758624\n  - 43.739931985757934\ncentroid:\n  - -115.16451002876639\n  - 44.16341541464588\ncomment: Idaho Power Company\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 248.2\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 434.3409585758064\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 441.2147276174657\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 448.424204594005\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 460.8753585507786\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 0.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 281.2\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 554.3409585758063\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 561.2147276174658\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 568.424204594005\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 580.8753585507786\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 38.0\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 38.0\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 38.0\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 38.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.1851570107101973\n        geothermal: 0.0\n        hydro: 0.5722531240265427\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0004871681262304195\n        solar: 0.0555175135897385\n        unknown: 0.035002531562908\n        wind: 0.15158139517526142\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.18515887638000256\n        geothermal: 0.0\n        hydro: 0.5722588901348329\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.000487173035009513\n        solar: 0.05550799627208016\n        unknown: 0.03500288425366486\n        wind: 0.15158292253212968\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 8.00492835722966e-08\n        biomass: 2.814636099800106e-07\n        coal: 6.012045494273335e-05\n        gas: 0.20402451233354554\n        geothermal: 4.863209163263181e-07\n        hydro: 0.5548336641347024\n        hydro discharge: 7.660630363370322e-08\n        nuclear: 2.206950140638371e-06\n        oil: 1.15856274933668e-06\n        solar: 0.06415606296772705\n        unknown: 0.033221226492244293\n        wind: 0.14369913122486716\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 2.754522108931375e-09\n        biomass: 3.7860906387261755e-06\n        coal: 0.18454148736627207\n        gas: 0.19841401751179993\n        geothermal: 3.910044133628088e-06\n        hydro: 0.4123954763359343\n        hydro discharge: 0.003559841767634351\n        nuclear: 0.005168561871760907\n        oil: 0.00027847874206032586\n        solar: 0.045224175067145364\n        unknown: 0.03320698427646198\n        wind: 0.1172027355307808\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 3.888079403504881e-08\n        biomass: 5.999752692654335e-06\n        coal: 0.181978020878349\n        gas: 0.16604999305244827\n        geothermal: 7.526939291145761e-06\n        hydro: 0.4549249728153137\n        hydro discharge: 1.1479395091331624e-06\n        nuclear: 0.004306063874133309\n        oil: 0.0004091986859566397\n        solar: 0.04449083688040906\n        unknown: 0.029054267390231873\n        wind: 0.11877139240409511\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 7.416004479266706e-09\n        biomass: 7.30847241431734e-06\n        coal: 0.1470509034547457\n        gas: 0.16401934464768417\n        geothermal: 1.2100447308670173e-06\n        hydro: 0.46259490322732155\n        hydro discharge: 6.358605840597928e-06\n        nuclear: 0.005543814372463881\n        oil: 0.00036461404022688034\n        solar: 0.04954825779514771\n        unknown: 0.03650580920350875\n        wind: 0.13435675801948185\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 1.0697033476218515e-07\n        biomass: 9.139758160757975e-06\n        coal: 0.2076260906911046\n        gas: 0.21040258551436095\n        geothermal: 6.063622290939334e-06\n        hydro: 0.3219465090408549\n        hydro discharge: 1.6979324407279444e-06\n        nuclear: 0.004518455899174609\n        oil: 0.00031867349220141944\n        solar: 0.05951553726382531\n        unknown: 0.03158041223057438\n        wind: 0.1640738357712227\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 8.865131679921074e-07\n        biomass: 1.585179272634345e-05\n        coal: 0.20995133470063979\n        gas: 0.19276224495002206\n        geothermal: 1.2946216528166681e-05\n        hydro: 0.3408059298686161\n        hydro discharge: 6.136969696609932e-09\n        nuclear: 0.005709850553384282\n        oil: 0.0004416804985966971\n        solar: 0.059491414347035865\n        unknown: 0.03194761535779657\n        wind: 0.15885963206242273\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 5.485832428887847e-06\n        biomass: 1.7967667306850855e-05\n        coal: 0.17621150238088762\n        gas: 0.2192590727555405\n        geothermal: 2.843817944681624e-05\n        hydro: 0.358033909471735\n        hydro discharge: 3.376348639578048e-05\n        nuclear: 0.004074175833017417\n        oil: 0.0002501853926665949\n        solar: 0.07344448620207487\n        unknown: 0.027019299204349246\n        wind: 0.1416212057295658\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 6.49245887488187e-06\n        biomass: 1.6417900119483766e-05\n        coal: 0.12843187923241747\n        gas: 0.24399103206203182\n        geothermal: 2.1672609632983098e-05\n        hydro: 0.3730123678898783\n        hydro discharge: 1.3571621852339779e-06\n        nuclear: 0.0037312854184535682\n        oil: 0.00016299359718089678\n        solar: 0.0871122427942582\n        unknown: 0.026889556885679546\n        wind: 0.13662238355509054\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.6298\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.6283\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Mountain\nzone_name: Idaho Power Company\n"
  },
  {
    "path": "config/zones/US-NW-NEVP.yaml",
    "content": "bounding_box:\n  - - -120.00540005400048\n    - 35.1203926157127\n  - - -111.71451714517138\n    - 41.9933830361321\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 25.0\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 35.0\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 110.0\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 175.0\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 470.0\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 850.0\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 1035.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 1135.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 15.2\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 35.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 15.2\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1103.8\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 809.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 531.8\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 7606.2\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 8061.8\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 8339.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 633.4\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 670.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 678.4\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 667.0\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 734.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 735.7\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 761.7\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 740.7\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 718.9\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 750.5\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 775.3\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 800.8\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 822.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 819.7\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 856.7\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 844.7\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 860.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 889.3\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 918.5\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 863.9\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 853.9\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 858.7\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 12.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 16.4\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 16.9\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 15.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 837.7\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 887.7\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 898.3\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 998.3\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 1077.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1092.3\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 1095.4\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 1115.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1115.6\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 1215.6\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 1222.9\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 1422.9\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 1432.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1433.7\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 1483.7\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 1593.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1592.5\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 1844.5\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 2045.5\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 2046.4\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 2347.5\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 2349.3\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 2356.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2355.8\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 2663.8\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 2794.8\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 2806.8\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 3006.8\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 3700.4\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 3805.9\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 4015.9\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 4080.9\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 4180.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 4186.7\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 4259.7\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 4375.7\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 7.5\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 150.0\ncenter_point:\n  - -115.85771214718278\n  - 38.79209090856581\ncentroid:\n  - -114.98185638409322\n  - 38.83583418075562\ncomment: Nevada Power Company\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 368.88\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 409.65\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1092.3994193686647\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1092.633856676898\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1049.698182363371\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1124.243615415859\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 405.9274374453633\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 399.4991639237896\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 400.24829769089723\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 403.4625388058051\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 14.379757812501364\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 3.4303641735972765\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1.1347416194747946\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1.183420260702788\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 0.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 401.88\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 442.65\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1152.3994193686647\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1152.633856676898\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1109.698182363371\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1184.243615415859\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 525.9274374453632\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 519.4991639237896\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 520.2482976908973\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 523.462538805805\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 52.37975781250137\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 41.430364173597276\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 39.134741619474795\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 39.18342026070279\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 24.0\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0894806936629927\n        gas: 0.6955694411101571\n        geothermal: 0.0\n        hydro: 0.0026832274546137527\n        hydro discharge: 0.0\n        nuclear: 0.00018856835277713345\n        oil: 0.0001892515714466158\n        solar: 0.09519360875951474\n        unknown: 0.10659509359396953\n        wind: 0.010098541283840632\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0894820954282705\n        gas: 0.6955803375957668\n        geothermal: 0.0\n        hydro: 0.0026832694888775065\n        hydro discharge: 0.0\n        nuclear: 0.00018857130680619369\n        oil: 0.00018925453617867993\n        solar: 0.09517943440511581\n        unknown: 0.10659676346592589\n        wind: 0.010098699483156582\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.00014309635633442063\n        biomass: 0.0003588268044027549\n        coal: 0.12939432076969035\n        gas: 0.5788949808905842\n        geothermal: 0.0006231266862784682\n        hydro: 0.04773544450158368\n        hydro discharge: 0.0027603900549758847\n        nuclear: 0.004409762463088398\n        oil: 5.616128255388486e-05\n        solar: 0.11133702595751821\n        unknown: 0.09494911317531483\n        wind: 0.029337600053824613\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 6.728591157063228e-06\n        biomass: 0.0005553636158154\n        coal: 0.17246620816762492\n        gas: 0.6085647134279034\n        geothermal: 0.0007870026282591714\n        hydro: 0.04327619918421075\n        hydro discharge: 0.0018797087820141953\n        nuclear: 0.019406131170724112\n        oil: 9.292643809174448e-05\n        solar: 0.055298039324088215\n        unknown: 0.07581934916355512\n        wind: 0.02184762976567679\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 6.74576342931461e-06\n        biomass: 0.000411809471396028\n        coal: 0.1440220839864209\n        gas: 0.5891371194060141\n        geothermal: 0.0005285364287683245\n        hydro: 0.06333281837590972\n        hydro discharge: 0.00016747237325502235\n        nuclear: 0.024981322031079767\n        oil: 0.00013798611560782682\n        solar: 0.06297142344822003\n        unknown: 0.09143262750278806\n        wind: 0.02287022922583746\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 3.5390204600317625e-06\n        biomass: 0.0007087202707176041\n        coal: 0.10835455459109825\n        gas: 0.5959297218088148\n        geothermal: 0.0003549881816819225\n        hydro: 0.08941291752517788\n        hydro discharge: 0.00013373229971989982\n        nuclear: 0.011806172254665959\n        oil: 0.00010263187707542443\n        solar: 0.07723326696245152\n        unknown: 0.08827445297571705\n        wind: 0.02768582458764027\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 3.7648454702063816e-06\n        biomass: 0.00040704316129359485\n        coal: 0.13927714911990724\n        gas: 0.5480544562423654\n        geothermal: 0.00013920883813624892\n        hydro: 0.08201621426437956\n        hydro discharge: 8.50145817317162e-05\n        nuclear: 0.01879222052895048\n        oil: 0.00011950188579034058\n        solar: 0.09343942371885634\n        unknown: 0.07926604756790845\n        wind: 0.0383999505717988\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 2.4035643889599126e-05\n        biomass: 0.0004115881312759442\n        coal: 0.12345259979677739\n        gas: 0.5172518153158673\n        geothermal: 0.00018389361052678011\n        hydro: 0.08664462453933919\n        hydro discharge: 1.695834903316181e-06\n        nuclear: 0.017801906894346853\n        oil: 0.00012796500699520583\n        solar: 0.13668662826983805\n        unknown: 0.08122856365929564\n        wind: 0.03618460329480164\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.00011145825626036205\n        biomass: 0.00019156675435751818\n        coal: 0.09199544437173056\n        gas: 0.5450735858183692\n        geothermal: 0.00031353016655370514\n        hydro: 0.06982187029256672\n        hydro discharge: 0.00015783077731684286\n        nuclear: 0.01969826189883462\n        oil: 8.6813750862557e-05\n        solar: 0.14888842263053334\n        unknown: 0.09266477904536434\n        wind: 0.030996482747352047\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.3196\n    - datetime: '2025-01-01'\n      value: 0.201\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 1.0\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.2996\n    - datetime: '2025-01-01'\n      value: 0.1879\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 1.0\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Nevada Power Company\n"
  },
  {
    "path": "config/zones/US-NW-NWMT.yaml",
    "content": "bounding_box:\n  - - -115.69255692556919\n    - 43.82423840576526\n  - - -104.04644046440458\n    - 48.999089700338764\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2437.8\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 2530.7\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1814.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1810.7\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 258.0\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 465.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 645.4\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 642.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 657.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 662.2\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 665.7\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 678.1\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 669.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 644.9\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 649.0\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 652.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 668.9\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 666.1\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 698.1\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 701.2\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 704.7\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 699.1\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 68.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 8.0\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 17.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 97.0\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 177.0\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 179.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 181.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 258.3\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 283.3\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 363.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 371.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 372.9\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 452.9\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 555.7\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 763.6\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 1011.6\ncenter_point:\n  - -110.68984647487405\n  - 46.30215557229568\ncentroid:\n  - -109.85464945606991\n  - 46.3798337690431\ncomment: Northwestern Energy (Nwmt)\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ndisclaimer: This zone includes all electricity production from the generation-only\n  balancing authorities NaturEner Power Watch, LLC and NaturEner Wind Watch, LLC.\n  Read more on the wiki page.\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1063.9600437074787\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1031.1107560999872\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1019.8754600552801\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1041.256839238835\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 655.0343565422723\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 603.2813480693219\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 585.8110833393567\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 581.6705529835303\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 867.13\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 825.7991358770756\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 830.0476571185673\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 838.4331666962912\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 837.1102281005788\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1123.9600437074787\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1091.1107560999872\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1079.8754600552802\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1101.256839238835\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 775.0343565422723\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 723.2813480693219\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 705.8110833393567\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 701.6705529835303\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 891.13\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1069.7991358770755\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1074.0476571185673\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1082.4331666962912\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1102281005788\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6571573855991798\n        gas: 0.020928555152924643\n        geothermal: 0.0\n        hydro: 0.21601863693607018\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.026461008897765367\n        solar: 0.0017971039296415976\n        unknown: 0.0\n        wind: 0.07763693889607305\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.6571577526908395\n        gas: 0.020928566843728423\n        geothermal: 0.0\n        hydro: 0.21601875760524578\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.026461023679027643\n        solar: 0.0017965461964592677\n        unknown: 0.0\n        wind: 0.07763698226448583\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5935794841775107\n        gas: 0.025953577348594527\n        geothermal: 0.0\n        hydro: 0.19882626617213386\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.024537619546296845\n        solar: 0.00555684178913225\n        unknown: 0.0\n        wind: 0.15154683323986243\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.987092340776412e-07\n        coal: 0.6767576935197022\n        gas: 0.025045048193275528\n        geothermal: 2.5718229274081948e-08\n        hydro: 0.1911837691443498\n        hydro discharge: 1.1065982540431372e-06\n        nuclear: 0.0005022798753038509\n        oil: 0.024273440591456176\n        solar: 0.0017846300786487454\n        unknown: 0.0006041212056481849\n        wind: 0.07984684777321799\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 4.209145572751549e-08\n        biomass: 5.951910952448254e-06\n        coal: 0.6518342585918924\n        gas: 0.02353536045163193\n        geothermal: 7.113456017950119e-06\n        hydro: 0.21614373221219557\n        hydro discharge: 8.955628878194786e-08\n        nuclear: 0.0010390284801966077\n        oil: 0.021100338393094088\n        solar: 0.0021775378770979787\n        unknown: 0.0009645364547506714\n        wind: 0.08319168453953463\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 2.029247384268161e-09\n        biomass: 2.6501970838542185e-06\n        coal: 0.5123719702420856\n        gas: 0.019664605424138892\n        geothermal: 2.242318359616318e-07\n        hydro: 0.29424122888104665\n        hydro discharge: 8.045965878623259e-07\n        nuclear: 0.003150128557184676\n        oil: 0.02819155366401831\n        solar: 0.0025379320161906587\n        unknown: 0.0039740222730477\n        wind: 0.13586429143503848\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 2.0096981986833884e-08\n        biomass: 4.509188558360185e-05\n        coal: 0.5911746854020353\n        gas: 0.029406661029456837\n        geothermal: 2.7398885442050194e-06\n        hydro: 0.21891055072184648\n        hydro discharge: 1.1579689620985235e-07\n        nuclear: 0.0021301174007502125\n        oil: 0.02583763225642016\n        solar: 0.00339476114323485\n        unknown: 0.0016995405186814383\n        wind: 0.12739760248900012\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 9.33457973400747e-08\n        biomass: 7.65902267175313e-05\n        coal: 0.5885043621941616\n        gas: 0.03566126101977909\n        geothermal: 1.3965263405975885e-06\n        hydro: 0.20036035248211356\n        hydro discharge: 0.0\n        nuclear: 0.0014100248750168636\n        oil: 0.0232374533714749\n        solar: 0.0036948343988769824\n        unknown: 0.0010853782585717186\n        wind: 0.1459679513000406\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 9.703740267834795e-07\n        biomass: 8.193367687236941e-05\n        coal: 0.5507949224682919\n        gas: 0.04227716075031356\n        geothermal: 3.6516706797378315e-06\n        hydro: 0.19254694962751406\n        hydro discharge: 4.016472945445907e-06\n        nuclear: 0.0010346576580352283\n        oil: 0.02353283601336139\n        solar: 0.012994801171903207\n        unknown: 0.0011187062760430401\n        wind: 0.17560892142107948\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 3.890711059389329e-06\n        biomass: 0.00030571628210676057\n        coal: 0.45661434149826446\n        gas: 0.05609392664579398\n        geothermal: 1.209746180652417e-05\n        hydro: 0.19441655769835817\n        hydro discharge: 1.1330475755390072e-07\n        nuclear: 0.0017863052836409635\n        oil: 0.01816911164751423\n        solar: 0.024043798598998\n        unknown: 0.0013187296690682232\n        wind: 0.24723499458575396\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2024-01-01'\n      value: 0.139\nisRenewable:\n  hydro discharge:\n    - datetime: '2024-01-01'\n      value: 0.139\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Mountain\nzone_name: Northwestern Energy\n"
  },
  {
    "path": "config/zones/US-NW-PACE.yaml",
    "content": "bounding_box:\n  - - -114.05009233748142\n    - 34.52219999153611\n  - - -104.65484654846543\n    - 45.00068037022231\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 200.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 16.9\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 15.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 12.1\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 9.8\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 7923.5\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 7841.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 7447.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 6988.4\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 5824.3\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3346.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 3399.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 3784.3\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 3774.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 3767.4\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 3766.8\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 3766.2\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 3765.5\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 3764.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 3757.2\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 3753.3\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 3755.8\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 3770.7\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 3777.2\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 3776.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 3447.0\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 3442.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 3435.0\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 4601.3\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 4603.5\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 4611.0\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 4608.5\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 4606.5\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 4605.1\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 4611.5\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 83.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 77.1\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 269.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 264.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 264.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 271.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 271.8\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 271.9\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 271.3\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 10.2\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 855.8\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 949.8\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 1007.4\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 1129.4\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 1286.4\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 1386.4\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 1466.4\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 1547.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1551.9\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 1631.9\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 1633.4\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 1705.4\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 1717.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 1917.9\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 1997.9\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 2037.9\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 2192.9\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 2197.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2199.4\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2197.9\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 2297.9\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 2497.9\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2522.9\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 52.8\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1846.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1948.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1923.0\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 1906.2\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 2690.1\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2708.6\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 2948.4\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 3451.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 3443.2\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 3603.2\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 4067.8\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 3984.8\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 3983.3\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 4173.3\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 4573.3\ncenter_point:\n  - -109.51721481248637\n  - 39.57918484411764\ncentroid:\n  - -110.63403009487944\n  - 39.59953986324012\ncomment: Pacificorp - East\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ndisclaimer:\n  This zone includes all gas related electricity production from the generation-only\n  balancing authority Avangrid Renewables, LLC. Read more on the zone definition wiki\n  page.\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1048.4956104894752\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1038.2985708247186\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1047.4235967504487\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1096.453245499706\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 405.7227070033736\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 404.1966603887903\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 410.0950813261025\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.8612718735854\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 32.63419569396435\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 61.077625605917994\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 25.855668050323082\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 24.805281488072655\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1108.4956104894752\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1098.2985708247186\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1107.4235967504487\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1156.453245499706\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 525.7227070033737\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 524.1966603887903\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 530.0950813261024\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.8612718735853\n    geothermal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 70.63419569396436\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 99.077625605918\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 63.85566805032308\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 62.80528148807265\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 27.475\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5392276388182086\n        gas: 0.20234656948574695\n        geothermal: 0.0\n        hydro: 0.022578072633447743\n        hydro discharge: 0.010448159188550089\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.06141221920585414\n        unknown: 0.017666005428310417\n        wind: 0.1463207402457067\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5392294583304459\n        gas: 0.2023472522624314\n        geothermal: 0.0\n        hydro: 0.02257814881848816\n        hydro discharge: 0.01044819444370419\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.06140905220412467\n        unknown: 0.017666065038595108\n        wind: 0.14632123397480792\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 4.04952881504996e-09\n        biomass: 6.01355029034919e-08\n        coal: 0.5189306218930243\n        gas: 0.20864160033977164\n        geothermal: 1.0630013139506146e-07\n        hydro: 0.0213487751450936\n        hydro discharge: 0.010367263106917561\n        nuclear: 5.987228353051365e-07\n        oil: 7.491628307842426e-09\n        solar: 0.0652729613244486\n        unknown: 0.01831969195558266\n        wind: 0.15711843770312178\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 4.62266796700369e-09\n        biomass: 0.00013818541353764128\n        coal: 0.5838492599365236\n        gas: 0.19095822021744943\n        geothermal: 1.431178002584342e-06\n        hydro: 0.07710238377022903\n        hydro discharge: 0.00456622297224595\n        nuclear: 0.005135506381449641\n        oil: 0.0005346400260186534\n        solar: 0.03478700004852988\n        unknown: 0.015239074091647334\n        wind: 0.08768796834865605\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 2.062125896934907e-07\n        biomass: 0.00013216953574994084\n        coal: 0.5492665112664474\n        gas: 0.17799400747035915\n        geothermal: 1.5744454457713368e-05\n        hydro: 0.09966932702131112\n        hydro discharge: 0.00030844946432890874\n        nuclear: 0.0073022554255528505\n        oil: 0.0005861245751204224\n        solar: 0.04617538988710868\n        unknown: 0.013890753417208595\n        wind: 0.1046590795495668\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 5.298909020339183e-09\n        biomass: 0.0002823029813167039\n        coal: 0.5117118326948749\n        gas: 0.18508505925335444\n        geothermal: 2.28213413687968e-06\n        hydro: 0.09232108556926276\n        hydro discharge: 0.00018541073422891538\n        nuclear: 0.0035556760503916074\n        oil: 0.0006613127479054843\n        solar: 0.05655813942841262\n        unknown: 0.020403628497897276\n        wind: 0.12923344562004155\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 2.4281973599591004e-07\n        biomass: 0.00020046760692223872\n        coal: 0.48157543992198476\n        gas: 0.1839289203754357\n        geothermal: 1.2781092781613198e-05\n        hydro: 0.07131447128090009\n        hydro discharge: 0.00045265015653532997\n        nuclear: 0.005048899618695175\n        oil: 0.00028426427323370655\n        solar: 0.0663489831731483\n        unknown: 0.018584611643950366\n        wind: 0.17224830180095313\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 1.2850367309379247e-06\n        biomass: 7.293015459198649e-05\n        coal: 0.5000033778360831\n        gas: 0.1840975742732571\n        geothermal: 1.6452161887445172e-05\n        hydro: 0.05042850674003895\n        hydro discharge: 7.097942798973445e-06\n        nuclear: 0.0039180599085533886\n        oil: 0.00034807961164416397\n        solar: 0.06932496421010209\n        unknown: 0.017017255808031657\n        wind: 0.1747643126336101\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 6.7243961688789805e-06\n        biomass: 2.088380926656518e-05\n        coal: 0.4687680359217302\n        gas: 0.2192011270319618\n        geothermal: 3.320130120668048e-05\n        hydro: 0.041056837392770947\n        hydro discharge: 2.4113796554924103e-05\n        nuclear: 0.007293846029421079\n        oil: 0.0003456084435503269\n        solar: 0.07690011096176308\n        unknown: 0.018316593815589824\n        wind: 0.16803287999854508\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Mountain\nzone_name: Pacificorp East\n"
  },
  {
    "path": "config/zones/US-NW-PACW.yaml",
    "content": "bounding_box:\n  - - -124.48024480244796\n    - 39.1660637844859\n  - - -117.60417604176035\n    - 47.082814016411376\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 185.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 123.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 118.7\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 115.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 118.7\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1240.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1301.8\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 1240.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 621.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 626.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3.7\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1055.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1060.8\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 1033.8\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 897.1\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 893.8\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 42.3\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 93.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 110.9\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 120.9\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 130.9\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 140.9\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 158.9\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 166.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 172.5\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 229.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 284.1\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 294.1\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 297.4\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 337.4\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 407.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 408.4\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 463.4\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 466.2\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 468.5\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 470.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 474.6\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 480.8\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 483.8\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 486.1\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 491.1\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 495.5\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 619.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 629.6\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 650.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 674.3\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 694.3\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 480.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 481.9\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 489.9\ncenter_point:\n  - -121.15138084484636\n  - 43.369207468708666\ncentroid:\n  - -121.36958197432962\n  - 44.139979983322945\ncomment: Pacificorp - West\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 401.3274363408074\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 404.12602180659843\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 404.59127498819026\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 401.38927523144184\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 187.89\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 395.8\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 521.3274363408075\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 524.1260218065984\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 524.5912749881902\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 521.3892752314418\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 211.89\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 419.8\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.575\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5342014720586332\n        gas: 0.008435658347889563\n        geothermal: 0.0\n        hydro: 0.1555963457968817\n        hydro discharge: 0.12876717954702924\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.04700173790928907\n        unknown: 0.022395389854551945\n        wind: 0.10360246990157802\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.5342054659157242\n        gas: 0.008435721415506693\n        geothermal: 0.0\n        hydro: 0.15559750908377157\n        hydro discharge: 0.12876814225069072\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.04699461230416433\n        unknown: 0.02239555728948287\n        wind: 0.10360324446600869\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 2.1738191608315642e-07\n        biomass: 1.2430792602011548e-06\n        coal: 0.535417119758201\n        gas: 0.13241308139077937\n        geothermal: 2.1518455375451803e-06\n        hydro: 0.15810649929315956\n        hydro discharge: 3.845384075117208e-08\n        nuclear: 6.83693593110635e-06\n        oil: 1.930539760160884e-07\n        solar: 0.0465500120490009\n        unknown: 0.022381245769930377\n        wind: 0.10512104707956303\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 1.9660893455658984e-08\n        biomass: 0.0010182837073313045\n        coal: 0.34198128969060243\n        gas: 0.09337813263237381\n        geothermal: 3.209041439152925e-06\n        hydro: 0.40932066210680795\n        hydro discharge: 0.0011539208545439886\n        nuclear: 0.03722506003988497\n        oil: 0.0005636245871012168\n        solar: 0.01717351997634961\n        unknown: 0.02158516647851463\n        wind: 0.07659711314229324\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 1.5531329814166745e-06\n        biomass: 0.0008796640846390336\n        coal: 0.3482198192300914\n        gas: 0.07566561763052107\n        geothermal: 0.00010931907763147219\n        hydro: 0.42468759591687155\n        hydro discharge: 1.9703975986863272e-05\n        nuclear: 0.028359430555205876\n        oil: 0.000990834501260242\n        solar: 0.02292220459841498\n        unknown: 0.021051098970266118\n        wind: 0.07709388901477322\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 5.633451580798242e-08\n        biomass: 0.0022566396103833285\n        coal: 0.2556032285079354\n        gas: 0.12133940112929592\n        geothermal: 6.1099257565573455e-06\n        hydro: 0.444693032867981\n        hydro discharge: 9.375748201014497e-06\n        nuclear: 0.028651381991102558\n        oil: 0.00035281096321694913\n        solar: 0.025611559935306182\n        unknown: 0.01927392374796335\n        wind: 0.10220312366308357\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 1.2174292367164833e-06\n        biomass: 0.0016127357040318544\n        coal: 0.28703772976606673\n        gas: 0.11289564456464693\n        geothermal: 2.8533462880147578e-05\n        hydro: 0.3992263663830702\n        hydro discharge: 1.8884374170267325e-05\n        nuclear: 0.02629324585540075\n        oil: 0.0006479545432111255\n        solar: 0.035332979165341005\n        unknown: 0.02203942596900926\n        wind: 0.11486582875784239\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 3.801806165782319e-06\n        biomass: 0.0016707835135592155\n        coal: 0.15972626193273975\n        gas: 0.14319207124354008\n        geothermal: 3.864567689905504e-05\n        hydro: 0.4806761215441902\n        hydro discharge: 0.0\n        nuclear: 0.03261709234541887\n        oil: 0.000663596725594441\n        solar: 0.043743694479977155\n        unknown: 0.024454589129574007\n        wind: 0.11321372519921519\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0001502291445699367\n        biomass: 0.0002875357318903857\n        coal: 0.05557978446708941\n        gas: 0.22498673285131882\n        geothermal: 0.000426058257044364\n        hydro: 0.4519373794418333\n        hydro discharge: 2.937633122100552e-07\n        nuclear: 0.03478787844868816\n        oil: 0.0008382223170179269\n        solar: 0.05754511705279815\n        unknown: 0.028237803048731375\n        wind: 0.14522387099354464\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.7924\n    - datetime: '2021-01-01'\n      value: 0.5026\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.762\n    - datetime: '2021-01-01'\n      value: 0.4888\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Pacificorp West\n"
  },
  {
    "path": "config/zones/US-NW-PGE.yaml",
    "content": "bounding_box:\n  - - -123.720637206372\n    - 44.78020173818142\n  - - -121.66861668616679\n    - 45.90646392771963\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 292.0\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 492.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 493.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 14.7\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 15.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 14.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 15.9\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 14.7\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 642.2\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2085.6\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2115.3\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 692.4\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 693.6\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 676.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 606.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 624.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6.6\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 24.2\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 28.6\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 30.8\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 37.4\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 41.8\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 43.7\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 63.7\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 65.9\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 70.3\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 73.4\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 76.4\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 83.9\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 87.5\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 112.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 125.4\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 128.4\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 132.7\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 135.2\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 137.4\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 147.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 149.9\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 151.8\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 165.0\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 170.9\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 173.5\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 189.7\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 191.7\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 194.2\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 196.8\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 197.9\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 716.5\ncenter_point:\n  - -122.6946269462694\n  - 45.34333283295052\ncentroid:\n  - -122.79128791287906\n  - 45.341830195975916\ncomment: Portland General Electric Company\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 127.37\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 214.57\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1040.9460372675912\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 465.36521947530525\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 453.7655300710371\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 480.81563364794056\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 480.58105543060304\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 160.37\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 247.57\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1100.9460372675912\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 585.3652194753053\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 573.7655300710371\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 600.8156336479406\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 600.5810554306031\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 30.16666667\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0010741020124494648\n        gas: 0.6855501497321558\n        geothermal: 0.0\n        hydro: 0.29920227169981184\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.013088996745911958\n        wind: 0.0010741020124494648\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0010741020124494646\n        gas: 0.6855501497321557\n        geothermal: 0.0\n        hydro: 0.29920227169981184\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.013088996745911956\n        wind: 0.0010741020124494646\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.7058240342513324\n        geothermal: 0.0\n        hydro: 0.28319614696074213\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.010982764176301524\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 4.01974496814187e-08\n        biomass: 0.0014188541668157125\n        coal: 0.03967654576577029\n        gas: 0.26389016533072274\n        geothermal: 4.4939791661690836e-06\n        hydro: 0.5635846259513175\n        hydro discharge: 0.00014501421388998852\n        nuclear: 0.06378437377835942\n        oil: 0.0010027871141007143\n        solar: 0.0013362302231598267\n        unknown: 0.016203839850852917\n        wind: 0.048952877730876546\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 2.8656732918079836e-06\n        biomass: 0.0017079301219978644\n        coal: 0.04817986295065472\n        gas: 0.23893267537293403\n        geothermal: 0.00020351132510833985\n        hydro: 0.5837058364919504\n        hydro discharge: 8.993245545943829e-05\n        nuclear: 0.057277338264827456\n        oil: 0.0018578748030037631\n        solar: 0.0025780598414593663\n        unknown: 0.01652142702397747\n        wind: 0.04894250032362554\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 1.1621621503834917e-08\n        biomass: 0.004101644541762611\n        coal: 0.0147092393779469\n        gas: 0.20723226338390724\n        geothermal: 1.7345270094473618e-06\n        hydro: 0.6381268091293454\n        hydro discharge: 9.199481888743989e-06\n        nuclear: 0.056444967772517216\n        oil: 0.000741344204198088\n        solar: 0.0012483568116720594\n        unknown: 0.01598749377940603\n        wind: 0.061396849659266166\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 5.618427911746858e-07\n        biomass: 0.0029029369359345803\n        coal: 0.023795080131998304\n        gas: 0.26341258716486776\n        geothermal: 2.3075884737528616e-05\n        hydro: 0.5700710103739719\n        hydro discharge: 5.796854718944165e-05\n        nuclear: 0.05442739763659866\n        oil: 0.0011164887099624186\n        solar: 0.0029199702292670247\n        unknown: 0.015288742261147495\n        wind: 0.06598393041910429\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 5.6172230844436586e-06\n        biomass: 0.002488523529783388\n        coal: 0.024849574599941526\n        gas: 0.21617780962650365\n        geothermal: 6.481195360934042e-05\n        hydro: 0.614423796613571\n        hydro discharge: 9.551406808103894e-08\n        nuclear: 0.05947632365185869\n        oil: 0.001207484774620718\n        solar: 0.003918778345627371\n        unknown: 0.014019379728364525\n        wind: 0.06336761974825729\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.00016160770846625403\n        biomass: 0.00039904184260978787\n        coal: 0.031918952478896964\n        gas: 0.32440501106862163\n        geothermal: 0.0006091631108313825\n        hydro: 0.4842117673065091\n        hydro discharge: 3.8968709459277905e-07\n        nuclear: 0.05427088087903467\n        oil: 0.0012967043527531894\n        solar: 0.01084136274033947\n        unknown: 0.01600995200693216\n        wind: 0.07587504128718962\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.7585\n    - datetime: '2025-01-01'\n      value: 0.5843\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.7585\n    - datetime: '2025-01-01'\n      value: 0.5458\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Portland General Electric Company\n"
  },
  {
    "path": "config/zones/US-NW-PSCO.yaml",
    "content": "bounding_box:\n  - - -109.06129061290606\n    - 36.21803314859174\n  - - -103.16443164431638\n    - 41.225391981112935\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 1.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1.0\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 2.0\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 227.0\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 232.8\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 240.6\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 248.4\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 258.6\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 252.8\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 352.8\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 364.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 22.8\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 10.2\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1506.0\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 1314.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1311.3\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6507.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 6510.0\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 6514.0\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 6430.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 6816.8\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 6731.2\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 6784.4\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 56.0\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 55.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 53.7\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 53.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 48.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 53.4\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 300.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 30.0\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 28.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 81.2\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 28.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 20.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 377.4\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 378.7\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 382.3\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 385.5\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 412.8\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 414.0\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 418.5\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 420.0\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 421.5\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 477.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 486.2\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 487.8\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 489.3\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 492.3\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 493.8\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 501.9\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 503.4\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 504.9\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 507.6\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 512.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 514.7\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 516.3\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 517.9\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 518.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 520.3\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 526.3\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 548.3\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 549.8\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 629.8\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 634.3\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 875.8\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 881.6\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 889.4\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 1089.4\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 1093.9\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 1666.9\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 1671.4\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 1676.4\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 1684.4\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 1941.4\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 1944.8\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 1954.6\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 2108.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2116.3\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2131.3\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 2142.5\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 2447.4\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2788.6\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2870.1\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 2867.1\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 3467.1\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 3526.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 3520.7\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 4019.1\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 4319.1\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 4490.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 4462.6\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 4662.6\ncenter_point:\n  - -106.50923943567419\n  - 39.42986049036256\ncentroid:\n  - -105.7788616855921\n  - 38.91579644601377\ncomment: Public Service Company Of Colorado\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 323.94\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1078.7421604341275\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1052.61822786813\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1041.816747591299\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1087.1965526428457\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 480.4971118923412\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 468.99710753062755\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 525.3410692589177\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 450.847303672373\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 356.94\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1138.7421604341275\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1112.61822786813\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1101.816747591299\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1147.1965526428457\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 600.4971118923412\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 588.9971075306275\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 645.3410692589177\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 570.8473036723731\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.39108484071304433\n        gas: 0.2952403071190413\n        geothermal: 0.0\n        hydro: 0.006119198629259448\n        hydro discharge: 0.011800759998538198\n        nuclear: 0.0\n        oil: 0.00014785274489151627\n        solar: 0.029330616319475093\n        unknown: 0.0\n        wind: 0.2662767009524721\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.3910863933238935\n        gas: 0.2952414792261041\n        geothermal: 0.0\n        hydro: 0.006119222922541086\n        hydro discharge: 0.01180080684767704\n        nuclear: 0.0\n        oil: 0.00014785333186843763\n        solar: 0.029326762699985305\n        unknown: 0.0\n        wind: 0.26627775807371984\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.690512380550921e-07\n        coal: 0.3592199337986433\n        gas: 0.29532983627556425\n        geothermal: 0.0\n        hydro: 0.005778193159144115\n        hydro discharge: 0.011419518067474611\n        nuclear: 3.317909265225015e-05\n        oil: 8.451424276657328e-06\n        solar: 0.04142843016661361\n        unknown: 0.006765764098936505\n        wind: 0.2800163344268481\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.226214131589916e-07\n        coal: 0.570229374204683\n        gas: 0.20106629233621184\n        geothermal: 0.0\n        hydro: 0.024886025752632844\n        hydro discharge: 0.006447979059498749\n        nuclear: 0.00037362604066883874\n        oil: 1.42761425006985e-05\n        solar: 0.02033401639831554\n        unknown: 0.003830145119888856\n        wind: 0.17281742316995982\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 9.269388774703598e-07\n        coal: 0.4976375329835031\n        gas: 0.2510075829297966\n        geothermal: 2.4665749799637033e-10\n        hydro: 0.030002293298087623\n        hydro discharge: 9.323653424262796e-08\n        nuclear: 0.000503419320398162\n        oil: 2.1677740868909e-05\n        solar: 0.02287105381147807\n        unknown: 2.4406759426740846e-05\n        wind: 0.19793087509948776\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.1010255045777316e-06\n        coal: 0.3480634978708961\n        gas: 0.35567093498465524\n        geothermal: 1.8594974472612433e-09\n        hydro: 0.023300776976545583\n        hydro discharge: 2.194206987768267e-07\n        nuclear: 0.0004066483314708744\n        oil: 1.978794539044426e-05\n        solar: 0.022885862559089146\n        unknown: 3.47963625089447e-05\n        wind: 0.2496152398129808\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 2.687835730066116e-09\n        biomass: 3.877926688701544e-06\n        coal: 0.4032529099801843\n        gas: 0.2638401826520838\n        geothermal: 8.973236206528418e-08\n        hydro: 0.015424544377212026\n        hydro discharge: 1.575485251007985e-07\n        nuclear: 0.0007772187148378106\n        oil: 3.6148495977064574e-05\n        solar: 0.029530822353059174\n        unknown: 5.2950363882302484e-05\n        wind: 0.2870809955106734\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 8.649343466772959e-10\n        biomass: 3.383839397788251e-06\n        coal: 0.3531069227201153\n        gas: 0.2663376477314487\n        geothermal: 1.1027912920135523e-08\n        hydro: 0.014351155666296323\n        hydro discharge: 8.467274786797388e-06\n        nuclear: 0.0008874926993729864\n        oil: 8.839845256628633e-06\n        solar: 0.03997932793937427\n        unknown: 4.561706991093392e-05\n        wind: 0.32527104726022577\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.155926352418996e-09\n        biomass: 5.674442464024852e-06\n        coal: 0.29908930820878177\n        gas: 0.30457826286999823\n        geothermal: 1.664533947483354e-08\n        hydro: 0.006233661138503523\n        hydro discharge: 9.627063270540461e-05\n        nuclear: 0.001001552388053439\n        oil: 5.149189529485659e-06\n        solar: 0.08238639648109145\n        unknown: 0.00015659958496450446\n        wind: 0.3064469544491784\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.5081\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.5064\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Mountain\nzone_name: Public Service Company of Colorado\nzone_short_name: PSCo\n"
  },
  {
    "path": "config/zones/US-NW-PSEI.yaml",
    "content": "bounding_box:\n  - - -123.20575860017632\n    - 46.73649197083546\n  - - -120.2826028260282\n    - 48.991878515577795\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 37.9\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 32.5\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1677.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1696.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 335.8\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 347.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 340.5\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 5.4\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 5.5\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 10.5\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 15.5\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 366.9\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 502.9\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 868.4\ncenter_point:\n  - -121.72261722617219\n  - 47.96436104151371\ncentroid:\n  - -122.04414089782469\n  - 47.736102970250556\ncomment: Puget Sound Energy\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\n  - miniksa\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 325.38772042741823\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 388.89681040704664\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 383.5930609522924\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 395.57659664427666\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 445.38772042741823\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 508.89681040704664\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 503.5930609522924\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 515.5765966442766\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1976975560769997\n        gas: 0.4633696836478343\n        geothermal: 0.0\n        hydro: 0.23150998466906786\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0005105059017105918\n        solar: 0.0011718717086126617\n        unknown: 0.01411175710668211\n        wind: 0.09162811031212982\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.19769761593856183\n        gas: 0.46336982395322635\n        geothermal: 0.0\n        hydro: 0.23151005476881825\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0005105060562885308\n        solar: 0.0011715691013479653\n        unknown: 0.014111761379632375\n        wind: 0.09162813805653865\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.16062873033814642\n        gas: 0.5029302797493521\n        geothermal: 0.0\n        hydro: 0.21203058435663677\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 3.1364738465903946e-05\n        solar: 0.0018397329939668927\n        unknown: 0.016542423377201233\n        wind: 0.10599663841280975\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.00021298910833140867\n        biomass: 0.0003586881777351314\n        coal: 0.035624678285878286\n        gas: 0.2758559402526117\n        geothermal: 0.0006816315249421283\n        hydro: 0.48316715065490007\n        hydro discharge: 2.3916321443622667e-08\n        nuclear: 0.05027717164087208\n        oil: 0.0015433252577720109\n        solar: 0.012343861755240158\n        unknown: 0.023701468540557\n        wind: 0.11623287745634421\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 7.077620332132518e-08\n        biomass: 7.70193804781129e-06\n        coal: 0.13706180938546422\n        gas: 0.23993567029156068\n        geothermal: 4.657184336058095e-06\n        hydro: 0.4927984692626294\n        hydro discharge: 2.8113023983077196e-05\n        nuclear: 0.04643720746890489\n        oil: 0.0007200316526162676\n        solar: 0.0005267239407495575\n        unknown: 0.023438620375077976\n        wind: 0.05904080600570443\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 2.463054563254408e-06\n        biomass: 9.686956025193024e-05\n        coal: 0.1433420349453882\n        gas: 0.23426209758746766\n        geothermal: 0.00016726937605722253\n        hydro: 0.4946133396726604\n        hydro discharge: 3.276540474054029e-07\n        nuclear: 0.043596445029926295\n        oil: 0.0014249320301069183\n        solar: 0.001464789786110308\n        unknown: 0.026063901700121427\n        wind: 0.054965269129018904\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 1.3923249844769349e-07\n        biomass: 1.9069707437506843e-05\n        coal: 0.06683531673044611\n        gas: 0.22759417683220634\n        geothermal: 5.634575220089915e-06\n        hydro: 0.5464595356257195\n        hydro discharge: 3.02259927346032e-08\n        nuclear: 0.041711510798923865\n        oil: 0.0005799663804450262\n        solar: 0.0008467432431924333\n        unknown: 0.04055253401544232\n        wind: 0.07539488892103138\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 6.17860390221158e-07\n        biomass: 3.1210218942688247e-05\n        coal: 0.0210082362465067\n        gas: 0.1955738050679178\n        geothermal: 2.7323677778393864e-05\n        hydro: 0.5672322953785534\n        hydro discharge: 2.7945778802727733e-07\n        nuclear: 0.05360462730700488\n        oil: 0.001163870868543928\n        solar: 0.0025178828653699237\n        unknown: 0.045612369500554584\n        wind: 0.1132269014319029\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 7.134554428112242e-06\n        biomass: 6.507091165081303e-05\n        coal: 0.024402508157677846\n        gas: 0.1566331155884334\n        geothermal: 8.460966323137813e-05\n        hydro: 0.6124575804684494\n        hydro discharge: 0.0\n        nuclear: 0.05926723739023872\n        oil: 0.0013326502606288387\n        solar: 0.004402848980341612\n        unknown: 0.04299202579835306\n        wind: 0.09835473320969919\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0002184078915148602\n        biomass: 0.00029603749013127354\n        coal: 0.02479391040701796\n        gas: 0.24598179698565614\n        geothermal: 0.0004985708257578328\n        hydro: 0.49626879187749123\n        hydro discharge: 2.1109781766357557e-08\n        nuclear: 0.06196602038240283\n        oil: 0.0006641579837198498\n        solar: 0.011671150973628582\n        unknown: 0.021450705959756258\n        wind: 0.13619023487744694\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  PSE 2023 IRP:\n    link: https://www.pse.com/en/IRP/Past-IRPs/2023-IRP\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Puget Sound Energy\n"
  },
  {
    "path": "config/zones/US-NW-SCL.yaml",
    "content": "bounding_box:\n  - - -122.4339658965978\n    - 47.46082968401358\n  - - -122.23721179834855\n    - 47.778030463903605\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4.6\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 5.0\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 3.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 0.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2007.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 2005.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1816.7\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2005.1\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 2046.2\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -122.33558884747318\n  - 47.6194300739586\ncentroid:\n  - -122.34031285770172\n  - 47.614746192254984\ncomment: Seattle City Light\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9999993425866456\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.9999999960447142\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: Seattle City Light\n"
  },
  {
    "path": "config/zones/US-NW-TPWR.yaml",
    "content": "bounding_box:\n  - - -123.50463504635039\n    - 46.38444559392771\n  - - -121.08901089010884\n    - 47.87563390587029\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 64.0\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 716.6\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -121.98710180807089\n  - 47.126620583694155\ncentroid:\n  - -122.3587856604095\n  - 47.242332938203425\ncomment: City Of Tacoma, Department Of Public Utilities, Light Division\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 3.672912232102265e-08\n        biomass: 0.0013992607309175715\n        coal: 0.020682164457894642\n        gas: 0.06409953464245231\n        geothermal: 4.2843440919169375e-06\n        hydro: 0.7966621731682277\n        hydro discharge: 4.380920078255156e-05\n        nuclear: 0.06046959980453886\n        oil: 0.0010267647750207955\n        solar: 0.0003008287961020325\n        unknown: 0.011878364519937474\n        wind: 0.04343324796808339\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 2.7250045477232012e-06\n        biomass: 0.0017003552394465663\n        coal: 0.038179991119817056\n        gas: 0.06321884018483369\n        geothermal: 0.00019999827773366138\n        hydro: 0.7753753365534319\n        hydro discharge: 5.604703676758199e-06\n        nuclear: 0.05789710066298885\n        oil: 0.0018645496546619983\n        solar: 0.0017543833136016423\n        unknown: 0.01258769244119953\n        wind: 0.04721317890260544\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 3.692026405335931e-09\n        biomass: 0.003027550261009191\n        coal: 0.009795121424610479\n        gas: 0.031852127106094544\n        geothermal: 1.5137308261877315e-06\n        hydro: 0.860365163379045\n        hydro discharge: 8.140918223765728e-07\n        nuclear: 0.04164166434076695\n        oil: 0.0006127028580447139\n        solar: 0.000780420541559909\n        unknown: 0.008731269553952538\n        wind: 0.04319146441892162\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 3.9931485593485806e-07\n        biomass: 0.0022749532582815894\n        coal: 0.016036258518261085\n        gas: 0.038851231330207125\n        geothermal: 1.907229859853249e-05\n        hydro: 0.8394284145158062\n        hydro discharge: 1.8379423506042785e-06\n        nuclear: 0.041812614119262764\n        oil: 0.0008949047059711612\n        solar: 0.0020376453624593714\n        unknown: 0.009294113442615538\n        wind: 0.04934787325637071\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 4.817253135032609e-06\n        biomass: 0.001751440307956229\n        coal: 0.017769443988672893\n        gas: 0.034554073803194266\n        geothermal: 5.3792660007864126e-05\n        hydro: 0.8439667923272733\n        hydro discharge: 8.999264098412565e-08\n        nuclear: 0.04384494758506557\n        oil: 0.0008997781866678708\n        solar: 0.0027559928680302654\n        unknown: 0.008022648077398541\n        wind: 0.04637599414186727\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.00016241637575713862\n        biomass: 0.00039655851732184956\n        coal: 0.032594452499541675\n        gas: 0.06526584648280792\n        geothermal: 0.0006225993218853018\n        hydro: 0.7457518213855023\n        hydro discharge: 3.047645824283023e-07\n        nuclear: 0.05488000188722574\n        oil: 0.0013346161864771153\n        solar: 0.010409492784066799\n        unknown: 0.01329162443563458\n        wind: 0.07528960567889836\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Pacific\nzone_name: City of Tacoma\n"
  },
  {
    "path": "config/zones/US-NW-WACM.yaml",
    "content": "bounding_box:\n  - - -111.30411304113035\n    - 36.99299649965343\n  - - -96.45036450364498\n    - 47.57510651094904\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 4.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 8.2\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 10.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 6.3\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 37.7\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 49.5\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 61.3\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 69.1\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 104.5\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 108.5\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3.2\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 4.8\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 3.2\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6432.4\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 6432.7\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 6318.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 6186.6\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 5929.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 6007.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 6082.6\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 6007.6\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 5625.1\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1798.5\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1813.3\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 1811.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1946.6\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 1928.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2003.0\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 1995.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1915.5\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 1783.2\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1340.2\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 1585.3\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 1590.3\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 1671.6\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 1725.8\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 1752.9\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 1716.8\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 679.7\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 682.1\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 704.1\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 698.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 704.1\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 208.5\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 21.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 72.0\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 75.5\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 77.0\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 78.5\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 80.0\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 84.0\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 122.5\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 124.6\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 184.6\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 192.2\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 197.2\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 199.2\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 205.2\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 210.2\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 219.2\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 227.7\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 234.9\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 236.9\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 243.9\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 256.2\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 259.3\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 414.3\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 416.3\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 544.3\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 549.4\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 572.3\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 652.3\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 661.8\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 775.5\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 10.6\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 11.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 10.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 12.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 7.9\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 375\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 400\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 550\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 800\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1100\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1300\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1400\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 1500\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1900\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 1857.3\ncenter_point:\n  - -103.06439832839291\n  - 41.46969264806815\ncentroid:\n  - -104.25116534030634\n  - 40.497833722528355\ncomment: Western Area Power Administration - Rocky Mountain Region\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1107.615308189345\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1076.4273735741049\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1094.927576530494\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1107.2657286711817\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 451.71503142731837\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 521.1324027607403\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 471.6847263350428\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 455.87998325889254\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 695.25\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 671.46\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 953.0188557505772\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 938.8752567850639\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 927.2427781942617\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 914.8824271853546\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1167.615308189345\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1136.4273735741049\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1154.927576530494\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1167.2657286711817\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 571.7150314273183\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 641.1324027607403\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 591.6847263350428\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 575.8799832588925\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 719.25\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 695.46\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1197.0188557505771\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1182.8752567850638\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1171.2427781942617\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1158.8824271853546\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2206717959267389\n        gas: 0.01471379089719616\n        geothermal: 0.0\n        hydro: 0.06296408881644881\n        hydro discharge: 0.669613498708566\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0016737800965772663\n        unknown: 0.0\n        wind: 0.03036316468062711\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.22067183986329889\n        gas: 0.014713793826765627\n        geothermal: 0.0\n        hydro: 0.06296410135282869\n        hydro discharge: 0.6696136320310574\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.001673581276554992\n        unknown: 0.0\n        wind: 0.03036317072604401\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.3382474812112105e-06\n        coal: 0.6429813885760366\n        gas: 0.05580472043215265\n        geothermal: 0.0\n        hydro: 0.18472729106640687\n        hydro discharge: 0.0\n        nuclear: 0.0006176655799712646\n        oil: 1.6092597758117802e-05\n        solar: 0.011785370802358884\n        unknown: 1.9291439802795242e-05\n        wind: 0.10404492551101918\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.7086069259014576e-06\n        coal: 0.6221233997397673\n        gas: 0.13995649016986897\n        geothermal: 4.384886327777568e-08\n        hydro: 0.1674425656728364\n        hydro discharge: 1.2881543206345416e-05\n        nuclear: 0.002533058941387381\n        oil: 7.702084155357924e-05\n        solar: 0.003498889664251982\n        unknown: 0.00010506344244438187\n        wind: 0.06424772812955327\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.1521169970887884e-06\n        coal: 0.648625484138566\n        gas: 0.05886693941772327\n        geothermal: 2.864780101886972e-08\n        hydro: 0.20911846862154615\n        hydro discharge: 8.358878927423632e-08\n        nuclear: 0.0030858069127670507\n        oil: 0.0001328225861567615\n        solar: 0.004750795131588457\n        unknown: 0.0001428143897422607\n        wind: 0.0752744859327624\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.358280491046782e-06\n        coal: 0.668244416289401\n        gas: 0.02268303121328961\n        geothermal: 2.2224936380841797e-08\n        hydro: 0.20754818559749516\n        hydro discharge: 1.1510664967244312e-06\n        nuclear: 0.0009953484060110792\n        oil: 0.0001399198651026371\n        solar: 0.007428447919308308\n        unknown: 0.00019802788730936382\n        wind: 0.09275796669791084\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 1.3804975727401427e-08\n        biomass: 1.3229912207256865e-05\n        coal: 0.6647132766938187\n        gas: 0.0293500233476652\n        geothermal: 2.933557342072803e-07\n        hydro: 0.17325257566334634\n        hydro discharge: 2.050038895519112e-06\n        nuclear: 0.003166702674645022\n        oil: 6.334628815263885e-05\n        solar: 0.007703288621317782\n        unknown: 0.0003247163250050216\n        wind: 0.12141026800289628\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 2.0633451388385635e-08\n        biomass: 5.85085043492065e-06\n        coal: 0.6586650337657309\n        gas: 0.05151091836021367\n        geothermal: 1.9040693737352356e-07\n        hydro: 0.139114151155513\n        hydro discharge: 0.0\n        nuclear: 0.002042632773548377\n        oil: 7.434341132347913e-05\n        solar: 0.008773692851053672\n        unknown: 0.00015759721573336375\n        wind: 0.13965540097451604\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 6.815736617704599e-08\n        biomass: 1.0717562612614199e-05\n        coal: 0.5937385347675701\n        gas: 0.09285386681209015\n        geothermal: 1.5335407389835346e-06\n        hydro: 0.15521344788865796\n        hydro discharge: 1.024375898644796e-05\n        nuclear: 0.0031445577150002895\n        oil: 7.718638500824174e-06\n        solar: 0.02100439082504936\n        unknown: 0.0002758684053514039\n        wind: 0.13373881191154424\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 7.291817558303245e-08\n        biomass: 6.598934277542888e-06\n        coal: 0.5261965831175094\n        gas: 0.09832301411373753\n        geothermal: 2.1339006184937642e-06\n        hydro: 0.15474125400417635\n        hydro discharge: 1.709883033605646e-06\n        nuclear: 0.003139522244919113\n        oil: 3.1987629623605157e-06\n        solar: 0.04683928497071764\n        unknown: 0.0027340384044213656\n        wind: 0.1680123086368647\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2023-01-01'\n      value: 0.3102\n    - datetime: '2025-01-01'\n      value: 0.3325\nisRenewable:\n  hydro discharge:\n    - datetime: '2023-01-01'\n      value: 0.3041\n    - datetime: '2025-01-01'\n      value: 0.3325\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Mountain\nzone_name: Western Area Power Administration - Rocky Mountain Region\nzone_short_name: WAPA Rocky Mountains\n"
  },
  {
    "path": "config/zones/US-NW-WAUW.yaml",
    "content": "bounding_box:\n  - - -112.82692826928263\n    - 44.99800807928961\n  - - -102.57402574025734\n    - 48.63410780733821\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 936.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 945.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 940.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 950.2\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 952.8\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 955.4\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 80.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 77.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 77.6\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 71.4\ncenter_point:\n  - -107.7338772905498\n  - 46.92392322871979\ncentroid:\n  - -107.17404954367677\n  - 46.82277719237385\ncomment: Western Area Power Administration Ugp West\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 1.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.5224406182091784e-05\n        coal: 0.37007776215157645\n        gas: 0.04622041410235731\n        geothermal: 0.0\n        hydro: 0.5109504172434508\n        hydro discharge: 3.785132703636088e-06\n        nuclear: 0.006346851587247236\n        oil: 0.010963920194398069\n        solar: 0.001301643673477635\n        unknown: 0.00043532425911608705\n        wind: 0.053642458699357465\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.48723747822273e-05\n        coal: 0.3297197317383347\n        gas: 0.0592433639052312\n        geothermal: 2.1807899360219943e-06\n        hydro: 0.48801850731054686\n        hydro discharge: 2.842377894141026e-06\n        nuclear: 0.011641411975722174\n        oil: 0.014534940420328882\n        solar: 0.0016067888725806098\n        unknown: 0.0009700839726641657\n        wind: 0.09419174779286907\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00021468028806646648\n        coal: 0.2750859901161431\n        gas: 0.05660759997766934\n        geothermal: 0.0\n        hydro: 0.5072277595847701\n        hydro discharge: 5.7767239116969536e-05\n        nuclear: 0.014043035541462887\n        oil: 0.014860378123013194\n        solar: 0.002103771671118713\n        unknown: 0.0014003109289719494\n        wind: 0.128395614091856\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00017040115403605896\n        coal: 0.26078404655655046\n        gas: 0.09529961585261798\n        geothermal: 5.876728989137732e-07\n        hydro: 0.41819884085238623\n        hydro discharge: 1.2712923935685703e-06\n        nuclear: 0.027852097411172554\n        oil: 0.004817886345188723\n        solar: 0.0016196265094063586\n        unknown: 0.0015695783664029471\n        wind: 0.18968466875463252\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.222385662663065e-05\n        coal: 0.07691243822881694\n        gas: 0.030120998390783027\n        geothermal: 0.0\n        hydro: 0.8418210541921771\n        hydro discharge: 0.0\n        nuclear: 0.010813045721729711\n        oil: 0.00024269304851480054\n        solar: 0.00022303551181522994\n        unknown: 0.00030076531342116563\n        wind: 0.03950394581282464\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00011413913387962398\n        coal: 0.253474699612927\n        gas: 0.09428548589983757\n        geothermal: 0.0\n        hydro: 0.3883408301976705\n        hydro discharge: 0.0\n        nuclear: 0.025870066828780052\n        oil: 0.004251226814807025\n        solar: 0.0015998706766742915\n        unknown: 0.0010367770145430762\n        wind: 0.23102261220530515\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 6.942317326680212e-08\n        biomass: 0.00019549565591931483\n        coal: 0.17835174212742458\n        gas: 0.11723108450352292\n        geothermal: 3.272806739720672e-07\n        hydro: 0.4239557254704251\n        hydro discharge: 5.9505577085830396e-08\n        nuclear: 0.03192146929980829\n        oil: 0.0037996393664500717\n        solar: 0.002805509442865646\n        unknown: 0.0008318185444866423\n        wind: 0.24090125758590733\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Mountain\nzone_name: Western Area Power Administration - Upper Great Plains West\nzone_short_name: WAPA Upper Great Plains\n"
  },
  {
    "path": "config/zones/US-NY-NYIS.yaml",
    "content": "bounding_box:\n  - - -79.78587755694078\n    - 40.58999120327944\n  - - -72.06482694841942\n    - 45.01060607428772\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 20.0\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 21.0\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 26.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 28.0\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 33.0\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 53.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 60.0\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 63.0\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 68.1\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 71.1\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 73.1\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 83.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 115.8\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 125.8\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 130.8\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 131.8\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 137.8\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 162.5\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 163.2\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 176.8\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 196.8\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 216.8\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 227.3\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 229.3\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 228.3\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 238.5\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 241.5\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 249.5\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 243.5\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 253.5\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 250.5\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 260.5\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 262.5\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 268.1\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 558.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 516.3\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 513.1\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 511.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 508.5\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 506.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 451.4\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 446.6\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1098.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 930.8\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 775.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 655.1\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 23705.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 23873.2\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 24775.2\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 24776.7\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 24920.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 24990.7\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 26303.2\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 26302.9\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 26308.9\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 26305.1\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 26307.1\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 26314.6\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 26349.5\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 26345.3\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 26347.3\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 26355.7\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 25725.9\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 25730.9\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 25675.9\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 25685.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 26305.1\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 25777.3\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 25777.0\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 25728.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 25775.0\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 25800.2\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 25781.7\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 25778.1\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4660.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 4670.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 4651.9\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 4653.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 4599.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 4589.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 4617.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 4353.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 4272.5\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 4081.2\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 4113.4\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1240.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1220.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 5709.4\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 4410.4\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 3398.4\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3642.7\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 3645.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 3622.7\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 3606.4\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 3660.4\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 3608.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 3512.3\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 3507.2\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 4098.0\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 4065.4\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 3444.4\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 3423.1\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 3483.6\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 3486.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 3488.5\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 114.2\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 116.2\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 121.2\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 123.0\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 125.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 161.0\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 163.0\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 173.0\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 178.4\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 188.0\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 232.3\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 235.8\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 237.3\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 239.1\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 243.9\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 261.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 297.5\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 307.7\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 318.8\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 320.8\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 333.0\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 334.7\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 358.7\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 370.7\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 384.8\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 406.7\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 475.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 537.7\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 554.4\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 563.4\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 567.8\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 571.3\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 575.3\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 582.3\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 584.3\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 594.3\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 599.3\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 664.1\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 694.9\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 698.4\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 708.4\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 713.4\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 718.4\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 730.3\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 731.3\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 741.3\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 765.0\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 792.2\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 856.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1028.8\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 1033.8\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 1069.1\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 1079.4\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 1099.4\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 1130.9\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 1137.4\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 1160.3\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 1171.0\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 1216.6\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 1226.1\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 1276.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1366.5\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 1373.9\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 1428.9\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 1430.4\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 1432.4\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 1454.6\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 1471.1\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 1494.6\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 1512.8\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 1518.8\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 1564.8\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 1599.2\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 1628.5\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 1688.1\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 1695.1\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 1730.8\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 1799.0\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 1828.4\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 1837.2\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 1947.9\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 1955.9\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 1980.9\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 2207.7\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 2340.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 2359.9\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 2451.8\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 2461.4\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 2483.5\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 2590.4\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 2605.9\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 2636.4\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 2651.4\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 2813.3\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2894.4\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 244.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1822.2\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 1823.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1824.9\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 1904.7\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 1984.6\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1990.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1988.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1985.4\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 2109.4\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 2189.1\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 2420.3\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 2526.3\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 2638.1\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 2745.6\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 2739.0\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 2869.0\ncenter_point:\n  - -76.24218291697775\n  - 43.02465560796782\ncentroid:\n  - -75.48417383731932\n  - 42.62337021879663\ncomment: New York Independent System Operator\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\n  - brandongalbraith\n  - alejandranavcas\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1095.5785620809695\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 412.8877102227465\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 412.8088445158036\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 419.59471382500686\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 421.90534715307166\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 662.057614498095\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 503.5012255171227\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 660.944095982844\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 779.7224473492394\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1155.5785620809695\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 532.8877102227465\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 532.8088445158037\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 539.5947138250069\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 541.9053471530717\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 906.057614498095\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 747.5012255171227\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 904.944095982844\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1023.7224473492394\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 27.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.48519719803736144\n        geothermal: 0.0\n        hydro: 0.2151846369204856\n        hydro discharge: 0.0\n        nuclear: 0.24631404516828156\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.019219428627274007\n        wind: 0.03408477747852106\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.48519719803736144\n        geothermal: 0.0\n        hydro: 0.21518463692048556\n        hydro discharge: 0.0\n        nuclear: 0.24631404516828156\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.019219428627274007\n        wind: 0.03408477747852107\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0\n        gas: 0.48878730292560985\n        geothermal: 0.0\n        hydro: 0.21772288699742232\n        hydro discharge: 0.0\n        nuclear: 0.23700175300500906\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.019220103157980256\n        wind: 0.03726754944992021\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 3.9583255030511154e-07\n        biomass: 0.0011089866458034961\n        coal: 0.00036785687011022417\n        gas: 0.45946959606238397\n        geothermal: 0.0\n        hydro: 0.24681463666570416\n        hydro discharge: 1.5622503612633696e-07\n        nuclear: 0.2357435169777839\n        oil: 5.993232720240944e-06\n        solar: 7.102297751819688e-05\n        unknown: 0.018023117322037683\n        wind: 0.03839452007106383\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 7.144637938063987e-07\n        biomass: 0.001971485258344278\n        coal: 0.0025995222373694712\n        gas: 0.4313528605955694\n        geothermal: 0.0\n        hydro: 0.27083239404911835\n        hydro discharge: 1.395700209996801e-06\n        nuclear: 0.23630960885265567\n        oil: 2.1786108981909026e-05\n        solar: 0.00022366693506945453\n        unknown: 0.01682375063543507\n        wind: 0.039862805315519514\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 3.453816359558061e-07\n        biomass: 0.0016646572223021014\n        coal: 0.010981029571201457\n        gas: 0.39626275999907906\n        geothermal: 0.0\n        hydro: 0.2555512508295311\n        hydro discharge: 5.891438639675826e-06\n        nuclear: 0.28223165062708166\n        oil: 0.00013710277619872268\n        solar: 0.0004131295932624466\n        unknown: 0.016864826633641167\n        wind: 0.03588735196459088\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 4.300710108699191e-06\n        biomass: 0.0020705238314205083\n        coal: 0.019485489124540865\n        gas: 0.4222523877737683\n        geothermal: 0.0\n        hydro: 0.25326674300243535\n        hydro discharge: 8.917566998550378e-06\n        nuclear: 0.2499992297321197\n        oil: 0.00023569951427754348\n        solar: 0.000779859282236882\n        unknown: 0.015938090093270258\n        wind: 0.03595874593668033\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 6.625863147853202e-06\n        biomass: 0.0020532168891286996\n        coal: 0.01839409568209285\n        gas: 0.4613624810598794\n        geothermal: 0.0\n        hydro: 0.23914875113246845\n        hydro discharge: 2.6821930464795772e-08\n        nuclear: 0.22048860214681626\n        oil: 0.0002792792495529887\n        solar: 0.0009660705337331437\n        unknown: 0.016546666278552464\n        wind: 0.040754178288232634\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 8.418949329473694e-06\n        biomass: 0.001095303619353748\n        coal: 0.006295767368240834\n        gas: 0.47691329893294765\n        geothermal: 0.0\n        hydro: 0.22877586186064777\n        hydro discharge: 1.4810620873748668e-10\n        nuclear: 0.22886327518178814\n        oil: 0.00013489061767873634\n        solar: 0.000687284047628341\n        unknown: 0.01756555009051059\n        wind: 0.03966033748337813\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: US_NY.fetch_consumption_forecast\n  gridAlerts: US_NY.fetch_grid_alerts\n  production: US_NY.fetch_production\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: New York ISO\n"
  },
  {
    "path": "config/zones/US-SE-SEPA.yaml",
    "content": "bounding_box:\n  - - -85.61569\n    - 30.211187\n  - - -83.357543\n    - 33.075117\ncan_have_zero_production: true\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 1.7\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 945.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 996.9\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 328.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 246.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 164.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 82.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 22.0\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 25.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 25.0\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 275.0\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 415.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncomment: Southeastern Power Administration\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.54956423174013\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 403.07062959378845\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 409.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 411.26540305697193\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2014-01-01'\n        source: IPCC 2014\n        value: 490.0\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.5495642317401\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 523.0706295937885\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 529.3455569635937\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 531.265403056972\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.0654790569883904\n        gas: 0.06621268634586248\n        geothermal: 0.0\n        hydro: 0.32236638575904847\n        hydro discharge: 0.4659870174349138\n        nuclear: 0.0733624232507706\n        oil: 1.5648401611370587e-05\n        solar: 0.0017949988595360993\n        unknown: 0.00475584479815969\n        wind: 2.4684802541880363e-05\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.07110478011070599\n        gas: 0.07527195659159772\n        geothermal: 0.0\n        hydro: 0.37402340261590444\n        hydro discharge: 0.4065080430864732\n        nuclear: 0.06815007938357844\n        oil: 4.519818958727871e-06\n        solar: 0.0014417764903869145\n        unknown: 0.0034734325702546883\n        wind: 1.804368670925221e-05\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1923669613108413\n        gas: 0.22171642751517148\n        geothermal: 0.0\n        hydro: 0.36362557691271014\n        hydro discharge: 0.019596727993225604\n        nuclear: 0.1845831753852683\n        oil: 6.962755074610228e-06\n        solar: 0.0021282342804857593\n        unknown: 0.01589177064799634\n        wind: 7.727222513214341e-05\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.11983416376113655\n        gas: 0.13025380813943907\n        geothermal: 0.0\n        hydro: 0.5845421929111513\n        hydro discharge: 0.021964647031286876\n        nuclear: 0.13255791393899324\n        oil: 2.7797945617188185e-06\n        solar: 0.0033196765178860436\n        unknown: 0.00747627180258071\n        wind: 3.5908067895192577e-05\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2665463132918476\n        gas: 0.273930474101267\n        geothermal: 0.0\n        hydro: 0.11426288221336796\n        hydro discharge: 0.01696154362716569\n        nuclear: 0.30736423870707796\n        oil: 9.625285400904331e-06\n        solar: 0.0035333751175180192\n        unknown: 0.01722679858530689\n        wind: 7.565922012803868e-05\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.2345334918665681\n        gas: 0.290079156530295\n        geothermal: 0.0\n        hydro: 0.10640513884201715\n        hydro discharge: 0.07513754971590786\n        nuclear: 0.27338993374184445\n        oil: 9.679060537478818e-06\n        solar: 0.002634992244139461\n        unknown: 0.017504434329598056\n        wind: 0.00027594121677757796\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.24664446721864947\n        gas: 0.26008085923142893\n        geothermal: 0.0\n        hydro: 0.14952994170538178\n        hydro discharge: 0.06712776869186393\n        nuclear: 0.2588154431581557\n        oil: 2.636103424276741e-06\n        solar: 0.003077153777525404\n        unknown: 0.014598611119213888\n        wind: 0.00011062991419915504\ngeneration_only: true\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Southeastern Power Administration\n"
  },
  {
    "path": "config/zones/US-SE-SOCO.yaml",
    "content": "bounding_box:\n  - - -90.00630006300058\n    - 29.74524549512121\n  - - -80.77940779407788\n    - 34.987301912247574\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1.0\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 2.2\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 42.2\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 82.2\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 81.2\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 82.7\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 83.7\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 148.7\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1758.8\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 1813.8\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 1868.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1848.7\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1925.4\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 1908.2\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 1932.9\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 1871.9\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 1987.9\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1975.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1917.5\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1898.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1898.9\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 1891.8\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 1878.8\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 1882.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1872.7\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 1881.2\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 1878.0\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 1776.8\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 17522.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 18462.1\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 17295.4\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 16164.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 15029.7\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 14138.7\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 12234.7\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 35594.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 34715.8\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 34607.0\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 34614.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 34767.5\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 34817.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 34829.7\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 34830.3\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 35949.5\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 36921.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 37167.0\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 37168.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 37573.0\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 37601.8\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 37606.8\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 38339.5\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 39113.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 36372.2\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 36251.2\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 38992.5\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 36251.2\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 36233.7\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3225.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 3311.4\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 3310.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 3309.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 3317.6\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1056.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1306.6\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 5818.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 6054.4\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 7168.4\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 8282.4\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1132.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1188.3\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 1188.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2069.7\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 2001.3\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1387.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 1346.1\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 1387.9\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 1346.1\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 1349.9\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 957.1\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 967.7\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 971.2\n    - datetime: '2017-06-01'\n      source: EIA.gov\n      value: 1053.2\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 1060.6\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 1063.0\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 1113.0\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 1205.9\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 1286.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1292.6\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 1323.6\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 1326.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1339.5\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 1340.5\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 1342.8\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 1346.5\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 1350.8\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 1354.4\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 1458.3\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 1878.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1892.4\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 2063.8\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 2069.5\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 2161.7\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 2170.4\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 2222.9\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 2500.9\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 2504.4\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 2524.4\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 2635.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 2639.2\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 2767.2\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 2770.1\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 3657.1\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 3674.9\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 3870.4\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 3876.0\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 4220.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 4221.8\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 4321.8\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 4324.8\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 4416.8\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 4496.8\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 4536.8\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 4645.3\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 4648.3\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 4650.2\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 4658.1\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 4893.6\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 4670.1\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 4828.6\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 4908.6\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 4918.6\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 4923.5\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 5073.5\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 5352.0\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 5470.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 5746.9\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 5970.4\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 5746.9\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 5745.9\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 5744.9\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 5824.9\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 45.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 45.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\ncenter_point:\n  - -85.48180948658279\n  - 32.559201385486254\ncentroid:\n  - -85.28725940904894\n  - 32.164450602652266\ncomment: Southern Company Services, Inc. - Trans\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\n  - MisterClean\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 385.57\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 867.1160983983897\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 872.6874296995918\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 865.3097109319093\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1039.9273282774575\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 406.06689068673234\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 396.88877958385467\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 404.79442413927694\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 424.35485209409916\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 387.01\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 569.2843707617432\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 554.5699717082107\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 362.1182499048772\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 250.47181242406236\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 418.57\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 927.1160983983897\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 932.6874296995918\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 925.3097109319093\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1099.9273282774575\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 526.0668906867323\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 516.8887795838547\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 524.794424139277\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 544.3548520940992\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 411.01\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 813.2843707617432\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 798.5699717082107\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 606.1182499048772\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 494.47181242406236\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.20991751771719439\n        gas: 0.5170751263531372\n        geothermal: 0.0\n        hydro: 0.04433604659129754\n        hydro discharge: 0.0\n        nuclear: 0.19818868985985666\n        oil: 5.219349322086551e-05\n        solar: 0.020476561670608413\n        unknown: 0.00992882226058571\n        wind: 2.4930033104630298e-05\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.20991766424731897\n        gas: 0.5170754872905354\n        geothermal: 0.0\n        hydro: 0.04433607753948376\n        hydro discharge: 0.0\n        nuclear: 0.1981888282028293\n        oil: 5.219352965383759e-05\n        solar: 0.020475877945474875\n        unknown: 0.009928829191267714\n        wind: 2.493005050670753e-05\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.1483723833030185e-10\n        coal: 0.19648613683333016\n        gas: 0.5117464024730168\n        geothermal: 0.0\n        hydro: 0.046697371878498414\n        hydro discharge: 0.0021152328369741682\n        nuclear: 0.2100103568976472\n        oil: 0.0001216742730169011\n        solar: 0.02267876907631403\n        unknown: 0.009909986907808383\n        wind: 0.00023404398820916448\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.747750166659991e-08\n        coal: 0.2774827672472431\n        gas: 0.46658094097976877\n        geothermal: 0.0\n        hydro: 0.04453890326745629\n        hydro discharge: 0.0015251142036424726\n        nuclear: 0.1943632950747425\n        oil: 0.00010107317832199923\n        solar: 0.00917042076793575\n        unknown: 0.006061179061926319\n        wind: 0.0001762100277668118\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.073010566132406e-08\n        coal: 0.22640392897930603\n        gas: 0.504658585579516\n        geothermal: 0.0\n        hydro: 0.050465964836702085\n        hydro discharge: 0.00033725427600555483\n        nuclear: 0.19818960244370276\n        oil: 5.8244030558997403e-05\n        solar: 0.011257094421811062\n        unknown: 0.008439041074614443\n        wind: 0.00019015137595267226\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.636643041796521e-08\n        coal: 0.16517744652719155\n        gas: 0.5332215174188785\n        geothermal: 0.0\n        hydro: 0.059128706665264284\n        hydro discharge: 0.0004000014045687904\n        nuclear: 0.2107704610991511\n        oil: 2.851859159817431e-05\n        solar: 0.0196035666937495\n        unknown: 0.011492730724367298\n        wind: 0.00017695020869450248\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.1827977897063863e-08\n        coal: 0.2075532698498857\n        gas: 0.4961271712453573\n        geothermal: 0.0\n        hydro: 0.04867717131884271\n        hydro discharge: 0.00039817829853722284\n        nuclear: 0.21285808221198924\n        oil: 2.4397303825135722e-05\n        solar: 0.02288165371748535\n        unknown: 0.011132746824234258\n        wind: 0.00034662648657174497\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.49004431065841e-08\n        coal: 0.18990692491543876\n        gas: 0.5196637099544391\n        geothermal: 4.163827518714278e-10\n        hydro: 0.04411110423028898\n        hydro discharge: 2.644213682794389e-05\n        nuclear: 0.20312260304649637\n        oil: 0.00016657312875893615\n        solar: 0.031225810573232638\n        unknown: 0.011123276314754946\n        wind: 0.0006528931931656963\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.2234518413085014e-08\n        coal: 0.15955033332999508\n        gas: 0.529227743374339\n        geothermal: 0.0\n        hydro: 0.0396979172959332\n        hydro discharge: 1.2489804316954948e-05\n        nuclear: 0.22676932145870837\n        oil: 2.3553723240714526e-05\n        solar: 0.03388584704198945\n        unknown: 0.010455775763807308\n        wind: 0.00037636503223176254\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.3413\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 0.3422\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.0659\n  hydro discharge:\n    - datetime: '2025-01-01'\n      value: 0.0605\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Eastern\nzone_name: Southern Company Services\n"
  },
  {
    "path": "config/zones/US-SW-AZPS.yaml",
    "content": "bounding_box:\n  - - -114.8177481774817\n    - 31.33374743970495\n  - - -109.27729277292767\n    - 36.14218575844494\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 2.0\n    - datetime: '2023-02-01'\n      source: EIA.gov\n      value: 62.0\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 200.0\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 260.0\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 320.0\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 535.0\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 617.0\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 984.0\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 1743.8\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 2161.8\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 2236.8\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 2349.8\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 33.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 30.4\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2476.1\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 2062.1\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 1636.2\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2124.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1897.2\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 2544.8\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 2714.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 2605.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2416.5\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 2602.5\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 123.8\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 694.9\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 734.9\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 737.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 740.0\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 741.4\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 767.4\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 769.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 757.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 772.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 771.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 766.9\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 826.9\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 978.3\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 1193.3\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1195.7\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 1193.8\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 1563.8\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 2189.3\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 2489.3\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 174.3\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 412.5\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 628.5\ncenter_point:\n  - -112.12828211789612\n  - 34.39885067236607\ncentroid:\n  - -111.98417237712306\n  - 33.36208835383213\ncomment: Arizona Public Service Company\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 406.44\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 266.98\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1055.103823874164\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1030.782226173178\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 991.2994370558566\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1003.8223333180867\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 371.36562029179186\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 362.6564678883666\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 394.6192180069698\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 335.1262756050809\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 439.44\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 299.98\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1115.103823874164\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1090.782226173178\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1051.2994370558567\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1063.8223333180867\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 491.36562029179186\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 482.6564678883666\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 514.6192180069697\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 455.1262756050809\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.24099398394415494\n        gas: 0.27045967294492\n        geothermal: 0.0\n        hydro: 0.00017026247081268955\n        hydro discharge: 0.0\n        nuclear: 0.43044470620782926\n        oil: 0.00017170188783646834\n        solar: 0.042855302210168866\n        unknown: 0.007209834241104496\n        wind: 0.007693478361094166\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.24099524605429917\n        gas: 0.2704610893698915\n        geothermal: 0.0\n        hydro: 0.00017026336249466466\n        hydro discharge: 0.0\n        nuclear: 0.43044696049078424\n        oil: 0.00017170278705681765\n        solar: 0.04285028934537776\n        unknown: 0.007209871999743883\n        wind: 0.0076935186526272785\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 5.320326937452337e-07\n        biomass: 1.3153511874678578e-06\n        coal: 0.27444708251016725\n        gas: 0.3071945595799394\n        geothermal: 2.2698039760026706e-06\n        hydro: 9.163266671589326e-06\n        hydro discharge: 3.0327596548995406e-07\n        nuclear: 0.3356004375755746\n        oil: 2.878955415258207e-06\n        solar: 0.05171472118242661\n        unknown: 0.009445961463558373\n        wind: 0.021580958267757556\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 1.959506706570703e-08\n        biomass: 1.1354221646459184e-05\n        coal: 0.24393139177376735\n        gas: 0.19367789733339064\n        geothermal: 5.083520255903425e-06\n        hydro: 0.007231983593836387\n        hydro discharge: 0.00034674534904980726\n        nuclear: 0.5144511189821274\n        oil: 2.7747734683159196e-05\n        solar: 0.02930923170615232\n        unknown: 0.005309487770009862\n        wind: 0.005697683964071407\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 7.178104934888498e-10\n        biomass: 5.986898420943751e-06\n        coal: 0.20725256348915913\n        gas: 0.1934137309654899\n        geothermal: 1.097173339297707e-06\n        hydro: 0.008462205817132362\n        hydro discharge: 5.38347102959235e-05\n        nuclear: 0.5437795225630941\n        oil: 2.0965449988575583e-05\n        solar: 0.03496685653967319\n        unknown: 0.006240070899807762\n        wind: 0.005802954457313779\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 3.482523390589946e-07\n        biomass: 4.4066756338786266e-05\n        coal: 0.23479969514271165\n        gas: 0.46326031085775854\n        geothermal: 2.2141874030240446e-05\n        hydro: 0.01970263908785387\n        hydro discharge: 0.0008219200809792181\n        nuclear: 0.2099003745912108\n        oil: 4.689200792951105e-05\n        solar: 0.04834142302447459\n        unknown: 0.01073780628666682\n        wind: 0.012322199919654844\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 2.061389116377651e-06\n        biomass: 2.6717436699308803e-05\n        coal: 0.21710142322161796\n        gas: 0.40239864850017976\n        geothermal: 3.59143305653072e-05\n        hydro: 0.016955114232099198\n        hydro discharge: 0.0008229210788008039\n        nuclear: 0.28196817891795223\n        oil: 9.772312300324665e-06\n        solar: 0.04621984708602888\n        unknown: 0.010047491622998362\n        wind: 0.024411648087870316\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 1.1474178170068977e-05\n        biomass: 2.672892203210494e-05\n        coal: 0.24280202372431847\n        gas: 0.3897215223347283\n        geothermal: 3.9812917753057054e-05\n        hydro: 0.010702002873485493\n        hydro discharge: 9.614744940576139e-06\n        nuclear: 0.2609729574040785\n        oil: 1.5238770964157555e-05\n        solar: 0.04647173950945136\n        unknown: 0.008233605731124867\n        wind: 0.04099307406002725\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.5193082564903899e-05\n        biomass: 5.726584142767842e-05\n        coal: 0.18637802306874843\n        gas: 0.43094291017728187\n        geothermal: 9.952005327661556e-05\n        hydro: 0.010808759935755299\n        hydro discharge: 2.071568230766443e-05\n        nuclear: 0.2570442955029667\n        oil: 4.095309780411878e-06\n        solar: 0.05310475524020144\n        unknown: 0.009288429954751765\n        wind: 0.05223583306779387\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.2665\n    - datetime: '2025-01-01'\n      value: 0.5676\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.0196\n    - datetime: '2025-01-01'\n      value: 0.2838\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Arizona\nzone_name: Arizona Public Service Company\n"
  },
  {
    "path": "config/zones/US-SW-EPE.yaml",
    "content": "bounding_box:\n  - - -108.22901201954507\n    - 30.630950309039566\n  - - -104.84760623311561\n    - 33.47985722277469\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 1.0\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 51.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 126.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3.2\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1910.5\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1911.7\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1915.9\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 2143.7\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2093.7\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 2.1\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 114.5\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 117.5\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 119.5\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 124.5\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 127.3\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 126.8\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 129.8\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 249.8\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 251.3\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 261.3\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 564.3\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 579.3\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 50.4\ncenter_point:\n  - -106.55067756368078\n  - 32.22951090470256\ncentroid:\n  - -106.45210081678198\n  - 32.33387441098371\ncomment: El Paso Electric Company\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 984.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 992.9479158763683\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 545.8860297806025\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 564.574101597481\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 556.8931251172002\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 526.8511593887226\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1044.2045157721725\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1052.9479158763684\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 665.8860297806025\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 684.574101597481\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 676.8931251172002\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 646.8511593887226\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0\n        biomass: 0\n        coal: 0\n        gas: 0.9417706321553654\n        geothermal: 0\n        hydro: 0\n        hydro discharge: 0\n        nuclear: 0\n        oil: 0\n        solar: 0.058227941075081995\n        unknown: 0\n        wind: 0\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0\n        biomass: 0\n        coal: 0\n        gas: 0.9417707828037308\n        geothermal: 0\n        hydro: 0\n        hydro discharge: 0\n        nuclear: 0\n        oil: 0\n        solar: 0.05822779042648821\n        unknown: 0\n        wind: 0\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.5315642488530927e-06\n        coal: 0.00439138572992024\n        gas: 0.9255126759139227\n        geothermal: 0.0\n        hydro: 0.0004968254927239107\n        hydro discharge: 0.0\n        nuclear: 0.0005651551588843604\n        oil: 1.8923997627223597e-05\n        solar: 0.06730662233950956\n        unknown: 2.4970752612705857e-05\n        wind: 0.0016798518437861215\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.658163620942205e-06\n        coal: 0.1712703941633413\n        gas: 0.7144214242217384\n        geothermal: 3.830290939495131e-07\n        hydro: 0.004300708066037713\n        hydro discharge: 0.0018362337495822722\n        nuclear: 0.02649158913808259\n        oil: 1.5041894706772375e-05\n        solar: 0.0407686012361636\n        unknown: 0.0007168682008279249\n        wind: 0.0401724302493092\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 1.2921790941382155e-08\n        biomass: 4.3428964645718026e-06\n        coal: 0.16401446104877482\n        gas: 0.6911897691668535\n        geothermal: 2.477459735943179e-06\n        hydro: 0.007462207400155317\n        hydro discharge: 8.581243893345149e-06\n        nuclear: 0.030520292846266176\n        oil: 4.528500370820746e-06\n        solar: 0.05059654698945196\n        unknown: 0.0014204313933562356\n        wind: 0.054774986646004525\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 1.1559965965148204e-08\n        biomass: 4.3569511722643584e-06\n        coal: 0.1743656217247365\n        gas: 0.6771660674076643\n        geothermal: 3.507293673825966e-06\n        hydro: 0.007338407426260855\n        hydro discharge: 2.6705833372685384e-05\n        nuclear: 0.010063557270874683\n        oil: 5.514103765375693e-06\n        solar: 0.0615549263979857\n        unknown: 0.0019331615483857694\n        wind: 0.06753667471452231\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 1.3886318360995715e-07\n        biomass: 9.16728450465067e-06\n        coal: 0.1828475068498807\n        gas: 0.6527607840260246\n        geothermal: 1.2097297678820764e-05\n        hydro: 0.00629871481764839\n        hydro discharge: 4.853615425127027e-05\n        nuclear: 0.01980411757968363\n        oil: 3.294529031146233e-06\n        solar: 0.05957488978107995\n        unknown: 0.0015033328257613957\n        wind: 0.07713632412931448\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 1.7611163927069107e-06\n        biomass: 1.2533353205495164e-05\n        coal: 0.17690661260153157\n        gas: 0.6090327437396068\n        geothermal: 1.3537459107969636e-05\n        hydro: 0.007265377854659744\n        hydro discharge: 4.536447136570927e-06\n        nuclear: 0.020311921275518473\n        oil: 1.932847704215129e-05\n        solar: 0.06758798564734618\n        unknown: 0.0013763877126850882\n        wind: 0.11746639038808822\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.5123595851331105e-06\n        biomass: 2.3750944737412674e-05\n        coal: 0.0861686333897387\n        gas: 0.6695948923308611\n        geothermal: 1.7203227170786415e-05\n        hydro: 0.00648372318232732\n        hydro discharge: 5.096684655473928e-06\n        nuclear: 0.011576024075730803\n        oil: 1.6338083019986155e-05\n        solar: 0.09135509153496706\n        unknown: 0.0017100778771663165\n        wind: 0.13304699157269873\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Mountain\nzone_name: El Paso Electric Company\n"
  },
  {
    "path": "config/zones/US-SW-PNM.yaml",
    "content": "bounding_box:\n  - - -110.80730807308066\n    - 31.332316356872\n  - - -102.03175407765414\n    - 37.80081076184365\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 2.6\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 3.6\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 1.8\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 13.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 14.3\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 188.0\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 238.0\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 338.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 638.0\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 738.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 887.5\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 900.4\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 14.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 16.8\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 4.4\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 3.3\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1848.0\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 924.0\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 555.0\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1742.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1736.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1734.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 1584.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 1732.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1733.8\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4.0\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 19.2\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 150.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 151.2\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 163.1\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 164.1\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 174.1\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 177.1\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 187.1\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 195.1\n    - datetime: '2018-10-01'\n      source: EIA.gov\n      value: 197.1\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 198.1\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 208.1\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 218.1\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 229.3\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 239.3\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 307.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 309.4\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 311.8\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 314.9\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 369.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 369.5\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 372.0\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 422.0\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 471.5\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 486.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 436.5\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 486.5\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 544.0\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 594.0\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 894.0\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 1084.0\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 1284.0\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 1584.0\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 2084.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1784.0\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 2064.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 2069.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 2199.8\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1.1\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 496.4\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 794.4\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 845.3\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 1065.8\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 1230.8\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 1372.0\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 2424.0\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 2569.0\ncenter_point:\n  - -106.21269318854388\n  - 34.38777036219062\ncentroid:\n  - -106.53541157041239\n  - 34.919446822264426\ncomment: Public Service Company Of New Mexico\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\n  - brandongalbraith\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 351.27\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 281.32\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 185.67\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1202.4278014215604\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1205.8112087662323\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1200.756757313188\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1021.1805847188886\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 412.14997218452635\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 415.9584964953238\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 427.7389118754995\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 444.9483249442232\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 619.21\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 356.98\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 161.72\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 384.27\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 314.32\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 218.67\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1262.4278014215604\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1265.8112087662323\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1260.756757313188\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1081.1805847188884\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 532.1499721845264\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 535.9584964953237\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 547.7389118754995\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 564.9483249442233\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 643.21\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 380.98\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 185.72\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0\n        biomass: 0\n        coal: 0.38771715539485374\n        gas: 0.2724026841992751\n        geothermal: 0\n        hydro: 0.004573210109852285\n        hydro discharge: 0.07387535451744988\n        nuclear: 0\n        oil: 0\n        solar: 0.05226940404200543\n        unknown: 0.002975512255600611\n        wind: 0.20618827946450805\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0\n        biomass: 0\n        coal: 0.38771562214248273\n        gas: 0.2724042767725692\n        geothermal: 0\n        hydro: 0.004573214239360576\n        hydro discharge: 0.07387505809857528\n        nuclear: 3.98869848528616e-06\n        oil: 0\n        solar: 0.052266634712780737\n        unknown: 0.002975499125725628\n        wind: 0.20618730118981254\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.3345367262465077e-06\n        coal: 0.34955315481517907\n        gas: 0.3002072806922401\n        geothermal: 0.0\n        hydro: 0.0054444375514605195\n        hydro discharge: 2.665779926515112e-05\n        nuclear: 0.00023717273401559295\n        oil: 6.033080886323674e-06\n        solar: 0.06475253611710229\n        unknown: 0.004574836030821133\n        wind: 0.27519636627650196\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.0109258656233805e-06\n        coal: 0.45634247102638864\n        gas: 0.31221443715758673\n        geothermal: 5.601973645339924e-07\n        hydro: 0.010055589122786299\n        hydro discharge: 0.0004874402095396931\n        nuclear: 0.05687127602665254\n        oil: 8.806363461492245e-06\n        solar: 0.033021401461197954\n        unknown: 0.0016409056115582721\n        wind: 0.12935412611903657\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 1.613866469817994e-09\n        biomass: 1.7478173868128876e-06\n        coal: 0.41396637460794145\n        gas: 0.29846463038140747\n        geothermal: 6.253732570544726e-07\n        hydro: 0.015865986626372727\n        hydro discharge: 6.567629598924326e-06\n        nuclear: 0.06075776598597277\n        oil: 7.78690571687182e-06\n        solar: 0.040551445261805055\n        unknown: 0.004151400364039859\n        wind: 0.16622488470739671\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 2.2167570237718227e-08\n        biomass: 4.816330933571933e-06\n        coal: 0.4007956397951303\n        gas: 0.33941829896483044\n        geothermal: 2.8579113629550577e-06\n        hydro: 0.014034455826875047\n        hydro discharge: 4.799193696580467e-05\n        nuclear: 0.01485645235145873\n        oil: 1.1250894494497297e-05\n        solar: 0.06231980616274157\n        unknown: 0.004676425429609707\n        wind: 0.16383103840109423\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 1.8916000522319128e-07\n        biomass: 4.016469169200944e-06\n        coal: 0.42177638226892483\n        gas: 0.28458531385131175\n        geothermal: 4.5737701711365346e-06\n        hydro: 0.009187839905897053\n        hydro discharge: 5.4763093888830606e-05\n        nuclear: 0.018427091465411022\n        oil: 4.95633143730541e-06\n        solar: 0.060895239677347654\n        unknown: 0.003434810635651076\n        wind: 0.201623891142777\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 1.3260665057528825e-06\n        biomass: 5.327885528203057e-06\n        coal: 0.3642451152786013\n        gas: 0.2550484792242052\n        geothermal: 5.545522397467843e-06\n        hydro: 0.010982562938252272\n        hydro discharge: 9.899946890277246e-06\n        nuclear: 0.014730694978085336\n        oil: 1.0094807808107344e-05\n        solar: 0.06723095267321362\n        unknown: 0.0029030936283807687\n        wind: 0.2848260812110037\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.1543975843986955e-06\n        biomass: 9.090982811789023e-06\n        coal: 0.19246686475260225\n        gas: 0.3433657592833896\n        geothermal: 1.3745233623129707e-05\n        hydro: 0.013619330965482757\n        hydro discharge: 1.753592660845584e-05\n        nuclear: 0.013023841040915786\n        oil: 1.2456414301662708e-06\n        solar: 0.09317128158024654\n        unknown: 0.005706052023268491\n        wind: 0.3386034024377126\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2023-01-01'\n      value: 0.4919\n    - datetime: '2024-01-01'\n      value: 0.5511\n    - datetime: '2025-01-01'\n      value: 0.7346\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 0.276\n    - datetime: '2023-01-01'\n      value: 0.4728\n    - datetime: '2024-01-01'\n      value: 0.7807\nisRenewable:\n  battery discharge:\n    - datetime: '2023-01-01'\n      value: 0.4825\n    - datetime: '2024-01-01'\n      value: 0.5288\n    - datetime: '2025-01-01'\n      value: 0.7218\n  hydro discharge:\n    - datetime: '2022-01-01'\n      value: 0.2628\n    - datetime: '2023-01-01'\n      value: 0.464\n    - datetime: '2024-01-01'\n      value: 0.7806\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Mountain\nzone_name: Public Service Company of New Mexico\n"
  },
  {
    "path": "config/zones/US-SW-SRP.yaml",
    "content": "bounding_box:\n  - - -113.6585365853658\n    - 32.50580427989783\n  - - -110.94050940509399\n    - 34.347607885915195\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 10.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 20.0\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 45.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 35.0\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 295.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 483.0\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 733.0\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 1033.0\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 1123.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 3231.1\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 2428.0\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 1000\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 821.8\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 6300.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 8157.6\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 7474.8\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 7573.8\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 7672.8\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 7772.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 8268.4\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 8455.4\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 8442.1\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 89.3\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 91.1\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 154.1\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4209.6\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 163.2\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 550\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 600\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 650\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 750\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 359.8\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 459.8\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 559.8\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 562.9\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 1174.9\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 1474.9\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 1674.9\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 63.0\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 226.0\ncenter_point:\n  - -112.34764947928672\n  - 33.531684403250075\ncentroid:\n  - -112.4015701695478\n  - 33.47728935688684\ncomment: Salt River Project\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ndisclaimer: This zone includes all electricity production from the generation-only\n  balancing authorities Arlington Valley, LLC - AVBA and New Harquahala Generating\n  Company, LLC - HGBA. Read more on the wiki page.\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 184.26\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 250.01\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 284.05\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 243.17\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1218.5201933237183\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1158.447444803718\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1190.7635865078173\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1187.512537600055\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 377.65928159519075\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 385.40906841862005\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 386.11117611501976\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 414.8222825456002\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 237.84\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 214.36\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 205.58\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 262.97\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 240.66\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 240.2\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 217.26\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 283.01\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 317.05\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 276.17\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1278.5201933237183\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1218.447444803718\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1250.7635865078173\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1247.512537600055\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 497.65928159519075\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 505.40906841862005\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 506.11117611501976\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 534.8222825456003\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 261.84\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 238.36\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 229.58\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 286.97\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 264.66\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 264.2\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.04642444710729002\n        gas: 0.40648624369054626\n        geothermal: 0.0\n        hydro: 0.004434165011901996\n        hydro discharge: 0.006351855404964932\n        nuclear: 0.5092886647963919\n        oil: 9.768364475275976e-05\n        solar: 0.023775823227590955\n        unknown: 0.00031281181649993073\n        wind: 0.002827811742634391\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.04642450732594513\n        gas: 0.4064867937164666\n        geothermal: 0.0\n        hydro: 0.004434173074998432\n        hydro discharge: 0.006351859127897313\n        nuclear: 0.5092892646032979\n        oil: 9.7683957300656e-05\n        solar: 0.02377459640498656\n        unknown: 0.0003128124950321635\n        wind: 0.002827816116576366\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 6.809013560529835e-07\n        biomass: 1.2613557736074736e-05\n        coal: 0.050159977368421066\n        gas: 0.40562953740018576\n        geothermal: 2.1753341594456666e-05\n        hydro: 0.005092100049701921\n        hydro discharge: 0.001999043029321173\n        nuclear: 0.5080371953145556\n        oil: 1.95240601357329e-06\n        solar: 0.025530876970108266\n        unknown: 0.00028614874664512606\n        wind: 0.0032280020605113076\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 3.016030407101531e-07\n        biomass: 2.969254316465385e-05\n        coal: 0.11041611356204273\n        gas: 0.3197843507767187\n        geothermal: 5.3676282107455505e-05\n        hydro: 0.008579065570763626\n        hydro discharge: 0.004712199065678413\n        nuclear: 0.5208305668711567\n        oil: 2.005825936678952e-06\n        solar: 0.03219892033447119\n        unknown: 0.0004969255889662198\n        wind: 0.002896068847193458\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 5.746597628340785e-08\n        biomass: 6.565865856012792e-06\n        coal: 0.05914466992517215\n        gas: 0.41983062657731407\n        geothermal: 8.702503783418577e-06\n        hydro: 0.01582650415342763\n        hydro discharge: 0.0007754213097021318\n        nuclear: 0.4712561142109285\n        oil: 3.360436382862307e-06\n        solar: 0.029809047243120314\n        unknown: 0.0009691487564271524\n        wind: 0.002369658302513037\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 1.1584040662634583e-07\n        biomass: 1.0123783229104396e-05\n        coal: 0.051930745038341684\n        gas: 0.46489385692017043\n        geothermal: 1.430450805825176e-05\n        hydro: 0.014739866825845317\n        hydro discharge: 0.0009901512221189965\n        nuclear: 0.4256404770247441\n        oil: 4.801362084649291e-06\n        solar: 0.036200782014570526\n        unknown: 0.002474611058143617\n        wind: 0.0030999899733667735\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 7.930894240721491e-07\n        biomass: 2.778151331448804e-05\n        coal: 0.0732577577895643\n        gas: 0.3644940704508448\n        geothermal: 4.8080802756541105e-05\n        hydro: 0.0192892369605296\n        hydro discharge: 0.0014941385795646626\n        nuclear: 0.5116543131703094\n        oil: 6.006629360448159e-07\n        solar: 0.019446747053359793\n        unknown: 0.0007664736742661408\n        wind: 0.009519503021327261\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 5.925034547321845e-06\n        biomass: 2.7563101350310424e-05\n        coal: 0.05982840879417169\n        gas: 0.40361975648960374\n        geothermal: 4.508104971986281e-05\n        hydro: 0.012385290508186491\n        hydro discharge: 1.691630966492384e-05\n        nuclear: 0.49364284438897904\n        oil: 5.473101259497187e-07\n        solar: 0.02125779693478046\n        unknown: 0.0006748655800092944\n        wind: 0.008494799257563836\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.565933092888953e-05\n        biomass: 8.071837877332661e-05\n        coal: 0.07209774207782838\n        gas: 0.43066522487698167\n        geothermal: 0.00014149696912755998\n        hydro: 0.014223117068317106\n        hydro discharge: 6.5744852475226946e-06\n        nuclear: 0.44509759460917603\n        oil: 1.528600683085825e-07\n        solar: 0.028391651449343587\n        unknown: 0.0006835290063331449\n        wind: 0.008596420205364573\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.6476\n    - datetime: '2023-01-01'\n      value: 0.5527\n    - datetime: '2024-01-01'\n      value: 0.5374\n    - datetime: '2025-01-01'\n      value: 0.5469\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4802\n    - datetime: '2021-01-01'\n      value: 0.5686\n    - datetime: '2022-01-01'\n      value: 0.5954\n    - datetime: '2023-01-01'\n      value: 0.5272\n    - datetime: '2024-01-01'\n      value: 0.5775\n    - datetime: '2025-01-01'\n      value: 0.5884\nisRenewable:\n  battery discharge:\n    - datetime: '2022-01-01'\n      value: 0.0356\n    - datetime: '2023-01-01'\n      value: 0.0565\n    - datetime: '2024-01-01'\n      value: 0.0366\n    - datetime: '2025-01-01'\n      value: 0.0964\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.035\n    - datetime: '2021-01-01'\n      value: 0.0336\n    - datetime: '2022-01-01'\n      value: 0.0437\n    - datetime: '2023-01-01'\n      value: 0.0376\n    - datetime: '2024-01-01'\n      value: 0.0603\n    - datetime: '2025-01-01'\n      value: 0.0912\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Arizona\nzone_name: Salt River Project\n"
  },
  {
    "path": "config/zones/US-SW-TEPC.yaml",
    "content": "bounding_box:\n  - - -114.74574745747451\n    - 31.731588467267372\n  - - -110.5697056970569\n    - 36.210877734426944\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 10.0\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 20.0\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 50.0\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 70.0\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 270.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1765.8\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 941.3\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 817.7\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 1436.7\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 1530.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 1530.2\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 258.4\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 262.8\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 264.8\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 266.1\n    - datetime: '2018-06-01'\n      source: EIA.gov\n      value: 321.1\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 322.4\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 323.5\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 325.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 328.9\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 458.9\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 474.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 475.0\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 495.0\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 492.2\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 30.0\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 279.8\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 379.8\ncenter_point:\n  - -113.25893258932582\n  - 34.347607885915195\ncentroid:\n  - -113.2174065926705\n  - 34.46299309944698\ncomment: Tucson Electric Power Company\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 404.51\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1062.3990359820225\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1044.036558945808\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1049.8710181012766\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1043.24530714986\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 505.31676919101574\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 551.2211466358136\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 522.3770975723654\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 363.84094767168796\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 437.51\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1122.3990359820225\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1104.036558945808\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1109.8710181012766\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1103.24530714986\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 625.3167691910157\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 671.2211466358136\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 642.3770975723654\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 483.84094767168796\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.4762657415345327\n        gas: 0.39949798046059326\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.06738931955133136\n        unknown: 0.002414375037718254\n        wind: 0.05443041396922187\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.47626740937820994\n        gas: 0.3994993794698493\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0673860543516837\n        unknown: 0.0024143834926621853\n        wind: 0.05443060458008019\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.43142509222149744\n        gas: 0.4287679934956673\n        geothermal: 0.0\n        hydro: 0.0\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0714823480737832\n        unknown: 0.0018020399580009692\n        wind: 0.06652335584906117\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 5.134746227090972e-06\n        coal: 0.4391124805282432\n        gas: 0.3651235149090021\n        geothermal: 6.317318728812044e-06\n        hydro: 0.008371798240512993\n        hydro discharge: 0.02220029293901737\n        nuclear: 0.10757466625476327\n        oil: 6.904498825152716e-06\n        solar: 0.03941345179977839\n        unknown: 0.0026306037869968848\n        wind: 0.015553354709200438\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 9.472651391481814e-08\n        biomass: 1.4354511458600937e-05\n        coal: 0.38981529319248104\n        gas: 0.38351310722032367\n        geothermal: 1.7258309685153362e-05\n        hydro: 0.026231598202431435\n        hydro discharge: 0.0003116226739757036\n        nuclear: 0.12154903763980336\n        oil: 8.543470404990096e-06\n        solar: 0.04566081740977979\n        unknown: 0.0026543368133078774\n        wind: 0.030223004065397602\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 1.9636772534598375e-07\n        biomass: 2.3322059191000633e-05\n        coal: 0.3497392419764938\n        gas: 0.4720268709081237\n        geothermal: 2.8530445331631925e-05\n        hydro: 0.028206650661954425\n        hydro discharge: 0.00022434334259545627\n        nuclear: 0.058466786463975094\n        oil: 1.2281194575365724e-05\n        solar: 0.0526170797558463\n        unknown: 0.004038201588651887\n        wind: 0.03461600610138372\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 1.3026926316440545e-06\n        biomass: 4.343978890905366e-05\n        coal: 0.338718918680164\n        gas: 0.41730170171777925\n        geothermal: 7.30734289286627e-05\n        hydro: 0.02616284134253304\n        hydro discharge: 0.00023343399450680236\n        nuclear: 0.08809550528753181\n        oil: 2.9037631967128955e-06\n        solar: 0.047350300939758505\n        unknown: 0.002623495083873944\n        wind: 0.07939226292782316\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 9.78215398712604e-06\n        biomass: 4.234801029832894e-05\n        coal: 0.3810412127475919\n        gas: 0.30300173079753084\n        geothermal: 6.748870044943608e-05\n        hydro: 0.022077821815163743\n        hydro discharge: 3.009182759893621e-06\n        nuclear: 0.0754611975292583\n        oil: 4.2157818859819795e-06\n        solar: 0.08443267860487598\n        unknown: 0.0031128463339509895\n        wind: 0.13074496917695946\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 1.2219601506014728e-05\n        biomass: 6.29616275077828e-05\n        coal: 0.2590421883727156\n        gas: 0.4764170117737294\n        geothermal: 0.00010500946117875988\n        hydro: 0.016734083892799418\n        hydro discharge: 0.00012050034186303802\n        nuclear: 0.06368621253102906\n        oil: 7.638632082547033e-07\n        solar: 0.07786897710286665\n        unknown: 0.0025693853856152958\n        wind: 0.10338034646937623\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.2633\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.2268\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Arizona\nzone_name: Tucson Electric Power Company\n"
  },
  {
    "path": "config/zones/US-SW-WALC.yaml",
    "content": "bounding_box:\n  - - -121.08901089010884\n    - 31.332316356872\n  - - -105.62685626856262\n    - 38.510627846990985\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 90.0\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 105.0\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 115.0\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 130.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 140.0\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 190.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 408.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 204.0\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1713.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 1917.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 2153.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1517.0\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 1599.8\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 1689.8\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 5614.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 5610.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 3789.5\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 3770.0\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 65.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 40.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1.5\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 34.4\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 61.7\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 151.7\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 81.7\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 109.7\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 142.2\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 322.2\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 323.1\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 340.7\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 579.2\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 350.0\ncenter_point:\n  - -110.02697591635858\n  - 33.21112655362538\ncentroid:\n  - -111.57498726391051\n  - 34.22847276486294\ncomment: Western Area Power Administration - Desert Southwest Region\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\ndisclaimer: This zone includes all electricity production from the generation-only\n  balancing authority Griffith Energy, LLC. Read more on the zone definition wiki\n  page.\nemissionFactors:\n  direct:\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 991.8668607823284\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 837.488207915474\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 866.6840107698806\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 681.6270222428261\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 483.72245562038313\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 405.1724150951613\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 408.36356010340177\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 408.23419876051724\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 250.74\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 538.35\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 803.8986689024886\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1051.8668607823283\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 897.488207915474\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 926.6840107698806\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 741.6270222428261\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 603.7224556203831\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 525.1724150951613\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 528.3635601034018\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 528.2341987605173\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 274.74\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 562.35\n    oil:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1047.8986689024887\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.11275865522480874\n        gas: 0.016523394940958537\n        geothermal: 0.0\n        hydro: 0.02287174921988805\n        hydro discharge: 0.841183524983747\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.00120460026817122\n        unknown: 0.0\n        wind: 0.005457995643173142\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.11275867108483262\n        gas: 0.01652339726505009\n        geothermal: 0.0\n        hydro: 0.022871752436904855\n        hydro discharge: 0.8411836433000818\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0012044598252164062\n        unknown: 0.0\n        wind: 0.005457996410865351\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 4.061569659899597e-06\n        biomass: 3.1203573807595425e-05\n        coal: 0.29240643794985277\n        gas: 0.07800737029803148\n        geothermal: 5.4309556329316095e-05\n        hydro: 0.05531601874128646\n        hydro discharge: 0.5491837336963346\n        nuclear: 0.0002733499967330196\n        oil: 4.849471026129491e-06\n        solar: 0.007143208484285963\n        unknown: 0.0036715122700611003\n        wind: 0.013903829823852938\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 3.466810833091937e-07\n        biomass: 4.657951742301398e-05\n        coal: 0.34074026468650825\n        gas: 0.10381548182183624\n        geothermal: 9.051062385164965e-05\n        hydro: 0.09042090492361125\n        hydro discharge: 0.39453527293259427\n        nuclear: 0.022783688526096985\n        oil: 8.971138807825717e-06\n        solar: 0.005664355460125296\n        unknown: 0.009679936686565254\n        wind: 0.03221370019642685\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 2.0450013818203185e-06\n        biomass: 0.0001410572955165554\n        coal: 0.19348833985206274\n        gas: 0.21376108904337326\n        geothermal: 0.00020759257929600406\n        hydro: 0.26604714194960816\n        hydro discharge: 0.06492792100635167\n        nuclear: 0.2117025021188365\n        oil: 3.7046945764562e-05\n        solar: 0.02020528492824484\n        unknown: 0.014841647406643448\n        wind: 0.014637147268461416\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 2.7788212605821755e-06\n        biomass: 0.00020572864980731038\n        coal: 0.15881060179722398\n        gas: 0.4175277281379737\n        geothermal: 0.0002980833097133526\n        hydro: 0.2712315870373622\n        hydro discharge: 0.018082016850382222\n        nuclear: 0.053747928863339026\n        oil: 4.674300144597458e-05\n        solar: 0.043856822447386534\n        unknown: 0.014912559475363914\n        wind: 0.02127673289570877\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 1.3069296109873164e-05\n        biomass: 0.0004824777995683708\n        coal: 0.15557222738315216\n        gas: 0.35918483111615734\n        geothermal: 0.0008418404348403923\n        hydro: 0.2565107441791119\n        hydro discharge: 0.0003834351689378131\n        nuclear: 0.10727544726372894\n        oil: 1.5337744073194808e-05\n        solar: 0.03955921610533964\n        unknown: 0.008215205381399469\n        wind: 0.0719440093072143\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 7.670606313777633e-05\n        biomass: 0.0004433397662161392\n        coal: 0.13882603743633165\n        gas: 0.416885257942429\n        geothermal: 0.000732222650328912\n        hydro: 0.22377476485942333\n        hydro discharge: 3.302376142560656e-06\n        nuclear: 0.08768927652915415\n        oil: 1.3941736246539811e-05\n        solar: 0.05518245487156894\n        unknown: 0.005994540417439751\n        wind: 0.07037705079871356\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 7.622161788672196e-05\n        biomass: 0.0004252941214920052\n        coal: 0.12398717459688091\n        gas: 0.4499580029750956\n        geothermal: 0.000708910186276374\n        hydro: 0.19572242862088565\n        hydro discharge: 0.02563223681737553\n        nuclear: 0.07841998328993836\n        oil: 3.046447623791319e-06\n        solar: 0.05133000190223975\n        unknown: 0.006238086068185822\n        wind: 0.06749767730316335\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2024-01-01'\n      value: 0.4499\n    - datetime: '2025-01-01'\n      value: 0.1686\nisRenewable:\n  hydro discharge:\n    - datetime: '2024-01-01'\n      value: 0.322\n    - datetime: '2025-01-01'\n      value: 0.126\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Arizona\nzone_name: Western Area Power Administration - Desert Southwest Region\nzone_short_name: WAPA Desert Southwest\n"
  },
  {
    "path": "config/zones/US-TEN-TVA.yaml",
    "content": "bounding_box:\n  - - -90.30870308703082\n    - 32.324056760112114\n  - - -81.67458504103661\n    - 37.586148336899896\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 1.0\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 51.0\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 101.0\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 151.0\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 286.7\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 284.9\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 221.7\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 216.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 213.3\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 218.1\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 213.3\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 218.1\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 12642.1\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 11234.1\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 10734.1\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 9744.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 8593.9\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 7643.9\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 14674.0\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 15834.0\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 15840.3\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 17011.2\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 17067.4\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 16443.4\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 16493.4\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 17187.0\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 17880.6\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 17906.6\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 18498.8\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 18090.8\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 18156.6\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 4866.8\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 4749.3\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 4731.8\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 4756.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 4846.8\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 4871.8\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 1808.6\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 8474.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 8548.3\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 8834.8\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 57.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 677.8\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 176.2\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 150.7\n    - datetime: '2017-10-01'\n      source: EIA.gov\n      value: 166.7\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 179.7\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 194.7\n    - datetime: '2018-08-01'\n      source: EIA.gov\n      value: 196.3\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 283.4\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 284.0\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 286.3\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 291.3\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 293.0\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 292.8\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 519.8\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 528.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 526.8\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 676.8\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 677.8\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 697.5\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 697.3\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 797.3\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 867.3\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 902.3\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 918.4\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 919.7\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 935.7\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 1085.7\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 1127.7\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 1307.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 1308.8\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 1508.8\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 1529.7\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 1536.2\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 1790.2\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 1799.8\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 1816.4\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 100\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 250\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 0.0\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 28.8\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 1.8\ncenter_point:\n  - -86.671418402335\n  - 35.04187120335755\ncentroid:\n  - -86.75331430505567\n  - 35.161774339957056\ncomment: Tennessee Valley Authority\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\ncountry: US\ncountry_name: USA\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 367.12\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 342.89\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1070.741205794168\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1089.663513125364\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1120.384301079964\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1156.4235068348414\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 393.73104440922407\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 399.8819617917093\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 392.2385664881519\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 388.2369872584053\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 0.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 0.0\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 332.72\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 365.32\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 325.6\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 366.13\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 343.06\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 472.79756723454796\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 756.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 740.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 757.3688858307635\n  lifecycle:\n    battery discharge:\n      - _comment: used non-null storage values\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 400.12\n      - _comment: used non-null storage values\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 375.89\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1130.741205794168\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1149.663513125364\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1180.384301079964\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1216.4235068348414\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 513.7310444092241\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 519.8819617917093\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 512.238566488152\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 508.2369872584053\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    hydro discharge:\n      - _comment: used default IPCC 2014 value of 24.0\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 24.0\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 356.72\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 389.32\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 349.6\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 390.13\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 367.06\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 716.797567234548\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1000.6867166175201\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 984.5235575792449\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1001.3688858307635\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.06666667\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1616582386585121\n        gas: 0.27899319691073954\n        geothermal: 0.0\n        hydro: 0.1345716777095002\n        hydro discharge: 0.018622098280262404\n        nuclear: 0.4009373330980699\n        oil: 3.7470785134482255e-05\n        solar: 0.004214653914558283\n        unknown: 0.0009275432672667829\n        wind: 3.744817150434678e-05\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.1616582789479754\n        gas: 0.2789932664431449\n        geothermal: 0.0\n        hydro: 0.1345717112482838\n        hydro discharge: 0.018622102921376598\n        nuclear: 0.400937433022145\n        oil: 3.7470794473182444e-05\n        solar: 0.004214405738792297\n        unknown: 0.0009275434984348369\n        wind: 3.744818083741106e-05\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 6.136453488037771e-07\n        coal: 0.17573091517710446\n        gas: 0.2865588521670497\n        geothermal: 0.0\n        hydro: 0.12462555951040964\n        hydro discharge: 0.0007202631473569895\n        nuclear: 0.3943519286872087\n        oil: 0.002066755774313153\n        solar: 0.0054384426551417776\n        unknown: 0.0023569238876039113\n        wind: 0.008149690648518894\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.708100640989688e-06\n        coal: 0.22333085839591546\n        gas: 0.29887935382111974\n        geothermal: 0.0\n        hydro: 0.1207656888961849\n        hydro discharge: 0.0028515496981762383\n        nuclear: 0.3436614042425701\n        oil: 0.0011901467711355038\n        solar: 0.0012941226548538562\n        unknown: 0.0022596795635269804\n        wind: 0.005765413008984425\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.996802918557855e-06\n        coal: 0.19641896023841035\n        gas: 0.2842185504888905\n        geothermal: 0.0\n        hydro: 0.11890717872925571\n        hydro discharge: 0.0013457457307136775\n        nuclear: 0.38775982586204155\n        oil: 5.463981569406666e-05\n        solar: 0.002832619516260879\n        unknown: 0.0018650397785837255\n        wind: 0.006594362173036369\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.7422329214855693e-06\n        coal: 0.1477210274278777\n        gas: 0.28468028781864474\n        geothermal: 0.0\n        hydro: 0.145027887772036\n        hydro discharge: 0.0017533880402967551\n        nuclear: 0.40675140105547863\n        oil: 2.4414727289889558e-05\n        solar: 0.0029894725741760023\n        unknown: 0.0021278150057131005\n        wind: 0.008921435659452645\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.3380976749635352e-06\n        coal: 0.19022998255872853\n        gas: 0.2703258847551532\n        geothermal: 0.0\n        hydro: 0.11955513728363829\n        hydro discharge: 0.0011541983734023654\n        nuclear: 0.40018196234240594\n        oil: 4.8942264446719913e-05\n        solar: 0.00454271222674941\n        unknown: 0.0022281550698765745\n        wind: 0.011729630567890163\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.482987043106388e-06\n        coal: 0.17783843646879355\n        gas: 0.3134433828499834\n        geothermal: 0.0\n        hydro: 0.10520487379922844\n        hydro discharge: 2.1678266619555077e-06\n        nuclear: 0.375401931152465\n        oil: 7.02646816806329e-05\n        solar: 0.008359818580111202\n        unknown: 0.0022818298708808023\n        wind: 0.017393668970246697\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.201554923168348e-06\n        coal: 0.16124449609557742\n        gas: 0.30375418116786995\n        geothermal: 0.0\n        hydro: 0.0937228133199137\n        hydro discharge: 5.27816554770762e-06\n        nuclear: 0.41199214769838044\n        oil: 3.25149380463193e-05\n        solar: 0.010567272522676962\n        unknown: 0.006034844645347208\n        wind: 0.01264416307073402\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.3954\n    - datetime: '2025-01-01'\n      value: 0.4818\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 0.5012\n    - datetime: '2022-01-01'\n      value: 0.4537\n    - datetime: '2023-01-01'\n      value: 0.509\n    - datetime: '2024-01-01'\n      value: 0.4014\n    - datetime: '2025-01-01'\n      value: 0.4834\nisRenewable:\n  battery discharge:\n    - datetime: '2024-01-01'\n      value: 0.0535\n    - datetime: '2025-01-01'\n      value: 0.1246\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 1.0\n    - datetime: '2021-01-01'\n      value: 0.0288\n    - datetime: '2022-01-01'\n      value: 0.0267\n    - datetime: '2023-01-01'\n      value: 0.0211\n    - datetime: '2024-01-01'\n      value: 0.0503\n    - datetime: '2025-01-01'\n      value: 0.114\nparsers:\n  consumption: EIA.fetch_consumption\n  consumptionForecast: EIA.fetch_consumption_forecast\n  production: EIA.fetch_production_mix\n  productionCapacity: EIA.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Central\nzone_name: Tennessee Valley Authority\nzone_short_name: TVA\n"
  },
  {
    "path": "config/zones/US-TEX-ERCO.yaml",
    "content": "bounding_box:\n  - - -104.97656406478228\n    - 25.868442100637097\n  - - -93.8295382953829\n    - 36.0577518713004\ncapacity:\n  battery storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 41.0\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 71.0\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 73.0\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 92.8\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 94.3\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 114.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 124.1\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 134.0\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 143.9\n    - datetime: '2020-04-01'\n      source: EIA.gov\n      value: 153.8\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 163.7\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 183.5\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 203.3\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 223.1\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 233.0\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 244.9\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 354.8\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 372.2\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 382.1\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 432.1\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 792.4\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 841.9\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 962.7\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 1273.0\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 1542.1\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 1662.9\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 1937.9\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 1986.9\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 2086.9\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 2104.7\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 2300.7\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 2320.5\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 2448.0\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 2799.8\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 2989.8\n    - datetime: '2023-09-01'\n      source: EIA.gov\n      value: 3109.8\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 3191.2\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 3201.2\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 3814.4\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 3632.8\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 3642.7\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 3891.6\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 4134.9\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 4562.6\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 4825.1\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 5423.5\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 5705.4\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 6081.3\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 6306.6\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 7455.6\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 7607.8\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 7847.7\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 8122.6\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 8482.2\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 8845.7\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 9265.3\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 9925.1\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 10205.1\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 12447.0\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 13779.4\n  biomass:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 218.7\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 208.5\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 206.8\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 198.3\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 193.2\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 181.5\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 179.9\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 170.1\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 160.5\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 137.0\n  coal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 20089.6\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 15925.5\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 14738.7\n    - datetime: '2019-10-01'\n      source: EIA.gov\n      value: 14285.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 14329.7\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 13321.7\n  gas:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 60012.9\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 62474.9\n    - datetime: '2017-08-01'\n      source: EIA.gov\n      value: 62508.9\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 62604.3\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 62602.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 62727.3\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 63391.3\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 63512.8\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 64352.1\n    - datetime: '2019-07-01'\n      source: EIA.gov\n      value: 64452.1\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 64539.1\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 64476.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 64149.9\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 64299.9\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 64302.3\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 64303.5\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 64304.7\n    - datetime: '2020-09-01'\n      source: EIA.gov\n      value: 64305.9\n    - datetime: '2020-10-01'\n      source: EIA.gov\n      value: 63987.3\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 63887.8\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 63890.2\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 63939.4\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 63918.3\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 64282.5\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 64282.3\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 64283.5\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 64284.7\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 64710.6\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 64837.6\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 64853.2\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 65046.7\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 65052.7\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 64672.3\n    - datetime: '2022-02-01'\n      source: EIA.gov\n      value: 64735.2\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 64332.6\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 64635.1\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 64796.8\n    - datetime: '2022-08-01'\n      source: EIA.gov\n      value: 64857.3\n    - datetime: '2022-10-01'\n      source: EIA.gov\n      value: 64792.5\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 65155.5\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 65156.7\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 65842.4\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 65843.6\n    - datetime: '2023-04-01'\n      source: EIA.gov\n      value: 65844.8\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 66289.4\n    - datetime: '2023-06-01'\n      source: EIA.gov\n      value: 66214.4\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 66215.6\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 66222.4\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 66343.4\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 66393.4\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 66756.4\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 66877.4\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 67065.0\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 67159.2\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 67339.2\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 67359.2\n  geothermal:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 566.1\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 560.1\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 562.8\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 512.0\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 558.0\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 550.4\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 549.1\n  hydro storage:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 0.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 5138.6\n  oil:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 88.1\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 89.4\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 248.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 785.2\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 854.7\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 853.3\n  solar:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 575.9\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 577.4\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 682.4\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 966.3\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 974.0\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 1024.0\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 1221.0\n    - datetime: '2018-03-01'\n      source: EIA.gov\n      value: 1223.6\n    - datetime: '2018-05-01'\n      source: EIA.gov\n      value: 1605.6\n    - datetime: '2018-11-01'\n      source: EIA.gov\n      value: 1710.6\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 1927.6\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 1939.5\n    - datetime: '2019-04-01'\n      source: EIA.gov\n      value: 1951.2\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 1961.2\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 2223.7\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 2428.7\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 2630.7\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 2647.5\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 3347.5\n    - datetime: '2020-07-01'\n      source: EIA.gov\n      value: 3677.5\n    - datetime: '2020-08-01'\n      source: EIA.gov\n      value: 4197.5\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 4864.0\n    - datetime: '2021-02-01'\n      source: EIA.gov\n      value: 5119.0\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 5574.0\n    - datetime: '2021-04-01'\n      source: EIA.gov\n      value: 5602.0\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 5761.0\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 6137.0\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 7271.6\n    - datetime: '2021-09-01'\n      source: EIA.gov\n      value: 7501.3\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 7978.2\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 8822.2\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 8829.0\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 9129.7\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 9692.2\n    - datetime: '2022-07-01'\n      source: EIA.gov\n      value: 9971.1\n    - datetime: '2022-09-01'\n      source: EIA.gov\n      value: 10493.2\n    - datetime: '2022-11-01'\n      source: EIA.gov\n      value: 10743.2\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 11354.1\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 11356.6\n    - datetime: '2023-03-01'\n      source: EIA.gov\n      value: 11464.6\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 11957.4\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 12163.1\n    - datetime: '2023-08-01'\n      source: EIA.gov\n      value: 12320.6\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 13001.1\n    - datetime: '2023-11-01'\n      source: EIA.gov\n      value: 13290.7\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 14899.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 15652.7\n    - datetime: '2024-02-01'\n      source: EIA.gov\n      value: 15952.7\n    - datetime: '2024-03-01'\n      source: EIA.gov\n      value: 16352.7\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 16787.5\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 16993.8\n    - datetime: '2024-06-01'\n      source: EIA.gov\n      value: 17743.8\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 17946.6\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 18596.6\n    - datetime: '2024-09-01'\n      source: EIA.gov\n      value: 19585.1\n    - datetime: '2024-10-01'\n      source: EIA.gov\n      value: 21037.1\n    - datetime: '2024-11-01'\n      source: EIA.gov\n      value: 21584.1\n    - datetime: '2024-12-01'\n      source: EIA.gov\n      value: 22172.9\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 22814.5\n    - datetime: '2025-02-01'\n      source: EIA.gov\n      value: 23210.4\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 23610.4\n    - datetime: '2025-04-01'\n      source: EIA.gov\n      value: 24355.4\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 24655.4\n    - datetime: '2025-06-01'\n      source: EIA.gov\n      value: 25399.8\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 25496.8\n    - datetime: '2025-08-01'\n      source: EIA.gov\n      value: 26011.8\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 28723.2\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 29771.7\n  unknown:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 239.9\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 229.7\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 275.7\n  wind:\n    - datetime: '2017-01-01'\n      source: EIA.gov\n      value: 18795.2\n    - datetime: '2017-02-01'\n      source: EIA.gov\n      value: 18890.5\n    - datetime: '2017-03-01'\n      source: EIA.gov\n      value: 18940.9\n    - datetime: '2017-04-01'\n      source: EIA.gov\n      value: 19092.1\n    - datetime: '2017-05-01'\n      source: EIA.gov\n      value: 19255.1\n    - datetime: '2017-07-01'\n      source: EIA.gov\n      value: 19508.1\n    - datetime: '2017-09-01'\n      source: EIA.gov\n      value: 19657.4\n    - datetime: '2017-11-01'\n      source: EIA.gov\n      value: 20298.8\n    - datetime: '2017-12-01'\n      source: EIA.gov\n      value: 20927.3\n    - datetime: '2018-01-01'\n      source: EIA.gov\n      value: 20836.5\n    - datetime: '2018-02-01'\n      source: EIA.gov\n      value: 21033.2\n    - datetime: '2018-04-01'\n      source: EIA.gov\n      value: 21333.2\n    - datetime: '2018-07-01'\n      source: EIA.gov\n      value: 21483.2\n    - datetime: '2018-09-01'\n      source: EIA.gov\n      value: 21643.2\n    - datetime: '2018-12-01'\n      source: EIA.gov\n      value: 22292.6\n    - datetime: '2019-01-01'\n      source: EIA.gov\n      value: 22392.7\n    - datetime: '2019-02-01'\n      source: EIA.gov\n      value: 22692.7\n    - datetime: '2019-03-01'\n      source: EIA.gov\n      value: 22892.2\n    - datetime: '2019-05-01'\n      source: EIA.gov\n      value: 22922.4\n    - datetime: '2019-06-01'\n      source: EIA.gov\n      value: 23688.5\n    - datetime: '2019-08-01'\n      source: EIA.gov\n      value: 23851.4\n    - datetime: '2019-09-01'\n      source: EIA.gov\n      value: 24771.0\n    - datetime: '2019-11-01'\n      source: EIA.gov\n      value: 25078.1\n    - datetime: '2019-12-01'\n      source: EIA.gov\n      value: 25690.0\n    - datetime: '2020-01-01'\n      source: EIA.gov\n      value: 25643.4\n    - datetime: '2020-02-01'\n      source: EIA.gov\n      value: 25693.8\n    - datetime: '2020-03-01'\n      source: EIA.gov\n      value: 26273.4\n    - datetime: '2020-05-01'\n      source: EIA.gov\n      value: 26453.4\n    - datetime: '2020-06-01'\n      source: EIA.gov\n      value: 26604.6\n    - datetime: '2020-11-01'\n      source: EIA.gov\n      value: 26749.5\n    - datetime: '2020-12-01'\n      source: EIA.gov\n      value: 27743.9\n    - datetime: '2021-01-01'\n      source: EIA.gov\n      value: 27862.4\n    - datetime: '2021-03-01'\n      source: EIA.gov\n      value: 28135.0\n    - datetime: '2021-05-01'\n      source: EIA.gov\n      value: 28344.4\n    - datetime: '2021-06-01'\n      source: EIA.gov\n      value: 29268.1\n    - datetime: '2021-07-01'\n      source: EIA.gov\n      value: 30355.7\n    - datetime: '2021-08-01'\n      source: EIA.gov\n      value: 30694.1\n    - datetime: '2021-10-01'\n      source: EIA.gov\n      value: 31434.5\n    - datetime: '2021-11-01'\n      source: EIA.gov\n      value: 31734.5\n    - datetime: '2021-12-01'\n      source: EIA.gov\n      value: 32027.8\n    - datetime: '2022-01-01'\n      source: EIA.gov\n      value: 32626.7\n    - datetime: '2022-03-01'\n      source: EIA.gov\n      value: 33118.3\n    - datetime: '2022-04-01'\n      source: EIA.gov\n      value: 34213.9\n    - datetime: '2022-05-01'\n      source: EIA.gov\n      value: 34414.1\n    - datetime: '2022-06-01'\n      source: EIA.gov\n      value: 34682.3\n    - datetime: '2022-12-01'\n      source: EIA.gov\n      value: 35954.6\n    - datetime: '2023-01-01'\n      source: EIA.gov\n      value: 35524.7\n    - datetime: '2023-05-01'\n      source: EIA.gov\n      value: 35764.3\n    - datetime: '2023-07-01'\n      source: EIA.gov\n      value: 36263.8\n    - datetime: '2023-10-01'\n      source: EIA.gov\n      value: 36460.6\n    - datetime: '2023-12-01'\n      source: EIA.gov\n      value: 36684.5\n    - datetime: '2024-01-01'\n      source: EIA.gov\n      value: 37180.0\n    - datetime: '2024-04-01'\n      source: EIA.gov\n      value: 37708.4\n    - datetime: '2024-05-01'\n      source: EIA.gov\n      value: 37874.8\n    - datetime: '2024-07-01'\n      source: EIA.gov\n      value: 38282.3\n    - datetime: '2024-08-01'\n      source: EIA.gov\n      value: 38466.1\n    - datetime: '2025-01-01'\n      source: EIA.gov\n      value: 38969.6\n    - datetime: '2025-03-01'\n      source: EIA.gov\n      value: 38821.2\n    - datetime: '2025-05-01'\n      source: EIA.gov\n      value: 39227.4\n    - datetime: '2025-07-01'\n      source: EIA.gov\n      value: 39393.8\n    - datetime: '2025-11-01'\n      source: EIA.gov\n      value: 39834.8\n    - datetime: '2025-12-01'\n      source: EIA.gov\n      value: 39984.8\ncenter_point:\n  - -99.6234521418142\n  - 31.05836020574414\ncentroid:\n  - -98.77455484112068\n  - 30.508820822816638\ncomment: Electric Reliability Council Of Texas, Inc.\ncontributors:\n  - systemcatch\n  - robertahunt\n  - KabelWlan\n  - silkeholmebonnen\n  - alejandranavcas\ncountry: US\ncountry_name: USA\ncurrency: USD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 268.74\n    biomass:\n      - datetime: '2020-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2021-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2022-01-01'\n        source: BEIS 2021\n        value: 0.0\n      - datetime: '2023-01-01'\n        source: BEIS 2021\n        value: 0.0\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1043.4008891244728\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1032.0234558048815\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1041.5714428045928\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1062.9695874892159\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 393.10006596259814\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 392.2742477255014\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 393.7660838295522\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 392.3322057315127\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 70.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 78.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 29.707905036391203\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 28.739435464835893\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 1070.8111086067734\n      - datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 1068.7253320833786\n      - datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 1068.5017353846156\n      - datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 1479.6758322526446\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 301.74\n    biomass:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020\n        value: 281.38853074481284\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021\n        value: 280.6015234636058\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022\n        value: 274.05045073430733\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023\n        value: 282.7016835752059\n    coal:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1103.4008891244728\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1092.0234558048815\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1101.5714428045928\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1122.9695874892159\n    gas:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 513.1000659625981\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 512.2742477255015\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 513.7660838295521\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 512.3322057315127\n    geothermal:\n      - _comment: Mean of all US zones\n        datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 108.87985131255388\n      - _comment: Mean of all US zones\n        datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 116.28737905336972\n      - _comment: Mean of all US zones\n        datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 67.7079050363912\n      - _comment: Mean of all US zones\n        datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 66.73943546483589\n    oil:\n      - datetime: '2020-01-01'\n        source: eGrid 2020; IPCC 2014\n        value: 1314.8111086067734\n      - datetime: '2021-01-01'\n        source: eGrid 2021; IPCC 2014\n        value: 1312.7253320833786\n      - datetime: '2022-01-01'\n        source: eGrid 2022; IPCC 2014\n        value: 1312.5017353846156\n      - datetime: '2023-01-01'\n        source: eGrid 2023; IPCC 2014\n        value: 1723.6758322526446\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 25.6\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0\n        biomass: 0\n        coal: 0.1949175601554299\n        gas: 0.4459707369749529\n        geothermal: 0\n        hydro: 0.0015546525109556703\n        hydro discharge: 0\n        nuclear: 0.10425041841030042\n        oil: 0\n        solar: 0.029187962214659528\n        unknown: 0.002396495130441387\n        wind: 0.22172211912519735\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0\n        biomass: 0\n        coal: 0.19491786578971063\n        gas: 0.44597143626518254\n        geothermal: 0\n        hydro: 0.0015546549486790931\n        hydro discharge: 0\n        nuclear: 0.10425058187685324\n        oil: 0\n        solar: 0.029186439963721104\n        unknown: 0.002396498888189354\n        wind: 0.2217224667895142\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 8.404729506510182e-07\n        coal: 0.18024230465958455\n        gas: 0.4425833188758418\n        geothermal: 0.0\n        hydro: 0.0014101642119089405\n        hydro discharge: 3.4611781707007457e-10\n        nuclear: 0.10151390300746489\n        oil: 4.00154225125079e-06\n        solar: 0.04018948605272968\n        unknown: 0.0025397705872362377\n        wind: 0.23151619471805798\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.3502425358014573e-06\n        coal: 0.2632385563593742\n        gas: 0.46668851411609763\n        geothermal: 1.1577966669215217e-07\n        hydro: 0.0026950149796575898\n        hydro discharge: 7.568925672249097e-08\n        nuclear: 0.10357576370385667\n        oil: 8.834904847507445e-06\n        solar: 0.00768957203751795\n        unknown: 0.0007516413395046966\n        wind: 0.1553495791475963\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.25723703093592e-06\n        coal: 0.20469661724946975\n        gas: 0.47180753716004087\n        geothermal: 5.710132214479319e-07\n        hydro: 0.002487713476628793\n        hydro discharge: 0.0\n        nuclear: 0.10807792748731698\n        oil: 6.704291177666471e-06\n        solar: 0.010439589142992992\n        unknown: 0.0020317648204969552\n        wind: 0.20044731655605996\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 3.356277541933444e-06\n        coal: 0.1814775005168527\n        gas: 0.45164478438499556\n        geothermal: 4.2999620828954627e-07\n        hydro: 0.0016651359053034495\n        hydro discharge: 1.8393873490753022e-10\n        nuclear: 0.1095398308416306\n        oil: 4.8211130728127555e-06\n        solar: 0.02179603213262863\n        unknown: 0.004331181610216886\n        wind: 0.22953692335883566\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.648398350205084e-06\n        coal: 0.19252896670585568\n        gas: 0.418277351866136\n        geothermal: 2.7067997916285295e-07\n        hydro: 0.001392620362255648\n        hydro discharge: 5.0961118170545595e-11\n        nuclear: 0.10324993825220949\n        oil: 7.0087080625542214e-06\n        solar: 0.038801938066184295\n        unknown: 0.0015153923208738548\n        wind: 0.24422386593960171\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 2.3820277066535297e-06\n        coal: 0.16866819581113865\n        gas: 0.42490918851350223\n        geothermal: 2.5448845300264115e-07\n        hydro: 0.0009115264020183709\n        hydro discharge: 0.0\n        nuclear: 0.09732216762142645\n        oil: 5.778944777607685e-06\n        solar: 0.054873246415372945\n        unknown: 0.0026751621418813383\n        wind: 0.25063209364065464\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 1.706378867528772e-06\n        coal: 0.14036071235976233\n        gas: 0.4511695932710841\n        geothermal: 6.042376908541695e-08\n        hydro: 0.000813322112690699\n        hydro discharge: 0.0\n        nuclear: 0.09156492488369625\n        oil: 3.190070876229793e-06\n        solar: 0.07115076013356555\n        unknown: 0.0026028574593210904\n        wind: 0.24233286045039404\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.5241\nisRenewable:\n  battery discharge:\n    - datetime: '2025-01-01'\n      value: 0.4362\nparsers:\n  consumption: US_ERCOT.fetch_consumption\n  consumptionForecast: US_ERCOT.fetch_consumption_forecast\n  dayaheadLocationalMarginalPrice: US_ERCOT.fetch_dayahead_locational_marginal_price\n  gridAlerts: email_grid_alerts.fetch_grid_alerts_emails\n  production: US_ERCOT.fetch_production\n  productionCapacity: EIA.fetch_production_capacity\n  productionPerModeForecast: US_ERCOT.fetch_wind_solar_forecasts\n  realtimeLocationalMarginalPrice: US_ERCOT.fetch_realtime_locational_marginal_price\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\ntimezone: US/Central\nzone_name: Electric Reliability Council of Texas\nzone_short_name: ERCOT\n"
  },
  {
    "path": "config/zones/US.yaml",
    "content": "bounding_box:\n  - - -178.21438214382135\n    - 18.906224118294816\n  - - 179.780397803978\n    - 71.35397886338464\ncenter_point:\n  - -117.09340068022681\n  - 45.024183836233846\ncentroid:\n  - -124.71143136720069\n  - 49.97276787769272\nbypassedSubZones:\n  - US-FLA-HST\n  - US-SE-SEPA\n  - US-CAR-YAD\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 11720.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 11500.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10990.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 10830.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 10280.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 10080.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 9960.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 9980.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 277700.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 260860.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 244610.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 232950.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 224240.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 209080.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 198880.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 194130.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 483380.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 507760.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 517900.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 522280.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 529010.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 534630.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 543810.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 542200.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 83790.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 83880.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 83790.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 83960.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 84390.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 84530.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 84320.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 84170.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 99630.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 99430.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 98120.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 96500.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 95550.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 94660.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 95770.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 96890.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 43770.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 51990.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 61590.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 76440.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 95390.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 114360.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 139210.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 177470.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40210.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 38340.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 37630.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 33780.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 34440.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 36850.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 35860.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 35580.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 87830.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 94670.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 103840.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 118660.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 133020.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 141670.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 148020.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 153150.0\ncontributors:\n  - kepiej\n  - KabelWlan\n  - robertahunt\n  - danielmatsuda\n  - brandongalbraith\n  - systemcatch\n  - VIKTORVAV99\n  - MisterClean\ncountry: US\ncountry_name: United States\ncurrency: USD\nemissionFactors:\n  direct:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 359.36\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 377.97\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 361.05\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 340.32\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 328.47\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 330.7\n    biomass:\n      datetime: '2020-01-01'\n      source: eGrid 2020\n      value: 0.0\n    coal:\n      datetime: '2020-01-01'\n      source: eGrid 2020\n      value: 989.615358\n    gas:\n      datetime: '2021-01-01'\n      source: eGrid 2020\n      value: 406.0342962\n    geothermal:\n      datetime: '2021-01-01'\n      source: eGrid 2020\n      value: 70.87985131\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 353.31\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 374.73\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 359.12\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 339.4\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 327.53\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 334.83\n    oil:\n      datetime: '2021-01-01'\n      source: eGrid 2020\n      value: 803.8986689\n  lifecycle:\n    battery discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; National Laboratory of the Rockies\n        value: 392.36\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; National Laboratory of the Rockies\n        value: 410.97\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; National Laboratory of the Rockies\n        value: 394.05\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; National Laboratory of the Rockies\n        value: 373.32\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; National Laboratory of the Rockies\n        value: 361.47\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; National Laboratory of the Rockies\n        value: 363.7\n    biomass:\n      datetime: '2020-01-01'\n      source: eGrid 2020\n      value: 285.8412641\n    coal:\n      datetime: '2020-01-01'\n      source: eGrid 2020; IPCC 2014\n      value: 1049.615358\n    gas:\n      datetime: '2021-01-01'\n      source: eGrid 2020; IPCC 2014\n      value: 526.0342962\n    geothermal:\n      datetime: '2021-01-01'\n      source: eGrid 2020; IPCC 2014\n      value: 108.87985131\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 377.31\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 398.73\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 383.12\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 363.4\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 351.53\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 358.83\n    oil:\n      datetime: '2021-01-01'\n      source: eGrid 2020; IPCC 2014\n      value: 1047.8986688999998\n    solar:\n      datetime: '2021-01-01'\n      source: INCER ACV\n      value: 26.22100877\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 2.6751196302328822e-05\n        biomass: 0.0028266210534100247\n        coal: 0.28123441182649267\n        gas: 0.35454908348416\n        geothermal: 0.0019874998216454676\n        hydro: 0.0744535458395\n        hydro discharge: 0.002060774058131473\n        nuclear: 0.19644076851110243\n        oil: 0.001310740719245416\n        solar: 0.014299303424240855\n        unknown: 0.01406260359628589\n        wind: 0.05674773295745195\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 3.199270653000092e-05\n        biomass: 0.0028735632496634557\n        coal: 0.2551030005292525\n        gas: 0.3377156871431816\n        geothermal: 0.0020752268213588805\n        hydro: 0.08657998205558926\n        hydro discharge: 0.0006458901903401022\n        nuclear: 0.21538252440062855\n        oil: 0.000687823169015468\n        solar: 0.013661544163452185\n        unknown: 0.014521858034886263\n        wind: 0.07072079900234686\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 3.735743809937116e-05\n        biomass: 0.002846683471598554\n        coal: 0.21070541496440243\n        gas: 0.391809333491901\n        geothermal: 0.001962938872514026\n        hydro: 0.07884476068291084\n        hydro discharge: 0.0008278123361740544\n        nuclear: 0.19538459968023322\n        oil: 0.000730295061438464\n        solar: 0.021233814915913175\n        unknown: 0.016564302040173416\n        wind: 0.0790524026400058\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.000244989052381138\n        biomass: 0.002809128988987215\n        coal: 0.2240286568696107\n        gas: 0.360300096070007\n        geothermal: 0.0019879007587004283\n        hydro: 0.07381241222766502\n        hydro discharge: 0.0008213275150807546\n        nuclear: 0.19824224228709858\n        oil: 0.0008557548842680487\n        solar: 0.024266747224198998\n        unknown: 0.01614842777486053\n        wind: 0.09648214040820481\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0006644936781819898\n        biomass: 0.00248965054583771\n        coal: 0.20441566515927173\n        gas: 0.3682374077728569\n        geothermal: 0.0018021250007380712\n        hydro: 0.07543869511605193\n        hydro discharge: 4.537677447046086e-06\n        nuclear: 0.18797920726572112\n        oil: 0.001466124673963169\n        solar: 0.03143540285660474\n        unknown: 0.015793964123191024\n        wind: 0.11027244203767458\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0011208311628839352\n        biomass: 0.0022911596155774897\n        coal: 0.1681048880022955\n        gas: 0.40767285419088717\n        geothermal: 0.0017633983825025336\n        hydro: 0.06664840375503789\n        hydro discharge: 2.2653203277626558e-05\n        nuclear: 0.1919297673328401\n        oil: 0.0008875521364880435\n        solar: 0.036972927459937105\n        unknown: 0.017414508337906885\n        wind: 0.10517083862296002\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.4048\n    - datetime: '2021-01-01'\n      value: 0.3991\n    - datetime: '2022-01-01'\n      value: 0.4122\n    - datetime: '2023-01-01'\n      value: 0.4112\n    - datetime: '2024-01-01'\n      value: 0.4255\n    - datetime: '2025-01-01'\n      value: 0.4392\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.4174\n    - datetime: '2021-01-01'\n      value: 0.4112\n    - datetime: '2022-01-01'\n      value: 0.4202\n    - datetime: '2023-01-01'\n      value: 0.4139\n    - datetime: '2024-01-01'\n      value: 0.4264\n    - datetime: '2025-01-01'\n      value: 0.4348\nisRenewable:\n  battery discharge:\n    - datetime: '2020-01-01'\n      value: 0.1972\n    - datetime: '2021-01-01'\n      value: 0.2025\n    - datetime: '2022-01-01'\n      value: 0.2221\n    - datetime: '2023-01-01'\n      value: 0.22\n    - datetime: '2024-01-01'\n      value: 0.2411\n    - datetime: '2025-01-01'\n      value: 0.2585\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1971\n    - datetime: '2021-01-01'\n      value: 0.2036\n    - datetime: '2022-01-01'\n      value: 0.2186\n    - datetime: '2023-01-01'\n      value: 0.2102\n    - datetime: '2024-01-01'\n      value: 0.2243\n    - datetime: '2025-01-01'\n      value: 0.2371\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\nsources:\n  INCER ACV:\n    link: https://docs.google.com/spreadsheets/d/1w5DJ7sPen6axIHU8TCVcuzNCjlct4I6JAbhUlw-ZXu8/edit?usp=sharing\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\n  eGrid 2020:\n    link: https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing\n  eGrid 2021:\n    link: ' https://drive.google.com/file/d/1_FAAuTtIdMuORZKsqHnd9vMNHlQgYarh/view?usp=sharing'\n  eGrid 2022:\n    link: https://www.epa.gov/egrid/historical-egrid-data\n  eGrid 2023:\n    link: https://www.epa.gov/egrid/detailed-data\nsubZoneNames:\n  - US-AK\n  - US-AK-SEAPA\n  - US-CAL-BANC\n  - US-CAL-CISO\n  - US-CAL-IID\n  - US-CAL-LDWP\n  - US-CAL-TIDC\n  - US-CAR-CPLE\n  - US-CAR-CPLW\n  - US-CAR-DUK\n  - US-CAR-SC\n  - US-CAR-SCEG\n  - US-CAR-YAD\n  - US-CENT-SPA\n  - US-CENT-SWPP\n  - US-FLA-FMPP\n  - US-FLA-FPC\n  - US-FLA-FPL\n  - US-FLA-GVL\n  - US-FLA-HST\n  - US-FLA-JEA\n  - US-FLA-SEC\n  - US-FLA-TAL\n  - US-FLA-TEC\n  - US-HI\n  - US-MIDA-PJM\n  - US-MIDW-AECI\n  - US-MIDW-LGEE\n  - US-MIDW-MISO\n  - US-NE-ISNE\n  - US-NW-AVA\n  - US-NW-BPAT\n  - US-NW-CHPD\n  - US-NW-DOPD\n  - US-NW-GCPD\n  - US-NW-GRID\n  - US-NW-IPCO\n  - US-NW-NEVP\n  - US-NW-NWMT\n  - US-NW-PACE\n  - US-NW-PACW\n  - US-NW-PGE\n  - US-NW-PSCO\n  - US-NW-PSEI\n  - US-NW-SCL\n  - US-NW-TPWR\n  - US-NW-WACM\n  - US-NW-WAUW\n  - US-NY-NYIS\n  - US-SE-SEPA\n  - US-SE-SOCO\n  - US-SW-AZPS\n  - US-SW-EPE\n  - US-SW-PNM\n  - US-SW-SRP\n  - US-SW-TEPC\n  - US-SW-WALC\n  - US-TEN-TVA\n  - US-TEX-ERCO\ntimezone: US/Central\nzone_name: United States\n"
  },
  {
    "path": "config/zones/UY.yaml",
    "content": "bounding_box:\n  - - -58.43398433984335\n    - -34.96975129408742\n  - - -53.10953109531091\n    - -30.102638579196146\ncenter_point:\n  - -55.87466207590916\n  - -32.5622335370598\ncentroid:\n  - -56.108361083610774\n  - -32.559729744321984\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 420.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 740.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 750.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1110.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1540.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 280.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 300.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 330.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 80.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 70.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1520.0\ncontributors:\n  - jarek\n  - corradio\n  - nessie2013\n  - ZachEichen\n  - ananyasharma20\ncountry: UY\ncountry_name: Uruguay\ncurrency: UYU\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.10189178210352563\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.5322689371691393\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.005807650838278039\n        solar: 0.013372358999566437\n        unknown: 0.0\n        wind: 0.34665924462806685\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08922782706975073\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.5427438121367806\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.04240009566862567\n        solar: 0.013863384072457234\n        unknown: 0.0\n        wind: 0.31176490117183686\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07294626391000532\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.5869869372678077\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.018352633824324324\n        solar: 0.018086425703040337\n        unknown: 0.0\n        wind: 0.3036277586973342\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0654664697660637\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.4957158682889593\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.02950662902675255\n        solar: 0.030168741379979058\n        unknown: 0.0\n        wind: 0.37914220536229815\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.05815814588529661\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.5641765425318966\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.020438186661280396\n        solar: 0.028492099967150297\n        unknown: 0.0\n        wind: 0.3287349870761098\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.08468185479073317\n        coal: 6.59190490809591e-05\n        gas: 0.024013678413536913\n        geothermal: 0.0\n        hydro: 0.33957226081757397\n        hydro discharge: 0.000507628760693358\n        nuclear: 0.003827639280891196\n        oil: 0.06898748504076768\n        solar: 0.036891293712008055\n        unknown: 0.0008484239753806226\n        wind: 0.4406037579031474\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07303559006116893\n        coal: 2.716601900530922e-05\n        gas: 0.0025670670099371606\n        geothermal: 0.0\n        hydro: 0.3668311383666573\n        hydro discharge: 3.058338748759803e-05\n        nuclear: 0.00027276987818213857\n        oil: 0.17346466458981274\n        solar: 0.033294828749634915\n        unknown: 0.0003064269840484016\n        wind: 0.350169781879017\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.07298196307604185\n        coal: 0.0\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.4227444933954138\n        hydro discharge: 0.0\n        nuclear: 1.5401276940754675e-05\n        oil: 0.10218022765118535\n        solar: 0.03829332106711431\n        unknown: 0.00014799074306594834\n        wind: 0.36363661131760455\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.09581798555076412\n        coal: 2.4754602352701224e-07\n        gas: 1.5141990442545767e-07\n        geothermal: 0.0\n        hydro: 0.36335425559431467\n        hydro discharge: 0.0\n        nuclear: 0.0017245663772034168\n        oil: 0.08086309821899737\n        solar: 0.040384944955206836\n        unknown: 0.01060976982660328\n        wind: 0.4072449456333638\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.1293631502974144\n        coal: 1.5651030164388572e-07\n        gas: 9.569023623823065e-08\n        geothermal: 0.0\n        hydro: 0.4983044878157197\n        hydro discharge: 0.0\n        nuclear: 3.503235767365732e-05\n        oil: 0.008651041237695145\n        solar: 0.03225785414410065\n        unknown: 0.0002458679526720795\n        wind: 0.3311423018301735\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: UY.fetch_consumption\n  production: UY.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Montevideo\nzone_name: Uruguay\n"
  },
  {
    "path": "config/zones/UZ.yaml",
    "content": "bounding_box:\n  - - 55.997790533287294\n    - 37.18830730933749\n  - - 73.11853118531187\n    - 45.56232808111943\ncenter_point:\n  - 64.18417880216785\n  - 41.39517100143724\ncentroid:\n  - 66.14360204736195\n  - 40.8635212297955\ncapacity:\n  solar:\n    - datetime: '2024-08-30'\n      source: gov.uz\n      comment: The Ministry of Energy of the Republic of Uzbekistan\n      value: 2300\n    - datetime: '2026-01-01'\n      source: gov.uz\n      comment: The Ministry of Energy of the Republic of Uzbekistan\n      value: 3930\n  wind:\n    - datetime: '2024-08-30'\n      source: gov.uz\n      comment: The Ministry of Energy of the Republic of Uzbekistan\n      value: 500\n    - datetime: '2026-01-01'\n      source: gov.uz\n      comment: The Ministry of Energy of the Republic of Uzbekistan\n      value: 1652\n  hydro:\n    - datetime: '2024-08-29'\n      source: stat.uz\n      comment: Statistics Agency under the President of the Republic of Uzbekistan\n      value: 2381\n    - datetime: '2026-01-01'\n      source: gov.uz\n      comment: The Ministry of Energy of the Republic of Uzbekistan\n      value: 2441\n  gas:\n    - datetime: '2024-08-29'\n      source: stat.uz\n      comment: Statistics Agency under the President of the Republic of Uzbekistan\n      value: 13874\ncountry: UZ\ncountry_name: Uzbekistan\ncurrency: UZS\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Asia\ntimezone: Asia/Samarkand\nzone_name: Uzbekistan\n"
  },
  {
    "path": "config/zones/VC.yaml",
    "content": "bounding_box:\n  - - -61.27081270812704\n    - 13.14611571563755\n  - - -61.166411664116595\n    - 13.36936463757904\ncenter_point:\n  - -61.21861218612182\n  - 13.257740176608294\ncentroid:\n  - -61.216812168121635\n  - 13.233888796058986\ncapacity:\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\ncountry: VC\ncountry_name: Saint Vincent and the Grenadines\ncurrency: XCD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/St_Vincent\nzone_name: Saint Vincent and the Grenadines\n"
  },
  {
    "path": "config/zones/VE.yaml",
    "content": "bounding_box:\n  - - -73.37773377733772\n    - 0.655624749577242\n  - - -59.81639816398159\n    - 12.198738880219125\ncenter_point:\n  - -66.62619358017581\n  - 6.1445372481449185\ncentroid:\n  - -65.93656804407969\n  - 7.592686628815739\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 60.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 12240.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 12590.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 16830.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 16910.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 16830.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 16910.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 4110.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 4390.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 4360.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 4660.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\ncountry: VE\ncountry_name: Venezuela\ncurrency: VEF\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/Caracas\nzone_name: Venezuela\n"
  },
  {
    "path": "config/zones/VI.yaml",
    "content": "bounding_box:\n  - - -64.87804878048776\n    - 17.689803710280245\n  - - -64.55764557645571\n    - 17.775668680257738\ncenter_point:\n  - -64.71784717847174\n  - 17.73273619526899\ncentroid:\n  - -64.77124771247708\n  - 17.738937554211812\ncapacity:\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 330.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: VI\ncountry_name: USA\ncurrency: USD\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Americas\ntimezone: America/St_Thomas\nzone_name: Virgin Islands\n"
  },
  {
    "path": "config/zones/VN.yaml",
    "content": "bounding_box:\n  - - 102.12042120421202\n    - 8.590979058331172\n  - - 109.46449464494643\n    - 23.36547822579297\ncenter_point:\n  - 107.67929054213772\n  - 15.790569851015427\ncentroid:\n  - 106.15360914332568\n  - 16.184287678591165\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 270.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 390.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 380.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 420.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 15570.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 17800.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 19000.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 20290.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 22690.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 24610.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 26520.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 27240.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 8150.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 17810.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 17990.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 20330.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 20820.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 21850.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 22530.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 22920.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 23710.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 4990.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 16660.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 16700.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 18590.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 18670.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 240.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 370.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 520.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 4120.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 5070.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 5890.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 6180.0\ncontributors:\n  - alixunderplatz\n  - MuffinCompiler\n  - VIKTORVAV99\ncountry: VN\ncountry_name: Vietnam\ncurrency: VND\nemissionFactors:\n  direct:\n    unknown:\n      - datetime: '2022-01-01'\n        source: EMBER 2022; assumes 38.76% coal, 36.91% hydro, 10.68% gas, 10.14% solar, 3.09% wind, 0.14% biomass and 0.27% from other thermal\n        value: 336\n  lifecycle:\n    unknown:\n      - datetime: '2022-01-01'\n        source: EMBER 2022; assumes 38.76% coal, 36.91% hydro, 10.68% gas, 10.14% solar, 3.09% wind, 0.14% biomass and 0.27% from other thermal\n        value: 386\nfallbackZoneMixes:\n  _source: EMBER 2022\n  powerOriginRatios:\n    value:\n      biomass: 0.0014\n      coal: 0.3876\n      gas: 0.1068\n      hydro: 0.3691\n      solar: 0.1014\n      unknown: 0.0027\n      wind: 0.0309\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nisLowCarbon:\n  unknown:\n    - datetime: '2022-01-01'\n      source: EMBER 2022; assumes 38.76% coal, 36.91% hydro, 10.68% gas, 10.14% solar, 3.09% wind, 0.14% biomass and 0.27% from other thermal\n      value: 0.5028\nisRenewable:\n  unknown:\n    - datetime: '2022-01-01'\n      source: EMBER 2022; assumes 38.76% coal, 36.91% hydro, 10.68% gas, 10.14% solar, 3.09% wind, 0.14% biomass and 0.27% from other thermal\n      value: 0.5028\nparsers:\n  consumption: VN.fetch_consumption\n  price: VN.fetch_price\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\nsources:\n  EMBER 2022:\n    link: https://ember-climate.org/countries-and-regions/countries/viet-nam/\ntimezone: Asia/Ho_Chi_Minh\nzone_name: Vietnam\n"
  },
  {
    "path": "config/zones/VU.yaml",
    "content": "bounding_box:\n  - - 166.52146521465212\n    - -19.657164981433297\n  - - 169.43749437494373\n    - -13.708153644825515\ncenter_point:\n  - 168.1450814508145\n  - -16.573181476408095\ncentroid:\n  - 167.92384287479237\n  - -16.292246906454437\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: VU\ncountry_name: Vanuatu\ncurrency: VUV\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Efate\nzone_name: Vanuatu\n"
  },
  {
    "path": "config/zones/WS.yaml",
    "content": "bounding_box:\n  - - -172.7819278192781\n    - -14.051613524735515\n  - - -171.43911439114382\n    - -13.463438480389641\ncenter_point:\n  - -172.21312213122124\n  - -13.801174028967807\ncentroid:\n  - -172.0957609576095\n  - -13.782713060422646\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 20.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\ncountry: WS\ncountry_name: Samoa\ncurrency: WST\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Oceania\ntimezone: Pacific/Apia\nzone_name: Samoa\n"
  },
  {
    "path": "config/zones/XK.yaml",
    "content": "bounding_box:\n  - - 20.02520025200255\n    - 41.87367250444305\n  - - 21.764017640176434\n    - 43.25752960391377\ncenter_point:\n  - 20.820077774509578\n  - 42.59485102103011\ncentroid:\n  - 20.795007950079523\n  - 42.56909925665897\ncapacity:\n  coal:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 1288.0\n  hydro:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 68.0\n  wind:\n    - datetime: '2021-01-01'\n      source: entsoe.eu\n      value: 32.0\n    - datetime: '2022-01-01'\n      source: entsoe.eu\n      value: 136.0\ncontributors:\n  - veqtrus\ncountry: XK\ncountry_name: Kosovo\ncurrency: EUR\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9447379017783285\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.005432064852648763\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0498275361549771\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9447379017783285\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.005432064852648763\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.0498275361549771\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.944738381475537\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.005431956334587535\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.04982654073467818\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.9615268271994712\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.0037817640729053033\n        hydro discharge: 0.0\n        nuclear: 0.0\n        oil: 0.0\n        solar: 0.0\n        unknown: 0.0\n        wind: 0.03468923949819431\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 4.353036795176602e-05\n        coal: 0.9975576208818636\n        gas: 0.00020344715880278754\n        geothermal: 1.7899540164261716e-07\n        hydro: 0.0017422788375226076\n        hydro discharge: 2.8718087925927422e-05\n        nuclear: 0.000221023193516374\n        oil: 4.827949365406371e-07\n        solar: 3.951528761216786e-05\n        unknown: 0.00010016024341640502\n        wind: 6.297518034488738e-05\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0023816003001928695\n        coal: 0.835014786998203\n        gas: 0.03384239731342175\n        geothermal: 0.00020927339476325204\n        hydro: 0.06047395765504976\n        hydro discharge: 0.0020188910831115204\n        nuclear: 0.0183562161017522\n        oil: 0.004128541971831687\n        solar: 0.0058458081620847355\n        unknown: 0.001751888418549963\n        wind: 0.03597584692153015\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0033897390890116714\n        coal: 0.7875672777743695\n        gas: 0.038787231841712566\n        geothermal: 0.0003112069146015089\n        hydro: 0.10406654495068075\n        hydro discharge: 0.003069996226269464\n        nuclear: 0.01951752066950715\n        oil: 0.003960144316652212\n        solar: 0.007718163854089555\n        unknown: 0.0020727838824586447\n        wind: 0.02953889531474525\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 2.2592924488630297e-08\n        biomass: 0.003470411986561186\n        coal: 0.7999001644487332\n        gas: 0.0499852784504032\n        geothermal: 0.0004942750917196887\n        hydro: 0.08680507561280547\n        hydro discharge: 0.0019120424270334232\n        nuclear: 0.018420251788848048\n        oil: 0.0029364007820069584\n        solar: 0.01435756790059774\n        unknown: 0.002092146765935501\n        wind: 0.0196257037300602\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  consumption: ENTSOE.fetch_consumption\n  consumptionForecast: ENTSOE.fetch_consumption_forecast\n  generationForecast: ENTSOE.fetch_generation_forecast\n  production: ENTSOE.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n  productionPerModeForecast: ENTSOE.fetch_wind_solar_forecasts\n  productionPerModeForecastDayAhead: ENTSOE.fetch_wind_solar_forecasts_day_ahead\n  productionPerModeForecastIntraday: ENTSOE.fetch_wind_solar_forecasts_intraday\n  productionPerModeForecastLatest: ENTSOE.fetch_wind_solar_forecasts_current\nregion: Europe\ntimezone: Europe/Belgrade\nzone_name: Kosovo\n"
  },
  {
    "path": "config/zones/XX.yaml",
    "content": "bounding_box:\n  - - 32.704233654148894\n    - 35.0036150292379\n  - - 34.585475775831256\n    - 35.69471538398224\ncenter_point:\n  - 33.644854714990075\n  - 35.34916520661007\ncentroid:\n  - 33.508806431331756\n  - 35.20741965776527\ncountry: null\ncountry_name: Northern Cyprus\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nregion: Europe\ntimezone: Asia/Nicosia\nzone_name: Northern Cyprus\n"
  },
  {
    "path": "config/zones/YE.yaml",
    "content": "bounding_box:\n  - - 42.611826118261206\n    - 12.30463900985805\n  - - 54.47034470344704\n    - 18.99495125393824\ncenter_point:\n  - 47.84706497522005\n  - 15.7867314011554\ncentroid:\n  - 47.581614398684586\n  - 15.034887883231493\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 400.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 530.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 790.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 250.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 290.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1180.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 1270.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 1290.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1400.0\ncountry: YE\ncountry_name: Yemen\ncurrency: YER\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Asia\ntimezone: Asia/Aden\nzone_name: Yemen\n"
  },
  {
    "path": "config/zones/YT.yaml",
    "content": "bounding_box:\n  - - 45.0418504185042\n    - -12.886712098707434\n  - - 45.200252002520045\n    - -12.69780916475694\ncenter_point:\n  - 45.12105121051212\n  - -12.792260631732187\ncentroid:\n  - 45.12465124651248\n  - -12.769363306404854\ncapacity:\n  oil:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 99.0\n  solar:\n    - datetime: '2017-01-01'\n      source: IRENA.org\n      value: 15.15\n    - datetime: '2018-01-01'\n      source: IRENA.org\n      value: 15.73\n    - datetime: '2019-01-01'\n      source: IRENA.org\n      value: 16.81\n    - datetime: '2020-01-01'\n      source: IRENA.org\n      value: 18.57\n    - datetime: '2021-01-01'\n      source: IRENA.org\n      value: 30.03\n    - datetime: '2023-01-01'\n      source: IRENA.org\n      value: 31.23\ncountry: YT\ncountry_name: Mayotte\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: IRENA.fetch_production_capacity\nregion: Africa\ntimezone: Indian/Mayotte\nzone_name: Mayotte\n"
  },
  {
    "path": "config/zones/ZA.yaml",
    "content": "bounding_box:\n  - - 16.486364863648646\n    - -46.95507002011344\n  - - 37.89577895778959\n    - -22.131507199618248\ncenter_point:\n  - 24.738611853654092\n  - -28.466860005694404\ncentroid:\n  - 24.86591619045054\n  - -29.15101718443006\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 260.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 41490.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 42290.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 43880.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 44680.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 46270.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 45890.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 46690.0\n  gas:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1290.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 750.0\n  nuclear:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 1940.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 1930.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1940.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1930.0\n  oil:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2420.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 3450.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 4810.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 4910.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 5990.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 6320.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 6330.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 6160.0\n    - datetime: '2024-01-01'\n      source: Ember, Yearly electricity data\n      value: 6670.0\n  wind:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2090.0\n    - datetime: '2020-01-01'\n      source: Ember, Yearly electricity data\n      value: 2520.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2490.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3160.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 3440.0\ncontributors:\n  - IV1T3\ncountry: ZA\ncountry_name: South Africa\ncurrency: ZAR\nemissionFactors:\n  direct:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average\n        value: 656.24\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average\n        value: 641.14\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average\n        value: 637.6\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average\n        value: 636.0\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average\n        value: 658.32\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average\n        value: 646.53\n  lifecycle:\n    hydro discharge:\n      - _comment: used storage values greater than zero.\n        datetime: '2020-01-01'\n        source: Electricity Maps, 2020 zone average; IPCC 2014\n        value: 680.24\n      - _comment: used storage values greater than zero.\n        datetime: '2021-01-01'\n        source: Electricity Maps, 2021 zone average; IPCC 2014\n        value: 665.14\n      - _comment: used storage values greater than zero.\n        datetime: '2022-01-01'\n        source: Electricity Maps, 2022 zone average; IPCC 2014\n        value: 661.6\n      - _comment: used storage values greater than zero.\n        datetime: '2023-01-01'\n        source: Electricity Maps, 2023 zone average; IPCC 2014\n        value: 660.0\n      - _comment: used storage values greater than zero.\n        datetime: '2024-01-01'\n        source: Electricity Maps, 2024 zone average; IPCC 2014\n        value: 682.32\n      - _comment: used storage values greater than zero.\n        datetime: '2025-01-01'\n        source: Electricity Maps, 2025 zone average; IPCC 2014\n        value: 670.53\nfallbackZoneMixes:\n  powerOriginRatios:\n    - _source: Electricity Maps, 2015 average\n      datetime: '2015-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.84842248637789\n        gas: 3.476470527164604e-05\n        geothermal: 0.0\n        hydro: 0.0060998505339288816\n        hydro discharge: 0.025580767615433594\n        nuclear: 0.05183612201972084\n        oil: 0.010793678792186435\n        solar: 0.02309443781351213\n        unknown: 0.0005424864389259665\n        wind: 0.033595356617739484\n    - _source: Electricity Maps, 2016 average\n      datetime: '2016-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0\n        coal: 0.8484209927505983\n        gas: 3.4764641058272466e-05\n        geothermal: 0.0\n        hydro: 0.006099840599747045\n        hydro discharge: 0.025580720365575602\n        nuclear: 0.051836030527260726\n        oil: 0.010793661530356033\n        solar: 0.023096157087432772\n        unknown: 0.0005424854909769813\n        wind: 0.03359529787349316\n    - _source: Electricity Maps, 2017 average\n      datetime: '2017-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000760892274589424\n        coal: 0.844572491359832\n        gas: 8.284184102038638e-06\n        geothermal: 0.0\n        hydro: 0.006900259846437895\n        hydro discharge: 0.020041923174845506\n        nuclear: 0.048710309529651746\n        oil: 0.013288739108568601\n        solar: 0.025204953835438717\n        unknown: 0.0004831570072476832\n        wind: 0.04002900778013009\n    - _source: Electricity Maps, 2018 average\n      datetime: '2018-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.000173947558842206\n        coal: 0.8752628301955635\n        gas: 1.3540860096541649e-05\n        geothermal: 0.0\n        hydro: 0.004846967391191555\n        hydro discharge: 0.02616477406084253\n        nuclear: 0.04321701102298505\n        oil: 0.004468535054515985\n        solar: 0.017649830612491275\n        unknown: 0.0004804502279955954\n        wind: 0.027722106945612692\n    - _source: Electricity Maps, 2019 average\n      datetime: '2019-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0002621345260866036\n        coal: 0.8498764387939348\n        gas: 6.939507185274348e-06\n        geothermal: 0.0\n        hydro: 0.0028990989234765857\n        hydro discharge: 0.028350154939791854\n        nuclear: 0.05926960859155413\n        oil: 0.009263782772792738\n        solar: 0.02109751165266777\n        unknown: 8.75132256739638e-05\n        wind: 0.028886792477136637\n    - _source: Electricity Maps, 2020 average\n      datetime: '2020-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.00039741943897321854\n        coal: 0.8464302597332872\n        gas: 1.4361373827902206e-05\n        geothermal: 0.0\n        hydro: 0.003448888205842276\n        hydro discharge: 0.03155911499240145\n        nuclear: 0.05290767346134312\n        oil: 0.008676974198060738\n        solar: 0.026130748066342163\n        unknown: 0.0\n        wind: 0.030434534965674397\n    - _source: Electricity Maps, 2021 average\n      datetime: '2021-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0005550119630604033\n        coal: 0.8268065924868174\n        gas: 1.2419063868655336e-06\n        geothermal: 0.0\n        hydro: 0.007023381547052183\n        hydro discharge: 0.029636903611890135\n        nuclear: 0.05446166987493735\n        oil: 0.014220180835782492\n        solar: 0.029868263442209574\n        unknown: 0.0\n        wind: 0.0374267298542658\n    - _source: Electricity Maps, 2022 average\n      datetime: '2022-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0010104816471092491\n        coal: 0.8200639840543928\n        gas: 1.9648686436505895e-05\n        geothermal: 0.0\n        hydro: 0.014524550051118855\n        hydro discharge: 0.026930971638054014\n        nuclear: 0.046777570430097476\n        oil: 0.016606120835264974\n        solar: 0.029039561136780613\n        unknown: 0.0\n        wind: 0.04502708181511649\n    - _source: Electricity Maps, 2023 average\n      datetime: '2023-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0011619642039834147\n        coal: 0.8094105863589608\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.009646156552495752\n        hydro discharge: 0.027541670335339056\n        nuclear: 0.03977775737224078\n        oil: 0.02455661197517739\n        solar: 0.03106976815652497\n        unknown: 0.0\n        wind: 0.05683535650908905\n    - _source: Electricity Maps, 2024 average\n      datetime: '2024-01-01'\n      value:\n        battery discharge: 0.0\n        biomass: 0.0011050903063520342\n        coal: 0.8343913566249075\n        gas: 0.0\n        geothermal: 0.0\n        hydro: 0.005247400461642989\n        hydro discharge: 0.022812642697142897\n        nuclear: 0.03754746705427782\n        oil: 0.014101937491012602\n        solar: 0.031763672924306964\n        unknown: 0.0\n        wind: 0.05303024755245981\nhas_day_ahead_price_license: false\nhide_day_ahead_price: false\nisLowCarbon:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.1307\n    - datetime: '2021-01-01'\n      value: 0.1472\n    - datetime: '2022-01-01'\n      value: 0.1504\n    - datetime: '2023-01-01'\n      value: 0.1503\n    - datetime: '2024-01-01'\n      value: 0.1281\n    - datetime: '2025-01-01'\n      value: 0.1435\n  unknown:\n    value: 1\nisRenewable:\n  hydro discharge:\n    - datetime: '2020-01-01'\n      value: 0.078\n    - datetime: '2021-01-01'\n      value: 0.0932\n    - datetime: '2022-01-01'\n      value: 0.1039\n    - datetime: '2023-01-01'\n      value: 0.1091\n    - datetime: '2024-01-01'\n      value: 0.0878\n    - datetime: '2025-01-01'\n      value: 0.0907\n  unknown:\n    value: 1\nparsers:\n  production: ESKOM.fetch_production\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\nsources:\n  IPCC 2014:\n    link: https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_annex-iii.pdf#page=7\n  National Laboratory of the Rockies:\n    link: https://docs.nrel.gov/docs/fy21osti/80580.pdf\ntimezone: Africa/Johannesburg\nzone_name: South Africa\n"
  },
  {
    "path": "config/zones/ZM.yaml",
    "content": "bounding_box:\n  - - 21.980019800198022\n    - -18.065800871183633\n  - - 33.67293672936731\n    - -8.194191489437074\ncenter_point:\n  - 27.793429278161966\n  - -13.134822739245156\ncentroid:\n  - 28.652614526145285\n  - -12.804842711999566\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 40.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 330.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 2400.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 2710.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 3170.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 0.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2019-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 130.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 200.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 190.0\ncountry: ZM\ncountry_name: Zambia\ncurrency: ZMW\nfallbackZoneMixes:\n  _source: Our world in data 2019\n  _url: https://ourworldindata.org/grapher/electricity-prod-source-stacked?time=earliest..latest&country=~ZMB\n  powerOriginRatios:\n    value:\n      coal: 0.11\n      hydro: 0.83\n      oil: 0.06\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Maputo\nzone_name: Zambia\n"
  },
  {
    "path": "config/zones/ZW.yaml",
    "content": "bounding_box:\n  - - 25.227252272522747\n    - -22.3976886065485\n  - - 33.03573035730358\n    - -15.61435597832601\ncenter_point:\n  - 29.321467588966293\n  - -18.989150357823178\ncentroid:\n  - 29.81626959126735\n  - -18.691388509591135\ncapacity:\n  biomass:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 100.0\n  coal:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 950.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 1000.0\n    - datetime: '2023-01-01'\n      source: Ember, Yearly electricity data\n      value: 1330.0\n  hydro:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 780.0\n    - datetime: '2018-01-01'\n      source: Ember, Yearly electricity data\n      value: 1080.0\n  solar:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\n    - datetime: '2021-01-01'\n      source: Ember, Yearly electricity data\n      value: 30.0\n    - datetime: '2022-01-01'\n      source: Ember, Yearly electricity data\n      value: 50.0\n  unknown:\n    - datetime: '2017-01-01'\n      source: Ember, Yearly electricity data\n      value: 10.0\ncountry: ZW\ncountry_name: Zimbabwe\ncurrency: ZWL\nhas_day_ahead_price_license: False\nhide_day_ahead_price: False\nparsers:\n  productionCapacity: EMBER.fetch_production_capacity\nregion: Africa\ntimezone: Africa/Harare\nzone_name: Zimbabwe\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/CA_ON.py",
    "content": "import logging\nfrom datetime import datetime\nfrom typing import Any\n\nimport pandas as pd\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\n\nlogger = logging.getLogger(__name__)\n\nMODE_MAPPING = {\n    \"Nuclear\": \"nuclear\",\n    \"Hydroelectric\": \"hydro\",\n    \"Gas/Oil\": \"gas\",\n    \"Wind\": \"wind\",\n    \"Biofuel\": \"biomass\",\n    \"Solar\": \"solar\",\n}\n\n\n\"\"\"Disclaimer: only valid for real-time data, historical capacity is not available\"\"\"\nOUTLOOK_URL = \"https://www.ieso.ca/-/media/Files/IESO/Document-Library/planning-forecasts/reliability-outlook/ReliabilityOutlookTables_{date}.ashx\"\n\n\ndef get_data_from_url(session: Session, target_datetime: datetime) -> pd.DataFrame:\n    file_url = OUTLOOK_URL.format(date=target_datetime.strftime(\"%Y%b\"))\n    file_response: Response = session.get(file_url)\n    if \"Error-404\" not in file_response.url and file_response.ok:\n        df = pd.read_excel(\n            file_response.url, sheet_name=\"Table 4.1\", header=4, skipfooter=3\n        )\n        return df\n    else:\n        raise ValueError(\n            f\"Failed to fetch capacity data for IESO from url: {file_url} with date {target_datetime.date()}\"\n        )\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session\n) -> dict[str, Any]:\n    last_full_quarter_month = get_last_month_of_last_full_quarter(target_datetime)\n    df = get_data_from_url(session, last_full_quarter_month)\n\n    df = df.rename(\n        columns={\"Fuel Type\": \"mode\", \"Total Installed Capacity\\n(MW)\": \"value\"}\n    )\n    df = df[[\"mode\", \"value\"]]\n    df[\"mode\"] = df[\"mode\"].apply(lambda x: MODE_MAPPING.get(x))\n    df = df.dropna(subset=[\"mode\"])  # Drop rows where 'mode' is None\n    capacity = {}\n    for _idx, data in df.iterrows():\n        capacity[data[\"mode\"]] = {\n            \"datetime\": last_full_quarter_month.strftime(\"%Y-%m-%d\"),\n            \"value\": round(data[\"value\"], 0),\n            \"source\": \"ieso.ca\",\n        }\n    logger.info(\n        f\"Fetched capacity for {zone_key} on {target_datetime.date()}: \\n{capacity}\"\n    )\n    return capacity\n\n\ndef get_last_month_of_last_full_quarter(\n    target_datetime: datetime,\n) -> datetime:\n    # Calculate the last month of the last full quarter\n    current_quarter = ((target_datetime.month - 1) // 3) + 1\n    last_full_quarter = current_quarter - 1 if current_quarter > 1 else 4\n    year = target_datetime.year if current_quarter > 1 else target_datetime.year - 1\n    quarter_end_month = last_full_quarter * 3\n    last_day_of_month = 31 if quarter_end_month in [3, 12] else 30\n    return target_datetime.replace(\n        year=year, month=quarter_end_month, day=last_day_of_month\n    )\n\n\nif __name__ == \"__main__\":\n    logging.basicConfig(level=logging.INFO)\n    fetch_production_capacity(ZoneKey(\"CA_ON\"), datetime(2025, 3, 1), Session())\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/CEA.py",
    "content": "from datetime import datetime\nfrom logging import getLogger\nfrom typing import Any\n\nimport pandas as pd\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config.capacity import CAPACITY_PARSER_SOURCE_TO_ZONES\nfrom electricitymap.contrib.types import ZoneKey\n\nlogger = getLogger(__name__)\nSOURCE = \"cea.nic.in\"\nCAPACITY_URL = \"https://cea.nic.in/api/installed_capacity.php\"\nREGION_MAPPING = {\n    \"Northern\": \"IN-NO\",\n    \"Western\": \"IN-WE\",\n    \"Southern\": \"IN-SO\",\n    \"Eastern\": \"IN-EA\",\n    \"North Eastern\": \"IN-NE\",\n}\nMODE_MAPPING = {\n    \"Coal\": \"coal\",\n    \"Gas\": \"gas\",\n    \"Diesel\": \"oil\",\n    \"Nuclear\": \"nuclear\",\n    \"Hydro\": \"hydro\",\n}\nIN_ZONES = CAPACITY_PARSER_SOURCE_TO_ZONES[\"CEA\"]\n\nIN_STATE_TO_ZONE_MAPPING = {\n    \"Andhra Pradesh\": \"IN-SO\",\n    \"Arunachal Pradesh\": \"IN-NE\",\n    \"Assam\": \"IN-NE\",\n    \"Bihar\": \"IN-EA\",\n    \"Chhatisgarh\": \"IN-WE\",\n    \"Goa\": \"IN-WE\",\n    \"Gujarat\": \"IN-WE\",\n    \"Haryana\": \"IN-NO\",\n    \"Himachal Pradesh\": \"IN-NO\",\n    \"Jammu & Kashmir\": \"IN-NO\",\n    \"Jharkhand\": \"IN-EA\",\n    \"Karnataka\": \"IN-SO\",\n    \"Kerala\": \"IN-SO\",\n    \"Ladakh\": \"IN-NO\",\n    \"Madhya Pradesh\": \"IN-WE\",\n    \"Maharashtra\": \"IN-WE\",\n    \"Manipur\": \"IN-NE\",\n    \"Meghalaya\": \"IN-NE\",\n    \"Mizoram\": \"IN-NE\",\n    \"Nagaland\": \"IN-NE\",\n    \"Odisha\": \"IN-EA\",\n    \"Punjab\": \"IN-NO\",\n    \"Rajasthan\": \"IN-NO\",\n    \"Sikkim\": \"IN-EA\",\n    \"Tamil Nadu\": \"IN-SO\",\n    \"Telangana\": \"IN-SO\",\n    \"Tripura\": \"IN-NE\",\n    \"Uttar Pradesh\": \"IN-NO\",\n    \"Uttarakhand\": \"IN-NO\",\n    \"West Bengal\": \"IN-EA\",\n    \"Delhi\": \"IN-NO\",\n    \"Pondicherry\": \"IN-SO\",\n}\n\nMNRE_MODE_MAPPING = {\n    \"Small Hydro Power\": \"hydro\",\n    \"Wind Power\": \"wind\",\n    \"Bio Power Total\": \"biomass\",\n    \"Solar Power Total\": \"solar\",\n}\n\n\ndef fetch_production_capacity_for_all_zones(\n    target_datetime: datetime, session: Session\n) -> dict[str, Any] | None:\n    logger.warning(\n        \"Renewable capacity is not available and should be downloaded from https://mnre.gov.in/physical-progress/\"\n    )\n    r: Response = session.get(CAPACITY_URL)\n    data = r.json()\n    df = pd.DataFrame(data)\n\n    df_filtered = df.loc[df[\"Month\"] == target_datetime.strftime(\"%b-%Y\")].copy()\n    if df_filtered.empty:\n        raise logger.warning(f\"No capacity data for IN zones in {target_datetime.year}\")\n    df_filtered[\"datetime\"] = pd.to_datetime(df_filtered[\"Month\"])\n    df_filtered[\"zoneKey\"] = df_filtered[\"Region\"].map(REGION_MAPPING)\n    df_filtered = df_filtered[[\"datetime\", \"zoneKey\"] + list(MODE_MAPPING.keys())]\n\n    df_filtered = df_filtered.set_index([\"datetime\", \"zoneKey\"])\n    all_capacity = {}\n    for idx, data in df_filtered.iterrows():\n        capacity_dict = {}\n        for cea_mode in data.index:\n            mode = MODE_MAPPING[cea_mode]\n            capacity_dict[mode] = {\n                \"datetime\": idx[0].strftime(\"%Y-%m-%d\"),\n                \"value\": float(data[cea_mode]),\n                \"source\": SOURCE,\n            }\n        all_capacity[idx[1]] = capacity_dict\n    return all_capacity\n\n\ndef fetch_production_capacity(\n    target_datetime: datetime, zone_key: ZoneKey, session: Session\n) -> dict[str, Any] | None:\n    all_capacities = fetch_production_capacity_for_all_zones(target_datetime, session)\n    return all_capacities[zone_key]\n\n\n# manual update, the output of the function should be added to the config file\ndef get_renewable_capacity(path: str, zone_key: ZoneKey | None = None) -> None:\n    \"\"\"Extract renewable capacity from MNRE report which then should be added to the config file\"\"\"\n    df = pd.read_excel(path, skiprows=2)\n    for col in df.columns:\n        if \"Unnamed:\" in col:\n            df = df.rename(columns={col: df[col].iloc[0]})\n    df = df.iloc[2:]\n    cols_to_keep = [\n        \"STATES / Uts\",\n        \"Small Hydro Power\",\n        \"Wind Power\",\n        \"Bio Power Total\",\n        \"Solar Power Total\",\n    ]\n    df_filtered = df[cols_to_keep].copy()\n    df_filtered = df_filtered.rename(\n        columns={**{\"STATES / Uts\": \"zoneKey\"}, **MNRE_MODE_MAPPING}\n    )\n    df_filtered[\"zoneKey\"] = df_filtered[\"zoneKey\"].map(IN_STATE_TO_ZONE_MAPPING)\n    df_filtered = df_filtered.groupby([\"zoneKey\"]).sum(numeric_only=True)\n    all_capacity = {}\n    for idx, data in df_filtered.iterrows():\n        capacity_dict = {}\n        for mode in data.index.sort_values():\n            capacity_dict[mode] = round(data[mode], 1)\n        all_capacity[idx] = capacity_dict\n    if zone_key:\n        return all_capacity[zone_key]\n    return all_capacity\n\n\nif __name__ == \"__main__\":\n    print(\n        get_renewable_capacity(\n            \"/Users/mathildedaugy/Downloads/202401091363179073.xlsx\", \"IN-SO\"\n        )\n    )\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/CL_SEN.py",
    "content": "import logging\nfrom datetime import datetime\nfrom typing import Any\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\n\nlogger = logging.getLogger(__name__)\n\n# Mapping conventional thermal as unknown as the production parser data is aggregated\nMODE_MAPPING = {\n    \"Hídrico\": \"hydro\",\n    \"Carbón\": \"unknown\",\n    \"Diésel\": \"unknown\",\n    \"Gas Natural\": \"unknown\",\n    \"Eólico\": \"wind\",\n    \"Solar\": \"solar\",\n    \"Termosolar\": \"solar\",\n    \"Geotérmico\": \"geothermal\",\n    \"Otros*\": \"unknown\",\n}\n\nSOURCE = \"coordinador.cl\"\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session\n) -> dict[str, Any] | None:\n    url = \"https://www.coordinador.cl/reportes-y-estadisticas/#Estadisticas\"\n    r: Response = session.get(url)\n    soup = BeautifulSoup(r.text, \"html.parser\")\n\n    capacity_link = soup.find_all(\n        \"a\", href=lambda x: x and \"hist_cap_inst_por_tecnologia\" in x\n    )\n    if not len(capacity_link):\n        logger.error(\n            f\"{zone_key}: No capacity data available for year {target_datetime.year}\"\n        )\n\n    df = pd.read_excel(\n        capacity_link[0].get(\"href\"),\n        sheet_name=\"Capacidad por Tecnología\",\n        header=2,\n        skipfooter=2,\n    )\n    df = df.drop(columns=[\"Unnamed: 0\", \"TOTAL\"])\n    df = df.rename(columns={\"Año\": \"datetime\"})\n    df = df.melt(id_vars=[\"datetime\"], var_name=\"mode\", value_name=\"value\")\n    df[\"mode\"] = df[\"mode\"].apply(lambda x: MODE_MAPPING[x.strip()])\n\n    df = df.groupby([\"datetime\", \"mode\"])[[\"value\"]].sum().reset_index()\n\n    if target_datetime.year in df[\"datetime\"].unique():\n        df = df.loc[df[\"datetime\"] == target_datetime.year]\n        capacity = {}\n        for _idx, data in df.iterrows():\n            mode_capacity = {}\n            mode_capacity[\"datetime\"] = target_datetime.strftime(\"%Y-%m-%d\")\n            mode_capacity[\"value\"] = round(data[\"value\"], 0)\n            mode_capacity[\"source\"] = SOURCE\n            capacity[data[\"mode\"]] = mode_capacity\n        logger.info(\n            f\"Fetched capacity for {zone_key} on {target_datetime.date()}: \\n {capacity}\"\n        )\n        return capacity\n    else:\n        logger.error(\n            f\"{zone_key}: No capacity data available for year {target_datetime.year}\"\n        )\n\n\nif __name__ == \"__main__\":\n    logging.basicConfig(level=logging.INFO)\n    fetch_production_capacity(\"CL-SEN\", datetime(2022, 1, 1), Session())\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/DE.py",
    "content": "import logging\nfrom datetime import datetime\nfrom typing import Any\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\n\nlogger = logging.getLogger(__name__)\n\nMODE_MAPPING = {\n    \"Nuclear\": \"nuclear\",\n    \"Fossil brown coal / lignite\": \"coal\",\n    \"Fossil hard coal\": \"coal\",\n    \"Fossil gas\": \"gas\",\n    \"Fossil oil\": \"oil\",\n    \"Other, non-renewable\": \"unknown\",\n    \"Hydro Run-of-River\": \"hydro\",\n    \"Hydro pumped storage\": \"hydro storage\",\n    \"Battery Storage (Power)\": \"battery storage\",\n    \"Biomass\": \"biomass\",\n    \"Wind onshore\": \"wind\",\n    \"Wind offshore\": \"wind\",\n    \"Solar\": \"solar\",\n}\n\nSOURCE = \"Fraunhofer ISE\"\n\nREQUEST_URL = \"https://api.energy-charts.info/installed_power?country=de&time_step=yearly&installation_decommission=false\"\nCONVERT_GW_TO_MW = 1000\n\n\ndef convert_to_mw(value: float | int | None) -> float:\n    if isinstance(value, int | float):\n        return float(value) * CONVERT_GW_TO_MW\n    else:\n        return None\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session\n) -> dict[str, Any] | None:\n    r: Response = session.get(REQUEST_URL)\n    if not r.ok:\n        raise ValueError(\n            f\"Failed to fetch capacity data for DE at {target_datetime.date()}\"\n        )\n    data = r.json()\n    all_capacity = {}\n    for i in range(len(data[\"production_types\"])):\n        capacity_mode = {}\n        mode = data[\"production_types\"][i][\"name\"]\n        for j in range(len(data[\"time\"])):\n            capacity_mode[int(data[\"time\"][j])] = convert_to_mw(\n                data[\"production_types\"][i][\"data\"][j]\n            )\n\n        all_capacity[mode] = capacity_mode\n\n    capacity = update_capacity_breakdown(all_capacity, target_datetime)\n\n    logger.info(\n        f\"Fetched capacity for {zone_key} on {target_datetime.date()}: \\n {capacity}\"\n    )\n    return capacity\n\n\ndef update_capacity_breakdown(\n    all_capacity: dict[str, Any], target_datetime: datetime\n) -> dict[str, Any]:\n    capacity = {}\n\n    for mode, capacity_data in all_capacity.items():\n        mapped_mode = MODE_MAPPING.get(mode)\n        if mode not in MODE_MAPPING:\n            continue\n        if mapped_mode in capacity:\n            capacity[mapped_mode][\"value\"] += round(\n                capacity_data[target_datetime.year], 0\n            )\n        else:\n            capacity[mapped_mode] = {\n                \"datetime\": target_datetime.strftime(\"%Y-%m-%d\"),\n                \"value\": round(capacity_data[target_datetime.year], 0),\n                \"source\": SOURCE,\n            }\n\n    return capacity\n\n\nif __name__ == \"__main__\":\n    logging.basicConfig(level=logging.INFO)\n    fetch_production_capacity(ZoneKey(\"DE\"), datetime(2023, 1, 1), Session())\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/EIA.py",
    "content": "import calendar\nfrom datetime import datetime\nfrom logging import getLogger\nfrom typing import Any\n\nimport pandas as pd\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.config.capacity import CAPACITY_PARSER_SOURCE_TO_ZONES\nfrom electricitymap.contrib.config.constants import PRODUCTION_MODES\nfrom electricitymap.contrib.parsers.EIA import REGIONS\nfrom electricitymap.contrib.parsers.lib.utils import get_token\n\nlogger = getLogger(__name__)\n\nCAPACITY_URL = \"https://api.eia.gov/v2/electricity/operating-generator-capacity/data/?frequency=monthly&data[0]=nameplate-capacity-mw&facets[balancing_authority_code][]={}\"\nSOURCE = \"EIA.gov\"\nUS_ZONES = CAPACITY_PARSER_SOURCE_TO_ZONES[\"EIA\"]\nTECHNOLOGY_TO_MODE = {\n    \"All Other\": \"unknown\",\n    \"Batteries\": \"battery storage\",\n    \"Coal Integrated Gasification Combined Cycle\": \"coal\",\n    \"Conventional Hydroelectric\": \"hydro\",\n    \"Conventional Steam Coal\": \"coal\",\n    \"Flywheels\": \"battery storage\",\n    \"Geothermal\": \"geothermal\",\n    \"Hydroelectric Pumped Storage\": \"hydro storage\",\n    \"Landfill Gas\": \"biomass\",\n    \"Municipal Solid Waste\": \"biomass\",  # or unknown?\n    \"Natural Gas Fired Combined Cycle\": \"gas\",\n    \"Natural Gas Fired Combustion Turbine\": \"gas\",\n    \"Natural Gas Internal Combustion Engine\": \"gas\",\n    \"Natural Gas Steam Turbine\": \"gas\",\n    \"Natural Gas with Compressed Air Storage\": \"gas\",\n    \"Nuclear\": \"nuclear\",\n    \"Offshore Wind Turbine\": \"wind\",\n    \"Onshore Wind Turbine\": \"wind\",\n    \"Other Gases\": \"gas\",\n    \"Other Natural Gas\": \"gas\",\n    \"Other Waste Biomass\": \"biomass\",\n    \"Petroleum Coke\": \"oil\",\n    \"Petroleum Liquids\": \"oil\",\n    \"Solar Photovoltaic\": \"solar\",\n    \"Solar Thermal with Energy Storage\": \"solar\",\n    \"Solar Thermal without Energy Storage\": \"solar\",\n    \"Wood/Wood Waste Biomass\": \"biomass\",\n}\nCAPACITY_MODES = PRODUCTION_MODES + [\"hydro storage\", \"battery storage\"]\n\n\ndef format_capacity(df: pd.DataFrame, target_datetime: datetime) -> dict[str, Any]:\n    df = df.copy()\n    df = df.loc[df[\"statusDescription\"] == \"Operating\"]\n    df[\"mode\"] = df[\"technology\"].map(TECHNOLOGY_TO_MODE)\n    df[\"nameplate-capacity-mw\"] = pd.to_numeric(\n        df[\"nameplate-capacity-mw\"], errors=\"coerce\"\n    )\n    df_aggregated = df.groupby([\"mode\"])[[\"nameplate-capacity-mw\"]].sum().reset_index()\n    capacity_dict = {}\n    for mode in CAPACITY_MODES:\n        mode_dict = {}\n        mode_dict[\"value\"] = round(\n            float(\n                df_aggregated.loc[df_aggregated[\"mode\"] == mode][\n                    \"nameplate-capacity-mw\"\n                ].sum()\n            ),\n            1,\n        )\n        mode_dict[\"source\"] = SOURCE\n        mode_dict[\"datetime\"] = target_datetime.strftime(\"%Y-%m-%d\")\n        capacity_dict[mode] = mode_dict\n    return capacity_dict\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey,\n    target_datetime: datetime,\n    session: Session,\n) -> dict[str, Any] | None:\n    API_KEY = get_token(\"EIA_KEY\")\n    url_prefix = CAPACITY_URL.format(REGIONS[zone_key])\n    start_date = target_datetime.strftime(\"%Y-%m-01\")\n    end_date = target_datetime.replace(\n        day=calendar.monthrange(target_datetime.year, target_datetime.month)[1]\n    ).strftime(\"%Y-%m-%d\")\n    url = f\"{url_prefix}&api_key={API_KEY}&start={start_date}&end={end_date}&sort[0][column]=period&sort[0][direction]=desc&offset=0&length=5000\"\n    r: Response = session.get(url)\n    json_data = r.json()\n\n    if json_data.get(\"response\", {}).get(\"data\", []) != []:\n        data = pd.DataFrame(json_data[\"response\"][\"data\"])\n        capacity_dict = format_capacity(data, target_datetime)\n        logger.info(\n            f\"Fetched capacity data for {zone_key} at {target_datetime.strftime('%Y-%m')}: \\n{capacity_dict}\"\n        )\n        return capacity_dict\n    else:\n        logger.warning(\n            f\"Failed to fetch capacity data for {zone_key} at {target_datetime.strftime('%Y-%m')}\"\n        )\n\n\ndef fetch_production_capacity_for_all_zones(\n    target_datetime: datetime, session: Session | None = None\n) -> dict[str, Any]:\n    eia_capacity = {}\n    if session is None:\n        session = Session()\n    for zone in US_ZONES:\n        try:\n            zone_capacity = fetch_production_capacity(zone, target_datetime, session)\n            if zone_capacity:\n                eia_capacity[zone] = zone_capacity\n        except Exception as e:\n            logger.error(\n                f\"Error fetching production capacity for {zone} at {target_datetime.strftime('%Y-%m')}: {e}\"\n            )\n    return eia_capacity\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/EMBER.py",
    "content": "import logging\nfrom datetime import datetime\nfrom time import sleep\nfrom typing import Any\n\nimport pandas as pd\nimport pycountry\nimport requests\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.config.capacity import CAPACITY_PARSER_SOURCE_TO_ZONES\nfrom electricitymap.contrib.config.constants import ENERGIES\nfrom electricitymap.contrib.parsers.lib.utils import get_token\n\n\"\"\" Collects capacity data from the yearly electricity data from Ember. The data and documentation can be found here: https://ember-climate.org/data-catalogue/yearly-electricity-data/\"\"\"\nlogger = logging.getLogger(__name__)\nEMBER_URL = \"https://ember-climate.org\"\nSOURCE = \"Ember, Yearly electricity data\"\nSTART_YEAR = 2017\nSPECIFIC_MODE_MAPPING = {\n    \"AR\": {\"other fossil\": \"unknown\"},\n    \"BD\": {\"other fossil\": \"oil\"},\n    \"BO\": {\"other fossil\": \"oil\"},\n    \"CO\": {\"other fossil\": \"oil\"},\n    \"CR\": {\"other fossil\": \"oil\", \"other renewables\": \"geothermal\"},\n    \"CY\": {\"other fossil\": \"oil\"},\n    \"IE\": {\"other fossil\": \"oil\"},\n    \"KR\": {\"other fossil\": \"oil\"},\n    \"KW\": {\"other fossil\": \"oil\"},\n    \"MN\": {\"other fossil\": \"coal\"},\n    \"NZ\": {\"other renewables\": \"geothermal\"},\n    \"SG\": {\"other fossil\": \"coal\"},\n    \"SV\": {\"other renewables\": \"geothermal\"},\n    \"TR\": {\"other fossil\": \"oil\", \"other renewables\": \"geothermal\"},\n    \"TW\": {\"other fossil\": \"oil\"},\n    \"UY\": {\"other fossil\": \"unknown\"},\n    \"ZA\": {\"other fossil\": \"oil\"},\n}\n\nEMBER_ZONES = CAPACITY_PARSER_SOURCE_TO_ZONES[\"EMBER\"]\n\n\ndef get_ember_capacity_yearly_data(country_iso2: ZoneKey, session: Session) -> str:\n    \"\"\"\n    Creates a URL to fetch generation_yearly data from the API,\n    using ISO 3 country code and a year\n    ex: 'https://api.ember-energy.org/data-tools/electricity-capacity/yearly?entity=xxx&api_key=xxxx\n    Args:\n        country_iso2 (str | None): ISO 2 country code (e.g., \"FR\").\n        session (Session): The requests session to use.\n    Returns:\n        pd.DataFrame: A dataframe with the capacity data.\n    \"\"\"\n    ember_api_key = get_token(\"EMBER_CAPACITY_KEY\")\n    if not ember_api_key:\n        raise ValueError(\"EMBER_CAPACITY_KEY not found in environment variables\")\n\n    # Go from ISO2 to country name, capitalize each word\n\n    if country_iso2 in SPECIAL_MAPPING_ZONE_KEY:\n        country_name = SPECIAL_MAPPING_ZONE_KEY[country_iso2]\n    else:\n        country = pycountry.countries.get(alpha_2=country_iso2)\n        if country:\n            country_name = country.name.title()\n        else:\n            raise ValueError(f\"Invalid ISO2 country code: {country_iso2}\")\n\n    query_params = {\n        \"entity\": country_name,\n        \"api_key\": ember_api_key,\n    }\n\n    base_url = \"https://api.ember-energy.org/data-tools/electricity-capacity/yearly\"\n\n    # Retry up to 3 times with exponential backoff\n    max_retries = 3\n    for attempt in range(max_retries):\n        try:\n            logger.info(\n                f\"Fetching Ember capacity data for {country_iso2} (attempt {attempt + 1}/{max_retries})\"\n            )\n            response = session.get(base_url, params=query_params, timeout=30)\n            response.raise_for_status()\n\n            # Add a small delay to avoid spamming the API\n            sleep(1)\n\n            df_raw = pd.DataFrame(response.json()[\"data\"])\n            df_raw[\"country_code_iso2\"] = country_iso2\n            return df_raw\n\n        except requests.exceptions.RequestException as e:\n            if attempt < max_retries - 1:\n                wait_time = 2**attempt  # Exponential backoff: 1, 2, 4 seconds\n                logger.warning(\n                    f\"Failed to fetch Ember data for {country_iso2}: {e}. Retrying in {wait_time}s...\"\n                )\n                sleep(wait_time)\n            else:\n                logger.error(\n                    f\"Failed to fetch Ember data for {country_iso2} after {max_retries} attempts: {e}\"\n                )\n                raise\n\n    # This should never be reached as the loop always returns or raises\n    raise RuntimeError(\n        f\"Failed to fetch Ember data for {country_iso2}: retry loop completed without returning\"\n    )\n\n\ndef _ember_production_mode_mapper(row: pd.Series) -> str | None:\n    category_col = \"mode\"\n\n    # Ember also reports the following, which we exclude due to:\n    # 'Wind and solar' is contained in 'wind' and 'solar' data\n    # 'Fossil' contained in all non-renewable sources, i.e. 'coal', 'gas', 'oil', 'other fossil\n    # 'Clean' containd in all renewable sources, i.e. 'wind', 'solar', 'other renewables', ...\n    ember_mapper = {\n        \"other fossil\": \"unknown\",\n        \"bioenergy\": \"biomass\",\n        \"other renewables\": \"unknown\",\n    }\n\n    if isinstance(row[category_col], str):\n        mode = row[category_col].lower()\n        if (\n            row[\"zone_key\"] in SPECIFIC_MODE_MAPPING\n            and mode in SPECIFIC_MODE_MAPPING[row[\"zone_key\"]]\n        ):\n            production_mode = SPECIFIC_MODE_MAPPING[row[\"zone_key\"]][mode]\n        elif mode in ENERGIES:\n            production_mode = mode\n        elif mode in ember_mapper:\n            production_mode = ember_mapper[mode]\n        else:\n            production_mode = \"unknown\"\n            raise ValueError(f\"Unknown production mode: {row[category_col]}\")\n\n    return production_mode\n\n\ndef transform_ember_data(ember_df: pd.DataFrame) -> pd.DataFrame:\n    if ember_df.empty is True:\n        logger.warning(\"Empty Ember data received\")\n        raise ValueError(\"Empty Ember data received\")\n    df = ember_df.loc[~ember_df[\"is_aggregate_series\"]].reset_index(drop=True)\n\n    df_capacity = df[[\"country_code_iso2\", \"date\", \"series\", \"capacity_gw\"]].rename(\n        columns={\"date\": \"year\", \"series\": \"variable\"}\n    )\n\n    df_capacity = df_capacity.rename(\n        columns={\n            \"country_code_iso2\": \"zone_key\",\n            \"variable\": \"mode\",\n        }\n    )\n    df_capacity[\"datetime\"] = df_capacity[\"year\"].apply(\n        lambda x: datetime(int(x), 1, 1)\n    )\n    df_capacity[\"capacity_mw\"] = pd.to_numeric(\n        df_capacity[\"capacity_gw\"] * 1000, errors=\"coerce\"\n    ).astype(float)  # convert from GW to MW\n    df_capacity.drop(columns=[\"capacity_gw\"], inplace=True)\n    df_capacity.dropna(subset=[\"capacity_mw\"], inplace=True)\n\n    df_capacity[\"mode\"] = df_capacity.apply(_ember_production_mode_mapper, axis=1)\n    df_capacity = (\n        df_capacity.groupby([\"zone_key\", \"datetime\", \"mode\"])[[\"capacity_mw\"]]\n        .sum()\n        .reset_index()\n        .set_index([\"zone_key\"])\n    )\n    return df_capacity\n\n\ndef get_capacity_dict_from_df(\n    df_capacity: pd.DataFrame, zone_key: ZoneKey, target_datetime: datetime\n) -> dict[str, Any]:\n    \"\"\"Get capacity data for a specific zone for a specific year. The unit is the MW\n\n    Args:\n        df_capacity: DataFrame with capacity data\n        zone_key: The zone key\n        target_datetime: The target datetime (year will be used to filter data)\n\n    Returns:\n        Dictionary with capacity data per mode for the target year\n    \"\"\"\n    if [zone_key] != df_capacity.index.unique().tolist():\n        raise ValueError(f\"Zone key {zone_key} not found in dataframe\")\n\n    # Filter data for the target year\n    target_year = target_datetime.year\n    df_year = df_capacity[df_capacity[\"datetime\"].dt.year == target_year]\n\n    if df_year.empty:\n        logger.warning(f\"No capacity data for {zone_key} in year {target_year}\")\n        return {}\n\n    zone_capacity = {}\n    for _i, data in df_year.iterrows():\n        mode_capacity = {}\n        mode_capacity[\"datetime\"] = data[\"datetime\"].strftime(\"%Y-%m-%d\")\n        mode_capacity[\"source\"] = SOURCE\n        mode_capacity[\"value\"] = round(float(data[\"capacity_mw\"]), 2)\n\n        # Store single dict per mode (not a list)\n        zone_capacity[data[\"mode\"]] = mode_capacity\n\n    return zone_capacity\n\n\ndef remove_consecutive_duplicates(\n    capacity_list: list[dict[str, Any]],\n) -> list[dict[str, Any]]:\n    \"\"\"Remove consecutive entries with the same value, keeping only the first occurrence.\n\n    This optimizes the capacity data by removing redundant year-over-year entries\n    where the capacity hasn't changed.\n\n    Args:\n        capacity_list: List of capacity entries sorted by datetime\n\n    Returns:\n        Optimized list with consecutive duplicates removed\n    \"\"\"\n    if not capacity_list:\n        return []\n\n    # Sort by datetime to ensure chronological order\n    sorted_list = sorted(capacity_list, key=lambda x: x[\"datetime\"])\n\n    # Always keep the first entry\n    optimized = [sorted_list[0]]\n\n    # Only add entries where the value changed from the previous entry\n    for entry in sorted_list[1:]:\n        if entry[\"value\"] != optimized[-1][\"value\"]:\n            optimized.append(entry)\n\n    return optimized\n\n\ndef get_capacity_dict_all_years_from_df(\n    df_capacity: pd.DataFrame, zone_key: ZoneKey\n) -> dict[str, Any]:\n    \"\"\"Get capacity data for a specific zone for ALL available years. The unit is the MW\n\n    Args:\n        df_capacity: DataFrame with capacity data\n        zone_key: The zone key\n\n    Returns:\n        Dictionary with capacity data per mode as lists (all years)\n    \"\"\"\n    if [zone_key] != df_capacity.index.unique().tolist():\n        raise ValueError(f\"Zone key {zone_key} not found in dataframe\")\n\n    zone_capacity = {}\n    for _i, data in df_capacity.iterrows():\n        mode_capacity = {}\n        mode_capacity[\"datetime\"] = data[\"datetime\"].strftime(\"%Y-%m-%d\")\n        mode_capacity[\"source\"] = SOURCE\n        mode_capacity[\"value\"] = round(float(data[\"capacity_mw\"]), 2)\n\n        # Initialize list for this mode if it doesn't exist\n        if data[\"mode\"] not in zone_capacity:\n            zone_capacity[data[\"mode\"]] = []\n\n        # Append the entry to the list for this mode\n        zone_capacity[data[\"mode\"]].append(mode_capacity)\n\n    # Remove consecutive duplicates for each mode\n    for mode in zone_capacity:\n        zone_capacity[mode] = remove_consecutive_duplicates(zone_capacity[mode])\n\n    return zone_capacity\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session\n) -> dict[str, Any] | None:\n    \"\"\"Get capacity data for a specific zone for a specific year. The unit is the MW\n\n    Args:\n        zone_key: The zone key (ISO2 country code)\n        target_datetime: The target datetime (year will be used to filter data)\n        session: The requests session\n\n    Returns:\n        Dictionary with capacity data for the zone\n    \"\"\"\n    session = session or Session()\n    df_capacity = get_ember_capacity_yearly_data(\n        country_iso2=zone_key,\n        session=session,\n    )\n    df_capacity = transform_ember_data(df_capacity)\n    capacity = get_capacity_dict_from_df(df_capacity, zone_key, target_datetime)\n\n    if capacity:\n        logger.info(\n            f\"Fetched capacity for {zone_key} in {target_datetime.year}: \\n{capacity}\"\n        )\n    return capacity if capacity else None\n\n\ndef fetch_production_capacity_all_years(\n    zone_key: ZoneKey, session: Session | None = None\n) -> dict[str, Any]:\n    \"\"\"Get capacity data for a specific zone for ALL available years >= 2017. The unit is the MW\n\n    This function fetches all years available from EMBER in one API call and returns\n    them in the list format that matches the zone YAML configuration structure.\n\n    Data is filtered to start from 2017 and consecutive duplicate values are\n    automatically removed to optimize the data.\n\n    Args:\n        zone_key: The zone key (ISO2 country code)\n        session: The requests session\n\n    Returns:\n        Dictionary with capacity data per mode as lists containing all years >= 2017\n        (with consecutive duplicates removed):\n        {\n            \"coal\": [\n                {\"datetime\": \"2017-01-01\", \"value\": 1234.56, \"source\": \"...\"},\n                {\"datetime\": \"2022-01-01\", \"value\": 1245.67, \"source\": \"...\"}  # 2018-2021 removed (duplicates)\n            ],\n            \"solar\": [...]\n        }\n    \"\"\"\n    session = session or Session()\n    df_capacity = get_ember_capacity_yearly_data(\n        country_iso2=zone_key,\n        session=session,\n    )\n    df_capacity = transform_ember_data(df_capacity)\n    # Filter to only include years >= 2017\n    df_capacity = df_capacity[df_capacity[\"datetime\"].dt.year >= START_YEAR]\n    capacity = get_capacity_dict_all_years_from_df(df_capacity, zone_key)\n\n    if capacity:\n        years = set()\n        for mode_data in capacity.values():\n            for entry in mode_data:\n                years.add(entry[\"datetime\"][:4])\n        logger.info(\n            f\"Fetched capacity for {zone_key} for years {sorted(years)}: {len(capacity)} modes\"\n        )\n    return capacity\n\n\ndef fetch_production_capacity_for_all_zones(\n    target_datetime: datetime, session: Session | None = None\n) -> dict[str, Any]:\n    \"\"\"Get capacity data for all zones supported by Ember for a specific year.\n\n    Args:\n        target_datetime: The target datetime (year will be used to filter data)\n        session: The requests session\n\n    Returns:\n        Dictionary with capacity data for all zones: {zone_key: {mode: dict}}\n    \"\"\"\n    session = session or Session()\n    all_capacity = {}\n\n    for zone_key in EMBER_ZONES:\n        try:\n            capacity = fetch_production_capacity(zone_key, target_datetime, session)\n            if capacity:\n                all_capacity[zone_key] = capacity\n        except Exception as e:\n            logger.error(f\"Failed to fetch capacity for {zone_key}: {e}\")\n            continue\n\n    return all_capacity\n\n\ndef fetch_production_capacity_for_all_zones_all_years(\n    session: Session | None = None,\n) -> dict[str, Any]:\n    \"\"\"Get capacity data for ALL zones for ALL available years.\n\n    This function is useful for doing a complete update of all EMBER zones at once.\n\n    Args:\n        session: The requests session\n\n    Returns:\n        Dictionary with capacity data for all zones with all years:\n        {\n            \"FR\": {\n                \"coal\": [{\"datetime\": \"2021-01-01\", \"value\": 1234, \"source\": \"...\"}],\n                \"solar\": [...]\n            },\n            \"DE\": {...}\n        }\n    \"\"\"\n    session = session or Session()\n    all_capacity = {}\n\n    logger.info(f\"Fetching capacity for {len(EMBER_ZONES)} zones...\")\n    for zone_key in EMBER_ZONES:\n        try:\n            capacity = fetch_production_capacity_all_years(zone_key, session)\n            if capacity:\n                all_capacity[zone_key] = capacity\n        except Exception as e:\n            logger.error(f\"Failed to fetch capacity for {zone_key}: {e}\")\n            continue\n\n    return all_capacity\n\n\nSPECIAL_MAPPING_ZONE_KEY = {\n    \"FK\": \"Falkland Islands [Malvinas]\",\n    \"KP\": \"North Korea\",\n    \"KR\": \"South Korea\",\n    \"LA\": \"Lao\",\n    \"MO\": \"Macao (SAR of China)\",\n    \"PS\": \"Palestine (State of)\",\n    \"RU\": \"Russia\",\n    \"SY\": \"Syria\",\n    \"TR\": \"Türkiye\",\n    \"TW\": \"Taiwan (China)\",\n    \"TZ\": \"Tanzania (the United Republic of)\",\n    \"VI\": \"Virgin Islands (U.S.)\",\n}\nif __name__ == \"__main__\":\n    logging.basicConfig(level=logging.INFO)\n\n    session = Session()\n\n    # Example 1: Fetch capacity for one year (for use with update_capacity_configuration.py)\n    print(\"\\n=== Example 1: Single year ===\")\n    FR_single_year = fetch_production_capacity(\n        zone_key=\"FR\", target_datetime=datetime(2024, 1, 1), session=session\n    )\n    print(f\"FR capacity data for 2024: {list(FR_single_year.keys())}\")\n\n    # Example 2: Fetch capacity for all years at once\n    print(\"\\n=== Example 2: All years for one zone ===\")\n    FR_all_years = fetch_production_capacity_all_years(zone_key=\"FR\", session=session)\n    print(\"FR capacity data for all years:\")\n    for mode, data in FR_all_years.items():\n        print(f\"  {mode}: {len(data)} years\")\n\n    # Example 3: Fetch capacity for all zones and all years (use with caution - many API calls!)\n    # Uncomment to run:\n    # print(\"\\n=== Example 3: All zones, all years ===\")\n    # all_data = fetch_production_capacity_for_all_zones_all_years(session=session)\n    # print(f\"Fetched data for {len(all_data)} zones\")\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/ENTSOE.py",
    "content": "from datetime import datetime\nfrom logging import getLogger\nfrom typing import Any\n\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.config.capacity import CAPACITY_PARSER_SOURCE_TO_ZONES\nfrom electricitymap.contrib.parsers.ENTSOE import (\n    ENTSOE_DOMAIN_MAPPINGS,\n    ENTSOE_PARAMETER_BY_GROUP,\n    query_ENTSOE,\n)\n\n\"\"\"\nUpdate capacity configurations for ENTOS-E zones for a chosen year.\n\"\"\"\nlogger = getLogger(__name__)\nSOURCE = \"entsoe.eu\"\n\nENDPOINT = \"/api\"\nENTSOE_HOST = \"https://web-api.tp.entsoe.eu\"\n\n\nEU_PROXY = \"https://eu-proxy-jfnx5klx2a-ew.a.run.app{endpoint}?host={host}\"\n\nENTSOE_ENDPOINT = ENTSOE_HOST + ENDPOINT\nENTSOE_EU_PROXY_ENDPOINT = EU_PROXY.format(endpoint=ENDPOINT, host=ENTSOE_HOST)\n\n\nENTSOE_ZONES = CAPACITY_PARSER_SOURCE_TO_ZONES[\"ENTSOE\"]\n\n# ENTSOE does not have battery storage capacity and the data needs to be collected from other sources for the following zones\n# TODO monitor this list and update if necessary\nZONES_WITH_BATTERY_STORAGE = [\"FR\"]\n\n\n# reallocate B10 to hydro storage\nENTSOE_CODE_TO_EM_MAPPING = ENTSOE_PARAMETER_BY_GROUP.copy()\nENTSOE_CODE_TO_EM_MAPPING.update({\"B10\": \"hydro storage\", \"B25\": \"battery storage\"})\n\n\ndef query_capacity(\n    in_domain: str, session: Session, target_datetime: datetime\n) -> str | None:\n    params = {\n        \"documentType\": \"A68\",\n        \"processType\": \"A33\",\n        \"in_Domain\": in_domain,\n    }\n    return query_ENTSOE(\n        session,\n        params,\n        target_datetime=target_datetime,\n        span=(0, 72),  # DO NOT USE A NEGATIVE LOOKBACK\n        function_name=query_capacity.__name__,\n    )\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session\n) -> dict[str, Any] | None:\n    xml_str = query_capacity(ENTSOE_DOMAIN_MAPPINGS[zone_key], session, target_datetime)\n    soup = BeautifulSoup(xml_str, \"html.parser\")\n    # Each time series is dedicated to a different fuel type.\n    capacity_dict = {}\n    for timeseries in soup.find_all(\"timeseries\"):\n        fuel_code = str(\n            timeseries.find_all(\"mktpsrtype\")[0].find_all(\"psrtype\")[0].contents[0]\n        )\n        point = timeseries.find_all(\"point\")\n        value = float(point[0].find_all(\"quantity\")[0].contents[0])\n        if ENTSOE_CODE_TO_EM_MAPPING[fuel_code] not in capacity_dict:\n            capacity_dict[ENTSOE_CODE_TO_EM_MAPPING[fuel_code]] = {\n                \"value\": 0,\n                \"datetime\": f\"{target_datetime.year}-01-01\",\n                \"source\": SOURCE,\n            }\n        capacity_dict[ENTSOE_CODE_TO_EM_MAPPING[fuel_code]][\"value\"] += value\n    if capacity_dict:\n        logger.info(\n            f\"Capacity data for {zone_key} on {target_datetime.date()}: \\n{capacity_dict}\"\n        )\n        if zone_key in ZONES_WITH_BATTERY_STORAGE:\n            logger.info(\n                f\"\\n\\n Warning: {zone_key} has battery storage, data source can be found on the contrib wiki \\n\\n\"\n            )\n        return capacity_dict\n    else:\n        logger.warning(\n            f\"Failed to fecth capacity data for {zone_key} on {target_datetime.date()}\"\n        )\n\n\ndef fetch_production_capacity_for_all_zones(\n    target_datetime: datetime, session: Session | None = None\n) -> dict[str, Any]:\n    capacity_dict = {}\n    if session is None:\n        session = Session()\n\n    for zone in ENTSOE_ZONES:\n        try:\n            zone_capacity = fetch_production_capacity(zone, target_datetime, session)\n            capacity_dict[zone] = zone_capacity\n        except Exception:\n            logger.warning(\n                f\"Failed to update capacity for {zone} on {target_datetime.date()}\"\n            )\n            continue\n    return capacity_dict\n\n\nif __name__ == \"__main__\":\n    fetch_production_capacity(\"FR\", datetime(2023, 1, 1), Session())\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/FI.py",
    "content": "from datetime import datetime, timedelta\nfrom typing import Any\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.capacity_parsers.ENTSOE import (\n    fetch_production_capacity as fetch_entsoe_production_capacity,\n)\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.parsers.lib.utils import get_token\n\nSOURCE = \"fingrid.fi\"\n\nFINGRID_URL = \"https://data.fingrid.fi/api/datasets/{data_set}/data\"\nMODE_TO_DATASET = {\"solar\": 267, \"wind\": 268}\n\n\ndef get_fingrid_capacity(\n    session: Session, target_datetime: datetime, mode: str\n) -> dict[str, Any] | None:\n    params = {\n        \"format\": \"json\",\n        \"locale\": \"en\",\n        \"pageSize\": 24,\n        \"startTime\": (target_datetime - timedelta(days=1)).strftime(\n            \"%Y-%m-%dT23:00:00\"\n        ),\n        \"endTime\": (target_datetime + timedelta(days=1)).strftime(\"%Y-%m-%dT00:00:00\"),\n    }\n    headers = {\"x-api-key\": get_token(\"FINGRID_TOKEN\")}\n    r: Response = session.get(\n        FINGRID_URL.format(data_set=MODE_TO_DATASET[mode]),\n        params=params,\n        headers=headers,\n    )\n    data = r.json()\n    if not r.ok or \"data\" not in r.json():\n        raise ValueError(\n            f\"Failed to fetch solar capacity from {FINGRID_URL} for {target_datetime.date()}\"\n        )\n    data = r.json()[\"data\"]\n    capacity = {mode: parse_fingrid_capacity(data, target_datetime)}\n    return capacity\n\n\ndef parse_fingrid_capacity(\n    data: dict[str, Any], target_datetime: datetime\n) -> list[dict[str, Any]]:\n    target_data = [\n        x\n        for x in data\n        if x[\"startTime\"] == target_datetime.strftime(\"%Y-%m-%dT00:00:00.000Z\")\n    ]\n    if len(target_data) == 0:\n        raise ValueError(f\"No solar capacity data found for {target_datetime.date()}\")\n    capacity = {\n        \"value\": target_data[0][\"value\"],\n        \"datetime\": target_datetime.strftime(\"%Y-%m-%d\"),\n        \"source\": SOURCE,\n    }\n    return capacity\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session\n) -> dict[str, Any] | None:\n    solar_capacity = get_fingrid_capacity(session, target_datetime, \"solar\")\n    wind_capacity = get_fingrid_capacity(session, target_datetime, \"wind\")\n    entsoe_capacity = fetch_entsoe_production_capacity(\n        zone_key, target_datetime, session\n    )\n    return {**entsoe_capacity, **solar_capacity, **wind_capacity}\n\n\nif __name__ == \"__main__\":\n    session = Session()\n    target_datetime = datetime(2023, 12, 31)\n    fetch_production_capacity(\"FI\", target_datetime, session)\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/GB.py",
    "content": "from datetime import datetime, timedelta\nfrom logging import getLogger\nfrom typing import Any\n\nimport pandas as pd\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\n\nlogger = getLogger(__name__)\nMODE_MAPPING = {\n    \"Wind Onshore\": \"wind\",\n    \"Wind Offshore\": \"wind\",\n    \"Solar\": \"solar\",\n    \"Other renewable\": \"unknown\",\n    \"Other\": \"unknown\",\n    \"Nuclear\": \"nuclear\",\n    \"Hydro Run-of-river and poundage\": \"hydro\",\n    \"Fossil Hard coal\": \"coal\",\n    \"Fossil Gas\": \"gas\",\n    \"Biomass\": \"biomass\",\n    \"Hydro Pumped Storage\": \"hydro storage\",\n}\n\nSOURCE = \"bmreports.com\"\nBMREPORTS_base_url = \"https://data.elexon.co.uk/bmrs/api/v1/datasets/IGCA\"\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session\n) -> dict[str, Any] | None:\n    start_date = (target_datetime - timedelta(days=366)).strftime(\"%Y-%m-%dT%H:%M:%SZ\")\n    end_date = target_datetime.strftime(\"%Y-%m-%dT%H:%M:%SZ\")\n\n    url = f\"{BMREPORTS_base_url}?publishDateTimeFrom={start_date}&publishDateTimeTo={end_date}&format=json\"\n\n    r = session.get(url)\n    if r.status_code != 200:\n        raise ValueError(\n            f\"GB: No capacity data available for year {target_datetime.year}. {r.status_code} :{r.text}\"\n        )\n    else:\n        if r.json()[\"data\"] == []:\n            raise ValueError(\n                f\"GB: No capacity data available for year {target_datetime.year}. {r.status_code} :{r.text}\"\n            )\n        df = pd.DataFrame(r.json()[\"data\"])\n        df[\"datetime\"] = pd.to_datetime(df[\"year\"].astype(str) + \"-01-01\").dt.strftime(\n            \"%Y-%m-%d\"\n        )\n        df[\"mode\"] = df[\"psrType\"].str.strip().map(MODE_MAPPING)\n        df[\"source\"] = SOURCE\n        df[\"value\"] = pd.to_numeric(df[\"quantity\"].round(0), downcast=\"integer\")\n        df_result = (\n            df[[\"datetime\", \"value\", \"mode\", \"source\"]]\n            .groupby([\"datetime\", \"mode\", \"source\"])\n            .sum(numeric_only=True)\n            .reset_index()\n        )\n        result = {}\n        for _, row in df_result.iterrows():\n            result[row[\"mode\"]] = {\n                \"datetime\": row[\"datetime\"],\n                \"value\": row[\"value\"],\n                \"source\": row[\"source\"],\n            }\n        logger.info(\n            f\"Fetched capacity for {zone_key} on {target_datetime.date()}: \\n{df}\"\n        )\n\n        return result\n\n\nif __name__ == \"__main__\":\n    print(fetch_production_capacity(\"GB\", datetime(2024, 1, 1), Session()))\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/IRENA.py",
    "content": "import json\nfrom datetime import datetime\nfrom logging import getLogger\nfrom typing import Any\n\nimport pycountry\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.config.capacity import CAPACITY_PARSER_SOURCE_TO_ZONES\n\n\"\"\"The data is downloaded from the IRENA API. \"\"\"\nlogger = getLogger(__name__)\nIRENA_ZONES = CAPACITY_PARSER_SOURCE_TO_ZONES[\"IRENA\"]\nSOURCE = \"IRENA.org\"\nIRENA_JSON_TO_MODE_MAPPING = {\n    0: \"unknown\",  # Total Renewable -> Do not consider\n    1: \"solar\",  # Solar photovoltaic\n    2: \"solar\",  # Solar thermal energy\n    3: \"wind\",  # Onshore wind energy\n    4: \"wind\",  # Offshore wind energy\n    5: \"hydro\",  # Renewable hydropower\n    6: \"hydro\",  # Mixed Hydro Plants\n    7: \"unknown\",  # Marine energy -> Not mapped currently\n    8: \"biomass\",  # Solid biofuels\n    9: \"biomass\",  # Renewable municipal waste\n    10: \"biomass\",  # Liquid biofuels\n    11: \"biomass\",  # Biogas\n    12: \"geothermal\",  # Geothermal energy\n    13: \"unknown\",  # Total Non-Renewable -> Do not consider\n    14: \"hydro storage\",  # Pumped storage\n    15: \"coal\",  # Coal and peat\n    16: \"oil\",  # Oil\n    17: \"gas\",  # Natural gas\n    18: \"unknown\",  # Fossil fuels n.e.s.\n    19: \"nuclear\",  # Nuclear\n    20: \"unknown\",  # Other non-renewable energy\n}\n\n\ndef get_data_from_url(\n    target_datetime: datetime, session: Session, zone_key_3_letters: str | None = None\n) -> list:\n    base_url = (\n        \"https://pxweb.irena.org:443/api/v1/en/IRENASTAT/Power Capacity and Generation/\"\n    )\n    url_year = datetime.now().year\n    filename_combinations = [\n        f\"Country_ELECSTAT_{url_year}_H2.px\",\n        f\"Country_ELECSTAT_{url_year - 1}_H2.px\",\n    ]\n    query_list = [\n        {\n            \"code\": \"Year\",\n            \"selection\": {\n                \"filter\": \"item\",\n                \"values\": [target_datetime.strftime(\"%y\")],\n            },\n        },\n        {\n            \"code\": \"Data Type\",\n            \"selection\": {\n                \"filter\": \"item\",\n                \"values\": [\n                    \"1\"  # 1 = Capacity (MW) # 0 = Generation (GWh)\n                ],\n            },\n        },\n        {\n            \"code\": \"Technology\",\n            \"selection\": {  # We are not selecting 0 and 13 because they are total renewable and total non-renewable (see mapping above)\n                \"filter\": \"item\",\n                \"values\": [\n                    \"1\",\n                    \"2\",\n                    \"3\",\n                    \"4\",\n                    \"5\",\n                    \"6\",\n                    \"7\",\n                    \"8\",\n                    \"9\",\n                    \"10\",\n                    \"11\",\n                    \"12\",\n                    \"14\",\n                    \"15\",\n                    \"16\",\n                    \"17\",\n                    \"18\",\n                    \"19\",\n                    \"20\",\n                ],\n            },\n        },\n        {\n            \"code\": \"Grid connection\",\n            \"selection\": {\n                \"filter\": \"item\",\n                \"values\": [\n                    \"0\"  # 0 = Total # 1 = on grid (connected to the main power lines) # 2 = off grid (completely independent of the main power lines)\n                ],\n            },\n        },\n    ]\n    if zone_key_3_letters is not None:\n        query_list.append(\n            {\n                \"code\": \"Country/area\",\n                \"selection\": {\"filter\": \"item\", \"values\": [zone_key_3_letters]},\n            }\n        )\n    json_query = {\n        \"query\": query_list,\n        \"response\": {\"format\": \"json\"},\n    }\n    data = None\n    for filename in filename_combinations:\n        url = base_url + filename\n\n        json_data = json.dumps(json_query)\n        r: Response = session.post(url, data=json_data)\n        if r.status_code == 200:\n            data = r.json()\n        else:\n            continue\n    if not data:\n        raise ValueError(f\"Could not fetch data for {target_datetime.year}\")\n    return data[\"data\"]\n\n\ndef get_capacity_data_for_zones(\n    target_datetime: datetime, session: Session, zone_key: ZoneKey | None = None\n) -> dict:\n    \"\"\"\n    Get capacity data for a specific zone or all zones. The unit is the MW\n    If zone_key is None, get data for all zones.\n    If zone_key is not None, get data for the specific zone.\n    \"\"\"\n    if zone_key is None:\n        data = get_data_from_url(target_datetime, session)\n    else:\n        if pycountry.countries.get(alpha_2=zone_key) is not None:\n            zone_key_3_letters = pycountry.countries.get(alpha_2=zone_key).alpha_3\n        else:\n            raise ValueError(\n                f\"Impossible to find the pycountry.countries 3 letters for {zone_key}\"\n            )\n        data = get_data_from_url(target_datetime, session, zone_key_3_letters)\n    capacity_dict = {}\n    for item in data:\n        if pycountry.countries.get(alpha_3=item[\"key\"][0]) is not None:\n            zone = pycountry.countries.get(alpha_3=item[\"key\"][0]).alpha_2\n        else:\n            pass\n        if int(item[\"key\"][1]) not in IRENA_JSON_TO_MODE_MAPPING:\n            continue\n        mode: str = IRENA_JSON_TO_MODE_MAPPING[int(item[\"key\"][1])]\n        value: float = float(item[\"values\"][0] if item[\"values\"][0] != \"-\" else 0)\n        datetime_value: datetime = datetime.strptime(item[\"key\"][-1], \"%y\")\n\n        if zone not in capacity_dict:\n            zone_dict = {\n                mode: {\n                    \"datetime\": datetime_value.strftime(\"%Y-%m-%d\"),\n                    \"value\": round(value, 2),\n                    \"source\": SOURCE,\n                }\n            }\n            capacity_dict[zone] = zone_dict\n        else:\n            if mode in capacity_dict[zone]:\n                zone_dict = capacity_dict[zone][mode]\n                capacity_dict[zone][mode][\"value\"] += value\n                capacity_dict[zone][mode][\"value\"] = round(\n                    capacity_dict[zone][mode][\"value\"], 2\n                )\n            else:\n                capacity_dict[zone] = {\n                    **capacity_dict[zone],\n                    **{\n                        mode: {\n                            \"datetime\": datetime_value.strftime(\"%Y-%m-%d\"),\n                            \"value\": round(value, 2),\n                            \"source\": SOURCE,\n                        }\n                    },\n                }\n    return capacity_dict\n\n\ndef fetch_production_capacity(\n    target_datetime: datetime, zone_key: ZoneKey, session: Session\n) -> dict[str, Any] | None:\n    all_capacity = get_capacity_data_for_zones(target_datetime, session, zone_key)\n    zone_capacity = all_capacity[zone_key]\n\n    if zone_capacity:\n        logger.info(\n            f\"Fetched capacity for {zone_key} in {target_datetime.year}: \\n{zone_capacity}\"\n        )\n        return zone_capacity\n    else:\n        logger.warning(f\"No capacity data for {zone_key} in {target_datetime.year}\")\n\n\ndef fetch_production_capacity_for_all_zones(\n    target_datetime: datetime, session: Session\n) -> dict[str, Any] | None:\n    all_capacity = get_capacity_data_for_zones(target_datetime, session)\n\n    all_capacity = {k: v for k, v in all_capacity.items() if k in IRENA_ZONES}\n    logger.info(f\"Fetched capacity data from IRENA for {target_datetime.year}\")\n    return all_capacity\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/MY_WM.py",
    "content": "import json\nimport logging\nfrom datetime import datetime\nfrom typing import Any\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\nfrom dateutil import parser\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\n\nlogger = logging.getLogger(__name__)\n\n\"\"\"Disclaimer: only valid for real-time data, historical capacity is not available\"\"\"\n\nMODE_MAPPING = {\"Gas\": \"gas\", \"Water\": \"hydro\", \"Coal\": \"coal\", \"Solar\": \"solar\"}\nGSO_URL = \"https://www.gso.org.my/SystemData/PowerStation.aspx/GetDataSource\"\n\nGSO_REQUEST_HEADERS = {\n    \"Content-Type\": \"application/json\",\n    \"Origin\": \"https://www.gso.org.my\",\n    \"Referer\": \"https://www.gso.org.my/SystemData/PowerStation.aspx\",\n}\n\n\ndef get_capacity_datetime(session: Session) -> datetime:\n    r: Response = session.get(GSO_URL)\n    soup: BeautifulSoup = BeautifulSoup(r.content, \"html.parser\")\n    date_str = soup.find_all(\"b\")[0].string\n    capacity_datetime = parser.parse(date_str, fuzzy=True)\n    return capacity_datetime.replace(day=1)\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, session: Session, target_datetime: datetime | None = None\n) -> dict[str, Any]:\n    if target_datetime is not None:\n        raise ValueError(\"MY-WM capacity parser not enabled for past dates\")\n    target_datetime = datetime.now()\n    capacity_datetime = get_capacity_datetime(session)\n\n    r: Response = session.post(GSO_URL, headers=GSO_REQUEST_HEADERS)\n    if not r.ok:\n        raise ValueError(\n            f\"Failed to fetch capacity data for GSO at {target_datetime.strftime('%Y-%m')}\"\n        )\n    else:\n        data = pd.DataFrame(json.loads(r.json()[\"d\"]))\n        data = data[[\"Fuel\", \"Capacity (MW)\"]]\n        data = data.rename(\n            columns={\n                \"Fuel\": \"mode\",\n                \"Capacity (MW)\": \"value\",\n            }\n        )\n        data[\"mode\"] = data[\"mode\"].apply(lambda x: x.strip())\n        data[\"mode\"] = data[\"mode\"].apply(lambda x: MODE_MAPPING[x])\n\n        filtered_data = data.groupby([\"mode\"])[[\"value\"]].sum().reset_index()\n\n        capacity_dict = {}\n        for _idx, data in filtered_data.iterrows():\n            capacity_dict[data[\"mode\"]] = {\n                \"value\": round(float(data[\"value\"]), 0),\n                \"source\": \"gso.org.my\",\n                \"datetime\": capacity_datetime.strftime(\"%Y-%m-%d\"),\n            }\n        logger.info(\n            f\"Fetched capacity for {zone_key} on {target_datetime.date()}: \\n{capacity_dict}\"\n        )\n        return capacity_dict\n\n\nif __name__ == \"__main__\":\n    logging.basicConfig(level=logging.INFO)\n    fetch_production_capacity(ZoneKey(\"MY-WM\"), Session())\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/ONS.py",
    "content": "from datetime import datetime\nfrom logging import getLogger\nfrom typing import Any\n\nimport pandas as pd\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\n\n\"\"\"Disclaimer: this parser does not include distributed capacity.\nSolar capacity is much lower than in reality because the majority is distributed.\nThis capacity is not available in this dataset and should collected from the link below and added manually to the zone configuration.\nDistributed solar generation is available here (tipo de usina = Geracao Distribuida): https://www.ons.org.br/Paginas/resultados-da-operacao/historico-da-operacao/capacidade_instalada.aspx\"\"\"\nlogger = getLogger(__name__)\nCAPACITY_URL = \"https://ons-dl-prod-opendata.s3.amazonaws.com/dataset/capacidade-geracao/CAPACIDADE_GERACAO.csv\"\nMODE_MAPPING = {\n    \"HIDRÁULICA\": \"hydro\",\n    \"ÓLEO DIESEL\": \"unknown\",\n    \"ÓLEO COMBUSTÍVEL\": \"unknown\",\n    \"MULTI-COMBUSTÍVEL GÁS/DIESEL\": \"unknown\",\n    \"MULTI-COMBUSTÍVEL DIESEL/ÓLEO\": \"unknown\",\n    \"GÁS\": \"unknown\",\n    \"RESÍDUO CICLO COMBINADO\": \"unknown\",\n    \"EÓLICA\": \"wind\",\n    \"CARVÃO\": \"unknown\",\n    \"BIOMASSA\": \"unknown\",\n    \"NUCLEAR\": \"nuclear\",\n    \"RESÍDUOS INDUSTRIAIS\": \"unknown\",\n    \"FOTOVOLTAICA\": \"solar\",\n}\n\nREGION_MAPPING = {\n    \"NORDESTE\": \"BR-NE\",\n    \"NORTE\": \"BR-N\",\n    \"SUDESTE\": \"BR-CS\",\n    \"SUL\": \"BR-S\",\n}\n\nSOURCE = \"ons.org.br\"\n\n\ndef filter_data_by_date(data: pd.DataFrame, target_datetime: datetime) -> pd.DataFrame:\n    \"\"\"Filter capacity data for all rows that have:\n    - start <= target_datetime : the power plant was connected before the considered target_datetime\n    - end >= target_datetime : the power plant was not closed before the considered target_datetime\n    \"\"\"\n    df = data.copy()\n\n    df = df[\n        (df[\"start\"] <= target_datetime)\n        & ((df[\"end\"] >= target_datetime) | (df[\"end\"].isna()))\n    ]\n\n    return df\n\n\ndef fetch_production_capacity_for_all_zones(\n    target_datetime: datetime, session: Session | None = None\n) -> dict[str, Any] | None:\n    session = session or Session()\n    r: Response = session.get(CAPACITY_URL)\n    df = pd.read_csv(r.url, sep=\";\")\n    df = df[\n        [\n            \"nom_subsistema\",\n            \"nom_combustivel\",\n            \"dat_entradaoperacao\",\n            \"dat_desativacao\",\n            \"val_potenciaefetiva\",\n        ]\n    ]\n    df = df.rename(\n        columns={\n            \"nom_subsistema\": \"zone_key\",\n            \"nom_combustivel\": \"mode\",\n            \"dat_entradaoperacao\": \"start\",\n            \"dat_desativacao\": \"end\",\n            \"val_potenciaefetiva\": \"value\",\n        }\n    )\n\n    # convert start and end columns to datetime\n    df[\"start\"] = df[\"start\"].apply(\n        lambda x: pd.to_datetime(x, utc=False).replace(day=1, month=1)\n    )\n    df[\"end\"] = df[\"end\"].apply(\n        lambda x: (\n            pd.to_datetime(x, utc=False).replace(day=31, month=12)\n            if x is not None\n            else x\n        )\n    )\n    df = filter_data_by_date(df, target_datetime)\n    df[\"datetime\"] = target_datetime\n    df[\"mode\"] = df[\"mode\"].map(MODE_MAPPING)\n    df[\"zone_key\"] = df[\"zone_key\"].map(REGION_MAPPING)\n\n    df = df.groupby([\"zone_key\", \"mode\", \"datetime\"])[[\"value\"]].sum().reset_index()\n    if not df.empty:\n        capacity = {}\n        for zone in df[\"zone_key\"].unique():\n            zone_capacity_df = df.loc[df[\"zone_key\"] == zone]\n            zone_capacity = {}\n            for _idx, data in zone_capacity_df.iterrows():\n                mode_capacity = {\n                    \"datetime\": target_datetime.strftime(\"%Y-%m-%d\"),\n                    \"value\": round(data[\"value\"], 0),\n                    \"source\": SOURCE,\n                }\n\n                zone_capacity[data[\"mode\"]] = mode_capacity\n            capacity[zone] = zone_capacity\n        return capacity\n    else:\n        logger.error(f\"No capacity data for ONS in {target_datetime}\")\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session | None = None\n) -> dict[str, Any] | None:\n    session = session or Session()\n    capacity = fetch_production_capacity_for_all_zones(target_datetime, session)[\n        zone_key\n    ]\n    logger.info(f\"Fetched capacity for {zone_key} in {target_datetime}: \\n{capacity}\")\n    return capacity\n\n\nif __name__ == \"__main__\":\n    print(fetch_production_capacity(\"BR-N\", datetime(2021, 1, 1), Session()))\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/OPENELECTRICITY.py",
    "content": "from datetime import datetime\nfrom logging import getLogger\nfrom typing import Any\n\nimport pandas as pd\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.parsers.lib.utils import get_token\nfrom electricitymap.contrib.parsers.OPENNEM import ZONE_KEY_TO_REGION\n\n\"\"\"Disclaimer: only works for real-time data. There is retired capacity included but we do not have the information on when the capacity was retired.\"\"\"\nlogger = getLogger(__name__)\nREGION_MAPPING = {\n    ZONE_KEY_TO_REGION[key]: key for key in ZONE_KEY_TO_REGION\n}  # NT only has solar capacity so it will be excluded\n\nFUEL_MAPPING = {\n    \"wind\": \"wind\",\n    \"solar_rooftop\": \"solar\",\n    \"battery_charging\": \"battery storage\",\n    \"solar_utility\": \"solar\",\n    \"coal_black\": \"coal\",\n    \"battery_discharging\": \"battery storage\",\n    \"pumps\": \"hydro storage\",\n    \"gas_steam\": \"gas\",\n    \"gas_ocgt\": \"gas\",\n    \"hydro\": \"hydro\",\n    \"coal_brown\": \"coal\",\n    \"distillate\": \"oil\",\n    \"bioenergy_biogas\": \"biomass\",\n    \"gas_ccgt\": \"gas\",\n    \"gas_wcmg\": \"gas\",\n    \"gas_recip\": \"gas\",\n    \"bioenergy_biomass\": \"biomass\",\n}\n\nCAPACITY_URL = \"https://api.openelectricity.org.au/v4/facilities/\"\nSOURCE = \"https://openelectricity.org.au/\"\n\n\ndef get_openelectricity_capacity_data(session: Session) -> pd.DataFrame:\n    token = get_token(\"OPENELECTRICITY_TOKEN\")\n    headers = {\"Authorization\": f\"Bearer {token}\"}\n    r: Response = session.request(\"GET\", CAPACITY_URL, headers=headers)\n    data = r.json()\n    result = []\n\n    time_stamp = data.get(\"created_at\")\n\n    for entry in data.get(\"data\", []):\n        region = entry.get(\"network_region\")\n\n        for unit in entry.get(\"units\", []):\n            if unit.get(\"dispatch_type\") != \"GENERATOR\":\n                continue\n\n            if unit.get(\"status_id\") != \"operating\":\n                continue\n\n            transformed = {\n                \"zone_key\": region,\n                \"value\": unit.get(\"capacity_registered\"),\n                \"mode\": unit.get(\"fueltech_id\"),\n                \"datetime\": time_stamp,\n            }\n            result.append(transformed)\n\n    capacity_df = pd.DataFrame(result)\n    capacity_df[\"datetime\"] = capacity_df[\"datetime\"].apply(\n        lambda x: pd.to_datetime(x).replace(\n            month=1, day=1, hour=0, minute=0, second=0, microsecond=0, tzinfo=None\n        )\n    )\n\n    return capacity_df\n\n\ndef filter_capacity_data_by_datetime(\n    data: pd.DataFrame, target_datetime: datetime\n) -> pd.DataFrame:\n    \"\"\"Filter capacity data by datetime. For a given target_datetime, the capacity should only include plants created before then.\"\"\"\n    df = data.copy()\n    max_datetime = df[\"datetime\"].max()\n    min_datetime = df[\"datetime\"].min()\n\n    if target_datetime >= max_datetime:\n        df = df.copy()\n    elif target_datetime <= min_datetime:\n        df = df.loc[\n            df[\"datetime\"] == min_datetime\n        ].copy()  # we backfill the capacity data using the first data point\n    else:\n        df = df.loc[df[\"datetime\"] <= target_datetime]\n    return df\n\n\ndef fetch_production_capacity_for_all_zones(\n    target_datetime: datetime, session: Session | None = None\n) -> dict[str, Any]:\n    session = session or Session()\n    capacity_df = get_openelectricity_capacity_data(session)\n    capacity_df = filter_capacity_data_by_datetime(capacity_df, target_datetime)\n\n    capacity_df[\"zone_key\"] = capacity_df[\"zone_key\"].map(REGION_MAPPING)\n    capacity_df[\"mode\"] = capacity_df[\"mode\"].map(FUEL_MAPPING)\n\n    capacity_df = (\n        capacity_df.groupby([\"zone_key\", \"mode\"])[[\"value\"]].sum().reset_index()\n    )\n\n    capacity_df = capacity_df.dropna(subset=[\"value\"])\n\n    capacity = {}\n    for zone in capacity_df[\"zone_key\"].unique():\n        zone_capacity_df = capacity_df.loc[capacity_df[\"zone_key\"] == zone]\n        zone_capacity = {}\n        for _idx, data in zone_capacity_df.iterrows():\n            zone_capacity[data[\"mode\"]] = {\n                \"datetime\": target_datetime.strftime(\"%Y-%m-%d\"),\n                \"value\": round(data[\"value\"], 2),\n                \"source\": SOURCE,\n            }\n        capacity[zone] = zone_capacity\n    return capacity\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session | None = None\n) -> dict[str, Any] | None:\n    session = session or Session()\n    capacity = fetch_production_capacity_for_all_zones(target_datetime, session)[\n        zone_key\n    ]\n    if capacity:\n        logger.info(\n            f\"Updated capacity for {zone_key} in {target_datetime}: \\n{capacity}\"\n        )\n        return capacity\n    else:\n        logger.error(f\"No capacity data for {zone_key} in {target_datetime}\")\n\n\ndef get_solar_capacity_au_nt(target_datetime: datetime) -> float | None:\n    \"\"\"Get solar capacity for AU-NT.\"\"\"\n    session = Session()\n    capacity_df = get_openelectricity_capacity_data(session)\n    capacity_df = filter_capacity_data_by_datetime(capacity_df, target_datetime)\n\n    capacity_df = capacity_df.loc[capacity_df[\"zone_key\"] == \"NT1\"]\n    capacity_df[\"zone_key\"] = \"AU-NT\"\n\n    capacity_df[\"mode\"] = capacity_df[\"mode\"].map(FUEL_MAPPING)\n\n    capacity_df = (\n        capacity_df.groupby([\"zone_key\", \"mode\"])[[\"value\"]].sum().reset_index()\n    )\n\n    solar_capacity = capacity_df.get(\"value\")\n    if solar_capacity is not None:\n        return round(solar_capacity.values[0], 0)\n    else:\n        logger.error(f\"No capacity data for AU-NT in {target_datetime.date()}\")\n\n\nif __name__ == \"__main__\":\n    session = Session()\n\n    print(fetch_production_capacity(\"AU-QLD\", datetime(2025, 1, 1), session))\n    # print(fetch_production_capacity(\"AU-VIC\", datetime(2015, 1, 1), Session()))\n    # print(get_solar_capacity_au_nt(datetime(2021, 1, 1)))\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/README.md",
    "content": "# Capacity update process\n\n## Table of contents\n\n- Context\n- Capacity source\n- Capacity update process\n  - When should capacity data be updated?\n  - Format of the capacity configuration\n  - Opening a PR\n  - The zone capacity can be updated automatically\n  - The zone capacity is updated manually\n- Technical requirements for adding a new data source\n- Building a new capacity parser\n\n## Context\n\nIn an effort to increase the quality of the data published on our app or API, we have started a whole initiative to enable us to track outliers in the source data. You can find more information on this [wiki page](https://github.com/electricitymaps/electricitymaps-contrib/wiki/Capacity-update-process).\n\n## Capacity sources\n\nOf all electricity data available, capacity is probably the least consistent (e.g. different reporting standards, different update frequencies, accessibility). A review of available capacity data was done in order to manage the number of different data sources used for capacity and to ensure that the capacity data has been reviewed and has an overall consistent quality level.\n\nThe main organisations that published capacity data are:\n\n- **[EIA](https://www.eia.gov/electricity/data/eia860/)**: The EIA publishes generator-level specific information about existing and planned generators and associated environmental equipment at electric power plants with 1 megawatt or greater of combined nameplate capacity. This data is available in the EIA API and can be aggregated by balancing authority.\n- **[EMBER](https://ember-climate.org/)**: EMBER aggregates data from different sources:\n  - IRENA for non-fossil generation,\n  - Global Energy Monitor for coal and gas generation,\n  - World Resource Institue, although this datbase is incomplete is can be used to verify information from the other sources.\n- **[ENTSO-e](https://transparency.entsoe.eu/generation/r2/installedGenerationCapacityAggregation/show)**: Net generation capacity is published on an annual basis on the ENTSO-e Transparency platform. This will be the prefered data source for European zones as the capacity breakdown is more detailed.\n- **[IRENA](https://www.irena.org/Data/Downloads/IRENASTAT)**: For most countries and technologies, the data reflects the capacity installed and connected at the end of the calendar year. Data has been obtained from a variety of sources, including an IRENA questionnaire, official national statistics, industry association reports, other reports and news articles.\n\nIn the case of countries divided in subzones, capacity data is collected directly from the main data source. This is the case for Brasil, Australia or Spain for instance.\n\n## Capacity update process\n\nThere are two ways of updating capacity configuration files:\n\n- The zone has a capacity parser\n- The update must be done manually.\n\n### When should capacity data be updated?\n\nDepending on the source, capacity data can be updated at a more or less regular frequency.\n\nIn the case of EMBER, IRENA and ENTSO-e, capacity data is updated once a year with data for the previous year. This update usually happens in the third quarter of the year (June to September of Y+1). The capacity for these zones should therefore be updated **once per year**.\n\nThe EIA updates their capacity dataset on a monthly basis so updates can happen **every semester or every quarter**.\n\nWe would like to update the capacity data for **all zones** once per year, around the 3rd quarter. This can be done more for capacity that are updated every month or quarter but it is not absolutely required.\n\n### Format of the capacity configuration\n\nThe capacity configuration should include the date from which the value is valid.\n\nFor a chosen mode, a data point needs to include the following fields:\n\n- **value**: the installed capacity for the chosen mode,\n- **datetime**: from this date forward, the value is considered to be the most up-to-date\n- **source**: the data source\n\nThis format will enable us to track the evolution of capacity across different zones over time such as the increase of renewables or phase out of fossil power plants.\n\nLooking at the example of DK-DK1 mentioned above, the capacity configuration format would be the following:\n\n```\ncapacity\n├── wind\n    ├── datetime: \"2023-01-01\"\n    ├── source: \"ENTSOE\"\n    └── value: 5233\n```\n\n### Opening a PR\n\nBefore opening a PR to update capacity data, you should check the following:\n\n- **Do not update all capacities at once!** Smaller PRs will help us make sure that no error slips through the cracks. We recommend updated a few zones at once or by group of zones (EIA, ENTSOE, EMBER, IRENA etc.)\n- **The new data points are consistent with the previous ones.** Big breaks in trends are rare for capacity data. You should check whether the variation between two data points is realistic. We expect that renewable capacity will increase in the coming years and fossil capacity to decrease,so these are patterns to look out for.\n- **Reference main changes in the PR description**. If you spot a major change in values, please mention it and verify it. This will make the reviewer's job easier!\n\n### The zone capacity can be updated automatically\n\nFor some zones, we have developed capacity parsers which collect the data automatically.\n\nThe update of capacity configurations can be done in the `contrib` repo using `uv run capacity_update`.\n\nThe `capacity_update` function has the following arguments:\n| Argument | Description |\n|-------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| --zone | A specific zone (e.g. DK-DK1) |\n| --source | A group of zones. The capacity update will run for all the zones that have capacity from this data source. The groups of zones are: EIA, EMBER, ENTSOE, IRENA, ONS, OPENNEM, REE |\n| --target_datetime | Date for the capacity data (e.g. \"2023-01-01\") |\n| --update_aggregate | Boolean to update the aggregate zone (for instance DK should be updated if we change the capacity for DK-DK1). This value is set to False by default|\n\nHere is a list of examples:\n\n```{python}\nuv run capacity_update --zone DK-DK1 --target_datetime \"2023-01-01 --update_aggregate True\"\n```\n\n```{python}\nuv run capacity_update --source EIA --target_datetime \"2023-06-01\"\n```\n\nThe following zones can be updated with a parser are listed on our wiki page [Capacity update process](https://github.com/electricitymaps/electricitymaps-contrib/wiki/Capacity-update-process)\n\n### The zone capacity is updated manually\n\nFor more information on manual capacity updates, please check our wiki page [Manual capacity updates](https://github.com/electricitymaps/electricitymaps-contrib/wiki/Manual-capacity-updates).\n\n## Technical requirements for adding a new data source\n\nIf a new data source becomes available for a zone that does **not** have a capacity parser:\n\n- **Verify the data source.** Please refer to our wiki page [Verify data sources](https://github.com/electricitymaps/electricitymaps-contrib/wiki/Verify-data-sources). The data should come from an authoritative data source, the criteria are listed on the wiki page.\n- **Update this document with the new data source**. For maintainability and transparency reasons, the data should be easily accessible. This will enable another contributor to update the capacity breakdown in the future. You can create a new subsection in the wiki page [Manual updates](https://github.com/electricitymaps/electricitymaps-contrib/wiki/Manual-capacity-updates)\n- **Add the guidelines to collect the data**. This should also be done for maintainability and transparency reasons.\n\nIf the capacity for the zone in question is collected using a capacity parser:\n\n- **Verify the data source.**\n- **Compare the new data with the existing data.** As explained above, we want to limit the number of data sources used and wish to use sources for which a certain level of quality is implied.\n- **Discuss with the Electricity Maps team.** If the new data source is indeed of higher quality and meets all the requirements, feel free to ask the Electricity Maps team. We will find the best way forward otgether :)\n\nYou can create an issue on [contrib](https://github.com/electricitymaps/electricitymaps-contrib/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc) if you find a new data source or if an existing link is broken.\n\n## Building a new capacity parser\n\nIf data can be parsed from an online source, you can build a parser to automatically get this data.\n\nHere are the following steps to build a capacity parser:\n\n- **Building the parser.** The parser should include a `fetch_production_capacity` function.\n\n```{python}\ndef fetch_production_capacity(zone_key: ZoneKey, target_datetime: datetime, session:Session)-> Dict[str:Any]:\n  capacity_dict = ....\n  return capacity_dict\n```\n\n- **Update the zone configuration.** Add the productionCapacity parser to the parsers items.\n\n```\nparsers:\n  consumption: FR.fetch_consumption\n  production: FR.fetch_production\n  productionCapacity: ENTSOE.fetch_production_capacity\n```\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/REE.py",
    "content": "from calendar import monthrange\nfrom datetime import datetime\nfrom logging import getLogger\nfrom typing import Any\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\n\n\"\"\"Disclaimer: Capacity for the Spanish isles is only available per archipelago. This parser should not be used for the Canary Islands and the Balearic Islands as we do not get the capacity per island.\"\"\"\n\nlogger = getLogger(__name__)\nMODE_MAPPING = {\n    \"Hidráulica\": \"hydro\",\n    \"Turbinación bombeo\": \"hydro storage\",\n    \"Nuclear\": \"nuclear\",\n    \"Carbón\": \"coal\",\n    \"Fuel + Gas\": \"gas\",\n    \"Ciclo combinado\": \"gas\",\n    \"Eólica\": \"wind\",\n    \"Solar fotovoltaica\": \"solar\",\n    \"Solar térmica\": \"solar\",\n    \"Otras renovables\": \"biomass\",  # Cross-checked against ENTSOE installed capacity + production data\n    \"Cogeneración\": \"gas\",\n    \"Residuos no renovables\": \"unknown\",\n    \"Residuos renovables\": \"biomass\",\n    \"Motores diésel\": \"oil\",\n    \"Turbina de gas\": \"gas\",\n    \"Turbina de vapor\": \"gas\",\n}\n\nGEO_LIMIT_TO_GEO_IDS = {\n    \"peninsular\": 8741,\n    \"canarias\": 19,\n    \"baleares\": 18,\n    \"ceuta\": 12,\n    \"melilla\": 8746,\n}\n\nZONE_KEY_TO_GEO_LIMIT = {\n    \"ES\": \"peninsular\",\n    # \"ES-IB-FO\": \"baleares\",\n    # \"ES-IB-IZ\": \"baleares\",\n    # \"ES-IB-MA\": \"baleares\",\n    # \"ES-IB-ME\": \"baleares\",\n    # \"ES-CN-FVLZ\": \"canarias\",\n    # \"ES-CN-GC\": \"canarias\",\n    # \"ES-CN-HI\": \"canarias\",\n    # \"ES-CN-IG\": \"canarias\",\n    # \"ES-CN-LP\": \"canarias\",\n    # \"ES-CN-TE\": \"canarias\",\n    \"ES-CE\": \"ceuta\",\n    \"ES-ML\": \"melilla\",\n}\n\n\ndef fetch_production_capacity(\n    zone_key: ZoneKey, target_datetime: datetime, session: Session\n) -> dict[str, Any] | None:\n    geo_limit = ZONE_KEY_TO_GEO_LIMIT[zone_key]\n    geo_ids = GEO_LIMIT_TO_GEO_IDS[geo_limit]\n    url = \"https://apidatos.ree.es/es/datos/generacion/potencia-instalada\"\n    params = {\n        \"start_date\": target_datetime.strftime(\"%Y-%m-01T00:00\"),\n        \"end_date\": target_datetime.strftime(\n            f\"%Y-%m-{monthrange(target_datetime.year, target_datetime.month)[1]}T23:59\"\n        ),\n        \"time_trunc\": \"month\",\n        \"geo_trunc\": \"electric_system\",\n        \"geo_limit\": geo_limit,\n        \"geo_ids\": geo_ids,\n        \"tecno_select\": \"all\",\n    }\n\n    r: Response = session.get(url, params=params)\n    if r.status_code == 200:\n        data = r.json()[\"included\"]\n        capacity = {}\n        for item in data:\n            value: float = round(item[\"attributes\"][\"values\"][0][\"value\"], 0)\n            if item[\"type\"] in MODE_MAPPING:\n                mode = MODE_MAPPING[item[\"type\"]]\n                if mode in capacity:\n                    capacity[mode][\"value\"] += value\n                else:\n                    mode_capacity = {\n                        \"datetime\": target_datetime.strftime(\"%Y-%m-%d\"),\n                        \"value\": value,\n                        \"source\": \"ree.es\",\n                    }\n                    capacity[mode] = mode_capacity\n        logger.info(\n            f\"Fetched capacity for {zone_key} on {target_datetime.date()}: \\n{capacity}\"\n        )\n        return capacity\n    else:\n        logger.warning(\n            f\"{zone_key}: No capacity data available for year {target_datetime.year}\"\n        )\n\n\ndef fetch_production_capacity_for_all_zones(\n    target_datetime: datetime, session: Session | None = None\n) -> dict[str, Any]:\n    if session is None:\n        session = Session()\n    ree_capacity = {}\n    for zone in ZONE_KEY_TO_GEO_LIMIT:\n        zone_capacity = fetch_production_capacity(zone, target_datetime, session)\n        ree_capacity[zone] = zone_capacity\n    logger.info(f\"Fetched capacity for REE zones on {target_datetime.date()}\")\n    return ree_capacity\n\n\nif __name__ == \"__main__\":\n    fetch_production_capacity(\"ES\", datetime(2023, 1, 1), Session())\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/tests/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/tests/__snapshots__/test_OPENELECTRICITY.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_capacities\n  dict({\n    'battery storage': dict({\n      'datetime': '2025-01-01',\n      'source': 'https://openelectricity.org.au/',\n      'value': 1250.6,\n    }),\n    'biomass': dict({\n      'datetime': '2025-01-01',\n      'source': 'https://openelectricity.org.au/',\n      'value': 313.28,\n    }),\n    'coal': dict({\n      'datetime': '2025-01-01',\n      'source': 'https://openelectricity.org.au/',\n      'value': 8119.0,\n    }),\n    'gas': dict({\n      'datetime': '2025-01-01',\n      'source': 'https://openelectricity.org.au/',\n      'value': 3201.98,\n    }),\n    'hydro': dict({\n      'datetime': '2025-01-01',\n      'source': 'https://openelectricity.org.au/',\n      'value': 726.0,\n    }),\n    'hydro storage': dict({\n      'datetime': '2025-01-01',\n      'source': 'https://openelectricity.org.au/',\n      'value': 480.0,\n    }),\n    'oil': dict({\n      'datetime': '2025-01-01',\n      'source': 'https://openelectricity.org.au/',\n      'value': 453.0,\n    }),\n    'solar': dict({\n      'datetime': '2025-01-01',\n      'source': 'https://openelectricity.org.au/',\n      'value': 4364.81,\n    }),\n    'wind': dict({\n      'datetime': '2025-01-01',\n      'source': 'https://openelectricity.org.au/',\n      'value': 2648.2,\n    }),\n  })\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/tests/conftest.py",
    "content": "\"\"\"\nThis is a configuration file for pytest that defines test fixtures available for\nuse by all tests under this path.\n\nFixtures ref: https://docs.pytest.org/en/stable/explanation/fixtures.html\n\"\"\"\n\nimport pytest\nfrom requests import Session\nfrom requests_mock import Adapter\n\n\n@pytest.fixture\ndef adapter():\n    \"\"\"\n    A `requests.Adapter` enables us to mock responses when making web requests\n    via `requests.Session`.\n\n    Adapter ref: https://requests.readthedocs.io/en/latest/user/advanced/#transport-adapters\n    \"\"\"\n    adapter = Adapter()\n    yield adapter\n\n\n@pytest.fixture\ndef session(adapter):\n    \"\"\"\n    A `request.Session` using the adapter fixture's object whenever http:// or\n    https:// requests are made.\n\n    Session ref: https://requests.readthedocs.io/en/latest/user/advanced/#session-objects\n    \"\"\"\n    session = Session()\n    session.mount(\"http://\", adapter)\n    session.mount(\"https://\", adapter)\n    yield session\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/tests/mocks/OPENELECTRICITY/AU-QLD_capacities.json",
    "content": "{\n  \"version\": \"4.0.14\",\n  \"created_at\": \"2025-07-21T21:19:57+10:00\",\n  \"success\": true,\n  \"data\": [\n    {\n      \"code\": \"ADP\",\n      \"name\": \"Adelaide Desalination\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Adelaide Desalination plant (ADP), formerly known as the Port Stanvac Desalination Plant, is a sea water reverse osmosis desalination plant located in Lonsdale, South Australia which has the capacity to provide the city of Adelaide with up to 50% of its drinking water needs.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ADPBA1L\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.76,\n          \"data_first_seen\": \"2021-05-18T09:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"ADPPV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 24.75,\n          \"data_first_seen\": \"2021-05-18T13:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ADPBA1G\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.76,\n          \"data_first_seen\": \"2021-05-18T10:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ADPPV2\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 0.2,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ADPPV3\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 0.02,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ALBANY\",\n      \"name\": \"Albany\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Albany wind and Grasmere farms are two wind power stations near Albany, Western Australia, owned by Bright Energy Investments. They are adjacent and are often considered a single facility. They have 18 wind turbines, with a maximum generating capacity of 35.4 MW of electricity. The original Albany Wind Farm was commissioned in October 2001, after ten years of planning. The wind farm has the capacity to produce 80 per cent of the electricity requirements of Albany.Originally commissioned in 2001 the farm was the largest of its kind in Australia.<br/>The farm originally had 12 wind turbines, with 6 extra turbines installed in 2011 as the Grasmere Wind Farm. The  original Albany Wind Farm turbines are ENERCON model E66, each with three 35 metres (115 ft) long blades made from fibreglass and kevlar (making them very flexible in order to withstand any conditions) and are fitted to 65 metres (213 ft) towers. The nose cone which the blades attach to weighs around 14 tonnes. At the time of construction these turbines were the largest installed in the southern hemisphere. The turbines operate automatically, with the three blades adjusted to make best use of power output from any wind direction or strength. They have been designed to withstand the strongest winds likely in Albany and incorporate special lightning protection. Each turbine has a rating of 1.8 MW and is able to produce electrical energy at wind speeds of 7\\u2013130 kilometres per hour (4\\u201370 kn) at which the turbines are shut down. Maximum output is achieved at a wind speed of 50 kilometres per hour (27 kn). The 6 new turbines installed in 2011 are ENERCON model E70 with a rating of 2.3 MW. The turbines were made in Germany.<br/>The Albany and Grasmere wind farms are situated on the coast about 12 kilometres (7 mi) south-west of the city. They are in an elevated position at approximately 80 metres (262 ft) above the Southern Ocean. The height and locality is designed to maximise exploitation of local wind conditions, and combined with the short distance to the main electricity transmission system make this an outstanding wind farm site.The farms also acts as a tourist attraction in Albany. When built A$200,000 was spent on board walks, viewing towers, interpretive displays and picnic areas on and around the site. The road to the site underwent a A$400,000 upgrade for better access for visitors. The Bibbulmun Track also traverses the site and had to be re-aligned toward the cliffs and stabilized.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ALBANY_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.6,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0ALDOGA\",\n      \"name\": \"Aldoga\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Aldoga Solar Farm will be approximately 380MW. This solar photovoltaic (PV) facility is located approximately 20 km north-west of Gladstone on the central Queensland coast.</p><p>The Aldoga Solar Farm will deliver a flagship renewable energy project on Economic Development Queensland (EDQ) land as part of the Queensland Government\\u2019s <em>'Advancing our cities and regions strategy\\u2019</em>, which aims to renew and repurpose underutilised state land to generate jobs and drive economic growth.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0ALDOGA\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 387.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ALDGASF\",\n      \"name\": \"Aldoga\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Aldoga Solar Farm will be approximately 380MW. This solar photovoltaic (PV) facility is located approximately 20 km north-west of Gladstone on the central Queensland coast.</p><p>The Aldoga Solar Farm will deliver a flagship renewable energy project on Economic Development Queensland (EDQ) land as part of the Queensland Government\\u2019s <em>'Advancing our cities and regions strategy\\u2019</em>, which aims to renew and repurpose underutilised state land to generate jobs and drive economic growth.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ALDGASF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 535.21,\n          \"data_first_seen\": \"2025-03-21T15:05:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:35:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"AMCORGR\",\n      \"name\": \"Amcor Glass\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"AMCORGR\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 4.0,\n          \"emissions_factor_co2\": 0.9,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ANGASTON\",\n      \"name\": \"Angaston\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Angaston Power Station is a diesel-powered electricity generator in the Barossa Valley region of South Australia near the town of Angaston. It is owned and operated by Snowy Hydro since 2014. It consists of 30 diesel reciprocating engines generating up to 50 MW of electricity to meet peak demands in the National Electricity Market.The power station was designed and built by Cummins Power Generation under contract from Infratil in 2005. At the time, it was Australia&#x27;s largest and lowest-emission diesel power station. It achieves the low emissions through selective catalytic reduction technology, spraying urea into the exhaust.Snowy Hydro bought assets from Infratil in 2014. These included Lumo Energy, Direct Connect and three diesel peaking generators for a total of 136 MW. The other two were Lonsdale Power Station and Port Stanvac Power Station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ANGAS2\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 20.0,\n          \"emissions_factor_co2\": 1.0136,\n          \"data_first_seen\": \"2005-01-06T11:10:00+10:00\",\n          \"data_last_seen\": \"2016-05-23T09:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ANGAST1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.6606,\n          \"data_first_seen\": \"2016-05-27T12:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-09T21:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ANGAS1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.0136,\n          \"data_first_seen\": \"2005-01-06T11:10:00+10:00\",\n          \"data_last_seen\": \"2016-05-23T09:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"APS\",\n      \"name\": \"Anglesea\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Anglesea Power Station was a brown coal\\u2013powered thermal power station located at Anglesea, in Victoria, Australia. The station had one steam turbine, with a capacity of 150 megawatts. It was operated by Alcoa of Australia and supplied almost 40% of the electricity used by the company&#x27;s Point Henry aluminium smelter, until the smelter&#x27;s closure in August 2014.</p>\",\n      \"units\": [\n        {\n          \"code\": \"APS\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 165.0,\n          \"emissions_factor_co2\": 1.2286,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2015-08-21T21:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"APPIN\",\n      \"name\": \"Appin\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>In a world first, EDL developed the largest WCMG power station at Appin that captured drained WCMG and also directly used a portion of the methane present as combustion air in the generator sets, further reducing the mine\\u2019s greenhouse gas (GHG) emissions.</p>\",\n      \"units\": [\n        {\n          \"code\": \"APPIN\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 55.6,\n          \"emissions_factor_co2\": 0.8126,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ARWF\",\n      \"name\": \"Ararat\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Ararat Wind Farm is wind farm in western Victoria, Australia. It was officially opened on 27 June 2017 and was the third-largest wind farm in Australia at that time, with capacity to generate 240MW from 75 turbines.Of the 75 turbines, 70 are in the Rural City of Ararat and five are in the Shire of Northern Grampians.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ARWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 241.59,\n          \"data_first_seen\": \"2016-08-19T10:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"AVLSF\",\n      \"name\": \"Avonlie\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Avonlie Solar Farm will be a large-scale solar farm in Narrandera, New South Wales. The project will comprise more than 450,000 solar panels with a total energy capacity of up to roughly 245MW(DC).</p>\",\n      \"units\": [\n        {\n          \"code\": \"AVLSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 254.1,\n          \"data_first_seen\": \"2023-03-28T14:25:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:10:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"AWABAREF\",\n      \"name\": \"Awaba\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"AWABAREF\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.0741,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BADGINGARRA\",\n      \"name\": \"Badgingarra\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Badgingarra Wind Farm (BWF) is located just to the north of APA\\u2019s 80-megawatt Emu Downs Wind Farm and the 20-megawatt Emu Downs Solar Farm. BWF consists of 37 Siemens 3.6-megawatt wind turbine generators installed with a hub height of 85 metres and tip height of 150 metres.</p><p>BWF generates 130 megawatts of power into the Western Power electricity grid, creating a 230-megawatt renewable energy precinct near Cervantes, approximately 180 kilometres north of Perth, Western Australia.</p><p>The $315 million APA development is underpinned by an agreement with Alinta Energy for the purchase of all the energy and Large Scale Renewable Generation Certificates generated by the wind farm through to December 2035.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BADGINGARRA_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 130.0,\n          \"data_first_seen\": \"2019-01-14T14:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DEIBDL\",\n      \"name\": \"Bairnsdale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Bairnsdale Power Station is a 94 megawatts (126,000 hp) natural gas-fired power station in Victoria\\u2019s East Gippsland region, owned and operated by Alinta Energy. It is a fast start, peaking power station dispatching into the National Electricity Market. Bairnsdale Power Station is connected to the AusNet Services distribution network grid.<br/>The station was commissioned in 2001. It has two GE LM6000PD gas turbines.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BDL01\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 46.0,\n          \"emissions_factor_co2\": 0.5382,\n          \"data_first_seen\": \"2001-05-22T17:15:00+10:00\",\n          \"data_last_seen\": \"2025-02-13T07:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BDL02\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 46.0,\n          \"emissions_factor_co2\": 0.5382,\n          \"data_first_seen\": \"2001-12-20T17:25:00+10:00\",\n          \"data_last_seen\": \"2025-05-06T14:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BAKING\",\n      \"name\": \"Baking Board\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Impact Investment Group\\u2019s Chinchilla Solar Farm is located approximately 7 km northwest of Chinchilla in the Western Downs shire of southeast Queensland. Located on 73 ha of land it has approximately 61,000 panels mounted on a single axis tracking system.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BAKING1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 17.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BHWF\",\n      \"name\": \"Bald Hills\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Bald Hills Wind Farm is an operating wind farm located approximately 10 km south east of Tarwin Lower in South Gippsland, Victoria, Australia.  The Bald Hills Wind Farm site covers approximately 1,750ha of largely cleared cattle and sheep grazing farmland. The turbines are located in three distinct areas, one to the west and one to the east of Tarwin Lower Waratah Road, and one near the end of Bald Hills Road.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BALDHWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 106.6,\n          \"data_first_seen\": \"2015-02-24T08:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BALBESS\",\n      \"name\": \"Ballarat\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Ballarat Energy Storage System (BESS) is a grid-connected energy storage system connected to the Ballarat Area Terminal Substation in Warrenheip, a suburb pf Ballarat in Victoria. It was commissioned in 2018 and provides 30 MWh of storage capacity at 30 MW. The battery was developed by NuvoGroup (owned by Spotless). Fluence provided the batteries, AusNet Services owns the facility, which is operated by EnergyAustralia. Funding was provided by AusNet Services and Australian Renewable Energy Agency (ARENA).The system consists of nine units each of which contains Lithium-ion batteries along with cooling and safety systems.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BALBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"2018-11-07T11:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T16:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BALBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"2018-11-07T10:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T19:45:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BBASEHOS\",\n      \"name\": \"Ballarat Hospital\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BBASEHOS\",\n          \"fueltech_id\": \"gas_recip\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.812,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BANGOWF\",\n      \"name\": \"Bango\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Bango Wind Farm is a development of 46 wind turbines and associated infrastructure on agricultural land approximately 30 km north of Yass, NSW. The site is well suited to wind generation due to its reliable wind resource, low density of rural residential dwellings and proximity to existing transmission infrastructure.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BANGOWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 84.8,\n          \"data_first_seen\": \"2021-06-10T16:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BANGOWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 159.0,\n          \"data_first_seen\": \"2021-01-14T12:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BAPS\",\n      \"name\": \"Banimboola\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Banimboola Power Station is a hydroelectric power station on the Dartmouth Dam Regulating Pond (or Banimboola Pondage), downstream of Dartmouth Dam on the Mitta Mitta River in Victoria, Australia. Banimboola has three turbo generators, with a generating capacity of 12.2 megawatts (16,360 hp) of electricity.  It is owned and operated by AGL Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BAPS\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 12.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BANKSPT\",\n      \"name\": \"Bankstown Sports Club\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BANKSPT1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.9,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BANNSP\",\n      \"name\": \"Bannerton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Bannerton Solar Park is a solar power station in the locality of Bannerton southeast of Robinvale in the Sunraysia district of Victoria. It generates up to 88MW of electricity to the National Electricity Market (NEM).<br/>Bannerton Solar Park is the second solar farm to be funded by the Clean Energy Finance Corporation (after the Gannawarra Solar Farm). It uses 320,000 solar panels to generate 110MWDC/88MWAC of electricity. It has offtake agreements with Alinta Energy and Yarra Trams.CIMIC Group company UGL Limited designed and built the solar farm, including  single axis tracking system, substation and connection to the Powercor Australia grid. It is built on land unsuitable for Almond orchards.Bannerton is near the edge of the Victorian electricity grid. The Solar Farm exports electricity at 66kV into the distribution network to support the local grid in responding to the load imposed from irrigation in summer.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BANN1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 100.0,\n          \"data_first_seen\": \"2018-07-20T14:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BARCALDN\",\n      \"name\": \"Barcaldine\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Barcaldine Power Station is a combined-cycle power station in Barcaldine, Queensland.  Its NEMMCO registered capacity as of January 2009 was 55 MW.<br/>According to the Geoscience Australia database, it is also known as the Len Wishaw power station and consists of a 38 MW gas turbine and a 15MW steam turbine.  The steam turbine at the power station is to be taken offline.The power station was built by Energy Equity Corporation, with the gas turbine being completed in 1995 and the steam turbine added in 1999.  The station had originally been planned for Blackall.  Enertrade acquired the station and associated gas pipeline in June 2003.  With the dissolution of Enertrade in May 2007, the station and pipeline were acquired by Ergon Energy Queensland Pty Ltd.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BARCALDN\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 37.0,\n          \"emissions_factor_co2\": 1.2153,\n          \"data_first_seen\": \"1998-12-07T07:40:00+10:00\",\n          \"data_last_seen\": \"2025-06-30T19:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BARCSF\",\n      \"name\": \"Barcaldine\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Barcaldine Solar Farm is a solar farm located five kilometres east of the town of Barcaldine in Central Queensland, Australia. The power station is owned by Elecnor and is situated on a 90 hectare site. It will use single-axis tracking technology. The power station can generate 20 megawatts AC. It consists of 78,000 panels.<br/><br/>Power was supplied to the grid in December 2016. It was Queensland&#x27;s first large scale solar farm.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BARCSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 20.0,\n          \"data_first_seen\": \"2016-12-21T15:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BARKIPS\",\n      \"name\": \"Barker Inlet\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Barker Inlet Power Station is a power station in South Australia. It was announced on 7 June 2017 by AGL Energy to replace part of its ageing Torrens Island Power Station and was built alongside the existing station on Torrens Island in the northwestern suburbs of Adelaide. The power station was commissioned on 4 November 2019.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BARKIPS1\",\n          \"fueltech_id\": \"gas_recip\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 211.0,\n          \"emissions_factor_co2\": 0.5897,\n          \"data_first_seen\": \"2019-10-15T17:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T22:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BARRON\",\n      \"name\": \"Barron Gorge\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Barron Gorge Hydroelectric Power Station (or Barron Gorge Hydro) in Queensland, Australia is an electricity power station commissioned in 1963 with a maximum capacity of 66 megawatts (89,000 hp). It is located in the locality of Barron Gorge in the Wet Tropics World Heritage Area 20 kilometres (12 mi) north-west of Cairns. It replaced an earlier station which was the first underground power station in the country and the first hydroelectric station in Queensland. The power station was refurbished in 2006.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BARRON-2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"1998-12-08T11:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BARRON-1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"1998-12-22T09:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BASTYAN\",\n      \"name\": \"Bastyan\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Bastyan Power Station is a conventional hydroelectric power station located in Western Tasmania, Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BASTYAN\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 79.9,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BAYSW\",\n      \"name\": \"Bayswater\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Bayswater Power Station is a bituminous (black) coal-powered thermal power station with four 660 megawatts (890,000 hp) Tokyo Shibaura Electric (Japan) steam driven turbo alternators for a combined capacity of 2,640 megawatts (3,540,000 hp). Commissioned between 1985 and 1986, the station is located 16 kilometres (10 mi) from Muswellbrook, and 28 km (17 mi) from Singleton in the Hunter Region of New South Wales, Australia.<br/>Prior to September 2014 Bayswater Power Station was part of NSW Government power producer, Macquarie Generation.  Macquarie Generation was acquired by AGL Energy in September 2014.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BW04\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 660.0,\n          \"emissions_factor_co2\": 0.8919,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BW02\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 660.0,\n          \"emissions_factor_co2\": 0.8919,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BW03\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 660.0,\n          \"emissions_factor_co2\": 0.8919,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BW01\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 660.0,\n          \"emissions_factor_co2\": 0.8919,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BBDISEL1\",\n      \"name\": \"Bell Bay\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BBDISEL1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 75.0,\n          \"emissions_factor_co2\": 0.972,\n          \"data_first_seen\": \"2016-05-24T14:00:00+10:00\",\n          \"data_last_seen\": \"2016-08-01T11:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BELLBAY\",\n      \"name\": \"Bell Bay\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Bell Bay Power Station was a power station located in Bell Bay, on the Tamar River, Tasmania, Australia, adjacent to the Tamar Valley Power Station, with which it was often confused. It was commissioned between 1971 and 1974 as an oil fired thermal power station, and was converted to natural gas in 2003, after the commissioning of the Tasmanian Gas Pipeline, a submarine gas pipeline which transports natural gas from Longford, Victoria, under Bass Strait, to Bell Bay, Tasmania. As the power station&#x27;s primary role was to provide system security in the event of drought for Tasmania&#x27;s predominantly hydro-electric based generation system it only was rarely called on to operate, resulting in intervals of five to eight years between periods of significant use. After the commissioning of Basslink in 2006, the power station was decommissioned in 2009.<br/>At the time of decommissioning, it had two 120 megawatts (160,000 hp) gas fired steam turbines and three 35 megawatts (47,000 hp) gas turbines, giving a total capacity of 345 megawatts (463,000 hp) of electricity. After the Bell Bay Power Station was decommissioned, the three smaller units became part of the Tamar Valley Power Station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BELLBAY1\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 120.0,\n          \"emissions_factor_co2\": 0.7086,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2008-11-19T08:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BELLBAY2\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 120.0,\n          \"emissions_factor_co2\": 0.7086,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2009-04-01T07:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BBP31\",\n      \"name\": \"Bell Bay Three\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Tamar Valley Power Station is a $230 million natural gas-fired power station located in Bell Bay in the Tamar Valley, Tasmania. It is owned by Hydro Tasmania, and is immediately adjacent to the decommissioned Bell Bay Power Station, which is also owned by Hydro Tasmania.</p><p>This facility refers to the 178MW open-cycle gas turbines at the sight.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TVPP104\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 58.0,\n          \"emissions_factor_co2\": 0.6647,\n          \"data_first_seen\": \"2009-04-01T18:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T19:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BBTHREE2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 35.0,\n          \"emissions_factor_co2\": 0.6647,\n          \"data_first_seen\": \"2006-08-21T17:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-01T09:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BBTHREE1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 35.0,\n          \"emissions_factor_co2\": 0.6647,\n          \"data_first_seen\": \"2006-07-26T14:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-01T09:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BBTHREE3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 35.0,\n          \"emissions_factor_co2\": 0.6647,\n          \"data_first_seen\": \"2006-06-29T15:10:00+10:00\",\n          \"data_last_seen\": \"2023-08-30T22:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BLAIRFOX_BEROSRD_WF\",\n      \"name\": \"Beros Road\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Blair Fox managed the purchase and dismantling of 19 ENERCON E40 500kW wind turbines from the Vila Lobos Wind Farm near Lamego, Portugal.<br/><br/>These wind turbines were transported to Western Australia, refurbished and installed at the Beros Rd Wind Farm at Warradarge around 270km north of Perth.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BLAIRFOX_BEROSRD_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 9.5,\n          \"data_first_seen\": \"2019-07-29T08:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-20T12:35:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BRYB1WF1\",\n      \"name\": \"Berrybank\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Berrybank 1 Wind Farm site is located in South-Western Victoria approximately 14km east of Lismore and 16km west of Cressy. It is approximately 130km west of Melbourne within the Victorian district known as the Western Plains, located within the Corangamite and Golden Plains Local Government Areas.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BRYB1WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 180.6,\n          \"data_first_seen\": \"2021-02-16T01:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BRYB2WF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 109.0,\n          \"data_first_seen\": \"2022-11-29T08:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BERWICK\",\n      \"name\": \"Berwick\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BERWICK\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.0,\n          \"emissions_factor_co2\": 0.062,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BERYLSF\",\n      \"name\": \"Beryl\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Located on Wiradjuri Country in the Central West of NSW, approximately 5 kilometres west of Gulgong, Beryl Solar Farm supplies clean, green energy to power the Sydney Metro Northwest Rail Link.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BERYLSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 98.0,\n          \"data_first_seen\": \"2019-04-23T09:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BIALAWF\",\n      \"name\": \"Biala\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Biala wind farm is a 31 turbine wind farm located approximately 6km south of Grabben Gullen on Grabben Gullen Road, 8km east of Biala and 14.5km south west of Crookwell in the Southern Tablelands of NSW. The planned wind farm is 100% owned by Beijing Jingneng Clean Energy (Australia) Holding Pty Ltd (BJCE Australia) who own the nearby 73 turbine Gullen Range Wind Farm and 10MW Gullen Solar Farm.<br/>Biala Wind Farm is expected to have an installed capacity of approximately 110MW producing enough electricity for approximately 46,000 typical homes on an average day of wind.<br/>BJCE Australia commenced construction of the wind farm in August 2019 with electricity expected to be generated in the second quarter of 2020.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GULLRWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 110.67,\n          \"data_first_seen\": \"2020-06-20T12:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BLAYNEY\",\n      \"name\": \"Blayney\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Blayney wind farm is a wind power station at Lake Carcoar, south of Blayney, New South Wales, Australia. It was acquired by Trustpower in 2014, and is now owned by Tilt Renewables. Blayney has fifteen wind turbines, with a total nameplate capacity of 9.9 MW of electricity.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BLAYNEY\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 9.9,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNOWY6\",\n      \"name\": \"Blowering\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The dam houses a hydroelectric power station and has one turbine generator, with a generating capacity of 80 megawatts of electricity; with a net generation of 260 gigawatt-hours per annum. The power station has 86.6 metres rated hydraulic head.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BLOWERNG\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 80.0,\n          \"data_first_seen\": \"2001-08-07T13:50:00+10:00\",\n          \"data_last_seen\": \"2025-04-24T13:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SNOWY6\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 80.0,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2001-09-24T19:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BLUEGSF\",\n      \"name\": \"Blue Grass\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Blue Grass solar farm in Queensland, Australia, is being developed by Spanish renewable energy producer X-ELIO. The 200MW solar facility will produce 420GWh of green electricity a year, sufficient to power approximately 80,000 Queensland homes, once fully operational in the fourth quarter of 2021.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BLUEGSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 183.0,\n          \"data_first_seen\": \"2022-08-01T13:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BLULAKE\",\n      \"name\": \"Blue Lake Milling\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BLULAKE1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.657,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BLUEWATERS\",\n      \"name\": \"Bluewaters\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Bluewaters Power Station was the first privately owned, coal-fired power station in Western Australia. It was built by Griffin Energy in 2009. The site is 4.5 km (2.8 mi) northeast of Collie.<br/>The plant consists of two 208  megawatts units, running on sub-bituminous coal. The boilers were constructed by IHI while the turbines and generators were supplied by Alstom.  EPC contractors were Mitsui and Hitachi Plant Technologies.<br/>Griffin Coal appointed administrators KordaMentha after financial difficulty in 2009, however the power station continues to operate.Community consultation commenced in 2009 for a proposed expansion and the WA Government approved it in 2010.  The proposal is to add two identical units and bring the capacity of the plant to 830 megawatts. As of 2018 it remains on hold, with two years remaining until they are required to re-apply for approvals.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BW2_BLUEWATERS_G1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 217.0,\n          \"emissions_factor_co2\": 0.7017,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BW1_BLUEWATERS_G2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 217.0,\n          \"emissions_factor_co2\": 0.7017,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BLYTHB\",\n      \"name\": \"Blyth\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Blyth Battery is a grid-scale battery that will connect into South Australia\\u2019s electricity grid via the transmission network.</p><p>The Blyth Battery will use CATL batteries supplied and installed by our project consortium \\u2013 Green Light Contractors and NHOA Australia.</p><p>The Blyth Battery will provide stability for the region by dispatching stored energy to the grid during peak times of demand.</p><p><br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"BLYTHB1G1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 281.0,\n          \"data_first_seen\": \"2024-09-06T13:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BLYTHB1L1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 281.0,\n          \"data_first_seen\": \"2024-08-20T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BOCOROCK\",\n      \"name\": \"Boco Rock\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Boco Rock Wind Farm is a wind farm 10km southwest of Nimmitabel in the Snowy Mountains region of New South Wales, Australia. It has 67 GE 100-1.7 wind turbines with a hub height of 80m, and generates up to 113MW of electricity. It is managed by the developers, CWP Renewables but is now owned by EGCO.The engineering, procurement and construction contract for the wind farm was let in June 2013 to a consortium of GE and Downer EDI. The electricity generated is contracted for sale to EnergyAustralia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BOCORWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 113.0,\n          \"data_first_seen\": \"2014-08-29T00:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BODWF\",\n      \"name\": \"Bodangora\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Bodangora Wind Farm is a wind farm owned by Infigen Energy in the district of Bodangora near Wellington, New South Wales, Australia. It has 33 wind turbines with a total generating capacity of 113.2 MW. The towers are 85 metres tall, and the rotor diameter is 130 metres. The wind turbine blades were manufactured in Bergama, Turkey. The development of the project began in 2009. It received planning approval in August 2013. The wind farm was completed on 27 February 2019.Bodangora Wind Farm has a power purchase agreement to sell 60% of the electricity generated to EnergyAustralia until the end of 2030.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BODWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 113.0,\n          \"data_first_seen\": \"2018-08-08T11:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MCKAY\",\n      \"name\": \"Bogong / Mackay\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>McKay Creek Power Station is one of four hydroelectric power stations in the Kiewa Hydroelectric Scheme, Victoria, Australia. McKay Creek has six 25 megawatts generators driven by Pelton wheel turbines, with a total generating capacity of 150 megawatts.<br/><br/>The power station is located on the slopes of Mount McKay at ground level. The water is transported from the Rocky Valley Dam through a near vertical pipe. Water released from the power station is used by the Bogong Hydropower Project, commissioned in 2009.<br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"MCKAY1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 300.0,\n          \"data_first_seen\": \"1998-12-07T06:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MCKAY2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 53.0,\n          \"data_first_seen\": \"1998-12-07T06:35:00+10:00\",\n          \"data_last_seen\": \"2009-09-22T10:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BOLIVAR\",\n      \"name\": \"Bolivar\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Iberdrola Australia has agreed to lease 120 MW of aero-derivative gas turbine equipment from the South Australian Government for a period of 25 years.</p><p>The equipment includes four independent 30 MW dual fuel units and related balance of plant. The generators can start in less than ten minutes and enable\\u00a0Iberdrola Australia\\u00a0to manage the intermittency risks associated with its large and growing fleet of renewable energy assets.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BOWWPV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 8.25,\n          \"data_first_seen\": \"2022-02-23T10:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T18:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BOWWBA1L\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 3.08,\n          \"data_first_seen\": \"2022-02-28T14:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"BOLIVAR1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 9.9,\n          \"emissions_factor_co2\": 0.0201,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BOWWBA1G\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 3.08,\n          \"data_first_seen\": \"2022-03-02T15:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BOLIVPS\",\n      \"name\": \"Bolivar\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Iberdrola Australia has agreed to lease 120 MW of aero-derivative gas turbine equipment from the South Australian Government for a period of 25 years.</p><p>The equipment includes four independent 30 MW dual fuel units and related balance of plant. The generators can start in less than ten minutes and enable\\u00a0Iberdrola Australia\\u00a0to manage the intermittency risks associated with its large and growing fleet of renewable energy assets.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BOLIVPS1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 128.0,\n          \"emissions_factor_co2\": 0.7974,\n          \"data_first_seen\": \"2022-12-10T18:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BOMENSF\",\n      \"name\": \"Bomen\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Located 10 km north-east of Wagga Wagga city centre on Wiradjuri land, in the Wagga Wagga Special Activation Precinct, Bomen Solar Farm is a 100 MW solar farm and battery built by Australian developer Spark Renewables.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BOMENSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 121.0,\n          \"data_first_seen\": \"2020-03-17T07:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0BCWF\",\n      \"name\": \"Boulder Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Boulder Creek Wind Farm (Stage 1) is a 228 MW onshore wind farm, located 40 km southwest of Rockhampton and approximately 5 km west of Mount Morgan in central Queensland. The project, which is co-owned by Aula Energy and CS Energy will comprise 38 wind turbines, and will commence construction in November 2024.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0BCWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 221.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BBATTERY\",\n      \"name\": \"Bouldercombe\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Bouldercombe Battery Project (BBP) located in Rockhampton, is now operational and is\\u00a0Genex\\u2019s first large-scale battery energy storage project of 50MW/100MWh\\u2019s.</p><p>Genex has signed a Connection Agreement with Powerlink enabling BBP to connect into the adjacent 275kV/132kV Bouldercombe substation, via an exiting 132kV bay. BBP is located at critical part of the Queensland electricity grid with high network strength and Marginal Loss Factors.</p><p></p><p>BBP is built using the Tesla Megapack 2.0 hardware and will operate under the Tesla Autobidder software.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BBATRYL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 67.0,\n          \"data_first_seen\": \"2023-08-11T15:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:50:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"BBATTERY\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 67.0,\n          \"data_first_seen\": \"2023-08-08T15:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BRAEMARA\",\n      \"name\": \"Braemar\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Braemar-1 is a 502 MW open-cycle natural gas turbine plant located 35 kilometres south west of Dalby, adjacent to the Kogan Creek Power Station, Queensland \\u2013 New South Wales high voltage transmission interconnector and Powerlink 320/274 kV substation. It is supplied from the Tipton West coal seam gas fields, with the 150-kilometre pipeline between Condamine and Braemar, which is used exclusively to supply the Braemar Power Station.<br/><br/>The power station was developed by ERM Power and was built by Alstom. It is equipped by three Alstom&#x27;s 150 MW GT13E2 gas turbines. The power station cost A$545 million. It was completed in 2006 and is anticipated to operate until 2036.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BRAEMAR2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 168.0,\n          \"emissions_factor_co2\": 0.5923,\n          \"data_first_seen\": \"2006-06-02T12:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T20:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BRAEMAR1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 168.0,\n          \"emissions_factor_co2\": 0.5923,\n          \"data_first_seen\": \"2006-05-10T11:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T19:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BRAEMAR3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 168.0,\n          \"emissions_factor_co2\": 0.5923,\n          \"data_first_seen\": \"2006-06-08T16:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-04T00:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"B2PS\",\n      \"name\": \"Braemar 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Braemar-2 is a 450 MW open-cycle natural gas turbine plant adjacent to the Braemar-1 power station. The power station was developed by ERM Power and was built by Bilfinger. It supplies peak demand power and it is equipped by three Siemens&#x27;s 150 MW SGT5-2000E gas turbines. The power station cost A$546 million. Gas for this power station is sourced from the Stratheden field at Daandine.<br/><br/>Arrow Energy acquired 50% of the station in 2008 and on 4 July 2011, it took full control of Braemar-2.<br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"BRAEMAR6\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 173.0,\n          \"emissions_factor_co2\": 0.5806,\n          \"data_first_seen\": \"2009-04-07T15:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T19:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BRAEMAR5\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 173.0,\n          \"emissions_factor_co2\": 0.5806,\n          \"data_first_seen\": \"2009-03-27T16:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-17T21:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BRAEMAR7\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 173.0,\n          \"emissions_factor_co2\": 0.5806,\n          \"data_first_seen\": \"2009-04-25T09:50:00+10:00\",\n          \"data_last_seen\": \"2025-06-21T06:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BREMER_BAY\",\n      \"name\": \"Bremer Bay\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>This installation, opened in 2004, generates around 40% of Bremer Bay&#x27;s annual electricity, which reduces the diesel consumption required by around 40,000 litres. Situated at Bremer Bay, around 400km south-east of Perth, the 600kw turbine sits at 46 metres high, featuring three 22-metre-long blades. An identical wind turbine was installed at Hopetoun Wind Farm, about 175km west of Esperance.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BREMER_BAY_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 0.6,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0BRENDALEBESS\",\n      \"name\": \"Brendale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Brendale BESS will allow Akaysha to trade capacity in the electricity market to provide ancillary services, such as Energy Arbitrage, Contingency and regulation Frequency Control Ancillary Services (FCAS), to support the National Electricity Market (NEM). These features will place further downward pressure on the cost to electricity users in QLD. Akaysha expects to commence operations in 2025.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0BRENDALEBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 205.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0BRENDALEBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 205.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BROADMDW\",\n      \"name\": \"Broadmeadows\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BROADMDW\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.0,\n          \"emissions_factor_co2\": 0.0783,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0BSSF\",\n      \"name\": \"Broadsound\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Broadsound Solar Farm and Battery is located on Barada Kabalbara Yetimarala People land in Central Queensland\\u2019s Renewable Energy Zone, approximately 150 km north west of Rockhampton.</p><p>The 368 MWdc Solar Farm will comprise of 634,000 solar panels over an area of approximately 900 ha.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0BSBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 180.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0BSBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 180.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0BSSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 368.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BWTR1\",\n      \"name\": \"Broadwater\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Commissioned in 2008, Cape Byron is one of the largest base load generators of renewable power in Australia. Cape Byron Management purchased the Broadwater and Condong power stations in November 2013 and has continued to implement a range of efficiency, reliability and environmental improvements. Since taking over the power stations annual renewable energy generation has increased by more than 20% at both Broadwater and Condong.</p><p>The 38MW biomass power station at Broadwater produces clean, renewable electricity from mostly sugar cane milling waste, along with certain types of wood residues and energy crops, commonly referred to as \\u2018biomass\\u2019 fuel.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BWTR1\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 38.0,\n          \"emissions_factor_co2\": 0.0289,\n          \"data_first_seen\": \"2023-08-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BHILLGT\",\n      \"name\": \"Broken Hill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"GB01\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.6022,\n          \"data_first_seen\": \"2009-07-02T18:00:00+10:00\",\n          \"data_last_seen\": \"2025-06-07T14:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BROKENH\",\n      \"name\": \"Broken Hill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Broken Hill Solar Plant, which became operational in December 2015, is a 53 megawatt farm located near Broken Hill in western New South Wales, Australia. It is associated with the Nyngan Solar Plant (almost 600 km to the east), making the total capacity of the combined plants 155 megawatts.<br/>The Broken Hill solar plant, like other generation near the edge of the grid, has suffered from changes in loss factor calculations, with a decrease of 22.7% from a 2017-18 financial year (FY) Marginal Loss Factor (MLF) of 1.2841 to 1.0603 (2018-19 FY MLF), which has affected revenue. On 12 September 2019, the output of the farm was reduced by 50%.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BROKENH1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 53.0,\n          \"data_first_seen\": \"2015-09-15T10:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BHB\",\n      \"name\": \"Broken Hill Battery\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>AGL has commenced construction of a 50 MW / 100 MWh Large-Scale Battery Energy Storage System (BESS) facility with advanced grid-forming inverters at 74 \\u2013 76 Pinnacles Place, Broken Hill. The Project will support the reliable supply of electricity to Broken Hill in the event of line failure and provide efficient grid support for the region. The Project will also provide storage and firming capacity to the National Energy Market (NEM) as well as additional services to assist grid stability.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BHBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 66.0,\n          \"data_first_seen\": \"2023-12-01T09:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BHBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 66.0,\n          \"data_first_seen\": \"2023-12-04T09:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BROOKLYN\",\n      \"name\": \"Brooklyn\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BROOKLYN\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.83,\n          \"emissions_factor_co2\": 0.0738,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BROWNMT\",\n      \"name\": \"Brown Mountain\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BROWNMT\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BPLANDF\",\n      \"name\": \"Browns Plains\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BPLANDF1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.0,\n          \"emissions_factor_co2\": 0.0762,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BULGANA\",\n      \"name\": \"Bulgana Green Power Hub\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Bulgana Green Power Hub is a wind farm north of Stawell in the Australian state of Victoria. The project is owned by Neoen. Construction of the 56 wind turbines, with a total generation capacity of 194MW, was completed in August 2019, and connections to the national grid reached full capacity in 2021. 90% of the energy is contracted for supply to the Government of Victoria.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BULBESL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 24.0,\n          \"data_first_seen\": \"2021-07-06T19:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"BULBESG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 24.0,\n          \"data_first_seen\": \"2021-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"BULGANA1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 204.0,\n          \"data_first_seen\": \"2020-05-14T11:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0BUNDSF\",\n      \"name\": \"Bundaberg\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The 100 MW Solar PV SAT project is located in the Bundaberg region, approximately 360 kilometres north of Brisbane and is expected to have a life span of 25 years. The farm is being constructed across 146 hectares with an estimated 162,000 modules installed in 2,319 rows.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0BUNDSF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 78.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BNGSF1\",\n      \"name\": \"Bungala One\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Bungala Solar Farm is located near Port Augusta, in South Australia. The Project was developed by Reach Solar Energy, and acquired by Enel Green Power in 2017.</p><p>The Plants, with a total capacity of 275 MW from approximately\\u202f800,000\\u202fphotovoltaic (PV) modules, commenced full production in 2020.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BNGSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 135.0,\n          \"data_first_seen\": \"2018-05-14T17:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BNGSF2\",\n      \"name\": \"Bungala Two\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BNGSF2\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 135.0,\n          \"data_first_seen\": \"2018-10-30T09:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0BUNGAMA\",\n      \"name\": \"Bungama\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Bungama BESS is designed to integrate into the National Electricity Market through a 275 kV connection to ElectraNet\\u2019s Bungama Substation. Through grid connection, the Project will contribute to a more reliable and stable network for South Australia, by storing excess energy until it is needed. The project is being designed for an operational life of up to 25 years.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0BUNGAMABESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 150.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0BUNGAMABESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 150.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BDONGHYD\",\n      \"name\": \"Burrendong\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Burrendong Dam is a rock-fill embankment major gated dam with a clay core across the Macquarie River upstream of Wellington in the central west region of New South Wales, Australia. A hydro-electric power station generates up to 19 megawatts (25,000 hp) of electricity from the flow of the water leaving Burrendong Dam.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BDONGHYD\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 19.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BURRIN\",\n      \"name\": \"Burrinjuck\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Burrinjuck Power Station is a hydroelectric power station at Burrinjuck Dam, New South Wales, Australia. Burrinjuck has three turbines with a total generating capacity of 28 megawatts (38,000 hp) of electricity.<br/>The power station was commenced in 1927, running two 5 megawatts (6,700 hp) turbines. In 1938, an additional two 5 MW turbines were added at the dam wall. In 1972, floods damaged the original two turbines, which were decommissioned. In 2017, the remaining two turbines were each upgraded to 6 megawatts (8,000 hp), and an additional turbine of 16 megawatts (21,000 hp) was added.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BURRIN\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 34.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BUTLERSG\",\n      \"name\": \"Butlers Gorge\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Butlers Gorge Power Station is a conventional hydroelectric power station located in the Central Highlands region of Tasmania, Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BUTLERSG\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 14.4,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T08:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0CALBESS1\",\n      \"name\": \"Calala 1\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The proposed Calala Battery Energy Storage System (BESS) is located approximately 5.8km southeast of the Tamworth CBD within the Tamworth regional municipality. The BESS has a charge/discharge capacity of up to 250MW and an energy storage capacity up to 500MWh which is enough power to supply electricity for up to 110,000 homes.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0CALBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 150.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0CALBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 150.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0CALBESS2\",\n      \"name\": \"Calala 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The proposed Calala Battery Energy Storage System (BESS) is located approximately 5.8km southeast of the Tamworth CBD within the Tamworth regional municipality. The BESS has a charge/discharge capacity of up to 250MW and an energy storage capacity up to 500MWh which is enough power to supply electricity for up to 110,000 homes.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0CALBESSL2\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0CALBESSG2\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CALL_A\",\n      \"name\": \"Callide A\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Callide Power Station is located near Biloela, in Central Queensland, Australia. It is coal powered with eight steam turbines with a combined generation capacity of 1,720 MW of electricity. Callide A was commissioned in 1965, refurbished in 1998 and decommissioned in 2015/16.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CALL_A_2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.328,\n          \"data_first_seen\": \"1998-12-21T07:05:00+10:00\",\n          \"data_last_seen\": \"2001-12-12T04:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CALL_A_1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.328,\n          \"data_first_seen\": \"1999-01-14T14:10:00+10:00\",\n          \"data_last_seen\": \"2001-12-12T17:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CALL_A_3\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.328,\n          \"data_first_seen\": \"1999-01-14T05:15:00+10:00\",\n          \"data_last_seen\": \"2001-09-14T14:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CALL_A_4\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.328,\n          \"data_first_seen\": \"1999-01-14T06:50:00+10:00\",\n          \"data_last_seen\": \"2015-03-06T21:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CALL_B\",\n      \"name\": \"Callide B\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Callide Power Station is located near Biloela, in Central Queensland, Australia. It is coal powered with eight steam turbines with a combined generation capacity of 1,720 MW of electricity. Callide A was commissioned in 1965, refurbished in 1998 and decommissioned in 2015/16. As of 2018, generation capacity was 1510 MW.The coal for Callide comes from the nearby Callide Coalfields and water from the Awoonga dam and Stag Creek Pipeline.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CALL_B_2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 350.0,\n          \"emissions_factor_co2\": 0.9556,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CALL_B_1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 350.0,\n          \"emissions_factor_co2\": 0.9556,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CALLIDEC1\",\n      \"name\": \"Callide C\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Callide Power Station is located near Biloela, in Central Queensland, Australia. It is coal powered with eight steam turbines with a combined generation capacity of 1,720 MW of electricity. Callide A was commissioned in 1965, refurbished in 1998 and decommissioned in 2015/16. As of 2018, generation capacity was 1510 MW.The coal for Callide comes from the nearby Callide Coalfields and water from the Awoonga dam and Stag Creek Pipeline.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CPP_3\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 420.0,\n          \"emissions_factor_co2\": 0.887,\n          \"data_first_seen\": \"2001-02-08T10:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CPP_4\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 420.0,\n          \"emissions_factor_co2\": 0.887,\n          \"data_first_seen\": \"2001-08-01T14:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CANUNDA1\",\n      \"name\": \"Canunda\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Canunda Wind Farm (formerly named Lake Bonney Central Wind Farm) is a $92.5 million, 46 MW wind power project located on grazing land approximately 16 kilometres south of Millicent, and 6 kilometres west of Tantanoola in South Australia. It is jointly owned by GDF Suez Energy AustraliaEn 72%) and Mitsui (28%).<br/>The wind farm is made up of 23 Vestas 2.0 MW wind turbines, together with an underground electrical cable network, access tracks, crane hardstandings, wind monitoring masts and a 33 kV double-circuit distribution line. Each turbine consists of a 67-metre-high (220 ft) tower and 40-metre-long (130 ft) blades, and so are 107 metres in height to the tip of the blade. These wind turbines rotate at speeds between 9 rpm and 19 rpm, depending on the wind speed. The wind yield in South Australia enables Canunda to produce electricity at a 34 per cent capacity factor, a high yield by global standards.The wind farm generates enough electricity to supply around 30,000 average South Australian homes. The Canunda Wind Farm distribution line is 16 km long and transports the generated electricity from the wind farm to a nearby substation at Snuggery. The distribution line traverses mostly roadside verges, avoiding areas of environmental sensitivity along the route. The Canunda Wind Farm provides a number of benefits to the local and wider community, including clean electricity generation, enhanced agricultural viability of the farms involved and increased diversity of electricity supply for South Australia and the south east in particular. There has also been widespread community interest in the project and site tours have commenced.The Canunda Wind Farm was opened by the Premier of South Australia, Mike Rann, on 31 March 2005. The project was completed on time and on budget and Wind Prospect provided engineering support to the owners of the wind farm, International Power, during the construction phase. Canunda Wind Farm was International Power&#x27;s first wind farm globally. It represents a diversification of the company&#x27;s energy business in Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CNUNDAWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 46.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CAPBES\",\n      \"name\": \"Capital\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Capital Battery is a 100MW stand-alone battery capable of storing up to 200MWh of energy with up to 2 hours of power in reserve. 50 MW was committed as part of the ACT Government\\u2019s 2020 renewable energy auction, with a further 50 MW yet to be contracted.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CAPBES1G\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 125.0,\n          \"data_first_seen\": \"2023-07-26T11:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CAPBES1L\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 125.0,\n          \"data_first_seen\": \"2023-07-25T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CAPTL_WF\",\n      \"name\": \"Capital\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Capital Wind Farm near Bungendore is the largest wind farm in New South Wales.  It is part of the 6,000-hectare (15,000-acre) Capital Renewable Energy Precinct, along with nearby Woodlawn Wind Farm and the Capital East Solar Demonstration Plant.<br/>Capital Wind Farm was built by international contractors Suzlon Energy for owner and operator Infigen Energy.  Construction began in early 2008, and the wind farm became fully operational in October 2009. It is a 140.7 megawatt wind farm with 67 turbines.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CAPTL_WF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 140.0,\n          \"data_first_seen\": \"2009-07-04T17:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CESF\",\n      \"name\": \"Capital East\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Capital East Solar Farm 1 and 2 are co-located on the same site and adjacent to Capital Wind Farm. Construction was completed on the 120kW Capital East Solar Farm 1 in 2013. This was expanded in 2018 to 500kW with the addition of Capital East Solar 2 by 5B whom now provide the operations and maintenance services for both solar farms.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CESF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 0.5,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LI_WY_CA\",\n      \"name\": \"Catagunya / Liapootah / Wayatinah\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Liapootah is the first power station in the lower run-of-river system and it is where the cascade effect begins. Water from Lake Liapootah runs through to Liapootah Power Station and continues to Wayatinah Lagoon.</p><p>Water from Wayatinah Lagoon flows through to Wayatinah Power Station, continuing to Lake Catagunya.</p><p>Water from Lake Catagunya flows into Catagunya Power Station and then on to Lake Repulse.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LI_WY_CA\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 173.7,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CATAGUN1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 24.0,\n          \"emissions_factor_co2\": 0.972,\n          \"data_first_seen\": \"2016-03-11T16:35:00+10:00\",\n          \"data_last_seen\": \"2016-05-06T15:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CATHROCK\",\n      \"name\": \"Cathedral Rocks\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Cathedral Rocks Wind Farm is a wind power station located about 30 km west of Port Lincoln in South Australia, near the southern tip of the Eyre Peninsula. It has 33 wind turbines of 2 MW each, with a combined generating capacity of 66 MW of electricity. The site covers an area of about 29 km\\u00b2, with a coastal exposure of nearly 11 km and is private farming land. The wind farm was commissioned in September 2005.Before the wind farm was built, extensive environmental and cultural studies were conducted. Surveys undertaken included the assessment of potential impacts to Aboriginal and European cultural heritage, flora, visual amenity, noise levels, birds and other animals. Construction of the wind farm was undertaken with consideration for the environment.Construction started in 2004, and the first turbines were commissioned in late 2005. The wind farm was fully operational by 2007. It is operated by a joint venture between EnergyAustralia and Acciona Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CATHROCK\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 66.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CTHLWF\",\n      \"name\": \"Cattle Hill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Cattle Hill Wind Farm is a wind farm project being developed and constructed by Goldwind Australia, in Tasmania.  <br/>The facility began construction in 2018 and has 48 wind turbines at a site just east of Lake Echo in the Tasmanian Central Highlands.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CTHLWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 148.0,\n          \"data_first_seen\": \"2020-01-07T10:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CETHANA\",\n      \"name\": \"Cethana\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Cethana Power Station is a conventional hydroelectric power station located in north-western Tasmania, Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CETHANA\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 85.0,\n          \"data_first_seen\": \"2005-05-16T17:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CHALLWF\",\n      \"name\": \"Challicum Hills\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Challicum Hills Wind Farm is a wind farm encompassed by 35 (1.5 MW) NEG NM 64 wind turbines,  with a total generating capacity of 52.5 MW of electricity. The wind farm is near Ararat in western  Victoria, Australia. The power station was commissioned in August 2003 and is in a long term Power Purchase Agreement (PPA) with Origin Energy.<br/>The wind farm is owned and operated by Pacific Hydro. Part of the profits flow into a community fund that supports local projects.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CHALLHWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 52.5,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CHPSTWF\",\n      \"name\": \"Chepstowe\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Chepstowe Wind Farm, located approximately 30 km west of Ballarat, is a three turbine wind farm of 6.15MW capacity. The project was completed in March 2015. The three Senvion turbines began supplying energy to the local grid in April 2015. All the energy produced is be purchased on a long term contract. In an average year, enough renewable energy will be produced to power over 3,400 households.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CHPSTWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 6.15,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CHYTWF\",\n      \"name\": \"Cherry Tree\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Cherry Tree Wind Farm is a small wind farm located approximately 15\\u00a0km south-east of Seymour, Victoria. The 16 turbine, 57.6 MW farm was developed and constructed by Infigen Energy for John Laing Group. Construction started in January 2019 and was operational in June 2020. The wind farm is expected to generate 182 GWh on average annually, for a capacity factor of 36%.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CHYTWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 57.6,\n          \"data_first_seen\": \"2020-05-01T18:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CHILDSF\",\n      \"name\": \"Childers\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Atmos Renewables acquired 100% of the interests in Childers Solar Farm Solar Farm in June 2022. The plant is located approximately 75km south of Bundaberg, QLD. Commercial operations were reached in June 2019 and is connected to the 66kV Ergon network at the onsite Childers substation. The Childers Solar Farm is expected to generate over 120GWh of electricity per annum.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CHILDSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 64.38,\n          \"data_first_seen\": \"2019-02-06T16:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CHBESS\",\n      \"name\": \"Chinchilla\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Chinchilla Battery is a $150 million grid-scale battery at CS Energy&#x27;s Kogan Creek site near Chinchilla on the Western Downs.</p><p>It uses lithium iron phosphate (also known as lithium ferro phosphate [LFP], or LiFePO4) batteries, which are the safest lithium batteries currently available.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CHBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 134.0,\n          \"data_first_seen\": \"2024-02-16T14:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CHBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 134.0,\n          \"data_first_seen\": \"2023-12-16T06:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CBWWBA\",\n      \"name\": \"Christies Beach\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Christies Beach wastewater treatment plant began operating in 1970 and was expanded in 1981 to support the growing southern suburbs population. It also received a significant upgrade in 2013 to ensure it can meet community needs until 2030.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CBWWPV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.75,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CBWWBG1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 0.66,\n          \"emissions_factor_co2\": 0.357,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CBWWDG1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 2.0,\n          \"emissions_factor_co2\": 0.785,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CBWWDG2\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 0.72,\n          \"emissions_factor_co2\": 0.785,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CBWWPV2\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.08,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CBWWBA1G\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.16,\n          \"data_first_seen\": \"2023-05-09T03:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T18:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CBWWBA1L\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.09,\n          \"data_first_seen\": \"2023-05-02T11:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:40:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CLARESF\",\n      \"name\": \"Clare\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"CLARESF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 110.0,\n          \"data_first_seen\": \"2018-04-17T09:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CLRKCWF\",\n      \"name\": \"Clarke Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Stage One of the Clarke Creek Wind Farm is located 150km north-west of Rockhampton and 150km south of Mackay on the land of the Barada Kabalbara Yetimarala (BKY) peoples. The 450MW wind farm will produce enough electricity to power around 330,000 Queensland homes and avoid 738,000 tonnes of carbon emissions each year.<br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"CLRKCWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 103.5,\n          \"data_first_seen\": \"2025-04-30T14:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CLRKCWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 346.5,\n          \"data_first_seen\": \"2024-10-02T02:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CLAYTON\",\n      \"name\": \"Clayton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>EDL\\u2019s Clayton Power Station occupies the former sand quarries at Clayton in Victoria. The landfill site, which is part of the Cleanaway Waste Management Clayton South Resource Recovery Centre, is substantially filled and closed but continues to generate landfill gas (LFG).</p>\",\n      \"units\": [\n        {\n          \"code\": \"CLAYTON\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 11.0,\n          \"emissions_factor_co2\": 0.0654,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CLEMGPWF\",\n      \"name\": \"Clements Gap\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Clements Gap Wind Farm is a wind farm opened in 2010 located in the Barunga Range, South Australia near Clements Gap, some 20 minutes south of Port Pirie. The wind farm consists of 27 wind turbines with a total generating capacity of 57 MW. It provides enough electricity for up to 33,000 homes and is estimated to avoid the emission of 150,000 tonnes of greenhouse gases each year.  The Clements Gap site was chosen because of its powerful winds, easy construction access, simple grid connection, and strong community support.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CLEMGPWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 57.0,\n          \"data_first_seen\": \"2009-05-07T15:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CLERMSF\",\n      \"name\": \"Clermont\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Located in Clermont, 106km north of Emerald, Queensland, the 89MWp DC Clermont Solar Farm is the third solar plant in Gentari Solar Australia\\u2019s portfolio based in QLD. It created just under 600 jobs in various capacities during construction and continues to employ those within the local community for the operations and maintenance of the asset.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CLERMSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 92.0,\n          \"data_first_seen\": \"2019-06-19T09:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CLOVER\",\n      \"name\": \"Clover\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>One of four units in the Kiewa Hydroelectric Scheme.</p><p>350km northeast of Melbourne in the Australian Alps, the Kiewa Hydroelectric Scheme is the largest in the State. Kiewa houses four power stations with an average annual electricity output of 404 GWh. The scheme harnesses energy from the Rocky Valley and Pretty Valley branches of the East Kiewa River, which rises on the Bogong High Plains, and the West Kiewa River, which rises near Mount Hotham.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CLOVER\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 29.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-02-28T08:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CLOVER1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 14.5,\n          \"data_first_seen\": \"1998-12-07T06:40:00+10:00\",\n          \"data_last_seen\": \"1999-10-14T10:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CLOVER2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 14.5,\n          \"data_first_seen\": \"1998-12-07T06:40:00+10:00\",\n          \"data_last_seen\": \"1999-10-14T10:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CLUNY\",\n      \"name\": \"Cluny\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Cluny Power Station is a conventional hydroelectric power station located in the Central Highlands region of Tasmania, Australia. The power station is situated on the Lower River Derwent catchment and is owned and operated by Hydro Tasmania.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CLUNY\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 19.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COCKBURN\",\n      \"name\": \"Cockburn\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Cockburn Power Station (CKB) is a power station in Cockburn, Western Australia. The station was commissioned by Western Power Corporation in 2003 and is immediately south of the older Kwinana Power Station. It has a 160 MW natural gas powered Alstom GT13E2 gas turbine which provides steam to an 80 MW steam turbine that together generate a total 240 MW of electricity. It was the first combined cycle gas turbine power station in Western Australia. It came under the control of Verve Energy in 2006 when Western Power was split, and since 2014 has been under control of Synergy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"COCKBURN_CCG1\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 249.7,\n          \"emissions_factor_co2\": 0.3733,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CODRGTON\",\n      \"name\": \"Codrington\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Codrington Wind Farm is a wind farm near Yambuk on the coast of south-western Victoria, Australia.<br/>Completed in June 2001, the 18.2MW installation of 14 wind turbines generates 51 GWh annually, for a capital cost of A$30 million by<br/>Pacific Hydro being the first fully private investment in a wind farm in Australia. When opened it was Australia&#x27;s largest wind farm and the first in Victoria.<br/>The Yambuk wind farm (Part of the Portland Wind Farm project) is directly adjacent to the Codrington Wind Farm. It has a total of 30MW in its 20 turbines.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CODRNGTON\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 18.2,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COHUNSF1\",\n      \"name\": \"Cohuna\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Cohuna Solar Farm is situated approximately 8 kilometres south of the town of Cohuna and around 25km east of Kerang in the Shire of Gannawarra in northern Victoria. Cohuna was one of 6 solar projects to score a guernsey in Victoria\\u2019s first renewable energy auction. Cohuna Solar Farm is expected to generate up to 77 GWh of electricity each year, avoiding around 71,000 tonnes of CO2 emissions annually. The project will involve the installation of approximately 87,000 bifacial solar panels, which make use of light hitting both the front and rear of the module</p>\",\n      \"units\": [\n        {\n          \"code\": \"COHUNSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 31.1,\n          \"data_first_seen\": \"2021-03-05T16:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COLEASF\",\n      \"name\": \"Coleambally\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Colleambally Solar Farm is a photovoltaic power station near the town of Coleambally in New South Wales, Australia. It is on the western side of the Kidman Way north of the town.<br/>It has an output of 150MW and was the largest solar power station in Australia  when it was commissioned in November 2018. It is owned by Neoen and was built by Bouygues. It has a 12-year power purchase agreement to sell its output to EnergyAustralia.The power station consists of a total of 565,488 solar panels arranged into 19,086 strings of panels. Each solar tracker drives three strings.</p>\",\n      \"units\": [\n        {\n          \"code\": \"COLEASF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 180.0,\n          \"data_first_seen\": \"2018-09-07T10:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COLWF01\",\n      \"name\": \"Collector\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Construction work on the 226.8MW project started in May 2019 and is expected to be finished in early 2021. The wind farm successfully exported its first safe, clean, renewable electricity in November 2020. The 54 turbines measure 150m to the blade tip and are located around 4km from Collector.</p>\",\n      \"units\": [\n        {\n          \"code\": \"COLWF01\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 226.0,\n          \"data_first_seen\": \"2020-11-12T22:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"INVESTEC_COLLGAR\",\n      \"name\": \"Collgar\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Collgar Wind Farm is a wind farm located approximately 25 kilometres south-east of Merredin, Western Australia. With 111 Vestas V90-2MW wind turbines built in the first stage, and a total capacity of 222 MW, it is expected to generate 720 GWh on average per year over the life of the project. It became fully operational in October 2011.</p>\",\n      \"units\": [\n        {\n          \"code\": \"INVESTEC_COLLGAR_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 222.0,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0SYNCOLLIEBESS\",\n      \"name\": \"Collie\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>In line with the WA State Government\\u2019s decarbonisation strategy to be delivered by 2030, the Collie Battery Energy Storage System (CBESS) Project forms part of Synergy&#x27;s decarbonisation strategy.</p><p>Coal-fired power generation is being replaced with renewable energy generation infrastructure and energy storage solutions.</p><p>CBESS is expected to deliver 64% of the new energy storage capacity announced as part of this plan.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0SYCOLLBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 500.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0SYCOLLBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 500.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COLLIE\",\n      \"name\": \"Collie\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Collie Power Station is a power station in Collie, Western Australia. It is coal powered with one steam turbine that generates a total capacity of 300 megawatts of electricity. The coal is mined locally from the Collie Sub-basin and is transported to the power plant by overland conveyor.<br/>The station was commissioned in 1999 with a single 300 megawatts steam turbine. Power generated by the station supplies the south-west of Australia through the South West Interconnected System (SWIS) operated by Western Power.In the financial year of 2008/2009, the station consumed approximately 1 million tonnes (2.2 billion pounds) of coal. Carbon Monitoring for Action estimates that, in 2009, Collie Power Station emitted 2.59 million tonnes (5.7 billion pounds) of CO2 to generate 2.3 terawatt-hours (8.3 petajoules) of electricity.In household consumer terms, this equates to 1.13 kilograms (2.5 lb) of CO2 emitted for each one kilowatt-hour (kWh), or 3.6 megajoules, of electricity produced and fed into the electricity grid. That is, Collie Power Station emits slightly less CO2 per kilowatt-hour of electricity produced than nearby closing Muja Power Station (1.14 kilograms or 2.5 pounds) but more than also nearby Bluewaters Power Station (0.825 kilograms or 1.82 pounds) based on estimates for the same year.</p>\",\n      \"units\": [\n        {\n          \"code\": \"COLLIE_G1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 318.3,\n          \"emissions_factor_co2\": 0.9501,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COLLIE_ESR\",\n      \"name\": \"Collie 1\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Collie Battery is Neoen\\u2019s first 4-hour long duration battery &amp; its first major project in Western Australia. The project\\u00a0has development approval for 1 GW / 4 GWh.<br/><br/>Once operational, Collie Battery will be able to provide short duration storage in peak times to ease pressure on the grid. It will have the ability to charge and discharge 20% of the average demand in Western Australia\\u2019s South-West Interconnected System (SWIS).</p><p>Stage 1 is sized at 219 MW / 877 MWh</p>\",\n      \"units\": [\n        {\n          \"code\": \"COLLIE_ESRG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 219.0,\n          \"data_first_seen\": \"2024-08-05T16:45:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"COLLIE_ESRL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 219.0,\n          \"data_first_seen\": \"2024-07-25T14:40:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:25:00+08:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0COLLIE_ESR2\",\n      \"name\": \"Collie 2\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Collie Battery is Neoen\\u2019s first 4-hour long duration battery &amp; its first major project in Western Australia. The project\\u00a0has development approval for 1 GW / 4 GWh.<br/><br/>Once operational, Collie Battery will be able to provide short duration storage in peak times to ease pressure on the grid. It will have the ability to charge and discharge 20% of the average demand in Western Australia\\u2019s South-West Interconnected System (SWIS).</p><p>Stage 2 is sized at 341 MW / 1,363 MWh</p>\",\n      \"units\": [\n        {\n          \"code\": \"0COLLIE_ESRG2\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 341.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0COLLIE_ESRL2\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 341.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"COLLIE_BESSG2\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 341.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"COLLIE_BESSL2\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 341.0,\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COLNSV\",\n      \"name\": \"Collinsville\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Collinsville Power Station is located south of Townsville, Queensland, Australia. It had five coal powered steam turbines with a combined generation capacity of 190 MW of electricity. The coal-fired power station closed in 2013. A solar power farm generating 42MW has been built on adjacent land.</p>\",\n      \"units\": [\n        {\n          \"code\": \"COLNSV_1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.1918,\n          \"data_first_seen\": \"1998-12-07T02:50:00+08:00\",\n          \"data_last_seen\": \"2012-08-16T10:20:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"COLNSV_2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.1918,\n          \"data_first_seen\": \"1998-12-14T01:30:00+08:00\",\n          \"data_last_seen\": \"2012-08-16T10:30:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"COLNSV_3\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.1918,\n          \"data_first_seen\": \"1998-12-07T03:00:00+08:00\",\n          \"data_last_seen\": \"2012-04-18T17:20:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"COLNSV_4\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.1918,\n          \"data_first_seen\": \"1998-12-07T02:50:00+08:00\",\n          \"data_last_seen\": \"2012-08-15T11:50:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"COLNSV_5\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 66.0,\n          \"emissions_factor_co2\": 1.1918,\n          \"data_first_seen\": \"1998-12-07T02:50:00+08:00\",\n          \"data_last_seen\": \"2012-08-16T11:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CSPVPS\",\n      \"name\": \"Collinsville\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Collinsville Solar Farm is located near Collinsville in central Queensland. The project was constructed on land surrounding the decommissioned (2013) Collinsville coal-fired power station, commencing operations in 2018.</p><p>The project consists of approximately 180,000 individual solar PV panels and has a generation capacity of 42.5 megawatts. It produces enough electricity each year to power up to 15,000 homes. The project offsets 90,000tonnes of carbon dioxide emissions (Co2) a year.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CSPVPS1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 42.0,\n          \"data_first_seen\": \"2018-07-31T14:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COLONGRA\",\n      \"name\": \"Colongra\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Colongra Gas Generation Plant (also known as Colongra Power Station) is a 667 MW gas-fired power station located in Colongra, New South Wales, Australia and is the largest gas-fired power station in New South Wales. It will generally be used during peak demand periods in New South Wales.<br/>The plant&#x27;s construction was tendered to Alstom which began the construction in October 2007, adjacent to the Munmorah coal-fired power station.  The plant was completed and commissioned in December 2009 at a cost of A$500 million.It was bought by Snowy Hydro in January 2015.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CG1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 181.0,\n          \"emissions_factor_co2\": 0.6158,\n          \"data_first_seen\": \"2009-06-22T17:45:00+10:00\",\n          \"data_last_seen\": \"2025-06-30T21:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CG2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 181.0,\n          \"emissions_factor_co2\": 0.6158,\n          \"data_first_seen\": \"2009-07-23T12:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-01T20:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CG4\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 181.0,\n          \"emissions_factor_co2\": 0.6158,\n          \"data_first_seen\": \"2009-10-21T21:40:00+10:00\",\n          \"data_last_seen\": \"2025-06-30T20:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"CG3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 181.0,\n          \"emissions_factor_co2\": 0.6158,\n          \"data_first_seen\": \"2009-09-12T18:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-01T20:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COLUMSF\",\n      \"name\": \"Columboola\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Columboola Solar Farm is a 162MWAC or 202.5 MWDC utility scale generation project situated on 410 hectares of grazing land in Western Downs, Queensland. The site is located approximately 10km north-east of Miles, and is accessible from Ryall Road off the Warrego Highway.</p>\",\n      \"units\": [\n        {\n          \"code\": \"COLUMSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 217.0,\n          \"data_first_seen\": \"2022-06-14T10:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CPSA\",\n      \"name\": \"Condamine A\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Condamine Power Station is a 140 MW combined cycle power station near Miles on the western Darling Downs in Queensland, Australia.  The station is located 8 kilometres (5.0 mi) east of Miles on the south side of the Warrego Highway.  The Condamine Power Station is owned by QGC Limited, a subsidiary of Royal Dutch Shell. It has been claimed to be the world\\u2019s first combined-cycle power station entirely fired by untreated coal seam gas and Australia&#x27;s first steam turbine condenser cooled by coal seam methane waste water. However, the Townsville Power Station at Yabulu, which was converted from a peak load power station to burn only coal seam gas in a combined cycle configuration, was commissioned much earlier, in February 2005.<br/>Construction began on 19 October 2007. It was completed in mid-2010.  The EPC contractor was Austrian Energy and Environment with the gas turbines supplied by Siemens. Parsons Brinckerhoff were the owner&#x27;s engineer for construction.  The gas turbine with dispatchable unit ID (DUID) &quot;CPSA&quot; began bidding into the National Electricity Market on 1 June 2009, with the first generation made available to the market on 10 July 2009. The Columboola Switching Station, which connects Condamine Power Station with the Chinchilla-to-Roma 132-kilovolt<br/>transmission line, was completed in October 2008.<br/>AGL Energy had an option to acquire the Condamine Power Station. This option was not exercised and expired on 14 April 2009.The power station has installed capacity of 140 MW.  <br/>Electricity is generated by two gas turbines and one steam turbine from coal seam gas. The two gas turbines are Siemens SGT-800 models and the steam turbine is a Siemens SST-400. According to the NEMMCO Applicants list, the registered capacity of the gas turbine is 87.4 MW (2 x 43.7 MW) and the registered capacity of the steam turbine is 57.1 MW.The gas reserves are extracted from the Berwyndale South Gasfield. Building the plant directly on top of the gas source will provide some of the cheapest gas-fired electricity to the National Electricity Market.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CPSA\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 143.0,\n          \"emissions_factor_co2\": 0.4543,\n          \"data_first_seen\": \"2009-07-08T16:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T20:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CONDONG1\",\n      \"name\": \"Condong\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Commissioned in 2008, Cape Byron is one of the largest base load generators of renewable power in Australia. Cape Byron Management purchased the Broadwater and Condong power stations in November 2013 and has continued to implement a range of efficiency, reliability and environmental improvements. Since taking over the power stations annual renewable energy generation has increased by more than 20% at both Broadwater and Condong.</p><p>Cape Byron Power operates the Condong Cogeneration Plant. This exists alongside the sugar mill, which has been part of the community for over 140 years. The Condong Plant contributes to the local economy, supporting the sugar cane industry and directly employs 25 people. The power to operate the sugar mill is generated primarily from bagasse, a waste product from sugar cane. It also provides power that is sold to the grid. This waste product is only available during the sugar cane crush season being from June to December. The use of this waste avoids it being transported elsewhere and potentially going to landfill. Other products are used to fuel the generation of power in the non-crush season (generally January through to mid June</p>\",\n      \"units\": [\n        {\n          \"code\": \"CONDONG1\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 0.0366,\n          \"data_first_seen\": \"2023-08-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CBWF\",\n      \"name\": \"Coonoer Bridge\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Coonooer Bridge Wind Farm is a wind farm 90 km northwest of Bendigo in the Australian state of Victoria. Its output is contracted to supply the Australian Capital Territory via the National Electricity Market at $81.50 per megawatt hour.The site is jointly owned by Eurus Energy, Windlab and the local community. It was the first commercial wind farm in Australia to have the local community included in the ownership in this way.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CBWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 19.8,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COOPGWF\",\n      \"name\": \"Coopers Gap\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Coopers Gap Wind Farm is a 453 megawatt wind power station in the Bilboa and Cooranga North region, of Australia, approximately 50 kilometres (31 mi) south-west of Kingaroy and 65 km (40 mi) north of Dalby in Queensland, Australia.<br/>A 60-metre (197 ft) wind-monitoring mast was installed in March 2006 in order to accurately measure wind speed and direction in the area.</p>\",\n      \"units\": [\n        {\n          \"code\": \"COOPGWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 452.0,\n          \"data_first_seen\": \"2019-06-24T11:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"COPTNHYD\",\n      \"name\": \"Copeton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Copeton is AGL&#x27;s largest hydroelectric power station in New South Wales, located 340 metres downstream from the Copeton Dam. The Copeton Dam has a storage capacity of around 1,364 GL and experiences variable water flow. Similarly to the Burrendong Dam, the primary purpose of the Copeton Dam is to supply irrigation for farming, domestic and industrial needs. The dam&#x27;s secondary purpose is to provide a measure of flood mitigation. Dam releases required by State Water are made to assist in wildlife conservation in downstream areas, especially in the lower reaches known as the Watercourse country . The station has two Kvaerner turbines, giving a total generating capacity of 22.5 MW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"COPTNHYD\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 22.5,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CORIO\",\n      \"name\": \"Corio\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"CORIO1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.062,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CRWASF1\",\n      \"name\": \"Corowa\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Corowa Solar Farm is a 30 MWac solar farm in NSW just outside of the 5,500 person strong town of Corowa. The project has been in development since 2017 and is currently in the late stages of construction.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CRWASF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 36.0,\n          \"data_first_seen\": \"2021-02-14T13:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CROOKWEL\",\n      \"name\": \"Crookwell\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Crookwell Wind Farm, located at Crookwell west of Goulburn, New South Wales with a total capacity of 4.8 MW. It was the first grid-connected wind farm in Australia when built by Pacific Power in 1998. It is now owned by Tilt Renewables.<br/>The farm was the largest wind farm in Australia when built, with the energy produced bought and on-sold to customers by then energy retailer Great Southern Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CROOKWEL\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.8,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CROOKWF2\",\n      \"name\": \"Crookwell 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>In November, GPG (the international electricity generation subsidiary of Naturgy) opened its Crookwell II Wind Farm in New South Wales, inside the ATC (Australian Capital Territory) and only 90 kilometres from Canberra, the Australian capital. The facility has a power capacity of 96 MW, 28 wind turbines and it will be able to supply 42,000 homes in Canberra thanks to generating 300,000 megawatts/hour per year of renewable electricity.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CROOKWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 96.04,\n          \"data_first_seen\": \"2018-08-14T08:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CROOKWF3\",\n      \"name\": \"Crookwell 3\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Crookwell 3 Wind Farm, located at Crookwell 25km north-west of Goulburn, and 90km north-east of Canberra, within the Upper Lachlan Shire Local Government Area, New South Wales</p>\",\n      \"units\": [\n        {\n          \"code\": \"CROOKWF3\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 57.0,\n          \"data_first_seen\": \"2024-05-22T14:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CROWLWF\",\n      \"name\": \"Crowlands\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Crowlands Wind Farm is located in Western Victoria\\u2019s Pyrenees Shire Council, 25km north-east of Ararat (205km west of Melbourne). The site was identified as an area highly suitable for efficiently capturing energy from the wind.</p><p>After a long period of consultation with the local community that began in 2004, the project was granted planning approval in August 2010. Following pre-construction assessments, consultations and reviews, the layout for the project has been refined and subsequently reduced. Development approval to construct and operate a wind energy facility at Crowlands was granted to Pacific Blue in 2013.</p><p>Crowlands Wind Farm consists of 39 turbines that produce clean energy equivalent to the yearly needs of around 50,000 Victorian homes. The turbines are Senvion MM92 wind turbine generators, rated at 2.05MW each, with a maximum hub height of 100m and a maximum blade tip height of 146.5m.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CROWLWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 79.95,\n          \"data_first_seen\": \"2018-12-09T13:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CRURWF1\",\n      \"name\": \"Crudine Ridge\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Crudine Ridge Wind Farm is a 135MW wind energy project situated approximately 45 km south of Mudgee, NSW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CRURWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 141.0,\n          \"data_first_seen\": \"2020-12-02T11:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0CULCSF\",\n      \"name\": \"Culcairn\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The 440 MWp Culcairn Solar Farm spans across 1,000 hectares of land and will be Neoen\\u2019s second largest solar asset in Australia once it goes into operations.</p><p>Neoen secured development approval for Culcairn Solar Farm from the NSW Government in 2021, with an option to build a 100 MW / 200 MWh battery in the future.</p><p>It will connect into the on-site 330 kV transmission line managed by TransGrid.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CUSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 350.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"CULLERIN\",\n      \"name\": \"Cullerin Range\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The 30 megawatt Cullerin Range Wind Farm is  located in the localities of Cullerin and Breadalbane in the Upper Lachlan Shire, New South Wales, Australia. The wind farm was completed in 2009 and cost around $90 million. The owner, Origin Energy, sold the business to Energy Developments, a subsidiary of Duet.</p>\",\n      \"units\": [\n        {\n          \"code\": \"CULLRGWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SBSOLAR1_CUNDERDIN_PV\",\n      \"name\": \"Cunderdin\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Cunderdin Solar Farm Project is a 128 MW DC photovoltaic solar system developed on the outskirts of Cunderdin, planned over 165ha which includes a 55 MW / 220 MWh battery energy storage system.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SBSOLAR1_CUNDERDIN_PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 128.0,\n          \"data_first_seen\": \"2024-08-19T16:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DAANDINE\",\n      \"name\": \"Daandine\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Queensland located Arrow Energy&#x27;s Daandine power station&#x27;s first electricity production occurred in December 2006 as a result of coal seam methane gas obtained from the nearby Daandine gas field. Prior to the opening of the new power station, ramp up gas from the Daandine field, had been sold to CS Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DAANDINE\",\n          \"fueltech_id\": \"gas_recip\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 33.0,\n          \"emissions_factor_co2\": 0.706,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DALNTH\",\n      \"name\": \"Dalrymple North\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Dalrymple ESCRI battery (Energy Storage for Commercial Renewable Integration) is a 30 MW / 8 MW\\u00b7h grid-connected battery array near Stansbury on Yorke Peninsula in South Australia. Its role is to provide improved reliability and stability to the electricity network on Yorke Peninsula and South Australia.<br/>The battery is installed adjacent to the Dalrymple substation, seven kilometres southwest of Stansbury. Dalrymple substation is at the end of a 275 kV power line into the peninsula. It feeds 33 kV lines to various towns across the lower end of the peninsula and receives electricity generated by the Wattle Point Wind Farm.<br/>The facility is able to store excess generation from Wattle Point Wind Farm as well as a colocated solar farm and is expected to provide a similar service to the Hornsdale Power Reserve in the Mid North of the state.The battery was constructed by Consolidated Power Projects with ABB and Samsung components. It was part-funded by a grant from the Commonwealth Government through the Australian Renewable Energy Agency (ARENA). It was commissioned in June and July 2018. It provides frequency control to the grid, and also enables the possibility for Yorke Peninsula to operate independently of the wider grid in the event of a system failure.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DALNTHL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"2018-07-05T11:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"DALNTH01\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"2018-06-05T15:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DDPS1\",\n      \"name\": \"Darling Downs\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Darling Downs Power Station is in Kogan, Western Downs Region, Queensland, Australia. It is 40 kilometres (25 mi) west of Dalby and owned by Origin Energy. The Darling Downs Power Station is adjacent to the QLD-NSW high voltage transmission Interconnector and the Powerlink Queensland R2 Braemar 330/275 kV Substation. <br/>Darling Downs is a gas fired combined cycle gas turbine power station and is the largest of its type in Australia. It is powered by three 120 MW GE Frame 9E gas turbines and one 270 MW steam turbine, which generate a total of 630 MW of electricity. A 205 kilometre pipeline transports the gas to the station from gas fields near Wallumbilla. The power station uses less than 3% of the water that a traditional coal powered power station does by utilising air-cooled technology.Origin Energy developed the power station and the construction costs for the project were $780 million. Darling Downs entered commercial operation in July 2010. and was officially opened on the 5 November 2010 by Premier Anna Bligh.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DDPS1\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 664.0,\n          \"emissions_factor_co2\": 0.4349,\n          \"data_first_seen\": \"2009-12-05T14:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DDSF\",\n      \"name\": \"Darling Downs\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Darling Downs Solar Farm is a 110MW photovoltaic solar power station in Queensland, Australia developed by APA Group 45 km west of Dalby in the Darling Downs region next to the Darling Downs Power Station. All of the electricity produced will be sold to Origin Energy until 2030. The solar farm connects to the national electricity grid through Powerlink&#x27;s Braemar substation. It has approximately 430,000 solar panels on an area of approximately 250 hectares (620 acres).The solar farm was planned by Origin Energy which owns the adjacent natural gas Darling Downs Power Station. Origin received planning approval and A$20 million support from the Australian Renewable Energy Agency (ARENA) before selling the project to APA Group in May 2017. designed and built by RCR Tomlinson under an engineering, procurement and construction contract worth approximately A$175 million.Darling Downs Solar Farm was the ninth solar farm to be approved by the Western Downs Regional Council.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DDSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 121.0,\n          \"data_first_seen\": \"2018-07-28T11:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DARLSF\",\n      \"name\": \"Darlington Point\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Darlington Point Solar Far is a photovoltaic power station under development 10 km south of the town of Darlington Point in New South Wales, Australia. It received planning approval and development consent on 7 December 2018, and has a power purchase agreement for supply of 150MW to Delta Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DARLSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 324.0,\n          \"data_first_seen\": \"2020-09-03T10:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DPNTB\",\n      \"name\": \"Darlington Point\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The combined 150MW / 300MWh Riverina and Darlington Point Energy Storage Systems is located adjacent to TransGrid\\u2019s Darlington Point Substation in the Murrumbidgee Shire, South West NSW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DPNTBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"data_first_seen\": \"2023-06-23T11:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"DPNTBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"data_first_seen\": \"2023-06-26T15:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DARTM\",\n      \"name\": \"Dartmouth\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Designed by the State Electricity Commission of Victoria, and constructed by Lewis Constructions, and commissioned in January 1981, Dartmouth Power Station has one Francis turbine-generator, with a generating capacity of 180 megawatts, the largest single installed hydroelectric turbine in Australia. It is owned and operated by AGL Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DARTM1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 185.0,\n          \"data_first_seen\": \"1998-12-07T07:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T21:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DAYDSF\",\n      \"name\": \"Daydream\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Daydream Solar Farm is a photovoltaic power station near Collinsville in Queensland, Australia. It uses a single-axis tracking system to follow the sun across the sky. It was developed by Edify Energy. It generates up to 180MW DC and  150MW AC.<br/>Powerlink upgraded its transmission network to connect the Hayman and Daydream solar farms to the grid.Daydream has a 12-year power purchase agreement to provide electricity to Origin Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DAYDSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 167.0,\n          \"data_first_seen\": \"2018-10-24T18:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DCWL_DENMARK\",\n      \"name\": \"Denmark\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"DCWL_DENMARK_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.44,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DEVILS_G\",\n      \"name\": \"Devils Gate\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Devils Gate Power Station is a conventional hydroelectric power station located in north-western Tasmania, Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DEVILS_G\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 60.0,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DIAPURWF\",\n      \"name\": \"Diapur 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The wind farm has an output of up to 7.4 MW and connected to the existing 22 kV electricity network via the Nhill substation in Western Victoria. The two Vestas V150 4.0 MW turbines have 125m hub height (tip height 200m) and produce the equivalent energy usage of around 6000 households.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DIAPURWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 8.0,\n          \"data_first_seen\": \"2021-11-25T17:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DRYCGT\",\n      \"name\": \"Dry Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Dry Creek Power Station is a power station at Dry Creek in the northern suburbs of Adelaide, South Australia. It is owned and operated by Synergen Power, a joint venture of Engie and Mitsui. The power station has three open cycle gas turbines, each rated at 52MW. It was commissioned in 1973\\u20131974 by the Electricity Trust of South Australia.As well as peaking electricity generation, the power station also provides ancillary services to support electricity grid stability. Dry Creek Power Station was established around 1978. It receives gas from the Moomba Adelaide Pipeline System. In 2018, the operators of Dry Creek Power Station were fined A$60,000 for failing to respond to instructions from AEMO during a blackout caused by faults elsewhere in the network.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DRYCGT1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 52.0,\n          \"emissions_factor_co2\": 0.8592,\n          \"data_first_seen\": \"1998-12-08T08:15:00+10:00\",\n          \"data_last_seen\": \"2025-06-27T20:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"DRYCGT2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 52.0,\n          \"emissions_factor_co2\": 0.8592,\n          \"data_first_seen\": \"1998-12-10T17:45:00+10:00\",\n          \"data_last_seen\": \"2025-06-27T20:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"DRYCGT3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 52.0,\n          \"emissions_factor_co2\": 0.8592,\n          \"data_first_seen\": \"1998-12-10T17:45:00+10:00\",\n          \"data_last_seen\": \"2025-06-27T20:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DULAWF\",\n      \"name\": \"Dulacca\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Dulacca Wind Farm is located between the communities of Dulacca and Drillham in the Western Downs Region of Queensland. Construction of Wind Farm commenced in October 2021 and is expected to be completed by Q3 2023.\\u200b</p>\",\n      \"units\": [\n        {\n          \"code\": \"DULAWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 180.0,\n          \"data_first_seen\": \"2023-04-13T11:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"DUNDWF\",\n      \"name\": \"Dundonnell\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Dundonnell Wind Farm is at Dundonnell, 23 kilometres (14 mi) northeast of Mortlake in the Australian state of Victoria. Construction began in January 2019 and was completed in 2020 with 80 Vestas wind turbines with a capacity to generate 336MW of electricity. The drive trains and hubs were assembled at the former Ford Australia site in Geelong.The wind farm is the largest in Victoria, soon to be overtaken by Stockyard Hill. It has contracts to supply 37% of its output to the government of Victoria and 50% to Snowy Hydro. It is being developed by Tilt Renewables. The wind farm connects to the grid via 38 kilometres of 220kV overhead transmission line to a substation near the Mortlake Power Station.A 327 tonne transformer transported at night took four nights to reach Dundonnell from Glen Waverley in eastern Melbourne in August 2019. It was manufactured there by the Wilson Transformer Company. The developer spent $80 million to connect the wind farm to the main 500 kV grid via a 38 km 220 kV Ausnet line, avoiding the connection problems many other generating stations have in the interior. Full commissioning was delayed in mid-2020 due to concerns of the Australian Energy Market Operator (AEMO), despite it being commissioned according to a plan negotiated with AEMO in 2018.</p>\",\n      \"units\": [\n        {\n          \"code\": \"DUNDWF3\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 121.0,\n          \"data_first_seen\": \"2020-03-11T13:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"DUNDWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 168.0,\n          \"data_first_seen\": \"2020-04-30T18:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"DUNDWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 46.0,\n          \"data_first_seen\": \"2020-03-11T17:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PMATTAEP\",\n      \"name\": \"Earthpower\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"PMATTAEP\",\n          \"fueltech_id\": \"gas_recip\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 4.0,\n          \"emissions_factor_co2\": 0.22,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"EASTCRK\",\n      \"name\": \"Eastern Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"EASTCRK\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.0,\n          \"emissions_factor_co2\": 0.0719,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"EASTCRK2\",\n      \"name\": \"Eastern Creek 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>This facility is owned and operated by LMS in partnership with Waste Assets Management Corporation and has an installed capacity of 4.5MW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"EASTCRK2\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 8.98,\n          \"emissions_factor_co2\": 0.0716,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"EDENVSF\",\n      \"name\": \"Edenvale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Edenvale Solar Park project (the Project) is a 204 megawatt solar farm under construction in the Western Downs region of Queensland.</p>\",\n      \"units\": [\n        {\n          \"code\": \"EDENVSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 180.0,\n          \"data_first_seen\": \"2023-02-18T13:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"EILDON\",\n      \"name\": \"Eildon\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Eildon Dam or Eildon Weir, a rock and earth-fill embankment dam with a controlled spillway across the Goulburn River, is located between the regional towns of Mansfield and Eildon within Lake Eildon National Park, in the Alpine region of Victoria, Australia. The dam&#x27;s purpose is for the supply of potable water, irrigation, and the generation of hydroelectricity. The impounded reservoir is called Lake Eildon.</p>\",\n      \"units\": [\n        {\n          \"code\": \"EILDON2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 60.0,\n          \"data_first_seen\": \"1998-12-07T06:40:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"EILDON1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 60.0,\n          \"data_first_seen\": \"1998-12-07T06:40:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"EILDONPD\",\n      \"name\": \"Eildon\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Eildon Pondage Power Station is a hydroelectric power station on the Eildon Pondage at Lake Eildon, Victoria, Australia. Eildon Pondage has one turbo generator, with a total generating capacity of 4.5 megawatts (6,000 hp) of electricity. It is owned and operated by Pacific Hydro, and the electricity produced is sold to electricity retailer TXU.Eildon Pondage re-uses the water from Eildon Power Station, which is stored in the pondage to ensure a controlled release into the Goulburn River downstream from Lake Eildon.</p>\",\n      \"units\": [\n        {\n          \"code\": \"EILDON3\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.5,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ELAINEWF\",\n      \"name\": \"Elaine\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Lal Lal Wind Farms, which consists of the adjacent Yendon and Elaine sites, are located approximately 10km southeast of Ballarat, Victoria in the area originally inhabited by the Wathaurong people and consist of 60 x 3.8MW turbines in total.</p><p>Elaine Wind Farm comprises 22 wind turbines and connects to the 220kV network via the Elaine Terminal Station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ELAINWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 83.6,\n          \"data_first_seen\": \"2020-04-07T04:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"EMERASF\",\n      \"name\": \"Emerald\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Emerald Solar Park is a photovoltaic solar power station near Emerald in Queensland, Australia. It was developed by RES Australia who then sold it to Lighthouse Solar Fund. It delivers up to 72 MW AC of electricity to the National Electricity Market. The entire production of the solar farm is contracted to be supplied to Telstra.</p>\",\n      \"units\": [\n        {\n          \"code\": \"EMERASF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 88.0,\n          \"data_first_seen\": \"2018-09-20T13:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"EDWFMAN\",\n      \"name\": \"Emu Downs\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Emu Downs Solar Farm is a solar farm adjacent to Emu Downs Wind Farm in Western Australia, Australia. It was developed and is owned by APA Group. At the time of its completion in 2018, it was the largest solar farm in Western Australia.When APA group bought Emu Downs Wind Farm in June 2011, it realised that there is usually a drop in output in the middle of the day as the wind changes from easterly in the morning to the westerly Fremantle Doctor in the afternoon. To balance that and achieve better utilisation of transmission infrastructure, APA installed a 20MW solar farm on an adjacent site. The solar farm&#x27;s peak output is during the time when the wind farm is not at full capacity, so no additional capacity was needed in the substation or grid connection point. The solar farm has 75,000 photovoltaic solar panels on a 70-hectare site east of the wind farm. It cost A$50 million (including a federal government grant of A$5.5 million) and began operation in December 2017. The output of both the solar and wind farms is contracted to Synergy until 2030.</p>\",\n      \"units\": [\n        {\n          \"code\": \"EDWFMAN_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 79.2,\n          \"data_first_seen\": \"2013-12-17T09:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ENERGYB\",\n      \"name\": \"Energy Brix\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Energy Brix Power Station was a brown coal\\u2013fired thermal power station located at Morwell, in Victoria, Australia. The power station was used to supply electricity for the retail market, as well as the production of briquettes in the adjacent Energy Brix briquette works. It was shut down in August 2014 and is currently the earliest surviving large-scale power station designed to provide electricity to the state electricity network.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MOR3\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 75.0,\n          \"emissions_factor_co2\": 1.6487,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2015-01-06T15:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MOR1\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 90.0,\n          \"emissions_factor_co2\": 1.6487,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2015-07-27T03:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MOR2\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 1.6487,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2014-09-04T11:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ERARING\",\n      \"name\": \"Eraring\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Eraring Power Station is a coal fired electricity power station with four 720 MW Toshiba steam driven turbo-alternators for a combined capacity of 2,880 MW. The station is located near the township of Dora Creek, on the western shore of Lake Macquarie, New South Wales, Australia and is owned and operated by Origin Energy.  It is Australia&#x27;s largest power station. The plant has two smokestacks rising 200 m (656 ft) in height.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ER01\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 720.0,\n          \"emissions_factor_co2\": 0.892,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ER02\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 720.0,\n          \"emissions_factor_co2\": 0.892,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ER03\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 720.0,\n          \"emissions_factor_co2\": 0.892,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ER04\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 720.0,\n          \"emissions_factor_co2\": 0.892,\n          \"data_first_seen\": \"1998-12-07T09:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ERB\",\n      \"name\": \"Eraring\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Eraring BESS will support further renewable project development by charging during the day when renewable energy sources like solar generation is plentiful and discharging into the grid during peak periods.</p><p>Locating a battery at Eraring also takes advantage of the existing transmission infrastructure, minimising the need for construction of long transmission lines.</p><p>All three stages of the Eraring BESS are now under construction. Stage one and three have a capacity of 460MW with a dispatch duration of four hours and are scheduled to come online in the final quarter of 2025. The second stage of the battery is scheduled to come online in the first quarter of 2027, adding a further 240MW with a dispatch duration of four hours.</p><p>The combined energy storage of all stages of the battery will be 2.8 GWh, enabling Origin to help keep the grid stable and support more variable renewable energy coming into the system.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ERBG01\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 614.6,\n          \"data_first_seen\": \"2025-03-13T09:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T14:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ERBL01\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 614.6,\n          \"data_first_seen\": \"2025-03-08T04:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T16:05:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ERGT01\",\n      \"name\": \"Eraring\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"Eraring Power Station is a coal fired electricity power station with four 720 MW Toshiba steam driven turbo-alternators for a combined capacity of 2,880 MW. The station is located near the township of Dora Creek, on the western shore of Lake Macquarie, New South Wales, Australia and is owned and operated by Origin Energy.  It is Australia's largest power station. The plant has two smokestacks rising 200 m (656 ft) in height.\",\n      \"units\": [\n        {\n          \"code\": \"ERGT01\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 41.5,\n          \"emissions_factor_co2\": 0.706,\n          \"data_first_seen\": \"2013-05-28T08:00:00+10:00\",\n          \"data_last_seen\": \"2024-12-17T20:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0ERB2\",\n      \"name\": \"Eraring 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Eraring BESS will support further renewable project development by charging during the day when renewable energy sources like solar generation is plentiful and discharging into the grid during peak periods.</p><p>Locating a battery at Eraring also takes advantage of the existing transmission infrastructure, minimising the need for construction of long transmission lines.</p><p>All three stages of the Eraring BESS are now under construction. Stage one and three have a capacity of 460MW with a dispatch duration of four hours and are scheduled to come online in the final quarter of 2025. The second stage of the battery is scheduled to come online in the first quarter of 2027, adding a further 240MW with a dispatch duration of four hours.</p><p>The combined energy storage of all stages of the battery will be 2.8 GWh, enabling Origin to help keep the grid stable and support more variable renewable energy coming into the system.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0ERB2L1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 240.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0ERB2G1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 240.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"FWF\",\n      \"name\": \"Ferguson\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Ferguson Wind Farm has an output of 10.8 MW and is connected to the existing 22 kV electricity network in the southwest Victoria via two separate connection points (Ferguson North 3.6 MW and Ferguson South 7.2 MW). It consists of three Vestas V136 4.0 MW turbines that have a rotor diameter of 136m, a tip height of 200m and together produce the equivalent energy usage of around 7,500 households.</p>\",\n      \"units\": [\n        {\n          \"code\": \"FNWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"FSWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 8.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"FINLEYSF\",\n      \"name\": \"Finley\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Finley Solar Farm is a photovoltaic power station near Finley in New South Wales, Australia. It was developed at a cost of A$170 million by ESCO Pacific in 2019 and built and commissioned by Signal Energy Australia Pty Ltd. ESCO sold the project to John Laing Group on 12 November 2018 at the same time as Westpac and ANZ Banks committed to the debt funding for the development.The solar farm has a seven-year power purchase agreement to supply electricity to Bluescope Steel.</p>\",\n      \"units\": [\n        {\n          \"code\": \"FINLYSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 162.36,\n          \"data_first_seen\": \"2019-08-02T09:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"FISHER\",\n      \"name\": \"Fisher\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Water from Lake Mackenzie flows through canals, tunnels and pipes to the Fisher Power Station. The water drops 650 metres to Fisher then runs into Lake Parangana.</p>\",\n      \"units\": [\n        {\n          \"code\": \"FISHER\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 43.2,\n          \"data_first_seen\": \"2005-05-16T20:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"FLATROCKS\",\n      \"name\": \"Flat Rocks\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Flat Rocks Wind Farm Stage 1 Project will consist of the construction and operation of\\u00a018\\u00a0wind turbines \\u00a0and the related civil and electrical infrastructure. The project site spans the shires of Kojonup and Broomehill-Tambellup, in the\\u00a0Great Southern Region\\u00a0of Western\\u00a0Australia. Construction of the project commenced in 2022 and it\\u2019s anticipated for the project to be fully operational in 2024.</p><p>The construction of the Flat Rocks\\u00a0Wind Farm\\u00a0Stage 1 has an investment value of over $200 million. The estimated construction timeframe for the plant is expected to be approximately 18 months while the plant&#x27;s operational life is estimated at approximately 30 years.</p>\",\n      \"units\": [\n        {\n          \"code\": \"FLATROCKS_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 75.6,\n          \"data_first_seen\": \"2023-11-26T12:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"FLYCRKWF\",\n      \"name\": \"Flyers Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Flyers Creek Wind Farm is a 145-Megawatt project owned by Iberdrola Australia. The wind farm site is located approximately 20 kilometres south of Orange in the Blayney and Cabonne Local Government Areas in the Central West region of New South Wales.</p>\",\n      \"units\": [\n        {\n          \"code\": \"FLYCRKWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 145.0,\n          \"data_first_seen\": \"2023-09-20T11:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0FULHAMSF\",\n      \"name\": \"Fulham\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Fulham Project is a proposed solar farm of 80 megawatts (enough to power around 25,000 homes) with battery storage of up to 120 megawatt hours to be located on 400 acres of farmland adjacent to the north west corner of the Hopkins Road and McLarens Road intersection, Fulham (within the Wellington Shire). The solar farm is planned to co-exist with existing grazing activities on the site.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0FULHAMSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 80.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0FULHAML1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 64.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0FULHAMG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 64.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GANGARR\",\n      \"name\": \"Gangarri\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The 120MW solar farm is located in Woleebee, not far from the town of Wandoan in the Western Downs region of Queensland and is being built on land owned by Shell\\u2019s QGC business. The project is expected to be completed in early 2021.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GANGARR1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 162.0,\n          \"data_first_seen\": \"2021-09-21T11:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GANNBESS\",\n      \"name\": \"Gannawarra\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Gannawarra Energy Storage System (GESS) is a grid-connected energy storage system adjacent to the Gannawarra Solar Farm in Wandella in the Shire of Gannawarra, 14km west of Kerang.<br/>The Gannawarra Energy Storage System was partially funded by grants from the Australian Renewable Energy Agency and the Victorian Government. It is owned by Wirsol and Edify Energy and operated by EnergyAustralia. The batteries were provided by Tesla, Inc. and Engineering, procurement and construction was provided by RCR Tomlinson. It helps to ease the demand on a constrained transmission line and balances higher levels of renewable energy on the grid. It first exported electricity to the grid in October 2018.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GANNBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"data_first_seen\": \"2018-11-08T00:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"GANNBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"data_first_seen\": \"2018-11-08T00:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GANNSF\",\n      \"name\": \"Gannawarra\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Gannawarra Solar Farm is a photovoltaic solar power station in the Gannawarra Shire, 13 kilometres (8.1\\u00a0mi) west of Kerang in the Australian state of Victoria. It generates up to 60\\u00a0MWdc electricity and exports up to 50.61\\u00a0MWAC to the National Electricity Market at 66\\u00a0kV.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GANNSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 55.0,\n          \"data_first_seen\": \"2018-04-06T12:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GEORGTWN\",\n      \"name\": \"George Town\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Tempo</p><p>Tempo</p>\",\n      \"units\": [\n        {\n          \"code\": \"GEORGTN2\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 17.0,\n          \"emissions_factor_co2\": 0.972,\n          \"data_first_seen\": \"2016-03-28T17:40:00+10:00\",\n          \"data_last_seen\": \"2016-05-01T08:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GEORGTN1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 17.0,\n          \"emissions_factor_co2\": 0.972,\n          \"data_first_seen\": \"2016-03-30T17:15:00+10:00\",\n          \"data_last_seen\": \"2016-05-01T08:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TESLA_GERALDTON\",\n      \"name\": \"Geraldton\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Commissioned in 2012, Geraldton is located immediately adjacent to the Geraldton Airport.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TESLA_GERALDTON_G1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"emissions_factor_co2\": 0.97,\n          \"data_first_seen\": \"2013-12-19T08:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GERMCRK\",\n      \"name\": \"German Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p><p></p><p>The power station consists of sixteen 2MW power generation modules using Caterpillar 3520C generator sets and four 3.3MW power generating modules using Jenbacher J620 generator sets.</p><p></p>\",\n      \"units\": [\n        {\n          \"code\": \"GERMCRK\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 45.0,\n          \"emissions_factor_co2\": 0.5657,\n          \"data_first_seen\": \"2013-07-18T10:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GIRGSF\",\n      \"name\": \"Girgarre\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Girgarre Solar Farm Project will consist of the construction and operation of approximately 169,500 photovoltaic (PV)\\u00a0modules and the related civil and electrical infrastructure. The Project is in the Shire of Campaspe, in Victoria, Australia. The site is located approximately 10 km north-west of Stanhope and approximately 50km west of Shepparton.</p><p>The construction of the Girgarre Solar Farm has an investment value of over $140 million. The estimated construction timeframe for the plant is expected to be approximately 18 months, while the plant&#x27;s operational life is estimated at approximately 35 years.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GIRGSF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 93.31,\n          \"data_first_seen\": \"2024-07-20T10:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GSTONE\",\n      \"name\": \"Gladstone\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Gladstone Power Station is a power station at Callemondah, Gladstone, Queensland, Australia. It is Queensland&#x27;s largest power station, with six coal powered steam turbines generating a maximum of 1,680 MW of electricity. Power from the station was first generated in 1976.<br/>This fossil fuel power plant draws seawater for cooling. Black coal is brought by rail from the Curragh coal mine, 200 kilometres (120 mi) west of Rockhampton.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GSTONE5\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 280.0,\n          \"emissions_factor_co2\": 0.9758,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GSTONE6\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 280.0,\n          \"emissions_factor_co2\": 0.9758,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-19T00:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GSTONE3\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 280.0,\n          \"emissions_factor_co2\": 0.9758,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GSTONE4\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 280.0,\n          \"emissions_factor_co2\": 0.9758,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GSTONE2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 280.0,\n          \"emissions_factor_co2\": 0.9758,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GSTONE1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 280.0,\n          \"emissions_factor_co2\": 0.9758,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-04-22T17:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GLBWNHYD\",\n      \"name\": \"Glenbawn\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Glenbawn Power Station was built in 1995 within the Glenbawn Dam wall structure on the Hunter River about 15 kilometres south-east of Scone in New South Wales and has a maximum generation capacity of 5.5 MW. Glenbawn power station typically generates power using summer irrigation and flood mitigation flows.<br/><br/>Glenbawn Dam&#x27;s storage capacity is approximately 750 GL with only small demands from other uses, enabling water releases for the power station on a regular basis.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GLBWNHYD\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.5,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0GLENELLEN\",\n      \"name\": \"Glenellen\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Glenellen project will have an installed capacity of 260 MWp and will be located in Greater Hume (New South Wales). The plant will generate energy with its 370,000 solar modules. The project is currently in the development phase, and commercial operations are scheduled to begin in 2025.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0GLENELLEN\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 260.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GLENMAGG\",\n      \"name\": \"Glenmaggie\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"GLENMAG1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 3.8,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GLENNCRK\",\n      \"name\": \"Glennies Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"GLENNCRK\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 12.78,\n          \"emissions_factor_co2\": 0.526,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GLENSF\",\n      \"name\": \"Glenrowan\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Glenrowan Solar Farm is a 130MWac solar project located 2km south-west of Glenrowan, in the Rural City of Wangaratta, approximately 230 kilometres north-east of Melbourne, Victoria.</p><p>The location sits within Victoria\\u2019s Central North Renewable Energy Zone (REZ), one of six across the state supporting the Victorian Government\\u2019s Renewable Energy Target (VRET) of 50% by 2030 and the transition to a carbon-neutral future.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GLENSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 126.0,\n          \"data_first_seen\": \"2023-11-21T09:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GLRWNSF\",\n      \"name\": \"Glenrowan West\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Glenrowan West Solar Farm will be a single axis tracking project, located just off the Hume Freeway, between Benalla and Wangaratta, 11km south-west of the town of Glenrowan in Victoria. The site is designed to have an installed capacity of approx. 149-megawatt peak (MWp) DC which covers 323 hectares of land and has commenced early stage construction as of February 2020.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GLRWNSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 132.0,\n          \"data_first_seen\": \"2020-12-22T07:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GPWFEST\",\n      \"name\": \"Golden Plains East\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Golden Plains Wind Farm \\u2013 East commenced construction in 2023. The project involves the establishment of the first stage of a wind energy facility including 122 wind turbines and associated electrical infrastructure to the west, south and south-west of Rokewood. Rokewood is a small rural town in the Shire of Golden Plains located approximately 60 km north-west of Geelong.\\u00a0</p>\",\n      \"units\": [\n        {\n          \"code\": \"GPWFEST3\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 248.0,\n          \"data_first_seen\": \"2025-05-30T10:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GPWFEST2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 260.4,\n          \"data_first_seen\": \"2024-08-21T11:45:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GPWFEST1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 248.0,\n          \"data_first_seen\": \"2024-09-18T14:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0GPWFWST\",\n      \"name\": \"Golden Plains West\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Golden Plains Wind Farm \\u2013 West involves the establishment of the second stage of a wind energy facility including wind turbines and associated electrical infrastructure to the west, south and south-west of\\u00a0Rokewood, a small rural town in the Shire of Golden Plains, approximately 60 km north-west of Geelong</p>\",\n      \"units\": [\n        {\n          \"code\": \"0GPWFWST1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 557.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GOONUMSF\",\n      \"name\": \"Goonumbla\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Goonumbla Solar Farm is a 83.70 MW dc PV plant located approximately 10km west of the town of Parkes and 280km North West of Sydney in New South Wales.</p><p>The plant consists of approximately 270,000 solar panels installed across the 385-hectare site.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GOONSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 85.0,\n          \"data_first_seen\": \"2020-05-12T13:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0GOORESF\",\n      \"name\": \"Goorambat\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Goorambat East Solar Farm is a renewable energy development located about 12 kilometres north of Benalla and just south of the Goorambat township in Victoria, on the land of the Yorta Yorta people.</p><p>ENGIE entered into a commercial arrangement with Neoen to purchase the project in 2023 and have been progressing steadily towards construction.</p><p>The site is approximately 630 hectares across five private rural properties in the Benalla Rural City Council local government area and is primarily accessible from the Goorambat-Chesney Road, Spinks Lane and Saunders Road.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0GOORESF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GORDON\",\n      \"name\": \"Gordon\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Gordon Power Station is the largest conventional hydroelectric power station in Tasmania, Australia; located in the South West region of the state. The power station is situated on  Gordon River. Water from  Lake Gordon descends 183 metres (600 ft) underground past the Gordon Dam and into the power station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GOVILLB1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GORDON\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 432.0,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GOSNELLS\",\n      \"name\": \"Gosnells\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"GOSNELLS\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.057,\n          \"data_first_seen\": \"2006-11-17T00:00:00+10:00\",\n          \"data_last_seen\": \"2023-03-19T23:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0GRIVSF\",\n      \"name\": \"Goulburn River\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Goulburn River project consists of a 585 MWp solar farm and battery energy storage system (BESS), located between Wollar and Merriwa, on Wollara Road, in the Upper Hunter Region of NSW.</p><p>Lightsource bp will construct and operate the project and deliver renewable energy to Australia\\u2019s grid. The project includes a battery to shift renewable energy to night-time peaks and support the reliable operation of Australia\\u2019s grid. The project will also include operation and maintenance buildings, a temporary onsite workers accommodation camp, and electrical infrastructure required to connect to the existing electricity network.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0GRIVSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 588.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GSWF\",\n      \"name\": \"Goyder South\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Goyder South Wind Farm is the first stage of the Goyder Renewables Zone development near Burra, South Australia. The Goyder South Wind Farm will be on the hills south-east of the town of Burra.<br/><br/>Early construction works for stage 1 began in December 2021. The project is owned by Neoen and the construction contract was awarded to a consortium of GE Renewable Energy and Elecnor.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GSWF1B1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 203.5,\n          \"data_first_seen\": \"2024-11-13T09:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GSWF1A\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 209.0,\n          \"data_first_seen\": \"2024-04-04T14:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GRANGEAV\",\n      \"name\": \"Grange Avenue\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"GRANGEAV\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.0,\n          \"emissions_factor_co2\": 0.0774,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GRANWF\",\n      \"name\": \"Granville Harbour\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Granville Harbour Wind Farm is a wind farm project being developed and constructed by Palisade Investment Partners, on the west coast of Tasmania, Australia.  <br/>The facility first generated to the grid on 27th February 2020 with the completion of its first turbine. When finished, the wind farm will have 31 wind turbines and have a maximum capacity of 112 MW. It is located on a site 35 kilometres (22 mi) northwest of Zeehan, Tasmania.Considerations are underway for a second Bass Strait interconnector to increase Tasmania&#x27;s electricity export capacity.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GRANWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 110.0,\n          \"data_first_seen\": \"2020-01-28T12:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GRASMERE\",\n      \"name\": \"Grasmere\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Albany wind and Grasmere farms are two wind power stations near Albany, Western Australia, owned by Bright Energy Investments. They are adjacent and are often considered a single facility. They have 18 wind turbines, with a maximum generating capacity of 35.4\\u00a0MW of electricity. The original Albany Wind Farm was commissioned in October 2001, after ten years of planning. The wind farm has the capacity to produce 80 per cent of the electricity requirements of Albany.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GRASMERE_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 13.8,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GREENB\",\n      \"name\": \"Greenbank\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>CS Energy is developing a large-scale battery in Greenbank, a suburb within the Logan City Council area, to develop cleaner and more reliable energy for Queenslanders.<br/><br/>The Greenbank Battery will have a discharge capacity of 200 megawatts and store 400 megawatt hours of energy (200MW/400MWh) - enough to power 66,000 homes for two hours in the evening peak before needing to recharge.</p><p>It will use lithium iron phosphate (also known as lithium ferro phosphate [LFP], or LiFePO4) batteries, which are the safest lithium batteries currently available.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GREENB1L1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 259.2,\n          \"data_first_seen\": \"2025-02-11T21:50:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+08:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"GREENB1G1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 259.2,\n          \"data_first_seen\": \"2025-02-13T15:10:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GREENOUGH_RIVER\",\n      \"name\": \"Greenough River\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Greenough River Solar Farm is a 10 megawatt (MW) photovoltaic power station located in Walkaway, Western Australia. When it opened in October, 2012, it was the country&#x27;s first utility-scale solar farm. It remained Australia&#x27;s largest solar PV system until 2014, when it was superseded by the 20 MW Royalla solar farm in Canberra. The Greenough River Solar Farm was built by Verve Energy and joint venture partners GE Financial Services. It uses over 150,000 thin film modules based on CdTe-PV technology provided by U.S. company First Solar. Its exact location is at Nangetty Walkaway Road, Walkaway, 50 kilometres southeast of Geraldton and covers an area of 80 hectares (200 acres).The solar farm has been owned by Bright Energy investments since April 2018. It is currently undergoing and expansion to increase capacity by a further 30MW and RCR Tomlinson was awarded a $60 million engineering, construction and procurement contract for expansion, The expansion project is expected to be complete by mid 2019.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GREENOUGH_RIVER_PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 40.0,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-13T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GRIFSF\",\n      \"name\": \"Griffith\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Initial development started in 2013 with the land lease signed in November 2013. Government Planning Approvals was achieved in Jun 2016. Construction started in Jan 2017 and was completed in April 2018. It has been operational ever since.</p><p>Griffith Solar Farm is one of 12 successful projects that received funding from the Australian Renewable Energy Agency (ARENA) in 2016.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GRIFSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 27.2,\n          \"data_first_seen\": \"2018-04-20T15:35:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GROSV1\",\n      \"name\": \"Grosvenor 1\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Grosvenor Power Station, located in Moranbah, Queensland, is operated by EDL. It generates electricity by capturing and converting waste coal mine gas (methane), which is released during coal mining operations. This process not only provides reliable energy but also significantly reduces greenhouse gas emissions by repurposing what was once a waste product. The station has a capacity of 21.3 MW, powers around 22,800 homes annually, and avoids approximately 100,500 tonnes of CO2 emissions each year.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GROSV1\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"emissions_factor_co2\": 0.5563,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GROSV2\",\n      \"name\": \"Grosvenor 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>EDL negotiated gas supply and connection agreements with Anglo American to develop and build the 21 MW Grosvenor Power Station in 2015. These agreements were updated in 2017 to include a 15MW expansion at Grosvenor 2.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GROSV2\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 15.0,\n          \"emissions_factor_co2\": 0.5717,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GULLRGWF\",\n      \"name\": \"Gullen Range\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Gullen Range Wind Farm is a wind farm in the Southern Tablelands region of New South Wales, Australia. It consists of 73 wind turbines and produces up to 165.5MW of electricity. It is owned by BJCE Australia and built and operated by Goldwind Australia. Gullen Range was BJCE Australia&#x27;s first wind farm, when it bought the project in 2014.The wind farm consists of two different turbine models, both manufactured by Goldwind. There are 56 GRW100-2.5MW turbines with a 100m diameter on 80m towers (total height 130m) which generate 2.5MW of electricity. There are also 17 smaller GW82-1.5MW turbines with 82m diameter on 85m towers (total height 126m) which produce 1.5MW of electricity.The project was developed by Epuron, who sold it to Goldwind Australia before construction. Goldwind began construction in 2012. It began generating electricity in 2013 and was fully operational by 23 December 2014. Goldwind onsold 75% of the project to BJCE Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GULLRSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"data_first_seen\": \"2017-08-22T10:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T16:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"GULLRWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 165.0,\n          \"data_first_seen\": \"2013-12-10T18:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GNNDHSF\",\n      \"name\": \"Gunnedah\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Gunnedah Solar Farm, located near Gunnedah \\u2013 west of Tamworth in regional New South Wales. The 154MW Project will accommodate a large scale solar PV system utilising single-axis tracking, ground mounted panels which will generate energy throughout the day, when it is needed most. Single-axis tracking has been selected for this project to harness the highest amount of solar irradiance as the panels will track the sun\\u2019s movement east to west each day.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GNNDHSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 144.0,\n          \"data_first_seen\": \"2021-06-29T10:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"GUNNING\",\n      \"name\": \"Gunning\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Gunning Wind Farm project is a wind farm development in the Cullerin Range, north-east of Gunning, in New South Wales. Wind turbines in the farm are visible from the Hume Highway. <br/>The Gunning Wind Farm comprises an electrical substation and operation and maintenance facilities plus 31 turbines which send power to the substation via 17km of underground cabling.<br/>A 14km-long 132kV transmission line was constructed to connect the wind farm to the 132kV Yass-Goulburn transmission line. Turbines generate electricity at 12kV which travels via underground cables to the substation where it is stepped up to 132kV to match the grid voltage.<br/>Construction began in April 2010 and created about 100 jobs, bringing significant economic activity to the Gunning region. The wind farm was completed in May 2011.<br/>A great deal of work was done prior to development of the wind farm. Technical studies identified constraints and the best design, with independent consultants engaged to report on:<br/><br/>flora and fauna<br/>cultural heritage<br/>traffic and transport<br/>geology and hydrology<br/>landscape and visual amenity<br/>soundThe wind farm is capable of producing 46.5MW of clean, renewable energy.<br/>Each of the 1.5MW turbines at the Gunning Wind Farm can provide sufficient renewable energy to power approximately 750 homes and save more than 5,250 tonnes of greenhouse gas emissions a year.<br/>The 31 turbines can power 35,000 homes annually and save more than 162,750 tonnes of greenhouse gases a year.<br/>ACCIONA Energy [1] has established a Community Benefit Fund to deliver tangible benefits to the local community. This initiative will run for the life of the project (25 years).<br/>The Fund support services, events and projects which directly and indirectly benefit the community in the vicinity. <br/>ACCIONA Energy also provides sponsorship support to local groups and events.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GUNNING1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 46.5,\n          \"data_first_seen\": \"2011-04-05T10:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0GUNSYNDSF\",\n      \"name\": \"Gunsynd\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Located in South West Queensland near the township of Goondiwindi, Gunsynd Solar Farm will generate up to 94MW of electricity and 20MW of battery storage that will supply the full township of Goondiwindi and inject into the QLD/NSW electricity grid via the Powerlink Bulli Creek 330/132kV Substation.</p><p><br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"0GUNSYNDSF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 94.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNOWY3\",\n      \"name\": \"Guthega\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Guthega Power Station is located in the Snowy Mountains region of New South Wales, Australia. The power station&#x27;s purpose is for the generation of electricity. It is the first to be completed and smallest of the initial seven hydroelectric power stations that comprise the Snowy Mountains Scheme, a vast hydroelectricity and irrigation complex constructed in south-east Australia between 1949 and 1974 and now run by Snowy Hydro.This station is connected to the National Electricity Market via the TransGrid 330/132KV Substation @ the TransGrid 330KV Murray Switching Station, 1.56 kilometres (1.71 mi) South East of Khancoban.</p>\",\n      \"units\": [\n        {\n          \"code\": \"GUTHEGA\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 60.0,\n          \"data_first_seen\": \"2001-07-16T07:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SNOWY3\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"data_first_seen\": \"1998-12-07T04:15:00+10:00\",\n          \"data_last_seen\": \"2001-05-27T23:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HLMSEW01\",\n      \"name\": \"Hallam\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"HLMSEW01\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HALAMRD\",\n      \"name\": \"Hallam Road\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>This facility is owned and operated by LMS in partnership with SUEZ Recycling &amp; Recovery and has an installed capacity of 9.0MW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HALAMRD1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 9.0,\n          \"emissions_factor_co2\": 0.0717,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"AGLHAL\",\n      \"name\": \"Hallett\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Hallett Power Station is located in Canowie, in the Mid North of South Australia, located about 210 kilometres (130 mi) north of Adelaide. It was commissioned in 2001 and opened in 2002. It was built by AGL Energy, but was sold in 2007, and is currently operated by EnergyAustralia. It has capacity of approximately 200 megawatts (270,000 hp), and connects to the National Electricity Grid. It contains 12 gas turbine generators.The powerstation is fuelled by natural gas drawn from the Moomba Adelaide Pipeline System, and can also operate from a back-up supply of diesel in the event of a failure of the gas supply. It was built using second-hand gas turbines. These are all General Electric (GE) Frame 5 units, manufactured under licence by John Brown, AEG and Nuovo Pignone.</p>\",\n      \"units\": [\n        {\n          \"code\": \"AGLHAL\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 217.0,\n          \"emissions_factor_co2\": 0.729,\n          \"data_first_seen\": \"2002-01-03T15:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T19:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HALLWF\",\n      \"name\": \"Hallett 1\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Hallett 1 is a 45 turbine, 94.5MW operating wind farm, located approximately 180km north of Adelaide, South Australia. The wind farm has been operational since 2008 and its electricity and green outputs are contracted to AGL under a long-term offtake agreement</p>\",\n      \"units\": [\n        {\n          \"code\": \"HALLWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 95.0,\n          \"data_first_seen\": \"2007-12-19T05:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HALLWF2\",\n      \"name\": \"Hallett 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Hallett Hill Wind Farm, also known as Hallett 2 Wind Farm, was completed in late 2009. It consists of 34 Suzlon turbines each 2.1MW, giving an installed capacity of 71.4MW. Up to March 2011 it was averaging a capacity factor of 39%.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HALLWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 71.4,\n          \"data_first_seen\": \"2009-05-12T14:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HAMISF\",\n      \"name\": \"Hamilton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Hamilton Solar Farm is a solar farm at Collinsville in North Queensland, Australia. The power station can generate 69 megawatts of power. It is owned and operated by Gentari. The site covers 330 hectares. It is co-located with the WhitSunday Solar Farm and the Daydream Solar Farm.</p><p>Power from the station is bought by ERM.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HAMISF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 57.5,\n          \"data_first_seen\": \"2018-07-10T12:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HAMPTON\",\n      \"name\": \"Hampton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"HAMPTON\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.32,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HVWW\",\n      \"name\": \"Happy Valley\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"HVWWPV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 11.0,\n          \"data_first_seen\": \"2022-06-15T15:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T18:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HVWWBA1G\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.52,\n          \"data_first_seen\": \"2022-06-07T13:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HVWWBA1L\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.52,\n          \"data_first_seen\": \"2022-06-07T12:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:05:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HASTING\",\n      \"name\": \"Hastings\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Esso Australia and Woodside Energy, the other Gippsland Basin Joint Venture participant, are planning a project to install three small, modern, efficient ethane power generation units at the Long Island Point plant.<br/><br/>These will be capable of converting ethane into 35-40 megawatts of electricity to power Victorian homes, while ensuring we can maintain our reliable supply of natural gas and natural gas liquids across the east coast.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HASTINGS1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 14.82,\n          \"emissions_factor_co2\": 0.631,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HASTINGS2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 14.82,\n          \"emissions_factor_co2\": 0.631,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HASTINGS3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 14.82,\n          \"emissions_factor_co2\": 0.631,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HAUGHT1\",\n      \"name\": \"Haughton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Located in North Queensland\\u2019s Burdekin Shire (40km west of Ayr and 60km south of Townsville), Haughton Solar Farm is a large-scale solar photovoltaic power station. The solar farm is being built in stages with the first 100MW of the project opened in 2019. Once all stages are complete, Haughton Solar Farm is expected to have a generating capacity of up to 500MW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HAUGHT11\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 132.0,\n          \"data_first_seen\": \"2019-05-28T09:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HD1WF\",\n      \"name\": \"Hawkesdale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Hawkesdale Wind Farm site is located in South-Western Victoria near the township of Hawkesdale, 30km north-west of Warrnambool, and 175km west of Geelong, within the Moyne Shire Local Government Area.</p><p>The project covers an area of approximately 2,280 ha, where the current land use is primarily agricultural activities including grazing of sheep and cattle.</p><p>The windfarm comprises 23 turbines with a total output of approximately 97MW. It will connect to the grid via a 132kV overhead transmission circuit to the existing 500kV Tarrone Terminal Station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HD1WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 94.6,\n          \"data_first_seen\": \"2024-06-17T08:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HAYMSF\",\n      \"name\": \"Hayman\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>With a project value of approximately $70 million, the farm is operating as a merchant plant. Supported by Whitsunday Regional Council, the Hayman Solar Farm sits within a former coal mining hub, 10km northwest of Collinsville.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HAYMSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 57.75,\n          \"data_first_seen\": \"2019-01-12T10:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HAZEL\",\n      \"name\": \"Hazelwood\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Hazelwood Power Station is a decommissioned brown coal-fuelled thermal power station located in the Latrobe Valley of Victoria, Australia. Built between 1964 and 1971, the 1,600 megawatt capacity power station was made up of eight 200MW units, and supplied up to 25% of Victoria&#x27;s base load electricity and more than 5% of Australia&#x27;s total electricity demand. It was a &#x27;subcritical&#x27; pulverized coal-fired boiler. The station was listed as the least carbon efficient power station in the OECD in a 2005 report by WWF Australia, making it one of the most polluting power stations in the world. At 1.56 tonnes of CO2 for each megawatt hour of electricity, it was 50% more polluting than the average black coal power station in New South Wales or Queensland. Hazelwood emitted 14% of Victoria&#x27;s annual greenhouse gas emissions and 3% of Australia&#x27;s greenhouse gas emissions.<br/>International Power plc purchased Hazelwood Power Station and the adjoining mine from the Victorian Government in 1996 with an expected 40-year life. In 2005, the Bracks Labor Government approved an environmental effects statement (EES) that allowed Hazelwood to relocate a road and a section of the Morwell river to allow access to an additional 43 million tonnes of coal in addition to that allowed under the mining licence boundaries set at the time of privatisation. This was estimated to provide sufficient coal for the plant to operate to at least 2030 (prior to decommissioning plans). The EES also capped its expected total greenhouse output at 445 million tonnes of carbon dioxide over its life, after which Hazelwood may have been made to cease operation.<br/>Hazelwood was jointly owned by Engie (formerly GDF Suez), with a 72% share and Mitsui &amp; Co. with a 28% share. In 2014, Hazelwood employed 495 staff directly and on average 300 contractors. On 3 November 2016, Engie announced that the entire Hazelwood plant would be closed at the end of March 2017 giving five months notice of the closure. The power station closed in March 2017.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HWPS1\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 220.0,\n          \"emissions_factor_co2\": 1.558,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2017-03-29T17:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HWPS2\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 220.0,\n          \"emissions_factor_co2\": 1.558,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2017-03-28T00:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HWPS3\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 1.558,\n          \"data_first_seen\": \"1998-12-29T17:30:00+10:00\",\n          \"data_last_seen\": \"2017-03-29T11:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HWPS4\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 1.558,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2017-03-27T16:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HWPS5\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 1.558,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2017-03-28T18:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HWPS6\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 1.558,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2017-03-27T11:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HWPS7\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 1.558,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2017-03-28T10:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HWPS8\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 1.558,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2017-03-27T02:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HBESS\",\n      \"name\": \"Hazelwood BESS\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Hazelwood Battery Energy Storage System (HBESS) is a 150MW/150MWh utility-scale battery that will help deliver further electricity grid stability for Victoria. It has the capacity to store the energy equivalent of an hour of energy generation from the rooftop solar systems of 30,000 Victorian homes</p>\",\n      \"units\": [\n        {\n          \"code\": \"HBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 200.0,\n          \"data_first_seen\": \"2023-03-11T00:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"HBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 200.0,\n          \"data_first_seen\": \"2023-03-10T12:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HENDERSON_RENEWABLE\",\n      \"name\": \"Henderson\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"HENDERSON_RENEWABLE_IG1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 3.0,\n          \"emissions_factor_co2\": 0.065,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HEPWIND\",\n      \"name\": \"Hepburn\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Hepburn Wind Project is a wind farm built and owned by Hepburn Wind, a community co-operative, and supported by the Victorian Government. The location of the project is Leonards Hill, 10 kilometres (6.2 mi) south of Daylesford, Victoria, north-west of Melbourne, Victoria.  It comprises two individual 2.05 MW wind turbines supplied by REpower System AG which are projected to produce enough energy for 2,300 households, almost as many houses are in the twin-towns of Daylesford and Hepburn Springs.The project is the first community-owned wind farm in Australia. The initiative emerged because the community felt that the state and federal governments were not doing enough to address climate change. Hepburn Wind is the first project of the Hepburn Renewable Energy Association, now known as SHARE.<br/>Hepburn Wind Project formally launched their share offer on 25 July 2008, and as of June 2011 over 1700 members had subscribed a total of $9.0 million. The project has secured over $13.1 million in funding with the additional funds being bank debt and Government grants. Shares have been issued with priority to the local residents of Daylesford and Hepburn Springs.<br/>As the project is under 30 MW, it was assessed under the local planning guidelines administered through the Hepburn Shire Council. The planning permit was issued by Hepburn Shire in February 2007. The council received 325 submissions in support of the proposal and 18 objections.<br/>The permit was subsequently challenged unsuccessfully at the Victorian Civil and Administrative Tribunal (VCAT) in June 2007.On 28 April 2010 the project signed a contract with REpower Systems for the turnkey construction of the wind farm. The official ground breaking ceremony was held on 8 October 2010 and was officiated by the Hon Gavin Jennings, the Victorian Minister for the Environment at the time.<br/>Construction began in November 2010. The turbines left Germany on 5 December 2010 on the SE Panthea and arrived in Melbourne on 22 February 2011.<br/>A community picnic day was held to view and celebrate the erection of the first turbine on Saturday, 19 April 2011.<br/>The wind farm began generating power into the local electricity network on Wednesday, 22 June 2011.Community-owned wind farms are common in Denmark and Germany, which have high levels of wind power use. Community wind projects are also emerging in Canada, the Netherlands, the United Kingdom and the United States.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HEPWIND1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.1,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HIGHBRY\",\n      \"name\": \"Highbury\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"HIGHBRY1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 2.0,\n          \"emissions_factor_co2\": 0.0576,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HILLSTN\",\n      \"name\": \"Hillston Sun\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Hillston Sun Farm (\\u201cHillston\\u201d) is a 119MWdc solar photovoltaic development located 3.5km south of the township of Hillston in south west New South Wales. The solar farm will power the equivalent of 48,000 homes each year.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HILLSTN1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 110.0,\n          \"data_first_seen\": \"2021-10-05T13:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HORNSDAL\",\n      \"name\": \"Hornsdale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Hornsdale Wind Farm is an electricity generator in the locality of Hornsdale in the south-west of the Narien Range, north of Jamestown, South Australia. It consists of 99 wind turbines with a generation capacity of  315 megawatts. Stage 1 specifically is 32 of these 99 turbines, for a total of 102MW. The plant is owned and operated by Neoen, a French renewable energy company.<br/>The electricity generated by Hornsdale Wind Farm is contracted to be supplied to the Australian Capital Territory.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HDWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 102.4,\n          \"data_first_seen\": \"2016-06-23T16:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HORNSDAL2\",\n      \"name\": \"Hornsdale 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Hornsdale Wind Farm is an electricity generator in the locality of Hornsdale in the south-west of the Narien Range, north of Jamestown, South Australia. It consists of 99 wind turbines with a generation capacity of  315 megawatts. Stage 2 specifically is 32 of these 99 turbines, for a total of 102MW. The plant is owned and operated by Neoen, a French renewable energy company.<br/>The electricity generated by Hornsdale Wind Farm is contracted to be supplied to the Australian Capital Territory.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HDWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 102.4,\n          \"data_first_seen\": \"2017-02-21T15:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HORNSDAL3\",\n      \"name\": \"Hornsdale 3\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Hornsdale Wind Farm is an electricity generator in the locality of Hornsdale in the south-west of the Narien Range, north of Jamestown, South Australia. It consists of 99 wind turbines with a generation capacity of 315 megawatts. Stage 3 specifically is 35 of these 99 turbines, for a total of 112MW. The plant is owned and operated by Neoen, a French renewable energy company.<br/><br/>The electricity generated by Hornsdale Wind Farm is contracted to be supplied to the Australian Capital Territory.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HDWF3\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 112.0,\n          \"data_first_seen\": \"2017-08-18T07:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HORNSDPR\",\n      \"name\": \"Hornsdale Power Reserve\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Hornsdale Power Reserve is a 150MW/194MWh grid-connected energy storage system co-located with the Hornsdale Wind Farm in the Mid North region of South Australia.<br/>Between 2017 and 2020, it was the largest lithium-ion battery in the world.<br/><br/>During 2017 Tesla, Inc. won the contract and built the Hornsdale Power Reserve, for a capital cost of A$90 million, leading to the colloquial Tesla big battery name.In November 2019, Neoen confirmed that it was increasing capacity by a further 50MW/64.5MWh to a combined 185 MWh. The increased storage capacity was installed by March 23, 2020, and the increased power became operational in early September 2020.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HPRG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 150.0,\n          \"data_first_seen\": \"2017-11-25T17:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HPRL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 150.0,\n          \"data_first_seen\": \"2017-11-24T11:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:40:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0HORSHAMSF\",\n      \"name\": \"Horsham\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The SEC Renewable Energy Park is a 100% publicly owned utility-scale renewable energy project in Victoria\\u2019s west, near Horsham.<br/><br/>The SEC is working with developer OX2 to build the energy park in two stages, starting with a 119-megawatt solar farm comprising more than 212,000 PV solar panels.</p><p>The SEC\\u2019s $370 million investment allowed work on the solar farm to begin immediately while supporting the addition of a 100-megawatt two-hour battery storage system \\u2013 making it one of Australia\\u2019s first integrated solar and BESS projects with a single connection point.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0HORSHAML1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0HORSHAMG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0HORSHAMSF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 118.8,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HUGSF\",\n      \"name\": \"Hughenden\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Hughenden Solar Farm is a solar farm at Hughenden in North West Queensland, Australia. The power station was constructed by BayWa, beginning in 2017. Construction was completed in 2018. Lighthouse Infrastructure bought the solar farm from Baywa who continue to operate and manage the plant.<br/><br/>The power station can generate 20.16 megawatts.<br/><br/>CS Energy has signed a Power Purchase Agreement with Hughenden Solar Farm.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HUGSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 20.97,\n          \"data_first_seen\": \"2018-01-25T01:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HUMENSW\",\n      \"name\": \"Hume\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Hume Power Station is a 58 megawatts (78,000\\u00a0hp) hydro-electric power station installed in the dam wall, and is primarily used for peak-load generation. The station has an average annual output of 220 gigawatt-hours (790\\u00a0TJ). The power station has two 29 megawatts (39,000\\u00a0hp) turbines and is operated by Meridian Energy.</p><p>The power station was completed in 1957, running two 25 megawatts (34,000\\u00a0hp) turbines. In 2000, these turbines were each upgraded to 29 megawatts (39,000\\u00a0hp).</p>\",\n      \"units\": [\n        {\n          \"code\": \"HUMENSW\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 29.0,\n          \"data_first_seen\": \"1998-12-09T05:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-09T10:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HUMEV\",\n      \"name\": \"Hume\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Hume Power Station is a 58 megawatts (78,000\\u00a0hp) hydro-electric power station installed in the dam wall, and is primarily used for peak-load generation. The station has an average annual output of 220 gigawatt-hours (790\\u00a0TJ). The power station has two 29 megawatts (39,000\\u00a0hp) turbines and is operated by Meridian Energy.</p><p>The power station was completed in 1957, running two 25 megawatts (34,000\\u00a0hp) turbines. In 2000, these turbines were each upgraded to 29 megawatts (39,000\\u00a0hp).</p>\",\n      \"units\": [\n        {\n          \"code\": \"HUMEV\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 29.0,\n          \"data_first_seen\": \"1998-12-09T05:25:00+10:00\",\n          \"data_last_seen\": \"2025-03-13T09:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HUNTER\",\n      \"name\": \"Hunter\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The power station will comprise two heavy-duty, open cycle gas turbines (OCGT) and are the latest and most efficient turbines that the world\\u2019s best manufacturers can offer for the site.</p><p>The OCGTs will operate on natural gas and will be hydrogen-ready. Diesel is available on-site as a backup for the extreme and rare cases where the NSW power grid needs it to keep the lights on. Over the power station\\u2019s life, diesel usage is negligible.</p><p>It is expected that OCGTs will be capable of initially running on up to 15% hydrogen. With some additional investment, we expect they will be capable of up to 30% hydrogen. The ability to run on hydrogen is dependent on the balance of plant modifications and the availability of green hydrogen.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HUNTER1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 375.0,\n          \"emissions_factor_co2\": 0.581,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HUNTER2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 375.0,\n          \"emissions_factor_co2\": 0.581,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HEZ\",\n      \"name\": \"Hunter Economic Zone\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The power station will comprise two heavy-duty, open cycle gas turbines (OCGT) and are the latest and most efficient turbines that the world\\u2019s best manufacturers can offer for the site. The OCGTs will operate on natural gas and will be hydrogen-ready. Diesel is available on-site as back-up for the extreme and rare cases where the NSW power grid needs it to keep the lights on. Over the power station\\u2019s life, diesel usage is negligible.</p>\",\n      \"units\": [\n        {\n          \"code\": \"HEZ1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 28.0,\n          \"emissions_factor_co2\": 0.5543,\n          \"data_first_seen\": \"2022-04-28T11:50:00+10:00\",\n          \"data_last_seen\": \"2025-06-30T10:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"HEZ\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 29.0,\n          \"emissions_factor_co2\": 1.01,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"HUNTVGT\",\n      \"name\": \"Hunter Valley\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"HVGTS\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.706,\n          \"data_first_seen\": \"1998-12-07T11:25:00+10:00\",\n          \"data_last_seen\": \"2020-02-09T16:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"INVICTA\",\n      \"name\": \"Invicta Sugar Mill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"INVICTA\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.3,\n          \"emissions_factor_co2\": 0.18,\n          \"data_first_seen\": \"2009-07-01T00:05:00+08:00\",\n          \"data_last_seen\": \"2018-06-14T00:00:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ICSM\",\n      \"name\": \"Isis Central Sugar Mill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"ICSM\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"emissions_factor_co2\": 0.0157,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"JACKSGUL\",\n      \"name\": \"Jacks Gully\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"JACKSGUL\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.3,\n          \"emissions_factor_co2\": 0.0778,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"JEERA\",\n      \"name\": \"Jeeralang A\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Jeeralang Power Station is a gas turbine power station with a capacity of 460 megawatts near Morwell, Victoria, Australia. The station is a peaking facility which is used only during periods of peak demand, and is also used as a black start facility to restore power to the grid in the event of major system failure. As a result, the actual capacity factor of the station is less than 5%. The power station was built by the State Electricity Commission of Victoria in response to the scaling back of Newport D power station from 1,000 megawatts to 500 megawatts, as a result of community concerns and union bans. Jeeralang consists of seven gas turbines configured to operate in single cycle mode.<br/><br/>Jeeralang A was built between 1977 and 1979 and consists of four Siemens Industries V93.1 gas turbines with a combined capacity of 220 megawatts.</p>\",\n      \"units\": [\n        {\n          \"code\": \"JLA03\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 51.0,\n          \"emissions_factor_co2\": 0.8091,\n          \"data_first_seen\": \"1998-12-10T12:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T19:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"JLA01\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 51.0,\n          \"emissions_factor_co2\": 0.8091,\n          \"data_first_seen\": \"1998-12-09T16:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-15T09:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"JLA02\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 51.0,\n          \"emissions_factor_co2\": 0.8091,\n          \"data_first_seen\": \"1998-12-09T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T19:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"JLA04\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 51.0,\n          \"emissions_factor_co2\": 0.8091,\n          \"data_first_seen\": \"1998-12-09T10:30:00+10:00\",\n          \"data_last_seen\": \"2025-06-26T11:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"JEERB\",\n      \"name\": \"Jeeralang B\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Jeeralang Power Station is a gas turbine power station with a capacity of 460 megawatts near Morwell, Victoria, Australia. The station is a peaking facility which is used only during periods of peak demand, and is also used as a black start facility to restore power to the grid in the event of major system failure. As a result, the actual capacity factor of the station is less than 5%. The power station was built by the State Electricity Commission of Victoria in response to the scaling back of Newport D power station from 1,000 megawatts to 500 megawatts, as a result of community concerns and union bans. Jeeralang consists of seven gas turbines configured to operate in single cycle mode.</p><p>Jeeralang B was built between 1978 and 1980 and consists of three Alstom Atlantique MS-9001 gas turbines with a combined capacity of 240 megawatts.</p>\",\n      \"units\": [\n        {\n          \"code\": \"JLB03\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 76.0,\n          \"emissions_factor_co2\": 0.8091,\n          \"data_first_seen\": \"1998-12-11T10:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T20:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"JLB02\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 76.0,\n          \"emissions_factor_co2\": 0.8091,\n          \"data_first_seen\": \"1998-12-10T12:25:00+10:00\",\n          \"data_last_seen\": \"2025-06-18T21:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"JLB01\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 76.0,\n          \"emissions_factor_co2\": 0.8091,\n          \"data_first_seen\": \"1998-12-09T16:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-16T10:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"JEMALNG1\",\n      \"name\": \"Jemalong\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Jemalong Solar Project (JSP) development is a 50MW solar farm located near Forbes in the central west region of New South Wales.</p>\",\n      \"units\": [\n        {\n          \"code\": \"JEMALNG1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 55.0,\n          \"data_first_seen\": \"2021-02-02T14:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"JNDSHPS\",\n      \"name\": \"Jindabyne\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"JNDABNE1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.1,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNWYGJP2\",\n      \"name\": \"Jindabyne Pump At Guthega\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"SNWYGJP2\",\n          \"fueltech_id\": \"pumps\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 70.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SNOWYGJP\",\n          \"fueltech_id\": \"pumps\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 70.0,\n          \"data_first_seen\": \"2019-11-10T14:25:00+10:00\",\n          \"data_last_seen\": \"2023-03-16T16:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"JBUTTERS\",\n      \"name\": \"John Butters\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The John Butters Power Station is a conventional hydroelectric power station located in Western Tasmania, Australia. The power station forms part of the King \\u2013 Yolande River Power Scheme and is owned and operated by Hydro Tasmania.</p>\",\n      \"units\": [\n        {\n          \"code\": \"JBUTTERS\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 144.0,\n          \"data_first_seen\": \"2005-05-17T16:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"JOUNAMA\",\n      \"name\": \"Jounama\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>A 14.4 megawatts small hydroelectric power station was completed in 2010 and is attached to the diverted flow of the Tumut River below the Jounama Dam wall. It is claimed that the small hydro facility generates enough energy to power 6,800 homes.</p>\",\n      \"units\": [\n        {\n          \"code\": \"JOUNAMA1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 14.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"JUNEESF\",\n      \"name\": \"Junee\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Junee Solar Farm is a 30 MWac solar farm in NSW just north of the 5000 person town of Junee, which is approximately 30 minutes\\u2019 drive from Wagga Wagga. The project commenced development in 2017 and is now operational having been acquired by Mytilineos.</p><p>The project is in a 10 year Power Purchase Agreement with Coles alongside two of Terrain Solar\\u2019s other solar farm developments, providing approximately 10% of Coles\\u2019 energy Australia wide.</p>\",\n      \"units\": [\n        {\n          \"code\": \"JUNEESF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 36.0,\n          \"data_first_seen\": \"2021-05-25T12:40:00+10:00\",\n          \"data_last_seen\": \"2025-06-20T09:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KABANWF\",\n      \"name\": \"Kaban\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Kaban Green Power Hub is a renewable energy project located in the Atherton Tablelands of Far North Queensland.\\u200b It consists of a 157 MW wind farm with approval for a 100 MW battery, and a network upgrade.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KABANWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 156.0,\n          \"data_first_seen\": \"2022-09-26T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KALAMUNDA_SG\",\n      \"name\": \"Kalamunda\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"KALAMUNDA_SG\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 1.3,\n          \"emissions_factor_co2\": 0.057,\n          \"data_first_seen\": \"2014-08-06T10:30:00+10:00\",\n          \"data_last_seen\": \"2022-03-21T15:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KALBARRI\",\n      \"name\": \"Kalbarri\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Located around 20km south of Kalbarri, this wind farm generates around one third of the electricity needed by the Kalbarri community, offsetting nearly 5,000 tonnes of greenhouse gases each year. While 1.6 megawatts are supplied by the wind farm, another 2 megawatts are stored in a back-up battery. The project was completed in 2021 to provide an alternative and renewable energy supply to Kalbarri if connection to the main grid is lost.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KALBARRI_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.6,\n          \"data_first_seen\": \"2013-12-18T08:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"STHRNCRS\",\n      \"name\": \"Kambalda\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Southern Cross Energy, in Australia, is 100 per cent owned by TransAlta and is made up of four simple-cycle power stations, each with one gas turbine. The stations are located in Kambalda, where TransAlta is a significant sponsor of the Kambalda Community Recreation Centre, as well as in Mt. Keith, Leinster and Kalgoorlie.</p><p>Simple-cycle power generation is often used for periods of peak usage, or to reinforce baseload power provided by other sources. BHP Billiton Nickel West uses most of the electricity generated by Southern Cross Energy in its area mining operations.</p>\",\n      \"units\": [\n        {\n          \"code\": \"STHRNCRS_EG\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 245.0,\n          \"emissions_factor_co2\": 0.5572,\n          \"data_first_seen\": \"2014-02-26T12:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KARSF\",\n      \"name\": \"Karadoc\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Karadoc Solar Farm is a photovoltaic power station 35 kilometres (22 mi) south of Mildura near the town of Iraak in the Australian state of Victoria. It can generate up to 112MW of electricity, and was designed by  BayWa r.e. Solar. It was officially opened in March 2019.The solar farm is on a site of 269 hectares (664 acres) and was built by Melbourne construction company Beon Energy Solutions with first generation in November 2018. It has an offtake agreement to provide 74,000 MWh per year of electricity to Carlton &amp; United Breweries for 12 years. At the time of its construction, it was the largest in Victoria at 90 MWAC, 120 MWP.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KARSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 104.0,\n          \"data_first_seen\": \"2018-10-24T08:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BLAIRFOX_KARAKIN\",\n      \"name\": \"Karakin\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Blair Fox managed the purchase and dismantling of 20 ENERCON E40 500kW wind turbines from the San Giorgio La Molara wind farm in the province of Benevento, Italy.<br/><br/>These wind turbines were transported to Western Australia, refurbished and installed at the West Hills and Karakin Wind Farms around 150km north of Perth.<br/><br/>The 5MW Karakin Wind Farm supplies local horticulturalists over a private 33kV distribution network with the balance of electricity generated used to supply Blair Fox retail customers in the South West Interconnected System (SWIS).</p>\",\n      \"units\": [\n        {\n          \"code\": \"BLAIRFOX_KARAKIN_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.0,\n          \"data_first_seen\": \"2013-12-17T09:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T06:45:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KAREEYA\",\n      \"name\": \"Kareeya\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Kareeya Hydro Power Station near Tully in Queensland, Australia in a hydroelectric power station that began generating power in 1957. It has a capacity of 88 megawatts (118,000 hp) which is fed into the National Electricity Market.  The power station is owned by CleanCo Queensland.<br/>Taking its name from the Aboriginal word meaning &#x27;big water&#x27;, the Kareeya Hydro project originally comprised construction of Koombooloomba Dam, the Tully Falls Weir and Kareeya Hydro power station. A dam was needed for water storage because most of the rain in the area falls in the first few months of the year. An intake tower is located in the weir, which directs water down a tunnel to the turbines in an underground power station below Tully Falls.<br/>Planning for the project began in 1949 and it was intended to be operating by 1955. Construction of a diversion tunnel started in early 1952. The 132 Kv transmission line was the first ever constructed in Queensland and the state&#x27;s first use of steel towers for electricity distribution. The last of the four generating sets was installed by mid-1959.<br/>The power station&#x27;s staff and families were provided accommodation in a small village, named Cardstone, located downstream from the plant.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KAREEYA3\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"data_first_seen\": \"1998-12-07T02:50:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KAREEYA5\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KAREEYA1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"data_first_seen\": \"1998-12-07T02:50:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KAREEYA2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"data_first_seen\": \"1998-12-07T05:05:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KAREEYA4\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"data_first_seen\": \"1998-12-07T02:50:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KEEPIT\",\n      \"name\": \"Keepit\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Keepit Power Station is a hydro-electric power station located at the Keepit Dam on the Namoi River, near Gunnedah in the North West Slopes region of New South Wales, Australia. The Keepit Power Station has one turbine with a generating capacity of 7.2 megawatts (9,700 hp) of electricity. The power station is operated by Eraring Energy and generated 1,603 megawatts (2,150,000 hp) of net energy production during 2009, used primarily for peak-load generation.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KEEPIT\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.2,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KEMERTON\",\n      \"name\": \"Kemerton\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Kemerton Power Station is a power station 17 km northeast of Bunbury in Western Australia.  It is located in an area known as the Kemerton Industrial Park.  The location had been considered as being Kemerton, in the 1980s as a potential aluminium smelter location, but is now considered to be part of Wellesley.  The consideration of the site as being appropriate as a power station site was being considered in the early 2000s.It is rated at 300 MW using two Siemens open cycle gas turbine generators powered by natural gas. It operates as a peaking plant and provides electricity into the South West Interconnected System (SWIS). When it was built in 2005, it was rated at 260.9 MW, and received an upgrade to the current capacity in June 2008. When gas is not available, the power station can also operate on fuel oil. Gas is supplied to the Kemerton Power Station via a 4.94 km lateral branch from the Dampier to Bunbury Natural Gas Pipeline. The branch line is a 300 mm diameter steel pipe with 6.4 mm wall thickness.Kemerton power station also has four 1.25 MW diesel generators completed in October 2018. These are used in a contract with the Australian Energy Market Operator (AEMO) to provide the capability for a black start on the SWIS if needed.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KEMERTON_GT11\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 154.7,\n          \"emissions_factor_co2\": 0.667,\n          \"data_first_seen\": \"2014-01-06T15:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T21:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KEMERTON_GT12\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 154.7,\n          \"emissions_factor_co2\": 0.667,\n          \"data_first_seen\": \"2014-01-10T14:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TESLA_KEMERTON\",\n      \"name\": \"Kemerton\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Commissioned in 2012, Kemerton is located in the Kemerton Industrial Park north of Bunbury.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TESLA_KEMERTON_G1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"emissions_factor_co2\": 0.667,\n          \"data_first_seen\": \"2014-01-22T12:30:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"AGLSITA\",\n      \"name\": \"Kemps Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"AGLSITA1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.062,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KENNEDY\",\n      \"name\": \"Kennedy Energy Park\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Kennedy Energy Park is a world-first wind, solar and energy storage facility located in Flinders Shire in central north Queensland. The project is owned by Windlab and Eurus. Construction has commenced and it will be generating by late 2019.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KEPBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.0,\n          \"data_first_seen\": \"2024-06-06T10:50:00+08:00\",\n          \"data_last_seen\": \"2025-07-20T15:05:00+08:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"KEPSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 16.0,\n          \"data_first_seen\": \"2021-07-06T10:05:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KEPBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.0,\n          \"data_first_seen\": \"2021-07-09T17:10:00+08:00\",\n          \"data_last_seen\": \"2025-07-13T18:25:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KEPWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 43.2,\n          \"data_first_seen\": \"2021-07-06T13:20:00+08:00\",\n          \"data_last_seen\": \"2025-07-13T22:50:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KERNGSP\",\n      \"name\": \"Kerang\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"units\": [\n        {\n          \"code\": \"KERNGSP1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 37.0,\n          \"data_first_seen\": \"2025-02-28T16:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KIAMSF1\",\n      \"name\": \"Kiamal\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Kiamal Solar Farm is located in north-west Victoria, approximately 3 km north of the township of Ouyen with Stage 1 currently under construction. When completed it will be Victoria&#x27;s largest solar farm.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KIAMSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 239.0,\n          \"data_first_seen\": \"2020-09-08T12:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KIATAWF\",\n      \"name\": \"Kiata\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Kiata Wind Farm is a small wind farm located along the Western Highway north of Nhill. The wind farm is owned by Windlab, the John Laing Group and some local shareholders. The turbines were built by Keppel Prince and assembled at the site by Windlab. It was &quot;officially opened&quot; by Lily D&#x27;Ambrosio on Australia Day 2018. According to Kiata Wind Farm director Rob Fisher, the Kiata turbines &quot;are the biggest turbines operating in Australia to date.&quot; The ABC reported that some of the local landholders would become part owners &quot;via a community investment model.&quot;</p>\",\n      \"units\": [\n        {\n          \"code\": \"KIATAWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 31.0,\n          \"data_first_seen\": \"2017-11-10T09:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0KIDSTON\",\n      \"name\": \"Kidston\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Kidston Pumped Hydro Project is the flagship project of the Kidston Clean Energy Hub, located in Kidston, Far-North Queensland.</p><p>The Kidston Pumped Storage Hydro Project is the first pumped hydro project in Australia for over 40 years, the first to be developed by the private sector, and the third largest electricity storage device in the country.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0KIDSTON\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KSP1\",\n      \"name\": \"Kidston\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>KS1 is the first of four projects that comprise the Kidston Clean Energy Hub, located in Kidston, Far-North Queensland.</p><p>This site was selected in order to take advantage of the highest solar radiation zone in the country. The project has 540,000 solar panels operating on a single axis tracking system with an anticipated project life of 30 years.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KSP1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"data_first_seen\": \"2017-11-30T14:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KINCUMB\",\n      \"name\": \"Kincumber\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"KINCUM1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.62,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KINGASF\",\n      \"name\": \"Kingaroy\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The proposed development site is located approximately 1 km east of Kingaroy, Queensland. Kingaroy is agricultural town in the South Burnett Region, approximately 200 km north of Brisbane. The township is located at the junction of D\\u2019Aguilar Highway and the Bunya Highway. The development is located on the State-controlled Kingaroy Barkers Creek Road.</p><p>The project is located in the local government area of the South Burnett Regional Council, in the Kingaroy Shire.</p><p>The Solar Farm will involve the construction of electricity generation works across an area of approximately 118.37 hectares. The solar array is anticipated to have a 30-50 year life span.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KINGASF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 47.0,\n          \"data_first_seen\": \"2024-09-04T09:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KOGANCK\",\n      \"name\": \"Kogan Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Kogan Creek Power Station is a 750 megawatt coal fired power station owned by CS Energy on the Darling Downs in Queensland. The $1.2 billion plant is situated at Brigalow, in the Surat Basin between Dalby and Chinchilla.<br/>The power station uses supercritical steam technology, which produces lower greenhouse gases emissions per energy unit delivered, and air-cooled surface condensers, which reduces water consumption. The plant consumes 90% less water when compared to conventional power stations through the use of dry cooling technology. The plant runs at 40 per cent efficiency, and requires 42 per cent less fuel input than conventional power stations.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KPP_1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 744.0,\n          \"emissions_factor_co2\": 0.8436,\n          \"data_first_seen\": \"2007-05-12T17:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KOOLKHAN\",\n      \"name\": \"Koolkhan\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Located ten minutes north of Grafton on the banks of the Clarence River, the Koolkhan power station was commissioned in the 1950s to provide a reliable electricity supply to the Northern Rivers region. The power station was coal-fired and operated daily up until 1979, when it was decommissioned and used as a storage facility over ensuing years.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KKGTS\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 20.0,\n          \"emissions_factor_co2\": 0.5447,\n          \"data_first_seen\": \"1998-12-07T11:45:00+10:00\",\n          \"data_last_seen\": \"2000-03-03T05:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KESS1\",\n      \"name\": \"Koorangie\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Currently in the development phase, the new lithium-ion battery will be connected to AusNet\\u2019s 220kV transmission network and provide system strength to the Murray River Renewable Energy Zone (REZ).</p><p>Edify has been awarded a System Support Agreement with the Australian Energy Market Operator (AEMO) to provide 125 megawatts (MW) of services to strengthen the power system and increase the potential for generation in the Murray River region. The objective for KESS is to increase the renewable hosting capacity of the Murray River REZ by up to 300MW, through the provision of system strength to improve network stability.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 185.0,\n          \"data_first_seen\": \"2025-02-14T11:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"KESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 185.0,\n          \"data_first_seen\": \"2025-02-14T14:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KRCCOGEN\",\n      \"name\": \"KRC Cogen\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"KRCCOGEN\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 5.0,\n          \"emissions_factor_co2\": 0.68,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KWINANA\",\n      \"name\": \"Kwinana\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Kwinana Cogeneration Plant is located 40 kilometres south of Perth, Western Australia. It provides steam and electrical power to the BP Australia Kwinana Oil Refinery and electricity only to Synergy, the State owned generator/retailer.<br/>As a cogeneration plant, Kwinana supplies both steam and electrical power to its two customers. Steam production from the plant comes predominantly from the waste heat from the gas turbine exhausts and is supported by burning refinery fuel gas from the BP Refinery using &#x27;Duct Burners&#x27; inside the Heat Recovery Steam Generators (HRSG). The steam produced drives a steam turbine, further enhancing the plant&#x27;s efficiency, with BP&#x27;s steam supply coming from the extraction port on the steam turbine after some pressure and temperature has been lost.<br/>Kwinana produces 119MW of electricity, or approximately 6% of Western Australia&#x27;s requirements. It is primarily fueled by natural gas from Western Australia&#x27;s North West Shelf gas fields and delivered to the plant by the Dampier to Bunbury Natural Gas Pipeline. The plant is certified for its environmental practices (ISO 14001), quality assurance (ISO 9001) and health and safety (AS4801 &amp; BS18001).</p><p>Kwinana Cogeneration Plant is located 40 kilometres south of Perth, Western Australia. It provides steam and electrical power to the BP Australia Kwinana Oil Refinery and electricity only to Synergy, the State owned generator/retailer.<br/>As a cogeneration plant, Kwinana supplies both steam and electrical power to its two customers. Steam production from the plant comes predominantly from the waste heat from the gas turbine exhausts and is supported by burning refinery fuel gas from the BP Refinery using &#x27;Duct Burners&#x27; inside the Heat Recovery Steam Generators (HRSG). The steam produced drives a steam turbine, further enhancing the plant&#x27;s efficiency, with BP&#x27;s steam supply coming from the extraction port on the steam turbine after some pressure and temperature has been lost.<br/>Kwinana produces 119MW of electricity, or approximately 6% of Western Australia&#x27;s requirements. It is primarily fueled by natural gas from Western Australia&#x27;s North West Shelf gas fields and delivered to the plant by the Dampier to Bunbury Natural Gas Pipeline. The plant is certified for its environmental practices (ISO 14001), quality assurance (ISO 9001) and health and safety (AS4801 &amp; BS18001).</p>\",\n      \"units\": [\n        {\n          \"code\": \"KWINANA_GT2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 103.2,\n          \"emissions_factor_co2\": 0.5072,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KWINANA_GT3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 103.2,\n          \"emissions_factor_co2\": 0.5072,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T23:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KWINANA_C5\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 0.91,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KWINANA_C6\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 0.91,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KWINANA_ESR\",\n      \"name\": \"Kwinana Battery\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>A 100MW battery in Perth, Western Australia that commenced operation in May 2023.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KWINANA_ESR1.G1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 100.0,\n          \"data_first_seen\": \"2023-09-28T08:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"KWINANA_ESR1.L1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 100.0,\n          \"data_first_seen\": \"2023-09-28T10:25:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T06:10:00+08:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"KWINANA_ESR2\",\n      \"name\": \"Kwinana Battery 2\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Kwinana Battery Energy Storage System 2 (KBESS2) is Synergy&#x27;s second lithium ion phosphate (LFP), large scale battery energy storage system in the SWIS.</p>\",\n      \"units\": [\n        {\n          \"code\": \"KWINANA_ESR2L1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 225.0,\n          \"data_first_seen\": \"2024-10-19T14:20:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T06:45:00+08:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"KWINANA_ESR2G1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 225.0,\n          \"data_first_seen\": \"2024-10-19T13:15:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TIWEST_COG1\",\n      \"name\": \"Kwinana Cogen\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Kwinana Co-generation power plant was commissioned in December 1996, 40km south of Perth in Western Australia. The plant is primarily fuelled by Western Australia\\u2019s gas fields, north of Perth. The gas is transported to Kwinana through the Dampier to Bunbury Gas pipeline. It can produce over 120 MW of electricity which can supply about 6 per cent of Western Australia\\u2019s power needs.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TIWEST_COG1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 42.1,\n          \"emissions_factor_co2\": 0.58,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PPP_KCP_EG1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 120.0,\n          \"emissions_factor_co2\": 0.52,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2021-11-27T23:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PERTHENERGY_KWINANA\",\n      \"name\": \"Kwinana Swift\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Kwinana Swift Power Station is a dual-fuel 120 MW peaking station located 40km south of Perth in the city of Kwinana. The station features four 30MW gas turbines connected to two common generators.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PERTHENERGY_KWINANA_GT1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 116.0,\n          \"emissions_factor_co2\": 0.5823,\n          \"data_first_seen\": \"2013-12-20T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LADBROKE\",\n      \"name\": \"Ladbroke Grove\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Ladbroke Grove Power Station is a gas-fired power station in the locality of Monbulla near Penola in the Limestone Coast region of South Australia. It was built by Boral Limited in 2000. It is now owned by Origin Energy.The power station was originally built with a generating capacity of 40 MW, and now has a generating capacity of 80 MW. It is used as a peaking power plant.Ladbroke Grove power station was built next to the Katnook gas processing plant, which processed gas extracted from the Katnook Gas Field in the western Otway Basin. Originally, Ladbroke Grove used gas processed next door. When the wells in the field were becoming depleted, a branch from the SEAGas pipeline was built to the Katnook plant, and gas from that pipeline, drawn from further east in the Otway Basin, now fuels the power station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LADBROK1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 40.0,\n          \"emissions_factor_co2\": 0.5078,\n          \"data_first_seen\": \"2000-01-10T14:10:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LADBROK2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 40.0,\n          \"emissions_factor_co2\": 0.5078,\n          \"data_first_seen\": \"2000-05-04T13:50:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LBBESS\",\n      \"name\": \"Lake Bonney\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The 25 MW / 52 MWh Battery Energy Storage System is co-located with the Lake Bonney Wind Farms near Millicent in South Australia. The battery was energised in 2019.</p><p>Iberdrola Australia entered into funding agreements with the South Australian (SA) Government and the Australian Renewable Energy Agency (ARENA) to co-fund the ~$38 million development. The SA Government and ARENA are each contributing up to $5 million in funding.</p><p>The battery assists Iberdrola Australia in managing the intermittency risk associated with renewable energy. It also participates in the volatile Frequency Control Ancillary Services (FCAS) markets, providing\\u00a0Iberdrola Australia\\u00a0with a degree of hedging against FCAS costs. In addition, the battery contributes towards system reliability for our customers - and the network as a whole - in South Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LBBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"data_first_seen\": \"2019-10-16T10:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"LBBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"data_first_seen\": \"2019-10-16T13:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LKBONNY1\",\n      \"name\": \"Lake Bonney\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Lake Bonney Wind Farms are located on the Woakwine Range, about 2 km from the eastern shore of Lake Bonney, near Millicent in South Australia. The wind farm was constructed in three separate stages (Lake Bonney 1, 2 and 3) with the final stage commencing operations in July 2010.</p><p>The 278.5 MW wind farm comprises 112 wind turbines which include 46 Vestas V66 wind turbines and 66 Vestas V90 wind turbines.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LKBONNY1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 80.5,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LKBONNY_2\",\n      \"name\": \"Lake Bonney 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Lake Bonney Wind Farms are located on the Woakwine Range, about 2 km from the eastern shore of Lake Bonney, near Millicent in South Australia. The wind farm was constructed in three separate stages (Lake Bonney 1, 2 and 3) with the final stage commencing operations in July 2010.</p><p>The 278.5 MW wind farm comprises 112 wind turbines which include 46 Vestas V66 wind turbines and 66 Vestas V90 wind turbines.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LKBONNY2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 159.0,\n          \"data_first_seen\": \"2007-05-31T17:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LKBONNY3\",\n      \"name\": \"Lake Bonney 3\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>After the successful development of both the Lake Bonney Stage 1 (80.5 MW) and Lake Bonney Stage 2 (159 MW) wind farm projects, Lake Bonney Wind Power, a subsidiary of Infigen energy, successfully commissioned the 39 MW Lake Bonney Stage 3 wind farm. Construction commenced in February 2009 and was commissioned in September 2009.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LKBONNY3\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 39.0,\n          \"data_first_seen\": \"2010-07-02T15:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LK_ECHO\",\n      \"name\": \"Lake Echo\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Lake Echo Power Station is a conventional hydroelectric power station located in the Central Highlands region of Tasmania, Australia. The power station is situated on the Upper River Derwent catchment and is owned and operated by Hydro Tasmania.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LK_ECHO\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 32.4,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-09T16:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0LANCSF\",\n      \"name\": \"Lancaster\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Lancaster Solar farm is currently under development, and is set to provide over 100MW of solar power to Victoria. The site is located approximately 9 km east of Kyabram.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0LANCSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 106.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0LVBESS\",\n      \"name\": \"Latrobe Valley\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Latrobe Valley BESS (Battery Energy Storage System) is a 100 MW Battery Energy Storage System located beside the existing Morwell Terminal Station on Monash Way, just south of the Princes Freeway.</p><p>The Latrobe Valley BESS is now under construction and when complete will improve the reliability of the electricity network by storing power for use during peak periods.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0LVBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0LVBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LVESL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 140.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"LVESG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 140.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LNGS\",\n      \"name\": \"Laverton North\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Laverton North Power Station is a natural gas-powered plant, owned and operated by Snowy Hydro Limited. It is situated in Laverton North, on the south-western outskirts of Melbourne, Victoria, approximately 15 km from the Melbourne Central Business District. It is a peaking power plant, particularly constructed to cater for the growth in Victoria&#x27;s summer electricity demand, and can be rapidly activated when required.The station has two open-cycle gas turbines that together can generate a total of 320 MW of electricity. The turbines are primarily fuelled by natural gas supplied from the Brooklyn-Lara gas pipeline but, in the event of a gas supply curtailment, they can burn low sulphur emission heavy oil as a backup fuel. The plant is normally operated remotely from Snowy Hydro Limited&#x27;s central control room in Cooma, New South Wales, but is also equipped to be run locally.Snowy Hydro contracted Siemens to complete the engineering, procurement and construction (EPC) for the project. Initial civil works started in October 2004 and the station was commissioned in December 2006.The original licence only allowed the power station to operate for 10% of the year, but in May 2007 Snowy Hydro applied for an emergency extension of operating hours because a drought had affected hydro energy supplies. The Victorian Civil and Administrative Tribunal issued an interim order that the plant remain shut down on weekdays between 8am to 5pm, due to neighbouring offices being affected by the level of noise and vibration. However, the order was lifted in July 2007.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LNGS1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 156.0,\n          \"emissions_factor_co2\": 0.6581,\n          \"data_first_seen\": \"2015-07-01T00:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-04T00:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LNGS2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 156.0,\n          \"emissions_factor_co2\": 0.6581,\n          \"data_first_seen\": \"2015-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-03T23:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LAVNORTH\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 320.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"2006-10-28T13:00:00+10:00\",\n          \"data_last_seen\": \"2015-06-24T15:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LEM_WIL\",\n      \"name\": \"Lemonthyme / Wilmot\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Water from Lake Parangana is transferred west via tunnels to Lemonthyme Power Station. The water runs into Lake Cethana.</p><p></p><p>Water from Wilmot River is stored at Lake Gairdner in the Wilmot Dam. Water is transferred by tunnel, pipeline and penstock to Wilmot Power Station and then flows to Lake Cethana.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LEM_WIL\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 81.6,\n          \"data_first_seen\": \"2005-05-16T16:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0LIDDELLBESS\",\n      \"name\": \"Liddell\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Liddell Battery is a 500 MW, two-hour duration, grid scale battery to be located on the former Liddell Power Station site at <a href=\\\"https://www.agl.com.au/about-agl/how-we-source-energy/agl-macquarie\\\">AGL Macquarie</a>.</p><p>Construction work for the battery has commenced in June 2024, with the commencement of operations targeted for December 2025. Significant targets have been set around the employment of apprentices, local procurement \\u2013 including 95% of steel being sourced locally - and working with First Nations businesses. At the peak of construction more than 150 workers will be involved in the project.</p><p>The total construction cost is estimated to be approximately $750 million.\\u00a0Fluence has been selected as the engineering, procurement and construction (EPC) contractor. Connection Agreements have been signed with Transgrid to construct and operate 330/33kV battery substation and ~450mtrs of 330kV overhead transmission line and an extension to the existing 330kV switch yard.</p><p>The project will be supported by both a $35 million grant awarded by the Australian Renewable Energy Agency (ARENA) as part of its Advancing Renewables Program and a Long-Term Energy Service Agreement (LTESA), arranged by AEMO Services on behalf of the NSW Government.</p><p><br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"0LIDDELLBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 500.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0LIDDELLBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 500.0,\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LIDDELL\",\n      \"name\": \"Liddell\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Liddell Power Station is a coal-powered thermal power station with four 500 megawatts (670,000 hp) GEC steam driven turbine alternators for a combined electrical capacity of 2,000 megawatts (2,700,000 hp). <br/>However, as at April 2018, its operating capacity has been assessed at 1,680 megawatts (2,250,000 hp). Commissioned between 1971 and 1973, the station is located adjacent to Lake Liddell near Muswellbrook in the Hunter Region of Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LD02\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 500.0,\n          \"emissions_factor_co2\": 0.9479,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2023-04-26T22:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LD03\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 500.0,\n          \"emissions_factor_co2\": 0.9479,\n          \"data_first_seen\": \"1999-04-09T14:45:00+10:00\",\n          \"data_last_seen\": \"2022-04-01T09:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LD04\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 500.0,\n          \"emissions_factor_co2\": 0.9479,\n          \"data_first_seen\": \"1998-12-21T13:30:00+10:00\",\n          \"data_last_seen\": \"2023-04-24T08:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LD01\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 500.0,\n          \"emissions_factor_co2\": 0.9479,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2023-04-28T10:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LILYVASF\",\n      \"name\": \"Lilyvale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The project is located around 50 km North-East of Emerald, in Central Queensland. The solar farm will be connected to the electricity network via a newly constructed substation.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LILYSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 118.0,\n          \"data_first_seen\": \"2019-03-09T12:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T13:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0LCNBESS\",\n      \"name\": \"Limestone Coast North\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Limestone Coast North Energy Park is the first of two new grid-scale co-located battery projects, being developed as part of the Limestone Coast Energy Park, located in regional South East Australia. These projects will significantly boost energy storage capacity, enhancing the state\\u2019s energy stability and supporting its transition to net-zero emissions.</p><p>Strategically located near the 275kV South East Substation, the batteries will store excess renewable energy and discharge it during peak demand, stabilizing the grid and lowering energy costs. The parks will collectively store up to 60% of South Australia\\u2019s residential solar output, preventing an average of 80,000 tonnes of carbon dioxide emissions annually.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0LCNBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0LCNBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0LIMBESS\",\n      \"name\": \"Limondale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>RWE has started construction of Australia&#x27;s first eight-hour Battery Energy Storage System (BESS), near Balranald, in New South Wales.</p><p>The landmark project has a planned capacity of 50+ megawatts (MW) and 400+ megawatt hours (MWh). The BESS will be located next to our existing 249 MWac Limondale Solar Farm \\u2013 which is one of Australia\\u2019s largest \\u2013 and will connect to the existing 33kV transmission line.</p><p>Tesla will supply 144 Megapack batteries for the eight-hour lithium-ion BESS, which was the only successful project in New South Wales\\u2019 first Long Duration Storage Long-Term Energy Service Agreements tender process.</p><p><br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"0LIMBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 50.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0LIMBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 50.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LIMOSF1\",\n      \"name\": \"Limondale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>RWE\\u2019s first Australian renewables project is the Limondale Solar Farm, near Balranald in New South Wales.</p><p>The photovoltaic plant has about 872,000\\u00a0panels on 770\\u00a0hectares, and an installed capacity of 249\\u00a0MWac.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LIMOSF11\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 275.0,\n          \"data_first_seen\": \"2020-07-01T08:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LIMOSF2\",\n      \"name\": \"Limondale 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>RWE\\u2019s first Australian renewables project is the Limondale Solar Farm, near Balranald in New South Wales.</p><p>The photovoltaic plant has about 872,000\\u00a0panels on 770\\u00a0hectares, and an installed capacity of 249\\u00a0MWac.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LIMOSF21\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 38.0,\n          \"data_first_seen\": \"2019-12-24T07:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LGAPWF1\",\n      \"name\": \"Lincoln Gap\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Lincoln Gap Wind Farm is a wind farm under construction in the vicinity of Lincoln Gap on northeastern Eyre Peninsula in South Australia, Australia. It is proposed to consist of 59 wind turbines and generate a total of 212 MW of electricity. Construction began in late 2017 and was initially expected to be commissioned in late 2018. Construction was delayed in July 2018 when unexploded ordnance was discovered on the site, left from historic military testing. The site is not far from the Cultana Training Area.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LGAPWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 126.0,\n          \"data_first_seen\": \"2019-05-01T11:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LGAPWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 86.0,\n          \"data_first_seen\": \"2021-12-14T01:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0LOCKHART\",\n      \"name\": \"Lockhart\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Lockhart Hybrid Renewable Energy Project is has been designed to showcase how a regional town can benefit from lower power prices and share in the ownership of the electrical generation assets which export the bulk of the power back into the grid.</p><p>Lockhart is a town of 1,000 people, south of Wagga in NSW. The renewable hybrid energy plant will comprise of 10MW of solar AC coupled to a 10MW/20MWh battery with a single connection point, making it unique in the NEM.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0LOCKHARTSF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 10.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LONGFORD\",\n      \"name\": \"Longford\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"LONGFORD\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 44.0,\n          \"emissions_factor_co2\": 0.6022,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LRSF\",\n      \"name\": \"Longreach\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Longreach Solar Farm is a solar farm located ten kilometres east of Longreach in Central West Queensland, Australia. It has a generating capacity of 17.5 megawatts. The solar farm uses 53,000 single-axis tracking solar panels across a 50 hectare site. It was owned and operated by Canadian Solar Australia and Foresight. Foresight Solar Fund acquired the plant in 2022.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LRSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 17.0,\n          \"data_first_seen\": \"2018-04-16T10:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LONSDALE\",\n      \"name\": \"Lonsdale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Lonsdale Power Station is a diesel-powered electricity generator in South Australia in Lonsdale, an industrial southern suburb of Adelaide. It is owned by Snowy Hydro since 2014. It consists of 18 diesel reciprocating engines generating up to 21MW of electricity to meet peak demands in the National Electricity Market.The power station was designed and built by Cummins Power Generation under contract from Infratil in 2002 on what is now the site of the Port Stanvac Power Station. It was moved along the road to its present site in 2011. Snowy Hydro bought assets from Infratil in 2014. These included Lumo Energy, Direct Connect and three diesel peaking generators for a total of 136 MW. The other two were Angaston Power Station and Port Stanvac Power Station.It achieves the low emissions mandated by the Environment Protection Agency through selective catalytic reduction technology, matching standards set for gas turbines.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LONSDALE\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 20.0,\n          \"emissions_factor_co2\": 0.6749,\n          \"data_first_seen\": \"2016-01-12T12:45:00+10:00\",\n          \"data_last_seen\": \"2025-05-21T09:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0LOTUSCRKWF\",\n      \"name\": \"Lotus Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Lotus Creek Wind Farm is a proposed renewable energy project in Central Queensland, north of Rockhampton. The project will consist of up to 46 wind turbines, each with a maximum blade tip height of 230 metres and a combined maximum capacity of around 285 MW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0LOTUSCRKWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 285.2,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LOYYANGA\",\n      \"name\": \"Loy Yang A\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Loy Yang Power Station is a brown coal- fired thermal power station located on the outskirts of the city of Traralgon, in south-eastern Victoria, Australia. It consists of two sections, known as Loy Yang A (4 units) and Loy Yang B (2 units). Both Loy Yang A and B are supplied by the Loy Yang brown coal mine. The Loy Yang power stations are located in the brown coal rich Latrobe Valley, along with the Yallourn Power Station.</p><p>Loy Yang A has four generating units with a combined capacity of 2,210\\u00a0MW, which have been completed between 1984 and 1988.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LYA1\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 560.0,\n          \"emissions_factor_co2\": 1.1609,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LYA2\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 530.0,\n          \"emissions_factor_co2\": 1.1609,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LYA3\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 560.0,\n          \"emissions_factor_co2\": 1.1609,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LYA4\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 560.0,\n          \"emissions_factor_co2\": 1.1609,\n          \"data_first_seen\": \"1998-12-07T10:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LOYYB\",\n      \"name\": \"Loy Yang B\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Loy Yang B has two units with a capacity of 1,070\\u00a0MW (1,430,000\\u00a0hp) which entered service in 1993 and 1996. The two units have Hitachi turbo generators.</p><p>Loy Yang B employs up to 152 full-time staff and another 40 contractors. It is Victoria&#x27;s newest and most efficient brown coal-fired power station and can generate approximately 17% of Victoria&#x27;s power needs.</p><p><br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"LOYYB2\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 500.0,\n          \"emissions_factor_co2\": 1.1223,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LOYYB1\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 500.0,\n          \"emissions_factor_co2\": 1.1223,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LUCASHGT\",\n      \"name\": \"Lucas Heights\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>EDL owns and operates the 21 MW Lucas Heights Power Stations, which processes landfill gas (LFG) from the decomposition of organic waste into electricity, reducing greenhouse gas emissions.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LUCASHGT\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 12.65,\n          \"emissions_factor_co2\": 0.0774,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"LUCAS2S2\",\n      \"name\": \"Lucas Heights 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>EDL owns and operates the 21 MW Lucas Heights Power Stations, which processes landfill gas (LFG) from the decomposition of organic waste into electricity, reducing greenhouse gas emissions.</p>\",\n      \"units\": [\n        {\n          \"code\": \"LUCAS2S2\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.6,\n          \"emissions_factor_co2\": 0.0787,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MACARTH\",\n      \"name\": \"Macarthur\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Macarthur Wind Farm is a wind farm located in Macarthur, Victoria, Australia, near Hamilton, 260 km west of Melbourne. It is on a 5,500 ha site which has an installed capacity of 420 megawatts (MW). Based on a capacity factor of around 35%, it is estimated that the long-term average generation will be approximately 1,250 GWh per year. The energy produced annually by a wind farm varies year-to-year, and during FY2015 the farm produced 977.9 GWh.<br/>It is the largest wind farm in the southern hemisphere generating enough power for 220,000 homes and abating 1.7 million tons of greenhouse gases annually, at a capacity factor of 35%. The wind farm comprises 140 Vestas V112-3.0MW wind turbines manufactured in Denmark.The project cost about A$1 billion and was fully operational in January 2013. It was constructed by Vestas and Leighton Contractors. The first turbines were connected to the grid in September 2012. AGL also invested an additional $27m in the substation, which is completely owned by the company.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MACARTH1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 420.0,\n          \"data_first_seen\": \"2012-09-27T14:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MCINTYR\",\n      \"name\": \"MacIntyre\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>With a total investment of AU$1.96 billion, the 1,026MW MacIntyre Wind Farm Precinct will be ACCIONA Energ\\u00eda\\u2019s biggest renewable energy facility and one of the largest onshore wind farms in the world. Developed in partnership with CleanCo, the Queensland Government\\u2019s newest renewable energy generator, the wind farm is expected to be operational in 2024.</p><p></p><p>The MacIntyre Wind Farm will be constructed on land predominately used for sheep farming. Current farming practices will continue during the construction and operations phases of the wind farm. The site has been selected due to its exposure to consistent winds across this part of the country and provides a suitable resource for the development of a wind farm.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MCINTYR1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 923.0,\n          \"data_first_seen\": \"2024-08-28T14:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MACKAY\",\n      \"name\": \"Mackay\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Mackay Gas Turbine was a remote-controlled power generator that was owned and operated by Stanwell Corporation  Ltd. for short periods when customer demand for electricity was high. The gas turbine&#x27;s ability to start quickly played a role in ensuring a secure, reliable power supply for distribution to consumers.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MACKAYGT\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 34.0,\n          \"emissions_factor_co2\": 1.0458,\n          \"data_first_seen\": \"1999-01-13T15:35:00+10:00\",\n          \"data_last_seen\": \"2021-02-25T19:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MACKNTSH\",\n      \"name\": \"Mackintosh\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Mackintosh Power Station is a conventional hydroelectric power station located in Western Tasmania, Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MACKNTSH\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 79.9,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MANSLR\",\n      \"name\": \"Manildra\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Located on Wiradjuri Country in the Central West of NSW, approximately 45 kilometres west of Orange, Manildra Solar Farm supplies clean, green energy to Energy Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MANSLR1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"data_first_seen\": \"2018-05-02T13:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BRIDGETOWN_BIOMASS_PLANT\",\n      \"name\": \"Manjimup\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BRIDGETOWN_BIOMASS_PLANT\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 40.0,\n          \"emissions_factor_co2\": 0.057,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MANNUMB\",\n      \"name\": \"Mannum\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The BESS will store excess renewable energy to supply to the electricity grid during peak demand periods, to support consistency of renewable energy supply. This means a cleaner, more reliable power grid for South Australians.</p><p>The BESS can send 100 megawatts of power into the electricity grid for up to two hours \\u2013 enough to power about 16,000 South Australian homes each day.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MANNUMBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 131.7,\n          \"data_first_seen\": \"2025-05-30T04:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T18:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MANNUMBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 131.7,\n          \"data_first_seen\": \"2025-05-30T11:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MANNSF\",\n      \"name\": \"Mannum 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Stage 2 of the Mannum Solar Farm is the second project in Epic\\u2019s growing Mannum Energy Park in the Riverland region of South Australia.</p><p>The project was acquired by Epic in August 2022 from its developers Canadian Solar and is now under construction, with operations expected to commence in late 2023.</p><p>Stage 2 will operate independently of Epic\\u2019s initial Mannum Solar Farm with its own connection to SA Power Network\\u2019s distribution network and will use Trina bifacial panels and single-axis tracking system, along with Sungrow inverters.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0MANNBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0MANNBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MANNSF2\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 37.0,\n          \"data_first_seen\": \"2024-01-03T09:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MAPS2\",\n      \"name\": \"Mannum Pumping Station\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"MAPS3PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 16.5,\n          \"data_first_seen\": \"2023-03-23T13:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MAPS2PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 16.5,\n          \"data_first_seen\": \"2021-08-18T11:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MAROOWF1\",\n      \"name\": \"Maroona\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The construction of Maroona Wind Farm was completed in January 2018. It is a a two-turbine wind farm located on private farm land near the township of Maroona, approximately 18km south west of Ararat in Western Victoria. The wind farm has a capacity of 6.9MW and connects to the existing electricity network in the area. In an average year the wind farm will produce the equivalent energy usage of around 4000 households.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MAROOWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 6.8,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MARYRSF\",\n      \"name\": \"Maryrorough\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>This facility is situated about 50 kilometres west of Toowoomba, in SE Queensland, and has a generation capacity of 34.5 MWdc (27.3 MWac).</p>\",\n      \"units\": [\n        {\n          \"code\": \"MARYRSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 33.0,\n          \"data_first_seen\": \"2020-03-17T17:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MEADOWBK\",\n      \"name\": \"Meadowbank\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Meadowbank Power Station is a run-of-the-river hydroelectric power station located in the Central Highlands region of Tasmania, Australia. The power station is situated on the  Lower River Derwent catchment and is owned and operated by Hydro Tasmania.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MEADOWBK\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 40.0,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MEADOWB2\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 24.0,\n          \"emissions_factor_co2\": 0.972,\n          \"data_first_seen\": \"2016-03-31T15:30:00+10:00\",\n          \"data_last_seen\": \"2016-05-01T08:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0MREH\",\n      \"name\": \"Melbourne\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p><br/>Equis has launched the Melbourne Renewable Energy Hub (MREH), a globally significant energy storage precinct located 25km northwest of Melbourne\\u2019s commercial business district. Fully developed, MREH will be a 1.2GW/2.4GWh Battery Energy Storage System (BESS), the largest such system in Australia and Asia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0MREHL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 600.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0MREHG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 600.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MERSOLAR\",\n      \"name\": \"Merredin\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Merredin Solar Farm is the largest solar farm in Western Australia and will have an expected output of 281GWh of electricity annually, generating enough energy to power approximately 42,000 Western Australian homes.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MERSOLAR_PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 100.0,\n          \"data_first_seen\": \"2020-07-09T12:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NAMKKN_MERR\",\n      \"name\": \"Merredin\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Merredin Energy Pty Ltd (MEPL) operates an 82 MW open cycle gas turbine power station in Merredin, Western Australia. The station entered service in mid 2012 and has a minimum operating life of 30 years.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NAMKKN_MERR_SG1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 92.6,\n          \"emissions_factor_co2\": 0.8794,\n          \"data_first_seen\": \"2013-12-17T19:00:00+10:00\",\n          \"data_last_seen\": \"2025-04-15T18:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"AMBRISOLAR\",\n      \"name\": \"Metro\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"AMBRISOLAR_PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 0.96,\n          \"data_first_seen\": \"2018-09-26T08:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"METZSF\",\n      \"name\": \"Metz N\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Metz Solar Farm is a 135MW solar farm located 15km from Armidale</p>\",\n      \"units\": [\n        {\n          \"code\": \"METZSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 135.0,\n          \"data_first_seen\": \"2022-03-29T09:20:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:10:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MIDDLSF1\",\n      \"name\": \"Middlemount\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Middlemount Sun Farm development site is located around 1km east from the town of Middlemount in central Queensland.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MIDDLSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"2020-12-10T12:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MIDLDPS\",\n      \"name\": \"Midlands\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"MIDLDPS1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 6.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MILLMERN\",\n      \"name\": \"Millmerran\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Millmerran Power Station is a coal-fired power station south of Millmerran in the Darling Downs region of Queensland, Australia. The power station was commissioned in 2002 and cost $1.5 billion to build.  The power station is owned and operated by InterGen, a multinational company owned by the Ontario Teachers&#x27; Pension Plan and AIG Highstar Capital II, a private equity fund sponsored by a subsidiary of American International Group, Inc.The plant takes advantage of the abundant deposits of bituminous coal from the Surat Basin. Fuel is transported via conveyor belt from the open-cut Commodore Mine.Water is supplied via pipeline from the Wetalla sewage treatment plant in Toowoomba. The 850 MW plant uses air cooling technology to reduce water consumption. In 2002, when the plant became operational, wholesale prices for electricity fell by about one third to $20/MWh. This was due to the market strategy to bid at short run marginal cost - so with high efficiency plant and cheap coal, this had a significant impact on the market.<br/>Millmerran Power Station which won the Banksia Environmental Award 2006 in the water category, supplies enough electricity to power approximately 1.1 million homes by selling all its electricity into the National Electricity Market (NEM).Carbon Monitoring for Action estimates this power station emits 5.75 million tonnes of greenhouse gases each year as a result of burning coal. The Australian Government has announced the introduction of a Carbon Pollution Reduction Scheme commencing in 2010 to help combat climate change. It is expected to impact on emissions from power stations. The National Pollutant Inventory provides details of other pollutant emissions, but, as at 23 November 2008, not CO2.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MPP_2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 426.0,\n          \"emissions_factor_co2\": 0.8373,\n          \"data_first_seen\": \"2003-01-01T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MPP_1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 426.0,\n          \"emissions_factor_co2\": 0.8373,\n          \"data_first_seen\": \"2001-11-09T20:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MINTARO\",\n      \"name\": \"Mintaro\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"MINTARO\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 90.0,\n          \"emissions_factor_co2\": 0.8589,\n          \"data_first_seen\": \"1998-12-08T08:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MINTNL1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"emissions_factor_co2\": 0.8589,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ATLAS\",\n      \"name\": \"Mirrabooka\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"ATLAS\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.23,\n          \"emissions_factor_co2\": 0.057,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2018-07-31T07:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MOKOSF\",\n      \"name\": \"Mokoan\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Mokoan Solar Farm project consists of a 53MWdc solar farm and battery energy storage system (BESS). The solar project is made up of two separate sites Mokoan and the expansion site, located on Lee Road and Nelson Road, Winton, in the Hume Region of Victoria.</p><p>The Mokoan Solar Farm received development approval from Benalla Rural City Council in December 2018. The Mokoan Expansion site received development approval from the Victorian Department of Environment, Land, Water and Planning in June 2020. The solar farm covers 94 hectares of land, which has been predominantly used for grazing.</p><p><br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"MOKOSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 58.0,\n          \"data_first_seen\": \"2024-12-16T11:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MOLNGSF1\",\n      \"name\": \"Molong\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p><br/>The Molong Solar farm is a 30 MWac Solar Farm located in the central west region of NSW, just north west of Orange.</p><p>The site was developed by Terrain Solar and was acquired by TEC-C Investments in November 2017 and is now owned by AMP Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MOLNGSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 36.0,\n          \"data_first_seen\": \"2020-11-10T06:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MOORAWF1\",\n      \"name\": \"Moorabool\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Project consists of 104 wind turbines located approximately 25km south east of Ballarat.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MOORAWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 312.0,\n          \"data_first_seen\": \"2020-11-19T10:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MORANBAH\",\n      \"name\": \"Moranbah\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Moranbah Power Station was constructed to supply power to Arrow Energy to operate their gas compressors. Arrow has subsequently sold its interest to Queensland Pacific Metals (QPM).<br/><br/>The Moranbah Power Station utilises the coal seam methane from the Bowen Basin to provide electricity to QPM with the ability to export 50% of it\\u2019s capacity to the grid.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MORANBAH\",\n          \"fueltech_id\": \"gas_recip\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 12.56,\n          \"emissions_factor_co2\": 0.5601,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MBAHNTH\",\n      \"name\": \"Moranbah North\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>EDL owns and operates the 67MW Moranbah North Power Station, which captures and combusts waste coal mine gas and converts it to electricity for the national electricity market.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MBAHNTH\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 63.42,\n          \"emissions_factor_co2\": 0.6378,\n          \"data_first_seen\": \"2014-10-21T01:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MOREESF\",\n      \"name\": \"Moree\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Moree Solar Farm is a 56MW photovoltaic solar plant located about 10km south of Moree in New South Wales, Australia.<br/><br/>The plant was one of the largest solar power plants in Australia at the time of its construction and the first that utilises mechanical devices (trackers) to continually orient its solar panels with the sun to increase their power output each day.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MOREESF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 57.0,\n          \"data_first_seen\": \"2016-02-22T09:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MWPS\",\n      \"name\": \"Morganwhyalla Pipeline\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Commencing in 2019, the pumping stations are being fitted with solar panel arrays to reduce the cost of pumping water. The first of these was commissioned at Pumping Station Number 3 near Geranium Plains. The second will be at Pumping Station number 4 near Robertstown. The ground under the solar panel arrays will be planted with native grasses and ground covers to suppress dust.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MWPS1PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.0,\n          \"data_first_seen\": \"2021-03-18T10:35:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MWPS2PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.0,\n          \"data_first_seen\": \"2021-03-16T12:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MWPS3PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.0,\n          \"data_first_seen\": \"2020-11-13T16:25:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:35:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MWPS4PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.0,\n          \"data_first_seen\": \"2021-03-01T10:40:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:40:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0MORNBESS\",\n      \"name\": \"Mornington\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Scheduled for completion in 2025, Mornington BESS is a utility-scale Battery Energy Storage System (BESS) located in Victoria\\u2019s Mornington Peninsula.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0MORNBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 240.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0MORNBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 240.0,\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MORNW\",\n      \"name\": \"Mornington Disposal\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"MORNW\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.06,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0MRTLKBESS\",\n      \"name\": \"Mortlake\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Origin has approved construction of a large-scale battery at our Mortlake Power Station with a capacity of 300MW, that is expected to deliver output of up to 650MWh.</p><p>Mortlake is Victoria\\u2019s largest gas-fired generator, with a generation capacity of 566MW.</p><p>Located adjacent to the Moorabool to Heywood 500kv transmission line, the power station also sits within Victoria\\u2019s South-West Renewable Energy Zone (REZ). Western Victoria is already home to several operating renewable energy generators, and further new renewable energy developments are expected within the South-West REZ.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0MRTLKBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 300.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0MRTLKBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 300.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MORTLK\",\n      \"name\": \"Mortlake\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Mortlake Power Station is a 566 MW open cycle gas-fired power station developed by Origin Energy, located 12 km west of Mortlake, Victoria.Construction of the $640 million power station began in 2008. It was initially due to be operational in 2010, and was completed in August 2012.The plant is located on approximately 20 hectares of land with an extensive buffer zone around it. Although approvals were gained for approximately 1,000 MW, the Mortlake Power Station was built to provide 566MW. It is adjacent to the existing Moorabool to Heywood 500 kV high voltage transmission line. The plant is supplied with natural gas via an 83 km dedicated underground natural gas transmission pipeline from the Otway Gas Plant near Port Campbell, as part of the offshore Otway Gas Project.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MORTLK12\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 283.0,\n          \"emissions_factor_co2\": 0.5518,\n          \"data_first_seen\": \"2011-09-23T17:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-17T20:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MORTLK11\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 283.0,\n          \"emissions_factor_co2\": 0.5518,\n          \"data_first_seen\": \"2011-08-01T15:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T21:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MRTLSWF\",\n      \"name\": \"Mortlake South\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>ACCIONA&#x27;s fifth wind farm in Australia, with 157.5 MW of power and battery storage. The wind farm is being constructed on cleared open and level land that is predominantly used for dairy farming.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MRTLSWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 157.5,\n          \"data_first_seen\": \"2022-10-25T18:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MLWF\",\n      \"name\": \"Mortons Lane\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Mortons Lane Wind Farm consists of 13 Goldwind GW82/1500 wind turbines with generating capacity up to 19.5 megawatts. The wind farm generates approximately 63.69 GWh of clean electricity which is enough to power more than 12,738 households in Victoria and reduce up to 68,148 t CO2 annually. In April 2021, Prime Super, a leading Australian superannuation fund, acquired Mortons Lane. Prime Super\\u2019s investment in the project will be managed by PATRIZIA.</p><p>The Moyne and Southern Grampians Shires granted planning approval for the proposed Mortons Lane wind farm in June 2007 and the project commenced operations in late 2012 and is expected to operate until 2035, at which point the project may be extended through a repowering or asset life extension. Mortons Lane is proud to support Victoria\\u2019s transition to clean energy production.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MLWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 19.5,\n          \"data_first_seen\": \"2012-11-13T14:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SKYFRM_MTBARKER\",\n      \"name\": \"Mount Barker\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Mt Barker Windfarm was commissioned in March of 2011. The project consists of three 800kW E53 Enercon wind turbines are on a hill on a private sheep farm 4 km north of Mt Barker on the western side of Albany Highway. These wind turbines are bigger than those in Esperance but smaller than those in Albany. As Mt Barker is inland, they are on 73m high towers. The project cost was about $8.5 million in total.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SKYFRM_MTBARKER_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.43,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MOUSF\",\n      \"name\": \"Moura\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Moura Solar Farm is a 110MW project located 6.5km south west of the township of Banana, Queensland.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MOUSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 99.0,\n          \"data_first_seen\": \"2022-10-21T13:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MEWF\",\n      \"name\": \"Mt Emerald\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Mount Emerald Wind Farm is a 180 MW wind farm situated on Mount Emerald, in Arriga, Shire of Mareeba, Queensland, Australia. It is approximately 8 km WNW of Tolga, and 49 km SW of Cairns. The project is a joint venture between Port Bajool (land owner) and RATCH-Australia (wind farm developer and operator). RATCH-Australia bought the project from Transfield Services in July 2011. The wind farm incorporates 53 turbines.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MEWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 180.0,\n          \"data_first_seen\": \"2018-08-20T14:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MTGELWF\",\n      \"name\": \"Mt Gellibrand\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>ACCIONA Energ\\u00eda&#x27;s fourth wind farm in Australia, fully operational since August 2018. The Mt Gellibrand Wind Farm has a capacity of 132 MW and will produce enough clean energy to power some 90,000 Australian homes.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MTGELWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 137.98,\n          \"data_first_seen\": \"2018-06-21T16:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MTMERCER\",\n      \"name\": \"Mt Mercer\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Mount Mercer Wind Farm is located at Mount Mercer approximately 30 kilometres south of Ballarat in Western Victoria on 2600ha. The wind farm consists of 64 REpower MM92 wind turbines, giving a total installed capacity of 131 MW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MERCER01\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 131.0,\n          \"data_first_seen\": \"2013-11-25T14:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MTMILLAR\",\n      \"name\": \"Mt Millar\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Mt Millar Wind Farm was the first wind farm in South Australia to use Enercon E-70 2MW direct drive turbines (don&#x27;t have gearboxes). It connects to ElectraNet\\u2019s existing transmission network at Yadnarie Substation, via a 33 km 132 kV overhead transmission line and substation.</p><p>Construction of this wind farm started in late 2004 and was completed in December 2005. Power production started in February 2006. The $130 million project was developed by Tarong Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MTMILLAR\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 70.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MP\",\n      \"name\": \"Mt Piper\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Mt Piper was originally built in the 1980s, then stored in near fully assembled state, before being commissioned in 1992 and 1993 (Units 2 and 1 respectively). While initially constructed as 660MW machines, both were upgraded to 700MW in 2009, with Unit one upgraded in 2023 to 730MW, using modern turbine technology, bringing the station total to 1430MW. Importantly, the minimum generation of these units has also been lowered to facilitate the modern requirements of lower minimum generation rates to better match the shape of renewables.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MP2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 700.0,\n          \"emissions_factor_co2\": 0.8691,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MP1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 730.0,\n          \"emissions_factor_co2\": 0.8691,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MSTUART\",\n      \"name\": \"Mt Stuart\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Mount Stuart Power Station is a power station located in Stuart, Townsville, Australia. The station runs on kerosene with three gas turbines that generate a combined capacity of 414 MW of electricity. Mount Stuart was commissioned in December 1998, and operates as a peaking plant. It currently runs on kerosene, but can be converted to natural gas.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MSTUART1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 144.0,\n          \"emissions_factor_co2\": 1.0498,\n          \"data_first_seen\": \"1998-12-14T12:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-15T20:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MSTUART3\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 131.0,\n          \"emissions_factor_co2\": 1.0498,\n          \"data_first_seen\": \"2009-10-16T13:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-16T20:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MSTUART2\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 144.0,\n          \"emissions_factor_co2\": 1.0498,\n          \"data_first_seen\": \"1998-12-23T10:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-02T07:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MLLFGEF\",\n      \"name\": \"Mugga Lane\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>LGI designed, built and operates the new 6MW power station, commissioned in June 2020 with 4MW and expanded in 2024 by 50% with a 20MW grid connection. It is currently being upgraded to include a 12MW battery energy storage system (BESS).</p>\",\n      \"units\": [\n        {\n          \"code\": \"MLLFGEF1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.26,\n          \"emissions_factor_co2\": 0.1175,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MLSP\",\n      \"name\": \"Mugga Lane\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Mugga Lane Solar Park is a photovoltaic solar power station at Hume in the Australian Capital Territory.</p><p>Construction of the Mugga Lane Solar Park at Mugga Lane was completed in March 2017. It is owned by the Maoneng Group, which has been contracted by the Government of the Australian Capital Territory to produce up to 24,600 megawatt hours each year for up to $4.38 million.</p><p>The Mugga Lane Solar Park uses sheep for grass and weed control under the solar panels.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MLSP1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 12.0,\n          \"data_first_seen\": \"2016-11-16T15:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MUJA_AB\",\n      \"name\": \"Muja AB\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Muja AB is a retired coal plant with 4x 60MW units.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MUJA_M2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"emissions_factor_co2\": 0.9459,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MUJA_M1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"emissions_factor_co2\": 0.9459,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MUJA_M3\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"emissions_factor_co2\": 0.9459,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MUJA_M4\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"emissions_factor_co2\": 0.9459,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MUJA\",\n      \"name\": \"Muja CD\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Muja Power Station is a power station 22\\u00a0km (14\\u00a0mi) east of Collie, Western Australia. It has eight steam turbines served by coal-fired boilers that together generate a total capacity of 854 megawatts of electricity. It is the largest power station in the South West Interconnected System, accounting for roughly 15 percent of capacity</p>\",\n      \"units\": [\n        {\n          \"code\": \"MUJA_G7\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 212.6,\n          \"emissions_factor_co2\": 0.92,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MUJA_G8\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 212.6,\n          \"emissions_factor_co2\": 0.92,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MUJA_G5\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 195.8,\n          \"emissions_factor_co2\": 0.92,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2022-09-29T10:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MUJA_G6\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 193.6,\n          \"emissions_factor_co2\": 0.92,\n          \"data_first_seen\": \"2013-12-18T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-04-02T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MWF_MUMBIDA\",\n      \"name\": \"Mumbida\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Mumbida Wind Farm is a 55 MW renewable energy project that was developed by joint venture partners Synergy and Infrastructure Capital Group (ICG). Construction of Mumbida was completed in 2013.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MWF_MUMBIDA_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 55.0,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MUNGARRA\",\n      \"name\": \"Mungarra\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Mungarra Power Station is a power station 50 km south-east of Geraldton, Western Australia. It is natural gas powered with three gas turbines that together generate a total capacity of 112 MW of electricity.<br/>The station was commissioned in 1990.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MUNGARRA_GT1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 39.5,\n          \"emissions_factor_co2\": 0.8919,\n          \"data_first_seen\": \"2014-01-12T09:30:00+08:00\",\n          \"data_last_seen\": \"2025-07-03T13:05:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MUNGARRA_GT2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 39.5,\n          \"emissions_factor_co2\": 0.8919,\n          \"data_first_seen\": \"2013-12-18T08:00:00+08:00\",\n          \"data_last_seen\": \"2018-09-03T20:00:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MUNGARRA_GT3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 38.0,\n          \"emissions_factor_co2\": 0.8919,\n          \"data_first_seen\": \"2013-12-18T08:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-05T14:30:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MM\",\n      \"name\": \"Munmorah\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Munmorah Power Station is a demolished coal fired electricity power station with four 350 MW English Electric steam driven turbo-alternators for a combined capacity of 1,400 MW. The station was located near Doyalson, on the shores of Lake Munmorah, New South Wales, Australia and was owned and operated by Delta Electricity, a company owned by the New South Wales Government.<br/>In July 2012 the coal-fired generators were permanently retired from service. However, the nearby gas-fired Colongra power station, which was commissioned in 2009, remains in operation.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MM3\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 300.0,\n          \"emissions_factor_co2\": 1.163,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2011-07-04T14:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MM4\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 300.0,\n          \"emissions_factor_co2\": 1.163,\n          \"data_first_seen\": \"2000-02-28T10:10:00+10:00\",\n          \"data_last_seen\": \"2011-07-04T14:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0MUNNACRKSF\",\n      \"name\": \"Munna Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The proposed site includes the construction, operation, maintenance, upgrading and eventual decommissioning of a solar farm located approximately about 19 km from Woolooga and 40 km north-west from Gympie in the QLD Fraser Coast region.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0MUNNACRKSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 154.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MUWAWF\",\n      \"name\": \"Murra Warra\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Murra Warra Wind Farm will be one of Australia&#x27;s largest wind farms. Located on the plains of north-western Victoria, approximately 25 kilometres (16 mi) north of the city of Horsham, it will consist of 99 wind turbines with a maximum tip height of 220m.<br/>The project is expected to produce more than 1800 GWh annually, enough electricity to power about 420,000 average Victorian homes each year, displacing up to 1.7 million tonnes of greenhouse gas emissions each year. The project was developed by a joint venture between RES Group and Macquarie Capital and was sold in two stages to Partners Group in September 2018 and August 2020,</p>\",\n      \"units\": [\n        {\n          \"code\": \"MUWAWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 209.0,\n          \"data_first_seen\": \"2022-02-15T01:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MUWAWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 231.8,\n          \"data_first_seen\": \"2019-04-08T19:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MURRAY\",\n      \"name\": \"Murray\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Murray Region Hydroelectric Power Stations refers to two of the original seven hydroelectric power stations, both located near the town of Khancoban in the Snowy Mountains region of New South Wales, Australia. The two power stations are part of the Snowy Mountains Scheme, a vast hydroelectricity and irrigation complex constructed in south-east Australia between 1949 and 1974 and now run by Snowy Hydro. Although both power stations are physically located in New South Wales, since 1 July 2008 all power generated has been allocated to the Victorian region of the National Electricity Market.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MURRAY\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1500.0,\n          \"data_first_seen\": \"2001-07-15T00:40:00+08:00\",\n          \"data_last_seen\": \"2025-07-20T22:10:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MBPS2\",\n      \"name\": \"Murray Bridge-Onkaparinga\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"MBPS2PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 13.0,\n          \"data_first_seen\": \"2022-03-08T10:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"MUSSELRO\",\n      \"name\": \"Musselroe\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Musselroe Wind Farm is a wind farm at Cape Portland, Tasmania, Australia. It is third wind farm in the state, being owned and operated by Hydro Tasmania. It consists of 56 Vestas V90-3MW wind turbines, with a generating capacity of 168 MW. The energy output from the Musselroe Wind Farm will be sufficient to supply electricity to around 50,000 households and abate 450,000 tonnes of CO2 emissions annually.The first 37 turbines have been connected to the grid in 2013, and the full farm was completed in January 2014.</p>\",\n      \"units\": [\n        {\n          \"code\": \"MUSSELR1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 168.0,\n          \"data_first_seen\": \"2013-03-21T15:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NASF\",\n      \"name\": \"Narromine\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Dubbo Solar Hub is a renewable electricity project that consists of two separate solar farm sites at South Keswick &amp; Narromine.</p><p>The 28 MW Dubbo Solar Hub is one of the first projects completed by Neoen in Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NASF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NEWGEN_NEERABUP\",\n      \"name\": \"Neerabup\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Neerabup Power Station is situated on the northern outskirts of Perth, Western Australia near the locality of Pinjar and the Pinjar Power Station. It is powered by natural gas, and has a total electrical generation capacity of 330 MW and includes a 30 km high-pressure gas linepack pipeline connected to the Dampier to Bunbury Natural Gas Pipeline.<br/>The station was commissioned in October 2009.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NEWGEN_NEERABUP_GT1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 342.0,\n          \"emissions_factor_co2\": 0.6881,\n          \"data_first_seen\": \"2013-12-17T09:30:00+08:00\",\n          \"data_last_seen\": \"2025-07-19T19:45:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NEVERSF\",\n      \"name\": \"Nevertire\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Nevertire Solar Farm Solar Farm is located approximately 100km north west of Dubbo, NSW. It is connected to the 132kV Essential Energy network at the onsite Nevertire substation.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NEVERSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 132.0,\n          \"data_first_seen\": \"2019-12-03T07:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NEWENSF\",\n      \"name\": \"New England\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The New England Solar and battery project will be Australia\\u2019s largest hybrid solar and battery energy storage facility. The 720 megawatt (MW) solar farm will be located across two solar fields near Uralla, NSW in the New England Renewable Energy Zone.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NEWENSF2\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 235.0,\n          \"data_first_seen\": \"2022-12-20T11:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"NEWENSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 235.0,\n          \"data_first_seen\": \"2023-04-18T08:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0NEWENBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 200.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0NEWENBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 200.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NEWGEN_KWINANA\",\n      \"name\": \"Newgen Kwinana\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Situated just 30km south of Perth, the NewGen Power Kwinana station stands as one of Western Australia\\u2019s most advanced and efficient intermediate load power stations, providing energy to the South West Interconnected System (SWIS) since 2008.</p><p>Leveraging low-emission technologies, the power station actively reduces greenhouse gas emissions and engages in best water efficiency practices through filtration and recycling systems.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NEWGEN_KWINANA_CCG1\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 327.8,\n          \"emissions_factor_co2\": 0.3998,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NEWPORT\",\n      \"name\": \"Newport\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Newport Power Station was a complex of power stations located on the west bank of the Yarra River, approximately 6 km south-west of Melbourne, Victoria, Australia, in the suburb of Newport. Newport A, B, and C were coal-fired plants which operated at the site between 1919 and the 1980s, and were claimed to be (in terms of the amount of plant) the largest power station in the southern hemisphere in 1953 with 42 boilers and 14 turbo-alternators producing 327 megawatts (439,000 hp).<br/>Newport D is a gas-fired peaking power plant which has operated since 1981. It uses natural gas to generate steam in a boiler which supplies a three-stage steam turbine coupled to a generator to produce up to 510 MW (680,000 hp) of electricity. The plant has a single smokestack 183 m /600 ft in height which towers over the local vicinity.<br/>The power station is owned by Ecogen Energy. The output from Ecogen&#x27;s Newport and Jeeralang power stations is currently contracted to EnergyAustralia, the country&#x27;s third-biggest electricity and gas retailer.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NPS\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 500.0,\n          \"emissions_factor_co2\": 0.543,\n          \"data_first_seen\": \"1998-12-07T11:15:00+08:00\",\n          \"data_last_seen\": \"2025-07-18T00:20:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NBHWF\",\n      \"name\": \"North Brown Hill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The North Brown Hill Wind Farm at Hallett, South Australia consists of 63 wind turbine generators with a total capacity of 132.3-megawatts. It is owned by EII2, in which APA has a 20.2% interest with ICG (39.9%) and Osaka Gas Company Ltd (39.9%). The wind farm has a long-term offtake arrangement with AGL Energy for both the electricity generated and the renewable energy credits produced.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NBHWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 132.0,\n          \"data_first_seen\": \"2010-08-14T20:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NORTHAM_SF\",\n      \"name\": \"Northam\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Northam Solar Farm is located on Ballardong Noongar Boodja (country), on the outskirts of the historic wheatbelt town of Northam approximately 100 km from Perth. The 10MW Northam Solar Farm consists of 33,600 solar panels and is constructed over 25 hectares (around 0.25 km2). The solar farm provides renewable, sustainable, zero emission, electricity, powered by Western Australia\\u2019s Wheatbelt sunshine.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NORTHAM_SF_PV1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"data_first_seen\": \"2018-11-15T09:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-17T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TESLA_NORTHAM\",\n      \"name\": \"Northam\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Commissioned in 2012, Northam is located in Grass Valley east of Northam.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TESLA_NORTHAM_G1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"emissions_factor_co2\": 0.97,\n          \"data_first_seen\": \"2014-02-21T10:30:00+08:00\",\n          \"data_last_seen\": \"2025-06-25T12:25:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NORTHGT\",\n      \"name\": \"Northern\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"NGTS\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1998-12-07T11:45:00+08:00\",\n          \"data_last_seen\": \"2001-04-11T12:00:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NORTHP\",\n      \"name\": \"Northern\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Northern Power Station was located at Port Paterson in the Australian state  of South Australia about 6 kilometres (3.7 mi) south of the city centre of Port Augusta. It was coal powered with two 260 MW steam turbines that generated a total of 520 MW of electricity. It was operated and maintained by Alinta Energy and was commissioned in 1985. Northern received coal by rail from the Leigh Creek Coal Mine, 280 km to the north. The plant ceased electricity production in May 2016 and decommissioned and demolished over the following few years.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NPS1\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 265.0,\n          \"emissions_factor_co2\": 1.1306,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2016-05-09T10:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"NPS2\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 265.0,\n          \"emissions_factor_co2\": 1.1306,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2016-05-05T23:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"NPSNL1\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 100.0,\n          \"emissions_factor_co2\": 1.1306,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"NPSNL2\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 100.0,\n          \"emissions_factor_co2\": 1.1306,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NUMURKSF\",\n      \"name\": \"Numurkah\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Numurkah Solar Farm is a solar photovoltaic power station near the town of Numurkah in the Australian state of Victoria.<br/>At its commissioning in 2019, Numurkah was the largest solar farm in Victoria. It cost A$198 million and generates up to 112MWp of AC electricity (installed 128MW DC). It is a leader in harnessing clean energy and retaining the use of farmland via sheep agistment (Agri-Solar). It presently runs upward of 1600 sheep over its 1200 acres. Its primary customers are the Melbourne tram network and Laverton steel works under a power purchase agreement, despite many believing the power goes to these locations directly, the site puts power into the local grid. The Laverton steel works is a scrap iron recycler owned by the GFG Alliance.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NUMURSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 112.0,\n          \"data_first_seen\": \"2019-05-07T07:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NYNGAN\",\n      \"name\": \"Nyngan\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Nyngan Solar Plant or Farm is one of the largest operating solar plants in Australia.  At the time of construction, it was the largest solar plant in the southern hemisphere. It is located 10 km west of Nyngan in western New South Wales. It is was built and is operated by AGL Energy.<br/>It has over 1.3 million solar panels, generating 102 megawatts of power.  It was opened on 18 April 2015, and became fully operational in July 2015. The Nyngan Solar Plant is associated with the Broken Hill Solar Plant, a 53 megawatt farm located almost 600 km west, which became operational in December 2015,, making the total capacity of the combined plants 155 megawatts. The solar panels do not track the movement of the sun. They are arranged in rows facing north, tilted at 25 degrees.</p>\",\n      \"units\": [\n        {\n          \"code\": \"NYNGAN1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 102.0,\n          \"data_first_seen\": \"2015-03-21T14:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"OAKEY\",\n      \"name\": \"Oakey\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Oakey Power Station is a 332 MW power station located at Oakey on the Darling Downs in southern Queensland, adjacent to the Roma to Brisbane Pipeline. The station is an open-cycle, dual liquid/gas-fired power station that typically operates during times of peak electricity demand when Queensland&#x27;s power needs are greatest. ERM Power led the development of Oakey with commissioning occurring safely and on time in December 1999. ERM Power owns 100% of Oakey and also operates and financially manages the power station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"OAKEY2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 141.0,\n          \"emissions_factor_co2\": 0.6356,\n          \"data_first_seen\": \"1999-11-20T22:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T19:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"OAKEY1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 141.0,\n          \"emissions_factor_co2\": 0.6356,\n          \"data_first_seen\": \"1999-09-26T13:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-15T19:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"OAKEY1SF\",\n      \"name\": \"Oakey\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Oakey 1 Solar Project is a 25 MW solar generation development located near Oakey, West of Toowoomba in Queensland. The generating plant connects to the Ergon Energy network near Toowoomba. The technology is solar photovoltaic panels mounted on solar tracking structures which will maximize production of energy throughout the day. The solar farm has a total of 88,200 panels (335Wp and 340Wp).</p><p>The above PV modules make up a total nameplate capacity of 30 MWdc and the project has a connection agreement with Ergon Energy to export up to 25 MWac. The project is capable of generating approximately 55 GWh of electricity in a calendar year.</p>\",\n      \"units\": [\n        {\n          \"code\": \"OAKEY1SF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"2019-03-13T08:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"OAKEY2SF\",\n      \"name\": \"Oakey 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Oakey 2 Solar Project is a 55 MW solar generation development located near Oakey, West of Toowoomba in Queensland. The generating plant connects to the Ergon Energy network near Toowoomba. The technology is solar photovoltaic panels mounted on solar tracking structures which will maximize production of energy throughout the day.</p>\",\n      \"units\": [\n        {\n          \"code\": \"OAKEY2SF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 65.0,\n          \"data_first_seen\": \"2019-09-13T06:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"OAKLAND\",\n      \"name\": \"Oaklands Hill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The $200m Oaklands Hill Wind Farm is located on 2,323 hectares of freehold agricultural land 3 km south of Glenthompson, in the shire of Southern Grampians in Western Victoria.</p><p>Suzlon Energy Australia Pty Ltd (SEA) was awarded the Engineer Procure &amp; Construct (EPC) contract \\u2013 they installed 32 Suzlon S88 turbines with a capacity of 2.1 MW each. Suzlon are also responsible for the ongoing maintenance of the site.</p>\",\n      \"units\": [\n        {\n          \"code\": \"OAKLAND1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 67.0,\n          \"data_first_seen\": \"2011-08-25T12:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"OCPS\",\n      \"name\": \"Oaky Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>EDL owns and operates the Oaky Creek I and II Power Stations, which capture and combust waste coal mine gas and convert it to electricity for the National Electricity Market.</p>\",\n      \"units\": [\n        {\n          \"code\": \"OAKYCREK\",\n          \"fueltech_id\": \"gas_recip\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 20.0,\n          \"emissions_factor_co2\": 0.519,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"OAKY2\",\n      \"name\": \"Oaky Creek 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>EDL owns and operates the Oaky Creek I and II Power Stations, which capture and combust waste coal mine gas and convert it to electricity for the National Electricity Market.</p>\",\n      \"units\": [\n        {\n          \"code\": \"OAKY2\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 15.0,\n          \"emissions_factor_co2\": 0.568,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"OSBORNE\",\n      \"name\": \"Osborne\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Osborne Power Station is located in Osborne, a northwestern suburb of Adelaide, South Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"OSB-AG\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 180.0,\n          \"emissions_factor_co2\": 0.4144,\n          \"data_first_seen\": \"2000-02-15T14:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T22:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"OSB01\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 120.0,\n          \"emissions_factor_co2\": 0.5447,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2000-02-16T00:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"OSB02\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"emissions_factor_co2\": 0.5447,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2000-02-16T00:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PALOONA\",\n      \"name\": \"Paloona\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Paloona Power Station is a conventional hydroelectric power station located in northern Tasmania, Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PALOONA\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 28.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PSF\",\n      \"name\": \"Parkes\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Initial development started in 2013 with the land lease signed in November 2013. Government Planning Approvals was achieved in June 2014. Construction started in Jan 2017 and was completed in April 2018. It has been operational ever since.</p><p>Parkes Solar Farm is one of 12 successful projects that received funding from the Australian Renewable Energy Agency (ARENA) in 2016.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PARSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 55.0,\n          \"data_first_seen\": \"2018-02-02T18:35:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PRK_AG\",\n      \"name\": \"Parkeston\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The simple-cycle Parkeston power plant was developed to provide low-cost electricity to gold mining operations in the surrounding region. TransAlta co-owns the plant, which is located in Kalgoorlie, Western Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PRK_AG\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 110.0,\n          \"emissions_factor_co2\": 0.5813,\n          \"data_first_seen\": \"2013-12-18T07:00:00+10:00\",\n          \"data_last_seen\": \"2025-05-27T20:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PEDLER\",\n      \"name\": \"Pedler Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"PEDLER1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 3.0,\n          \"emissions_factor_co2\": 0.06,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NPPPPS\",\n      \"name\": \"Pelican Point\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Pelican Point Power Station is located at Pelican Point, 20 km from the centre of Adelaide, South Australia on the Lefevre Peninsula. It is operated by Engie (previously known as GDF Suez Australian Energy), which owns 72 per cent of the power station. Mitsui owns the remaining 28 per cent. It burns natural gas in a combined cycle power station, comprising two 160 MW gas turbines and one 165 MW steam turbine, to generate up to 485 MW of electricity.Construction began in 1999. The plant has two GT13E2 gas turbines manufactured by ABB (now Alstom). The plant, including steam turbine and heat recovery steam generator (HRSG), was manufactured and constructed by ABB.<br/>Fuel is supplied via either the SEAGas pipeline, which runs from the Iona Gas Plant in Victoria to the Pelican Point power station, or the Moomba Adelaide Pipeline System (MAPS), which supplies gas from Moomba to Adelaide.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PPCCGT\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 478.0,\n          \"emissions_factor_co2\": 0.4018,\n          \"data_first_seen\": \"2000-09-11T18:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PIBESS\",\n      \"name\": \"Phillip Island\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The $10 million Phillip Island Community Energy Storage System (PICESS) is the first of its kind on the island. Mondo, working with project delivery partner TEC-C, built the battery on behalf of AusNet to provide the community of Phillip Island with a battery that will provide energy support during peak periods.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PIBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.0,\n          \"data_first_seen\": \"2023-04-19T09:10:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PIBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.0,\n          \"data_first_seen\": \"2023-04-19T08:25:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+08:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PHOENIX_KWINANA_WTE\",\n      \"name\": \"Phoenix\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>This Phoenix Energy development (now owned by Avertas Energy) will be a leader in integrating the disposal of waste with the generation of renewable energy to provide a practical solution to two community challenges: the disposal of significant quantities of household rubbish and establishing additional (baseload) renewable energy supplies for the community. As such, the project is a unique and important renewable energy project for Western Australia and Australia, as it will be the first Waste to Energy (WtE) facility of its kind constructed in Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PHOENIX_KWINANA_WTE_G1\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 38.0,\n          \"data_first_seen\": \"2025-04-09T10:25:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TESLA_PICTON\",\n      \"name\": \"Picton\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Commissioned in 2011, Picton is located in Picton East less than 3km from the centre of Bunbury.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TESLA_PICTON_G1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"emissions_factor_co2\": 0.97,\n          \"data_first_seen\": \"2014-03-07T14:30:00+08:00\",\n          \"data_last_seen\": \"2025-06-21T11:00:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PINDARI\",\n      \"name\": \"Pindari\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Pindari Hydroelectric Power Station was commissioned in April 2002, and is located on the Pindari Dam, near Inverell, on the Severn River in northern NSW. The station comprises two horizontal Francis turbines and has a capacity of 5.7 MW. Pindari Power Station typically generates on summer irrigation and flood mitigation flows.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PINDARI\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.7,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PINJAR\",\n      \"name\": \"Pinjar\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Pinjar Power Station is a power station in Pinjar, on the northern outskirts of Perth, Western Australia and near the locality of Neerabup and the recently commissioned Neerabup Power Station. It is natural gas-powered with nine gas turbines that together generate a total capacity of 576 MW of electricity. Although the power station primarily burns natural gas, it can also burn diesel fuel.<br/>The station was commissioned in 1989. It is used as a peaking power plant.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PINJAR_GT7\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 39.3,\n          \"emissions_factor_co2\": 0.933,\n          \"data_first_seen\": \"2013-12-21T14:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-15T09:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PINJAR_GT5\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 39.3,\n          \"emissions_factor_co2\": 0.933,\n          \"data_first_seen\": \"2014-01-20T13:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T10:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PINJAR_GT1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 38.5,\n          \"emissions_factor_co2\": 0.933,\n          \"data_first_seen\": \"2014-01-08T13:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-19T20:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PINJAR_GT4\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 39.3,\n          \"emissions_factor_co2\": 0.933,\n          \"data_first_seen\": \"2014-01-20T15:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PINJAR_GT11\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 130.0,\n          \"emissions_factor_co2\": 0.933,\n          \"data_first_seen\": \"2013-12-21T16:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PINJAR_GT3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 39.3,\n          \"emissions_factor_co2\": 0.933,\n          \"data_first_seen\": \"2013-12-21T17:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-08T19:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PINJAR_GT10\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 118.2,\n          \"emissions_factor_co2\": 0.933,\n          \"data_first_seen\": \"2013-12-20T16:00:00+10:00\",\n          \"data_last_seen\": \"2025-04-26T07:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PINJAR_GT2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 38.5,\n          \"emissions_factor_co2\": 0.933,\n          \"data_first_seen\": \"2014-01-08T14:00:00+10:00\",\n          \"data_last_seen\": \"2025-04-15T20:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PINJAR_GT9\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 118.2,\n          \"emissions_factor_co2\": 0.933,\n          \"data_first_seen\": \"2013-12-19T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ALINTA_PNJ\",\n      \"name\": \"Pinjarra\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Pinjarra Power Station is a natural-gas-fired power station in Western Australia. It is a 280 MW base load cogeneration power station located in Alcoa&#x27;s Pinjarra Alumina Refinery, near the town of Pinjarra, approximately 80 km south of Perth. Generated electricity is sold by Alinta Energy to contracted customers or into the Wholesale Energy Market. In addition to electricity, the power station supplies steam to Alcoa&#x27;s refinery.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ALINTA_PNJ_U2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 143.0,\n          \"emissions_factor_co2\": 0.7941,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ALINTA_PNJ_U1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 143.0,\n          \"emissions_factor_co2\": 0.7941,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PIONEER\",\n      \"name\": \"Pioneer Sugar Mill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"PIONEER\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 67.78,\n          \"emissions_factor_co2\": 0.0201,\n          \"data_first_seen\": \"2009-07-01T00:05:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PLAYF\",\n      \"name\": \"Playford B\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Playford B Power Station was located at Port Paterson in the Australian state of South Australia about  5.5 kilometres (3.4 mi) south of the city centre of Port Augusta.  It was coal powered with four 60 MW steam turbines that generated a total of 240 MW of electricity. Playford B received coal by rail from the Leigh Creek Coal Mine, 280 km to the north and drew cooling water from Spencer Gulf, returning it to the sea at an elevated temperature. Commissioned in 1963, it was co-located with the older Playford A Power Station and the larger, newer Northern Power Station. Playford B was mothballed in 2012 and its permanent closure was announced by operator Alinta Energy in October 2015. Prior to being mothballed it primarily operated in the summer, when electricity demand peaks.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PLAYFB1\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"emissions_factor_co2\": 1.509,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"1999-04-16T20:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PLAYFB2\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"emissions_factor_co2\": 1.509,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"1999-05-26T05:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PLAYFB4\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"emissions_factor_co2\": 1.509,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"1999-05-26T05:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PLAYFB3\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 60.0,\n          \"emissions_factor_co2\": 1.509,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"1999-05-25T05:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PLAYB-AG\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 240.0,\n          \"emissions_factor_co2\": 1.509,\n          \"data_first_seen\": \"1999-05-26T10:30:00+10:00\",\n          \"data_last_seen\": \"2012-02-28T13:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PTINA\",\n      \"name\": \"Poatina\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The station is underground on the northern side of\\u00a0<em>yingina</em> / Great Lake.</p><p>When Waddmana Power Station was decommissioned, Poatina replaced it in the broader power system. Poatina is ideally located, making use of a steep drop from <em>yingina</em>\\u00a0/ Great Lake down the face of the Great Western Tiers. Water that passes through Poatina is subsequently used to generate energy at Trevallyn Power Station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PO110NL1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"POAT110\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 100.0,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-17T12:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"POAT220\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 200.0,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PAREPW\",\n      \"name\": \"Port Augusta Energy Park\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Port Augusta Renewable Energy Park is a combined wind and solar farm under construction south of Port Augusta in South Australia, Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PAREPW1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 210.0,\n          \"data_first_seen\": \"2022-04-19T18:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PAREPS1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 99.0,\n          \"data_first_seen\": \"2022-10-04T17:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0PLWF\",\n      \"name\": \"Port Latta\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Port Latta Wind Farm (PLWF) is located on cattle grazing farmland in Northwest Tasmania and sits across two properties on approximately seven hectares of privately owned land.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0PLWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 21.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PORTLATT\",\n      \"name\": \"Port Latta\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Tempo</p><p>Tempo</p>\",\n      \"units\": [\n        {\n          \"code\": \"PORTLAT1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 11.0,\n          \"emissions_factor_co2\": 0.972,\n          \"data_first_seen\": \"2016-04-01T16:00:00+10:00\",\n          \"data_last_seen\": \"2016-05-23T07:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PORTLCN\",\n      \"name\": \"Port Lincoln\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"POR01\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 1.3888,\n          \"data_first_seen\": \"2000-10-06T14:40:00+10:00\",\n          \"data_last_seen\": \"2025-06-21T18:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"POR03\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 23.5,\n          \"emissions_factor_co2\": 1.3888,\n          \"data_first_seen\": \"2010-11-13T20:05:00+10:00\",\n          \"data_last_seen\": \"2025-03-12T10:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"STANVAC\",\n      \"name\": \"Port Stanvac\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Port Stanvac Power Station is a diesel-powered electricity generator in South Australia in Lonsdale, an industrial southern suburb of Adelaide. It is owned by Snowy Hydro since 2014. It consists of 36 diesel engines each generating 1.6MW for a total of 58MW of electricity to meet peak demands in the National Electricity Market.The power station was designed by Petro Min Engineers and built by Cummins Power Generation under contract from Infratil. The site had previously been used by the Lonsdale Power Station which was moved to a new site next door in 2011. Snowy Hydro bought assets from Infratil in 2014. These included Lumo Energy, Direct Connect and three diesel peaking generators for a total of 136 MW. The power stations were the Angaston Power Station along with Lonsdale and Port Stanvac.</p>\",\n      \"units\": [\n        {\n          \"code\": \"STANV2\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 58.0,\n          \"emissions_factor_co2\": 0.6749,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PTSTAN1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 57.6,\n          \"emissions_factor_co2\": 1.4918,\n          \"data_first_seen\": \"2016-01-12T17:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"STANV1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 58.0,\n          \"emissions_factor_co2\": 0.6749,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PORTWF\",\n      \"name\": \"Portland\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Portland wind farm is one of Australia&#x27;s largest wind farms. Located on the coast of south-western Victoria near the city of Portland, it consists of four separate sites, all of which have been completed as of 2015. Completion of the entire 195 MW project was expected in 2011, at a capital cost of A$330 million.<br/>The project is expected to produce more than 500 GWh annually, enough electricity to power about 125,000 homes each year, and equal to more than 7% of Victoria&#x27;s residential electricity demand, or powering a city the size of Geelong. The project is being developed by Pacific Hydro.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PORTWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 148.0,\n          \"data_first_seen\": \"2009-07-10T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"QUARANTN\",\n      \"name\": \"Quarantine\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Quarantine Power Station is a gas-powered electricity generation facility near the northern end of Torrens Island in the northwestern suburbs of Adelaide, South Australia. It is at the opposite end of Torrens Island from AGL Energy&#x27;s Torrens Island and Barker Inlet power stations. It gets its name from the Torrens Island Quarantine Station which was nearby.<br/>The power station is owned by Origin Energy and is configured as a peaking power plant. It has a capacity of 224MW produced by open cycle gas turbines. It was initially installed in 2002 with four Alstom GT10B (now designated Siemens SGT600 after Siemens bought the Alstom Medium sized GT business) turbines generating 95MW of power. It was expanded in 2007 by the addition of a new 120MW General Electric Frame 9E gas turbine set. The power station is fuelled by natural gas, delivered by the EPIC energy &amp; SEAGas pipeline.</p>\",\n      \"units\": [\n        {\n          \"code\": \"QPS4\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 24.0,\n          \"emissions_factor_co2\": 0.6336,\n          \"data_first_seen\": \"2001-12-20T10:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T20:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"QPS5\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 128.0,\n          \"emissions_factor_co2\": 0.6336,\n          \"data_first_seen\": \"2009-02-10T17:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"QPS1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 29.0,\n          \"emissions_factor_co2\": 0.6336,\n          \"data_first_seen\": \"2001-11-24T14:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"QPS3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 24.0,\n          \"emissions_factor_co2\": 0.6336,\n          \"data_first_seen\": \"2001-12-04T19:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"QPS2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 24.0,\n          \"emissions_factor_co2\": 0.6336,\n          \"data_first_seen\": \"2001-11-27T13:10:00+10:00\",\n          \"data_last_seen\": \"2025-04-17T18:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"QUERIVER\",\n      \"name\": \"Que River\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"QUERIVE1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 24.0,\n          \"emissions_factor_co2\": 0.972,\n          \"data_first_seen\": \"2016-04-12T13:20:00+10:00\",\n          \"data_last_seen\": \"2016-06-17T11:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"QBYNB\",\n      \"name\": \"Queanbeyan\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>As part of the commitments associated with the Berrybank 2\\u00a0wind farm, GPG is committed to installing a\\u00a020 MW battery energy storage system located within the Australian Capital Territory, which will support the ACT distribution network at the Queanbeyan substation, in partnership with TransGrid, the region\\u2019s distribution network service provider.</p>\",\n      \"units\": [\n        {\n          \"code\": \"QBYNBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"data_first_seen\": \"2022-07-07T09:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"QBYNBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"data_first_seen\": \"2022-07-05T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"QP\",\n      \"name\": \"Quorn Park\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Quorn Park Hybrid Project will consist of the construction and operation of a solar farm consisting of photovoltaic (PV) modules, a Battery Energy Storage System (BESS) and related civil and electrical infrastructure. The Project is in the Parkes Shire, New South Wales, Australia, located approximately 10 km northwest of Parkes.<br/><br/>The construction of the Quorn Park Hybrid Project has an investment value of over $190 million. The project is expected to begin construction in the mid second half 2024, with a targeted start to operations in the first half of 2026.</p>\",\n      \"units\": [\n        {\n          \"code\": \"QPSF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 96.8,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"QPBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 27.6,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"QPBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 27.6,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RACOMIL\",\n      \"name\": \"Racecourse Mill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"RACOMIL1\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 48.5,\n          \"emissions_factor_co2\": 0.0201,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RANGEB\",\n      \"name\": \"Rangebank\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Rangebank BESS (Battery Energy Storage System) is an industrial scale BESS to be located in Cranbourne West, Victoria, Australia.<br/>It will provide 200MW / 400MWh capacity of reliable and flexible energy solutions.</p>\",\n      \"units\": [\n        {\n          \"code\": \"RANGEB1L1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 260.0,\n          \"data_first_seen\": \"2024-08-27T12:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"RANGEB1G1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 260.0,\n          \"data_first_seen\": \"2024-08-27T11:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RED_HILL\",\n      \"name\": \"Red Hill\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Operating since 1993, EDL\\u2019s Red Hill power station is WA\\u2019s first environmentally sustainable, waste to energy power station converting landfill gas (LFG) to energy.</p><p>The Red Hill landfill gas generators use the methane that is produced by the decomposition of organic materials in the Red Hill Waste Management Facility to produce clean, renewable electricity.</p>\",\n      \"units\": [\n        {\n          \"code\": \"RED_HILL\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 3.64,\n          \"emissions_factor_co2\": 0.0769,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"REDBANK1\",\n      \"name\": \"Redbank\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Redbank Power Station is located near Singleton, in the Hunter Region, New South Wales, Australia. It was coal powered with one steam driven turbo generator with a capacity of 151 MW of electricity.</p><p>The station is currently awaiting a restart of operations after converting to a biomass generator. Upon re-fire, the station will operate using 100% biomass at a capacity of 151MW of electricity.</p>\",\n      \"units\": [\n        {\n          \"code\": \"REDBANK1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 150.0,\n          \"emissions_factor_co2\": 1.1873,\n          \"data_first_seen\": \"2001-02-23T20:20:00+10:00\",\n          \"data_last_seen\": \"2014-11-10T17:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"REECE\",\n      \"name\": \"Reece\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The last power station in the Pieman River Power Development before the water runs out to the Southern Ocean, Reece Power Station is located at the foot of the Reece Dam on Lake Pieman. The dam and power station are named after the Honourable Eric Reece who was the Premier of Tasmania (1958\\u201369 and 1972\\u201375) and a great supporter of the Hydro-Electric Commission.</p>\",\n      \"units\": [\n        {\n          \"code\": \"REECE2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 116.0,\n          \"data_first_seen\": \"2005-05-16T13:35:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"REECE1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 116.0,\n          \"data_first_seen\": \"2005-05-16T13:35:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"REMOUNT\",\n      \"name\": \"Remount\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"REMOUNT\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.0,\n          \"emissions_factor_co2\": 0.0764,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"REPULSE\",\n      \"name\": \"Repulse\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Repulse Power Station is a conventional hydroelectric power station located in the Central Highlands region of Tasmania, Australia. The power station is situated on the Lower River Derwent catchment and is owned and operated by Hydro Tasmania.</p>\",\n      \"units\": [\n        {\n          \"code\": \"REPULSE\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 28.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BIOGAS01\",\n      \"name\": \"Richgro\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"BIOGAS01\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.0,\n          \"emissions_factor_co2\": 0.057,\n          \"data_first_seen\": \"2015-10-12T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T06:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0RIVERINASF\",\n      \"name\": \"Riverina\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Riverina Solar Farm is an approximately 30 MW commercial scale solar station\\u00a0located at Yoogali, near Griffith in New South Wales. The project is one of several in the region, which combined could make Griffith a leading renewable energy hub in New South Wales.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0RIVERINASF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 32.4,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RESS\",\n      \"name\": \"Riverina 1\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The combined 150MW / 300MWh Riverina and Darlington Point Energy Storage Systems is located adjacent to TransGrid\\u2019s Darlington Point Substation in the Murrumbidgee Shire, South West NSW.</p><p>Developed by Edify, the lithium-ion battery serves to add more flexible dispatchable capacity to the NSW market and complement the significant presence of renewable generation in the region.</p>\",\n      \"units\": [\n        {\n          \"code\": \"RESS1L\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 80.0,\n          \"data_first_seen\": \"2023-06-27T11:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"RESS1G\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 80.0,\n          \"data_first_seen\": \"2023-06-02T07:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RIVNB\",\n      \"name\": \"Riverina 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The combined 150MW / 300MWh Riverina and Darlington Point Energy Storage Systems is located adjacent to TransGrid\\u2019s Darlington Point Substation in the Murrumbidgee Shire, South West NSW.</p><p>Developed by Edify, the lithium-ion battery serves to add more flexible dispatchable capacity to the NSW market and complement the significant presence of renewable generation in the region.</p>\",\n      \"units\": [\n        {\n          \"code\": \"RIVNBG2\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 65.0,\n          \"data_first_seen\": \"2023-06-25T11:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"RIVNBL2\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 65.0,\n          \"data_first_seen\": \"2023-06-26T15:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ROCHEDAL\",\n      \"name\": \"Rochedale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>This facility is owned and operated by LMS in partnership with Brisbane City Council. The facility was commissioned in 2004 and currently has an installed capacity of 7.7MW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ROCHEDAL\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.7,\n          \"emissions_factor_co2\": 0.0767,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ROCKINGHAM\",\n      \"name\": \"Rockingham\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"ROCKINGHAM\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.2,\n          \"emissions_factor_co2\": 0.0726,\n          \"data_first_seen\": \"2013-12-17T08:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RPCG\",\n      \"name\": \"Rocky Point Cogen\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"RPCG\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"emissions_factor_co2\": 0.0443,\n          \"data_first_seen\": \"2011-01-28T13:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T00:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"EDLRGNRD\",\n      \"name\": \"Roghan Road\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"EDLRGNRD\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 2.0,\n          \"emissions_factor_co2\": 0.062,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ROMA\",\n      \"name\": \"Roma\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Roma Power Station is a peaking power station and was built and commissioned by the energy business of Boral in 1999, which became Origin in 2000.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ROMA_8\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 40.0,\n          \"emissions_factor_co2\": 0.7664,\n          \"data_first_seen\": \"1999-02-05T14:20:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T20:35:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ROMA_7\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 40.0,\n          \"emissions_factor_co2\": 0.7664,\n          \"data_first_seen\": \"1999-02-09T12:45:00+08:00\",\n          \"data_last_seen\": \"2025-06-02T19:05:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RRSF\",\n      \"name\": \"Ross River\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Ross River Solar Farm has been built on a 202 hectare site that was historically a disused mango farm. The solar farm is \\u2018utility scale\\u2019 and has the capacity to generate 116 megawatts of clean renewable energy \\u2013 enough to power over 54,000 homes.</p><p>Ross River Solar Farm has 413,280 solar panels installed on single axis tracking systems that allow its panels to rotate and capture the maximum amount of sunlight. Each of the farm\\u2019s crystalline solar photovoltaic panels are identical in type but larger in size to those used on household rooftops throughout Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"RRSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 128.0,\n          \"data_first_seen\": \"2018-09-12T10:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ROWALLAN\",\n      \"name\": \"Rowallan\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Rowallan Power Station is a conventional hydroelectric power station located in north-western Tasmania, Australia. The station is located 25 kilometres (16 mi) south of Liena.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ROWALLAN\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.5,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ROYALLA\",\n      \"name\": \"Royalla\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Located 23 kilometers south of the capital Canberra, at the time of completion, the Royalla Solar Farm was once the largest photovoltaic plant in Australia with 20 MW rated capacity (24 MWp) and around 82,000 solar panels installed on 41 kilometers of fixed structures.</p><p>The Royalla PV plant\\u00a0was the first solar installation built by ACCIONA in Australia, acting as a\\u00a0contractor for the development company FRV.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ROYALLA1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 20.0,\n          \"data_first_seen\": \"2016-04-23T07:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RUBICON\",\n      \"name\": \"Rubicon\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Rubicon Hydroelectric Scheme is a small run-of-river hydroelectric scheme located on the Rubicon and Royston Rivers, north east of Melbourne, 40\\u00a0km (25\\u00a0mi) south-west of Alexandra, Victoria, Australia. The scheme commenced in 1922, and was the first state-owned hydroelectric scheme to generate electricity in mainland Australia, and among the first in the world to be remotely controlled. For the first ten years of its operation it supplied on average 16.9% of electricity generated by the State Electricity Commission of Victoria. It is now owned and operated by AGL Energy and contributes approximately 0.02% of Victoria&#x27;s energy supply.</p>\",\n      \"units\": [\n        {\n          \"code\": \"RUBICON\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 13.0,\n          \"data_first_seen\": \"2010-03-04T16:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RUGBYR\",\n      \"name\": \"Rugby Run\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Located near the town of Moranbah in Central Queensland, the Rugby Run solar farm is Bravus\\u2019 flagship solar investment in Australia. Officially opened in October 2019, the Rugby Run solar farm features 247,000 solar panels which generate 185,000MWh of power each year. Rugby Run has a power purchase agreement to sell 80 per cent of the energy generated.</p>\",\n      \"units\": [\n        {\n          \"code\": \"RUGBYR1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 83.0,\n          \"data_first_seen\": \"2019-05-28T11:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RYANCWF\",\n      \"name\": \"Ryan Corner\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Ryan Corner Wind Farm site is located in South-Western Victoria near the township of Yambuk, 16.5km north west of Port Fairy within the Moyne Shire Local Government Area.</p><p>The project covers an area of approximately 3,388 Ha, where the current land use is primarily agricultural activities including grazing of sheep and cattle.</p><p>The windfarm comprises 52 turbines with a total output of approximately 218.4MW. It will connect to the grid via a 132kV overhead transmission circuit to the existing 500kV Tarrone Terminal Station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"RYANCWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 218.4,\n          \"data_first_seen\": \"2024-07-30T03:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"RYEPARK\",\n      \"name\": \"Rye Park\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Rye Park Wind Farm is located to the north of Yass and east of Boorowa, New South Wales, on the edge of the Southern Tablelands and the South-West Slopes near the township of Rye Park. The project area spans the Hilltops, Upper Lachlan and Yass Valley local government areas, located 11 km north-east of Yass on predominately stock farming land.</p>\",\n      \"units\": [\n        {\n          \"code\": \"RYEPARK1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 396.0,\n          \"data_first_seen\": \"2023-08-18T09:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SALTCRK\",\n      \"name\": \"Salt Creek\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Financial close for the project was reached on June 30, 2017. Construction of the Salt Creek Wind Farm commenced in September 2017 and was completed in late July 2018.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SALTCRK1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 54.0,\n          \"data_first_seen\": \"2018-06-06T16:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SAPHWF1\",\n      \"name\": \"Sapphire\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Sapphire Wind Farm is a wind farm in the Australian state of New South Wales. When it was built in 2018, it was the largest wind farm in New South Wales. It is in the New England region of northern New South Wales, 28 kilometres (17 mi) east of Inverell and 18 kilometres (11 mi) west of Glen Innes. It is north of the Gwydir Highway. The White Rock and Glen Innes Wind Farms are south of the highway closer to Glen Innes. It is intended to be colocated with a 200 MW solar farm. The wind farm contains 75 Vestas V126 turbines, each of which can generate 3.6 MW of electricity. They have a 137-metre hub height and 126-metre rotor diameter. The project is approved to build up to 109 wind turbines.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SAPHWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 270.0,\n          \"data_first_seen\": \"2018-02-01T19:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SEBSF\",\n      \"name\": \"Sebastopol\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Sebastopol Solar Farm uses the latest in solar energy generation technology to generate clean, zero emissions energy to meet the region\\u2019s energy needs. It is located on private land approximately 16 kilometres south of Temora in New South Wales. The site covers approximately 248 hectares of agricultural land that is still used for livestock grazing.<br/><br/>Construction of the solar farm was completed mid-December 2021 and commissioning was finished in July 2022, with operations now underway. The project received development approval in February 2019. Construction of the project took 14 months. During construction 150 people were employed, many from the local area. Three people are employed on an ongoing basis to support the operations and maintenance of the solar farm which is expected to have an operating life of around 30 years.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SEBSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 110.0,\n          \"data_first_seen\": \"2021-11-03T08:30:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SHEP1\",\n      \"name\": \"Shepparton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Organic rich wastwater from Shepparton\\u2019s local community and food processing industry (including the SPC Ardmona processing factory) flows into Goulburn Valley Water\\u2019s Shepparton Wastewater Treatment Plant, producing a methane-rich biogas from the anaerobic digestion process. The biogas is captured and cleaned as the fuel source for the generator, and\\u00a0the renewable electricity is fed into the national grid.</p><p>The Shepparton facility was a lead and significant part of the \\u2018Resource Recovery Precinct\\u2019 that won the 2010 United Nations World Environment Day \\u2018Best Business Environmental Initiative\\u2019 award.<br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"SHEP1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.1,\n          \"emissions_factor_co2\": 0.0748,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SHOALHAV\",\n      \"name\": \"Shoalhaven\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Shoalhaven Scheme is a dual-purpose water supply and Pumped-storage Hydroelectricity scheme located on the South Coast region of New South Wales, Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SHPUMP\",\n          \"fueltech_id\": \"pumps\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 240.0,\n          \"data_first_seen\": \"1998-12-09T05:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T16:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SHGEN\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 240.0,\n          \"data_first_seen\": \"1998-12-07T11:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T21:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SHOAL\",\n      \"name\": \"Shoalhaven Starches\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Manildra Group commissioned GE Gas Power to deliver a secure supply of electricity and steam. GE technology offered a turnkey solution for the complete cogeneration plant. GE will provide Manildra Group&#x27;s Shoalhaven Starches site operations with two LM2500+ aeroderivative gas turbines, two Heat Recovery Steam Generators (HRSG) with fresh air firing and associated Balance of Plant to electricity and steam on a continuous basis.<br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"SHOAL1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 54.0,\n          \"emissions_factor_co2\": 0.6022,\n          \"data_first_seen\": \"2023-10-17T01:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"STWF\",\n      \"name\": \"Silverton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Silverton Wind Farm is a 199 megawatt wind farm situated on the Barrier Ranges in New South Wales, built for AGL Energy by CATCON and General Electric.On 3 June 2009, the project was approved by the NSW state Government.The project was initially set to begin construction in the first half of 2010, yet several issues caused delays. To begin, the transmission line needed to connect the fully developed wind farm would need to be as long as 300 km, and due to multiple connection options, as well as an expected large cost of the infrastructure, the decision of the final solution was delayed.In 2012, the start-date for construction of the wind farm has been pushed back to 2014, after AGL Energy decided to give priority to building two solar photovoltaic plants which have received almost A$200m in government funding.The project&#x27;s planning approval was set to expire on 24 May 2016, however AGL submitted a Modification Application on 25 February 2016 with the sole aim to extend the project&#x27;s Planning Approval expiry to 2021. On 3 June 2016 that application was granted, giving AGL the option to optimise and build the project within their Powering Australian Renewables Fund. The project secured a Power Purchase Agreement with EnergyAustralia for supply of 60% of its annual output until December 2030.On 16 May 2017, AGL announced construction had commenced.As of 2019, it had been completed and is now operating. The project uses General Electric 3.43-130 wind turbines with a hub height of 110m.</p>\",\n      \"units\": [\n        {\n          \"code\": \"STWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 198.0,\n          \"data_first_seen\": \"2018-05-15T09:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0SMITHBESS\",\n      \"name\": \"Smithfield\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Smithfield Battery Energy Storage System (BESS) is a 65 MW / 130 MWh battery system currently under development. The project is located on Darug land in Smithfield, approximately 30km from Sydney CBD.</p><p>This project will be co-located with the existing operational Smithfield Open Cycle Gas Turbine Gas Peaker plant owned by Iberdrola Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0SMITHBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 65.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0SMITHBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 65.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SITHE\",\n      \"name\": \"Smithfield\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Smithfield OCGT has a fifteen minute start time, enabling the asset to capture high electricity price events. As a peaking generator, Smithfield OCGT operates with very low capacity utilisation, estimated at 2-8% per annum.</p><p>Smithfield OCGT was acquired by Iberdrola Australia in May 2019.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SITHE01\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 187.0,\n          \"emissions_factor_co2\": 0.7156,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T08:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNAPPER\",\n      \"name\": \"Snapper Point\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Snapper Point Power Station is a gas turbine power station under development at Outer Harbor, South Australia, beside the older Pelican Point Power Station.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SNAPPER1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 154.0,\n          \"emissions_factor_co2\": 0.7364,\n          \"data_first_seen\": \"2022-01-19T08:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T18:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNOWTOWN\",\n      \"name\": \"Snowtown\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Snowtown wind farms are located on the Barunga and Hummocks ranges west of Snowtown in the Mid North of South Australia, around 150 kilometres (93 mi) north of the state capital, Adelaide. They were developed by Trustpower and owned by Tilt Renewables, which demerged from Trustpower in 2016. The first stage of 47 turbines was completed in 2008 and Stage 2 of 90 turbines became operational in 2014. Stage 2 was sold by Tilt Renewables to Palisade Investment Partners in December 2019.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SNOWTWN1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 99.0,\n          \"data_first_seen\": \"2008-04-18T16:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNOWNTH\",\n      \"name\": \"Snowtown North\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Snowtown Wind Farm 2 is located approximately 170 km north of Adelaide in South Australia.</p><p>Snowtown Wind Farm 2 was initially commissioned in October 2014 using Siemens direct drive turbines. The 270 MW (144MW for Snowtown North) windfarm generates an average of 875GWh of electricity per year.</p><p>Following its acquisition in 2019, Snowtown Wind Farm 2 is now owned by Australian superannuation fund investors whose investment is managed by Palisade Investment Partners Pty Ltd, Hesta and First State Super.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SNOWNTH1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 144.0,\n          \"data_first_seen\": \"2014-02-10T17:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNOWSTH\",\n      \"name\": \"Snowtown South\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Snowtown Wind Farm 2 is located approximately 170 km north of Adelaide in South Australia.</p><p>Snowtown Wind Farm 2 was initially commissioned in October 2014 using Siemens direct drive turbines. The 270 MW (144MW for Snowtown North) windfarm generates an average of 875GWh of electricity per year.</p><p>Following its acquisition in 2019, Snowtown Wind Farm 2 is now owned by Australian superannuation fund investors whose investment is managed by Palisade Investment Partners Pty Ltd, Hesta and First State Super.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SNOWSTH1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 126.0,\n          \"data_first_seen\": \"2013-10-03T09:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNOWY4\",\n      \"name\": \"Snowy\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"SNOWY4\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"data_first_seen\": \"1998-12-07T04:15:00+10:00\",\n          \"data_last_seen\": \"2001-03-26T16:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNOWY5\",\n      \"name\": \"Snowy\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"SNOWY5\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"data_first_seen\": \"1998-12-07T09:15:00+10:00\",\n          \"data_last_seen\": \"2001-07-13T22:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0SNOWY20\",\n      \"name\": \"Snowy 2.0\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Snowy 2.0 Pumped Storage Power Station or Snowy Hydro 2.0 or simply Snowy 2.0 is a pumped-hydro battery megaproject in New South Wales, Australia. The dispatchable generation project expands upon the original Snowy Mountains Scheme (ex post facto Snowy 1.0) connecting two existing dams through a 27-kilometre underground tunnel and a new, underground pumped-hydro power station. Construction began in 2019.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0SNOWY201\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 1468.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0SNOWY202\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 732.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNUG\",\n      \"name\": \"Snuggery\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Snuggery Power Station is a power station near Tantanoola in the Limestone Coast region of South Australia. It was built in 1978. It is now owned by Synergen Power, a subsidiary of Engie Energy International.The power station has a generating capacity of 63 MW, consisting of three diesel-fueled open cycle gas turbines. It is used as a peaking power plant.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SNUG1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"emissions_factor_co2\": 1.066,\n          \"data_first_seen\": \"1998-12-07T09:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SNUG2\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"emissions_factor_co2\": 1.066,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SNUG3\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"emissions_factor_co2\": 1.066,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SNUGNL1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"emissions_factor_co2\": 1.066,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"AGLSOM\",\n      \"name\": \"Somerton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Somerton Power Station is an open cycle, gas turbine power station located in the Melbourne suburb of Somerton, Victoria, Australia. It is owned and operated by AGL Energy. The facility normally operates three or four hours at a time as a peaking power plant, but is able to run 24 hours a day, seven days a week if required.<br/><br/>The plant cost $125 million to build, with the 2003 opening being delayed by environmental concerns and technical issues. The plant uses four second-hand 37.5MW GT-1 Frame 6B gas turbines, manufactured under license to GE by Alstom and Thomassen International.</p>\",\n      \"units\": [\n        {\n          \"code\": \"AGLSOM\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 170.0,\n          \"emissions_factor_co2\": 0.7386,\n          \"data_first_seen\": \"2002-05-15T13:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T20:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SOUTH_CARDUP\",\n      \"name\": \"South Cardup\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>This facility is owned and operated by LMS in partnership with Western Australian Landfill Services (WALS). The facility was commissioned in 2005 and has an installed capacity of 4.1MW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SOUTH_CARDUP\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.16,\n          \"emissions_factor_co2\": 0.0802,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SKSF\",\n      \"name\": \"South Keswick\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"SKSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 15.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"STHBKTEC\",\n      \"name\": \"Southbank Institute Of Technology\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"STHBKTEC\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.957,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SVALE\",\n      \"name\": \"Springvale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"SVALE1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.2,\n          \"emissions_factor_co2\": 0.0785,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"STGEORGE\",\n      \"name\": \"St George Leagues Club\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"STGEORG1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.812,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SLDCBLK\",\n      \"name\": \"St Leonards Data Centre\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"units\": [\n        {\n          \"code\": \"SLDCBLK1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 20.0,\n          \"emissions_factor_co2\": 0.0,\n          \"data_first_seen\": \"2022-01-25T01:05:00+08:00\",\n          \"data_last_seen\": \"2022-09-27T14:15:00+08:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0STANBESS\",\n      \"name\": \"Stanwell\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Stanwell Battery Energy Storage System (BESS) will provide essential firming capacity to support the renewable projects we have planned in Central Queensland. At 300MW capacity and four hours storage duration, it is the largest committed battery project in Queensland.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0STANBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 300.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0STANBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 300.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"STANWELL\",\n      \"name\": \"Stanwell\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Stanwell Power Station is a coal-fired power generation station located in Stanwell, 23 kilometres (14 mi) south-west of Rockhampton, Queensland, Australia. At the time of construction, it was one of the largest industrial developments undertaken in Queensland. With a capacity to generate 1,445 megawatts (MW), Stanwell Power Station supplies electricity for distribution to customers via the state&#x27;s high voltage electricity grid.Stanwell became fully operational in 1996 and is located on 4,000 acres (1,600 hectares) of land. Construction of the station took seven years, with infrastructure built to withstand cyclonic winds.</p>\",\n      \"units\": [\n        {\n          \"code\": \"STAN-1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 365.0,\n          \"emissions_factor_co2\": 0.8571,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"STAN-2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 365.0,\n          \"emissions_factor_co2\": 0.8571,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"STAN-4\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 365.0,\n          \"emissions_factor_co2\": 0.8571,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"STAN-3\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 365.0,\n          \"emissions_factor_co2\": 0.8571,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"STAPYLTON\",\n      \"name\": \"Stapylton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>This facility is owned and operated by LMS in partnership with Gold Coast City Council and has an installed capacity of 3.5MW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"STAPYLTON1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 3.0,\n          \"emissions_factor_co2\": 0.075,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"STARFHILL\",\n      \"name\": \"Starfish Hill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Starfish Hill Wind Farm is a wind power station spread over two hills near Cape Jervis, South Australia. It has 22 wind turbines, eight on Starfish Hill itself and 14 on Salt Creek Hill, with a combined generating capacity of 33 MW of electricity.<br/>Starfish Hill Wind Farm was commissioned in September 2003, making it the first major wind farm in the state. On 30 October 2010, one of the original 23 turbines caught fire and was destroyed. It was not replaced, leaving the wind farm with 22 turbines.Starfish Hill Wind Farm was developed by Tarong Energy at a cost of $65 million. RATCH-Australia (at that time part of Transfield Services) acquired the wind farm in December 2007.</p>\",\n      \"units\": [\n        {\n          \"code\": \"STARHLWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 34.5,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"STOCKYD\",\n      \"name\": \"Stockyard Hill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Stockyard Hill Wind Farm is a wind farm project under construction in Victoria (Australia). As of June 2020, 1 of a planned 149 turbines was operational and connected to the grid.[1] When it is complete, it is expected to produce up to 530MW, which would be Australia&#x27;s largest wind farm.</p>\",\n      \"units\": [\n        {\n          \"code\": \"STOCKYD1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 531.0,\n          \"data_first_seen\": \"2021-07-08T00:05:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0STUBBOSF\",\n      \"name\": \"Stubbo\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Stubbo Solar is a 400-megawatt (MW) large scale solar project approved by the NSW Department of Planning, Industry and Environment in July 2021. It is currently in construction across 1,250 hectares of mostly cleared grazing land in the Central West region of NSW.</p><p>It is being constructed by EPC contracting partner PCL Construction.</p>\",\n      \"units\": [\n        {\n          \"code\": \"STUBSF2\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 248.0,\n          \"data_first_seen\": \"2024-12-19T09:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"STUBSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 255.0,\n          \"data_first_seen\": \"2024-12-19T09:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0SUMMFBESS\",\n      \"name\": \"Summerfield\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Summerfield Battery is a large-scale four-hour duration battery storage project that will supply energy to South Australians and the national electricity grid to support Australia\\u2019s renewable energy transition.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0SUMMFBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 240.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0SUMMFBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 240.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SMCSF\",\n      \"name\": \"Sun Metals\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Sun Metals Solar Farm is a photovoltaic solar power station near Townsville in the Australian state of Queensland. It supplies some of the electricity consumed by the nearby Sun Metals (a subsidiary of Korea Zinc) zinc refinery as well as exporting to the National Electricity Market. When the Sun Metals Solar Farm started exporting electricity to the grid in May 2018, it took over from Clare Solar Farm as the largest capacity solar farm in Queensland.Construction was undertaken by RCR Tomlinson. The solar farm is connected to the refinery&#x27;s existing 33/132kV substation and consists of over 1 million solar panels.The photovoltaic cells are thin-film with single axis tracking.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SMCSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 143.0,\n          \"data_first_seen\": \"2018-05-30T07:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SUNCOAST\",\n      \"name\": \"Suncoast Gold Macadamias\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"SUNCOAST\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.0216,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SUNRSF1\",\n      \"name\": \"Sunraysia\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Scheduled for completion in 2020, Sunraysia Solar Farm is a utility-scale solar photovoltaic (PV) farm near Balranald in southern New South Wales.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SUNRSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 228.0,\n          \"data_first_seen\": \"2020-11-10T01:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"VALDORA\",\n      \"name\": \"Sunshine Coast\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Sunshine Coast Solar Farm is a photovoltaic power station operating on a 24 hectares (59 acres) site in Valdora in the Sunshine Coast near Yandina, in Queensland, Australia. The station has a maximum generating capacity of 15 megawatts, generated from 57,850 photovoltaic panels.</p>\",\n      \"units\": [\n        {\n          \"code\": \"VALDORA1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 15.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SUNTPSF\",\n      \"name\": \"Suntop\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Suntop Solar Farm is located near Wellington, south of Dubbo in regional New South Wales. The site will accommodate a large-scale solar PV system utilising single-axis tracking, and ground mounted panels which will generate 395GWh of energy throughout the year. Single-axis tracking has been selected for this project to harness the highest amount of solar irradiance as the panels will track the sun\\u2019s movement east to west each day.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SUNTPSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 175.0,\n          \"data_first_seen\": \"2021-08-04T18:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0SUPERNODE\",\n      \"name\": \"Supernode\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The South Pine switchyard is the central node of the Queensland electricity transmission network, 80% of Queensland\\u2019s total electricity flows through this \\u2018supernode\\u2019 on a daily basis. Quinbrook\\u2019s Supernode Data Centre and Battery Energy Storage Site (\\u2018BESS\\u2019) site, located adjacent to the South Pine switchyard, will host one of the largest battery storage installations in the Australian National Electricity Market. The 750 MW (2 \\u2013 4 Hour) BESS offers large power users an innovative solution to obtain stable power supply and overcome the critical stability issues facing the Queensland power grid as recently identified by AEMO.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0SUPERNODEG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0SUPERNODEL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"SNBL01\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 260.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"SNBG01\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 260.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0SUPERNODE2\",\n      \"name\": \"Supernode 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The South Pine switchyard is the central node of the Queensland electricity transmission network, 80% of Queensland\\u2019s total electricity flows through this \\u2018supernode\\u2019 on a daily basis. Quinbrook\\u2019s Supernode Data Centre and Battery Energy Storage Site (\\u2018BESS\\u2019) site, located adjacent to the South Pine switchyard, will host one of the largest battery storage installations in the Australian National Electricity Market. The 750 MW (2 \\u2013 4 Hour) BESS offers large power users an innovative solution to obtain stable power supply and overcome the critical stability issues facing the Queensland power grid as recently identified by AEMO.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SNBL02\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 260.0,\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SRSF\",\n      \"name\": \"Susan River\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Susan River Solar Farm is a 95MW project located 17km south of Hervey Bay, Queensland.</p><p>The project began exporting electricity in 2018 and is connected to the national grid via Ergon Energy&#x27;s network.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SRSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 85.0,\n          \"data_first_seen\": \"2018-12-28T14:40:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0SWANBBESS\",\n      \"name\": \"Swanbank\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Formerly the home of two coal-fired power stations (A and B), CleanCo is redeveloping our Swanbank site into a Clean Energy Hub featuring a range of future energy generation and storage technologies.</p><p>The first major project is the Swanbank Battery - the first big battery to be built in Ipswich.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0SWANBBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0SWANBBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SWAN_B\",\n      \"name\": \"Swanbank B\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"units\": [\n        {\n          \"code\": \"SWAN_A_3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 66.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1999-01-04T14:50:00+10:00\",\n          \"data_last_seen\": \"2002-06-28T21:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_A_4\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 66.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1998-12-08T11:15:00+10:00\",\n          \"data_last_seen\": \"2002-06-28T23:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_B_3\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 125.0,\n          \"emissions_factor_co2\": 1.091,\n          \"data_first_seen\": \"1998-12-07T04:00:00+10:00\",\n          \"data_last_seen\": \"2012-05-24T12:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_B_4\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 125.0,\n          \"emissions_factor_co2\": 1.091,\n          \"data_first_seen\": \"1998-12-07T05:05:00+10:00\",\n          \"data_last_seen\": \"2010-06-01T14:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"MRIDGE\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 56.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1999-01-14T18:00:00+10:00\",\n          \"data_last_seen\": \"2000-02-25T23:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_A_1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 66.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1998-12-07T06:35:00+10:00\",\n          \"data_last_seen\": \"2002-05-14T19:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_A_5\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 66.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1998-12-21T13:35:00+10:00\",\n          \"data_last_seen\": \"2001-09-25T22:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_D\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 37.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1999-02-02T14:20:00+10:00\",\n          \"data_last_seen\": \"2004-04-24T16:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_B_1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 125.0,\n          \"emissions_factor_co2\": 1.091,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2011-05-15T10:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_B_2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 125.0,\n          \"emissions_factor_co2\": 1.091,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2010-06-28T19:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_A_6\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 66.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1998-12-07T08:30:00+10:00\",\n          \"data_last_seen\": \"2002-06-14T22:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_C\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 28.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1999-05-10T09:00:00+10:00\",\n          \"data_last_seen\": \"2002-03-22T12:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SWAN_A_2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 66.0,\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"1998-12-07T08:15:00+10:00\",\n          \"data_last_seen\": \"2002-06-26T23:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SWAN_E\",\n      \"name\": \"Swanbank E\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Swanbank E was commissioned in 2002 with a single 385 megawatts combined cycle gas turbine. The gas turbine of Swanbank E was the largest of its type at the time of its commissioning.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SWAN_E\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 385.0,\n          \"emissions_factor_co2\": 0.401,\n          \"data_first_seen\": \"2002-05-21T10:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TABMILL2\",\n      \"name\": \"Tableland Mill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The $100 million green energy power plant at the Tableland Mill converts 100 per cent renewable sugarcane fibre, known as bagasse, into green energy.</p><p>The power plant produces 24 megawatts of electricity \\u2013 enough to power 26,280 homes \\u2013 which is the entire population of the Tableland region.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TABMILL2\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 24.0,\n          \"emissions_factor_co2\": 0.0201,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TAHMOOR\",\n      \"name\": \"Tahmoor\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"TAHMOOR1\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.0,\n          \"emissions_factor_co2\": 0.5689,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TBSF\",\n      \"name\": \"Tailem Bend\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Tailem Bend Solar Power Farm is a solar power farm near Tailem Bend in South Australia. It has 108MW of generation capacity but is limited to supplying 95MW to the national grid. It is developed and owned by Singapore-based Vena Energy, a new name for the former Equis Energy following acquisition by Global Infrastructure Partners in January 2018. The output will be sold to Snowy Hydro for retail sale under its Lumo Energy brand.</p><p>The solar farm covers 200 hectares of land with more than 390,000 photovoltaic solar panels.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TBSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 108.0,\n          \"data_first_seen\": \"2019-02-28T12:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TB2SF\",\n      \"name\": \"Tailem Bend 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Tailem Bend 2 Hybrid Project is the second stage of the Tailem Bend Project and is immediately co-located, with the Tailem Bend Solar 1 Project that is situated immediately south of Substation Road. The Hybrid Project incorporates a second solar farm, a battery energy storage system, and the construction of a new bay in the existing Coorong Substation.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TB2SF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 105.0,\n          \"data_first_seen\": \"2023-08-25T09:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TB2BG1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"data_first_seen\": \"2023-10-27T13:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"TB2BL1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"data_first_seen\": \"2024-07-03T09:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TALLAWAR\",\n      \"name\": \"Tallawarra\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Tallawarra Power Station is a 435-megawatt (583,000 hp) combined cycle natural gas power station in the city of Wollongong, New South Wales, Australia.  Owned and operated by EnergyAustralia, the station is the first of its type in New South Wales and produces electricity for the state during periods of high demand.  It is located on the western shore of Lake Illawarra in the suburb of Yallah.</p><p><br/>The station comprises a 260-megawatt (350,000 hp) gas turbine and a 160-megawatt (210,000 hp) steam turbine unit and has a total capacity of 435 megawatts (583,000 hp).  It uses many of the previous power station&#x27;s structures including the cooling system channels from Lake Illawarra. The power station is connected to the state grid via a 132kV switching station maintained by Endeavour Energy (Previously known as Integral Energy).</p>\",\n      \"units\": [\n        {\n          \"code\": \"TALWA1\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 440.0,\n          \"emissions_factor_co2\": 0.3718,\n          \"data_first_seen\": \"2008-10-14T08:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-20T21:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TALWB\",\n      \"name\": \"Tallawarra B\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The construction of the Tallawarra B gas-fired power station was completed in early 2024. It is now supplying power into the grid during times of high demand.</p><p>Tallawarra B is Australia\\u2019s first peaking power station with direct emissions offset. Its fast-start gas turbine can come online to full load within 30 minutes, generating 320 MW - enough power for 180,000 homes in New South Wales.</p><p>Tallawarra B features a $13 million purpose-built plume dispersion device to ensure the safety of planes flying nearby.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TALWB1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 320.0,\n          \"emissions_factor_co2\": 0.7831,\n          \"data_first_seen\": \"2024-01-24T09:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T20:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TAMALA_PARK\",\n      \"name\": \"Tamala Park\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Tamala Park LFG Power Station began operation in 2004, later expanding in 2007. It has a generation capacity of six megawatts - sufficient to provide power to approximately 6,000 homes.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TAMALA_PARK\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 6.0,\n          \"emissions_factor_co2\": 0.077,\n          \"data_first_seen\": \"2013-12-17T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TVCCPS\",\n      \"name\": \"Tamar Valley\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Tamar Valley Power Station is a $230 million natural gas-fired power station located in Bell Bay in the Tamar Valley, Tasmania. It is owned by Hydro Tasmania, and is immediately adjacent to the decommissioned Bell Bay Power Station, which is also owned by Hydro Tasmania.</p><p>This facility refers to the 208MW combined-cycle gas turbine commissioned at the sight in 2009.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TVCC201\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 208.6,\n          \"emissions_factor_co2\": 0.6117,\n          \"data_first_seen\": \"2009-06-27T15:25:00+10:00\",\n          \"data_last_seen\": \"2024-08-23T10:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TARALGA\",\n      \"name\": \"Taralga\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Taralga Wind Farm is a wind farm located near Taralga, New South Wales.<br/>Taralga Wind Farm was CBD Energy/Santander&#x27;s first and only wind farm. It is a 106.8 megawatt wind farm with 51 turbines.  The energy produced by the wind farm can power around 45,000 average Australian households per year, saving over 258,000 tonnes of greenhouse gas emissions per year.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TARALGA1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 106.8,\n          \"data_first_seen\": \"2014-12-22T17:35:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0TARONGBESS\",\n      \"name\": \"Tarong\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Tarong Battery Energy Storage System (BESS) will provide essential firming capacity to support the renewable projects we have planned in Southern Queensland. It will have a storage capacity of 300MW over two hours duration. The Tarong BESS will be the first battery energy storage in Stanwell&#x27;s portfolio.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0TARONGBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 300.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0TARONGBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 300.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TARBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 393.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"TARBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 393.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TARONG\",\n      \"name\": \"Tarong\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Tarong Power Station is a coal fired power station located on a 1,500 hectares (3,700 acres) site in Tarong in the South Burnett Region near the Burnett River and Nanango, in Queensland, Australia.  The station has a maximum generating capacity of 1,400 megawatts, generated from four turbines. Coal is supplied via a conveyor from Meandu Mine, which is 1.5 kilometres (0.93 mi) away and is also owned by Stanwell.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TARONG#3\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 350.0,\n          \"emissions_factor_co2\": 0.8837,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TARONG#1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 350.0,\n          \"emissions_factor_co2\": 0.8837,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TARONG#4\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 350.0,\n          \"emissions_factor_co2\": 0.8837,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TARONG#2\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 350.0,\n          \"emissions_factor_co2\": 0.8837,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TARONGN\",\n      \"name\": \"Tarong North\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Tarong North Power Station is a 443 megawatt coal fired power station on the same site as Tarong Power Station in the South Burnett. The Queensland Government commissioned the construction of the power station in November 1999.  Construction work began in 2000.  The power station was initially owned by a 50/50 joint venture between Tarong Energy and TM Energy. Full ownership of the power station by Tarong Energy was obtained in November 2009.The plant was opened in 2003 and is based on an energy efficient supercritical design.  The Steam Generator was supplied by IHI and the steam turbine was manufactured by Toshiba.<br/>Particulate emissions at the power station are reduced by bag filter technology.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TNPS1\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 443.0,\n          \"emissions_factor_co2\": 0.8438,\n          \"data_first_seen\": \"2002-11-09T13:15:00+10:00\",\n          \"data_last_seen\": \"2025-04-25T09:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TARRALEA\",\n      \"name\": \"Tarraleah\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Tarraleah Power Station is a hydroelectric power station located in the Central Highlands region of Tasmania, Australia. The power station is part of the Upper Derwent hydro scheme and is operated by Hydro Tasmania.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TARRALEA\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 90.0,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TATIARA\",\n      \"name\": \"Tataria\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"TATIARA1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 0.5,\n          \"emissions_factor_co2\": 0.812,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TATURA\",\n      \"name\": \"Tatura\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Organic rich wastewater from Tatura\\u2019s local community and thriving local food processing industry (including Tatura Milk\\u2019s production factory) flows into Goulburn Valley Water\\u2019s Tatura Wastewater Treatment Plant, producing a methane-rich biogas from the anaerobic digestion process. The biogas is captured and cleaned as the fuel source for the generator, and\\u00a0the renewable electricity is\\u00a0fed into the national grid.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TATURA01\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.1,\n          \"emissions_factor_co2\": 0.0201,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TEATREE\",\n      \"name\": \"Tea Tree Gully\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"TEATREE1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.0576,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0TEMPLERBESS\",\n      \"name\": \"Templers\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Construction of ZEN Energy\\u2019s Templers Battery Energy Storage project is underway, with earthworks completed and key equipment arriving onsite over the next 6 months.</p><p>The Templers Battery is South Australia\\u2019s second-largest energy storage project, enhancing electricity reliability as the state leads the way nationally toward 100% renewable energy by 2027.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0TEMPLERBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 111.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0TEMPLERBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 111.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TEMPBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 138.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"TEMPBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 138.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SATGN\",\n      \"name\": \"Temporary Generation North\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Temporary Generation North and its smaller sibling Temporary Generation South are gas turbine power stations in South Australia. They were bought by the Government of South Australia in 2017 as a response to the 2016 South Australian blackout and load-shedding in February 2017.<br/>Temporary Generation North is five open cycle gas turbines installed at the former Holden site in Elizabeth South, a northern suburb of Adelaide.The generators were purchased to be used only in emergency shortfalls in electricity supply to the grid, such as in extreme weather. Both sets were first used on 24 January 2019 to deal with a supply shortfall in Victoria.The intent of the Weatherill ALP state government was that the turbines would be converted from diesel fuel to natural gas and moved to a single location while remaining owned by the government.In August 2019, the state government (following the 2018 election, now controlled by the Liberal party) announced that it had arranged 25-year leases of the power stations to two different companies, with the leases taking effect from May 2020. Both companies operate wind farms in South Australia. The five northern generators will be leased to Nexif Energy and relocated to a new site at Outer Harbor and operating on natural gas before the end of 2020. Nexif Energy also proposes to convert them to combined cycle with a steam turbine in the following few years.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SATGN1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 154.0,\n          \"emissions_factor_co2\": 0.957,\n          \"data_first_seen\": \"2017-10-26T19:15:00+10:00\",\n          \"data_last_seen\": \"2021-02-25T09:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SATGS\",\n      \"name\": \"Temporary Generation South\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Temporary Generation South and its larger sibling Temporary Generation North are gas turbine power stations in South Australia. They were bought by the Government of South Australia in 2017 as a response to the 2016 South Australian blackout and load-shedding in February 2017.<br/>Temporary Generation South is four open cycle gas turbines at the former Port Stanvac Refinery at Lonsdale.The generators were purchased to be used only in emergency shortfalls in electricity supply to the grid, such as in extreme hot weather. They were first used on 24 January 2019 to deal with a supply shortfall in Victoria.The intent of the Weatherill ALP state government was that the turbines will be converted from diesel fuel to natural gas and moved to a single location while remaining owned by the government.In August 2019, the state government (following the 2018 election, now controlled by the Liberal party) announced that it had arranged 25-year leases of the power stations to two different companies, with the leases taking effect from May 2020. Both companies operate wind farms in South Australia. The four generators at Lonsdale will be leased to Infigen Energy and will be moved from the SA Water desalination plant to the SA Water Bolivar Waste Water Treatment Plant and converted to operate on natural gas instead of diesel.</p>\",\n      \"units\": [\n        {\n          \"code\": \"SATGS1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 123.0,\n          \"emissions_factor_co2\": 0.957,\n          \"data_first_seen\": \"2017-10-26T15:50:00+10:00\",\n          \"data_last_seen\": \"2022-04-15T00:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TERALBA\",\n      \"name\": \"Teralba\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"TERALBA\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 3.0,\n          \"emissions_factor_co2\": 0.62,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0TERANGBESS\",\n      \"name\": \"Terang\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>FRV Services Australia (FRV) is building the Terang Battery Energy Storage System (BESS). The Terang BESS will have a total anticipated discharge capacity of 100 megawatts (MW) and a storage capacity of 200 megawatt hours (MWh).</p><p>The Terang BESS is now under construction. Once operational, it will improve the reliability of the electricity network by storing power when there is a lot of energy available (for example during the day) and releasing this stored energy when demand is higher.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0TERANGBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0TERANGBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TERMSTOR\",\n      \"name\": \"Terminal\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"TERMSTOR\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BLUFF\",\n      \"name\": \"The Bluff\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>AGL&#x27;s Bluff Range Wind Farm, also known as Hallett 5 Wind Farm consists of 25 Suzlon turbines each of 2.1MW for a total of 52.5MW. Total project investment was $120 million. The project was completed in early 2012. Turbines spread 8 kilometres over the Porcupine Range.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BLUFF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 52.5,\n          \"data_first_seen\": \"2011-07-05T15:50:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"THEDROP\",\n      \"name\": \"The Drop\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Drop Hydro Power Station is a Pacific Hydro hydroelectric power station on the Mulwala Canal, near Berrigan, New South Wales, Australia. It has one turbine, with a generating capacity of 2.5 megawatts (3,400 hp) of electricity.The power station was completed in November 2002, and is Australia&#x27;s first hydroelectric power station built on an irrigation canal.</p>\",\n      \"units\": [\n        {\n          \"code\": \"THEDROP1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.5,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0TILBSF\",\n      \"name\": \"Tilbuster\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The proposed Tilbuster solar farm would add to secure, affordable and clean energy generation for the state of NSW whilst also contributing to the national Renewable Energy Target (RET) of 33,000 gigawatt hours. The New England region is considered an excellent province for solar energy generation due to its solar irradiance capabilities.</p><p>It has access to two existing transmission lines that transect the proposal site and does not appear highly constrained by environmental factors; a 132kV eastern line and a 330kV central line. Both the eastern and central line run south east to north west through the proposal site. The 330\\u00a0kV transmission line would be used to connect the solar farm to the national electricity grid.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0TILBSF\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 249.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TIMWEST\",\n      \"name\": \"Timboon West\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Timboon West Wind Farm was developed and constructed in 2018 by BayWa r.e. Wind Pty Ltd and commenced operations in late 2018. Epic Energy acquired the Timboon West Wind Farm in April 2019.</p><p>Located approximately seven kilometres southwest of Timboon in south-western Victoria, the site was chosen for its undisturbed wind flow with strong, consistent wind speeds, close proximity to the electrical grid, and large setbacks to nearby dwellings</p>\",\n      \"units\": [\n        {\n          \"code\": \"TIMWEST\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.2,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TOORAWF\",\n      \"name\": \"Toora\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Toora wind farm is a wind power station at Toora in South Gippsland, Victoria, Australia. It is located north of Wilsons Promontory and 150 km SE of Melbourne. The wind farm is on a ridge overlooking the town of Toora.<br/>Toora has 12 wind turbines, each of 1.75 MW rated capacity, with a total generating capacity of 21 MW of electricity. The power station was completed in 2002. <br/>As of May 2008, it was owned by Transfield Services Infrastructure Fund. Danish company Vestas Wind Systems, one of the world&#x27;s largest turbine manufacturers, constructed the wind farm. Transfield Services Infrastructure Fund became RATCH-Australia on 11 July 2011.Viewing and photography points are available on a road that passes the wind farm.  From some of these views of the coastal plain, the Strzelecki Ranges, and Wilsons Promontory can be combined with views of the turbines.  Accommodation is available in a caravan park at Toora.<br/>One of Toora&#x27;s turbines can power up to 6,600 homes.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TOORAWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 21.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TIB\",\n      \"name\": \"Torrens Island\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>AGL has broken ground at Torrens Island power station in preparation for the construction of its $180 million, 250 MW grid-scale battery.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TIBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 250.0,\n          \"data_first_seen\": \"2023-04-26T11:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"TIBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 250.0,\n          \"data_first_seen\": \"2023-04-26T12:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TORRIS\",\n      \"name\": \"Torrens Island\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Torrens Island Power Station is located on Torrens Island, near Adelaide, South Australia and is operated by AGL Energy. It burns natural gas in eight steam turbines to generate up to 1,280 MW of electricity. The gas is supplied via the SEAGas pipeline from Victoria, and the Moomba Adelaide Pipeline System (MAPS) from Moomba in the Cooper Basin. The station is capable of burning either natural gas or fuel oil. It is the largest power station in South Australia and was formerly the largest single power station user of natural gas in Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TORRB2\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 0.5758,\n          \"data_first_seen\": \"1998-12-09T05:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-19T20:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TORRB3\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 0.5758,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TORRA1\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 120.0,\n          \"emissions_factor_co2\": 0.5758,\n          \"data_first_seen\": \"1998-12-07T05:45:00+10:00\",\n          \"data_last_seen\": \"2020-09-17T18:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TORRA4\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 120.0,\n          \"emissions_factor_co2\": 0.5758,\n          \"data_first_seen\": \"1998-12-08T14:40:00+10:00\",\n          \"data_last_seen\": \"2020-09-17T17:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TORRA2\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 120.0,\n          \"emissions_factor_co2\": 0.5758,\n          \"data_first_seen\": \"1998-12-07T06:55:00+10:00\",\n          \"data_last_seen\": \"2020-03-21T01:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TORRA3\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 120.0,\n          \"emissions_factor_co2\": 0.5758,\n          \"data_first_seen\": \"1998-12-08T14:40:00+10:00\",\n          \"data_last_seen\": \"2021-12-07T12:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TORRB1\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 0.5758,\n          \"data_first_seen\": \"1998-12-08T05:40:00+10:00\",\n          \"data_last_seen\": \"2021-12-07T12:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TORRB4\",\n          \"fueltech_id\": \"gas_steam\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 200.0,\n          \"emissions_factor_co2\": 0.5758,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-05-17T00:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TOWER\",\n      \"name\": \"Tower\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"TOWER\",\n          \"fueltech_id\": \"gas_wcmg\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 41.2,\n          \"emissions_factor_co2\": 0.7005,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YABULU\",\n      \"name\": \"Townsville\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Townsville Power Station is located in Yabulu, an industrial suburb of Townsville. The station is owned by RATCH-Australia. The station has a 160 MW Siemens turbine and an 82 MW heat recovery steam generator.<br/>The station was built in the late 1990s as an open-cycle plant and was upgraded to combined-cycle operation in 2005.</p>\",\n      \"units\": [\n        {\n          \"code\": \"YABULU2\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 82.0,\n          \"emissions_factor_co2\": 0.6046,\n          \"data_first_seen\": \"2004-12-08T18:10:00+10:00\",\n          \"data_last_seen\": \"2025-01-05T15:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"YABULU\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 160.0,\n          \"emissions_factor_co2\": 0.6046,\n          \"data_first_seen\": \"1998-12-16T19:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T18:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TGNSS\",\n      \"name\": \"Traralgon Network Support\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"TGNSS1\",\n          \"fueltech_id\": \"gas_recip\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"emissions_factor_co2\": 0.5399,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TREVALLN\",\n      \"name\": \"Trevallyn\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Trevallyn Power Station is a run-of-the-river hydroelectric power station located in the northern Midlands region of Tasmania, Australia. The power station is situated on the Great Lake and South Esk catchment and is owned and operated by Hydro Tasmania.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TREVALLN\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 93.0,\n          \"data_first_seen\": \"2005-05-16T17:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TRIBUTE\",\n      \"name\": \"Tribute\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Tribute Power Station is a conventional hydroelectric power station located in Western Tasmania, Australia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TRIBNL1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 25.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TRIBUTE\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 83.0,\n          \"data_first_seen\": \"2005-05-17T07:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TULLYSM\",\n      \"name\": \"Tully Sugar Mill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"units\": [\n        {\n          \"code\": \"TULLYSM1\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 28.0,\n          \"emissions_factor_co2\": 0.018,\n          \"data_first_seen\": \"2024-08-27T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"SNOWY2\",\n      \"name\": \"Tumut\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Located downstream of Tumut Pond Dam and 366 metres below ground level, Tumut 1 Power Station is situated approximately 2.25 kilometres south-west from Cabramurra, under Happy Valley Rd. The conventional hydroelectric power station has four turbine generators, with a combined generating capacity of 330 megawatts of electricity; and a net generation of 847 gigawatt-hours per annum. The power station was completed in 1959, and has 292.6 metres rated head.<br/><br/>Tumut 2 Power Station is situated approximately 5.91 kilometres north of north-west from Cabramurra, under Goat Ridge Rd, some 244 metres below ground level. The conventional hydroelectric power station has four Francis turbine generators, with a combined generating capacity of 286.4 megawatts and a net generation of 787 gigawatt-hours per annum. The power station was completed in 1962, and has 262.1 metres rated head. Water flows through the turbines at the rate of 118.9 cubic metres per second.<br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"UPPTUMUT\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 616.0,\n          \"data_first_seen\": \"2001-07-15T00:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"SNOWY2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 616.0,\n          \"data_first_seen\": \"1998-12-07T04:15:00+10:00\",\n          \"data_last_seen\": \"2001-07-13T23:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TUMUT3\",\n      \"name\": \"Tumut 3\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Tumut 3 Power Station is the first major pumped storage hydroelectric power station in Australia. Pump-storage schemes use off-peak energy to pump water to a reservoir on a higher level. This water then passes through turbines to generate electricity when prices are higher. The sole powerhouse is located above ground, below Talbingo Dam.<br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"SNOWYP\",\n          \"fueltech_id\": \"pumps\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 600.0,\n          \"data_first_seen\": \"1998-12-09T18:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T14:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TUMUT3\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1500.0,\n          \"data_first_seen\": \"2001-07-16T07:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TUMUT3-1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 250.0,\n          \"data_last_seen\": \"2011-01-06T13:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TUMUT3-2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 250.0,\n          \"data_last_seen\": \"2011-01-06T13:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TUMUT3-3\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 250.0,\n          \"data_last_seen\": \"2011-01-06T13:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TUMUT3-4\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 250.0,\n          \"data_last_seen\": \"2011-01-06T13:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TUMUT3-5\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 250.0,\n          \"data_last_seen\": \"2011-01-06T13:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"TUMUT3-6\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 250.0,\n          \"data_last_seen\": \"2011-01-06T13:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TUNGATIN\",\n      \"name\": \"Tungatinah\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>The Tungatinah Power Station is a conventional hydroelectric power station located in the Central Highlands region of Tasmania, Australia. The power station is situated on the Upper River Derwent catchment and is owned and operated by Hydro Tasmania.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TUNGATIN\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 125.0,\n          \"data_first_seen\": \"2005-05-16T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ULBESS\",\n      \"name\": \"Ulinda Park\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Akaysha is developing a large scale BESS adjacent to the Western Downs Substation in Queensland\\u2019s energy heartland. The BESS will support the rapid expansion of solar and wind projects leveraging existing transmission infrastructure in the Western Downs built for conventional energy. The BESS will ensure cost efficient delivery of renewable energy to customers in Queensland while supporting the network.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ULBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 150.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ULBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 150.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"ULPBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 197.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"ULPBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 197.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"URANQ\",\n      \"name\": \"Uranquinty\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Uranquinty Power Station is a 640-megawatt (860,000 hp) natural gas-fired power station located in Uranquinty, New South Wales, Australia, comprising four Siemens V94.2 gas turbines.  It is the second largest gas-fired power station in New South Wales, and is used during peak loads.<br/>Uranquinty Power Station was the fourth power station to be constructed by NewGen Power which was jointly owned by ERM Power and Babcock and Brown Power at a cost of $500 million.On 4 July 2008 Babcock and Brown Power announced that it had sold the Uranquinty power station for $700 million to Origin Energy.On 19 January 2009 Origin Energy Limited announced that the Uranquinty Power Station was commissioned with eight people employed to operate the facility.</p>\",\n      \"units\": [\n        {\n          \"code\": \"URANQ14\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 166.0,\n          \"emissions_factor_co2\": 0.5641,\n          \"data_first_seen\": \"2008-10-27T20:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T20:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"URANQ11\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 166.0,\n          \"emissions_factor_co2\": 0.5641,\n          \"data_first_seen\": \"2008-10-27T19:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-17T21:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"URANQ13\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 166.0,\n          \"emissions_factor_co2\": 0.5641,\n          \"data_first_seen\": \"2008-10-27T19:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"URANQ12\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 166.0,\n          \"emissions_factor_co2\": 0.5641,\n          \"data_first_seen\": \"2008-10-27T19:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-17T21:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0UUNGULAWF\",\n      \"name\": \"Uungula\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Uungula Wind Farm is located on Wiradjuri Country, 14km east of Wellington, NSW.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0UUNGULAWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 414.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"VP\",\n      \"name\": \"Vales Point B\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>In 1978, two Toshiba 660 MW units were added to the Vales Point Power Station, becoming &quot;B&quot; Station. The combined capacity of 2195 MW made Vales Point the largest power station in Australia at the time. The Toshiba 660 MW turbo-alternator became the standard in New South Wales, with similar units later being installed at Eraring, Bayswater and Mount Piper.<br/></p>\",\n      \"units\": [\n        {\n          \"code\": \"VP6\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 660.0,\n          \"emissions_factor_co2\": 0.9877,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"VP5\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 660.0,\n          \"emissions_factor_co2\": 0.9877,\n          \"data_first_seen\": \"1999-01-22T09:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"VPGS\",\n      \"name\": \"Valley Power Peaking\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Valley Power Peaking Facility is an open cycle, gas turbine power station at Traralgon in the Latrobe Valley in Victoria, Australia. It is owned and operated by Snowy Hydro.</p>\",\n      \"units\": [\n        {\n          \"code\": \"VPGS3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.941,\n          \"data_first_seen\": \"2002-05-16T13:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-16T08:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"VPGS5\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.941,\n          \"data_first_seen\": \"2002-05-16T13:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T08:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"VPGS6\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.941,\n          \"data_first_seen\": \"2002-05-16T15:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-18T08:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"VPGS4\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.941,\n          \"data_first_seen\": \"2002-05-16T11:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-01T08:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"VPGS2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.941,\n          \"data_first_seen\": \"2002-05-16T13:05:00+10:00\",\n          \"data_last_seen\": \"2025-06-30T23:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"VPGS\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"2006-02-02T12:05:00+10:00\",\n          \"data_last_seen\": \"2015-07-01T00:00:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"VPGS1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"emissions_factor_co2\": 0.941,\n          \"data_first_seen\": \"2002-05-15T18:10:00+10:00\",\n          \"data_last_seen\": \"2025-06-30T23:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LYGS1\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"2002-02-18T17:10:00+10:00\",\n          \"data_last_seen\": \"2002-05-13T14:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LYGS2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"2002-03-13T19:45:00+10:00\",\n          \"data_last_seen\": \"2002-05-11T18:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LYGS3\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"2002-03-11T16:00:00+10:00\",\n          \"data_last_seen\": \"2002-05-15T04:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LYGS4\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"2002-04-09T12:35:00+10:00\",\n          \"data_last_seen\": \"2002-05-11T18:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LYGS5\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"emissions_factor_co2\": 0.8715,\n          \"data_first_seen\": \"2002-05-07T11:35:00+10:00\",\n          \"data_last_seen\": \"2002-05-11T18:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"LYGS6\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"retired\",\n          \"emissions_factor_co2\": 0.8715,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"TITREE\",\n      \"name\": \"Veolia Ti Tree\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The facility utilises the 36 million cubic metre void left over from a previous open cut coal operation on the outskirts of Ipswich. As the site is filled, completed areas are rehabilitated to complement the surrounding natural environment. Ti Tree is located adjacent to main roads and rail transport, further enhancing its appeal for economically sustainable waste management in Australia and the world.</p>\",\n      \"units\": [\n        {\n          \"code\": \"TITREE\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 2.0,\n          \"emissions_factor_co2\": 0.7226,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"VICMILL\",\n      \"name\": \"Victoria Mill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"VICMILL1\",\n          \"fueltech_id\": \"bioenergy_biomass\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 24.0,\n          \"emissions_factor_co2\": 0.0201,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"VBB\",\n      \"name\": \"Victorian Big Battery\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Victorian Big Battery is a 300 MW grid-scale battery storage project in Geelong, Australia which will store enough energy in reserve to power over one million Victorian homes for 1/2 an hour.</p>\",\n      \"units\": [\n        {\n          \"code\": \"VBBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 360.0,\n          \"data_first_seen\": \"2021-07-28T12:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T20:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"VBBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 360.0,\n          \"data_first_seen\": \"2021-07-28T11:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0WAGERUP_BESS\",\n      \"name\": \"Wagerup\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"units\": [\n        {\n          \"code\": \"0WAGERUPBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0WAGERUPBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 100.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ALCOA_WGP\",\n      \"name\": \"Wagerup\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Wagerup Power Station is a 380MW dual natural gas and distillate fuelled power station located at Alcoa\\u2019s Wagerup refinery in south-west Western Australia.  Located about 130 km south of Perth, on the border of Western Australia\\u2019s Peel and South West regions, the Power Station is four kilometres north of Yarloop and 13 km south of Waroona. Wagerup is only operated when there is insufficient capacity in the South West Interconnected System to meet high demand.<br/>Two open system gas turbines commenced operations at Wagerup in October 2007.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ALCOA_WGP\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 26.0,\n          \"emissions_factor_co2\": 0.5834,\n          \"data_first_seen\": \"2013-12-17T08:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ALINTA_WGP_GT\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 195.15,\n          \"emissions_factor_co2\": 0.5834,\n          \"data_first_seen\": \"2014-01-11T14:30:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"ALINTA_WGP_U2\",\n          \"fueltech_id\": \"gas_ocgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 196.85,\n          \"emissions_factor_co2\": 0.5834,\n          \"data_first_seen\": \"2014-02-24T10:30:00+08:00\",\n          \"data_last_seen\": \"2025-06-26T18:50:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WAGGNSF\",\n      \"name\": \"Wagga North\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Wagga Wagga Solar Farm site is located six kilometres from the town centre adjacent to the Bomen industrial zone. The project has been in development since 2017 and is currently in the early stages of construction.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WAGGNSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 55.0,\n          \"data_first_seen\": \"2021-08-03T18:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"ALINTA_WWF\",\n      \"name\": \"Walkaway\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Alinta wind farm (also known as Walkaway wind farm) is a wind power station at Walkaway, just south of Geraldton, Western Australia. It is  owned by Infigen Energy and has offtake agreements with Alinta Energy and AGL Energy.The Alinta wind farm has an installed capacity of 89.1 megawatts. It supplies Perth and the south west in the South West Interconnected System (SWIS).<br/>Each year the wind farm generates energy that would normally produce 360,150 tonnes of greenhouse gases if generated by fossil fuel based methods. This is the equivalent of removing 76,000 cars from the roads.Electricity produced by the wind farm is purchased  mainly by Alinta Energy.</p>\",\n      \"units\": [\n        {\n          \"code\": \"ALINTA_WWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 89.1,\n          \"data_first_seen\": \"2013-12-17T08:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WLWLSF\",\n      \"name\": \"Walla Walla\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>FRV Services Australia (FRV) is constructing a 300 megawatt (MWac) solar farm near Walla Walla in NSW. The solar farm will utilise the region\\u2019s abundant sunlight to generate clean, renewable energy for business and households in NSW.<br/><br/>The Independent Planning Commission (IPC) provided planning consent for the Project on 27th November 2020 after extensive community consultation and detailed assessment of the Project proposal. The solar farm is due to commence construction in January 2023.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WLWLSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 201.6,\n          \"data_first_seen\": \"2024-10-21T17:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WLWLSF2\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 201.6,\n          \"data_first_seen\": \"2024-10-28T09:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WW\",\n      \"name\": \"Wallerawang\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Wallerawang Power Station was a thermal coal power station, located near Wallerawang, in the Central Tablelands region of New South Wales, Australia. The power station was equipped with two turbo-alternators of 500 megawatts (670,000 hp) each, supplied by CA Parsons and Company of Newcastle-upon-Tyne, England. Production commenced in May 1957.In July 2013, EnergyAustralia acquired Wallerawang Power Station, along with Mount Piper Power Station, from Delta Electricity for $160 million. Due to dwindling demand, the first of the two generating units had been mothballed in January 2013, and the second in April 2014. In November 2014, EnergyAustralia announced that it would permanently close Wallerawang due to ongoing reduced energy demand, lack of access to competitively priced coal and the power station\\u2019s high operating costs.  EnergyAustralia began the process of removing useful equipment from the station in 2015 and began demolition of the site when this process has been completed.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WW7\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 500.0,\n          \"emissions_factor_co2\": 1.03,\n          \"data_first_seen\": \"1998-12-07T09:30:00+10:00\",\n          \"data_last_seen\": \"2014-01-25T11:45:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WW8\",\n          \"fueltech_id\": \"coal_black\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 500.0,\n          \"emissions_factor_co2\": 1.03,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2014-03-31T22:20:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WALGRV\",\n      \"name\": \"Wallgrove\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>A 50MW/75MWh lithium ion battery will be installed at Transgrid\\u2019s Wallgrove substation in Western Sydney.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WALGRVG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 50.0,\n          \"data_first_seen\": \"2021-10-29T12:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WALGRVL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 47.0,\n          \"data_first_seen\": \"2021-11-02T14:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"PRDSO_WALPOLE\",\n      \"name\": \"Walpole\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Western Power is partnering with WA engineering firm Power Research and Development (PRD) to develop a mini-pumped hydro facility in Walpole and connect it to the SWIS network.<br/><br/>Two dams are being built on a farming property near Walpole, one high and one low, to transfer and store the water. Solar panels and batteries will power the pumping action and shift the water, making it self-sufficient.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PRDSO_WALPOLE_HG1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.5,\n          \"data_first_seen\": \"2025-03-04T12:25:00+10:00\",\n          \"data_last_seen\": \"2025-06-10T17:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0WAMBOWF\",\n      \"name\": \"Wambo\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Wambo Wind Farm is a renewable energy generation project located near Jandowae, at a site chosen for its excellent wind resources and attractive grid connectivity.</p><p>The project is a 50:50 joint venture between Cubico Sustainable Investments, a major investor in the renewable energy sector globally and Stanwell, a Queensland Government-owned electricity generator.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0WAMBOWF2\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 248.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WAMBOWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 252.0,\n          \"data_first_seen\": \"2025-06-21T11:25:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WANDSF\",\n      \"name\": \"Wandoan\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Wandoan South Solar 1 consists of approximately 250,000 solar photovoltaic panels across 500 ha of the Wandoan South Project site and will have a maximum output of 125 MW. The project is connected to Powerlink\\u2019s Wandoan South Substation, located to the south of the Project site.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0WANDSF2\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 240.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WANDSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 159.0,\n          \"data_first_seen\": \"2023-05-25T12:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WANDBG\",\n      \"name\": \"Wandoan South\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Wandoan South Battery Energy Storage System (BESS) Project is located near Wandoan, 400km north-west of Brisbane in the Darling Downs region. The BESS will have a discharge capacity of up to 100MW and store 150MWh of energy, which could power up to 57,000 average homes annually. It represents the first milestone of the Wandoan South Project to be developed across several stages.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WANDBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 123.0,\n          \"data_first_seen\": \"2021-09-08T15:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WANDBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 123.0,\n          \"data_first_seen\": \"2021-10-14T12:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T19:35:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WTAHB\",\n      \"name\": \"Waratah Super Battery\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>To ensure NSW continues to have reliable energy supply as our coal-fired power stations close, the NSW Government is delivering the Waratah Super Battery project.</p><p>The Waratah Super Battery project is a System Integrity Protection Scheme (SIPS) designed to act as a &#x27;shock absorber&#x27; in the event of any sudden power surges, including from bush fires or lightning strikes. The SIPS also provides a virtual transmission solution that increases the capacity of the existing transmission system, allowing electricity consumers in the Hunter, Sydney and Illawarra regions to access more energy from existing generators.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WTAHB1L1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1093.84,\n          \"data_first_seen\": \"2024-09-30T16:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:10:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"WTAHB1G1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1095.84,\n          \"data_first_seen\": \"2024-09-03T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WARRADARGE\",\n      \"name\": \"Warradarge\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Warradarge Wind Farm will have a total output of 180 megawatts with a capacity factor of nearly 50 per cent \\u2013 the equivalent of the average annual electricity needs of 148,500 West Australian homes.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WARRADARGE_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 180.0,\n          \"data_first_seen\": \"2020-08-05T11:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WG\",\n      \"name\": \"Warragamba\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Warragamba Power Station is a hydroelectric power station at Warragamba Dam, New South Wales, Australia. Warragamba has one turbine with a generating capacity of 50 MW of electricity.<br/>The power station was completed in 1959 and is now disconnected from the electricity grid.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WG01\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 50.0,\n          \"data_first_seen\": \"2010-03-04T16:00:00+08:00\",\n          \"data_last_seen\": \"2012-05-17T01:25:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WARWSF\",\n      \"name\": \"Warwick\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Warwick Solar Farm is a 64 MWac renewable energy facility in the Southern Downs Region of Queensland, which is approximately 160km west of Brisbane.</p><p>The project was developed by Terrain Solar and acquired by the University of Queensland in 2018 at a ready-to-build status, enabling them to become the first major university in the world to offset 100 per cent of their electricity use with renewable power produced from their own assets.</p><p>The University of Queensland will also use the project as a research and teaching facility. Construction commenced in February 2019 and was formally opened in July 2020.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WARWSF2\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 39.0,\n          \"data_first_seen\": \"2020-09-22T08:25:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WARWSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 39.0,\n          \"data_first_seen\": \"2020-09-22T08:35:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WATERLWF\",\n      \"name\": \"Waterloo\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Waterloo wind farm is east of Manoora, South Australia. It is the largest wind farm operated by EnergyAustralia.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WATERLWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 130.0,\n          \"data_first_seen\": \"2010-08-20T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WPWF\",\n      \"name\": \"Wattle Point\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>Wattle Point Wind Farm is a wind farm near Edithburgh on the Yorke Peninsula in South Australia, which has been operating since April 2005. When it was officially opened in June of that year it was Australia&#x27;s largest wind farm at 91 megawatts (122,000 hp). The installation consists of 55 wind turbines covering 17.5 square kilometres (6.8 sq mi)and was built at a cost of 180 million Australian dollars. It is connected to ETSA Utilities electricity transmission system via a 132 kilovolt line.The location was chosen after identification as having one of mainland Australia&#x27;s highest average wind speeds. The wind farm was officially opened by South Australian Premier Mike Rann and Southern Hydro Chairman, Dr Keith Turner. The opening was opposed by some of the local Indigenous Australians, the Adjahdura (or Narungga). A descendant of the traditional landowners argued that construction desecrated an ancient burial ground, disturbing skeletons in the construction of turbine number four. Work was halted in late 2004 after the discovery of human remains, artefacts and tools. The Aboriginal Affairs Department, and the developers, separately commissioned archaeological reports resulting in the development allowed to proceed with five towers being repositioned. Both reports concluded that the bones had come from elsewhere on the peninsula, being later reburied at Wattle Point. The region&#x27;s aboriginal community was divided on construction; Narungga National Aboriginal Corporation supporting development and the Narungga Heritage Committee strongly opposing.Wattle Point Wind Farm was built and owned by Southern Hydro Pty Limited. Southern Hydro was owned by Meridian Energy of New Zealand until October 2005, when it was bought by the Australian Gas Light Company (AGL). The windfarm was acquired by Alinta in October 2006, as part of an asset merger with AGL, and subsequently by the Australia and New Zealand Banking Group&#x27;s Energy Infrastructure Trust, for 225 million dollars on 23 April 2007.<br/><br/>The District Council of Yorke Peninsula approved a second wind farm, Wattle Point Stage 2. However it did not proceed due to insufficient capacity in the electrical transmission lines.The facility is closely connected to the Dalrymple ESCRI battery, a 30-megawatt battery storage facility at Dalrymple substation about 21 kilometres (13 mi) to the north.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WPWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 91.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WAUBRAWF\",\n      \"name\": \"Waubra\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Waubra wind farm is located on both sides of the Sunraysia Highway 35 km north-west of Ballarat in Victoria, Australia. It is the fourth largest wind farm in Australia and was the largest wind farm by number of turbines and total capacity in the southern hemisphere upon its completion in July 2009.Consisting of 128 wind turbines, with associated substations and an operations centre, each wind turbine has a capacity of 1.5 megawatts (MW). The total installed capacity is 192 MW.The green energy generated by the wind farm each year provides electricity for 143,000 households enough to power a city 3-4 times the size of Ballarat.Acciona Energy formed a Community Reference Group (CRG) for the construction phase of the Waubra wind farm, to provide a regular forum for community input to the project and to facilitate communication between members of the Waubra community and the wind farm project team. In 2010 the anti-wind farm lobby group the Waubra Foundation adopted the name of the nearby town.<br/>The construction of the Waubra wind farm received financial assistance as part of the Victorian State Government\\u2019s Victorian Renewable Energy Target (VRET).In July 2011 the Australian Broadcasting Corporation 4 Corners program explored health concerns connected with Australian wind farms in its &quot;Against the Wind&quot; report. The Waubra wind farm and the community living around it was featured in the report.<br/>A viewing platform designed by Melbourne-based firm JOH Architects is accessible to tourists and located just off the Sunraysia Highway.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WAUBRAWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 192.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WELLSF1\",\n      \"name\": \"Wellington\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>This project consists of a 200MWdc solar farm at Goolma Road, Wuuluman. Construction on this project commenced in December 2019. </p><p>The solar farm is situated on 316 hectares of grazed agricultural land, which has predominantly been used for sheep and cattle grazing.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WELLSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 216.0,\n          \"data_first_seen\": \"2020-11-14T15:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WELNSF\",\n      \"name\": \"Wellington North\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>This solar project consists of a 425MWdc solar farm approximately seven kilometres north-east of Wellington, off Goolma Road, and 50 kilometres south-east of Dubbo in the Orana region of NSW. The project has been approved by the NSW Department Planning, Industry and Environment with construction, which will create 400 jobs, currently underway.<br/><br/>The solar farm is adjacent to our 200MWdc Wellington solar farm which is currently in construction. Once operational, both sites will create a solar hub with a combined installed capacity of 625MWdc.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WELNSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 436.0,\n          \"data_first_seen\": \"2024-05-21T15:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WEMENSF1\",\n      \"name\": \"Wemen\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Wemen Solar Farm is a photovoltaic power station in northwestern Victoria, Australia. It was constructed by RCR and Laing O\\u2019Rourke for owner Wirsol Energy, completed in 2018.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WEMENSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 97.0,\n          \"data_first_seen\": \"2018-11-07T13:30:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"BLAIRFOX_WESTHILLS\",\n      \"name\": \"West Hills\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Blair Fox managed the purchase and dismantling of 20 ENERCON E40 500kW wind turbines from the San Giorgio La Molara wind farm in the province of Benevento, Italy.<br/><br/>These wind turbines were transported to Western Australia, refurbished and installed at the West Hills and Karakin Wind Farms around 150km north of Perth.<br/><br/>The 5MW West Hills Wind Farm supplies electricity to our client farm in Lancelin.</p>\",\n      \"units\": [\n        {\n          \"code\": \"BLAIRFOX_WESTHILLS_WF3\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.0,\n          \"data_first_seen\": \"2013-12-18T12:00:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T05:05:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WESTILLA\",\n      \"name\": \"West Illawarra Leagues Club\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WESTILL1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.812,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WEST_KALGOORLIE\",\n      \"name\": \"West Kalgoorlie\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>The Kalgoorlie Gas Turbine Station is used to provide emergency back-up electricity for our electricity network, especially in the Kalgoorlie region. It consists of two open cycle gas turbines with a total electricity generation output capacity of 57 megawatts, operated on distillate as the primary fuel. The power station is not attended with all turbines operated remotely from the Pinjar control room.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WEST_KALGOORLIE_GT2\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 41.2,\n          \"emissions_factor_co2\": 0.562,\n          \"data_first_seen\": \"2014-01-09T08:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WEST_KALGOORLIE_GT3\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 23.3,\n          \"emissions_factor_co2\": 0.562,\n          \"data_first_seen\": \"2014-01-09T09:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WKIEWA\",\n      \"name\": \"West Kiewa\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>One of four units in the Kiewa Hydroelectric Scheme.</p><p>350km northeast of Melbourne in the Australian Alps, the Kiewa Hydroelectric Scheme is the largest in the State. Kiewa houses four power stations with an average annual electricity output of 404 GWh. The scheme harnesses energy from the Rocky Valley and Pretty Valley branches of the East Kiewa River, which rises on the Bogong High Plains, and the West Kiewa River, which rises near Mount Hotham.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WKIEWA2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 31.0,\n          \"data_first_seen\": \"1998-12-07T06:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WKIEWA1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 31.0,\n          \"data_first_seen\": \"1998-12-07T06:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"AGLNOW1\",\n      \"name\": \"West Nowra\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"AGLNOW1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.062,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WSTWYSF\",\n      \"name\": \"West Wyalong\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>West Wyalong solar farm is a 107MW project located near Wyalong, NSW. Snowy Hydro will purchase two-thirds of the power generated from the solar project through a 15-year PPA.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WSTWYSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 105.0,\n          \"data_first_seen\": \"2022-09-27T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WDBESS\",\n      \"name\": \"Western Downs\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>This is the first stage of the Western Downs Battery.</p><p>Western Downs battery is a 540 MW storing up to 1,080 MWh of energy with up to 2 hrs of power in reserve.</p><p>It is a grid-scale battery which will leverage leading-edge technology, connecting into Australia\\u2019s national electricity grid via the transmission network.</p><p>As an industrial sized battery energy storage system, the battery will provide grid stability by dispatching stored energy to the grid during peak times of demand.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WDBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 272.4,\n          \"data_first_seen\": \"2024-07-01T14:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WDBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 270.48,\n          \"data_first_seen\": \"2024-07-05T10:20:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:00:00+10:00\",\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WDGPH\",\n      \"name\": \"Western Downs\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Western Downs Green Power Hub is a large solar farm project under construction. At a size of 460 MW of installed solar panels once built, it will be Australia\\u2019s largest operating solar farm. The site also holds up to 150MW battery energy storage potential. The 200 MW battery which will be located next to the solar farm is in advanced stage of development</p>\",\n      \"units\": [\n        {\n          \"code\": \"WDGPH1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 501.0,\n          \"data_first_seen\": \"2022-02-15T14:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WDBESS2\",\n      \"name\": \"Western Downs 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>This is the second stage of the Western Downs Battery.</p><p>Western Downs battery is a 540 MW storing up to 1,080 MWh of energy with up to 2 hrs of power in reserve.</p><p>It is a grid-scale battery which will leverage leading-edge technology, connecting into Australia\\u2019s national electricity grid via the transmission network.</p><p>As an industrial sized battery energy storage system, the battery will provide grid stability by dispatching stored energy to the grid during peak times of demand.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WDBESSG2\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 270.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"WDBESSL2\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 270.0,\n          \"dispatch_type\": \"LOAD\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WESTCBT\",\n      \"name\": \"Western Suburbs League Club\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WESTCBT1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.812,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WRSF1\",\n      \"name\": \"White Rock Solar Farm\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The White Rock Solar Farm is a 20 MW solar photovoltaic development located near the White Rock Wind Farm in New South Wales, Australia. Together, they form a hybrid renewable energy facility that shares infrastructure, such as grid connections and substations, to maximize efficiency. The solar farm, which became operational in 2018, powers approximately 8,000 homes annually. It was developed with support from ARENA to improve large-scale solar energy expertise.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WRSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 22.0,\n          \"data_first_seen\": \"2018-10-05T13:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WRWF1\",\n      \"name\": \"White Rock Wind Farm\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The White Rock Wind Farm is located in New South Wales, Australia, and is comprised of up to 119 wind turbines. Stage One of the project, with 70 turbines, generates 175 MW of clean energy, powering approximately 105,000 homes annually. The second stage, currently in planning, will add up to 48 turbines, boosting the overall capacity to 216 MW. This wind farm is part of a larger effort to increase renewable energy production in the region.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WRWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 175.0,\n          \"data_first_seen\": \"2017-07-08T09:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WHITSF\",\n      \"name\": \"Whitsunday\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Whitsunday Solar Farm is a solar farm located at Collinsville in North Queensland, Australia. It has a generating capacity of 57.5 megawatts. Operations commenced in 2018. The power station is jointly owned by Edify Energy and Wirsol. It is co-located at the same site as the Hamilton Solar Farm and the Daydream Solar Farm.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WHITSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 57.5,\n          \"data_first_seen\": \"2018-07-11T13:55:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WHIT1\",\n      \"name\": \"Whitwood Road\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WHIT1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.062,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WILGAPK\",\n      \"name\": \"Wilga Park\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WILGAPK\",\n          \"fueltech_id\": \"gas_recip\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 10.0,\n          \"emissions_factor_co2\": 0.5692,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WILGAPKB\",\n      \"name\": \"Wilga Park B\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WILGB01\",\n          \"fueltech_id\": \"gas_recip\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 12.0,\n          \"emissions_factor_co2\": 0.5692,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WILLHOV\",\n      \"name\": \"William Hovel\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"units\": [\n        {\n          \"code\": \"WILLHOV1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.5,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0WDBESS\",\n      \"name\": \"Williamsdale\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Eku Energy has partnered with the Australian Capital Territory (ACT) Government to deliver a 250 megawatt (MW) / 500 megawatt-hour (MWh) battery energy storage system (BESS).<br/><br/>Located at Williamsdale in the south of Canberra, the battery will store enough renewable energy to power one-third of Canberra for two hours during peak demand periods, increasing energy security and reliability for Canberrans.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0WDBESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0WDBESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 250.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WGWF\",\n      \"name\": \"Willogoleche\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>The Willogoleche Wind Farm is a wind farm in the vicinity of Hallett in the Mid North region of South Australia. It generates up to 119 MW of electricity. There are 32 turbines in the wind farm. The closest to the town of Hallett is 3.2km west of the town, and the furthest is 8.3km southwest of the town. It was officially opened on 30 July 2019. The electricity generated is sold by Engie&#x27;s retail brand Simply Energy.The Australian Energy Market Operator expected the wind farm to start providing electricity to the grid from Winter 2018. A generation licence was issued on 20 June 2018 for 32 turbines to generate up to 122.56MW. The Willogoleche Wind Farm in Hallet, South Australia officially opened in July 2019.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WGWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 119.0,\n          \"data_first_seen\": \"2018-08-29T14:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"NINEWIL\",\n      \"name\": \"Willoughby\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"NINEWIL1\",\n          \"fueltech_id\": \"distillate\",\n          \"status_id\": \"retired\",\n          \"capacity_registered\": 3.0,\n          \"emissions_factor_co2\": 0.957,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WINDHILL\",\n      \"name\": \"Windy Hill\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Windy Hill Wind Farm is a wind power station near Ravenshoe on the Atherton Tablelands, Queensland, Australia. Windy Hill has 20 wind turbines with a generating capacity of 12 MW of electricity, providing enough power for about 3,500 homes. The cost of the project was A$20 million. It was the second wind farm to be constructed in Queensland after the 0.45Mw station on Thursday Island (1997).<br/>The power station was commissioned in 2000 and was initially operated by the Stanwell Corporation. In December 2007 Windy Hill was sold to Transfield Services Infrastructure Fund (TSIF) as part of Queensland Government&#x27;s ClimateSmart 2050 strategy. A new substation was built to allow the wind farm&#x27;s power to connect to the existing 66 kV transmission line. RATCH-Australia bought TSIF in 2011.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WHILL1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 12.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WINGF1\",\n      \"name\": \"Wingfield\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>EDL owns and operates the Wingfield I and II power stations, which are located adjacent to and work collaboratively with the world-class Wingfield Waste and Recycling Centre.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WINGF1_1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.12,\n          \"emissions_factor_co2\": 0.143,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WINGF2\",\n      \"name\": \"Wingfield 2\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"SA1\",\n      \"description\": \"<p>EDL owns and operates the Wingfield I and II power stations, which are located adjacent to and work collaboratively with the world-class Wingfield Waste and Recycling Centre.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WINGF2_1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.12,\n          \"emissions_factor_co2\": 0.0763,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WINTSF1\",\n      \"name\": \"Winton\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>FRV, a global renewable energy solutions provider and leading solar developer, is currently constructing the 85 MW AC Winton Solar Farm project, near Benalla in Victoria.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WINTSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 107.0,\n          \"data_first_seen\": \"2021-03-30T05:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WIVENHOE\",\n      \"name\": \"Wivenhoe\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>The Wivenhoe Power Station is situated between the Splityard Creek Dam and Lake Wivenhoe.  The Splityard Creek dam is situated in hills adjacent to Lake Wivenhoe and is about 100 metres (330 ft) above it.The Wivenhoe Dam has been built across the Brisbane River about 80 kilometres (50 mi) by road from the centre of Brisbane, the capital of the state of Queensland, Australia.  The body of water held behind the dam is called Lake Wivenhoe.</p>\",\n      \"units\": [\n        {\n          \"code\": \"PUMP2\",\n          \"fueltech_id\": \"pumps\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 240.0,\n          \"data_first_seen\": \"1998-12-29T03:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T14:30:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"W/HOE#1\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 285.0,\n          \"data_first_seen\": \"1998-12-17T15:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"PUMP1\",\n          \"fueltech_id\": \"pumps\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 240.0,\n          \"data_first_seen\": \"1998-12-20T03:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T15:50:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"W/HOE#2\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 285.0,\n          \"data_first_seen\": \"1998-12-15T10:45:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T18:35:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WIVENSH\",\n      \"name\": \"Wivenhoe\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WIVENSH\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 5.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WOLARSF\",\n      \"name\": \"Wollar\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The solar farm will be located on the western side of Barigan Road approximately 7km south of Wollar, around 50km from Mudgee.</p><p>Wollar Solar Farm will have a capacity of up to 280MWac and comprise approximately 660,000 solar panels across almost 500 hectares.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WOLARSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 324.0,\n          \"data_first_seen\": \"2025-01-28T09:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WOLLERT\",\n      \"name\": \"Wollert\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WOLLERT1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.0,\n          \"emissions_factor_co2\": 0.0718,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WONWP\",\n      \"name\": \"Wonthaggi\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Wonthaggi wind farm is a wind power station at Wonthaggi in Gippsland, Victoria, Australia. It has 6 wind turbines, with a total generating capacity of 12 MW of electricity.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WONWP\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 12.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WDLNGN\",\n      \"name\": \"Woodlawn\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WDLNGN01\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.0,\n          \"emissions_factor_co2\": 0.0717,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WOODLWN\",\n      \"name\": \"Woodlawn\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>The Woodlawn Wind Farm is a wind farm located near Bungendore, New South Wales.  It is part of the Capital Renewable Energy Precinct, along with nearby Capital Wind Farm and the Woodlawn Bioreactor.<br/>Woodlawn Wind Farm was owner and operator Infigen Energy&#x27;s sixth Australian wind farm. It is a 48.3 megawatt wind farm with 23 turbines.  The energy produced by the wind farm can power around 32,000 average Australian households per year, saving over 138,000 tonnes of greenhouse gas emissions per year.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WOODLWN1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 48.3,\n          \"data_first_seen\": \"2011-06-01T10:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WOOLNTH1\",\n      \"name\": \"Woolnorth\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"TAS1\",\n      \"description\": \"<p>Woolnorth Wind Farm is a wind power development, comprising two wind farms, at the Woolnorth property at Woolnorth (which includes the location known as Cape Grim), in the far north-west of Tasmania, Australia.   Both wind farms are operated by Woolnorth Wind Farm Holdings, a joint venture between Hydro Tasmania (who own a 25% share) and Shenhua Group (75% share).Bluff Point Wind Farm was constructed in two stages.  The first consisted of six Vestas 1.75 MW (2,350 hp) turbines and was commissioned in 2002.  Stage two, commissioned in 2004, expanded the wind farm with a further 31 of the same turbines, for a total generating capacity of 65 MW (87,000 hp).Studland Bay Wind Farm was commissioned in 2007 and consists of 25 Vestas V90 3 MW (4,000 hp) turbines, for a total capacity of 75 MW (101,000 hp).Tours to the wind farms are available and operated by a private commercial entity.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WOOLNTH1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 140.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WOOLGSF\",\n      \"name\": \"Woolooga\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>This 214MWp project in Lower Wonga, Queensland began construction in June 2021, and interested parties will be able to find all the information they need about the Woolooga project here.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0WOOLGBG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 222.0,\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"0WOOLGBL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 222.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"WOOLGSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 222.5,\n          \"data_first_seen\": \"2022-05-24T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:05:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"0WOORBESS\",\n      \"name\": \"Wooreen\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>EnergyAustralia has committed to building a four-hour utility-scale battery of 350 MW capacity, which is scheduled to be in operation before the end of 2026. The project will provide an economic boost for the Gippsland region, helping to secure Victoria\\u2019s energy supply, enable more renewable energy to enter the electricity network and carry on the Latrobe Valley\\u2019s proud history of powering industry and communities. EnergyAustralia\\u2019s gas-fired Jeeralang power station, located at Hazelwood North in the Latrobe Valley, has been selected as the preferred location for our battery development, based on land availability and optimal connection to the grid.</p>\",\n      \"units\": [\n        {\n          \"code\": \"0WESSL1\",\n          \"fueltech_id\": \"battery_charging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 350.0,\n          \"dispatch_type\": \"LOAD\"\n        },\n        {\n          \"code\": \"0WESSG1\",\n          \"fueltech_id\": \"battery_discharging\",\n          \"status_id\": \"committed\",\n          \"capacity_registered\": 350.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WOYWOY\",\n      \"name\": \"Woy Woy\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WOYWOY1\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.0696,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WUNUSF\",\n      \"name\": \"Wunghnu\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Wunghnu Solar Farm project consists of a 90 MWdc solar farm and battery energy storage system (BESS). The solar project is located on Reillys Pit Road, Wunghnu, in the Goulburn Valley Region of Victoria. Development approval was received from Moira Shire Council in June 2018. The solar farm is situated on 222 hectares of agricultural land, which has been predominantly used for cropping.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WUNUSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 93.5,\n          \"data_first_seen\": \"2024-11-19T05:40:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WYASF\",\n      \"name\": \"Wyalong\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p>Situated 7.5 km north east of West Wyalong in New South Wales and occupying approximately 160 hectares of land, the Wyalong Solar Farm will generate enough electricity to power 27,000 average Australian homes, whilst also creating 150 jobs during construction and full and part-time positions during operation.</p>\",\n      \"units\": [\n        {\n          \"code\": \"WYASF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 62.32,\n          \"data_first_seen\": \"2023-08-01T11:10:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:10:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WYANGALA\",\n      \"name\": \"Wyangala A\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WYANGALA\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 20.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WYANGALB\",\n      \"name\": \"Wyangala B\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"NSW1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WYANGALB\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 4.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"WYNDW\",\n      \"name\": \"Wyndham\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"WYNDW\",\n          \"fueltech_id\": \"bioenergy_biogas\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 1.0,\n          \"emissions_factor_co2\": 0.0766,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YALLOURN\",\n      \"name\": \"Yallourn W\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Yallourn Power Station, now owned by EnergyAustralia a wholly owned subsidiary of the Hong-Kong\\u2013based CLP Group, is located in the Latrobe Valley of Victoria, Australia, beside the Latrobe River. Yallourn PS was a complex of six brown coal\\u2013fired thermal power stations built progressively from the 1920s to the 1960s; all except one have now been decommissioned. Today, only the 1,450 megawatts Yallourn W plant remains. It is the second largest power station in Victoria, supplying 22% of Victoria&#x27;s electricity and 8% of the National Electricity Market.</p>\",\n      \"units\": [\n        {\n          \"code\": \"YWPS4\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 380.0,\n          \"emissions_factor_co2\": 1.2999,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"YWPS2\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 360.0,\n          \"emissions_factor_co2\": 1.2999,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"YWPS3\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 380.0,\n          \"emissions_factor_co2\": 1.2999,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        },\n        {\n          \"code\": \"YWPS1\",\n          \"fueltech_id\": \"coal_brown\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 360.0,\n          \"emissions_factor_co2\": 1.2999,\n          \"data_first_seen\": \"1998-12-07T02:50:00+10:00\",\n          \"data_last_seen\": \"2025-07-12T18:25:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YSWF\",\n      \"name\": \"Yaloak South\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Located an hour west of Melbourne approximately 15 kilometres south of Ballan, the Yaloak South Wind Farm commenced construction in late 2016 and construction was completed in June 2018, 25 days ahead of schedule.</p><p>The project comprises fourteen Senvion MM92 wind turbine generators, rated at 2.05MW each, providing a total installed capacity of 28.7MW with a maximum hub height of 80m and a maximum tip height of 126.25m.</p><p>The project has been built in the southern section of the Parwan Valley, which is predominantly cleared agricultural land used for cropping and livestock grazing. Initial plans for a 70 turbine, 115MW capacity wind farm at the site were amended following concerns from local residents of the Parwan Valley about the potential impact on the wedge-tail eagle population and the visual amenity of the local area.</p>\",\n      \"units\": [\n        {\n          \"code\": \"YSWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 28.7,\n          \"data_first_seen\": \"2017-12-19T22:15:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YAMBUK\",\n      \"name\": \"Yambuk\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Yambuk wind farm is the first stage of Pacific Blue\\u2019s four-stage Portland Wind Energy Project (PWEP) in southwest Victoria.</p><p>Located next to our Codrington Wind Farm, near Port Fairy, the site was chosen for its ideal wind conditions \\u2013 its average annual wind speed of 30km/h is perfect for producing clean, non-polluting electricity.</p><p>Completed in 2005, the 30MW Yambuk wind farm comprises 20 wind generators that produce enough energy to meet the annual needs of 35,000 homes per annum, with an average electricity generation of 92.6GWh per year. The turbines installed are NEG Micon NM72C wind turbine generators, rated at 1.5MW each, with a maximum hub height of 70m and a maximum blade tip height of 106m.</p>\",\n      \"units\": [\n        {\n          \"code\": \"YAMBUKWF\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 30.0,\n          \"data_first_seen\": \"2009-07-01T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YANDIN\",\n      \"name\": \"Yandin\",\n      \"network_id\": \"WEM\",\n      \"network_region\": \"WEM\",\n      \"description\": \"<p>Yandin Wind Farm is Western Australia&#x27;s largest wind power station located in Dandaragan, Western Australia. Construction was completed in late October 2020. It comprises of 51 turbines with hub heights of 105m to maximise performance in the site\\u2019s specific wind conditions</p>\",\n      \"units\": [\n        {\n          \"code\": \"YANDIN_WF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 214.0,\n          \"data_first_seen\": \"2020-07-13T07:00:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T07:55:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YARANSF\",\n      \"name\": \"Yarranlea\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p>Yarranlea Solar is an innovative energy company, which has been established to harness the Earth&#x27;s abundant natural resources to create carbon-free energy. Using a range of technologies, our aim is to deliver renewable energy to established power grids across a 24 hour period. Yarranlea Solar is named after our flagship project located on sparsely vegetated farmland approximately 50km west of Toowoomba. This project will connect to the power grid using the existing Ergon Energy infrastructure in the area.</p>\",\n      \"units\": [\n        {\n          \"code\": \"YARANSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 121.0,\n          \"data_first_seen\": \"2020-01-07T09:05:00+08:00\",\n          \"data_last_seen\": \"2025-07-21T17:20:00+08:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YWNGAHYD\",\n      \"name\": \"Yarrawonga\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>Yarrawonga Power Station is adjacent to the original weir structure on Lake Mulwala, on the Murray River, on the south side of the Victorian/NSW border. Yarrawonga Power Station was completed in 1994 and is a run-of-river scheme using a Kaplan-type turbine. The station has two ESAC variable pitch Kaplan turbo-alternators, each with a capacity of 4.75 MW, and feeds power into the Victorian transmission grid at a voltage of 22 kV. Despite the power station&#x27;s presence, Lake Mulwala is kept at a reasonably constant level for recreational purposes. Changes in the head are driven by changes in the height of the Murray River. These changes are directly related to precipitation in the catchment areas and water releases from the Hume Dam.<br/><br/>Upstream storage control at Lake Hume and Dartmouth allows consistent storage levels at Lake Mulwala. This permits Yarrawonga Power Station to be a relatively consistent power producer.</p>\",\n      \"units\": [\n        {\n          \"code\": \"YWNGAHYD\",\n          \"fueltech_id\": \"hydro\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 9.0,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YARWUN\",\n      \"name\": \"Yarwun\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"QLD1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"YARWUN_1\",\n          \"fueltech_id\": \"gas_ccgt\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 154.0,\n          \"emissions_factor_co2\": 0.6132,\n          \"data_first_seen\": \"2010-07-08T10:35:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YATSF1\",\n      \"name\": \"Yatpool\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The 258-hectare Yatpool Solar Farm in northwest Victoria has 350,000 solar PV panels installed totaling 106.5 MWp and generating enough renewable electricity to power 40,000 homes. The Yatpool Solar Farm is just 6km from its sister project the Karadoc Solar Farm which is already generating 112.5 MWp of clean power.</p>\",\n      \"units\": [\n        {\n          \"code\": \"YATSF1\",\n          \"fueltech_id\": \"solar_utility\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 94.0,\n          \"data_first_seen\": \"2020-11-18T13:25:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T17:40:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YAWWF\",\n      \"name\": \"Yawong\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p>The Yawong Wind Farm was developed and constructed by BayWa r.e. Wind Pty Ltd in 2018, commenced operations in late 2018, and was acquired by Epic Energy in April 2019.</p>\",\n      \"units\": [\n        {\n          \"code\": \"YAWWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 7.2,\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    },\n    {\n      \"code\": \"YENDONWF\",\n      \"name\": \"Yendon\",\n      \"network_id\": \"NEM\",\n      \"network_region\": \"VIC1\",\n      \"description\": \"<p></p>\",\n      \"units\": [\n        {\n          \"code\": \"YENDWF1\",\n          \"fueltech_id\": \"wind\",\n          \"status_id\": \"operating\",\n          \"capacity_registered\": 144.4,\n          \"data_first_seen\": \"2019-06-19T00:05:00+10:00\",\n          \"data_last_seen\": \"2025-07-21T21:15:00+10:00\",\n          \"dispatch_type\": \"GENERATOR\"\n        }\n      ]\n    }\n  ],\n  \"total_records\": 570\n}\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/tests/test_ONS.py",
    "content": "from datetime import datetime\n\nimport pandas as pd\n\nfrom electricitymap.contrib.capacity_parsers.ONS import filter_data_by_date\n\n\ndef test_filter_data_by_date():\n    datetime_tuple1 = (datetime(1980, 1, 1), datetime(2015, 1, 1))\n    datetime_tuple2 = (datetime(2018, 10, 1), datetime(2023, 10, 1))\n    datetime_tuple3 = (datetime(2023, 7, 1), None)\n    datetime_tuple4 = (datetime(2010, 1, 1), datetime(2024, 10, 1))\n\n    test_df = pd.DataFrame(\n        [\n            {\"start\": datetime_tuple1[0], \"end\": datetime_tuple1[1], \"value\": 1},\n            {\"start\": datetime_tuple2[0], \"end\": datetime_tuple2[1], \"value\": 1},\n            {\"start\": datetime_tuple3[0], \"end\": datetime_tuple3[1], \"value\": 1},\n            {\"start\": datetime_tuple4[0], \"end\": datetime_tuple4[1], \"value\": 1},\n        ]\n    )\n\n    dt_1 = datetime(2019, 1, 1)\n    dt_2 = datetime(2015, 1, 1)\n    dt_3 = datetime(2023, 10, 31)\n\n    df_1 = filter_data_by_date(test_df, dt_1)\n    df_2 = filter_data_by_date(test_df, dt_2)\n    df_3 = filter_data_by_date(test_df, dt_3)\n\n    filtered_test_df_1 = test_df.loc[\n        (test_df[\"start\"].isin([datetime_tuple2[0], datetime_tuple4[0]]))\n    ]\n\n    filtered_test_df_2 = test_df.loc[\n        (test_df[\"start\"].isin([datetime_tuple1[0], datetime_tuple4[0]]))\n    ]\n    filtered_test_df_3 = test_df.loc[\n        (test_df[\"start\"].isin([datetime_tuple3[0], datetime_tuple4[0]]))\n    ]\n\n    assert df_1.equals(filtered_test_df_1)\n\n    assert df_2.equals(filtered_test_df_2)\n\n    assert df_3.equals(filtered_test_df_3)\n"
  },
  {
    "path": "electricitymap/contrib/capacity_parsers/tests/test_OPENELECTRICITY.py",
    "content": "import os\nfrom datetime import datetime\nfrom pathlib import Path\n\nimport pandas as pd\nimport pytest\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.capacity_parsers.OPENELECTRICITY import (\n    fetch_production_capacity,\n    filter_capacity_data_by_datetime,\n)\nfrom electricitymap.contrib.config import ZoneKey\n\nbase_path_to_mock = Path(\n    \"electricitymap/contrib/capacity_parsers/tests/mocks/OPENELECTRICITY\"\n)\n\n\ntest_df = pd.DataFrame(\n    [\n        {\"datetime\": datetime(2021, 1, 1), \"value\": 1},\n        {\"datetime\": datetime(2022, 1, 20), \"value\": 1},\n        {\"datetime\": datetime(2022, 4, 12), \"value\": 1},\n        {\"datetime\": datetime(2022, 10, 3), \"value\": 1},\n        {\"datetime\": datetime(2023, 3, 1), \"value\": 1},\n    ]\n)\n\n\n@pytest.fixture(autouse=True)\ndef openelectricity_token_env():\n    os.environ[\"OPENELECTRICITY_TOKEN\"] = \"token\"\n\n\ndef test_filter_capacity_data_by_datetime():\n    target_datetime_1 = datetime(2022, 3, 1)\n    filtered_df_1 = filter_capacity_data_by_datetime(test_df, target_datetime_1)\n    target_datetime_2 = datetime(2023, 10, 1)\n    filtered_df_2 = filter_capacity_data_by_datetime(test_df, target_datetime_2)\n    target_datetime_3 = datetime(2020, 10, 1)\n    filtered_df_3 = filter_capacity_data_by_datetime(test_df, target_datetime_3)\n\n    assert filtered_df_1.equals(test_df.loc[test_df[\"datetime\"] <= target_datetime_1])\n    assert filtered_df_2.equals(test_df)\n    assert filtered_df_3.equals(\n        test_df.loc[test_df[\"datetime\"] <= datetime(2021, 1, 1)]\n    )\n\n\ndef test_fetch_capacities(adapter, session, snapshot):\n    data = Path(base_path_to_mock, \"AU-QLD_capacities.json\")\n    adapter.register_uri(\n        GET,\n        ANY,\n        text=data.read_text(),\n    )\n\n    target_datetime = datetime(2025, 1, 1)\n    assert snapshot == fetch_production_capacity(\n        ZoneKey(\"AU-QLD\"), target_datetime, session\n    )\n"
  },
  {
    "path": "electricitymap/contrib/config/__init__.py",
    "content": "\"\"\"Global config variables with data read from the config directory.\"\"\"\n\nfrom operator import itemgetter\nfrom pathlib import Path\nfrom typing import Any\n\nfrom electricitymap.contrib.config.co2eq_parameters import generate_co2eq_parameters\nfrom electricitymap.contrib.config.reading import (\n    read_data_centers_config,\n    read_defaults,\n    read_exchanges_config,\n    read_zones_config,\n)\nfrom electricitymap.contrib.config.zones import (\n    generate_all_neighbours,\n    generate_zone_neighbours,\n    zone_bounding_boxes,\n    zone_parents,\n)\nfrom electricitymap.contrib.types import BoundingBox, ZoneKey\n\nCONFIG_DIR = Path(__file__).parent.parent.parent.parent.joinpath(\"config\").resolve()\n\nZONES_CONFIG = read_zones_config(CONFIG_DIR)\nRETIRED_ZONES_CONFIG = read_zones_config(CONFIG_DIR, retired=True)\nEXCHANGES_CONFIG = read_exchanges_config(CONFIG_DIR)\nDATA_CENTERS_CONFIG = read_data_centers_config(CONFIG_DIR)\n\nEU_ZONES = [\n    \"AT\",\n    \"BE\",\n    \"BG\",\n    \"CY\",\n    \"CZ\",\n    \"DE\",\n    \"DK-DK1\",\n    \"DK-DK2\",\n    \"EE\",\n    \"ES\",\n    \"ES-IB-ME\",\n    \"ES-IB-MA\",\n    \"ES-IB-IZ\",\n    \"ES-IB-FO\",\n    \"ES-CN-FV\",\n    \"ES-CN-LZ\",\n    \"ES-CN-GC\",\n    \"ES-CN-TE\",\n    \"ES-CN-LP\",\n    \"ES-CN-IG\",\n    \"ES-CN-HI\",\n    \"ES-CE\",\n    \"ES-ML\",\n    \"FI\",\n    \"FR\",\n    \"FR-COR\",\n    \"PF\",\n    \"NC\",\n    \"RE\",\n    \"GF\",\n    \"GP\",\n    \"MQ\",\n    \"PM\",\n    \"GR\",\n    \"HR\",\n    \"HU\",\n    \"IE\",\n    \"IT-SAR\",\n    \"IT-SIC\",\n    \"IT-NO\",\n    \"IT-CNO\",\n    \"IT-CSO\",\n    \"IT-SO\",\n    \"LT\",\n    \"LU\",\n    \"LV\",\n    \"MT\",\n    \"NL\",\n    \"PL\",\n    \"PT\",\n    \"PT-AC\",\n    \"PT-MA\",\n    \"RO\",\n    \"SE-SE1\",\n    \"SE-SE2\",\n    \"SE-SE3\",\n    \"SE-SE4\",\n    \"AX\",\n    \"SI\",\n    \"SK\",\n]\nEU_ZONES_CONFIG = {k: v for k, v in ZONES_CONFIG.items() if k in EU_ZONES}\n\n# Prepare the CO2eq parameters config dicts.\ndefaults = read_defaults(CONFIG_DIR)\n(\n    co2eq_parameters_all,\n    co2eq_parameters_direct,\n    co2eq_parameters_lifecycle,\n) = generate_co2eq_parameters(defaults, ZONES_CONFIG)\nCO2EQ_PARAMETERS_DIRECT = {**co2eq_parameters_all, **co2eq_parameters_direct}\nCO2EQ_PARAMETERS_LIFECYCLE = {**co2eq_parameters_all, **co2eq_parameters_lifecycle}\nCO2EQ_PARAMETERS = CO2EQ_PARAMETERS_LIFECYCLE  # Global LCA is the default\n\n# Make a dict mapping each zone to its bounding box.\nZONE_BOUNDING_BOXES: dict[ZoneKey, BoundingBox] = zone_bounding_boxes(ZONES_CONFIG)\n\n# Make a mapping from subzone to the parent zone (full zone).\nZONE_PARENT: dict[ZoneKey, ZoneKey] = zone_parents(ZONES_CONFIG)\n\n# Zone neighbours are zones that are connected by exchanges.\nZONE_NEIGHBOURS: dict[ZoneKey, list[ZoneKey]] = generate_zone_neighbours(\n    ZONES_CONFIG, EXCHANGES_CONFIG\n)\n\nALL_NEIGHBOURS: dict[ZoneKey, list[ZoneKey]] = generate_all_neighbours(EXCHANGES_CONFIG)\n\n\ndef _get_most_recent_value(emission_factors: dict) -> dict[dict, Any]:\n    return {\n        k: max(v, key=itemgetter(\"datetime\")) if isinstance(v, list) else v\n        for k, v in emission_factors.items()\n    }\n\n\ndef emission_factors(zone_key: ZoneKey) -> dict[str, float]:\n    \"\"\"Looks up the emission factors for a given zone.\"\"\"\n    override = CO2EQ_PARAMETERS[\"emissionFactors\"][\"zoneOverrides\"].get(zone_key, {})\n    defaults = CO2EQ_PARAMETERS[\"emissionFactors\"][\"defaults\"]\n\n    # Only use most recent yearly numbers from defaults & overrides\n    defaults = _get_most_recent_value(defaults)\n    override = _get_most_recent_value(override)\n\n    merged = {**defaults, **override}\n    return {k: (v or {}).get(\"value\") for (k, v) in merged.items()}\n"
  },
  {
    "path": "electricitymap/contrib/config/capacity.py",
    "content": "from dataclasses import dataclass\nfrom datetime import datetime\nfrom pathlib import Path\n\nfrom electricitymap.contrib.config.reading import read_zones_config\nfrom electricitymap.contrib.types import ZoneKey\n\nCONFIG_DIR = Path(__file__).parent.parent.parent.parent.joinpath(\"config\").resolve()\n\nZONES_CONFIG = read_zones_config(CONFIG_DIR)\n# Get productionCapacity source to zones mapping\nCAPACITY_PARSER_SOURCE_TO_ZONES: dict[str, list[ZoneKey]] = {}\nfor zone_id, zone_config in ZONES_CONFIG.items():\n    if zone_config.get(\"parsers\", {}).get(\"productionCapacity\") is None:\n        continue\n    source = zone_config.get(\"parsers\", {}).get(\"productionCapacity\").split(\".\")[0]\n    if source not in CAPACITY_PARSER_SOURCE_TO_ZONES:\n        CAPACITY_PARSER_SOURCE_TO_ZONES[source] = []\n    CAPACITY_PARSER_SOURCE_TO_ZONES[source].append(zone_id)\n\nZONE_TO_CAPACITY_PARSER_SOURCE = {\n    zone: source\n    for source, zones in CAPACITY_PARSER_SOURCE_TO_ZONES.items()\n    for zone in zones\n}\n\n\n@dataclass\nclass CapacityData:\n    value: float | None\n    source: str | None = None\n\n\ndef get_capacity_data(capacity_config: dict, dt: datetime) -> dict[str, float | None]:\n    \"\"\"Gets the capacity data for a given zone and datetime from ZONES_CONFIG.\"\"\"\n    capacity = {}\n    for mode, capacity_value in capacity_config.items():\n        if isinstance(capacity_value, int | float | None):\n            # TODO: This part is used for the old capacity format. It shoud be removed once all capacity configs are updated\n            capacity[mode] = capacity_value\n        else:\n            capacity[mode] = _get_capacity_from_dict_or_list(capacity_value, dt).value\n    return capacity\n\n\ndef get_capacity_data_with_source(\n    capacity_config: dict, dt: datetime\n) -> dict[str, CapacityData]:\n    \"\"\"Gets the capacity data for a given zone and datetime from ZONES_CONFIG.\"\"\"\n    capacity = {}\n    for mode, capacity_value in capacity_config.items():\n        if isinstance(capacity_value, int | float):\n            # TODO: This part is used for the old capacity format. It shoud be removed once all capacity configs are updated\n            capacity[mode] = CapacityData(capacity_value)\n        else:\n            capacity[mode] = _get_capacity_from_dict_or_list(capacity_value, dt)\n\n    return capacity\n\n\ndef _get_capacity_from_dict_or_list(\n    mode_capacity: list | dict, dt: datetime\n) -> CapacityData:\n    if isinstance(mode_capacity, dict):\n        # TODO: To be removed as eventually we should only have lists.\n        return CapacityData(mode_capacity[\"value\"], mode_capacity.get(\"source\"))\n    elif isinstance(mode_capacity, list):\n        capacity_tuples = [\n            (d[\"datetime\"], d[\"value\"], d.get(\"source\")) for d in mode_capacity\n        ]\n\n        if dt.isoformat() <= min(capacity_tuples)[0]:\n            return CapacityData(min(capacity_tuples)[1], min(capacity_tuples)[2])\n        else:\n            # valid datetime is the max datetime that is lower than the given datetime\n            # In other words, it is the most recent value that is valid for the given dt\n            max_tuple = max(\n                [(d, v, s) for d, v, s in capacity_tuples if d <= dt.isoformat()]\n            )\n            return CapacityData(max_tuple[1], max_tuple[2])\n"
  },
  {
    "path": "electricitymap/contrib/config/co2eq_parameters.py",
    "content": "\"\"\"Contains a function to make co2eq parameter dicts from\nconfig read from defaults.yaml and zones/*.yaml.\n\"\"\"\n\nfrom typing import Any\n\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef generate_co2eq_parameters(\n    defaults: dict[str, Any], zones_config: dict[ZoneKey, Any]\n) -> tuple[dict[str, Any], dict[str, Any], dict[str, Any]]:\n    \"\"\"Returns dicts with co2eq parameters.\n\n    Args:\n      defaults: config read from defaults.yaml\n      zones_config: config read from zones/*.yaml\n\n    Returns:\n        co2eq_parameters_all: dict with co2eq parameters that apply to all zones\n        co2eq_parameters_direct: dict with co2eq parameters that apply to direct emissions\n        co2eq_parameters_lifecycle: dict with co2eq parameters that apply to lifecycle emissions\n    \"\"\"\n    co2eq_parameters_all = {\n        k: {\n            \"defaults\": defaults[k],\n            \"zoneOverrides\": {},\n        }\n        for k in [\"fallbackZoneMixes\", \"isLowCarbon\", \"isRenewable\"]\n    }\n    co2eq_parameters_direct = {\n        \"emissionFactors\": {\n            \"defaults\": defaults[\"emissionFactors\"][\"direct\"],\n            \"zoneOverrides\": {},\n        },\n    }\n    co2eq_parameters_lifecycle = {\n        \"emissionFactors\": {\n            \"defaults\": defaults[\"emissionFactors\"][\"lifecycle\"],\n            \"zoneOverrides\": {},\n        },\n    }\n\n    # Populate zone overrides.\n    for zone_key, zone_config in zones_config.items():\n        for k in [\"fallbackZoneMixes\", \"isLowCarbon\", \"isRenewable\"]:\n            if k in zone_config:\n                co2eq_parameters_all[k][\"zoneOverrides\"][zone_key] = zone_config[k]\n                del zone_config[k]\n        if \"emissionFactors\" in zone_config:\n            for k in [\"direct\", \"lifecycle\"]:\n                if k in zone_config[\"emissionFactors\"]:\n                    if k == \"direct\":\n                        co2eq_parameters_direct[\"emissionFactors\"][\"zoneOverrides\"][\n                            zone_key\n                        ] = zone_config[\"emissionFactors\"][k]\n                    elif k == \"lifecycle\":\n                        co2eq_parameters_lifecycle[\"emissionFactors\"][\"zoneOverrides\"][\n                            zone_key\n                        ] = zone_config[\"emissionFactors\"][k]\n            del zone_config[\"emissionFactors\"]\n\n    return co2eq_parameters_all, co2eq_parameters_direct, co2eq_parameters_lifecycle\n"
  },
  {
    "path": "electricitymap/contrib/config/constants.py",
    "content": "EXCHANGE_FILENAME_ZONE_SEPARATOR = \"_\"\n\n\nWEATHER_GFS_KEYS = [\"wind\", \"solar\", \"temperature\", \"dewpoint\", \"precipitation\"]\nWEATHER_DATABASE_KEYS = [\n    \"wind_x\",\n    \"wind_y\",\n    \"solar\",\n    \"temperature\",\n    \"dewpoint\",\n    \"precipitation\",\n]\n\n# Note: this is sorted for plotting purposes\nPRODUCTION_MODES = [\n    \"nuclear\",\n    \"geothermal\",\n    \"biomass\",\n    \"coal\",\n    \"wind\",\n    \"solar\",\n    \"hydro\",\n    \"gas\",\n    \"oil\",\n    \"unknown\",\n]\nFORECASTED_PRODUCTION_MODES = [\n    \"solar\",\n    \"wind\",\n]\nSTORAGE_MODES = [\n    \"battery\",\n    \"hydro\",\n]\n\n\n# TODO(olc): Find a more explicit name for `ENERGIES`\n# TODO(olc): This is forecast specific, so it should not be here.\nENERGIES = PRODUCTION_MODES + [f\"{s} discharge\" for s in STORAGE_MODES]\n\nBATCH_SIZE = 500\nPLOT_COLUMNS = {\n    \"consumptionForecast\": {\"title\": \"consumption forecast\", \"col\": \"value\"},\n    \"consumption\": {\"title\": \"consumption\", \"col\": \"consumption\"},\n    \"production\": {\"title\": \"production total\", \"col\": \"prod_total\"},\n    \"price\": {\"title\": \"price\", \"col\": \"price\"},\n    \"generationForecast\": {\"title\": \"generation forecast\", \"col\": \"value\"},\n    \"exchange\": {\"title\": \"exchange\", \"col\": \"netFlow\"},\n    \"exchangeForecast\": {\"title\": \"exchange forecast\", \"col\": \"netFlow\"},\n    \"weatherForecast\": {\"title\": \"weather forecast\", \"col\": \"value\"},\n}\n\nMODE_COLORS = {\n    \"wind\": \"#74cdb9\",\n    \"solar\": \"#f27406\",\n    \"hydro\": \"#2772b2\",\n    \"battery charge\": \"lightgray\",\n    \"hydro charge\": \"#0052cc\",\n    \"hydro discharge\": \"#0052cc\",\n    \"battery discharge\": \"lightgray\",\n    \"biomass\": \"#166a57\",\n    \"geothermal\": \"yellow\",\n    \"nuclear\": \"#AEB800\",\n    \"gas\": \"#bb2f51\",\n    \"coal\": \"#ac8c35\",\n    \"oil\": \"#867d66\",\n    \"unknown\": \"lightgray\",\n}\n\nweatherForecastSchemaVersion = 3\n"
  },
  {
    "path": "electricitymap/contrib/config/data_center_model.py",
    "content": "\"\"\"Data Center model definitions.\"\"\"\n\nimport re\nfrom datetime import date\n\nfrom pydantic.v1 import BaseModel, validator\n\nfrom electricitymap.contrib.types import ZoneKey\n\nDATE_PATTERN = re.compile(r\"^\\d{4}(-\\d{2}(-\\d{2})?)?$\")\n\n\nclass StrictBaseModel(BaseModel):\n    class Config:\n        extra = \"forbid\"\n\n\nclass DataCenter(BaseModel):\n    provider: str\n    lonlat: tuple[float, float]\n    displayName: str\n    region: str\n    zoneKey: ZoneKey\n    operationalSince: date | None\n    operationalUntil: date | None\n    status: str | None\n    source: str | None\n\n    @property\n    def ID(self) -> str:\n        return f\"{self.provider}-{self.region}\"\n\n    @validator(\"provider\", \"region\", \"displayName\")\n    def string_not_empty(cls, v):\n        if not v or v.strip() == \"\":\n            raise ValueError(\"Value must be a non-empty string\")\n        return v\n\n    @validator(\"lonlat\")\n    def lonlat_valid(cls, v):\n        lon, lat = v\n        if not (-180 <= lon <= 180):\n            raise ValueError(\"Longitude must be between -180 and 180\")\n        if not (-90 <= lat <= 90):\n            raise ValueError(\"Latitude must be between -90 and 90\")\n        return v\n\n    @validator(\"operationalSince\", \"operationalUntil\", pre=True)\n    def parse_date(cls, v):\n        if v is None or isinstance(v, date):\n            return v\n        if not isinstance(v, str) or not DATE_PATTERN.match(v):\n            raise ValueError(\n                f\"Date '{v}' must be in YYYY, YYYY-MM, or YYYY-MM-DD format\"\n            )\n        parts = [int(p) for p in v.split(\"-\")]\n        year = parts[0]\n        month = parts[1] if len(parts) >= 2 else 1\n        day = parts[2] if len(parts) == 3 else 1\n        try:\n            return date(year, month, day)\n        except ValueError as err:\n            raise ValueError(f\"Date '{v}' is not a valid calendar date\") from err\n\n    @validator(\"zoneKey\")\n    def zone_key_exists(cls, v):\n        # Import here to avoid circular dependency\n        from electricitymap.contrib.config import ZONES_CONFIG\n\n        if v not in ZONES_CONFIG:\n            raise ValueError(\n                f\"Data center zone key {v} is not one of the allowed zone keys: {ZONES_CONFIG.keys()}\"\n            )\n        return v\n\n\nclass DataCenters(BaseModel):\n    \"\"\"Container for data centers.\"\"\"\n\n    data_centers: list[DataCenter]\n\n    class Config:\n        extra = \"forbid\"\n\n    # check that the ID for each data center is unique\n    @validator(\"data_centers\")\n    def ids_are_unique(cls, v):\n        ids = set()\n        for data_center in v:\n            if data_center.ID in ids:\n                raise ValueError(f\"Duplicate data center ID found: {data_center.ID}\")\n            ids.add(data_center.ID)\n        return v\n\n    @validator(\"data_centers\")\n    def check_unique_combination(cls, v):\n        combinations = set()\n        for data_center in v:\n            combination = (\n                data_center.provider,\n                data_center.region,\n                data_center.zoneKey,\n            )\n            if combination in combinations:\n                raise ValueError(\n                    f\"Duplicate provider-region-zoneKey combination found: {combination}\"\n                )\n            combinations.add(combination)\n        return v\n"
  },
  {
    "path": "electricitymap/contrib/config/emission_factors_lookup.py",
    "content": "from datetime import datetime, timezone\nfrom operator import itemgetter\nfrom typing import Any\n\nfrom pydantic import ValidationError\n\nfrom electricitymap.contrib.config import (\n    CO2EQ_PARAMETERS_DIRECT,\n    CO2EQ_PARAMETERS_LIFECYCLE,\n    ZONE_PARENT,\n    ZONES_CONFIG,\n)\nfrom electricitymap.contrib.config.constants import ENERGIES\nfrom electricitymap.contrib.config.model import (\n    EmissionFactorVariant,\n    YearZoneModeEmissionFactor,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef get_zone_specific_co2eq_parameter(\n    co2eq_parameters: dict,\n    zone_key: str,\n    key: str,\n    sub_key: str,\n    dt: datetime,\n    metadata: bool = False,\n) -> dict[str, float]:\n    if metadata:\n        return _get_zone_specific_co2eq_parameter_with_metadata(\n            co2eq_parameters=co2eq_parameters,\n            zone_key=zone_key,\n            key=key,\n            sub_key=sub_key,\n            dt=dt,\n        )\n    else:\n        return _get_zone_specific_co2eq_parameter_no_metadata(\n            co2eq_parameters=co2eq_parameters,\n            zone_key=zone_key,\n            key=key,\n            sub_key=sub_key,\n            dt=dt,\n        )\n\n\ndef _get_zone_specific_co2eq_parameter_no_metadata(\n    co2eq_parameters: dict, zone_key: str, key: str, sub_key: str, dt: datetime\n) -> dict[str, float]:  # TODO: actually this returns Union[Dict, bool]\n    \"\"\"Accessor for co2eq_parameters.\n    If Available, it will return the zoneOverride value. If not, it will return the default value.\n\n    Args:\n        co2eq_parameters (dict): The dictionary to read from.\n        zone_key (str): The zone_key to try and find a zoneOverride for.\n        key (str): The key of the parameter to find.\n        sub_key (str): The specific sub key inside the parameter that you want to access\n        dt (datetime): Will return the most recent co2eq for that dt. For the latest co2eq, pass `datetime.max`\n\n    Raises:\n        ValueError: Raised when both the zoneOverride and default value is unavailable\n    \"\"\"\n    # TODO this doesn't raise a ValueError at the moment. Which gives typing errors because it can return None.\n    params = co2eq_parameters[key]\n    zone_key = ZoneKey(zone_key)\n\n    defaults = params[\"defaults\"][sub_key]\n    zone_override = params[\"zoneOverrides\"].get(zone_key, {}).get(sub_key, None)\n    # If no entry was found, use the parent if it exists\n    if ZONE_PARENT.get(zone_key) and not zone_override:\n        zone_override = (\n            params[\"zoneOverrides\"].get(ZONE_PARENT[zone_key], {}).get(sub_key, None)\n        )\n\n    res = None\n    res = zone_override if zone_override is not None else defaults\n\n    if isinstance(res, list):\n        # `n` dates are sorted in ascending order (d1, d2, ..., dn)\n        # d1 is valid from from (epoch to d2)\n        # d2 is valid from (d2 to d3)\n        # dn is valid from (dn to end_of_time)\n\n        if len(res) == 0:\n            raise ValueError(\n                f\"Error in given co2eq_parameters. List is empty for [{zone_key}, {key}, {sub_key}]\"\n            )\n\n        res.sort(key=itemgetter(\"datetime\"))\n        dt = dt.replace(tzinfo=timezone.utc)\n        for co2eq in reversed(res):\n            co2eq_dt = datetime.fromisoformat(co2eq[\"datetime\"]).replace(\n                tzinfo=timezone.utc\n            )\n            if co2eq_dt <= dt:\n                return co2eq  # type: ignore[no-any-return]\n        return res[0]  # type: ignore[no-any-return]\n\n    else:\n        return res  # type: ignore[no-any-return]\n\n\ndef _get_zone_specific_co2eq_parameter_with_metadata(\n    co2eq_parameters: dict,\n    zone_key: str,\n    key: str,\n    sub_key: str,\n    dt: datetime,\n) -> dict[str, Any]:\n    \"\"\"\n    Lookup logic identical to get_zone_specific_co2eq_parameter.\n    Adds a 'variant' field that provides context about where an emission factor comes from.\n    Variant selection logic:\n\n    GLOBAL/ZONE -> defined in config/defaults.yaml or config/zones/<zone_key>.yaml\n\n    *_EXACT_TIMELESS -> no \"datetime\"\n    *_EXACT_TIMELY -> has \"datetime\" and \"datetime\".year == dt.year\n    *_FALLBACK_LATEST -> has \"datetime\" and max(\"datetime\").year < dt.year\n    *_FALLBACK_OLDER -> has \"datetime\" and max(\"datetime\").year < dt.year < min(\"datetime\").year and is not EXACT\n    *_FALLBACK_OLDEST -> has \"datetime\" and dt.year < min(\"datetime\").year\n    \"\"\"\n    params = co2eq_parameters[key]\n    zone_key = ZoneKey(zone_key)\n\n    defaults = params[\"defaults\"][sub_key]\n    zone_override = params[\"zoneOverrides\"].get(zone_key, {}).get(sub_key, None)\n    # If no entry was found, use the parent if it exists\n    if ZONE_PARENT.get(zone_key) and not zone_override:\n        zone_override = (\n            params[\"zoneOverrides\"].get(ZONE_PARENT[zone_key], {}).get(sub_key, None)\n        )\n\n    res = None\n    res = zone_override if zone_override is not None else defaults\n\n    if isinstance(res, list):\n        # `n` dates are sorted in ascending order (d1, d2, ..., dn)\n        # d1 is valid from from (epoch to d2)\n        # d2 is valid from (d2 to d3)\n        # dn is valid from (dn to end_of_time)\n\n        if len(res) == 0:\n            raise ValueError(\n                f\"Error in given co2eq_parameters. List is empty for [{zone_key}, {key}, {sub_key}]\"\n            )\n\n        res.sort(key=itemgetter(\"datetime\"))\n        dt = dt.replace(tzinfo=timezone.utc)\n        for i, co2eq in enumerate(reversed(res)):\n            co2eq_dt = datetime.fromisoformat(co2eq[\"datetime\"]).replace(\n                tzinfo=timezone.utc\n            )\n            if co2eq_dt <= dt:\n                ret = co2eq\n\n                ef_year = co2eq_dt.year\n                dt_year = dt.year\n                if ef_year == dt_year:\n                    if zone_override:\n                        variant = EmissionFactorVariant.ZONE_EXACT_TIMELY\n                    else:\n                        variant = EmissionFactorVariant.GLOBAL_EXACT_TIMELY\n                elif ef_year < dt_year:\n                    if i == 0:\n                        if zone_override:\n                            variant = EmissionFactorVariant.ZONE_FALLBACK_LATEST\n                        else:\n                            variant = EmissionFactorVariant.GLOBAL_FALLBACK_LATEST\n                    else:\n                        if zone_override:\n                            variant = EmissionFactorVariant.ZONE_FALLBACK_OLDER\n                        else:\n                            variant = EmissionFactorVariant.GLOBAL_FALLBACK_OLDER\n\n                ret[\"variant\"] = variant.value\n                return ret\n\n        # res is sorted in ascending order, if we get here\n        # it means dt < res[0][\"datetime\"]\n        ret = res[0]\n        if zone_override:\n            variant = EmissionFactorVariant.ZONE_FALLBACK_OLDEST\n        else:\n            variant = EmissionFactorVariant.GLOBAL_FALLBACK_OLDEST\n        ret[\"variant\"] = variant.value\n        return ret\n\n    else:\n        # res is not a list, which implies it's a dict\n        # there are two kinds of dicts\n        # if it has \"datetime\" then it's timely\n        # else it's timeless\n        ret = res\n        ret_dt = res.get(\"datetime\")\n        if ret_dt is None:\n            if zone_override:\n                variant = EmissionFactorVariant.ZONE_EXACT_TIMELESS\n            else:\n                variant = EmissionFactorVariant.GLOBAL_EXACT_TIMELESS\n        else:\n            ret_dt_year = (\n                datetime.fromisoformat(ret_dt).replace(tzinfo=timezone.utc).year\n            )\n            dt_year = dt.year\n            if ret_dt_year == dt_year:\n                if zone_override:\n                    variant = EmissionFactorVariant.ZONE_EXACT_TIMELY\n                else:\n                    variant = EmissionFactorVariant.GLOBAL_EXACT_TIMELY\n            elif ret_dt_year < dt_year:\n                if zone_override:\n                    variant = EmissionFactorVariant.ZONE_FALLBACK_LATEST\n                else:\n                    variant = EmissionFactorVariant.GLOBAL_FALLBACK_LATEST\n            else:\n                if zone_override:\n                    variant = EmissionFactorVariant.ZONE_FALLBACK_OLDEST\n                else:\n                    variant = EmissionFactorVariant.GLOBAL_FALLBACK_OLDEST\n\n        ret[\"variant\"] = variant.value\n        return ret\n\n\ndef _get_emission_factor_lifecycle_and_direct(\n    zone_key, dt, mode\n) -> YearZoneModeEmissionFactor:\n    item = {}\n    item[\"dt\"] = dt\n    item[\"zone_key\"] = zone_key\n    item[\"mode\"] = mode\n    for description, data in [\n        (\"lifecycle\", CO2EQ_PARAMETERS_LIFECYCLE),\n        (\"direct\", CO2EQ_PARAMETERS_DIRECT),\n    ]:\n        result = get_zone_specific_co2eq_parameter(\n            co2eq_parameters=data,\n            zone_key=zone_key,\n            key=\"emissionFactors\",\n            sub_key=mode,\n            dt=dt,\n            metadata=True,\n        )\n        d = {\n            f\"{description}_{k}\": v\n            for k, v in result.items()\n            if k in (\"datetime\", \"source\", \"value\", \"variant\")\n        }\n        item = {**item, **d}\n    model_obj = YearZoneModeEmissionFactor(**item)\n    return model_obj\n\n\ndef get_emission_factors_with_metadata_all_years(\n    start: int | None = None,\n    end: int | None = None,\n) -> tuple[list[YearZoneModeEmissionFactor], list[ValidationError]]:\n    start = 2015 if start is None else start\n    end = datetime.now(tz=timezone.utc).year if end is None else end\n\n    efs = []\n    errors = []\n    for zone_key in ZONES_CONFIG:\n        for i in range(start, end + 1):\n            dt = datetime(year=i, month=1, day=1, tzinfo=timezone.utc)\n            for mode in ENERGIES:\n                try:\n                    model_obj = _get_emission_factor_lifecycle_and_direct(\n                        zone_key, dt, mode\n                    )\n                    efs.append(model_obj)\n                except ValidationError as e:\n                    errors.append(\n                        {\n                            \"mode\": mode,\n                            \"zone_key\": zone_key,\n                            \"dt\": dt,\n                            \"errors\": e.errors(),\n                        }\n                    )\n\n    return efs, errors\n"
  },
  {
    "path": "electricitymap/contrib/config/model.py",
    "content": "from collections.abc import Callable\nfrom datetime import date, datetime, timezone\nfrom enum import Enum\n\n# Pydantic v1.10.17+ provides .v1 namespace for forward compatibility with v2\nfrom pydantic.v1 import (\n    BaseModel,\n    Field,\n    NonNegativeFloat,\n    PositiveInt,\n    confloat,\n    root_validator,\n    validator,\n)\nfrom pydantic.v1.utils import import_string\n\nfrom electricitymap.contrib.config import (\n    CO2EQ_PARAMETERS_DIRECT,\n    CO2EQ_PARAMETERS_LIFECYCLE,\n    EXCHANGES_CONFIG,\n    ZONE_NEIGHBOURS,\n    ZONES_CONFIG,\n)\nfrom electricitymap.contrib.lib.models.constants import VALID_CURRENCIES\nfrom electricitymap.contrib.types import Point, ZoneKey\n\n# NOTE: we could cast Point to a NamedTuple with x/y accessors\n\nPercentage = confloat(ge=0, le=1)\n\n\nclass StrictBaseModel(BaseModel):\n    class Config:\n        extra = \"forbid\"\n\n\nclass StrictBaseModelWithAlias(BaseModel):\n    class Config:\n        extra = \"forbid\"\n        # To allow for both comment and _comment.\n        # _source and source\n        # _url and url\n        # TODO: stick to one of them\n        allow_population_by_field_name = True\n\n\nclass ModeCapacity(StrictBaseModelWithAlias):\n    source: str | None = Field(None, alias=\"_source\")\n    comment: str | None = Field(None, alias=\"_comment\")\n    url: str | list[str] | None = Field(None, alias=\"_url\")\n    datetime: date | datetime | None\n    value: NonNegativeFloat | None\n\n\nclass Capacity(StrictBaseModel):\n    # TODO: if zone.json used underscores for keys we didn't need the Field()\n    battery_storage: (\n        ModeCapacity | list[ModeCapacity] | NonNegativeFloat\n    ) | None = Field(None, alias=\"battery storage\")\n    biomass: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n    coal: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n    gas: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n    geothermal: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n    hydro_storage: (\n        ModeCapacity | list[ModeCapacity] | NonNegativeFloat\n    ) | None = Field(None, alias=\"hydro storage\")\n    hydro: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n    nuclear: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n    oil: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n    solar: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n    unknown: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n    wind: (ModeCapacity | list[ModeCapacity] | NonNegativeFloat) | None\n\n\ndef _get_parser_folder(parser_key: str) -> str:\n    return (\n        \"electricitymap.contrib.capacity_parsers\"\n        if parser_key == \"productionCapacity\"\n        else \"parsers\"\n    )\n\n\nclass ParsersBaseModel(StrictBaseModel):\n    def get_function(self, data_type: str) -> Callable | None:\n        \"\"\"Lazy load parser functions.\n\n        This requires the consumer to have installed all parser dependencies.\n\n        Returns:\n            Optional[Callable]: parser function\n        \"\"\"\n        function_str = getattr(self, data_type)\n\n        if function_str:\n            parser_folder = _get_parser_folder(data_type)\n            return import_string(f\"{parser_folder}.{function_str}\")\n\n\nclass Parsers(ParsersBaseModel):\n    consumption: str | None\n    consumptionForecast: str | None\n    generationForecast: str | None\n    productionPerModeForecast: str | None\n    productionPerModeForecastDayAhead: str | None\n    productionPerModeForecastIntraday: str | None\n    productionPerModeForecastLatest: str | None\n    dayaheadLocationalMarginalPrice: str | None\n    realtimeLocationalMarginalPrice: str | None\n    price: str | None\n    priceIntraday: str | None\n    production: str | None\n    productionCapacity: str | None\n    gridAlerts: str | None\n\n\nclass Source(StrictBaseModel):\n    link: str\n\n\nclass Delays(StrictBaseModel):\n    consumption: PositiveInt | None\n    consumptionForecast: PositiveInt | None\n    generationForecast: PositiveInt | None\n    price: PositiveInt | None\n    production: PositiveInt | None\n    productionPerModeForecast: PositiveInt | None\n\n\nclass Zone(StrictBaseModelWithAlias):\n    bounding_box: list[Point] | None\n    bypass_aggregation_checks: list[ZoneKey] | None = Field(\n        [], alias=\"bypassedSubZones\"\n    )\n    capacity: Capacity | None\n    center_point: Point | None\n    centroid: Point | None\n    comment: str | None = Field(None, alias=\"_comment\")\n    contributors: list[str] | None\n    delays: Delays | None\n    disclaimer: str | None\n    parsers: Parsers = Parsers()\n    generation_only: bool | None\n    can_have_zero_production: bool | None\n    has_day_ahead_price_license: bool | None\n    hide_day_ahead_price: bool | None\n    sub_zone_names: list[ZoneKey] | None = Field(None, alias=\"subZoneNames\")\n    timezone: str | None\n    key: ZoneKey  # This is not part of zones/{zone_key}.yaml, but added here to enable self referencing\n    sources: dict[str, Source] | None\n    region: str | None\n    country: str | None\n    zone_name: str | None\n    zone_short_name: str | None\n    country_name: str | None\n    currency: str | None\n\n    @validator(\"currency\")\n    def currency_is_valid(cls, v):\n        if v and v not in VALID_CURRENCIES:\n            raise ValueError(f\"Currency {v} is not a valid ISO 4217 currency code\")\n        return v\n\n    def neighbors(self) -> list[ZoneKey]:\n        return ZONE_NEIGHBOURS.get(self.key, [])\n\n\nclass ExchangeParsers(ParsersBaseModel):\n    exchange: str | None\n    exchangeCapacityForecastDayAhead: str | None\n    exchangeCapacityForecastWeekAhead: str | None\n    exchangeCapacityForecastMonthAhead: str | None\n    shadowAuctionAtcDayAhead: str | None\n    coreExternalAtcDayAhead: str | None\n    maxBexDayAhead: str | None\n    scheduledExchangesDayAhead: str | None\n    maxBflowDayAhead: str | None\n    exchangeForecast: str | None\n\n\nclass Exchange(StrictBaseModelWithAlias):\n    capacity: tuple[int, int] | None\n    comment: str | None = Field(None, alias=\"_comment\")\n    lonlat: tuple[float, float] | None\n    parsers: ExchangeParsers | None\n    rotation: int | None\n\n\nclass PowerOriginRatiosValues(StrictBaseModelWithAlias):\n    battery_charge: Percentage | None = Field(None, alias=\"battery charge\")\n    battery_discharge: Percentage | None = Field(None, alias=\"battery discharge\")\n    biomass: Percentage | None\n    coal: Percentage | None\n    gas: Percentage | None\n    geothermal: Percentage | None\n    hydro_discharge: Percentage | None = Field(None, alias=\"hydro discharge\")\n    hydro_charge: Percentage | None = Field(None, alias=\"hydro charge\")\n    hydro: Percentage | None\n    nuclear: Percentage | None\n    oil: Percentage | None\n    solar: Percentage | None\n    unknown: Percentage | None\n    wind: Percentage | None\n\n    @root_validator\n    @classmethod\n    def check_sum(cls, values):\n        \"\"\"Check that the sum of all values is approximately 1.\"\"\"\n        _v = [0 if v is None else v for v in values.values()]\n        if abs(sum(_v) - 1) > 0.01:\n            raise ValueError(\n                f\"All values must approximately sum to 1. Sum to {sum(_v)}\"\n            )\n        return values\n\n\nclass PowerOriginRatios(StrictBaseModelWithAlias):\n    source: str | None = Field(None, alias=\"_source\")\n    comment: str | None = Field(None, alias=\"_comment\")\n    url: str | list[str] | None = Field(None, alias=\"_url\")\n    datetime: date | datetime | None\n    value: PowerOriginRatiosValues\n\n\nclass PowerOriginRatiosForZone(StrictBaseModelWithAlias):\n    source: str | None = Field(None, alias=\"_source\")\n    comment: str | None = Field(None, alias=\"_comment\")\n    url: str | list[str] | None = Field(None, alias=\"_url\")\n    power_origin_ratios: list[PowerOriginRatios] | PowerOriginRatios = Field(\n        alias=\"powerOriginRatios\"\n    )\n\n\nclass FallbackZoneMixes(StrictBaseModelWithAlias):\n    defaults: PowerOriginRatiosForZone\n    zone_overrides: dict[str, PowerOriginRatiosForZone] = Field(alias=\"zoneOverrides\")\n\n\nclass ModeCategoryContribution(StrictBaseModelWithAlias):\n    source: str | None = Field(None, alias=\"_source\")\n    comment: str | None = Field(None, alias=\"_comment\")\n    url: str | list[str] | None = Field(None, alias=\"_url\")\n    datetime: datetime | date | None\n    value: Percentage | None\n\n\nclass CategoryContribution(StrictBaseModelWithAlias):\n    battery_charge: None | (\n        ModeCategoryContribution | list[ModeCategoryContribution]\n    ) = Field(None, alias=\"battery charge\")\n    battery_discharge: None | (\n        ModeCategoryContribution | list[ModeCategoryContribution]\n    ) = Field(None, alias=\"battery discharge\")\n    biomass: ModeCategoryContribution | list[ModeCategoryContribution] | None\n    coal: ModeCategoryContribution | list[ModeCategoryContribution] | None\n    gas: ModeCategoryContribution | list[ModeCategoryContribution] | None\n    geothermal: None | (ModeCategoryContribution | list[ModeCategoryContribution])\n    hydro_charge: None | (\n        ModeCategoryContribution | list[ModeCategoryContribution]\n    ) = Field(None, alias=\"hydro charge\")\n    hydro_discharge: None | (\n        ModeCategoryContribution | list[ModeCategoryContribution]\n    ) = Field(None, alias=\"hydro discharge\")\n    hydro: ModeCategoryContribution | list[ModeCategoryContribution] | None\n    nuclear: ModeCategoryContribution | list[ModeCategoryContribution] | None\n    oil: ModeCategoryContribution | list[ModeCategoryContribution] | None\n    solar: ModeCategoryContribution | list[ModeCategoryContribution] | None\n    unknown: ModeCategoryContribution | list[ModeCategoryContribution] | None\n    wind: ModeCategoryContribution | list[ModeCategoryContribution] | None\n\n    @root_validator\n    @classmethod\n    def check_contributions(cls, values):\n        for v in values.values():\n            if isinstance(v, list):\n                # verify ordered by datetime\n                dts = [c.datetime for c in v]\n                if dts != sorted(dts):\n                    raise ValueError(\"Contributions must be ordered by datetime\")\n        return values\n\n\nclass IsLowCarbon(StrictBaseModelWithAlias):\n    defaults: CategoryContribution = CategoryContribution()\n    zone_overrides: dict[str, CategoryContribution] = Field(alias=\"zoneOverrides\")\n\n\nclass IsRenewable(StrictBaseModelWithAlias):\n    defaults: CategoryContribution = CategoryContribution()\n    zone_overrides: dict[str, CategoryContribution] = Field(alias=\"zoneOverrides\")\n\n\nclass ModeEmissionFactor(StrictBaseModelWithAlias):\n    source: str | None = Field(None, alias=\"_source\")\n    comment: str | None = Field(None, alias=\"_comment\")\n    url: str | list[str] | None = Field(None, alias=\"_url\")\n    datetime: date | datetime | None\n    value: NonNegativeFloat\n\n\nclass AllModesEmissionFactors(StrictBaseModelWithAlias):\n    battery_charge: None | (\n        list[ModeEmissionFactor] | ModeEmissionFactor\n    ) = Field(None, alias=\"battery charge\")\n    battery_discharge: None | (\n        list[ModeEmissionFactor] | ModeEmissionFactor\n    ) = Field(None, alias=\"battery discharge\")\n    biomass: list[ModeEmissionFactor] | ModeEmissionFactor | None\n    coal: list[ModeEmissionFactor] | ModeEmissionFactor | None\n    gas: list[ModeEmissionFactor] | ModeEmissionFactor | None\n    geothermal: list[ModeEmissionFactor] | ModeEmissionFactor | None\n    hydro_charge: list[ModeEmissionFactor] | ModeEmissionFactor | None = Field(\n        None, alias=\"hydro charge\"\n    )\n    hydro_discharge: None | (\n        list[ModeEmissionFactor] | ModeEmissionFactor\n    ) = Field(None, alias=\"hydro discharge\")\n    hydro: list[ModeEmissionFactor] | ModeEmissionFactor | None\n    nuclear: list[ModeEmissionFactor] | ModeEmissionFactor | None\n    oil: list[ModeEmissionFactor] | ModeEmissionFactor | None\n    solar: list[ModeEmissionFactor] | ModeEmissionFactor | None\n    unknown: list[ModeEmissionFactor] | ModeEmissionFactor | None\n    wind: list[ModeEmissionFactor] | ModeEmissionFactor | None\n\n    @root_validator\n    @classmethod\n    def check_emission_factors(cls, values):\n        \"\"\"\n        Check that all emission factors given as list are not empty.\n        \"\"\"\n        for v in values.values():\n            if isinstance(v, list) and len(v) == 0:\n                raise ValueError(\"Emission factors must not be an empty list\")\n        return values\n\n\nclass EmissionFactors(StrictBaseModelWithAlias):\n    defaults: AllModesEmissionFactors\n    zone_overrides: dict[str, AllModesEmissionFactors] = Field(alias=\"zoneOverrides\")\n\n\nclass CO2eqParameters(StrictBaseModelWithAlias):\n    fallback_zone_mixes: FallbackZoneMixes = Field(alias=\"fallbackZoneMixes\")\n    is_low_carbon: IsLowCarbon = Field(alias=\"isLowCarbon\")\n    is_renewable: IsRenewable = Field(alias=\"isRenewable\")\n    emission_factors: EmissionFactors = Field(alias=\"emissionFactors\")\n\n\nclass ConfigModel(StrictBaseModel):\n    exchanges: dict[str, Exchange]\n    zones: dict[str, Zone]\n\n\n# The co2eq parameters config model is separated as it does not respect the\n# format: [zone_key]: [config for zone]\n# NOTE: Possibility to parse the co2eq config to make it available as [zone_key]: [co2eq params]\nclass CO2eqConfigModel(StrictBaseModel):\n    direct: CO2eqParameters\n    lifecycle: CO2eqParameters\n\n\ndef _load_config_model() -> ConfigModel:\n    for zone_key, zone in ZONES_CONFIG.items():\n        zone[\"key\"] = zone_key\n\n    return ConfigModel(exchanges=EXCHANGES_CONFIG, zones=ZONES_CONFIG)\n\n\nCONFIG_MODEL = _load_config_model()\nCO2EQ_CONFIG_MODEL = CO2eqConfigModel(\n    direct=CO2EQ_PARAMETERS_DIRECT, lifecycle=CO2EQ_PARAMETERS_LIFECYCLE\n)\n\n\nclass EmissionFactorVariant(Enum):\n    \"\"\"\n    Describes where an emission factor (EF) comes from.\n    See electricitymap/contrib/config/emission_factors.py::_get_zone_specific_co2eq_parameter_with_metadata\n    \"\"\"\n\n    GLOBAL_EXACT_TIMELESS = \"global_exact_timeless\"\n    GLOBAL_EXACT_TIMELY = \"global_exact_timely\"\n    GLOBAL_FALLBACK_LATEST = \"global_fallback_latest\"\n    GLOBAL_FALLBACK_OLDER = \"global_fallback_older\"\n    GLOBAL_FALLBACK_OLDEST = \"global_fallback_oldest\"\n\n    ZONE_EXACT_TIMELESS = \"zone_exact_timeless\"\n    ZONE_EXACT_TIMELY = \"zone_exact_timely\"\n    ZONE_FALLBACK_LATEST = \"zone_fallback_latest\"\n    ZONE_FALLBACK_OLDER = \"zone_fallback_older\"\n    ZONE_FALLBACK_OLDEST = \"zone_fallback_oldest\"\n\n\nclass EmissionFactorMode(Enum):\n    BIOMASS = \"biomass\"\n    COAL = \"coal\"\n    GAS = \"gas\"\n    GEOTHERMAL = \"geothermal\"\n    HYDRO = \"hydro\"\n    NUCLEAR = \"nuclear\"\n    OIL = \"oil\"\n    SOLAR = \"solar\"\n    UNKNOWN = \"unknown\"\n    WIND = \"wind\"\n    BATTERY_DISCHARGE = \"battery discharge\"\n    HYDRO_DISCHARGE = \"hydro discharge\"\n\n\nclass YearZoneModeEmissionFactor(StrictBaseModelWithAlias):\n    dt: datetime = Field(..., alias=\"datetime\")\n    zone_key: ZoneKey\n    mode: EmissionFactorMode\n    lifecycle_value: NonNegativeFloat\n    lifecycle_source: str\n    lifecycle_variant: EmissionFactorVariant\n    lifecycle_datetime: datetime | None\n    direct_value: NonNegativeFloat\n    direct_source: str\n    direct_variant: EmissionFactorVariant\n    direct_datetime: datetime | None\n\n    @validator(\"dt\", \"lifecycle_datetime\", \"direct_datetime\", pre=True)\n    def validate_datetime_field(cls, v: datetime | None) -> datetime | None:\n        if v is None:\n            return v\n\n        if isinstance(v, str):\n            v = datetime.fromisoformat(v).replace(tzinfo=timezone.utc)\n\n        if v.tzinfo is None or v.tzinfo.utcoffset(v) is None:\n            raise ValueError(\"Datetime must be timezone-aware\")\n\n        truncated_to_year = v.replace(\n            month=1,\n            day=1,\n            hour=0,\n            minute=0,\n            second=0,\n            microsecond=0,\n        )\n        if v != truncated_to_year:\n            raise ValueError(\"Datetime must be truncated to year.\")\n        return v\n\n    @root_validator\n    def check_factor_relationship(cls, values):\n        direct_value = values[\"direct_value\"]\n        lifecycle_value = values[\"lifecycle_value\"]\n        if direct_value > lifecycle_value:\n            raise ValueError(\n                f\"Direct factor must be <= lifecycle factor. Got {direct_value=}, {lifecycle_value=}\"\n            )\n        return values\n"
  },
  {
    "path": "electricitymap/contrib/config/py.typed",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/config/reading.py",
    "content": "import json\nfrom typing import Any\n\nfrom ruamel.yaml import YAML\n\nfrom electricitymap.contrib.config.constants import EXCHANGE_FILENAME_ZONE_SEPARATOR\nfrom electricitymap.contrib.types import ZoneKey\n\nyaml = YAML(typ=\"safe\")\n\n\ndef read_defaults(config_dir) -> dict[str, Any]:\n    \"\"\"Reads the defaults.yaml file.\"\"\"\n    defaults_path = config_dir.joinpath(\"defaults.yaml\")\n    with open(defaults_path, encoding=\"utf-8\") as file:\n        return yaml.load(file)\n\n\ndef read_zones_config(config_dir, retired=False) -> dict[ZoneKey, Any]:\n    \"\"\"Reads all the zone config files.\"\"\"\n    zones_config: dict[ZoneKey, Any] = {}\n    for zone_path in config_dir.joinpath(\n        \"retired_zones\" if retired is True else \"zones\"\n    ).glob(\"*.yaml\"):\n        try:\n            zone_key = ZoneKey(zone_path.stem)\n            with open(zone_path, encoding=\"utf-8\") as file:\n                zones_config[zone_key] = yaml.load(file)\n        except Exception as e:\n            print(f\"Error reading zone config for {zone_path.stem}: {e}\")\n    return zones_config\n\n\ndef read_exchanges_config(config_dir) -> dict[ZoneKey, Any]:\n    \"\"\"Reads all the exchange config files.\"\"\"\n    exchanges_config = {}\n    for exchange_path in config_dir.joinpath(\"exchanges\").glob(\"*.yaml\"):\n        exchange_key_unicode = exchange_path.stem\n        zone_keys = exchange_key_unicode.split(EXCHANGE_FILENAME_ZONE_SEPARATOR)\n        assert len(zone_keys) == 2\n        exchange_key = \"->\".join(zone_keys)\n        with open(exchange_path, encoding=\"utf-8\") as file:\n            exchanges_config[exchange_key] = yaml.load(file)\n    return exchanges_config\n\n\ndef read_data_centers_config(config_dir):\n    \"\"\"Reads the data centers config file.\"\"\"\n    from electricitymap.contrib.config.data_center_model import DataCenters\n\n    data_centers_path = config_dir.joinpath(\"data_centers\", \"data_centers.json\")\n    with open(data_centers_path, encoding=\"utf-8\") as file:\n        data_centers_dict = json.load(file)\n    return DataCenters(data_centers=list(data_centers_dict.values()))\n"
  },
  {
    "path": "electricitymap/contrib/config/types.py",
    "content": "# DEPRECATED: Import from electricitymap.contrib.types instead.\n# This re-export is kept for backward compatibility.\nfrom electricitymap.contrib.types import BoundingBox, Point\n\n__all__ = [\"Point\", \"BoundingBox\"]\n"
  },
  {
    "path": "electricitymap/contrib/config/zones.py",
    "content": "\"\"\"This module contains functions for working with zones configs.\"\"\"\n\nfrom collections import defaultdict\nfrom typing import Any\n\nfrom electricitymap.contrib.types import BoundingBox, ZoneKey\n\n\ndef zone_bounding_boxes(zones_config: dict[ZoneKey, Any]) -> dict[ZoneKey, BoundingBox]:\n    \"\"\"Returns a dict mapping each zone to its bounding box.\"\"\"\n    bounding_boxes = {}\n    for zone_id, zone_config in zones_config.items():\n        if \"bounding_box\" in zone_config:\n            bounding_boxes[zone_id] = zone_config[\"bounding_box\"]\n    return bounding_boxes\n\n\ndef zone_parents(zones_config: dict[ZoneKey, Any]) -> dict[ZoneKey, ZoneKey]:\n    \"\"\"Returns a dict mapping each zone to its parent zone.\"\"\"\n    zone_parents = {}\n    for zone_id, zone_config in zones_config.items():\n        if \"subZoneNames\" in zone_config:\n            for sub_zone_id in zone_config[\"subZoneNames\"]:\n                zone_parents[sub_zone_id] = zone_id\n    return zone_parents\n\n\ndef generate_zone_neighbours(\n    zones_config: dict[ZoneKey, Any], exchanges_config: dict[ZoneKey, Any]\n) -> dict[ZoneKey, list[ZoneKey]]:\n    \"\"\"Returns a dict mapping each zone to its neighbours.\n\n    Neighbours are defined as zones that are connected by an exchange.\n    This represents the edges of the flow-tracing graph.\n    \"\"\"\n    zone_neighbours = defaultdict(set)\n    for k, v in exchanges_config.items():\n        if not v.get(\"parsers\", {}).get(\"exchange\", None):\n            # Interconnector config has no parser, and will therefore not be part\n            # of the flowtracing graph.\n            continue\n        try:\n            zone_1, zone_2 = k.split(\"->\")\n            zone_1 = ZoneKey(zone_1)\n            zone_2 = ZoneKey(zone_2)\n            if zones_config[zone_1].get(\"subZoneNames\") or zones_config[zone_2].get(\n                \"subZoneNames\"\n            ):\n                # Both zones must not have subzones.\n                continue\n            pairs = [(zone_1, zone_2), (zone_2, zone_1)]\n            for zone_name_1, zone_name_2 in pairs:\n                zone_neighbours[zone_name_1].add(zone_name_2)\n        except Exception:\n            continue\n    # Sort the lists of neighbours for each zone.\n    return {k: sorted(v) for k, v in zone_neighbours.items()}\n\n\ndef generate_all_neighbours(\n    exchanges_config: dict[ZoneKey, Any],\n) -> dict[ZoneKey, list[ZoneKey]]:\n    \"\"\"This object represents all neighbours regardless of granularity.\"\"\"\n    zone_neighbours = defaultdict(set)\n    for k in exchanges_config:\n        zone_1, zone_2 = k.split(\"->\")\n        pairs = [(zone_1, zone_2), (zone_2, zone_1)]\n        for zone_name_1, zone_name_2 in pairs:\n            zone_neighbours[zone_name_1].add(zone_name_2)\n    # Sort the lists of neighbours for each zone.\n    return {k: sorted(v) for k, v in zone_neighbours.items()}\n"
  },
  {
    "path": "electricitymap/contrib/lib/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/lib/data_types.py",
    "content": "# DEPRECATED: Import from electricitymap.contrib.types instead.\n# This re-export is kept for backward compatibility.\nfrom electricitymap.contrib.types import (\n    ALL_DATA_TYPES,\n    EXCHANGE_DATA_TYPES,\n    LMP_DATA_TYPES,\n    ParserDataType,\n)\n\n__all__ = [\"ParserDataType\", \"ALL_DATA_TYPES\", \"EXCHANGE_DATA_TYPES\", \"LMP_DATA_TYPES\"]\n"
  },
  {
    "path": "electricitymap/contrib/lib/models/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/lib/models/constants.py",
    "content": "VALID_CURRENCIES = [\n    \"AFN\",\n    \"ALL\",\n    \"DZD\",\n    \"USD\",\n    \"EUR\",\n    \"AOA\",\n    \"XCD\",\n    \"ARS\",\n    \"AMD\",\n    \"AWG\",\n    \"AUD\",\n    \"AZN\",\n    \"BSD\",\n    \"BHD\",\n    \"BDT\",\n    \"BBD\",\n    \"BYN\",\n    \"BZD\",\n    \"XOF\",\n    \"BMD\",\n    \"BTN\",\n    \"INR\",\n    \"BOB\",\n    \"BOV\",\n    \"BAM\",\n    \"BWP\",\n    \"NOK\",\n    \"BRL\",\n    \"BND\",\n    \"BGN\",\n    \"BIF\",\n    \"CVE\",\n    \"KHR\",\n    \"XAF\",\n    \"CAD\",\n    \"KYD\",\n    \"CLF\",\n    \"CLP\",\n    \"CNY\",\n    \"COP\",\n    \"COU\",\n    \"KMF\",\n    \"CDF\",\n    \"NZD\",\n    \"CRC\",\n    \"HRK\",\n    \"CUC\",\n    \"CUP\",\n    \"ANG\",\n    \"CZK\",\n    \"DKK\",\n    \"DJF\",\n    \"DOP\",\n    \"EGP\",\n    \"SVC\",\n    \"ERN\",\n    \"ETB\",\n    \"FKP\",\n    \"FJD\",\n    \"XPF\",\n    \"GMD\",\n    \"GEL\",\n    \"GHS\",\n    \"GIP\",\n    \"GTQ\",\n    \"GBP\",\n    \"GNF\",\n    \"GYD\",\n    \"HTG\",\n    \"HNL\",\n    \"HKD\",\n    \"HUF\",\n    \"ISK\",\n    \"IDR\",\n    \"XDR\",\n    \"IRR\",\n    \"IQD\",\n    \"ILS\",\n    \"JMD\",\n    \"JPY\",\n    \"JOD\",\n    \"KZT\",\n    \"KES\",\n    \"KPW\",\n    \"KRW\",\n    \"KWD\",\n    \"KGS\",\n    \"LAK\",\n    \"LBP\",\n    \"LSL\",\n    \"ZAR\",\n    \"LRD\",\n    \"LYD\",\n    \"CHF\",\n    \"MOP\",\n    \"MGA\",\n    \"MWK\",\n    \"MYR\",\n    \"MVR\",\n    \"MRU\",\n    \"MUR\",\n    \"XUA\",\n    \"MXN\",\n    \"MXV\",\n    \"MDL\",\n    \"MNT\",\n    \"MAD\",\n    \"MZN\",\n    \"MMK\",\n    \"NAD\",\n    \"NPR\",\n    \"NIO\",\n    \"NGN\",\n    \"OMR\",\n    \"PKR\",\n    \"PAB\",\n    \"PGK\",\n    \"PYG\",\n    \"PEN\",\n    \"PHP\",\n    \"PLN\",\n    \"QAR\",\n    \"MKD\",\n    \"RON\",\n    \"RUB\",\n    \"RWF\",\n    \"SHP\",\n    \"WST\",\n    \"STN\",\n    \"SAR\",\n    \"RSD\",\n    \"SCR\",\n    \"SLE\",\n    \"SGD\",\n    \"XSU\",\n    \"SBD\",\n    \"SOS\",\n    \"SSP\",\n    \"LKR\",\n    \"SDG\",\n    \"SRD\",\n    \"SZL\",\n    \"SEK\",\n    \"CHE\",\n    \"CHW\",\n    \"SYP\",\n    \"TWD\",\n    \"TJS\",\n    \"TZS\",\n    \"THB\",\n    \"TOP\",\n    \"TTD\",\n    \"TND\",\n    \"TRY\",\n    \"TMT\",\n    \"UGX\",\n    \"UAH\",\n    \"AED\",\n    \"USN\",\n    \"UYI\",\n    \"UYU\",\n    \"UZS\",\n    \"VUV\",\n    \"VEF\",\n    \"VED\",\n    \"VND\",\n    \"YER\",\n    \"ZMW\",\n    \"ZWL\",\n]\n"
  },
  {
    "path": "electricitymap/contrib/lib/models/event_lists.py",
    "content": "from abc import ABC, abstractmethod\nfrom collections.abc import Sequence\nfrom datetime import datetime\nfrom logging import Logger\nfrom operator import itemgetter\nfrom typing import Any, Generic, TypeVar\n\nimport pandas as pd\n\nfrom electricitymap.contrib.lib.models.events import (\n    Event,\n    EventSourceType,\n    Exchange,\n    ExchangeCapacity,\n    GridAlert,\n    GridAlertType,\n    LocationalMarginalPrice,\n    Price,\n    ProductionBreakdown,\n    ProductionMix,\n    StorageMix,\n    TotalConsumption,\n    TotalProduction,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nEventType = TypeVar(\"EventType\", bound=\"Event\")\n\n\nclass EventList(ABC, Generic[EventType]):\n    \"\"\"\n    A wrapper around Events lists.\n    Events are indexed by datetimes.\n    \"\"\"\n\n    logger: Logger\n    events: list[EventType]\n\n    def __init__(self, logger: Logger):\n        self.events = []\n        self.logger = logger\n\n    def __len__(self):\n        return len(self.events)\n\n    def __contains__(self, datetime) -> bool:\n        return any(event.datetime == datetime for event in self.events)\n\n    def __setitem__(self, datetime, event: EventType):\n        self.events[self.events.index(self[datetime])] = event\n\n    def __add__(self, other: \"EventList\") -> \"EventList\":\n        new_list = self.__class__(self.logger)\n        new_list.events = self.events + other.events\n        return new_list\n\n    def __getitem__(self, datetime) -> EventType:\n        return next(event for event in self.events if event.datetime == datetime)\n\n    def __iter__(self):\n        return iter(self.events)\n\n    @abstractmethod\n    def append(self, **kwargs):\n        \"\"\"Handles creation of events and adding it to the batch.\"\"\"\n        # TODO Handle one day the creation of mixed batches.\n        pass\n\n    def to_list(self) -> list[dict[str, Any]]:\n        return sorted(\n            [event.to_dict() for event in self.events], key=itemgetter(\"datetime\")\n        )\n\n    @property\n    def dataframe(self) -> pd.DataFrame:\n        \"\"\"Gives the dataframe representation of the events, indexed by datetime.\"\"\"\n        return pd.DataFrame.from_records(\n            [\n                {\n                    \"datetime\": event.datetime,\n                    \"zoneKey\": event.zoneKey,\n                    \"source\": event.source,\n                    \"sourceType\": event.sourceType,\n                    \"data\": event,\n                }\n                for event in self.events\n                if len(self.events) > 0\n            ]\n        ).set_index(\"datetime\")\n\n\nclass AggregatableEventList(EventList[EventType], ABC, Generic[EventType]):\n    \"\"\"An abstract class to supercharge event lists with aggregation capabilities.\"\"\"\n\n    @classmethod\n    def is_completely_empty(\n        cls, ungrouped_events: Sequence[\"AggregatableEventList\"], logger: Logger\n    ) -> bool:\n        \"\"\"Checks if the lists to be merged have any data.\"\"\"\n        if len(ungrouped_events) == 0:\n            return True\n        if all(len(event_list.events) == 0 for event_list in ungrouped_events):\n            logger.warning(f\"All {cls.__name__} are empty.\")\n            return True\n        return False\n\n    @classmethod\n    def get_zone_source_type(\n        cls,\n        events: pd.DataFrame,\n    ) -> tuple[ZoneKey, str, EventSourceType]:\n        \"\"\"\n        Given a concatenated dataframe of events, return the unique zone, the aggregated sources and the unique source type.\n        Raises an error if there are multiple zones or source types.\n        It assumes that zoneKey, source and sourceType are present in the dataframe's columns.\n        \"\"\"\n        return (\n            AggregatableEventList._get_unique_zone(events),\n            AggregatableEventList._get_aggregated_sources(events),\n            AggregatableEventList._get_unique_source_type(events),\n        )\n\n    @classmethod\n    def _get_unique_zone(cls, events: pd.DataFrame) -> ZoneKey:\n        \"\"\"\n        Given a concatenated dataframe of events, return the unique zone.\n        Raises an error if there are multiple zones.\n        It assumes that `zoneKey` is present in the dataframe's columns.\n        \"\"\"\n        zones = events[\"zoneKey\"].unique()\n        if len(zones) != 1:\n            raise ValueError(\n                f\"Trying to merge {cls.__name__} from multiple zones \\\n                , got {len(zones)}: {', '.join(zones)}\"\n            )\n        return zones[0]\n\n    @classmethod\n    def _get_aggregated_sources(cls, events: pd.DataFrame) -> str:\n        \"\"\"\n        Given a concatenated dataframe of events, return the aggregated sources.\n        It assumes that `source` is present in the dataframe's columns.\n        \"\"\"\n        sources = events[\"source\"].unique()\n        sources = \", \".join(sources)\n        return sources\n\n    @classmethod\n    def _get_unique_source_type(cls, events: pd.DataFrame) -> EventSourceType:\n        \"\"\"\n        Given a concatenated dataframe of events, return the unique source type.\n        Raises an error if there are multiple source types.\n        It assumes that `sourceType` is present in the dataframe's columns.\n        \"\"\"\n        source_types = events[\"sourceType\"].unique()\n        if len(source_types) != 1:\n            raise ValueError(\n                f\"Trying to merge {cls.__name__} from multiple source types \\\n                , got {len(source_types)}: {', '.join(source_types)}\"\n            )\n        return source_types[0]\n\n\nclass ExchangeList(AggregatableEventList[Exchange]):\n    def append(\n        self,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        netFlow: float | None,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ):\n        event = Exchange.create(\n            self.logger, zoneKey, datetime, source, netFlow, sourceType\n        )\n        if event:\n            self.events.append(event)\n\n    @staticmethod\n    def merge_exchanges(\n        ungrouped_exchanges: list[\"ExchangeList\"], logger: Logger\n    ) -> \"ExchangeList\":\n        \"\"\"\n        Given multiple parser outputs, sum the netflows of corresponding datetimes\n        to create a unique exchange list. Sources will be aggregated in a\n        comma-separated string. Ex: \"entsoe, eia\".\n        \"\"\"\n        exchanges = ExchangeList(logger)\n        if ExchangeList.is_completely_empty(ungrouped_exchanges, logger):\n            return exchanges\n\n        # Create a dataframe for each parser output, then flatten the exchanges.\n        exchange_dfs = [\n            pd.json_normalize(exchanges.to_list()).set_index(\"datetime\")\n            for exchanges in ungrouped_exchanges\n            if len(exchanges.events) > 0\n        ]\n\n        exchange_df = pd.concat(exchange_dfs)\n        exchange_df = exchange_df.rename(columns={\"sortedZoneKeys\": \"zoneKey\"})\n        zone_key, sources, source_type = ExchangeList.get_zone_source_type(exchange_df)\n        exchange_df = exchange_df.groupby(level=\"datetime\", dropna=False).sum(\n            numeric_only=True,\n        )\n        for dt, row in exchange_df.iterrows():\n            exchanges.append(\n                zone_key, dt.to_pydatetime(), sources, row[\"netFlow\"], source_type\n            )  # type: ignore\n\n        return exchanges\n\n    @staticmethod\n    def update_exchanges(\n        exchanges: \"ExchangeList\", new_exchanges: \"ExchangeList\", logger: Logger\n    ) -> \"ExchangeList\":\n        \"\"\"Given a new batch of exchanges, update the existing ones.\"\"\"\n        if len(new_exchanges) == 0:\n            return exchanges\n        elif len(exchanges) == 0:\n            return new_exchanges\n\n        for new_event in new_exchanges.events:\n            if new_event.datetime in exchanges:\n                existing_event = exchanges[new_event.datetime]\n                updated_event = Exchange._update(existing_event, new_event)\n                exchanges[new_event.datetime] = updated_event\n            else:\n                exchanges.append(\n                    new_event.zoneKey,\n                    new_event.datetime,\n                    new_event.source,\n                    new_event.netFlow,\n                    new_event.sourceType,\n                )\n\n        return exchanges\n\n\nclass ExchangeCapacityList(EventList[ExchangeCapacity]):\n    def append(\n        self,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        capacityExport: float | None,\n        capacityImport: float | None,\n        sourceType: EventSourceType = EventSourceType.published,\n    ):\n        event = ExchangeCapacity.create(\n            self.logger,\n            zoneKey,\n            datetime,\n            source,\n            capacityExport,\n            capacityImport,\n            sourceType,\n        )\n        if event:\n            self.events.append(event)\n\n\nclass ProductionBreakdownList(AggregatableEventList[ProductionBreakdown]):\n    def append(\n        self,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        production: ProductionMix | None = None,\n        storage: StorageMix | None = None,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ):\n        event = ProductionBreakdown.create(\n            self.logger, zoneKey, datetime, source, production, storage, sourceType\n        )\n        if event:\n            self.events.append(event)\n\n    @staticmethod\n    def merge_production_breakdowns(\n        ungrouped_production_breakdowns: list[\"ProductionBreakdownList\"],\n        logger: Logger,\n        matching_timestamps_only: bool = False,\n    ) -> \"ProductionBreakdownList\":\n        \"\"\"\n        Given multiple parser outputs, sum the production and storage\n        of corresponding datetimes to create a unique production breakdown list.\n        Sources will be aggregated in a comma-separated string. Ex: \"entsoe, eia\".\n        There should be only one zone in the list of production breakdowns.\n        Matching timestamps only will only keep the timestamps where all the production breakdowns have data.\n        \"\"\"\n        production_breakdowns = ProductionBreakdownList(logger)\n        if ProductionBreakdownList.is_completely_empty(\n            ungrouped_production_breakdowns, logger\n        ):\n            return production_breakdowns\n        len_ungrouped_production_breakdowns = len(ungrouped_production_breakdowns)\n        df = pd.concat(\n            [\n                production_breakdowns.dataframe\n                for production_breakdowns in ungrouped_production_breakdowns\n                if len(production_breakdowns.events) > 0\n            ]\n        )\n        _, _, _ = ProductionBreakdownList.get_zone_source_type(df)\n\n        df = df.drop(columns=[\"source\", \"sourceType\", \"zoneKey\"])\n        df = df.groupby(level=0, dropna=False)[\"data\"].apply(list)\n        if matching_timestamps_only:\n            logger.info(\n                f\"Filtering production breakdowns to keep \\\n                only the timestamps where all the production breakdowns \\\n                have data, {len(df[df.apply(lambda x: len(x) != len_ungrouped_production_breakdowns)])}\\\n                points where discarded.\"\n            )\n            df = df[df.apply(lambda x: len(x) == len_ungrouped_production_breakdowns)]\n        for row in df:\n            prod = ProductionBreakdown.aggregate(row)\n            production_breakdowns.events.append(prod)\n        return production_breakdowns\n\n    @staticmethod\n    def update_production_breakdowns(\n        production_breakdowns: \"ProductionBreakdownList\",\n        new_production_breakdowns: \"ProductionBreakdownList\",\n        logger: Logger,\n        matching_timestamps_only: bool = False,\n    ) -> \"ProductionBreakdownList\":\n        \"\"\"\n        Given a new batch of production breakdowns, update the existing ones.\n\n        Params:\n        - production_breakdowns: The existing production breakdowns to be updated.\n        - new_production_breakdowns: The new batch of production breakdowns.\n        - logger: The logger object used for logging information.\n        - matching_timestamps_only: Flag indicating whether to update only the events with matching timestamps from both the production breakdowns.\n        \"\"\"\n\n        if len(new_production_breakdowns) == 0:\n            return production_breakdowns\n        elif len(production_breakdowns) == 0:\n            return new_production_breakdowns\n\n        updated_production_breakdowns = ProductionBreakdownList(logger)\n\n        if matching_timestamps_only:\n            diff = abs(len(new_production_breakdowns) - len(production_breakdowns))\n            logger.info(\n                f\"Filtering production breakdowns to keep only the events where both the production breakdowns have matching datetimes, {diff} events where discarded.\"\n            )\n\n        for new_event in new_production_breakdowns.events:\n            if new_event.datetime in production_breakdowns:\n                existing_event = production_breakdowns[new_event.datetime]\n                updated_event = ProductionBreakdown._update(existing_event, new_event)\n                updated_production_breakdowns.append(\n                    updated_event.zoneKey,\n                    updated_event.datetime,\n                    updated_event.source,\n                    updated_event.production,\n                    updated_event.storage,\n                    updated_event.sourceType,\n                )\n            elif matching_timestamps_only is False:\n                updated_production_breakdowns.append(\n                    new_event.zoneKey,\n                    new_event.datetime,\n                    new_event.source,\n                    new_event.production,\n                    new_event.storage,\n                    new_event.sourceType,\n                )\n\n        if matching_timestamps_only is False:\n            for existing_event in production_breakdowns.events:\n                if existing_event.datetime not in new_production_breakdowns:\n                    updated_production_breakdowns.append(\n                        existing_event.zoneKey,\n                        existing_event.datetime,\n                        existing_event.source,\n                        existing_event.production,\n                        existing_event.storage,\n                        existing_event.sourceType,\n                    )\n\n        return updated_production_breakdowns\n\n\nclass TotalProductionList(AggregatableEventList[TotalProduction]):\n    def append(\n        self,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        value: float | None,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ):\n        event = TotalProduction.create(\n            self.logger, zoneKey, datetime, source, value, sourceType\n        )\n        if event:\n            self.events.append(event)\n\n    @staticmethod\n    def merge_total_production_lists(\n        ungrouped_production_lists: list[\"TotalProductionList\"],\n        logger: Logger,\n    ) -> \"TotalProductionList\":\n        \"\"\"\n        Given multiple parser outputs, sum the production of corresponding datetimes\n        to create a unique production list. Sources will be aggregated in a\n        comma-separated string. Ex: \"entsoe, eia\".\n        \"\"\"\n        production_list = TotalProductionList(logger)\n        if TotalProductionList.is_completely_empty(ungrouped_production_lists, logger):\n            return production_list\n\n        # Create a dataframe for each parser output, then flatten the production.\n        production_dfs = [\n            pd.json_normalize(production.to_list()).set_index(\"datetime\")\n            for production in ungrouped_production_lists\n            if len(production.events) > 0\n        ]\n\n        production_df = pd.concat(production_dfs)\n\n        zone_key, sources, source_type = TotalProductionList.get_zone_source_type(\n            production_df\n        )\n        production_df = production_df.groupby(level=\"datetime\", dropna=False).sum(\n            numeric_only=True\n        )\n        for dt, row in production_df.iterrows():\n            production_list.append(\n                zone_key, dt.to_pydatetime(), sources, row[\"value\"], source_type\n            )  # type: ignore\n\n        return production_list\n\n\nclass TotalConsumptionList(AggregatableEventList[TotalConsumption]):\n    def append(\n        self,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        consumption: float | None,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ):\n        event = TotalConsumption.create(\n            self.logger, zoneKey, datetime, source, consumption, sourceType\n        )\n        if event:\n            self.events.append(event)\n\n    @staticmethod\n    def merge_consumption_lists(\n        ungrouped_consumption_lists: list[\"TotalConsumptionList\"],\n        logger: Logger,\n    ) -> \"TotalConsumptionList\":\n        \"\"\"\n        Given multiple parser outputs, sum the consumption of corresponding datetimes\n        to create a unique consumption list. Sources will be aggregated in a\n        comma-separated string. Ex: \"entsoe, eia\".\n        \"\"\"\n        consumption_list = TotalConsumptionList(logger)\n        if TotalConsumptionList.is_completely_empty(\n            ungrouped_consumption_lists, logger\n        ):\n            return consumption_list\n\n        # Create a dataframe for each parser output, then flatten the consumption.\n        consumption_dfs = [\n            pd.json_normalize(consumption.to_list()).set_index(\"datetime\")\n            for consumption in ungrouped_consumption_lists\n            if len(consumption.events) > 0\n        ]\n\n        consumption_df = pd.concat(consumption_dfs)\n\n        zone_key, sources, source_type = TotalConsumptionList.get_zone_source_type(\n            consumption_df\n        )\n        consumption_df = consumption_df.groupby(level=\"datetime\", dropna=False).sum(\n            numeric_only=True\n        )\n        for dt, row in consumption_df.iterrows():\n            consumption_list.append(\n                zone_key, dt.to_pydatetime(), sources, row[\"consumption\"], source_type\n            )  # type: ignore\n\n        return consumption_list\n\n\nclass PriceList(EventList[Price]):\n    def append(\n        self,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        price: float | None,\n        currency: str,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ):\n        event = Price.create(\n            self.logger, zoneKey, datetime, source, price, currency, sourceType\n        )\n        if event:\n            self.events.append(event)\n\n\nclass LocationalMarginalPriceList(EventList[LocationalMarginalPrice]):\n    def append(\n        self,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        price: float | None,\n        currency: str,\n        node: str,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ):\n        event = LocationalMarginalPrice.create(\n            self.logger, zoneKey, datetime, source, price, currency, node, sourceType\n        )\n        if event:\n            self.events.append(event)\n\n\nclass GridAlertList(EventList[GridAlert]):\n    def append(\n        self,\n        zoneKey: ZoneKey,\n        locationRegion: str | None,\n        source: str,\n        alertType: GridAlertType,\n        message: str,\n        issuedTime: datetime,\n        startTime: datetime | None,\n        endTime: datetime | None,\n    ):\n        event = GridAlert.create(\n            self.logger,\n            zoneKey,\n            locationRegion,\n            source,\n            alertType,\n            message,\n            issuedTime,\n            startTime,\n            endTime,\n        )\n        if event:\n            self.events.append(event)\n"
  },
  {
    "path": "electricitymap/contrib/lib/models/events.py",
    "content": "# pylint: disable=no-member\nimport datetime as dt\nimport math\nfrom abc import ABC, abstractmethod\nfrom collections.abc import Set\nfrom datetime import datetime, timedelta, timezone\nfrom enum import Enum\nfrom logging import Logger\nfrom typing import Any\n\nimport pandas as pd\nfrom pydantic import BaseModel, PrivateAttr, ValidationError, root_validator, validator\n\nfrom electricitymap.contrib.config import (\n    EXCHANGES_CONFIG,\n    RETIRED_ZONES_CONFIG,\n    ZONES_CONFIG,\n)\nfrom electricitymap.contrib.lib.models.constants import VALID_CURRENCIES\nfrom electricitymap.contrib.parsers.lib.config import ProductionModes, StorageModes\nfrom electricitymap.contrib.types import ZoneKey\n\nLOWER_DATETIME_BOUND = datetime(2000, 1, 1, tzinfo=timezone.utc)\n\n\ndef _is_naive(t: dt.datetime) -> bool:\n    \"\"\"Determines if a datetime object is naive.\"\"\"\n    return t.tzinfo is None or t.tzinfo.utcoffset(t) is None\n\n\ndef _none_safe_round(value: float | None, precision: int = 6) -> float | None:\n    \"\"\"\n    Rounds a value to the provided precision.\n    If the value is None, it is returned as is.\n    The default precision is 6 decimal places, which gives us a precision of 1 W.\n    \"\"\"\n    return None if value is None or math.isnan(value) else round(value, precision)\n\n\nclass Mix(BaseModel, ABC):\n    def add_value(\n        self,\n        mode: str,\n        value: float | None,\n    ) -> None:\n        \"\"\"\n        Adds the provided value to the existing value of the provided mode.\n        This is useful if there are multiple production modes in the source\n        that maps to the same Electricity Maps production mode.\n        \"\"\"\n        existing_value: float | None = getattr(self, mode)\n        if value is not None and math.isnan(value):\n            value = None\n        if existing_value is not None:\n            value = 0 if value is None else value\n            self.__setattr__(mode, existing_value + value)\n        else:\n            self.__setattr__(mode, value)\n\n    @classmethod\n    def merge(cls, mixes: list[\"Mix\"]) -> \"Mix\":\n        raise NotImplementedError()\n\n    @classmethod\n    def _update(cls, mix: \"Mix\", new_mix: \"Mix\") -> \"Mix\":\n        raise NotImplementedError()\n\n    def __setattr__(self, name: str, value: float | None) -> None:\n        \"\"\"\n        Overriding the setattr method to raise an error if the mode is unknown.\n        \"\"\"\n        # 6 decimal places gives us a precision of 1 W.\n        super().__setattr__(name, _none_safe_round(value))\n\n    def __setitem__(self, key: str, value: float | None) -> None:\n        \"\"\"\n        Allows to set the value of a mode using the bracket notation.\n        \"\"\"\n        self.__setattr__(key, value)\n\n\nclass ProductionMix(Mix):\n    \"\"\"\n    Contains the production mix for a zone at a given time.\n    All values should be positives, otherwise they will be set to None\n    and a warning will be logged.\n    All values are in MW.\n    \"\"\"\n\n    # We use a private attribute to keep track of the modes that have been set to None.\n    _corrected_negative_values: set = PrivateAttr(set())\n    biomass: float | None = None\n    coal: float | None = None\n    gas: float | None = None\n    geothermal: float | None = None\n    hydro: float | None = None\n    nuclear: float | None = None\n    oil: float | None = None\n    solar: float | None = None\n    unknown: float | None = None\n    wind: float | None = None\n\n    def __init__(self, **data: Any):\n        \"\"\"\n        Overriding the constructor to check for negative values and set them to None.\n        This method also keeps track of the modes that have been corrected.\n        Note: This method does NOT allow to set negative values to zero for self consumption.\n        As we want self consumption to be set to zero, on a fine grained level with the `add_value` method.\n        \"\"\"\n        super().__init__(**data)\n        for attr, value in data.items():\n            if value is not None and value < 0:\n                self._corrected_negative_values.add(attr)\n                value = None\n            # Ensure that the value is rounded to 6 decimal places and set to None if it is NaN.\n            self.__setattr__(attr, value)\n\n    def dict(  # noqa: A003\n        self,\n        *,\n        include: set | dict | None = None,\n        exclude: set | dict | None = None,\n        by_alias: bool = False,\n        skip_defaults: bool | None = None,\n        exclude_unset: bool = False,\n        exclude_defaults: bool = False,\n        exclude_none: bool = False,\n        keep_corrected_negative_values: bool = False,\n    ) -> dict[str, Any]:\n        \"\"\"Overriding the dict method to add the corrected negative values as Nones.\"\"\"\n        production_mix = super().dict(\n            include=include,\n            exclude=exclude,\n            by_alias=by_alias,\n            skip_defaults=skip_defaults,\n            exclude_unset=exclude_unset,\n            exclude_defaults=exclude_defaults,\n            exclude_none=exclude_none,\n        )\n        if keep_corrected_negative_values:\n            for corrected_negative_mode in self._corrected_negative_values:\n                if corrected_negative_mode not in production_mix:\n                    production_mix[corrected_negative_mode] = None\n        return production_mix\n\n    def __setattr__(\n        self,\n        name: str,\n        value: float | None,\n    ) -> None:\n        \"\"\"\n        Overriding the setattr method to check that the name is a valid production mode\n        and to check for negative values and set them to None.\n        This method also keeps track of the modes that have been corrected.\n        \"\"\"\n        if name not in ProductionModes.values():\n            raise AttributeError(f\"Unknown production mode: {name}\")\n        if value is not None and value < 0:\n            self._corrected_negative_values.add(name)\n            value = None\n        return super().__setattr__(name, value)\n\n    def _correct_negative_value(\n        self, mode: str, value: float | None, correct_negative_with_zero: bool\n    ) -> float | None:\n        \"\"\"\n        Corrects a negative value by setting it to None or 0.\n        This method also keeps track of the modes that have been corrected.\n        \"\"\"\n        if value is not None and value < 0:\n            self._corrected_negative_values.add(mode)\n            return 0 if correct_negative_with_zero else None\n        return value\n\n    def add_value(\n        self,\n        mode: str,\n        value: float | None,\n        correct_negative_with_zero: bool = False,\n    ) -> None:\n        \"\"\"Adds the provided value to the existing value of the provided mode. Negative values are set to None by default.\n        If correct_negative_with_zero is set to True, negative values will be set to 0 instead of None.\n        This method keeps track of modes that have been corrected.\n        \"\"\"\n        value = self._correct_negative_value(mode, value, correct_negative_with_zero)\n        super().add_value(mode, value)\n\n    @property\n    def has_corrected_negative_values(self) -> bool:\n        return len(self._corrected_negative_values) > 0\n\n    @property\n    def corrected_negative_modes(self) -> Set[str]:\n        return self._corrected_negative_values\n\n    @classmethod\n    def merge(cls, production_mixes: list[\"ProductionMix\"]) -> \"ProductionMix\":\n        \"\"\"\n        Merge a list of production mixes into a single production mix.\n        The values are summed. Negative values have been set to None or 0.\n        Therefore merging cannot result in a lower production value.\n        \"\"\"\n        merged_production_mix = cls()\n        for production_mix in production_mixes:\n            # Process all set production modes\n            for mode in ProductionModes.values():\n                if mode in production_mix.__fields_set__:\n                    merged_production_mix.add_value(mode, getattr(production_mix, mode))\n\n            # Update corrected negative values\n            merged_production_mix._corrected_negative_values.update(\n                production_mix.corrected_negative_modes\n            )\n        return merged_production_mix\n\n    @classmethod\n    def _update(\n        cls,\n        production_mix: \"ProductionMix | None\",\n        new_production_mix: \"ProductionMix | None\",\n    ) -> \"ProductionMix | None\":\n        \"\"\"Update the production mix of a zone at a given time.\"\"\"\n        if production_mix is None:\n            return new_production_mix\n        elif new_production_mix is not None:\n            for mode, value in new_production_mix:\n                if value is not None:\n                    production_mix[mode] = value\n        return production_mix\n\n\nclass StorageMix(Mix):\n    \"\"\"\n    Contains the storage mix for a zone at a given time.\n    All values are in MW.\n    Values can be both positive (when storing energy) or negative (when the storage is discharged).\n    \"\"\"\n\n    battery: float | None = None\n    hydro: float | None = None\n\n    def __init__(self, **data: Any):\n        \"\"\"\n        Overriding the constructor to check for NaN values and set them to None.\n        \"\"\"\n        super().__init__(**data)\n        for attr, value in data.items():\n            self.__setattr__(attr, value)\n\n    def __setattr__(self, name: str, value: float | None) -> None:\n        \"\"\"\n        Overriding the setattr method to raise an error if the mode is unknown.\n        \"\"\"\n        if name not in StorageModes.values():\n            raise AttributeError(f\"Unknown storage mode: {name}\")\n        return super().__setattr__(name, value)\n\n    @classmethod\n    def merge(cls, storage_mixes: list[\"StorageMix\"]) -> \"StorageMix\":\n        \"\"\"\n        Merge a list of storage mixes into a single storage mix.\n        The values are summed.\n        \"\"\"\n        merged_storage_mix = cls()\n        for storage_mix in storage_mixes:\n            for mode in StorageModes.values():\n                if mode in storage_mix.__fields_set__:\n                    merged_storage_mix.add_value(mode, getattr(storage_mix, mode))\n\n        return merged_storage_mix\n\n    @classmethod\n    def _update(\n        cls, storage_mix: \"StorageMix | None\", new_storage_mix: \"StorageMix | None\"\n    ) -> \"StorageMix | None\":\n        \"\"\"Update the storage mix of a zone at a given time.\"\"\"\n        if storage_mix is None:\n            return new_storage_mix\n        elif new_storage_mix is not None:\n            for mode, value in new_storage_mix:\n                if value is not None:\n                    storage_mix[mode] = value\n        return storage_mix\n\n\nclass EventSourceType(str, Enum):\n    measured = \"measured\"\n    forecasted = \"forecasted\"\n    estimated = \"estimated\"\n    # TSO-published ex-ante value for a future MTU — e.g. day-ahead transfer\n    # capacity, cleared market-coupling schedules, allocated ATC. Not a\n    # statistical prediction, but still legitimately dated in the future.\n    published = \"published\"\n\n\nclass Event(BaseModel, ABC):\n    \"\"\"\n    An abstract class representing all types of electricity events that can occur in a zone.\n    sourceType: How was the event observed.\n    Should be set to forecasted if the point is a forecast provided by a datasource.\n    Should be set to estimated if the point is an estimate or data that has not been consolidated yet by the datasource.\n    Should be set to published if the point is a TSO-published ex-ante value for a future MTU (e.g. day-ahead capacity, cleared schedules).\n    zoneKey: The zone key of the zone the event is happening in.\n    datetime: The datetime of the event.\n    source: The source of the event.\n    We currently use the root url of the datasource. Ex: edf.fr\n    \"\"\"\n\n    # The order of the attributes matters for the validation.\n    # As the validators are called in the order of the attributes, we need to make sure that the sourceType is validated before the datetime.\n    sourceType: EventSourceType = EventSourceType.measured\n    zoneKey: ZoneKey\n    datetime: datetime\n    source: str\n\n    @validator(\"zoneKey\")\n    def _validate_zone_key(cls, v):\n        if v not in ZONES_CONFIG and v not in RETIRED_ZONES_CONFIG:\n            raise ValueError(f\"Unknown zone: {v}\")\n        return v\n\n    @validator(\"datetime\")\n    def _validate_datetime(cls, v: dt.datetime, values: dict[str, Any]) -> dt.datetime:\n        if _is_naive(v):\n            raise ValueError(f\"Missing timezone: {v}\")\n        if v < LOWER_DATETIME_BOUND:\n            raise ValueError(f\"Date is before 2000, this is not plausible: {v}\")\n        source_type = values.get(\"sourceType\", EventSourceType.measured)\n        future_ok = {EventSourceType.forecasted, EventSourceType.published}\n        if source_type not in future_ok and v.astimezone(timezone.utc) > datetime.now(\n            timezone.utc\n        ) + timedelta(days=1):\n            raise ValueError(\n                f\"Date is in the future and this is not a forecasted or published point: {v}\"\n            )\n        return v.replace(second=0, microsecond=0)\n\n    @staticmethod\n    @abstractmethod\n    def create(*args, **kwargs) -> \"Event\":\n        \"\"\"To avoid having one Event failure crashing the whole parser, we use a factory method to create the Event.\"\"\"\n        pass\n\n    @abstractmethod\n    def to_dict(self) -> dict[str, Any]:\n        \"\"\"As part of a backwards compatibility, the points will be converted to a dict before being sent to the database.\"\"\"\n        pass\n\n\nclass AggregatableEvent(Event):\n    \"\"\"\n    An abstract class representing all types of electricity events that can be aggregated.\n    \"\"\"\n\n    @staticmethod\n    def _unique_zone_key(df_view: pd.DataFrame) -> ZoneKey:\n        zone_key = df_view[\"zoneKey\"].unique()\n        if len(zone_key) > 1:\n            raise ValueError(f\"Cannot merge events from different zones: {zone_key}\")\n        return zone_key[0]\n\n    @staticmethod\n    def _sources(df_view: pd.DataFrame) -> str:\n        sources = df_view[\"source\"].unique()\n        flattened_sources = [\n            source.strip() for sublist in sources for source in sublist.split(\",\")\n        ]\n        unique_sources = sorted(set(flattened_sources))\n        return \", \".join(unique_sources)\n\n    @staticmethod\n    def _unique_source_type(df_view: pd.DataFrame) -> EventSourceType:\n        source_type = df_view[\"sourceType\"].unique()\n        if len(source_type) > 1:\n            raise ValueError(\n                f\"Cannot merge events from different source types: {source_type}\"\n            )\n        return source_type[0]\n\n    @staticmethod\n    def _unique_datetime(df_view: pd.DataFrame) -> datetime:\n        target_datetime = df_view.datetime.unique()\n        if len(target_datetime) > 1:\n            raise ValueError(\n                f\"Cannot merge events from different datetimes: {target_datetime}\"\n            )\n        return target_datetime[0].to_pydatetime()\n\n    @staticmethod\n    def _aggregated_fields(\n        df_view: pd.DataFrame,\n    ) -> tuple[ZoneKey, str, EventSourceType, datetime]:\n        return (\n            AggregatableEvent._unique_zone_key(df_view),\n            AggregatableEvent._sources(df_view),\n            AggregatableEvent._unique_source_type(df_view),\n            AggregatableEvent._unique_datetime(df_view),\n        )\n\n    @staticmethod\n    @abstractmethod\n    def aggregate(events: list[\"AggregatableEvent\"]) -> \"AggregatableEvent\":\n        \"\"\"Aggregate a list of events into a single event.\"\"\"\n        pass\n\n\nclass Exchange(Event):\n    \"\"\"\n    An event class representing the net exchange between two zones.\n    netFlow: The net flow of electricity between the two zones.\n    It should be positive if the zoneKey on the left of the arrow is exporting electricity to the zoneKey on the right of the arrow.\n    Negative otherwise.\n    \"\"\"\n\n    netFlow: float | None\n\n    @validator(\"zoneKey\")\n    def _validate_zone_key(cls, v: str):\n        if \"->\" not in v:\n            raise ValueError(f\"Not an exchange key: {v}\")\n        zone_keys = v.split(\"->\")\n        if zone_keys != sorted(zone_keys):\n            raise ValueError(f\"Exchange key not sorted: {v}\")\n        if v not in EXCHANGES_CONFIG:\n            raise ValueError(f\"Unknown zone: {v}\")\n        return v\n\n    @validator(\"netFlow\")\n    def _validate_value(cls, v: float | None):\n        if v is None:\n            raise ValueError(f\"Exchange cannot be None: {v}\")\n        if math.isnan(v):\n            raise ValueError(f\"Exchange cannot be NaN: {v}\")\n        # TODO in the future those checks should be performed in the data quality layer.\n        if abs(v) > 100000:\n            raise ValueError(f\"Exchange is implausibly high, above 100GW: {v}\")\n        return v\n\n    @staticmethod\n    def create(\n        logger: Logger,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        netFlow: float | None,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ) -> \"Exchange | None\":\n        try:\n            return Exchange(\n                zoneKey=zoneKey,\n                datetime=datetime,\n                source=source,\n                netFlow=_none_safe_round(netFlow),\n                sourceType=sourceType,\n            )\n        except ValidationError as e:\n            logger.error(\n                f\"Error(s) creating exchange Event {datetime}: {e}\",\n                extra={\n                    \"zoneKey\": zoneKey,\n                    \"datetime\": datetime.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n                    \"kind\": \"exchange\",\n                },\n            )\n\n    @staticmethod\n    def _update(event: \"Exchange\", new_event: \"Exchange\") -> \"Exchange\":\n        \"\"\"Update the net exchange between two zones.\"\"\"\n        if event.zoneKey != new_event.zoneKey:\n            raise ValueError(\n                f\"Cannot update events from different zones: {event.zoneKey} and {new_event.zoneKey}\"\n            )\n        if event.datetime != new_event.datetime:\n            raise ValueError(\n                f\"Cannot update events from different datetimes: {event.datetime} and {new_event.datetime}\"\n            )\n        if event.source != new_event.source:\n            raise ValueError(\n                f\"Cannot update events from different sources: {event.source} and {new_event.source}\"\n            )\n        if event.sourceType != new_event.sourceType:\n            raise ValueError(\n                f\"Cannot update events from different source types: {event.sourceType} and {new_event.sourceType}\"\n            )\n        return Exchange(\n            zoneKey=event.zoneKey,\n            datetime=event.datetime,\n            source=event.source,\n            netFlow=new_event.netFlow,  # Exchange values can never be none so a new valid value will always be provided.\n            sourceType=event.sourceType,\n        )\n\n    def to_dict(self) -> dict[str, Any]:\n        return {\n            \"datetime\": self.datetime,\n            \"sortedZoneKeys\": self.zoneKey,\n            \"netFlow\": self.netFlow,\n            \"source\": self.source,\n            \"sourceType\": self.sourceType,\n        }\n\n\nclass TotalProduction(Event):\n    \"\"\"Represents the total production of a zone at a given time. The value is in MW.\"\"\"\n\n    value: float | None\n\n    @validator(\"value\")\n    def _validate_value(cls, v: float | None):\n        if v is None:\n            raise ValueError(f\"Total production cannot be None: {v}\")\n        if math.isnan(v):\n            raise ValueError(f\"Exchange cannot be NaN: {v}\")\n        if v < 0:\n            raise ValueError(f\"Total production cannot be negative: {v}\")\n        # TODO in the future those checks should be performed in the data quality layer.\n        if v > 500000:\n            raise ValueError(f\"Total production is implausibly high, above 500GW: {v}\")\n        return v\n\n    @staticmethod\n    def create(\n        logger: Logger,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        value: float | None,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ) -> \"TotalProduction | None\":\n        try:\n            return TotalProduction(\n                zoneKey=zoneKey,\n                datetime=datetime,\n                source=source,\n                value=_none_safe_round(value),\n                sourceType=sourceType,\n            )\n        except ValidationError as e:\n            logger.error(\n                f\"Error(s) creating total production Event {datetime}: {e}\",\n                extra={\n                    \"zoneKey\": zoneKey,\n                    \"datetime\": datetime.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n                    \"kind\": \"production\",\n                },\n            )\n\n    @staticmethod\n    def _update(\n        event: \"TotalProduction\", new_event: \"TotalProduction\"\n    ) -> \"TotalProduction\":\n        \"\"\"Update the total production of a zone at a given time.\"\"\"\n        if event.zoneKey != new_event.zoneKey:\n            raise ValueError(\n                f\"Cannot update events from different zones: {event.zoneKey} and {new_event.zoneKey}\"\n            )\n        if event.datetime != new_event.datetime:\n            raise ValueError(\n                f\"Cannot update events from different datetimes: {event.datetime} and {new_event.datetime}\"\n            )\n        if event.source != new_event.source:\n            raise ValueError(\n                f\"Cannot update events from different sources: {event.source} and {new_event.source}\"\n            )\n        if event.sourceType != new_event.sourceType:\n            raise ValueError(\n                f\"Cannot update events from different source types: {event.sourceType} and {new_event.sourceType}\"\n            )\n        return TotalProduction(\n            zoneKey=event.zoneKey,\n            datetime=event.datetime,\n            source=event.source,\n            value=new_event.value,  # Production values can never be none so a new valid value will always be provided.\n            sourceType=event.sourceType,\n        )\n\n    def to_dict(self) -> dict[str, Any]:\n        return {\n            \"datetime\": self.datetime,\n            \"zoneKey\": self.zoneKey,\n            \"value\": self.value,\n            \"source\": self.source,\n            \"sourceType\": self.sourceType,\n        }\n\n\nclass ProductionBreakdown(AggregatableEvent):\n    production: ProductionMix | None = None\n    storage: StorageMix | None = None\n    \"\"\"\n    An event representing the production and storage breakdown of a zone at a given time.\n    If a production mix is supplied it should not be fully empty.\n    \"\"\"\n\n    @validator(\"production\")\n    def _validate_production_mix(cls, v):\n        if (\n            v is not None\n            and not v.has_corrected_negative_values\n            and all(value is None or math.isnan(value) for value in v.dict().values())\n        ):\n            raise ValueError(\"Mix is completely empty\")\n        return v\n\n    @validator(\"storage\")\n    def _validate_storage_mix(cls, v):\n        if v is not None and all(\n            value is None or math.isnan(value) for value in v.dict().values()\n        ):\n            return None\n        return v\n\n    def get_value(self, mode: str) -> float | None:\n        \"\"\"Returns the value of the provided mode this can be production or storage.\n        To retrieve the value of a storage mode, the mode should be suffixed with storage.\n        Ex: retrive hydro production: get_value(\"hydro\")\n        Ex: retrive hydro storage: get_value(\"hydro storage\")\n        \"\"\"\n        if \"storage\" in mode:\n            if self.storage is None:\n                return None\n            # This naming is the same as the capacity naming in the config.\n            return getattr(self.storage, mode.split(\" \")[0])\n        if self.production is None:\n            return None\n        return getattr(self.production, mode)\n\n    @staticmethod\n    def create(\n        logger: Logger,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        production: ProductionMix | None = None,\n        storage: StorageMix | None = None,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ) -> \"ProductionBreakdown | None\":\n        try:\n            # Log warning if production has been corrected.\n            if production is not None and production.has_corrected_negative_values:\n                logger.debug(\n                    f\"Negative production values were detected: {production._corrected_negative_values}.\\\n                    They have been set to None.\"\n                )\n            return ProductionBreakdown(\n                zoneKey=zoneKey,\n                datetime=datetime,\n                source=source,\n                production=production,\n                storage=storage,\n                sourceType=sourceType,\n            )\n        except ValidationError as e:\n            logger.error(\n                f\"Error(s) creating production breakdown Event {datetime}: {e}\",\n                extra={\n                    \"zoneKey\": zoneKey,\n                    \"datetime\": datetime.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n                    \"kind\": \"production breakdown\",\n                },\n            )\n\n    @staticmethod\n    def aggregate(events: list[\"ProductionBreakdown\"]) -> \"ProductionBreakdown\":\n        \"\"\"Merge ProductionBreakdown events into one.\"\"\"\n        if len(events) == 0:\n            raise ValueError(\"Cannot aggregate empty list of events\")\n        df_view = pd.DataFrame.from_records(\n            [\n                {\n                    \"zoneKey\": event.zoneKey,\n                    \"datetime\": event.datetime,\n                    \"source\": event.source,\n                    \"sourceType\": event.sourceType,\n                    \"data\": event,\n                }\n                for event in events\n            ]\n        )\n        (\n            zoneKey,\n            sources,\n            source_type,\n            target_datetime,\n        ) = ProductionBreakdown._aggregated_fields(df_view)\n\n        production_mix = ProductionMix.merge(\n            [event.production for event in events if event.production is not None]\n        )\n        storage_mix = StorageMix.merge(\n            [event.storage for event in events if event.storage is not None]\n        )\n        return ProductionBreakdown(\n            zoneKey=zoneKey,\n            datetime=target_datetime,\n            source=sources,\n            production=production_mix,\n            storage=storage_mix,\n            sourceType=source_type,\n        )\n\n    @staticmethod\n    def _update(\n        event: \"ProductionBreakdown\", new_event: \"ProductionBreakdown\"\n    ) -> \"ProductionBreakdown\":\n        \"\"\"Update the production and storage breakdown of a zone at a given time.\"\"\"\n        if event.zoneKey != new_event.zoneKey:\n            raise ValueError(\n                f\"Cannot update events from different zones: {event.zoneKey} and {new_event.zoneKey}\"\n            )\n        if event.datetime != new_event.datetime:\n            raise ValueError(\n                f\"Cannot update events from different datetimes: {event.datetime} and {new_event.datetime}\"\n            )\n        if event.sourceType != new_event.sourceType:\n            raise ValueError(\n                f\"Cannot update events from different source types: {event.sourceType} and {new_event.sourceType}\"\n            )\n        production_mix = ProductionMix._update(event.production, new_event.production)\n        storage_mix = StorageMix._update(event.storage, new_event.storage)\n        source = \", \".join(\n            sorted(set(event.source.split(\", \")) | set(new_event.source.split(\", \")))\n        )\n        return ProductionBreakdown(\n            zoneKey=event.zoneKey,\n            datetime=event.datetime,\n            source=source,\n            production=production_mix,\n            storage=storage_mix,\n            sourceType=event.sourceType,\n        )\n\n    def to_dict(self) -> dict[str, Any]:\n        return {\n            \"datetime\": self.datetime,\n            \"zoneKey\": self.zoneKey,\n            \"production\": self.production.dict(\n                exclude_unset=True, keep_corrected_negative_values=True\n            )\n            if self.production\n            else {},\n            \"storage\": self.storage.dict(exclude_unset=True) if self.storage else {},\n            \"source\": self.source,\n            \"sourceType\": self.sourceType,\n            \"correctedModes\": []\n            if self.production is None\n            else sorted(map(str, self.production._corrected_negative_values)),\n        }\n\n\nclass TotalConsumption(Event):\n    \"\"\"Reprensent the total consumption of a zone. The total consumption is expressed in MW.\"\"\"\n\n    consumption: float | None\n\n    @validator(\"consumption\")\n    def _validate_consumption(cls, v: float):\n        if v is None:\n            raise ValueError(f\"Total consumption cannot be None: {v}\")\n        if math.isnan(v):\n            raise ValueError(f\"Exchange cannot be NaN: {v}\")\n        if v < 0:\n            raise ValueError(f\"Total consumption cannot be negative: {v}\")\n        # TODO in the future those checks should be performed in the data quality layer.\n        if v > 500000:\n            raise ValueError(f\"Total consumption is implausibly high, above 500GW: {v}\")\n        if v == 0:\n            raise ValueError(f\"Total consumption cannot be 0 MW: {v}\")\n        return v\n\n    @staticmethod\n    def create(\n        logger: Logger,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        consumption: float | None,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ) -> \"TotalConsumption | None\":\n        try:\n            return TotalConsumption(\n                zoneKey=zoneKey,\n                datetime=datetime,\n                source=source,\n                consumption=_none_safe_round(consumption),\n                sourceType=sourceType,\n            )\n        except ValidationError as e:\n            logger.error(\n                f\"Error(s) creating total consumption Event {datetime}: {e}\",\n                extra={\n                    \"zoneKey\": zoneKey,\n                    \"datetime\": datetime.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n                    \"kind\": \"consumption\",\n                },\n            )\n\n    @staticmethod\n    def _update(\n        event: \"TotalConsumption\", new_event: \"TotalConsumption\"\n    ) -> \"TotalConsumption\":\n        \"\"\"Update the total consumption of a zone at a given time.\"\"\"\n        if event.zoneKey != new_event.zoneKey:\n            raise ValueError(\n                f\"Cannot update events from different zones: {event.zoneKey} and {new_event.zoneKey}\"\n            )\n        if event.datetime != new_event.datetime:\n            raise ValueError(\n                f\"Cannot update events from different datetimes: {event.datetime} and {new_event.datetime}\"\n            )\n        if event.source != new_event.source:\n            raise ValueError(\n                f\"Cannot update events from different sources: {event.source} and {new_event.source}\"\n            )\n        if event.sourceType != new_event.sourceType:\n            raise ValueError(\n                f\"Cannot update events from different source types: {event.sourceType} and {new_event.sourceType}\"\n            )\n        return TotalConsumption(\n            zoneKey=event.zoneKey,\n            datetime=event.datetime,\n            source=event.source,\n            consumption=new_event.consumption,  # Consumption values can never be none so a new valid value will always be provided.\n            sourceType=event.sourceType,\n        )\n\n    def to_dict(self) -> dict[str, Any]:\n        return {\n            \"datetime\": self.datetime,\n            \"zoneKey\": self.zoneKey,\n            \"consumption\": self.consumption,\n            \"source\": self.source,\n            \"sourceType\": self.sourceType,\n        }\n\n\nclass Price(Event):\n    price: float | None\n    currency: str\n\n    @validator(\"currency\")\n    def _validate_currency(cls, v: str) -> str:\n        if v not in VALID_CURRENCIES:\n            raise ValueError(f\"Unknown currency: {v}\")\n        return v\n\n    @validator(\"datetime\")\n    def _validate_datetime(cls, v: dt.datetime) -> datetime:\n        \"\"\"Prices are given for the day ahead, so we should allow them to be in the future.\"\"\"\n        if _is_naive(v):\n            raise ValueError(f\"Missing timezone: {v}\")\n        if v < LOWER_DATETIME_BOUND:\n            raise ValueError(f\"Date is before 2000, this is not plausible: {v}\")\n        return v\n\n    @validator(\"price\")\n    def _validate_price(cls, v: float | None) -> float:\n        \"\"\"Prices can be negative but not None, so we should only check for None values\"\"\"\n        if v is None:\n            raise ValueError(f\"Price cannot be None: {v}\")\n        if math.isnan(v):\n            raise ValueError(f\"Price cannot be NaN: {v}\")\n        return v\n\n    @staticmethod\n    def create(\n        logger: Logger,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        price: float | None,\n        currency: str,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ) -> \"Price | None\":\n        try:\n            return Price(\n                zoneKey=zoneKey,\n                datetime=datetime,\n                source=source,\n                price=price,\n                currency=currency,\n                sourceType=sourceType,\n            )\n        except ValidationError as e:\n            logger.error(\n                f\"Error(s) creating price Event {datetime}: {e}\",\n                extra={\n                    \"zoneKey\": zoneKey,\n                    \"datetime\": datetime.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n                    \"kind\": \"price\",\n                },\n            )\n\n    def to_dict(self) -> dict[str, Any]:\n        return {\n            \"datetime\": self.datetime,\n            \"zoneKey\": self.zoneKey,\n            \"currency\": self.currency,\n            \"price\": self.price,\n            \"source\": self.source,\n            \"sourceType\": self.sourceType,\n        }\n\n\nclass LocationalMarginalPrice(Price):\n    node: str\n\n    @validator(\"node\")\n    def _validate_node(cls, v: str) -> str:\n        clean_value = v.strip()\n        if not clean_value:\n            raise ValueError(f\"Node cannot be an invalid string: {v}\")\n        if clean_value != v:\n            raise ValueError(f\"Node should not contain leading or trailing spaces: {v}\")\n        return v\n\n    @staticmethod\n    def create(\n        logger: Logger,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        price: float | None,\n        currency: str,\n        node: str,\n        sourceType: EventSourceType = EventSourceType.measured,\n    ) -> \"LocationalMarginalPrice | None\":\n        try:\n            return LocationalMarginalPrice(\n                zoneKey=zoneKey,\n                datetime=datetime,\n                source=source,\n                price=price,\n                currency=currency,\n                node=node,\n                sourceType=sourceType,\n            )\n        except ValidationError as e:\n            logger.error(\n                f\"Error(s) creating Locational Marginal Price Event {datetime}: {e}\",\n                extra={\n                    \"zoneKey\": zoneKey,\n                    \"datetime\": datetime.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n                    \"kind\": \"Locational Marginal Price\",\n                },\n            )\n\n    def to_dict(self) -> dict[str, Any]:\n        return {\n            \"datetime\": self.datetime,\n            \"zoneKey\": self.zoneKey,\n            \"currency\": self.currency,\n            \"price\": self.price,\n            \"node\": self.node,\n            \"source\": self.source,\n            \"sourceType\": self.sourceType,\n        }\n\n\nclass GridAlertType(str, Enum):\n    informational = \"informational\"\n    action = \"action\"\n    undefined = \"undefined\"\n\n\nclass GridAlert(Event):\n    locationRegion: str | None = None\n    alertType: GridAlertType\n    message: str\n    issuedTime: datetime\n    startTime: datetime | None\n    endTime: datetime | None\n\n    @validator(\"alertType\")\n    def _validate_alert_type(cls, v: GridAlertType) -> GridAlertType:\n        if v not in GridAlertType:\n            raise ValueError(f\"Unknown alert type: {v}\")\n        return v\n\n    @validator(\"message\")\n    def _validate_message(cls, v: str) -> str:\n        if not v:\n            raise ValueError(f\"message cannot be empty: {v}\")\n        return v\n\n    @validator(\"issuedTime\")\n    def _validate_issued_time(cls, v: datetime) -> datetime:\n        if _is_naive(v):\n            raise ValueError(f\"Missing timezone: {v}\")\n        if v < LOWER_DATETIME_BOUND:\n            raise ValueError(f\"Date is before 2000, this is not plausible: {v}\")\n        return v\n\n    @validator(\"startTime\")\n    def _validate_start_time(cls, v: datetime | None) -> datetime | None:\n        if v and _is_naive(v):\n            raise ValueError(f\"Missing timezone: {v}\")\n        if v and v < LOWER_DATETIME_BOUND:\n            raise ValueError(f\"Date is before 2000, this is not plausible: {v}\")\n        return v\n\n    @root_validator\n    def _default_start_time(cls, values):\n        if values.get(\"startTime\") is None:\n            values[\"startTime\"] = values[\"issuedTime\"]\n        return values\n\n    @validator(\"endTime\")\n    def _validate_end_time(cls, v: datetime | None) -> datetime | None:\n        if v is None:\n            return v\n        if _is_naive(v):\n            raise ValueError(f\"Missing timezone: {v}\")\n        if v < LOWER_DATETIME_BOUND:\n            raise ValueError(f\"Date is before 2000, this is not plausible: {v}\")\n        return v\n\n    @staticmethod\n    def create(\n        logger: Logger,\n        zoneKey: ZoneKey,\n        locationRegion: str | None,\n        source: str,\n        alertType: GridAlertType,\n        message: str,\n        issuedTime: datetime,\n        startTime: datetime | None,\n        endTime: datetime | None,\n    ) -> \"GridAlert | None\":\n        try:\n            return GridAlert(\n                zoneKey=zoneKey,\n                locationRegion=locationRegion,\n                source=source,\n                alertType=alertType,\n                message=message,\n                issuedTime=issuedTime,\n                startTime=startTime,\n                endTime=endTime,\n                datetime=issuedTime,  # Event requires a datetime field\n            )\n        except ValidationError as e:\n            logger.error(\n                f\"Error(s) creating Grid Alert Event {issuedTime}: {e}\",\n                extra={\n                    \"zoneKey\": zoneKey,\n                    \"issuedTime\": issuedTime.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n                    \"kind\": \"Grid Alert\",\n                },\n            )\n\n    def to_dict(self) -> dict[str, Any]:\n        return {\n            \"zoneKey\": self.zoneKey,\n            \"locationRegion\": self.locationRegion,\n            \"alertType\": self.alertType,\n            \"message\": self.message,\n            \"issuedTime\": self.issuedTime,\n            \"startTime\": self.startTime,\n            \"endTime\": self.endTime,\n            \"source\": self.source,\n            \"datetime\": self.datetime,\n        }\n\n\nclass ExchangeCapacity(Event):\n    \"\"\"\n    An event representing the forecasted net transfer capacity (NTC) between\n    two zones in both directions.\n\n    capacityExport: Capacity for zone1→zone2 direction (may be None).\n    capacityImport: Capacity for zone2→zone1 direction (may be None).\n    \"\"\"\n\n    sourceType: EventSourceType = EventSourceType.published\n    capacityExport: float | None\n    capacityImport: float | None\n\n    @validator(\"zoneKey\")\n    def _validate_zone_key(cls, v: str):\n        if \"->\" not in v:\n            raise ValueError(f\"Not an exchange key: {v}\")\n        zone_keys = v.split(\"->\")\n        if zone_keys != sorted(zone_keys):\n            raise ValueError(f\"Exchange key not sorted: {v}\")\n        if v not in EXCHANGES_CONFIG:\n            raise ValueError(f\"Unknown zone: {v}\")\n        return v\n\n    @root_validator(pre=False)\n    def _validate_capacity_bounds(cls, values: dict[str, Any]) -> dict[str, Any]:\n        if (\n            values.get(\"capacityExport\") is None\n            and values.get(\"capacityImport\") is None\n        ):\n            raise ValueError(\n                \"At least one of capacityExport or capacityImport must be set\"\n            )\n        return values\n\n    @staticmethod\n    def create(\n        logger: Logger,\n        zoneKey: ZoneKey,\n        datetime: datetime,\n        source: str,\n        capacityExport: float | None,\n        capacityImport: float | None,\n        sourceType: EventSourceType = EventSourceType.published,\n    ) -> \"ExchangeCapacity | None\":\n        try:\n            return ExchangeCapacity(\n                zoneKey=zoneKey,\n                datetime=datetime,\n                source=source,\n                capacityExport=_none_safe_round(capacityExport),\n                capacityImport=_none_safe_round(capacityImport),\n                sourceType=sourceType,\n            )\n        except ValidationError as e:\n            logger.error(\n                f\"Error(s) creating ExchangeCapacity Event {datetime}: {e}\",\n                extra={\n                    \"zoneKey\": zoneKey,\n                    \"datetime\": datetime.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n                    \"kind\": \"exchange capacity forecast\",\n                },\n            )\n            return None\n\n    def to_dict(self) -> dict[str, Any]:\n        return {\n            \"datetime\": self.datetime,\n            \"sortedZoneKeys\": self.zoneKey,\n            \"capacityExport\": self.capacityExport,\n            \"capacityImport\": self.capacityImport,\n            \"source\": self.source,\n            \"sourceType\": self.sourceType,\n        }\n"
  },
  {
    "path": "electricitymap/contrib/lib/tests/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/lib/tests/test_event_lists.py",
    "content": "import logging\nimport math\nfrom datetime import datetime, timedelta, timezone\nfrom unittest.mock import patch\n\nimport pytest\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeCapacityList,\n    ExchangeList,\n    GridAlertList,\n    LocationalMarginalPriceList,\n    PriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n    TotalProductionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    GridAlertType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_exchange_list():\n    exchange_list = ExchangeList(logging.Logger(\"test\"))\n    exchange_list.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    exchange_list.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    assert len(exchange_list.events) == 2\n\n\ndef test_append_to_list_logs_error():\n    exchange_list = ExchangeList(logging.Logger(\"test\"))\n    with patch.object(exchange_list.logger, \"error\") as mock_error:\n        exchange_list.append(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            netFlow=1,\n            source=\"trust.me\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_merge_exchanges():\n    dt = datetime(2023, 1, 1, tzinfo=timezone.utc)\n    exchange_list_1 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list_1.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=dt,\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    exchange_list_2 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list_2.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=dt,\n        netFlow=2,\n        source=\"trust.me\",\n    )\n    exchanges = ExchangeList.merge_exchanges(\n        [exchange_list_1, exchange_list_2], logging.Logger(\"test\")\n    )\n    assert len(exchanges) == 1\n    assert exchanges[dt].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert exchanges[dt].netFlow == 3\n\n\ndef test_merge_exchanges_with_none():\n    exchange_list_1 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list_1.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    exchange_list_2 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list_2.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=math.nan,\n        source=\"trust.me\",\n    )\n    exchanges = ExchangeList.merge_exchanges(\n        [exchange_list_1, exchange_list_2], logging.Logger(\"test\")\n    )\n    assert len(exchanges) == 1\n    assert exchanges.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert exchanges.events[0].netFlow == 1\n\n\ndef test_merge_exchanges_with_negatives():\n    exchange_list_1 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list_1.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    exchange_list_2 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list_2.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=-11,\n        source=\"trust.me\",\n    )\n    exchanges = ExchangeList.merge_exchanges(\n        [exchange_list_1, exchange_list_2], logging.Logger(\"test\")\n    )\n    assert len(exchanges) == 1\n    assert exchanges.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert exchanges.events[0].netFlow == -10\n\n\ndef test_update_exchange_list():\n    exchange_list1 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list1.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    exchange_list1.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    exchange_list2 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list2.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=2,\n        source=\"trust.me\",\n    )\n    updated_list = ExchangeList.update_exchanges(\n        exchange_list1, exchange_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 2\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].netFlow == 2\n    assert updated_list.events[0].source == \"trust.me\"\n    assert updated_list.events[1].datetime == datetime(2023, 1, 2, tzinfo=timezone.utc)\n    assert updated_list.events[1].netFlow == 1\n    assert updated_list.events[1].source == \"trust.me\"\n\n\ndef test_update_exchange_list_with_different_zoneKey():\n    exchange_list1 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list1.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    exchange_list2 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list2.append(\n        zoneKey=ZoneKey(\"DE->DK-DK1\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=2,\n        source=\"trust.me\",\n    )\n    with pytest.raises(ValueError):\n        ExchangeList.update_exchanges(\n            exchange_list1, exchange_list2, logging.Logger(\"test\")\n        )\n\n\ndef test_update_exchange_list_with_longer_new_list():\n    exchange_list1 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list1.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    exchange_list2 = ExchangeList(logging.Logger(\"test\"))\n    exchange_list2.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=2,\n        source=\"trust.me\",\n    )\n    exchange_list2.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        netFlow=3,\n        source=\"trust.me\",\n    )\n    updated_list = ExchangeList.update_exchanges(\n        exchange_list1, exchange_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 2\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].netFlow == 2\n    assert updated_list.events[0].source == \"trust.me\"\n    assert updated_list.events[1].datetime == datetime(2023, 1, 2, tzinfo=timezone.utc)\n    assert updated_list.events[1].netFlow == 3\n    assert updated_list.events[1].source == \"trust.me\"\n\n\ndef test_consumption_list():\n    consumption_list = TotalConsumptionList(logging.Logger(\"test\"))\n    consumption_list.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        consumption=1,\n        source=\"trust.me\",\n    )\n    consumption_list.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        consumption=1,\n        source=\"trust.me\",\n    )\n    assert len(consumption_list.events) == 2\n\n\ndef test_append_to_consumption_list_logs_error():\n    consumption_list = TotalConsumptionList(logging.Logger(\"test\"))\n    with patch.object(consumption_list.logger, \"error\") as mock_error:\n        consumption_list.append(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            consumption=-1,\n            source=\"trust.me\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_price_list():\n    price_list = PriceList(logging.Logger(\"test\"))\n    price_list.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        price=1,\n        source=\"trust.me\",\n        currency=\"EUR\",\n    )\n    assert len(price_list.events) == 1\n\n\ndef test_append_to_price_list_logs_error():\n    price_list = PriceList(logging.Logger(\"test\"))\n    with patch.object(price_list.logger, \"error\") as mock_error:\n        price_list.append(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            price=1,\n            source=\"trust.me\",\n            currency=\"EURO\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_locational_marginal_price_list():\n    lmp_list = LocationalMarginalPriceList(logging.Logger(\"test\"))\n    lmp_list.append(\n        zoneKey=ZoneKey(\"US-CENT-SWPP\"),\n        datetime=datetime(2025, 3, 1, tzinfo=timezone.utc),\n        price=1,\n        source=\"trust.me\",\n        currency=\"USD\",\n        node=\"SPPNORTH_HUB\",\n    )\n    assert len(lmp_list.events) == 1\n\n\ndef test_append_to_locational_marginal_price_list_logs_error():\n    lmp_list = LocationalMarginalPriceList(logging.Logger(\"test\"))\n    with patch.object(lmp_list.logger, \"error\") as mock_error:\n        lmp_list.append(\n            zoneKey=ZoneKey(\"US-CENT-SWPP\"),\n            datetime=datetime(2025, 3, 1, tzinfo=timezone.utc),\n            price=1,\n            source=\"trust.me\",\n            currency=\"EUR\",\n            node=\"\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_grid_alert_list():\n    grid_alert_list = GridAlertList(logging.Logger(\"test\"))\n    grid_alert_list.append(\n        zoneKey=ZoneKey(\"US-MIDA-PJM\"),\n        locationRegion=\"Test Region\",\n        source=\"trust.me\",\n        alertType=GridAlertType.action,\n        message=\"This is a test message\",\n        issuedTime=datetime(2025, 3, 1, tzinfo=timezone.utc),\n        startTime=None,\n        endTime=None,\n    )\n    assert len(grid_alert_list.events) == 1\n\n\ndef test_append_to_grid_alert_list_logs_error():\n    grid_alert_list = GridAlertList(logging.Logger(\"test\"))\n    with patch.object(grid_alert_list.logger, \"error\") as mock_error:\n        grid_alert_list.append(\n            zoneKey=ZoneKey(\"US-MIDA-PJM\"),\n            locationRegion=\"\",\n            source=\"trust.me\",\n            alertType=GridAlertType.action,\n            message=\"\",\n            issuedTime=datetime(2025, 3, 1, tzinfo=timezone.utc),\n            startTime=None,\n            endTime=None,\n        )\n        mock_error.assert_called_once()\n\n\ndef test_production_list():\n    production_list = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10),\n        source=\"trust.me\",\n    )\n    assert len(production_list.events) == 1\n\n\ndef test_production_list_logs_error():\n    production_list = ProductionBreakdownList(logging.Logger(\"test\"))\n    with patch.object(production_list.logger, \"error\") as mock_error:\n        production_list.append(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1),\n            production=ProductionMix(wind=10),\n            source=\"trust.me\",\n        )\n        mock_error.assert_called_once()\n    with patch.object(production_list.logger, \"debug\") as mock_logger:\n        production_list.append(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            production=ProductionMix(wind=-10),\n            source=\"trust.me\",\n        )\n        mock_logger.assert_called_once()\n\n\ndef test_merge_production_list_production_mix_only():\n    production_list_1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10),\n        source=\"trust.me\",\n    )\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        production=ProductionMix(wind=11, coal=1),\n        source=\"trust.me\",\n    )\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 3, tzinfo=timezone.utc),\n        production=ProductionMix(wind=12, coal=2),\n        source=\"trust.me\",\n    )\n    production_list_2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=20),\n        source=\"trust2.me\",\n    )\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        production=ProductionMix(wind=21, coal=1),\n        source=\"trust2.me\",\n    )\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 3, tzinfo=timezone.utc),\n        production=ProductionMix(wind=22, coal=2),\n        source=\"trust2.me\",\n    )\n    production_list_3 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_3.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=30),\n        source=\"trust3.me\",\n    )\n    production_list_3.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        production=ProductionMix(wind=31, coal=1),\n        source=\"trust3.me\",\n    )\n    merged = ProductionBreakdownList.merge_production_breakdowns(\n        [production_list_1, production_list_2, production_list_3],\n        logging.Logger(\"test\"),\n    )\n    assert len(merged.events) == 3\n    assert merged.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert merged.events[0].production is not None\n    assert merged.events[0].production.wind == 60\n    assert merged.events[0].production.coal is None\n    assert merged.events[0].source == \"trust.me, trust2.me, trust3.me\"\n    assert merged.events[0].zoneKey == ZoneKey(\"AT\")\n    assert merged.events[0].storage is None\n    assert merged.events[0].sourceType == EventSourceType.measured\n\n    assert merged.events[1].datetime == datetime(2023, 1, 2, tzinfo=timezone.utc)\n    assert merged.events[1].production is not None\n    assert merged.events[1].production.wind == 63\n    assert merged.events[1].production.coal == 3\n\n    assert merged.events[2].datetime == datetime(2023, 1, 3, tzinfo=timezone.utc)\n    assert merged.events[2].production is not None\n    assert merged.events[2].production.wind == 34\n    assert merged.events[2].production.coal == 4\n\n\ndef test_merge_production_list():\n    production_list_1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        production=ProductionMix(wind=11, coal=1),\n        storage=StorageMix(hydro=1, battery=1),\n        source=\"trust.me\",\n    )\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 3, tzinfo=timezone.utc),\n        production=ProductionMix(wind=12, coal=2),\n        source=\"trust.me\",\n    )\n    production_list_2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=20),\n        storage=StorageMix(hydro=1, battery=1),\n        source=\"trust.me\",\n    )\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        production=ProductionMix(wind=21, coal=1),\n        source=\"trust.me\",\n    )\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 3, tzinfo=timezone.utc),\n        production=ProductionMix(wind=22, coal=2),\n        storage=StorageMix(hydro=1, battery=1),\n        source=\"trust.me\",\n    )\n    production_list_3 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_3.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=30),\n        source=\"trust.me\",\n    )\n    production_list_3.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        production=ProductionMix(wind=31, coal=1),\n        source=\"trust.me\",\n    )\n    merged = ProductionBreakdownList.merge_production_breakdowns(\n        [production_list_1, production_list_2, production_list_3],\n        logging.Logger(\"test\"),\n    )\n    assert len(merged.events) == 3\n    assert merged.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert merged.events[0].storage.hydro == 2\n\n\ndef test_merge_production_list_doesnt_yield_extra_modes():\n    production_list_1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10, coal=None),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    production_list_2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_mix = ProductionMix(wind=20)\n    production_mix.add_value(\"hydro\", None)\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=production_mix,\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    merged = ProductionBreakdownList.merge_production_breakdowns(\n        [production_list_1, production_list_2], logging.Logger(\"test\")\n    )\n    assert len(merged.events) == 1\n    assert merged.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert merged.events[0].production.hydro is None\n    assert merged.events[0].storage.battery is None\n    merged_dict = merged.events[0].to_dict()\n    assert merged_dict[\"production\"].keys() == {\"coal\", \"hydro\", \"wind\"}\n    assert merged_dict[\"storage\"].keys() == {\"hydro\"}\n\n\ndef test_merge_production_list_predicted():\n    production_list_1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n        sourceType=EventSourceType.forecasted,\n    )\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 3, tzinfo=timezone.utc),\n        production=ProductionMix(wind=12, coal=2),\n        source=\"trust.me\",\n        sourceType=EventSourceType.forecasted,\n    )\n    production_list_2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=20),\n        storage=StorageMix(hydro=1, battery=1),\n        source=\"trust.me\",\n        sourceType=EventSourceType.forecasted,\n    )\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 3, tzinfo=timezone.utc),\n        production=ProductionMix(wind=22, coal=2),\n        storage=StorageMix(hydro=1, battery=1),\n        source=\"trust.me\",\n        sourceType=EventSourceType.forecasted,\n    )\n    merged = ProductionBreakdownList.merge_production_breakdowns(\n        [production_list_1, production_list_2],\n        logging.Logger(\"test\"),\n    )\n    assert len(merged.events) == 2\n    assert merged.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert merged.events[0].storage is not None\n    assert merged.events[0].storage.hydro == 2\n    assert merged.events[0].sourceType == EventSourceType.forecasted\n\n\ndef test_merge_production_retains_corrected_negatives():\n    production_list_1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=-10, coal=10),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 3, tzinfo=timezone.utc),\n        production=ProductionMix(wind=-12, coal=12),\n        storage=StorageMix(hydro=1, battery=1),\n        source=\"trust.me\",\n    )\n    production_list_2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(hydro=20, coal=20),\n        storage=StorageMix(hydro=1, battery=1),\n        source=\"trust.me\",\n    )\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 3, tzinfo=timezone.utc),\n        production=ProductionMix(hydro=22, coal=22),\n        storage=StorageMix(hydro=1, battery=1),\n        source=\"trust.me\",\n    )\n    merged = ProductionBreakdownList.merge_production_breakdowns(\n        [production_list_1, production_list_2],\n        logging.Logger(\"test\"),\n    )\n    assert len(merged.events) == 2\n    assert merged.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert merged.events[0].production is not None\n    assert merged.events[0].production.wind is None\n    assert merged.events[0].production.coal == 30\n    assert merged.events[0].storage.hydro == 2\n    assert merged.events[0].production._corrected_negative_values == {\"wind\"}\n\n    assert merged.events[1].datetime == datetime(2023, 1, 3, tzinfo=timezone.utc)\n    assert merged.events[1].production is not None\n    assert merged.events[1].production.wind is None\n    assert merged.events[1].production.coal == 34\n    assert merged.events[1].storage.hydro == 2\n    assert merged.events[1].production._corrected_negative_values == {\"wind\"}\n\n\ndef test_merge_production_retains_corrected_negatives_with_0_and_none():\n    production_list_1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_mix_1 = ProductionMix(wind=-10, coal=10)\n    production_mix_1.add_value(\"solar\", -10, correct_negative_with_zero=True)\n    production_mix_1.add_value(\"biomass\", -10, correct_negative_with_zero=True)\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=production_mix_1,\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    production_list_2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_mix_2 = ProductionMix(hydro=20, coal=20)\n    production_mix_2.add_value(\"solar\", 20, correct_negative_with_zero=True)\n    production_list_2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=production_mix_2,\n        storage=StorageMix(hydro=1, battery=1),\n        source=\"trust.me\",\n    )\n    merged = ProductionBreakdownList.merge_production_breakdowns(\n        [production_list_1, production_list_2],\n        logging.Logger(\"test\"),\n    )\n    assert len(merged.events) == 1\n    assert merged.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert merged.events[0].production is not None\n    assert merged.events[0].production.wind is None\n    assert merged.events[0].production.solar == 20\n    assert merged.events[0].production.coal == 30\n    assert merged.events[0].production.biomass == 0\n    assert merged.events[0].production._corrected_negative_values == {\n        \"wind\",\n        \"solar\",\n        \"biomass\",\n    }\n\n\ndef test_update_production_list_with_production():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10, coal=10),\n        source=\"trust.me\",\n    )\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        production=ProductionMix(wind=11, coal=11),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=20, coal=20),\n        source=\"trust.me\",\n    )\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 2\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].production.wind == 20\n    assert updated_list.events[0].production.coal == 20\n    assert updated_list.events[0].source == \"trust.me\"\n    assert updated_list.events[1].datetime == datetime(2023, 1, 2, tzinfo=timezone.utc)\n    assert updated_list.events[1].production.wind == 11\n    assert updated_list.events[1].production.coal == 11\n    assert updated_list.events[1].source == \"trust.me\"\n\n\ndef test_update_production_list_with_new_list_being_longer():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10, coal=10),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=20, coal=20),\n        source=\"trust.me\",\n    )\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        production=ProductionMix(wind=21, coal=21),\n        source=\"trust.me\",\n    )\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 2\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].production is not None\n    assert updated_list.events[0].production.wind == 20\n    assert updated_list.events[0].production.coal == 20\n    assert updated_list.events[0].source == \"trust.me\"\n    assert updated_list.events[1].datetime == datetime(2023, 1, 2, tzinfo=timezone.utc)\n    assert updated_list.events[1].production is not None\n    assert updated_list.events[1].production.wind == 21\n    assert updated_list.events[1].production.coal == 21\n    assert updated_list.events[1].source == \"trust.me\"\n\n\ndef test_update_storage_list_with_new_list_being_longer():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=2),\n        source=\"trust.me\",\n    )\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=3),\n        source=\"trust.me\",\n    )\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 2\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].storage is not None\n    assert updated_list.events[0].storage.hydro == 2\n    assert updated_list.events[0].source == \"trust.me\"\n    assert updated_list.events[1].datetime == datetime(2023, 1, 2, tzinfo=timezone.utc)\n    assert updated_list.events[1].storage is not None\n    assert updated_list.events[1].storage.hydro == 3\n    assert updated_list.events[1].source == \"trust.me\"\n\n\ndef test_update_production_list_with_storage():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=2),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=2),\n        source=\"trust.me\",\n    )\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 2\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].storage is not None\n    assert updated_list.events[0].storage.hydro == 2\n    assert updated_list.events[0].source == \"trust.me\"\n    assert updated_list.events[1].datetime == datetime(2023, 1, 2, tzinfo=timezone.utc)\n    assert updated_list.events[1].storage is not None\n    assert updated_list.events[1].storage.hydro == 2\n    assert updated_list.events[1].source == \"trust.me\"\n\n\ndef test_update_production_list_with_none_in_production():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10, coal=10),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=None, coal=20),\n        source=\"trust.me\",\n    )\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 1\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].production is not None\n    assert updated_list.events[0].production.wind == 10\n    assert updated_list.events[0].production.coal == 20\n    assert updated_list.events[0].source == \"trust.me\"\n\n\ndef test_update_production_list_with_none_in_storage():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=None),\n        source=\"trust.me\",\n    )\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 1\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].storage.hydro == 1\n    assert updated_list.events[0].source == \"trust.me\"\n\n\ndef test_update_production_with_different_zoneKey():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10, coal=10),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=20, coal=20),\n        source=\"trust.me\",\n    )\n    with pytest.raises(ValueError):\n        ProductionBreakdownList.update_production_breakdowns(\n            production_list1, production_list2, logging.Logger(\"test\")\n        )\n\n\ndef test_update_production_with_different_source():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10, coal=10),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=20, coal=20),\n        source=\"trust.me.too\",\n    )\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 1\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].production is not None\n    assert updated_list.events[0].production.wind == 20\n    assert updated_list.events[0].production.coal == 20\n    assert updated_list.events[0].source == \", \".join(\n        sorted({\"trust.me\", \"trust.me.too\"})\n    )\n\n\ndef test_update_production_with_different_sourceType():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10, coal=10),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=20, coal=20),\n        source=\"trust.me\",\n        sourceType=EventSourceType.forecasted,\n    )\n    with pytest.raises(ValueError):\n        ProductionBreakdownList.update_production_breakdowns(\n            production_list1, production_list2, logging.Logger(\"test\")\n        )\n\n\ndef test_update_production_with_empty_list():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=20, coal=20),\n        source=\"trust.me\",\n    )\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 1\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].production is not None\n    assert updated_list.events[0].production.wind == 20\n    assert updated_list.events[0].production.coal == 20\n    assert updated_list.events[0].source == \"trust.me\"\n\n\ndef test_update_production_with_empty_new_list():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10, coal=10),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 1\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].production is not None\n    assert updated_list.events[0].production.wind == 10\n    assert updated_list.events[0].production.coal == 10\n    assert updated_list.events[0].source == \"trust.me\"\n\n\ndef test_update_stroage_with_empty_list():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list2.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 1\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].storage is not None\n    assert updated_list.events[0].storage.hydro == 1\n    assert updated_list.events[0].source == \"trust.me\"\n\n\ndef test_update_stroage_with_empty_new_list():\n    production_list1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_list1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    production_list2 = ProductionBreakdownList(logging.Logger(\"test\"))\n    updated_list = ProductionBreakdownList.update_production_breakdowns(\n        production_list1, production_list2, logging.Logger(\"test\")\n    )\n    assert len(updated_list.events) == 1\n    assert updated_list.events[0].datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert updated_list.events[0].storage is not None\n    assert updated_list.events[0].storage.hydro == 1\n    assert updated_list.events[0].source == \"trust.me\"\n\n\ndef test_total_production_list():\n    total_production = TotalProductionList(logging.Logger(\"test\"))\n    total_production.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        value=1,\n        source=\"trust.me\",\n    )\n    assert len(total_production.events) == 1\n\n\ndef test_merge_total_production_lists():\n    logger = logging.Logger(\"test\")\n    dt = datetime(2023, 1, 1, tzinfo=timezone.utc)\n    dt_later = dt + timedelta(hours=1)\n\n    first = TotalProductionList(logger)\n    first.append(\n        zoneKey=ZoneKey(\"IT-SO\"),\n        datetime=dt,\n        value=100,\n        source=\"entsoe\",\n    )\n\n    second = TotalProductionList(logger)\n    second.append(\n        zoneKey=ZoneKey(\"IT-SO\"),\n        datetime=dt,\n        value=50,\n        source=\"entsoe\",\n    )\n    second.append(\n        zoneKey=ZoneKey(\"IT-SO\"),\n        datetime=dt_later,\n        value=25,\n        source=\"entsoe\",\n    )\n\n    merged = TotalProductionList.merge_total_production_lists([first, second], logger)\n\n    assert merged.to_list() == [\n        {\n            \"datetime\": dt,\n            \"zoneKey\": ZoneKey(\"IT-SO\"),\n            \"value\": 150,\n            \"source\": \"entsoe\",\n            \"sourceType\": EventSourceType.measured,\n        },\n        {\n            \"datetime\": dt_later,\n            \"zoneKey\": ZoneKey(\"IT-SO\"),\n            \"value\": 25,\n            \"source\": \"entsoe\",\n            \"sourceType\": EventSourceType.measured,\n        },\n    ]\n\n\ndef test_merge_consumption_lists():\n    logger = logging.Logger(\"test\")\n    dt = datetime(2023, 1, 1, tzinfo=timezone.utc)\n    dt_later = dt + timedelta(hours=1)\n\n    first = TotalConsumptionList(logger)\n    first.append(\n        zoneKey=ZoneKey(\"IT-SO\"),\n        datetime=dt,\n        consumption=80,\n        source=\"entsoe\",\n    )\n\n    second = TotalConsumptionList(logger)\n    second.append(\n        zoneKey=ZoneKey(\"IT-SO\"),\n        datetime=dt,\n        consumption=20,\n        source=\"entsoe\",\n    )\n    second.append(\n        zoneKey=ZoneKey(\"IT-SO\"),\n        datetime=dt_later,\n        consumption=30,\n        source=\"entsoe\",\n    )\n\n    merged = TotalConsumptionList.merge_consumption_lists([first, second], logger)\n\n    assert merged.to_list() == [\n        {\n            \"datetime\": dt,\n            \"zoneKey\": ZoneKey(\"IT-SO\"),\n            \"consumption\": 100,\n            \"source\": \"entsoe\",\n            \"sourceType\": EventSourceType.measured,\n        },\n        {\n            \"datetime\": dt_later,\n            \"zoneKey\": ZoneKey(\"IT-SO\"),\n            \"consumption\": 30,\n            \"source\": \"entsoe\",\n            \"sourceType\": EventSourceType.measured,\n        },\n    ]\n\n\ndef test_df_representation():\n    production_list_1 = ProductionBreakdownList(logging.Logger(\"test\"))\n    production_mix_1 = ProductionMix(wind=-10, coal=10)\n    production_mix_1.add_value(\"solar\", -10, correct_negative_with_zero=True)\n    production_mix_1.add_value(\"biomass\", -10, correct_negative_with_zero=True)\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=production_mix_1,\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n    production_list_1.append(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        production=ProductionMix(wind=-12, coal=12),\n        storage=StorageMix(hydro=1),\n        source=\"trust.me\",\n    )\n\n\ndef test_exchange_capacity_forecast_list():\n    forecast_list = ExchangeCapacityList(logging.Logger(\"test\"))\n    forecast_list.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        source=\"trust.me\",\n        capacityExport=1000.0,\n        capacityImport=900.0,\n    )\n    forecast_list.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        source=\"trust.me\",\n        capacityExport=1100.0,\n        capacityImport=950.0,\n    )\n    assert len(forecast_list.events) == 2\n\n\ndef test_append_to_exchange_capacity_forecast_list_logs_error():\n    forecast_list = ExchangeCapacityList(logging.Logger(\"test\"))\n    with patch.object(forecast_list.logger, \"error\") as mock_error:\n        # Unsorted zone key should log error and not append\n        forecast_list.append(\n            zoneKey=ZoneKey(\"DE->AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            source=\"trust.me\",\n            capacityExport=1000.0,\n            capacityImport=900.0,\n        )\n        mock_error.assert_called_once()\n    assert len(forecast_list.events) == 0\n\n\ndef test_exchange_capacity_forecast_list_to_list_sorted_by_datetime():\n    dt1 = datetime(2023, 1, 1, tzinfo=timezone.utc)\n    dt2 = datetime(2023, 1, 2, tzinfo=timezone.utc)\n    forecast_list = ExchangeCapacityList(logging.Logger(\"test\"))\n    forecast_list.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=dt2,\n        source=\"trust.me\",\n        capacityExport=1100.0,\n        capacityImport=950.0,\n    )\n    forecast_list.append(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=dt1,\n        source=\"trust.me\",\n        capacityExport=1000.0,\n        capacityImport=900.0,\n    )\n    result = forecast_list.to_list()\n    assert len(result) == 2\n    assert result[0][\"datetime\"] == dt1\n    assert result[1][\"datetime\"] == dt2\n    assert result[0][\"capacityExport\"] == 1000.0\n    assert result[0][\"capacityImport\"] == 900.0\n    assert result[0][\"sortedZoneKeys\"] == ZoneKey(\"AT->DE\")\n    assert result[0][\"source\"] == \"trust.me\"\n    assert result[0][\"sourceType\"] == EventSourceType.published\n"
  },
  {
    "path": "electricitymap/contrib/lib/tests/test_events.py",
    "content": "import logging\nimport math\nfrom datetime import datetime, timezone\nfrom unittest.mock import patch\nfrom zoneinfo import ZoneInfo\n\nimport freezegun\nimport numpy as np\nimport pytest\n\nfrom electricitymap.contrib.config.constants import PRODUCTION_MODES, STORAGE_MODES\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    Exchange,\n    ExchangeCapacity,\n    GridAlert,\n    GridAlertType,\n    LocationalMarginalPrice,\n    Price,\n    ProductionBreakdown,\n    ProductionMix,\n    StorageMix,\n    TotalConsumption,\n    TotalProduction,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_create_exchange():\n    exchange = Exchange(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    assert exchange.zoneKey == ZoneKey(\"AT->DE\")\n    assert exchange.datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert exchange.netFlow == 1\n    assert exchange.source == \"trust.me\"\n\n    exchange = Exchange(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=-1,\n        source=\"trust.me\",\n    )\n    assert exchange.netFlow == -1\n\n\ndef test_raises_if_invalid_exchange():\n    # This should raise a ValueError because the netFlow is None.\n    with pytest.raises(ValueError):\n        Exchange(\n            zoneKey=ZoneKey(\"AT->DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            netFlow=None,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the netFlow is NaN.\n    with pytest.raises(ValueError):\n        Exchange(\n            zoneKey=ZoneKey(\"AT->DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            netFlow=math.nan,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the netFlow is Nan using Numpy.\n    with pytest.raises(ValueError):\n        Exchange(\n            zoneKey=ZoneKey(\"AT->DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            netFlow=np.nan,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the timezone is missing.\n    with pytest.raises(ValueError):\n        Exchange(\n            zoneKey=ZoneKey(\"AT->DE\"),\n            datetime=datetime(2023, 1, 1),\n            netFlow=1,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the zoneKey is not an Exchange\n    with pytest.raises(ValueError):\n        Exchange(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            netFlow=1,\n            source=\"trust.me\",\n        )\n\n    with pytest.raises(ValueError):\n        Exchange(\n            zoneKey=ZoneKey(\"AT-DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            netFlow=1,\n            source=\"trust.me\",\n        )\n\n    with pytest.raises(ValueError):\n        Exchange(\n            zoneKey=ZoneKey(\"UNKNOWN->UNKNOWN\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            netFlow=1,\n            source=\"trust.me\",\n        )\n\n    with pytest.raises(ValueError):\n        Exchange(\n            zoneKey=ZoneKey(\"DE->AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            netFlow=1,\n            source=\"trust.me\",\n        )\n\n\ndef test_exchange_static_create_logs_error():\n    logger = logging.Logger(\"test\")\n    with patch.object(logger, \"error\") as mock_error:\n        Exchange.create(\n            logger=logger,\n            zoneKey=ZoneKey(\"DER->FR\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            netFlow=-1,\n            source=\"trust.me\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_update_exchange():\n    exchange = Exchange(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=1,\n        source=\"trust.me\",\n    )\n    new_exchange = Exchange(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        netFlow=2,\n        source=\"trust.me\",\n    )\n    final_exchange = Exchange._update(exchange, new_exchange)\n    assert final_exchange is not None\n    assert final_exchange.netFlow == 2\n    assert final_exchange.zoneKey == ZoneKey(\"AT->DE\")\n    assert final_exchange.datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert final_exchange.source == \"trust.me\"\n\n\ndef test_update_total_production():\n    production = TotalProduction(\n        zoneKey=ZoneKey(\"IT-SO\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        value=100,\n        source=\"entsoe\",\n    )\n    new_production = TotalProduction(\n        zoneKey=ZoneKey(\"IT-SO\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        value=150,\n        source=\"entsoe\",\n    )\n\n    updated = TotalProduction._update(production, new_production)\n\n    assert updated.value == 150\n    assert updated.zoneKey == ZoneKey(\"IT-SO\")\n    assert updated.sourceType == EventSourceType.measured\n\n\ndef test_update_total_consumption_raises_on_mismatched_zone():\n    consumption = TotalConsumption(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        consumption=100,\n        source=\"entsoe\",\n    )\n    new_consumption = TotalConsumption(\n        zoneKey=ZoneKey(\"AT\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        consumption=120,\n        source=\"entsoe\",\n    )\n\n    with pytest.raises(ValueError):\n        TotalConsumption._update(consumption, new_consumption)\n\n\ndef test_create_consumption():\n    consumption = TotalConsumption(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        consumption=1,\n        source=\"trust.me\",\n    )\n    assert consumption.zoneKey == ZoneKey(\"DE\")\n    assert consumption.datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert consumption.consumption == 1\n    assert consumption.source == \"trust.me\"\n\n\ndef test_raises_if_invalid_consumption():\n    # This should raise a ValueError because the consumption is None.\n    with pytest.raises(ValueError):\n        TotalConsumption(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            consumption=None,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the consumption is NaN.\n    with pytest.raises(ValueError):\n        TotalConsumption(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            consumption=math.nan,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the consumption is Nan using Numpy.\n    with pytest.raises(ValueError):\n        TotalConsumption(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            consumption=math.nan,\n            source=\"trust.me\",\n        )\n\n    with pytest.raises(ValueError):\n        TotalConsumption(\n            zoneKey=ZoneKey(\"ATT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            consumption=1,\n            source=\"trust.me\",\n        )\n    with pytest.raises(ValueError):\n        TotalConsumption(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1),\n            consumption=1,\n            source=\"trust.me\",\n        )\n    with pytest.raises(ValueError):\n        TotalConsumption(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            consumption=-1,\n            source=\"trust.me\",\n        )\n\n\ndef test_static_create_logs_error():\n    logger = logging.Logger(\"test\")\n    with patch.object(logger, \"error\") as mock_error:\n        TotalConsumption.create(\n            logger=logger,\n            zoneKey=ZoneKey(\"DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            consumption=-1,\n            source=\"trust.me\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_create_price():\n    price = Price(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        price=1,\n        source=\"trust.me\",\n        currency=\"EUR\",\n    )\n    assert price.zoneKey == ZoneKey(\"DE\")\n    assert price.datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert price.price == 1\n    assert price.source == \"trust.me\"\n    assert price.currency == \"EUR\"\n\n\ndef test_invalid_price_raises():\n    # This should raise a ValueError because the price is None.\n    with pytest.raises(ValueError):\n        Price(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            price=None,\n            source=\"trust.me\",\n            currency=\"EUR\",\n        )\n\n    # This should raise a ValueError because the price is NaN.\n    with pytest.raises(ValueError):\n        Price(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            price=math.nan,\n            source=\"trust.me\",\n            currency=\"EUR\",\n        )\n\n    # This should raise a ValueError because the price is Nan using Numpy.\n    with pytest.raises(ValueError):\n        Price(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            price=math.nan,\n            source=\"trust.me\",\n            currency=\"EUR\",\n        )\n\n    with pytest.raises(ValueError):\n        Price(\n            zoneKey=ZoneKey(\"ATT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            price=1,\n            source=\"trust.me\",\n            currency=\"EUR\",\n        )\n    with pytest.raises(ValueError):\n        Price(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1),\n            price=1,\n            source=\"trust.me\",\n            currency=\"EUR\",\n        )\n    with pytest.raises(ValueError):\n        Price(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            price=1,\n            source=\"trust.me\",\n            currency=\"EURO\",\n        )\n\n\n@freezegun.freeze_time(\"2023-01-01\")\ndef test_prices_can_be_in_future():\n    Price(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 2, tzinfo=timezone.utc),\n        price=1,\n        source=\"trust.me\",\n        currency=\"EUR\",\n    )\n\n\ndef test_create_locational_marginal_price():\n    lmp = LocationalMarginalPrice(\n        zoneKey=ZoneKey(\"US-CENT-SWPP\"),\n        datetime=datetime(2025, 3, 1, tzinfo=timezone.utc),\n        price=1,\n        source=\"trust.me\",\n        currency=\"USD\",\n        node=\"SPPNORTH_HUB\",\n    )\n    assert lmp.zoneKey == ZoneKey(\"US-CENT-SWPP\")\n    assert lmp.datetime == datetime(2025, 3, 1, tzinfo=timezone.utc)\n    assert lmp.price == 1\n    assert lmp.source == \"trust.me\"\n    assert lmp.currency == \"USD\"\n    assert lmp.node == \"SPPNORTH_HUB\"\n\n\n@pytest.mark.parametrize(\n    \"node\",\n    [\n        \"\",  # Empty string\n        None,  # None value\n        \" \",  # Space only\n        \"\\t\",  # Tab only\n        \"\\n\",  # Newline only\n        \"   \",  # Multiple spaces\n        \" \\t\\n \",  # Mixed whitespace\n        \"\\tSPPNORTH_HUB\",  # Leading whitespace\n        \"SPPNORTH_HUB\\t\",  # Trailing whitespace\n    ],\n)\ndef test_invalid_locational_marginal_price_node_raises(node):\n    # This should raise a ValueError because the node is a empty string.\n    with pytest.raises(ValueError):\n        LocationalMarginalPrice(\n            zoneKey=ZoneKey(\"US-CENT-SWPP\"),\n            datetime=datetime(2025, 3, 1, tzinfo=timezone.utc),\n            price=1,\n            source=\"trust.me\",\n            currency=\"USD\",\n            node=node,\n        )\n\n\ndef test_create_grid_alerts():\n    grid_alert = GridAlert.create(\n        logger=logging.Logger(\"test\"),\n        zoneKey=ZoneKey(\"US-MIDA-PJM\"),\n        locationRegion=\"Test Region\",\n        source=\"trust.me\",\n        alertType=GridAlertType.action,\n        message=\"This is a test message\",\n        issuedTime=datetime(2025, 3, 1, tzinfo=timezone.utc),\n        startTime=None,\n        endTime=None,\n    )\n    assert grid_alert is not None\n    assert grid_alert.zoneKey == ZoneKey(\"US-MIDA-PJM\")\n    assert grid_alert.locationRegion == \"Test Region\"\n    assert grid_alert.source == \"trust.me\"\n    assert grid_alert.alertType == GridAlertType.action\n    assert grid_alert.message == \"This is a test message\"\n    assert grid_alert.issuedTime == datetime(2025, 3, 1, tzinfo=timezone.utc)\n    assert grid_alert.startTime == grid_alert.issuedTime  # because of the default\n    assert grid_alert.endTime is None\n\n\ndef test_invalid_message_raises():\n    # This should raise a ValueError because empty message\n    with pytest.raises(ValueError):\n        GridAlert(\n            logger=logging.Logger(\"test\"),\n            zoneKey=ZoneKey(\"US-MIDA-PJM\"),\n            locationRegion=None,\n            source=\"trust.me\",\n            alertType=GridAlertType.action,\n            message=\"\",\n            issuedTime=datetime(2025, 3, 1, tzinfo=timezone.utc),\n            startTime=None,\n            endTime=None,\n        )\n\n\ndef test_create_production_breakdown():\n    mix = ProductionMix(wind=10)\n    breakdown = ProductionBreakdown(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=mix,\n        source=\"trust.me\",\n    )\n    assert breakdown.zoneKey == ZoneKey(\"DE\")\n    assert breakdown.datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert breakdown.production is not None\n    assert breakdown.production.wind == 10\n    assert breakdown.source == \"trust.me\"\n\n\ndef test_create_production_breakdown_with_storage():\n    mix = ProductionMix(\n        wind=10,\n        hydro=20,\n    )\n    storage = StorageMix(\n        hydro=10,\n    )\n    breakdown = ProductionBreakdown(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=mix,\n        storage=storage,\n        source=\"trust.me\",\n    )\n\n    assert breakdown.production is not None\n    assert breakdown.production.hydro == 20\n    assert breakdown.storage is not None\n    assert breakdown.storage.hydro == 10\n\n\ndef test_invalid_breakdown_raises():\n    mix = ProductionMix(\n        wind=10,\n        hydro=20,\n    )\n    storage = StorageMix(\n        hydro=10,\n    )\n    with pytest.raises(ValueError):\n        ProductionBreakdown(\n            zoneKey=ZoneKey(\"ATT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            production=mix,\n            source=\"trust.me\",\n        )\n    with pytest.raises(ValueError):\n        ProductionBreakdown(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1),\n            production=mix,\n            source=\"trust.me\",\n        )\n    with pytest.raises(ValueError):\n        ProductionBreakdown(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            production=ProductionMix(wind=None),\n            storage=storage,\n            source=\"trust.me\",\n        )\n\n\ndef test_negative_production_gets_corrected():\n    mix = ProductionMix(\n        wind=10,\n        hydro=-20,\n    )\n    logger = logging.Logger(\"test\")\n    with patch.object(logger, \"debug\") as mock_logger:\n        breakdown = ProductionBreakdown.create(\n            logger=logger,\n            zoneKey=ZoneKey(\"DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            production=mix,\n            source=\"trust.me\",\n        )\n        mock_logger.assert_called_once()\n        assert breakdown is not None\n        assert breakdown.production is not None\n        assert breakdown.production.hydro is None\n        assert breakdown.production.wind == 10\n\n        dict_form = breakdown.to_dict()\n        assert dict_form[\"production\"][\"wind\"] == 10\n        assert dict_form[\"production\"][\"hydro\"] is None\n\n\ndef test_self_report_negative_value():\n    mix = ProductionMix()\n    # We have manually set a 0 to avoid reporting self consumption for instance.\n    mix.add_value(\"wind\", 0)\n    # This one has been set through the attributes and should be reported as None.\n    mix.biomass = -10\n    logger = logging.Logger(\"test\")\n    with patch.object(logger, \"debug\") as mock_logger:\n        breakdown = ProductionBreakdown.create(\n            logger=logger,\n            zoneKey=ZoneKey(\"DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            production=mix,\n            source=\"trust.me\",\n        )\n        mock_logger.assert_called_once()\n        assert breakdown is not None\n        assert breakdown.production is not None\n        assert breakdown.production.wind == 0\n        assert breakdown.production.biomass is None\n\n\ndef test_unknown_production_mode_raises():\n    mix = ProductionMix()\n    with pytest.raises(AttributeError):\n        mix.add_value(\"nuke\", 10)\n    with pytest.raises(AttributeError):\n        mix.nuke = 10\n    storage = StorageMix()\n    with pytest.raises(AttributeError):\n        storage.add_value(\"nuke\", 10)\n    with pytest.raises(AttributeError):\n        storage.nuke = 10\n\n\n@freezegun.freeze_time(\"2023-01-01\")\ndef test_forecasted_points():\n    mix = ProductionMix(wind=10)\n    breakdown = ProductionBreakdown(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 2, 1, tzinfo=timezone.utc),\n        production=mix,\n        source=\"trust.me\",\n        sourceType=EventSourceType.forecasted,\n    )\n    assert breakdown.zoneKey == ZoneKey(\"DE\")\n    assert breakdown.datetime == datetime(2023, 2, 1, tzinfo=timezone.utc)\n    assert breakdown.production is not None\n    assert breakdown.production.wind == 10\n    assert breakdown.source == \"trust.me\"\n    assert breakdown.sourceType == EventSourceType.forecasted\n\n\n@freezegun.freeze_time(\"2023-01-01\")\ndef test_non_forecasted_points_in_future():\n    mix = ProductionMix(wind=10)\n    with pytest.raises(ValueError):\n        _breakdown = ProductionBreakdown(\n            zoneKey=ZoneKey(\"DE\"),\n            datetime=datetime(2023, 3, 1, tzinfo=timezone.utc),\n            production=mix,\n            source=\"trust.me\",\n        )\n\n\n@freezegun.freeze_time(\"2023-01-01\")\ndef test_non_forecasted_point_with_timezone_forward():\n    \"\"\"Test that points in a timezone that is ahead of UTC are accepted.\"\"\"\n    mix = ProductionMix(wind=10)\n    breakdown = ProductionBreakdown(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, 5, tzinfo=ZoneInfo(\"Asia/Tokyo\")),\n        production=mix,\n        source=\"trust.me\",\n    )\n    assert breakdown.datetime == datetime(2023, 1, 1, 5, tzinfo=ZoneInfo(\"Asia/Tokyo\"))\n\n\ndef test_static_create_logs_error_with_none():\n    logger = logging.Logger(\"test\")\n    with patch.object(logger, \"error\") as mock_error:\n        ProductionBreakdown.create(\n            logger=logger,\n            zoneKey=ZoneKey(\"DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            production=ProductionMix(wind=None),\n            source=\"trust.me\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_static_create_logs_with_nan():\n    logger = logging.Logger(\"test\")\n    with patch.object(logger, \"error\") as mock_error:\n        ProductionBreakdown.create(\n            logger=logger,\n            zoneKey=ZoneKey(\"DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            production=ProductionMix(wind=math.nan),\n            source=\"trust.me\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_static_create_logs_with_nan_using_numpy():\n    logger = logging.Logger(\"test\")\n    with patch.object(logger, \"error\") as mock_error:\n        ProductionBreakdown.create(\n            logger=logger,\n            zoneKey=ZoneKey(\"DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            production=ProductionMix(wind=np.nan),\n            source=\"trust.me\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_set_breakdown_all_present():\n    breakdown = ProductionBreakdown(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=ProductionMix(wind=10, solar=None),\n        source=\"trust.me\",\n    )\n    dict_form = breakdown.to_dict()\n    assert dict_form[\"production\"].keys() == {\"wind\", \"solar\"}\n    assert dict_form[\"production\"][\"wind\"] == 10\n    assert dict_form[\"production\"][\"solar\"] is None\n\n\ndef test_set_modes_all_present_add_mode():\n    mix = ProductionMix(wind=10)\n    mix.add_value(\"solar\", None)\n    breakdown = ProductionBreakdown(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        production=mix,\n        source=\"trust.me\",\n    )\n    dict_form = breakdown.to_dict()\n    assert dict_form[\"production\"].keys() == {\"wind\", \"solar\"}\n    assert dict_form[\"production\"][\"wind\"] == 10\n    assert dict_form[\"production\"][\"solar\"] is None\n\n\ndef test_create_generation():\n    generation = TotalProduction(\n        zoneKey=ZoneKey(\"DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        source=\"trust.me\",\n        value=1,\n    )\n    assert generation.zoneKey == ZoneKey(\"DE\")\n    assert generation.datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert generation.source == \"trust.me\"\n    assert generation.value == 1\n\n\ndef test_total_production_static_create_logs_error():\n    logger = logging.Logger(\"test\")\n    with patch.object(logger, \"error\") as mock_error:\n        TotalProduction.create(\n            logger=logger,\n            zoneKey=ZoneKey(\"DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            value=-1,\n            source=\"trust.me\",\n        )\n        mock_error.assert_called_once()\n\n\ndef test_raises_if_invalid_generation():\n    # This should raise a ValueError because the generation is None.\n    with pytest.raises(ValueError):\n        TotalProduction(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            value=None,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the generation is NaN.\n    with pytest.raises(ValueError):\n        TotalProduction(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            value=math.nan,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the generation is Nan using Numpy.\n    with pytest.raises(ValueError):\n        TotalProduction(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            value=np.nan,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the timezone is missing.\n    with pytest.raises(ValueError):\n        TotalProduction(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1),\n            value=1,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the zoneKey is not a ZoneKey.\n    with pytest.raises(ValueError):\n        TotalProduction(\n            zoneKey=ZoneKey(\"ATT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            value=1,\n            source=\"trust.me\",\n        )\n\n    # This should raise a ValueError because the value is negative.\n    with pytest.raises(ValueError):\n        TotalProduction(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            value=-1,\n            source=\"trust.me\",\n        )\n\n\ndef test_production_mix_has_all_production_modes():\n    mix = ProductionMix()\n    for mode in PRODUCTION_MODES:\n        assert hasattr(mix, mode)\n\n\ndef test_storage_mix_has_all_storage_modes():\n    mix = StorageMix()\n    for mode in STORAGE_MODES:\n        assert hasattr(mix, mode)\n\n\ndef test_set_attr():\n    mix = ProductionMix()\n    mix.wind = 10\n    assert mix.wind == 10\n\n\ndef test_set_attr_with_negative_value():\n    mix = ProductionMix()\n    mix.wind = -10\n    assert mix.wind is None\n\n\ndef test_set_attr_with_none():\n    mix = ProductionMix()\n    mix.wind = None\n    assert mix.wind is None\n\n\ndef test_set_attr_with_invalid_mode():\n    mix = ProductionMix()\n    with pytest.raises(AttributeError):\n        mix.nuke = 10\n\n\ndef test_set_item():\n    mix = ProductionMix()\n    mix[\"wind\"] = 10\n    assert mix.wind == 10\n\n\ndef test_set_item_with_negative_value():\n    mix = ProductionMix()\n    mix[\"wind\"] = -10\n    assert mix.wind is None\n\n\ndef test_set_item_with_none():\n    mix = ProductionMix()\n    mix[\"wind\"] = None\n    assert mix.wind is None\n\n\ndef test_set_item_with_invalid_mode():\n    mix = ProductionMix()\n    with pytest.raises(AttributeError):\n        mix[\"nuke\"] = 10\n\n\ndef test_set_attr_storage():\n    mix = StorageMix()\n    mix.hydro = 10\n    assert mix.hydro == 10\n\n\ndef test_set_attr_storage_with_negative_value():\n    mix = StorageMix()\n    mix.hydro = -10\n    assert mix.hydro == -10\n\n\ndef test_set_attr_storage_with_none():\n    mix = StorageMix()\n    mix.hydro = None\n    assert mix.hydro is None\n\n\ndef test_set_attr_storage_with_invalid_mode():\n    mix = StorageMix()\n    with pytest.raises(AttributeError):\n        mix.nuke = 10\n\n\ndef test_set_item_storage():\n    mix = StorageMix()\n    mix[\"hydro\"] = 10\n    assert mix.hydro == 10\n\n\ndef test_set_item_storage_with_negative_value():\n    mix = StorageMix()\n    mix[\"hydro\"] = -10\n    assert mix.hydro == -10\n\n\ndef test_set_item_storage_with_none():\n    mix = StorageMix()\n    mix[\"hydro\"] = None\n    assert mix.hydro is None\n\n\ndef test_set_item_storage_with_invalid_mode():\n    mix = StorageMix()\n    with pytest.raises(AttributeError):\n        mix[\"nuke\"] = 10\n\n\ndef test_production():\n    mix = ProductionMix()\n    mix.add_value(\"wind\", 10)\n    assert mix.wind == 10\n    mix.add_value(\"wind\", 5)\n    assert mix.wind == 15\n    assert mix.corrected_negative_modes == set()\n\n\ndef test_production_with_negative_value():\n    mix = ProductionMix()\n    mix.add_value(\"wind\", 10)\n    assert mix.wind == 10\n    mix.add_value(\"wind\", -5)\n    assert mix.wind == 10\n    assert mix.corrected_negative_modes == {\"wind\"}\n\n\ndef test_production_with_negative_value_expect_none():\n    mix = ProductionMix()\n    mix.add_value(\"wind\", -10)\n    assert mix.wind is None\n    assert mix.corrected_negative_modes == {\"wind\"}\n\n\ndef test_production_with_negative_value_and_correct_with_none():\n    mix = ProductionMix()\n    mix.add_value(\"wind\", -10, correct_negative_with_zero=True)\n    assert mix.wind == 0\n    mix.add_value(\"wind\", 15, correct_negative_with_zero=True)\n    assert mix.wind == 15\n    assert mix.corrected_negative_modes == {\"wind\"}\n\n\ndef test_production_with_none():\n    mix = ProductionMix()\n    mix.add_value(\"wind\", 10)\n    assert mix.wind == 10\n    mix.add_value(\"wind\", None)\n    assert mix.wind == 10\n    assert mix.corrected_negative_modes == set()\n\n\ndef test_production_with_nan():\n    mix = ProductionMix()\n    mix.add_value(\"wind\", 10)\n    assert mix.wind == 10\n    mix.add_value(\"wind\", math.nan)\n    assert mix.wind == 10\n    assert mix.corrected_negative_modes == set()\n\n\ndef test_production_with_nan_using_numpy():\n    mix = ProductionMix()\n    mix.add_value(\"wind\", 10)\n    assert mix.wind == 10\n    mix.add_value(\"wind\", math.nan)\n    assert mix.wind == 10\n    assert mix.corrected_negative_modes == set()\n\n\ndef test_production_with_nan_init():\n    mix = ProductionMix(wind=math.nan)\n    assert mix.wind is None\n\n\ndef test_production_with_nan_using_numpy_init():\n    mix = ProductionMix(wind=math.nan)\n    assert mix.wind is None\n\n\ndef test_storage():\n    mix = StorageMix()\n    mix.add_value(\"hydro\", 10)\n    assert mix.hydro == 10\n    mix.add_value(\"hydro\", 5)\n    assert mix.hydro == 15\n\n\ndef test_storage_with_negative_value():\n    mix = StorageMix()\n    mix.add_value(\"hydro\", 10)\n    assert mix.hydro == 10\n    mix.add_value(\"hydro\", -5)\n    assert mix.hydro == 5\n\n\ndef test_storage_with_none():\n    mix = StorageMix()\n    mix.add_value(\"hydro\", None)\n    assert mix.hydro is None\n    mix.add_value(\"hydro\", -5)\n    assert mix.hydro == -5\n    mix.add_value(\"hydro\", None)\n    assert mix.hydro == -5\n\n\ndef test_storage_with_nan():\n    mix = StorageMix()\n    mix.add_value(\"hydro\", math.nan)\n    assert mix.hydro is None\n    mix.add_value(\"hydro\", -5)\n    assert mix.hydro == -5\n    mix.add_value(\"hydro\", math.nan)\n    assert mix.hydro == -5\n\n\ndef test_storage_with_nan_using_numpy():\n    mix = StorageMix()\n    mix.add_value(\"hydro\", math.nan)\n    assert mix.hydro is None\n    mix.add_value(\"hydro\", -5)\n    assert mix.hydro == -5\n    mix.add_value(\"hydro\", math.nan)\n    assert mix.hydro == -5\n\n\ndef test_storage_with_nan_init():\n    mix = StorageMix(hydro=math.nan)\n    assert mix.hydro is None\n\n\ndef test_storage_with_nan_using_numpy_init():\n    mix = StorageMix(hydro=math.nan)\n    assert mix.hydro is None\n\n\ndef test_update_production():\n    mix = ProductionMix(wind=10, solar=20)\n    new_mix = ProductionMix(wind=5, solar=25)\n    final_mix = ProductionMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.wind == 5\n    assert final_mix.solar == 25\n\n\ndef test_update_storage():\n    mix = StorageMix(hydro=10, battery=20)\n    new_mix = StorageMix(hydro=5, battery=25)\n    final_mix = StorageMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.hydro == 5\n    assert final_mix.battery == 25\n\n\ndef test_update_production_with_none():\n    mix = ProductionMix(wind=10, solar=20)\n    new_mix = ProductionMix(wind=None, solar=25)\n    final_mix = ProductionMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.wind == 10\n    assert final_mix.solar == 25\n\n\ndef test_update_storage_with_none():\n    mix = StorageMix(hydro=10, battery=20)\n    new_mix = StorageMix(hydro=None, battery=25)\n    final_mix = StorageMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.hydro == 10\n    assert final_mix.battery == 25\n\n\ndef test_update_production_with_empty():\n    mix = ProductionMix()\n    new_mix = ProductionMix(wind=0, solar=25)\n    final_mix = ProductionMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.wind == 0\n    assert final_mix.solar == 25\n\n\ndef test_update_storage_with_empty():\n    mix = StorageMix()\n    new_mix = StorageMix(hydro=0, battery=25)\n    final_mix = StorageMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.hydro == 0\n    assert final_mix.battery == 25\n\n\ndef test_update_production_with_new_empty():\n    mix = ProductionMix(wind=10, solar=20)\n    new_mix = ProductionMix()\n    final_mix = ProductionMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.wind == 10\n    assert final_mix.solar == 20\n\n\ndef test_update_storage_with_new_empty():\n    mix = StorageMix(hydro=10, battery=20)\n    new_mix = StorageMix()\n    final_mix = StorageMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.hydro == 10\n    assert final_mix.battery == 20\n\n\ndef test_update_production_with_empty_and_new_none():\n    mix = ProductionMix()\n    new_mix = ProductionMix(wind=None, solar=None)\n    final_mix = ProductionMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.wind is None\n    assert final_mix.solar is None\n\n\ndef test_update_storage_with_empty_and_new_none():\n    mix = StorageMix()\n    new_mix = StorageMix(hydro=None, battery=None)\n    final_mix = StorageMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.hydro is None\n    assert final_mix.battery is None\n\n\ndef test_update_production_with_empty_and_new_empty():\n    mix = ProductionMix()\n    new_mix = ProductionMix()\n    final_mix = ProductionMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.wind is None\n    assert final_mix.solar is None\n\n\ndef test_update_storage_with_empty_and_new_empty():\n    mix = StorageMix()\n    new_mix = StorageMix()\n    final_mix = StorageMix._update(mix, new_mix)\n    assert final_mix is not None\n    assert final_mix.hydro is None\n    assert final_mix.battery is None\n\n\ndef test_create_exchange_capacity_forecast():\n    forecast = ExchangeCapacity(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        source=\"trust.me\",\n        capacityExport=1000.0,\n        capacityImport=900.0,\n    )\n    assert forecast.zoneKey == ZoneKey(\"AT->DE\")\n    assert forecast.datetime == datetime(2023, 1, 1, tzinfo=timezone.utc)\n    assert forecast.source == \"trust.me\"\n    assert forecast.capacityExport == 1000.0\n    assert forecast.capacityImport == 900.0\n    assert forecast.sourceType == EventSourceType.published\n\n\ndef test_exchange_capacity_forecast_create_defaults_to_published():\n    logger = logging.Logger(\"test\")\n    forecast = ExchangeCapacity.create(\n        logger=logger,\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        source=\"trust.me\",\n        capacityExport=1000.0,\n        capacityImport=900.0,\n    )\n    assert forecast is not None\n    assert forecast.sourceType == EventSourceType.published\n\n\ndef test_exchange_capacity_forecast_allows_one_none_capacity():\n    # One direction may be None as long as the other is set\n    forward_only = ExchangeCapacity(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        source=\"trust.me\",\n        capacityExport=1000.0,\n        capacityImport=None,\n    )\n    assert forward_only.capacityExport == 1000.0\n    assert forward_only.capacityImport is None\n\n    reverse_only = ExchangeCapacity(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n        source=\"trust.me\",\n        capacityExport=None,\n        capacityImport=900.0,\n    )\n    assert reverse_only.capacityExport is None\n    assert reverse_only.capacityImport == 900.0\n\n\ndef test_raises_if_invalid_exchange_capacity_forecast():\n    # Missing timezone\n    with pytest.raises(ValueError):\n        ExchangeCapacity(\n            zoneKey=ZoneKey(\"AT->DE\"),\n            datetime=datetime(2023, 1, 1),\n            source=\"trust.me\",\n            capacityExport=1000.0,\n            capacityImport=900.0,\n        )\n\n    # Unsorted zone key\n    with pytest.raises(ValueError):\n        ExchangeCapacity(\n            zoneKey=ZoneKey(\"DE->AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            source=\"trust.me\",\n            capacityExport=1000.0,\n            capacityImport=900.0,\n        )\n\n    # Not an exchange key (no \"->\")\n    with pytest.raises(ValueError):\n        ExchangeCapacity(\n            zoneKey=ZoneKey(\"AT\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            source=\"trust.me\",\n            capacityExport=1000.0,\n            capacityImport=900.0,\n        )\n\n    # Both capacities None\n    with pytest.raises(ValueError):\n        ExchangeCapacity(\n            zoneKey=ZoneKey(\"AT->DE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            source=\"trust.me\",\n            capacityExport=None,\n            capacityImport=None,\n        )\n\n    # Unknown zone key not in EXCHANGES_CONFIG\n    with pytest.raises(ValueError):\n        ExchangeCapacity(\n            zoneKey=ZoneKey(\"UNKNOWN->ZONE\"),\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            source=\"trust.me\",\n            capacityExport=1000.0,\n            capacityImport=900.0,\n        )\n\n\ndef test_exchange_capacity_forecast_static_create_logs_error():\n    logger = logging.Logger(\"test\")\n    with patch.object(logger, \"error\") as mock_error:\n        ExchangeCapacity.create(\n            logger=logger,\n            zoneKey=ZoneKey(\"DE->AT\"),  # unsorted\n            datetime=datetime(2023, 1, 1, tzinfo=timezone.utc),\n            source=\"trust.me\",\n            capacityExport=1000.0,\n            capacityImport=900.0,\n        )\n        mock_error.assert_called_once()\n\n\n@freezegun.freeze_time(\"2023-01-01\")\ndef test_exchange_capacity_forecast_allows_future_datetime():\n    # Forecasted events can be in the future\n    forecast = ExchangeCapacity(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=datetime(2023, 3, 1, tzinfo=timezone.utc),\n        source=\"trust.me\",\n        capacityExport=1000.0,\n        capacityImport=900.0,\n        sourceType=EventSourceType.forecasted,\n    )\n    assert forecast.datetime == datetime(2023, 3, 1, tzinfo=timezone.utc)\n\n\ndef test_exchange_capacity_forecast_to_dict():\n    dt = datetime(2023, 1, 1, tzinfo=timezone.utc)\n    forecast = ExchangeCapacity(\n        zoneKey=ZoneKey(\"AT->DE\"),\n        datetime=dt,\n        source=\"trust.me\",\n        capacityExport=1000.0,\n        capacityImport=900.0,\n    )\n    d = forecast.to_dict()\n    assert d[\"datetime\"] == dt\n    assert d[\"sortedZoneKeys\"] == ZoneKey(\"AT->DE\")\n    assert d[\"capacityExport\"] == 1000.0\n    assert d[\"capacityImport\"] == 900.0\n    assert d[\"source\"] == \"trust.me\"\n    assert d[\"sourceType\"] == EventSourceType.published\n"
  },
  {
    "path": "electricitymap/contrib/lib/types.py",
    "content": "# DEPRECATED: Import from electricitymap.contrib.types instead.\n# This re-export is kept for backward compatibility.\nfrom electricitymap.contrib.types import ZoneKey\n\n__all__ = [\"ZoneKey\"]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/AEMO.py",
    "content": "import io\nimport re\nimport zipfile\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom urllib.parse import urljoin\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import TotalConsumptionList\nfrom electricitymap.contrib.lib.models.events import EventSourceType\nfrom electricitymap.contrib.types import ZoneKey\n\nSOURCE = \"aemo.com.au\"\n\nZONE_KEY_TO_REGION = {\n    \"AU-NSW\": \"NSW1\",\n    \"AU-QLD\": \"QLD1\",\n    \"AU-SA\": \"SA1\",\n    \"AU-TAS\": \"TAS1\",\n    \"AU-VIC\": \"VIC1\",\n    \"AU-WA\": \"WEM\",  # This zone is not implemented yet\n}\n\nZONE_KEY_TO_TIMEZONE = {\n    \"AU-NSW\": ZoneInfo(\"Australia/Sydney\"),\n    \"AU-QLD\": ZoneInfo(\"Australia/Brisbane\"),\n    \"AU-SA\": ZoneInfo(\"Australia/Adelaide\"),\n    \"AU-TAS\": ZoneInfo(\"Australia/Hobart\"),\n    \"AU-VIC\": ZoneInfo(\"Australia/Melbourne\"),\n    \"AU-WA\": ZoneInfo(\"Australia/Perth\"),  # This zone is not implemented yet\n}\n\n# TODO, what about the other zone in Australia (AU-WA)? Check remaining zone\n\n\ndef find_document(session, target_datetime):\n    # Fetch the directory listing\n    base_url = \"http://nemweb.com.au/Reports/CURRENT/Operational_Demand/FORECAST_HH/\"\n    response = session.get(base_url)\n\n    # Parse with BeautifulSoup\n    soup = BeautifulSoup(response.text, \"html.parser\")\n\n    # String datetime\n    target_date_str = target_datetime.strftime(\"%Y%m%d\")\n\n    # Find matching links\n    matching_links = soup.find_all(\n        \"a\",\n        href=re.compile(\n            rf\"PUBLIC_FORECAST_OPERATIONAL_DEMAND_HH_{target_date_str}\\d+_\\d+\\.zip\"\n        ),\n    )\n\n    if matching_links:\n        target_link = matching_links[-1]  # Get the last (most recent) link\n        full_url = urljoin(base_url, target_link[\"href\"])  # Construct full URL\n\n        file_response = session.get(full_url)\n\n        with zipfile.ZipFile(io.BytesIO(file_response.content)) as z:\n            csv_filename = z.namelist()[0]\n            with z.open(csv_filename) as f:\n                df = pd.read_csv(f)\n                return df\n    else:\n        print(\"No matching files found\")\n\n\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey,  # \"AU-NSW\", \"AU-QLD\", \"AU-SA\", \"AU-TAS\", \"AU-VIC\", \"AU-WA\"\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Consumption forecast in MW every half an hour for 10 days ahead.\n    Only for NSW1, QND1, SA1, TAS1, VIC1 zones.\"\"\"\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=ZONE_KEY_TO_TIMEZONE[zone_key])\n\n    df = find_document(session, target_datetime)\n\n    # Transform dataframe\n    df.columns = df.iloc[0]\n    df = df.iloc[1:-1].reset_index(drop=True)\n\n    #\n    region = ZONE_KEY_TO_REGION.get(zone_key)\n    all_consumption_events = df[\n        df[\"REGIONID\"] == region\n    ]  # all events with a datetime and a consumption value\n    consumption_list = TotalConsumptionList(logger)\n    for _, event in all_consumption_events.iterrows():\n        datetime_object = datetime.strptime(\n            event[\"INTERVAL_DATETIME\"], \"%Y/%m/%d %H:%M:%S\"\n        ).replace(tzinfo=ZONE_KEY_TO_TIMEZONE[zone_key])\n\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=datetime_object,\n            consumption=float(\n                event[\"OPERATIONAL_DEMAND_POE50\"]\n            ),  # 50% probability of exceedance operational demand forecast value\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumption_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the electricityMap backend, but handy for testing.\"\"\"\n\n    print(fetch_consumption_forecast(\"AU-NSW\"))\n    print(fetch_consumption_forecast(\"AU-QLD\"))\n    print(fetch_consumption_forecast(\"AU-SA\"))\n    print(fetch_consumption_forecast(\"AU-TAS\"))\n    print(fetch_consumption_forecast(\"AU-VIC\"))\n    print(\n        fetch_consumption_forecast(\"AU-WA\")\n    )  # Not implemented yet. It returns an empty list\n"
  },
  {
    "path": "electricitymap/contrib/parsers/AW.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.types import ZoneKey\n\nfrom .lib.exceptions import ParserException\n\nFUEL_MAPPING = {\n    \"Fossil\": \"oil\",\n    \"Wind\": \"wind\",\n    \"TotalSolar\": \"solar\",\n    \"total_bio_gas\": \"biomass\",\n}\nTIMEZONE = ZoneInfo(\"America/Aruba\")\nPRODUCTION_URL = (\n    \"https://www.webaruba.com/renewable-energy-dashboard/app/rest/results.json\"\n)\nSOURCE = \"webaruba.com\"\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"AW\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    r = session or Session()\n    # User agent is mandatory or services answers 404\n    headers = {\n        \"user-agent\": \"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko)\"\n    }\n    response = r.get(PRODUCTION_URL, headers=headers)\n    aruba_json = response.json()\n    top_data = aruba_json[\"dashboard_top_data\"]\n    mix = ProductionMix()\n    sources_total = 0\n    for fuel, mode in FUEL_MAPPING.items():\n        value = float(top_data[fuel][\"value\"])\n        mix.add_value(mode, value)\n        sources_total += value\n    # \"unknown\" is when data reported in the categories above is less than total reported.\n    # If categories sum up to more than total, accept the datapoint, but only if it's less than 10% of total.\n    # This helps avoid missing data when it's a little bit off, due to rounding or reporting\n    reported_total = float(top_data[\"TotalPower\"][\"value\"])\n\n    if (sources_total / reported_total) > 1.1:\n        raise ParserException(\n            \"AW.py\",\n            f\"AW parser reports fuel sources add up to {sources_total} but total generation {reported_total} is lower\",\n            zone_key,\n        )\n\n    mix.add_value(\n        \"unknown\", reported_total - sources_total, correct_negative_with_zero=True\n    )\n    # We're using Fossil data to get timestamp in correct time zone\n    local_date_time = datetime.strptime(\n        top_data[\"total_bio_gas\"][\"timestamp\"], \"%Y-%m-%d %H:%M:%S.%f\"\n    ).replace(tzinfo=TIMEZONE)\n\n    production_list = ProductionBreakdownList(logger)\n    production_list.append(\n        zone_key,\n        local_date_time,\n        SOURCE,\n        production=mix,\n    )\n\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/AX.py",
    "content": "from datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom re import findall\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.types import ZoneKey\n\nfrom .lib.exceptions import ParserException\n\nIFRAME_URL = \"https://grafik.kraftnat.ax/grafer/tot_inm_24h_15.php\"\nTIME_ZONE = ZoneInfo(\"Europe/Mariehamn\")\nSOURCE = \"kraftnat.ax\"\n\n\ndef fetch_data(session: Session, logger: Logger):\n    \"\"\"Fetch data from the iFrame.\"\"\"\n\n    response: Response = session.get(IFRAME_URL)\n    response.raise_for_status()\n\n    soup = BeautifulSoup(response.text, \"html.parser\").find_all(\"script\")\n    result_time_series = findall(r\"data: \\[(.*?)\\]\", str(soup))\n    if len(result_time_series) != 3:\n        raise ParserException(\n            \"AX.py\",\n            \"Did not find the expected amount of results. Check if the website has changed.\",\n        )\n    time_series: list = result_time_series[0].split(\",\")\n    raw_data: list[str] = findall(r\"data:\\[(.*?)\\]\", str(soup))\n    if len(raw_data) != 6:\n        raise ParserException(\n            \"AX.py\",\n            \"The raw data did not match the expected format. Check if the website has changed.\",\n        )\n    for raw in raw_data:\n        if len(raw.split(\",\")) != len(time_series):\n            raise ParserException(\n                \"AX.py\",\n                \"The raw data did not match the length of the the time series. Check if the website has changed.\",\n            )\n    data_list = []\n    for time, sweden, alink, fossil, gustavs, wind, consumption in zip(\n        time_series,\n        raw_data[0].split(\",\"),\n        raw_data[1].split(\",\"),\n        raw_data[2].split(\",\"),\n        raw_data[3].split(\",\"),\n        raw_data[4].split(\",\"),\n        raw_data[5].split(\",\"),\n        strict=True,\n    ):\n        data_list.append(\n            {\n                \"time\": str(time.replace('\"', \"\")),\n                \"sweden\": float(sweden),\n                \"alink\": float(alink),\n                \"fossil\": float(fossil),\n                \"gustavs\": float(gustavs),\n                \"wind\": float(wind),\n                \"consumption\": float(consumption),\n            }\n        )\n    return data_list\n\n\ndef formatted_data(\n    zone_key: ZoneKey | None,\n    zone_key1: ZoneKey | None,\n    zone_key2: ZoneKey | None,\n    session: Session,\n    logger: Logger,\n    data_type: str,\n):\n    \"\"\"Format data to Electricity Map standards.\"\"\"\n    data_list = fetch_data(session, logger)\n    data_list.reverse()\n    date_time = datetime.now(TIME_ZONE)\n    date = date_time.replace(\n        hour=int(data_list[0][\"time\"].split(\":\")[0]),\n        minute=int(data_list[0][\"time\"].split(\":\")[1]),\n        second=0,\n        microsecond=0,\n    )\n    if date > date_time:\n        date = date - timedelta(days=1)\n    exchanges = ExchangeList(logger)\n    production_breakdowns = ProductionBreakdownList(logger)\n    consumption = TotalConsumptionList(logger)\n    for data in data_list:\n        corrected_date = date - timedelta(minutes=15 * data_list.index(data))\n        if data_type == \"production\" and zone_key is not None:\n            production_mix = ProductionMix(wind=data[\"wind\"], oil=data[\"fossil\"])\n            production_breakdowns.append(\n                datetime=corrected_date,\n                production=production_mix,\n                source=SOURCE,\n                zoneKey=zone_key,\n            )\n        elif data_type == \"consumption\" and zone_key is not None:\n            consumption.append(\n                datetime=corrected_date,\n                consumption=data[\"consumption\"],\n                source=SOURCE,\n                zoneKey=zone_key,\n            )\n        elif data_type == \"exchange\":\n            if zone_key1 == ZoneKey(\"AX\") and zone_key2 == ZoneKey(\"SE-SE3\"):\n                exchanges.append(\n                    datetime=corrected_date,\n                    netFlow=data[\"sweden\"] * -1,\n                    source=SOURCE,\n                    zoneKey=ZoneKey(\"AX->SE-SE3\"),\n                )\n            elif zone_key1 == ZoneKey(\"AX\") and zone_key2 == ZoneKey(\"FI\"):\n                exchanges.append(\n                    datetime=corrected_date,\n                    netFlow=round(data[\"alink\"] + data[\"gustavs\"], 2) * -1,\n                    source=SOURCE,\n                    zoneKey=ZoneKey(\"AX->FI\"),\n                )\n            else:\n                raise ParserException(\n                    \"AX.py\",\n                    \"This parser can only fetch data between Åland <-> Sweden and Åland <-> Finland\",\n                )\n        else:\n            raise ParserException(\n                \"AX.py\",\n                \"The datasource currently implemented is only for production, consumption and exchange data\",\n                zone_key,\n            )\n\n    if data_type == \"production\":\n        return production_breakdowns.to_list()\n    elif data_type == \"consumption\":\n        return consumption.to_list()\n    elif data_type == \"exchange\":\n        return exchanges.to_list()\n    else:\n        raise ParserException(\n            \"AX.py\",\n            \"The datasource currently implemented is only for production, consumption and exchange data\",\n            zone_key,\n        )\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"AX\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Fetch production data.\"\"\"\n\n    if target_datetime is not None:\n        raise ParserException(\n            \"AX.py\", \"The datasource currently implemented is only for real time data\"\n        )\n\n    return formatted_data(\n        zone_key=zone_key,\n        zone_key1=None,\n        zone_key2=None,\n        session=session,\n        logger=logger,\n        data_type=\"production\",\n    )\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"AX\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Fetch consumption data.\"\"\"\n\n    if target_datetime is not None:\n        raise ParserException(\n            \"AX.py\", \"The datasource currently implemented is only for real time data\"\n        )\n\n    return formatted_data(\n        zone_key=zone_key,\n        zone_key1=None,\n        zone_key2=None,\n        session=session,\n        logger=logger,\n        data_type=\"consumption\",\n    )\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Fetch exchange data.\"\"\"\n\n    if target_datetime is not None:\n        raise ParserException(\n            \"AX.py\", \"The datasource currently implemented is only for real time data\"\n        )\n\n    return formatted_data(\n        zone_key=None,\n        zone_key1=zone_key1,\n        zone_key2=zone_key2,\n        session=session,\n        logger=logger,\n        data_type=\"exchange\",\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/BB.py",
    "content": "from datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\n\n# The request library is used to fetch content through HTTP\nimport requests\nfrom requests import Session\nfrom requests.auth import AuthBase\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nSOURCE = \"energy.gov.bb\"\nbase_url = \"https://dataservices.acelerex.com/api\"\n\n\nclass JwtPublicAuth(AuthBase):\n    def __init__(self):\n        self.token = None\n\n    def __call__(self, r):\n        if self.token is None:\n            self.token = self.get_token()\n        r.headers[\"Authorization\"] = f\"Bearer {self.token}\"\n        return r\n\n    def get_token(self) -> str:\n        url = base_url + \"/authentication\"\n        response = requests.post(\n            url, json={\"dashboardId\": \"barbados\", \"strategy\": \"jwt-public\"}\n        )\n        return response.json()[\"accessToken\"]\n\n\ndef session_with_auth(session: Session) -> Session:\n    if session.auth is None:\n        session.auth = JwtPublicAuth()\n    return session\n\n\ndef parse_operational_data(response_json) -> tuple[list[str], list[list[str]]]:\n    header, *table = (x for x in response_json[\"data\"][0][\"data\"][\"data\"] if len(x) > 1)\n    return header, table\n\n\ndef fetch_operational_data(\n    zone_key,\n    session: Session,\n    target_datetime: datetime | None,\n    logger: Logger,\n) -> pd.DataFrame:\n    session = session_with_auth(session)\n\n    params = {\"name\": \"operational-data\", \"$sort[created_at]\": -1}\n\n    header = None\n    table = None\n\n    if target_datetime is None:\n        data = session.get(base_url + \"/barbados/uploads\", params=params).json()\n        header, table = parse_operational_data(data)\n    elif target_datetime > datetime(year=2023, month=2, day=27):\n        expected_date = target_datetime.astimezone(\n            ZoneInfo(\"America/Barbados\")\n        ).strftime(\"%Y-%m-%d\")\n\n        for i in range(10):\n            url_date = (\n                (target_datetime + timedelta(days=i))\n                .astimezone(ZoneInfo(\"America/Barbados\"))\n                .strftime(\"%Y-%m-%d\")\n            )\n            params[\"created_at[$lt]\"] = url_date\n            data = session.get(base_url + \"/barbados/uploads\", params=params).json()\n            header, table = parse_operational_data(data)\n            if table[0][0][:10] == expected_date:\n                break\n            if table[0][0][:10] > expected_date:\n                raise ParserException(\"BB.py\", \"Date not found\", zone_key)\n    else:\n        raise ParserException(\n            \"BB.py\",\n            \"This parser is not yet able to parse dates before 2023-02-27\",\n            zone_key,\n        )\n\n    if table is None or header is None:\n        raise ParserException(\"BB.py\", \"No data found\", zone_key)\n\n    operational_data = pd.DataFrame(\n        table,\n        columns=header,\n    )\n    columns = [\n        \"24 hr monitored solar production\",\n        \"24 hr monitored wind production\",\n        \"24 hr storage charging\",\n        \"24 hr storage discharging\",\n        \"24 hr fossil production\",\n        \"24 hr Net demand\",\n        \"24 hr Curtailment\",\n    ]\n    for columm in columns:\n        operational_data[columm] = pd.to_numeric(operational_data[columm])\n    return operational_data\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"BB\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict] | dict:\n    operational_data = fetch_operational_data(\n        zone_key, session, target_datetime, logger\n    )\n\n    production_list = ProductionBreakdownList(logger=logger)\n\n    for _index, row in operational_data.iterrows():\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(row[\"datetime\"]),\n            production=ProductionMix(\n                solar=row[\"24 hr monitored solar production\"],\n                wind=row[\"24 hr monitored wind production\"],\n                oil=row[\"24 hr fossil production\"],\n            ),\n            storage=StorageMix(\n                battery=(\n                    row[\"24 hr storage discharging\"] + row[\"24 hr storage charging\"]\n                )\n                * -1\n            ),\n            source=SOURCE,\n        )\n    return production_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict[str, Any] | list[dict[str, Any]]:\n    operational_data = fetch_operational_data(\n        zone_key, session, target_datetime, logger\n    )\n\n    consumption_list = TotalConsumptionList(logger=logger)\n\n    for _index, row in operational_data.iterrows():\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(row[\"datetime\"]),\n            consumption=row[\"24 hr Net demand\"],\n            source=SOURCE,\n        )\n    return consumption_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Maps backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production(XX) ->\")\n    print(fetch_production(ZoneKey(\"BB\")))\n    fetch_production(ZoneKey(\"BB\"), target_datetime=datetime(2024, 2, 2))\n    print(\"fetch_consumption(XX) ->\")\n    print(fetch_consumption(ZoneKey(\"BB\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/BE.py",
    "content": "import json\nfrom datetime import datetime, timedelta, timezone\nfrom itertools import groupby\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.parsers import ENTSOE\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\n# API is limited to 100 items per query\n# 2 hours * 4 (15 min intervals) * 12 (number of modes) = 96 items\nTWO_HR_LIMIT = 2 * 4 * 12\n\nELIA_WINDOW_HOURS = (\n    2  # Elia API max window per call (96 items = 2h * 4 intervals * 12 modes)\n)\n\nELIA_API_ENDPOINT = \"https://opendata.elia.be/api/explore/v2.1\"\nDATASET_ID_ELIA = \"ods201\"\nBASE_URL_ELIA = f\"{ELIA_API_ENDPOINT}/catalog/datasets/{DATASET_ID_ELIA}/records?order_by=datetime desc&limit={TWO_HR_LIMIT}\"\n\nSOURCE_ELIA = \"opendata.elia.be\"\nTIMEZONE = ZoneInfo(\"Europe/Brussels\")\n\nFUEL_TYPE_MAPPING_ELIA = {\n    \"Fossil Gas\": \"gas\",\n    \"Solar\": \"solar\",\n    \"Waste\": \"biomass\",\n    \"Wind Onshore\": \"wind\",\n    \"Wind Offshore\": \"wind\",\n    \"Biomass\": \"biomass\",\n    \"Energy Storage\": \"storage_battery\",\n    \"Nuclear\": \"nuclear\",\n    \"Hydro Run-of-river and poundage\": \"hydro\",\n    \"Hydro Pumped Storage\": \"storage_hydro\",\n    \"Fossil Oil\": \"oil\",\n    \"Other\": \"unknown\",\n}\n\n\ndef fetch_elia(\n    zone_key: ZoneKey = ZoneKey(\"BE\"),\n    session: Session | None = None,\n    start_datetime: datetime | None = None,\n    end_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> ProductionBreakdownList:\n    session = session or Session()\n\n    if start_datetime is not None and end_datetime is not None:\n        start_brussels = start_datetime.astimezone(TIMEZONE).replace(tzinfo=None)\n        end_brussels = end_datetime.astimezone(TIMEZONE).replace(tzinfo=None)\n        url = f\"{BASE_URL_ELIA}&timezone=Europe/Brussels&where=datetime >= date'{start_brussels.isoformat()}' AND datetime < date'{end_brussels.isoformat()}'\"\n    else:\n        url = BASE_URL_ELIA\n\n    response = session.get(url)\n    results = json.loads(response.text).get(\"results\", [])\n    production_breakdown_list = ProductionBreakdownList(logger)\n\n    sorted_results = sorted(results, key=lambda x: x.get(\"datetime\", \"\"))\n\n    for dt_key, events in groupby(sorted_results, key=lambda x: x.get(\"datetime\")):\n        production_mix = ProductionMix()\n        storage_mix = StorageMix()\n\n        for event in events:\n            fuel_type = FUEL_TYPE_MAPPING_ELIA.get(\n                event.get(\"fueltypeentsoe\"), \"unknown\"\n            )\n            power = event.get(\"generatedpower\")\n\n            if \"storage\" in fuel_type:\n                storage_mix.add_value(\n                    fuel_type.removeprefix(\"storage_\"),\n                    -power if power is not None else None,\n                )\n            else:\n                production_mix.add_value(\n                    fuel_type,\n                    power,\n                )\n\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(dt_key).astimezone(timezone.utc),\n            production=production_mix,\n            storage=storage_mix,\n            source=SOURCE_ELIA,\n        )\n\n    return production_breakdown_list\n\n\nENTSOE_SPAN = (timedelta(hours=-48), timedelta(hours=0))\n\n\ndef fetch_entsoe(\n    zone_key: ZoneKey = ZoneKey(\"BE\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> ProductionBreakdownList:\n    session = session or Session()\n    domain = ENTSOE.ENTSOE_DOMAIN_MAPPINGS[zone_key]\n    params = {\n        \"documentType\": \"A75\",\n        \"processType\": \"A16\",\n        \"in_Domain\": domain,\n    }\n    raw_production = ENTSOE.query_ENTSOE(\n        session=session,\n        params=params,\n        span=ENTSOE_SPAN,\n        target_datetime=target_datetime,\n    )\n    if raw_production is None:\n        raise ParserException(\n            parser=\"BE.py\",\n            message=f\"No production data found for {zone_key} from ENTSOE\",\n            zone_key=zone_key,\n        )\n    return ENTSOE.parse_production(raw_production, logger, zone_key)\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"BE\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n\n    entsoe_data = fetch_entsoe(zone_key, session, target_datetime, logger)\n    # Determine the time range covered by ENTSOE data and fetch Elia in 2-hour chunks.\n    entsoe_datetimes = [event.datetime for event in entsoe_data.events]\n    elia_data = ProductionBreakdownList(logger)\n\n    if entsoe_datetimes:\n        range_start = min(entsoe_datetimes)\n        range_end = max(entsoe_datetimes)\n        chunk_start = range_start\n        while chunk_start <= range_end:\n            chunk_end = chunk_start + timedelta(hours=ELIA_WINDOW_HOURS)\n            chunk = fetch_elia(zone_key, session, chunk_start, chunk_end, logger)\n            elia_data = ProductionBreakdownList.update_production_breakdowns(\n                elia_data, chunk, logger\n            )\n            chunk_start = chunk_end\n\n    # Prefer Elia data where available; fall back to ENTSOE for other datetimes.\n    return ProductionBreakdownList.update_production_breakdowns(\n        entsoe_data, elia_data, logger\n    ).to_list()\n\n\nif __name__ == \"__main__\":\n    fetch_elia(ZoneKey(\"BE\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/BG.py",
    "content": "from datetime import datetime, timezone\nfrom logging import Logger, getLogger\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"BG.py\"\n\nSOURCE = \"eso.bg\"\nSOURCE_API_URL = \"http://www.eso.bg/api/rabota_na_EEC_json.php?en\"\n\nPRODUCTION_TYPE_TO_PRODUCTION_MODE = {\n    \"NPP\": \"nuclear\",\n    \"CHP\": \"coal\",\n    \"Heating TPPs\": \"gas\",\n    \"Factory TPPs\": \"gas\",\n    \"HPP\": \"hydro\",\n    \"Small HPPs\": \"hydro\",\n    \"Wind\": \"wind\",\n    \"PV\": \"solar\",\n    \"Bio\": \"biomass\",\n}\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"BG\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    session = session or Session()\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER, \"This parser is not yet able to parse historical data\", zone_key\n        )\n\n    time = datetime.now(timezone.utc)\n    response = session.get(SOURCE_API_URL)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    response_payload = response.json()\n    logger.debug(f\"Raw generation breakdown: {response_payload}\")\n\n    production_mix = ProductionMix()\n    for header, value in response_payload:\n        production_type, _delimiter, _percentage = header.rpartition(\" \")\n        production_mode = PRODUCTION_TYPE_TO_PRODUCTION_MODE[production_type]\n        production_mix.add_value(production_mode, value)\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n    production_breakdown_list.append(\n        zoneKey=zone_key,\n        datetime=time,\n        source=SOURCE,\n        production=production_mix,\n    )\n    return production_breakdown_list.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CAMMESA.py",
    "content": "#!/usr/bin/env python3\n\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\n# Useful links.\n# https://en.wikipedia.org/wiki/Electricity_sector_in_Argentina\n# https://en.wikipedia.org/wiki/List_of_power_stations_in_Argentina\n# http://globalenergyobservatory.org/countryid/10#\n# http://www.industcards.com/st-other-argentina.htm\n\n# API Documentation: https://api.cammesa.com/demanda-svc/swagger-ui.html\nCAMMESA_DEMANDA_ENDPOINT = (\n    \"https://api.cammesa.com/demanda-svc/generacion/ObtieneGeneracioEnergiaPorRegion/\"\n)\nCAMMESA_EXCHANGE_ENDPOINT = (\n    \"https://api.cammesa.com/demanda-svc/demanda/IntercambioCorredoresGeo/\"\n)\nCAMMESA_RENEWABLES_ENDPOINT = \"https://cdsrenovables.cammesa.com/exhisto/RenovablesService/GetChartTotalTRDataSource/\"\n\n# Expected arrow direction if flow is first -> second\nEXCHANGE_NAME_DIRECTION_MAPPING = {\n    \"AR->CL-SEN\": (\"ARG-CHI\", 180),\n    \"AR->PY\": (\"ARG-PAR\", 45),\n    \"AR->UY\": (\"ARG-URU\", 0),\n    \"AR-NEA->BR-S\": (\"ARG-BRA\", 45),\n    \"AR-BAS->AR-COM\": (\"PBA-COM\", 225),\n    \"AR-CEN->AR-COM\": (\"CEN-COM\", 270),\n    \"AR-CEN->AR-NOA\": (\"CEN-NOA\", 135),\n    \"AR-CUY->AR-COM\": (\"CUY-COM\", 315),\n    \"AR-CEN->AR-CUY\": (\"CEN-CUY\", 225),\n    \"AR-LIT->AR-NEA\": (\"LIT-NEA\", 45),\n    \"AR-BAS->AR-LIT\": (\"PBA-LIT\", 90),\n    \"AR-CUY->AR-NOA\": (\"CUY-NOA\", 45),\n    \"AR-LIT->AR-CEN\": (\"LIT-CEN\", 225),\n    \"AR-LIT->AR-NOA\": (\"LIT-NOA\", 135),\n    \"AR-BAS->AR-CEN\": (\"PBA-CEN\", 135),\n    \"AR-COM->AR-PAT\": (\"COM-PAT\", 270),\n    \"AR-NEA->AR-NOA\": (\"NEA-NOA\", 180),\n}\n\nSOURCE = \"cammesaweb.cammesa.com\"\n\nSPLIT_UNKNOWN_PRODUCTION = {  # To be updated with the latest data when available\n    2017: {\"oil\": 0.12, \"gas\": 0.85, \"coal\": 0.03},\n    2018: {\"oil\": 0.07, \"gas\": 0.90, \"coal\": 0.03},\n    2019: {\"oil\": 0.04, \"gas\": 0.95, \"coal\": 0.01},\n    2020: {\"oil\": 0.075, \"gas\": 0.90, \"coal\": 0.025},\n    2021: {\"oil\": 0.12, \"gas\": 0.85, \"coal\": 0.03},\n    2022: {\"oil\": 0.17, \"gas\": 0.80, \"coal\": 0.03},\n}  # source: EIA 2022 (https://www.iea.org/data-and-statistics/data-tools/energy-statistics-data-browser?country=ARGENTINA&fuel=Energy%20supply&indicator=ElecGenByFuel)\ndf_split_unknown_production = pd.DataFrame(SPLIT_UNKNOWN_PRODUCTION).T\ndf_split_unknown_production = df_split_unknown_production.reindex(\n    range(2017, datetime.now().year + 1), method=\"ffill\"\n)\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"AR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests up to date list of production mixes (in MW) of a given country.\"\"\"\n\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    current_session = session or Session()\n\n    conventional_production = non_renewables_production_mix(\n        zone_key, current_session, logger\n    )\n    renewables_production = renewables_production_mix(zone_key, current_session, logger)\n    # Hydro comes from both conventional and renewables production which are merged together\n    return ProductionBreakdownList.merge_production_breakdowns(\n        [conventional_production, renewables_production],\n        logger,\n        matching_timestamps_only=True,\n    ).to_list()\n\n\ndef renewables_production_mix(\n    zone_key: ZoneKey, session: Session, logger: Logger\n) -> ProductionBreakdownList:\n    \"\"\"Retrieves production mix for renewables using CAMMESA's API\"\"\"\n\n    today = (\n        datetime.now()\n        .astimezone(tz=ZoneInfo(\"America/Argentina/Buenos_Aires\"))\n        .strftime(\"%d-%m-%Y\")\n    )\n    params = {\"desde\": today, \"hasta\": today}\n    renewables_response = session.get(CAMMESA_RENEWABLES_ENDPOINT, params=params)\n    assert renewables_response.status_code == 200, (\n        \"Exception when fetching production for \"\n        f\"{zone_key}: error when calling url={CAMMESA_RENEWABLES_ENDPOINT} with payload={params}\"\n    )\n\n    production_list = renewables_response.json()\n    renewables_production = ProductionBreakdownList(logger)\n    for production_info in production_list:\n        renewables_production.append(\n            zoneKey=zone_key,\n            datetime=datetime.strptime(\n                production_info[\"momento\"], \"%Y-%m-%dT%H:%M:%S.%f%z\"\n            ),\n            production=ProductionMix(\n                biomass=production_info[\"biocombustible\"],\n                hydro=production_info[\"hidraulica\"],\n                solar=production_info[\"fotovoltaica\"],\n                wind=production_info[\"eolica\"],\n            ),\n            source=SOURCE,\n        )\n\n    return renewables_production\n\n\ndef non_renewables_production_mix(\n    zone_key: ZoneKey, session: Session, logger: Logger\n) -> ProductionBreakdownList:\n    \"\"\"Retrieves production mix for non renewables using CAMMESA's API\"\"\"\n\n    params = {\"id_region\": 1002}\n    api_cammesa_response = session.get(CAMMESA_DEMANDA_ENDPOINT, params=params)\n    assert api_cammesa_response.status_code == 200, (\n        \"Exception when fetching production for \"\n        f\"{zone_key}: error when calling url={CAMMESA_DEMANDA_ENDPOINT} with payload={params}\"\n    )\n    production_list = api_cammesa_response.json()\n    conventional_production = ProductionBreakdownList(logger)\n    for production_info in production_list:\n        # Convert fecha string to datetime and extract the year\n        production_datetime = datetime.strptime(\n            production_info[\"fecha\"], \"%Y-%m-%dT%H:%M:%S.%f%z\"\n        )\n        production_year = production_datetime.year\n\n        # use the split from EIA 2022 to split the termico production into gas and oil\n        for mode in [\"gas\", \"oil\", \"coal\"]:\n            production_info[mode] = (\n                production_info[\"termico\"]\n                * df_split_unknown_production.loc[production_year][mode]\n            )  # use the split from EIA 2022 to split the termico production into gas and oil\n        conventional_production.append(\n            zoneKey=zone_key,\n            datetime=production_datetime,\n            production=ProductionMix(\n                hydro=production_info[\"hidraulico\"],\n                nuclear=production_info[\"nuclear\"],\n                # As of 2022 thermal energy is mostly natural gas but\n                # the data is not split. We put it into unknown for now.\n                # More info: see page 21 in https://microfe.cammesa.com/static-content/CammesaWeb/download-manager-files/Sintesis%20Mensual/Informe%20Mensual_2021-12.pdf\n                # unknown=production_info[\"termico\"],\n                gas=production_info[\"gas\"],\n                oil=production_info[\"oil\"],\n                coal=production_info[\"coal\"],\n            ),\n            source=SOURCE,\n        )\n\n    return conventional_production\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known power exchange (in MW) between two zones.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    if sorted_zone_keys not in EXCHANGE_NAME_DIRECTION_MAPPING:\n        raise ParserException(\n            parser=\"CAMMESA.py\",\n            message=\"This exchange is not currently implemented\",\n            zone_key=sorted_zone_keys,\n        )\n\n    current_session = session or Session()\n\n    api_cammesa_response = current_session.get(CAMMESA_EXCHANGE_ENDPOINT)\n    if not api_cammesa_response.ok:\n        raise ParserException(\n            parser=\"CAMMESA.py\",\n            message=f\"Exception when fetching exchange for {sorted_zone_keys}: error when calling url={CAMMESA_EXCHANGE_ENDPOINT}\",\n            zone_key=sorted_zone_keys,\n        )\n    exchange_name, expected_angle = EXCHANGE_NAME_DIRECTION_MAPPING[sorted_zone_keys]\n    exchange_list = api_cammesa_response.json()[\"features\"]\n    exchange_data = next(\n        (\n            exchange[\"properties\"]\n            for exchange in exchange_list\n            if exchange[\"properties\"][\"nombre\"] == exchange_name\n        ),\n        None,\n    )\n    if exchange_data is None:\n        raise ParserException(\n            parser=\"CAMMESA.py\",\n            message=f\"Exception when fetching exchange for {sorted_zone_keys}: exchange not found\",\n            zone_key=sorted_zone_keys,\n        )\n    given_angle = int(exchange_data[\"url\"][6:])\n    flow = int(exchange_data[\"text\"])\n\n    # inverse flow if arrow doesn't match expected direction\n    if expected_angle != given_angle:\n        flow = -flow\n    exchange_datetime = datetime.fromisoformat(\n        exchange_data[\"fecha\"][:-2] + \":\" + exchange_data[\"fecha\"][-2:]\n    )\n    exchanges = ExchangeList(logger)\n    exchanges.append(\n        zoneKey=sorted_zone_keys,\n        datetime=exchange_datetime,\n        netFlow=flow,\n        source=SOURCE,\n    )\n    return exchanges.to_list()\n\n\ndef fetch_price(\n    zone_key: str = \"AR\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the last known power price of a given country.\"\"\"\n\n    raise NotImplementedError(\"Fetching the price is not currently implemented\")\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_exchange(AR, PY) ->\")\n    print(fetch_exchange(ZoneKey(\"AR\"), ZoneKey(\"PY\")))\n    print(\"fetch_exchange(AR, UY) ->\")\n    print(fetch_exchange(ZoneKey(\"AR\"), ZoneKey(\"UY\")))\n    print(\"fetch_exchange(AR, CL-SEN) ->\")\n    print(fetch_exchange(ZoneKey(\"AR\"), ZoneKey(\"CL-SEN\")))\n    print(\"fetch_exchange(AR-CEN, AR-COM) ->\")\n    print(fetch_exchange(ZoneKey(\"AR-CEN\"), ZoneKey(\"AR-COM\")))\n    print(\"fetch_exchange(AR-BAS, AR-LIT) ->\")\n    print(fetch_exchange(ZoneKey(\"AR-BAS\"), ZoneKey(\"AR-LIT\")))\n    print(\"fetch_exchange(AR-COM, AR-PAT) ->\")\n    print(fetch_exchange(ZoneKey(\"AR-COM\"), ZoneKey(\"AR-PAT\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CA_AB.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Parse the Alberta Electric System Operator's (AESO's) Energy Trading System\n(ETS) website.\n\"\"\"\n\n# Standard library imports\nimport csv\nimport io\nimport re\nimport urllib.parse\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\n\n# Third-party library imports\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    GridAlertList,\n    PriceList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    GridAlertType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nDEFAULT_ZONE_KEY = ZoneKey(\"CA-AB\")\nTIMEZONE = ZoneInfo(\"Canada/Mountain\")\nURL = urllib.parse.urlsplit(\"http://ets.aeso.ca/ets_web/ip/Market/Reports\")\nURL_STRING = urllib.parse.urlunsplit(URL)\n\nSOURCE = URL.netloc\n\nPRODUCTION_MAPPING = {\n    \"COGENERATION\": \"gas\",\n    \"COMBINED CYCLE\": \"gas\",\n    \"GAS FIRED STEAM\": \"gas\",\n    \"SIMPLE CYCLE\": \"gas\",\n    \"WIND\": \"wind\",\n    \"SOLAR\": \"solar\",\n    \"HYDRO\": \"hydro\",\n    \"OTHER\": \"biomass\",\n}\n\nSTORAGE_MAPPING = {\"ENERGY STORAGE\": \"battery\"}\nGRID_ALERTS_URL = \"http://ets.aeso.ca/ets_web/ip/Market/Reports/RealTimeShiftReportServlet?contentType=html\"\nGRID_ALERT_SOURCE = \"aeso.ca\"\nSKIP_KEYS = [\"TOTAL\"]\n\n\ndef fetch_exchange(\n    zone_key1: str = DEFAULT_ZONE_KEY,\n    zone_key2: str = \"CA-BC\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Request the last known power exchange (in MW) between two countries.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"Currently unable to scrape historical data\")\n    session = session or Session()\n    response = session.get(\n        f\"{URL_STRING}/CSDReportServlet\", params={\"contentType\": \"csv\"}\n    )\n    interchange = dict(csv.reader(response.text.split(\"\\r\\n\\r\\n\")[4].splitlines()))\n    flows = {\n        f\"{DEFAULT_ZONE_KEY}->CA-BC\": interchange[\"British Columbia\"],\n        f\"{DEFAULT_ZONE_KEY}->CA-SK\": interchange[\"Saskatchewan\"],\n        f\"{DEFAULT_ZONE_KEY}->US-MT\": interchange[\"Montana\"],\n        f\"{DEFAULT_ZONE_KEY}->US-NW-NWMT\": interchange[\"Montana\"],\n    }\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted((zone_key1, zone_key2))))\n    if sorted_zone_keys not in flows:\n        raise NotImplementedError(f\"Pair '{sorted_zone_keys}' not implemented\")\n    exchanges = ExchangeList(logger)\n    exchanges.append(\n        zoneKey=sorted_zone_keys,\n        datetime=get_csd_report_timestamp(response.text),\n        netFlow=float(flows[sorted_zone_keys]),\n        source=URL.netloc,\n    )\n    return exchanges.to_list()\n\n\ndef fetch_price(\n    zone_key: ZoneKey = DEFAULT_ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Request the last known power price of a given country.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"Currently unable to scrape historical data\")\n    session = session or Session()\n    response = session.get(\n        f\"{URL_STRING}/SMPriceReportServlet\", params={\"contentType\": \"csv\"}\n    )\n    prices = PriceList(logger)\n    for row in csv.reader(response.text.split(\"\\r\\n\\r\\n\")[2].splitlines()[1:]):\n        if row[1] != \"-\":\n            date, hour = row[0].split()\n            prices.append(\n                zoneKey=zone_key,\n                datetime=datetime.strptime(\n                    f\"{date} {int(hour) - 1}\", \"%m/%d/%Y %H\"\n                ).replace(tzinfo=TIMEZONE)\n                + timedelta(hours=1),\n                price=float(row[1]),\n                source=URL.netloc,\n                currency=\"CAD\",\n            )\n    return prices.to_list()\n\n\ndef fetch_production(\n    zone_key: str = DEFAULT_ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict[str, Any] | None:\n    \"\"\"Request the last known production mix (in MW) of a given country.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n    session = session or Session()\n    response = session.get(\n        f\"{URL_STRING}/CSDReportServlet\", params={\"contentType\": \"csv\"}\n    )\n    generation = {\n        row[0]: float(row[2])  # total net generation\n        for row in csv.reader(response.text.split(\"\\r\\n\\r\\n\")[3].splitlines())\n    }\n\n    production_breakdowns = ProductionBreakdownList(logger)\n    production = ProductionMix()\n    storage = StorageMix()\n\n    for key in generation:\n        if key in PRODUCTION_MAPPING:\n            production.add_value(\n                PRODUCTION_MAPPING[key],\n                generation.get(key),\n                correct_negative_with_zero=True,\n            )\n        elif key in STORAGE_MAPPING:\n            storage.add_value(STORAGE_MAPPING[key], generation.get(key))\n\n        elif key not in SKIP_KEYS:\n            logger.warning(f\"Unrecognized key: {key} in data\")\n\n    date = get_csd_report_timestamp(response.text)\n\n    production_breakdowns.append(\n        zoneKey=zone_key,\n        datetime=date,\n        production=production,\n        storage=storage,\n        source=SOURCE,\n    )\n\n    return production_breakdowns.to_list()\n\n\ndef get_csd_report_timestamp(report):\n    \"\"\"Get the timestamp from a current supply/demand (CSD) report.\"\"\"\n    return datetime.strptime(\n        re.search(r'\"Last Update : (.*)\"', report).group(1), \"%b %d, %Y %H:%M\"\n    ).replace(tzinfo=TIMEZONE)\n\n\ndef _get_wind_solar_data(session: Session, url: str) -> pd.DataFrame:\n    response = session.get(url)\n    csv = pd.read_csv(io.StringIO(response.text))\n    return csv\n\n\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey = DEFAULT_ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests wind and solar production forecasts in hourly data (in MW) for 7 days ahead.\"\"\"\n    session = session or Session()\n\n    # Requests\n    # Wind 7 days\n    url_wind = \"http://ets.aeso.ca/Market/Reports/Manual/Operations/prodweb_reports/wind_solar_forecast/wind_rpt_longterm.csv\"\n    csv_wind = _get_wind_solar_data(session, url_wind)\n\n    # Solar 7 days\n    url_solar = \"http://ets.aeso.ca/Market/Reports/Manual/Operations/prodweb_reports/wind_solar_forecast/solar_rpt_longterm.csv\"\n    csv_solar = _get_wind_solar_data(session, url_solar)\n\n    all_production_events = csv_wind.merge(\n        csv_solar, on=\"Forecast Transaction Date\", suffixes=(\"_wind\", \"_solar\")\n    )\n\n    production_list = ProductionBreakdownList(logger)\n    for _, event in all_production_events.iterrows():\n        event_datetime = event[\"Forecast Transaction Date\"]\n        event_datetime = datetime.fromisoformat(event_datetime).replace(tzinfo=TIMEZONE)\n        production_mix = ProductionMix()\n        production_mix.add_value(\n            \"solar\", event[\"Most Likely_solar\"], correct_negative_with_zero=True\n        )\n        production_mix.add_value(\n            \"wind\", event[\"Most Likely_wind\"], correct_negative_with_zero=True\n        )\n\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=event_datetime,\n            production=production_mix,\n            source=URL.netloc,\n            sourceType=EventSourceType.forecasted,\n        )\n    return production_list.to_list()\n\n\ndef fetch_grid_alerts(\n    zone_key: ZoneKey = DEFAULT_ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n\n    data = session.get(GRID_ALERTS_URL)\n    soup = BeautifulSoup(data.text, \"html.parser\")\n    table = soup.find_all(\"table\")[-1]\n    rows = table.find_all(\"tr\")\n    grid_alert_list = GridAlertList(logger)\n    for row in rows:\n        cells = row.find_all(\"td\")\n        if len(cells) < 2:\n            continue\n        message = cells[1].text\n        time = cells[0].text\n        time = datetime.strptime(time, \"%m/%d/%Y %H:%M\").replace(tzinfo=TIMEZONE)\n        grid_alert_list.append(\n            zoneKey=zone_key,\n            locationRegion=None,\n            source=GRID_ALERT_SOURCE,\n            alertType=GridAlertType.undefined,\n            message=message,\n            issuedTime=time,\n            startTime=None,\n            endTime=None,\n        )\n    return grid_alert_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the electricityMap backend, but handy for testing.\"\"\"\n    \"\"\"\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_price() ->\")\n    print(fetch_price())\n    print(f\"fetch_exchange({DEFAULT_ZONE_KEY}, CA-BC) ->\")\n    print(fetch_exchange(DEFAULT_ZONE_KEY, \"CA-BC\"))\n    print(f\"fetch_exchange({DEFAULT_ZONE_KEY}, CA-SK) ->\")\n    print(fetch_exchange(DEFAULT_ZONE_KEY, \"CA-SK\"))\n    print(f\"fetch_exchange({DEFAULT_ZONE_KEY}, US-MT) ->\")\n    print(fetch_exchange(DEFAULT_ZONE_KEY, \"US-MT\"))\n    print(f\"fetch_exchange({DEFAULT_ZONE_KEY}, US-NW-NWMT) ->\")\n    print(fetch_exchange(DEFAULT_ZONE_KEY, \"US-NW-NWMT\"))\"\n    \"\"\"\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CA_BC.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZONES_CONFIG\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\n# More info:\n# https://www.bchydro.com/energy-in-bc/our_system/transmission/transmission-system/actual-flow-data.html\n\nHISTORICAL_LOAD_REPORTS = \"https://www.bchydro.com/content/dam/BCHydro/customer-portal/documents/corporate/suppliers/transmission-system/balancing_authority_load_data/Historical%20Transmission%20Data/BalancingAuthorityLoad{0}.xls\"\nEXCHANGES_URL = \"https://www.bchydro.com/bctc/system_cms/actual_flow/latest_values.txt\"\nTIMEZONE = ZoneInfo(ZONES_CONFIG.get(ZoneKey(\"CA-BC\"), {}).get(\"timezone\"))\nSOURCE = \"bchydro.com\"\nPUBLICATION_DELAY = timedelta(days=31)\n\nEXCHANGE_POSITION_MULTIPLIER = {\n    ZoneKey(\"CA-BC->US-NW-BPAT\"): (1, 1),\n    ZoneKey(\"CA-AB->CA-BC\"): (2, -1),\n}\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    r = session or Session()\n    consumption_list = TotalConsumptionList(logger)\n    if target_datetime is None:\n        start_date = datetime.now(tz=TIMEZONE) - PUBLICATION_DELAY - timedelta(days=1)\n        end_date = datetime.now(tz=TIMEZONE)\n    else:\n        start_date = target_datetime - timedelta(days=1)\n        end_date = target_datetime\n    # If the range spans multiple years, we need to fetch each year separately.\n    for year in range(start_date.year, end_date.year + 1):\n        url = HISTORICAL_LOAD_REPORTS.format(year)\n        response: Response = r.get(url)\n        if not response.ok:\n            raise ParserException(\n                \"CA_BC.py\",\n                f\"Could not fetch load report for year {year}\",\n                zone_key,\n            )\n        df = pd.read_excel(response.content, skiprows=3)\n        df = df.rename(columns={\"Date ?\": \"Date\"})\n        # The first hour of each day is set at 1 and the last at 24 so we need to subtract 1\n        # to correctly align dates and hours.\n        # Due to DST there might be some missing hours, we use shift_backward to fill them with the previous hour.\n        df[\"datetime\"] = pd.to_datetime(\n            df[\"Date\"] + \" \" + (df[\"HE\"] - 1).astype(\"str\"), format=\"%m/%d/%Y %H\"\n        ).dt.tz_localize(TIMEZONE, nonexistent=\"shift_backward\")\n        df = df.set_index(\"datetime\")\n        selected_times = df[start_date:end_date]\n        for row in selected_times.iterrows():\n            consumption_list.append(\n                zoneKey=zone_key,\n                datetime=row[0].to_pydatetime(),\n                source=SOURCE,\n                consumption=row[1][\"Control Area Load\"],\n            )\n    return consumption_list.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known power exchange (in MW) between two countries.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    r = session or Session()\n    response = r.get(EXCHANGES_URL)\n    obj = response.text.split(\"\\r\\n\")[1].replace(\"\\r\", \"\").split(\",\")\n\n    parsed_datetime = datetime.strptime(obj[0], \"%d-%b-%y %H:%M:%S\").replace(\n        tzinfo=TIMEZONE\n    )\n\n    sortedZoneKeys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    if sortedZoneKeys not in EXCHANGE_POSITION_MULTIPLIER:\n        raise NotImplementedError(\"This exchange pair is not implemented\")\n    position, multiplier = EXCHANGE_POSITION_MULTIPLIER[sortedZoneKeys]\n\n    exchanges = ExchangeList(logger)\n    exchanges.append(\n        sortedZoneKeys,\n        parsed_datetime,\n        SOURCE,\n        float(obj[position]) * multiplier,\n    )\n    return exchanges.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(\"fetch_exchange(CA-AB, CA-BC) ->\")\n    print(fetch_exchange(\"CA-AB\", \"CA-BC\"))\n    print(\"fetch_consumption(CA-BC) ->\")\n    print(\n        fetch_consumption(\n            ZoneKey(\"CA-BC\"), target_datetime=datetime(2023, 3, 1, 0, 0, 0, 0, TIMEZONE)\n        )\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CA_NB.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any\n\n# BeautifulSoup is used to parse HTML to get information\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.types import ZoneKey\n\nSOURCE = \"tso.nbpower.com\"\nEXCHANGE_TO_FLOWS = {\n    ZoneKey(\"CA-NB->CA-QC\"): [\"QUEBEC\"],\n    # all of these exports are to Maine\n    # (see https://www.nbpower.com/en/about-us/our-energy/system-map/),\n    # currently this is mapped to ISO-NE\n    ZoneKey(\"CA-NB->US-NE-ISNE\"): [\"EMEC\", \"ISO-NE\", \"MPS\"],\n    ZoneKey(\"CA-NB->CA-NS\"): [\"NOVA SCOTIA\"],\n    ZoneKey(\"CA-NB->CA-PE\"): [\"PEI\"],\n}\n\n\ndef _get_new_brunswick_flows(requests_obj):\n    \"\"\"\n    Gets current electricity flows in and out of New Brunswick.\n\n    There is no reported data timestamp in the page.\n    The page returns current time and says \"Times at which values are sampled may vary by as much as 5 minutes.\"\n    \"\"\"\n\n    url = \"https://tso.nbpower.com/Public/en/SystemInformation_realtime.asp\"\n    response = requests_obj.get(url)\n\n    soup = BeautifulSoup(response.text, \"html.parser\")\n\n    table = soup.find(\"table\", attrs={\"bordercolor\": \"#191970\"})\n\n    rows = table.find_all(\"tr\")\n\n    headers = rows[1].find_all(\"td\")\n    values = rows[2].find_all(\"td\")\n\n    flows = {\n        headers[i].text.strip(): float(row.text.strip()) for i, row in enumerate(values)\n    }\n\n    return flows\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"CA-NB\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n\n    \"\"\"\n    In this case, we are calculating the amount of electricity generated\n    in New Brunswick, versus imported and exported elsewhere.\n    \"\"\"\n\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    requests_obj = session or Session()\n    flows = _get_new_brunswick_flows(requests_obj)\n\n    # nb_flows['NB Demand'] is the use of electricity in NB\n    # 'EMEC', 'ISO-NE', 'MPS', 'NOVA SCOTIA', 'PEI', and 'QUEBEC'\n    # are exchanges - positive for exports, negative for imports\n    # Electricity generated in NB is then 'NB Demand' plus all the others\n\n    generated = (\n        flows[\"NB Demand\"]\n        + flows[\"EMEC\"]\n        + flows[\"ISO-NE\"]\n        + flows[\"MPS\"]\n        + flows[\"NOVA SCOTIA\"]\n        + flows[\"PEI\"]\n        + flows[\"QUEBEC\"]\n    )\n    production = ProductionBreakdownList(logger)\n    production.append(\n        zoneKey=zone_key,\n        # Using the current utc time because the page returns the current time.\n        datetime=datetime.now(tz=timezone.utc).replace(\n            minute=0, second=0, microsecond=0\n        ),\n        source=SOURCE,\n        production=ProductionMix(\n            unknown=generated,\n        ),\n    )\n\n    return production.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known power exchange (in MW) between two regions.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    sorted_zone_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    requests_obj = session or Session()\n    flows = _get_new_brunswick_flows(requests_obj)\n\n    # In this source, positive values are exports and negative are imports.\n    # In expected result, \"net\" represents an export.\n    # So these can be used directly.\n\n    if sorted_zone_keys not in EXCHANGE_TO_FLOWS:\n        raise NotImplementedError(\"This exchange pair is not implemented\")\n    exchanges = ExchangeList(logger)\n    exchanges.append(\n        zoneKey=sorted_zone_keys,\n        datetime=datetime.now(tz=timezone.utc).replace(\n            minute=0, second=0, microsecond=0\n        ),\n        source=SOURCE,\n        netFlow=sum([flows[flow] for flow in EXCHANGE_TO_FLOWS[sorted_zone_keys]]),\n    )\n\n    return exchanges.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n\n    print('fetch_exchange(\"CA-NB\", \"CA-PE\") ->')\n    print(fetch_exchange(ZoneKey(\"CA-NB\"), ZoneKey(\"CA-PE\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CA_NS.py",
    "content": "#!/usr/bin/env python3\nfrom datetime import datetime, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\n# The table shown on the \"Daily Report\" page\n# (https://www.nspower.ca/oasis/system-reports-messages/daily-report) is inside\n# an iframe which refers to the following URL.\nEXCHANGE_URL = (\n    \"https://resourcesprd-nspower.aws.silvertech.net/oasis/current_report.shtml\"\n)\nLOAD_URL = \"https://www.nspower.ca/library/CurrentLoad/CurrentLoad.json\"\nMIX_URL = \"https://www.nspower.ca/library/CurrentLoad/CurrentMix.json\"\nPARSER = \"CA_NS.py\"\nSOURCE = \"nspower.ca\"\nZONE_KEY = ZoneKey(\"CA-NS\")\n\n\ndef _parse_timestamp(timestamp: str) -> datetime:\n    \"\"\"\n    Construct a datetime object from a date string formatted as, e.g.,\n    \"/Date(1493924400000)/\" by extracting the Unix timestamp 1493924400. Note\n    that the three trailing zeros are cut out as well).\n    \"\"\"\n    return datetime.fromtimestamp(int(timestamp[6:-5]), tz=timezone.utc)\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    if target_datetime:\n        raise ParserException(PARSER, \"Unable to fetch historical data\", zone_key)\n\n    if zone_key != ZONE_KEY:\n        raise ParserException(PARSER, f\"Cannot parse zone '{zone_key}'\", zone_key)\n\n    # Request data from the source. Skip the first element of each JSON array\n    # because the reported base load is always 0 MW.\n    session = session or Session()\n    loads = {  # A lookup table mapping timestamps to base loads (in MW)\n        _parse_timestamp(load[\"datetime\"]): load[\"Base Load\"]\n        for load in session.get(LOAD_URL).json()[1:]\n    }\n    mixes = session.get(MIX_URL).json()[1:]  # Electricity mix breakdowns in %\n\n    production_breakdowns = ProductionBreakdownList(logger)\n    for mix in mixes:\n        timestamp = _parse_timestamp(mix[\"datetime\"])\n        if timestamp not in loads:\n            logger.warning(\n                f\"unable to find base load for {timestamp}\",\n                extra={\"zone_key\": ZONE_KEY},\n            )\n            continue\n        load = loads[timestamp]\n        if load <= 0:\n            logger.warning(\n                f\"invalid base load of {load} MW\", extra={\"zone_key\": ZONE_KEY}\n            )\n            continue\n\n        production_mix = ProductionMix()\n        production_mix.add_value(\"biomass\", load * mix[\"Biomass\"] / 100)\n        production_mix.add_value(\"coal\", load * mix[\"Solid Fuel\"] / 100)\n        production_mix.add_value(\"gas\", load * mix[\"HFO/Natural Gas\"] / 100)\n        production_mix.add_value(\"gas\", load * mix[\"LM 6000's\"] / 100)\n        production_mix.add_value(\"hydro\", load * mix[\"Hydro\"] / 100)\n        production_mix.add_value(\"oil\", load * mix[\"CT's\"] / 100)\n        production_mix.add_value(\"wind\", load * mix[\"Wind\"] / 100)\n        # Sanity checks: verify that reported production doesn't exceed listed\n        # capacity by a lot. In particular, we've seen error cases where hydro\n        # production ends up calculated as 900 MW which greatly exceeds known\n        # capacity of around 520 MW.\n        if (\n            (production_mix.biomass or 0) > 100\n            or (production_mix.coal or 0) > 1300\n            or (production_mix.gas or 0) > 700\n            or (production_mix.hydro or 0) > 600\n            or (production_mix.oil or 0) > 300\n            or (production_mix.wind or 0) > 700\n        ):\n            logger.warning(\n                \"discarding datapoint at %s because some mode's production is \"\n                \"infeasible: %s\",\n                timestamp,\n                production_mix,\n                extra={\"key\": ZONE_KEY},\n            )\n            continue\n        production_breakdowns.append(\n            datetime=timestamp,\n            production=production_mix,\n            source=SOURCE,\n            zoneKey=ZONE_KEY,\n        )\n\n    return production_breakdowns.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Requests the last known power exchange (in MW) between two regions.\n    \"\"\"\n    if target_datetime:\n        raise ParserException(PARSER, \"Unable to fetch historical data\", ZONE_KEY)\n\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted((zone_key1, zone_key2))))\n    if sorted_zone_keys not in (ZoneKey(\"CA-NB->CA-NS\"), ZoneKey(\"CA-NL->CA-NS\")):\n        raise ParserException(PARSER, \"Unimplemented exchange pair\", sorted_zone_keys)\n\n    session = session or Session()\n    soup = BeautifulSoup(session.get(EXCHANGE_URL).text, \"html.parser\")\n\n    # Extract the timestamp from the table header.\n    try:\n        timestamp = datetime.strptime(\n            soup.find(string=\"Current System Conditions\").find_next(\"td\").em.i.string,\n            \"%d-%b-%y %H:%M:%S\",\n        ).replace(tzinfo=ZoneInfo(\"America/Halifax\"))\n    except (AttributeError, TypeError, ValueError) as error:\n        raise ParserException(\n            PARSER, \"unable to extract timestamp\", sorted_zone_keys\n        ) from error\n\n    # Choose the appropriate exchange figure for the requested zone pair.\n    try:\n        exchange = (\n            -float(soup.find(string=\"NS Export \").find_next(\"td\").string)\n            if sorted_zone_keys == ZoneKey(\"CA-NB->CA-NS\")\n            else float(soup.find(string=\"Maritime Link Import \").find_next(\"td\").string)\n        )\n    except (AttributeError, TypeError) as error:\n        raise ParserException(\n            PARSER, \"unable to extract exchange data\", sorted_zone_keys\n        ) from error\n\n    exchanges = ExchangeList(logger)\n    exchanges.append(\n        datetime=timestamp,\n        netFlow=exchange,\n        source=SOURCE,\n        zoneKey=sorted_zone_keys,\n    )\n    return exchanges.to_list()\n\n\nif __name__ == \"__main__\":\n    # Never used by the Electricity Map backend, but handy for testing.\n    from pprint import pprint\n\n    print(\"fetch_production() ->\")\n    pprint(fetch_production())\n    print('fetch_exchange(\"CA-NS\", \"CA-NB\") ->')\n    pprint(fetch_exchange(ZoneKey(\"CA-NS\"), ZoneKey(\"CA-NB\")))\n    print('fetch_exchange(\"CA-NL-NF\", \"CA-NS\") ->')\n    pprint(fetch_exchange(ZoneKey(\"CA-NL-NF\"), ZoneKey(\"CA-NS\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CA_ON.py",
    "content": "#!/usr/bin/env python3\nfrom collections import defaultdict\nfrom datetime import date, datetime, time, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom xml.etree import ElementTree\n\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    GridAlertList,\n    PriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    GridAlertType,\n    ProductionMix,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n# Some notes about timestamps:\n#\n# The IESO website says:\n#\n#   The IESO uses the \"Hour Ending\" naming convention for the hours in a day.\n#   For example, Hour 1 is from 12 am. to 1 am., Hour 2 is from 1 am. to 2 am.\n#   Hours 1-24 are the hours from midnight one day through midnight the next\n#   day.\n#\n# Observations:\n#\n# - At 13:53, HOEP report will have data with \"Hour\" column from 1 to 13.\n#   Output and Capability report will have data with \"Hour\" column from 1 to\n#   13. Intertie Flow report will have data with \"Hour\" column from 1 to 13\n#   *and* Interval column from 1 to 12 for all of these hours, including the\n#   13th hour.\n# - At 14:18, HOEP report will go up to 14, Output report will go up to 14, but\n#   update for Intertie report is not yet updated.\n# - At 14:31, Intertie report is updated with Hour 14 which has Intervals 1 to\n#   12.\n#\n# In the script, the Intertie report is shifted 1 hour and 5 minutes back, so\n# that it lines up with the production and price data availability.\n\n# Map IESO's exchange names to ours.\nEXCHANGES = {\n    \"MANITOBA SK\": \"CA-MB->CA-ON\",\n    \"MANITOBA\": \"CA-MB->CA-ON\",\n    \"MICHIGAN\": \"CA-ON->US-MIDW-MISO\",\n    \"MINNESOTA\": \"CA-ON->US-MIDW-MISO\",\n    \"NEW-YORK\": \"CA-ON->US-NY-NYIS\",\n    \"PQ.AT\": \"CA-ON->CA-QC\",\n    \"PQ.B5D.B31L\": \"CA-ON->CA-QC\",\n    \"PQ.D4Z\": \"CA-ON->CA-QC\",\n    \"PQ.D5A\": \"CA-ON->CA-QC\",\n    \"PQ.H4Z\": \"CA-ON->CA-QC\",\n    \"PQ.H9A\": \"CA-ON->CA-QC\",\n    \"PQ.P33C\": \"CA-ON->CA-QC\",\n    \"PQ.Q4C\": \"CA-ON->CA-QC\",\n    \"PQ.X2Y\": \"CA-ON->CA-QC\",\n}\nEXCHANGE_URL = \"http://reports.ieso.ca/public/IntertieScheduleFlow/PUB_IntertieScheduleFlow_{YYYYMMDD}.xml\"\n# Map IESO's production modes to ours.\nMODES = {\n    \"BIOFUEL\": \"biomass\",\n    \"GAS\": \"gas\",\n    \"HYDRO\": \"hydro\",\n    \"NUCLEAR\": \"nuclear\",\n    \"SOLAR\": \"solar\",\n    \"WIND\": \"wind\",\n}\nNAMESPACE = \"{http://www.theIMO.com/schema}\"\nPRICE_URL = (\n    \"http://reports.ieso.ca/public/DispUnconsHOEP/PUB_DispUnconsHOEP_{YYYYMMDD}.xml\"\n)\nPRODUCTION_URL = \"http://reports.ieso.ca/public/GenOutputCapability/PUB_GenOutputCapability_{YYYYMMDD}.xml\"\nSOURCE = \"ieso.ca\"\n# IESO says \"Eastern Standard Time is used year round.\" This means daylight\n# savings is not used (that is called \"Eastern Daylight Time\"), and we need to\n# use UTC-5 rather than 'Canada/Eastern'.\nTIMEZONE = timezone(timedelta(hours=-5), name=\"UTC-5\")\nZONE_KEY = ZoneKey(\"CA-ON\")\n\n\ndef _fetch_xml(\n    logger: Logger,\n    session: Session | None,\n    target_datetime: datetime | None,\n    url_template: str,\n) -> tuple[date, ElementTree.Element | None]:\n    date_ = (target_datetime or datetime.now(TIMEZONE)).astimezone(TIMEZONE).date()\n\n    session = session or Session()\n    url = url_template.format(YYYYMMDD=date_.strftime(\"%Y%m%d\"))\n    response = session.get(url)\n\n    if not response.ok:\n        # Historical data is generally available for 3 months; requesting\n        # anything older returns an HTTP 404 error.\n        logger.info(f\"GET request to {url} failed\")\n        return date_, None\n\n    return date_, ElementTree.fromstring(response.text)\n\n\ndef _fetch_xmls(\n    logger: Logger,\n    session: Session,\n    target_datetime: datetime | None,\n    url_template: str,\n) -> dict[date, ElementTree.Element | None]:\n    # If target_datetime is not specified, it means that we are fetching data in a 'real-time' manner.\n    # Then, we fetch for the last 2 days to avoid missing last hour of the previous day.\n    date_xml = {}\n    if target_datetime is None:\n        for i in range(2):\n            target_datetime = datetime.now(TIMEZONE).astimezone(TIMEZONE) - timedelta(\n                days=i\n            )\n            date, xml = _fetch_xml(logger, session, target_datetime, url_template)\n            date_xml[date] = xml\n    else:\n        date, xml = _fetch_xml(logger, session, target_datetime, url_template)\n        date_xml[date] = xml\n    return date_xml\n\n\ndef _parse_hour(element: ElementTree.Element) -> int:\n    # Decrement the reported hour to convert from the hour-ending ([1, 24])\n    # convention used by the source to our hour-starting ([0, 23]) convention.\n    return int(element.findtext(NAMESPACE + \"Hour\")) - 1\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given region.\"\"\"\n    if zone_key != ZONE_KEY:\n        raise NotImplementedError(f\"unimplemented zone '{zone_key}'\")\n\n    date_xml = _fetch_xmls(logger, session, target_datetime, PRODUCTION_URL)\n    production_breakdowns = ProductionBreakdownList(logger)\n    for date_, xml in date_xml.items():\n        if xml is None:\n            continue\n\n        # Collect the source data into a dictionary keying ProductionMix objects by\n        # the time of day at which they occurred.\n        mixes: defaultdict[time, ProductionMix] = defaultdict(ProductionMix)\n        for generator in xml.iter(NAMESPACE + \"Generator\"):\n            try:\n                mode = MODES[generator.findtext(NAMESPACE + \"FuelType\")]\n            except KeyError as error:\n                logger.warning(error)\n                continue\n            for output in generator.iter(NAMESPACE + \"Output\"):\n                try:\n                    hour = _parse_hour(output)\n                except (TypeError, ValueError) as error:\n                    logger.warning(error)\n                    continue\n                # The \"EnergyMW\" element will occasionally be absent from the XML\n                # for a given plant at a given hour. In the browser, this is\n                # displayed as an \"N/A\" entry in the table.\n                generation = output.findtext(NAMESPACE + \"EnergyMW\")\n                mixes[time(hour=hour)].add_value(\n                    mode, None if generation is None else float(generation)\n                )\n\n        for time_, mix in mixes.items():\n            production_breakdowns.append(\n                datetime=datetime.combine(date_, time_, tzinfo=TIMEZONE),\n                production=mix,\n                source=SOURCE,\n                zoneKey=ZONE_KEY,\n            )\n\n    return production_breakdowns.to_list()\n\n\ndef fetch_price(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known power price per MWh of a given region.\"\"\"\n\n    if zone_key != ZONE_KEY:\n        raise NotImplementedError(f\"unimplemented zone '{zone_key}'\")\n\n    date_xml = _fetch_xmls(logger, session, target_datetime, PRICE_URL)\n    prices = PriceList(logger)\n    for date_, xml in date_xml.items():\n        if xml is None:\n            continue\n\n        # \"HOEP\" stands for \"Hourly Ontario Energy Price\". There also exists a\n        # 5-minute price, but its archives only go back roughly 4 days (see \"5\n        # Minute Market Clearing Price\" at http://www.ieso.ca/power-data ).\n        for hoep in xml.iter(NAMESPACE + \"HOEP\"):\n            try:\n                hour = _parse_hour(hoep)\n            except (TypeError, ValueError) as error:\n                logger.warning(error)\n                continue\n            price = hoep.findtext(NAMESPACE + \"Price\")\n            prices.append(\n                currency=\"CAD\",\n                datetime=datetime.combine(date_, time(hour=hour), tzinfo=TIMEZONE),\n                price=None if price is None else float(price),\n                source=SOURCE,\n                zoneKey=zone_key,\n            )\n\n    return prices.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known power exchange (in MW) between two regions.\"\"\"\n\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted((zone_key1, zone_key2))))\n\n    if sorted_zone_keys not in EXCHANGES.values():\n        raise NotImplementedError(f\"unimplemented exchange '{sorted_zone_keys}'\")\n\n    date_xml = _fetch_xmls(logger, session, target_datetime, EXCHANGE_URL)\n\n    exchanges = ExchangeList(logger)\n    for date_, xml in date_xml.items():\n        if xml is None:\n            continue\n\n        # Collect the source data into a dictionary keying exchange flows by the\n        # time of day at which they occurred for the exchange of interest.\n        flows: defaultdict[time, float] = defaultdict(float)\n        for intertie in xml.iter(NAMESPACE + \"IntertieZone\"):\n            zone_name = intertie.findtext(NAMESPACE + \"IntertieZoneName\")\n            if zone_name not in EXCHANGES:\n                logger.warning(\n                    f\"unrecognized intertie '{zone_name}', please implement!\"\n                )\n                continue\n            if EXCHANGES[zone_name] != sorted_zone_keys:\n                # Ignore exchanges that we aren't interested in.\n                continue\n            for actual in intertie.iter(NAMESPACE + \"Actual\"):\n                try:\n                    flow = float(actual.findtext(NAMESPACE + \"Flow\"))\n                    hour = _parse_hour(actual)\n                    # The source reports flows in twelve five-minute intervals\n                    # using an interval-ending convention (i.e., [1, 12]). Subtract\n                    # one from the interval and multiply the result by five to\n                    # convert to a minute-starting convention (0, 5, ..., 50, 55).\n                    minute = 5 * (int(actual.findtext(NAMESPACE + \"Interval\")) - 1)\n                except (TypeError, ValueError) as error:\n                    logger.warning(error)\n                    continue\n                # The IESO IntertieZone reports flows from the neighboring\n                # zone's perspective: positive = neighboring zone exporting\n                # to Ontario (i.e., flow INTO Ontario).\n                # For EM convention, positive netFlow = flow in the direction\n                # of the sorted_zone_keys arrow (zone1 -> zone2).\n                # - CA-ON->CA-QC: positive = QC exporting to ON = flow QC->ON\n                #   = opposite of arrow, so flip.\n                # - CA-MB->CA-ON: positive = MB exporting to ON = flow MB->ON\n                #   = same as arrow direction (MB is zone1), so no flip needed,\n                #   but the current sign is already handled by the else branch.\n                if (\n                    not sorted_zone_keys.startswith(\"CA-ON->\")\n                    or sorted_zone_keys == \"CA-ON->CA-QC\"\n                ):\n                    flow *= -1\n                flows[time(hour=hour, minute=minute)] += flow\n\n        for time_, flow in flows.items():\n            exchanges.append(\n                datetime=datetime.combine(date_, time_, tzinfo=TIMEZONE),\n                netFlow=flow,\n                source=SOURCE,\n                zoneKey=sorted_zone_keys,\n            )\n\n    return exchanges.to_list()\n\n\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the demand forecast (in MW) of Canada Ontario zone for 7 days ahead hourly.\"\"\"\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(TIMEZONE)\n\n    # Dictionary to store extracted data\n    consumption_list = TotalConsumptionList(logger)\n\n    # Extract the file in adequacy folder until 7 days later.\n    # They have forecast until 34 days, but depends at what time of the day the url is extracted, the 34th day might not be published yet\n    end_date = target_datetime + timedelta(days=7)\n\n    # Iterate on every available date\n    current_date = target_datetime\n    while current_date <= end_date:\n        # Extract Adequacy report\n        date_, xml = _fetch_xml(logger, session, current_date, ADEQUACY_URL)\n\n        # Define the namespace (if applicable)\n        NAMESPACE = \"{http://www.ieso.ca/schema}\"\n        ns = {\"ns0\": \"http://www.ieso.ca/schema\"}\n\n        forecast_date = xml.find(\".//ns0:DeliveryDate\", ns)\n\n        for forecast_ontario_demand in xml.findall(\".//ns0:ForecastOntDemand\", ns):\n            for demand in forecast_ontario_demand.findall(\".//ns0:Demand\", ns):\n                delivery_hour = demand.findtext(NAMESPACE + \"DeliveryHour\")\n                date_object = datetime.strptime(forecast_date.text, \"%Y-%m-%d\").replace(\n                    tzinfo=TIMEZONE\n                )\n                date_object = date_object.replace(hour=int(delivery_hour) - 1)\n                energy_mw = demand.findtext(NAMESPACE + \"EnergyMW\")\n\n                # Update consumption list\n                consumption_list.append(\n                    zoneKey=zone_key,\n                    datetime=date_object,\n                    consumption=float(energy_mw) if energy_mw is not None else None,\n                    source=SOURCE,\n                    sourceType=EventSourceType.forecasted,\n                )\n\n        current_date += timedelta(days=1)  # Go to next day\n\n    return consumption_list.to_list()\n\n\ndef read_adequacy_report(root, logger):\n    \"\"\"Helper function for fetch_wind_solar_forecasts() that reads Adequacy report for a given xml root\"\"\"\n    NAMESPACE = \"{http://www.ieso.ca/schema}\"\n    ns = {\"ns0\": \"http://www.ieso.ca/schema\"}\n\n    # Dictionary to store extracted data\n    production_list = ProductionBreakdownList(logger)\n    forecast_date = root.find(\".//ns0:DeliveryDate\", ns)\n\n    # Dictionary to store ProductionMix for each timestamp\n    mixes: dict[datetime, ProductionMix] = {}\n\n    # Iterate through InternalResource elements\n    for resource in root.findall(\".//ns0:InternalResource\", ns):\n        mode = resource.findtext(NAMESPACE + \"FuelType\")\n        if mode == \"Wind\" or mode == \"Solar\":\n            for c in resource.findall(\"ns0:Forecasts\", ns):\n                for value in c.findall(\"ns0:Forecast\", ns):\n                    date_object = datetime.strptime(\n                        forecast_date.text, \"%Y-%m-%d\"\n                    ).replace(tzinfo=TIMEZONE)\n                    delivery_hour = value.findtext(NAMESPACE + \"DeliveryHour\")\n                    date_object = date_object.replace(hour=int(delivery_hour) - 1)\n                    timestamp = date_object\n                    energy_mw = value.findtext(NAMESPACE + \"EnergyMW\")\n\n                    # Create production mix\n                    mix: defaultdict[datetime, ProductionMix] = defaultdict(\n                        ProductionMix\n                    )\n                    mix[date_object].add_value(\n                        mode.lower(),\n                        None if energy_mw is None else float(energy_mw),\n                        correct_negative_with_zero=True,\n                    )\n\n                    # Get or create ProductionMix for this timestamp\n                    if timestamp not in mixes:\n                        mixes[timestamp] = ProductionMix()\n\n                    # Add wind/solar output to the existing ProductionMix\n                    mixes[timestamp].add_value(\n                        mode.lower(),\n                        None if energy_mw is None else float(energy_mw),\n                        correct_negative_with_zero=True,\n                    )\n\n                    # Check if this datetime already exists in the production_list\n                    datetime_exists = any(\n                        item[\"datetime\"] == date_object for item in production_list\n                    )\n\n                    # Only append if the datetime doesn't exist yet\n                    if not datetime_exists:\n                        production_list.append(\n                            zoneKey=ZONE_KEY,\n                            datetime=date_object,\n                            production=mix[date_object],\n                            source=SOURCE,\n                            sourceType=EventSourceType.forecasted,\n                        )\n\n    return production_list\n\n\ndef read_VGForecastSummary_report(root, logger):\n    \"\"\"Helper function for fetch_wind_solar_forecasts() that reads VGForecastsSummary report for a given XML root.\"\"\"\n\n    ns = {\"ns0\": \"http://www.ieso.ca/schema\"}\n    production_list = ProductionBreakdownList(logger)\n\n    # Dictionary to store ProductionMix for each timestamp\n    mixes: dict[datetime, ProductionMix] = {}\n\n    for org_data in root.findall(\".//ns0:OrganizationData\", ns):\n        for fuel_data in org_data.findall(\".//ns0:FuelData\", ns):\n            fuel_type = fuel_data.find(\"ns0:FuelType\", ns).text.lower()\n\n            for resource in fuel_data.findall(\".//ns0:ResourceData\", ns):\n                zone = resource.find(\"ns0:ZoneName\", ns)\n\n                if zone.text == \"OntarioTotal\":\n                    for energy_forecast in resource.findall(\n                        \".//ns0:EnergyForecast\", ns\n                    ):\n                        forecast_date = energy_forecast.find(\"ns0:ForecastDate\", ns)\n                        base_date = datetime.strptime(\n                            forecast_date.text, \"%Y-%m-%d\"\n                        ).replace(tzinfo=TIMEZONE)\n\n                        for forecast_interval in energy_forecast.findall(\n                            \".//ns0:ForecastInterval\", ns\n                        ):\n                            forecast_hour_ending = forecast_interval.find(\n                                \"ns0:ForecastHour\", ns\n                            )\n                            timestamp = base_date.replace(\n                                hour=int(forecast_hour_ending.text) - 1\n                            )\n\n                            mw_output = forecast_interval.find(\"ns0:MWOutput\", ns)\n                            mw_value = (\n                                None if mw_output is None else float(mw_output.text)\n                            )\n\n                            # Get or create ProductionMix for this timestamp\n                            if timestamp not in mixes:\n                                mixes[timestamp] = ProductionMix()\n\n                            # Add wind/solar output to the existing ProductionMix\n                            mixes[timestamp].add_value(\n                                fuel_type,\n                                mw_value,\n                                correct_negative_with_zero=True,\n                            )\n\n    # Append all combined ProductionMix objects to production_list\n    for timestamp, mix in mixes.items():\n        production_list.append(\n            zoneKey=ZONE_KEY,\n            datetime=timestamp,\n            production=mix,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n\n    return production_list\n\n\nADEQUACY_URL = (\n    \"https://reports-public.ieso.ca/public/Adequacy2/PUB_Adequacy2_{YYYYMMDD}.xml\"\n)\nVG_FORECAST_SUMMARY = \"https://reports-public.ieso.ca/public/VGForecastSummary/PUB_VGForecastSummary_{YYYYMMDD}.xml\"\n\n\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the forecasts for wind and solar (in MW) of Canada Ontario zone for 7 days ahead.\"\"\"\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(TIMEZONE)\n\n    # Extract the file in adequacy folder until 7 days later.\n    # They have forecast until 34 days, but depends at what time of the day the url is extracted, the 34th day might not be published yet\n    end_date = target_datetime + timedelta(days=7)\n\n    # Direct iteration method\n    production_list = ProductionBreakdownList(logger)\n    current_date = target_datetime\n    while current_date <= end_date:\n        # First try to get the VG Forecast Summary report\n        date_, xml = _fetch_xml(logger, session, current_date, VG_FORECAST_SUMMARY)\n\n        # Check if the data is available before trying to read it\n        if xml is not None:\n            production_list_1 = read_VGForecastSummary_report(xml, logger)\n        else:\n            # When VG Forecast is not available, use Adequacy report instead\n            date_, xml = _fetch_xml(logger, session, current_date, ADEQUACY_URL)\n            production_list_1 = read_adequacy_report(xml, logger)\n\n        production_list = ProductionBreakdownList.merge_production_breakdowns(\n            [production_list, production_list_1], logger\n        )\n\n        current_date += timedelta(days=1)\n    return production_list.to_list()\n\n\ndef fetch_grid_alerts(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Requests the grid alerts for IESO.\n    For current emergency advisory notices: https://www.ieso.ca/Sector-Participants/RSS-Feeds/Emergency-Advisory-Notices\n    For current day 0 advisory notices (non-emergency): https://www.ieso.ca/Sector-Participants/RSS-Feeds/Day-0-Advisory-Notices-Summary\n    For archive: in https://www.ieso.ca/Sector-Participants/RSS-Feeds/Advisory-Notices-Archive\n    Url for archive table json: https://www.ieso.ca/ieso/api/table/data?source=958805C0C35B4BF3BB6A6EA429850C06&ctx=CF5ADB2D-E44E-4899-AFAF-E16C97A7A36F\n    \"\"\"\n    session = session or Session()\n\n    urls = [\n        # Current Emergency Advisory Notices\n        \"https://www.ieso.ca/ieso/api/table/data?source=E6324F9AEEA84B658C34E78C92E0BCEF&ctx=3435D509-B2FC-4B5D-824A-A21A8BC45822\",\n        # Current Day 0 Advisory Notices\n        \"https://www.ieso.ca/ieso/api/table/data?source=92EEB31A6F184529B467FD465EE8EFA2&ctx=DEA30159-2D04-48E5-9358-2B4FBAC28B83\",\n    ]\n\n    grid_alert_list = GridAlertList(logger)\n\n    for url in urls:\n        # Fetch the data from the URL\n        response = session.get(url)\n        json_data = response.json()\n        entries = json_data[0][\"TableRows\"]  # stored in a table\n\n        # Record events in grid_alert_list\n        for notice in entries:\n            alert_type = notice[\"Cells\"][0][\"Value\"]\n\n            # \"Alert\", \"Warning\" --> \"Informational\", \"Action\" --> \"Action\" based on https://www.ieso.ca/Sector-Participants/RSS-Feeds/Day-0-Advisory-Notices-Summary\n            if alert_type == \"Alert\" or alert_type == \"Warning\":\n                alert_type = GridAlertType.informational\n            elif alert_type == \"Action\":\n                alert_type = GridAlertType.action\n            else:\n                alert_type = GridAlertType.undefined\n\n            notice_content = notice[\"Cells\"][1][\"Value\"]\n\n            # Take the \"Updated At\" (the latest update)\n            issued_at = notice[\"Cells\"][3][\"Value\"]\n            issued_at_dt = datetime.strptime(issued_at, \"%a, %d %b %Y %H:%M\").replace(\n                tzinfo=TIMEZONE\n            )\n\n            soup = BeautifulSoup(notice_content, \"html.parser\")\n            link = soup.find_all(\"a\")[0][\"href\"]\n            subject = soup.find_all(\"a\")[0][\"title\"]\n\n            # Extract the body\n            url2 = \"https://www.ieso.ca\" + link\n            response2 = session.get(url2)\n            soup2 = BeautifulSoup(response2.text, \"html.parser\")\n\n            # Find start and end times before the table\n            start_time = soup2.find_all(\"p\")[0].get_text(strip=True)\n            start_time_dt = datetime.strptime(\n                start_time, \"Start: %a, %d %b %Y %H:%M EST\"\n            ).replace(tzinfo=TIMEZONE)\n            end_time = soup2.find_all(\"p\")[1].get_text(strip=True)\n            end_time_dt = datetime.strptime(\n                end_time, \"End: %a, %d %b %Y %H:%M EST\"\n            ).replace(tzinfo=TIMEZONE)\n\n            # Find all <tr> rows\n            rows = soup2.find_all(\"tr\")\n\n            # Extract the 2nd <td> (description) from each row\n            for row in rows:\n                tds = row.find_all(\"td\")\n                if len(tds) >= 2:\n                    description = tds[1].get_text(separator=\" \", strip=True)\n\n            grid_alert_list.append(\n                zoneKey=zone_key,\n                locationRegion=None,\n                source=SOURCE,\n                alertType=alert_type,\n                message=subject + \"\\n\" + description,\n                issuedTime=issued_at_dt,\n                startTime=start_time_dt,  # if None, it defaults to issuedTime\n                endTime=end_time_dt,\n            )\n    return grid_alert_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    from pprint import pprint\n\n    \"\"\"\n    now = datetime.now(timezone.utc)\n    two_months_ago = now - timedelta(days=60)\n    two_years_ago = now - timedelta(days=2 * 365)\n\n    print(\"fetch_production() ->\")\n    print(fetch_production(), end=\"\\n\\n\")\n\n    print(\"data should be for \" + now.astimezone(TIMEZONE).strftime(\"%Y-%m-%d\"))\n    print('fetch_production(\"CA-ON\", target_datetime=now) ->')\n    print(fetch_production(ZoneKey(\"CA-ON\"), target_datetime=now), end=\"\\n\\n\")\n\n    print(\"we expect results for ~2 months ago\")\n    print(\"fetch_production(target_datetime=two_months_ago) ->\")\n    print(fetch_production(target_datetime=two_months_ago), end=\"\\n\\n\")\n\n    print(\"there are likely no results for ~2 years ago\")\n    print(\"fetch_production(target_datetime=two_years_ago) ->\")\n    print(fetch_production(target_datetime=two_years_ago), end=\"\\n\\n\")\n\n    print(\"fetch_price() ->\")\n    print(fetch_price(), end=\"\\n\\n\")\n\n    print(\"data should be for \" + now.astimezone(TIMEZONE).strftime(\"%Y-%m-%d\"))\n    print(\"fetch_price(target_datetime=now) ->\")\n    print(fetch_price(target_datetime=now), end=\"\\n\\n\")\n\n    print(\"we expect results for ~2 months ago\")\n    print(\"fetch_price(target_datetime=two_months_ago) ->\")\n    print(fetch_price(target_datetime=two_months_ago), end=\"\\n\\n\")\n\n    print(\"there are likely no results for ~2 years ago\")\n    print(\"fetch_price(target_datetime=two_years_ago) ->\")\n    print(fetch_price(target_datetime=two_years_ago), end=\"\\n\\n\")\n\n    print('fetch_exchange(\"CA-ON\", \"US-NY-NYIS\") ->')\n    print(fetch_exchange(ZoneKey(\"CA-ON\"), ZoneKey(\"US-NY-NYIS\")), end=\"\\n\\n\")\n\n    print('fetch_exchange(\"CA-ON\", \"CA-QC\", target_datetime=now) ->')\n    print(\n        fetch_exchange(ZoneKey(\"CA-ON\"), ZoneKey(\"CA-QC\"), target_datetime=now),\n        end=\"\\n\\n\",\n    )\n\n    print(\"Ontario-to-Manitoba must be opposite sign from reported IESO values\")\n    print('fetch_exchange(\"CA-ON\", \"CA-MB\", target_datetime=now) ->')\n    print(\n        fetch_exchange(ZoneKey(\"CA-ON\"), ZoneKey(\"CA-MB\"), target_datetime=now),\n        end=\"\\n\\n\",\n    )\n\n    print(\"data should be for \" + now.astimezone(TIMEZONE).strftime(\"%Y-%m-%d\"))\n    print('fetch_exchange(\"CA-ON\", \"CA-QC\", target_datetime=now) ->')\n    print(\n        fetch_exchange(ZoneKey(\"CA-ON\"), ZoneKey(\"CA-QC\"), target_datetime=now),\n        end=\"\\n\\n\",\n    )\n\n    print(\"we expect results for ~2 months ago\")\n    print('fetch_exchange(\"CA-ON\", \"CA-QC\", target_datetime=two_months_ago) ->')\n    print(\n        fetch_exchange(\n            ZoneKey(\"CA-ON\"), ZoneKey(\"CA-QC\"), target_datetime=two_months_ago\n        ),\n        end=\"\\n\\n\",\n    )\n\n    print(\"there are likely no results for ~2 years ago\")\n    print('fetch_exchange(\"CA-ON\", \"CA-QC\", target_datetime=two_years_ago) ->')\n    print(\n        fetch_exchange(\n            ZoneKey(\"CA-ON\"), ZoneKey(\"CA-QC\"), target_datetime=two_years_ago\n        ),\n        end=\"\\n\\n\",\n    )\n\n    print(\"requesting an exchange with Nova Scotia should raise exception\")\n    print('fetch_exchange(\"CA-ON\", \"CA-NS\")) ->')\n    try:\n        fetch_exchange(ZoneKey(\"CA-ON\"), ZoneKey(\"CA-NS\"))\n    except NotImplementedError:\n        print(\"Task failed successfully\")\n    \"\"\"\n\n    # print(\"Requesting fetch_wind_solar_forecasts\")\n    # pprint(fetch_wind_solar_forecasts())\n\n    # print(\"Requesting fetch_consumption_forecast\")\n    # pprint(fetch_consumption_forecast())\n\n    pprint(fetch_grid_alerts())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CA_QC.py",
    "content": "from datetime import datetime\nfrom logging import Logger, getLogger\nfrom pprint import pprint\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.types import ZoneKey\n\nUS_PROXY = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app\"\nHOST_PARAM = \"?host=https://hydroquebec.com\"\nDATA_PATH = \"data/documents-donnees/donnees-ouvertes/json\"\nPRODUCTION_URL = f\"{US_PROXY}/{DATA_PATH}/production.json{HOST_PARAM}\"\nCONSUMPTION_URL = f\"{US_PROXY}/{DATA_PATH}/demande.json{HOST_PARAM}\"\nSOURCE = \"hydroquebec.com\"\nTIMEZONE = ZoneInfo(\"America/Montreal\")\n\nMODE_MAPPING = {\n    \"hydraulique\": \"hydro\",\n    \"thermique\": \"gas\",  # See Github issue #3218, Québec's thermal generation is at Bécancour gas turbine.\n    \"solaire\": \"solar\",\n    \"eolien\": \"wind\",\n    \"autres\": \"biomass\",  # Other renewables, mostly biomass. See Github #3218\n}\n\nIGNORED_KEYS = {\"total\"}\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"CA-QC\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given region.\"\"\"\n\n    if target_datetime is not None:\n        raise NotImplementedError(\n            \"CA-QC parser does not support historical data requests.\"\n        )\n\n    data = _fetch_quebec_production(session)\n    production_breakdown_list = ProductionBreakdownList(logger)\n    now = datetime.now(tz=TIMEZONE)\n\n    for elem in data:\n        values = elem[\"valeurs\"]\n        if not isinstance(values, dict):\n            continue\n\n        # Remove ignored keys and skip if no meaningful data remains\n        for key in IGNORED_KEYS:\n            values.pop(key, None)\n        if not values:\n            continue\n\n        # Parse timestamp and skip if invalid or future\n        if not isinstance(elem[\"date\"], str):\n            continue\n        timestamp = datetime.fromisoformat(elem[\"date\"]).replace(tzinfo=TIMEZONE)\n        if timestamp > now:\n            continue\n\n        # Process production data\n        production = ProductionMix()\n        for key, value in values.items():\n            if key in MODE_MAPPING:\n                production.add_value(\n                    MODE_MAPPING[key], value, correct_negative_with_zero=True\n                )\n            else:\n                logger.warning(\n                    f\"CA-QC: Unknown production mode '{key}' in data from hydroquebec\"\n                )\n\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=timestamp,\n            production=production,\n            source=SOURCE,\n        )\n    return production_breakdown_list.to_list()\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"CA-QC\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    data = _fetch_quebec_consumption(session)\n\n    consumption = TotalConsumptionList(logger)\n    for elem in data:\n        if \"demandeTotal\" in elem[\"valeurs\"]:\n            consumption.append(\n                zoneKey=zone_key,\n                datetime=datetime.fromisoformat(elem[\"date\"]).replace(tzinfo=TIMEZONE),\n                consumption=elem[\"valeurs\"][\"demandeTotal\"],\n                source=SOURCE,\n            )\n    return consumption.to_list()\n\n\ndef _fetch_quebec_production(\n    session: Session | None = None, logger: Logger = getLogger(__name__)\n) -> list[dict[str, str | dict[str, float]]]:\n    s = session or Session()\n    response = s.get(PRODUCTION_URL)\n\n    if not response.ok:\n        logger.info(\n            f\"CA-QC: failed getting requested production data from hydroquebec - URL {PRODUCTION_URL}\"\n        )\n    return response.json()[\"details\"]\n\n\ndef _fetch_quebec_consumption(\n    session: Session | None = None, logger: Logger = getLogger(__name__)\n) -> list[dict[str, Any]]:\n    s = session or Session()\n    response = s.get(CONSUMPTION_URL)\n\n    if not response.ok:\n        logger.info(\n            f\"CA-QC: failed getting requested consumption data from hydroquebec - URL {CONSUMPTION_URL}\"\n        )\n    return response.json()[\"details\"]\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    test_logger = getLogger(__name__)\n\n    print(\"fetch_production() ->\")\n    pprint(fetch_production(logger=test_logger))\n\n    print(\"fetch_consumption() ->\")\n    pprint(fetch_consumption(logger=test_logger))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CA_SK.py",
    "content": "from datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\nTIMEZONE = ZoneInfo(\"America/Regina\")\nPRODUCTION_URL = (\n    \"https://www.saskpower.com/ignitionapi/PowerUseDashboard/GetPowerUseDashboardData\"\n)\nCONSUMPTION_URL = \"https://www.saskpower.com/ignitionapi/Content/GetNetLoad\"\nPRODUCTION_MAPPING = {\n    \"Hydro\": \"hydro\",\n    \"Wind\": \"wind\",\n    \"Solar\": \"solar\",\n    \"Natural Gas\": \"gas\",\n    \"Coal\": \"coal\",\n    # \"Other\" represents internal consumption, losses, heat recovery facilities\n    # and small independent power producers.\n    \"Other\": \"unknown\",\n}\nUSER_AGENT = (\n    \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 \"\n    \"(KHTML, like Gecko) Chrome/75.0.3770.142 Safari/537.36\"\n)\n\n\ndef _request(\n    session: Session | None,\n    target_datetime: datetime | None,\n    url: str,\n    zone_key: ZoneKey,\n) -> dict | str:\n    # The source does not offer historical data, so bail out if it's requested.\n    if target_datetime:\n        raise ParserException(\"CA_SK.py\", \"Unable to fetch historical data\", zone_key)\n    # The zone key must be \"CA-SK\"; bail out otherwise.\n    if zone_key != \"CA-SK\":\n        raise ParserException(\"CA_SK.py\", f\"Cannot parse zone '{zone_key}'\", zone_key)\n    session = session or Session()\n    # Mimic a user browser in the headers or the API will respond with a 403.\n    response = session.get(url, headers={\"user-agent\": USER_AGENT})\n    if not response.ok:\n        raise ParserException(\n            \"CA_SK.py\",\n            f\"Request to {url} failed. Response Code: {response.status_code}\\n\"\n            f\"Error:\\n{response.text}\",\n            zone_key,\n        )\n    return response.json()\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"CA-SK\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    payload = _request(session, target_datetime, PRODUCTION_URL, zone_key)\n    if not isinstance(payload, dict):\n        raise ParserException(\"CA_SK.py\", \"Unexpected payload type\", zone_key)\n    # Date is in the format \"Jan 01, 2020\"\n    date = datetime.strptime(payload[\"SupplyDataText\"], \"%b %d, %Y\")\n    production_mix = ProductionMix()\n    for generation_by_type in payload[\"PowerCacheData\"][\"generationByType\"]:\n        production_mix.add_value(\n            PRODUCTION_MAPPING[generation_by_type[\"type\"]],\n            generation_by_type[\"totalGenerationForType\"],\n        )\n    production_breakdown_list = ProductionBreakdownList(logger)\n    # Copy the daily average returned by the API into hourly values. This is a\n    # bit of a hack, but it's required because the back-end requires hourly\n    # datapoints while the API only provides daily averages.\n    for hour in range(24):\n        production_breakdown_list.append(\n            datetime=date.replace(hour=hour, tzinfo=TIMEZONE),\n            production=production_mix,\n            source=\"saskpower.com\",\n            zoneKey=ZoneKey(zone_key),\n        )\n    return production_breakdown_list.to_list()\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"CA-SK\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    payload = _request(session, target_datetime, CONSUMPTION_URL, zone_key)\n    if not isinstance(payload, str):\n        raise ParserException(\"CA_SK.py\", \"Unexpected payload type\", zone_key)\n    # The source refreshes every 5 minutes, so we assume the current data is\n    # from 5 minutes before the most recent multiple of 5 minutes.\n    now = datetime.now(TIMEZONE)\n    assumed_datetime = now.replace(second=0, microsecond=0) - timedelta(\n        minutes=(5 + now.minute % 5)\n    )\n    total_consumption = TotalConsumptionList(logger)\n    total_consumption.append(\n        consumption=float(payload),\n        datetime=assumed_datetime,\n        source=\"saskpower.com\",\n        zoneKey=zone_key,\n    )\n    return total_consumption.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CEB.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Quarter-hourly data parser for Sri Lanka\nFetches data for the previous day in 15-minute increments\nData is from the backend for the load curve graph on https://cebcare.ceb.lk/gensum/details\n\"\"\"\n\nimport json\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\n# The request library is used to fetch content through HTTP\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nTIMEZONE = ZoneInfo(\"Asia/Colombo\")\nGENERATION_BREAKDOWN_URL = \"https://cebcare.ceb.lk/GenSum/GetLoadCurveData\"\nSOURCE_NAME = \"ceb.lk\"\n\nPRODUCTION_MAPPING = {\n    \"SPP Biomass\": \"biomass\",\n    \"Coal\": \"coal\",\n    \"Thermal-Oil\": \"oil\",\n    \"SPP Minihydro\": \"hydro\",\n    \"Major Hydro\": \"hydro\",\n    \"Solar\": \"solar\",\n    \"Wind\": \"wind\",\n}\n\n\n@refetch_frequency(timedelta(hours=24))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"LK\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    \"\"\"Requests the previous day's production mix (in MW) for Sri Lanka, per quarter-hour\"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE)\n\n    if session is None:\n        session = Session()\n\n    params = {\n        \"date\": target_datetime.strftime(\"%Y-%m-%d\"),\n    }\n\n    response = session.get(GENERATION_BREAKDOWN_URL, params=params)\n\n    if not response.ok:\n        raise ParserException(\n            \"CEB.py\",\n            f\"Failed to fetch production data. Response Code: {response.status_code}\\nError:\\n{response.text}\",\n            zone_key,\n        )\n\n    source_data = json.loads(\n        response.json()\n    )  # Response is double encoded; a JSON array encoded as a JSON string\n\n    production_data = ProductionBreakdownList(logger)\n\n    for quarter_hourly_source_data in source_data:\n        production = ProductionMix()\n\n        for generation_type, outputInMW in quarter_hourly_source_data.items():\n            if generation_type == \"DateTime\":\n                continue\n            elif generation_type in PRODUCTION_MAPPING:\n                production.add_value(PRODUCTION_MAPPING[generation_type], outputInMW)\n            else:\n                logger.warning(\n                    f\"Unknown generation type {generation_type}\",\n                    extra={\"zone_key\": zone_key},\n                )\n\n        production_data.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(\n                quarter_hourly_source_data[\"DateTime\"]\n            ).replace(tzinfo=TIMEZONE),\n            production=production,\n            source=SOURCE_NAME,\n        )\n\n    return production_data.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CENACE.py",
    "content": "#!/usr/bin/env python3\n\nimport json\nimport urllib\nfrom datetime import datetime, timedelta\nfrom io import StringIO\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\nfrom dateutil import tz\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nCAISO_PROXY = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app\"\nMX_PRODUCTION_URL = f\"{CAISO_PROXY}/Paginas/SIM/Reportes/EnergiaGeneradaTipoTec.aspx?host=https://www.cenace.gob.mx\"\nMX_EXCHANGE_URL = f\"{CAISO_PROXY}/Paginas/Publicas/Info/DemandaRegional.aspx?host=https://www.cenace.gob.mx\"\n\nEXCHANGES = {\n    \"MX-NO->MX-NW\": \"IntercambioNTE-NOR\",\n    \"MX-NE->MX-NO\": \"IntercambioNES-NTE\",\n    \"MX-NE->MX-OR\": \"IntercambioNES-ORI\",\n    \"MX-OR->MX-PN\": \"IntercambioORI-PEN\",\n    \"MX-CE->MX-OR\": \"IntercambioORI-CEL\",\n    \"MX-OC->MX-OR\": \"IntercambioOCC-ORI\",\n    \"MX-CE->MX-OC\": \"IntercambioOCC-CEL\",\n    \"MX-NE->MX-OC\": \"IntercambioNES-OCC\",\n    \"MX-NO->MX-OC\": \"IntercambioNTE-OCC\",\n    \"MX-NW->MX-OC\": \"IntercambioNOR-OCC\",\n    \"MX->US-CAL-CISO\": \"IntercambioUSA-BCA\",\n    \"MX-BC->US-CAL-CISO\": \"IntercambioUSA-BCA\",\n    \"MX->US-TEX-ERCO\": \"DummyValueNotUsed\",\n    \"MX-NO->US-TEX-ERCO\": \"IntercambioUSA-NTE\",\n    \"MX-NE->US-TEX-ERCO\": \"IntercambioUSA-NES\",\n    \"BZ->MX\": \"IntercambioPEN-BEL\",\n    \"BZ->MX-PN\": \"IntercambioPEN-BEL\",\n}\n\nREGION_MAPPING = {\n    \"MX-BC\": \"BCA\",\n    \"MX-BCS\": \"BCS\",\n    \"MX-NW\": \"NOR\",\n    \"MX-NO\": \"NTE\",\n    \"MX-NE\": \"NES\",\n    \"MX-OC\": \"OCC\",\n    \"MX-CE\": \"CEL\",\n    \"MX-OR\": \"ORI\",\n    \"MX-PN\": \"PEN\",\n}\n\nMAPPING = {\n    \"Eolica\": \"wind\",\n    \"Fotovoltaica\": \"solar\",\n    \"Biomasa\": \"biomass\",\n    \"Carboelectrica\": \"coal\",\n    \"Ciclo Combinado\": \"gas\",\n    \"Geotermoelectrica\": \"geothermal\",\n    \"Hidroelectrica\": \"hydro\",\n    \"Nucleoelectrica\": \"nuclear\",\n    \"Combustion Interna\": \"unknown\",\n    \"Termica Convencional\": \"unknown\",\n    \"Turbo Gas\": \"gas\",\n}\nSOURCE = \"cenace.gob.mx\"\nTIMEZONE = ZoneInfo(\"America/Mexico_City\")\n\n# cache where the data for whole months is stored as soon as it has been fetched once\nDATA_CACHE = {}\n\n\ndef parse_date(date, hour):\n    tzoffset = tz.tzoffset(\"CST\", -3600 * 6)\n    dt = datetime.strptime(date, \"%d/%m/%Y\")\n    dt = dt.replace(hour=int(hour) - 1, tzinfo=tzoffset)\n    return dt\n\n\ndef fetch_csv_for_date(dt, session: Session | None = None):\n    \"\"\"\n    Fetches the whole month of the give datetime.\n    returns the data as a DataFrame.\n    throws an exception data is not available.\n    \"\"\"\n    session = session or Session()\n\n    response = session.get(MX_PRODUCTION_URL)\n    response.raise_for_status()\n\n    # extract necessary viewstate, validation tokens\n    soup = BeautifulSoup(response.content, \"html.parser\")\n    viewstate = soup.find(\"input\", {\"name\": \"__VIEWSTATE\"})[\"value\"]\n    eventvalidation = soup.find(\"input\", {\"name\": \"__EVENTVALIDATION\"})[\"value\"]\n\n    # format date string for the requested date\n    datestr = dt.strftime(\"%m/%d/%Y\")\n    client_state = {\"minDateStr\": f\"{datestr} 0:0:0\", \"maxDateStr\": f\"{datestr} 0:0:0\"}\n\n    # build parameters for POST request\n    parameters = {\n        \"__VIEWSTATE\": viewstate,\n        \"__EVENTVALIDATION\": eventvalidation,\n        \"ctl00_ContentPlaceHolder1_FechaConsulta_ClientState\": json.dumps(client_state),\n        \"ctl00$ContentPlaceHolder1$GridRadResultado$ctl00$ctl04$gbccolumn.x\": \"0\",\n        \"ctl00$ContentPlaceHolder1$GridRadResultado$ctl00$ctl04$gbccolumn.y\": \"0\",\n    }\n\n    # urlencode the data in the weird form which is expected by the API\n    # plus signs MUST be contained in the date strings but MAY NOT be contained in the VIEWSTATE...\n    data = urllib.parse.urlencode(parameters, quote_via=urllib.parse.quote).replace(\n        \"%2B0\", \"+0\"\n    )\n\n    response = session.post(\n        MX_PRODUCTION_URL,\n        data=data,\n        headers={\n            \"Content-Type\": \"application/x-www-form-urlencoded\",\n        },\n    )\n    response.raise_for_status()\n\n    # API returns normally status 200 but content type text/html when data is missing\n    if \"Content-Type\" not in response.headers or \"text/html\" in response.headers.get(\n        \"Content-Type\", \"\"\n    ):\n        return None\n\n    # skip non-csv data, the header starts with \"Sistema\"\n    csv_str = response.text\n    df = pd.read_csv(\n        StringIO(csv_str),\n        skiprows=7,\n    )\n\n    # cleanup and parse the data\n    df.columns = df.columns.str.strip()\n\n    # transform 01-24 entries where 24 means 00 the next day\n    df[\"Hora\"] = df[\"Hora\"].apply(lambda x: \"00\" if int(x) == 24 else f\"{int(x):02d}\")\n    df[\"Dia\"] = pd.to_datetime(df[\"Dia\"], format=\"%d/%m/%Y\")\n    df.loc[df[\"Hora\"] == \"00\", \"Dia\"] = df[\"Dia\"] + pd.Timedelta(days=1)\n\n    # The hour column has been seen at least once (3rd Nov 2024) to include 1-25\n    # hours rather than the expected 1-24, due to this, we are for now dropping\n    # such entries if they show up\n    df = df.drop(df[df[\"Hora\"] == \"25\"].index)\n\n    # create datetime objects\n    df[\"Dia\"] = df[\"Dia\"].dt.strftime(\"%d/%m/%Y\")\n    df[\"instante\"] = pd.to_datetime(df[\"Dia\"] + \" \" + df[\"Hora\"], format=\"%d/%m/%Y %H\")\n    df[\"instante\"] = df[\"instante\"].dt.tz_localize(TIMEZONE)\n    return df\n\n\ndef convert_production(series: pd.Series) -> ProductionMix:\n    mix = ProductionMix()\n\n    for name, val in series.items():\n        name = name.strip()\n        if isinstance(val, float | int):\n            mix.add_value(MAPPING.get(name, \"unknown\"), val)\n\n    return mix\n\n\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    if zone_key != \"MX\":\n        raise ValueError(f\"MX parser cannot fetch production for zone {zone_key}\")\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE)\n\n    original_target_datetime = target_datetime\n    df = None\n    up_to_months = 6  # Try up to 6 previous months\n    for _ in range(up_to_months):\n        cache_key = target_datetime.strftime(\"%Y-%m\")\n        if cache_key in DATA_CACHE:\n            df = DATA_CACHE[cache_key]\n            break\n        else:\n            df = fetch_csv_for_date(target_datetime, session=session)\n            if df is not None and not df.empty:\n                DATA_CACHE[cache_key] = df\n                break\n            else:\n                logger.warning(f\"No data found for {cache_key}. Trying previous month.\")\n                target_datetime = (\n                    target_datetime.replace(day=1) - timedelta(days=1)\n                ).replace(day=1)\n\n    if df is None or df.empty:\n        raise Exception(\n            f\"No data found for {original_target_datetime}, or any previous {up_to_months} months.\"\n        )\n\n    production = ProductionBreakdownList(logger)\n    for _idx, series in df.iterrows():\n        production.append(\n            zoneKey=zone_key,\n            datetime=series[\"instante\"].to_pydatetime(),\n            production=convert_production(series),\n            source=SOURCE,\n        )\n    return production.to_list()\n\n\ndef fetch_MX_exchange(sorted_zone_keys: ZoneKey, s: Session) -> float:\n    \"\"\"Finds current flow between two Mexican control areas.\"\"\"\n    req = s.get(MX_EXCHANGE_URL, headers={\"User-Agent\": \"Mozilla/5.0\"})\n    soup = BeautifulSoup(req.text, \"html.parser\")\n    # cenace html uses unicode hyphens instead of minus signs and , as thousand separator\n    trantab = str.maketrans({chr(8208): chr(45), \",\": \"\"})\n    if sorted_zone_keys == \"MX->US-TEX-ERCO\":\n        exchange_div1 = soup.find(\"div\", attrs={\"id\": \"IntercambioUSA-NTE\"})\n        exchange_div2 = soup.find(\"div\", attrs={\"id\": \"IntercambioUSA-NES\"})\n        val1, val2 = exchange_div1.text, exchange_div2.text\n        val1 = val1.translate(trantab)\n        val2 = val2.translate(trantab)\n        flow = float(val1) + float(val2)\n    else:\n        exchange_div = soup.find(\"div\", attrs={\"id\": EXCHANGES[sorted_zone_keys]})\n        val = exchange_div.text\n        val = val.translate(trantab)\n        flow = float(val)\n\n    if sorted_zone_keys in [\"BZ->MX\", \"BZ->MX-PN\", \"MX-CE->MX-OR\", \"MX-CE->MX-OC\"]:\n        # reversal needed for these zones due to EM ordering\n        flow = -1 * flow\n\n    return flow\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known power exchange (in MW) between two zones.\"\"\"\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    if sorted_zone_keys not in EXCHANGES:\n        raise NotImplementedError(f\"Exchange pair not supported: {sorted_zone_keys}\")\n\n    s = session or Session()\n\n    netflow = fetch_MX_exchange(sorted_zone_keys, s)\n    exchange = ExchangeList(logger)\n    exchange.append(\n        zoneKey=sorted_zone_keys,\n        datetime=datetime.now(tz=TIMEZONE),\n        netFlow=netflow,\n        source=SOURCE,\n    )\n\n    return exchange.to_list()\n\n\n@refetch_frequency(timedelta(hours=1))\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Gets the consumption data for a region using the live dashboard.\"\"\"\n    # TODO the calls could be improved since we can get all the data in one call.\n    if session is None:\n        session = Session()\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n    response: Response = session.get(\n        MX_EXCHANGE_URL, headers={\"User-Agent\": \"Mozilla/5.0\"}\n    )\n    if not response.ok:\n        raise ParserException(\n            \"CENACE.py\",\n            f\"[{response.status_code}] Demand dashboard could not be reached: {response.text}\",\n            zone_key,\n        )\n    soup = BeautifulSoup(response.text, \"html.parser\")\n    demand_td = soup.find(\n        \"td\", attrs={\"id\": f\"Demanda{REGION_MAPPING[zone_key]}\", \"class\": \"num\"}\n    )\n    if demand_td is None:\n        raise ParserException(\"CENACE.py\", \"Could not find demand cell\", zone_key)\n    demand = float(demand_td.text.replace(\",\", \"\"))\n    if zone_key == \"MX-BC\" or zone_key == \"MX-BCS\":\n        timezone = \"America/Tijuana\"\n    else:\n        timezone = \"America/Mexico_City\"\n    consumption_list = TotalConsumptionList(logger)\n    consumption_list.append(\n        zoneKey=zone_key,\n        datetime=datetime.now(tz=ZoneInfo(timezone)),\n        consumption=demand,\n        source=\"cenace.gob.mx\",\n    )\n    return consumption_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(\n        fetch_production(\n            ZoneKey(\"MX\"), target_datetime=datetime(year=2019, month=7, day=1)\n        )\n    )\n    print(\"fetch_exchange(MX-NO, MX-NW)\")\n    print(fetch_exchange(ZoneKey(\"MX-NO\"), ZoneKey(\"MX-NW\")))\n    print(\"fetch_exchange(MX-OR, MX-PN)\")\n    print(fetch_exchange(ZoneKey(\"MX-OR\"), ZoneKey(\"MX-PN\")))\n    print(\"fetch_exchange(MX-NE, MX-OC)\")\n    print(fetch_exchange(ZoneKey(\"MX-NE\"), ZoneKey(\"MX-OC\")))\n    print(\"fetch_exchange(MX-NE, MX-NO)\")\n    print(fetch_exchange(ZoneKey(\"MX-NE\"), ZoneKey(\"MX-NO\")))\n    print(\"fetch_exchange(MX-OC, MX-OR)\")\n    print(fetch_exchange(ZoneKey(\"MX-OC\"), ZoneKey(\"MX-OR\")))\n    print(\"fetch_exchange(MX-NE, US-TEX-ERCO)\")\n    print(fetch_exchange(ZoneKey(\"MX-NE\"), ZoneKey(\"US-TEX-ERCO\")))\n    print(\"fetch_exchange(MX-CE, MX-OC)\")\n    print(fetch_exchange(ZoneKey(\"MX-CE\"), ZoneKey(\"MX-OC\")))\n    print(\"fetch_exchange(MX-PN, BZ)\")\n    print(fetch_exchange(ZoneKey(\"MX-PN\"), ZoneKey(\"BZ\")))\n    print(\"fetch_exchange(MX-NO, MX-OC)\")\n    print(fetch_exchange(ZoneKey(\"MX-NO\"), ZoneKey(\"MX-OC\")))\n    print(\"fetch_exchange(MX-NO, US-TEX-ERCO)\")\n    print(fetch_exchange(ZoneKey(\"MX-NO\"), ZoneKey(\"US-TEX-ERCO\")))\n    print(\"fetch_exchange(MX-NE, MX-OR)\")\n    print(fetch_exchange(ZoneKey(\"MX-NE\"), ZoneKey(\"MX-OR\")))\n    print(\"fetch_exchange(MX-CE, MX-OR)\")\n    print(fetch_exchange(ZoneKey(\"MX-CE\"), ZoneKey(\"MX-OR\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CH.py",
    "content": "from datetime import datetime, timedelta, timezone\nfrom io import StringIO\nfrom logging import Logger, getLogger\n\nimport pandas as pd\nfrom requests import Session\n\nfrom electricitymap.contrib.parsers import ENTSOE\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef get_solar_capacity_at(target_datetime: datetime) -> float:\n    \"\"\"Returns the solar capacity (in MW) at a given time.\n\n    References:\n        https://www.uvek-gis.admin.ch/BFE/storymaps/EE_Elektrizitaetsproduktionsanlagen/?lang=en\n        https://www.uvek-gis.admin.ch/BFE/storymaps/EE_Elektrizitaetsproduktionsanlagen/data/solar.csv\n    \"\"\"\n\n    # Prepare historical records\n    # Values before 2015 are ignored as that is the absolute earliest we have some confidence in the data we are\n    # collecting and flowtracing (2015 is when the ENTSO-E transparency platform launched).\n    historical_data = \"\"\"\n        Power_sum,Year,Plant_count\n        1398.217,2015,46162\n        1656.707,2016,56830\n        1875.034,2017,70074\n        2107.374,2018,83239\n        2398.745,2019,97776\n        2831.102,2020,117258\n        3370.261,2021,140428\n        4080.415,2022,173068\n        5094.375,2023,216440\n        5108.034,2024,216918\n        \"\"\"\n\n    historical_capacities = pd.read_csv(\n        StringIO(historical_data),\n        names=[\"installed capacity in megawatts\", \"year\", \"number of plants\"],\n        header=0,\n        index_col=[\"year\"],\n    )\n    historical_capacities.index = pd.to_datetime(\n        historical_capacities.index, format=\"%Y\", utc=True\n    )\n\n    # mask all rows earlier than target date (use the earliest date in dataset if target date is even earlier)\n    dt = max(\n        target_datetime.astimezone(timezone.utc), historical_capacities.index.min()\n    )\n    mask = historical_capacities.index <= dt\n    return historical_capacities[mask].iloc[-1].loc[\"installed capacity in megawatts\"]\n\n\ndef fetch_swiss_exchanges(session, target_datetime, logger):\n    \"\"\"Returns the total exchanges of Switzerland with its neighboring countries.\"\"\"\n    swiss_transmissions = {}\n    for exchange_key in [\"AT\", \"DE\", \"IT\", \"FR\"]:\n        exchanges = ENTSOE.fetch_exchange(\n            zone_key1=ZoneKey(\"CH\"),\n            zone_key2=ZoneKey(exchange_key),\n            session=session,\n            target_datetime=target_datetime,\n            logger=logger,\n        )\n        if not exchanges:\n            continue\n\n        for exchange in exchanges:\n            dt = exchange[\"datetime\"]\n            if dt not in swiss_transmissions:\n                swiss_transmissions[dt] = exchange[\"netFlow\"]\n            else:\n                swiss_transmissions[dt] += exchange[\"netFlow\"]\n\n    return swiss_transmissions\n\n\ndef fetch_swiss_consumption(\n    session: Session, target_datetime: datetime, logger: Logger\n):\n    \"\"\"Returns the total consumption of Switzerland.\"\"\"\n    consumptions = ENTSOE.fetch_consumption(\n        zone_key=ZoneKey(\"CH\"),\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n    )\n    return {c[\"datetime\"]: c[\"consumption\"] for c in consumptions}\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"CH\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    \"\"\"\n    Returns the total production by type for Switzerland.\n    Currently, the majority of the run-of-river production is missing.\n    The difference between the sum of all production types and the total production is allocated as 'unknown'.\n    The total production is calculated as sum of the consumption, storage and net imports.\n    \"\"\"\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n\n    r = session or Session()\n\n    exchanges = fetch_swiss_exchanges(r, target_datetime, logger)\n    consumptions = fetch_swiss_consumption(r, target_datetime, logger)\n    productions = ENTSOE.fetch_production(\n        zone_key=zone_key, session=r, target_datetime=target_datetime, logger=logger\n    )\n\n    if not productions:\n        return\n\n    for p in productions:\n        dt = p[\"datetime\"]\n        if dt not in exchanges or dt not in consumptions:\n            continue\n        known_production = sum([x or 0 for x in p[\"production\"].values()])\n\n        storage = sum([x or 0 for x in p[\"storage\"].values()])\n        total_production = consumptions[dt] + storage + exchanges[dt]\n        unknown_production = total_production - known_production\n        p[\"production\"][\"unknown\"] = unknown_production if unknown_production > 0 else 0\n\n    for p in productions:\n        p[\"capacity\"] = {\n            \"solar\": get_solar_capacity_at(p[\"datetime\"]),\n        }\n\n    return productions\n\n\nif __name__ == \"__main__\":\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CL.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Parser for the electricity grid of Chile\"\"\"\n\nfrom collections import defaultdict\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom operator import itemgetter\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\n\n# Historical API\nAPI_BASE_URL = \"https://sipub.coordinador.cl/api/v1/recursos/generacion_centrales_tecnologia_horario?\"\n\nTIMEZONE = ZoneInfo(\"Chile/Continental\")\n\nTYPE_MAPPING = {\n    \"hidraulica\": \"hydro\",\n    \"termica\": \"unknown\",\n    \"eolica\": \"wind\",\n    \"solar\": \"solar\",\n    \"geotermica\": \"geothermal\",\n}\n\n\ndef production_processor_historical(raw_data):\n    \"\"\"Takes raw json data and groups by datetime while mapping generation to type.\n    Returns a list of dictionaries.\n    \"\"\"\n\n    clean_datapoints = []\n    for datapoint in raw_data:\n        clean_datapoint = {}\n        date, hour = datapoint[\"fecha\"], datapoint[\"hora\"]\n        hour -= 1  # `hora` starts at 1\n        parsed_datetime = datetime.fromisoformat(date).replace(\n            tzinfo=TIMEZONE\n        ) + timedelta(hours=hour)\n        clean_datapoint[\"datetime\"] = parsed_datetime\n\n        gen_type_es = datapoint[\"tipo_central\"]\n        mapped_gen_type = TYPE_MAPPING[gen_type_es]\n        value_mw = float(datapoint[\"generacion_sum\"])\n\n        clean_datapoint[mapped_gen_type] = value_mw\n\n        clean_datapoints.append(clean_datapoint)\n\n    combined = defaultdict(dict)\n    for elem in clean_datapoints:\n        combined[elem[\"datetime\"]].update(elem)\n\n    ordered_data = sorted(combined.values(), key=itemgetter(\"datetime\"))\n\n    return ordered_data\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"CL-SEN\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if target_datetime:\n        target_datetime_aware = target_datetime.replace(tzinfo=TIMEZONE)\n    else:\n        target_datetime_aware = datetime.now(tz=TIMEZONE)\n    start = (target_datetime_aware + timedelta(days=-1)).date().isoformat()\n    end = target_datetime_aware.date().isoformat()\n\n    date_component = f\"fecha__gte={start}&fecha__lte={end}\"\n\n    # required for access\n    headers = {\n        \"Referer\": \"https://www.coordinador.cl/operacion/graficos/operacion-real/generacion-real-del-sistema/\",\n        \"Origin\": \"https://www.coordinador.cl\",\n    }\n\n    s = session or Session()\n    url = API_BASE_URL + date_component\n\n    req = s.get(url, headers=headers)\n    req.raise_for_status()\n    raw_data = req.json()[\"aggs\"]\n    historical_data = production_processor_historical(raw_data)\n\n    \"\"\"The last 9 datapoints should be omitted because they usually are incomplete and shouldn't appear on the map.\"\"\"\n    del historical_data[-9:]\n\n    production_list = ProductionBreakdownList(logger)\n\n    for event in historical_data:\n        dt = event.pop(\"datetime\")\n\n        production_mix = ProductionMix()\n        for key, value in event.items():\n            production_mix.add_value(key, value)\n\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            production=production_mix,\n            storage=None,\n            source=\"coordinador.cl\",\n        )\n\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    # For fetching historical data instead, try:\n    print(fetch_production(target_datetime=datetime.strptime(\"20200220\", \"%Y%m%d\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CNDC.py",
    "content": "#!/usr/bin/env python3\n\nimport json\nimport re\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.config import CONFIG_DIR\nfrom electricitymap.contrib.config.reading import read_zones_config\nfrom electricitymap.contrib.lib.models.event_lists import (\n    EventSourceType,\n    ProductionBreakdownList,\n    ProductionMix,\n    TotalProductionList,\n)\nfrom electricitymap.contrib.parsers.lib.config import use_proxy\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\ntz_bo = ZoneInfo(\"America/La_Paz\")\n\nZONES_CONFIG = read_zones_config(config_dir=CONFIG_DIR)\ngas_oil_ratio = ZONES_CONFIG[\"BO\"][\"capacity\"][\"gas\"][-1][\"value\"] / (\n    ZONES_CONFIG[\"BO\"][\"capacity\"][\"gas\"][-1][\"value\"]\n    + ZONES_CONFIG[\"BO\"][\"capacity\"][\"oil\"][-1][\"value\"]\n)\nINDEX_URL = \"https://www.cndc.bo/gene/index.php\"\nDATA_URL = \"https://www.cndc.bo/gene/dat/gene.php?fechag={0}\"\nSOURCE = \"cndc.bo\"\n# User-Agent to avoid being blocked as a bot\nUSER_AGENT = \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36\"\nREQUEST_TIMEOUT = 30  # seconds\n\n\ndef extract_xsrf_token(html):\n    \"\"\"Extracts XSRF token from the source code of the generation graph page.\"\"\"\n    return re.search(r'var ttoken = \"([a-f0-9]+)\";', html).group(1)\n\n\ndef get_datetime(query_date: datetime, hour: int) -> datetime:\n    return datetime(\n        year=query_date.year,\n        month=query_date.month,\n        day=query_date.day,\n        hour=hour,\n        tzinfo=tz_bo,\n    )\n\n\ndef _check_response(response, context: str = \"\"):\n    \"\"\"Check HTTP response and raise appropriate ParserException if needed.\"\"\"\n    if response.status_code == 403:\n        raise ParserException(\n            \"CNDC.py\",\n            f\"Access forbidden (403){context}. The server may be blocking requests.\",\n            \"BO\",\n        )\n    elif response.status_code == 429:\n        raise ParserException(\"CNDC.py\", f\"Rate limit exceeded (429){context}.\", \"BO\")\n    elif response.status_code >= 500:\n        raise ParserException(\n            \"CNDC.py\",\n            f\"Server error ({response.status_code}){context}. The CNDC server may be down.\",\n            \"BO\",\n        )\n    elif not response.ok:\n        raise ParserException(\"CNDC.py\", f\"HTTP {response.status_code}{context}\", \"BO\")\n\n\ndef fetch_data(\n    session: Session | None = None, target_datetime: datetime | None = None\n) -> tuple[list[dict], datetime]:\n    session = session or Session()\n    target_datetime = (target_datetime or datetime.now()).astimezone(tz_bo)\n    formatted_dt = target_datetime.strftime(\"%Y-%m-%d\")\n\n    # Headers to mimic a browser and avoid being blocked\n    headers = {\n        \"User-Agent\": USER_AGENT,\n        \"Accept\": \"text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8\",\n        \"Accept-Language\": \"en-US,en;q=0.5\",\n        \"Connection\": \"keep-alive\",\n    }\n\n    try:\n        # Get XSRF token from index page\n        index_response = session.get(\n            INDEX_URL, headers=headers, timeout=REQUEST_TIMEOUT\n        )\n        _check_response(index_response)\n\n        try:\n            xsrf_token = extract_xsrf_token(index_response.text)\n        except (AttributeError, IndexError) as e:\n            raise ParserException(\n                \"CNDC.py\",\n                \"Failed to extract XSRF token. Website structure may have changed.\",\n                \"BO\",\n            ) from e\n\n        # Fetch data with XSRF token\n        headers[\"x-csrf-token\"] = xsrf_token\n        data_response = session.get(\n            DATA_URL.format(formatted_dt), headers=headers, timeout=REQUEST_TIMEOUT\n        )\n        _check_response(data_response, \" when fetching data\")\n\n        # Parse JSON response\n        try:\n            hour_rows = json.loads(data_response.text.replace(\"\", \"\"))[\"data\"]\n        except (json.JSONDecodeError, KeyError) as e:\n            raise ParserException(\n                \"CNDC.py\",\n                f\"Failed to parse JSON response. API format may have changed: {e}\",\n                \"BO\",\n            ) from e\n\n        return hour_rows, target_datetime\n\n    except ParserException:\n        raise\n    except Exception as e:\n        raise ParserException(\n            \"CNDC.py\",\n            f\"Unexpected error: {type(e).__name__}: {e}\",\n            \"BO\",\n        ) from e\n\n\ndef parse_generation_forecast(\n    zone_key: ZoneKey, date: datetime, raw_data: list[dict], logger: Logger\n) -> TotalProductionList:\n    result = TotalProductionList(logger)\n    assert date.tzinfo == tz_bo\n    for hour_row in raw_data:\n        [hour, forecast, total, thermo, hydro, wind, solar, bagasse] = hour_row\n\n        # \"hour\" is one-indexed\n        timestamp = get_datetime(query_date=date, hour=hour - 1)\n\n        result.append(\n            zoneKey=zone_key,\n            datetime=timestamp,\n            value=forecast,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n\n    return result\n\n\ndef parser_production_breakdown(\n    zone_key: ZoneKey, date: datetime, raw_data: list[dict], logger: Logger\n) -> ProductionBreakdownList:\n    result = ProductionBreakdownList(logger)\n    assert date.tzinfo == tz_bo\n    for hour_row in raw_data:\n        [hour, forecast, total, thermo, hydro, wind, solar, bagasse] = hour_row\n\n        # \"hour\" is one-indexed\n        timestamp = get_datetime(query_date=date, hour=hour - 1)\n        modes_extracted = [hydro, solar, wind, bagasse]\n\n        if total is None or None in modes_extracted:\n            continue\n\n        unknown_value = round(total - thermo - hydro - solar - wind - bagasse, 3)\n        unknown_value = None if abs(unknown_value) < 0.05 else unknown_value\n\n        result.append(\n            zoneKey=zone_key,\n            datetime=timestamp,\n            production=ProductionMix(\n                hydro=hydro,\n                solar=solar,\n                wind=wind,\n                biomass=bagasse,\n                gas=round(thermo * gas_oil_ratio, 3),\n                oil=round(thermo * (1 - gas_oil_ratio), 3),\n                unknown=unknown_value,\n            ),\n            source=SOURCE,\n        )\n\n    return result\n\n\n@use_proxy(country_code=\"BO\")\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"BO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    production = ProductionBreakdownList(logger)\n    raw_data, query_date = fetch_data(session=session, target_datetime=target_datetime)\n    production = parser_production_breakdown(zone_key, query_date, raw_data, logger)\n\n    return production.to_list()\n\n\ndef fetch_generation_forecast(\n    zone_key: ZoneKey = ZoneKey(\"BO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    raw_data, query_date = fetch_data(session=session, target_datetime=target_datetime)\n    generation_forecast = parse_generation_forecast(\n        zone_key, query_date, raw_data, logger\n    )\n    return generation_forecast.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(fetch_production())\n    print(\"fetch_production() ->\")\n\n    # print(\"fetch_generation_forecast() ->\")\n    # print(fetch_generation_forecast())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CO.py",
    "content": "#!/usr/bin/env python3\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pydataxm.pydataxm as pydataxm\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    PriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency, use_proxy\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\n# The production, price, and historical consumption parser makes use of a third\n# party library called pydataxm, for details on what data is available, refer to\n# https://github.com/EquipoAnaliticaXM/API_XM/?tab=readme-ov-file#variables-disponibles-para-consumir-en-la-api-xm.\n#\n# Note:\n# - Currently there is a delay of two days for data to be made available via\n#   this library.\n# - Sometimes fetching data with start date / end date being the same day, you\n#   can get a full month of days.\n#\n# Delay live production and price data fetches, as data isn't made available\n# that quick when using the pydataxm library\nXM_DELAY_MIN = 2\nXM_DELAY_MAX = 5\n\n# Fetching live consumption is done using another API currently, which as of\n# 2023-02-11 provides demand data with 5-minute-granularity of the current day.\n# For details, refer to https://www.xm.com.co/consumo/demanda-en-tiempo-real.\n#\nCO_DEMAND_URL = \"https://serviciosfacturacion.xm.com.co/XM.Portal.Indicadores/api/Operacion/DemandaTiempoReal\"\n\nZONE_INFO = ZoneInfo(\"America/Bogota\")  # UTC-5\n\n# dictionnary of plant types XM to EMaps https://www.xm.com.co/generacion/tipos\nPRODUCTION_MAPPING = {\n    \"AGUA\": \"hydro\",\n    \"BIOGAS\": \"biomass\",\n    \"CARBON\": \"coal\",\n    \"GAS\": \"gas\",\n    \"BAGAZO\": \"biomass\",\n    \"RAD SOLAR\": \"solar\",\n    \"VIENTO\": \"wind\",\n    \"COMBUSTOLEO\": \"oil\",\n    \"ACPM\": \"oil\",\n    \"JET-A1\": \"oil\",\n}\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"CO\", monkeypatch_for_pydataxm=True)\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"CO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if target_datetime is None:\n        session = session or Session()\n        return _fetch_live_consumption(zone_key, session, logger)\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n        return _fetch_historical_consumption(zone_key, target_datetime, logger)\n\n\ndef _fetch_live_consumption(\n    zone_key: ZoneKey,\n    session: Session,\n    logger: Logger,\n) -> list[dict[str, Any]]:\n    response: Response = session.get(CO_DEMAND_URL, verify=False)\n    response.raise_for_status()\n\n    demand_data = response.json()[\"Variables\"][0][\"Datos\"]\n    demand_list = TotalConsumptionList(logger)\n    for datapoint in demand_data:\n        dt_string = datapoint[\"Fecha\"]\n        # TODO: Remove the truncation of sub-seconds when we run on Python 3.11\n        #       or above and fromisoformat can parse such strings\n        if dt_string.find(\".\") != -1:\n            dt_string = dt_string[: dt_string.find(\".\")]\n        dt = datetime.fromisoformat(dt_string).replace(tzinfo=ZONE_INFO)\n\n        demand_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            consumption=round(datapoint[\"Valor\"], 1),\n            source=\"xm.com.co\",\n        )\n    return demand_list.to_list()\n\n\ndef _fetch_historical_consumption(\n    zone_key: ZoneKey,\n    target_datetime: datetime,\n    logger: Logger,\n) -> list[dict[str, Any]]:\n    api_client = pydataxm.ReadDB()\n    target_date = target_datetime.date()\n\n    # get system demand\n    df_cons = api_client.request_data(\"DemaReal\", \"Sistema\", target_date, target_date)\n    if df_cons.empty:\n        raise ParserException(\n            parser=\"CO\",\n            message=f\"{target_datetime} : no consumption data available\",\n            zone_key=zone_key,\n        )\n\n    # preserve the date column as the index\n    df_cons = df_cons.set_index(\"Date\")\n\n    # filter out column of relevance: hour\n    df_cons = df_cons[[c for c in df_cons.columns if \"Hour\" in c]]\n\n    consumption_list = TotalConsumptionList(logger)\n    for date, df in df_cons.groupby(\"Date\"):\n        for hour_col in df.columns:\n            consumption = float(df[hour_col]) / 1000\n\n            # hour_col is \"Values_Hour01\" to \"Values_Hour24\"\n            hour = int(hour_col[-2:]) - 1\n            dt = date.to_pydatetime().replace(hour=hour).replace(tzinfo=ZONE_INFO)\n\n            consumption_list.append(\n                zoneKey=zone_key,\n                datetime=dt,\n                consumption=consumption,\n                source=\"xm.com.co\",\n            )\n    return consumption_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"CO\", monkeypatch_for_pydataxm=True)\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"CO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n        target_date_range = [\n            target_datetime.date() - timedelta(days=days)\n            for days in range(XM_DELAY_MIN, XM_DELAY_MAX + 1)\n        ]\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n        target_date_range = [target_datetime.date()]\n\n    api_client = pydataxm.ReadDB()\n    for date in target_date_range:\n        # get power production resources, where we are interested in a mapping\n        # between a resource id (Values_Code column) to power production type\n        # (Values_EnerSource column)\n        df_res = api_client.request_data(\"ListadoRecursos\", \"Sistema\", date, date)\n        if df_res.empty:\n            continue\n\n        # get power production per resource\n        df_prod = api_client.request_data(\"Gene\", \"Recurso\", date, date)\n        if df_prod.empty:\n            continue\n\n        break\n    if df_prod.empty:\n        raise ParserException(\n            parser=\"CO\",\n            message=f\"{target_datetime}: no production data available\",\n            zone_key=zone_key,\n        )\n\n    # join the Values_EnerSource column from df_res to df_prod using Values_code column\n    df_res = df_res[[\"Values_Code\", \"Values_EnerSource\"]].set_index(\"Values_Code\")\n    df_prod = df_prod.set_index(\"Values_code\")\n    df_prod = df_prod.join(df_res, how=\"left\").reset_index()\n\n    # map power production type values to our terminology\n    df_prod[\"Values_EnerSource\"] = df_prod[\"Values_EnerSource\"].map(PRODUCTION_MAPPING)\n\n    # filter out columns of relevance: date, hour, and power production type\n    df_cols = [\n        c\n        for c in df_prod.columns\n        if \"Date\" in c or \"Hour\" in c or \"Values_EnerSource\" in c\n    ]\n    df_prod = df_prod[df_cols]\n\n    # sum all values for given combination of date and power production type,\n    # and make a multi index of those combinations\n    df_prod = df_prod.groupby([\"Date\", \"Values_EnerSource\"]).sum(\n        numeric_only=True,\n    )\n\n    # loop over each date in the multi index\n    production_list = ProductionBreakdownList(logger)\n    for date, df in df_prod.groupby(level=0):\n        # in the date specific df, drop the date from the index, leaving the\n        # power production type as index\n        df = df.droplevel(0)\n\n        for hour_col in df.columns:\n            prod_kw = df[hour_col].to_dict()\n            prod_mw = {mode: round(kw / 1000, 3) for mode, kw in prod_kw.items()}\n\n            production_mix = ProductionMix()\n            for mode, value in prod_mw.items():\n                production_mix.add_value(mode, value)\n\n            # hour_col is \"Values_Hour01\" to \"Values_Hour24\"\n            hour = int(hour_col[-2:]) - 1\n            dt = date.to_pydatetime().replace(hour=hour).replace(tzinfo=ZONE_INFO)\n\n            production_list.append(\n                zoneKey=zone_key,\n                datetime=dt,\n                production=production_mix,\n                source=\"xm.com.co\",\n            )\n    return production_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"CO\", monkeypatch_for_pydataxm=True)\ndef fetch_price(\n    zone_key: ZoneKey = ZoneKey(\"CO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n        target_date_range = [\n            target_datetime.date() - timedelta(days=days)\n            for days in range(XM_DELAY_MIN, XM_DELAY_MAX + 1)\n        ]\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n        target_date_range = [target_datetime.date()]\n\n    api_client = pydataxm.ReadDB()\n    for date in target_date_range:\n        df_price = api_client.request_data(\"PrecBolsNaci\", \"Sistema\", date, date)\n        if df_price.empty:\n            continue\n        break\n    if df_price.empty:\n        raise ParserException(\n            parser=\"CO\",\n            message=f\"{target_datetime}: no price data available\",\n            zone_key=zone_key,\n        )\n\n    # preserve the date column as the index\n    df_price = df_price.set_index(\"Date\")\n\n    # filter out column of relevance: hour\n    df_price = df_price[[c for c in df_price.columns if \"Hour\" in c]]\n\n    price_list = PriceList(logger)\n    for date, df in df_price.groupby(\"Date\"):\n        for hour_col in df.columns:\n            price = float(df[hour_col])\n\n            # hour_col is \"Values_Hour01\" to \"Values_Hour24\"\n            hour = int(hour_col[-2:]) - 1\n            dt = date.to_pydatetime().replace(hour=hour).replace(tzinfo=ZONE_INFO)\n\n            price_list.append(\n                zoneKey=zone_key,\n                datetime=dt,\n                currency=\"COP\",\n                price=price,\n                source=\"xm.com.co\",\n            )\n    return price_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n\n    print(\"fetch_price() ->\")\n    print(fetch_price())\n\n    dt = datetime.fromisoformat(\"2025-01-01T00:00:00-05:00\")\n    print(\"fetch_production(target_datetime=...) ->\")\n    print(fetch_production(target_datetime=dt))\n\n    print(\"fetch_price(target_datetime=...) ->\")\n    print(fetch_price(target_datetime=dt))\n\n    print(\"fetch_consumption(target_datetime=...) ->\")\n    print(fetch_consumption(target_datetime=dt))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CR.py",
    "content": "from collections import defaultdict\nfrom datetime import datetime, time, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"CR.py\"\nTIMEZONE = ZoneInfo(\"America/Costa_Rica\")\n\nEXCHANGE_URL = (\n    \"https://mapa.enteoperador.org/WebServiceScadaEORRest/webresources/generic\"\n)\nEXCHANGE_SOURCE = \"enteoperador.org\"\n\nPRODUCTION_URL = (\n    \"https://apps.grupoice.com/CenceWeb/data/sen/json/EnergiaHorariaFuentePlanta\"\n)\nPRODUCTION_SOURCE = \"grupoice.com\"\n\nSPANISH_TO_ENGLISH = {\n    \"Bagazo\": \"biomass\",\n    \"Eólica\": \"wind\",\n    \"Geotérmica\": \"geothermal\",\n    \"Hidroeléctrica\": \"hydro\",\n    \"Solar\": \"solar\",\n    \"Térmica\": \"oil\",\n}\n\nEXCHANGE_JSON_MAPPING = {\n    \"CR->NI\": \"5SISTEMA.LT230.INTER_NET_CR.CMW.MW\",\n    \"CR->PA\": \"6SISTEMA.LT230.INTER_NET_PAN.CMW.MW\",\n}\n\n\ndef _parse_exchange_data(\n    exchange_data: list[dict], sorted_zone_keys: ZoneKey\n) -> float | None:\n    \"\"\"Extracts flow value and direction for a given exchange.\"\"\"\n    exchange_name = EXCHANGE_JSON_MAPPING[sorted_zone_keys]\n    net_flow = next(\n        (item[\"value\"] for item in exchange_data if item[\"nombre\"] == exchange_name),\n        None,\n    )\n\n    if net_flow is None:\n        raise ValueError(f\"No flow value found for exchange {sorted_zone_keys}\")\n\n    return net_flow\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"CR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    # if no target_datetime is specified, this defaults to now.\n    now = datetime.now(timezone.utc)\n    target_datetime = now if target_datetime is None else target_datetime\n\n    # the backend production API works in terms of local times\n    now = now.astimezone(TIMEZONE)\n    target_datetime = target_datetime.astimezone(TIMEZONE)\n\n    # if before 01:30am on the current day then fetch previous day due to data lag.\n    today = datetime.combine(now, time(), tzinfo=TIMEZONE)  # truncates to day\n    if today <= target_datetime < today + timedelta(hours=1, minutes=30):\n        target_datetime -= timedelta(days=1)\n\n    # data availability limit found by manual trial and error\n    cutoff_datetime = datetime(2017, 7, 1, tzinfo=TIMEZONE)\n    if target_datetime < cutoff_datetime:\n        raise ParserException(\n            parser=PARSER,\n            message=f\"CR API does not provide data before {cutoff_datetime.isoformat()}, {target_datetime.isoformat()} was requested.\",\n            zone_key=zone_key,\n        )\n\n    session = session or Session()\n    url = f\"{PRODUCTION_URL}?{target_datetime.strftime('anno=%Y&mes=%m&dia=%d')}\"\n    response = session.get(url)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    response_payload = response.json()\n\n    production_mixes = defaultdict(ProductionMix)\n    for hourly_item in response_payload[\"data\"]:\n        # returned timestamps are missing timezone but are local (CR) times\n        timestamp = datetime.strptime(\n            hourly_item[\"fecha\"], \"%Y-%m-%d %H:%M:%S.%f\"\n        ).replace(tzinfo=TIMEZONE)\n\n        source = hourly_item[\"fuente\"]\n        if source == \"Intercambio\":\n            continue\n\n        production_mode = SPANISH_TO_ENGLISH[source]\n        value = hourly_item[\"dato\"]\n\n        production_mixes[timestamp].add_value(production_mode, value)\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n    for timestamp, production_mix in production_mixes.items():\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=timestamp,\n            source=PRODUCTION_SOURCE,\n            production=production_mix,\n        )\n    return production_breakdown_list.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey = ZoneKey(\"CR\"),\n    zone_key2: ZoneKey = ZoneKey(\"PA\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Gets an exchange pair from the SIEPAC system.\"\"\"\n\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    if sorted_zone_keys not in EXCHANGE_JSON_MAPPING:\n        raise ParserException(\n            PARSER, \"This exchange is not implemented\", sorted_zone_keys\n        )\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER,\n            \"This parser is not yet able to parse historical data\",\n            sorted_zone_keys,\n        )\n\n    session = session or Session()\n    dt = datetime.now(TIMEZONE)\n    response = session.get(EXCHANGE_URL)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching exchange error code: {response.status_code}: {response.text}\",\n            sorted_zone_keys,\n        )\n\n    net_flow = _parse_exchange_data(response.json(), sorted_zone_keys=sorted_zone_keys)\n\n    exchange_list = ExchangeList(logger)\n    exchange_list.append(\n        zoneKey=sorted_zone_keys,\n        datetime=dt.replace(minute=0, second=0, microsecond=0),\n        netFlow=net_flow,\n        source=EXCHANGE_SOURCE,\n    )\n    return exchange_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CY.py",
    "content": "#!/usr/bin/env python3\n\nimport sys\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\n# BeautifulSoup is used to parse HTML\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\n# Local library imports\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency, use_proxy\n\nREALTIME_SOURCE = \"https://tsoc.org.cy/electrical-system/total-daily-system-generation-on-the-transmission-system/\"\nHISTORICAL_SOURCE = \"https://tsoc.org.cy/electrical-system/archive-total-daily-system-generation-on-the-transmission-system/?startdt={}&enddt=%2B1days\"\n\nTIMEZONE = ZoneInfo(\"Asia/Nicosia\")\n\n\nclass CyprusParser:\n    CAPACITY_KEYS = {\n        \"Συμβατική Εγκατεστημένη Ισχύς\": \"oil\",\n        \"Αιολική Εγκατεστημένη Ισχύς\": \"wind\",\n        \"Φωτοβολταϊκή Εγκατεστημένη Ισχύς\": \"solar\",\n        \"Εγκατεστημένη Ισχύς Βιομάζας\": \"biomass\",\n    }\n\n    session: Session\n    logger: Logger\n\n    def __init__(self, session, logger: Logger = getLogger(__name__)):\n        self.session = session\n        self.logger = logger\n\n    def warn(self, text: str) -> None:\n        self.logger.warning(text, extra={\"key\": \"CY\"})\n\n    def parse_capacity(self, html) -> dict:\n        capacity = {}\n        table = html.find(id=\"production_graph_static_data2\")\n        for tr in table.find_all(\"tr\"):\n            values = [td.string for td in tr.find_all(\"td\")]\n            key = self.CAPACITY_KEYS.get(values[0])\n            if key:\n                capacity[key] = float(values[1])\n        return capacity\n\n    def parse_production(self, html, capacity: dict) -> list:\n        table = html.find(id=\"production_graph_data\")\n        columns = [th.string for th in table.find_all(\"th\")]\n        biomass_estimate = 0.0\n        production_breakdowns = ProductionBreakdownList(self.logger)\n        for tr in table.tbody.find_all(\"tr\"):\n            values = [td.string for td in tr.find_all(\"td\")]\n            if None in values or \"\" in values:\n                break\n            production_mix = ProductionMix()\n            date_time = None\n            for col, val in zip(columns, values, strict=True):\n                if col == \"Timestamp\":\n                    date_time = datetime.fromisoformat(val).replace(tzinfo=TIMEZONE)\n                elif col == \"Αιολική Παραγωγή στο ΣΜ\":\n                    production_mix.add_value(\"wind\", float(val))\n                elif col == \"Συμβατική Παραγωγή στο ΣΜ\":\n                    production_mix.add_value(\"oil\", float(val))\n                elif col == \"Εκτίμηση Διεσπαρμένης Παραγωγής\":\n                    # Because solar is explicitly listed as \"Solar PV\" (so no thermal with energy storage)\n                    # and there is no sunlight between 10pm and 3am (https://www.timeanddate.com/sun/cyprus/nicosia),\n                    # we use the nightly biomass+solar generation reported to determine the portion of biomass+solar\n                    # which constitutes biomass.\n                    value = float(val)\n                    hour = date_time.hour\n                    if hour < 3 or hour >= 22:\n                        biomass_estimate = value\n                    production_mix.add_value(\"biomass\", biomass_estimate)\n                    production_mix.add_value(\n                        \"solar\", max(value - biomass_estimate, 0.0)\n                    )\n            production_breakdowns.append(\n                zoneKey=ZoneKey(\"CY\"),\n                datetime=date_time,\n                production=production_mix,\n                source=\"tsoc.org.cy\",\n            )\n        return [\n            {**e, **{\"capacity\": capacity}} for e in production_breakdowns.to_list()\n        ]\n\n    def fetch_production(self, target_datetime: datetime | None) -> list:\n        if target_datetime is None:\n            url = REALTIME_SOURCE\n        else:\n            # convert target datetime to local datetime\n            url_date = target_datetime.astimezone(TIMEZONE).strftime(\"%d-%m-%Y\")\n            url = HISTORICAL_SOURCE.format(url_date)\n\n        # Add User-Agent headers to mimic a browser and avoid 403 errors\n        headers = {\n            \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36\"\n        }\n        res = self.session.get(url, headers=headers)\n        assert res.status_code == 200, (\n            f\"CY parser: GET {url} returned {res.status_code}\"\n        )\n\n        html = BeautifulSoup(res.text, \"lxml\")\n\n        # Capacity is only available if we fetch data from realtime url\n        capacity = self.parse_capacity(html) if url is REALTIME_SOURCE else {}\n        data = self.parse_production(html, capacity)\n\n        if len(data) == 0:\n            self.warn(\"No production data returned for Cyprus\")\n        return data\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"DK\")\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"CY\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    assert zone_key == ZoneKey(\"CY\")\n\n    parser = CyprusParser(session or Session(), logger)\n    return parser.fetch_production(target_datetime)\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    target_datetime = None\n    if len(sys.argv) == 4:\n        target_datetime = datetime(int(sys.argv[1]), int(sys.argv[2]), int(sys.argv[3]))\n\n    print(\"fetch_production() ->\")\n    fetched_production = fetch_production(target_datetime=target_datetime)\n    if isinstance(fetched_production, list):\n        for datum in fetched_production:\n            print(datum)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/CZ.py",
    "content": "from datetime import datetime, timedelta\nfrom logging import Logger, getLogger\n\nfrom bs4 import BeautifulSoup\n\n# The request library is used to fetch content through HTTP\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\n# please try to write PEP8 compliant code (use a linter). One of PEP8's\n# requirement is to limit your line length to 79 characters.\n\ntranslate_table_gen = {\n    \"TPP\": \"coal\",  # coal\n    \"CCGT\": \"gas\",  # gas and steem gas\n    \"NPP\": \"nuclear\",  # Nuclear\n    \"HPP\": \"hydro\",  # Water\n    \"PsPP\": \"hydro\",  # Pump Water storage\n    \"AltPP\": \"biomass\",  # Alternative\n    \"ApPP\": \"unknown\",  # factory\n    \"PVPP\": \"solar\",  # photovoltaic\n    \"WPP\": \"wind\",  # wind\n    \"unknown\": \"unknown\",\n}\ntranslate_table_dist = {\n    \"SEPS\": \"SK\",\n    \"APG\": \"AT\",\n    \"PSE\": \"PL\",\n    \"TenneT\": \"DE\",\n    \"50HzT\": \"DE\",\n}\n\nurl = \"https://www.ceps.cz/_layouts/CepsData.asmx\"\nsource = \"ceps.cz\"\n\n\ndef get_mapper(xmlload):\n    series = xmlload.find(\"series\")\n    mapping = {}\n    for tag in series:\n        generator = tag[\"name\"].replace(\" [MW]\", \"\")\n        mapping[generator] = tag[\"id\"]\n\n    return mapping\n\n\ndef make_request(session, payload, zone_key):\n    headers = {\n        \"Content-Type\": \"application/soap+xml; charset=utf-8\",\n        \"Content-Length\": \"1\",\n    }\n\n    res: Response = session.post(url, headers=headers, data=payload)\n    assert res.status_code == 200, (\n        f\"Exception when fetching production for {zone_key}: error when calling {url}\"\n    )\n\n    return res\n\n\ndef get_target_datetime(dt: datetime | None) -> datetime:\n    if dt is None:\n        now = datetime.now()\n        dt = (now - timedelta(minutes=now.minute % 15)).replace(second=0, microsecond=0)\n    return dt\n\n\ndef __get_exchange_data(\n    zone_key1: ZoneKey = ZoneKey(\"CZ\"),\n    zone_key2: ZoneKey = ZoneKey(\"DE\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n    mode: str = \"Actual\",\n) -> list:\n    target_datetime = get_target_datetime(target_datetime)\n    from_datetime = target_datetime - timedelta(hours=48)\n\n    payload = \"\"\"<?xml version=\"1.0\" encoding=\"utf-8\"?>\n    <soap12:Envelope xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\" xmlns:xsd=\"http://www.w3.org/2001/XMLSchema\" xmlns:soap12=\"http://www.w3.org/2003/05/soap-envelope\">\n      <soap12:Body>\n        <CrossborderPowerFlows xmlns=\"https://www.ceps.cz/CepsData/\">\n          <dateFrom>{}</dateFrom>\n          <dateTo>{}</dateTo>\n          <agregation>{}</agregation>\n          <function>{}</function>\n          <version>{}</version>\n        </CrossborderPowerFlows>\n      </soap12:Body>\n    </soap12:Envelope>\"\"\".format(\n        from_datetime.isoformat(), target_datetime.isoformat(), \"QH\", \"AVG\", \"RT\"\n    )\n\n    content = make_request(session, payload, zone_key1).text\n    xml = BeautifulSoup(content, \"xml\")\n    mapper = get_mapper(xml)\n    data_tag = xml.find(\"data\")\n    exchanges = ExchangeList(logger)\n\n    if data_tag is not None:\n        for values in data_tag:\n            totalNetFlow = 0.0\n\n            for k, v in mapper.items():\n                country = \"\".join(\n                    [\n                        c\n                        for key, c in translate_table_dist.items()\n                        if key in k and mode in k\n                    ]\n                )\n                if country != \"\" and country in (zone_key1, zone_key2):\n                    netFlow = float(values[v])\n                    totalNetFlow += -1 * netFlow if zone_key1 == \"CZ\" else netFlow\n\n            exchanges.append(\n                zoneKey=ZoneKey(f\"{zone_key1}->{zone_key2}\"),\n                datetime=datetime.fromisoformat(values[\"date\"]),\n                source=source,\n                netFlow=totalNetFlow,\n            )\n\n    else:\n        zone_key = f\"{zone_key1}->{zone_key2}\"\n        raise ParserException(\n            \"CZ.py\",\n            f\"There was no data returned for {zone_key1} and {zone_key2} at {target_datetime}\",\n            zone_key,\n        )\n\n    return exchanges.to_list()\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"CZ\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    target_datetime = get_target_datetime(target_datetime)\n    from_datetime = target_datetime - timedelta(hours=48)\n\n    payload = \"\"\"<?xml version=\"1.0\" encoding=\"utf-8\"?>\n            <soap12:Envelope xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\" xmlns:xsd=\"http://www.w3.org/2001/XMLSchema\" xmlns:soap12=\"http://www.w3.org/2003/05/soap-envelope\">\n              <soap12:Body>\n                <Generation xmlns=\"https://www.ceps.cz/CepsData/\">\n                  <dateFrom>{}</dateFrom>\n                  <dateTo>{}</dateTo>\n                  <agregation>{}</agregation>\n                  <function>{}</function>\n                  <version>{}</version>\n                  <para1>{}</para1>\n                </Generation>\n              </soap12:Body>\n            </soap12:Envelope>\"\"\".format(\n        from_datetime.isoformat(), target_datetime.isoformat(), \"QH\", \"AVG\", \"RT\", \"all\"\n    )\n\n    content = make_request(session, payload, zone_key).text\n    xml = BeautifulSoup(content, \"xml\")\n    mapper = get_mapper(xml)\n\n    data_tag = xml.find(\"data\")\n    production_breakdowns = ProductionBreakdownList(logger)\n\n    if data_tag is not None:\n        for values in data_tag:\n            production = ProductionMix()\n            storage = StorageMix()\n\n            for k, v in mapper.items():\n                generator = translate_table_gen[k]\n                if k != \"PsPP\":\n                    production.add_value(mode=generator, value=float(values[v]))\n                else:\n                    storage.add_value(mode=generator, value=float(values[v]) * -1)\n\n            production_breakdowns.append(\n                zoneKey=zone_key,\n                datetime=datetime.fromisoformat(values[\"date\"]),\n                source=source,\n                production=production,\n                storage=storage,\n            )\n\n    else:\n        ParserException(\n            \"CZ.py\",\n            f\"There was no data returned for {zone_key} at {target_datetime}\",\n            zone_key,\n        )\n\n    return production_breakdowns.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: ZoneKey = ZoneKey(\"CZ\"),\n    zone_key2: ZoneKey = ZoneKey(\"DE\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    return __get_exchange_data(\n        zone_key1, zone_key2, session, target_datetime, logger, mode=\"Actual\"\n    )\n\n\ndef fetch_exchange_forecast(\n    zone_key1: ZoneKey = ZoneKey(\"CZ\"),\n    zone_key2: ZoneKey = ZoneKey(\"DE\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    return __get_exchange_data(\n        zone_key1, zone_key2, session, target_datetime, logger, mode=\"Planned\"\n    )\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    # print(\"fetch_production() ->\")\n    # print(fetch_production())\n    # print(\"fetch_price() ->\")\n    # print(fetch_price())\n    # print(\"fetch_exchange_forecast('AT', 'CZ') ->\")\n    # print(fetch_exchange_forecast(\"AT\", \"CZ\"))\n    print(\"fetch_exchange('AT', 'CZ') ->\")\n    print(fetch_exchange(ZoneKey(\"AT\"), ZoneKey(\"CZ\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/DK.py",
    "content": "from datetime import datetime, timedelta, timezone\nfrom itertools import groupby\nfrom logging import Logger, getLogger\nfrom operator import itemgetter\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import EventSourceType, ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nEXCHANGE_MAPPING = {\n    \"DE->DK-DK1\": {\"id\": \"ExchangeGermany\", \"direction\": 1, \"priceArea\": \"DK1\"},\n    \"DE->DK-DK2\": {\"id\": \"ExchangeGermany\", \"direction\": 1, \"priceArea\": \"DK2\"},\n    \"DK-DK1->DK-DK2\": {\"id\": \"ExchangeGreatBelt\", \"direction\": -1, \"priceArea\": \"DK1\"},\n    \"DK-DK1->NL\": {\"id\": \"ExchangeNetherlands\", \"direction\": -1, \"priceArea\": \"DK1\"},\n    \"DK-DK1->NO-NO2\": {\"id\": \"ExchangeNorway\", \"direction\": -1, \"priceArea\": \"DK1\"},\n    \"DK-DK1->SE-SE3\": {\"id\": \"ExchangeSweden\", \"direction\": -1, \"priceArea\": \"DK1\"},\n    \"DK-DK2->SE-SE4\": {\"id\": \"ExchangeSweden\", \"direction\": -1, \"priceArea\": \"DK2\"},\n}\n\nFORCAST_PARSE_MAPPING = {\n    \"Offshore Wind\": \"wind\",\n    \"Onshore Wind\": \"wind\",\n    \"Solar\": \"solar\",\n}\n\nFORCAST_AREA_MAPPING = {\n    \"DK-DK1\": \"DK1\",\n    \"DK-DK2\": \"DK2\",\n}\n\nEXCHANGE_URL = \"https://api.energidataservice.dk/dataset/ElectricityProdex5MinRealtime\"\nFORECAST_URL = \"https://api.energidataservice.dk/dataset/Forecasts_5Min\"\n\nSOURCE = \"energidataservice.dk\"\n\n\ndef fetch_data(\n    zone_key: ZoneKey,\n    session: Session | None,\n    target_datetime: datetime | None,\n    logger: Logger,\n    is_forecast: bool = False,\n) -> dict:\n    \"\"\"\n    Helper function to fetch data from the API.\n    \"\"\"\n    ses = session or Session()\n\n    if target_datetime and target_datetime.tzinfo:\n        # Data source doesn't support timezone aware\n        # datetimes.\n        target_datetime = target_datetime.replace(tzinfo=None)\n\n    price_area = (\n        FORCAST_AREA_MAPPING[zone_key]\n        if is_forecast\n        else EXCHANGE_MAPPING[zone_key][\"priceArea\"]\n    )\n\n    params = {\n        \"limit\": 500,\n        \"filter\": '{\"PriceArea\":\"DK1\"}'\n        if price_area == \"DK1\"\n        else '{\"PriceArea\":\"DK2\"}',\n        \"start\": target_datetime.strftime(\"%Y-%m-%d\") if target_datetime else None,\n        \"end\": (target_datetime + timedelta(days=1)).strftime(\"%Y-%m-%d\")\n        if target_datetime\n        else None,\n    }\n    response: Response = ses.get(\n        FORECAST_URL if is_forecast else EXCHANGE_URL,\n        params=params,\n    )\n    if response.ok:\n        data = response.json()\n        if data[\"total\"] == 0:\n            raise ParserException(\n                parser=\"DK.py\",\n                zone_key=zone_key,\n                message=f\"No exchange data was returned for {target_datetime.date() or datetime.now().date()}\",\n            )\n\n        else:\n            return data\n    else:\n        raise ParserException(\n            parser=\"DK.py\",\n            zone_key=zone_key,\n            message=f\"No exchange data was returned for {target_datetime.date() or datetime.now().date()}\",\n        )\n\n\ndef flow(sorted_keys: ZoneKey, datapoint: dict) -> int | float | None:\n    \"\"\"\n    Helper function to extract the net flow from a datapoint.\n    \"\"\"\n\n    return (\n        datapoint[EXCHANGE_MAPPING[sorted_keys][\"id\"]]\n        * EXCHANGE_MAPPING[sorted_keys][\"direction\"]\n        if datapoint[EXCHANGE_MAPPING[sorted_keys][\"id\"]] is not None\n        else None\n    )\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    sorted_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    data = fetch_data(sorted_keys, session, target_datetime, logger)\n    all_exchange_data = ExchangeList(logger)\n\n    if sorted_keys not in EXCHANGE_MAPPING:\n        raise ParserException(\n            \"DK.py\",\n            sorted_keys,\n            \"Only able to fetch data for exchanges that are connected to Denmark (DK-DK1, DK-DK2)\",\n        )\n    else:\n        price_area = EXCHANGE_MAPPING[sorted_keys][\"priceArea\"]\n        for datapoint in data[\"records\"]:\n            if datapoint[\"PriceArea\"] != price_area:\n                continue\n            all_exchange_data.append(\n                zoneKey=sorted_keys,\n                datetime=datetime.fromisoformat(datapoint[\"Minutes5UTC\"]).replace(\n                    tzinfo=timezone.utc\n                ),\n                netFlow=flow(sorted_keys, datapoint),\n                source=SOURCE,\n            )\n        return all_exchange_data.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    data = fetch_data(zone_key, session, target_datetime, logger, True)\n\n    # Group data by datetime Minutes5UTC\n    grouped_data = groupby(data[\"records\"], key=itemgetter(\"Minutes5UTC\"))\n\n    forecast = ProductionBreakdownList(logger=logger)\n    for date_time_str, group in grouped_data:\n        date_time = datetime.fromisoformat(date_time_str).replace(tzinfo=timezone.utc)\n        productionMix = ProductionMix()\n        for datapoint in group:\n            productionMix.add_value(\n                FORCAST_PARSE_MAPPING[datapoint[\"ForecastType\"]],\n                datapoint[\"ForecastCurrent\"],\n            )\n        forecast.append(\n            zoneKey=zone_key,\n            production=productionMix,\n            datetime=date_time,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n\n    return forecast.to_list()\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_exchange(DK-DK1, DE) ->\")\n    print(fetch_exchange(\"DK-DK2\", \"SE-SE4\"))\n\n    print(\"fetch_forecasts(DK-DK1) ->\")\n    print(fetch_wind_solar_forecasts(ZoneKey(\"DK-DK1\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/DO.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import use_proxy\nfrom electricitymap.contrib.types import ZoneKey\n\n# This parser gets hourly electricity generation data from oc.org.do for the Dominican Republic.\n# The data is in MWh but since it is updated hourly we can view it as MW.\n# Solar generation now has some data available but multiple projects are planned/under construction.\n\nDO_SOURCE = \"oc.org.do\"\nURL = \"https://apps.oc.org.do/reportesgraficos/reportepostdespacho.aspx\"\n\nTOTAL_RENEWABLES_MAPPING = {\n    \"Total E\\xf3lico\": \"wind\",\n    \"Total Hidroel\\xe9ctrica\": \"hydro\",\n    \"Total Solar\": \"solar\",\n}\n\nTOTAL_MAPPING = {\n    \"Total T\\xe9rmico\": \"Thermal\",\n    \"Total Generado\": \"Generated\",\n}\n\n# Power plant types\n# http://www.sie.gob.do/images/Estadisticas/MEM/GeneracionDiariaEnero2017/\n# Reporte_diario_de_generacion_31_enero_2017_merged2.pdf\n\nTHERMAL_PLANTS = {\n    \"AES ANDRES\": \"gas\",\n    \"BARAHONA CARBON\": \"coal\",\n    \"BERSAL\": \"oil\",\n    \"CEPP 1\": \"oil\",\n    \"CEPP 2\": \"oil\",\n    \"CESPM 1 FO\": \"oil\",\n    \"CESPM 1 GN\": \"gas\",\n    \"CESPM 2 FO\": \"oil\",\n    \"CESPM 2 GN\": \"gas\",\n    \"CESPM 3 FO\": \"oil\",\n    \"CESPM 3 GN\": \"gas\",\n    \"ESTRELLA DEL MAR 2 CFO\": \"oil\",\n    \"ESTRELLA DEL MAR 2 CGN\": \"gas\",\n    \"ESTRELLA DEL MAR 2 SFO\": \"oil\",\n    \"ESTRELLA DEL MAR 2 SGN\": \"gas\",\n    \"ESTRELLA DEL MAR 3\": \"gas\",\n    \"GENERACI\\xd3N DE EMERGENCIA AES ANDR\\xc9S\": \"gas\",\n    \"HAINA TG\": \"oil\",\n    \"INCA KM22\": \"oil\",\n    \"ITABO 1\": \"coal\",\n    \"ITABO 2\": \"coal\",\n    \"LA VEGA\": \"oil\",\n    \"LOS MINA 5\": \"gas\",\n    \"LOS MINA 6\": \"gas\",\n    \"LOS MINA 7\": \"gas\",\n    \"LOS OR\\xcdGENES POWER PLANT FUEL OIL\": \"oil\",\n    \"LOS OR\\xcdGENES POWER PLANT GAS NATURAL\": \"gas\",\n    \"METALDOM\": \"oil\",\n    \"MONTE RIO\": \"oil\",\n    \"PALAMARA\": \"oil\",\n    \"PALENQUE\": \"oil\",\n    \"PARQUE ENERGETICO LOS MINA CC PARCIAL\": \"gas\",\n    \"PARQUE ENERGETICO LOS MINA CC TOTAL\": \"gas\",\n    \"PIMENTEL 1\": \"oil\",\n    \"PIMENTEL 2\": \"oil\",\n    \"PIMENTEL 3\": \"oil\",\n    \"PUNTA CATALINA 1\": \"coal\",\n    \"PUNTA CATALINA 2\": \"coal\",\n    \"QUISQUEYA 1B SAN PEDRO GN\": \"gas\",\n    \"QUISQUEYA 1 FO\": \"oil\",\n    \"QUISQUEYA 1 GN\": \"gas\",\n    \"QUISQUEYA 2 FO\": \"oil\",\n    \"QUISQUEYA 2 GN\": \"gas\",\n    \"QUISQUEYA 1 SAN PEDRO FO\": \"oil\",\n    \"QUISQUEYA 1 SAN PEDRO GN\": \"gas\",\n    \"RIO SAN JUAN\": \"oil\",\n    \"SAN FELIPE\": \"oil\",\n    \"SAN FELIPE CC\": \"gas\",\n    \"SAN FELIPE VAP\": \"oil\",\n    \"SAN LORENZO 1\": \"gas\",\n    \"SAN PEDRO BIO-ENERGY\": \"biomass\",\n    \"SAN PEDRO VAPOR\": \"oil\",\n    \"SULTANA DEL ESTE\": \"oil\",\n}\n\n\ndef get_datetime_from_hour(now: datetime, hour: int) -> datetime:\n    return now + timedelta(hours=int(hour) - 1)\n\n\ndef get_data(session: Session | None = None) -> list[list[str]]:\n    \"\"\"\n    Makes a request to source url.\n    Finds main table and creates a list of all table elements in string format.\n    \"\"\"\n\n    s = session or Session()\n    data_req = s.get(URL)\n    soup = BeautifulSoup(data_req.content, \"lxml\")\n\n    tbs = soup.find(\"table\", id=\"PostdespachoUnidadesTermicasGrid_DXMainTable\")\n    rows = tbs.find_all(\"tr\")\n\n    data = []\n    for row in rows:\n        row_data = []\n        cols = row.find_all(\"td\")\n        for col in cols:\n            row_data.append(str(col.getText().strip()))\n        data.append(row_data)\n\n    return data\n\n\ndef floater(item):\n    \"\"\"\n    Attempts to convert any item given to a float.\n    Returns item if it fails.\n    \"\"\"\n\n    try:\n        return float(item)\n    except ValueError:\n        return item\n\n\ndef chunker(big_lst) -> dict:\n    \"\"\"\n    Breaks a big list into a list of lists.\n    Removes any list with no data then turns remaining\n    lists into key: value pairs with first element from the list being the key.\n    \"\"\"\n\n    chunks = [big_lst[x : x + 27] for x in range(0, len(big_lst), 27)]\n\n    # Remove the list if it contains no data.\n    for chunk in chunks:\n        if any(chunk):\n            continue\n        else:\n            chunks.remove(chunk)\n\n    chunked_list = {words[0]: words[1:] for words in chunks}\n\n    return chunked_list\n\n\ndef data_formatter(data: list[list[str]]) -> list[list[str]]:\n    \"\"\"\n    Aligns the tabular data to a standard format: (ID, hour_0, hour_1, ... , hour_23, hour_24)\n    \"\"\"\n\n    INIT_ROWS_TO_DROP = 26\n    data = data[INIT_ROWS_TO_DROP:]\n\n    def format_row(row: list[str]) -> list[str]:\n        # Case Grupo: X\n        match_grupo = len(row) == 2 and row[0] == \"\" and \"grupo\" in row[1].lower()\n        # Case Empresa: X\n        match_empresa = (\n            len(row) == 3\n            and all(c == \"\" for c in row[:2])\n            and \"empresa\" in row[2].lower()\n        )\n        # Case Unit: X\n        match_unit = len(row) == 27 and all(c == \"\" for c in row[:2])\n\n        if match_grupo:\n            return [row[1]] + [\"\"] * 24\n        elif match_empresa:\n            return [row[2]] + [\"\"] * 24\n        elif match_unit:\n            return row[2:]\n        else:\n            raise ValueError(f\"Unexpected row format: {row}\")\n\n    data = [format_row(row) for row in data]\n    return data\n\n\ndef correct_solar_production(production: pd.DataFrame) -> pd.DataFrame:\n    \"\"\"\n    Solar production is not reported when it's zero.\n    \"\"\"\n    if production.solar.isnull().all() or production.solar.notnull().all():\n        return production\n    production = production.copy()\n    null_production_index = production[production.solar.isnull()].index\n    max_non_null_solar_idx = production.solar.last_valid_index()\n    indices_to_set_to_zero = [\n        idx for idx in null_production_index if idx < max_non_null_solar_idx\n    ]\n    # Replace all NaN values with 0 up to the first non-null value\n    production.loc[indices_to_set_to_zero] = 0\n    return production\n\n\ndef extract_renewable_production(data: list[list[str]], dt: datetime) -> pd.DataFrame:\n    \"\"\"\n    Extract renewable production data from the total rows.\n    \"\"\"\n    renewable_indices = [\n        i for i, row in enumerate(data) if row[0] in TOTAL_RENEWABLES_MAPPING\n    ]\n    renewable_data = []\n    for i in renewable_indices:\n        row = data[i]\n        renewable_data.append([TOTAL_RENEWABLES_MAPPING[row[0]]] + row[1:])\n    df = pd.DataFrame(renewable_data, columns=[\"mode\"] + list(range(1, 25)))\n    # pivot to have hours as index and mode as columns\n    df = df.set_index(\"mode\").T\n    df.index = [get_datetime_from_hour(dt, hour) for hour in df.index]\n    df.index.name = \"datetime\"\n    # Convert to numeric\n    df = df.apply(pd.to_numeric)\n    df = correct_solar_production(df)\n    return df\n\n\ndef extract_thermal_production(data: list[list[str]], dt: datetime) -> pd.DataFrame:\n    \"\"\"\n    Extract thermal production from individual power plants.\n    \"\"\"\n    thermal_indices = [i for i, row in enumerate(data) if row[0] in THERMAL_PLANTS]\n    thermal_data = []\n    for i in thermal_indices:\n        row = data[i]\n        thermal_data.append([THERMAL_PLANTS.get(row[0], \"unknown\")] + row[1:])\n    df = pd.DataFrame(thermal_data, columns=[\"mode\"] + list(range(1, 25)))\n    # Convert numeric\n    df = df.apply(pd.to_numeric, errors=\"ignore\")\n    # Group by sum per mode\n    df = df.groupby(\"mode\").sum(numeric_only=True, min_count=1)\n    # pivot to have hours as index and mode as columns\n    df = df.T\n    df.index = [get_datetime_from_hour(dt, hour) for hour in df.index]\n    df.index.name = \"datetime\"\n    return df\n\n\n@use_proxy(country_code=\"DO\")\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"DO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    now = datetime.now(tz=ZoneInfo(\"America/Dominica\")).replace(\n        hour=0, minute=0, second=0, microsecond=0\n    )\n\n    data = data_formatter(get_data(session=session))\n    renewable_production = extract_renewable_production(data, now)\n    thermal_production = extract_thermal_production(data, now)\n    production = pd.concat([renewable_production, thermal_production], axis=1)\n    # only keep rows with at least one non-null value\n    production = production.dropna(how=\"all\")\n\n    production_list = ProductionBreakdownList(logger)\n    for ts, mix in production.iterrows():\n        production_mix = ProductionMix(**mix.to_dict())\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=ts.to_pydatetime(),\n            source=DO_SOURCE,\n            production=production_mix,\n        )\n\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/EC.py",
    "content": "#!/usr/bin/env python3\n\"\"\"\nEcuador (EC) electricity parser for electricitymaps by alixunderplatz / initiaded March 2026 based on issue #1558.\n\nSource:      CENACE — https://www.cenace.gob.ec/info-operativa/InformacionOperativa.htm\nGranularity: 30-minute intervals, current day only\nData:        Plotly.js charts embedded in HTML (binary float64 / bdata)\n\nProduction categories:\n  hydro    → Hidráulica\n  unknown  → Térmica + Gas Natural + Renovable\n             (fuel mix and renewable types not distinguishable from this source,\n             though a solar peak in the renovable-data is visible during the day,\n             as of March 2026)\n\nNote: \"Datos preliminares del SCADA, sujetos a revisión y validación.\"\n\"\"\"\n\nimport base64\nimport json\nimport re\nimport struct\nfrom datetime import date, datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport urllib3\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.types import ZoneKey\n\n# CENACE has an incomplete SSL certificate chain — suppress the warning.\nurllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)\n\nSOURCE = \"cenace.gob.ec\"\nZONE_KEY = ZoneKey(\"EC\")\nURL = \"https://www.cenace.gob.ec/info-operativa/InformacionOperativa.htm\"\nTZ_EC = ZoneInfo(\"America/Guayaquil\")\n\n# Maps the three chart series names from the real-time dashboard to electricitymaps categories.\nPRODUCTION_MAPPINGS = {\n    \"Hidr\\u00e1ulica\": \"hydro\",  # Hidráulica\n    \"T\\u00e9rmica\": \"unknown\",  # Térmica   (diesel/fuel oil/gas mix)\n    \"Renovable\": \"unknown\",  # Renovable (solar + wind, not split further)\n}\n\nMONTHS_ES = {\n    \"enero\": 1,\n    \"febrero\": 2,\n    \"marzo\": 3,\n    \"abril\": 4,\n    \"mayo\": 5,\n    \"junio\": 6,\n    \"julio\": 7,\n    \"agosto\": 8,\n    \"septiembre\": 9,\n    \"octubre\": 10,\n    \"noviembre\": 11,\n    \"diciembre\": 12,\n}\n\n\n# ── Plotly data decoding ──────────────────────────────────────────────────────\n\n\ndef _decode_bdata(b64: str) -> list:\n    \"\"\"Decode Plotly binary float64 array (base64, dtype f8).\"\"\"\n    raw = base64.b64decode(b64)\n    n = len(raw) // 8\n    return list(struct.unpack(f\"{n}d\", raw[: n * 8]))\n\n\ndef _get_y_values(trace: dict) -> list:\n    \"\"\"Return y-values from a Plotly trace, handling bdata and plain list.\"\"\"\n    if \"bdata\" in trace:\n        return _decode_bdata(trace[\"bdata\"])\n    y = trace.get(\"y\", [])\n    if isinstance(y, dict) and \"bdata\" in y:  # nested typed array\n        return _decode_bdata(y[\"bdata\"])\n    return [float(v) for v in y]\n\n\n# ── HTML parsing ──────────────────────────────────────────────────────────────\n\n\ndef _parse_traces(html: str) -> dict:\n    \"\"\"\n    Find the time-series chart (identified by 'stackgroup') and return all\n    series as: { series_name: {\"x\": [\"00:00\", ...], \"y\": [float, ...]} }\n    \"\"\"\n    for m in re.finditer(r'Plotly\\.newPlot\\(\\s*\"[^\"]+\"\\s*,\\s*', html):\n        pos = m.end()\n        if html[pos] != \"[\":\n            continue\n        if '\"stackgroup\"' not in html[pos : pos + 2000]:\n            continue\n        traces_data, _ = json.JSONDecoder().raw_decode(html, pos)\n        result = {}\n        for trace in traces_data:\n            name = trace.get(\"name\", \"\")\n            x = list(trace.get(\"x\", []))\n            y = _get_y_values(trace)\n            if name and x and y:\n                result[name] = {\"x\": x, \"y\": y}\n        return result\n    raise ValueError(\"No time-series chart (stackgroup) found in CENACE HTML\")\n\n\ndef _parse_page_date(html: str) -> date:\n    \"\"\"\n    Read the date from the CENACE page header, e.g.:\n      'Domingo, 22 de marzo de 2026'  →  date(2026, 3, 22)\n\n    More reliable than using the server clock: a server in UTC+1 at 01:00\n    would already be on the 23rd while Ecuador (UTC-5) is still on the 22nd.\n    Falls back to datetime.now(TZ_EC).date() if parsing fails.\n    \"\"\"\n    m = re.search(r\"(\\d{1,2})\\s+de\\s+(\\w+)\\s+de\\s+(\\d{4})\", html)\n    if m:\n        month = MONTHS_ES.get(m.group(2).lower())\n        if month:\n            return date(int(m.group(3)), month, int(m.group(1)))\n    return datetime.now(TZ_EC).date()  # fallback\n\n\ndef _str_to_dt(time_str: str, today: date) -> datetime:\n    \"\"\"Convert '13:30' + date from page header → timezone-aware datetime for Ecuador.\"\"\"\n    h, m = map(int, str(time_str).split(\":\"))\n    return datetime(today.year, today.month, today.day, h, m, tzinfo=TZ_EC)\n\n\n# ── Public parser functions ───────────────────────────────────────────────────\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Fetch real-time production breakdown for Ecuador (30-min resolution).\n    Only current-day data is available. target_datetime is ignored.\n    \"\"\"\n    s = session or Session()\n    logger.info(f\"Fetching Ecuador production from {URL}\")\n\n    resp = s.get(URL, timeout=30, verify=False)\n    resp.raise_for_status()\n\n    traces = _parse_traces(resp.text)\n    today = _parse_page_date(resp.text)\n    now_ec = datetime.now(TZ_EC)\n\n    ref = next((v for k, v in traces.items() if k in PRODUCTION_MAPPINGS), None)\n    if ref is None:\n        raise ValueError(\"No production data found in CENACE chart\")\n\n    production_list = ProductionBreakdownList(logger)\n\n    for i, ts in enumerate(ref[\"x\"]):\n        dt = _str_to_dt(ts, today)\n        if dt > now_ec:\n            break\n\n        mix = ProductionMix()\n        for series_name, series_data in traces.items():\n            if series_name not in PRODUCTION_MAPPINGS:\n                continue\n            em_key = PRODUCTION_MAPPINGS[series_name]\n            val = float(series_data[\"y\"][i]) if i < len(series_data[\"y\"]) else 0.0\n            if val != val:\n                continue  # NaN\n            val = max(val, 0.0)\n            current = getattr(mix, em_key) or 0.0\n            setattr(mix, em_key, round(current + val, 3))\n\n        # Skip slot if SCADA has not yet populated any value (all NaN)\n        if mix.hydro is None and mix.unknown is None:\n            continue\n\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            production=mix,\n            source=SOURCE,\n        )\n\n    logger.info(f\"fetch_production: {len(production_list.events)} datapoints\")\n    return production_list.to_list()\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Fetch real-time national demand (DEMANDA NACIONAL) for Ecuador.\n    \"\"\"\n    s = session or Session()\n    logger.info(f\"Fetching Ecuador consumption from {URL}\")\n\n    resp = s.get(URL, timeout=30, verify=False)\n    resp.raise_for_status()\n\n    traces = _parse_traces(resp.text)\n    today = _parse_page_date(resp.text)\n    now_ec = datetime.now(TZ_EC)\n\n    demand_trace = next((v for k, v in traces.items() if \"DEMANDA\" in k.upper()), None)\n    if demand_trace is None:\n        logger.warning(\"DEMANDA NACIONAL trace not found\")\n        return []\n\n    consumption_list = TotalConsumptionList(logger)\n\n    for i, ts in enumerate(demand_trace[\"x\"]):\n        dt = _str_to_dt(ts, today)\n        if dt > now_ec:\n            break\n        val = float(demand_trace[\"y\"][i])\n        if val != val or val <= 0:\n            continue\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            consumption=round(val, 3),\n            source=SOURCE,\n        )\n\n    logger.info(f\"fetch_consumption: {len(consumption_list.events)} datapoints\")\n    return consumption_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ECO2MIX.py",
    "content": "#!/usr/bin/env python3\n\nimport math\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nimport requests\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZONES_CONFIG\nfrom electricitymap.contrib.lib.models.event_lists import ExchangeList\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\n# from .lib.validation import validate, validate_production_diffs\n\n# From RTE domain to EM domain\nMAP_ZONES = {\n    \"France\": \"FR\",\n    **{\n        subzone.replace(\"FR-\", \"\"): subzone\n        for subzone in ZONES_CONFIG[\"FR\"].get(\"subZoneNames\", [])\n    },\n    \"BE\": \"BE\",\n    \"CH\": \"CH\",\n    \"DE\": \"DE\",\n    \"ES\": \"ES\",\n    \"GB\": \"GB\",\n    \"IT\": \"IT-NO\",\n    \"LU\": \"LU\",\n    \"ACA\": \"FR-ACA\",  # Manual mapping since we can't read the subzones yet\n    \"ARA\": \"FR-ARA\",\n    \"BFC\": \"FR-BFC\",\n    \"BRE\": \"FR-BRE\",\n    \"CEN\": \"FR-CEN\",\n    \"NPP\": \"FR-NPP\",\n    \"IDF\": \"FR-IDF\",\n    \"NOR\": \"FR-NOR\",\n    \"ALP\": \"FR-ALP\",\n    \"LRM\": \"FR-LRM\",\n    \"PLO\": \"FR-PLO\",\n    \"PAC\": \"FR-PAC\",\n}\n\nEXCHANGE_OVERRIDE = {\n    \"DE->FR\": (ZoneKey(\"DE\"), ZoneKey(\"FR-ACA\")),\n    \"FR->LU\": (ZoneKey(\"FR-ACA\"), ZoneKey(\"LU\")),\n}\n\nMAP_MODES = {\n    \"Nucléaire\": \"production.nuclear\",\n    \"Thermique\": \"production.unknown\",\n    \"Eolien\": \"production.wind\",\n    \"Solaire\": \"production.solar\",\n    \"Hydraulique\": \"production.hydro\",\n    \"Bioénergies\": \"production.biomass\",\n    \"Consommation\": \"consumption\",\n    \"Autres\": \"production.unknown\",\n    \"Charbon\": \"production.coal\",\n    \"Fioul\": \"production.oil\",\n    \"Gaz\": \"production.gas\",\n    \"Pompage\": \"storage.hydro\",\n    \"Destockage\": \"storage.hydro\",\n    \"Batterie_Injection\": \"storage.battery\",\n    \"Batterie_Soutirage\": \"storage.battery\",\n    \"Stockage\": \"storage.battery\",\n    \"Solde\": \"IGNORED\",\n    \"Co2\": \"IGNORED\",\n    \"Taux de Co2\": \"IGNORED\",\n    \"PrévisionJ\": \"IGNORED\",\n    \"PrévisionJ-1\": \"IGNORED\",\n}\n\nSOURCE = \"rte-france.com\"\n\n\ndef query(url_type_arg, session: Session, target_datetime: datetime | None):\n    if target_datetime:\n        date_to = target_datetime.replace(tzinfo=ZoneInfo(\"Europe/Paris\"))\n    else:\n        date_to = datetime.now(tz=ZoneInfo(\"Europe/Paris\"))\n    date_from = (date_to - timedelta(days=1)).replace(\n        hour=0, minute=0, second=0, microsecond=0\n    )\n    date_from = date_from.strftime(\"%d/%m/%Y\")\n    date_to = date_to.strftime(\"%d/%m/%Y\")\n\n    url = f\"http://www.rte-france.com/getEco2MixXml.php?type={url_type_arg}&dateDeb={date_from}&dateFin={date_to}\"\n    if url_type_arg == \"regionFlux\":\n        url = url.replace(\"dateDeb\", \"dateDebut\")\n    r = session or requests.session()\n    response = r.get(url, verify=False)\n    response.raise_for_status()\n    return response.text\n\n\ndef query_exchange(session: Session, target_datetime: datetime | None):\n    return query(\n        url_type_arg=\"regionFlux\", session=session, target_datetime=target_datetime\n    )\n\n\ndef query_production(session: Session, target_datetime: datetime | None):\n    return query(\n        url_type_arg=\"region\", session=session, target_datetime=target_datetime\n    )\n\n\ndef parse_production_to_df(text):\n    bs_content = BeautifulSoup(text, features=\"xml\")\n    # Flatten\n    df = pd.DataFrame(\n        [\n            {\n                **valeur.attrs,\n                **valeur.parent.attrs,\n                **valeur.parent.parent.attrs,\n                \"value\": valeur.contents[0],\n            }\n            for valeur in bs_content.find_all(\"valeur\")\n        ]\n    )\n    if df.empty:\n        return df\n    # Add datetime\n    df[\"datetime\"] = pd.to_datetime(df[\"date\"]) + pd.to_timedelta(\n        df[\"periode\"].astype(\"int\") * 15, unit=\"minute\"\n    )\n    df.datetime = df.datetime.dt.tz_localize(\"Europe/Paris\")\n    # Set index\n    df = df.set_index(\"datetime\").drop([\"date\", \"periode\"], axis=1)\n    # Remove invalid granularities\n    df = df[df.granularite == \"Global\"].drop(\"granularite\", axis=1)\n    # Create key (will crash if a mode is not in the map and ensures we coded this right)\n    df[\"key\"] = df.v.apply(lambda k: MAP_MODES[k])\n    # Filter out invalid modes\n    df = df[df.key != \"IGNORED\"]\n    # Compute zone_key\n    df[\"zone_key\"] = df[\"perimetre\"].apply(lambda k: MAP_ZONES[k])\n    # Compute values\n    df.value = df.value.replace(\"ND\", math.nan).replace(\"-\", math.nan).astype(\"float\")\n    # Storage works the other way around (RTE treats storage as production)\n    df.loc[df.key.str.startswith(\"storage.\"), \"value\"] *= -1\n    return df\n\n\ndef format_production_df(df, zone_key):\n    if df.empty:\n        return []\n    # There can be multiple rows with the same key\n    # (e.g. multiple things lumping into `unknown`)\n    # so we need to group them and sum.\n    df = (\n        df[df.zone_key == zone_key]\n        .reset_index()\n        .groupby([\"datetime\", \"key\"])\n        # We use `min_count=1` to make sure at least one non-NaN\n        # value is present to compute a sum.\n        .sum(numeric_only=True, min_count=1)\n        # We unstack `key` which creates a df where keys are columns\n        .unstack(\"key\")[\"value\"]\n    )\n    return [\n        {\n            \"zoneKey\": zone_key,\n            \"datetime\": ts.to_pydatetime(),\n            \"production\": (\n                row.filter(like=\"production.\")\n                .rename(lambda c: c.replace(\"production.\", \"\"))\n                .to_dict()\n            ),\n            \"storage\": (\n                row.filter(like=\"storage.\")\n                .rename(lambda c: c.replace(\"storage.\", \"\"))\n                .to_dict()\n            ),\n            \"source\": SOURCE,\n        }\n        for (ts, row) in df.iterrows()\n    ]\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key, session=None, target_datetime=None, logger: Logger = getLogger(__name__)\n):\n    if zone_key == \"FR-COR\":\n        raise ParserException(\"ECO2MIX.py\", \"FR-COR is not supported in this parser\")\n\n    datapoints = [\n        # validate(d, logger, required=VALIDATIONS.get(zone_key, []))\n        # for d in\n        format_production_df(\n            df=parse_production_to_df(query_production(session, target_datetime)),\n            zone_key=zone_key,\n        )\n    ]\n\n    return datapoints\n\n\ndef parse_exchange_to_df(text):\n    bs_content = BeautifulSoup(text, features=\"xml\")\n    # Flatten\n    df = pd.DataFrame(\n        [\n            {\n                **valeur.attrs,\n                **valeur.parent.attrs,\n                **valeur.parent.parent.attrs,\n                \"value\": valeur.contents[0],\n            }\n            for valeur in bs_content.find_all(\"valeur\")\n        ]\n    )\n    # Add datetime\n    if df.empty:\n        return df\n    df[\"datetime\"] = pd.to_datetime(df[\"date\"]) + pd.to_timedelta(\n        df[\"periode\"].astype(\"int\") * 15, unit=\"minute\"\n    )\n    df.datetime = df.datetime.dt.tz_localize(\"Europe/Paris\")\n    # Set index\n    df = df.set_index(\"datetime\").drop([\"date\", \"periode\"], axis=1)\n    # Remove invalid granularities\n    df = df[df.granularite == \"Global\"].drop(\"granularite\", axis=1)\n    # Compute values\n    df.value = df.value.replace(\"ND\", math.nan).replace(\"-\", math.nan).astype(\"float\")\n    df[\"zone_key_other\"] = df.v.apply(lambda x: MAP_ZONES[x.split(\"_\")[1]])\n    df[\"zone_key\"] = df.perimetre.apply(lambda k: MAP_ZONES[k])\n    df[\"sorted_zone_keys\"] = df.apply(\n        lambda row: \"->\".join(sorted([row[\"zone_key\"], row[\"zone_key_other\"]])), axis=1\n    )\n\n    # Data comes in for all zones, which means on zone's import\n    # will be another's export. We therefore only keep one of them\n    df = df[\n        df.perimetre\n        == df.sorted_zone_keys.apply(\n            # make sure we only selected rows where `perimetre`\n            # is one of the FR- keys of the pair (to make sure we capture\n            # exchange with neighboring countries)\n            lambda k: [\n                zone_key.replace(\"FR-\", \"\")\n                for zone_key in k.split(\"->\")\n                if \"FR-\" in zone_key\n            ][0]\n        )\n    ]\n    # RTE defines flow in the follow way:\n    # `value` represents flow from `zone_key_other` to `zone_key` (`perimetre`)\n    # We here flip the sign if the alphabetical order requires it\n    # (e.g. if zone_key is not the second key)\n    df[\"net_flow\"] = df.apply(\n        lambda row: (\n            row[\"value\"]\n            if row[\"sorted_zone_keys\"].split(\"->\")[1] == row[\"zone_key\"]\n            else row[\"value\"] * -1\n        ),\n        axis=1,\n    )\n    return df\n\n\ndef format_exchange_df(df, sorted_zone_keys: ZoneKey, logger: Logger):\n    # There can be multiple rows with the same key\n    # (e.g. multiple things lumping into `unknown`)\n    # so we need to group them and sum.\n    if df.empty:\n        return []\n    # Handle exchange overrides, this is temporary until we use all FR subzones\n    new_zone_keys = None\n    if sorted_zone_keys in EXCHANGE_OVERRIDE:\n        zone_key1, zone_key2 = EXCHANGE_OVERRIDE[sorted_zone_keys]\n        new_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    use_zone_key = new_zone_keys or sorted_zone_keys\n\n    df = (\n        df[df.sorted_zone_keys == use_zone_key]\n        .reset_index()\n        .groupby([\"datetime\"])\n        # We use `min_count=1` to make sure at least one non-NaN\n        # value is present to compute a sum.\n        .sum(numeric_only=True, min_count=1)\n    )\n    exchange_list = ExchangeList(logger)\n    for ts, row in df.iterrows():\n        exchange_list.append(\n            zoneKey=sorted_zone_keys,\n            datetime=ts.to_pydatetime(),\n            netFlow=row.net_flow,\n            source=SOURCE,\n        )\n    return exchange_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    session = session or Session()\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    datapoints = format_exchange_df(\n        df=parse_exchange_to_df(query_exchange(session, target_datetime)),\n        sorted_zone_keys=sorted_zone_keys,\n        logger=logger,\n    )\n    return datapoints\n\n\nif __name__ == \"__main__\":\n    session = requests.Session()\n    # target_datetime = datetime.now(tz=ZoneInfo(\"Europe/Paris\"))\n    target_datetime = datetime(2025, 8, 19, 0, 0, 0, tzinfo=ZoneInfo(\"Europe/Paris\"))\n    print(\n        fetch_production(\n            zone_key=\"FR-ARA\", session=session, target_datetime=target_datetime\n        )\n    )\n    print(\n        fetch_exchange(\n            zone_key1=ZoneKey(\"FR-BRE\"),\n            zone_key2=ZoneKey(\"FR-PLO\"),\n            session=session,\n            target_datetime=target_datetime,\n        )\n    )\n    print(\n        fetch_exchange(\n            zone_key1=ZoneKey(\"FR-BRE\"),\n            zone_key2=ZoneKey(\"FR-NOR\"),\n            session=session,\n            target_datetime=target_datetime,\n        )\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/EIA.py",
    "content": "#!/usr/bin/env python3\n\"\"\"\nParser for U.S. Energy Information Administration, https://www.eia.gov/ .\n\nAggregates and standardizes data from most of the US ISOs,\nand exposes them via a unified API.\n\nRequires an API key, set in the EIA_KEY environment variable. Get one here:\nhttps://www.eia.gov/opendata/register.php\n\"\"\"\n\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any\n\nfrom dateutil import parser\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.utils import get_token\nfrom electricitymap.contrib.types import ZoneKey\n\n# Reverse exchanges need to be multiplied by -1, since they are reported in the opposite direction\nREVERSE_EXCHANGES = [\n    \"US-CA->MX-BC\",\n    \"MX-BC->US-CAL-CISO\",\n    \"CA-SK->US-CENT-SWPP\",\n    \"CA-MB->US-MIDW-MISO\",\n    \"CA-ON->US-MIDW-MISO\",\n    \"CA-QC->US-NE-ISNE\",\n    \"CA-NB->US-NE-ISNE\",\n    \"CA-BC->US-NW-BPAT\",\n    \"CA-AB->US-NW-NWMT\",\n    \"CA-QC->US-NY-NYIS\",\n    \"CA-ON->US-NY-NYIS\",\n    \"MX-NE->US-TEX-ERCO\",\n    \"MX-NO->US-TEX-ERCO\",\n    \"US-SW-PNM->US-SW-SRP\",  # For some reason EBA.SRP-PNM.ID.H exists in EIA, but PNM-SRP does not. Probably because it is unidirectional\n]\n\n# Those threshold correspond to the ranges where the negative values are most likely\n# self consumption and should be set to 0 for production that is being injected into the grid.\nNEGATIVE_PRODUCTION_THRESHOLDS_TYPE = {\n    \"default\": -10,\n    \"coal\": -50,\n    \"gas\": -20,\n    \"solar\": -100,\n    \"wind\": -20,\n    \"unknown\": -50,\n}\n\n# based on https://www.eia.gov/beta/electricity/gridmonitor/dashboard/electric_overview/US48/US48\n# or https://www.eia.gov/opendata/qb.php?category=3390101\n# List includes regions and Balancing Authorities.\nREGIONS = {\n    # Non-US regions - EIA\n    \"MX-BC\": \"CFE\",\n    \"MX-NE\": \"CEN\",\n    \"MX-NO\": \"CFE\",\n    \"CA-SK\": \"SPC\",\n    \"CA-MB\": \"MHEB\",\n    \"CA-ON\": \"IESO\",\n    \"CA-QC\": \"HQT\",\n    \"CA-NB\": \"NBSO\",\n    \"CA-BC\": \"BCHA\",\n    \"CA-AB\": \"AESO\",\n    # New regions - EIA\n    \"US-CAL-BANC\": \"BANC\",  # Balancing Authority Of Northern California\n    \"US-CAL-CISO\": \"CISO\",  # California Independent System Operator\n    \"US-CAL-IID\": \"IID\",  # Imperial Irrigation District\n    \"US-CAL-LDWP\": \"LDWP\",  # Los Angeles Department Of Water And Power\n    \"US-CAL-TIDC\": \"TIDC\",  # Turlock Irrigation District\n    \"US-CAR-CPLE\": \"CPLE\",  # Duke Energy Progress East\n    \"US-CAR-CPLW\": \"CPLW\",  # Duke Energy Progress West\n    \"US-CAR-DUK\": \"DUK\",  # Duke Energy Carolinas\n    \"US-CAR-SC\": \"SC\",  # South Carolina Public Service Authority\n    \"US-CAR-SCEG\": \"SCEG\",  # South Carolina Electric & Gas Company\n    \"US-CAR-YAD\": \"YAD\",  # Alcoa Power Generating, Inc. - Yadkin Division\n    \"US-CENT-SPA\": \"SPA\",  # Southwestern Power Administration\n    \"US-CENT-SWPP\": \"SWPP\",  # Southwest Power Pool\n    \"US-FLA-FMPP\": \"FMPP\",  # Florida Municipal Power Pool\n    \"US-FLA-FPC\": \"FPC\",  # Duke Energy Florida Inc\n    \"US-FLA-FPL\": \"FPL\",  # Florida Power & Light Company\n    \"US-FLA-GVL\": \"GVL\",  # Gainesville Regional Utilities\n    \"US-FLA-HST\": \"HST\",  # City Of Homestead\n    \"US-FLA-JEA\": \"JEA\",  # Jea\n    \"US-FLA-NSB\": \"NSB\",  # Utilities Commission Of New Smyrna Beach, Decomissioned data is directly integrated in another balancing authority\n    # Some solar plants within this zone are operated by Florida Power & Light, therefore on the map the zones got merged.\n    \"US-FLA-SEC\": \"SEC\",  # Seminole Electric Cooperative\n    \"US-FLA-TAL\": \"TAL\",  # City Of Tallahassee\n    \"US-FLA-TEC\": \"TEC\",  # Tampa Electric Company\n    \"US-MIDA-PJM\": \"PJM\",  # Pjm Interconnection, Llc\n    \"US-MIDW-AECI\": \"AECI\",  # Associated Electric Cooperative, Inc.\n    # \"US-MIDW-GLHB\": \"GLHB\",  # GridLiance US-MIDW-GLHB decommissioned no more powerplant\n    \"US-MIDW-LGEE\": \"LGEE\",  # Louisville Gas And Electric Company And Kentucky Utilities\n    \"US-MIDW-MISO\": \"MISO\",  # Midcontinent Independent Transmission System Operator, Inc..\n    \"US-NE-ISNE\": \"ISNE\",  # Iso New England Inc.\n    \"US-NW-AVA\": \"AVA\",  # Avista Corporation\n    \"US-NW-AVRN\": \"AVRN\",  # Avangrid Renewables, LLC, integrated with US-NW-BPAT and US-NW-PACW\n    \"US-NW-BPAT\": \"BPAT\",  # Bonneville Power Administration\n    \"US-NW-CHPD\": \"CHPD\",  # Public Utility District No. 1 Of Chelan County\n    \"US-NW-DOPD\": \"DOPD\",  # Pud No. 1 Of Douglas County\n    \"US-NW-GCPD\": \"GCPD\",  # Public Utility District No. 2 Of Grant County, Washington\n    \"US-NW-GRID\": \"GRID\",  # Gridforce Energy Management, Llc\n    \"US-NW-GWA\": \"GWA\",  # Naturener Power Watch, Llc (Gwa), integrated with US-NW-NWMT\n    \"US-NW-IPCO\": \"IPCO\",  # Idaho Power Company\n    \"US-NW-NEVP\": \"NEVP\",  # Nevada Power Company\n    \"US-NW-NWMT\": \"NWMT\",  # Northwestern Energy (Nwmt)\n    \"US-NW-PACE\": \"PACE\",  # Pacificorp - East\n    \"US-NW-PACW\": \"PACW\",  # Pacificorp - West\n    \"US-NW-PGE\": \"PGE\",  # Portland General Electric Company\n    \"US-NW-PSCO\": \"PSCO\",  # Public Service Company Of Colorado\n    \"US-NW-PSEI\": \"PSEI\",  # Puget Sound Energy\n    \"US-NW-SCL\": \"SCL\",  # Seattle City Light\n    \"US-NW-TPWR\": \"TPWR\",  # City Of Tacoma, Department Of Public Utilities, Light Division\n    \"US-NW-WACM\": \"WACM\",  # Western Area Power Administration - Rocky Mountain Region\n    \"US-NW-WAUW\": \"WAUW\",  # Western Area Power Administration Ugp West\n    \"US-NW-WWA\": \"WWA\",  # Naturener Wind Watch, Llc, integrated with US-NW-NWMT\n    \"US-NY-NYIS\": \"NYIS\",  # New York Independent System Operator\n    \"US-SE-AEC\": \"AEC\",  # Powersouth Energy Cooperative, decomissioned merged with US-SE-SOCO\n    # Though it is unclear which BA took over AEC.\n    \"US-SE-SEPA\": \"SEPA\",  # Southeastern Power Administration\n    \"US-SE-SOCO\": \"SOCO\",  # Southern Company Services, Inc. - Trans\n    \"US-SW-AZPS\": \"AZPS\",  # Arizona Public Service Company\n    \"US-SW-DEAA\": \"DEAA\",  # Arlington Valley, LLC, integrated with US-SW-SRP\n    \"US-SW-EPE\": \"EPE\",  # El Paso Electric Company\n    \"US-SW-GRIF\": \"GRIF\",  # Griffith Energy, Llc, integrated with US-SW-WALC\n    \"US-SW-GRMA\": \"GRMA\",  # Gila River Power, Llc Decommissioned,\n    #  The only gas power plant is owned by US-SW-SRP but there's a PPA with US-SW-AZPS, so it was merged with\n    # US-SW-AZPS https://www.power-technology.com/marketdata/gila-river-power-station-us/\n    \"US-SW-HGMA\": \"HGMA\",  # New Harquahala Generating Company, Llc - Hgba, integrated with US-SW-SRP\n    \"US-SW-PNM\": \"PNM\",  # Public Service Company Of New Mexico\n    \"US-SW-SRP\": \"SRP\",  # Salt River Project\n    \"US-SW-TEPC\": \"TEPC\",  # Tucson Electric Power Company\n    \"US-SW-WALC\": \"WALC\",  # Western Area Power Administration - Desert Southwest Region\n    \"US-TEN-TVA\": \"TVA\",  # Tennessee Valley Authority\n    \"US-TEX-ERCO\": \"ERCO\",  # Electric Reliability Council Of Texas, Inc.\n}\n\nEXCHANGES = {\n    # Exchanges to non-US BAs\n    \"MX-BC->US-CAL-CISO\": \"&facets[fromba][]=CISO&facets[toba][]=CFE\",  # Unable to verify if MX-BC is correct\n    \"CA-SK->US-CENT-SWPP\": \"&facets[fromba][]=SWPP&facets[toba][]=SPC\",\n    \"CA-MB->US-MIDW-MISO\": \"&facets[fromba][]=MISO&facets[toba][]=MHEB\",\n    \"CA-ON->US-MIDW-MISO\": \"&facets[fromba][]=MISO&facets[toba][]=IESO\",\n    \"CA-QC->US-NE-ISNE\": \"&facets[fromba][]=ISNE&facets[toba][]=HQT\",\n    \"CA-NB->US-NE-ISNE\": \"&facets[fromba][]=ISNE&facets[toba][]=NBSO\",\n    \"CA-BC->US-NW-BPAT\": \"&facets[fromba][]=BPAT&facets[toba][]=BCHA\",\n    \"CA-AB->US-NW-NWMT\": \"&facets[fromba][]=NWMT&facets[toba][]=AESO\",\n    \"CA-QC->US-NY-NYIS\": \"&facets[fromba][]=NYIS&facets[toba][]=HQT\",\n    \"CA-ON->US-NY-NYIS\": \"&facets[fromba][]=NYIS&facets[toba][]=IESO\",\n    \"MX-NE->US-TEX-ERCO\": \"&facets[fromba][]=ERCO&facets[toba][]=CEN\",  # Unable to verify if MX-NE is correct\n    \"MX-NO->US-TEX-ERCO\": \"&facets[fromba][]=ERCO&facets[toba][]=CFE\",  # Unable to verify if MX-NO is correct\n    # Exchanges to other US balancing authorities\n    \"US-CAL-BANC->US-NW-BPAT\": \"&facets[fromba][]=BANC&facets[toba][]=BPAT\",\n    \"US-CAL-BANC->US-CAL-CISO\": \"&facets[fromba][]=BANC&facets[toba][]=CISO\",\n    \"US-CAL-BANC->US-CAL-TIDC\": \"&facets[fromba][]=BANC&facets[toba][]=TIDC\",\n    \"US-CAL-CISO->US-SW-AZPS\": \"&facets[fromba][]=CISO&facets[toba][]=AZPS\",\n    \"US-CAL-CISO->US-NW-BPAT\": \"&facets[fromba][]=CISO&facets[toba][]=BPAT\",\n    \"US-CAL-CISO->US-CAL-IID\": \"&facets[fromba][]=CISO&facets[toba][]=IID\",\n    \"US-CAL-CISO->US-CAL-LDWP\": \"&facets[fromba][]=CISO&facets[toba][]=LDWP\",\n    \"US-CAL-CISO->US-NW-NEVP\": \"&facets[fromba][]=CISO&facets[toba][]=NEVP\",\n    \"US-CAL-CISO->US-NW-PACW\": \"&facets[fromba][]=CISO&facets[toba][]=PACW\",\n    \"US-CAL-CISO->US-SW-SRP\": \"&facets[fromba][]=CISO&facets[toba][]=SRP\",\n    \"US-CAL-CISO->US-CAL-TIDC\": \"&facets[fromba][]=CISO&facets[toba][]=TIDC\",\n    \"US-CAL-CISO->US-SW-WALC\": \"&facets[fromba][]=CISO&facets[toba][]=WALC\",\n    \"US-CAL-IID->US-SW-AZPS\": \"&facets[fromba][]=IID&facets[toba][]=AZPS\",\n    \"US-CAL-IID->US-SW-WALC\": \"&facets[fromba][]=IID&facets[toba][]=WALC\",\n    \"US-CAL-LDWP->US-SW-AZPS\": \"&facets[fromba][]=LDWP&facets[toba][]=AZPS\",\n    \"US-CAL-LDWP->US-NW-BPAT\": \"&facets[fromba][]=LDWP&facets[toba][]=BPAT\",\n    \"US-CAL-LDWP->US-NW-NEVP\": \"&facets[fromba][]=LDWP&facets[toba][]=NEVP\",\n    \"US-CAL-LDWP->US-NW-PACE\": \"&facets[fromba][]=LDWP&facets[toba][]=PACE\",\n    \"US-CAL-LDWP->US-SW-WALC\": \"&facets[fromba][]=LDWP&facets[toba][]=WALC\",\n    \"US-CAR-CPLE->US-CAR-YAD\": \"&facets[fromba][]=CPLE&facets[toba][]=YAD\",\n    \"US-CAR-CPLE->US-CAR-DUK\": \"&facets[fromba][]=CPLE&facets[toba][]=DUK\",\n    \"US-CAR-CPLE->US-MIDA-PJM\": \"&facets[fromba][]=CPLE&facets[toba][]=PJM\",\n    \"US-CAR-CPLE->US-CAR-SCEG\": \"&facets[fromba][]=CPLE&facets[toba][]=SCEG\",\n    \"US-CAR-CPLE->US-CAR-SC\": \"&facets[fromba][]=CPLE&facets[toba][]=SC\",\n    \"US-CAR-CPLW->US-CAR-DUK\": \"&facets[fromba][]=CPLW&facets[toba][]=DUK\",\n    \"US-CAR-CPLW->US-MIDA-PJM\": \"&facets[fromba][]=CPLW&facets[toba][]=PJM\",\n    \"US-CAR-CPLW->US-TEN-TVA\": \"&facets[fromba][]=CPLW&facets[toba][]=TVA\",\n    \"US-CAR-DUK->US-CAR-YAD\": \"&facets[fromba][]=DUK&facets[toba][]=YAD\",\n    \"US-CAR-DUK->US-MIDA-PJM\": \"&facets[fromba][]=DUK&facets[toba][]=PJM\",\n    \"US-CAR-DUK->US-CAR-SCEG\": \"&facets[fromba][]=DUK&facets[toba][]=SCEG\",\n    \"US-CAR-DUK->US-CAR-SC\": \"&facets[fromba][]=DUK&facets[toba][]=SC\",\n    \"US-CAR-DUK->US-SE-SEPA\": \"&facets[fromba][]=DUK&facets[toba][]=SEPA\",\n    \"US-CAR-DUK->US-SE-SOCO\": \"&facets[fromba][]=DUK&facets[toba][]=SOCO\",\n    \"US-CAR-DUK->US-TEN-TVA\": \"&facets[fromba][]=DUK&facets[toba][]=TVA\",\n    \"US-CAR-SC->US-CAR-SCEG\": \"&facets[fromba][]=SC&facets[toba][]=SCEG\",\n    \"US-CAR-SC->US-SE-SEPA\": \"&facets[fromba][]=SC&facets[toba][]=SEPA\",\n    \"US-CAR-SC->US-SE-SOCO\": \"&facets[fromba][]=SC&facets[toba][]=SOCO\",\n    \"US-CAR-SCEG->US-SE-SEPA\": \"&facets[fromba][]=SCEG&facets[toba][]=SEPA\",\n    \"US-CAR-SCEG->US-SE-SOCO\": \"&facets[fromba][]=SCEG&facets[toba][]=SOCO\",\n    \"US-CENT-SPA->US-MIDW-AECI\": \"&facets[fromba][]=SPA&facets[toba][]=AECI\",\n    \"US-CENT-SPA->US-MIDW-MISO\": \"&facets[fromba][]=SPA&facets[toba][]=MISO\",\n    \"US-CENT-SPA->US-CENT-SWPP\": \"&facets[fromba][]=SPA&facets[toba][]=SWPP\",\n    \"US-CENT-SWPP->US-MIDW-AECI\": \"&facets[fromba][]=SWPP&facets[toba][]=AECI\",\n    \"US-CENT-SWPP->US-SW-EPE\": \"&facets[fromba][]=SWPP&facets[toba][]=EPE\",\n    \"US-CENT-SWPP->US-TEX-ERCO\": \"&facets[fromba][]=SWPP&facets[toba][]=ERCO\",\n    \"US-CENT-SWPP->US-MIDW-MISO\": \"&facets[fromba][]=SWPP&facets[toba][]=MISO\",\n    \"US-CENT-SWPP->US-NW-PSCO\": \"&facets[fromba][]=SWPP&facets[toba][]=PSCO\",\n    \"US-CENT-SWPP->US-SW-PNM\": \"&facets[fromba][]=SWPP&facets[toba][]=PNM\",\n    \"US-CENT-SWPP->US-NW-WACM\": \"&facets[fromba][]=SWPP&facets[toba][]=WACM\",\n    \"US-CENT-SWPP->US-NW-WAUW\": \"&facets[fromba][]=SWPP&facets[toba][]=WAUW\",\n    \"US-FLA-FMPP->US-FLA-FPC\": \"&facets[fromba][]=FMPP&facets[toba][]=FPC\",\n    \"US-FLA-FMPP->US-FLA-FPL\": \"&facets[fromba][]=FMPP&facets[toba][]=FPL\",\n    \"US-FLA-FMPP->US-FLA-JEA\": \"&facets[fromba][]=FMPP&facets[toba][]=JEA\",\n    \"US-FLA-FMPP->US-FLA-TEC\": \"&facets[fromba][]=FMPP&facets[toba][]=TEC\",\n    \"US-FLA-FPC->US-FLA-TAL\": \"&facets[fromba][]=FPC&facets[toba][]=TAL\",\n    \"US-FLA-FPC->US-FLA-FPL\": \"&facets[fromba][]=FPC&facets[toba][]=FPL\",\n    \"US-FLA-FPC->US-FLA-GVL\": \"&facets[fromba][]=FPC&facets[toba][]=GVL\",\n    \"US-FLA-FPC->US-FLA-SEC\": \"&facets[fromba][]=FPC&facets[toba][]=SEC\",\n    \"US-FLA-FPC->US-SE-SOCO\": \"&facets[fromba][]=FPC&facets[toba][]=SOCO\",\n    \"US-FLA-FPC->US-FLA-TEC\": \"&facets[fromba][]=FPC&facets[toba][]=TEC\",\n    \"US-FLA-FPC->US-FLA-NSB\": \"&facets[fromba][]=FPC&facets[toba][]=NSB\",  # decomissioned NSB zone, merged with FPL, exchange transfered\n    \"US-FLA-FPL->US-FLA-HST\": \"&facets[fromba][]=FPL&facets[toba][]=HST\",\n    \"US-FLA-FPL->US-FLA-GVL\": \"&facets[fromba][]=FPL&facets[toba][]=GVL\",\n    \"US-FLA-FPL->US-FLA-JEA\": \"&facets[fromba][]=FPL&facets[toba][]=JEA\",\n    \"US-FLA-FPL->US-FLA-SEC\": \"&facets[fromba][]=FPL&facets[toba][]=SEC\",\n    \"US-FLA-FPL->US-SE-SOCO\": \"&facets[fromba][]=FPL&facets[toba][]=SOCO\",\n    \"US-FLA-FPL->US-FLA-TEC\": \"&facets[fromba][]=FPL&facets[toba][]=TEC\",\n    #    \"US-FLA-FPL->US-FLA-NSB\": \"&facets[fromba][]=FPL&facets[toba][]=NSB\", decomissioned NSB zone\n    \"US-FLA-JEA->US-FLA-SEC\": \"&facets[fromba][]=JEA&facets[toba][]=SEC\",\n    \"US-FLA-SEC->US-FLA-TEC\": \"&facets[fromba][]=SEC&facets[toba][]=TEC\",\n    \"US-FLA-TAL->US-SE-SOCO\": \"&facets[fromba][]=TAL&facets[toba][]=SOCO\",\n    \"US-MIDA-PJM->US-MIDW-LGEE\": \"&facets[fromba][]=PJM&facets[toba][]=LGEE\",\n    \"US-MIDA-PJM->US-MIDW-MISO\": \"&facets[fromba][]=PJM&facets[toba][]=MISO\",\n    \"US-MIDA-PJM->US-NY-NYIS\": \"&facets[fromba][]=PJM&facets[toba][]=NYIS\",\n    \"US-MIDA-PJM->US-TEN-TVA\": \"&facets[fromba][]=PJM&facets[toba][]=TVA\",\n    \"US-MIDW-AECI->US-MIDW-MISO\": \"&facets[fromba][]=AECI&facets[toba][]=MISO\",\n    \"US-MIDW-AECI->US-TEN-TVA\": \"&facets[fromba][]=AECI&facets[toba][]=TVA\",\n    # \"US-MIDW-GLHB->US-MIDW-LGEE\": \"&facets[fromba][]=GLHB&facets[toba][]=LGEE\", US-MIDW-GLHB decommissioned no more powerplant\n    # \"US-MIDW-GLHB->US-MIDW-MISO\": \"&facets[fromba][]=GLHB&facets[toba][]=MISO\", US-MIDW-GLHB decommissioned no more powerplant\n    # \"US-MIDW-GLHB->US-TEN-TVA\": \"&facets[fromba][]=EEI&facets[toba][]=TVA\", US-MIDW-GLHB decommissioned no more powerplant\n    \"US-MIDW-LGEE->US-MIDW-MISO\": \"&facets[fromba][]=LGEE&facets[toba][]=MISO\",\n    \"US-MIDW-LGEE->US-TEN-TVA\": \"&facets[fromba][]=LGEE&facets[toba][]=TVA\",\n    \"US-MIDW-MISO->US-SE-AEC\": \"&facets[fromba][]=MISO&facets[toba][]=AEC\",  # US-SE-AEC decommissioned, merged with US-SE-SOCO, exchange transfered\n    \"US-MIDW-MISO->US-SE-SOCO\": \"&facets[fromba][]=MISO&facets[toba][]=SOCO\",\n    \"US-MIDW-MISO->US-TEN-TVA\": \"&facets[fromba][]=MISO&facets[toba][]=TVA\",\n    \"US-NE-ISNE->US-NY-NYIS\": \"&facets[fromba][]=ISNE&facets[toba][]=NYIS\",\n    \"US-NW-AVA->US-NW-BPAT\": \"&facets[fromba][]=AVA&facets[toba][]=BPAT\",\n    \"US-NW-AVA->US-NW-IPCO\": \"&facets[fromba][]=AVA&facets[toba][]=IPCO\",\n    \"US-NW-AVA->US-NW-NWMT\": \"&facets[fromba][]=AVA&facets[toba][]=NWMT\",\n    \"US-NW-AVA->US-NW-PACW\": \"&facets[fromba][]=AVA&facets[toba][]=PACW\",\n    \"US-NW-AVA->US-NW-CHPD\": \"&facets[fromba][]=AVA&facets[toba][]=CHPD\",\n    \"US-NW-AVA->US-NW-GCPD\": \"&facets[fromba][]=AVA&facets[toba][]=GCPD\",\n    \"US-NW-BPAT->US-NW-TPWR\": \"&facets[fromba][]=BPAT&facets[toba][]=TPWR\",\n    \"US-NW-BPAT->US-NW-GRID\": \"&facets[fromba][]=BPAT&facets[toba][]=GRID\",\n    \"US-NW-BPAT->US-NW-IPCO\": \"&facets[fromba][]=BPAT&facets[toba][]=IPCO\",\n    \"US-NW-BPAT->US-NW-NEVP\": \"&facets[fromba][]=BPAT&facets[toba][]=NEVP\",\n    \"US-NW-BPAT->US-NW-NWMT\": \"&facets[fromba][]=BPAT&facets[toba][]=NWMT\",\n    \"US-NW-BPAT->US-NW-DOPD\": \"&facets[fromba][]=BPAT&facets[toba][]=DOPD\",\n    \"US-NW-BPAT->US-NW-PACW\": \"&facets[fromba][]=BPAT&facets[toba][]=PACW\",\n    \"US-NW-BPAT->US-NW-PGE\": \"&facets[fromba][]=BPAT&facets[toba][]=PGE\",\n    \"US-NW-BPAT->US-NW-CHPD\": \"&facets[fromba][]=BPAT&facets[toba][]=CHPD\",\n    \"US-NW-BPAT->US-NW-GCPD\": \"&facets[fromba][]=BPAT&facets[toba][]=GCPD\",\n    \"US-NW-BPAT->US-NW-PSEI\": \"&facets[fromba][]=BPAT&facets[toba][]=PSEI\",\n    \"US-NW-BPAT->US-NW-SCL\": \"&facets[fromba][]=BPAT&facets[toba][]=SCL\",\n    \"US-NW-CHPD->US-NW-DOPD\": \"&facets[fromba][]=CHPD&facets[toba][]=DOPD\",\n    \"US-NW-CHPD->US-NW-PSEI\": \"&facets[fromba][]=CHPD&facets[toba][]=PSEI\",\n    \"US-NW-GCPD->US-NW-PACW\": \"&facets[fromba][]=GCPD&facets[toba][]=PACW\",\n    \"US-NW-GCPD->US-NW-PSEI\": \"&facets[fromba][]=GCPD&facets[toba][]=PSEI\",\n    #    \"US-NW-GWA->US-NW-NWMT\": \"&facets[fromba][]=GWA&facets[toba][]=NWMT\", integrated directly with US-NW-NWMT\n    \"US-NW-IPCO->US-NW-NEVP\": \"&facets[fromba][]=IPCO&facets[toba][]=NEVP\",\n    \"US-NW-IPCO->US-NW-NWMT\": \"&facets[fromba][]=IPCO&facets[toba][]=NWMT\",\n    \"US-NW-IPCO->US-NW-PACE\": \"&facets[fromba][]=IPCO&facets[toba][]=PACE\",\n    \"US-NW-IPCO->US-NW-PACW\": \"&facets[fromba][]=IPCO&facets[toba][]=PACW\",\n    \"US-NW-NEVP->US-NW-PACE\": \"&facets[fromba][]=NEVP&facets[toba][]=PACE\",\n    \"US-NW-NEVP->US-SW-WALC\": \"&facets[fromba][]=NEVP&facets[toba][]=WALC\",\n    #    \"US-NW-NWMT->US-NW-WWA\": \"&facets[fromba][]=NWMT&facets[toba][]=WWA\", intergrated directly with US-NW-NWMT\n    \"US-NW-NWMT->US-NW-PACE\": \"&facets[fromba][]=NWMT&facets[toba][]=PACE\",\n    \"US-NW-NWMT->US-NW-WAUW\": \"&facets[fromba][]=NWMT&facets[toba][]=WAUW\",\n    \"US-NW-PACE->US-SW-AZPS\": \"&facets[fromba][]=PACE&facets[toba][]=AZPS\",\n    \"US-NW-PACE->US-NW-PACW\": \"&facets[fromba][]=PACE&facets[toba][]=PACW\",\n    \"US-NW-PACE->US-NW-WACM\": \"&facets[fromba][]=PACE&facets[toba][]=WACM\",\n    \"US-NW-PACW->US-NW-PGE\": \"&facets[fromba][]=PACW&facets[toba][]=PGE\",\n    \"US-NW-PSCO->US-SW-PNM\": \"&facets[fromba][]=PSCO&facets[toba][]=PNM\",\n    \"US-NW-PSCO->US-NW-WACM\": \"&facets[fromba][]=PSCO&facets[toba][]=WACM\",\n    \"US-NW-PSEI->US-NW-TPWR\": \"&facets[fromba][]=PSEI&facets[toba][]=TPWR\",\n    \"US-NW-PSEI->US-NW-SCL\": \"&facets[fromba][]=PSEI&facets[toba][]=SCL\",\n    \"US-NW-WACM->US-SW-AZPS\": \"&facets[fromba][]=WACM&facets[toba][]=AZPS\",\n    \"US-NW-WACM->US-SW-PNM\": \"&facets[fromba][]=WACM&facets[toba][]=PNM\",\n    \"US-NW-WACM->US-SW-WALC\": \"&facets[fromba][]=WACM&facets[toba][]=WALC\",\n    \"US-NW-WACM->US-NW-WAUW\": \"&facets[fromba][]=WACM&facets[toba][]=WAUW\",\n    # \"US-SE-AEC->US-SE-SOCO\": \"&facets[fromba][]=AEC&facets[toba][]=SOCO\", Decommisioned BA\n    \"US-SE-SEPA->US-SE-SOCO\": \"&facets[fromba][]=SEPA&facets[toba][]=SOCO\",\n    \"US-SE-SOCO->US-TEN-TVA\": \"&facets[fromba][]=SOCO&facets[toba][]=TVA\",\n    # \"US-SW-AZPS->US-SW-GRMA\": \"&facets[fromba][]=AZPS&facets[toba][]=GRMA\", , directly integrated in US-SW-AZPS\n    \"US-SW-AZPS->US-SW-PNM\": \"&facets[fromba][]=AZPS&facets[toba][]=PNM\",\n    \"US-SW-AZPS->US-SW-SRP\": \"&facets[fromba][]=AZPS&facets[toba][]=SRP\",\n    \"US-SW-AZPS->US-SW-TEPC\": \"&facets[fromba][]=AZPS&facets[toba][]=TEPC\",\n    \"US-SW-AZPS->US-SW-WALC\": \"&facets[fromba][]=AZPS&facets[toba][]=WALC\",\n    \"US-SW-EPE->US-SW-PNM\": \"&facets[fromba][]=EPE&facets[toba][]=PNM\",\n    \"US-SW-EPE->US-SW-TEPC\": \"&facets[fromba][]=EPE&facets[toba][]=TEPC\",\n    #    \"US-SW-GRIF->US-SW-WALC\": \"&facets[fromba][]=GRIF&facets[toba][]=WALC\", directly integrated in US-WALC\n    #    \"US-SW-HGMA->US-SW-SRP\": \"&facets[fromba][]=HGMA&facets[toba][]=SRP\", directly integrated in US-SW-SRP\n    \"US-SW-PNM->US-SW-TEPC\": \"&facets[fromba][]=PNM&facets[toba][]=TEPC\",\n    \"US-SW-PNM->US-SW-SRP\": \"&facets[fromba][]=SRP&facets[toba][]=PNM\",\n    \"US-SW-SRP->US-SW-TEPC\": \"&facets[fromba][]=SRP&facets[toba][]=TEPC\",\n    \"US-SW-SRP->US-SW-WALC\": \"&facets[fromba][]=SRP&facets[toba][]=WALC\",\n    \"US-SW-TEPC->US-SW-WALC\": \"&facets[fromba][]=TEPC&facets[toba][]=WALC\",\n}\n# Some zones transfer all or part of their productions to another zone.\n# To avoid having multiple small production zones with no consumption,\n# their production is directly integrated into supplied zones according\n# to the supplied percentage.\n\nSC_VIRGIL_OWNERSHIP = 0.3333333\n\nPRODUCTION_ZONES_TRANSFERS = {\n    # key receives production from the dict of keys\n    \"US-SW-SRP\": {\"all\": {\"US-SW-DEAA\": 1.0, \"US-SW-HGMA\": 1.0}},\n    \"US-NW-NWMT\": {\"all\": {\"US-NW-GWA\": 1.0, \"US-NW-WWA\": 1.0}},\n    \"US-SW-WALC\": {\"all\": {\"US-SW-GRIF\": 1.0}},\n    \"US-NW-PACW\": {\"gas\": {\"US-NW-AVRN\": 1.0}},\n    \"US-NW-BPAT\": {\n        \"wind\": {\"US-NW-AVRN\": 1.0},\n    },\n    \"US-CAR-SC\": {\"nuclear\": {\"US-CAR-SCEG\": SC_VIRGIL_OWNERSHIP}},\n    \"US-SE-SOCO\": {\"all\": {\"US-SE-AEC\": 1.0}},\n    \"US-FLA-FPL\": {\"all\": {\"US-FLA-NSB\": 1.0}},\n    \"US-SW-AZPS\": {\"gas\": {\"US-SW-GRMA\": 1.0}},\n}\n\nEXCHANGE_TRANSFERS = {\n    # key receives the exchange from the set of keys\n    \"US-FLA-FPC->US-FLA-FPL\": {\"US-FLA-FPC->US-FLA-NSB\"},\n    \"US-MIDW-MISO->US-SE-SOCO\": {\"US-MIDW-MISO->US-SE-AEC\"},\n}\n\n# Available modes\n# biomass: float | None = None\n# coal: float | None = None\n# gas: float | None = None\n# geothermal: float | None = None\n# hydro: float | None = None\n# nuclear: float | None = None\n# oil: float | None = None\n# solar: float | None = None\n# unknown: float | None = None\n# wind: float | None = None\n# battery_storage: float | None = None\n# hydro_storage: float | None = None\nTYPES = {\n    \"biomass\": \"BM\",\n    \"coal\": \"COL\",\n    \"gas\": \"NG\",\n    \"geothermal\": \"GEO\",\n    \"hydro\": \"WAT\",\n    \"nuclear\": \"NUC\",\n    \"oil\": \"OIL\",\n    \"solar\": \"SUN\",\n    \"unknown\": \"OTH\",\n    \"wind\": \"WND\",\n    \"battery_storage\": \"BAT\",\n    \"hydro_storage\": \"PS\",\n}\n\nBASE_URL = \"https://api.eia.gov/v2/electricity/rto\"\n\nPRODUCTION = (\n    f\"{BASE_URL}/region-data/data/\"\n    \"?data[]=value&facets[respondent][]={}&facets[type][]=NG&frequency=hourly\"\n)\nCONSUMPTION = (\n    f\"{BASE_URL}/region-data/data/\"\n    \"?data[]=value&facets[respondent][]={}&facets[type][]=D&frequency=hourly\"\n)\nCONSUMPTION_FORECAST = (\n    f\"{BASE_URL}/region-data/data/\"\n    \"?data[]=value&facets[respondent][]={}&facets[type][]=DF&frequency=hourly\"\n)\nPRODUCTION_MIX = (\n    f\"{BASE_URL}/fuel-type-data/data/\"\n    \"?data[]=value&facets[respondent][]={}&facets[fueltype][]={}&frequency=hourly\"\n)\nEXCHANGE = f\"{BASE_URL}/interchange-data/data/?data[]=value{{}}&frequency=hourly\"\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    return _fetch_historical(\n        zone_key,\n        PRODUCTION.format(REGIONS[zone_key]),\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n    )\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    consumption_list = TotalConsumptionList(logger)\n    consumption = _fetch_historical(\n        zone_key,\n        CONSUMPTION.format(REGIONS[zone_key]),\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n    )\n    for point in consumption:\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=point[\"datetime\"],\n            consumption=point[\"value\"],\n            source=\"eia.gov\",\n        )\n\n    return consumption_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    consumptions = TotalConsumptionList(logger)\n    consumption_forecasts = _fetch_forecast(\n        zone_key,\n        CONSUMPTION_FORECAST.format(REGIONS[zone_key]),\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n    )\n    for forecast in consumption_forecasts:\n        consumptions.append(\n            zoneKey=zone_key,\n            datetime=forecast[\"datetime\"],\n            consumption=forecast[\"value\"],\n            source=\"eia.gov\",\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumptions.to_list()\n\n\ndef create_production_storage(\n    fuel_type: str, production_point: dict[str, float | None], negative_threshold: float\n) -> tuple[ProductionMix | None, StorageMix | None]:\n    \"\"\"Create a production mix or a storage mix from a production point\n    handling the special cases of hydro storage and self consumption\"\"\"\n    production_value = production_point[\"value\"]\n    production_mix = ProductionMix()\n    storage_mix = StorageMix()\n    if production_value is not None and production_value < 0 and fuel_type == \"hydro\":\n        # Negative hydro is reported by some BAs, according to the EIA those are pumped storage.\n        # https://www.eia.gov/electricity/gridmonitor/about\n        storage_mix.add_value(\"hydro\", abs(production_value))\n        return None, storage_mix\n    # production_value > negative_threshold, this is considered to be self consumption and should be reported as 0.\n    # Lower values are set to None as they are most likely outliers.\n\n    # have to have early returns because of downstream validation in ProductionBreakdownList\n    if fuel_type == \"hydro_storage\":\n        storage_mix.add_value(\n            \"hydro\",\n            -production_value if production_value is not None else production_value,\n        )\n        return None, storage_mix\n    elif fuel_type == \"battery_storage\":\n        storage_mix.add_value(\n            \"battery\",\n            -production_value if production_value is not None else production_value,\n        )\n        return None, storage_mix\n    else:\n        production_mix.add_value(\n            fuel_type,\n            production_value,\n            production_value > negative_threshold if bool(production_value) else False,\n        )\n        return production_mix, None\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production_mix(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    all_production_breakdowns: list[ProductionBreakdownList] = []\n    # TODO: We could be smarter in the future and only fetch the expected production types.\n    for production_mode, code in TYPES.items():\n        negative_threshold = NEGATIVE_PRODUCTION_THRESHOLDS_TYPE.get(\n            production_mode, NEGATIVE_PRODUCTION_THRESHOLDS_TYPE[\"default\"]\n        )\n        production_breakdown = ProductionBreakdownList(logger)\n        url_prefix = PRODUCTION_MIX.format(REGIONS[zone_key], code)\n        production_and_storage_values = _fetch_historical(\n            zone_key,\n            url_prefix,\n            session=session,\n            target_datetime=target_datetime,\n            logger=logger,\n        )\n        # EIA does not currently split production from the Virgil Summer C\n        # plant across the two owning/ utilizing BAs:\n        # US-CAR-SCEG and US-CAR-SC,\n        # but attributes it all to US-CAR-SCEG\n        # Here we apply a temporary fix for that until EIA properly splits the production\n        # This split can be found in the eGRID data,\n        # https://www.epa.gov/energy/emissions-generation-resource-integrated-database-egrid\n\n        if zone_key == \"US-CAR-SCEG\" and production_mode == \"nuclear\":\n            for point in production_and_storage_values:\n                point.update({\"value\": point[\"value\"] * (1 - SC_VIRGIL_OWNERSHIP)})\n\n        # hardcoded exception for US-SW-AZPS nuclear production : Palo Verde nuclear plant is doucle counted in US-SW-AZPS and US-SW-SRP.\n        # Even though the plant is operated by US-SW-AZPS, the reporting is consistently done by US-SW-SRP on the time period below but also after.\n        # So keep US-SW-SRP nuclear production and set US-SW-AZPS nuclear production to 0.0.\n        if zone_key == \"US-SW-AZPS\" and production_mode == \"nuclear\":\n            first_appearance = datetime(\n                year=2018, month=7, day=1, hour=7, tzinfo=timezone.utc\n            )\n            last_apperance = datetime(\n                year=2019, month=12, day=4, hour=6, tzinfo=timezone.utc\n            )\n            for event in production_and_storage_values:\n                if (\n                    event[\"datetime\"] >= first_appearance\n                    and event[\"datetime\"] <= last_apperance\n                ):\n                    event[\"value\"] = 0.0\n\n        # hardcoded exception\n        # parser is double counting \"geothermal\" and \"unknown\"\n        # we set unknown to 0.0 and keep geothermal as is\n        # see GMM-555 for details\n        if zone_key == \"US-CAL-IID\" and production_mode == \"unknown\":\n            first_appearance = datetime(\n                year=2025, month=1, day=1, hour=8, tzinfo=timezone.utc\n            )\n            last_apperance = datetime(\n                year=2025, month=2, day=12, hour=7, tzinfo=timezone.utc\n            )\n            for event in production_and_storage_values:\n                if (\n                    event[\"datetime\"] >= first_appearance\n                    and event[\"datetime\"] <= last_apperance\n                ):\n                    event[\"value\"] = 0.0\n\n        for point in production_and_storage_values:\n            production_mix, storage_mix = create_production_storage(\n                production_mode, point, negative_threshold\n            )\n            production_breakdown.append(\n                zoneKey=zone_key,\n                datetime=point[\"datetime\"],\n                production=production_mix,\n                storage=storage_mix,\n                source=\"eia.gov\",\n            )\n        all_production_breakdowns.append(production_breakdown)\n        # Integrate the supplier zones in the zones they supply\n\n        supplying_zones = PRODUCTION_ZONES_TRANSFERS.get(zone_key, {})\n        zones_to_integrate = {\n            **supplying_zones.get(\"all\", {}),\n            **supplying_zones.get(production_mode, {}),\n        }\n        for zone, percentage in zones_to_integrate.items():\n            url_prefix = PRODUCTION_MIX.format(REGIONS[zone], code)\n            additional_breakdown = ProductionBreakdownList(logger)\n            additional_production = _fetch_historical(\n                ZoneKey(zone),\n                url_prefix,\n                session=session,\n                target_datetime=target_datetime,\n                logger=logger,\n            )\n            for point in additional_production:\n                point.update({\"value\": point[\"value\"] * percentage})\n                production_mix, storage_mix = create_production_storage(\n                    production_mode, point, negative_threshold\n                )\n                additional_breakdown.append(\n                    zoneKey=zone_key,\n                    datetime=point[\"datetime\"],\n                    production=production_mix,\n                    storage=storage_mix,\n                    source=\"eia.gov\",\n                )\n            all_production_breakdowns.append(additional_breakdown)\n\n    all_production_breakdowns = list(\n        filter(lambda x: len(x.events) > 0, all_production_breakdowns)\n    )\n\n    if len(all_production_breakdowns) == 0:\n        logger.warning(f\"No production mix data found for {zone_key}\")\n        return ProductionBreakdownList(logger).to_list()\n    # Some of the returned mixes could be for older timeframes.\n    # Fx the latest oil data could be 6 months old.\n    # In this case we want to discard the old data as we won't be able to merge it\n    timeframes = [\n        sorted(x.datetime for x in breakdowns.events)\n        for breakdowns in all_production_breakdowns\n        if len(breakdowns.events) > 0\n    ]\n    latest_timeframe = max(timeframes, key=lambda x: x[-1])\n\n    for production_list in all_production_breakdowns:\n        correct_mix = []\n        for production_mix in production_list.events:\n            if production_mix.datetime in latest_timeframe:\n                correct_mix.append(production_mix)\n        production_list.events = correct_mix\n    events = ProductionBreakdownList.merge_production_breakdowns(\n        all_production_breakdowns, logger\n    )\n\n    return events.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    sortedcodes = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    exchange_list = ExchangeList(logger)\n    exchange = _fetch_historical(\n        sortedcodes,\n        url_prefix=EXCHANGE.format(EXCHANGES[sortedcodes]),\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n    )\n    for point in exchange:\n        exchange_list.append(\n            zoneKey=ZoneKey(point[\"zoneKey\"]),\n            datetime=point[\"datetime\"],\n            netFlow=-point[\"value\"]\n            if sortedcodes in REVERSE_EXCHANGES\n            else point[\"value\"],\n            source=\"eia.gov\",\n        )\n\n    # Integrate remapped exchanges\n    remapped_exchanges = EXCHANGE_TRANSFERS.get(sortedcodes, {})\n    remapped_exchange_list = ExchangeList(logger)\n    for remapped_exchange in remapped_exchanges:\n        exchange = _fetch_historical(\n            ZoneKey(remapped_exchange),\n            url_prefix=EXCHANGE.format(EXCHANGES[remapped_exchange]),\n            session=session,\n            target_datetime=target_datetime,\n            logger=logger,\n        )\n        for point in exchange:\n            remapped_exchange_list.append(\n                zoneKey=sortedcodes,\n                datetime=point[\"datetime\"],\n                netFlow=-point[\"value\"]\n                if remapped_exchange in REVERSE_EXCHANGES\n                else point[\"value\"],\n                source=\"eia.gov\",\n            )\n\n    exchange_list = ExchangeList.merge_exchanges(\n        [exchange_list, remapped_exchange_list], logger\n    )\n\n    return exchange_list.to_list()\n\n\ndef _fetch_any(\n    zone_key: ZoneKey,\n    url_prefix: str,\n    start_datetime: datetime,\n    end_datetime: datetime,\n    session: Session | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    # get EIA API key\n    API_KEY = get_token(\"EIA_KEY\")\n\n    eia_ts_format = \"%Y-%m-%dT%H\"\n    url = f\"{url_prefix}&api_key={API_KEY}&start={start_datetime.strftime(eia_ts_format)}&end={end_datetime.strftime(eia_ts_format)}\"\n\n    s = session or Session()\n    req = s.get(url)\n    raw_data = req.json()\n    if raw_data.get(\"response\", {}).get(\"data\", None) is None:\n        return []\n    return [\n        {\n            \"zoneKey\": zone_key,\n            \"datetime\": _parse_hourly_interval(datapoint[\"period\"]),\n            \"value\": float(datapoint[\"value\"]) if datapoint[\"value\"] else None,\n            \"source\": \"eia.gov\",\n        }\n        for datapoint in raw_data[\"response\"][\"data\"]\n    ]\n\n\ndef _fetch_historical(\n    zone_key: ZoneKey,\n    url_prefix: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    start, end = None, None\n    if target_datetime:\n        end = target_datetime.astimezone(timezone.utc) + timedelta(hours=1)\n        start = end - timedelta(days=1)\n    else:\n        end = datetime.now(timezone.utc).replace(\n            minute=0, second=0, microsecond=0\n        ) + timedelta(hours=1)\n        start = end - timedelta(hours=72)\n\n    return _fetch_any(zone_key, url_prefix, start, end, session, logger)\n\n\ndef _fetch_forecast(\n    zone_key: ZoneKey,\n    url_prefix: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    LOOKAHEAD = timedelta(days=15)\n\n    start, end = None, None\n    if target_datetime:\n        start = target_datetime.astimezone(timezone.utc).replace(\n            minute=0, second=0, microsecond=0\n        )\n        end = start + LOOKAHEAD\n    else:\n        start = datetime.now(timezone.utc).replace(minute=0, second=0, microsecond=0)\n        end = start + LOOKAHEAD\n\n    return _fetch_any(zone_key, url_prefix, start, end, session, logger)\n\n\ndef _parse_hourly_interval(period: str):\n    interval_end_naive = parser.parse(period)\n\n    # NB: the EIA API can respond with time intervals relative to either UTC\n    # or local-time.  We request UTC times using the 'frequency=hourly'\n    # parameter, meaning that we can attach timezone.utc without performing\n    # any timezone conversion.\n    interval_end = interval_end_naive.replace(tzinfo=timezone.utc)\n\n    # The timestamp given by EIA represents the end of the time interval.\n    # ElectricityMap using another convention,\n    # where the timestamp represents the beginning of the interval.\n    # So we need shift the datetime 1 hour back.\n    return interval_end - timedelta(hours=1)\n\n\nif __name__ == \"__main__\":\n    from pprint import pprint\n\n    # pprint(fetch_production_mix(\"US-NW-NEVP\"))\n    # pprint(fetch_consumption_forecast('US-CAL-CISO'))\n    pprint(\n        fetch_exchange(\n            zone_key1=ZoneKey(\"US-CENT-SWPP\"),\n            zone_key2=ZoneKey(\"CA-SK\"),\n            target_datetime=datetime(2022, 3, 1),\n        )\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ELEXON.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"\nParser that uses the ELEXON API to return the following data types.\n\nProduction\nExchanges\n\nDocumentation:\nhttps://bscdocs.elexon.co.uk/guidance-notes/bmrs-api-and-data-push-user-guide\n\"\"\"\n\nimport re\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nELEXON_API_ENDPOINT = \"https://data.elexon.co.uk/bmrs/api/v1\"\nELEXON_URLS = {\n    \"production_fuelhh\": \"/\".join((ELEXON_API_ENDPOINT, \"datasets/FUELINST/stream\")),\n    \"exchange\": \"/\".join((ELEXON_API_ENDPOINT, \"generation/outturn/interconnectors\")),\n    \"balancing\": \"/\".join((ELEXON_API_ENDPOINT, \"balancing/physical\")),\n    \"actual_load\": \"/\".join(\n        (ELEXON_API_ENDPOINT, \"datasets/ATL/stream\")\n    ),  # B0610 - Actual Total Load https://bmrs.elexon.co.uk/api-documentation/endpoint/datasets/ATL\n}\nELEXON_START_DATE = datetime(\n    2019, 1, 1, tzinfo=timezone.utc\n)  # ELEXON API only has data from 2019-01-01\nELEXON_SOURCE = \"elexon.co.uk\"\nESO_NATIONAL_GRID_ENDPOINT = \"https://api.neso.energy/api/3/action/datastore_search_sql\"\nESO_SOURCE = \"nationalgrideso.com\"\n\n# A specific report to query most recent data (within 1 month time span + forecast ahead)\nESO_DEMAND_DATA_UPDATE_ID = \"177f6fa4-ae49-4182-81ea-0c6b35f26ca6\"\n\n# 'hydro' key is for hydro production\n# 'hydro storage' key is for hydro storage\nRESOURCE_TYPE_TO_FUEL = {\n    \"Biomass\": \"biomass\",\n    \"Fossil Gas\": \"gas\",\n    \"Fossil Hard coal\": \"coal\",\n    \"Fossil Oil\": \"oil\",\n    \"Hydro Pumped Storage\": \"hydro storage\",\n    \"Hydro Run-of-river and poundage\": \"hydro\",\n    \"Nuclear\": \"nuclear\",\n    \"Solar\": \"solar\",\n    \"Wind Onshore\": \"wind\",\n    \"Wind Offshore\": \"wind\",\n    \"Other\": \"unknown\",\n}\n# Mapping is ordered to match the FUELINST output file as there's no header.\nFUEL_INST_MAPPING = {\n    \"CCGT\": \"gas\",\n    \"OIL\": \"oil\",\n    \"COAL\": \"coal\",\n    \"NUCLEAR\": \"nuclear\",\n    \"WIND\": \"wind\",\n    \"PS\": \"solar\",\n    \"NPSHYD\": \"hydro\",\n    \"OCGT\": \"gas\",\n    \"OTHER\": \"unknown\",\n    \"INTFR\": \"exchange\",  # IFA (France)\n    \"INTIRL\": \"exchange\",  # Northen Ireland\n    \"INTGRNL\": \"exchange\",  # Greenlink (Ireland)\n    \"INTNED\": \"exchange\",  # BritNed (Netherlands)\n    \"INTEW\": \"exchange\",  # East West (Ireland)\n    \"BIOMASS\": \"biomass\",\n    \"INTNEM\": \"exchange\",  # Nemolink (Belgium)\n    \"INTELEC\": \"exchange\",  # Eleclink (France)\n    \"INTIFA2\": \"exchange\",  # IFA2 (France)\n    \"INTNSL\": \"exchange\",  # North Sea Link (Norway)\n    \"INTVKL\": \"exchange\",  # Viking Link (Denmark)\n}\n\nESO_FUEL_MAPPING = {\n    \"EMBEDDED_WIND_GENERATION\": \"wind\",\n    \"EMBEDDED_SOLAR_GENERATION\": \"solar\",\n    \"PUMP_STORAGE_PUMPING\": \"hydro storage\",\n}\n\nZONEKEY_TO_INTERCONNECTOR = {\n    \"BE->GB\": [\"Belgium (Nemolink)\"],\n    \"DK-DK1->GB\": [\"Denmark (Viking link)\"],\n    \"FR->GB\": [\"Eleclink (INTELEC)\", \"France(IFA)\", \"IFA2 (INTIFA2)\"],\n    \"GB->GB-NIR\": [\"Northern Ireland(Moyle)\"],\n    \"GB->IE\": [\"Ireland(East-West)\", \"Ireland (Greenlink)\"],\n    \"GB->NL\": [\"Netherlands(BritNed)\"],\n    \"GB->NO-NO2\": [\"North Sea Link (INTNSL)\"],\n}\n\n# Change direction of exchange for connectors where data is from Elexon and zonekey \"GB->*\". Due to Elexon showing wrt UK\nEXHANGE_KEY_IS_IMPORT = {\n    \"BE->GB\": False,\n    \"DK-DK1->GB\": False,\n    \"FR->GB\": False,\n    \"GB->GB-NIR\": False,\n    \"GB->IE\": True,\n    \"GB->NL\": True,\n    \"GB->NO-NO2\": False,\n}\n\n\ndef zulu_to_utc(datetime_str: str) -> str:\n    return datetime_str.replace(\"Z\", \"+00:00\")\n\n\ndef query_elexon(url: str, session: Session, params: dict) -> list | dict:\n    r: Response = session.get(url, params=params)\n    if not r.ok:\n        raise ParserException(\n            parser=\"ELEXON\",\n            message=f\"Error fetching data: {r.status_code} {r.reason}\",\n        )\n    return r.json()\n\n\ndef parse_datetime(\n    settlementDate: str | None, settlementPeriod: int | None\n) -> datetime:\n    if settlementDate is None or settlementPeriod is None:\n        raise ParserException(\n            parser=\"ELEXON\",\n            message=\"Error fetching data: settlementDate or settlementPeriod is None\",\n        )\n    parsed_datetime = datetime.strptime(settlementDate, \"%Y-%m-%d\")\n    parsed_datetime += timedelta(hours=(settlementPeriod - 1) / 2)\n    return parsed_datetime.replace(tzinfo=timezone.utc)\n\n\ndef query_IM_exchange(\n    session: Session, target_datetime: datetime, logger: Logger\n) -> ExchangeList:\n    \"\"\"\n    Fetches balancing mechanism data from the ELEXON API.\n    This is used to get the imbalance quantity for the GB->IM interconnector.\n    \"\"\"\n    bm_unit = \"MANXENR-1\"\n    balancing_params = {\n        \"bmUnit\": bm_unit,\n        \"dataset\": \"PN\",  # Physical data\n        \"from\": (target_datetime - timedelta(days=2)).strftime(\"%Y-%m-%d\"),\n        \"to\": (target_datetime + timedelta(days=1)).strftime(\"%Y-%m-%d\"),\n    }\n    balancing_data = query_elexon(ELEXON_URLS[\"balancing\"], session, balancing_params)\n\n    exchange_list = ExchangeList(logger)\n    if isinstance(balancing_data, dict):\n        for event in balancing_data.get(\"data\", []):\n            event_datetime = datetime.fromisoformat(\n                event[\"timeFrom\"].replace(\"Z\", \"+00:00\")\n            )\n            exchange_list.append(\n                zoneKey=ZoneKey(\"GB->IM\"),\n                netFlow=event.get(\"levelFrom\") * -1,\n                source=ELEXON_SOURCE,\n                datetime=event_datetime,\n            )\n    return exchange_list\n\n\ndef get_event_value(event: dict[str, Any], key: str) -> float | None:\n    value = event.get(key)\n    if value is not None:\n        return float(value)\n\n\ndef parse_production(\n    production_data: list[dict[str, Any]], logger: Logger, dataset: str\n) -> ProductionBreakdownList:\n    \"\"\"Parses production events from the ELEXON API. This function is used for the B1620 data or the FUELHH data.\"\"\"\n    dataset_info = {\n        \"B1620\": {\n            \"mode_mapping\": RESOURCE_TYPE_TO_FUEL,\n            \"mode_key\": \"psrType\",\n            \"quantity_key\": \"quantity\",\n        },\n        \"FUELHH\": {\n            \"mode_mapping\": FUEL_INST_MAPPING,\n            \"mode_key\": \"fuelType\",\n            \"quantity_key\": \"generation\",\n        },\n    }\n\n    mode_mapping = dataset_info[dataset][\"mode_mapping\"]\n    mode_key = dataset_info[dataset][\"mode_key\"]\n    quantity_key = dataset_info[dataset][\"quantity_key\"]\n\n    all_production_breakdowns: list[ProductionBreakdownList] = []\n\n    for event in production_data:\n        production_breakdown = ProductionBreakdownList(logger=logger)\n        event_datetime_str = event.get(\"startTime\")\n        production_mix = ProductionMix()\n        storage_mix = StorageMix()\n\n        production_mode = mode_mapping[event.get(mode_key)]\n\n        if production_mode == \"exchange\":\n            continue\n\n        if production_mode == \"hydro storage\":\n            storage_value = get_event_value(event, quantity_key)\n            if storage_value is not None:\n                storage_mix.add_value(\"hydro\", -1 * storage_value)\n\n        else:\n            production_value = get_event_value(event, quantity_key)\n            production_mix.add_value(\n                production_mode, production_value, correct_negative_with_zero=True\n            )\n        if event_datetime_str:\n            event_datetime = datetime.fromisoformat(zulu_to_utc(event_datetime_str))\n            production_breakdown.append(\n                zoneKey=ZoneKey(\"GB\"),\n                production=production_mix,\n                storage=storage_mix,\n                source=ELEXON_SOURCE,\n                datetime=event_datetime,\n            )\n\n        all_production_breakdowns.append(production_breakdown)\n    events = ProductionBreakdownList.merge_production_breakdowns(\n        all_production_breakdowns, logger\n    )\n    return events\n\n\ndef _create_eso_historical_demand_index(session: Session) -> dict[int, str]:\n    \"\"\"Get the ids of all historical_demand_data reports\"\"\"\n    index = {}\n    response = session.get(\n        \"https://data.nationalgrideso.com/demand/historic-demand-data/datapackage.json\"\n    )\n    data = response.json()\n    pattern = re.compile(r\"historic_demand_data_(?P<year>\\d+)\")\n    for resource in data.get(\"result\").get(\"resources\"):\n        match = pattern.match(resource[\"name\"])\n        if match is not None:\n            index[int(match[\"year\"])] = resource[\"id\"]\n    return index\n\n\ndef query_additional_eso_data(\n    target_datetime: datetime, session: Session\n) -> list[dict[str, Any]]:\n    \"\"\"Fetches embedded wind and solar and hydro storage data from the ESO API.\"\"\"\n    begin = (target_datetime - timedelta(days=2)).strftime(\"%Y-%m-%d\")\n    end = (target_datetime).strftime(\"%Y-%m-%d\")\n    if target_datetime > (datetime.now(tz=timezone.utc) - timedelta(days=30)):\n        report_id = ESO_DEMAND_DATA_UPDATE_ID\n    else:\n        index = _create_eso_historical_demand_index(session)\n        report_id = index[target_datetime.year]\n    params = {\n        \"sql\": f'''SELECT * FROM \"{report_id}\" WHERE \"SETTLEMENT_DATE\" BETWEEN '{begin}' AND '{end}' ORDER BY \"SETTLEMENT_DATE\"'''\n    }\n    response = session.get(ESO_NATIONAL_GRID_ENDPOINT, params=params)\n    eso_data = response.json()[\"result\"][\"records\"]\n    return eso_data\n\n\ndef parse_eso_production(\n    production_data: list[dict[str, Any]], logger: Logger\n) -> ProductionBreakdownList:\n    all_production_breakdowns: list[ProductionBreakdownList] = []\n    for event in production_data:\n        production_breakdown = ProductionBreakdownList(logger=logger)\n        event_datetime = parse_datetime(\n            event.get(\"SETTLEMENT_DATE\"), event.get(\"SETTLEMENT_PERIOD\")\n        )\n        production_mix = ProductionMix()\n        storage_mix = StorageMix()\n        for production_mode in ESO_FUEL_MAPPING:\n            if ESO_FUEL_MAPPING[production_mode] == \"hydro storage\":\n                storage_value = get_event_value(event, production_mode)\n                if storage_value:\n                    storage_mix.add_value(\"hydro\", event.get(production_mode))\n            else:\n                production_value = get_event_value(event, production_mode)\n                if production_value:\n                    production_mix.add_value(\n                        ESO_FUEL_MAPPING[production_mode],\n                        event.get(production_mode),\n                        correct_negative_with_zero=True,\n                    )\n        production_breakdown.append(\n            zoneKey=ZoneKey(\"GB\"),\n            production=production_mix,\n            storage=storage_mix,\n            source=ESO_SOURCE,\n            datetime=event_datetime,\n        )\n\n        all_production_breakdowns.append(production_breakdown)\n    events = ProductionBreakdownList.merge_production_breakdowns(\n        all_production_breakdowns, logger\n    )\n    return events\n\n\ndef parse_eso_hydro_storage(\n    eso_data: list[dict[str, Any]], logger: Logger\n) -> ProductionBreakdownList:\n    \"\"\"Parses only hydro storage data from the ESO API. This data will be merged with the B1620 data\"\"\"\n    storage_breakdown = ProductionBreakdownList(logger=logger)\n    for event in eso_data:\n        event_datetime = parse_datetime(\n            event.get(\"SETTLEMENT_DATE\"), event.get(\"SETTLEMENT_PERIOD\")\n        )\n        storage_mix = StorageMix()\n        storage_value = get_event_value(event, \"PUMP_STORAGE_PUMPING\")\n        storage_mix.add_value(\"hydro\", storage_value)\n        storage_breakdown.append(\n            zoneKey=ZoneKey(\"GB\"),\n            storage=storage_mix,\n            source=ESO_SOURCE,\n            datetime=event_datetime,\n        )\n    return storage_breakdown\n\n\ndef query_production_fuelhh(\n    session: Session, target_datetime: datetime, logger: Logger\n) -> list[dict[str, Any]]:\n    \"\"\"Fetches production data from the FUELHH endpoint.\n    This endpoint provides the half-hourly generation outturn (Generation By Fuel type)\n    to give our users an indication of the generation outturn for Great Britain.\n    The data is aggregated by Fuel Type category and updated at 30-minute intervals\n    with average MW values over 30 minutes for each category.\"\"\"\n    params = {\n        \"settlementDateFrom\": (target_datetime - timedelta(days=1)).strftime(\n            \"%Y-%m-%d\"\n        ),\n        \"settlementDateTo\": target_datetime.strftime(\"%Y-%m-%d\"),\n        \"format\": \"json\",\n    }\n\n    fuelhh_data = query_elexon(ELEXON_URLS[\"production_fuelhh\"], session, params)\n\n    return fuelhh_data if isinstance(fuelhh_data, list) else []\n\n\ndef query_and_merge_production_fuelhh_and_eso(\n    session: Session, target_datetime: datetime, logger: Logger\n) -> ProductionBreakdownList:\n    events_fuelhh = query_production_fuelhh(session, target_datetime, logger)\n    parsed_events_fuelhh = parse_production(events_fuelhh, logger, \"FUELHH\")\n    events_eso = query_additional_eso_data(target_datetime, session)\n    parsed_events_eso = parse_eso_production(events_eso, logger)\n\n    merged_events = ProductionBreakdownList.merge_production_breakdowns(\n        [parsed_events_fuelhh, parsed_events_eso], logger, matching_timestamps_only=True\n    )\n    return merged_events\n\n\n# TODO: Why are we using this other endpoint instead of FUELINST that also have this data?\ndef query_exchange(\n    zone_key: ZoneKey, session: Session, target_datetime: datetime, logger: Logger\n) -> ExchangeList:\n    all_exchanges: list[ExchangeList] = []\n    for interconnector in ZONEKEY_TO_INTERCONNECTOR[zone_key]:\n        exchange_params = {\n            \"settlementDateFrom\": (target_datetime - timedelta(days=2)).strftime(\n                \"%Y-%m-%d\"\n            ),\n            \"settlementDateTo\": target_datetime.strftime(\"%Y-%m-%d\"),\n            \"interconnectorName\": interconnector,\n            \"format\": \"json\",\n        }\n        data = query_elexon(ELEXON_URLS[\"exchange\"], session, exchange_params)\n        exchange_data = data.get(\"data\", []) if isinstance(data, dict) else []\n\n        if EXHANGE_KEY_IS_IMPORT.get(zone_key):\n            for event in exchange_data:\n                event[\"generation\"] = -1 * event[\"generation\"]\n\n        if not exchange_data:\n            raise ParserException(\n                parser=\"ELEXON.py\",\n                message=f\"No exchange data found for {target_datetime.date()}\",\n            )\n        for event in exchange_data:\n            exchange_list = ExchangeList(logger)\n            event_datetime_str = event.get(\"startTime\")\n            if event_datetime_str:\n                event_datetime = datetime.fromisoformat(zulu_to_utc(event_datetime_str))\n                exchange_list.append(\n                    zoneKey=zone_key,\n                    netFlow=event.get(\"generation\"),\n                    source=ELEXON_SOURCE,\n                    datetime=event_datetime,\n                )\n            all_exchanges.append(exchange_list)\n    return ExchangeList.merge_exchanges(all_exchanges, logger)\n\n\ndef query_actual_demand(\n    session: Session, target_datetime: datetime, logger: Logger\n) -> list[dict[str, Any]]:\n    \"\"\"Fetches actual electrical demand data from the ATL (Actual Total Load) endpoint.\"\"\"\n    params = {\n        \"publishDateTimeFrom\": (target_datetime - timedelta(days=1)).strftime(\n            \"%Y-%m-%dT%H:%M:%SZ\"\n        ),\n        \"publishDateTimeTo\": target_datetime.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n        \"format\": \"json\",\n    }\n\n    demand_data = query_elexon(ELEXON_URLS[\"actual_load\"], session, params)\n    return demand_data if isinstance(demand_data, list) else []\n\n\ndef parse_demand_data(\n    demand_data: list[dict[str, Any]], logger: Logger\n) -> TotalConsumptionList:\n    \"\"\"Parses demand data from the ELEXON API.\"\"\"\n    consumption_list = TotalConsumptionList(logger=logger)\n\n    for event in demand_data:\n        event_datetime_str = event.get(\"startTime\")\n        consumption_value = get_event_value(\n            event, \"quantity\"\n        )  # or whatever the demand field is called\n\n        if event_datetime_str and consumption_value is not None:\n            event_datetime = datetime.fromisoformat(zulu_to_utc(event_datetime_str))\n            consumption_list.append(\n                zoneKey=ZoneKey(\"GB\"),\n                consumption=consumption_value,\n                source=ELEXON_SOURCE,\n                datetime=event_datetime,\n            )\n    return consumption_list\n\n\n@refetch_frequency(timedelta(hours=1))\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"GB\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    session = session or Session()\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=timezone.utc)\n    else:\n        target_datetime = target_datetime.astimezone(timezone.utc)\n\n    if target_datetime < ELEXON_START_DATE:\n        raise ParserException(\n            parser=\"ELEXON.py\",\n            message=f\"Demand data is not available before {ELEXON_START_DATE.date()}\",\n        )\n    demand_data = query_actual_demand(session, target_datetime, logger)\n    parsed_demand = parse_demand_data(demand_data, logger)\n    if not parsed_demand:\n        raise ParserException(\n            parser=\"ELEXON.py\",\n            message=f\"No demand data found for {target_datetime.date()}\",\n        )\n    return parsed_demand.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    session = session or Session()\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=timezone.utc)\n\n    if target_datetime.tzinfo is None:\n        target_datetime = target_datetime.replace(tzinfo=timezone.utc)\n\n    exchangeKey = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    if target_datetime < ELEXON_START_DATE:\n        raise ParserException(\n            parser=\"ELEXON.py\",\n            message=f\"Production data is not available before {ELEXON_START_DATE.date()}\",\n        )\n    exchange_data = (\n        query_exchange(exchangeKey, session, target_datetime, logger)\n        if exchangeKey != \"GB->IM\"\n        else query_IM_exchange(session, target_datetime, logger)\n    )\n\n    return exchange_data.to_list()\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"GB\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    session = session or Session()\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=timezone.utc)\n    else:\n        target_datetime = target_datetime.astimezone(timezone.utc)\n\n    if target_datetime < ELEXON_START_DATE:\n        raise ParserException(\n            parser=\"ELEXON.py\",\n            message=f\"Production data is not available before {ELEXON_START_DATE.date()}\",\n        )\n\n    data = query_and_merge_production_fuelhh_and_eso(session, target_datetime, logger)\n    eso_data = query_additional_eso_data(target_datetime, session)\n    parsed_hydro_storage_data = parse_eso_hydro_storage(eso_data, logger)\n\n    return ProductionBreakdownList.merge_production_breakdowns(\n        [data, parsed_hydro_storage_data],\n        logger,\n        matching_timestamps_only=True,\n    ).to_list()\n\n\ndef validate_bmrs_data(data: ProductionBreakdownList):\n    \"\"\"Check if the PowerProductionBreakdown event contains a full power breakdown or just wind and solar or if data is missing.\"\"\"\n    if not data:\n        return False\n    available_production_modes = []\n    for event in data.to_list():\n        available_production_modes += [*event[\"production\"].keys()]\n    return \"gas\" in set(available_production_modes)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ENERCAL.py",
    "content": "import json\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.types import ZoneKey\n\nfrom .lib.exceptions import ParserException\n\nTZ = ZoneInfo(\"Pacific/Noumea\")\n\nSOURCE = \"enercal.nc\"\n\nINDEX_TO_TYPE_MAP = {0: \"solar\", 1: \"hydro\", 2: \"wind\", 3: \"coal\", 4: \"oil\"}\n\n\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n\n    if target_datetime and target_datetime.tzinfo is None:\n        target_datetime = target_datetime.replace(tzinfo=TZ)\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TZ)\n\n    # No data since 2024-06-30, but the API is still working\n    data = session.get(\n        \"https://www.enercal.nc/wp-content/themes/enercal/ajax-e-co2.php\",\n        params={\"date_day\": target_datetime.strftime(\"%Y-%m-%d\")},\n    ).json()\n\n    production = ProductionBreakdownList(logger)\n\n    # Reformat data to native values\n    mix = [json.loads(m) for m in data[\"mix\"]]\n    time = json.loads(data[\"time\"][0])\n    prettyTime = json.loads(data[\"prettyTime\"][0])\n\n    if not time:\n        raise ParserException(\n            \"ENERCAL.py\",\n            f\"This parser cannot retrieve data for: {target_datetime}\",\n            ZoneKey(\"NC\"),\n        )\n\n    # Reformat the data to add key value pairs instead of using index values.\n    production_data = []\n    for i in range(len(time)):\n        production_entry = {}\n        for index, type_name in INDEX_TO_TYPE_MAP.items():\n            production_entry[type_name] = mix[index][i]\n        production_data.append(production_entry)\n\n    # Use zip to ensure the same length of the data and make it easier to loop over\n    zipped_data = zip(production_data, time, prettyTime, strict=True)\n\n    for production_entry, time, prettyTime in zipped_data:\n        production_mix = ProductionMix()\n        for production_mode, production_value in production_entry.items():\n            production_mix.add_value(production_mode, production_value)\n        date_time = datetime.strptime(f\"{time}:{prettyTime}\", \"%Y-%m-%d:%H\").replace(\n            tzinfo=TZ\n        )\n        production.append(\n            zoneKey=ZoneKey(\"NC\"),\n            datetime=date_time,\n            production=production_mix,\n            source=SOURCE,\n        )\n\n    return production.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ENTE.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\n\n# This parser gets all real time interconnection flows from the\n# Central American Electrical Interconnection System (SIEPAC).\n\n# map for reference\n# https://www.enteoperador.org/flujos-regionales-en-tiempo-real/\n\nDATA_URL = \"https://mapa.enteoperador.org/WebServiceScadaEORRest/webresources/generic\"\n\nTIMEZONE = ZoneInfo(\"America/Tegucigalpa\")\n\nJSON_MAPPING = {\n    \"GT->MX\": \"2LBR.LT400.1FR2-2LBR-01A.-.MW\",\n    \"GT->MX-OR\": \"2LBR.LT400.1FR2-2LBR-01A.-.MW\",\n    \"GT->SV\": \"3SISTEMA.LT230.INTER_NET_GT.CMW.MW\",\n    \"GT->HN\": \"4LEC.LT230.2FR4-4LEC-01B.-.MW\",\n    \"HN->SV\": \"3SISTEMA.LT230.INTER_NET_HO.CMW.MW\",\n    \"HN->NI\": \"5SISTEMA.LT230.INTER_NET_HN.CMW.MW\",\n    \"CR->NI\": \"5SISTEMA.LT230.INTER_NET_CR.CMW.MW\",\n    \"CR->PA\": \"6SISTEMA.LT230.INTER_NET_PAN.CMW.MW\",\n}\n\n\ndef floor_to_minute(dt: datetime) -> datetime:\n    return dt.replace(second=0, microsecond=0)\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"HN\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    r = session or Session()\n    response = r.get(DATA_URL).json()\n\n    # Total production data for HN from the ENTE-data is the 57th element in the JSON ('4SISTEMA.GTOT.OSYMGENTOTR.-.MW')\n    production = round(response[56][\"value\"], 1)\n\n    dt = floor_to_minute(datetime.now(tz=TIMEZONE))\n\n    production_list = ProductionBreakdownList(logger)\n    production_list.append(\n        zoneKey=zone_key,\n        datetime=dt,\n        production=ProductionMix(unknown=production),\n        source=\"enteoperador.org\",\n    )\n\n    return production_list.to_list()\n\n\ndef extract_exchange(raw_data, exchange) -> float | None:\n    \"\"\"Extracts flow value and direction for a given exchange.\"\"\"\n    search_value = JSON_MAPPING[exchange]\n\n    interconnection = None\n    for datapoint in raw_data:\n        if datapoint[\"nombre\"] == search_value:\n            interconnection = float(datapoint[\"value\"])\n\n    if interconnection is None:\n        return None\n\n    # positive and negative flow directions do not always correspond to EM ordering of exchanges\n    if exchange in [\"GT->SV\", \"GT->HN\", \"HN->SV\", \"CR->NI\", \"HN->NI\"]:\n        interconnection *= -1\n\n    return interconnection\n\n\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Gets an exchange pair from the SIEPAC system.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    sorted_zones = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    if sorted_zones not in JSON_MAPPING:\n        raise NotImplementedError(\"This exchange is not implemented.\")\n\n    s = session or Session()\n\n    raw_data = s.get(DATA_URL).json()\n    flow = round(extract_exchange(raw_data, sorted_zones), 1)\n    dt = floor_to_minute(datetime.now(tz=TIMEZONE))\n\n    exchanges = ExchangeList(logger)\n    exchanges.append(\n        zoneKey=ZoneKey(sorted_zones),\n        datetime=dt,\n        netFlow=flow,\n        source=\"enteoperador.org\",\n    )\n\n    return exchanges.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(\"fetch_production(HN) ->\")\n    print(fetch_production())\n    print(\"fetch_exchange(CR, PA) ->\")\n    print(fetch_exchange(\"CR\", \"PA\"))\n    print(\"fetch_exchange(CR, NI) ->\")\n    print(fetch_exchange(\"CR\", \"NI\"))\n    print(\"fetch_exchange(HN, NI) ->\")\n    print(fetch_exchange(\"HN\", \"NI\"))\n    print(\"fetch_exchange(GT, MX) ->\")\n    print(fetch_exchange(\"GT\", \"MX\"))\n    print(\"fetch_exchange(GT, SV) ->\")\n    print(fetch_exchange(\"GT\", \"SV\"))\n    print(\"fetch_exchange(GT, HN) ->\")\n    print(fetch_exchange(\"GT\", \"HN\"))\n    print(\"fetch_exchange(HN, SV) ->\")\n    print(fetch_exchange(\"HN\", \"SV\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ENTSOE.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"\nParser that uses the ENTSOE API to return the following data types.\n\nConsumption\nProduction\nExchanges\nExchange Forecast\nDay-ahead Price\nGeneration Forecast\nConsumption Forecast\n\nLink to the API documentation:\nhttps://documenter.getpostman.com/view/7009892/2s93JtP3F6\n\"\"\"\n\nfrom collections.abc import Generator, Iterable\nfrom dataclasses import dataclass\nfrom datetime import datetime, timedelta, timezone\nfrom enum import Enum\nfrom functools import cache, lru_cache\nfrom itertools import chain, groupby, pairwise\nfrom logging import Logger, getLogger\nfrom operator import attrgetter, itemgetter\nfrom re import fullmatch\nfrom typing import Any, Literal, NamedTuple\n\nfrom bs4 import BeautifulSoup, SoupStrainer\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeCapacityList,\n    ExchangeList,\n    PriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n    TotalProductionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import (\n    ProductionModes,\n    StorageModes,\n    refetch_frequency,\n)\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.parsers.lib.utils import get_token\n\nSOURCE = \"entsoe.eu\"\n\nENTSOE_URL = \"https://entsoe-proxy-jfnx5klx2a-ew.a.run.app\"\n\nDEFAULT_LOOKBACK_HOURS_REALTIME = timedelta(hours=72)\nDEFAULT_TARGET_HOURS_REALTIME = (-DEFAULT_LOOKBACK_HOURS_REALTIME, timedelta(hours=0))\nDEFAULT_TARGET_HOURS_FORECAST = (-timedelta(hours=24), timedelta(hours=48))\nEXCHANGE_CAPACITY_TARGET_DAYS_FORECAST_DAY_AHEAD = (\n    -timedelta(days=2),\n    timedelta(days=7),\n)\nEXCHANGE_CAPACITY_TARGET_DAYS_FORECAST_WEEK_AND_MONTH_AHEAD = (\n    -timedelta(days=7),\n    timedelta(days=30),\n)\n\n# SoupStrainer instances for efficient XML parsing\n# Only parse the elements we care about in each context\nSTRAINER_TIMESERIES = SoupStrainer(\"timeseries\")\nSTRAINER_TEXT = SoupStrainer(\"text\")\n\n\n# TODO: Switch this to a string enum when we migrate to Python 3.11\nclass EntsoeTypeEnum(str, Enum):\n    DAY_AHEAD = \"A01\"\n    WEEK_AHEAD = \"A02\"\n    MONTH_AHEAD = \"A03\"\n    YEAR_AHEAD = \"A04\"\n    INTRADAY_PRICE = \"A07\"\n    TOTAL = \"A05\"\n    INTRADAY = \"A40\"\n    CURRENT = \"A18\"\n\n    def __str__(self) -> str:\n        return self.value\n\n\nclass EntsoeDocumentTypeEnum(str, Enum):\n    ESTIMATED_NET_TRANSFER_CAPACITY = \"A61\"\n\n\nENTSOE_PARAMETER_DESC = {\n    \"B01\": \"Biomass\",\n    \"B02\": \"Fossil Brown coal/Lignite\",\n    \"B03\": \"Fossil Coal-derived gas\",\n    \"B04\": \"Fossil Gas\",\n    \"B05\": \"Fossil Hard coal\",\n    \"B06\": \"Fossil Oil\",\n    \"B07\": \"Fossil Oil shale\",\n    \"B08\": \"Fossil Peat\",\n    \"B09\": \"Geothermal\",\n    \"B10\": \"Hydro Pumped Storage\",\n    \"B11\": \"Hydro Run-of-river and poundage\",\n    \"B12\": \"Hydro Water Reservoir\",\n    \"B13\": \"Marine\",\n    \"B14\": \"Nuclear\",\n    \"B15\": \"Other renewable\",\n    \"B16\": \"Solar\",\n    \"B17\": \"Waste\",\n    \"B18\": \"Wind Offshore\",\n    \"B19\": \"Wind Onshore\",\n    \"B20\": \"Other\",\n    \"B25\": \"Energy Storage\",\n}\nENTSOE_PARAMETER_BY_DESC = {v: k for k, v in ENTSOE_PARAMETER_DESC.items()}\nENTSOE_PARAMETER_GROUPS = {\n    \"production\": {\n        ProductionModes.BIOMASS: [\"B01\", \"B17\"],\n        ProductionModes.COAL: [\"B02\", \"B05\", \"B07\", \"B08\"],\n        ProductionModes.GAS: [\"B03\", \"B04\"],\n        ProductionModes.GEOTHERMAL: [\"B09\"],\n        ProductionModes.HYDRO: [\"B11\", \"B12\"],\n        ProductionModes.NUCLEAR: [\"B14\"],\n        ProductionModes.OIL: [\"B06\"],\n        ProductionModes.SOLAR: [\"B16\"],\n        ProductionModes.WIND: [\"B18\", \"B19\"],\n        ProductionModes.UNKNOWN: [\"B20\", \"B13\", \"B15\"],\n    },\n    \"storage\": {StorageModes.HYDRO: [\"B10\"], StorageModes.BATTERY: [\"B25\"]},\n}\n# ENTSOE production type codes mapped to their Electricity Maps production type.\nENTSOE_PARAMETER_BY_GROUP = {\n    ENTSOE_key: data_type\n    for key in [\"production\", \"storage\"]\n    for data_type, groups in ENTSOE_PARAMETER_GROUPS[key].items()\n    for ENTSOE_key in groups\n}\n\n# Get all the individual storage parameters in one list\nENTSOE_STORAGE_PARAMETERS = list(\n    chain.from_iterable(ENTSOE_PARAMETER_GROUPS[\"storage\"].values())\n)\n# Define all ENTSOE zone_key <-> domain mapping\n# see https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html\nENTSOE_DOMAIN_MAPPINGS: dict[str, str] = {\n    \"AL\": \"10YAL-KESH-----5\",\n    \"AM\": \"10Y1001A1001B004\",\n    \"AT\": \"10YAT-APG------L\",\n    \"AZ\": \"10Y1001A1001B05V\",\n    \"BA\": \"10YBA-JPCC-----D\",\n    \"BE\": \"10YBE----------2\",\n    \"BG\": \"10YCA-BULGARIA-R\",\n    \"BY\": \"10Y1001A1001A51S\",\n    \"CH\": \"10YCH-SWISSGRIDZ\",\n    \"CY\": \"10YCY-1001A0003J\",\n    \"CZ\": \"10YCZ-CEPS-----N\",\n    \"DE\": \"10Y1001A1001A83F\",\n    \"DE-LU\": \"10Y1001A1001A82H\",\n    \"DK\": \"10Y1001A1001A65H\",\n    \"DK-DK1\": \"10YDK-1--------W\",\n    \"DK-DK2\": \"10YDK-2--------M\",\n    \"EE\": \"10Y1001A1001A39I\",\n    \"ES\": \"10YES-REE------0\",\n    \"FI\": \"10YFI-1--------U\",\n    \"FR\": \"10YFR-RTE------C\",\n    \"GB\": \"10YGB----------A\",\n    \"GB-NIR\": \"10Y1001A1001A016\",\n    \"GE\": \"10Y1001A1001B012\",\n    \"GR\": \"10YGR-HTSO-----Y\",\n    \"HR\": \"10YHR-HEP------M\",\n    \"HU\": \"10YHU-MAVIR----U\",\n    \"IE\": \"10YIE-1001A00010\",\n    \"IE(SEM)\": \"10Y1001A1001A59C\",\n    \"IT\": \"10YIT-GRTN-----B\",\n    \"IT-BR\": \"10Y1001A1001A699\",\n    \"IT-CA\": \"10Y1001C--00096J\",\n    \"IT-CNO\": \"10Y1001A1001A70O\",\n    \"IT-CSO\": \"10Y1001A1001A71M\",\n    \"IT-FO\": \"10Y1001A1001A72K\",\n    \"IT-NO\": \"10Y1001A1001A73I\",\n    \"IT-PR\": \"10Y1001A1001A76C\",\n    \"IT-SACOAC\": \"10Y1001A1001A885\",\n    \"IT-SACODC\": \"10Y1001A1001A893\",\n    \"IT-SAR\": \"10Y1001A1001A74G\",\n    \"IT-SIC\": \"10Y1001A1001A75E\",\n    \"IT-SO\": \"10Y1001A1001A788\",\n    \"LT\": \"10YLT-1001A0008Q\",\n    \"LU\": \"10YLU-CEGEDEL-NQ\",\n    \"LV\": \"10YLV-1001A00074\",\n    \"MD\": \"10Y1001A1001A990\",\n    \"ME\": \"10YCS-CG-TSO---S\",\n    \"MK\": \"10YMK-MEPSO----8\",\n    \"MT\": \"10Y1001A1001A93C\",\n    \"NL\": \"10YNL----------L\",\n    \"NO\": \"10YNO-0--------C\",\n    \"NO-NO1\": \"10YNO-1--------2\",\n    \"NO-NO2\": \"10YNO-2--------T\",\n    \"NO-NO3\": \"10YNO-3--------J\",\n    \"NO-NO4\": \"10YNO-4--------9\",\n    \"NO-NO5\": \"10Y1001A1001A48H\",\n    \"PL\": \"10YPL-AREA-----S\",\n    \"PT\": \"10YPT-REN------W\",\n    \"RO\": \"10YRO-TEL------P\",\n    \"RS\": \"10YCS-SERBIATSOV\",\n    \"RU\": \"10Y1001A1001A49F\",\n    \"RU-KGD\": \"10Y1001A1001A50U\",\n    \"SE\": \"10YSE-1--------K\",\n    \"SE-SE1\": \"10Y1001A1001A44P\",\n    \"SE-SE2\": \"10Y1001A1001A45N\",\n    \"SE-SE3\": \"10Y1001A1001A46L\",\n    \"SE-SE4\": \"10Y1001A1001A47J\",\n    \"SI\": \"10YSI-ELES-----O\",\n    \"SK\": \"10YSK-SEPS-----K\",\n    \"TR\": \"10YTR-TEIAS----W\",\n    \"UA\": \"10YUA-WEPS-----0\",\n    \"UA-IPS\": \"10Y1001C--000182\",\n    \"XK\": \"10Y1001C--00100H\",\n}\n\n# Define zone_keys to an array of zone_keys for aggregated production data\nZONE_KEY_AGGREGATES: dict[str, list[str]] = {\n    \"IT-SO\": [\"IT-CA\", \"IT-SO\"],\n}\n\n# Some exchanges require specific domains\nENTSOE_EXCHANGE_DOMAIN_OVERRIDE: dict[str, list[str]] = {\n    \"AT->IT-NO\": [ENTSOE_DOMAIN_MAPPINGS[\"AT\"], ENTSOE_DOMAIN_MAPPINGS[\"IT\"]],\n    \"BY->UA\": [ENTSOE_DOMAIN_MAPPINGS[\"BY\"], ENTSOE_DOMAIN_MAPPINGS[\"UA-IPS\"]],\n    \"CH->DE\": [ENTSOE_DOMAIN_MAPPINGS[\"CH\"], ENTSOE_DOMAIN_MAPPINGS[\"DE-LU\"]],\n    \"DE->DK-DK1\": [ENTSOE_DOMAIN_MAPPINGS[\"DE-LU\"], ENTSOE_DOMAIN_MAPPINGS[\"DK-DK1\"]],\n    \"DE->DK-DK2\": [ENTSOE_DOMAIN_MAPPINGS[\"DE-LU\"], ENTSOE_DOMAIN_MAPPINGS[\"DK-DK2\"]],\n    \"DE->NO-NO2\": [ENTSOE_DOMAIN_MAPPINGS[\"DE-LU\"], ENTSOE_DOMAIN_MAPPINGS[\"NO-NO2\"]],\n    \"DE->SE-SE4\": [ENTSOE_DOMAIN_MAPPINGS[\"DE\"], ENTSOE_DOMAIN_MAPPINGS[\"SE\"]],\n    \"DE->NL\": [ENTSOE_DOMAIN_MAPPINGS[\"DE-LU\"], ENTSOE_DOMAIN_MAPPINGS[\"NL\"]],\n    \"EE->RU-1\": [ENTSOE_DOMAIN_MAPPINGS[\"EE\"], ENTSOE_DOMAIN_MAPPINGS[\"RU\"]],\n    \"FI->RU-1\": [ENTSOE_DOMAIN_MAPPINGS[\"FI\"], ENTSOE_DOMAIN_MAPPINGS[\"RU\"]],\n    \"FR-COR->IT-CNO\": [\n        ENTSOE_DOMAIN_MAPPINGS[\"IT-SACODC\"],\n        ENTSOE_DOMAIN_MAPPINGS[\"IT-CNO\"],\n    ],\n    \"GE->RU-1\": [ENTSOE_DOMAIN_MAPPINGS[\"GE\"], ENTSOE_DOMAIN_MAPPINGS[\"RU\"]],\n    \"GR->IT-SO\": [ENTSOE_DOMAIN_MAPPINGS[\"GR\"], ENTSOE_DOMAIN_MAPPINGS[\"IT-SO\"]],\n    \"HU->UA\": [ENTSOE_DOMAIN_MAPPINGS[\"HU\"], ENTSOE_DOMAIN_MAPPINGS[\"UA-IPS\"]],\n    \"IT-CSO->ME\": [ENTSOE_DOMAIN_MAPPINGS[\"IT\"], ENTSOE_DOMAIN_MAPPINGS[\"ME\"]],\n    \"IT-SIC->IT-SO\": [\n        ENTSOE_DOMAIN_MAPPINGS[\"IT-SIC\"],\n        ENTSOE_DOMAIN_MAPPINGS[\"IT-CA\"],\n    ],\n    \"LV->RU-1\": [ENTSOE_DOMAIN_MAPPINGS[\"LV\"], ENTSOE_DOMAIN_MAPPINGS[\"RU\"]],\n    \"MD->UA\": [ENTSOE_DOMAIN_MAPPINGS[\"MD\"], ENTSOE_DOMAIN_MAPPINGS[\"UA-IPS\"]],\n    \"PL->UA\": [ENTSOE_DOMAIN_MAPPINGS[\"PL\"], ENTSOE_DOMAIN_MAPPINGS[\"UA-IPS\"]],\n    \"RO->UA\": [ENTSOE_DOMAIN_MAPPINGS[\"RO\"], ENTSOE_DOMAIN_MAPPINGS[\"UA-IPS\"]],\n    \"RU-1->UA\": [ENTSOE_DOMAIN_MAPPINGS[\"RU\"], ENTSOE_DOMAIN_MAPPINGS[\"UA-IPS\"]],\n    \"SK->UA\": [ENTSOE_DOMAIN_MAPPINGS[\"SK\"], ENTSOE_DOMAIN_MAPPINGS[\"UA-IPS\"]],\n}\n\nEXCHANGE_AGGREGATES: dict[str, list[list]] = {\n    \"FR-COR->IT-SAR\": [\n        [ENTSOE_DOMAIN_MAPPINGS[\"IT-SACOAC\"], ENTSOE_DOMAIN_MAPPINGS[\"IT-SAR\"]],\n        [ENTSOE_DOMAIN_MAPPINGS[\"IT-SACODC\"], ENTSOE_DOMAIN_MAPPINGS[\"IT-SAR\"]],\n    ],\n}\n\n# Some zone_keys are part of bidding zone domains for price data\nENTSOE_PRICE_DOMAIN_MAPPINGS: dict[str, str] = {\n    **ENTSOE_DOMAIN_MAPPINGS,  # Note: This has to be first so the domains are overwritten.\n    \"AX\": ENTSOE_DOMAIN_MAPPINGS[\"SE-SE3\"],\n    \"DE\": ENTSOE_DOMAIN_MAPPINGS[\"DE-LU\"],\n    \"IE\": ENTSOE_DOMAIN_MAPPINGS[\"IE(SEM)\"],\n    \"GB-NIR\": ENTSOE_DOMAIN_MAPPINGS[\"IE(SEM)\"],\n    \"LU\": ENTSOE_DOMAIN_MAPPINGS[\"DE-LU\"],\n    \"UA\": ENTSOE_DOMAIN_MAPPINGS[\"UA-IPS\"],\n}\n\n\ndef query_ENTSOE(\n    session: Session,\n    params: dict[str, str],\n    span: tuple[timedelta, timedelta],\n    target_datetime: datetime | None = None,\n) -> str:\n    \"\"\"\n    Makes a standard query to the ENTSOE API with a modifiable set of parameters.\n    Allows an existing session to be passed.\n    Raises an exception if no API token is found.\n    Returns a request object.\n    \"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(timezone.utc)\n\n    if not isinstance(target_datetime, datetime):\n        raise ParserException(\n            parser=\"ENTSOE.py\",\n            message=\"target_datetime has to be a datetime in query_entsoe\",\n        )\n\n    params[\"periodStart\"] = (target_datetime + span[0]).strftime(\n        \"%Y%m%d%H00\"  # YYYYMMDDHH00\n    )\n    params[\"periodEnd\"] = (target_datetime + span[1]).strftime(\n        \"%Y%m%d%H00\"  # YYYYMMDDHH00\n    )\n\n    token = get_token(\"ENTSOE_TOKEN\")\n    params[\"securityToken\"] = token\n    response: Response = session.get(ENTSOE_URL, params=params)\n    if response.ok:\n        return response.text\n\n    # If we get here, the request failed to fetch valid data\n    # and we will check the response for an error message\n    exception_message = None\n    soup = BeautifulSoup(response.text, \"html.parser\", parse_only=STRAINER_TEXT)\n    text = soup.find_all(\"text\")\n    if len(text):\n        error_text = soup.find_all(\"text\")[0].prettify()\n        if \"No matching data found\" in error_text:\n            exception_message = \"No matching data found\"\n        else:\n            exception_message = f\"Status code: [{response.status_code}]. ENTSOE error: {error_text.strip()}. URL: {response.request.url}\"\n    if exception_message is None:\n        exception_message = f\"Status code: [{response.status_code}]. Reason: {response.reason}. URL: {response.request.url}\"\n\n    raise ParserException(\n        parser=\"ENTSOE.py\",\n        message=exception_message\n        if exception_message\n        else \"An unknown error occured while querying ENTSOE.\",\n    )\n\n\ndef query_consumption(\n    domain: str, session: Session, target_datetime: datetime | None = None\n) -> str | None:\n    params = {\n        # System total load - Total load', including losses without power used\n        # for energy storage, is equal to generation deducted with exports,\n        # added with imports and deducted with power used for energy storage.\n        \"documentType\": \"A65\",\n        # Realised - The process for the treatment of realised data as opposed\n        # to forecast data\n        \"processType\": \"A16\",\n        \"outBiddingZone_Domain\": domain,\n    }\n    return query_ENTSOE(\n        session,\n        params,\n        target_datetime=target_datetime,\n        span=DEFAULT_TARGET_HOURS_REALTIME,\n    )\n\n\ndef query_production(\n    in_domain: str, session: Session, target_datetime: datetime | None = None\n) -> str | None:\n    params = {\n        # Actual generation per type - A document providing the actual\n        # generation per generation type for a period.\n        \"documentType\": \"A75\",\n        # Realised - The process for the treatment of realised data as opposed\n        # to forecast data\n        \"processType\": \"A16\",\n        \"in_Domain\": in_domain,\n    }\n    return query_ENTSOE(\n        session,\n        params,\n        target_datetime=target_datetime,\n        span=DEFAULT_TARGET_HOURS_REALTIME,\n    )\n\n\ndef query_exchange(\n    in_domain: str,\n    out_domain: str,\n    session: Session,\n    target_datetime: datetime | None = None,\n) -> str | None:\n    params = {\n        # Aggregated energy data report - A compilation of the time series of\n        # all the meter readings or their equivalent for a given period.\n        \"documentType\": \"A11\",\n        \"in_Domain\": in_domain,\n        \"out_Domain\": out_domain,\n    }\n    return query_ENTSOE(\n        session,\n        params,\n        target_datetime=target_datetime,\n        span=DEFAULT_TARGET_HOURS_REALTIME,\n    )\n\n\ndef query_exchange_forecast(\n    in_domain: str,\n    out_domain: str,\n    session: Session,\n    target_datetime: datetime | None = None,\n) -> str | None:\n    \"\"\"Gets exchange forecast for 48 hours ahead and previous 24 hours.\"\"\"\n\n    params = {\n        # Finalised schedule - A compilation of a set of schedules that have\n        # been finalized after a given cutoff.\n        \"documentType\": \"A09\",\n        \"in_Domain\": in_domain,\n        \"out_Domain\": out_domain,\n    }\n    return query_ENTSOE(\n        session,\n        params,\n        target_datetime=target_datetime,\n        span=DEFAULT_TARGET_HOURS_FORECAST,\n    )\n\n\ndef query_exchange_capacity_forecast(\n    in_domain: str,\n    out_domain: str,\n    session: Session,\n    forecast_type: EntsoeTypeEnum,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> str | None:\n    \"\"\"Queries exchange capacity forecast for a given pair of domains and forecast type.\"\"\"\n    params = {\n        \"documentType\": EntsoeDocumentTypeEnum.ESTIMATED_NET_TRANSFER_CAPACITY,\n        \"Contract_MarketAgreement.Type\": forecast_type,\n        \"in_Domain\": in_domain,\n        \"out_Domain\": out_domain,\n    }\n    try:\n        return query_ENTSOE(\n            session,\n            params,\n            target_datetime=target_datetime,\n            span=EXCHANGE_CAPACITY_TARGET_DAYS_FORECAST_DAY_AHEAD\n            if forecast_type == EntsoeTypeEnum.DAY_AHEAD\n            else EXCHANGE_CAPACITY_TARGET_DAYS_FORECAST_WEEK_AND_MONTH_AHEAD,\n        )\n    except ParserException as e:\n        logger.warning(\n            f\"ENTSOE exchange capacity {forecast_type} query failed: {e}\",\n            exc_info=True,\n        )\n        return None\n\n\ndef query_price(\n    domain: str,\n    session: Session,\n    target_datetime: datetime | None = None,\n    marketType: EntsoeTypeEnum = EntsoeTypeEnum.DAY_AHEAD,\n) -> str | None:\n    \"\"\"Gets day-ahead price for 24 hours ahead and previous 72 hours.\"\"\"\n\n    params = {\n        # Price Document - The document is used to provide market spot price\n        # information.\n        \"documentType\": \"A44\",\n        \"in_Domain\": domain,\n        \"out_Domain\": domain,\n        \"contract_MarketAgreement.type\": marketType,\n        # TODO: There are multiple series available, we should parse all of them but we need to model this properly first\n        # This only affects INTRADAY prices as far as we know\n        # classificationSequence_AttributeInstanceComponent.position: \"1\", # OR \"2\" OR \"3\"\n    }\n    return query_ENTSOE(\n        session,\n        params,\n        target_datetime=target_datetime,\n        span=(-DEFAULT_LOOKBACK_HOURS_REALTIME, timedelta(hours=24)),\n    )\n\n\ndef query_generation_forecast(\n    in_domain: str, session: Session, target_datetime: datetime | None = None\n) -> str | None:\n    \"\"\"Gets generation forecast for 48 hours ahead and previous 24 hours.\"\"\"\n\n    # Note: this does not give a breakdown of the production\n    params = {\n        # Generation forecast - A document providing the generation forecast for\n        # a period.\n        \"documentType\": \"A71\",\n        # Day ahead - The information provided concerns a day ahead schedule\n        \"processType\": \"A01\",\n        \"in_Domain\": in_domain,\n    }\n    return query_ENTSOE(\n        session,\n        params,\n        target_datetime=target_datetime,\n        span=DEFAULT_TARGET_HOURS_FORECAST,\n    )\n\n\ndef query_consumption_forecast(\n    in_domain: str, session: Session, target_datetime: datetime | None = None\n) -> str | None:\n    \"\"\"Gets consumption forecast for 48 hours ahead and previous 24 hours.\"\"\"\n\n    params = {\n        # System total load - Total load', including losses without power used\n        # for energy storage, is equal to generation deducted with exports,\n        # added with imports and deducted with power used for energy storage.\n        \"documentType\": \"A65\",\n        # Day ahead - The information provided concerns a day ahead schedule\n        \"processType\": \"A01\",\n        \"outBiddingZone_Domain\": in_domain,\n    }\n    return query_ENTSOE(\n        session,\n        params,\n        target_datetime=target_datetime,\n        span=DEFAULT_TARGET_HOURS_FORECAST,\n    )\n\n\ndef query_wind_solar_production_forecast(\n    in_domain: str,\n    session: Session,\n    process_type: EntsoeTypeEnum,\n    target_datetime: datetime | None = None,\n) -> str | None:\n    \"\"\"Gets consumption forecast for 48 hours ahead and previous 24 hours.\"\"\"\n\n    allowed_types = {\n        EntsoeTypeEnum.DAY_AHEAD,\n        EntsoeTypeEnum.INTRADAY,\n        EntsoeTypeEnum.CURRENT,\n    }\n    if process_type not in allowed_types:\n        raise ValueError(\n            f\"Invalid process type: {process_type}. Must be one of {allowed_types}.\"\n        )\n\n    params = {\n        # Wind and solar forecast - A document providing the forecast of wind\n        # and solar generation.\n        \"documentType\": \"A69\",\n        \"processType\": EntsoeTypeEnum(process_type),\n        \"in_Domain\": in_domain,\n    }\n    return query_ENTSOE(\n        session,\n        params,\n        target_datetime=target_datetime,\n        span=DEFAULT_TARGET_HOURS_FORECAST,\n    )\n\n\n# TODO: Remove this when we run on Python 3.11 or above\n@lru_cache(maxsize=8)\ndef zulu_to_utc(datetime_string: str) -> str:\n    \"\"\"Converts a zulu time string to a UTC time string.\"\"\"\n    return datetime_string.replace(\"Z\", \"+00:00\")\n\n\n@lru_cache(maxsize=1024)\ndef datetime_from_position(\n    start: datetime, position: int, resolution: timedelta\n) -> datetime:\n    \"\"\"Calculates the datetime from a given start datetime, position, and resolution.\"\"\"\n    return start + resolution * (position - 1)\n\n\ndef parse_scalar(\n    xml_text: str,\n    only_inBiddingZone_Domain: bool = False,\n    only_outBiddingZone_Domain: bool = False,\n) -> Generator[tuple[datetime, float], None, None]:\n    if not xml_text:\n        return None\n    soup = BeautifulSoup(xml_text, \"html.parser\", parse_only=STRAINER_TIMESERIES)\n    # Get all points\n    for timeseries in soup.find_all(\"timeseries\"):\n        if (\n            only_inBiddingZone_Domain\n            and not timeseries.find(\"inBiddingZone_Domain.mRID\".lower())\n        ) or (\n            only_outBiddingZone_Domain\n            and not timeseries.find(\"outBiddingZone_Domain.mRID\".lower())\n        ):\n            continue\n        yield from _get_datetime_value_from_timeseries(timeseries, \"quantity\")\n\n\ndef parse_production(\n    xml: str,\n    logger: Logger,\n    zoneKey: ZoneKey,\n    forecasted: bool = False,\n) -> ProductionBreakdownList:\n    production_breakdowns = ProductionBreakdownList(logger)\n    source_type = EventSourceType.forecasted if forecasted else EventSourceType.measured\n    if not xml:\n        return production_breakdowns\n    soup = BeautifulSoup(xml, \"html.parser\", parse_only=STRAINER_TIMESERIES)\n    list_of_raw_data = _get_raw_production_events(soup)\n\n    grouped_data = _group_production_data_by_datetime(list_of_raw_data)\n\n    expected_length = _get_expected_production_group_length(grouped_data)\n\n    # Loop over the grouped data and create production and storage mixes for each datetime.\n    for dt, values in grouped_data.items():\n        production, storage = _create_production_and_storage_mixes(\n            zoneKey, dt, values, expected_length, logger\n        )\n        # If production and storage are None, the datapoint is considered invalid and is skipped\n        # in order to not crash the parser.\n        if production is None and storage is None:\n            continue\n\n        production_breakdowns.append(\n            zoneKey=zoneKey,\n            datetime=dt,\n            source=SOURCE,\n            sourceType=source_type,\n            production=production,\n            storage=storage,\n        )\n\n    return production_breakdowns\n\n\ndef _get_raw_production_events(soup: BeautifulSoup) -> list[dict[str, Any]]:\n    \"\"\"\n    Extracts the raw production events from the soup object and returns a list of dictionaries containing the raw production events.\n    \"\"\"\n    list_of_raw_data = []\n    # Each timeserie is dedicated to a different fuel type.\n    for timeseries in soup.find_all(\"timeseries\"):\n        # The fuel code is the ENTSOE code for the fuel type.\n        fuel_code = str(timeseries.find(\"mktpsrtype\").find(\"psrtype\").contents[0])\n        points = _get_datetime_value_from_timeseries(\n            timeseries, \"quantity\", production_parsing=True\n        )\n\n        # Loop over all the points in the timeseries.\n        for dt, quantity in points:\n            # Appends the raw data to a master list so it later can be sorted and grouped by datetime.\n            list_of_raw_data.append(\n                {\"datetime\": dt, \"fuel_code\": fuel_code, \"quantity\": quantity}\n            )\n\n    return list_of_raw_data\n\n\ndef _create_production_and_storage_mixes(\n    zoneKey: ZoneKey,\n    dt: datetime,\n    values: list[dict[str, Any]],\n    expected_length: int,\n    logger: Logger,\n) -> tuple[ProductionMix, StorageMix] | tuple[None, None]:\n    \"\"\"\n    Creates a populated ProductionMix and StorageMix object from a list of production values and ensures that the expected length is met.\n    If the expected length is not met, the datapoint is discarded. And the function returns (None, None).\n    \"\"\"\n    value_length = len(values)\n    # Checks that the number of values have the expected length and skips the datapoint if not.\n    if value_length < expected_length:\n        if zoneKey == \"BE\" and value_length == expected_length - 1:\n            logger.warning(\n                f\"BE only has {value_length} production values for {dt}, but should have {expected_length}. BE doesn't report 0 values for storage so we will continue.\"\n            )\n        else:\n            logger.warning(\n                f\"Expected {expected_length} production values for {dt}, received {value_length} instead. Discarding datapoint...\"\n            )\n            return None, None\n    production = ProductionMix()\n    storage = StorageMix()\n    for production_mode in values:\n        _datetime, fuel_code, quantity = production_mode.values()\n        fuel_em_type = ENTSOE_PARAMETER_BY_GROUP[fuel_code]\n        if fuel_code in ENTSOE_STORAGE_PARAMETERS:\n            storage.add_value(fuel_em_type, -quantity)\n        else:\n            production.add_value(\n                fuel_em_type, quantity, correct_negative_with_zero=True\n            )\n\n    return production, storage\n\n\ndef _get_expected_production_group_length(\n    grouped_data: dict[datetime, list[dict[str, Any]]],\n) -> int:\n    \"\"\"\n    Returns the expected length of the grouped data. This is the maximum length of the grouped data values.\n    \"\"\"\n    expected_length = 0\n    if grouped_data:\n        expected_length = max(len(v) for v in grouped_data.values())\n    return expected_length\n\n\ndef _group_production_data_by_datetime(\n    list_of_raw_data,\n) -> dict[datetime, list[dict[str, Any]]]:\n    \"\"\"\n    Sorts and groups raw production objects in the format of `{datetime: datetime.datetime, fuel_code: str, quantity: float}` by the datetime key.\n    And returns a dictionary with the datetime as the key and a list of the grouped data as the value.\n    \"\"\"\n    # Sort the data in place by the datetime key so we can group it by datetime.\n    list_of_raw_data.sort(key=itemgetter(\"datetime\"))\n    # Group the data by the datetime key. It requires the data to be sorted by the datetime key first.\n    grouped_data = {\n        k: list(v) for k, v in groupby(list_of_raw_data, key=itemgetter(\"datetime\"))\n    }\n\n    return grouped_data\n\n\nclass IntPoint(NamedTuple):\n    \"\"\"A single point in time, referenced by position.\"\"\"\n\n    position: int\n    value: float\n\n\nclass DateTimePoint(NamedTuple):\n    \"\"\"The final processed point with an absolute datetime.\"\"\"\n\n    dt: datetime\n    value: float\n\n\n@dataclass(slots=True, kw_only=True)\nclass Period:\n    \"\"\"Represents one <Period> block from the XML.\"\"\"\n\n    datetime_start: datetime\n    datetime_end: datetime\n    resolution: timedelta\n    points: Iterable[IntPoint]\n\n\n@dataclass(slots=True, kw_only=True)\nclass TimeSeries:\n    \"\"\"The top-level object, representing the entire <TimeSeries> block.\"\"\"\n\n    curve_type: str\n    periods: Iterable[Period]\n\n\ndef _iter_points(\n    period_xml: Any,\n    target_str: str,\n    is_consumption: bool,\n) -> Generator[IntPoint, None, None]:\n    \"\"\"\n    A generator that parses and yields one <Point> object at a time\n    from a single <period> XML element.\n    \"\"\"\n    for point in period_xml.find_all(\"point\"):\n        position = int(point.find(\"position\").contents[0])\n        value = float(point.find(target_str).contents[0])\n\n        if is_consumption:\n            value *= -1\n\n        yield IntPoint(position=position, value=value)\n\n\n@cache\ndef _resolution_to_timedelta(resolution: str) -> timedelta:\n    \"\"\"\n    Converts an ENTSOE resolution string (e.g., 'PT15M', 'P1D') to a timedelta object.\n    \"\"\"\n    m = fullmatch(r\"PT(\\d+)([MH])\", resolution)\n    if m is not None:\n        digits = int(m.group(1))\n        scale = m.group(2)\n        if scale == \"M\":\n            return timedelta(minutes=digits)\n        if scale == \"H\":\n            return timedelta(hours=digits)\n    m = fullmatch(r\"P(\\d+)D\", resolution)\n    if m is not None:\n        return timedelta(days=int(m.group(1)))\n    raise NotImplementedError(f\"Could not recognise resolution {resolution}\")\n\n\ndef _iter_periods(\n    timeseries_xml: Any,\n    target_str: str,\n    is_consumption: bool,\n) -> Generator[Period, None, None]:\n    \"\"\"\n    A generator that parses and yields one <Period> object at a time.\n    The points *within* each period are also a generator.\n    \"\"\"\n    for period in timeseries_xml.find_all(\"period\"):\n        datetime_start = datetime.fromisoformat(\n            zulu_to_utc(period.find(\"start\").contents[0])\n        )\n        datetime_end = datetime.fromisoformat(\n            zulu_to_utc(period.find(\"end\").contents[0])\n        )\n        resolution = _resolution_to_timedelta(\n            str(period.find(\"resolution\").contents[0])\n        )\n\n        points_generator = _iter_points(period, target_str, is_consumption)\n\n        yield Period(\n            datetime_start=datetime_start,\n            datetime_end=datetime_end,\n            resolution=resolution,\n            points=points_generator,\n        )\n\n\ndef _get_datetime_value_from_timeseries(\n    timeseries: Any,  # BeautifulSoup object\n    target_str: str,\n    production_parsing: bool = False,\n) -> Generator[DateTimePoint, None, None]:\n    \"\"\"\n    Extracts DateTimePoints from a timeseries XML object\n    by streaming periods one at a time.\n    \"\"\"\n\n    curve_type = str(timeseries.find(\"curvetype\").contents[0])\n\n    is_consumption = False\n    if production_parsing:\n        is_consumption = not bool(timeseries.find(\"inBiddingZone_Domain.mRID\".lower()))\n\n    periods_generator = _iter_periods(timeseries, target_str, is_consumption)\n\n    ts_object = TimeSeries(\n        curve_type=curve_type,\n        periods=periods_generator,\n    )\n\n    if ts_object.curve_type == \"A01\":\n        for period in ts_object.periods:\n            for point in period.points:\n                dt = datetime_from_position(\n                    period.datetime_start, point.position, period.resolution\n                )\n                yield DateTimePoint(dt, point.value)\n    elif ts_object.curve_type == \"A03\":\n        for period in ts_object.periods:\n            yield from _reverse_A3_curve_compression_for_period(period)\n    else:\n        raise NotImplementedError(f\"Curve type {ts_object.curve_type} not implemented.\")\n\n\ndef _reverse_A3_curve_compression_for_period(\n    period: Period,\n) -> Generator[DateTimePoint, None, None]:\n    \"\"\"\n    Reverses the A3 curve compression for a *single* Period object.\n    Fills in missing points with the last known value.\n    \"\"\"\n\n    points_list = sorted(period.points, key=attrgetter(\"position\"))\n\n    if not points_list:\n        return\n\n    start_time = period.datetime_start\n    end_time = period.datetime_end\n    resolution = period.resolution\n\n    point_duration_sec = resolution.total_seconds()\n    period_duration_sec = (end_time - start_time).total_seconds()\n\n    expected_points = int(period_duration_sec / point_duration_sec)\n\n    for p1, p2 in pairwise(points_list):\n        for position in range(p1.position, p2.position):\n            dt = datetime_from_position(start_time, position, resolution)\n            yield DateTimePoint(dt, p1.value)\n\n    last_point = points_list[-1]\n    for position in range(last_point.position, expected_points + 1):\n        dt = datetime_from_position(start_time, position, resolution)\n        yield DateTimePoint(dt, last_point.value)\n\n\ndef parse_exchange(\n    xml_text: str,\n    is_import: bool,\n    sorted_zone_keys: ZoneKey,\n    logger: Logger,\n) -> ExchangeList:\n    exchange_list = ExchangeList(logger)\n    points = parse_scalar(xml_text)\n    for dt, quantity in points:\n        if is_import:\n            quantity *= -1\n        # Find out whether or not we should update the net production\n        exchange_list.append(\n            zoneKey=sorted_zone_keys,\n            datetime=dt,\n            source=SOURCE,\n            netFlow=quantity,\n        )\n\n    return exchange_list\n\n\ndef parse_exchange_forecast(\n    xml_text: str,\n    is_import: bool,\n    sorted_zone_keys: ZoneKey,\n    logger: Logger,\n    market_type: EntsoeTypeEnum,\n) -> ExchangeList:\n    exchange_list = ExchangeList(logger)\n\n    soup = BeautifulSoup(xml_text, \"html.parser\", parse_only=STRAINER_TIMESERIES)\n    # Get all points\n    for timeseries in soup.find_all(\"timeseries\"):\n        marketAgreementType = timeseries.find(\"contract_marketagreement.type\").contents[\n            0\n        ]\n        if marketAgreementType and marketAgreementType != market_type:\n            continue\n\n        points = _get_datetime_value_from_timeseries(timeseries, \"quantity\")\n\n        for dt, quantity in points:\n            if is_import:\n                quantity *= -1\n            # Find out whether or not we should update the net production\n            exchange_list.append(\n                zoneKey=sorted_zone_keys,\n                datetime=dt,\n                source=SOURCE,\n                netFlow=quantity,\n                sourceType=EventSourceType.forecasted,\n            )\n\n    return exchange_list\n\n\ndef _merge_exchange_capacity_forecasts(\n    export_list: ExchangeCapacityList,\n    import_list: ExchangeCapacityList,\n    logger: Logger,\n) -> ExchangeCapacityList:\n    \"\"\"\n    Merges export and import direction capacity forecasts into a single list.\n    For each datetime, combines capacities from both directions into one event.\n    \"\"\"\n    merged = ExchangeCapacityList(logger)\n\n    # Create a dict of export capacities by datetime\n    export_by_dt = {event.datetime: event for event in export_list.events}\n    import_by_dt = {event.datetime: event for event in import_list.events}\n\n    # Merge events by datetime\n    for dt in sorted(set(export_by_dt.keys()) | set(import_by_dt.keys())):\n        export_event = export_by_dt.get(dt)\n        import_event = import_by_dt.get(dt)\n\n        # Use values from whichever event exists (prefer export if both exist)\n        zoneKey = export_event.zoneKey if export_event else import_event.zoneKey\n        source = export_event.source if export_event else import_event.source\n\n        export_cap = export_event.capacityExport if export_event else None\n        import_cap = import_event.capacityImport if import_event else None\n\n        merged.append(\n            zoneKey=zoneKey,\n            datetime=dt,\n            source=source,\n            capacityExport=export_cap,\n            capacityImport=import_cap,\n        )\n\n    return merged\n\n\ndef parse_exchange_capacity_forecast(\n    xml_text: str,\n    sorted_zone_keys: ZoneKey,\n    logger: Logger,\n    direction: Literal[\"export\", \"import\"] = \"export\",\n) -> ExchangeCapacityList:\n    \"\"\"\n    Parses NTC (A61) exchange capacity forecast XML for a given direction.\n\n    Args:\n        xml_text: The XML response from ENTSOE\n        sorted_zone_keys: The exchange pair (sorted, format \"A->B\")\n        logger: Logger instance\n        direction: \"export\" for A→B, \"import\" for B→A\n\n    Returns:\n        ExchangeCapacityList with capacity populated for the specified direction\n    \"\"\"\n    try:\n        soup = BeautifulSoup(xml_text, \"html.parser\", parse_only=STRAINER_TIMESERIES)\n        forecasts = ExchangeCapacityList(logger)\n        for timeseries in soup.find_all(\"timeseries\"):\n            for dt, quantity in _get_datetime_value_from_timeseries(\n                timeseries, \"quantity\"\n            ):\n                if direction == \"export\":\n                    forecasts.append(\n                        zoneKey=sorted_zone_keys,\n                        datetime=dt,\n                        source=SOURCE,\n                        capacityExport=quantity,\n                        capacityImport=None,\n                    )\n                else:\n                    forecasts.append(\n                        zoneKey=sorted_zone_keys,\n                        datetime=dt,\n                        source=SOURCE,\n                        capacityExport=None,\n                        capacityImport=quantity,\n                    )\n        return forecasts\n    except Exception as e:\n        raise ParserException(\n            parser=\"ENTSOE.py\",\n            message=f\"Failed to parse exchange capacity forecast XML for {sorted_zone_keys} ({direction} direction): {e}\",\n            zone_key=sorted_zone_keys,\n        ) from e\n\n\ndef parse_prices(\n    xml_text: str,\n    zoneKey: ZoneKey,\n    logger: Logger,\n) -> PriceList:\n    if not xml_text:\n        return PriceList(logger)\n    soup = BeautifulSoup(xml_text, \"html.parser\", parse_only=STRAINER_TIMESERIES)\n    prices = PriceList(logger)\n    for timeseries in soup.find_all(\"timeseries\"):\n        currency = str(timeseries.find(\"currency_unit.name\").contents[0])\n        points = _get_datetime_value_from_timeseries(timeseries, \"price.amount\")\n        for dt, value in points:\n            prices.append(\n                zoneKey=zoneKey,\n                datetime=dt,\n                price=value,\n                source=\"entsoe.eu\",\n                currency=currency,\n            )\n\n    return prices\n\n\n@refetch_frequency(DEFAULT_LOOKBACK_HOURS_REALTIME)\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Gets values and corresponding datetimes for all production types in the specified zone.\n    Removes any values that are in the future or don't have a datetime associated with them.\n    \"\"\"\n    if not session:\n        session = Session()\n    non_aggregated_data: list[ProductionBreakdownList] = []\n    for _zone_key in ZONE_KEY_AGGREGATES.get(zone_key, [zone_key]):\n        domain = ENTSOE_DOMAIN_MAPPINGS[_zone_key]\n        try:\n            raw_production = query_production(\n                domain, session, target_datetime=target_datetime\n            )\n        except Exception as e:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"Failed to fetch production for {_zone_key}\",\n                zone_key=zone_key,\n            ) from e\n        if raw_production is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No production data found for {_zone_key}\",\n                zone_key=zone_key,\n            )\n        # Aggregated data are regrouped unde the same zone key.\n        non_aggregated_data.append(parse_production(raw_production, logger, zone_key))\n\n    return ProductionBreakdownList.merge_production_breakdowns(\n        non_aggregated_data, logger\n    ).to_list()\n\n\ndef get_raw_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n    forecast: bool = False,\n) -> ExchangeList:\n    \"\"\"\n    Gets exchange status between two specified zones.\n    Removes any datapoints that are in the future.\n    \"\"\"\n    if not session:\n        session = Session()\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    # This will be filled with a list of raw exchanges to merge\n    raw_exchange_lists: list[ExchangeList] = []\n\n    # Create lists for forecast exchanges so we can merge them later without fetching the same data twice\n    raw_exchange_lists_forecast_day_ahead: list[ExchangeList] = []\n    raw_exchange_lists_forecast_total: list[ExchangeList] = []\n\n    query_function = query_exchange_forecast if forecast else query_exchange\n\n    # This will be filled with a list of domain pairs to fetch\n    exchanges_to_fetch: list[list[str]] = []\n\n    if sorted_zone_keys in EXCHANGE_AGGREGATES:\n        for domain_pair in EXCHANGE_AGGREGATES[sorted_zone_keys]:\n            exchanges_to_fetch.append(domain_pair)\n    elif sorted_zone_keys in ENTSOE_EXCHANGE_DOMAIN_OVERRIDE:\n        exchanges_to_fetch.append(ENTSOE_EXCHANGE_DOMAIN_OVERRIDE[sorted_zone_keys])\n    else:\n        exchanges_to_fetch.append(\n            [ENTSOE_DOMAIN_MAPPINGS[zone_key1], ENTSOE_DOMAIN_MAPPINGS[zone_key2]]\n        )\n\n    def _fetch_exchange(\n        domain_pair: list[str],\n        is_import: bool,\n    ) -> str | None:\n        \"\"\"\n        Internal function to fetch and parse exchange data\n        only used to avoid code duplication in the parent function.\n        \"\"\"\n        domain1, domain2 = domain_pair if is_import else domain_pair[::-1]\n        try:\n            raw_exchange = query_function(domain1, domain2, session, target_datetime)\n        except Exception as e:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"Failed to query {'import' if is_import else 'export'} for {domain1} -> {domain2}\",\n                zone_key=sorted_zone_keys,\n            ) from e\n        if raw_exchange is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No exchange data found for {domain1} -> {domain2}\",\n                zone_key=sorted_zone_keys,\n            )\n        return raw_exchange\n\n    # Grab all exchanges\n    for domain_pair in exchanges_to_fetch:\n        # First we try to get the import data\n        raw_exchange = _fetch_exchange(domain_pair, is_import=True)\n        if raw_exchange is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No exchange data found for {domain_pair[0]} -> {domain_pair[1]}\",\n                zone_key=sorted_zone_keys,\n            )\n        if not forecast:\n            raw_exchange_lists.append(\n                parse_exchange(\n                    raw_exchange,\n                    is_import=True,\n                    sorted_zone_keys=sorted_zone_keys,\n                    logger=logger,\n                )\n            )\n        else:\n            raw_exchange_lists_forecast_day_ahead.append(\n                parse_exchange_forecast(\n                    raw_exchange,\n                    is_import=True,\n                    sorted_zone_keys=sorted_zone_keys,\n                    logger=logger,\n                    market_type=EntsoeTypeEnum.DAY_AHEAD,\n                )\n            )\n            raw_exchange_lists_forecast_total.append(\n                parse_exchange_forecast(\n                    raw_exchange,\n                    is_import=True,\n                    sorted_zone_keys=sorted_zone_keys,\n                    logger=logger,\n                    market_type=EntsoeTypeEnum.TOTAL,\n                )\n            )\n\n        # Then we try to get the export data\n        raw_exchange = _fetch_exchange(domain_pair, is_import=False)\n\n        if raw_exchange is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No exchange data found for {domain_pair[1]} -> {domain_pair[0]}\",\n                zone_key=sorted_zone_keys,\n            )\n        if not forecast:\n            raw_exchange_lists.append(\n                parse_exchange(\n                    raw_exchange,\n                    is_import=False,\n                    sorted_zone_keys=sorted_zone_keys,\n                    logger=logger,\n                )\n            )\n        else:\n            raw_exchange_lists_forecast_day_ahead.append(\n                parse_exchange_forecast(\n                    raw_exchange,\n                    is_import=False,\n                    sorted_zone_keys=sorted_zone_keys,\n                    logger=logger,\n                    market_type=EntsoeTypeEnum.DAY_AHEAD,\n                )\n            )\n            raw_exchange_lists_forecast_total.append(\n                parse_exchange_forecast(\n                    raw_exchange,\n                    is_import=False,\n                    sorted_zone_keys=sorted_zone_keys,\n                    logger=logger,\n                    market_type=EntsoeTypeEnum.TOTAL,\n                )\n            )\n    if not forecast:\n        return ExchangeList(logger).merge_exchanges(raw_exchange_lists, logger)\n    merged_forecast_day_ahead = ExchangeList(logger).merge_exchanges(\n        raw_exchange_lists_forecast_day_ahead, logger\n    )\n    merged_forecast_total = ExchangeList(logger).merge_exchanges(\n        raw_exchange_lists_forecast_total, logger\n    )\n    return ExchangeList(logger).update_exchanges(\n        merged_forecast_day_ahead, merged_forecast_total, logger\n    )\n\n\n@refetch_frequency(DEFAULT_LOOKBACK_HOURS_REALTIME)\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Gets exchange status between two specified zones.\n    \"\"\"\n    exchanges = get_raw_exchange(\n        zone_key1,\n        zone_key2,\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n    )\n    return exchanges.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange_forecast(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Gets exchange forecast between two specified zones.\n    \"\"\"\n    exchanges = get_raw_exchange(\n        zone_key1,\n        zone_key2,\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n        forecast=True,\n    )\n    return exchanges.to_list()\n\n\n@refetch_frequency(DEFAULT_LOOKBACK_HOURS_REALTIME)\ndef fetch_price(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Gets day-ahead price for specified zone.\"\"\"\n    if not session:\n        session = Session()\n\n    domain = ENTSOE_PRICE_DOMAIN_MAPPINGS[zone_key]\n    try:\n        raw_price_data = query_price(domain, session, target_datetime=target_datetime)\n    except Exception as e:\n        raise ParserException(\n            parser=\"ENTSOE.py\",\n            message=f\"Failed to fetch price for {zone_key}\",\n            zone_key=zone_key,\n        ) from e\n    if raw_price_data is None:\n        raise ParserException(\n            parser=\"ENTSOE.py\",\n            message=f\"No price data found for {zone_key}\",\n            zone_key=zone_key,\n        )\n    return parse_prices(raw_price_data, zone_key, logger).to_list()\n\n\n# DO NOT USE, THIS IS FOR FUTURE USE CASES\n@refetch_frequency(DEFAULT_LOOKBACK_HOURS_REALTIME)\ndef fetch_price_intraday(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    DO NOT USE, THIS IS FOR FUTURE USE CASES.\n    Gets intraday price for specified zone.\n    \"\"\"\n    if not session:\n        session = Session()\n\n    domain = ENTSOE_PRICE_DOMAIN_MAPPINGS[zone_key]\n    try:\n        raw_price_data = query_price(\n            domain,\n            session,\n            target_datetime=target_datetime,\n            marketType=EntsoeTypeEnum.INTRADAY_PRICE,\n        )\n    except Exception as e:\n        raise ParserException(\n            parser=\"ENTSOE.py\",\n            message=f\"Failed to fetch price for {zone_key}\",\n            zone_key=zone_key,\n        ) from e\n    if raw_price_data is None:\n        raise ParserException(\n            parser=\"ENTSOE.py\",\n            message=f\"No price data found for {zone_key}\",\n            zone_key=zone_key,\n        )\n    return parse_prices(raw_price_data, zone_key, logger).to_list()\n\n\n# ------------------- #\n#  Generation\n# ------------------- #\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_generation_forecast(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Gets generation forecast for specified zone.\"\"\"\n    session = session or Session()\n    non_aggregated_data: list[TotalProductionList] = []\n    for _zone_key in ZONE_KEY_AGGREGATES.get(zone_key, [zone_key]):\n        generation_list = TotalProductionList(logger)\n        domain = ENTSOE_DOMAIN_MAPPINGS[_zone_key]\n        try:\n            raw_generation_forecast = query_generation_forecast(\n                domain, session, target_datetime=target_datetime\n            )\n        except Exception as e:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"Failed to fetch generation forecast for {_zone_key}\",\n                zone_key=zone_key,\n            ) from e\n        if raw_generation_forecast is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No generation forecast data found for {_zone_key}\",\n                zone_key=zone_key,\n            )\n        parsed = parse_scalar(\n            raw_generation_forecast,\n            only_inBiddingZone_Domain=True,\n        )\n        if parsed is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No generation forecast data found for {_zone_key}\",\n                zone_key=zone_key,\n            )\n        for dt, value in parsed:\n            generation_list.append(\n                zoneKey=zone_key,\n                datetime=dt,\n                source=SOURCE,\n                value=value,\n                sourceType=EventSourceType.forecasted,\n            )\n        # Aggregated data are regrouped under the same zone key.\n        non_aggregated_data.append(generation_list)\n\n    return TotalProductionList.merge_total_production_lists(\n        non_aggregated_data, logger\n    ).to_list()\n\n\n# ------------------- #\n#  Consumption\n# ------------------- #\n\n\n@refetch_frequency(DEFAULT_LOOKBACK_HOURS_REALTIME)\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    \"\"\"Gets consumption for a specified zone.\"\"\"\n    session = session or Session()\n    non_aggregated_data: list[TotalConsumptionList] = []\n    for _zone_key in ZONE_KEY_AGGREGATES.get(zone_key, [zone_key]):\n        domain = ENTSOE_DOMAIN_MAPPINGS[_zone_key]\n        try:\n            raw_consumption = query_consumption(\n                domain, session, target_datetime=target_datetime\n            )\n        except Exception as e:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"Failed to fetch consumption for {_zone_key}\",\n                zone_key=zone_key,\n            ) from e\n        if raw_consumption is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No consumption data found for {_zone_key}\",\n                zone_key=zone_key,\n            )\n        parsed = parse_scalar(raw_consumption, only_outBiddingZone_Domain=True)\n        if parsed is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No consumption data found for {_zone_key}\",\n                zone_key=zone_key,\n            )\n\n        consumption_list = TotalConsumptionList(logger)\n        for dt, value in parsed:\n            consumption_list.append(\n                zoneKey=zone_key,\n                datetime=dt,\n                source=SOURCE,\n                consumption=value,\n                sourceType=EventSourceType.measured,\n            )\n\n        # Aggregated data are regrouped under the same zone key.\n        non_aggregated_data.append(consumption_list)\n\n    return TotalConsumptionList.merge_consumption_lists(\n        non_aggregated_data, logger\n    ).to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Gets consumption forecast for specified zone.\"\"\"\n    session = session or Session()\n    non_aggregated_data: list[TotalConsumptionList] = []\n    for _zone_key in ZONE_KEY_AGGREGATES.get(zone_key, [zone_key]):\n        domain = ENTSOE_DOMAIN_MAPPINGS[_zone_key]\n        try:\n            raw_consumption = query_consumption_forecast(\n                domain, session, target_datetime=target_datetime\n            )\n        except Exception as e:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"Failed to fetch consumption forecast for {_zone_key}\",\n                zone_key=zone_key,\n            ) from e\n        if raw_consumption is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No consumption forecast data found for {_zone_key}\",\n                zone_key=zone_key,\n            )\n        parsed = parse_scalar(raw_consumption, only_outBiddingZone_Domain=True)\n        if parsed is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No consumption forecast data found for {_zone_key}\",\n                zone_key=zone_key,\n            )\n\n        consumption_list = TotalConsumptionList(logger)\n        for dt, value in parsed:\n            consumption_list.append(\n                zoneKey=zone_key,\n                datetime=dt,\n                source=SOURCE,\n                consumption=value,\n                sourceType=EventSourceType.forecasted,\n            )\n\n        # Aggregated data are regrouped under the same zone key.\n        non_aggregated_data.append(consumption_list)\n    return TotalConsumptionList.merge_consumption_lists(\n        non_aggregated_data, logger\n    ).to_list()\n\n\ndef _fetch_wind_solar_forecasts(\n    zone_key: ZoneKey,\n    forecast_type: EntsoeTypeEnum,\n    session: Session,\n    target_datetime: datetime | None,\n    logger: Logger,\n) -> ProductionBreakdownList:\n    \"\"\"Shared logic for the 3 type-specific wind/solar forecast fetchers.\"\"\"\n    label = forecast_type.name.lower().replace(\"_\", \"-\")\n    non_aggregated_data: list[ProductionBreakdownList] = []\n    for _zone_key in ZONE_KEY_AGGREGATES.get(zone_key, [zone_key]):\n        domain = ENTSOE_DOMAIN_MAPPINGS[_zone_key]\n        try:\n            raw_forecast = query_wind_solar_production_forecast(\n                domain,\n                session,\n                forecast_type,\n                target_datetime=target_datetime,\n            )\n        except Exception as e:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"Failed to fetch {label} wind and solar forecast for {_zone_key}\",\n                zone_key=zone_key,\n            ) from e\n        if raw_forecast is None:\n            raise ParserException(\n                parser=\"ENTSOE.py\",\n                message=f\"No {label} wind and solar forecast data found for {_zone_key}\",\n                zone_key=zone_key,\n            )\n        parsed = parse_production(raw_forecast, logger, zone_key, forecasted=True)\n        # Aggregated data are regrouped under the same zone key.\n        non_aggregated_data.append(parsed)\n    return ProductionBreakdownList.merge_production_breakdowns(\n        non_aggregated_data, logger\n    )\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Gets values and corresponding datetimes for all production types in the specified zone.\n    \"\"\"\n    session = session or Session()\n    forecast_breakdown_list = ProductionBreakdownList(logger)\n    # Order matters: later types override earlier ones at matching datetimes\n    # (intraday overrides day-ahead, current overrides intraday).\n    for forecast_type in [\n        EntsoeTypeEnum.DAY_AHEAD,\n        EntsoeTypeEnum.INTRADAY,\n        EntsoeTypeEnum.CURRENT,\n    ]:\n        try:\n            per_type = _fetch_wind_solar_forecasts(\n                zone_key, forecast_type, session, target_datetime, logger\n            )\n        except ParserException as e:\n            logger.error(\n                f\"Failed to fetch {forecast_type.name} wind and solar forecast for {zone_key}: {e}\",\n                extra={\"zone_key\": zone_key},\n            )\n            continue\n\n        forecast_breakdown_list = ProductionBreakdownList.update_production_breakdowns(\n            forecast_breakdown_list,\n            per_type,\n            logger,\n        )\n    if len(forecast_breakdown_list) == 0:\n        raise ParserException(\n            parser=\"ENTSOE.py\",\n            message=f\"No wind and solar forecast data found for {zone_key}\",\n            zone_key=zone_key,\n        )\n    return forecast_breakdown_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_wind_solar_forecasts_day_ahead(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    return _fetch_wind_solar_forecasts(\n        zone_key,\n        EntsoeTypeEnum.DAY_AHEAD,\n        session or Session(),\n        target_datetime,\n        logger,\n    ).to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_wind_solar_forecasts_intraday(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    return _fetch_wind_solar_forecasts(\n        zone_key,\n        EntsoeTypeEnum.INTRADAY,\n        session or Session(),\n        target_datetime,\n        logger,\n    ).to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_wind_solar_forecasts_current(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    return _fetch_wind_solar_forecasts(\n        zone_key,\n        EntsoeTypeEnum.CURRENT,\n        session or Session(),\n        target_datetime,\n        logger,\n    ).to_list()\n\n\ndef _fetch_exchange_capacity_forecasts(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    forecast_type: EntsoeTypeEnum,\n    session: Session,\n    target_datetime: datetime | None,\n    logger: Logger,\n) -> list[dict]:\n    \"\"\"Shared logic for all 3 type-specific fetch functions.\"\"\"\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    domain_1 = ENTSOE_DOMAIN_MAPPINGS[zone_key1]\n    domain_2 = ENTSOE_DOMAIN_MAPPINGS[zone_key2]\n\n    raw_export: str | None = None\n    raw_import: str | None = None\n    max_retries = 5\n\n    for attempt in range(1, max_retries + 1):\n        if raw_export is None:\n            raw_export = query_exchange_capacity_forecast(\n                domain_2,\n                domain_1,\n                session,\n                forecast_type,\n                target_datetime=target_datetime,\n                logger=logger,\n            )\n        if raw_import is None:\n            raw_import = query_exchange_capacity_forecast(\n                domain_1,\n                domain_2,\n                session,\n                forecast_type,\n                target_datetime=target_datetime,\n                logger=logger,\n            )\n\n        if raw_export is not None and raw_import is not None:\n            break\n\n        if attempt < max_retries:\n            logger.info(\n                f\"Attempt {attempt}/{max_retries} for {sorted_zone_keys} \"\n                f\"{forecast_type}: export={'OK' if raw_export else 'MISSING'}, \"\n                f\"import={'OK' if raw_import else 'MISSING'}. Retrying...\"\n            )\n\n    if raw_export is None or raw_import is None:\n        raise ParserException(\n            parser=\"ENTSOE.py\",\n            message=(\n                f\"Failed to get both export and import exchange capacity forecast \"\n                f\"data for {sorted_zone_keys} after {max_retries} attempts. \"\n                f\"export={'OK' if raw_export else 'MISSING'}, \"\n                f\"import={'OK' if raw_import else 'MISSING'}\"\n            ),\n            zone_key=sorted_zone_keys,\n        )\n\n    export_list = parse_exchange_capacity_forecast(\n        raw_export,\n        sorted_zone_keys=sorted_zone_keys,\n        logger=logger,\n        direction=\"export\",\n    )\n    import_list = parse_exchange_capacity_forecast(\n        raw_import,\n        sorted_zone_keys=sorted_zone_keys,\n        logger=logger,\n        direction=\"import\",\n    )\n\n    return _merge_exchange_capacity_forecasts(\n        export_list, import_list, logger\n    ).to_list()\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_exchange_capacity_forecasts_day_ahead(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Gets day-ahead exchange capacity forecast between two zones for both directions.\"\"\"\n    return _fetch_exchange_capacity_forecasts(\n        zone_key1,\n        zone_key2,\n        EntsoeTypeEnum.DAY_AHEAD,\n        session or Session(),\n        target_datetime,\n        logger,\n    )\n\n\n@refetch_frequency(timedelta(days=7))\ndef fetch_exchange_capacity_forecasts_week_ahead(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Gets week-ahead exchange capacity forecast between two zones for both directions.\"\"\"\n    return _fetch_exchange_capacity_forecasts(\n        zone_key1,\n        zone_key2,\n        EntsoeTypeEnum.WEEK_AHEAD,\n        session or Session(),\n        target_datetime,\n        logger,\n    )\n\n\n@refetch_frequency(timedelta(days=7))\ndef fetch_exchange_capacity_forecasts_month_ahead(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Gets month-ahead exchange capacity forecast between two zones for both directions.\"\"\"\n    return _fetch_exchange_capacity_forecasts(\n        zone_key1,\n        zone_key2,\n        EntsoeTypeEnum.MONTH_AHEAD,\n        session or Session(),\n        target_datetime,\n        logger,\n    )\n\n\nif __name__ == \"__main__\":\n    print(fetch_exchange_capacity_forecasts_day_ahead(ZoneKey(\"PL\"), ZoneKey(\"SE-SE4\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ERP_PGCB.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import date, datetime, time, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup, Tag\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\n# Power Grid Company of Bangladesh: erp.pgcb.gov.bd\n# Has table (also historical) of production, consumption and exchange.\n# This table gets updated batch-wise every few hours, so most of the time, the delay will be >2h.\n\nTIMEZONE = ZoneInfo(\"Asia/Dhaka\")\nLATEST_URL = \"https://erp.pgcb.gov.bd/web/generations/view_generations\"\nHISTORICAL_URL = (\n    \"https://erp.pgcb.gov.bd/web/generations/view_generations?search=\"  # DD-MM-YYYY\n)\nSOURCE = \"erp.pgcb.gov.bd\"\nTABLE_HEADERS = [\n    \"Date\",\n    \"Time\",\n    \"Generation(MW)\",\n    \"Demand(MW)\",\n    \"Loadshed\",\n    \"Gas\",\n    \"Liquid Fuel\",\n    \"Coal\",\n    \"Hydro\",\n    \"Solar\",\n    \"Wind\",\n    \"India\",  # Visual grouping of India imports\n    \"Nepal\",  # Import\n    \"Remarks\",\n    \"Bheramara HVDC\",  # Import\n    \"Tripura\",  # Import\n    \"Adani\",  # Import\n]\nPARSER = \"ERP_PGCB.py\"\n\n\ndef table_entry_to_float(entry: str):\n    \"\"\"\n    Helper function to handle empty cells in table.\n    \"\"\"\n    if entry == \"\":\n        return None\n    try:\n        return float(entry)\n    except ValueError as e:\n        raise ParserException(\n            parser=PARSER,\n            message=(f'Failed to parse entry: \"{entry}\" to float in table.'),\n        ) from e\n\n\ndef parse_table_body(table_body: Tag) -> list[dict]:\n    \"\"\"\n    Parse the table body returned by the URL.\n    Returns a list of rows represented by dicts.\n    \"\"\"\n\n    rows = table_body.find_all(\"tr\")\n    row_data = []\n\n    for row in rows:\n        row_items = row.find_all(\"td\")\n        row_items = [item.text.strip() for item in row_items]\n\n        # date and time in [0]; [1] are DD-MM-YYYY; HH:mm[:ss]\n        parsed_day = datetime.strptime(row_items[0], \"%d-%m-%Y\").date()\n        assert isinstance(row_items[1], str)\n        hour = int(row_items[1][0:2])\n        # The hour is backwards looking so if it's 01:00, it's actually 00:00\n        hour = hour - 1\n        minute = int(row_items[1][3:5])\n        second = int(row_items[1][6:8])\n        parsed_time = time(hour, minute, second)\n\n        row_data.append(\n            {\n                \"time\": datetime.combine(parsed_day, parsed_time, tzinfo=TIMEZONE),\n                \"total_generation\": table_entry_to_float(row_items[2]),  # MW\n                \"total_demand\": table_entry_to_float(row_items[3]),  # MW\n                \"loadshed\": table_entry_to_float(row_items[4]),\n                \"gas\": table_entry_to_float(row_items[5]),\n                \"oil\": table_entry_to_float(row_items[6]),\n                \"coal\": table_entry_to_float(row_items[7]),\n                \"hydro\": table_entry_to_float(row_items[8]),\n                \"solar\": table_entry_to_float(row_items[9]),\n                \"wind\": table_entry_to_float(row_items[10]),\n                \"bd_import_bheramara\": table_entry_to_float(row_items[11]),\n                \"bd_import_tripura\": table_entry_to_float(row_items[12]),\n                \"bd_import_adani\": table_entry_to_float(row_items[13]),\n                \"bd_import_nepal\": table_entry_to_float(row_items[14]),\n                \"remarks\": row_items[15],\n            }\n        )\n\n    return row_data\n\n\ndef verify_table_header(table_header: Tag):\n    \"\"\"\n    Validate the table headers, that it looks like expected.\n    Don't parse if the table has changed.\n    \"\"\"\n    header_items = table_header.find_all(\"th\")\n    header_items = [item.text.strip() for item in header_items]\n\n    if header_items != TABLE_HEADERS:\n        raise ParserException(\n            parser=PARSER,\n            message=(\n                f\"Table headers mismatch with expected ones.\\n\"\n                f\"Expected: {TABLE_HEADERS}\\n\"\n                f\"Parsed: {header_items}\"\n            ),\n        )\n\n\ndef query(\n    session: Session, target_datetime: datetime | None, logger: Logger\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Query the table and read it into list.\n    \"\"\"\n\n    if target_datetime is not None and target_datetime.date() < date(2015, 5, 1):\n        raise ParserException(\n            parser=PARSER,\n            message=\"Data before 2015-05-01 is not reliable and will not be parsed.\",\n            zone_key=\"BD\",\n        )\n\n    # build URL to call\n    if target_datetime is None:\n        target_url = LATEST_URL\n    else:\n        # Convert timezone of target_datetime, and build URL from day\n        target_datetime_bd = target_datetime.astimezone(TIMEZONE)\n        target_dt_str = target_datetime_bd.strftime(\"%d-%m-%Y\")\n        target_url = HISTORICAL_URL + target_dt_str\n\n    target_response: Response = session.get(target_url, verify=False)\n    # SSL verification is disabled because the server's certificate is expired.\n\n    if not target_response.ok:\n        raise ParserException(\n            parser=PARSER,\n            message=f\"Data request did not succeed: {target_response.status_code}\",\n        )\n\n    response_soup = BeautifulSoup(target_response.text, \"html.parser\")\n\n    # Find the table, there is only one, and verify its headers.\n    table = response_soup.find(\"table\")\n    if table is None:\n        raise ParserException(\n            parser=PARSER,\n            message=\"Could not find table in returned HTML.\",\n        )\n\n    table_head = table.find(\"thead\")\n    if table_head is None:\n        raise ParserException(\n            parser=PARSER,\n            message=(\"Could not find table header in returned HTML.\"),\n        )\n    verify_table_header(table_head)\n\n    # Table valid as we expect, parse the rows.\n    table_body = table.find(\"tbody\")\n    if table_body is None:\n        raise ParserException(\n            parser=PARSER,\n            message=(\"Could not find table body in returned HTML.\"),\n        )\n    row_data = parse_table_body(table_body)\n\n    return row_data\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"BD\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n\n    row_data = query(session, target_datetime, logger)\n    production_data_list = ProductionBreakdownList(logger)\n    for row in row_data:\n        # Create data with empty production\n        production = ProductionMix()\n\n        # And add sources if they are present in the table z\n        known_sources_sum_mw = 0.0\n        for source_type in [\"coal\", \"gas\", \"hydro\", \"oil\", \"solar\", \"wind\"]:\n            if row[source_type] is not None:\n                # also accumulate the sources to infer 'unknown'\n                known_sources_sum_mw += row[source_type]\n                production.add_value(source_type, row[source_type])\n\n        # infer 'unknown'\n        if row[\"total_generation\"] is not None:\n            # Total generation includes all sources, including imports so we need to subtract them to get the unknown source\n            # Before this date Adani import in NoneType\n\n            unknown_source_mw = (\n                row[\"total_generation\"]\n                - known_sources_sum_mw\n                - row[\"bd_import_bheramara\"]\n                - row[\"bd_import_tripura\"]\n            )\n            # Adani import was added after this date\n            if target_datetime is None or target_datetime.date() > date(2024, 8, 27):\n                unknown_source_mw -= row[\"bd_import_adani\"]\n\n            production.add_value(\n                \"unknown\", unknown_source_mw, correct_negative_with_zero=True\n            )\n\n        production_data_list.append(\n            zoneKey=zone_key,\n            datetime=row[\"time\"],\n            production=production,\n            source=SOURCE,\n        )\n\n    return production_data_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"BD\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n\n    row_data = query(session, target_datetime, logger)\n\n    result_list = TotalConsumptionList(logger)\n\n    for row in row_data:\n        # get the demand from the table\n        consumption = row[\"total_demand\"]\n        if consumption is None:\n            continue  # no data in table\n\n        result_list.append(\n            zoneKey=zone_key,\n            datetime=row[\"time\"],\n            consumption=consumption,\n            source=SOURCE,\n        )\n\n    if not len(result_list):\n        raise ParserException(\n            parser=PARSER,\n            message=\"No valid consumption data for requested day found.\",\n        )\n\n    return result_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n\n    # Query table, contains import from india.\n    row_data = query(session, target_datetime, logger)\n\n    exchange_list = ExchangeList(logger)\n    sortedZoneKeys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    for row in row_data:\n        if zone_key2 == \"IN-NE\":\n            # Import from India NorthEast via Tripura\n            bd_import = row[\"bd_import_tripura\"]\n        elif zone_key2 == \"IN-EA\":\n            # Import from India East via Bheramara and Adani (Jharkhand plant)\n            bd_import = row[\"bd_import_bheramara\"]\n\n            if (\n                target_datetime is None\n                or target_datetime.date() > datetime(2024, 8, 27).date()\n            ):\n                bd_import += row[\"bd_import_adani\"]\n        elif zone_key2 == \"NP\":\n            # Import from Nepal\n            bd_import = row[\"bd_import_nepal\"]\n        else:\n            raise ParserException(\n                parser=PARSER,\n                message=f\"Exchange pair {sortedZoneKeys} is not implemented.\",\n            )\n        if bd_import is None:\n            continue  # no data in table\n\n        bd_export = -1.0 * bd_import\n\n        exchange_list.append(\n            zoneKey=sortedZoneKeys,\n            datetime=row[\"time\"],\n            netFlow=bd_export,\n            source=SOURCE,\n        )\n\n    return exchange_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n    print(\"fetch_exchange('BD', 'IN-NE') ->\")\n    print(fetch_exchange(ZoneKey(\"BD\"), ZoneKey(\"IN-NE\")))\n    print(\"fetch_exchange('BD', 'IN-EA') ->\")\n    print(fetch_exchange(ZoneKey(\"BD\"), ZoneKey(\"IN-EA\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ES.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime, timedelta\nfrom json import loads\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\n# The request library is used to fetch content through HTTP\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.types import ZoneKey\n\nfrom .lib.config import refetch_frequency\nfrom .lib.exceptions import ParserException\n\n#    Zone name Cheat Sheet\n\n#    ZoneKey(\"ES\"): \"IberianPeninsula\"\n#    ZoneKey(\"ES-CE\"): \"Ceuta\"\n#    ZoneKey(\"ES-CN-FVLZ\"): \"LanzaroteFuerteventura\"\n#    ZoneKey(\"ES-CN-GC\"): \"GranCanaria\"\n#    ZoneKey(\"ES-CN-HI\"): \"ElHierro\"\n#    ZoneKey(\"ES-CN-IG\"): \"Gomera\"\n#    ZoneKey(\"ES-CN-LP\"): \"LaPalma\"\n#    ZoneKey(\"ES-CN-TE\"): \"Tenerife\"\n#    ZoneKey(\"ES-IB-FO\"): \"Formentera\"\n#    ZoneKey(\"ES-IB-IZ\"): \"Ibiza\"\n#    ZoneKey(\"ES-IB-MA\"): \"Mallorca\"\n#    ZoneKey(\"ES-IB-ME\"): \"Menorca\"\n#    ZoneKey(\"ES-ML\"): \"Melilla\"\n#    ZoneKey(\"ES-CN-FV\"): \"Fuerteventura\"\n#    ZoneKey(\"ES-CN-LZ\"): \"Lanzarote\"\n\nPRODUCTION_PARSE_MAPPING = {\n    \"nuc\": \"nuclear\",  # Nuclear\n    \"die\": \"oil\",  # Diesel engines\n    \"genAux\": \"oil\",  # Auxiliary generation\n    \"gas\": \"gas\",  # Gas turbine\n    \"gf\": \"gas\",  # Fuel/gas\n    \"eol\": \"wind\",  # Wind\n    \"cc\": \"gas\",  # Combined cycle\n    \"vap\": \"oil\",  # Vapor turbine\n    \"fot\": \"solar\",  # Solar PV\n    \"sol\": \"solar\",  # Solar\n    \"car\": \"coal\",  # Coal\n    \"resid\": \"biomass\",  # Wastes\n    \"termRenov\": \"unknown\",  # Thermal renewable\n    \"cogenResto\": \"unknown\",  # Cogeneration and waste\n    \"tnr\": \"unknown\",  # Other special regime\n    \"trn\": \"unknown\",  # Thermal renewable\n    \"otrRen\": \"unknown\",  # Other renewable\n    \"cogen\": \"gas\",  # Cogeneration\n    \"turb\": \"hydro_storage\",  # Pumping Turbine\n    \"conb\": \"hydro_storage\",  # Pumping consumption\n    \"residNr\": \"unknown\",  # Non-renewable waste\n    \"residRen\": \"biomass\",  # Renewable wastes\n    \"bat\": \"battery_storage\",  # Battery\n    \"consBat\": \"battery_storage\",  # Battery consumption\n    \"aut\": \"unknown\",  # Other special regime\n    \"gnhd\": \"hydro\",  # Hydro\n}\n\nPRODUCTION_IGNORE_KEYS = [\n    \"dem\",  # Demand\n    \"hid\",  # Hydro => sum of hydro\n    \"ts\",  # Timestamp\n    \"expTot\",  # Exportation Total\n    \"impTot\",  # Importation Total\n    \"dif\",  # ?\n    \"solFot\",  # Solar PV => include in solar\n    \"solTer\",  # Solar thermal => include in solar\n    \"inter\",  # Int. exchanges\n    \"icb\",  # Balear link => include in cb (Balearic-Peninsula link)\n]\n\nZONE_MAPPING = {\n    ZoneKey(\"ES\"): {\n        \"API_CODE\": \"DEMANDAAU\",\n        \"SYSTEM\": \"Peninsula\",\n        \"TZ\": \"Europe/Madrid\",\n    },\n    ZoneKey(\"ES-CE\"): {\n        \"API_CODE\": \"CEUTAAU\",\n        \"SYSTEM\": \"Peninsula\",\n        \"TZ\": \"Africa/Ceuta\",\n    },\n    ZoneKey(\"ES-CN-FVLZ\"): {\n        \"API_CODE\": \"LZ_FVAU\",\n        \"SYSTEM\": \"Canarias\",\n        \"TZ\": \"Atlantic/Canary\",\n    },\n    ZoneKey(\"ES-CN-GC\"): {\n        \"API_CODE\": \"GCANARIAAU\",\n        \"SYSTEM\": \"Canarias\",\n        \"TZ\": \"Atlantic/Canary\",\n    },\n    ZoneKey(\"ES-CN-HI\"): {\n        \"API_CODE\": \"EL_HIERROAU\",\n        \"SYSTEM\": \"Canarias\",\n        \"TZ\": \"Atlantic/Canary\",\n    },\n    ZoneKey(\"ES-CN-IG\"): {\n        \"API_CODE\": \"LA_GOMERAAU\",\n        \"SYSTEM\": \"Canarias\",\n        \"TZ\": \"Atlantic/Canary\",\n    },\n    ZoneKey(\"ES-CN-LP\"): {\n        \"API_CODE\": \"LA_PALMAAU\",\n        \"SYSTEM\": \"Canarias\",\n        \"TZ\": \"Atlantic/Canary\",\n    },\n    ZoneKey(\"ES-CN-TE\"): {\n        \"API_CODE\": \"TENERIFEAU\",\n        \"SYSTEM\": \"Canarias\",\n        \"TZ\": \"Atlantic/Canary\",\n    },\n    ZoneKey(\"ES-IB-FO\"): {\n        \"API_CODE\": \"FORMENTERAAU\",\n        \"SYSTEM\": \"Baleares\",\n        \"TZ\": \"Europe/Madrid\",\n    },\n    ZoneKey(\"ES-IB-IZ\"): {\n        \"API_CODE\": \"IBIZAAU\",\n        \"SYSTEM\": \"Baleares\",\n        \"TZ\": \"Europe/Madrid\",\n    },\n    ZoneKey(\"ES-IB-MA\"): {\n        \"API_CODE\": \"MALLORCAAU\",\n        \"SYSTEM\": \"Baleares\",\n        \"TZ\": \"Europe/Madrid\",\n    },\n    ZoneKey(\"ES-IB-ME\"): {\n        \"API_CODE\": \"MENORCAAU\",\n        \"SYSTEM\": \"Baleares\",\n        \"TZ\": \"Europe/Madrid\",\n    },\n    ZoneKey(\"ES-ML\"): {\n        \"API_CODE\": \"MELILLAAU\",\n        \"SYSTEM\": \"Peninsula\",\n        \"TZ\": \"Africa/Ceuta\",\n    },\n    ZoneKey(\"ES-CN-FV\"): {\n        \"API_CODE\": \"FUERTEVEAU\",\n        \"SYSTEM\": \"Canarias\",\n        \"TZ\": \"Atlantic/Canary\",\n    },\n    ZoneKey(\"ES-CN-LZ\"): {\n        \"API_CODE\": \"LANZAROTAU\",\n        \"SYSTEM\": \"Canarias\",\n        \"TZ\": \"Atlantic/Canary\",\n    },\n}\n\nEXCHANGE_MAPPING = {\n    ZoneKey(\"ES->ES-IB-MA\"): {\n        \"zone_ref\": ZoneKey(\"ES-IB-MA\"),\n        \"codes\": [\"cb\"],\n        \"coef\": 1,\n    },\n    ZoneKey(\"ES-IB-IZ->ES-IB-MA\"): {\n        \"zone_ref\": ZoneKey(\"ES-IB-MA\"),\n        \"codes\": [\"emi\"],\n        \"coef\": 1,\n    },\n    ZoneKey(\"ES-IB-FO->ES-IB-IZ\"): {\n        \"zone_ref\": ZoneKey(\"ES-IB-FO\"),\n        \"codes\": [\"eif\"],\n        \"coef\": -1,\n    },\n    ZoneKey(\"ES-IB-MA->ES-IB-ME\"): {\n        \"zone_ref\": ZoneKey(\"ES-IB-MA\"),\n        \"codes\": [\"emm\"],\n        \"coef\": -1,\n    },\n    ZoneKey(\"AD->ES\"): {\n        \"zone_ref\": ZoneKey(\"ES\"),\n        \"codes\": [\"expAnd\", \"impAnd\"],\n        \"coef\": 1,\n    },\n    ZoneKey(\"ES->MA\"): {\n        \"zone_ref\": ZoneKey(\"ES\"),\n        \"codes\": [\"expMar\", \"impMar\"],\n        \"coef\": -1,\n    },\n    ZoneKey(\"ES->PT\"): {\n        \"zone_ref\": ZoneKey(\"ES\"),\n        \"codes\": [\"expPor\", \"impPor\"],\n        \"coef\": -1,\n    },\n    ZoneKey(\"ES->FR\"): {\n        \"zone_ref\": ZoneKey(\"ES\"),\n        \"codes\": [\"expFra\", \"impFra\"],\n        \"coef\": -1,\n    },\n    ZoneKey(\"ES-CN-FV->ES-CN-LZ\"): {\n        \"zone_ref\": ZoneKey(\"ES-CN-LZ\"),\n        \"codes\": [\"efl\"],\n        \"coef\": 1,\n    },\n}\n\nEXCHANGE_MAPPING_CODES = [m for v in EXCHANGE_MAPPING.values() for m in v[\"codes\"]]\n\nKNOWN_KEY = (\n    EXCHANGE_MAPPING_CODES\n    + list(PRODUCTION_PARSE_MAPPING.keys())\n    + PRODUCTION_IGNORE_KEYS\n)\n\nSOURCE = \"demanda.ree.es\"\n\nURL_PATERN = \"https://demanda.ree.es/WSvisionaMoviles{system}Rest/resources/demandaGeneracion{system}?curva={zone}&fecha={date}\"\n\n\ndef check_valid_parameters(\n    zone_key: ZoneKey,\n    session: Session | None,\n    target_datetime: datetime | None,\n):\n    \"\"\"Raise an exception if the parameters are not valid for this parser.\"\"\"\n    if \"->\" not in zone_key and zone_key not in ZONE_MAPPING:\n        raise ParserException(\n            \"ES.py\",\n            f\"This parser cannot parse data for zone: {zone_key}\",\n            zone_key,\n        )\n    elif \"->\" in zone_key and zone_key not in EXCHANGE_MAPPING:\n        zone_key1, zone_key2 = zone_key.split(\"->\")\n        raise ParserException(\n            \"ES.py\",\n            f\"This parser cannot parse data between {zone_key1} and {zone_key2}.\",\n            zone_key,\n        )\n    if session is not None and not isinstance(session, Session):\n        raise ParserException(\n            \"ES.py\",\n            f\"Invalid session: {session}\",\n            zone_key,\n        )\n    if target_datetime is not None and not isinstance(target_datetime, datetime):\n        raise ParserException(\n            \"ES.py\",\n            f\"Invalid target_datetime: {target_datetime}\",\n            zone_key,\n        )\n\n\ndef check_known_key(key: str, logger: Logger):\n    \"\"\"Check if the given key is already known and log a warning if not.\"\"\"\n    if key not in KNOWN_KEY:\n        logger.warning(f'Key \"{key}\" could not be parsed!')\n\n\ndef get_url(zone_key: ZoneKey, date: str) -> str:\n    return URL_PATERN.format(\n        system=ZONE_MAPPING[zone_key][\"SYSTEM\"],\n        zone=ZONE_MAPPING[zone_key][\"API_CODE\"],\n        date=date,\n    )\n\n\ndef get_ree_data(\n    zone_key: ZoneKey, session: Session, target_datetime: datetime | None, tz: str\n) -> dict:\n    if target_datetime is None:\n        date = datetime.now(tz=ZoneInfo(tz)).strftime(\"%Y-%m-%d\")\n    else:\n        date = target_datetime.strftime(\"%Y-%m-%d\")\n    res = session.get(get_url(zone_key, date))\n    if not res.ok:\n        raise ParserException(\n            \"ES.py\",\n            f\"Failed fetching data for {zone_key}\",\n            zone_key,\n        )\n    # The response is not a valid JSON, but a JSON-like string starting with \"'null(\" and ending with \");\" or \")\"\n    json = loads(res.text[5:-2]) if res.text[-1] == \";\" else loads(res.text[5:-1])\n\n    return json[\"valoresHorariosGeneracion\"]\n\n\n# Parses the date. In DST end days, the repeated hours are distinguished using a leter, this needs to be parsed\ndef parse_date(str_date, tz):\n    if \"A\" in str_date:\n        index = str_date.index(\"A\")\n        new_value = (\n            str_date[: index - 1] + \"0\" + str_date[index - 1] + str_date[index + 1 :]\n        )\n        # If A, we use the timezone from yesterday\n        return datetime.fromisoformat(\n            new_value\n            + f\" +0{ZoneInfo(tz).utcoffset(datetime.fromisoformat(new_value) - timedelta(days=1))}\"\n        )\n    elif \"B\" in str_date:\n        index = str_date.index(\"B\")\n        new_value = (\n            str_date[: index - 1] + \"0\" + str_date[index - 1] + str_date[index + 1 :]\n        )\n        # If B, we use the timezone from tomorrow\n        return datetime.fromisoformat(\n            new_value\n            + f\" +0{ZoneInfo(tz).utcoffset(datetime.fromisoformat(new_value) + timedelta(days=1))}\"\n        )\n    else:\n        return datetime.fromisoformat(str_date).replace(tzinfo=ZoneInfo(tz))\n\n\ndef fetch_and_preprocess_data(\n    zone_key: ZoneKey,\n    session: Session,\n    logger: Logger,\n    target_datetime: datetime | None,\n):\n    \"\"\"Fetch data for the given zone key.\"\"\"\n    tz = ZONE_MAPPING[zone_key][\"TZ\"]\n    data = get_ree_data(zone_key, session, target_datetime, tz)\n    for value in data:\n        # Add timezone info to time object\n        value[\"ts\"] = parse_date(value[\"ts\"], tz)\n\n        for key in value:\n            check_known_key(key, logger)\n    if data:\n        return data\n    else:\n        raise ParserException(\n            \"ES.py\",\n            f\"Failed fetching data for {zone_key}\",\n            zone_key,\n        )\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    check_valid_parameters(zone_key, session, target_datetime)\n\n    ses = session or Session()\n    data = fetch_and_preprocess_data(zone_key, ses, logger, target_datetime)\n    consumption = TotalConsumptionList(logger)\n    for event in data:\n        consumption.append(\n            zoneKey=zone_key,\n            datetime=event[\"ts\"],\n            consumption=event[\"dem\"],\n            source=\"demanda.ree.es\",\n        )\n    return consumption.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    check_valid_parameters(zone_key, session, target_datetime)\n    ses = session or Session()\n    data_mapping = PRODUCTION_PARSE_MAPPING.copy()\n\n    ## Production mapping override for Canary Islands\n    # NOTE the LNG terminals are not built yet, so power generated by \"gas\" or \"cc\" in ES-CN domain is actually using oil.\n    # Recheck this every 6 months and move to gas key if there has been a change.\n    # As of 2025-02-02 it seems LNG terminals have been canceled.\n    if zone_key.startswith(\"ES-CN\"):\n        data_mapping[\"gas\"] = \"oil\"\n        data_mapping[\"cc\"] = \"oil\"\n\n    if zone_key == \"ES-IB-ME\" or zone_key == \"ES-IB-FO\":\n        data_mapping[\"gas\"] = \"oil\"\n    if zone_key == \"ES-IB-IZ\":\n        data_mapping[\"die\"] = \"gas\"\n\n    # Remove the key \"gnhd\" for the zone ES-CN-HI because it is already included in storage\n    if zone_key == ZoneKey(\"ES-CN-HI\"):\n        del data_mapping[\"gnhd\"]\n\n    data = fetch_and_preprocess_data(zone_key, ses, logger, target_datetime)\n    productionEventList = ProductionBreakdownList(logger)\n    for event in data:\n        storage = StorageMix()\n        production = ProductionMix()\n        for key in event:\n            if key in data_mapping:\n                if data_mapping[key].endswith(\"_storage\"):\n                    storage.add_value(data_mapping[key].split(\"_\")[0], -event[key])\n                else:\n                    production.add_value(data_mapping[key], event[key])\n\n        productionEventList.append(\n            zoneKey=zone_key,\n            datetime=event[\"ts\"],\n            production=production,\n            storage=storage,\n            source=\"demanda.ree.es\",\n        )\n\n    return productionEventList.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    check_valid_parameters(sorted_zone_keys, session, target_datetime)\n    ses = session or Session()\n\n    data = fetch_and_preprocess_data(\n        EXCHANGE_MAPPING[sorted_zone_keys][\"zone_ref\"],\n        ses,\n        logger,\n        target_datetime,\n    )\n\n    exchangeList = ExchangeList(logger)\n    for event in data:\n        net_flow = None\n        for key in event:\n            if key in EXCHANGE_MAPPING[sorted_zone_keys][\"codes\"]:\n                net_flow = (0 if net_flow is None else net_flow) + EXCHANGE_MAPPING[\n                    sorted_zone_keys\n                ][\"coef\"] * event[key]\n\n        if net_flow is not None:\n            exchangeList.append(\n                zoneKey=sorted_zone_keys,\n                datetime=event[\"ts\"],\n                netFlow=net_flow,\n                source=\"demanda.ree.es\",\n            )\n\n    return exchangeList.to_list()\n\n\nif __name__ == \"__main__\":\n    # Spain\n    print(\"fetch_consumption(ES)\")\n    print(fetch_consumption(ZoneKey(\"ES\")))\n    print(\"fetch_production(ES)\")\n    print(fetch_production(ZoneKey(\"ES\")))\n\n    # Autonomous cities\n    print(\"fetch_consumption(ES-CE)\")\n    print(fetch_consumption(ZoneKey(\"ES-CE\")))\n    print(\"fetch_production(ES-CE)\")\n    print(fetch_production(ZoneKey(\"ES-CE\")))\n    print(\"fetch_consumption(ES-ML)\")\n    print(fetch_consumption(ZoneKey(\"ES-ML\")))\n    print(\"fetch_production(ES-ML)\")\n    print(fetch_production(ZoneKey(\"ES-ML\")))\n\n    # Canary Islands\n    print(\"fetch_consumption(ES-CN-FVLZ)\")\n    print(fetch_consumption(ZoneKey(\"ES-CN-FVLZ\")))\n    print(\"fetch_production(ES-CN-FVLZ)\")\n    print(fetch_production(ZoneKey(\"ES-CN-FVLZ\")))\n    print(\"fetch_consumption(ES-CN-GC)\")\n    print(fetch_consumption(ZoneKey(\"ES-CN-GC\")))\n    print(\"fetch_production(ES-CN-GC)\")\n    print(fetch_production(ZoneKey(\"ES-CN-GC\")))\n    print(\"fetch_consumption(ES-CN-IG)\")\n    print(fetch_consumption(ZoneKey(\"ES-CN-IG\")))\n    print(\"fetch_production(ES-CN-IG)\")\n    print(fetch_production(ZoneKey(\"ES-CN-IG\")))\n    print(\"fetch_consumption(ES-CN-LP)\")\n    print(fetch_consumption(ZoneKey(\"ES-CN-LP\")))\n    print(\"fetch_production(ES-CN-LP)\")\n    print(fetch_production(ZoneKey(\"ES-CN-LP\")))\n    print(\"fetch_consumption(ES-CN-TE)\")\n    print(fetch_consumption(ZoneKey(\"ES-CN-TE\")))\n    print(\"fetch_production(ES-CN-TE)\")\n    print(fetch_production(ZoneKey(\"ES-CN-TE\")))\n    print(\"fetch_consumption(ES-CN-HI)\")\n    print(fetch_consumption(ZoneKey(\"ES-CN-HI\")))\n    print(\"fetch_production(ES-CN-HI)\")\n    print(fetch_production(ZoneKey(\"ES-CN-HI\")))\n    print(\"fetch_consumption(ES-CN-FV)\")\n    print(fetch_consumption(ZoneKey(\"ES-CN-FV\")))\n    print(\"fetch_production(ES-CN-LZ)\")\n    print(fetch_production(ZoneKey(\"ES-CN-LZ\")))\n\n    # Balearic Islands\n    print(\"fetch_consumption(ES-IB-FO)\")\n    print(fetch_consumption(ZoneKey(\"ES-IB-FO\")))\n    print(\"fetch_production(ES-IB-FO)\")\n    print(fetch_production(ZoneKey(\"ES-IB-FO\")))\n    print(\"fetch_consumption(ES-IB-IZ)\")\n    print(fetch_consumption(ZoneKey(\"ES-IB-IZ\")))\n    print(\"fetch_production(ES-IB-IZ)\")\n    print(fetch_production(ZoneKey(\"ES-IB-IZ\")))\n    print(\"fetch_consumption(ES-IB-MA)\")\n    print(fetch_consumption(ZoneKey(\"ES-IB-MA\")))\n    print(\"fetch_production(ES-IB-MA)\")\n    print(fetch_production(ZoneKey(\"ES-IB-MA\")))\n    print(\"fetch_consumption(ES-IB-ME)\")\n    print(fetch_consumption(ZoneKey(\"ES-IB-ME\")))\n    print(\"fetch_production(ES-IB-ME)\")\n    print(fetch_production(ZoneKey(\"ES-IB-ME\")))\n\n    # Exchanges\n    print(\"fetch_exchange(ES, ES-IB-MA)\")\n    print(fetch_exchange(ZoneKey(\"ES\"), ZoneKey(\"ES-IB-MA\")))\n    print(\"fetch_exchange(ES-IB-MA, ES-IB-ME)\")\n    print(fetch_exchange(ZoneKey(\"ES-IB-MA\"), ZoneKey(\"ES-IB-ME\")))\n    print(\"fetch_exchange(ES-IB-MA, ES-IB-IZ)\")\n    print(fetch_exchange(ZoneKey(\"ES-IB-MA\"), ZoneKey(\"ES-IB-IZ\")))\n    print(\"fetch_exchange(ES-IB-IZ, ES-IB-FO)\")\n    print(fetch_exchange(ZoneKey(\"ES-IB-IZ\"), ZoneKey(\"ES-IB-FO\")))\n    print(\"fetch_exchange(ES, MA)\")\n    print(fetch_exchange(ZoneKey(\"ES\"), ZoneKey(\"MA\")))\n    print(\"fetch_exchange(ES, AD)\")\n    print(fetch_exchange(ZoneKey(\"ES\"), ZoneKey(\"AD\")))\n    print(\"fetch_exchange(ES, FR)\")\n    print(fetch_exchange(ZoneKey(\"ES\"), ZoneKey(\"FR\")))\n    print(\"fetch_exchange(ES, PT)\")\n    print(fetch_exchange(ZoneKey(\"ES\"), ZoneKey(\"PT\")))\n    print(\"fetch_exchange(ES-CN-FV, ES-CN-LZ)\")\n    print(fetch_exchange(ZoneKey(\"ES-CN-FV\"), ZoneKey(\"ES-CN-LZ\")))\n\n    # DST date test (his only happened when they switched time zones twice a year )\n    print(\"fetch_production(ES, '2024-10-26') DST\")\n    print(fetch_production(ZoneKey(\"ES\"), None, datetime(2024, 10, 26, 0, 0, 0)))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ESIOS.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom time import sleep\nfrom urllib.parse import urlencode\nfrom zoneinfo import ZoneInfo\n\nimport requests\nfrom requests import Response, Session\nfrom requests.adapters import HTTPAdapter\nfrom urllib3.util.retry import Retry\n\nfrom electricitymap.contrib.lib.models.event_lists import ExchangeList\nfrom electricitymap.contrib.types import ZoneKey\n\nfrom .lib.exceptions import ParserException\nfrom .lib.utils import get_token\n\nTIMEZONE = ZoneInfo(\"Europe/Madrid\")\n\n# Map each exchange to the ID used in the API\nEXCHANGE_ID_MAP = {\n    \"AD->ES\": \"10278\",  # Switch to 10210 when it has data\n    \"ES->MA\": \"10209\",\n}\n\n# Threshold date for ES->MA: from 2022-05-24T10:00:00.000+02:00 onwards, factor is 4 (15 min intervals)\n# Before this date, factor is 1 (hourly intervals)\n# Convert to UTC for comparison: 2022-05-24T10:00:00+02:00 = 2022-05-24T08:00:00+00:00\nES_MA_FACTOR_THRESHOLD = datetime(2022, 5, 24, 8, 0, 0, tzinfo=ZoneInfo(\"UTC\"))\n\n\ndef get_exchange_multiplication_factor(\n    zone_key: ZoneKey, exchange_datetime: datetime\n) -> int:\n    \"\"\"\n    Get the multiplication factor to adjust from MWh to MW.\n    Depends on the time granularity of the API for each request.\n    E.g ES->MA is 4 because the API returns 15 minutes intervals data (15 min = 1/4 of an hour; P=E/t).\n    \"\"\"\n    if zone_key == \"ES->MA\":\n        # From 2022-05-24T10:00:00.000+02:00 onwards, use factor 4 (15 min intervals)\n        # Before this date, use factor 1 (hourly intervals)\n        if exchange_datetime >= ES_MA_FACTOR_THRESHOLD:\n            return 4\n        else:\n            return 1\n    elif zone_key == \"AD->ES\":\n        return 1\n    else:\n        raise ParserException(\n            \"ESIOS.py\",\n            f\"Unknown exchange {zone_key} for multiplication factor.\",\n        )\n\n\ndef format_url(target_datetime: datetime, ID: str):\n    start_date = (target_datetime - timedelta(hours=24)).isoformat()\n    end_date = target_datetime.isoformat()\n    dates = {\"start_date\": start_date, \"end_date\": end_date}\n    query = urlencode(dates)\n    return f\"https://api.esios.ree.es/indicators/{ID}?{query}\"\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    # Get ESIOS token\n    token = get_token(\"ESIOS_TOKEN\")\n\n    # Only create a new session if one wasn't provided\n    # This allows tests to pass in a session with mock adapters\n    ses = session or Session()\n    is_new_session = session is None\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE)\n    # Request headers\n    headers = {\n        \"Content-Type\": \"application/json\",\n        \"Accept\": \"application/json; application/vnd.esios-api-v2+json\",\n        \"x-api-key\": token,\n    }\n\n    zone_key = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    if zone_key not in EXCHANGE_ID_MAP:\n        raise ParserException(\n            \"ESIOS.py\",\n            f\"This parser cannot parse data between {zone_key1} and {zone_key2}.\",\n        )\n    url = format_url(target_datetime, EXCHANGE_ID_MAP[zone_key])\n\n    if is_new_session:\n        # Configure retry strategy for HTTP status code errors\n        retry_strategy = Retry(\n            total=3,\n            backoff_factor=2,\n            status_forcelist=[\n                429,\n                500,\n                502,\n                503,\n                504,\n            ],\n            allowed_methods=[\"GET\"],\n        )\n        adapter = HTTPAdapter(max_retries=retry_strategy)\n        ses.mount(\"https://\", adapter)\n        ses.mount(\"http://\", adapter)\n\n    # Manual retry loop with exponential backoff for connection/timeout errors\n    # This gives us better control over retry behavior for network issue\n    max_retries = 5\n    for attempt in range(max_retries):\n        try:\n            response: Response = ses.get(url, headers=headers, timeout=(30, 30))\n            if response.status_code != 200 or not response.text:\n                raise ParserException(\"ESIOS\", f\"Response code: {response.status_code}\")\n            break\n        except (\n            requests.exceptions.ConnectTimeout,\n            requests.exceptions.ConnectionError,\n            requests.exceptions.Timeout,\n        ) as e:\n            if attempt < max_retries - 1:\n                wait_time = 2**attempt\n                logger.warning(\n                    f\"Connection error fetching ESIOS data (attempt {attempt + 1}/{max_retries}): {e}. \"\n                    f\"Retrying in {wait_time}s...\"\n                )\n                sleep(wait_time)\n            else:\n                logger.error(\n                    f\"Failed to fetch ESIOS data after {max_retries} attempts: {e}\"\n                )\n                raise ParserException(\n                    \"ESIOS\",\n                    f\"Connection failed after {max_retries} retries: {e}\",\n                ) from e\n        except requests.exceptions.RequestException as e:\n            raise ParserException(\"ESIOS\", f\"Request failed: {e}\") from e\n\n    json = response.json()\n    values = json[\"indicator\"][\"values\"]\n    if not values:\n        raise ParserException(\"ESIOS\", \"No values received\")\n    exchanges = ExchangeList(logger)\n\n    for value in values:\n        exchange_datetime = datetime.fromisoformat(\n            value[\"datetime_utc\"].replace(\"Z\", \"+00:00\")\n        )\n\n        # Get last value in datasource\n        # Datasource negative value is exporting, positive value is importing\n        # If Spain is the first zone invert the values to match Electricity Maps schema\n        net_flow = (\n            -value[\"value\"] if zone_key.partition(\"->\")[0] == \"ES\" else value[\"value\"]\n        )\n\n        net_flow *= get_exchange_multiplication_factor(zone_key, exchange_datetime)\n\n        exchanges.append(\n            zoneKey=zone_key,\n            datetime=exchange_datetime,\n            netFlow=net_flow,\n            source=\"api.esios.ree.es\",\n        )\n\n    return exchanges.to_list()\n\n\nif __name__ == \"__main__\":\n    session = Session()\n    print(fetch_exchange(ZoneKey(\"ES\"), ZoneKey(\"MA\"), session))\n    print(\"fetch_exchange(ES, MA)\")\n    print(fetch_exchange(ZoneKey(\"AD\"), ZoneKey(\"ES\"), session))\n    print(\"fetch_exchange(AD, ES)\")\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ESKOM.py",
    "content": "import csv\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom math import nan\nfrom pprint import PrettyPrinter\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\npp = PrettyPrinter(indent=4)\n\nTIMEZONE = ZoneInfo(\"Africa/Johannesburg\")\nSOURCE = \"eskom.co.za\"\n\n# Mapping columns to keys\n# Helpful: https://www.eskom.co.za/dataportal/glossary/\nCOLUMN_MAPPING = {\n    0: \"coal\",  # Thermal_Gen_Excl_Pumping_and_SCO\n    1: \"ignored\",  # Eskom_OCGT_SCO_Pumping             changed to ignored since negative oil is not possible, usually [-6, 0]\n    2: \"ignored\",  # Eskom_Gas_SCO_Pumping              changed to ignored since negative gas is not possible, usually -1 or 0\n    3: \"ignored\",  # Hydro_Water_SCO_Pumping            Probably electricity consumed by the plant itself (even) when not generating power. Can be ignored.\n    4: \"hydro\",  # Pumped_Water_SCO_Pumping\n    5: \"ignored\",  # Thermal_Generation                 sum of 0, 1, 2, 3, 4. Can be ignored.\n    6: \"nuclear\",  # Nuclear_Generation\n    7: \"ignored\",  # International_Imports\n    8: \"oil\",  # Eskom_OCGT_Generation\n    9: \"gas\",  # Eskom_Gas_Generation\n    10: \"oil\",  # Dispatchable_IPP_OCGT\n    11: \"hydro\",  # Hydro_Water_Generation\n    12: \"hydro\",  # Pumped_Water_Generation\n    13: \"ignored\",  # IOS_Excl_ILS_and_MLR              Interruption of Supply. Can be ignored.\n    14: \"ignored\",  # ILS_Usage                         Interruptible Load Shed = companies paid not to consume electricity. Can be ignored.\n    15: \"ignored\",  # Manual_Load_Reduction_MLR         MLS = forced load shedding. Can be ignored.\n    16: \"wind\",  # Wind\n    17: \"solar\",  # PV\n    18: \"solar\",  # CSP\n    19: \"biomass\",  # Other_RE - looking at capacity data and the IEA annual balances, other RE is likely to be biomass\n}\n\n# Ignored values\n# 1, 2, 3, 5, 7, 13, 14, 15\n# TODO:\n# - 7 (international imports) can be further implemented in exchange function.\n\nSTORAGE_IDS = [4, 12]\nPRODUCTION_IDS = [0, 6, 8, 9, 10, 11, 16, 17, 18, 19]\n\n\ndef get_url() -> str:\n    \"\"\"Returns the formatted URL\"\"\"\n    date = datetime.now(timezone.utc)\n    return f\"https://www.eskom.co.za/dataportal/wp-content/uploads/{date.strftime('%Y')}/{date.strftime('%m')}/Station_Build_Up.csv\"\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"ZA\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    if target_datetime is not None:\n        local_target_datetime = target_datetime.astimezone(TIMEZONE)\n        local_one_week_ago = datetime.now(TIMEZONE) - timedelta(days=7)\n\n        if local_target_datetime < local_one_week_ago:\n            raise NotImplementedError(\n                f\"No production data is available for {local_target_datetime}.\"\n            )\n\n    res: Response = session.get(get_url())\n    if not res.ok:\n        raise ParserException(\n            \"ESKOM.py\",\n            f\"Exception when fetching production for {zone_key}: error when calling url={get_url()}\",\n            zone_key=zone_key,\n        )\n\n    csv_data = csv.reader(res.text.splitlines())\n\n    return_list = ProductionBreakdownList(logger)\n\n    for row in csv_data:\n        if row[0] == \"Date_Time_Hour_Beginning\":\n            continue\n\n        returned_datetime = datetime.fromisoformat(row[0]).replace(tzinfo=TIMEZONE)\n\n        returned_production = row[1:]  # First column is datetime\n\n        production = ProductionMix()\n        storage = StorageMix()\n\n        if all(value == \"\" for value in returned_production):\n            logger.warning(\n                f\"Empty data for {returned_datetime} in {zone_key}. Skipping.\"\n            )\n            continue\n        else:\n            for index, prod_data_value in enumerate(returned_production):\n                prod_data_value = float(prod_data_value) if prod_data_value else nan\n                if index in PRODUCTION_IDS:\n                    production.add_value(\n                        COLUMN_MAPPING[index],\n                        prod_data_value,\n                        correct_negative_with_zero=True,\n                    )\n                elif index in STORAGE_IDS:\n                    storage.add_value(COLUMN_MAPPING[index], prod_data_value * -1)\n\n            return_list.append(\n                zoneKey=zone_key,\n                datetime=returned_datetime,\n                production=production,\n                storage=storage,\n                source=SOURCE,\n            )\n\n    return return_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Maps backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    pp.pprint(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ESTADISTICO_UT.py",
    "content": "#!/usr/bin/env python3\n\nimport json\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    ProductionMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\n# This parser gets hourly electricity generation data from ut.com.sv for El Salvador.\n# The 'Termico' category historically only consisted of generation from oil/diesel, but this changed in 2022\n# when a new Liquid Natural Gas power plant came online\n# See: https://ourworldindata.org/grapher/electricity-prod-source-stacked?country=~SLV\n# A better data source that distinguishes between oil and gas can be found in #1733 and #5233\n\n# Thanks to jarek for figuring out how to make the correct POST request to the data url.\n\nDAILY_OPERATION_URL = \"https://estadistico.ut.com.sv/OperacionDiaria.aspx\"\nSOURCE = \"ut.com.sv\"\nZONE_INFO = ZoneInfo(\"America/El_Salvador\")\n\nMODE_MAPPING = {\n    \"Biomasa\": \"biomass\",\n    \"Eólico\": \"wind\",\n    \"Geotérmico\": \"geothermal\",\n    \"Hidroeléctrico\": \"hydro\",\n    \"Solar\": \"solar\",\n    \"Térmico\": \"unknown\",\n    \"Interconexión\": \"exchange\",\n}\n\n\ndef _fetch_data(session: Session, target_datetime: datetime | None = None) -> dict:\n    \"\"\"\n    Fetches production data from a webpage meant for human eyes rather than\n    programmatic access.\n\n    The returned production data is a response meant to be used by a dashboard\n    component on the webpage which needs to be parsed further.\n    \"\"\"\n    # initial GET request to acquire required state data for POST request\n    initial_resp = session.get(DAILY_OPERATION_URL)\n    soup = BeautifulSoup(initial_resp.content, \"html.parser\")\n\n    # define POST request's post data based on\n    if not target_datetime:\n        date_encoded = \"1990-01-01T17%3A32%3A00.000\"  # This means live data - I know it is weird but it works\n    else:\n        date_encoded = (\n            target_datetime.strftime(\"%Y-%m-%d\") + \"T00%3A00%3A00%2E000\"\n        )  # This means historical data\n\n    post_data = {\n        # dynamically set based on initial request's response\n        \"__VIEWSTATE\": soup.find(\"input\", {\"id\": \"__VIEWSTATE\"})[\"value\"],\n        \"__VIEWSTATEGENERATOR\": soup.find(\"input\", {\"id\": \"__VIEWSTATEGENERATOR\"})[\n            \"value\"\n        ],\n        \"__EVENTVALIDATION\": soup.find(\"input\", {\"id\": \"__EVENTVALIDATION\"})[\"value\"],\n        # hardcoded based on mimicing requests seen at\n        # https://estadistico.ut.com.sv/OperacionDiaria.aspx\n        \"__CALLBACKID\": \"ASPxDashboardViewer1\",\n        \"__CALLBACKPARAM\": 'c1:{\"url\":\"DXDD.axd?action=DashboardItemBatchGetAction&dashboardId=DashboardID&parameters=%5B%7B%22name%22%3A%22FechaConsulta%22%2C%22value%22%3A%22'\n        + date_encoded\n        + '%22%2C%22type%22%3A%22System.DateTime%22%2C%22allowMultiselect%22%3Afalse%2C%22selectAll%22%3Afalse%7D%5D&items=%7B%22pivotDashboardItem1%22%3A%7B%7D%2C%22chartDashboardItem1%22%3A%7B%7D%2C%22gridDashboardItem1%22%3A%7B%7D%2C%22gridDashboardItem2%22%3A%7B%7D%2C%22gridDashboardItem3%22%3A%7B%7D%7D\",\"method\":\"GET\",\"data\":\"\"}',\n        \"DXScript\": \"1_9,1_10,1_253,1_21,1_62,1_12,1_13,1_0,1_4,24_364,24_365,24_366,24_367,24_359,24_362,24_363,24_360,24_361,24_479,24_480,25_0,24_368,24_440,24_441,15_0,25_2,25_1,25_3\",\n        \"DXCss\": \"1_72,1_66,24_378,24_379,24_414,24_442,24_443,24_478,15_1\",\n    }\n\n    data_resp = session.post(DAILY_OPERATION_URL, data=post_data)\n\n    # The text response is expected to look like one of the strings:\n    #\n    #     0|/*DX*/({'id':1,'result':'{\"gridDashboardItem3\": {}, \"gridDashboardItem2\": {}}'})\n    #\n    #     0|/*DX*/({'error':{'message':'Callback request failed due to an internal server error.'},'result':null,'id':1})\n    #\n    # Note that:\n    # - <content> is wrapped like 0|/*DX*/(<content>)\n    # - <content> is JSON like, but using single quotes instead of double quotes\n    # - content data can include a result key, and possibly also an error key\n    # - the result value is a JSON string\n    #\n    content_string = data_resp.text[len(\"0|/*DX*/(\") : -len(\")\")]\n    content_json = content_string.replace('\"', r\"\\\"\").replace(\"'\", '\"')\n    content_data = json.loads(content_json)\n    if content_data.get(\"error\"):\n        raise ParserException(\n            parser=\"SV\", message=f\"Error response returned: {content_data['error']}\"\n        )\n    data_resp = json.loads(content_data[\"result\"])\n\n    return data_resp\n\n\ndef _parse_data(data: dict) -> list[dict]:\n    \"\"\"\n    Parses already fetched data meant for use by a dashboard further into a list\n    of dictionaries.\n    \"\"\"\n    production_data = data[\"pivotDashboardItem1\"][\"ItemData\"][\"DataStorageDTO\"]\n\n    # power production data is available for listed modes, days, and hours\n    modes = production_data[\"EncodeMaps\"][\"DataItem2\"]\n    days = production_data[\"EncodeMaps\"][\"DataItem3\"]\n    hours = production_data[\"EncodeMaps\"][\"DataItem1\"]\n\n    # look at power production data for specific mode, day, and hour\n    mode_day_hour_dict = [\n        s\n        for s in production_data[\"Slices\"]\n        if s[\"KeyIds\"] == [\"DataItem2\", \"DataItem3\", \"DataItem1\"]\n    ][0][\"Data\"]\n\n    data_points = []\n    for index_values_json, mwh_production_dict in mode_day_hour_dict.items():\n        # index_values_json can for example look like \"[1,0,1]\", which would\n        # indicate that its associated with the second mode, first day, and\n        # second hour from the available modes, days, and hours\n        index_values = json.loads(index_values_json)\n        mode = modes[index_values[0]]\n        day = days[index_values[1]]\n        hour = hours[index_values[2]]\n\n        mwh_production = mwh_production_dict[\"0\"]\n\n        # TODO: Remove the truncation of sub-seconds when we run on Python 3.11\n        #       or above and fromisoformat can parse such strings\n        day = day[: day.find(\".\")]\n        dt = datetime.fromisoformat(day).replace(hour=int(hour), tzinfo=ZONE_INFO)\n\n        data_points.append(\n            {\n                \"mode\": MODE_MAPPING[mode],\n                \"datetime\": dt,\n                \"value\": mwh_production,\n            }\n        )\n    return data_points\n\n\ndef _process_data(\n    zone_key: ZoneKey, data: list[dict], logger: Logger\n) -> ProductionBreakdownList:\n    # ignore collected exchange data for now\n    data = [d for d in data if d[\"mode\"] != \"exchange\"]\n\n    per_mode_production: dict[str, ProductionBreakdownList] = {}\n    for d in data:\n        mode = d[\"mode\"]\n        if mode not in per_mode_production:\n            per_mode_production[mode] = ProductionBreakdownList(logger)\n\n        mix = ProductionMix()\n        mix.add_value(mode, d[\"value\"])\n        per_mode_production[mode].append(\n            datetime=d[\"datetime\"],\n            production=mix,\n            zoneKey=zone_key,\n            source=SOURCE,\n        )\n\n    return ProductionBreakdownList.merge_production_breakdowns(\n        list(per_mode_production.values()),\n        logger,\n    )\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"SV\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    if session is None:\n        session = Session()\n\n    data = _fetch_data(session, target_datetime)\n    parsed_data = _parse_data(data)\n    production_breakdown = _process_data(zone_key, parsed_data, logger)\n    return production_breakdown.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/FO.py",
    "content": "from datetime import datetime, time, timedelta, timezone\nfrom itertools import groupby\nfrom logging import Logger, getLogger\nfrom operator import itemgetter\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"FO.py\"\nTIMEZONE = ZoneInfo(\"Atlantic/Faroe\")\n\nMAP_PRODUCTION_MODE = {\n    \"Water\": \"hydro\",\n    \"Oil\": \"oil\",\n    \"Wind\": \"wind\",\n    \"Solar\": \"solar\",\n    \"Biogas\": \"biomass\",\n}\n\nMAP_PRODUCTION_MODE_REALTIME_API = {\n    \"Vand\": \"hydro\",\n    \"Olie\": \"oil\",\n    \"Diesel\": \"oil\",\n    \"Vind\": \"wind\",\n    \"Sol\": \"solar\",\n    \"Biogas\": \"biomass\",\n    \"Tidal\": \"unknown\",\n}\n\nMAP_ZONE_KEY_TO_REALTIME_API_DATA_KEY = {\n    \"FO\": \"Sev_E\",\n    \"FO-MI\": \"H_E\",\n    \"FO-SI\": \"S_E\",\n}\n\nVALID_ZONE_KEYS = [ZoneKey(\"FO\"), ZoneKey(\"FO-MI\"), ZoneKey(\"FO-SI\")]\n\n\ndef _fetch_production_historical(\n    zone_key: ZoneKey,\n    session: Session,\n    target_datetime_utc: datetime,\n    logger: Logger,\n) -> ProductionBreakdownList:\n    \"\"\"Fetches production breakdown data from the historical API for the target zone and date of interest.\n\n    Data has hourly granularity and spans 48 h (the target day and the previous one).\n\n    Note that when requesting data for the current day not all data will be available: data for the hour seems to\n    be getting published at hour + 2:25 h, so data for the last 2 or 3 hours will not be available.\n\n    Also note that earliest retrievable target date is 2022/01/01, which might not enough historical data to enable\n    TSA estimations. It is therefore recommended to supplement this API with a realtime API for the time being.\n\n    References:\n        https://www.sev.fo/framleidsla/hagtoel\n    \"\"\"\n\n    # API provides max one day of backlog\n    target_date_utc_to = datetime.combine(\n        target_datetime_utc, time(), tzinfo=timezone.utc\n    )\n    target_date_utc_from = target_date_utc_to - timedelta(days=1)\n\n    # API takes local days as query parameters and returns data for the corresponding interval as UTC\n    target_date_local_to = target_date_utc_to.astimezone(tz=TIMEZONE)\n    target_date_local_from = target_date_utc_from.astimezone(tz=TIMEZONE)\n\n    # during SDT local time is UTC + 0 so day boundaries align\n    # but during DST local time is UTC + 1 so the data for UTC 23:00 is at 00:00 of the next local day, which will thus need to be requested\n    if target_date_local_to.dst():\n        target_date_local_to = target_date_local_to + timedelta(days=1)\n\n    url = f\"https://www.sev.fo/api/elproduction/search?type=item&group=powerplant&from={target_date_local_from.strftime('%Y%m%d')}170000&to={target_date_local_to.strftime('%Y%m%d')}170000\"\n    response = session.get(url)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    hourly_production_for_each_power_plant = response.json()\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n\n    hourly_production_for_each_power_plant_by_hour = groupby(\n        hourly_production_for_each_power_plant, key=itemgetter(\"date\")\n    )\n    for hour, group in hourly_production_for_each_power_plant_by_hour:\n        dt = datetime.fromisoformat(hour).replace(tzinfo=timezone.utc)\n\n        # filter out entries outside of time window of interest (which happens if DST)\n        end_of_day = target_date_utc_to + timedelta(days=1) - timedelta(microseconds=1)\n        if dt < target_date_utc_from or dt > end_of_day:\n            continue\n\n        production_mix = ProductionMix()\n\n        for power_plant_data in group:\n            # filter out entries for areas that are not relevant\n            area = power_plant_data[\"area\"]\n            if (\n                zone_key == ZoneKey(\"FO-MI\")\n                and area != \"Main\"\n                or zone_key == ZoneKey(\"FO-SI\")\n                and area != \"South\"\n            ):\n                continue\n\n            production_mode = MAP_PRODUCTION_MODE[power_plant_data[\"motivepower\"]]\n            production_mix.add_value(production_mode, power_plant_data[\"mwh\"])\n\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            source=\"sev.fo\",\n            production=production_mix,\n        )\n\n    return production_breakdown_list\n\n\ndef _fetch_production_live(\n    zone_key: ZoneKey,\n    session: Session,\n    logger: Logger,\n) -> ProductionBreakdownList:\n    \"\"\"Fetches 'instantaneous' production breakdown data from the live API for the target zone and date of interest.\n\n    Data seems to be getting updated roughly every 2 mn.\n\n    References:\n        https://www.sev.fo/framleidsla/el-orka-i-foroyum\n    \"\"\"\n    url = \"https://www.sev.fo/api/realtimemap/now\"\n    response = session.get(url)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    obj = response.json()\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n    production_mix = ProductionMix()\n    for key, value in obj.items():\n        if \"Sum\" in key or \"Test\" in key or \"VnVand\" in key:\n            # \"VnVand\" is the sum of hydro (Mýrarnar + Fossá + Heygar)\n            continue\n\n        data_key = MAP_ZONE_KEY_TO_REALTIME_API_DATA_KEY[zone_key]\n        if key.endswith(data_key):\n            # E stands for Energy\n            raw_generation_type: str = key.replace(data_key, \"\")\n            generation_type = MAP_PRODUCTION_MODE_REALTIME_API.get(raw_generation_type)\n            if generation_type is None:\n                raise ParserException(\n                    PARSER,\n                    f\"Unknown generation type: {raw_generation_type}\",\n                    zone_key,\n                )\n            # Power (MW)\n            value = float(value.replace(\",\", \".\"))\n            production_mix.add_value(generation_type, value)\n        else:\n            continue\n\n    dt = (\n        datetime.fromisoformat(obj[\"tiden\"])\n        # floor to hourly granularity to match historical API entries\n        .replace(minute=0, second=0, microsecond=0, tzinfo=TIMEZONE)\n        # cast to UTC just to keep consistent with historical API entries\n        .astimezone(timezone.utc)\n    )\n\n    production_breakdown_list.append(\n        zoneKey=zone_key,\n        datetime=dt,\n        source=\"sev.fo\",\n        production=production_mix,\n    )\n\n    return production_breakdown_list\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"FO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    if zone_key not in VALID_ZONE_KEYS:\n        raise ParserException(\n            PARSER,\n            f\"This parser cannot retrieve data for zone {zone_key!r}\",\n        )\n\n    now = datetime.now(timezone.utc)\n    target_datetime = (\n        now if target_datetime is None else target_datetime.astimezone(timezone.utc)\n    )\n\n    session = session or Session()\n\n    historical_production_breakdown_list = _fetch_production_historical(\n        zone_key=zone_key,\n        session=session,\n        target_datetime_utc=target_datetime,\n        logger=logger,\n    )\n\n    # historical API has a ~2:25h delay, so supplement with realtime API data if applicable\n    # note that this will still leave a small gap, but at least it will provide a realtime signal\n    if target_datetime > historical_production_breakdown_list.events[-1].datetime:\n        live_production_breakdown_list = _fetch_production_live(\n            zone_key=zone_key,\n            session=session,\n            logger=logger,\n        )\n    else:\n        live_production_breakdown_list = ProductionBreakdownList(logger)\n\n    # favour historical data on merge as realtime data is not representative of hourly production and / or might be stale\n    return ProductionBreakdownList.update_production_breakdowns(\n        live_production_breakdown_list,\n        historical_production_breakdown_list,\n        logger=logger,\n    ).to_list()\n\n\nif __name__ == \"__main__\":\n    for zone_key in VALID_ZONE_KEYS:\n        print(fetch_production(zone_key))\n        print(fetch_production(zone_key, target_datetime=datetime(2023, 7, 16, 12)))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/FR.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.utils import get_token\nfrom electricitymap.contrib.types import ZoneKey\n\nAPI_ENDPOINT = \"https://opendata.reseaux-energies.fr/api/records/1.0/search/\"\n\nMAP_GENERATION = {\n    \"nucleaire\": \"nuclear\",\n    \"charbon\": \"coal\",\n    \"gaz\": \"gas\",\n    \"fioul\": \"oil\",\n    \"eolien\": \"wind\",\n    \"solaire\": \"solar\",\n    \"bioenergies\": \"biomass\",\n    \"hydraulique_fil_eau_eclusee\": \"hydro\",\n    \"hydraulique_lacs\": \"hydro\",\n    \"hydraulique_step_turbinage\": \"hydro_storage\",\n    \"pompage\": \"hydro_storage\",\n    \"stockage_batterie\": \"battery_storage\",\n    \"destockage_batterie\": \"battery_storage\",\n}\n\nSTORAGE_MODES = [\"hydro_storage\", \"battery_storage\"]\nDATASET_REAL_TIME = \"eco2mix-national-tr\"  # API called is Données éCO2mix nationales en temps réel if no consolidated data is available\nDATASET_CONSOLIDATED = \"eco2mix-national-cons-def\"  # API called is Données éCO2mix nationales consolidées et définitives\n\n\nDELTA_15 = timedelta(minutes=15)\nTZ = ZoneInfo(\"Europe/Paris\")\nSOURCE = \"opendata.reseaux-energies.fr\"\n\n\ndef get_data(session: Session, target_datetime: datetime) -> pd.DataFrame:\n    \"\"\"Returns data from the consolidated data endpoint if it is available, otherwise returns data from the real-time data endpoint.\"\"\"\n    df_consolidated = request_data(DATASET_CONSOLIDATED, session, target_datetime)\n    if df_consolidated.empty:\n        df_real_time = request_data(DATASET_REAL_TIME, session, target_datetime)\n        if df_real_time.empty:\n            return pd.DataFrame()\n        else:\n            return df_real_time\n    else:\n        return df_consolidated\n\n\ndef request_data(\n    dataset: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n) -> pd.DataFrame:\n    \"\"\"Returns a DataFrame with the data from the API.\"\"\"\n    if target_datetime:\n        target_datetime_localised = target_datetime.replace(tzinfo=TZ)\n    else:\n        target_datetime_localised = datetime.now(tz=TZ)\n\n    # setup request\n    r = session or Session()\n    formatted_from = (target_datetime_localised - timedelta(days=1)).strftime(\n        \"%Y-%m-%dT%H:%M\"\n    )\n    formatted_to = target_datetime_localised.strftime(\"%Y-%m-%dT%H:%M\")\n\n    params = {\n        \"dataset\": dataset,\n        \"q\": f\"date_heure >= {formatted_from} AND date_heure <= {formatted_to}\",\n        \"timezone\": \"Europe/Paris\",\n        \"rows\": 100,\n    }\n\n    params[\"apikey\"] = get_token(\"RESEAUX_ENERGIES_TOKEN\")\n    # make request and create dataframe with response\n    response = r.get(API_ENDPOINT, params=params)\n    if not response.ok:\n        raise ValueError(\n            f\"Failed to fetch data from {API_ENDPOINT}. Status code: {response.status_code}\"\n        )\n    data = response.json()\n    data = [d[\"fields\"] for d in data[\"records\"]]\n    df = pd.DataFrame(data)\n    return df\n\n\ndef reindex_data(df_to_reindex: pd.DataFrame) -> pd.DataFrame:\n    \"\"\"Reindex data to get averaged half-hourly values instead of quart-hourly values. This is done to ensure consistency between the historical set (1/2 hourly granularity) and the real-time set (1/4 hourly granularity)\"\"\"\n    df_to_reindex = df_to_reindex.copy()\n    # Round dates to the lower bound with 30 minutes granularity\n    df_to_reindex[\"datetime\"] = pd.to_datetime(\n        df_to_reindex[\"date_heure\"]\n    ).dt.tz_convert(TZ)\n    df_to_reindex[\"datetime_30\"] = df_to_reindex[\"datetime\"].apply(\n        lambda x: x if x.minute in [0, 30] else x - DELTA_15\n    )\n\n    # Average data points corresponding to the same time with 30 min granularity\n    df_reindexed = (\n        df_to_reindex.groupby(\"datetime_30\").mean(numeric_only=True).reset_index()\n    )\n    df_reindexed = df_reindexed.rename(columns={\"datetime_30\": \"date_heure\"})\n    return df_reindexed.set_index(\"date_heure\")\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"FR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    df_production = get_data(session, target_datetime)\n    # filter out desired columns and convert values to float\n    value_columns = list(MAP_GENERATION.keys())\n    missing_fuels = [v for v in value_columns if v not in df_production.columns]\n    present_fuels = [v for v in value_columns if v in df_production.columns]\n    if len(missing_fuels) == len(value_columns):\n        logger.warning(\"No fuels present in the API response\")\n        return []\n    elif len(missing_fuels) > 0:\n        mf_str = \", \".join(missing_fuels)\n        logger.warning(f\"Fuels [{mf_str}] are not present in the API response\")\n\n    df_production = df_production.loc[:, [\"date_heure\"] + present_fuels]\n    df_production[present_fuels] = df_production[present_fuels].astype(float)\n\n    # reindex df_production to get 1/2 hourly values\n    df_production_reindexed = reindex_data(df_production)\n    df_production_reindexed = df_production_reindexed.dropna(how=\"any\", axis=0)\n    df_production_reindexed = df_production_reindexed.rename(columns=MAP_GENERATION)\n    df_production_reindexed = df_production_reindexed.groupby(\n        df_production_reindexed.columns, axis=1\n    ).sum(\n        numeric_only=True,\n    )\n\n    production_mixes = ProductionBreakdownList(logger)\n    for idx, row in df_production_reindexed.iterrows():\n        productionMix = ProductionMix()\n        storageMix = StorageMix()\n        for mode in row.index:\n            if mode in STORAGE_MODES:\n                storageMix.add_value(mode.split(\"_\")[0], -1 * row[mode])\n            else:\n                productionMix.add_value(mode, row[mode])\n        production_mixes.append(\n            zoneKey=zone_key,\n            production=productionMix,\n            storage=storageMix,\n            datetime=idx.to_pydatetime(),\n            source=SOURCE,\n        )\n    return production_mixes.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"FR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    df_consumption = get_data(session, target_datetime)\n    df_consumption = df_consumption[[\"date_heure\", \"consommation\"]].dropna()\n\n    # reindex df_consumption to get 1/2 hourly values\n    df_consumption_reindexed = reindex_data(df_consumption)\n    consumption_list = TotalConsumptionList(logger)\n    for row in df_consumption_reindexed.itertuples():\n        consumption_list.append(\n            zoneKey=zone_key,\n            consumption=row.consommation,\n            datetime=row.Index.to_pydatetime(),\n            source=SOURCE,\n        )\n\n    return consumption_list.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/FR_O.py",
    "content": "from datetime import datetime, timedelta\nfrom logging import getLogger\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    PriceList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nfrom .lib.config import refetch_frequency\nfrom .lib.exceptions import ParserException\n\nDOMAIN_MAPPING = {\n    \"FR-COR\": \"https://opendata-corse.edf.fr\",\n    \"RE\": \"https://opendata-reunion.edf.fr\",\n    \"GF\": \"https://opendata-guyane.edf.fr\",\n    \"MQ\": \"https://opendata-martinique.edf.fr\",\n    \"GP\": \"https://opendata-guadeloupe.edf.fr\",\n}\n\nLIVE_DATASETS = {\n    \"FR-COR\": \"production-delectricite-par-filiere-en-temps-reel\",\n    \"GP\": \"mix-temps-reel-guadeloupe\",\n    \"RE\": \"prod-electricite-temps-reel\",\n    \"GF\": \"production-d-electricite-par-filiere-en-temps-reel\",\n    \"MQ\": \"production-delectricite-par-filiere-en-temps-reel\",\n}\n\nHISTORICAL_MAPPING = {\n    \"FR-COR\": \"Corse\",\n    \"RE\": \"Réunion\",\n    \"GF\": \"Guyane\",\n    \"MQ\": \"Martinique\",\n    \"GP\": \"Guadeloupe\",\n}\n\nAPI_PARAMETER_GROUPS = {\n    \"production\": {\n        \"RE\": {\n            \"bioenergies\": \"biomass\",\n            \"charbon\": \"biomass\",\n            \"diesel\": \"biomass\",\n            \"eolien\": \"wind\",\n            \"hydraulique\": \"hydro\",\n            \"photovoltaique\": \"solar\",\n            \"turbines_combustion\": \"gas\",\n        },\n        \"GP\": {\n            \"charbon\": \"coal\",\n            \"bioenergies\": \"biomass\",\n            \"diesel\": \"oil\",\n            \"hydraulique\": \"hydro\",\n            \"photovoltaique\": \"solar\",\n            \"eolien\": \"wind\",\n            \"turbines_combustion\": \"gas\",\n            \"geothermie\": \"geothermal\",\n        },\n        \"GF\": {\n            \"bioenergies\": \"biomass\",\n            \"hydraulique\": \"hydro\",\n            \"moteur_diesel\": \"oil\",\n            \"photovoltaique\": \"solar\",\n            \"tac\": \"oil\",\n        },\n        \"MQ\": {\n            \"bioenergies\": \"biomass\",\n            \"eolien\": \"wind\",\n            \"hydraulique\": \"hydro\",\n            \"moteurs_diesels\": \"oil\",\n            \"turbines_combustion\": \"gas\",\n        },\n        \"FR-COR\": {\n            \"moteur_diesel\": \"oil\",\n            \"tac\": \"gas\",\n            \"hydraulique\": \"hydro\",\n            \"micro_hydro\": \"hydro\",\n            \"photovoltaique\": \"solar\",\n            \"eolien\": \"wind\",\n            \"bioenergies\": \"biomass\",\n        },\n    },\n    \"storage\": {\"battery\": [\"solde_stockage\", \"stockage\"]},\n    \"price\": {\n        \"price\": [\"cout_moyen_de_production_eur_mwh\"],\n    },\n}\n\nSTORAGE_MAPPING = {\n    API_TYPE: data_type\n    for key in [\"storage\"]\n    for data_type, groups in API_PARAMETER_GROUPS[key].items()\n    for API_TYPE in groups\n}\n\nPRICE_MAPPING = {\n    API_TYPE: data_type\n    for key in [\"price\"]\n    for data_type, groups in API_PARAMETER_GROUPS[key].items()\n    for API_TYPE in groups\n}\n\nIGNORED_VALUES = [\"jour\", \"total\", \"statut\", \"date\", \"heure\", \"liaisons\", \"tac\"]\n\n\ndef generate_url(zone_key, target_datetime):\n    if target_datetime:\n        return \"https://opendata.edf.fr/api/explore/v2.1/catalog/datasets/courbe-de-charge-de-la-production-delectricite-par-filiere/exports/json\"\n    return f\"{DOMAIN_MAPPING[zone_key]}/api/explore/v2.1/catalog/datasets/{LIVE_DATASETS[zone_key]}/exports/json\"\n\n\ndef fetch_data(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n) -> tuple[list, str, str]:\n    ses = session or Session()\n\n    if target_datetime is None and zone_key not in LIVE_DATASETS:\n        raise ParserException(\n            \"FR_O.py\",\n            f\"Live data not implemented for {zone_key} in this parser.\",\n            zone_key,\n        )\n\n    target_date = target_datetime.strftime(\"%Y-%m-%d\") if target_datetime else None\n    past_date = (\n        (target_datetime - timedelta(days=3)).strftime(\"%Y-%m-%d\")\n        if target_datetime\n        else None\n    )\n\n    URL_QUERIES: dict[str, str | None] = (\n        {\n            \"timezone\": \"UTC\",\n            \"order_by\": \"date_heure\",\n            \"where\": f\"date_heure >= date'{past_date}' AND date_heure <= date'{target_date}'\",\n            \"refine\": f\"territoire:{HISTORICAL_MAPPING[zone_key]}\",\n        }\n        if target_datetime\n        else {\n            \"timezone\": \"UTC\",\n            \"order_by\": \"date\",\n        }\n    )\n\n    url = generate_url(zone_key, target_datetime)\n    response: Response = ses.get(url, params=URL_QUERIES)\n    data: dict | list | None = response.json()\n    if data == []:\n        raise ParserException(\n            \"FR_O.py\",\n            f\"No data available for {zone_key} for {target_datetime.strftime('%Y')}\"\n            if target_datetime\n            else f\"No live data available for {zone_key}.\",\n            zone_key,\n        )\n    elif isinstance(data, dict):\n        if data.get(\"errorcode\") == \"10002\":\n            raise ParserException(\n                \"FR_O.py\",\n                f\"Rate limit exceeded. Please try again later after: {data.get('reset_time')}\",\n            )\n        elif data.get(\"error_code\") == \"ODSQLError\":\n            raise ParserException(\n                \"FR_O.py\",\n                \"Query malformed. Please check the parameters. If this was previously working there has likely been a change in the API.\",\n            )\n    if not isinstance(data, list):\n        raise ParserException(\n            \"FR_O.py\",\n            f\"Unexpected data format for {zone_key} for {target_datetime}\"\n            if target_datetime\n            else f\"Unexpected data format for {zone_key}.\",\n            zone_key,\n        )\n    source = url.split(\"//\")[1].split(\"/\")[0]\n    return data, \"date_heure\" if target_datetime else \"date\", source\n\n\n@refetch_frequency(timedelta(hours=72))\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger=getLogger(__name__),\n):\n    production_objects, date_string, source = fetch_data(\n        zone_key, session, target_datetime\n    )\n\n    production_breakdown_list = ProductionBreakdownList(logger=logger)\n    for production_object in production_objects:\n        production = ProductionMix()\n        storage = StorageMix()\n        for mode_key in production_object:\n            if mode_key in API_PARAMETER_GROUPS[\"production\"][zone_key]:\n                production.add_value(\n                    API_PARAMETER_GROUPS[\"production\"][zone_key][mode_key],\n                    production_object[mode_key],\n                    correct_negative_with_zero=True,\n                )\n            elif mode_key in STORAGE_MAPPING:\n                storage.add_value(\n                    STORAGE_MAPPING[mode_key], -production_object[mode_key]\n                )\n            elif mode_key in IGNORED_VALUES:\n                pass\n            else:\n                logger.warning(\n                    f\"Unknown mode_key: '{mode_key}' encountered for {zone_key}.\"\n                )\n\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(production_object[date_string]),\n            production=production,\n            storage=storage,\n            source=source,\n            sourceType=EventSourceType.estimated\n            if production_object.get(\"statut\") == \"Estimé\"\n            else EventSourceType.measured,\n        )\n    return production_breakdown_list.to_list()\n\n\n@refetch_frequency(timedelta(hours=72))\ndef fetch_price(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger=getLogger(__name__),\n):\n    data_objects, date_string, source = fetch_data(zone_key, session, target_datetime)\n\n    price_list = PriceList(logger=logger)\n    for data_object in data_objects:\n        price: float | int | None = None\n        for mode_key in data_object:\n            if mode_key in PRICE_MAPPING:\n                price = data_object[mode_key]\n                break\n        if price is not None:\n            price_list.append(\n                zoneKey=zone_key,\n                currency=\"EUR\",\n                datetime=datetime.fromisoformat(data_object[date_string]),\n                source=source,\n                price=price,\n            )\n    return price_list.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/GB.py",
    "content": "\"\"\"\nPrice parser that uses the RTE-FRANCE API\nProduction parser that uses the NESO and Elexon APIs\nThe storage values are computed using the Elexon API, aggregating the data per unit. To debug this use you can use:\n\nPRINT_DETAILS=hydro_storage uv run test_parser GB     -> which prints the hydro storage details, also including the minute details\nPRINT_DETAILS=battery_storage uv run test_parser GB   -> which prints the battery storage details, excluding the minute details, since there are too many battery units to print the minute details for each one\n\n\"\"\"\n\nimport os\nimport xml.etree.ElementTree as ET\nfrom datetime import datetime, timedelta, timezone\nfrom io import BytesIO\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom openpyxl import load_workbook\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    PriceList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"GB.py\"\nTIMEZONE = ZoneInfo(\"Europe/London\")\nZONE_KEY = ZoneKey(\"GB\")\n\nNESO_API = \"https://api.neso.energy/api/3/action/datastore_search_sql\"\nNESO_GENERATION_DATASET_ID = \"f93d1835-75bc-43e5-84ad-12472b180a98\"\n\nELEXON_BMU_UNITS = \"https://data.elexon.co.uk/bmrs/api/v1/reference/bmunits/all\"\nELEXON_PN_STREAM = \"https://data.elexon.co.uk/bmrs/api/v1/datasets/PN/stream\"\nELEXON_MELS_STREAM = \"https://data.elexon.co.uk/bmrs/api/v1/datasets/MELS/stream\"\nELEXON_MILS_STREAM = \"https://data.elexon.co.uk/bmrs/api/v1/datasets/MILS/stream\"\nELEXON_BOALF_STREAM = \"https://data.elexon.co.uk/bmrs/api/v1/datasets/BOALF/stream\"\nELEXON_BMU_FUEL_TYPE_URL = (\n    \"https://www.elexon.co.uk/documents/data/operational-data/bmu-fuel-type/\"\n)\n\n\nNESO_TO_PRODUCTION_MIX_MAPPING = {\n    \"BIOMASS\": \"biomass\",\n    \"COAL\": \"coal\",\n    \"GAS\": \"gas\",\n    \"HYDRO\": \"hydro\",\n    \"NUCLEAR\": \"nuclear\",\n    \"SOLAR\": \"solar\",\n    \"WIND\": \"wind\",\n    \"WIND_EMB\": \"wind\",\n    \"OTHER\": \"unknown\",\n}\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_price(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the power price per MWh of a given country.\n\n    This function will return one-hourly prices for the requested day, and previous one. For live data, it will also\n    return prices from day-ahead market data.\n    \"\"\"\n\n    now = datetime.now(timezone.utc)\n    target_datetime = (\n        now if target_datetime is None else target_datetime.astimezone(timezone.utc)\n    )\n    is_today = target_datetime.date() == now.date()\n\n    # API works in UTC timestamps, and allows fetching day-ahead market data\n    num_backlog_days = 1\n    day_start = (target_datetime - timedelta(days=num_backlog_days)).strftime(\n        \"%d/%m/%Y\"\n    )\n    day_end = (target_datetime + timedelta(days=1 if is_today else 0)).strftime(\n        \"%d/%m/%Y\"\n    )\n    url = f\"http://eco2mix.rte-france.com/curves/getDonneesMarche?dateDeb={day_start}&dateFin={day_end}&mode=NORM\"\n\n    session = session or Session()\n    response = session.get(url)\n\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching price error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    xml_tree = ET.fromstring(response.content)\n\n    price_list = PriceList(logger=logger)\n    for daily_market_data in xml_tree.iterfind(\"donneesMarche\"):\n        date = daily_market_data.get(\"date\")\n        if date is None:\n            raise ParserException(\n                PARSER,\n                \"Exception when parsing price API response: missing 'date' for daily market data.\",\n                zone_key,\n            )\n        day = datetime.strptime(date, \"%Y-%m-%d\").replace(tzinfo=timezone.utc)\n\n        for daily_zone_data in daily_market_data:\n            zone_code = daily_zone_data.get(\"perimetre\")\n\n            # Data for Germany / Luxembourg is not set / reported as aggregate region\n            if zone_code in {\"DE\", \"DL\"}:\n                continue\n\n            if zone_key != zone_code:\n                continue\n\n            granularity = daily_zone_data.get(\"granularite\")\n            if granularity != \"Global\":\n                continue\n\n            for value in daily_zone_data:\n                price = (\n                    None\n                    if value.text == \"ND\"\n                    else float(value.text)\n                    if value.text is not None\n                    else None\n                )\n                if price is None:\n                    continue\n\n                period_number = int(value.attrib[\"periode\"])\n                dt = day + timedelta(hours=period_number)\n\n                price_list.append(\n                    zoneKey=zone_key,\n                    datetime=dt,\n                    source=\"rte-france.com\",\n                    price=price,\n                    currency=\"EUR\",\n                    # Can use EventSourceType.measured even for dt > now entries as price is set on day-ahead market\n                    sourceType=EventSourceType.measured,\n                )\n\n    return price_list.to_list()\n\n\n@refetch_frequency(timedelta(hours=72))\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict] | dict:\n    session = session or Session()\n\n    if target_datetime is None:\n        start_datetime = datetime.now(tz=ZoneInfo(\"UTC\")) - timedelta(hours=72)\n        end_datetime = datetime.now(tz=ZoneInfo(\"UTC\"))\n        sql_query = f\"\"\"SELECT * FROM \"{NESO_GENERATION_DATASET_ID}\" WHERE \"DATETIME\" >= '{start_datetime.strftime(\"%Y-%m-%d\")}' ORDER BY \"DATETIME\" ASC\"\"\"\n\n    elif target_datetime.astimezone(timezone.utc) > datetime(\n        year=2009, month=1, day=1, tzinfo=timezone.utc\n    ):\n        target_datetime = target_datetime.astimezone(ZoneInfo(\"Europe/London\"))\n        start_datetime = target_datetime - timedelta(hours=48)\n        end_datetime = target_datetime + timedelta(hours=24)\n\n        sql_query = f\"\"\"SELECT * FROM \"{NESO_GENERATION_DATASET_ID}\" WHERE \"DATETIME\" >= '{start_datetime.strftime(\"%Y-%m-%d\")}' AND \"DATETIME\" <= '{end_datetime.strftime(\"%Y-%m-%d\")}' ORDER BY \"DATETIME\" ASC\"\"\"\n    else:\n        raise ParserException(\n            \"GB.py\",\n            \"This parser is not yet able to parse dates before 2009-01-01\",\n            zone_key,\n        )\n\n    params = {\"sql\": sql_query}\n\n    res: Response = session.get(NESO_API, params=params)\n    if not res.status_code == 200:\n        raise ParserException(\n            \"GB.py\",\n            f\"Exception when fetching production error code: {res.status_code}: {res.text}\",\n            zone_key,\n        )\n\n    obj = res.json()[\"result\"][\"records\"]\n\n    rows_to_process: list[tuple[datetime, dict]] = []\n    for row in obj:\n        ts = datetime.fromisoformat(row[\"DATETIME\"]).replace(tzinfo=ZoneInfo(\"UTC\"))\n        if ts < start_datetime:\n            continue\n        if ts > end_datetime:\n            break\n        rows_to_process.append((ts, row))\n\n    hydro_units = get_hydro_storage_units(session, zone_key)\n    battery_units = get_battery_units(session, zone_key)\n\n    pn_df, mels_df, mils_df, boalf_df = _fetch_all_storage_data(\n        session, hydro_units + battery_units, start_datetime, end_datetime\n    )\n\n    storage_lookup = _build_storage_lookup(\n        pn_df, mels_df, mils_df, boalf_df, rows_to_process\n    )\n\n    production_list = ProductionBreakdownList(logger=logger)\n    for period_start, row in rows_to_process:\n        production_mix = ProductionMix()\n        for neso_key, emaps_key in NESO_TO_PRODUCTION_MIX_MAPPING.items():\n            production_mix.add_value(emaps_key, float(row[neso_key]))\n\n        pn_by_unit, mels_by_unit, mils_by_unit, boalf_by_unit, period_end = (\n            storage_lookup[period_start]\n        )\n        storage_mix = _compute_storage_mix(\n            period_start,\n            period_end,\n            hydro_units,\n            battery_units,\n            pn_by_unit,\n            mels_by_unit,\n            mils_by_unit,\n            boalf_by_unit,\n        )\n\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=period_start,\n            production=production_mix,\n            storage=storage_mix,\n            source=\"neso.energy, elexon.co.uk\",\n        )\n\n    return production_list.to_list()\n\n\ndef _fetch_all_storage_data(\n    session: Session,\n    units: list[str],\n    time_from: datetime,\n    time_to: datetime,\n) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame, pd.DataFrame]:\n    \"\"\"Fetch PN, MELS, MILS, and BOALF for all units over a time range.\n\n    Makes 4 API calls total — one per dataset — covering the entire production window.\n\n    Args:\n        time_from: Start of the production window. PN/MELS/MILS are fetched\n            from 30 minutes before this to catch records whose timeFrom fell\n            in the preceding period. BOALF is fetched from 4 hours before to\n            catch long-running acceptances.\n        time_to: End of the production window (inclusive).\n\n    Returns:\n        Four DataFrames (pn, mels, mils, boalf) with pre-parsed columns:\n        unit, time_from, time_to, level_from, acceptance_number.\n    \"\"\"\n    physical_params = {\n        \"from\": (time_from - timedelta(minutes=30)).strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n        \"to\": time_to.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n        \"bmUnit\": units,\n    }\n    boalf_params = {\n        \"from\": (time_from - timedelta(hours=4)).strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n        \"to\": time_to.strftime(\"%Y-%m-%dT%H:%M:%SZ\"),\n        \"bmUnit\": units,\n    }\n\n    pn_rows = _fetch_storage_dataset(session, physical_params, ELEXON_PN_STREAM)\n    mels_rows = _fetch_storage_dataset(session, physical_params, ELEXON_MELS_STREAM)\n    mils_rows = _fetch_storage_dataset(session, physical_params, ELEXON_MILS_STREAM)\n    boalf_rows = _fetch_storage_dataset(session, boalf_params, ELEXON_BOALF_STREAM)\n\n    return (\n        _rows_to_df(pn_rows),\n        _rows_to_df(mels_rows),\n        _rows_to_df(mils_rows),\n        _rows_to_df(boalf_rows),\n    )\n\n\ndef _rows_to_df(rows: list[dict]) -> pd.DataFrame:\n    \"\"\"Convert raw Elexon API rows to a DataFrame with pre-parsed columns.\n\n    Parses timeFrom/timeTo once via vectorised pd.to_datetime so downstream\n    code never re-parses datetime strings.\n    \"\"\"\n    if not rows:\n        return pd.DataFrame(\n            columns=[\"unit\", \"time_from\", \"time_to\", \"level_from\", \"acceptance_number\"]\n        )\n    df = pd.DataFrame(rows)\n    df[\"time_from\"] = pd.to_datetime(df[\"timeFrom\"]).dt.tz_convert(\"UTC\")\n    df[\"time_to\"] = pd.to_datetime(df[\"timeTo\"]).dt.tz_convert(\"UTC\")\n    df[\"unit\"] = (\n        df[\"nationalGridBmUnit\"] if \"nationalGridBmUnit\" in df.columns else pd.NA\n    )\n    df[\"level_from\"] = (\n        pd.to_numeric(df[\"levelFrom\"], errors=\"coerce\")\n        if \"levelFrom\" in df.columns\n        else float(\"nan\")\n    )\n    df[\"acceptance_number\"] = (\n        df[\"acceptanceNumber\"].fillna(0).astype(int)\n        if \"acceptanceNumber\" in df.columns\n        else 0\n    )\n    return df[[\"unit\", \"time_from\", \"time_to\", \"level_from\", \"acceptance_number\"]]\n\n\n_UnitRecords = dict[str, list[dict]]\n_StorageLookup = dict[\n    datetime,\n    tuple[_UnitRecords, _UnitRecords, _UnitRecords, _UnitRecords, datetime],\n]\n\n\ndef _build_storage_lookup(\n    pn_df: pd.DataFrame,\n    mels_df: pd.DataFrame,\n    mils_df: pd.DataFrame,\n    boalf_df: pd.DataFrame,\n    rows_to_process: list[tuple[datetime, datetime]],\n) -> _StorageLookup:\n    \"\"\"Pre-filter and group storage data for each timestamp's window.\n\n    For each timestamp performs a vectorised boolean filter on the DataFrames\n    (datetimes already parsed), then groups the matching rows by unit.\n    The returned records have pre-parsed datetime fields so per-minute lookups\n    require only simple comparisons.\n    \"\"\"\n    lookup: _StorageLookup = {}\n\n    timestamps = [ts for ts, _ in rows_to_process]\n    period_duration = timestamps[1] - timestamps[0] if len(timestamps) >= 2 else None\n\n    for i, period_start in enumerate(timestamps):\n        if i + 1 < len(timestamps):\n            period_end = timestamps[i + 1]\n        elif period_duration is not None:\n            period_end = period_start + period_duration\n        else:\n            raise ParserException(\n                PARSER,\n                \"Cannot determine settlement period duration: only one NESO timestamp returned.\",\n                ZONE_KEY,\n            )\n        ps_pd = pd.Timestamp(period_start)\n        pe_pd = pd.Timestamp(period_end)\n\n        def filter_and_group(\n            df: pd.DataFrame, _ts: pd.Timestamp, _pe: pd.Timestamp\n        ) -> _UnitRecords:\n            window = df[(df[\"time_from\"] < _pe) & (df[\"time_to\"] > _ts)]\n            grouped: _UnitRecords = {}\n            for row in window.itertuples(index=False):\n                unit = row.unit\n                if not isinstance(unit, str):\n                    continue\n                grouped.setdefault(unit, []).append(\n                    {\n                        \"time_from\": row.time_from.to_pydatetime(),\n                        \"time_to\": row.time_to.to_pydatetime(),\n                        \"level_from\": (\n                            None if pd.isna(row.level_from) else float(row.level_from)\n                        ),\n                        \"acceptance_number\": int(row.acceptance_number),\n                    }\n                )\n            return grouped\n\n        lookup[period_start] = (\n            filter_and_group(pn_df, ps_pd, pe_pd),\n            filter_and_group(mels_df, ps_pd, pe_pd),\n            filter_and_group(mils_df, ps_pd, pe_pd),\n            filter_and_group(boalf_df, ps_pd, pe_pd),\n            period_end,\n        )\n\n    return lookup\n\n\ndef _compute_storage_mix(\n    period_start: datetime,\n    period_end: datetime,\n    hydro_units: list[str],\n    battery_units: list[str],\n    pn_by_unit: _UnitRecords,\n    mels_by_unit: _UnitRecords,\n    mils_by_unit: _UnitRecords,\n    boalf_by_unit: _UnitRecords,\n) -> StorageMix:\n    \"\"\"Compute hydro and battery storage mixes for a given timestamp from pre-fetched data.\"\"\"\n    debug = os.environ.get(\"PRINT_DETAILS\", \"\").lower()\n    storage_mix = StorageMix()\n    period_minutes = int((period_end - period_start).total_seconds() / 60)\n\n    hydro_storage = _compute_storage_for_units(\n        hydro_units,\n        period_start,\n        pn_by_unit,\n        mels_by_unit,\n        mils_by_unit,\n        boalf_by_unit,\n        period_minutes,\n        print_details=debug == \"hydro_storage\",\n        print_minute_details=debug == \"hydro_storage\",\n    )\n    storage_mix.add_value(\"hydro\", -hydro_storage)\n\n    battery_storage = _compute_storage_for_units(\n        battery_units,\n        period_start,\n        pn_by_unit,\n        mels_by_unit,\n        mils_by_unit,\n        boalf_by_unit,\n        period_minutes,\n        print_details=debug == \"battery_storage\",\n        print_minute_details=False,\n    )\n    storage_mix.add_value(\"battery\", -battery_storage)\n    return storage_mix\n\n\ndef _compute_storage_for_units(\n    units: list[str],\n    period_start: datetime,\n    pn_by_unit: _UnitRecords,\n    mels_by_unit: _UnitRecords,\n    mils_by_unit: _UnitRecords,\n    boalf_by_unit: _UnitRecords,\n    period_minutes: int,\n    print_details: bool = False,\n    print_minute_details: bool = False,\n) -> float:\n    \"\"\"Compute the aggregate storage MW for a list of units at a given timestamp.\n\n    Uses pre-filtered, pre-parsed records from _build_storage_lookup.\n    \"\"\"\n    if print_details:\n        total_boalf = sum(len(boalf_by_unit.get(u, [])) for u in units)\n        total_pn = sum(len(pn_by_unit.get(u, [])) for u in units)\n        print(\n            f\"\\n  [{period_start.strftime('%Y-%m-%d %H:%M')}] {len(units)} units, \"\n            f\"pre-fetched: {total_boalf} BOALF, {total_pn} PN rows\"\n        )\n\n    total_storage = 0.0\n    for unit in units:\n        if print_details:\n            n_boalf = len(boalf_by_unit.get(unit, []))\n            n_pn = len(pn_by_unit.get(unit, []))\n            print(f\"  {unit}: {n_boalf} BOALF recs, {n_pn} PN recs\", end=\"\")\n        unit_mw = _compute_unit_storage_mw(\n            boalf_records=boalf_by_unit.get(unit, []),\n            pn_records=pn_by_unit.get(unit, []),\n            mels_records=mels_by_unit.get(unit, []),\n            mils_records=mils_by_unit.get(unit, []),\n            period_start=period_start,\n            period_minutes=period_minutes,\n            print_details=print_details,\n            print_minute_details=print_minute_details,\n        )\n        total_storage += unit_mw\n\n    if print_details:\n        print(f\"  TOTAL: {total_storage:.1f} MW\")\n    return total_storage\n\n\ndef _extract_data_rows(payload: dict | list) -> list[dict]:\n    if isinstance(payload, dict):\n        data = payload.get(\"data\")\n        return data if isinstance(data, list) else []\n    return payload if isinstance(payload, list) else []\n\n\ndef _get_boalf_value_at_minute(\n    records: list[dict], minute_dt: datetime\n) -> float | None:\n    \"\"\"Determine the BOALF MW level for a single unit at a specific minute.\n\n    BOALF (Bid-Offer Acceptance Level Flagged) records represent instructions\n    from the System Operator to a generation/storage unit. Multiple BOALF\n    records can cover the same minute — each identified by an acceptanceNumber.\n    A higher acceptanceNumber represents a more recent instruction that\n    supersedes earlier ones.\n\n    Algorithm:\n      1. Find all BOALF records whose [timeFrom, timeTo) interval covers\n         the minute.\n      2. Among those, pick the record with the highest acceptanceNumber.\n      3. Return its levelFrom (the MW level at the start of the interval).\n\n    We use levelFrom rather than interpolating between levelFrom and levelTo.\n    In practice, \"body\" records (spanning many minutes) have\n    levelFrom == levelTo, and \"ramp\" records are only 1 minute long, so\n    the error from not interpolating is negligible.\n\n    Returns None if no BOALF record covers this minute, signalling the\n    caller to fall back to PN data.\n    \"\"\"\n    best_acceptance = -1\n    best_value: float | None = None\n\n    for rec in records:\n        if rec[\"time_from\"] <= minute_dt < rec[\"time_to\"]:\n            acceptance = rec[\"acceptance_number\"]\n            if acceptance > best_acceptance:\n                level = rec[\"level_from\"]\n                if level is not None:\n                    best_acceptance = acceptance\n                    best_value = level\n\n    return best_value\n\n\ndef _get_level_at_minute(records: list[dict], minute_dt: datetime) -> float | None:\n    \"\"\"Determine the MW level from a PN/MELS/MILS dataset at a specific minute.\n\n    Physical Notification (PN), Maximum Export Limit (MELS), and Minimum\n    Import Limit (MILS) datasets share the same record structure with\n    timeFrom/timeTo and levelFrom/levelTo fields. Their intervals typically\n    align to settlement period boundaries but are not guaranteed to.\n\n    For a given minute, finds all records whose [timeFrom, timeTo) interval\n    covers it and returns the levelFrom of the one with the latest timeFrom,\n    making the result deterministic when overlapping records exist.\n\n    Returns None if no record covers this minute.\n    \"\"\"\n    best_rec = None\n    for rec in records:\n        if rec[\"time_from\"] <= minute_dt < rec[\"time_to\"] and (\n            best_rec is None or rec[\"time_from\"] > best_rec[\"time_from\"]\n        ):\n            best_rec = rec\n    return best_rec[\"level_from\"] if best_rec is not None else None\n\n\ndef _compute_unit_storage_mw(\n    boalf_records: list[dict],\n    pn_records: list[dict],\n    mels_records: list[dict],\n    mils_records: list[dict],\n    period_start: datetime,\n    period_minutes: int,\n    print_details: bool = False,\n    print_minute_details: bool = False,\n) -> float:\n    \"\"\"Compute the average MW output for one storage unit over a period.\n\n    Resolves the effective MW value at each minute in [period_start,\n    period_start + period_minutes) using the following precedence:\n\n      1. BOALF available  → use it directly. If multiple BOALF records\n         cover a minute, the highest acceptanceNumber wins.\n      2. PN available, and MELS and/or MILS available → clamp PN to\n         the [MILS, MELS] range. MELS is the Maximum Export Limit\n         (upper bound), MILS is the Minimum Import Limit (lower bound,\n         typically negative for storage importing/charging).\n      3. PN available, no limits → use PN as-is.\n      4. No data at all → assume 0 MW.\n\n    Returns the average MW over the period (sum of per-minute values\n    divided by period_minutes).\n    \"\"\"\n    total = 0.0\n    boalf_minutes = 0\n    pn_minutes = 0\n    zero_minutes = 0\n    minute_details: list[str] = []\n\n    for m in range(period_minutes):\n        minute_dt = period_start + timedelta(minutes=m)\n        ts = minute_dt.strftime(\"%H:%M\")\n\n        boalf_value = _get_boalf_value_at_minute(boalf_records, minute_dt)\n        pn_value = _get_level_at_minute(pn_records, minute_dt)\n        mels_value = _get_level_at_minute(mels_records, minute_dt)\n        mils_value = _get_level_at_minute(mils_records, minute_dt)\n\n        if boalf_value is not None:\n            total += boalf_value\n            boalf_minutes += 1\n            if boalf_value != 0 or (pn_value is not None and pn_value != 0):\n                pn_str = f\"|PN:{pn_value:.0f}\" if pn_value is not None else \"\"\n                minute_details.append(f\"{ts}=BOALF:{boalf_value:.0f}{pn_str}\")\n            continue\n\n        if pn_value is not None:\n            clamped = pn_value\n            if mels_value is not None:\n                clamped = min(clamped, mels_value)\n            if mils_value is not None:\n                clamped = max(clamped, mils_value)\n            total += clamped\n            pn_minutes += 1\n            if clamped != 0:\n                extra = \"\"\n                if clamped != pn_value:\n                    extra = f\"(raw:{pn_value:.0f})\"\n                minute_details.append(f\"{ts}=PN:{clamped:.0f}{extra}\")\n            continue\n\n        zero_minutes += 1\n\n    avg_mw = total / period_minutes\n    if print_details:\n        summary = (\n            f\"    {boalf_minutes}xBOALF {pn_minutes}xPN {zero_minutes}xNODATA\"\n            f\" → avg={avg_mw:.1f} MW\"\n        )\n        print(summary)\n        if print_minute_details and minute_details:\n            for m in minute_details:\n                print(f\"      {m}\")\n    return avg_mw\n\n\ndef _fetch_storage_dataset(\n    session: Session,\n    params: dict,\n    endpoint: str,\n) -> list[dict]:\n    res = session.get(endpoint, params=params)\n    if not res.ok:\n        raise ParserException(\n            \"GB.py\",\n            f\"Exception when fetching storage units error code: {res.status_code}: {res.text}\",\n            ZONE_KEY,\n        )\n    return _extract_data_rows(res.json())\n\n\ndef get_hydro_storage_units(session: Session, zone_key: ZoneKey) -> list[str]:\n    res = session.get(ELEXON_BMU_UNITS)\n    if not res.status_code == 200:\n        raise ParserException(\n            \"GB.py\",\n            f\"Exception when fetching storage units error code: {res.status_code}: {res.text}\",\n            zone_key,\n        )\n\n    hydro_storage_units = []\n    for r in res.json():\n        if r[\"fuelType\"] == \"PS\":  # PS = pumped storage\n            hydro_storage_units.append(r[\"nationalGridBmUnit\"])\n\n    return hydro_storage_units\n\n\ndef get_battery_units(session: Session, zone_key: ZoneKey) -> list[str]:\n    \"\"\"Fetch battery BMU IDs from the Elexon BMU Fuel Type spreadsheet.\n\n    Filters for units where BMRS FUEL TYPE = \"OTHER\" and REG FUEL TYPE = \"BATTERY\".\n    \"\"\"\n    res = session.get(\n        ELEXON_BMU_FUEL_TYPE_URL,\n        headers={\"User-Agent\": \"electricitymaps.com\"},\n    )\n    if not res.ok:\n        raise ParserException(\n            \"GB.py\",\n            f\"Failed to download BMU fuel type spreadsheet: {res.status_code}\",\n            zone_key,\n        )\n\n    wb = load_workbook(BytesIO(res.content), read_only=True, data_only=True)\n    ws = wb.active\n\n    battery_units = []\n    for row in ws.iter_rows(min_row=2, values_only=True):\n        neso_bmu_id = row[0]\n        bmrs_fuel_type = row[3]\n        reg_fuel_type = row[4]\n        if bmrs_fuel_type == \"OTHER\" and reg_fuel_type == \"BATTERY\":\n            battery_units.append(neso_bmu_id)\n\n    wb.close()\n    return battery_units\n\n\nif __name__ == \"__main__\":\n    for zone_key in [\"BE\", \"CH\", \"AT\", \"ES\", \"FR\", \"GB\", \"IT\", \"NL\", \"PT\"]:\n        print(f\"fetch_price({zone_key}) ->\")\n        print(fetch_price(ZoneKey(zone_key)))\n\n    historical_datetime = datetime(2022, 7, 16, 12, tzinfo=timezone.utc)\n    print(f\"fetch_price(target_datetime={historical_datetime.isoformat()}) ->\")\n    print(fetch_price(target_datetime=historical_datetime))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/GCCIA.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"\nThis parser returns Gulf Cooperation Council countries (United Arab Emirates, Bahrain, Saudi Arabia, Oman, Qatar, and Kuwait) electricity demand (only consumption, production data is not available)\nKuwait has a good data source and parser of its own, but should it become unavailable this parser can return data for Kuwait as well\nSource: Gulf Cooperation Council Interconnection Authority\nURL: https://www.gccia.com.sa/\nScroll down to see the system demand map\nKuwait shares of Electricity production in 2017: 65.6% oil, 34.4% gas (source: IEA; https://www.iea.org/statistics/?country=KUWAIT&indicator=ElecGenByFuel)\n\"\"\"\n\n# TODO get this data for the other countries as well\n\nimport re\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom sys import stderr\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import TotalConsumptionList\n\nfrom .lib.exceptions import ParserException\n\nCONSUMPTION_URL = \"https://www.gccia.com.sa/\"\nSOURCE = \"www.gccia.com.sa\"\n\nCOUNTRY_CODE_MAPPING = {\n    \"AE\": \"uae\",\n    \"BH\": \"bah\",\n    \"KW\": \"kuw\",\n    \"OM\": \"omn\",\n    \"QA\": \"qat\",\n    \"SA\": \"ksa\",\n}\n\nTIME_ZONE_MAPPING = {\n    \"AE\": ZoneInfo(\"Asia/Dubai\"),\n    \"BH\": ZoneInfo(\"Asia/Bahrain\"),\n    \"KW\": ZoneInfo(\"Asia/Kuwait\"),\n    \"OM\": ZoneInfo(\"Asia/Muscat\"),\n    \"QA\": ZoneInfo(\"Asia/Qatar\"),\n    \"SA\": ZoneInfo(\"Asia/Riyadh\"),\n}\n\n\ndef fetch_consumption(\n    zone_key,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    r = session or Session()\n    response = r.get(CONSUMPTION_URL)\n\n    pattern = COUNTRY_CODE_MAPPING[zone_key] + r'-mw-val\">\\s*(\\d+)'\n\n    match = re.findall(pattern, response.text)\n    if not match:\n        # if no data, the text becomes \" - \"\n        raise ParserException(\n            \"GCCIA.py\", \"data is currently not available\", zone_key=zone_key\n        )\n    consumption = TotalConsumptionList(logger)\n    consumption.append(\n        zoneKey=zone_key,\n        datetime=datetime.now(tz=TIME_ZONE_MAPPING[zone_key]),\n        consumption=int(match[0]),\n        source=SOURCE,\n    )\n\n    return consumption.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the electricityMap backend, but handy for testing.\"\"\"\n\n    for i in COUNTRY_CODE_MAPPING:\n        print(f\"fetch_consumption('{i}') ->\")\n        try:\n            print(fetch_consumption(i))\n        except IndexError as error:\n            print(f\"Could not fetch consumption data for {i}\", file=stderr)\n            print(type(error), \":\", error, file=stderr)\n        print()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/GSO.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Parse Peninsular Malaysian electricity data from the GSO API.\"\"\"\n\n# The states of Sabah and Sarawak are not included. There is pumped storage on\n# the Peninsula but no data is currently available.\n# https://www.scribd.com/document/354635277/Doubling-Up-in-Malaysia-International-Water-Power\n\n# Standard library imports\nimport json\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\n# Third-party library imports\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\n\n# Local library imports\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency, use_proxy\nfrom electricitymap.contrib.types import ZoneKey\n\nDEFAULT_ZONE_KEY = ZoneKey(\"MY-WM\")\nDOMAIN = \"www.gso.org.my\"\nPRODUCTION_THRESHOLD = 10  # MW\nZONE_INFO = ZoneInfo(\"Asia/Kuala_Lumpur\")\nCONSUMPTION_URL = f\"https://{DOMAIN}/SystemData/SystemDemand.aspx/GetChartDataSource\"\nEXCHANGE_URL = f\"https://{DOMAIN}/SystemData/TieLine.aspx/GetChartDataSource\"\nPRODUCTION_URL = f\"https://{DOMAIN}/SystemData/CurrentGen.aspx/GetChartDataSource\"\n\nPRODUCTION_BREAKDOWN = {\n    \"Coal\": \"coal\",\n    \"Gas\": \"gas\",\n    \"CoGen\": \"unknown\",\n    \"Oil\": \"oil\",\n    \"Hydro\": \"hydro\",\n    \"Solar\": \"solar\",\n}\n\n\ndef get_api_data(session: Session, url, data):\n    \"\"\"Parse JSON data from the API.\"\"\"\n    # The API returns a JSON string containing only one key-value pair whose\n    # value is another JSON string. We must therefore parse the response as\n    # JSON, access the lone value, and parse it as JSON again!\n    return json.loads(session.post(url, json=data).json()[\"d\"])\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"MY\")\ndef fetch_consumption(\n    zone_key: ZoneKey = DEFAULT_ZONE_KEY,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Request the power consumption (in MW) of a given zone.\"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    date_string = target_datetime.strftime(\"%d/%m/%Y\")\n    consumption_data = get_api_data(\n        session or Session(),\n        CONSUMPTION_URL,\n        {\n            \"Fromdate\": date_string,\n            \"Todate\": date_string,\n        },\n    )\n    all_consumption_data = TotalConsumptionList(logger)\n\n    for item in consumption_data:\n        all_consumption_data.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(item[\"DT\"]).replace(tzinfo=ZONE_INFO),\n            consumption=item[\"MW\"],\n            source=DOMAIN,\n        )\n    return all_consumption_data.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"MY\")\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Request the power exchange (in MW) between two zones.\"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    date_string = target_datetime.strftime(\"%d/%m/%Y\")\n\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted((zone_key1, zone_key2))))\n    all_exchange_data = ExchangeList(logger)\n    if sorted_zone_keys == \"MY-WM->SG\":\n        # The Singapore exchange is a PLTG tie.\n        exchange_data = get_api_data(\n            session,\n            EXCHANGE_URL,\n            {\n                \"Fromdate\": date_string,\n                \"Todate\": date_string,\n                \"Line\": \"PLTG\",\n            },\n        )\n        for item in exchange_data:\n            all_exchange_data.append(\n                datetime=datetime.fromisoformat(item[\"Tarikhmasa\"]).replace(\n                    tzinfo=ZONE_INFO\n                ),\n                netFlow=item[\"MW\"],\n                zoneKey=sorted_zone_keys,\n                source=DOMAIN,\n            )\n\n    elif sorted_zone_keys == \"MY-WM->TH\":\n        # The Thailand exchange is made up of EGAT and HVDC ties.\n        egat_exchanges = get_api_data(\n            session,\n            EXCHANGE_URL,\n            {\n                \"Fromdate\": date_string,\n                \"Todate\": date_string,\n                \"Line\": \"EGAT\",\n            },\n        )\n        hvdc_exchanges = get_api_data(\n            session,\n            EXCHANGE_URL,\n            {\n                \"Fromdate\": date_string,\n                \"Todate\": date_string,\n                \"Line\": \"HVDC\",\n            },\n        )\n        for exchange in egat_exchanges + hvdc_exchanges:\n            all_exchange_data.append(\n                datetime=datetime.fromisoformat(exchange[\"Tarikhmasa\"]).replace(\n                    tzinfo=ZONE_INFO\n                ),\n                netFlow=exchange[\"MW\"],\n                zoneKey=sorted_zone_keys,\n                source=DOMAIN,\n            )\n    else:\n        raise NotImplementedError(\"'{sorted_zone_keys}' is not implemented\")\n    return all_exchange_data.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"MY\")\ndef fetch_production(\n    zone_key: ZoneKey = DEFAULT_ZONE_KEY,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Request the production mix (in MW) of a given zone.\"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    date_string = target_datetime.strftime(\"%d/%m/%Y\")\n    all_production_data = ProductionBreakdownList(logger)\n\n    production_data = get_api_data(\n        session,\n        PRODUCTION_URL,\n        {\n            \"Fromdate\": date_string,\n            \"Todate\": date_string,\n        },\n    )\n    for item in production_data:\n        production_mix = ProductionMix()\n        item_datetime = datetime.fromisoformat(item[\"DT\"]).replace(tzinfo=ZONE_INFO)\n        for mode in [key for key in item if key != \"DT\"]:\n            production_mix.add_value(PRODUCTION_BREAKDOWN[mode], item[mode], True)\n        all_production_data.append(\n            zoneKey=zone_key,\n            production=production_mix,\n            source=DOMAIN,\n            datetime=item_datetime,\n        )\n    return all_production_data.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/GT.py",
    "content": "\"\"\"Parse Guatemalan electricity data from the Administrador del Mercado Mayorista (AMM) API.\"\"\"\n\nimport collections\nimport enum\nfrom datetime import datetime, time, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"GT.py\"\nDEFAULT_ZONE_KEY = ZoneKey(\"GT\")\nTIMEZONE = ZoneInfo(\"America/Guatemala\")\n\nSOURCE = \"amm.org.gt\"  # Source is slightly different than API URL\nURL = \"https://wl12.amm.org.gt/GraficaPW/graficaCombustible\"\n\nPRODUCTION_TYPE_TO_PRODUCTION_MODE = {\n    \"BIOGAS\": \"biomass\",\n    \"BIOMASA\": \"biomass\",\n    \"CARBÓN\": \"coal\",\n    \"CARBÓN/PETCOKE\": \"coal\",\n    \"GAS NATURAL\": \"gas\",\n    \"SYNGAN\": \"gas\",\n    \"VAPOR\": \"geothermal\",\n    \"AGUA\": \"hydro\",\n    \"BUNKER\": \"oil\",\n    \"DIESEL\": \"oil\",\n    \"IRRADIACIÓN\": \"solar\",\n    \"BIOMASA/CARBÓN\": \"unknown\",  # not always present, e.g. 15/07/2023 TZ\n    \"VIENTO\": \"wind\",\n}\n\nKNOWN_API_DATA_KEYS = [\n    *PRODUCTION_TYPE_TO_PRODUCTION_MODE.keys(),\n    \"DEM SNI\",\n    \"DEMANDA LOCAL PROG\",\n    \"INTERCONEXIÓN\",\n    \"null\",\n]\n\n\nclass ApiKind(enum.Enum):\n    PRODUCTION = \"production\"\n    CONSUMPTION = \"consumption\"\n\n\ndef _get_api_data(\n    session: Session,\n    target_datetime: datetime,\n    target: ApiKind,\n    num_backlog_days: int,\n) -> dict[datetime, dict]:\n    \"\"\"Get the one-hourly AMM API data for the desired UTC day + n days of backlog.\"\"\"\n\n    now_utc = datetime.now(timezone.utc)\n    hour_now_utc = now_utc.replace(minute=0, second=0, microsecond=0)\n\n    target_datetime_utc = target_datetime.astimezone(timezone.utc)\n\n    # The API expects local (TZ) timestamps and can only return one day of data\n    # so might need to do multiple api calls if UTC day straddles multiple local days\n    target_day_utc = datetime.combine(target_datetime_utc, time(), tzinfo=timezone.utc)\n\n    target_day_utc_start = target_day_utc - timedelta(days=num_backlog_days)\n    target_day_utc_end = target_day_utc + timedelta(days=1) - timedelta(microseconds=1)\n\n    local_day_of_target_day_utc_start = datetime.combine(\n        target_day_utc_start.astimezone(TIMEZONE), time(), tzinfo=TIMEZONE\n    )\n    local_day_of_target_day_utc_end = datetime.combine(\n        target_day_utc_end.astimezone(TIMEZONE), time(), tzinfo=TIMEZONE\n    )\n    num_local_days = (\n        local_day_of_target_day_utc_end - local_day_of_target_day_utc_start\n    ).days\n\n    daily_payloads: dict[datetime, list[dict]] = {}\n    for i in range(num_local_days + 1):\n        local_day = local_day_of_target_day_utc_start + timedelta(days=i)\n        response = session.get(URL, params={\"dt\": local_day.strftime(\"%d/%m/%Y\")})\n        if not response.ok:\n            raise ParserException(\n                PARSER,\n                f\"Exception when fetching {target.value} error code: {response.status_code}: {response.text}\",\n            )\n\n        # The JSON data returned by the API is a list of objects, each representing one technology type.\n        daily_payloads[local_day] = response.json()\n\n    if not any(daily_payload for daily_payload in daily_payloads.values()):\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching {target.value}: no data available for UTC day {target_day_utc.strftime('%Y-%m-%d %Z')}. \"\n            f\"Note that historical data is only available for the last 1 year.\",\n        )\n\n    # aggregate all individual hourly items into a dict keyed by common UTC timestamp\n    results: dict[datetime, dict] = collections.defaultdict(dict)\n    for local_day, daily_payload in daily_payloads.items():\n        for row in daily_payload:\n            # The API returns hours in the range [1, 24], so each one refers to the\n            # past hour (e.g., 1 is the time period [00:00, 01:00)). Shift the hour\n            # so each index represents the hour ahead and is in the range [0, 24),\n            # e.g., hour 0 represents the period [00:00, 01:00).\n            dt_local = local_day + timedelta(hours=int(row[\"hora\"]) - 1)\n            dt_utc = dt_local.astimezone(timezone.utc)\n\n            # ignore data outside of range of interest\n            if dt_utc < target_day_utc_start or dt_utc > target_day_utc_end:\n                continue\n\n            # For live data, the current hour's data isn't finished updating until the hour has passed,\n            # so the current hour should not be included in the results.\n            if dt_utc >= hour_now_utc:\n                continue\n\n            results[dt_utc][row[\"tipo\"]] = row[\"potencia\"]\n\n    return results\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey = DEFAULT_ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Fetch a list of hourly consumption data, in MW, for the UTC day of the requested date-time.\"\"\"\n\n    session = session or Session()\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n    api_data = _get_api_data(\n        session,\n        target_datetime=target_datetime,\n        target=ApiKind.CONSUMPTION,\n        num_backlog_days=0,\n    )\n\n    consumption_list = TotalConsumptionList(logger=logger)\n    for dt, row in api_data.items():\n        consumption = row[\"DEM SNI\"]\n        if not consumption:\n            continue\n\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            consumption=consumption,\n            source=SOURCE,\n        )\n    return consumption_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = DEFAULT_ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Fetch a list of hourly production data, in MW, for the UTC day of the requested date-time.\"\"\"\n\n    session = session or Session()\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n    api_data = _get_api_data(\n        session,\n        target_datetime=target_datetime,\n        target=ApiKind.PRODUCTION,\n        num_backlog_days=0,\n    )\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n    for dt, row in api_data.items():\n        production_mix = ProductionMix()\n        for key in row:\n            if key not in PRODUCTION_TYPE_TO_PRODUCTION_MODE:\n                if key not in KNOWN_API_DATA_KEYS:\n                    logger.warning(f\"Unmapped production type returned by API: {key}\")\n                continue\n\n            production_mode = PRODUCTION_TYPE_TO_PRODUCTION_MODE[key]\n            production_mix.add_value(production_mode, row[key])\n\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            source=SOURCE,\n            production=production_mix,\n        )\n    return production_breakdown_list.to_list()\n\n\nif __name__ == \"__main__\":\n    # Never used by the electricityMap back-end, but handy for testing.\n\n    target_datetime = datetime.fromisoformat(\"2023-07-16T12:00:00+00:00\")\n\n    print(\"fetch_production():\")\n    print(fetch_production())\n    print(f\"fetch_production(target_datetime={target_datetime.isoformat()!r}):\")\n    print(fetch_production(target_datetime=target_datetime))\n\n    print(\"fetch_consumption():\")\n    print(fetch_consumption())\n    print(f\"fetch_consumption(target_datetime={target_datetime.isoformat()!r}):\")\n    print(fetch_consumption(target_datetime=target_datetime))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/HN.py",
    "content": "from csv import reader\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nDATA_URL = \"https://otr.ods.org.hn:3200/odsprd/ods_prd/r/operador-del-sistema-ods/producci%C3%B3n-horaria\"\n\nINDEX_TO_TYPE_MAP = {\n    1: \"hydro\",\n    2: \"wind\",\n    3: \"solar\",\n    4: \"geothermal\",\n    5: \"biomass\",\n    6: \"coal\",\n    # 7: Exchanges\n    8: \"oil\",\n    9: \"oil\",\n    10: \"hydro\",\n}\n\nEXCHANGE_MAP = {\n    \"Guatemala\": \"GT->HN\",\n    \"Nicaragua\": \"HN->NI\",\n    \"El Salvador\": \"HN->SV\",\n}\n\nEXCHANGE_DIRECTION_MAP = {\n    \"GT->HN\": -1,\n    \"HN->NI\": 1,\n    \"HN->SV\": 1,\n}\n\n\ndef get_production_data_by_type(\n    session: Session,\n) -> list[tuple[list[Any], dict[str, str]]]:\n    \"\"\"\n    Gets the production data from otr.ods.org.hn separated by plant type.\n    Returns a list of tuples containing (CSV_data, plant_to_type_mapping) for each type.\n    \"\"\"\n    data_by_type = []\n\n    for index in range(1, 11):\n        if index == 7:\n            continue\n\n        params = {\n            \"request\": \"CSV_N_\",\n            \"p8_indx\": index,\n        }\n        response: Response = session.get(\n            DATA_URL,\n            params=params,\n            verify=False,\n        )\n\n        parsed_csv = list(reader(response.text.splitlines()))\n        csv_data = []\n        plant_to_type_map = {}\n\n        for row in parsed_csv:\n            if row[0] == \"Fecha\" or row[1] == \"Planta\":\n                continue\n            plant_to_type_map[row[1]] = INDEX_TO_TYPE_MAP[index]\n            csv_data.append(row)\n\n        if csv_data:\n            data_by_type.append((csv_data, plant_to_type_map))\n\n    return data_by_type\n\n\ndef get_exchange_data(session: Session) -> tuple[list[Any], dict[str, str]]:\n    \"\"\"\n    Gets the exchange data from otr.ods.org.hn.\n    Returns a tuple with CSV data and exchange mapping.\n    \"\"\"\n    params = {\n        \"request\": \"CSV_N_\",\n        \"p8_indx\": 7,\n    }\n    response: Response = session.get(DATA_URL, params=params, verify=False)\n    CSV_data = list(reader(response.text.splitlines()))\n    return CSV_data, EXCHANGE_MAP\n\n\ndef safe_float_conversion(value: str | None) -> float | None:\n    \"\"\"\n    Safely converts a string value to float, returning None for missing or empty values.\n    \"\"\"\n    if value is None or value == \"\" or value.strip() == \"\":\n        return None\n    try:\n        return float(value)\n    except (ValueError, TypeError):\n        return None\n\n\ndef extract_date_from_csv(CSV_data: list) -> str | None:\n    \"\"\"\n    Extracts the date from the CSV data\n    \"\"\"\n    for row in CSV_data:\n        if row and len(row) > 0 and row[0] != \"Fecha\":\n            return row[0]\n    return None\n\n\ndef create_production_breakdown_list(\n    csv_data: list[Any], plant_to_type_map: dict[str, str], date: str, logger: Logger\n) -> ProductionBreakdownList:\n    \"\"\"\n    Create a ProductionBreakdownList from CSV data for a specific plant type.\n    Uses ProductionMix.add_value() for automatic aggregation and validation.\n    \"\"\"\n    breakdown_list = ProductionBreakdownList(logger)\n\n    hourly_mixes = {hour: ProductionMix() for hour in range(24)}\n\n    for row in csv_data:\n        if not row or len(row) < 2 or row[1] not in plant_to_type_map:\n            continue\n\n        production_mode = plant_to_type_map[row[1]]\n        hourly_values = row[2:]\n\n        for hour, value in enumerate(hourly_values[:24]):\n            float_value = safe_float_conversion(value)\n            hourly_mixes[hour].add_value(production_mode, float_value)\n\n    for hour, production_mix in hourly_mixes.items():\n        dt = get_datetime(date, hour)\n        if dt is not None:\n            breakdown_list.append(\n                zoneKey=ZoneKey(\"HN\"),\n                datetime=dt,\n                source=\"ods.org.hn\",\n                production=production_mix,\n            )\n\n    return breakdown_list\n\n\ndef parse_exchange_data_by_hour(\n    CSV_data: list, mapping: dict[str, str], date: str | None, logger: Logger\n) -> dict[str, ExchangeList]:\n    \"\"\"\n    Parse CSV data and return exchange lists by zone.\n    Returns a dictionary with zone keys and ExchangeList values.\n    \"\"\"\n    exchanges_by_zone = {}\n\n    if date is None:\n        return exchanges_by_zone\n\n    for zone_key in mapping.values():\n        exchanges_by_zone[zone_key] = ExchangeList(logger)\n\n    for row in CSV_data:\n        if not row or len(row) < 3 or row[1] not in mapping:\n            continue\n\n        zone_key = mapping[row[1]]\n        direction_multiplier = EXCHANGE_DIRECTION_MAP[zone_key]\n        hourly_values = row[2:]\n\n        for hour, value in enumerate(hourly_values[:24]):\n            float_value = safe_float_conversion(value)\n            if float_value is not None:\n                dt = get_datetime(date, hour)\n                if dt is not None:\n                    net_flow = float_value * direction_multiplier\n                    exchanges_by_zone[zone_key].append(\n                        zoneKey=ZoneKey(zone_key),\n                        datetime=dt,\n                        source=\"ods.org.hn\",\n                        netFlow=net_flow,\n                    )\n\n    return exchanges_by_zone\n\n\ndef get_production_values(\n    data_by_type: list[tuple[list[Any], dict[str, str]]],\n    logger: Logger,\n) -> ProductionBreakdownList:\n    \"\"\"\n    Gets the production values using the merge functionality to combine\n    production breakdowns from different plant types.\n    \"\"\"\n    if not data_by_type:\n        return ProductionBreakdownList(logger)\n\n    # Extract date from the first data source\n    first_csv_data, _ = data_by_type[0]\n    date = extract_date_from_csv(first_csv_data)\n\n    if date is None:\n        return ProductionBreakdownList(logger)\n\n    production_breakdown_lists = []\n\n    for csv_data, plant_to_type_map in data_by_type:\n        if not csv_data:\n            continue\n\n        breakdown_list = create_production_breakdown_list(\n            csv_data, plant_to_type_map, date, logger\n        )\n\n        if len(breakdown_list) > 0:\n            production_breakdown_lists.append(breakdown_list)\n\n    return ProductionBreakdownList.merge_production_breakdowns(\n        production_breakdown_lists, logger\n    )\n\n\ndef get_datetime(date: str | None, hour: int) -> datetime | None:\n    \"\"\"\n    Returns a datetime object with the given date and hour, or None if date is invalid\n    \"\"\"\n    if date is None or date == \"\" or date.strip() == \"\":\n        return None\n    try:\n        return datetime.strptime(date, \"%m/%d/%Y\").replace(\n            tzinfo=ZoneInfo(\"America/Tegucigalpa\")\n        ) + timedelta(hours=hour)\n    except (ValueError, TypeError):\n        return None\n\n\ndef fetch_production(\n    zone_key: str = \"HN\",\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    if target_datetime is not None:\n        raise ParserException(\n            \"HN.py\", \"This parser is not yet able to parse past dates\"\n        )\n\n    data_by_type = get_production_data_by_type(session)\n    production_breakdowns = get_production_values(data_by_type, logger)\n\n    return production_breakdowns.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    if target_datetime is not None:\n        raise ParserException(\n            \"HN.py\", \"This parser is not yet able to parse past dates\"\n        )\n\n    CSV_data, EXCHANGE_MAP = get_exchange_data(session)\n    date = extract_date_from_csv(CSV_data)\n    exchanges_by_zone = parse_exchange_data_by_hour(\n        CSV_data, EXCHANGE_MAP, date, logger\n    )\n    sorted_zone_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    if sorted_zone_keys in exchanges_by_zone:\n        return exchanges_by_zone[sorted_zone_keys].to_list()\n    else:\n        return []\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IEMOP.py",
    "content": "import logging\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import NamedTuple\n\nimport pandas as pd\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config.constants import PRODUCTION_MODES\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nREPORTS_ADMIN_URL = \"https://www.iemop.ph/wp-admin/admin-ajax.php\"\nDIPC_URL = \"https://www.iemop.ph/market-data/dipc-energy-results-raw/\"\nRTDHS_URL = \"https://www.iemop.ph/market-data/rtd-hvdc-schedules/\"\n\nTIMEZONE = \"Asia/Manila\"\nSOURCE = \"iemop.ph\"\nREGION_TO_ZONE_KEY = {\n    \"LUZON\": \"PH-LU\",\n    \"VISAYAS\": \"PH-VI\",\n    \"MINDANAO\": \"PH-MI\",\n}\nRESOURCE_NAME_TO_MODE = {\n    \"1ACNPC_G01\": \"biomass\",\n    \"1AMBUK_U01\": \"hydro\",\n    \"1AMBUK_U02\": \"hydro\",\n    \"1AMBUK_U03\": \"hydro\",\n    \"1ANDA_G01\": \"coal\",\n    \"1APEC_G01\": \"coal\",\n    \"1ARMSOL_G01\": \"solar\",\n    \"1BAKUN_G01\": \"hydro\",\n    \"1BINGA_U01\": \"hydro\",\n    \"1BINGA_U02\": \"hydro\",\n    \"1BINGA_U03\": \"hydro\",\n    \"1BINGA_U04\": \"hydro\",\n    \"1BOSUNG_G01\": \"solar\",\n    \"1BT2020_G01\": \"biomass\",\n    \"1BTNSOL_G01\": \"solar\",\n    \"1BULSOL_G01\": \"solar\",\n    \"1BURGOS_G01\": \"wind\",\n    \"1BURGOS_G02\": \"solar\",\n    \"1BURGOS_G03\": \"solar\",\n    \"1CABSOL_G01\": \"solar\",\n    \"1CAPRIS_G01\": \"wind\",\n    \"1CASECN_G01\": \"hydro\",\n    \"1CIP2_G01\": \"oil\",\n    \"1CLASOL_G01\": \"solar\",\n    \"1DALSOL_G01\": \"solar\",\n    \"1GFII_G01\": \"biomass\",\n    \"1GIFT_G01\": \"biomass\",\n    \"1IBEC_G01\": \"biomass\",\n    \"1IPOWER_G01\": \"biomass\",\n    \"1IPOWER_G02\": \"unknown\",\n    \"1MAEC_G01\": \"solar\",\n    \"1MAGAT_U01\": \"hydro\",\n    \"1MAGAT_U02\": \"hydro\",\n    \"1MAGAT_U03\": \"hydro\",\n    \"1MAGAT_U04\": \"hydro\",\n    \"1MARSOL_G01\": \"solar\",\n    \"1MARVEL_G01\": \"coal\",\n    \"1MARVEL_G02\": \"coal\",\n    \"1MASIWA_G01\": \"hydro\",\n    \"1MSINLO_G01\": \"coal\",\n    \"1MSINLO_G02\": \"coal\",\n    \"1NIABAL_G01\": \"hydro\",\n    \"1NMHC_G01\": \"hydro\",\n    \"1NMHC_G03\": \"hydro\",\n    \"1NWIND_G01\": \"wind\",\n    \"1NWIND_G02\": \"wind\",\n    \"1PETRON_G01\": \"unknown\",\n    \"1PETSOL_G01\": \"solar\",\n    \"1PNTBNG_U01\": \"hydro\",\n    \"1PNTBNG_U02\": \"hydro\",\n    \"1RASLAG_G01\": \"solar\",\n    \"1RASLAG_G02\": \"solar\",\n    \"1SABANG_G01\": \"hydro\",\n    \"1SLANGN_G01\": \"hydro\",\n    \"1SMBELL_G01\": \"hydro\",\n    \"1SMC_G01\": \"coal\",\n    \"1SMC_G02\": \"coal\",\n    \"1SMC_G03\": \"coal\",\n    \"1SPABUL_G01\": \"solar\",\n    \"1SROQUE_U01\": \"hydro\",\n    \"1SROQUE_U02\": \"hydro\",\n    \"1SROQUE_U03\": \"hydro\",\n    \"1SUAL_G01\": \"coal\",\n    \"1SUAL_G02\": \"coal\",\n    \"1SUBSOL_G01\": \"solar\",\n    \"1S_ENRO_G01\": \"oil\",\n    \"1T_ASIA_G01\": \"oil\",\n    \"1UPPC_G01\": \"coal\",\n    \"1YHGRN_G01\": \"solar\",\n    \"1ZAMSOL_G01\": \"solar\",\n    \"2MMPP_G01\": \"gas\",\n    \"2PNGEA_G01\": \"gas\",\n    \"2SMNRTH_G01\": \"solar\",\n    \"2VALSOL_G01\": \"solar\",\n    \"3ADISOL_G01\": \"solar\",\n    \"3AVION_U01\": \"gas\",\n    \"3AVION_U02\": \"gas\",\n    \"3AWOC_G01\": \"wind\",\n    \"3BART_G01\": \"hydro\",\n    \"3BBEC_G01\": \"biomass\",\n    \"3BOTOCA_G01\": \"hydro\",\n    \"3CALACA_G01\": \"coal\",\n    \"3CALACA_G02\": \"coal\",\n    \"3CALIRY_G01\": \"hydro\",\n    \"3CALSOL_G01\": \"solar\",\n    \"3ILIJAN_G01\": \"gas\",\n    \"3ILIJAN_G02\": \"gas\",\n    \"3KAL_G01\": \"hydro_storage\",\n    \"3KAL_G02\": \"hydro_storage\",\n    \"3KAL_G03\": \"hydro_storage\",\n    \"3KAL_G04\": \"hydro_storage\",\n    \"3MALAYA_G01\": \"gas\",\n    \"3MALAYA_G02\": \"gas\",\n    \"3MEC_G01\": \"solar\",\n    \"3MGPP_G01\": \"geothermal\",\n    \"3ORMAT_G01\": \"geothermal\",\n    \"3PAGBIL_G01\": \"coal\",\n    \"3PAGBIL_G02\": \"coal\",\n    \"3PAGBIL_G03\": \"coal\",\n    \"3QPPL_G01\": \"coal\",\n    \"3RCBMI_G01\": \"oil\",\n    \"3RCBMI_G02\": \"oil\",\n    \"3SLPGC_G01\": \"coal\",\n    \"3SLPGC_G02\": \"coal\",\n    \"3SLTEC_G01\": \"coal\",\n    \"3SLTEC_G02\": \"coal\",\n    \"3SNGAB_G01\": \"gas\",\n    \"3STA-RI_G01\": \"gas\",\n    \"3STA-RI_G02\": \"gas\",\n    \"3STA-RI_G03\": \"gas\",\n    \"3STA-RI_G04\": \"gas\",\n    \"3STA-RI_G05\": \"gas\",\n    \"3STA-RI_G06\": \"gas\",\n    \"1ARAYSOL_G01\": \"solar\",\n    \"1ARAYSOL_G02\": \"solar\",\n    \"1BALWIND_G01\": \"wind\",\n    \"1BTSOLEN_G01\": \"solar\",\n    \"1CONSOL_G01\": \"solar\",\n    \"1CURSOL_G02\": \"solar\",\n    \"1GIGSOL_G01\": \"solar\",\n    \"1PASQSOL_G01\": \"solar\",\n    \"1PETSOL_G02\": \"solar\",\n    \"2PNGYSOL_G01\": \"solar\",\n    \"3SOLACE_G01\": \"solar\",\n    \"1AMPHAW_G01\": \"hydro\",\n    \"1BAKSIP_G01\": \"hydro\",\n    \"1BINENG_G01\": \"hydro\",\n    \"1BT2020_G02\": \"biomass\",\n    \"1BUTAO_G01\": \"hydro\",\n    \"1CAGBIO_G01\": \"biomass\",\n    \"1CLEANG_G01\": \"biomass\",\n    \"1GIFT_G02\": \"biomass\",\n    \"1GNPD_U01\": \"coal\",\n    \"1GNPD_U02\": \"coal\",\n    \"1GRGOLD_G01\": \"biomass\",\n    \"1HYPGRN_G01\": \"biomass\",\n    \"1LASUER_U01\": \"biomass\",\n    \"1LIMAY_U01\": \"gas\",\n    \"1LIMAY_U02\": \"gas\",\n    \"1LIMAY_U03\": \"gas\",\n    \"1LIMAY_U04\": \"gas\",\n    \"1LIMAY_U05\": \"gas\",\n    \"1LIMAY_U06\": \"gas\",\n    \"1LIMAY_U07\": \"gas\",\n    \"1LIMAY_U08\": \"gas\",\n    \"1MARIS_U01\": \"hydro\",\n    \"1MARIS_U02\": \"hydro\",\n    \"1MATUNO_G01\": \"hydro\",\n    \"1MPGC_U01\": \"coal\",\n    \"1MSINLO_G03\": \"coal\",\n    \"1RASLAG_G03\": \"solar\",\n    \"1SMC_G04\": \"coal\",\n    \"1TERASU_G01\": \"solar\",\n    \"1VSGRIP_G01\": \"biomass\",\n    \"2ECOPRK_G01\": \"solar\",\n    \"2ECOTAGA_G01\": \"solar\",\n    \"2TMOBIL_G01\": \"oil\",\n    \"2TMOBIL_G02\": \"oil\",\n    \"2TMOBIL_G03\": \"oil\",\n    \"2TMOBIL_G04\": \"oil\",\n    \"3BACMAN_U01\": \"geothermal\",\n    \"3BACMAN_U02\": \"geothermal\",\n    \"3BACMAN_U03\": \"geothermal\",\n    \"3BALUG_G01\": \"hydro\",\n    \"3CADPI_G01\": \"biomass\",\n    \"3CLBATO_G01\": \"hydro\",\n    \"3INARI_G01\": \"hydro\",\n    \"3LWERLAB_G01\": \"hydro\",\n    \"3MAJAY_G01\": \"hydro\",\n    \"3MGI_G02\": \"geothermal\",\n    \"3PALAK_G01\": \"hydro\",\n    \"3SBPL_G01\": \"coal\",\n    \"3TIBAG_G01\": \"hydro\",\n    \"3UPLAB_G01\": \"hydro\",\n    \"4LGPP_G01\": \"geothermal\",\n    \"4PHSOL_G01\": \"solar\",\n    \"4SEPSOL_G01\": \"solar\",\n    \"5CEDC_U01\": \"coal\",\n    \"5CEDC_U02\": \"coal\",\n    \"5CEDC_U03\": \"coal\",\n    \"5KSPC_G01\": \"coal\",\n    \"5KSPC_G02\": \"coal\",\n    \"5TOLSOL_G01\": \"solar\",\n    \"5TPC_G01\": \"oil\",\n    \"5TPC_G02\": \"coal\",\n    \"6AMLA_G01\": \"hydro\",\n    \"6CARSOL_G01\": \"solar\",\n    \"6CENPRI_U01\": \"oil\",\n    \"6CENPRI_U02\": \"oil\",\n    \"6CENPRI_U03\": \"oil\",\n    \"6CENPRI_U04\": \"oil\",\n    \"6FFHC_G01\": \"biomass\",\n    \"6HELIOS_G01\": \"solar\",\n    \"6HPCO_G01\": \"biomass\",\n    \"6MANSOL_G01\": \"solar\",\n    \"6MNTSOL_G01\": \"solar\",\n    \"6NASULO_G01\": \"geothermal\",\n    \"6PAL1A_G01\": \"geothermal\",\n    \"6PAL2A_U01\": \"geothermal\",\n    \"6PAL2A_U02\": \"geothermal\",\n    \"6PAL2A_U03\": \"geothermal\",\n    \"6PAL2A_U04\": \"geothermal\",\n    \"6SACASL_G01\": \"solar\",\n    \"6SACASL_G02\": \"solar\",\n    \"6SACSUN_G01\": \"solar\",\n    \"6SCBE_G01\": \"oil\",\n    \"6SLYSOL_G01\": \"solar\",\n    \"6URC_G01\": \"biomass\",\n    \"6VMC_G01\": \"biomass\",\n    \"7JANOPO_G01\": \"hydro\",\n    \"7LOBOC_G01\": \"hydro\",\n    \"8CASA_G01\": \"biomass\",\n    \"8COSMO_G01\": \"solar\",\n    \"8GLOBAL_G01\": \"unknown\",\n    \"8PALM_G01\": \"coal\",\n    \"8PEDC_U01\": \"coal\",\n    \"8PEDC_U02\": \"coal\",\n    \"8PEDC_U03\": \"coal\",\n    \"8PWIND_G01\": \"wind\",\n    \"8SLWIND_G01\": \"wind\",\n    \"8SUWECO_G01\": \"hydro\",\n    \"4CLBYBNK_G01\": \"oil\",\n    \"4IASMOD_G01\": \"oil\",\n    \"4IASMOD_G02\": \"oil\",\n    \"4IASMOD_G03\": \"oil\",\n    \"4IASMOD_G04\": \"oil\",\n    \"4IASMOD_G05\": \"oil\",\n    \"4IASMOD_G06\": \"oil\",\n    \"4TAFT_G01\": \"hydro\",\n    \"5CPPC_U01\": \"oil\",\n    \"5CPPC_U02\": \"oil\",\n    \"5CPPC_U03\": \"oil\",\n    \"5CPPC_U04\": \"oil\",\n    \"5CPPC_U05\": \"oil\",\n    \"5CPPC_U06\": \"oil\",\n    \"5CPPC_U07\": \"oil\",\n    \"5CPPC_U08\": \"oil\",\n    \"5CPPC_U09\": \"oil\",\n    \"5EAUC_U01\": \"coal\",\n    \"5EAUC_U02\": \"coal\",\n    \"5EAUC_U03\": \"coal\",\n    \"5EAUC_U04\": \"coal\",\n    \"5THVI_U01\": \"coal\",\n    \"5THVI_U02\": \"coal\",\n    \"5TPVI_U01\": \"oil\",\n    \"5TPVI_U02\": \"oil\",\n    \"5TPVI_U03\": \"oil\",\n    \"5TPVI_U04\": \"oil\",\n    \"5TPVI_U05\": \"oil\",\n    \"5TPVI_U06\": \"oil\",\n    \"6BISCOM_G01\": \"biomass\",\n    \"6CABI_G01\": \"biomass\",\n    \"6CENPRI_U05\": \"oil\",\n    \"6HPCO_G02\": \"biomass\",\n    \"6NTNEGB_G01\": \"biomass\",\n    \"6SCBIOP_G01\": \"biomass\",\n    \"6STNEGB_G01\": \"biomass\",\n    \"6VMC_G02\": \"biomass\",\n    \"7BDPP_U01\": \"oil\",\n    \"7BDPP_U02\": \"oil\",\n    \"7BDPP_U03\": \"oil\",\n    \"7BDPP_U04\": \"oil\",\n    \"7LOBOC_G02\": \"hydro\",\n    \"7SEVILL_G01\": \"hydro\",\n    \"7TPLPB4_U01\": \"oil\",\n    \"7TPLPB4_U02\": \"oil\",\n    \"7TPLPB4_U03\": \"oil\",\n    \"7TPLPB4_U04\": \"oil\",\n    \"8PDPP1_U02\": \"oil\",\n    \"8PDPP1_U03\": \"oil\",\n    \"8PDPP1_U05\": \"oil\",\n    \"8STBPB1_U01\": \"oil\",\n    \"8STBPB1_U02\": \"oil\",\n    \"8STBPB1_U03\": \"oil\",\n    \"8STBPB1_U04\": \"oil\",\n    \"8TIMBA_G01\": \"hydro\",\n    \"11KBSOL_G01\": \"solar\",\n    \"13DIGSOL_G01\": \"solar\",\n    \"14ASTROSOL_G01\": \"solar\",\n    \"14NVSOL_G01\": \"solar\",\n    \"9KEGJIM_G01\": \"oil\",\n    \"9PANABNK_U01\": \"unknown\",\n    \"9PANABNK_U02\": \"unknown\",\n    \"9WMPC_U01\": \"oil\",\n    \"9WMPC_U02\": \"oil\",\n    \"9WMPC_U03\": \"oil\",\n    \"9WMPC_U04\": \"oil\",\n    \"9WMPC_U05\": \"oil\",\n    \"9WMPC_U06\": \"oil\",\n    \"9WMPC_U07\": \"oil\",\n    \"9WMPC_U08\": \"oil\",\n    \"9WMPC_U09\": \"oil\",\n    \"10AGUS1_U01\": \"hydro\",\n    \"10AGUS1_U02\": \"hydro\",\n    \"10AGUS2_U01\": \"hydro\",\n    \"10AGUS2_U02\": \"hydro\",\n    \"10AGUS2_U03\": \"hydro\",\n    \"10AGUS4_U01\": \"hydro\",\n    \"10AGUS4_U02\": \"hydro\",\n    \"10AGUS4_U03\": \"hydro\",\n    \"10AGUS5_U01\": \"hydro\",\n    \"10AGUS5_U02\": \"hydro\",\n    \"10AGUS6_U01\": \"hydro\",\n    \"10AGUS6_U02\": \"hydro\",\n    \"10AGUS6_U03\": \"hydro\",\n    \"10AGUS6_U04\": \"hydro\",\n    \"10AGUS6_U05\": \"hydro\",\n    \"10AGUS7_U01\": \"hydro\",\n    \"10AGUS7_U02\": \"hydro\",\n    \"10GNPK_U01\": \"coal\",\n    \"10GNPK_U02\": \"coal\",\n    \"10GNPK_U03\": \"coal\",\n    \"10GNPK_U04\": \"coal\",\n    \"10IDPP_G01\": \"oil\",\n    \"10MEGC_G01\": \"oil\",\n    \"10PPEI_U01\": \"coal\",\n    \"11FDC_U01\": \"coal\",\n    \"11FDC_U02\": \"coal\",\n    \"11FDC_U03\": \"coal\",\n    \"11FGBPC_G01\": \"hydro\",\n    \"11KEGMAR_G01\": \"biomass\",\n    \"11KIRAS_G01\": \"solar\",\n    \"11MANFOR_G01\": \"hydro\",\n    \"11MANFOR_G02\": \"hydro\",\n    \"11MINBAL_G01\": \"oil\",\n    \"11MINBU_G01\": \"hydro\",\n    \"11MNCBLG_G01\": \"hydro\",\n    \"11MNRGY_G01\": \"oil\",\n    \"11MNRGY_G02\": \"oil\",\n    \"11NBPC_G01\": \"oil\",\n    \"11PACERM_G01\": \"oil\",\n    \"11PKBUK_G01\": \"oil\",\n    \"11PULA4_U01\": \"hydro\",\n    \"11PULA4_U02\": \"hydro\",\n    \"11PULA4_U03\": \"hydro\",\n    \"11STEAG_U01\": \"coal\",\n    \"11STEAG_U02\": \"coal\",\n    \"12ASIGA_G01\": \"hydro\",\n    \"12KEGGIN_G01\": \"oil\",\n    \"12KEGTAN_G01\": \"oil\",\n    \"12LKMAINIT_G01\": \"hydro\",\n    \"12NACSUR_G01\": \"oil\",\n    \"12PKSFRA_U01\": \"oil\",\n    \"12PKSFRA_U02\": \"oil\",\n    \"12TM2_U01\": \"oil\",\n    \"12TM2_U02\": \"oil\",\n    \"13DCPP_U01\": \"coal\",\n    \"13DCPP_U02\": \"coal\",\n    \"13EUROH_G01\": \"hydro\",\n    \"13MAGDBNK_G01\": \"oil\",\n    \"13MATIBNK_G01\": \"oil\",\n    \"13MPCDIG_G01\": \"oil\",\n    \"13SIBULAN_G01\": \"hydro\",\n    \"13SMC_U01\": \"coal\",\n    \"13SMC_U02\": \"coal\",\n    \"13TALOM1_G01\": \"hydro\",\n    \"13TALOM23_G01\": \"hydro\",\n    \"13TM1_U01\": \"oil\",\n    \"13TM1_U02\": \"oil\",\n    \"13TUDAY2_G01\": \"hydro\",\n    \"14ALMADA_G01\": \"hydro\",\n    \"14BIOGS_G01\": \"biomass\",\n    \"14BIOMS_U01\": \"biomass\",\n    \"14GERBIO_G01\": \"biomass\",\n    \"14LAMSAN_G01\": \"biomass\",\n    \"14MARBEL_U01\": \"hydro\",\n    \"14MTAPO_U01\": \"geothermal\",\n    \"14MTAPO_U02\": \"geothermal\",\n    \"14MTAPO_U03\": \"geothermal\",\n    \"14PKPSOC_G01\": \"oil\",\n    \"14SARANG_U01\": \"coal\",\n    \"14SARANG_U02\": \"coal\",\n    \"14SPGI_U01\": \"biomass\",\n    \"14SUPKOR_G01\": \"oil\",\n    \"1ANGAT_A\": \"hydro\",\n    \"1ANGAT_M\": \"hydro\",\n    \"1BAUANG_GS2\": \"oil\",\n    \"1BAUANG_GS3\": \"oil\",\n    \"1BAUANG_GS1\": \"oil\",\n    \"1CNCEP_BAT\": \"battery\",\n    \"1LAMAO_BAT\": \"battery\",\n    \"1LIMAY_BAT\": \"battery\",\n    \"1BTSOLEN_BAT\": \"battery\",\n    \"1MAGAT_BAT\": \"battery\",\n    \"1MSINLO_BAT\": \"battery\",\n    \"1SNMAN_BAT\": \"battery\",\n    \"1MAGAPIT_BAT\": \"battery\",\n    \"3INGRID_GS1\": \"oil\",\n    \"3INGRID_GS4\": \"oil\",\n    \"3INGRID_GS6\": \"oil\",\n    \"3INGRID_GS2\": \"oil\",\n    \"3INGRID_GS3\": \"oil\",\n    \"3INGRID_GS5\": \"oil\",\n    \"3MKBN_A\": \"geothermal\",\n    \"3MKBN_E\": \"geothermal\",\n    \"3ALMNOS_BAT1\": \"battery\",\n    \"3ALMNOS_BAT2\": \"battery\",\n    \"3MKBN_B\": \"geothermal\",\n    \"3MKBN_C\": \"geothermal\",\n    \"3MKBN_D\": \"geothermal\",\n    \"3TIWI_A\": \"geothermal\",\n    \"3TIWI_C\": \"geothermal\",\n    \"4ORMOC_BAT\": \"battery\",\n    \"5CPPC_U10\": \"oil\",\n    \"5TOLEDO_BAT\": \"battery\",\n    \"6KABAN_BAT\": \"battery\",\n    \"7UBAY_BAT\": \"battery\",\n    \"8PDPP3_C\": \"oil\",\n    \"8PDPP3_E\": \"oil\",\n    \"8PDPP3_G\": \"oil\",\n    \"8PDPP3_H\": \"oil\",\n    \"9WMPC_U10\": \"oil\",\n    \"11JASA_BAT\": \"battery\",\n    \"11VILLA_BAT\": \"battery\",\n    \"13MALITA_BAT\": \"battery\",\n    \"13MACO_BAT\": \"battery\",\n}\nEXCHANGE_KEY_MAPPING = {\n    \"MINVIS1\": {\"zone_key\": \"PH-MI->PH-VI\", \"flow\": 1},\n    \"VISLUZ1\": {\"zone_key\": \"PH-LU->PH-VI\", \"flow\": -1},\n}\nKIND_TO_URL = {\"production\": DIPC_URL, \"exchange\": RTDHS_URL}\nKIND_TO_POST_ID = {\"production\": \"5754\", \"exchange\": \"5770\"}\nSTORAGE_METHODS_TO_MODE = {\"hydro_storage\": \"hydro\", \"battery\": \"battery\"}\nMODES_TO_RESOURCE_KIND = {\n    **dict.fromkeys(PRODUCTION_MODES, \"production\"),\n    **dict.fromkeys(STORAGE_METHODS_TO_MODE, \"storage\"),\n}\n\n\ndef _validate_resource_name_to_mode_mapping():\n    for resource_name, mode in RESOURCE_NAME_TO_MODE.items():\n        if mode not in set(PRODUCTION_MODES).union(STORAGE_METHODS_TO_MODE.keys()):\n            raise ValueError(\n                f\"Resource {resource_name} has an unknown mode {mode} in RESOURCE_NAME_TO_MODE\"\n            )\n\n\nclass MarketReportsItem(NamedTuple):\n    datetime: datetime\n    filename: str\n    link: str\n\n\ndef get_all_market_reports_items(\n    session: Session, zone_key: ZoneKey, kind: str, logger: Logger = getLogger(__name__)\n) -> dict[datetime, MarketReportsItem]:\n    \"\"\"\n    Gets a dictionary that converts a date into its code and filename\n    \"\"\"\n\n    logger.debug(\"Fetching list of available market reports\")\n    form_data = {\n        \"action\": \"display_filtered_market_data_files\",\n        \"datefilter%5Bstart%5D\": \"2021-09-13+00%3A00\",\n        \"datefilter%5Bend%5D\": \"2021-09-13+12%3A20\",\n        \"sort\": \"\",\n        \"page\": \"1\",\n        \"post_id\": KIND_TO_POST_ID[kind],\n    }\n    res = session.post(REPORTS_ADMIN_URL, data=form_data, verify=False)\n    id_to_items = res.json().get(\"data\", {})\n    if not id_to_items:\n        raise ParserException(\n            parser=\"IEMOP.py\",\n            zone_key=zone_key,\n            message=f\"No reports available to fetch {kind} data\",\n        )\n    datetime_to_items = {}\n    for report_id, items in id_to_items.items():\n        market_reports_item = MarketReportsItem(\n            datetime.strptime(items[\"date\"], \"%d %B %Y %H:%M\"),\n            items[\"filename\"],\n            KIND_TO_URL[kind] + f\"?md_file={report_id}\",\n        )\n        datetime_to_items[market_reports_item.datetime] = market_reports_item\n    logger.info(\n        f\"{zone_key} - {kind}: Succesfully recovered {len(datetime_to_items)} market reports items\"\n    )\n    return datetime_to_items\n\n\ndef filter_reports_items(\n    kind: str,\n    zone_key: ZoneKey,\n    reports_items: dict[datetime, MarketReportsItem],\n    target_datetime: datetime | None,\n) -> list[MarketReportsItem]:\n    # Date filtering\n    if target_datetime is None:\n        last_available_datetime = max(reports_items.keys())\n        start_datetime = last_available_datetime - timedelta(days=1)\n        _exception_date = start_datetime.date()\n        _reports_items = [\n            item for item in reports_items.values() if item.datetime >= start_datetime\n        ]\n    else:\n        # Refetch the whole day\n        _exception_date = target_datetime.date()\n        _reports_items = [\n            item\n            for item in reports_items.values()\n            if item.datetime.date() == target_datetime.date()\n        ]\n\n    if len(_reports_items) == 0:\n        raise ParserException(\n            parser=\"IEMOP.py\",\n            zone_key=zone_key,\n            message=f\"{zone_key}: No {kind} data available for {_exception_date} \",\n        )\n\n    return _reports_items\n\n\ndef download_production_market_reports_items(\n    session: Session, reports_items: list[MarketReportsItem], logger: Logger\n) -> pd.DataFrame:\n    from io import BytesIO\n    from zipfile import ZipFile\n\n    COLUMNS_MAPPING = {\n        \"REGION_NAME\": \"zone_key\",\n        \"RESOURCE_NAME\": \"resource_name\",\n        \"SCHED_MW\": \"value\",\n    }\n\n    _all_items_df = []\n    for reports_item in reports_items:\n        logger.debug(f\"Downloading market reports for {reports_item.filename}\")\n        res: Response = session.get(reports_item.link)\n        _item_dfs = []\n        # zip containing a list of csv files which we want to concatenate in a single dataframe\n        with ZipFile(BytesIO(res.content)) as zip_file:\n            for csv_filename in zip_file.namelist():\n                if csv_filename.endswith(\".csv\"):\n                    with zip_file.open(csv_filename) as csv_file:\n                        _df = pd.read_csv(csv_file, header=0)\n                        # The last line is EOF\n                        _df = _df[:-1]\n                        # All numeric types\n                        _df = _df.apply(pd.to_numeric, errors=\"ignore\")\n                        # Add datetime column\n                        _df = convert_column_to_datetime(_df, \"TIME_INTERVAL\")\n                        # Localize to TIMEZONE\n                        _df[\"datetime\"] = _df[\"datetime\"].dt.tz_localize(TIMEZONE)\n                        # Remove 5 minute interval as we want start of interval convention\n                        _df[\"datetime\"] = _df[\"datetime\"] - timedelta(minutes=5)\n                        # Misc\n                        _df[\"REGION_NAME\"] = _df[\"REGION_NAME\"].apply(\n                            lambda x: REGION_TO_ZONE_KEY[x]\n                        )\n                        _df[\"filename\"] = csv_filename\n                        _df = _df[[\"datetime\", \"filename\", *COLUMNS_MAPPING.keys()]]\n                        _df = _df.rename(columns=COLUMNS_MAPPING)\n                        _item_dfs.append(_df)\n\n        _all_items_df.append(pd.concat(_item_dfs, ignore_index=True))\n\n    df = pd.concat(_all_items_df, ignore_index=True)\n\n    # Add kind column for production/storage\n    df.loc[:, \"resource_kind\"] = \"\"\n\n    logger.info(\n        f\"Succesfully extracted unit level production between the {df.datetime.min()} and the {df.datetime.max()}\"\n    )\n\n    return df\n\n\ndef filter_for_zone(df: pd.DataFrame, zone_key: ZoneKey) -> pd.DataFrame:\n    df = df.copy()\n    return df.query(f\"zone_key == '{zone_key}'\")\n\n\ndef filter_valid_values(df: pd.DataFrame, logger: Logger) -> pd.DataFrame:\n    df = df.copy()\n    # Filter out non generation resources - with the exception of storage resources\n    df_production = df[df[\"resource_kind\"] == \"production\"]\n    df_production = df_production[df_production[\"value\"] >= 0]\n    df_storage = df[df[\"resource_kind\"] == \"storage\"]\n    df = pd.concat([df_production, df_storage])\n    # Remove duplicates if there is discharge\n    df = df.drop_duplicates(\n        subset=[\"datetime\", \"zone_key\", \"resource_name\"], keep=\"first\"\n    )\n    # Fill a list of all unknown resources\n    unknown_resources = df[df[\"mode\"] == \"unknown\"][\"resource_name\"].unique()\n    logger.warning(\n        f\"PH - production: Unknown resources found: {unknown_resources}. Please report this issue to the Electricity Maps team\"\n    )\n    return df\n\n\ndef match_resources_to_modes(df: pd.DataFrame) -> pd.DataFrame:\n    df = df.copy()\n    # Remove 0 padding in resource name\n    df[\"resource_name\"] = df[\"resource_name\"].apply(lambda x: x.strip(\"0\"))\n    # Match resource name to mode\n    df[\"mode\"] = df[\"resource_name\"].apply(\n        lambda x: RESOURCE_NAME_TO_MODE.get(x, \"unknown\")\n    )\n    # Match resource name to kind\n    df[\"resource_kind\"] = df[\"mode\"].map(MODES_TO_RESOURCE_KIND)\n    return df\n\n\ndef aggregate_per_datetime_mode(df: pd.DataFrame) -> pd.DataFrame:\n    return (\n        df.groupby([\"datetime\", \"mode\", \"resource_kind\"])\n        .sum(numeric_only=True)\n        .reset_index()\n    )\n\n\ndef pivot_per_mode(df: pd.DataFrame) -> pd.DataFrame:\n    df = df.copy()\n    # Flatten columns and make them \"{resource_kind}.{mode}\"\n    df[\"resource_kind_mode\"] = df[\"resource_kind\"] + \".\" + df[\"mode\"]\n    df = df[[\"resource_kind_mode\", \"datetime\", \"value\"]].pivot(\n        index=\"datetime\", columns=\"resource_kind_mode\"\n    )\n    df.columns = df.columns.droplevel()  # reset columns index\n\n    # Handle storage\n    df = df.rename(\n        columns={\n            f\"storage.{storage_method}\": f\"storage.{storage_mode}\"\n            for storage_method, storage_mode in STORAGE_METHODS_TO_MODE.items()\n        }\n    )\n    for storage_mode in STORAGE_METHODS_TO_MODE.values():\n        col_name = f\"storage.{storage_mode}\"\n        if col_name in df.columns:\n            df[col_name] *= -1\n    # With the pivot if some modes only have data for some datetimes, we will have NaNs\n    # Fill them with 0\n    df = df.fillna(0)\n    return df\n\n\ndef download_exchange_market_reports_items(\n    session: Session, reports_items: list[MarketReportsItem], logger: Logger\n) -> pd.DataFrame:\n    _all_items_df = []\n    for reports_item in reports_items:\n        logger.debug(f\"Downloading market reports for {reports_item.filename}\")\n        r: Response = session.get(reports_item.link)\n        _df = pd.read_csv(r.url)\n        _df = _df[:-1]\n        _df = convert_column_to_datetime(_df, \"RUN_TIME\")\n        _df[\"zone_key\"] = _df[\"HVDC_NAME\"].apply(\n            lambda x: EXCHANGE_KEY_MAPPING[x][\"zone_key\"]\n        )\n        _df[\"net_flow\"] = _df.apply(\n            lambda x: EXCHANGE_KEY_MAPPING[x[\"HVDC_NAME\"]][\"flow\"] * x[\"FLOW_FROM\"],\n            axis=1,\n        )\n        _df = _df[[\"datetime\", \"zone_key\", \"net_flow\"]]\n        _all_items_df.append(_df)\n\n    df = (\n        pd.concat(_all_items_df, ignore_index=True)\n        .set_index(\"datetime\")\n        .tz_localize(TIMEZONE)\n    )\n    return df\n\n\ndef convert_column_to_datetime(df: pd.DataFrame, datetime_column: str) -> pd.DataFrame:\n    \"\"\"convert datetime column to datetime format\"\"\"\n    dt1 = pd.to_datetime(\n        df[datetime_column],\n        format=\"%m/%d/%Y %I:%M:%S %p\",\n        errors=\"coerce\",\n    )\n    dt2 = pd.to_datetime(df[datetime_column], format=\"%m/%d/%Y\", errors=\"coerce\")\n    df[\"datetime\"] = dt1.combine_first(dt2)\n    return df\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"PH-LU\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n    _validate_resource_name_to_mode_mapping()\n    reports_items = get_all_market_reports_items(\n        session, zone_key, \"production\", logger\n    )\n    reports_items = filter_reports_items(\n        \"production\", zone_key, reports_items, target_datetime\n    )\n\n    df = download_production_market_reports_items(session, reports_items, logger)\n    df = (\n        df.pipe(filter_for_zone, zone_key)\n        .pipe(match_resources_to_modes)\n        .pipe(filter_valid_values, logger)\n        .pipe(aggregate_per_datetime_mode)\n        .pipe(pivot_per_mode)\n    )\n\n    production_breakdown = ProductionBreakdownList(logger)\n    for tstamp, row in df.iterrows():\n        production_mix = ProductionMix()\n        for mode in [m for m in row.index if \"production.\" in m]:\n            production_mix.add_value(mode.replace(\"production.\", \"\"), row[mode])\n        storage_mix = StorageMix()\n        for mode in [m for m in row.index if \"storage.\" in m]:\n            storage_mix.add_value(mode.replace(\"storage.\", \"\"), row[mode])\n        production_breakdown.append(\n            zone_key,\n            tstamp.to_pydatetime(),\n            SOURCE,\n            production_mix,\n            storage_mix,\n            sourceType=EventSourceType.measured,\n        )\n\n    return production_breakdown.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict] | dict:\n    session = session or Session()\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    all_exchange_items = get_all_market_reports_items(\n        session, sorted_zone_keys, \"exchange\", logger\n    )\n    reports_items = filter_reports_items(\n        \"exchange\", sorted_zone_keys, all_exchange_items, target_datetime\n    )\n\n    df = download_exchange_market_reports_items(session, reports_items, logger).pipe(\n        filter_for_zone, sorted_zone_keys\n    )\n\n    # Convert to EventList\n    exchange_list = ExchangeList(logger)\n    for tstamp, row in df.iterrows():\n        exchange_list.append(\n            zoneKey=row[\"zone_key\"],\n            datetime=tstamp.to_pydatetime(),\n            netFlow=row[\"net_flow\"],\n            source=SOURCE,\n        )\n    return exchange_list.to_list()\n\n\nif __name__ == \"__main__\":\n    logger = getLogger(__name__)\n    logging.basicConfig(level=logging.DEBUG)\n\n    # print(fetch_production())\n    # print(fetch_production(ZoneKey(\"PH-VI\"), target_datetime=datetime(2023, 8, 15)))\n    print(fetch_exchange(ZoneKey(\"PH-LU\"), ZoneKey(\"PH-VI\")))\n    print(\n        fetch_exchange(\n            ZoneKey(\"PH-MI\"), ZoneKey(\"PH-VI\"), target_datetime=datetime(2023, 8, 15)\n        )\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IL.py",
    "content": "\"\"\"\nIsrael's electricity system load parser.\n\nSource: Israel Electric Corporation\nURL: https://www.iec.co.il/en/pages/default.aspx\n\nShares of Electricity production in 2019:\n    64.0% Gas\n    31.0% Coal\n    1.0% oil,\n    4.0% Renewables\n    (source: IEA; https://www.iea.org/data-and-statistics?country=ISRAEL&fuel=Electricity%20and%20heat&indicator=Electricity%20generation%20by%20source)\n\"\"\"\n\nimport re\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom requests import Response, Session, get\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalProductionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.types import ZoneKey\n\nURL = \"https://www.noga-iso.co.il/Umbraco/Api/Documents/GetElectricalData\"\n\nIEC_URL = \"www.iec.co.il\"\nIEC_PRODUCTION = (\n    \"https://www.iec.co.il/_layouts/iec/applicationpages/lackmanagment.aspx\"\n)\nTZ = ZoneInfo(\"Asia/Jerusalem\")\n\n\ndef fetch_all() -> list:\n    \"\"\"Fetch info from IEC dashboard.\"\"\"\n    first = get(IEC_PRODUCTION)\n    second = get(IEC_PRODUCTION, cookies=first.cookies)\n    soup = BeautifulSoup(second.content, \"lxml\")\n\n    values: list = soup.find_all(\"span\", class_=\"statusVal\")\n    if len(values) == 0:\n        raise ValueError(\"Could not parse IEC dashboard\")\n    del values[1]\n\n    cleaned_list = []\n    for value in values:\n        value = re.findall(r\"\\d+\", value.text.replace(\",\", \"\"))\n        cleaned_list.append(value)\n\n    def flatten_list(_2d_list) -> list:\n        \"\"\"Flatten the list.\"\"\"\n        flat_list = []\n        for element in _2d_list:\n            if isinstance(element, list):\n                for item in element:\n                    flat_list.append(item)\n            else:\n                flat_list.append(element)\n        return flat_list\n\n    return flatten_list(cleaned_list)\n\n\ndef fetch_noga_iso_data(session: Session, logger: Logger):\n    \"\"\"Fetches data from Noga-ISO\"\"\"\n    response: Response = session.get(URL)\n    if not response.ok:\n        logger.warning(\n            \"IL.py\",\n            f\"Failed to fetch data from www.noga-iso.co.il with error: {response.status_code}\",\n        )\n\n    data = response.json()\n    return data\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"IL\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    session = session or Session()\n\n    data = fetch_noga_iso_data(session, logger)\n    eventList = ProductionBreakdownList(logger=logger)\n\n    productionMix = ProductionMix()\n\n    productionMix.add_value(\n        mode=\"unknown\", value=float(data.get(\"Production\").replace(\",\", \"\"))\n    )\n\n    eventList.append(\n        zoneKey=zone_key,\n        datetime=datetime.now(tz=TZ),\n        production=productionMix,\n        source=\"noga-iso.co.il\",\n    )\n\n    return eventList.to_list()\n\n\ndef fetch_total_production(\n    zone_key: ZoneKey = ZoneKey(\"IL\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    session = session or Session()\n\n    data = fetch_noga_iso_data(session, logger)\n\n    eventList = TotalProductionList(logger=logger)\n\n    eventList.append(\n        zoneKey=zone_key,\n        datetime=datetime.now(tz=TZ),\n        value=float(data.get(\"Production\").replace(\",\", \"\")),\n        source=\"noga-iso.co.il\",\n    )\n\n\ndef fetch_consumption(\n    zone_key: str = \"IL\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    data = fetch_all()\n    consumption = [float(item) for item in data]\n\n    # all mapped to unknown as there is no available breakdown\n    return {\n        \"zoneKey\": zone_key,\n        \"datetime\": datetime.now(tz=TZ),\n        \"consumption\": consumption[0],\n        \"source\": IEC_URL,\n    }\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IN.py",
    "content": "#!usr/bin/env python3\n\n\"\"\"Parser for all of India\"\"\"\n\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Response, Session\nfrom requests.adapters import HTTPAdapter\nfrom urllib3.util.retry import Retry\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\n# TODO 1 Migrate the IN_WE and IN_EA consumption fetching to this parser, using the grid india data.\n# TODO 2 Migrate the fetch_consumption in this file so that it uses the grid india data instead of meritindia.in.\n\n# This parsers does not work locally with all VPN. It does not work with SurfShark, but it works with NordVPN. Local proxies could also be used.\nIN_TZ = ZoneInfo(\"Asia/Kolkata\")\nSTART_DATE_RENEWABLE_DATA = datetime(2020, 12, 17, tzinfo=IN_TZ)\n# 1 MU = 1 GWH = 1000 MWH then assume uniform production per hour -> 1000/24 = 41.6666 = 1/0.024\n# So MU / 0.024 = MW\nCONVERSION_DAILY_GWH_TO_HOURLY_MW = 0.024\n\n# Some of the websites we use work with the VPC connector, some work without it.\nINDIA_PROXY_NO_VPC_CONNECTOR = (\n    \"https://in-proxy-no-vpc-connector-jfnx5klx2a-el.a.run.app\"\n)\n\nNPP_MODE_MAPPING = {\n    \"THER (GT)\": \"gas\",\n    \"THERMAL\": \"coal\",\n    \"HYDRO\": \"hydro\",\n    \"THER (DG)\": \"oil\",\n    \"NUCLEAR\": \"nuclear\",\n}\nNPP_REGION_MAPPING = {\n    \"NORTHERN\": \"IN-NO\",\n    \"EASTERN\": \"IN-EA\",\n    \"WESTERN\": \"IN-WE\",\n    \"SOUTHERN\": \"IN-SO\",\n    \"NORTH EASTERN\": \"IN-NE\",\n}\n\nGRID_INDIA_REGION_MAPPING = {\n    \"NR\": \"IN-NO\",\n    \"ER\": \"IN-EA\",\n    \"WR\": \"IN-WE\",\n    \"SR\": \"IN-SO\",\n    \"NER\": \"IN-NE\",\n    \"TOTAL\": \"IN\",\n}\n\nGRID_INDIA_REGION_MAPPING = {\n    \"IN-NO\": \"NR\",\n    \"IN-EA\": \"ER\",\n    \"IN-WE\": \"WR\",\n    \"IN-SO\": \"SR\",\n    \"IN-NE\": \"NER\",\n    \"IN\": \"TOTAL\",\n}\n\nGRID_INDIA_SOURCE = \"grid-india.in\"\n\nCEA_REGION_MAPPING = {\n    \"northern region\": \"IN-NO\",\n    \"western region\": \"IN-WE\",\n    \"southern region\": \"IN-SO\",\n    \"eastern region\": \"IN-EA\",\n    \"north-eastern region\": \"IN-NE\",\n}\n\nDEMAND_URL_MERITINDIA = (\n    \"{proxy}/StateWiseDetails/BindCurrentStateStatus?host=https://meritindia.in\"\n)\n\n# States codes as on meritindia.in\nSTATE_CODES = {\n    \"andhra-pradesh\": \"AP\",\n    \"arunachal-pradesh\": \"ACP\",\n    \"assam\": \"ASM\",\n    \"bihar\": \"BHR\",\n    \"chandiagarh\": \"CHG\",\n    \"chhattisgarh\": \"CTG\",\n    \"dadra-nagar-haveli\": \"DNH\",\n    \"daman-diu\": \"DND\",\n    \"delhi\": \"DL\",\n    \"goa\": \"GOA\",\n    \"gujarat\": \"GJT\",\n    \"haryana\": \"HRN\",\n    \"himachal-pradesh\": \"HP\",\n    \"jammu-kashmir\": \"JAK\",\n    \"jharkhand\": \"JHK\",\n    \"karnataka\": \"KRT\",\n    \"kerala\": \"KRL\",\n    \"madhya-pradesh\": \"MPD\",\n    \"maharashtra\": \"MHA\",\n    \"manipur\": \"MIP\",\n    \"meghalaya\": \"MGA\",\n    \"mizoram\": \"MZM\",\n    \"nagaland\": \"NGD\",\n    \"odisha\": \"ODI\",\n    \"puducherry\": \"PU\",\n    \"punjab\": \"PNB\",\n    \"rajasthan\": \"RJ\",\n    \"sikkim\": \"SKM\",\n    \"tamil-nadu\": \"TND\",\n    \"telangana\": \"TLG\",\n    \"tripura\": \"TPA\",\n    \"uttar-pradesh\": \"UP\",\n    \"uttarakhand\": \"UTK\",\n    \"west-bengal\": \"WB\",\n}\n\n\nSTATES_MAPPING = {\n    \"IN-NO\": [\n        \"delhi\",\n        \"haryana\",\n        \"himachal-pradesh\",\n        \"jammu-kashmir\",\n        \"punjab\",\n        \"rajasthan\",\n        \"uttar-pradesh\",\n        \"uttarakhand\",\n    ],\n    \"IN-WE\": [\"gujarat\", \"madya-pradesh\", \"maharashtra\", \"goa\", \"chhattisgarh\"],\n    \"IN-EA\": [\"bihar\", \"west-bengal\", \"odisha\", \"sikkim\"],\n    \"IN-NE\": [\n        \"arunachal-pradesh\",\n        \"assam\",\n        \"meghalaya\",\n        \"tripura\",\n        \"mizoram\",\n        \"nagaland\",\n        \"manipur\",\n    ],\n    \"IN-SO\": [\n        \"karnataka\",\n        \"kerala\",\n        \"tamil-nadu\",\n        \"andhra-pradesh\",\n        \"telangana\",\n        \"puducherry\",\n    ],\n}\n\n\ndef fetch_consumption_from_meritindia(\n    zone_key: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> TotalConsumptionList:\n    \"\"\"Fetches the live consumption from the Merit Order Despatch of Electricity.\n    This source seems to be a bit more stable right now than vidyutpravah.in\"\"\"\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    import concurrent.futures\n\n    total_consumption = 0\n    futures = []\n\n    def fetch_state_consumption(session, state):\n        resp: Response = session.post(\n            DEMAND_URL_MERITINDIA.format(proxy=INDIA_PROXY_NO_VPC_CONNECTOR),\n            data={\"StateCode\": STATE_CODES[state]},\n        )\n        data = resp.json()[0]\n        return float(str(data[\"Demand\"]).replace(\",\", \"\"))\n\n    with concurrent.futures.ThreadPoolExecutor() as executor:\n        for state in STATES_MAPPING[zone_key]:\n            future = executor.submit(fetch_state_consumption, session, state)\n            futures.append(future)\n\n        for future in concurrent.futures.as_completed(futures):\n            total_consumption += future.result()\n\n    consumption_list = TotalConsumptionList(logger=logger)\n    consumption_list.append(\n        zoneKey=ZoneKey(zone_key),\n        datetime=datetime.now(tz=IN_TZ),\n        consumption=total_consumption,\n        source=\"meritindia.in\",\n    )\n    return consumption_list\n\n\ndef fetch_npp_production(\n    zone_key: str,\n    target_datetime: datetime,\n    session: Session = Session(),\n    logger: Logger = getLogger(__name__),\n) -> dict[str, Any]:\n    \"\"\"Gets production for conventional thermal, nuclear and hydro from NPP daily reports\n    This data most likely doesn't inlcude distributed generation\"\"\"\n\n    npp_url = f\"https://npp.gov.in/public-reports/cea/daily/dgr/{target_datetime:%d-%m-%Y}/dgr2-{target_datetime:%Y-%m-%d}.xls\"\n    r: Response = session.get(npp_url)\n\n    if r.status_code == 200:\n        df_npp = pd.read_excel(r.content, header=3)\n        # Since 15/04/2025, a footer was added to the excel file.\n        # It modifies the structure of its columns. By removing the footer and then removing the empty columns, we can have a consistent structure.\n        df_npp = df_npp[df_npp[df_npp.columns[0]].notnull()]\n        df_npp = df_npp.dropna(axis=\"columns\", how=\"all\")\n        df_npp = df_npp.rename(\n            columns={\n                df_npp.columns[0]: \"power_station\",\n                df_npp.columns[2]: \"production_mode\",\n                \"TODAY'S\\nACTUAL\\n\": \"value\",\n            }\n        )\n        df_npp[\"region\"] = (\n            df_npp[\"power_station\"].apply(lambda x: NPP_REGION_MAPPING.get(x)).ffill()\n        )\n        df_npp = df_npp[[\"region\", \"production_mode\", \"value\"]]\n\n        df_npp_filtered = df_npp.loc[~df_npp[\"production_mode\"].isna()].copy()\n\n        df_zone = df_npp_filtered.loc[df_npp_filtered[\"region\"] == zone_key].copy()\n        df_zone[\"production_mode\"] = df_zone[\"production_mode\"].map(NPP_MODE_MAPPING)\n        production_in_zone = df_zone.groupby([\"production_mode\"])[\"value\"].sum()\n        production_dict = {\n            mode: round(production_in_zone.get(mode), 3)\n            for mode in production_in_zone.index\n        }\n        return production_dict\n    else:\n        raise ParserException(\n            parser=\"IN.py\",\n            message=f\"{target_datetime}: {zone_key} conventional production data is not available : [{r.status_code}]\",\n        )\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    return fetch_consumption_from_meritindia(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n    ).to_list()\n\n\ndef format_ren_production_data(\n    content: bytes, zone_key: str, target_datetime: datetime\n) -> dict[str, Any]:\n    \"\"\"Formats daily renewable production data for each zone\"\"\"\n    df_ren = pd.read_excel(content, engine=\"openpyxl\", header=5)\n    df_ren = df_ren.dropna(axis=0, how=\"all\")\n\n    # They changed format of the data from 2024/07/01\n    if target_datetime < datetime(2024, 7, 1, 0, 0, tzinfo=IN_TZ):\n        df_ren = df_ren.rename(\n            columns={\n                df_ren.columns[1]: \"region\",\n                df_ren.columns[2]: \"wind\",\n                df_ren.columns[3]: \"solar\",\n                df_ren.columns[4]: \"unknown\",\n            }\n        )\n    else:\n        # columns 4-7 are cumulative values for the month\n        df_ren = df_ren.rename(\n            columns={\n                df_ren.columns[0]: \"region\",\n                df_ren.columns[1]: \"wind\",\n                df_ren.columns[2]: \"solar\",\n                df_ren.columns[3]: \"unknown\",\n            }\n        )\n\n    is_region = df_ren[\"region\"].str.contains(\"Region\")\n    # values should be \"{Indian name}/{English name}\"\n    df_ren[\"zone_key\"] = (\n        df_ren[\"region\"]\n        .loc[is_region]\n        .str.split(\"/\")\n        .str[1]\n        .str.lower()\n        .map(CEA_REGION_MAPPING)\n    )\n\n    zone_data = df_ren.loc[\n        (df_ren[\"zone_key\"] == zone_key), [\"wind\", \"solar\", \"unknown\"]\n    ]\n    if zone_data.shape != (1, 3):\n        raise ParserException(\n            parser=\"IN.py\",\n            message=f\"{target_datetime}: {zone_key} renewable production data is not available\",\n        )\n    zone_data = zone_data.iloc[0, :].to_dict()\n\n    return zone_data\n\n\ndef fetch_cea_production(\n    zone_key: str,\n    target_datetime: datetime,\n    session: Session = Session(),\n    logger: Logger = getLogger(__name__),\n) -> dict[str, Any] | None:\n    \"\"\"Gets production data for wind, solar and other renewables\n    Other renewables includes a share of hydro, biomass and others and will categorized as unknown\n    DISCLAIMER: this data is only available since 2020/12/17\"\"\"\n    cea_data_url = (\n        \"https://cea.nic.in/wp-admin/admin-ajax.php?action=getpostsfordatatables\"\n    )\n\n    headers = {\n        \"User-Agent\": \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:144.0) Gecko/20100101 Firefox/144.0\",\n    }\n\n    retry_strategy = Retry(\n        total=3,  # Total number of retries\n        backoff_factor=1,  # A delay factor to apply between attempts\n        status_forcelist=[\n            429,\n            500,\n            502,\n            503,\n            504,\n        ],  # A set of HTTP status codes that we should force a retry on\n        allowed_methods=[\n            \"GET\"\n        ],  # Set of uppercased HTTP method verbs that we should retry on.\n    )\n    adapter = HTTPAdapter(max_retries=retry_strategy)\n    session.mount(\"https://\", adapter)\n    session.mount(\"http://\", adapter)\n    r_all_data: Response = session.get(cea_data_url, headers=headers, verify=False)\n    if r_all_data.status_code == 200:\n        all_data = r_all_data.json()[\"data\"]\n        target_elem = [\n            elem\n            for elem in all_data\n            if target_datetime.strftime(\"%Y-%m-%d\") in elem[\"date\"]\n        ]\n\n        if len(target_elem) > 0 and target_elem[0][\"link\"] != \"file_not_found\":\n            target_url = target_elem[0][\"link\"].split(\": \")[0]\n            formatted_url = target_url.split(\"^\")[0]\n            r: Response = session.get(formatted_url, headers=headers, verify=False)\n            renewable_production = format_ren_production_data(\n                content=r.content, zone_key=zone_key, target_datetime=target_datetime\n            )\n            return renewable_production\n        else:\n            raise ParserException(\n                parser=\"IN.py\",\n                message=f\"{target_datetime}: {zone_key} renewable production data is not available\",\n            )\n    else:\n        raise ParserException(\n            parser=\"IN.py\",\n            message=f\"{target_datetime}: {zone_key} renewable production data is not available, {r_all_data.status_code}\",\n        )\n\n\ndef fetch_grid_india_report(\n    target_datetime: datetime, session: Session\n) -> tuple[datetime, bytes | None]:\n    \"\"\"\n    Rely on grid-india.in backend API to fetch data report.\n    First query the backend to get the list of files available for a given date.\n    Reports can be found here : https://grid-india.in/en/reports/daily-psp-report\n    And also here here : https://report.grid-india.in/index.php?p=\n\n    \"\"\"\n\n    GRID_INDIA_BACKEND_URL = \"https://webapi.grid-india.in\"\n    GRID_INDIA_CDN_URL = \"https://webcdn.grid-india.in\"\n\n    GRID_INDIA_BACKEND_WITH_PROXY_URL = (\n        f\"{INDIA_PROXY_NO_VPC_CONNECTOR}/api/v1/file?host={GRID_INDIA_BACKEND_URL}\"\n    )\n\n    # Reports are stored per fiscal year, which goes from April N to March N+1.\n    fiscal_year_start = (\n        target_datetime.year - 1 if target_datetime.month < 4 else target_datetime.year\n    )\n    fiscal_year_end_short = (fiscal_year_start + 1) % 100\n\n    payload = {\n        \"_source\": \"GRDW\",\n        \"_type\": \"DAILY_PSP_REPORT\",\n        \"_fileDate\": f\"{fiscal_year_start}-{fiscal_year_end_short}\",\n        \"_month\": target_datetime.strftime(\"%m\"),\n    }\n\n    headers = {\n        \"User-Agent\": \"Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:144.0) Gecko/20100101 Firefox/144.0\",\n        \"Content-Type\": \"application/json\",\n    }\n\n    r: Response = session.post(\n        GRID_INDIA_BACKEND_WITH_PROXY_URL, json=payload, headers=headers\n    )\n    # We process the file that pass the file type filters and that is the most recent one\n    # before target_datetime.\n    if r.status_code == 200:\n        file_list = r.json()[\"retData\"]\n        latest_file_url = None\n        latest_file_date = None\n        for file in file_list:\n            is_correct_type = (\n                file.get(\"MimeType\") in (\"attachment/xls\", \"application/vnd.ms-excel\")\n            ) and file.get(\"FileType\") == \"DAILY_PSP_REPORT\"\n\n            if is_correct_type:\n                try:\n                    # Title_ is expected to start with \"dd.mm.yy\"\n                    file_date_str = file[\"Title_\"].split(\"_\")[0]\n                    file_date = datetime.strptime(file_date_str, \"%d.%m.%y\").replace(\n                        tzinfo=IN_TZ\n                    )\n\n                    if file_date <= target_datetime and (\n                        latest_file_date is None or file_date > latest_file_date\n                    ):\n                        latest_file_date = file_date\n                        latest_file_url = file.get(\"FilePath\")\n                except (ValueError, IndexError):\n                    # Ignore files with titles that don't match the expected date format\n                    continue\n\n        if latest_file_url is not None:\n            file_full_url = f\"{INDIA_PROXY_NO_VPC_CONNECTOR}/{latest_file_url}?host={GRID_INDIA_CDN_URL}\"\n            r: Response = session.get(file_full_url, headers=headers)\n            return latest_file_date, r.content\n        else:\n            raise ParserException(\n                parser=\"IN.py\",\n                message=f\"{target_datetime}: Grid India daily production data is not available\",\n            )\n    else:\n        raise ParserException(\n            parser=\"IN.py\",\n            message=f\"{target_datetime}: Grid India daily production data is not available, {r.status_code}\",\n        )\n\n\ndef get_daily_generation_table(content: bytes) -> pd.DataFrame:\n    \"\"\"\n    Get the G. Sourcewise generation (Gross) (MU) table from the daily report.\n    Returns a DataFrame with the generation for each mode.\n    Shape of the dataframe :\n    'mode' is the mode name.\n    'value' is the generation, in MU/GWh :\n    | mode | value |\n    |------|-------|\n    | coal | 100   |\n    | lignite| 200   |\n    | hydro | 300   |\n    | nuclear | 400   |\n    | gas | 500   |\n    | unknown | 600   |\n    \"\"\"\n    df = pd.read_excel(content, engine=\"xlrd\", header=4)\n\n    START_PATTERN = \"Sourcewise generation\"\n    END_PATTERN = \"Demand Diversity Factor\"\n    SECOND_END_PATTERN = \"Total\"\n\n    description_column = df.columns[0]\n    start_index = df.index[\n        df[description_column].str.contains(START_PATTERN, na=False, case=False)\n    ].tolist()[0]\n    end_index = df.index[\n        df[description_column].str.contains(END_PATTERN, na=False, case=False)\n    ].tolist()[0]\n\n    if not start_index or not end_index:\n        raise ParserException(\n            parser=\"IN.py\",\n            message=\"Could not find the generation table in the daily report; the format may have changed.\",\n        )\n    generation_df = df.iloc[start_index + 1 : end_index, 0:]\n\n    second_end_index = generation_df.index[\n        generation_df[description_column].str.contains(\n            SECOND_END_PATTERN, na=False, case=False\n        )\n    ].tolist()[0]\n\n    if not second_end_index:\n        raise ParserException(\n            parser=\"IN.py\",\n            message=\"Could not find the second end of the generation table in the daily report; the format may have changed.\",\n        )\n    total_row_position = generation_df.index.get_loc(\n        generation_df[\n            generation_df[description_column].str.contains(\"Total\", na=False)\n        ].index[0]\n    )\n\n    generation_df_without_re_share = generation_df.iloc[: total_row_position + 1, :]\n    generation_df_without_re_share = generation_df_without_re_share.set_index(\n        generation_df_without_re_share.columns[0]\n    )\n    generation_df_without_re_share.columns = generation_df_without_re_share.iloc[0]\n    generation_df_without_re_share = generation_df_without_re_share.iloc[1:].dropna(\n        axis=1, how=\"all\"\n    )\n    generation_df_without_re_share.index.name = \"mode\"\n\n    return generation_df_without_re_share\n\n\ndef get_wind_solar(content: bytes, zone_key: str) -> pd.DataFrame:\n    \"\"\"\n    Gets the wind and solar production for a given zone key.\n    Retrieves it from the daily report,\n    in the A. Power Supply Position at All India and Regional level table.\n    Returns a DataFrame with the wind and solar production for the given zone key.\n    Shape of the dataframe :\n    'mode' is 'wind' and 'solar'.\n    'value' is the generation, in MU/GWh :\n    | mode | value |\n    |------|-------|\n    | wind | 100   |\n    | solar| 200   |\n    \"\"\"\n\n    df = pd.read_excel(content, engine=\"xlrd\", header=2)\n    START_PATTERN = \"A. Power Supply Position\"\n    END_PATTERN = \"B. Frequency Profile\"\n\n    description_column = df.columns[0]\n\n    start_mask = df[description_column].str.contains(\n        START_PATTERN, na=False, case=False\n    )\n    end_mask = df[description_column].str.contains(END_PATTERN, na=False, case=False)\n    start_index = start_mask[start_mask].first_valid_index()\n    end_index = end_mask[end_mask].first_valid_index()\n\n    if start_index is None or end_index is None:\n        raise ParserException(\n            parser=\"IN.py\",\n            message=\"Could not find the generation table in the daily report; the format may have changed.\",\n        )\n    # Only keep the first table (A. Power Supply Position at All India and Regional level)\n    generation_df = df.iloc[start_index + 1 : end_index].copy()\n\n    # Set the row that contains the region names as the header.\n    generation_df.columns = generation_df.iloc[0]\n    generation_df = generation_df.iloc[1:].reset_index(drop=True)\n\n    # The descriptions ('Wind Gen', etc.) are now in the first data column.\n    # Let's search this column to find the integer index of the rows we want.\n    description_col = generation_df.iloc[:, 0]\n    wind_mask = description_col.str.contains(\"Wind Gen\", na=False, case=False)\n    solar_mask = description_col.str.contains(\"Solar Gen\", na=False, case=False)\n    wind_row_index = description_col[wind_mask].index[0]\n    solar_row_index = description_col[solar_mask].index[0]\n\n    region_column = GRID_INDIA_REGION_MAPPING[zone_key]\n    wind_gen_nr = generation_df.loc[wind_row_index, region_column]\n    solar_gen_nr = generation_df.loc[solar_row_index, region_column]\n\n    wind_solar_df = pd.DataFrame(\n        {\"value\": [wind_gen_nr, solar_gen_nr]}, index=[\"wind\", \"solar\"]\n    )\n    wind_solar_df.index.name = \"mode\"\n    wind_solar_df[\"value\"] = pd.to_numeric(\n        wind_solar_df[\"value\"].replace(\"-\", 0), errors=\"coerce\"\n    ).fillna(0)\n\n    return wind_solar_df\n\n\ndef parse_daily_production_grid_india_report(\n    content: bytes,\n    zone_key: str,\n    target_datetime: datetime,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Parses production data from grid india daily report.\n    Will split the daily production evenly across the 24 hours of the day.\n    This will then be reestimated by the estimation pipeline and the mode breakdown.\n    \"\"\"\n    daily_production_breakdown = get_production_breakdown(\n        content=content, zone_key=zone_key\n    )\n    daily_production_breakdown[\"value\"] = (\n        daily_production_breakdown[\"value\"] / CONVERSION_DAILY_GWH_TO_HOURLY_MW\n    )\n    df_pivoted = daily_production_breakdown.T\n    df_hourly = pd.concat([df_pivoted] * 24, ignore_index=True)\n\n    # Next, create a DatetimeIndex for the 24 hours of the target_datetime\n    start_of_day = target_datetime.replace(\n        hour=0, minute=0, second=0, microsecond=0, tzinfo=IN_TZ\n    )\n    hourly_index = pd.date_range(start=start_of_day, periods=24, freq=\"H\")\n\n    # Set this as the index of your new DataFrame\n    df_hourly.index = hourly_index\n\n    all_data_points = ProductionBreakdownList(logger)\n    for timestamp, production_series in df_hourly.iterrows():\n        production_dict = production_series.dropna().to_dict()\n        production_mix = ProductionMix()\n        for mode, value in production_dict.items():\n            production_mix.add_value(mode, value)\n        all_data_points.append(\n            zoneKey=ZoneKey(zone_key),\n            datetime=timestamp.to_pydatetime(),\n            production=production_mix,\n            source=GRID_INDIA_SOURCE,\n        )\n    return all_data_points.to_list()\n\n\ndef parse_15m_production_grid_india_report(\n    content: bytes,\n    zone_key: str,\n    target_datetime: datetime,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Parses production data from grid india report. Uses the 15-minute data in the TimeSeries sheet of the report.\n    Since 15-minute data aggregated to daily values do not match the daily production value from the first sheet of the report, we rescale the 15-minute data so that the total matches the daily production value.\n    Then, we assume that each zone has the same share of the production share for a given mode over the whole day.\n    We then breakdown the (15-minute, country-level, per mode) data, to (15-minute, zone-level, per mode) data.\n    \"\"\"\n    # Get total production for the whole country, from the daily data report.\n    daily_india_generation = parse_daily_total_production_grid_india_report(\n        content=content\n    )\n    # Get total production for the whole country, from the 15-minute time series report.\n    _15min_india_generation_aggregated_daily = (\n        parse_total_production_15min_grid_india_report(content=content)\n    )\n\n    # Compute the scaling factor that will be used to scale the 15-minute data so that its total matches the daily production value.\n    generation_scaling_factor = (\n        daily_india_generation / _15min_india_generation_aggregated_daily\n    )\n    # Scale the 15-minute data\n    _15min_scaled_generation_df = scale_15min_production(\n        content=content, scaling_factor=generation_scaling_factor\n    )\n\n    # Now, compute the share of the considered zone key in the India-level production, for each mode.\n    zone_mode_share_out_of_country = compute_zone_key_share_per_mode_out_of_total(\n        content=content, zone_key=zone_key\n    )\n\n    # Scale the 15-minute by the share of the mode for the considered zone key out of the country-level production.\n    ## Do not scale the time column\n    mode_columns = _15min_scaled_generation_df.columns.intersection(\n        zone_mode_share_out_of_country.index\n    )\n    ordered_zone_mode_share_out_of_country = zone_mode_share_out_of_country.reindex(\n        mode_columns\n    )\n\n    # Multiply the modes columns by the scaling factors\n    _15min_scaled_generation_df[mode_columns] = _15min_scaled_generation_df[\n        mode_columns\n    ].mul(ordered_zone_mode_share_out_of_country)\n\n    ## Convert the time column to a datetime index and drop the TIME column\n    datetime_series = pd.to_datetime(\n        target_datetime.strftime(\"%Y-%m-%d\") + \" \" + _15min_scaled_generation_df[\"TIME\"]\n    )\n    _15min_scaled_generation_df.index = datetime_series\n    _15min_scaled_generation_df.index = _15min_scaled_generation_df.index.tz_localize(\n        IN_TZ\n    )\n    _15min_scaled_generation_df = _15min_scaled_generation_df.drop(columns=[\"TIME\"])\n\n    all_data_points = ProductionBreakdownList(logger)\n    for timestamp, production_series in _15min_scaled_generation_df.iterrows():\n        production_dict = production_series.dropna().to_dict()\n        production_mix = ProductionMix()\n        for mode, value in production_dict.items():\n            production_mix.add_value(mode, value)\n        all_data_points.append(\n            zoneKey=ZoneKey(zone_key),\n            datetime=timestamp.to_pydatetime(),\n            production=production_mix,\n            source=GRID_INDIA_SOURCE,\n        )\n    return all_data_points.to_list()\n\n\ndef get_production_breakdown(content: bytes, zone_key: str) -> pd.DataFrame:\n    \"\"\"\n    Computes the share of the zone key in the total production for each mode.\n    Returns a dictionary with the mode as key and the share as value.\n    We will then assume this percentage is uniform across the day.\n    \"\"\"\n    daily_generation_df = get_daily_generation_table(content)\n    if zone_key == \"IN\":\n        zone_generation = daily_generation_df[\"All India\"]\n    else:\n        zone_generation = daily_generation_df[GRID_INDIA_REGION_MAPPING[zone_key]]\n\n    # Removes Total row\n    modes = [\"coal\", \"lignite\", \"hydro\", \"nuclear\", \"gas\", \"RES\"]\n    pattern = \"|\".join(modes)\n    mask = zone_generation.index.str.contains(pattern, case=False, na=False)\n    selected_df = zone_generation[mask]\n\n    # Sum the 'Coal' and 'Lignite'\n    numeric_df = selected_df.apply(pd.to_numeric, errors=\"coerce\")\n    coal_lignite_sum = numeric_df.loc[[\"Coal\", \"Lignite\"]].sum()\n    numeric_df.loc[\"coal\"] = coal_lignite_sum\n    all_modes_except_wind_solar = numeric_df.drop([\"Coal\", \"Lignite\"])\n    all_modes_except_wind_solar_df = all_modes_except_wind_solar.to_frame(name=\"value\")\n\n    # Get wind and solar for the considered zone key\n    wind_solar_india_df = get_wind_solar(content=content, zone_key=zone_key)\n\n    all_modes_df = pd.concat([all_modes_except_wind_solar_df, wind_solar_india_df])\n    all_modes_df.index = all_modes_df.index.str.lower()\n    # Rename the \"Gas, Naphta & Diesel\" mode to \"gas\"\n    gas_mask = all_modes_df.index.str.contains(\"gas\", na=False)\n    if gas_mask.any():\n        old_gas_label = all_modes_df.index[gas_mask][0]\n        all_modes_df = all_modes_df.rename(index={old_gas_label: \"gas\"})\n\n    # RES contains wind, solar, biomass and others.\n    # Substract wind and solar from RES, and map it to unknown.\n    res_mask = all_modes_df.index.str.contains(\"res\", na=False)\n    if res_mask.any():\n        old_res_label = all_modes_df.index[res_mask][0]\n        all_modes_cleaned_df = all_modes_df.rename(index={old_res_label: \"unknown\"})\n\n    # Replace any '-' strings with 0 and ensure the value column is numeric.\n    # Coerce errors will turn any other non-numeric values into NaN, which we then fill with 0.\n    all_modes_cleaned_df[\"value\"] = pd.to_numeric(\n        all_modes_cleaned_df[\"value\"].replace(\"-\", 0), errors=\"coerce\"\n    ).fillna(0)\n\n    all_modes_cleaned_df.loc[\"unknown\", \"value\"] = (\n        all_modes_cleaned_df.loc[\"unknown\", \"value\"]\n        - all_modes_cleaned_df.loc[\"wind\", \"value\"]\n        - all_modes_cleaned_df.loc[\"solar\", \"value\"]\n    )\n\n    return all_modes_cleaned_df\n\n\ndef compute_zone_key_share_per_mode_out_of_total(\n    content: bytes, zone_key: str\n) -> pd.Series:\n    country_production_breakdown = get_production_breakdown(\n        content=content, zone_key=\"IN\"\n    )\n    zone_production_breakdown = get_production_breakdown(\n        content=content, zone_key=zone_key\n    )\n\n    total_production_zone_share_out_of_country = (\n        zone_production_breakdown.sum() / country_production_breakdown.sum()\n    )[\"value\"]\n\n    zone_key_share_per_mode_out_of_country = (\n        zone_production_breakdown[\"value\"] / country_production_breakdown[\"value\"]\n    )\n\n    # We ensure that all share are between 0 and 1.\n    # If not, we replace the value by the share of the total production of the zone out of the total production of the country.\n    condition = (zone_key_share_per_mode_out_of_country >= 0) & (\n        zone_key_share_per_mode_out_of_country <= 1\n    )\n\n    return zone_key_share_per_mode_out_of_country.where(\n        condition, total_production_zone_share_out_of_country\n    )\n\n\ndef scale_15min_production(content: bytes, scaling_factor: float) -> pd.DataFrame:\n    df = pd.read_excel(content, engine=\"xlrd\", header=2, sheet_name=\"TimeSeries\")\n\n    KEYWORD_MAPPING = {\n        \"NUCLEAR\": \"nuclear\",\n        \"WIND\": \"wind\",\n        \"SOLAR\": \"solar\",\n        \"HYDRO\": \"hydro\",\n        \"GAS\": \"gas\",\n        \"THERMAL\": \"coal\",\n        \"OTHERS\": \"unknown\",\n    }\n\n    # Columns names are like NUCLEAR\\n(MW) or WIND**\\n(MW), etc.\n    # Try to make mapping robust by not relying on exact match.\n    dynamic_rename_mapping = {}\n    for col_name in df.columns:\n        for source_mode, mode in KEYWORD_MAPPING.items():\n            if source_mode.lower() in str(col_name).lower():\n                dynamic_rename_mapping[col_name] = mode\n                break\n\n    df = df[list(dynamic_rename_mapping.keys()) + [\"TIME\"]]\n    df.rename(columns=dynamic_rename_mapping, inplace=True)\n\n    # The first and last rows are not part of the time series and should be deleted.\n    df = df.iloc[1:-1].reset_index(drop=True)\n    mode_columns = list(dynamic_rename_mapping.values())\n\n    # Ensure all mode columns are numeric before scaling\n    for col in mode_columns:\n        df[col] = pd.to_numeric(df[col].replace(\"-\", 0), errors=\"coerce\").fillna(0)\n\n    scaled_generation = df[mode_columns].mul(scaling_factor, axis=0)\n    scaled_generation = pd.concat([df[\"TIME\"], scaled_generation], axis=1)\n    return scaled_generation\n\n\ndef parse_daily_total_production_grid_india_report(\n    content: bytes,\n) -> float:\n    \"\"\"\n    Extract the total production across the whole country from the daily report.\n    Returns it in MWh.\n    \"\"\"\n    generation_df = get_daily_generation_table(content)\n    # Data is in MU=GWh.\n    total_generation = generation_df.loc[\"Total\", \"All India\"]\n    total_generation_numeric = pd.to_numeric(\n        str(total_generation).replace(\"-\", \"0\"), errors=\"coerce\"\n    )\n    total_all_india_generation = total_generation_numeric * 1000\n    return float(total_all_india_generation)\n\n\ndef parse_total_production_15min_grid_india_report(\n    content: bytes,\n) -> float:\n    \"\"\"\n    Computes the total production from the 15-minute data, in MWh.\n    \"\"\"\n    df = pd.read_excel(content, engine=\"xlrd\", header=2, sheet_name=\"TimeSeries\")\n    total_gen_col = \"TOTAL GENERATION\\n(MW)\"\n    df[total_gen_col] = pd.to_numeric(df[total_gen_col], errors=\"coerce\")\n    df[\"15min_energy\"] = df[total_gen_col] / 4\n    total_generation_from_15_min = df[\"15min_energy\"].sum()\n    return float(total_generation_from_15_min)\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Indian parser has a long history. There have been many sources being used, with different formats and different periods of availability.\n    Here we try to resolve how to fetch and parse the production data for the given zone key and target datetime.\n    \"\"\"\n    session = session or Session()\n    if target_datetime is None:\n        _target_datetime = datetime.now(tz=IN_TZ)\n    else:\n        if target_datetime.tzinfo is None:\n            _target_datetime = target_datetime.replace(tzinfo=IN_TZ)\n        else:\n            _target_datetime = target_datetime.astimezone(IN_TZ)\n\n    if _target_datetime > datetime(2024, 11, 4, tzinfo=IN_TZ):\n        # PSP Reports with TimeSeries sheets are only available since 2024/11/04\n        report_date, report_content = fetch_grid_india_report(\n            target_datetime=_target_datetime, session=session\n        )\n        production_data = parse_15m_production_grid_india_report(\n            content=report_content,\n            zone_key=zone_key,\n            target_datetime=report_date,\n        )\n        return production_data\n    elif _target_datetime >= datetime(\n        2023, 4, 1, tzinfo=IN_TZ\n    ) and _target_datetime < datetime(2024, 11, 4, tzinfo=IN_TZ):\n        # PSP Reports are available as spreadsheet since 2023/04/01, but without TimeSeries (15-minute) data.\n        report_date, report_content = fetch_grid_india_report(\n            target_datetime=_target_datetime, session=session\n        )\n        production_data = parse_daily_production_grid_india_report(\n            content=report_content,\n            zone_key=zone_key,\n            target_datetime=report_date,\n        )\n        return production_data\n    elif _target_datetime > START_DATE_RENEWABLE_DATA and _target_datetime < datetime(\n        2023, 4, 1, tzinfo=IN_TZ\n    ):\n        production_data = parse_production_from_cea_npp(\n            zone_key=zone_key,\n            target_datetime=_target_datetime,\n            session=session,\n        )\n        return production_data\n    else:\n        # An alternative here would be to parse the PDF from Grid India.\n        raise ParserException(\n            parser=\"IN.py\",\n            message=f\"{target_datetime}: {zone_key} production data is not available before {START_DATE_RENEWABLE_DATA}\",\n        )\n\n\ndef parse_production_from_cea_npp(\n    zone_key: str,\n    target_datetime: datetime,\n    session: Session = Session(),\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Parses production data from CEA NPP.\n    \"\"\"\n    renewable_production = {}\n    try:\n        renewable_production = fetch_cea_production(\n            zone_key=zone_key,\n            session=session,\n            target_datetime=target_datetime,\n        )\n    except ParserException:\n        logger.warning(\n            f\"{zone_key}: renewable production not available for {target_datetime} - will compute production with conventional production only\"\n        )\n\n    conventional_production = None\n    try:\n        conventional_production = fetch_npp_production(\n            zone_key=zone_key,\n            session=session,\n            target_datetime=target_datetime,\n        )\n    except ParserException:\n        logger.warning(\n            f\"{zone_key}: conventional production not available for {target_datetime} - do not return any production data\"\n        )\n\n    if conventional_production is not None:\n        production = {**conventional_production, **renewable_production}\n        hourly_production_data = daily_to_hourly_production_data(\n            target_datetime=target_datetime,\n            production=production,\n            zone_key=zone_key,\n            logger=logger,\n        )\n    return hourly_production_data.to_list()\n\n\ndef daily_to_hourly_production_data(\n    target_datetime: datetime, production: dict, zone_key: str, logger: Logger\n) -> ProductionBreakdownList:\n    \"\"\"convert daily power production average to hourly values\"\"\"\n    all_hourly_production = ProductionBreakdownList(logger)\n    production_mix = ProductionMix()\n    for mode, value in production.items():\n        production_mix.add_value(mode, value / CONVERSION_DAILY_GWH_TO_HOURLY_MW)\n\n    start_of_day_local = target_datetime.astimezone(IN_TZ).replace(\n        hour=0, minute=0, second=0, microsecond=0\n    )\n    for hour in range(0, 24):\n        all_hourly_production.append(\n            zoneKey=ZoneKey(zone_key),\n            datetime=start_of_day_local + timedelta(hours=hour),\n            production=production_mix,\n            source=GRID_INDIA_SOURCE,\n        )\n    return all_hourly_production\n\n\nif __name__ == \"__main__\":\n    print(fetch_production(target_datetime=datetime(2024, 12, 24), zone_key=\"IN-WE\"))\n    print(fetch_consumption(zone_key=ZoneKey(\"IN-NO\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IN_DL.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime, time\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom .lib import IN, web, zonekey\n\nZONE_INFO = ZoneInfo\n\n# Constant mapping of plant names to type\n_PLANT_NAME_TO_TYPE = {\n    \"CCGT-Bawana\": \"gas\",\n    \"DMSWSL-Dsidc\": \"biomass\",\n    \"EDWPL-Gazipur\": \"biomass\",\n    \"GT\": \"gas\",\n    \"Pragati\": \"gas\",\n    \"TOWMP-Okhla\": \"biomass\",\n    \"TWEPL-TUGLAKABAD\": \"biomass\",\n}\n_POWER_COLUMN_HEADER = \"Actual\"\n_TOTAL_ROW_TITLE = \"Total\"\n\n\ndef fetch_consumption(\n    zone_key: str = \"IN-DL\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Fetch Delhi consumption\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    zonekey.assert_zone_key(zone_key, \"IN-DL\")\n    html = web.get_response_soup(\n        zone_key, \"http://www.delhisldc.org/Redirect.aspx\", session\n    )\n\n    india_date_time = IN.read_datetime_from_span_id(\n        html, \"DynamicData1_LblDate\", \"%d-%b-%Y %I:%M:%S %p\"\n    )\n\n    demand_value = IN.read_value_from_span_id(html, \"DynamicData1_LblLoad\")\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": india_date_time,\n        \"consumption\": demand_value,\n        \"source\": \"delhisldc.org\",\n    }\n\n    return data\n\n\ndef fetch_production(\n    zone_key: str = \"IN-DL\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Fetch Delhi production\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    energy: dict[str, float] = {\"gas\": 0, \"biomass\": 0, \"coal\": 0}\n\n    zonekey.assert_zone_key(zone_key, \"IN-DL\")\n\n    html = web.get_response_soup(\n        zone_key, \"http://www.delhisldc.org/Redirect.aspx?Loc=0804\", session\n    )\n\n    india_time_string = IN.read_text_from_span_id(html, \"ContentPlaceHolder3_ddgenco\")\n    india_time = time.fromisoformat(india_time_string)\n    india_date_time = datetime.combine(datetime.now(IN.ZONE_INFO), india_time).replace(\n        tzinfo=IN.ZONE_INFO\n    )\n\n    prod_table = html.find(\"table\", {\"id\": \"ContentPlaceHolder3_dgenco\"})\n    prod_rows = prod_table.findAll(\"tr\")\n\n    # Determine the index of the column that contains the actual power values\n    header_row = prod_rows[0]\n    column_headers = [cell.text for cell in header_row.findAll(\"td\")]\n    try:\n        value_column_index = column_headers.index(_POWER_COLUMN_HEADER)\n    except ValueError as e:\n        raise ValueError(\n            f\"Could not find a column with header '{_POWER_COLUMN_HEADER}' in the scraped HTML table\"\n        ) from e\n\n    for row in prod_rows[1:]:\n        cells = row.findAll(\"td\")\n        plant_name = cells[0].text\n        if plant_name == _TOTAL_ROW_TITLE:\n            continue\n        try:\n            plant_type = _PLANT_NAME_TO_TYPE[plant_name]\n        except KeyError as e:\n            raise KeyError(\n                f\"Unknown plant '{plant_name}'; manually add the type of this plant to `_PLANT_NAME_TO_TYPE`\"\n            ) from e\n        power = max(0.0, float(cells[value_column_index].text))\n        energy[plant_type] += power\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": india_date_time,\n        \"production\": energy,\n        \"source\": \"delhisldc.org\",\n    }\n\n    return data\n\n\nif __name__ == \"__main__\":\n    session = Session()\n    print(fetch_production(\"IN-DL\", session))\n    print(fetch_consumption(\"IN-DL\", session))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IN_EA.py",
    "content": "from collections.abc import Callable\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import ExchangeList\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\nIN_WE_PROXY = \"https://in-proxy-jfnx5klx2a-el.a.run.app\"\nHOST = \"https://app.erldc.in\"\nINTERNATIONAL_EXCHANGES_URL = \"{proxy}/api/pspreportpsp/Get/pspreport_psp_transnationalexchange/GetByTwoDate?host={host}&firstDate={target_date}&secondDate={target_date}\"\nINTERREGIONAL_EXCHANGES_URL = \"{proxy}/api/pspreportpsp/Get/pspreport_psp_interregionalexchanges/GetByTwoDate?host={host}&firstDate={target_date}&secondDate={target_date}\"\nIN_EA_TZ = ZoneInfo(\"Asia/Kolkata\")\n\nINTERREGIONAL_EXCHANGES = {\n    ZoneKey(\"IN-EA->IN-NO\"): \"Import/Export between EAST REGION and NORTH REGION\",\n    ZoneKey(\"IN-EA->IN-NE\"): \"Import/Export between EAST REGION and NORTH_EAST REGION\",\n    ZoneKey(\"IN-EA->IN-SO\"): \"Import/Export between EAST REGION and SOUTH REGION\",\n    ZoneKey(\"IN-EA->IN-WE\"): \"Import/Export between EAST REGION and WEST REGION\",\n}\nINTERRNATIONAL_EXCHANGES = {\n    ZoneKey(\"BT->IN-EA\"): \"BHUTAN\",\n    ZoneKey(\"IN-EA->NP\"): \"NEPAL\",\n    ZoneKey(\"BD->IN-EA\"): \"BANGLADESH\",\n}\nMAPPING = {\n    **INTERREGIONAL_EXCHANGES,\n    **INTERRNATIONAL_EXCHANGES,\n}\n\n\ndef get_fetch_function(\n    exchange_key: ZoneKey,\n) -> tuple[str, Callable[[list, ZoneKey, Logger], ExchangeList]]:\n    \"\"\"Get the url, the lookup key and the extract function for the exchange.\"\"\"\n    if exchange_key not in MAPPING:\n        raise ParserException(\n            \"IN_EA.py\",\n            f\"Unsupported exchange key {exchange_key}\",\n            zone_key=exchange_key,\n        )\n    if exchange_key in INTERRNATIONAL_EXCHANGES:\n        return (\n            INTERNATIONAL_EXCHANGES_URL,\n            extract_international_exchanges,\n        )\n    return (\n        INTERREGIONAL_EXCHANGES_URL,\n        extract_interregional_exchanges,\n    )\n\n\ndef extract_international_exchanges(\n    raw_data: list, exchange_key: ZoneKey, logger: Logger\n) -> ExchangeList:\n    exchanges = ExchangeList(logger)\n    zone_data = [item for item in raw_data if item[\"Region\"] == MAPPING[exchange_key]][\n        0\n    ]\n    exchanges.append(\n        zoneKey=exchange_key,\n        datetime=datetime.strptime(zone_data[\"Date\"], \"%Y-%m-%d\").replace(\n            tzinfo=IN_EA_TZ\n        ),\n        netFlow=float(zone_data[\"DayAverageMW\"]),\n        source=\"erldc.in\",\n    )\n    return exchanges\n\n\ndef extract_interregional_exchanges(\n    raw_data: list, exchange_key: ZoneKey, logger: Logger\n) -> ExchangeList:\n    exchanges = ExchangeList(logger)\n    zone_data = [item for item in raw_data if item[\"Type\"] == MAPPING[exchange_key]]\n    imports = sum(float(item[\"ImportMW\"]) for item in zone_data)\n    exports = sum(float(item[\"ExportMW\"]) for item in zone_data)  # always negative\n    exchanges.append(\n        zoneKey=exchange_key,\n        datetime=datetime.strptime(zone_data[0][\"Date\"], \"%Y-%m-%d\").replace(\n            tzinfo=IN_EA_TZ\n        ),\n        netFlow=imports + exports,\n        source=\"erldc.in\",\n    )\n    return exchanges\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"collects average daily exchanges for ERLC\"\"\"\n    if target_datetime is None:\n        # 1 day delay observed\n        target_datetime = datetime.now(tz=IN_EA_TZ).replace(\n            hour=0, minute=0, second=0\n        ) - timedelta(days=1)\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    target_date = target_datetime.strftime(\"%Y-%m-%d\")\n    url, extract_function = get_fetch_function(sorted_zone_keys)\n    resp = session.get(\n        url=url.format(\n            proxy=IN_WE_PROXY,\n            host=HOST,\n            target_date=target_date,\n        )\n    )\n    if not resp.ok:\n        raise ParserException(\n            parser=\"IN_EA.py\",\n            message=f\"{target_datetime}: {sorted_zone_keys} data is not available : [{resp.status_code}]\",\n            zone_key=sorted_zone_keys,\n        )\n    data = resp.json()\n    exchanges = extract_function(data, sorted_zone_keys, logger)\n    return exchanges.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IN_HP.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Parser for Himachal Pradesh (Indian State).\"\"\"\n\nfrom datetime import datetime\nfrom enum import Enum\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\n# This URL is called from within the\n# https://hpsldc.com/intra-state-power-transaction/\n# page to load the data.\nDATA_URL = \"https://hpsldc.com/wp-admin/admin-ajax.php\"\nZONE_KEY = \"IN-HP\"\nTZ = ZoneInfo(\"Asia/Kolkata\")\n\n\nclass GenType(Enum):\n    \"\"\"\n    Enum for plant generation types found in the data.\n    Enum values are the keys for the production dictionary returned from fetch_production().\n    \"\"\"\n\n    HYDRO = \"hydro\"\n    UNKNOWN = \"unknown\"\n\n\n# Map of plant names (as given in data source) to their type.\n# Source for types is http://meritindia.in/state-data/himachal-pradesh\n# (click 'Show details' at the bottom) or the link above/next to the\n# relevant entry if there is no record in meritindia.\n# Corroborating source: https://hpaldc.org/index.asp?pg=powStn\n#\n# Total plant capacity as manually calculated from the data source:\n# GENERATION OF HP(Z): 992.45 MW Hydro, 608.26 MW Unknown.\n# (Unknown capacity value not given in data, estimated as 135% of actual generation\n# as this is the average ratio for plants with known capacity).\n# (B1)ISGS(HPSLDC WEB PORTAL): 4483.02 MW Hydro.\n# Total (for zones/IN_HP.yaml): 5475.47 MW Hydro, 608.26 MW Unknown.\nPLANT_NAMES_TO_TYPES = {\n    ### Plants in GENERATION OF HP(Z) table ###\n    # Listed as ISGS in type source but state in data source\n    \"BASPA(3X100MW)\": GenType.HYDRO,\n    \"BHABA(3X40MW)\": GenType.HYDRO,\n    \"GIRI(2X30MW)\": GenType.HYDRO,\n    \"LARJI(3X42MW)\": GenType.HYDRO,\n    \"BASSI(4X16.5MW)\": GenType.HYDRO,\n    # http://globalenergyobservatory.org/geoid/44638\n    \"MALANA(2X43MW)\": GenType.HYDRO,\n    \"ANDHRA(3X5.65MW)\": GenType.HYDRO,\n    \"GHANVI(2X11.25MW)\": GenType.HYDRO,  # GANVI in type source\n    # https://www.ejatlas.org/conflict/kashang-hydroelectricity-project\n    \"KASHANG(3X65MW)\": GenType.HYDRO,\n    # https://cdm.unfccc.int/Projects/DB/RWTUV1354641854.75/view\n    \"Sawra Kuddu (3x37MW)\": GenType.HYDRO,\n    \"MICROP/HMONITORED(HPSEBL)\": GenType.UNKNOWN,  # No type source\n    \"IPPsP/HMONITORED\": GenType.UNKNOWN,  # No type source\n    \"MICROP/HUNMONITORED\": GenType.UNKNOWN,  # No type source\n    ### Plants in (B1)ISGS(HPSLDC WEB PORTAL) table ###\n    \"BSIUL\": GenType.HYDRO,  # BAIRASIUL HEP in type source.\n    \"CHAMERA1\": GenType.HYDRO,\n    \"CHAMERA2\": GenType.HYDRO,\n    \"CHAMERA3\": GenType.HYDRO,\n    \"PARBATI3\": GenType.HYDRO,\n    \"NJPC\": GenType.HYDRO,  # NATHPA JHAKRI HEP in type source.\n    \"RAMPUR\": GenType.HYDRO,\n    \"KOLDAM\": GenType.HYDRO,\n}\n\n\ndef fetch_production(\n    zone_key: str = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the last known production mix (in MW) of Himachal Pradesh (India)\"\"\"\n    r = session or Session()\n    if target_datetime is None:\n        url = DATA_URL\n    else:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n    res = r.post(url, {\"action\": \"intra_state_power_transaction\"})\n    assert res.status_code == 200, (\n        \"Exception when fetching production for \"\n        \"{zone_key}: {res.status_code} error when calling url={url}\"\n    )\n    soup = BeautifulSoup(res.text, \"html.parser\")\n    return {\n        \"zoneKey\": ZONE_KEY,\n        \"datetime\": datetime.now(tz=TZ),\n        \"production\": combine_gen(\n            get_state_gen(soup, logger), get_isgs_gen(soup, logger)\n        ),\n        \"source\": \"hpsldc.com\",\n    }\n\n\ndef get_state_gen(soup, logger: Logger):\n    \"\"\"\n    Gets the total generation by type from state powerplants (MW).\n    Data is from the table titled GENERATION OF HP(Z).\n    \"\"\"\n    table_name = \"GENERATION OF HP(Z)\"\n    gen = {GenType.HYDRO.value: 0.0, GenType.UNKNOWN.value: 0.0}\n    # Read all rows except the last (Total).\n    for row in get_table_rows(soup, \"table_5\", table_name)[:-1]:\n        try:\n            cols = row.find_all(\"td\")\n            # Column 1: plant name, column 2: current generation.\n            gen_type = PLANT_NAMES_TO_TYPES[cols[0].text]\n            gen[gen_type.value] += float(cols[1].text)\n        except (AttributeError, KeyError, IndexError, ValueError):\n            logger.error(\n                f\"Error importing data from row: {row}\", extra={\"key\": ZONE_KEY}\n            )\n    return gen\n\n\ndef get_isgs_gen(soup, logger: Logger):\n    \"\"\"\n    Gets the total generation by type from ISGS powerplants (MW).\n    ISGS means Inter-State Generating Station: one owned by multiple states.\n    Data is from the table titled (B1)ISGS(HPSLDC WEB PORTAL).\n    \"\"\"\n    table_name = \"(B1)ISGS(HPSLDC WEB PORTAL)\"\n    gen = {GenType.HYDRO.value: 0.0, GenType.UNKNOWN.value: 0.0}\n    # Read all rows except the first (headers) and last two (OTHERISGS and\n    # Total).\n    for row in get_table_rows(soup, \"table_4\", table_name)[1:-2]:\n        try:\n            cols = row.find_all(\"td\")\n            if not cols[0].has_attr(\"class\"):\n                # Ignore first column (COMPANY), which only has cells for some\n                # rows (using rowspan).\n                del cols[0]\n            # Once COMPANY column is excluded, we have\n            # column 1: plant name, column 3: current generation.\n            gen_type = PLANT_NAMES_TO_TYPES[cols[0].text]\n            gen[gen_type.value] += float(cols[2].text)\n        except (AttributeError, KeyError, IndexError, ValueError):\n            logger.error(\n                f\"Error importing data from row: {row}\", extra={\"key\": ZONE_KEY}\n            )\n    return gen\n\n\ndef get_table_rows(soup, container_class, table_name):\n    \"\"\"Gets the table rows in the div identified by the provided class.\"\"\"\n    try:\n        rows = soup.find(\"div\", class_=container_class).find(\"tbody\").find_all(\"tr\")\n        if len(rows) == 0:\n            raise ValueError\n        return rows\n    except (AttributeError, ValueError) as err:\n        raise Exception(f\"Error reading table {table_name}: {err}\") from err\n\n\ndef combine_gen(gen1, gen2):\n    \"\"\"\n    Combines two dictionaries of generation data.\n\n    Currently only does Hydro and Unknown as there are no other types in the\n    data source.\n    \"\"\"\n    return {\n        GenType.HYDRO.value: round(\n            gen1[GenType.HYDRO.value] + gen2[GenType.HYDRO.value], 2\n        ),\n        GenType.UNKNOWN.value: round(\n            gen1[GenType.UNKNOWN.value] + gen2[GenType.UNKNOWN.value], 2\n        ),\n    }\n\n\ndef fetch_consumption(\n    zone_key: str = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger=getLogger(__name__),\n):\n    # Not currently implemented as this function is not used by the map,\n    # but if required the data is available as 'Demand Met' on\n    # https://hpsldc.com/\n    raise NotImplementedError(\"Fetch production not implemented\")\n\n\ndef fetch_price(\n    zone_key: str = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger=getLogger(__name__),\n):\n    # The only price data available in the source is 'DSM Rate'.\n    # I.e. Demand side management rate.\n    # I believe (though I'm not sure) that this refers to a payment\n    # made by the grid to consumers who reduce their consumption at times\n    # of high demand, therefore it is not appropriate for this function.\n    raise NotImplementedError(\"No price data available\")\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IN_KA.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\n\nfrom requests import Session\n\nfrom .lib import IN, web, zonekey\nfrom .lib.exceptions import ParserException\n\n\ndef fetch_consumption(\n    zone_key: str = \"IN-KA\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Fetch Karnataka consumption\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    zonekey.assert_zone_key(zone_key, \"IN-KA\")\n    html = web.get_response_soup(zone_key, \"https://kptclsldc.in/Default.aspx\", session)\n\n    india_date_time = IN.read_datetime_from_span_id(html, \"Label6\", \"%d/%m/%Y %H:%M\")\n\n    demand_value = IN.read_value_from_span_id(html, \"Label5\")\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": india_date_time,\n        \"consumption\": demand_value,\n        \"source\": \"kptclsldc.in\",\n    }\n\n    return data\n\n\ndef fetch_production(\n    zone_key: str = \"IN-KA\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Fetch Karnataka  production\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    zonekey.assert_zone_key(zone_key, \"IN-KA\")\n\n    html = web.get_response_soup(\n        zone_key, \"https://kptclsldc.in/StateGen.aspx\", session\n    )\n\n    india_date_time = IN.read_datetime_from_span_id(\n        html, \"lbldate\", \"%d/%m/%Y %H:%M:%S\"\n    )\n\n    # RTPS Production: https://en.wikipedia.org/wiki/Raichur_Thermal_Power_Station\n    rtps_value = IN.read_value_from_span_id(html, \"lblrtptot\")\n\n    # BTPS Production: https://en.wikipedia.org/wiki/Bellary_Thermal_Power_station\n    btps_value = IN.read_value_from_span_id(html, \"lblbtptot\")\n\n    # YTPS Production: https://en.wikipedia.org/wiki/Yermarus_Thermal_Power_Station\n    ytps_value = IN.read_value_from_span_id(html, \"ytptot\")\n\n    # UPCL Production: https://en.wikipedia.org/wiki/Udupi_Power_Plant\n    upcl_value = IN.read_value_from_span_id(html, \"lblupctot\")\n\n    # JINDAl Production: https://en.wikipedia.org/wiki/JSW_Vijayanagar_Power_Station\n    jindal_value = IN.read_value_from_span_id(html, \"lbljintot\")\n\n    # Coal Production\n    coal_value = rtps_value + btps_value + ytps_value + upcl_value + jindal_value\n\n    # Sharavati Production: Sharavati  Hydroelectric\n    sharavati_value = IN.read_value_from_span_id(html, \"lblshvytot\")\n\n    # Nagjhari Production: Kalinadi-Nagjhari Hydroelectric\n    nagjhari_value = IN.read_value_from_span_id(html, \"lblngjtot\")\n\n    # Varahi Production: https://en.wikipedia.org/wiki/Varahi_River#Varahi_Hydro-electric_Project\n    varahi_value = IN.read_value_from_span_id(html, \"lblvrhtot\")\n\n    # Kodsalli Production: Kalinadi Kodasalli Hydroelectric\n    kodsalli_value = IN.read_value_from_span_id(html, \"lblkdsltot\")\n\n    # Kadra Production: https://en.wikipedia.org/wiki/Kadra_Dam\n    kadra_value = IN.read_value_from_span_id(html, \"lblkdrtot\")\n\n    # GERUSOPPA production: Gerusoppa Dam\n    gerusoppa_value = IN.read_value_from_span_id(html, \"lblgrsptot\")\n\n    # JOG production: https://en.wikipedia.org/wiki/Jog_Falls\n    jog_value = IN.read_value_from_span_id(html, \"lbljogtot\")\n\n    # LPH Production: Linganamakki Dam\n    lph_value = IN.read_value_from_span_id(html, \"lbllphtot\")\n\n    # Supa production: https://en.wikipedia.org/wiki/Supa_Dam\n    supa_value = IN.read_value_from_span_id(html, \"lblsupatot\")\n\n    # SHIMSHA: https://en.wikipedia.org/wiki/Shimsha#Power_generation\n    shimsha_value = IN.read_value_from_span_id(html, \"lblshimtot\")\n\n    # SHIVASAMUDRA: https://en.wikipedia.org/wiki/Shivanasamudra_Falls#Power_generation\n    shivasamudra_value = IN.read_value_from_span_id(html, \"lblshivtot\")\n\n    # MANIDAM: Mani Dam Hydroelectric\n    manidam_value = IN.read_value_from_span_id(html, \"lblmanitot\")\n\n    # MUNRABAD: Munirabad Hydroelectric\n    munrabad_value = IN.read_value_from_span_id(html, \"lblmbdtot\")\n\n    # BHADRA: https://en.wikipedia.org/wiki/Bhadra_Dam\n    bhadra_value = IN.read_value_from_span_id(html, \"lblbdratot\")\n\n    # GHATAPRABHA: Ghataprabha Hydroelectric\n    ghataprabha_value = IN.read_value_from_span_id(html, \"lblgtprtot\")\n\n    # ALMATTI: https://en.wikipedia.org/wiki/Almatti_Dam\n    almatti_value = IN.read_value_from_span_id(html, \"lblalmttot\")\n\n    # CGS (Central Generating Stations) Production\n    # TODO: Search CGS production type\n    cgs_value = IN.read_value_from_span_id(html, \"lblcgs\")\n\n    # NCEP (Non-Conventional Energy Production)\n    ncep_html = web.get_response_soup(\n        zone_key, \"https://kptclsldc.in/StateNCEP.aspx\", session\n    )\n    ncep_date_time = IN.read_datetime_from_span_id(\n        ncep_html, \"Label1\", \"%d/%m/%Y %H:%M:%S\"\n    )\n\n    # Check ncep date is similar than state gen date\n    if abs((india_date_time - ncep_date_time).total_seconds()) > 600:\n        raise ParserException(\"IN-KA\", \"NCEP or State datetime is not valid\")\n\n    # cogen type is sugarcane bagasee. Proof in Issue #1867\n    cogen_value = IN.read_value_from_span_id(ncep_html, \"lbl_tc\")\n\n    biomass_value = IN.read_value_from_span_id(ncep_html, \"lbl_tb\")\n\n    # cogen_value is generated from sugarcane bagasse\n    biomass_value += cogen_value\n\n    mini_hydro_value = IN.read_value_from_span_id(ncep_html, \"lbl_tm\")\n\n    wind_value = IN.read_value_from_span_id(ncep_html, \"lbl_tw\")\n\n    solar_value = IN.read_value_from_span_id(ncep_html, \"lbl_kar_slr\")\n\n    # Hydro production\n    hydro_value = (\n        sharavati_value\n        + nagjhari_value\n        + varahi_value\n        + kodsalli_value\n        + kadra_value\n        + gerusoppa_value\n        + jog_value\n        + lph_value\n        + supa_value\n        + shimsha_value\n        + shivasamudra_value\n        + manidam_value\n        + munrabad_value\n        + bhadra_value\n        + ghataprabha_value\n        + almatti_value\n        + mini_hydro_value\n    )\n\n    # Unknown production\n    unknown_value = cgs_value\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": india_date_time,\n        \"production\": {\n            \"biomass\": biomass_value,\n            \"coal\": coal_value,\n            \"gas\": 0.0,\n            \"hydro\": hydro_value,\n            \"nuclear\": 0.0,\n            \"oil\": 0.0,\n            \"solar\": solar_value,\n            \"wind\": wind_value,\n            \"geothermal\": 0.0,\n            \"unknown\": unknown_value,\n        },\n        \"storage\": {\"hydro\": 0.0},\n        \"source\": \"kptclsldc.in\",\n    }\n\n    return data\n\n\nif __name__ == \"__main__\":\n    session = Session()\n    print(fetch_production(\"IN-KA\", session))\n    print(fetch_consumption(\"IN-KA\", session))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IN_MH.py",
    "content": "from datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport cv2\nimport numpy as np\nimport pytesseract\nfrom imageio import imread\nfrom PIL import Image, ImageOps\nfrom requests import Session\n\nfrom .lib.exceptions import ParserException\n\nurl = \"https://mahasldc.in/wp-content/reports/sldc/mvrreport3.jpg\"\n\n# specifies locations of data in the image\n# (x,y,x,y) = upper left, lower right corner of rectangle\n\nlocations = {\n    \"MS WIND\": {\"label\": (595, 934, 692, 961), \"value\": (785, 934, 844, 934 + 25)},\n    \"SOLAR TTL\": {\"label\": (592, 577, 715, 605), \"value\": (772, 561, 814, 561 + 25)},\n    \"MS SOLAR\": {\"label\": (595, 963, 705, 984), \"value\": (785, 955, 848, 955 + 25)},\n    \"THERMAL\": {\"label\": (407, 982, 502, 1004), \"value\": (516, 987, 581, 987 + 25)},\n    \"GAS\": {\"label\": (403, 1033, 493, 1056), \"value\": (515, 1042, 582, 1042 + 25)},\n    \"HYDRO\": {\"label\": (589, 472, 666, 496), \"value\": (753, 451, 813, 451 + 25)},\n    \"TPC HYD.\": {\"label\": (926, 525, 1035, 554), \"value\": (1105, 524, 1173, 524 + 25)},\n    \"TPC THM.\": {\"label\": (924, 578, 1030, 604), \"value\": (1088, 581, 1173, 581 + 25)},\n    \"OTHR+SMHYD\": {\n        \"label\": (594, 1009, 730, 1031),\n        \"value\": (789, 1009, 846, 1009 + 25),\n    },\n    \"COGEN\": {\"label\": (594, 989, 670, 1011), \"value\": (789, 982, 844, 982 + 25)},\n    \"AEML GEN.\": {\"label\": (922, 687, 1041, 716), \"value\": (1081, 692, 1175, 692 + 25)},\n    \"CS GEN. TTL.\": {\n        \"label\": (1341, 998, 1492, 1029),\n        \"value\": (1549, 1030, 1616, 1030 + 25),\n    },\n    \"KK’ PARA\": {\"label\": (1346, 708, 1457, 730), \"value\": (1560, 707, 1626, 707 + 25)},\n    \"TARPR PH-I\": {\n        \"label\": (1341, 730, 1484, 757),\n        \"value\": (1556, 733, 1626, 733 + 25),\n    },\n    \"TARPR PH-II\": {\n        \"label\": (1341, 750, 1490, 782),\n        \"value\": (1556, 757, 1626, 757 + 25),\n    },\n    \"SSP\": {\"label\": (1341, 800, 1401, 823), \"value\": (1557, 802, 1626, 802 + 25)},\n    \"RGPPL\": {\"label\": (1343, 822, 1421, 849), \"value\": (1560, 823, 1620, 823 + 25)},\n    \"GANDHAR\": {\"label\": (1341, 660, 1446, 689), \"value\": (1562, 661, 1623, 661 + 25)},\n    \"CS EXCH\": {\"label\": (920, 303, 1021, 338), \"value\": (1090, 309, 1172, 309 + 25)},\n    # STATE DEMAND (including Mumbai!)\n    \"DEMAND\": {\"label\": (932, 1003, 1021, 1030), \"value\": (1080, 996, 1167, 996 + 25)},\n    # RE TTL\n    \"TTL\": {\"label\": (597, 1035, 663, 1056), \"value\": (784, 1032, 845, 1032 + 25)},\n    \"TTL (IPP/CPP+RE)\": {\n        \"label\": (594, 1072, 765, 1098),\n        \"value\": (786, 1068, 849, 1068 + 25),\n    },\n    \"PIONEER\": {\"label\": (592, 910, 694, 929), \"value\": (800, 885, 844, 885 + 25)},\n}\n\ngeneration_map = {\n    \"biomass\": {\"add\": [\"COGEN\"], \"subtract\": []},\n    \"coal\": {\n        \"add\": [\n            \"THERMAL\",\n            \"TTL (IPP/CPP+RE)\",\n            \"TPC THM.\",\n            \"CS GEN. TTL.\",\n            \"AEML GEN.\",\n            \"SOLAR TTL\",\n        ],\n        \"subtract\": [\n            \"TTL\",\n            \"PIONEER\",\n            \"SSP\",\n            \"RGPPL\",\n            \"TARPR PH-I\",\n            \"TARPR PH-II\",\n            \"KK’ PARA\",\n            \"GANDHAR\",\n        ],\n    },\n    \"gas\": {\"add\": [\"GAS\", \"PIONEER\", \"GANDHAR\", \"RGPPL\"], \"subtract\": []},\n    \"hydro\": {\"add\": [\"HYDRO\", \"TPC HYD.\", \"SSP\"], \"subtract\": []},\n    \"nuclear\": {\"add\": [\"TARPR PH-I\", \"TARPR PH-II\", \"KK’ PARA\"], \"subtract\": []},\n    \"solar\": {\"add\": [\"MS SOLAR\"], \"subtract\": []},\n    \"wind\": {\"add\": [\"MS WIND\"], \"subtract\": []},\n    \"unknown\": {\"add\": [\"OTHR+SMHYD\"], \"subtract\": []},\n}\n\n# list of values that belong to Central State production\nCS = [\n    \"SSP\",\n    \"RGPPL\",\n    \"TARPR PH-I\",\n    \"TARPR PH-II\",\n    \"KK’ PARA\",\n    \"GANDHAR\",\n    \"CS GEN. TTL.\",\n]\n\n\n# converts image into a black and white\ndef RGBtoBW(pil_image):\n    # pylint: disable=no-member\n    image = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2GRAY)\n    image = cv2.threshold(image, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]\n    return Image.fromarray(image)\n\n\n# returns image section\ndef read_image_sections(location, source):\n    img = source.crop(location)\n    img = RGBtoBW(img)\n    img = ImageOps.invert(img)\n    return img\n\n\n# TODO: this function actually fetches consumption data\ndef fetch_production(\n    zone_key: str = \"IN-MH\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    dt = datetime.now(tz=ZoneInfo(\"Asia/Kolkata\")).replace(\n        minute=0, second=0, microsecond=0\n    )\n\n    data = {\n        \"zoneKey\": \"IN-MH\",\n        \"datetime\": dt,\n        \"production\": {\n            \"biomass\": 0.0,\n            \"coal\": 0.0,\n            \"gas\": 0.0,\n            \"hydro\": 0.0,\n            \"nuclear\": 0.0,\n            \"solar\": 0.0,\n            \"wind\": 0.0,\n            \"unknown\": 0.0,\n        },\n        \"storage\": {},\n        \"source\": \"mahasldc.in\",\n    }\n\n    image = imread(url)\n    # In certain scenario, the URL returns a blank image. Let's verify if the image was read is of proper size\n    if image.size == 0:\n        raise ParserException(\n            \"IN_MH.py\",\n            \"Invalid data read from the source, the source might not be available\",\n        )\n\n    image = Image.fromarray(image)  # create PIL image\n\n    # Read small images for each loaction's bounding box from the main image\n    imgs = [read_image_sections(loc[\"value\"], image) for loc in locations.values()]\n\n    values = {}\n\n    # for each location, convert the image to a float integer and add it in the map corresponding to the key\n    for index, key in enumerate(locations):\n        digit_text = pytesseract.image_to_string(\n            imgs[index], lang=\"digits_comma\", config=\"--psm 7\"\n        )\n        try:\n            val = float(digit_text)\n        except ValueError:\n            # If the image cannot be converted to a valid number, log an error but do not break the parser\n            val = 0\n            logger.error(f\"Error reading value for key {key}, value read {digit_text}\")\n        values[key] = max(val, 0)\n\n    logger.debug(\"values %s\", values)\n\n    # fraction of central state production that is exchanged with Maharashtra\n    share = round(values[\"CS EXCH\"] / values[\"CS GEN. TTL.\"], 2)\n\n    for production_type, plants in generation_map.items():\n        for plant in plants[\"add\"]:\n            fac = (\n                share if plant in CS else 1\n            )  # add only a fraction of central state plant consumption\n            data[\"production\"][production_type] += fac * values[plant]\n        for plant in plants[\"subtract\"]:\n            fac = share if plant in CS else 1\n            data[\"production\"][production_type] -= fac * values[plant]\n\n    # Sum over all production types is expected to equal the total demand\n    demand_diff = sum(data[\"production\"].values()) - values[\"DEMAND\"]\n    assert abs(demand_diff) < 30, (\n        f\"Production types do not add up to total demand. Difference: {round(demand_diff, 2)}\"\n    )\n\n    return data\n\n\nif __name__ == \"__main__\":\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IN_PB.py",
    "content": "#!/usr/bin/env python3\n\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport requests\nfrom requests import Session\n\nGENERATION_URL = \"https://sldcapi.pstcl.org/wsDataService.asmx/pbGenData2\"\nDATE_URL = \"https://sldcapi.pstcl.org/wsDataService.asmx/dynamicData\"\nZONE_INFO = ZoneInfo(\"Asia/Kolkata\")\n\nGENERATION_MAPPING = {\n    \"totalHydro\": \"hydro\",\n    \"totalThermal\": \"coal\",\n    \"totalIpp\": \"coal\",\n    \"resSolar\": \"solar\",\n    \"resNonSolar\": \"biomass\",\n}\n\n\ndef fetch_production(\n    zone_key: str = \"IN-PB\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known production mix (in MW) of a given zone.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\n            \"The IN-PB production parser is not yet able to parse past dates\"\n        )\n\n    s = session or Session()\n    data_req = s.get(GENERATION_URL)\n    timestamp_req = s.get(DATE_URL)\n\n    raw_data = data_req.json()\n    timestamp_data = timestamp_req.json()\n    dt = datetime.strptime(timestamp_data[\"updateDate\"], \"%d-%m-%Y %H:%M:%S\").replace(\n        tzinfo=ZONE_INFO\n    )\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": dt,\n        \"production\": {\n            \"hydro\": 0.0,\n            \"coal\": 0.0,\n            \"biomass\": 0.0,\n            \"solar\": 0.0,\n        },\n        \"storage\": {},\n        \"source\": \"punjasldc.org\",\n    }\n\n    for from_key, to_key in GENERATION_MAPPING.items():\n        data[\"production\"][to_key] += max(0, raw_data[from_key][\"value\"])\n\n    return [data]\n\n\ndef fetch_consumption(\n    zone_key: str = \"IN-PB\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the last known consumption (in MW) of a given zone.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\n            \"The IN-PB consumption parser is not yet able to parse past dates\"\n        )\n\n    s = session or requests.Session()\n    req = s.get(GENERATION_URL)\n    raw_data = req.json()\n\n    consumption = float(raw_data[\"grossGeneration\"][\"value\"])\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": datetime.now(tz=ZONE_INFO),\n        \"consumption\": consumption,\n        \"source\": \"punjasldc.org\",\n    }\n\n    return data\n\n\nif __name__ == \"__main__\":\n    print(fetch_production(\"IN-PB\"))\n    print(fetch_consumption(\"IN-PB\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IN_UT.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom .lib import web\n\n# IMPORTANT: This parser is as of December 2024 not functional, and the data is\n#            currently very unreliable or not available at all - in both an old\n#            and new URL.\n#\n#            The parser seems based on scraping\n#            http://uksldc.in/real-time-data.php, but this seems to have\n#            migrated to the URL https://uksldc.in/real-time-data along with\n#            some HTML changes making the parser broken for using an old URL and\n#            trying to scrape it in the same way even though there have been\n#            HTML changes.\n#\n#            Internet archive ref: https://web.archive.org/web/20180203084712/https://uksldc.in/real-time-data.php\n#\nENDPOINT = \"http://uksldc.in/real-time-data.php\"\nZONE_INFO = ZoneInfo(\"Asia/Kolkata\")\n\nINTERCONNECTIONS = {\n    \"IN-UP->IN-UT\": [\n        {\"name\": \"400KV MORADABAD-KASHIPUR\", \"direction\": 1},\n        {\"name\": \"400KV KASHIPUR-BARIELY 2\", \"direction\": -1},\n        {\"name\": \"400KV KASHIPUR-BARIELY 1\", \"direction\": -1},\n        {\"name\": \"400 KV POHANA-MUZZAFFARNAGAR\", \"direction\": -1},\n        {\"name\": \"220KV ROORKEE-NARA\", \"direction\": -1},\n        {\"name\": \"220KV KHODRI-SHARANPUR2\", \"direction\": -1},\n        {\"name\": \"220KV KHODRI-SHARANPUR1\", \"direction\": -1},\n        {\"name\": \"220KV BAREILLY-PANTNAGAR\", \"direction\": 1},\n        {\"name\": \"132KV SITARGANJ-DOHANA\", \"direction\": -1},\n        {\"name\": \"132KV RAMGANGA-DHAMPUR\", \"direction\": -1},\n        {\"name\": \"132KV MAHUAKHEDAGANJ-THAKURDWARA\", \"direction\": -1},\n        {\"name\": \"132KV KHATIMA-PILIBHIT\", \"direction\": -1},\n    ],\n    \"IN-HP->IN-UT\": [\n        {\"name\": \"220KV KHODRI-MAJRI\", \"direction\": -1},\n        {\"name\": \"132KV GIRBATTAI-KULHAL\", \"direction\": 1},\n    ],\n}\n\n\ndef get_connection(soup, connection_name):\n    cells = soup.find_all(\"td\")\n    for cell in cells:\n        if cell.text == connection_name:\n            return float(cell.find_next_sibling().text)\n    return 0\n\n\ndef get_datetime(soup, zone_key, logger):\n    paras = soup.find_all(\"p\")\n    for para in paras:\n        para_text = para.text.strip()\n        if \"Last Updated: \" in para_text:\n            dt_string = para_text[len(\"Last updated: \") :]\n            return datetime.strptime(dt_string, \"%d-%m-%Y %H:%M:%S\").replace(\n                tzinfo=ZONE_INFO\n            )\n    logger.warning(\"Datetime could not be read from webpage.\", extra={\"key\": zone_key})\n    return None\n\n\ndef get_production_values(soup):\n    production = {}\n    for cell in soup.find_all(\"td\"):\n        cell_text = cell.text.strip()\n        if cell_text == \"HYDRO Total\":\n            production[\"hydro\"] = float(cell.find_next_sibling().text)\n        elif cell_text == \"GAS Total\":\n            production[\"gas\"] = float(cell.find_next_sibling().text)\n\n    return production\n\n\ndef fetch_exchange(\n    zone_key1: str = \"IN-UP\",\n    zone_key2: str = \"IN-UT\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    soup = web.get_response_soup(zone_key1, ENDPOINT)\n    dt = get_datetime(soup, zone_key1, logger)\n\n    sorted_zone_keys = sorted([zone_key1, zone_key2])\n    sorted_zone_keys = f\"{sorted_zone_keys[0]}->{sorted_zone_keys[1]}\"\n\n    connections = INTERCONNECTIONS.get(sorted_zone_keys)\n    if connections is None:\n        return\n\n    exchange_value = 0\n    for connection in connections:\n        connection_value = get_connection(soup, connection[\"name\"])\n        connection_value *= connection[\"direction\"]\n        exchange_value += connection_value\n\n    data = {\n        \"datetime\": dt,\n        \"netFlow\": exchange_value,\n        \"sortedZoneKeys\": sorted_zone_keys,\n        \"source\": \"uksldc.in\",\n    }\n\n    return data\n\n\ndef fetch_production(\n    zone_key: str = \"IN-UT\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    soup = web.get_response_soup(zone_key, ENDPOINT)\n    dt = get_datetime(soup, zone_key, logger)\n    production = get_production_values(soup)\n\n    data = {\n        \"zoneKey\": \"IN-UT\",\n        \"datetime\": dt,\n        \"production\": production,\n        \"source\": \"uksldc.in\",\n    }\n\n    return data\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_exchange(IN-HP, IN-UT) ->\")\n    print(fetch_exchange(\"IN-HP\", \"IN-UT\"))\n\n    print(\"fetch_exchange(IN-UP, IN-UT) ->\")\n    print(fetch_exchange(\"IN-UP\", \"IN-UT\"))\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/IN_WE.py",
    "content": "#!/usr/bin/env python3\n\n\nimport json\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nIN_WE_PROXY = \"https://in-proxy-jfnx5klx2a-el.a.run.app\"\nEXCHANGE_URL = f\"{IN_WE_PROXY}/InterRegionalLinks_Data.aspx/Get_InterRegionalLinks_Region_Wise?host=https://www.wrldc.in\"\nCONSUMPTION_URL = f\"{IN_WE_PROXY}/OnlinestateTest1.aspx/GetRealTimeData_state_Wise?host=https://www.wrldc.in\"\nZONE_INFO = ZoneInfo(\"Asia/Kolkata\")\n\nEXCHANGES_MAPPING = {\n    \"WR-SR\": \"IN-SO->IN-WE\",\n    \"WR-ER\": \"IN-EA->IN-WE\",\n    \"WR-NR\": \"IN-NO->IN-WE\",\n}\n\nKIND_MAPPING = {\n    \"exchange\": {\n        \"url\": EXCHANGE_URL,\n        \"datetime_col\": \"lastUpdate\",\n        \"region_col\": \"Region_Name\",\n    },\n    \"consumption\": {\n        \"url\": CONSUMPTION_URL,\n        \"datetime_col\": \"current_datetime\",\n        \"region_col\": \"StateName\",\n    },\n}\n\n\ndef _get_hour_dts(dt: datetime):\n    \"\"\"\n    Returns up to 24 datetime objects for a given datetime's date, one for each\n    hour, excluding future hours.\n    \"\"\"\n    date_dt = datetime.combine(dt.date(), datetime.min.time()).replace(tzinfo=ZONE_INFO)\n    dts = pd.date_range(\n        date_dt,\n        date_dt + timedelta(hours=23),\n        freq=\"H\",\n    ).to_pydatetime()\n\n    now_dt = datetime.now(ZONE_INFO)\n    return [dt for dt in dts if dt < now_dt]\n\n\ndef _fetch_data(\n    kind: str,\n    session: Session,\n    target_datetime: datetime,\n) -> dict:\n    \"\"\"\n    Fetches 24 hours of either exchange or production data from wrldc.in.\n    \"\"\"\n    url = KIND_MAPPING[kind][\"url\"]\n    datetime_col = KIND_MAPPING[kind][\"datetime_col\"]\n\n    payload = {\"date\": target_datetime.strftime(\"%Y-%m-%d\")}\n    resp: Response = session.post(url, json=payload)\n\n    try:\n        data = json.loads(resp.json().get(\"d\", {}))\n    except Exception as e:\n        raise ParserException(\n            parser=\"IN_WE.py\",\n            message=f\"{target_datetime}: {kind} data is not available\",\n        ) from e\n\n    # The source data is a 12 hour format without mentioning if its AM/PM, so\n    # 12:15 (AM or PM) could mean 00:15 or 12:15. This is addressed by relying\n    # on the full date worth of ordered data, where we assume the second time\n    # 12:xx shows up it must have transitioned to PM time.\n    am_time = True\n    checkpoint = False\n    dt_format = \"%Y-%d-%m %I:%M:%S %p\"\n    for item in data:\n        dt_string = item[datetime_col] + (\" AM\" if am_time else \" PM\")\n        dt = datetime.strptime(dt_string, dt_format).replace(tzinfo=ZONE_INFO)\n        if am_time:\n            if not checkpoint and dt.hour != 0:\n                checkpoint = True\n            elif checkpoint and dt.hour == 0:\n                am_time = False\n                dt_string = item[datetime_col] + (\" AM\" if am_time else \" PM\")\n                dt = datetime.strptime(dt_string, dt_format).replace(tzinfo=ZONE_INFO)\n        item[datetime_col] = dt\n    return data\n\n\ndef _get_df_for_hour(kind: str, data: dict, hour: int) -> pd.DataFrame:\n    \"\"\"\n    Returns a dataframe with a specific hour of interest.\n    \"\"\"\n    datetime_col = KIND_MAPPING[kind][\"datetime_col\"]\n    return pd.DataFrame([item for item in data if item[datetime_col].hour == hour])\n\n\ndef _get_mean_hourly_net_flow(\n    data: dict,\n    zone_key1: str,\n    zone_key2: str,\n    target_datetime: datetime,\n) -> float:\n    \"\"\"\n    Average all data points in the target_datetime hour.\n    \"\"\"\n    region_col = KIND_MAPPING[\"exchange\"][\"region_col\"]\n    exchange_string = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    df = _get_df_for_hour(kind=\"exchange\", data=data, hour=target_datetime.hour)\n    df[\"zone_key\"] = df[region_col].map(EXCHANGES_MAPPING)\n    df = df.loc[df[\"zone_key\"] == exchange_string]\n    df.loc[:, \"target_datetime\"] = target_datetime\n    df = (\n        df.groupby([region_col, \"target_datetime\"])\n        .mean(numeric_only=True)\n        .reset_index()\n    )\n\n    return -round(df.iloc[0].get(\"Current_Loading\", 0), 3)\n\n\ndef _get_mean_hourly_consumption(\n    data: dict,\n    target_datetime: datetime,\n) -> float:\n    \"\"\"\n    Average all data points in the target_datetime hour.\n    \"\"\"\n    region_col = KIND_MAPPING[\"consumption\"][\"region_col\"]\n\n    df = _get_df_for_hour(kind=\"consumption\", data=data, hour=target_datetime.hour)\n    df.loc[:, \"target_datetime\"] = target_datetime\n    df = (\n        df.groupby([region_col, \"target_datetime\"])\n        .mean(numeric_only=True)\n        .reset_index()\n    )\n\n    return round(\n        df.groupby([\"target_datetime\"])[\"Demand\"].sum().values[0],\n        3,\n    )\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if session is None:\n        session = Session()\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    exchange_string = \"->\".join(sorted([zone_key1, zone_key2]))\n    data = _fetch_data(\n        kind=\"exchange\",\n        session=session,\n        target_datetime=target_datetime,\n    )\n    exchange_list = ExchangeList(logger)\n    for dt in _get_hour_dts(target_datetime):\n        net_flow = _get_mean_hourly_net_flow(\n            zone_key1=zone_key1,\n            zone_key2=zone_key2,\n            data=data,\n            target_datetime=dt,\n        )\n        exchange_list.append(\n            zoneKey=ZoneKey(exchange_string),\n            datetime=dt,\n            netFlow=net_flow,\n            source=\"wrldc.in\",\n        )\n\n    return exchange_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"IN-WE\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if session is None:\n        session = Session()\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    data = _fetch_data(\n        kind=\"consumption\",\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n    consumption_list = TotalConsumptionList(logger)\n    for dt in _get_hour_dts(target_datetime):\n        consumption = _get_mean_hourly_consumption(data=data, target_datetime=dt)\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            consumption=consumption,\n            source=\"wrldc.in\",\n        )\n    return consumption_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(fetch_exchange(zone_key1=\"IN-WE\", zone_key2=\"IN-NO\"))\n    print(fetch_consumption())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/JAO.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"\nParser for the JAO (Joint Allocation Office) Publication Tool.\n\nDocs: https://publicationtool.jao.eu/PublicationHandbook/Core_PublicationTool_Handbook_v2.2.pdf\nRegions:\n    - Core CCR:   https://publicationtool.jao.eu/core/api\n    - Nordic CCR: https://publicationtool.jao.eu/nordic/api\n\nEvery JAO dataset (Core or Nordic) is served from the same URL template per\nregion — `/data/<datasetName>` with `FromUtc`/`ToUtc` query params and a\n`{data, rejected, messages}` envelope — so the HTTP layer is reusable. Datasets\ndiffer only in row shape:\n\n- Per-border (bidirectional): fields named `border_XX_YY`, one row per hour.\n    e.g. shadowAuctionATC, maxExchanges\n- Per-zone: one row per hour, fields per country (`maxAT`, `minDE`, ...).\n    e.g. maxNetPos, referenceNetPosition\n- Per-CNEC: many rows per hour, one per critical network element.\n    e.g. shadowPrices, validationReductions\n\nCurrently wired (all day-ahead horizon):\n- fetch_shadow_auction_atc_day_ahead        → Core shadowAuctionATC (per-border)\n- fetch_core_external_atc_day_ahead         → Core atc (per-border, 15-min)\n- fetch_core_max_bex_day_ahead              → Core maxExchanges (per-border, hourly)\n- fetch_nordic_max_bex_day_ahead            → Nordic maxExchanges (per-border, 15-min)\n- fetch_core_scheduled_exchanges_day_ahead  → Core scheduledExchanges (per-border, 15-min)\n- fetch_nordic_max_bflow_day_ahead          → Nordic maxBorderFlow (per-border, 15-min)\n\"\"\"\n\nfrom datetime import datetime, time, timedelta, timezone\nfrom enum import Enum\nfrom logging import Logger, getLogger\n\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeCapacityList,\n    ExchangeList,\n)\nfrom electricitymap.contrib.lib.models.events import EventSourceType\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\nSOURCE = \"jao.eu\"\nREQUEST_TIMEOUT_SECONDS = 30\n\n# JAO Publication Tool API caps all datasets to a 2-day range per call.\nJAO_MAX_FETCH_DAYS = 2\n\n\nclass JaoRegion(str, Enum):\n    \"\"\"JAO Publication Tool region — each has its own base URL and dataset catalog.\"\"\"\n\n    CORE = \"core\"\n    NORDIC = \"nordic\"\n\n    def __str__(self) -> str:\n        return self.value\n\n\nclass JaoDataset(str, Enum):\n    \"\"\"Canonical JAO Publication Tool dataset slugs.\n\n    Each dataset is published by exactly one region's Publication Tool. The\n    caller of `_query_jao` must pass the matching `JaoRegion`.\n    \"\"\"\n\n    # Per-border, bidirectional (`border_XX_YY` fields).\n    # Enum keys use JAO's human-readable terminology (MaxBex, MaxBflow);\n    # enum values are the exact URL slugs JAO serves the dataset under.\n    SHADOW_AUCTION_ATC = \"shadowAuctionATC\"  # Core only\n    CORE_EXTERNAL_ATC = \"atc\"  # Core only\n    MAX_BEX = \"maxExchanges\"  # Core + Nordic\n    SCHEDULED_EXCHANGES = \"scheduledExchanges\"  # Core only\n    MAX_BFLOW = \"maxBorderFlow\"  # Nordic only\n\n    def __str__(self) -> str:\n        return self.value\n\n\n# Mapping from EM zone keys to the zone codes JAO uses in `border_XX_YY`\n# fields. Only zones where the two differ need an entry; everything else\n# passes through as-is (AT, BE, CZ, DE, FR, etc. all match 1:1).\n#\n# Notes on the DE-LU joint bidding zone: JAO treats DE-LU as a single zone\n# under the code \"DE\" (no \"LU\" zone is ever published). Core-external ATC on\n# borders involving LU is therefore fully accounted for under the DE-side\n# exchange (e.g. BE-LU capacity is rolled into `border_BE_DE`). EM exchanges\n# where LU is a party (BE_LU, DE_LU, FR_LU) should NOT be wired to this\n# parser to avoid double-counting.\nEM_TO_JAO_ZONE: dict[str, str] = {\n    # Italy: JAO publishes a single \"IT\" code for Core-external borders,\n    # which physically corresponds to the Italy North bidding zone.\n    \"IT-NO\": \"IT\",\n    \"DK-DK1\": \"DK1\",\n    \"DK-DK2\": \"DK2\",\n    \"NO-NO1\": \"NO1\",\n    \"NO-NO2\": \"NO2\",\n    \"NO-NO3\": \"NO3\",\n    \"NO-NO4\": \"NO4\",\n    \"NO-NO5\": \"NO5\",\n    \"SE-SE1\": \"SE1\",\n    \"SE-SE2\": \"SE2\",\n    \"SE-SE3\": \"SE3\",\n    \"SE-SE4\": \"SE4\",\n}\n\n\ndef _em_to_jao_zone(em_zone: str) -> str:\n    \"\"\"Translate an EM zone key to the zone code JAO uses in its border field names.\"\"\"\n    return EM_TO_JAO_ZONE.get(em_zone, em_zone)\n\n\ndef _format_utc(dt: datetime) -> str:\n    \"\"\"Format a tz-aware datetime as the ISO-8601 string JAO expects.\"\"\"\n    return dt.astimezone(timezone.utc).strftime(\"%Y-%m-%dT%H:%M:%S.000Z\")\n\n\ndef _parse_utc(value: str) -> datetime:\n    \"\"\"Parse JAO's `dateTimeUtc` field into a tz-aware datetime.\"\"\"\n    return datetime.fromisoformat(value.replace(\"Z\", \"+00:00\"))\n\n\ndef _target_window(\n    target_datetime: datetime | None,\n    days: int = JAO_MAX_FETCH_DAYS,\n) -> tuple[datetime, datetime]:\n    \"\"\"Return a [day_start, day_start + `days`) UTC window starting at the\n    UTC day containing `target_datetime`. Matches the `@refetch_frequency`\n    the public fetcher is decorated with so refetches are gapless.\n    \"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=timezone.utc)\n    elif target_datetime.tzinfo is None:\n        target_datetime = target_datetime.replace(tzinfo=timezone.utc)\n    day_start = datetime.combine(\n        target_datetime.astimezone(timezone.utc).date(),\n        time.min,\n        tzinfo=timezone.utc,\n    )\n    return day_start, day_start + timedelta(days=days)\n\n\nBASE_URL_BY_REGION: dict[JaoRegion, str] = {\n    JaoRegion.CORE: \"https://publicationtool.jao.eu/core/api\",\n    JaoRegion.NORDIC: \"https://publicationtool.jao.eu/nordic/api\",\n}\n\n\ndef _query_jao(\n    session: Session,\n    region: JaoRegion,\n    dataset: JaoDataset,\n    from_utc: datetime,\n    to_utc: datetime,\n    logger: Logger,\n) -> list[dict]:\n    \"\"\"Call a JAO Publication Tool dataset endpoint in the given region.\n\n    Shared by every JAO dataset (Core and Nordic alike) — formats params,\n    unwraps the envelope, raises on HTTP error or `rejected=True`.\n    \"\"\"\n    base_url = BASE_URL_BY_REGION[region]\n    url = f\"{base_url}/data/{dataset.value}\"\n    params = {\"FromUtc\": _format_utc(from_utc), \"ToUtc\": _format_utc(to_utc)}\n    logger.debug(\n        \"Querying JAO\",\n        extra={\n            \"region\": region.value,\n            \"dataset\": dataset.value,\n            \"from_utc\": params[\"FromUtc\"],\n            \"to_utc\": params[\"ToUtc\"],\n        },\n    )\n    response = session.get(url, params=params, timeout=REQUEST_TIMEOUT_SECONDS)\n    if not response.ok:\n        raise ParserException(\n            parser=\"JAO.py\",\n            message=(\n                f\"{region.value}/{dataset.value}: HTTP {response.status_code} \"\n                f\"for {params['FromUtc']}..{params['ToUtc']}\"\n            ),\n        )\n    payload = response.json()\n    if payload.get(\"rejected\"):\n        raise ParserException(\n            parser=\"JAO.py\",\n            message=(\n                f\"{region.value}/{dataset.value}: request rejected by JAO \"\n                f\"(messages={payload.get('messages')!r})\"\n            ),\n        )\n    return payload.get(\"data\") or []\n\n\ndef _extract_border_capacity(\n    rows: list[dict],\n    sorted_zone_keys: ZoneKey,\n    source: str,\n    logger: Logger,\n    field_prefix: str = \"border\",\n) -> ExchangeCapacityList:\n    \"\"\"Turn per-border rows into an ExchangeCapacityList.\n\n    For a sorted zone key `\"A->B\"`, reads `f'{prefix}_A_B'` as capacityExport\n    (A→B) and `f'{prefix}_B_A'` as capacityImport (B→A). Works for any JAO\n    dataset that uses the `border_XX_YY` shape (shadowAuctionATC,\n    maxExchanges).\n    \"\"\"\n    zone_a, zone_b = sorted_zone_keys.split(\"->\")\n    jao_a = _em_to_jao_zone(zone_a)\n    jao_b = _em_to_jao_zone(zone_b)\n    export_field = f\"{field_prefix}_{jao_a}_{jao_b}\"\n    import_field = f\"{field_prefix}_{jao_b}_{jao_a}\"\n\n    capacities = ExchangeCapacityList(logger)\n    for row in rows:\n        export_value = row.get(export_field)\n        import_value = row.get(import_field)\n        if export_value is None and import_value is None:\n            continue\n        capacities.append(\n            zoneKey=sorted_zone_keys,\n            datetime=_parse_utc(row[\"dateTimeUtc\"]),\n            source=source,\n            capacityExport=export_value,\n            capacityImport=import_value,\n        )\n    return capacities\n\n\ndef _extract_border_net_flow(\n    rows: list[dict],\n    sorted_zone_keys: ZoneKey,\n    source: str,\n    logger: Logger,\n    field_prefix: str = \"border\",\n) -> ExchangeList:\n    \"\"\"Turn per-border rows into an ExchangeList of scheduled netFlow events.\n\n    For a sorted zone key `\"A->B\"`, netFlow = `{prefix}_A_B` − `{prefix}_B_A`\n    (positive when A exports to B). JAO publishes both directional fields; day-\n    ahead market coupling clears a netted schedule so typically only one side\n    is non-zero per MTU, but subtracting handles both cases uniformly.\n\n    Emitted with sourceType=published since the values are TSO-published\n    ex-ante schedules, not statistical forecasts.\n    \"\"\"\n    zone_a, zone_b = sorted_zone_keys.split(\"->\")\n    jao_a = _em_to_jao_zone(zone_a)\n    jao_b = _em_to_jao_zone(zone_b)\n    export_field = f\"{field_prefix}_{jao_a}_{jao_b}\"\n    import_field = f\"{field_prefix}_{jao_b}_{jao_a}\"\n\n    flows = ExchangeList(logger)\n    for row in rows:\n        export_value = row.get(export_field)\n        import_value = row.get(import_field)\n        if export_value is None and import_value is None:\n            continue\n        net_flow = (export_value or 0) - (import_value or 0)\n        flows.append(\n            zoneKey=sorted_zone_keys,\n            datetime=_parse_utc(row[\"dateTimeUtc\"]),\n            source=source,\n            netFlow=net_flow,\n            sourceType=EventSourceType.published,\n        )\n    return flows\n\n\ndef _fetch_per_border_dataset(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    region: JaoRegion,\n    dataset: JaoDataset,\n    session: Session | None,\n    target_datetime: datetime | None,\n    logger: Logger,\n) -> list[dict]:\n    \"\"\"Shared body for per-border JAO capacity fetchers: sort zone keys, build\n    the window, query, extract capacities, return. Each public fetcher is then\n    a one-line wrapper that pins its region + dataset.\"\"\"\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    from_utc, to_utc = _target_window(target_datetime)\n    rows = _query_jao(session or Session(), region, dataset, from_utc, to_utc, logger)\n    return _extract_border_capacity(rows, sorted_zone_keys, SOURCE, logger).to_list()\n\n\n@refetch_frequency(timedelta(days=JAO_MAX_FETCH_DAYS))\ndef fetch_shadow_auction_atc_day_ahead(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Day-ahead shadow-auction ATC capacity for a Core internal border.\n\n    JAO publishes this as a fallback when Core day-ahead market coupling\n    can't produce a result; on days where coupling succeeded, the response\n    for the requested pair may be empty. Hourly granularity.\n    \"\"\"\n    return _fetch_per_border_dataset(\n        zone_key1,\n        zone_key2,\n        JaoRegion.CORE,\n        JaoDataset.SHADOW_AUCTION_ATC,\n        session,\n        target_datetime,\n        logger,\n    )\n\n\n@refetch_frequency(timedelta(days=JAO_MAX_FETCH_DAYS))\ndef fetch_core_external_atc_day_ahead(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Day-ahead ATC capacity on Core's external borders (non-flow-based\n    neighbors: IT, DK1, ES, BG, ...). 15-minute granularity.\n    \"\"\"\n    return _fetch_per_border_dataset(\n        zone_key1,\n        zone_key2,\n        JaoRegion.CORE,\n        JaoDataset.CORE_EXTERNAL_ATC,\n        session,\n        target_datetime,\n        logger,\n    )\n\n\n@refetch_frequency(timedelta(days=JAO_MAX_FETCH_DAYS))\ndef fetch_core_max_bex_day_ahead(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Day-ahead max bilateral exchange capacity (MaxBex) for a Core border.\n\n    Published hourly; computed by Core TSOs as the max NTC that could be\n    commercially exchanged per direction given grid constraints.\n    \"\"\"\n    return _fetch_per_border_dataset(\n        zone_key1,\n        zone_key2,\n        JaoRegion.CORE,\n        JaoDataset.MAX_BEX,\n        session,\n        target_datetime,\n        logger,\n    )\n\n\n@refetch_frequency(timedelta(days=JAO_MAX_FETCH_DAYS))\ndef fetch_nordic_max_bex_day_ahead(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Day-ahead max bilateral exchange capacity (MaxBex) for a Nordic border.\n\n    15-minute granularity. Uses Nordic bidding-zone codes (NO1..NO5, SE1..SE4,\n    DK1/DK2, FI) — `EM_TO_JAO_ZONE` handles the EM→JAO translation.\n    \"\"\"\n    return _fetch_per_border_dataset(\n        zone_key1,\n        zone_key2,\n        JaoRegion.NORDIC,\n        JaoDataset.MAX_BEX,\n        session,\n        target_datetime,\n        logger,\n    )\n\n\n@refetch_frequency(timedelta(days=JAO_MAX_FETCH_DAYS))\ndef fetch_core_scheduled_exchanges_day_ahead(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Day-ahead scheduled commercial exchanges for a Core border.\n\n    The cleared net commercial flow from Core day-ahead market coupling, per\n    MTU (15 min). Covers Core internal borders and Core-external ones (e.g.\n    FR↔ES, DK1↔DE). Emitted as signed netFlow events (Exchange shape), not\n    capacity pairs, since market coupling publishes a netted schedule.\n    \"\"\"\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    from_utc, to_utc = _target_window(target_datetime)\n    rows = _query_jao(\n        session or Session(),\n        JaoRegion.CORE,\n        JaoDataset.SCHEDULED_EXCHANGES,\n        from_utc,\n        to_utc,\n        logger,\n    )\n    return _extract_border_net_flow(rows, sorted_zone_keys, SOURCE, logger).to_list()\n\n\n@refetch_frequency(timedelta(days=JAO_MAX_FETCH_DAYS))\ndef fetch_nordic_max_bflow_day_ahead(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Day-ahead max border flow (MaxBflow) for a Nordic border.\n\n    15-minute granularity. Complementary to maxExchanges — maxBorderFlow is\n    the raw physical capability ceiling on the border; maxExchanges is what\n    was offered to the market after security constraints.\n    \"\"\"\n    return _fetch_per_border_dataset(\n        zone_key1,\n        zone_key2,\n        JaoRegion.NORDIC,\n        JaoDataset.MAX_BFLOW,\n        session,\n        target_datetime,\n        logger,\n    )\n\n\nif __name__ == \"__main__\":\n    from pprint import pprint\n\n    pprint(fetch_shadow_auction_atc_day_ahead(ZoneKey(\"DE\"), ZoneKey(\"FR\")))\n    pprint(fetch_core_external_atc_day_ahead(ZoneKey(\"DE\"), ZoneKey(\"DK-DK1\")))\n    pprint(fetch_core_max_bex_day_ahead(ZoneKey(\"DE\"), ZoneKey(\"FR\")))\n    pprint(fetch_nordic_max_bex_day_ahead(ZoneKey(\"NO-NO2\"), ZoneKey(\"SE-SE3\")))\n    pprint(fetch_core_scheduled_exchanges_day_ahead(ZoneKey(\"DE\"), ZoneKey(\"FR\")))\n    pprint(fetch_nordic_max_bflow_day_ahead(ZoneKey(\"NO-NO2\"), ZoneKey(\"SE-SE3\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/JP.py",
    "content": "#!/usr/bin/env python3\nfrom datetime import datetime, timedelta\nfrom io import BytesIO, StringIO\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zipfile import ZipFile\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZONES_CONFIG\nfrom electricitymap.contrib.lib.models.event_lists import (\n    TotalConsumptionList,\n    TotalProductionList,\n)\nfrom electricitymap.contrib.lib.models.events import EventSourceType\nfrom electricitymap.contrib.parsers import occtonet\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.types import ZoneKey\n\n# Abbreviations\n# JP-HKD : Hokkaido\n# JP-TH  : Tohoku\n# JP-TK  : Tokyo area\n# JP-CB  : Chubu\n# JP-HR  : Hokuriku\n# JP-KN  : Kansai\n# JP-SK  : Shikoku\n# JP-KY  : Kyushu\n# JP-ON  : Okinawa\n# JP-CG  : Chūgoku\n\nsources = {\n    \"JP-HKD\": \"denkiyoho.hepco.co.jp\",\n    \"JP-TH\": \"setsuden.nw.tohoku-epco.co.jp\",\n    \"JP-TK\": \"www.tepco.co.jp\",\n    \"JP-CB\": \"denki-yoho.chuden.jp\",\n    \"JP-HR\": \"www.rikuden.co.jp/denki-yoho\",\n    \"JP-KN\": \"www.kepco.co.jp\",\n    \"JP-SK\": \"www.yonden.co.jp\",\n    \"JP-CG\": \"www.energia.co.jp\",\n    \"JP-KY\": \"www.kyuden.co.jp/power_usages/pc.html\",\n    \"JP-ON\": \"www.okiden.co.jp/denki/\",\n}\nZONES_ONLY_LIVE = [\"JP-TK\", \"JP-CB\", \"JP-SK\"]\nZONE_INFO = ZoneInfo(\"Asia/Tokyo\")\n\n\ndef get_wind_capacity(datetime: datetime, zone_key, logger: Logger):\n    ZONE_CONFIG = ZONES_CONFIG[zone_key]\n    try:\n        capacity = ZONE_CONFIG[\"capacity\"][\"wind\"]\n        if zone_key == \"JP-HKD\":\n            if datetime.year <= 2019:\n                capacity = 480\n            elif datetime.year == 2020:\n                capacity = 520\n            elif datetime.year >= 2021:\n                capacity = 577\n    except Exception as e:\n        logger.error(f\"Wind capacity not found in configuration file: {e.args}\")\n        capacity = None\n    return capacity\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: str = \"JP-TK\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Calculates production from consumption and imports for a given area\n    All production is mapped to unknown\n    \"\"\"\n    df = fetch_production_df(zone_key, session, target_datetime)\n    # add a row to production for each entry in the dictionary:\n\n    datalist = []\n\n    for i in df.index:\n        capacity = get_wind_capacity(\n            df.loc[i, \"datetime\"].to_pydatetime(), zone_key, logger\n        )\n        data = {\n            \"zoneKey\": zone_key,\n            \"datetime\": df.loc[i, \"datetime\"].to_pydatetime(),\n            \"production\": {\n                \"biomass\": None,\n                \"coal\": None,\n                \"gas\": None,\n                \"hydro\": None,\n                \"nuclear\": None,\n                \"oil\": None,\n                \"solar\": df.loc[i, \"solar\"] if \"solar\" in df.columns else None,\n                \"wind\": None,\n                \"geothermal\": None,\n                \"unknown\": df.loc[i, \"unknown\"],\n            },\n            \"capacity\": {\"wind\": capacity if capacity is not None else {}},\n            \"source\": f\"occto.or.jp, {sources[zone_key]}\",\n        }\n        datalist.append(data)\n    return datalist\n\n\ndef fetch_production_df(\n    zone_key: str = \"JP-TK\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    \"\"\"\n    Calculates production from consumption and imports for a given area.\n    All production is mapped to unknown.\n    \"\"\"\n    exch_map = {\n        \"JP-HKD\": [\"JP-TH\"],\n        \"JP-TH\": [\"JP-TK\", \"JP-HKD\"],\n        \"JP-TK\": [\"JP-TH\", \"JP-CB\"],\n        \"JP-CB\": [\"JP-TK\", \"JP-HR\", \"JP-KN\"],\n        \"JP-HR\": [\"JP-CB\", \"JP-KN\"],\n        \"JP-KN\": [\"JP-CB\", \"JP-HR\", \"JP-SK\", \"JP-CG\"],\n        \"JP-SK\": [\"JP-KN\", \"JP-CG\"],\n        \"JP-CG\": [\"JP-KN\", \"JP-SK\", \"JP-KY\"],\n        \"JP-ON\": [],\n        \"JP-KY\": [\"JP-CG\"],\n    }\n    df = fetch_consumption_df(zone_key, target_datetime)\n    df[\"imports\"] = 0\n    for zone in exch_map[zone_key]:\n        df2 = occtonet.fetch_exchange(\n            zone_key1=zone_key,\n            zone_key2=zone,\n            session=session,\n            target_datetime=target_datetime,\n        )\n        df2 = pd.DataFrame(df2)\n        exchname = df2.loc[0, \"sortedZoneKeys\"]\n        df2 = df2[[\"datetime\", \"netFlow\"]]\n        df2.columns = [\"datetime\", exchname]\n        df = pd.merge(df, df2, how=\"inner\", on=\"datetime\")\n        if exchname.split(\"->\")[-1] == zone_key:\n            df[\"imports\"] = df[\"imports\"] + df[exchname]\n        else:\n            df[\"imports\"] = df[\"imports\"] - df[exchname]\n    # By default all production is mapped to unknown\n    df[\"unknown\"] = df[\"cons\"] - df[\"imports\"]\n    # When there is solar, remove it from other production\n    if \"solar\" in df.columns:\n        df[\"unknown\"] = df[\"unknown\"] - df[\"solar\"]\n    return df\n\n\ndef fetch_consumption_df(\n    zone_key: str = \"JP-TK\",\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    \"\"\"\n    Returns the consumption for an area as a pandas DataFrame.\n    For JP-CB the consumption file includes solar production.\n    \"\"\"\n    if target_datetime is not None and zone_key in ZONES_ONLY_LIVE:\n        raise NotImplementedError(\"This parser can only fetch live data\")\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n    datestamp = target_datetime.astimezone(ZONE_INFO).strftime(\"%Y%m%d\")\n    consumption_url = {\n        \"JP-HKD\": f\"http://denkiyoho.hepco.co.jp/area/data/juyo_01_{datestamp}.csv\",\n        \"JP-TH\": f\"https://setsuden.nw.tohoku-epco.co.jp/common/demand/juyo_02_{datestamp}.csv\",\n        \"JP-TK\": \"https://www.tepco.co.jp/forecast/html/images/juyo-d1-j.csv\",\n        \"JP-HR\": f\"http://www.rikuden.co.jp/nw/denki-yoho/csv/juyo_05_{datestamp}.csv\",\n        \"JP-CB\": \"https://powergrid.chuden.co.jp/denki_yoho_content_data/juyo_cepco003.csv\",\n        \"JP-KN\": \"https://www.kansai-td.co.jp/yamasou/juyo1_kansai.csv\",\n        \"JP-CG\": f\"https://www.energia.co.jp/nw/jukyuu/sys/juyo_07_{datestamp}.csv\",\n        \"JP-SK\": \"http://www.yonden.co.jp/denkiyoho/juyo_shikoku.csv\",\n        \"JP-KY\": f\"https://www.kyuden.co.jp/td_power_usages/csv/juyo-hourly-{datestamp}.csv\",\n        \"JP-ON\": f\"https://www.okiden.co.jp/denki2/juyo_10_{datestamp}.csv\",\n    }\n\n    # First roughly 40 rows of the consumption files have hourly data,\n    # the parser skips to the rows with 5-min actual values\n    startrow = 57 if zone_key == \"JP-KN\" else 54\n\n    try:\n        df = pd.read_csv(\n            consumption_url[zone_key], skiprows=startrow, encoding=\"shift-jis\"\n        )\n    except pd.errors.EmptyDataError as e:\n        logger.exception(\"Data not available yet\")\n        raise e\n\n    if zone_key in [\"JP-TH\"]:\n        df.columns = [\"Date\", \"Time\", \"cons\", \"solar\", \"wind\"]\n    elif zone_key in [\"JP-TK\"]:\n        df.columns = [\"Date\", \"Time\", \"cons\", \"solar\", \"solar_pct\"]\n    else:\n        df.columns = [\"Date\", \"Time\", \"cons\", \"solar\"]\n    # Convert 万kW to MW\n    df[\"cons\"] = 10 * df[\"cons\"]\n    if \"solar\" in df.columns:\n        df[\"solar\"] = 10 * df[\"solar\"]\n\n    df = df.dropna()\n    df[\"datetime\"] = df.apply(parse_dt, axis=1)\n    if \"solar\" in df.columns:\n        df = df[[\"datetime\", \"cons\", \"solar\"]]\n    else:\n        df = df[[\"datetime\", \"cons\"]]\n    return df\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_price(\n    zone_key: str = \"JP-TK\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO) + timedelta(days=1)\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    # price files contain data for fiscal year and not calendar year.\n    if target_datetime.month <= 3:\n        fiscal_year = target_datetime.year - 1\n    else:\n        fiscal_year = target_datetime.year\n    url = f\"http://www.jepx.jp/market/excel/spot_{fiscal_year}.csv\"\n    df = pd.read_csv(url, encoding=\"shift-jis\")\n\n    df = df.iloc[:, [0, 1, 6, 7, 8, 9, 10, 11, 12, 13, 14]]\n    df.columns = [\n        \"Date\",\n        \"Period\",\n        \"JP-HKD\",\n        \"JP-TH\",\n        \"JP-TK\",\n        \"JP-CB\",\n        \"JP-HR\",\n        \"JP-KN\",\n        \"JP-CG\",\n        \"JP-SK\",\n        \"JP-KY\",\n    ]\n\n    if zone_key not in df.columns[2:]:\n        return []\n\n    start = target_datetime - timedelta(days=1)\n    df[\"Date\"] = pd.to_datetime(df[\"Date\"], format=\"%Y/%m/%d\").dt.date\n    df = df[(df[\"Date\"] >= start.date()) & (df[\"Date\"] <= target_datetime.date())]\n\n    df[\"datetime\"] = df.apply(\n        lambda row: (\n            datetime.combine(row[\"Date\"], datetime.min.time()).replace(tzinfo=ZONE_INFO)\n            + timedelta(minutes=30 * (row[\"Period\"] - 1))\n        ),\n        axis=1,\n    )\n\n    data = []\n    for row in df.iterrows():\n        data.append(\n            {\n                \"zoneKey\": zone_key,\n                \"currency\": \"JPY\",\n                \"datetime\": row[1][\"datetime\"].to_pydatetime(),\n                \"price\": round(\n                    int(1000 * row[1][zone_key]), -1\n                ),  # Convert from JPY/kWh to JPY/MWh\n                \"source\": \"jepx.jp\",\n            }\n        )\n\n    return data\n\n\ndef parse_dt(row):\n    \"\"\"Parses datetime objects from date and time strings.\"\"\"\n    format_string = \"%Y/%m/%d %H:%M\"\n    if \"AM\" in row[\"Time\"] or \"PM\" in row[\"Time\"]:\n        format_string = \"%Y/%m/%d %I:%M %p\"\n    datetime_string = \" \".join([row[\"Date\"], row[\"Time\"]])\n    return datetime.strptime(datetime_string, format_string).replace(tzinfo=ZONE_INFO)\n\n\nSOURCES_FORECAST_DATA = {\n    \"JP-HKD\": \"denkiyoho.hepco.co.jp\",\n    \"JP-TH\": \"setsuden.nw.tohoku-epco.co.jp\",\n    \"JP-TK\": \"www.tepco.co.jp/forecast\",\n    \"JP-CB\": \"powergrid.chuden.co.jp\",\n    \"JP-HR\": \"www.rikuden.co.jp/nw/denki-yoho\",\n    \"JP-KN\": \"www.kansai-td.co.jp\",\n    \"JP-SK\": \"www.yonden.co.jp\",\n    \"JP-CG\": \"www.energia.co.jp\",\n    \"JP-KY\": \"www.kyuden.co.jp\",\n    \"JP-ON\": \"www.okiden.co.jp/denki2/\",\n}\n\n\ndef read_csv_forecast(\n    datestamp, zone_key, session, logger, data_type=None\n):  # data_type = generation_fcst or consumption_fcst\n    \"\"\"Reads the file where the forecast data is given, for a given zone in Japan. Now implemented for consumption and generation forecast data.\"\"\"\n    if datestamp < datetime.now(ZONE_INFO).strftime(\"%Y%m%d\"):\n        raise NotImplementedError(\"Past dates not implemented for selected region\")\n\n    # Forecasts ahead of current date are not available for JP-KY\n    if datestamp > datetime.now(ZONE_INFO).strftime(\"%Y%m%d\") and zone_key == \"JP-KY\":\n        raise NotImplementedError(\n            \"Future dates (local time) not implemented for selected region\"\n        )\n\n    # Forecasts ahead of tomorrow's date are not available\n    if datestamp > (datetime.now(ZONE_INFO) + timedelta(days=1)).strftime(\"%Y%m%d\"):\n        raise NotImplementedError(\n            \"Dates after tomorrow (local time) not implemented for selected region\"\n        )\n\n    # Urls for some Japan zones based on datestamp\n    forecast_url = {\n        \"JP-HKD\": f\"http://denkiyoho.hepco.co.jp/area/data/{datestamp}_hokkaido_yosoku.csv\",\n        \"JP-HR\": f\"https://www.rikuden.co.jp/nw/denki-yoho/csv/yosoku_05_{datestamp}.csv\",\n        \"JP-KN\": f\"https://www.kansai-td.co.jp/interchange/denkiyoho/imbalance/{datestamp}_yosoku.csv\",\n        \"JP-CG\": f\"https://www.energia.co.jp/nw/jukyuu/sys/{datestamp[:6]}_jyukyu2_chugoku.zip\",\n        \"JP-KY\": rf\"https://www.kyuden.co.jp/td_power_usages/csv/kouhyo/imbalance/21110_TSO9_0_{datestamp}.csv?a={datestamp}\\d{6}\",\n        \"JP-ON\": f\"http://www.okiden.co.jp/denki2/dem_pg/csv/jukyu_yosoku_{datestamp}.csv\",\n    }\n\n    # For zones with different URLs for today vs tomorrow\n    if datestamp == datetime.now(ZONE_INFO).strftime(\"%Y%m%d\"):\n        forecast_url[\"JP-TH\"] = (\n            f\"https://setsuden.nw.tohoku-epco.co.jp/common/demand/area_tso_yosoku_{datestamp}.csv\"\n        )\n        forecast_url[\"JP-TK\"] = (\n            \"https://www4.tepco.co.jp/forecast/html/images/AREA_YOSOKU.csv\"\n        )\n        forecast_url[\"JP-CB\"] = (\n            \"https://powergrid.chuden.co.jp/denki_yoho_content_data/keito_yosoku_cepco003.csv\"\n        )\n        forecast_url[\"JP-SK\"] = (\n            \"https://www.yonden.co.jp/nw/denkiyoho/supply_demand/csv/yosoku_today.csv\"\n        )\n    # TODO: what time the new doc is created for next day?\n    elif datestamp == (datetime.now(ZONE_INFO) + timedelta(days=1)).strftime(\"%Y%m%d\"):\n        forecast_url[\"JP-TH\"] = (\n            \"https://setsuden.nw.tohoku-epco.co.jp/common/demand/area_tso_yosoku_y.csv\"\n        )\n        forecast_url[\"JP-TK\"] = (\n            \"https://www4.tepco.co.jp/forecast/html/images/AREA_ONCE_YOSOKU.csv\"\n        )\n        forecast_url[\"JP-SK\"] = (\n            \"https://www.yonden.co.jp/nw/denkiyoho/supply_demand/csv/yosoku_tomorrow.csv\"\n        )\n        if zone_key == \"JP-CB\":  # Raise exception for JP-CB\n            raise ValueError(\n                f\"Forecast data for tomorrow not available for zone: {zone_key}\"\n            )\n\n    # Skip non-tabular data at the start of source files\n    startrow = 1 if zone_key == \"JP-HR\" else 3 if zone_key == \"JP-KN\" else 2\n\n    # Get response from correspondent url\n    response = session.get(forecast_url[zone_key])\n\n    # Parse the different formats\n    df = pd.DataFrame()\n    if zone_key == \"JP-CG\":\n        with ZipFile(BytesIO(response.content)) as z:\n            target_file = f\"{datestamp}_yosoku_chugoku.csv\"\n            if target_file in z.namelist():\n                with z.open(target_file) as f:\n                    df = pd.read_csv(f, encoding=\"shift_jis\", skiprows=startrow)\n            else:\n                logger.error(f\"File '{target_file}' not found in the zip archive.\")\n                logger.debug(f\"Available files: {z.namelist()}\")\n    else:\n        content = response.content.decode(\"shift_jis\")\n        df = pd.read_csv(StringIO(content), skiprows=startrow)\n\n    # Check if df is still empty after the above operations\n    if df.empty:\n        logger.error(f\"Failed to load forecast data for {zone_key}\")\n        raise ValueError(f\"Could not obtain forecast data for zone: {zone_key}\")\n\n    # Consumption or generation data\n    if data_type == \"consumption_fcst\":\n        column_name_japanese = \"エリア総需要量\"\n    elif data_type == \"generation_fcst\":\n        column_name_japanese = \"エリア総発電量\"\n\n    # Extract the correspondant information from the files for each zone\n    if zone_key == \"JP-HKD\" or zone_key == \"JP-HR\":\n        df = df[[\"日付\", \"時間帯_自\", column_name_japanese + \"(kWh)\"]]\n    elif zone_key == \"JP-KN\" or zone_key == \"JP-KY\":\n        if zone_key == \"JP-KY\":\n            df = df.drop(index=0)\n        df = df[[\"日付\", \"時間帯＿自\", column_name_japanese]]\n    elif zone_key == \"JP-CG\" or zone_key == \"JP-CB\" or zone_key == \"JP-SK\":\n        df = df[[\"日付\", \"時間帯_自\", column_name_japanese]]\n    elif zone_key == \"JP-ON\" or zone_key == \"JP-TH\":\n        df = df[[\"DATE\", \"時間帯_自\", column_name_japanese + \"(kWh)\"]]\n    elif zone_key == \"JP-TK\":\n        df = df[\n            [\"日付(yyyymmdd)\", \"時間帯_自(HH:MI)\", column_name_japanese + \"[30分kWh]\"]\n        ]\n\n    df.columns = [\"Date\", \"Time\", data_type]\n\n    return df\n\n\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey = ZoneKey(\"JP-HKD\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Gets demand/consumption forecast for every half hour for the specified Japan zones in MW.\"\"\"\n    # Session\n    session = session or Session()\n\n    # Date\n    # Currently past dates not implemented for areas with no date in their demand csv files\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    datestamp = target_datetime.astimezone(ZONE_INFO).strftime(\"%Y%m%d\")\n\n    # Read csv\n    df = read_csv_forecast(\n        datestamp, zone_key, session, logger, data_type=\"consumption_fcst\"\n    )\n\n    # Transform to MW: the data is given every half hour\n    df[\"consumption_fcst\"] = df[\"consumption_fcst\"].astype(float) * 2 / 1000\n\n    all_consumption_events = df  # all events with a datetime and a consumption value\n    consumption_list = TotalConsumptionList(logger)\n\n    for row in all_consumption_events.itertuples():\n        if (\n            zone_key == \"JP-HR\"\n            or zone_key == \"JP-ON\"\n            or zone_key == \"JP-TH\"\n            or zone_key == \"JP-CB\"\n        ):\n            event_datetime = datetime.strptime(\n                f\"{row.Date} {row.Time}\", \"%Y/%m/%d %H:%M\"\n            ).replace(tzinfo=ZONE_INFO)\n        elif zone_key == \"JP-TK\":\n            # Format as string in the format \"YYYYMMDD HHMM\" and parse\n            event_datetime = datetime.strptime(\n                f\"{row.Date:08d} {row.Time:04d}\", \"%Y%m%d %H%M\"\n            ).replace(tzinfo=ZONE_INFO)\n        elif zone_key == \"JP-KY\":\n            event_datetime = datetime.strptime(\n                f\"{row.Date} {row.Time}\", \"%Y%m%d %H:%M\"\n            ).replace(tzinfo=ZONE_INFO)\n        else:\n            # Use strptime to directly parse the date integer and time string\n            event_datetime = datetime.strptime(\n                f\"{row.Date:08d} {row.Time}\", \"%Y%m%d %H:%M\"\n            ).replace(tzinfo=ZONE_INFO)\n\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=event_datetime,\n            consumption=row.consumption_fcst,\n            source=SOURCES_FORECAST_DATA[zone_key],\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumption_list.to_list()\n\n\ndef fetch_generation_forecast(\n    zone_key: ZoneKey = ZoneKey(\"JP-HKD\"),  # Just as default\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Gets generation forecast for every half hour for the specified Japan zones in MW.\"\"\"\n\n    # Session\n    session = session or Session()\n\n    # Date\n    # Currently past dates not implemented for areas with no date in their demand csv files\n    if target_datetime is None:\n        target_datetime = datetime.now(ZONE_INFO)\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    datestamp = target_datetime.astimezone(ZONE_INFO).strftime(\"%Y%m%d\")\n\n    # Read csv\n    df = read_csv_forecast(\n        datestamp, zone_key, session, logger, data_type=\"generation_fcst\"\n    )\n\n    # Transform to MW: the data is given every half hour\n    df[\"generation_fcst\"] = df[\"generation_fcst\"].astype(float) * 2 / 1000\n\n    all_generation_events = df  # all events with a datetime and a generation value\n    generation_list = TotalProductionList(logger)\n\n    for row in all_generation_events.itertuples():\n        if (\n            zone_key == \"JP-HR\"\n            or zone_key == \"JP-ON\"\n            or zone_key == \"JP-TH\"\n            or zone_key == \"JP-CB\"\n        ):\n            event_datetime = datetime.strptime(\n                f\"{row.Date} {row.Time}\", \"%Y/%m/%d %H:%M\"\n            ).replace(tzinfo=ZONE_INFO)\n        elif zone_key == \"JP-TK\":\n            # Format as string in the format \"YYYYMMDD HHMM\" and parse\n            event_datetime = datetime.strptime(\n                f\"{row.Date:08d} {row.Time:04d}\", \"%Y%m%d %H%M\"\n            ).replace(tzinfo=ZONE_INFO)\n        elif zone_key == \"JP-KY\":\n            event_datetime = datetime.strptime(\n                f\"{row.Date} {row.Time}\", \"%Y%m%d %H:%M\"\n            ).replace(tzinfo=ZONE_INFO)\n        else:\n            # Use strptime to directly parse the date integer and time string\n            event_datetime = datetime.strptime(\n                f\"{row.Date:08d} {row.Time}\", \"%Y%m%d %H:%M\"\n            ).replace(tzinfo=ZONE_INFO)\n\n        generation_list.append(\n            zoneKey=zone_key,\n            datetime=event_datetime,\n            value=row.generation_fcst,\n            source=SOURCES_FORECAST_DATA[zone_key],\n            sourceType=EventSourceType.forecasted,\n        )\n    return generation_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    \"\"\"\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_price() ->\")\n    print(fetch_price())\n    \"\"\"\n    print(\"fetch_consumption_forecast() ->\")\n    print(fetch_consumption_forecast())\n    print(\"fetch_consumption_forecast(JP-TH) ->\")\n    print(fetch_consumption_forecast(\"JP-TH\"))\n    print(\"fetch_consumption_forecast(JP-TK) ->\")\n    print(fetch_consumption_forecast(\"JP-TK\"))\n    print(\"fetch_consumption_forecast(JP-CB) ->\")\n    print(fetch_consumption_forecast(\"JP-CB\"))\n    print(\"fetch_consumption_forecast(JP-KN) ->\")\n    print(fetch_consumption_forecast(\"JP-KN\"))\n    print(\"fetch_consumption_forecast(JP-SK) ->\")\n    print(fetch_consumption_forecast(\"JP-SK\"))\n    print(\"fetch_consumption_forecast(JP-KY) ->\")\n    print(fetch_consumption_forecast(\"JP-KY\"))\n    print(\"fetch_consumption_forecast(JP-ON) ->\")\n    print(fetch_consumption_forecast(\"JP-ON\"))\n\n    print(\n        fetch_generation_forecast(\n            zone_key=\"JP-HKD\", target_datetime=datetime(2025, 4, 25)\n        )\n    )\n\n    print(\n        fetch_consumption_forecast(\n            zone_key=\"JP-HKD\", target_datetime=datetime(2025, 4, 25)\n        )\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/JP_KN.py",
    "content": "#!/usr/bin/env python3\nimport re\nfrom datetime import datetime\nfrom io import BytesIO\nfrom logging import Logger, getLogger\nfrom urllib.request import Request, urlopen\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom PIL import Image\nfrom pytesseract import image_to_string\n\n# The request library is used to fetch content through HTTP\nfrom requests import Session\n\nfrom .JP import fetch_production as jp_fetch_production\n\n# please try to write PEP8 compliant code (use a linter). One of PEP8's\n# requirement is to limit your line length to 79 characters.\n\nTIMEZONE = ZoneInfo(\"Asia/Tokyo\")\n\n\ndef fetch_production(\n    zone_key: str = \"JP-KN\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    \"\"\"\n    This method adds nuclear production on top of the solar data returned by the JP parser.\n    It tries to match the solar data with the nuclear data.\n    If there is a difference of more than 30 minutes between solar and nuclear data, the method will fail.\n    \"\"\"\n    session = session or Session()\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser can only fetch live data\")\n\n    jp_data = jp_fetch_production(zone_key, session, target_datetime, logger)\n    nuclear_mw, nuclear_datetime = get_nuclear_production()\n    latest = jp_data[\n        -1\n    ]  # latest solar data is the most likely to fit with nuclear production\n    diff = None\n    if nuclear_datetime > latest[\"datetime\"]:\n        diff = nuclear_datetime - latest[\"datetime\"]\n    else:\n        diff = latest[\"datetime\"] - nuclear_datetime\n    if abs(diff.seconds) > 30 * 60:\n        raise Exception(\"Difference between nuclear datetime and JP data is too large\")\n\n    latest[\"production\"][\"nuclear\"] = nuclear_mw\n    latest[\"production\"][\"unknown\"] = latest[\"production\"][\"unknown\"] - nuclear_mw\n    return [latest]\n\n\nURL = (\n    \"https://www.kepco.co.jp/energy_supply/energy/nuclear_power/info/monitor/live_unten\"\n)\nIMAGE_CORE_URL = \"https://www.kepco.co.jp/\"\n\n\ndef get_image_text(img_url, lang, width=None):\n    \"\"\"\n    Fetches image based on URL, crops it and extract text from the image.\n    \"\"\"\n    r = Request(img_url, headers={\"User-Agent\": \"Mozilla/5.0\"})\n    img_bytes = urlopen(r).read()\n    img = Image.open(BytesIO(img_bytes))\n    height = img.size[1]\n\n    if width is None:\n        width = 160\n\n    img = img.crop((0, int(height / 8), width, height))\n    # cropping the image, makes it easier to read for tesseract\n    text = image_to_string(img, lang=lang)\n    return text\n\n\ndef extract_capacity(tr):\n    \"\"\"\n    The capacity for each unit has the class \"list03\".\n    and it uses the chinese symbol for 10k(万).\n    If this changes, the method will become inaccurate.\n    \"\"\"\n    td = tr.findAll(\"td\", {\"class\": \"list03\"})\n    if len(td) == 0:\n        return None\n    raw_text = td[0].getText()\n    kw_energy = raw_text.split(\"万\")[0]\n    return float(kw_energy) * 10000\n\n\ndef extract_operation_percentage(tr):\n    \"\"\"Operation percentage is located on images of type .gif\"\"\"\n    td = tr.findAll(\"img\")\n    if len(td) == 0:\n        return None\n    img = td[0]\n    url = IMAGE_CORE_URL + img[\"src\"]\n    if \".gif\" in url:\n        text = get_image_text(url, \"eng\", width=65)\n        # will return a number and percentage eg (\"104%\"). Sometimes a little more eg: (\"104% 4...\")\n        split = text.split(\"%\")\n        if len(split) == 0:\n            return None\n        return float(split[0]) / 100\n    else:\n        return None\n\n\ndef extract_time(soup):\n    \"\"\"\n    Time is located in an image.\n    Decipher the text containing the data and assumes there will only be 4 digits making up the datetime.\n    \"\"\"\n    img_relative = soup.findAll(\"img\", {\"class\": \"time-data\"})[0][\"src\"]\n    img_url_full = IMAGE_CORE_URL + img_relative\n    text = get_image_text(img_url_full, \"jpn\")\n    digits = re.findall(r\"\\d+\", text)\n    digits = [int(x) for x in digits]\n    if len(digits) != 4:\n        # something went wrong while extracting time from Japan\n        raise Exception(\"Something went wrong while extracting local time\")\n\n    nuclear_datetime = datetime.now(tz=TIMEZONE).replace(\n        month=digits[0],\n        day=digits[1],\n        hour=digits[2],\n        minute=digits[3],\n        second=0,\n        microsecond=0,\n    )\n    return nuclear_datetime\n\n\ndef get_nuclear_production():\n    \"\"\"\n    Fetches all the rows that contains data of nuclear units and calculates the total kw generated by all plants.\n    Illogically, all the rows has the class \"mihama_realtime\" which they might fix in the future.\n    \"\"\"\n    r = Request(URL, headers={\"User-Agent\": \"Mozilla/5.0\"})\n    html = urlopen(r).read()\n    soup = BeautifulSoup(html, \"html.parser\")\n\n    nuclear_datetime = extract_time(soup)\n    _rows = soup.findAll(\n        \"tr\", {\"class\": \"mihama_realtime\"}\n    )  # TODO: Should we just remove this?\n    tr_list = soup.findAll(\"tr\")\n\n    total_kw = 0\n    for tr in tr_list:\n        capacity = extract_capacity(tr)\n        operation_percentage = extract_operation_percentage(tr)\n        if capacity is None or operation_percentage is None:\n            continue\n        kw = capacity * operation_percentage\n        total_kw = total_kw + kw\n    nuclear_mw = total_kw / 1000.0  # convert to mw\n\n    return nuclear_mw, nuclear_datetime\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/JP_KY.py",
    "content": "#!/usr/bin/env python3\nimport io\nimport re\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\n\n# The request library is used to fetch content through HTTP\nfrom requests import Session, get\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers import occtonet\n\nTIMEZONE = ZoneInfo(\"Asia/Tokyo\")\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"JP-KY\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given zone.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    production_list = ProductionBreakdownList(logger)\n\n    # url for consumption and solar\n    url = f\"https://www.kyuden.co.jp/td_power_usages/csv/juyo-hourly-{datetime.now(tz=TIMEZONE).strftime('%Y%m%d')}.csv\"\n    response = get(url)\n    content = response.text\n\n    # Filter out the irrelevant data\n    start_idx = content.rfind(\"DATE,TIME\")\n    if start_idx == -1:\n        logger.error(\n            \"Could not find time series data section in solar and consumption CSV\"\n        )\n        return production_list.to_list()\n    time_series_section = content[start_idx:]\n    df = pd.read_csv(io.StringIO(time_series_section))\n\n    # Translate column names to english\n    df.columns = [\"DATE\", \"TIME\", \"consumption\", \"solar\"]\n\n    last_complete_row = df.dropna().iloc[-1]\n\n    dt = datetime.strptime(\n        f\"{last_complete_row['DATE']} {last_complete_row['TIME']}\", \"%Y/%m/%d %H:%M\"\n    )\n    dt = dt.replace(tzinfo=TIMEZONE)\n\n    # Get values in MW - convert from 10000 kW to MW\n    consumption = last_complete_row[\"consumption\"].astype(float) * 10\n    solar = last_complete_row[\"solar\"].astype(float) * 10\n\n    # add two nuclear power plants at Sendai and Genkai\n    sendai_url = (\n        \"http://www.kyuden.co.jp/php/nuclear/sendai/rename.php?\"\n        \"A=s_power.fdat&B=ncp_state.fdat&_=1520532401043\"\n    )\n    genkai_url = (\n        \"http://www.kyuden.co.jp/php/nuclear/genkai/rename.php?\"\n        \"A=g_power.fdat&B=ncp_state.fdat&_=1520532904073\"\n    )\n\n    sendai_raw_text = get(sendai_url).text\n    genkai_raw_text = get(genkai_url).text\n\n    regex = r\"(?<=gouki=)[-+]?[.]?[\\d]+(?:,\\d\\d\\d)*[\\.]?\\d*\" + r\"(?:[eE][-+]?\\d+)?(?=&)\"\n    sendai_values = re.findall(regex, sendai_raw_text)\n    genkai_values = re.findall(regex, genkai_raw_text)\n\n    sendai_total = sum(map(float, sendai_values))\n    genkai_total = sum(map(float, genkai_values))\n\n    nuclear = sendai_total + genkai_total\n    # convert from 万kW to MW\n    nuclear *= 10\n\n    # add the exchange JP-CG->JP-KY\n    exchanges = occtonet.fetch_exchange(\"JP-KY\", \"JP-CG\")\n    # find the nearest exchanges in time to consumption timestamp\n    nearest_exchanges = sorted(\n        exchanges, key=lambda exchange: abs(exchange[\"datetime\"] - dt)\n    )\n    # take the nearest exchange\n    exchange = nearest_exchanges[0]\n\n    # check that consumption and exchange timestamps are within a 15 minute window\n    if abs(dt - exchange[\"datetime\"]).seconds <= 900:\n        generation = consumption - exchange[\"netFlow\"]\n        unknown = generation - nuclear - solar\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            production=ProductionMix(\n                biomass=0,\n                coal=0,\n                gas=0,\n                nuclear=nuclear,\n                oil=0,\n                solar=solar,\n                unknown=unknown,\n            ),\n            source=\"www.kyuden.co.jp\",\n        )\n\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/JP_SK.py",
    "content": "import re\nfrom datetime import datetime\nfrom io import BytesIO\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom PIL import Image\nfrom pytesseract import image_to_string\n\n# The request library is used to fetch content through HTTP\nfrom requests import Session\n\nfrom .JP import fetch_production as JP_fetch_production\n\n# please try to write PEP8 compliant code (use a linter). One of PEP8's\n# requirement is to limit your line length to 79 characters.\n\nJP_TZ = ZoneInfo(\"Asia/Tokyo\")\n\n\ndef fetch_production(\n    zone_key: str = \"JP-SK\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    \"\"\"\n    This method adds nuclear production on top of the solar data returned by the JP parser.\n    It tries to match the solar + unknown data with the nuclear data.\n    \"\"\"\n\n    if session is None:\n        session = Session()\n\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser can only fetch live data\")\n    # fetch data from TSO - unknown + solar\n    JP_data = JP_fetch_production(zone_key, session, target_datetime, logger)\n    # we fetch the latest data point from the JP parser\n    latest_data_point_JP_SK = JP_data[-1]\n    # Fetch nuclear data from the nuclear power plant website\n    ## fetch image url\n    image_url = get_nuclear_power_image_url(session)\n    ## fetch nuclear power from image url\n    (\n        nuclear_power_MW,\n        datetime_nuclear,\n    ) = get_nuclear_power_value_and_timestamp_from_image_url(image_url, session)\n    if (\n        latest_data_point_JP_SK[\"datetime\"] - datetime_nuclear\n    ).total_seconds() / 3600 > 1:\n        latest_data_point_JP_SK[\"production\"][\"nuclear\"] = None\n        logger.info(\"The nuclear data is not close to the parser data\")\n    elif (\n        latest_data_point_JP_SK[\"datetime\"] - datetime_nuclear\n    ).total_seconds() / 3600 <= 1:\n        latest_data_point_JP_SK[\"production\"][\"nuclear\"] = nuclear_power_MW\n    return [latest_data_point_JP_SK]\n\n\nNUCLEAR_REPORT_URL = \"https://www.yonden.co.jp/energy/atom/ikata/ikt722.html\"\nIMAGE_CORE_URL = \"https://www.yonden.co.jp/energy/atom/ikata/\"\n\n\ndef get_nuclear_power_image_url(session: Session) -> str:\n    \"\"\"This method fetches the image url from the nuclear power plant website\"\"\"\n    response_main_page = session.get(NUCLEAR_REPORT_URL)\n    soup = BeautifulSoup(response_main_page.content, \"html.parser\")\n    images_links = soup.find_all(\"img\", src=True)\n    filtered_img_tags = [tag for tag in images_links if \"ikt721-1\" in tag[\"src\"]]\n    if len(filtered_img_tags) == 0:\n        raise Exception(\"No image found\")\n    img_url = IMAGE_CORE_URL + filtered_img_tags[0][\"src\"]\n    return img_url\n\n\ndef get_nuclear_power_value_and_timestamp_from_image_url(\n    img_url: str, session: Session\n) -> tuple[float, datetime]:\n    \"\"\"This method reads the image from the image url and extracts nuclear power and timestamp from it.\"\"\"\n    response_image = session.get(img_url)\n    image = Image.open(BytesIO(response_image.content))\n    width, height = image.size\n    img = image.crop((0, 0, width, height))\n    text = str(image_to_string(img))\n    numeric_pattern = r\"\\d+\"\n    # this method extracts the second number from the image since it is the nuclear power value from the image\n    # in case the image format changes, this method will need to be updated\n    nuclear_power = float(re.findall(numeric_pattern, text)[1])\n    # extract timestamp from image_url and convert it to datetime\n    timestamp_pattern = r\"\\d{12}\"\n    timestamp = re.findall(timestamp_pattern, img_url)[0]\n    datetime_nuclear = datetime.strptime(timestamp, \"%Y%m%d%H%M\").replace(tzinfo=JP_TZ)\n    return nuclear_power, datetime_nuclear\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/KPX.py",
    "content": "import json\nimport re\nfrom datetime import datetime, time, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    PriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency, use_proxy\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\nTIMEZONE = ZoneInfo(\"Asia/Seoul\")\nKR_CURRENCY = \"KRW\"\nKR_SOURCE = \"new.kpx.or.kr\"\nREAL_TIME_URL = \"https://new.kpx.or.kr/powerinfoSubmain.es?mid=a10606030000\"\nPRICE_URL = \"https://new.kpx.or.kr/smpInland.es?mid=a10606080100&device=pc\"\nHISTORICAL_PRODUCTION_URL = (\n    \"https://new.kpx.or.kr/powerSource.es?mid=a10606030000&device=chart\"\n)\n\n#### Classification of New & Renewable Energy Sources ####\n#\n# Source: https://cms.khnp.co.kr/eng/content/563/main.do?mnCd=EN040101\n# New energy: Hydrogen, Fuel Cell, Coal liquefied or gasified energy, and vacuum residue gasified energy, etc.\n# Renewable: Solar, Wind power, Water power, ocean energy, Geothermal, Bio energy, etc.\n#\nPRODUCTION_MAPPING = {\n    \"coal\": \"coal\",\n    \"localCoal\": \"coal\",\n    \"gas\": \"gas\",\n    \"oil\": \"oil\",\n    \"nuclearPower\": \"nuclear\",\n    \"waterPower\": \"hydro\",\n    \"windPower\": \"wind\",\n    \"sunlight\": \"solar\",\n    \"newRenewable\": \"unknown\",\n}\nSTORAGE_MAPPING = {\n    \"raisingWater\": \"hydro\",\n}\nIGNORE_LIST = [\n    \"ppa\",\n    \"btm\",\n    \"newRenewablePlusWindPower\",\n    \"once\",\n    \"regDate\",\n    \"seq\",\n]\n\n\ndef parse_consumption_data(\n    raw_data: str,\n    zone_key: ZoneKey = ZoneKey(\"KR\"),\n    logger: Logger = getLogger(__name__),\n) -> TotalConsumptionList:\n    consumption_list = TotalConsumptionList(logger)\n\n    # The realtime page embeds consumption data inside a drawChart() function as JS arrays:\n    # x = total demand (총수요) including behind-the-meter generation,\n    # v = market demand (전력시장수요) excluding self-consumption.\n    # We use x as it represents total system consumption per Electricity Maps definition.\n    # Anchoring to drawChart() avoids false matches on other var x declarations in the page.\n    draw_chart_match = re.search(\n        r\"function drawChart[^{]*\\{(.*?)(?=function\\s|\\Z)\", raw_data, re.DOTALL\n    )\n    if not draw_chart_match:\n        raise ParserException(\n            \"KPX.py\",\n            \"Could not find drawChart function in response\",\n            zone_key,\n        )\n    draw_chart_body = draw_chart_match.group(1)\n    values_match = re.search(r\"var x\\s*=\\s*\\[([\\d.,\\s]+)\\]\", draw_chart_body)\n    times_match = re.search(r\"var t_time\\s*=\\s*\\[([\\d,\\s]+)\\]\", draw_chart_body)\n\n    if not values_match or not times_match:\n        raise ParserException(\n            \"KPX.py\",\n            \"Could not find consumption time series in response\",\n            zone_key,\n        )\n\n    values = [float(v.strip()) for v in values_match.group(1).split(\",\") if v.strip()]\n    timestamps = [t.strip() for t in times_match.group(1).split(\",\") if t.strip()]\n\n    for ts, val in zip(timestamps, values, strict=True):\n        dt = datetime.strptime(ts, \"%Y%m%d%H%M%S\").replace(tzinfo=TIMEZONE)\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            source=KR_SOURCE,\n            consumption=val,\n        )\n\n    return consumption_list\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"KR\")\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"KR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    session = session or Session()\n    if target_datetime:\n        raise ParserException(\n            \"KPX.py\",\n            \"This parser is not yet able to parse past dates\",\n            zone_key,\n        )\n\n    logger.debug(f\"Fetching consumption data from {REAL_TIME_URL}\")\n    response = session.get(REAL_TIME_URL, verify=False)\n    assert response.ok\n\n    return parse_consumption_data(response.text, zone_key, logger).to_list()\n\n\n@refetch_frequency(timedelta(hours=167))\n@use_proxy(country_code=\"KR\")\ndef fetch_price(\n    zone_key: ZoneKey = ZoneKey(\"KR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    session = session or Session()\n    now = datetime.now(tz=TIMEZONE)\n    target_datetime = (\n        now if target_datetime is None else target_datetime.astimezone(TIMEZONE)\n    )\n\n    today = datetime.combine(now, time(), tzinfo=TIMEZONE)  # truncates to day\n    first_available_api_date = today - timedelta(days=6) + timedelta(hours=1)\n    if target_datetime < first_available_api_date:\n        raise ParserException(\n            \"KPX.py\",\n            \"This parser is not able to parse dates more than one week in the past.\",\n            zone_key,\n        )\n\n    logger.debug(f\"Fetching price data from {PRICE_URL}\")\n    response = session.get(PRICE_URL, verify=False)\n    assert response.ok\n\n    price_list = PriceList(logger)\n\n    table_prices = pd.read_html(response.text, header=0)[0]\n    for col_idx in range(1, table_prices.shape[1]):\n        for row_idx in range(24):\n            day = col_idx\n            hour = row_idx + 1\n\n            if hour == 24:\n                hour = 0\n                day += 1\n\n            dt = (now + timedelta(days=-1 * (7 - day))).replace(\n                hour=hour, minute=0, second=0, microsecond=0\n            )\n\n            price_value = (\n                table_prices.iloc[row_idx, col_idx] * 1000\n            )  # Convert from Won/kWh to Won/MWh\n\n            price_list.append(\n                zoneKey=zone_key,\n                datetime=dt,\n                source=KR_SOURCE,\n                price=price_value,\n                currency=KR_CURRENCY,\n            )\n\n    return price_list.to_list()\n\n\ndef parse_chart_prod_data(\n    raw_data: str,\n    zone_key: ZoneKey = ZoneKey(\"KR\"),\n    logger: Logger = getLogger(__name__),\n) -> ProductionBreakdownList:\n    production_list = ProductionBreakdownList(logger)\n\n    # Extract object with data\n    json_string = re.search(r\"var ictArr = (\\[\\{.+\\}\\]);\", raw_data).group(1)\n    json_obj = json.loads(json_string)\n\n    for item in json_obj:\n        if item[\"regDate\"] == \"0\":\n            break\n\n        dt = datetime.strptime(item[\"regDate\"], \"%Y-%m-%d %H:%M\").replace(\n            tzinfo=TIMEZONE\n        )\n\n        production_mix = ProductionMix()\n        storage_mix = StorageMix()\n        for item_key, item_value in item.items():\n            if item_key in IGNORE_LIST:\n                continue\n            elif item_key in PRODUCTION_MAPPING:\n                production_mix.add_value(\n                    PRODUCTION_MAPPING[item_key],\n                    float(item_value),\n                    correct_negative_with_zero=True,\n                )\n            elif item_key in STORAGE_MAPPING:\n                storage_mix.add_value(STORAGE_MAPPING[item_key], -float(item_value))\n            else:\n                logger.warning(f\"Unknown mode {item_key} with value {item_value}\")\n\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            source=KR_SOURCE,\n            production=production_mix,\n            storage=storage_mix,\n        )\n\n    return production_list\n\n\ndef get_real_time_prod_data(\n    zone_key: ZoneKey = ZoneKey(\"KR\"),\n    session: Session | None = None,\n    logger: Logger = getLogger(__name__),\n) -> ProductionBreakdownList:\n    session = session or Session()\n    res = session.get(REAL_TIME_URL, verify=False)\n    return parse_chart_prod_data(res.text, zone_key, logger)\n\n\ndef get_historical_prod_data(\n    zone_key: ZoneKey = ZoneKey(\"KR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> ProductionBreakdownList:\n    session = session or Session()\n    target_datetime_formatted_daily = target_datetime.strftime(\"%Y-%m-%d\")\n\n    # CSRF token is needed to access the production data\n    logger.debug(\n        f\"Fetching CSRF token to access production data from {HISTORICAL_PRODUCTION_URL}\"\n    )\n    session.get(HISTORICAL_PRODUCTION_URL, verify=False)\n    cookies_dict = session.cookies.get_dict()\n\n    payload = {\n        \"mid\": \"a10606030000\",\n        \"device\": \"chart\",\n        \"view_sdate\": target_datetime_formatted_daily,\n        \"view_edate\": target_datetime_formatted_daily,\n        \"_csrf\": cookies_dict.get(\"XSRF-TOKEN\", None),\n    }\n\n    logger.debug(f\"Fetching production data from {HISTORICAL_PRODUCTION_URL}\")\n    res = session.post(HISTORICAL_PRODUCTION_URL, payload)\n    assert res.ok\n\n    return parse_chart_prod_data(res.text, zone_key, logger)\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"KR\")\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"KR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    session = session or Session()\n    first_available_date = datetime(2021, 12, 22, 0, 0, 0, tzinfo=TIMEZONE)\n    if target_datetime is not None and target_datetime < first_available_date:\n        raise ParserException(\n            \"KPX.py\",\n            \"This parser is not able to parse dates before 2021-12-22.\",\n            zone_key,\n        )\n\n    if target_datetime is None:\n        production_list = get_real_time_prod_data(\n            zone_key=zone_key, session=session, logger=logger\n        )\n    else:\n        production_list = get_historical_prod_data(\n            zone_key=zone_key,\n            session=session,\n            target_datetime=target_datetime,\n            logger=logger,\n        )\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    target_datetime = datetime(2022, 2, 7, 16, 35, 0, tzinfo=TIMEZONE)\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(fetch_production(target_datetime=target_datetime))\n\n    print(\"fetch_price() -> \")\n    print(fetch_price())\n\n    print(\"fetch_consumption() -> \")\n    print(fetch_consumption())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/KW.py",
    "content": "\"\"\"\nThis parser returns Kuwait's electricity system load\nSource: Ministry of Electricity and Water / State of Kuwait\nURL: https://www.mew.gov.kw/en/\nScroll down to see the system load gauge\nShares of Electricity production in 2017: 65.6% oil, 34.4% gas (source: IEA; https://www.iea.org/statistics/?country=KUWAIT&indicator=ElecGenByFuel)\n\"\"\"\n\nimport re\nimport ssl\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport requests\nimport urllib3\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    TotalConsumptionList,\n)\n\n\n# A workaround is required to connect to the API as of 2025-01-14, to avoid the\n# following error:\n#\n#     SSLError(1, '[SSL: UNSAFE_LEGACY_RENEGOTIATION_DISABLED] unsafe legacy renegotiation disabled (_ssl.c:1007)')\n#\n# The workaround is based on https://stackoverflow.com/a/73519818/2220152.\n#\nclass _CustomHttpAdapter(requests.adapters.HTTPAdapter):\n    # \"Transport adapter\" that allows us to use custom ssl_context.\n\n    def __init__(self, ssl_context=None, **kwargs):\n        self.ssl_context = ssl_context\n        super().__init__(**kwargs)\n\n    def init_poolmanager(self, connections, maxsize, block=False):\n        self.poolmanager = urllib3.poolmanager.PoolManager(\n            num_pools=connections,\n            maxsize=maxsize,\n            block=block,\n            ssl_context=self.ssl_context,\n        )\n\n\ndef _patch_session_for_legacy_connect(session):\n    ctx = ssl.create_default_context(ssl.Purpose.SERVER_AUTH)\n    ctx.options |= 0x4  # OP_LEGACY_SERVER_CONNECT\n    session.mount(\"https://\", _CustomHttpAdapter(ctx))\n    return session\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"KW\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n    r = _patch_session_for_legacy_connect(session or Session())\n\n    url = \"https://www.mew.gov.kw/en\"\n    response = r.get(url)\n    # The regexp gets the load value from a line looking like this:\n    #\n    # var obj= {\"maxValue\":10865,\"currentValue\":7285,\"highlights\":[{\"from\":0,\"to\":10179,\"color\":\"#83e043\"},{\"from\":10179,\"to\":10604,\"color\":\"#ff6a00\"},{\"from\":10604,\"to\":10865,\"color\":\"#f12828\"}]};\n    #\n    load = re.findall(r'\"currentValue\":(\\d+)', response.text)\n    load = int(load[0])\n    consumption = load\n    consumption_list = TotalConsumptionList(logger=logger)\n    consumption_list.append(\n        zoneKey=zone_key,\n        datetime=datetime.now(tz=ZoneInfo(\"Asia/Kuwait\")),\n        consumption=consumption,\n        source=\"mew.gov.kw\",\n    )\n\n    return consumption_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the electricityMap backend, but handy for testing.\"\"\"\n\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/MD.py",
    "content": "\"\"\"Parser for Moldova.\"\"\"\n\n# Further information on the equipment used at CERS Moldovenească can be found at:\n# http://moldgres.com/o-predpriyatii/equipment\n# Further information on the fuel-mix used at CERS Moldovenească can be found at:\n# http://moldgres.com/search/%D0%9F%D1%80%D0%BE%D0%B8%D0%B7%D0%B2%D0%BE%D0%B4%D1%81%D1%82%D0%B2%D0%B5%D0%BD%D0%BD%D1%8B%D0%B5%20%D0%BF%D0%BE%D0%BA%D0%B0%D0%B7%D0%B0%D1%82%D0%B5%D0%BB%D0%B8\n# (by searching for 'Производственные показатели' aka. 'Performance Indicators')\n# Data for the fuel-mix at CERS Moldovenească for the year 2020 can be found at:\n# http://moldgres.com/wp-content/uploads/2021/02/proizvodstvennye-pokazateli-zao-moldavskaja-gres-za-2020-god.pdf\n\n# Annual reports from moldelectrica can be found at:\n# https://moldelectrica.md/ro/network/annual_report\n\nfrom datetime import datetime, time, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom operator import attrgetter\nfrom typing import NamedTuple\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    PriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import EventSourceType, ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"MD.py\"\nTZ = ZoneInfo(\"Europe/Chisinau\")\nZONE_KEY = ZoneKey(\"MD\")\n\n# Supports the following formats:\n# - type=csv for zip-data with semicolon-separated-values\n# - type=array for a 2D json-array containing an array for each datapoint\n# - type=html for a HTML-table (default when no type is given)\nARCHIVE_BASE_URL = \"https://moldelectrica.md/utils/archive2.php?id=table&type=array\"\nSOURCE = \"moldelectrica.md\"\n\n\n# Moldoelectrica electricity tariffs as defined by government-agency decisions.\n_MOLDOELECTRICA_NEW_POWER_PRICE_IN_MDL_PER_MW = {\n    # https://www.legis.md/cautare/getResults?doc_id=78826&lang=ro\n    datetime(2000, 4, 1, tzinfo=timezone.utc): 18.8,\n    # https://www.legis.md/cautare/getResults?doc_id=103953&lang=ro\n    datetime(2001, 10, 1, tzinfo=timezone.utc): 28.0,\n    # https://www.legis.md/cautare/getResults?doc_id=40249&lang=ro\n    datetime(2002, 9, 1, tzinfo=timezone.utc): 35.2,\n    # https://www.legis.md/cautare/getResults?doc_id=42701&lang=ro\n    datetime(2005, 9, 1, tzinfo=timezone.utc): 39.3,\n    # https://www.legis.md/cautare/getResults?doc_id=10948&lang=ro\n    datetime(2007, 8, 3, tzinfo=timezone.utc): 51.8,\n    # https://www.legis.md/cautare/getResults?doc_id=40130&lang=ro\n    datetime(2010, 1, 19, tzinfo=timezone.utc): 63.2,\n    # https://www.legis.md/cautare/getResults?doc_id=40589&lang=ro\n    datetime(2012, 5, 11, tzinfo=timezone.utc): 80.2,\n    # https://www.legis.md/cautare/getResults?doc_id=84436&lang=ro\n    datetime(2015, 7, 31, tzinfo=timezone.utc): 145.0,\n    # https://www.legis.md/cautare/getResults?doc_id=134854&lang=ro\n    datetime(2023, 12, 31, tzinfo=timezone.utc): 201.0,\n    # https://www.legis.md/cautare/getResults?doc_id=142391&lang=ro\n    datetime(2024, 3, 21, tzinfo=timezone.utc): 185.0,\n    # TODO(amv213): update as new tariffs get rolled out...\n}\n\n\nclass ArchiveDatapoint(NamedTuple):\n    \"\"\"Datapoint returned by the archive_url with ordered fetchable fields.\"\"\"\n\n    datetime: datetime\n    consumption: float | None\n    planned_consumption: float | None\n    production: float | None\n    planned_production: float | None\n    tpp: float | None  # production from thermal power plants\n    hpp: float | None  # production from hydro power plants\n    res: float | None  # production from renewable energy sources\n    exchange_UA_to_MD: float | None\n    planned_exchange_UA_to_MD: float | None\n    exchange_RO_to_MD: float | None\n    planned_exchange_RO_to_MD: float | None\n\n\ndef _get_archive_data(\n    target_datetime: datetime | None,\n    session: Session | None,\n    num_backlog_days: int = 0,\n) -> list[ArchiveDatapoint]:\n    \"\"\"Returns archive data in 15 mn buckets for the UTC day of interest and (optionally) previous ones.\"\"\"\n\n    target_utc_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n\n    target_utc_day = datetime.combine(target_utc_datetime, time(), tzinfo=timezone.utc)\n    target_utc_timestamp_from, target_utc_timestamp_to = (\n        target_utc_day - timedelta(days=num_backlog_days),\n        target_utc_day + timedelta(days=1) - timedelta(seconds=1),\n    )\n\n    # the API works in local (TZ) timestamps\n    date1 = target_utc_timestamp_from.astimezone(TZ).strftime(\"%d.%m.%Y\")\n    date2 = target_utc_timestamp_to.astimezone(TZ).strftime(\"%d.%m.%Y\")\n    archive_url = f\"{ARCHIVE_BASE_URL}&date1={date1}&date2={date2}\"\n\n    s = session or Session()\n    response = s.get(archive_url)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching data error code: {response.status_code}: {response.text}\",\n        )\n\n    data = response.json()\n\n    try:\n        archive_datapoints = []\n        for entry in data:\n            dt_utc = (\n                datetime.strptime(entry[0], \"%Y-%m-%d %H:%M\")\n                .replace(tzinfo=TZ)\n                .astimezone(timezone.utc)\n            )\n\n            # filter out results outside of UTC target range\n            # The API returns data for whole TZ days, so some data might be outside boundaries\n            if dt_utc < target_utc_timestamp_from or dt_utc > target_utc_timestamp_to:\n                continue\n\n            # keep in mind that some values might be null\n            datapoint = ArchiveDatapoint(\n                dt_utc, *(float(x) if x is not None else x for x in entry[1:])\n            )\n            archive_datapoints.append(datapoint)\n\n        return sorted(archive_datapoints, key=attrgetter(\"datetime\"))\n\n    except Exception as e:\n        raise ParserException(\n            \"MD.py\",\n            \"Not able to parse received data. Check that the specifed URL returns correct data.\",\n        ) from e\n\n\ndef fetch_price(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known power price of a given zone.\n\n    This will be a static power price for Moldoelectrica electricity as defined by government-agency decision.\n\n    References:\n        https://www.anre.md/energie-electrica-3-290\n        https://moldelectrica.md/ro/activity/tariff\n    \"\"\"\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n\n    # find price band for given target datetime\n    prices = iter(_MOLDOELECTRICA_NEW_POWER_PRICE_IN_MDL_PER_MW.items())\n    _, price = next(\n        prices\n    )  # assume base price for times before we could find references\n    for dt, new_price in prices:\n        if target_datetime < dt:\n            break\n        price = new_price\n\n    price_list = PriceList(logger=logger)\n    price_list.append(\n        zoneKey=zone_key,\n        datetime=target_datetime.replace(minute=0, second=0, microsecond=0),\n        source=SOURCE,\n        price=price,\n        currency=\"MDL\",\n    )\n    return price_list.to_list()\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_consumption(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known power consumption (in MW) of a given zone.\"\"\"\n    archive_data = _get_archive_data(\n        target_datetime, session=session, num_backlog_days=1\n    )\n\n    consumption_list = TotalConsumptionList(logger=logger)\n\n    for archive_datapoint in archive_data:\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=archive_datapoint.datetime,\n            source=SOURCE,\n            consumption=archive_datapoint.consumption,\n        )\n    return consumption_list.to_list()\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the production mix (in MW) of a given zone.\"\"\"\n\n    archive_data = _get_archive_data(\n        target_datetime, session=session, num_backlog_days=1\n    )\n\n    production_list = ProductionBreakdownList(logger=logger)\n\n    for archive_datapoint in archive_data:\n        production_mix = ProductionMix()\n        production_mix.add_value(\"gas\", archive_datapoint.tpp)\n        production_mix.add_value(\"hydro\", archive_datapoint.hpp)\n        # Renewables (solar + biogas + wind) make up a small part of the energy produced.\n        # The exact mix of renewable energy sources is unknown,\n        # so everything is attributed to biomass.\n        production_mix.add_value(\"biomass\", archive_datapoint.res)\n\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=archive_datapoint.datetime,\n            source=SOURCE,\n            production=production_mix,\n        )\n\n    return production_list.to_list()\n\n\ndef _fetch_exchange(\n    event_type: EventSourceType,\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None,\n    target_datetime: datetime | None,\n    logger: Logger,\n    num_backlog_days: int,\n) -> list[dict]:\n    \"\"\"Requests measured or forecasted power exchange (in MW) between two zones.\"\"\"\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    if ZONE_KEY not in {zone_key1, zone_key2}:\n        raise ParserException(\n            PARSER,\n            f\"This parser can only parse exchanges to / from {ZONE_KEY}.\",\n            sorted_zone_keys,\n        )\n\n    archive_data = _get_archive_data(\n        target_datetime,\n        session=session,\n        num_backlog_days=num_backlog_days,\n    )\n\n    use_actual = event_type == EventSourceType.measured\n\n    exchange_list = ExchangeList(logger=logger)\n    for entry in archive_data:\n        netflow = None\n\n        if sorted_zone_keys == ZoneKey(\"MD->UA\"):\n            netflow = (\n                entry.exchange_UA_to_MD\n                if use_actual\n                else entry.planned_exchange_UA_to_MD\n            )\n\n        elif sorted_zone_keys == ZoneKey(\"MD->RO\"):\n            netflow = (\n                entry.exchange_RO_to_MD\n                if use_actual\n                else entry.planned_exchange_RO_to_MD\n            )\n        else:\n            raise NotImplementedError(f\"{sorted_zone_keys} pair is not implemented\")\n\n        if netflow != 0 and netflow is not None:\n            netflow *= -1\n\n        exchange_list.append(\n            zoneKey=sorted_zone_keys,\n            datetime=entry.datetime,\n            netFlow=netflow,\n            source=SOURCE,\n            sourceType=event_type,\n        )\n\n    return exchange_list.to_list()\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the known power exchange (in MW) between two zones.\"\"\"\n    return _fetch_exchange(\n        event_type=EventSourceType.measured,\n        zone_key1=zone_key1,\n        zone_key2=zone_key2,\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n        num_backlog_days=1,\n    )\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_exchange_forecast(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the forecasted power exchange (in MW) between two zones.\"\"\"\n    return _fetch_exchange(\n        event_type=EventSourceType.forecasted,\n        zone_key1=zone_key1,\n        zone_key2=zone_key2,\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n        num_backlog_days=1,\n    )\n\n\nif __name__ == \"__main__\":\n    # Main method, never used by the Electricity Map backend, but handy for testing.\n\n    for target_datetime in (None, datetime.fromisoformat(\"2021-07-25T15:00+00:00\")):\n        print(f\"fetch_price({target_datetime=}) ->\")\n        print(fetch_price(target_datetime=target_datetime))\n\n        print(f\"fetch_consumption({target_datetime=}) ->\")\n        print(fetch_consumption(target_datetime=target_datetime))\n\n        print(f\"fetch_production({target_datetime=}) ->\")\n        print(fetch_production(target_datetime=target_datetime))\n\n        for neighbour in [\"RO\", \"UA\"]:\n            print(f\"fetch_exchange({ZONE_KEY}, {neighbour}, {target_datetime=}) ->\")\n            print(\n                fetch_exchange(\n                    ZONE_KEY, ZoneKey(neighbour), target_datetime=target_datetime\n                )\n            )\n\n            print(\n                f\"fetch_exchange_forecast({ZONE_KEY}, {neighbour}, {target_datetime=}) ->\"\n            )\n            print(\n                fetch_exchange_forecast(\n                    ZONE_KEY, ZoneKey(neighbour), target_datetime=target_datetime\n                )\n            )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/MN.py",
    "content": "#!/usr/bin/env python3\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\nNDC_API = \"https://disnews.energy.mn/convertt.php\"\nTZ = ZoneInfo(\"Asia/Ulaanbaatar\")  # UTC+8\n\n# https://ndc.energy.mn/ provides a list with icons and numbers next to them,\n# where the JSON response from https://disnews.energy.mn/convertt.php is used to\n# populate the numbers. Below is a formatted JSON response from 2025-01-13:\n#\n#     {\n#         \"date\": \"2025-01-14 03:00:00\",\n#         \"syssum\": \"1351.8\",\n#         \"dts\": 1061,\n#         \"sumnar\": -0.5,\n#         \"sumsalhit\": 128.6,\n#         \"energyimport\": \"162.7\",\n#         \"t\": \"-20.2\",\n#         \"Songino\": \"-23.9\"\n#     }\n#\n# Notes:\n# - dts is assumed to be coal, as coal is reported as the main source of\n#   electricity for mongolia.\n# - Songino is ignored for now, but it seems to be a specific area of Mongolia.\n#   Ideally we'd figure out if we should make use of this value.\n# - t is temperature, and ignored.\n#\nJSON_API_MAPPING = {\n    \"date\": \"datetime\",\n    \"syssum\": \"consumption\",\n    \"energyimport\": \"import\",  # positive = import\n    \"dts\": \"coal\",\n    \"sumnar\": \"solar\",\n    \"sumsalhit\": \"wind\",\n}\n\n\ndef _fetch_and_parse(session: Session) -> dict[str, Any]:\n    \"\"\"\n    Fetches and parses consumption and production data from a JSON API seen used\n    at https://ndc.energy.mn/.\n    \"\"\"\n    response: Response = session.get(NDC_API)\n    if not response.ok:\n        raise ParserException(\n            parser=\"MN.py\",\n            message=f\"Data request did not succeed: {response.status_code}\",\n        )\n    data = response.json()\n\n    # validate that the expected and required keys are present\n    received_keys = set(data.keys())\n    expected_keys = set(JSON_API_MAPPING.keys())\n    if not set(expected_keys).issubset(received_keys):\n        missing = expected_keys - received_keys\n        raise ParserException(\n            parser=\"MN.py\",\n            message=f\"Fetched JSON didn't include expected keys: {missing}\",\n        )\n\n    # pick out relevant values into a new dictionary with keys with our names\n    result = {JSON_API_MAPPING[k]: data[k] for k in expected_keys}\n\n    # ensure that relevant values are set\n    if None in result.values():\n        raise ParserException(\n            parser=\"MN.py\",\n            message=f\"Fetched values contain null. Fetched data: {result}.\",\n        )\n\n    # parse values\n    for k, v in result.items():\n        if k == \"datetime\":\n            result[k] = datetime.fromisoformat(v).replace(tzinfo=TZ)\n        else:\n            result[k] = float(v)\n    return result\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"MN\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates.\")\n\n    data = _fetch_and_parse(session)\n\n    prod_mix = ProductionMix()\n    prod_mix.add_value(\"coal\", data[\"coal\"])\n    prod_mix.add_value(\"solar\", data[\"solar\"])\n    prod_mix.add_value(\"wind\", data[\"wind\"])\n\n    prod_breakdown_list = ProductionBreakdownList(logger)\n    prod_breakdown_list.append(\n        datetime=data[\"datetime\"],\n        zoneKey=zone_key,\n        source=\"https://ndc.energy.mn/\",\n        production=prod_mix,\n    )\n\n    return prod_breakdown_list.to_list()\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"MN\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates.\")\n\n    data = _fetch_and_parse(session)\n\n    consumption_list = TotalConsumptionList(logger)\n    consumption_list.append(\n        datetime=data[\"datetime\"],\n        zoneKey=zone_key,\n        consumption=data[\"consumption\"],\n        source=\"https://ndc.energy.mn/\",\n    )\n\n    return consumption_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/NED.py",
    "content": "from datetime import datetime, timedelta, timezone\nfrom enum import Enum\nfrom logging import Logger, getLogger\nfrom typing import Any\n\nimport pandas as pd\nimport requests\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    ProductionMix,\n)\nfrom electricitymap.contrib.parsers.ENTSOE import ENTSOE_DOMAIN_MAPPINGS\nfrom electricitymap.contrib.parsers.ENTSOE import (\n    parse_production as ENTSOE_parse_production,\n)\nfrom electricitymap.contrib.parsers.ENTSOE import (\n    query_production as ENTSOE_query_production,\n)\nfrom electricitymap.contrib.parsers.lib.config import ProductionModes, refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.parsers.lib.utils import get_token\nfrom electricitymap.contrib.types import ZoneKey\n\nURL = \"https://api.ned.nl/v1/utilizations\"\n\nTYPE_MAPPING = {\n    1: ProductionModes.WIND,  # Wind Onshore (Wind)\n    2: ProductionModes.SOLAR,  # Solar (Zon)\n    18: ProductionModes.GAS,  # Fossil Gas Power (Aardgas)\n    19: ProductionModes.COAL,  # Fossil Hard Coal (Steenkool)\n    20: ProductionModes.NUCLEAR,  # Nuclear (Kernenergie)\n    21: ProductionModes.BIOMASS,  # Waste Power (Aftval)\n    25: ProductionModes.BIOMASS,  # Biomass Power (Biomassa)\n    26: ProductionModes.UNKNOWN,  # Other Power (Overig)\n    35: ProductionModes.GAS,  # CHP (WKK)\n    51: ProductionModes.WIND,  # Wind Offshore (ZeeWind)\n}\n\n\nclass NedType(Enum):\n    WIND = 1\n    SOLAR = 2\n    FOSSILGASPOWER = 18\n    FOSSILHARDCOAL = 19\n    NUCLEAR = 20\n    WASTEPOWER = 21\n    BIOMASSPOWER = 25\n    OTHERPOWER = 26\n    WKKTOTAL = 35\n    WINDOFFSHORE = 51\n\n\nclass NedActivity(Enum):\n    PRODUCTION = 1\n    CONSUMPTION = 2\n\n\nclass NedGranularity(Enum):\n    TEN_MINUTES = 3\n    FIFTEEN_MINUTES = 4\n    HOURLY = 5\n    DAILY = 6\n    MONTHLY = 7\n    YEARLY = 8\n\n\nclass NedGranularityTimezone(Enum):\n    UTC = 0\n    LOCAL = 1\n\n\nclass NedClassification(Enum):\n    FORECAST = 1\n    MEASURED = 2\n\n\nclass NedPoint(Enum):\n    NETHERLANDS = 0\n\n\n# kWh to MW conversion based on granularity with 6 decimal places\ndef _kwh_to_mw(kwh: float, granularity: int) -> float:\n    \"\"\"\n    Convert kWh to MW based on the time granularity.\n\n    Args:\n        kwh: Energy in kilowatt-hours\n        granularity: NedGranularity value (3=TEN_MINUTES, 4=FIFTEEN_MINUTES, 5=HOURLY)\n\n    Returns:\n        Power in megawatts\n\n    Raises:\n        ParserException: If granularity is not supported\n    \"\"\"\n    # Map granularity to periods per hour\n    granularity_multipliers = {\n        NedGranularity.TEN_MINUTES.value: 6,  # 6 x 10-minute periods per hour\n        NedGranularity.FIFTEEN_MINUTES.value: 4,  # 4 x 15-minute periods per hour\n        NedGranularity.HOURLY.value: 1,  # 1 hour per hour\n    }\n\n    if granularity not in granularity_multipliers:\n        raise ParserException(\n            parser=\"NED.py\",\n            message=f\"Unsupported granularity: {granularity}. Only TEN_MINUTES, FIFTEEN_MINUTES, and HOURLY are supported.\",\n        )\n\n    multiplier = granularity_multipliers[granularity]\n    return round((kwh / 1000) * multiplier, 6)\n\n\n# It seems the API can take max itemPerPage 200. We fetch x items per page as this is: x = (# types * 4 quaters * n hours) < 200\n# If the itemsPerPage is not a multiple of the types the API sometime skips a type, sometimes duplicates a type!\n# The API does not include the last page number in the response, so we need to keep querying until we get an empty response\ndef call_api(target_datetime: datetime, forecast: bool = False):\n    is_last_page = False\n    pageNum = 1\n    results = []\n\n    itemsPerPage = max(\n        [(len(NedType) * 4 * n) for n in range(1, 6) if (len(NedType) * 4 * n) < 200]\n    )\n\n    while not is_last_page:\n        # API fetches full day of data, so we add 1 day to validfrom[before] to get todays data\n        params = {\n            \"page\": pageNum,\n            \"itemsPerPage\": itemsPerPage,\n            \"point\": NedPoint.NETHERLANDS.value,\n            \"type[]\": [\n                NedType.WIND.value,\n                NedType.SOLAR.value,\n                NedType.FOSSILGASPOWER.value,\n                NedType.FOSSILHARDCOAL.value,\n                NedType.NUCLEAR.value,\n                NedType.WASTEPOWER.value,\n                NedType.BIOMASSPOWER.value,\n                NedType.OTHERPOWER.value,\n                NedType.WKKTOTAL.value,\n                NedType.WINDOFFSHORE.value,\n            ],\n            \"granularity\": NedGranularity.FIFTEEN_MINUTES.value,\n            \"granularitytimezone\": NedGranularityTimezone.UTC.value,\n            \"classification\": NedClassification.FORECAST.value\n            if forecast\n            else NedClassification.MEASURED.value,\n            \"activity\": NedActivity.PRODUCTION.value,\n            \"validfrom[before]\": (\n                target_datetime + timedelta(days=2 if forecast else 1)\n            )\n            .date()\n            .isoformat(),\n            \"validfrom[after]\": (target_datetime - timedelta(days=0 if forecast else 1))\n            .date()\n            .isoformat(),\n        }\n\n        headers = {\"X-AUTH-TOKEN\": get_token(\"NED_TOKEN\"), \"accept\": \"application/json\"}\n        response = requests.get(URL, params=params, headers=headers)\n        if not response.ok:\n            raise ParserException(\n                parser=\"NED.py\",\n                message=f\"Failed to fetch NED data: {response.status_code}, err: {response.text}\",\n            )\n        results += response.json()\n        pageNum += 1\n\n        if response.json() == [] or pageNum > 30:\n            is_last_page = True\n\n    return results\n\n\ndef _get_entsoe_production_data(\n    zone_key: ZoneKey,\n    session: Session,\n    target_datetime: datetime,\n    logger: Logger,\n) -> ProductionBreakdownList:\n    # Add 2 days as ENTSOE fetches data from three days before target_datetime, where NED.nl fetches for target_datetime and day before\n    ENTSOE_raw_data = ENTSOE_query_production(\n        ENTSOE_DOMAIN_MAPPINGS[zone_key],\n        session,\n        target_datetime=(target_datetime + timedelta(days=2)),\n    )\n    if ENTSOE_raw_data is None:\n        raise ParserException(\n            parser=\"NED.py\",\n            message=\"Failed to fetch ENTSOE data\",\n            zone_key=zone_key,\n        )\n    ENTSOE_parsed_data = ENTSOE_parse_production(\n        ENTSOE_raw_data, zoneKey=zone_key, logger=logger\n    )\n\n    return ENTSOE_parsed_data\n\n\ndef format_data(\n    json: Any, logger: Logger, forecast: bool = False\n) -> ProductionBreakdownList:\n    df = pd.DataFrame(json)\n\n    # Capture and parse granularity before dropping it (format: \"/v1/granularities/4\")\n    if \"granularity\" in df.columns and not df.empty:\n        granularity_raw = df[\"granularity\"].iloc[0]\n        granularity = int(granularity_raw.split(\"/\")[-1])\n    else:\n        raise ParserException(\n            parser=\"NED.py\",\n            message=\"Granularity not found in API response\",\n        )\n\n    df.drop(\n        columns=[\n            \"id\",\n            \"point\",\n            \"classification\",\n            \"activity\",\n            \"granularity\",\n            \"granularitytimezone\",\n            \"emission\",\n            \"emissionfactor\",\n            \"capacity\",\n            \"validto\",\n            \"lastupdate\",\n        ],\n        inplace=True,\n    )\n\n    df = df.groupby(by=\"validfrom\")\n\n    formatted_production_data = ProductionBreakdownList(logger)\n    for _group_key, group_df in df:\n        # Add lag to avoid using data that is not yet complete and remove \"future\" data\n        if (\n            datetime.fromisoformat(group_df[\"validfrom\"].iloc[0])\n            > (datetime.now(timezone.utc) - timedelta(hours=0.5))\n            and not forecast\n        ):\n            continue\n        data_dict = group_df.to_dict(orient=\"records\")\n        mix = ProductionMix()\n        for data in data_dict:\n            clean_type = int(data[\"type\"].split(\"/\")[-1])\n            if clean_type in TYPE_MAPPING:\n                mix.add_value(\n                    TYPE_MAPPING[clean_type], _kwh_to_mw(data[\"volume\"], granularity)\n                )\n\n            else:\n                logger.warning(f\"Unknown type: {clean_type}\")\n\n        formatted_production_data.append(\n            zoneKey=ZoneKey(\"NL\"),\n            datetime=group_df[\"validfrom\"].iloc[0],\n            production=mix,\n            source=\"ned.nl\",\n            sourceType=EventSourceType.forecasted\n            if forecast\n            else EventSourceType.measured,\n        )\n\n    return formatted_production_data\n\n\n@refetch_frequency(timedelta(hours=24))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"NL\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n    target_datetime = target_datetime or datetime.now(timezone.utc)\n\n    json_data = call_api(target_datetime)\n    NED_data = format_data(json_data, logger)\n\n    all_dates = [item.get(\"datetime\") for item in NED_data.to_list()]\n\n    if all(\n        date >= datetime(2021, 1, 1, tzinfo=timezone.utc)\n        for date in all_dates\n        if date is not None\n    ):\n        return NED_data.to_list()\n\n    else:\n        ENTSOE_data = _get_entsoe_production_data(\n            zone_key, session, target_datetime, logger\n        )\n        combined_data = ProductionBreakdownList.update_production_breakdowns(\n            ENTSOE_data, NED_data, logger, matching_timestamps_only=True\n        )\n        return combined_data.to_list()\n\n\ndef fetch_production_forecast(\n    zone_key: ZoneKey = ZoneKey(\"NL\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n    target_datetime = target_datetime or datetime.now(timezone.utc)\n    json_data = call_api(target_datetime, forecast=True)\n    NED_data = format_data(json_data, logger, forecast=True)\n\n    return NED_data.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/NG.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Parser for the Nigerian electricity grid\"\"\"\n\nimport re\nimport urllib.parse\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport bs4\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib import config\nfrom electricitymap.contrib.types import ZoneKey\n\nAPI_URL = urllib.parse.urlparse(\"https://niggrid.org/GenerationProfile2\")\nAPI_URL_STRING = API_URL.geturl()\nNORMALISE = {\n    \"gas\": \"gas\",\n    \"gas/steam\": \"gas\",\n    \"hydro\": \"hydro\",\n    # Per the \"Electricity generation by source\" plot at\n    # https://www.iea.org/countries/nigeria, the majority of Nigeria's\n    # generation comes from natural gas, so \"steam\" most likely implies \"gas\";\n    # therefore, we do not map \"steam\" to \"unknown\" (coal/gas/oil). See issues\n    # #2570 and #3651 for more information.\n    \"steam\": \"gas\",\n}\nPATTERN = re.compile(r\"\\((.*)\\)\")\nTIMEZONE = ZoneInfo(\"Africa/Lagos\")\n\n\ndef get_data(session: Session, logger: Logger, timestamp: datetime):\n    # GET the landing page (HTML) and scrape some form data from it.\n    response = session.get(API_URL_STRING)\n    soup = bs4.BeautifulSoup(response.text, \"html.parser\")\n    data = {tag[\"name\"]: tag[\"value\"] for tag in soup.find_all(\"input\")}\n    data[\"ctl00$MainContent$txtReadingDate\"] = timestamp.strftime(\"%Y/%m/%d\")\n\n    # Send a POST request for the desired grid data using parameters from the\n    # landing page form. The grid data is presented as an HTML table; we ignore\n    # its header and footer rows.\n    response = session.post(API_URL_STRING, data=data)\n    rows = bs4.BeautifulSoup(response.text, \"html.parser\").find_all(\"tr\")[1:-1]\n\n    # Values from the future should not be returned\n    max_hour = min(\n        int(\n            (datetime.now(TIMEZONE) - timestamp.replace(hour=0)).total_seconds() / 3600\n        ),\n        24,\n    )\n\n    production_dict = {}\n    production_mix = ProductionMix()\n\n    for hour in range(0, max_hour):\n        production_dict[timestamp.replace(hour=hour)] = production_mix.copy()\n\n    for row in rows:\n        _, source, *power, _ = (tag.text for tag in row.find_all(\"td\"))\n        try:\n            technology = NORMALISE[PATTERN.search(source).group(1).casefold()]\n        except (AttributeError, KeyError):\n            logger.warning(f\"Unexpected source '{source.strip()}' encountered\")\n            continue\n        for hour in range(0, max_hour):\n            production_dict[timestamp.replace(hour=hour)].add_value(\n                technology,\n                float(power.pop(0)),\n            )\n    return production_dict\n\n\n@config.refetch_frequency(timedelta(hours=24))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"NG\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known production mix (in MW) of a given zone.\"\"\"\n\n    if target_datetime is None:\n        target_datetime = datetime.now(timezone.utc)\n    timestamp = target_datetime.replace(minute=0, second=0, microsecond=0).astimezone(\n        TIMEZONE\n    )\n\n    session = session or Session()\n    production_dict = get_data(session=session, logger=logger, timestamp=timestamp)\n\n    # Add data from previous day if few hours ago to update preliminary data\n    if len(production_dict) < 12:\n        production_dict = production_dict | get_data(\n            session=session, logger=logger, timestamp=timestamp - timedelta(days=1)\n        )\n\n    production_list = ProductionBreakdownList(logger=logger)\n    for ts in production_dict:\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=ts,\n            production=production_dict[ts],\n            source=API_URL.netloc,\n        )\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(fetch_production())\n    print(\n        fetch_production(target_datetime=datetime.fromisoformat(\"2022-03-09T15:00:00\"))\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/NI.py",
    "content": "from datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    PriceList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib import config\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nTIMEZONE = ZoneInfo(\"America/Managua\")\n\nPRICE_URL = (\n    \"http://www.cndc.org.ni/consultas/infoRelevanteSIN/consultaCostoMarginal.php\"\n)\n\n\nPRODUCTION_TYPE_TO_PRODUCTION_MODE = {\n    \"EOLICA\": \"wind\",\n    \"GEOTERMICA\": \"geothermal\",\n    \"BIOMASA\": \"biomass\",\n    \"HIDROELECTRICA\": \"hydro\",\n    \"SOLAR\": \"solar\",\n    \"TERMICA\": \"oil\",\n    # \"MER\" is imports and exports\n}\n\nZONE_KEYS_TO_INTERCONNECTION = {\n    \"CR->NI\": [\"amy\", \"lvg\"],\n    \"HN->NI\": [\"snd\", \"leon\"],\n}\n\n\ndef extract_text(full_text: str, start_text: str, end_text: str | None = None):\n    start = full_text.find(start_text)\n\n    if start == -1:\n        return full_text\n\n    start += len(start_text)\n\n    if not end_text:\n        return full_text[start:]\n\n    end = full_text.find(end_text, start)\n\n    if end == -1:\n        return full_text[start:]\n    else:\n        return full_text[start:end]\n\n\n@config.refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: str = \"NI\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of Nicaragua.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    url = \"https://www.cndc.org.ni/graficos/consultarGeneracionPorTipo\"\n\n    requests_obj = session or Session()\n    response = requests_obj.get(url)\n    if not response.ok:\n        raise ParserException(\n            f\"Exception when fetching production error code for {zone_key}: {response.status_code}: {response.text}\",\n        )\n\n    response_payload = response.json().get(\"GeneracionTipo\")\n    response_df = pd.DataFrame(response_payload).set_index(\"fecha_hora\")\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n\n    for idx in response_df.index.unique():\n        production_mix = ProductionMix()\n        time = datetime.strptime(idx, \"%Y-%m-%d %H:%M:%S\").replace(tzinfo=TIMEZONE)\n\n        for _, item in response_df.loc[idx].iterrows():\n            production_type = item.get(\"tipo\")\n            production_mode = PRODUCTION_TYPE_TO_PRODUCTION_MODE.get(production_type)\n\n            if production_mode is None:\n                continue\n\n            value = float(item.get(\"valor\"))\n            production_mix.add_value(production_mode, value)\n\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=time,\n            source=\"cndc.org.ni\",\n            production=production_mix,\n        )\n\n    return production_breakdown_list.to_list()\n\n\n@config.refetch_frequency(timedelta(minutes=45))\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known power exchange (in MW) between two regions.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n    sorted_zone_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    url = \"https://www.cndc.org.ni/Inicio/ConsultarTipoGeneracion\"\n\n    requests_obj = session or Session()\n    response = requests_obj.get(url)\n\n    if not response.ok:\n        raise ParserException(\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n        )\n\n    response_payload = response.json().get(\"interconexion\")[0]\n    time = datetime.strptime(\n        response.json().get(\"tipoGeneracion\")[0].get(\"fecha_hora\"), \"%Y-%m-%d %H:%M:%S\"\n    ).replace(tzinfo=TIMEZONE)\n\n    # Cross-comparing regional data on https://www.enteoperador.org/flujos-regionales-en-tiempo-real/\n    # and NI data (both fairly real-time), we can see that negative is import to NI, and positive is export from NI.\n\n    # Because in both possible sorted_zone_key values (HN->NI and CR->NI) NI is second,\n    # we expect netFlow to be positive when NI is importing, and negative when NI is exporting.\n    # So multiply value reported by the MAP_URL by -1.\n\n    if sorted_zone_keys in ZONE_KEYS_TO_INTERCONNECTION:\n        interchange_list = [\n            float(response_payload.get(con).replace(\",\", \".\"))\n            for con in ZONE_KEYS_TO_INTERCONNECTION.get(sorted_zone_keys)\n        ]\n\n        flow = -1 * sum(interchange_list)\n\n    else:\n        raise NotImplementedError(\"This exchange pair is not implemented\")\n\n    exchange_list = ExchangeList(logger)\n    exchange_list.append(\n        zoneKey=ZoneKey(sorted_zone_keys),\n        datetime=time,\n        netFlow=flow,\n        source=\"cndc.org.ni\",\n    )\n    return exchange_list.to_list()\n\n\n@config.refetch_frequency(timedelta(minutes=45))\ndef fetch_price(\n    zone_key: str = \"NI\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the most recent known power prices in Nicaragua grid.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    url = \"https://www.cndc.org.ni/Inicio/consultarInfoTecnicaRelevante\"\n    requests_obj = session or Session()\n    response = requests_obj.get(url)\n    if not response.ok:\n        raise ParserException(\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n        )\n\n    respose_payload = response.json()\n\n    date = respose_payload.get(\"fecha\")\n    hours = respose_payload.get(\"hora\")\n\n    price_date = datetime.strptime(f\"{date} {hours}\", \"%d/%m/%Y %H\").replace(\n        tzinfo=TIMEZONE\n    )\n    price = respose_payload.get(\"costoMarginal\")[0].get(\"valor\")\n\n    price_list = PriceList(logger)\n    price_list.append(\n        zoneKey=ZoneKey(zone_key),\n        datetime=price_date,\n        price=price,\n        currency=\"USD\",\n        source=\"cndc.org.ni\",\n    )\n    return price_list.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/NL.py",
    "content": "from copy import copy\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\n\nimport pandas as pd\nfrom requests import Session, get\n\nfrom electricitymap.contrib.config import ZONES_CONFIG\nfrom electricitymap.contrib.parsers import DK, ENTSOE\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.types import ZoneKey\n\nZONE_CONFIG = ZONES_CONFIG[\"NL\"]\nUTC = timezone.utc\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"NL\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    target_datetime = (\n        datetime.now(UTC)\n        if target_datetime is None\n        else target_datetime.astimezone(UTC)\n    )\n\n    r = session or Session()\n\n    consumptions = ENTSOE.fetch_consumption(\n        zone_key=zone_key, session=r, target_datetime=target_datetime, logger=logger\n    )\n    if not consumptions:\n        return\n    for c in consumptions:\n        del c[\"source\"]\n    df_consumptions = pd.DataFrame.from_dict(consumptions)\n    df_consumptions[\"datetime\"] = df_consumptions[\"datetime\"].apply(\n        lambda x: x.replace(tzinfo=UTC)\n    )\n\n    # NL has exchanges with BE, DE, NO, GB, DK-DK1\n    exchanges = []\n    for exchange_key in [\"BE\", \"DE\", \"GB\", \"NO-NO2\"]:\n        zone_1, zone_2 = sorted([exchange_key, zone_key])\n        exchange = ENTSOE.fetch_exchange(\n            zone_key1=zone_1,\n            zone_key2=zone_2,\n            session=r,\n            target_datetime=target_datetime,\n            logger=logger,\n        )\n        if not exchange:\n            return\n        exchanges.extend(exchange or [])\n\n    # add DK1 data (only for dates after operation)\n    if target_datetime > datetime(2019, 8, 24, tzinfo=UTC):\n        zone_1, zone_2 = sorted([\"DK-DK1\", zone_key])\n        df_dk = pd.DataFrame(\n            DK.fetch_exchange(\n                zone_key1=zone_1,\n                zone_key2=zone_2,\n                session=r,\n                target_datetime=target_datetime,\n                logger=logger,\n            )\n        )\n\n        # Because other exchanges and consumption data is only available per hour\n        # we floor the timpstamp to hour and group by hour with averaging of netFlow\n        df_dk[\"datetime\"] = df_dk[\"datetime\"].dt.floor(\"H\")\n        exchange_DK = (\n            df_dk.groupby([\"datetime\"])\n            .aggregate({\"netFlow\": \"mean\", \"sortedZoneKeys\": \"max\", \"source\": \"max\"})\n            .reset_index()\n        )\n\n        # because averaging with high precision numbers leads to rounding errors\n        exchange_DK = exchange_DK.round({\"netFlow\": 3})\n\n        exchanges.extend(exchange_DK.to_dict(orient=\"records\"))\n\n    # We want to know the net-imports into NL, so if NL is in zone_1 we need\n    # to flip the direction of the flow. E.g. 100MW for NL->DE means 100MW\n    # export to DE and needs to become -100MW for import to NL.\n    for e in exchanges:\n        if e[\"sortedZoneKeys\"].startswith(\"NL->\"):\n            e[\"NL_import\"] = -1 * e[\"netFlow\"]\n        else:\n            e[\"NL_import\"] = e[\"netFlow\"]\n        del e[\"source\"]\n        del e[\"netFlow\"]\n\n    df_exchanges = pd.DataFrame.from_dict(exchanges)\n    df_exchanges[\"datetime\"] = df_exchanges[\"datetime\"].apply(\n        lambda x: x.replace(tzinfo=UTC)\n    )\n    # Sum all exchanges to NL imports\n    df_exchanges = df_exchanges.groupby(\"datetime\").sum(\n        numeric_only=True,\n    )\n\n    # Fill missing values by propagating the value forward\n    df_consumptions_with_exchanges = df_consumptions.join(df_exchanges).fillna(\n        method=\"ffill\", limit=3\n    )  # Limit to 3 x 15min\n\n    # Load = Generation + netImports\n    # => Generation = Load - netImports\n    df_total_generations = (\n        df_consumptions_with_exchanges[\"consumption\"]\n        - df_consumptions_with_exchanges[\"NL_import\"]\n    )\n\n    # Fetch all production\n    productions = ENTSOE.fetch_production(\n        zone_key=zone_key, session=r, target_datetime=target_datetime, logger=logger\n    )\n    if not productions:\n        return\n\n    # Flatten production dictionaries (we ignore storage)\n    for p in productions:\n        # if for some reason theré's no unknown value\n        if \"unknown\" not in p[\"production\"] or p[\"production\"][\"unknown\"] is None:\n            p[\"production\"][\"unknown\"] = 0\n\n        Z = sum([x or 0 for x in p[\"production\"].values()])\n        # Only calculate the difference if the datetime exists\n        # If total ENTSOE reported production (Z) is less than total generation\n        # (calculated from consumption and imports), then there must be some\n        # unknown production missing, so we add the difference.\n        # The difference can actually be negative, because consumption is based\n        # on TSO network load, but locally generated electricity may never leave\n        # the DSO network and be substantial (e.g. Solar).\n        if (\n            p[\"datetime\"] in df_total_generations\n            and df_total_generations[p[\"datetime\"]] > Z\n        ):\n            p[\"production\"][\"unknown\"] = round(\n                (df_total_generations[p[\"datetime\"]] - Z + p[\"production\"][\"unknown\"]),\n                3,\n            )\n\n    # Add capacities\n    solar_capacity_df = get_solar_capacities()\n    wind_capacity_df = get_wind_capacities()\n    for p in productions:\n        p[\"capacity\"] = {\n            \"solar\": round(get_solar_capacity_at(p[\"datetime\"], solar_capacity_df), 3),\n            \"wind\": round(get_wind_capacity_at(p[\"datetime\"], wind_capacity_df), 3),\n        }\n\n    # Filter invalid\n    # We should probably add logging to this\n    return [p for p in productions if p[\"production\"][\"unknown\"] > 0]\n\n\ndef get_wind_capacities() -> pd.DataFrame:\n    url_wind_capacities = \"https://api.windstats.nl/stats\"\n\n    capacities_df = pd.DataFrame(columns=[\"datetime\", \"capacity (MW)\"])\n    try:\n        r = get(url_wind_capacities)\n        per_year_split_capacity = r.json()[\"combinedPowerPerYearSplitByLandAndSea\"]\n    except Exception as e:\n        Logger.error(f\"Error fetching wind capacities: {e}\")\n        return capacities_df\n\n    per_year_capacity = {\n        f\"{year}-01-01 00:00:00+00:00\": sum(split.values())\n        for (year, split) in per_year_split_capacity.items()\n    }\n\n    capacities_df[\"datetime\"] = pd.to_datetime(list(per_year_capacity.keys()))\n    capacities_df[\"capacity (MW)\"] = list(per_year_capacity.values())\n    capacities_df = capacities_df.set_index(\"datetime\")\n\n    return capacities_df\n\n\ndef get_solar_capacities() -> pd.DataFrame:\n    solar_capacity_base_url = \"https://opendata.cbs.nl/ODataApi/odata/82610ENG/UntypedDataSet?$filter=((EnergySourcesTechniques+eq+%27E006590+%27))+and+(\"\n\n    START_YEAR = 2010\n    end_year = datetime.now(UTC).year\n\n    years = list(range(START_YEAR, end_year + 1))\n    url_solar_capacity = copy(solar_capacity_base_url)\n\n    for i, year in enumerate(years):\n        if i == len(years) - 1:\n            url_solar_capacity += f\"(Periods+eq+%27{year}JJ00%27))\"\n        else:\n            url_solar_capacity += f\"(Periods+eq+%27{year}JJ00%27)+or+\"\n\n    solar_capacity_df = pd.DataFrame(columns=[\"datetime\", \"capacity (MW)\"])\n\n    try:\n        r = get(url_solar_capacity)\n        per_year_capacity = r.json()[\"value\"]\n    except Exception as e:\n        Logger.error(f\"Error fetching solar capacities: {e}\")\n        return solar_capacity_df\n\n    for yearly_row in per_year_capacity:\n        capacity = float(yearly_row[\"ElectricalCapacityEndOfYear_8\"])\n        year = yearly_row[\"Periods\"].split(\"JJ\")[0]\n        dt = datetime(int(year), 1, 1, tzinfo=UTC)\n        solar_capacity_df = solar_capacity_df.append(\n            {\"datetime\": dt, \"capacity (MW)\": capacity}, ignore_index=True\n        )\n    solar_capacity_df = solar_capacity_df.set_index(\"datetime\")\n\n    return solar_capacity_df\n\n\ndef _get_capacity_at(date: datetime, mode: str, capacity_df: pd.DataFrame) -> float:\n    assert mode in [\"solar\", \"wind\"]\n    default_capacity = ZONE_CONFIG[\"capacity\"][mode]\n    if capacity_df.empty:\n        return default_capacity\n    latest_year = date.year\n    while latest_year > 2015:\n        # Latest capacity for the year to date might not have been published yet, so revert back to latest known year\n        if capacity_df[capacity_df.index.year == latest_year][\"capacity (MW)\"].empty:\n            latest_year -= 1\n        else:\n            return float(\n                capacity_df[capacity_df.index.year == latest_year][\"capacity (MW)\"][0]\n            )\n    return default_capacity\n\n\ndef get_solar_capacity_at(date: datetime, solar_capacity_df: pd.DataFrame) -> float:\n    return _get_capacity_at(date, \"solar\", solar_capacity_df)\n\n\ndef get_wind_capacity_at(date: datetime, wind_capacity_df: pd.DataFrame) -> float:\n    return _get_capacity_at(date, \"wind\", wind_capacity_df)\n\n\nif __name__ == \"__main__\":\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/NO-NO4_SE.py",
    "content": "from collections.abc import Callable\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom typing import Literal\n\nfrom requests import Session\n\nfrom .ENTSOE import fetch_exchange as fetch_ENTSOE_exchange\nfrom .ENTSOE import fetch_exchange_forecast as fetch_ENTSOE_exchange_forecast\nfrom .lib.config import refetch_frequency\nfrom .lib.exceptions import ParserException\n\n\"\"\"\nFetches data for the NO-NO4->SE-SE1 and NO-NO4->SE-SE2 exchanges\nby wrapping the ENTSOE.py parser and combining the data from the two\nto produce a single data list for the NO-NO4->SE exchange.\n\"\"\"\n\nEXCHANGE_FUNCTION_MAP: dict[str, Callable] = {\n    \"exchange\": fetch_ENTSOE_exchange,\n    \"exchange_forecast\": fetch_ENTSOE_exchange_forecast,\n}\n\n\ndef fetch_data(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None,\n    target_datetime: datetime | None,\n    logger: Logger,\n    exchange_type: Literal[\"exchange\", \"exchange_forecast\"],\n) -> list[dict]:\n    if target_datetime is None:\n        target_datetime = datetime.now(timezone.utc)\n\n    # NO-NO4 to SE-SE1\n    SE1_dataList = EXCHANGE_FUNCTION_MAP[exchange_type](\n        zone_key1=\"NO-NO4\",\n        zone_key2=\"SE-SE1\",\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n    )\n    # NO-NO4 to SE-SE2\n    SE2_dataList = EXCHANGE_FUNCTION_MAP[exchange_type](\n        zone_key1=\"NO-NO4\",\n        zone_key2=\"SE-SE2\",\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n    )\n    returnList: list[dict] = []\n\n    # Compare the length and datetimes of the two data lists and\n    # if they are the same combine the data from the two lists.\n    if (\n        len(SE1_dataList) == len(SE2_dataList)\n        and SE1_dataList[0][\"datetime\"] == SE2_dataList[0][\"datetime\"]\n        and SE1_dataList[-1][\"datetime\"] == SE2_dataList[-1][\"datetime\"]\n    ):\n        logger.info(\"Clean match! Merging data with zip\")\n        for SE1, SE2 in zip(SE1_dataList, SE2_dataList, strict=True):\n            returnList.append(\n                {\n                    \"datetime\": SE1[\"datetime\"],\n                    \"netFlow\": SE1[\"netFlow\"] + SE2[\"netFlow\"],\n                    \"sortedZoneKeys\": \"NO-NO4->SE\",\n                    \"source\": SE1[\"source\"],\n                }\n            )\n\n    # Parse values from the two lists and loop over them to find missing datetimes\n    # if the two lists are not of equal length and do not have the same datetimes.\n    else:\n        logger.info(\"Data mismatch! Recursively looping over lists to match data\")\n        for SE1_data in SE1_dataList:\n            for SE2_data in SE2_dataList:\n                if SE1_data[\"datetime\"] == SE2_data[\"datetime\"]:\n                    returnList.append(\n                        {\n                            \"datetime\": SE1_data[\"datetime\"],\n                            \"netFlow\": SE1_data[\"netFlow\"] + SE2_data[\"netFlow\"],\n                            \"sortedZoneKeys\": \"NO-NO4->SE\",\n                            \"source\": SE1_data[\"source\"],\n                        }\n                    )\n    if returnList != []:\n        return returnList\n    else:\n        raise ParserException(\n            parser=\"NO-NO4_SE.py\",\n            message=f\"No matching exchange data found between {zone_key1} and {zone_key2} at {target_datetime}.\",\n        )\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_exchange(\n    zone_key1: str = \"NO-NO4\",\n    zone_key2: str = \"SE\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    return fetch_data(\n        zone_key1=zone_key1,\n        zone_key2=zone_key2,\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n        exchange_type=\"exchange\",\n    )\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_exchange_forecast(\n    zone_key1: str = \"NO-NO4\",\n    zone_key2: str = \"SE\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    return fetch_data(\n        zone_key1=zone_key1,\n        zone_key2=zone_key2,\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n        exchange_type=\"exchange_forecast\",\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/NORDPOOL.py",
    "content": "from dataclasses import dataclass\nfrom datetime import datetime, timedelta, timezone\nfrom enum import Enum\nfrom logging import Logger, getLogger\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ExchangeList, PriceList\nfrom electricitymap.contrib.types import ZoneKey\n\nfrom .lib.config import refetch_frequency\nfrom .lib.utils import get_token\n\n\"\"\"\nParser for the Nordpool API.\nAPI documentation: https://data-api.nordpoolgroup.com/index.html\n\"\"\"\n\nNORDPOOL_BASE_URL = \"https://data-api.nordpoolgroup.com/api/v2/\"\n\n\n@dataclass\nclass NordpoolToken:\n    token: str\n    expiration: datetime\n\n    @property\n    def is_expired(self) -> bool:\n        return datetime.now(tz=timezone.utc) > self.expiration + timedelta(minutes=5)\n\n\nCURRENT_TOKEN: NordpoolToken | None = None\n\nSOURCE = \"nordpool.com\"\n\n\nclass NORDPOOL_API_ENDPOINT(Enum):\n    PRICE = \"Auction/Prices/ByAreas\"\n    EXCHANGE = \"PowerSystem/Exchanges/ByAreas\"\n\n\nclass MARKET_TYPE(Enum):\n    DAY_AHEAD = \"DayAhead\"\n    GB_DAY_AHEAD = \"GbHalfHour_DayAhead\"\n\n\nclass CURRENCY(Enum):\n    EUR = \"EUR\"\n    DKK = \"DKK\"\n    SEK = \"SEK\"\n    NOK = \"NOK\"\n    GBP = \"GBP\"\n    PLN = \"PLN\"\n    RON = \"RON\"\n\n\nZONE_MAPPING = {\n    \"AT\": \"AT\",\n    \"BE\": \"BE\",\n    \"DK-DK1\": \"DK1\",\n    \"DK-DK2\": \"DK2\",\n    \"DE\": \"GER\",\n    \"EE\": \"EE\",\n    \"FI\": \"FI\",\n    \"FR\": \"FR\",\n    \"GB\": \"UK\",\n    \"LT\": \"LT\",\n    \"LV\": \"LV\",\n    \"NL\": \"NL\",\n    \"NO-NO1\": \"NO1\",\n    \"NO-NO2\": \"NO2\",\n    \"NO-NO3\": \"NO3\",\n    \"NO-NO4\": \"NO4\",\n    \"NO-NO5\": \"NO5\",\n    \"PL\": \"PL\",\n    \"SE-SE1\": \"SE1\",\n    \"SE-SE2\": \"SE2\",\n    \"SE-SE3\": \"SE3\",\n    \"SE-SE4\": \"SE4\",\n    \"RU-1\": \"RU\",\n    \"RU-KGD\": \"LKAL\",\n}\n\nINVERTED_ZONE_MAPPING = {value: key for key, value in ZONE_MAPPING.items()}\n\n\ndef _generate_new_nordpool_token(session: Session) -> NordpoolToken:\n    URL = \"https://sts.nordpoolgroup.com/connect/token\"\n    username = get_token(\"EMAPS_NORDPOOL_USERNAME\")\n    password = get_token(\"EMAPS_NORDPOOL_PASSWORD\")\n    headers = {\n        \"accept\": \"application/json\",\n        \"Authorization\": \"Basic Y2xpZW50X21hcmtldGRhdGFfYXBpOmNsaWVudF9tYXJrZXRkYXRhX2FwaQ==\",  # This is a public key listed in the Nordpool API documentation\n        \"Content-Type\": \"application/x-www-form-urlencoded\",\n    }\n    data = {\n        \"grant_type\": \"password\",\n        \"scope\": \"marketdata_api\",\n        \"username\": username,\n        \"password\": password,\n    }\n    response = session.post(URL, headers=headers, data=data)\n    response = _handle_status_code(response, getLogger(__name__))\n    token_data = response.json()\n    token = NordpoolToken(\n        token=token_data[\"access_token\"],\n        expiration=datetime.now(tz=timezone.utc)\n        + timedelta(seconds=token_data[\"expires_in\"]),\n    )\n\n    return token\n\n\ndef _handle_status_code(response: Response, logger: Logger) -> Response:\n    match response.status_code:\n        case 200:\n            return response\n        case 400:\n            # Bad request\n            raise ValueError(f\"Bad request: {response.text}\")\n        case 401:\n            # Unauthorized\n            raise PermissionError(f\"Unauthorized access: {response.text}\")\n        case 403:\n            # Forbidden\n            raise PermissionError(f\"Forbidden access: {response.text}\")\n        case _:\n            # Other errors\n            raise Exception(\n                f\"Unexpected error: Code: {response.status_code}, Text: {response.text}\"\n            )\n\n\n# TODO: Remove this when we run on Python 3.11 or above\ndef zulu_to_utc(datetime_string: str) -> str:\n    \"\"\"Converts a zulu time string to a UTC time string.\"\"\"\n    return datetime_string.replace(\"Z\", \"+00:00\")\n\n\ndef _query_nordpool(\n    endpoint: NORDPOOL_API_ENDPOINT,\n    params: dict[str, str],\n    logger: Logger,\n    session: Session,\n):\n    global CURRENT_TOKEN\n    if CURRENT_TOKEN is None or CURRENT_TOKEN.is_expired:\n        CURRENT_TOKEN = _generate_new_nordpool_token(session)\n    headers = {\n        \"Authorization\": f\"Bearer {CURRENT_TOKEN.token}\",\n    }\n\n    response = session.get(\n        f\"{NORDPOOL_BASE_URL}{endpoint.value}\", params=params, headers=headers\n    )\n\n    response = _handle_status_code(response, logger)\n    return response\n\n\ndef _parse_price(response: Response, logger: Logger) -> PriceList:\n    price_list = PriceList(logger)\n    json = response.json()[0]\n    prices = json[\"prices\"]\n    for price in prices:\n        price_list.append(\n            zoneKey=ZoneKey(INVERTED_ZONE_MAPPING[json[\"deliveryArea\"]]),\n            price=price[\"price\"],\n            datetime=datetime.fromisoformat(zulu_to_utc(price[\"deliveryStart\"])),\n            currency=json[\"currency\"],\n            source=SOURCE,\n        )\n    return price_list\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_price(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n    target_datetime = target_datetime or datetime.now()\n    params = {\n        \"areas\": f\"{ZONE_MAPPING[zone_key]}\",\n        \"currency\": CURRENCY.EUR.value\n        if zone_key != ZoneKey(\"GB\")  # GB uses GBP not EUR\n        else CURRENCY.GBP.value,\n        \"market\": MARKET_TYPE.DAY_AHEAD.value\n        if zone_key != ZoneKey(\"GB\")  # GB uses it's own 30 minute TMU day ahead market\n        else MARKET_TYPE.GB_DAY_AHEAD.value,\n        \"date\": target_datetime.date().isoformat(),\n    }\n    response_target = _query_nordpool(\n        NORDPOOL_API_ENDPOINT.PRICE, params, logger, session\n    )\n    params[\"date\"] = (target_datetime + timedelta(days=1)).date().isoformat()\n    response_target_day_ahead = _query_nordpool(\n        NORDPOOL_API_ENDPOINT.PRICE, params, logger, session\n    )\n    price_data_target: PriceList = _parse_price(response_target, logger)\n    price_data_target_day_ahead: PriceList = _parse_price(\n        response_target_day_ahead, logger\n    )\n\n    return (price_data_target + price_data_target_day_ahead).to_list()\n\n\ndef _parse_exchange(response: Response, logger: Logger, target_zone) -> ExchangeList:\n    exchange_list = ExchangeList(logger)\n    json = response.json()[0]\n    exchanges = json[\"exchanges\"]\n    for exchange in exchanges:\n        for connection in exchange[\"byConnections\"]:\n            if connection[\"area\"] == ZONE_MAPPING[target_zone]:\n                exchange_list.append(\n                    zoneKey=ZoneKey(\n                        f\"{INVERTED_ZONE_MAPPING[json['deliveryArea']]}->{INVERTED_ZONE_MAPPING[connection['area']]}\"\n                    ),\n                    netFlow=-connection[\n                        \"netPosition\"\n                    ],  # Import is positive, export is negative\n                    datetime=datetime.fromisoformat(\n                        zulu_to_utc(exchange[\"deliveryStart\"])\n                    ),\n                    source=SOURCE,\n                )\n    return exchange_list\n\n\n@refetch_frequency(timedelta(days=2))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Gets exchange status between two specified zones.\n    Only supports Nordpool zones.\n    \"\"\"\n    session = session or Session()\n    target_datetime = target_datetime or datetime.now()\n    params = {\n        \"areas\": f\"{ZONE_MAPPING[zone_key1]}\",\n        \"date\": target_datetime.date().isoformat(),\n    }\n    response_target = _query_nordpool(\n        NORDPOOL_API_ENDPOINT.EXCHANGE, params, logger, session\n    )\n    exchange_data = _parse_exchange(\n        response=response_target,\n        logger=logger,\n        target_zone=zone_key2,\n    )\n    # Request the day before as well so we get overlapping data\n    params[\"date\"] = (target_datetime - timedelta(days=1)).date().isoformat()\n    response_target_day_before = _query_nordpool(\n        NORDPOOL_API_ENDPOINT.EXCHANGE, params, logger, session\n    )\n    exchange_data_day_before = _parse_exchange(\n        response=response_target_day_before,\n        logger=logger,\n        target_zone=zone_key2,\n    )\n    # Combines both ExchangeLists and return them as a native list.\n    return (exchange_data + exchange_data_day_before).to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/NTESMO.py",
    "content": "\"\"\"Parser for AU-NT using https://ntesmo.com.au data, the electricity market operator for the Northen Territories.\nUses some webscrapping as no API seems to be available. Data is available in the form of daily xslx files.\nMapping is done using EDL's website and Territory Generation.\nhttps://edlenergy.com/project/pine-creek/\nhttps://territorygeneration.com.au/about-us/our-power-stations/\n\"\"\"\n\nimport collections\nimport logging\nimport math\nimport re\nfrom collections.abc import Iterable, Iterator\nfrom datetime import date, datetime, time, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any, TypedDict\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\nfrom requests import Session\nfrom requests.adapters import Retry\n\nfrom electricitymap.contrib.lib.models.event_lists import TotalConsumptionList\nfrom electricitymap.contrib.lib.models.events import EventSourceType\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency, retry_policy\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"NTESMO.py\"\nAUSTRALIA_TZ = ZoneInfo(\"Australia/Darwin\")\nZONE_KEY = ZoneKey(\"AU-NT\")\n\nAPI_URL = \"https://ntesmo.com.au/data/daily-trading\"\n\n\nclass Generator(TypedDict):\n    power_plant: str\n    fuel_type: str\n\n\nPLANT_MAPPING = {\n    \"C1\": Generator(power_plant=\"Channel Island Power Station\", fuel_type=\"gas\"),\n    \"C2\": Generator(power_plant=\"Channel Island Power Station\", fuel_type=\"gas\"),\n    \"C3\": Generator(power_plant=\"Channel Island Power Station\", fuel_type=\"gas\"),\n    \"C4\": Generator(power_plant=\"Channel Island Power Station\", fuel_type=\"gas\"),\n    \"C5\": Generator(power_plant=\"Channel Island Power Station\", fuel_type=\"gas\"),\n    \"C6\": Generator(power_plant=\"Channel Island Power Station\", fuel_type=\"gas\"),\n    \"C7\": Generator(power_plant=\"Channel Island Power Station\", fuel_type=\"gas\"),\n    \"C8\": Generator(power_plant=\"Channel Island Power Station\", fuel_type=\"gas\"),\n    \"C9\": Generator(power_plant=\"Channel Island Power Station\", fuel_type=\"gas\"),\n    \"W1\": Generator(power_plant=\"Weddell Power Station\", fuel_type=\"gas\"),\n    \"W2\": Generator(power_plant=\"Weddell Power Station\", fuel_type=\"gas\"),\n    \"W3\": Generator(power_plant=\"Weddell Power Station\", fuel_type=\"gas\"),\n    \"LMS\": Generator(\n        power_plant=\"LMS Energy from the Shoal Bay landfill\", fuel_type=\"biomass\"\n    ),\n    \"K1\": Generator(power_plant=\"Katherine Power Station\", fuel_type=\"gas\"),\n    \"K2\": Generator(power_plant=\"Katherine Power Station\", fuel_type=\"gas\"),\n    \"K3\": Generator(power_plant=\"Katherine Power Station\", fuel_type=\"gas\"),\n    \"K4\": Generator(power_plant=\"Katherine Power Station\", fuel_type=\"gas\"),\n    \"P1\": Generator(power_plant=\"Pine Creek Power Station\", fuel_type=\"gas\"),\n    \"P2\": Generator(power_plant=\"Pine Creek Power Station\", fuel_type=\"gas\"),\n    \"P3\": Generator(power_plant=\"Pine Creek Power Station\", fuel_type=\"gas\"),\n    \"KS01\": Generator(power_plant=\"\", fuel_type=\"unknown\"),\n    \"MY01\": Generator(power_plant=\"\", fuel_type=\"unknown\"),\n    \"BJ01\": Generator(power_plant=\"\", fuel_type=\"unknown\"),\n    \"BP01\": Generator(power_plant=\"\", fuel_type=\"unknown\"),\n    \"HP01\": Generator(power_plant=\"\", fuel_type=\"unknown\"),\n    \"RD01\": Generator(power_plant=\"\", fuel_type=\"unknown\"),\n    \"RB01\": Generator(power_plant=\"\", fuel_type=\"unknown\"),\n    \"RB02\": Generator(power_plant=\"\", fuel_type=\"unknown\"),\n    \"RB03\": Generator(power_plant=\"\", fuel_type=\"unknown\"),\n}\n\n# For some reason the page doesn't always load on first attempt.\n# Therefore we retry a few times.\nretry_strategy = Retry(\n    total=3,\n    status_forcelist=[500, 502, 503, 504],\n)\n\n\ndef _scan_daily_report_urls(\n    urls: Iterable[str], session: Session\n) -> Iterator[tuple[date, str]]:\n    \"\"\"Scans pages of daily report cards yielding links to the excel data files for each day.\"\"\"\n\n    for url in urls:\n        response = session.get(url)\n        if not response.ok:\n            raise ParserException(\n                PARSER,\n                f\"Exception when fetching daily trading data error code: {response.status_code}: {response.text}\",\n            )\n\n        page = response.text\n        soup = BeautifulSoup(page, \"html.parser\")\n        for a in soup.find_all(\"a\", href=True):\n            if a[\"href\"].startswith(\"https://ntesmo.com.au/__data/assets/excel_doc/\"):\n                timestamp = a.find(\"div\", {\"class\": \"smp-tiles-article__title\"}).text\n\n                try:\n                    date_time = datetime.strptime(timestamp, \"%d %B %Y\")\n                except ValueError:\n                    # some dates are not formatted properly or will contain extra information\n                    # e.g. \"05 April 2018 - Publishing Recommencement\", \"05 January 2018 - System Notice\", \"18 June2018\"\n                    # so extract individual %d %B %Y groups, potentially separated by 0 or more spaces\n                    match = re.search(r\"(\\d{2})\\s*([a-zA-Z]+)\\s*(\\d{4})\", timestamp)\n                    if not match:\n                        raise\n                    cleaned_timestamp = \" \".join(match.groups())\n\n                    # some timestamps have typos e.g.  \"02 Januray 2019\"\n                    cleaned_timestamp = cleaned_timestamp.replace(\"Januray\", \"January\")\n\n                    date_time = datetime.strptime(cleaned_timestamp, \"%d %B %Y\")\n\n                dt = date_time.replace(tzinfo=AUSTRALIA_TZ).date()\n                yield dt, a[\"href\"]\n\n\ndef _find_link_to_daily_report(target_datetime: datetime, session: Session) -> str:\n    \"\"\"Scrapes daily report cards to find the link to the data for the target date.\"\"\"\n\n    today_datetime = datetime.now(AUSTRALIA_TZ)\n    today_date = today_datetime.date()\n    target_datetime = target_datetime.astimezone(AUSTRALIA_TZ)\n    target_date = target_datetime.date()\n\n    is_this_year = target_date.year == today_date.year\n    if is_this_year:\n        # current year's report cards are paginated (9 per page) [and in reverse chronological order, latest data first]\n        maximum_possible_num_pages = int(math.ceil(365 / 9))\n        urls = (\n            f\"{API_URL}?result_70160_result_page={page_number}\"\n            # page 0 is a hidden page. Usually it's just a duplicate of page=1, but it seems like sometimes it's\n            # updated with new daily data before page 1 is.\n            for page_number in range(0, maximum_possible_num_pages + 1)\n        )\n    else:\n        # historical report cards are all on the same page\n        urls = [\n            f\"{API_URL}/historical-daily-trading-data/{target_date.year}-daily-trading-data\"\n        ]\n\n    index = _scan_daily_report_urls(urls, session=session)\n\n    # cap target date if more recent than what the API makes available:\n    # data for a given day is published with a variable delay (+1-4 days)\n    if is_this_year:\n        date_of_latest_available_data, link = next(index)\n        if target_date >= date_of_latest_available_data:\n            return link\n\n    for dt, link in index:\n        if dt == target_date:\n            return link\n\n    raise ParserException(\n        PARSER,\n        f\"Cannot find link to daily report for date {target_date.strftime('%Y-%m-%d %Z')}\",\n    )\n\n\ndef get_daily_report_data(\n    zone_key: ZoneKey,\n    session: Session | None,\n    target_datetime: datetime,\n) -> bytes:\n    session = session or Session()\n\n    link_to_daily_report = _find_link_to_daily_report(\n        target_datetime=target_datetime, session=session\n    )\n\n    response = session.get(link_to_daily_report)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching daily report data error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    return response.content\n\n\ndef extract_consumption_and_price_data(file: bytes) -> pd.DataFrame:\n    return pd.read_excel(\n        file, \"System Demand and Market Price\", skiprows=4, header=0, usecols=\"A:C\"\n    )\n\n\ndef parse_consumption_and_price(\n    raw_consumption: pd.DataFrame,\n    target_datetime: datetime,\n    price: bool,\n) -> list[dict]:\n    target_datetime = target_datetime.astimezone(AUSTRALIA_TZ)\n\n    data_points = []\n    for _, consumption in raw_consumption.iterrows():\n        # Market day starts at 4:30 and reports up until 4:00 the next day.\n        # Therefore timestamps between 0:00 and 4:30 excluded need to have an extra day.\n        raw_timestamp = consumption[0]\n        timestamp = datetime.combine(date=target_datetime.date(), time=raw_timestamp)\n        if raw_timestamp < time(hour=4, minute=30):\n            timestamp = timestamp + timedelta(days=1)\n        data_point = {\n            \"zoneKey\": \"AU-NT\",\n            \"datetime\": timestamp.replace(tzinfo=AUSTRALIA_TZ),\n            \"source\": \"ntesmo.com.au\",\n        }\n        if price:\n            data_point[\"price\"] = consumption[\"Market Price\"]\n            data_point[\"currency\"] = \"AUD\"\n        else:\n            data_point[\"consumption\"] = consumption[\"Demand\"]\n        data_points.append(data_point)\n    return data_points\n\n\ndef parse_production_mix(\n    raw_production_mix_df: pd.DataFrame, logger: logging.Logger\n) -> list[dict]:\n    raw_production_mix_df[\"Period Start\"] = raw_production_mix_df[\n        \"Period Start\"\n    ].dt.tz_localize(\"Australia/Darwin\")\n\n    # some older data may miss columns for newer plants\n    raw_production_mix_df = raw_production_mix_df.dropna(axis=1, how=\"all\")\n\n    generation_units = set(raw_production_mix_df.columns)\n    generation_units.remove(\"Period Start\")\n    generation_units.remove(\"Period End\")\n    unknown_units = generation_units.difference(PLANT_MAPPING.keys())\n    if unknown_units:\n        logger.warning(\n            f\"New generator(s) {unknown_units} detected in {ZONE_KEY}, please update the mapping of generators.\"\n        )\n\n    production_breakdown_list = []\n    for row in raw_production_mix_df.itertuples():\n        production_mix = collections.defaultdict(float)\n        for generator_key in generation_units:\n            generator_production = getattr(row, generator_key)\n\n            # Some decommissioned plants have negative production values.\n            if generator_production < 0:\n                continue\n\n            fuel_type = (\n                \"unknown\"\n                if generator_key in unknown_units\n                else PLANT_MAPPING[generator_key][\"fuel_type\"]\n            )\n            production_mix[fuel_type] += generator_production\n\n        production_breakdown = {\n            \"zoneKey\": ZONE_KEY,\n            \"datetime\": row[1].to_pydatetime(),\n            \"source\": \"ntesmo.com.au\",\n            \"production\": dict(production_mix),\n            \"storage\": {},\n        }\n        production_breakdown_list.append(production_breakdown)\n\n    return production_breakdown_list\n\n\n@refetch_frequency(timedelta(days=1))\n@retry_policy(retry_policy=retry_strategy)\ndef fetch_consumption(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n    daily_report_data = get_daily_report_data(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n    consumption_and_price_data = extract_consumption_and_price_data(daily_report_data)\n    return parse_consumption_and_price(\n        raw_consumption=consumption_and_price_data,\n        target_datetime=target_datetime,\n        price=False,\n    )\n\n\n@refetch_frequency(timedelta(days=1))\n@retry_policy(retry_policy=retry_strategy)\ndef fetch_price(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n    daily_report_data = get_daily_report_data(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n    consumption_and_price_data = extract_consumption_and_price_data(daily_report_data)\n    return parse_consumption_and_price(\n        raw_consumption=consumption_and_price_data,\n        target_datetime=target_datetime,\n        price=True,\n    )\n\n\n@refetch_frequency(timedelta(days=1))\n@retry_policy(retry_policy=retry_strategy)\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n    daily_report_data = get_daily_report_data(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n    production_mix = pd.read_excel(\n        daily_report_data,\n        sheet_name=\"Generating Unit Output\",\n        header=0,\n        usecols=\"A:AE\",\n        skiprows=4,\n        # avoid loading potential extra non-numerical lines at the bottom of the sheet\n        # e.g. sometimes there might be a disclaimer\n        nrows=48,\n    )\n\n    return parse_production_mix(production_mix, logger=logger)\n\n\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the latest demand forecast for every half an hour until 7 days ahead in MW.\"\"\"\n    session = session or Session()\n\n    url_dk = \"https://ntesmo.com.au/data/data-dashboard/2024-enhancements/demand-forecast/darwin-katherine/dk-7-days-forecast\"\n    url_as = \"https://ntesmo.com.au/data/data-dashboard/2024-enhancements/demand-forecast/alice-springs/as-7-days-forecast\"\n    url_tc = \"https://ntesmo.com.au/data/data-dashboard/2024-enhancements/demand-forecast/tennant-creek/tc-7-days-forecast\"\n\n    # Collect all values into a dict by timestamp\n    combined = collections.defaultdict(float)\n\n    for url in [url_dk, url_as, url_tc]:\n        data = session.get(url).json()  # Expecting list of [timestamp, value]\n        for timestamp, value in data[\"forecastedDemand\"]:\n            combined[timestamp] += value  # Add value for each matching timestamp\n\n    # Optionally: convert to sorted list\n    all_consumption_events = sorted(combined.items())\n\n    consumption_list = TotalConsumptionList(logger)\n    for event in all_consumption_events:\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.strptime(event[0], \"%Y-%m-%dT%H:%M+09:30\").replace(\n                tzinfo=AUSTRALIA_TZ\n            ),\n            consumption=event[1],\n            source=\"ntesmo.com.au\",\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumption_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"\n    for dt in [\n        # now\n        None,\n        # this year, but old enough that the api data is not in the first page of results\n        datetime(2024, 4, 2, tzinfo=timezone.utc),\n        # historical data (previous years)\n        datetime(2023, 2, 15, tzinfo=timezone.utc),\n        datetime(2022, 3, 11, tzinfo=timezone.utc),\n    ]:\n        print(f\"fetch_consumption(target_datetime={dt}) ->\")\n        print(fetch_consumption(target_datetime=dt))\n\n        print(f\"fetch_price(target_datetime={dt}) ->\")\n        print(fetch_price(target_datetime=dt))\n\n        print(f\"fetch_production(target_datetime={dt}) ->\")\n        print(fetch_production(target_datetime=dt))\n    \"\"\"\n\n    print(fetch_consumption_forecast())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/NZ.py",
    "content": "#!/usr/bin/env python3\n\n# The datetime library is used to handle datetimes\nimport json\nfrom datetime import datetime, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any\n\nfrom bs4 import BeautifulSoup\n\n# The request library is used to fetch content through HTTP\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    PriceList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\n\ntime_zone = \"Pacific/Auckland\"\n\nNZ_PRICE_REGIONS = set(range(1, 14))\nPRODUCTION_URL = \"https://www.transpower.co.nz/system-operator/live-system-and-market-data/consolidated-live-data\"\nPRICE_URL = \"https://api.em6.co.nz/ords/em6/data_api/region/price/\"\n\n\ndef fetch(session: Session | None = None):\n    r = session or Session()\n    url = PRODUCTION_URL\n    response = r.get(url)\n    soup = BeautifulSoup(response.text, \"html.parser\")\n    for item in soup.find_all(\"script\"):\n        if item.attrs.get(\"data-drupal-selector\"):\n            body = item.contents[0]\n            obj = json.loads(body)\n    return obj\n\n\ndef fetch_price(\n    zone_key: ZoneKey = ZoneKey(\"NZ\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Requests the current price of electricity based on the zone key.\n\n    Note that since EM6 breaks the electricity price down into regions,\n    the regions are averaged out for each island.\n    \"\"\"\n    if target_datetime:\n        raise NotImplementedError(\n            \"This parser is not able to retrieve data for past dates\"\n        )\n\n    r = session or Session()\n    url = PRICE_URL\n    response = r.get(url, verify=False)\n    obj = response.json()\n    region_prices = []\n\n    regions = NZ_PRICE_REGIONS\n    for item in obj.get(\"items\"):\n        region = item.get(\"grid_zone_id\")\n        if region in regions:\n            time = item.get(\"timestamp\")\n            price = float(item.get(\"price\"))\n            region_prices.append(price)\n\n    avg_price = sum(region_prices) / len(region_prices)\n    date_time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%SZ\").replace(\n        tzinfo=timezone.utc\n    )\n    price_list = PriceList(logger)\n    price_list.append(\n        zoneKey=zone_key,\n        price=avg_price,\n        currency=\"NZD\",\n        datetime=date_time,\n        source=\"api.em6.co.nz\",\n    )\n    return price_list.to_list()\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"NZ\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given zone.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\n            \"This parser is not able to retrieve data for past dates\"\n        )\n\n    obj = fetch(session)\n\n    date_time = datetime.fromtimestamp(obj[\"soPgenGraph\"][\"timestamp\"], tz=timezone.utc)\n\n    region_key = \"New Zealand\"\n    productions = obj[\"soPgenGraph\"][\"data\"][region_key]\n    production_breakdowns = ProductionBreakdownList(logger)\n    production_mix = ProductionMix()\n    mix_mapping = {\n        \"coal\": \"Coal\",\n        \"oil\": \"Diesel/Oil\",\n        \"gas\": \"Gas\",\n        \"geothermal\": \"Geothermal\",\n        \"wind\": \"Wind\",\n        \"hydro\": \"Hydro\",\n        \"solar\": \"Solar\",\n        \"unknown\": \"Co-Gen\",\n    }\n    for mix_key, prod_key in mix_mapping.items():\n        production_mix.add_value(\n            mix_key, productions.get(prod_key, {\"generation\": None})[\"generation\"]\n        )\n    production_mix.add_value(\"nuclear\", 0)  # famous issue in NZ politics\n    storage_mix = StorageMix()\n    storage_mix.add_value(\n        \"battery\", productions.get(\"Battery\", {\"generation\": None})[\"generation\"]\n    )\n    production_breakdowns.append(\n        zoneKey=zone_key,\n        datetime=date_time,\n        production=production_mix,\n        storage=storage_mix,\n        source=\"transpower.co.nz\",\n    )\n    capacity = {\n        mix_key: productions.get(prod_key, {\"capacity\": None})[\"capacity\"]\n        for mix_key, prod_key in mix_mapping.items()\n    }\n    capacity[\"battery storage\"] = productions.get(\"Battery\", {\"capacity\": None})[\n        \"capacity\"\n    ]\n    capacity[\"nuclear\"] = 0  # famous issue in NZ politics\n    return [{**e, **{\"capacity\": capacity}} for e in production_breakdowns.to_list()]\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(\"fetch_price(NZ) ->\")\n    print(fetch_price(\"NZ\"))\n    print(\"fetch_production(NZ) ->\")\n    print(fetch_production(\"NZ\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/ONS.py",
    "content": "from datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.types import ZoneKey\n\nURL = \"http://tr.ons.org.br/Content/GetBalancoEnergetico/null\"\nSOURCE = \"ons.org.br\"\n\nGENERATION_MAPPING = {\n    \"nuclear\": \"nuclear\",\n    \"eolica\": \"wind\",\n    \"termica\": \"unknown\",\n    \"solar\": \"solar\",\n    \"hidraulica\": \"hydro\",\n    \"itaipu50HzBrasil\": \"hydro\",  # BR_CS contains the Itaipu Dam.\n    # We merge the hydro keys into one.\n    \"itaipu60Hz\": \"hydro\",\n}\n\n# Those modes report self consumption, therefore they can be negative.\nCORRECTED_NEGATIVE_PRODUCTION = {\"solar\"}\n\nREGIONS = {\n    \"BR-NE\": \"nordeste\",\n    \"BR-N\": \"norte\",\n    \"BR-CS\": \"sudesteECentroOeste\",\n    \"BR-S\": \"sul\",\n}\n\nEXCHANGES = {\n    \"BR-CS->BR-S\": {\"name\": \"sul_sudeste\", \"flow\": -1, \"level\": \"intercambio\"},\n    \"BR-CS->BR-NE\": {\"name\": \"sudeste_nordeste\", \"flow\": 1, \"level\": \"intercambio\"},\n    \"BR-CS->BR-N\": {\"name\": \"sudeste_norteFic\", \"flow\": 1, \"level\": \"intercambio\"},\n    \"BR-N->BR-NE\": {\"name\": \"norteFic_nordeste\", \"flow\": 1, \"level\": \"intercambio\"},\n    \"BR-S->UY\": {\"name\": \"uruguai\", \"flow\": 1, \"level\": \"internacional\"},\n    \"AR->BR-S\": {\"name\": \"argentina\", \"flow\": -1, \"level\": \"internacional\"},\n    \"BR-S->PY\": {\"name\": \"paraguai\", \"flow\": -1, \"level\": \"internacional\"},\n}\n\n\ndef get_data(session: Session | None):\n    \"\"\"Requests generation data in json format.\"\"\"\n    s = session or Session()\n    json_data = s.get(URL).json()\n\n    return json_data\n\n\ndef production_processor(\n    json_data: dict, zone_key: str\n) -> tuple[datetime, ProductionMix]:\n    \"\"\"Extracts data timestamp and sums regional data into totals by key.\"\"\"\n\n    dt = datetime.fromisoformat(json_data[\"Data\"])\n    production = ProductionMix()\n\n    region = REGIONS[zone_key]\n    breakdown = json_data[region][\"geracao\"]\n    for generation, val in breakdown.items():\n        if generation != \"total\":  # Skip the total field\n            mode_name = GENERATION_MAPPING.get(generation, \"unknown\")\n            production.add_value(\n                mode_name, val, mode_name in CORRECTED_NEGATIVE_PRODUCTION\n            )\n\n    return dt, production\n\n\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    data = get_data(session)\n    date, production = production_processor(data, zone_key)\n    productions = ProductionBreakdownList(logger)\n    productions.append(\n        zoneKey=zone_key,\n        datetime=date,\n        source=SOURCE,\n        production=production,\n    )\n\n    return productions.to_list()\n\n\ndef get_exchange_flow(sorted_zone_keys: ZoneKey, raw_data: dict) -> float:\n    \"\"\"Returns the flow of the exchange between two regions.\"\"\"\n    name, flow, level = EXCHANGES[sorted_zone_keys].values()\n    return raw_data[level][name] * flow\n\n\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known power exchange (in MW) between two regions.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    data = get_data(session)\n    dt = datetime.fromisoformat(data[\"Data\"])\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    exchanges = ExchangeList(logger)\n\n    net_flow = get_exchange_flow(sorted_zone_keys, data)\n    exchanges.append(\n        zoneKey=sorted_zone_keys,\n        datetime=dt,\n        source=SOURCE,\n        netFlow=net_flow,\n    )\n    return exchanges.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production(BR-NE) ->\")\n    print(fetch_production(ZoneKey(\"BR-NE\")))\n\n    print(\"fetch_production(BR-N) ->\")\n    print(fetch_production(ZoneKey(\"BR-N\")))\n\n    print(\"fetch_production(BR-CS) ->\")\n    print(fetch_production(ZoneKey(\"BR-CS\")))\n\n    print(\"fetch_production(BR-S) ->\")\n    print(fetch_production(ZoneKey(\"BR-S\")))\n\n    print(\"fetch_exchange(BR-S, UY) ->\")\n    print(fetch_exchange(\"BR-S\", \"UY\"))\n\n    print(\"fetch_exchange(BR-S, AR) ->\")\n    print(fetch_exchange(\"BR-S\", \"AR\"))\n\n    print(\"fetch_region_exchange(BR-CS->BR-S)\")\n    print(fetch_exchange(\"BR-CS\", \"BR-S\"))\n\n    print(\"fetch_region_exchange(BR-CS->BR-NE)\")\n    print(fetch_exchange(\"BR-CS\", \"BR-NE\"))\n\n    print(\"fetch_region_exchange(BR-CS->BR-N)\")\n    print(fetch_exchange(\"BR-CS\", \"BR-N\"))\n\n    print(\"fetch_region_exchange(BR-N->BR-NE)\")\n    print(fetch_exchange(\"BR-N\", \"BR-NE\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/OPENNEM.py",
    "content": "from datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    PriceList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.parsers.lib.utils import get_token\nfrom electricitymap.contrib.types import ZoneKey\n\nREFETCH_FREQUENCY = timedelta(days=7)\n\n\nZONE_KEY_TO_REGION = {\n    \"AU-NSW\": \"NSW1\",\n    \"AU-QLD\": \"QLD1\",\n    \"AU-SA\": \"SA1\",\n    \"AU-TAS\": \"TAS1\",\n    \"AU-VIC\": \"VIC1\",\n    \"AU-WA\": \"WEM\",\n}\nZONE_KEY_TO_NETWORK = {\n    \"AU-NSW\": \"NEM\",\n    \"AU-QLD\": \"NEM\",\n    \"AU-SA\": \"NEM\",\n    \"AU-TAS\": \"NEM\",\n    \"AU-VIC\": \"NEM\",\n    \"AU-WA\": \"WEM\",\n}\n\n# exchanges are reconstructed from each zones total imports and exports\n# all exchanges except AU-NSW->AU-VIC only have one connection so we can\n# reconstruct the net flow by querying to leaf node\n# see diagram below\n#       QLD\n#        |\n#       NSW\n#        |\n#   SA--VIC\n#        |\n#       TAS\nEXCHANGE_MAPPING_DICTIONARY = {\n    \"AU-NSW->AU-QLD\": {\n        \"zone_to_query\": \"AU-QLD\",\n        \"direction\": -1,\n    },\n    \"AU-SA->AU-VIC\": {\n        \"zone_to_query\": \"AU-SA\",\n        \"direction\": 1,\n    },\n    \"AU-TAS->AU-VIC\": {\n        \"zone_to_query\": \"AU-TAS\",\n        \"direction\": 1,\n    },\n    # we get this flow by substracting QLD imports/exports from NSW imports/exports\n    \"AU-NSW->AU-VIC\": {\n        \"zone_to_query\": \"AU-NSW\",\n        \"direction\": 1,\n    },\n}\n\n# Mapped from https://docs.openelectricity.org.au/guides/fueltechs#fueltechs\nOPENNEM_PRODUCTION_CATEGORIES = {\n    \"coal\": [\"COAL_BLACK\", \"COAL_BROWN\"],\n    \"gas\": [\"GAS_CCGT\", \"GAS_OCGT\", \"GAS_RECIP\", \"GAS_STEAM\", \"GAS_WCMG\"],\n    \"oil\": [\"DISTILLATE\"],\n    \"hydro\": [\"HYDRO\"],\n    \"wind\": [\"WIND\", \"WIND_OFFSHORE\"],\n    \"biomass\": [\"BIOENERGY_BIOGAS\", \"BIOENERGY_BIOMASS\"],\n    \"solar\": [\"SOLAR_UTILITY\", \"SOLAR_ROOFTOP\", \"SOLAR_THERMAL\"],\n    \"nuclear\": [\"NUCLEAR\"],\n}\nOPENNEM_STORAGE_CATEGORIES = {\n    # Storage\n    \"battery\": [\"BATTERY_DISCHARGING\", \"BATTERY_CHARGING\", \"BATTERY\"],\n    \"hydro\": [\"PUMPS\"],\n}\n\n# Reverse mapping from fuel type to category\nPRODUCTION_MAPPING = {\n    fuel_type.lower(): category\n    for category, fuel_types in OPENNEM_PRODUCTION_CATEGORIES.items()\n    for fuel_type in fuel_types\n}\nSTORAGE_MAPPING = {\n    fuel_type.lower(): category\n    for category, fuel_types in OPENNEM_STORAGE_CATEGORIES.items()\n    for fuel_type in fuel_types\n}\n\nIGNORED_FUEL_TECH_KEYS = {\n    \"imports\",\n    \"exports\",\n    \"interconnector\",\n    \"aggregator_vpp\",\n    \"aggregator_dr\",\n}\n\nSOURCE = \"opennem.org.au\"\n\n\n# TODO: after full v4 migration: deprecate this in favor of fetch_network_datasets\ndef fetch_datasets(\n    zone_key: ZoneKey, session: Session, target_datetime: datetime | None\n):\n    region = ZONE_KEY_TO_REGION.get(zone_key)\n    if not region:\n        raise ParserException(\n            parser=\"OPENNEM\",\n            message=f\"Invalid zone_key {zone_key}, valid keys are {list(ZONE_KEY_TO_REGION.keys())}\",\n            zone_key=zone_key,\n        )\n    url = generate_url(\n        zone_key=zone_key,\n        target_datetime=target_datetime,\n    )\n    response = session.get(url)\n    response.raise_for_status()\n\n    return response.json()[\"data\"]\n\n\n# TODO: after full v4 migration: deprecate this in favor of generate_network_url\ndef generate_url(zone_key: ZoneKey, target_datetime: datetime | None) -> str:\n    # Only 7d or 30d data is available\n    duration = (\n        \"7d\"\n        if not target_datetime\n        or (datetime.now() - target_datetime.replace(tzinfo=None)) < timedelta(days=7)\n        else \"30d\"\n    )\n    network = ZONE_KEY_TO_NETWORK[zone_key]\n    region = ZONE_KEY_TO_REGION.get(zone_key)\n    # Western Australia have no region in url\n    region = \"\" if region == \"WEM\" else f\"/{region}\"\n    url = f\"https://data.openelectricity.org.au/v4/stats/au/{network}{region}/power/{duration}.json\"\n\n    return url\n\n\ndef process_production_datasets(\n    datasets: list,\n    zone_key: ZoneKey,\n    logger: Logger,\n) -> ProductionBreakdownList:\n    \"\"\"\n    Process production datasets from v4 API endpoint and return a production breakdown list.\n    v4 API format: data[].results[] with columns.fueltech and time series data as [timestamp, value] pairs.\n    \"\"\"\n    now = datetime.now(tz=timezone.utc)\n    unmerged_production_breakdown_lists = []\n\n    # v4 API format: data[].results[] with columns.fueltech\n    for dataset in datasets:\n        if dataset.get(\"metric\") != \"power\":\n            continue\n\n        for result in dataset.get(\"results\", []):\n            columns = result.get(\"columns\", {})\n            fueltech = columns.get(\"fueltech\")\n\n            if not fueltech:\n                continue\n\n            # Map fueltech to our categories using existing mappings\n            # v4 API fueltech values are like \"COAL_BLACK\", \"GAS_CCGT\", \"BATTERY_CHARGING\", etc.\n            fueltech_key = fueltech.lower()\n\n            if fueltech_key in IGNORED_FUEL_TECH_KEYS:\n                continue\n\n            # Map fueltech to category using existing PRODUCTION_MAPPING and STORAGE_MAPPING\n            if fueltech_key in PRODUCTION_MAPPING:\n                category = PRODUCTION_MAPPING[fueltech_key]\n                is_production = True\n                is_storage = False\n            elif fueltech_key in STORAGE_MAPPING:\n                category = STORAGE_MAPPING[fueltech_key]\n                is_production = False\n                is_storage = True\n            else:\n                raise ParserException(\n                    parser=\"OPENNEM\",\n                    message=f\"Unknown fueltech {fueltech} in result. Map it in OPENNEM_PRODUCTION_CATEGORIES or OPENNEM_STORAGE_CATEGORIES. See https://docs.openelectricity.org.au/guides/fueltechs#fueltechs\",\n                    zone_key=zone_key,\n                )\n\n            if category in IGNORED_FUEL_TECH_KEYS:\n                continue\n\n            production_breakdown_list = ProductionBreakdownList(logger=logger)\n            time_series_data = result.get(\"data\", [])\n\n            for data_point in time_series_data:\n                # v4 format: data is array of [timestamp, value] pairs\n                if not isinstance(data_point, list) or len(data_point) < 2:\n                    continue\n\n                timestamp_str, value = data_point[0], data_point[1]\n\n                # Parse timestamp (handle both with and without timezone)\n                if timestamp_str.endswith(\"Z\"):\n                    dt = datetime.fromisoformat(timestamp_str.replace(\"Z\", \"+00:00\"))\n                elif \"+\" in timestamp_str or timestamp_str.count(\"-\") >= 3:\n                    # Has timezone info\n                    dt = datetime.fromisoformat(timestamp_str)\n                else:\n                    # No timezone, assume it's in Australia/Sydney timezone\n                    dt = datetime.fromisoformat(timestamp_str)\n                    if not dt.tzinfo:\n                        dt = dt.replace(tzinfo=ZoneInfo(\"Australia/Sydney\"))\n\n                if dt > now:\n                    logger.debug(f\"Skipping future datetime {dt} for zone {zone_key}\")\n                    continue\n\n                if value is None:\n                    continue\n\n                if is_production:\n                    production = ProductionMix()\n                    production.add_value(\n                        category,\n                        value,\n                        correct_negative_with_zero=True,\n                    )\n                    production_breakdown_list.append(\n                        zoneKey=zone_key,\n                        datetime=dt,\n                        production=production,\n                        source=SOURCE,\n                    )\n                elif is_storage:\n                    storage = StorageMix()\n                    # For storage, we want to treat discharging as positive and charging as negative, so we flip the sign for discharging fueltechs\n                    # Refrence: https://docs.openelectricity.org.au/guides/batteries\n                    multiplier = (\n                        -1\n                        if (\"discharging\" in fueltech_key or fueltech_key == \"battery\")\n                        else 1\n                    )\n                    value = value * multiplier if value is not None else None\n                    storage.add_value(\n                        category,\n                        value,\n                    )\n                    production_breakdown_list.append(\n                        zoneKey=zone_key,\n                        datetime=dt,\n                        storage=storage,\n                        source=SOURCE,\n                    )\n\n            unmerged_production_breakdown_lists.append(production_breakdown_list)\n\n    # Merge all production breakdown lists into one\n    merged_production = ProductionBreakdownList.merge_production_breakdowns(\n        unmerged_production_breakdown_lists,\n        logger=logger,\n    )\n\n    # OPENNEM sometimes only report solar for the latest data, remove the datapoint if it only has solar\n    # TODO: Remove this once the race condition between feeder-electricity and quality validation is fixed\n    corrected_breakdown = ProductionBreakdownList(logger=logger)\n    for event in merged_production:\n        for mode, value in event.production.__dict__.items():\n            if mode != \"solar\" and value is not None:\n                dt = event.datetime\n                production = event.production\n                storage = event.storage\n                source = event.source\n                zoneKey = event.zoneKey\n                corrected_breakdown.append(\n                    zoneKey=zoneKey,\n                    datetime=dt,\n                    production=production,\n                    storage=storage,\n                    source=source,\n                )\n                break\n    merged_production = corrected_breakdown\n    return merged_production\n\n\n@refetch_frequency(REFETCH_FREQUENCY)\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n\n    # Get network_region for the zone (will be included if available)\n    network_region = ZONE_KEY_TO_REGION.get(zone_key)\n\n    # For v4 API, we can pass None for target_datetime to get latest data without date params\n    # Only include dates if specifically requested\n    datasets = _fetch_network_datasets(\n        zone_key=zone_key,\n        session=session,\n        dataset_type=\"data\",\n        target_datetime=target_datetime,  # Pass None to get latest data without date params\n        metrics=[\"power\"],\n        secondary_grouping=\"fueltech\",\n        network_region=network_region,  # Include network_region if available\n    )\n\n    return process_production_datasets(\n        datasets=datasets,\n        zone_key=zone_key,\n        logger=logger,\n    ).to_list()\n\n\n@refetch_frequency(REFETCH_FREQUENCY)\ndef fetch_price(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n    target_datetime = target_datetime or datetime.now(tz=timezone.utc)\n\n    datasets = _fetch_network_datasets(\n        zone_key=zone_key,\n        session=session,\n        dataset_type=\"market\",\n        target_datetime=target_datetime,\n        metrics=[\"price\"],\n    )\n\n    price_list = _build_price_list(datasets, zone_key, logger)\n\n    return price_list.to_list()\n\n\n@refetch_frequency(REFETCH_FREQUENCY)\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n    exchange_key = ZoneKey(\"->\".join([zone_key1, zone_key2]))\n\n    try:\n        exchange_params = EXCHANGE_MAPPING_DICTIONARY[exchange_key]\n    except KeyError:\n        raise ParserException(\n            parser=\"OPENNEM\",\n            message=f\"Valid exchange keys for this parser are {[EXCHANGE_MAPPING_DICTIONARY.keys()]}, you passed {exchange_key=}\",\n            zone_key=exchange_key,\n        ) from None\n\n    zone_key = exchange_params[\"zone_to_query\"]\n    direction = exchange_params[\"direction\"]\n\n    if exchange_key == \"AU-NSW->AU-VIC\":\n        datetimes_and_netflows = _fetch_au_nsw_au_vic_exchange(\n            session=session,\n            target_datetime=target_datetime,\n            logger=logger,\n        )\n    else:\n        datetimes_and_netflows = _fetch_regular_exchange(\n            zone_key=zone_key,\n            direction=direction,\n            session=session,\n            target_datetime=target_datetime,\n            logger=logger,\n        )\n\n    events = ExchangeList(logger=logger)\n    for dt, netflow in datetimes_and_netflows:\n        events.append(datetime=dt, netFlow=netflow, zoneKey=exchange_key, source=SOURCE)\n    return events.to_list()\n\n\ndef _fetch_regular_exchange(\n    zone_key: ZoneKey,\n    direction: int,\n    session: Session,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[tuple[datetime, float]]:\n    \"\"\"\n    Calculate netflows for zones that have a single exchange.\n    \"\"\"\n    url = generate_url(zone_key=zone_key, target_datetime=target_datetime)\n    response = session.get(url)\n    response.raise_for_status()\n\n    exports = None\n    imports = None\n    for dataset in response.json()[\"data\"]:\n        if dataset[\"id\"].endswith(\"exports.power\"):\n            exports = dataset.get(\"history\", None)\n        elif dataset[\"id\"].endswith(\"imports.power\"):\n            imports = dataset.get(\"history\", None)\n        else:\n            continue\n    if exports is None or imports is None:\n        raise ParserException(\n            parser=\"OPENNEM\",\n            message=\"Response did not contain both export and import datasets.\",\n            zone_key=zone_key,\n        )\n\n    if (\n        exports[\"start\"] != imports[\"start\"]\n        or exports[\"last\"] != imports[\"last\"]\n        or len(exports[\"data\"]) != len(imports[\"data\"])\n    ):\n        raise ParserException(\n            parser=\"OPENNEM\",\n            message=\"Export and import data is misaligned\",\n            zone_key=zone_key,\n        )\n\n    # assume data is sorted from start to end\n    start = datetime.fromisoformat(exports[\"start\"])\n    datetimes_and_netflows = [\n        (start + timedelta(minutes=5 * i), (exp - imp) * direction)\n        for i, (exp, imp) in enumerate(\n            zip(exports[\"data\"], imports[\"data\"], strict=True)\n        )\n    ]\n\n    return datetimes_and_netflows\n\n\ndef _fetch_au_nsw_au_vic_exchange(\n    session: Session,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[tuple[datetime, float]]:\n    \"\"\"\n    Calculate AU-NSW->AU-VIC netflow from exports and imports of AU-NSW and AU-QLD.\n\n    NSW has two exchanges one to QLD, one to VIC. QLD only has one exchange to NSW.\n    We want to know\n        AU-NSW->AU-VIC = NSW_exports_to_VIC - NSW_imports_from_VIC\n\n    NSW has two exchanges one to QLD, one to VIC:\n        NSW_exports = NSW_exports_to_QLD + NSW_exports_to_VIC\n        NSW_imports = NSW_imports_from_QLD + NSW_imports_from_VIC\n\n    and because QLD only has one exchange to NSW:\n        NSW_exports_to_QLD = QLD_imports_from_NSW = QLD_imports\n        NSW_imports_from_QLD = QLD_exports_to_NSW = QLD_exports\n\n    thus\n        NSW_exports_to_VIC = NSW_exports - QLD_imports\n        NSW_imports_from_VIC = NSW_imports - QLD_exports\n\n    and\n        AU-NSW->AU-VIC = NSW_exports - QLD_imports - NSW_imports + QLD_exports\n        = NSW_exports - NSW_imports + QLD_exports - QLD_imports\n    \"\"\"\n    nsw_zk = ZoneKey(\"AU-NSW\")\n    qld_zk = ZoneKey(\"AU-QLD\")\n\n    nsw_url = generate_url(zone_key=nsw_zk, target_datetime=target_datetime)\n    qld_url = generate_url(zone_key=qld_zk, target_datetime=target_datetime)\n\n    # potential race condition here\n    # if the first request if right before a 5 minute interval and\n    # the second request is right after then the responses could be out of sync\n    # so we issue additional request as close to base request\n    nsw_response = session.get(nsw_url)\n    qld_response = session.get(qld_url)\n\n    nsw_response.raise_for_status()\n    qld_response.raise_for_status()\n\n    nsw_exports = None\n    nsw_imports = None\n    for dataset in nsw_response.json()[\"data\"]:\n        if dataset[\"id\"].endswith(\"exports.power\"):\n            nsw_exports = dataset.get(\"history\", None)\n        elif dataset[\"id\"].endswith(\"imports.power\"):\n            nsw_imports = dataset.get(\"history\", None)\n        else:\n            continue\n    if nsw_exports is None or nsw_imports is None:\n        raise ParserException(\n            parser=\"OPENNEM\",\n            message=\"Response did not contain both export and import datasets.\",\n            zone_key=nsw_zk,\n        )\n\n    qld_exports = None\n    qld_imports = None\n    for dataset in qld_response.json()[\"data\"]:\n        if dataset[\"id\"].endswith(\"exports.power\"):\n            qld_exports = dataset.get(\"history\", None)\n        elif dataset[\"id\"].endswith(\"imports.power\"):\n            qld_imports = dataset.get(\"history\", None)\n        else:\n            continue\n    if qld_exports is None or qld_imports is None:\n        raise ParserException(\n            parser=\"OPENNEM\",\n            message=\"Response did not contain both export and import datasets.\",\n            zone_key=qld_zk,\n        )\n\n    # all must have same start, end, and number of data points\n    if not (\n        nsw_exports[\"start\"]\n        == nsw_imports[\"start\"]\n        == qld_exports[\"start\"]\n        == qld_imports[\"start\"]\n        and nsw_exports[\"last\"]\n        == nsw_imports[\"last\"]\n        == qld_exports[\"last\"]\n        == qld_imports[\"last\"]\n        and len(nsw_exports[\"data\"])\n        == len(nsw_imports[\"data\"])\n        == len(qld_exports[\"data\"])\n        == len(qld_imports[\"data\"])\n    ):\n        raise ParserException(\n            parser=\"OPENNEM\",\n            message=f\"{nsw_zk} and {qld_zk} export and import data is misaligned\",\n            zone_key=nsw_zk,\n        )\n\n    # assume data is sorted from start to end\n    start = datetime.fromisoformat(nsw_exports[\"start\"])\n    datetimes_and_netflows = [\n        (start + timedelta(minutes=5 * i), (nsw_exp - nsw_imp + qld_exp - qld_imp))\n        for i, (nsw_exp, nsw_imp, qld_exp, qld_imp) in enumerate(\n            zip(\n                nsw_exports[\"data\"],\n                nsw_imports[\"data\"],\n                qld_exports[\"data\"],\n                qld_imports[\"data\"],\n                strict=True,\n            )\n        )\n    ]\n\n    return datetimes_and_netflows\n\n\ndef _build_network_url(\n    path: str,\n    network_code: str,\n    metrics: list[str],\n    target_datetime: datetime | None,\n    network_region: str | None = None,\n    secondary_grouping: str | None = None,\n) -> tuple[str, dict[str, Any]]:\n    base_url = f\"https://api.openelectricity.org.au/v4/{path}/network/{network_code}\"\n\n    params: dict[str, Any] = {\n        \"metrics\": metrics,\n    }\n\n    # Add date range only if target_datetime is explicitly provided\n    # If None, API will return latest available data\n    if target_datetime:\n        # API expects naive datetime in network-local time; target_datetime is UTC -> convert and drop tzinfo.\n        def format_datetime(dt: datetime) -> str:\n            local_dt = dt.astimezone(ZoneInfo(\"Australia/Sydney\"))\n            naive_dt = local_dt.replace(tzinfo=None)\n            return naive_dt.isoformat()\n\n        params[\"date_start\"] = format_datetime(target_datetime - REFETCH_FREQUENCY)\n        params[\"date_end\"] = format_datetime(target_datetime)\n\n    # Add network_region only if provided (not required for production data endpoint)\n    if network_region:\n        params[\"network_region\"] = network_region\n\n    # Add secondary_grouping if provided (for production data with fueltech)\n    if secondary_grouping:\n        params[\"secondary_grouping\"] = secondary_grouping\n\n    return base_url, params\n\n\ndef _fetch_network_datasets(\n    zone_key: str,\n    session: Session,\n    dataset_type: str,\n    target_datetime: datetime | None,\n    metrics: list[str],\n    secondary_grouping: str | None = None,\n    network_region: str | None = None,\n) -> list[dict[str, Any]]:\n    network_code = ZONE_KEY_TO_NETWORK.get(zone_key)\n\n    if not network_code:\n        raise ParserException(\n            parser=\"OPENNEM\",\n            message=f\"Invalid zone_key {zone_key}, valid keys are {list(ZONE_KEY_TO_NETWORK.keys())}\",\n            zone_key=zone_key,\n        )\n\n    # Use provided network_region or get from zone_key mapping\n    if network_region is None:\n        network_region = ZONE_KEY_TO_REGION.get(zone_key)\n\n    url, params = _build_network_url(\n        path=dataset_type,\n        network_code=network_code,\n        metrics=metrics,\n        target_datetime=target_datetime or datetime.now(tz=timezone.utc),\n        network_region=network_region,\n        secondary_grouping=secondary_grouping,\n    )\n\n    token = get_token(\"OPENELECTRICITY_TOKEN\")\n    headers = {\n        \"Authorization\": f\"Bearer {token}\",\n    }\n\n    response = session.get(url, headers=headers, params=params)\n    response.raise_for_status()\n\n    return response.json()[\"data\"]\n\n\ndef _build_price_list(datasets, zone_key: ZoneKey, logger: Logger) -> PriceList:\n    price_list = PriceList(logger=logger)\n    for dataset in datasets:\n        if dataset[\"metric\"] != \"price\":\n            continue\n        for result in dataset[\"results\"]:\n            for ts, price in result[\"data\"]:\n                price_list.append(\n                    zoneKey=zone_key,\n                    datetime=datetime.fromisoformat(ts),\n                    currency=\"AUD\",\n                    price=price,\n                    source=SOURCE,\n                )\n\n    return price_list\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the electricityMap backend, but handy for testing.\"\"\"\n    # print(\"fetch_price(zone_key='AU-SA') ->\")\n    # print(fetch_price(zone_key=\"AU-SA\"))\n    # print(fetch_production(ZoneKey(\"AU-TAS\")))\n    # print(fetch_production(ZoneKey(\"AU-NSW\")))\n    # target_datetime = datetime.fromisoformat(\"2020-01-01T00:00:00+00:00\")\n    # print(fetch_production(ZoneKey(\"AU-SA\"), target_datetime=target_datetime))\n    #\n    # print(fetch_exchange(ZoneKey(\"AU-SA\"), ZoneKey(\"AU-VIC\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/PA.py",
    "content": "import json\nimport re\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"PA.py\"\nTIMEZONE = ZoneInfo(\"America/Panama\")\nZONE_KEY = ZoneKey(\"PA\")\n\nCONSUMPTION_URL = \"https://sitr.cnd.com.pa/m/pub/sin.html\"\nCONSUMPTION_SOURCE = \"sitr.cnd.com.pa\"\n\nEXCHANGE_URL = \"https://sitr.cnd.com.pa/m/pub/int.html\"\nEXCHANGE_SOURCE = \"sitr.cnd.com.pa\"\n\nPRODUCTION_URL = \"https://sitr.cnd.com.pa/m/pub/gen.html\"\nPRODUCTION_SOURCE = \"sitr.cnd.com.pa\"\n\n# Sources:\n# 1. https://www.celsia.com/Portals/0/contenidos-celsia/accionistas-e-inversionistas/perfil-corporativo-US/presentaciones-US/2014/presentacion-morgan-ingles-v2.pdf\n# 2. https://www.celsia.com/en/about-celsia/business-model/power-generation/thermoelectric-power-plants\n# 3. https://endcoal.org/tracker/\n# 4. http://aesmcac.com/aespanamades/en/colon/ \"It reuses the heat from the exhaust gas from the gas turbines in order to obtain steam, to be later used by a steam turbine and to save fuel consumption in the production of electricity.\"\n# 5. https://panamcham.com/sites/default/files/el_inicio_del_futuro_del_gas_natural_en_panama.pdf \"3 gas turbines and 1 steam (3X1 configuration)\" \"Technology: Combined Cycle\" | This and the previous source taken together seems to imply that the steam turbine is responsible for the second cycle of the CCGT plant, giving confidence that output from all four units should indeed be tallied under \"gas\". Furthermore, as the plant also has a LNG import facility it is most unlikely the steam turbine would be burning a different fuel such as coal or oil.\n# 6. https://www.etesa.com.pa/documentos/Tomo_II__Plan_Indicativo_de_Generacin_2019__2033.pdf page 142\n# 7. http://168.77.210.79/energia/wp-content/uploads/sites/2/2020/08/2-CEE-1970-2019-GE-Generaci%C3%B3n-El%C3%A9ctrica.xls (via http://www.energia.gob.pa/mercado-energetico/?tag=84#documents-list)\n# 8. https://www.asep.gob.pa/wp-content/uploads/electricidad/resoluciones/anno_12528_elec.pdf\n# 9. https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2018/May/IRENA_RRA_Panama_2018_En.pdf\n# 10. https://www.asep.gob.pa/wp-content/uploads/electricidad/concesiones_licencias/concesiones_licencias/2021/listado_licencias_abr27.pdf\n# 11. https://generadoragatun.com/\nMAP_THERMAL_GENERATION_UNIT_NAME_TO_FUEL_TYPE = {\n    \"ACP Miraflores 2\": \"oil\",  # [7] Sheet \"C-GE-1A-1 CapInstXEmp\"\n    \"ACP Miraflores 5\": \"oil\",  # [7] Sheet \"C-GE-1A-1 CapInstXEmp\"\n    \"ACP Miraflores 6\": \"oil\",  # [7] Sheet \"C-GE-1A-1 CapInstXEmp\"\n    \"ACP Miraflores 7\": \"oil\",  # [7] Sheet \"C-GE-1A-1 CapInstXEmp\"\n    \"ACP Miraflores 8\": \"oil\",  # [7] Sheet \"C-GE-1A-1 CapInstXEmp\"\n    \"ACP Miraflores 9\": \"oil\",  # [7] Sheet \"C-GE-1A-1 CapInstXEmp\"\n    \"ACP Miraflores 10\": \"oil\",  # [7] Sheet \"C-GE-1A-1 CapInstXEmp\"\n    \"BLM 2\": \"coal\",  # [7] Sheet \"C-GE-1A-2 CapInstXEmp\"\n    \"BLM 3\": \"coal\",  # [7] Sheet \"C-GE-1A-2 CapInstXEmp\"\n    \"BLM 4\": \"coal\",  # [7] Sheet \"C-GE-1A-2 CapInstXEmp\"\n    \"BLM 5\": \"oil\",  # [7] Sheet \"C-GE-1A-2 CapInstXEmp\"\n    \"BLM 6\": \"oil\",  # [7] Sheet \"C-GE-1A-2 CapInstXEmp\"\n    \"BLM 8\": \"oil\",  # [7] Sheet \"C-GE-1A-2 CapInstXEmp\"\n    \"BLM 9\": \"oil\",  # [7] Sheet \"C-GE-1A-2 CapInstXEmp\" mentions no fuel type, and given all other units are accounted for this must be the heat recovery boiler for the 3 diesel-fired units mentioned in [2]\n    \"CADASA 1\": \"biomass\",  # [9]\n    \"CADASA 2\": \"biomass\",  # [9]\n    \"Cativá 1\": \"oil\",  # [1][2]\n    \"Cativá 2\": \"oil\",  # [1][2]\n    \"Cativá 3\": \"oil\",  # [1][2]\n    \"Cativá 4\": \"oil\",  # [1][2]\n    \"Cativá 5\": \"oil\",  # [1][2]\n    \"Cativá 6\": \"oil\",  # [1][2]\n    \"Cativá 7\": \"oil\",  # [1][2]\n    \"Cativá 8\": \"oil\",  # [1][2]\n    \"Cativá 9\": \"oil\",  # [1][2]\n    \"Cativá 10\": \"oil\",  # [1][2]\n    \"Cobre Panamá 1\": \"coal\",  # [3]\n    \"Cobre Panamá 2\": \"coal\",  # [3]\n    \"Costa Norte 1\": \"gas\",  # [4][5]\n    \"Costa Norte 2\": \"gas\",  # [4][5]\n    \"Costa Norte 3\": \"gas\",  # [4][5]\n    \"Costa Norte 4\": \"gas\",  # [4][5]\n    \"Esperanza 1\": \"oil\",  # [7] has a single 92MW bunker fuel power plant, but [8] shows this is actually a power barge with 7 units\n    \"Esperanza 2\": \"oil\",  # [7] has a single 92MW bunker fuel power plant, but [8] shows this is actually a power barge with 7 units\n    \"Esperanza 3\": \"oil\",  # [7] has a single 92MW bunker fuel power plant, but [8] shows this is actually a power barge with 7 units\n    \"Esperanza 4\": \"oil\",  # [7] has a single 92MW bunker fuel power plant, but [8] shows this is actually a power barge with 7 units\n    \"Esperanza 5\": \"oil\",  # [7] has a single 92MW bunker fuel power plant, but [8] shows this is actually a power barge with 7 units\n    \"Esperanza 6\": \"oil\",  # [7] has a single 92MW bunker fuel power plant, but [8] shows this is actually a power barge with 7 units\n    \"Esperanza 7\": \"oil\",  # [7] has a single 92MW bunker fuel power plant, but [8] shows this is actually a power barge with 7 units\n    \"Jinro\": \"oil\",  # [6][7]\n    \"Pacora 1\": \"oil\",  # [6]\n    \"Pacora 2\": \"oil\",  # [6]\n    \"Pacora 3\": \"oil\",  # [6]\n    \"PanAm 1\": \"oil\",  # [6][7]\n    \"PanAm 2\": \"oil\",  # [6][7]\n    \"PanAm 3\": \"oil\",  # [6][7]\n    \"PanAm 4\": \"oil\",  # [6][7]\n    \"PanAm 5\": \"oil\",  # [6][7]\n    \"PanAm 6\": \"oil\",  # [6][7]\n    \"PanAm 7\": \"oil\",  # [6][7]\n    \"PanAm 8\": \"oil\",  # [6][7]\n    \"PanAm 9\": \"oil\",  # [6][7]\n    \"Proyecto Gatún 1\": \"gas\",  # [11]\n    \"Proyecto Gatún 2\": \"gas\",  # [11]\n    \"Proyecto Gatún 3\": \"gas\",  # [11]\n    \"Sparkle Power 1\": \"oil\",  # [10]\n    \"Sparkle Power 2\": \"oil\",  # [10]\n    \"Sparkle Power 3\": \"oil\",  # [10]\n    \"Sparkle Power 4\": \"oil\",  # [10]\n    \"Sparkle Power 5\": \"oil\",  # [10]\n    \"Sparkle Power 6\": \"oil\",  # [10]\n    \"Sparkle Power 7\": \"oil\",  # [10]\n    \"Sparkle Power 8\": \"oil\",  # [10]\n    \"Termocolón 1\": \"oil\",  # [6] (spelled \"Termo Colón\")\n    \"Termocolón 2\": \"oil\",  # [6] (spelled \"Termo Colón\")\n    \"Termocolón 3\": \"oil\",  # [6] (spelled \"Termo Colón\")\n    \"Tropitérmica 1\": \"oil\",  # [6]:162[7] spelled \"Tropitermica\" in both\n    \"Tropitérmica 2\": \"oil\",  # [6]:162[7] spelled \"Tropitermica\" in both\n    \"Tropitérmica 3\": \"oil\",  # [6]:162[7] spelled \"Tropitermica\" in both\n}\n\nPRODUCTION_TYPE_TO_PRODUCTION_MODE = {\n    \"Hídrica\": \"hydro\",\n    \"Eólica\": \"wind\",\n    \"Solar\": \"solar\",\n    \"Biogás\": \"biomass\",\n    \"Térmica\": \"unknown\",\n}\n\n_SPANISH_CALENDAR = {\n    \"enero\": \"01\",\n    \"febrero\": \"02\",\n    \"marzo\": \"03\",\n    \"abril\": \"04\",\n    \"mayo\": \"05\",\n    \"junio\": \"06\",\n    \"julio\": \"07\",\n    \"agosto\": \"08\",\n    \"septiembre\": \"09\",\n    \"octubre\": \"10\",\n    \"noviembre\": \"11\",\n    \"diciembre\": \"12\",\n}\n\n\ndef _localise_spanish_date(date: str) -> str:\n    \"\"\"Localises a date containing full name (lowercase) spanish months, replacing them with zero-padded decimal numbers.\n\n    This avoids having to mess up the global locale to be able to parse the date.\n    \"\"\"\n    return re.sub(\n        \"|\".join(_SPANISH_CALENDAR.keys()),\n        lambda m: _SPANISH_CALENDAR[m.group(0)],\n        date,\n    )\n\n\ndef extract_pie_chart_data(html):\n    \"\"\"Extracts generation breakdown pie chart data from the source code of the page\"\"\"\n    # Extract object with data\n    data_source = re.search(r\"var localPie = (\\[\\{.+\\}\\]);\", html).group(1)\n    # Un-quoted keys ({key:\"value\"}) are valid JavaScript but not valid JSON (which requires {\"key\":\"value\"}).\n    # Will break if other keys than these three are introduced.\n    # Alternatively, use a JSON5 library (JSON5 allows un-quoted keys)\n    data_source = re.sub(r\"(name|value|color)\", r'\"\\1\"', data_source)\n    return json.loads(data_source)\n\n\ndef sum_thermal_units(soup) -> float:\n    \"\"\"Sums thermal units of the generation mix to prevent using slightly outdated chart data.\n\n    Thermal total from the graph and the total one would get from summing output of all generators deviates a bit,\n    presumably because they aren't updated at the exact same moment.\n    \"\"\"\n\n    # Sum thermal units from table Térmicas (MW)\n    thermal_h3 = soup.find(\"h3\", string=re.compile(r\"\\s*Térmicas\\s*\"))\n    thermal_tables = thermal_h3.find_next_sibling().find_all(\n        \"table\", {\"class\": \"table table-hover table-striped table-sm sitr-gen-group\"}\n    )\n\n    thermal_units = 0\n    for thermal_table in thermal_tables:\n        thermal_units += sum(\n            [\n                float(span.text)\n                for span in thermal_table.find_all(\"span\", {\"style\": \"color:#222\"})\n            ]\n        )\n        thermal_units += sum(\n            [\n                float(span.text)\n                for span in thermal_table.find_all(\"span\", {\"style\": \"color:ROYALBLUE\"})\n            ]\n        )\n\n    return thermal_units\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER, \"This parser is not yet able to parse historical data\", zone_key\n        )\n\n    # Fetch page and load into BeautifulSoup\n    r = session or Session()\n    response = r.get(PRODUCTION_URL)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    response.encoding = \"utf-8\"\n    html_doc = response.text\n    soup = BeautifulSoup(html_doc, \"html.parser\")\n\n    # Parse the datetime and return a python datetime object\n    spanish_date = soup.find(\"h3\", {\"class\": \"sitr-update\"}).string\n    english_date = _localise_spanish_date(spanish_date)\n    date = datetime.strptime(english_date, \"%d-%m-%Y %H:%M:%S\").replace(tzinfo=TIMEZONE)\n\n    production_mix = ProductionMix()\n    productions = extract_pie_chart_data(html_doc)\n    # [{name:\"Hídrica 1342.54 (80.14%)\",value:1342.54,color:\"#99ccee\"}, ...]\n    for prod in productions:  # {name:\"Hídrica 1342.54 (80.14%)\", ...}\n        production_type, production_value, _percentage = prod[\"name\"].split(\" \", 2)\n        # ignore termica data to avoid using outdated chart data\n        if production_type == \"Térmica\":\n            continue\n        production_mode = PRODUCTION_TYPE_TO_PRODUCTION_MODE[production_type]  # hydro\n        production_mix.add_value(production_mode, float(production_value))\n\n    # Calculate manually thermal generation to avoid using outdated chart data\n    thermal_generation = sum_thermal_units(soup)\n    # Known fossil plants: parse, subtract from \"unknown\", add to \"coal\"/\"oil\"/\"gas\"\n    thermal_production_breakdown = soup.find_all(\"table\", {\"class\": \"sitr-table-gen\"})[\n        1\n    ]\n    # Make sure the table header is indeed \"Térmicas (MW)\" (in case the tables are re-arranged)\n    thermal_production_breakdown_table_header = (\n        thermal_production_breakdown.parent.parent.parent.select(\"> .tile-title\")[\n            0\n        ].string\n    )\n    assert \"Térmicas\" in thermal_production_breakdown_table_header, (\n        f\"Exception when extracting thermal generation breakdown for {zone_key}: table header does not contain \"\n        f\"'Térmicas' but is instead named {thermal_production_breakdown_table_header}\"\n    )\n    thermal_production_units = thermal_production_breakdown.select(\n        \"tbody tr td table.sitr-gen-group tr\"\n    )\n\n    for thermal_production_unit in thermal_production_units:\n        unit_name_and_generation = thermal_production_unit.find_all(\"td\")\n        unit_name = unit_name_and_generation[0].string\n        unit_generation = float(unit_name_and_generation[1].string)\n        if unit_name in MAP_THERMAL_GENERATION_UNIT_NAME_TO_FUEL_TYPE:\n            if unit_generation > 0:  # Ignore self-consumption\n                unit_fuel_type = MAP_THERMAL_GENERATION_UNIT_NAME_TO_FUEL_TYPE[\n                    unit_name\n                ]\n                production_mix.add_value(unit_fuel_type, unit_generation)\n                thermal_generation -= unit_generation\n        else:\n            logger.warning(\n                f\"{unit_name} is not mapped to generation type\",\n                extra={\"key\": zone_key},\n            )\n\n    # Round remaining \"unknown\" output to 13 decimal places to get rid of floating point errors\n    thermal_generation = round(thermal_generation, 13)\n    if 0 < thermal_generation < 1e-3:\n        thermal_generation = 0.0\n    # assign anything remaining to 'unknown'\n    production_mix.add_value(\"unknown\", max(thermal_generation, 0.0))\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n    production_breakdown_list.append(\n        zoneKey=zone_key,\n        datetime=date,\n        source=PRODUCTION_SOURCE,\n        production=production_mix,\n    )\n    return production_breakdown_list.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey = ZONE_KEY,\n    zone_key2: ZoneKey = ZoneKey(\"CR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known power exchange (in MW) between two countries.\"\"\"\n\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER,\n            \"This parser is not yet able to parse historical data\",\n            sorted_zone_keys,\n        )\n\n    session = session or Session()\n    timestamp = datetime.now(tz=TIMEZONE)\n    response = session.get(EXCHANGE_URL)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n            sorted_zone_keys,\n        )\n\n    df = pd.read_html(response.text)[0]\n\n    # A positive value on website indicates a flow from country specified to PA.\n    net_flow_cr = round(\n        float(df[4][1])\n        + float(df[4][3])\n        + float(df[4][5])\n        + float(df[1][8])\n        + float(df[1][10]),\n        2,\n    )\n    net_flow_gt = round(\n        float(df[4][23]) + float(df[4][26]) + float(df[4][28]) + float(df[1][31]), 2\n    )\n    net_flow_hn = round(\n        float(df[1][13])\n        + float(df[1][15])\n        + float(df[1][18])\n        + float(df[1][20])\n        + float(df[1][23]),\n        2,\n    )\n    net_flow_ni = round(\n        float(df[4][8]) + float(df[4][10]) + float(df[4][13]) + float(df[4][15]), 2\n    )\n\n    # invert sign to account for direction in alphabetical order\n    net_flow_sv = -1 * round(\n        float(df[4][18]) + float(df[4][20]) + float(df[1][26]) + float(df[1][28]), 2\n    )\n\n    net_flows = {\n        \"CR->PA\": net_flow_cr,  # Costa Rica to Panama\n        \"GT->PA\": net_flow_gt,  # Guatemala to Panama\n        \"HN->PA\": net_flow_hn,  # Honduras to Panama\n        \"NI->PA\": net_flow_ni,  # Nicaragua to Panama\n        \"PA->SV\": net_flow_sv,  # Panama to El Salvador\n    }\n\n    exchange_list = ExchangeList(logger)\n    exchange_list.append(\n        zoneKey=sorted_zone_keys,\n        datetime=timestamp,\n        netFlow=net_flows[sorted_zone_keys],\n        source=EXCHANGE_SOURCE,\n    )\n    return exchange_list.to_list()\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Fetches consumption of Panama.\"\"\"\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER, \"This parser is not yet able to parse historical data\", zone_key\n        )\n\n    r = session or Session()\n    timestamp = datetime.now(tz=TIMEZONE)\n    response = r.get(CONSUMPTION_URL)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    soup = BeautifulSoup(response.text, \"html.parser\")\n    consumption_title = soup.find(\"h5\", string=re.compile(r\"\\s*Demanda Total\\s*\"))\n    consumption_val = float(consumption_title.find_next_sibling().text.split()[0])\n\n    consumption_list = TotalConsumptionList(logger)\n    consumption_list.append(\n        zoneKey=zone_key,\n        datetime=timestamp,\n        consumption=consumption_val,\n        source=PRODUCTION_SOURCE,\n    )\n    return consumption_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_exchange() ->\")\n    print(fetch_exchange())\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/PE.py",
    "content": "#!/usr/bin/env python3\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.types import ZoneKey\n\nlogger = getLogger(__name__)\n\nAPI_ENDPOINT = \"https://www.coes.org.pe/Portal/portalinformacion/generacion\"\n\nTIMEZONE = ZoneInfo(\"America/Lima\")\n\nMAP_GENERATION = {\n    \"DIESEL\": \"oil\",\n    \"RESIDUAL\": \"biomass\",\n    \"CARBÓN\": \"coal\",\n    \"GAS\": \"gas\",\n    \"HÍDRICO\": \"hydro\",\n    \"BIOGÁS\": \"biomass\",\n    \"BAGAZO\": \"biomass\",\n    \"SOLAR\": \"solar\",\n    \"EÓLICA\": \"wind\",\n}\nSOURCE = \"coes.org.pe\"\n\n\ndef parse_datetime(dt: str):\n    return datetime.strptime(dt, \"%Y/%m/%d %H:%M:%S\").replace(\n        tzinfo=TIMEZONE\n    ) - timedelta(minutes=30)\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"PE\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE)\n    df_current = _get_production_data(session, target_datetime)\n    df_yesterday = _get_production_data(session, target_datetime - timedelta(days=1))\n\n    df = pd.concat([df_yesterday, df_current]).reset_index(drop=True)\n\n    # Parse datetime column with Peru timezone and set as index\n    df[\"datetime\"] = pd.to_datetime(df[\"datetime\"], format=\"%Y/%m/%d %H:%M:%S\")\n    df[\"datetime\"] = df[\"datetime\"].dt.tz_localize(TIMEZONE)\n    df = df.set_index(\"datetime\")\n    # Create production breakdown list\n    production_breakdown_list = ProductionBreakdownList(logger)\n\n    for datetime_idx, row in df.iterrows():\n        productionMix = ProductionMix()\n\n        # Add each energy source to the production mix\n        for energy_source, value in row.items():\n            if energy_source in MAP_GENERATION:\n                production_mode = MAP_GENERATION[energy_source]\n                productionMix.add_value(production_mode, round(float(value), 3))\n            else:\n                raise ValueError(f\"Unknown energy source: {energy_source}\")\n\n        # Add production breakdown to the list\n        # Convert pandas Timestamp to native datetime object\n        native_datetime = datetime_idx.to_pydatetime()\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=native_datetime,\n            source=SOURCE,\n            production=productionMix,\n        )\n\n    return production_breakdown_list.to_list()\n\n\ndef _get_production_data(session: Session, target_datetime: datetime) -> pd.DataFrame:\n    \"\"\"Get the production data for the target datetime.\"\"\"\n    r = session or Session()\n\n    # To guarantee a full 24 hours of data we must make 2 requests.\n    response_url_current: Response = r.post(\n        API_ENDPOINT,\n        data={\n            \"fechaInicial\": (target_datetime).strftime(\"%d/%m/%Y\"),\n            \"fechaFinal\": (target_datetime + timedelta(days=1)).strftime(\"%d/%m/%Y\"),\n            \"indicador\": 0,\n        },\n    )\n    # Data in MW (it is production not generation) + local time, be careful.\n\n    production_data = response_url_current.json()[\"GraficoTipoCombustible\"][\"Series\"]\n\n    # Transform production_data into a pandas DataFrame\n    # First, collect all datetime values and validate consistency across all sources\n    datetime_values = []\n    if production_data and production_data[0][\"Data\"]:\n        datetime_values = [data[\"Nombre\"] for data in production_data[0][\"Data\"]]\n\n    # Validate that all energy sources have the same datetime values\n    for item in production_data:\n        source_datetimes = [data[\"Nombre\"] for data in item[\"Data\"]]\n        if source_datetimes != datetime_values:\n            raise ValueError(\n                f\"Datetime values are not consistent across all sources: {source_datetimes} != {datetime_values}\"\n            )\n\n    # Create DataFrame with datetime as index and energy sources as columns\n    df_data = {\"datetime\": datetime_values}\n\n    for item in production_data:\n        source_name = item[\"Name\"]\n        values = [data[\"Valor\"] for data in item[\"Data\"]]\n        df_data[source_name] = values\n\n    # Convert to pandas DataFrame\n    df = pd.DataFrame(df_data)\n\n    return df\n\n\nif __name__ == \"__main__\":\n    fetch_production()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/PF.py",
    "content": "#!/usr/bin/env python3\n\nimport json\nimport re\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"PF.py\"\nTIMEZONE = ZoneInfo(\"Pacific/Tahiti\")\n\nPRODUCTION_API_URL = \"https://www.edt.pf/transition-energetique-innovation\"\nPRODUCTION_SOURCE = \"edt.pf\"\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"PF\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    session = session or Session()\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER, \"This parser is not yet able to parse historical data\", zone_key\n        )\n\n    time = datetime.now(tz=TIMEZONE)\n    response = session.get(PRODUCTION_API_URL)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    soup = BeautifulSoup(response.text, \"lxml\")\n    block = soup.find(\n        id=\"id1____detailMesurePortlet__WAR__EDTAEL2018__Script\"\n    ).prettify()\n    block = block.replace(\"\\n\", \"\")\n    block = re.search(r'\\{\"cols.*\\}\\]\\}\\]\\}', block)\n    data_table = block.group(0)\n    data_table = re.sub(\"Thermique\", \"oil\", data_table)\n    data_table = re.sub(\"Hydro électricité\", \"hydro\", data_table)\n    data_table = re.sub(\"Solaire\", \"solar\", data_table)\n    data_dict = json.loads(data_table)\n\n    # Parse the dict 'data_dict' containing the production mix (the values are in kW)\n    production_mix = ProductionMix()\n    for line in data_dict[\"rows\"]:\n        resource = line[\"c\"][0].get(\"v\")\n        production_value = line[\"c\"][1].get(\"v\")\n        production_value_mw = production_value / 1000\n        production_mix.add_value(resource, production_value_mw)\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n    production_breakdown_list.append(\n        zoneKey=zone_key,\n        datetime=time.replace(second=0, microsecond=0),  # truncate to minutes\n        source=PRODUCTION_SOURCE,\n        production=production_mix,\n    )\n    return production_breakdown_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/PrinceEdwardIsland.py",
    "content": "#!/usr/bin/env python3\nimport json\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nSOURCE = \"PrinceEdwardIsland.ca\"\nTIMEZONE = ZoneInfo(\"Canada/Atlantic\")\n# The dashboard associated with this API can be found at\n# https://www.PrinceEdwardIsland.ca/en/feature/pei-wind-energy.\nURL = \"https://wdf.PrinceEdwardIsland.ca/api/workflow\"  # API\nZONE_KEY = ZoneKey(\"CA-PE\")\n\n\ndef _parse_power(text: str) -> float:\n    return float(text[: text.index(\" MW\")])\n\n\ndef _get_event(session: Session):\n    # Request an event from the source.\n    event = session.post(\n        URL,\n        data=json.dumps({\"featureName\": \"WindEnergy\", \"queryName\": \"WindEnergy\"}),\n        headers={\"Content-Type\": \"application/json\"},\n    ).json()[\"data\"]\n    # Collect the production modes and power values into a lookup table.\n    modes = dict(\n        object_[\"data\"][\"header\"].split(\": \", maxsplit=1)\n        for object_ in event\n        if object_[\"type\"] == \"GaugeChart\"\n    )\n    # Extract the timestamp.\n    timestamp = datetime.strptime(\n        event[-1][\"data\"][\"text\"][len(\"Last updated \") :], \"%B %d, %Y %I:%M %p\"\n    ).replace(tzinfo=TIMEZONE)\n    # Return a new, more convenient lookup table.\n    return {\n        \"datetime\": timestamp,\n        \"fossil\": _parse_power(modes[\"Total On-Island Fossil Fuel Generation\"]),\n        \"load\": _parse_power(modes[\"Total On-Island Load\"]),\n        \"wind\": _parse_power(modes[\"Total On-Island Wind Generation\"]),\n    }\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    if zone_key != ZONE_KEY:\n        raise ParserException(\n            \"PrinceEdwardIsland.py\", \"Cannot parse zone '{zone_key}'\", zone_key\n        )\n    if target_datetime:\n        raise ParserException(\n            \"PrinceEdwardIsland.py\", \"Unable to fetch historical data\", ZONE_KEY\n        )\n\n    event = _get_event(session or Session())\n\n    production_mix = ProductionMix()\n\n    # These are oil-fueled (\"heavy fuel oil\" and \"diesel\") generators used as\n    # peakers and back-up.\n    production_mix.add_value(\"oil\", event[\"fossil\"])\n    production_mix.add_value(\"wind\", event[\"wind\"])\n\n    production_breakdowns = ProductionBreakdownList(logger)\n    production_breakdowns.append(\n        datetime=event[\"datetime\"],\n        production=production_mix,\n        source=SOURCE,\n        zoneKey=ZONE_KEY,\n    )\n    return production_breakdowns.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known power exchange (in MW) between two regions.\"\"\"\n\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted((zone_key1, zone_key2))))\n\n    if target_datetime:\n        raise ParserException(\n            \"PrinceEdwardIsland.py\", \"Unable to fetch historical data\", sorted_zone_keys\n        )\n\n    if sorted_zone_keys != ZoneKey(\"CA-NB->CA-PE\"):\n        raise ParserException(\n            \"PrinceEdwardIsland.py\",\n            f\"The exchange pair '{sorted_zone_keys}' is not implemented\",\n            sorted_zone_keys,\n        )\n\n    # PEI imports most of its electricity. Everything not generated on the\n    # island is imported from New Brunswick.\n    #\n    # In the case of wind, some is \"paper-exported\" even if there is a net\n    # import, and the \"Wind Power Exported Off Island\" gauge on the dashboard\n    # indicates their accounting of these exports. The dashboard says:\n    #\n    #   Wind Power Exported Off-Island is that portion of wind generation that\n    #   is supplying contracts elsewhere. The actual electricity from this\n    #   portion of wind generation may stay within PEI but is satisfying a\n    #   contractual arrangement in another jurisdiction.\n    #\n    # We are ignoring these paper exports, as they are an accounting/legal\n    # detail that doesn't actually reflect what happens on the wires. Given\n    # that NB is the only interconnection with PEI, physically exporting wind\n    # power to NB while simultaneously importing the balance seems unlikely.\n    event = _get_event(session or Session())\n    exchanges = ExchangeList(logger)\n    exchanges.append(\n        datetime=event[\"datetime\"],\n        # The sorted zones are CA-NB -> CA-PE, so a positive value represents\n        # export from NB / import into PE.\n        netFlow=event[\"load\"] - event[\"fossil\"] - event[\"wind\"],\n        source=SOURCE,\n        zoneKey=sorted_zone_keys,\n    )\n\n    return exchanges.to_list()\n\n\nif __name__ == \"__main__\":\n    # Never used by the Electricity Map backend, but handy for testing.\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n\n    print('fetch_exchange(\"CA-PE\", \"CA-NB\") ->')\n    print(fetch_exchange(ZoneKey(\"CA-PE\"), ZoneKey(\"CA-NB\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/README.md",
    "content": "# Parsers\n\nA parser is a file or script that is responsible for fetching data for a particular zone or set of zones and/or exchanges.\n\nParsers are built using public URLs that has data available at hourly or better granularity. For a full list of technical requirements regarding data sources check out our wiki page: [Technical requirements for data sources][wiki data source req]\n\nIf you want to **create a new parser** you can check out the specific parser function documentation in the [examples folder](/electricitymap/contrib/parsers/examples/) or take a look at one of our existing parsers.\nNote: Not all of our existing parsers have been updated with the latest syntax and might be functional but outdated.\n\n## Different kinds of parsers\n\nRight now we support the following parsers:\n\n### Live parsers:\n\n- #### Production parsers:\n  These parsers are our primary source of data and parse aggregated production data from our sources.\n- #### Consumption parsers:\n  Like the production parsers these parse aggregated data but instead of parsing what a zone produces they parse the zones electricity consumption.\n- #### Price parsers:\n  Price parsers parse electricity cost before any potential taxes or transmission fees and should return the price at hourly or better resolution even if the _Market Time Unit_ or MTU, is longer.\n- #### Production Per Unit parsers:\n  These parsers parse the production of individual production units or power plants for a zone.\n- #### Exchange parsers:\n  These parsers parse the net flow, exchange, of electricity between two zones.\n\n### Forecast parsers:\n\n- #### Generation Forecast parser:\n  Parse the forecasted total generation for a zone.\n- #### Generation Per Mode Forecast parser:\n  Similar to the generation forecast parser but parse forecasted generation per production mode.\n- #### Consumption Forecast parser:\n  Parse the forecasted consumption for a zone.\n- #### Exchange Forecast parser:\n  Parse the forecasted net flow, exchange, between two zones.\n\n# Archived parsers\n\nParsers that are no longer used or have been broken for a long time reside in the [/archived](/electricitymap/contrib/parsers/archived/) folder.\n\n[wiki data source req]: https://github.com/electricitymaps/electricitymaps-contrib/wiki/Technical-requirements-for-parser-data\n"
  },
  {
    "path": "electricitymap/contrib/parsers/RU.py",
    "content": "#!/usr/bin/python3\n\nimport json\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.types import ZoneKey\n\n# RU-1: European and Uralian Market Zone (Price Zone 1)\n# RU-2: Siberian Market Zone (Price Zone 2)\n# RU-AS: Russia East Power System (2nd synchronous zone)\n# Handling of hours: data at t on API side corresponds to\n# production / consumption from t to t+1\n\n# http://br.so-ups.ru is not available outside Russia (sometimes?), use a reverse proxy in Russia\nHOST = \"https://858127-cc16935.tmweb.ru\"\nBASE_EXCHANGE_URL = f\"{HOST}/webapi/api/flowDiagramm/GetData?\"\n\nMAP_GENERATION_1 = {\n    \"P_AES\": \"nuclear\",\n    \"P_GES\": \"hydro\",\n    \"P_GRES\": \"unknown\",\n    \"P_TES\": \"unknown\",\n    \"P_BS\": \"unknown\",\n    \"P_REN\": \"solar\",\n    \"P_WIND\": \"wind\",\n}\n\nMAP_GENERATION_2 = {\"aes_gen\": \"nuclear\", \"ges_gen\": \"hydro\", \"P_tes\": \"unknown\"}\n\nIGNORE_KEYS = {\n    \"M_DATE\",\n    \"INTERVAL\",\n    \"date\",\n    \"hour\",\n    \"fHour\",\n    \"Pmin_tes\",\n    \"Pmax_tes\",\n    \"power_sys_id\",\n    \"price_zone_id\",\n}\n\nexchange_ids = {\n    \"RU-AS->CN\": 764,\n    \"RU->MN\": 276,\n    \"RU-2->MN\": 276,\n    \"RU->KZ\": 785,\n    \"RU-1->KZ\": 2394,\n    \"RU-2->KZ\": 344,\n    \"RU-2->RU-1\": 139,\n    \"RU->GE\": 752,\n    \"RU-1->GE\": 752,\n    \"AZ->RU\": 598,\n    \"AZ->RU-1\": 598,\n    \"BY->RU\": 321,\n    \"BY->RU-1\": 321,\n    \"RU->FI\": 187,\n    \"RU-1->FI\": 187,\n    \"RU-KGD->LT\": 212,\n    \"RU-1->UA-CR\": 5688,\n    \"UA->RU-1\": 880,\n}\n\nSOURCE = \"so-ups.ru\"\n\n# Each exchange is contained in a div tag with a \"data-id\" attribute that is unique.\n\n\nTIMEZONE = ZoneInfo(\"Europe/Moscow\")\n\n\n@refetch_frequency(timedelta(hours=24))\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict] | dict:\n    \"\"\"Fetch production data for Russian zones (1st and 2nd synchronous zones).\"\"\"\n    session = session or Session()\n\n    # Zone configuration\n    zone_key_price_zone_mapper = {\n        \"RU-1\": 1,\n        \"RU-2\": 2,\n    }\n\n    # Validate zone\n    if zone_key not in zone_key_price_zone_mapper and zone_key != \"RU-AS\":\n        raise NotImplementedError(\"This parser is not able to parse given zone\")\n\n    # Prepare datetime\n    if target_datetime:\n        target_datetime_tz = target_datetime.astimezone(tz=TIMEZONE)\n    else:\n        target_datetime_tz = datetime.now(TIMEZONE)\n    datetime_to_fetch = target_datetime_tz - timedelta(hours=1)\n    date = datetime_to_fetch.strftime(\"%Y.%m.%d\")\n\n    # Build URL based on zone type\n    if zone_key in zone_key_price_zone_mapper:\n        # 1st synchronous zone (RU-1, RU-2)\n        price_zone = zone_key_price_zone_mapper[zone_key]\n        url = f\"{HOST}/webapi/api/CommonInfo/PowerGeneration?priceZone[]={price_zone}&startDate={date}&endDate={date}\"\n        generation_map = MAP_GENERATION_1\n        date_key = \"M_DATE\"\n        hour_key = \"INTERVAL\"\n    else:\n        # 2nd synchronous zone (RU-AS)\n        url = f\"{HOST}/webapi/api/CommonInfo/GenEquipOptions_Z2?oesTerritory[]=540000&startDate={date}\"\n        generation_map = MAP_GENERATION_2\n        date_key = \"date\"\n        hour_key = \"hour\"\n\n    response = session.get(url, verify=False)\n    json_content = json.loads(response.text)\n    dataset = json_content[0][\"m_Item2\"]\n\n    production_breakdown_list = ProductionBreakdownList(logger=logger)\n    for datapoint in dataset:\n        production = ProductionMix()\n\n        for key in datapoint:\n            if key in IGNORE_KEYS:\n                continue\n            if key in generation_map:\n                production_type = generation_map[key]\n                gen_value = datapoint[key]\n                production.add_value(\n                    mode=production_type,\n                    value=gen_value,\n                    correct_negative_with_zero=True,\n                )\n            else:\n                logger.warning(\n                    f\"Unknown production type '{key}' with value {datapoint[key]} in {zone_key} production data\"\n                )\n\n        # Parse datetime based on zone type\n        date = datetime.fromisoformat(datapoint[date_key])\n        interval_hour = datapoint[hour_key]\n\n        dt = date + timedelta(hours=interval_hour)\n\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            production=production,\n            source=SOURCE,\n        )\n\n    return production_breakdown_list.to_list()\n\n\ndef response_checker(json_content) -> bool:\n    flow_values = json_content[\"Flows\"]\n\n    if not flow_values:\n        return False\n\n    non_zero = False\n    for item in flow_values:\n        if item[\"Id\"] in list(exchange_ids.values()):\n            if item[\"NumValue\"] == 0.0:\n                continue\n            else:\n                non_zero = True\n                break\n\n    return non_zero\n\n\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known power exchange (in MW) between two zones.\"\"\"\n    today = target_datetime if target_datetime else datetime.now(timezone.utc)\n\n    date = today.date().isoformat()\n    r = session or Session()\n    DATE = f\"Date={date}\"\n\n    exchange_urls = []\n    if target_datetime:\n        for hour in range(0, 24):\n            url = BASE_EXCHANGE_URL + DATE + f\"&Hour={hour}\"\n            exchange_urls.append((url, hour))\n    else:\n        # Only fetch last 2 hours when not fetching historical data.\n        for shift in range(0, 2):\n            hour = (today - timedelta(hours=shift)).strftime(\"%H\")\n            url = BASE_EXCHANGE_URL + DATE + f\"&Hour={hour}\"\n            exchange_urls.append((url, int(hour)))\n\n    datapoints = []\n    for url, hour in exchange_urls:\n        response = r.get(url, verify=False)\n        json_content = json.loads(response.text)\n\n        if response_checker(json_content):\n            datapoints.append((json_content[\"Flows\"], hour))\n        else:\n            # data not yet available for this hour\n            continue\n\n    sortedcodes = \"->\".join(sorted([zone_key1, zone_key2]))\n    reversesortedcodes = \"->\".join(sorted([zone_key1, zone_key2], reverse=True))\n\n    if sortedcodes in exchange_ids:\n        exchange_id = exchange_ids[sortedcodes]\n        direction = 1\n    elif reversesortedcodes in exchange_ids:\n        exchange_id = exchange_ids[reversesortedcodes]\n        direction = -1\n    else:\n        raise NotImplementedError(\"This exchange pair is not implemented.\")\n\n    data = []\n    for datapoint, hour in datapoints:\n        try:\n            exchange = [item for item in datapoint if item[\"Id\"] == exchange_id][0]\n            flow = exchange.get(\"NumValue\") * direction\n        except KeyError:\n            # flow is unknown or not available\n            flow = None\n\n        dt = today.replace(hour=hour, minute=0, second=0, microsecond=0)\n\n        exchange = {\n            \"sortedZoneKeys\": sortedcodes,\n            \"datetime\": dt,\n            \"netFlow\": flow,\n            \"source\": SOURCE,\n        }\n\n        data.append(exchange)\n\n    return data\n"
  },
  {
    "path": "electricitymap/contrib/parsers/SE.py",
    "content": "\"\"\"\nPoor mans parser timeboxing for Sweden subzones.\n\"\"\"\n\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\n\nfrom requests import Session\n\nfrom electricitymap.contrib.parsers.ENTSOE import (\n    fetch_production as fetch_production_enstoe,\n)\nfrom electricitymap.contrib.parsers.eSett import (\n    fetch_production as fetch_production_esett,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@refetch_frequency(timedelta(days=3))\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    assert zone_key in {\n        ZoneKey(\"SE-SE1\"),\n        ZoneKey(\"SE-SE2\"),\n        ZoneKey(\"SE-SE3\"),\n        ZoneKey(\"SE-SE4\"),\n    }, f\"Zone {zone_key} is not supported by the SE parser.\"\n    target_datetime = (target_datetime or datetime.now(timezone.utc)).astimezone(\n        timezone.utc\n    )\n\n    if target_datetime < datetime(2022, 1, 1, tzinfo=timezone.utc):\n        return fetch_production_esett(zone_key, session, target_datetime, logger)\n    else:\n        return fetch_production_enstoe(zone_key, session, target_datetime, logger)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/SEAPA.py",
    "content": "from datetime import datetime, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER_NAME = \"SEAPA.py\"\n\nSOURCE = \"seapahydro.org\"\nDATA_URL = \"https://seapahydro.org/api/scada/index\"\n\n\ndef get_value(data: dict, key: str) -> float:\n    return float(data[key][\"text\"])\n\n\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER_NAME, \"This parser is not yet able to parse past dates\", zone_key\n        )\n\n    res = session.get(DATA_URL)\n    data = res.json()\n\n    data = {\n        \"seapa_total\": get_value(data, \"ss_mw\"),  # 2 hydro plants owned by SEAPA\n        \"ktn_hydro\": get_value(\n            data, \"ktn_hydro_mw\"\n        ),  # hydro from pre-existing Ketchikan plants\n        \"ktn_diesel\": get_value(data, \"ktn_diesel_mw\"),  # backup Ketchikan diesel\n    }\n\n    production_mix = ProductionMix(oil=data[\"ktn_diesel\"])\n    production_mix.add_value(\"hydro\", data[\"seapa_total\"], True)\n    production_mix.add_value(\"hydro\", data[\"ktn_hydro\"], True)\n\n    production_list = ProductionBreakdownList(logger=logger)\n    production_list.append(\n        zoneKey=zone_key,\n        datetime=datetime.now(timezone.utc),\n        production=production_mix,\n        source=SOURCE,\n    )\n\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Maps backend, but handy for testing.\"\"\"\n\n    print(fetch_production(ZoneKey(\"US-AK-SEAPA\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/SG.py",
    "content": "#!/usr/bin/env python3\n\nimport re\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom PIL import Image, ImageOps\nfrom pytesseract import image_to_string\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    PriceList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\n\nTIMEZONE = ZoneInfo(\"Asia/Singapore\")\n\nTICKER_URL = \"https://www.emcsg.com/ChartServer/blue/ticker\"\n\nSOLAR_URL = (\n    \"https://www.ema.gov.sg//content/dam/corporate/solar-irradiance-map/plot.png\"\n)\n\n\"\"\"\nAround 95% of Singapore's generation is done with combined-cycle gas turbines.\n\nResources:\n\n- https://www.ema.gov.sg/Statistics.aspx particularly filtering by \"Generation\"\nThe most recent document at time of writing is\nhttps://www.ema.gov.sg/cmsmedia/Publications_and_Statistics/Statistics/27RSU.pdf\nIt says that between January 2016 and March 2017, non-gas monthly generation breakdown has been 0.7% to 1.4% coal,\n0.1% to 1.0% \"petroleum products\" (excluding an exceptional value of 3.9% in Nov 2016),\nand 2.7% to 3.4% \"other\", which includes among others waste-to-energy and solar.\n\n- Write-up of energy statistics in 2015 and first half of 2016:\nhttps://www.ema.gov.sg/cmsmedia/Publications_and_Statistics/Publications/SES/2016/Singapore%20Energy%20Statistics%202016.pdf\n(referred to as \"Singapore Energy Statistics 2016\" below)\nIt states among others \"In 2015, [natural gas] accounted for about 95% of fuel mix,\ncomparable with that recorded in 2014. Petroleum products, mainly in the form of diesel and fuel oil,\nmade up 0.7% of the fuel mix. Other energy products (e.g. municipal waste, coal and biomass)\naccounted for 2.9% while the remaining 1.2% was from coal\", and that steam turbines in Singapore\n\"typically run on fuel oil and diesel'\n\nThe real-time information on EMCSG website includes data for three categories: \"CCGT/COGEN/TRIGEN\", \"GT\", and \"ST\".\nI take these to mean combined-cycle gas turbines/co-generation/tri-generation,\nsingle-cycle gas turbines (following the Energy Statistics 2016 pg 24), and steam turbines respectively.\nThere is no real-time information on fuel for steam turbines.\n\nFor Electricity Map, we map CCGT and GT to gas, and ST to \"unknown\".\n\nThe Energy Market Authority estimates current solar production and publishes it at\nhttps://www.ema.gov.sg/solarmap.aspx\n\nThere exists an interconnection to Malaysia, it is implemented in MY_WM.py.\n\"\"\"\n\nTYPE_MAPPINGS = {\"CCGT/COGEN/TRIGEN\": \"gas\", \"GT\": \"gas\", \"ST\": \"unknown\"}\n\n\ndef get_solar(session: Session, logger: Logger) -> float | None:\n    \"\"\"\n    Fetches a graphic showing estimated solar production data.\n    Uses OCR (tesseract) to extract MW value.\n    \"\"\"\n    requests_obj = session or Session()\n    requests_obj.headers.update({\"User-Agent\": \"Mozilla/5.0\"})\n    solar_image = Image.open(session.get(SOLAR_URL, stream=True).raw)\n\n    solar_mw = __detect_output_from_solar_image(solar_image, logger)\n    solar_dt = __detect_datetime_from_solar_image(solar_image, logger)\n\n    singapore_dt = datetime.now(tz=TIMEZONE)\n    diff = singapore_dt - solar_dt\n\n    # Need to be sure we don't get old data if image stops updating.\n    if diff.total_seconds() > 3600:\n        msg = f\"Singapore solar data is too old to use, parsed data timestamp was {solar_dt}.\"\n        logger.warning(msg, extra={\"key\": \"SG\"})\n        return None\n\n    return solar_mw\n\n\ndef parse_megawatt_value(val) -> int:\n    \"\"\"Turns values like \"5,156MW\" and \"26MW\" into 5156 and 26 respectively.\"\"\"\n    return int(val.replace(\",\", \"\").replace(\"MW\", \"\"))\n\n\ndef parse_percent(val) -> float:\n    \"\"\"Turns values like \"97.92%\" into 0.9792.\"\"\"\n    return float(val.replace(\"%\", \"\")) / 100\n\n\ndef parse_price(price_str) -> float:\n    \"\"\"Turns values like \"$70.57/MWh\" into 70.57\"\"\"\n\n    return float(price_str.replace(\"$\", \"\").replace(\"/MWh\", \"\"))\n\n\ndef find_first_list_item_by_key_value(\n    section_list: list, filter_key, filter_value, sought_key\n):\n    \"\"\"\n    Parses a common pattern in Singapore JSON response format. Examples:\n\n    [d['Value'] for d in energy_section if d['Label'] == 'Demand'][0]\n        => find_first_list_item_by_key_value(energy_section, 'Label', 'Demand', 'Value')\n\n    [section['SectionData'] for section in sections if section['Name'] == 'Energy'][0]\n        => find_first_list_item_by_key_value(sections, 'Name', 'Energy', 'SectionData')\n\n    [d['Value'] for d in energy_section if d['Label'] == 'USEP'][0]\n        => find_first_list_item_by_key_value(energy_section, 'Label', 'USEP', 'Value')\n    \"\"\"\n\n    return [\n        list_item[sought_key]\n        for list_item in section_list\n        if list_item[filter_key] == filter_value\n    ][0]\n\n\ndef sg_period_to_hour(period_str) -> float:\n    \"\"\"\n    Singapore electricity markets are split into 48 periods.\n    Period 1 starts at 00:00 Singapore time, Period 9 starts at 04:00.\n    Returns hours since midnight, possibly with 0.5 to indicate 30 minutes.\n    \"\"\"\n    return (float(period_str) - 1) / 2.0\n\n\ndef sg_data_to_datetime(data):\n    data_date = data[\"Date\"]\n    data_time = sg_period_to_hour(data[\"Period\"])\n    data_datetime = datetime.strptime(data_date, \"%d %b %Y\").replace(\n        tzinfo=TIMEZONE\n    ) + timedelta(hours=data_time)\n    return data_datetime\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"SG\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of Singapore.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    requests_obj = session or Session()\n    # TODO: restore verification when source fixes configuration or we manually install their chain\n    requests_obj.verify = False\n\n    response = requests_obj.get(TICKER_URL)\n    data = response.json()\n\n    sections = data[\"Sections\"]\n\n    energy_section = find_first_list_item_by_key_value(\n        sections, \"Name\", \"Energy\", \"SectionData\"\n    )\n\n    demand_str = find_first_list_item_by_key_value(\n        energy_section, \"Label\", \"Demand\", \"Value\"\n    )\n    demand = parse_megawatt_value(demand_str)\n    system_loss_str = find_first_list_item_by_key_value(\n        energy_section, \"Label\", \"System Loss\", \"Value\"\n    )\n    system_loss = parse_megawatt_value(system_loss_str)\n\n    generation = demand + system_loss\n\n    mix_section = find_first_list_item_by_key_value(\n        sections, \"Name\", \"Generator Type Share\", \"SectionData\"\n    )\n\n    gen_types = {\n        gen_type[\"Label\"]: parse_percent(gen_type[\"Value\"]) for gen_type in mix_section\n    }\n\n    production_breakdowns = ProductionBreakdownList(logger)\n    mix = ProductionMix()\n    for gen_type, gen_percent in gen_types.items():\n        gen_mw = gen_percent * generation\n        mapped_type = TYPE_MAPPINGS.get(gen_type)\n\n        if mapped_type:\n            mix.add_value(TYPE_MAPPINGS[gen_type], gen_mw)\n\n        else:\n            # unrecognized - log it, then add into unknown\n            msg = (\n                f'Singapore has unrecognized generation type \"{gen_type}\" '\n                f\"with production share {gen_percent}%\"\n            )\n            logger.warning(msg)\n            mix.add_value(\"unknown\", gen_mw)\n\n    mix.add_value(\"solar\", get_solar(requests_obj, logger))\n\n    production_breakdowns.append(\n        datetime=sg_data_to_datetime(data),\n        zoneKey=zone_key,\n        production=mix,\n        storage=None,\n        source=\"emcsg.com, ema.gov.sg\",\n    )\n    return production_breakdowns.to_list()\n\n\ndef fetch_price(\n    zone_key: ZoneKey = ZoneKey(\"SG\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Requests the most recent known power prices in Singapore (USEP).\n\n    See https://www.emcsg.com/marketdata/guidetoprices for details of what different prices in the data source mean.\n    We use USEP here: \"The Uniform Singapore Energy Price (USEP) is the uniform price of energy\n    that applies for settlement purposes for all energy injections or withdrawals that are deemed to occur\n    at the Singapore hub. It is the weighted-average of the nodal prices at all off-take nodes in each half hour.\"\n\n    There are also price forecasts for future prices at https://www.emcsg.com/marketdata/priceinformation\n    that appears to extend to end of day in Singapore, so up to 24 hours into the future,\n    however we don't currently use this.\n    \"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    requests_obj = session or Session()\n    # TODO: restore verification when source fixes configuration or we manually install their chain\n    requests_obj.verify = False\n    response = requests_obj.get(TICKER_URL)\n    data = response.json()\n\n    sections = data[\"Sections\"]\n\n    energy_section = find_first_list_item_by_key_value(\n        sections, \"Name\", \"Energy\", \"SectionData\"\n    )\n\n    price_str = find_first_list_item_by_key_value(\n        energy_section, \"Label\", \"USEP\", \"Value\"\n    )\n    price = parse_price(price_str)\n    price_list = PriceList(logger)\n    price_list.append(\n        zoneKey=zone_key,\n        datetime=sg_data_to_datetime(data),\n        currency=\"SGD\",\n        price=price,\n        source=\"emcsg.com\",\n    )\n    return price_list.to_list()\n\n\ndef __detect_datetime_from_solar_image(solar_image, logger: Logger):\n    w, h = solar_image.size\n    crop_left = int(w * 0.64)\n    crop_top = int(h * 0.80)\n    crop_right = int(w * 0.87)\n    crop_bottom = int(h * 0.86)\n    time_img = solar_image.crop((crop_left, crop_top, crop_right, crop_bottom))\n    processed_img = __preprocess_image_for_ocr(time_img)\n    text = image_to_string(\n        processed_img,\n        lang=\"eng\",\n        config='--psm 7 -c tessedit_char_whitelist=\"0123456789:- \"',\n    )\n\n    try:\n        time_pattern = r\"\\d+-\\d+-\\d+\\s+\\d+:\\d+\"\n        time_string = re.search(time_pattern, text, re.MULTILINE).group(0)\n    except AttributeError:\n        msg = f\"Unable to get values for SG solar from OCR text: {text}\"\n        logger.warning(msg, extra={\"key\": \"SG\"})\n        return None\n\n    solar_dt = datetime.fromisoformat(time_string).replace(tzinfo=TIMEZONE)\n    return solar_dt\n\n\ndef __detect_output_from_solar_image(solar_image, logger: Logger):\n    w, h = solar_image.size\n    crop_left = int(w * 0.55)\n    crop_top = int(h * 0.70)\n    crop_right = int(w * 0.87)\n    crop_bottom = int(h * 0.75)\n    output_img = solar_image.crop((crop_left, crop_top, crop_right, crop_bottom))\n    processed_img = __preprocess_image_for_ocr(output_img)\n    text = image_to_string(processed_img, lang=\"eng\", config=\"--psm 7\")\n\n    try:\n        pattern = r\"Est. PV Output: (.*)MWac\"\n        val = re.search(pattern, text, re.MULTILINE).group(1)\n    except AttributeError:\n        msg = f\"Unable to get values for SG solar from OCR text: {text}\"\n        logger.warning(msg, extra={\"key\": \"SG\"})\n        return None\n\n    # At night format changes from 0.00 to 0\n    # tesseract cannot distinguish singular 0 and O in font provided by image.\n    # This try/except will make sure no invalid data is returned.\n    try:\n        solar_mw = float(val)\n    except ValueError:\n        if val == \"O\":\n            solar_mw = 0.0\n        else:\n            msg = f\"Singapore solar data is unreadable - got {val}.\"\n            logger.warning(msg, extra={\"key\": \"SG\"})\n            return None\n\n    return solar_mw\n\n\ndef __preprocess_image_for_ocr(img):\n    \"\"\"\n    Perform a number of image pre-processing recommendations to improve success of character recognition.\n\n    :param img: the image to be processed\n    :return: pre-processed image, optimized for optical character recognition (OCR)\n    \"\"\"\n    # https://tesseract-ocr.github.io/tessdoc/ImproveQuality#inverting-images\n    inverted_img = ImageOps.invert(\n        img.convert(\"RGB\")  # Mode P not supported yet, so we convert to RGB\n    )  # assumes black background of Singapore solar output image\n    gray_text_on_light_bg = ImageOps.grayscale(inverted_img)\n    black_text_on_light_bg = ImageOps.autocontrast(gray_text_on_light_bg)\n\n    # https://tesseract-ocr.github.io/tessdoc/ImproveQuality#missing-borders\n    img_with_border = ImageOps.expand(black_text_on_light_bg, border=2)\n    return img_with_border\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print('fetch_price(\"SG\") ->')\n    print(fetch_price(\"SG\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/SMARTGRIDDASHBOARD.py",
    "content": "from datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom operator import itemgetter\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n    TotalProductionList,\n)\nfrom electricitymap.contrib.lib.models.events import EventSourceType, ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nIE_TZ = ZoneInfo(\"Europe/Dublin\")\nURL = \"https://www.smartgriddashboard.com/api/chart\"\n\nSOURCE = \"eirgridgroup.com\"\n\nKINDS_AREA_MAPPING = {\n    \"demand\": \"demandactual\",\n    \"demand_forecast\": \"demandforecast\",\n    \"wind\": \"windactual\",\n    \"wind_forecast\": \"windforecast\",\n    \"exchange\": \"interconnection\",\n    \"generation\": \"generationactual\",\n    \"solar\": \"solaractual\",\n    \"solar_forecast\": \"solarforecast\",\n}\n\nREGION_MAPPING = {\n    \"IE\": \"ROI\",\n    \"GB-NIR\": \"NI\",\n}\n\nEXCHANGE_MAPPING = {\n    ZoneKey(\"GB->IE\"): {\n        \"key\": \"ROI\",\n        \"exchange\": [\"INTER_EWIC\", \"INTER_GRNLK\"],\n        \"direction\": 1,\n    },\n    ZoneKey(\"GB->GB-NIR\"): {\"key\": \"NI\", \"exchange\": [\"INTER_MOYLE\"], \"direction\": 1},\n}\n\n\ndef get_datetime_params(datetime: datetime) -> dict:\n    return {\n        \"datefrom\": (datetime - timedelta(days=2)).strftime(\"%Y-%m-%d\"),\n        \"dateto\": (datetime + timedelta(days=1)).strftime(\"%Y-%m-%d\"),\n    }\n\n\ndef parse_datetime(datetime_str: str) -> datetime:\n    return datetime.strptime(datetime_str, \"%d-%b-%Y %H:%M:%S\").replace(tzinfo=IE_TZ)\n\n\ndef fetch_data(\n    target_datetime: datetime,\n    zone_key: ZoneKey,\n    kind: str,\n    session: Session,\n) -> list:\n    \"\"\"\n    Gets values and corresponding datetimes for the specified data kind in ROI.\n    Removes any values that are in the future or don't have a datetime associated with them.\n    \"\"\"\n    assert isinstance(target_datetime, datetime)\n    assert kind != \"\"\n    assert session is not None\n\n    resp: Response = session.get(\n        url=URL,\n        params={\n            \"areas\": KINDS_AREA_MAPPING[kind],\n            \"chartType\": \"default\",\n            \"region\": EXCHANGE_MAPPING[zone_key][\"key\"]\n            if zone_key in EXCHANGE_MAPPING\n            else REGION_MAPPING[zone_key],\n            \"dateRange\": \"day\",\n            **get_datetime_params(target_datetime),\n        },\n    )\n    try:\n        data = resp.json().get(\"Rows\", [])\n    except Exception as e:\n        raise ParserException(\n            parser=\"SMARTGRIDDASHBOARD.py\",\n            message=f\"{target_datetime}: {kind} data is not available for {zone_key}\",\n        ) from e\n    return data\n\n\ndef parse_consumption(\n    zone_key: ZoneKey,\n    session: Session | None,\n    target_datetime: datetime | None,\n    logger: Logger,\n    forecast: bool,\n) -> list:\n    \"\"\"gets forecasted consumption values for ROI\"\"\"\n\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=IE_TZ)\n\n    data = fetch_data(\n        target_datetime=target_datetime,\n        zone_key=zone_key,\n        kind=\"demand_forecast\" if forecast else \"demand\",\n        session=session,\n    )\n\n    demandList = TotalConsumptionList(logger=logger)\n    for item in data:\n        dt = parse_datetime(item[\"EffectiveTime\"])\n        # when fetching real-time data we remove future values\n        if not forecast:\n            now = datetime.now(tz=IE_TZ)\n            # datetimes in the future are expected to be None\n            if dt > now:\n                continue\n\n        demandList.append(\n            zoneKey=zone_key,\n            consumption=item[\"Value\"],\n            datetime=dt,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted\n            if forecast\n            else EventSourceType.measured,\n        )\n    return demandList.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Gets values for wind production and estimates unknwon production as demand - wind - exchange\"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=IE_TZ)\n\n    total_generation = fetch_data(\n        target_datetime=target_datetime,\n        zone_key=zone_key,\n        kind=\"generation\",\n        session=session,\n    )\n\n    wind_data = fetch_data(\n        target_datetime=target_datetime, zone_key=zone_key, kind=\"wind\", session=session\n    )\n\n    solar_data = fetch_data(\n        target_datetime=target_datetime,\n        zone_key=zone_key,\n        kind=\"solar\",\n        session=session,\n    )\n\n    assert len(total_generation) > 0\n    assert len(wind_data) > 0\n    assert len(solar_data) > 0\n\n    # sort by time\n    total_generation.sort(key=itemgetter(\"EffectiveTime\"))\n    wind_data.sort(key=itemgetter(\"EffectiveTime\"))\n    solar_data.sort(key=itemgetter(\"EffectiveTime\"))\n\n    production = ProductionBreakdownList(logger=logger)\n\n    for total, wind, solar in zip(total_generation, wind_data, solar_data, strict=True):\n        dt = parse_datetime(total[\"EffectiveTime\"])\n        dt_wind = parse_datetime(wind[\"EffectiveTime\"])\n        dt_solar = parse_datetime(solar[\"EffectiveTime\"])\n\n        assert dt == dt_wind == dt_solar\n\n        now = datetime.now(tz=IE_TZ)\n        # datetimes in the future are expected to be None\n        if dt > now:\n            continue\n\n        total_prod = total.get(\"Value\")\n        wind_prod = wind.get(\"Value\")\n        solar_prod = solar.get(\"Value\")\n\n        productionMix = ProductionMix()\n        if all([total_prod is not None, wind_prod is not None, solar_prod is not None]):\n            productionMix.add_value(\n                \"unknown\",\n                total_prod - wind_prod - solar_prod,\n            )\n            productionMix.add_value(\"wind\", wind_prod, correct_negative_with_zero=True)\n            productionMix.add_value(\n                \"solar\", solar_prod, correct_negative_with_zero=True\n            )\n\n        production.append(\n            zoneKey=zone_key,\n            production=productionMix,\n            datetime=dt,\n            source=SOURCE,\n        )\n\n    return production.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Fetches exchanges values for the East-West (GB->IE) and Moyle (GB->GB-NIR)\n    interconnectors.\n    \"\"\"\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=IE_TZ)\n\n    exchangeKey = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    if exchangeKey == \"GB-NIR->IE\":\n        raise ParserException(\n            parser=\"SMARTGRIDDASHBOARD.py\",\n            message=\"the GB-NIR_IE interconnection is unsupported.\",\n        )\n\n    exchange_data = fetch_data(\n        target_datetime=target_datetime,\n        zone_key=exchangeKey,\n        kind=\"exchange\",\n        session=session,\n    )\n\n    exchange_mapping = EXCHANGE_MAPPING[exchangeKey]\n    exchanges = {x: ExchangeList(logger=logger) for x in exchange_mapping[\"exchange\"]}\n\n    for exchange in exchange_data:\n        target_exchange = exchanges.get(exchange[\"FieldName\"])\n        if target_exchange is None:\n            continue\n\n        dt = parse_datetime(exchange[\"EffectiveTime\"])\n        now = datetime.now(tz=IE_TZ)\n        # datetimes in the future are expected to be None\n        if dt > now:\n            continue\n\n        flow = (\n            exchange[\"Value\"] * exchange_mapping[\"direction\"]\n            if exchange[\"Value\"]\n            else exchange[\"Value\"]\n        )\n\n        target_exchange.append(\n            zoneKey=exchangeKey,\n            netFlow=flow,\n            datetime=parse_datetime(exchange[\"EffectiveTime\"]),\n            source=SOURCE,\n        )\n\n    return ExchangeList.merge_exchanges(exchanges.values(), logger=logger).to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"gets consumption values for ROI\"\"\"\n    return parse_consumption(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n        forecast=False,\n    )\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"gets forecasted consumption values for ROI\"\"\"\n    return parse_consumption(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=target_datetime,\n        logger=logger,\n        forecast=True,\n    )\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Gets values and corresponding datetimes for forecasted wind produciton.\n    \"\"\"\n\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=IE_TZ)\n\n    wind_forecast_data = fetch_data(\n        target_datetime=target_datetime,\n        zone_key=zone_key,\n        kind=\"wind_forecast\",\n        session=session,\n    )\n\n    wind_forecast = ProductionBreakdownList(logger=logger)\n    for item in wind_forecast_data:\n        productionMix = ProductionMix()\n        productionMix.add_value(\"wind\", item[\"Value\"], correct_negative_with_zero=True)\n        wind_forecast.append(\n            zoneKey=zone_key,\n            production=productionMix,\n            datetime=parse_datetime(item[\"EffectiveTime\"]),\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n\n    solar_forecast_data = fetch_data(\n        target_datetime=target_datetime,\n        zone_key=zone_key,\n        kind=\"solar_forecast\",\n        session=session,\n    )\n\n    solar_forecast = ProductionBreakdownList(logger=logger)\n    for item in solar_forecast_data:\n        productionMix = ProductionMix()\n        productionMix.add_value(\"solar\", item[\"Value\"], correct_negative_with_zero=True)\n        solar_forecast.append(\n            zoneKey=zone_key,\n            production=productionMix,\n            datetime=parse_datetime(item[\"EffectiveTime\"]),\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n\n    return ProductionBreakdownList.merge_production_breakdowns(\n        [wind_forecast, solar_forecast], logger=logger\n    ).to_list()\n\n\ndef fetch_total_generation(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"\n    Gets values and corresponding datetimes for the total generation.\n    This is the sum of all generation reported as a single value.\n    \"\"\"\n\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=IE_TZ)\n\n    generation_data = fetch_data(\n        target_datetime=target_datetime,\n        zone_key=zone_key,\n        kind=\"generation\",\n        session=session,\n    )\n    total_generation = TotalProductionList(logger=logger)\n    for item in generation_data:\n        total_generation.append(\n            zoneKey=zone_key,\n            value=item[\"Value\"],\n            datetime=parse_datetime(item[\"EffectiveTime\"]),\n            source=SOURCE,\n            sourceType=EventSourceType.measured,\n        )\n    return total_generation.to_list()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/TAIPOWER.py",
    "content": "#!/usr/bin/env python3\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\nSOURCE = \"taipower.com.tw\"\nTIMEZONE = ZoneInfo(\"Asia/Taipei\")\nPRODUCTION_URL = (\n    \"http://www.taipower.com.tw/d006/loadGraph/loadGraph/data/genary_eng.json\"\n)\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: str = \"TW\",\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    response = session.get(PRODUCTION_URL)\n    if not response.status_code == 200:\n        raise ParserException(\n            \"TW\",\n            f\"Query failed with status code {response.status_code} and {response.content}\",\n        )\n\n    data = response.json()\n\n    dt = data[\"\"]\n    prodData = data[\"dataset\"]\n\n    dt = datetime.strptime(dt, \"%Y-%m-%d %H:%M\").replace(tzinfo=TIMEZONE)\n\n    objData = pd.DataFrame(prodData)\n\n    columns = [\n        \"fueltype\",\n        \"additional_1\",\n        \"name\",\n        \"capacity\",\n        \"output\",\n        \"percentage\",\n        \"additional_2\",\n        \"additional_3\",\n    ]\n    assert len(objData.iloc[0]) == len(columns), \"number of input columns changed\"\n    objData.columns = columns\n    objData[\"fueltype\"] = objData.fueltype.str.split(\"<b>\").str[1]\n    objData[\"fueltype\"] = objData.fueltype.str.split(\"</b>\").str[0]\n    objData.loc[:, [\"capacity\", \"output\"]] = objData[[\"capacity\", \"output\"]].apply(\n        pd.to_numeric, errors=\"coerce\"\n    )\n    if objData[\"fueltype\"].str.contains(\"OTHERRENEWABLEENERGY\").any():\n        if objData[\"name\"].str.contains(\"Geothermal\").any():\n            objData.loc[objData[\"name\"].str.contains(\"Geothermal\"), \"fueltype\"] = (\n                \"Geothermal\"\n            )\n        if objData[\"name\"].str.contains(\"Biofuel\").any():\n            objData.loc[objData[\"name\"].str.contains(\"Biofuel\"), \"fueltype\"] = \"Biofuel\"\n    if objData[\"fueltype\"].str.contains(\"ENERGYSTORAGESYSTEM\").any():\n        if objData[\"additional_1\"].str.contains(\"Pumped Hydro\").any():\n            objData.loc[\n                objData[\"additional_1\"].str.contains(\"Pumped Hydro\"), \"fueltype\"\n            ] = \"HYDRO_DISCHARGE\"\n        if objData[\"additional_1\"].str.contains(\"Battery\").any():\n            objData.loc[objData[\"additional_1\"].str.contains(\"Battery\"), \"fueltype\"] = (\n                \"BATTERY_DISCHARGE\"\n            )\n\n    # For the load we need to invert the sign\n    # to be consistent with the rest of the parsers\n    if objData[\"fueltype\"].str.contains(\"ENERGYSTORAGESYSTEMLOAD\").any():\n        if objData[\"additional_1\"].str.contains(\"Pumped Hydro\").any():\n            pumped_hydro_mask = objData[\"additional_1\"].str.contains(\"Pumped Hydro\")\n            objData.loc[pumped_hydro_mask, \"fueltype\"] = \"HYDRO_PUMPING\"\n            # Invert the sign for pumped hydro load\n            objData.loc[pumped_hydro_mask, \"output\"] = -objData.loc[\n                pumped_hydro_mask, \"output\"\n            ]\n        if objData[\"additional_1\"].str.contains(\"Battery\").any():\n            battery_mask = objData[\"additional_1\"].str.contains(\"Battery\")\n            objData.loc[battery_mask, \"fueltype\"] = \"BATTERY_CHARGING\"\n\n            objData.loc[battery_mask, \"output\"] = -objData.loc[battery_mask, \"output\"]\n\n    assert not objData.capacity.isna().all(), (\n        \"capacity data is entirely NaN - input column order may have changed\"\n    )\n    assert not objData.output.isna().all(), (\n        \"output data is entirely NaN - input column order may have changed\"\n    )\n\n    objData.drop(\n        columns=[\"additional_1\", \"name\", \"additional_2\", \"percentage\", \"additional_3\"],\n        axis=1,\n        inplace=True,\n    )\n    # summing because items in returned object are for each power plant and operational units\n    production = pd.DataFrame(objData.groupby(\"fueltype\").sum())\n    production.columns = [\"capacity\", \"output\"]\n\n    # check output values coincide with total capacity by fuel type\n    check_values = production.output <= production.capacity\n    modes_with_capacity_exceeded = production[~check_values].index.tolist()\n    for mode in modes_with_capacity_exceeded:\n        logger.warning(f\"Capacity exceeded for {mode} in {zone_key} at {dt}\")\n\n    # For storage, note that load will be negative, and generation positive.\n    # We require the opposite\n    PRODUCTION_MODE_MAPPING = {\n        \"biomass\": [\"Biofuel\"],\n        \"coal\": [\"COAL\", \"IPPCOAL\"],\n        \"gas\": [\"LNG\", \"IPPLNG\"],\n        \"geothermal\": [\"Geothermal\"],\n        \"oil\": [\"OIL\", \"DIESEL\"],\n        \"hydro\": [\"HYDRO\"],\n        \"nuclear\": [\"NUCLEAR\"],\n        \"solar\": [\"SOLAR\"],\n        \"wind\": [\"WIND\"],\n        \"unknown\": [\"COGEN\"],\n    }\n    STORAGE_MODE_MAPPING = {\n        \"hydro\": [\"HYDRO_PUMPING\", \"HYDRO_DISCHARGE\"],\n        \"battery\": [\"BATTERY_CHARGING\", \"BATTERY_DISCHARGE\"],\n    }\n\n    production_breakdown = ProductionBreakdownList(logger)\n    production_mix = ProductionMix()\n    for mode, parser_modes in PRODUCTION_MODE_MAPPING.items():\n        parser_modes_in_df = [\n            parser_mode\n            for parser_mode in parser_modes\n            if parser_mode in production.index\n        ]\n        production_mix.add_value(\n            mode,\n            production.loc[parser_modes_in_df].output.sum(),\n        )\n    storage_mix = StorageMix()\n    for mode, storage_modes in STORAGE_MODE_MAPPING.items():\n        storage_modes_in_df = [\n            storage_mode\n            for storage_mode in storage_modes\n            if storage_mode in production.index\n        ]\n        storage_mix.add_value(\n            mode,\n            -1 * production.loc[storage_modes_in_df].output.sum(),\n        )\n    production_breakdown.append(\n        zone_key,\n        dt,\n        SOURCE,\n        production_mix,\n        storage_mix,\n    )\n\n    capacity = {}\n    for mode, parser_modes in PRODUCTION_MODE_MAPPING.items():\n        parser_modes_in_df = [\n            parser_mode\n            for parser_mode in parser_modes\n            if parser_mode in production.index\n        ]\n        capacity[mode] = production.loc[parser_modes_in_df].capacity.sum()\n\n    return [{**e, **{\"capacity\": capacity}} for e in production_breakdown.to_list()]\n\n\nif __name__ == \"__main__\":\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/TH.py",
    "content": "import json\nimport re\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    PriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency, use_proxy\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\nEGAT_GENERATION_URL = \"https://www.sothailand.com/sysgen/ws/sysgen\"\nEGAT_URL = \"www.egat.co.th\"\nMEA_BASEPRICE_URL = (\n    \"https://www.mea.or.th/en/our-services/tariff-calculation/other/-yosbxMGAjzp0\"\n)\nMEA_FT_URL = \"https://www.mea.or.th/our-services/tariff-calculation/ft/bG2m6iSUN\"\nMEA_URL = \"www.mea.or.th\"\nTZ = ZoneInfo(\"Asia/Bangkok\")\n\n\ndef _as_localtime(dt: datetime) -> datetime:\n    \"\"\"\n    If there is no datetime given, returns the current datetime with timezone.\n    Otherwise, it interprets the datetime as the representation of local time\n    since the API server supposes the local timezone instead of UTC.\n    \"\"\"\n    if dt is None:\n        return datetime.now(tz=TZ)\n    return dt.astimezone(TZ)\n\n\ndef _seconds_to_time(target_datetime: datetime, seconds_in_day: int) -> datetime:\n    \"\"\"Convert a given seconds integer to a datetime value.\"\"\"\n    today = target_datetime.replace(hour=0, minute=0, second=0, microsecond=0)\n    dt = today + timedelta(seconds=seconds_in_day)\n    return dt\n\n\ndef _fetch_data(\n    session: Session, target_datetime: datetime, data_type: str\n) -> list[dict]:\n    \"\"\"Fetch actual or planning generation data from the EGAT API endpoint.\"\"\"\n    url = f\"{EGAT_GENERATION_URL}/{data_type}\"\n    if target_datetime is None:\n        target_datetime = _as_localtime(datetime.now())\n\n    if data_type == \"actual\":\n        params = {\"name\": \"SYSTEM_GEN(MW)\", \"day\": target_datetime.strftime(\"%d-%m-%Y\")}\n    elif data_type == \"plan\":\n        params = {\"day\": target_datetime.strftime(\"%d-%m-%Y\")}\n    else:\n        raise ParserException(\"TH.py\", f\"unexpected data_type: {data_type}\", \"TZ\")\n\n    # This API returns a list of 2-elements list\n    # Example: [[0, 12345], [60, 12345.6], ...]\n    # - The first integer is the seconds number since 00:00 am (i.e. 900 == 00:15 am)\n    # - The second integer is the total generation (MW)\n    raw_text = session.post(url, data=params).text\n\n    # Fix programming error of the returned value.\n    # This API server returns a invalid string if the list is empty.\n    # e.g. {\"id\":\"\",\"name\":\"\",\"day\":\"\",\"timeStart\":0,list:[],\"count\":0}\n    raw_text = raw_text.replace(\",list:\", ',\"list\":')\n\n    raw_data = json.loads(raw_text)[\"list\"]\n\n    data = []\n    for item in raw_data:\n        # The data structure of `item` is inconsistent.\n        # If there is temperature data is available, `item` is 3-tuple.\n        # Otherwise, it returns 2-tuple. So we cannot simply iterate `raw_data`.\n        seconds_in_day = item[0]\n        generation = item[1]\n\n        dt = _seconds_to_time(target_datetime, seconds_in_day)\n        data.append(\n            {\n                \"datetime\": dt,\n                \"generation\": generation,\n            }\n        )\n\n    return data\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(country_code=\"TH\")\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"TH\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n    \"\"\"Request the last known production mix (in MW) of a given country.\"\"\"\n    data = _fetch_data(session, _as_localtime(target_datetime), \"actual\")\n\n    production_breakdowns = ProductionBreakdownList(logger)\n    for item in data:\n        # All mapped to 'unknown' because there is no available breakdown.\n        mix = ProductionMix(unknown=item[\"generation\"])\n        production_breakdowns.append(\n            zoneKey=zone_key,\n            datetime=item[\"datetime\"],\n            production=mix,\n            source=EGAT_URL,\n        )\n    return production_breakdowns.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"TH\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Gets consumption for a specified zone.\n\n    We use the same value as the production for now.\n    But it would be better to include exchanged electricity data if available.\n    \"\"\"\n    session = session or Session()\n    production_data = _fetch_data(session, _as_localtime(target_datetime), \"actual\")\n    consumptions = TotalConsumptionList(logger)\n\n    for item in production_data:\n        consumptions.append(\n            zoneKey=zone_key,\n            datetime=item[\"datetime\"],\n            consumption=item[\"generation\"],\n            source=EGAT_URL,\n        )\n    return consumptions.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_generation_forecast(\n    zone_key: ZoneKey = ZoneKey(\"TH\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Gets generation forecast for specified zone.\"\"\"\n    session = session or Session()\n    data = _fetch_data(session, _as_localtime(target_datetime), \"plan\")\n\n    production_breakdowns = ProductionBreakdownList(logger)\n    for item in data:\n        # All mapped to 'unknown' because there is no available breakdown.\n        mix = ProductionMix(unknown=item[\"generation\"])\n        production_breakdowns.append(\n            zoneKey=zone_key,\n            datetime=item[\"datetime\"],\n            production=mix,\n            source=EGAT_URL,\n        )\n    return production_breakdowns.to_list()\n\n\ndef fetch_price(\n    zone_key: ZoneKey = ZoneKey(\"TH\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    Fetch the base tariff data from the MEA (Unit in THB). This is then added up with\n    Float Time (Ft) rate from another MEA's webpage (Unit in Satang (THB/100)).\n\n    The Thai MEA/PEA Electicity Fee calculation are as follows:\n    AmountDue = (BasePrice** + FtRate) * UnitAmountInKWh\n    ActualDue = (AmountDue * 7%VAT) + FixedServiceFee\n\n    * Time-of-Use (TOU) rate is uncommon and thus left unimplemented.\n    **While actual BasePrice is done in a progressive manner, For Electricity Maps -\n      we use \"AmountDue\" at 1MWh calculated at the highest pricing bracket for simplification.\n    \"\"\"\n    session = session or Session()\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    # Fetch price from MEA table.\n    # `price_base` is 'Over 400 kWh (up from 401st)' from Table 1.1\n    with session.get(MEA_BASEPRICE_URL) as response:\n        soup_base = BeautifulSoup(response.content, \"lxml\")\n\n    if response.status_code != 200:\n        raise ParserException(\n            parser=\"TH.py\",\n            message=f\"{MEA_BASEPRICE_URL} returned {response.status_code}\",\n            zone_key=zone_key,\n        )\n\n    unit_price_table = soup_base.find_all(\"table\")[1]\n    price_base = unit_price_table.find_all(\"td\")[8].text\n\n    # Available Ft pricing history dated back as far as September 2535 B.E. (1992 C.E.)\n    # `price_ft` slot's is 0+(month number), additional +13 is needed if that slot is \" \"\n    # For 2023 multi-Ft rates, we assumed the household rate.\n    with session.get(MEA_FT_URL) as response:\n        soup_ft = BeautifulSoup(response.content, \"lxml\")\n\n    if response.status_code != 200:\n        raise ParserException(\n            parser=\"TH.py\",\n            message=f\"{MEA_FT_URL} returned {response.status_code}\",\n            zone_key=zone_key,\n        )\n\n    ft_rate_table = soup_ft.find_all(\"table\")[0]\n    curr_ft_month = _as_localtime(datetime.now()).month\n    price_ft = ft_rate_table.find_all(\"td\")[curr_ft_month].text\n\n    if price_ft == \"\\xa0\":\n        price_ft = ft_rate_table.find_all(\"td\")[curr_ft_month + 13].text\n    if \"\\n\" in price_ft:\n        price_ft = re.findall(r\"\\d+\\.\\d+\", price_ft)[0]\n    prices = PriceList(logger)\n    prices.append(\n        zoneKey=zone_key,\n        currency=\"THB\",\n        datetime=_as_localtime(\n            datetime.now().replace(\n                minute=0,\n                second=0,\n                microsecond=0,\n            )\n        ),\n        price=float(price_base) * 1000 + float(price_ft) * 10,\n        source=MEA_URL,\n    )\n    return prices.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n\n    print(\"fetch_generation_forecast() ->\")\n    print(fetch_generation_forecast())\n\n    print(\"fetch_price() ->\")\n    print(fetch_price())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/TR.py",
    "content": "#!/usr/bin/env python3\nimport json\nimport urllib.parse\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom operator import itemgetter\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    PriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency, use_proxy\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\nfrom .lib.utils import get_token\n\nTR_TZ = ZoneInfo(\"Europe/Istanbul\")\n\nEPIAS_MAIN_URL = \"https://seffaflik.epias.com.tr/electricity-service/v1\"\nKINDS_MAPPING = {\n    \"production\": {\n        \"url\": \"generation/data/realtime-generation\",\n    },\n    \"consumption\": {\n        \"url\": \"consumption/data/realtime-consumption\",\n    },\n    \"price\": {\"url\": \"markets/dam/data/mcp\"},\n}\nPRODUCTION_MAPPING = {\n    \"biomass\": [\"biomass\"],\n    \"solar\": [\"sun\"],\n    \"geothermal\": [\"geothermal\"],\n    \"oil\": [\"fueloil\", \"gasOil\", \"naphta\"],\n    \"gas\": [\"naturalGas\", \"lng\"],\n    \"wind\": [\"wind\"],\n    \"coal\": [\"blackCoal\", \"asphaltiteCoal\", \"lignite\", \"importCoal\"],\n    \"hydro\": [\"river\", \"dammedHydro\"],\n    \"nuclear\": [\"nucklear\"],\n    \"unknown\": [\"wasteheat\"],\n}\nINVERT_PRODUCTION_MAPPPING = {\n    val: mode for mode in PRODUCTION_MAPPING for val in PRODUCTION_MAPPING[mode]\n}\nIGNORED_KEYS = [\"total\", \"date\", \"importExport\", \"hour\"]\nSOURCE = \"epias.com.tr\"\n\n\ndef fetch_ticket_TGT(session: Session) -> str:\n    url = \"https://giris.epias.com.tr/cas/v1/tickets\"\n\n    TR_USERNAME = urllib.parse.quote_plus(get_token(\"TR_USERNAME\"))\n    TR_PASSWORD = urllib.parse.quote_plus(get_token(\"TR_PASSWORD\"))\n\n    payload = f\"username={TR_USERNAME}&password={TR_PASSWORD}\"\n\n    headers = {\n        \"Content-Type\": \"application/x-www-form-urlencoded\",\n        \"Accept\": \"text/plain\",\n    }\n\n    response_TGT = session.request(\"POST\", url, headers=headers, data=payload)\n\n    return response_TGT.text\n\n\ndef fetch_data(target_datetime: datetime, kind: str, session: Session) -> list:\n    TGT_ticket = fetch_ticket_TGT(session)\n    url = \"/\".join((EPIAS_MAIN_URL, KINDS_MAPPING[kind][\"url\"]))\n\n    is_last_page = False\n    pagenum = 1\n    results = []\n\n    target_datetime = target_datetime.replace(tzinfo=TR_TZ)\n    # Fetch for the last 2 days since start and end date are truncated to the day and to avoid missing last hours.\n    while not is_last_page:\n        payload = json.dumps(\n            {\n                \"startDate\": (target_datetime - timedelta(days=1)).strftime(\n                    \"%Y-%m-%dT%H:%M:%S+03:00\"\n                ),\n                \"endDate\": (target_datetime).strftime(\"%Y-%m-%dT%H:%M:%S+03:00\"),\n                \"page\": {\n                    \"number\": pagenum,\n                    \"size\": 48,\n                    \"sort\": {\"field\": \"date\", \"direction\": \"ASC\"},\n                },\n            }\n        )\n        headers = {\n            \"TGT\": TGT_ticket,\n            \"Content-Type\": \"application/json\",\n        }\n\n        r: Response = session.request(\"POST\", url, headers=headers, data=payload)\n\n        if r.status_code == 200:\n            results += r.json()[\"items\"]\n            pagenum += 1\n\n        else:\n            raise ParserException(\n                parser=\"TR.py\",\n                message=f\"{target_datetime}: {kind} data is not available for TR\",\n            )\n\n        if r.json()[\"items\"] == [] or pagenum > 20:\n            is_last_page = True\n\n    return results\n\n\n@refetch_frequency(timedelta(days=1))\n@use_proxy(\"TR\")\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"TR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n\n    # For real-time data, the last data point seems to but continously updated thoughout the hour and will be excluded as not final\n    exclude_last_data_point = False\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TR_TZ)\n        exclude_last_data_point = True\n\n    data = fetch_data(\n        target_datetime=target_datetime, kind=\"production\", session=session\n    )\n\n    # Sort the data by date\n    data = sorted(data, key=itemgetter(\"date\"))\n\n    data = data[:-1] if exclude_last_data_point else data\n\n    production_breakdowns = ProductionBreakdownList(logger)\n    for item in data:\n        mix = ProductionMix()\n        for key, value in item.items():\n            if key in INVERT_PRODUCTION_MAPPPING:\n                mix.add_value(\n                    INVERT_PRODUCTION_MAPPPING[key],\n                    value,\n                    correct_negative_with_zero=True,\n                )\n            elif key not in IGNORED_KEYS:\n                logger.warning(\"Unrecognized key '%s' in data skipped\", key)\n\n        date = str(item.get(\"date\"))\n\n        production_breakdowns.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(date)\n            if \"+\" in date\n            else datetime.fromisoformat(date).replace(tzinfo=TR_TZ),\n            production=mix,\n            source=SOURCE,\n        )\n\n    return production_breakdowns.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"TR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TR_TZ).replace(\n            hour=0, minute=0, second=0, microsecond=0\n        )\n\n    data = fetch_data(\n        target_datetime=target_datetime, kind=\"consumption\", session=session\n    )\n\n    consumptions = TotalConsumptionList(logger)\n    for item in data:\n        consumptions.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(item.get(\"date\")).replace(tzinfo=TR_TZ),\n            consumption=item.get(\"consumption\"),\n            source=SOURCE,\n        )\n\n    return consumptions.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_price(\n    zone_key: ZoneKey = ZoneKey(\"TR\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TR_TZ)\n\n    data = fetch_data(target_datetime=target_datetime, kind=\"price\", session=session)\n    prices = PriceList(logger)\n    for item in data:\n        prices.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(item.get(\"date\")).replace(tzinfo=TR_TZ),\n            price=item.get(\"price\"),\n            source=SOURCE,\n            currency=\"TRY\",\n        )\n\n    return prices.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_price() ->\")\n    print(fetch_price())\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/UA.py",
    "content": "#!/usr/bin/env python3\n\nimport http.client\nimport json\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.types import ZoneKey\n\n\"\"\"\ntec - same as `tes` but also working as central heater,\n      main fuel is gas, in critical situations - black oil\ngesgaes - hydro run of river and poundage\nconsumptiongaespump - hydro pumped storage\nvde - renewable sources - mostly wind at nighttimes and solar peaks during the day\n\n\"\"\"\nMAP_GENERATION = {\n    \"aes\": \"nuclear\",\n    \"tec\": \"gas\",\n    \"tes\": \"coal\",\n    \"vde\": \"unknown\",\n    \"gesgaes\": \"hydro\",\n}\n\nMAP_STORAGE = {\n    \"consumptiongaespump\": \"hydro\",\n}\n\nIGNORED_VALUES = [\"hour\", \"consumption\", \"consumption_diff\"]\n\nSOURCE = \"ua.energy\"\n\nTZ = ZoneInfo(\"Europe/Kiev\")\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"UA\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    if target_datetime:\n        target_datetime = target_datetime.astimezone(TZ)\n    else:\n        target_datetime = datetime.now(TZ)\n\n    # We are using HTTP.client because Request returns 403 http codes.\n    # TODO: Look into why requests are returning 403 http codes while HTTP.client works.\n    conn = http.client.HTTPSConnection(\"ua.energy\")\n    payload = f\"action=get_data_oes&report_date={target_datetime.date().strftime('%d.%m.%Y')}&type=day\"\n    headers = {\n        \"Content-Type\": \"application/x-www-form-urlencoded\",\n        \"User-Agent\": \"PostmanRuntime/7.32.3\",\n    }\n    conn.request(\"POST\", \"/wp-admin/admin-ajax.php\", payload, headers)\n    res = conn.getresponse()\n    response = json.loads(res.read().decode(\"utf-8\"))\n\n    production_list = ProductionBreakdownList(logger)\n\n    for serie in response:\n        production = ProductionMix()\n        storage = StorageMix()\n\n        for mode in serie:\n            # Production\n            if mode in MAP_GENERATION:\n                production.add_value(MAP_GENERATION[mode], serie[mode])\n            # Storage\n            elif mode in MAP_STORAGE:\n                storage.add_value(MAP_STORAGE[mode], -serie[mode])\n            # Log unknown modes\n            elif mode not in IGNORED_VALUES:\n                logger.warning(f\"Unknown mode: {mode}\")\n\n        # Date\n        # For some reason, every hour returned normally as string, except for 12 AM\n        if serie[\"hour\"] == 24:\n            target_datetime = target_datetime + timedelta(days=1)\n            serie[\"hour\"] = \"00:00\"\n\n        date_time = target_datetime.replace(\n            hour=int(serie[\"hour\"][:2]), minute=0, second=0, microsecond=0\n        )\n\n        production_list.append(\n            zoneKey=zone_key,\n            production=production,\n            storage=storage,\n            datetime=date_time,\n            source=SOURCE,\n        )\n\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/US_CA.py",
    "content": "#!/usr/bin/env python3\n\nimport io\nimport math\nimport zipfile\nfrom datetime import datetime, timedelta, timezone\nfrom enum import Enum\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.types import ZoneKey\n\nCAISO_PROXY = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app\"\nPRODUCTION_URL_REAL_TIME = (\n    f\"{CAISO_PROXY}/outlook/current/fuelsource.csv?host=https://www.caiso.com\"\n)\nDEMAND_URL_REAL_TIME = (\n    f\"{CAISO_PROXY}/outlook/current/netdemand.csv?host=https://www.caiso.com\"\n)\n\nHISTORICAL_URL_MAPPING = {\"production\": \"fuelsource\", \"consumption\": \"netdemand\"}\nREAL_TIME_URL_MAPPING = {\n    \"production\": PRODUCTION_URL_REAL_TIME,\n    \"consumption\": DEMAND_URL_REAL_TIME,\n}\nPRODUCTION_MODES_MAPPING = {\n    \"solar\": \"solar\",\n    \"wind\": \"wind\",\n    \"geothermal\": \"geothermal\",\n    \"biomass\": \"biomass\",\n    \"biogas\": \"biomass\",\n    \"small hydro\": \"hydro\",\n    \"coal\": \"coal\",\n    \"nuclear\": \"nuclear\",\n    \"natural gas\": \"gas\",\n    \"large hydro\": \"hydro\",\n    \"other\": \"unknown\",\n}\n\nCORRECT_NEGATIVE_PRODUCTION_MODES_WITH_ZERO = [\n    mode\n    for mode in PRODUCTION_MODES_MAPPING\n    if mode not in [\"large hydro\", \"small hydro\"]\n]\nSTORAGE_MAPPING = {\"batteries\": \"battery\"}\n\nTIMEZONE = ZoneInfo(\"US/Pacific\")\n\n\ndef get_target_url(target_datetime: datetime | None, kind: str) -> str:\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=timezone.utc)\n        target_url = REAL_TIME_URL_MAPPING[kind]\n    else:\n        target_url = f\"{CAISO_PROXY}/outlook/history/{target_datetime.strftime('%Y%m%d')}/{HISTORICAL_URL_MAPPING[kind]}.csv?host=https://www.caiso.com\"\n    return target_url\n\n\ndef add_production_to_dict(mode: str, value: float, production_dict: dict) -> dict:\n    \"\"\"Add production to production_dict, if mode is in PRODUCTION_MODES.\"\"\"\n    if PRODUCTION_MODES_MAPPING[mode] not in production_dict:\n        production_dict[PRODUCTION_MODES_MAPPING[mode]] = value\n    else:\n        production_dict[PRODUCTION_MODES_MAPPING[mode]] += value\n    return production_dict\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"US-CAL-CISO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    target_url = get_target_url(target_datetime, kind=\"production\")\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE).replace(\n            hour=0, minute=0, second=0, microsecond=0\n        )\n\n    # Get the production from the CSV\n    csv = pd.read_csv(target_url)\n\n    # Filter out last row if timestamp is 00:00\n    df = csv.copy().iloc[:-1] if csv.iloc[-1][\"Time\"] == \"OO:OO\" else csv.copy()\n\n    # lower case column names\n    df.columns = [col.lower() for col in df.columns]\n\n    all_data_points = ProductionBreakdownList(logger)\n    for _index, row in df.iterrows():\n        production_mix = ProductionMix()\n        storage_mix = StorageMix()\n        row_datetime = target_datetime.replace(\n            hour=int(row[\"time\"][:2]), minute=int(row[\"time\"][-2:]), tzinfo=TIMEZONE\n        )\n\n        for mode in [\n            mode\n            for mode in PRODUCTION_MODES_MAPPING\n            if mode not in [\"small hydro\", \"large hydro\"]\n        ]:\n            production_value = float(row[mode])\n            production_mix.add_value(\n                PRODUCTION_MODES_MAPPING[mode],\n                production_value,\n                mode in CORRECT_NEGATIVE_PRODUCTION_MODES_WITH_ZERO,\n            )\n\n        for mode in [\"small hydro\", \"large hydro\"]:\n            production_value = float(row[mode])\n            if production_value < 0:\n                storage_mix.add_value(\"hydro\", production_value * -1)\n            else:\n                production_mix.add_value(\"hydro\", production_value)\n\n        storage_mix.add_value(\"battery\", float(row[\"batteries\"]) * -1)\n        all_data_points.append(\n            zoneKey=zone_key,\n            production=production_mix,\n            storage=storage_mix,\n            source=\"caiso.com\",\n            datetime=row_datetime,\n        )\n\n    return all_data_points.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"US-CAL-CISO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n\n    target_url = get_target_url(target_datetime, kind=\"consumption\")\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE).replace(\n            hour=0, minute=0, second=0, microsecond=0\n        )\n\n    # Get the demand from the CSV\n    csv = pd.read_csv(target_url)\n\n    # Filter out last row if timestamp is 00:00\n    df = csv.copy().iloc[:-1] if csv.iloc[-1][\"Time\"] == \"OO:OO\" else csv.copy()\n\n    all_data_points = TotalConsumptionList(logger)\n    for row in df.itertuples():\n        consumption = row._3\n        row_datetime = target_datetime.replace(\n            hour=int(row.Time[:2]), minute=int(row.Time[-2:]), tzinfo=TIMEZONE\n        )\n        if not math.isnan(consumption):\n            all_data_points.append(\n                zoneKey=zone_key,\n                consumption=consumption,\n                source=\"caiso.com\",\n                datetime=row_datetime,\n            )\n\n    return all_data_points.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict] | dict:\n    \"\"\"Requests the last known power exchange (in MW) between two zones.\"\"\"\n    sorted_zone_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    # CSV has imports to California as positive.\n    # Electricity Map expects A->B to indicate flow to B as positive.\n    # So values in CSV can be used as-is.\n    target_url = get_target_url(target_datetime, kind=\"production\")\n    csv = pd.read_csv(target_url)\n    latest_index = len(csv) - 1\n    daily_data = []\n    for i in range(0, latest_index + 1):\n        h, m = map(int, csv[\"Time\"][i].split(\":\"))\n        date = datetime.now(tz=TIMEZONE).replace(\n            hour=h, minute=m, second=0, microsecond=0\n        )\n        data = {\n            \"sortedZoneKeys\": sorted_zone_keys,\n            \"datetime\": date,\n            \"netFlow\": float(csv[\"Imports\"][i]),\n            \"source\": \"caiso.com\",\n        }\n\n        daily_data.append(data)\n\n    return daily_data\n\n\nBASE_OASIS_URL = \"http://oasis.caiso.com/oasisapi/\"\n\n\nclass OasisDatasetType(Enum):\n    FORECAST_7_DAY_AHEAD = \"load_forecast_7_day_ahead\"\n    WIND_SOLAR_FORECAST = \"wind_solar_forecast\"\n\n\ndef _generate_oasis_url(oasis_url_config, dataset_type: OasisDatasetType) -> str:\n    dataset_config = {\n        **oasis_url_config[dataset_type.value],\n    }\n    # combine kv from query and params\n    config_flat = {\n        **dataset_config[\"query\"],\n        **dataset_config[\"params\"],\n    }\n    url = (\n        BASE_OASIS_URL\n        + f\"{config_flat.pop('path')}?\"\n        + \"&\".join(\n            [f\"{k}={v}\" for k, v in config_flat.items()],\n        )\n    )\n    return url\n\n\ndef _get_oasis_data(session: Session, target_url: str) -> pd.DataFrame:\n    # Make a request to download the ZIP file and open the ZIP file in memory\n    response = session.get(target_url)\n    with zipfile.ZipFile(io.BytesIO(response.content)) as z:\n        csv_filename = z.namelist()[0]  # Get the first file in the zip\n        with z.open(csv_filename) as f:  # Read the CSV file into a pandas DataFrame\n            df = pd.read_csv(f)\n\n    return df\n\n\n@refetch_frequency(timedelta(days=7))\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey = ZoneKey(\"US-CAL-CISO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the total load forecast 7 days ahead (in MW) for a given date in hourly intervals.\"\"\"\n    session = session or Session()\n\n    # Interval of time\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=timezone.utc)\n    target_datetime_gmt = target_datetime\n    GMT_URL_SUFFIX = \"-0000\"\n    END_OFFSET = timedelta(days=7)\n    startdatetime = target_datetime_gmt.strftime(\"%Y%m%dT%H:%M\") + GMT_URL_SUFFIX\n    enddatetime = (target_datetime_gmt + END_OFFSET).strftime(\n        \"%Y%m%dT%H:%M\"\n    ) + GMT_URL_SUFFIX\n\n    # Config to obtain the url\n    oasis_config = {\n        \"load_forecast_7_day_ahead\": {\n            \"query\": {\n                \"path\": \"SingleZip\",\n                \"resultformat\": 6,\n                \"queryname\": \"SLD_FCST\",\n                \"version\": 1,\n            },\n            \"params\": {\n                \"market_run_id\": \"7DA\",\n                \"startdatetime\": startdatetime,\n                \"enddatetime\": enddatetime,\n            },\n        },\n    }\n\n    # Extract data\n    target_url = _generate_oasis_url(\n        oasis_config, OasisDatasetType.FORECAST_7_DAY_AHEAD\n    )\n    df = _get_oasis_data(session, target_url)\n\n    # Transform dataframe\n    COL_DATETIME, COL_TACAREA = \"INTERVALSTARTTIME_GMT\", \"TAC_AREA_NAME\"\n    df = df.sort_values(by=COL_DATETIME)\n    df = df[df[COL_TACAREA] == \"CA ISO-TAC\"]\n\n    # Add events\n    all_consumption_events = (\n        df.copy()\n    )  # all events with a datetime and a consumption value\n    consumption_list = TotalConsumptionList(logger)\n    for _index, event in all_consumption_events.iterrows():\n        event_datetime = datetime.fromisoformat(event[COL_DATETIME])\n        event_consumption_value = event[\"MW\"]\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=event_datetime,\n            consumption=event_consumption_value,\n            source=\"oasis.caiso.com\",\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumption_list.to_list()\n\n\n@refetch_frequency(timedelta(days=7))\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey = ZoneKey(\"US-CAL-CISO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the wind and solar forecast 7 days ahead (in MW) for a given date in hourly intervals.\"\"\"\n    session = session or Session()\n\n    # Interval of time: datetime is in GMT\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=timezone.utc)\n    target_datetime_gmt = target_datetime\n    GMT_URL_SUFFIX = \"-0000\"\n    END_OFFSET = timedelta(days=7)\n    startdatetime = target_datetime_gmt.strftime(\"%Y%m%dT%H:%M\") + GMT_URL_SUFFIX\n    enddatetime = (target_datetime_gmt + END_OFFSET).strftime(\n        \"%Y%m%dT%H:%M\"\n    ) + GMT_URL_SUFFIX\n\n    # Config to obtain the url\n    oasis_config = {\n        \"wind_solar_forecast\": {\n            \"query\": {\n                \"path\": \"SingleZip\",\n                \"resultformat\": 6,\n                \"queryname\": \"SLD_REN_FCST\",\n                \"version\": 1,\n            },\n            \"params\": {\n                \"market_run_id\": \"DAM\",\n                \"startdatetime\": startdatetime,\n                \"enddatetime\": enddatetime,\n            },\n        },\n    }\n\n    # Extract data and get the dataframe\n    target_url = _generate_oasis_url(oasis_config, OasisDatasetType.WIND_SOLAR_FORECAST)\n    df = _get_oasis_data(session, target_url)\n\n    # There are 3 trading hubs in CAISO\n    COL_DATETIME, COL_DATATYPE = \"INTERVALSTARTTIME_GMT\", \"RENEWABLE_TYPE\"\n    df = df.groupby([COL_DATETIME, COL_DATATYPE], as_index=False).sum(\n        numeric_only=True,\n    )\n    df = df.pivot(index=COL_DATETIME, columns=COL_DATATYPE, values=\"MW\")\n\n    all_production_events = (\n        df.copy()\n    )  # all events with a datetime and a production breakdown\n    production_list = ProductionBreakdownList(logger)\n    for _index, event in all_production_events.iterrows():\n        event_datetime = datetime.fromisoformat(_index)\n        production_mix = ProductionMix()\n        production_mix.add_value(\n            \"solar\", event[\"Solar\"], correct_negative_with_zero=True\n        )\n        production_mix.add_value(\"wind\", event[\"Wind\"], correct_negative_with_zero=True)\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=event_datetime,\n            production=production_mix,\n            source=\"oasis.caiso.com\",\n            sourceType=EventSourceType.forecasted,\n        )\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"Main method, not used by Electricity Map backend, but handy for testing\"\n\n    from pprint import pprint\n\n    # print(\"fetch_production() ->\")\n    # pprint(fetch_production(target_datetime=datetime(2020, 1, 20)))\n\n    # print('fetch_exchange(\"US-CA\", \"US\") ->')\n    # pprint(fetch_exchange(\"US-CA\", \"US\"))\n\n    # pprint(fetch_production(target_datetime=datetime(2023,1,20)))\n    # pprint(fetch_consumption(target_datetime=datetime(2022, 2, 22)))\n\n    # print(\"fetch_consumption_forecast() ->\")\n    pprint(fetch_consumption_forecast())\n\n    # print(\"fetch_wind_solar_forecasts() ->\")\n    # pprint(fetch_wind_solar_forecasts())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/US_ERCOT.py",
    "content": "\"\"\"Parser for the ERCOT grid area of the United States.\"\"\"\n\nimport gzip\nimport json\nimport time\nimport zipfile\nfrom datetime import datetime, timedelta\nfrom enum import Enum\nfrom io import BytesIO\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nimport requests\nfrom requests import Response, Session\n\n# import time\nimport electricitymap.contrib.parsers.EIA as EIA\nfrom electricitymap.contrib.lib.models.event_lists import (\n    LocationalMarginalPriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.utils import get_token\nfrom electricitymap.contrib.parsers.lib.validation import validate_exchange\nfrom electricitymap.contrib.types import ZoneKey\n\nSOURCE = \"ercot.com\"\nTX_TZ = ZoneInfo(\"US/Central\")\nUS_PROXY = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app\"\nHOST_PARAMETER = \"host=https://www.ercot.com\"\n\nRT_GENERATION_URL = (\n    f\"{US_PROXY}/api/1/services/read/dashboards/fuel-mix.json?{HOST_PARAMETER}\"\n)\nRT_CONSUMPTION_URL = f\"{US_PROXY}/api/1/services/read/dashboards/loadForecastVsActual.json?{HOST_PARAMETER}\"\nRT_EXCHANGE_URL = (\n    f\"{US_PROXY}/api/1/services/read/dashboards/rtsyscond.json?{HOST_PARAMETER}\"\n)\nRT_PRICES_URL = (\n    f\"{US_PROXY}/api/1/services/read/dashboards/systemWidePrices.json?{HOST_PARAMETER}\"\n)\nRT_STORAGE_URL = f\"{US_PROXY}/api/1/services/read/dashboards/energy-storage-resources.json?{HOST_PARAMETER}\"\nAUTH_URL_ERCOT = \"https://ercotb2c.b2clogin.com/ercotb2c.onmicrosoft.com/B2C_1_PUBAPI-ROPC-FLOW/oauth2/v2.0/token\"\nDAYAHEAD_LMP_URL = f\"{US_PROXY}/api/public-reports/np4-190-cd/dam_stlmnt_pnt_prices\"\nREALTIME_LMP_URL = f\"{US_PROXY}/api/public-reports/np6-788-cd/lmp_node_zone_hub\"\n\n# These links are found at https://www.ercot.com/gridinfo/generation, and should be updated as new data is released\n# HISTORICAL_GENERATION_URL = {\n#     \"2025\": f\"{US_PROXY}/files/docs/2025/02/08/IntGenbyFuel2025.xlsx?{HOST_PARAMETER}\",\n#     \"all_previous\": f\"{US_PROXY}/files/docs/2021/03/10/FuelMixReport_PreviousYears.zip?{HOST_PARAMETER}\",\n# }\nGENERATION_MAPPING = {\n    \"Coal and Lignite\": \"coal\",\n    \"Hydro\": \"hydro\",\n    \"Natural Gas\": \"gas\",\n    \"Nuclear\": \"nuclear\",\n    \"Other\": \"unknown\",\n    \"Power Storage\": \"battery\",\n    \"Solar\": \"solar\",\n    \"Wind\": \"wind\",\n    \"WSL\": \"battery\",\n    \"Biomass\": \"biomass\",\n    \"Gas\": \"gas\",\n    \"Coal\": \"coal\",\n    \"Gas-CC\": \"gas\",\n}\nEXCHANGE_MAPPING = {\"US-CENT-SWPP\": [\"dcE\", \"dcN\"], \"MX-NE\": [\"dcL\"], \"MX-NO\": [\"dcR\"]}\n\n\n# Report type IDs\nclass ReportTypeID(Enum):\n    # Wind production actual and forecast: https://www.ercot.com/mp/data-products/data-product-details?id=NP4-732-CD\n    WIND_POWER_PRODUCTION_REPORTID = 13028\n\n    # Solar production forecast: https://www.ercot.com/mp/data-products/data-product-details?id=np4-737-cd\n    SOLAR_POWER_PRODUCTION_REPORTID = 13483\n\n    # Load forecast: https://www.ercot.com/mp/data-products/data-product-details?id=np3-560-cd\n    LOAD_FORECAST_REPORTID = 12311\n\n\ndef get_data(\n    url: str,\n    session: Session | None = None,\n    headers: dict | None = None,\n    params: dict | None = None,\n):\n    \"\"\"requests ERCOT url and return json\"\"\"\n    if not session:\n        session = Session()\n\n    resp: Response = session.get(url, verify=False, headers=headers, params=params)\n    response_text = gzip.decompress(resp.content).decode(\"utf-8\")\n    data_json = json.loads(response_text)\n    return data_json\n\n\ndef parse_storage_data_live(session: Session) -> pd.DataFrame:\n    \"\"\"\n    Parse the storage data from the ERCOT API. The data is returned in 5 minute intervals.\n    \"\"\"\n    storage_data_json = get_data(url=RT_STORAGE_URL, session=session)\n    df = pd.concat(\n        [\n            pd.DataFrame(storage_data_json[\"previousDay\"][\"data\"]),\n            pd.DataFrame(storage_data_json[\"currentDay\"][\"data\"]),\n        ]\n    )\n    df[\"datetime\"] = pd.to_datetime(df[\"timestamp\"]).dt.floor(\"5min\")\n    df.rename(columns={\"netOutput\": \"battery_storage\"}, inplace=True)\n    df[\"battery_storage\"] = -df[\"battery_storage\"].astype(\n        float\n    )  # Storage is positive when charging'\n    df = df[[\"battery_storage\", \"datetime\"]].groupby(\"datetime\").mean().reset_index()\n    df.set_index(\"datetime\", inplace=True)\n    return df[[\"battery_storage\"]]\n\n\ndef fetch_live_consumption(\n    zone_key: str,\n    session: Session | None = None,\n    logger: Logger = getLogger(__name__),\n) -> TotalConsumptionList:\n    data_json = get_data(url=RT_CONSUMPTION_URL, session=session)\n    consumption_list = TotalConsumptionList(logger)\n    for key in [\"previousDay\", \"currentDay\"]:\n        data_dict = data_json[key]\n        dt = datetime.strptime(data_dict[\"dayDate\"], \"%Y-%m-%d %H:%M:%S%z\").replace(\n            tzinfo=TX_TZ\n        )\n        for item in data_dict[\"data\"]:\n            if \"systemLoad\" in item:\n                consumption_list.append(\n                    zoneKey=ZoneKey(zone_key),\n                    datetime=dt.replace(hour=item[\"hourEnding\"] - 1),\n                    consumption=item[\"systemLoad\"],\n                    source=SOURCE,\n                )\n    return consumption_list\n\n\ndef fetch_live_production(\n    zone_key: str,\n    session: Session | None = None,\n    logger: Logger = getLogger(__name__),\n) -> ProductionBreakdownList:\n    \"\"\"\n    Fetch the live production data from the ERCOT API at a 5 minute interval.\n    The data is returned in 5 minute intervals.\n    \"\"\"\n    session = session or Session()\n    gen_data_json = get_data(url=RT_GENERATION_URL, session=session)[\"data\"]\n    production_breakdowns = ProductionBreakdownList(logger)\n\n    # Process storage data first - keep at 15-minute intervals\n    df_storage = parse_storage_data_live(session)\n\n    # Process generation data\n    df_generation = process_generation_dataframe(\n        pd.concat([pd.DataFrame(gen_data_json[day]).T for day in gen_data_json])\n    )\n    if not df_storage.empty:\n        df_generation_storage = df_generation.merge(\n            df_storage, left_index=True, right_index=True, how=\"inner\"\n        )\n    else:\n        df_generation_storage = df_generation.copy()\n\n    # Round up to 2 decimals\n    df_generation_storage = df_generation_storage.round(2)\n    # Create production breakdowns for each timestamp - optimized version\n    timestamps = df_generation_storage.index\n    production_columns = [\n        col for col in df_generation_storage.columns if col != \"battery_storage\"\n    ]\n    has_storage = \"battery_storage\" in df_generation_storage.columns\n\n    # Use iloc for faster access instead of iterrows()\n    for i, timestamp in enumerate(timestamps):\n        production = ProductionMix()\n        storage = StorageMix()\n\n        # Get row data using iloc (faster than iterrows)\n        row_data = df_generation_storage.iloc[i]\n\n        # Add production values efficiently\n        for col in production_columns:\n            production.add_value(\n                col,\n                row_data[col],\n                correct_negative_with_zero=True,\n            )\n\n        # Add storage data if available\n        if has_storage:\n            storage.add_value(\"battery\", row_data[\"battery_storage\"])\n\n        # Add breakdown for each timestamp\n        production_breakdowns.append(\n            zoneKey=ZoneKey(zone_key),\n            datetime=timestamp,\n            source=SOURCE,\n            production=production,\n            storage=storage,\n        )\n\n    return production_breakdowns\n\n\n# def get_sheet_from_date(year: int, month: str, session: Session | None = None):\n#     \"\"\"Unit is MWh and not MW\"\"\"\n#     if not session:\n#         session = Session()\n\n#     if year > 2024:\n#         url = HISTORICAL_GENERATION_URL[str(year)]\n#         return pd.read_excel(url, engine=\"openpyxl\", sheet_name=month)\n#     else:\n#         url = HISTORICAL_GENERATION_URL[\"all_previous\"]\n#         response = session.get(url)\n\n#         if response.content.startswith(b\"PK\"):\n#             zip_data = BytesIO(response.content)\n#         else:\n#             try:\n#                 decompressed = gzip.decompress(response.content)\n#                 zip_data = BytesIO(decompressed)\n#             except gzip.BadGzipFile as err:\n#                 raise ValueError(\"File is neither a ZIP nor a gzipped file\") from err\n\n#         year_file = f\"IntGenbyFuel{year}.xlsx\"\n\n#         with zipfile.ZipFile(zip_data) as zf:\n#             if year_file not in zf.namelist():\n#                 raise NotImplementedError(\n#                     f\"Data for year {year} not found in historical data\"\n#                 )\n#             with zf.open(year_file) as excel_file:\n#                 return pd.read_excel(excel_file, engine=\"openpyxl\", sheet_name=month)\n\n\n# def fetch_historical_production(\n#     zone_key: ZoneKey,\n#     session: Session,\n#     target_datetime: datetime,\n#     logger: Logger = getLogger(__name__),\n# ) -> ProductionBreakdownList:\n#     if target_datetime.tzinfo is None:\n#         target_datetime = target_datetime.replace(tzinfo=timezone.utc)\n\n#     year = target_datetime.year\n#     month = target_datetime.strftime(\"%b\")\n\n#     production_breakdowns = ProductionBreakdownList(logger)\n\n#     df = get_sheet_from_date(year, month, session)\n#     df_standardized = transform_historical_production(df)\n\n#     # Process the standardized DataFrame to create ProductionBreakdown objects\n#     if df_standardized.empty:\n#         logger.warning(f\"No production data found for {year}-{month}\")\n#         return production_breakdowns\n\n#     for i, timestamp in enumerate(df_standardized.index):\n#         production = ProductionMix()\n#         storage = StorageMix()\n\n#         # Get row data using iloc (faster than iterrows)\n#         row_data = df_standardized.iloc[i]\n\n#         # Add production values efficiently\n#         for col in df_standardized.columns:\n#             production.add_value(\n#                 col,\n#                 row_data[col],\n#                 correct_negative_with_zero=True,\n#             )\n\n#         # Add storage data if available\n#         if \"battery\" in df_standardized.columns:\n#             storage.add_value(\"battery\", row_data[\"battery\"])\n\n#         # Add breakdown for each timestamp\n#         production_breakdowns.append(\n#             zoneKey=ZoneKey(zone_key),\n#             datetime=timestamp,\n#             source=SOURCE,\n#             production=production,\n#             storage=storage,\n#         )\n\n#     return production_breakdowns\n\n\ndef fetch_live_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    data_json = get_data(url=RT_EXCHANGE_URL, session=session)\n    all_data_points = []\n    sortedZoneKeys = \"->\".join(sorted([zone_key1, zone_key2]))\n    for item in data_json[\"data\"]:\n        data_point = {}\n        data_point[\"datetime\"] = datetime.fromtimestamp(\n            item[\"interval\"] / 1000\n        ).replace(second=0, tzinfo=TX_TZ)\n        data_point[\"netFlow\"] = sum(item[key] for key in EXCHANGE_MAPPING[zone_key2])\n\n        all_data_points.append(data_point)\n\n    # aggregate data points in the same minute interval\n    aggregated_data_points = []\n    for dt in sorted({item[\"datetime\"] for item in all_data_points}):\n        agg_data_point = {}\n        agg_data_point[\"datetime\"] = dt\n        values_dt = [\n            item[\"netFlow\"] for item in all_data_points if item[\"datetime\"] == dt\n        ]\n        agg_data_point[\"netFlow\"] = sum(values_dt) / len(values_dt)\n        agg_data_point[\"sortedZoneKeys\"] = sortedZoneKeys\n        agg_data_point[\"source\"] = SOURCE\n        aggregated_data_points.append(agg_data_point)\n    validated_data_points = [x for x in all_data_points if validate_exchange(x, logger)]\n    return validated_data_points\n\n\n@refetch_frequency(timedelta(days=28))  # A month\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"US-TEX-ERCO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates.\")\n\n    production = fetch_live_production(\n        zone_key=zone_key, session=session, logger=logger\n    )\n    return production.to_list()\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey = ZoneKey(\"US-TEX-ERCO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    if target_datetime is None or target_datetime >= datetime.now(tz=TX_TZ).replace(\n        hour=0, minute=0, second=0, microsecond=0\n    ) - timedelta(days=1):\n        consumption = fetch_live_consumption(\n            zone_key=zone_key, session=session, logger=logger\n        ).to_list()\n    else:\n        consumption = EIA.fetch_consumption(\n            zone_key=zone_key,\n            session=session,\n            target_datetime=target_datetime,\n            logger=logger,\n        )\n    return consumption\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    now = datetime.now(tz=TX_TZ)\n    if target_datetime is None or target_datetime >= datetime.now(tz=TX_TZ).replace(\n        hour=0, minute=0, second=0, microsecond=0\n    ):\n        target_datetime = now\n        exchanges = fetch_live_exchange(zone_key1, zone_key2, session, logger)\n\n    else:\n        exchanges = EIA.fetch_exchange(\n            zone_key1, zone_key2, session, target_datetime, logger\n        )\n    return exchanges\n\n\ndef _get_publish_date(doc):\n    return datetime.fromisoformat(doc[\"Document\"][\"PublishDate\"])\n\n\ndef _find_document_by_publish_date(documents, target_date):\n    \"\"\"\n    Find the latest document published on a specific date (ignoring time) or the latest document if no date is provided.\n\n    Args:\n        documents: List of document dictionaries\n        target_date: A datetime object representing the date to search for (ignores time), or None to find the latest document\n\n    Returns:\n        The best matching document (or None if no match is found)\n    \"\"\"\n    if target_date is None:\n        # If no target_date is provided, return the latest document\n        matching_docs = [\n            doc for doc in documents if doc[\"Document\"][\"FriendlyName\"][-3:] == \"csv\"\n        ]\n        return max(matching_docs, key=_get_publish_date, default=None)\n\n    # If target_date is provided, find documents matching the specific date\n    matching_docs = [\n        doc\n        for doc in documents\n        if doc[\"Document\"][\"FriendlyName\"][-3:] == \"csv\"\n        and datetime.fromisoformat(doc[\"Document\"][\"PublishDate\"]).date()\n        == target_date.date()\n    ]\n\n    return max(matching_docs, key=_get_publish_date, default=None)\n\n\ndef _get_dataframe_from_url(url, session, target_date):\n    response = session.get(url)\n    docs = response.json()[\"ListDocsByRptTypeRes\"][\"DocumentList\"]\n\n    doc = _find_document_by_publish_date(docs, target_date)\n    doc_id = doc[\"Document\"][\"DocID\"]\n\n    doc_url = f\"{US_PROXY}/misdownload/servlets/mirDownload?doclookupId={doc_id}&{HOST_PARAMETER}\"\n    resp: Response = session.get(doc_url)  # verify=False\n\n    # Open the ZIP file\n    with zipfile.ZipFile(BytesIO(resp.content)) as z:\n        # Extract the first file in the ZIP (assuming it contains a CSV)\n        csv_filename = z.namelist()[0]\n        with z.open(csv_filename) as f:\n            df = pd.read_csv(f)\n\n    return df\n\n\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey = ZoneKey(\"US-TEX-ERCO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests load forecast data in MW. target_datetime only date (takes the latest report on that date).\n    If target_datetime is None, it takes the latest report created\"\"\"\n    session = session or Session()\n\n    url = f\"{US_PROXY}/misapp/servlets/IceDocListJsonWS?reportTypeId={ReportTypeID.LOAD_FORECAST_REPORTID.value}&_{int(time.time())}&{HOST_PARAMETER}\"\n    df = _get_dataframe_from_url(url, session, target_datetime)\n\n    # Transfrom Hour column\n    df[\"HourStarting\"] = df[\"HourEnding\"].str.split(\":\", expand=True)[0].astype(int) - 1\n    df[\"HourStarting\"] = df[\"HourStarting\"].astype(str) + \":00\"\n\n    all_consumption_events = (\n        df.copy()\n    )  # all events with a datetime and a consumption value\n    consumption_list = TotalConsumptionList(logger)\n    for _, row in all_consumption_events.iterrows():\n        date_, time_ = row.DeliveryDate, row.HourStarting\n        datetime_object = datetime.strptime(\n            date_ + \"T\" + time_, \"%m/%d/%YT%H:%M\"\n        ).replace(tzinfo=TX_TZ)\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=datetime_object,\n            consumption=row.SystemTotal,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumption_list.to_list()\n\n\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey = ZoneKey(\"US-TEX-ERCO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests wind and solar power data in MW. target_datetime only date (takes the latest report on that date).\n    If target_datetime is None, it takes the latest report created\"\"\"\n    session = session or Session()\n\n    # Request wind power data\n    url_wind = f\"{US_PROXY}/misapp/servlets/IceDocListJsonWS?reportTypeId={ReportTypeID.WIND_POWER_PRODUCTION_REPORTID.value}&_{int(time.time())}&{HOST_PARAMETER}\"\n    df_wind = _get_dataframe_from_url(url_wind, session, target_datetime)\n\n    # Request solar power data\n    url_solar = f\"{US_PROXY}/misapp/servlets/IceDocListJsonWS?reportTypeId={ReportTypeID.SOLAR_POWER_PRODUCTION_REPORTID.value}&_{int(time.time())}&{HOST_PARAMETER}\"\n    df_solar = _get_dataframe_from_url(url_solar, session, target_datetime)\n\n    # Transfrom Hour column\n    df_wind[\"HOUR_STARTING\"] = df_wind[\"HOUR_ENDING\"] - 1\n    df_wind[\"HOUR_STARTING\"] = df_wind[\"HOUR_STARTING\"].astype(str) + \":00\"\n    df_solar[\"HOUR_STARTING\"] = df_solar[\"HOUR_ENDING\"] - 1\n    df_solar[\"HOUR_STARTING\"] = df_solar[\"HOUR_STARTING\"].astype(str) + \":00\"\n\n    # Merge wind and solar into one dataframe\n    merged_df = pd.merge(\n        df_wind, df_solar, on=[\"DELIVERY_DATE\", \"HOUR_STARTING\"], how=\"outer\"\n    )\n\n    all_production_events = (\n        merged_df.copy()\n    )  # all events with a datetime and a production breakdown\n    production_list = ProductionBreakdownList(logger)\n    for _, event in all_production_events.iterrows():\n        date_, time_ = event.DELIVERY_DATE, event.HOUR_STARTING\n        datetime_object = datetime.strptime(\n            date_ + \"T\" + time_, \"%m/%d/%YT%H:%M\"\n        ).replace(tzinfo=TX_TZ)\n\n        production_mix = ProductionMix()\n        production_mix.add_value(\n            \"solar\", event[\"STPPF_SYSTEM_WIDE\"], correct_negative_with_zero=True\n        )\n        production_mix.add_value(\n            \"wind\", event[\"STWPF_SYSTEM_WIDE\"], correct_negative_with_zero=True\n        )\n\n        production_list.append(\n            zoneKey=ZoneKey(zone_key),\n            datetime=datetime_object,\n            production=production_mix,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n    return production_list.to_list()\n\n\ndef fetch_dayahead_locational_marginal_price(\n    zone_key: ZoneKey = ZoneKey(\"US-TEX-ERCO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TX_TZ)\n\n    ERCOT_API_SUBSCRIPTION_KEY = get_token(\"ERCOT_API_SUBSCRIPTION_KEY\")\n\n    if not ERCOT_API_SUBSCRIPTION_KEY:\n        raise ValueError(\"ERCOT_API_SUBSCRIPTION_KEY must be set\")\n\n    id_token = get_id_token()\n\n    params = {\n        \"host\": \"https://api.ercot.com\",\n        \"deliveryDateFrom\": target_datetime.strftime(\"%Y-%m-%d\"),\n        \"deliveryDateTo\": target_datetime.strftime(\"%Y-%m-%d\"),\n    }\n    headers = {\n        \"Authorization\": f\"Bearer {id_token}\",\n        \"Ocp-Apim-Subscription-Key\": ERCOT_API_SUBSCRIPTION_KEY,\n    }\n    response = get_data(DAYAHEAD_LMP_URL, headers=headers, params=params)\n\n    params[\"size\"] = response[\"_meta\"][\"totalRecords\"]\n\n    response = get_data(DAYAHEAD_LMP_URL, headers=headers, params=params)\n\n    prices = LocationalMarginalPriceList(logger)\n    for row in response[\"data\"]:\n        if row[1] == \"24:00\":\n            date = datetime.strptime(f\"{row[0]} 00:00\", \"%Y-%m-%d %H:%M\").replace(\n                tzinfo=TX_TZ\n            ) + timedelta(days=1)\n        else:\n            date = datetime.strptime(f\"{row[0]} {row[1]}\", \"%Y-%m-%d %H:%M\").replace(\n                tzinfo=TX_TZ\n            )\n        prices.append(\n            zoneKey=zone_key,\n            datetime=date,\n            price=row[3],\n            currency=\"USD\",\n            node=row[2],\n            source=SOURCE,\n        )\n    return prices.to_list()\n\n\ndef fetch_realtime_locational_marginal_price(\n    zone_key: ZoneKey = ZoneKey(\"US-TEX-ERCO\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TX_TZ)\n\n    ERCOT_API_SUBSCRIPTION_KEY = get_token(\"ERCOT_API_SUBSCRIPTION_KEY\")\n\n    if not ERCOT_API_SUBSCRIPTION_KEY:\n        raise ValueError(\"ERCOT_API_SUBSCRIPTION_KEY must be set\")\n\n    id_token = get_id_token()\n\n    start_datetime = target_datetime - timedelta(minutes=40)\n    end_datetime = target_datetime + timedelta(minutes=10)\n\n    params = {\n        \"host\": \"https://api.ercot.com\",\n        \"SCEDTimestampTo\": end_datetime.strftime(\"%Y-%m-%dT%H:%M:%S\"),\n        \"SCEDTimestampFrom\": start_datetime.strftime(\"%Y-%m-%dT%H:%M:%S\"),\n    }\n    headers = {\n        \"Authorization\": f\"Bearer {id_token}\",\n        \"Ocp-Apim-Subscription-Key\": ERCOT_API_SUBSCRIPTION_KEY,\n    }\n    response = get_data(REALTIME_LMP_URL, headers=headers, params=params)\n\n    params[\"size\"] = response[\"_meta\"][\"totalRecords\"]\n\n    response = get_data(REALTIME_LMP_URL, headers=headers, params=params)\n\n    prices = LocationalMarginalPriceList(logger)\n    for row in response[\"data\"]:\n        date = datetime.strptime(row[0], \"%Y-%m-%dT%H:%M:%S\").replace(tzinfo=TX_TZ)\n        prices.append(\n            zoneKey=zone_key,\n            datetime=date,\n            price=row[3],\n            currency=\"USD\",\n            node=row[2],\n            source=SOURCE,\n        )\n    return prices.to_list()\n\n\ndef process_generation_dataframe(df):\n    \"\"\"\n    Process generation DataFrame by:\n    1. Flooring timestamps to nearest 5 minutes\n    2. Extracting 'gen' values from dictionary format\n    3. Grouping by datetime index and taking mean (temporal aggregation)\n    4. Standardizing columns using GENERATION_MAPPING (column aggregation)\n    \"\"\"\n    df_processed = df.copy()\n\n    # Convert to DatetimeIndex if it isn't already\n    if not isinstance(df_processed.index, pd.DatetimeIndex):\n        df_processed.index = pd.to_datetime(df_processed.index)\n\n    df_processed.index = df_processed.index.floor(\"5min\")\n\n    # Extract 'gen' values from dictionaries\n    df_processed = df_processed.apply(\n        lambda col: col.apply(\n            lambda x: x[\"gen\"] if isinstance(x, dict) and \"gen\" in x else None\n        )\n    )\n\n    # First group by datetime index to aggregate multiple rows with same 5-minute timestamp\n    df_processed = df_processed.groupby(df_processed.index).mean()\n\n    # Then group columns by their target names and sum (for columns that map to same target)\n    column_mapping = pd.Series(\n        {col: GENERATION_MAPPING.get(col, col) for col in df_processed.columns}\n    )\n    df_generation_standardized = df_processed.groupby(column_mapping, axis=1).sum(\n        numeric_only=True,\n    )\n\n    return df_generation_standardized[\n        [col for col in df_generation_standardized.columns if col != \"battery\"]\n    ]\n\n\ndef transform_historical_production(df):\n    \"\"\"\n    Transform the historical production data to a standardized format.\n    The input is unstandardized MWH per 15min and the output is standardized MW per 15min.\n    \"\"\"\n    # Identify time columns (all except 'Date', 'Fuel', 'Settlement Type', 'Total')\n    time_columns = [\n        col\n        for col in df.columns\n        if col not in [\"Date\", \"Fuel\", \"Settlement Type\", \"Total\"]\n    ]\n    records = []\n    for _, row in df.iterrows():\n        fuel = row[\"Fuel\"]\n        date_str = row[\"Date\"].strftime(\"%Y-%m-%d\")\n        for time_col in time_columns:\n            dt_str = f\"{date_str} {time_col}\"\n            dt = pd.to_datetime(dt_str, format=\"%Y-%m-%d %H:%M\").tz_localize(TX_TZ)\n            value = row[time_col]\n            records.append({\"datetime\": dt, \"fuel\": fuel, \"value\": value})\n    df_records = pd.DataFrame(records)\n    df_pivot = df_records.pivot(index=\"datetime\", columns=\"fuel\", values=\"value\")\n    column_mapping = pd.Series(\n        {col: GENERATION_MAPPING.get(col, col) for col in df_pivot.columns}\n    )\n    df_pivot_standardized = df_pivot.groupby(column_mapping, axis=1).sum(\n        numeric_only=True,\n    )\n    # From MWH to MW. The step are 15min steps\n    df_result = (\n        df_pivot_standardized[\n            [col for col in df_pivot_standardized.columns if col != \"battery\"]\n        ]\n        * 60\n        / 15\n    )\n    return df_result\n\n\ndef get_id_token():\n    ERCOT_API_PASSWORD = get_token(\"ERCOT_API_PASSWORD\")\n    ERCOT_API_USERNAME = get_token(\"ERCOT_API_USERNAME\")\n\n    if not ERCOT_API_PASSWORD or not ERCOT_API_USERNAME:\n        raise ValueError(\"ERCOT_API_PASSWORD and ERCOT_API_USERNAME must be set\")\n\n    auth_url = f\"{AUTH_URL_ERCOT}?username={ERCOT_API_USERNAME}&password={ERCOT_API_PASSWORD}&grant_type=password&scope=openid+fec253ea-0d06-4272-a5e6-b478baeecd70+offline_access&client_id=fec253ea-0d06-4272-a5e6-b478baeecd70&response_type=id_token\"\n\n    auth_response = requests.post(auth_url)\n    return auth_response.json().get(\"id_token\")\n\n\nif __name__ == \"__main__\":\n    \"Main method, not used by Electricity Map backend, but handy for testing\"\n\n    from pprint import pprint\n\n    pprint(fetch_production())\n    # pprint(fetch_production(target_datetime = datetime(2023,5,14)))\n\n    # pprint(parse_storage_data(session=Session()))\n    # print(\"fetch_consumption_forecast() -->\")\n    # pprint(fetch_consumption_forecast(target_datetime=datetime(2025,3,14)))\n    # pprint(fetch_consumption_forecast())\n\n    # print(\"fetch_wind_solar_forecasts() -->\")\n    # pprint(fetch_wind_solar_forecasts())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/US_MISO.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Parser for the MISO area of the United States.\"\"\"\n\nimport io\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\nfrom dateutil import parser, tz\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    GridAlertList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    GridAlertType,\n    ProductionMix,\n)\n\nSOURCE = \"misoenergy.org\"\nZONE = \"US-MIDW-MISO\"\nTIMEZONE = ZoneInfo(\"America/New_York\")\n\nmix_url = (\n    \"https://api.misoenergy.org/MISORTWDDataBroker/DataBrokerServices.asmx?messageType\"\n    \"=getfuelmix&returnType=json\"\n)\n\nmapping = {\n    \"Coal\": \"coal\",\n    \"Natural Gas\": \"gas\",\n    \"Nuclear\": \"nuclear\",\n    \"Wind\": \"wind\",\n    \"Solar\": \"solar\",\n    \"Other\": \"unknown\",\n}\n\nwind_forecast_url = \"https://api.misoenergy.org/MISORTWDDataBroker/DataBrokerServices.asmx?messageType=getWindForecast&returnType=json\"\nsolar_forecast_url = \"https://api.misoenergy.org/MISORTWDDataBroker/DataBrokerServices.asmx?messageType=getSolarForecast&returnType=json\"\n\n# To quote the MISO data source;\n# \"The category listed as \"Other\" is the combination of Hydro, Pumped Storage Hydro, Diesel, Demand Response Resources,\n# External Asynchronous Resources and a varied assortment of solid waste, garbage and wood pulp burners\".\n\n# Timestamp reported by data source is in format 23-Jan-2018 - Interval 11:45 EST\n# Unsure exactly why EST is used, possibly due to operational connections with PJM.\n\n\ndef get_json_data(logger: Logger, session: Session | None = None) -> dict:\n    \"\"\"Returns 5 minute generation data in json format.\"\"\"\n\n    s = session or Session()\n    json_data = s.get(mix_url).json()\n\n    return json_data\n\n\ndef data_processer(json_data, logger: Logger) -> tuple[datetime, ProductionMix]:\n    \"\"\"\n    Identifies any unknown fuel types and logs a warning.\n    Returns a tuple containing datetime object and production dictionary.\n    \"\"\"\n\n    generation = json_data[\"Fuel\"][\"Type\"]\n\n    mix = ProductionMix()\n    for fuel in generation:\n        try:\n            k = mapping[fuel[\"CATEGORY\"]]\n        except KeyError:\n            logger.warning(\n                \"Key '{}' is missing from the MISO fuel mapping.\".format(\n                    fuel[\"CATEGORY\"]\n                )\n            )\n            k = \"unknown\"\n        mix.add_value(k, float(fuel[\"ACT\"]))\n\n    # Remove unneeded parts of timestamp to allow datetime parsing.\n    timestamp = json_data[\"RefId\"]\n    split_time = timestamp.split(\" \")\n    time_junk = {1, 2}  # set literal\n    useful_time_parts = [v for i, v in enumerate(split_time) if i not in time_junk]\n\n    if useful_time_parts[-1] != \"EST\":\n        raise ValueError(\"Timezone reported for US-MISO has changed.\")\n\n    time_data = \" \".join(useful_time_parts)\n    tzinfos = {\"EST\": tz.gettz(\"America/New_York\")}\n    dt = parser.parse(time_data, tzinfos=tzinfos)\n\n    return dt, mix\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(ZONE),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    json_data = get_json_data(logger, session=session)\n    dt, mix = data_processer(json_data, logger)\n\n    production_breakdowns = ProductionBreakdownList(logger)\n    production_breakdowns.append(\n        zoneKey=zone_key,\n        datetime=dt,\n        production=mix,\n        source=SOURCE,\n    )\n    return production_breakdowns.to_list()\n\n\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey = ZoneKey(ZONE),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the 6 days ahead load (in MW) hourly data.\"\"\"\n    session = session or Session()\n\n    # Datetime\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE)\n    else:\n        # assume passed in correct timezone\n        target_datetime = target_datetime.replace(tzinfo=TIMEZONE)\n\n    # Request data\n    url = f\"https://docs.misoenergy.org/marketreports/{target_datetime.strftime('%Y%m%d')}_df_al.xls\"\n    response = session.get(\n        url, verify=False\n    )  # use requests library with verification disabled\n    df = pd.read_excel(\n        io.BytesIO(response.content), sheet_name=\"Sheet1\", skiprows=4, skipfooter=1\n    )\n\n    # Process dataframe\n    df = df.dropna(subset=[\"HourEnding\"])\n    df = df.loc[df[\"HourEnding\"] != \"HourEnding\"]\n    df.loc[:, \"HourEnding\"] = df[\"HourEnding\"].astype(int)\n    df[\"Interval End\"] = pd.to_datetime(df[\"Market Day\"]) + pd.to_timedelta(\n        df[\"HourEnding\"], unit=\"h\"\n    )\n    df[\"Interval Start\"] = df[\"Interval End\"] - pd.Timedelta(hours=1)\n\n    # Record events in consumption_list\n    all_consumption_events = df.copy()\n    consumption_list = TotalConsumptionList(logger)\n    for _, event in all_consumption_events.iterrows():\n        event_datetime = event[\"Interval Start\"].strftime(\"%Y-%m-%d %H:%M:%S\")\n        event_datetime = datetime.fromisoformat(event_datetime).replace(tzinfo=TIMEZONE)\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=event_datetime,\n            consumption=float(event[\"MISO MTLF (MWh)\"]),\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumption_list.to_list()\n\n\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey = ZoneKey(ZONE),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the day ahead wind and solar forecast (in MW) hourly data.\"\"\"\n\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    s = session or Session()\n\n    # Request wind data\n    req_wind = s.get(wind_forecast_url)\n    raw_json_wind = req_wind.json()\n    raw_data_wind = raw_json_wind[\"Forecast\"]\n\n    # Request solar data\n    req_solar = s.get(solar_forecast_url)\n    raw_json_solar = req_solar.json()\n    raw_data_solar = raw_json_solar[\"Forecast\"]\n\n    production_breakdowns = ProductionBreakdownList(logger)\n\n    for wind_event, solar_event in zip(raw_data_wind, raw_data_solar, strict=True):\n        # Check that we loop over same dates\n        if wind_event[\"DateTimeEST\"] == solar_event[\"DateTimeEST\"]:\n            dt = parser.parse(wind_event[\"DateTimeEST\"]).replace(tzinfo=TIMEZONE)\n\n            production_mix = ProductionMix()\n            production_mix.add_value(\n                \"wind\", float(wind_event[\"Value\"]), correct_negative_with_zero=True\n            )\n            production_mix.add_value(\n                \"solar\", float(solar_event[\"Value\"]), correct_negative_with_zero=True\n            )\n\n            production_breakdowns.append(\n                datetime=dt,\n                production=production_mix,\n                source=SOURCE,\n                zoneKey=zone_key,\n                sourceType=EventSourceType.forecasted,\n            )\n\n    return production_breakdowns.to_list()\n\n\ndef fetch_grid_alerts(\n    zone_key: ZoneKey = ZoneKey(ZONE),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Fetch Grid Alerts from MISO\"\"\"\n    session = session or Session()\n\n    # API URL\n    url = \"https://www.misoenergy.org/api/topicnotifications/getrecentnotifications\"\n\n    # Request payload (can be adjusted if you want specific filters)\n    payload = {\"topics\": [\"RealTime\"], \"take\": 0}  # take 0 is equal to get all possible\n    # TODO: do we just need the last one?\n\n    # Request headers\n    headers = {\n        \"Content-Type\": \"application/json\",\n        \"Accept\": \"application/json\",\n        \"User-Agent\": \"Mozilla/5.0\",\n        \"Referer\": \"https://www.misoenergy.org/markets-and-operations/notifications/real-time-operations-notifications/\",\n        \"X-Requested-With\": \"XMLHttpRequest\",\n    }\n\n    # Make the POST request\n    response = session.post(url, json=payload, headers=headers)\n\n    # Check for success\n    if response.status_code == 200:\n        notifications = response.json()\n\n    # TODO: maybe extract locationRegion from each notification?\n    # TODO: maybe extract startTime and endTime from each notification?\n    # TODO: maybe extract alertType from each notification?\n\n    # Record events in grid_alert_list\n    grid_alert_list = GridAlertList(logger)\n    for notification in notifications:\n        publish_datetime = datetime.fromisoformat(\n            notification[\"publishDateUnformatted\"]\n        ).replace(tzinfo=TIMEZONE)\n\n        clean_subject = extract_text_with_links(notification[\"subject\"])\n        clean_body = extract_text_with_links(notification[\"body\"])\n        message = clean_subject + \"\\n\" + clean_body\n\n        grid_alert_list.append(\n            zoneKey=zone_key,\n            locationRegion=None,\n            source=SOURCE,\n            alertType=GridAlertType.undefined,\n            message=message,\n            issuedTime=publish_datetime,\n            startTime=None,  # if None, it defaults to issuedTime\n            endTime=None,\n        )\n    return grid_alert_list.to_list()\n\n\ndef extract_text_with_links(html_content):\n    soup = BeautifulSoup(html_content, \"html.parser\")\n    for a in soup.find_all(\"a\"):\n        if a.get(\"href\"):\n            a.replace_with(f\"{a.get_text()} ({a['href']})\")\n    return soup.get_text(separator=\" \")\n\n\nif __name__ == \"__main__\":\n    from pprint import pprint\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n\n    print(fetch_consumption_forecast())\n\n    print(\"fetch_wind_solar_forecasts() ->\")\n    print(fetch_wind_solar_forecasts())\n\n    pprint(fetch_grid_alerts())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/US_NEISO.py",
    "content": "#!/usr/bin/env python3\n\n\n\"\"\"Real time parser for the New England ISO (NEISO) area.\"\"\"\n\nimport io\nimport time\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    GridAlertList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    GridAlertType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.types import ZoneKey\n\nUS_NEISO_KEY = ZoneKey(\"US-NE-ISNE\")\nSOURCE = \"iso-ne.com\"\n\nurl = \"https://www.iso-ne.com/ws/wsclient\"\n\ngeneration_mapping = {\n    \"Coal\": \"coal\",\n    \"NaturalGas\": \"gas\",\n    \"Wind\": \"wind\",\n    \"Hydro\": \"hydro\",\n    \"Nuclear\": \"nuclear\",\n    \"Wood\": \"biomass\",\n    \"Oil\": \"oil\",\n    \"Refuse\": \"biomass\",\n    \"LandfillGas\": \"biomass\",\n    \"Solar\": \"solar\",\n}\n\n\ndef get_json_data(\n    target_datetime: datetime | None, params, session: Session | None = None\n) -> dict:\n    \"\"\"Fetches json data for requested params and target_datetime using a post request.\"\"\"\n\n    epoch_time = str(int(time.time()))\n\n    target_datetime = target_datetime or datetime.now(tz=timezone.utc)\n    target_ne = target_datetime.astimezone(tz=ZoneInfo(\"America/New_York\"))\n    target_ne_day = target_ne.strftime(\"%m/%d/%Y\")\n\n    postdata = {\n        \"_nstmp_formDate\": epoch_time,\n        \"_nstmp_startDate\": target_ne_day,\n        \"_nstmp_endDate\": target_ne_day,\n        \"_nstmp_twodays\": \"false\",\n        \"_nstmp_showtwodays\": \"false\",\n    }\n    postdata.update(params)\n\n    s = session or Session()\n\n    req = s.post(url, data=postdata)\n    json_data = req.json()\n    raw_data = json_data[0][\"data\"]\n\n    return raw_data\n\n\ndef production_data_processer(\n    zone_key: ZoneKey, raw_data: dict | list, logger: Logger\n) -> ProductionBreakdownList:\n    \"\"\"\n    Takes raw json data and removes unnecessary keys.\n    Separates datetime key and converts to a datetime object.\n    \"\"\"\n\n    other_keys = {\"BeginDateMs\", \"Renewables\", \"BeginDate\", \"Other\"}\n    known_keys = generation_mapping.keys() | other_keys\n\n    unmapped = set()\n\n    production_breakdowns = ProductionBreakdownList(logger)\n    counter = 0\n    for datapoint in raw_data:\n        current_keys = datapoint.keys() | set()\n        unknown_keys = current_keys - known_keys\n        unmapped = unmapped | unknown_keys\n\n        keys_to_remove = {\"BeginDateMs\", \"Renewables\"} | unknown_keys\n        for k in keys_to_remove:\n            datapoint.pop(k, None)\n\n        time_string = datapoint.pop(\"BeginDate\", None)\n        if time_string:\n            dt = datetime.fromisoformat(time_string)\n        else:\n            counter += 1\n            logger.warning(\n                f\"Skipping {zone_key} datapoint missing timestamp.\",\n                extra={\"zone_key\": zone_key},\n            )\n            continue\n\n        # neiso storage flow signs are opposite to EM\n        battery_storage = -1 * datapoint.pop(\"Other\", 0.0)\n        storage_mix = StorageMix(battery=battery_storage, hydro=None)\n\n        production_mix = ProductionMix()\n        for k, v in datapoint.items():\n            production_mix.add_value(\n                mode=generation_mapping[k], value=v, correct_negative_with_zero=v > -5\n            )\n\n        production_breakdowns.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            source=SOURCE,\n            production=production_mix,\n            storage=storage_mix,\n        )\n\n    for key in unmapped:\n        logger.warning(\n            f\"Key '{key}' in {zone_key} is not mapped to type.\",\n            extra={\"zone_key\": zone_key},\n        )\n\n    if counter > 0:\n        logger.warning(\n            f\"Skipped {counter} {zone_key} datapoints that were missing timestamps.\",\n            extra={\"zone_key\": zone_key},\n        )\n\n    return production_breakdowns\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = US_NEISO_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n\n    postdata = {\n        \"_nstmp_chartTitle\": \"Fuel+Mix+Graph\",\n        \"_nstmp_requestType\": \"genfuelmix\",\n        \"_nstmp_fuelType\": \"all\",\n        \"_nstmp_height\": \"250\",\n    }\n\n    production_json = get_json_data(target_datetime, postdata, session)\n    production_breakdowns = production_data_processer(zone_key, production_json, logger)\n\n    return production_breakdowns.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known power exchange (in MW) between two zones.\"\"\"\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    # For directions, note that ISO-NE always reports its import as negative\n\n    if sorted_zone_keys == \"CA-NB->US-NE-ISNE\":\n        # CA-NB->US-NEISO means import to NEISO should be positive\n        multiplier = -1\n\n        postdata = {\"_nstmp_zone0\": \"4010\"}  # \".I.SALBRYNB345 1\"\n\n    elif sorted_zone_keys == \"CA-QC->US-NE-ISNE\":\n        # CA-QC->US-NEISO means import to NEISO should be positive\n        multiplier = -1\n\n        postdata = {\n            \"_nstmp_zone0\": \"4012\",  # \".I.HQ_P1_P2345 5\"\n            \"_nstmp_zone1\": \"4013\",  # \".I.HQHIGATE120 2\"\n            \"_nstmp_zone2\": \"4018\",  # \".I.HQMRL_RD345 1\"\n        }\n\n    elif sorted_zone_keys == \"US-NE-ISNE->US-NY-NYIS\":\n        # US-NEISO->US-NY means import to NEISO should be negative\n        multiplier = 1\n\n        postdata = {\n            \"_nstmp_zone0\": \"4014\",  # \".I.SHOREHAM138 99\"\n            \"_nstmp_zone1\": \"4017\",  # \".I.NRTHPORT138 5\"\n            \"_nstmp_zone2\": \"4011\",  # \".I.ROSETON 345 1\"\n        }\n\n    else:\n        raise Exception(f\"Exchange pair not supported: {sorted_zone_keys}\")\n\n    postdata[\"_nstmp_requestType\"] = \"externalflow\"\n\n    unmerged_exchanges: list[ExchangeList] = []\n    exchange_data = get_json_data(target_datetime, postdata, session)\n    for exchange_values in exchange_data.values():\n        # Creates a exchange list for each exchange\n        exchanges = ExchangeList(logger)\n        for datapoint in exchange_values:\n            time_string = datapoint.pop(\"BeginDate\", None)\n            if time_string:\n                dt = datetime.fromisoformat(time_string)\n            else:\n                logger.warning(\n                    f\"Skipping {sorted_zone_keys} datapoint missing timestamp.\",\n                    extra={\"zone_key\": sorted_zone_keys},\n                )\n                continue\n            exchanges.append(\n                zoneKey=sorted_zone_keys,\n                datetime=dt,\n                netFlow=datapoint[\"Actual\"] * multiplier,\n                source=SOURCE,\n            )\n        # Append the exchange list to the unmerged list\n        unmerged_exchanges.append(exchanges)\n\n    # Merge all exchanges into one\n    return ExchangeList.merge_exchanges(unmerged_exchanges, logger).to_list()\n\n\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey = US_NEISO_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests load forecast in MW for 1 day ahead (hourly)\"\"\"\n    session = session or Session()\n\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n    target_datetime = target_datetime.astimezone(tz=ZoneInfo(\"America/New_York\"))\n    postdata = {\n        \"_nstmp_startDate\": target_datetime.strftime(\"%m/%d/%Y\"),\n        \"_nstmp_endDate\": (target_datetime + pd.Timedelta(days=1)).strftime(\"%m/%d/%Y\"),\n        \"_nstmp_requestType\": \"systemload\",\n    }\n\n    # Request data\n    raw_data = get_json_data(target_datetime=None, params=postdata, session=session)\n\n    all_consumption_events = raw_data[\"forecast\"]\n\n    consumption_list = TotalConsumptionList(logger)\n    for event in all_consumption_events:\n        event_datetime = datetime.fromisoformat(event[\"BeginDate\"]).replace(\n            tzinfo=ZoneInfo(\"America/New_York\")\n        )\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=event_datetime,\n            consumption=event[\"Mw\"],\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumption_list.to_list()\n\n\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey = US_NEISO_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests wind and solar power forecast in MW for 7 days\"\"\"\n\n    # Datetime\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n    target_datetime = target_datetime.astimezone(tz=ZoneInfo(\"America/New_York\"))\n    if (\n        target_datetime.hour <= 10\n    ):  # the data is updated every day at approximately 10:00:00-05:00\n        target_datetime = target_datetime - timedelta(days=1)\n    target_datetime_string = target_datetime.strftime(\"%Y%m%d\")\n\n    # Request url\n    session = session or Session()\n    merged_data = None\n    for data_type in [\"solar\", \"wind\"]:\n        # Get cookies by accessing the forecast pages\n        session.get(\n            \"https://www.iso-ne.com/isoexpress/web/reports/operations/-/tree/seven-day-\"\n            + data_type\n            + \"-power-forecast\"\n        )\n        response = session.get(\n            \"https://www.iso-ne.com/transform/csv/\"\n            + data_type[0]\n            + \"phf?start=\"\n            + target_datetime_string\n        )\n\n        # Get dataframe\n        df = pd.read_csv(\n            io.StringIO(response.content.decode(\"utf8\")),\n            skiprows=[0, 1, 2, 3, 4, 5],\n            skipfooter=1,\n            engine=\"python\",\n        ).drop_duplicates()\n\n        df = df.drop(columns=[\"D\", \"Date\"])\n\n        data = df.melt(\n            id_vars=[\"Hour Ending\"],\n            var_name=\"Date\",\n            value_name=data_type,\n        ).dropna(subset=[data_type])\n\n        if merged_data is None:\n            # For the first iteration (solar), just store the data\n            merged_data = data\n        else:\n            # For the second iteration (wind), merge with the first data\n            merged_data = pd.merge(\n                merged_data, data, on=[\"Hour Ending\", \"Date\"], how=\"outer\"\n            )\n\n    # Convert 'Hour Ending' to numeric type if it isn't already\n    merged_data[\"Hour Ending\"] = pd.to_numeric(merged_data[\"Hour Ending\"])\n\n    # Combine Date and Hour Ending into a datetime iso column\n    merged_data[\"datetime\"] = pd.to_datetime(\n        merged_data[\"Date\"]\n        + \" \"\n        + (merged_data[\"Hour Ending\"] - 1).astype(str)\n        + \":00\",\n        format=\"%m/%d/%Y %H:%M\",\n    )\n    # Convert to ISO format string\n    merged_data[\"datetime_iso\"] = merged_data[\"datetime\"].dt.strftime(\n        \"%Y-%m-%dT%H:%M:%S\"\n    )\n    data_final = merged_data[[\"datetime_iso\", \"solar\", \"wind\"]]\n\n    # All events with a datetime and a production breakdown\n    all_production_events = data_final.copy()\n    production_list = ProductionBreakdownList(logger)\n    for _index, event in all_production_events.iterrows():\n        event_datetime = datetime.fromisoformat(event[\"datetime_iso\"]).replace(\n            tzinfo=ZoneInfo(\"America/New_York\")\n        )\n        production_mix = ProductionMix()\n        production_mix.add_value(\n            \"solar\", event[\"solar\"], correct_negative_with_zero=True\n        )\n        production_mix.add_value(\"wind\", event[\"wind\"], correct_negative_with_zero=True)\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=event_datetime,\n            production=production_mix,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n    return production_list.to_list()\n\n\ndef fetch_grid_alerts(\n    zone_key: ZoneKey = US_NEISO_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Fetch Grid Alerts from ISONE\"\"\"\n    session = session or Session()\n\n    # Make the request\n    url = \"https://www.iso-ne.com/markets-operations/system-forecast-status/current-system-status\"\n    response = session.get(url)\n    soup = BeautifulSoup(response.content, \"html.parser\")\n\n    # Find the table\n    table = soup.find(\"table\", id=\"PowerSystemConditions-Table\")\n    # Extract footer <pre> text (updated at)\n    footer_pre = table.find(\"tfoot\").find(\"pre\").get_text(strip=True)\n    # Extract the datetime part (remove 'Updated: ')\n    datetime_part = footer_pre.replace(\"Updated: \", \"\")\n    # Parse the datetime\n    updated_at = datetime.strptime(datetime_part, \" %m/%d/%Y  %I:%M %p\").replace(\n        tzinfo=ZoneInfo(\"America/New_York\")\n    )\n    issued_at = updated_at\n\n    grid_alert_list = GridAlertList(logger)\n    # Extract table rows\n    for tr in table.find(\"tbody\").find_all(\"tr\"):\n        cells = tr.find_all(\"td\")\n\n        # Rows with at least 3 cells\n        row_data = [\n            cells[0].get_text(strip=True),\n            cells[1].get_text(strip=True),\n            cells[2].get_text(strip=True),\n        ]\n\n        # If message starts by \"Normal\":\n        if row_data[1].startswith(\"Normal\"):\n            continue\n\n        # If \"time in\" is not empty\n        if row_data[2] != \"\":\n            time_in = row_data[2]\n            time_in = datetime.strptime(time_in, \"%m/%d/%Y  %I:%M:%S %p\").replace(\n                tzinfo=ZoneInfo(\"America/New_York\")\n            )\n            issued_at = time_in\n\n        # Append\n        grid_alert_list.append(\n            zoneKey=zone_key,\n            locationRegion=row_data[0],\n            source=SOURCE,\n            alertType=GridAlertType.undefined,\n            message=row_data[1],\n            issuedTime=issued_at,\n            startTime=None,  # if None, it defaults to issuedTime\n            endTime=None,\n        )\n\n    # TODO: maybe extract startTime and endTime from each notification?\n    # TODO: maybe extract alertType from each notification?\n\n    return grid_alert_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    from pprint import pprint\n\n    \"\"\"\n    print(\"fetch_production() ->\")\n    pprint(fetch_production())\n\n    print(\n        'fetch_production(target_datetime=datetime.fromisoformat(\"2017-12-31T12:00:00+00:00\")) ->'\n    )\n    pprint(\n        fetch_production(\n            target_datetime=datetime.fromisoformat(\"2017-12-31T12:00:00+00:00\")\n        )\n    )\n\n    print(\n        'fetch_production(target_datetime=datetime.fromisoformat(\"2007-03-13T12:00:00+00:00\")) ->'\n    )\n    pprint(\n        fetch_production(\n            target_datetime=datetime.fromisoformat(\"2007-03-13T12:00:00+00:00\")\n        )\n    )\n\n    print(f'fetch_exchange(\"{US_NEISO_KEY}\", \"CA-QC\") ->')\n    pprint(fetch_exchange(US_NEISO_KEY, ZoneKey(\"CA-QC\")))\n\n    print(\n        f'fetch_exchange(\"{US_NEISO_KEY}\", \"CA-QC\", target_datetime=datetime.fromisoformat(\"2017-12-31T12:00:00+00:00\")) ->'\n    )\n    pprint(\n        fetch_exchange(\n            US_NEISO_KEY,\n            ZoneKey(\"CA-QC\"),\n            target_datetime=datetime.fromisoformat(\"2017-12-31T12:00:00+00:00\"),\n        )\n    )\n\n    print(\n        f'fetch_exchange(\"{US_NEISO_KEY}\", \"CA-QC\", target_datetime=datetime.fromisoformat(\"2007-03-13T12:00:00+00:00\")) ->'\n    )\n    pprint(\n        fetch_exchange(\n            US_NEISO_KEY,\n            ZoneKey(\"CA-QC\"),\n            target_datetime=datetime.fromisoformat(\"2007-03-13T12:00:00+00:00\"),\n        )\n    )\n\n    print(\"fetch_wind_solar_forecasts()\")\n    pprint(fetch_wind_solar_forecasts())\n\n    pprint(fetch_consumption_forecast())\n    \"\"\"\n\n    print(\"fetch_grid_alerts()\")\n    pprint(fetch_grid_alerts())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/US_NY.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Real time parser for the state of New York.\"\"\"\n\nfrom collections import defaultdict\nfrom datetime import datetime, timedelta\nfrom io import BytesIO\nfrom logging import Logger, getLogger\nfrom operator import itemgetter\nfrom typing import Any\nfrom zipfile import ZipFile\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Session\nfrom requests.exceptions import HTTPError\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    GridAlertList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    GridAlertType,\n    ProductionMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\n\n# Pumped storage is present but is not split into a separate category.\n\n# Dual Fuel systems can run either Natural Gas or Oil, they represent\n# significantly more capacity in NY State than plants that can only\n# burn Natural Gas. When looking up fuel usage for NY in 2016 in\n# https://www.eia.gov/electricity/data/state/annual_generation_state.xls\n# 100 times more energy came from NG than Oil. That means Oil\n# consumption in the Dual Fuel systems is roughly ~1%, and to a first\n# approximation it's just Natural Gas.\n\nSOURCE = \"nyiso.com\"\nTIMEZONE = ZoneInfo(\"America/New_York\")\nZONE = \"US-NY-NYIS\"\n\nmapping_pre_april_2020 = {\n    \"Dual Fuel\": \"gas\",\n    \"Natural Gas\": \"gas\",\n    \"Nuclear\": \"nuclear\",\n    \"Other Fossil Fuels\": \"unknown\",\n    \"Other Renewables\": \"unknown\",\n    \"Wind\": \"wind\",\n    \"Hydro\": \"hydro\",\n}\n\nmapping_post_april_2020 = {\n    \"Dual Fuel\": \"gas\",\n    \"Natural Gas\": \"gas\",\n    \"Nuclear\": \"nuclear\",\n    \"Other Fossil Fuels\": \"oil\",\n    \"Other Renewables\": \"unknown\",\n    \"Wind\": \"wind\",\n    \"Hydro\": \"hydro\",\n}\n\n\ndef read_csv_data(session: Session, url: str) -> pd.DataFrame:\n    \"\"\"Gets csv data from a url and returns a dataframe.\"\"\"\n\n    response = session.get(url)\n    response.raise_for_status()\n\n    csv_data = pd.read_csv(BytesIO(response.content))\n\n    return csv_data\n\n\ndef read_zip_data(session: Session, url: str, csv_file: str) -> pd.DataFrame:\n    \"\"\"Gets zip data from a url (with a session), extracts a csv file and returns a dataframe.\"\"\"\n\n    response = session.get(url)\n    response.raise_for_status()\n\n    zip_file = ZipFile(BytesIO(response.content))\n    csv_data = pd.read_csv(zip_file.open(csv_file))\n\n    return csv_data\n\n\ndef timestamp_converter(timestamp_string: str) -> datetime:\n    \"\"\"Converts timestamps in nyiso data into aware datetime objects.\"\"\"\n    try:\n        dt_naive = datetime.strptime(timestamp_string, \"%m/%d/%Y %H:%M:%S\")\n    except ValueError:\n        dt_naive = datetime.strptime(timestamp_string, \"%m/%d/%Y %H:%M\")\n    dt_aware = dt_naive.replace(tzinfo=TIMEZONE)\n\n    return dt_aware\n\n\ndef data_parser(df, mapping, logger) -> list[tuple[datetime, ProductionMix]]:\n    \"\"\"\n    Takes dataframe and loops over rows to form dictionaries consisting of datetime and generation type.\n    Merges these dictionaries using datetime key.\n\n    :return: list of tuples containing datetime and production.\n    \"\"\"\n\n    chunks = []\n    for row in df.itertuples():\n        piece = {}\n        piece[\"datetime\"] = row[1]\n        piece[row[3]] = row[4]\n        chunks.append(piece)\n\n    # Join dicts on shared 'datetime' keys.\n    combine = defaultdict(dict)\n    for elem in chunks:\n        combine[elem[\"datetime\"]].update(elem)\n\n    ordered = sorted(combine.values(), key=itemgetter(\"datetime\"))\n\n    mapped_generation = []\n    for item in ordered:\n        mix = ProductionMix()\n        dt = timestamp_converter(item.pop(\"datetime\"))\n        for key, val in item.items():\n            try:\n                mix.add_value(mapping[key], val)\n            except KeyError:\n                logger.warning(\"Unrecognized production key '%s'\", key)\n\n        mapped_generation.append((dt, mix))\n\n    return mapped_generation\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(ZONE),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given zone.\"\"\"\n    session = session or Session()\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE)\n    else:\n        # assume passed in correct timezone\n        target_datetime = target_datetime.replace(tzinfo=TIMEZONE)\n\n    ny_date = target_datetime.strftime(\"%Y%m%d\")\n    if (datetime.now(tz=TIMEZONE) - target_datetime).days <= 9:\n        mix_url = f\"http://mis.nyiso.com/public/csv/rtfuelmix/{ny_date}rtfuelmix.csv\"\n        try:\n            raw_data = read_csv_data(session, mix_url)\n        except HTTPError:\n            # this can happen when target_datetime has no data available\n            return []\n    else:\n        mix_csv = f\"{ny_date}rtfuelmix.csv\"\n        ny_zip_date = target_datetime.strftime(\"%Y%m01\")\n        mix_zip_url = (\n            f\"http://mis.nyiso.com/public/csv/rtfuelmix/{ny_zip_date}rtfuelmix_csv.zip\"\n        )\n        try:\n            raw_data = read_zip_data(session, mix_zip_url, mix_csv)\n        except (HTTPError, KeyError):\n            # this can happen when target_datetime has no data available\n            return []\n\n    if target_datetime > datetime(2020, 4, 1, tzinfo=TIMEZONE):\n        clean_data = data_parser(raw_data, mapping_post_april_2020, logger)\n\n    else:\n        clean_data = data_parser(raw_data, mapping_pre_april_2020, logger)\n\n    production_breakdowns = ProductionBreakdownList(logger=logger)\n    for dt, mix in clean_data:\n        production_breakdowns.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            production=mix,\n            source=SOURCE,\n        )\n\n    return production_breakdowns.to_list()\n\n\n@refetch_frequency(timedelta(hours=24))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known power exchange (in MW) between two zones.\"\"\"\n    session = session or Session()\n\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    # In the source CSV, positive is flow into NY, negative is flow out of NY.\n    # In Electricity Map, A->B means flow to B is positive.\n    if (\n        sorted_zone_keys == \"US-NEISO->US-NY\"\n        or sorted_zone_keys == \"US-NE-ISNE->US-NY-NYIS\"\n    ):\n        direction = 1\n        relevant_exchanges = [\"SCH - NE - NY\", \"SCH - NPX_1385\", \"SCH - NPX_CSC\"]\n    elif sorted_zone_keys == \"US-NY->US-PJM\":\n        direction = -1\n        relevant_exchanges = [\n            \"SCH - PJ - NY\",\n            \"SCH - PJM_HTP\",\n            \"SCH - PJM_NEPTUNE\",\n            \"SCH - PJM_VFT\",\n        ]\n    elif sorted_zone_keys == \"US-MIDA-PJM->US-NY-NYIS\":\n        direction = 1\n        relevant_exchanges = [\n            \"SCH - PJ - NY\",\n            \"SCH - PJM_HTP\",\n            \"SCH - PJM_NEPTUNE\",\n            \"SCH - PJM_VFT\",\n        ]\n    elif sorted_zone_keys == \"CA-ON->US-NY\" or sorted_zone_keys == \"CA-ON->US-NY-NYIS\":\n        direction = 1\n        relevant_exchanges = [\"SCH - OH - NY\"]\n    elif sorted_zone_keys == \"CA-QC->US-NY\" or sorted_zone_keys == \"CA-QC->US-NY-NYIS\":\n        direction = 1\n        relevant_exchanges = [\"SCH - HQ_CEDARS\", \"SCH - HQ - NY\"]\n    else:\n        raise NotImplementedError(f\"Exchange pair not supported: {sorted_zone_keys}\")\n\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE)\n    ny_date = target_datetime.strftime(\"%Y%m%d\")\n    file_name = f\"{ny_date}ExternalLimitsFlows.csv\"\n    exchange_url = \"http://mis.nyiso.com/public/csv/ExternalLimitsFlows\"\n    csv_url = f\"{exchange_url}/{file_name}\"\n\n    try:\n        exchange_data = read_csv_data(session, csv_url)\n    except HTTPError:\n        try:\n            ny_zip_date = target_datetime.strftime(\"%Y%m01\")\n            zip_file_name = f\"{ny_zip_date}ExternalLimitsFlows_csv.zip\"\n            zip_url = f\"{exchange_url}/{zip_file_name}\"\n            exchange_data = read_zip_data(session, zip_url, file_name)\n        except HTTPError:\n            # this can happen when target_datetime has no data available\n            return []\n\n    new_england_exs = exchange_data.loc[\n        exchange_data[\"Interface Name\"].isin(relevant_exchanges)\n    ]\n    consolidated_flows = (\n        new_england_exs.reset_index().groupby(\"Timestamp\").sum(numeric_only=True)\n    )\n\n    now = datetime.now(tz=TIMEZONE)\n\n    exchange_5min = ExchangeList(logger)\n    for row in consolidated_flows.itertuples():\n        flow = float(row[3]) * direction\n        # Timestamp for exchange does not include seconds.\n        dt = timestamp_converter(row[0] + \":00\")\n\n        if (dt > now) and ((dt - now) < timedelta(seconds=300)):\n            # NYISO exchanges CSV (and only the exchanges CSV) includes data\n            # up to 5 minutes in the future (but only 5 minutes in the future).\n            # This also happens on their official website.\n            # Electricity Map raises error with data in the future, so skip\n            # that datapoint. If it's more than 5 minutes in the future,\n            # it's weird/unexpected and thus worthy of failure and logging.\n            continue\n\n        exchange_5min.append(\n            source=SOURCE, datetime=dt, netFlow=flow, zoneKey=sorted_zone_keys\n        )\n\n    return exchange_5min.to_list()\n\n\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey = ZoneKey(ZONE),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the load forecast (in MW) for a given date in hourly intervals.\"\"\"\n    session = session or Session()\n\n    # Datetime\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE)\n    else:\n        # assume passed in correct timezone\n        target_datetime = target_datetime.replace(tzinfo=TIMEZONE)\n\n    ny_date = target_datetime.strftime(\"%Y%m%d\")\n    if (datetime.now(tz=TIMEZONE) - target_datetime).days <= 9:\n        target_url = f\"http://mis.nyiso.com/public/csv/isolf/{ny_date}isolf.csv\"\n        try:\n            df = read_csv_data(session, target_url)\n        except HTTPError:\n            # this can happen when target_datetime has no data available\n            return []\n    else:\n        target_csv = f\"{ny_date}isolf.csv\"\n        ny_zip_date = target_datetime.strftime(\"%Y%m01\")\n        target_zip_url = (\n            f\"http://mis.nyiso.com/public/csv/isolf/{ny_zip_date}isolf_csv.zip\"\n        )\n        try:\n            df = read_zip_data(session, target_zip_url, target_csv)\n        except (HTTPError, KeyError):\n            # this can happen when target_datetime has no data available\n            return []\n\n    # Add events consumption_list\n    all_consumption_events = (\n        df.copy()\n    )  # all events with a datetime and a generation value\n    consumption_list = TotalConsumptionList(logger)\n    for _index, event in all_consumption_events.iterrows():\n        event_datetime = timestamp_converter(event[\"Time Stamp\"])\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=event_datetime,\n            consumption=event[\"NYISO\"],\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumption_list.to_list()\n\n\ndef fetch_grid_alerts(\n    zone_key: ZoneKey = ZoneKey(ZONE),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Fetch Grid Alerts from NYISO (http://mis.nyiso.com/public/P-35list.htm)\"\"\"\n    session = session or Session()\n\n    # Target Datetime\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=TIMEZONE)\n    else:\n        # assume passed in correct timezone\n        target_datetime = target_datetime.replace(tzinfo=TIMEZONE)\n\n    # Make URL with specified date\n    target_datetime_string = target_datetime.strftime(\"%Y%m%d\")\n    url = (\n        \"http://mis.nyiso.com/public/csv/RealTimeEvents/\"\n        + target_datetime_string\n        + \"RealTimeEvents.csv\"\n    )\n\n    # Make the request and check for success\n    try:\n        csv = pd.read_csv(url)\n    except Exception as e:\n        logger.error(\n            \"Failed to fetch grid alerts from NYISO for date of %s: %s\",\n            target_datetime_string,\n            e,\n        )\n        return []\n\n    # TODO: maybe extract locationRegion from each notification?\n    # TODO: maybe extract startTime and endTime from each notification?\n    # TODO: maybe extract alertType from each notification?\n\n    # Record events in grid_alert_list\n    grid_alert_list = GridAlertList(logger)\n    for _, notification in csv.iterrows():\n        # Parse and assign EDT timezone\n        dt_edt = datetime.strptime(\n            notification[\"Timestamp\"], \"%m/%d/%Y %H:%M:%S\"\n        ).replace(tzinfo=TIMEZONE)\n        # Convert to UTC\n        dt_utc = dt_edt.astimezone(ZoneInfo(\"UTC\"))\n\n        # Parse message\n        message = notification[\"Message\"]\n\n        if message.startswith(\"**\") and message.endswith(\"**\"):\n            # If the message is not the normal state (starting and ending with \"**\"\"), we add it to the grid_alert_list\n            message_content = message[2:-2]\n            grid_alert_list.append(\n                zoneKey=zone_key,\n                locationRegion=None,\n                source=SOURCE,\n                alertType=GridAlertType.undefined,\n                message=message_content,\n                issuedTime=dt_utc,\n                startTime=None,  # if None, it defaults to issuedTime\n                endTime=None,\n            )\n    return grid_alert_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    from pprint import pprint\n\n    \"\"\"\n    print(\"fetch_production() ->\")\n    pprint(fetch_production())\n\n    print(\"fetch_production(target_datetime=datetime(2018, 3, 13, 12, 0)) ->\")\n    pprint(fetch_production(target_datetime=datetime(2018, 3, 13, 12, 0)))\n\n    print(\"fetch_production(target_datetime=datetime(2007, 3, 13, 12)) ->\")\n    pprint(fetch_production(target_datetime=datetime(2007, 3, 13, 12)))\n\n    print(\"fetch_exchange(US-NY, US-NEISO)\")\n    pprint(fetch_exchange(\"US-NY\", \"US-NEISO\"))\n\n    print('fetch_exchange(\"US-NY\", \"CA-QC\")')\n    pprint(fetch_exchange(\"US-NY\", \"CA-QC\"))\n\n    print(\n        'fetch_exchange(\"US-NY\", \"CA-QC\", target_datetime=datetime(2018, 3, 13, 12, 0))'\n    )\n    pprint(\n        fetch_exchange(\"US-NY\", \"CA-QC\", target_datetime=datetime(2018, 3, 13, 12, 0))\n    )\n\n    print(\n        'fetch_exchange(\"US-NY\", \"CA-QC\", target_datetime=datetime(2007, 3, 13, 12)))'\n    )\n    pprint(fetch_exchange(\"US-NY\", \"CA-QC\", target_datetime=datetime(2007, 3, 13, 12)))\n\n    print(\"fetch_consumption_forecast() ->\")\n    pprint(fetch_consumption_forecast())\n    \"\"\"\n\n    print(\"fetch_grid_alerts() ->\")\n    pprint(fetch_grid_alerts())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/US_PJM.py",
    "content": "\"\"\"Parser for the PJM area of the United States (US-MIDA-PJM).\"\"\"\n\nimport gzip\nimport json\nimport re\nfrom datetime import datetime, time, timedelta, timezone\nfrom itertools import groupby\nfrom logging import Logger, getLogger\nfrom operator import itemgetter\nfrom typing import Any, Literal\nfrom zoneinfo import ZoneInfo\n\nimport demjson3 as demjson\nfrom bs4 import BeautifulSoup\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    GridAlertList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    GridAlertType,\n    ProductionMix,\n    StorageMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nPARSER = \"US_PJM.py\"\nTIMEZONE = ZoneInfo(\"America/New_York\")\nZONE_KEY = ZoneKey(\"US-MIDA-PJM\")\n# Used for production and consumption forecast data (https://dataminer2.pjm.com/list)\nDATA_MINER_API_ENDPOINT = \"https://api.pjm.com/api/v1/\"\n\n\nUS_PROXY = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app\"\nDATA_PATH = \"api/v1\"\n\nSOURCE = \"pjm.com\"\n\nZONE_TO_PJM_INTERFACES = {\n    ZoneKey(\"US-MIDW-MISO\"): [\"MISO\"],  # \"MISO LMP\"\n    # ?: [\"DEOK|OVEC\"],  # Ohio Valley Electric Corporation (OVEC)\n    ZoneKey(\"US-MIDW-LGEE\"): [\n        \"SOUTH|LGEE\"\n    ],  # Louisville Gas and Electric Company (LGEE)\n    ZoneKey(\"US-TEN-TVA\"): [\"SOUTH|TVA\"],  # Tennessee Valley Authority (TVA)\n    ZoneKey(\"US-CAR-CPLW\"): [\"SOUTH|CPLW\"],  # CPL Retail Energy West (CPLW)\n    ZoneKey(\"US-CAR-DUK\"): [\"SOUTH|DUKE\"],  # Duke Energy\n    ZoneKey(\"US-CAR-CPLE\"): [\"SOUTH|CPLE\"],  # CPL Retail Energy East (CPLE)\n    ZoneKey(\"US-NY-NYIS\"): [\n        \"NEPTUNE|SAYR\",  # NYISO (Neptune)\n        \"LINDENVFT|LINDEN\",  # NYISO (Linden)\n        \"HUDSONTP|HTP\",  # NYISO (Hudson)\n        \"NYIS|NYIS\",  # \"NYISO LMP\"\n    ],\n}\n\nFUEL_MAPPING = {\n    \"Coal\": \"coal\",\n    \"Gas\": \"gas\",\n    \"Hydro\": \"hydro\",\n    \"Multiple Fuels\": \"unknown\",\n    \"Nuclear\": \"nuclear\",\n    \"Oil\": \"oil\",\n    \"Other\": \"unknown\",\n    \"Other Renewables\": \"unknown\",\n    \"Solar\": \"solar\",\n    \"Storage\": \"battery\",\n    \"Wind\": \"wind\",\n}\n\n\ndef _get_api_subscription_key(session: Session) -> str:\n    response = session.get(\"https://dataminer2.pjm.com/config/settings.json\")\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Could not get API key: {response.status_code}: {response.text}\",\n        )\n    return response.json()[\"subscriptionKey\"]\n\n\ndef _fetch_api_data(\n    kind: Literal[\n        \"load_frcstd_7_day\",\n        \"gen_by_fuel\",\n        \"hourly_solar_power_forecast\",\n        \"hourly_wind_power_forecast\",\n    ],\n    params: dict,\n    session: Session,\n) -> dict:\n    headers = {\n        \"Ocp-Apim-Subscription-Key\": _get_api_subscription_key(session=session),\n        \"Accept-Encoding\": \"identity\",\n    }\n    url = f\"{US_PROXY}/{DATA_PATH}/{kind}\"\n    resp: Response = session.get(\n        url=url, params={\"host\": \"https://api.pjm.com\", **params}, headers=headers\n    )\n    if (resp.status_code == 200) and (kind != \"load_frcstd_7_day\"):\n        data = resp.json()\n        return data\n    elif (resp.status_code == 200) and (kind == \"load_frcstd_7_day\"):\n        decompressed_data = gzip.decompress(resp.content)\n        data = json.loads(decompressed_data)\n        return data\n    else:\n        raise ParserException(\n            PARSER,\n            f\"{kind} data is not available in the API: {resp.status_code}: {resp.text}\",\n        )\n\n\ndef fetch_consumption_forecast(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Gets consumption forecast 7 days ahead for PJM zone. Hourly data in MW.\"\"\"\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER, \"This parser is not yet able to parse historical data\", zone_key\n        )\n\n    session = session or Session()\n    # startRow must be set if forecast_area is set. RTO_COMBINED is area for whole PJM zone.\n    params = {\"download\": True, \"startRow\": 1, \"forecast_area\": \"RTO_COMBINED\"}\n    data = _fetch_api_data(kind=\"load_frcstd_7_day\", params=params, session=session)\n\n    consumption_list = TotalConsumptionList(logger)\n    for elem in data:\n        utc_datetime = elem[\"forecast_datetime_beginning_utc\"]\n        consumption_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(utc_datetime).replace(tzinfo=timezone.utc),\n            source=SOURCE,\n            consumption=elem[\"forecast_load_mw\"],\n            sourceType=EventSourceType.forecasted,\n        )\n    return consumption_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Uses PJM API to get generation by fuel.\n\n    We assume that storage is battery storage (see https://learn.pjm.com/energy-innovations/energy-storage)\n    \"\"\"\n    target_datetime = (\n        datetime.now(timezone.utc).replace(hour=0, minute=0, second=0, microsecond=0)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n\n    session = session or Session()\n\n    params = {\n        \"startRow\": 1,\n        \"rowCount\": 500,\n        \"fields\": \"datetime_beginning_utc,fuel_type,mw\",\n        \"datetime_beginning_utc\": target_datetime.strftime(\"%Y-%m-%dT%H:00:00.0000000\"),\n    }\n    resp_data = _fetch_api_data(kind=\"gen_by_fuel\", params=params, session=session)\n\n    items = resp_data.get(\"items\", [])\n\n    if items == []:\n        raise ParserException(\n            parser=PARSER,\n            message=f\"{target_datetime}: Production data is not available in the API\",\n            zone_key=zone_key,\n        )\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n    for key, group in groupby(items, itemgetter(\"datetime_beginning_utc\")):\n        dt = datetime.fromisoformat(key).replace(tzinfo=timezone.utc)\n        production = ProductionMix()\n        storage = StorageMix()\n        for data in group:\n            mode = FUEL_MAPPING[data[\"fuel_type\"]]\n            value = data[\"mw\"]\n            if mode == \"battery\":\n                storage.add_value(mode, -value)\n            else:\n                production.add_value(mode, value)\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            production=production,\n            storage=storage,\n            source=SOURCE,\n        )\n\n    return production_breakdown_list.to_list()\n\n\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Uses PJM API to request the wind and solar forecast (in MW) for a given date in hourly intervals.\"\"\"\n\n    session = session or Session()\n\n    # Datetime\n    target_datetime = (\n        datetime.now(timezone.utc).replace(hour=0, minute=0, second=0, microsecond=0)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n\n    # Config for url\n    params = {\n        \"startRow\": 1,\n        \"rowCount\": 10000,\n        \"datetime_beginning_utc\": target_datetime.strftime(\"%Y-%m-%dT%H:00:00.0000000\"),\n    }\n\n    resp_data_wind = _fetch_api_data(\n        kind=\"hourly_wind_power_forecast\", params=params, session=session\n    )\n    items_wind = resp_data_wind.get(\"items\", [])\n\n    resp_data_solar = _fetch_api_data(\n        kind=\"hourly_solar_power_forecast\", params=params, session=session\n    )\n    items_solar = resp_data_solar.get(\"items\", [])\n\n    # Combine wind and solar data and sort by datetime_beginning_utc\n    items = items_wind + items_solar\n    items.sort(key=itemgetter(\"datetime_beginning_utc\", \"evaluated_at_utc\"))\n    production_list = ProductionBreakdownList(logger)\n\n    # Group by datetime_beginning_utc and get the last evaluated_at_utc entry for each group\n    for datetime_utc, group in groupby(items, key=itemgetter(\"datetime_beginning_utc\")):\n        group_list = list(group)\n        wind_entries = [entry for entry in group_list if \"wind_forecast_mwh\" in entry]\n        latest_entry_wind = max(wind_entries, key=itemgetter(\"evaluated_at_utc\"))\n        solar_entries = [entry for entry in group_list if \"solar_forecast_mwh\" in entry]\n        latest_entry_solar = max(solar_entries, key=itemgetter(\"evaluated_at_utc\"))\n\n        production_mix = ProductionMix()\n        production_mix.add_value(\n            \"solar\",\n            latest_entry_solar[\"solar_forecast_mwh\"],\n            correct_negative_with_zero=True,\n        )\n        production_mix.add_value(\n            \"wind\",\n            latest_entry_wind[\"wind_forecast_mwh\"],\n            correct_negative_with_zero=True,\n        )\n\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(datetime_utc).replace(tzinfo=timezone.utc),\n            production=production_mix,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n\n    return production_list.to_list()\n\n\ndef _get_interface_data(\n    interface: str, session: Session\n) -> list[tuple[datetime, float]]:\n    \"\"\"Fetches 5min data for any PJM interface in the current day.\"\"\"\n\n    # For some reason the US-MIDW-MISO data is on a chart at a different url\n    if interface == \"MISO\":\n        url = \"https://www.pjm.com/Charts/MISO.aspx\"\n    else:\n        url = f\"http://www.pjm.com/Charts/InterfaceChartDM2.aspx?open={interface}\"\n\n    response = session.get(url)\n\n    soup = BeautifulSoup(response.text, \"html.parser\")\n    scripts = soup.find(\n        \"script\",\n        {\n            \"type\": \"text/javascript\",\n            \"src\": \"/assets/js/Highcharts/HighCharts/highcharts.js\",\n        },\n    )\n    exchange_script = scripts.find_next_sibling(\"script\")\n\n    # x-axis (time)\n    time_pattern = r\"var timeArray = (\\[(.*)\\])\"\n    time_array = re.search(time_pattern, str(exchange_script)).group(1)\n    time_vals = demjson.decode(time_array)\n\n    # y-axis [right] (actual & scheduled load)\n    load_pattern = r\"var load = (\\[(.*)\\])\"\n    load = re.search(load_pattern, str(exchange_script)).group(1)\n    load_actual = demjson.decode(load)[0]\n\n    converted_flows = []\n    today = datetime.combine(datetime.now(TIMEZONE), time(), tzinfo=TIMEZONE)\n    for t, flow in zip(time_vals, load_actual, strict=True):\n        # some tail values might be null\n        if flow is None:\n            continue\n\n        # make sure to use %I and not %H for %p to take effect\n        time_of_the_day = datetime.strptime(t, \"%I:%M %p\").replace(tzinfo=TIMEZONE)\n        dt = today.replace(hour=time_of_the_day.hour, minute=time_of_the_day.minute)\n\n        converted_flows.append((dt, float(flow)))\n\n    return converted_flows\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known power exchange (in MW) between two zones.\"\"\"\n\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER,\n            \"This parser is not yet able to parse historical data\",\n            sorted_zone_keys,\n        )\n\n    if not session:\n        session = Session()\n\n    # PJM reports exports as negative.\n    direction = -1 if sorted_zone_keys.startswith(ZONE_KEY) else 1\n\n    neighbour = zone_key2 if zone_key1 == ZONE_KEY else zone_key1\n    interfaces = ZONE_TO_PJM_INTERFACES[neighbour]\n\n    # get flow data from each interface with neighbour and merge\n    session = session or Session()\n    ungrouped_exchange_lists = []\n    for interface in interfaces:\n        exchange_list = ExchangeList(logger)\n\n        interface_data = _get_interface_data(interface, session=session)\n        for dt, net_flow in interface_data:\n            exchange_list.append(\n                zoneKey=sorted_zone_keys,\n                datetime=dt,\n                source=SOURCE,\n                netFlow=direction * net_flow,\n            )\n\n        ungrouped_exchange_lists.append(exchange_list)\n\n    return ExchangeList.merge_exchanges(ungrouped_exchange_lists, logger).to_list()\n\n\ndef fetch_grid_alerts(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    GRID_ALERTS_PATH = \"ep/pages/dashboard.jsf\"\n    GRID_ALERTS_SOURCE = \"https://emergencyprocedures.pjm.com\"\n\n    if target_datetime is not None:\n        raise ParserException(\n            PARSER,\n            \"This parser is not yet able to parse historical data\",\n            zone_key,\n        )\n\n    session = session or Session()\n\n    url = f\"{US_PROXY}/{GRID_ALERTS_PATH}\"\n    headers = {\n        \"Accept-Encoding\": \"identity\",\n    }\n    response: Response = session.get(\n        url=url,\n        params={\n            \"host\": GRID_ALERTS_SOURCE,\n        },\n        headers=headers,\n    )\n\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching grid alerts error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    soup = BeautifulSoup(response.text, \"html.parser\")\n    tbody = soup.find(\"tbody\", {\"id\": \"frmTable:tblPostings_data\"})\n    if not tbody:\n        raise ParserException(\n            PARSER,\n            f\"BeautifulSoup could not find the tbody element in the response from {GRID_ALERTS_SOURCE}/{GRID_ALERTS_PATH}, error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    alerts = GridAlertList(logger)\n    for i, alert in enumerate(tbody.children):\n        alertType = extract_alert_type(alert, i)\n        message = extract_message(alert, i)\n        startTime, endTime = extract_start_and_end_time(alert, i)\n        locationRegion = alert.find(class_=re.compile(r\"region-name\")).text.strip()\n\n        alerts.append(\n            zoneKey=ZONE_KEY,\n            locationRegion=locationRegion,\n            source=SOURCE,\n            alertType=alertType,\n            message=message,\n            issuedTime=startTime,\n            startTime=startTime,\n            endTime=endTime,\n        )\n    return alerts.to_list()\n\n\ndef extract_alert_type(alert: BeautifulSoup, i: int) -> GridAlertType:\n    alertType = alert.find(\n        \"span\",\n        {\"id\": re.compile(f\"frmTable:tblPostings:{i}:j_idt\\\\d+:txtPriority\")},\n    ).text.strip()\n    if alertType == \"Action\":\n        return GridAlertType.action\n    else:\n        return GridAlertType.informational\n\n\ndef extract_message(alert: BeautifulSoup, i: int) -> str:\n    messageBody = alert.find(\n        \"span\", {\"id\": f\"frmTable:tblPostings:{i}:txtMessage\"}\n    ).text.strip()\n    topic = alert.find(\n        \"span\",\n        {\"id\": re.compile(f\"frmTable:tblPostings:{i}:j_idt\\\\d+:txtMessageTypeName\")},\n    ).text.strip()\n    return f\"{topic}\\n{messageBody}\"\n\n\ndef extract_start_and_end_time(\n    alert: BeautifulSoup, i: int\n) -> tuple[datetime, datetime]:\n    startTime = alert.find(\n        \"span\", {\"id\": f\"frmTable:tblPostings:{i}:txtEffectiveStartTime\"}\n    ).text.strip()\n    endTime = alert.find(\n        \"span\", {\"id\": f\"frmTable:tblPostings:{i}:txtEffectiveEndTime\"}\n    ).text.strip()\n    startTime = datetime.strptime(startTime, \"%m.%d.%Y %H:%M\").replace(tzinfo=TIMEZONE)\n    if endTime != \"\":\n        endTime = datetime.strptime(endTime, \"%m.%d.%Y %H:%M\").replace(tzinfo=TIMEZONE)\n    else:\n        endTime = None\n    return startTime, endTime\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_consumption_forecast() ->\")\n    print(fetch_consumption_forecast())\n\n    # print(\"fetch_production() ->\")\n    # print(fetch_production())\n\n    \"\"\"\n    for neighbor in [\n        \"US-CAR-DUK\",\n        \"US-CAR-CPLE\",\n        \"US-CAR-CPLW\",\n        \"US-MIDW-LGEE\",\n        \"US-MIDW-MISO\",\n        \"US-NY-NYIS\",\n        \"US-TEN-TVA\",\n    ]:\n        print(f\"fetch_exchange(US-MIDA-PJM, {neighbor}) ->\")\n        print(fetch_exchange(ZONE_KEY, ZoneKey(neighbor)))\n    \"\"\"\n    # print(\"fetch_wind_solar_forecasts() ->\")\n    # print(fetch_wind_solar_forecasts())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/US_PREPA.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"\nReal-time parser for Puerto Rico.\n\nFetches data from various pages embedded as an iframe at https://aeepr.com/en-us/Pages/Generaci%C3%B3n.aspx\n\nThe electricity authority is known in English as PREPA (Puerto Rico Electric Power Authority) and in Spanish as AEEPR (Autoridad de Energía Eléctrica Puerto Rico)\n\"\"\"\n\nimport json\nimport re\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nTIMEZONE = ZoneInfo(\"America/Puerto_Rico\")\n\nUS_PROXY = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app\"\nHOST_PARAMETER = \"?host=https://aeepr.com\"\nGENERATION_BREAKDOWN_URL = (\n    f\"{US_PROXY}/es-pr/generacion/Documents/combustibles.aspx{HOST_PARAMETER}\"\n)\nRENEWABLES_BREAKDOWN_URL = (\n    f\"{US_PROXY}/es-pr/generacion/Documents/Unidades_renovables.aspx{HOST_PARAMETER}\"\n)\nTIMESTAMP_URL = (\n    f\"{US_PROXY}/es-pr/generacion/Documents/CostosCombustible.aspx{HOST_PARAMETER}\"\n)\n\n\ndef extract_data(html):\n    \"\"\"Extracts data from the source code of an HTML page with a FusionCharts chart\"\"\"\n    dataSource = re.search(r\"dataSource: (\\{.+\\}\\]\\})\\}\\);\", html).group(\n        1\n    )  # Extract object with data\n    dataSource = re.sub(\n        r\",\\s*\\}\", \"}\", dataSource\n    )  # ,} is valid JavaScript but not valid JSON\n    dataSource = json.loads(dataSource)\n    sourceData = dataSource[\n        \"data\"\n    ]  # The rest of the dataSource object contains unnecessary stuff like chart theme, label, axis names etc.\n    return sourceData\n\n\ndef convert_timestamp(\n    zone_key: str, timestamp_string: str, logger: Logger = getLogger(__name__)\n):\n    \"\"\"Converts timestamp fetched from website into timezone-aware datetime object.\n\n    Arguments:\n    ----------\n    timestamp_string: timestamp in the format 06/01/2020 08:40:00 AM\n    \"\"\"\n    timestamp_string = re.sub(\n        r\"\\s+\", \" \", timestamp_string\n    )  # Replace double spaces with one\n    timestamp = datetime.strptime(timestamp_string, \"%m/%d/%Y %I:%M:%S %p\").replace(\n        tzinfo=TIMEZONE\n    )\n    logger.debug(f\"PARSED TIMESTAMP {timestamp}\", extra={\"key\": zone_key})\n    return timestamp\n\n\ndef fetch_production(\n    zone_key: str = \"US-PR\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the last known production mix (in MW) of a given region.\"\"\"\n\n    global renewable_output\n\n    if target_datetime is not None:\n        raise NotImplementedError(\n            \"The datasource currently implemented is only real time\"\n        )\n\n    r = session or Session()\n\n    data = {  # To be returned as response data\n        \"zoneKey\": zone_key,\n        #'datetime': '2017-01-01T00:00:00Z',\n        \"production\": {\n            \"biomass\": 0.0,\n            \"coal\": 0.0,\n            \"gas\": 0.0,\n            \"hydro\": 0.0,\n            \"nuclear\": 0.0,\n            \"oil\": 0.0,\n            \"solar\": 0.0,\n            \"wind\": 0.0,\n            \"geothermal\": 0.0,\n            \"unknown\": 0.0,\n        },\n        #   'storage': {\n        #        'hydro': -10.0,\n        #    },\n        \"source\": \"aeepr.com\",\n    }\n\n    renewable_output = 0.0  # Temporarily stored here. We'll subtract solar, wind and biomass (landfill gas) from it and assume the remainder, if any,  is hydro\n\n    # Step 1: fetch production by generation type\n    # Note: seems to be rounded down (to an integer)\n    # Total at the top of the page fetched in step 3 isn't rounded down, but seems to be lagging behind sometimes.\n    # Difference is only minor, so for now we will IGNORE that total (instead of trying to parse the total and addding the difference to \"unknown\")\n    res = r.get(GENERATION_BREAKDOWN_URL)\n\n    assert res.status_code == 200, (\n        \"Exception when fetching production for \"\n        f\"{zone_key}: error when calling url={GENERATION_BREAKDOWN_URL}\"\n    )\n\n    sourceData = extract_data(res.text)\n\n    logger.debug(f\"Raw generation breakdown: {sourceData}\", extra={\"key\": zone_key})\n\n    for item in sourceData:  # Item has a label with fuel type + generation in MW, and a value with a percentage\n        if item[\"label\"] == \"  MW\":  # There's one empty item for some reason. Skip it.\n            continue\n\n        logger.debug(item[\"label\"], extra={\"key\": zone_key})\n\n        parsedLabel = re.search(r\"^(.+?)\\s+(\\d+)\\s+MW$\", item[\"label\"])\n\n        category = parsedLabel.group(1)  # E.g. GAS NATURAL\n        outputInMW = float(parsedLabel.group(2))\n\n        if category == \"BUNKER C\" or category == \"DIESEL CC\" or category == \"DIESEL GT\":\n            data[\"production\"][\"oil\"] += outputInMW\n        elif category == \"GAS NATURAL\":\n            data[\"production\"][\"gas\"] += outputInMW\n        elif category == \"CARBON\":\n            data[\"production\"][\"coal\"] += outputInMW\n        elif category == \"RENOVABLES\":\n            renewable_output += outputInMW  # Temporarily store aggregate renewable output. We'll subtract solar, wind and biomass (landfill gas) from it and assume the remainder, if any,  is hydro\n        else:\n            logger.warn(\n                f'Unknown energy type \"{category}\" is present for Puerto Rico',\n                extra={\"key\": zone_key},\n            )\n\n        logger.info(\n            f'Category \"{category}\" produces {outputInMW}MW', extra={\"key\": zone_key}\n        )\n\n    # Step 2: fetch renewable production breakdown\n    # Data from this source isn't rounded. Assume renewable production not accounted for is hydro\n    res = r.get(RENEWABLES_BREAKDOWN_URL)\n\n    assert res.status_code == 200, (\n        \"Exception when fetching renewable production for \"\n        f\"{zone_key}: error when calling url={RENEWABLES_BREAKDOWN_URL}\"\n    )\n\n    sourceData = extract_data(res.text)\n    logger.debug(\n        f\"Raw renewable generation breakdown: {sourceData}\", extra={\"key\": zone_key}\n    )\n\n    original_renewable_output = renewable_output  # If nothing gets subtracted renewable_output, there probably was no data on the renewables breakdown page\n\n    logger.debug(\n        f\"Total (unspecified) renewable output from total generation breakdown: {original_renewable_output}MW\",\n        extra={\"key\": zone_key},\n    )\n\n    for item in sourceData:  # Somewhat different from above, the item's label has the generation type and the item's value has generation in MW\n        if item[\"label\"] == \"  \":  # There's one empty item for some reason. Skip it.\n            continue\n\n        if item[\"label\"] == \"Solar\":\n            data[\"production\"][\"solar\"] += float(item[\"value\"])\n        elif item[\"label\"] == \"Eolica\":\n            data[\"production\"][\"wind\"] += float(item[\"value\"])\n        elif item[\"label\"] == \"Landfill Gas\":\n            data[\"production\"][\"biomass\"] += float(item[\"value\"])\n        else:\n            logger.warn(\n                f'Unknown renewable type \"{item[\"label\"]}\" is present for Puerto Rico',\n                extra={\"key\": zone_key},\n            )\n\n        renewable_output -= float(\n            item[\"value\"]\n        )  # Subtract production accounted for from the renewable output total\n\n        logger.info(\n            f'Renewable \"{item[\"label\"]}\" produces {item[\"value\"]}MW',\n            extra={\"key\": zone_key},\n        )\n        logger.debug(\n            f\"Renewable output yet to be accounted for: {renewable_output}MW\",\n            extra={\"key\": zone_key},\n        )\n\n    logger.debug(\n        \"Rounding remaining renewable output to 14 decimal places to get rid of floating point errors\"\n    )\n    renewable_output = round(renewable_output, 14)\n\n    logger.info(\n        f\"Remaining renewable output not accounted for: {renewable_output}MW\",\n        extra={\"key\": zone_key},\n    )\n\n    # Assume renewable generation not accounted for is hydro - if we could fetch the other renewable generation data\n    if renewable_output >= 0.0:\n        if (\n            original_renewable_output == renewable_output\n        ):  # Nothing got subtracted for Solar, Wind or Landfill gas - so the page probably didn't contain any data. Renewable type=unknown\n            logger.warning(\n                f\"Renewable generation breakdown page was empty, reporting unspecified renewable output ({renewable_output}MW) as 'unknown'\",\n                extra={\"key\": zone_key},\n            )\n            data[\"production\"][\"unknown\"] += renewable_output\n        else:  # Otherwise, any remaining renewable output is probably hydro\n            logger.info(\n                f\"Assuming remaining renewable output of {renewable_output}MW is hydro\",\n                extra={\"key\": zone_key},\n            )\n            data[\"production\"][\"hydro\"] += renewable_output\n    else:\n        logger.warn(\n            f\"Renewable generation breakdown page total is greater than total renewable output, a difference of {renewable_output}MW\",\n            extra={\"key\": zone_key},\n        )\n\n    # Step 3: fetch the timestamp, which is at the bottom of a different iframe\n    # Note: there's a race condition here when requesting data very close to <hour>:10 and <hour>:40, which is when the data gets updated\n    # Sometimes it's some seconds later, so we grab the timestamp from here to know the exact moment\n\n    res = r.get(\n        TIMESTAMP_URL\n    )  # TODO do we know for sure the timestamp on this page gets updated *every time* the generation breakdown gets updated?\n\n    assert res.status_code == 200, (\n        f\"Exception when fetching timestamp for {zone_key}: error when calling url={TIMESTAMP_URL}\"\n    )\n\n    raw_timestamp_match = re.search(\n        r\"Ultima Actualizaci�n:  ((?:0[1-9]|1[0-2])/(?:[0-2][0-9]|3[0-2])/2[01][0-9]{2}  [0-2][0-9]:[0-5][0-9]:[0-5][0-9] [AP]M)\",\n        res.text,\n    )\n\n    if raw_timestamp_match is None:\n        raise Exception(f\"Could not find timestamp in {res.text}\")\n\n    raw_timestamp = raw_timestamp_match.group(1)\n\n    logger.debug(f\"RAW TIMESTAMP: {raw_timestamp}\", extra={\"key\": zone_key})\n\n    data[\"datetime\"] = convert_timestamp(zone_key, raw_timestamp)\n\n    assert data[\"production\"][\"oil\"] > 0.0, (\n        f\"{zone_key} is missing required generation type: oil\"\n    )\n\n    return data\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n# TODO add forecast parser\n#    print('fetch_generation_forecast() ->')\n#    print(fetch_generation_forecast())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/US_SPP.py",
    "content": "#!usr/bin/env python3\n\n\"\"\"Parser for the Southwest Power Pool area of the United States.\"\"\"\n\nimport math\nfrom datetime import datetime, timedelta, timezone\nfrom io import StringIO\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom dateutil import parser\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    LocationalMarginalPriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import (\n    EventSourceType,\n    ProductionMix,\n)\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.validation import validate_exchange\nfrom electricitymap.contrib.types import ZoneKey\n\nSOURCE = \"spp.org\"\nUS_PROXY = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app\"\nHOST_PARAMETER = \"host=https://marketplace.spp.org\"\n\nHISTORIC_GENERATION_BASE_URL = f\"{US_PROXY}/file-browser-api/download/generation-mix-historical?{HOST_PARAMETER}&path=\"\n\nSPP_PORTAL = \"host=https://portal.spp.org\"\nDAYAHEAD_PRICE_URL = (\n    f\"{US_PROXY}/file-browser-api/download/da-lmp-by-location?{SPP_PORTAL}\"\n)\nREALTIME_PRICE_URL = (\n    f\"{US_PROXY}/file-browser-api/download/rtbm-lmp-by-location?{SPP_PORTAL}\"\n)\n\nGENERATION_URL = f\"{US_PROXY}/chart-api/gen-mix/asFile?{HOST_PARAMETER}\"\n\nEXCHANGE_URL = f\"{US_PROXY}/chart-api/interchange-trend/asFile?{HOST_PARAMETER}\"\nHISTORICAL_EXCHANGE_URL = (\n    f\"{US_PROXY}/file-browser-api/download/historical-tie-flow?{HOST_PARAMETER}&path=\"\n)\n\nMAPPING = {\n    \"Wind\": \"wind\",\n    \"Nuclear\": \"nuclear\",\n    \"Hydro\": \"hydro\",\n    \"Solar\": \"solar\",\n    \"Natural Gas\": \"gas\",\n    \"Diesel Fuel Oil\": \"oil\",\n    \"Waste Disposal Services\": \"biomass\",\n    \"Coal\": \"coal\",\n    \"Other\": \"unknown\",\n    \"Waste Heat\": \"unknown\",\n}\n\nTIE_MAPPING = {\"US-MISO->US-SPP\": [\"AMRN\", \"DPC\", \"GRE\", \"MDU\", \"MEC\", \"NSP\", \"OTP\"]}\n\nEXCHANGE_MAPPING = {\n    \"AECI\": \"US-MIDW-AECI\",\n    \"AMRN\": \"US-MIDW-MISO\",\n    \"BLKW\": \"US-NW-PNM\",\n    \"CLEC\": \"US-MIDW-MISO\",\n    \"EDDY\": \"US-SW-EPE\",\n    \"EES\": \"US-MIDW-MISO\",\n    \"ERCOTE\": \"US-TEX-ERCO\",\n    \"ERCOTN\": \"US-TEX-ERCO\",\n    \"LAMAR\": \"US-NW-PSCO\",\n    \"MEC\": \"US-MIDW-MISO\",\n    \"SCSE\": \"US-NW-WACM\",\n    \"SOUC\": \"US-SE-SOCO\",\n    \"SPA\": \"US-CENT-SPA\",\n    \"TVA\": \"US-TEN-TVA\",\n    \"RCEAST\": \"US-NW-WAUW\",\n    \"SPC\": \"CA-SK\",\n    \"MCWEST\": \"US-NW-WAUW\",\n    \"SGE\": \"US-NW-WACM\",\n    \"ALTW\": \"US-MIDW-MISO\",\n    \"DPC\": \"US-MIDW-MISO\",\n    \"GRE\": \"US-MIDW-MISO\",\n    \"MDU\": \"US-MIDW-MISO\",\n    \"NSP\": \"US-MIDW-MISO\",\n    \"OTP\": \"US-MIDW-MISO\",\n}\n# NOTE\n# Data sources return timestamps in GMT.\n# Energy storage situation unclear as of 16/03/2018, likely to change quickly in future.\n\n\ndef get_data(url, session: Session | None = None):\n    \"\"\"Returns a pandas dataframe.\"\"\"\n\n    s = session or Session()\n    req = s.get(url)\n\n    if req.text == \"\":\n        return pd.DataFrame()\n\n    df = pd.read_csv(StringIO(req.text))\n\n    return df\n\n\ndef data_processor(df, logger: Logger) -> list[tuple[datetime, ProductionMix]]:\n    \"\"\"\n    Takes a dataframe and logging instance as input.\n    Checks for new generation types and logs a warning if any are found.\n    Parses the dataframe row by row removing unneeded keys.\n\n    :return: list of tuples containing a datetime object and production dictionary.\n    \"\"\"\n\n    # Remove leading whitespace in column headers.\n    df.columns = df.columns.str.strip()\n    df = df.rename(\n        columns={\"Gas Self\": \"Natural Gas Self\"}\n    )  # Fix naming error which otherwise misclassifies Gas Self as Unknown\n    # Some historical csvs split the production into 'Market' and 'Self',\n    # So first we need to combine those.\n    for col in df.columns:\n        if \"Market\" in col:\n            combined_col = col.replace(\"Market\", \"\").strip()\n            self_col = col.replace(\"Market\", \"Self\")\n            if self_col in df.columns:\n                df[combined_col] = df[col] + df[self_col]\n                df.drop(self_col, inplace=True, axis=1)\n            else:\n                logger.warning(\n                    f'Corresponding column \"{self_col}\" to \"{col}\" not found in file',\n                    extra={\"key\": \"US-SPP\"},\n                )\n                df[combined_col] = df[col]\n\n            df.drop(col, inplace=True, axis=1)\n\n    keys_to_remove = {\"GMT MKT Interval\", \"Average Actual Load\", \"Load\"}\n\n    # Check for new generation columns.\n    known_keys = MAPPING.keys() | keys_to_remove\n    column_headers = set(df.columns)\n\n    unknown_keys = column_headers - known_keys\n\n    for heading in unknown_keys:\n        logger.warning(\n            f\"New column '{heading}' present in US-SPP data source.\",\n            extra={\"key\": \"US-SPP\"},\n        )\n\n    processed_data = []\n    for index in range(len(df)):\n        mix = ProductionMix()\n        production = df.iloc[index].to_dict()\n        dt_aware = production[\"GMT MKT Interval\"].to_pydatetime()\n        for k in keys_to_remove | unknown_keys:\n            production.pop(k, None)\n\n        for k, v in production.items():\n            mix.add_value(MAPPING[k], float(v))\n        processed_data.append((dt_aware, mix))\n    return processed_data\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the last known production mix (in MW) of a given zone.\"\"\"\n\n    if target_datetime is not None:\n        # check if target_datetime is timezone naive\n        # https://docs.python.org/3/library/datetime.html#determining-if-an-object-is-aware-or-naive\n        if (\n            target_datetime.tzinfo is None  # order is important here\n            or target_datetime.tzinfo.utcoffset(target_datetime) is None\n        ):\n            target_datetime = target_datetime.replace(tzinfo=timezone.utc)\n        current_year = datetime.now().year\n        target_year = target_datetime.year\n\n        # Check if datetime is too far in the past\n        if target_year < 2011:\n            raise NotImplementedError(\"Data before 2011 not available from this source\")\n\n        # Check if datetime in current year, or past year\n        if target_year == current_year:\n            filename = \"GenMixYTD.csv\"\n        else:\n            filename = f\"GenMix_{target_year}.csv\"\n\n        historic_generation_url = HISTORIC_GENERATION_BASE_URL + filename\n        raw_data = get_data(historic_generation_url, session=session)\n        # In some cases the timeseries column is named differently, so we standardize it\n        raw_data.rename(columns={\"GMTTime\": \"GMT MKT Interval\"}, inplace=True)\n\n        raw_data[\"GMT MKT Interval\"] = pd.to_datetime(\n            raw_data[\"GMT MKT Interval\"], utc=True\n        )\n        end = target_datetime\n        start = target_datetime - timedelta(days=1)\n        start = max(start, raw_data[\"GMT MKT Interval\"].min())\n        raw_data = raw_data[\n            (raw_data[\"GMT MKT Interval\"] >= start)\n            & (raw_data[\"GMT MKT Interval\"] <= end)\n        ]\n    else:\n        raw_data = get_data(GENERATION_URL, session=session)\n        raw_data[\"GMT MKT Interval\"] = pd.to_datetime(raw_data[\"GMT MKT Interval\"])\n\n    processed_data = data_processor(raw_data, logger)\n\n    production_list = ProductionBreakdownList(logger)\n    for dt, mix in processed_data:\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=dt.replace(tzinfo=timezone.utc),\n            production=mix,\n            source=SOURCE,\n        )\n\n    return production_list.to_list()\n\n\ndef _NaN_safe_get(forecast: dict, key: str) -> float:\n    try:\n        return float(forecast[key])\n    except ValueError:\n        return math.nan\n\n\ndef fetch_load_forecast(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the load forecast (in MW) of a given zone.\"\"\"\n\n    if not target_datetime:\n        target_datetime = datetime.now()\n\n    if isinstance(target_datetime, datetime):\n        dt = target_datetime\n    else:\n        dt = parser.parse(target_datetime)\n    LOAD_URL = f\"{US_PROXY}/chart-api/load-forecast/asFile?{HOST_PARAMETER}\"\n\n    raw_data = get_data(LOAD_URL)\n\n    consumption_list = TotalConsumptionList(logger)\n    for index in range(len(raw_data)):\n        forecast = raw_data.loc[index].to_dict()\n\n        dt = parser.parse(forecast[\"GMTIntervalEnd\"]).replace(tzinfo=timezone.utc)\n        load = _NaN_safe_get(forecast, \"STLF\")  # short term load forecast\n        if math.isnan(load):\n            load = _NaN_safe_get(forecast, \"MTLF\")  # medium term load forecast\n        if math.isnan(load):\n            # STLF is reported every 5 minutes while MTLF is reported once every hour so we know load is None at times like 12.05, 12.10, etc\n            logger.warning(f\"fetch_load_forecast: {dt} has no forecasted load\")\n            # Drop there data points to prevent errors in .append\n            continue\n\n        consumption_list.append(\n            datetime=dt,\n            consumption=load,\n            zoneKey=zone_key,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n\n    return consumption_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_wind_solar_forecasts(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"Requests the load forecast (in MW) of a given zone.\"\"\"\n\n    if not target_datetime:\n        target_datetime = datetime.now()\n\n    if isinstance(target_datetime, datetime):\n        dt = target_datetime\n    else:\n        dt = parser.parse(target_datetime)\n\n    FORECAST_URL_PATH = f\"%2F{dt.year}%2F{dt.month:02d}%2F{dt.day:02d}%2FOP-MTRF-{dt.year}{dt.month:02d}{dt.day:02d}0000.csv\"\n    FORECAST_URL = (\n        f\"{US_PROXY}/file-browser-api/download/midterm-resource-forecast?{HOST_PARAMETER}&path=\"\n        + FORECAST_URL_PATH\n    )\n\n    try:\n        raw_data = get_data(FORECAST_URL)\n    except pd.errors.ParserError:\n        logger.error(\n            f\"fetch_wind_solar_forecasts: {dt} has no forecast for url: {FORECAST_URL}\"\n        )\n        return []\n\n    # sometimes there is a leading whitespace in column names\n    raw_data.columns = raw_data.columns.str.lstrip()\n\n    production_list = ProductionBreakdownList(logger)\n    for index in range(len(raw_data)):\n        forecast = raw_data.loc[index].to_dict()\n\n        dt = parser.parse(forecast[\"GMTIntervalEnd\"]).replace(tzinfo=timezone.utc)\n\n        # Get short term forecast if available, else medium term\n        solar = _NaN_safe_get(forecast, \"Solar Forecast MW\")\n        wind = _NaN_safe_get(forecast, \"Wind Forecast MW\")\n\n        if math.isnan(solar) and math.isnan(wind):\n            logger.info(\n                f\"fetch_wind_solar_forecasts: {dt} has no solar nor wind forecasted production\"\n            )\n            continue\n\n        mix = ProductionMix(solar=solar, wind=wind)\n\n        production_list.append(\n            datetime=dt,\n            production=mix,\n            zoneKey=zone_key,\n            source=SOURCE,\n            sourceType=EventSourceType.forecasted,\n        )\n\n    return production_list.to_list()\n\n\ndef fetch_live_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    data = get_data(EXCHANGE_URL, session)\n\n    data = data.dropna(axis=0)\n    data[\"GMTTime\"] = pd.to_datetime(data[\"GMTTime\"], utc=True)\n    data = data.loc[data[\"GMTTime\"] <= target_datetime]\n    data = data.set_index(\"GMTTime\")\n\n    exchanges = format_exchange_data(\n        data=data, zone_key1=zone_key1, zone_key2=zone_key2, logger=logger\n    )\n    return exchanges\n\n\ndef fetch_historical_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if target_datetime is None:\n        return []\n    filename = target_datetime.strftime(\"TieFlows_%b%Y.csv\")\n    file_url = f\"{US_PROXY}/file-browser-api/download/historical-tie-flow?{HOST_PARAMETER}&path={filename}\"\n\n    data = get_data(file_url, session)\n\n    data[\"GMTTIME\"] = pd.to_datetime(data[\"GMTTIME\"], utc=True)\n    data = data.loc[\n        (data[\"GMTTIME\"] >= target_datetime - timedelta(days=1))\n        & (data[\"GMTTIME\"] <= target_datetime)\n    ]\n    data = data.set_index(\"GMTTIME\")\n\n    exchanges = format_exchange_data(\n        data=data, zone_key1=zone_key1, zone_key2=zone_key2, logger=logger\n    )\n    return exchanges\n\n\ndef format_exchange_data(\n    data: pd.DataFrame,\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"format exchanges data into list of data points\"\"\"\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n    data = data[list(EXCHANGE_MAPPING)]\n    data = data.melt(var_name=\"zone_key2\", value_name=\"exchange\", ignore_index=False)\n    data.zone_key2 = data.zone_key2.map(EXCHANGE_MAPPING)\n\n    data_filtered = data.loc[data[\"zone_key2\"] == zone_key2]\n    data_filtered = data_filtered.groupby([data_filtered.index])[\"exchange\"].sum()\n\n    exchange_list = ExchangeList(logger)\n    for dt in data_filtered.index:\n        data_dt = data_filtered.loc[data_filtered.index == dt]\n        exchange_list.append(\n            zoneKey=sorted_zone_keys,\n            netFlow=round(data_dt.values[0], 4),\n            datetime=dt.to_pydatetime(),\n            source=SOURCE,\n        )\n\n    return [x for x in exchange_list.to_list() if validate_exchange(x, logger)]\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    now = datetime.now(tz=timezone.utc)\n    if target_datetime is None or target_datetime > now.date():\n        target_datetime = now\n        exchanges = fetch_live_exchange(\n            zone_key1, zone_key2, session, target_datetime, logger\n        )\n    elif target_datetime < datetime(2014, 3, 1, tzinfo=timezone.utc):\n        raise NotImplementedError(\n            \"Exchange data is not available from this source before 03/2014\"\n        )\n    else:\n        exchanges = fetch_historical_exchange(\n            zone_key1, zone_key2, session, target_datetime, logger\n        )\n    return exchanges\n\n\n@refetch_frequency(timedelta(minutes=30))\ndef fetch_realtime_locational_marginal_price(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=timezone.utc)\n    if target_datetime.tzinfo is None:\n        target_datetime = target_datetime.replace(tzinfo=timezone.utc)\n\n    prices = LocationalMarginalPriceList(logger)\n    # Get data for target datetime and previous 30 minutes in 5 min intervals\n    for minutes in range(0, 35, 5):\n        check_datetime = target_datetime - timedelta(minutes=minutes)\n        url = get_realtime_url(check_datetime)\n        raw_data = get_data(url, session)\n        if raw_data.empty:\n            logger.warning(f\"Empty response for {check_datetime}\")\n            continue\n\n        grouped = raw_data.groupby([\"Pnode\", \"GMTIntervalEnd\"]).first()\n\n        for (node, interval_end), row in grouped.iterrows():\n            prices.append(\n                zoneKey=zone_key,\n                datetime=datetime.strptime(interval_end, \"%m/%d/%Y %H:%M:%S\").replace(\n                    tzinfo=timezone.utc\n                ),\n                price=row[\"LMP\"],\n                currency=\"USD\",\n                node=node,\n                source=SOURCE,\n            )\n\n    price_list = prices.to_list()\n    return price_list\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_dayahead_locational_marginal_price(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=timezone.utc)\n\n    url = get_dayahead_url(target_datetime)\n    raw_data = get_data(url, session)\n    if raw_data.empty:\n        logger.warning(f\"Empty response for {target_datetime}\")\n        return []\n    # filter by column \"Settlement Location\" so it only includes SPPNORTH_HUB\n    grouped = raw_data.groupby([\"Pnode\", \"GMTIntervalEnd\"]).first()\n    prices = LocationalMarginalPriceList(logger)\n    for (node, interval_end), row in grouped.iterrows():\n        prices.append(\n            zoneKey=zone_key,\n            datetime=datetime.strptime(interval_end, \"%m/%d/%Y %H:%M:%S\").replace(\n                tzinfo=timezone.utc\n            ),\n            price=row[\"LMP\"],\n            currency=\"USD\",\n            node=node,\n            source=SOURCE,\n        )\n\n    price_list = prices.to_list()\n    return price_list\n\n\ndef get_closest_5_minutes_datetime(target_datetime: datetime) -> datetime:\n    cdt_datetime = target_datetime.astimezone(tz=ZoneInfo(\"America/Chicago\"))\n    minute = (cdt_datetime.minute // 5) * 5\n    rounded_cdt = cdt_datetime.replace(minute=minute, second=0, microsecond=0)\n    return rounded_cdt\n\n\ndef get_realtime_url(target_datetime: datetime) -> str:\n    closest_5_minutes_datetime = get_closest_5_minutes_datetime(target_datetime)\n    year = closest_5_minutes_datetime.strftime(\"%Y\")\n    month = closest_5_minutes_datetime.strftime(\"%m\")\n    day = closest_5_minutes_datetime.strftime(\"%d\")\n    hour = closest_5_minutes_datetime.strftime(\"%H\")\n    minute = closest_5_minutes_datetime.strftime(\"%M\")\n    # SPP puts the first 5 minutes of the day (00:00) in the previous day's directory\n    if minute == \"00\" and hour == \"00\":\n        one_day_before = closest_5_minutes_datetime - timedelta(days=1)\n        one_day_before_days = one_day_before.strftime(\"%d\")\n        one_day_before_month = one_day_before.strftime(\"%m\")\n        one_day_before_year = one_day_before.strftime(\"%Y\")\n\n        return f\"{REALTIME_PRICE_URL}&path=/{one_day_before_year}/{one_day_before_month}/By_Interval/{one_day_before_days}/RTBM-LMP-SL-{year}{month}{day}{hour}{minute}.csv\"\n\n    return f\"{REALTIME_PRICE_URL}&path=/{year}/{month}/By_Interval/{day}/RTBM-LMP-SL-{year}{month}{day}{hour}{minute}.csv\"\n\n\ndef get_dayahead_url(target_datetime: datetime) -> str:\n    year = target_datetime.strftime(\"%Y\")\n    month = target_datetime.strftime(\"%m\")\n    day = target_datetime.strftime(\"%d\")\n    return f\"{DAYAHEAD_PRICE_URL}&path=/{year}/{month}/By_Day/DA-LMP-SL-{year}{month}{day}0100.csv\"\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production() -> \")\n    print(fetch_production(zone_key=ZoneKey(\"US-CENT-SWPP\")))\n\n    print(\"fetch_exchange() -> \")\n    print(fetch_exchange(\"US-CENT-SWPP\", \"US-MIDW-MISO\"))\n\n    print(\"fetch_load_forecast() -> \")\n    print(\n        fetch_load_forecast(\n            zone_key=ZoneKey(\"US-CENT-SWPP\"), target_datetime=\"20190125\"\n        )\n    )\n    print(\"fetch_wind_solar_forecasts() -> \")\n    print(\n        fetch_wind_solar_forecasts(\n            zone_key=ZoneKey(\"US-CENT-SWPP\"), target_datetime=\"20221118\"\n        )\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/UY.py",
    "content": "#!/usr/bin/python3\n\nimport io\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\n\n# BeautifulSoup is used to parse HTML to get information\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.config.constants import PRODUCTION_MODES\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nUY_TZ = ZoneInfo(\"America/Montevideo\")\nUY_SOURCE = \"pronos.adme.com.uy\"\n\nADME_URL = \"https://pronos.adme.com.uy/gpf.php?fecha_ini=\"\nPRODUCTION_MODE_MAPPING = {\n    \"Salto Grande\": \"hydro\",\n    \"Bonete\": \"hydro\",\n    \"Baygorria\": \"hydro\",\n    \"Palmar\": \"hydro\",\n    \"Eólica\": \"wind\",\n    \"Solar\": \"solar\",\n    \"Térmica\": \"oil\",\n    \"Biomasa\": \"biomass\",\n}\nEXCHANGES_MAPPING = {\n    \"Exp_Intercon_ARG\": \"AR->UY\",\n    \"Exp_Intercon_BR_MELO\": \"BR-S->UY\",\n    \"Exp_Intercon_BR_RIVERA\": \"BR-S->UY\",\n    \"Imp_Intercon_AG_Imp\": \"AR->UY\",\n    \"Imp_Intercon_BR_MELO\": \"BR-S->UY\",\n    \"Imp_Intercon_BR_RIVERA\": \"BR-S->UY\",\n}\n\n\ndef get_adme_url(target_datetime: datetime, session: Session) -> str:\n    \"\"\"\"\"\"\n    next_day = target_datetime + timedelta(days=1)\n    date_format = (\n        f\"{target_datetime.day}%2F{target_datetime.month}%2F{target_datetime.year}\"\n    )\n    next_day_format = f\"{next_day.day}%2F{next_day.month}%2F{next_day.year}\"\n\n    link = f\"{ADME_URL}{date_format}&fecha_fin={next_day_format}&send=MOSTRAR\"\n    r = session.get(url=link)\n    if not r.ok:\n        raise ParserException(\n            parser=\"UY.py\",\n            message=\"Impossible to fetch data url from ADME\",\n        )\n    soup = BeautifulSoup(r.content, \"html.parser\")\n    href_tags = soup.find_all(\"a\", href=True)\n    data_url: str = \"\"\n    for tag in href_tags:\n        if (\n            tag.button is not None\n            and tag.button.string == \"Archivo Scada Detalle 10minutal\"\n        ):\n            data_url = \"https://pronos.adme.com.uy\" + tag.get(\"href\")\n\n    if not data_url:\n        raise ParserException(\n            parser=\"UY.py\",\n            message=\"Impossible to fetch data url from ADME\",\n        )\n    return data_url\n\n\ndef fetch_data(\n    session: Session,\n    target_datetime: datetime,\n    sheet_name: str,\n    logger: Logger = getLogger(__name__),\n) -> pd.DataFrame:\n    \"\"\" \"\"\"\n    assert target_datetime is not None\n    assert session is not None\n    assert sheet_name != \"\" or sheet_name is not None\n    adme_url = get_adme_url(target_datetime=target_datetime, session=session)\n    r = session.get(url=adme_url)\n    if r.status_code == 200:\n        df_data = pd.read_excel(\n            io.BytesIO(r.content), engine=\"odf\", header=2, sheet_name=sheet_name\n        )\n        df_data.columns = df_data.columns.str.strip()\n        df_data = df_data.rename(columns={\"Fecha\": \"datetime\"})\n\n        df_data = df_data.set_index(\"datetime\")\n        return df_data\n    else:\n        raise ParserException(\n            parser=\"UY.py\",\n            message=\"no data available for target_datetime\",\n        )\n\n\ndef fix_solar_production(dt: datetime, value: float) -> int:\n    \"\"\"sets solar production to 0 during the night as there is only solar PV in UY\"\"\"\n    if (dt.hour <= 5 or dt.hour >= 20) and value != 0:\n        return 0\n    else:\n        return round(value, 3)\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: str = \"UY\",\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"collects production data from ADME and format all data points for target_datetime\"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=UY_TZ)\n    session = session or Session()\n\n    production_list = ProductionBreakdownList(logger)\n\n    data = fetch_data(\n        session=session,\n        target_datetime=target_datetime,\n        sheet_name=\"GPF\",\n        logger=logger,\n    )\n    data = data.rename(columns=PRODUCTION_MODE_MAPPING)\n    data = data.groupby(data.columns, axis=1).sum(\n        numeric_only=True,\n    )\n    production = data[[col for col in data.columns if col in PRODUCTION_MODES]]\n\n    for dt, row in production.iterrows():\n        production_mix = ProductionMix()\n        if not row.eq(0).all() and not row.isna().all():\n            for mode, value in row.items():\n                if mode == \"solar\":\n                    value = fix_solar_production(dt, value)\n                production_mix.add_value(\n                    mode,\n                    round(float(value), 3),\n                    correct_negative_with_zero=True,\n                )\n        production_list.append(\n            zoneKey=ZoneKey(zone_key),\n            datetime=dt.to_pydatetime().replace(tzinfo=UY_TZ),\n            source=UY_SOURCE,\n            production=production_mix,\n        )\n\n    return production_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_consumption(\n    zone_key: str = \"UY\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"collects consumption data from ADME and format all data points for target_datetime\"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=UY_TZ)\n    session = session or Session()\n\n    consumption_list = TotalConsumptionList(logger)\n\n    data = fetch_data(\n        session=session,\n        target_datetime=target_datetime,\n        sheet_name=\"GPF\",\n        logger=logger,\n    )\n    data = data.rename(columns={\"Demanda\": \"consumption\"})\n\n    consumption = data[[\"consumption\"]]\n\n    for dt, row in consumption.iterrows():\n        consumption_list.append(\n            zoneKey=ZoneKey(zone_key),\n            datetime=dt.to_pydatetime().replace(tzinfo=UY_TZ),\n            consumption=row[\"consumption\"],\n            source=UY_SOURCE,\n        )\n\n    return consumption_list.to_list()\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"collects exchanges data from ADME and format all data points for target_datetime\"\"\"\n    if target_datetime is None:\n        target_datetime = datetime.now(tz=UY_TZ)\n    session = session or Session()\n\n    exchange_list = ExchangeList(logger)\n\n    data = fetch_data(\n        session=session,\n        target_datetime=target_datetime,\n        sheet_name=\"Intercambios.\",\n        logger=logger,\n    )\n    data.loc[:, data.columns.str.contains(\"Exp_\")] = -data.loc[\n        :, data.columns.str.contains(\"Exp_\")\n    ]\n\n    data = data.rename(columns=EXCHANGES_MAPPING)\n    data = data.groupby(data.columns, axis=1).sum(\n        numeric_only=True,\n    )\n    sorted_zone_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n    exchange = data[[sorted_zone_keys]]\n\n    for dt, row in exchange.iterrows():\n        exchange_list.append(\n            zoneKey=ZoneKey(sorted_zone_keys),\n            datetime=dt.to_pydatetime().replace(tzinfo=UY_TZ),\n            netFlow=row[sorted_zone_keys],\n            source=UY_SOURCE,\n        )\n\n    return exchange_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    # print(\"fetch_exchange(UY, BR) ->\")\n    # print(fetch_exchange(\"UY\", \"BR\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/VN.py",
    "content": "#!/usr/bin/env python3\n\nimport json\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import (\n    PriceList,\n    TotalConsumptionList,\n)\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\n## Vietnamese National Load Dispatch Center https://www.nldc.evn.vn/\n# Access via day, can also parse historical data\n\ntz = ZoneInfo(\"Asia/Ho_Chi_Minh\")\nLIVE_DATA = {\n    \"consumption\": \"https://www.nldc.evn.vn/api/services/app/Pages/GetChartPhuTaiVM\",\n    \"price\": \"https://www.nldc.evn.vn/api/services/app/Pages/GetChartGiaBienVM\",\n}\n\nHISTORICAL_DATA = \"https://www.nldc.evn.vn/api/services/app/Dashboard/GetBieuDoTuongQuanPT\"  # + dd/mm/yyyy\n\nZONE_CODE = {\n    ZoneKey(\"VN\"): \"HT\",\n    ZoneKey(\"VN-N\"): \"MB\",\n    ZoneKey(\"VN-C\"): \"MT\",\n    ZoneKey(\"VN-S\"): \"MN\",\n}\n\n\ndef fetch_live_data(data_type: str, session: Session):\n    res = session.get(LIVE_DATA[data_type])\n    if not res.ok:\n        raise ParserException(\n            parser=\"VN.py\", message=f\"Request failed: {res.status_code}\"\n        )\n    return json.loads(res.text)[\"result\"][\"data\"]\n\n\ndef fetch_historical_data(\n    target_datetime: datetime,\n    session: Session,\n):\n    res = session.get(\n        f\"{HISTORICAL_DATA}?day={(target_datetime.astimezone(tz)).strftime('%d/%m/%Y')}\"\n    )\n    if not res.ok:\n        raise ParserException(\n            parser=\"VN.py\", message=f\"Request failed: {res.status_code}\"\n        )\n    return json.loads(res.text)[\"result\"][\"data\"][\"phuTai\"]\n\n\ndef fetch_live_price(\n    zone_key: ZoneKey,\n    session: Session,\n    logger: Logger = getLogger(__name__),\n):\n    data_list = fetch_live_data(\"price\", session)[\"giaBiens\"]\n\n    result_list = PriceList(logger)\n\n    for data in data_list:\n        result_list.append(\n            datetime=datetime.fromisoformat(data[\"thoiGian\"]).replace(tzinfo=tz)\n            - timedelta(minutes=30),\n            price=data[f\"giaBien{ZONE_CODE[zone_key]}\"],\n            currency=\"VND\",\n            zoneKey=zone_key,\n            source=\"nldc.evn.vn\",\n        )\n    return result_list.to_list()\n\n\ndef fetch_live_consumption(\n    zone_key: ZoneKey,\n    session: Session,\n    logger: Logger = getLogger(__name__),\n):\n    data_list = fetch_live_data(\"consumption\", session)[\"phuTais\"]\n\n    result_list = TotalConsumptionList(logger)\n\n    for data in data_list:\n        result_list.append(\n            datetime=datetime.fromisoformat(data[\"thoiGian\"]).replace(tzinfo=tz)\n            - timedelta(minutes=30),\n            consumption=data[f\"congSuat{ZONE_CODE[zone_key]}\"],\n            zoneKey=zone_key,\n            source=\"nldc.evn.vn\",\n        )\n    return result_list.to_list()\n\n\ndef fetch_historical_price(\n    target_datetime: datetime,\n    session: Session,\n    logger: Logger = getLogger(__name__),\n):\n    data_list = fetch_historical_data(session=session, target_datetime=target_datetime)\n\n    result_list = PriceList(logger)\n\n    for data in data_list:\n        result_list.append(\n            datetime=datetime.fromisoformat(data[\"thoiGian\"]).replace(tzinfo=tz)\n            - timedelta(minutes=30),\n            currency=\"VND\",\n            price=data[\"giaBan\"],\n            zoneKey=ZoneKey(\"VN\"),\n            source=\"nldc.evn.vn\",\n        )\n    return result_list.to_list()\n\n\ndef fetch_historical_consumption(\n    target_datetime: datetime,\n    session: Session,\n    logger: Logger = getLogger(__name__),\n):\n    data_list = fetch_historical_data(session=session, target_datetime=target_datetime)\n    result_list = TotalConsumptionList(logger)\n\n    for data in data_list:\n        result_list.append(\n            datetime=datetime.fromisoformat(data[\"thoiGian\"]).replace(tzinfo=tz)\n            - timedelta(\n                minutes=30\n            ),  # Substract 30 minutes to convert backwards looking timestamp to forward looking\n            consumption=data[\"congSuat\"],\n            zoneKey=ZoneKey(\"VN\"),\n            source=\"nldc.evn.vn\",\n        )\n    return result_list.to_list()\n\n\ndef fetch_price(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    session = session or Session()\n    if target_datetime is None:\n        live_consumption = fetch_live_price(zone_key, session, logger)\n        if len(live_consumption) > 0:\n            return live_consumption\n        else:\n            if zone_key is ZoneKey(\"VN\"):\n                return fetch_historical_price(\n                    datetime.now() - timedelta(days=1), session, logger\n                )\n            else:\n                raise ParserException(\n                    \"VN.py\",\n                    \"No real time data found\",\n                    zone_key,\n                )\n    elif target_datetime is not None and zone_key is ZoneKey(\"VN\"):\n        return fetch_historical_price(target_datetime, session, logger)\n    else:\n        raise NotImplementedError(\n            \"This parser is not yet able to parse past dates for this zone\"\n        )\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    session = session or Session()\n    if target_datetime is None:\n        live_consumption = fetch_live_consumption(zone_key, session, logger)\n        # Live data is empty at 00:00, resort to historical from previous day\n        if len(live_consumption) > 0:\n            return live_consumption\n        else:\n            if zone_key is ZoneKey(\"VN\"):\n                return fetch_historical_consumption(\n                    datetime.now() - timedelta(days=1), session, logger\n                )\n            else:\n                raise ParserException(\n                    \"VN.py\",\n                    \"No real time data found\",\n                    zone_key,\n                )\n    elif target_datetime is not None and zone_key is ZoneKey(\"VN\"):\n        return fetch_historical_consumption(target_datetime, session, logger)\n    else:\n        raise NotImplementedError(\n            \"This parser is not yet able to parse past dates for this zone\"\n        )\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption(ZoneKey(\"VN\")))\n    print(\"fetch_price() ->\")\n    print(fetch_price(ZoneKey(\"VN\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/YUKONENERGY.py",
    "content": "#!/usr/bin/env python3\nimport json\nimport re\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\nfrom bs4 import BeautifulSoup\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nSOURCE = \"yukonenergy.ca\"\nTIMEZONE = ZoneInfo(\"America/Whitehorse\")\nURL = \"http://www.yukonenergy.ca/consumption/chart_current.php?chart=current&width=420\"\nZONE_KEY = ZoneKey(\"CA-YT\")\n\nFUEL_MAPPING = {\n    \"thermal\": \"unknown\",\n    \"hydro\": \"hydro\",\n    \"wind\": \"wind\",\n    \"solar\": \"solar\",\n}\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    \"\"\"\n    We are using Yukon Energy's data from\n    http://www.yukonenergy.ca/energy-in-yukon/electricity-101/current-energy-consumption\n\n    Generation in Yukon is done with solar, wind, hydro, diesel oil, and LNG.\n\n    There are two companies, Yukon Energy and ATCO aka Yukon Electric aka YECL.\n    Yukon Energy does most of the generation and feeds into Yukon's grid. ATCO\n    does operations, billing, and generation in some of the off-grid\n    communities.\n\n    See schema of the grid at http://www.atcoelectricyukon.com/About-Us/\n\n    Thermal is a mix of diesel oil and LNG, therefore thermal is set to unknown.\n    https://yukonenergy.ca/energy-in-yukon/projects-facilities/\n    \"\"\"\n\n    if zone_key != ZONE_KEY:\n        raise ParserException(\n            \"YUKONENERGY.py\", \"Cannot parse zone '{zone_key}'\", zone_key\n        )\n    if target_datetime:\n        raise ParserException(\n            \"YUKONENERGY.py\", \"Unable to fetch historical data\", zone_key\n        )\n\n    session = session or Session()\n\n    response = session.get(URL)\n    html = response.text\n    soup = BeautifulSoup(html, \"html.parser\")\n\n    # Extract JavaScript data\n    match_past_day = re.search(\n        r\"var rows_chart_past_day = parseDates\\((\\[\\[.*?\\]\\])\\);\", html, re.DOTALL\n    )\n    match_current = re.search(\n        r\"var rows_chart_current = parseDates\\((\\[\\[.*?\\]\\])\\);\", html, re.DOTALL\n    )\n    if not match_past_day or not match_current:\n        raise ParserException(\"YUKONENERGY.py\", \"Cannot find data\", zone_key)\n\n    past_day_data = json.loads(match_past_day.group(1))\n    current_data = json.loads(match_current.group(1))\n\n    # Search html for when the data was updatead\n    pane = soup.find(\"div\", class_=\"consumption-pane total\")\n    updated_text = pane.find(\"p\").get_text(strip=True) if pane else None\n\n    timestamp = None\n    if updated_text:\n        match = re.search(r\"Updated (\\d+) minute\", updated_text)\n        if match:\n            minutes_ago = int(match.group(1))\n            timestamp = datetime.now(TIMEZONE) - timedelta(minutes=minutes_ago)\n        else:\n            timestamp = datetime.now(TIMEZONE)\n\n    else:\n        timestamp = datetime.now(TIMEZONE)\n\n    timestamp = timestamp.replace(second=0, microsecond=0).isoformat(timespec=\"seconds\")\n\n    if timestamp != past_day_data[-1][0]:\n        new_row = [timestamp] + [source[1] for source in current_data[:-1]]\n        past_day_data.append(new_row)\n\n    # Remove capacity\n    production_mode_order = [item[0].lower() for item in current_data][:-1]\n\n    all_production_breakdowns: list[ProductionBreakdownList] = []\n\n    for item in past_day_data:\n        time, *datetime_data = item\n\n        production_mode_list = ProductionBreakdownList(logger)\n        productionMix = ProductionMix()\n\n        for i, data in enumerate(datetime_data):\n            production_mode = FUEL_MAPPING.get(production_mode_order[i])\n            productionMix.add_value(production_mode, round(float(data), 3))\n\n        production_mode_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(time).replace(tzinfo=TIMEZONE),\n            source=SOURCE,\n            production=productionMix,\n        )\n        all_production_breakdowns.append(production_mode_list)\n\n        production_events = ProductionBreakdownList.merge_production_breakdowns(\n            all_production_breakdowns, logger\n        )\n        production_events = production_events.to_list()\n\n    return production_events\n\n\nif __name__ == \"__main__\":\n    # Never used by the Electricity Map backend, but handy for testing.\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/parsers/ajenti.py",
    "content": "\"\"\"\nInitial PR https://github.com/electricitymaps/electricitymaps-contrib/pull/2456\nDiscussion thread https://github.com/electricitymaps/electricitymaps-contrib/issues/636\nA promotion webpage for King's Island energy production is here: https://www.hydro.com.au/clean-energy/hybrid-energy-solutions/success-stories/king-island\nAs of 09/2020, it embeds with <iframe> the URI https://data.ajenti.com.au/KIREIP/index.html\n\nAbout the data, the feed we get seems to be counters with a 2 seconds interval.\nThat means that if we fetch these counters every 15 minutes, we only are reading \"instantaneous\" metters that could differ from the total quantity of energies at play.\nTo get the very exact data, we would need to have a parser running constanty to collect those 2-sec interval counters.\n\"\"\"\n\nimport json\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\nfrom signalr import Connection\n\nZONE_PARAMS = {\n    # King Island\n    # https://www.hydro.com.au/clean-energy/hybrid-energy-solutions/success-stories/king-island\n    \"AU-TAS-KI\": {\n        \"hub\": \"TagHub\",\n        \"method\": \"Dashboard\",\n        \"tz\": \"Australia/Currie\",\n        \"source\": \"hydro.com.au\",  # Iframe: https://data.ajenti.com.au/KIREIP/index.html\n    },\n    # Flinders Island\n    # https://github.com/electricitymaps/electricitymaps-contrib/issues/2533\n    # https://en.wikipedia.org/wiki/Flinders_Island\n    # https://www.hydro.com.au/clean-energy/hybrid-energy-solutions/success-stories/flinders-island\n    \"AU-TAS-FI\": {\n        \"hub\": \"flindershub\",\n        \"method\": \"SendDashboard\",\n        \"tz\": \"Australia/Hobart\",\n        \"source\": \"hydro.com.au\",\n    },\n    # Rottnest Island\n    # https://github.com/electricitymaps/electricitymaps-contrib/issues/2534\n    # https://en.wikipedia.org/wiki/Rottnest_Island\n    # https://www.hydro.com.au/clean-energy/hybrid-energy-solutions/success-stories/rottnest-island\n    \"AU-WA-RI\": {\n        \"hub\": \"HogsHub\",\n        \"method\": \"SendDashboard\",\n        \"tz\": \"Australia/Perth\",\n        \"source\": \"hydro.com.au\",\n    },\n}\n\n\nclass SignalR:\n    def __init__(self, url):\n        self.url = url\n\n    def update_res(self, msg):\n        if msg != {}:\n            self.res = msg\n\n    def get_value(self, hub, method):\n        self.res = {}\n        with Session() as session:\n            # create a connection\n            connection = Connection(self.url, session)\n            chat = connection.register_hub(hub)\n            chat.client.on(method, self.update_res)\n            connection.start()\n            connection.wait(3)\n            connection.close()\n            return self.res\n\n\ndef parse_payload(logger: Logger, payload) -> dict:\n    technologies_parsed = {\n        \"biomass\": 0,\n        \"battery\": 0,\n        \"coal\": 0,\n        \"flywheel\": 0,\n        \"gas\": 0,\n        \"hydro\": 0,\n        \"nuclear\": 0,\n        \"oil\": 0,\n        \"solar\": 0,\n        \"wind\": 0,\n        \"geothermal\": 0,\n        \"unknown\": 0,\n    }\n    if \"technologies\" not in payload:\n        raise KeyError(f\"No 'technologies' in payload\\nserie : {json.dumps(payload)}\")\n    else:\n        logger.debug(f\"serie : {json.dumps(payload)}\")\n    for technology in payload[\"technologies\"]:\n        # rename upstream key to match our payload needs\n        if technology[\"id\"] == \"diesel\":\n            technology[\"id\"] = \"oil\"\n\n        assert technology[\"unit\"] == \"kW\"\n        # The upstream API gives us kW, we need MW\n        technologies_parsed[technology[\"id\"]] = int(technology[\"value\"]) / 1000\n\n    # King's Island uses some percentage of biodiesel; since we account differently traditionnal oil & biomass, here we do math to separate both\n    if \"biodiesel\" in payload:\n        # sanity check to be sure that we are not remaking data that the data source could otherwise give us\n        assert \"biomass\" and \"oil\" != 0\n        technologies_parsed[\"biomass\"] = (\n            technologies_parsed[\"oil\"] * payload[\"biodiesel\"][\"percent\"] / 100\n        )\n        technologies_parsed[\"oil\"] = (\n            technologies_parsed[\"oil\"] * (100 - payload[\"biodiesel\"][\"percent\"]) / 100\n        )\n\n    logger.debug(f\"production : {json.dumps(technologies_parsed)}\")\n\n    return technologies_parsed\n\n\n# Both keys battery and flywheel are negative when storing energy, and positive when feeding energy to the grid\ndef format_storage_techs(technologies_parsed):\n    # sometimes we don't get those keys. For instance Rottnest island don't have any storage.\n    if \"battery\" and \"flywheel\" in technologies_parsed:\n        storage_techs = technologies_parsed[\"battery\"] + technologies_parsed[\"flywheel\"]\n    else:\n        storage_techs = 0\n    _battery_production = (\n        storage_techs if storage_techs > 0 else 0\n    )  # TODO: Should this just be removed?\n    _battery_storage = storage_techs if storage_techs < 0 else 0\n\n\ndef sum_storage_techs(technologies_parsed):\n    storage_techs = technologies_parsed[\"battery\"] + technologies_parsed[\"flywheel\"]\n\n    return storage_techs\n\n\ndef fetch_production(\n    zone_key: str = \"AU-TAS-KI\",\n    session: Session | None = None,\n    target_datetime=None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    if target_datetime is not None:\n        raise NotImplementedError(\n            \"The datasource currently implemented is only real time\"\n        )\n\n    # get the specific zone parameters\n    try:\n        hub, dashboard, tz, source = (\n            ZONE_PARAMS[zone_key][\"hub\"],\n            ZONE_PARAMS[zone_key][\"method\"],\n            ZONE_PARAMS[zone_key][\"tz\"],\n            ZONE_PARAMS[zone_key][\"source\"],\n        )\n    except KeyError as e:\n        raise KeyError(\"The zone \" + zone_key + \" isn't implemented\") from e\n\n    payload = SignalR(\"https://data.ajenti.com.au/live/signalr\").get_value(\n        hub, dashboard\n    )\n    technologies_parsed = parse_payload(logger, payload)\n    storage_techs = sum_storage_techs(technologies_parsed)\n\n    return [\n        {\n            \"zoneKey\": zone_key,\n            \"datetime\": datetime.now(tz=ZoneInfo(tz)),\n            \"production\": {\n                \"biomass\": technologies_parsed[\"biomass\"],\n                \"coal\": technologies_parsed[\"coal\"],\n                \"gas\": technologies_parsed[\"gas\"],\n                \"hydro\": technologies_parsed[\"hydro\"],\n                \"nuclear\": technologies_parsed[\"nuclear\"],\n                \"oil\": technologies_parsed[\"oil\"],\n                \"solar\": technologies_parsed[\"solar\"],\n                \"wind\": 0\n                if technologies_parsed[\"wind\"] < 0\n                and technologies_parsed[\"wind\"] > -0.1\n                else technologies_parsed[\n                    \"wind\"\n                ],  # If wind between 0 and -0.1 set to 0 to ignore self-consumption\n                \"geothermal\": technologies_parsed[\"geothermal\"],\n                \"unknown\": technologies_parsed[\"unknown\"],\n            },\n            \"storage\": {\n                \"battery\": storage_techs\n                * -1  # Somewhat counterintuitively,to ElectricityMap positive means charging and negative means discharging\n            },\n            \"source\": source,\n        }\n    ]\n\n\nif __name__ == \"__main__\":\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/amper_landsnet.py",
    "content": "from datetime import datetime\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nSOURCE = \"amper.landsnet.is\"\nSOURCE_URL = \"https://amper.landsnet.is/generation/api/Values\"\n\n\ndef fetch_production(\n    zone_key: ZoneKey = ZoneKey(\"IS\"),\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    r = session or Session()\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n    res = r.get(SOURCE_URL)\n    if not res.ok:\n        raise ParserException(\n            parser=\"amper_landsnet.py\",\n            message=f\"Failed to fetch {SOURCE}: {res.status_code}, err: {res.text}\",\n            zone_key=zone_key,\n        )\n\n    obj = res.json()\n    mix = ProductionMix(\n        geothermal=obj[\"geothermal\"],\n        hydro=obj[\"hydro\"],\n        oil=obj[\"oil\"],\n    )\n    breakdowns = ProductionBreakdownList(logger=logger)\n    breakdowns.append(\n        zoneKey=zone_key,\n        datetime=datetime.fromisoformat(obj[\"timestamp\"]).replace(\n            tzinfo=ZoneInfo(\"Atlantic/Reykjavik\")\n        ),\n        production=mix,\n        source=SOURCE,\n    )\n    return breakdowns.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/AM.py",
    "content": "# Archived reason: Data source is no longer available.\n\nimport logging\nimport re\nfrom datetime import datetime\n\nimport requests\nfrom bs4 import BeautifulSoup\nfrom dateutil import parser as dparser\nfrom dateutil import tz\n\n# URL of the power system summary: http://epso.am/poweren.htm\n# URL of the detailled SCADA-page: http://epso.am/scada.htm\n\nSOURCE = \"http://epso.am/poweren.htm\"\nTZ = \"Asia/Yerevan\"\n\nPOWER_PLANT_MAPPING = {\n    \"var atom\": \"nuclear\",  # atom = 'atomnaya elektro stantsiya'\n    \"var tes\": \"gas\",  # tes = 'termalnaya elektro stantsiya' - only gas in AM\n    \"var ges\": \"hydro\",  # ges = 'gidro elektro stantsiya'\n    \"var altern\": \"hydro\",  # altern = two hydro power plants according to SCADA data (middle row, right box)\n}\n\nTIE_LINE_MAPPING = {\n    \"var Lalvar\": \"GE\",\n    \"var ninoc\": \"GE\",\n    \"var alaver\": \"GE\",\n    \"var shin\": \"NKR\",\n    \"var arcakh\": \"NKR\",\n    \"var ahar\": \"IR\",\n}\n\nOTHER_VARIABLES_MAPPING = {\n    \"var cons\": \"total production\",  # please note, this is an error of the variable name ('cons' is actually used for total production)\n    \"var peretok\": \"total import/export\",  # positive = import, negative = export\n    \"var herc2\": \"frequency\",  # \"hertz\" ;)\n    \"var time2\": \"timestamp\",  # date is missing\n    \"sparum2\": \"total consumption\",  # please note, this is an error of the variable name (probably means \"production\", but is used for consumption)\n}\n\nSOUP_CONTENT_VARIABLES_MAPPING = {\n    \"[0]\": \"empty\",\n    \"[1]\": \"Lalvar (GE)\",\n    \"[2]\": \"ninoc (GE)\",\n    \"[3]\": \"alaver (GE)\",\n    \"[4]\": \"shin (NKR)\",\n    \"[5]\": \"arcakh (NKR)\",\n    \"[6]\": \"ahar (IR)\",\n    \"[7]\": \"cons [total production]\",\n    \"[8]\": \"altern\",\n    \"[9]\": \"atom\",\n    \"[10]\": \"tes\",\n    \"[11]\": \"ges\",\n    \"[12]\": \"peretok\",\n    \"[13]\": \"herc2\",\n    # unstable other mappings\n    \"[27]\": \"time2\",\n    \"[28]\": \"sparum2\",\n}\n\nREGEX = r\"[-+]?[.]?[\\d]+(?:,\\d\\d\\d)*[\\.]?\\d*(?:[eE][-+]?\\d+)?\"\n\n\ndef fetch_production(\n    zone_key=\"AM\",\n    session=None,\n    target_datetime=None,\n    logger: logging.Logger = logging.getLogger(__name__),\n) -> dict:\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    r = session or requests.session()\n    response = r.get(SOURCE)\n    response.encoding = \"utf-8\"\n    html_doc = response.text\n    start_string = \"<script type='text/javascript'>\"\n    start_index = html_doc.find(start_string) + len(start_string)\n    stop_index = html_doc.find(\"left:\")\n    soup = BeautifulSoup(html_doc[start_index:stop_index], \"html.parser\")\n    data_string = soup.find(text=re.compile(\"var\"))\n\n    if data_string is None:\n        logger.warning(f\"Could not parse {html_doc}\")\n        raise ValueError(\"Empty data object scraped, cannot be parsed.\")\n\n    data_split = data_string.split(\"\\r\\n\")\n\n    gas_tes = re.findall(REGEX, data_split[10])\n    gas_total = float(gas_tes[0])\n\n    hydro_ges = re.findall(REGEX, data_split[11])\n    hydro_altern = re.findall(REGEX, data_split[8])\n    hydro_total = float(hydro_ges[0]) + float(hydro_altern[0])\n\n    nuclear_atom = re.findall(REGEX, data_split[9])\n    nuclear_total = float(nuclear_atom[0])\n\n    time_data = [s for s in data_split if \"time2\" in s][0]\n    yerevan = tz.gettz(TZ)\n    date_time = dparser.parse(\n        time_data.split()[3], default=datetime.now(yerevan), fuzzy=True\n    )\n\n    # Operating solar, wind and biomass plants exist in small numbers, but are not reported yet\n    return {\n        \"zoneKey\": zone_key,\n        \"datetime\": date_time,\n        \"production\": {\n            \"gas\": gas_total,\n            \"hydro\": hydro_total,\n            \"nuclear\": nuclear_total,\n            \"biomass\": None,\n            \"coal\": 0,\n            \"geothermal\": 0,\n            \"oil\": 0,\n            \"solar\": None,\n            \"wind\": None,\n        },\n        \"storage\": {\"hydro\": 0, \"battery\": 0},\n        \"source\": SOURCE,\n    }\n\n\ndef fetch_exchange(\n    zone_key1, zone_key2, session=None, target_datetime=None, logger=None\n) -> dict:\n    \"\"\"Requests the last known power exchange (in MW) between two countries.\"\"\"\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    sorted_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    r = session or requests.session()\n    response = r.get(SOURCE)\n    response.encoding = \"utf-8\"\n    html_doc = response.text\n    start_string = \"<script type='text/javascript'>\"\n    start_index = html_doc.find(start_string) + len(start_string)\n    stop_index = html_doc.find(\"left:\")\n    soup = BeautifulSoup(html_doc[start_index:stop_index], \"html.parser\")\n    data_string = soup.find(text=re.compile(\"var\"))\n    data_split = data_string.split(\"\\r\\n\")\n\n    GE_1 = re.findall(REGEX, data_split[1])\n    GE_2 = re.findall(REGEX, data_split[2])\n    GE_3 = re.findall(REGEX, data_split[3])\n    NKR_1 = re.findall(REGEX, data_split[4])\n    NKR_2 = re.findall(REGEX, data_split[5])\n    IR_1 = re.findall(REGEX, data_split[6])\n\n    AM_NKR = float(NKR_1[0]) + float(NKR_2[0])\n    AM_GE = float(GE_1[0]) + float(GE_2[0]) + float(GE_3[0])\n    AM_IR = float(IR_1[0])\n\n    time_data = [s for s in data_split if \"time2\" in s][0]\n    yerevan = tz.gettz(TZ)\n    date_time = dparser.parse(\n        time_data.split()[3], default=datetime.now(yerevan), fuzzy=True\n    )\n\n    if sorted_keys == \"AM->NKR\":\n        netflow = -1 * AM_NKR\n    elif sorted_keys == \"AM->GE\":\n        netflow = -1 * AM_GE\n    elif sorted_keys == \"AM->IR\":\n        netflow = -1 * AM_IR\n    else:\n        raise NotImplementedError(\"This exchange pair is not implemented\")\n\n    return {\n        \"sortedZoneKeys\": sorted_keys,\n        \"datetime\": date_time,\n        \"netFlow\": netflow,\n        \"source\": SOURCE,\n    }\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production->\")\n    print(fetch_production())\n    print(\"fetch_exchange(AM, NKR) ->\")\n    print(fetch_exchange(\"AM\", \"NKR\"))\n    print(\"fetch_exchange(AM, GE) ->\")\n    print(fetch_exchange(\"AM\", \"GE\"))\n    print(\"fetch_exchange(AM, IR) ->\")\n    print(fetch_exchange(\"AM\", \"IR\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/AX.py",
    "content": "# Archived reason: Replaced by a new AX parser that parses the iFrame instead of using OCR.\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\n\nimport arrow\n\n# Numpy and PIL are used to process the image\nimport numpy as np\nfrom PIL import Image\nfrom requests import Session\n\nURL = \"http://194.110.178.135/grafik/stamnat.php\"\nSOURCE = \"kraftnat.ax\"\nTZ = \"Europe/Mariehamn\"\n\n\ndef _get_masks(session=None):\n    Minus = np.array(\n        [\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Minus = Image.fromarray(Minus)\n\n    Dot = np.array(\n        [\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Dot = Image.fromarray(Dot)\n\n    Zero = np.array(\n        [\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [[0, 0, 0], [0, 0, 0], [255, 255, 255], [0, 0, 0], [0, 0, 0], [0, 0, 0]],\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [255, 255, 255], [0, 0, 0], [0, 0, 0]],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Zero = Image.fromarray(Zero)\n\n    One = np.array(\n        [\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [0, 0, 0],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    One = Image.fromarray(One)\n\n    Two = np.array(\n        [\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Two = Image.fromarray(Two)\n\n    Three = np.array(\n        [\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Three = Image.fromarray(Three)\n\n    Four = np.array(\n        [\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Four = Image.fromarray(Four)\n\n    Five = np.array(\n        [\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [255, 255, 255]],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Five = Image.fromarray(Five)\n\n    Six = np.array(\n        [\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [255, 255, 255]],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Six = Image.fromarray(Six)\n\n    Seven = np.array(\n        [\n            [[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Seven = Image.fromarray(Seven)\n\n    Eight = np.array(\n        [\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Eight = Image.fromarray(Eight)\n\n    Nine = np.array(\n        [\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [[255, 255, 255], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n            ],\n            [\n                [255, 255, 255],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [0, 0, 0],\n                [255, 255, 255],\n            ],\n            [\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n                [255, 255, 255],\n            ],\n        ],\n        dtype=np.uint8,\n    )\n    Nine = Image.fromarray(Nine)\n\n    shorts = [\"-\", \".\", \"0\", \"1\", \"2\", \"3\", \"4\", \"5\", \"6\", \"7\", \"8\", \"9\"]\n    masks = [Minus, Dot, Zero, One, Two, Three, Four, Five, Six, Seven, Eight, Nine]\n\n    return dict(zip(shorts, masks))\n\n\ndef _fetch_data(session: Session | None = None) -> dict:\n    \"\"\"Return usable data from source.\"\"\"\n    # Load masks for reading numbers from the image\n    # Create a dictionary of symbols and their pixel masks\n    mapping = _get_masks(session)\n\n    # Download the updating image from Kraftnät Åland\n    r = session or Session()\n\n    im = Image.open(r.get(URL, stream=True).raw)\n    # Get timestamp\n    fetchtime = arrow.utcnow().floor(\"second\").to(TZ)\n\n    # \"data\" is a height x width x 3 RGB numpy array\n    data = np.array(im)\n    # red, green, blue, alpha = data.T\n    # Temporarily unpack the bands for readability\n    red, green, blue = data.T\n    # Color non-blue areas in the image with white\n    blue_areas = (red == 0) & (green == 0) & (blue == 255)\n    data[~blue_areas.T] = (255, 255, 255)\n    # Color blue areas in the image with black\n    data[blue_areas.T] = (0, 0, 0)\n\n    # Transform the array back to image\n    im = Image.fromarray(data)\n\n    shorts = mapping.keys()\n\n    # check import from Sweden\n    se_3_flow = []\n    for x in range(80, 130 - 6):\n        for abr in shorts:\n            im1 = im.crop((x, 443, x + 6, 452))\n            if im1 == mapping[abr]:\n                se_3_flow.append(abr)\n    se_3_flow = \"\".join(se_3_flow)\n    se_3_flow = round(float(se_3_flow), 1)\n\n    # export Åland-Finland(Kustavi/Gustafs)\n    gustafs_flow = []\n    for x in range(780, 825 - 6):\n        for abr in shorts:\n            im1 = im.crop((x, 43, x + 6, 52))\n            if im1 == mapping[abr]:\n                gustafs_flow.append(abr)\n    gustafs_flow = \"\".join(gustafs_flow)\n    gustafs_flow = round(float(gustafs_flow), 1)\n\n    # Reserve cable import Naantali-Åland\n    # Åland administration does not allow export\n    # to Finland through this cable\n    fin_flow = []\n    for x in range(760, 815 - 6):\n        for abr in shorts:\n            im1 = im.crop((x, 328, x + 6, 337))\n            if im1 == mapping[abr]:\n                fin_flow.append(abr)\n    fin_flow = \"\".join(fin_flow)\n    fin_flow = round(float(fin_flow), 1)\n\n    # The shown total consumption is not reliable according to the TSO\n    # Consumption\n    # Cons = []\n    # for x in range(650, 700-6):\n    #    for abr in shorts:\n    #        im1 = im.crop((x, 564, x+6, 573))\n    #        if im1 == mapping[abr]:\n    #            Cons.append(abr)\n    # Cons = \"\".join(Cons)\n    # Cons = round(float(Cons),1)\n\n    # Wind production\n    wind = []\n    for x in range(650, 700 - 6):\n        for abr in shorts:\n            im1 = im.crop((x, 576, x + 6, 585))\n            if im1 == mapping[abr]:\n                wind.append(abr)\n    wind = \"\".join(wind)\n    wind = round(float(wind), 1)\n\n    # Fossil fuel production\n    fossil = []\n    for x in range(650, 700 - 6):\n        for abr in shorts:\n            im1 = im.crop((x, 588, x + 6, 597))\n            if im1 == mapping[abr]:\n                fossil.append(abr)\n    fossil = \"\".join(fossil)\n    fossil = round(float(fossil), 1)\n\n    # Both are confirmed to be import from Finland by the TSO\n    fin_flow = fin_flow + gustafs_flow\n\n    # Calculate sum of exchanges\n    sum_exchanges = se_3_flow + fin_flow\n    # Calculate total production\n    total_production = fossil + wind\n    # Calculate total consumption\n    consumption = round(total_production + sum_exchanges, 1)\n\n    # The production that is not fossil fuel or wind based is unknown\n    # Impossible to estimate with current data\n    # UProd = TotProd - WProd - FProd\n    return {\n        \"production\": total_production,\n        \"consumption\": consumption,\n        \"wind\": wind,\n        \"fossil\": fossil,\n        \"SE3->AX\": se_3_flow,\n        \"FI->AX\": fin_flow,\n        \"fetchtime\": fetchtime,\n    }\n\n\ndef fetch_production(\n    zone_key: str = \"AX\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    obj = _fetch_data(session)\n\n    return {\n        \"zoneKey\": zone_key,\n        \"production\": {\n            \"biomass\": None,\n            \"coal\": 0,\n            \"gas\": 0,\n            \"hydro\": None,\n            \"nuclear\": 0,\n            \"oil\": obj[\"fossil\"],\n            \"solar\": None,\n            \"wind\": obj[\"wind\"],\n            \"geothermal\": None,\n            \"unknown\": None,\n        },\n        \"storage\": {},\n        \"source\": SOURCE,\n        \"datetime\": arrow.get(obj[\"fetchtime\"]).datetime,\n    }\n\n\ndef fetch_consumption(\n    zone_key: str = \"AX\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    obj = _fetch_data(session)\n\n    return {\n        \"zoneKey\": zone_key,\n        \"datetime\": arrow.get(obj[\"fetchtime\"]).datetime,\n        \"consumption\": obj[\"consumption\"],\n        \"source\": SOURCE,\n    }\n\n\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the last known power exchange (in MW) between two countries.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    obj = _fetch_data(session)\n\n    # Country codes are sorted in order to enable easier indexing in the database\n    sorted_zone_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    data = {\n        \"sortedZoneKeys\": sorted_zone_keys,\n        \"source\": SOURCE,\n        \"datetime\": arrow.get(obj[\"fetchtime\"]).datetime,\n    }\n\n    # Here we assume that the net flow returned by the api is the flow from\n    # country1 to country2. A positive flow indicates an export from country1\n    # to country2. A negative flow indicates an import.\n    net_flow: float | None = None\n    if sorted_zone_keys in [\"AX->SE\", \"AX->SE-SE3\"]:\n        net_flow = obj[\"SE3->AX\"]\n\n    elif sorted_zone_keys == \"AX->FI\":\n        net_flow = obj[\"FI->AX\"]  # Import is positive\n\n    # The net flow to be reported should be from the first country to the second\n    # (sorted alphabetically). This is NOT necessarily the same direction as the flow\n    # from country1 to country2\n\n    #  AX is before both FI and SE\n    if net_flow:\n        data[\"netFlow\"] = round(-1 * net_flow, 1)\n    else:\n        data[\"netFlow\"] = None\n\n    return data\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption())\n    print(\"fetch_exchange(AX, FI) ->\")\n    print(fetch_exchange(\"FI\", \"AX\"))\n    print(\"fetch_exchange(AX, SE-SE3) ->\")\n    print(fetch_exchange(\"SE-SE3\", \"AX\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/DK_old.py",
    "content": "# Archived reason: The SQL API is no longer available and a new DK parser was created.\nimport json\nimport time\nfrom datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\n\nimport arrow  # the arrow library is used to handle datetimes\nimport pandas as pd\nfrom requests import Session, exceptions\n\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\n\nfrom .lib.exceptions import ParserException\n\nids = {\n    \"real_time\": \"06380963-b7c6-46b7-aec5-173d15e4648b\",\n    \"energy_bal\": \"02356e88-7c4e-4ee9-b896-275d217cc1b9\",\n}\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: str = \"DK-DK1\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"\n    Queries \"Electricity balance Non-Validated\" from energinet api\n    for Danish bidding zones\n\n    NOTE: Missing historical wind/solar data @ 2017-08-01\n    \"\"\"\n    r = session or Session()\n\n    if zone_key not in [\"DK-DK1\", \"DK-DK2\"]:\n        raise NotImplementedError(f\"fetch_production() for {zone_key} not implemented\")\n\n    zone = zone_key[-3:]\n\n    timestamp = arrow.get(target_datetime).strftime(\"%Y-%m-%d %H:%M\")\n\n    # fetch hourly energy balance from recent hours\n    sqlstr = 'SELECT \"HourUTC\" as timestamp, \"Biomass\", \"Waste\", \\\n                     \"OtherRenewable\", \"FossilGas\" as gas, \"FossilHardCoal\" as coal, \\\n                     \"FossilOil\" as oil, \"HydroPower\" as hydro, \\\n                     (\"OffshoreWindPower\"%2B\"OnshoreWindPower\") as wind, \\\n                     \"SolarPower\" as solar from \"{0}\" \\\n                     WHERE \"PriceArea\" = \\'{1}\\' AND \\\n                     \"HourUTC\" >= (timestamp\\'{2}\\'-INTERVAL \\'24 hours\\') AND \\\n                     \"HourUTC\" <= timestamp\\'{2}\\' \\\n                     ORDER BY \"HourUTC\" ASC'.format(ids[\"energy_bal\"], zone, timestamp)\n\n    url = f\"https://api.energidataservice.dk/datastore_search_sql?sql={sqlstr}\"\n    response = r.get(url)\n\n    # raise errors for responses with an error or no data\n    retry_count = 0\n    while response.status_code in [429, 403, 500]:\n        retry_count += 1\n        if retry_count > 5:\n            raise Exception(\"Retried too many times..\")\n        # Wait and retry\n        logger.warn(\"Retrying..\")\n        time.sleep(5**retry_count)\n        response = r.get(url)\n    if response.status_code != 200:\n        j = response.json()\n        if \"error\" in j and \"info\" in j[\"error\"]:\n            error = j[\"error\"][\"__type\"]\n            text = j[\"error\"][\"info\"][\"orig\"]\n            msg = f'\"{error}\" fetching production data for {zone_key}: {text}'\n        else:\n            msg = \"error while fetching production data for {}: {}\".format(\n                zone_key, json.dumps(j)\n            )\n        exceptions.HTTPError(msg)\n    if not response.json()[\"result\"][\"records\"]:\n        raise ParserException(\"DK.py\", \"API returned no data\", zone_key=zone_key)\n\n    df = pd.DataFrame(response.json()[\"result\"][\"records\"])\n    # index response dataframe by time\n    df = df.set_index(\"timestamp\")\n    df.index = pd.DatetimeIndex(df.index)\n    # drop empty rows from energy balance\n    df.dropna(how=\"all\", inplace=True)\n\n    # Divide waste into 55% renewable and 45% non-renewable parts according to\n    # https://ens.dk/sites/ens.dk/files/Statistik/int.reporting_2016.xls (visited Jan 24th, 2019)\n    df[\"unknown\"] = 0.45 * df[\"Waste\"]  # Report fossil waste as unknown\n    df[\"renwaste\"] = 0.55 * df[\"Waste\"]\n    # Report biomass, renewable waste and other renewables (biogas etc.) as biomass\n    df[\"biomass\"] = df.filter([\"Biomass\", \"renwaste\", \"OtherRenewable\"]).sum(axis=1)\n\n    fuels = [\"biomass\", \"coal\", \"oil\", \"gas\", \"unknown\", \"hydro\"]\n    # Format output as a list of dictionaries\n    output = []\n    for dt in df.index:\n        data = {\n            \"zoneKey\": zone_key,\n            \"datetime\": None,\n            \"production\": {\n                \"biomass\": 0,\n                \"coal\": 0,\n                \"gas\": 0,\n                \"hydro\": None,\n                \"nuclear\": 0,\n                \"oil\": 0,\n                \"solar\": None,\n                \"wind\": None,\n                \"geothermal\": None,\n                \"unknown\": 0,\n            },\n            \"storage\": {},\n            \"source\": \"api.energidataservice.dk\",\n        }\n\n        data[\"datetime\"] = dt.to_pydatetime()\n        data[\"datetime\"] = data[\"datetime\"].replace(tzinfo=timezone.utc)\n        for f in [\"solar\", \"wind\"] + fuels:\n            data[\"production\"][f] = df.loc[dt, f]\n        output.append(data)\n    return output\n\n\ndef fetch_exchange(\n    zone_key1: str = \"DK-DK1\",\n    zone_key2: str = \"DK-DK2\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    \"\"\"\n    Fetches 5-minute frequency exchange data for Danish bidding zones\n    from api.energidataservice.dk\n    \"\"\"\n    r = session or Session()\n    sorted_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    # pick the correct zone to search\n    if \"DK1\" in sorted_keys and \"DK2\" in sorted_keys:\n        zone = \"DK1\"\n    elif \"DK1\" in sorted_keys:\n        zone = \"DK1\"\n    elif \"DK2\" in sorted_keys:\n        zone = \"DK2\"\n    else:\n        raise NotImplementedError(\n            \"Only able to fetch exchanges for Danish bidding zones\"\n        )\n\n    exch_map = {\n        \"DE->DK-DK1\": '\"ExchangeGermany\"',\n        \"DE->DK-DK2\": '\"ExchangeGermany\"',\n        \"DK-DK1->DK-DK2\": '\"ExchangeGreatBelt\"',\n        \"DK-DK1->NO-NO2\": '\"ExchangeNorway\"',\n        \"DK-DK1->NL\": '\"ExchangeNetherlands\"',\n        \"DK-DK1->SE\": '\"ExchangeSweden\"',\n        \"DK-DK1->SE-SE3\": '\"ExchangeSweden\"',\n        \"DK-DK1->NL\": '\"ExchangeNetherlands\"',\n        \"DK-DK2->SE\": '\"ExchangeSweden\"',\n        \"DK-DK2->SE-SE4\": '\"ExchangeSweden\"',\n    }\n    if sorted_keys not in exch_map:\n        raise NotImplementedError(f\"Exchange {sorted_keys} not implemented\")\n\n    timestamp = arrow.get(target_datetime).strftime(\"%Y-%m-%d %H:%M\")\n\n    # fetch real-time/5-min data\n    sqlstr = 'SELECT \"Minutes5UTC\" as timestamp, {0} as \"netFlow\" \\\n                     from \"{1}\" WHERE \"PriceArea\" = \\'{2}\\' AND \\\n                     \"Minutes5UTC\" >= (timestamp\\'{3}\\'-INTERVAL \\'24 hours\\') AND \\\n                     \"Minutes5UTC\" <= timestamp\\'{3}\\' \\\n                     ORDER BY \"Minutes5UTC\" ASC'.format(\n        exch_map[sorted_keys], ids[\"real_time\"], zone, timestamp\n    )\n\n    url = f\"https://api.energidataservice.dk/datastore_search_sql?sql={sqlstr}\"\n    response = r.get(url)\n\n    # raise errors for responses with an error or no data\n    retry_count = 0\n    while response.status_code in [429, 403, 500]:\n        retry_count += 1\n        if retry_count > 5:\n            raise Exception(\"Retried too many times..\")\n        # Wait and retry\n        logger.warn(\"Retrying..\")\n        time.sleep(5**retry_count)\n        response = r.get(url)\n    if response.status_code != 200:\n        j = response.json()\n        if \"error\" in j and \"info\" in j[\"error\"]:\n            error = j[\"error\"][\"__type\"]\n            text = j[\"error\"][\"info\"][\"orig\"]\n            msg = f'\"{error}\" fetching exchange data for {sorted_keys}: {text}'\n        else:\n            msg = \"error while fetching exchange data for {}: {}\".format(\n                sorted_keys, json.dumps(j)\n            )\n        raise exceptions.HTTPError(msg)\n    if not response.json()[\"result\"][\"records\"]:\n        raise ParserException(\"DK.py\", \"API returned no data\", zone_key=sorted_keys)\n\n    df = pd.DataFrame(response.json()[\"result\"][\"records\"])\n    df = df.set_index(\"timestamp\")\n    df.index = pd.DatetimeIndex(df.index)\n    # drop empty rows\n    df.dropna(how=\"all\", inplace=True)\n\n    # all exchanges are reported as net import,\n    # where as eMap expects net export from\n    # the first zone in alphabetical order\n    if \"DE\" not in sorted_keys:\n        df[\"netFlow\"] = -1 * df[\"netFlow\"]\n    # Format output\n    output = []\n    for dt in df.index:\n        data = {\n            \"sortedZoneKeys\": sorted_keys,\n            \"datetime\": None,\n            \"netFlow\": None,\n            \"source\": \"api.energidataservice.dk\",\n        }\n\n        data[\"datetime\"] = dt.to_pydatetime()\n        data[\"datetime\"] = data[\"datetime\"].replace(tzinfo=timezone.utc)\n        data[\"netFlow\"] = df.loc[dt, \"netFlow\"]\n        output.append(data)\n    return output\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_exchange(DK-DK2, SE-SE4) ->\")\n    print(fetch_exchange(\"DK-DK2\", \"SE-SE4\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/GB_NIR.py",
    "content": "#!/usr/bin/env python3\n# Archived reason: Data is no longer available.\n\nimport logging\nfrom datetime import datetime, timedelta\nfrom io import StringIO\n\nimport pandas as pd\nimport requests\nfrom bs4 import BeautifulSoup\nfrom dateutil import parser, tz\n\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\n\nfrom .lib.validation import validate\n\nproduction_url = \"http://ws.soni.ltd.uk/DownloadCentre/aspx/FuelMix.aspx\"\nexchange_url = \"http://ws.soni.ltd.uk/DownloadCentre/aspx/SystemOutput.aspx\"\n# Positive values in the .csv represent imports to Northern Ireland from GB / IR.\n# Negative values in the .csv represent exports from Northern Ireland to GB / IR.\n\n## exchange_url = 'http://ws.soni.ltd.uk/DownloadCentre/aspx/MoyleTie.aspx' ## see comment below\n## Old exchange_url was used for exchanges, but it provided incomplete data.\n## \"Total_Moyle_Load_MW\" was showing \"0\" when exporting to GB. Tie-line data was missing for the two 110kV Lines \"Enniskillen(NIR)-Corraclassy(IR)\" and \"Strabane(NIR)-Letterkenny(IR)\"\n## Exchanges are now based on data with better quality provided in \"SystemOutput.csv\" under the new exchange_url = 'http://ws.soni.ltd.uk/DownloadCentre/aspx/SystemOutput.aspx'\n\n\ndef get_data(url, target_datetime, session=None):\n    \"\"\"\n    Requests data from a specified url in CSV format.\n    Returns a response.text object.\n    \"\"\"\n\n    s = session or requests.Session()\n\n    headers = {\n        \"User-Agent\": \"Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:55.0) Gecko/20100101 Firefox/55.0\",\n        \"Accept\": \"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\",\n    }\n\n    pagereq = requests.get(url, headers=headers)\n    soup = BeautifulSoup(pagereq.text, \"html.parser\")\n\n    # Find and define parameters needed to send a POST request for the actual data.\n    viewstategenerator = soup.find(\"input\", attrs={\"id\": \"__VIEWSTATEGENERATOR\"})[\n        \"value\"\n    ]\n    viewstate = soup.find(\"input\", attrs={\"id\": \"__VIEWSTATE\"})[\"value\"]\n    eventvalidation = soup.find(\"input\", attrs={\"id\": \"__EVENTVALIDATION\"})[\"value\"]\n\n    # Set date for post request.\n    if target_datetime:\n        target_date = target_datetime.date()\n    else:\n        # get the latest data\n        target_date = datetime.now().date()\n\n    month = target_date.month\n    day = target_date.day\n    year = target_date.year\n\n    FromDatePicker_clientState = (\n        '|0|01%s-%s-%s-0-0-0-0||[[[[]],[],[]],[{%s},[]],\"01%s-%s-%s-0-0-0-0\"]'\n        % (year, month, day, \"\", year, month, day)\n    )\n    ToDatePicker_clientState = (\n        '|0|01%s-%s-%s-0-0-0-0||[[[[]],[],[]],[{%s},[]],\"01%s-%s-%s-0-0-0-0\"]'\n        % (year, month, day, \"\", year, month, day)\n    )\n    btnDownloadCSV = \"Download+CSV\"\n    ig_def_dp_cal_clientState = (\n        '|0|15,2017,09,2017,%s,%s||[[null,[],null],[{%s},[]],\"11,2017,09,2017,%s,%s\"]'\n        % (month, day, \"\", month, day)\n    )\n    IG_CSS_LINKS_ = \"ig_res/default/ig_monthcalendar.css|ig_res/default/ig_texteditor.css|ig_res/default/ig_shared.css\"\n\n    postdata = {\n        \"__VIEWSTATE\": viewstate,\n        \"__VIEWSTATEGENERATOR\": viewstategenerator,\n        \"__EVENTVALIDATION\": eventvalidation,\n        \"FromDatePicker_clientState\": FromDatePicker_clientState,\n        \"ToDatePicker_clientState\": ToDatePicker_clientState,\n        \"btnDownloadCSV\": btnDownloadCSV,\n        \"_ig_def_dp_cal_clientState\": ig_def_dp_cal_clientState,\n        \"_IG_CSS_LINKS_\": IG_CSS_LINKS_,\n    }\n\n    postheaders = {\n        \"User-Agent\": \"Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:55.0) Gecko/20100101 Firefox/55.0\",\n        \"Accept\": \"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\",\n        \"Content-Type\": \"application/x-www-form-urlencoded\",\n    }\n\n    datareq = s.post(url, headers=postheaders, data=postdata)\n\n    return datareq.text\n\n\ndef add_default_tz(timestamp):\n    \"\"\"Adds Northern Ireland timezone to datetime object if tz = None.\"\"\"\n\n    NIR = tz.gettz(\"Europe/Belfast\")\n    modified_timestamp = timestamp.replace(tzinfo=timestamp.tzinfo or NIR)\n\n    return modified_timestamp\n\n\ndef create_production_df(text_data):\n    \"\"\"\n    Turns thermal csv data into a usable dataframe.\n    \"\"\"\n\n    cols_to_use = [0, 1, 2, 3, 4, 5]\n    df_production = pd.read_csv(StringIO(text_data), usecols=cols_to_use)\n    df_production.fillna(0.0, inplace=True)\n\n    return df_production\n\n\ndef create_exchange_df(text_data):\n    \"\"\"\n    Turns exchange csv data into a usable dataframe.\n    \"\"\"\n\n    df_exchange = pd.read_csv(StringIO(text_data))\n    df_exchange.fillna(0.0, inplace=True)\n\n    return df_exchange\n\n\ndef production_processor(df) -> list:\n    \"\"\"Creates quarter hour datapoints for thermal production.\"\"\"\n\n    datapoints = []\n    for index, row in df.iterrows():\n        snapshot = {}\n        snapshot[\"datetime\"] = add_default_tz(\n            parser.parse(row[\"TimeStamp\"], dayfirst=True)\n        )\n        snapshot[\"gas\"] = row[\"Gas_MW\"]\n        snapshot[\"coal\"] = row[\"Coal_MW\"]\n        snapshot[\"oil\"] = row[\"Distillate_MW\"] + row[\"Diesel_MW\"]\n        snapshot[\"wind\"] = row[\"Wind_MW\"]\n        if snapshot[\"wind\"] > -20:\n            snapshot[\"wind\"] = max(snapshot[\"wind\"], 0)\n        datapoints.append(snapshot)\n\n    return datapoints\n\n\ndef moyle_processor(df) -> list:\n    \"\"\"Creates quarter hour datapoints for GB exchange.\"\"\"\n\n    datapoints = []\n    for index, row in df.iterrows():\n        snapshot = {}\n        snapshot[\"datetime\"] = add_default_tz(\n            parser.parse(row[\"TimeStamp\"], dayfirst=True)\n        )\n        snapshot[\"netFlow\"] = row[\"Total_Moyle_Load_MW\"]\n        snapshot[\"source\"] = \"soni.ltd.uk\"\n        snapshot[\"sortedZoneKeys\"] = \"GB->GB-NIR\"\n        datapoints.append(snapshot)\n\n    return datapoints\n\n\ndef IE_processor(df) -> list:\n    \"\"\"Creates quarter hour datapoints for IE exchange.\"\"\"\n\n    datapoints = []\n    for index, row in df.iterrows():\n        snapshot = {}\n        snapshot[\"datetime\"] = add_default_tz(\n            parser.parse(row[\"TimeStamp\"], dayfirst=True)\n        )\n        netFlow = -1 * row[\"Tie_Lines_MW\"]\n        snapshot[\"netFlow\"] = netFlow\n        snapshot[\"source\"] = \"soni.ltd.uk\"\n        snapshot[\"sortedZoneKeys\"] = \"GB-NIR->IE\"\n        datapoints.append(snapshot)\n\n    return datapoints\n\n\n@refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key=\"GB-NIR\",\n    session=None,\n    target_datetime=None,\n    logger=logging.getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n\n    production_data = get_data(production_url, target_datetime)\n    production_df = create_production_df(production_data)\n    production = production_processor(production_df)\n\n    production_mix_by_quarter_hour = []\n\n    for datapoint in production:\n        production_mix = {\n            \"zoneKey\": zone_key,\n            \"datetime\": datapoint.get(\"datetime\", 0.0),\n            \"production\": {\n                \"coal\": datapoint.get(\"coal\", 0.0),\n                \"gas\": datapoint.get(\"gas\", 0.0),\n                \"oil\": datapoint.get(\"oil\", 0.0),\n                \"solar\": None,\n                \"wind\": datapoint.get(\"wind\", 0.0),\n            },\n            \"source\": \"soni.ltd.uk\",\n        }\n        production_mix_by_quarter_hour.append(\n            validate(production_mix, logger=logger, floor=1.0)\n        )\n\n    return production_mix_by_quarter_hour\n\n\ndef fetch_exchange(\n    zone_key1, zone_key2, session=None, target_datetime=None, logger=None\n) -> dict:\n    \"\"\"Requests the last known power exchange (in MW) between two countries.\"\"\"\n\n    exchange_data = get_data(exchange_url, target_datetime)\n    exchange_dataframe = create_exchange_df(exchange_data)\n    if \"->\".join(sorted([zone_key1, zone_key2])) == \"GB->GB-NIR\":\n        moyle = moyle_processor(exchange_dataframe)\n        return moyle\n    elif \"->\".join(sorted([zone_key1, zone_key2])) == \"GB-NIR->IE\":\n        IE = IE_processor(exchange_dataframe)\n        return IE\n    else:\n        raise NotImplementedError(\"This exchange pair is not implemented\")\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n    print(\"fetch_exchange(GB-NIR, GB) ->\")\n    print(fetch_exchange(\"GB-NIR\", \"GB\"))\n    print(\"fetch_exchange(GB-NIR, IE) ->\")\n    print(fetch_exchange(\"GB-NIR\", \"IE\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/GE.py",
    "content": "# Archived reason: Switched to ENTSOE parser for production data as it has higer resolution.\n\n\"\"\"Fetch the status of the Georgian electricity grid.\"\"\"\n\nimport urllib.parse\nfrom datetime import datetime, time, timedelta, timezone\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport numpy as np\nimport pandas\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    ProductionBreakdownList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix\nfrom electricitymap.contrib.types import ZoneKey\nfrom electricitymap.contrib.parsers.ENTSOE import (\n    fetch_exchange as ENTSOE_fetch_exchange,\n)\nfrom electricitymap.contrib.parsers.lib import config\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\nPARSER = \"GE.py\"\nTIMEZONE = ZoneInfo(\"Asia/Tbilisi\")\nZONE_KEY = ZoneKey(\"GE\")\n\nMINIMUM_PRODUCTION_THRESHOLD = 10  # MW\nURL = urllib.parse.urlsplit(\"https://gse.com.ge/apps/gsebackend/rest\")\nURL_STRING = URL.geturl()\nSOURCE = URL.netloc\n\n\n@config.refetch_frequency(timedelta(days=1))\ndef fetch_production(\n    zone_key: ZoneKey = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Request the last known production mix (in MW) of a given country.\"\"\"\n    session = session or Session()\n\n    target_datetime = (\n        datetime.now(timezone.utc)\n        if target_datetime is None\n        else target_datetime.astimezone(timezone.utc)\n    )\n\n    # Get the production mix for every hour on the (UTC) day of interest.\n    day = datetime.combine(target_datetime, time(), tzinfo=timezone.utc)\n    timestamp_from, timestamp_to = (\n        day,\n        day + timedelta(days=1) - timedelta(seconds=1),\n    )\n\n    # TODO: remove `verify=False` ASAP.\n    response = session.get(\n        f\"{URL_STRING}/diagramDownload\",\n        params={\n            \"fromDate\": timestamp_from.astimezone(TIMEZONE).strftime(\n                \"%Y-%m-%dT%H:%M:%S\"\n            ),\n            \"lang\": \"EN\",\n            \"toDate\": timestamp_to.astimezone(TIMEZONE).strftime(\"%Y-%m-%dT%H:%M:%S\"),\n            \"type\": \"FACT\",\n        },\n        verify=False,\n    )\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching production error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    tables = pandas.read_excel(\n        response.content,\n        header=None,\n        # labels column + the 24 columns of hourly data\n        usecols=[1] + list(range(3, 27)),\n        # drop every 11th row (separation between tables)\n        skiprows=lambda x: x % 11 == 0,\n    )\n\n    production_breakdown_list = ProductionBreakdownList(logger)\n    for _i, daily_table in reversed(\n        tuple(tables.groupby(np.arange(len(tables)) // 10))\n    ):\n        day = daily_table.iloc[1][1]\n        timestamps = pandas.date_range(start=day, freq=\"1H\", periods=24)\n\n        # zoom in on fields of interest\n        itemised_production_data = daily_table.iloc[4:8].set_index(1)\n        itemised_production_data.columns = timestamps\n\n        for timestamp, production in itemised_production_data.dropna(\n            axis=\"columns\", how=\"all\"\n        ).items():\n            dt = timestamp.to_pydatetime().replace(tzinfo=TIMEZONE)\n\n            production_mix = ProductionMix()\n            production_mix.add_value(\"gas\", production[\"Thermal Power Plants\"])\n            production_mix.add_value(\"hydro\", production[\"Hydro Power Plants\"])\n            production_mix.add_value(\"solar\", production[\"Solar Power Plants\"])\n            production_mix.add_value(\"wind\", production[\"Wind Power Plants\"])\n\n            production_breakdown_list.append(\n                zoneKey=zone_key,\n                datetime=dt.astimezone(timezone.utc),\n                source=SOURCE,\n                production=production_mix,\n            )\n    return production_breakdown_list.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey,\n    zone_key2: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Request the last known power exchange (in MW) between two countries.\"\"\"\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([zone_key1, zone_key2])))\n\n    if ZONE_KEY not in {zone_key1, zone_key2}:\n        raise ParserException(\n            PARSER,\n            f\"This parser can only parse exchanges to / from {ZONE_KEY}.\",\n            sorted_zone_keys,\n        )\n\n    session = session or Session()\n    if target_datetime is not None:\n        return ENTSOE_fetch_exchange(\n            zone_key1, zone_key2, session, target_datetime, logger\n        )\n\n    now = datetime.now(timezone.utc)\n    # The API uses the convention of positive net flow into GE.\n    # TODO: remove `verify=False` ASAP.\n    response = session.get(f\"{URL_STRING}/map\", verify=False)\n    if not response.ok:\n        raise ParserException(\n            PARSER,\n            f\"Exception when fetching exchange error code: {response.status_code}: {response.text}\",\n            sorted_zone_keys,\n        )\n\n    net_flows = response.json()[\"areaSum\"]\n\n    neighbour = zone_key2 if zone_key1 == ZONE_KEY else zone_key1\n    direction = -1 if sorted_zone_keys.startswith(ZONE_KEY) else 1\n    if neighbour == ZoneKey(\"AM\"):\n        net_flow = net_flows[\"armeniaSum\"]\n    elif neighbour == ZoneKey(\"AZ\"):\n        net_flow = net_flows[\"azerbaijanSum\"]\n    elif neighbour == ZoneKey(\"RU-1\"):\n        # GE->RU might be falsely reported, exchanges/*.yaml has a definition to\n        # use the Russian TSO for this flow.\n        net_flow = (\n            net_flows[\"russiaSum\"]\n            + net_flows[\"russiaJavaSum\"]\n            + net_flows[\"russiaSalkhinoSum\"]\n        )\n    elif neighbour == ZoneKey(\"TR\"):\n        net_flow = net_flows[\"turkeySum\"]\n    else:\n        raise NotImplementedError(f\"{sorted_zone_keys} pair is not implemented\")\n\n    exchange_list = ExchangeList(logger)\n    exchange_list.append(\n        zoneKey=sorted_zone_keys,\n        datetime=now.replace(second=0, microsecond=0),\n        netFlow=direction * net_flow,\n        source=SOURCE,\n    )\n    return exchange_list.to_list()\n\n\nif __name__ == \"__main__\":\n    # Never used by the Electricity Map backend, but handy for testing.\n\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n\n    print(\"fetch_production(target_datetime=datetime.datetime(2020, 1, 1)) ->\")\n    print(fetch_production(target_datetime=datetime(2020, 1, 1, tzinfo=timezone.utc)))\n\n    for neighbour in [\"AM\", \"AZ\", \"RU-1\", \"TR\"]:\n        print(f\"fetch_exchange('GE', {neighbour}) ->\")\n        print(fetch_exchange(ZONE_KEY, ZoneKey(neighbour)))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/HOPS.py",
    "content": "#!/usr/bin/env python3\n# Archived reason: Replaced by the ENTSOE parser for higher data granularity.\n\n\"\"\"Parser for power production in Croatia\"\"\"\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\n\nimport arrow\nimport pandas as pd\nfrom requests import Session\n\nURL = \"https://www.hops.hr/Home/PowerExchange\"\n\n\ndef fetch_solar_production(\n    feed_date, session: Session | None = None, logger: Logger = getLogger(__name__)\n) -> float | None:\n    \"\"\"\n    Calls extra resource at https://files.hrote.hr/files/EKO_BG/FORECAST/SOLAR/FTP/TEST_DRIVE/<dd.m.yyyy>.json\n    to get Solar power production in MW.\n    :param feed_date: date_time string from the original HOPS feed\n    \"\"\"\n    r = session or Session()\n\n    dt = datetime.strptime(feed_date, \"%Y-%m-%d %H:%M:%S\")\n    # Get all available files\n    dates_url = (\n        \"https://files.hrote.hr/files/EKO_BG/FORECAST/SOLAR/FTP/TEST_DRIVE/dates.json\"\n    )\n    response = r.get(dates_url)\n    dates = response.json()\n    # Use latest file to get more up to date estimation\n    solar_url = (\n        \"https://files.hrote.hr/files/EKO_BG/FORECAST/SOLAR/FTP/TEST_DRIVE/{}\".format(\n            dates[-1][\"Filename\"]\n        )\n    )\n    response = r.get(solar_url)\n    obj = response.json()\n\n    df = pd.DataFrame.from_dict(obj[\"FullPower\"]).set_index(\"Timestamp\")\n    df.index = pd.to_datetime(df.index)  # cast strings to datetimes\n    solar_production_dt = pd.Timestamp(feed_date, tz=\"Europe/Zagreb\").floor(\"1h\")\n    try:\n        solar = df[\"Value\"].loc[solar_production_dt]\n        # Converting to MW\n        solar *= 0.001\n    except KeyError:\n        logger.warning(f\"No value for Solar power production on {solar_production_dt}\")\n        solar = None\n\n    return solar\n\n\ndef fetch_production(\n    zone_key: str = \"HR\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    r = session or Session()\n    response = r.get(URL)\n    obj = response.json()\n\n    # We assume the timezone of the time returned is local time and convert to UTC\n    date_time = arrow.get(obj[\"updateTime\"]).replace(tzinfo=\"Europe/Belgrade\").to(\"utc\")\n\n    # The json returned contains a list of values\n    # 0 - 9 are individual exchanges with neighbouring countries\n    # 10 - 13 are cumulative exchanges with neigbouring countries\n    # 14 grid frequency\n    # 15 total load of Croatia\n    # 16 'Ukupna proizvodnja'  total generation\n    # 17 'Proizvodnja VE'      wind generation\n    df = pd.DataFrame.from_dict(obj[\"resources\"]).set_index(\"sourceName\")\n\n    # Get the wind power generation\n    # In some cases value may be negative. It looks like an issue at data source side.\n    wind = abs(df[\"value\"].loc[\"Proizvodnja VE\"])\n\n    solar = fetch_solar_production(obj[\"updateTime\"], session)\n\n    # Get the total power generation and substract wind and solar power\n    unknown = df[\"value\"].loc[\"Ukupna proizvodnja\"] - wind\n    if solar:\n        unknown -= solar\n\n    return [\n        {\n            \"zoneKey\": zone_key,\n            \"datetime\": date_time.datetime,\n            \"production\": {\"wind\": wind, \"solar\": solar, \"unknown\": unknown},\n            \"source\": \"hops.hr\",\n        }\n    ]\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production(HR)->\")\n    print(fetch_production(\"HR\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/IN_AP.py",
    "content": "from datetime import datetime\nfrom logging import Logger, getLogger\n\nfrom requests import Session\n\nfrom ..lib import IN, web, zonekey\n\nURL = \"https://core.ap.gov.in/CMDashBoard/UserInterface/Power/PowerReport.aspx\"\nZONE_KEY = \"IN-AP\"\nTIME_FORMAT = \"%d-%m-%Y %H:%M\"\nSOURCE = \"core.ap.gov.in\"\n\n\ndef fetch_production(\n    zone_key: str = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Fetch Andhra Pradesh  production\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    zonekey.assert_zone_key(zone_key, ZONE_KEY)\n\n    html = web.get_response_soup(zone_key, URL, session)\n    india_date = IN.read_datetime_from_span_id(\n        html, \"MainContent_lblPowerStatusDate\", TIME_FORMAT\n    )\n\n    hydro_value = IN.read_value_from_span_id(html, \"MainContent_lblHydel\")\n    gas_value = IN.read_value_from_span_id(html, \"MainContent_lblGas\")\n    wind_value = IN.read_value_from_span_id(html, \"MainContent_lblWind\")\n    solar_value = IN.read_value_from_span_id(html, \"MainContent_lblSolar\")\n\n    # All thermal centrals are considered coal based production\n    # https://en.wikipedia.org/wiki/Power_sector_of_Andhra_Pradesh\n    thermal_value = IN.read_value_from_span_id(html, \"MainContent_lblThermal\")\n\n    cgs_value = IN.read_value_from_span_id(html, \"MainContent_lblCGS\")\n    ipp_value = IN.read_value_from_span_id(html, \"MainContent_lblIPPS\")\n\n    return {\n        \"zoneKey\": zone_key,\n        \"datetime\": india_date,\n        \"production\": {\n            \"biomass\": 0.0,\n            \"coal\": thermal_value,\n            \"gas\": gas_value,\n            \"hydro\": hydro_value,\n            \"nuclear\": 0.0,\n            \"oil\": 0.0,\n            \"solar\": solar_value,\n            \"wind\": wind_value,\n            \"geothermal\": 0.0,\n            \"unknown\": round(cgs_value + ipp_value, 2),\n        },\n        \"storage\": {\"hydro\": 0.0},\n        \"source\": SOURCE,\n    }\n\n\ndef fetch_consumption(\n    zone_key: str = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Fetch Andhra Pradesh consumption\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    zonekey.assert_zone_key(zone_key, ZONE_KEY)\n\n    html = web.get_response_soup(zone_key, URL, session)\n    india_date = IN.read_datetime_from_span_id(\n        html, \"MainContent_lblPowerStatusDate\", TIME_FORMAT\n    )\n\n    demand_value = IN.read_value_from_span_id(html, \"MainContent_lblGridDemand\")\n\n    return {\n        \"zoneKey\": zone_key,\n        \"datetime\": india_date,\n        \"consumption\": demand_value,\n        \"source\": SOURCE,\n    }\n\n\nif __name__ == \"__main__\":\n    session = Session()\n    print(fetch_production(ZONE_KEY, session))\n    print(fetch_consumption(ZONE_KEY, session))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/IN_CT.py",
    "content": "from datetime import datetime\nfrom logging import Logger, getLogger\n\nfrom requests import Session\n\nfrom ..lib import IN, web, zonekey\n\nZONE_KEY = \"IN-CT\"\nURL = \"http://117.239.199.203/csptcl/GEN.aspx\"\nSOURCE = \"cspc.co.in\"\nTIME_FORMAT = \"hh:m DD-MM-YY\"\n\n\ndef fetch_consumption(\n    zone_key: str = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Fetch Chhattisgarh consumption\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    zonekey.assert_zone_key(zone_key, ZONE_KEY)\n\n    html = web.get_response_soup(zone_key, URL, session)\n\n    india_date_time = IN.read_datetime_from_span_id(html, \"L34\", TIME_FORMAT)\n    demand_value = IN.read_value_from_span_id(html, \"L26\")\n\n    return {\n        \"zoneKey\": zone_key,\n        \"datetime\": india_date_time.datetime,\n        \"consumption\": demand_value,\n        \"source\": SOURCE,\n    }\n\n\ndef fetch_production(\n    zone_key: str = ZONE_KEY,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Fetch Chhattisgarh production\"\"\"\n\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    zonekey.assert_zone_key(zone_key, ZONE_KEY)\n\n    html = web.get_response_soup(zone_key, URL, session)\n\n    india_date_time = IN.read_datetime_from_span_id(html, \"L34\", \"hh:m DD-MM-YY\")\n    korba_east_value = IN.read_value_from_span_id(html, \"L3\")\n    korba_west_value = IN.read_value_from_span_id(html, \"L9\")\n    dsmp_value = IN.read_value_from_span_id(html, \"L12\")\n    marwa_value = IN.read_value_from_span_id(html, \"L19\")\n    coal_value = round(\n        korba_east_value + korba_west_value + dsmp_value + marwa_value, 2\n    )\n    bango_value = IN.read_value_from_span_id(html, \"L16\")\n\n    return {\n        \"zoneKey\": zone_key,\n        \"datetime\": india_date_time.datetime,\n        \"production\": {\"coal\": coal_value, \"hydro\": bango_value},\n        \"source\": SOURCE,\n    }\n\n\nif __name__ == \"__main__\":\n    session = Session()\n    print(fetch_production(ZONE_KEY, session))\n    print(fetch_consumption(ZONE_KEY, session))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/IN_GJ.py",
    "content": "#!/usr/bin/env python3\n\nimport collections\nimport itertools\nimport re\nfrom datetime import datetime\nfrom logging import Logger, getLogger\nfrom operator import itemgetter\n\nimport arrow\nfrom requests import Session\n\nfrom ..lib import web, zonekey\nfrom ..lib.validation import validate\n\nSLDCGUJ_URL = (\n    \"http://www.sldcguj.com/RealTimeData/PrintPage.php?page=realtimedemand.php\"\n)\n\nstation_map = {\n    \"coal\": [\n        \"Ukai(1-5)+Ukai6\",\n        \"Wanakbori\",\n        \"Gandhinagar\",\n        \"Sikka(3-4)\",\n        \"KLTPS(1-3)+KLTPS4\",\n        \"SLPP(I+II)\",\n        \"Akrimota\",\n        \"TPAECo\",\n        \"EPGL(I+II)\",\n        \"Adani(I+II+III)\",\n        \"BECL(I+II)\",\n        \"CGPL\",\n    ],\n    \"hydro\": [\"Ukai(Hydro)\", \"Kadana(Hydro)\", \"SSP(RBPH)\"],\n    \"gas\": [\n        \"Utran(Gas)(II)\",\n        \"Dhuvaran(Gas)(I)+(II)+(III)\",\n        \"GIPCL(I)+(II)\",\n        \"GSEG(I+II)\",\n        \"GPPC\",\n        \"CLPI\",\n        \"KAWAS\",\n        \"Sugen+Unosgn\",\n        \"JHANOR\",\n    ],\n    \"nuclear\": [\"KAPP\"],\n}\n\n\ndef split_and_sum(expression) -> float:\n    \"\"\"Avoid using literal_eval for simple addition expressions.\"\"\"\n\n    split_vals = expression.split(\"+\")\n    float_vals = [float(v) for v in split_vals]\n    total = sum([v for v in float_vals if v > 0.0])\n\n    return total\n\n\ndef fetch_data(\n    zone_key: str,\n    session: Session | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    session = session or Session()\n\n    values = collections.Counter()\n    zonekey.assert_zone_key(zone_key, \"IN-GJ\")\n\n    cookies_params = {\n        \"ASPSESSIONIDSUQQQTRD\": \"ODMNNHADJFGCMLFFGFEMOGBL\",\n        \"PHPSESSID\": \"a301jk6p1p8d50dduflceeg6l1\",\n    }\n\n    soup = web.get_response_soup(zone_key, SLDCGUJ_URL, session)\n    rows = soup.find_all(\"tr\")\n    cells = [c.text.strip() for c in soup.find_all(\"td\")]\n\n    # get wind and solar values\n    values[\"date\"] = arrow.get(cells[1], \"D-MM-YYYY H:mm:ss\").replace(\n        tzinfo=\"Asia/Kolkata\"\n    )\n    [wind_solar_index] = [\n        i for i, c in enumerate(cells) if c == \"(Wind+Solar) Generation\"\n    ]\n    value = cells[wind_solar_index + 1]\n    values[\"wind\"], values[\"solar\"] = (int(v) for v in value.split(\" + \"))\n\n    # get other production values\n    for row in rows:\n        elements = row.find_all(\"td\")\n        if len(elements) > 3:  # will find production rows\n            v1, v2 = (\n                re.sub(r\"\\s+\", r\"\", x.text) for x in itemgetter(*[0, 3])(elements)\n            )\n            energy_type = [k for k, v in station_map.items() if v1 in v]\n            if len(energy_type) > 0:\n                v2 = split_and_sum(v2)\n                values[energy_type[0]] += v2\n            else:\n                if \"StationName\" in (v1, v2):  # meta data row\n                    continue\n                elif \"DSMRate\" in v2:  # demand side management\n                    continue\n                else:\n                    try:\n                        logger.warning(\n                            f\"Unknown fuel for station name: {v1}\",\n                            extra={\"key\": zone_key},\n                        )\n                        v2 = split_and_sum(v2)\n                        values[\"unknown\"] += v2\n                    except ValueError:\n                        # handle float failures\n                        logger.warning(\n                            f\"couldn't convert {v2} to float\",\n                            extra={\"key\": zone_key},\n                        )\n                        continue\n        elif len(elements) == 3:  # will find consumption row\n            v1, v2 = (\n                re.sub(r\"\\s+\", r\"\", x.text) for x in itemgetter(*[0, 2])(elements)\n            )\n            if v1 == \"GujaratCatered\":\n                values[\"total consumption\"] = split_and_sum(v2.split(\"MW\")[0])\n        elif len(elements) == 1:\n            # CGPL/KAPP/KAWAS/JHANOR plants have a different html structure.\n            plant_name = re.sub(r\"\\s+\", r\"\", elements[0].text)\n            known_plants = itertools.chain.from_iterable(station_map.values())\n\n            if plant_name in known_plants:\n                energy_type = [k for k, v in station_map.items() if plant_name in v][0]\n                generation_tag = row.find_all_next(\"td\")[3]\n                val = float(re.sub(r\"\\s+\", r\"\", generation_tag.text))\n                if val > 0:\n                    values[energy_type] += val\n            else:\n                if plant_name and plant_name != \"GMR\":\n                    # GMR is outside Gujarat, sometimes plant_name is ''\n                    logger.warning(\n                        f\"Unknown fuel for station name: {plant_name}\",\n                        extra={\"key\": zone_key},\n                    )\n\n    return values\n\n\ndef fetch_production(\n    zone_key: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    session = session or Session()\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    value_map = fetch_data(zone_key, session, logger=logger)\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": value_map[\"date\"].datetime,\n        \"production\": {\n            \"biomass\": None,\n            \"coal\": value_map.get(\"coal\", 0),\n            \"gas\": value_map.get(\"gas\", 0),\n            \"hydro\": value_map.get(\"hydro\", 0),\n            \"nuclear\": value_map.get(\"nuclear\", 0),\n            \"oil\": None,\n            \"solar\": value_map.get(\"solar\", 0),\n            \"wind\": value_map.get(\"wind\", 0),\n            \"geothermal\": None,\n            \"unknown\": value_map.get(\"unknown\", 0),\n        },\n        \"storage\": {\"hydro\": None},\n        \"source\": \"sldcguj.com\",\n    }\n\n    valid_data = validate(data, logger, remove_negative=True, floor=7000)\n\n    return valid_data\n\n\ndef fetch_consumption(\n    zone_key=\"IN-GJ\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(\"IN-GJ\"),\n) -> dict:\n    \"\"\"Method to get consumption data of Gujarat.\"\"\"\n    session = session or Session()\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    value_map = fetch_data(zone_key, session, logger=logger)\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": value_map[\"date\"].datetime,\n        \"consumption\": value_map[\"total consumption\"],\n        \"source\": \"sldcguj.com\",\n    }\n\n    return data\n\n\nif __name__ == \"__main__\":\n    session = Session()\n    print(fetch_production(\"IN-GJ\", session))\n    print(fetch_consumption(\"IN-GJ\", session))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/IN_UP.py",
    "content": "#!/usr/bin/env python3\n# Archived reason: Data is no longer available.\n\nimport json\nfrom ast import literal_eval\n\nimport arrow\nfrom requests import Session\n\nfrom .lib import web\n\n\ndef fetch_data(zone_key=\"IN-UP\", session=None):\n    time_now = arrow.now(tz=\"Asia/Kolkata\")\n\n    html_params = {\n        \"p_p_id\": \"upgenerationsummary_WAR_UPSLDCDynamicDisplayportlet\",\n        \"p_p_lifecycle\": 2,\n        \"p_p_state\": \"normal\",\n        \"p_p_mode\": \"view\",\n        \"p_p_resource_id\": \"realtimedata\",\n        \"p_p_cacheability\": \"cacheLevelPage\",\n        \"p_p_col_id\": \"column-1\",\n        \"p_p_col_count\": 1,\n        \"_upgenerationsummary_WAR_UPSLDCDynamicDisplayportlet_time\": time_now,\n        \"_upgenerationsummary_WAR_UPSLDCDynamicDisplayportlet_cmd\": \"realtimedata\",\n    }\n\n    key_map = {\n        \"total hydro generation\": \"hydro\",\n        \"total thermal up generation\": \"unknown\",\n        \"cogen-sent out\": \"unknown\",\n        \"solar generation\": \"solar\",\n        \"total up load/demand\": \"demand\",\n    }\n\n    response_objects = literal_eval(\n        web.get_response_with_params(\n            zone_key,\n            \"http://www.upsldc.org/real-time-data\",\n            session,\n            params=html_params,\n        ).text.lower()\n    )\n    india_date = arrow.get(\n        json.loads(list(response_objects[1].values())[0])[\"time_val\"],\n        \"M/D/YYYY h:m\",\n        tzinfo=\"Asia/Kolkata\",\n    )\n\n    value_map = {\n        \"date\": india_date.datetime,\n        \"production\": {\n            \"solar\": None,\n            \"hydro\": None,\n            \"geothermal\": None,\n            \"wind\": None,\n            \"gas\": None,\n            \"coal\": None,\n            \"unknown\": None,\n        },\n        \"consumption\": {\"demand\": None},\n    }\n\n    for obj in response_objects:\n        val = json.loads(list(obj.values())[0])\n        if \"point_desc\" in val and val[\"point_desc\"] in key_map:\n            if key_map[val[\"point_desc\"]] == \"demand\":\n                value_map[\"consumption\"][\"demand\"] = float(val[\"point_val\"])\n            else:\n                check = value_map[\"production\"][key_map[val[\"point_desc\"]]]\n                if check is None:\n                    value_map[\"production\"][key_map[val[\"point_desc\"]]] = float(\n                        val[\"point_val\"]\n                    )\n                else:\n                    value_map[\"production\"][key_map[val[\"point_desc\"]]] += float(\n                        val[\"point_val\"]\n                    )\n\n    return value_map\n\n\ndef fetch_production(zone_key, session=None, target_datetime=None, logger=None) -> dict:\n    \"\"\"Method to get production data of Uttar Pradesh.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    value_map = fetch_data(zone_key, session)\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": value_map.get(\"date\"),\n        \"production\": value_map.get(\"production\"),\n        \"storage\": {\"hydro\": None},\n        \"source\": \"upsldc.org\",\n    }\n\n    return data\n\n\ndef fetch_consumption(\n    zone_key, session=None, target_datetime=None, logger=None\n) -> dict:\n    \"\"\"Method to get consumption data of Uttar Pradesh.\"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    value_map = fetch_data(zone_key, session)\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"datetime\": value_map.get(\"date\"),\n        \"consumption\": value_map[\"consumption\"].get(\"demand\"),\n        \"source\": \"upsldc.org\",\n    }\n\n    return data\n\n\nif __name__ == \"__main__\":\n    session = Session()\n    print(fetch_production(\"IN-UP\", session))\n    print(fetch_consumption(\"IN-UP\", session))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/IQ.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Parser for the electricity grid of Iraq\"\"\"\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\n\nimport arrow\nimport requests\nfrom dateutil.tz import tz\nfrom requests import Session\n\nLIVE_PRODUCTION_API_URL = \"https://www.gdoco.org/vueips.php\"\nDATA_SOURCE = \"www.gdoco.org\"\nCELL_MAPPING = {\n    \"hydro\": [\"1220\"],\n    \"gas\": [\"1219\"],\n    \"oil\": [\"1218\", \"1221\"],  # Thermal  # Diesel\n}\n\n\ndef template_response(zone_key: str, datetime: datetime, source: str) -> dict:\n    return {\n        \"zoneKey\": zone_key,\n        \"datetime\": datetime,\n        \"production\": {\n            \"gas\": 0.0,\n            \"hydro\": 0.0,\n            \"oil\": 0.0,\n            \"solar\": None,  # IEA has a count, but no data is available\n        },\n        \"storage\": {},\n        \"source\": source,\n    }\n\n\ndef fetch_data(r: Session):\n    resp = r.get(LIVE_PRODUCTION_API_URL)\n    data = resp.json()\n\n    timestamp = arrow.get(\n        data[\"lastmodified\"], \"HH:mm:ss A DD-MM-YYYY\", tzinfo=tz.gettz(\"Asia/Baghdad\")\n    )\n\n    return data[\"d\"], timestamp.datetime\n\n\ndef fetch_production(\n    zone_key: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known production mix (in MW) of a given zone.\"\"\"\n    if target_datetime is not None:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    r = session or requests.session()\n    data, timestamp = fetch_data(r)\n\n    result = template_response(zone_key, timestamp, DATA_SOURCE)\n\n    for production_type, ids in CELL_MAPPING.items():\n        for data_id in ids:\n            result[\"production\"][production_type] += data[\"d_\" + data_id]\n\n    return [result]\n\n\ndef fetch_exchange(\n    zone_key1: str,\n    zone_key2: str,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    r = session or requests.session()\n    data, timestamp = fetch_data(r)\n\n    sortedZoneKeys = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    if sortedZoneKeys == \"IQ->IR\":\n        netflow = -1 * (\n            data[\"d_1226\"] + data[\"d_1227\"] + data[\"d_1228\"] + data[\"d_1229\"]\n        )\n    elif sortedZoneKeys == \"IQ->IQ-KUR\":\n        netflow = -1 * data[\"d_1230\"]\n    else:\n        raise NotImplementedError(\"This exchange pair is not implemented\")\n\n    exchange = {\n        \"sortedZoneKeys\": sortedZoneKeys,\n        \"datetime\": timestamp,\n        \"netFlow\": netflow,\n        \"source\": DATA_SOURCE,\n    }\n\n    return exchange\n\n\ndef fetch_consumption(\n    zone_key: str = \"IQ\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    r = session or requests.session()\n\n    data, timestamp = fetch_data(r)\n\n    consumption = {\n        \"zoneKey\": zone_key,\n        \"datetime\": timestamp,\n        \"consumption\": data[\"d_1234\"],\n        \"source\": DATA_SOURCE,\n    }\n\n    return consumption\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n    r = requests.session()\n    print(fetch_production(session=r))\n    # print(fetch_production(target_datetime=arrow.get(\"20200220\", \"YYYYMMDD\")))\n    print(fetch_exchange(\"IQ\", \"IR\", session=r))\n    print(fetch_exchange(\"IQ\", \"IQ-KUR\", session=r))\n    print(fetch_consumption(session=r))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/JP_ISEP.py",
    "content": "#!/usr/bin/env python3\n# Archive reason: No longer in use.\n\nimport datetime\nimport logging\nimport re\n\nimport pandas as pd\nimport requests\n\nurl = \"https://isep-energychart.com/en/graphics/electricityproduction/?region={region}&period_year={year}&period_month={month}&period_day={day}&period_length=1day&display_format=residual_demand\"\ntimezone = \"Japan\"\n\nMAP_ZONE_TO_REGION_NAME = {\n    \"JP\": \"all\",\n    \"JP-HKD\": \"hokkaido\",\n    \"JP-TH\": \"tohoku\",\n    \"JP-TK\": \"tokyo\",\n    \"JP-CB\": \"chubu\",\n    \"JP-HR\": \"hokuriku\",\n    \"JP-KN\": \"kansai\",\n    \"JP-CG\": \"chugoku\",\n    \"JP-SK\": \"shikoku\",\n    \"JP-KY\": \"kyushu\",\n    \"JP-ON\": \"okinawa\",\n}\n\nCOLUMN_MAP = {\n    \"demand\": \"consumption\",\n    \"wind_performance\": \"wind\",\n    \"solar_performance\": \"solar\",\n    \"thermal\": \"unknown\",\n    \"pumped\": \"pumped hydro\",\n    \"interconnection\": \"exchanges\",\n    \"solar_suppression\": \"solar curtailment\",\n    \"wind_suppression\": \"wind curtailment\",\n}\n\n\ndef get_data(region, year, month, day):\n    r = requests.get(url.format(region=region, year=year, month=month, day=day))\n\n    assert r.status_code == 200, \"Could not get url\"\n\n    jsonval_matches = re.findall(\n        \"(?<=var jsonval = JSON.parse\\\\(').*(?='\\\\)\\n\\t)\", r.text\n    )\n    assert len(jsonval_matches), (\n        \"Data not found. Perhaps the format of the html file has changed, or data for this date is not yet available?\"\n    )\n\n    df = pd.read_json(jsonval_matches[0])\n\n    return df\n\n\ndef process_data(df):\n    # convert to timestamp with timezone info\n    df[\"date_time\"] = (\n        pd.to_datetime(df[\"date_time\"]).dt.tz_localize(timezone).dt.tz_convert(\"UTC\")\n    )\n\n    df = df.rename(columns=COLUMN_MAP)\n\n    df[\"hydro storage\"] = df[\"pumped hydro\"].map(lambda x: x if x < 0 else 0)\n    df[\"hydro discharge\"] = df[\"pumped hydro\"].map(lambda x: x if x > 0 else 0)\n\n    # Should be removed if we ever handle curtailment data separately\n    if \"wind\" in df.columns:\n        df[\"wind adjusted\"] = df[\"wind\"] + df.get(\"wind curtailment\", 0)\n\n    if \"solar\" in df.columns:\n        df[\"solar adjusted\"] = df[\"solar\"] + df.get(\"solar curtailment\", 0)\n    return df\n\n\ndef fetch_production(\n    zone_key=\"JP\",\n    session=None,\n    target_datetime: datetime.datetime = None,\n    logger: logging.Logger = logging.getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the historic production mix (in MW) of japan.\"\"\"\n    if target_datetime is None:\n        # This data is only available with approx 4 month delay\n        raise NotImplementedError(\n            \"target_datetime must be provided, this parser can only parse historic data\"\n        )\n\n    region = MAP_ZONE_TO_REGION_NAME[zone_key]\n\n    year = target_datetime.year\n    month = target_datetime.month\n    day = target_datetime.day\n\n    df = get_data(region, year, month, day)\n    df = process_data(df)\n\n    data = []\n    for name, row in df.iterrows():\n        dat = {\n            \"datetime\": row[\"date_time\"].to_pydatetime(),\n            \"zoneKey\": zone_key,\n            \"production\": {\n                \"biomass\": row.get(\"biomass\", None),\n                \"hydro\": row.get(\"hydro\", None),\n                \"hydro discharge\": row.get(\"hydro discharge\", None),\n                \"nuclear\": row.get(\"nuclear\", None),\n                \"solar\": row.get(\"solar adjusted\", None),\n                \"wind\": row.get(\"wind adjusted\", None),\n                \"geothermal\": row.get(\"geothermal\", None),\n                \"unknown\": row.get(\"unknown\", None),\n            },\n            \"storage\": {\"hydro\": row.get(\"hydro storage\", None)},\n            \"source\": \"isep-energychart.com\",\n        }\n        data += [dat]\n\n    return data\n\n\ndef fetch_consumption(\n    zone_key=\"JP\",\n    session=None,\n    target_datetime: datetime.datetime = None,\n    logger: logging.Logger = logging.getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the historic consumption mix (in MW) of japan.\"\"\"\n    if target_datetime is None:\n        # This data is only available with approx 4 month delay\n        raise NotImplementedError(\n            \"target_datetime must be provided, this parser can only parse historic data\"\n        )\n\n    region = MAP_ZONE_TO_REGION_NAME[zone_key]\n\n    year = target_datetime.year\n    month = target_datetime.month\n    day = target_datetime.day\n\n    df = get_data(region, year, month, day)\n    df = process_data(df)\n\n    data = []\n    for name, row in df.iterrows():\n        dat = {\n            \"datetime\": row[\"date_time\"].to_pydatetime(),\n            \"zoneKey\": zone_key,\n            \"consumption\": row.get(\"consumption\", None),\n            \"source\": \"isep-energychart.com\",\n        }\n        data += [dat]\n\n    return data\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    print(fetch_production(target_datetime=pd.Timestamp(\"2019-01-01\")))\n    print(\"fetch_consumption() ->\")\n    print(fetch_consumption(target_datetime=pd.Timestamp(\"2019-01-01\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/SE.py",
    "content": "# Archived reason: No longer in use and data url has changed.\n\nimport datetime\nfrom collections import defaultdict\n\nimport arrow\nimport requests\n\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\n\nSVK_URL = (\n    \"http://www.svk.se/ControlRoom/GetProductionHistory/\"\n    \"?productionDate={date}&countryCode={zoneKey}\"\n)\n\n# what the value refer to (FYI)\nNAMES_MEANING = {\n    2: \"nuclear\",\n    4: \"thermal\",\n    5: \"wind\",\n    6: \"unknown\",\n    1: \"production\",\n    7: \"consumption\",\n    3: \"hydro\",\n}\n# mapping from the value to electricity map values\nMAPPING = {\n    2: \"nuclear\",\n    4: \"unknown\",\n    5: \"wind\",\n    6: \"unknown\",\n    1: None,\n    7: None,\n    3: \"hydro\",\n}\n\n\n@refetch_frequency(datetime.timedelta(days=1))\ndef fetch_production(\n    zone_key=\"SE\", session=None, target_datetime=None, logger=None\n) -> list:\n    # parse target_datetime - and convert None to now\n    target_datetime = arrow.get(target_datetime).datetime\n    url = SVK_URL.format(date=target_datetime.strftime(\"%Y-%m-%d\"), zoneKey=\"SE\")\n\n    data = requests.get(url).json()\n\n    # creating a dict looking like\n    # {'2018-01-01 01:00': {'nuclear': xxx, 'hydro': ...}, ...}\n    productions = defaultdict(lambda: defaultdict(lambda: 0))\n    for sub_data in data:\n        # sub_data is a list of (x, y) values for that prod type\n        # x is a timestamp, y a value (MWH)\n        name = MAPPING[sub_data[\"name\"]]\n        if not name:\n            continue\n        for value in sub_data[\"data\"]:\n            dt = datetime.datetime.fromtimestamp(value[\"x\"] / 1000)\n            prod = value[\"y\"]\n            productions[dt][name] += prod\n\n    datetimes = sorted(list(productions))\n\n    # SVK returns almost a point per minute, but only nuclear is updated\n    # with that granularity. Other points are updated every hour, at minute 6\n    to_return = []\n    last_inserted_datetime = datetime.datetime(2010, 1, 1)\n    for dt in datetimes:\n        if (dt - last_inserted_datetime).total_seconds() < 3200 or dt.minute < 7:\n            continue\n        last_inserted_datetime = dt\n        prod = productions[dt]\n        to_return.append(\n            {\n                \"production\": dict(prod),\n                \"datetime\": dt.replace(minute=0).replace(tzinfo=datetime.timezone.utc),\n                \"zoneKey\": \"SE\",\n                \"storage\": {},\n                \"source\": \"svk.se\",\n            }\n        )\n\n    return to_return\n\n\nif __name__ == \"__main__\":\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/US_BPA.py",
    "content": "#!/usr/bin/env python3\n# Archive reason: No longer in use.\n\n\"\"\"Parser for the Bonneville Power Administration area of the USA.\"\"\"\n\nimport logging\nfrom io import StringIO\n\nimport arrow\nimport pandas as pd\nimport requests\n\nGENERATION_URL = \"https://transmission.bpa.gov/business/operations/Wind/baltwg.txt\"\n\nGENERATION_MAPPING = {\n    \"Wind\": \"wind\",\n    \"Hydro\": \"hydro\",\n    \"Fossil/Biomass\": \"unknown\",\n    \"Nuclear\": \"nuclear\",\n}\n\n\ndef get_data(url, session=None):\n    \"\"\"Returns a pandas dataframe.\"\"\"\n    s = session or requests.Session()\n    req = s.get(url)\n    df = pd.read_table(StringIO(req.text), skiprows=11)\n\n    return df\n\n\ndef timestamp_converter(timestamp):\n    \"\"\"Turns a timestamp str into an aware datetime object.\"\"\"\n\n    arr_dt_naive = arrow.get(timestamp, \"MM/DD/YYYY HH:mm\")\n    dt_aware = arr_dt_naive.replace(tzinfo=\"America/Los_Angeles\").datetime\n\n    return dt_aware\n\n\ndef data_processor(df, logger) -> list:\n    \"\"\"\n    Takes a dataframe and drops all generation rows that are empty or more than 1 day old.\n    Turns each row into a dictionary and removes any generation types that are unknown.\n\n    :return: list of tuples in the form of (datetime, production).\n    \"\"\"\n\n    df = df.dropna(thresh=2)\n    df.columns = df.columns.str.strip()\n\n    # 5min data for the last 24 hours.\n    df = df.tail(288)\n    df[\"Date/Time\"] = df[\"Date/Time\"].map(timestamp_converter)\n\n    known_keys = GENERATION_MAPPING.keys() | {\"Date/Time\", \"Load\"}\n    column_headers = set(df.columns)\n\n    unknown_keys = column_headers - known_keys\n\n    for k in unknown_keys:\n        logger.warning(\n            f\"New data {k} seen in US-BPA data source\", extra={\"key\": \"US-BPA\"}\n        )\n\n    keys_to_remove = unknown_keys | {\"Load\"}\n\n    processed_data = []\n    for index, row in df.iterrows():\n        production = row.to_dict()\n\n        dt = production.pop(\"Date/Time\")\n        dt = dt.to_pydatetime()\n        mapped_production = {\n            GENERATION_MAPPING[k]: v\n            for k, v in production.items()\n            if k not in keys_to_remove\n        }\n\n        processed_data.append((dt, mapped_production))\n\n    return processed_data\n\n\ndef fetch_production(\n    zone_key=\"US-BPA\",\n    session=None,\n    target_datetime=None,\n    logger=logging.getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known production mix (in MW) of a given zone.\"\"\"\n\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    raw_data = get_data(GENERATION_URL, session=session)\n    processed_data = data_processor(raw_data, logger)\n\n    data = []\n    for item in processed_data:\n        datapoint = {\n            \"zoneKey\": zone_key,\n            \"datetime\": item[0],\n            \"production\": item[1],\n            \"storage\": {},\n            \"source\": \"bpa.gov\",\n        }\n\n        data.append(datapoint)\n\n    return data\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production() ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/US_HI.py",
    "content": "#!/usr/bin/env python3\n\n\nfrom datetime import datetime\nfrom logging import Logger, getLogger\n\nimport arrow\nfrom requests import Session\n\nBASE_URL = \"https://www.islandpulse.org/api/mix?\"\n\nEARLIEST_PROD_DT = arrow.get(\n    \"2013/12/04 08:30\", tzinfo=\"Pacific/Honolulu\"\n)  # this is the earliest datetime with recorded data\n\n\ndef get_historical_prod(r, request_dt):\n    \"\"\"Return the closest historical data (as a dictionary) for the requested datetime.\"\"\"\n    if request_dt < EARLIEST_PROD_DT.shift(hours=-2):\n        return None\n\n    # The API does not provide energy production data between 11:31pm and 11:59pm HST, so adjust date to query if needed\n    if request_dt.hour == 23 and (31 <= request_dt.minute <= 59):\n        query_url = BASE_URL + \"date={}\".format(\n            request_dt.shift(days=+1).format(\"YYYY-MM-DD\")\n        )\n    else:\n        query_url = BASE_URL + \"date={}\".format(request_dt.format(\"YYYY-MM-DD\"))\n    res = r.get(query_url).json()\n\n    # the first entry returned always has a UTC datetime, but any additional entries are in descending HST (local time)\n    res[0][\"dateTime\"] = (\n        arrow.get(res[0][\"dateTime\"]).to(tz=\"Pacific/Honolulu\").datetime\n    )\n\n    raw_data = res[0]\n    for entry in res:\n        if arrow.get(entry[\"dateTime\"], tzinfo=\"Pacific/Honolulu\") >= request_dt:\n            raw_data = entry\n        else:\n            break\n\n    return raw_data\n\n\ndef validate_prod_timestamp(logger: Logger, energy_dt, request_dt):\n    \"\"\"Check that the energy production data was captured up to 2 hours after the requested datetime.\n    Compares two Arrow objects in local HST time.\"\"\"\n    diff = energy_dt - request_dt\n    if diff.total_seconds() > 7200:\n        msg = f\"Hawaii data is too old to use, parsed data timestamp was {energy_dt}.\"\n        logger.warning(msg, extra={\"key\": \"US-HI-OA\"})\n        return False\n\n    return True\n\n\ndef fetch_production(\n    zone_key: str = \"US-HI-OA\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    r = session or Session()\n    if target_datetime is None:\n        request_dt = arrow.now(\"Pacific/Honolulu\")\n        res = r.get(BASE_URL + \"limit=1\").json()\n        raw_data = res[0]\n        # the first entry returned by the API always has a UTC datetime, but any additional entries are in HST (local time)\n        raw_data[\"dateTime\"] = (\n            arrow.get(raw_data[\"dateTime\"]).to(tz=\"Pacific/Honolulu\").datetime\n        )\n    else:\n        request_dt = arrow.get(target_datetime).to(tz=\"Pacific/Honolulu\")\n        raw_data = get_historical_prod(r, request_dt)\n        if raw_data is None:\n            return None\n\n    energy_dt = arrow.get(raw_data[\"dateTime\"], tzinfo=\"Pacific/Honolulu\")\n    if validate_prod_timestamp(logger, energy_dt, request_dt) is False:\n        return None\n\n    production = {\n        \"biomass\": float(raw_data[\"Waste2Energy\"] + raw_data[\"BioFuel\"]),\n        \"coal\": float(raw_data[\"Coal\"]),\n        \"oil\": float(raw_data[\"Fossil_Fuel\"]),\n        \"solar\": float(raw_data[\"Solar\"]),\n        \"wind\": float(raw_data[\"WindFarm\"]),\n    }\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"production\": production,\n        \"datetime\": energy_dt.datetime,\n        \"storage\": {},\n        \"source\": \"islandpulse.org\",\n    }\n\n    return data\n\n\nif __name__ == \"__main__\":\n    print(\"fetch_production ->\")\n    print(fetch_production())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/XK.py",
    "content": "#!/usr/bin/env python3\n# Archive reason: No longer in use.\n\nimport datetime\nimport logging\nimport re\n\n# The arrow library is used to handle datetimes\nimport arrow\n\n# The request library is used to fetch content through HTTP\nimport requests\n\n# Tablib is used to parse XLSX files\nimport tablib\n\n# please try to write PEP8 compliant code (use a linter). One of PEP8's\n# requirement is to limit your line length to 79 characters.\n\n\ndef fetch_production(\n    zone_key=\"XK\",\n    session=None,\n    target_datetime: datetime.datetime = None,\n    logger: logging.Logger = logging.getLogger(__name__),\n) -> list:\n    \"\"\"Requests the last known production mix (in MW) of a given country.\"\"\"\n    r = session or requests.session()\n    if target_datetime is None:\n        url = \"https://www.kostt.com/Content/ViewFiles/Transparency/BasicMarketDataOnGeneration/Prodhimi%20aktual%20gjenerimi%20faktik%20i%20energjise%20elektrike.xlsx\"\n    else:\n        # WHEN HISTORICAL DATA IS NOT AVAILABLE\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    res = r.get(url)\n    assert res.status_code == 200, \"XK (Kosovo) parser: GET {} returned {}\".format(\n        url, res.status_code\n    )\n\n    sheet = tablib.Dataset().load(res.content, headers=False)\n\n    productions = {}  # by time\n    for i in range(5, 1000):\n        try:\n            row = sheet[i]\n        except IndexError:\n            break\n        time = row[1]\n        if time is None:\n            break\n        if isinstance(time, float):\n            time = datetime.time(hour=round(time * 24) % 24)\n        time_str = time.strftime(\"%H:%M\")\n        assert \"TC KOSOVA\" in row[3], \"Parser assumes only coal data\"\n        prod = float(row[2])\n        productions[time_str] = productions.get(time_str, 0.0) + prod\n\n    date_match = re.search(\n        r\"ACTUAL\\s+GENERATION\\s+FOR\\s+DAY\\s+(\\d+)\\.(\\d+)\\.(\\d+)\", sheet[1][1]\n    )\n    assert date_match is not None, \"Date not found in spreadsheet\"\n    date_str = (\n        date_match.group(3)\n        + \"-\"\n        + date_match.group(2)\n        + \"-\"\n        + date_match.group(1)\n        + \" \"\n    )\n\n    data = []\n    for time_str, prod in productions.items():\n        timestamp = arrow.get(date_str + time_str).replace(tzinfo=\"Europe/Belgrade\")\n        timestamp = timestamp.shift(hours=-1)  # shift to start of period\n        if time_str == \"00:00\":\n            # Based on the apparent discontinuity in production and the order in the spreadsheet\n            # it seems that the last data-point belongs to the next day\n            timestamp = timestamp.shift(days=1)\n        data.append(\n            {\n                \"zoneKey\": zone_key,\n                \"production\": {\"coal\": prod},\n                \"storage\": {},\n                \"source\": \"kostt.com\",\n                \"datetime\": timestamp.datetime,\n            }\n        )\n\n    return data\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production() ->\")\n    for datum in fetch_production():\n        print(datum)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/archived/statnett.py",
    "content": "# Archived because the parser was only used for NO-NO4 to RU-1 exchange, which has since been removed from the source.\n# This exchange is no longer active.\n\nfrom datetime import datetime, timedelta\nfrom logging import Logger, getLogger\n\nimport arrow\nfrom requests import Session\n\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\n\nexchanges_mapping = {\n    \"BY->LT\": [\"BY->LT\"],\n    \"DE->DK-DK1\": [\n        \"DE->DK1\",\n    ],\n    \"DE->DK-DK2\": [\n        \"DE->DK2\",\n    ],\n    \"DE->SE\": [\"DE->SE4\"],\n    \"DE->SE-SE4\": [\"DE->SE4\"],\n    \"DK-DK1->NO\": [\"DK1->NO2\"],\n    \"DK-DK1->NO-NO2\": [\"DK1->NO2\"],\n    \"DK-DK1->SE\": [\"DK1->SE3\"],\n    \"DK-DK1->SE-SE3\": [\"DK1->SE3\"],\n    \"DK-DK2->SE\": [\"DK2->SE4\"],\n    \"DK-DK2->SE-SE4\": [\"DK2->SE4\"],\n    \"EE->RU\": [\"EE->RU\"],\n    \"EE->RU-1\": [\"EE->RU\"],\n    \"EE->LV\": [\"EE->LV\"],\n    \"EE->FI\": [\"EE->FI\"],\n    \"FI->NO\": [\"FI->NO4\"],\n    \"FI->NO-NO4\": [\"FI->NO4\"],\n    \"FI->RU\": [\"FI->RU\"],\n    \"FI->RU-1\": [\"FI->RU\"],\n    \"FI->SE\": [\"FI->SE1\", \"FI->SE3\"],\n    \"FI->SE-SE1\": [\n        \"FI->SE1\",\n    ],\n    \"FI->SE-SE3\": [\"FI->SE3\"],\n    \"LT->LV\": [\"LT->LV\"],\n    \"LT->SE\": [\"LT->SE4\"],\n    \"LT->SE-SE4\": [\"LT->SE4\"],\n    \"LT->PL\": [\"LT->PL\"],\n    \"LT->RU-KGD\": [\"LT->RU\"],\n    \"LV->RU\": [\"LV->RU\"],\n    \"LV->RU-1\": [\"LV->RU\"],\n    \"NL->NO\": [\"NL->NO2\"],\n    \"NL->NO-NO2\": [\"NL->NO2\"],\n    \"NO->SE\": [\"NO1->SE3\", \"NO3->SE2\", \"NO4->SE1\", \"NO4->SE2\"],\n    \"NO-NO1->NO-NO2\": [\"NO1->NO2\"],\n    \"NO-NO1->NO-NO3\": [\"NO1->NO3\"],\n    \"NO-NO1->NO-NO5\": [\"NO1->NO5\"],\n    \"NO-NO1->SE\": [\"NO1->SE3\"],\n    \"NO-NO2->NO-NO5\": [\"NO2->NO5\"],\n    \"NO-NO3->NO-NO4\": [\"NO3->NO4\"],\n    \"NO-NO3->NO-NO5\": [\"NO3->NO5\"],\n    \"NO-NO3->SE\": [\"NO3->SE2\"],\n    \"NO-NO3->SE-SE2\": [\"NO3->SE2\"],\n    \"NO->RU\": [\"NO4->RU\"],\n    \"NO->RU-1\": [\"NO4->RU\"],\n    \"NO-NO4->RU\": [\"NO4->RU\"],\n    \"NO-NO4->RU-1\": [\"NO4->RU\"],\n    \"NO-NO4->SE\": [\"NO4->SE1\", \"NO4->SE2\"],\n    \"PL->SE\": [\n        \"PL->SE4\",\n    ],\n    \"PL->SE-SE4\": [\"PL->SE4\"],\n    \"SE-SE1->SE-SE2\": [\"SE1->SE2\"],\n    \"SE-SE2->SE-SE3\": [\"SE1->SE2\"],\n    \"SE-SE3->SE-SE4\": [\"SE1->SE2\"],\n}\n\n# Mappings used to go from country to bidding zone level\n\n\n@refetch_frequency(timedelta(hours=1))\ndef fetch_production(\n    zone_key: str = \"SE\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    r = session or Session()\n    timestamp = (\n        target_datetime.timestamp() if target_datetime else arrow.now().timestamp\n    ) * 1000\n    url = (\n        \"http://driftsdata.statnett.no/restapi/ProductionConsumption/GetLatestDetailedOverview?timestamp=%d\"\n        % timestamp\n    )\n    response = r.get(url)\n    obj = response.json()\n\n    data = {\n        \"zoneKey\": zone_key,\n        \"production\": {\n            \"nuclear\": float(\n                list(\n                    filter(\n                        lambda x: x[\"titleTranslationId\"]\n                        == \"ProductionConsumption.{}{}Desc\".format(\"Nuclear\", zone_key),\n                        obj[\"NuclearData\"],\n                    )\n                )[0][\"value\"].replace(\"\\xa0\", \"\")\n            ),\n            \"hydro\": float(\n                list(\n                    filter(\n                        lambda x: x[\"titleTranslationId\"]\n                        == \"ProductionConsumption.{}{}Desc\".format(\"Hydro\", zone_key),\n                        obj[\"HydroData\"],\n                    )\n                )[0][\"value\"].replace(\"\\xa0\", \"\")\n            ),\n            \"wind\": float(\n                list(\n                    filter(\n                        lambda x: x[\"titleTranslationId\"]\n                        == \"ProductionConsumption.{}{}Desc\".format(\"Wind\", zone_key),\n                        obj[\"WindData\"],\n                    )\n                )[0][\"value\"].replace(\"\\xa0\", \"\")\n            ),\n            \"unknown\": float(\n                list(\n                    filter(\n                        lambda x: x[\"titleTranslationId\"]\n                        == \"ProductionConsumption.{}{}Desc\".format(\"Thermal\", zone_key),\n                        obj[\"ThermalData\"],\n                    )\n                )[0][\"value\"].replace(\"\\xa0\", \"\")\n            )\n            + float(\n                list(\n                    filter(\n                        lambda x: x[\"titleTranslationId\"]\n                        == f\"ProductionConsumption.{'NotSpecified'}{zone_key}Desc\",\n                        obj[\"NotSpecifiedData\"],\n                    )\n                )[0][\"value\"].replace(\"\\xa0\", \"\")\n            ),\n        },\n        \"storage\": {},\n        \"source\": \"driftsdata.stattnet.no\",\n    }\n    data[\"datetime\"] = arrow.get(obj[\"MeasuredAt\"] / 1000).datetime\n\n    return data\n\n\n@refetch_frequency(timedelta(hours=1))\ndef fetch_exchange_by_bidding_zone(\n    bidding_zone1: str = \"DK1\",\n    bidding_zone2: str = \"NO2\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict:\n    # Convert bidding zone names into statnett zones\n    bidding_zone_1_trimmed, bidding_zone_2_trimmed = (\n        x.split(\"-\")[-1] for x in [bidding_zone1, bidding_zone2]\n    )\n    bidding_zone_a, bidding_zone_b = sorted(\n        [bidding_zone_1_trimmed, bidding_zone_2_trimmed]\n    )\n    r = session or Session()\n    timestamp = (\n        target_datetime.timestamp() if target_datetime else arrow.now().timestamp\n    ) * 1000\n    url = (\n        \"http://driftsdata.statnett.no/restapi/PhysicalFlowMap/GetFlow?Ticks=%d\"\n        % timestamp\n    )\n    response = r.get(url)\n    obj = response.json()\n\n    exchange = list(\n        filter(\n            lambda x: {x[\"OutAreaElspotId\"], x[\"InAreaElspotId\"]}\n            == {bidding_zone_a, bidding_zone_b},\n            obj,\n        )\n    )[0]\n\n    return {\n        \"sortedZoneKeys\": \"->\".join(sorted([bidding_zone1, bidding_zone2])),\n        \"netFlow\": exchange[\"Value\"]\n        if bidding_zone_a == exchange[\"OutAreaElspotId\"]\n        else -1 * exchange[\"Value\"],\n        \"datetime\": arrow.get(obj[0][\"MeasureDate\"] / 1000).datetime,\n        \"source\": \"driftsdata.stattnet.no\",\n    }\n\n\ndef _fetch_exchanges_from_sorted_bidding_zones(\n    sorted_bidding_zones,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n):\n    zones = sorted_bidding_zones.split(\"->\")\n    return fetch_exchange_by_bidding_zone(zones[0], zones[1], session, target_datetime)\n\n\ndef _sum_of_exchanges(exchanges):\n    exchange_list = list(exchanges)\n    return {\n        \"netFlow\": sum(e[\"netFlow\"] for e in exchange_list),\n        \"datetime\": exchange_list[0][\"datetime\"],\n        \"source\": exchange_list[0][\"source\"],\n    }\n\n\n@refetch_frequency(timedelta(hours=1))\ndef fetch_exchange(\n    zone_key1: str = \"DK\",\n    zone_key2: str = \"NO\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n):\n    r = session or Session()\n\n    sorted_exchange = \"->\".join(sorted([zone_key1, zone_key2]))\n    data = _sum_of_exchanges(\n        _fetch_exchanges_from_sorted_bidding_zones(e, r, target_datetime)\n        for e in exchanges_mapping[sorted_exchange]\n    )\n    data[\"sortedZoneKeys\"] = \"->\".join(sorted([zone_key1, zone_key2]))\n\n    return data\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production(SE) ->\")\n    print(fetch_production(\"SE\"))\n    print(\"fetch_exchange(NO, SE) ->\")\n    print(fetch_exchange(\"NO\", \"SE\"))\n    print(\"fetch_exchange(NO-NO4, RU-1) ->\")\n    print(fetch_exchange(\"NO-NO4\", \"RU-1\"))\n    print(\"fetch_exchange(EE, RU-1) ->\")\n    print(fetch_exchange(\"EE\", \"RU-1\"))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/eSett.py",
    "content": "from datetime import datetime, timedelta, timezone\nfrom logging import Logger, getLogger\n\nfrom requests import Session\n\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.parsers.ENTSOE import ENTSOE_DOMAIN_MAPPINGS\nfrom electricitymap.contrib.parsers.lib.config import refetch_frequency\nfrom electricitymap.contrib.types import ZoneKey\n\nBASE_URL = \"https://api.opendata.esett.com\"\nPRODUCTION_URL = f\"{BASE_URL}/EXP16/Aggregate\"\n\nIGNORED_PRODUCTION_KEYS = {\"timestamp\", \"timestampUTC\", \"mba\", \"total\"}\n\nPRODUCTION_MAPPINGS = {\n    \"hydro\": \"hydro\",\n    \"wind\": \"wind\",\n    \"windOffshore\": \"wind\",\n    \"nuclear\": \"nuclear\",\n    \"solar\": \"solar\",\n    \"thermal\": \"unknown\",\n    \"other\": \"unknown\",\n}\n\nSTORAGE_MAPPINGS = {\"energyStorage\": \"battery\"}\n\n\n@refetch_frequency(timedelta(days=3))\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list:\n    session = session or Session()\n    target_datetime = (target_datetime or datetime.now(timezone.utc)).astimezone(\n        timezone.utc\n    )\n\n    start_time = target_datetime - timedelta(days=3)\n\n    query_params = {\n        \"start\": start_time.isoformat(timespec=\"milliseconds\").replace(\"+00:00\", \"Z\"),\n        \"end\": target_datetime.isoformat(timespec=\"milliseconds\").replace(\n            \"+00:00\", \"Z\"\n        ),\n        \"resolution\": \"hour\",\n        \"mba\": ENTSOE_DOMAIN_MAPPINGS[zone_key],\n    }\n\n    response = session.get(PRODUCTION_URL, params=query_params)\n    response.raise_for_status()\n\n    json: list = response.json()\n    production_breakdown_list = ProductionBreakdownList(logger)\n    for entry in json or []:\n        production_mix = ProductionMix()\n        storage_mix = StorageMix()\n        timestamp = datetime.fromisoformat(entry[\"timestampUTC\"].replace(\"Z\", \"+00:00\"))\n        for key, value in entry.items():\n            if key in IGNORED_PRODUCTION_KEYS:\n                continue\n            elif key in PRODUCTION_MAPPINGS:\n                production_mix.add_value(PRODUCTION_MAPPINGS[key], value)\n            elif key in STORAGE_MAPPINGS:\n                storage_mix.add_value(STORAGE_MAPPINGS[key], value)\n            else:\n                logger.warning(f\"Unknown production key: {key}\")\n\n        production_breakdown_list.append(\n            zoneKey=zone_key,\n            datetime=timestamp,\n            production=production_mix,\n            source=\"eSett\",\n        )\n    return production_breakdown_list.to_list()\n\n\nif __name__ == \"__main__\":\n    print(fetch_production(ZoneKey(\"SE-SE4\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/email_grid_alerts.py",
    "content": "\"\"\"Parser from email alerts sent to grid-alerts@alerts.electricitymaps.com through the Mailgun API.\"\"\"\n\nimport datetime\nimport json\nfrom logging import Logger, getLogger\nfrom typing import Any\n\nfrom requests import Session\nfrom requests.auth import HTTPBasicAuth\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.lib.models.event_lists import GridAlertList\nfrom electricitymap.contrib.lib.models.events import GridAlertType\nfrom electricitymap.contrib.parsers.lib.utils import get_token\n\n# CONFIGURATION\nREGION = \"eu\"  # use 'us' or 'eu'\nAPI_BASE_URL = f\"https://api.{REGION}.mailgun.net/v1/analytics/logs\"\n\n\ndef fetch_grid_alerts_emails(\n    zone_key: ZoneKey = None,\n    session: Session | None = None,\n    target_datetime: datetime.datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict[str, Any]]:\n    session = session or Session()\n    MAILGUN_API_KEY = get_token(\"MAILGUN_TOKEN\")\n\n    domain_name = \"alerts.electricitymaps.com\"\n    # REQUEST BODY: only implemented for the last 5 hours\n    nowminus5hours = (\n        datetime.datetime.now(datetime.timezone.utc).replace(microsecond=0)\n        - datetime.timedelta(hours=5)\n    ).strftime(\"%a, %d %b %Y %H:%M:%S -0000\")\n\n    now = (\n        datetime.datetime.now(datetime.timezone.utc)\n        .replace(microsecond=0)\n        .strftime(\"%a, %d %b %Y %H:%M:%S -0000\")\n    )\n\n    # Prepare the payload for the API request\n    payload = {\n        \"start\": nowminus5hours,\n        \"end\": now,\n        \"filter\": {\n            \"AND\": [\n                {\n                    \"attribute\": \"domain\",\n                    \"comparator\": \"=\",\n                    \"values\": [\n                        {\n                            \"label\": domain_name,\n                            \"value\": domain_name,\n                        }\n                    ],\n                },\n                {\n                    \"attribute\": \"event\",\n                    \"comparator\": \"=\",\n                    \"values\": [{\"label\": \"stored\", \"value\": \"stored\"}],\n                },\n            ],\n        },\n        \"events\": [\n            \"stored\",\n            \"delivered\",\n            \"accepted\",\n        ],  # Add or change based on your needs\n        \"include_subaccounts\": True,\n        \"include_totals\": True,\n        \"pagination\": {\n            \"sort\": \"timestamp:asc\",\n            \"limit\": 100,\n            # \"token\": \"your-pagination-token\"  # Optional for next pages\n        },\n    }\n\n    # MAKE REQUEST\n    response = session.post(\n        API_BASE_URL,\n        auth=HTTPBasicAuth(\"api\", MAILGUN_API_KEY),\n        headers={\"Content-Type\": \"application/json\"},\n        data=json.dumps(payload),\n    )\n\n    # Get storage keys\n    keys = []\n    if response.status_code == 200:\n        logs = response.json()\n        for log in logs.get(\"items\", []):\n            keys.append(log[\"storage\"][\"key\"])\n        if logs.get(\"pagination\", {}).get(\"next\"):\n            print(\"\\n:repeat: Next page token:\", logs[\"pagination\"][\"next\"][\"token\"])\n    else:\n        print(\"Error:\", response.status_code, response.text)\n\n    # Record events in grid_alert_list\n    grid_alert_list = GridAlertList(logger)\n\n    # Get email using storage keys # The email is stored only for a few days (less than 3 days)\n    for storage_key in keys:\n        API_BASE_URL2 = f\"https://api.{REGION}.mailgun.net/v3/domains/{domain_name}/messages/{storage_key}\"\n\n        # MAKE REQUEST\n        response = session.get(\n            API_BASE_URL2,\n            auth=HTTPBasicAuth(\"api\", MAILGUN_API_KEY),\n            headers={\"Content-Type\": \"application/json\"},\n        )\n\n        # Parse email\n        email_json = response.json()\n\n        date_str = email_json[\"Date\"].replace(\" (UTC)\", \"\")\n        dt_received = datetime.datetime.strptime(date_str, \"%a, %d %b %Y %H:%M:%S %z\")\n        sender = email_json[\"From\"].lower()\n\n        # Extract zone key from sender\n        if (\n            (\"ercot\" in sender and zone_key == ZoneKey(\"US-TEX-ERCO\"))\n            or (\"flexalert\" in sender and zone_key == ZoneKey(\"US-CAL-CISO\"))\n            or (\"spp\" in sender and zone_key == ZoneKey(\"US-CENT-SWPP\"))\n            or (\"electricitymaps\" in sender)\n        ):\n            body = \"\"\n            if ZoneKey(\"US-CENT-SWPP\") == zone_key:\n                body = email_json[\"body-plain\"].split(\n                    \"The following chart shows the relative severity of\"\n                )[0]\n            # add more cases when we know the format of the other emails\n\n            message = email_json[\"subject\"] + \"\\n\" + body\n            # Add to grid_alert_list\n            grid_alert_list.append(\n                zoneKey=zone_key,\n                locationRegion=None,\n                source=sender,\n                alertType=GridAlertType.undefined,\n                message=message,\n                issuedTime=dt_received,\n                startTime=None,  # if None, it defaults to issuedTime\n                endTime=None,\n            )\n        else:\n            logger.warning(f\"Unknown sender: {email_json['sender']}\")\n\n    return grid_alert_list.to_list()\n\n\nif __name__ == \"__main__\":\n    from pprint import pprint\n\n    pprint(fetch_grid_alerts_emails())\n"
  },
  {
    "path": "electricitymap/contrib/parsers/examples/example_parser.py",
    "content": "from datetime import datetime\nfrom logging import Logger, getLogger\nfrom typing import Any\nfrom zoneinfo import ZoneInfo\n\n# The request library is used to fetch content through HTTP\nfrom requests import Response, Session\n\nfrom electricitymap.contrib.lib.models.event_lists import (\n    ExchangeList,\n    PriceList,\n    ProductionBreakdownList,\n    TotalConsumptionList,\n    TotalProductionList,\n)\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef fetch_production(\n    zone_key: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict] | dict:\n    \"\"\"\n        Requests the last known production mix (in MW) of a given country.\n\n        Arguments:\n        ----------\n        zone_key: used in case a parser is able to fetch multiple countries\n        session: request session passed in order to re-use an existing session\n        target_datetime: the datetime for which we want production data. If not\n          provided, we should default it to now. If past data is not available,\n          raise a ParserException. Beware that the provided target_datetime is\n          UTC. To convert to local timezone, you can use\n          `target_datetime = target_datetime.astimezone(tz=ZoneInfo('America/New_York'))`.\n        logger: an instance of a `logging.Logger` that will be passed by the\n          backend. Information logged will be publicly available so that correct\n          execution of the logger can be checked. All Exceptions will automatically\n          be logged, so when something's wrong, simply raise an Exception (with an\n          explicit text). Use `logger.warning` or `logger.info` for information\n          that can useful to check if the parser is working correctly. A default\n          logger is used so that logger output can be seen when coding / debugging.\n\n        Returns:\n        --------\n        If no data can be fetched, any falsy value (None, [], False) will be\n          ignored by the backend. If there is no data because the source may have\n          changed or is not available, raise an ParserException.\n\n        A  ProductionBreakdownList should be returned containing all ProductionBreakdown\n        events. Each ProductionBreakdown event should contain a datetime, a zoneKey,\n        a ProductionMix, a source and optionally a StorageMix.\n        The ProductionMix should contain the production breakdown for each fuel type.\n\n    -     A  ProductionBreakdownList contains all ProductionBreakdown events.\n    -     Each ProductionBreakdown event contains a datetime, a zoneKey,\n       a ProductionMix, a source and optionally a StorageMix.\n    -     The ProductionMix contains the production breakdown for each fuel type.\n    -     The StorageMix contains the storage breakdown for each storage type.\n\n\n    \"\"\"\n    if target_datetime is None:\n        url = \"https://api.someservice.com/v1/productionmix/latest\"\n    elif target_datetime > datetime(year=2000, month=1, day=1):\n        # WHEN HISTORICAL DATA IS AVAILABLE\n        # convert target datetime to local datetime\n        url_date = target_datetime.astimezone(\n            ZoneInfo(\"America/Argentina/Buenos_Aires\")\n        ).strftime(\"%Y-%m-%d\")\n        url = f\"https://api.someservice.com/v1/productionmix/{url_date}\"\n    else:\n        # WHEN HISTORICAL DATA IS NOT AVAILABLE\n        raise ParserException(\n            \"example_parser.py\",\n            \"This parser is not yet able to parse dates before 2000-01-01\",\n            zone_key,\n        )\n\n    res: Response = session.get(url)\n    if not res.status_code == 200:\n        raise ParserException(\n            \"example_parser.py\",\n            f\"Exception when fetching production error code: {res.status_code}: {res.text}\",\n            zone_key,\n        )\n\n    obj = res.json()\n\n    production_list = ProductionBreakdownList(logger=logger)\n\n    for item in obj[\"productionMix\"]:\n        # You can create the production mix directly\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(item[\"datetime\"]),\n            production=ProductionMix(\n                biomass=item[\"biomass\"],\n                coal=item[\"coal\"],\n                gas=item[\"gas\"],\n                hydro=item[\"hydro\"],\n                nuclear=item[\"nuclear\"],\n                oil=item[\"oil\"],\n                solar=item[\"solar\"],\n                wind=item[\"wind\"],\n                geothermal=item[\"geothermal\"],\n                unknown=item[\"unknown\"]\n                if item[\"unknown\"] > 0\n                else 0 + item[\"other\"]\n                if item[\"other\"] > 0\n                else 0,\n            ),\n            storage=StorageMix(hydro=item[\"hydroStorage\"] * -1),\n            source=\"someservice.com\",\n        )\n        # Or you can create the production mix and fill it later.\n        production_mix = ProductionMix()\n        for mode, value in item.items():\n            production_mix.add_value(mode, value)\n        production_list.append(\n            zoneKey=zone_key,\n            datetime=datetime.fromisoformat(item[\"datetime\"]),\n            production=production_mix,\n            storage=StorageMix(hydro=item[\"hydroStorage\"] * -1),\n            source=\"someservice.com\",\n        )\n    # For now we should return a list of dictionaries\n    # and therefore we convert the ProductionBreakdownList to a list\n    # using the to_list() method.\n    # In the future we will return a ProductionBreakdownList directly.\n    return production_list.to_list()\n\n\ndef fetch_price(\n    zone_key: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict] | dict:\n    \"\"\"\n    Requests the last known power price of a given country.\n\n    Arguments:\n    ----------\n    zone_key: used in case a parser is able to fetch multiple countries\n    session: request session passed in order to re-use an existing session\n    target_datetime: the datetime for which we want production data. If not\n      provided, we should default it to now. If past data is not available,\n      raise a ParserException. Beware that the provided target_datetime is\n      UTC. To convert to local timezone, you can use\n      `target_datetime = target_datetime.astimezone(tz=ZoneInfo('America/New_York'))`.\n    logger: an instance of a `logging.Logger` that will be passed by the\n      backend. Information logged will be publicly available so that correct\n      execution of the logger can be checked. All Exceptions will automatically\n      be logged, so when something's wrong, simply raise an Exception (with an\n      explicit text). Use `logger.warning` or `logger.info` for information\n      that can useful to check if the parser is working correctly. A default\n      logger is used so that logger output can be seen when coding / debugging.\n\n    Returns:\n    --------\n    If no data can be fetched, any falsy value (None, [], False) will be\n      ignored by the backend. If there is no data because the source may have\n      changed or is not available, raise an Exception.\n    Returns a PriceList containing all price events.\n    \"\"\"\n    if target_datetime:\n        raise ParserException(\n            \"example_parser.py\",\n            \"This parser is not yet able to parse past dates\",\n            zone_key,\n        )\n\n    url = \"https://api.someservice.com/v1/price/latest\"\n\n    response = session.get(url)\n    if not response.ok:\n        raise ParserException(\n            \"example_parser.py\",\n            f\"Exception when fetching price error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n\n    obj = response.json()\n\n    price_list = PriceList(logger=logger)\n\n    for item in obj:\n        price_list.append(\n            zoneKey=zone_key,\n            currency=\"EUR\",\n            datetime=datetime.fromisoformat(item[\"datetime\"]),\n            price=item[\"price\"],\n            source=\"someservice.com\",\n        )\n    # For now we should return a list of dictionaries\n    # and therefore we convert the PriceList to a list\n    # using the to_list() method.\n    # In the future we will return a PriceList directly.\n    return price_list.to_list()\n\n\ndef fetch_exchange(\n    zone_key1: ZoneKey = ZoneKey(\"XX\"),\n    zone_key2: ZoneKey = ZoneKey(\"YY\"),\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict] | dict:\n    \"\"\"\n    Requests the last known power exchange (in MW) between two countries.\n\n    Arguments:\n    ----------\n    zone_key1: used is used to identify the first zone of a exchange pair.\n    zone_key2: used is used to identify the second zone of a exchange pair.\n    session: request session passed in order to re-use an existing session\n    target_datetime: the datetime for which we want production data. If not\n      provided, we should default it to now. If past data is not available,\n      raise a ParserException. Beware that the provided target_datetime is\n      UTC. To convert to local timezone, you can use\n      `target_datetime = target_datetime.astimezone(tz=ZoneInfo('America/New_York'))`.\n    logger: an instance of a `logging.Logger` that will be passed by the\n      backend. Information logged will be publicly available so that correct\n      execution of the logger can be checked. All Exceptions will automatically\n      be logged, so when something's wrong, simply raise an Exception (with an\n      explicit text). Use `logger.warning` or `logger.info` for information\n      that can useful to check if the parser is working correctly. A default\n      logger is used so that logger output can be seen when coding / debugging.\n\n    Returns:\n    --------\n    If no data can be fetched, any falsy value (None, [], False) will be\n      ignored by the backend. If there is no data because the source may have\n      changed or is not available, raise an Exception.\n\n    Returns an ExchangeList containing all exchange events.\n    \"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    url = \"https://api.someservice.com/v1/exchange/latest\"\n    params = {\n        \"from\": zone_key1,\n        \"to\": zone_key2,\n    }\n\n    response = session.get(url, params=params)\n    if not response.ok:\n        raise ParserException(\n            \"example_parser.py\",\n            f\"Exception when fetching exchange error code: {response.status_code}: {response.text}\",\n            ZoneKey(\"->\".join(sorted([zone_key1, zone_key2]))),\n        )\n    obj = response.json()\n\n    exchange_list = ExchangeList(logger=logger)\n\n    for item in obj:\n        exchange_list.append(\n            # Zone keys are sorted in order to enable easier indexing in the database\n            zoneKey=ZoneKey(\"->\".join(sorted([zone_key1, zone_key2]))),\n            # Parse the datetime and return a python datetime object\n            datetime=datetime.fromisoformat(item[\"datetime\"]),\n            # Here we assume that the net flow returned by the api is the flow from\n            # country1 to country2. A positive flow indicates an export from country1\n            # to country2. A negative flow indicates an import.\n            netFlow=item[\"exchange\"],\n            source=\"someservice.com\",\n        )\n\n    return exchange_list.to_list()\n\n\ndef fetch_consumption(\n    zone_key: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict[str, Any] | list[dict[str, Any]]:\n    \"\"\"\n    Requests the last known power consumption (in MW) of a given zone.\n\n    Arguments:\n    ----------\n    zone_key: used is used to identify the zone to which the consumption data\n      is related to.\n    session: request session passed in order to re-use an existing session\n    target_datetime: the datetime for which we want production data. If not\n      provided, we should default it to now. If past data is not available,\n      raise a ParserException. Beware that the provided target_datetime is\n      UTC. To convert to local timezone, you can use\n      `target_datetime = target_datetime.astimezone(tz=ZoneInfo('America/New_York'))`.\n    logger: an instance of a `logging.Logger` that will be passed by the\n      backend. Information logged will be publicly available so that correct\n      execution of the logger can be checked. All Exceptions will automatically\n      be logged, so when something's wrong, simply raise an Exception (with an\n      explicit text). Use `logger.warning` or `logger.info` for information\n      that can useful to check if the parser is working correctly. A default\n      logger is used so that logger output can be seen when coding / debugging.\n\n    Returns:\n    --------\n    If no data can be fetched, any falsy value (None, [], False) will be\n      ignored by the backend. If there is no data because the source may have\n      changed or is not available, raise a ParserException.\n\n    Returns a ConsumptionList containing all consumption events.\n    \"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    url = \"https://api.someservice.com/v1/consumption/latest\"\n    params = {\n        \"zone\": zone_key,\n    }\n\n    response = session.get(url, params=params)\n    if not response.ok:\n        raise ParserException(\n            \"example_parser.py\",\n            f\"Exception when fetching consumption error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n    obj = response.json()\n\n    consumption_list = TotalConsumptionList(logger=logger)\n\n    for item in obj:\n        consumption_list.append(\n            zoneKey=zone_key,\n            # Parse the datetime and return a python datetime object\n            datetime=datetime.fromisoformat(item[\"datetime\"]),\n            consumption=item[\"consumption\"],\n            source=\"someservice.com\",\n        )\n    return consumption_list.to_list()\n\n\ndef fetch_total_production(\n    zone_key: ZoneKey,\n    session: Session = Session(),\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> dict | list[dict]:\n    \"\"\"\n    Requests the last known power production (in MW) of a given zone.\n\n    Arguments:\n    ----------\n    zone_key: used is used to identify the zone to which the production data\n      is related to.\n    session: request session passed in order to re-use an existing session\n    target_datetime: the datetime for which we want production data. If not\n        provided, we should default it to now. If past data is not available,\n        raise a ParserException. Beware that the provided target_datetime is\n        UTC. To convert to local timezone, you can use\n        `target_datetime = target_datetime.astimezone(tz=ZoneInfo('America/New_York'))`.\n    logger: an instance of a `logging.Logger` that will be passed by the\n      backend. Information logged will be publicly available so that correct\n      execution of the logger can be checked. All Exceptions will automatically\n      be logged, so when something's wrong, simply raise an Exception (with an\n      explicit text). Use `logger.warning` or `logger.info` for information\n      that can useful to check if the parser is working correctly. A default\n      logger is used so that logger output can be seen when coding / debugging.\n    \"\"\"\n    if target_datetime:\n        raise NotImplementedError(\"This parser is not yet able to parse past dates\")\n\n    url = \"https://api.someservice.com/v1/production/latest\"\n    params = {\n        \"zone\": zone_key,\n    }\n\n    response = session.get(url, params=params)\n    if not response.ok:\n        raise ParserException(\n            \"example_parser.py\",\n            f\"Exception when fetching total production error code: {response.status_code}: {response.text}\",\n            zone_key,\n        )\n    obj = response.json()\n\n    production_list = TotalProductionList(logger=logger)\n\n    for item in obj:\n        production_list.append(\n            zoneKey=zone_key,\n            # Parse the datetime and return a python datetime object\n            datetime=datetime.fromisoformat(item[\"datetime\"]),\n            value=item[\"production\"],\n            source=\"someservice.com\",\n        )\n    return production_list.to_list()\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Maps backend, but handy for testing.\"\"\"\n\n    print(\"fetch_production(XX) ->\")\n    print(fetch_production(ZoneKey(\"XX\")))\n    print(\"fetch_price(XX) ->\")\n    print(fetch_price(ZoneKey(\"XX\")))\n    print(\"fetch_exchange(XX, YY) ->\")\n    print(fetch_exchange(ZoneKey(\"XX\"), ZoneKey(\"YY\")))\n    print(\"fetch_consumption(XX) ->\")\n    print(fetch_consumption(ZoneKey(\"XX\")))\n    print(\"fetch_total_production(XX) ->\")\n    print(fetch_total_production(ZoneKey(\"XX\")))\n"
  },
  {
    "path": "electricitymap/contrib/parsers/examples/production.md",
    "content": "# Production Parser\n\n## Arguments\n\n`zone_key`\n\n> Type: `str` - Native Python string object. <br/>\n> Description: <br/>\n> Passed to the parser as a unique identifier for each zone.\n\n---\n\n`session`\n\n> Type: `request.Session` - A Request Session object. <br/>\n> Description: <br/>\n> Passed to the parser in order to reuse an existing connection. Should default to `request.Session()`.\n\n---\n\n`target_datetime`\n\n> Type: Datetime | None - Native python datetime or None. <br/>\n> Description: <br/>\n> Passed to the parser if the backend request to fetch data from a specific datetime. Should default to `None`.\n\n---\n\n`logger`\n\n> Type: logging.Logger - Native python logging object. <br/>\n> Description: <br/>\n> Passed to the parser by the backend to enable public logging. Should default to `logging.getLogger(__name__)`.\n\n## Return value signature\n\nThe parser should return a list of ProductionBreakdown objects.\n\n```python\nfrom logging import get_logger\nfrom datetime import datetime, timezone\nfrom electricitymap.contrib.lib.models.events import ProductionMix, StorageMix\nfrom electricitymap.contrib.lib.models.event_lists import ProductionBreakdownList\n\n\nlogger = getLogger(__name__)\nproduction_list = ProductionBreakdownList(logger=logger)\nproduction_list.append(\n            zoneKey=\"AT\",\n            datetime= datetime(2023, 1, 1, tzinfo=timezone.utc),\n            production=ProductionMix(\n                biomass=10,\n                coal=4,\n                gas=3,\n                hydro=1,\n                nuclear=None,\n                oil=None,\n                solar=10,\n                wind=10,\n                geothermal=10,\n                unknown=10\n            ),\n            storage=StorageMix(hydro=-10),\n            source=\"someservice.com\",\n        )\nproduction_list.to_list()\n```\n\nNote: If data from a production mode is missing it should be omitted or returned as `None` like the above example, _NOT_ `0`.\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/IN.py",
    "content": "from datetime import datetime\nfrom zoneinfo import ZoneInfo\n\nZONE_INFO = ZoneInfo(\"Asia/Kolkata\")\n\n\ndef read_datetime_from_span_id(html, span_id, time_format):\n    date_time_span = html.find(\"span\", {\"id\": span_id})\n    return datetime.strptime(date_time_span.text, time_format).replace(tzinfo=ZONE_INFO)\n\n\ndef read_text_from_span_id(html, span_id):\n    return html.find(\"span\", {\"id\": span_id}).text\n\n\ndef read_value_from_span_id(html, span_id):\n    html_span = read_text_from_span_id(html, span_id)\n    return float(html_span)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/parsers/lib/config.py",
    "content": "import functools\nimport os\nfrom collections.abc import ItemsView, KeysView, ValuesView\nfrom copy import deepcopy\nfrom datetime import timedelta\nfrom enum import Enum\nfrom inspect import signature\nfrom logging import getLogger\nfrom typing import TypeVar\n\nimport requests\nfrom requests import Session\nfrom requests.adapters import HTTPAdapter, Retry\n\nModeEnumType = TypeVar(\"ModeEnumType\", bound=\"BaseModeEnum\")\n\n\n# TODO: Switch this to StringEnum when we migrate to Python 3.11\nclass BaseModeEnum(str, Enum):\n    \"\"\"Base class for Mode enums.\"\"\"\n\n    def __str__(self) -> str:\n        return self.value\n\n    @classmethod\n    def values(cls: type[ModeEnumType]) -> ValuesView[ModeEnumType]:\n        \"\"\"Return a Values View of all enum members.\"\"\"\n        return cls.__members__.values()\n\n    @classmethod\n    def names(cls) -> KeysView[str]:\n        \"\"\"Return a Keys View of all enum names.\"\"\"\n        return cls.__members__.keys()\n\n    @classmethod\n    def items(cls: type[ModeEnumType]) -> ItemsView[str, ModeEnumType]:\n        \"\"\"Return an Items View of (name, member) tuples.\"\"\"\n        return cls.__members__.items()\n\n\nclass ProductionModes(BaseModeEnum):\n    \"\"\"Energy production modes/sources used throughout the parsers.\"\"\"\n\n    # TODO: When we migrate to StringEnum, we should use the `auto()` method\n    BIOMASS = \"biomass\"\n    COAL = \"coal\"\n    GAS = \"gas\"\n    GEOTHERMAL = \"geothermal\"\n    HYDRO = \"hydro\"\n    NUCLEAR = \"nuclear\"\n    OIL = \"oil\"\n    SOLAR = \"solar\"\n    WIND = \"wind\"\n    UNKNOWN = \"unknown\"\n\n\nclass StorageModes(BaseModeEnum):\n    \"\"\"Energy storage modes/sources used throughout the parsers.\"\"\"\n\n    # TODO: When we migrate to StringEnum, we should use the `auto()` method\n    BATTERY = \"battery\"\n    HYDRO = \"hydro\"\n\n\ndef refetch_frequency(frequency: timedelta):\n    \"\"\"Specifies the refetch frequency of a parser.\n    The refetch frequency is used to determine the how much data is returned by the parser.\n\n    i.e. if we refetch from d1 to d2 and the frequency is timedelta(days=1), then we will only\n    call the function once every day between d1 and d2.\n    \"\"\"\n    assert isinstance(frequency, timedelta)\n\n    def wrap(f):\n        @functools.wraps(f)\n        def wrapped_f(*args, **kwargs):\n            result = f(*args, **kwargs)\n            return result\n\n        wrapped_f.REFETCH_FREQUENCY = frequency\n        return wrapped_f\n\n    return wrap\n\n\ndef retry_policy(retry_policy: Retry):\n    assert isinstance(retry_policy, Retry)\n\n    def wrap(f):\n        def wrapped_f(*args, **kwargs):\n            session = args[1] if len(args) > 2 else kwargs.get(\"session\")\n            logger = kwargs.get(\"logger\", getLogger(__name__))\n            session = Session() if session is None else session\n            old_adapters = None\n            if \"https://\" in session.adapters or \"http://\" in session.adapters:\n                logger.warning(\"Session already has adapters, they will be overriden.\")\n                old_adapters = deepcopy(session.adapters)\n            session.mount(\"https://\", HTTPAdapter(max_retries=retry_policy))\n            session.mount(\"http://\", HTTPAdapter(max_retries=retry_policy))\n            result = f(*args, **kwargs)\n            del session.adapters[\"https://\"]\n            del session.adapters[\"http://\"]\n            if old_adapters is not None:\n                session.adapters.update(old_adapters)\n            return result\n\n        return wrapped_f\n\n    return wrap\n\n\ndef use_proxy(country_code: str, monkeypatch_for_pydataxm: bool = False):\n    \"\"\"\n    Decorator to route requests through webshare.io proxies for a specific country.\n\n    This decorator should be used as a last resort when the data provider is non-responsive\n    and other proxy methods (like cloud run datacenter proxies) do not work. Note that this\n    proxy service is not free and is charged per GB.\n\n    If you create an account with webshare.io to develop parsers for this\n    project, you should subscribe to the \"residential\" proxy type (not \"static\n    residential\"), as this choice includes most countries. As a practical\n    example, South Korea proxies are only available using this subscription.\n\n    Args:\n        country_code (str):\n            The ISO 3166-1 alpha-2 code of the country for which the proxy\n            should be used.\n        monkeypatch_for_pydataxm (bool):\n            The CO parser specifically makes use both requests.post and\n            aiohttp.ClientSession via a API specific third party library called\n            pydataxm that isn't configurable to use a proxy. By setting this to\n            True, we temporarily monkeypatch whats needed to get setup the\n            proxy.\n\n            See\n\n    Usage:\n    ```\n        @use_proxy(country_code='MY')\n        def fetch_production(zone_key, session, target_datetime, logger):\n            ...\n    ```\n    \"\"\"\n\n    def wrap(f):\n        sig = signature(f)\n        if \"zone_key\" in sig.parameters:\n            exchange_signature = False\n        elif \"zone_key1\" in sig.parameters and \"zone_key2\" in sig.parameters:\n            exchange_signature = True\n        else:\n            raise ValueError(\n                \"Invalid function signature. Maybe you added the @decorators in \"\n                \"the wrong order? The use_proxy decorator should be the bottom decorator.\"\n            )\n\n        def wrapped_f(*args, **kwargs):\n            WEBSHARE_USERNAME = os.environ.get(\"WEBSHARE_USERNAME\")\n            WEBSHARE_PASSWORD = os.environ.get(\"WEBSHARE_PASSWORD\")\n            logger = kwargs.get(\"logger\", getLogger(__name__))\n            if not WEBSHARE_USERNAME or not WEBSHARE_PASSWORD:\n                logger.warning(\n                    \"Proxy environment variables are not set. \"\n                    \"Attempting without proxy...\\n\"\n                    \"Add WEBSHARE_USERNAME and WEBSHARE_PASSWORD to use the proxy.\"\n                )\n                return f(*args, **kwargs)\n\n            logger.debug(f\"Using proxy in {country_code}\")\n            # get an existing Session object from args or kwargs, or create a\n            # new one, so it can be temporarily re-configured\n            if exchange_signature and len(args) >= 3:\n                session = args[2]\n            elif not exchange_signature and len(args) >= 2:\n                session = args[1]\n            else:\n                session = kwargs.setdefault(\"session\", Session())\n\n            requests_proxy_dict = {\n                \"http\": f\"http://{WEBSHARE_USERNAME}-{country_code}-rotate:{WEBSHARE_PASSWORD}@p.webshare.io:80/\",\n                \"https\": f\"http://{WEBSHARE_USERNAME}-{country_code}-rotate:{WEBSHARE_PASSWORD}@p.webshare.io:80/\",\n            }\n\n            if monkeypatch_for_pydataxm:\n                from aiohttp import BasicAuth, ClientSession\n\n                aiohttp_old_post = ClientSession.post\n                requests_old_post = requests.post\n\n                ClientSession.post = functools.partialmethod(\n                    ClientSession.post,\n                    proxy=\"http://p.webshare.io\",\n                    proxy_auth=BasicAuth(\n                        f\"{WEBSHARE_USERNAME}-{country_code}-rotate\",\n                        WEBSHARE_PASSWORD,\n                    ),\n                )\n                requests.post = functools.partial(\n                    requests.post,\n                    proxies=requests_proxy_dict,\n                )\n\n            old_proxies = session.proxies\n            session.proxies = requests_proxy_dict\n            try:\n                return f(*args, **kwargs)\n            finally:\n                session.proxies = old_proxies\n                if monkeypatch_for_pydataxm:\n                    ClientSession.post = aiohttp_old_post\n                    requests.post = requests_old_post\n\n        return wrapped_f\n\n    return wrap\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/exceptions.py",
    "content": "class ParserException(Exception):\n    \"\"\"Parser Exception\n\n    Args:\n        parser (str): Parser name.\n        message (str): String describing the exception.\n        zone_key (str | None): Country code or sortedZoneKeys.\n\n    Attributes:\n        parser (str): Parser name.\n        message (str): String describing the exception.\n        zone_key (str | None): Country code or sortedZoneKeys.\"\"\"\n\n    def __init__(self, parser: str, message: str, zone_key: str | None = None):\n        super().__init__(message)\n        self.parser = parser\n        self.zone_key = zone_key\n\n    def __str__(self):\n        zone_key_info = f\" ({self.zone_key})\" if self.zone_key else \"\"\n        return f\"{self.parser} Parser{zone_key_info}: {self.args[0]}\"\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/parsers.py",
    "content": "import importlib\n\nfrom electricitymap.contrib.config import EXCHANGES_CONFIG, ZONES_CONFIG\nfrom electricitymap.contrib.types import ParserDataType\n\n# Prepare all parsers\nCONSUMPTION_PARSERS = {}\nPRODUCTION_PARSERS = {}\nPRODUCTION_PER_MODE_FORECAST_PARSERS = {}\nPRODUCTION_PER_MODE_FORECAST_DAY_AHEAD_PARSERS = {}\nPRODUCTION_PER_MODE_FORECAST_INTRADAY_PARSERS = {}\nPRODUCTION_PER_MODE_FORECAST_LATEST_PARSERS = {}\nEXCHANGE_PARSERS = {}\nEXCHANGE_CAPACITY_FORECAST_DAY_AHEAD_PARSERS = {}\nEXCHANGE_CAPACITY_FORECAST_WEEK_AHEAD_PARSERS = {}\nEXCHANGE_CAPACITY_FORECAST_MONTH_AHEAD_PARSERS = {}\nSHADOW_AUCTION_ATC_DAY_AHEAD_PARSERS = {}\nCORE_EXTERNAL_ATC_DAY_AHEAD_PARSERS = {}\nMAX_BEX_DAY_AHEAD_PARSERS = {}\nSCHEDULED_EXCHANGES_DAY_AHEAD_PARSERS = {}\nMAX_BFLOW_DAY_AHEAD_PARSERS = {}\nPRICE_PARSERS = {}\nPRICE_INTRADAY_PARSERS = {}\nCONSUMPTION_FORECAST_PARSERS = {}\nGENERATION_FORECAST_PARSERS = {}\nEXCHANGE_FORECAST_PARSERS = {}\nPRODUCTION_CAPACITY_PARSERS = {}\nDAYAHEAD_LOCATIONAL_MARGINAL_PRICE_PARSERS = {}\nREALTIME_LOCATIONAL_MARGINAL_PRICE_PARSERS = {}\nGRID_ALERTS_PARSERS = {}\n# TODO remove\nPRODUCTION_PER_UNIT_PARSERS = {}\n\nPARSER_DATA_TYPE_TO_DICT = {\n    ParserDataType.CONSUMPTION: CONSUMPTION_PARSERS,\n    ParserDataType.CONSUMPTION_FORECAST: CONSUMPTION_FORECAST_PARSERS,\n    ParserDataType.DAYAHEAD_LOCATIONAL_MARGINAL_PRICE: DAYAHEAD_LOCATIONAL_MARGINAL_PRICE_PARSERS,\n    ParserDataType.EXCHANGE: EXCHANGE_PARSERS,\n    ParserDataType.EXCHANGE_CAPACITY_FORECAST_DAY_AHEAD: EXCHANGE_CAPACITY_FORECAST_DAY_AHEAD_PARSERS,\n    ParserDataType.EXCHANGE_CAPACITY_FORECAST_WEEK_AHEAD: EXCHANGE_CAPACITY_FORECAST_WEEK_AHEAD_PARSERS,\n    ParserDataType.EXCHANGE_CAPACITY_FORECAST_MONTH_AHEAD: EXCHANGE_CAPACITY_FORECAST_MONTH_AHEAD_PARSERS,\n    ParserDataType.SHADOW_AUCTION_ATC_DAY_AHEAD: SHADOW_AUCTION_ATC_DAY_AHEAD_PARSERS,\n    ParserDataType.CORE_EXTERNAL_ATC_DAY_AHEAD: CORE_EXTERNAL_ATC_DAY_AHEAD_PARSERS,\n    ParserDataType.MAX_BEX_DAY_AHEAD: MAX_BEX_DAY_AHEAD_PARSERS,\n    ParserDataType.SCHEDULED_EXCHANGES_DAY_AHEAD: SCHEDULED_EXCHANGES_DAY_AHEAD_PARSERS,\n    ParserDataType.MAX_BFLOW_DAY_AHEAD: MAX_BFLOW_DAY_AHEAD_PARSERS,\n    ParserDataType.EXCHANGE_FORECAST: EXCHANGE_FORECAST_PARSERS,\n    ParserDataType.GENERATION_FORECAST: GENERATION_FORECAST_PARSERS,\n    ParserDataType.PRICE: PRICE_PARSERS,\n    ParserDataType.PRICE_INTRADAY: PRICE_INTRADAY_PARSERS,\n    ParserDataType.PRODUCTION: PRODUCTION_PARSERS,\n    ParserDataType.PRODUCTION_PER_MODE_FORECAST: PRODUCTION_PER_MODE_FORECAST_PARSERS,\n    ParserDataType.PRODUCTION_PER_MODE_FORECAST_DAY_AHEAD: PRODUCTION_PER_MODE_FORECAST_DAY_AHEAD_PARSERS,\n    ParserDataType.PRODUCTION_PER_MODE_FORECAST_INTRADAY: PRODUCTION_PER_MODE_FORECAST_INTRADAY_PARSERS,\n    ParserDataType.PRODUCTION_PER_MODE_FORECAST_LATEST: PRODUCTION_PER_MODE_FORECAST_LATEST_PARSERS,\n    ParserDataType.REALTIME_LOCATIONAL_MARGINAL_PRICE: REALTIME_LOCATIONAL_MARGINAL_PRICE_PARSERS,\n    ParserDataType.PRODUCTION_CAPACITY: PRODUCTION_CAPACITY_PARSERS,\n    ParserDataType.GRID_ALERTS: GRID_ALERTS_PARSERS,\n}\n\n\ndef _parser_key_to_parser_folder(parser_key: ParserDataType):\n    CAPACITY_PARSERS_FOLDER = \"electricitymap.contrib.capacity_parsers\"\n    DEFAULT_PARSERS_FOLDER = \"electricitymap.contrib.parsers\"\n    return (\n        CAPACITY_PARSERS_FOLDER\n        if parser_key == ParserDataType.PRODUCTION_CAPACITY\n        else DEFAULT_PARSERS_FOLDER\n    )\n\n\n# Read all zones\nfor zone_id, zone_config in ZONES_CONFIG.items():\n    for parser_key, v in zone_config.get(\"parsers\", {}).items():\n        mod_name, fun_name = v.split(\".\")\n        try:\n            _parser_key = ParserDataType(parser_key)\n        except ValueError:\n            raise ValueError(\n                f\"Invalid parser key: {parser_key} for zone: {zone_id}\"\n            ) from None\n        mod = importlib.import_module(\n            f\"{_parser_key_to_parser_folder(_parser_key)}.{mod_name}\"\n        )\n        PARSER_DATA_TYPE_TO_DICT[_parser_key][zone_id] = getattr(mod, fun_name)\n\n\n# Read all exchanges\nfor exchange_id, exchange_config in EXCHANGES_CONFIG.items():\n    for parser_key, v in exchange_config.get(\"parsers\", {}).items():\n        try:\n            _parser_key = ParserDataType(parser_key)\n        except ValueError:\n            raise ValueError(\n                f\"Invalid parser key: {parser_key} for exchange: {exchange_id}\"\n            ) from None\n        mod_name, fun_name = v.split(\".\")\n        mod = importlib.import_module(\n            f\"{_parser_key_to_parser_folder(_parser_key)}.{mod_name}\"\n        )\n        PARSER_DATA_TYPE_TO_DICT[_parser_key][exchange_id] = getattr(mod, fun_name)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/quality.py",
    "content": "\"\"\"\nThis library contains validation functions applied to all parsers by the feeder.\nThis is a higher level validation than validation.py\n\"\"\"\n\nfrom datetime import datetime, timezone\nfrom typing import Any\n\nfrom electricitymap.contrib.config import EXCHANGES_CONFIG\nfrom electricitymap.contrib.types import ZoneKey\n\n\nclass ValidationError(ValueError):\n    pass\n\n\ndef validate_datapoint_format(datapoint: dict[str, Any], kind: str, zone_key: ZoneKey):\n    \"\"\"\n    Checks that a datapoint has the required keys. A parser can only be merged if the datapoints for each function have the correct format.\n    \"\"\"\n    standard_keys = [\"datetime\", \"source\"]\n    keys_dict = {\n        \"consumption\": [\"zoneKey\", \"consumption\"] + standard_keys,\n        \"exchange\": [\"sortedZoneKeys\", \"netFlow\"] + standard_keys,\n        \"price\": [\"zoneKey\", \"currency\", \"price\"] + standard_keys,\n        \"consumptionForecast\": [\"zoneKey\", \"value\"] + standard_keys,\n        \"productionPerModeForecast\": [\"zoneKey\", \"production\"] + standard_keys,\n        \"generationForecast\": [\"zoneKey\", \"value\"] + standard_keys,\n        \"exchangeForecast\": [\"zoneKey\", \"netFlow\"] + standard_keys,\n    }\n    for key in keys_dict[kind]:\n        if key not in datapoint:\n            raise ValidationError(\n                f\"{zone_key} - data point does not have the required keys:  {[key for key in keys_dict[kind] if key not in datapoint]} is missing\"\n            )\n\n\ndef validate_reasonable_time(item, k):\n    data_dt = item[\"datetime\"].astimezone(timezone.utc)\n    now = datetime.now(timezone.utc)\n\n    if data_dt.year < 2000:\n        raise ValidationError(\n            f\"Data from {k} can't be before year 2000, it was from: {data_dt}\"\n        )\n    if data_dt > now:\n        raise ValidationError(\n            f\"Data from {k} can't be in the future, it was from {data_dt}, now is {now}\"\n        )\n\n\ndef validate_consumption(obj: dict, zone_key: ZoneKey) -> None:\n    validate_datapoint_format(datapoint=obj, kind=\"consumption\", zone_key=zone_key)\n    if (obj.get(\"consumption\") or 0) < 0:\n        raise ValidationError(\n            f\"{zone_key}: consumption has negative value {obj['consumption']}\"\n        )\n    # Plausibility Check, no more than 500GW\n    if abs(obj.get(\"consumption\") or 0) > 500000:\n        raise ValidationError(\n            f\"{zone_key}: consumption is not realistic (>500GW) {obj['consumption']}\"\n        )\n    validate_reasonable_time(obj, zone_key)\n\n\ndef validate_exchange(item, k) -> None:\n    validate_datapoint_format(datapoint=item, kind=\"exchange\", zone_key=k)\n    if item.get(\"sortedZoneKeys\", None) != k:\n        raise ValidationError(\n            f\"Sorted country codes {item.get('sortedZoneKeys', None)} and {k} don't match\"\n        )\n    if \"datetime\" not in item:\n        raise ValidationError(f\"datetime was not returned for {k}\")\n    if not isinstance(item[\"datetime\"], datetime):\n        raise ValidationError(f\"datetime {item['datetime']} is not valid for {k}\")\n    validate_reasonable_time(item, k)\n    if \"netFlow\" not in item:\n        raise ValidationError(f\"netFlow was not returned for {k}\")\n    # Verify that the exchange flow is not greater than the interconnector\n    # capacity and has physical sense (no exchange should exceed 100GW)\n    # Use https://github.com/electricitymaps/electricitymaps-contrib/blob/master/parsers/examples/example_parser.py for expected format\n    if item.get(\"sortedZoneKeys\", None) and item.get(\"netFlow\", None):\n        zone_names: list[str] = item[\"sortedZoneKeys\"]\n        if abs(item.get(\"netFlow\", 0)) > 100000:\n            raise ValidationError(\n                f\"netFlow {item['netFlow']} exceeds physical plausibility (>100GW) for {k}\"\n            )\n        if (\n            len(zone_names) == 2\n            and (zone_names in EXCHANGES_CONFIG)\n            and (\"capacity\" in EXCHANGES_CONFIG[zone_names])\n        ):\n            interconnector_capacities = EXCHANGES_CONFIG[zone_names][\"capacity\"]\n            margin = 0.1\n            if not (\n                min(interconnector_capacities) * (1 - margin)\n                <= item[\"netFlow\"]\n                <= max(interconnector_capacities) * (1 + margin)\n            ):\n                raise ValidationError(\n                    f\"netFlow {item['netFlow']} exceeds interconnector capacity for {k}\"\n                )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/session.py",
    "content": "import ssl\n\nimport urllib3\nfrom requests import Session, adapters\n\n\nclass LegacyHttpAdapter(adapters.HTTPAdapter):\n    def init_poolmanager(self, connections, maxsize, block=False):\n        ctx = ssl.create_default_context(ssl.Purpose.SERVER_AUTH)\n        ctx.options |= 0x4  # OP_LEGACY_SERVER_CONNECT\n        self.poolmanager = urllib3.poolmanager.PoolManager(\n            num_pools=connections, maxsize=maxsize, block=block, ssl_context=ctx\n        )\n\n\n# Use a LegacyHttpAdapter to avoid \"unsafe legacy renegotiation disabled\" error\n# Original code source: https://stackoverflow.com/questions/71603314/ssl-error-unsafe-legacy-renegotiation-disabled\ndef get_session_with_legacy_adapter():\n    session = Session()\n    session.mount(\"https://\", LegacyHttpAdapter())\n    session.mount(\"http://\", LegacyHttpAdapter())\n    return session\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/tests/__snapshots__/test_config.ambr",
    "content": "# serializer version: 1\n# name: test_ProductionModes_enum_items\n  dict_items([('BIOMASS', <ProductionModes.BIOMASS: 'biomass'>), ('COAL', <ProductionModes.COAL: 'coal'>), ('GAS', <ProductionModes.GAS: 'gas'>), ('GEOTHERMAL', <ProductionModes.GEOTHERMAL: 'geothermal'>), ('HYDRO', <ProductionModes.HYDRO: 'hydro'>), ('NUCLEAR', <ProductionModes.NUCLEAR: 'nuclear'>), ('OIL', <ProductionModes.OIL: 'oil'>), ('SOLAR', <ProductionModes.SOLAR: 'solar'>), ('WIND', <ProductionModes.WIND: 'wind'>), ('UNKNOWN', <ProductionModes.UNKNOWN: 'unknown'>)])\n# ---\n# name: test_ProductionModes_enum_names\n  dict_keys(['BIOMASS', 'COAL', 'GAS', 'GEOTHERMAL', 'HYDRO', 'NUCLEAR', 'OIL', 'SOLAR', 'WIND', 'UNKNOWN'])\n# ---\n# name: test_ProductionModes_enum_values\n  dict_values([<ProductionModes.BIOMASS: 'biomass'>, <ProductionModes.COAL: 'coal'>, <ProductionModes.GAS: 'gas'>, <ProductionModes.GEOTHERMAL: 'geothermal'>, <ProductionModes.HYDRO: 'hydro'>, <ProductionModes.NUCLEAR: 'nuclear'>, <ProductionModes.OIL: 'oil'>, <ProductionModes.SOLAR: 'solar'>, <ProductionModes.WIND: 'wind'>, <ProductionModes.UNKNOWN: 'unknown'>])\n# ---\n# name: test_StorageModes_enum_items\n  dict_items([('BATTERY', <StorageModes.BATTERY: 'battery'>), ('HYDRO', <StorageModes.HYDRO: 'hydro'>)])\n# ---\n# name: test_StorageModes_enum_names\n  dict_keys(['BATTERY', 'HYDRO'])\n# ---\n# name: test_StorageModes_enum_values\n  dict_values([<StorageModes.BATTERY: 'battery'>, <StorageModes.HYDRO: 'hydro'>])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/tests/test_config.py",
    "content": "from electricitymap.contrib.parsers.lib.config import ProductionModes, StorageModes\n\n\ndef test_ProductionModes_enum_values(snapshot):\n    assert snapshot == ProductionModes.values()\n\n\ndef test_ProductionModes_enum_names(snapshot):\n    assert snapshot == ProductionModes.names()\n\n\ndef test_ProductionModes_enum_items(snapshot):\n    assert snapshot == ProductionModes.items()\n\n\ndef test_StorageModes_enum_values(snapshot):\n    assert snapshot == StorageModes.values()\n\n\ndef test_StorageModes_enum_names(snapshot):\n    assert snapshot == StorageModes.names()\n\n\ndef test_StorageModes_enum_items(snapshot):\n    assert snapshot == StorageModes.items()\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/utils.py",
    "content": "import os\n\nTOKEN_WIKI_URL = (\n    \"https://github.com/electricitymaps/electricitymaps-contrib/wiki/Create-tokens\"\n)\n\n\ndef get_token(token):\n    \"\"\"\n    Get a token from the environment variables.\n\n    Raises:\n        Exception: if the token variable does not exists or if its value is null\n    \"\"\"\n    if not os.environ.get(token):\n        raise Exception(\n            f\"Environment variable {token} not found !\\n\"\n            f\"Please visit {TOKEN_WIKI_URL}#{token} for more information about how to create \"\n            \"tokens.\"\n        )\n    return os.environ[token]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/validation.py",
    "content": "\"\"\"Centralised validation function for all parsers.\"\"\"\n\nfrom logging import Logger, getLogger\nfrom typing import Any\n\n\ndef validate_exchange(\n    datapoint: dict, logger: Logger = getLogger(__name__)\n) -> dict[str, Any] | None:\n    \"\"\"\n    Validates a production datapoint based on given constraints.\n    If the datapoint is found to be invalid then None is returned.\n    \"\"\"\n    exchange: float = datapoint[\"netFlow\"]\n    if exchange is None:\n        logger.warning(\n            \"{}: expected exchange cannot be null\".format(\n                datapoint[\"sortedZoneKeys\"],\n            ),\n            extra={\"key\": datapoint[\"sortedZoneKeys\"]},\n        )\n        return\n    return datapoint\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/web.py",
    "content": "from bs4 import BeautifulSoup\nfrom requests import Response, Session\n\nfrom .exceptions import ParserException\n\n\ndef get_response(zone_key: str, url: str, session: Session | None = None):\n    ses = session or Session()\n    response: Response = ses.get(url)\n    if response.status_code != 200:\n        raise ParserException(zone_key, f\"Response code: {response.status_code}\")\n    return response\n\n\ndef get_response_with_params(\n    zone_key: str, url, session: Session | None = None, params=None\n):\n    ses = session or Session()\n    response: Response = ses.get(url, params=params)\n    if response.status_code != 200:\n        raise ParserException(zone_key, f\"Response code: {response.status_code}\")\n    return response\n\n\ndef get_response_text(zone_key: str, url, session: Session | None = None):\n    response = get_response(zone_key, url, session)\n    if not response.text:\n        raise ParserException(zone_key, \"Response empty\")\n    return response.text\n\n\ndef get_response_soup(zone_key: str, url, session: Session | None = None):\n    response_text = get_response_text(zone_key, url, session)\n    return BeautifulSoup(response_text, \"html.parser\")\n"
  },
  {
    "path": "electricitymap/contrib/parsers/lib/zonekey.py",
    "content": "from .exceptions import ParserException\n\n\ndef assert_zone_key(zone_key: str, expected, parser_name=None):\n    \"\"\"Assert country code\"\"\"\n    if not zone_key or zone_key != expected:\n        if not parser_name:\n            parser_name = zone_key\n        raise ParserException(\n            parser_name,\n            f\"zone_key expected {expected}, is {zone_key}\",\n            zone_key,\n        )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/occtonet.py",
    "content": "#!/usr/bin/env python3\nfrom datetime import datetime, timedelta\nfrom io import StringIO\nfrom logging import Logger, getLogger\nfrom zoneinfo import ZoneInfo\n\nimport pandas as pd\nfrom requests import Session, cookies\n\nfrom .lib.exceptions import ParserException\n\n# Abbreviations:\n# JP-HKD : Hokkaido\n# JP-TH  : Tohoku (incl. Niigata)\n# JP-TK  : Tokyo area (Kanto)\n# JP-CB  : Chubu\n# JP-HR  : Hokuriku\n# JP-KN  : Kansai\n# JP-CG  : Chugoku\n# JP-SK  : Shikoku\n# JP-KY  : Kyushu\n# JP-ON  : Okinawa\n\n# In selector, they correspond to (format: Japanese original name [english translation])\nEXCHANGE_MAPPING = {\n    \"JP-HKD->JP-TH\": [\n        1\n    ],  # 北海道・本州間電力連系設備 [Hokkaido-Honshu Electric Power Interconnection Facility]\n    \"JP-TH->JP-TK\": [2],  # 相馬双葉幹線 [Soma Futaba Trunk Line]\n    \"JP-CB->JP-TK\": [3],  # 周波数変換設備 [Frequency conversion equipment]\n    \"JP-CB->JP-KN\": [4],  # 三重東近江線 [Mie Higashi-Omi Line]\n    \"JP-CB->JP-HR\": [\n        5,\n        11,\n    ],  # 南福光連系所・南福光変電所の連系設備 [Minami-Fukumitsu Interconnection / Minami-Fukumitsu Substation Interconnection equipment] and 北陸フェンス [Hokuriku fence]\n    \"JP-HR->JP-KN\": [6],  # 越前嶺南線 [Echizen Rinan Line]\n    \"JP-CG->JP-KN\": [\n        7\n    ],  # 西播東岡山線・山崎智頭線 [Nishiban Higashi Okayama Line / Yamazaki Chitou Line]\n    \"JP-KN->JP-SK\": [8],  # 阿南紀北直流幹線 [Anan Kihoku DC Trunk Line]\n    \"JP-CG->JP-SK\": [9],  # 本四連系線 [This Quadruple Interconnection Line]\n    \"JP-CG->JP-KY\": [10],  # 関門連系線 [Kanmon Interconnection Line]\n}\n# correct flow direction, if needed\nFLOWS_TO_REVERT = [\"JP-CB->JP-TK\", \"JP-CG->JP-KN\", \"JP-CG->JP-SK\"]\n\nSOURCE_URL = \"occtonet.occto.or.jp\"\nEXCHANGE_COLUMNS = [\"sortedZoneKeys\", \"netFlow\", \"source\"]\n\nZONE_INFO = ZoneInfo(\"Asia/Tokyo\")\n\n\ndef _fetch_exchange(\n    session: Session, datetime: datetime, sorted_zone_keys: str\n) -> list[dict]:\n    exch_id = EXCHANGE_MAPPING[sorted_zone_keys]\n\n    # This authorises subsequent calls\n    _cookies = get_cookies(session)\n\n    df = pd.DataFrame()\n    for i in range(len(exch_id)):\n        form_data = get_form_data(session, exch_id[i], datetime)\n        _df = get_exchange(session, form_data)\n        if df.empty:\n            df = _df\n        else:\n            df += _df\n            df.reset_index()\n\n    if sorted_zone_keys in FLOWS_TO_REVERT:\n        df[\"netFlow\"] = -1 * df[\"netFlow\"]\n\n    df[\"source\"] = SOURCE_URL\n\n    df[\"sortedZoneKeys\"] = sorted_zone_keys\n    df = df[EXCHANGE_COLUMNS]\n    df = df.reset_index()\n\n    results = df.to_dict(\"records\")\n    # For some reason, to_dict converts datetimes to Timestamps\n    # See https://stackoverflow.com/questions/64171427/pandas-to-dict-converts-datetime-to-timestamp\n    for result in results:\n        result[\"datetime\"] = result[\"datetime\"].to_pydatetime()\n    return results\n\n\ndef fetch_exchange(\n    zone_key1: str = \"JP-TH\",\n    zone_key2: str = \"JP-TK\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Requests the last known power exchange (in MW) between two zones.\"\"\"\n    if not session:\n        session = Session()\n    now = datetime.now(ZONE_INFO)\n    if target_datetime is None:\n        target_datetime = now\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    query_datetime = target_datetime.strftime(\"%Y/%m/%d\")\n\n    sorted_zone_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n    return _fetch_exchange(session, query_datetime, sorted_zone_keys)\n\n\ndef fetch_exchange_forecast(\n    zone_key1: str = \"JP-TH\",\n    zone_key2: str = \"JP-TK\",\n    session: Session | None = None,\n    target_datetime: datetime | None = None,\n    logger: Logger = getLogger(__name__),\n) -> list[dict]:\n    \"\"\"Gets exchange forecast between two specified zones.\"\"\"\n    if not session:\n        session = Session()\n    now = datetime.now(ZONE_INFO)\n    if target_datetime is None:\n        target_datetime = now\n    else:\n        target_datetime = target_datetime.astimezone(ZONE_INFO)\n\n    query_datetime = target_datetime.strftime(\"%Y/%m/%d\")\n\n    if query_datetime > now.strftime(\"%Y/%m/%d\"):\n        raise NotImplementedError(\n            \"Future dates(local time) not implemented for selected exchange\"\n        )\n\n    sorted_zone_keys = \"->\".join(sorted([zone_key1, zone_key2]))\n    return _fetch_exchange(session, query_datetime, sorted_zone_keys)\n\n\ndef get_cookies(session: Session | None = None) -> cookies.RequestsCookieJar:\n    if not session:\n        session = Session()\n    session.get(\"http://occtonet.occto.or.jp/public/dfw/RP11/OCCTO/SD/LOGIN_login\")\n    return session.cookies\n\n\ndef get_form_data(session: Session, exchange_id: int, datetime: str) -> dict[str, str]:\n    form_data = {\n        \"ajaxToken\": \"\",\n        \"downloadKey\": \"\",\n        \"fwExtention.actionSubType\": \"headerInput\",\n        \"fwExtention.actionType\": \"reference\",\n        \"fwExtention.formId\": \"CA01S070P\",\n        \"fwExtention.jsonString\": \"\",\n        \"fwExtention.pagingTargetTable\": \"\",\n        \"fwExtention.pathInfo\": \"CA01S070C\",\n        \"fwExtention.prgbrh\": \"0\",\n        \"msgArea\": \"・マージンには需給調整市場の連系線確保量が含まれております。\",\n        \"requestToken\": \"\",\n        \"requestTokenBk\": \"\",\n        \"searchReqHdn\": \"\",\n        \"simFlgHdn\": \"\",\n        \"sntkTgtRklCdHdn\": \"\",\n        \"spcDay\": datetime,\n        \"spcDayHdn\": \"\",\n        \"tgtRkl\": f\"{exchange_id:02d}\",\n        \"tgtRklHdn\": \"01,北海道・本州間電力連系設備,02,相馬双葉幹線,03,周波数変換設備,04,三重東近江線,05,南福光連系所・南福光変電所の連系設備,06,越前嶺南線,07,西播東岡山線・山崎智頭線,08,阿南紀北直流幹線,09,本四連系線,10,関門連系線,11,北陸フェンス\",\n        \"transitionContextKey\": \"DEFAULT\",\n        \"updDaytime\": \"\",\n    }\n\n    r = session.post(\n        \"https://occtonet3.occto.or.jp/public/dfw/RP11/OCCTO/SD/CA01S070C\",\n        data=form_data,\n    )\n    response_content = r.json()\n\n    if response_content[\"root\"][\"errMessage\"]:\n        raise ParserException(\n            \"occtonet.py\",\n            \"Headers not available due to {}\".format(\n                response_content[\"root\"][\"errMessage\"]\n            ),\n        )\n    else:\n        form_data[\"msgArea\"] = response_content[\"root\"][\"bizRoot\"][\"header\"][\"msgArea\"][\n            \"value\"\n        ]\n        form_data[\"searchReqHdn\"] = response_content[\"root\"][\"bizRoot\"][\"header\"][\n            \"searchReqHdn\"\n        ][\"value\"]\n        form_data[\"spcDayHdn\"] = response_content[\"root\"][\"bizRoot\"][\"header\"][\n            \"spcDayHdn\"\n        ][\"value\"]\n        form_data[\"updDaytime\"] = response_content[\"root\"][\"bizRoot\"][\"header\"][\n            \"updDaytime\"\n        ][\"value\"]\n\n    form_data[\"fwExtention.actionSubType\"] = \"ok\"\n    r = session.post(\n        \"https://occtonet3.occto.or.jp/public/dfw/RP11/OCCTO/SD/CA01S070C\",\n        data=form_data,\n    )\n    response_content = r.json()\n\n    if response_content[\"root\"][\"errFields\"]:\n        raise ParserException(\n            \"occtonet.py\",\n            \"Request token not available due to {}\".format(\n                response_content[\"root\"][\"errFields\"]\n            ),\n        )\n    else:\n        form_data[\"downloadKey\"] = response_content[\"root\"][\"bizRoot\"][\"header\"][\n            \"downloadKey\"\n        ][\"value\"]\n        form_data[\"requestToken\"] = response_content[\"root\"][\"bizRoot\"][\"header\"][\n            \"requestToken\"\n        ][\"value\"]\n    return form_data\n\n\ndef _get_exchange(session: Session, form_data: dict[str, str], columns: list[str]):\n    def parse_dt(str_dt: str) -> datetime:\n        \"\"\"\n        Expects arguments like \"2024/12/23 00:05\", including the edge case 24:00\n        which is the same as 00:00 of the subsequent date.\n        \"\"\"\n        dt = None\n        if \"24:00\" in str_dt:\n            str_dt = str_dt.replace(\"24:00\", \"00:00\")\n            dt = datetime.strptime(str_dt, \"%Y/%m/%d %H:%M\") + timedelta(days=1)\n        else:\n            dt = datetime.strptime(str_dt, \"%Y/%m/%d %H:%M\")\n        return dt.replace(tzinfo=ZONE_INFO)\n\n    form_data[\"fwExtention.actionSubType\"] = \"download\"\n    r = session.post(\n        \"https://occtonet3.occto.or.jp/public/dfw/RP11/OCCTO/SD/CA01S070C\",\n        data=form_data,\n    )\n    r.encoding = \"shift-jis\"\n    df = pd.read_csv(StringIO(r.text), delimiter=\",\")\n    df = df[columns]\n    df.columns = [\"date\", \"time\", \"netFlow\"]\n    df.loc[:, \"datetime\"] = (df.date + \" \" + df.time).apply(lambda x: parse_dt(x))\n    df = df.set_index(\"datetime\")\n    df = df.drop(columns=[\"date\", \"time\"])\n    df = df.dropna()\n    return df\n\n\ndef get_exchange(session: Session, form_data):\n    return _get_exchange(session, form_data, [\"対象日付\", \"対象時刻\", \"潮流実績\"])\n\n\ndef get_exchange_fcst(session: Session, form_data):\n    return _get_exchange(\n        session, form_data, [\"対象日付\", \"対象時刻\", \"計画潮流(順方向)\"]\n    )\n\n\nif __name__ == \"__main__\":\n    \"\"\"Main method, never used by the Electricity Map backend, but handy for testing.\"\"\"\n\n    print(\"fetch_exchange(JP-CB, JP-HR) ->\")\n    print(fetch_exchange(\"JP-CB\", \"JP-HR\")[-3:])\n    print(\"fetch_exchange(JP-CG, JP-KY) ->\")\n    print(fetch_exchange(\"JP-CG\", \"JP-KY\")[-3:])\n    print(\"fetch_exchange_forecast(JP-CB, JP-HR) ->\")\n    print(fetch_exchange_forecast(\"JP-CB\", \"JP-HR\")[-3:])\n    print(\"fetch_exchange_forecast(JP-CG, JP-KY) ->\")\n    print(fetch_exchange_forecast(\"JP-CG\", \"JP-KY\")[-3:])\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_AEMO/test_snapshot_fetch_consumption_forecast[AU-NSW].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast[AU-NSW]\n  list([\n    dict({\n      'consumption': 8407.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8394.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8359.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8223.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8047.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7870.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7678.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7594.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7502.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7406.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7289.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7163.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7043.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6898.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6707.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6521.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6348.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6250.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6199.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6200.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6277.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6457.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6660.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7029.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7377.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7690.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7848.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7770.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7511.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7223.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6879.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6650.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6499.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6240.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6079.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5961.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5860.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5754.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5738.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5737.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5816.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5988.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6327.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6673.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7105.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7565.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7997.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8277.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8469.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8468.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8363.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8221.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8054.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7906.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7715.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7622.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7510.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7400.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7274.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7157.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7035.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6896.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6712.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6525.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6360.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6258.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6208.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6215.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6291.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6475.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6675.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7045.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7375.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7651.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7751.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7599.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7256.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6896.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6480.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6171.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5987.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5771.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5646.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5500.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5569.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5529.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5567.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5655.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5816.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6099.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6521.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6955.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7441.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7923.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8349.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8613.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8765.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8733.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8593.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8414.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8234.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8043.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7836.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7732.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7602.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7479.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7342.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7218.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7092.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6948.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6762.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6597.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6431.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6322.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6266.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6257.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6328.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6510.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6699.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7053.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7363.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7583.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7637.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7466.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7128.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6797.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6408.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6086.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5901.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5708.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5587.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5476.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5493.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5448.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5469.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5533.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5670.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5962.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6385.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6808.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7253.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7714.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8116.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8316.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8420.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8388.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8269.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8102.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7932.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7812.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7653.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7606.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7538.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7466.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7356.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7236.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7107.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6955.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6764.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6596.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6417.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6302.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6227.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6178.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6199.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6289.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6369.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6535.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6705.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6816.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6815.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6714.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6454.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6179.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5798.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5498.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5217.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4930.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4736.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4557.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4429.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4321.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4293.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4330.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4473.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4763.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5200.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5714.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6239.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6762.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7273.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7652.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7876.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7921.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7849.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7746.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7631.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7544.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7421.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7352.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7303.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7251.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7130.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7022.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6911.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6824.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6713.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6605.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6446.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6298.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6178.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6099.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6050.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6031.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6006.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6008.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6026.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6113.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6119.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6066.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5901.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5690.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5416.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5175.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4915.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4651.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4460.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4348.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4193.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4085.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4066.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4143.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4326.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4572.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 4968.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5424.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5975.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6511.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7097.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7584.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7992.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8210.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8185.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8012.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7836.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7730.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7599.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7413.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7248.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7155.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7031.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6953.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6850.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6744.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6627.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6503.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6364.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6237.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6144.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6116.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6122.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6203.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6319.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6575.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6825.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7172.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7364.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7299.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7092.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6807.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6443.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6171.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5934.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5731.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5594.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5491.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5441.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5413.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5456.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5550.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5715.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 5930.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6265.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6627.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7088.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7552.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8019.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8368.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8676.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8780.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8703.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8470.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8244.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8109.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7946.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7768.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7597.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7505.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7403.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7337.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7254.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7157.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7027.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6893.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6714.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6538.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6404.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6330.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6318.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6382.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6484.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6723.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6966.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7328.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7565.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7578.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7463.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7285.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7009.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6805.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6619.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6426.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6312.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6237.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6196.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6167.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6148.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6177.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6254.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6403.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6634.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6919.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7296.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7685.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8082.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8414.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8717.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8830.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8784.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8571.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8365.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8205.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8043.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7860.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7688.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7599.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7490.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7409.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7314.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7204.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7067.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6926.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6739.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6560.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6423.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6345.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6332.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6392.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6490.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6726.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6967.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7322.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7549.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7538.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7406.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7230.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6950.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6736.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6552.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6380.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6276.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6183.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6148.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6115.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6134.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6204.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6322.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6459.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6717.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 6996.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7381.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7760.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8147.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8429.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8708.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8811.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8748.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8521.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8303.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 8156.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7997.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7830.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7665.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7576.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7471.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7386.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'consumption': 7283.0,\n      'datetime': datetime.datetime(2025, 4, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Sydney')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NSW',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_AEMO/test_snapshot_fetch_consumption_forecast[AU-QLD].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast[AU-QLD]\n  list([\n    dict({\n      'consumption': 8263.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8232.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8113.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7901.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7729.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7566.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7387.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7238.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7043.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6823.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6623.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6460.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6321.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6177.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6049.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5996.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5947.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5868.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5822.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5815.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5820.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5872.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5963.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6132.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6333.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6613.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6838.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6967.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6937.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6867.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6753.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6709.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6676.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6715.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6800.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6910.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6956.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6994.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7094.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7154.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7200.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7270.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7399.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7546.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7753.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7894.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8021.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8095.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8172.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8149.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8067.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7869.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7682.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7527.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7357.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7219.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7031.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6800.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6598.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6434.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6302.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6168.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6047.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6001.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5957.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5885.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5839.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5830.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5836.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5887.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5978.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6152.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6339.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6613.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6824.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6932.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6882.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6789.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6642.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6563.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6511.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6527.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6568.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6609.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6632.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6617.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6727.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6793.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6869.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6949.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7146.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7370.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7672.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7892.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8080.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8187.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8286.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8280.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8209.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8039.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7858.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7689.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7519.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7341.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7127.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6901.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6686.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6506.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6359.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6214.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6086.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6029.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5977.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5905.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5858.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5843.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5851.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5897.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5981.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6134.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6293.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6503.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6599.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6606.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6430.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6217.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5936.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5744.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5588.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5542.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5523.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5573.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5604.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5611.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5684.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5797.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5939.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6161.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6382.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6714.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7148.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7536.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7845.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8010.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8106.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 8082.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7996.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7821.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7637.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7446.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7284.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7164.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6985.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6831.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6648.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6475.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6315.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6147.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6004.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5926.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5863.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5784.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5731.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5706.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5694.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5705.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5726.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5773.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5809.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5839.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5765.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5599.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5361.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5146.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4869.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4669.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4482.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4405.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4388.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4441.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4488.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4511.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4581.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4722.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4902.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5177.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5450.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5875.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6368.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6810.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7217.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7499.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7675.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7711.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7634.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7448.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7264.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7085.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6951.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6851.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6697.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6552.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6397.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6256.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6125.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5992.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5868.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5799.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5737.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5660.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5607.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5576.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5558.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5557.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5564.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5577.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5579.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5555.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5426.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5225.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4970.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4767.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4527.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4346.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4202.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4202.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4245.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4349.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4452.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4517.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4599.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4720.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4892.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5144.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5445.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5834.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6282.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6685.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7077.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7382.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7580.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7630.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7550.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7374.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7196.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7049.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6903.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6777.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6594.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6414.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6243.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6105.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5979.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5852.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5733.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5682.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5638.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5583.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5544.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5533.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5541.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5590.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5668.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5803.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5935.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6077.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6106.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6042.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5833.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5610.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5328.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5064.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4827.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4705.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4671.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4676.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4705.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4717.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4792.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4932.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5110.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5379.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5699.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6107.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6583.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7038.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7470.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7758.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7943.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7974.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7883.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7667.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7471.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7297.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7111.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6966.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6768.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6551.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6363.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6209.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6072.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5931.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5799.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5723.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5672.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5604.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5561.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5543.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5552.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5595.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5675.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5809.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5937.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6070.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6083.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5981.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5742.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5492.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5203.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4960.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4765.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4682.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4688.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4739.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4779.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4810.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4892.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5029.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5185.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5439.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5763.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6139.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6558.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6954.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7328.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7600.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7787.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7828.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7747.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7559.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7386.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7227.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7053.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6907.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6707.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6507.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6324.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6175.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6042.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5910.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5784.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5717.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5666.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5607.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5570.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5555.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5563.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5611.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5694.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5825.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5955.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6092.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6112.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6011.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5770.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5516.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5224.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4970.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4757.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4683.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4684.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4719.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4759.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4782.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4857.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 4985.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5129.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5370.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 5702.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6086.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6515.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6929.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7310.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7593.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7787.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7828.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7749.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7564.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7393.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7233.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 7065.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6922.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6727.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6529.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6354.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6207.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'consumption': 6069.0,\n      'datetime': datetime.datetime(2025, 4, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Brisbane')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-QLD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_AEMO/test_snapshot_fetch_consumption_forecast[AU-SA].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast[AU-SA]\n  list([\n    dict({\n      'consumption': 1443.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1571.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1641.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1653.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1626.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1584.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1550.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1506.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1465.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1426.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1394.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1377.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1410.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1422.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1439.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1419.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1388.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1356.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1325.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1304.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1297.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1297.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1314.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1335.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1392.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1452.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1522.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1518.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1440.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1303.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1159.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1013.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 880.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 800.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 733.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 661.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 613.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 581.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 583.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 581.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 602.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 659.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 723.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 831.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 935.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1084.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1228.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1387.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1516.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1614.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1650.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1647.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1612.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1573.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1537.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1494.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1448.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1410.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1374.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1352.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1385.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1391.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1409.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1383.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1352.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1319.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1290.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1272.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1267.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1272.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1290.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1316.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1375.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1442.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1523.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1536.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1487.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1388.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1281.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1157.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1042.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 955.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 895.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 835.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 776.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 733.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 710.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 692.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 692.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 724.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 754.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 819.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 894.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1010.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1142.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1292.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1427.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1534.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1585.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1604.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1591.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1561.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1528.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1484.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1439.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1389.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1353.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1332.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1367.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1370.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1390.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1366.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1336.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1303.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1274.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1257.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1251.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1258.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1277.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1304.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1356.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1421.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1504.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1526.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1480.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1365.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1240.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1098.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 975.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 886.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 813.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 721.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 644.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 585.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 562.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 541.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 543.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 559.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 591.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 674.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 762.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 898.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1051.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1220.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1367.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1481.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1533.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1549.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1535.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1506.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1476.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1439.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1403.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1363.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1333.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1314.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1349.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1364.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1380.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1354.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1322.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1285.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1255.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1237.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1231.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1230.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1242.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1258.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1285.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1314.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1347.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1332.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1251.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1115.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 971.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 815.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 666.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 574.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 477.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 366.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 260.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 175.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 140.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 122.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 119.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 162.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 240.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 357.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 487.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 670.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 868.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1089.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1269.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1407.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1472.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1488.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1474.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1447.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1424.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1388.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1357.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1331.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1307.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1291.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1331.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1374.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1387.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1360.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1326.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1286.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1251.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1229.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1212.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1197.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1183.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1170.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1157.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1144.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1152.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1137.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1101.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1005.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 899.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 775.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 658.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 580.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 515.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 425.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 365.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 318.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 286.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 269.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 252.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 288.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 353.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 447.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 567.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 709.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 883.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1087.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1279.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1420.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1500.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1514.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1490.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1457.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1434.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1404.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1375.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1346.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1320.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1299.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1333.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1373.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1395.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1375.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1348.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1314.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1285.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1263.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1249.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1241.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1241.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1246.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1277.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1313.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1376.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1391.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1376.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1287.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1162.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1021.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 883.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 765.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 668.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 579.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 526.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 467.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 423.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 401.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 399.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 445.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 505.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 597.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 707.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 837.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1000.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1198.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1395.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1545.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1627.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1647.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1623.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1589.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1561.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1528.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1491.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1443.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1404.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1375.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1397.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1396.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1410.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1385.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1356.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1319.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1288.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1266.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1252.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1247.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1245.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1252.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1275.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1309.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1370.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1384.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1357.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1238.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1099.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 943.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 803.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 691.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 608.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 517.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 442.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 401.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 375.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 364.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 375.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 423.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 484.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 579.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 692.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 831.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1003.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1205.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1403.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1550.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1629.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1647.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1620.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1585.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1555.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1522.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1486.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1440.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1402.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1371.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1395.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1417.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1431.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1406.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1377.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1339.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1306.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1280.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1266.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1259.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1258.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1265.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1293.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1326.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1385.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1392.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1365.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1262.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1128.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 979.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 839.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 740.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 651.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 550.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 502.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 449.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 421.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 410.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 428.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 483.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 564.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 674.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 797.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 934.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1102.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1295.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1474.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1600.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1667.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1674.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1639.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1603.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1572.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1537.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1497.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1457.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1420.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1392.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'consumption': 1415.0,\n      'datetime': datetime.datetime(2025, 4, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Adelaide')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-SA',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_AEMO/test_snapshot_fetch_consumption_forecast[AU-TAS].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast[AU-TAS]\n  list([\n    dict({\n      'consumption': 1323.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1325.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1320.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1303.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1283.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1263.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1235.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1209.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1179.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1153.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1128.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1111.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1096.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1080.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1069.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1063.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1061.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1063.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1064.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1068.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1060.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1070.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1092.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1142.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1195.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1260.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1306.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1317.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1330.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1286.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1230.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1176.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1134.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1099.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1078.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1053.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1036.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1025.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1020.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1027.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1031.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1044.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1060.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1088.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1130.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1180.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1222.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1203.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1224.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1230.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1226.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1213.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1193.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1181.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1158.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1192.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1169.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1147.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1124.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1109.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1096.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1087.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1081.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1079.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1077.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1079.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1081.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1085.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1094.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1109.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1128.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1119.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1169.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1242.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1353.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1370.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1344.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1297.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1244.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1196.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1159.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1129.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1112.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1095.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1084.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1082.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1082.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1092.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1100.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1116.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1130.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1154.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1188.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1229.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1262.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1231.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1245.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1250.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1246.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1232.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1212.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1196.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1167.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1138.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1108.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1085.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1063.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1049.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1043.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1095.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1095.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1092.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1090.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1090.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1094.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1101.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1105.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1061.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1080.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1131.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1188.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1255.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1302.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1319.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1307.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1333.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1287.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1244.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1203.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1178.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1159.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1142.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1128.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1116.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1108.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1105.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1102.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1105.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1116.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1136.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1172.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1213.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1251.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1283.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1302.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1307.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1303.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1290.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1272.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1257.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1230.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1208.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1185.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1170.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1152.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1137.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1124.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1112.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1105.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1102.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1098.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1096.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1097.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1102.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1108.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1118.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1133.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1159.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1188.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1226.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1260.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1273.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1269.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1253.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1235.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1214.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1192.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1168.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1150.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1133.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1114.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1097.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1086.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1082.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1079.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1086.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1102.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1126.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1165.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1218.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1265.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1301.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1327.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1335.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1326.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1302.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1281.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1263.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1239.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1216.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1196.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1175.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1156.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1140.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1129.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1114.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1102.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1093.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1087.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1086.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1082.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1082.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1080.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1082.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1080.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1079.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1081.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1093.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1120.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1151.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1175.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1183.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1178.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1170.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1148.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1125.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1102.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1085.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1069.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1060.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1050.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1048.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1048.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1058.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1071.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1098.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1132.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1176.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1225.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1280.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1330.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1357.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1357.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1337.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1316.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1293.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1268.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1242.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1218.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1191.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1165.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1140.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1120.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1104.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1094.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1088.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1084.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1084.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1084.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1087.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1092.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1103.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1118.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1154.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1194.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1255.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1310.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1350.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1353.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1336.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1298.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1269.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1233.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1208.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1182.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1162.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1148.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1140.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1131.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1126.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1126.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1132.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1145.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1168.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1198.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1240.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1287.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1286.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1333.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1358.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1358.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1334.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1311.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1286.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1258.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1233.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1203.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1168.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1134.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1107.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1090.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1121.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1114.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1107.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1102.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1101.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1102.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1106.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1111.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1122.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1138.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1172.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1213.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1276.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1331.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1368.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1366.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1334.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1286.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1240.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1197.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1163.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1133.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1110.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1093.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1084.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1074.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1072.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1071.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1078.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1089.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1109.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1138.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1177.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1225.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1284.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1338.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1371.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1372.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1357.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1336.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1318.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1291.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1268.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1240.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1207.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1176.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1149.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1129.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1115.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1106.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1099.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1095.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1094.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1094.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1097.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1101.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1111.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1127.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1162.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1201.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1261.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1313.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1345.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1339.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1305.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1260.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1217.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1177.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1145.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1118.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1098.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1082.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1075.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1067.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1068.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1069.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1076.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1087.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1109.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1138.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1176.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1222.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1279.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1329.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1352.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1351.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1335.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1313.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1294.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1269.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1248.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1222.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1195.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1164.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1139.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'consumption': 1119.0,\n      'datetime': datetime.datetime(2025, 4, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Hobart')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-TAS',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_AEMO/test_snapshot_fetch_consumption_forecast[AU-VIC].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast[AU-VIC]\n  list([\n    dict({\n      'consumption': 5449.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5525.0,\n      'datetime': datetime.datetime(2025, 4, 1, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5599.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5562.0,\n      'datetime': datetime.datetime(2025, 4, 1, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5435.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5279.0,\n      'datetime': datetime.datetime(2025, 4, 1, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5111.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4948.0,\n      'datetime': datetime.datetime(2025, 4, 1, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4790.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4654.0,\n      'datetime': datetime.datetime(2025, 4, 1, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4588.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4655.0,\n      'datetime': datetime.datetime(2025, 4, 1, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4612.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4493.0,\n      'datetime': datetime.datetime(2025, 4, 2, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4369.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4264.0,\n      'datetime': datetime.datetime(2025, 4, 2, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4170.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4122.0,\n      'datetime': datetime.datetime(2025, 4, 2, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4092.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4111.0,\n      'datetime': datetime.datetime(2025, 4, 2, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4152.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4275.0,\n      'datetime': datetime.datetime(2025, 4, 2, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4432.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4729.0,\n      'datetime': datetime.datetime(2025, 4, 2, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5040.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5397.0,\n      'datetime': datetime.datetime(2025, 4, 2, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5567.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5450.0,\n      'datetime': datetime.datetime(2025, 4, 2, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5176.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4795.0,\n      'datetime': datetime.datetime(2025, 4, 2, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4373.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4016.0,\n      'datetime': datetime.datetime(2025, 4, 2, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3692.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3390.0,\n      'datetime': datetime.datetime(2025, 4, 2, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3121.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2939.0,\n      'datetime': datetime.datetime(2025, 4, 2, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2812.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2757.0,\n      'datetime': datetime.datetime(2025, 4, 2, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2777.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2860.0,\n      'datetime': datetime.datetime(2025, 4, 2, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2995.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3135.0,\n      'datetime': datetime.datetime(2025, 4, 2, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3359.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3669.0,\n      'datetime': datetime.datetime(2025, 4, 2, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4038.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4410.0,\n      'datetime': datetime.datetime(2025, 4, 2, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4813.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5139.0,\n      'datetime': datetime.datetime(2025, 4, 2, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5420.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5600.0,\n      'datetime': datetime.datetime(2025, 4, 2, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5653.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5588.0,\n      'datetime': datetime.datetime(2025, 4, 2, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5487.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5358.0,\n      'datetime': datetime.datetime(2025, 4, 2, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5182.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5007.0,\n      'datetime': datetime.datetime(2025, 4, 2, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4837.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4685.0,\n      'datetime': datetime.datetime(2025, 4, 2, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4609.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4672.0,\n      'datetime': datetime.datetime(2025, 4, 2, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4630.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4515.0,\n      'datetime': datetime.datetime(2025, 4, 3, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4392.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4289.0,\n      'datetime': datetime.datetime(2025, 4, 3, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4192.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4140.0,\n      'datetime': datetime.datetime(2025, 4, 3, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4110.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4128.0,\n      'datetime': datetime.datetime(2025, 4, 3, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4175.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4300.0,\n      'datetime': datetime.datetime(2025, 4, 3, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4460.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4757.0,\n      'datetime': datetime.datetime(2025, 4, 3, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5067.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5423.0,\n      'datetime': datetime.datetime(2025, 4, 3, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5611.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5529.0,\n      'datetime': datetime.datetime(2025, 4, 3, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5310.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5023.0,\n      'datetime': datetime.datetime(2025, 4, 3, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4684.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4420.0,\n      'datetime': datetime.datetime(2025, 4, 3, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4162.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3906.0,\n      'datetime': datetime.datetime(2025, 4, 3, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3740.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3647.0,\n      'datetime': datetime.datetime(2025, 4, 3, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3530.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3458.0,\n      'datetime': datetime.datetime(2025, 4, 3, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3460.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3511.0,\n      'datetime': datetime.datetime(2025, 4, 3, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3611.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3737.0,\n      'datetime': datetime.datetime(2025, 4, 3, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3910.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4130.0,\n      'datetime': datetime.datetime(2025, 4, 3, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4414.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4721.0,\n      'datetime': datetime.datetime(2025, 4, 3, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5037.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5288.0,\n      'datetime': datetime.datetime(2025, 4, 3, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5495.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5624.0,\n      'datetime': datetime.datetime(2025, 4, 3, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5663.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5623.0,\n      'datetime': datetime.datetime(2025, 4, 3, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5533.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5384.0,\n      'datetime': datetime.datetime(2025, 4, 3, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5224.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5045.0,\n      'datetime': datetime.datetime(2025, 4, 3, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4876.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4727.0,\n      'datetime': datetime.datetime(2025, 4, 3, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4643.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4704.0,\n      'datetime': datetime.datetime(2025, 4, 3, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4662.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4551.0,\n      'datetime': datetime.datetime(2025, 4, 4, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4429.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4338.0,\n      'datetime': datetime.datetime(2025, 4, 4, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4238.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4188.0,\n      'datetime': datetime.datetime(2025, 4, 4, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4154.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4166.0,\n      'datetime': datetime.datetime(2025, 4, 4, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4213.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4336.0,\n      'datetime': datetime.datetime(2025, 4, 4, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4492.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4764.0,\n      'datetime': datetime.datetime(2025, 4, 4, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5073.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5438.0,\n      'datetime': datetime.datetime(2025, 4, 4, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5658.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5637.0,\n      'datetime': datetime.datetime(2025, 4, 4, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5470.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5255.0,\n      'datetime': datetime.datetime(2025, 4, 4, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4951.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4642.0,\n      'datetime': datetime.datetime(2025, 4, 4, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4395.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4239.0,\n      'datetime': datetime.datetime(2025, 4, 4, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4040.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3912.0,\n      'datetime': datetime.datetime(2025, 4, 4, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3775.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3667.0,\n      'datetime': datetime.datetime(2025, 4, 4, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3612.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3577.0,\n      'datetime': datetime.datetime(2025, 4, 4, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3606.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3692.0,\n      'datetime': datetime.datetime(2025, 4, 4, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3843.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4051.0,\n      'datetime': datetime.datetime(2025, 4, 4, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4348.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4655.0,\n      'datetime': datetime.datetime(2025, 4, 4, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4973.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5222.0,\n      'datetime': datetime.datetime(2025, 4, 4, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5432.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5582.0,\n      'datetime': datetime.datetime(2025, 4, 4, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5623.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5579.0,\n      'datetime': datetime.datetime(2025, 4, 4, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5486.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5325.0,\n      'datetime': datetime.datetime(2025, 4, 4, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5195.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5044.0,\n      'datetime': datetime.datetime(2025, 4, 4, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4899.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4781.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4710.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4768.0,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4715.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4601.0,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4468.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4356.0,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4244.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4172.0,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4120.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4105.0,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4118.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4185.0,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4261.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4391.0,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4541.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4746.0,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4829.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4757.0,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4605.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4496.0,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4324.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4144.0,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3965.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3874.0,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3777.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3661.0,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3539.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3433.0,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3361.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3301.0,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3293.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3391.0,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3528.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3742.0,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4039.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4352.0,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4674.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4952.0,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5166.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5325.0,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5356.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5312.0,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5221.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5086.0,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4985.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4860.0,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4746.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4669.0,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4622.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4712.0,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4710.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4659.0,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4548.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4444.0,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4299.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4193.0,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4113.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4057.0,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4017.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3986.0,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3962.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3951.0,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3959.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4046.0,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4112.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4154.0,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4122.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4056.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3889.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3650.0,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3398.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3206.0,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3032.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2935.0,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2834.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2788.0,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2757.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2800.0,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2868.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 2971.0,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3142.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3365.0,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3652.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3986.0,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4402.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4845.0,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5244.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5498.0,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5585.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5522.0,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5419.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5297.0,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5175.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5059.0,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4931.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4802.0,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4700.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4721.0,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4659.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4546.0,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4411.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4296.0,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4174.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4085.0,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4029.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4007.0,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4003.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4053.0,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4125.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4275.0,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4467.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4772.0,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5043.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5244.0,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5326.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5304.0,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5179.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4981.0,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4750.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4612.0,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4556.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4487.0,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4396.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4333.0,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4299.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4288.0,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4307.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4388.0,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4498.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4657.0,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4862.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5100.0,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5389.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5688.0,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5967.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 6171.0,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 6208.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 6114.0,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5979.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5814.0,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5689.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5538.0,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5368.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5201.0,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5062.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5047.0,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4960.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4815.0,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4655.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4516.0,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4381.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4286.0,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4224.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4190.0,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4188.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4232.0,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4309.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4439.0,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4636.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4942.0,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5201.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5363.0,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5383.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5297.0,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5080.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4823.0,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4526.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4261.0,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3990.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3865.0,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3734.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3657.0,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3608.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3589.0,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3616.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3739.0,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3879.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4061.0,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4329.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4629.0,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4995.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5378.0,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5751.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 6025.0,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 6113.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 6052.0,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5937.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5781.0,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5653.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5505.0,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5340.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5175.0,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5041.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5028.0,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4940.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4799.0,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4642.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4503.0,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4370.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4274.0,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4211.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4177.0,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4168.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4204.0,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4278.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4414.0,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4606.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4913.0,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5167.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5315.0,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5331.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5244.0,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5029.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4734.0,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4415.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4154.0,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3875.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3720.0,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3600.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3545.0,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3527.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3570.0,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3615.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3708.0,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 3846.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4035.0,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4296.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4588.0,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4956.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5333.0,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5686.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5922.0,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 6002.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5947.0,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5831.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5677.0,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5552.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5417.0,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5269.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 5111.0,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4986.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4997.0,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'consumption': 4934.0,\n      'datetime': datetime.datetime(2025, 4, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Melbourne')),\n      'source': 'aemo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-VIC',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_AW.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n        'unknown',\n      ]),\n      'datetime': datetime.datetime(2023, 9, 12, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Aruba')),\n      'production': dict({\n        'biomass': 0.0,\n        'oil': 108.567078,\n        'solar': 0.0,\n        'unknown': 0,\n        'wind': 4.692129,\n      }),\n      'source': 'webaruba.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AW',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_BE/test_fetch_production.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 320.0,\n        'gas': 700.0,\n        'hydro': 46.0,\n        'nuclear': 3950.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 560.0,\n        'wind': 4230.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 30.0,\n        'hydro': 200.0,\n      }),\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 321.0,\n        'gas': 550.0,\n        'hydro': 46.7,\n        'nuclear': 3948.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 607.0,\n        'wind': 4217.0,\n      }),\n      'source': 'entsoe.eu, opendata.elia.be',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 40.0,\n        'hydro': 180.0,\n      }),\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 325.84,\n        'gas': 560.96,\n        'hydro': 46.67,\n        'nuclear': 3947.66,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 600.66,\n        'wind': 4251.79,\n      }),\n      'source': 'opendata.elia.be',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 45.0,\n        'hydro': None,\n      }),\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 320.65,\n        'gas': None,\n        'hydro': 46.86,\n        'nuclear': 3947.71,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 591.49,\n        'wind': 4266.5,\n      }),\n      'source': 'opendata.elia.be',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 50.0,\n        'hydro': None,\n      }),\n      'zoneKey': 'BE',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_BG.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 21.58,\n        'coal': 762.85,\n        'gas': 458.2,\n        'hydro': 778.79,\n        'nuclear': 2118.06,\n        'solar': 159.23,\n        'wind': 178.62,\n      }),\n      'source': 'eso.bg',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BG',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CAMMESA.ambr",
    "content": "# serializer version: 1\n# name: test_exchanges_AR_BAS_AR_COM\n  list([\n  ])\n# ---\n# name: test_exchanges_AR_CL_SEN\n  list([\n    dict({\n      'datetime': datetime.datetime(2023, 8, 30, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'netFlow': 200.0,\n      'sortedZoneKeys': 'AR->CL-SEN',\n      'source': 'cammesaweb.cammesa.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 7, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'biomass': 161.85,\n        'coal': np.float64(224.613),\n        'gas': np.float64(5989.68),\n        'hydro': 6086.5,\n        'nuclear': 1388.4,\n        'oil': np.float64(1272.807),\n        'solar': 0.0,\n        'wind': 2009.54,\n      }),\n      'source': 'cammesaweb.cammesa.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 7, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'biomass': 157.2,\n        'coal': np.float64(216.69),\n        'gas': np.float64(5778.4),\n        'hydro': 5893.23,\n        'nuclear': 1390.4,\n        'oil': np.float64(1227.91),\n        'solar': 0.0,\n        'wind': 1944.1,\n      }),\n      'source': 'cammesaweb.cammesa.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 7, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'biomass': 158.55,\n        'coal': np.float64(216.18),\n        'gas': np.float64(5764.8),\n        'hydro': 6028.12,\n        'nuclear': 1394.0,\n        'oil': np.float64(1225.02),\n        'solar': 0.0,\n        'wind': 1922.51,\n      }),\n      'source': 'cammesaweb.cammesa.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 7, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'biomass': 148.3,\n        'coal': np.float64(204.066),\n        'gas': np.float64(5441.76),\n        'hydro': 6592.0,\n        'nuclear': 1394.6,\n        'oil': np.float64(1156.374),\n        'solar': 0.0,\n        'wind': 1900.64,\n      }),\n      'source': 'cammesaweb.cammesa.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 7, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'biomass': 149.74,\n        'coal': np.float64(202.74),\n        'gas': np.float64(5406.4),\n        'hydro': 6678.26,\n        'nuclear': 1387.0,\n        'oil': np.float64(1148.86),\n        'solar': 0.0,\n        'wind': 1871.5,\n      }),\n      'source': 'cammesaweb.cammesa.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 7, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'biomass': 155.96,\n        'coal': np.float64(203.736),\n        'gas': np.float64(5432.96),\n        'hydro': 6525.16,\n        'nuclear': 1388.1,\n        'oil': np.float64(1154.504),\n        'solar': 0.0,\n        'wind': 1835.68,\n      }),\n      'source': 'cammesaweb.cammesa.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AR',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CA_AB.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_wind_solar_forecasts\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2075.84,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1906.32,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1835.3,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 6.45,\n        'wind': 1611.24,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 92.67,\n        'wind': 1279.4,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 255.75,\n        'wind': 951.19,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 378.89,\n        'wind': 896.19,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 592.6,\n        'wind': 751.44,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 744.04,\n        'wind': 587.83,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 945.51,\n        'wind': 428.2,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1044.34,\n        'wind': 318.69,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1017.66,\n        'wind': 327.06,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1051.89,\n        'wind': 380.76,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 875.65,\n        'wind': 400.51,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 438.7,\n        'wind': 474.17,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 49.55,\n        'wind': 682.37,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1153.81,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1998.39,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2734.04,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3223.62,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3354.24,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3343.46,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3108.56,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2972.83,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2815.32,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2398.31,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2203.6,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 37.0,\n        'wind': 2179.59,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 425.15,\n        'wind': 1937.05,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1052.06,\n        'wind': 1676.27,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1394.69,\n        'wind': 1571.24,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1542.91,\n        'wind': 1413.35,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1526.05,\n        'wind': 1463.77,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1520.99,\n        'wind': 1599.64,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1459.68,\n        'wind': 1683.99,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1474.66,\n        'wind': 1884.76,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1302.4,\n        'wind': 2054.58,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 903.29,\n        'wind': 2066.41,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 367.85,\n        'wind': 2151.22,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 34.62,\n        'wind': 2446.55,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2787.36,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3005.29,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2958.56,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2728.82,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2872.64,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3057.42,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2760.59,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2761.04,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.16,\n        'wind': 2518.45,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2630.01,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2684.44,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 26.79,\n        'wind': 2726.33,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 270.37,\n        'wind': 2695.77,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 684.02,\n        'wind': 2608.56,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 980.8,\n        'wind': 2581.71,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1052.13,\n        'wind': 2664.17,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1067.09,\n        'wind': 2723.39,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1063.03,\n        'wind': 2749.84,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1002.02,\n        'wind': 2805.44,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 924.19,\n        'wind': 2819.94,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 793.55,\n        'wind': 2728.52,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 573.29,\n        'wind': 2545.87,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 248.39,\n        'wind': 2336.72,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 26.89,\n        'wind': 2196.89,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2127.59,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2085.43,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2138.91,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2296.83,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2501.88,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2623.14,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2664.52,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2609.34,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2454.05,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2306.57,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2229.69,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 39.76,\n        'wind': 2247.47,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 385.04,\n        'wind': 2325.91,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 957.74,\n        'wind': 2402.4,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1198.69,\n        'wind': 2520.28,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1275.6,\n        'wind': 2769.0,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1377.96,\n        'wind': 3026.26,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1397.03,\n        'wind': 3159.56,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1349.97,\n        'wind': 3224.79,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1241.67,\n        'wind': 3263.18,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1113.24,\n        'wind': 3163.95,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 807.78,\n        'wind': 3002.09,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 338.54,\n        'wind': 2924.69,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 37.67,\n        'wind': 2905.45,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2882.94,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2905.29,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2888.12,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 21, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2774.21,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2757.69,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2693.8,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2501.02,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2337.3,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2289.05,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2289.41,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2314.28,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 35.84,\n        'wind': 2359.24,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 336.2,\n        'wind': 2388.96,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 883.09,\n        'wind': 2263.51,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1176.49,\n        'wind': 2232.78,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1271.94,\n        'wind': 2456.57,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1283.86,\n        'wind': 2661.78,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1289.17,\n        'wind': 2787.19,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1283.37,\n        'wind': 2863.95,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1224.96,\n        'wind': 2832.66,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1118.23,\n        'wind': 2663.64,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 844.65,\n        'wind': 2308.15,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 381.27,\n        'wind': 1846.8,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 44.23,\n        'wind': 1466.25,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1286.42,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1350.13,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1552.23,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 22, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1856.1,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2172.01,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2331.96,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2443.43,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2537.34,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2538.76,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2474.68,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2331.5,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 40.94,\n        'wind': 2171.29,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 343.79,\n        'wind': 2046.98,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 761.01,\n        'wind': 1915.01,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1095.24,\n        'wind': 1836.61,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1225.34,\n        'wind': 1865.58,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1244.38,\n        'wind': 1980.43,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1218.48,\n        'wind': 2171.58,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1105.9,\n        'wind': 2365.33,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 924.7,\n        'wind': 2462.26,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 715.81,\n        'wind': 2463.87,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 500.26,\n        'wind': 2476.2,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 207.14,\n        'wind': 2549.52,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 22.0,\n        'wind': 2682.49,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2824.99,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3004.88,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3222.3,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 23, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3432.0,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3410.77,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3347.85,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3336.45,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3381.71,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3489.38,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3615.25,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 3648.05,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 39.21,\n        'wind': 3592.14,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 347.06,\n        'wind': 3544.68,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 839.6,\n        'wind': 3451.86,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1099.13,\n        'wind': 3315.51,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1166.37,\n        'wind': 3203.98,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1181.96,\n        'wind': 3184.4,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1184.72,\n        'wind': 3249.39,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1171.91,\n        'wind': 3305.01,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1113.87,\n        'wind': 3238.0,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 996.96,\n        'wind': 3050.58,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 737.12,\n        'wind': 2866.87,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 332.57,\n        'wind': 2750.01,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 40.25,\n        'wind': 2677.44,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2596.28,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2434.07,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2193.09,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 24, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1972.17,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1954.94,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1861.77,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1663.76,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1487.08,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1386.28,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1343.79,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1285.85,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 83.25,\n        'wind': 1199.83,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 608.86,\n        'wind': 1117.63,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1235.43,\n        'wind': 981.59,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1480.63,\n        'wind': 807.26,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1524.12,\n        'wind': 660.33,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1507.31,\n        'wind': 545.48,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1482.3,\n        'wind': 461.07,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1392.35,\n        'wind': 387.29,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1189.23,\n        'wind': 343.33,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 927.13,\n        'wind': 332.73,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 658.17,\n        'wind': 335.67,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 299.52,\n        'wind': 384.62,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 36.22,\n        'wind': 478.75,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 592.31,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 738.91,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 940.19,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1218.63,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1382.06,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1371.95,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1376.56,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1398.32,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1424.7,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1466.54,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1418.28,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 101.49,\n        'wind': 1269.18,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 674.47,\n        'wind': 1126.72,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1288.7,\n        'wind': 979.06,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1508.01,\n        'wind': 838.16,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1529.61,\n        'wind': 725.9,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1507.52,\n        'wind': 666.05,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1495.4,\n        'wind': 666.97,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1486.39,\n        'wind': 694.43,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1458.18,\n        'wind': 734.62,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1348.36,\n        'wind': 793.65,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 1031.83,\n        'wind': 893.54,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 492.13,\n        'wind': 1026.32,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 67.68,\n        'wind': 1173.18,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1326.32,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1484.26,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1669.98,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1890.94,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2012.26,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 27, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2015.65,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 27, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2040.9,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 27, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Canada/Mountain')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2080.44,\n      }),\n      'source': 'ets.aeso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-AB',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CA_CQ.ambr",
    "content": "# serializer version: 1\n# name: test_consumption\n  list([\n    dict({\n      'consumption': 15812.0,\n      'datetime': datetime.datetime(2023, 8, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15704.0,\n      'datetime': datetime.datetime(2023, 8, 15, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15497.0,\n      'datetime': datetime.datetime(2023, 8, 15, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15477.0,\n      'datetime': datetime.datetime(2023, 8, 15, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15330.0,\n      'datetime': datetime.datetime(2023, 8, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15231.0,\n      'datetime': datetime.datetime(2023, 8, 15, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15136.0,\n      'datetime': datetime.datetime(2023, 8, 15, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15049.0,\n      'datetime': datetime.datetime(2023, 8, 15, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14879.0,\n      'datetime': datetime.datetime(2023, 8, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14942.0,\n      'datetime': datetime.datetime(2023, 8, 15, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14872.0,\n      'datetime': datetime.datetime(2023, 8, 15, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14812.0,\n      'datetime': datetime.datetime(2023, 8, 15, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14759.0,\n      'datetime': datetime.datetime(2023, 8, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14795.0,\n      'datetime': datetime.datetime(2023, 8, 15, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14744.0,\n      'datetime': datetime.datetime(2023, 8, 15, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14686.0,\n      'datetime': datetime.datetime(2023, 8, 15, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14578.0,\n      'datetime': datetime.datetime(2023, 8, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14694.0,\n      'datetime': datetime.datetime(2023, 8, 15, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14754.0,\n      'datetime': datetime.datetime(2023, 8, 15, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14820.0,\n      'datetime': datetime.datetime(2023, 8, 15, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14894.0,\n      'datetime': datetime.datetime(2023, 8, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15189.0,\n      'datetime': datetime.datetime(2023, 8, 15, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15246.0,\n      'datetime': datetime.datetime(2023, 8, 15, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15360.0,\n      'datetime': datetime.datetime(2023, 8, 15, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15512.0,\n      'datetime': datetime.datetime(2023, 8, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16031.0,\n      'datetime': datetime.datetime(2023, 8, 15, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16220.0,\n      'datetime': datetime.datetime(2023, 8, 15, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16540.0,\n      'datetime': datetime.datetime(2023, 8, 15, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16783.0,\n      'datetime': datetime.datetime(2023, 8, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 17240.0,\n      'datetime': datetime.datetime(2023, 8, 15, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 17396.0,\n      'datetime': datetime.datetime(2023, 8, 15, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 17668.0,\n      'datetime': datetime.datetime(2023, 8, 15, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 17734.0,\n      'datetime': datetime.datetime(2023, 8, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18065.0,\n      'datetime': datetime.datetime(2023, 8, 15, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18268.0,\n      'datetime': datetime.datetime(2023, 8, 15, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18272.0,\n      'datetime': datetime.datetime(2023, 8, 15, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18316.0,\n      'datetime': datetime.datetime(2023, 8, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18315.0,\n      'datetime': datetime.datetime(2023, 8, 15, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18514.0,\n      'datetime': datetime.datetime(2023, 8, 15, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18500.0,\n      'datetime': datetime.datetime(2023, 8, 15, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18538.0,\n      'datetime': datetime.datetime(2023, 8, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18539.0,\n      'datetime': datetime.datetime(2023, 8, 15, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18663.0,\n      'datetime': datetime.datetime(2023, 8, 15, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18812.0,\n      'datetime': datetime.datetime(2023, 8, 15, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18918.0,\n      'datetime': datetime.datetime(2023, 8, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18997.0,\n      'datetime': datetime.datetime(2023, 8, 15, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19117.0,\n      'datetime': datetime.datetime(2023, 8, 15, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19084.0,\n      'datetime': datetime.datetime(2023, 8, 15, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19082.0,\n      'datetime': datetime.datetime(2023, 8, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19070.0,\n      'datetime': datetime.datetime(2023, 8, 15, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19177.0,\n      'datetime': datetime.datetime(2023, 8, 15, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19244.0,\n      'datetime': datetime.datetime(2023, 8, 15, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19293.0,\n      'datetime': datetime.datetime(2023, 8, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19195.0,\n      'datetime': datetime.datetime(2023, 8, 15, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19160.0,\n      'datetime': datetime.datetime(2023, 8, 15, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19055.0,\n      'datetime': datetime.datetime(2023, 8, 15, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19091.0,\n      'datetime': datetime.datetime(2023, 8, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18962.0,\n      'datetime': datetime.datetime(2023, 8, 15, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19109.0,\n      'datetime': datetime.datetime(2023, 8, 15, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19141.0,\n      'datetime': datetime.datetime(2023, 8, 15, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19007.0,\n      'datetime': datetime.datetime(2023, 8, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18956.0,\n      'datetime': datetime.datetime(2023, 8, 15, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19095.0,\n      'datetime': datetime.datetime(2023, 8, 15, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19157.0,\n      'datetime': datetime.datetime(2023, 8, 15, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19153.0,\n      'datetime': datetime.datetime(2023, 8, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19238.0,\n      'datetime': datetime.datetime(2023, 8, 15, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19285.0,\n      'datetime': datetime.datetime(2023, 8, 15, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19569.0,\n      'datetime': datetime.datetime(2023, 8, 15, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19675.0,\n      'datetime': datetime.datetime(2023, 8, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19723.0,\n      'datetime': datetime.datetime(2023, 8, 15, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19714.0,\n      'datetime': datetime.datetime(2023, 8, 15, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19734.0,\n      'datetime': datetime.datetime(2023, 8, 15, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19745.0,\n      'datetime': datetime.datetime(2023, 8, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19530.0,\n      'datetime': datetime.datetime(2023, 8, 15, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19573.0,\n      'datetime': datetime.datetime(2023, 8, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19492.0,\n      'datetime': datetime.datetime(2023, 8, 15, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19317.0,\n      'datetime': datetime.datetime(2023, 8, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19310.0,\n      'datetime': datetime.datetime(2023, 8, 15, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19307.0,\n      'datetime': datetime.datetime(2023, 8, 15, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19273.0,\n      'datetime': datetime.datetime(2023, 8, 15, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19083.0,\n      'datetime': datetime.datetime(2023, 8, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19001.0,\n      'datetime': datetime.datetime(2023, 8, 15, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19100.0,\n      'datetime': datetime.datetime(2023, 8, 15, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 19039.0,\n      'datetime': datetime.datetime(2023, 8, 15, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18930.0,\n      'datetime': datetime.datetime(2023, 8, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18579.0,\n      'datetime': datetime.datetime(2023, 8, 15, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18534.0,\n      'datetime': datetime.datetime(2023, 8, 15, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 18198.0,\n      'datetime': datetime.datetime(2023, 8, 15, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 17922.0,\n      'datetime': datetime.datetime(2023, 8, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 17589.0,\n      'datetime': datetime.datetime(2023, 8, 15, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 17350.0,\n      'datetime': datetime.datetime(2023, 8, 15, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 17124.0,\n      'datetime': datetime.datetime(2023, 8, 15, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16811.0,\n      'datetime': datetime.datetime(2023, 8, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16558.0,\n      'datetime': datetime.datetime(2023, 8, 15, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16338.0,\n      'datetime': datetime.datetime(2023, 8, 15, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16305.0,\n      'datetime': datetime.datetime(2023, 8, 15, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16097.0,\n      'datetime': datetime.datetime(2023, 8, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15834.0,\n      'datetime': datetime.datetime(2023, 8, 16, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15685.0,\n      'datetime': datetime.datetime(2023, 8, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15481.0,\n      'datetime': datetime.datetime(2023, 8, 16, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15369.0,\n      'datetime': datetime.datetime(2023, 8, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15294.0,\n      'datetime': datetime.datetime(2023, 8, 16, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14978.0,\n      'datetime': datetime.datetime(2023, 8, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14978.0,\n      'datetime': datetime.datetime(2023, 8, 16, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14753.0,\n      'datetime': datetime.datetime(2023, 8, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14961.0,\n      'datetime': datetime.datetime(2023, 8, 16, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14751.0,\n      'datetime': datetime.datetime(2023, 8, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14724.0,\n      'datetime': datetime.datetime(2023, 8, 16, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14441.0,\n      'datetime': datetime.datetime(2023, 8, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14349.0,\n      'datetime': datetime.datetime(2023, 8, 16, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14581.0,\n      'datetime': datetime.datetime(2023, 8, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14720.0,\n      'datetime': datetime.datetime(2023, 8, 16, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14800.0,\n      'datetime': datetime.datetime(2023, 8, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14859.0,\n      'datetime': datetime.datetime(2023, 8, 16, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14951.0,\n      'datetime': datetime.datetime(2023, 8, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14857.0,\n      'datetime': datetime.datetime(2023, 8, 16, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 14956.0,\n      'datetime': datetime.datetime(2023, 8, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15283.0,\n      'datetime': datetime.datetime(2023, 8, 16, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15362.0,\n      'datetime': datetime.datetime(2023, 8, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15387.0,\n      'datetime': datetime.datetime(2023, 8, 16, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 15599.0,\n      'datetime': datetime.datetime(2023, 8, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16027.0,\n      'datetime': datetime.datetime(2023, 8, 16, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'consumption': 16363.0,\n      'datetime': datetime.datetime(2023, 8, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CA-QC',\n    }),\n  ])\n# ---\n# name: test_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 633.0,\n        'gas': 0.0,\n        'hydro': 15660.0,\n        'solar': 0.0,\n        'wind': 201.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 615.0,\n        'gas': 0.0,\n        'hydro': 15324.0,\n        'solar': 0.0,\n        'wind': 146.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 614.0,\n        'gas': 0.0,\n        'hydro': 14781.0,\n        'solar': 0.0,\n        'wind': 115.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 610.0,\n        'gas': 0.0,\n        'hydro': 14809.0,\n        'solar': 0.0,\n        'wind': 55.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 610.0,\n        'gas': 0.0,\n        'hydro': 14420.0,\n        'solar': 0.0,\n        'wind': 30.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 613.0,\n        'gas': 0.0,\n        'hydro': 15449.0,\n        'solar': 0.0,\n        'wind': 23.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 611.0,\n        'gas': 0.0,\n        'hydro': 16572.0,\n        'solar': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 609.0,\n        'gas': 0.0,\n        'hydro': 18555.0,\n        'solar': 1.0,\n        'wind': 12.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 605.0,\n        'gas': 0.0,\n        'hydro': 19478.0,\n        'solar': 4.0,\n        'wind': 7.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 592.0,\n        'gas': 0.0,\n        'hydro': 20074.0,\n        'solar': 4.0,\n        'wind': 5.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 599.0,\n        'gas': 0.0,\n        'hydro': 20286.0,\n        'solar': 7.0,\n        'wind': 6.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 605.0,\n        'gas': 0.0,\n        'hydro': 20599.0,\n        'solar': 7.0,\n        'wind': 14.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 599.0,\n        'gas': 0.0,\n        'hydro': 20653.0,\n        'solar': 7.0,\n        'wind': 20.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 603.0,\n        'gas': 0.0,\n        'hydro': 20549.0,\n        'solar': 7.0,\n        'wind': 48.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 603.0,\n        'gas': 0.0,\n        'hydro': 20586.0,\n        'solar': 4.0,\n        'wind': 43.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 605.0,\n        'gas': 0.0,\n        'hydro': 21051.0,\n        'solar': 6.0,\n        'wind': 49.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 603.0,\n        'gas': 0.0,\n        'hydro': 21225.0,\n        'solar': 7.0,\n        'wind': 39.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 606.0,\n        'gas': 0.0,\n        'hydro': 21785.0,\n        'solar': 1.0,\n        'wind': 60.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 603.0,\n        'gas': 0.0,\n        'hydro': 21498.0,\n        'solar': 1.0,\n        'wind': 60.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 606.0,\n        'gas': 0.0,\n        'hydro': 21503.0,\n        'solar': 0.0,\n        'wind': 65.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 609.0,\n        'gas': 0.0,\n        'hydro': 20725.0,\n        'solar': 0.0,\n        'wind': 110.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 614.0,\n        'gas': 0.0,\n        'hydro': 19213.0,\n        'solar': 0.0,\n        'wind': 194.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 613.0,\n        'gas': 0.0,\n        'hydro': 18053.0,\n        'solar': 0.0,\n        'wind': 215.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 15, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 615.0,\n        'gas': 0.0,\n        'hydro': 16093.0,\n        'solar': 0.0,\n        'wind': 211.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 618.0,\n        'gas': 0.0,\n        'hydro': 15415.0,\n        'solar': 0.0,\n        'wind': 209.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 612.0,\n        'gas': 0.0,\n        'hydro': 14289.0,\n        'solar': 0.0,\n        'wind': 199.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 613.0,\n        'gas': 0.0,\n        'hydro': 14093.0,\n        'solar': 0.0,\n        'wind': 157.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 611.0,\n        'hydro': 13974.0,\n        'solar': 0.0,\n        'wind': 92.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 611.0,\n        'hydro': 14545.0,\n        'solar': 0.0,\n        'wind': 100.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 608.0,\n        'hydro': 15028.0,\n        'solar': 0.0,\n        'wind': 113.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 603.0,\n        'hydro': 16175.0,\n        'solar': 0.0,\n        'wind': 106.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montreal')),\n      'production': dict({\n        'biomass': 599.0,\n        'hydro': 18527.0,\n        'solar': 0.0,\n        'wind': 78.0,\n      }),\n      'source': 'hydroquebec.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-QC',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CA_ON.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': 15660.0,\n      'datetime': datetime.datetime(2025, 2, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15660.0,\n      'datetime': datetime.datetime(2025, 2, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15660.0,\n      'datetime': datetime.datetime(2025, 2, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15660.0,\n      'datetime': datetime.datetime(2025, 2, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15660.0,\n      'datetime': datetime.datetime(2025, 2, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15660.0,\n      'datetime': datetime.datetime(2025, 2, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15660.0,\n      'datetime': datetime.datetime(2025, 2, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15660.0,\n      'datetime': datetime.datetime(2025, 2, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15363.0,\n      'datetime': datetime.datetime(2025, 2, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15363.0,\n      'datetime': datetime.datetime(2025, 2, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15363.0,\n      'datetime': datetime.datetime(2025, 2, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15363.0,\n      'datetime': datetime.datetime(2025, 2, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15363.0,\n      'datetime': datetime.datetime(2025, 2, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15363.0,\n      'datetime': datetime.datetime(2025, 2, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15363.0,\n      'datetime': datetime.datetime(2025, 2, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15363.0,\n      'datetime': datetime.datetime(2025, 2, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15280.0,\n      'datetime': datetime.datetime(2025, 2, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15280.0,\n      'datetime': datetime.datetime(2025, 2, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15280.0,\n      'datetime': datetime.datetime(2025, 2, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15280.0,\n      'datetime': datetime.datetime(2025, 2, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15280.0,\n      'datetime': datetime.datetime(2025, 2, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15280.0,\n      'datetime': datetime.datetime(2025, 2, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15280.0,\n      'datetime': datetime.datetime(2025, 2, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15280.0,\n      'datetime': datetime.datetime(2025, 2, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15934.0,\n      'datetime': datetime.datetime(2025, 2, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15934.0,\n      'datetime': datetime.datetime(2025, 2, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15934.0,\n      'datetime': datetime.datetime(2025, 2, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15934.0,\n      'datetime': datetime.datetime(2025, 2, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15934.0,\n      'datetime': datetime.datetime(2025, 2, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15934.0,\n      'datetime': datetime.datetime(2025, 2, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15934.0,\n      'datetime': datetime.datetime(2025, 2, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 15934.0,\n      'datetime': datetime.datetime(2025, 2, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16942.0,\n      'datetime': datetime.datetime(2025, 2, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16942.0,\n      'datetime': datetime.datetime(2025, 2, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16942.0,\n      'datetime': datetime.datetime(2025, 2, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16942.0,\n      'datetime': datetime.datetime(2025, 2, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16942.0,\n      'datetime': datetime.datetime(2025, 2, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16942.0,\n      'datetime': datetime.datetime(2025, 2, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16942.0,\n      'datetime': datetime.datetime(2025, 2, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16942.0,\n      'datetime': datetime.datetime(2025, 2, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18185.0,\n      'datetime': datetime.datetime(2025, 2, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18185.0,\n      'datetime': datetime.datetime(2025, 2, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18185.0,\n      'datetime': datetime.datetime(2025, 2, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18185.0,\n      'datetime': datetime.datetime(2025, 2, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18185.0,\n      'datetime': datetime.datetime(2025, 2, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18185.0,\n      'datetime': datetime.datetime(2025, 2, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18185.0,\n      'datetime': datetime.datetime(2025, 2, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18185.0,\n      'datetime': datetime.datetime(2025, 2, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18770.0,\n      'datetime': datetime.datetime(2025, 2, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18770.0,\n      'datetime': datetime.datetime(2025, 2, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18770.0,\n      'datetime': datetime.datetime(2025, 2, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18770.0,\n      'datetime': datetime.datetime(2025, 2, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18770.0,\n      'datetime': datetime.datetime(2025, 2, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18770.0,\n      'datetime': datetime.datetime(2025, 2, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18770.0,\n      'datetime': datetime.datetime(2025, 2, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18770.0,\n      'datetime': datetime.datetime(2025, 2, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18985.0,\n      'datetime': datetime.datetime(2025, 2, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18985.0,\n      'datetime': datetime.datetime(2025, 2, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18985.0,\n      'datetime': datetime.datetime(2025, 2, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18985.0,\n      'datetime': datetime.datetime(2025, 2, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18985.0,\n      'datetime': datetime.datetime(2025, 2, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18985.0,\n      'datetime': datetime.datetime(2025, 2, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18985.0,\n      'datetime': datetime.datetime(2025, 2, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18985.0,\n      'datetime': datetime.datetime(2025, 2, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18708.0,\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18708.0,\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18708.0,\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18708.0,\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18708.0,\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18708.0,\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18708.0,\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18708.0,\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18450.0,\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18450.0,\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18450.0,\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18450.0,\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18450.0,\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18450.0,\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18450.0,\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18450.0,\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18271.0,\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18271.0,\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18271.0,\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18271.0,\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18271.0,\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18271.0,\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18271.0,\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18271.0,\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18054.0,\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18054.0,\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18054.0,\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18054.0,\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18054.0,\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18054.0,\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18054.0,\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18054.0,\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17917.0,\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17917.0,\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17917.0,\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17917.0,\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17917.0,\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17917.0,\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17917.0,\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17917.0,\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17986.0,\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17986.0,\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17986.0,\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17986.0,\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17986.0,\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17986.0,\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17986.0,\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17986.0,\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18189.0,\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18189.0,\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18189.0,\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18189.0,\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18189.0,\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18189.0,\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18189.0,\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18189.0,\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18729.0,\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18729.0,\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18729.0,\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18729.0,\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18729.0,\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18729.0,\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18729.0,\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18729.0,\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19290.0,\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19440.0,\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19440.0,\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19440.0,\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19440.0,\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19440.0,\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19440.0,\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19440.0,\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19440.0,\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19310.0,\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19310.0,\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19310.0,\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19310.0,\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19310.0,\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19310.0,\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19310.0,\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 19310.0,\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18860.0,\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18860.0,\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18860.0,\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18860.0,\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18860.0,\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18860.0,\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18860.0,\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18860.0,\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 18101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 17101.0,\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16298.0,\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16298.0,\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16298.0,\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16298.0,\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16298.0,\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16298.0,\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16298.0,\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'consumption': 16298.0,\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'CA-ON',\n    }),\n  ])\n# ---\n# name: test_fetch_wind_solar_forecasts\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 4693.6,\n        'wind': 10244.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 5377.6,\n        'wind': 10604.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 5249.6,\n        'wind': 13379.2,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 4906.4,\n        'wind': 16050.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 4701.6,\n        'wind': 29812.0,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 4021.6,\n        'wind': 30736.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 3046.4,\n        'wind': 31907.2,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 1661.6,\n        'wind': 32556.0,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 259.2,\n        'wind': 33255.2,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 1.6,\n        'wind': 32872.0,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 31558.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 31788.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 32656.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 34071.2,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 35463.2,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 36150.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 36074.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 35696.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 35472.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 34880.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 34392.0,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.8,\n        'wind': 33822.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 275.2,\n        'wind': 33194.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 1312.8,\n        'wind': 32457.6,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 2480.8,\n        'wind': 31860.0,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 3272.0,\n        'wind': 30615.2,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 3880.0,\n        'wind': 29368.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 4195.2,\n        'wind': 28253.6,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 4515.2,\n        'wind': 27013.6,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 4399.2,\n        'wind': 25938.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 3707.2,\n        'wind': 24936.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 2155.2,\n        'wind': 23464.0,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 336.0,\n        'wind': 21787.2,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 2.4,\n        'wind': 20144.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 19039.2,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 18060.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 17521.6,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 16314.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 14976.0,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 13607.2,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 12222.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 10761.6,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 9357.6,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 8112.0,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 7108.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 8.0,\n        'wind': 6428.0,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 700.8,\n        'wind': 6066.4,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=68400), 'UTC-5')),\n      'production': dict({\n        'solar': 2576.0,\n        'wind': 6376.8,\n      }),\n      'source': 'ieso.ca',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CA-ON',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CEB.ambr",
    "content": "# serializer version: 1\n# name: test_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 9.582844,\n        'coal': 535.0471,\n        'hydro': 150.607342,\n        'oil': 765.390242,\n        'solar': 2e-06,\n        'wind': 134.589145,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 9.582244,\n        'coal': 534.5295,\n        'hydro': 171.710697,\n        'oil': 728.840836,\n        'solar': 2e-06,\n        'wind': 128.617261,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 9.543541,\n        'coal': 540.2533,\n        'hydro': 162.789886,\n        'oil': 702.058741,\n        'solar': 2e-06,\n        'wind': 140.47863,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 9.444535,\n        'coal': 538.7913,\n        'hydro': 165.110165,\n        'oil': 691.825552,\n        'solar': 2e-06,\n        'wind': 138.62259,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 9.742753,\n        'coal': 540.999,\n        'hydro': 142.31307,\n        'oil': 676.487486,\n        'solar': 2e-06,\n        'wind': 142.72405,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 9.940463,\n        'coal': 542.7344,\n        'hydro': 147.58053,\n        'oil': 658.033851,\n        'solar': 2e-06,\n        'wind': 138.58616,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.24288,\n        'coal': 540.1766,\n        'hydro': 129.697611,\n        'oil': 659.580088,\n        'solar': 2e-06,\n        'wind': 143.72577,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.11927,\n        'coal': 542.1865,\n        'hydro': 134.469001,\n        'oil': 640.447879,\n        'solar': 2e-06,\n        'wind': 142.10192,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.02983,\n        'coal': 542.2016,\n        'hydro': 148.73672,\n        'oil': 615.651953,\n        'solar': 2e-06,\n        'wind': 139.46731,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.49665,\n        'coal': 542.582,\n        'hydro': 148.538581,\n        'oil': 613.88587,\n        'solar': 2e-06,\n        'wind': 139.67993,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.55215,\n        'coal': 540.9233,\n        'hydro': 137.82093,\n        'oil': 610.841411,\n        'solar': 2e-06,\n        'wind': 125.44663,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.26534,\n        'coal': 540.4814,\n        'hydro': 133.58916,\n        'oil': 612.759146,\n        'solar': 2e-06,\n        'wind': 126.40797,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.32924,\n        'coal': 539.6136,\n        'hydro': 134.895424,\n        'oil': 613.627742,\n        'solar': 2e-06,\n        'wind': 130.46761,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.83031,\n        'coal': 541.7597,\n        'hydro': 125.386074,\n        'oil': 618.745405,\n        'solar': 2e-06,\n        'wind': 129.6132,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.74121,\n        'coal': 540.4814,\n        'hydro': 119.951287,\n        'oil': 616.952703,\n        'solar': 2e-06,\n        'wind': 135.51611,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.5969,\n        'coal': 541.1967,\n        'hydro': 110.559727,\n        'oil': 615.691865,\n        'solar': 2e-06,\n        'wind': 137.77664,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.48319,\n        'coal': 541.5014,\n        'hydro': 148.167257,\n        'oil': 597.949263,\n        'solar': 2e-06,\n        'wind': 134.40364,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.70821,\n        'coal': 542.0341,\n        'hydro': 161.474602,\n        'oil': 597.774458,\n        'solar': 2e-06,\n        'wind': 136.66579,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.51315,\n        'coal': 537.1942,\n        'hydro': 158.720622,\n        'oil': 645.110401,\n        'solar': 2e-06,\n        'wind': 135.81862,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.33764,\n        'coal': 538.1072,\n        'hydro': 165.367421,\n        'oil': 677.25684,\n        'solar': 2e-06,\n        'wind': 139.23463,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.17533,\n        'coal': 537.6209,\n        'hydro': 170.757453,\n        'oil': 730.443592,\n        'solar': 2e-06,\n        'wind': 143.28454,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.04993,\n        'coal': 539.9344,\n        'hydro': 210.913157,\n        'oil': 754.623583,\n        'solar': 2e-06,\n        'wind': 139.28339,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.01482,\n        'coal': 541.3036,\n        'hydro': 203.628222,\n        'oil': 811.452284,\n        'solar': 2e-06,\n        'wind': 144.88414,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.51555,\n        'coal': 539.5076,\n        'hydro': 230.163339,\n        'oil': 838.511014,\n        'solar': 2e-06,\n        'wind': 141.4328,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.94218,\n        'coal': 540.9535,\n        'hydro': 301.590314,\n        'oil': 835.359318,\n        'solar': 2e-06,\n        'wind': 142.58908,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.69406,\n        'coal': 538.8377,\n        'hydro': 299.514678,\n        'oil': 843.061429,\n        'solar': 0.878571,\n        'wind': 136.4606,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.62506,\n        'coal': 540.1312,\n        'hydro': 292.589907,\n        'oil': 828.343135,\n        'solar': 3.528812,\n        'wind': 127.58743,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.68836,\n        'coal': 540.892,\n        'hydro': 253.523534,\n        'oil': 812.980259,\n        'solar': 5.860573,\n        'wind': 129.17974,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.63016,\n        'coal': 539.4613,\n        'hydro': 232.379677,\n        'oil': 817.004741,\n        'solar': 8.09683,\n        'wind': 132.70247,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.47685,\n        'coal': 540.7245,\n        'hydro': 228.292833,\n        'oil': 816.933288,\n        'solar': 10.727663,\n        'wind': 137.85714,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.51105,\n        'coal': 540.6942,\n        'hydro': 234.18242,\n        'oil': 816.394335,\n        'solar': 13.521382,\n        'wind': 130.68616,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.22874,\n        'coal': 542.019,\n        'hydro': 230.174056,\n        'oil': 857.215482,\n        'solar': 16.442442,\n        'wind': 124.50251,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.31844,\n        'coal': 540.5267,\n        'hydro': 229.662564,\n        'oil': 899.449738,\n        'solar': 17.120022,\n        'wind': 122.46324,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.662,\n        'coal': 541.9121,\n        'hydro': 268.120847,\n        'oil': 913.087483,\n        'solar': 20.368272,\n        'wind': 118.80545,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.05563,\n        'coal': 538.6844,\n        'hydro': 313.539751,\n        'oil': 923.797965,\n        'solar': 20.530282,\n        'wind': 103.65566,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.01302,\n        'coal': 540.8002,\n        'hydro': 322.198218,\n        'oil': 922.437548,\n        'solar': 24.177932,\n        'wind': 100.78531,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.84052,\n        'coal': 536.8572,\n        'hydro': 339.512661,\n        'oil': 915.576384,\n        'solar': 24.508052,\n        'wind': 99.5733,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.13573,\n        'coal': 537.0398,\n        'hydro': 361.110247,\n        'oil': 907.041742,\n        'solar': 19.616532,\n        'wind': 83.66355,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.12013,\n        'coal': 537.8167,\n        'hydro': 377.338744,\n        'oil': 906.009462,\n        'solar': 24.802832,\n        'wind': 81.47051,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.26894,\n        'coal': 539.5218,\n        'hydro': 359.855618,\n        'oil': 908.082201,\n        'solar': 30.635882,\n        'wind': 70.10661,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.92362,\n        'coal': 539.7196,\n        'hydro': 324.365571,\n        'oil': 906.11764,\n        'solar': 27.371872,\n        'wind': 81.88009,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.6434,\n        'coal': 539.095,\n        'hydro': 352.730646,\n        'oil': 903.434362,\n        'solar': 23.836802,\n        'wind': 78.567862,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.18463,\n        'coal': 540.4349,\n        'hydro': 359.232789,\n        'oil': 905.981298,\n        'solar': 28.250372,\n        'wind': 77.06822,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.35174,\n        'coal': 539.5673,\n        'hydro': 345.214241,\n        'oil': 906.920545,\n        'solar': 32.684812,\n        'wind': 75.635324,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.53986,\n        'coal': 541.12,\n        'hydro': 336.786907,\n        'oil': 907.609991,\n        'solar': 30.529062,\n        'wind': 80.8908,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.14413,\n        'coal': 539.309,\n        'hydro': 342.318375,\n        'oil': 905.629977,\n        'solar': 33.037292,\n        'wind': 84.82274,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.22784,\n        'coal': 541.4549,\n        'hydro': 354.348989,\n        'oil': 906.837514,\n        'solar': 32.846912,\n        'wind': 81.930272,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.75201,\n        'coal': 538.8671,\n        'hydro': 356.484878,\n        'oil': 902.911232,\n        'solar': 32.731602,\n        'wind': 80.171483,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.02833,\n        'coal': 542.4145,\n        'hydro': 354.682195,\n        'oil': 901.533897,\n        'solar': 32.689342,\n        'wind': 73.14363,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.26774,\n        'coal': 542.5669,\n        'hydro': 320.821419,\n        'oil': 907.333088,\n        'solar': 33.169462,\n        'wind': 71.504827,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.22304,\n        'coal': 541.0897,\n        'hydro': 292.780242,\n        'oil': 910.543466,\n        'solar': 32.692042,\n        'wind': 71.991664,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.18493,\n        'coal': 543.6322,\n        'hydro': 284.303162,\n        'oil': 908.19185,\n        'solar': 33.121292,\n        'wind': 81.49898,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.88222,\n        'coal': 541.5469,\n        'hydro': 261.290884,\n        'oil': 905.09753,\n        'solar': 32.127982,\n        'wind': 87.16048,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.00732,\n        'coal': 542.2016,\n        'hydro': 244.713336,\n        'oil': 906.272386,\n        'solar': 31.796412,\n        'wind': 86.6778,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.05023,\n        'coal': 541.4096,\n        'hydro': 268.151825,\n        'oil': 903.788014,\n        'solar': 30.352502,\n        'wind': 87.86155,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.5171,\n        'coal': 542.3994,\n        'hydro': 287.929164,\n        'oil': 903.860548,\n        'solar': 30.053272,\n        'wind': 88.54005,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.81201,\n        'coal': 541.2572,\n        'hydro': 340.997206,\n        'oil': 901.122217,\n        'solar': 29.237682,\n        'wind': 82.03813,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.21764,\n        'coal': 541.0746,\n        'hydro': 354.470214,\n        'oil': 895.853519,\n        'solar': 28.414172,\n        'wind': 79.88274,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.13843,\n        'coal': 542.6577,\n        'hydro': 425.045098,\n        'oil': 892.499065,\n        'solar': 27.101122,\n        'wind': 76.56565,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.99532,\n        'coal': 543.4345,\n        'hydro': 433.849185,\n        'oil': 900.724186,\n        'solar': 25.837382,\n        'wind': 72.88342,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.557,\n        'coal': 543.6475,\n        'hydro': 431.513219,\n        'oil': 904.411042,\n        'solar': 23.852802,\n        'wind': 82.80592,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.68331,\n        'coal': 542.3227,\n        'hydro': 466.497869,\n        'oil': 905.315306,\n        'solar': 20.714762,\n        'wind': 86.96032,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.87652,\n        'coal': 541.2875,\n        'hydro': 502.111428,\n        'oil': 910.445884,\n        'solar': 18.483302,\n        'wind': 93.33382,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.84712,\n        'coal': 540.7548,\n        'hydro': 511.596086,\n        'oil': 916.320194,\n        'solar': 18.160282,\n        'wind': 92.62987,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.30254,\n        'coal': 541.8051,\n        'hydro': 509.582821,\n        'oil': 919.962099,\n        'solar': 16.924032,\n        'wind': 110.85673,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.87802,\n        'coal': 542.8554,\n        'hydro': 545.052842,\n        'oil': 919.320346,\n        'solar': 13.412971,\n        'wind': 99.53248,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.88762,\n        'coal': 538.303,\n        'hydro': 552.453404,\n        'oil': 920.12503,\n        'solar': 9.888518,\n        'wind': 109.11659,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 7.305864,\n        'coal': 539.095,\n        'hydro': 528.459314,\n        'oil': 921.686424,\n        'solar': 7.275113,\n        'wind': 121.85211,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 9.036512,\n        'coal': 539.6429,\n        'hydro': 498.060283,\n        'oil': 923.170547,\n        'solar': 3.640241,\n        'wind': 123.51388,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.95242,\n        'coal': 539.2776,\n        'hydro': 499.204507,\n        'oil': 926.628774,\n        'solar': 2.269467,\n        'wind': 107.75946,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.89627,\n        'coal': 538.3948,\n        'hydro': 490.052211,\n        'oil': 930.347443,\n        'solar': 2e-06,\n        'wind': 112.73453,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.47415,\n        'coal': 539.4755,\n        'hydro': 496.611785,\n        'oil': 929.691716,\n        'solar': 2e-06,\n        'wind': 117.44817,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.80931,\n        'coal': 541.227,\n        'hydro': 510.904633,\n        'oil': 928.410788,\n        'solar': 2e-06,\n        'wind': 119.52368,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.99952,\n        'coal': 542.6273,\n        'hydro': 592.319337,\n        'oil': 928.845776,\n        'solar': 2e-06,\n        'wind': 124.01588,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.90562,\n        'coal': 543.2822,\n        'hydro': 719.306441,\n        'oil': 923.701769,\n        'solar': 2e-06,\n        'wind': 127.77465,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.90292,\n        'coal': 541.9272,\n        'hydro': 733.807339,\n        'oil': 927.380747,\n        'solar': 2e-06,\n        'wind': 128.19678,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.12523,\n        'coal': 543.4648,\n        'hydro': 722.284296,\n        'oil': 929.292427,\n        'solar': 2e-06,\n        'wind': 135.25679,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.51105,\n        'coal': 542.3994,\n        'hydro': 691.337426,\n        'oil': 931.541448,\n        'solar': 2e-06,\n        'wind': 132.80013,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.09703,\n        'coal': 541.8969,\n        'hydro': 648.46002,\n        'oil': 928.493351,\n        'solar': 2e-06,\n        'wind': 132.28857,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.03703,\n        'coal': 543.8301,\n        'hydro': 614.286058,\n        'oil': 927.780083,\n        'solar': 2e-06,\n        'wind': 128.92568,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.75861,\n        'coal': 540.8466,\n        'hydro': 504.014536,\n        'oil': 891.211849,\n        'solar': 2e-06,\n        'wind': 135.84487,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.71571,\n        'coal': 541.5771,\n        'hydro': 471.59087,\n        'oil': 898.348726,\n        'solar': 2e-06,\n        'wind': 133.03643,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.78921,\n        'coal': 542.3076,\n        'hydro': 519.8143,\n        'oil': 904.294998,\n        'solar': 2e-06,\n        'wind': 136.50999,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.49455,\n        'coal': 543.6475,\n        'hydro': 490.524941,\n        'oil': 924.713995,\n        'solar': 2e-06,\n        'wind': 128.78328,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.54045,\n        'coal': 542.7495,\n        'hydro': 445.257912,\n        'oil': 925.547073,\n        'solar': 2e-06,\n        'wind': 132.36975,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.93472,\n        'coal': 542.7344,\n        'hydro': 391.89864,\n        'oil': 922.172548,\n        'solar': 2e-06,\n        'wind': 134.21474,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.02293,\n        'coal': 542.917,\n        'hydro': 356.146721,\n        'oil': 895.795417,\n        'solar': 2e-06,\n        'wind': 138.08055,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.72171,\n        'coal': 542.2621,\n        'hydro': 344.77222,\n        'oil': 885.219942,\n        'solar': 2e-06,\n        'wind': 134.91349,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.5537,\n        'coal': 543.4648,\n        'hydro': 340.704864,\n        'oil': 817.388811,\n        'solar': 2e-06,\n        'wind': 139.09804,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.16753,\n        'coal': 542.9623,\n        'hydro': 324.444867,\n        'oil': 800.990745,\n        'solar': 2e-06,\n        'wind': 137.1403,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.94912,\n        'coal': 541.2421,\n        'hydro': 287.719558,\n        'oil': 800.713582,\n        'solar': 2e-06,\n        'wind': 140.37154,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.509,\n        'coal': 541.7748,\n        'hydro': 252.236844,\n        'oil': 801.573871,\n        'solar': 2e-06,\n        'wind': 143.09553,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 9.970466,\n        'coal': 545.4434,\n        'hydro': 218.219477,\n        'oil': 782.126903,\n        'solar': 2e-06,\n        'wind': 141.17221,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 10.36919,\n        'coal': 542.6577,\n        'hydro': 215.185927,\n        'oil': 765.745818,\n        'solar': 2e-06,\n        'wind': 143.44182,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 8, 23, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Colombo')),\n      'production': dict({\n        'biomass': 11.19843,\n        'coal': 542.2319,\n        'hydro': 188.997677,\n        'oil': 736.417345,\n        'solar': 2e-06,\n        'wind': 143.09574,\n      }),\n      'source': 'ceb.lk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LK',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CL.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_historical_data\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 53.14,\n        'hydro': 2700.906657,\n        'solar': 100.000032,\n        'unknown': 5268.170499,\n        'wind': 1280.780885,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 53.26,\n        'hydro': 2462.475625,\n        'solar': 81.105925,\n        'unknown': 5170.743269,\n        'wind': 1189.91521,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 53.79,\n        'hydro': 2379.239039,\n        'solar': 8.300033,\n        'unknown': 5117.478787,\n        'wind': 1117.397269,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 54.38,\n        'hydro': 2354.243241,\n        'solar': 59.902852,\n        'unknown': 5094.783766,\n        'wind': 1090.907371,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 53.56,\n        'hydro': 2283.744427,\n        'solar': 120.724776,\n        'unknown': 5087.732329,\n        'wind': 1084.973849,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 53.56,\n        'hydro': 2303.131467,\n        'solar': 122.795107,\n        'unknown': 5009.660575,\n        'wind': 1155.499893,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 54.17,\n        'hydro': 2410.308194,\n        'solar': 125.61644,\n        'unknown': 5045.755455,\n        'wind': 1224.985927,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 54.96,\n        'hydro': 2631.740156,\n        'solar': 245.078277,\n        'unknown': 4924.854536,\n        'wind': 1302.988293,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 54.56,\n        'hydro': 2611.38258,\n        'solar': 2278.50336,\n        'unknown': 3316.625734,\n        'wind': 1288.618092,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 52.9,\n        'hydro': 2576.73036,\n        'solar': 4210.016137,\n        'unknown': 2046.03737,\n        'wind': 1075.449985,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 52.15,\n        'hydro': 2319.68927,\n        'solar': 5132.126592,\n        'unknown': 1755.337808,\n        'wind': 974.676364,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 49.11,\n        'hydro': 2234.245319,\n        'solar': 5484.558118,\n        'unknown': 1696.242462,\n        'wind': 932.930836,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 48.82,\n        'hydro': 2172.62459,\n        'solar': 5671.553406,\n        'unknown': 1678.230359,\n        'wind': 931.12142,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 49.19,\n        'hydro': 2144.243675,\n        'solar': 5578.896809,\n        'unknown': 1736.036832,\n        'wind': 1099.386722,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 46.03,\n        'hydro': 2263.655016,\n        'solar': 5422.101832,\n        'unknown': 1778.553306,\n        'wind': 1230.231538,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 42.12,\n        'hydro': 2246.264277,\n        'solar': 5389.586746,\n        'unknown': 1751.539326,\n        'wind': 1361.218869,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 42.29,\n        'hydro': 2129.363594,\n        'solar': 5202.744165,\n        'unknown': 1878.335343,\n        'wind': 1421.011156,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 43.37,\n        'hydro': 2269.306443,\n        'solar': 4613.716848,\n        'unknown': 2089.748741,\n        'wind': 1461.531899,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 42.92,\n        'hydro': 2130.077228,\n        'solar': 4030.796152,\n        'unknown': 2880.643438,\n        'wind': 1285.360625,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 49.96,\n        'hydro': 2679.453131,\n        'solar': 1850.659698,\n        'unknown': 4302.627242,\n        'wind': 1485.318669,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 52.22,\n        'hydro': 3204.530755,\n        'solar': 238.576226,\n        'unknown': 5535.749833,\n        'wind': 1607.077091,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 53.13,\n        'hydro': 3339.080773,\n        'solar': 183.033445,\n        'unknown': 5590.121261,\n        'wind': 1596.874509,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 53.31,\n        'hydro': 3397.70348,\n        'solar': 126.82,\n        'unknown': 5451.267958,\n        'wind': 1475.910419,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 23, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 54.39,\n        'hydro': 3050.825042,\n        'solar': 124.8,\n        'unknown': 5427.384926,\n        'wind': 1468.875217,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 55.44,\n        'hydro': 2921.135053,\n        'solar': 97.9,\n        'unknown': 5242.05276,\n        'wind': 1394.006656,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 54.72,\n        'hydro': 2873.639079,\n        'solar': 12.0,\n        'unknown': 5092.276621,\n        'wind': 1278.197109,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 45.19,\n        'hydro': 2779.006138,\n        'solar': 3.3e-05,\n        'unknown': 5017.079483,\n        'wind': 1255.251476,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 36.36,\n        'hydro': 2535.719159,\n        'solar': 0.002682,\n        'unknown': 5161.346538,\n        'wind': 1216.978644,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 50.56,\n        'hydro': 2455.683144,\n        'solar': 0.666425,\n        'unknown': 5156.500387,\n        'wind': 1190.1354,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 50.6,\n        'hydro': 2344.02243,\n        'solar': 2.78778,\n        'unknown': 5173.181655,\n        'wind': 1265.949049,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 49.93,\n        'hydro': 2436.928362,\n        'solar': 4.671609,\n        'unknown': 5066.064531,\n        'wind': 1340.589791,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 50.17,\n        'hydro': 2612.45783,\n        'solar': 128.868019,\n        'unknown': 4821.509308,\n        'wind': 1252.866856,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 49.77,\n        'hydro': 2416.600953,\n        'solar': 2229.983225,\n        'unknown': 3304.393787,\n        'wind': 980.684729,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 48.89,\n        'hydro': 2422.68662,\n        'solar': 4072.759647,\n        'unknown': 2101.012526,\n        'wind': 738.109111,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 50.32,\n        'hydro': 2125.226312,\n        'solar': 4940.913316,\n        'unknown': 1942.611623,\n        'wind': 586.726374,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 47.35,\n        'hydro': 2150.054145,\n        'solar': 5228.110012,\n        'unknown': 1821.132904,\n        'wind': 572.901276,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 45.0,\n        'hydro': 2085.775046,\n        'solar': 5508.17195,\n        'unknown': 1796.212359,\n        'wind': 473.008079,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 43.41,\n        'hydro': 2192.233165,\n        'solar': 5395.869378,\n        'unknown': 1908.469311,\n        'wind': 472.354431,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 24, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Chile/Continental')),\n      'production': dict({\n        'geothermal': 43.09,\n        'hydro': 2270.685839,\n        'solar': 5182.93405,\n        'unknown': 1935.465852,\n        'wind': 649.912391,\n      }),\n      'source': 'coordinador.cl',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CL-SEN',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CNDC.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_generation_forecast\n  list([\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1199.23,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1141.49,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1108.31,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1088.02,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1118.32,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1080.45,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1228.59,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1292.94,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1399.9,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1454.64,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1485.06,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1499.31,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1488.93,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1547.23,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1590.45,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1572.62,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1516.26,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1442.56,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1571.34,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1627.02,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1599.87,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1525.8,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1411.17,\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 1294.64,\n      'zoneKey': 'BO',\n    }),\n  ])\n# ---\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 733.676,\n        'hydro': 384.86,\n        'oil': 11.074,\n        'solar': 0,\n        'unknown': None,\n        'wind': 45.39,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 686.045,\n        'hydro': 402.78,\n        'oil': 10.355,\n        'solar': 0,\n        'unknown': None,\n        'wind': 47.16,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 651.565,\n        'hydro': 406.37,\n        'oil': 9.835,\n        'solar': 0,\n        'unknown': None,\n        'wind': 48.76,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 652.905,\n        'hydro': 380.18,\n        'oil': 9.855,\n        'solar': 0,\n        'unknown': None,\n        'wind': 47.33,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 651.319,\n        'hydro': 379.26,\n        'oil': 9.831,\n        'solar': 0,\n        'unknown': None,\n        'wind': 51.32,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 637.872,\n        'hydro': 350.42,\n        'oil': 9.628,\n        'solar': 0.39,\n        'unknown': None,\n        'wind': 50.26,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 660.412,\n        'hydro': 422.66,\n        'oil': 9.968,\n        'solar': 13.45,\n        'unknown': None,\n        'wind': 41.49,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 706.624,\n        'hydro': 500.35,\n        'oil': 10.666,\n        'solar': 47.85,\n        'unknown': None,\n        'wind': 45.95,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 758.264,\n        'hydro': 505.62,\n        'oil': 11.446,\n        'solar': 90.01,\n        'unknown': None,\n        'wind': 46.62,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 832.553,\n        'hydro': 523.88,\n        'oil': 12.567,\n        'solar': 113.07,\n        'unknown': None,\n        'wind': 32.52,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/La_Paz')),\n      'production': dict({\n        'biomass': 0,\n        'gas': 907.295,\n        'hydro': 511.72,\n        'oil': 13.695,\n        'solar': 124.97,\n        'unknown': None,\n        'wind': 24.76,\n      }),\n      'source': 'cndc.bo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BO',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CO.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption_dt\n  list([\n    dict({\n      'consumption': 8847.44789,\n      'datetime': datetime.datetime(2024, 12, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8574.9738,\n      'datetime': datetime.datetime(2024, 12, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8345.37466,\n      'datetime': datetime.datetime(2024, 12, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8160.00821,\n      'datetime': datetime.datetime(2024, 12, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8052.39207,\n      'datetime': datetime.datetime(2024, 12, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7911.88003,\n      'datetime': datetime.datetime(2024, 12, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7759.65182,\n      'datetime': datetime.datetime(2024, 12, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8001.06547,\n      'datetime': datetime.datetime(2024, 12, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8320.20935,\n      'datetime': datetime.datetime(2024, 12, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8635.62421,\n      'datetime': datetime.datetime(2024, 12, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8956.34954,\n      'datetime': datetime.datetime(2024, 12, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9206.50346,\n      'datetime': datetime.datetime(2024, 12, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9332.43283,\n      'datetime': datetime.datetime(2024, 12, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9358.45829,\n      'datetime': datetime.datetime(2024, 12, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9301.74154,\n      'datetime': datetime.datetime(2024, 12, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9251.21398,\n      'datetime': datetime.datetime(2024, 12, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9259.54144,\n      'datetime': datetime.datetime(2024, 12, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9510.84649,\n      'datetime': datetime.datetime(2024, 12, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10174.55843,\n      'datetime': datetime.datetime(2024, 12, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10267.98496,\n      'datetime': datetime.datetime(2024, 12, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10154.35033,\n      'datetime': datetime.datetime(2024, 12, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9916.71921,\n      'datetime': datetime.datetime(2024, 12, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9528.87819,\n      'datetime': datetime.datetime(2024, 12, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9090.83953,\n      'datetime': datetime.datetime(2024, 12, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8672.86633,\n      'datetime': datetime.datetime(2024, 12, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8391.70261,\n      'datetime': datetime.datetime(2024, 12, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8205.18684,\n      'datetime': datetime.datetime(2024, 12, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8144.91254,\n      'datetime': datetime.datetime(2024, 12, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8274.33985,\n      'datetime': datetime.datetime(2024, 12, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8478.87171,\n      'datetime': datetime.datetime(2024, 12, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8765.48871,\n      'datetime': datetime.datetime(2024, 12, 2, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9362.01937,\n      'datetime': datetime.datetime(2024, 12, 2, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9919.53145,\n      'datetime': datetime.datetime(2024, 12, 2, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10228.10275,\n      'datetime': datetime.datetime(2024, 12, 2, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10520.78045,\n      'datetime': datetime.datetime(2024, 12, 2, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10948.00087,\n      'datetime': datetime.datetime(2024, 12, 2, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10896.70909,\n      'datetime': datetime.datetime(2024, 12, 2, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10900.35392,\n      'datetime': datetime.datetime(2024, 12, 2, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11012.8799,\n      'datetime': datetime.datetime(2024, 12, 2, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11039.81329,\n      'datetime': datetime.datetime(2024, 12, 2, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10879.19786,\n      'datetime': datetime.datetime(2024, 12, 2, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10845.02678,\n      'datetime': datetime.datetime(2024, 12, 2, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11328.76129,\n      'datetime': datetime.datetime(2024, 12, 2, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11303.58921,\n      'datetime': datetime.datetime(2024, 12, 2, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11082.89859,\n      'datetime': datetime.datetime(2024, 12, 2, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10662.72724,\n      'datetime': datetime.datetime(2024, 12, 2, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10114.43688,\n      'datetime': datetime.datetime(2024, 12, 2, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9543.77802,\n      'datetime': datetime.datetime(2024, 12, 2, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9027.65662,\n      'datetime': datetime.datetime(2024, 12, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8674.03525,\n      'datetime': datetime.datetime(2024, 12, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8439.00812,\n      'datetime': datetime.datetime(2024, 12, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8372.67089,\n      'datetime': datetime.datetime(2024, 12, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8488.70415,\n      'datetime': datetime.datetime(2024, 12, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8731.01269,\n      'datetime': datetime.datetime(2024, 12, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8973.88818,\n      'datetime': datetime.datetime(2024, 12, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9561.83249,\n      'datetime': datetime.datetime(2024, 12, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9948.58626,\n      'datetime': datetime.datetime(2024, 12, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10218.16423,\n      'datetime': datetime.datetime(2024, 12, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10587.94621,\n      'datetime': datetime.datetime(2024, 12, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10918.26775,\n      'datetime': datetime.datetime(2024, 12, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10896.77162,\n      'datetime': datetime.datetime(2024, 12, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10925.98035,\n      'datetime': datetime.datetime(2024, 12, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11162.37119,\n      'datetime': datetime.datetime(2024, 12, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11204.00793,\n      'datetime': datetime.datetime(2024, 12, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11011.83147,\n      'datetime': datetime.datetime(2024, 12, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10990.25295,\n      'datetime': datetime.datetime(2024, 12, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11422.00824,\n      'datetime': datetime.datetime(2024, 12, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11393.53753,\n      'datetime': datetime.datetime(2024, 12, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11151.27649,\n      'datetime': datetime.datetime(2024, 12, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10709.00634,\n      'datetime': datetime.datetime(2024, 12, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10101.88938,\n      'datetime': datetime.datetime(2024, 12, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9553.33936,\n      'datetime': datetime.datetime(2024, 12, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9061.76799,\n      'datetime': datetime.datetime(2024, 12, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8762.87756,\n      'datetime': datetime.datetime(2024, 12, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8533.72813,\n      'datetime': datetime.datetime(2024, 12, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8444.46563,\n      'datetime': datetime.datetime(2024, 12, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8586.80726,\n      'datetime': datetime.datetime(2024, 12, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8795.65879,\n      'datetime': datetime.datetime(2024, 12, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9066.97268,\n      'datetime': datetime.datetime(2024, 12, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9622.29547,\n      'datetime': datetime.datetime(2024, 12, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10063.94425,\n      'datetime': datetime.datetime(2024, 12, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10303.89345,\n      'datetime': datetime.datetime(2024, 12, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10669.54251,\n      'datetime': datetime.datetime(2024, 12, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10919.14754,\n      'datetime': datetime.datetime(2024, 12, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10859.28418,\n      'datetime': datetime.datetime(2024, 12, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10921.29645,\n      'datetime': datetime.datetime(2024, 12, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11182.16479,\n      'datetime': datetime.datetime(2024, 12, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11189.68082,\n      'datetime': datetime.datetime(2024, 12, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11148.53966,\n      'datetime': datetime.datetime(2024, 12, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11095.48427,\n      'datetime': datetime.datetime(2024, 12, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11538.14159,\n      'datetime': datetime.datetime(2024, 12, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11494.74593,\n      'datetime': datetime.datetime(2024, 12, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11212.65304,\n      'datetime': datetime.datetime(2024, 12, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10752.83402,\n      'datetime': datetime.datetime(2024, 12, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10164.87185,\n      'datetime': datetime.datetime(2024, 12, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9599.51095,\n      'datetime': datetime.datetime(2024, 12, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9091.36093,\n      'datetime': datetime.datetime(2024, 12, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8851.78906,\n      'datetime': datetime.datetime(2024, 12, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8639.12332,\n      'datetime': datetime.datetime(2024, 12, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8517.76912,\n      'datetime': datetime.datetime(2024, 12, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8629.88935,\n      'datetime': datetime.datetime(2024, 12, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8788.89258,\n      'datetime': datetime.datetime(2024, 12, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9046.80315,\n      'datetime': datetime.datetime(2024, 12, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9523.45105,\n      'datetime': datetime.datetime(2024, 12, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9941.0828,\n      'datetime': datetime.datetime(2024, 12, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10211.75518,\n      'datetime': datetime.datetime(2024, 12, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10573.29777,\n      'datetime': datetime.datetime(2024, 12, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10896.16838,\n      'datetime': datetime.datetime(2024, 12, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10865.48121,\n      'datetime': datetime.datetime(2024, 12, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10945.68077,\n      'datetime': datetime.datetime(2024, 12, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11172.44299,\n      'datetime': datetime.datetime(2024, 12, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11265.21099,\n      'datetime': datetime.datetime(2024, 12, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11143.25725,\n      'datetime': datetime.datetime(2024, 12, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11031.5852,\n      'datetime': datetime.datetime(2024, 12, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11575.91111,\n      'datetime': datetime.datetime(2024, 12, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11577.19113,\n      'datetime': datetime.datetime(2024, 12, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11289.64,\n      'datetime': datetime.datetime(2024, 12, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10824.35502,\n      'datetime': datetime.datetime(2024, 12, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10260.93467,\n      'datetime': datetime.datetime(2024, 12, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9698.22995,\n      'datetime': datetime.datetime(2024, 12, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9207.67035,\n      'datetime': datetime.datetime(2024, 12, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8850.38651,\n      'datetime': datetime.datetime(2024, 12, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8628.64143,\n      'datetime': datetime.datetime(2024, 12, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8524.3642,\n      'datetime': datetime.datetime(2024, 12, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8618.39954,\n      'datetime': datetime.datetime(2024, 12, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8843.39542,\n      'datetime': datetime.datetime(2024, 12, 6, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9094.44635,\n      'datetime': datetime.datetime(2024, 12, 6, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9651.47651,\n      'datetime': datetime.datetime(2024, 12, 6, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10117.45062,\n      'datetime': datetime.datetime(2024, 12, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10381.59754,\n      'datetime': datetime.datetime(2024, 12, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10608.0466,\n      'datetime': datetime.datetime(2024, 12, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10892.63989,\n      'datetime': datetime.datetime(2024, 12, 6, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10843.65955,\n      'datetime': datetime.datetime(2024, 12, 6, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10877.92079,\n      'datetime': datetime.datetime(2024, 12, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11063.97967,\n      'datetime': datetime.datetime(2024, 12, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11102.62533,\n      'datetime': datetime.datetime(2024, 12, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10898.06339,\n      'datetime': datetime.datetime(2024, 12, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10841.2598,\n      'datetime': datetime.datetime(2024, 12, 6, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11277.72683,\n      'datetime': datetime.datetime(2024, 12, 6, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11229.54756,\n      'datetime': datetime.datetime(2024, 12, 6, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10962.87577,\n      'datetime': datetime.datetime(2024, 12, 6, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10513.93104,\n      'datetime': datetime.datetime(2024, 12, 6, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10055.82528,\n      'datetime': datetime.datetime(2024, 12, 6, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9508.34171,\n      'datetime': datetime.datetime(2024, 12, 6, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9107.17689,\n      'datetime': datetime.datetime(2024, 12, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8796.5501,\n      'datetime': datetime.datetime(2024, 12, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8525.38836,\n      'datetime': datetime.datetime(2024, 12, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8411.45742,\n      'datetime': datetime.datetime(2024, 12, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8411.2833,\n      'datetime': datetime.datetime(2024, 12, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8460.26586,\n      'datetime': datetime.datetime(2024, 12, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8587.29686,\n      'datetime': datetime.datetime(2024, 12, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9111.50082,\n      'datetime': datetime.datetime(2024, 12, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9588.98716,\n      'datetime': datetime.datetime(2024, 12, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9838.71925,\n      'datetime': datetime.datetime(2024, 12, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10121.14673,\n      'datetime': datetime.datetime(2024, 12, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10231.94185,\n      'datetime': datetime.datetime(2024, 12, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10157.93757,\n      'datetime': datetime.datetime(2024, 12, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10122.3548,\n      'datetime': datetime.datetime(2024, 12, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10128.47638,\n      'datetime': datetime.datetime(2024, 12, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10067.48397,\n      'datetime': datetime.datetime(2024, 12, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10010.37975,\n      'datetime': datetime.datetime(2024, 12, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10065.13603,\n      'datetime': datetime.datetime(2024, 12, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10627.45777,\n      'datetime': datetime.datetime(2024, 12, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10323.49337,\n      'datetime': datetime.datetime(2024, 12, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9852.83455,\n      'datetime': datetime.datetime(2024, 12, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9480.72452,\n      'datetime': datetime.datetime(2024, 12, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9129.34559,\n      'datetime': datetime.datetime(2024, 12, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8830.15704,\n      'datetime': datetime.datetime(2024, 12, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8390.90156,\n      'datetime': datetime.datetime(2024, 12, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8146.35258,\n      'datetime': datetime.datetime(2024, 12, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8014.58434,\n      'datetime': datetime.datetime(2024, 12, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7752.17866,\n      'datetime': datetime.datetime(2024, 12, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7782.90289,\n      'datetime': datetime.datetime(2024, 12, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7655.36967,\n      'datetime': datetime.datetime(2024, 12, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7503.33934,\n      'datetime': datetime.datetime(2024, 12, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7794.28285,\n      'datetime': datetime.datetime(2024, 12, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8125.37485,\n      'datetime': datetime.datetime(2024, 12, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8422.99186,\n      'datetime': datetime.datetime(2024, 12, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8719.15635,\n      'datetime': datetime.datetime(2024, 12, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8989.30617,\n      'datetime': datetime.datetime(2024, 12, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9157.18608,\n      'datetime': datetime.datetime(2024, 12, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9182.54675,\n      'datetime': datetime.datetime(2024, 12, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9146.2518,\n      'datetime': datetime.datetime(2024, 12, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9162.52305,\n      'datetime': datetime.datetime(2024, 12, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9097.49832,\n      'datetime': datetime.datetime(2024, 12, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9182.7474,\n      'datetime': datetime.datetime(2024, 12, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9940.18055,\n      'datetime': datetime.datetime(2024, 12, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10027.42061,\n      'datetime': datetime.datetime(2024, 12, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9878.43249,\n      'datetime': datetime.datetime(2024, 12, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9582.69423,\n      'datetime': datetime.datetime(2024, 12, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9269.65446,\n      'datetime': datetime.datetime(2024, 12, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8881.4088,\n      'datetime': datetime.datetime(2024, 12, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8435.83293,\n      'datetime': datetime.datetime(2024, 12, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8036.52434,\n      'datetime': datetime.datetime(2024, 12, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7789.92693,\n      'datetime': datetime.datetime(2024, 12, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7670.95395,\n      'datetime': datetime.datetime(2024, 12, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7804.19149,\n      'datetime': datetime.datetime(2024, 12, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8098.76668,\n      'datetime': datetime.datetime(2024, 12, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8432.8647,\n      'datetime': datetime.datetime(2024, 12, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9186.34663,\n      'datetime': datetime.datetime(2024, 12, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9811.64714,\n      'datetime': datetime.datetime(2024, 12, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10106.98987,\n      'datetime': datetime.datetime(2024, 12, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10415.73318,\n      'datetime': datetime.datetime(2024, 12, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10688.37984,\n      'datetime': datetime.datetime(2024, 12, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10719.96928,\n      'datetime': datetime.datetime(2024, 12, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10896.22293,\n      'datetime': datetime.datetime(2024, 12, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11110.33066,\n      'datetime': datetime.datetime(2024, 12, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11122.25374,\n      'datetime': datetime.datetime(2024, 12, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11007.59504,\n      'datetime': datetime.datetime(2024, 12, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10822.66467,\n      'datetime': datetime.datetime(2024, 12, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11403.32266,\n      'datetime': datetime.datetime(2024, 12, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11387.52818,\n      'datetime': datetime.datetime(2024, 12, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11171.32174,\n      'datetime': datetime.datetime(2024, 12, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10747.52597,\n      'datetime': datetime.datetime(2024, 12, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10126.01374,\n      'datetime': datetime.datetime(2024, 12, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9591.56769,\n      'datetime': datetime.datetime(2024, 12, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9118.49842,\n      'datetime': datetime.datetime(2024, 12, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8830.75878,\n      'datetime': datetime.datetime(2024, 12, 10, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8593.32086,\n      'datetime': datetime.datetime(2024, 12, 10, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8449.26362,\n      'datetime': datetime.datetime(2024, 12, 10, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8544.30461,\n      'datetime': datetime.datetime(2024, 12, 10, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8786.96411,\n      'datetime': datetime.datetime(2024, 12, 10, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9050.57577,\n      'datetime': datetime.datetime(2024, 12, 10, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9601.96089,\n      'datetime': datetime.datetime(2024, 12, 10, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10139.52247,\n      'datetime': datetime.datetime(2024, 12, 10, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10431.81995,\n      'datetime': datetime.datetime(2024, 12, 10, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10714.41067,\n      'datetime': datetime.datetime(2024, 12, 10, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10976.96094,\n      'datetime': datetime.datetime(2024, 12, 10, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10964.78112,\n      'datetime': datetime.datetime(2024, 12, 10, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11110.6347,\n      'datetime': datetime.datetime(2024, 12, 10, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11332.38824,\n      'datetime': datetime.datetime(2024, 12, 10, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11401.11077,\n      'datetime': datetime.datetime(2024, 12, 10, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11254.838,\n      'datetime': datetime.datetime(2024, 12, 10, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11076.73384,\n      'datetime': datetime.datetime(2024, 12, 10, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11570.93174,\n      'datetime': datetime.datetime(2024, 12, 10, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11505.13865,\n      'datetime': datetime.datetime(2024, 12, 10, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11222.97358,\n      'datetime': datetime.datetime(2024, 12, 10, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10800.49697,\n      'datetime': datetime.datetime(2024, 12, 10, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10171.63465,\n      'datetime': datetime.datetime(2024, 12, 10, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9441.70319,\n      'datetime': datetime.datetime(2024, 12, 10, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8959.07139,\n      'datetime': datetime.datetime(2024, 12, 11, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8674.80153,\n      'datetime': datetime.datetime(2024, 12, 11, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8344.83141,\n      'datetime': datetime.datetime(2024, 12, 11, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8233.30198,\n      'datetime': datetime.datetime(2024, 12, 11, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8296.62771,\n      'datetime': datetime.datetime(2024, 12, 11, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8707.91858,\n      'datetime': datetime.datetime(2024, 12, 11, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8938.07921,\n      'datetime': datetime.datetime(2024, 12, 11, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9485.54646,\n      'datetime': datetime.datetime(2024, 12, 11, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9929.77879,\n      'datetime': datetime.datetime(2024, 12, 11, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10214.50329,\n      'datetime': datetime.datetime(2024, 12, 11, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10575.05872,\n      'datetime': datetime.datetime(2024, 12, 11, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10935.5348,\n      'datetime': datetime.datetime(2024, 12, 11, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10933.24519,\n      'datetime': datetime.datetime(2024, 12, 11, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11036.94932,\n      'datetime': datetime.datetime(2024, 12, 11, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11349.79215,\n      'datetime': datetime.datetime(2024, 12, 11, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11321.43083,\n      'datetime': datetime.datetime(2024, 12, 11, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11186.1644,\n      'datetime': datetime.datetime(2024, 12, 11, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11071.10947,\n      'datetime': datetime.datetime(2024, 12, 11, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11543.03594,\n      'datetime': datetime.datetime(2024, 12, 11, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11514.88406,\n      'datetime': datetime.datetime(2024, 12, 11, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11276.89553,\n      'datetime': datetime.datetime(2024, 12, 11, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10881.32793,\n      'datetime': datetime.datetime(2024, 12, 11, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10321.85854,\n      'datetime': datetime.datetime(2024, 12, 11, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9766.84497,\n      'datetime': datetime.datetime(2024, 12, 11, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9081.39444,\n      'datetime': datetime.datetime(2024, 12, 12, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8795.22004,\n      'datetime': datetime.datetime(2024, 12, 12, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8457.58722,\n      'datetime': datetime.datetime(2024, 12, 12, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8161.55726,\n      'datetime': datetime.datetime(2024, 12, 12, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8667.8595,\n      'datetime': datetime.datetime(2024, 12, 12, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8893.14572,\n      'datetime': datetime.datetime(2024, 12, 12, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9132.98046,\n      'datetime': datetime.datetime(2024, 12, 12, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9669.82415,\n      'datetime': datetime.datetime(2024, 12, 12, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10011.6817,\n      'datetime': datetime.datetime(2024, 12, 12, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10335.72721,\n      'datetime': datetime.datetime(2024, 12, 12, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10701.21322,\n      'datetime': datetime.datetime(2024, 12, 12, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11021.74566,\n      'datetime': datetime.datetime(2024, 12, 12, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11004.45308,\n      'datetime': datetime.datetime(2024, 12, 12, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11117.40731,\n      'datetime': datetime.datetime(2024, 12, 12, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11323.52154,\n      'datetime': datetime.datetime(2024, 12, 12, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11339.24632,\n      'datetime': datetime.datetime(2024, 12, 12, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11131.35846,\n      'datetime': datetime.datetime(2024, 12, 12, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11023.79432,\n      'datetime': datetime.datetime(2024, 12, 12, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11496.37917,\n      'datetime': datetime.datetime(2024, 12, 12, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11465.05095,\n      'datetime': datetime.datetime(2024, 12, 12, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11178.40152,\n      'datetime': datetime.datetime(2024, 12, 12, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10718.66419,\n      'datetime': datetime.datetime(2024, 12, 12, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10162.80391,\n      'datetime': datetime.datetime(2024, 12, 12, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9621.92927,\n      'datetime': datetime.datetime(2024, 12, 12, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9175.01143,\n      'datetime': datetime.datetime(2024, 12, 13, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8846.66451,\n      'datetime': datetime.datetime(2024, 12, 13, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8631.28658,\n      'datetime': datetime.datetime(2024, 12, 13, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8526.25918,\n      'datetime': datetime.datetime(2024, 12, 13, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8617.33328,\n      'datetime': datetime.datetime(2024, 12, 13, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8815.43851,\n      'datetime': datetime.datetime(2024, 12, 13, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9026.99774,\n      'datetime': datetime.datetime(2024, 12, 13, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9602.86389,\n      'datetime': datetime.datetime(2024, 12, 13, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10075.00826,\n      'datetime': datetime.datetime(2024, 12, 13, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10362.4016,\n      'datetime': datetime.datetime(2024, 12, 13, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10664.23583,\n      'datetime': datetime.datetime(2024, 12, 13, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10949.67873,\n      'datetime': datetime.datetime(2024, 12, 13, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10865.81105,\n      'datetime': datetime.datetime(2024, 12, 13, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10952.33517,\n      'datetime': datetime.datetime(2024, 12, 13, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11156.67627,\n      'datetime': datetime.datetime(2024, 12, 13, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11140.37985,\n      'datetime': datetime.datetime(2024, 12, 13, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10930.5821,\n      'datetime': datetime.datetime(2024, 12, 13, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10805.7824,\n      'datetime': datetime.datetime(2024, 12, 13, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11302.97851,\n      'datetime': datetime.datetime(2024, 12, 13, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11257.54948,\n      'datetime': datetime.datetime(2024, 12, 13, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11001.13237,\n      'datetime': datetime.datetime(2024, 12, 13, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10561.95698,\n      'datetime': datetime.datetime(2024, 12, 13, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9996.70901,\n      'datetime': datetime.datetime(2024, 12, 13, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9533.81053,\n      'datetime': datetime.datetime(2024, 12, 13, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9077.64432,\n      'datetime': datetime.datetime(2024, 12, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8777.05784,\n      'datetime': datetime.datetime(2024, 12, 14, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8512.67306,\n      'datetime': datetime.datetime(2024, 12, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8348.38641,\n      'datetime': datetime.datetime(2024, 12, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8371.32604,\n      'datetime': datetime.datetime(2024, 12, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8025.62173,\n      'datetime': datetime.datetime(2024, 12, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8127.88949,\n      'datetime': datetime.datetime(2024, 12, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8590.83736,\n      'datetime': datetime.datetime(2024, 12, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9090.54144,\n      'datetime': datetime.datetime(2024, 12, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9400.94645,\n      'datetime': datetime.datetime(2024, 12, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9677.72841,\n      'datetime': datetime.datetime(2024, 12, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9810.5647,\n      'datetime': datetime.datetime(2024, 12, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9757.49714,\n      'datetime': datetime.datetime(2024, 12, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9726.46979,\n      'datetime': datetime.datetime(2024, 12, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9688.87811,\n      'datetime': datetime.datetime(2024, 12, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9644.04183,\n      'datetime': datetime.datetime(2024, 12, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9534.54844,\n      'datetime': datetime.datetime(2024, 12, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9657.58878,\n      'datetime': datetime.datetime(2024, 12, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10528.38067,\n      'datetime': datetime.datetime(2024, 12, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10616.24085,\n      'datetime': datetime.datetime(2024, 12, 14, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10333.3277,\n      'datetime': datetime.datetime(2024, 12, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9988.13742,\n      'datetime': datetime.datetime(2024, 12, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9553.86372,\n      'datetime': datetime.datetime(2024, 12, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9119.4342,\n      'datetime': datetime.datetime(2024, 12, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8766.49342,\n      'datetime': datetime.datetime(2024, 12, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8447.26465,\n      'datetime': datetime.datetime(2024, 12, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8180.35872,\n      'datetime': datetime.datetime(2024, 12, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8067.21465,\n      'datetime': datetime.datetime(2024, 12, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7941.50773,\n      'datetime': datetime.datetime(2024, 12, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7676.77391,\n      'datetime': datetime.datetime(2024, 12, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7435.16101,\n      'datetime': datetime.datetime(2024, 12, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7700.54464,\n      'datetime': datetime.datetime(2024, 12, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8008.14097,\n      'datetime': datetime.datetime(2024, 12, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8332.09277,\n      'datetime': datetime.datetime(2024, 12, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8587.49151,\n      'datetime': datetime.datetime(2024, 12, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8769.38568,\n      'datetime': datetime.datetime(2024, 12, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8921.32521,\n      'datetime': datetime.datetime(2024, 12, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8960.95325,\n      'datetime': datetime.datetime(2024, 12, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8936.46287,\n      'datetime': datetime.datetime(2024, 12, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8907.12891,\n      'datetime': datetime.datetime(2024, 12, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8894.52365,\n      'datetime': datetime.datetime(2024, 12, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9021.87883,\n      'datetime': datetime.datetime(2024, 12, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9721.28238,\n      'datetime': datetime.datetime(2024, 12, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9878.06882,\n      'datetime': datetime.datetime(2024, 12, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9994.01289,\n      'datetime': datetime.datetime(2024, 12, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9751.95016,\n      'datetime': datetime.datetime(2024, 12, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9449.43613,\n      'datetime': datetime.datetime(2024, 12, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9006.2255,\n      'datetime': datetime.datetime(2024, 12, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8678.66338,\n      'datetime': datetime.datetime(2024, 12, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8418.57849,\n      'datetime': datetime.datetime(2024, 12, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8251.92084,\n      'datetime': datetime.datetime(2024, 12, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8163.81913,\n      'datetime': datetime.datetime(2024, 12, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8252.57858,\n      'datetime': datetime.datetime(2024, 12, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8519.81215,\n      'datetime': datetime.datetime(2024, 12, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8780.11779,\n      'datetime': datetime.datetime(2024, 12, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9300.09304,\n      'datetime': datetime.datetime(2024, 12, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9895.44864,\n      'datetime': datetime.datetime(2024, 12, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10288.78915,\n      'datetime': datetime.datetime(2024, 12, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10599.63436,\n      'datetime': datetime.datetime(2024, 12, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10828.59667,\n      'datetime': datetime.datetime(2024, 12, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10704.40858,\n      'datetime': datetime.datetime(2024, 12, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10798.29264,\n      'datetime': datetime.datetime(2024, 12, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10946.24711,\n      'datetime': datetime.datetime(2024, 12, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10964.11788,\n      'datetime': datetime.datetime(2024, 12, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10877.37895,\n      'datetime': datetime.datetime(2024, 12, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10735.42875,\n      'datetime': datetime.datetime(2024, 12, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11247.79645,\n      'datetime': datetime.datetime(2024, 12, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11185.90682,\n      'datetime': datetime.datetime(2024, 12, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10982.95534,\n      'datetime': datetime.datetime(2024, 12, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10587.44336,\n      'datetime': datetime.datetime(2024, 12, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9967.93014,\n      'datetime': datetime.datetime(2024, 12, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9351.81495,\n      'datetime': datetime.datetime(2024, 12, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9127.71386,\n      'datetime': datetime.datetime(2024, 12, 17, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8704.57394,\n      'datetime': datetime.datetime(2024, 12, 17, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8170.15281,\n      'datetime': datetime.datetime(2024, 12, 17, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8040.08518,\n      'datetime': datetime.datetime(2024, 12, 17, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8148.35909,\n      'datetime': datetime.datetime(2024, 12, 17, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8384.69619,\n      'datetime': datetime.datetime(2024, 12, 17, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8510.84863,\n      'datetime': datetime.datetime(2024, 12, 17, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9110.92895,\n      'datetime': datetime.datetime(2024, 12, 17, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9910.39253,\n      'datetime': datetime.datetime(2024, 12, 17, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10206.65834,\n      'datetime': datetime.datetime(2024, 12, 17, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10520.05482,\n      'datetime': datetime.datetime(2024, 12, 17, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10761.69493,\n      'datetime': datetime.datetime(2024, 12, 17, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10674.07714,\n      'datetime': datetime.datetime(2024, 12, 17, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10677.88407,\n      'datetime': datetime.datetime(2024, 12, 17, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10841.74601,\n      'datetime': datetime.datetime(2024, 12, 17, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10901.94849,\n      'datetime': datetime.datetime(2024, 12, 17, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10699.25883,\n      'datetime': datetime.datetime(2024, 12, 17, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10670.22852,\n      'datetime': datetime.datetime(2024, 12, 17, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11255.02474,\n      'datetime': datetime.datetime(2024, 12, 17, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11217.15202,\n      'datetime': datetime.datetime(2024, 12, 17, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11025.81185,\n      'datetime': datetime.datetime(2024, 12, 17, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10747.22762,\n      'datetime': datetime.datetime(2024, 12, 17, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10198.72788,\n      'datetime': datetime.datetime(2024, 12, 17, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9599.91171,\n      'datetime': datetime.datetime(2024, 12, 17, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8910.37542,\n      'datetime': datetime.datetime(2024, 12, 18, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8569.45993,\n      'datetime': datetime.datetime(2024, 12, 18, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8193.36137,\n      'datetime': datetime.datetime(2024, 12, 18, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8071.9085,\n      'datetime': datetime.datetime(2024, 12, 18, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8164.5302,\n      'datetime': datetime.datetime(2024, 12, 18, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8353.98297,\n      'datetime': datetime.datetime(2024, 12, 18, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8624.07274,\n      'datetime': datetime.datetime(2024, 12, 18, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9356.71995,\n      'datetime': datetime.datetime(2024, 12, 18, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9876.62549,\n      'datetime': datetime.datetime(2024, 12, 18, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10365.2751,\n      'datetime': datetime.datetime(2024, 12, 18, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10791.3427,\n      'datetime': datetime.datetime(2024, 12, 18, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11045.82523,\n      'datetime': datetime.datetime(2024, 12, 18, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10966.48318,\n      'datetime': datetime.datetime(2024, 12, 18, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10977.79102,\n      'datetime': datetime.datetime(2024, 12, 18, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11209.49479,\n      'datetime': datetime.datetime(2024, 12, 18, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11176.4972,\n      'datetime': datetime.datetime(2024, 12, 18, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11068.92124,\n      'datetime': datetime.datetime(2024, 12, 18, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10912.96093,\n      'datetime': datetime.datetime(2024, 12, 18, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11353.43458,\n      'datetime': datetime.datetime(2024, 12, 18, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11277.21526,\n      'datetime': datetime.datetime(2024, 12, 18, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11050.62615,\n      'datetime': datetime.datetime(2024, 12, 18, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10703.80482,\n      'datetime': datetime.datetime(2024, 12, 18, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10028.89381,\n      'datetime': datetime.datetime(2024, 12, 18, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9423.30764,\n      'datetime': datetime.datetime(2024, 12, 18, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8965.0294,\n      'datetime': datetime.datetime(2024, 12, 19, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8666.36414,\n      'datetime': datetime.datetime(2024, 12, 19, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8363.47526,\n      'datetime': datetime.datetime(2024, 12, 19, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8199.10847,\n      'datetime': datetime.datetime(2024, 12, 19, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8235.47764,\n      'datetime': datetime.datetime(2024, 12, 19, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8518.87909,\n      'datetime': datetime.datetime(2024, 12, 19, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8745.30927,\n      'datetime': datetime.datetime(2024, 12, 19, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9288.45145,\n      'datetime': datetime.datetime(2024, 12, 19, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9920.5656,\n      'datetime': datetime.datetime(2024, 12, 19, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10384.0073,\n      'datetime': datetime.datetime(2024, 12, 19, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10728.11853,\n      'datetime': datetime.datetime(2024, 12, 19, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10903.58014,\n      'datetime': datetime.datetime(2024, 12, 19, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10895.76467,\n      'datetime': datetime.datetime(2024, 12, 19, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10931.62259,\n      'datetime': datetime.datetime(2024, 12, 19, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11089.3667,\n      'datetime': datetime.datetime(2024, 12, 19, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10924.75356,\n      'datetime': datetime.datetime(2024, 12, 19, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10846.53941,\n      'datetime': datetime.datetime(2024, 12, 19, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10758.89714,\n      'datetime': datetime.datetime(2024, 12, 19, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11385.69597,\n      'datetime': datetime.datetime(2024, 12, 19, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11303.36255,\n      'datetime': datetime.datetime(2024, 12, 19, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11086.28209,\n      'datetime': datetime.datetime(2024, 12, 19, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10761.8645,\n      'datetime': datetime.datetime(2024, 12, 19, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10081.86537,\n      'datetime': datetime.datetime(2024, 12, 19, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9541.23898,\n      'datetime': datetime.datetime(2024, 12, 19, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9186.3774,\n      'datetime': datetime.datetime(2024, 12, 20, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8894.81159,\n      'datetime': datetime.datetime(2024, 12, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8679.66899,\n      'datetime': datetime.datetime(2024, 12, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8551.16003,\n      'datetime': datetime.datetime(2024, 12, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8566.14736,\n      'datetime': datetime.datetime(2024, 12, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8813.50975,\n      'datetime': datetime.datetime(2024, 12, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8997.84097,\n      'datetime': datetime.datetime(2024, 12, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9514.35561,\n      'datetime': datetime.datetime(2024, 12, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9972.1652,\n      'datetime': datetime.datetime(2024, 12, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10267.97427,\n      'datetime': datetime.datetime(2024, 12, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10572.35902,\n      'datetime': datetime.datetime(2024, 12, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10914.71396,\n      'datetime': datetime.datetime(2024, 12, 20, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10889.6169,\n      'datetime': datetime.datetime(2024, 12, 20, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10936.7076,\n      'datetime': datetime.datetime(2024, 12, 20, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11032.40595,\n      'datetime': datetime.datetime(2024, 12, 20, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11009.60615,\n      'datetime': datetime.datetime(2024, 12, 20, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10835.18066,\n      'datetime': datetime.datetime(2024, 12, 20, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10731.71617,\n      'datetime': datetime.datetime(2024, 12, 20, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11240.24031,\n      'datetime': datetime.datetime(2024, 12, 20, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 11173.20757,\n      'datetime': datetime.datetime(2024, 12, 20, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10990.9658,\n      'datetime': datetime.datetime(2024, 12, 20, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10631.65951,\n      'datetime': datetime.datetime(2024, 12, 20, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10032.31909,\n      'datetime': datetime.datetime(2024, 12, 20, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9525.46084,\n      'datetime': datetime.datetime(2024, 12, 20, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9082.10443,\n      'datetime': datetime.datetime(2024, 12, 21, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8546.05834,\n      'datetime': datetime.datetime(2024, 12, 21, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8221.43604,\n      'datetime': datetime.datetime(2024, 12, 21, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8308.43327,\n      'datetime': datetime.datetime(2024, 12, 21, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8374.08971,\n      'datetime': datetime.datetime(2024, 12, 21, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8483.1362,\n      'datetime': datetime.datetime(2024, 12, 21, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8493.42095,\n      'datetime': datetime.datetime(2024, 12, 21, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8809.2299,\n      'datetime': datetime.datetime(2024, 12, 21, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9326.02674,\n      'datetime': datetime.datetime(2024, 12, 21, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9620.23287,\n      'datetime': datetime.datetime(2024, 12, 21, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9850.07835,\n      'datetime': datetime.datetime(2024, 12, 21, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10069.13229,\n      'datetime': datetime.datetime(2024, 12, 21, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10020.0994,\n      'datetime': datetime.datetime(2024, 12, 21, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10087.18553,\n      'datetime': datetime.datetime(2024, 12, 21, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10085.15182,\n      'datetime': datetime.datetime(2024, 12, 21, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10023.49653,\n      'datetime': datetime.datetime(2024, 12, 21, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9946.32157,\n      'datetime': datetime.datetime(2024, 12, 21, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10040.81749,\n      'datetime': datetime.datetime(2024, 12, 21, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10631.96952,\n      'datetime': datetime.datetime(2024, 12, 21, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10585.21653,\n      'datetime': datetime.datetime(2024, 12, 21, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10363.61893,\n      'datetime': datetime.datetime(2024, 12, 21, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10039.55898,\n      'datetime': datetime.datetime(2024, 12, 21, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9631.4599,\n      'datetime': datetime.datetime(2024, 12, 21, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9190.64865,\n      'datetime': datetime.datetime(2024, 12, 21, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8636.42784,\n      'datetime': datetime.datetime(2024, 12, 22, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8318.72158,\n      'datetime': datetime.datetime(2024, 12, 22, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8079.93067,\n      'datetime': datetime.datetime(2024, 12, 22, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7948.94374,\n      'datetime': datetime.datetime(2024, 12, 22, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7898.63151,\n      'datetime': datetime.datetime(2024, 12, 22, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7816.90494,\n      'datetime': datetime.datetime(2024, 12, 22, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7715.4535,\n      'datetime': datetime.datetime(2024, 12, 22, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8018.87975,\n      'datetime': datetime.datetime(2024, 12, 22, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8307.19566,\n      'datetime': datetime.datetime(2024, 12, 22, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8551.82034,\n      'datetime': datetime.datetime(2024, 12, 22, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8784.64243,\n      'datetime': datetime.datetime(2024, 12, 22, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9154.83374,\n      'datetime': datetime.datetime(2024, 12, 22, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9248.5868,\n      'datetime': datetime.datetime(2024, 12, 22, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9184.45437,\n      'datetime': datetime.datetime(2024, 12, 22, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9155.60026,\n      'datetime': datetime.datetime(2024, 12, 22, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9130.88997,\n      'datetime': datetime.datetime(2024, 12, 22, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9111.12203,\n      'datetime': datetime.datetime(2024, 12, 22, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9322.08847,\n      'datetime': datetime.datetime(2024, 12, 22, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9902.2795,\n      'datetime': datetime.datetime(2024, 12, 22, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9910.26705,\n      'datetime': datetime.datetime(2024, 12, 22, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9806.89574,\n      'datetime': datetime.datetime(2024, 12, 22, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9665.50253,\n      'datetime': datetime.datetime(2024, 12, 22, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9329.64608,\n      'datetime': datetime.datetime(2024, 12, 22, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8884.26873,\n      'datetime': datetime.datetime(2024, 12, 22, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8507.9385,\n      'datetime': datetime.datetime(2024, 12, 23, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8241.06567,\n      'datetime': datetime.datetime(2024, 12, 23, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7971.12131,\n      'datetime': datetime.datetime(2024, 12, 23, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7598.94639,\n      'datetime': datetime.datetime(2024, 12, 23, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7680.31232,\n      'datetime': datetime.datetime(2024, 12, 23, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7888.76729,\n      'datetime': datetime.datetime(2024, 12, 23, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8137.90545,\n      'datetime': datetime.datetime(2024, 12, 23, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8803.56566,\n      'datetime': datetime.datetime(2024, 12, 23, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9455.55467,\n      'datetime': datetime.datetime(2024, 12, 23, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9798.21169,\n      'datetime': datetime.datetime(2024, 12, 23, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10028.66625,\n      'datetime': datetime.datetime(2024, 12, 23, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10266.95233,\n      'datetime': datetime.datetime(2024, 12, 23, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10230.48287,\n      'datetime': datetime.datetime(2024, 12, 23, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10302.19933,\n      'datetime': datetime.datetime(2024, 12, 23, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10439.1461,\n      'datetime': datetime.datetime(2024, 12, 23, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10427.63563,\n      'datetime': datetime.datetime(2024, 12, 23, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10337.7047,\n      'datetime': datetime.datetime(2024, 12, 23, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10219.741,\n      'datetime': datetime.datetime(2024, 12, 23, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10544.42973,\n      'datetime': datetime.datetime(2024, 12, 23, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10477.30488,\n      'datetime': datetime.datetime(2024, 12, 23, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10284.14142,\n      'datetime': datetime.datetime(2024, 12, 23, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9958.73433,\n      'datetime': datetime.datetime(2024, 12, 23, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9412.96358,\n      'datetime': datetime.datetime(2024, 12, 23, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8903.59652,\n      'datetime': datetime.datetime(2024, 12, 23, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8432.22702,\n      'datetime': datetime.datetime(2024, 12, 24, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8084.88945,\n      'datetime': datetime.datetime(2024, 12, 24, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7759.93379,\n      'datetime': datetime.datetime(2024, 12, 24, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7653.13153,\n      'datetime': datetime.datetime(2024, 12, 24, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7688.44797,\n      'datetime': datetime.datetime(2024, 12, 24, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7933.22845,\n      'datetime': datetime.datetime(2024, 12, 24, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8044.82475,\n      'datetime': datetime.datetime(2024, 12, 24, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8474.57301,\n      'datetime': datetime.datetime(2024, 12, 24, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9061.62481,\n      'datetime': datetime.datetime(2024, 12, 24, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9430.61575,\n      'datetime': datetime.datetime(2024, 12, 24, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9615.0168,\n      'datetime': datetime.datetime(2024, 12, 24, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9774.02007,\n      'datetime': datetime.datetime(2024, 12, 24, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9696.10289,\n      'datetime': datetime.datetime(2024, 12, 24, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9537.4715,\n      'datetime': datetime.datetime(2024, 12, 24, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9390.18582,\n      'datetime': datetime.datetime(2024, 12, 24, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9327.71359,\n      'datetime': datetime.datetime(2024, 12, 24, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9277.58957,\n      'datetime': datetime.datetime(2024, 12, 24, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9424.93306,\n      'datetime': datetime.datetime(2024, 12, 24, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10121.06756,\n      'datetime': datetime.datetime(2024, 12, 24, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10026.62457,\n      'datetime': datetime.datetime(2024, 12, 24, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9368.27124,\n      'datetime': datetime.datetime(2024, 12, 24, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8877.66644,\n      'datetime': datetime.datetime(2024, 12, 24, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8437.26091,\n      'datetime': datetime.datetime(2024, 12, 24, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8154.4477,\n      'datetime': datetime.datetime(2024, 12, 24, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7862.78354,\n      'datetime': datetime.datetime(2024, 12, 25, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7698.22579,\n      'datetime': datetime.datetime(2024, 12, 25, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7352.61867,\n      'datetime': datetime.datetime(2024, 12, 25, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7160.68646,\n      'datetime': datetime.datetime(2024, 12, 25, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7050.81633,\n      'datetime': datetime.datetime(2024, 12, 25, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6918.4984,\n      'datetime': datetime.datetime(2024, 12, 25, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6566.54421,\n      'datetime': datetime.datetime(2024, 12, 25, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6588.83897,\n      'datetime': datetime.datetime(2024, 12, 25, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6782.11034,\n      'datetime': datetime.datetime(2024, 12, 25, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7069.08898,\n      'datetime': datetime.datetime(2024, 12, 25, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7567.76893,\n      'datetime': datetime.datetime(2024, 12, 25, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7851.09222,\n      'datetime': datetime.datetime(2024, 12, 25, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8186.29917,\n      'datetime': datetime.datetime(2024, 12, 25, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8314.63849,\n      'datetime': datetime.datetime(2024, 12, 25, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8345.04647,\n      'datetime': datetime.datetime(2024, 12, 25, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8319.75348,\n      'datetime': datetime.datetime(2024, 12, 25, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8332.74644,\n      'datetime': datetime.datetime(2024, 12, 25, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8462.60161,\n      'datetime': datetime.datetime(2024, 12, 25, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9188.82875,\n      'datetime': datetime.datetime(2024, 12, 25, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9326.21977,\n      'datetime': datetime.datetime(2024, 12, 25, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9228.36447,\n      'datetime': datetime.datetime(2024, 12, 25, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9048.04995,\n      'datetime': datetime.datetime(2024, 12, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8764.11398,\n      'datetime': datetime.datetime(2024, 12, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8426.24439,\n      'datetime': datetime.datetime(2024, 12, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7837.42123,\n      'datetime': datetime.datetime(2024, 12, 26, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7604.15646,\n      'datetime': datetime.datetime(2024, 12, 26, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7476.25995,\n      'datetime': datetime.datetime(2024, 12, 26, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7556.10854,\n      'datetime': datetime.datetime(2024, 12, 26, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7486.06582,\n      'datetime': datetime.datetime(2024, 12, 26, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7684.53058,\n      'datetime': datetime.datetime(2024, 12, 26, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7934.04004,\n      'datetime': datetime.datetime(2024, 12, 26, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8497.30928,\n      'datetime': datetime.datetime(2024, 12, 26, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9233.28242,\n      'datetime': datetime.datetime(2024, 12, 26, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9578.83532,\n      'datetime': datetime.datetime(2024, 12, 26, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9957.45423,\n      'datetime': datetime.datetime(2024, 12, 26, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10351.26249,\n      'datetime': datetime.datetime(2024, 12, 26, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10405.09058,\n      'datetime': datetime.datetime(2024, 12, 26, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10530.54277,\n      'datetime': datetime.datetime(2024, 12, 26, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10646.45488,\n      'datetime': datetime.datetime(2024, 12, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10608.86382,\n      'datetime': datetime.datetime(2024, 12, 26, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10435.11325,\n      'datetime': datetime.datetime(2024, 12, 26, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10354.7418,\n      'datetime': datetime.datetime(2024, 12, 26, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10838.20671,\n      'datetime': datetime.datetime(2024, 12, 26, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10830.16724,\n      'datetime': datetime.datetime(2024, 12, 26, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10542.26782,\n      'datetime': datetime.datetime(2024, 12, 26, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10165.77878,\n      'datetime': datetime.datetime(2024, 12, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9654.97813,\n      'datetime': datetime.datetime(2024, 12, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9174.38395,\n      'datetime': datetime.datetime(2024, 12, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8554.1009,\n      'datetime': datetime.datetime(2024, 12, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8236.80232,\n      'datetime': datetime.datetime(2024, 12, 27, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8051.18243,\n      'datetime': datetime.datetime(2024, 12, 27, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7945.44884,\n      'datetime': datetime.datetime(2024, 12, 27, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7856.0949,\n      'datetime': datetime.datetime(2024, 12, 27, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8090.10681,\n      'datetime': datetime.datetime(2024, 12, 27, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8161.95199,\n      'datetime': datetime.datetime(2024, 12, 27, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8702.72807,\n      'datetime': datetime.datetime(2024, 12, 27, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9465.40975,\n      'datetime': datetime.datetime(2024, 12, 27, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9753.06113,\n      'datetime': datetime.datetime(2024, 12, 27, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10030.32991,\n      'datetime': datetime.datetime(2024, 12, 27, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10333.61172,\n      'datetime': datetime.datetime(2024, 12, 27, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10317.25045,\n      'datetime': datetime.datetime(2024, 12, 27, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10316.00386,\n      'datetime': datetime.datetime(2024, 12, 27, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10380.94772,\n      'datetime': datetime.datetime(2024, 12, 27, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10407.02465,\n      'datetime': datetime.datetime(2024, 12, 27, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10279.45168,\n      'datetime': datetime.datetime(2024, 12, 27, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10252.48386,\n      'datetime': datetime.datetime(2024, 12, 27, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10780.87458,\n      'datetime': datetime.datetime(2024, 12, 27, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10735.61592,\n      'datetime': datetime.datetime(2024, 12, 27, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10486.72813,\n      'datetime': datetime.datetime(2024, 12, 27, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10114.49547,\n      'datetime': datetime.datetime(2024, 12, 27, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9612.58759,\n      'datetime': datetime.datetime(2024, 12, 27, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9147.02657,\n      'datetime': datetime.datetime(2024, 12, 27, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8691.48025,\n      'datetime': datetime.datetime(2024, 12, 28, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8372.4737,\n      'datetime': datetime.datetime(2024, 12, 28, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8160.21451,\n      'datetime': datetime.datetime(2024, 12, 28, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8022.96026,\n      'datetime': datetime.datetime(2024, 12, 28, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7893.75709,\n      'datetime': datetime.datetime(2024, 12, 28, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7923.70298,\n      'datetime': datetime.datetime(2024, 12, 28, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7993.15786,\n      'datetime': datetime.datetime(2024, 12, 28, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8369.33175,\n      'datetime': datetime.datetime(2024, 12, 28, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9079.61784,\n      'datetime': datetime.datetime(2024, 12, 28, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9391.16778,\n      'datetime': datetime.datetime(2024, 12, 28, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9677.02194,\n      'datetime': datetime.datetime(2024, 12, 28, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9808.95318,\n      'datetime': datetime.datetime(2024, 12, 28, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9763.10569,\n      'datetime': datetime.datetime(2024, 12, 28, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9745.67181,\n      'datetime': datetime.datetime(2024, 12, 28, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9752.67733,\n      'datetime': datetime.datetime(2024, 12, 28, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9659.40764,\n      'datetime': datetime.datetime(2024, 12, 28, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9625.73863,\n      'datetime': datetime.datetime(2024, 12, 28, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9704.30386,\n      'datetime': datetime.datetime(2024, 12, 28, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10250.85111,\n      'datetime': datetime.datetime(2024, 12, 28, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10195.43357,\n      'datetime': datetime.datetime(2024, 12, 28, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9977.25543,\n      'datetime': datetime.datetime(2024, 12, 28, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9673.24208,\n      'datetime': datetime.datetime(2024, 12, 28, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9239.30771,\n      'datetime': datetime.datetime(2024, 12, 28, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8852.8834,\n      'datetime': datetime.datetime(2024, 12, 28, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8386.67653,\n      'datetime': datetime.datetime(2024, 12, 29, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8115.33061,\n      'datetime': datetime.datetime(2024, 12, 29, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7928.54267,\n      'datetime': datetime.datetime(2024, 12, 29, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7740.82741,\n      'datetime': datetime.datetime(2024, 12, 29, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7690.39256,\n      'datetime': datetime.datetime(2024, 12, 29, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7652.12036,\n      'datetime': datetime.datetime(2024, 12, 29, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7362.5075,\n      'datetime': datetime.datetime(2024, 12, 29, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7386.37123,\n      'datetime': datetime.datetime(2024, 12, 29, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7743.45512,\n      'datetime': datetime.datetime(2024, 12, 29, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8210.40037,\n      'datetime': datetime.datetime(2024, 12, 29, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8650.41363,\n      'datetime': datetime.datetime(2024, 12, 29, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8900.28588,\n      'datetime': datetime.datetime(2024, 12, 29, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8986.95923,\n      'datetime': datetime.datetime(2024, 12, 29, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9041.8857,\n      'datetime': datetime.datetime(2024, 12, 29, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9020.22568,\n      'datetime': datetime.datetime(2024, 12, 29, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8969.12849,\n      'datetime': datetime.datetime(2024, 12, 29, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8943.23253,\n      'datetime': datetime.datetime(2024, 12, 29, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9043.16371,\n      'datetime': datetime.datetime(2024, 12, 29, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9740.26352,\n      'datetime': datetime.datetime(2024, 12, 29, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9849.4954,\n      'datetime': datetime.datetime(2024, 12, 29, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9723.13743,\n      'datetime': datetime.datetime(2024, 12, 29, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9470.6336,\n      'datetime': datetime.datetime(2024, 12, 29, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9066.65275,\n      'datetime': datetime.datetime(2024, 12, 29, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8592.07477,\n      'datetime': datetime.datetime(2024, 12, 29, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7961.58179,\n      'datetime': datetime.datetime(2024, 12, 30, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7637.45028,\n      'datetime': datetime.datetime(2024, 12, 30, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7366.06934,\n      'datetime': datetime.datetime(2024, 12, 30, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7273.31742,\n      'datetime': datetime.datetime(2024, 12, 30, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7327.59909,\n      'datetime': datetime.datetime(2024, 12, 30, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7499.38183,\n      'datetime': datetime.datetime(2024, 12, 30, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7643.12061,\n      'datetime': datetime.datetime(2024, 12, 30, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8094.76397,\n      'datetime': datetime.datetime(2024, 12, 30, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8744.18064,\n      'datetime': datetime.datetime(2024, 12, 30, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9279.50298,\n      'datetime': datetime.datetime(2024, 12, 30, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9525.55641,\n      'datetime': datetime.datetime(2024, 12, 30, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9809.3297,\n      'datetime': datetime.datetime(2024, 12, 30, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9866.57444,\n      'datetime': datetime.datetime(2024, 12, 30, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9885.75861,\n      'datetime': datetime.datetime(2024, 12, 30, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9931.4746,\n      'datetime': datetime.datetime(2024, 12, 30, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9877.0645,\n      'datetime': datetime.datetime(2024, 12, 30, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9744.91882,\n      'datetime': datetime.datetime(2024, 12, 30, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9724.92078,\n      'datetime': datetime.datetime(2024, 12, 30, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10263.46596,\n      'datetime': datetime.datetime(2024, 12, 30, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 10248.63476,\n      'datetime': datetime.datetime(2024, 12, 30, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9949.04342,\n      'datetime': datetime.datetime(2024, 12, 30, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9367.64943,\n      'datetime': datetime.datetime(2024, 12, 30, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8912.80537,\n      'datetime': datetime.datetime(2024, 12, 30, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8457.74459,\n      'datetime': datetime.datetime(2024, 12, 30, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8007.54931,\n      'datetime': datetime.datetime(2024, 12, 31, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7648.40858,\n      'datetime': datetime.datetime(2024, 12, 31, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7336.61436,\n      'datetime': datetime.datetime(2024, 12, 31, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7191.97381,\n      'datetime': datetime.datetime(2024, 12, 31, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7190.983,\n      'datetime': datetime.datetime(2024, 12, 31, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7272.97339,\n      'datetime': datetime.datetime(2024, 12, 31, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7255.41841,\n      'datetime': datetime.datetime(2024, 12, 31, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7583.73473,\n      'datetime': datetime.datetime(2024, 12, 31, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8083.30991,\n      'datetime': datetime.datetime(2024, 12, 31, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8452.37563,\n      'datetime': datetime.datetime(2024, 12, 31, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8614.00826,\n      'datetime': datetime.datetime(2024, 12, 31, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8745.76856,\n      'datetime': datetime.datetime(2024, 12, 31, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8792.71922,\n      'datetime': datetime.datetime(2024, 12, 31, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8715.56372,\n      'datetime': datetime.datetime(2024, 12, 31, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8668.97539,\n      'datetime': datetime.datetime(2024, 12, 31, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8675.27004,\n      'datetime': datetime.datetime(2024, 12, 31, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8691.99343,\n      'datetime': datetime.datetime(2024, 12, 31, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8842.77824,\n      'datetime': datetime.datetime(2024, 12, 31, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9496.90058,\n      'datetime': datetime.datetime(2024, 12, 31, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9559.18281,\n      'datetime': datetime.datetime(2024, 12, 31, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 9144.29732,\n      'datetime': datetime.datetime(2024, 12, 31, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8688.39718,\n      'datetime': datetime.datetime(2024, 12, 31, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8116.86562,\n      'datetime': datetime.datetime(2024, 12, 31, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7573.45633,\n      'datetime': datetime.datetime(2024, 12, 31, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7306.48365,\n      'datetime': datetime.datetime(2025, 1, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7183.62888,\n      'datetime': datetime.datetime(2025, 1, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7059.6042,\n      'datetime': datetime.datetime(2025, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6928.0031,\n      'datetime': datetime.datetime(2025, 1, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6817.47314,\n      'datetime': datetime.datetime(2025, 1, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6681.1566,\n      'datetime': datetime.datetime(2025, 1, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6328.18434,\n      'datetime': datetime.datetime(2025, 1, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6304.23399,\n      'datetime': datetime.datetime(2025, 1, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6477.09356,\n      'datetime': datetime.datetime(2025, 1, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6674.85881,\n      'datetime': datetime.datetime(2025, 1, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6923.08161,\n      'datetime': datetime.datetime(2025, 1, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7130.68352,\n      'datetime': datetime.datetime(2025, 1, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7304.81407,\n      'datetime': datetime.datetime(2025, 1, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7406.58739,\n      'datetime': datetime.datetime(2025, 1, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7375.07319,\n      'datetime': datetime.datetime(2025, 1, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7342.85141,\n      'datetime': datetime.datetime(2025, 1, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7307.4416,\n      'datetime': datetime.datetime(2025, 1, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7475.79909,\n      'datetime': datetime.datetime(2025, 1, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8436.64463,\n      'datetime': datetime.datetime(2025, 1, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8641.72283,\n      'datetime': datetime.datetime(2025, 1, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8558.02618,\n      'datetime': datetime.datetime(2025, 1, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8388.22406,\n      'datetime': datetime.datetime(2025, 1, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8222.3187,\n      'datetime': datetime.datetime(2025, 1, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7925.23103,\n      'datetime': datetime.datetime(2025, 1, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n  ])\n# ---\n# name: test_fetch_consumption_live\n  list([\n    dict({\n      'consumption': 7636.8,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7695.9,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7600.0,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7571.0,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7573.7,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7544.4,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7488.7,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7462.2,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7474.7,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7440.9,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7398.9,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7401.6,\n      'datetime': datetime.datetime(2025, 1, 6, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7378.4,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7351.2,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7303.5,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7317.6,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7290.5,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7265.1,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7249.8,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7216.3,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7187.4,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7209.1,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7198.2,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7158.1,\n      'datetime': datetime.datetime(2025, 1, 6, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7150.0,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7092.1,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7077.9,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7099.9,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7084.3,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7056.1,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 25, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7039.7,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7048.1,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 35, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7017.6,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7001.8,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7018.3,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6997.5,\n      'datetime': datetime.datetime(2025, 1, 6, 2, 55, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6974.6,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6952.3,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 5, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6966.7,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6950.2,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6930.8,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6888.1,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 25, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6926.2,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6926.9,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 35, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6928.4,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6892.0,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6868.6,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6904.7,\n      'datetime': datetime.datetime(2025, 1, 6, 3, 55, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6910.5,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6905.6,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 5, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6930.4,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 11, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6915.0,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 16, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6883.4,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 21, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6905.4,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 26, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6897.8,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 31, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6897.4,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 36, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6875.8,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 41, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6863.5,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 46, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6854.9,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 51, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6862.4,\n      'datetime': datetime.datetime(2025, 1, 6, 4, 56, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6880.5,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 1, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6894.2,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 6, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6897.7,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 11, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6955.0,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 16, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6930.9,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 21, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6920.7,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 26, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6921.4,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 31, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6929.2,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 36, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6934.0,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 41, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6921.6,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 46, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6937.9,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 51, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6895.2,\n      'datetime': datetime.datetime(2025, 1, 6, 5, 56, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6843.5,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 1, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6837.3,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 6, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6795.4,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 11, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6770.9,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 16, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6733.3,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 21, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6743.6,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 26, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6737.1,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 31, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6750.1,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 36, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6784.4,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 41, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6796.9,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 46, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6791.9,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 51, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6808.4,\n      'datetime': datetime.datetime(2025, 1, 6, 6, 56, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6809.3,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 1, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6844.8,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 6, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6882.4,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 11, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6898.0,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 16, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6895.8,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 21, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6930.4,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 26, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6975.8,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 31, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 6989.0,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 36, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7000.3,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 41, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7021.1,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 46, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7030.6,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 51, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7015.1,\n      'datetime': datetime.datetime(2025, 1, 6, 7, 56, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7048.4,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 1, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7068.8,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 6, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7143.5,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 11, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7141.1,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 16, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7196.1,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 22, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7191.1,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 27, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7233.6,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 32, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7229.0,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 37, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7245.0,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 42, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7257.1,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 47, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7317.6,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 52, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7333.7,\n      'datetime': datetime.datetime(2025, 1, 6, 8, 57, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7352.1,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 2, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7368.9,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 7, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7378.5,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 12, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7423.0,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 17, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7446.0,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 22, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7488.6,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 27, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7499.3,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 32, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7506.7,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 37, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7565.0,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 42, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7552.8,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 47, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7576.4,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 52, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7611.6,\n      'datetime': datetime.datetime(2025, 1, 6, 9, 57, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7630.9,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 2, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7657.1,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 7, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7663.7,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 12, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7693.4,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 17, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7706.3,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 22, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7733.2,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 27, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7788.7,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 32, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7841.5,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 37, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7848.8,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 42, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7818.7,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 47, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7839.7,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 52, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7833.1,\n      'datetime': datetime.datetime(2025, 1, 6, 10, 57, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7882.7,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 2, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7884.5,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 7, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7925.5,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 12, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8011.2,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 17, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8078.0,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 22, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 7980.6,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 27, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8015.7,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 32, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8072.2,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 37, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8098.3,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 42, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8071.0,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 47, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8090.9,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 52, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8116.9,\n      'datetime': datetime.datetime(2025, 1, 6, 11, 57, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8164.4,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 2, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8172.8,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 7, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8221.4,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 12, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8155.7,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 17, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8157.3,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 22, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8193.4,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 27, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8243.4,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 33, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8290.6,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 38, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8262.6,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 43, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8268.1,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 48, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8263.6,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 53, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8309.4,\n      'datetime': datetime.datetime(2025, 1, 6, 12, 58, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8300.1,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 3, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8284.3,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 8, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8314.7,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 13, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8292.3,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 18, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8319.7,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 23, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8356.4,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 28, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8262.2,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 33, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8245.5,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 38, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8246.6,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 43, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8282.6,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 48, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8279.3,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 53, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8312.1,\n      'datetime': datetime.datetime(2025, 1, 6, 13, 58, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8304.5,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 3, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8283.0,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 8, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8274.8,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 13, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8247.3,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 18, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8239.7,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 23, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8246.4,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 28, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8285.6,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 33, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8256.4,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 38, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8291.1,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 43, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8285.4,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 48, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8308.3,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 53, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8314.1,\n      'datetime': datetime.datetime(2025, 1, 6, 14, 58, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8294.2,\n      'datetime': datetime.datetime(2025, 1, 6, 15, 3, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8321.6,\n      'datetime': datetime.datetime(2025, 1, 6, 15, 8, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8334.8,\n      'datetime': datetime.datetime(2025, 1, 6, 15, 13, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8324.7,\n      'datetime': datetime.datetime(2025, 1, 6, 15, 18, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8299.2,\n      'datetime': datetime.datetime(2025, 1, 6, 15, 23, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'consumption': 8272.7,\n      'datetime': datetime.datetime(2025, 1, 6, 15, 28, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n  ])\n# ---\n# name: test_fetch_price_dt\n  list([\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 642.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 642.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 637.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 637.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 637.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 516.81203,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 222.61603,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 114.93803,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 114.93603,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 146.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 229.82403,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 516.81203,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 637.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 637.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 642.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 642.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 642.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 723.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 723.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 723.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 723.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 723.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 723.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 642.08503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 556.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 556.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 556.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 556.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 556.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 638.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 638.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 638.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 638.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 638.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 638.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 656.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 656.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 656.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 725.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 726.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 725.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 727.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 756.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 756.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 726.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 725.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 686.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 2, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 656.02462,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.0355,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.0355,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.0355,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.0355,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.0355,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 726.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 726.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 727.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 736.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 746.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 746.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 756.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 756.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 746.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 736.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 727.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 724.4495,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 756.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 754.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 754.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 754.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 754.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 756.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 759.83157,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 759.83157,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 759.83157,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 759.83157,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 759.83157,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 797.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 797.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 797.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 797.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 797.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 797.39457,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 759.83157,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 768.80148,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 768.80148,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 768.80148,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 726.44048,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 768.80148,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 768.80148,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 768.80148,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 768.80148,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 803.61948,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 803.61948,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 805.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 816.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 817.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 820.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 820.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 817.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 817.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.09748,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 765.59098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 765.59098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 765.59098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 765.59098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 765.59098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 765.59098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 765.59098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 765.59098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 765.59098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 791.93498,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 791.93498,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 791.93498,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 791.93498,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 791.93498,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.49098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.49098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.49098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.49098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.49098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.49098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.49098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.49098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.49098,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 6, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 791.93498,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 802.99418,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 789.16618,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 802.99418,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 802.99418,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 802.99418,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 802.99418,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 802.99418,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 802.99418,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 830.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 835.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 830.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 806.47218,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 249.39863,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 249.39863,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 249.39863,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 419.21363,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 790.95263,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 808.45063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 849.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 849.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 849.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 809.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 809.75063,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 807.27263,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 845.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 845.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 827.82672,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 827.82672,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 816.87172,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 845.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 845.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 845.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 845.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 845.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 845.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 850.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 850.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 850.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 850.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 850.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 850.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 860.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 861.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 861.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 861.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 860.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 850.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 850.51472,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 839.71187,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 829.04187,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 829.04187,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 829.04187,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 829.04187,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 829.04187,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 856.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 856.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 856.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 856.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 856.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 856.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 856.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 866.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 866.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 866.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 909.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 871.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 909.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 909.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 909.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 866.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 866.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 10, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 856.21087,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 828.71715,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 828.71715,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 828.71715,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 828.71715,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 828.71715,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 909.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 909.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 909.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 951.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 951.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 909.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 909.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.89115,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 11, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 865.48815,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.5081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 826.6331,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 826.6331,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 784.1871,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 826.6331,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 826.6331,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 826.6331,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 826.6331,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 826.6331,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.5081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 908.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 916.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 916.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 917.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 946.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 12, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 917.1051,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 925.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 952.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 965.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 965.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 966.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 966.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 966.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 966.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 965.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 951.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 13, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.56314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1000.20475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1000.20475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1000.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1000.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1095.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1095.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1095.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1000.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 995.50475,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.02344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 926.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 877.00044,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 811.32344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 811.32344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 811.32344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 753.29644,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 753.29644,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 753.29644,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 753.29644,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 811.32344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 753.29644,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 811.32344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 926.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.62644,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.02344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1001.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1186.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1186.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1186.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1186.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1166.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1186.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1001.22344,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 810.28099,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 810.28099,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 810.28099,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 810.28099,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 810.28099,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 908.38299,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.77999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 810.28099,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 926.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1049.50299,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1301.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1301.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1301.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1308.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1326.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1326.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1308.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1326.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1326.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1308.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1301.97999,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1090.07199,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 908.38299,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 809.7917,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 809.7917,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 809.7917,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 809.7917,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.7967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.7967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1049.5197,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1056.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1056.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1056.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1056.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1347.5967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1356.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1347.5967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1356.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1356.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1090.0887,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1056.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 986.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 17, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 986.9967,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.42232,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 808.84632,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 751.42032,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 751.42032,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 751.42032,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 808.84632,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 860.01932,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.42232,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 860.01932,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.42232,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.01932,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1048.54232,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1048.54232,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1006.01832,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 18, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.01932,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 735.78114,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 735.78114,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 735.78114,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 729.10014,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 735.78114,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 807.22414,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 729.10014,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 773.78614,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.46314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.46314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1106.66314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1106.66314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1106.66314,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 19, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 906.65214,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 832.99662,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 788.82062,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 788.82062,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 788.82062,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 788.82062,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 788.82062,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 788.82062,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 832.99662,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 788.82062,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 832.99662,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 877.07262,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.69862,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 898.60362,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 902.29562,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.29562,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1048.81862,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1156.29562,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1156.29562,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1156.29562,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1156.29562,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1156.29562,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1048.81862,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.29562,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 20, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.69862,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 790.45658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 790.45658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 877.04558,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.67158,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 907.67158,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.06858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 966.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1156.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1156.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1156.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 966.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.06858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 21, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 936.26858,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 837.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 837.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 809.32229,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 796.58629,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 796.58629,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 796.58629,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 796.58629,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 796.58629,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 796.58629,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 796.58629,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 796.58629,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 837.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 837.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 837.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 837.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 908.41729,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.81429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 967.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1008.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1008.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1008.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 1008.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 967.01429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 22, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 954.81429,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 120.88181,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 430.13081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 260.01281,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 125.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 165.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 407.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 719.40681,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 759.41281,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 759.41281,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 795.51581,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 805.90581,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 805.90581,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 805.90581,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 805.90581,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 980.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 980.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 980.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 950.36481,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 23, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 805.90581,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 425.51164,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 425.51164,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 425.51164,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 627.98964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 627.98964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 730.46864,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 627.98964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 627.98964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 730.46864,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 730.46864,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 770.82964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 770.82964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 770.82964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 770.82964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 730.46864,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 770.82964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 770.82964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 862.98964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 937.98964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 862.98964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 862.98964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 770.82964,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 730.46864,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 24, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 730.46864,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 413.06703,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 266.24403,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 413.06703,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 423.83303,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 413.06703,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 266.24403,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 159.06703,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 114.58403,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 114.58403,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 114.58403,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 115.74503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 115.74503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 236.80603,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 413.06703,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 413.06703,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 413.06703,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 437.35503,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 611.71303,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 657.13903,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 764.06703,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 764.06703,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 657.13903,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 611.71303,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 611.71303,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 112.94194,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 112.94194,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 112.94194,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 151.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 157.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 358.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 511.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 511.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 511.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 511.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 612.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 662.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 662.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 692.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 662.42494,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 114.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 120.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 120.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 120.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 120.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 120.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 120.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 120.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 264.27358,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 264.27358,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 264.27358,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 582.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 582.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 583.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 583.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 583.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 583.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 614.94758,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 663.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 663.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 663.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 583.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 421.86258,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 27, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 358.09658,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 485.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 485.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 415.42975,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 372.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 392.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 415.42975,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 372.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 428.95175,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 485.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 485.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 485.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 537.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 537.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 537.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 555.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 555.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 555.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 555.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 555.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 555.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 555.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 555.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 555.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 28, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 537.66375,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 149.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 210.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 210.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 155.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 155.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 155.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 110.93781,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 110.93781,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 111.99881,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 149.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 155.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 210.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 210.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 210.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 233.05981,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 249.96881,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 525.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 525.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 535.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 544.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 535.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 535.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 532.73081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 29, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 525.32081,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 209.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 209.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 209.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 209.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 209.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 209.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 209.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 209.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 248.92412,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 489.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 509.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 509.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 489.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 489.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 30, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 483.27612,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.70824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.70824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.70824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.70824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.70824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.70824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.70824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 230.52624,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 500.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 500.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 249.85624,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 149.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2024, 12, 31, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 119.20824,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 113.54083,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 113.53983,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 113.53983,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 113.53983,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 113.53983,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 113.54083,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 202.68783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 256.86083,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 449.05883,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 449.05883,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 449.05883,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 242.83583,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 229.18783,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n  ])\n# ---\n# name: test_fetch_price_live\n  list([\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 481.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 506.54671,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 516.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 551.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 551.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 551.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 551.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 551.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 551.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 551.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 551.15771,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'currency': 'COP',\n      'datetime': datetime.datetime(2025, 1, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'price': 506.54671,\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CO',\n    }),\n  ])\n# ---\n# name: test_fetch_production_dt\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.806,\n        'coal': 957.425,\n        'gas': 999.13,\n        'hydro': 6780.737,\n        'oil': 77.351,\n        'solar': 0.0,\n        'wind': 15.404,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.16,\n        'coal': 943.174,\n        'gas': 1039.439,\n        'hydro': 6469.758,\n        'oil': 64.481,\n        'solar': 0.0,\n        'wind': 15.222,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.602,\n        'coal': 940.056,\n        'gas': 885.943,\n        'hydro': 6390.131,\n        'oil': 64.495,\n        'solar': 0.0,\n        'wind': 13.549,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.82,\n        'coal': 939.584,\n        'gas': 854.419,\n        'hydro': 6229.313,\n        'oil': 64.759,\n        'solar': 0.0,\n        'wind': 13.742,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.5,\n        'coal': 937.477,\n        'gas': 801.059,\n        'hydro': 6199.897,\n        'oil': 64.71,\n        'solar': 0.0,\n        'wind': 10.18,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 102.387,\n        'coal': 944.182,\n        'gas': 678.077,\n        'hydro': 6212.565,\n        'oil': 64.766,\n        'solar': 1.353,\n        'wind': 8.644,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 105.956,\n        'coal': 949.142,\n        'gas': 678.369,\n        'hydro': 5867.445,\n        'oil': 64.535,\n        'solar': 162.582,\n        'wind': 5.08,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 102.358,\n        'coal': 944.213,\n        'gas': 673.426,\n        'hydro': 5571.449,\n        'oil': 69.305,\n        'solar': 707.076,\n        'wind': 7.637,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 105.129,\n        'coal': 963.931,\n        'gas': 616.12,\n        'hydro': 5433.516,\n        'oil': 126.537,\n        'solar': 1137.805,\n        'wind': 14.054,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.143,\n        'coal': 934.143,\n        'gas': 551.717,\n        'hydro': 5524.776,\n        'oil': 165.75,\n        'solar': 1404.048,\n        'wind': 17.079,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 108.685,\n        'coal': 955.026,\n        'gas': 439.06,\n        'hydro': 5852.57,\n        'oil': 165.628,\n        'solar': 1484.169,\n        'wind': 16.648,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.477,\n        'coal': 1034.361,\n        'gas': 439.612,\n        'hydro': 6045.512,\n        'oil': 172.505,\n        'solar': 1459.335,\n        'wind': 17.753,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 102.107,\n        'coal': 1087.611,\n        'gas': 419.294,\n        'hydro': 6154.03,\n        'oil': 283.085,\n        'solar': 1354.256,\n        'wind': 17.836,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 104.424,\n        'coal': 1113.955,\n        'gas': 502.335,\n        'hydro': 6065.877,\n        'oil': 298.142,\n        'solar': 1347.87,\n        'wind': 18.335,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 101.323,\n        'coal': 1080.287,\n        'gas': 545.816,\n        'hydro': 6103.116,\n        'oil': 305.788,\n        'solar': 1232.333,\n        'wind': 19.281,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.288,\n        'coal': 1114.547,\n        'gas': 632.772,\n        'hydro': 6156.593,\n        'oil': 305.877,\n        'solar': 1022.99,\n        'wind': 19.322,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 112.567,\n        'coal': 1122.917,\n        'gas': 743.535,\n        'hydro': 6603.351,\n        'oil': 305.823,\n        'solar': 450.98,\n        'wind': 18.792,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.811,\n        'coal': 1101.985,\n        'gas': 799.526,\n        'hydro': 7293.94,\n        'oil': 226.982,\n        'solar': 27.781,\n        'wind': 17.472,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.508,\n        'coal': 1082.121,\n        'gas': 828.741,\n        'hydro': 8094.411,\n        'oil': 180.681,\n        'solar': 0.024,\n        'wind': 17.591,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 108.072,\n        'coal': 1082.545,\n        'gas': 948.375,\n        'hydro': 8152.88,\n        'oil': 118.608,\n        'solar': 0.0,\n        'wind': 16.535,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 103.986,\n        'coal': 1091.61,\n        'gas': 973.015,\n        'hydro': 8069.408,\n        'oil': 77.172,\n        'solar': 0.0,\n        'wind': 16.885,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.404,\n        'coal': 1099.748,\n        'gas': 985.483,\n        'hydro': 7794.608,\n        'oil': 77.407,\n        'solar': 0.0,\n        'wind': 15.397,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.968,\n        'coal': 1105.108,\n        'gas': 995.901,\n        'hydro': 7361.91,\n        'oil': 77.365,\n        'solar': 0.0,\n        'wind': 16.296,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.201,\n        'coal': 1111.886,\n        'gas': 1012.541,\n        'hydro': 6882.525,\n        'oil': 95.601,\n        'solar': 0.0,\n        'wind': 17.087,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.0,\n        'coal': 1107.444,\n        'gas': 1009.757,\n        'hydro': 6345.085,\n        'oil': 162.488,\n        'solar': 0.0,\n        'wind': 14.857,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.124,\n        'coal': 1099.71,\n        'gas': 871.239,\n        'hydro': 6217.448,\n        'oil': 165.488,\n        'solar': 0.0,\n        'wind': 14.528,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.634,\n        'coal': 1094.76,\n        'gas': 768.101,\n        'hydro': 6131.984,\n        'oil': 165.772,\n        'solar': 0.0,\n        'wind': 15.531,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.138,\n        'coal': 1099.546,\n        'gas': 796.632,\n        'hydro': 6016.038,\n        'oil': 165.425,\n        'solar': 0.0,\n        'wind': 15.481,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.636,\n        'coal': 1147.701,\n        'gas': 781.589,\n        'hydro': 6097.651,\n        'oil': 174.858,\n        'solar': 0.0,\n        'wind': 14.857,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.763,\n        'coal': 1235.08,\n        'gas': 722.487,\n        'hydro': 6265.894,\n        'oil': 201.255,\n        'solar': 1.368,\n        'wind': 12.019,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.058,\n        'coal': 1282.954,\n        'gas': 699.141,\n        'hydro': 6344.081,\n        'oil': 248.407,\n        'solar': 140.816,\n        'wind': 9.137,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.028,\n        'coal': 1285.265,\n        'gas': 700.051,\n        'hydro': 6381.383,\n        'oil': 324.916,\n        'solar': 629.902,\n        'wind': 8.492,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.747,\n        'coal': 1285.761,\n        'gas': 785.371,\n        'hydro': 6499.095,\n        'oil': 327.384,\n        'solar': 998.148,\n        'wind': 7.628,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.525,\n        'coal': 1266.543,\n        'gas': 813.964,\n        'hydro': 6644.296,\n        'oil': 296.26,\n        'solar': 1172.137,\n        'wind': 11.255,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 10, 0, 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'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 115.507,\n        'coal': 1187.184,\n        'gas': 692.129,\n        'hydro': 7813.244,\n        'oil': 440.076,\n        'solar': 862.014,\n        'wind': 17.131,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 115.142,\n        'coal': 1179.198,\n        'gas': 822.826,\n        'hydro': 7989.281,\n        'oil': 441.353,\n        'solar': 604.665,\n        'wind': 17.06,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 112.226,\n        'coal': 1187.321,\n        'gas': 844.009,\n        'hydro': 8107.022,\n        'oil': 412.638,\n        'solar': 333.024,\n        'wind': 18.575,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.35,\n        'coal': 1164.207,\n        'gas': 990.739,\n        'hydro': 8296.166,\n        'oil': 341.884,\n        'solar': 26.586,\n        'wind': 18.677,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 110.262,\n        'coal': 1172.539,\n        'gas': 1111.537,\n        'hydro': 8721.398,\n        'oil': 334.007,\n        'solar': 0.021,\n        'wind': 16.734,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 112.629,\n        'coal': 1186.662,\n        'gas': 1163.725,\n        'hydro': 8705.259,\n        'oil': 268.532,\n        'solar': 0.0,\n        'wind': 15.289,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.861,\n        'coal': 1181.682,\n        'gas': 1135.533,\n        'hydro': 8530.557,\n        'oil': 267.429,\n        'solar': 0.002,\n        'wind': 13.998,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.308,\n        'coal': 1181.645,\n        'gas': 1064.679,\n        'hydro': 8097.45,\n        'oil': 345.229,\n        'solar': 0.002,\n        'wind': 11.767,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.137,\n        'coal': 1181.315,\n        'gas': 1193.036,\n        'hydro': 7540.28,\n        'oil': 218.033,\n        'solar': 0.002,\n        'wind': 13.519,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 2, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.797,\n        'coal': 1182.534,\n        'gas': 1248.957,\n        'hydro': 6966.567,\n        'oil': 164.661,\n        'solar': 0.002,\n        'wind': 13.175,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.888,\n        'coal': 1224.718,\n        'gas': 1352.957,\n        'hydro': 6286.261,\n        'oil': 154.113,\n        'solar': 0.002,\n        'wind': 13.217,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.205,\n        'coal': 1233.417,\n        'gas': 1386.901,\n        'hydro': 5871.253,\n        'oil': 172.194,\n        'solar': 0.002,\n        'wind': 10.453,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 130.517,\n        'coal': 1233.886,\n        'gas': 1263.634,\n        'hydro': 5759.075,\n        'oil': 165.682,\n        'solar': 0.002,\n        'wind': 11.992,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.659,\n        'coal': 1198.593,\n        'gas': 1268.366,\n        'hydro': 5699.295,\n        'oil': 166.133,\n        'solar': 0.002,\n        'wind': 9.967,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.189,\n        'coal': 1175.72,\n        'gas': 1247.038,\n        'hydro': 5856.54,\n        'oil': 166.077,\n        'solar': 0.002,\n        'wind': 10.341,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.769,\n        'coal': 1163.668,\n        'gas': 1221.968,\n        'hydro': 6116.664,\n        'oil': 166.051,\n        'solar': 1.502,\n        'wind': 13.542,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.797,\n        'coal': 1162.556,\n        'gas': 1216.538,\n        'hydro': 6253.738,\n        'oil': 202.241,\n        'solar': 86.13,\n        'wind': 15.107,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.187,\n        'coal': 1162.22,\n        'gas': 1198.592,\n        'hydro': 6401.477,\n        'oil': 313.451,\n        'solar': 434.925,\n        'wind': 15.348,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.075,\n        'coal': 1153.278,\n        'gas': 1217.106,\n        'hydro': 6432.243,\n        'oil': 299.048,\n        'solar': 825.68,\n        'wind': 17.296,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 109.987,\n        'coal': 1141.355,\n        'gas': 1235.428,\n        'hydro': 6372.813,\n        'oil': 342.258,\n        'solar': 1090.261,\n        'wind': 16.647,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 110.653,\n        'coal': 1080.092,\n        'gas': 1242.051,\n        'hydro': 6518.134,\n        'oil': 385.517,\n        'solar': 1336.143,\n        'wind': 13.667,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 110.19,\n        'coal': 1063.211,\n        'gas': 1235.773,\n        'hydro': 6717.508,\n        'oil': 457.354,\n        'solar': 1410.874,\n        'wind': 13.26,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 101.077,\n        'coal': 1039.251,\n        'gas': 1259.298,\n        'hydro': 6731.744,\n        'oil': 456.245,\n        'solar': 1403.267,\n        'wind': 12.161,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.831,\n        'coal': 1036.897,\n        'gas': 1246.538,\n        'hydro': 6809.751,\n        'oil': 456.892,\n        'solar': 1372.618,\n        'wind': 17.006,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.954,\n        'coal': 1036.625,\n        'gas': 1229.885,\n        'hydro': 7341.359,\n        'oil': 456.874,\n        'solar': 1085.425,\n        'wind': 18.641,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.872,\n        'coal': 1039.553,\n        'gas': 1211.562,\n        'hydro': 7615.532,\n        'oil': 456.615,\n        'solar': 852.918,\n        'wind': 19.487,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.607,\n        'coal': 1047.215,\n        'gas': 1210.275,\n        'hydro': 8021.532,\n        'oil': 366.332,\n        'solar': 379.846,\n        'wind': 18.986,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.845,\n        'coal': 1061.768,\n        'gas': 1334.499,\n        'hydro': 8169.884,\n        'oil': 371.2,\n        'solar': 28.847,\n        'wind': 15.825,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.265,\n        'coal': 1067.647,\n        'gas': 1434.268,\n        'hydro': 8643.371,\n        'oil': 298.593,\n        'solar': 0.005,\n        'wind': 17.275,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.428,\n        'coal': 1080.904,\n        'gas': 1403.14,\n        'hydro': 8623.874,\n        'oil': 318.164,\n        'solar': 0.0,\n        'wind': 15.218,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.928,\n        'coal': 1087.152,\n        'gas': 1447.146,\n        'hydro': 8397.195,\n        'oil': 267.801,\n        'solar': 0.0,\n        'wind': 8.441,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    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'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 130.423,\n        'coal': 1098.431,\n        'gas': 1508.106,\n        'hydro': 6795.653,\n        'oil': 165.616,\n        'solar': 0.0,\n        'wind': 6.243,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.362,\n        'coal': 1101.839,\n        'gas': 1434.096,\n        'hydro': 6391.092,\n        'oil': 154.21,\n        'solar': 0.0,\n        'wind': 7.958,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.427,\n        'coal': 1097.408,\n        'gas': 1525.434,\n        'hydro': 6006.297,\n        'oil': 136.388,\n        'solar': 0.0,\n        'wind': 10.721,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.017,\n        'coal': 1095.405,\n        'gas': 1474.481,\n        'hydro': 5885.183,\n        'oil': 64.559,\n        'solar': 0.0,\n        'wind': 10.941,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.418,\n        'coal': 1093.276,\n        'gas': 1444.59,\n        'hydro': 5814.632,\n        'oil': 64.396,\n        'solar': 0.0,\n        'wind': 11.344,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.695,\n        'coal': 1078.452,\n        'gas': 1548.911,\n        'hydro': 5835.795,\n        'oil': 77.306,\n        'solar': 0.0,\n        'wind': 9.477,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.61,\n        'coal': 1047.433,\n        'gas': 1577.362,\n        'hydro': 6062.807,\n        'oil': 67.328,\n        'solar': 1.242,\n        'wind': 9.059,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.843,\n        'coal': 1048.313,\n        'gas': 1582.092,\n        'hydro': 6216.122,\n        'oil': 67.657,\n        'solar': 121.214,\n        'wind': 5.359,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.505,\n        'coal': 1049.994,\n        'gas': 1579.863,\n        'hydro': 6305.922,\n        'oil': 85.933,\n        'solar': 585.585,\n        'wind': 5.08,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n 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    'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.914,\n        'coal': 1125.236,\n        'gas': 1523.709,\n        'hydro': 6427.501,\n        'oil': 177.631,\n        'solar': 1341.053,\n        'wind': 21.146,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.013,\n        'coal': 1137.037,\n        'gas': 1601.728,\n        'hydro': 6633.863,\n        'oil': 177.538,\n        'solar': 1349.088,\n        'wind': 20.604,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.384,\n        'coal': 1154.833,\n        'gas': 1585.717,\n        'hydro': 6594.785,\n        'oil': 165.849,\n        'solar': 1354.0,\n        'wind': 20.098,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.855,\n        'coal': 1179.714,\n        'gas': 1634.965,\n        'hydro': 6496.515,\n        'oil': 270.809,\n        'solar': 1301.669,\n        'wind': 22.316,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.659,\n        'coal': 1204.751,\n        'gas': 1561.856,\n        'hydro': 6971.068,\n        'oil': 305.15,\n        'solar': 1119.026,\n        'wind': 19.942,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.534,\n        'coal': 1205.731,\n        'gas': 1569.195,\n        'hydro': 7197.707,\n        'oil': 332.768,\n        'solar': 878.528,\n        'wind': 20.08,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.5,\n        'coal': 1274.57,\n        'gas': 1680.42,\n        'hydro': 7426.754,\n        'oil': 362.853,\n        'solar': 396.629,\n        'wind': 21.654,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 115.616,\n        'coal': 1245.841,\n        'gas': 1742.701,\n        'hydro': 7781.931,\n        'oil': 305.483,\n        'solar': 34.419,\n        'wind': 20.559,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.293,\n        'coal': 1253.585,\n        'gas': 1859.993,\n        'hydro': 8072.347,\n        'oil': 395.774,\n        'solar': 0.014,\n        'wind': 20.33,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 103.514,\n        'coal': 1251.716,\n        'gas': 1924.121,\n        'hydro': 7942.118,\n        'oil': 428.115,\n        'solar': 0.0,\n        'wind': 21.733,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.901,\n        'coal': 1337.312,\n        'gas': 1938.508,\n        'hydro': 7563.131,\n        'oil': 428.876,\n        'solar': 0.0,\n        'wind': 16.094,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.402,\n        'coal': 1403.97,\n        'gas': 1889.797,\n        'hydro': 7107.675,\n        'oil': 401.458,\n        'solar': 0.0,\n        'wind': 17.331,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.834,\n        'coal': 1465.961,\n        'gas': 1801.324,\n        'hydro': 6751.229,\n        'oil': 192.292,\n        'solar': 0.0,\n        'wind': 12.746,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.938,\n        'coal': 1468.627,\n        'gas': 1818.301,\n        'hydro': 6172.493,\n        'oil': 166.669,\n        'solar': 0.0,\n        'wind': 6.356,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.986,\n        'coal': 1466.896,\n        'gas': 1867.806,\n        'hydro': 5586.838,\n        'oil': 166.664,\n        'solar': 0.0,\n        'wind': 6.05,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.98,\n        'coal': 1471.751,\n        'gas': 1858.058,\n        'hydro': 5368.16,\n        'oil': 166.805,\n        'solar': 0.0,\n        'wind': 6.363,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.592,\n        'coal': 1469.436,\n        'gas': 1700.74,\n        'hydro': 5307.241,\n        'oil': 166.719,\n        'solar': 0.0,\n        'wind': 8.859,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.012,\n        'coal': 1471.829,\n        'gas': 1633.966,\n        'hydro': 5224.75,\n        'oil': 166.665,\n        'solar': 0.0,\n        'wind': 11.138,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.156,\n        'coal': 1467.141,\n        'gas': 1687.998,\n        'hydro': 5240.654,\n        'oil': 201.661,\n        'solar': 0.0,\n        'wind': 14.154,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.498,\n        'coal': 1458.905,\n        'gas': 1809.163,\n        'hydro': 5212.833,\n        'oil': 267.401,\n        'solar': 1.177,\n        'wind': 12.089,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n  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    'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 102.167,\n        'coal': 1432.517,\n        'gas': 1793.603,\n        'hydro': 5454.424,\n        'oil': 366.872,\n        'solar': 885.163,\n        'wind': 18.578,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 108.104,\n        'coal': 1318.192,\n        'gas': 1883.209,\n        'hydro': 5439.874,\n        'oil': 367.083,\n        'solar': 1181.614,\n        'wind': 16.182,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.417,\n        'coal': 1298.894,\n        'gas': 1882.214,\n        'hydro': 5638.407,\n        'oil': 366.622,\n        'solar': 1347.685,\n        'wind': 19.597,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n    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12, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.762,\n        'coal': 1191.171,\n        'gas': 1876.796,\n        'hydro': 6097.13,\n        'oil': 400.533,\n        'solar': 1350.369,\n        'wind': 16.043,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.287,\n        'coal': 1190.85,\n        'gas': 1876.437,\n        'hydro': 6384.418,\n        'oil': 440.978,\n        'solar': 1259.377,\n        'wind': 21.175,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.361,\n        'coal': 1194.01,\n        'gas': 1885.921,\n        'hydro': 6671.173,\n        'oil': 445.482,\n        'solar': 1073.731,\n        'wind': 20.395,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.535,\n        'coal': 1151.083,\n        'gas': 1879.943,\n        'hydro': 7172.341,\n        'oil': 470.636,\n        'solar': 471.553,\n        'wind': 19.076,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': 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0.012,\n        'wind': 21.143,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.217,\n        'coal': 1067.194,\n        'gas': 1885.819,\n        'hydro': 8129.266,\n        'oil': 486.051,\n        'solar': 0.0,\n        'wind': 20.882,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.859,\n        'coal': 1056.816,\n        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datetime.datetime(2024, 12, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.245,\n        'coal': 1064.096,\n        'gas': 1769.441,\n        'hydro': 6092.997,\n        'oil': 299.919,\n        'solar': 0.0,\n        'wind': 2.99,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.45,\n        'coal': 1073.782,\n        'gas': 1506.228,\n        'hydro': 6136.75,\n        'oil': 154.73,\n        'solar': 0.0,\n        'wind': 7.629,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.861,\n        'coal': 1086.445,\n        'gas': 1187.96,\n        'hydro': 6306.781,\n        'oil': 64.119,\n        'solar': 0.0,\n        'wind': 9.336,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.223,\n        'coal': 1101.074,\n        'gas': 1122.836,\n        'hydro': 6241.415,\n        'oil': 64.036,\n        'solar': 0.0,\n        'wind': 4.874,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 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6726.48,\n        'oil': 65.673,\n        'solar': 735.482,\n        'wind': 1.583,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 109.354,\n        'coal': 1020.102,\n        'gas': 1118.739,\n        'hydro': 6805.916,\n        'oil': 64.168,\n        'solar': 1132.728,\n        'wind': 8.695,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 111.728,\n        'coal': 1028.846,\n        'gas': 1109.109,\n        'hydro': 6837.103,\n        'oil': 69.141,\n        'solar': 1319.456,\n        'wind': 16.892,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 103.092,\n        'coal': 1036.25,\n        'gas': 1048.9,\n        'hydro': 6998.306,\n        'oil': 127.982,\n        'solar': 1383.136,\n        'wind': 17.02,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 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dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.873,\n        'coal': 1091.003,\n        'gas': 1210.379,\n        'hydro': 6975.307,\n        'oil': 166.942,\n        'solar': 1399.439,\n        'wind': 19.24,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 111.186,\n        'coal': 1098.803,\n        'gas': 1292.976,\n        'hydro': 7138.448,\n        'oil': 167.028,\n        'solar': 1350.488,\n        'wind': 21.311,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 112.001,\n        'coal': 1098.151,\n        'gas': 1295.032,\n        'hydro': 7565.27,\n        'oil': 166.949,\n        'solar': 979.591,\n        'wind': 22.505,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 109.591,\n        'coal': 1102.349,\n        'gas': 1372.864,\n        'hydro': 7840.634,\n        'oil': 166.891,\n        'solar': 435.582,\n        'wind': 22.328,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 111.117,\n        'coal': 1103.995,\n        'gas': 1460.752,\n        'hydro': 8075.853,\n        'oil': 166.899,\n        'solar': 30.794,\n        'wind': 20.981,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.034,\n        'coal': 1102.042,\n        'gas': 1606.21,\n        'hydro': 8429.997,\n        'oil': 166.554,\n        'solar': 0.026,\n        'wind': 21.636,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.195,\n        'coal': 1103.08,\n        'gas': 1615.873,\n        'hydro': 8375.276,\n        'oil': 167.124,\n        'solar': 0.0,\n        'wind': 19.94,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 111.529,\n        'coal': 1102.693,\n        'gas': 1545.607,\n        'hydro': 8192.254,\n        'oil': 167.086,\n        'solar': 0.0,\n        'wind': 15.843,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.986,\n        'coal': 1101.721,\n        'gas': 1515.889,\n        'hydro': 7833.081,\n        'oil': 109.296,\n        'solar': 0.0,\n        'wind': 13.441,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.085,\n        'coal': 1099.815,\n        'gas': 1481.51,\n        'hydro': 7444.948,\n        'oil': 64.471,\n        'solar': 0.0,\n        'wind': 16.18,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 6, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.879,\n        'coal': 1101.157,\n        'gas': 1499.157,\n        'hydro': 6882.346,\n        'oil': 64.542,\n        'solar': 0.0,\n        'wind': 14.147,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.22,\n        'coal': 1102.364,\n        'gas': 1600.665,\n        'hydro': 6344.692,\n        'oil': 64.547,\n        'solar': 0.0,\n        'wind': 7.278,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.749,\n        'coal': 1102.6,\n        'gas': 1552.604,\n        'hydro': 6065.305,\n        'oil': 64.622,\n        'solar': 0.0,\n        'wind': 4.967,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': 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 'wind': 2.607,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.628,\n        'coal': 1087.977,\n        'gas': 1566.094,\n        'hydro': 5665.006,\n        'oil': 64.468,\n        'solar': 0.0,\n        'wind': 2.552,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.405,\n        'coal': 1060.983,\n        'gas': 1568.538,\n   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14.45,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 109.338,\n        'coal': 1073.591,\n        'gas': 1646.174,\n        'hydro': 6175.738,\n        'oil': 64.899,\n        'solar': 1094.281,\n        'wind': 18.385,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.786,\n        'coal': 1083.52,\n        'gas': 1688.623,\n        'hydro': 6617.379,\n        'oil': 64.732,\n        'solar': 552.811,\n        'wind': 21.52,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 101.489,\n        'coal': 1085.26,\n        'gas': 1794.346,\n        'hydro': 7052.733,\n        'oil': 64.842,\n        'solar': 43.309,\n        'wind': 20.803,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': 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12, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 112.261,\n        'coal': 1082.06,\n        'gas': 1716.686,\n        'hydro': 6997.992,\n        'oil': 64.459,\n        'solar': 0.0,\n        'wind': 12.55,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.146,\n        'coal': 1028.552,\n        'gas': 1754.237,\n        'hydro': 6637.179,\n        'oil': 64.501,\n        'solar': 0.0,\n        'wind': 8.777,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.729,\n        'coal': 1046.949,\n        'gas': 1756.904,\n        'hydro': 6256.905,\n        'oil': 64.718,\n        'solar': 0.0,\n        'wind': 15.812,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.433,\n        'coal': 1050.493,\n        'gas': 1792.821,\n        'hydro': 5935.254,\n        'oil': 64.6,\n        'solar': 0.0,\n        'wind': 10.425,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.749,\n        'coal': 1053.239,\n        'gas': 1626.028,\n        'hydro': 5653.685,\n        'oil': 63.719,\n        'solar': 0.0,\n        'wind': 9.749,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.934,\n        'coal': 1080.963,\n        'gas': 1603.83,\n        'hydro': 5405.327,\n        'oil': 63.651,\n        'solar': 0.0,\n        'wind': 9.519,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.812,\n        'coal': 1110.381,\n        'gas': 1254.575,\n        'hydro': 5594.112,\n        'oil': 64.076,\n        'solar': 0.0,\n        'wind': 7.768,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.282,\n        'coal': 1108.382,\n        'gas': 1091.404,\n        'hydro': 5477.319,\n        'oil': 63.902,\n        'solar': 0.0,\n        'wind': 8.642,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.438,\n        'coal': 1108.012,\n        'gas': 1087.103,\n        'hydro': 5515.798,\n        'oil': 64.454,\n        'solar': 0.0,\n        'wind': 10.157,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.008,\n        'coal': 1104.228,\n        'gas': 986.151,\n        'hydro': 5485.26,\n        'oil': 64.662,\n        'solar': 1.128,\n        'wind': 12.514,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.457,\n        'coal': 1096.301,\n        'gas': 928.02,\n        'hydro': 5208.009,\n        'oil': 76.609,\n        'solar': 150.291,\n        'wind': 13.518,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 7, 0, 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21.617,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 112.984,\n        'coal': 1141.951,\n        'gas': 857.28,\n        'hydro': 5320.008,\n        'oil': 268.19,\n        'solar': 1537.935,\n        'wind': 22.775,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 115.903,\n        'coal': 1150.667,\n        'gas': 856.687,\n        'hydro': 5379.679,\n        'oil': 270.106,\n        'solar': 1441.286,\n        'wind': 22.491,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.265,\n        'coal': 1153.215,\n        'gas': 956.215,\n        'hydro': 5570.141,\n        'oil': 269.739,\n        'solar': 1177.919,\n        'wind': 22.129,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 103.135,\n        'coal': 1152.349,\n        'gas': 1090.317,\n        'hydro': 5973.877,\n        'oil': 269.063,\n        'solar': 584.3,\n        'wind': 22.171,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.218,\n        'coal': 1154.739,\n        'gas': 1309.874,\n        'hydro': 6341.083,\n        'oil': 269.356,\n        'solar': 46.463,\n        'wind': 22.162,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.553,\n        'coal': 1154.015,\n        'gas': 1419.461,\n        'hydro': 7156.03,\n        'oil': 199.905,\n        'solar': 0.016,\n        'wind': 22.3,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 115.777,\n        'coal': 1151.266,\n        'gas': 1609.897,\n        'hydro': 7106.554,\n        'oil': 167.243,\n        'solar': 0.0,\n        'wind': 21.691,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.938,\n        'coal': 1168.473,\n        'gas': 1572.974,\n        'hydro': 6378.133,\n        'oil': 166.917,\n        'solar': 0.0,\n        'wind': 16.357,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.141,\n        'coal': 1177.561,\n        'gas': 1500.708,\n        'hydro': 6012.338,\n        'oil': 181.56,\n        'solar': 0.0,\n  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dict({\n        'biomass': 114.8,\n        'coal': 1215.326,\n        'gas': 1875.173,\n        'hydro': 4253.728,\n        'oil': 269.236,\n        'solar': 0.0,\n        'wind': 8.611,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.319,\n        'coal': 1191.614,\n        'gas': 1863.039,\n        'hydro': 4412.445,\n        'oil': 269.347,\n        'solar': 0.0,\n        'wind': 8.785,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.703,\n        'coal': 1182.48,\n        'gas': 1932.26,\n        'hydro': 4650.287,\n        'oil': 268.219,\n        'solar': 0.841,\n        'wind': 12.194,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.321,\n        'coal': 1181.458,\n        'gas': 1996.039,\n        'hydro': 4762.779,\n        'oil': 302.181,\n        'solar': 132.232,\n        'wind': 6.32,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n    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18.918,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.31,\n        'coal': 1146.495,\n        'gas': 2009.575,\n        'hydro': 5660.638,\n        'oil': 376.821,\n        'solar': 1450.668,\n        'wind': 20.037,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.893,\n        'coal': 1128.114,\n        'gas': 2006.179,\n        'hydro': 5806.638,\n        'oil': 377.146,\n        'solar': 1383.457,\n        'wind': 19.522,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 110.698,\n        'coal': 1166.886,\n        'gas': 1995.558,\n        'hydro': 5943.484,\n        'oil': 386.488,\n        'solar': 1377.869,\n        'wind': 21.142,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 108.608,\n        'coal': 1179.615,\n        'gas': 1966.313,\n        'hydro': 6243.686,\n        'oil': 396.08,\n        'solar': 1305.921,\n        'wind': 23.002,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 108.87,\n        'coal': 1184.424,\n        'gas': 1982.772,\n        'hydro': 6501.278,\n        'oil': 426.307,\n        'solar': 1009.866,\n        'wind': 23.006,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.285,\n        'coal': 1218.026,\n        'gas': 1996.858,\n        'hydro': 6805.825,\n        'oil': 453.715,\n        'solar': 512.764,\n        'wind': 22.999,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 110.193,\n        'coal': 1247.389,\n        'gas': 1993.741,\n        'hydro': 7039.803,\n        'oil': 471.033,\n        'solar': 40.682,\n        'wind': 23.026,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 110.466,\n        'coal': 1266.86,\n        'gas': 1995.268,\n        'hydro': 7682.418,\n        'oil': 433.631,\n        'solar': 0.016,\n        'wind': 22.737,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 112.141,\n        'coal': 1260.556,\n        'gas': 1997.07,\n        'hydro': 7678.314,\n        'oil': 441.493,\n        'solar': 0.0,\n        'wind': 22.555,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.85,\n        'coal': 1257.137,\n        'gas': 2004.354,\n        'hydro': 7462.55,\n        'oil': 439.708,\n        'solar': 0.0,\n        'wind': 22.644,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.288,\n        'coal': 1257.56,\n        'gas': 2003.986,\n        'hydro': 7051.845,\n        'oil': 428.487,\n        'solar': 0.0,\n        'wind': 21.874,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 115.608,\n        'coal': 1263.013,\n        'gas': 2003.889,\n        'hydro': 6505.086,\n        'oil': 376.689,\n        'solar': 0.0,\n        'wind': 20.916,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.912,\n        'coal': 1269.053,\n        'gas': 2001.725,\n        'hydro': 5908.088,\n        'oil': 420.562,\n        'solar': 0.0,\n        'wind': 21.044,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.998,\n        'coal': 1268.705,\n        'gas': 1856.563,\n        'hydro': 5579.12,\n        'oil': 423.213,\n        'solar': 0.0,\n        'wind': 18.999,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.033,\n        'coal': 1268.743,\n        'gas': 1843.93,\n        'hydro': 5310.939,\n        'oil': 409.317,\n        'solar': 0.0,\n        'wind': 14.94,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.226,\n        'coal': 1262.674,\n        'gas': 1895.171,\n        'hydro': 5070.76,\n        'oil': 366.231,\n        'solar': 0.0,\n        'wind': 9.906,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.556,\n        'coal': 1266.944,\n        'gas': 1893.282,\n        'hydro': 4981.198,\n        'oil': 308.797,\n        'solar': 0.0,\n        'wind': 6.311,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.512,\n        'coal': 1254.658,\n        'gas': 1846.536,\n        'hydro': 5037.771,\n        'oil': 398.78,\n        'solar': 0.0,\n        'wind': 3.26,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.937,\n        'coal': 1252.716,\n        'gas': 1847.719,\n        'hydro': 5284.684,\n        'oil': 391.987,\n        'solar': 0.206,\n        'wind': 4.773,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.518,\n        'coal': 1245.42,\n        'gas': 1865.36,\n        'hydro': 5375.596,\n        'oil': 421.438,\n        'solar': 114.413,\n        'wind': 5.362,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': 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989.839,\n        'wind': 12.747,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.698,\n        'coal': 1241.094,\n        'gas': 1926.642,\n        'hydro': 5431.348,\n        'oil': 371.364,\n        'solar': 1394.832,\n        'wind': 20.841,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.945,\n        'coal': 1247.117,\n 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22.778,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 111.562,\n        'coal': 1395.422,\n        'gas': 2094.557,\n        'hydro': 7655.905,\n        'oil': 442.948,\n        'solar': 0.017,\n        'wind': 22.395,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.266,\n        'coal': 1416.333,\n        'gas': 2203.357,\n   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dict({\n        'biomass': 117.052,\n        'coal': 1405.262,\n        'gas': 2238.666,\n        'hydro': 6893.314,\n        'oil': 309.931,\n        'solar': 0.02,\n        'wind': 19.196,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.33,\n        'coal': 1402.02,\n        'gas': 2173.719,\n        'hydro': 6327.264,\n        'oil': 302.939,\n        'solar': 0.02,\n        'wind': 17.331,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 10, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.917,\n        'coal': 1398.077,\n        'gas': 2066.659,\n        'hydro': 5699.835,\n        'oil': 303.572,\n        'solar': 0.022,\n        'wind': 14.13,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.858,\n        'coal': 1399.017,\n        'gas': 2057.653,\n        'hydro': 5324.14,\n        'oil': 177.602,\n        'solar': 0.027,\n        'wind': 10.159,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.0,\n        'coal': 1400.563,\n        'gas': 2077.191,\n        'hydro': 5038.948,\n        'oil': 162.54,\n        'solar': 0.0,\n        'wind': 1.64,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.409,\n        'coal': 1403.465,\n        'gas': 2028.909,\n        'hydro': 4746.995,\n        'oil': 166.539,\n        'solar': 0.0,\n        'wind': 0.051,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': 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     'wind': 5.899,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.876,\n        'coal': 1399.125,\n        'gas': 2043.881,\n        'hydro': 4960.726,\n        'oil': 266.882,\n        'solar': 0.659,\n        'wind': 5.879,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.518,\n        'coal': 1401.165,\n        'gas': 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'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 99.066,\n        'coal': 1417.227,\n        'gas': 2027.473,\n        'hydro': 6331.296,\n        'oil': 388.382,\n        'solar': 1193.414,\n        'wind': 22.556,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 96.209,\n        'coal': 1410.347,\n        'gas': 2043.194,\n        'hydro': 6486.774,\n        'oil': 451.864,\n        'solar': 950.208,\n        'wind': 22.857,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 101.054,\n        'coal': 1416.022,\n        'gas': 2083.312,\n        'hydro': 6788.801,\n        'oil': 506.957,\n        'solar': 396.5,\n        'wind': 22.689,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 104.644,\n        'coal': 1398.164,\n        'gas': 2133.153,\n        'hydro': 7086.889,\n        'oil': 408.06,\n        'solar': 32.521,\n        'wind': 22.245,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 106.634,\n        'coal': 1409.031,\n        'gas': 2152.643,\n        'hydro': 7691.42,\n        'oil': 320.772,\n        'solar': 0.015,\n        'wind': 18.428,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 101.437,\n        'coal': 1410.035,\n        'gas': 2224.689,\n        'hydro': 7635.196,\n        'oil': 301.813,\n        'solar': 0.0,\n        'wind': 17.516,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 105.483,\n        'coal': 1430.674,\n        'gas': 2148.196,\n        'hydro': 7489.741,\n        'oil': 267.41,\n        'solar': 0.0,\n        'wind': 17.738,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.132,\n        'coal': 1451.728,\n        'gas': 2224.954,\n        'hydro': 6969.12,\n        'oil': 305.614,\n        'solar': 0.0,\n        'wind': 19.199,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 101.27,\n        'coal': 1456.886,\n        'gas': 2230.131,\n        'hydro': 6381.368,\n        'oil': 307.32,\n        'solar': 0.0,\n        'wind': 16.924,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 11, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 103.23,\n        'coal': 1460.815,\n        'gas': 2240.045,\n        'hydro': 5784.95,\n        'oil': 307.441,\n        'solar': 0.0,\n        'wind': 11.351,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 110.498,\n        'coal': 1460.903,\n        'gas': 2234.99,\n        'hydro': 5178.125,\n        'oil': 221.887,\n        'solar': 0.0,\n        'wind': 7.495,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.606,\n        'coal': 1460.192,\n        'gas': 2235.81,\n        'hydro': 4971.975,\n        'oil': 163.922,\n        'solar': 0.0,\n        'wind': 4.328,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 104.621,\n        'coal': 1437.892,\n        'gas': 2219.754,\n        'hydro': 4645.175,\n        'oil': 188.263,\n        'solar': 0.0,\n        'wind': 3.768,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 106.299,\n        'coal': 1425.533,\n        'gas': 2098.733,\n        'hydro': 4426.792,\n        'oil': 198.075,\n        'solar': 0.0,\n        'wind': 9.967,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 110.952,\n        'coal': 1439.435,\n        'gas': 2241.376,\n        'hydro': 4713.313,\n        'oil': 268.352,\n        'solar': 0.0,\n        'wind': 17.92,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.012,\n        'coal': 1445.652,\n        'gas': 2368.948,\n        'hydro': 4749.116,\n        'oil': 324.972,\n        'solar': 0.541,\n        'wind': 15.693,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.458,\n        'coal': 1447.363,\n        'gas': 2356.325,\n        'hydro': 4839.379,\n        'oil': 393.685,\n        'solar': 112.489,\n        'wind': 1.582,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.444,\n        'coal': 1454.394,\n        'gas': 2331.143,\n        'hydro': 4963.67,\n        'oil': 375.55,\n        'solar': 558.135,\n        'wind': 1.928,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 94.678,\n        'coal': 1457.172,\n        'gas': 2374.632,\n        'hydro': 4847.519,\n        'oil': 377.894,\n        'solar': 979.374,\n        'wind': 3.358,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 92.686,\n        'coal': 1457.062,\n        'gas': 2339.239,\n        'hydro': 5018.765,\n        'oil': 432.734,\n        'solar': 1079.794,\n        'wind': 5.737,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 95.632,\n        'coal': 1463.549,\n        'gas': 2318.975,\n        'hydro': 5149.586,\n        'oil': 433.658,\n        'solar': 1296.782,\n        'wind': 8.065,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 104.647,\n        'coal': 1471.905,\n        'gas': 2330.07,\n        'hydro': 5388.505,\n        'oil': 460.736,\n        'solar': 1339.589,\n        'wind': 11.044,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 109.994,\n        'coal': 1470.941,\n        'gas': 2308.674,\n        'hydro': 5442.695,\n        'oil': 457.072,\n        'solar': 1288.011,\n        'wind': 16.673,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 112.065,\n        'coal': 1473.981,\n        'gas': 2308.876,\n        'hydro': 5640.405,\n        'oil': 468.181,\n        'solar': 1180.004,\n        'wind': 22.118,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.751,\n        'coal': 1473.992,\n        'gas': 2287.473,\n        'hydro': 5841.381,\n        'oil': 494.045,\n        'solar': 1161.037,\n        'wind': 21.883,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.352,\n        'coal': 1399.396,\n        'gas': 2315.627,\n        'hydro': 6089.561,\n        'oil': 470.169,\n        'solar': 973.512,\n        'wind': 21.702,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.418,\n        'coal': 1278.774,\n        'gas': 2435.313,\n        'hydro': 6601.543,\n        'oil': 305.34,\n        'solar': 484.234,\n        'wind': 21.206,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.803,\n        'coal': 1280.131,\n        'gas': 2461.355,\n        'hydro': 6867.43,\n        'oil': 297.265,\n        'solar': 39.534,\n        'wind': 15.082,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 130.192,\n        'coal': 1280.314,\n        'gas': 2459.948,\n        'hydro': 7465.642,\n        'oil': 280.259,\n        'solar': 0.021,\n        'wind': 12.553,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.389,\n        'coal': 1277.548,\n        'gas': 2442.248,\n        'hydro': 7455.91,\n        'oil': 280.06,\n        'solar': 0.0,\n        'wind': 9.735,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.244,\n        'coal': 1277.31,\n        'gas': 2432.687,\n        'hydro': 7184.536,\n        'oil': 281.075,\n        'solar': 0.0,\n        'wind': 8.625,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.633,\n        'coal': 1282.648,\n        'gas': 2420.316,\n        'hydro': 6726.26,\n        'oil': 295.779,\n        'solar': 0.0,\n        'wind': 7.911,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.028,\n        'coal': 1305.729,\n        'gas': 2419.016,\n        'hydro': 6116.256,\n        'oil': 295.806,\n        'solar': 0.0,\n        'wind': 10.345,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 12, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.951,\n        'coal': 1343.891,\n        'gas': 2463.208,\n        'hydro': 5501.85,\n        'oil': 294.379,\n        'solar': 0.0,\n        'wind': 7.759,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.776,\n        'coal': 1370.942,\n        'gas': 2459.73,\n        'hydro': 5067.794,\n        'oil': 259.275,\n        'solar': 0.0,\n        'wind': 7.533,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.949,\n        'coal': 1376.146,\n        'gas': 2358.056,\n        'hydro': 4778.289,\n        'oil': 302.471,\n        'solar': 0.0,\n        'wind': 12.302,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.815,\n        'coal': 1375.883,\n        'gas': 2318.411,\n        'hydro': 4644.021,\n        'oil': 263.316,\n        'solar': 0.0,\n        'wind': 9.784,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 136.015,\n        'coal': 1386.62,\n        'gas': 2323.764,\n        'hydro': 4460.392,\n        'oil': 309.773,\n        'solar': 0.0,\n        'wind': 5.139,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 138.612,\n        'coal': 1394.939,\n        'gas': 2327.326,\n        'hydro': 4459.052,\n        'oil': 365.75,\n        'solar': 0.0,\n        'wind': 5.724,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.441,\n        'coal': 1411.277,\n        'gas': 2330.784,\n        'hydro': 4569.921,\n        'oil': 429.987,\n        'solar': 0.288,\n        'wind': 8.687,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.993,\n        'coal': 1375.81,\n        'gas': 2333.902,\n        'hydro': 4744.769,\n        'oil': 426.749,\n        'solar': 114.093,\n        'wind': 9.478,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.752,\n        'coal': 1374.771,\n        'gas': 2336.85,\n        'hydro': 4703.822,\n        'oil': 452.601,\n        'solar': 711.804,\n        'wind': 8.53,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.065,\n        'coal': 1373.367,\n        'gas': 2331.47,\n        'hydro': 4844.691,\n        'oil': 426.455,\n        'solar': 1082.174,\n        'wind': 6.231,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.904,\n        'coal': 1390.784,\n        'gas': 2281.798,\n        'hydro': 4862.238,\n        'oil': 431.55,\n        'solar': 1340.411,\n        'wind': 13.234,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.496,\n        'coal': 1417.603,\n        'gas': 2333.137,\n        'hydro': 5010.789,\n        'oil': 447.474,\n        'solar': 1403.719,\n        'wind': 10.048,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.769,\n        'coal': 1430.666,\n        'gas': 2339.779,\n        'hydro': 5234.519,\n        'oil': 465.56,\n        'solar': 1425.796,\n        'wind': 15.414,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 130.938,\n        'coal': 1435.398,\n        'gas': 2333.754,\n        'hydro': 5267.109,\n        'oil': 464.838,\n        'solar': 1320.032,\n        'wind': 21.282,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.597,\n        'coal': 1435.523,\n        'gas': 2330.353,\n        'hydro': 5353.475,\n        'oil': 463.555,\n        'solar': 1315.584,\n        'wind': 22.577,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.728,\n        'coal': 1435.566,\n        'gas': 2325.406,\n        'hydro': 5638.893,\n        'oil': 463.682,\n        'solar': 1234.623,\n        'wind': 22.564,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n   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15.751,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.829,\n        'coal': 1466.459,\n        'gas': 2338.642,\n        'hydro': 6980.267,\n        'oil': 474.76,\n        'solar': 0.0,\n        'wind': 12.582,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 13, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.371,\n        'coal': 1465.906,\n        'gas': 2381.268,\n      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'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.514,\n        'coal': 1459.777,\n        'gas': 2442.719,\n        'hydro': 4529.613,\n        'oil': 66.1,\n        'solar': 0.0,\n        'wind': 2.328,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 136.035,\n        'coal': 1462.402,\n        'gas': 2396.161,\n        'hydro': 4383.928,\n        'oil': 68.203,\n        'solar': 0.0,\n        'wind': 1.755,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      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'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.787,\n        'coal': 1467.362,\n        'gas': 2152.068,\n        'hydro': 4251.327,\n        'oil': 59.692,\n        'solar': 113.209,\n        'wind': 2.94,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 136.225,\n        'coal': 1469.261,\n        'gas': 2288.143,\n        'hydro': 3980.829,\n        'oil': 59.771,\n        'solar': 723.918,\n        'wind': 0.066,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 138.076,\n        'coal': 1465.469,\n        'gas': 2099.41,\n        'hydro': 4216.825,\n        'oil': 59.681,\n        'solar': 1197.414,\n        'wind': 0.604,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.114,\n        'coal': 1468.442,\n        'gas': 2095.169,\n        'hydro': 4372.482,\n        'oil': 59.468,\n        'solar': 1371.667,\n        'wind': 1.808,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.53,\n        'coal': 1468.859,\n        'gas': 2235.757,\n        'hydro': 4427.424,\n        'oil': 59.829,\n        'solar': 1450.586,\n        'wind': 2.498,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 11, 0, 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18.793,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 134.911,\n        'coal': 1467.507,\n        'gas': 2375.414,\n        'hydro': 5580.212,\n        'oil': 108.823,\n        'solar': 43.704,\n        'wind': 18.738,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.248,\n        'coal': 1474.354,\n        'gas': 2502.486,\n        'hydro': 6304.615,\n        'oil': 253.166,\n        'solar': 0.008,\n        'wind': 15.614,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.323,\n        'coal': 1473.313,\n        'gas': 2511.491,\n        'hydro': 6312.958,\n        'oil': 367.3,\n        'solar': 0.002,\n        'wind': 11.261,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.322,\n        'coal': 1469.684,\n        'gas': 2514.126,\n        'hydro': 6077.153,\n        'oil': 341.143,\n        'solar': 0.002,\n        'wind': 6.948,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.898,\n        'coal': 1476.096,\n        'gas': 2513.796,\n        'hydro': 5727.661,\n        'oil': 336.994,\n        'solar': 0.002,\n        'wind': 3.116,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.793,\n        'coal': 1479.929,\n        'gas': 2514.071,\n        'hydro': 5279.042,\n        'oil': 337.212,\n        'solar': 0.002,\n        'wind': 2.427,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.562,\n        'coal': 1478.495,\n        'gas': 2492.552,\n        'hydro': 4846.238,\n        'oil': 345.872,\n        'solar': 0.002,\n        'wind': 3.748,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.802,\n        'coal': 1483.335,\n        'gas': 2264.632,\n        'hydro': 4770.501,\n        'oil': 267.483,\n        'solar': 0.002,\n        'wind': 2.366,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.063,\n        'coal': 1475.874,\n        'gas': 2228.933,\n        'hydro': 4475.16,\n        'oil': 263.937,\n        'solar': 0.002,\n        'wind': 0.255,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': 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datetime.datetime(2024, 12, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.602,\n        'coal': 1341.549,\n        'gas': 1228.274,\n        'hydro': 4201.704,\n        'oil': 180.378,\n        'solar': 1288.383,\n        'wind': 2.712,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.347,\n        'coal': 1340.718,\n        'gas': 1233.924,\n        'hydro': 4304.685,\n        'oil': 185.185,\n        'solar': 1434.358,\n        'wind': 2.314,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      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   'solar': 1167.388,\n        'wind': 21.608,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 130.728,\n        'coal': 1349.459,\n        'gas': 1797.389,\n        'hydro': 4560.773,\n        'oil': 183.665,\n        'solar': 944.907,\n        'wind': 21.971,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 130.838,\n        'coal': 1352.684,\n        'gas': 1961.372,\n        'hydro': 4883.582,\n        'oil': 188.184,\n        'solar': 436.655,\n        'wind': 19.395,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.085,\n        'coal': 1359.661,\n        'gas': 2120.583,\n        'hydro': 5154.711,\n        'oil': 208.043,\n        'solar': 43.798,\n        'wind': 19.711,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 15, 18, 0, 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   'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.461,\n        'coal': 1359.179,\n        'gas': 2477.374,\n        'hydro': 5066.079,\n        'oil': 505.474,\n        'solar': 0.0,\n        'wind': 5.745,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.464,\n        'coal': 1355.275,\n        'gas': 2323.609,\n        'hydro': 4860.59,\n        'oil': 443.595,\n        'solar': 0.0,\n        'wind': 4.836,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.864,\n        'coal': 1357.317,\n        'gas': 2148.845,\n        'hydro': 4812.186,\n        'oil': 309.092,\n        'solar': 0.0,\n        'wind': 6.926,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.533,\n        'coal': 1351.157,\n        'gas': 2155.722,\n        'hydro': 4593.338,\n        'oil': 264.862,\n        'solar': 0.0,\n        'wind': 6.158,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.131,\n        'coal': 1360.021,\n        'gas': 2095.891,\n        'hydro': 4469.037,\n        'oil': 264.985,\n        'solar': 0.0,\n        'wind': 4.308,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 136.777,\n        'coal': 1358.807,\n        'gas': 2095.831,\n        'hydro': 4366.429,\n        'oil': 264.291,\n        'solar': 0.0,\n        'wind': 3.784,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.769,\n        'coal': 1360.154,\n        'gas': 2102.122,\n        'hydro': 4351.73,\n        'oil': 352.311,\n        'solar': 0.0,\n        'wind': 3.343,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 5, 0, 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6.291,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.587,\n        'coal': 1343.79,\n        'gas': 2171.418,\n        'hydro': 5341.315,\n        'oil': 554.439,\n        'solar': 1350.784,\n        'wind': 6.281,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 106.867,\n        'coal': 1348.332,\n        'gas': 2281.712,\n        'hydro': 5059.181,\n        'oil': 586.953,\n        'solar': 1337.282,\n        'wind': 8.098,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.493,\n        'coal': 1349.224,\n        'gas': 2281.52,\n        'hydro': 5173.068,\n        'oil': 665.637,\n        'solar': 1202.338,\n        'wind': 17.77,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      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datetime.datetime(2024, 12, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.446,\n        'coal': 1462.777,\n        'gas': 2454.076,\n        'hydro': 5784.887,\n        'oil': 703.811,\n        'solar': 374.128,\n        'wind': 19.099,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.776,\n        'coal': 1469.398,\n        'gas': 2462.04,\n        'hydro': 5925.272,\n        'oil': 710.181,\n        'solar': 41.088,\n        'wind': 17.013,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 114.254,\n        'coal': 1476.797,\n        'gas': 2470.049,\n        'hydro': 6491.243,\n        'oil': 709.418,\n        'solar': 0.025,\n        'wind': 13.997,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.868,\n        'coal': 1479.109,\n        'gas': 2473.835,\n        'hydro': 6438.356,\n        'oil': 712.393,\n        'solar': 0.0,\n        'wind': 9.522,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.048,\n        'coal': 1479.543,\n        'gas': 2470.18,\n        'hydro': 6243.698,\n        'oil': 715.531,\n        'solar': 0.0,\n        'wind': 10.298,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.517,\n        'coal': 1481.535,\n        'gas': 2464.42,\n        'hydro': 5858.108,\n        'oil': 717.942,\n        'solar': 0.0,\n        'wind': 12.203,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.995,\n        'coal': 1483.927,\n        'gas': 2469.018,\n        'hydro': 5246.107,\n        'oil': 717.979,\n        'solar': 0.0,\n        'wind': 13.3,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 115.876,\n        'coal': 1474.215,\n        'gas': 2416.198,\n        'hydro': 4717.336,\n        'oil': 626.136,\n        'solar': 0.0,\n        'wind': 14.223,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.218,\n        'coal': 1475.202,\n        'gas': 2223.582,\n        'hydro': 4934.78,\n        'oil': 471.661,\n        'solar': 0.0,\n        'wind': 12.392,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n  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datetime.datetime(2024, 12, 17, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.405,\n        'coal': 1473.216,\n        'gas': 1720.711,\n        'hydro': 4528.909,\n        'oil': 265.198,\n        'solar': 0.0,\n        'wind': 11.534,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.594,\n        'coal': 1474.047,\n        'gas': 1694.739,\n        'hydro': 4657.9,\n        'oil': 264.985,\n        'solar': 0.0,\n        'wind': 10.017,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.977,\n        'coal': 1467.738,\n        'gas': 2009.021,\n        'hydro': 4813.056,\n        'oil': 352.989,\n        'solar': 427.205,\n        'wind': 7.046,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.176,\n        'coal': 1463.475,\n        'gas': 1892.475,\n        'hydro': 5143.604,\n        'oil': 471.768,\n        'solar': 911.738,\n        'wind': 7.542,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.916,\n        'coal': 1460.623,\n        'gas': 1878.625,\n        'hydro': 5104.89,\n        'oil': 496.464,\n        'solar': 1248.232,\n        'wind': 7.384,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.472,\n        'coal': 1451.459,\n        'gas': 1926.606,\n        'hydro': 5245.653,\n        'oil': 495.967,\n        'solar': 1331.141,\n        'wind': 13.292,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.908,\n        'coal': 1408.801,\n        'gas': 2063.815,\n        'hydro': 5484.504,\n        'oil': 385.746,\n        'solar': 1373.96,\n        'wind': 16.026,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.249,\n        'coal': 1288.027,\n        'gas': 2081.617,\n        'hydro': 5450.65,\n        'oil': 444.453,\n        'solar': 1366.42,\n        'wind': 19.967,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.917,\n        'coal': 1289.209,\n        'gas': 2094.769,\n        'hydro': 5486.532,\n        'oil': 490.805,\n        'solar': 1265.977,\n        'wind': 21.468,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.975,\n        'coal': 1289.966,\n        'gas': 2133.93,\n        'hydro': 5737.989,\n        'oil': 491.453,\n        'solar': 1126.785,\n        'wind': 22.619,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.032,\n        'coal': 1310.183,\n        'gas': 2291.265,\n        'hydro': 5861.893,\n        'oil': 514.06,\n        'solar': 853.172,\n        'wind': 22.767,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 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22.5,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.49,\n        'coal': 1468.789,\n        'gas': 2458.772,\n        'hydro': 6633.558,\n        'oil': 653.407,\n        'solar': 0.015,\n        'wind': 21.893,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.758,\n        'coal': 1475.638,\n        'gas': 2451.084,\n        'hydro': 6607.979,\n        'oil': 655.265,\n        'solar': 0.0,\n        'wind': 16.336,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.823,\n        'coal': 1475.441,\n        'gas': 2463.312,\n        'hydro': 6399.734,\n        'oil': 658.993,\n        'solar': 0.0,\n        'wind': 14.755,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.642,\n        'coal': 1476.883,\n        'gas': 2468.754,\n        'hydro': 6167.766,\n        'oil': 629.576,\n        'solar': 0.0,\n        'wind': 17.796,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.763,\n        'coal': 1474.947,\n        'gas': 2442.938,\n        'hydro': 5705.678,\n        'oil': 542.47,\n        'solar': 0.0,\n        'wind': 21.451,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 17, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.223,\n        'coal': 1472.662,\n        'gas': 2400.605,\n        'hydro': 5204.329,\n        'oil': 486.991,\n        'solar': 0.0,\n        'wind': 21.202,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.439,\n        'coal': 1473.787,\n        'gas': 2352.146,\n        'hydro': 4841.864,\n        'oil': 183.428,\n        'solar': 0.0,\n        'wind': 16.53,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.49,\n        'coal': 1466.556,\n        'gas': 2301.271,\n        'hydro': 4684.809,\n        'oil': 59.665,\n        'solar': 0.0,\n        'wind': 17.504,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.363,\n        'coal': 1473.868,\n        'gas': 2226.657,\n        'hydro': 4364.87,\n        'oil': 60.375,\n        'solar': 0.0,\n        'wind': 18.015,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.755,\n        'coal': 1472.313,\n        'gas': 2047.277,\n        'hydro': 4403.517,\n        'oil': 60.288,\n        'solar': 0.0,\n        'wind': 17.977,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.953,\n        'coal': 1475.905,\n        'gas': 2050.054,\n        'hydro': 4473.924,\n        'oil': 60.504,\n        'solar': 0.0,\n        'wind': 16.452,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.089,\n        'coal': 1477.977,\n        'gas': 2122.018,\n        'hydro': 4589.032,\n        'oil': 60.362,\n        'solar': 0.227,\n        'wind': 15.023,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.322,\n        'coal': 1474.693,\n        'gas': 2133.922,\n        'hydro': 4761.263,\n    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125.978,\n        'coal': 1479.667,\n        'gas': 2179.897,\n        'hydro': 4764.027,\n        'oil': 222.61,\n        'solar': 1155.504,\n        'wind': 14.828,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.769,\n        'coal': 1497.986,\n        'gas': 2200.813,\n        'hydro': 4984.659,\n        'oil': 271.106,\n        'solar': 1339.679,\n        'wind': 16.305,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 10, 0, 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'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.359,\n        'coal': 1504.38,\n        'gas': 2478.614,\n        'hydro': 5575.26,\n        'oil': 504.873,\n        'solar': 1076.181,\n        'wind': 22.526,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.611,\n        'coal': 1507.366,\n        'gas': 2412.151,\n        'hydro': 5699.075,\n        'oil': 584.645,\n        'solar': 922.167,\n        'wind': 22.965,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.62,\n        'coal': 1506.016,\n        'gas': 2401.597,\n        'hydro': 6109.789,\n        'oil': 600.985,\n        'solar': 410.795,\n        'wind': 22.973,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.53,\n        'coal': 1534.012,\n        'gas': 2458.763,\n        'hydro': 6200.765,\n        'oil': 589.095,\n        'solar': 42.596,\n        'wind': 22.836,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.971,\n        'coal': 1540.55,\n        'gas': 2490.757,\n        'hydro': 6734.233,\n        'oil': 544.422,\n        'solar': 0.017,\n        'wind': 21.566,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.262,\n        'coal': 1541.447,\n        'gas': 2495.72,\n        'hydro': 6642.244,\n        'oil': 562.015,\n        'solar': 0.0,\n        'wind': 21.788,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.492,\n        'coal': 1542.402,\n        'gas': 2469.322,\n        'hydro': 6436.274,\n        'oil': 563.053,\n        'solar': 0.001,\n        'wind': 22.035,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.422,\n        'coal': 1543.797,\n        'gas': 2425.467,\n        'hydro': 6176.019,\n        'oil': 541.865,\n        'solar': 0.0,\n        'wind': 21.817,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.438,\n        'coal': 1544.108,\n        'gas': 2410.796,\n        'hydro': 5568.113,\n        'oil': 463.343,\n        'solar': 0.0,\n        'wind': 19.97,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 18, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.589,\n        'coal': 1542.614,\n        'gas': 2417.956,\n        'hydro': 4956.398,\n        'oil': 440.51,\n        'solar': 0.0,\n        'wind': 20.729,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 130.768,\n        'coal': 1541.951,\n        'gas': 2244.449,\n        'hydro': 4843.389,\n        'oil': 271.598,\n        'solar': 0.0,\n        'wind': 21.95,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.969,\n        'coal': 1525.748,\n        'gas': 2084.717,\n        'hydro': 4813.557,\n        'oil': 160.403,\n        'solar': 0.0,\n        'wind': 19.531,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.328,\n        'coal': 1484.392,\n        'gas': 1924.528,\n        'hydro': 4780.31,\n        'oil': 142.482,\n        'solar': 0.0,\n        'wind': 21.673,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.336,\n        'coal': 1476.109,\n        'gas': 1748.631,\n        'hydro': 4837.085,\n        'oil': 76.349,\n        'solar': 0.0,\n        'wind': 21.156,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.394,\n        'coal': 1476.433,\n        'gas': 1693.134,\n        'hydro': 4946.711,\n        'oil': 60.649,\n        'solar': 0.0,\n        'wind': 20.143,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.818,\n        'coal': 1470.006,\n        'gas': 1852.15,\n        'hydro': 5074.431,\n        'oil': 60.407,\n        'solar': 0.43,\n        'wind': 19.121,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 133.861,\n        'coal': 1468.138,\n        'gas': 2009.521,\n        'hydro': 5063.274,\n        'oil': 60.325,\n        'solar': 60.701,\n        'wind': 21.07,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.646,\n        'coal': 1462.549,\n        'gas': 2096.729,\n        'hydro': 5270.561,\n        'oil': 60.53,\n        'solar': 338.58,\n        'wind': 20.647,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.385,\n        'coal': 1461.878,\n        'gas': 2096.06,\n        'hydro': 5596.781,\n        'oil': 61.236,\n        'solar': 659.627,\n        'wind': 21.745,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 130.569,\n        'coal': 1461.104,\n        'gas': 2090.299,\n        'hydro': 5590.72,\n        'oil': 96.301,\n        'solar': 1107.366,\n        'wind': 21.614,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.307,\n        'coal': 1462.443,\n        'gas': 2072.318,\n        'hydro': 5805.812,\n        'oil': 159.962,\n        'solar': 1200.812,\n        'wind': 21.741,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.017,\n        'coal': 1463.033,\n        'gas': 2061.486,\n        'hydro': 5934.622,\n        'oil': 178.091,\n        'solar': 1261.239,\n        'wind': 19.284,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.827,\n        'coal': 1464.533,\n        'gas': 2015.801,\n        'hydro': 5969.522,\n        'oil': 178.194,\n        'solar': 1252.887,\n        'wind': 17.554,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.3,\n        'coal': 1466.523,\n        'gas': 2086.665,\n        'hydro': 6062.696,\n        'oil': 163.911,\n        'solar': 1129.329,\n        'wind': 16.672,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.09,\n        'coal': 1460.825,\n        'gas': 2081.162,\n        'hydro': 6354.934,\n        'oil': 242.542,\n        'solar': 916.365,\n        'wind': 20.102,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.14,\n        'coal': 1459.47,\n        'gas': 2133.101,\n        'hydro': 6333.25,\n        'oil': 336.409,\n        'solar': 601.901,\n        'wind': 22.385,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.707,\n        'coal': 1462.168,\n        'gas': 2237.48,\n        'hydro': 6441.198,\n        'oil': 386.478,\n        'solar': 277.171,\n        'wind': 22.471,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.398,\n        'coal': 1470.533,\n        'gas': 2286.502,\n        'hydro': 6485.54,\n        'oil': 408.568,\n        'solar': 32.908,\n        'wind': 19.841,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.76,\n        'coal': 1474.873,\n        'gas': 2324.15,\n        'hydro': 7147.121,\n        'oil': 408.778,\n        'solar': 0.018,\n        'wind': 21.762,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.102,\n        'coal': 1475.945,\n        'gas': 2331.531,\n        'hydro': 7061.848,\n        'oil': 414.017,\n        'solar': 0.766,\n        'wind': 17.851,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.103,\n        'coal': 1479.308,\n        'gas': 2334.193,\n        'hydro': 6848.634,\n        'oil': 409.609,\n        'solar': 0.713,\n        'wind': 14.599,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 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    }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 19, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.979,\n        'coal': 1471.437,\n        'gas': 2281.843,\n        'hydro': 5602.237,\n        'oil': 132.279,\n        'solar': 0.0,\n        'wind': 14.572,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.905,\n        'coal': 1425.752,\n        'gas': 2277.38,\n        'hydro': 5369.991,\n        'oil': 77.575,\n        'solar': 0.0,\n        'wind': 12.622,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.225,\n        'coal': 1413.904,\n        'gas': 2309.703,\n        'hydro': 5066.212,\n        'oil': 59.778,\n        'solar': 0.0,\n        'wind': 13.333,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.375,\n        'coal': 1422.918,\n        'gas': 2286.188,\n        'hydro': 4871.069,\n        'oil': 59.883,\n        'solar': 0.001,\n        'wind': 13.795,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.579,\n        'coal': 1424.075,\n        'gas': 2213.917,\n        'hydro': 4810.371,\n        'oil': 59.901,\n        'solar': 0.002,\n        'wind': 12.91,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.187,\n        'coal': 1426.193,\n        'gas': 2214.34,\n        'hydro': 4804.993,\n        'oil': 59.962,\n        'solar': 0.004,\n        'wind': 6.619,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.413,\n        'coal': 1429.349,\n        'gas': 2282.15,\n        'hydro': 4985.078,\n        'oil': 59.783,\n        'solar': 0.392,\n        'wind': 1.251,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 135.918,\n        'coal': 1429.234,\n        'gas': 2313.071,\n        'hydro': 5013.319,\n        'oil': 74.887,\n        'solar': 94.942,\n        'wind': 0.801,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 134.618,\n        'coal': 1403.146,\n        'gas': 2309.754,\n        'hydro': 5054.848,\n        'oil': 154.252,\n        'solar': 545.72,\n        'wind': 0.054,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 132.751,\n        'coal': 1387.945,\n        'gas': 2269.59,\n        'hydro': 5112.417,\n        'oil': 216.47,\n        'solar': 944.243,\n        'wind': 0.643,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.111,\n        'coal': 1383.355,\n        'gas': 2222.508,\n        'hydro': 5269.979,\n        'oil': 260.419,\n        'solar': 1097.946,\n        'wind': 0.744,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.527,\n        'coal': 1383.382,\n        'gas': 2239.707,\n        'hydro': 5357.964,\n        'oil': 300.327,\n        'solar': 1249.472,\n        'wind': 2.863,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.159,\n        'coal': 1384.27,\n        'gas': 2291.932,\n        'hydro': 5569.685,\n        'oil': 388.745,\n        'solar': 1254.512,\n        'wind': 5.563,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.285,\n        'coal': 1385.388,\n        'gas': 2298.319,\n        'hydro': 5478.847,\n        'oil': 483.704,\n        'solar': 1206.24,\n        'wind': 13.16,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.56,\n        'coal': 1384.379,\n        'gas': 2292.948,\n        'hydro': 5558.759,\n        'oil': 503.026,\n        'solar': 1157.917,\n        'wind': 14.928,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.255,\n        'coal': 1388.501,\n        'gas': 2298.815,\n        'hydro': 5863.264,\n        'oil': 557.924,\n        'solar': 873.298,\n        'wind': 19.825,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.423,\n        'coal': 1385.304,\n        'gas': 2292.516,\n        'hydro': 6137.142,\n        'oil': 635.788,\n        'solar': 524.824,\n        'wind': 21.129,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.665,\n        'coal': 1411.843,\n        'gas': 2433.487,\n        'hydro': 6006.548,\n        'oil': 660.958,\n        'solar': 275.525,\n        'wind': 20.147,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.555,\n        'coal': 1421.499,\n        'gas': 2468.401,\n        'hydro': 6121.698,\n        'oil': 643.311,\n        'solar': 30.273,\n        'wind': 18.596,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.424,\n        'coal': 1424.929,\n        'gas': 2479.178,\n        'hydro': 6699.044,\n        'oil': 634.33,\n        'solar': 0.01,\n        'wind': 16.889,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 118.488,\n        'coal': 1423.546,\n        'gas': 2478.291,\n        'hydro': 6640.654,\n        'oil': 636.974,\n        'solar': 0.0,\n        'wind': 17.075,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.164,\n        'coal': 1422.761,\n        'gas': 2480.489,\n        'hydro': 6450.8,\n        'oil': 639.222,\n        'solar': 0.0,\n        'wind': 12.207,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.479,\n        'coal': 1420.689,\n        'gas': 2481.413,\n        'hydro': 6093.168,\n        'oil': 649.01,\n        'solar': 0.0,\n        'wind': 7.368,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.058,\n        'coal': 1423.988,\n        'gas': 2486.955,\n        'hydro': 5597.694,\n        'oil': 526.617,\n        'solar': 0.0,\n        'wind': 3.693,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 20, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.528,\n        'coal': 1421.121,\n        'gas': 2449.519,\n        'hydro': 5253.946,\n        'oil': 398.627,\n        'solar': 0.0,\n        'wind': 3.137,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.82,\n        'coal': 1390.111,\n        'gas': 2406.296,\n        'hydro': 4913.4,\n        'oil': 326.867,\n        'solar': 0.0,\n        'wind': 3.347,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.847,\n        'coal': 1382.801,\n        'gas': 2399.31,\n        'hydro': 4365.103,\n        'oil': 326.511,\n        'solar': 0.0,\n        'wind': 3.315,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.557,\n        'coal': 1393.875,\n        'gas': 2301.503,\n        'hydro': 4286.226,\n        'oil': 191.969,\n        'solar': 0.0,\n        'wind': 3.969,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.968,\n        'coal': 1391.075,\n        'gas': 2289.297,\n        'hydro': 4480.181,\n        'oil': 59.767,\n        'solar': 0.0,\n        'wind': 2.231,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.304,\n        'coal': 1395.62,\n        'gas': 2331.052,\n        'hydro': 4493.439,\n        'oil': 60.137,\n        'solar': 0.0,\n        'wind': 2.374,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.524,\n        'coal': 1393.641,\n        'gas': 2361.212,\n        'hydro': 4537.08,\n        'oil': 103.06,\n        'solar': 0.297,\n        'wind': 3.852,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.427,\n        'coal': 1395.791,\n        'gas': 2427.448,\n        'hydro': 4358.681,\n        'oil': 145.847,\n        'solar': 63.179,\n        'wind': 2.283,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.68,\n        'coal': 1398.403,\n        'gas': 2422.12,\n        'hydro': 4352.43,\n        'oil': 224.286,\n        'solar': 319.843,\n        'wind': 0.438,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.774,\n        'coal': 1405.0,\n        'gas': 2400.585,\n        'hydro': 4457.627,\n        'oil': 320.795,\n        'solar': 651.884,\n        'wind': 0.51,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.211,\n        'coal': 1401.898,\n        'gas': 2383.565,\n        'hydro': 4416.878,\n        'oil': 338.615,\n        'solar': 1018.301,\n        'wind': 2.55,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.934,\n        'coal': 1404.475,\n        'gas': 2406.276,\n        'hydro': 4560.913,\n        'oil': 274.718,\n        'solar': 1140.361,\n        'wind': 3.6,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.903,\n        'coal': 1404.235,\n        'gas': 2405.033,\n        'hydro': 4672.685,\n        'oil': 342.674,\n        'solar': 1183.6,\n        'wind': 1.548,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.096,\n        'coal': 1398.941,\n        'gas': 2409.021,\n        'hydro': 4577.178,\n        'oil': 407.784,\n        'solar': 1167.443,\n        'wind': 9.757,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.727,\n        'coal': 1398.085,\n        'gas': 2411.123,\n        'hydro': 4736.524,\n        'oil': 422.517,\n        'solar': 1070.214,\n        'wind': 20.313,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.732,\n        'coal': 1393.425,\n        'gas': 2419.482,\n        'hydro': 4846.599,\n        'oil': 422.195,\n        'solar': 941.303,\n        'wind': 19.092,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.987,\n        'coal': 1390.339,\n        'gas': 2417.287,\n        'hydro': 5222.997,\n        'oil': 417.87,\n        'solar': 522.718,\n        'wind': 17.564,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.699,\n        'coal': 1389.96,\n        'gas': 2431.744,\n        'hydro': 5325.5,\n        'oil': 474.917,\n        'solar': 266.896,\n        'wind': 17.43,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.324,\n        'coal': 1399.427,\n        'gas': 2494.127,\n        'hydro': 5479.472,\n        'oil': 573.607,\n        'solar': 25.258,\n        'wind': 11.366,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.531,\n        'coal': 1407.213,\n        'gas': 2497.882,\n        'hydro': 6073.865,\n        'oil': 619.998,\n        'solar': 0.009,\n        'wind': 5.118,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.162,\n        'coal': 1398.969,\n        'gas': 2496.765,\n        'hydro': 6014.088,\n        'oil': 644.037,\n        'solar': 0.0,\n        'wind': 5.46,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.998,\n        'coal': 1371.812,\n        'gas': 2497.674,\n        'hydro': 5835.121,\n        'oil': 645.45,\n        'solar': 0.0,\n        'wind': 8.717,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.129,\n        'coal': 1403.271,\n        'gas': 2433.547,\n        'hydro': 5574.042,\n        'oil': 613.717,\n        'solar': 0.0,\n        'wind': 6.084,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.288,\n        'coal': 1409.783,\n        'gas': 2377.943,\n        'hydro': 5247.95,\n        'oil': 580.441,\n        'solar': 0.0,\n        'wind': 6.306,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 21, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.09,\n        'coal': 1405.294,\n        'gas': 2337.393,\n        'hydro': 4798.654,\n        'oil': 614.479,\n        'solar': 0.0,\n        'wind': 12.037,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.783,\n        'coal': 1405.177,\n        'gas': 2165.155,\n        'hydro': 4524.837,\n        'oil': 493.727,\n        'solar': 0.0,\n        'wind': 10.471,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.576,\n        'coal': 1391.122,\n        'gas': 1995.734,\n        'hydro': 4434.818,\n        'oil': 430.226,\n        'solar': 0.0,\n        'wind': 10.145,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.563,\n        'coal': 1396.93,\n        'gas': 2055.049,\n        'hydro': 4131.234,\n        'oil': 428.936,\n        'solar': 0.0,\n        'wind': 11.954,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.272,\n        'coal': 1407.573,\n        'gas': 1961.97,\n        'hydro': 4087.519,\n        'oil': 426.622,\n        'solar': 0.0,\n        'wind': 11.948,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.759,\n        'coal': 1410.695,\n        'gas': 1938.098,\n        'hydro': 4122.767,\n        'oil': 348.665,\n        'solar': 0.0,\n        'wind': 10.192,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.341,\n        'coal': 1417.008,\n        'gas': 1881.142,\n        'hydro': 4119.984,\n        'oil': 319.329,\n        'solar': 0.273,\n        'wind': 8.201,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.028,\n        'coal': 1413.932,\n        'gas': 1874.514,\n        'hydro': 4054.488,\n        'oil': 213.975,\n        'solar': 48.337,\n        'wind': 6.987,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.71,\n        'coal': 1404.395,\n        'gas': 1820.358,\n        'hydro': 4144.338,\n        'oil': 212.114,\n        'solar': 323.339,\n        'wind': 3.578,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.098,\n        'coal': 1401.62,\n        'gas': 1941.934,\n        'hydro': 4099.397,\n        'oil': 165.777,\n        'solar': 594.382,\n        'wind': 2.771,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.926,\n        'coal': 1401.263,\n        'gas': 1965.812,\n        'hydro': 3925.883,\n        'oil': 166.014,\n        'solar': 996.463,\n        'wind': 2.591,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.056,\n        'coal': 1392.98,\n        'gas': 1911.45,\n        'hydro': 4040.808,\n        'oil': 166.577,\n        'solar': 1158.699,\n        'wind': 10.751,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.197,\n        'coal': 1397.012,\n        'gas': 2137.041,\n        'hydro': 4374.794,\n        'oil': 167.44,\n        'solar': 988.588,\n        'wind': 19.525,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.861,\n        'coal': 1403.057,\n        'gas': 2292.676,\n        'hydro': 4227.062,\n        'oil': 228.655,\n        'solar': 1015.81,\n        'wind': 22.173,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.981,\n        'coal': 1403.822,\n        'gas': 2328.16,\n        'hydro': 4319.792,\n        'oil': 165.729,\n        'solar': 870.339,\n        'wind': 22.531,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.954,\n        'coal': 1406.519,\n        'gas': 2470.56,\n        'hydro': 4320.919,\n        'oil': 166.527,\n        'solar': 715.295,\n        'wind': 21.955,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.045,\n        'coal': 1404.498,\n        'gas': 2430.831,\n        'hydro': 4562.111,\n        'oil': 254.56,\n        'solar': 391.45,\n        'wind': 20.227,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.332,\n        'coal': 1406.236,\n        'gas': 2405.644,\n        'hydro': 4776.414,\n        'oil': 226.296,\n        'solar': 217.294,\n        'wind': 17.558,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.193,\n        'coal': 1417.614,\n        'gas': 2352.43,\n        'hydro': 5082.381,\n        'oil': 331.678,\n        'solar': 32.694,\n        'wind': 13.514,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.978,\n        'coal': 1421.309,\n        'gas': 2357.479,\n        'hydro': 5666.625,\n        'oil': 386.581,\n        'solar': 0.002,\n        'wind': 12.001,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.957,\n        'coal': 1406.929,\n        'gas': 2495.044,\n        'hydro': 5503.422,\n        'oil': 454.316,\n        'solar': 0.0,\n        'wind': 12.316,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.41,\n        'coal': 1400.547,\n        'gas': 2483.823,\n        'hydro': 5382.436,\n        'oil': 497.726,\n        'solar': 0.0,\n        'wind': 14.13,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.953,\n        'coal': 1417.597,\n        'gas': 2481.196,\n        'hydro': 5182.911,\n        'oil': 545.898,\n        'solar': 0.0,\n        'wind': 14.049,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.525,\n        'coal': 1397.33,\n        'gas': 2477.861,\n        'hydro': 5002.254,\n        'oil': 426.592,\n        'solar': 0.0,\n        'wind': 9.35,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 22, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.818,\n        'coal': 1410.9,\n        'gas': 2451.015,\n        'hydro': 4636.438,\n        'oil': 346.934,\n        'solar': 0.0,\n        'wind': 10.062,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.756,\n        'coal': 1420.666,\n        'gas': 2241.657,\n        'hydro': 4671.438,\n        'oil': 156.302,\n        'solar': 0.0,\n        'wind': 9.397,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.329,\n        'coal': 1410.261,\n        'gas': 1693.698,\n        'hydro': 5049.58,\n        'oil': 64.682,\n        'solar': 0.0,\n        'wind': 8.499,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.373,\n        'coal': 1419.354,\n        'gas': 1475.763,\n        'hydro': 4973.282,\n        'oil': 64.002,\n        'solar': 0.0,\n        'wind': 12.252,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.423,\n        'coal': 1421.431,\n        'gas': 1097.407,\n        'hydro': 4955.377,\n        'oil': 63.706,\n        'solar': 0.0,\n        'wind': 11.031,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.757,\n        'coal': 1421.087,\n        'gas': 1164.999,\n        'hydro': 4957.079,\n        'oil': 64.478,\n        'solar': 0.0,\n        'wind': 3.671,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      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datetime.datetime(2024, 12, 23, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 120.387,\n        'coal': 1410.843,\n        'gas': 1623.376,\n        'hydro': 5394.127,\n        'oil': 67.079,\n        'solar': 209.092,\n        'wind': 2.732,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.066,\n        'coal': 1407.307,\n        'gas': 1760.426,\n        'hydro': 5620.978,\n        'oil': 125.556,\n        'solar': 479.39,\n        'wind': 2.776,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 104.134,\n        'coal': 1382.899,\n        'gas': 1874.55,\n        'hydro': 5622.895,\n        'oil': 345.14,\n        'solar': 1001.888,\n        'wind': 18.997,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 104.843,\n        'coal': 1367.519,\n        'gas': 1967.941,\n        'hydro': 5578.725,\n        'oil': 367.417,\n        'solar': 916.789,\n        'wind': 22.008,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 112.186,\n        'coal': 1346.385,\n        'gas': 2023.07,\n        'hydro': 5604.99,\n        'oil': 384.797,\n        'solar': 895.785,\n        'wind': 20.134,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 109.054,\n        'coal': 1362.433,\n        'gas': 2197.777,\n        'hydro': 5593.675,\n        'oil': 392.624,\n        'solar': 866.783,\n        'wind': 21.689,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 111.098,\n        'coal': 1328.587,\n        'gas': 2212.655,\n        'hydro': 5878.701,\n        'oil': 351.066,\n        'solar': 642.044,\n        'wind': 21.95,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 115.802,\n        'coal': 1326.615,\n        'gas': 2410.493,\n        'hydro': 5859.442,\n        'oil': 447.848,\n        'solar': 282.467,\n        'wind': 20.585,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.257,\n        'coal': 1338.472,\n        'gas': 2534.007,\n        'hydro': 5833.538,\n        'oil': 431.43,\n        'solar': 38.815,\n        'wind': 22.15,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.231,\n        'coal': 1362.351,\n        'gas': 2529.782,\n        'hydro': 6023.029,\n        'oil': 582.254,\n        'solar': 0.006,\n        'wind': 20.965,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.526,\n        'coal': 1376.27,\n        'gas': 2535.241,\n        'hydro': 6081.292,\n        'oil': 444.525,\n        'solar': 0.0,\n        'wind': 18.245,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.604,\n        'coal': 1375.901,\n        'gas': 2538.268,\n        'hydro': 5932.486,\n        'oil': 413.094,\n        'solar': 0.0,\n        'wind': 18.151,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.043,\n        'coal': 1379.506,\n        'gas': 2535.406,\n        'hydro': 5674.177,\n        'oil': 344.542,\n        'solar': 0.0,\n        'wind': 17.7,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.11,\n        'coal': 1390.59,\n        'gas': 2533.142,\n        'hydro': 5130.95,\n        'oil': 331.906,\n        'solar': 0.0,\n        'wind': 18.572,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 23, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.308,\n        'coal': 1406.626,\n        'gas': 2328.707,\n        'hydro': 4813.237,\n        'oil': 331.35,\n        'solar': 0.0,\n        'wind': 20.391,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.673,\n        'coal': 1421.013,\n        'gas': 2059.029,\n        'hydro': 4707.576,\n        'oil': 252.802,\n        'solar': 0.0,\n        'wind': 19.973,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 126.063,\n        'coal': 1417.426,\n        'gas': 1503.069,\n        'hydro': 4949.94,\n        'oil': 206.193,\n        'solar': 0.0,\n        'wind': 12.558,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.694,\n        'coal': 1429.311,\n        'gas': 1280.254,\n        'hydro': 4936.128,\n        'oil': 96.982,\n        'solar': 0.0,\n        'wind': 5.124,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 125.576,\n        'coal': 1429.775,\n        'gas': 935.477,\n        'hydro': 5209.522,\n        'oil': 54.711,\n        'solar': 0.0,\n        'wind': 2.822,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.277,\n        'coal': 1428.566,\n        'gas': 988.957,\n        'hydro': 5168.181,\n        'oil': 59.082,\n        'solar': 0.0,\n        'wind': 5.116,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 128.982,\n        'coal': 1432.567,\n        'gas': 1080.448,\n        'hydro': 5319.758,\n        'oil': 69.057,\n        'solar': 0.412,\n        'wind': 4.178,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.549,\n        'coal': 1431.248,\n        'gas': 1095.693,\n        'hydro': 5337.87,\n        'oil': 74.424,\n        'solar': 44.788,\n        'wind': 6.137,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 129.746,\n        'coal': 1422.247,\n        'gas': 1138.392,\n        'hydro': 5419.527,\n        'oil': 132.792,\n        'solar': 296.205,\n        'wind': 10.605,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 130.985,\n        'coal': 1418.869,\n        'gas': 1257.156,\n        'hydro': 5475.501,\n        'oil': 171.966,\n        'solar': 697.088,\n        'wind': 9.309,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 131.666,\n        'coal': 1414.947,\n        'gas': 1282.574,\n        'hydro': 5526.099,\n        'oil': 186.718,\n        'solar': 993.567,\n        'wind': 7.953,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 119.026,\n        'coal': 1415.838,\n        'gas': 1278.255,\n        'hydro': 5649.072,\n        'oil': 236.08,\n        'solar': 1031.19,\n        'wind': 12.101,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.929,\n        'coal': 1414.153,\n        'gas': 1271.743,\n        'hydro': 5629.629,\n        'oil': 271.631,\n        'solar': 1171.945,\n        'wind': 17.001,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.027,\n        'coal': 1414.57,\n        'gas': 1288.618,\n        'hydro': 5466.942,\n        'oil': 317.377,\n        'solar': 1203.925,\n        'wind': 18.024,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.634,\n        'coal': 1412.128,\n        'gas': 1316.288,\n        'hydro': 5333.155,\n        'oil': 338.232,\n        'solar': 1143.505,\n        'wind': 19.401,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 116.882,\n        'coal': 1411.424,\n        'gas': 1447.836,\n        'hydro': 5134.346,\n        'oil': 337.737,\n        'solar': 1038.141,\n        'wind': 22.024,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 122.6,\n        'coal': 1416.105,\n        'gas': 1477.373,\n        'hydro': 5220.615,\n        'oil': 329.775,\n        'solar': 838.224,\n        'wind': 21.971,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n   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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 124.792,\n        'coal': 1421.254,\n        'gas': 1667.39,\n        'hydro': 6554.272,\n        'oil': 489.502,\n        'solar': 0.019,\n        'wind': 20.85,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 24, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 127.332,\n        'coal': 1419.148,\n        'gas': 1540.657,\n        'hydro': 6622.259,\n        'oil': 493.756,\n        'solar': 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'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 26, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 121.679,\n        'coal': 1032.866,\n        'gas': 959.53,\n        'hydro': 5479.226,\n        'oil': 54.88,\n        'solar': 0.0,\n        'wind': 9.38,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 26, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 123.144,\n        'coal': 1082.051,\n        'gas': 959.317,\n        'hydro': 5332.415,\n        'oil': 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22.766,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.704,\n        'coal': 1384.735,\n        'gas': 1342.018,\n        'hydro': 6925.653,\n        'oil': 152.728,\n        'solar': 846.628,\n        'wind': 22.79,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 26, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.067,\n        'coal': 1375.885,\n        'gas': 1386.731,\n  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datetime.datetime(2024, 12, 26, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 104.946,\n        'coal': 1417.677,\n        'gas': 1484.381,\n        'hydro': 7828.416,\n        'oil': 157.359,\n        'solar': 0.0,\n        'wind': 18.376,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 26, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 109.516,\n        'coal': 1418.016,\n        'gas': 1437.235,\n        'hydro': 7589.578,\n        'oil': 155.963,\n        'solar': 0.0,\n        'wind': 16.564,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 117.647,\n        'coal': 1420.427,\n        'gas': 1278.68,\n        'hydro': 6464.973,\n        'oil': 51.326,\n        'solar': 0.0,\n        'wind': 8.293,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 113.781,\n        'coal': 1350.947,\n        'gas': 1002.514,\n        'hydro': 6226.465,\n        'solar': 0.0,\n        'wind': 6.856,\n    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0.0,\n        'wind': 6.452,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 106.241,\n        'coal': 1029.909,\n        'gas': 855.593,\n        'hydro': 6080.96,\n        'solar': 0.0,\n        'wind': 6.524,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 107.974,\n        'coal': 881.591,\n        'gas': 876.835,\n        'hydro': 6088.964,\n        'solar': 0.0,\n        'wind': 6.485,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 111.196,\n        'coal': 840.146,\n        'gas': 879.261,\n        'hydro': 6366.923,\n        'solar': 0.551,\n        'wind': 6.555,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 110.299,\n        'coal': 866.547,\n  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tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 95.318,\n        'coal': 1324.255,\n        'gas': 902.924,\n        'hydro': 7096.655,\n        'solar': 1035.337,\n        'wind': 19.084,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 97.455,\n        'coal': 1337.83,\n        'gas': 1034.546,\n        'hydro': 7081.178,\n        'solar': 889.818,\n        'wind': 21.853,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      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'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 92.571,\n        'coal': 1339.716,\n        'gas': 1142.707,\n        'hydro': 7489.633,\n        'solar': 337.131,\n        'wind': 22.761,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 98.752,\n        'coal': 1346.573,\n        'gas': 1261.253,\n        'hydro': 7608.183,\n        'solar': 45.138,\n        'wind': 21.135,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 97.531,\n        'coal': 1349.639,\n        'gas': 1413.63,\n        'hydro': 8061.135,\n        'solar': 0.008,\n        'wind': 15.817,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 94.491,\n        'coal': 1414.664,\n        'gas': 1436.591,\n        'hydro': 7961.207,\n        'solar': 0.0,\n        'wind': 13.709,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 97.782,\n        'coal': 1421.233,\n        'gas': 1292.893,\n        'hydro': 7849.098,\n        'solar': 0.0,\n        'wind': 12.026,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 27, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 98.666,\n        'coal': 1423.164,\n        'gas': 1188.075,\n        'hydro': 7586.683,\n        'solar': 0.0,\n        'wind': 10.172,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': 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'solar': 0.0,\n        'wind': 5.956,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 90.238,\n        'coal': 1164.856,\n        'gas': 780.578,\n        'hydro': 5942.444,\n        'solar': 0.0,\n        'wind': 6.272,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 96.665,\n        'coal': 1201.326,\n        'gas': 760.071,\n        'hydro': 5940.872,\n        'solar': 0.039,\n        'wind': 5.88,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 97.265,\n        'coal': 1201.534,\n        'gas': 740.869,\n        'hydro': 5971.08,\n        'solar': 35.572,\n        'wind': 4.046,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 88.513,\n        'coal': 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 'biomass': 80.714,\n        'coal': 1318.134,\n        'gas': 838.514,\n        'hydro': 6319.386,\n        'solar': 929.677,\n        'wind': 10.837,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 84.985,\n        'coal': 1316.183,\n        'gas': 845.269,\n        'hydro': 6464.112,\n        'solar': 1052.109,\n        'wind': 17.971,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 11, 0, 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'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 95.575,\n        'coal': 1312.232,\n        'gas': 1008.311,\n        'hydro': 6920.953,\n        'solar': 430.0,\n        'wind': 22.142,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 97.344,\n        'coal': 1309.306,\n        'gas': 978.7,\n        'hydro': 7149.266,\n        'solar': 200.15,\n        'wind': 22.225,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 96.209,\n        'coal': 1314.593,\n        'gas': 920.164,\n        'hydro': 7432.039,\n        'solar': 30.657,\n        'wind': 10.722,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 100.959,\n        'coal': 1318.295,\n        'gas': 929.057,\n        'hydro': 8052.228,\n        'solar': 0.012,\n        'wind': 2.639,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 103.966,\n        'coal': 1361.723,\n        'gas': 1141.25,\n        'hydro': 7231.819,\n        'solar': 0.0,\n        'wind': 6.973,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 99.593,\n        'coal': 1361.576,\n        'gas': 1109.663,\n        'hydro': 6824.106,\n        'solar': 0.0,\n        'wind': 5.779,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 28, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 94.688,\n        'coal': 1361.189,\n        'gas': 1095.855,\n        'hydro': 6435.277,\n        'solar': 0.0,\n        'wind': 7.817,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 100.089,\n        'coal': 1361.189,\n        'gas': 1031.11,\n        'hydro': 6061.402,\n        'oil': 0.0,\n        'solar': 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592.728,\n        'hydro': 6017.685,\n        'oil': 11.865,\n        'solar': 0.0,\n        'wind': 3.647,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 98.446,\n        'coal': 1267.569,\n        'gas': 571.281,\n        'hydro': 5915.96,\n        'oil': 16.719,\n        'solar': 0.0,\n        'wind': 4.689,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 98.417,\n        'coal': 1182.268,\n        'gas': 464.914,\n        'hydro': 6031.175,\n        'oil': 36.298,\n        'solar': 0.0,\n        'wind': 4.809,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 100.795,\n        'coal': 1060.916,\n        'gas': 429.638,\n        'hydro': 6145.956,\n        'oil': 41.983,\n        'solar': 0.145,\n        'wind': 4.376,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 106.193,\n        'coal': 916.878,\n        'gas': 382.97,\n        'hydro': 5963.615,\n        'oil': 53.121,\n        'solar': 24.334,\n        'wind': 2.559,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 105.109,\n        'coal': 742.821,\n        'gas': 354.569,\n        'hydro': 5963.757,\n        'oil': 53.681,\n        'solar': 235.544,\n        'wind': 0.742,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 103.699,\n        'coal': 698.994,\n        'gas': 351.936,\n        'hydro': 5986.833,\n        'oil': 53.274,\n        'solar': 616.8,\n        'wind': 0.303,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 103.503,\n        'coal': 800.273,\n        'gas': 349.077,\n        'hydro': 6032.933,\n        'oil': 54.624,\n        'solar': 938.725,\n        'wind': 1.742,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    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'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 91.967,\n        'coal': 1061.741,\n        'gas': 365.282,\n        'hydro': 6286.378,\n        'oil': 54.43,\n        'solar': 1207.653,\n        'wind': 17.281,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 89.45,\n        'coal': 1134.358,\n        'gas': 368.525,\n        'hydro': 6272.178,\n     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88.184,\n        'coal': 1114.683,\n        'gas': 496.919,\n        'hydro': 6544.101,\n        'oil': 54.872,\n        'solar': 776.031,\n        'wind': 21.356,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 92.616,\n        'coal': 1134.37,\n        'gas': 601.083,\n        'hydro': 6756.332,\n        'oil': 54.541,\n        'solar': 393.936,\n        'wind': 22.992,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 17, 0, 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'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 29, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 93.683,\n        'coal': 1205.773,\n        'gas': 721.585,\n        'hydro': 6677.339,\n        'oil': 54.424,\n        'solar': 0.0,\n        'wind': 5.91,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 94.146,\n        'coal': 1171.882,\n        'gas': 673.613,\n        'hydro': 6103.958,\n        'oil': 54.614,\n        'solar': 0.0,\n        'wind': 7.21,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 93.452,\n        'coal': 1079.482,\n        'gas': 617.575,\n        'hydro': 5984.405,\n        'oil': 54.612,\n        'solar': 0.0,\n        'wind': 4.287,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 90.27,\n        'coal': 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 'oil': 54.652,\n        'solar': 1114.842,\n        'wind': 4.508,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 74.463,\n        'coal': 1165.681,\n        'gas': 896.766,\n        'hydro': 6670.846,\n        'oil': 54.683,\n        'solar': 1108.76,\n        'wind': 15.889,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 71.711,\n        'coal': 1162.417,\n        'gas': 883.432,\n        'hydro': 6741.734,\n        'oil': 54.609,\n        'solar': 1081.401,\n        'wind': 19.755,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 69.582,\n        'coal': 1175.986,\n        'gas': 879.378,\n        'hydro': 6900.429,\n        'oil': 54.689,\n        'solar': 964.9,\n        'wind': 22.366,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 70.684,\n        'coal': 1194.973,\n        'gas': 857.728,\n        'hydro': 6998.097,\n        'oil': 54.687,\n        'solar': 831.72,\n        'wind': 21.91,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 63.2,\n        'coal': 1159.621,\n        'gas': 961.146,\n        'hydro': 7143.106,\n        'oil': 54.353,\n        'solar': 485.991,\n        'wind': 20.719,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 59.538,\n        'coal': 1166.53,\n        'gas': 1066.514,\n        'hydro': 7396.758,\n        'oil': 54.76,\n        'solar': 65.333,\n        'wind': 20.067,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 60.774,\n        'coal': 1213.239,\n        'gas': 1136.548,\n        'hydro': 7900.846,\n        'oil': 54.918,\n        'solar': 0.018,\n        'wind': 16.894,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 62.468,\n        'coal': 1203.594,\n        'gas': 1141.897,\n        'hydro': 7917.887,\n        'oil': 54.559,\n        'solar': 0.0,\n        'wind': 14.011,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 65.822,\n        'coal': 1197.908,\n        'gas': 1143.516,\n        'hydro': 7632.133,\n        'oil': 54.829,\n        'solar': 0.002,\n        'wind': 8.421,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 65.499,\n        'coal': 1175.03,\n        'gas': 1005.355,\n        'hydro': 7188.076,\n        'oil': 54.68,\n        'solar': 0.002,\n        'wind': 9.055,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 63.577,\n        'coal': 1177.046,\n        'gas': 938.997,\n        'hydro': 6800.433,\n        'oil': 54.864,\n        'solar': 0.002,\n        'wind': 12.017,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 30, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 62.551,\n        'coal': 1173.154,\n        'gas': 938.898,\n        'hydro': 6341.954,\n        'oil': 55.036,\n        'solar': 0.002,\n        'wind': 9.918,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 31, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 57.083,\n        'coal': 967.624,\n        'gas': 784.431,\n        'hydro': 6291.422,\n        'oil': 55.014,\n        'solar': 0.002,\n        'wind': 7.065,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 31, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 58.867,\n        'coal': 851.144,\n        'gas': 678.535,\n        'hydro': 6201.305,\n        'oil': 55.126,\n        'solar': 0.002,\n        'wind': 5.357,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 31, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 58.244,\n        'coal': 782.755,\n        'gas': 586.334,\n        'hydro': 6074.989,\n        'oil': 54.979,\n        'solar': 0.002,\n        'wind': 3.992,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 31, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 57.892,\n        'coal': 757.28,\n        'gas': 538.489,\n        'hydro': 5996.725,\n        'oil': 55.045,\n        'solar': 0.002,\n        'wind': 2.773,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      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'biomass': 29.944,\n        'coal': 907.157,\n        'gas': 524.773,\n        'hydro': 6782.928,\n        'oil': 55.129,\n        'solar': 0.0,\n        'wind': 12.794,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 12, 31, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 30.893,\n        'coal': 740.646,\n        'gas': 522.511,\n        'hydro': 6461.544,\n        'oil': 55.183,\n        'solar': 0.0,\n        'wind': 8.515,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 0, 0, 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datetime.datetime(2025, 1, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 33.181,\n        'coal': 288.39,\n        'gas': 303.428,\n        'hydro': 5530.351,\n        'oil': 43.623,\n        'solar': 1263.286,\n        'wind': 22.49,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 34.13,\n        'coal': 350.084,\n        'gas': 329.832,\n        'hydro': 5600.454,\n        'oil': 54.365,\n        'solar': 1061.903,\n        'wind': 22.44,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 34.143,\n        'coal': 382.693,\n        'gas': 348.305,\n        'hydro': 5873.488,\n        'oil': 54.891,\n        'solar': 711.629,\n        'wind': 22.616,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 35.863,\n        'coal': 485.35,\n        'gas': 408.785,\n        'hydro': 6007.24,\n        'oil': 54.88,\n        'solar': 378.463,\n        'wind': 22.927,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 33.897,\n        'coal': 602.608,\n        'gas': 571.534,\n        'hydro': 6175.08,\n        'oil': 54.791,\n        'solar': 46.767,\n        'wind': 21.828,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 34.054,\n        'coal': 836.905,\n        'gas': 763.709,\n        'hydro': 6813.896,\n        'oil': 40.661,\n        'solar': 0.019,\n        'wind': 21.888,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 36.454,\n        'coal': 845.799,\n        'gas': 769.147,\n        'hydro': 7007.98,\n        'oil': 55.103,\n        'solar': 0.0,\n        'wind': 21.326,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 34.755,\n        'coal': 846.603,\n        'gas': 756.654,\n        'hydro': 6963.501,\n        'oil': 55.036,\n        'solar': 0.0,\n        'wind': 20.459,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 33.26,\n        'coal': 783.12,\n        'gas': 618.847,\n        'hydro': 7000.82,\n        'oil': 55.033,\n        'solar': 0.0,\n        'wind': 18.576,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 32.93,\n        'coal': 789.216,\n        'gas': 583.609,\n        'hydro': 6903.785,\n        'oil': 20.977,\n        'solar': 0.0,\n        'wind': 17.238,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 33.488,\n        'coal': 784.327,\n        'gas': 592.398,\n        'hydro': 6633.218,\n        'oil': 23.712,\n        'solar': 0.0,\n        'wind': 12.785,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n  ])\n# ---\n# name: test_fetch_production_live\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 63.133,\n        'coal': 1101.335,\n        'gas': 832.279,\n        'hydro': 6155.493,\n        'oil': 60.208,\n        'solar': 0.0,\n        'wind': 9.508,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 65.38,\n        'coal': 1096.563,\n        'gas': 826.885,\n        'hydro': 5850.546,\n        'oil': 59.742,\n        'solar': 0.0,\n        'wind': 5.396,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 65.539,\n        'coal': 1101.925,\n        'gas': 791.214,\n        'hydro': 5652.68,\n        'oil': 60.223,\n        'solar': 0.0,\n        'wind': 9.466,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 68.167,\n        'coal': 1101.111,\n        'gas': 650.003,\n        'hydro': 5679.313,\n        'oil': 62.505,\n        'solar': 0.0,\n        'wind': 12.423,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 67.028,\n        'coal': 1128.049,\n        'gas': 684.398,\n        'hydro': 5638.451,\n        'oil': 63.596,\n        'solar': 0.029,\n        'wind': 10.156,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 67.663,\n        'coal': 1155.585,\n        'gas': 687.108,\n        'hydro': 5761.23,\n        'oil': 63.376,\n        'solar': 0.306,\n        'wind': 7.333,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 68.643,\n        'coal': 1198.055,\n        'gas': 637.567,\n        'hydro': 5722.605,\n        'oil': 62.325,\n        'solar': 22.207,\n        'wind': 10.204,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 70.777,\n        'coal': 1216.131,\n        'gas': 736.073,\n        'hydro': 5817.704,\n        'oil': 63.413,\n        'solar': 193.921,\n        'wind': 10.219,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 72.818,\n        'coal': 1218.231,\n        'gas': 698.426,\n        'hydro': 6140.461,\n        'oil': 65.654,\n        'solar': 401.814,\n        'wind': 11.839,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 85.787,\n        'coal': 1218.179,\n        'gas': 678.202,\n        'hydro': 6128.27,\n        'oil': 109.967,\n        'solar': 671.148,\n        'wind': 14.917,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 89.798,\n        'coal': 1219.417,\n        'gas': 682.953,\n        'hydro': 6025.624,\n        'oil': 74.747,\n        'solar': 1032.26,\n        'wind': 13.931,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 88.132,\n        'coal': 1229.227,\n        'gas': 675.716,\n        'hydro': 6228.848,\n        'oil': 72.68,\n        'solar': 1081.008,\n        'wind': 13.46,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 89.376,\n        'coal': 1223.046,\n        'gas': 726.889,\n        'hydro': 6333.194,\n        'oil': 64.58,\n        'solar': 1098.493,\n        'wind': 20.711,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 91.103,\n        'coal': 1239.365,\n        'gas': 767.155,\n        'hydro': 6474.603,\n        'oil': 63.825,\n        'solar': 988.428,\n        'wind': 17.969,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 93.111,\n        'coal': 1279.457,\n        'gas': 800.334,\n        'hydro': 6608.894,\n        'oil': 76.744,\n        'solar': 948.477,\n        'wind': 19.099,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 92.143,\n        'coal': 1280.49,\n        'gas': 883.191,\n        'hydro': 6700.524,\n        'oil': 76.912,\n        'solar': 732.828,\n        'wind': 21.416,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 88.871,\n        'coal': 1288.645,\n        'gas': 1005.026,\n        'hydro': 6884.194,\n        'oil': 76.65,\n        'solar': 299.539,\n        'wind': 22.391,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 87.025,\n        'coal': 1299.871,\n        'gas': 1124.153,\n        'hydro': 6940.256,\n        'oil': 76.505,\n        'solar': 34.471,\n        'wind': 20.237,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 90.181,\n        'coal': 1307.717,\n        'gas': 1222.859,\n        'hydro': 7582.185,\n        'oil': 64.343,\n        'solar': 0.02,\n        'wind': 18.958,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 94.647,\n        'coal': 1314.723,\n        'gas': 1207.728,\n        'hydro': 7710.26,\n        'oil': 64.499,\n        'solar': 0.0,\n        'wind': 19.437,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 91.774,\n        'coal': 1318.365,\n        'gas': 1211.148,\n        'hydro': 7513.684,\n        'oil': 64.399,\n        'solar': 0.0,\n        'wind': 15.677,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 94.761,\n        'coal': 1315.086,\n        'gas': 1180.312,\n        'hydro': 7124.852,\n        'oil': 64.211,\n        'solar': 0.0,\n        'wind': 10.025,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 94.101,\n        'coal': 1320.347,\n        'gas': 1141.989,\n        'hydro': 6637.288,\n        'oil': 64.132,\n        'solar': 0.0,\n        'wind': 16.646,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Bogota')),\n      'production': dict({\n        'biomass': 90.525,\n        'coal': 1323.986,\n        'gas': 1048.959,\n        'hydro': 6286.127,\n        'oil': 64.381,\n        'solar': 0.0,\n        'wind': 15.234,\n      }),\n      'source': 'xm.com.co',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CO',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CR.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_live\n  list([\n    dict({\n      'datetime': FakeDatetime(2024, 1, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'netFlow': 31.558895,\n      'sortedZoneKeys': 'CR->PA',\n      'source': 'enteoperador.org',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_fetch_production_historical\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 168.011,\n        'hydro': 710.031815,\n        'oil': 0,\n        'solar': 0,\n        'wind': 334.802279,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 168.35425,\n        'hydro': 671.606827,\n        'oil': 0,\n        'solar': 0,\n        'wind': 332.136786,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 168.19325,\n        'hydro': 642.654386,\n        'oil': 0,\n        'solar': 0,\n        'wind': 337.517291,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 168.36525,\n        'hydro': 654.120858,\n        'oil': 0,\n        'solar': 0,\n        'wind': 338.254346,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 168.0705,\n        'hydro': 728.076578,\n        'oil': 0,\n        'solar': 0,\n        'wind': 327.121795,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 168.2905,\n        'hydro': 805.379219,\n        'oil': 0,\n        'solar': 0.03825,\n        'wind': 319.604019,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 167.92225,\n        'hydro': 919.290978,\n        'oil': 0,\n        'solar': 0.4083,\n        'wind': 311.209597,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 167.72475,\n        'hydro': 1063.47016,\n        'oil': 0,\n        'solar': 1.3898,\n        'wind': 288.96851,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 163.49575,\n        'hydro': 1125.532559,\n        'oil': 0,\n        'solar': 2.4539,\n        'wind': 290.699937,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 163.08975,\n        'hydro': 1163.08957,\n        'oil': 0,\n        'solar': 3.2615,\n        'wind': 287.02421,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 162.4095,\n        'hydro': 1198.050065,\n        'oil': 0,\n        'solar': 3.78245,\n        'wind': 290.167949,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 162.16075,\n        'hydro': 1265.214676,\n        'oil': 0,\n        'solar': 3.82235,\n        'wind': 298.560845,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 161.54296,\n        'hydro': 1255.42204,\n        'oil': 0,\n        'solar': 3.94295,\n        'wind': 310.860435,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 161.51563,\n        'hydro': 1229.338198,\n        'oil': 0,\n        'solar': 3.6128,\n        'wind': 303.83357,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 161.64274,\n        'hydro': 1228.071012,\n        'oil': 0,\n        'solar': 2.94125,\n        'wind': 283.926575,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 164.44255,\n        'hydro': 1217.368787,\n        'oil': 0,\n        'solar': 2.0057,\n        'wind': 268.341069,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 166.075,\n        'hydro': 1204.84709,\n        'oil': 0,\n        'solar': 0.9573,\n        'wind': 248.79655,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 166.22884,\n        'hydro': 1138.826491,\n        'oil': 0,\n        'solar': 0.1984,\n        'wind': 242.765609,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 166.97141,\n        'hydro': 1284.569501,\n        'oil': 0,\n        'solar': 0,\n        'wind': 251.480158,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 166.88659,\n        'hydro': 1307.562202,\n        'oil': 0,\n        'solar': 0,\n        'wind': 254.715687,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 166.79794,\n        'hydro': 1215.979283,\n        'oil': 0,\n        'solar': 0,\n        'wind': 266.851227,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 167.27209,\n        'hydro': 1115.813374,\n        'oil': 0,\n        'solar': 0,\n        'wind': 276.952469,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 167.35488,\n        'hydro': 981.438874,\n        'oil': 0,\n        'solar': 0,\n        'wind': 276.439225,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 0,\n        'geothermal': 167.41837,\n        'hydro': 860.750772,\n        'oil': 0,\n        'solar': 0,\n        'wind': 284.758908,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n  ])\n# ---\n# name: test_fetch_production_live\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 18.577759,\n        'geothermal': 163.33713,\n        'hydro': 700.748489,\n        'oil': 0,\n        'solar': 0,\n        'wind': 296.452908,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 18.789446,\n        'geothermal': 163.38237,\n        'hydro': 666.709517,\n        'oil': 0,\n        'solar': 0,\n        'wind': 296.853684,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 17.598135,\n        'geothermal': 163.33988,\n        'hydro': 614.980704,\n        'oil': 0,\n        'solar': 0,\n        'wind': 299.250986,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 18.7675,\n        'geothermal': 163.34475,\n        'hydro': 595.174588,\n        'oil': 0,\n        'solar': 0,\n        'wind': 294.168876,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.72423,\n        'geothermal': 163.22813,\n        'hydro': 582.778563,\n        'oil': 0,\n        'solar': 0,\n        'wind': 297.101491,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 18.552462,\n        'geothermal': 163.23762,\n        'hydro': 555.405806,\n        'oil': 0,\n        'solar': 0,\n        'wind': 302.040768,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 18.982145,\n        'geothermal': 163.29175,\n        'hydro': 492.447345,\n        'oil': 0,\n        'solar': 0.2388,\n        'wind': 288.287073,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 18.960933,\n        'geothermal': 163.19012,\n        'hydro': 537.70388,\n        'oil': 0,\n        'solar': 1.46,\n        'wind': 259.991192,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 20.670307,\n        'geothermal': 163.096,\n        'hydro': 595.46407,\n        'oil': 0,\n        'solar': 2.2996,\n        'wind': 275.683921,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 21.566067,\n        'geothermal': 162.88225,\n        'hydro': 653.719449,\n        'oil': 0,\n        'solar': 2.6147,\n        'wind': 303.409412,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 21.159958,\n        'geothermal': 163.17313,\n        'hydro': 747.766433,\n        'oil': 0,\n        'solar': 3.6059,\n        'wind': 305.820401,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 21.016447,\n        'geothermal': 162.90987,\n        'hydro': 830.002135,\n        'oil': 0,\n        'solar': 3.8355,\n        'wind': 310.596043,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 20.474445,\n        'geothermal': 162.81538,\n        'hydro': 896.183148,\n        'oil': 0,\n        'solar': 3.4247,\n        'wind': 303.005786,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.395496,\n        'geothermal': 162.82875,\n        'hydro': 898.916769,\n        'oil': 0,\n        'solar': 3.408,\n        'wind': 283.384246,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.245838,\n        'geothermal': 162.66712,\n        'hydro': 925.985949,\n        'oil': 0,\n        'solar': 2.8063,\n        'wind': 271.445285,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 20.083724,\n        'geothermal': 162.87925,\n        'hydro': 906.291611,\n        'oil': 0,\n        'solar': 1.9453,\n        'wind': 279.865412,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.78922,\n        'geothermal': 162.96538,\n        'hydro': 889.61046,\n        'oil': 0,\n        'solar': 0.8122,\n        'wind': 281.610696,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.509736,\n        'geothermal': 163.41025,\n        'hydro': 908.88272,\n        'oil': 0,\n        'solar': 0.0433,\n        'wind': 287.995122,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.820335,\n        'geothermal': 163.43262,\n        'hydro': 997.760934,\n        'oil': 0,\n        'solar': 0,\n        'wind': 309.167618,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.630411,\n        'geothermal': 163.43863,\n        'hydro': 966.185639,\n        'oil': 0,\n        'solar': 0,\n        'wind': 309.91341,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.146717,\n        'geothermal': 163.47687,\n        'hydro': 936.102628,\n        'oil': 0,\n        'solar': 0,\n        'wind': 313.155425,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.258829,\n        'geothermal': 163.47188,\n        'hydro': 842.532733,\n        'oil': 0,\n        'solar': 0,\n        'wind': 319.285039,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.376949,\n        'geothermal': 163.38,\n        'hydro': 731.800474,\n        'oil': 0,\n        'solar': 0,\n        'wind': 317.338119,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Costa_Rica')),\n      'production': dict({\n        'biomass': 19.324172,\n        'geothermal': 163.37037,\n        'hydro': 639.940155,\n        'oil': 0,\n        'solar': 0,\n        'wind': 315.254165,\n      }),\n      'source': 'grupoice.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CR',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CY.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_historical_source\n  list([\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 411.0,\n        'solar': 0.0,\n        'wind': 36.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 404.0,\n        'solar': 0.0,\n        'wind': 29.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 394.0,\n        'solar': 0.0,\n        'wind': 28.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 380.0,\n        'solar': 0.0,\n        'wind': 31.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 374.0,\n        'solar': 0.0,\n        'wind': 27.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 362.0,\n        'solar': 0.0,\n        'wind': 32.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 351.0,\n        'solar': 0.0,\n        'wind': 35.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 332.0,\n        'solar': 0.0,\n        'wind': 47.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 328.0,\n        'solar': 0.0,\n        'wind': 46.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 309.0,\n        'solar': 0.0,\n        'wind': 60.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 310.0,\n        'solar': 0.0,\n        'wind': 55.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 313.0,\n        'solar': 0.0,\n        'wind': 48.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 327.0,\n        'solar': 0.0,\n        'wind': 34.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 327.0,\n        'solar': 0.0,\n        'wind': 33.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 320.0,\n        'solar': 0.0,\n        'wind': 39.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 315.0,\n        'solar': 0.0,\n        'wind': 43.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 320.0,\n        'solar': 0.0,\n        'wind': 37.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 319.0,\n        'solar': 0.0,\n        'wind': 41.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 316.0,\n        'solar': 0.0,\n        'wind': 45.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 326.0,\n        'solar': 0.0,\n        'wind': 37.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 333.0,\n        'solar': 0.0,\n        'wind': 31.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 354.0,\n        'solar': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 361.0,\n        'solar': 0.0,\n        'wind': 15.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 361.0,\n        'solar': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 345.0,\n        'solar': 0.0,\n        'wind': 31.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 354.0,\n        'solar': 0.0,\n        'wind': 31.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 355.0,\n        'solar': 5.0,\n        'wind': 31.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 350.0,\n        'solar': 19.0,\n        'wind': 36.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 343.0,\n        'solar': 31.0,\n        'wind': 42.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 346.0,\n        'solar': 45.0,\n        'wind': 38.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 332.0,\n        'solar': 60.0,\n        'wind': 41.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 326.0,\n        'solar': 72.0,\n        'wind': 38.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 314.0,\n        'solar': 100.0,\n        'wind': 35.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 279.0,\n        'solar': 159.0,\n        'wind': 29.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 249.0,\n        'solar': 192.0,\n        'wind': 23.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 258.0,\n        'solar': 196.0,\n        'wind': 15.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 251.0,\n        'solar': 210.0,\n        'wind': 14.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 248.0,\n        'solar': 231.0,\n        'wind': 15.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 254.0,\n        'solar': 232.0,\n        'wind': 19.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 254.0,\n        'solar': 249.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 249.0,\n        'solar': 245.0,\n        'wind': 14.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 236.0,\n        'solar': 247.0,\n        'wind': 12.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 236.0,\n        'solar': 251.0,\n        'wind': 11.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 234.0,\n        'solar': 265.0,\n        'wind': 12.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 230.0,\n        'solar': 267.0,\n        'wind': 15.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 227.0,\n        'solar': 276.0,\n        'wind': 14.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 230.0,\n        'solar': 244.0,\n        'wind': 13.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 229.0,\n        'solar': 229.0,\n        'wind': 15.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 221.0,\n        'solar': 231.0,\n        'wind': 12.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 225.0,\n        'solar': 231.0,\n        'wind': 15.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 226.0,\n        'solar': 209.0,\n        'wind': 8.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 234.0,\n        'solar': 204.0,\n        'wind': 7.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 233.0,\n        'solar': 207.0,\n        'wind': 10.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 231.0,\n        'solar': 233.0,\n        'wind': 12.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 227.0,\n        'solar': 197.0,\n        'wind': 11.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 231.0,\n        'solar': 159.0,\n        'wind': 10.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 233.0,\n        'solar': 151.0,\n        'wind': 15.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 235.0,\n        'solar': 151.0,\n        'wind': 18.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 230.0,\n        'solar': 162.0,\n        'wind': 18.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 242.0,\n        'solar': 152.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 277.0,\n        'solar': 115.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 305.0,\n        'solar': 97.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 321.0,\n        'solar': 89.0,\n        'wind': 18.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 331.0,\n        'solar': 88.0,\n        'wind': 24.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 352.0,\n        'solar': 78.0,\n        'wind': 23.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 387.0,\n        'solar': 69.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 409.0,\n        'solar': 51.0,\n        'wind': 22.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 434.0,\n        'solar': 34.0,\n        'wind': 27.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 460.0,\n        'solar': 23.0,\n        'wind': 27.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 483.0,\n        'solar': 18.0,\n        'wind': 28.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 504.0,\n        'solar': 9.0,\n        'wind': 28.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 534.0,\n        'solar': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 558.0,\n        'solar': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 582.0,\n        'solar': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 604.0,\n        'solar': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 616.0,\n        'solar': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 628.0,\n        'solar': 0.0,\n        'wind': 17.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 637.0,\n        'solar': 0.0,\n        'wind': 14.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 637.0,\n        'solar': 0.0,\n        'wind': 14.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 627.0,\n        'solar': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 619.0,\n        'solar': 0.0,\n        'wind': 23.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 608.0,\n        'solar': 0.0,\n        'wind': 27.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 598.0,\n        'solar': 0.0,\n        'wind': 27.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 580.0,\n        'solar': 0.0,\n        'wind': 34.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 576.0,\n        'solar': 0.0,\n        'wind': 28.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 570.0,\n        'solar': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 554.0,\n        'solar': 0.0,\n        'wind': 21.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 532.0,\n        'solar': 0.0,\n        'wind': 28.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 521.0,\n        'solar': 0.0,\n        'wind': 23.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 507.0,\n        'solar': 0.0,\n        'wind': 19.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 489.0,\n        'solar': 0.0,\n        'wind': 21.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 462.0,\n        'solar': 0.0,\n        'wind': 30.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 434.0,\n        'solar': 0.0,\n        'wind': 40.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 418.0,\n        'solar': 0.0,\n        'wind': 41.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 404.0,\n        'solar': 0.0,\n        'wind': 42.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 3, 18, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 402.0,\n        'solar': 0.0,\n        'wind': 33.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n  ])\n# ---\n# name: test_snapshot_realtime_source\n  list([\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 374.0,\n        'solar': 0.0,\n        'wind': 14.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 369.0,\n        'solar': 0.0,\n        'wind': 9.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 364.0,\n        'solar': 0.0,\n        'wind': 8.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 354.0,\n        'solar': 0.0,\n        'wind': 9.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 342.0,\n        'solar': 0.0,\n        'wind': 12.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 334.0,\n        'solar': 0.0,\n        'wind': 15.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 327.0,\n        'solar': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 317.0,\n        'solar': 0.0,\n        'wind': 22.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 310.0,\n        'solar': 0.0,\n        'wind': 25.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 303.0,\n        'solar': 0.0,\n        'wind': 29.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 304.0,\n        'solar': 0.0,\n        'wind': 24.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 304.0,\n        'solar': 0.0,\n        'wind': 21.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 305.0,\n        'solar': 0.0,\n        'wind': 19.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 301.0,\n        'solar': 0.0,\n        'wind': 21.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 301.0,\n        'solar': 0.0,\n        'wind': 19.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 302.0,\n        'solar': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 305.0,\n        'solar': 0.0,\n        'wind': 12.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 308.0,\n        'solar': 0.0,\n        'wind': 12.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 306.0,\n        'solar': 0.0,\n        'wind': 14.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 307.0,\n        'solar': 0.0,\n        'wind': 14.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 306.0,\n        'solar': 0.0,\n        'wind': 15.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 310.0,\n        'solar': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 308.0,\n        'solar': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 310.0,\n        'solar': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 316.0,\n        'solar': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 324.0,\n        'solar': 0.0,\n        'wind': 19.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 319.0,\n        'solar': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 318.0,\n        'solar': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 318.0,\n        'solar': 9.0,\n        'wind': 16.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 319.0,\n        'solar': 21.0,\n        'wind': 11.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 317.0,\n        'solar': 40.0,\n        'wind': 7.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 301.0,\n        'solar': 66.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 281.0,\n        'solar': 108.0,\n        'wind': 3.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 260.0,\n        'solar': 140.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 231.0,\n        'solar': 179.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 225.0,\n        'solar': 198.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 226.0,\n        'solar': 208.0,\n        'wind': 3.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 227.0,\n        'solar': 216.0,\n        'wind': 3.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 225.0,\n        'solar': 225.0,\n        'wind': 1.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 225.0,\n        'solar': 236.0,\n        'wind': 1.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 226.0,\n        'solar': 240.0,\n        'wind': 2.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 224.0,\n        'solar': 246.0,\n        'wind': 2.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 225.0,\n        'solar': 247.0,\n        'wind': 2.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 227.0,\n        'solar': 250.0,\n        'wind': 1.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 228.0,\n        'solar': 256.0,\n        'wind': 1.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 230.0,\n        'solar': 262.0,\n        'wind': 2.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 233.0,\n        'solar': 269.0,\n        'wind': 2.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 230.0,\n        'solar': 275.0,\n        'wind': 2.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 227.0,\n        'solar': 278.0,\n        'wind': 3.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 226.0,\n        'solar': 282.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 225.0,\n        'solar': 283.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 225.0,\n        'solar': 284.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 226.0,\n        'solar': 286.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 220.0,\n        'solar': 288.0,\n        'wind': 5.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 216.0,\n        'solar': 284.0,\n        'wind': 6.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 214.0,\n        'solar': 280.0,\n        'wind': 7.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 213.0,\n        'solar': 275.0,\n        'wind': 7.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 217.0,\n        'solar': 268.0,\n        'wind': 5.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 220.0,\n        'solar': 262.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n    dict({\n      'capacity': dict({\n        'biomass': 12.4,\n        'oil': 1478.0,\n        'solar': 674.46,\n        'wind': 155.1,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 4, 1, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Nicosia')),\n      'production': dict({\n        'biomass': 10.0,\n        'oil': 223.0,\n        'solar': 254.0,\n        'wind': 4.0,\n      }),\n      'source': 'tsoc.org.cy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'CY',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CZ/test_fetch_exchange[AT].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[AT]\n  list([\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CZ/test_fetch_exchange[DE].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[DE]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -945.9063,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -923.2897,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -963.7902,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -910.4536,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -894.2134,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -827.9028,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1122.0476,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1123.993,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1207.6045,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1072.005,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1137.9245,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1079.4685,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1021.0584,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 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dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1097.09843,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1181.46987,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1194.3882,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 15, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1798.4459,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1825.036,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1808.836,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1581.958,\n      'sortedZoneKeys': 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dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1309.3606,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1105.0605,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1050.1044,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -915.3804,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -811.8441,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -864.5746,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -858.5301,\n      'sortedZoneKeys': 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dict({\n      'datetime': datetime.datetime(2025, 10, 30, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -833.7164,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -763.7695,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -857.0317,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -717.1108,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -757.1704,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -670.3173,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -862.2165,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -838.1472,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -706.8542,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -657.774,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -999.8816,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -877.8081,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -594.683,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -558.542,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -661.031,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -698.2905,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -635.7221,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -574.0871,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -289.609,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -311.78,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n    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'netFlow': -108.021,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -82.392,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -84.516,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1.282,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': 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tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -122.2093,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -51.6483,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -13.464,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -118.0592,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -470.1381,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -554.8008,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -556.4052,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -769.7773,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -869.4816,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1097.863,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1248.5736,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1411.7561,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1595.1754,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1646.36457,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': 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'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -337.3895,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -83.4221,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 131.1706,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 57.8336,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -23.6801,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -126.7365,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -167.9415,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 120.6595,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 168.7888,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 251.3108,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 269.907,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 330.4658,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 385.6534,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 320.221,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 273.2344,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 164.9011,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1.2296,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -19.8414,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 178.4839,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 71.5409,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -15.8556,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -37.837,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -8.9547,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -83.1891,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -424.9436,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -484.3081,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -770.9435,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -826.6251,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1143.10833,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1264.9026,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1398.8176,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1201.6356,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1321.612582,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1354.66632,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1355.71361,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1276.39347,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1378.39388,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1399.96272,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1356.94016,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1460.22529,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1443.259,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1485.9194,\n      'sortedZoneKeys': 'CZ->DE',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CZ/test_fetch_exchange[PL].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[PL]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 57.34669,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -21.2968,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -180.7892,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -212.625,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -121.0926,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2.916756,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -260.1294,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -359.7804,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -420.2181,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -347.3683,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -488.6016,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -558.5971,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -446.0436,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -508.0216,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -957.1111,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1083.484,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1093.271,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1177.475,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1282.823,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1194.153,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1216.976,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1203.175,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1156.538,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1297.514,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1341.878,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1370.745,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1481.579,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1462.878,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1488.255,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1466.427,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1531.823,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1492.828,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1512.735,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1513.857,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1450.72,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1539.611,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1558.753,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1521.258,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1642.194,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1597.64,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1633.347,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1418.629,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1093.578,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1069.965,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1102.484,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1138.785,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -988.2491,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -962.4423,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1047.353,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -971.3198,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1151.263,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1258.991,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1203.425,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1106.238,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1155.085,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1047.058,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -887.6027,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -867.4426,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1043.641,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1229.851,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1257.556,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1206.823,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1165.509,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1096.422,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1084.969,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1058.067,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1048.228,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -954.2005,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -917.0439,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -918.5978,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1083.117,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1020.895,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -949.0921,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1041.434,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1122.948,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -968.808,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -980.1707,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -960.9024,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -991.0405,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -939.0203,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1008.56,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1063.174,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1108.698,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1166.516,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1154.239,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1216.68,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1120.435,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1219.383,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1207.281,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1336.379,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1349.651,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1578.245,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1838.891,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1935.048,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1988.37,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1988.173,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2054.686,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1980.631,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2076.869,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2078.229,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1935.405,\n      'sortedZoneKeys': 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dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1860.124,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1793.402,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1983.054,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1967.747,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1967.437,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1918.294,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1911.315,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1995.521,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1953.497,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1916.981,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1947.135,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2076.953,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2119.115,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2094.367,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2116.227,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2087.86,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -2045.088,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1988.343,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1896.855,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1853.709,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1837.28,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1836.376,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1817.729,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1792.44,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1768.738,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1761.688,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1797.975,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1800.884,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1788.972,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1770.364,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1667.427,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1641.134,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1673.105,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1658.9,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1409.562,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1348.678,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1358.964,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1319.181,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1113.538,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1174.805,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1235.508,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1361.635,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1471.268,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1458.236,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1450.016,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1337.559,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1427.817,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1427.628,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1278.326,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1190.114,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1054.859,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1089.437,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1222.252,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1257.162,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1452.764,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1484.646,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1439.999,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n 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<EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1523.553,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1486.812,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1439.545,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1303.006,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1131.616,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -1010.663,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -915.9167,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -866.4733,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -895.4972,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -622.2483,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -594.0666,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -721.8358,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -561.6174,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 27.66017,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 189.562,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 88.53818,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -96.01603,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -61.92467,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -57.12955,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -130.1398,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -179.6035,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -229.1808,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -153.5911,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -137.893,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -161.5014,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -206.4308,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -230.2321,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -264.4792,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_CZ.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_forecast_pl\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 494.95,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 494.95,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 366.475,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 366.475,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 366.475,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 366.475,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 200.675,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 200.675,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 200.675,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 200.675,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 21.8,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 21.8,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 21.8,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 21.8,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -300.65,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -300.65,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -300.65,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -300.65,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -402.7,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -402.7,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -402.7,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 29, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -402.7,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -358.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -358.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -358.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -358.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -603.675,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -603.675,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -603.675,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -603.675,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -725.3,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -725.3,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -725.3,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -725.3,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -645.7,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -645.7,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -645.7,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -645.7,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -693.2,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -693.2,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -693.2,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -693.2,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -446.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -446.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -446.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -446.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -296.275,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -296.275,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -296.275,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -296.275,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -456.875,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -456.875,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -456.875,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -456.875,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -236.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -236.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -236.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -236.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -466.575,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -466.575,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -466.575,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -466.575,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -658.6,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -658.6,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -658.6,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -658.6,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -445.375,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -445.375,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -445.375,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -445.375,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -542.225,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -542.225,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -542.225,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -542.225,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -580.4,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -580.4,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -580.4,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -580.4,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -479.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -479.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -479.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -479.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -366.025,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -366.025,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -366.025,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -366.025,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -263.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -263.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -263.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -263.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -422.625,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -422.625,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -422.625,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -422.625,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -681.05,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -681.05,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -681.05,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -681.05,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -698.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -698.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -698.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -698.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -543.925,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -543.925,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -543.925,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -543.925,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -827.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -827.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -827.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -827.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -843.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -843.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -843.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -843.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -851.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -851.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -851.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 30, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -851.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -890.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -890.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -890.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -890.0,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -817.75,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -817.75,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -817.75,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -817.75,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -815.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -815.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -815.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -815.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -787.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -787.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -787.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -787.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -750.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -750.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -750.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -750.25,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -619.725,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -619.725,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -619.725,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -619.725,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -499.425,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -499.425,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -499.425,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -499.425,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -416.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -416.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -416.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -416.775,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -535.375,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -535.375,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -535.375,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -535.375,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -705.65,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -705.65,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -705.65,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -705.65,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -867.275,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -867.275,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -867.275,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -867.275,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -982.075,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -982.075,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -982.075,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -982.075,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -682.125,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -682.125,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -682.125,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -682.125,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -219.475,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -219.475,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -219.475,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -219.475,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 31.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 31.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 31.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 31.35,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 499.3,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 499.3,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 499.3,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 499.3,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 442.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 442.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 442.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 442.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 352.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 352.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 352.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 352.5,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 320.75,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 320.75,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 10, 31, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 320.75,\n      'sortedZoneKeys': 'CZ->PL',\n      'source': 'ceps.cz',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_DK.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 5, tzinfo=datetime.timezone.utc),\n      'netFlow': -692.619995,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 10, tzinfo=datetime.timezone.utc),\n      'netFlow': -663.469971,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -664.880005,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 20, tzinfo=datetime.timezone.utc),\n      'netFlow': -686.450012,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 25, tzinfo=datetime.timezone.utc),\n      'netFlow': -665.419983,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -679.140015,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 35, tzinfo=datetime.timezone.utc),\n      'netFlow': -669.289978,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 40, tzinfo=datetime.timezone.utc),\n      'netFlow': -689.789978,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -723.039978,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 50, tzinfo=datetime.timezone.utc),\n      'netFlow': -689.450012,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 15, 55, tzinfo=datetime.timezone.utc),\n      'netFlow': -704.059998,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -720.640015,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 5, tzinfo=datetime.timezone.utc),\n      'netFlow': -784.27002,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 10, tzinfo=datetime.timezone.utc),\n      'netFlow': -757.090027,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -716.030029,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 20, tzinfo=datetime.timezone.utc),\n      'netFlow': -667.960022,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 25, tzinfo=datetime.timezone.utc),\n      'netFlow': -677.780029,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -645.01001,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 35, tzinfo=datetime.timezone.utc),\n      'netFlow': -612.159973,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 40, tzinfo=datetime.timezone.utc),\n      'netFlow': -590.429993,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -594.47998,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 50, tzinfo=datetime.timezone.utc),\n      'netFlow': -581.349976,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 16, 55, tzinfo=datetime.timezone.utc),\n      'netFlow': -569.880005,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -639.26001,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 5, tzinfo=datetime.timezone.utc),\n      'netFlow': -700.5,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 10, tzinfo=datetime.timezone.utc),\n      'netFlow': -627.330017,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -603.049988,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 20, tzinfo=datetime.timezone.utc),\n      'netFlow': -575.390015,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 25, tzinfo=datetime.timezone.utc),\n      'netFlow': -609.130005,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -586.719971,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 35, tzinfo=datetime.timezone.utc),\n      'netFlow': -589.940002,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 40, tzinfo=datetime.timezone.utc),\n      'netFlow': -589.52002,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -557.23999,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 50, tzinfo=datetime.timezone.utc),\n      'netFlow': -511.660004,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 17, 55, tzinfo=datetime.timezone.utc),\n      'netFlow': -459.75,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -517.23999,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 5, tzinfo=datetime.timezone.utc),\n      'netFlow': -578.190002,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 10, tzinfo=datetime.timezone.utc),\n      'netFlow': -547.5,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -565.809998,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 20, tzinfo=datetime.timezone.utc),\n      'netFlow': -589.690002,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 25, tzinfo=datetime.timezone.utc),\n      'netFlow': -572.219971,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -560.77002,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 35, tzinfo=datetime.timezone.utc),\n      'netFlow': -568.590027,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 40, tzinfo=datetime.timezone.utc),\n      'netFlow': -552.059998,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -543.27002,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 50, tzinfo=datetime.timezone.utc),\n      'netFlow': -513.619995,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 18, 55, tzinfo=datetime.timezone.utc),\n      'netFlow': -496.149994,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -553.169983,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 19, 5, tzinfo=datetime.timezone.utc),\n      'netFlow': -576.460022,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 21, 19, 10, tzinfo=datetime.timezone.utc),\n      'netFlow': -561.309998,\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_fetch_forecast\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.38,\n        'wind': 3521.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.72,\n        'wind': 3587.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.49,\n        'wind': 3549.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.04,\n        'wind': 3531.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.59,\n        'wind': 3500.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.89,\n        'wind': 3477.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.92,\n        'wind': 3440.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.16,\n        'wind': 3390.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.76,\n        'wind': 3351.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.52,\n        'wind': 3330.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.82,\n        'wind': 3307.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.76,\n        'wind': 3287.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.76,\n        'wind': 3274.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.91,\n        'wind': 3242.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.18,\n        'wind': 3221.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.69,\n        'wind': 3178.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.68,\n        'wind': 3129.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.75,\n        'wind': 3108.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.79,\n        'wind': 3074.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.54,\n        'wind': 3080.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.21,\n        'wind': 3011.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.95,\n        'wind': 2970.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.09,\n        'wind': 2934.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.07,\n        'wind': 2911.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.42,\n        'wind': 2878.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.23,\n        'wind': 2867.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.18,\n        'wind': 2846.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.87,\n        'wind': 2816.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.84,\n        'wind': 2769.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.7,\n        'wind': 2718.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.22,\n        'wind': 2633.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 5.02,\n        'wind': 2583.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 4.36,\n        'wind': 2562.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.97,\n        'wind': 2512.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 4.2,\n        'wind': 2471.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 1, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 4.09,\n        'wind': 2421.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.61,\n        'wind': 2387.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.32,\n        'wind': 2356.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.95,\n        'wind': 2282.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.0,\n        'wind': 2211.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.24,\n        'wind': 2156.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.49,\n        'wind': 2125.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.68,\n        'wind': 2070.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.63,\n        'wind': 2013.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.77,\n        'wind': 1945.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.62,\n        'wind': 1890.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.35,\n        'wind': 1850.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 2, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.97,\n        'wind': 1790.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.76,\n        'wind': 1726.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.59,\n        'wind': 1686.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.44,\n        'wind': 1655.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.31,\n        'wind': 1623.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.28,\n        'wind': 1573.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.25,\n        'wind': 1550.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.17,\n        'wind': 1542.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.16,\n        'wind': 1531.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.19,\n        'wind': 1535.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.4,\n        'wind': 1581.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.28,\n        'wind': 1588.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 3, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.13,\n        'wind': 1583.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 1561.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.89,\n        'wind': 1542.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.89,\n        'wind': 1541.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.66,\n        'wind': 1503.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.62,\n        'wind': 1508.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.55,\n        'wind': 1503.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.56,\n        'wind': 1499.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.51,\n        'wind': 1490.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.45,\n        'wind': 1468.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.49,\n        'wind': 1471.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.58,\n        'wind': 1511.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 4, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.8,\n        'wind': 1523.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.92,\n        'wind': 1521.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.11,\n        'wind': 1517.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.25,\n        'wind': 1533.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.41,\n        'wind': 1573.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.56,\n        'wind': 1568.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.69,\n        'wind': 1552.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.72,\n        'wind': 1537.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.51,\n        'wind': 1519.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.16,\n        'wind': 1508.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.03,\n        'wind': 1476.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.07,\n        'wind': 1476.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 5, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.04,\n        'wind': 1455.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.04,\n        'wind': 1452.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.11,\n        'wind': 1447.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.32,\n        'wind': 1450.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.45,\n        'wind': 1442.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.6,\n        'wind': 1445.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.76,\n        'wind': 1460.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.92,\n        'wind': 1464.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.09,\n        'wind': 1487.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.56,\n        'wind': 1502.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 4.23,\n        'wind': 1519.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 5.23,\n        'wind': 1541.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 6, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.35,\n        'wind': 1561.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.18,\n        'wind': 1572.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 11.07,\n        'wind': 1585.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 16.459999,\n        'wind': 1614.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 23.280001,\n        'wind': 1650.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 30.639999,\n        'wind': 1656.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 38.09,\n        'wind': 1669.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 44.419998,\n        'wind': 1650.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 49.470001,\n        'wind': 1649.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 54.450001,\n        'wind': 1669.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 59.68,\n        'wind': 1683.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 64.089996,\n        'wind': 1725.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 7, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 68.510002,\n        'wind': 1745.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 72.260002,\n        'wind': 1761.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 76.120003,\n        'wind': 1762.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 80.150002,\n        'wind': 1770.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 83.300003,\n        'wind': 1816.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 87.389999,\n        'wind': 1840.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 92.010002,\n        'wind': 1834.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 96.860001,\n        'wind': 1844.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 101.349998,\n        'wind': 1810.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 106.68,\n        'wind': 1791.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 112.0,\n        'wind': 1763.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 116.309998,\n        'wind': 1766.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 8, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 121.470001,\n        'wind': 1765.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 129.289993,\n        'wind': 1809.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 140.240005,\n        'wind': 1834.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 149.960007,\n      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}),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 161.320007,\n        'wind': 1868.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 161.869995,\n        'wind': 1877.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 162.529999,\n        'wind': 1882.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 167.729996,\n        'wind': 1882.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 177.529999,\n        'wind': 1900.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 186.639999,\n        'wind': 1911.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 9, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 193.979996,\n        'wind': 1935.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 198.570007,\n        'wind': 1978.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 204.169998,\n        'wind': 1952.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 205.080002,\n        'wind': 1963.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 206.179993,\n        'wind': 1972.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 206.839996,\n        'wind': 1960.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 211.529999,\n        'wind': 1983.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 213.25,\n        'wind': 1995.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 210.580002,\n        'wind': 1991.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 207.009995,\n        'wind': 2007.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 208.5,\n        'wind': 2025.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 213.839996,\n        'wind': 2077.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 10, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 218.820007,\n        'wind': 2095.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 216.960007,\n        'wind': 2091.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 212.380005,\n        'wind': 2082.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 205.990005,\n        'wind': 2102.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 200.100006,\n        'wind': 2128.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 193.330002,\n        'wind': 2142.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 190.350006,\n        'wind': 2155.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 194.279999,\n        'wind': 2176.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 199.289993,\n        'wind': 2191.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 202.339996,\n        'wind': 2201.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 201.350006,\n        'wind': 2217.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 199.25,\n        'wind': 2218.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 11, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 198.190002,\n        'wind': 2227.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 194.949997,\n        'wind': 2219.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 191.300003,\n        'wind': 2224.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 188.149994,\n        'wind': 2237.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 184.990005,\n        'wind': 2234.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 184.259995,\n        'wind': 2215.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 181.649994,\n        'wind': 2210.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 181.940002,\n        'wind': 2204.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 179.940002,\n        'wind': 2221.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 177.380005,\n        'wind': 2214.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 175.679993,\n        'wind': 2171.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 173.820007,\n        'wind': 2164.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 12, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 170.600006,\n        'wind': 2172.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.460007,\n        'wind': 2184.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 161.009995,\n        'wind': 2200.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 159.380005,\n        'wind': 2200.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 156.919998,\n        'wind': 2210.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 156.300003,\n        'wind': 2216.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 155.809998,\n        'wind': 2229.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.309998,\n        'wind': 2246.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.389999,\n        'wind': 2248.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 153.740005,\n        'wind': 2247.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 153.25,\n        'wind': 2263.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 153.050003,\n        'wind': 2273.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 13, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 153.960007,\n        'wind': 2278.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 157.75,\n        'wind': 2268.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 157.699997,\n        'wind': 2286.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 157.570007,\n        'wind': 2271.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 152.479996,\n        'wind': 2275.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 151.649994,\n        'wind': 2297.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 151.039993,\n        'wind': 2313.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.559998,\n        'wind': 2323.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.820007,\n        'wind': 2349.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 151.899994,\n        'wind': 2365.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 146.199997,\n        'wind': 2384.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 139.330002,\n        'wind': 2390.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 14, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 130.729996,\n        'wind': 2443.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 121.330002,\n        'wind': 2548.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 112.099998,\n        'wind': 2585.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 101.470001,\n        'wind': 2610.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 90.510002,\n        'wind': 2631.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 80.760002,\n        'wind': 2643.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 73.980003,\n        'wind': 2624.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 67.760002,\n        'wind': 2623.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 60.619999,\n        'wind': 2617.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 51.439999,\n        'wind': 2594.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 42.189999,\n        'wind': 2583.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 34.459999,\n        'wind': 2606.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 15, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 27.639999,\n        'wind': 2634.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 22.57,\n        'wind': 2643.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 19.24,\n        'wind': 2673.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 18.75,\n        'wind': 2699.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 18.1,\n        'wind': 2715.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 18.440001,\n        'wind': 2718.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 16.719999,\n        'wind': 2742.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 14.26,\n        'wind': 2788.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 11.67,\n        'wind': 2821.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.72,\n        'wind': 2821.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.07,\n        'wind': 2843.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.05,\n        'wind': 2896.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 16, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.33,\n        'wind': 2931.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.17,\n        'wind': 2931.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 5.79,\n        'wind': 2949.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 5.36,\n        'wind': 2955.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 5.09,\n        'wind': 2961.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 4.92,\n        'wind': 2964.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 5.65,\n        'wind': 2959.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.4,\n        'wind': 2960.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.12,\n        'wind': 2971.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.07,\n        'wind': 2978.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.03,\n        'wind': 2976.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.92,\n        'wind': 3006.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 17, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.82,\n        'wind': 3047.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.75,\n        'wind': 3123.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.19,\n        'wind': 3157.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.33,\n        'wind': 3183.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.04,\n        'wind': 3190.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.04,\n        'wind': 3187.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.57,\n        'wind': 3208.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.24,\n        'wind': 3237.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.8,\n        'wind': 3239.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.96,\n        'wind': 3243.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.58,\n        'wind': 3255.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.78,\n        'wind': 3271.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 18, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.15,\n        'wind': 3290.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.23,\n        'wind': 3288.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.15,\n        'wind': 3303.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.87,\n        'wind': 3321.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.79,\n        'wind': 3328.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.09,\n        'wind': 3318.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.23,\n        'wind': 3314.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.68,\n        'wind': 3295.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.81,\n        'wind': 3306.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.57,\n        'wind': 3313.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.65,\n        'wind': 3335.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.85,\n        'wind': 3349.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 19, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.03,\n        'wind': 3359.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.44,\n        'wind': 3370.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.64,\n        'wind': 3379.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.66,\n        'wind': 3387.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.84,\n        'wind': 3399.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.8,\n        'wind': 3405.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.82,\n        'wind': 3406.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.57,\n        'wind': 3410.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.6,\n        'wind': 3437.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.8,\n        'wind': 3441.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.99,\n        'wind': 3441.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.17,\n        'wind': 3437.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 20, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.99,\n        'wind': 3423.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.09,\n        'wind': 3402.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.93,\n        'wind': 3401.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.08,\n        'wind': 3393.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.8,\n        'wind': 3393.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.9,\n        'wind': 3412.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.97,\n        'wind': 3415.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.22,\n        'wind': 3406.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.04,\n        'wind': 3402.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.02,\n        'wind': 3403.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.01,\n        'wind': 3401.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.21,\n        'wind': 3391.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 21, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.75,\n        'wind': 3378.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 9.29,\n        'wind': 3364.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 5, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.82,\n        'wind': 3352.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 10, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 8.36,\n        'wind': 3341.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.89,\n        'wind': 3329.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 20, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7.43,\n        'wind': 3320.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 25, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.96,\n        'wind': 3312.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.5,\n        'wind': 3304.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 35, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.04,\n        'wind': 3290.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 40, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 5.57,\n        'wind': 3276.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 5.11,\n        'wind': 3269.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 50, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 4.64,\n        'wind': 3253.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 22, 55, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 4.18,\n        'wind': 3238.0,\n      }),\n      'source': 'energidataservice.dk',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DK-DK1',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_DO.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 30.02,\n        'coal': 940.42,\n        'gas': 914.61,\n        'hydro': 0.0,\n        'oil': 171.16,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 30.05,\n        'coal': 937.01,\n        'gas': 918.43,\n        'hydro': 0.0,\n        'oil': 198.85,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 30.1,\n        'coal': 936.61,\n        'gas': 867.07,\n        'hydro': 0.0,\n        'oil': 262.37,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 30.1,\n        'coal': 936.55,\n        'gas': 806.58,\n        'hydro': 0.0,\n        'oil': 264.72,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 29.72,\n        'coal': 932.76,\n        'gas': 827.35,\n        'hydro': 0.0,\n        'oil': 177.87,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 30.06,\n        'coal': 928.92,\n        'gas': 902.21,\n        'hydro': 0.0,\n        'oil': 119.51,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 28.46,\n        'coal': 930.8,\n        'gas': 928.82,\n        'hydro': 0.0,\n        'oil': 119.18,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 28.87,\n        'coal': 924.34,\n        'gas': 880.56,\n        'hydro': 114.06,\n        'oil': 126.49,\n        'solar': 23.9,\n        'wind': 9.91,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 27.89,\n        'coal': 924.49,\n        'gas': 772.35,\n        'hydro': 72.41,\n        'oil': 73.84,\n        'solar': 251.22,\n        'wind': 8.68,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 25.67,\n        'coal': 926.15,\n        'gas': 615.72,\n        'hydro': 67.23,\n        'oil': None,\n        'solar': 527.22,\n        'wind': 5.94,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 27.27,\n        'coal': 868.14,\n        'gas': 549.8,\n        'hydro': 65.77,\n        'oil': None,\n        'solar': 612.36,\n        'wind': 8.79,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 29.75,\n        'coal': 827.64,\n        'gas': 576.89,\n        'hydro': 58.3,\n        'oil': None,\n        'solar': 653.86,\n        'wind': 16.17,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 29.78,\n        'coal': 820.55,\n        'gas': 577.44,\n        'hydro': 54.27,\n        'oil': None,\n        'solar': 679.36,\n        'wind': 33.4,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 29.91,\n        'coal': 825.69,\n        'gas': 578.61,\n        'hydro': 42.51,\n        'oil': None,\n        'solar': 695.16,\n        'wind': 49.56,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 30.0,\n        'coal': 860.69,\n        'gas': 645.81,\n        'hydro': 42.39,\n        'oil': None,\n        'solar': 676.98,\n        'wind': 74.53,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 28.99,\n        'coal': 923.92,\n        'gas': 650.54,\n        'hydro': 42.53,\n        'oil': 2.09,\n        'solar': 599.58,\n        'wind': 83.42,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 29.19,\n        'coal': 933.95,\n        'gas': 794.39,\n        'hydro': 78.93,\n        'oil': 42.77,\n        'solar': 446.65,\n        'wind': 75.95,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Dominica')),\n      'production': dict({\n        'biomass': 30.09,\n        'coal': 932.86,\n        'gas': 810.65,\n        'hydro': 128.41,\n        'oil': 100.27,\n        'solar': 279.41,\n        'wind': 63.48,\n      }),\n      'source': 'oc.org.do',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'DO',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_EIA.ambr",
    "content": "# serializer version: 1\n# name: test_US_CAR_SC_nuclear_split\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 300.0,\n        'gas': 300.0,\n        'hydro': 300.0,\n        'nuclear': 330.666634,\n        'oil': 300.0,\n        'solar': 300.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAR-SC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 400.0,\n        'gas': 400.0,\n        'hydro': 400.0,\n        'nuclear': 330.3333,\n        'oil': 400.0,\n        'solar': 400.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAR-SC',\n    }),\n  ])\n# ---\n# name: test_US_CAR_SC_nuclear_split.1\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 300.0,\n        'gas': 300.0,\n        'hydro': 300.0,\n        'nuclear': 661.333366,\n        'oil': 300.0,\n        'solar': 300.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAR-SCEG',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 400.0,\n        'gas': 400.0,\n        'hydro': 400.0,\n        'nuclear': 660.6667,\n        'oil': 400.0,\n        'solar': 400.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAR-SCEG',\n    }),\n  ])\n# ---\n# name: test_US_NW_AVRN_rerouting\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 330.0,\n        'hydro': 300.0,\n        'solar': 300.0,\n        'wind': 300.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NW-PACW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 450.0,\n        'hydro': 400.0,\n        'solar': 400.0,\n        'wind': 400.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NW-PACW',\n    }),\n  ])\n# ---\n# name: test_US_NW_AVRN_rerouting.1\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 300.0,\n        'hydro': 300.0,\n        'nuclear': 300.0,\n        'solar': 300.0,\n        'wind': 21.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NW-BPAT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 400.0,\n        'hydro': 400.0,\n        'nuclear': 400.0,\n        'solar': 400.0,\n        'wind': 42.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NW-BPAT',\n    }),\n  ])\n# ---\n# name: test_fetch_production_mix\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.0,\n        'coal': 1.0,\n        'gas': 1.0,\n        'geothermal': 1.0,\n        'hydro': 1.0,\n        'nuclear': 1.0,\n        'oil': 1.0,\n        'solar': 1.0,\n        'unknown': 1.0,\n        'wind': 1.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.0,\n        'hydro': -1.0,\n      }),\n      'zoneKey': 'US-NW-PGE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'coal': 2.0,\n        'gas': 2.0,\n        'geothermal': 2.0,\n        'hydro': 2.0,\n        'nuclear': 2.0,\n        'oil': 2.0,\n        'solar': 2.0,\n        'unknown': 2.0,\n        'wind': 2.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.0,\n        'hydro': -2.0,\n      }),\n      'zoneKey': 'US-NW-PGE',\n    }),\n  ])\n# ---\n# name: test_fetch_production_mix_discards_null\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 400.0,\n        'coal': 400.0,\n        'gas': 400.0,\n        'geothermal': 400.0,\n        'hydro': 400.0,\n        'nuclear': 400.0,\n        'oil': 400.0,\n        'solar': 400.0,\n        'unknown': 400.0,\n        'wind': 400.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -400.0,\n        'hydro': -400.0,\n      }),\n      'zoneKey': 'US-NW-PGE',\n    }),\n  ])\n# ---\n# name: test_fetch_returns_storage\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 27, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.0,\n        'coal': 1.0,\n        'gas': 1.0,\n        'geothermal': 1.0,\n        'hydro': 1.0,\n        'nuclear': 1.0,\n        'oil': 1.0,\n        'solar': 1.0,\n        'unknown': 1.0,\n        'wind': 1.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.0,\n        'hydro': -1.0,\n      }),\n      'zoneKey': 'US-CAL-IID',\n    }),\n  ])\n# ---\n# name: test_hydro_transfer_mix\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 300.0,\n        'gas': 300.0,\n        'hydro': 7.0,\n        'nuclear': 300.0,\n        'solar': 300.0,\n        'wind': 300.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 5.0,\n      }),\n      'zoneKey': 'US-SW-SRP',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2022, 10, 31, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 400.0,\n        'gas': 400.0,\n        'hydro': 800.0,\n        'nuclear': 400.0,\n        'solar': 400.0,\n        'wind': 400.0,\n      }),\n      'source': 'eia.gov',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 900.0,\n      }),\n      'zoneKey': 'US-SW-SRP',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENERCAL.ambr",
    "content": "# serializer version: 1\n# name: test_production_with_snapshot\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 23.7,\n        'hydro': 35.9,\n        'oil': 32,\n        'solar': 0.3,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 20.7,\n        'hydro': 35.2,\n        'oil': 32.3,\n        'solar': 0,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 16.8,\n        'hydro': 35.7,\n        'oil': 33.8,\n        'solar': 0,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 21.1,\n        'hydro': 28.8,\n        'oil': 32,\n        'solar': 0,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 28.4,\n        'hydro': 21,\n        'oil': 32.6,\n        'solar': 0,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 27.8,\n        'hydro': 23.5,\n        'oil': 33.6,\n        'solar': 0.1,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 16.6,\n        'hydro': 34.5,\n        'oil': 33.7,\n        'solar': 3.6,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 20.2,\n        'hydro': 14,\n        'oil': 32.5,\n        'solar': 20,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 18.3,\n        'hydro': 0.3,\n        'oil': 27.3,\n        'solar': 34.6,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 12.8,\n        'hydro': 0.8,\n        'oil': 9.5,\n        'solar': 55.3,\n        'wind': 0.2,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 11.5,\n        'hydro': 1.4,\n        'oil': 5.9,\n        'solar': 53.1,\n        'wind': 1.3,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 9.4,\n        'hydro': 6.8,\n        'oil': 10.9,\n        'solar': 48.9,\n        'wind': 2,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 13.1,\n        'hydro': 10.2,\n        'oil': 27.9,\n        'solar': 41.5,\n        'wind': 3.4,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 16.5,\n        'hydro': 1.4,\n        'oil': 23.5,\n        'solar': 39.2,\n        'wind': 3.2,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 21.5,\n        'hydro': 6.8,\n        'oil': 17.8,\n        'solar': 24.6,\n        'wind': 2.4,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 18.5,\n        'hydro': 17.2,\n        'oil': 32,\n        'solar': 18.7,\n        'wind': 2.1,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 18.4,\n        'hydro': 34.6,\n        'oil': 36.4,\n        'solar': 14.2,\n        'wind': 2.2,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 20,\n        'hydro': 34.6,\n        'oil': 33.9,\n        'solar': 10.3,\n        'wind': 0.6,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 19.8,\n        'hydro': 37.5,\n        'oil': 34.9,\n        'solar': 3.1,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 21.3,\n        'hydro': 38.7,\n        'oil': 42.4,\n        'solar': 1.2,\n        'wind': 0,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 21.5,\n        'hydro': 39,\n        'oil': 44,\n        'solar': 0.5,\n        'wind': 0.1,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 20.2,\n        'hydro': 38.7,\n        'oil': 42.5,\n        'solar': 0,\n        'wind': 1.9,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 19,\n        'hydro': 38.6,\n        'oil': 37.1,\n        'solar': 0,\n        'wind': 3.2,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 1, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Noumea')),\n      'production': dict({\n        'coal': 17.3,\n        'hydro': 38.4,\n        'oil': 32,\n        'solar': 0.3,\n        'wind': 2.8,\n      }),\n      'source': 'enercal.nc',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'NC',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTE.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange\n  list([\n    dict({\n      'datetime': FakeDatetime(2024, 4, 3, 8, 37, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': -7.5,\n      'sortedZoneKeys': 'CR->NI',\n      'source': 'enteoperador.org',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'production': dict({\n        'unknown': 1460.3,\n      }),\n      'source': 'enteoperador.org',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'HN',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE/test_a03_curve_decompression[fake_time_series.xml].ambr",
    "content": "# serializer version: 1\n# name: test_a03_curve_decompression[fake_time_series.xml]\n  list([\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      value=0.9,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      value=0.7,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      value=0.6,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 16, 0, tzinfo=datetime.timezone.utc),\n      value=0.5,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 18, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 19, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 20, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 21, 0, tzinfo=datetime.timezone.utc),\n      value=0.2,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 22, 0, tzinfo=datetime.timezone.utc),\n      value=0.2,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      value=0.1,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      value=0.2,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      value=0.8,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      value=0.7,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      value=0.9,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      value=0.8,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      value=1.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      value=0.8,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      value=0.9,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      value=0.7,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      value=0.6,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      value=0.2,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      value=0.2,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 0, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 1, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 2, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 3, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 4, 0, tzinfo=datetime.timezone.utc),\n      value=0.2,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 5, 0, tzinfo=datetime.timezone.utc),\n      value=0.6,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 6, 0, tzinfo=datetime.timezone.utc),\n      value=0.7,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 7, 0, tzinfo=datetime.timezone.utc),\n      value=0.8,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 8, 0, tzinfo=datetime.timezone.utc),\n      value=0.8,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 9, 0, tzinfo=datetime.timezone.utc),\n      value=0.9,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 10, 0, tzinfo=datetime.timezone.utc),\n      value=0.9,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 11, 0, tzinfo=datetime.timezone.utc),\n      value=0.9,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 12, 0, tzinfo=datetime.timezone.utc),\n      value=0.8,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 13, 0, tzinfo=datetime.timezone.utc),\n      value=0.7,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 14, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 15, 0, tzinfo=datetime.timezone.utc),\n      value=0.2,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 16, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 17, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 18, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 19, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 20, 0, tzinfo=datetime.timezone.utc),\n      value=0.1,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 21, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 22, 0, tzinfo=datetime.timezone.utc),\n      value=0.2,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 23, 0, tzinfo=datetime.timezone.utc),\n      value=0.2,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 0, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 1, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 2, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 3, 0, tzinfo=datetime.timezone.utc),\n      value=0.4,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 4, 0, tzinfo=datetime.timezone.utc),\n      value=0.3,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 5, 0, tzinfo=datetime.timezone.utc),\n      value=0.5,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 6, 0, tzinfo=datetime.timezone.utc),\n      value=0.7,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 7, 0, tzinfo=datetime.timezone.utc),\n      value=0.8,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 8, 0, tzinfo=datetime.timezone.utc),\n      value=0.8,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 9, 0, tzinfo=datetime.timezone.utc),\n      value=0.9,\n    ),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE/test_a03_curve_decompression[fake_time_series_all_0.xml].ambr",
    "content": "# serializer version: 1\n# name: test_a03_curve_decompression[fake_time_series_all_0.xml]\n  list([\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 16, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n  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),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 0, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 1, 0, tzinfo=datetime.timezone.utc),\n 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tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 18, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 19, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 20, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 21, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 22, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 22, 23, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 0, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 1, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 2, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 3, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 4, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 5, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 6, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 7, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 8, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n    DateTimePoint(\n      dt=datetime.datetime(2025, 10, 23, 9, 0, tzinfo=datetime.timezone.utc),\n      value=0.0,\n    ),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE/test_production_with_snapshot[FI].ambr",
    "content": "# serializer version: 1\n# name: test_production_with_snapshot[FI]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 776.6,\n        'coal': 123.28,\n        'gas': 14.7,\n        'hydro': 961.81,\n        'nuclear': 4175.7,\n        'oil': 2.34,\n        'solar': 236.28,\n        'unknown': 145.01,\n        'wind': 4110.7,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 792.35,\n        'coal': 121.39,\n        'gas': 14.7,\n        'hydro': 933.71,\n        'nuclear': 4174.1,\n        'oil': 0.6,\n        'solar': 213.22,\n        'unknown': 139.41,\n        'wind': 4101.7,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 788.3,\n        'coal': 122.48,\n        'gas': 14.7,\n        'hydro': 979.03,\n        'nuclear': 4176.3,\n        'oil': 0.6,\n        'solar': 191.79,\n        'unknown': 135.13,\n        'wind': 4015.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 786.62,\n        'coal': 122.26,\n        'gas': 14.7,\n        'hydro': 1155.0,\n        'nuclear': 4175.3,\n        'oil': 0.6,\n        'solar': 173.18,\n        'unknown': 140.14,\n        'wind': 4022.4,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 808.4,\n        'coal': 127.69,\n        'gas': 14.7,\n        'hydro': 1314.7,\n        'nuclear': 4176.5,\n        'oil': 0.6,\n        'solar': 152.92,\n        'unknown': 146.06,\n        'wind': 4005.1,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 804.41,\n        'coal': 128.24,\n        'gas': 14.7,\n        'hydro': 1350.5,\n        'nuclear': 4174.9,\n        'oil': 0.6,\n        'solar': 126.54,\n        'unknown': 144.67,\n        'wind': 4125.1,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 804.52,\n        'coal': 130.76,\n        'gas': 14.7,\n        'hydro': 1364.7,\n        'nuclear': 4175.2,\n        'oil': 0.6,\n        'solar': 99.77,\n        'unknown': 144.5,\n        'wind': 4216.4,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 803.23,\n        'coal': 132.1,\n        'gas': 14.7,\n        'hydro': 1410.2,\n        'nuclear': 4174.1,\n        'oil': 0.6,\n        'solar': 74.25,\n        'unknown': 144.91,\n        'wind': 4354.8,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 804.52,\n        'coal': 131.12,\n        'gas': 14.7,\n        'hydro': 1437.6,\n        'nuclear': 4175.3,\n        'oil': 0.6,\n        'solar': 21.35,\n        'unknown': 144.19,\n        'wind': 4441.6,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 792.29,\n        'coal': 130.0,\n        'gas': 14.7,\n        'hydro': 1480.5,\n        'nuclear': 4175.2,\n        'oil': 0.6,\n        'solar': 13.49,\n        'unknown': 146.32,\n        'wind': 4551.1,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 791.71,\n        'coal': 127.66,\n        'gas': 14.7,\n        'hydro': 1468.6,\n        'nuclear': 4175.7,\n        'oil': 0.6,\n        'solar': 7.22,\n        'unknown': 145.85,\n        'wind': 4687.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 799.8,\n        'coal': 127.3,\n        'gas': 14.7,\n        'hydro': 1465.8,\n        'nuclear': 4177.0,\n        'oil': 0.6,\n        'solar': 1.96,\n        'unknown': 147.19,\n        'wind': 4920.2,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 803.89,\n        'coal': 129.03,\n        'gas': 14.7,\n        'hydro': 1467.4,\n        'nuclear': 4175.7,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 147.0,\n        'wind': 5185.9,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 804.41,\n        'coal': 127.83,\n        'gas': 14.7,\n        'hydro': 1435.4,\n        'nuclear': 4175.0,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 146.5,\n        'wind': 5375.1,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 802.16,\n        'coal': 125.51,\n        'gas': 14.7,\n        'hydro': 1288.3,\n        'nuclear': 4175.5,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 147.48,\n        'wind': 5405.3,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 787.62,\n        'coal': 123.43,\n        'gas': 14.7,\n        'hydro': 1251.5,\n        'nuclear': 4176.4,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 148.75,\n        'wind': 5574.4,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 788.74,\n        'coal': 126.06,\n        'gas': 14.7,\n        'hydro': 1247.5,\n        'nuclear': 4175.0,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 151.41,\n        'wind': 5669.9,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 789.3,\n        'coal': 129.35,\n        'gas': 14.7,\n        'hydro': 1247.1,\n        'nuclear': 4175.2,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 152.71,\n        'wind': 5609.6,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 787.92,\n        'coal': 129.6,\n        'gas': 14.7,\n        'hydro': 1236.0,\n        'nuclear': 4175.6,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 153.37,\n        'wind': 5705.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 774.79,\n        'coal': 129.6,\n        'gas': 14.7,\n        'hydro': 1236.7,\n        'nuclear': 4175.4,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 144.6,\n        'wind': 5821.4,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 769.04,\n        'coal': 129.6,\n        'gas': 14.7,\n        'hydro': 1143.4,\n        'nuclear': 4176.2,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 141.1,\n        'wind': 5821.4,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 775.39,\n        'coal': 129.6,\n        'gas': 14.7,\n        'hydro': 1100.8,\n        'nuclear': 4176.6,\n        'oil': 0.6,\n        'solar': 1.8,\n        'unknown': 142.01,\n        'wind': 5877.7,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 771.99,\n        'coal': 129.6,\n        'gas': 14.7,\n        'hydro': 1090.9,\n        'nuclear': 4175.6,\n        'oil': 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'biomass': 718.4,\n        'coal': 127.0,\n        'gas': 14.7,\n        'hydro': 648.32,\n        'nuclear': 3550.5,\n        'oil': 0.6,\n        'solar': 1.6,\n        'unknown': 115.45,\n        'wind': 5523.2,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 22, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 718.05,\n        'coal': 127.0,\n        'gas': 14.7,\n        'hydro': 675.73,\n        'nuclear': 3573.2,\n        'oil': 0.6,\n        'solar': 1.6,\n        'unknown': 114.29,\n        'wind': 5419.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n  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}),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 873.437,\n        'coal': 242.15,\n        'gas': 14.7,\n        'hydro': 1835.7,\n        'nuclear': 4046.3,\n        'oil': 0.0,\n        'solar': 90.317,\n        'unknown': 178.24,\n        'wind': 584.63,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 881.399,\n        'coal': 241.14,\n        'gas': 14.7,\n        'hydro': 1803.9,\n        'nuclear': 4045.2,\n        'oil': 0.0,\n        'solar': 86.473,\n        'unknown': 176.61,\n        'wind': 573.06,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 885.1,\n        'coal': 227.51,\n        'gas': 14.7,\n        'hydro': 1745.8,\n        'nuclear': 4046.6,\n        'oil': 0.0,\n        'solar': 88.02,\n        'unknown': 167.87,\n        'wind': 576.86,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 895.03,\n        'coal': 243.97,\n        'gas': 14.7,\n        'hydro': 1789.3,\n        'nuclear': 4045.2,\n        'oil': 0.0,\n        'solar': 88.713,\n        'unknown': 156.91,\n        'wind': 570.8,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 894.051,\n        'coal': 241.3,\n        'gas': 14.7,\n        'hydro': 1877.8,\n        'nuclear': 4046.0,\n        'oil': 0.0,\n        'solar': 89.2,\n        'unknown': 157.22,\n        'wind': 563.73,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 894.073,\n        'coal': 234.99,\n        'gas': 14.7,\n        'hydro': 1889.3,\n        'nuclear': 4044.1,\n        'oil': 0.0,\n        'solar': 87.154,\n        'unknown': 159.1,\n        'wind': 586.03,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 886.81,\n        'coal': 232.509,\n        'gas': 14.7,\n        'hydro': 1891.2,\n        'nuclear': 4046.7,\n        'oil': 0.0,\n        'solar': 89.123,\n        'unknown': 164.32,\n        'wind': 585.04,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 892.047,\n        'coal': 232.147,\n        'gas': 14.7,\n        'hydro': 1887.7,\n        'nuclear': 4031.2,\n        'oil': 0.0,\n        'solar': 94.17,\n        'unknown': 171.07,\n        'wind': 583.36,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 881.287,\n        'coal': 225.427,\n        'gas': 15.859,\n        'hydro': 1848.0,\n        'nuclear': 4023.3,\n        'oil': 0.0,\n        'solar': 88.181,\n        'unknown': 169.01,\n        'wind': 569.3,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 867.647,\n        'coal': 219.2,\n        'gas': 28.218,\n        'hydro': 1795.8,\n        'nuclear': 4023.0,\n        'oil': 0.0,\n        'solar': 80.427,\n        'unknown': 168.9,\n        'wind': 573.07,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 892.86,\n        'coal': 212.97,\n        'gas': 33.2,\n        'hydro': 1803.1,\n        'nuclear': 4022.0,\n        'oil': 0.0,\n        'solar': 74.886,\n        'unknown': 180.79,\n        'wind': 581.1,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 24, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 928.823,\n        'coal': 228.6,\n        'gas': 33.2,\n        'hydro': 1877.9,\n        'nuclear': 4021.9,\n        'oil': 0.0,\n        'solar': 69.748,\n        'unknown': 179.69,\n        'wind': 580.87,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE/test_production_with_snapshot[LU].ambr",
    "content": "# serializer version: 1\n# name: test_production_with_snapshot[LU]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 51.0,\n        'wind': 2.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 29.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 50.0,\n        'wind': 2.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 29.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 51.0,\n        'wind': 4.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 51.0,\n        'wind': 3.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 47.0,\n        'wind': 2.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 46.0,\n        'wind': 3.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 7.0,\n        'hydro': 14.0,\n        'solar': 44.0,\n        'wind': 5.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 7.0,\n        'hydro': 14.0,\n        'solar': 42.0,\n        'wind': 5.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 7.0,\n        'hydro': 14.0,\n        'solar': 37.0,\n        'wind': 5.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 7.0,\n        'hydro': 14.0,\n        'solar': 36.0,\n        'wind': 4.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 8.0,\n        'hydro': 14.0,\n        'solar': 39.0,\n        'wind': 3.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 35.0,\n        'gas': 8.0,\n        'hydro': 14.0,\n        'solar': 41.0,\n        'wind': 3.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 35.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 46.0,\n        'wind': 3.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 36.0,\n        'gas': 5.0,\n        'hydro': 14.0,\n        'solar': 48.0,\n        'wind': 3.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 39.0,\n        'gas': 5.0,\n        'hydro': 14.0,\n        'solar': 52.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 47.0,\n        'gas': 4.0,\n        'hydro': 13.0,\n        'solar': 54.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 51.0,\n        'gas': 6.0,\n        'hydro': 13.0,\n        'solar': 59.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 51.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 62.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 40.0,\n        'gas': 5.0,\n        'hydro': 14.0,\n        'solar': 65.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 5.0,\n        'hydro': 14.0,\n        'solar': 68.0,\n        'wind': 2.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 34.0,\n        'gas': 5.0,\n        'hydro': 13.0,\n        'solar': 67.0,\n        'wind': 3.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 5.0,\n        'hydro': 13.0,\n        'solar': 64.0,\n        'wind': 4.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 34.0,\n        'gas': 6.0,\n        'hydro': 13.0,\n        'solar': 56.0,\n        'wind': 5.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 6.0,\n        'hydro': 13.0,\n        'solar': 47.0,\n        'wind': 4.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 6.0,\n        'hydro': 13.0,\n        'solar': 42.0,\n        'wind': 3.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 29.0,\n        'gas': 5.0,\n        'hydro': 13.0,\n        'solar': 42.0,\n        'wind': 4.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 5.0,\n        'hydro': 13.0,\n        'solar': 43.0,\n        'wind': 6.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 4.0,\n        'hydro': 13.0,\n        'solar': 40.0,\n        'wind': 6.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 6.0,\n        'hydro': 13.0,\n        'solar': 34.0,\n        'wind': 6.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 6.0,\n        'hydro': 13.0,\n        'solar': 28.0,\n        'wind': 6.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 6.0,\n        'hydro': 13.0,\n        'solar': 22.0,\n        'wind': 8.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 18.0,\n        'wind': 9.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 7.0,\n        'hydro': 14.0,\n        'solar': 13.0,\n        'wind': 10.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 7.0,\n        'hydro': 14.0,\n        'solar': 9.0,\n        'wind': 10.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 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 'wind': 8.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 7.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 6.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 7.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 6.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': 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tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 17.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 17.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 22.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 26.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 34.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 44.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 21, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 41.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      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tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 25.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 29.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 33.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 33.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 35.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 30.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 34.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 37.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 34.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 46.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 54.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 34.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 61.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 66.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 34.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 70.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 69.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 70.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 1.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 60.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 4.0,\n        'hydro': 14.0,\n        'solar': 1.0,\n        'wind': 45.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 6.0,\n        'hydro': 14.0,\n        'solar': 2.0,\n        'wind': 37.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 9.0,\n        'hydro': 14.0,\n        'solar': 4.0,\n        'wind': 37.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 22, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 10.0,\n        'hydro': 14.0,\n        'solar': 6.0,\n       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datetime.datetime(2024, 5, 23, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 29.0,\n        'gas': 4.0,\n        'hydro': 15.0,\n        'solar': 88.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 3.0,\n        'hydro': 15.0,\n        'solar': 75.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 16, 0, tzinfo=datetime.timezone.utc),\n      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'hydro': 15.0,\n        'solar': 44.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 29.0,\n        'gas': 4.0,\n        'hydro': 15.0,\n        'solar': 35.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 4.0,\n        'hydro': 15.0,\n        'solar': 28.0,\n        'wind': 1.0,\n      }),\n      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}),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 5.0,\n        'hydro': 15.0,\n        'solar': 5.0,\n        'wind': 8.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 6.0,\n        'hydro': 15.0,\n        'solar': 3.0,\n        'wind': 9.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 6.0,\n        'hydro': 15.0,\n        'solar': 1.0,\n        'wind': 9.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 6.0,\n        'hydro': 15.0,\n        'solar': 1.0,\n        'wind': 7.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 29.0,\n        'gas': 7.0,\n        'hydro': 15.0,\n        'solar': 0.0,\n        'wind': 5.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 7.0,\n        'hydro': 15.0,\n        'solar': 0.0,\n        'wind': 4.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 6.0,\n        'hydro': 15.0,\n        'solar': 0.0,\n        'wind': 6.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 3.0,\n        'hydro': 15.0,\n        'solar': 0.0,\n        'wind': 6.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 1.0,\n        'hydro': 15.0,\n        'solar': 0.0,\n        'wind': 5.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 0.0,\n        'hydro': 16.0,\n        'solar': 0.0,\n        'wind': 3.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 1.0,\n        'hydro': 16.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 30.0,\n        'gas': 0.0,\n        'hydro': 16.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 0.0,\n        'hydro': 16.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 31.0,\n        'gas': 0.0,\n        'hydro': 16.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 32.0,\n        'gas': 0.0,\n        'hydro': 16.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 59.0,\n        'gas': 6.0,\n        'hydro': 15.0,\n        'solar': 0.0,\n        'wind': 4.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 56.0,\n        'gas': 3.0,\n        'hydro': 13.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 55.0,\n        'gas': 1.0,\n        'hydro': 12.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 56.0,\n        'gas': 0.0,\n        'hydro': 13.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 57.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 58.0,\n        'gas': 0.0,\n        'hydro': 12.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 56.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 23, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 56.0,\n        'gas': 0.0,\n        'hydro': 12.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 59.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 57.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 56.0,\n        'gas': 0.0,\n        'hydro': 12.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 53.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 55.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 53.0,\n        'gas': 0.0,\n        'hydro': 13.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 53.0,\n        'gas': 0.0,\n        'hydro': 12.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 53.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 52.0,\n        'gas': 0.0,\n        'hydro': 12.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 54.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 53.0,\n        'gas': 0.0,\n        'hydro': 11.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 54.0,\n        'gas': 0.0,\n        'hydro': 11.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 55.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 54.0,\n        'gas': 0.0,\n        'hydro': 14.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 54.0,\n        'gas': 0.0,\n        'hydro': 11.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 57.0,\n        'gas': 7.0,\n        'hydro': 12.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 54.0,\n        'gas': 15.0,\n        'hydro': 12.0,\n        'solar': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 53.0,\n        'gas': 26.0,\n        'hydro': 12.0,\n        'solar': 1.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 54.0,\n        'gas': 31.0,\n        'hydro': 12.0,\n        'solar': 2.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 57.0,\n        'gas': 35.0,\n        'hydro': 14.0,\n        'solar': 2.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 55.0,\n        'gas': 48.0,\n        'hydro': 14.0,\n        'solar': 3.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 53.0,\n        'gas': 23.0,\n        'hydro': 12.0,\n        'solar': 4.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 55.0,\n        'gas': 25.0,\n        'hydro': 14.0,\n        'solar': 5.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 54.0,\n        'gas': 37.0,\n        'hydro': 14.0,\n        'solar': 6.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 52.0,\n        'gas': 13.0,\n        'hydro': 14.0,\n        'solar': 6.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 50.0,\n        'gas': 20.0,\n        'hydro': 13.0,\n        'solar': 7.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 48.0,\n        'gas': 21.0,\n        'hydro': 13.0,\n        'solar': 9.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 50.0,\n        'gas': 18.0,\n        'hydro': 13.0,\n        'solar': 11.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 56.0,\n        'gas': 29.0,\n        'hydro': 13.0,\n        'solar': 13.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 33.0,\n        'gas': 0.0,\n        'hydro': 0.0,\n        'solar': 13.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 41.0,\n        'gas': 14.0,\n        'hydro': 14.0,\n        'solar': 17.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 43.0,\n        'gas': 12.0,\n        'hydro': 14.0,\n        'solar': 21.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 44.0,\n        'gas': 13.0,\n        'hydro': 14.0,\n        'solar': 25.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 43.0,\n        'gas': 17.0,\n        'hydro': 14.0,\n        'solar': 28.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 43.0,\n        'gas': 3.0,\n        'hydro': 12.0,\n        'solar': 29.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 45.0,\n        'gas': 10.0,\n        'hydro': 13.0,\n        'solar': 31.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 44.0,\n        'gas': 4.0,\n        'hydro': 14.0,\n        'solar': 34.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 43.0,\n        'gas': 3.0,\n        'hydro': 14.0,\n        'solar': 38.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 5, 24, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 44.0,\n        'gas': 6.0,\n        'hydro': 12.0,\n        'solar': 39.0,\n        'wind': 0.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'LU',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE/test_production_with_snapshot[NO-NO5].ambr",
    "content": "# serializer version: 1\n# name: test_production_with_snapshot[NO-NO5]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1065.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 969.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1011.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 0.0,\n        'hydro': 1177.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1317.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 1547.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 1950.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 2009.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 2053.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 2011.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2042.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1932.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 0.0,\n        'hydro': 1879.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1629.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1520.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1491.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1467.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -60.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 1513.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1552.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 1957.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -78.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2341.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -157.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2344.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -161.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2214.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -118.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2062.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -60.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 0.0,\n        'hydro': 2198.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -60.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2191.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -35.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 2200.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 0.0,\n        'hydro': 2157.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2279.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2583.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2733.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2637.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2725.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2880.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -33.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2756.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -33.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2632.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -33.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2603.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2546.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -70.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2390.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -70.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2393.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -71.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2394.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -71.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2449.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -71.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2700.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -73.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 1.0,\n        'hydro': 3155.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -74.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 0.0,\n        'hydro': 3440.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -74.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 3819.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -190.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 3677.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -114.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE/test_production_with_snapshot[SE-SE4].ambr",
    "content": "# serializer version: 1\n# name: test_production_with_snapshot[SE-SE4]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.9,\n        'hydro': 90.23,\n        'solar': 300.51,\n        'unknown': 184.23,\n        'wind': 1434.47,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.7,\n        'hydro': 90.23,\n        'solar': 250.13,\n        'unknown': 176.87,\n        'wind': 1399.7,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.6,\n        'hydro': 90.22,\n        'solar': 164.41,\n        'unknown': 172.11,\n        'wind': 1367.78,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.4,\n        'hydro': 91.13,\n        'solar': 71.24,\n        'unknown': 170.46,\n        'wind': 1353.7,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.4,\n        'hydro': 96.14,\n        'solar': 10.1,\n        'unknown': 166.67,\n        'wind': 1401.78,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.5,\n        'hydro': 97.02,\n        'solar': 1.63,\n        'unknown': 175.77,\n        'wind': 1505.79,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.4,\n        'hydro': 95.01,\n        'solar': 1.61,\n        'unknown': 176.44,\n        'wind': 1584.07,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.4,\n        'hydro': 47.0,\n        'solar': 1.6,\n        'unknown': 155.37,\n        'wind': 1619.49,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.4,\n        'hydro': 43.72,\n        'solar': 1.62,\n        'unknown': 148.88,\n        'wind': 1620.61,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.3,\n        'hydro': 36.28,\n        'solar': 1.61,\n        'unknown': 147.8,\n        'wind': 1576.38,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.2,\n        'hydro': 30.64,\n        'solar': 1.59,\n        'unknown': 141.83,\n        'wind': 1523.93,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.2,\n        'hydro': 30.42,\n        'solar': 1.61,\n        'unknown': 145.35,\n        'wind': 1538.7,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.1,\n        'hydro': 30.41,\n        'solar': 1.55,\n        'unknown': 141.38,\n        'wind': 1471.41,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.3,\n        'hydro': 31.24,\n        'solar': 1.55,\n        'unknown': 142.64,\n        'wind': 1435.03,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 32.19,\n        'solar': 1.51,\n        'unknown': 139.72,\n        'wind': 1421.61,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.4,\n        'hydro': 33.38,\n        'solar': 1.49,\n        'unknown': 137.79,\n        'wind': 1437.14,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.4,\n        'hydro': 41.61,\n        'solar': 1.47,\n        'unknown': 144.99,\n        'wind': 1452.18,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.2,\n        'hydro': 47.53,\n        'solar': 1.45,\n        'unknown': 154.99,\n        'wind': 1428.93,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.8,\n        'hydro': 58.41,\n        'solar': 1.85,\n        'unknown': 155.28,\n        'wind': 1434.73,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.7,\n        'hydro': 55.16,\n        'solar': 4.03,\n        'unknown': 149.29,\n        'wind': 1414.15,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.9,\n        'hydro': 54.1,\n        'solar': 18.91,\n        'unknown': 147.19,\n        'wind': 1383.86,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.8,\n        'hydro': 37.16,\n        'solar': 38.52,\n        'unknown': 149.85,\n        'wind': 1338.12,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 1.0,\n        'hydro': 40.08,\n        'solar': 60.84,\n        'unknown': 147.82,\n        'wind': 1306.66,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': 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tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.3,\n        'hydro': 55.63225,\n        'solar': 1.0945,\n        'unknown': 126.912,\n        'wind': 107.64775,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 23, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.5,\n        'hydro': 86.885,\n        'solar': 1.19775,\n        'unknown': 127.9035,\n        'wind': 150.92675,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 23, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.7,\n        'hydro': 85.15275,\n        'solar': 4.3105,\n        'unknown': 126.171,\n        'wind': 218.576,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 23, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.8,\n        'hydro': 87.76075,\n        'solar': 20.73975,\n        'unknown': 127.5785,\n        'wind': 299.371,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 23, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.8,\n        'hydro': 86.48775,\n        'solar': 44.0625,\n        'unknown': 144.81475,\n        'wind': 402.71525,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 10, 23, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'gas': 0.9,\n        'hydro': 80.24725,\n        'solar': 66.613,\n        'unknown': 149.37175,\n        'wind': 506.93375,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SE-SE4',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE/test_wind_and_solar_forecasts_by_type[current].ambr",
    "content": "# serializer version: 1\n# name: test_wind_and_solar_forecasts_by_type[current]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1860.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1866.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1876.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1897.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1802.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1811.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1825.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1860.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1791.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1800.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1815.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1849.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1795.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1803.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1816.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1841.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1711.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1722.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1742.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1781.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1813.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1825.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1845.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1884.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2008.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2019.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2039.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2081.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2230.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2239.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2253.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2291.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 30.0,\n        'wind': 2513.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 33.0,\n        'wind': 2516.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 40.0,\n        'wind': 2511.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 55.0,\n        'wind': 2540.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 94.0,\n        'wind': 2651.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 97.0,\n        'wind': 2619.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 101.0,\n        'wind': 2561.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 111.0,\n        'wind': 2452.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 148.0,\n        'wind': 1963.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 149.0,\n        'wind': 1941.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 150.0,\n        'wind': 1904.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 153.0,\n        'wind': 1826.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 1927.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 1907.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 1876.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 1799.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 172.0,\n        'wind': 1850.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 170.0,\n        'wind': 1844.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 1836.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 157.0,\n        'wind': 1808.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 127.0,\n        'wind': 1718.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 124.0,\n        'wind': 1729.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 117.0,\n        'wind': 1750.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 104.0,\n        'wind': 1789.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 65.0,\n        'wind': 1797.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 62.0,\n        'wind': 1812.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 57.0,\n        'wind': 1840.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 43.0,\n        'wind': 1895.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1946.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1961.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1986.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2042.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2112.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2119.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2131.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2161.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2199.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2200.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2201.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2208.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2323.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2315.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2298.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2424.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2411.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2388.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2487.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2476.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2457.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2419.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2456.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2442.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2418.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2368.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2487.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2472.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2447.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2391.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2220.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2208.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2187.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2145.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2088.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2077.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2059.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2020.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1966.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1957.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1941.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1906.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1762.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1755.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1742.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1722.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1574.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1566.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1552.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1522.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1372.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1368.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1361.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1345.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1272.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1272.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1271.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1271.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1351.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1349.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1345.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1342.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1368.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1361.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1348.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 13.0,\n        'wind': 1327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 45.0,\n        'wind': 1351.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 49.0,\n        'wind': 1341.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 57.0,\n        'wind': 1326.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 73.0,\n        'wind': 1285.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 124.0,\n        'wind': 1151.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 128.0,\n        'wind': 1153.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 133.0,\n        'wind': 1157.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 146.0,\n        'wind': 1161.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 181.0,\n        'wind': 1028.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 182.0,\n        'wind': 1024.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 184.0,\n        'wind': 1019.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 190.0,\n        'wind': 1007.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 209.0,\n        'wind': 834.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 208.0,\n        'wind': 826.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 206.0,\n        'wind': 813.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 202.0,\n        'wind': 785.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 195.0,\n        'wind': 646.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 192.0,\n        'wind': 642.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 187.0,\n        'wind': 635.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 178.0,\n        'wind': 619.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.0,\n        'wind': 529.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 150.0,\n        'wind': 529.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 142.0,\n        'wind': 530.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 127.0,\n        'wind': 528.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 88.0,\n        'wind': 442.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 83.0,\n        'wind': 447.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 76.0,\n        'wind': 456.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 57.0,\n        'wind': 475.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 486.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 491.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 499.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 514.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 552.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 557.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 565.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 580.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 619.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 624.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 631.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 651.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 759.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 757.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 753.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 746.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 730.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 725.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 717.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 697.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 658.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 637.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 627.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 621.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 627.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 625.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 620.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 615.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 611.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 605.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 599.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 592.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 584.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 576.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 568.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 558.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 548.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 539.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 530.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 521.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 511.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 503.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 497.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 489.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 478.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 474.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 475.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 479.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 485.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 496.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 511.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 530.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 553.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 579.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 607.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 640.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 677.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 715.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 752.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 796.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 848.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 891.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 927.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 965.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1008.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1036.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1053.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 13.0,\n        'wind': 1066.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 34.0,\n        'wind': 1075.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 49.0,\n        'wind': 1072.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 62.0,\n        'wind': 1063.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 78.0,\n        'wind': 1032.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 95.0,\n        'wind': 965.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 109.0,\n        'wind': 934.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 121.0,\n        'wind': 922.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 133.0,\n        'wind': 924.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 144.0,\n        'wind': 953.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 153.0,\n        'wind': 960.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 160.0,\n        'wind': 953.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 164.0,\n        'wind': 952.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 959.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 943.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 914.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 866.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 164.0,\n        'wind': 791.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 160.0,\n        'wind': 734.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.0,\n        'wind': 687.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 147.0,\n        'wind': 630.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 137.0,\n        'wind': 557.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 127.0,\n        'wind': 512.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 116.0,\n        'wind': 487.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 103.0,\n        'wind': 468.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 88.0,\n        'wind': 457.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 74.0,\n        'wind': 464.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 61.0,\n        'wind': 485.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 44.0,\n        'wind': 524.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 20.0,\n        'wind': 589.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.0,\n        'wind': 649.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.0,\n        'wind': 707.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 784.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 886.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 963.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1024.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1084.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1137.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1184.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1225.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1260.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1288.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1310.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1328.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1337.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1334.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1336.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1339.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1337.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1325.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1331.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1339.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1346.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1352.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1364.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1384.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1392.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1394.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1390.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1380.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1371.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1364.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1347.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1315.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1304.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1304.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1313.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1335.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1353.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1369.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1391.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1419.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1443.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1464.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1486.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1509.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1529.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1548.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1564.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1578.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1592.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1608.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1621.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1631.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1645.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1661.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1684.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1718.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1737.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1746.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1751.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE/test_wind_and_solar_forecasts_by_type[day_ahead].ambr",
    "content": "# serializer version: 1\n# name: test_wind_and_solar_forecasts_by_type[day_ahead]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2224.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2223.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2221.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2218.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2210.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2206.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2205.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2205.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2206.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2209.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2213.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2219.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2227.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2236.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2244.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2254.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2266.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2277.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2287.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2297.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2306.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2316.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2328.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2343.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2361.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2375.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2385.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2399.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2421.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2427.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2425.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 12.0,\n        'wind': 2406.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 30.0,\n        'wind': 2359.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 45.0,\n        'wind': 2341.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 59.0,\n        'wind': 2349.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 75.0,\n        'wind': 2338.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 94.0,\n        'wind': 2290.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 110.0,\n        'wind': 2324.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 123.0,\n        'wind': 2397.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 137.0,\n        'wind': 2559.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 151.0,\n        'wind': 2876.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 161.0,\n        'wind': 3033.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 170.0,\n        'wind': 3092.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 177.0,\n        'wind': 3124.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 184.0,\n        'wind': 3105.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 187.0,\n        'wind': 3062.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 188.0,\n        'wind': 2994.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 187.0,\n        'wind': 2874.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 183.0,\n        'wind': 2684.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 178.0,\n        'wind': 2517.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 171.0,\n        'wind': 2363.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 163.0,\n        'wind': 2167.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 153.0,\n        'wind': 1907.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 141.0,\n        'wind': 1721.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 128.0,\n        'wind': 1587.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 112.0,\n        'wind': 1456.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 92.0,\n        'wind': 1327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 75.0,\n        'wind': 1255.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 60.0,\n        'wind': 1222.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 42.0,\n        'wind': 1246.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 18.0,\n        'wind': 1351.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 4.0,\n        'wind': 1417.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 1464.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1531.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1615.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1687.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1749.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1818.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1896.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1955.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1999.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2034.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2058.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2077.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2091.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2097.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2093.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2086.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2076.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2057.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2029.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2002.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1975.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1943.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1906.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1870.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1834.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1795.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1749.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1710.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1677.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1640.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1597.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1571.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1557.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1549.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1727.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1722.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1712.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1698.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1678.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1654.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1626.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1589.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1540.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1498.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1460.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1416.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1361.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1322.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1294.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1274.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1265.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1254.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1241.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1238.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1249.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1244.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1228.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1210.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1187.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1160.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1131.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1092.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1039.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1000.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 971.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 14.0,\n        'wind': 935.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 35.0,\n        'wind': 887.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 52.0,\n        'wind': 867.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 67.0,\n        'wind': 867.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 84.0,\n        'wind': 885.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 104.0,\n        'wind': 932.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 122.0,\n        'wind': 966.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 137.0,\n        'wind': 993.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 152.0,\n        'wind': 1033.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 169.0,\n        'wind': 1092.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 181.0,\n        'wind': 1127.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 190.0,\n        'wind': 1146.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 198.0,\n        'wind': 1158.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 204.0,\n        'wind': 1157.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 207.0,\n        'wind': 1156.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 208.0,\n        'wind': 1148.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 208.0,\n        'wind': 1141.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 205.0,\n        'wind': 1141.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 200.0,\n        'wind': 1114.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 193.0,\n        'wind': 1070.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 183.0,\n        'wind': 1003.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 170.0,\n        'wind': 897.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 157.0,\n        'wind': 817.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 143.0,\n        'wind': 754.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 126.0,\n        'wind': 677.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 106.0,\n        'wind': 579.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 87.0,\n        'wind': 521.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 71.0,\n        'wind': 488.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 50.0,\n        'wind': 479.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 22.0,\n        'wind': 505.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.0,\n        'wind': 517.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.0,\n        'wind': 522.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 542.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 582.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 601.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 609.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 611.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 603.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 598.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 595.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 588.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 577.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 569.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 563.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 557.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 554.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 548.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 542.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 535.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 527.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 520.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 515.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 508.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 501.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 497.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 494.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 493.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 496.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 497.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 496.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 495.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 493.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 492.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 492.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 492.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 542.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 540.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 537.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 531.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 521.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 513.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 507.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 497.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 482.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 476.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 476.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 479.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 486.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 495.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 508.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 523.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 538.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 561.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 589.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 625.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 671.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 713.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 752.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 797.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 850.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 894.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 930.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 967.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1007.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1035.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1052.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 13.0,\n        'wind': 1066.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 33.0,\n        'wind': 1077.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 48.0,\n        'wind': 1075.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 61.0,\n        'wind': 1066.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 76.0,\n        'wind': 1036.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 94.0,\n        'wind': 971.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 108.0,\n        'wind': 941.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 120.0,\n        'wind': 929.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 132.0,\n        'wind': 930.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 145.0,\n        'wind': 957.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.0,\n        'wind': 963.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 161.0,\n        'wind': 955.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 953.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 958.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 167.0,\n        'wind': 941.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 167.0,\n        'wind': 911.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 864.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 164.0,\n        'wind': 790.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 160.0,\n        'wind': 733.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 155.0,\n        'wind': 687.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 148.0,\n        'wind': 630.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 140.0,\n        'wind': 557.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 130.0,\n        'wind': 512.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 119.0,\n        'wind': 487.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 107.0,\n        'wind': 469.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 92.0,\n        'wind': 458.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 77.0,\n        'wind': 465.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 63.0,\n        'wind': 486.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 46.0,\n        'wind': 526.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 20.0,\n        'wind': 591.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.0,\n        'wind': 651.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.0,\n        'wind': 710.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 788.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 891.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 969.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1031.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1090.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1142.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1188.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1229.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1264.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1293.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1316.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1334.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1343.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1339.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1340.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1343.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1340.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1329.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1329.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1333.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1341.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1348.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1355.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1367.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1389.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1398.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1400.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1394.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1375.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1366.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1364.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1362.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE/test_wind_and_solar_forecasts_by_type[intraday].ambr",
    "content": "# serializer version: 1\n# name: test_wind_and_solar_forecasts_by_type[intraday]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2036.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2016.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2008.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2004.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1539.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1532.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1522.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1490.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1419.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1393.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1393.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1407.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1449.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1482.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1512.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1548.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1584.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1631.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1684.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1752.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1846.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1916.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1973.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2028.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2076.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2122.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2164.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2197.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2216.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2246.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2281.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2326.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2392.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2429.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2449.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.0,\n        'wind': 2454.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 24.0,\n        'wind': 2432.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 36.0,\n        'wind': 2427.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 48.0,\n        'wind': 2423.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 64.0,\n        'wind': 2446.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 84.0,\n        'wind': 2527.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 100.0,\n        'wind': 2514.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 114.0,\n        'wind': 2446.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 130.0,\n        'wind': 2322.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 147.0,\n        'wind': 2104.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 159.0,\n        'wind': 1944.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 169.0,\n        'wind': 1817.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 176.0,\n        'wind': 1668.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 180.0,\n        'wind': 1491.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 183.0,\n        'wind': 1361.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 185.0,\n        'wind': 1264.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 186.0,\n        'wind': 1184.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 185.0,\n        'wind': 1130.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 181.0,\n        'wind': 1085.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 175.0,\n        'wind': 1050.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 1034.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.0,\n        'wind': 1039.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 142.0,\n        'wind': 1050.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 128.0,\n        'wind': 1069.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 113.0,\n        'wind': 1100.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 93.0,\n        'wind': 1142.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 76.0,\n        'wind': 1196.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 61.0,\n        'wind': 1260.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 42.0,\n        'wind': 1345.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 18.0,\n        'wind': 1462.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.0,\n        'wind': 1558.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1641.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1731.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1833.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1913.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1977.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2033.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2077.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2116.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2150.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2174.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2186.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2198.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2208.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2211.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2208.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2204.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2198.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2188.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2170.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2156.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2144.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2134.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2130.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2116.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2095.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2068.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2031.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1999.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1971.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1933.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1881.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1851.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1837.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1828.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1977.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1960.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1931.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1869.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1756.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1682.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1631.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1579.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1527.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1488.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1458.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1436.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1422.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1416.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1413.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1429.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1475.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1492.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1493.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1486.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1464.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1449.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1439.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1424.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1406.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1392.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1379.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1372.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1374.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1364.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1345.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 13.0,\n        'wind': 1322.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 32.0,\n        'wind': 1294.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 48.0,\n        'wind': 1263.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 63.0,\n        'wind': 1233.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 81.0,\n        'wind': 1189.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 103.0,\n        'wind': 1121.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 121.0,\n        'wind': 1083.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 136.0,\n        'wind': 1065.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 151.0,\n        'wind': 1055.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 1059.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 179.0,\n        'wind': 1066.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 188.0,\n        'wind': 1075.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 196.0,\n        'wind': 1103.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 203.0,\n        'wind': 1161.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 208.0,\n        'wind': 1189.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 209.0,\n        'wind': 1198.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 208.0,\n        'wind': 1207.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 205.0,\n        'wind': 1218.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 200.0,\n        'wind': 1206.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 193.0,\n        'wind': 1179.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 184.0,\n        'wind': 1134.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 171.0,\n        'wind': 1067.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 157.0,\n        'wind': 1003.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 143.0,\n        'wind': 942.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 127.0,\n        'wind': 857.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 107.0,\n        'wind': 733.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 89.0,\n        'wind': 655.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 72.0,\n        'wind': 606.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 51.0,\n        'wind': 572.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 23.0,\n        'wind': 562.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.0,\n        'wind': 549.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.0,\n        'wind': 537.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 540.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 561.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 573.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 579.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 589.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 602.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 613.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 621.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 631.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 643.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 650.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 651.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 650.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 643.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 637.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 630.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 621.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 610.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 598.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 586.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 571.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 552.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 538.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 526.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 518.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 514.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 506.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 497.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 486.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 470.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 461.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 457.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 454.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ENTSOE.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption\n  list([\n    dict({\n      'consumption': np.float64(3031.0),\n      'datetime': datetime.datetime(2023, 12, 28, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(3152.0),\n      'datetime': datetime.datetime(2023, 12, 28, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(3069.0),\n      'datetime': datetime.datetime(2023, 12, 28, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2918.0),\n      'datetime': datetime.datetime(2023, 12, 28, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2818.0),\n      'datetime': datetime.datetime(2023, 12, 28, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2756.0),\n      'datetime': datetime.datetime(2023, 12, 28, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2685.0),\n      'datetime': datetime.datetime(2023, 12, 28, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2693.0),\n      'datetime': datetime.datetime(2023, 12, 28, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2693.0),\n      'datetime': datetime.datetime(2023, 12, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2617.0),\n      'datetime': datetime.datetime(2023, 12, 29, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2522.0),\n      'datetime': datetime.datetime(2023, 12, 29, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2554.0),\n      'datetime': datetime.datetime(2023, 12, 29, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2493.0),\n      'datetime': datetime.datetime(2023, 12, 29, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2501.0),\n      'datetime': datetime.datetime(2023, 12, 29, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2576.0),\n      'datetime': datetime.datetime(2023, 12, 29, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2769.0),\n      'datetime': datetime.datetime(2023, 12, 29, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2960.0),\n      'datetime': datetime.datetime(2023, 12, 29, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2998.0),\n      'datetime': datetime.datetime(2023, 12, 29, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(3042.0),\n      'datetime': datetime.datetime(2023, 12, 29, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(3115.0),\n      'datetime': datetime.datetime(2023, 12, 29, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(3087.0),\n      'datetime': datetime.datetime(2023, 12, 29, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(3085.0),\n      'datetime': datetime.datetime(2023, 12, 29, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(3018.0),\n      'datetime': datetime.datetime(2023, 12, 29, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2913.0),\n      'datetime': datetime.datetime(2023, 12, 29, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2990.0),\n      'datetime': datetime.datetime(2023, 12, 29, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(3117.0),\n      'datetime': datetime.datetime(2023, 12, 29, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2938.0),\n      'datetime': datetime.datetime(2023, 12, 29, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2817.0),\n      'datetime': datetime.datetime(2023, 12, 29, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2662.0),\n      'datetime': datetime.datetime(2023, 12, 29, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2575.0),\n      'datetime': datetime.datetime(2023, 12, 29, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2467.0),\n      'datetime': datetime.datetime(2023, 12, 29, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2399.0),\n      'datetime': datetime.datetime(2023, 12, 29, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2300.0),\n      'datetime': datetime.datetime(2023, 12, 29, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2379.0),\n      'datetime': datetime.datetime(2023, 12, 30, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2339.0),\n      'datetime': datetime.datetime(2023, 12, 30, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2290.0),\n      'datetime': datetime.datetime(2023, 12, 30, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2346.0),\n      'datetime': datetime.datetime(2023, 12, 30, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2390.0),\n      'datetime': datetime.datetime(2023, 12, 30, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2399.0),\n      'datetime': datetime.datetime(2023, 12, 30, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2491.0),\n      'datetime': datetime.datetime(2023, 12, 30, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2644.0),\n      'datetime': datetime.datetime(2023, 12, 30, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2731.0),\n      'datetime': datetime.datetime(2023, 12, 30, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2753.0),\n      'datetime': datetime.datetime(2023, 12, 30, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2785.0),\n      'datetime': datetime.datetime(2023, 12, 30, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2772.0),\n      'datetime': datetime.datetime(2023, 12, 30, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2759.0),\n      'datetime': datetime.datetime(2023, 12, 30, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n    dict({\n      'consumption': np.float64(2723.0),\n      'datetime': datetime.datetime(2023, 12, 30, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'DK-DK1',\n    }),\n  ])\n# ---\n# name: test_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': np.float64(1554.0),\n      'datetime': datetime.datetime(2023, 12, 27, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1530.0),\n      'datetime': datetime.datetime(2023, 12, 28, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1485.0),\n      'datetime': datetime.datetime(2023, 12, 28, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1464.0),\n      'datetime': datetime.datetime(2023, 12, 28, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1411.0),\n      'datetime': datetime.datetime(2023, 12, 28, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1418.0),\n      'datetime': datetime.datetime(2023, 12, 28, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1476.0),\n      'datetime': datetime.datetime(2023, 12, 28, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1574.0),\n      'datetime': datetime.datetime(2023, 12, 28, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1700.0),\n      'datetime': datetime.datetime(2023, 12, 28, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1755.0),\n      'datetime': datetime.datetime(2023, 12, 28, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1836.0),\n      'datetime': datetime.datetime(2023, 12, 28, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1872.0),\n      'datetime': datetime.datetime(2023, 12, 28, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1847.0),\n      'datetime': datetime.datetime(2023, 12, 28, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1845.0),\n      'datetime': datetime.datetime(2023, 12, 28, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1841.0),\n      'datetime': datetime.datetime(2023, 12, 28, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1847.0),\n      'datetime': datetime.datetime(2023, 12, 28, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1901.0),\n      'datetime': datetime.datetime(2023, 12, 28, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1962.0),\n      'datetime': datetime.datetime(2023, 12, 28, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1924.0),\n      'datetime': datetime.datetime(2023, 12, 28, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1835.0),\n      'datetime': datetime.datetime(2023, 12, 28, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1763.0),\n      'datetime': datetime.datetime(2023, 12, 28, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1680.0),\n      'datetime': datetime.datetime(2023, 12, 28, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1601.0),\n      'datetime': datetime.datetime(2023, 12, 28, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1552.0),\n      'datetime': datetime.datetime(2023, 12, 28, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1454.0),\n      'datetime': datetime.datetime(2023, 12, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1418.0),\n      'datetime': datetime.datetime(2023, 12, 29, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1391.0),\n      'datetime': datetime.datetime(2023, 12, 29, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1382.0),\n      'datetime': datetime.datetime(2023, 12, 29, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1363.0),\n      'datetime': datetime.datetime(2023, 12, 29, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1348.0),\n      'datetime': datetime.datetime(2023, 12, 29, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1447.0),\n      'datetime': datetime.datetime(2023, 12, 29, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1587.0),\n      'datetime': datetime.datetime(2023, 12, 29, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1704.0),\n      'datetime': datetime.datetime(2023, 12, 29, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1764.0),\n      'datetime': datetime.datetime(2023, 12, 29, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1810.0),\n      'datetime': datetime.datetime(2023, 12, 29, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1806.0),\n      'datetime': datetime.datetime(2023, 12, 29, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1809.0),\n      'datetime': datetime.datetime(2023, 12, 29, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1814.0),\n      'datetime': datetime.datetime(2023, 12, 29, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1801.0),\n      'datetime': datetime.datetime(2023, 12, 29, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1821.0),\n      'datetime': datetime.datetime(2023, 12, 29, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1883.0),\n      'datetime': datetime.datetime(2023, 12, 29, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1932.0),\n      'datetime': datetime.datetime(2023, 12, 29, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1903.0),\n      'datetime': datetime.datetime(2023, 12, 29, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1828.0),\n      'datetime': datetime.datetime(2023, 12, 29, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1739.0),\n      'datetime': datetime.datetime(2023, 12, 29, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1655.0),\n      'datetime': datetime.datetime(2023, 12, 29, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1536.0),\n      'datetime': datetime.datetime(2023, 12, 29, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1435.0),\n      'datetime': datetime.datetime(2023, 12, 29, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1420.0),\n      'datetime': datetime.datetime(2023, 12, 29, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1385.0),\n      'datetime': datetime.datetime(2023, 12, 30, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1384.0),\n      'datetime': datetime.datetime(2023, 12, 30, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1369.0),\n      'datetime': datetime.datetime(2023, 12, 30, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1349.0),\n      'datetime': datetime.datetime(2023, 12, 30, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1343.0),\n      'datetime': datetime.datetime(2023, 12, 30, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1373.0),\n      'datetime': datetime.datetime(2023, 12, 30, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1444.0),\n      'datetime': datetime.datetime(2023, 12, 30, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1543.0),\n      'datetime': datetime.datetime(2023, 12, 30, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1641.0),\n      'datetime': datetime.datetime(2023, 12, 30, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1718.0),\n      'datetime': datetime.datetime(2023, 12, 30, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1738.0),\n      'datetime': datetime.datetime(2023, 12, 30, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1733.0),\n      'datetime': datetime.datetime(2023, 12, 30, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1713.0),\n      'datetime': datetime.datetime(2023, 12, 30, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1710.0),\n      'datetime': datetime.datetime(2023, 12, 30, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1743.0),\n      'datetime': datetime.datetime(2023, 12, 30, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1865.0),\n      'datetime': datetime.datetime(2023, 12, 30, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(2034.0),\n      'datetime': datetime.datetime(2023, 12, 30, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(2007.0),\n      'datetime': datetime.datetime(2023, 12, 30, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1866.0),\n      'datetime': datetime.datetime(2023, 12, 30, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1733.0),\n      'datetime': datetime.datetime(2023, 12, 30, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1624.0),\n      'datetime': datetime.datetime(2023, 12, 30, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1534.0),\n      'datetime': datetime.datetime(2023, 12, 30, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1452.0),\n      'datetime': datetime.datetime(2023, 12, 30, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1372.0),\n      'datetime': datetime.datetime(2023, 12, 30, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1305.0),\n      'datetime': datetime.datetime(2023, 12, 31, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1259.0),\n      'datetime': datetime.datetime(2023, 12, 31, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1235.0),\n      'datetime': datetime.datetime(2023, 12, 31, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1230.0),\n      'datetime': datetime.datetime(2023, 12, 31, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1266.0),\n      'datetime': datetime.datetime(2023, 12, 31, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1330.0),\n      'datetime': datetime.datetime(2023, 12, 31, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1414.0),\n      'datetime': datetime.datetime(2023, 12, 31, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1510.0),\n      'datetime': datetime.datetime(2023, 12, 31, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1609.0),\n      'datetime': datetime.datetime(2023, 12, 31, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1688.0),\n      'datetime': datetime.datetime(2023, 12, 31, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1730.0),\n      'datetime': datetime.datetime(2023, 12, 31, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1751.0),\n      'datetime': datetime.datetime(2023, 12, 31, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1761.0),\n      'datetime': datetime.datetime(2023, 12, 31, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1748.0),\n      'datetime': datetime.datetime(2023, 12, 31, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1773.0),\n      'datetime': datetime.datetime(2023, 12, 31, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1861.0),\n      'datetime': datetime.datetime(2023, 12, 31, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1935.0),\n      'datetime': datetime.datetime(2023, 12, 31, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1894.0),\n      'datetime': datetime.datetime(2023, 12, 31, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1752.0),\n      'datetime': datetime.datetime(2023, 12, 31, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1619.0),\n      'datetime': datetime.datetime(2023, 12, 31, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1540.0),\n      'datetime': datetime.datetime(2023, 12, 31, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1481.0),\n      'datetime': datetime.datetime(2023, 12, 31, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n    dict({\n      'consumption': np.float64(1432.0),\n      'datetime': datetime.datetime(2023, 12, 31, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'DK-DK2',\n    }),\n  ])\n# ---\n# name: test_fetch_exchange\n  list([\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1362.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(102.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-38.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-710.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-732.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1382.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1400.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1402.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1406.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1366.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1326.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-96.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(2.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-2.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK1->GB',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_fetch_exchange_capacity_forecasts_day_ahead\n  list([\n    dict({\n      'capacityExport': 1400.0,\n      'capacityImport': 3006.0,\n      'datetime': datetime.datetime(2026, 3, 19, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1400.0,\n      'capacityImport': 3006.0,\n      'datetime': datetime.datetime(2026, 3, 19, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1400.0,\n      'capacityImport': 3006.0,\n      'datetime': datetime.datetime(2026, 3, 19, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1400.0,\n      'capacityImport': 3006.0,\n      'datetime': datetime.datetime(2026, 3, 19, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1400.0,\n      'capacityImport': 2914.0,\n      'datetime': datetime.datetime(2026, 3, 19, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1350.0,\n      'capacityImport': 2914.0,\n      'datetime': datetime.datetime(2026, 3, 19, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1350.0,\n      'capacityImport': 2914.0,\n      'datetime': datetime.datetime(2026, 3, 19, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1350.0,\n      'capacityImport': 2914.0,\n      'datetime': datetime.datetime(2026, 3, 19, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1350.0,\n      'capacityImport': 2960.0,\n      'datetime': datetime.datetime(2026, 3, 19, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1350.0,\n      'capacityImport': 2960.0,\n      'datetime': datetime.datetime(2026, 3, 19, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1350.0,\n      'capacityImport': 2960.0,\n      'datetime': datetime.datetime(2026, 3, 19, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1500.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 19, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1500.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 19, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1500.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 19, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1500.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 19, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1500.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 19, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1500.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 19, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1500.0,\n      'capacityImport': 3422.0,\n      'datetime': datetime.datetime(2026, 3, 19, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1500.0,\n      'capacityImport': 3422.0,\n      'datetime': datetime.datetime(2026, 3, 20, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3422.0,\n      'datetime': datetime.datetime(2026, 3, 20, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3422.0,\n      'datetime': datetime.datetime(2026, 3, 20, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3515.0,\n      'datetime': datetime.datetime(2026, 3, 20, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3515.0,\n      'datetime': datetime.datetime(2026, 3, 20, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3469.0,\n      'datetime': datetime.datetime(2026, 3, 20, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3469.0,\n      'datetime': datetime.datetime(2026, 3, 20, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3469.0,\n      'datetime': datetime.datetime(2026, 3, 20, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3469.0,\n      'datetime': datetime.datetime(2026, 3, 20, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3469.0,\n      'datetime': datetime.datetime(2026, 3, 20, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3099.0,\n      'datetime': datetime.datetime(2026, 3, 20, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3099.0,\n      'datetime': datetime.datetime(2026, 3, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3099.0,\n      'datetime': datetime.datetime(2026, 3, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3099.0,\n      'datetime': datetime.datetime(2026, 3, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3099.0,\n      'datetime': datetime.datetime(2026, 3, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3099.0,\n      'datetime': datetime.datetime(2026, 3, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3099.0,\n      'datetime': datetime.datetime(2026, 3, 20, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 20, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 20, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 20, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 20, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1450.0,\n      'capacityImport': 3607.0,\n      'datetime': datetime.datetime(2026, 3, 20, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n  ])\n# ---\n# name: test_fetch_exchange_capacity_forecasts_month_ahead\n  list([\n    dict({\n      'capacityExport': 2150.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2150.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 17, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 18, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 19, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 22, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 23, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 26, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 27, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 29, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2400.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 30, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 3, 31, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 1, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 2, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 3, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 4, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 5, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 6, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 8, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 9, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 11, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 12, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 17, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 18, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 19, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 22, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 23, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 26, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 27, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 29, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 4, 30, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 1, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 2, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 3, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 4, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 5, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 6, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 8, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 9, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 11, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 12, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 0.0,\n      'capacityImport': 3000.0,\n      'datetime': datetime.datetime(2026, 5, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'ES->FR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n  ])\n# ---\n# name: test_fetch_exchange_capacity_forecasts_week_ahead\n  list([\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 17, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 18, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 19, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 22, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 23, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 26, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 27, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 2, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 1, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 2, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 3, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 4, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 5, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 6, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 8, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 9, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 11, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 12, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 17, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 18, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 19, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 22, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 23, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 26, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 450.0,\n      'capacityImport': 600.0,\n      'datetime': datetime.datetime(2026, 3, 27, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DK-DK1->DK-DK2',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n  ])\n# ---\n# name: test_fetch_exchange_forecast\n  list([\n    dict({\n      'datetime': datetime.datetime(2023, 12, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1264.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(990.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(862.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1022.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1078.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1160.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1259.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(731.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(719.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(576.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(542.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(716.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1099.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1212.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1309.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1218.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1065.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(810.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(433.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-122.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-285.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(85.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(640.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(986.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1301.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1228.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1186.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1196.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1334.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1255.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(880.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(707.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(530.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1039.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(831.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1269.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1089.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1164.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1118.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(582.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(341.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(132.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(76.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(121.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(130.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-51.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(12.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(138.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 22, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(631.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1191.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1148.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1340.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1477.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1578.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1625.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1485.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1252.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(432.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1141.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(1102.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(130.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-470.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-462.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-362.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-213.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1248.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1239.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-560.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-995.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-380.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-2.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-277.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 23, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 24, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'DK-DK2->SE-SE4',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n  ])\n# ---\n# name: test_fetch_exchange_forecast_15_min\n  list([\n    dict({\n      'datetime': datetime.datetime(2024, 3, 23, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-355.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 23, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-299.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 23, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-275.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 23, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-261.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-857.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-805.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-789.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-744.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-244.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-215.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-184.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-187.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-12.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-21.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-20.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-30.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(11.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(4.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-15.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-29.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(184.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(184.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(157.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(126.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-53.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-95.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-96.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-132.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-169.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-222.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-213.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-214.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-636.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-614.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-649.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-646.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-810.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-783.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-762.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-718.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-660.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-645.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-580.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-600.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-703.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-710.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-700.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-685.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-976.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-908.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-952.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-967.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1747.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1747.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1748.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1748.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1135.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1136.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1136.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1134.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-770.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-812.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-759.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-792.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-699.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-736.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-631.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-622.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1066.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-967.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-852.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-654.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1032.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1120.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-951.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1035.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1242.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1269.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1265.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1289.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1604.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1624.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1478.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1457.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1007.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1011.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1000.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-942.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-910.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-943.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-997.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-925.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-777.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-726.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-716.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-680.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-410.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-394.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-322.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-271.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-801.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-756.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-680.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-598.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-892.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-892.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-892.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-892.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-87.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-73.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-71.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-76.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-259.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-339.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-317.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-355.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-986.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1077.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1119.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1289.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1770.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1868.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1979.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-2210.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1250.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1267.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1303.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1320.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1487.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1567.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1714.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1700.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1793.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-2008.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1926.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1905.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1351.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1464.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1361.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1313.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1745.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1665.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1733.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1757.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1782.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1796.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1822.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1817.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1664.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1664.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1513.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1528.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1798.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1795.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1577.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1557.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1388.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1388.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1388.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1405.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1570.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1570.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1570.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1559.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1204.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1204.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1236.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1292.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-652.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-734.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-770.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-822.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1438.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1438.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1438.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1438.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1231.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1244.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1175.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1188.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1649.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1548.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1527.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1492.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-941.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-883.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-863.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-784.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-662.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-646.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-623.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-571.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-899.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-899.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-899.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-899.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-799.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-799.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-799.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-799.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-743.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-743.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-743.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-743.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-883.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-883.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-883.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-883.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-822.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-822.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-822.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-822.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-997.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-997.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-997.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-997.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1189.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1189.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1189.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1189.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-915.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-915.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-915.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-915.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1899.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1899.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1899.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1899.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1227.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1227.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1227.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1227.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1368.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1368.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1368.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1368.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1762.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1762.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1762.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1762.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1756.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1756.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1756.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1756.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1755.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1755.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1755.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1755.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1172.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1172.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1172.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1172.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1378.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1378.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1378.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1378.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1341.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1341.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1341.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1341.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1124.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1124.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1124.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1124.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1275.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1275.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1275.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1275.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1387.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1387.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1387.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1387.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1249.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1249.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1249.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1249.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1477.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1477.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1477.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-1477.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-950.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-950.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-950.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-950.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-815.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-815.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-815.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-815.0),\n      'sortedZoneKeys': 'BE->NL',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n  ])\n# ---\n# name: test_fetch_exchange_forecast_with_aggregated_exchanges\n  list([\n    dict({\n      'datetime': datetime.datetime(2023, 12, 26, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-141.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-135.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-122.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-115.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-113.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-117.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-127.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-139.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-141.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-122.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-98.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-81.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-73.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-73.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-86.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-110.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-137.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-137.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-129.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-122.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-119.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-123.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-134.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-136.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-116.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-101.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-95.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-93.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-106.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-125.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-142.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(4.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(4.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(4.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(4.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-86.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-100.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-146.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-56.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-57.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n  ])\n# ---\n# name: test_fetch_exchange_forecast_with_longer_day_ahead_than_total\n  list([\n    dict({\n      'datetime': datetime.datetime(2024, 3, 23, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-258.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-190.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-176.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-222.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-234.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-154.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-44.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-86.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(46.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(70.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(90.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(47.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(31.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-43.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-60.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-221.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-334.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-355.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-333.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-333.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-311.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-266.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-274.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-325.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-323.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-315.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-207.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-92.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-19.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-59.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-106.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-212.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-321.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-353.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-258.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-318.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-290.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-355.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-285.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-295.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-219.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-164.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-156.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-30.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(45.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-14.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-14.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-14.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(73.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(103.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-16.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-65.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-85.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-185.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-200.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-276.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-309.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 3, 26, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(-358.0),\n      'sortedZoneKeys': 'EE->FI',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n  ])\n# ---\n# name: test_fetch_exchange_with_aggregated_exchanges\n  list([\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(37.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(38.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(35.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(41.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(36.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(17.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(15.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(17.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(20.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(21.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(21.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(21.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(22.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(33.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(70.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(81.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(85.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(85.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(83.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(65.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(82.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(45.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(19.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(19.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(19.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(21.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(22.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(27.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(24.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(20.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(60.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(70.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(73.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(51.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(23.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(14.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(30.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(70.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(83.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(75.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(88.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(86.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(87.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(83.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(37.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(21.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': np.float64(22.0),\n      'sortedZoneKeys': 'FR-COR->IT-SAR',\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_fetch_generation_forecast\n  list([\n    dict({\n      'datetime': datetime.datetime(2023, 12, 27, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9958.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10183.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10414.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10583.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10709.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10872.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10979.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(11006.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10901.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10798.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10634.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10612.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10607.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10554.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10426.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10453.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10429.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10330.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10228.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10099.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9972.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9828.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9737.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9711.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9693.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9765.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9900.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10031.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10097.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10147.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10259.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10273.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10242.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10169.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10058.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9996.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10004.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10014.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9961.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10115.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10130.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(10090.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9999.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9887.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9764.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9627.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9522.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9449.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 29, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9467.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9463.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9454.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9428.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9403.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9409.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9345.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9286.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9198.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9217.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9232.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9236.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9257.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9251.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9257.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9476.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9694.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9780.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9837.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9795.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9652.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9669.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9620.0),\n      'zoneKey': 'SE-SE3',\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 12, 30, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': np.float64(9598.0),\n      'zoneKey': 'SE-SE3',\n    }),\n  ])\n# ---\n# name: test_fetch_prices_day_ahead\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 51.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 47.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 45.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 32.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 32.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 50.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 77.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 73.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 59.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 40.14,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 21.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 27.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 52.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 85.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 101.13,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 133.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 90.04,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 88.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 88.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 80.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 76.43,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 78.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 80.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 97.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 120.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 93.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 60.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 31.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.47,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 21.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 22.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 29.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 54.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 117.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 199.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 172.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 119.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 101.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 105.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 104.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 102.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 102.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 106.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 105.19,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 105.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 104.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 102.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 100.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 100.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 97.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 97.51,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 97.51,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 97.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 98.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 100.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 102.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 105.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 101.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 101.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 101.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 102.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 101.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 102.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 104.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 106.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 110.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 114.15,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 122.58,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 140.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 130.56,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 115.17,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 106.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 125.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 92.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 60.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 100.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 65.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 58.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 45.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 59.07,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 44.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 35.87,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 24.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 26.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 22.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 23.92,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 22.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 15.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 15.45,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.67,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 15.31,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 16.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 17.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 18.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 16.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 24.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 26.56,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 43.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 58.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 50.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 60.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 77.67,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 59.07,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 75.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 101.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 110.69,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 112.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 148.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 134.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 194.14,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 217.45,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 230.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 230.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 150.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 130.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 123.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 113.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 114.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 109.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 106.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 104.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 104.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 102.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 101.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 103.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 103.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 102.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 100.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 99.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 98.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 95.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 95.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 95.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 96.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 97.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 98.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 98.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 99.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 100.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 103.29,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 103.29,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 103.71,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 107.38,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 103.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 103.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 105.19,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 110.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 110.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 119.87,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 125.85,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 129.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 153.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 140.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 121.06,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 110.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 119.87,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 103.36,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 92.29,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 58.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 60.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 55.56,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 36.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 44.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 37.22,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 33.32,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 22.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 20.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 22.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 17.15,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 20.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 19.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 16.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 15.06,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 15.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 16.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 16.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 15.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 16.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 18.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 20.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 29.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 30.09,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 46.89,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 40.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 55.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 61.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 47.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 67.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 101.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 104.48,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 90.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 103.36,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 110.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 123.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 170.51,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 201.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 220.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 225.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 180.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 173.66,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 147.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 125.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 128.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 121.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 115.44,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 109.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 106.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 103.84,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 103.27,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n  ])\n# ---\n# name: test_fetch_prices_integrated_zone\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 6, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 106.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 6, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.02,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 90.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 83.71,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.86,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 85.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.48,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 77.51,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 76.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 63.48,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 55.13,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 60.48,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 47.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 27.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.09,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 57.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 77.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 101.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 107.43,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 109.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 106.23,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 97.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 98.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 88.58,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 87.23,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 90.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 93.96,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 99.74,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 110.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 100.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 92.04,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 83.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 83.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 83.71,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 77.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 78.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 97.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 106.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 112.82,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 122.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 121.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 114.71,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2023, 5, 8, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 104.04,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AX',\n    }),\n  ])\n# ---\n# name: test_fetch_prices_intraday\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 75.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 77.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 66.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 63.85,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 51.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 56.53,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 47.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 42.39,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 66.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 64.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 49.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 61.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 47.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 59.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 44.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 28, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 44.95,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 66.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 64.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 54.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 53.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 45.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 45.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 43.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 49.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 49.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 59.02,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 46.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 46.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 34.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 38.09,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 34.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 36.69,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 43.48,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 43.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 41.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 40.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 49.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 37.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 44.62,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 60.12,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 34.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 46.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 46.85,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 32.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 49.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 43.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 66.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 62.95,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 43.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 45.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 50.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 60.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 66.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 66.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 80.65,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 81.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 70.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 60.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 76.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 82.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 83.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 84.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 85.44,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 85.45,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 83.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 84.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 78.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 81.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 76.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 64.96,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 89.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 89.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 83.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 79.04,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 69.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 69.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 40.09,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 29.38,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 67.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 70.86,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 59.13,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 48.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 39.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 23.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 28.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 18.48,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 40.14,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 29.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 32.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 22.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 25.14,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 19.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 22.88,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 16.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 29.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 27.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 23.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 22.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 24.92,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 24.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 35.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 23.07,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 24.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 35.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 23.29,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 22.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 23.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 23.06,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 23.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 24.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 22.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 23.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 26.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 20.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 23.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 25.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 20.95,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 19.83,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 16.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 17.02,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 21.44,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 18.09,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 13.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 13.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 22.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 22.93,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 22.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 22.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 18.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 22.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 22.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 18.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 24.32,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 23.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 26.87,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 22.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 22.88,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 22.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 19.93,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 34.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 30.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 34.12,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 37.18,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 42.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 41.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 22.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 20.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 31.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 30.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 28.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 52.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 46.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 40.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 72.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 72.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 70.87,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 58.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 49.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 36.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 69.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 62.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 62.13,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 89.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 90.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 87.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 96.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 98.87,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 100.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 80.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 72.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 61.56,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 91.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 89.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 89.13,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 101.13,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 106.13,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 101.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 111.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 122.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 133.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 128.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 130.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 135.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 126.36,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 132.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 135.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 123.36,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 125.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 128.14,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 120.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 124.37,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 108.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 104.37,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 108.14,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 109.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 100.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 98.37,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 104.12,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 104.88,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 95.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 97.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 95.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 91.29,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 101.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 105.72,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 89.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 96.27,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 95.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 88.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 97.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 96.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 86.54,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 90.04,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 89.13,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 89.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 96.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 98.02,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 88.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 92.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 94.42,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 87.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 90.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 91.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 80.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 83.37,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 86.82,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.31,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 94.96,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 92.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 94.96,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 90.36,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 92.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 87.53,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 89.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 91.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 97.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 89.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 94.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 88.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 93.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 88.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 29, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 91.39,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 81.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 90.45,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 80.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 89.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 79.85,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 88.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 79.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 87.23,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 76.43,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 76.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 83.38,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 76.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 84.07,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 76.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 83.86,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 77.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 85.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 77.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 85.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 77.85,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 84.86,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 78.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 86.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 77.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 86.45,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 79.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 87.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 79.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 85.85,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 81.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 87.58,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 85.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 79.54,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 89.66,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 85.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 92.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 88.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 96.96,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 89.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 85.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 100.47,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 97.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 102.86,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 113.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 106.74,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 122.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 120.03,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 135.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 120.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 129.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 112.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 115.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 105.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 100.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 129.96,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 138.88,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 100.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 115.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 84.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 84.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 35.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 36.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 88.31,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 92.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 73.83,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 84.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 60.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 60.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 48.61,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 42.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 80.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 56.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 57.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 42.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 55.61,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 31.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 48.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 37.37,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 48.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 63.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 31.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 45.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 61.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 33.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 45.23,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 59.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 32.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 44.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 65.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 29.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 41.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 66.73,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 37.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 45.17,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 65.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 37.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 37.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 71.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 36.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 36.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 71.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 41.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 42.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 65.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 42.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 46.93,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 65.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 49.04,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 48.84,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 65.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 43.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 48.38,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 71.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 57.03,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 48.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 63.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 68.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 49.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 65.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 74.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 66.08,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 74.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 79.07,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 79.07,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 83.37,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 38.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 48.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 61.43,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 50.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 59.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 75.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 80.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 83.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 85.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 85.37,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 90.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 87.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 44.89,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 40.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 54.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 54.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 54.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 84.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 85.69,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 69.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 92.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 98.88,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 69.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 33.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 36.44,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 22.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 65.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 62.93,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 51.48,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 90.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 95.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 66.23,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 113.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 119.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 113.93,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 88.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 89.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 80.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 107.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 109.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 91.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 131.92,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 137.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 133.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 157.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 157.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 153.09,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 195.27,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 210.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 201.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 199.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 220.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 221.94,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 199.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 239.67,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 249.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 199.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 237.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 242.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 173.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 184.42,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 189.42,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 172.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 174.62,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 174.82,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 171.61,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 167.74,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 166.02,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 164.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 154.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 127.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 139.89,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 141.62,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 131.89,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 121.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 132.31,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 118.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 117.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 119.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 109.95,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 113.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 110.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 104.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 111.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 122.65,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 109.95,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 101.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 111.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.18,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 98.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 98.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 97.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 96.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 91.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 87.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 106.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 102.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 109.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 102.39,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 107.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 102.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 105.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 106.74,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 111.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 110.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 105.19,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 110.19,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 105.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 9, 30, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 109.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 103.71,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 101.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 94.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 99.38,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 92.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 99.38,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 94.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 91.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 96.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 91.51,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 96.66,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 92.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 96.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 93.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 97.66,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 92.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 100.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 96.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 102.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 98.27,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 104.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 98.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 99.64,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.38,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 100.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 80.62,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 101.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 95.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 102.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 92.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 101.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 102.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 102.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 104.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 109.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 106.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 115.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 108.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 134.54,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 112.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 150.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 122.15,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 154.74,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 124.58,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 155.96,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 142.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 160.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 132.56,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 150.56,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 118.17,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 135.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 108.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 129.23,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 120.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 107.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 95.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 85.95,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 92.22,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 86.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 61.02,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 31.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 87.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 61.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 58.82,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 35.89,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 53.43,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 31.42,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 35.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 20.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 56.92,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.93,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 35.02,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 24.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 25.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 20.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 19.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 0.65,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.65,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -9.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 14.69,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 0.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 0.65,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 18.92,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 3.51,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 16.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 7.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 12.2,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 13.73,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 9.09,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': -0.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': -7.83,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': -0.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': -2.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': -10.62,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 5.32,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': -0.09,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 2.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 6.36,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 2.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 13.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 16.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 12.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 12.76,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.17,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.44,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 10.06,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 12.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 16.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 10.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 13.42,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 16.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 14.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 18.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 4.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 12.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 27.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 34.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 35.93,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 38.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 53.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 49.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 53.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 35.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 14.31,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 43.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 55.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 20.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 44.96,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 64.92,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 49.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 39.86,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 55.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 48.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 36.77,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 75.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 63.75,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 61.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 86.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 71.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 72.66,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 90.69,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 90.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 92.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 105.17,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 98.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 89.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 112.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 112.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 108.04,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 142.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 139.67,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 120.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 133.83,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 129.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 129.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 174.14,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 172.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 154.14,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 201.17,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 206.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 196.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 217.45,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 219.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 210.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 215.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 220.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 210.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 150.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 165.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 155.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 130.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 143.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 133.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 123.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 133.89,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 122.89,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 113.25,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 120.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 109.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 119.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 120.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 114.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 112.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 118.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 109.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 106.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 116.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 111.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 104.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 114.66,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 109.66,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 108.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 115.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 105.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 105.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 115.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 107.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 105.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 115.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 107.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 105.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 115.15,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 106.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 102.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 94.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 104.86,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 15, tzinfo=datetime.timezone.utc),\n      'price': 99.21,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 101.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 30, tzinfo=datetime.timezone.utc),\n      'price': 95.53,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 102.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 22, 45, tzinfo=datetime.timezone.utc),\n      'price': 93.63,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 100.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 92.58,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 98.19,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 15, tzinfo=datetime.timezone.utc),\n      'price': 91.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 96.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 30, tzinfo=datetime.timezone.utc),\n      'price': 91.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 96.47,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 1, 23, 45, tzinfo=datetime.timezone.utc),\n      'price': 91.05,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 93.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 77.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 92.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 15, tzinfo=datetime.timezone.utc),\n      'price': 78.34,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 93.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 30, tzinfo=datetime.timezone.utc),\n      'price': 78.54,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 92.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 0, 45, tzinfo=datetime.timezone.utc),\n      'price': 77.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 93.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 79.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 94.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 15, tzinfo=datetime.timezone.utc),\n      'price': 79.8,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 95.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 30, tzinfo=datetime.timezone.utc),\n      'price': 83.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 96.69,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 1, 45, tzinfo=datetime.timezone.utc),\n      'price': 85.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 96.98,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 85.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 98.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 15, tzinfo=datetime.timezone.utc),\n      'price': 88.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 98.23,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 30, tzinfo=datetime.timezone.utc),\n      'price': 91.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 100.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 2, 45, tzinfo=datetime.timezone.utc),\n      'price': 91.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 101.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 91.15,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 101.66,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 15, tzinfo=datetime.timezone.utc),\n      'price': 91.17,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 103.68,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 30, tzinfo=datetime.timezone.utc),\n      'price': 98.67,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 106.19,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 3, 45, tzinfo=datetime.timezone.utc),\n      'price': 98.37,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 101.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 96.26,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 101.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 15, tzinfo=datetime.timezone.utc),\n      'price': 101.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 102.29,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 30, tzinfo=datetime.timezone.utc),\n      'price': 112.19,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 107.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 4, 45, tzinfo=datetime.timezone.utc),\n      'price': 113.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 110.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 112.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 123.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 15, tzinfo=datetime.timezone.utc),\n      'price': 123.87,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 126.95,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 30, tzinfo=datetime.timezone.utc),\n      'price': 134.85,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 134.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 5, 45, tzinfo=datetime.timezone.utc),\n      'price': 138.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 153.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 153.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 138.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 15, tzinfo=datetime.timezone.utc),\n      'price': 140.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 123.44,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 30, tzinfo=datetime.timezone.utc),\n      'price': 121.06,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 110.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 6, 45, tzinfo=datetime.timezone.utc),\n      'price': 108.51,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 114.87,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 121.87,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 103.36,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 15, tzinfo=datetime.timezone.utc),\n      'price': 104.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 91.19,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 30, tzinfo=datetime.timezone.utc),\n      'price': 85.29,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 68.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 7, 45, tzinfo=datetime.timezone.utc),\n      'price': 75.24,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.49,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 79.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 58.82,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 15, tzinfo=datetime.timezone.utc),\n      'price': 63.67,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 53.83,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 30, tzinfo=datetime.timezone.utc),\n      'price': 43.33,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 36.17,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 8, 45, tzinfo=datetime.timezone.utc),\n      'price': 23.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 34.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 42.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 27.22,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 15, tzinfo=datetime.timezone.utc),\n      'price': 32.12,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 19.07,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 30, tzinfo=datetime.timezone.utc),\n      'price': 23.97,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 8.62,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 9, 45, tzinfo=datetime.timezone.utc),\n      'price': 13.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 27.19,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 20.67,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 15, tzinfo=datetime.timezone.utc),\n      'price': 19.69,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 22.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 30, tzinfo=datetime.timezone.utc),\n      'price': 22.48,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 17.15,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 10, 45, tzinfo=datetime.timezone.utc),\n      'price': 16.15,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 23.16,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 26.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 19.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 15, tzinfo=datetime.timezone.utc),\n      'price': 22.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 16.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 30, tzinfo=datetime.timezone.utc),\n      'price': 16.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 7.35,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 11, 45, tzinfo=datetime.timezone.utc),\n      'price': 15.04,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 15.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.46,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 15, tzinfo=datetime.timezone.utc),\n      'price': 16.45,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 21.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 30, tzinfo=datetime.timezone.utc),\n      'price': 22.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 22.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 12, 45, tzinfo=datetime.timezone.utc),\n      'price': 23.01,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 11.55,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 15, tzinfo=datetime.timezone.utc),\n      'price': 14.45,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 6.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 30, tzinfo=datetime.timezone.utc),\n      'price': 11.5,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 8.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 13, 45, tzinfo=datetime.timezone.utc),\n      'price': 16.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.7,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.69,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 17.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 15, tzinfo=datetime.timezone.utc),\n      'price': 20.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 14.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 30, tzinfo=datetime.timezone.utc),\n      'price': 25.03,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 45.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 14, 45, tzinfo=datetime.timezone.utc),\n      'price': 51.89,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 35.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 15, tzinfo=datetime.timezone.utc),\n      'price': 40.59,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 42.22,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 30, tzinfo=datetime.timezone.utc),\n      'price': 36.72,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 61.31,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 15, 45, tzinfo=datetime.timezone.utc),\n      'price': 66.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 37.22,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 31.47,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 52.4,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 15, tzinfo=datetime.timezone.utc),\n      'price': 43.6,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 87.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 30, tzinfo=datetime.timezone.utc),\n      'price': 90.11,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 94.69,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 16, 45, tzinfo=datetime.timezone.utc),\n      'price': 97.1,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 92.65,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 109.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 15, tzinfo=datetime.timezone.utc),\n      'price': 99.29,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 115.93,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 30, tzinfo=datetime.timezone.utc),\n      'price': 110.41,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 125.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 17, 45, tzinfo=datetime.timezone.utc),\n      'price': 123.9,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 162.78,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 155.51,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 199.28,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 15, tzinfo=datetime.timezone.utc),\n      'price': 201.52,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 217.56,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 30, tzinfo=datetime.timezone.utc),\n      'price': 220.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 223.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 18, 45, tzinfo=datetime.timezone.utc),\n      'price': 225.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 184.36,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 205.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 176.29,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 15, tzinfo=datetime.timezone.utc),\n      'price': 193.92,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 154.3,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 30, tzinfo=datetime.timezone.utc),\n      'price': 164.66,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 125.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 19, 45, tzinfo=datetime.timezone.utc),\n      'price': 135.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 140.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 143.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 130.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 15, tzinfo=datetime.timezone.utc),\n      'price': 136.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 132.81,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 30, tzinfo=datetime.timezone.utc),\n      'price': 130.44,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 121.79,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 20, 45, tzinfo=datetime.timezone.utc),\n      'price': 124.91,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 113.0,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 118.57,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 109.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 15, tzinfo=datetime.timezone.utc),\n      'price': 117.09,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 129.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 30, tzinfo=datetime.timezone.utc),\n      'price': 118.84,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 129.99,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2025, 10, 2, 21, 45, tzinfo=datetime.timezone.utc),\n      'price': 115.27,\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n  ])\n# ---\n# name: test_fetch_with_negative_values\n  list([\n    dict({\n      'correctedModes': list([\n        'gas',\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0,\n        'hydro': 1065.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n        'gas',\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0,\n        'hydro': 969.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1011.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 0.0,\n        'hydro': 1177.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1317.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 1547.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 1950.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 2009.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 2053.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 2011.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2042.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1932.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 0.0,\n        'hydro': 1879.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -62.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1629.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 9, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1520.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1491.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1467.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -60.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 1513.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 1552.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -61.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 1957.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -78.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2341.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -157.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2344.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -161.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2214.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -118.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2062.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -60.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 0.0,\n        'hydro': 2198.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -60.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 0.0,\n        'hydro': 2191.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -35.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 0.0,\n        'hydro': 2200.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 0.0,\n        'hydro': 2157.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2279.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2583.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2733.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2637.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2725.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2880.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -33.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2756.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -33.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0.0,\n        'hydro': 2632.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -33.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2603.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -34.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2546.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -70.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2390.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -70.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2393.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -71.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2394.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -71.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2449.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -71.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 2700.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -73.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 1.0,\n        'hydro': 3155.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -74.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 0.0,\n        'hydro': 3440.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -74.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 0.0,\n        'hydro': 3819.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -190.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n    dict({\n      'correctedModes': list([\n        'gas',\n      ]),\n      'datetime': datetime.datetime(2023, 5, 11, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 0,\n        'hydro': 3677.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -114.0,\n      }),\n      'zoneKey': 'NO-NO5',\n    }),\n  ])\n# ---\n# name: test_wind_and_solar_forecasts\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1860.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1866.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1876.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1897.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1802.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1811.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1825.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 7, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1860.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1791.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1800.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1815.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1849.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1795.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1803.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1816.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1841.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1711.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1722.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1742.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1781.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1813.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1825.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1845.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1884.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2008.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2019.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2039.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2081.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2230.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2239.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2253.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2291.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 10.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 30.0,\n        'wind': 2513.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 33.0,\n        'wind': 2516.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 40.0,\n        'wind': 2511.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 55.0,\n        'wind': 2540.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 94.0,\n        'wind': 2651.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 97.0,\n        'wind': 2619.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 101.0,\n        'wind': 2561.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 111.0,\n        'wind': 2452.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 148.0,\n        'wind': 1963.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 149.0,\n        'wind': 1941.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 150.0,\n        'wind': 1904.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 153.0,\n        'wind': 1826.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 1927.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 1907.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 1876.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 1799.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 172.0,\n        'wind': 1850.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 170.0,\n        'wind': 1844.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 1836.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 157.0,\n        'wind': 1808.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 127.0,\n        'wind': 1718.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 124.0,\n        'wind': 1729.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 117.0,\n        'wind': 1750.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 104.0,\n        'wind': 1789.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 65.0,\n        'wind': 1797.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 62.0,\n        'wind': 1812.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 57.0,\n        'wind': 1840.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 43.0,\n        'wind': 1895.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1946.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1961.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1986.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 2042.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2112.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2119.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2131.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2161.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2199.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2200.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2201.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2208.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2323.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2315.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2298.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2431.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2424.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2411.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2388.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2487.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2476.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2457.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2419.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2456.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2442.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2418.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2368.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2487.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2472.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2447.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2391.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2220.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2208.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2187.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2145.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2088.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2077.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2059.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 8, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 2020.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1966.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1957.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1941.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1906.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1762.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1755.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1742.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1722.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1574.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1566.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1552.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1522.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1372.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1368.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1361.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1345.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1272.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1272.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1271.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1271.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1351.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1349.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1345.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1342.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1368.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1361.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1348.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 13.0,\n        'wind': 1327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 45.0,\n        'wind': 1351.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 49.0,\n        'wind': 1341.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 57.0,\n        'wind': 1326.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 73.0,\n        'wind': 1285.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 124.0,\n        'wind': 1151.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 128.0,\n        'wind': 1153.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 133.0,\n        'wind': 1157.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 146.0,\n        'wind': 1161.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 181.0,\n        'wind': 1028.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 182.0,\n        'wind': 1024.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 184.0,\n        'wind': 1019.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 190.0,\n        'wind': 1007.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 209.0,\n        'wind': 834.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 208.0,\n        'wind': 826.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 206.0,\n        'wind': 813.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 202.0,\n        'wind': 785.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 195.0,\n        'wind': 646.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 192.0,\n        'wind': 642.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 187.0,\n        'wind': 635.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 178.0,\n        'wind': 619.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.0,\n        'wind': 529.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 150.0,\n        'wind': 529.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 142.0,\n        'wind': 530.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 127.0,\n        'wind': 528.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 88.0,\n        'wind': 442.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 83.0,\n        'wind': 447.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 76.0,\n        'wind': 456.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 57.0,\n        'wind': 475.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 486.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 491.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 499.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 514.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 552.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 557.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 565.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 580.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 619.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 624.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 631.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 651.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 759.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 757.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 753.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 746.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 730.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 725.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 717.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 697.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 658.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 637.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 627.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 621.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 627.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 625.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 620.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 615.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 611.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 605.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 599.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 592.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 584.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 576.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 568.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 558.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 548.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 539.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 530.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 9, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 521.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 511.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 503.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 497.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 489.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 478.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 474.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 475.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 479.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 485.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 496.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 511.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 530.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 553.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 579.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 607.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 640.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 677.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 715.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 752.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 796.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 848.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 891.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 927.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 965.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1008.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1036.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1053.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 13.0,\n        'wind': 1066.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 34.0,\n        'wind': 1075.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 49.0,\n        'wind': 1072.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 62.0,\n        'wind': 1063.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 78.0,\n        'wind': 1032.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 95.0,\n        'wind': 965.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 109.0,\n        'wind': 934.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 121.0,\n        'wind': 922.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 133.0,\n        'wind': 924.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 144.0,\n        'wind': 953.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 153.0,\n        'wind': 960.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 160.0,\n        'wind': 953.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 164.0,\n        'wind': 952.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 959.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 943.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 166.0,\n        'wind': 914.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 165.0,\n        'wind': 866.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 164.0,\n        'wind': 791.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 160.0,\n        'wind': 734.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 154.0,\n        'wind': 687.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 147.0,\n        'wind': 630.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 137.0,\n        'wind': 557.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 127.0,\n        'wind': 512.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 116.0,\n        'wind': 487.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 103.0,\n        'wind': 468.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 88.0,\n        'wind': 457.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 74.0,\n        'wind': 464.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 61.0,\n        'wind': 485.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 44.0,\n        'wind': 524.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 20.0,\n        'wind': 589.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6.0,\n        'wind': 649.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.0,\n        'wind': 707.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 784.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 886.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 963.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1024.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1084.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1137.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1184.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1225.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1260.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1288.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1310.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1328.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1337.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1334.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1336.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1339.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1337.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1325.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1327.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1331.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1339.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1346.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1352.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1364.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1384.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1392.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1394.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1390.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1380.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1371.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1364.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1347.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1315.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1304.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1304.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 10, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1313.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1335.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1353.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1369.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1391.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1419.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1443.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1464.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1486.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1509.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1529.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1548.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1564.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1578.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1592.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1608.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1621.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1631.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1645.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1661.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1684.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1718.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1737.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1746.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 2, 11, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1751.0,\n      }),\n      'source': 'entsoe.eu',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ERP_PGCB/test_exchanges[None].ambr",
    "content": "# serializer version: 1\n# name: test_exchanges[None]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 1, 13, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 13, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -55.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -50.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -44.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -50.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -50.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -52.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -36.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -48.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -60.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -66.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -48.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -44.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -48.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -50.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -50.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -60.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -60.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ERP_PGCB/test_exchanges[target_datetime1].ambr",
    "content": "# serializer version: 1\n# name: test_exchanges[target_datetime1]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -44.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -50.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -52.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -50.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 1, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'netFlow': -48.0,\n      'sortedZoneKeys': 'BD->IN-NE',\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ERP_PGCB/test_fetch_consumption[None].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption[None]\n  list([\n    dict({\n      'consumption': 9480.0,\n      'datetime': datetime.datetime(2025, 1, 13, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9093.0,\n      'datetime': datetime.datetime(2025, 1, 13, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8508.0,\n      'datetime': datetime.datetime(2025, 1, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8069.0,\n      'datetime': datetime.datetime(2025, 1, 14, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7674.0,\n      'datetime': datetime.datetime(2025, 1, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7517.0,\n      'datetime': datetime.datetime(2025, 1, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7469.0,\n      'datetime': datetime.datetime(2025, 1, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7854.0,\n      'datetime': datetime.datetime(2025, 1, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8664.0,\n      'datetime': datetime.datetime(2025, 1, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9358.0,\n      'datetime': datetime.datetime(2025, 1, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9854.0,\n      'datetime': datetime.datetime(2025, 1, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9675.0,\n      'datetime': datetime.datetime(2025, 1, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9710.0,\n      'datetime': datetime.datetime(2025, 1, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10242.0,\n      'datetime': datetime.datetime(2025, 1, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10465.0,\n      'datetime': datetime.datetime(2025, 1, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10210.0,\n      'datetime': datetime.datetime(2025, 1, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9740.0,\n      'datetime': datetime.datetime(2025, 1, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9513.0,\n      'datetime': datetime.datetime(2025, 1, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9714.0,\n      'datetime': datetime.datetime(2025, 1, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10701.0,\n      'datetime': datetime.datetime(2025, 1, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10901.0,\n      'datetime': datetime.datetime(2025, 1, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10772.0,\n      'datetime': datetime.datetime(2025, 1, 14, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10725.0,\n      'datetime': datetime.datetime(2025, 1, 14, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10458.0,\n      'datetime': datetime.datetime(2025, 1, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10125.0,\n      'datetime': datetime.datetime(2025, 1, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9427.0,\n      'datetime': datetime.datetime(2025, 1, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8966.0,\n      'datetime': datetime.datetime(2025, 1, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8415.0,\n      'datetime': datetime.datetime(2025, 1, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7967.0,\n      'datetime': datetime.datetime(2025, 1, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7687.0,\n      'datetime': datetime.datetime(2025, 1, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7426.0,\n      'datetime': datetime.datetime(2025, 1, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7365.0,\n      'datetime': datetime.datetime(2025, 1, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7908.0,\n      'datetime': datetime.datetime(2025, 1, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8542.0,\n      'datetime': datetime.datetime(2025, 1, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9363.0,\n      'datetime': datetime.datetime(2025, 1, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9682.0,\n      'datetime': datetime.datetime(2025, 1, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9496.0,\n      'datetime': datetime.datetime(2025, 1, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9576.0,\n      'datetime': datetime.datetime(2025, 1, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10149.0,\n      'datetime': datetime.datetime(2025, 1, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10434.0,\n      'datetime': datetime.datetime(2025, 1, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10046.0,\n      'datetime': datetime.datetime(2025, 1, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9788.0,\n      'datetime': datetime.datetime(2025, 1, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9347.0,\n      'datetime': datetime.datetime(2025, 1, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9468.0,\n      'datetime': datetime.datetime(2025, 1, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10577.0,\n      'datetime': datetime.datetime(2025, 1, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10893.0,\n      'datetime': datetime.datetime(2025, 1, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10879.0,\n      'datetime': datetime.datetime(2025, 1, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10769.0,\n      'datetime': datetime.datetime(2025, 1, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10658.0,\n      'datetime': datetime.datetime(2025, 1, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10054.0,\n      'datetime': datetime.datetime(2025, 1, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9529.0,\n      'datetime': datetime.datetime(2025, 1, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ERP_PGCB/test_fetch_consumption[target_datetime1].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption[target_datetime1]\n  list([\n    dict({\n      'consumption': 8104.0,\n      'datetime': datetime.datetime(2025, 1, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7669.0,\n      'datetime': datetime.datetime(2025, 1, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7351.0,\n      'datetime': datetime.datetime(2025, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7082.0,\n      'datetime': datetime.datetime(2025, 1, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 6952.0,\n      'datetime': datetime.datetime(2025, 1, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 7382.0,\n      'datetime': datetime.datetime(2025, 1, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8038.0,\n      'datetime': datetime.datetime(2025, 1, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8896.0,\n      'datetime': datetime.datetime(2025, 1, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9335.0,\n      'datetime': datetime.datetime(2025, 1, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9048.0,\n      'datetime': datetime.datetime(2025, 1, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9272.0,\n      'datetime': datetime.datetime(2025, 1, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9764.0,\n      'datetime': datetime.datetime(2025, 1, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10087.0,\n      'datetime': datetime.datetime(2025, 1, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9531.0,\n      'datetime': datetime.datetime(2025, 1, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9201.0,\n      'datetime': datetime.datetime(2025, 1, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8829.0,\n      'datetime': datetime.datetime(2025, 1, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9175.0,\n      'datetime': datetime.datetime(2025, 1, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10336.0,\n      'datetime': datetime.datetime(2025, 1, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10118.0,\n      'datetime': datetime.datetime(2025, 1, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 10107.0,\n      'datetime': datetime.datetime(2025, 1, 1, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9970.0,\n      'datetime': datetime.datetime(2025, 1, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9829.0,\n      'datetime': datetime.datetime(2025, 1, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 9430.0,\n      'datetime': datetime.datetime(2025, 1, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8898.0,\n      'datetime': datetime.datetime(2025, 1, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'consumption': 8514.0,\n      'datetime': datetime.datetime(2025, 1, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ERP_PGCB/test_fetch_production[None].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production[None]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 13, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3483.0,\n        'gas': 3932.0,\n        'hydro': 40.0,\n        'oil': 306.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 13, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3368.0,\n        'gas': 3831.0,\n        'hydro': 40.0,\n        'oil': 177.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2993.0,\n        'gas': 3821.0,\n        'hydro': 40.0,\n        'oil': 79.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2863.0,\n        'gas': 3821.0,\n        'hydro': 40.0,\n        'oil': 52.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 5.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2586.0,\n        'gas': 3851.0,\n        'hydro': 40.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 12.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2489.0,\n        'gas': 3885.0,\n        'hydro': 40.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 9.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2488.0,\n        'gas': 3833.0,\n        'hydro': 40.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 13.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2582.0,\n        'gas': 4007.0,\n        'hydro': 40.0,\n        'oil': 13.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 12.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2891.0,\n        'gas': 4066.0,\n        'hydro': 40.0,\n        'oil': 132.0,\n        'solar': 6.0,\n        'unknown': 0.0,\n        'wind': 27.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3353.0,\n        'gas': 4007.0,\n        'hydro': 40.0,\n        'oil': 302.0,\n        'solar': 101.0,\n        'unknown': 0.0,\n        'wind': 28.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3430.0,\n        'gas': 3963.0,\n        'hydro': 40.0,\n        'oil': 450.0,\n        'solar': 245.0,\n        'unknown': 0.0,\n        'wind': 13.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3136.0,\n        'gas': 3912.0,\n        'hydro': 40.0,\n        'oil': 456.0,\n        'solar': 374.0,\n        'unknown': 0.0,\n        'wind': 9.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3123.0,\n        'gas': 3848.0,\n        'hydro': 40.0,\n        'oil': 492.0,\n        'solar': 448.0,\n        'unknown': 0.0,\n        'wind': 10.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3280.0,\n        'gas': 4142.0,\n        'hydro': 40.0,\n        'oil': 565.0,\n        'solar': 472.0,\n        'unknown': 0.0,\n        'wind': 14.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3300.0,\n        'gas': 4407.0,\n        'hydro': 40.0,\n        'oil': 570.0,\n        'solar': 454.0,\n        'unknown': 0.0,\n        'wind': 15.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3183.0,\n        'gas': 4435.0,\n        'hydro': 40.0,\n        'oil': 523.0,\n        'solar': 405.0,\n        'unknown': 0.0,\n        'wind': 41.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2988.0,\n        'gas': 4293.0,\n        'hydro': 40.0,\n        'oil': 508.0,\n        'solar': 298.0,\n        'unknown': 0.0,\n        'wind': 40.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2974.0,\n        'gas': 4287.0,\n        'hydro': 40.0,\n        'oil': 510.0,\n        'solar': 150.0,\n        'unknown': 0.0,\n        'wind': 29.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3083.0,\n        'gas': 4455.0,\n        'hydro': 40.0,\n        'oil': 564.0,\n        'solar': 27.0,\n        'unknown': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3328.0,\n        'gas': 4684.0,\n        'hydro': 40.0,\n        'oil': 1020.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3591.0,\n        'gas': 4823.0,\n        'hydro': 40.0,\n        'oil': 718.0,\n        'solar': 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  'hydro': 40.0,\n        'oil': 586.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 14.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3349.0,\n        'gas': 4866.0,\n        'hydro': 40.0,\n        'oil': 515.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3319.0,\n        'gas': 4839.0,\n        'hydro': 40.0,\n        'oil': 288.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 30.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2939.0,\n        'gas': 4845.0,\n        'hydro': 40.0,\n        'oil': 140.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 39.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2692.0,\n        'gas': 4692.0,\n        'hydro': 40.0,\n        'oil': 125.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 45.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2294.0,\n        'gas': 4640.0,\n        'hydro': 40.0,\n        'oil': 43.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 31.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2063.0,\n        'gas': 4629.0,\n        'hydro': 40.0,\n        'oil': 24.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 27.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 1979.0,\n        'gas': 4458.0,\n        'hydro': 40.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 30.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 1976.0,\n        'gas': 4292.0,\n        'hydro': 40.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 33.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 1973.0,\n        'gas': 4236.0,\n        'hydro': 40.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 33.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 1948.0,\n        'gas': 4702.0,\n        'hydro': 40.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 40.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2302.0,\n        'gas': 4603.0,\n        'hydro': 40.0,\n        'oil': 99.0,\n        'solar': 7.0,\n        'unknown': 0.0,\n        'wind': 38.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3037.0,\n        'gas': 4374.0,\n        'hydro': 40.0,\n        'oil': 180.0,\n        'solar': 111.0,\n        'unknown': 0.0,\n        'wind': 25.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3007.0,\n        'gas': 4404.0,\n        'hydro': 40.0,\n        'oil': 296.0,\n        'solar': 297.0,\n        'unknown': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2859.0,\n        'gas': 4247.0,\n        'hydro': 40.0,\n        'oil': 366.0,\n        'solar': 450.0,\n        'unknown': 0.0,\n        'wind': 10.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2860.0,\n        'gas': 4257.0,\n        'hydro': 40.0,\n        'oil': 362.0,\n        'solar': 532.0,\n        'unknown': 0.0,\n        'wind': 8.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3102.0,\n        'gas': 4606.0,\n        'hydro': 40.0,\n        'oil': 345.0,\n        'solar': 532.0,\n        'unknown': 0.0,\n        'wind': 7.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3349.0,\n        'gas': 4567.0,\n        'hydro': 40.0,\n        'oil': 399.0,\n        'solar': 517.0,\n        'unknown': 0.0,\n        'wind': 4.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3382.0,\n        'gas': 4196.0,\n        'hydro': 40.0,\n        'oil': 471.0,\n        'solar': 431.0,\n        'unknown': 0.0,\n        'wind': 0.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3239.0,\n        'gas': 4246.0,\n        'hydro': 40.0,\n        'oil': 472.0,\n        'solar': 341.0,\n        'unknown': 0.0,\n        'wind': 6.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2883.0,\n        'gas': 4349.0,\n        'hydro': 40.0,\n        'oil': 479.0,\n        'solar': 155.0,\n        'unknown': 0.0,\n        'wind': 7.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3000.0,\n        'gas': 4394.0,\n        'hydro': 40.0,\n        'oil': 530.0,\n        'solar': 25.0,\n        'unknown': 0.0,\n        'wind': 4.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3349.0,\n        'gas': 4697.0,\n        'hydro': 40.0,\n        'oil': 910.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 10.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3520.0,\n        'gas': 4962.0,\n        'hydro': 40.0,\n        'oil': 673.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 12.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3557.0,\n        'gas': 5245.0,\n        'hydro': 40.0,\n        'oil': 480.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 8.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3559.0,\n        'gas': 5093.0,\n        'hydro': 40.0,\n        'oil': 576.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 8.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3491.0,\n        'gas': 4903.0,\n        'hydro': 40.0,\n        'oil': 792.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 9.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3226.0,\n        'gas': 4858.0,\n        'hydro': 40.0,\n        'oil': 505.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 8.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3193.0,\n        'gas': 4822.0,\n        'hydro': 40.0,\n        'oil': 496.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 9.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ERP_PGCB/test_fetch_production[target_datetime1].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production[target_datetime1]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2139.0,\n        'gas': 4489.0,\n        'hydro': 26.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 20.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2131.0,\n        'gas': 4311.0,\n        'hydro': 26.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2105.0,\n        'gas': 4021.0,\n        'hydro': 26.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 21.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2103.0,\n        'gas': 3843.0,\n        'hydro': 26.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 29.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2045.0,\n        'gas': 3768.0,\n        'hydro': 26.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 31.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2126.0,\n        'gas': 4131.0,\n        'hydro': 26.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2130.0,\n        'gas': 4672.0,\n        'hydro': 26.0,\n        'oil': 15.0,\n        'solar': 6.0,\n        'unknown': 0.0,\n        'wind': 11.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2531.0,\n        'gas': 4756.0,\n        'hydro': 26.0,\n        'oil': 111.0,\n        'solar': 65.0,\n        'unknown': 0.0,\n        'wind': 11.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3225.0,\n        'gas': 4496.0,\n        'hydro': 46.0,\n        'oil': 163.0,\n        'solar': 127.0,\n        'unknown': 0.0,\n        'wind': 3.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3407.0,\n        'gas': 3780.0,\n        'hydro': 46.0,\n        'oil': 274.0,\n        'solar': 206.0,\n        'unknown': 0.0,\n        'wind': 1.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3289.0,\n        'gas': 3609.0,\n        'hydro': 46.0,\n        'oil': 347.0,\n        'solar': 267.0,\n        'unknown': 0.0,\n        'wind': 2.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3297.0,\n        'gas': 4078.0,\n        'hydro': 46.0,\n        'oil': 334.0,\n        'solar': 288.0,\n        'unknown': 0.0,\n        'wind': 2.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3406.0,\n        'gas': 4344.0,\n        'hydro': 30.0,\n        'oil': 261.0,\n        'solar': 316.0,\n        'unknown': 0.0,\n        'wind': 6.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3142.0,\n        'gas': 4120.0,\n        'hydro': 26.0,\n        'oil': 244.0,\n        'solar': 304.0,\n        'unknown': 0.0,\n        'wind': 16.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2904.0,\n        'gas': 4257.0,\n        'hydro': 26.0,\n        'oil': 285.0,\n        'solar': 205.0,\n        'unknown': 0.0,\n        'wind': 7.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2765.0,\n        'gas': 4267.0,\n        'hydro': 30.0,\n        'oil': 252.0,\n        'solar': 90.0,\n        'unknown': 0.0,\n        'wind': 7.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3057.0,\n        'gas': 3946.0,\n        'hydro': 30.0,\n        'oil': 635.0,\n        'solar': 12.0,\n        'unknown': 0.0,\n        'wind': 3.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3364.0,\n        'gas': 4307.0,\n        'hydro': 40.0,\n        'oil': 1256.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 8.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3615.0,\n        'gas': 4422.0,\n        'hydro': 40.0,\n        'oil': 586.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 13.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3630.0,\n        'gas': 4371.0,\n        'hydro': 40.0,\n        'oil': 620.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 9.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3603.0,\n        'gas': 4295.0,\n        'hydro': 40.0,\n        'oil': 587.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 7.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3626.0,\n        'gas': 4228.0,\n        'hydro': 40.0,\n        'oil': 202.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 11.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3379.0,\n        'gas': 4204.0,\n        'hydro': 40.0,\n        'oil': 88.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 18.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 3081.0,\n        'gas': 4161.0,\n        'hydro': 40.0,\n        'oil': 62.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 19.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Dhaka')),\n      'production': dict({\n        'coal': 2847.0,\n        'gas': 4132.0,\n        'hydro': 40.0,\n        'oil': 35.0,\n        'solar': 0.0,\n        'unknown': 0.0,\n        'wind': 19.0,\n      }),\n      'source': 'erp.pgcb.gov.bd',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ES.ambr",
    "content": "# serializer version: 1\n# name: test_es_cn_te_consumption\n  list([\n    dict({\n      'consumption': 514.2,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 519.3,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 520.1,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 517.6,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 518.1,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 516.0,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 515.8,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 516.2,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 512.8,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 513.7,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 511.8,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 511.0,\n      'datetime': datetime.datetime(2024, 10, 25, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 508.7,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 502.1,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 496.8,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 494.1,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 491.7,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 491.2,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 486.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 476.5,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 479.1,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 478.5,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 472.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 465.8,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 463.2,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 452.9,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 448.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 445.3,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 437.2,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 431.6,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 429.4,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 426.4,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 420.2,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 419.3,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 412.7,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 408.1,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 404.8,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 400.3,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 399.6,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 393.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 388.9,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 388.1,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 381.2,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 376.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 376.6,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 368.2,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 363.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 367.8,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 359.2,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 361.7,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 356.6,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 354.9,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 352.4,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 349.6,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 349.6,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 346.2,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 344.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 341.5,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 337.8,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 334.1,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 333.5,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 331.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 330.8,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 327.9,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 325.9,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 327.2,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 320.3,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 318.2,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 314.7,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 315.6,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 315.2,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 314.2,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 313.4,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 311.3,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 311.1,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 309.7,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 309.6,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 307.7,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 305.3,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 304.7,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 304.1,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 303.0,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 302.2,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 300.1,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 302.2,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 298.9,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 299.4,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 300.0,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 300.1,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 299.5,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 300.0,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.4,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.5,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 297.0,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.2,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.6,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.1,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.0,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 294.9,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 295.1,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.5,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.1,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.7,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.9,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 295.9,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 295.5,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 294.1,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 295.0,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 297.7,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 299.1,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 295.1,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 294.5,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.6,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 293.9,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 293.2,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 296.3,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 295.0,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 300.1,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 300.5,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 300.5,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 305.8,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 311.8,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 315.1,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 316.7,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 318.0,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 316.7,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 320.4,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 319.2,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 322.4,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 323.8,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 327.3,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 331.3,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 330.5,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 335.6,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 339.5,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 343.6,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 349.4,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 349.0,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 350.3,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 353.0,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 353.9,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 358.6,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 355.9,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 360.5,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 369.1,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 369.9,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 374.2,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 369.8,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 377.1,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 375.5,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 379.4,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 383.1,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 386.9,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 391.2,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 395.9,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 399.9,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 404.6,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 408.9,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 415.9,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 419.5,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 424.0,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 423.5,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 428.5,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 435.3,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 433.7,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 439.2,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 443.7,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 443.7,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 450.0,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 452.8,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 453.9,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.5,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 455.9,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.1,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 455.9,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 456.3,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.0,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.8,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 456.5,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.6,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.2,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.1,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.1,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.3,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.2,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 460.2,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.2,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.6,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.6,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 459.4,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.9,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 454.8,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 459.0,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 454.8,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 456.3,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 462.8,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 459.1,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 454.6,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 462.2,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 462.7,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 464.3,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.3,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.6,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 463.2,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 460.8,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 461.7,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 461.7,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.6,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 460.7,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.9,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.1,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 460.0,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 461.7,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 462.5,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 458.5,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 461.0,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 459.4,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 456.7,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 456.6,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 457.1,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 454.5,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 451.7,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 447.4,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 451.9,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 445.8,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 443.5,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 442.8,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 440.6,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 438.9,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 436.4,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 435.0,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 434.9,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 430.8,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 430.6,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 427.9,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 425.9,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 426.6,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 422.4,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 421.8,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 421.9,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 421.7,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 419.4,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 418.6,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 416.6,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 417.2,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 417.4,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 416.2,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 415.3,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 415.8,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 416.1,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 417.7,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 418.9,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 417.7,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 418.2,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 419.4,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 420.6,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 425.1,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 426.1,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 431.0,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 429.0,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 427.0,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 431.6,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 435.9,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 435.4,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 439.3,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 437.0,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 434.7,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 435.8,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 441.4,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 443.1,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 441.0,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 440.1,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 447.6,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 444.5,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 447.9,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 449.5,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 446.8,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 451.7,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 452.1,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 453.0,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 454.7,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 461.8,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 469.5,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 471.9,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 479.3,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 485.6,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 483.4,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 487.0,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 487.2,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 487.2,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 485.7,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 486.2,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 484.3,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 482.3,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 477.9,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 479.0,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 478.4,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 476.9,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 476.3,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 478.9,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 477.1,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 476.4,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 470.4,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 465.2,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 464.8,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 459.5,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 453.2,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 453.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 447.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 441.4,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 437.9,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 438.6,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 430.5,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 425.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 427.8,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 420.8,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 417.8,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 412.7,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 412.4,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 408.7,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 403.9,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 400.7,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 396.3,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 396.3,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 389.5,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 386.6,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 384.9,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 382.6,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 378.8,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 373.7,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 370.4,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 369.3,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 364.4,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 363.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 359.5,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 353.2,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 352.2,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 347.9,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 346.7,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 342.7,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 341.9,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 337.7,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 334.8,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 332.7,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 330.9,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 328.5,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 325.1,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 324.1,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 319.5,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 318.9,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 317.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 313.4,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 313.4,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 311.8,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 309.9,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 308.9,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 305.9,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 304.1,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 303.4,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 300.4,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'consumption': 301.4,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-CN-TE',\n    }),\n  ])\n# ---\n# name: test_es_cn_te_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 410.8,\n        'solar': 0.2,\n        'wind': 103.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 414.2,\n        'solar': 0.2,\n        'wind': 101.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 413.4,\n        'solar': 0.2,\n        'wind': 105.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 412.1,\n        'solar': 0.2,\n        'wind': 103.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 414.4,\n        'solar': 0.2,\n        'wind': 102.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 409.3,\n        'solar': 0.2,\n        'wind': 106.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 400.4,\n        'solar': 0.2,\n        'wind': 114.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 401.1,\n        'solar': 0.2,\n        'wind': 112.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 405.7,\n        'solar': 0.2,\n        'wind': 108.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 408.5,\n        'solar': 0.2,\n        'wind': 103.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 411.0,\n        'solar': 0.2,\n        'wind': 99.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 409.7,\n        'solar': 0.2,\n        'wind': 99.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 401.0,\n        'solar': 0.0,\n        'wind': 106.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 388.7,\n        'solar': 0.0,\n        'wind': 112.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 388.2,\n        'solar': 0.0,\n        'wind': 109.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 381.2,\n        'solar': 0.0,\n        'wind': 112.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 381.2,\n        'solar': 0.0,\n        'wind': 108.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 376.8,\n        'solar': 0.0,\n        'wind': 113.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 376.5,\n        'solar': 0.0,\n        'wind': 110.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 373.1,\n        'solar': 0.0,\n        'wind': 105.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 375.4,\n        'solar': 0.0,\n        'wind': 103.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 373.2,\n        'solar': 0.0,\n        'wind': 104.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 363.8,\n        'solar': 0.0,\n        'wind': 107.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 356.5,\n        'solar': 0.0,\n        'wind': 108.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 360.2,\n        'solar': 0.0,\n        'wind': 99.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 348.1,\n        'solar': 0.0,\n        'wind': 102.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 346.7,\n        'solar': 0.0,\n        'wind': 100.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 344.3,\n        'solar': 0.0,\n        'wind': 100.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 332.9,\n        'solar': 0.0,\n        'wind': 103.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 324.8,\n        'solar': 0.0,\n        'wind': 109.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 315.6,\n        'solar': 0.0,\n        'wind': 113.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 310.3,\n        'solar': 0.0,\n        'wind': 115.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 300.4,\n        'solar': 0.0,\n        'wind': 119.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 289.0,\n        'solar': 0.0,\n        'wind': 128.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 288.3,\n        'solar': 0.0,\n        'wind': 122.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 287.1,\n        'solar': 0.0,\n        'wind': 121.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 273.6,\n        'solar': 0.0,\n        'wind': 129.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 275.4,\n        'solar': 0.0,\n        'wind': 123.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 267.9,\n        'solar': 0.0,\n        'wind': 132.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 256.3,\n        'solar': 0.0,\n        'wind': 135.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 248.0,\n        'solar': 0.0,\n        'wind': 139.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 237.3,\n        'solar': 0.0,\n        'wind': 147.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 234.6,\n        'solar': 0.0,\n        'wind': 143.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 221.7,\n        'solar': 0.0,\n        'wind': 151.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 222.8,\n        'solar': 0.0,\n        'wind': 152.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.2,\n        'solar': 0.0,\n        'wind': 157.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.6,\n        'solar': 0.0,\n        'wind': 158.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.5,\n        'solar': 0.0,\n        'wind': 158.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 211.2,\n        'solar': 0.0,\n        'wind': 147.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.2,\n        'solar': 0.0,\n        'wind': 150.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.8,\n        'solar': 0.0,\n        'wind': 147.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.9,\n        'solar': 0.0,\n        'wind': 150.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.1,\n        'solar': 0.0,\n        'wind': 141.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.4,\n        'solar': 0.0,\n        'wind': 141.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.4,\n        'solar': 0.0,\n        'wind': 142.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.8,\n        'solar': 0.0,\n        'wind': 141.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.2,\n        'solar': 0.0,\n        'wind': 132.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.1,\n        'solar': 0.0,\n        'wind': 132.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.4,\n        'solar': 0.0,\n        'wind': 132.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 200.7,\n        'solar': 0.0,\n        'wind': 132.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.4,\n        'solar': 0.0,\n        'wind': 125.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.1,\n        'solar': 0.0,\n        'wind': 123.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.6,\n        'solar': 0.0,\n        'wind': 124.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.5,\n        'solar': 0.0,\n        'wind': 121.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.7,\n        'solar': 0.0,\n        'wind': 117.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.8,\n        'solar': 0.0,\n        'wind': 118.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.0,\n        'solar': 0.0,\n        'wind': 116.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 199.7,\n        'solar': 0.0,\n        'wind': 118.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.5,\n        'solar': 0.0,\n        'wind': 104.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.5,\n        'solar': 0.0,\n        'wind': 104.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.1,\n        'solar': 0.0,\n        'wind': 104.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.6,\n        'solar': 0.0,\n        'wind': 104.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.6,\n        'solar': 0.0,\n        'wind': 105.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.7,\n        'solar': 0.0,\n        'wind': 102.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.6,\n        'solar': 0.0,\n        'wind': 103.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.6,\n        'solar': 0.0,\n        'wind': 103.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.4,\n        'solar': 0.0,\n        'wind': 105.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 201.9,\n        'solar': 0.0,\n        'wind': 103.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 201.6,\n        'solar': 0.0,\n        'wind': 102.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 201.7,\n        'solar': 0.0,\n        'wind': 102.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 200.5,\n        'solar': 0.0,\n        'wind': 103.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 198.4,\n        'solar': 0.0,\n        'wind': 103.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 197.1,\n        'solar': 0.0,\n        'wind': 103.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.5,\n        'solar': 0.0,\n        'wind': 94.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.5,\n        'solar': 0.0,\n        'wind': 94.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.0,\n        'solar': 0.0,\n        'wind': 92.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.1,\n        'solar': 0.0,\n        'wind': 93.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.9,\n        'solar': 0.0,\n        'wind': 93.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.3,\n        'solar': 0.0,\n        'wind': 92.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.1,\n        'solar': 0.0,\n        'wind': 91.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.9,\n        'solar': 0.0,\n        'wind': 92.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.0,\n        'solar': 0.0,\n        'wind': 92.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.6,\n        'solar': 0.0,\n        'wind': 92.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.1,\n        'solar': 0.0,\n        'wind': 91.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.7,\n        'solar': 0.0,\n        'wind': 92.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.5,\n        'solar': 0.0,\n        'wind': 92.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.8,\n        'solar': 0.0,\n        'wind': 93.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.9,\n        'solar': 0.0,\n        'wind': 92.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.8,\n        'solar': 0.0,\n        'wind': 90.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 201.6,\n        'solar': 0.0,\n        'wind': 93.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.4,\n        'solar': 0.0,\n        'wind': 92.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.4,\n        'solar': 0.0,\n        'wind': 91.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.0,\n        'solar': 0.0,\n        'wind': 92.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.4,\n        'solar': 0.0,\n        'wind': 93.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.4,\n        'solar': 0.0,\n        'wind': 93.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.1,\n        'solar': 0.0,\n        'wind': 93.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 200.6,\n        'solar': 0.0,\n        'wind': 92.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.6,\n        'solar': 0.0,\n        'wind': 91.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.5,\n        'solar': 0.0,\n        'wind': 93.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.4,\n        'solar': 0.0,\n        'wind': 92.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 198.4,\n        'solar': 0.0,\n        'wind': 95.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 197.9,\n        'solar': 0.0,\n        'wind': 97.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 198.1,\n        'solar': 0.0,\n        'wind': 97.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 198.5,\n        'solar': 0.0,\n        'wind': 95.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.9,\n        'solar': 0.0,\n        'wind': 90.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.6,\n        'solar': 0.0,\n        'wind': 93.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 203.6,\n        'solar': 0.0,\n        'wind': 91.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.0,\n        'solar': 0.0,\n        'wind': 91.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 212.5,\n        'solar': 0.0,\n        'wind': 85.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.5,\n        'solar': 0.0,\n        'wind': 91.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 219.1,\n        'solar': 0.0,\n        'wind': 86.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 223.2,\n        'solar': 0.0,\n        'wind': 87.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 226.8,\n        'solar': 0.0,\n        'wind': 85.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 228.5,\n        'solar': 0.0,\n        'wind': 88.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 222.5,\n        'solar': 0.0,\n        'wind': 92.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 215.1,\n        'solar': 0.0,\n        'wind': 102.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 219.1,\n        'solar': 0.0,\n        'wind': 100.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 220.0,\n        'solar': 0.0,\n        'wind': 98.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 219.8,\n        'solar': 0.0,\n        'wind': 101.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 219.0,\n        'solar': 0.0,\n        'wind': 105.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 228.5,\n        'solar': 0.0,\n        'wind': 96.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 245.2,\n        'solar': 0.0,\n        'wind': 85.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 260.0,\n        'solar': 0.0,\n        'wind': 71.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 268.4,\n        'solar': 0.0,\n        'wind': 64.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 278.4,\n        'solar': 0.0,\n        'wind': 60.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 279.1,\n        'solar': 0.0,\n        'wind': 64.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 265.6,\n        'solar': 0.0,\n        'wind': 83.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 252.4,\n        'solar': 0.0,\n        'wind': 97.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 273.5,\n        'solar': 0.0,\n        'wind': 74.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 279.7,\n        'solar': 0.0,\n        'wind': 72.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 278.2,\n        'solar': 0.0,\n        'wind': 75.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 275.5,\n        'solar': 0.0,\n        'wind': 78.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 281.9,\n        'solar': 0.0,\n        'wind': 74.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 295.0,\n        'solar': 0.0,\n        'wind': 66.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 288.0,\n        'solar': 0.0,\n        'wind': 80.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 280.5,\n        'solar': 0.0,\n        'wind': 90.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 279.7,\n        'solar': 0.0,\n        'wind': 93.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 281.0,\n        'solar': 0.0,\n        'wind': 86.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 289.7,\n        'solar': 0.0,\n        'wind': 87.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 295.1,\n        'solar': 0.2,\n        'wind': 78.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 293.7,\n        'solar': 0.4,\n        'wind': 84.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 296.2,\n        'solar': 1.4,\n        'wind': 84.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 306.7,\n        'solar': 2.6,\n        'wind': 77.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 306.8,\n        'solar': 3.2,\n        'wind': 79.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 315.2,\n        'solar': 3.1,\n        'wind': 75.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 316.1,\n        'solar': 4.2,\n        'wind': 80.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 300.4,\n        'solar': 6.0,\n        'wind': 98.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 299.0,\n        'solar': 8.1,\n        'wind': 103.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 313.4,\n        'solar': 7.6,\n        'wind': 94.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 305.4,\n        'solar': 10.0,\n        'wind': 104.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 295.6,\n        'solar': 13.1,\n        'wind': 113.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 288.7,\n        'solar': 17.5,\n        'wind': 119.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 269.1,\n        'solar': 19.2,\n        'wind': 139.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 272.1,\n        'solar': 22.7,\n        'wind': 136.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 273.6,\n        'solar': 23.9,\n        'wind': 135.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 268.0,\n        'solar': 28.8,\n        'wind': 142.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 260.3,\n        'solar': 26.9,\n        'wind': 153.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 260.0,\n        'solar': 26.5,\n        'wind': 156.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 264.6,\n        'solar': 28.2,\n        'wind': 157.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 250.8,\n        'solar': 33.4,\n        'wind': 163.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 248.9,\n        'solar': 31.8,\n        'wind': 173.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 243.8,\n        'solar': 33.6,\n        'wind': 178.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 242.2,\n        'solar': 36.6,\n        'wind': 178.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 232.1,\n        'solar': 42.2,\n        'wind': 179.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 232.3,\n        'solar': 41.4,\n        'wind': 180.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 233.5,\n        'solar': 43.9,\n        'wind': 175.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 224.1,\n        'solar': 48.6,\n        'wind': 183.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 224.9,\n        'solar': 49.5,\n        'wind': 184.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 219.3,\n        'solar': 54.2,\n        'wind': 182.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 220.7,\n        'solar': 54.6,\n        'wind': 180.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 223.6,\n        'solar': 54.1,\n        'wind': 179.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 223.4,\n        'solar': 51.6,\n        'wind': 180.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 223.3,\n        'solar': 51.6,\n        'wind': 182.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 223.5,\n        'solar': 51.5,\n        'wind': 180.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 227.0,\n        'solar': 52.1,\n        'wind': 178.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 219.9,\n        'solar': 59.6,\n        'wind': 178.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 221.9,\n        'solar': 58.6,\n        'wind': 176.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 218.5,\n        'solar': 60.6,\n        'wind': 178.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 216.0,\n        'solar': 59.3,\n        'wind': 180.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.6,\n        'solar': 63.8,\n        'wind': 182.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.4,\n        'solar': 70.9,\n        'wind': 181.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.0,\n        'solar': 67.7,\n        'wind': 184.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.3,\n        'solar': 72.0,\n        'wind': 178.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 200.6,\n        'solar': 71.1,\n        'wind': 184.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 213.4,\n        'solar': 66.5,\n        'wind': 179.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.3,\n        'solar': 80.0,\n        'wind': 177.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.3,\n        'solar': 76.2,\n        'wind': 175.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 211.7,\n        'solar': 70.3,\n        'wind': 172.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.3,\n        'solar': 77.6,\n        'wind': 173.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 216.9,\n        'solar': 77.7,\n        'wind': 165.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 211.8,\n        'solar': 77.4,\n        'wind': 170.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.5,\n        'solar': 72.7,\n        'wind': 175.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 200.0,\n        'solar': 78.5,\n        'wind': 178.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 196.0,\n        'solar': 79.8,\n        'wind': 184.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 198.3,\n        'solar': 79.5,\n        'wind': 182.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.2,\n        'solar': 76.4,\n        'wind': 179.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.8,\n        'solar': 75.6,\n        'wind': 176.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.8,\n        'solar': 75.8,\n        'wind': 174.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.9,\n        'solar': 75.3,\n        'wind': 173.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 213.5,\n        'solar': 72.4,\n        'wind': 171.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 217.9,\n        'solar': 66.3,\n        'wind': 171.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 214.5,\n        'solar': 73.8,\n        'wind': 169.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 215.8,\n        'solar': 73.2,\n        'wind': 171.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 219.0,\n        'solar': 72.3,\n        'wind': 170.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 216.0,\n        'solar': 68.8,\n        'wind': 173.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 213.2,\n        'solar': 72.3,\n        'wind': 175.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 211.3,\n        'solar': 73.5,\n        'wind': 175.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.0,\n        'solar': 74.1,\n        'wind': 175.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.6,\n        'solar': 71.9,\n        'wind': 177.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.9,\n        'solar': 74.1,\n        'wind': 176.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.9,\n        'solar': 75.1,\n        'wind': 175.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 200.2,\n        'solar': 74.8,\n        'wind': 175.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.7,\n        'solar': 72.2,\n        'wind': 172.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.1,\n        'solar': 72.0,\n        'wind': 171.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 201.1,\n        'solar': 72.3,\n        'wind': 172.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.8,\n        'solar': 67.9,\n        'wind': 166.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 211.3,\n        'solar': 65.9,\n        'wind': 164.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.1,\n        'solar': 64.2,\n        'wind': 165.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.2,\n        'solar': 64.8,\n        'wind': 165.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.5,\n        'solar': 63.1,\n        'wind': 167.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.8,\n        'solar': 61.7,\n        'wind': 165.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.0,\n        'solar': 63.9,\n        'wind': 166.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 202.6,\n        'solar': 64.2,\n        'wind': 164.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.4,\n        'solar': 59.2,\n        'wind': 163.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.3,\n        'solar': 59.5,\n        'wind': 163.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.3,\n        'solar': 59.5,\n        'wind': 161.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 204.9,\n        'solar': 58.9,\n        'wind': 161.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.0,\n        'solar': 57.9,\n        'wind': 159.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.7,\n        'solar': 56.0,\n        'wind': 156.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.9,\n        'solar': 55.7,\n        'wind': 156.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.1,\n        'solar': 55.0,\n        'wind': 156.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.0,\n        'solar': 54.1,\n        'wind': 155.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.3,\n        'solar': 53.7,\n        'wind': 155.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.0,\n        'solar': 53.2,\n        'wind': 156.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.7,\n        'solar': 52.2,\n        'wind': 156.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.2,\n        'solar': 51.8,\n        'wind': 157.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.4,\n        'solar': 50.6,\n        'wind': 158.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.0,\n        'solar': 49.2,\n        'wind': 157.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.8,\n        'solar': 48.4,\n        'wind': 157.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.6,\n        'solar': 47.0,\n        'wind': 160.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 211.5,\n        'solar': 45.3,\n        'wind': 160.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 211.4,\n        'solar': 45.4,\n        'wind': 160.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 212.7,\n        'solar': 43.8,\n        'wind': 161.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 213.0,\n        'solar': 41.5,\n        'wind': 162.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 215.0,\n        'solar': 40.0,\n        'wind': 163.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 220.0,\n        'solar': 35.9,\n        'wind': 164.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 214.4,\n        'solar': 35.6,\n        'wind': 172.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 217.7,\n        'solar': 34.8,\n        'wind': 172.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 220.3,\n        'solar': 33.8,\n        'wind': 177.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 218.3,\n        'solar': 29.4,\n        'wind': 181.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 218.2,\n        'solar': 27.7,\n        'wind': 179.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 225.2,\n        'solar': 24.3,\n        'wind': 181.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 222.4,\n        'solar': 22.8,\n        'wind': 189.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 224.1,\n        'solar': 22.0,\n        'wind': 189.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 223.6,\n        'solar': 19.6,\n        'wind': 194.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 224.5,\n        'solar': 18.4,\n        'wind': 192.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 226.6,\n        'solar': 16.5,\n        'wind': 191.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 230.7,\n        'solar': 14.3,\n        'wind': 190.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 236.6,\n        'solar': 13.0,\n        'wind': 189.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 239.9,\n        'solar': 11.2,\n        'wind': 190.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 236.8,\n        'solar': 9.7,\n        'wind': 195.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 242.7,\n        'solar': 7.7,\n        'wind': 188.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 242.1,\n        'solar': 5.7,\n        'wind': 195.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 247.0,\n        'solar': 3.1,\n        'wind': 196.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 253.9,\n        'solar': 2.2,\n        'wind': 190.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 252.6,\n        'solar': 0.6,\n        'wind': 194.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 246.7,\n        'solar': 0.3,\n        'wind': 199.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 248.8,\n        'solar': 0.1,\n        'wind': 203.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 252.2,\n        'solar': 0.0,\n        'wind': 199.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 256.0,\n        'solar': 0.0,\n        'wind': 196.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 259.4,\n        'solar': 0.0,\n        'wind': 196.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 262.8,\n        'solar': 0.0,\n        'wind': 197.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 268.1,\n        'solar': 0.0,\n        'wind': 201.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 275.4,\n        'solar': 0.0,\n        'wind': 198.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 279.8,\n        'solar': 0.0,\n        'wind': 197.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 283.9,\n        'solar': 0.0,\n        'wind': 198.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 281.7,\n        'solar': 0.0,\n        'wind': 201.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 284.3,\n        'solar': 0.0,\n        'wind': 203.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 284.5,\n        'solar': 0.0,\n        'wind': 201.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 286.3,\n        'solar': 0.0,\n        'wind': 200.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 287.3,\n        'solar': 0.0,\n        'wind': 197.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 285.0,\n        'solar': 0.0,\n        'wind': 197.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 291.9,\n        'solar': 0.0,\n        'wind': 193.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 286.2,\n        'solar': 0.0,\n        'wind': 194.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 277.6,\n        'solar': 0.0,\n        'wind': 199.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 275.2,\n        'solar': 0.0,\n        'wind': 203.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 271.3,\n        'solar': 0.0,\n        'wind': 205.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 269.5,\n        'solar': 0.0,\n        'wind': 207.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 268.0,\n        'solar': 0.0,\n        'wind': 207.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 273.1,\n        'solar': 0.0,\n        'wind': 205.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 275.3,\n        'solar': 0.0,\n        'wind': 203.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 276.0,\n        'solar': 0.0,\n        'wind': 201.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 271.1,\n        'solar': 0.0,\n        'wind': 198.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 272.3,\n        'solar': 0.0,\n        'wind': 192.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 272.5,\n        'solar': 0.0,\n        'wind': 190.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 267.0,\n        'solar': 0.0,\n        'wind': 191.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 259.3,\n        'solar': 0.0,\n        'wind': 193.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 250.7,\n        'solar': 0.0,\n        'wind': 199.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 248.4,\n        'solar': 0.0,\n        'wind': 197.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 242.1,\n        'solar': 0.0,\n        'wind': 195.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 247.5,\n        'solar': 0.0,\n        'wind': 190.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 252.4,\n        'solar': 0.0,\n        'wind': 181.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 263.1,\n        'solar': 0.0,\n        'wind': 166.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 272.9,\n        'solar': 0.0,\n        'wind': 147.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 265.4,\n        'solar': 0.0,\n        'wind': 157.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 249.3,\n        'solar': 0.0,\n        'wind': 170.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 234.4,\n        'solar': 0.0,\n        'wind': 181.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 223.0,\n        'solar': 0.0,\n        'wind': 190.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 220.5,\n        'solar': 0.0,\n        'wind': 190.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 215.8,\n        'solar': 0.0,\n        'wind': 191.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 214.3,\n        'solar': 0.0,\n        'wind': 190.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.8,\n        'solar': 0.0,\n        'wind': 190.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.6,\n        'solar': 0.0,\n        'wind': 187.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.5,\n        'solar': 0.0,\n        'wind': 190.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.8,\n        'solar': 0.0,\n        'wind': 181.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 205.8,\n        'solar': 0.0,\n        'wind': 178.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.5,\n        'solar': 0.0,\n        'wind': 178.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 212.8,\n        'solar': 0.0,\n        'wind': 169.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.4,\n        'solar': 0.0,\n        'wind': 166.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.9,\n        'solar': 0.0,\n        'wind': 164.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 210.6,\n        'solar': 0.0,\n        'wind': 157.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.7,\n        'solar': 0.0,\n        'wind': 160.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 213.4,\n        'solar': 0.0,\n        'wind': 150.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 211.9,\n        'solar': 0.0,\n        'wind': 149.9,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 213.5,\n        'solar': 0.0,\n        'wind': 144.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 215.8,\n        'solar': 0.0,\n        'wind': 136.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 229.0,\n        'solar': 0.0,\n        'wind': 120.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 236.5,\n        'solar': 0.0,\n        'wind': 111.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 242.9,\n        'solar': 0.0,\n        'wind': 104.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 247.0,\n        'solar': 0.0,\n        'wind': 94.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 248.7,\n        'solar': 0.0,\n        'wind': 92.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 251.6,\n        'solar': 0.0,\n        'wind': 84.6,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 250.3,\n        'solar': 0.0,\n        'wind': 83.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 245.5,\n        'solar': 0.0,\n        'wind': 86.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 233.6,\n        'solar': 0.0,\n        'wind': 92.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 226.9,\n        'solar': 0.0,\n        'wind': 99.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 222.6,\n        'solar': 0.0,\n        'wind': 102.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Canary')),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 223.1,\n        'solar': 0.0,\n        'wind': 101.1,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 219.1,\n        'solar': 0.0,\n        'wind': 101.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 219.1,\n        'solar': 0.0,\n        'wind': 99.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 211.5,\n        'solar': 0.0,\n        'wind': 105.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 214.5,\n        'solar': 0.0,\n        'wind': 99.7,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 225.5,\n        'solar': 0.0,\n        'wind': 84.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 217.4,\n        'solar': 0.0,\n        'wind': 93.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.4,\n        'solar': 0.0,\n        'wind': 99.2,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 209.5,\n        'solar': 0.0,\n        'wind': 98.4,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 208.1,\n        'solar': 0.0,\n        'wind': 97.8,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 207.3,\n        'solar': 0.0,\n        'wind': 95.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.7,\n        'solar': 0.0,\n        'wind': 96.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 206.7,\n        'solar': 0.0,\n        'wind': 92.5,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 218.0,\n        'solar': 0.0,\n        'wind': 82.3,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'ES-CN-TE',\n    }),\n  ])\n# ---\n# name: test_es_consumption\n  list([\n    dict({\n      'consumption': 29998.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 29796.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 29865.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 29631.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 29678.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 29600.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 29315.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 29130.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 28740.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 28597.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 28199.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 28104.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 27782.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 27424.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 27169.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 27064.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26655.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26611.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26324.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26182.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26082.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25798.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25771.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25400.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25312.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25226.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24960.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24596.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24581.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24423.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24164.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24091.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24050.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23823.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23517.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23497.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23638.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23354.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23261.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23141.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23105.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22953.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22849.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22633.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22660.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22404.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22217.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22227.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22053.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21884.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21763.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21731.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21782.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21580.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21245.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21356.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21305.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21102.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21053.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20765.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20862.0,\n      'datetime': datetime.datetime(2024, 10, 26, 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'ES',\n    }),\n    dict({\n      'consumption': 26974.0,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26794.0,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26755.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26922.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26801.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26535.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26518.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26383.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26340.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 26135.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25799.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25553.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25431.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25575.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25338.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 25143.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24811.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24717.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24476.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23999.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 24081.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23975.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23839.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23266.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23143.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23353.0,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23263.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23220.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23067.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 23082.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22792.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22721.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22538.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22407.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22118.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 22133.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21975.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21915.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21665.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21652.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21505.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21505.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21312.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 21102.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20898.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20882.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20652.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20557.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20543.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20485.0,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20229.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20296.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20288.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20055.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 20021.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19789.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19755.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19714.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19649.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19613.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19298.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19358.0,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19284.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19192.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19058.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19230.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 19127.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 18971.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 18733.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 18754.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 18966.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 18778.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 18666.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 18719.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'consumption': 18524.0,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n  ])\n# ---\n# name: test_es_ib_ma_consumption\n  list([\n    dict({\n      'consumption': 601.1,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 599.6,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 593.9,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 593.7,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 584.2,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 581.2,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 574.8,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 566.7,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 559.0,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 556.2,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 543.7,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 541.3,\n      'datetime': datetime.datetime(2024, 10, 25, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 530.2,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 521.5,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 517.5,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 512.7,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 506.9,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 502.2,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 496.6,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 491.8,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 486.0,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 482.1,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 476.3,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 470.3,\n      'datetime': datetime.datetime(2024, 10, 25, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 462.4,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 459.5,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 455.8,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 452.6,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 447.2,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 442.4,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 437.5,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 435.2,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 430.3,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 425.0,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 422.9,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 419.6,\n      'datetime': datetime.datetime(2024, 10, 25, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 415.2,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 411.9,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 411.1,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 407.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 404.1,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 401.2,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 396.3,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 394.9,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 390.3,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 388.5,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 386.0,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 383.3,\n      'datetime': datetime.datetime(2024, 10, 26, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 380.5,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 379.1,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 377.1,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 376.1,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 373.0,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 372.3,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 370.3,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 367.5,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 367.3,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 363.2,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 362.7,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 360.5,\n      'datetime': datetime.datetime(2024, 10, 26, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 360.4,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 359.6,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 357.0,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 356.7,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 353.7,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 353.1,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 352.0,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 350.4,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 350.5,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 349.7,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 347.4,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 348.8,\n      'datetime': datetime.datetime(2024, 10, 26, 2, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 347.0,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 346.8,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 344.3,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 346.1,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 344.4,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 343.8,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 343.3,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 342.9,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 343.9,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 342.9,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 342.1,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 341.6,\n      'datetime': datetime.datetime(2024, 10, 26, 3, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 341.2,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 340.3,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 339.7,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 339.5,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 340.6,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 340.5,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 339.6,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 340.9,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 341.4,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 342.5,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 341.1,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 342.3,\n      'datetime': datetime.datetime(2024, 10, 26, 4, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 340.8,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 345.5,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 345.4,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 347.8,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 349.3,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 349.2,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 349.8,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 351.6,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 352.2,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 355.0,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 355.1,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 356.8,\n      'datetime': datetime.datetime(2024, 10, 26, 5, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 361.4,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 368.4,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 372.7,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 374.7,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 376.4,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 380.0,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 380.7,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 385.1,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 389.0,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 392.1,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 394.4,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 399.8,\n      'datetime': datetime.datetime(2024, 10, 26, 6, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 405.0,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 412.5,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 420.9,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 423.4,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 425.0,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 429.3,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 431.9,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 438.4,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 440.0,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 441.5,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 447.2,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 450.6,\n      'datetime': datetime.datetime(2024, 10, 26, 7, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 455.4,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 463.6,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 471.0,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 469.8,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 472.5,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 472.2,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 480.0,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 482.8,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 484.9,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 491.9,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 468.6,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 489.1,\n      'datetime': datetime.datetime(2024, 10, 26, 8, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 496.6,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 507.0,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 515.9,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 523.6,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 525.4,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 552.4,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 554.2,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 557.3,\n      'datetime': datetime.datetime(2024, 10, 26, 9, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 561.4,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 572.0,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 578.9,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 577.5,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 577.3,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 583.1,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 583.1,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 586.9,\n      'datetime': datetime.datetime(2024, 10, 26, 10, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 594.5,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 595.9,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 595.4,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 595.0,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 598.8,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 598.9,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 599.5,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 599.2,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 597.6,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 597.9,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 597.6,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 593.9,\n      'datetime': datetime.datetime(2024, 10, 26, 11, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 595.7,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 597.6,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 597.8,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 601.2,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 604.0,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 601.5,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 602.8,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 602.2,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 599.7,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 601.2,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 598.9,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 598.0,\n      'datetime': datetime.datetime(2024, 10, 26, 12, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 592.8,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 587.7,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 579.1,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 570.9,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 565.4,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 559.8,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 551.2,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 542.5,\n      'datetime': datetime.datetime(2024, 10, 26, 13, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 539.7,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 14, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 516.4,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 509.1,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 501.5,\n      'datetime': datetime.datetime(2024, 10, 26, 14, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 14, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 495.9,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 495.1,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 501.5,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 486.7,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 483.7,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 485.4,\n      'datetime': datetime.datetime(2024, 10, 26, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 16, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 475.7,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 479.7,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 481.4,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 483.0,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 486.4,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 486.5,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 484.5,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 487.0,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 492.0,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 488.3,\n      'datetime': datetime.datetime(2024, 10, 26, 16, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 493.3,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 499.1,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 497.5,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 502.7,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 506.3,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 504.4,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 507.8,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 509.6,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 512.3,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 512.7,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 518.9,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 519.6,\n      'datetime': datetime.datetime(2024, 10, 26, 17, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 520.5,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 523.8,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 524.9,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 525.4,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 525.2,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 527.7,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 531.7,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 534.7,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 538.7,\n      'datetime': datetime.datetime(2024, 10, 26, 18, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 567.4,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 573.2,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 576.4,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 19, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 583.5,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 586.5,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 585.7,\n      'datetime': datetime.datetime(2024, 10, 26, 19, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 20, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 586.6,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 587.5,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 586.6,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 579.5,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 575.7,\n      'datetime': datetime.datetime(2024, 10, 26, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 571.7,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': 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datetime.datetime(2024, 10, 26, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 550.8,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 545.9,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 534.4,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 532.1,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 525.0,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 519.5,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 512.4,\n      'datetime': datetime.datetime(2024, 10, 26, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 507.9,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 497.4,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 492.6,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 485.1,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 481.3,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 473.5,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 468.6,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 463.5,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 461.8,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 456.1,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 452.3,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 448.9,\n      'datetime': datetime.datetime(2024, 10, 26, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 447.7,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 440.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 439.7,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 434.1,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 429.2,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 430.4,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 425.4,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 422.6,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 418.4,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 414.5,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 412.0,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 407.1,\n      'datetime': datetime.datetime(2024, 10, 26, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 405.3,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 401.1,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 399.3,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 395.7,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 393.1,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 391.3,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 387.4,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 384.9,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 381.8,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 380.7,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 377.6,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 375.7,\n      'datetime': datetime.datetime(2024, 10, 27, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 373.4,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 370.9,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 369.3,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 367.2,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 364.3,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 361.5,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 358.9,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 357.5,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 355.6,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 353.7,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 351.2,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 350.9,\n      'datetime': datetime.datetime(2024, 10, 27, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 349.2,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 348.8,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 346.8,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 344.1,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 343.1,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 342.1,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 339.3,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 336.8,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 336.7,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 335.1,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 335.1,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 334.2,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'consumption': 334.5,\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES-IB-MA',\n    }),\n  ])\n# ---\n# name: test_es_ib_ma_exchange\n  list([\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -100.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -98.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -100.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -98.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -98.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -97.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -96.8,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -96.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -95.5,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -93.4,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -93.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -90.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -88.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -87.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 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tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -52.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -52.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 16, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -50.5,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 16, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -51.3,\n      'sortedZoneKeys': 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tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -55.8,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 16, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -58.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 16, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -56.8,\n      'sortedZoneKeys': 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tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -66.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -65.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -63.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -61.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -61.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -60.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -60.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -60.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -62.4,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -66.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -64.5,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -65.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -63.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -59.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -57.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -58.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -60.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -59.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -57.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -55.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -55.5,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -55.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -54.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -57.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -61.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -73.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -74.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -77.8,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -78.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -81.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -81.1,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -85.8,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -87.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -91.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -91.5,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -90.5,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -89.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -88.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -88.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -87.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -87.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -86.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -85.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -85.4,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -84.8,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -83.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -83.5,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -83.4,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -82.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -82.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -81.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -81.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -80.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -81.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -80.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -80.1,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -79.5,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -79.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -79.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -78.8,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -78.6,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -77.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -77.5,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -77.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -77.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -76.7,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -77.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -76.9,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -76.3,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': -76.2,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': -76.0,\n      'sortedZoneKeys': 'ES-IB-IZ->ES-IB-MA',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_es_ib_ma_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 401.8,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 425.2,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 428.4,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 16.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 432.5,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 427.2,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.5,\n        'coal': 0.0,\n        'gas': 423.7,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 413.8,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 405.9,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 398.0,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 392.4,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 16.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 379.4,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 373.8,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 370.4,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.6,\n        'coal': 0.0,\n        'gas': 370.4,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.8,\n        'coal': 0.0,\n        'gas': 376.6,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 379.0,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 380.9,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 384.3,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 16.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 388.1,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.4,\n        'coal': 0.0,\n        'gas': 392.1,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.8,\n        'coal': 0.0,\n        'gas': 393.0,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 16.1,\n        'coal': 0.0,\n        'gas': 404.5,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 18.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.9,\n        'coal': 0.0,\n        'gas': 421.0,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 18.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.4,\n        'coal': 0.0,\n        'gas': 420.0,\n        'oil': 0.0,\n        'solar': 1.9,\n        'unknown': 17.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 411.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 411.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 409.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.4,\n        'coal': 0.0,\n        'gas': 405.8,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 402.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 398.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 391.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.6,\n        'coal': 0.0,\n        'gas': 386.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 381.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 377.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 372.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 367.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 362.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 358.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 357.4,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 353.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 350.4,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 346.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n 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'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 333.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 333.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 329.8,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 324.8,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 324.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 323.4,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 321.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 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   'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 313.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.5,\n        'coal': 0.0,\n        'gas': 311.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 306.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.5,\n        'coal': 0.0,\n        'gas': 305.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 303.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.1,\n        'coal': 0.0,\n        'gas': 302.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 12.7,\n        'coal': 0.0,\n        'gas': 302.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.0,\n        'coal': 0.0,\n        'gas': 301.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 298.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 295.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 293.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.2,\n        'coal': 0.0,\n        'gas': 292.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.5,\n        'coal': 0.0,\n        'gas': 289.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.6,\n        'coal': 0.0,\n        'gas': 285.8,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.3,\n        'coal': 0.0,\n        'gas': 285.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.2,\n        'coal': 0.0,\n        'gas': 286.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 284.8,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 281.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 281.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 280.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 0.0,\n        'gas': 280.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 278.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 0.0,\n        'gas': 279.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 276.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.5,\n        'coal': 0.0,\n        'gas': 275.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 275.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 275.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 275.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 275.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 275.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 3, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 274.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 272.4,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 270.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 270.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 271.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 271.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 271.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 270.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 270.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 271.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 271.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 271.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 4, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 272.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 272.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.1,\n        'coal': 0.0,\n        'gas': 277.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 12.7,\n        'coal': 0.0,\n        'gas': 277.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.3,\n        'coal': 0.0,\n        'gas': 280.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 279.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 280.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 0.0,\n        'gas': 281.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 283.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 283.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.0,\n        'coal': 0.0,\n        'gas': 290.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.1,\n        'coal': 0.0,\n        'gas': 290.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 5, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 0.0,\n        'gas': 290.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 293.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 302.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 312.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.2,\n        'coal': 0.0,\n        'gas': 315.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.2,\n        'coal': 0.0,\n        'gas': 318.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 318.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 319.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 324.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 0.0,\n        'gas': 329.4,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 333.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 330.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.2,\n        'wind': 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13.9,\n        'coal': 0.0,\n        'gas': 346.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 350.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.3,\n        'coal': 0.0,\n        'gas': 353.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 362.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n 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'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 0.0,\n        'gas': 375.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 376.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 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10, 26, 8, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 407.9,\n        'oil': 0.0,\n        'solar': 4.4,\n        'unknown': 17.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.9,\n        'coal': 0.0,\n        'gas': 409.8,\n        'oil': 0.0,\n        'solar': 6.3,\n        'unknown': 18.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      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dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 8, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 11.4,\n        'coal': 0.0,\n        'gas': 422.7,\n        'oil': 0.0,\n        'solar': 14.4,\n        'unknown': 11.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 6.8,\n        'coal': 0.0,\n        'gas': 431.2,\n        'oil': 0.0,\n        'solar': 17.2,\n        'unknown': 6.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 9.2,\n        'coal': 0.0,\n        'gas': 434.0,\n        'oil': 0.0,\n        'solar': 18.9,\n        'unknown': 9.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 10.4,\n        'coal': 0.0,\n        'gas': 441.0,\n        'oil': 0.0,\n        'solar': 19.7,\n        'unknown': 10.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 10.3,\n        'coal': 0.0,\n        'gas': 447.7,\n        'oil': 0.0,\n        'solar': 20.3,\n        'unknown': 10.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 9.4,\n        'coal': 0.0,\n        'gas': 450.7,\n        'oil': 0.0,\n        'solar': 22.2,\n        'unknown': 9.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 11.6,\n        'coal': 0.0,\n        'gas': 448.1,\n        'oil': 0.0,\n        'solar': 24.5,\n        'unknown': 11.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.3,\n        'coal': 0.0,\n        'gas': 454.2,\n        'oil': 0.0,\n        'solar': 20.2,\n        'unknown': 13.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.1,\n        'coal': 0.0,\n        'gas': 465.3,\n        'oil': 0.0,\n        'solar': 20.5,\n        'unknown': 14.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 467.0,\n        'oil': 0.0,\n        'solar': 18.7,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.1,\n        'coal': 0.0,\n        'gas': 467.6,\n        'oil': 0.0,\n        'solar': 20.1,\n        'unknown': 15.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 12.9,\n        'coal': 0.0,\n        'gas': 466.4,\n        'oil': 0.0,\n        'solar': 20.5,\n        'unknown': 15.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 467.7,\n        'oil': 0.0,\n        'solar': 21.7,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 473.0,\n        'oil': 0.0,\n        'solar': 17.6,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 0.0,\n        'gas': 466.0,\n        'oil': 0.0,\n        'solar': 22.1,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': 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tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 504.5,\n        'oil': 0.0,\n        'solar': 10.1,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.5,\n        'coal': 0.0,\n        'gas': 501.2,\n        'oil': 0.0,\n        'solar': 11.6,\n        'unknown': 17.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 10, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.9,\n        'coal': 0.0,\n        'gas': 498.2,\n        'oil': 0.0,\n        'solar': 10.7,\n        'unknown': 18.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 500.7,\n        'oil': 0.0,\n        'solar': 4.8,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 477.9,\n        'oil': 0.0,\n        'solar': 6.0,\n        'unknown': 16.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 490.7,\n        'oil': 0.0,\n        'solar': 6.0,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 497.4,\n        'oil': 0.0,\n        'solar': 5.9,\n        'unknown': 17.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 496.7,\n        'oil': 0.0,\n        'solar': 7.2,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 494.7,\n        'oil': 0.0,\n        'solar': 9.2,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 493.8,\n        'oil': 0.0,\n        'solar': 10.9,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.1,\n        'coal': 0.0,\n        'gas': 496.2,\n        'oil': 0.0,\n        'solar': 11.7,\n        'unknown': 15.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 487.3,\n        'oil': 0.0,\n        'solar': 13.5,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 11, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.3,\n        'coal': 0.0,\n        'gas': 479.9,\n        'oil': 0.0,\n        'solar': 11.2,\n        'unknown': 16.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 476.3,\n        'oil': 0.0,\n        'solar': 12.2,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 473.9,\n        'oil': 0.0,\n        'solar': 18.5,\n        'unknown': 17.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 475.5,\n        'oil': 0.0,\n        'solar': 16.7,\n        'unknown': 17.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 480.7,\n        'oil': 0.0,\n        'solar': 14.4,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 485.3,\n        'oil': 0.0,\n        'solar': 13.2,\n        'unknown': 16.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 485.0,\n        'oil': 0.0,\n        'solar': 13.6,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 485.2,\n        'oil': 0.0,\n        'solar': 13.4,\n        'unknown': 17.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.4,\n        'coal': 0.0,\n        'gas': 484.5,\n        'oil': 0.0,\n        'solar': 15.1,\n        'unknown': 17.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 481.7,\n        'oil': 0.0,\n        'solar': 20.1,\n        'unknown': 17.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 486.6,\n        'oil': 0.0,\n        'solar': 23.8,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.3,\n        'coal': 0.0,\n        'gas': 490.6,\n        'oil': 0.0,\n        'solar': 26.3,\n        'unknown': 17.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 480.1,\n        'oil': 0.0,\n        'solar': 33.5,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 0.0,\n        'gas': 463.9,\n        'oil': 0.0,\n        'solar': 45.5,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 456.4,\n        'oil': 0.0,\n        'solar': 48.3,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 438.5,\n        'oil': 0.0,\n        'solar': 54.2,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 415.3,\n        'oil': 0.0,\n        'solar': 73.0,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 392.0,\n        'oil': 0.0,\n        'solar': 89.1,\n        'unknown': 14.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 374.5,\n        'oil': 0.0,\n        'solar': 97.2,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.3,\n        'coal': 0.0,\n        'gas': 357.9,\n        'oil': 0.0,\n        'solar': 105.7,\n        'unknown': 16.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 337.0,\n        'oil': 0.0,\n        'solar': 120.8,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 333.6,\n        'oil': 0.0,\n        'solar': 120.9,\n        'unknown': 14.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 329.8,\n        'oil': 0.0,\n        'solar': 124.0,\n        'unknown': 14.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 338.6,\n        'oil': 0.0,\n        'solar': 106.8,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 331.0,\n        'oil': 0.0,\n        'solar': 107.3,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 319.3,\n        'oil': 0.0,\n        'solar': 114.5,\n        'unknown': 14.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 316.4,\n        'oil': 0.0,\n        'solar': 130.1,\n        'unknown': 14.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 320.0,\n        'oil': 0.0,\n        'solar': 135.6,\n        'unknown': 14.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.1,\n        'coal': 0.0,\n        'gas': 313.5,\n        'oil': 0.0,\n        'solar': 126.9,\n        'unknown': 14.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.1,\n        'coal': 0.0,\n        'gas': 307.7,\n        'oil': 0.0,\n        'solar': 134.9,\n        'unknown': 13.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 0.0,\n        'gas': 311.9,\n        'oil': 0.0,\n        'solar': 125.5,\n        'unknown': 13.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 0.0,\n        'gas': 287.7,\n        'oil': 0.0,\n        'solar': 138.3,\n        'unknown': 13.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 269.2,\n        'oil': 0.0,\n        'solar': 150.8,\n        'unknown': 14.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.3,\n        'coal': 0.0,\n        'gas': 279.2,\n        'oil': 0.0,\n        'solar': 145.3,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.0,\n        'coal': 0.0,\n        'gas': 289.8,\n        'oil': 0.0,\n        'solar': 126.9,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.2,\n        'coal': 0.0,\n        'gas': 281.9,\n        'oil': 0.0,\n        'solar': 148.7,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 12.9,\n        'coal': 0.0,\n        'gas': 285.2,\n        'oil': 0.0,\n        'solar': 133.2,\n        'unknown': 15.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 296.9,\n        'oil': 0.0,\n        'solar': 124.5,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 0.0,\n        'gas': 298.7,\n        'oil': 0.0,\n        'solar': 120.6,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.2,\n        'coal': 0.0,\n        'gas': 290.3,\n        'oil': 0.0,\n        'solar': 142.8,\n        'unknown': 15.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.3,\n        'coal': 0.0,\n        'gas': 293.4,\n        'oil': 0.0,\n        'solar': 116.9,\n        'unknown': 15.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.5,\n        'coal': 0.0,\n        'gas': 306.6,\n        'oil': 0.0,\n        'solar': 107.6,\n        'unknown': 16.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 310.4,\n        'oil': 0.0,\n        'solar': 101.2,\n        'unknown': 17.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.5,\n        'coal': 0.0,\n        'gas': 308.6,\n        'oil': 0.0,\n        'solar': 104.1,\n        'unknown': 16.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 308.9,\n        'oil': 0.0,\n        'solar': 104.7,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 12.9,\n        'coal': 0.0,\n        'gas': 299.7,\n        'oil': 0.0,\n        'solar': 110.8,\n        'unknown': 15.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 0.0,\n        'gas': 292.0,\n        'oil': 0.0,\n        'solar': 121.1,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 284.3,\n        'oil': 0.0,\n        'solar': 118.8,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 15, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.5,\n        'coal': 0.0,\n        'gas': 283.6,\n        'oil': 0.0,\n        'solar': 113.6,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 0.0,\n        'gas': 286.2,\n        'oil': 0.0,\n        'solar': 110.5,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.6,\n        'coal': 0.0,\n        'gas': 289.6,\n        'oil': 0.0,\n        'solar': 110.9,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 286.9,\n        'oil': 0.0,\n        'solar': 106.5,\n        'unknown': 17.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 16.2,\n        'coal': 0.0,\n        'gas': 299.0,\n        'oil': 0.0,\n        'solar': 94.2,\n        'unknown': 18.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.4,\n        'coal': 0.0,\n        'gas': 312.1,\n        'oil': 0.0,\n        'solar': 80.9,\n        'unknown': 17.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 314.4,\n        'oil': 0.0,\n        'solar': 87.7,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 0.0,\n        'gas': 330.0,\n        'oil': 0.0,\n        'solar': 68.3,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.4,\n        'coal': 0.0,\n        'gas': 336.3,\n        'oil': 0.0,\n        'solar': 82.8,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': 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0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 333.8,\n        'oil': 0.0,\n        'solar': 70.2,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 16, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 344.5,\n        'oil': 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tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 295.3,\n        'oil': 0.0,\n        'solar': 43.3,\n        'unknown': 17.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 289.0,\n        'oil': 0.0,\n        'solar': 40.5,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 284.4,\n        'oil': 0.0,\n        'solar': 44.5,\n        'unknown': 17.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 289.3,\n        'oil': 0.0,\n        'solar': 39.7,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n    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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 310.1,\n        'oil': 0.0,\n        'solar': 29.5,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.5,\n        'coal': 0.0,\n        'gas': 318.0,\n        'oil': 0.0,\n        'solar': 25.5,\n        'unknown': 16.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 17, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 316.9,\n        'oil': 0.0,\n        'solar': 27.9,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 319.6,\n        'oil': 0.0,\n        'solar': 25.6,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 330.3,\n        'oil': 0.0,\n        'solar': 20.1,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 335.1,\n        'oil': 0.0,\n        'solar': 14.8,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.4,\n        'coal': 0.0,\n        'gas': 339.9,\n        'oil': 0.0,\n        'solar': 11.3,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 356.4,\n        'oil': 0.0,\n        'solar': 9.0,\n        'unknown': 16.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 364.0,\n        'oil': 0.0,\n        'solar': 6.8,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 370.5,\n        'oil': 0.0,\n        'solar': 4.6,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 376.9,\n        'oil': 0.0,\n        'solar': 3.4,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 381.2,\n        'oil': 0.0,\n        'solar': 2.5,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 385.2,\n        'oil': 0.0,\n        'solar': 1.8,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 387.9,\n        'oil': 0.0,\n        'solar': 0.8,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 18, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 392.3,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 402.2,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 404.9,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 405.6,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 407.1,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 410.1,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 416.3,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 423.9,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 427.5,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 427.3,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.3,\n        'coal': 0.0,\n        'gas': 430.0,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 19, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 429.7,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': 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'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 409.3,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 402.1,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.4,\n        'coal': 0.0,\n        'gas': 395.6,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 389.2,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 384.5,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.0,\n        'coal': 0.0,\n        'gas': 377.3,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 349.4,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 341.6,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 342.9,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 333.7,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 330.9,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 325.7,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 320.1,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 308.3,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 305.0,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 299.2,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 296.2,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 311.9,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.0,\n        'coal': 0.0,\n        'gas': 335.7,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 353.7,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 369.1,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 0.0,\n        'gas': 382.5,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 395.3,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.5,\n        'coal': 0.0,\n        'gas': 404.3,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.8,\n        'coal': 0.0,\n        'gas': 399.8,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 393.9,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 390.7,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 382.9,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.6,\n        'coal': 0.0,\n        'gas': 375.7,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.9,\n        'coal': 0.0,\n        'gas': 370.6,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 18.0,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.4,\n        'coal': 0.0,\n        'gas': 369.9,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 17.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 367.1,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.0,\n        'coal': 0.0,\n        'gas': 370.8,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 0.0,\n        'gas': 375.8,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 379.7,\n        'oil': 0.0,\n        'solar': 0.4,\n        'unknown': 16.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.5,\n        'coal': 0.0,\n        'gas': 386.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 384.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 383.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 382.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 381.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 380.3,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 378.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 376.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 372.4,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.3,\n        'coal': 0.0,\n        'gas': 367.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 362.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 13.9,\n        'coal': 0.0,\n        'gas': 359.4,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.3,\n        'coal': 0.0,\n        'gas': 359.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 354.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 351.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.5,\n        'coal': 0.0,\n        'gas': 348.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 345.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 342.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.1,\n        'coal': 0.0,\n        'gas': 340.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n 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'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.7,\n        'coal': 0.0,\n        'gas': 332.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 15.1,\n        'coal': 0.0,\n        'gas': 330.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.3,\n        'coal': 0.0,\n        'gas': 328.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 324.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 321.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 319.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.5,\n        'coal': 0.0,\n        'gas': 316.2,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 312.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 312.1,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 311.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 14.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 308.8,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 14.9,\n        'coal': 0.0,\n        'gas': 305.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.6,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 14.7,\n        'coal': 0.0,\n        'gas': 303.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 14.8,\n        'coal': 0.0,\n        'gas': 300.5,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 14.6,\n        'coal': 0.0,\n        'gas': 299.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.7,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 14.2,\n        'coal': 0.0,\n        'gas': 298.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 294.0,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.2,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 15.2,\n        'coal': 0.0,\n        'gas': 290.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 17.3,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 14.4,\n        'coal': 0.0,\n        'gas': 291.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.5,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 13.7,\n        'coal': 0.0,\n        'gas': 291.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.8,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 0.0,\n        'gas': 290.9,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 15.9,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'biomass': 14.0,\n        'coal': 0.0,\n        'gas': 288.8,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.1,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'biomass': 14.3,\n        'coal': 0.0,\n        'gas': 288.7,\n        'oil': 0.0,\n        'solar': 0.0,\n        'unknown': 16.4,\n        'wind': 0.0,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'ES-IB-MA',\n    }),\n  ])\n# ---\n# name: test_es_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 448,\n        'gas': 6424,\n        'hydro': 6375,\n        'nuclear': 6066,\n        'solar': 56,\n        'unknown': 4992,\n        'wind': 4485,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2299,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 436,\n        'gas': 6322,\n        'hydro': 6256,\n        'nuclear': 6064,\n        'solar': 55,\n        'unknown': 4922,\n        'wind': 4390,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2265,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 6124,\n        'hydro': 6207,\n        'nuclear': 6066,\n        'solar': 55,\n        'unknown': 4847,\n        'wind': 4392,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2347,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5911,\n        'hydro': 6163,\n        'nuclear': 6066,\n        'solar': 54,\n        'unknown': 4797,\n        'wind': 4552,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3,\n        'hydro': -2316,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5955,\n        'hydro': 6220,\n        'nuclear': 6066,\n        'solar': 54,\n        'unknown': 2203,\n        'wind': 4548,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -6,\n        'hydro': -2315,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5975,\n        'hydro': 6116,\n        'nuclear': 6067,\n        'solar': 55,\n        'unknown': 2206,\n        'wind': 4477,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -6,\n        'hydro': -2262,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5899,\n        'hydro': 6105,\n        'nuclear': 6062,\n        'solar': 54,\n        'unknown': 2193,\n        'wind': 4408,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2267,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5841,\n        'hydro': 6090,\n        'nuclear': 6062,\n        'solar': 54,\n        'unknown': 2169,\n        'wind': 4419,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2248,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5764,\n        'hydro': 6052,\n        'nuclear': 6065,\n        'solar': 54,\n        'unknown': 2206,\n        'wind': 4474,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2132,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 427,\n        'gas': 5606,\n        'hydro': 5849,\n        'nuclear': 6068,\n        'solar': 54,\n        'unknown': 2210,\n        'wind': 4469,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -1970,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 428,\n        'gas': 5458,\n        'hydro': 5793,\n        'nuclear': 6063,\n        'solar': 54,\n        'unknown': 2197,\n        'wind': 4456,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -6,\n        'hydro': -1940,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 428,\n        'gas': 5266,\n        'hydro': 5608,\n        'nuclear': 6066,\n        'solar': 54,\n        'unknown': 2162,\n        'wind': 4441,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3,\n        'hydro': -1875,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 428,\n        'gas': 5257,\n        'hydro': 5680,\n        'nuclear': 6065,\n        'solar': 54,\n        'unknown': 2197,\n        'wind': 4300,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -1910,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 428,\n        'gas': 5548,\n        'hydro': 5925,\n        'nuclear': 6062,\n        'solar': 54,\n        'unknown': 2186,\n        'wind': 4327,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2070,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5789,\n        'hydro': 5926,\n        'nuclear': 6066,\n        'solar': 54,\n        'unknown': 2183,\n        'wind': 4371,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2069,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5807,\n        'hydro': 5910,\n        'nuclear': 6060,\n        'solar': 54,\n        'unknown': 2181,\n        'wind': 4364,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2077,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5508,\n        'hydro': 5944,\n        'nuclear': 6065,\n        'solar': 54,\n        'unknown': 2148,\n        'wind': 4353,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2103,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5371,\n        'hydro': 5933,\n        'nuclear': 6063,\n        'solar': 54,\n        'unknown': 2153,\n        'wind': 4346,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2075,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5249,\n        'hydro': 5874,\n        'nuclear': 6062,\n        'solar': 54,\n        'unknown': 2151,\n        'wind': 4316,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -2073,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5196,\n        'hydro': 5855,\n        'nuclear': 6065,\n        'solar': 54,\n        'unknown': 2153,\n        'wind': 4303,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3,\n        'hydro': -2047,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5152,\n        'hydro': 5732,\n        'nuclear': 6066,\n        'solar': 54,\n        'unknown': 2089,\n        'wind': 4274,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -1997,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5142,\n        'hydro': 5710,\n        'nuclear': 6066,\n        'solar': 54,\n        'unknown': 2137,\n        'wind': 4260,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1972,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5109,\n        'hydro': 5623,\n        'nuclear': 6069,\n        'solar': 54,\n        'unknown': 2133,\n        'wind': 4209,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1922,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5063,\n        'hydro': 5410,\n        'nuclear': 6068,\n        'solar': 54,\n        'unknown': 2135,\n        'wind': 4356,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1711,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 429,\n        'gas': 5048,\n        'hydro': 5512,\n        'nuclear': 6071,\n        'solar': 54,\n        'unknown': 2130,\n        'wind': 4504,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -1793,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 430,\n        'gas': 5076,\n        'hydro': 5647,\n        'nuclear': 6067,\n        'solar': 54,\n        'unknown': 2107,\n        'wind': 4551,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -1870,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 432,\n        'gas': 5071,\n        'hydro': 5734,\n        'nuclear': 6068,\n        'solar': 54,\n        'unknown': 2098,\n        'wind': 4543,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -1900,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 430,\n        'gas': 5083,\n        'hydro': 5731,\n        'nuclear': 6065,\n        'solar': 54,\n        'unknown': 2099,\n        'wind': 4528,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -1854,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 431,\n        'gas': 4874,\n        'hydro': 5736,\n        'nuclear': 6063,\n        'solar': 53,\n        'unknown': 2059,\n        'wind': 4637,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -1870,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 25, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 435,\n        'gas': 4680,\n        'hydro': 5682,\n        'nuclear': 6065,\n        'solar': 52,\n        'unknown': 2096,\n        'wind': 4648,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': 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dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3164,\n        'hydro': 4487,\n        'nuclear': 6070,\n        'solar': 36,\n        'unknown': 3952,\n        'wind': 4578,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1003,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3157,\n        'hydro': 4456,\n        'nuclear': 6073,\n        'solar': 39,\n        'unknown': 3969,\n        'wind': 4615,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': 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   }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 3092,\n        'hydro': 3825,\n        'nuclear': 6073,\n        'solar': 40,\n        'unknown': 1858,\n        'wind': 4955,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -790,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 3103,\n        'hydro': 3857,\n        'nuclear': 6071,\n        'solar': 40,\n        'unknown': 1832,\n        'wind': 4992,\n      }),\n      'source': 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dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 3119,\n        'hydro': 4567,\n        'nuclear': 6072,\n        'solar': 2763,\n        'unknown': 1889,\n        'wind': 6138,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -815,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 248,\n        'gas': 3068,\n        'hydro': 4532,\n        'nuclear': 6069,\n        'solar': 3168,\n        'unknown': 1890,\n        'wind': 6028,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': 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    'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -707,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1156,\n        'hydro': 3568,\n        'nuclear': 6070,\n        'solar': 10773,\n        'unknown': 1664,\n        'wind': 6082,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -699,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1090,\n        'hydro': 3614,\n        'nuclear': 6070,\n        'solar': 10930,\n        'unknown': 1660,\n        'wind': 6135,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -702,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1162,\n        'hydro': 3634,\n        'nuclear': 6070,\n        'solar': 10940,\n        'unknown': 1622,\n        'wind': 6072,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -703,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1205,\n        'hydro': 3667,\n        'nuclear': 6072,\n        'solar': 11032,\n        'unknown': 1651,\n        'wind': 6051,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -701,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1230,\n        'hydro': 3711,\n        'nuclear': 6068,\n        'solar': 10817,\n        'unknown': 1651,\n        'wind': 5979,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -701,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1279,\n        'hydro': 3712,\n        'nuclear': 6076,\n        'solar': 11090,\n        'unknown': 1651,\n        'wind': 5932,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -698,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 12, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1309,\n        'hydro': 3665,\n        'nuclear': 6071,\n      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    'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3,\n        'hydro': -700,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1407,\n        'hydro': 3542,\n        'nuclear': 6071,\n        'solar': 10998,\n        'unknown': 3431,\n        'wind': 5980,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -702,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1395,\n        'hydro': 3515,\n        'nuclear': 6068,\n        'solar': 10939,\n        'unknown': 3430,\n        'wind': 6021,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -701,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1406,\n        'hydro': 3517,\n        'nuclear': 6071,\n        'solar': 10925,\n        'unknown': 3433,\n        'wind': 6152,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6,\n        'hydro': -704,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1441,\n        'hydro': 3535,\n        'nuclear': 6065,\n        'solar': 10676,\n        'unknown': 3392,\n        'wind': 6101,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3,\n        'hydro': -700,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1432,\n        'hydro': 3497,\n        'nuclear': 6076,\n        'solar': 10629,\n        'unknown': 3430,\n        'wind': 6167,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3,\n        'hydro': -697,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1461,\n        'hydro': 3454,\n        'nuclear': 6077,\n        'solar': 10332,\n        'unknown': 3433,\n        'wind': 6271,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 7,\n        'hydro': -699,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1478,\n        'hydro': 3511,\n        'nuclear': 6069,\n      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tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1509,\n        'hydro': 3512,\n        'nuclear': 6071,\n        'solar': 10249,\n        'unknown': 3423,\n        'wind': 6251,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3,\n        'hydro': -719,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 13, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1479,\n        'hydro': 3502,\n        'nuclear': 6077,\n        'solar': 9835,\n        'unknown': 3428,\n        'wind': 6218,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3,\n        'hydro': -719,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1479,\n        'hydro': 3504,\n        'nuclear': 6075,\n        'solar': 9983,\n        'unknown': 3431,\n        'wind': 6268,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 4,\n        'hydro': -716,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1505,\n        'hydro': 3467,\n        'nuclear': 6073,\n        'solar': 10150,\n        'unknown': 3408,\n        'wind': 6245,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6,\n        'hydro': -715,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1513,\n        'hydro': 3408,\n        'nuclear': 6073,\n        'solar': 9988,\n        'unknown': 3372,\n        'wind': 6310,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 5,\n        'hydro': -720,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 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   ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1590,\n        'hydro': 3471,\n        'nuclear': 6068,\n        'solar': 9646,\n        'unknown': 3408,\n        'wind': 6328,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3,\n        'hydro': -644,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1583,\n        'hydro': 3483,\n        'nuclear': 6072,\n        'solar': 9458,\n        'unknown': 3404,\n        'wind': 6339,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    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       'unknown': 3404,\n        'wind': 6441,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6,\n        'hydro': -644,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1660,\n        'hydro': 3316,\n        'nuclear': 6068,\n        'solar': 9285,\n        'unknown': 3399,\n        'wind': 6568,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6,\n        'hydro': -633,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1685,\n        'hydro': 3320,\n        'nuclear': 6070,\n        'solar': 8993,\n        'unknown': 3362,\n        'wind': 6616,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6,\n        'hydro': -645,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 14, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 1719,\n        'hydro': 3335,\n        'nuclear': 6074,\n        'solar': 8777,\n        'unknown': 3399,\n        'wind': 6592,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 5,\n        'hydro': 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 'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -6,\n        'hydro': -1678,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 4553,\n        'hydro': 5397,\n        'nuclear': 6067,\n        'solar': 47,\n        'unknown': 4067,\n        'wind': 4471,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4,\n        'hydro': -1641,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 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   'unknown': 4072,\n        'wind': 4263,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -1668,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 3752,\n        'hydro': 5042,\n        'nuclear': 6078,\n        'solar': 46,\n        'unknown': 1949,\n        'wind': 4140,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1684,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 22, 50, 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 'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -1798,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 4234,\n        'hydro': 5295,\n        'nuclear': 6072,\n        'solar': 46,\n        'unknown': 1936,\n        'wind': 3620,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1594,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 4241,\n        'hydro': 5260,\n        'nuclear': 6067,\n        'solar': 46,\n        'unknown': 4013,\n        'wind': 3575,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -1556,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 4084,\n        'hydro': 5049,\n        'nuclear': 6074,\n        'solar': 46,\n        'unknown': 4017,\n        'wind': 3573,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -1580,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 4056,\n        'hydro': 4972,\n        'nuclear': 6069,\n        'solar': 46,\n        'unknown': 4049,\n        'wind': 3521,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -1635,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 4019,\n        'hydro': 4953,\n        'nuclear': 6068,\n        'solar': 46,\n        'unknown': 4052,\n        'wind': 3449,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      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     'unknown': 4050,\n        'wind': 3376,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1618,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 248,\n        'gas': 3852,\n        'hydro': 4879,\n        'nuclear': 6072,\n        'solar': 46,\n        'unknown': 4052,\n        'wind': 3323,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -1602,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 248,\n        'gas': 3775,\n        'hydro': 4785,\n        'nuclear': 6071,\n        'solar': 46,\n        'unknown': 4055,\n        'wind': 3259,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -1611,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 26, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3716,\n        'hydro': 4759,\n        'nuclear': 6071,\n        'solar': 46,\n        'unknown': 4061,\n        'wind': 3219,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': 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'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1274,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 248,\n        'gas': 3694,\n        'hydro': 4149,\n        'nuclear': 6074,\n        'solar': 44,\n        'unknown': 1993,\n        'wind': 3018,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1210,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 248,\n        'gas': 3506,\n        'hydro': 4040,\n        'nuclear': 6070,\n        'solar': 44,\n        'unknown': 1997,\n        'wind': 2953,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -1176,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3469,\n        'hydro': 4036,\n        'nuclear': 6070,\n        'solar': 44,\n        'unknown': 2007,\n        'wind': 2915,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -1179,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3425,\n        'hydro': 4007,\n        'nuclear': 6071,\n        'solar': 44,\n        'unknown': 2013,\n        'wind': 2879,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -1148,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3360,\n        'hydro': 3909,\n        'nuclear': 6076,\n        'solar': 44,\n        'unknown': 2015,\n        'wind': 2850,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -1106,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3499,\n        'hydro': 3967,\n        'nuclear': 6073,\n        'solar': 44,\n        'unknown': 2017,\n        'wind': 2826,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -782,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3475,\n        'hydro': 3954,\n        'nuclear': 6071,\n        'solar': 44,\n        'unknown': 1980,\n        'wind': 2812,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -781,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3379,\n        'hydro': 3911,\n        'nuclear': 6070,\n        'solar': 44,\n        'unknown': 2025,\n        'wind': 2799,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -779,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3493,\n        'hydro': 3917,\n        'nuclear': 6070,\n        'solar': 44,\n        'unknown': 2026,\n        'wind': 2766,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -773,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3561,\n        'hydro': 3874,\n        'nuclear': 6072,\n        'solar': 44,\n        'unknown': 2027,\n        'wind': 2750,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -759,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 247,\n        'gas': 3613,\n        'hydro': 3933,\n        'nuclear': 6074,\n        'solar': 44,\n        'unknown': 1994,\n        'wind': 2721,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -763,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3732,\n        'hydro': 4095,\n        'nuclear': 6071,\n        'solar': 44,\n        'unknown': 1989,\n        'wind': 2680,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -777,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 249,\n        'gas': 3775,\n        'hydro': 4173,\n        'nuclear': 6076,\n        'solar': 44,\n        'unknown': 4281,\n        'wind': 2663,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -792,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3732,\n        'hydro': 4132,\n        'nuclear': 6072,\n        'solar': 44,\n        'unknown': 2008,\n        'wind': 2605,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -810,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3714,\n        'hydro': 4144,\n        'nuclear': 6069,\n        'solar': 44,\n        'unknown': 4268,\n        'wind': 2610,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -778,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3696,\n        'hydro': 4151,\n        'nuclear': 6071,\n        'solar': 44,\n        'unknown': 4268,\n        'wind': 2578,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -785,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3661,\n        'hydro': 4142,\n        'nuclear': 6076,\n        'solar': 44,\n        'unknown': 4273,\n        'wind': 2555,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -782,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3606,\n        'hydro': 4135,\n        'nuclear': 6071,\n        'solar': 44,\n        'unknown': 2020,\n        'wind': 2526,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -784,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 250,\n        'gas': 3485,\n        'hydro': 4098,\n        'nuclear': 6074,\n        'solar': 44,\n        'unknown': 2022,\n        'wind': 2497,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -778,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 248,\n        'gas': 3476,\n        'hydro': 4118,\n        'nuclear': 6071,\n        'solar': 44,\n        'unknown': 2022,\n        'wind': 2467,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -775,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 248,\n        'gas': 3467,\n        'hydro': 4028,\n        'nuclear': 6075,\n        'solar': 44,\n        'unknown': 2022,\n        'wind': 2478,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -765,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'production': dict({\n        'coal': 246,\n        'gas': 3488,\n        'hydro': 4004,\n        'nuclear': 6071,\n        'solar': 45,\n        'unknown': 2019,\n        'wind': 2488,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -767,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 247,\n        'gas': 3348,\n        'hydro': 3930,\n        'nuclear': 6075,\n        'solar': 44,\n        'unknown': 2017,\n        'wind': 2507,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -765,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 249,\n        'gas': 3334,\n        'hydro': 3852,\n        'nuclear': 6071,\n        'solar': 44,\n        'unknown': 2025,\n        'wind': 2500,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -765,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 247,\n        'gas': 3320,\n        'hydro': 3758,\n        'nuclear': 6073,\n        'solar': 44,\n        'unknown': 4295,\n        'wind': 2480,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -766,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 249,\n        'gas': 3312,\n        'hydro': 3747,\n        'nuclear': 6074,\n        'solar': 44,\n        'unknown': 4294,\n        'wind': 2468,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -762,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 248,\n        'gas': 3306,\n        'hydro': 3701,\n        'nuclear': 6071,\n        'solar': 44,\n        'unknown': 4296,\n        'wind': 2476,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -653,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 248,\n        'gas': 3289,\n        'hydro': 3679,\n        'nuclear': 6072,\n        'solar': 44,\n        'unknown': 2023,\n        'wind': 2479,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -650,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 247,\n        'gas': 3199,\n        'hydro': 3595,\n        'nuclear': 6070,\n        'solar': 44,\n        'unknown': 1987,\n        'wind': 2385,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -655,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 249,\n        'gas': 3204,\n        'hydro': 3562,\n        'nuclear': 6072,\n        'solar': 44,\n        'unknown': 2024,\n        'wind': 2442,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -652,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 247,\n        'gas': 3262,\n        'hydro': 3618,\n        'nuclear': 6071,\n        'solar': 44,\n        'unknown': 2025,\n        'wind': 2440,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -653,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 249,\n        'gas': 3244,\n        'hydro': 3444,\n        'nuclear': 6073,\n        'solar': 44,\n        'unknown': 2025,\n        'wind': 2466,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0,\n        'hydro': -650,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 248,\n        'gas': 3192,\n        'hydro': 3427,\n        'nuclear': 6067,\n        'solar': 44,\n        'unknown': 1991,\n        'wind': 2491,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -656,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'production': dict({\n        'coal': 248,\n        'gas': 3021,\n        'hydro': 3253,\n        'nuclear': 6069,\n        'solar': 44,\n        'unknown': 2029,\n        'wind': 2539,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1,\n        'hydro': -655,\n      }),\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'production': dict({\n        'coal': 252,\n        'gas': 3025,\n        'hydro': 3273,\n        'nuclear': 6074,\n        'solar': 43,\n        'unknown': 2027,\n        'wind': 2568,\n      }),\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1,\n        'hydro': -649,\n      }),\n      'zoneKey': 'ES',\n    }),\n  ])\n# ---\n# name: test_es_pt_exchange\n  list([\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -586.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -523.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -416.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -450.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -532.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -653.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -507.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -483.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -458.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -364.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -418.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -454.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -527.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -657.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -731.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -588.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -612.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 25, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -528.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': 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datetime.datetime(2024, 10, 26, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -1.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -76.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -100.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -109.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -82.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -178.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -80.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -185.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -215.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -300.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -198.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -263.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -224.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -198.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -55.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -248.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -150.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -178.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 26, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -195.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -245.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -441.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -262.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -449.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -431.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -416.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -382.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -458.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -432.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -476.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -426.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -523.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -444.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -251.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -204.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -193.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -138.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -150.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -128.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -149.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -200.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -151.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -151.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Europe/Madrid')),\n      'netFlow': -182.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 218.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 973.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 942.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 909.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 902.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 1017.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 1075.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 1015.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 1023.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 970.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 862.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=7200))),\n      'netFlow': 911.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 10, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=3600))),\n      'netFlow': 1031.0,\n      'sortedZoneKeys': 'ES->PT',\n      'source': 'demanda.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ESIOS.ambr",
    "content": "# serializer version: 1\n# name: test_exchange_with_snapshot\n  list([\n    dict({\n      'datetime': datetime.datetime(2017, 9, 3, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 798.8,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 3, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 885.77,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 3, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 831.96,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 3, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 864.34,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 3, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 818.91,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 3, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 754.92,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 677.24,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 556.32,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 427.75,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 468.63,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 525.34,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 579.95,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 588.74,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 707.18,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 733.78,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 867.64,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 748.9,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 742.29,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 814.46,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 768.23,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 752.18,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 789.92,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 775.27,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2017, 9, 4, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 835.21,\n      'sortedZoneKeys': 'ES->MA',\n      'source': 'api.esios.ree.es',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ESKOM.ambr",
    "content": "# serializer version: 1\n# name: test_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.535,\n        'coal': 14487.159,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 913.039,\n        'oil': 1627.623,\n        'solar': 0.0,\n        'wind': 1773.955,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2430.832,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.602,\n        'coal': 14231.943,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 913.092,\n        'oil': 672.435,\n        'solar': 0.0,\n        'wind': 1801.865,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2587.716,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.668,\n        'coal': 14354.055,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 913.209,\n        'oil': 626.846,\n        'solar': 0.0,\n        'wind': 1702.886,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2614.532,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.899,\n        'coal': 14436.056,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 913.53,\n        'oil': 624.065,\n        'solar': 0.0,\n        'wind': 1661.14,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2681.164,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.961,\n        'coal': 15399.591,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.828,\n        'oil': 1241.302,\n        'solar': 0.0,\n        'wind': 1639.818,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1983.492,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.023,\n        'coal': 17525.653,\n        'gas': 0.0,\n        'hydro': 4.004,\n        'nuclear': 911.88,\n        'oil': 1615.203,\n        'solar': 0.0,\n        'wind': 1503.038,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -83.038,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.767,\n        'coal': 17923.763,\n        'gas': 0.0,\n        'hydro': 243.004,\n        'nuclear': 912.307,\n        'oil': 1506.3,\n        'solar': 18.408,\n        'wind': 1630.611,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1891.706,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.724,\n        'coal': 18112.266,\n        'gas': 0.0,\n        'hydro': 488.616,\n        'nuclear': 912.486,\n        'oil': 1480.902,\n        'solar': 436.537,\n        'wind': 1620.955,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -441.201,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.886,\n        'coal': 18188.291,\n        'gas': 0.0,\n        'hydro': 212.545,\n        'nuclear': 912.502,\n        'oil': 1520.533,\n        'solar': 1010.172,\n        'wind': 1647.22,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -104.013,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.93,\n        'coal': 18128.402,\n        'gas': 0.0,\n        'hydro': 123.216,\n        'nuclear': 912.517,\n        'oil': 1166.889,\n        'solar': 1399.342,\n        'wind': 1758.582,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 38.863,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.332,\n        'coal': 17748.255,\n        'gas': 0.0,\n        'hydro': 22.004,\n        'nuclear': 912.672,\n        'oil': 886.735,\n        'solar': 1497.267,\n        'wind': 1910.863,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -987.356,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.788,\n        'coal': 17492.406,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.451,\n        'oil': 908.283,\n        'solar': 1652.185,\n        'wind': 2144.018,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -547.917,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.796,\n        'coal': 17337.569,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.48,\n        'oil': 799.242,\n        'solar': 1664.886,\n        'wind': 2371.257,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -72.375,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.86,\n        'coal': 17367.756,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.903,\n        'oil': 608.771,\n        'solar': 1560.735,\n        'wind': 2365.475,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -116.28,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.69,\n        'coal': 16786.084,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.055,\n        'oil': 612.745,\n        'solar': 1598.234,\n        'wind': 2297.922,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1020.665,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.657,\n        'coal': 16304.325,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.878,\n        'oil': 988.468,\n        'solar': 1582.616,\n        'wind': 2196.675,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2092.799,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.954,\n        'coal': 16336.383,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.543,\n        'oil': 2102.811,\n        'solar': 1357.995,\n        'wind': 2206.165,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1773.685,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.902,\n        'coal': 16499.066,\n        'gas': 135.31,\n        'hydro': 40.003,\n        'nuclear': 911.776,\n        'oil': 2735.936,\n        'solar': 774.198,\n        'wind': 2052.639,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2173.446,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.481,\n        'coal': 16904.072,\n        'gas': 327.517,\n        'hydro': 497.002,\n        'nuclear': 911.748,\n        'oil': 2719.142,\n        'solar': 356.413,\n        'wind': 1960.581,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2616.556,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.681,\n        'coal': 16994.121,\n        'gas': 328.345,\n        'hydro': 378.102,\n        'nuclear': 911.868,\n        'oil': 2700.807,\n        'solar': 219.222,\n        'wind': 1717.639,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2442.657,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.712,\n        'coal': 17140.437,\n        'gas': 95.007,\n        'hydro': 0.003,\n        'nuclear': 911.995,\n        'oil': 2728.692,\n        'solar': 100.0,\n        'wind': 1613.974,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1472.34,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.682,\n        'coal': 16475.758,\n        'gas': 0.0,\n        'hydro': 0.003,\n        'nuclear': 911.857,\n        'oil': 2724.46,\n        'solar': 100.0,\n        'wind': 1504.039,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 492.212,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.712,\n        'coal': 15568.751,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.127,\n        'oil': 2222.609,\n        'solar': 50.0,\n        'wind': 1360.843,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1517.901,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 11, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.906,\n        'coal': 15110.876,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.414,\n        'oil': 1937.072,\n        'solar': 0.0,\n        'wind': 1159.742,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2054.135,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.204,\n        'coal': 14860.657,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.26,\n        'oil': 1803.745,\n        'solar': 0.0,\n        'wind': 1005.752,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2326.169,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.249,\n        'coal': 14673.783,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.679,\n        'oil': 1563.586,\n        'solar': 0.0,\n        'wind': 1042.965,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2752.433,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.084,\n        'coal': 15097.239,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.071,\n        'oil': 1143.775,\n        'solar': 0.0,\n        'wind': 1027.239,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2221.332,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.869,\n        'coal': 15131.653,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.084,\n        'oil': 1168.859,\n        'solar': 0.0,\n        'wind': 1005.952,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2537.0,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.912,\n        'coal': 16554.638,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.074,\n        'oil': 1154.028,\n        'solar': 0.0,\n        'wind': 1017.813,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1259.721,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.145,\n        'coal': 17710.869,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.399,\n        'oil': 1251.501,\n        'solar': 0.0,\n        'wind': 1183.965,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1510.794,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.815,\n        'coal': 17687.172,\n        'gas': 0.0,\n        'hydro': 236.003,\n        'nuclear': 911.544,\n        'oil': 1858.128,\n        'solar': 38.161,\n        'wind': 1342.879,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2487.57,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.857,\n        'coal': 17811.809,\n        'gas': 0.0,\n        'hydro': 493.945,\n        'nuclear': 911.169,\n        'oil': 1963.043,\n        'solar': 646.256,\n        'wind': 1277.276,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1499.0,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.038,\n        'coal': 17838.704,\n        'gas': 0.0,\n        'hydro': 219.277,\n        'nuclear': 911.163,\n        'oil': 1990.274,\n        'solar': 1488.867,\n        'wind': 1059.567,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -916.123,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.411,\n        'coal': 17864.873,\n        'gas': 0.0,\n        'hydro': 116.183,\n        'nuclear': 909.772,\n        'oil': 1927.014,\n        'solar': 1988.32,\n        'wind': 1052.392,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -478.502,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.796,\n        'coal': 17882.139,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 909.282,\n        'oil': 1244.517,\n        'solar': 2161.106,\n        'wind': 1093.857,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -391.647,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.559,\n        'coal': 17675.814,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.931,\n        'oil': 1169.026,\n        'solar': 2183.787,\n        'wind': 1003.055,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -530.606,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.813,\n        'coal': 17565.959,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.136,\n        'oil': 1194.46,\n        'solar': 2170.815,\n        'wind': 828.316,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -732.257,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.707,\n        'coal': 17459.714,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.929,\n        'oil': 1190.961,\n        'solar': 2165.221,\n        'wind': 721.175,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -620.302,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.723,\n        'coal': 17616.844,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.989,\n        'oil': 1190.762,\n        'solar': 2159.39,\n        'wind': 702.066,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -436.202,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.705,\n        'coal': 17668.651,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.706,\n        'oil': 1383.711,\n        'solar': 2066.944,\n        'wind': 745.115,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -963.382,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.983,\n        'coal': 17737.191,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.721,\n        'oil': 1715.943,\n        'solar': 1687.253,\n        'wind': 837.591,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -762.662,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.917,\n        'coal': 18014.672,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.836,\n        'oil': 1996.599,\n        'solar': 870.041,\n        'wind': 941.606,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1737.472,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.275,\n        'coal': 18249.954,\n        'gas': 0.0,\n        'hydro': 458.213,\n        'nuclear': 910.576,\n        'oil': 2542.479,\n        'solar': 379.788,\n        'wind': 1241.682,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1403.61,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.339,\n        'coal': 18301.757,\n        'gas': 0.0,\n        'hydro': 420.523,\n        'nuclear': 910.576,\n        'oil': 2516.418,\n        'solar': 351.01,\n        'wind': 1549.879,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -434.828,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.319,\n        'coal': 17914.454,\n        'gas': 0.0,\n        'hydro': 46.004,\n        'nuclear': 910.283,\n        'oil': 2431.561,\n        'solar': 342.551,\n        'wind': 1560.726,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 204.505,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.326,\n        'coal': 16085.443,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.105,\n        'oil': 2374.535,\n        'solar': 326.466,\n        'wind': 1501.79,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1969.591,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.363,\n        'coal': 15555.347,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.869,\n        'oil': 2309.421,\n        'solar': 89.942,\n        'wind': 1479.394,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2450.97,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 12, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.383,\n        'coal': 15172.027,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.164,\n        'oil': 1535.403,\n        'solar': 39.891,\n        'wind': 1507.718,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2775.884,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.372,\n        'coal': 15176.669,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.163,\n        'oil': 1068.252,\n        'solar': 39.83,\n        'wind': 1490.433,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2780.857,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.193,\n        'coal': 15309.956,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.639,\n        'oil': 568.897,\n        'solar': 39.763,\n        'wind': 1372.542,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2758.531,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.303,\n        'coal': 15437.735,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.322,\n        'oil': 287.666,\n        'solar': 39.774,\n        'wind': 1437.939,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2709.805,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.262,\n        'coal': 15875.269,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.829,\n        'oil': 0.675,\n        'solar': 39.793,\n        'wind': 1426.093,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2339.299,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.957,\n        'coal': 17470.17,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.856,\n        'oil': 5.296,\n        'solar': 20.26,\n        'wind': 1449.507,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1083.778,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.18,\n        'coal': 18460.216,\n        'gas': 0.0,\n        'hydro': 4.004,\n        'nuclear': 912.304,\n        'oil': 649.573,\n        'solar': 0.0,\n        'wind': 1507.858,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -785.17,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.207,\n        'coal': 18340.358,\n        'gas': 0.0,\n        'hydro': 243.004,\n        'nuclear': 912.262,\n        'oil': 756.105,\n        'solar': 23.929,\n        'wind': 1888.947,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -961.335,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.185,\n        'coal': 18178.856,\n        'gas': 0.0,\n        'hydro': 487.374,\n        'nuclear': 911.863,\n        'oil': 286.404,\n        'solar': 520.475,\n        'wind': 2052.527,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -329.103,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.196,\n        'coal': 18348.253,\n        'gas': 0.0,\n        'hydro': 212.086,\n        'nuclear': 912.037,\n        'oil': 0.0,\n        'solar': 1295.503,\n        'wind': 1900.928,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -543.736,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 13.986,\n        'coal': 18101.21,\n        'gas': 0.0,\n        'hydro': 123.808,\n        'nuclear': 911.751,\n        'oil': 0.0,\n        'solar': 1852.081,\n        'wind': 1863.092,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 61.74,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.627,\n        'coal': 17775.894,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.069,\n        'oil': 0.0,\n        'solar': 2052.126,\n        'wind': 1954.543,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 598.019,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.178,\n        'coal': 16760.894,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.618,\n        'oil': 0.0,\n        'solar': 2071.356,\n        'wind': 2147.501,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1218.616,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.004,\n        'coal': 16888.327,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 915.909,\n        'oil': 0.0,\n        'solar': 2049.097,\n        'wind': 2292.733,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 960.728,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.981,\n        'coal': 16397.378,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 916.511,\n        'oil': 0.0,\n        'solar': 2069.073,\n        'wind': 2333.597,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1383.586,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 13.962,\n        'coal': 16487.899,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 916.369,\n        'oil': 0.0,\n        'solar': 1984.752,\n        'wind': 2299.789,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1316.976,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.532,\n        'coal': 17244.343,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 916.256,\n        'oil': 0.0,\n        'solar': 1867.392,\n        'wind': 2295.946,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 556.126,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.83,\n        'coal': 17855.056,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 915.088,\n        'oil': 0.0,\n        'solar': 1501.354,\n        'wind': 2268.529,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -619.343,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.046,\n        'coal': 17838.575,\n        'gas': 0.0,\n        'hydro': 92.004,\n        'nuclear': 911.738,\n        'oil': 0.0,\n        'solar': 776.187,\n        'wind': 2258.799,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2101.334,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.089,\n        'coal': 17982.06,\n        'gas': 0.0,\n        'hydro': 536.597,\n        'nuclear': 911.095,\n        'oil': 0.0,\n        'solar': 375.463,\n        'wind': 2157.05,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2893.095,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.953,\n        'coal': 18134.697,\n        'gas': 0.0,\n        'hydro': 329.179,\n        'nuclear': 910.903,\n        'oil': 0.0,\n        'solar': 347.231,\n        'wind': 2008.076,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2295.606,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.962,\n        'coal': 18002.872,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.892,\n        'oil': 0.0,\n        'solar': 338.505,\n        'wind': 2101.354,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1750.013,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.703,\n        'coal': 17601.118,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.039,\n        'oil': 0.0,\n        'solar': 325.101,\n        'wind': 2126.596,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -14.991,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.191,\n        'coal': 16850.659,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.845,\n        'oil': 0.0,\n        'solar': 86.669,\n        'wind': 2238.389,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 805.323,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 13, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.323,\n        'coal': 15743.68,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.88,\n        'oil': 0.0,\n        'solar': 36.6,\n        'wind': 2194.124,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1966.358,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.31,\n        'coal': 15305.423,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.266,\n        'oil': 0.0,\n        'solar': 36.565,\n        'wind': 2278.174,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2495.971,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2740.009,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 32.283,\n        'coal': 15175.184,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.842,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 2113.479,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2617.384,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 38.009,\n        'coal': 16455.666,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.077,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 2242.217,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1743.279,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 39.011,\n        'coal': 18363.392,\n        'gas': 0.0,\n        'hydro': 12.004,\n        'nuclear': 911.417,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 2062.67,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -735.258,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 39.05,\n        'coal': 18541.7,\n        'gas': 0.0,\n        'hydro': 234.004,\n        'nuclear': 911.167,\n        'oil': 503.884,\n        'solar': 27.151,\n        'wind': 1785.363,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1697.604,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 39.081,\n        'coal': 18524.118,\n        'gas': 0.0,\n        'hydro': 490.633,\n        'nuclear': 911.061,\n        'oil': 425.907,\n        'solar': 527.374,\n        'wind': 1601.42,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -706.251,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 37.789,\n        'coal': 18601.263,\n        'gas': 0.0,\n        'hydro': 216.027,\n        'nuclear': 910.969,\n        'oil': 0.055,\n        'solar': 1324.703,\n        'wind': 1372.768,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -919.597,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 37.648,\n        'coal': 18589.592,\n        'gas': 0.0,\n        'hydro': 120.474,\n        'nuclear': 910.945,\n        'oil': 0.0,\n        'solar': 1867.052,\n        'wind': 1495.889,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 161.094,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 28.669,\n        'coal': 17969.672,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.58,\n        'oil': 0.0,\n        'solar': 2158.964,\n        'wind': 1638.929,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 897.082,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.742,\n        'coal': 17167.775,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.59,\n        'oil': 0.0,\n        'solar': 2241.634,\n        'wind': 1818.458,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1450.984,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.725,\n        'coal': 17174.739,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.554,\n        'oil': 0.0,\n        'solar': 2268.113,\n        'wind': 1985.113,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1386.782,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.34,\n        'coal': 16933.638,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.655,\n        'oil': 0.0,\n        'solar': 2224.893,\n        'wind': 1913.911,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1264.776,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 13.801,\n        'coal': 17033.444,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.542,\n        'oil': 0.0,\n        'solar': 2135.265,\n        'wind': 1805.72,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1178.685,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 13.8,\n        'coal': 17707.67,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.876,\n        'oil': 0.0,\n        'solar': 1970.086,\n        'wind': 1706.233,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 624.844,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 13.59,\n        'coal': 18335.622,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.844,\n        'oil': 0.0,\n        'solar': 1598.955,\n        'wind': 1675.398,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -423.352,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 13.638,\n        'coal': 18505.351,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.885,\n        'oil': 0.0,\n        'solar': 826.241,\n        'wind': 1519.395,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1734.533,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.537,\n        'coal': 18506.525,\n        'gas': 0.0,\n        'hydro': 501.703,\n        'nuclear': 911.318,\n        'oil': 0.0,\n        'solar': 381.488,\n        'wind': 1512.361,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2559.025,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.581,\n        'coal': 18482.875,\n        'gas': 0.0,\n        'hydro': 487.179,\n        'nuclear': 911.15,\n        'oil': 0.0,\n        'solar': 357.721,\n        'wind': 1525.991,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2008.678,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.27,\n        'coal': 18418.464,\n        'gas': 0.0,\n        'hydro': 20.004,\n        'nuclear': 911.413,\n        'oil': 0.0,\n        'solar': 350.061,\n        'wind': 1657.748,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1865.559,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 14.723,\n        'coal': 18089.856,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.123,\n        'oil': 41.4,\n        'solar': 333.628,\n        'wind': 1564.079,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -56.913,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 13.95,\n        'coal': 17487.196,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.64,\n        'oil': 46.4,\n        'solar': 89.256,\n        'wind': 1481.886,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 732.452,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 13.463,\n        'coal': 16436.021,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.626,\n        'oil': 0.0,\n        'solar': 38.585,\n        'wind': 1462.628,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1941.604,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.892,\n        'coal': 16161.578,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.635,\n        'oil': 0.0,\n        'solar': 38.678,\n        'wind': 1814.583,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1887.046,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 16.196,\n        'coal': 15331.948,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.733,\n        'oil': 0.0,\n        'solar': 38.52,\n        'wind': 1941.388,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2689.449,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 16.004,\n        'coal': 15202.563,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.979,\n        'oil': 0.0,\n        'solar': 38.581,\n        'wind': 1930.479,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2774.841,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 33.821,\n        'coal': 15449.089,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.9,\n        'oil': 0.0,\n        'solar': 38.845,\n        'wind': 2086.511,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2761.036,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 39.886,\n        'coal': 16558.105,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.356,\n        'oil': 0.0,\n        'solar': 38.813,\n        'wind': 2243.112,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2277.678,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 40.573,\n        'coal': 18493.692,\n        'gas': 0.0,\n        'hydro': 2.004,\n        'nuclear': 912.527,\n        'oil': 0.0,\n        'solar': 5.51,\n        'wind': 2426.389,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 750.494,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 40.489,\n        'coal': 19208.302,\n        'gas': 0.0,\n        'hydro': 239.004,\n        'nuclear': 911.934,\n        'oil': 0.0,\n        'solar': 51.17,\n        'wind': 2408.121,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -562.267,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 40.589,\n        'coal': 18859.361,\n        'gas': 0.0,\n        'hydro': 485.49,\n        'nuclear': 911.954,\n        'oil': 0.0,\n        'solar': 674.022,\n        'wind': 2329.687,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 234.126,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 39.941,\n        'coal': 19189.161,\n        'gas': 0.0,\n        'hydro': 219.263,\n        'nuclear': 911.771,\n        'oil': 0.0,\n        'solar': 1457.996,\n        'wind': 2162.82,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 54.137,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 39.827,\n        'coal': 18092.421,\n        'gas': 0.0,\n        'hydro': 123.388,\n        'nuclear': 911.491,\n        'oil': 0.0,\n        'solar': 1857.552,\n        'wind': 2317.628,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 964.84,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 29.999,\n        'coal': 17567.777,\n        'gas': 0.0,\n        'hydro': 2.004,\n        'nuclear': 911.739,\n        'oil': 0.0,\n        'solar': 2074.985,\n        'wind': 2500.634,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1465.201,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.362,\n        'coal': 17200.022,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.824,\n        'oil': 0.0,\n        'solar': 2120.222,\n        'wind': 2527.676,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1770.336,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.606,\n        'coal': 17266.279,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.691,\n        'oil': 0.0,\n        'solar': 2143.27,\n        'wind': 2622.988,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1651.093,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.666,\n        'coal': 16634.255,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.324,\n        'oil': 0.0,\n        'solar': 2078.522,\n        'wind': 2809.59,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1797.633,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.502,\n        'coal': 17157.189,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 910.911,\n        'oil': 0.0,\n        'solar': 1966.107,\n        'wind': 2785.079,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1174.096,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.441,\n        'coal': 17042.097,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.374,\n        'oil': 0.0,\n        'solar': 1812.511,\n        'wind': 2887.07,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1112.193,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.592,\n        'coal': 18037.438,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.418,\n        'oil': 0.0,\n        'solar': 1417.505,\n        'wind': 2888.105,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 75.278,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.588,\n        'coal': 18476.201,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.815,\n        'oil': 0.0,\n        'solar': 705.556,\n        'wind': 2958.54,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -681.381,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.638,\n        'coal': 18699.786,\n        'gas': 0.0,\n        'hydro': 353.472,\n        'nuclear': 912.083,\n        'oil': 0.0,\n        'solar': 274.833,\n        'wind': 2833.575,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1879.119,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.676,\n        'coal': 18745.702,\n        'gas': 0.0,\n        'hydro': 508.303,\n        'nuclear': 911.677,\n        'oil': 0.0,\n        'solar': 248.472,\n        'wind': 2454.63,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1166.062,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.66,\n        'coal': 18941.121,\n        'gas': 0.0,\n        'hydro': 274.252,\n        'nuclear': 911.521,\n        'oil': 0.0,\n        'solar': 239.359,\n        'wind': 2397.731,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1505.032,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.636,\n        'coal': 18704.597,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.554,\n        'oil': 0.0,\n        'solar': 230.64,\n        'wind': 2407.463,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -320.25,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.586,\n        'coal': 18024.109,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.435,\n        'oil': 0.0,\n        'solar': 89.49,\n        'wind': 2415.219,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 857.814,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.543,\n        'coal': 16735.131,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.845,\n        'oil': 0.0,\n        'solar': 38.978,\n        'wind': 2505.211,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2199.021,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.536,\n        'coal': 16126.908,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.677,\n        'oil': 0.0,\n        'solar': 38.995,\n        'wind': 2586.956,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2383.607,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.552,\n        'coal': 15676.344,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.994,\n        'oil': 0.0,\n        'solar': 38.955,\n        'wind': 2584.196,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2716.762,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.76,\n        'coal': 15965.595,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.235,\n        'oil': 0.0,\n        'solar': 38.241,\n        'wind': 2662.397,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2326.575,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 33.734,\n        'coal': 15841.17,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.333,\n        'oil': 0.0,\n        'solar': 38.015,\n        'wind': 2668.258,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2460.021,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 39.477,\n        'coal': 16519.489,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 912.26,\n        'oil': 0.0,\n        'solar': 26.724,\n        'wind': 2651.483,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2243.249,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 40.186,\n        'coal': 16883.615,\n        'gas': 0.0,\n        'hydro': 100.004,\n        'nuclear': 912.178,\n        'oil': 0.0,\n        'solar': 0.9,\n        'wind': 2609.699,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2052.732,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 40.456,\n        'coal': 18174.918,\n        'gas': 0.0,\n        'hydro': 240.003,\n        'nuclear': 912.202,\n        'oil': 0.0,\n        'solar': 45.928,\n        'wind': 2576.675,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 962.719,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 40.502,\n        'coal': 18929.041,\n        'gas': 0.0,\n        'hydro': 419.965,\n        'nuclear': 911.999,\n        'oil': 0.0,\n        'solar': 594.809,\n        'wind': 2551.452,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 320.537,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 39.706,\n        'coal': 19332.959,\n        'gas': 0.0,\n        'hydro': 249.648,\n        'nuclear': 911.911,\n        'oil': 0.0,\n        'solar': 1264.197,\n        'wind': 2622.736,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2.054,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 39.575,\n        'coal': 18468.08,\n        'gas': 0.0,\n        'hydro': 266.197,\n        'nuclear': 911.7,\n        'oil': 0.0,\n        'solar': 1726.175,\n        'wind': 2625.688,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -428.904,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 30.107,\n        'coal': 18338.591,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.427,\n        'oil': 0.0,\n        'solar': 2024.641,\n        'wind': 2557.363,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -315.493,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.608,\n        'coal': 18134.099,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.309,\n        'oil': 0.0,\n        'solar': 2258.17,\n        'wind': 2559.897,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1030.118,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.662,\n        'coal': 17961.997,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.442,\n        'oil': 0.0,\n        'solar': 2228.616,\n        'wind': 2596.398,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -906.358,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.68,\n        'coal': 17694.423,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 911.456,\n        'oil': 0.0,\n        'solar': 2170.868,\n        'wind': 2682.144,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -665.383,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.601,\n        'coal': 17442.099,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 908.79,\n        'oil': 0.0,\n        'solar': 2162.607,\n        'wind': 2655.68,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -787.127,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.824,\n        'coal': 17387.199,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 909.047,\n        'oil': 50.61,\n        'solar': 1984.309,\n        'wind': 2753.16,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -677.76,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.778,\n        'coal': 17826.078,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 909.05,\n        'oil': 0.435,\n        'solar': 1524.591,\n        'wind': 2722.301,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1206.807,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.74,\n        'coal': 18734.611,\n        'gas': 0.0,\n        'hydro': 227.734,\n        'nuclear': 909.288,\n        'oil': 0.0,\n        'solar': 803.457,\n        'wind': 2674.245,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1887.258,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.608,\n        'coal': 19057.29,\n        'gas': 0.0,\n        'hydro': 498.426,\n        'nuclear': 909.284,\n        'oil': 0.0,\n        'solar': 375.769,\n        'wind': 2449.761,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2697.448,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.621,\n        'coal': 18894.618,\n        'gas': 0.0,\n        'hydro': 424.184,\n        'nuclear': 908.878,\n        'oil': 0.0,\n        'solar': 346.094,\n        'wind': 2077.651,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2251.274,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.652,\n        'coal': 18819.52,\n        'gas': 0.0,\n        'hydro': 80.004,\n        'nuclear': 908.785,\n        'oil': 0.0,\n        'solar': 339.724,\n        'wind': 1958.464,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1822.087,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.695,\n        'coal': 18535.428,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 908.836,\n        'oil': 0.0,\n        'solar': 327.044,\n        'wind': 1594.049,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1020.936,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.857,\n        'coal': 18150.259,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 909.027,\n        'oil': 0.0,\n        'solar': 88.398,\n        'wind': 1441.719,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -385.722,\n      }),\n      'zoneKey': 'ZA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2023, 9, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Africa/Johannesburg')),\n      'production': dict({\n        'biomass': 15.567,\n        'coal': 17406.885,\n        'gas': 0.0,\n        'hydro': 0.004,\n        'nuclear': 908.971,\n        'oil': 0.0,\n        'solar': 37.592,\n        'wind': 1457.81,\n      }),\n      'source': 'eskom.co.za',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 618.916,\n      }),\n      'zoneKey': 'ZA',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ESTADISTICO_UT.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_historical\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 145.81,\n        'geothermal': 162.33,\n        'hydro': 160.81,\n        'unknown': 58.28,\n        'wind': 18.08,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 147.53,\n        'geothermal': 165.11,\n        'hydro': 129.55,\n        'unknown': 59.52,\n        'wind': 15.79,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 148.04,\n        'geothermal': 166.12,\n        'hydro': 97.36,\n        'unknown': 56.4,\n        'wind': 19.01,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 147.72,\n        'geothermal': 165.89,\n        'hydro': 72.36,\n        'unknown': 53.61,\n        'wind': 24.31,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 145.98,\n        'geothermal': 164.5,\n        'hydro': 70.62,\n        'unknown': 58.92,\n        'wind': 21.53,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 135.25,\n        'geothermal': 164.18,\n        'hydro': 88.02,\n        'unknown': 69.01,\n        'wind': 22.95,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 114.92,\n        'geothermal': 164.99,\n        'hydro': 137.99,\n        'solar': 3.24,\n        'unknown': 62.91,\n        'wind': 21.54,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 109.92,\n        'geothermal': 167.34,\n        'hydro': 70.81,\n        'solar': 33.27,\n        'unknown': 62.01,\n        'wind': 15.28,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 97.85,\n        'geothermal': 167.18,\n        'hydro': 13.56,\n        'solar': 54.97,\n        'unknown': 59.2,\n        'wind': 3.54,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 81.29,\n        'geothermal': 166.4,\n        'hydro': 11.25,\n        'solar': 96.75,\n        'unknown': 58.97,\n        'wind': 0.46,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 75.74,\n        'geothermal': 164.83,\n        'hydro': 10.02,\n        'solar': 139.1,\n        'unknown': 55.99,\n        'wind': 4,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 75.79,\n        'geothermal': 164.01,\n        'hydro': 8.15,\n        'solar': 170.71,\n        'unknown': 52.59,\n        'wind': 12.09,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 75.59,\n        'geothermal': 166.46,\n        'hydro': 0.64,\n        'solar': 145.27,\n        'unknown': 56.75,\n        'wind': 22.4,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 78.69,\n        'geothermal': 165.66,\n        'hydro': 0.37,\n        'solar': 168.15,\n        'unknown': 63.48,\n        'wind': 13.31,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 88.26,\n        'geothermal': 165.34,\n        'hydro': 8.1,\n        'solar': 136.97,\n        'unknown': 58.21,\n        'wind': 22.96,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 88.72,\n        'geothermal': 162.88,\n        'hydro': 48.59,\n        'solar': 117.13,\n        'unknown': 60.33,\n        'wind': 35.25,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 89.86,\n        'geothermal': 161.3,\n        'hydro': 147.2,\n        'solar': 47.88,\n        'unknown': 78.18,\n        'wind': 33.77,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 91.64,\n        'geothermal': 160.79,\n        'hydro': 287.96,\n        'solar': 2.69,\n        'unknown': 105.65,\n        'wind': 37.91,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 111.45,\n        'geothermal': 164.02,\n        'hydro': 341.21,\n        'unknown': 131.4,\n        'wind': 32.53,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 132.85,\n        'geothermal': 165.25,\n        'hydro': 303.09,\n        'unknown': 139.91,\n        'wind': 45.01,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 131.87,\n        'geothermal': 165.82,\n        'hydro': 206.83,\n        'unknown': 212.99,\n        'wind': 45.57,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 131.89,\n        'geothermal': 164.44,\n        'hydro': 105.14,\n        'unknown': 262.78,\n        'wind': 46.6,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 132.89,\n        'geothermal': 164.23,\n        'hydro': 53.49,\n        'unknown': 215.68,\n        'wind': 47,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 130.44,\n        'geothermal': 164.23,\n        'hydro': 48.45,\n        'unknown': 162.02,\n        'wind': 46.72,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n  ])\n# ---\n# name: test_fetch_production_live\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 145.81,\n        'geothermal': 162.33,\n        'hydro': 160.81,\n        'unknown': 58.28,\n        'wind': 18.08,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 147.53,\n        'geothermal': 165.11,\n        'hydro': 129.55,\n        'unknown': 59.52,\n        'wind': 15.79,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/El_Salvador')),\n      'production': dict({\n        'biomass': 148.04,\n        'geothermal': 166.12,\n        'hydro': 97.36,\n        'unknown': 56.4,\n        'wind': 19.01,\n      }),\n      'source': 'ut.com.sv',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'SV',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FO/test_fetch_production_historical[DST-FO-MI].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_historical[DST-FO-MI]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.28,\n        'hydro': 0,\n        'oil': 32.04,\n        'wind': 4.75,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.24,\n        'hydro': 0,\n        'oil': 28.87,\n        'wind': 7.18,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 26.41,\n        'wind': 8.96,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.22,\n        'hydro': 0,\n        'oil': 25.84,\n        'wind': 8.93,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.27,\n        'hydro': 0,\n        'oil': 23.46,\n        'wind': 11.04,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 21.03,\n        'wind': 13.21,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.16,\n        'hydro': 0,\n        'oil': 21.11,\n        'wind': 14.41,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.37,\n        'hydro': 0,\n        'oil': 19.91,\n        'wind': 17.6,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 20.68,\n        'wind': 19.61,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.38,\n        'hydro': 0,\n        'oil': 20.55,\n        'wind': 22.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.13,\n        'hydro': 0.13,\n        'oil': 19.76,\n        'wind': 25.45,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.15,\n        'oil': 17.81,\n        'wind': 26.57,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.27,\n        'hydro': 0.93,\n        'oil': 18.73,\n        'wind': 26.73,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.21,\n        'hydro': 0.91,\n        'oil': 18.68,\n        'wind': 26.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0.94,\n        'oil': 18.86,\n        'wind': 26.27,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.44,\n        'hydro': 0.99,\n        'oil': 19.14,\n        'wind': 26.91,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.23,\n        'hydro': 1,\n        'oil': 19.26,\n        'wind': 27.26,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0.95,\n        'oil': 18.98,\n        'wind': 27.22,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'hydro': 1.2,\n        'oil': 19.23,\n        'wind': 26.19,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.31,\n        'hydro': 1.66,\n        'oil': 19.68,\n        'wind': 23.62,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.62,\n        'oil': 18.94,\n        'wind': 23.41,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.08,\n        'hydro': 1.2,\n        'oil': 19.91,\n        'wind': 23.02,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.37,\n        'hydro': 0.69,\n        'oil': 19.41,\n        'wind': 23.28,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0.53,\n        'oil': 18.72,\n        'wind': 22.69,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.52,\n        'hydro': 0.37,\n        'oil': 17.77,\n        'wind': 22.72,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'hydro': 0.03,\n        'oil': 17.75,\n        'wind': 22.45,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 18.12,\n        'wind': 20.95,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.41,\n        'hydro': 0,\n        'oil': 19.1,\n        'wind': 19.59,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.08,\n        'hydro': 0,\n        'oil': 18.98,\n        'wind': 19.23,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 18.74,\n        'wind': 19.26,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.3,\n        'hydro': 0,\n        'oil': 20.26,\n        'wind': 19.25,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.34,\n        'hydro': 0,\n        'oil': 21.26,\n        'wind': 19.74,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 22.08,\n        'wind': 20.68,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.34,\n        'hydro': 0,\n        'oil': 24.46,\n        'wind': 20.76,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.15,\n        'hydro': 0,\n        'oil': 23.6,\n        'wind': 23.58,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 22.4,\n        'wind': 24.87,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.25,\n        'hydro': 0,\n        'oil': 22.89,\n        'wind': 24.98,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.19,\n        'hydro': 0,\n        'oil': 21.26,\n        'wind': 26.26,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 20.36,\n        'wind': 26.23,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.42,\n        'hydro': 0.09,\n        'oil': 21.28,\n        'wind': 25.34,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.26,\n        'hydro': 3.24,\n        'oil': 23.74,\n        'wind': 19.79,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.76,\n        'oil': 26.35,\n        'wind': 13.61,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.22,\n        'hydro': 6.79,\n        'oil': 30.1,\n        'wind': 8.83,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.28,\n        'hydro': 5.36,\n        'oil': 30.15,\n        'wind': 10.17,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 4.15,\n        'oil': 28.98,\n        'wind': 11.23,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.12,\n        'hydro': 2.42,\n        'oil': 25.63,\n        'wind': 16.05,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.32,\n        'hydro': 1.63,\n        'oil': 24.58,\n        'wind': 17.36,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.65,\n        'oil': 23.72,\n        'wind': 12.04,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FO/test_fetch_production_historical[DST-FO-SI].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_historical[DST-FO-SI]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.8,\n        'solar': 0,\n        'wind': 1.07,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.25,\n        'solar': 0,\n        'wind': 1.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0.63,\n        'solar': 0,\n        'wind': 1.3,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0.78,\n        'solar': 0,\n        'wind': 1.77,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0.2,\n        'solar': 0,\n        'wind': 2.85,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 2.61,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 2.56,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 2.64,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 2.78,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 2.96,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 3.19,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.02,\n        'wind': 3.25,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.04,\n        'wind': 3.26,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.03,\n        'wind': 3.32,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.02,\n        'wind': 3.27,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 3.3,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 3.39,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 3.6,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 3.31,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 3.24,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 3.16,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 3.2,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 3.3,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 3.04,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.75,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.61,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.71,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.73,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.51,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 2.46,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.02,\n        'wind': 2.38,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.02,\n        'wind': 2.55,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.04,\n        'wind': 2.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.03,\n        'wind': 3.02,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.04,\n        'wind': 3.21,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.06,\n        'wind': 3.24,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.05,\n        'wind': 3.32,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.04,\n        'wind': 3.2,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.03,\n        'wind': 3.05,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.03,\n        'wind': 3.08,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.42,\n        'oil': 0,\n        'solar': 0.03,\n        'wind': 1.58,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 2.91,\n        'oil': 0,\n        'solar': 0.04,\n        'wind': 0.56,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 3.02,\n        'oil': 0,\n        'solar': 0.02,\n        'wind': 0.38,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 3.01,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 0.29,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 2.71,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 0.42,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 2.12,\n        'oil': 0,\n        'solar': 0,\n        'wind': 1.28,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 1.63,\n        'oil': 0,\n        'solar': 0,\n        'wind': 1.08,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 1.75,\n        'oil': 0,\n        'solar': 0,\n        'wind': 0.73,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FO/test_fetch_production_historical[DST-FO].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_historical[DST-FO]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.28,\n        'hydro': 0,\n        'oil': 33.84,\n        'solar': 0,\n        'wind': 5.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.24,\n        'hydro': 0,\n        'oil': 30.12,\n        'solar': 0,\n        'wind': 9.0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 27.04,\n        'solar': 0,\n        'wind': 10.26,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.22,\n        'hydro': 0,\n        'oil': 26.62,\n        'solar': 0,\n        'wind': 10.7,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.27,\n        'hydro': 0,\n        'oil': 23.66,\n        'solar': 0,\n        'wind': 13.89,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 21.03,\n        'solar': 0.01,\n        'wind': 15.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.16,\n        'hydro': 0,\n        'oil': 21.11,\n        'solar': 0.01,\n        'wind': 16.97,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.37,\n        'hydro': 0,\n        'oil': 19.91,\n        'solar': 0.01,\n        'wind': 20.24,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 20.68,\n        'solar': 0.01,\n        'wind': 22.39,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.38,\n        'hydro': 0,\n        'oil': 20.55,\n        'solar': 0.01,\n        'wind': 25.61,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.13,\n        'hydro': 0.13,\n        'oil': 19.76,\n        'solar': 0.01,\n        'wind': 28.64,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.15,\n        'oil': 17.81,\n        'solar': 0.02,\n        'wind': 29.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.27,\n        'hydro': 0.93,\n        'oil': 18.73,\n        'solar': 0.04,\n        'wind': 29.99,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.21,\n        'hydro': 0.91,\n        'oil': 18.68,\n        'solar': 0.03,\n        'wind': 29.97,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0.94,\n        'oil': 18.86,\n        'solar': 0.02,\n        'wind': 29.54,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.44,\n        'hydro': 0.99,\n        'oil': 19.14,\n        'solar': 0.01,\n        'wind': 30.21,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.23,\n        'hydro': 1,\n        'oil': 19.26,\n        'solar': 0.01,\n        'wind': 30.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0.95,\n        'oil': 18.98,\n        'solar': 0,\n        'wind': 30.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'hydro': 1.2,\n        'oil': 19.23,\n        'solar': 0,\n        'wind': 29.5,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.31,\n        'hydro': 1.66,\n        'oil': 19.68,\n        'solar': 0,\n        'wind': 26.86,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.62,\n        'oil': 18.94,\n        'solar': 0,\n        'wind': 26.57,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.08,\n        'hydro': 1.2,\n        'oil': 19.91,\n        'solar': 0,\n        'wind': 26.22,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.37,\n        'hydro': 0.69,\n        'oil': 19.41,\n        'solar': 0,\n        'wind': 26.58,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0.53,\n        'oil': 18.72,\n        'solar': 0,\n        'wind': 25.73,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.52,\n        'hydro': 0.37,\n        'oil': 17.77,\n        'solar': 0,\n        'wind': 25.47,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'hydro': 0.03,\n        'oil': 17.75,\n        'solar': 0,\n        'wind': 25.06,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 18.12,\n        'solar': 0,\n        'wind': 23.66,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.41,\n        'hydro': 0,\n        'oil': 19.1,\n        'solar': 0,\n        'wind': 22.32,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.08,\n        'hydro': 0,\n        'oil': 18.98,\n        'solar': 0,\n        'wind': 21.74,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 18.74,\n        'solar': 0.01,\n        'wind': 21.72,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.3,\n        'hydro': 0,\n        'oil': 20.26,\n        'solar': 0.02,\n        'wind': 21.63,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.34,\n        'hydro': 0,\n        'oil': 21.26,\n        'solar': 0.02,\n        'wind': 22.29,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 22.08,\n        'solar': 0.04,\n        'wind': 23.5,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.34,\n        'hydro': 0,\n        'oil': 24.46,\n        'solar': 0.03,\n        'wind': 23.78,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.15,\n        'hydro': 0,\n        'oil': 23.6,\n        'solar': 0.04,\n        'wind': 26.79,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 22.4,\n        'solar': 0.06,\n        'wind': 28.11,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.25,\n        'hydro': 0,\n        'oil': 22.89,\n        'solar': 0.05,\n        'wind': 28.3,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.19,\n        'hydro': 0,\n        'oil': 21.26,\n        'solar': 0.04,\n        'wind': 29.46,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 0,\n        'oil': 20.36,\n        'solar': 0.03,\n        'wind': 29.28,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.42,\n        'hydro': 0.09,\n        'oil': 21.28,\n        'solar': 0.03,\n        'wind': 28.42,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.26,\n        'hydro': 3.66,\n        'oil': 23.74,\n        'solar': 0.03,\n        'wind': 21.37,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 8.67,\n        'oil': 26.35,\n        'solar': 0.04,\n        'wind': 14.17,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.22,\n        'hydro': 9.81,\n        'oil': 30.1,\n        'solar': 0.02,\n        'wind': 9.21,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.28,\n        'hydro': 8.37,\n        'oil': 30.15,\n        'solar': 0.01,\n        'wind': 10.46,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 6.86,\n        'oil': 28.98,\n        'solar': 0.01,\n        'wind': 11.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.12,\n        'hydro': 4.54,\n        'oil': 25.63,\n        'solar': 0,\n        'wind': 17.33,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.32,\n        'hydro': 3.26,\n        'oil': 24.58,\n        'solar': 0,\n        'wind': 18.44,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 7.4,\n        'oil': 23.72,\n        'solar': 0,\n        'wind': 12.77,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FO/test_fetch_production_historical[SDT-FO-MI].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_historical[SDT-FO-MI]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 26.56,\n        'oil': 8.42,\n        'wind': 6.18,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 24.57,\n        'oil': 7.22,\n        'wind': 7.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.02,\n        'hydro': 22.01,\n        'oil': 7.98,\n        'wind': 8.48,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.81,\n        'hydro': 22.0,\n        'oil': 8.1,\n        'wind': 8.32,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.79,\n        'hydro': 25.22,\n        'oil': 7.56,\n        'wind': 6.63,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.76,\n        'hydro': 25.6,\n        'oil': 7.82,\n        'wind': 6.48,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.01,\n        'hydro': 29.55,\n        'oil': 7.99,\n        'wind': 4.96,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1,\n        'hydro': 32.51,\n        'oil': 14.48,\n        'wind': 1.8,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 30.9,\n        'oil': 22.93,\n        'wind': 0.68,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 29.25,\n        'oil': 24.87,\n        'wind': 0.48,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 30.01,\n        'oil': 26.03,\n        'wind': 0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.08,\n        'hydro': 29.93,\n        'oil': 26.18,\n        'wind': 0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 30.33,\n        'oil': 25.01,\n        'wind': 0.11,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 30.33,\n        'oil': 24.74,\n        'wind': 0.42,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.05,\n        'hydro': 29.59,\n        'oil': 23.73,\n        'wind': 1.13,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 27.07,\n        'oil': 23.29,\n        'wind': 3.69,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 27.79,\n        'oil': 19.57,\n        'wind': 6.0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.81,\n        'hydro': 25.35,\n        'oil': 20.38,\n        'wind': 10.94,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.91,\n        'hydro': 23.86,\n        'oil': 16.03,\n        'wind': 16.16,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.98,\n        'hydro': 23.33,\n        'oil': 11.7,\n        'wind': 18.4,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.89,\n        'hydro': 23.55,\n        'oil': 11.86,\n        'wind': 16.7,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.92,\n        'hydro': 23.28,\n        'oil': 11.17,\n        'wind': 15.99,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.06,\n        'hydro': 23.36,\n        'oil': 6.52,\n        'wind': 18.67,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.92,\n        'hydro': 21.6,\n        'oil': 5.97,\n        'wind': 18.02,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 17.69,\n        'oil': 5.22,\n        'wind': 19.28,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.8,\n        'hydro': 17.05,\n        'oil': 3.77,\n        'wind': 20.28,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.91,\n        'hydro': 17.09,\n        'oil': 3.78,\n        'wind': 19.6,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.07,\n        'hydro': 17.14,\n        'oil': 3.8,\n        'wind': 19.11,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.9,\n        'hydro': 18.96,\n        'oil': 3.96,\n        'wind': 16.69,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.86,\n        'hydro': 19.05,\n        'oil': 4,\n        'wind': 16.94,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 22.64,\n        'oil': 4.08,\n        'wind': 15.24,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.95,\n        'hydro': 27.53,\n        'oil': 6.01,\n        'wind': 13.43,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.01,\n        'hydro': 27.13,\n        'oil': 8.59,\n        'wind': 15.35,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.78,\n        'hydro': 26.62,\n        'oil': 9.65,\n        'wind': 16.75,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.85,\n        'hydro': 26.89,\n        'oil': 9.68,\n        'wind': 16.99,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.46,\n        'hydro': 24.46,\n        'oil': 12.23,\n        'wind': 17.38,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.67,\n        'hydro': 24.1,\n        'oil': 11.9,\n        'wind': 17.18,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.97,\n        'hydro': 25.33,\n        'oil': 9.18,\n        'wind': 17.49,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 25.11,\n        'oil': 8.84,\n        'wind': 17.34,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.85,\n        'hydro': 24.84,\n        'oil': 8.63,\n        'wind': 17.75,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.99,\n        'hydro': 24.95,\n        'oil': 8.69,\n        'wind': 17.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.9,\n        'hydro': 26.36,\n        'oil': 9.65,\n        'wind': 18.41,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.88,\n        'hydro': 26.34,\n        'oil': 9.21,\n        'wind': 18.38,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 25.27,\n        'oil': 7.98,\n        'wind': 17.2,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.03,\n        'hydro': 31.18,\n        'oil': 11.82,\n        'wind': 7.22,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.99,\n        'hydro': 31.96,\n        'oil': 16.5,\n        'wind': 2.19,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.85,\n        'hydro': 32.15,\n        'oil': 17.42,\n        'wind': 0.1,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.85,\n        'hydro': 29.79,\n        'oil': 16.48,\n        'wind': 0.34,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FO/test_fetch_production_historical[SDT-FO-SI].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_historical[SDT-FO-SI]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3,\n        'solar': 0,\n        'wind': 0.66,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.56,\n        'solar': 0,\n        'wind': 1.15,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.02,\n        'solar': 0,\n        'wind': 1.68,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.03,\n        'solar': 0,\n        'wind': 1.59,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.03,\n        'solar': 0,\n        'wind': 1.68,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0.52,\n        'solar': 0,\n        'wind': 3.08,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.02,\n        'oil': 1.26,\n        'solar': 0,\n        'wind': 2.03,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.53,\n        'oil': 3.38,\n        'solar': 0,\n        'wind': 0.16,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.6,\n        'oil': 4.16,\n        'solar': 0,\n        'wind': 0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 4.81,\n        'solar': 0,\n        'wind': 0.11,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 5.03,\n        'solar': 0.01,\n        'wind': 0.02,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 5.36,\n        'solar': 0.01,\n        'wind': 0.16,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 5.85,\n        'solar': 0.01,\n        'wind': 0.17,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.01,\n        'oil': 6.17,\n        'solar': 0.02,\n        'wind': 0.37,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.13,\n        'oil': 5.41,\n        'solar': 0.01,\n        'wind': 1.52,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 1.17,\n        'oil': 4.04,\n        'solar': 0.01,\n        'wind': 2.2,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 2.03,\n        'oil': 2.97,\n        'solar': 0,\n        'wind': 2.7,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 1.11,\n        'oil': 2.81,\n        'solar': 0,\n        'wind': 4.19,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.31,\n        'oil': 2.53,\n        'solar': 0,\n        'wind': 4.85,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.12,\n        'oil': 2.98,\n        'solar': 0,\n        'wind': 3.94,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 1.07,\n        'oil': 2.9,\n        'solar': 0,\n        'wind': 3.88,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.97,\n        'solar': 0,\n        'wind': 5.18,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.02,\n        'solar': 0,\n        'wind': 4.67,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.26,\n        'solar': 0,\n        'wind': 4.37,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.94,\n        'solar': 0,\n        'wind': 4.27,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.88,\n        'solar': 0,\n        'wind': 4.25,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.93,\n        'solar': 0,\n        'wind': 4.05,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.92,\n        'solar': 0,\n        'wind': 4.21,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.85,\n        'solar': 0,\n        'wind': 4.22,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.88,\n        'solar': 0,\n        'wind': 4.3,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.92,\n        'solar': 0,\n        'wind': 4.24,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.74,\n        'solar': 0,\n        'wind': 4,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.27,\n        'solar': 0,\n        'wind': 3.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.13,\n        'oil': 2.63,\n        'solar': 0.02,\n        'wind': 4.2,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.02,\n        'oil': 2.47,\n        'solar': 0.02,\n        'wind': 4.94,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.92,\n        'solar': 0.03,\n        'wind': 4.33,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.37,\n        'solar': 0.04,\n        'wind': 3.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.61,\n        'solar': 0.04,\n        'wind': 3.46,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.72,\n        'solar': 0.04,\n        'wind': 4.36,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.58,\n        'oil': 3.19,\n        'solar': 0.02,\n        'wind': 2.88,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 1.84,\n        'oil': 2.61,\n        'solar': 0.01,\n        'wind': 1.95,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 1.14,\n        'oil': 2.59,\n        'solar': 0,\n        'wind': 2.53,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.85,\n        'solar': 0,\n        'wind': 2.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.53,\n        'oil': 2.96,\n        'solar': 0,\n        'wind': 1.4,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 1.04,\n        'oil': 3.32,\n        'solar': 0,\n        'wind': 0.59,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.9,\n        'oil': 3.05,\n        'solar': 0,\n        'wind': 0.28,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.9,\n        'oil': 3.27,\n        'solar': 0,\n        'wind': 0.01,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.71,\n        'oil': 3.08,\n        'solar': 0,\n        'wind': 0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FO/test_fetch_production_historical[SDT-FO].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_historical[SDT-FO]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 26.56,\n        'oil': 11.42,\n        'solar': 0,\n        'wind': 6.84,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 24.57,\n        'oil': 9.78,\n        'solar': 0,\n        'wind': 8.97,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.02,\n        'hydro': 22.01,\n        'oil': 10.0,\n        'solar': 0,\n        'wind': 10.16,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.81,\n        'hydro': 22.0,\n        'oil': 10.13,\n        'solar': 0,\n        'wind': 9.91,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.79,\n        'hydro': 25.22,\n        'oil': 9.59,\n        'solar': 0,\n        'wind': 8.31,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.76,\n        'hydro': 25.6,\n        'oil': 8.34,\n        'solar': 0,\n        'wind': 9.56,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.01,\n        'hydro': 29.57,\n        'oil': 9.25,\n        'solar': 0,\n        'wind': 6.99,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1,\n        'hydro': 33.04,\n        'oil': 17.86,\n        'solar': 0,\n        'wind': 1.96,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 31.5,\n        'oil': 27.09,\n        'solar': 0,\n        'wind': 0.68,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 29.25,\n        'oil': 29.68,\n        'solar': 0,\n        'wind': 0.59,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 30.01,\n        'oil': 31.06,\n        'solar': 0.01,\n        'wind': 0.02,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.08,\n        'hydro': 29.93,\n        'oil': 31.54,\n        'solar': 0.01,\n        'wind': 0.16,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 30.33,\n        'oil': 30.86,\n        'solar': 0.01,\n        'wind': 0.28,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 30.34,\n        'oil': 30.91,\n        'solar': 0.02,\n        'wind': 0.79,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.05,\n        'hydro': 29.72,\n        'oil': 29.14,\n        'solar': 0.01,\n        'wind': 2.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 28.24,\n        'oil': 27.33,\n        'solar': 0.01,\n        'wind': 5.89,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 29.82,\n        'oil': 22.54,\n        'solar': 0,\n        'wind': 8.7,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.81,\n        'hydro': 26.46,\n        'oil': 23.19,\n        'solar': 0,\n        'wind': 15.13,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.91,\n        'hydro': 24.17,\n        'oil': 18.56,\n        'solar': 0,\n        'wind': 21.01,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.98,\n        'hydro': 23.45,\n        'oil': 14.68,\n        'solar': 0,\n        'wind': 22.34,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.89,\n        'hydro': 24.62,\n        'oil': 14.76,\n        'solar': 0,\n        'wind': 20.58,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.92,\n        'hydro': 23.28,\n        'oil': 13.14,\n        'solar': 0,\n        'wind': 21.17,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.06,\n        'hydro': 23.36,\n        'oil': 8.54,\n        'solar': 0,\n        'wind': 23.34,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.92,\n        'hydro': 21.6,\n        'oil': 8.23,\n        'solar': 0,\n        'wind': 22.39,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 17.69,\n        'oil': 7.16,\n        'solar': 0,\n        'wind': 23.55,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.8,\n        'hydro': 17.05,\n        'oil': 5.65,\n        'solar': 0,\n        'wind': 24.53,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.91,\n        'hydro': 17.09,\n        'oil': 5.71,\n        'solar': 0,\n        'wind': 23.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.07,\n        'hydro': 17.14,\n        'oil': 5.72,\n        'solar': 0,\n        'wind': 23.32,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.9,\n        'hydro': 18.96,\n        'oil': 5.81,\n        'solar': 0,\n        'wind': 20.91,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.86,\n        'hydro': 19.05,\n        'oil': 5.88,\n        'solar': 0,\n        'wind': 21.24,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 22.64,\n        'oil': 6.0,\n        'solar': 0,\n        'wind': 19.48,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.95,\n        'hydro': 27.53,\n        'oil': 8.75,\n        'solar': 0,\n        'wind': 17.43,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.01,\n        'hydro': 27.13,\n        'oil': 11.86,\n        'solar': 0,\n        'wind': 19.17,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.78,\n        'hydro': 26.75,\n        'oil': 12.28,\n        'solar': 0.02,\n        'wind': 20.95,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.85,\n        'hydro': 26.91,\n        'oil': 12.15,\n        'solar': 0.02,\n        'wind': 21.93,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.46,\n        'hydro': 24.46,\n        'oil': 15.15,\n        'solar': 0.03,\n        'wind': 21.71,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.67,\n        'hydro': 24.1,\n        'oil': 15.27,\n        'solar': 0.04,\n        'wind': 20.83,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.97,\n        'hydro': 25.33,\n        'oil': 12.79,\n        'solar': 0.04,\n        'wind': 20.95,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.84,\n        'hydro': 25.11,\n        'oil': 12.56,\n        'solar': 0.04,\n        'wind': 21.7,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.85,\n        'hydro': 25.42,\n        'oil': 11.82,\n        'solar': 0.02,\n        'wind': 20.63,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.99,\n        'hydro': 26.79,\n        'oil': 11.3,\n        'solar': 0.01,\n        'wind': 19.6,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.9,\n        'hydro': 27.5,\n        'oil': 12.24,\n        'solar': 0,\n        'wind': 20.94,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.88,\n        'hydro': 26.34,\n        'oil': 12.06,\n        'solar': 0,\n        'wind': 21.2,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.83,\n        'hydro': 25.8,\n        'oil': 10.94,\n        'solar': 0,\n        'wind': 18.6,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.03,\n        'hydro': 32.22,\n        'oil': 15.14,\n        'solar': 0,\n        'wind': 7.81,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.99,\n        'hydro': 32.86,\n        'oil': 19.55,\n        'solar': 0,\n        'wind': 2.47,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.85,\n        'hydro': 33.05,\n        'oil': 20.69,\n        'solar': 0,\n        'wind': 0.11,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 2, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.85,\n        'hydro': 30.5,\n        'oil': 19.56,\n        'solar': 0,\n        'wind': 0.34,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FO/test_fetch_production_live[FO-MI].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_live[FO-MI]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.09,\n        'oil': 26.78,\n        'wind': 8.15,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.79,\n        'hydro': 2.69,\n        'oil': 28.48,\n        'wind': 10.22,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.3,\n        'oil': 22.48,\n        'wind': 13.11,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.3,\n        'oil': 23.38,\n        'wind': 12.81,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.3,\n        'oil': 22.11,\n        'wind': 14.08,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.3,\n        'oil': 19.67,\n        'wind': 16.74,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 2.67,\n        'oil': 21.26,\n        'wind': 17.83,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.11,\n        'hydro': 10.07,\n        'oil': 18.28,\n        'wind': 19.35,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.73,\n        'hydro': 8.78,\n        'oil': 16.62,\n        'wind': 23.42,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.8,\n        'hydro': 9.92,\n        'oil': 15.99,\n        'wind': 25.16,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 9.73,\n        'oil': 15.95,\n        'wind': 25.49,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 11.26,\n        'oil': 17.26,\n        'wind': 22.09,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 11.21,\n        'oil': 19.77,\n        'wind': 18.33,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 10.68,\n        'oil': 29.58,\n        'wind': 9.59,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 11.92,\n        'oil': 33.66,\n        'wind': 3.22,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 14.41,\n        'oil': 34.57,\n        'wind': 0.22,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 15.8,\n        'oil': 34.52,\n        'wind': 0.37,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.21,\n        'hydro': 13.55,\n        'oil': 34.04,\n        'wind': 0.85,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.7,\n        'hydro': 12.6,\n        'oil': 33.1,\n        'wind': 0.92,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 10.09,\n        'oil': 32.98,\n        'wind': 2.19,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 8.06,\n        'oil': 33.06,\n        'wind': 3.55,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.33,\n        'hydro': 7.3,\n        'oil': 29.71,\n        'wind': 6.49,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.54,\n        'hydro': 9.66,\n        'oil': 29.02,\n        'wind': 5.9,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.33,\n        'oil': 29.16,\n        'wind': 6.25,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 3.89,\n        'oil': 29,\n        'wind': 6.72,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 2.29,\n        'oil': 27.84,\n        'wind': 8.58,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 3.98,\n        'oil': 23.4,\n        'wind': 7.32,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.53,\n        'oil': 27.75,\n        'wind': 3.19,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.11,\n        'oil': 27.45,\n        'wind': 2.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.55,\n        'hydro': 1.98,\n        'oil': 31.36,\n        'wind': 4.2,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.37,\n        'hydro': 4.36,\n        'oil': 36.59,\n        'wind': 2.05,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.86,\n        'hydro': 5.37,\n        'oil': 38.01,\n        'wind': 3.51,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 3.88,\n        'oil': 42.02,\n        'wind': 1.46,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 6.62,\n        'oil': 42.37,\n        'unknown': 0.0,\n        'wind': 0.09,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-MI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FO/test_fetch_production_live[FO-SI].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_live[FO-SI]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.73,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.97,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.95,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.76,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.65,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0,\n        'wind': 2.74,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 3.07,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.01,\n        'wind': 3.41,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0,\n        'solar': 0.02,\n        'wind': 3.45,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 0.72,\n        'solar': 0.04,\n        'wind': 2.53,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.47,\n        'solar': 0.08,\n        'wind': 1.51,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.77,\n        'solar': 0.08,\n        'wind': 0.58,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.24,\n        'solar': 0.1,\n        'wind': 0.05,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.35,\n        'solar': 0.16,\n        'wind': 0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.4,\n        'solar': 0.06,\n        'wind': 0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.29,\n        'solar': 0.06,\n        'wind': 0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.16,\n        'solar': 0.06,\n        'wind': 0.17,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.99,\n        'solar': 0.06,\n        'wind': 0.17,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.18,\n        'solar': 0.04,\n        'wind': 0.9,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.73,\n        'solar': 0.01,\n        'wind': 1.27,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.68,\n        'solar': 0,\n        'wind': 1.2,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.69,\n        'solar': 0,\n        'wind': 0.98,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.82,\n        'solar': 0,\n        'wind': 1.12,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.95,\n        'solar': 0,\n        'wind': 0.73,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.95,\n        'solar': 0,\n        'wind': 0.46,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.95,\n        'solar': 0,\n        'wind': 0.33,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.15,\n        'solar': 0,\n        'wind': 0.36,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.32,\n        'solar': 0,\n        'wind': 0.32,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.84,\n        'solar': 0,\n        'wind': 0.39,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 1.84,\n        'solar': 0.01,\n        'wind': 0.33,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.8,\n        'solar': 0.02,\n        'wind': 0.12,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 2.91,\n        'solar': 0.07,\n        'wind': 0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0,\n        'oil': 3.18,\n        'solar': 0.1,\n        'wind': 0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'hydro': 0.0,\n        'oil': 3.77,\n        'solar': 0.07,\n        'wind': 0.59,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO-SI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FO/test_fetch_production_live[FO].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_live[FO]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.09,\n        'oil': 26.78,\n        'solar': 0,\n        'wind': 10.88,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.79,\n        'hydro': 2.69,\n        'oil': 28.48,\n        'solar': 0,\n        'wind': 13.19,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.3,\n        'oil': 22.48,\n        'solar': 0,\n        'wind': 16.06,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.3,\n        'oil': 23.38,\n        'solar': 0,\n        'wind': 15.57,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.3,\n        'oil': 22.11,\n        'solar': 0,\n        'wind': 16.73,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 1.3,\n        'oil': 19.67,\n        'solar': 0,\n        'wind': 19.48,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 2.67,\n        'oil': 21.26,\n        'solar': 0.01,\n        'wind': 20.9,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.11,\n        'hydro': 10.07,\n        'oil': 18.28,\n        'solar': 0.01,\n        'wind': 22.76,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.73,\n        'hydro': 8.78,\n        'oil': 16.62,\n        'solar': 0.02,\n        'wind': 26.87,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.8,\n        'hydro': 9.92,\n        'oil': 16.71,\n        'solar': 0.04,\n        'wind': 27.69,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 9.73,\n        'oil': 18.42,\n        'solar': 0.08,\n        'wind': 27.0,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 11.26,\n        'oil': 20.03,\n        'solar': 0.08,\n        'wind': 22.67,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 11.21,\n        'oil': 23.01,\n        'solar': 0.1,\n        'wind': 18.38,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 10.68,\n        'oil': 32.93,\n        'solar': 0.16,\n        'wind': 9.59,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 11.92,\n        'oil': 37.06,\n        'solar': 0.06,\n        'wind': 3.22,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 14.41,\n        'oil': 37.86,\n        'solar': 0.06,\n        'wind': 0.22,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 15.8,\n        'oil': 37.68,\n        'solar': 0.06,\n        'wind': 0.54,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.21,\n        'hydro': 13.55,\n        'oil': 37.03,\n        'solar': 0.06,\n        'wind': 1.02,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.7,\n        'hydro': 12.6,\n        'oil': 35.28,\n        'solar': 0.04,\n        'wind': 1.82,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 10.09,\n        'oil': 34.71,\n        'solar': 0.01,\n        'wind': 3.46,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 8.06,\n        'oil': 34.74,\n        'solar': 0,\n        'wind': 4.75,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.33,\n        'hydro': 7.3,\n        'oil': 31.4,\n        'solar': 0,\n        'wind': 7.47,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.54,\n        'hydro': 9.66,\n        'oil': 30.84,\n        'solar': 0,\n        'wind': 7.02,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.33,\n        'oil': 31.11,\n        'solar': 0,\n        'wind': 6.98,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 3.89,\n        'oil': 30.95,\n        'solar': 0,\n        'wind': 7.18,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 2.29,\n        'oil': 29.79,\n        'solar': 0,\n        'wind': 8.91,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 3.98,\n        'oil': 25.55,\n        'solar': 0,\n        'wind': 7.68,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.53,\n        'oil': 30.07,\n        'solar': 0,\n        'wind': 3.51,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 5.11,\n        'oil': 29.29,\n        'solar': 0,\n        'wind': 3.04,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.55,\n        'hydro': 1.98,\n        'oil': 33.2,\n        'solar': 0.01,\n        'wind': 4.53,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.37,\n        'hydro': 4.36,\n        'oil': 39.39,\n        'solar': 0.02,\n        'wind': 2.17,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.86,\n        'hydro': 5.37,\n        'oil': 40.92,\n        'solar': 0.07,\n        'wind': 3.51,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 3.88,\n        'oil': 45.2,\n        'solar': 0.1,\n        'wind': 1.46,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 5, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.75,\n        'hydro': 6.62,\n        'oil': 46.14,\n        'solar': 0.07,\n        'unknown': 0.0,\n        'wind': 0.68,\n      }),\n      'source': 'sev.fo',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'FO',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_FR.ambr",
    "content": "# serializer version: 1\n# name: test_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(676.5),\n        'coal': np.float64(7.0),\n        'gas': np.float64(431.5),\n        'hydro': np.float64(3457.0),\n        'nuclear': np.float64(35323.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(9451.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(2.0),\n        'hydro': np.float64(781.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(676.5),\n        'coal': np.float64(7.0),\n        'gas': np.float64(446.5),\n        'hydro': np.float64(3490.0),\n        'nuclear': np.float64(34656.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(9097.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(1.5),\n        'hydro': np.float64(1097.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(677.0),\n        'coal': np.float64(7.0),\n        'gas': np.float64(414.0),\n        'hydro': np.float64(3407.5),\n        'nuclear': np.float64(34372.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(9050.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(4.5),\n        'hydro': np.float64(1423.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(676.5),\n        'coal': np.float64(7.0),\n        'gas': np.float64(434.0),\n        'hydro': np.float64(3184.0),\n        'nuclear': np.float64(34508.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(8904.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(8.5),\n        'hydro': np.float64(1422.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(677.0),\n        'coal': np.float64(7.0),\n        'gas': np.float64(414.0),\n        'hydro': np.float64(3207.0),\n        'nuclear': np.float64(34517.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(8366.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(5.0),\n        'hydro': np.float64(1422.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(676.0),\n        'coal': np.float64(7.0),\n        'gas': np.float64(461.0),\n        'hydro': np.float64(3227.5),\n        'nuclear': np.float64(34874.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(7937.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(3.0),\n        'hydro': np.float64(1421.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(676.5),\n        'coal': np.float64(7.0),\n        'gas': np.float64(458.5),\n        'hydro': np.float64(3386.0),\n        'nuclear': np.float64(35173.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(7489.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(3.5),\n        'hydro': np.float64(1256.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(676.5),\n        'coal': np.float64(7.0),\n        'gas': np.float64(601.5),\n        'hydro': np.float64(3732.0),\n        'nuclear': np.float64(36085.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(6962.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(932.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(674.0),\n        'coal': np.float64(7.0),\n        'gas': np.float64(808.5),\n        'hydro': np.float64(3954.0),\n        'nuclear': np.float64(36718.5),\n        'oil': np.float64(113.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(6596.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(12.0),\n        'hydro': np.float64(586.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(675.5),\n        'coal': np.float64(7.0),\n        'gas': np.float64(938.5),\n        'hydro': np.float64(4244.0),\n        'nuclear': np.float64(37910.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(6485.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-2.5),\n        'hydro': np.float64(-323.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(674.5),\n        'coal': np.float64(7.0),\n        'gas': np.float64(1133.0),\n        'hydro': np.float64(4394.0),\n        'nuclear': np.float64(38387.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(376.0),\n        'wind': np.float64(5863.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(5.0),\n        'hydro': np.float64(-667.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(674.5),\n        'coal': np.float64(7.0),\n        'gas': np.float64(1158.0),\n        'hydro': np.float64(4696.0),\n        'nuclear': np.float64(38681.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(401.5),\n        'wind': np.float64(5586.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(1.0),\n        'hydro': np.float64(-1045.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(673.5),\n        'coal': np.float64(9.0),\n        'gas': np.float64(1379.5),\n        'hydro': np.float64(4532.5),\n        'nuclear': np.float64(38725.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(501.5),\n        'wind': np.float64(5789.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(3.5),\n        'hydro': np.float64(-956.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(675.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1595.0),\n        'hydro': np.float64(4318.5),\n        'nuclear': np.float64(38691.5),\n        'oil': np.float64(113.5),\n        'solar': np.float64(868.5),\n        'wind': np.float64(5908.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-3.0),\n        'hydro': np.float64(-882.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(669.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1601.0),\n        'hydro': np.float64(4219.0),\n        'nuclear': np.float64(38771.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(1387.0),\n        'wind': np.float64(5784.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(1.0),\n        'hydro': np.float64(-957.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(668.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1569.0),\n        'hydro': np.float64(4074.5),\n        'nuclear': np.float64(38720.0),\n        'oil': np.float64(113.5),\n        'solar': np.float64(2034.0),\n        'wind': np.float64(5504.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(4.5),\n        'hydro': np.float64(-939.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(670.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1640.5),\n        'hydro': np.float64(4111.0),\n        'nuclear': np.float64(38828.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(2531.0),\n        'wind': np.float64(5099.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(-902.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(670.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1668.0),\n        'hydro': np.float64(4213.0),\n        'nuclear': np.float64(38899.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(3213.0),\n        'wind': np.float64(4500.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(0.5),\n        'hydro': np.float64(-753.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(670.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1611.0),\n        'hydro': np.float64(4379.0),\n        'nuclear': np.float64(38879.5),\n        'oil': np.float64(132.0),\n        'solar': np.float64(3541.5),\n        'wind': np.float64(4020.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(4.5),\n        'hydro': np.float64(-823.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(669.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1627.5),\n        'hydro': np.float64(4704.0),\n        'nuclear': np.float64(38751.5),\n        'oil': np.float64(186.5),\n        'solar': np.float64(4049.0),\n        'wind': np.float64(3706.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(8.5),\n        'hydro': np.float64(-879.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(668.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1595.0),\n        'hydro': np.float64(4456.0),\n        'nuclear': np.float64(38683.5),\n        'oil': np.float64(185.5),\n        'solar': np.float64(4069.5),\n        'wind': np.float64(3465.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(5.5),\n        'hydro': np.float64(-908.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(668.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1577.5),\n        'hydro': np.float64(4431.5),\n        'nuclear': np.float64(38599.0),\n        'oil': np.float64(185.5),\n        'solar': np.float64(4319.0),\n        'wind': np.float64(3696.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(6.5),\n        'hydro': np.float64(-807.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(665.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1466.0),\n        'hydro': np.float64(4157.0),\n        'nuclear': np.float64(38380.0),\n        'oil': np.float64(185.5),\n        'solar': np.float64(4654.0),\n        'wind': np.float64(4014.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(7.5),\n        'hydro': np.float64(-480.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(665.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1575.5),\n        'hydro': np.float64(3986.0),\n        'nuclear': np.float64(38566.5),\n        'oil': np.float64(150.5),\n        'solar': np.float64(4571.5),\n        'wind': np.float64(4111.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(3.5),\n        'hydro': np.float64(-478.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(670.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1519.5),\n        'hydro': np.float64(3917.0),\n        'nuclear': np.float64(38364.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(4710.5),\n        'wind': np.float64(4422.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(7.0),\n        'hydro': np.float64(-346.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(667.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1668.5),\n        'hydro': np.float64(3845.0),\n        'nuclear': np.float64(38267.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(4803.5),\n        'wind': np.float64(5231.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(0.5),\n        'hydro': np.float64(-96.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(664.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1671.0),\n        'hydro': np.float64(3944.5),\n        'nuclear': np.float64(37840.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(4974.5),\n        'wind': np.float64(5716.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(3.5),\n        'hydro': np.float64(22.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(655.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1708.0),\n        'hydro': np.float64(4127.0),\n        'nuclear': np.float64(37704.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(4534.5),\n        'wind': np.float64(5908.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-2.5),\n        'hydro': np.float64(-121.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(635.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1784.0),\n        'hydro': np.float64(4137.5),\n        'nuclear': np.float64(37800.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(4037.5),\n        'wind': np.float64(5689.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(3.0),\n        'hydro': np.float64(-480.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(639.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1899.5),\n        'hydro': np.float64(4338.0),\n        'nuclear': np.float64(37900.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(3663.5),\n        'wind': np.float64(5525.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(-1101.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(645.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1838.5),\n        'hydro': np.float64(4569.5),\n        'nuclear': np.float64(37771.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(3240.0),\n        'wind': np.float64(5645.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(9.5),\n        'hydro': np.float64(-959.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(651.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1835.0),\n        'hydro': np.float64(5028.5),\n        'nuclear': np.float64(37858.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(2509.0),\n        'wind': np.float64(5495.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-6.5),\n        'hydro': np.float64(-1170.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(651.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1762.0),\n        'hydro': np.float64(5006.0),\n        'nuclear': np.float64(37612.0),\n        'oil': np.float64(113.5),\n        'solar': np.float64(1923.5),\n        'wind': np.float64(5446.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(12.0),\n        'hydro': np.float64(-936.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(650.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(1936.0),\n        'hydro': np.float64(5174.5),\n        'nuclear': np.float64(37822.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(1162.0),\n        'wind': np.float64(5308.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-2.0),\n        'hydro': np.float64(-509.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(653.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(2256.5),\n        'hydro': np.float64(5745.0),\n        'nuclear': np.float64(37774.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(643.5),\n        'wind': np.float64(5164.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(5.0),\n        'hydro': np.float64(-945.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(657.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(2280.5),\n        'hydro': np.float64(5791.5),\n        'nuclear': np.float64(37791.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(369.0),\n        'wind': np.float64(5344.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(8.5),\n        'hydro': np.float64(-900.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(657.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(2303.5),\n        'hydro': np.float64(5777.0),\n        'nuclear': np.float64(37752.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(228.0),\n        'wind': np.float64(5333.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(7.0),\n        'hydro': np.float64(-1151.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(655.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(2195.0),\n        'hydro': np.float64(5707.5),\n        'nuclear': np.float64(37561.5),\n        'oil': np.float64(110.0),\n        'solar': np.float64(218.5),\n        'wind': np.float64(5381.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(3.0),\n        'hydro': np.float64(-1228.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(655.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(2252.0),\n        'hydro': np.float64(5697.0),\n        'nuclear': np.float64(37647.0),\n        'oil': np.float64(498.0),\n        'solar': np.float64(110.0),\n        'wind': np.float64(5378.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(-1421.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(653.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(2163.0),\n        'hydro': np.float64(5285.0),\n        'nuclear': np.float64(37785.5),\n        'oil': np.float64(543.5),\n        'solar': np.float64(0.0),\n        'wind': np.float64(5526.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(10.5),\n        'hydro': np.float64(-596.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(658.5),\n        'coal': np.float64(11.0),\n        'gas': np.float64(2197.5),\n        'hydro': np.float64(5168.0),\n        'nuclear': np.float64(37852.5),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(5895.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(5.5),\n        'hydro': np.float64(-486.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(655.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(2223.5),\n        'hydro': np.float64(5214.5),\n        'nuclear': np.float64(37831.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(6158.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(3.0),\n        'hydro': np.float64(-607.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(652.0),\n        'coal': np.float64(11.0),\n        'gas': np.float64(2301.5),\n        'hydro': np.float64(5142.0),\n        'nuclear': np.float64(37838.0),\n        'oil': np.float64(114.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(6445.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(2.0),\n        'hydro': np.float64(-703.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 21, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(653.5),\n        'coal': np.float64(9.0),\n        'gas': np.float64(2092.0),\n        'hydro': np.float64(4799.0),\n        'nuclear': np.float64(37548.0),\n        'oil': np.float64(113.5),\n        'solar': np.float64(0.0),\n        'wind': np.float64(6631.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(7.5),\n        'hydro': np.float64(-461.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 22, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(655.0),\n        'coal': np.float64(7.0),\n        'gas': np.float64(2083.0),\n        'hydro': np.float64(4451.0),\n        'nuclear': np.float64(37718.5),\n        'oil': np.float64(113.5),\n        'solar': np.float64(0.0),\n        'wind': np.float64(6738.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.5),\n        'hydro': np.float64(-657.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 22, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(654.0),\n        'coal': np.float64(7.0),\n        'gas': np.float64(1826.5),\n        'hydro': np.float64(4180.5),\n        'nuclear': np.float64(37300.0),\n        'oil': np.float64(113.5),\n        'solar': np.float64(0.0),\n        'wind': np.float64(6931.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(6.0),\n        'hydro': np.float64(-586.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 22, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(654.0),\n        'coal': np.float64(7.0),\n        'gas': np.float64(906.0),\n        'hydro': np.float64(4203.5),\n        'nuclear': np.float64(37458.5),\n        'oil': np.float64(112.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(6831.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-2.0),\n        'hydro': np.float64(-556.5),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 22, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(649.5),\n        'coal': np.float64(7.0),\n        'gas': np.float64(492.0),\n        'hydro': np.float64(4181.0),\n        'nuclear': np.float64(37619.5),\n        'oil': np.float64(109.5),\n        'solar': np.float64(0.0),\n        'wind': np.float64(7137.5),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(5.0),\n        'hydro': np.float64(-567.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 22, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Paris')),\n      'production': dict({\n        'biomass': np.float64(651.0),\n        'coal': np.float64(7.0),\n        'gas': np.float64(501.0),\n        'hydro': np.float64(3965.0),\n        'nuclear': np.float64(37536.0),\n        'oil': np.float64(110.0),\n        'solar': np.float64(0.0),\n        'wind': np.float64(7440.0),\n      }),\n      'source': 'opendata.reseaux-energies.fr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(-207.0),\n      }),\n      'zoneKey': 'FR',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB/test_fetch_price_live[AT].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_live[AT]\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 57.4,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 46.89,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 23.9,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.12,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.29,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.94,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 34.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 21.54,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.8,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -9.97,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -24.92,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -50.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -55.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -49.91,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -18.73,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.08,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 36.47,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 56.58,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 63.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 50.04,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 40.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 33.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 31.48,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.34,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.64,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.87,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.12,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 12.86,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.49,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -2.03,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -11.29,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -39.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -54.61,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -56.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -40.04,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -6.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.57,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 60.98,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 75.97,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.28,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 78.42,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 91.29,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 78.93,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 75.91,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 75.93,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 72.41,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 72.85,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 70.24,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 81.34,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 108.78,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 158.53,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 143.13,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 83.53,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.82,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 57.38,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 40.95,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 29.12,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 12.85,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 39.94,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 53.58,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 67.91,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 71.89,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 78.92,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 80.87,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 70.7,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 56.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 42.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AT',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB/test_fetch_price_live[BE].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_live[BE]\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 36.14,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.24,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.93,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.88,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 20.58,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 23.89,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.14,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.8,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -9.79,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -21.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -50.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -55.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -49.91,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -19.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.13,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 14.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 27.96,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 38.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 34.89,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 21.88,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.38,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.41,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.21,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.33,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.78,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.12,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 12.86,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.75,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.54,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -2.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -13.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -26.97,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -35.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -39.95,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -6.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.57,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 43.37,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 86.81,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 123.75,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 117.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 64.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 53.31,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 47.75,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 44.18,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 41.3,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 40.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 39.31,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 45.26,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 46.8,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 79.82,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 56.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 53.62,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.16,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 26.77,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.48,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 20.85,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.37,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 26.8,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 47.32,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 54.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 55.89,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 51.67,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 38.67,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'BE',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB/test_fetch_price_live[CH].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_live[CH]\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 65.11,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 55.66,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 50.05,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 41.71,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 39.95,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 43.12,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 56.29,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 55.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 38.14,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.95,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -9.08,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -25.34,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -51.75,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -51.93,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -32.98,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -13.39,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.79,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 63.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 78.45,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 80.4,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 58.85,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 58.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 56.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.71,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.35,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.35,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.27,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.36,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.36,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': -2.2,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': -12.92,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -26.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -47.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -65.78,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -91.49,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -91.51,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -62.04,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -31.71,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -5.94,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 45.43,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 79.22,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 83.77,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 85.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 81.55,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 76.98,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 73.13,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 67.88,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 66.68,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 67.2,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 78.14,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 92.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 107.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 103.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 77.92,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 65.27,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 39.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 23.75,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.84,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 50.05,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 62.11,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 67.51,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 66.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 73.05,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 71.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 66.4,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 67.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 65.97,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'CH',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB/test_fetch_price_live[ES].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_live[ES]\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.73,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.13,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.79,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.39,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.76,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.26,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.2,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.4,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.4,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.08,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.96,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.26,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.79,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.69,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.51,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.35,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 12.86,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.53,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.41,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.77,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.72,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.3,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.77,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.03,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.75,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.7,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.04,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.32,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.72,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 4.2,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'ES',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB/test_fetch_price_live[FR].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_live[FR]\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.73,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.13,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.79,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.39,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.76,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.26,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.8,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -9.79,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -20.64,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -50.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -55.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -49.91,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -19.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.08,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.2,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.66,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.96,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 33.82,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.26,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.79,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.69,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.51,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.35,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 12.86,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.53,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -7.37,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -2.16,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -10.58,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -23.62,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -39.89,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -6.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.57,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.96,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.41,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.77,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.72,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.3,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.77,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.03,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.75,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.7,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.04,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.32,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.72,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 4.2,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'FR',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB/test_fetch_price_live[GB].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_live[GB]\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.46,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.73,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.55,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 14.87,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.73,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 22.24,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 41.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 40.97,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 38.51,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.56,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 4.68,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -3.04,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -13.11,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -24.58,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -24.93,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -16.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -5.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.38,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 38.05,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 40.97,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.47,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 23.41,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.85,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.86,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': -1.4,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.17,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.81,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.81,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 4.68,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.55,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.97,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 21.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 21.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.62,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.54,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 16.39,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 37.46,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 65.56,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 87.33,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 87.68,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 83.11,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 67.08,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 40.33,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.03,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.16,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.47,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.47,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.49,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 39.92,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 70.94,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 71.17,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 60.99,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 46.36,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.99,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 14.28,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.27,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 4.68,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 21.89,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 60.76,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 75.97,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 81.48,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 76.21,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 52.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.03,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB/test_fetch_price_live[IT].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_live[IT]\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 90.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 85.98,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 71.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 70.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 71.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 72.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 85.58,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 91.69,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 90.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.86,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 36.99,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 42.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 26.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 15.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 26.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.89,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 64.87,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 93.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 100.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 100.29,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 89.3606,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 89.69,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 88.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 92.99,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 90.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 92.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.08,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.55,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 71.55,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 94.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.95,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 94.9,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 94.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 36.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 15.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 38.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 94.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 109.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 135.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 135.2,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 120.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 96.34,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 94.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 86.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 76.6143,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 73.8005,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 75.3,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 71.8417,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.4963,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 106.99,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 145.95,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 143.134,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 103.72,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 94.62,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 82.37,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 69.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 61.04,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 70.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 75.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 84.9999,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 90.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 96.64,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 127.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 126.23,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 102.41,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 95.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 87.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'IT',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB/test_fetch_price_live[NL].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_live[NL]\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 54.56,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 44.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 23.27,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.11,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.04,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.08,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.75,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 33.73,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 22.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.8,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -10.16,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -31.66,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -50.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -55.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -49.91,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -19.14,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 33.37,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 50.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 58.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 37.54,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 20.34,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.94,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.26,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 12.86,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 8.21,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -2.68,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -12.97,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -42.23,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -60.05,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -60.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -40.05,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -6.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.57,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 79.7,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 102.3,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 133.65,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 124.48,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 97.16,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 79.69,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 81.96,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.9,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 70.55,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 70.54,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 68.3,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 78.88,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 98.75,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 148.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 108.27,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 62.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 48.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 48.77,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 42.17,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 31.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 9.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.99,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 43.46,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 66.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 76.12,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.89,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 65.54,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 52.85,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 34.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'NL',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB/test_fetch_price_live[PT].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_live[PT]\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.73,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.13,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.79,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.39,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 11.76,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.26,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.06,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.96,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.26,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 13, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.83,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.79,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.74,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.69,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.51,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.35,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 12.86,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 13.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 5.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.53,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.55,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.55,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.57,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.6,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.02,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 2.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.41,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.77,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.72,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 14, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 17.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.3,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 3.25,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.77,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.03,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 7.07,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.7,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 1.5,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.01,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.04,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.1,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.32,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.63,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': -0.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 0.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 10.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 19.72,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 6.0,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': FakeDatetime(2024, 4, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 4.2,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'PT',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GB.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 370.99,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 335.11,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 299.45,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 280.51,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 242.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 242.62,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 262.98,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 336.87,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 381.58,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 367.58,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 329.34,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 305.93,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 288.28,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 270.63,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 246.27,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 237.68,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 243.56,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 301.34,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 331.81,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 377.7,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 405.7,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 410.29,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 394.29,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 15, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 366.11,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 277.69,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 247.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 245.92,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 242.62,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 241.92,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 237.68,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 233.21,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 231.8,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 237.68,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 249.45,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 248.33,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 243.21,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 235.33,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 217.44,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 194.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 185.91,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 188.26,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 204.15,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 247.09,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 301.57,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 335.58,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 348.52,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 343.34,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2022, 7, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 324.4,\n      'source': 'rte-france.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB',\n    }),\n  ])\n# ---\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 12, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n      'production': dict({\n        'biomass': 5.0,\n        'coal': 0.0,\n        'gas': 10.5,\n        'hydro': 2.0,\n        'nuclear': 8.0,\n        'solar': 3.5,\n        'unknown': 0.0,\n        'wind': 13.5,\n      }),\n      'source': 'neso.energy, elexon.co.uk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n        'hydro': -120.0,\n      }),\n      'zoneKey': 'GB',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 12, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n      'production': dict({\n        'biomass': 6.0,\n        'coal': 1.0,\n        'gas': 11.0,\n        'hydro': 2.5,\n        'nuclear': 8.0,\n        'solar': 4.0,\n        'unknown': 0.5,\n        'wind': 15.0,\n      }),\n      'source': 'neso.energy, elexon.co.uk',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'GB',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_GT.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption_historical\n  list([\n    dict({\n      'consumption': 1703.56375,\n      'datetime': datetime.datetime(2023, 7, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1730.42375,\n      'datetime': datetime.datetime(2023, 7, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1700.99375,\n      'datetime': datetime.datetime(2023, 7, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1492.59375,\n      'datetime': datetime.datetime(2023, 7, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1340.40375,\n      'datetime': datetime.datetime(2023, 7, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1203.66375,\n      'datetime': datetime.datetime(2023, 7, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1140.08,\n      'datetime': datetime.datetime(2023, 7, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1096.95,\n      'datetime': datetime.datetime(2023, 7, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1074.49,\n      'datetime': datetime.datetime(2023, 7, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1074.75,\n      'datetime': datetime.datetime(2023, 7, 16, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1088.75,\n      'datetime': datetime.datetime(2023, 7, 16, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1081.36,\n      'datetime': datetime.datetime(2023, 7, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1160.55,\n      'datetime': datetime.datetime(2023, 7, 16, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1203.68,\n      'datetime': datetime.datetime(2023, 7, 16, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1352.67,\n      'datetime': datetime.datetime(2023, 7, 16, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1350.31,\n      'datetime': datetime.datetime(2023, 7, 16, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1412.68,\n      'datetime': datetime.datetime(2023, 7, 16, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1448.37,\n      'datetime': datetime.datetime(2023, 7, 16, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1382.9,\n      'datetime': datetime.datetime(2023, 7, 16, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1405.98,\n      'datetime': datetime.datetime(2023, 7, 16, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1422.24,\n      'datetime': datetime.datetime(2023, 7, 16, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1352.48,\n      'datetime': datetime.datetime(2023, 7, 16, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1366.11,\n      'datetime': datetime.datetime(2023, 7, 16, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1370.2,\n      'datetime': datetime.datetime(2023, 7, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n  ])\n# ---\n# name: test_fetch_consumption_live\n  list([\n    dict({\n      'consumption': 2046.61,\n      'datetime': FakeDatetime(2024, 4, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 2066.08,\n      'datetime': FakeDatetime(2024, 4, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 2004.28,\n      'datetime': FakeDatetime(2024, 4, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1783.81,\n      'datetime': FakeDatetime(2024, 4, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1548.1,\n      'datetime': FakeDatetime(2024, 4, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1386.88,\n      'datetime': FakeDatetime(2024, 4, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1320.37,\n      'datetime': FakeDatetime(2024, 4, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1289.14,\n      'datetime': FakeDatetime(2024, 4, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1249.83,\n      'datetime': FakeDatetime(2024, 4, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1262.99,\n      'datetime': FakeDatetime(2024, 4, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1308.51,\n      'datetime': FakeDatetime(2024, 4, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'consumption': 1453.43,\n      'datetime': FakeDatetime(2024, 4, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GT',\n    }),\n  ])\n# ---\n# name: test_fetch_production_historical\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 646.85,\n        'gas': 0,\n        'geothermal': 32.5,\n        'hydro': 755.15,\n        'oil': 120.94375,\n        'solar': 0.99,\n        'wind': 24.45,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 646.58,\n        'gas': 0,\n        'geothermal': 29.79,\n        'hydro': 856.56,\n        'oil': 141.63375,\n        'solar': 0,\n        'wind': 17.5,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 646.87,\n        'gas': 0,\n        'geothermal': 32.37,\n        'hydro': 844.89,\n        'oil': 147.39375,\n        'solar': 0,\n        'wind': 37.05,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 645.67,\n        'gas': 0,\n        'geothermal': 31.9,\n        'hydro': 592.94,\n        'oil': 130.15375,\n        'solar': 0,\n        'wind': 6.5,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 645.66,\n        'gas': 0,\n        'geothermal': 32.72,\n        'hydro': 415.83,\n        'oil': 147.85375,\n        'solar': 0,\n        'wind': 29.06,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 645.56,\n        'gas': 0,\n        'geothermal': 32.94,\n        'hydro': 357.47,\n        'oil': 63.12375,\n        'solar': 0,\n        'wind': 81.45,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 642.73,\n        'gas': 0,\n        'geothermal': 32.64,\n        'hydro': 248.82,\n        'oil': 147.41,\n        'solar': 0,\n        'wind': 72.8,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 645.51,\n        'gas': 0,\n        'geothermal': 32.56,\n        'hydro': 247.63,\n        'oil': 88.99,\n        'solar': 0,\n        'wind': 85.67,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 625.63,\n        'gas': 0,\n        'geothermal': 32.45,\n        'hydro': 269.04,\n        'oil': 37.71,\n        'solar': 0,\n        'wind': 84.24,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 501.42,\n        'gas': 0,\n        'geothermal': 32.57,\n        'hydro': 341.65,\n        'oil': 61.21,\n        'solar': 0,\n        'wind': 91.68,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 401.97,\n        'gas': 0,\n        'geothermal': 31.48,\n        'hydro': 399.81,\n        'oil': 58.46,\n        'solar': 0,\n        'wind': 94.31,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 390.35,\n        'gas': 0,\n        'geothermal': 31.62,\n        'hydro': 429.84,\n        'oil': 27,\n        'solar': 0.84,\n        'wind': 97.22,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 392.48,\n        'gas': 0,\n        'geothermal': 31.36,\n        'hydro': 475.3,\n        'oil': 44.28,\n        'solar': 10.54,\n        'wind': 93.74,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 392.23,\n        'gas': 0,\n        'geothermal': 30.83,\n        'hydro': 558.06,\n        'oil': 23.92,\n        'solar': 20.52,\n        'wind': 97.33,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 525.43,\n        'gas': 0,\n        'geothermal': 30.44,\n        'hydro': 596.34,\n        'oil': 24.64,\n        'solar': 46.13,\n        'wind': 97.29,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 507.28,\n        'gas': 0,\n        'geothermal': 31.48,\n        'hydro': 581.02,\n        'oil': 25.83,\n        'solar': 67.54,\n        'wind': 79.35,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 472.48,\n        'gas': 0,\n        'geothermal': 30.83,\n        'hydro': 676.88,\n        'oil': 25.77,\n        'solar': 82.04,\n        'wind': 70.76,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 463.86,\n        'gas': 0,\n        'geothermal': 31.28,\n        'hydro': 689.19,\n        'oil': 27.72,\n        'solar': 79.66,\n        'wind': 70.43,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 459.65,\n        'gas': 0,\n        'geothermal': 24.62,\n        'hydro': 734.48,\n        'oil': 25.51,\n        'solar': 42.05,\n        'wind': 52.98,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 465.05,\n        'gas': 0,\n        'geothermal': 30.89,\n        'hydro': 711.11,\n        'oil': 63.44,\n        'solar': 17.4,\n        'wind': 44.74,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 553.4,\n        'gas': 0,\n        'geothermal': 31.09,\n        'hydro': 705.38,\n        'oil': 24,\n        'solar': 4.46,\n        'wind': 26.51,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.2,\n        'coal': 579.5,\n        'gas': 0,\n        'geothermal': 31.78,\n        'hydro': 774.33,\n        'oil': 105.65,\n        'solar': 0.75,\n        'wind': 27.53,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 625.5,\n        'gas': 0,\n        'geothermal': 31.93,\n        'hydro': 642.9,\n        'oil': 228.3,\n        'solar': 0,\n        'wind': 16.07,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 7, 16, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0,\n        'coal': 612.3,\n        'gas': 0,\n        'geothermal': 32.09,\n        'hydro': 673.49,\n        'oil': 178.9,\n        'solar': 0,\n        'wind': 16.16,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n  ])\n# ---\n# name: test_fetch_production_live\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 320.97,\n        'coal': 476.04,\n        'gas': 2.45,\n        'geothermal': 32,\n        'hydro': 671.14,\n        'oil': 359.01,\n        'solar': 0,\n        'unknown': 168.73,\n        'wind': 25.72,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 323.26,\n        'coal': 476.91,\n        'gas': 11.53,\n        'geothermal': 31.96,\n        'hydro': 628.87,\n        'oil': 323.92,\n        'solar': 0,\n        'unknown': 168.83,\n        'wind': 27.03,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 316.96,\n        'coal': 476.78,\n        'gas': 13,\n        'geothermal': 32.28,\n        'hydro': 624.92,\n        'oil': 324.23,\n        'solar': 0,\n        'unknown': 169.17,\n        'wind': 14.99,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 322.07,\n        'coal': 476.24,\n        'gas': 14.43,\n        'geothermal': 32.22,\n        'hydro': 460.45,\n        'oil': 322.46,\n        'solar': 0,\n        'unknown': 162.81,\n        'wind': 5.04,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 313.16,\n        'coal': 475.63,\n        'gas': 14.38,\n        'geothermal': 32.53,\n        'hydro': 304.46,\n        'oil': 348.93,\n        'solar': 0,\n        'unknown': 167.54,\n        'wind': 2.46,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 314.84,\n        'coal': 476.17,\n        'gas': 14.46,\n        'geothermal': 32.79,\n        'hydro': 211.5,\n        'oil': 274.99,\n        'solar': 0,\n        'unknown': 167.03,\n        'wind': 1.86,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 309.27,\n        'coal': 474.33,\n        'gas': 14.43,\n        'geothermal': 32.77,\n        'hydro': 172.63,\n        'oil': 199.04,\n        'solar': 0,\n        'unknown': 169.6,\n        'wind': 1.32,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 313.72,\n        'coal': 475.38,\n        'gas': 2,\n        'geothermal': 32.82,\n        'hydro': 115.6,\n        'oil': 170.97,\n        'solar': 0,\n        'unknown': 166.76,\n        'wind': 4.56,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 308.08,\n        'coal': 475.22,\n        'gas': 11.9,\n        'geothermal': 32.99,\n        'hydro': 108.85,\n        'oil': 150.89,\n        'solar': 0,\n        'unknown': 170,\n        'wind': 3.69,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 308.41,\n        'coal': 475.56,\n        'gas': 11.92,\n        'geothermal': 33.34,\n        'hydro': 92.28,\n        'oil': 188.95,\n        'solar': 0,\n        'unknown': 168.15,\n        'wind': 0.06,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 307.72,\n        'coal': 476.54,\n        'gas': 13.28,\n        'geothermal': 32.7,\n        'hydro': 193.68,\n        'oil': 133.98,\n        'solar': 0,\n        'unknown': 169.06,\n        'wind': 0,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 304.24,\n        'coal': 476.7,\n        'gas': 15.386,\n        'geothermal': 35.449,\n        'hydro': 256.285,\n        'oil': 209.18,\n        'solar': 0,\n        'unknown': 166.4,\n        'wind': 1.52,\n      }),\n      'source': 'amm.org.gt',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'GT',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_HN/test_fetch_exchange[GT-HN].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[GT-HN]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 27.6,\n      'sortedZoneKeys': 'GT->HN',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 21.5,\n      'sortedZoneKeys': 'GT->HN',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 22.7,\n      'sortedZoneKeys': 'GT->HN',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 23.3,\n      'sortedZoneKeys': 'GT->HN',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 14.4,\n      'sortedZoneKeys': 'GT->HN',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 5.9,\n      'sortedZoneKeys': 'GT->HN',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 5.2,\n      'sortedZoneKeys': 'GT->HN',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 24.4,\n      'sortedZoneKeys': 'GT->HN',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_HN/test_fetch_exchange[HN-NI].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[HN-NI]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': -98.5,\n      'sortedZoneKeys': 'HN->NI',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': -97.4,\n      'sortedZoneKeys': 'HN->NI',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': -98.0,\n      'sortedZoneKeys': 'HN->NI',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': -91.8,\n      'sortedZoneKeys': 'HN->NI',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': -101.6,\n      'sortedZoneKeys': 'HN->NI',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': -108.0,\n      'sortedZoneKeys': 'HN->NI',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': -82.7,\n      'sortedZoneKeys': 'HN->NI',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': -66.3,\n      'sortedZoneKeys': 'HN->NI',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_HN/test_fetch_exchange[HN-SV].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[HN-SV]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 58.5,\n      'sortedZoneKeys': 'HN->SV',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 51.5,\n      'sortedZoneKeys': 'HN->SV',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 33.9,\n      'sortedZoneKeys': 'HN->SV',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 23.8,\n      'sortedZoneKeys': 'HN->SV',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 36.3,\n      'sortedZoneKeys': 'HN->SV',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 45.0,\n      'sortedZoneKeys': 'HN->SV',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 28.7,\n      'sortedZoneKeys': 'HN->SV',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 25, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'netFlow': 20.1,\n      'sortedZoneKeys': 'HN->SV',\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_HN/test_fetch_exchange[HN-US].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[HN-US]\n  list([\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_HN.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n        'oil',\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 25, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'production': dict({\n        'biomass': 35.5,\n        'coal': 106.4,\n        'geothermal': 27.3,\n        'hydro': 455.6,\n        'oil': 653.4,\n        'solar': 0.0,\n        'wind': 115.1,\n      }),\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'HN',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 25, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'production': dict({\n        'biomass': 43.4,\n        'coal': 105.8,\n        'geothermal': 27.6,\n        'hydro': 440.7,\n        'oil': 608.5,\n        'solar': 0.0,\n        'wind': 106.2,\n      }),\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'HN',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 25, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'production': dict({\n        'biomass': 35.3,\n        'coal': 105.6,\n        'geothermal': 27.7,\n        'hydro': 436.4,\n        'oil': 530.4,\n        'solar': 0.0,\n        'wind': 114.6,\n      }),\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'HN',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 25, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'production': dict({\n        'biomass': 35.8,\n        'coal': 106.1,\n        'geothermal': 27.8,\n        'hydro': 449.6,\n        'oil': 484.8,\n        'solar': 0.0,\n        'wind': 108.7,\n      }),\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'HN',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 25, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'production': dict({\n        'biomass': 35.4,\n        'coal': 106.3,\n        'geothermal': 28.0,\n        'hydro': 455.7,\n        'oil': 484.1,\n        'solar': 0.0,\n        'wind': 105.2,\n      }),\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'HN',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 25, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'production': dict({\n        'biomass': 39.7,\n        'coal': 106.0,\n        'geothermal': 28.3,\n        'hydro': 475.5,\n        'oil': 483.2,\n        'solar': 0.3,\n        'wind': 107.8,\n      }),\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'HN',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 25, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'production': dict({\n        'biomass': 42.3,\n        'coal': 106.0,\n        'geothermal': 28.2,\n        'hydro': 449.2,\n        'oil': 436.7,\n        'solar': 77.9,\n        'wind': 125.9,\n      }),\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'HN',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 25, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Tegucigalpa')),\n      'production': dict({\n        'biomass': 47.4,\n        'coal': 106.1,\n        'geothermal': 27.9,\n        'hydro': 439.1,\n        'oil': 353.9,\n        'solar': 233.0,\n        'wind': 106.5,\n      }),\n      'source': 'ods.org.hn',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'HN',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_IEMOP/test_production[PH-LU].ambr",
    "content": "# serializer version: 1\n# name: test_production[PH-LU]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 0, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5637.4225),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(645.5),\n        'oil': np.float64(27.8338),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(8.4),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 5, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5628.8619),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(645.5),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(9.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 10, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5579.0433),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(645.5),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(9.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 15, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5530.5807),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(645.5),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(10.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 20, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5496.31),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(645.5),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(10.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 25, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5469.13),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(644.8),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(9.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 30, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5445.12),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(644.8),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(9.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 35, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5424.35),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(639.8),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(8.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 40, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5403.3),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(639.8),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(8.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 45, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5386.1),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(639.8),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(8.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 50, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5351.7597),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(639.8),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(8.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 55, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(34.9),\n        'coal': np.float64(5351.6),\n        'gas': np.float64(2628.4),\n        'geothermal': np.float64(484.0),\n        'hydro': np.float64(639.8),\n        'oil': np.float64(0.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(50.0),\n        'wind': np.float64(9.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n        'hydro': np.float64(306.0),\n      }),\n      'zoneKey': 'PH-LU',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_IEMOP/test_production[PH-MI].ambr",
    "content": "# serializer version: 1\n# name: test_production[PH-MI]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 0, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(1039.0631),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(645.4),\n        'oil': np.float64(134.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 5, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(1039.8314),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(645.4),\n        'oil': np.float64(134.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 10, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(1024.039),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(645.4),\n        'oil': np.float64(134.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 15, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(1030.8),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(645.4),\n        'oil': np.float64(125.5),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 20, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(1008.601),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(645.4),\n        'oil': np.float64(125.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 25, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(1002.6),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(645.4),\n        'oil': np.float64(125.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 30, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(1001.6925),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(645.4),\n        'oil': np.float64(125.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 35, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(986.69),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(645.4),\n        'oil': np.float64(116.5),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 40, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(976.8124),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(644.4),\n        'oil': np.float64(115.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 45, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(961.936),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(644.4),\n        'oil': np.float64(115.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 50, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(942.28),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(644.4),\n        'oil': np.float64(115.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 55, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(22.5),\n        'coal': np.float64(927.1405),\n        'geothermal': np.float64(83.2),\n        'hydro': np.float64(644.4),\n        'oil': np.float64(115.0),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(0.0),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-0.0),\n      }),\n      'zoneKey': 'PH-MI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_IEMOP/test_production[PH-VI].ambr",
    "content": "# serializer version: 1\n# name: test_production[PH-VI]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 0, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(984.4905),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(15.8),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(6.3),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 5, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(1008.2105),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(14.8),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(6.3),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 10, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(1018.81),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(14.8),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(6.3),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 15, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(1003.81),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(14.8),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(7.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 20, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(979.31),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(14.8),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(7.4),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 25, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(975.2524),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(15.08),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(7.5),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 30, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(968.0),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(15.77),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(7.3),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 35, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(949.7086),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(16.73),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(7.3),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 40, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(943.0),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(16.7),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(7.3),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 45, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(930.4156),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(16.49),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(7.3),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 50, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(915.65),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(16.85),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(7.3),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 13, 23, 55, tzinfo=<DstTzInfo 'Asia/Manila' PST+8:00:00 STD>),\n      'production': dict({\n        'biomass': np.float64(31.0),\n        'coal': np.float64(899.99),\n        'geothermal': np.float64(309.4),\n        'hydro': np.float64(15.3),\n        'oil': np.float64(16.37),\n        'solar': np.float64(0.0),\n        'unknown': np.float64(320.0),\n        'wind': np.float64(7.3),\n      }),\n      'source': 'iemop.ph',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': np.float64(-10.0),\n      }),\n      'zoneKey': 'PH-VI',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_IN.ambr",
    "content": "# serializer version: 1\n# name: test_parse_15m_production_grid_india_report\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38508.040242,\n        'gas': 905.87768,\n        'hydro': 9418.427258,\n        'nuclear': 1298.912855,\n        'solar': 40.698949,\n        'unknown': 612.583028,\n        'wind': 3141.624502,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38703.098615,\n        'gas': 916.171745,\n        'hydro': 8837.056556,\n        'nuclear': 1293.092633,\n        'solar': 40.261326,\n        'unknown': 619.373105,\n        'wind': 3146.627928,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38284.887982,\n        'gas': 887.863067,\n        'hydro': 8803.771974,\n        'nuclear': 1291.286358,\n        'solar': 39.38608,\n        'unknown': 619.963546,\n        'wind': 3083.426764,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38105.361189,\n        'gas': 887.071216,\n        'hydro': 8461.495521,\n        'nuclear': 1297.106579,\n        'solar': 38.510833,\n        'unknown': 624.687078,\n        'wind': 3060.516343,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37979.96652,\n        'gas': 872.224008,\n        'hydro': 8049.876189,\n        'nuclear': 1294.698211,\n        'solar': 36.760341,\n        'unknown': 624.391857,\n        'wind': 3027.862408,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38074.983245,\n        'gas': 857.970688,\n        'hydro': 7127.893264,\n        'nuclear': 1299.314249,\n        'solar': 34.572225,\n        'unknown': 623.210974,\n        'wind': 2969.137994,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38029.758939,\n        'gas': 836.78867,\n        'hydro': 6437.792928,\n        'nuclear': 1299.514946,\n        'solar': 31.508864,\n        'unknown': 620.258767,\n        'wind': 2929.637267,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37928.803669,\n        'gas': 798.383891,\n        'hydro': 6175.954215,\n        'nuclear': 1292.691239,\n        'solar': 29.320748,\n        'unknown': 608.449937,\n        'wind': 2932.533987,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37860.510398,\n        'gas': 760.573,\n        'hydro': 5586.262368,\n        'nuclear': 1293.494028,\n        'solar': 27.570256,\n        'unknown': 604.021626,\n        'wind': 2856.165914,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37793.58756,\n        'gas': 755.030042,\n        'hydro': 5364.365154,\n        'nuclear': 1292.891936,\n        'solar': 26.69501,\n        'unknown': 602.840743,\n        'wind': 2857.745943,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37608.807439,\n        'gas': 731.076546,\n        'hydro': 5234.00054,\n        'nuclear': 1297.708671,\n        'solar': 22.756402,\n        'unknown': 604.612068,\n        'wind': 2834.835521,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37579.571523,\n        'gas': 728.107104,\n        'hydro': 5140.80371,\n        'nuclear': 1295.701698,\n        'solar': 26.69501,\n        'unknown': 618.487442,\n        'wind': 2765.840918,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37439.558897,\n        'gas': 714.051747,\n        'hydro': 5129.154107,\n        'nuclear': 1294.698211,\n        'solar': 27.570256,\n        'unknown': 606.383392,\n        'wind': 2685.786111,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37386.340395,\n        'gas': 696.433059,\n        'hydro': 4993.796806,\n        'nuclear': 1300.317736,\n        'solar': 29.320748,\n        'unknown': 598.707653,\n        'wind': 2596.251129,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37333.80711,\n        'gas': 697.818799,\n        'hydro': 5106.409642,\n        'nuclear': 1298.912855,\n        'solar': 27.570256,\n        'unknown': 596.345887,\n        'wind': 2561.227151,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37277.162524,\n        'gas': 689.900288,\n        'hydro': 5121.387704,\n        'nuclear': 1298.712157,\n        'solar': 26.257386,\n        'unknown': 610.811703,\n        'wind': 2558.067093,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37215.949826,\n        'gas': 683.763441,\n        'hydro': 5058.146998,\n        'nuclear': 1300.518433,\n        'solar': 26.257386,\n        'unknown': 614.944794,\n        'wind': 2468.795449,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37325.584509,\n        'gas': 688.514548,\n        'hydro': 5225.124652,\n        'nuclear': 1301.923314,\n        'solar': 27.570256,\n        'unknown': 607.564275,\n        'wind': 2468.005435,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37485.468421,\n        'gas': 690.296213,\n        'hydro': 5185.183153,\n        'nuclear': 1304.331681,\n        'solar': 24.944517,\n        'unknown': 618.192222,\n        'wind': 2408.754344,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37759.783533,\n        'gas': 691.088064,\n        'hydro': 5251.752318,\n        'nuclear': 1305.736562,\n        'solar': 24.944517,\n        'unknown': 608.745158,\n        'wind': 2355.296693,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37894.086019,\n        'gas': 687.524734,\n        'hydro': 5483.634906,\n        'nuclear': 1302.9268,\n        'solar': 24.506894,\n        'unknown': 612.878248,\n        'wind': 2301.839042,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38256.565688,\n        'gas': 703.361757,\n        'hydro': 5952.392771,\n        'nuclear': 1304.532379,\n        'solar': 25.38214,\n        'unknown': 604.907289,\n        'wind': 2269.975122,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38675.91835,\n        'gas': 742.162462,\n        'hydro': 6195.370221,\n        'nuclear': 1295.300303,\n        'solar': 28.445502,\n        'unknown': 621.734871,\n        'wind': 2207.563974,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38807.479969,\n        'gas': 727.909141,\n        'hydro': 7059.105127,\n        'nuclear': 1297.909368,\n        'solar': 28.445502,\n        'unknown': 619.373105,\n        'wind': 2170.696628,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38871.433534,\n        'gas': 739.390983,\n        'hydro': 7616.067135,\n        'nuclear': 1301.923314,\n        'solar': 32.821733,\n        'unknown': 612.583028,\n        'wind': 2156.476366,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39159.681387,\n        'gas': 771.065027,\n        'hydro': 8285.087236,\n        'nuclear': 1308.14493,\n        'solar': 160.60768,\n        'unknown': 631.181934,\n        'wind': 2114.078919,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39120.624031,\n        'gas': 796.998152,\n        'hydro': 9340.20849,\n        'nuclear': 1300.518433,\n        'solar': 330.843069,\n        'unknown': 642.400322,\n        'wind': 2058.251225,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38916.886246,\n        'gas': 757.207633,\n        'hydro': 9011.24587,\n        'nuclear': 1308.747022,\n        'solar': 1006.533147,\n        'unknown': 618.782663,\n        'wind': 2030.074039,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38401.603237,\n        'gas': 708.112863,\n        'hydro': 8569.11567,\n        'nuclear': 1311.356086,\n        'solar': 2009.565309,\n        'unknown': 620.258767,\n        'wind': 1931.058883,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38092.34207,\n        'gas': 693.463618,\n        'hydro': 7582.22781,\n        'nuclear': 1309.148416,\n        'solar': 3442.780985,\n        'unknown': 631.772376,\n        'wind': 1863.117632,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 36947.344854,\n        'gas': 705.341384,\n        'hydro': 7332.038701,\n        'nuclear': 1320.989556,\n        'solar': 5232.659494,\n        'unknown': 645.352529,\n        'wind': 1804.12988,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 35869.270474,\n        'gas': 676.240856,\n        'hydro': 6881.587356,\n        'nuclear': 1308.747022,\n        'solar': 7289.925721,\n        'unknown': 655.094814,\n        'wind': 1710.118149,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 34733.409481,\n        'gas': 697.818799,\n        'hydro': 6645.266823,\n        'nuclear': 1315.370032,\n        'solar': 9381.764174,\n        'unknown': 651.256944,\n        'wind': 1589.7726,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 34101.182812,\n        'gas': 693.265655,\n        'hydro': 6216.450456,\n        'nuclear': 1309.750508,\n        'solar': 11507.737229,\n        'unknown': 664.541877,\n        'wind': 1453.100084,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 33555.750266,\n        'gas': 689.504362,\n        'hydro': 5895.808982,\n        'nuclear': 1313.162362,\n        'solar': 13629.771676,\n        'unknown': 640.628998,\n        'wind': 1306.420717,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 33037.041174,\n        'gas': 670.895861,\n        'hydro': 5931.312536,\n        'nuclear': 1306.338654,\n        'solar': 15538.246047,\n        'unknown': 671.627175,\n        'wind': 1151.314528,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 32465.341985,\n        'gas': 671.291786,\n        'hydro': 6063.896122,\n        'nuclear': 1305.13447,\n        'solar': 17286.112737,\n        'unknown': 681.074239,\n        'wind': 996.471678,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 32380.831917,\n        'gas': 686.732883,\n        'hydro': 6192.596506,\n        'nuclear': 1294.898909,\n        'solar': 19241.41278,\n        'unknown': 668.379747,\n        'wind': 912.20346,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 32214.095837,\n        'gas': 667.332531,\n        'hydro': 6111.604023,\n        'nuclear': 1301.521919,\n        'solar': 20985.340863,\n        'unknown': 664.246657,\n        'wind': 860.325838,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 31819.41098,\n        'gas': 688.514548,\n        'hydro': 6235.31172,\n        'nuclear': 1291.08566,\n        'solar': 22280.267637,\n        'unknown': 669.56063,\n        'wind': 838.205431,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 31436.146402,\n        'gas': 687.326772,\n        'hydro': 6053.910747,\n        'nuclear': 1296.905882,\n        'solar': 23061.424884,\n        'unknown': 670.446292,\n        'wind': 811.344936,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 30947.586847,\n        'gas': 664.363089,\n        'hydro': 5746.583105,\n        'nuclear': 1292.490541,\n        'solar': 24360.290266,\n        'unknown': 665.72276,\n        'wind': 814.241656,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 30631.701918,\n        'gas': 683.763441,\n        'hydro': 5509.153086,\n        'nuclear': 1290.282871,\n        'solar': 25377.763991,\n        'unknown': 690.226081,\n        'wind': 829.515271,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 30425.223266,\n        'gas': 666.936605,\n        'hydro': 5355.489265,\n        'nuclear': 1286.268925,\n        'solar': 25580.383489,\n        'unknown': 656.866138,\n        'wind': 861.115853,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 30091.751106,\n        'gas': 664.165126,\n        'hydro': 5394.321278,\n        'nuclear': 1291.687752,\n        'solar': 25814.074229,\n        'unknown': 659.227904,\n        'wind': 880.076202,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29809.213393,\n        'gas': 683.565479,\n        'hydro': 5145.241655,\n        'nuclear': 1289.480082,\n        'solar': 26228.065688,\n        'unknown': 679.598135,\n        'wind': 769.210827,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29598.395034,\n        'gas': 684.159367,\n        'hydro': 5257.299748,\n        'nuclear': 1282.455677,\n        'solar': 26333.532857,\n        'unknown': 677.82681,\n        'wind': 915.363518,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29354.22946,\n        'gas': 681.189925,\n        'hydro': 5235.66477,\n        'nuclear': 1286.67032,\n        'solar': 27123.880189,\n        'unknown': 666.903643,\n        'wind': 918.523576,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 28957.717358,\n        'gas': 680.002149,\n        'hydro': 5243.985915,\n        'nuclear': 1290.082174,\n        'solar': 27368.511506,\n        'unknown': 669.265409,\n        'wind': 920.103605,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 28675.636456,\n        'gas': 685.545106,\n        'hydro': 5137.475252,\n        'nuclear': 1279.24452,\n        'solar': 27625.833893,\n        'unknown': 677.82681,\n        'wind': 944.857394,\n      }),\n      'source': 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5271.168324,\n        'nuclear': 1267.202683,\n        'solar': 27984.684841,\n        'unknown': 676.941148,\n        'wind': 966.187787,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 28027.192989,\n        'gas': 681.981776,\n        'hydro': 5212.365562,\n        'nuclear': 1275.431272,\n        'solar': 27500.673684,\n        'unknown': 637.67679,\n        'wind': 958.55098,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 27994.759395,\n        'gas': 681.585851,\n        'hydro': 5094.760039,\n        'nuclear': 1267.804775,\n        'solar': 27188.648409,\n        'unknown': 645.057309,\n        'wind': 975.141285,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 28374.59789,\n        'gas': 685.149181,\n        'hydro': 5272.27781,\n        'nuclear': 1270.614537,\n        'solar': 26928.26266,\n        'unknown': 628.229727,\n        'wind': 966.714463,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 28939.216505,\n        'gas': 691.48399,\n        'hydro': 5947.400084,\n        'nuclear': 1271.417326,\n        'solar': 17869.026716,\n        'unknown': 561.21462,\n        'wind': 448.464923,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29155.745003,\n        'gas': 692.473804,\n        'hydro': 5970.699292,\n        'nuclear': 1271.216629,\n        'solar': 17547.811355,\n        'unknown': 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'coal': 31166.856213,\n        'gas': 698.016762,\n        'hydro': 5675.021254,\n        'nuclear': 1239.105062,\n        'solar': 24754.151063,\n        'unknown': 620.553988,\n        'wind': 1068.099663,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 31810.959973,\n        'gas': 719.198779,\n        'hydro': 5819.254443,\n        'nuclear': 1241.312733,\n        'solar': 24100.779764,\n        'unknown': 609.63082,\n        'wind': 1097.330201,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 32550.765675,\n        'gas': 703.361757,\n        'hydro': 6209.79354,\n        'nuclear': 1232.682749,\n        'solar': 23314.808663,\n        'unknown': 611.106924,\n        'wind': 1111.023787,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 33124.74892,\n        'gas': 706.529161,\n        'hydro': 5858.641198,\n        'nuclear': 1245.92877,\n        'solar': 22829.047014,\n        'unknown': 596.050666,\n        'wind': 1176.594994,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 33754.919939,\n        'gas': 705.935273,\n        'hydro': 6213.121998,\n        'nuclear': 1235.693208,\n        'solar': 21541.997455,\n        'unknown': 597.52677,\n        'wind': 1224.522543,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 34331.18724,\n        'gas': 719.594705,\n        'hydro': 6531.544501,\n        'nuclear': 1242.516916,\n        'solar': 19949.049345,\n        'unknown': 606.383392,\n        'wind': 1251.383037,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 35036.732103,\n        'gas': 729.294881,\n        'hydro': 6620.858129,\n        'nuclear': 1243.319705,\n        'solar': 18194.618308,\n        'unknown': 582.765733,\n        'wind': 1289.830412,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 35763.747092,\n        'gas': 750.476898,\n        'hydro': 6507.69055,\n        'nuclear': 1251.748992,\n        'solar': 16595.105851,\n        'unknown': 595.165004,\n        'wind': 1363.828441,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 36665.492357,\n        'gas': 783.140757,\n        'hydro': 6714.054959,\n        'nuclear': 1250.745505,\n        'solar': 15005.658725,\n        'unknown': 580.108747,\n        'wind': 1399.642433,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37254.321965,\n        'gas': 851.635879,\n        'hydro': 6884.915814,\n        'nuclear': 1258.572699,\n        'solar': 13141.821911,\n        'unknown': 567.119034,\n        'wind': 1406.752564,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37739.455435,\n        'gas': 914.39008,\n        'hydro': 7180.593852,\n        'nuclear': 1256.766424,\n        'solar': 11181.270391,\n        'unknown': 588.374927,\n        'wind': 1437.563132,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 37637.129732,\n        'gas': 953.58671,\n        'hydro': 7233.294441,\n        'nuclear': 1260.579672,\n        'solar': 9378.263189,\n        'unknown': 558.852854,\n        'wind': 1545.795124,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38109.472489,\n        'gas': 1034.553487,\n        'hydro': 7386.958261,\n        'nuclear': 1261.382461,\n        'solar': 7423.400769,\n        'unknown': 564.166827,\n        'wind': 1606.099568,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38114.725818,\n        'gas': 1121.855073,\n        'hydro': 8148.620449,\n        'nuclear': 1264.794315,\n        'solar': 5375.76225,\n        'unknown': 565.34771,\n        'wind': 1670.354084,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38474.007809,\n        'gas': 1124.230627,\n        'hydro': 8669.52416,\n        'nuclear': 1262.185251,\n        'solar': 3435.779015,\n        'unknown': 561.50984,\n        'wind': 1707.221429,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38541.387458,\n        'gas': 1093.546396,\n        'hydro': 9152.150601,\n        'nuclear': 1274.628483,\n        'solar': 2180.675944,\n        'unknown': 570.661683,\n        'wind': 1819.140156,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38758.829578,\n        'gas': 1288.143808,\n        'hydro': 11092.086996,\n        'nuclear': 1280.248007,\n        'solar': 1149.635903,\n        'unknown': 566.528593,\n        'wind': 1859.16756,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38954.573168,\n        'gas': 1331.101731,\n        'hydro': 12411.265934,\n        'nuclear': 1274.628483,\n        'solar': 498.452719,\n        'unknown': 580.699188,\n        'wind': 1919.99868,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39433.768093,\n        'gas': 1209.750547,\n        'hydro': 12785.717483,\n        'nuclear': 1276.234061,\n        'solar': 194.30466,\n        'unknown': 570.956904,\n        'wind': 1934.218941,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39558.934356,\n        'gas': 1145.412644,\n        'hydro': 13415.905572,\n        'nuclear': 1280.649401,\n        'solar': 112.906762,\n        'unknown': 580.699188,\n        'wind': 1961.079436,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39242.135804,\n        'gas': 1239.84089,\n        'hydro': 13666.094681,\n        'nuclear': 1280.248007,\n        'solar': 132.599802,\n        'unknown': 578.042202,\n        'wind': 1988.993283,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39015.329054,\n        'gas': 1182.629647,\n        'hydro': 13156.840574,\n        'nuclear': 1288.476595,\n        'solar': 151.417595,\n        'unknown': 578.042202,\n        'wind': 2136.199326,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38986.778356,\n        'gas': 1132.149138,\n        'hydro': 12735.235867,\n        'nuclear': 1279.24452,\n        'solar': 137.413656,\n        'unknown': 566.823814,\n        'wind': 2223.364264,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39240.765371,\n        'gas': 1101.66287,\n        'hydro': 11783.851561,\n        'nuclear': 1286.469623,\n        'solar': 161.045303,\n        'unknown': 593.39368,\n        'wind': 2363.196839,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39114.000269,\n        'gas': 1094.734172,\n        'hydro': 11292.349232,\n        'nuclear': 1289.881477,\n        'solar': 157.106696,\n        'unknown': 587.489265,\n        'wind': 2460.631966,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39299.694012,\n        'gas': 1081.074741,\n        'hydro': 10746.482085,\n        'nuclear': 1285.867531,\n        'solar': 149.22948,\n        'unknown': 595.460225,\n        'wind': 2503.292751,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39097.555066,\n        'gas': 1082.064554,\n        'hydro': 10776.992952,\n        'nuclear': 1290.282871,\n        'solar': 147.478987,\n        'unknown': 586.308382,\n        'wind': 2551.2203,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39156.94052,\n        'gas': 1085.627885,\n        'hydro': 10335.417495,\n        'nuclear': 1288.87799,\n        'solar': 142.665133,\n        'unknown': 597.52677,\n        'wind': 2673.672554,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39164.70631,\n        'gas': 1080.084927,\n        'hydro': 10985.576333,\n        'nuclear': 1280.649401,\n        'solar': 131.724555,\n        'unknown': 596.050666,\n        'wind': 2575.710751,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38858.414415,\n        'gas': 1085.231959,\n        'hydro': 11489.837752,\n        'nuclear': 1278.040336,\n        'solar': 124.722586,\n        'unknown': 594.574563,\n        'wind': 2617.581522,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38851.105436,\n        'gas': 1102.256758,\n        'hydro': 11731.150973,\n        'nuclear': 1278.441731,\n        'solar': 98.027576,\n        'unknown': 593.098459,\n        'wind': 2610.208053,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39129.303443,\n        'gas': 1134.920617,\n        'hydro': 11616.873907,\n        'nuclear': 1269.008958,\n        'solar': 93.213722,\n        'unknown': 595.755446,\n        'wind': 2591.77438,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39242.592615,\n        'gas': 1175.502987,\n        'hydro': 11737.807889,\n        'nuclear': 1273.825693,\n        'solar': 87.086998,\n        'unknown': 595.165004,\n        'wind': 2596.777805,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39065.121473,\n        'gas': 1233.902007,\n        'hydro': 11665.691295,\n        'nuclear': 1279.445217,\n        'solar': 74.833551,\n        'unknown': 573.909111,\n        'wind': 2569.653973,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39013.730215,\n        'gas': 1231.724416,\n        'hydro': 11346.159306,\n        'nuclear': 1275.029877,\n        'solar': 57.76625,\n        'unknown': 592.508018,\n        'wind': 2671.565849,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39111.487807,\n        'gas': 1231.724416,\n        'hydro': 11077.108934,\n        'nuclear': 1281.050796,\n        'solar': 63.455351,\n        'unknown': 588.670148,\n        'wind': 2725.550176,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 38947.264189,\n        'gas': 1090.378991,\n        'hydro': 11034.39372,\n        'nuclear': 1278.241034,\n        'solar': 64.330597,\n        'unknown': 583.060954,\n        'wind': 2751.357318,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 39064.436256,\n        'gas': 1004.265182,\n        'hydro': 10571.738029,\n        'nuclear': 1284.261952,\n        'solar': 58.641496,\n        'unknown': 585.127499,\n        'wind': 2796.651485,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-NO',\n    }),\n  ])\n# ---\n# name: test_parse_daily_production_grid_india_report\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Kolkata')),\n      'production': dict({\n        'coal': 29960.0,\n        'gas': 0.0,\n        'hydro': 1070.416667,\n        'nuclear': 0.0,\n        'solar': 169.166667,\n        'unknown': 40.833333,\n        'wind': 0.0,\n      }),\n      'source': 'grid-india.in',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IN-EA',\n    }),\n  ])\n# ---\n# name: test_scale_15min_production\n  '''\n  [\n    {\n      \"TIME\": \"0:00\",\n      \"nuclear\": 3236.0,\n      \"wind\": 5965.0,\n      \"solar\": 46.5,\n      \"hydro\": 8489.0,\n      \"gas\": 2288.0,\n      \"coal\": 84297.5,\n      \"unknown\": 1037.5\n    },\n    {\n      \"TIME\": \"0:15\",\n      \"nuclear\": 3221.5,\n      \"wind\": 5974.5,\n      \"solar\": 46.0,\n      \"hydro\": 7965.0,\n      \"gas\": 2314.0,\n      \"coal\": 84724.5,\n      \"unknown\": 1049.0\n    },\n    {\n      \"TIME\": \"0:30\",\n      \"nuclear\": 3217.0,\n      \"wind\": 5854.5,\n      \"solar\": 45.0,\n      \"hydro\": 7935.0,\n      \"gas\": 2242.5,\n      \"coal\": 83809.0,\n      \"unknown\": 1050.0\n    },\n    {\n      \"TIME\": \"0:45\",\n      \"nuclear\": 3231.5,\n      \"wind\": 5811.0,\n      \"solar\": 44.0,\n      \"hydro\": 7626.5,\n      \"gas\": 2240.5,\n      \"coal\": 83416.0,\n      \"unknown\": 1058.0\n    },\n    {\n      \"TIME\": \"1:00\",\n      \"nuclear\": 3225.5,\n      \"wind\": 5749.0,\n      \"solar\": 42.0,\n      \"hydro\": 7255.5,\n      \"gas\": 2203.0,\n      \"coal\": 83141.5,\n      \"unknown\": 1057.5\n    },\n    {\n      \"TIME\": \"1:15\",\n      \"nuclear\": 3237.0,\n      \"wind\": 5637.5,\n      \"solar\": 39.5,\n      \"hydro\": 6424.5,\n      \"gas\": 2167.0,\n      \"coal\": 83349.5,\n      \"unknown\": 1055.5\n    },\n    {\n      \"TIME\": \"1:30\",\n      \"nuclear\": 3237.5,\n      \"wind\": 5562.5,\n      \"solar\": 36.0,\n      \"hydro\": 5802.5,\n      \"gas\": 2113.5,\n      \"coal\": 83250.5,\n      \"unknown\": 1050.5\n    },\n    {\n      \"TIME\": \"1:45\",\n      \"nuclear\": 3220.5,\n      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  \"hydro\": 12317.5,\n      \"gas\": 3131.5,\n      \"coal\": 85904.5,\n      \"unknown\": 979.0\n    },\n    {\n      \"TIME\": \"19:45\",\n      \"nuclear\": 3210.0,\n      \"wind\": 4056.0,\n      \"solar\": 173.0,\n      \"hydro\": 11858.5,\n      \"gas\": 2987.0,\n      \"coal\": 85408.0,\n      \"unknown\": 979.0\n    },\n    {\n      \"TIME\": \"20:00\",\n      \"nuclear\": 3187.0,\n      \"wind\": 4221.5,\n      \"solar\": 157.0,\n      \"hydro\": 11478.5,\n      \"gas\": 2859.5,\n      \"coal\": 85345.5,\n      \"unknown\": 960.0\n    },\n    {\n      \"TIME\": \"20:15\",\n      \"nuclear\": 3205.0,\n      \"wind\": 4487.0,\n      \"solar\": 184.0,\n      \"hydro\": 10621.0,\n      \"gas\": 2782.5,\n      \"coal\": 85901.5,\n      \"unknown\": 1005.0\n    },\n    {\n      \"TIME\": \"20:30\",\n      \"nuclear\": 3213.5,\n      \"wind\": 4672.0,\n      \"solar\": 179.5,\n      \"hydro\": 10178.0,\n      \"gas\": 2765.0,\n      \"coal\": 85624.0,\n      \"unknown\": 995.0\n    },\n    {\n      \"TIME\": \"20:45\",\n      \"nuclear\": 3203.5,\n      \"wind\": 4753.0,\n      \"solar\": 170.5,\n      \"hydro\": 9686.0,\n      \"gas\": 2730.5,\n      \"coal\": 86030.5,\n      \"unknown\": 1008.5\n    },\n    {\n      \"TIME\": \"21:00\",\n      \"nuclear\": 3214.5,\n      \"wind\": 4844.0,\n      \"solar\": 168.5,\n      \"hydro\": 9713.5,\n      \"gas\": 2733.0,\n      \"coal\": 85588.0,\n      \"unknown\": 993.0\n    },\n    {\n      \"TIME\": \"21:15\",\n      \"nuclear\": 3211.0,\n      \"wind\": 5076.5,\n      \"solar\": 163.0,\n      \"hydro\": 9315.5,\n      \"gas\": 2742.0,\n      \"coal\": 85718.0,\n      \"unknown\": 1012.0\n    },\n    {\n      \"TIME\": \"21:30\",\n      \"nuclear\": 3190.5,\n      \"wind\": 4890.5,\n      \"solar\": 150.5,\n      \"hydro\": 9901.5,\n      \"gas\": 2728.0,\n      \"coal\": 85735.0,\n      \"unknown\": 1009.5\n    },\n    {\n      \"TIME\": \"21:45\",\n      \"nuclear\": 3184.0,\n      \"wind\": 4970.0,\n      \"solar\": 142.5,\n      \"hydro\": 10356.0,\n      \"gas\": 2741.0,\n      \"coal\": 85064.5,\n      \"unknown\": 1007.0\n    },\n    {\n      \"TIME\": \"22:00\",\n      \"nuclear\": 3185.0,\n      \"wind\": 4956.0,\n      \"solar\": 112.0,\n      \"hydro\": 10573.5,\n      \"gas\": 2784.0,\n      \"coal\": 85048.5,\n      \"unknown\": 1004.5\n    },\n    {\n      \"TIME\": \"22:15\",\n      \"nuclear\": 3161.5,\n      \"wind\": 4921.0,\n      \"solar\": 106.5,\n      \"hydro\": 10470.5,\n      \"gas\": 2866.5,\n      \"coal\": 85657.5,\n      \"unknown\": 1009.0\n    },\n    {\n      \"TIME\": \"22:30\",\n      \"nuclear\": 3173.5,\n      \"wind\": 4930.5,\n      \"solar\": 99.5,\n      \"hydro\": 10579.5,\n      \"gas\": 2969.0,\n      \"coal\": 85905.5,\n      \"unknown\": 1008.0\n    },\n    {\n      \"TIME\": \"22:45\",\n      \"nuclear\": 3187.5,\n      \"wind\": 4879.0,\n      \"solar\": 85.5,\n      \"hydro\": 10514.5,\n      \"gas\": 3116.5,\n      \"coal\": 85517.0,\n      \"unknown\": 972.0\n    },\n    {\n      \"TIME\": \"23:00\",\n      \"nuclear\": 3176.5,\n      \"wind\": 5072.5,\n      \"solar\": 66.0,\n      \"hydro\": 10226.5,\n      \"gas\": 3111.0,\n      \"coal\": 85404.5,\n      \"unknown\": 1003.5\n    },\n    {\n      \"TIME\": \"23:15\",\n      \"nuclear\": 3191.5,\n      \"wind\": 5175.0,\n      \"solar\": 72.5,\n      \"hydro\": 9984.0,\n      \"gas\": 3111.0,\n      \"coal\": 85618.5,\n      \"unknown\": 997.0\n    },\n    {\n      \"TIME\": \"23:30\",\n      \"nuclear\": 3184.5,\n      \"wind\": 5224.0,\n      \"solar\": 73.5,\n      \"hydro\": 9945.5,\n      \"gas\": 2754.0,\n      \"coal\": 85259.0,\n      \"unknown\": 987.5\n    },\n    {\n      \"TIME\": \"23:45\",\n      \"nuclear\": 3199.5,\n      \"wind\": 5310.0,\n      \"solar\": 67.0,\n      \"hydro\": 9528.5,\n      \"gas\": 2536.5,\n      \"coal\": 85515.5,\n      \"unknown\": 991.0\n    }\n  ]\n  '''\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_JAO/test_fetch_core_external_atc_day_ahead_de_dk_dk1.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_core_external_atc_day_ahead_de_dk_dk1\n  list([\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2260.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2260.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2260.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2260.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2298.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2298.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2298.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2298.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2339.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2339.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2339.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2339.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2419.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2419.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2419.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2419.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2455.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2455.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2455.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2455.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2473.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2473.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2473.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2473.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2502.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2502.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2502.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2502.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2523.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2523.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2523.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2523.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2511.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2511.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2511.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2511.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': 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<EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2518.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2518.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2518.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2518.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2340.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2340.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2340.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2340.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2349.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2349.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2349.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2349.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2332.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2332.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2332.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2332.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2325.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2325.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2325.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2325.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2315.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2315.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2315.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2315.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2294.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2294.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2294.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2294.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2399.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2399.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2399.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 2399.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 3500.0,\n      'capacityImport': 3500.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->DK-DK1',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_JAO/test_fetch_core_max_bex_day_ahead_de_fr.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_core_max_bex_day_ahead_de_fr\n  list([\n    dict({\n      'capacityExport': 13596.0,\n      'capacityImport': 3222.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13494.0,\n      'capacityImport': 3195.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13434.0,\n      'capacityImport': 3198.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 14018.0,\n      'capacityImport': 3184.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 14711.0,\n      'capacityImport': 3149.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 14546.0,\n      'capacityImport': 2950.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13477.0,\n      'capacityImport': 3214.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 12035.0,\n      'capacityImport': 3302.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11200.0,\n      'capacityImport': 3282.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11173.0,\n      'capacityImport': 3290.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11880.0,\n      'capacityImport': 3313.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 12020.0,\n      'capacityImport': 3330.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11514.0,\n      'capacityImport': 3330.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11230.0,\n      'capacityImport': 3313.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 10995.0,\n      'capacityImport': 3322.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 12064.0,\n      'capacityImport': 3322.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11496.0,\n      'capacityImport': 3343.0,\n      'datetime': datetime.datetime(2026, 4, 20, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 12311.0,\n      'capacityImport': 2997.0,\n      'datetime': datetime.datetime(2026, 4, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 12994.0,\n      'capacityImport': 3449.0,\n      'datetime': datetime.datetime(2026, 4, 20, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 12813.0,\n      'capacityImport': 3373.0,\n      'datetime': datetime.datetime(2026, 4, 20, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 12373.0,\n      'capacityImport': 3305.0,\n      'datetime': datetime.datetime(2026, 4, 20, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13120.0,\n      'capacityImport': 3282.0,\n      'datetime': datetime.datetime(2026, 4, 20, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 10900.0,\n      'capacityImport': 3314.0,\n      'datetime': datetime.datetime(2026, 4, 20, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11384.0,\n      'capacityImport': 3352.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 12047.0,\n      'capacityImport': 3350.0,\n      'datetime': datetime.datetime(2026, 4, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11715.0,\n      'capacityImport': 3370.0,\n      'datetime': datetime.datetime(2026, 4, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13081.0,\n      'capacityImport': 3362.0,\n      'datetime': datetime.datetime(2026, 4, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13683.0,\n      'capacityImport': 3319.0,\n      'datetime': datetime.datetime(2026, 4, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13758.0,\n      'capacityImport': 3697.0,\n      'datetime': datetime.datetime(2026, 4, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 14045.0,\n      'capacityImport': 3327.0,\n      'datetime': datetime.datetime(2026, 4, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13103.0,\n      'capacityImport': 3237.0,\n      'datetime': datetime.datetime(2026, 4, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 10924.0,\n      'capacityImport': 3326.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 10222.0,\n      'capacityImport': 3300.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 10055.0,\n      'capacityImport': 3297.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 10550.0,\n      'capacityImport': 3316.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11231.0,\n      'capacityImport': 3332.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 10716.0,\n      'capacityImport': 3325.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 10817.0,\n      'capacityImport': 3319.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11262.0,\n      'capacityImport': 3347.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 11880.0,\n      'capacityImport': 3325.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13811.0,\n      'capacityImport': 3381.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 15004.0,\n      'capacityImport': 3053.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 14866.0,\n      'capacityImport': 2764.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 14359.0,\n      'capacityImport': 3271.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 14562.0,\n      'capacityImport': 3271.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13966.0,\n      'capacityImport': 3292.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13325.0,\n      'capacityImport': 3254.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 13392.0,\n      'capacityImport': 3275.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_JAO/test_fetch_core_scheduled_exchanges_day_ahead_de_fr.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_core_scheduled_exchanges_day_ahead_de_fr\n  list([\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -213.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -207.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -206.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -205.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -104.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -98.3,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -107.3,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -85.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -120.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -95.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -92.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -49.7,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 147.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 178.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 193.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 233.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -116.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -59.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -137.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -173.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -850.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -838.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -784.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -817.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -363.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -736.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -801.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -890.9,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -648.3,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -685.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -704.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -770.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -744.3,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 20, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -758.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': 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<EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -423.9,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -937.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -982.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -994.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -969.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -807.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -730.7,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -755.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -740.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -729.9,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -758.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -837.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -894.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -797.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -742.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -716.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -778.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -799.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -953.3,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -1019.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -1123.3,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -1331.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -1386.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -1373.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -1393.7,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -744.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -397.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -524.9,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -401.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -292.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -272.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -252.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -238.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -226.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -218.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -249.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -235.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -341.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -439.3,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -517.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -1527.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -1689.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -1672.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -1804.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -1839.7,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -1890.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -1733.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -1600.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -1527.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -1402.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -1334.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -1404.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -1408.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -1113.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -1084.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -1135.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -1144.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -1091.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -1006.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -953.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -940.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -910.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -905.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -871.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -885.5,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -553.3,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -497.7,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -487.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -545.7,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -496.4,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -526.9,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -577.0,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -615.7,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -551.9,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -561.3,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -556.2,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -551.9,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -587.1,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -571.6,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -612.9,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2026, 4, 21, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -595.8,\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_JAO/test_fetch_nordic_max_bex_day_ahead_no1_se3.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_nordic_max_bex_day_ahead_no1_se3\n  list([\n    dict({\n      'capacityExport': 2339.0,\n      'capacityImport': 2024.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2339.0,\n      'capacityImport': 2024.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2339.0,\n      'capacityImport': 2024.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2339.0,\n      'capacityImport': 2024.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2329.0,\n      'capacityImport': 1937.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2329.0,\n      'capacityImport': 1937.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2329.0,\n      'capacityImport': 1937.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2329.0,\n      'capacityImport': 1937.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2343.0,\n      'capacityImport': 1779.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2343.0,\n      'capacityImport': 1779.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2343.0,\n      'capacityImport': 1779.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2343.0,\n      'capacityImport': 1779.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1884.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1884.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1884.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1884.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1739.0,\n      'capacityImport': 1790.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1739.0,\n      'capacityImport': 1790.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1739.0,\n      'capacityImport': 1790.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1739.0,\n      'capacityImport': 1790.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2083.0,\n      'capacityImport': 1678.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2083.0,\n      'capacityImport': 1678.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2083.0,\n      'capacityImport': 1678.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2083.0,\n      'capacityImport': 1678.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2100.0,\n      'capacityImport': 1669.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2100.0,\n      'capacityImport': 1669.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2100.0,\n      'capacityImport': 1669.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2100.0,\n      'capacityImport': 1669.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2056.0,\n      'capacityImport': 1714.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2056.0,\n      'capacityImport': 1714.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2056.0,\n      'capacityImport': 1714.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2056.0,\n      'capacityImport': 1714.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2073.0,\n      'capacityImport': 1695.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2073.0,\n      'capacityImport': 1695.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2073.0,\n      'capacityImport': 1695.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2073.0,\n      'capacityImport': 1695.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2025.0,\n      'capacityImport': 1717.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2025.0,\n      'capacityImport': 1717.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2025.0,\n      'capacityImport': 1717.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2025.0,\n      'capacityImport': 1717.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2019.0,\n      'capacityImport': 1733.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2019.0,\n      'capacityImport': 1733.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2019.0,\n      'capacityImport': 1733.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2019.0,\n      'capacityImport': 1733.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2005.0,\n      'capacityImport': 1742.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2005.0,\n      'capacityImport': 1742.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2005.0,\n      'capacityImport': 1742.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2005.0,\n      'capacityImport': 1742.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1954.0,\n      'capacityImport': 1778.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1954.0,\n      'capacityImport': 1778.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1954.0,\n      'capacityImport': 1778.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1954.0,\n      'capacityImport': 1778.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1994.0,\n      'capacityImport': 1755.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1994.0,\n      'capacityImport': 1755.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1994.0,\n      'capacityImport': 1755.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1994.0,\n      'capacityImport': 1755.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2033.0,\n      'capacityImport': 1789.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2033.0,\n      'capacityImport': 1789.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2033.0,\n      'capacityImport': 1789.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2033.0,\n      'capacityImport': 1789.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1969.0,\n      'capacityImport': 1773.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1969.0,\n      'capacityImport': 1773.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1969.0,\n      'capacityImport': 1773.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1969.0,\n      'capacityImport': 1773.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1959.0,\n      'capacityImport': 1778.0,\n      'datetime': datetime.datetime(2026, 4, 20, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1959.0,\n      'capacityImport': 1778.0,\n      'datetime': datetime.datetime(2026, 4, 20, 16, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1959.0,\n      'capacityImport': 1778.0,\n      'datetime': datetime.datetime(2026, 4, 20, 16, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1959.0,\n      'capacityImport': 1778.0,\n      'datetime': datetime.datetime(2026, 4, 20, 16, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1906.0,\n      'capacityImport': 1830.0,\n      'datetime': datetime.datetime(2026, 4, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1906.0,\n      'capacityImport': 1830.0,\n      'datetime': datetime.datetime(2026, 4, 20, 17, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1906.0,\n      'capacityImport': 1830.0,\n      'datetime': datetime.datetime(2026, 4, 20, 17, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1906.0,\n      'capacityImport': 1830.0,\n      'datetime': datetime.datetime(2026, 4, 20, 17, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1848.0,\n      'capacityImport': 1740.0,\n      'datetime': datetime.datetime(2026, 4, 20, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1848.0,\n      'capacityImport': 1740.0,\n      'datetime': datetime.datetime(2026, 4, 20, 18, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1848.0,\n      'capacityImport': 1740.0,\n      'datetime': datetime.datetime(2026, 4, 20, 18, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1848.0,\n      'capacityImport': 1740.0,\n      'datetime': datetime.datetime(2026, 4, 20, 18, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2019.0,\n      'capacityImport': 1719.0,\n      'datetime': datetime.datetime(2026, 4, 20, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2019.0,\n      'capacityImport': 1719.0,\n      'datetime': datetime.datetime(2026, 4, 20, 19, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2019.0,\n      'capacityImport': 1719.0,\n      'datetime': datetime.datetime(2026, 4, 20, 19, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2019.0,\n      'capacityImport': 1719.0,\n      'datetime': datetime.datetime(2026, 4, 20, 19, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2005.0,\n      'capacityImport': 1759.0,\n      'datetime': datetime.datetime(2026, 4, 20, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2005.0,\n      'capacityImport': 1759.0,\n      'datetime': datetime.datetime(2026, 4, 20, 20, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2005.0,\n      'capacityImport': 1759.0,\n      'datetime': datetime.datetime(2026, 4, 20, 20, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2005.0,\n      'capacityImport': 1759.0,\n      'datetime': datetime.datetime(2026, 4, 20, 20, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2262.0,\n      'capacityImport': 1736.0,\n      'datetime': datetime.datetime(2026, 4, 20, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2262.0,\n      'capacityImport': 1736.0,\n      'datetime': datetime.datetime(2026, 4, 20, 21, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2262.0,\n      'capacityImport': 1736.0,\n      'datetime': datetime.datetime(2026, 4, 20, 21, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2262.0,\n      'capacityImport': 1736.0,\n      'datetime': datetime.datetime(2026, 4, 20, 21, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2357.0,\n      'capacityImport': 1749.0,\n      'datetime': datetime.datetime(2026, 4, 20, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2357.0,\n      'capacityImport': 1749.0,\n      'datetime': datetime.datetime(2026, 4, 20, 22, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2357.0,\n      'capacityImport': 1749.0,\n      'datetime': datetime.datetime(2026, 4, 20, 22, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2357.0,\n      'capacityImport': 1749.0,\n      'datetime': datetime.datetime(2026, 4, 20, 22, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2393.0,\n      'capacityImport': 1723.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2393.0,\n      'capacityImport': 1723.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2393.0,\n      'capacityImport': 1723.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2393.0,\n      'capacityImport': 1723.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2373.0,\n      'capacityImport': 1737.0,\n      'datetime': datetime.datetime(2026, 4, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2373.0,\n      'capacityImport': 1737.0,\n      'datetime': datetime.datetime(2026, 4, 21, 0, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2373.0,\n      'capacityImport': 1737.0,\n      'datetime': datetime.datetime(2026, 4, 21, 0, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2373.0,\n      'capacityImport': 1737.0,\n      'datetime': datetime.datetime(2026, 4, 21, 0, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2404.0,\n      'capacityImport': 1718.0,\n      'datetime': datetime.datetime(2026, 4, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2404.0,\n      'capacityImport': 1718.0,\n      'datetime': datetime.datetime(2026, 4, 21, 1, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2404.0,\n      'capacityImport': 1718.0,\n      'datetime': datetime.datetime(2026, 4, 21, 1, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2404.0,\n      'capacityImport': 1718.0,\n      'datetime': datetime.datetime(2026, 4, 21, 1, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2398.0,\n      'capacityImport': 1720.0,\n      'datetime': datetime.datetime(2026, 4, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2398.0,\n      'capacityImport': 1720.0,\n      'datetime': datetime.datetime(2026, 4, 21, 2, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2398.0,\n      'capacityImport': 1720.0,\n      'datetime': datetime.datetime(2026, 4, 21, 2, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2398.0,\n      'capacityImport': 1720.0,\n      'datetime': datetime.datetime(2026, 4, 21, 2, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2303.0,\n      'capacityImport': 1680.0,\n      'datetime': datetime.datetime(2026, 4, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2303.0,\n      'capacityImport': 1680.0,\n      'datetime': datetime.datetime(2026, 4, 21, 3, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2303.0,\n      'capacityImport': 1680.0,\n      'datetime': datetime.datetime(2026, 4, 21, 3, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2303.0,\n      'capacityImport': 1680.0,\n      'datetime': datetime.datetime(2026, 4, 21, 3, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2088.0,\n      'capacityImport': 1596.0,\n      'datetime': datetime.datetime(2026, 4, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2088.0,\n      'capacityImport': 1596.0,\n      'datetime': datetime.datetime(2026, 4, 21, 4, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2088.0,\n      'capacityImport': 1596.0,\n      'datetime': datetime.datetime(2026, 4, 21, 4, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2088.0,\n      'capacityImport': 1596.0,\n      'datetime': datetime.datetime(2026, 4, 21, 4, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2057.0,\n      'capacityImport': 1605.0,\n      'datetime': datetime.datetime(2026, 4, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2057.0,\n      'capacityImport': 1605.0,\n      'datetime': datetime.datetime(2026, 4, 21, 5, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2057.0,\n      'capacityImport': 1605.0,\n      'datetime': datetime.datetime(2026, 4, 21, 5, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2057.0,\n      'capacityImport': 1605.0,\n      'datetime': datetime.datetime(2026, 4, 21, 5, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2130.0,\n      'capacityImport': 1599.0,\n      'datetime': datetime.datetime(2026, 4, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2130.0,\n      'capacityImport': 1599.0,\n      'datetime': datetime.datetime(2026, 4, 21, 6, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2130.0,\n      'capacityImport': 1599.0,\n      'datetime': datetime.datetime(2026, 4, 21, 6, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2130.0,\n      'capacityImport': 1599.0,\n      'datetime': datetime.datetime(2026, 4, 21, 6, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2143.0,\n      'capacityImport': 1606.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2143.0,\n      'capacityImport': 1606.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2143.0,\n      'capacityImport': 1606.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2143.0,\n      'capacityImport': 1606.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2043.0,\n      'capacityImport': 1696.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2043.0,\n      'capacityImport': 1696.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2043.0,\n      'capacityImport': 1696.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2043.0,\n      'capacityImport': 1696.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2234.0,\n      'capacityImport': 1765.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2234.0,\n      'capacityImport': 1765.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2234.0,\n      'capacityImport': 1765.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2234.0,\n      'capacityImport': 1765.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2273.0,\n      'capacityImport': 1729.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2273.0,\n      'capacityImport': 1729.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2273.0,\n      'capacityImport': 1729.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2273.0,\n      'capacityImport': 1729.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2272.0,\n      'capacityImport': 1731.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2272.0,\n      'capacityImport': 1731.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2272.0,\n      'capacityImport': 1731.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2272.0,\n      'capacityImport': 1731.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2238.0,\n      'capacityImport': 1739.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2238.0,\n      'capacityImport': 1739.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2238.0,\n      'capacityImport': 1739.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2238.0,\n      'capacityImport': 1739.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2253.0,\n      'capacityImport': 1751.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2253.0,\n      'capacityImport': 1751.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2253.0,\n      'capacityImport': 1751.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2253.0,\n      'capacityImport': 1751.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1941.0,\n      'capacityImport': 1746.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1941.0,\n      'capacityImport': 1746.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1941.0,\n      'capacityImport': 1746.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1941.0,\n      'capacityImport': 1746.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2270.0,\n      'capacityImport': 1779.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2270.0,\n      'capacityImport': 1779.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2270.0,\n      'capacityImport': 1779.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2270.0,\n      'capacityImport': 1779.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2237.0,\n      'capacityImport': 1764.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2237.0,\n      'capacityImport': 1764.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2237.0,\n      'capacityImport': 1764.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2237.0,\n      'capacityImport': 1764.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2193.0,\n      'capacityImport': 1780.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2193.0,\n      'capacityImport': 1780.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2193.0,\n      'capacityImport': 1780.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2193.0,\n      'capacityImport': 1780.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2008.0,\n      'capacityImport': 1757.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2008.0,\n      'capacityImport': 1757.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2008.0,\n      'capacityImport': 1757.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2008.0,\n      'capacityImport': 1757.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2292.0,\n      'capacityImport': 1717.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2292.0,\n      'capacityImport': 1717.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2292.0,\n      'capacityImport': 1717.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2292.0,\n      'capacityImport': 1717.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2415.0,\n      'capacityImport': 1694.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2415.0,\n      'capacityImport': 1694.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2415.0,\n      'capacityImport': 1694.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2415.0,\n      'capacityImport': 1694.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2395.0,\n      'capacityImport': 1671.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2395.0,\n      'capacityImport': 1671.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2395.0,\n      'capacityImport': 1671.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2395.0,\n      'capacityImport': 1671.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2454.0,\n      'capacityImport': 1648.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2454.0,\n      'capacityImport': 1648.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2454.0,\n      'capacityImport': 1648.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2454.0,\n      'capacityImport': 1648.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2403.0,\n      'capacityImport': 1644.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2403.0,\n      'capacityImport': 1644.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2403.0,\n      'capacityImport': 1644.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2403.0,\n      'capacityImport': 1644.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_JAO/test_fetch_nordic_max_bflow_day_ahead_no1_se3.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_nordic_max_bflow_day_ahead_no1_se3\n  list([\n    dict({\n      'capacityExport': 2098.0,\n      'capacityImport': 1938.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2098.0,\n      'capacityImport': 1938.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2098.0,\n      'capacityImport': 1938.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2098.0,\n      'capacityImport': 1938.0,\n      'datetime': datetime.datetime(2026, 4, 20, 0, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2092.0,\n      'capacityImport': 1936.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2092.0,\n      'capacityImport': 1936.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2092.0,\n      'capacityImport': 1936.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2092.0,\n      'capacityImport': 1936.0,\n      'datetime': datetime.datetime(2026, 4, 20, 1, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2091.0,\n      'capacityImport': 1829.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2091.0,\n      'capacityImport': 1829.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2091.0,\n      'capacityImport': 1829.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2091.0,\n      'capacityImport': 1829.0,\n      'datetime': datetime.datetime(2026, 4, 20, 2, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1502.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1502.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1502.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1502.0,\n      'datetime': datetime.datetime(2026, 4, 20, 3, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2076.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2076.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2076.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2076.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 4, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1761.0,\n      'capacityImport': 1379.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1761.0,\n      'capacityImport': 1379.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1761.0,\n      'capacityImport': 1379.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1761.0,\n      'capacityImport': 1379.0,\n      'datetime': datetime.datetime(2026, 4, 20, 5, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1763.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1763.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1763.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1763.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 6, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1762.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1762.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1762.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1762.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 7, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1761.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1761.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1761.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1761.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 8, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1741.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1741.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1741.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1741.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 20, 9, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1749.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1749.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1749.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1749.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 10, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1743.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1743.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1743.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1743.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 11, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1373.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1373.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1373.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1373.0,\n      'datetime': datetime.datetime(2026, 4, 20, 12, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1746.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1746.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1746.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1746.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 13, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1808.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1808.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1808.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1808.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 14, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1743.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1743.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1743.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1743.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 20, 15, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 16, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 16, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 16, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1736.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1736.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 17, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1736.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 17, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1736.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 17, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 18, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 18, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1735.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 20, 18, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1749.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 20, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1749.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 20, 19, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1749.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 20, 19, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1749.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 20, 19, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1759.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1759.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 20, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1759.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 20, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1759.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 20, 20, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1956.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1956.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 21, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1956.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 21, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1956.0,\n      'capacityImport': 1376.0,\n      'datetime': datetime.datetime(2026, 4, 20, 21, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2069.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 20, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2069.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 20, 22, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2069.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 20, 22, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2069.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 20, 22, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 20, 23, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2072.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2072.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 21, 0, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2072.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 21, 0, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2072.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 21, 0, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 1, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 1, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 1, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2073.0,\n      'capacityImport': 1385.0,\n      'datetime': datetime.datetime(2026, 4, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2073.0,\n      'capacityImport': 1385.0,\n      'datetime': datetime.datetime(2026, 4, 21, 2, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2073.0,\n      'capacityImport': 1385.0,\n      'datetime': datetime.datetime(2026, 4, 21, 2, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2073.0,\n      'capacityImport': 1385.0,\n      'datetime': datetime.datetime(2026, 4, 21, 2, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2074.0,\n      'capacityImport': 1387.0,\n      'datetime': datetime.datetime(2026, 4, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2074.0,\n      'capacityImport': 1387.0,\n      'datetime': datetime.datetime(2026, 4, 21, 3, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2074.0,\n      'capacityImport': 1387.0,\n      'datetime': datetime.datetime(2026, 4, 21, 3, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2074.0,\n      'capacityImport': 1387.0,\n      'datetime': datetime.datetime(2026, 4, 21, 3, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2066.0,\n      'capacityImport': 1384.0,\n      'datetime': datetime.datetime(2026, 4, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2066.0,\n      'capacityImport': 1384.0,\n      'datetime': datetime.datetime(2026, 4, 21, 4, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2066.0,\n      'capacityImport': 1384.0,\n      'datetime': datetime.datetime(2026, 4, 21, 4, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2066.0,\n      'capacityImport': 1384.0,\n      'datetime': datetime.datetime(2026, 4, 21, 4, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2062.0,\n      'capacityImport': 1388.0,\n      'datetime': datetime.datetime(2026, 4, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2062.0,\n      'capacityImport': 1388.0,\n      'datetime': datetime.datetime(2026, 4, 21, 5, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2062.0,\n      'capacityImport': 1388.0,\n      'datetime': datetime.datetime(2026, 4, 21, 5, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2062.0,\n      'capacityImport': 1388.0,\n      'datetime': datetime.datetime(2026, 4, 21, 5, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2070.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2070.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 6, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2070.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 6, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2070.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 6, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1385.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1385.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1385.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1385.0,\n      'datetime': datetime.datetime(2026, 4, 21, 7, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2077.0,\n      'capacityImport': 1374.0,\n      'datetime': datetime.datetime(2026, 4, 21, 8, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2082.0,\n      'capacityImport': 1372.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2082.0,\n      'capacityImport': 1372.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2082.0,\n      'capacityImport': 1372.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2082.0,\n      'capacityImport': 1372.0,\n      'datetime': datetime.datetime(2026, 4, 21, 9, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2064.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2064.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2064.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2064.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 10, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2060.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2060.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2060.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2060.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 11, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2050.0,\n      'capacityImport': 1372.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2050.0,\n      'capacityImport': 1372.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2050.0,\n      'capacityImport': 1372.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2050.0,\n      'capacityImport': 1372.0,\n      'datetime': datetime.datetime(2026, 4, 21, 12, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2049.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2049.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2049.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2049.0,\n      'capacityImport': 1375.0,\n      'datetime': datetime.datetime(2026, 4, 21, 13, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2074.0,\n      'capacityImport': 1380.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2074.0,\n      'capacityImport': 1380.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2074.0,\n      'capacityImport': 1380.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2074.0,\n      'capacityImport': 1380.0,\n      'datetime': datetime.datetime(2026, 4, 21, 14, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2050.0,\n      'capacityImport': 1383.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2050.0,\n      'capacityImport': 1383.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2050.0,\n      'capacityImport': 1383.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2050.0,\n      'capacityImport': 1383.0,\n      'datetime': datetime.datetime(2026, 4, 21, 15, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2031.0,\n      'capacityImport': 1379.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2031.0,\n      'capacityImport': 1379.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2031.0,\n      'capacityImport': 1379.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2031.0,\n      'capacityImport': 1379.0,\n      'datetime': datetime.datetime(2026, 4, 21, 16, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2034.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2034.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2034.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2034.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 21, 17, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1758.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1758.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1758.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 1758.0,\n      'capacityImport': 1381.0,\n      'datetime': datetime.datetime(2026, 4, 21, 18, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2067.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2067.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2067.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2067.0,\n      'capacityImport': 1378.0,\n      'datetime': datetime.datetime(2026, 4, 21, 19, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2078.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2078.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2078.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2078.0,\n      'capacityImport': 1377.0,\n      'datetime': datetime.datetime(2026, 4, 21, 20, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2076.0,\n      'capacityImport': 1370.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2076.0,\n      'capacityImport': 1370.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2076.0,\n      'capacityImport': 1370.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2076.0,\n      'capacityImport': 1370.0,\n      'datetime': datetime.datetime(2026, 4, 21, 21, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2088.0,\n      'capacityImport': 1387.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2088.0,\n      'capacityImport': 1387.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2088.0,\n      'capacityImport': 1387.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2088.0,\n      'capacityImport': 1387.0,\n      'datetime': datetime.datetime(2026, 4, 21, 22, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 15, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 30, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 2087.0,\n      'capacityImport': 1386.0,\n      'datetime': datetime.datetime(2026, 4, 21, 23, 45, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'NO-NO1->SE-SE3',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_JAO/test_fetch_shadow_auction_atc_day_ahead_de_fr.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_shadow_auction_atc_day_ahead_de_fr\n  list([\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 1, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 2, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 0, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 1, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 2, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 3, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 4, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 5, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 6, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 7, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 8, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 9, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 10, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 11, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 12, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 13, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 14, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 15, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 16, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 17, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 18, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 19, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 20, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 21, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 22, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n    dict({\n      'capacityExport': 595.0,\n      'capacityImport': 1000.0,\n      'datetime': datetime.datetime(2025, 10, 3, 23, 0, tzinfo=datetime.timezone.utc),\n      'sortedZoneKeys': 'DE->FR',\n      'source': 'jao.eu',\n      'sourceType': <EventSourceType.published: 'published'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_JP.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast[JP-CB]\n  list([\n    dict({\n      'consumption': 13217.198,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 12784.63,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 12678.114,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 12709.884,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 12754.234,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 12927.154,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13100.514,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13165.81,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13228.502,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13284.332,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13456.928,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13570.12,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13823.44,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14170.446,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14366.862,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14698.266,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15801.974,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 16343.664,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 16749.112,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 16622.76,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 16439.484,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 16438.93,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 16385.124,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 16099.35,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15226.802,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14987.148,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15517.214,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15603.964,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15548.586,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15340.016,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15101.82,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15176.93,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15094.36,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14839.598,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14519.836,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14601.092,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14905.032,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14944.362,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 15091.136,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14932.264,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14770.01,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14713.76,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14561.962,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14235.61,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 14137.57,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13808.264,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13645.392,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'consumption': 13369.254,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CB',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_consumption_forecast[JP-CG]\n  list([\n    dict({\n      'consumption': 5630.0,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5510.0,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5323.0,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5403.0,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5629.0,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5761.0,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5932.0,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6078.0,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6500.0,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6552.0,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6678.0,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6712.0,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6720.0,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6695.0,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6732.0,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6648.0,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6594.0,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6502.0,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6538.0,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6502.0,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6389.0,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6335.0,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6351.0,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6272.0,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5815.0,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5822.0,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5994.0,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6062.0,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5935.0,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5847.0,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5840.0,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5910.0,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6028.0,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6082.0,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6096.0,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6164.0,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6354.0,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6362.0,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6324.0,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6256.0,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6147.0,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 6033.0,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5904.0,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5796.0,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5656.0,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5544.0,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5416.0,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'consumption': 5304.0,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-CG',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_consumption_forecast[JP-HKD]\n  list([\n    dict({\n      'consumption': 2868.0,\n      'datetime': FakeDatetime(2025, 4, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 2815.0,\n      'datetime': FakeDatetime(2025, 4, 15, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 2878.0,\n      'datetime': FakeDatetime(2025, 4, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 2904.0,\n      'datetime': FakeDatetime(2025, 4, 15, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 2973.0,\n      'datetime': FakeDatetime(2025, 4, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3048.0,\n      'datetime': FakeDatetime(2025, 4, 15, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3132.0,\n      'datetime': FakeDatetime(2025, 4, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3199.0,\n      'datetime': FakeDatetime(2025, 4, 15, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3211.0,\n      'datetime': FakeDatetime(2025, 4, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3168.0,\n      'datetime': FakeDatetime(2025, 4, 15, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3185.0,\n      'datetime': FakeDatetime(2025, 4, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3147.0,\n      'datetime': FakeDatetime(2025, 4, 15, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3185.0,\n      'datetime': FakeDatetime(2025, 4, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3241.0,\n      'datetime': FakeDatetime(2025, 4, 15, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3217.0,\n      'datetime': FakeDatetime(2025, 4, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3311.0,\n      'datetime': FakeDatetime(2025, 4, 15, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3482.0,\n      'datetime': FakeDatetime(2025, 4, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3610.0,\n      'datetime': FakeDatetime(2025, 4, 15, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3734.0,\n      'datetime': FakeDatetime(2025, 4, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3696.0,\n      'datetime': FakeDatetime(2025, 4, 15, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3674.0,\n      'datetime': FakeDatetime(2025, 4, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3697.0,\n      'datetime': FakeDatetime(2025, 4, 15, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3736.0,\n      'datetime': FakeDatetime(2025, 4, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3699.0,\n      'datetime': FakeDatetime(2025, 4, 15, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3579.0,\n      'datetime': FakeDatetime(2025, 4, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3481.0,\n      'datetime': FakeDatetime(2025, 4, 15, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3459.0,\n      'datetime': FakeDatetime(2025, 4, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3486.0,\n      'datetime': FakeDatetime(2025, 4, 15, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3433.0,\n      'datetime': FakeDatetime(2025, 4, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3437.0,\n      'datetime': FakeDatetime(2025, 4, 15, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3469.0,\n      'datetime': FakeDatetime(2025, 4, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3531.0,\n      'datetime': FakeDatetime(2025, 4, 15, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3504.0,\n      'datetime': FakeDatetime(2025, 4, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3504.0,\n      'datetime': FakeDatetime(2025, 4, 15, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3459.0,\n      'datetime': FakeDatetime(2025, 4, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3469.0,\n      'datetime': FakeDatetime(2025, 4, 15, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3475.0,\n      'datetime': FakeDatetime(2025, 4, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3481.0,\n      'datetime': FakeDatetime(2025, 4, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3445.0,\n      'datetime': FakeDatetime(2025, 4, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3364.0,\n      'datetime': FakeDatetime(2025, 4, 15, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3273.0,\n      'datetime': FakeDatetime(2025, 4, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3176.0,\n      'datetime': FakeDatetime(2025, 4, 15, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 3072.0,\n      'datetime': FakeDatetime(2025, 4, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 2996.0,\n      'datetime': FakeDatetime(2025, 4, 15, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 2955.0,\n      'datetime': FakeDatetime(2025, 4, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 2882.0,\n      'datetime': FakeDatetime(2025, 4, 15, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 2923.0,\n      'datetime': FakeDatetime(2025, 4, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'consumption': 2856.0,\n      'datetime': FakeDatetime(2025, 4, 15, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HKD',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_consumption_forecast[JP-HR]\n  list([\n    dict({\n      'consumption': 2558.332,\n      'datetime': FakeDatetime(2025, 4, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 2535.666,\n      'datetime': FakeDatetime(2025, 4, 15, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 2554.666,\n      'datetime': FakeDatetime(2025, 4, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 2628.5,\n      'datetime': FakeDatetime(2025, 4, 15, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 2710.498,\n      'datetime': FakeDatetime(2025, 4, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 2805.0,\n      'datetime': FakeDatetime(2025, 4, 15, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 2905.5,\n      'datetime': FakeDatetime(2025, 4, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 2980.0,\n      'datetime': FakeDatetime(2025, 4, 15, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3036.332,\n      'datetime': FakeDatetime(2025, 4, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3045.332,\n      'datetime': FakeDatetime(2025, 4, 15, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3086.166,\n      'datetime': FakeDatetime(2025, 4, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3049.5,\n      'datetime': FakeDatetime(2025, 4, 15, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3042.166,\n      'datetime': FakeDatetime(2025, 4, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3024.332,\n      'datetime': FakeDatetime(2025, 4, 15, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3040.666,\n      'datetime': FakeDatetime(2025, 4, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3086.166,\n      'datetime': FakeDatetime(2025, 4, 15, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3227.332,\n      'datetime': FakeDatetime(2025, 4, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3385.0,\n      'datetime': FakeDatetime(2025, 4, 15, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3484.332,\n      'datetime': FakeDatetime(2025, 4, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3534.5,\n      'datetime': FakeDatetime(2025, 4, 15, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3504.166,\n      'datetime': FakeDatetime(2025, 4, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3511.166,\n      'datetime': FakeDatetime(2025, 4, 15, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3533.5,\n      'datetime': FakeDatetime(2025, 4, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3509.0,\n      'datetime': FakeDatetime(2025, 4, 15, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3346.832,\n      'datetime': FakeDatetime(2025, 4, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3311.0,\n      'datetime': FakeDatetime(2025, 4, 15, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3465.332,\n      'datetime': FakeDatetime(2025, 4, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3518.666,\n      'datetime': FakeDatetime(2025, 4, 15, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3553.5,\n      'datetime': FakeDatetime(2025, 4, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3584.0,\n      'datetime': FakeDatetime(2025, 4, 15, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3536.166,\n      'datetime': FakeDatetime(2025, 4, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3572.166,\n      'datetime': FakeDatetime(2025, 4, 15, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3596.0,\n      'datetime': FakeDatetime(2025, 4, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3584.5,\n      'datetime': FakeDatetime(2025, 4, 15, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3529.5,\n      'datetime': FakeDatetime(2025, 4, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3515.666,\n      'datetime': FakeDatetime(2025, 4, 15, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3526.832,\n      'datetime': FakeDatetime(2025, 4, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3557.332,\n      'datetime': FakeDatetime(2025, 4, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3494.332,\n      'datetime': FakeDatetime(2025, 4, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3447.332,\n      'datetime': FakeDatetime(2025, 4, 15, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3387.5,\n      'datetime': FakeDatetime(2025, 4, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3341.832,\n      'datetime': FakeDatetime(2025, 4, 15, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3309.832,\n      'datetime': FakeDatetime(2025, 4, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3279.5,\n      'datetime': FakeDatetime(2025, 4, 15, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3233.666,\n      'datetime': FakeDatetime(2025, 4, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3148.5,\n      'datetime': FakeDatetime(2025, 4, 15, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3096.666,\n      'datetime': FakeDatetime(2025, 4, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'consumption': 3031.332,\n      'datetime': FakeDatetime(2025, 4, 15, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-HR',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_consumption_forecast[JP-KN]\n  list([\n    dict({\n      'consumption': 12758.0,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 12442.0,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 12110.0,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 12090.0,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 12240.0,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 12560.0,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 12888.0,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13112.0,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13150.0,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13050.0,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13092.0,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13108.0,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13258.0,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13540.0,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13974.0,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 14426.0,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15144.0,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15856.0,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 16292.0,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 16508.0,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 16460.0,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 16340.0,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 16106.0,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15894.0,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15364.0,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15236.0,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15608.0,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15592.0,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15522.0,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15478.0,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15372.0,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15428.0,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15442.0,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15358.0,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15148.0,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15452.0,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15674.0,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15526.0,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15416.0,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15384.0,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 15130.0,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 14870.0,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 14612.0,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 14188.0,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13766.0,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13434.0,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 13142.0,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'consumption': 12658.0,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KN',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_consumption_forecast[JP-KY]\n  list([\n    dict({\n      'consumption': 7316.0,\n      'datetime': FakeDatetime(2025, 4, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 7150.0,\n      'datetime': FakeDatetime(2025, 4, 7, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 7100.0,\n      'datetime': FakeDatetime(2025, 4, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 7219.0,\n      'datetime': FakeDatetime(2025, 4, 7, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 7507.0,\n      'datetime': FakeDatetime(2025, 4, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 7844.0,\n      'datetime': FakeDatetime(2025, 4, 7, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8214.0,\n      'datetime': FakeDatetime(2025, 4, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8529.0,\n      'datetime': FakeDatetime(2025, 4, 7, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8756.0,\n      'datetime': FakeDatetime(2025, 4, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8905.0,\n      'datetime': FakeDatetime(2025, 4, 7, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8965.0,\n      'datetime': FakeDatetime(2025, 4, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8973.0,\n      'datetime': FakeDatetime(2025, 4, 7, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9230.0,\n      'datetime': FakeDatetime(2025, 4, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9085.0,\n      'datetime': FakeDatetime(2025, 4, 7, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8820.0,\n      'datetime': FakeDatetime(2025, 4, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8457.0,\n      'datetime': FakeDatetime(2025, 4, 7, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8359.0,\n      'datetime': FakeDatetime(2025, 4, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8777.0,\n      'datetime': FakeDatetime(2025, 4, 7, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9060.0,\n      'datetime': FakeDatetime(2025, 4, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9179.0,\n      'datetime': FakeDatetime(2025, 4, 7, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9224.0,\n      'datetime': FakeDatetime(2025, 4, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9254.0,\n      'datetime': FakeDatetime(2025, 4, 7, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9282.0,\n      'datetime': FakeDatetime(2025, 4, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9300.0,\n      'datetime': FakeDatetime(2025, 4, 7, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9093.0,\n      'datetime': FakeDatetime(2025, 4, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8800.0,\n      'datetime': FakeDatetime(2025, 4, 7, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9038.0,\n      'datetime': FakeDatetime(2025, 4, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9100.0,\n      'datetime': FakeDatetime(2025, 4, 7, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8978.0,\n      'datetime': FakeDatetime(2025, 4, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8854.0,\n      'datetime': FakeDatetime(2025, 4, 7, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8735.0,\n      'datetime': FakeDatetime(2025, 4, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8703.0,\n      'datetime': FakeDatetime(2025, 4, 7, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8750.0,\n      'datetime': FakeDatetime(2025, 4, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8844.0,\n      'datetime': FakeDatetime(2025, 4, 7, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8917.0,\n      'datetime': FakeDatetime(2025, 4, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9001.0,\n      'datetime': FakeDatetime(2025, 4, 7, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9121.0,\n      'datetime': FakeDatetime(2025, 4, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9296.0,\n      'datetime': FakeDatetime(2025, 4, 7, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9400.0,\n      'datetime': FakeDatetime(2025, 4, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9352.0,\n      'datetime': FakeDatetime(2025, 4, 7, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9201.0,\n      'datetime': FakeDatetime(2025, 4, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 9037.0,\n      'datetime': FakeDatetime(2025, 4, 7, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8865.0,\n      'datetime': FakeDatetime(2025, 4, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8665.0,\n      'datetime': FakeDatetime(2025, 4, 7, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8488.0,\n      'datetime': FakeDatetime(2025, 4, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8308.0,\n      'datetime': FakeDatetime(2025, 4, 7, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 8146.0,\n      'datetime': FakeDatetime(2025, 4, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'consumption': 7936.0,\n      'datetime': FakeDatetime(2025, 4, 7, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-KY',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_consumption_forecast[JP-ON]\n  list([\n    dict({\n      'consumption': 695.0,\n      'datetime': FakeDatetime(2025, 4, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 684.0,\n      'datetime': FakeDatetime(2025, 4, 15, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 667.0,\n      'datetime': FakeDatetime(2025, 4, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 673.0,\n      'datetime': FakeDatetime(2025, 4, 15, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 666.0,\n      'datetime': FakeDatetime(2025, 4, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 699.0,\n      'datetime': FakeDatetime(2025, 4, 15, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 703.0,\n      'datetime': FakeDatetime(2025, 4, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 724.0,\n      'datetime': FakeDatetime(2025, 4, 15, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 716.0,\n      'datetime': FakeDatetime(2025, 4, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 732.0,\n      'datetime': FakeDatetime(2025, 4, 15, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 724.0,\n      'datetime': FakeDatetime(2025, 4, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 724.0,\n      'datetime': FakeDatetime(2025, 4, 15, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 724.0,\n      'datetime': FakeDatetime(2025, 4, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 746.0,\n      'datetime': FakeDatetime(2025, 4, 15, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 771.0,\n      'datetime': FakeDatetime(2025, 4, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 791.0,\n      'datetime': FakeDatetime(2025, 4, 15, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 836.0,\n      'datetime': FakeDatetime(2025, 4, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 822.0,\n      'datetime': FakeDatetime(2025, 4, 15, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 815.0,\n      'datetime': FakeDatetime(2025, 4, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 833.0,\n      'datetime': FakeDatetime(2025, 4, 15, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 845.0,\n      'datetime': FakeDatetime(2025, 4, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 854.0,\n      'datetime': FakeDatetime(2025, 4, 15, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 863.0,\n      'datetime': FakeDatetime(2025, 4, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 881.0,\n      'datetime': FakeDatetime(2025, 4, 15, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 871.0,\n      'datetime': FakeDatetime(2025, 4, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 862.0,\n      'datetime': FakeDatetime(2025, 4, 15, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 877.0,\n      'datetime': FakeDatetime(2025, 4, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 876.0,\n      'datetime': FakeDatetime(2025, 4, 15, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 865.0,\n      'datetime': FakeDatetime(2025, 4, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 851.0,\n      'datetime': FakeDatetime(2025, 4, 15, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 832.0,\n      'datetime': FakeDatetime(2025, 4, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 823.0,\n      'datetime': FakeDatetime(2025, 4, 15, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 817.0,\n      'datetime': FakeDatetime(2025, 4, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 812.0,\n      'datetime': FakeDatetime(2025, 4, 15, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 804.0,\n      'datetime': FakeDatetime(2025, 4, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 800.0,\n      'datetime': FakeDatetime(2025, 4, 15, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 820.0,\n      'datetime': FakeDatetime(2025, 4, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 840.0,\n      'datetime': FakeDatetime(2025, 4, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 856.0,\n      'datetime': FakeDatetime(2025, 4, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 854.0,\n      'datetime': FakeDatetime(2025, 4, 15, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 844.0,\n      'datetime': FakeDatetime(2025, 4, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 832.0,\n      'datetime': FakeDatetime(2025, 4, 15, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 774.0,\n      'datetime': FakeDatetime(2025, 4, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 774.0,\n      'datetime': FakeDatetime(2025, 4, 15, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 748.0,\n      'datetime': FakeDatetime(2025, 4, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 727.0,\n      'datetime': FakeDatetime(2025, 4, 15, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 714.0,\n      'datetime': FakeDatetime(2025, 4, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'consumption': 693.0,\n      'datetime': FakeDatetime(2025, 4, 15, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-ON',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_consumption_forecast[JP-SK]\n  list([\n    dict({\n      'consumption': 2477.236,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2458.086,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2468.178,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2507.254,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2588.878,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2688.624,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2797.54,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2882.052,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2928.57,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2965.57,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 3004.312,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2982.992,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2994.152,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2921.304,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2803.706,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2803.61,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2901.828,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2982.586,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 3006.326,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 3002.134,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2881.784,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2885.814,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2878.38,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2828.726,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2717.584,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2732.468,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2817.182,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2781.182,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2729.382,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2677.15,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2629.43,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2653.08,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2712.208,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2817.8,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2847.984,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2866.088,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2893.28,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2923.922,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2849.002,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2795.516,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2773.53,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2732.11,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2653.236,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2571.242,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2503.676,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2419.726,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2407.25,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'consumption': 2363.946,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-SK',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_consumption_forecast[JP-TH]\n  list([\n    dict({\n      'consumption': 7386.394,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 7385.596,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 7473.848,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 7545.482,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 7677.29,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 7866.51,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 7950.104,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8136.658,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8293.068,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8421.01,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8514.424,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8621.602,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8661.956,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8538.8,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8407.858,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8590.902,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9181.96,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9618.646,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9681.374,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9724.916,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9611.418,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9687.304,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9563.654,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9399.97,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9247.0,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9152.0,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9341.686,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9500.846,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9532.27,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9453.564,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9544.0,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9650.0,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9545.0,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9524.0,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9670.338,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9727.366,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9818.894,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9793.99,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9802.576,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9567.054,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9257.978,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 9100.466,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8731.198,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8426.366,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 8096.4,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 7866.588,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 7741.72,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'consumption': 7649.586,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TH',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_consumption_forecast[JP-TK]\n  list([\n    dict({\n      'consumption': 24076.0,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 23281.0,\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 22922.0,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 22780.0,\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 22871.0,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 23068.0,\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 23320.0,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 23462.0,\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 23702.0,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 24001.0,\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 24464.0,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 24671.0,\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 25107.0,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 25914.0,\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 26444.0,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 26897.0,\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 27998.0,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 28524.0,\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29241.0,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29650.0,\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29637.0,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30222.0,\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30859.0,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30801.0,\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30214.0,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30140.0,\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30694.0,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30181.0,\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29633.0,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29504.0,\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29063.0,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29285.0,\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29351.0,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29105.0,\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29389.0,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29741.0,\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30247.0,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30798.0,\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30599.0,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 30208.0,\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29662.0,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 29345.0,\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 28601.0,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 27793.0,\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 27397.0,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 26554.0,\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 25952.0,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'consumption': 25068.0,\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'JP-TK',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-CB]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11587.198,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10972.63,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10874.114,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10949.884,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10902.234,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11241.154,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11512.514,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11567.81,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11602.502,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11618.332,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11888.928,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11706.12,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12131.44,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12488.446,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12926.862,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13302.266,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14307.974,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14721.664,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 15353.112,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14970.76,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13987.484,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14356.93,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14345.124,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14373.35,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13320.802,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13195.148,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13457.214,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13505.964,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13528.586,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13046.016,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13001.82,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13124.93,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13322.36,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12767.598,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12279.836,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12765.092,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12929.032,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12736.362,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12997.136,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12880.264,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12808.01,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12381.76,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12123.962,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12099.61,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11897.57,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11808.264,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11557.392,\n      'zoneKey': 'JP-CB',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'powergrid.chuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11657.254,\n      'zoneKey': 'JP-CB',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-CG]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 5852.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 5833.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 5781.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 5785.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6043.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 5930.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6102.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6252.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6385.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6445.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6711.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6655.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6600.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6721.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6987.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7073.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7401.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7559.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8041.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8606.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8807.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9079.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9245.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9340.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8791.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8664.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9042.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9046.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8727.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8201.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8027.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7586.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7311.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7369.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7244.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7800.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7223.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7235.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7386.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7099.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6843.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6851.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6658.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 6176.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 5850.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 5700.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 5638.0,\n      'zoneKey': 'JP-CG',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.energia.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 5470.0,\n      'zoneKey': 'JP-CG',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-HKD]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3462.54,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3413.68,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3474.94,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3500.5,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3547.37,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3545.81,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3561.03,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3560.33,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3575.83,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3583.38,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3581.63,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3564.62,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3559.79,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3685.84,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3578.26,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3684.87,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4111.41,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4272.93,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4428.74,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4390.55,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4580.93,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4612.31,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4651.38,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4576.3,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4225.89,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3882.53,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4001.06,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4004.83,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4072.08,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3999.51,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3988.46,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4038.49,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3831.61,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3753.1,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3685.54,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3627.71,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3710.11,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3720.09,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3714.21,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3698.62,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3661.65,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3693.91,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3550.95,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3520.36,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3326.22,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3365.76,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3458.37,\n      'zoneKey': 'JP-HKD',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'denkiyoho.hepco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3373.65,\n      'zoneKey': 'JP-HKD',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-HR]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3230.696,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3251.868,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3165.838,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3233.988,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3203.468,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3166.794,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3214.286,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3264.428,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3326.01,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3307.368,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3368.106,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3338.748,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3336.408,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3390.914,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3470.982,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3368.72,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3449.986,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3277.33,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3592.554,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3681.134,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3596.894,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3912.08,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3843.938,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4015.338,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3616.292,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3549.886,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3672.19,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3591.696,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3485.642,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3566.232,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3553.45,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3546.618,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3644.288,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3653.866,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3376.944,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3587.65,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3733.164,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3882.694,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3877.302,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3713.59,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3527.198,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3509.952,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3543.418,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3443.906,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3371.046,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3332.022,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3350.862,\n      'zoneKey': 'JP-HR',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.rikuden.co.jp/nw/denki-yoho',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3335.774,\n      'zoneKey': 'JP-HR',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-KN]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12782.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12456.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12144.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12038.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12144.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12618.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12862.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13274.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13430.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13592.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13316.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13564.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13686.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13524.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12774.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12656.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13232.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13798.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13670.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14252.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14344.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14156.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13744.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13228.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13046.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12816.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13146.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13278.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13424.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13784.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14222.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14046.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13894.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13808.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14166.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14014.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14348.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14052.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13978.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14086.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13922.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14048.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14352.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14146.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14050.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13798.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13564.0,\n      'zoneKey': 'JP-KN',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kansai-td.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13068.0,\n      'zoneKey': 'JP-KN',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-KY]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8064.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7874.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7872.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 7841.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8077.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8474.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8736.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9113.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9278.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9413.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9665.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9619.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9956.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9909.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10054.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9871.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10617.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11607.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11868.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12017.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12062.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12392.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12422.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12438.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12223.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11930.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12178.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12238.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12118.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11984.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11642.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11660.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11395.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10705.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10754.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10012.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9510.17,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9931.67,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9512.17,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9788.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9573.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9537.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9281.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9109.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9050.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8872.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8805.0,\n      'zoneKey': 'JP-KY',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 7, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 8643.0,\n      'zoneKey': 'JP-KY',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-ON]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 695.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 684.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 667.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 673.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 666.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 699.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 703.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 724.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 716.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 732.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 724.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 724.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 724.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 746.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 771.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 791.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 836.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 822.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 815.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 833.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 845.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 854.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 863.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 881.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 871.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 862.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 877.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 876.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 865.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 851.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 832.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 823.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 817.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 812.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 804.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 800.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 820.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 840.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 856.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 854.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 844.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 832.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 774.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 774.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 748.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 727.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 714.0,\n      'zoneKey': 'JP-ON',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 15, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.okiden.co.jp/denki2/',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 693.0,\n      'zoneKey': 'JP-ON',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-SK]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3259.236,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3232.686,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3217.378,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3192.054,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3157.478,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3184.824,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3286.14,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3315.252,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3359.97,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3366.37,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3456.512,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3404.592,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3512.952,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3762.704,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3872.106,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3637.21,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3597.428,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3988.986,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4042.326,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4197.934,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4090.384,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4085.214,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4080.98,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4032.126,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3907.984,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3924.268,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4016.182,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3986.182,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3944.382,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3901.15,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3833.43,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3670.28,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3683.608,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4107.0,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4152.984,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4172.688,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 4060.88,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3989.122,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3926.602,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3684.116,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3680.13,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3585.11,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3591.036,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3595.242,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3447.276,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3423.726,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3343.85,\n      'zoneKey': 'JP-SK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.yonden.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 3232.546,\n      'zoneKey': 'JP-SK',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-TH]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9789.556,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 9823.328,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10234.792,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10590.276,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10837.8,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11153.04,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11303.106,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12154.032,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12232.208,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12267.2,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12336.12,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12471.986,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12629.532,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12619.378,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12637.86,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13083.036,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14065.182,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14553.758,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14099.432,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14250.134,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13963.118,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 14019.156,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13943.004,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13778.558,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13723.248,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13434.146,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13460.096,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13309.544,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13394.496,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13349.974,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13315.978,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13167.058,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13271.698,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13241.782,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13506.25,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13618.052,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13714.21,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13612.954,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13877.742,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13674.8,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13361.01,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 13193.886,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12946.384,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 12624.75,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11549.638,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 11328.858,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10986.496,\n      'zoneKey': 'JP-TH',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'setsuden.nw.tohoku-epco.co.jp',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 10870.146,\n      'zoneKey': 'JP-TH',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_generation_forecast[JP-TK]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 20112.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 19385.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 18992.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 19044.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 19295.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 19598.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 19852.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 20006.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 20184.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 20391.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 20852.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 21075.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 21785.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 22164.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 22420.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 22873.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 24591.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 25993.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 27188.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 28470.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 29485.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 30500.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 31252.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 31554.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 31493.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 31443.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 30851.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 30204.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 29525.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 28189.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 26820.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 26182.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 25282.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 25128.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 25271.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 25411.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 26625.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 27585.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 27135.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 26653.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 26126.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 25664.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 24022.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 22996.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 23738.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 22542.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 22003.0,\n      'zoneKey': 'JP-TK',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 4, 16, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'source': 'www.tepco.co.jp/forecast',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'value': 20783.0,\n      'zoneKey': 'JP-TK',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_JP_KY.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 4, 25, 16, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Tokyo')),\n      'production': dict({\n        'biomass': 0,\n        'coal': 0,\n        'gas': 0,\n        'nuclear': 3119.0,\n        'oil': 0,\n        'solar': np.float64(2100.0),\n        'unknown': np.float64(3861.0),\n      }),\n      'source': 'www.kyuden.co.jp',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'JP-KY',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_KPX.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption_realtime\n  list([\n    dict({\n      'consumption': 64798.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64505.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64236.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63929.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63680.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63305.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63120.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62837.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62785.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62386.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62165.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61709.0,\n      'datetime': datetime.datetime(2025, 1, 5, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61522.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61325.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61159.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60742.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60441.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60361.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60327.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60246.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60372.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60168.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59833.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59714.0,\n      'datetime': datetime.datetime(2025, 1, 5, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59653.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59393.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59335.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59290.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58828.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58905.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58767.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58524.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58508.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58249.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58001.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58077.0,\n      'datetime': datetime.datetime(2025, 1, 5, 2, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58102.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58072.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57938.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57876.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57982.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58001.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57719.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57569.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57802.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57782.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57789.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57740.0,\n      'datetime': datetime.datetime(2025, 1, 5, 3, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57775.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57780.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57906.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57664.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57698.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57542.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57837.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57748.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57890.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57702.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 57882.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58095.0,\n      'datetime': datetime.datetime(2025, 1, 5, 4, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58259.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58290.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58160.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58285.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58197.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58090.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58270.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58472.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58549.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58790.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59050.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58964.0,\n      'datetime': datetime.datetime(2025, 1, 5, 5, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 58867.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59194.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59157.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59342.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59295.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59505.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59446.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59758.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59755.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59897.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59801.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 59722.0,\n      'datetime': datetime.datetime(2025, 1, 5, 6, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60031.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60264.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60718.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60630.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60368.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60510.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60288.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60458.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60112.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60357.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60599.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 60842.0,\n      'datetime': datetime.datetime(2025, 1, 5, 7, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61188.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61145.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61044.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61352.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61294.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61476.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 61680.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62028.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62273.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62332.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62550.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62451.0,\n      'datetime': datetime.datetime(2025, 1, 5, 8, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62502.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62566.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62188.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62735.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63007.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63012.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63269.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63348.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63261.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63359.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63375.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63321.0,\n      'datetime': datetime.datetime(2025, 1, 5, 9, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63541.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63783.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63610.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63514.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63930.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63806.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63693.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63769.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63841.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63711.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63259.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63398.0,\n      'datetime': datetime.datetime(2025, 1, 5, 10, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63675.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63768.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63708.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63730.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63774.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63926.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63822.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63741.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63497.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63799.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63606.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63539.0,\n      'datetime': datetime.datetime(2025, 1, 5, 11, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63443.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63366.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63394.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63346.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63288.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63456.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63314.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63381.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63376.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63265.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63685.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63533.0,\n      'datetime': datetime.datetime(2025, 1, 5, 12, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63555.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63599.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63820.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63733.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63650.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63490.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63357.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63619.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63699.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63383.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63045.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63406.0,\n      'datetime': datetime.datetime(2025, 1, 5, 13, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63435.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63394.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63122.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62966.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62913.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63205.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63233.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62914.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62701.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62883.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63220.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63115.0,\n      'datetime': datetime.datetime(2025, 1, 5, 14, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63082.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 62988.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63295.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63248.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63226.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63468.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63563.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63535.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63543.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63707.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63823.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64123.0,\n      'datetime': datetime.datetime(2025, 1, 5, 15, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64032.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63709.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63796.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64156.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64435.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64650.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64647.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64559.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65162.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65504.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65138.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65670.0,\n      'datetime': datetime.datetime(2025, 1, 5, 16, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65926.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66386.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66475.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66871.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66660.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66955.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67175.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67392.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67686.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67907.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68191.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68287.0,\n      'datetime': datetime.datetime(2025, 1, 5, 17, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68367.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68177.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68147.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68174.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68213.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68331.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68125.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 68011.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67898.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67796.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67887.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67713.0,\n      'datetime': datetime.datetime(2025, 1, 5, 18, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67662.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67903.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67658.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67419.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67429.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67317.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67296.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 67029.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66917.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66985.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66706.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66583.0,\n      'datetime': datetime.datetime(2025, 1, 5, 19, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66528.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66358.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66433.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66135.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66362.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66158.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 66011.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65735.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65755.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65873.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65764.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65432.0,\n      'datetime': datetime.datetime(2025, 1, 5, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65288.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64873.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 65003.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64668.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64439.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64274.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64601.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64303.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64214.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64287.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63712.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63908.0,\n      'datetime': datetime.datetime(2025, 1, 5, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64144.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64365.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64359.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64458.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64500.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64300.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64174.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64146.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63669.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63678.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63599.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63436.0,\n      'datetime': datetime.datetime(2025, 1, 5, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 63838.0,\n      'datetime': datetime.datetime(2025, 1, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64632.0,\n      'datetime': datetime.datetime(2025, 1, 5, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'consumption': 64918.0,\n      'datetime': datetime.datetime(2025, 1, 5, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'KR',\n    }),\n  ])\n# ---\n# name: test_fetch_production_realtime\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14191.075,\n        'gas': 21242.1,\n        'hydro': 38.1576,\n        'nuclear': 24132.1,\n        'oil': 361.51,\n        'solar': 0.0,\n        'unknown': 3212.03,\n        'wind': 440.859,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1168.98,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14190.524,\n        'gas': 20873.5,\n        'hydro': 36.1821,\n        'nuclear': 24183.2,\n        'oil': 361.527,\n        'solar': 0.0,\n        'unknown': 3214.68,\n        'wind': 470.42,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1165.73,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14269.455,\n        'gas': 20567.0,\n        'hydro': 36.0934,\n        'nuclear': 24169.9,\n        'oil': 361.922,\n        'solar': 0.0,\n        'unknown': 3198.27,\n        'wind': 461.526,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1163.87,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14152.906,\n        'gas': 20524.3,\n        'hydro': 36.0887,\n        'nuclear': 24157.8,\n        'oil': 361.538,\n        'solar': 0.0,\n        'unknown': 3181.6,\n        'wind': 466.664,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1038.83,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14328.314,\n        'gas': 20407.2,\n        'hydro': 36.0563,\n        'nuclear': 24189.1,\n        'oil': 362.933,\n        'solar': 0.0,\n        'unknown': 3173.52,\n        'wind': 478.882,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -693.423,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14329.32,\n        'gas': 20069.5,\n        'hydro': 36.0797,\n        'nuclear': 24170.2,\n        'oil': 362.799,\n        'solar': 0.0,\n        'unknown': 3170.81,\n        'wind': 463.816,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -691.803,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14340.718,\n        'gas': 19835.6,\n        'hydro': 36.2887,\n        'nuclear': 24199.9,\n        'oil': 361.121,\n        'solar': 0.0,\n        'unknown': 3180.16,\n        'wind': 462.251,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -694.062,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14346.741,\n        'gas': 19896.6,\n        'hydro': 36.2017,\n        'nuclear': 24151.4,\n        'oil': 362.47,\n        'solar': 0.0,\n        'unknown': 3163.46,\n        'wind': 468.733,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -399.7,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14397.983,\n        'gas': 19803.7,\n        'hydro': 36.1953,\n        'nuclear': 24147.0,\n        'oil': 362.279,\n        'solar': 0.0,\n        'unknown': 3165.69,\n        'wind': 461.708,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -399.101,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14358.304,\n        'gas': 19471.2,\n        'hydro': 36.165,\n        'nuclear': 24121.1,\n        'oil': 362.252,\n        'solar': 0.0,\n        'unknown': 3164.28,\n        'wind': 464.734,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -397.705,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14350.904,\n        'gas': 19210.3,\n        'hydro': 36.1917,\n        'nuclear': 24166.3,\n        'oil': 361.124,\n        'solar': 0.0,\n        'unknown': 3171.72,\n        'wind': 460.769,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -396.587,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14435.728,\n        'gas': 18670.9,\n        'hydro': 36.1654,\n        'nuclear': 24166.0,\n        'oil': 362.496,\n        'solar': 0.0,\n        'unknown': 3177.62,\n        'wind': 453.833,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -395.35,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14471.603,\n        'gas': 18609.3,\n        'hydro': 36.2448,\n        'nuclear': 24157.6,\n        'oil': 362.67,\n        'solar': 0.0,\n        'unknown': 3175.42,\n        'wind': 456.347,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -243.001,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14475.367,\n        'gas': 18661.9,\n        'hydro': 36.3584,\n        'nuclear': 24156.1,\n        'oil': 360.827,\n        'solar': 0.0,\n        'unknown': 3173.46,\n        'wind': 450.406,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14494.358,\n        'gas': 18465.5,\n        'hydro': 36.2203,\n        'nuclear': 24162.9,\n        'oil': 361.19,\n        'solar': 0.0,\n        'unknown': 3175.65,\n        'wind': 465.948,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 13.6875,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14614.655,\n        'gas': 18171.0,\n        'hydro': 39.3681,\n        'nuclear': 24167.3,\n        'oil': 362.781,\n        'solar': 0.0,\n        'unknown': 3172.11,\n        'wind': 467.07,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 263.156,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14649.917,\n        'gas': 17903.9,\n        'hydro': 39.2688,\n        'nuclear': 24150.6,\n        'oil': 361.823,\n        'solar': 0.0,\n        'unknown': 3169.61,\n        'wind': 473.956,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 319.661,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14691.644,\n        'gas': 18197.8,\n        'hydro': 39.3378,\n        'nuclear': 24178.0,\n        'oil': 362.212,\n        'solar': 0.0,\n        'unknown': 3162.46,\n        'wind': 469.297,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 750.092,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14758.653,\n        'gas': 18476.2,\n        'hydro': 39.3844,\n        'nuclear': 24169.7,\n        'oil': 362.154,\n        'solar': 0.0,\n        'unknown': 3169.86,\n        'wind': 463.928,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1122.33,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14676.438,\n        'gas': 18811.1,\n        'hydro': 39.3406,\n        'nuclear': 24166.4,\n        'oil': 362.113,\n        'solar': 0.0,\n        'unknown': 3163.81,\n        'wind': 461.985,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1445.14,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14776.08,\n        'gas': 19150.4,\n        'hydro': 39.3972,\n        'nuclear': 24179.5,\n        'oil': 362.655,\n        'solar': 0.0,\n        'unknown': 3170.49,\n        'wind': 447.686,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1764.86,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14694.186,\n        'gas': 19086.6,\n        'hydro': 39.3567,\n        'nuclear': 24140.2,\n        'oil': 362.72,\n        'solar': 0.0,\n        'unknown': 3175.53,\n        'wind': 431.951,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1772.93,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14647.789,\n        'gas': 18789.5,\n        'hydro': 39.3555,\n        'nuclear': 24150.0,\n        'oil': 362.101,\n        'solar': 0.0,\n        'unknown': 3177.2,\n        'wind': 426.055,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1768.77,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14733.222,\n        'gas': 18719.4,\n        'hydro': 39.2489,\n        'nuclear': 24186.4,\n        'oil': 362.519,\n        'solar': 0.0,\n        'unknown': 3182.56,\n        'wind': 432.408,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1952.31,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14693.522,\n        'gas': 18862.6,\n        'hydro': 39.326,\n        'nuclear': 24172.7,\n        'oil': 361.968,\n        'solar': 0.0,\n        'unknown': 3187.62,\n        'wind': 430.339,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2104.96,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14740.635,\n        'gas': 18588.2,\n        'hydro': 39.2935,\n        'nuclear': 24169.1,\n        'oil': 362.311,\n        'solar': 0.0,\n        'unknown': 3186.8,\n        'wind': 436.087,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2139.49,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14735.524,\n        'gas': 18774.6,\n        'hydro': 39.4017,\n        'nuclear': 24147.3,\n        'oil': 362.954,\n        'solar': 0.0,\n        'unknown': 3187.13,\n        'wind': 440.094,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2362.89,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14784.575,\n        'gas': 18670.2,\n        'hydro': 39.3569,\n        'nuclear': 24176.9,\n        'oil': 362.97,\n        'solar': 0.0,\n        'unknown': 3185.98,\n        'wind': 423.166,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2362.84,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14682.459,\n        'gas': 18336.4,\n        'hydro': 39.2663,\n        'nuclear': 24167.1,\n        'oil': 362.396,\n        'solar': 0.0,\n        'unknown': 3185.55,\n        'wind': 407.889,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2362.9,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14788.176,\n        'gas': 18301.8,\n        'hydro': 39.3441,\n        'nuclear': 24171.9,\n        'oil': 363.39,\n        'solar': 0.0,\n        'unknown': 3182.78,\n        'wind': 414.812,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2367.05,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14807.431,\n        'gas': 18604.8,\n        'hydro': 39.617,\n        'nuclear': 24138.1,\n        'oil': 363.116,\n        'solar': 0.0,\n        'unknown': 3184.28,\n        'wind': 416.764,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2796.41,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14695.139,\n        'gas': 18450.2,\n        'hydro': 39.4541,\n        'nuclear': 24178.6,\n        'oil': 362.282,\n        'solar': 0.0,\n        'unknown': 3190.45,\n        'wind': 397.973,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2798.87,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14788.887,\n        'gas': 18321.5,\n        'hydro': 39.3653,\n        'nuclear': 24177.2,\n        'oil': 362.544,\n        'solar': 0.0,\n        'unknown': 3191.95,\n        'wind': 405.127,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2788.74,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14695.884,\n        'gas': 18175.4,\n        'hydro': 39.3838,\n        'nuclear': 24151.4,\n        'oil': 361.964,\n        'solar': 0.0,\n        'unknown': 3194.68,\n        'wind': 410.883,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2789.84,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14695.67,\n        'gas': 17937.5,\n        'hydro': 39.363,\n        'nuclear': 24169.7,\n        'oil': 320.95,\n        'solar': 0.0,\n        'unknown': 3193.64,\n        'wind': 427.397,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2792.56,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 2, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14805.29,\n        'gas': 17934.9,\n        'hydro': 39.4119,\n        'nuclear': 24134.4,\n        'oil': 305.934,\n        'solar': 0.0,\n        'unknown': 3193.79,\n        'wind': 439.239,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2784.84,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14705.931,\n        'gas': 18006.2,\n        'hydro': 39.4556,\n        'nuclear': 24212.0,\n        'oil': 279.553,\n        'solar': 0.0,\n        'unknown': 3191.97,\n        'wind': 451.587,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2793.69,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14718.189,\n        'gas': 18006.2,\n        'hydro': 39.4651,\n        'nuclear': 24149.0,\n        'oil': 290.725,\n        'solar': 0.0,\n        'unknown': 3189.44,\n        'wind': 459.863,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2789.91,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14582.49,\n        'gas': 18003.0,\n        'hydro': 39.4675,\n        'nuclear': 24151.2,\n        'oil': 288.24,\n        'solar': 0.0,\n        'unknown': 3193.77,\n        'wind': 462.49,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2791.12,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14827.51,\n        'gas': 17955.3,\n        'hydro': 39.4332,\n        'nuclear': 24144.9,\n        'oil': 291.148,\n        'solar': 0.0,\n        'unknown': 3203.45,\n        'wind': 466.616,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3060.05,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14710.301,\n        'gas': 18175.1,\n        'hydro': 39.4767,\n        'nuclear': 24197.0,\n        'oil': 290.235,\n        'solar': 0.0,\n        'unknown': 3195.73,\n        'wind': 465.351,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3100.4,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14722.374,\n        'gas': 18190.4,\n        'hydro': 39.411,\n        'nuclear': 24171.4,\n        'oil': 289.782,\n        'solar': 0.0,\n        'unknown': 3199.28,\n        'wind': 479.103,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3098.65,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14572.086,\n        'gas': 18054.0,\n        'hydro': 39.4818,\n        'nuclear': 24165.9,\n        'oil': 289.824,\n        'solar': 0.0,\n        'unknown': 3197.2,\n        'wind': 494.02,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3101.26,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14696.645,\n        'gas': 17773.0,\n        'hydro': 39.4472,\n        'nuclear': 24158.3,\n        'oil': 290.177,\n        'solar': 0.0,\n        'unknown': 3203.43,\n        'wind': 492.103,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3093.01,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14823.097,\n        'gas': 17861.3,\n        'hydro': 39.5763,\n        'nuclear': 24165.5,\n        'oil': 291.794,\n        'solar': 0.0,\n        'unknown': 3207.68,\n        'wind': 488.163,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3084.37,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14726.755,\n        'gas': 17964.4,\n        'hydro': 39.3303,\n        'nuclear': 24145.7,\n        'oil': 290.261,\n        'solar': 0.0,\n        'unknown': 3211.85,\n        'wind': 489.994,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3094.06,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14636.741,\n        'gas': 18028.6,\n        'hydro': 39.4254,\n        'nuclear': 24178.1,\n        'oil': 289.872,\n        'solar': 0.0,\n        'unknown': 3213.14,\n        'wind': 492.009,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3097.81,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 3, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14701.459,\n        'gas': 17916.9,\n        'hydro': 39.3915,\n        'nuclear': 24161.6,\n        'oil': 291.226,\n        'solar': 0.0,\n        'unknown': 3215.35,\n        'wind': 497.072,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3091.93,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14748.136,\n        'gas': 17857.0,\n        'hydro': 47.3072,\n        'nuclear': 24190.6,\n        'oil': 290.64,\n        'solar': 0.0,\n        'unknown': 3211.28,\n        'wind': 510.679,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3088.26,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14729.739,\n        'gas': 17944.8,\n        'hydro': 48.7064,\n        'nuclear': 24153.9,\n        'oil': 290.467,\n        'solar': 0.0,\n        'unknown': 3214.07,\n        'wind': 512.051,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3121.96,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14722.703,\n        'gas': 18350.0,\n        'hydro': 48.8873,\n        'nuclear': 24182.5,\n        'oil': 290.046,\n        'solar': 0.0,\n        'unknown': 3213.25,\n        'wind': 513.986,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3423.24,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14697.844,\n        'gas': 18161.6,\n        'hydro': 49.2758,\n        'nuclear': 24158.3,\n        'oil': 290.102,\n        'solar': 0.0,\n        'unknown': 3212.61,\n        'wind': 506.656,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3420.25,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14699.083,\n        'gas': 18190.5,\n        'hydro': 50.1568,\n        'nuclear': 24172.3,\n        'oil': 289.5,\n        'solar': 0.0,\n        'unknown': 3203.26,\n        'wind': 502.092,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3417.15,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14640.634,\n        'gas': 18097.8,\n        'hydro': 48.9218,\n        'nuclear': 24183.5,\n        'oil': 289.247,\n        'solar': 0.0,\n        'unknown': 3203.92,\n        'wind': 488.416,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3418.97,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14716.59,\n        'gas': 18302.0,\n        'hydro': 47.8385,\n        'nuclear': 24190.8,\n        'oil': 290.495,\n        'solar': 0.0,\n        'unknown': 3200.8,\n        'wind': 490.07,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3409.69,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14680.718,\n        'gas': 18303.0,\n        'hydro': 48.9115,\n        'nuclear': 24149.4,\n        'oil': 290.341,\n        'solar': 0.0,\n        'unknown': 3195.86,\n        'wind': 483.873,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3412.79,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14719.983,\n        'gas': 18398.0,\n        'hydro': 49.7902,\n        'nuclear': 24158.4,\n        'oil': 291.257,\n        'solar': 0.0,\n        'unknown': 3195.83,\n        'wind': 478.861,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3410.77,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14637.215,\n        'gas': 18260.6,\n        'hydro': 48.265,\n        'nuclear': 24185.7,\n        'oil': 289.287,\n        'solar': 0.0,\n        'unknown': 3197.83,\n        'wind': 488.814,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3413.35,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14695.546,\n        'gas': 18396.5,\n        'hydro': 48.0326,\n        'nuclear': 24157.2,\n        'oil': 289.397,\n        'solar': 0.0,\n        'unknown': 3200.93,\n        'wind': 494.634,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3408.92,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 4, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14630.773,\n        'gas': 18657.9,\n        'hydro': 48.31,\n        'nuclear': 24184.3,\n        'oil': 289.645,\n        'solar': 0.0,\n        'unknown': 3194.68,\n        'wind': 492.765,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 3412.64,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14609.153,\n        'gas': 18411.7,\n        'hydro': 49.6208,\n        'nuclear': 24175.1,\n        'oil': 289.317,\n        'solar': 0.0,\n        'unknown': 3194.66,\n        'wind': 505.327,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2984.03,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14688.644,\n        'gas': 18392.9,\n        'hydro': 48.1514,\n        'nuclear': 24144.8,\n        'oil': 290.073,\n        'solar': 0.0,\n        'unknown': 3193.37,\n        'wind': 497.255,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2973.38,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14621.345,\n        'gas': 18321.7,\n        'hydro': 49.1691,\n        'nuclear': 24153.9,\n        'oil': 289.584,\n        'solar': 0.0,\n        'unknown': 3190.7,\n        'wind': 502.937,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2978.18,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14769.89,\n        'gas': 18274.1,\n        'hydro': 48.0088,\n        'nuclear': 24166.6,\n        'oil': 290.08,\n        'solar': 0.0,\n        'unknown': 3200.84,\n        'wind': 497.331,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2969.85,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14569.166,\n        'gas': 18086.1,\n        'hydro': 48.0314,\n        'nuclear': 24186.3,\n        'oil': 290.068,\n        'solar': 0.0,\n        'unknown': 3200.82,\n        'wind': 470.329,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2663.12,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14576.728,\n        'gas': 17674.6,\n        'hydro': 47.5713,\n        'nuclear': 24149.4,\n        'oil': 290.037,\n        'solar': 0.0,\n        'unknown': 3209.24,\n        'wind': 469.556,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2335.84,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14626.859,\n        'gas': 17513.7,\n        'hydro': 48.9161,\n        'nuclear': 24198.8,\n        'oil': 291.21,\n        'solar': 0.0,\n        'unknown': 3200.67,\n        'wind': 457.452,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2075.62,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14773.405,\n        'gas': 17563.2,\n        'hydro': 48.9603,\n        'nuclear': 24159.7,\n        'oil': 291.127,\n        'solar': 0.0,\n        'unknown': 3262.01,\n        'wind': 438.202,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 2074.13,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14770.749,\n        'gas': 17315.3,\n        'hydro': 47.8982,\n        'nuclear': 24153.1,\n        'oil': 290.285,\n        'solar': 0.0,\n        'unknown': 3292.84,\n        'wind': 435.451,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1766.12,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14669.963,\n        'gas': 17071.8,\n        'hydro': 49.5586,\n        'nuclear': 24149.9,\n        'oil': 290.915,\n        'solar': 0.0,\n        'unknown': 3299.37,\n        'wind': 422.452,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1173.91,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14677.046,\n        'gas': 17269.1,\n        'hydro': 50.4952,\n        'nuclear': 24174.4,\n        'oil': 290.556,\n        'solar': 0.0,\n        'unknown': 3300.97,\n        'wind': 412.971,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1136.19,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 5, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14656.166,\n        'gas': 16730.1,\n        'hydro': 48.1058,\n        'nuclear': 24167.2,\n        'oil': 290.891,\n        'solar': 0.0,\n        'unknown': 3305.23,\n        'wind': 396.479,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 639.264,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14607.146,\n        'gas': 16677.6,\n        'hydro': 48.689,\n        'nuclear': 24175.7,\n        'oil': 289.901,\n        'solar': 8.2849,\n        'unknown': 3314.66,\n        'wind': 383.186,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 639.917,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14777.451,\n        'gas': 16834.6,\n        'hydro': 49.4709,\n        'nuclear': 24168.9,\n        'oil': 291.073,\n        'solar': 8.28808,\n        'unknown': 3324.62,\n        'wind': 377.016,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 638.587,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14686.697,\n        'gas': 16870.2,\n        'hydro': 47.7793,\n        'nuclear': 24192.9,\n        'oil': 290.735,\n        'solar': 7.60632,\n        'unknown': 3328.11,\n        'wind': 370.587,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 639.103,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14644.128,\n        'gas': 16841.0,\n        'hydro': 49.1992,\n        'nuclear': 24158.0,\n        'oil': 290.446,\n        'solar': 8.19936,\n        'unknown': 3330.64,\n        'wind': 399.828,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 381.401,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14673.976,\n        'gas': 16758.6,\n        'hydro': 49.4636,\n        'nuclear': 24171.8,\n        'oil': 290.783,\n        'solar': 8.10165,\n        'unknown': 3327.75,\n        'wind': 393.711,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 380.61,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14679.67,\n        'gas': 16945.6,\n        'hydro': 50.5755,\n        'nuclear': 24175.1,\n        'oil': 289.892,\n        'solar': 7.63886,\n        'unknown': 3333.13,\n        'wind': 402.175,\n      }),\n      'source': 'new.kpx.or.kr',\n      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'hydro': 50.0124,\n        'nuclear': 24167.5,\n        'oil': 289.915,\n        'solar': 8.52564,\n        'unknown': 3332.31,\n        'wind': 398.118,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 380.61,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14727.151,\n        'gas': 17165.3,\n        'hydro': 48.4085,\n        'nuclear': 24157.2,\n        'oil': 290.743,\n        'solar': 7.99887,\n        'unknown': 3338.66,\n        'wind': 398.172,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 379.863,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14772.489,\n        'gas': 17262.6,\n        'hydro': 50.0722,\n        'nuclear': 24138.6,\n        'oil': 290.03,\n        'solar': 8.23244,\n        'unknown': 3350.17,\n        'wind': 403.184,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 379.863,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14602.203,\n        'gas': 17302.5,\n        'hydro': 48.6016,\n        'nuclear': 24174.7,\n        'oil': 289.822,\n        'solar': 8.34948,\n        'unknown': 3345.03,\n        'wind': 410.254,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 381.401,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 6, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14727.253,\n        'gas': 17106.5,\n        'hydro': 49.6315,\n        'nuclear': 24154.0,\n        'oil': 290.832,\n        'solar': 7.75305,\n        'unknown': 3352.17,\n        'wind': 412.101,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 379.116,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14679.925,\n        'gas': 17126.5,\n        'hydro': 48.0471,\n        'nuclear': 24135.2,\n        'oil': 291.207,\n        'solar': 8.62396,\n        'unknown': 3352.27,\n        'wind': 383.169,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -4.87793,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 7, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14750.532,\n        'gas': 17295.8,\n        'hydro': 49.3261,\n        'nuclear': 24141.4,\n        'oil': 290.711,\n        'solar': 8.53475,\n        'unknown': 3353.47,\n        'wind': 372.979,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14839.293,\n        'gas': 17600.1,\n        'hydro': 49.317,\n        'nuclear': 24177.1,\n        'oil': 290.701,\n        'solar': 8.45652,\n        'unknown': 3356.54,\n        'wind': 395.363,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14657.483,\n        'gas': 17693.5,\n        'hydro': 49.0114,\n        'nuclear': 24166.7,\n        'oil': 290.964,\n        'solar': 8.94349,\n        'unknown': 3360.59,\n        'wind': 401.083,\n      }),\n      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'gas': 17479.6,\n        'hydro': 49.1244,\n        'nuclear': 24151.2,\n        'oil': 291.013,\n        'solar': 8.55931,\n        'unknown': 3360.5,\n        'wind': 424.279,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14700.32,\n        'gas': 17286.0,\n        'hydro': 48.7974,\n        'nuclear': 24166.5,\n        'oil': 291.117,\n        'solar': 9.22994,\n        'unknown': 3360.49,\n        'wind': 424.484,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 7, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14693.073,\n        'gas': 17477.4,\n        'hydro': 48.0983,\n        'nuclear': 24149.4,\n        'oil': 290.409,\n        'solar': 8.07907,\n        'unknown': 3355.67,\n        'wind': 434.858,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14536.17,\n        'gas': 17256.1,\n        'hydro': 47.9,\n        'nuclear': 24160.8,\n        'oil': 289.84,\n        'solar': 8.8211,\n        'unknown': 3364.44,\n        'wind': 446.586,\n      }),\n      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'gas': 17580.9,\n        'hydro': 48.7882,\n        'nuclear': 24172.4,\n        'oil': 289.872,\n        'solar': 9.13717,\n        'unknown': 3366.41,\n        'wind': 463.027,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 7, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14636.139,\n        'gas': 17853.3,\n        'hydro': 49.5613,\n        'nuclear': 24173.4,\n        'oil': 289.345,\n        'solar': 9.47443,\n        'unknown': 3361.25,\n        'wind': 468.075,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14761.259,\n        'gas': 18016.5,\n        'hydro': 113.055,\n        'nuclear': 24157.5,\n        'oil': 290.073,\n        'solar': 9.87947,\n        'unknown': 3363.52,\n        'wind': 474.854,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14665.232,\n        'gas': 17810.0,\n        'hydro': 353.224,\n        'nuclear': 24173.3,\n        'oil': 290.366,\n        'solar': 11.041,\n        'unknown': 3362.45,\n        'wind': 478.814,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14723.398,\n        'gas': 17544.4,\n        'hydro': 449.797,\n        'nuclear': 24166.0,\n        'oil': 293.08,\n        'solar': 15.0904,\n        'unknown': 3356.18,\n        'wind': 494.362,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14799.977,\n        'gas': 17797.6,\n        'hydro': 409.347,\n        'nuclear': 24171.6,\n        'oil': 291.128,\n        'solar': 18.3638,\n        'unknown': 3354.46,\n        'wind': 508.457,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14743.577,\n        'gas': 17830.4,\n        'hydro': 371.559,\n        'nuclear': 24161.4,\n        'oil': 290.246,\n        'solar': 24.3175,\n        'unknown': 3362.0,\n        'wind': 508.579,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14678.755,\n        'gas': 18015.8,\n        'hydro': 392.474,\n        'nuclear': 24189.5,\n        'oil': 291.626,\n        'solar': 34.629,\n        'unknown': 3356.71,\n        'wind': 515.061,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14649.989,\n        'gas': 18245.0,\n        'hydro': 391.526,\n        'nuclear': 24173.9,\n        'oil': 294.834,\n        'solar': 45.4197,\n        'unknown': 3355.11,\n        'wind': 522.871,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14717.842,\n        'gas': 18499.0,\n        'hydro': 392.857,\n        'nuclear': 24182.0,\n        'oil': 292.057,\n        'solar': 60.0754,\n        'unknown': 3347.44,\n        'wind': 535.399,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14773.479,\n        'gas': 18711.1,\n        'hydro': 418.665,\n        'nuclear': 24128.4,\n        'oil': 291.557,\n        'solar': 81.5168,\n        'unknown': 3340.59,\n        'wind': 526.627,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14733.828,\n        'gas': 18748.7,\n        'hydro': 403.837,\n        'nuclear': 24168.2,\n        'oil': 291.471,\n        'solar': 97.46,\n        'unknown': 3338.49,\n        'wind': 548.63,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14744.424,\n        'gas': 18881.6,\n        'hydro': 402.98,\n        'nuclear': 24172.7,\n        'oil': 291.656,\n        'solar': 121.118,\n        'unknown': 3342.07,\n        'wind': 591.885,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 8, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14655.684,\n        'gas': 18909.1,\n        'hydro': 401.236,\n        'nuclear': 24161.7,\n        'oil': 289.86,\n        'solar': 148.736,\n        'unknown': 3334.82,\n        'wind': 570.176,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 20.957,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14567.097,\n        'gas': 18982.3,\n        'hydro': 466.645,\n        'nuclear': 24156.5,\n        'oil': 289.308,\n        'solar': 181.836,\n        'unknown': 3332.79,\n        'wind': 556.178,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 32.6088,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14795.776,\n        'gas': 18687.9,\n        'hydro': 511.24,\n        'nuclear': 24139.5,\n        'oil': 290.883,\n        'solar': 213.058,\n        'unknown': 3327.95,\n        'wind': 568.06,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -29.7058,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14588.011,\n        'gas': 18448.6,\n        'hydro': 536.358,\n        'nuclear': 24175.1,\n        'oil': 290.972,\n        'solar': 239.274,\n        'unknown': 3322.17,\n        'wind': 567.861,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -18.3879,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14720.534,\n        'gas': 18773.3,\n        'hydro': 554.47,\n        'nuclear': 24136.1,\n        'oil': 290.041,\n        'solar': 291.485,\n        'unknown': 3340.71,\n        'wind': 568.236,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -58.8004,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14817.175,\n        'gas': 18872.4,\n        'hydro': 544.932,\n        'nuclear': 24183.9,\n        'oil': 291.617,\n        'solar': 304.006,\n        'unknown': 3359.1,\n        'wind': 590.229,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -42.4511,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14681.176,\n        'gas': 19007.0,\n        'hydro': 549.084,\n        'nuclear': 24182.1,\n        'oil': 290.886,\n        'solar': 316.577,\n        'unknown': 3357.15,\n        'wind': 594.327,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -32.3917,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14709.72,\n        'gas': 19190.6,\n        'hydro': 569.188,\n        'nuclear': 24161.9,\n        'oil': 291.496,\n        'solar': 356.198,\n        'unknown': 3350.46,\n        'wind': 573.938,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -64.1956,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14826.476,\n        'gas': 19157.3,\n        'hydro': 557.728,\n        'nuclear': 24165.1,\n        'oil': 292.214,\n        'solar': 392.004,\n        'unknown': 3346.1,\n        'wind': 572.116,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -37.2565,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14718.005,\n        'gas': 19201.8,\n        'hydro': 548.785,\n        'nuclear': 24159.2,\n        'oil': 291.624,\n        'solar': 427.566,\n        'unknown': 3334.8,\n        'wind': 554.453,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -23.5994,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14761.946,\n        'gas': 19193.9,\n        'hydro': 544.703,\n        'nuclear': 24157.9,\n        'oil': 291.668,\n        'solar': 482.627,\n        'unknown': 3323.33,\n        'wind': 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    'coal': 14598.156,\n        'gas': 19238.8,\n        'hydro': 543.062,\n        'nuclear': 24194.1,\n        'oil': 290.392,\n        'solar': 590.959,\n        'unknown': 3303.8,\n        'wind': 528.816,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -31.4571,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14608.99,\n        'gas': 19326.6,\n        'hydro': 552.608,\n        'nuclear': 24170.3,\n        'oil': 291.081,\n        'solar': 609.008,\n        'unknown': 3298.74,\n        'wind': 521.126,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -160.866,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14653.176,\n        'gas': 19471.9,\n        'hydro': 554.788,\n        'nuclear': 24149.4,\n        'oil': 290.837,\n        'solar': 650.243,\n        'unknown': 3217.88,\n        'wind': 512.349,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -281.161,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14552.653,\n        'gas': 19267.8,\n        'hydro': 546.776,\n        'nuclear': 24170.1,\n        'oil': 290.654,\n        'solar': 705.779,\n        'unknown': 3213.01,\n        'wind': 508.621,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -353.571,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14586.284,\n        'gas': 19049.6,\n        'hydro': 557.535,\n        'nuclear': 24138.1,\n        'oil': 290.797,\n        'solar': 764.141,\n        'unknown': 3203.88,\n        'wind': 560.983,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -361.701,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14807.574,\n        'gas': 19181.6,\n        'hydro': 554.33,\n        'nuclear': 24143.8,\n        'oil': 291.537,\n        'solar': 816.334,\n        'unknown': 3198.86,\n        'wind': 560.831,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -374.004,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14716.001,\n        'gas': 19082.3,\n        'hydro': 553.042,\n        'nuclear': 24156.6,\n        'oil': 291.525,\n        'solar': 882.947,\n        'unknown': 3197.13,\n        'wind': 573.087,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -352.37,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14586.907,\n        'gas': 19060.6,\n        'hydro': 527.095,\n        'nuclear': 24186.3,\n        'oil': 291.109,\n        'solar': 926.827,\n        'unknown': 3193.53,\n        'wind': 565.107,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -353.985,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14617.462,\n        'gas': 19027.3,\n        'hydro': 547.133,\n        'nuclear': 24189.8,\n        'oil': 291.215,\n        'solar': 980.047,\n        'unknown': 3181.74,\n        'wind': 570.113,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -363.405,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14730.209,\n        'gas': 18984.8,\n        'hydro': 548.364,\n        'nuclear': 24155.4,\n        'oil': 291.326,\n        'solar': 966.747,\n        'unknown': 3164.57,\n        'wind': 569.466,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -429.023,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14684.161,\n        'gas': 18880.6,\n        'hydro': 551.981,\n        'nuclear': 24177.4,\n        'oil': 291.051,\n        'solar': 1023.56,\n        'unknown': 3153.59,\n        'wind': 575.572,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -372.251,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14668.104,\n        'gas': 18638.1,\n        'hydro': 551.368,\n        'nuclear': 24201.4,\n        'oil': 291.103,\n        'solar': 1028.12,\n        'unknown': 3145.27,\n        'wind': 575.756,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n 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'oil': 290.622,\n        'solar': 1157.5,\n        'unknown': 3122.68,\n        'wind': 593.176,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -196.818,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14574.746,\n        'gas': 19156.6,\n        'hydro': 539.535,\n        'nuclear': 24199.1,\n        'oil': 290.803,\n        'solar': 1126.6,\n        'unknown': 3139.82,\n        'wind': 605.18,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -135.023,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14508.208,\n        'gas': 19175.4,\n        'hydro': 552.111,\n        'nuclear': 24174.2,\n        'oil': 291.294,\n        'solar': 1136.23,\n        'unknown': 3120.12,\n        'wind': 616.152,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -133.773,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14649.322,\n        'gas': 18979.4,\n        'hydro': 556.676,\n        'nuclear': 24159.4,\n        'oil': 292.115,\n        'solar': 1204.19,\n        'unknown': 3105.95,\n        'wind': 613.635,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -167.962,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14642.678,\n        'gas': 18996.2,\n        'hydro': 538.153,\n        'nuclear': 24160.6,\n        'oil': 291.422,\n        'solar': 1266.43,\n        'unknown': 3105.49,\n        'wind': 628.683,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -143.448,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14461.491,\n        'gas': 19262.8,\n        'hydro': 529.975,\n        'nuclear': 24191.9,\n        'oil': 291.298,\n        'solar': 1323.38,\n        'unknown': 3100.45,\n        'wind': 643.012,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -120.466,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14547.047,\n        'gas': 19070.7,\n        'hydro': 503.623,\n        'nuclear': 24172.2,\n        'oil': 291.901,\n        'solar': 1332.42,\n        'unknown': 3091.66,\n        'wind': 662.512,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -149.156,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14628.722,\n        'gas': 18870.7,\n        'hydro': 508.818,\n        'nuclear': 24175.6,\n        'oil': 291.597,\n        'solar': 1365.31,\n        'unknown': 3061.47,\n        'wind': 655.937,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -181.837,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14484.815,\n        'gas': 18880.1,\n        'hydro': 500.667,\n        'nuclear': 24146.2,\n        'oil': 291.377,\n        'solar': 1328.74,\n        'unknown': 3058.06,\n        'wind': 664.504,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -141.792,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14610.64,\n        'gas': 19033.3,\n        'hydro': 497.856,\n        'nuclear': 24139.6,\n        'oil': 291.562,\n        'solar': 1325.33,\n        'unknown': 3050.36,\n        'wind': 668.964,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -180.468,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14454.209,\n        'gas': 19137.8,\n        'hydro': 490.207,\n        'nuclear': 24153.5,\n        'oil': 290.838,\n        'solar': 1271.88,\n        'unknown': 3020.04,\n        'wind': 660.095,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -126.47,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 11, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14596.9,\n        'gas': 18915.0,\n        'hydro': 516.52,\n        'nuclear': 24162.3,\n        'oil': 293.089,\n        'solar': 1205.68,\n        'unknown': 3031.19,\n        'wind': 667.727,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -149.574,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14595.607,\n        'gas': 19094.8,\n        'hydro': 430.18,\n        'nuclear': 24150.8,\n        'oil': 291.447,\n        'solar': 1224.46,\n        'unknown': 3043.51,\n        'wind': 667.711,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 57.1039,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14686.684,\n        'gas': 19035.6,\n        'hydro': 416.175,\n        'nuclear': 24161.7,\n        'oil': 292.526,\n        'solar': 1164.25,\n        'unknown': 3029.43,\n        'wind': 674.552,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 95.9953,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14615.159,\n        'gas': 19153.8,\n        'hydro': 411.622,\n        'nuclear': 24169.4,\n        'oil': 292.301,\n        'solar': 1158.78,\n        'unknown': 3026.13,\n        'wind': 664.976,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 98.6626,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14654.952,\n        'gas': 19043.2,\n        'hydro': 414.848,\n        'nuclear': 24153.0,\n        'oil': 291.867,\n        'solar': 1190.02,\n        'unknown': 3016.21,\n        'wind': 673.973,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 93.0684,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14627.149,\n        'gas': 18954.6,\n        'hydro': 413.318,\n        'nuclear': 24155.2,\n        'oil': 290.886,\n        'solar': 1249.97,\n        'unknown': 3026.98,\n        'wind': 678.07,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 108.86,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14680.197,\n        'gas': 19135.1,\n        'hydro': 432.96,\n        'nuclear': 24180.2,\n        'oil': 290.742,\n        'solar': 1373.18,\n        'unknown': 3000.4,\n        'wind': 660.871,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 298.502,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14576.466,\n        'gas': 19146.8,\n        'hydro': 408.433,\n        'nuclear': 24177.9,\n        'oil': 291.033,\n        'solar': 1364.36,\n        'unknown': 2990.25,\n        'wind': 658.96,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 301.387,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14577.198,\n        'gas': 19188.4,\n        'hydro': 429.221,\n        'nuclear': 24195.0,\n        'oil': 290.692,\n        'solar': 1352.64,\n        'unknown': 2971.24,\n        'wind': 678.654,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 303.134,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14635.534,\n        'gas': 19124.3,\n        'hydro': 394.37,\n        'nuclear': 24172.8,\n        'oil': 291.477,\n        'solar': 1392.76,\n        'unknown': 2972.93,\n        'wind': 679.101,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 288.461,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14600.853,\n        'gas': 19063.5,\n        'hydro': 373.054,\n        'nuclear': 24181.4,\n        'oil': 291.232,\n        'solar': 1378.99,\n        'unknown': 2982.04,\n        'wind': 693.453,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 300.964,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14698.863,\n        'gas': 19327.3,\n        'hydro': 390.183,\n        'nuclear': 24175.2,\n        'oil': 291.041,\n        'solar': 1432.5,\n        'unknown': 2960.5,\n        'wind': 710.2,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 301.818,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 12, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14714.31,\n        'gas': 19222.2,\n        'hydro': 371.566,\n        'nuclear': 24144.1,\n        'oil': 291.346,\n        'solar': 1422.53,\n        'unknown': 2944.84,\n        'wind': 704.391,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 283.424,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14686.642,\n        'gas': 19242.3,\n        'hydro': 370.812,\n        'nuclear': 24175.2,\n        'oil': 290.89,\n        'solar': 1399.71,\n        'unknown': 2958.97,\n        'wind': 723.143,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 293.589,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14757.046,\n        'gas': 19230.5,\n        'hydro': 373.023,\n        'nuclear': 24177.4,\n        'oil': 290.839,\n        'solar': 1372.99,\n        'unknown': 2980.89,\n        'wind': 701.737,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 287.116,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14759.703,\n        'gas': 19452.9,\n        'hydro': 373.245,\n        'nuclear': 24182.4,\n        'oil': 292.024,\n        'solar': 1411.2,\n        'unknown': 2990.37,\n        'wind': 660.967,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 304.446,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14691.241,\n        'gas': 19414.1,\n        'hydro': 364.769,\n        'nuclear': 24192.7,\n        'oil': 290.438,\n        'solar': 1486.77,\n        'unknown': 2943.59,\n        'wind': 654.307,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 306.963,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14622.655,\n        'gas': 19364.9,\n        'hydro': 370.814,\n        'nuclear': 24163.0,\n        'oil': 290.034,\n        'solar': 1552.29,\n        'unknown': 2908.14,\n        'wind': 662.45,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 286.191,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14624.593,\n        'gas': 19325.8,\n        'hydro': 370.649,\n        'nuclear': 24189.7,\n        'oil': 290.46,\n        'solar': 1548.21,\n        'unknown': 2902.22,\n        'wind': 663.923,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 426.89,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14628.759,\n        'gas': 19252.7,\n        'hydro': 364.851,\n        'nuclear': 24170.9,\n        'oil': 290.502,\n        'solar': 1524.91,\n        'unknown': 2889.73,\n        'wind': 659.959,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 427.049,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14613.539,\n        'gas': 19589.4,\n        'hydro': 366.027,\n        'nuclear': 24152.6,\n        'oil': 291.019,\n        'solar': 1491.44,\n        'unknown': 2883.16,\n        'wind': 656.43,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 425.892,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14763.469,\n        'gas': 19525.7,\n        'hydro': 374.16,\n        'nuclear': 24183.8,\n        'oil': 291.988,\n        'solar': 1431.42,\n        'unknown': 2886.26,\n        'wind': 663.307,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 422.141,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14586.906,\n        'gas': 19420.8,\n        'hydro': 368.122,\n        'nuclear': 24160.5,\n        'oil': 291.326,\n        'solar': 1387.12,\n        'unknown': 2916.93,\n        'wind': 672.089,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 422.061,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14559.597,\n        'gas': 19161.7,\n        'hydro': 367.153,\n        'nuclear': 24151.7,\n        'oil': 291.305,\n        'solar': 1318.13,\n        'unknown': 2959.87,\n        'wind': 655.72,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 421.982,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 13, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14684.497,\n        'gas': 19320.0,\n        'hydro': 390.73,\n        'nuclear': 24196.7,\n        'oil': 291.732,\n        'solar': 1320.97,\n        'unknown': 2988.08,\n        'wind': 635.004,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 422.54,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14727.884,\n        'gas': 19379.0,\n        'hydro': 386.912,\n        'nuclear': 24159.1,\n        'oil': 292.285,\n        'solar': 1317.72,\n        'unknown': 2989.81,\n        'wind': 602.338,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 421.303,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14640.283,\n        'gas': 19397.7,\n        'hydro': 406.766,\n        'nuclear': 24159.9,\n        'oil': 291.58,\n        'solar': 1325.67,\n        'unknown': 2988.26,\n        'wind': 608.524,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 425.334,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14594.745,\n        'gas': 19224.7,\n        'hydro': 416.258,\n        'nuclear': 24168.8,\n        'oil': 292.197,\n        'solar': 1260.42,\n        'unknown': 2996.7,\n        'wind': 586.833,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 420.864,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14667.559,\n        'gas': 19055.1,\n        'hydro': 418.705,\n        'nuclear': 24173.2,\n        'oil': 292.396,\n        'solar': 1216.71,\n        'unknown': 2990.47,\n        'wind': 571.947,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 421.224,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14675.042,\n        'gas': 18993.9,\n        'hydro': 387.632,\n        'nuclear': 24170.2,\n        'oil': 292.054,\n        'solar': 1265.56,\n        'unknown': 2970.39,\n        'wind': 582.176,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 425.134,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14707.336,\n        'gas': 19251.3,\n        'hydro': 416.438,\n        'nuclear': 24168.7,\n        'oil': 291.359,\n        'solar': 1228.62,\n        'unknown': 2973.72,\n        'wind': 588.008,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 421.782,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14761.128,\n        'gas': 19320.5,\n        'hydro': 410.303,\n        'nuclear': 24161.7,\n        'oil': 291.643,\n        'solar': 1161.41,\n        'unknown': 2967.43,\n        'wind': 578.838,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 420.705,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14592.19,\n        'gas': 19157.1,\n        'hydro': 410.04,\n        'nuclear': 24205.8,\n        'oil': 290.39,\n        'solar': 1135.47,\n        'unknown': 2964.75,\n        'wind': 581.741,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 425.453,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14628.428,\n        'gas': 18947.9,\n        'hydro': 410.453,\n        'nuclear': 24173.7,\n        'oil': 291.542,\n        'solar': 1084.0,\n        'unknown': 2991.5,\n        'wind': 595.697,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 424.376,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14794.518,\n        'gas': 18962.9,\n        'hydro': 417.95,\n        'nuclear': 24166.4,\n        'oil': 295.164,\n        'solar': 1079.87,\n        'unknown': 3002.46,\n        'wind': 580.94,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 419.149,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14869.41,\n        'gas': 19227.0,\n        'hydro': 412.898,\n        'nuclear': 24178.2,\n        'oil': 296.807,\n        'solar': 1073.03,\n        'unknown': 3009.28,\n        'wind': 573.872,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 421.623,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 14, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14690.103,\n        'gas': 19307.7,\n        'hydro': 415.406,\n        'nuclear': 24182.2,\n        'oil': 295.367,\n        'solar': 1071.62,\n        'unknown': 2998.86,\n        'wind': 574.368,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 422.381,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14767.304,\n        'gas': 19194.9,\n        'hydro': 415.165,\n        'nuclear': 24183.3,\n        'oil': 299.202,\n        'solar': 1075.16,\n        'unknown': 2993.25,\n        'wind': 572.552,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 420.106,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14642.42,\n        'gas': 19292.9,\n        'hydro': 407.403,\n        'nuclear': 24168.1,\n        'oil': 305.483,\n        'solar': 1058.1,\n        'unknown': 2996.6,\n        'wind': 537.308,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 421.423,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14749.979,\n        'gas': 19480.2,\n        'hydro': 413.989,\n        'nuclear': 24182.1,\n        'oil': 307.478,\n        'solar': 1024.82,\n        'unknown': 3039.79,\n        'wind': 517.297,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 422.181,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14736.397,\n        'gas': 19486.8,\n        'hydro': 409.787,\n        'nuclear': 24180.5,\n        'oil': 309.334,\n        'solar': 974.464,\n        'unknown': 3077.17,\n        'wind': 495.789,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 423.977,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14632.976,\n        'gas': 19548.3,\n        'hydro': 400.153,\n        'nuclear': 24187.2,\n        'oil': 311.01,\n        'solar': 939.301,\n        'unknown': 3118.35,\n        'wind': 508.195,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 421.343,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14748.697,\n        'gas': 19702.4,\n        'hydro': 404.87,\n        'nuclear': 24177.1,\n        'oil': 321.131,\n        'solar': 911.634,\n        'unknown': 3127.4,\n        'wind': 493.631,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 420.226,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14782.228,\n        'gas': 19810.9,\n        'hydro': 373.912,\n        'nuclear': 24167.1,\n        'oil': 331.693,\n        'solar': 895.852,\n        'unknown': 3129.39,\n        'wind': 491.481,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 421.263,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14714.922,\n        'gas': 19923.7,\n        'hydro': 363.016,\n        'nuclear': 24171.6,\n        'oil': 340.562,\n        'solar': 839.816,\n        'unknown': 3122.47,\n        'wind': 478.708,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 420.745,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14669.442,\n        'gas': 20015.7,\n        'hydro': 367.472,\n        'nuclear': 24182.7,\n        'oil': 341.375,\n        'solar': 804.817,\n        'unknown': 3128.93,\n        'wind': 452.412,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 421.543,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14727.603,\n        'gas': 20131.5,\n        'hydro': 371.867,\n        'nuclear': 24188.1,\n        'oil': 350.067,\n        'solar': 757.541,\n        'unknown': 3133.21,\n        'wind': 465.97,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 420.226,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14735.903,\n        'gas': 20302.2,\n        'hydro': 345.188,\n        'nuclear': 24189.1,\n        'oil': 356.305,\n        'solar': 722.779,\n        'unknown': 3138.56,\n        'wind': 451.627,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 419.867,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 15, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14783.994,\n        'gas': 20642.5,\n        'hydro': 286.442,\n        'nuclear': 24173.0,\n        'oil': 363.268,\n        'solar': 702.94,\n        'unknown': 3139.82,\n        'wind': 450.143,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 420.346,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14872.376,\n        'gas': 20491.9,\n        'hydro': 313.574,\n        'nuclear': 24179.8,\n        'oil': 364.509,\n        'solar': 657.667,\n        'unknown': 3135.82,\n        'wind': 432.687,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 418.311,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 16, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14753.859,\n        'gas': 20184.7,\n        'hydro': 361.895,\n        'nuclear': 24184.5,\n        'oil': 363.139,\n        'solar': 664.524,\n        'unknown': 3183.22,\n        'wind': 430.974,\n      }),\n      'source': 'new.kpx.or.kr',\n    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'hydro': 372.413,\n        'nuclear': 24162.7,\n        'oil': 362.646,\n        'solar': 543.873,\n        'unknown': 3455.13,\n        'wind': 411.999,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 16, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14792.244,\n        'gas': 20253.8,\n        'hydro': 340.453,\n        'nuclear': 24162.8,\n        'oil': 363.335,\n        'solar': 485.55,\n        'unknown': 3638.6,\n        'wind': 397.056,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 16, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14819.097,\n        'gas': 20360.4,\n        'hydro': 363.175,\n        'nuclear': 24188.5,\n        'oil': 363.225,\n        'solar': 460.607,\n        'unknown': 3706.9,\n        'wind': 386.257,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14828.744,\n        'gas': 20398.5,\n        'hydro': 375.912,\n        'nuclear': 24151.5,\n        'oil': 363.111,\n        'solar': 410.101,\n        'unknown': 3725.18,\n        'wind': 392.203,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 16, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14702.896,\n        'gas': 20502.0,\n        'hydro': 371.888,\n        'nuclear': 24155.9,\n        'oil': 362.973,\n        'solar': 386.596,\n        'unknown': 3699.56,\n        'wind': 375.616,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 16, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14890.631,\n        'gas': 20946.6,\n        'hydro': 370.717,\n        'nuclear': 24176.8,\n        'oil': 363.216,\n        'solar': 344.756,\n        'unknown': 3698.05,\n        'wind': 369.501,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14919.984,\n        'gas': 21313.6,\n        'hydro': 370.003,\n        'nuclear': 24170.2,\n        'oil': 363.674,\n        'solar': 307.627,\n        'unknown': 3684.45,\n        'wind': 373.273,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n   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323.62,\n        'nuclear': 24176.4,\n        'oil': 363.478,\n        'solar': 181.266,\n        'unknown': 3554.01,\n        'wind': 373.549,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -164.011,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14910.99,\n        'gas': 22304.7,\n        'hydro': 328.215,\n        'nuclear': 24145.2,\n        'oil': 364.74,\n        'solar': 144.13,\n        'unknown': 3525.21,\n        'wind': 356.858,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -393.721,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14990.222,\n        'gas': 22564.0,\n        'hydro': 317.711,\n        'nuclear': 24164.5,\n        'oil': 363.766,\n        'solar': 97.0092,\n        'unknown': 3507.49,\n        'wind': 345.267,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -519.969,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15010.059,\n        'gas': 22382.2,\n        'hydro': 311.478,\n        'nuclear': 24156.7,\n        'oil': 363.315,\n        'solar': 67.4273,\n        'unknown': 3502.25,\n        'wind': 342.304,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -522.492,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14972.617,\n        'gas': 22764.9,\n        'hydro': 325.164,\n        'nuclear': 24164.3,\n        'oil': 363.591,\n        'solar': 0.0,\n        'unknown': 3490.41,\n        'wind': 343.144,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -529.515,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14961.186,\n        'gas': 23010.9,\n        'hydro': 325.283,\n        'nuclear': 24144.2,\n        'oil': 363.596,\n        'solar': 0.0,\n        'unknown': 3466.91,\n        'wind': 365.388,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -535.731,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15051.158,\n        'gas': 22779.4,\n        'hydro': 318.778,\n        'nuclear': 24134.7,\n        'oil': 363.831,\n        'solar': 17.1478,\n        'unknown': 3420.95,\n        'wind': 367.731,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -937.306,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15029.825,\n        'gas': 23009.8,\n        'hydro': 327.892,\n        'nuclear': 24169.9,\n        'oil': 362.026,\n        'solar': 9.69618,\n        'unknown': 3459.22,\n        'wind': 375.927,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -939.786,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15014.545,\n        'gas': 22861.9,\n        'hydro': 325.953,\n        'nuclear': 24131.2,\n        'oil': 361.349,\n        'solar': 15.624,\n        'unknown': 3447.06,\n        'wind': 373.002,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1375.72,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15080.638,\n        'gas': 23042.6,\n        'hydro': 286.321,\n        'nuclear': 24206.0,\n        'oil': 363.082,\n        'solar': 17.5567,\n        'unknown': 3437.6,\n        'wind': 367.37,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1389.46,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 17, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15164.055,\n        'gas': 23097.6,\n        'hydro': 280.46,\n        'nuclear': 24183.2,\n        'oil': 363.214,\n        'solar': 20.6998,\n        'unknown': 3418.34,\n        'wind': 369.952,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1388.93,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15121.835,\n        'gas': 23232.0,\n        'hydro': 286.773,\n        'nuclear': 24168.9,\n        'oil': 363.602,\n        'solar': 21.0216,\n        'unknown': 3411.66,\n        'wind': 369.12,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1391.25,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15045.283,\n        'gas': 23109.4,\n        'hydro': 285.458,\n        'nuclear': 24174.1,\n        'oil': 363.612,\n        'solar': 22.8437,\n        'unknown': 3404.82,\n        'wind': 396.499,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1374.12,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15055.88,\n        'gas': 23083.1,\n        'hydro': 282.353,\n        'nuclear': 24159.1,\n        'oil': 363.175,\n        'solar': 22.5842,\n        'unknown': 3393.38,\n        'wind': 406.653,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1380.13,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15153.629,\n        'gas': 22969.8,\n        'hydro': 279.168,\n        'nuclear': 24169.1,\n        'oil': 363.358,\n        'solar': 19.4275,\n        'unknown': 3417.66,\n        'wind': 408.84,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1392.15,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15069.707,\n        'gas': 23131.0,\n        'hydro': 276.753,\n        'nuclear': 24134.7,\n        'oil': 363.124,\n        'solar': 19.6174,\n        'unknown': 3432.0,\n        'wind': 403.449,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1381.98,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15100.022,\n        'gas': 23168.2,\n        'hydro': 277.955,\n        'nuclear': 24190.5,\n        'oil': 363.772,\n        'solar': 14.7366,\n        'unknown': 3440.75,\n        'wind': 396.95,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1377.06,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15104.184,\n        'gas': 22967.7,\n        'hydro': 286.357,\n        'nuclear': 24153.2,\n        'oil': 363.759,\n        'solar': 13.5954,\n        'unknown': 3435.89,\n        'wind': 395.697,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1403.42,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15002.427,\n        'gas': 22967.6,\n        'hydro': 281.604,\n        'nuclear': 24177.1,\n        'oil': 362.826,\n        'solar': 21.2186,\n        'unknown': 3421.25,\n        'wind': 393.809,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1382.6,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15023.528,\n        'gas': 22839.2,\n        'hydro': 278.87,\n        'nuclear': 24194.8,\n        'oil': 362.895,\n        'solar': 22.147,\n        'unknown': 3415.3,\n        'wind': 392.791,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1367.49,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n   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'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 18, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15066.324,\n        'gas': 22673.4,\n        'hydro': 206.65,\n        'nuclear': 24214.4,\n        'oil': 362.999,\n        'solar': 20.6323,\n        'unknown': 3422.35,\n        'wind': 369.955,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1376.13,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15093.794,\n        'gas': 22621.1,\n        'hydro': 210.968,\n        'nuclear': 24176.1,\n        'oil': 361.086,\n        'solar': 0.0,\n        'unknown': 3415.4,\n        'wind': 380.291,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1381.12,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15170.136,\n        'gas': 22655.0,\n        'hydro': 213.499,\n        'nuclear': 24156.6,\n        'oil': 361.936,\n        'solar': 0.0,\n        'unknown': 3410.18,\n        'wind': 370.562,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1546.88,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15063.736,\n        'gas': 22522.1,\n        'hydro': 210.319,\n        'nuclear': 24157.6,\n        'oil': 361.932,\n        'solar': 0.0,\n        'unknown': 3420.9,\n        'wind': 382.182,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1521.46,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15099.336,\n        'gas': 22457.5,\n        'hydro': 214.224,\n        'nuclear': 24155.2,\n        'oil': 363.469,\n        'solar': 0.0,\n        'unknown': 3427.53,\n        'wind': 380.406,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1305.48,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15130.901,\n        'gas': 22468.3,\n        'hydro': 209.695,\n        'nuclear': 24165.7,\n        'oil': 361.968,\n        'solar': 0.0,\n        'unknown': 3434.15,\n        'wind': 385.446,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1259.4,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15071.193,\n        'gas': 22441.9,\n        'hydro': 205.009,\n        'nuclear': 24171.0,\n        'oil': 362.25,\n        'solar': 0.0,\n        'unknown': 3422.09,\n        'wind': 368.16,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1259.35,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15033.062,\n        'gas': 22404.5,\n        'hydro': 214.713,\n        'nuclear': 24158.8,\n        'oil': 362.493,\n        'solar': 0.0,\n        'unknown': 3423.72,\n        'wind': 379.804,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1302.98,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15019.153,\n        'gas': 22215.5,\n        'hydro': 202.077,\n        'nuclear': 24201.5,\n        'oil': 362.516,\n        'solar': 0.0,\n        'unknown': 3424.47,\n        'wind': 359.892,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1228.57,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15060.501,\n        'gas': 22052.3,\n        'hydro': 206.471,\n        'nuclear': 24169.7,\n        'oil': 363.071,\n        'solar': 0.0,\n        'unknown': 3414.14,\n        'wind': 395.03,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1238.19,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15123.617,\n        'gas': 22184.1,\n        'hydro': 211.018,\n        'nuclear': 24164.7,\n        'oil': 362.617,\n        'solar': 0.0,\n        'unknown': 3422.09,\n        'wind': 409.377,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1091.98,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15153.125,\n        'gas': 21947.2,\n        'hydro': 208.609,\n        'nuclear': 24156.4,\n        'oil': 363.247,\n        'solar': 0.0,\n        'unknown': 3420.34,\n        'wind': 400.987,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1038.85,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 19, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15099.527,\n        'gas': 21826.3,\n        'hydro': 210.411,\n        'nuclear': 24168.8,\n        'oil': 361.608,\n        'solar': 0.0,\n        'unknown': 3417.81,\n        'wind': 407.896,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1073.01,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15206.593,\n        'gas': 21716.4,\n        'hydro': 207.967,\n        'nuclear': 24155.9,\n        'oil': 363.228,\n        'solar': 0.0,\n        'unknown': 3409.03,\n        'wind': 388.231,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1064.16,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15089.451,\n        'gas': 21674.5,\n        'hydro': 241.604,\n        'nuclear': 24168.2,\n        'oil': 361.629,\n        'solar': 0.0,\n        'unknown': 3408.22,\n        'wind': 369.257,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1028.27,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15076.389,\n        'gas': 21682.8,\n        'hydro': 251.277,\n        'nuclear': 24170.6,\n        'oil': 362.662,\n        'solar': 0.0,\n        'unknown': 3414.25,\n        'wind': 387.884,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1069.51,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15063.435,\n        'gas': 21440.2,\n        'hydro': 245.796,\n        'nuclear': 24169.6,\n        'oil': 362.548,\n        'solar': 0.0,\n        'unknown': 3414.45,\n        'wind': 385.674,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1034.91,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15115.576,\n        'gas': 21531.9,\n        'hydro': 257.086,\n        'nuclear': 24185.6,\n        'oil': 363.946,\n        'solar': 0.0,\n        'unknown': 3411.05,\n        'wind': 389.992,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1088.81,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15043.306,\n        'gas': 21449.1,\n        'hydro': 250.5,\n        'nuclear': 24180.9,\n        'oil': 363.032,\n        'solar': 0.0,\n        'unknown': 3410.78,\n        'wind': 373.388,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1068.14,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15058.227,\n        'gas': 21343.7,\n        'hydro': 244.602,\n        'nuclear': 24173.4,\n        'oil': 363.96,\n        'solar': 0.0,\n        'unknown': 3397.36,\n        'wind': 370.487,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1040.67,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15031.315,\n        'gas': 21098.8,\n        'hydro': 247.437,\n        'nuclear': 24166.1,\n        'oil': 363.862,\n        'solar': 0.0,\n        'unknown': 3396.42,\n        'wind': 372.568,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1039.21,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15085.245,\n        'gas': 20972.2,\n        'hydro': 257.63,\n        'nuclear': 24191.7,\n        'oil': 365.201,\n        'solar': 0.0,\n        'unknown': 3395.05,\n        'wind': 366.65,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1102.78,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15192.942,\n        'gas': 21056.6,\n        'hydro': 250.522,\n        'nuclear': 24168.6,\n        'oil': 364.206,\n        'solar': 0.0,\n        'unknown': 3398.73,\n        'wind': 361.899,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1061.43,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15103.93,\n        'gas': 21002.2,\n        'hydro': 252.81,\n        'nuclear': 24184.1,\n        'oil': 365.684,\n        'solar': 0.0,\n        'unknown': 3392.83,\n        'wind': 354.807,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1089.88,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15069.19,\n        'gas': 20741.9,\n        'hydro': 252.049,\n        'nuclear': 24159.7,\n        'oil': 365.518,\n        'solar': 0.0,\n        'unknown': 3391.43,\n        'wind': 355.322,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1078.22,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15161.289,\n        'gas': 20534.4,\n        'hydro': 253.244,\n        'nuclear': 24144.6,\n        'oil': 366.059,\n        'solar': 0.0,\n        'unknown': 3388.49,\n        'wind': 368.897,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1054.75,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15038.37,\n        'gas': 20194.8,\n        'hydro': 251.977,\n        'nuclear': 24171.8,\n        'oil': 365.067,\n        'solar': 0.0,\n        'unknown': 3382.07,\n        'wind': 367.411,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1082.64,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15160.428,\n        'gas': 20151.8,\n        'hydro': 260.611,\n        'nuclear': 24187.8,\n        'oil': 365.897,\n        'solar': 0.0,\n        'unknown': 3380.32,\n        'wind': 381.618,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1094.59,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15044.104,\n        'gas': 20059.6,\n        'hydro': 240.238,\n        'nuclear': 24177.4,\n        'oil': 364.606,\n        'solar': 0.0,\n        'unknown': 3373.35,\n        'wind': 377.355,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1014.7,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15020.079,\n        'gas': 19797.8,\n        'hydro': 250.463,\n        'nuclear': 24175.9,\n        'oil': 364.706,\n        'solar': 0.0,\n        'unknown': 3372.35,\n        'wind': 367.716,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1073.26,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 14969.672,\n        'gas': 19778.4,\n        'hydro': 240.401,\n        'nuclear': 24183.3,\n        'oil': 365.0,\n        'solar': 0.0,\n        'unknown': 3367.88,\n        'wind': 358.94,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -994.249,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15078.911,\n        'gas': 19913.5,\n        'hydro': 251.38,\n        'nuclear': 24157.8,\n        'oil': 363.631,\n        'solar': 0.0,\n        'unknown': 3347.86,\n        'wind': 367.0,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1105.48,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15063.844,\n        'gas': 19654.5,\n        'hydro': 245.107,\n        'nuclear': 24203.5,\n        'oil': 364.105,\n        'solar': 0.0,\n        'unknown': 3349.35,\n        'wind': 374.939,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1031.37,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15064.077,\n        'gas': 19575.4,\n        'hydro': 250.389,\n        'nuclear': 24155.4,\n        'oil': 363.265,\n        'solar': 0.0,\n        'unknown': 3343.2,\n        'wind': 367.346,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1079.17,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15096.811,\n        'gas': 19798.2,\n        'hydro': 242.278,\n        'nuclear': 24194.1,\n        'oil': 364.416,\n        'solar': 0.0,\n        'unknown': 3343.79,\n        'wind': 378.451,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -852.022,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15021.958,\n        'gas': 19370.0,\n        'hydro': 233.194,\n        'nuclear': 24188.9,\n        'oil': 363.456,\n        'solar': 0.0,\n        'unknown': 3336.49,\n        'wind': 381.915,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -798.873,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15107.118,\n        'gas': 19446.2,\n        'hydro': 240.337,\n        'nuclear': 24156.2,\n        'oil': 364.077,\n        'solar': 0.0,\n        'unknown': 3334.89,\n        'wind': 379.939,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -863.181,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15137.151,\n        'gas': 19615.1,\n        'hydro': 248.136,\n        'nuclear': 24165.7,\n        'oil': 364.928,\n        'solar': 0.0,\n        'unknown': 3327.99,\n        'wind': 392.434,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -875.241,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15101.597,\n        'gas': 19895.9,\n        'hydro': 241.583,\n        'nuclear': 24169.9,\n        'oil': 364.482,\n        'solar': 0.0,\n        'unknown': 3319.88,\n        'wind': 400.036,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -854.384,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15098.284,\n        'gas': 19938.2,\n        'hydro': 237.936,\n        'nuclear': 24150.7,\n        'oil': 364.008,\n        'solar': 0.0,\n        'unknown': 3312.43,\n        'wind': 404.564,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -836.469,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15208.759,\n        'gas': 19971.8,\n        'hydro': 248.014,\n        'nuclear': 24146.8,\n        'oil': 364.559,\n        'solar': 0.0,\n        'unknown': 3305.77,\n        'wind': 379.915,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -814.817,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15187.914,\n        'gas': 20129.5,\n        'hydro': 199.699,\n        'nuclear': 24188.4,\n        'oil': 363.853,\n        'solar': 0.0,\n        'unknown': 3297.85,\n        'wind': 385.55,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -729.596,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15170.538,\n        'gas': 19947.9,\n        'hydro': 197.662,\n        'nuclear': 24169.6,\n        'oil': 363.962,\n        'solar': 0.0,\n        'unknown': 3305.82,\n        'wind': 398.197,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -728.466,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15153.494,\n        'gas': 19858.7,\n        'hydro': 200.638,\n        'nuclear': 24133.6,\n        'oil': 364.404,\n        'solar': 0.0,\n        'unknown': 3300.46,\n        'wind': 408.872,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -735.859,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15110.663,\n        'gas': 19949.8,\n        'hydro': 115.798,\n        'nuclear': 24151.1,\n        'oil': 363.392,\n        'solar': 0.0,\n        'unknown': 3292.85,\n        'wind': 407.016,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -737.419,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15083.22,\n        'gas': 19575.5,\n        'hydro': 39.2879,\n        'nuclear': 24173.6,\n        'oil': 364.19,\n        'solar': 0.0,\n        'unknown': 3289.28,\n        'wind': 407.101,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -720.656,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15089.41,\n        'gas': 19604.8,\n        'hydro': 39.4359,\n        'nuclear': 24154.7,\n        'oil': 362.624,\n        'solar': 0.0,\n        'unknown': 3281.83,\n        'wind': 390.382,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -739.031,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15089.653,\n        'gas': 19548.0,\n        'hydro': 39.4482,\n        'nuclear': 24147.0,\n        'oil': 362.858,\n        'solar': 0.0,\n        'unknown': 3278.0,\n        'wind': 382.7,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -734.685,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15063.484,\n        'gas': 19408.0,\n        'hydro': 39.4033,\n        'nuclear': 24170.8,\n        'oil': 363.248,\n        'solar': 0.0,\n        'unknown': 3268.34,\n        'wind': 375.826,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -729.511,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15256.879,\n        'gas': 19565.2,\n        'hydro': 39.5655,\n        'nuclear': 24187.0,\n        'oil': 364.105,\n        'solar': 0.0,\n        'unknown': 3256.59,\n        'wind': 382.195,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -768.727,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15338.959,\n        'gas': 20393.7,\n        'hydro': 39.4069,\n        'nuclear': 24168.4,\n        'oil': 364.249,\n        'solar': 0.0,\n        'unknown': 3188.17,\n        'wind': 371.972,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -749.907,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 1, 5, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 15280.791,\n        'gas': 20716.8,\n        'hydro': 39.4469,\n        'nuclear': 24174.8,\n        'oil': 364.165,\n        'solar': 0.0,\n        'unknown': 3191.41,\n        'wind': 390.882,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -742.367,\n      }),\n      'zoneKey': 'KR',\n    }),\n  ])\n# ---\n# name: test_production_historical\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22908.953,\n        'gas': 13844.6,\n        'hydro': 903.194,\n        'nuclear': 21038.2,\n        'oil': 233.421,\n        'solar': 0.0,\n        'unknown': 3591.31,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -516.098,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22938.433,\n        'gas': 13555.1,\n        'hydro': 896.427,\n        'nuclear': 21011.6,\n        'oil': 232.243,\n        'solar': 0.0,\n        'unknown': 3585.74,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -589.946,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23041.143,\n        'gas': 13276.3,\n        'hydro': 916.608,\n        'nuclear': 21025.6,\n        'oil': 232.751,\n        'solar': 0.0,\n        'unknown': 3580.93,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -340.346,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23081.68,\n        'gas': 13092.5,\n        'hydro': 913.775,\n        'nuclear': 21037.4,\n        'oil': 233.916,\n        'solar': 0.0,\n        'unknown': 3578.75,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -339.555,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22909.484,\n        'gas': 12739.8,\n        'hydro': 916.159,\n        'nuclear': 21036.2,\n        'oil': 233.141,\n        'solar': 0.0,\n        'unknown': 3585.31,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -316.703,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22966.015,\n        'gas': 12579.7,\n        'hydro': 916.721,\n        'nuclear': 21020.4,\n        'oil': 233.234,\n        'solar': 0.0,\n        'unknown': 3589.98,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -329.967,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22810.238,\n        'gas': 12370.4,\n        'hydro': 916.446,\n        'nuclear': 21037.5,\n        'oil': 232.829,\n        'solar': 0.0,\n        'unknown': 3587.11,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -305.277,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22660.447,\n        'gas': 12195.8,\n        'hydro': 915.268,\n        'nuclear': 21039.3,\n        'oil': 232.736,\n        'solar': 0.0,\n        'unknown': 3597.75,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -303.092,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22802.104,\n        'gas': 12057.4,\n        'hydro': 917.746,\n        'nuclear': 21029.8,\n        'oil': 232.921,\n        'solar': 0.0,\n        'unknown': 3600.07,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -335.48,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22701.316,\n        'gas': 11852.1,\n        'hydro': 914.957,\n        'nuclear': 21031.1,\n        'oil': 232.963,\n        'solar': 0.0,\n        'unknown': 3601.07,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -312.628,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22672.138,\n        'gas': 11671.5,\n        'hydro': 915.434,\n        'nuclear': 21039.4,\n        'oil': 233.214,\n        'solar': 0.0,\n        'unknown': 3602.41,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -313.871,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22629.656,\n        'gas': 11507.0,\n        'hydro': 915.273,\n        'nuclear': 21037.6,\n        'oil': 233.604,\n        'solar': 0.0,\n        'unknown': 3600.5,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -199.764,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22680.822,\n        'gas': 11554.4,\n        'hydro': 917.218,\n        'nuclear': 21029.6,\n        'oil': 232.666,\n        'solar': 0.0,\n        'unknown': 3584.35,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.40728,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22596.407,\n        'gas': 11538.1,\n        'hydro': 915.729,\n        'nuclear': 21030.7,\n        'oil': 233.454,\n        'solar': 0.0,\n        'unknown': 3583.21,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.30742,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22662.533,\n        'gas': 11496.0,\n        'hydro': 918.72,\n        'nuclear': 21035.8,\n        'oil': 232.218,\n        'solar': 0.0,\n        'unknown': 3573.55,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.40728,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22513.185,\n        'gas': 11290.9,\n        'hydro': 916.142,\n        'nuclear': 21032.2,\n        'oil': 232.794,\n        'solar': 0.0,\n        'unknown': 3578.28,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.40728,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22523.333,\n        'gas': 11000.5,\n        'hydro': 918.401,\n        'nuclear': 21022.5,\n        'oil': 232.961,\n        'solar': 0.0,\n        'unknown': 3565.86,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.40728,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22584.408,\n        'gas': 11000.1,\n        'hydro': 923.6,\n        'nuclear': 21024.3,\n        'oil': 233.034,\n        'solar': 0.0,\n        'unknown': 3558.27,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.50762,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22556.164,\n        'gas': 10939.0,\n        'hydro': 921.644,\n        'nuclear': 21017.8,\n        'oil': 233.258,\n        'solar': 0.0,\n        'unknown': 3559.68,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.30742,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22591.473,\n        'gas': 10969.8,\n        'hydro': 921.963,\n        'nuclear': 21013.4,\n        'oil': 233.464,\n        'solar': 0.0,\n        'unknown': 3552.51,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.30742,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22531.011,\n        'gas': 10821.3,\n        'hydro': 917.243,\n        'nuclear': 21024.7,\n        'oil': 233.445,\n        'solar': 0.0,\n        'unknown': 3549.66,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.999805,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22612.05,\n        'gas': 10769.7,\n        'hydro': 925.234,\n        'nuclear': 21020.0,\n        'oil': 232.55,\n        'solar': 0.0,\n        'unknown': 3543.52,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.09966,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22437.457,\n        'gas': 10520.8,\n        'hydro': 917.516,\n        'nuclear': 21024.1,\n        'oil': 233.215,\n        'solar': 0.0,\n        'unknown': 3541.2,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.899951,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22580.309,\n        'gas': 10555.8,\n        'hydro': 929.261,\n        'nuclear': 21024.3,\n        'oil': 232.677,\n        'solar': 0.0,\n        'unknown': 3547.21,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 342.369,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22748.751,\n        'gas': 10613.8,\n        'hydro': 922.483,\n        'nuclear': 21028.0,\n        'oil': 232.472,\n        'solar': 0.0,\n        'unknown': 3623.64,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 631.47,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22790.83,\n        'gas': 10728.1,\n        'hydro': 918.194,\n        'nuclear': 21027.0,\n        'oil': 233.074,\n        'solar': 0.0,\n        'unknown': 3635.64,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 641.114,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22835.378,\n        'gas': 10230.1,\n        'hydro': 918.713,\n        'nuclear': 21019.2,\n        'oil': 232.943,\n        'solar': 0.0,\n        'unknown': 3643.75,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 639.205,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22973.235,\n        'gas': 9954.98,\n        'hydro': 920.206,\n        'nuclear': 21011.1,\n        'oil': 233.13,\n        'solar': 0.0,\n        'unknown': 3644.67,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 637.734,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22868.857,\n        'gas': 10116.1,\n        'hydro': 916.905,\n        'nuclear': 21022.5,\n        'oil': 233.043,\n        'solar': 0.0,\n        'unknown': 3658.83,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 659.42,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22761.722,\n        'gas': 10383.8,\n        'hydro': 920.219,\n        'nuclear': 21006.0,\n        'oil': 232.87,\n        'solar': 0.0,\n        'unknown': 3667.92,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 845.45,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22846.713,\n        'gas': 10453.0,\n        'hydro': 925.53,\n        'nuclear': 21009.2,\n        'oil': 233.608,\n        'solar': 0.0,\n        'unknown': 3665.5,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1165.58,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22862.853,\n        'gas': 10366.4,\n        'hydro': 918.127,\n        'nuclear': 21013.3,\n        'oil': 233.967,\n        'solar': 0.0,\n        'unknown': 3669.83,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1185.96,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23086.51,\n        'gas': 10386.3,\n        'hydro': 928.378,\n        'nuclear': 21000.6,\n        'oil': 234.501,\n        'solar': 0.0,\n        'unknown': 3679.21,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1523.29,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23060.001,\n        'gas': 10409.3,\n        'hydro': 922.15,\n        'nuclear': 20993.0,\n        'oil': 233.943,\n        'solar': 0.0,\n        'unknown': 3688.4,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1548.74,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22996.375,\n        'gas': 10255.8,\n        'hydro': 916.227,\n        'nuclear': 21010.4,\n        'oil': 233.809,\n        'solar': 0.0,\n        'unknown': 3693.8,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1550.86,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 2, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22752.437,\n        'gas': 10013.8,\n        'hydro': 905.551,\n        'nuclear': 20991.4,\n        'oil': 233.371,\n        'solar': 0.0,\n        'unknown': 3703.1,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1227.1,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22703.064,\n        'gas': 9986.0,\n        'hydro': 920.526,\n        'nuclear': 20983.0,\n        'oil': 232.101,\n        'solar': 0.0,\n        'unknown': 3715.19,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1221.35,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22644.175,\n        'gas': 9871.57,\n        'hydro': 914.427,\n        'nuclear': 20974.4,\n        'oil': 233.94,\n        'solar': 0.0,\n        'unknown': 3718.35,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1223.54,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22598.767,\n        'gas': 9940.93,\n        'hydro': 919.945,\n        'nuclear': 20959.5,\n        'oil': 232.953,\n        'solar': 0.0,\n        'unknown': 3728.66,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1225.07,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22565.326,\n        'gas': 10045.3,\n        'hydro': 919.4,\n        'nuclear': 20986.7,\n        'oil': 233.711,\n        'solar': 0.0,\n        'unknown': 3737.59,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1223.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22483.343,\n        'gas': 9987.6,\n        'hydro': 912.955,\n        'nuclear': 20981.8,\n        'oil': 233.46,\n        'solar': 0.0,\n        'unknown': 3750.42,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1226.11,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22579.889,\n        'gas': 10102.7,\n        'hydro': 919.885,\n        'nuclear': 20965.3,\n        'oil': 233.364,\n        'solar': 0.0,\n        'unknown': 3763.87,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1556.91,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22600.16,\n        'gas': 10148.5,\n        'hydro': 915.215,\n        'nuclear': 20962.8,\n        'oil': 233.653,\n        'solar': 0.0,\n        'unknown': 3777.19,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1576.82,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22894.034,\n        'gas': 10120.0,\n        'hydro': 921.237,\n        'nuclear': 20969.8,\n        'oil': 233.114,\n        'solar': 0.0,\n        'unknown': 3779.67,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1583.7,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22960.917,\n        'gas': 10091.0,\n        'hydro': 914.431,\n        'nuclear': 20966.6,\n        'oil': 233.036,\n        'solar': 0.0,\n        'unknown': 3797.79,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1973.77,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22939.481,\n        'gas': 10287.4,\n        'hydro': 918.869,\n        'nuclear': 20960.3,\n        'oil': 233.838,\n        'solar': 0.0,\n        'unknown': 3798.08,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1974.83,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22945.114,\n        'gas': 10188.4,\n        'hydro': 916.919,\n        'nuclear': 20947.6,\n        'oil': 233.387,\n        'solar': 0.0,\n        'unknown': 3807.87,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1973.13,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 3, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22858.257,\n        'gas': 10053.7,\n        'hydro': 914.063,\n        'nuclear': 20985.6,\n        'oil': 232.425,\n        'solar': 0.0,\n        'unknown': 3804.7,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1973.54,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22813.236,\n        'gas': 10154.9,\n        'hydro': 915.895,\n        'nuclear': 20981.2,\n        'oil': 233.123,\n        'solar': 13.2724,\n        'unknown': 3809.74,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1977.58,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22693.475,\n        'gas': 10201.8,\n        'hydro': 916.49,\n        'nuclear': 20955.6,\n        'oil': 232.885,\n        'solar': 14.3104,\n        'unknown': 3806.17,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1974.98,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22890.955,\n        'gas': 10053.5,\n        'hydro': 912.207,\n        'nuclear': 20961.6,\n        'oil': 233.855,\n        'solar': 14.3104,\n        'unknown': 3808.91,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1967.6,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22952.471,\n        'gas': 10111.0,\n        'hydro': 913.066,\n        'nuclear': 20962.4,\n        'oil': 233.099,\n        'solar': 13.9313,\n        'unknown': 3813.08,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1964.76,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22704.578,\n        'gas': 9998.75,\n        'hydro': 910.253,\n        'nuclear': 20966.0,\n        'oil': 233.72,\n        'solar': 13.1479,\n        'unknown': 3818.03,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1966.67,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22751.1,\n        'gas': 10068.3,\n        'hydro': 913.646,\n        'nuclear': 20960.3,\n        'oil': 233.557,\n        'solar': 14.2535,\n        'unknown': 3822.17,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1965.06,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23002.691,\n        'gas': 10200.6,\n        'hydro': 916.09,\n        'nuclear': 20957.3,\n        'oil': 234.468,\n        'solar': 13.877,\n        'unknown': 3821.88,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1968.35,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22982.019,\n        'gas': 10318.3,\n        'hydro': 913.666,\n        'nuclear': 20962.2,\n        'oil': 233.952,\n        'solar': 13.7207,\n        'unknown': 3820.72,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1963.73,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22792.641,\n        'gas': 10203.0,\n        'hydro': 908.195,\n        'nuclear': 20965.5,\n        'oil': 234.134,\n        'solar': 14.1723,\n        'unknown': 3816.82,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1968.08,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22781.908,\n        'gas': 10172.8,\n        'hydro': 908.601,\n        'nuclear': 20972.8,\n        'oil': 233.51,\n        'solar': 13.9179,\n        'unknown': 3817.51,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1967.17,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22931.14,\n        'gas': 10362.2,\n        'hydro': 911.604,\n        'nuclear': 20981.3,\n        'oil': 234.021,\n        'solar': 13.2749,\n        'unknown': 3819.66,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1961.68,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 4, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22854.252,\n        'gas': 10387.5,\n        'hydro': 910.003,\n        'nuclear': 20989.6,\n        'oil': 233.764,\n        'solar': 14.8167,\n        'unknown': 3816.58,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1965.51,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22941.884,\n        'gas': 10259.4,\n        'hydro': 915.017,\n        'nuclear': 20961.4,\n        'oil': 233.913,\n        'solar': 14.3421,\n        'unknown': 3819.89,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1958.83,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22993.939,\n        'gas': 10446.5,\n        'hydro': 913.565,\n        'nuclear': 20969.3,\n        'oil': 234.046,\n        'solar': 21.5336,\n        'unknown': 3824.07,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1962.18,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23057.661,\n        'gas': 10618.2,\n        'hydro': 904.875,\n        'nuclear': 20981.5,\n        'oil': 233.882,\n        'solar': 20.6069,\n        'unknown': 3826.77,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1963.77,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22762.978,\n        'gas': 10340.2,\n        'hydro': 899.208,\n        'nuclear': 21011.9,\n        'oil': 234.061,\n        'solar': 20.8437,\n        'unknown': 3813.24,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1548.86,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23009.264,\n        'gas': 10470.5,\n        'hydro': 905.958,\n        'nuclear': 20990.1,\n        'oil': 233.101,\n        'solar': 20.6732,\n        'unknown': 3813.21,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1545.28,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22808.523,\n        'gas': 10626.6,\n        'hydro': 901.12,\n        'nuclear': 20988.2,\n        'oil': 234.32,\n        'solar': 20.3991,\n        'unknown': 3838.96,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1546.0,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22801.413,\n        'gas': 10615.6,\n        'hydro': 901.758,\n        'nuclear': 20987.1,\n        'oil': 233.922,\n        'solar': 20.8724,\n        'unknown': 3833.91,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1545.11,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22853.189,\n        'gas': 10810.3,\n        'hydro': 903.4,\n        'nuclear': 20988.5,\n        'oil': 233.233,\n        'solar': 20.6112,\n        'unknown': 3837.88,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1543.86,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23064.794,\n        'gas': 10925.9,\n        'hydro': 909.948,\n        'nuclear': 20956.3,\n        'oil': 233.556,\n        'solar': 20.4901,\n        'unknown': 3840.72,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1542.06,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22961.33,\n        'gas': 10947.6,\n        'hydro': 907.209,\n        'nuclear': 20982.7,\n        'oil': 234.543,\n        'solar': 20.4734,\n        'unknown': 3842.84,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1541.33,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22847.785,\n        'gas': 11038.7,\n        'hydro': 901.711,\n        'nuclear': 20986.6,\n        'oil': 234.307,\n        'solar': 20.7031,\n        'unknown': 3838.8,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1542.14,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 5, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22704.194,\n        'gas': 11238.6,\n        'hydro': 901.749,\n        'nuclear': 21001.0,\n        'oil': 233.171,\n        'solar': 20.7771,\n        'unknown': 3845.59,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1543.37,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22913.381,\n        'gas': 11449.5,\n        'hydro': 927.439,\n        'nuclear': 20984.7,\n        'oil': 233.47,\n        'solar': 20.4454,\n        'unknown': 3838.42,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1539.31,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23026.936,\n        'gas': 11830.9,\n        'hydro': 944.4,\n        'nuclear': 20994.8,\n        'oil': 233.067,\n        'solar': 20.7108,\n        'unknown': 3850.87,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1542.4,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22863.35,\n        'gas': 11902.0,\n        'hydro': 930.89,\n        'nuclear': 20995.9,\n        'oil': 233.031,\n        'solar': 21.1791,\n        'unknown': 3849.52,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1215.03,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22876.532,\n        'gas': 12087.2,\n        'hydro': 930.786,\n        'nuclear': 21012.3,\n        'oil': 232.192,\n        'solar': 21.3822,\n        'unknown': 3847.7,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1213.15,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22811.51,\n        'gas': 12184.7,\n        'hydro': 931.446,\n        'nuclear': 20995.9,\n        'oil': 231.933,\n        'solar': 22.2722,\n        'unknown': 3851.76,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 908.016,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22777.535,\n        'gas': 12385.7,\n        'hydro': 933.499,\n        'nuclear': 20989.3,\n        'oil': 231.372,\n        'solar': 24.3191,\n        'unknown': 3850.6,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 906.428,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22820.481,\n        'gas': 12623.1,\n        'hydro': 933.495,\n        'nuclear': 21005.2,\n        'oil': 232.082,\n        'solar': 28.7164,\n        'unknown': 3863.03,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 905.752,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22905.216,\n        'gas': 12924.5,\n        'hydro': 930.044,\n        'nuclear': 20987.4,\n        'oil': 231.623,\n        'solar': 40.576,\n        'unknown': 3864.4,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 907.837,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22821.618,\n        'gas': 13079.4,\n        'hydro': 932.116,\n        'nuclear': 21005.1,\n        'oil': 231.889,\n        'solar': 56.2159,\n        'unknown': 3850.35,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 907.772,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23069.908,\n        'gas': 13161.6,\n        'hydro': 946.032,\n        'nuclear': 21003.1,\n        'oil': 232.754,\n        'solar': 77.6794,\n        'unknown': 3854.44,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 903.596,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23056.439,\n        'gas': 13448.3,\n        'hydro': 933.88,\n        'nuclear': 21008.3,\n        'oil': 231.58,\n        'solar': 104.674,\n        'unknown': 3850.27,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 905.15,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 6, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23111.071,\n        'gas': 13883.5,\n        'hydro': 929.089,\n        'nuclear': 21014.5,\n        'oil': 232.687,\n        'solar': 137.396,\n        'unknown': 3846.07,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 904.614,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22916.071,\n        'gas': 14017.6,\n        'hydro': 923.634,\n        'nuclear': 21014.7,\n        'oil': 231.82,\n        'solar': 175.106,\n    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'coal': 23229.201,\n        'gas': 14512.1,\n        'hydro': 934.1,\n        'nuclear': 21006.3,\n        'oil': 232.339,\n        'solar': 272.013,\n        'unknown': 3811.15,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 375.524,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23268.339,\n        'gas': 14674.6,\n        'hydro': 933.921,\n        'nuclear': 21023.5,\n        'oil': 232.299,\n        'solar': 325.857,\n        'unknown': 3804.44,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 376.271,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': 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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 375.875,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23449.431,\n        'gas': 15641.6,\n        'hydro': 943.498,\n        'nuclear': 21008.9,\n        'oil': 232.489,\n        'solar': 483.597,\n        'unknown': 3761.29,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 375.883,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 7, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23495.594,\n        'gas': 15513.2,\n        'hydro': 929.45,\n        'nuclear': 21007.7,\n        'oil': 232.946,\n        'solar': 543.612,\n        'unknown': 3746.04,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -2.60625,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23549.854,\n        'gas': 15750.1,\n        'hydro': 934.109,\n        'nuclear': 21025.0,\n        'oil': 232.581,\n        'solar': 605.583,\n        'unknown': 3736.41,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.40728,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23378.999,\n        'gas': 15960.1,\n        'hydro': 933.739,\n        'nuclear': 21015.0,\n        'oil': 233.097,\n        'solar': 662.125,\n        'unknown': 3721.42,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.30742,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23563.134,\n        'gas': 16148.9,\n        'hydro': 934.341,\n        'nuclear': 21015.6,\n        'oil': 231.761,\n        'solar': 726.851,\n        'unknown': 3713.81,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.999805,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 7, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23535.486,\n        'gas': 16333.2,\n        'hydro': 935.443,\n        'nuclear': 21010.5,\n        'oil': 232.995,\n        'solar': 793.448,\n        'unknown': 3698.33,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.40728,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23799.813,\n        'gas': 16786.0,\n        'hydro': 1029.96,\n        'nuclear': 21003.3,\n        'oil': 232.01,\n        'solar': 866.994,\n        'unknown': 3682.35,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.79961,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24029.552,\n        'gas': 17295.6,\n        'hydro': 1041.29,\n        'nuclear': 21015.9,\n        'oil': 232.238,\n        'solar': 928.233,\n        'unknown': 3668.94,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.40728,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24094.418,\n        'gas': 17573.2,\n        'hydro': 1033.38,\n        'nuclear': 21007.4,\n        'oil': 232.348,\n        'solar': 1031.01,\n        'unknown': 3623.31,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.899707,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24312.984,\n        'gas': 17914.5,\n        'hydro': 1038.94,\n        'nuclear': 21012.6,\n        'oil': 232.773,\n        'solar': 1113.68,\n        'unknown': 3602.88,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.899707,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24216.765,\n        'gas': 18084.6,\n        'hydro': 1018.38,\n        'nuclear': 21002.8,\n        'oil': 232.331,\n        'solar': 1203.87,\n        'unknown': 3576.59,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.09966,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24194.405,\n        'gas': 18597.7,\n        'hydro': 1033.72,\n        'nuclear': 21012.7,\n        'oil': 231.759,\n        'solar': 1286.55,\n        'unknown': 3542.12,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.40728,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24245.197,\n        'gas': 19118.7,\n        'hydro': 1034.47,\n        'nuclear': 21017.9,\n        'oil': 232.242,\n        'solar': 1360.22,\n        'unknown': 3531.96,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.999805,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24431.668,\n        'gas': 19637.3,\n        'hydro': 1038.85,\n        'nuclear': 21018.9,\n        'oil': 232.642,\n        'solar': 1443.77,\n        'unknown': 3519.0,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.09966,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24323.158,\n        'gas': 19788.6,\n        'hydro': 1022.21,\n        'nuclear': 21019.2,\n        'oil': 232.688,\n        'solar': 1541.51,\n        'unknown': 3488.88,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.09966,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24403.508,\n        'gas': 19988.9,\n        'hydro': 1024.22,\n        'nuclear': 21028.6,\n        'oil': 232.251,\n        'solar': 1656.12,\n        'unknown': 3456.22,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.20732,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24314.961,\n        'gas': 19883.6,\n        'hydro': 1014.86,\n        'nuclear': 21007.5,\n        'oil': 232.501,\n        'solar': 1745.01,\n        'unknown': 3444.12,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -201.754,\n 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}),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -201.007,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24294.466,\n        'gas': 20480.5,\n        'hydro': 981.258,\n        'nuclear': 21019.3,\n        'oil': 232.66,\n        'solar': 2007.82,\n        'unknown': 3384.27,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -199.469,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24299.535,\n        'gas': 20421.7,\n        'hydro': 983.337,\n        'nuclear': 21021.6,\n        'oil': 231.773,\n        'solar': 2119.28,\n        'unknown': 3345.61,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -409.921,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24310.564,\n        'gas': 20299.3,\n        'hydro': 983.098,\n        'nuclear': 21020.3,\n        'oil': 232.527,\n        'solar': 2262.66,\n        'unknown': 3297.6,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -420.585,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24325.17,\n        'gas': 20355.3,\n        'hydro': 988.446,\n        'nuclear': 21010.1,\n        'oil': 230.906,\n        'solar': 2386.14,\n        'unknown': 3259.45,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -417.664,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24252.843,\n        'gas': 20354.7,\n        'hydro': 976.448,\n        'nuclear': 21028.6,\n        'oil': 231.732,\n        'solar': 2489.65,\n        'unknown': 3237.67,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -417.583,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24240.619,\n        'gas': 20354.8,\n        'hydro': 989.42,\n        'nuclear': 21005.1,\n        'oil': 233.347,\n        'solar': 2594.14,\n        'unknown': 3209.98,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -418.582,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24226.206,\n        'gas': 20239.9,\n        'hydro': 971.37,\n        'nuclear': 21016.8,\n        'oil': 233.094,\n        'solar': 2712.31,\n        'unknown': 3201.04,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -417.125,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23955.794,\n        'gas': 20123.9,\n        'hydro': 959.183,\n        'nuclear': 21005.5,\n        'oil': 232.779,\n        'solar': 2796.3,\n        'unknown': 3187.1,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -411.681,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23965.175,\n        'gas': 20147.9,\n        'hydro': 966.191,\n        'nuclear': 21017.8,\n        'oil': 233.21,\n        'solar': 2944.3,\n        'unknown': 3159.69,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -416.756,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23833.672,\n        'gas': 20189.7,\n        'hydro': 956.031,\n        'nuclear': 21007.4,\n        'oil': 231.385,\n        'solar': 3044.42,\n        'unknown': 3150.65,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -411.234,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 9, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23768.628,\n        'gas': 19957.2,\n        'hydro': 964.672,\n        'nuclear': 21008.7,\n        'oil': 233.416,\n        'solar': 3127.01,\n        'unknown': 3144.21,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -415.065,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23572.387,\n        'gas': 19850.4,\n        'hydro': 882.371,\n        'nuclear': 21008.8,\n        'oil': 233.735,\n        'solar': 3199.22,\n        'unknown': 3122.56,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -412.934,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23315.242,\n        'gas': 19683.6,\n        'hydro': 874.296,\n        'nuclear': 21033.2,\n        'oil': 231.985,\n        'solar': 3355.96,\n        'unknown': 3079.66,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -405.847,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23262.46,\n        'gas': 20171.2,\n        'hydro': 886.226,\n        'nuclear': 21011.0,\n        'oil': 248.189,\n        'solar': 3464.57,\n        'unknown': 3043.96,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -214.761,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23283.227,\n        'gas': 20375.8,\n        'hydro': 898.505,\n        'nuclear': 21004.9,\n        'oil': 256.945,\n        'solar': 3556.77,\n        'unknown': 2996.99,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -220.824,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23357.071,\n        'gas': 20443.5,\n        'hydro': 895.03,\n        'nuclear': 21020.2,\n        'oil': 236.664,\n        'solar': 3699.84,\n        'unknown': 2874.35,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -219.816,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23180.094,\n        'gas': 20277.2,\n        'hydro': 886.669,\n        'nuclear': 21018.8,\n        'oil': 233.152,\n        'solar': 3814.88,\n        'unknown': 2840.05,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -218.743,\n 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}),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -216.923,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22916.342,\n        'gas': 20475.9,\n        'hydro': 901.524,\n        'nuclear': 21024.9,\n        'oil': 232.979,\n        'solar': 3996.47,\n        'unknown': 2800.78,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.30742,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22921.763,\n        'gas': 20341.2,\n        'hydro': 893.648,\n        'nuclear': 21024.9,\n        'oil': 232.906,\n        'solar': 4082.28,\n        'unknown': 2780.3,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.999805,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22977.844,\n        'gas': 20362.5,\n        'hydro': 900.818,\n        'nuclear': 21026.6,\n        'oil': 232.82,\n        'solar': 4158.27,\n        'unknown': 2753.13,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.899707,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 10, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22775.636,\n        'gas': 20195.2,\n        'hydro': 886.276,\n        'nuclear': 21035.4,\n        'oil': 234.384,\n        'solar': 4251.71,\n        'unknown': 2718.5,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.20732,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22498.578,\n        'gas': 20062.0,\n        'hydro': 880.7,\n        'nuclear': 21042.2,\n        'oil': 238.784,\n        'solar': 4286.65,\n        'unknown': 2717.62,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.09966,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22392.149,\n        'gas': 19736.9,\n        'hydro': 889.539,\n        'nuclear': 21033.5,\n        'oil': 241.662,\n        'solar': 4390.68,\n        'unknown': 2691.23,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -0.999805,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22183.236,\n        'gas': 19830.8,\n        'hydro': 890.757,\n        'nuclear': 21017.8,\n        'oil': 236.698,\n        'solar': 4437.31,\n        'unknown': 2683.08,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.20732,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21813.962,\n        'gas': 19855.5,\n        'hydro': 895.391,\n        'nuclear': 21021.2,\n        'oil': 238.121,\n        'solar': 4582.73,\n        'unknown': 2679.68,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.20732,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21609.876,\n        'gas': 19977.0,\n        'hydro': 885.335,\n        'nuclear': 21019.7,\n        'oil': 246.419,\n        'solar': 4673.27,\n        'unknown': 2662.41,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.30742,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21285.135,\n        'gas': 19919.8,\n        'hydro': 886.234,\n        'nuclear': 21029.4,\n        'oil': 264.923,\n        'solar': 4795.46,\n        'unknown': 2625.36,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.10723,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21034.558,\n        'gas': 19737.7,\n        'hydro': 851.448,\n        'nuclear': 21026.6,\n        'oil': 263.223,\n        'solar': 4796.81,\n        'unknown': 2636.38,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.20732,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20736.034,\n        'gas': 19722.2,\n        'hydro': 852.701,\n        'nuclear': 21028.6,\n        'oil': 237.513,\n        'solar': 4795.74,\n        'unknown': 2622.48,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 8.22047,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20594.542,\n        'gas': 19869.8,\n        'hydro': 853.62,\n        'nuclear': 21023.7,\n        'oil': 233.146,\n        'solar': 4820.04,\n        'unknown': 2597.55,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 327.974,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20498.104,\n        'gas': 19668.3,\n        'hydro': 849.806,\n        'nuclear': 21009.0,\n        'oil': 233.358,\n        'solar': 4928.32,\n        'unknown': 2583.43,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 335.906,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20304.412,\n        'gas': 19413.6,\n        'hydro': 847.451,\n        'nuclear': 21012.1,\n        'oil': 233.415,\n        'solar': 4916.27,\n        'unknown': 2597.66,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 360.997,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 11, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20119.292,\n        'gas': 19505.0,\n        'hydro': 849.896,\n        'nuclear': 21021.6,\n        'oil': 231.824,\n        'solar': 4994.97,\n        'unknown': 2572.76,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 703.403,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 19933.018,\n        'gas': 19412.6,\n        'hydro': 850.273,\n        'nuclear': 21021.4,\n        'oil': 233.887,\n        'solar': 5089.53,\n        'unknown': 2545.3,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 908.985,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20067.798,\n        'gas': 19312.8,\n        'hydro': 882.901,\n        'nuclear': 21038.8,\n        'oil': 233.524,\n        'solar': 5090.95,\n        'unknown': 2566.43,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1151.04,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20002.405,\n        'gas': 19321.2,\n        'hydro': 890.994,\n        'nuclear': 21014.0,\n        'oil': 233.192,\n        'solar': 5060.54,\n        'unknown': 2622.9,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1246.87,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20163.36,\n        'gas': 18932.9,\n        'hydro': 914.288,\n        'nuclear': 21025.6,\n        'oil': 233.507,\n        'solar': 5116.24,\n        'unknown': 2629.92,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1241.83,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 19992.882,\n        'gas': 19060.9,\n        'hydro': 856.88,\n        'nuclear': 21023.5,\n        'oil': 234.224,\n        'solar': 5172.4,\n        'unknown': 2645.37,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1269.8,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 19916.488,\n        'gas': 19329.0,\n        'hydro': 910.889,\n        'nuclear': 21023.9,\n        'oil': 233.693,\n        'solar': 5206.12,\n        'unknown': 2648.76,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1655.73,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 19982.088,\n        'gas': 19112.0,\n        'hydro': 903.05,\n        'nuclear': 21028.8,\n        'oil': 234.993,\n        'solar': 5201.7,\n        'unknown': 2645.0,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1651.46,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 19957.615,\n        'gas': 19157.2,\n        'hydro': 877.041,\n        'nuclear': 21015.9,\n        'oil': 235.598,\n        'solar': 5224.77,\n        'unknown': 2652.51,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1650.43,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 19860.863,\n        'gas': 19151.4,\n        'hydro': 893.316,\n        'nuclear': 21016.1,\n        'oil': 234.692,\n        'solar': 5172.07,\n        'unknown': 2665.38,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1653.71,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 19949.37,\n        'gas': 19121.6,\n        'hydro': 892.813,\n        'nuclear': 21033.5,\n        'oil': 235.0,\n        'solar': 5192.14,\n        'unknown': 2681.03,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1651.1,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20120.64,\n        'gas': 19183.4,\n        'hydro': 917.62,\n        'nuclear': 21009.2,\n        'oil': 233.382,\n        'solar': 5198.02,\n        'unknown': 2705.32,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1645.61,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 12, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20083.426,\n        'gas': 19144.7,\n        'hydro': 915.343,\n        'nuclear': 21029.9,\n        'oil': 233.265,\n        'solar': 5293.94,\n        'unknown': 2700.59,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1653.16,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20289.844,\n        'gas': 19427.9,\n        'hydro': 917.044,\n        'nuclear': 21017.5,\n        'oil': 234.335,\n        'solar': 5260.5,\n        'unknown': 2749.34,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 1322.76,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20331.763,\n        'gas': 19480.7,\n        'hydro': 958.656,\n        'nuclear': 21027.1,\n        'oil': 233.905,\n        'solar': 5248.5,\n        'unknown': 2792.22,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 703.152,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20472.564,\n        'gas': 19681.1,\n        'hydro': 961.688,\n        'nuclear': 21034.4,\n        'oil': 235.648,\n        'solar': 5207.77,\n        'unknown': 2833.81,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 702.718,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20576.456,\n        'gas': 19765.7,\n        'hydro': 959.744,\n        'nuclear': 21030.0,\n        'oil': 235.95,\n        'solar': 5244.68,\n        'unknown': 2878.62,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 702.062,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20652.643,\n        'gas': 19973.1,\n        'hydro': 959.823,\n        'nuclear': 21032.0,\n        'oil': 235.403,\n        'solar': 5218.25,\n        'unknown': 2929.4,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 697.601,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20689.413,\n        'gas': 19929.4,\n        'hydro': 961.871,\n        'nuclear': 21020.5,\n        'oil': 235.427,\n        'solar': 5188.62,\n        'unknown': 2986.54,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': 374.381,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20663.463,\n        'gas': 19680.9,\n        'hydro': 942.44,\n        'nuclear': 21041.0,\n        'oil': 234.867,\n        'solar': 5146.38,\n        'unknown': 3015.54,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.09966,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20567.591,\n        'gas': 20271.7,\n        'hydro': 957.865,\n        'nuclear': 21015.9,\n        'oil': 233.635,\n        'solar': 5073.97,\n        'unknown': 3041.91,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1.09966,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20509.298,\n        'gas': 20468.5,\n        'hydro': 952.908,\n        'nuclear': 21035.1,\n        'oil': 233.194,\n        'solar': 5098.27,\n        'unknown': 3034.28,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -121.366,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20769.256,\n        'gas': 20552.3,\n        'hydro': 932.684,\n        'nuclear': 21023.9,\n        'oil': 234.202,\n        'solar': 5077.93,\n        'unknown': 3056.77,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -136.321,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20775.139,\n        'gas': 20490.2,\n        'hydro': 923.415,\n        'nuclear': 21033.4,\n        'oil': 232.768,\n        'solar': 5000.35,\n        'unknown': 3091.02,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -121.56,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 13, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20901.622,\n        'gas': 20375.3,\n        'hydro': 920.65,\n        'nuclear': 21025.2,\n        'oil': 234.687,\n        'solar': 4960.38,\n        'unknown': 3142.22,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -122.748,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21076.323,\n        'gas': 20493.4,\n        'hydro': 928.62,\n        'nuclear': 21016.2,\n        'oil': 234.614,\n        'solar': 4978.05,\n        'unknown': 3160.94,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -128.258,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21088.716,\n        'gas': 20615.7,\n        'hydro': 922.024,\n        'nuclear': 21016.3,\n        'oil': 241.185,\n        'solar': 5016.2,\n        'unknown': 3166.22,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -125.284,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21162.083,\n        'gas': 20710.3,\n        'hydro': 896.256,\n        'nuclear': 21031.9,\n        'oil': 244.85,\n        'solar': 5001.76,\n        'unknown': 3181.12,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      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'solar': 4782.86,\n        'unknown': 3283.17,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -121.012,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20933.08,\n        'gas': 21369.1,\n        'hydro': 905.954,\n        'nuclear': 21029.2,\n        'oil': 249.847,\n        'solar': 4798.94,\n        'unknown': 3292.72,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -123.551,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20845.932,\n        'gas': 21266.1,\n        'hydro': 873.253,\n        'nuclear': 21041.2,\n        'oil': 250.851,\n        'solar': 4817.08,\n        'unknown': 3300.53,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -119.827,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20878.787,\n        'gas': 21556.8,\n        'hydro': 891.695,\n        'nuclear': 21039.9,\n        'oil': 253.451,\n        'solar': 4734.68,\n        'unknown': 3354.74,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -122.252,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20633.238,\n        'gas': 21799.6,\n        'hydro': 889.43,\n        'nuclear': 21028.4,\n        'oil': 253.318,\n        'solar': 4632.75,\n        'unknown': 3407.11,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -120.94,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20605.203,\n        'gas': 21992.1,\n        'hydro': 894.862,\n        'nuclear': 21042.5,\n        'oil': 254.126,\n        'solar': 4566.15,\n        'unknown': 3435.56,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -122.814,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20681.5,\n        'gas': 22130.5,\n        'hydro': 915.617,\n        'nuclear': 21026.0,\n        'oil': 255.556,\n        'solar': 4508.12,\n        'unknown': 3492.45,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -145.348,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 14, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20635.499,\n        'gas': 22167.6,\n        'hydro': 933.358,\n        'nuclear': 21021.1,\n        'oil': 261.015,\n        'solar': 4469.12,\n        'unknown': 3517.08,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -123.9,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20667.562,\n        'gas': 22052.2,\n        'hydro': 917.015,\n        'nuclear': 21031.1,\n        'oil': 261.216,\n        'solar': 4437.5,\n        'unknown': 3516.72,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -121.243,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20380.209,\n        'gas': 22142.6,\n        'hydro': 950.536,\n        'nuclear': 21035.0,\n        'oil': 269.401,\n        'solar': 4373.81,\n        'unknown': 3565.92,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -120.939,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20400.596,\n        'gas': 22385.7,\n        'hydro': 982.388,\n        'nuclear': 21031.2,\n        'oil': 269.344,\n        'solar': 4237.49,\n        'unknown': 3593.17,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -120.922,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20465.478,\n        'gas': 22448.1,\n        'hydro': 962.61,\n        'nuclear': 21030.0,\n        'oil': 268.787,\n        'solar': 4187.71,\n        'unknown': 3665.74,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -126.721,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20674.282,\n        'gas': 22632.0,\n        'hydro': 1014.95,\n        'nuclear': 21028.0,\n        'oil': 268.415,\n        'solar': 4062.48,\n        'unknown': 3678.88,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -129.043,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21100.148,\n        'gas': 22615.5,\n        'hydro': 1008.96,\n        'nuclear': 21019.2,\n        'oil': 267.968,\n        'solar': 4019.99,\n        'unknown': 3680.18,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -507.633,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 20974.627,\n        'gas': 22289.6,\n        'hydro': 977.948,\n        'nuclear': 21012.7,\n        'oil': 269.185,\n        'solar': 3960.18,\n        'unknown': 3699.52,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -905.932,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21087.523,\n        'gas': 22225.1,\n        'hydro': 1002.26,\n        'nuclear': 21020.5,\n        'oil': 269.466,\n        'solar': 3830.49,\n        'unknown': 3696.9,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -913.298,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21209.571,\n        'gas': 22439.5,\n        'hydro': 999.981,\n        'nuclear': 21024.6,\n        'oil': 269.124,\n        'solar': 3744.75,\n        'unknown': 3708.89,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -920.338,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21438.831,\n        'gas': 22699.2,\n        'hydro': 1001.73,\n        'nuclear': 21018.4,\n        'oil': 269.245,\n        'solar': 3666.75,\n        'unknown': 3720.5,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1075.33,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21557.544,\n        'gas': 22784.1,\n        'hydro': 1005.31,\n        'nuclear': 21037.2,\n        'oil': 275.435,\n        'solar': 3494.94,\n        'unknown': 3722.35,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1103.41,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 15, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21687.137,\n        'gas': 22930.8,\n        'hydro': 1001.21,\n        'nuclear': 21042.5,\n        'oil': 272.401,\n        'solar': 3369.7,\n        'unknown': 3726.69,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1146.95,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 21765.66,\n        'gas': 22966.4,\n        'hydro': 1003.42,\n        'nuclear': 21025.0,\n        'oil': 274.781,\n        'solar': 3418.18,\n        'unknown': 3730.55,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1145.72,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22134.453,\n        'gas': 22687.9,\n        'hydro': 970.734,\n        'nuclear': 21034.3,\n        'oil': 274.326,\n        'solar': 3374.82,\n        'unknown': 3735.24,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1101.39,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22312.844,\n        'gas': 22920.9,\n        'hydro': 963.291,\n        'nuclear': 21024.8,\n        'oil': 275.474,\n        'solar': 3224.49,\n        'unknown': 3758.45,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1147.8,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22438.734,\n        'gas': 23003.0,\n        'hydro': 969.377,\n        'nuclear': 21038.4,\n        'oil': 277.562,\n        'solar': 3033.74,\n        'unknown': 3916.69,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1344.36,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22626.833,\n        'gas': 22967.8,\n        'hydro': 966.654,\n        'nuclear': 21020.5,\n        'oil': 296.039,\n        'solar': 2869.86,\n        'unknown': 4004.88,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1341.93,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22790.516,\n        'gas': 23153.9,\n        'hydro': 966.915,\n        'nuclear': 21035.4,\n        'oil': 311.159,\n        'solar': 2795.02,\n        'unknown': 3998.73,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1200.94,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23072.195,\n        'gas': 23084.9,\n        'hydro': 1029.02,\n        'nuclear': 21031.8,\n        'oil': 330.133,\n        'solar': 2676.43,\n        'unknown': 4041.31,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1158.44,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23108.655,\n        'gas': 23244.5,\n        'hydro': 1051.41,\n        'nuclear': 21040.6,\n        'oil': 331.038,\n        'solar': 2655.07,\n        'unknown': 4020.09,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1027.02,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23290.401,\n        'gas': 23321.6,\n        'hydro': 1065.33,\n        'nuclear': 21031.2,\n        'oil': 332.266,\n        'solar': 2569.48,\n        'unknown': 4053.74,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1054.35,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23205.405,\n        'gas': 23505.8,\n        'hydro': 1059.62,\n        'nuclear': 21004.5,\n        'oil': 332.05,\n        'solar': 2495.83,\n        'unknown': 4066.04,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1037.2,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23297.478,\n        'gas': 23533.2,\n        'hydro': 1059.55,\n        'nuclear': 21008.6,\n        'oil': 331.45,\n        'solar': 2360.98,\n        'unknown': 4107.01,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1039.95,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 16, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23239.017,\n        'gas': 23221.7,\n        'hydro': 1043.44,\n        'nuclear': 21009.4,\n        'oil': 332.389,\n        'solar': 2306.01,\n        'unknown': 4100.21,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1264.01,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23507.726,\n        'gas': 22950.6,\n        'hydro': 1014.25,\n        'nuclear': 21005.9,\n        'oil': 332.291,\n        'solar': 2208.98,\n        'unknown': 4131.3,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1295.98,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23436.016,\n        'gas': 22943.2,\n        'hydro': 996.338,\n        'nuclear': 21001.4,\n        'oil': 331.942,\n        'solar': 2123.1,\n        'unknown': 4138.24,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1270.64,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23385.524,\n        'gas': 23177.7,\n        'hydro': 1000.92,\n        'nuclear': 21007.7,\n        'oil': 332.183,\n        'solar': 1919.18,\n        'unknown': 4210.38,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1277.06,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23556.282,\n        'gas': 23153.8,\n        'hydro': 1024.1,\n        'nuclear': 20999.5,\n        'oil': 331.491,\n        'solar': 1760.64,\n        'unknown': 4282.59,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1306.59,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23794.602,\n        'gas': 23199.4,\n        'hydro': 1023.72,\n        'nuclear': 21006.1,\n        'oil': 331.888,\n        'solar': 1654.15,\n        'unknown': 4334.85,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1306.89,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23828.465,\n        'gas': 23328.3,\n        'hydro': 999.186,\n        'nuclear': 21007.6,\n        'oil': 331.534,\n        'solar': 1514.45,\n        'unknown': 4360.17,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1291.63,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23924.36,\n        'gas': 23286.7,\n        'hydro': 998.604,\n        'nuclear': 21015.0,\n        'oil': 332.576,\n        'solar': 1405.17,\n        'unknown': 4423.32,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1293.88,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23881.682,\n        'gas': 23244.8,\n        'hydro': 998.337,\n        'nuclear': 20999.6,\n        'oil': 330.707,\n        'solar': 1321.33,\n        'unknown': 4433.77,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1278.85,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23919.53,\n        'gas': 23097.5,\n        'hydro': 945.125,\n        'nuclear': 21012.3,\n        'oil': 332.131,\n        'solar': 1236.3,\n        'unknown': 4443.53,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1276.55,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24209.082,\n        'gas': 23214.9,\n        'hydro': 955.911,\n        'nuclear': 20991.7,\n        'oil': 331.701,\n        'solar': 1141.55,\n        'unknown': 4457.89,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1306.85,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24046.168,\n        'gas': 23382.2,\n        'hydro': 947.537,\n        'nuclear': 21000.3,\n        'oil': 331.603,\n        'solar': 1044.35,\n        'unknown': 4473.56,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1275.85,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 17, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23920.998,\n        'gas': 23429.0,\n        'hydro': 944.57,\n        'nuclear': 21005.8,\n        'oil': 331.694,\n        'solar': 938.44,\n        'unknown': 4495.42,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1271.18,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24070.109,\n        'gas': 23412.3,\n        'hydro': 854.475,\n        'nuclear': 21017.3,\n        'oil': 331.766,\n        'solar': 827.543,\n        'unknown': 4520.28,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1285.29,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24028.683,\n        'gas': 23177.3,\n        'hydro': 811.484,\n        'nuclear': 20996.7,\n        'oil': 333.226,\n        'solar': 739.265,\n        'unknown': 4527.9,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1246.67,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23989.188,\n        'gas': 23102.9,\n        'hydro': 838.787,\n        'nuclear': 21007.5,\n        'oil': 331.27,\n        'solar': 653.718,\n        'unknown': 4533.51,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1280.88,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24049.078,\n        'gas': 23280.3,\n        'hydro': 836.698,\n        'nuclear': 21001.0,\n        'oil': 330.909,\n        'solar': 563.402,\n        'unknown': 4576.04,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1284.62,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24002.906,\n        'gas': 23383.5,\n        'hydro': 836.092,\n        'nuclear': 20995.7,\n        'oil': 332.62,\n        'solar': 454.824,\n        'unknown': 4647.37,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1288.83,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24087.934,\n        'gas': 23459.0,\n        'hydro': 839.571,\n        'nuclear': 20989.4,\n        'oil': 332.416,\n        'solar': 372.871,\n        'unknown': 4667.91,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1283.54,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24014.974,\n        'gas': 23570.9,\n        'hydro': 834.371,\n        'nuclear': 21004.7,\n        'oil': 333.451,\n        'solar': 313.835,\n        'unknown': 4684.53,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1281.06,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24081.693,\n        'gas': 23455.8,\n        'hydro': 836.632,\n        'nuclear': 20983.3,\n        'oil': 338.392,\n        'solar': 255.266,\n        'unknown': 4698.36,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1298.21,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24029.884,\n        'gas': 23512.7,\n        'hydro': 830.666,\n        'nuclear': 20993.2,\n        'oil': 341.546,\n        'solar': 195.595,\n        'unknown': 4711.61,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1297.7,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24070.041,\n        'gas': 23676.2,\n        'hydro': 834.854,\n        'nuclear': 20968.8,\n        'oil': 346.372,\n        'solar': 149.08,\n        'unknown': 4723.56,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1281.29,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23979.064,\n        'gas': 23759.8,\n        'hydro': 834.088,\n        'nuclear': 20983.8,\n        'oil': 345.49,\n        'solar': 105.487,\n        'unknown': 4734.47,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1280.55,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 18, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24090.607,\n        'gas': 23722.8,\n        'hydro': 844.691,\n        'nuclear': 20968.3,\n        'oil': 346.197,\n        'solar': 61.0313,\n        'unknown': 4741.69,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1307.52,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24050.508,\n        'gas': 23885.8,\n        'hydro': 835.146,\n        'nuclear': 20991.0,\n        'oil': 346.234,\n        'solar': 28.8268,\n        'unknown': 4747.15,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1281.68,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23963.986,\n        'gas': 23663.5,\n        'hydro': 835.415,\n        'nuclear': 20978.5,\n        'oil': 346.323,\n        'solar': 5.26572,\n        'unknown': 4761.33,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1281.82,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24166.168,\n        'gas': 23747.8,\n        'hydro': 846.884,\n        'nuclear': 20983.1,\n        'oil': 346.328,\n        'solar': 0.0,\n        'unknown': 4794.44,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1298.4,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24169.009,\n        'gas': 23921.9,\n        'hydro': 837.595,\n        'nuclear': 20977.2,\n        'oil': 346.323,\n        'solar': 0.0,\n        'unknown': 4827.14,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1294.88,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24028.65,\n        'gas': 23734.7,\n        'hydro': 830.536,\n        'nuclear': 20983.9,\n        'oil': 344.999,\n        'solar': 0.0,\n        'unknown': 4849.31,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1286.78,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24086.551,\n        'gas': 23580.2,\n        'hydro': 822.088,\n        'nuclear': 20973.7,\n        'oil': 344.973,\n        'solar': 0.0,\n        'unknown': 4865.52,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1291.91,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24083.823,\n        'gas': 23400.1,\n        'hydro': 789.092,\n        'nuclear': 20985.0,\n        'oil': 346.636,\n        'solar': 0.0,\n        'unknown': 4857.07,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1274.64,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24126.745,\n        'gas': 23361.1,\n        'hydro': 789.31,\n        'nuclear': 20994.1,\n        'oil': 346.614,\n        'solar': 0.0,\n        'unknown': 4843.59,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1291.81,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24169.886,\n        'gas': 23265.8,\n        'hydro': 787.382,\n        'nuclear': 20998.4,\n        'oil': 346.234,\n        'solar': 0.0,\n        'unknown': 4844.53,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1287.52,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 24004.291,\n        'gas': 23017.2,\n        'hydro': 782.884,\n        'nuclear': 20995.2,\n        'oil': 344.79,\n        'solar': 0.0,\n        'unknown': 4833.72,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1275.81,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23999.299,\n        'gas': 22711.5,\n        'hydro': 774.939,\n        'nuclear': 20997.4,\n        'oil': 346.369,\n        'solar': 0.0,\n        'unknown': 4815.18,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1251.39,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 19, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23903.872,\n        'gas': 22464.1,\n        'hydro': 778.613,\n        'nuclear': 20995.5,\n        'oil': 346.435,\n        'solar': 0.0,\n        'unknown': 4815.27,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1263.1,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23904.274,\n        'gas': 22343.4,\n        'hydro': 753.673,\n        'nuclear': 21008.8,\n        'oil': 345.956,\n        'solar': 0.0,\n        'unknown': 4787.85,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1261.56,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23735.531,\n        'gas': 22163.1,\n        'hydro': 688.229,\n        'nuclear': 21008.9,\n        'oil': 345.877,\n        'solar': 0.0,\n        'unknown': 4757.17,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1246.36,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23788.623,\n        'gas': 22228.9,\n        'hydro': 695.648,\n        'nuclear': 20994.2,\n        'oil': 337.453,\n        'solar': 0.0,\n        'unknown': 4704.33,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1310.47,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23716.283,\n        'gas': 22062.2,\n        'hydro': 689.704,\n        'nuclear': 20991.9,\n        'oil': 331.938,\n        'solar': 0.0,\n        'unknown': 4694.21,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1280.17,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23865.067,\n        'gas': 21668.2,\n        'hydro': 689.265,\n        'nuclear': 20992.7,\n        'oil': 322.073,\n        'solar': 0.0,\n        'unknown': 4683.1,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1271.47,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23677.975,\n        'gas': 21589.5,\n        'hydro': 689.471,\n        'nuclear': 21006.3,\n        'oil': 313.086,\n        'solar': 0.0,\n        'unknown': 4663.02,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1279.87,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23572.688,\n        'gas': 21194.2,\n        'hydro': 688.682,\n        'nuclear': 21008.5,\n        'oil': 309.16,\n        'solar': 0.0,\n        'unknown': 4644.38,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1257.48,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23715.04,\n        'gas': 21045.2,\n        'hydro': 693.281,\n        'nuclear': 20996.8,\n        'oil': 307.448,\n        'solar': 0.0,\n        'unknown': 4631.19,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1294.29,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23680.071,\n        'gas': 20979.4,\n        'hydro': 689.066,\n        'nuclear': 21003.6,\n        'oil': 305.505,\n        'solar': 0.0,\n        'unknown': 4611.86,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1278.44,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23673.816,\n        'gas': 20634.5,\n        'hydro': 690.19,\n        'nuclear': 20992.1,\n        'oil': 304.776,\n        'solar': 0.0,\n        'unknown': 4592.39,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1280.56,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23598.092,\n        'gas': 20176.3,\n        'hydro': 688.88,\n        'nuclear': 20981.6,\n        'oil': 305.783,\n        'solar': 0.0,\n        'unknown': 4562.1,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1269.15,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23778.58,\n        'gas': 20296.1,\n        'hydro': 691.368,\n        'nuclear': 20982.5,\n        'oil': 305.385,\n        'solar': 0.0,\n        'unknown': 4538.52,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1293.62,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23730.25,\n        'gas': 20034.2,\n        'hydro': 689.224,\n        'nuclear': 21012.8,\n        'oil': 306.015,\n        'solar': 0.0,\n        'unknown': 4501.14,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -1152.1,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23673.292,\n        'gas': 20144.6,\n        'hydro': 688.457,\n        'nuclear': 20991.8,\n        'oil': 304.472,\n        'solar': 0.0,\n        'unknown': 4476.68,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -929.355,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23725.711,\n        'gas': 20034.4,\n        'hydro': 689.515,\n        'nuclear': 21005.4,\n        'oil': 304.064,\n        'solar': 0.0,\n        'unknown': 4430.08,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -940.006,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23810.198,\n        'gas': 19838.2,\n        'hydro': 689.44,\n        'nuclear': 21005.8,\n        'oil': 304.905,\n        'solar': 0.0,\n        'unknown': 4340.73,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -932.272,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23538.073,\n        'gas': 19526.7,\n        'hydro': 688.734,\n        'nuclear': 21005.9,\n        'oil': 303.648,\n        'solar': 0.0,\n        'unknown': 4294.17,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -927.656,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23561.426,\n        'gas': 19350.6,\n        'hydro': 688.647,\n        'nuclear': 21013.3,\n        'oil': 305.12,\n        'solar': 0.0,\n        'unknown': 4252.9,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -912.148,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23504.916,\n        'gas': 19256.3,\n        'hydro': 689.332,\n        'nuclear': 20984.5,\n        'oil': 305.641,\n        'solar': 0.0,\n        'unknown': 4221.58,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -931.385,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23553.68,\n        'gas': 19025.8,\n        'hydro': 689.052,\n        'nuclear': 21003.7,\n        'oil': 305.329,\n        'solar': 0.0,\n        'unknown': 4205.84,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -823.368,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23537.016,\n        'gas': 18836.5,\n        'hydro': 689.584,\n        'nuclear': 21013.5,\n        'oil': 305.148,\n        'solar': 0.0,\n        'unknown': 4162.06,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -644.575,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23514.322,\n        'gas': 18769.6,\n        'hydro': 690.643,\n        'nuclear': 20990.4,\n        'oil': 303.072,\n        'solar': 0.0,\n        'unknown': 4129.88,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -643.789,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23489.485,\n        'gas': 18448.1,\n        'hydro': 689.612,\n        'nuclear': 21014.8,\n        'oil': 304.466,\n        'solar': 0.0,\n        'unknown': 4098.81,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -648.847,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23470.457,\n        'gas': 18438.6,\n        'hydro': 689.492,\n        'nuclear': 21021.0,\n        'oil': 304.172,\n        'solar': 0.0,\n        'unknown': 4072.03,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -648.185,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23534.018,\n        'gas': 18335.7,\n        'hydro': 686.214,\n        'nuclear': 20998.1,\n        'oil': 306.343,\n        'solar': 0.0,\n        'unknown': 4047.08,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -650.269,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23451.878,\n        'gas': 18449.6,\n        'hydro': 686.773,\n        'nuclear': 20993.3,\n        'oil': 305.183,\n        'solar': 0.0,\n        'unknown': 4018.27,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -656.417,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23646.245,\n        'gas': 18351.9,\n        'hydro': 663.805,\n        'nuclear': 21024.5,\n        'oil': 304.958,\n        'solar': 0.0,\n        'unknown': 3979.79,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -669.735,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23688.954,\n        'gas': 18242.5,\n        'hydro': 662.178,\n        'nuclear': 21025.4,\n        'oil': 305.379,\n        'solar': 0.0,\n        'unknown': 3963.38,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -635.765,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23889.313,\n        'gas': 18128.7,\n        'hydro': 665.263,\n        'nuclear': 21017.5,\n        'oil': 305.107,\n        'solar': 0.0,\n        'unknown': 3934.55,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -668.872,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23823.157,\n        'gas': 17945.8,\n        'hydro': 661.232,\n        'nuclear': 20998.8,\n        'oil': 306.52,\n        'solar': 0.0,\n        'unknown': 3904.66,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -638.573,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23738.947,\n        'gas': 17659.7,\n        'hydro': 650.865,\n        'nuclear': 21017.3,\n        'oil': 305.455,\n        'solar': 0.0,\n        'unknown': 3887.86,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -650.65,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23673.077,\n        'gas': 17514.7,\n        'hydro': 649.58,\n        'nuclear': 21019.3,\n        'oil': 305.077,\n        'solar': 0.0,\n        'unknown': 3879.18,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -638.921,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23760.353,\n        'gas': 17397.9,\n        'hydro': 652.48,\n        'nuclear': 21026.4,\n        'oil': 305.566,\n        'solar': 0.0,\n        'unknown': 3864.85,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -646.358,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23757.735,\n        'gas': 17108.9,\n        'hydro': 651.954,\n        'nuclear': 21016.0,\n        'oil': 305.415,\n        'solar': 0.0,\n        'unknown': 3860.11,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -656.59,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23787.083,\n        'gas': 16936.5,\n        'hydro': 651.208,\n        'nuclear': 21018.3,\n        'oil': 304.212,\n        'solar': 0.0,\n        'unknown': 3858.19,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -636.344,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23653.436,\n        'gas': 16769.4,\n        'hydro': 648.488,\n        'nuclear': 21023.1,\n        'oil': 305.759,\n        'solar': 0.0,\n        'unknown': 3854.5,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -635.101,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23664.894,\n        'gas': 16684.1,\n        'hydro': 651.528,\n        'nuclear': 21023.6,\n        'oil': 304.292,\n        'solar': 0.0,\n        'unknown': 3852.83,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -641.672,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23539.45,\n        'gas': 16717.7,\n        'hydro': 649.613,\n        'nuclear': 21012.8,\n        'oil': 304.974,\n        'solar': 0.0,\n        'unknown': 3850.78,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -632.988,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23636.02,\n        'gas': 16600.0,\n        'hydro': 651.319,\n        'nuclear': 21028.5,\n        'oil': 304.305,\n        'solar': 0.0,\n        'unknown': 3835.13,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -445.401,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23568.115,\n        'gas': 16460.8,\n        'hydro': 651.741,\n        'nuclear': 21022.0,\n        'oil': 304.412,\n        'solar': 0.0,\n        'unknown': 3820.16,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -448.64,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23564.371,\n        'gas': 16313.8,\n        'hydro': 653.166,\n        'nuclear': 21017.5,\n        'oil': 305.195,\n        'solar': 0.0,\n        'unknown': 3812.62,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -449.037,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23461.98,\n        'gas': 15918.8,\n        'hydro': 652.409,\n        'nuclear': 21017.2,\n        'oil': 305.771,\n        'solar': 0.0,\n        'unknown': 3810.68,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -442.143,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23283.904,\n        'gas': 15557.2,\n        'hydro': 652.589,\n        'nuclear': 21029.4,\n        'oil': 304.393,\n        'solar': 0.0,\n        'unknown': 3812.09,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -440.388,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23271.213,\n        'gas': 15435.1,\n        'hydro': 654.279,\n        'nuclear': 21018.6,\n        'oil': 305.209,\n        'solar': 0.0,\n        'unknown': 3803.64,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -439.749,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23268.711,\n        'gas': 15103.3,\n        'hydro': 652.968,\n        'nuclear': 21024.4,\n        'oil': 305.323,\n        'solar': 0.0,\n        'unknown': 3789.01,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -442.203,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23301.872,\n        'gas': 14911.3,\n        'hydro': 630.929,\n        'nuclear': 21015.4,\n        'oil': 304.956,\n        'solar': 0.0,\n        'unknown': 3787.08,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -453.978,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 23196.116,\n        'gas': 14573.8,\n        'hydro': 619.958,\n        'nuclear': 21023.7,\n        'oil': 304.444,\n        'solar': 0.0,\n        'unknown': 3783.48,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -445.314,\n      }),\n      'zoneKey': 'KR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 9, 1, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='Asia/Seoul')),\n      'production': dict({\n        'coal': 22896.78,\n        'gas': 14224.4,\n        'hydro': 637.67,\n        'nuclear': 21027.5,\n        'oil': 305.52,\n        'solar': 0.0,\n        'unknown': 3787.59,\n      }),\n      'source': 'new.kpx.or.kr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'hydro': -437.866,\n      }),\n      'zoneKey': 'KR',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_exchange_forecast_historical[RO].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_forecast_historical[RO]\n  list([\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -68.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -68.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -68.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -68.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 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tzinfo=datetime.timezone.utc),\n      'netFlow': -69.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -69.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -69.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -69.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 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17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -72.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -72.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -72.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -73.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 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20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 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22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 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tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 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tzinfo=datetime.timezone.utc),\n      'netFlow': -69.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -72.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -72.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -72.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 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'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -36.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -36.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -36.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -36.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_exchange_forecast_historical[UA].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_forecast_historical[UA]\n  list([\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      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tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_exchange_forecast_live[RO].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_forecast_live[RO]\n  list([\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 22.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 22.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 22.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 22.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 20.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 20.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 20.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 20.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 19.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 19.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 19.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 19.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 17.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 17.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 17.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 17.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -12.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -12.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -12.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -12.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -39.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -39.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -39.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -39.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -51.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -51.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -51.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -51.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -37.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -37.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -37.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -37.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 4.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 4.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 4.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 4.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 2.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 2.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 2.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 2.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -28.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -28.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -28.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -28.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -98.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -98.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -98.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -98.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -83.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -83.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -83.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -83.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -32.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -32.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -32.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -32.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 6.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 6.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 6.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 6.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -21.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -21.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -21.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -21.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -24.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -24.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_exchange_forecast_live[UA].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_forecast_live[UA]\n  list([\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 322.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 299.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 274.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 297.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 255.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 218.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 213.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 175.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 176.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 191.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 101.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 162.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 161.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 159.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 154.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -15.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -5.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -21.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 10.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -53.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 23.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -128.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -108.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -261.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -229.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -358.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -305.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -363.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -322.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -373.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -375.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -354.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -361.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -253.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -381.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -486.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -478.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -495.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -582.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -580.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -557.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -545.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -587.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -510.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -559.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -574.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -494.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -493.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -491.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -539.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -557.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -495.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -465.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -427.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -410.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -364.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -269.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -339.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -301.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -239.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -292.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -438.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -302.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -345.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -254.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -271.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -301.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -273.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -207.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -187.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -214.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -108.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -208.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -149.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -118.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -116.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -167.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -196.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -209.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -190.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -128.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -148.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -115.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -84.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 19.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -61.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -61.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 4.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 61.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 109.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 61.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 90.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 149.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 185.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 142.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 169.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 39.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 25.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 50.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -22.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -76.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -48.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -16.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -105.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -134.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -102.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -53.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -192.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -192.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -201.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -246.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -425.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -451.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -394.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -371.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -479.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -559.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -508.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -507.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -493.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_exchange_historical[RO].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_historical[RO]\n  list([\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 19, 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 dict({\n      'datetime': datetime.datetime(2021, 7, 24, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      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 dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_exchange_historical[UA].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_historical[UA]\n  list([\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -33.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -31.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -32.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -32.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -31.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -33.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -28.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -26.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -27.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -31.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -37.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -22.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -29.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -53.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -26.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -13.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -29.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -55.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 6.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 32.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 18.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 8.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -17.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -84.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -97.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -26.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -28.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -76.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -22.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -22.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -20.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -8.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -5.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -7.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -123.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -6.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -3.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -1.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -7.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -13.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -94.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 4.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -61.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 17.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -68.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -66.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 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'netFlow': 19.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -36.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -37.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 17.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 32.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -21.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 45.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -3.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -31.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 45.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 14.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 33.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 23.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -78.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -101.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 20.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -7.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 75.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 51.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 49.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -4.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 32.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 24.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 36.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 32.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -50.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 36.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 26.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 26.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -83.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 24, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 2.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -69.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -48.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -52.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 25.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -57.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -65.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -46.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 20.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -60.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -48.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -57.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -77.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -12.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -26.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -7.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -12.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -32.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -58.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -84.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -10.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -25.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -113.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 4.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -29.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -60.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -24.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -79.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -65.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -2.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -94.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -16.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -19.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -66.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -65.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -74.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -68.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 19.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -61.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -54.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -30.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 23.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 4.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -51.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -77.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -83.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -21.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -74.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -70.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -90.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -65.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -4.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -77.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -1.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -10.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -5.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -7.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -66.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -85.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -74.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -33.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 30.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -1.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -82.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -17.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -19.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -44.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -28.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -21.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -2.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -75.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -73.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -41.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 67.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -36.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -43.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 29.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -51.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -67.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -78.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -19.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2021, 7, 25, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -65.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_exchange_live[RO].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_live[RO]\n  list([\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 34.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 105.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 74.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 101.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 122.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 102.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 88.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 87.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 91.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 100.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 8.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 67.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 59.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 9.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 53.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -72.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -11.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 39.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -30.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 41.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 31.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 25.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 10.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -69.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -72.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -48.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -24.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -30.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -22.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -19.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -46.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -40.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -8.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -8.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -5.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -21.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -6.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -12.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -55.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -37.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -27.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -51.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -56.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -48.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -74.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -65.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -38.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -62.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 1.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 12.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 9.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -4.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 8.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -23.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -3.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -11.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -15.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -29.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -65.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -120.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -106.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -107.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -96.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -77.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -64.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -75.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -46.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 2.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -17.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -14.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 125.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 28.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 57.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 8.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 62.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -7.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -42.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -33.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 45.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -39.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -10.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 1.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 69.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 34.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -9.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 49.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 68.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 88.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 80.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 85.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 2.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -4.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 56.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -22.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 81.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -33.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 27.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -13.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 63.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -11.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -28.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -33.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -33.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 32.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 33.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 36.0,\n      'sortedZoneKeys': 'MD->RO',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_exchange_live[UA].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange_live[UA]\n  list([\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -287.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -194.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -199.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -196.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -132.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -115.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -125.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -87.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -84.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -90.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -93.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -94.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -101.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -149.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -101.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -57.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -30.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 10.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 28.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 23.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 17.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 132.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 140.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 286.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 239.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 288.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 241.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 291.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 280.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 324.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 350.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 323.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 338.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 234.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 334.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 445.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 469.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 486.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 576.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 558.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 550.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 532.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 532.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 471.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 521.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 547.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 443.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 459.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 434.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 491.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 482.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 430.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 427.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 382.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 347.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 302.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 206.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 354.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 302.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 252.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 302.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 433.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 310.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 322.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 250.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 260.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 286.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 243.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 172.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 122.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 94.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 2.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 100.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 52.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 40.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 52.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 92.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 149.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 173.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 193.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 110.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 134.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 100.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 210.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 84.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 38.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 69.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 123.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -11.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -106.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -151.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -95.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -45.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -188.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -195.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 10, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -141.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -100.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -4.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -35.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 0.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 91.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 131.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 157.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 134.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 19.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 100.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 191.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 102.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 31.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 273.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 158.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 229.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 233.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 489.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 451.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 383.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 342.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 446.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 525.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 540.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 541.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': FakeDatetime(2024, 4, 11, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 530.0,\n      'sortedZoneKeys': 'MD->UA',\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime0].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime0]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2000, 1, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.8,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime10].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime10]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2024, 3, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 185.0,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime1].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime1]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2000, 4, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 18.8,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime2].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime2]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2001, 10, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.0,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime3].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime3]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2002, 9, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 35.2,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime4].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime4]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2005, 9, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 39.3,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime5].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime5]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2007, 8, 3, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 51.8,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime6].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime6]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2010, 1, 19, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 63.2,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime7].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime7]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2012, 5, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 80.2,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime8].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime8]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2015, 7, 31, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 145.0,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD/test_fetch_price_historical[historical_datetime9].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_price_historical[historical_datetime9]\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': datetime.datetime(2023, 12, 31, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 201.0,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_MD.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption_historical\n  list([\n    dict({\n      'consumption': 437.0,\n      'datetime': datetime.datetime(2021, 7, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 437.0,\n      'datetime': datetime.datetime(2021, 7, 24, 0, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 433.0,\n      'datetime': datetime.datetime(2021, 7, 24, 0, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 433.0,\n      'datetime': datetime.datetime(2021, 7, 24, 0, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 433.0,\n      'datetime': datetime.datetime(2021, 7, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 432.0,\n      'datetime': datetime.datetime(2021, 7, 24, 1, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 435.0,\n      'datetime': datetime.datetime(2021, 7, 24, 1, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 431.0,\n      'datetime': datetime.datetime(2021, 7, 24, 1, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 430.0,\n      'datetime': datetime.datetime(2021, 7, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 430.0,\n      'datetime': datetime.datetime(2021, 7, 24, 2, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 434.0,\n      'datetime': datetime.datetime(2021, 7, 24, 2, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 440.0,\n      'datetime': datetime.datetime(2021, 7, 24, 2, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 442.0,\n      'datetime': datetime.datetime(2021, 7, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 449.0,\n      'datetime': datetime.datetime(2021, 7, 24, 3, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 467.0,\n      'datetime': datetime.datetime(2021, 7, 24, 3, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 481.0,\n      'datetime': datetime.datetime(2021, 7, 24, 3, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 501.0,\n      'datetime': datetime.datetime(2021, 7, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 513.0,\n      'datetime': datetime.datetime(2021, 7, 24, 4, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 530.0,\n      'datetime': datetime.datetime(2021, 7, 24, 4, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 553.0,\n      'datetime': datetime.datetime(2021, 7, 24, 4, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 573.0,\n      'datetime': datetime.datetime(2021, 7, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 612.0,\n      'datetime': datetime.datetime(2021, 7, 24, 5, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 616.0,\n      'datetime': datetime.datetime(2021, 7, 24, 5, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 641.0,\n      'datetime': datetime.datetime(2021, 7, 24, 5, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 655.0,\n      'datetime': datetime.datetime(2021, 7, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 666.0,\n      'datetime': datetime.datetime(2021, 7, 24, 6, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 742.0,\n      'datetime': datetime.datetime(2021, 7, 24, 6, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 689.0,\n      'datetime': datetime.datetime(2021, 7, 24, 6, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 693.0,\n      'datetime': datetime.datetime(2021, 7, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 760.0,\n      'datetime': datetime.datetime(2021, 7, 24, 7, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 713.0,\n      'datetime': datetime.datetime(2021, 7, 24, 7, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 772.0,\n      'datetime': datetime.datetime(2021, 7, 24, 7, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 722.0,\n      'datetime': datetime.datetime(2021, 7, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 727.0,\n      'datetime': datetime.datetime(2021, 7, 24, 8, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 787.0,\n      'datetime': datetime.datetime(2021, 7, 24, 8, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 734.0,\n      'datetime': datetime.datetime(2021, 7, 24, 8, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 735.0,\n      'datetime': datetime.datetime(2021, 7, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 731.0,\n      'datetime': datetime.datetime(2021, 7, 24, 9, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 734.0,\n      'datetime': datetime.datetime(2021, 7, 24, 9, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 738.0,\n      'datetime': datetime.datetime(2021, 7, 24, 9, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 740.0,\n      'datetime': datetime.datetime(2021, 7, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 856.0,\n      'datetime': datetime.datetime(2021, 7, 24, 10, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 739.0,\n      'datetime': datetime.datetime(2021, 7, 24, 10, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 736.0,\n      'datetime': datetime.datetime(2021, 7, 24, 10, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 733.0,\n      'datetime': datetime.datetime(2021, 7, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 744.0,\n      'datetime': datetime.datetime(2021, 7, 24, 11, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 746.0,\n      'datetime': datetime.datetime(2021, 7, 24, 11, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 828.0,\n      'datetime': datetime.datetime(2021, 7, 24, 11, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 777.0,\n      'datetime': datetime.datetime(2021, 7, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 798.0,\n      'datetime': datetime.datetime(2021, 7, 24, 12, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 727.0,\n      'datetime': datetime.datetime(2021, 7, 24, 12, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 795.0,\n      'datetime': datetime.datetime(2021, 7, 24, 12, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 794.0,\n      'datetime': datetime.datetime(2021, 7, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 717.0,\n      'datetime': datetime.datetime(2021, 7, 24, 13, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 800.0,\n      'datetime': datetime.datetime(2021, 7, 24, 13, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 801.0,\n      'datetime': datetime.datetime(2021, 7, 24, 13, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 719.0,\n      'datetime': datetime.datetime(2021, 7, 24, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 715.0,\n      'datetime': datetime.datetime(2021, 7, 24, 14, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 725.0,\n      'datetime': datetime.datetime(2021, 7, 24, 14, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 715.0,\n      'datetime': datetime.datetime(2021, 7, 24, 14, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 773.0,\n      'datetime': datetime.datetime(2021, 7, 24, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 773.0,\n      'datetime': datetime.datetime(2021, 7, 24, 15, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 716.0,\n      'datetime': datetime.datetime(2021, 7, 24, 15, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 703.0,\n      'datetime': datetime.datetime(2021, 7, 24, 15, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 773.0,\n      'datetime': datetime.datetime(2021, 7, 24, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 758.0,\n      'datetime': datetime.datetime(2021, 7, 24, 16, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 691.0,\n      'datetime': datetime.datetime(2021, 7, 24, 16, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 739.0,\n      'datetime': datetime.datetime(2021, 7, 24, 16, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 750.0,\n      'datetime': datetime.datetime(2021, 7, 24, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 670.0,\n      'datetime': datetime.datetime(2021, 7, 24, 17, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 701.0,\n      'datetime': datetime.datetime(2021, 7, 24, 17, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 683.0,\n      'datetime': datetime.datetime(2021, 7, 24, 17, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 689.0,\n      'datetime': datetime.datetime(2021, 7, 24, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 791.0,\n      'datetime': datetime.datetime(2021, 7, 24, 18, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 825.0,\n      'datetime': datetime.datetime(2021, 7, 24, 18, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 822.0,\n      'datetime': datetime.datetime(2021, 7, 24, 18, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 739.0,\n      'datetime': datetime.datetime(2021, 7, 24, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 761.0,\n      'datetime': datetime.datetime(2021, 7, 24, 19, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 770.0,\n      'datetime': datetime.datetime(2021, 7, 24, 19, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 662.0,\n      'datetime': datetime.datetime(2021, 7, 24, 19, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 691.0,\n      'datetime': datetime.datetime(2021, 7, 24, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 640.0,\n      'datetime': datetime.datetime(2021, 7, 24, 20, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 663.0,\n      'datetime': datetime.datetime(2021, 7, 24, 20, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 567.0,\n      'datetime': datetime.datetime(2021, 7, 24, 20, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 567.0,\n      'datetime': datetime.datetime(2021, 7, 24, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 602.0,\n      'datetime': datetime.datetime(2021, 7, 24, 21, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 530.0,\n      'datetime': datetime.datetime(2021, 7, 24, 21, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 530.0,\n      'datetime': datetime.datetime(2021, 7, 24, 21, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 592.0,\n      'datetime': datetime.datetime(2021, 7, 24, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 572.0,\n      'datetime': datetime.datetime(2021, 7, 24, 22, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 484.0,\n      'datetime': datetime.datetime(2021, 7, 24, 22, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 494.0,\n      'datetime': datetime.datetime(2021, 7, 24, 22, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 470.0,\n      'datetime': datetime.datetime(2021, 7, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 469.0,\n      'datetime': datetime.datetime(2021, 7, 24, 23, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 554.0,\n      'datetime': datetime.datetime(2021, 7, 24, 23, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 472.0,\n      'datetime': datetime.datetime(2021, 7, 24, 23, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 468.0,\n      'datetime': datetime.datetime(2021, 7, 25, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 540.0,\n      'datetime': datetime.datetime(2021, 7, 25, 0, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 519.0,\n      'datetime': datetime.datetime(2021, 7, 25, 0, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 508.0,\n      'datetime': datetime.datetime(2021, 7, 25, 0, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 524.0,\n      'datetime': datetime.datetime(2021, 7, 25, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 442.0,\n      'datetime': datetime.datetime(2021, 7, 25, 1, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 527.0,\n      'datetime': datetime.datetime(2021, 7, 25, 1, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 537.0,\n      'datetime': datetime.datetime(2021, 7, 25, 1, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 518.0,\n      'datetime': datetime.datetime(2021, 7, 25, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 518.0,\n      'datetime': datetime.datetime(2021, 7, 25, 2, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 453.0,\n      'datetime': datetime.datetime(2021, 7, 25, 2, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 533.0,\n      'datetime': datetime.datetime(2021, 7, 25, 2, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 522.0,\n      'datetime': datetime.datetime(2021, 7, 25, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 531.0,\n      'datetime': datetime.datetime(2021, 7, 25, 3, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 550.0,\n      'datetime': datetime.datetime(2021, 7, 25, 3, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 485.0,\n      'datetime': datetime.datetime(2021, 7, 25, 3, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 552.0,\n      'datetime': datetime.datetime(2021, 7, 25, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 548.0,\n      'datetime': datetime.datetime(2021, 7, 25, 4, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 580.0,\n      'datetime': datetime.datetime(2021, 7, 25, 4, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 528.0,\n      'datetime': datetime.datetime(2021, 7, 25, 4, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 582.0,\n      'datetime': datetime.datetime(2021, 7, 25, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 610.0,\n      'datetime': datetime.datetime(2021, 7, 25, 5, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 642.0,\n      'datetime': datetime.datetime(2021, 7, 25, 5, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 667.0,\n      'datetime': datetime.datetime(2021, 7, 25, 5, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 594.0,\n      'datetime': datetime.datetime(2021, 7, 25, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 609.0,\n      'datetime': datetime.datetime(2021, 7, 25, 6, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 698.0,\n      'datetime': datetime.datetime(2021, 7, 25, 6, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 632.0,\n      'datetime': datetime.datetime(2021, 7, 25, 6, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 681.0,\n      'datetime': datetime.datetime(2021, 7, 25, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 724.0,\n      'datetime': datetime.datetime(2021, 7, 25, 7, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 724.0,\n      'datetime': datetime.datetime(2021, 7, 25, 7, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 693.0,\n      'datetime': datetime.datetime(2021, 7, 25, 7, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 750.0,\n      'datetime': datetime.datetime(2021, 7, 25, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 735.0,\n      'datetime': datetime.datetime(2021, 7, 25, 8, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 671.0,\n      'datetime': datetime.datetime(2021, 7, 25, 8, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 757.0,\n      'datetime': datetime.datetime(2021, 7, 25, 8, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 676.0,\n      'datetime': datetime.datetime(2021, 7, 25, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 685.0,\n      'datetime': datetime.datetime(2021, 7, 25, 9, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 737.0,\n      'datetime': datetime.datetime(2021, 7, 25, 9, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 743.0,\n      'datetime': datetime.datetime(2021, 7, 25, 9, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 762.0,\n      'datetime': datetime.datetime(2021, 7, 25, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 760.0,\n      'datetime': datetime.datetime(2021, 7, 25, 10, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 671.0,\n      'datetime': datetime.datetime(2021, 7, 25, 10, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 752.0,\n      'datetime': datetime.datetime(2021, 7, 25, 10, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 733.0,\n      'datetime': datetime.datetime(2021, 7, 25, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 743.0,\n      'datetime': datetime.datetime(2021, 7, 25, 11, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 722.0,\n      'datetime': datetime.datetime(2021, 7, 25, 11, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 668.0,\n      'datetime': datetime.datetime(2021, 7, 25, 11, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 669.0,\n      'datetime': datetime.datetime(2021, 7, 25, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 715.0,\n      'datetime': datetime.datetime(2021, 7, 25, 12, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 740.0,\n      'datetime': datetime.datetime(2021, 7, 25, 12, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 747.0,\n      'datetime': datetime.datetime(2021, 7, 25, 12, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 685.0,\n      'datetime': datetime.datetime(2021, 7, 25, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 738.0,\n      'datetime': datetime.datetime(2021, 7, 25, 13, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 734.0,\n      'datetime': datetime.datetime(2021, 7, 25, 13, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 731.0,\n      'datetime': datetime.datetime(2021, 7, 25, 13, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 751.0,\n      'datetime': datetime.datetime(2021, 7, 25, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 665.0,\n      'datetime': datetime.datetime(2021, 7, 25, 14, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 725.0,\n      'datetime': datetime.datetime(2021, 7, 25, 14, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 718.0,\n      'datetime': datetime.datetime(2021, 7, 25, 14, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 666.0,\n      'datetime': datetime.datetime(2021, 7, 25, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 740.0,\n      'datetime': datetime.datetime(2021, 7, 25, 15, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 664.0,\n      'datetime': datetime.datetime(2021, 7, 25, 15, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 663.0,\n      'datetime': datetime.datetime(2021, 7, 25, 15, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 671.0,\n      'datetime': datetime.datetime(2021, 7, 25, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 668.0,\n      'datetime': datetime.datetime(2021, 7, 25, 16, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 671.0,\n      'datetime': datetime.datetime(2021, 7, 25, 16, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 729.0,\n      'datetime': datetime.datetime(2021, 7, 25, 16, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 749.0,\n      'datetime': datetime.datetime(2021, 7, 25, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 747.0,\n      'datetime': datetime.datetime(2021, 7, 25, 17, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 737.0,\n      'datetime': datetime.datetime(2021, 7, 25, 17, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 672.0,\n      'datetime': datetime.datetime(2021, 7, 25, 17, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 748.0,\n      'datetime': datetime.datetime(2021, 7, 25, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 708.0,\n      'datetime': datetime.datetime(2021, 7, 25, 18, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 804.0,\n      'datetime': datetime.datetime(2021, 7, 25, 18, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 740.0,\n      'datetime': datetime.datetime(2021, 7, 25, 18, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 730.0,\n      'datetime': datetime.datetime(2021, 7, 25, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 710.0,\n      'datetime': datetime.datetime(2021, 7, 25, 19, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 691.0,\n      'datetime': datetime.datetime(2021, 7, 25, 19, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 672.0,\n      'datetime': datetime.datetime(2021, 7, 25, 19, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 647.0,\n      'datetime': datetime.datetime(2021, 7, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 615.0,\n      'datetime': datetime.datetime(2021, 7, 25, 20, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 649.0,\n      'datetime': datetime.datetime(2021, 7, 25, 20, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 636.0,\n      'datetime': datetime.datetime(2021, 7, 25, 20, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 620.0,\n      'datetime': datetime.datetime(2021, 7, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 604.0,\n      'datetime': datetime.datetime(2021, 7, 25, 21, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 494.0,\n      'datetime': datetime.datetime(2021, 7, 25, 21, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 599.0,\n      'datetime': datetime.datetime(2021, 7, 25, 21, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 557.0,\n      'datetime': datetime.datetime(2021, 7, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 555.0,\n      'datetime': datetime.datetime(2021, 7, 25, 22, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 480.0,\n      'datetime': datetime.datetime(2021, 7, 25, 22, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 562.0,\n      'datetime': datetime.datetime(2021, 7, 25, 22, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 554.0,\n      'datetime': datetime.datetime(2021, 7, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 549.0,\n      'datetime': datetime.datetime(2021, 7, 25, 23, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 482.0,\n      'datetime': datetime.datetime(2021, 7, 25, 23, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 527.0,\n      'datetime': datetime.datetime(2021, 7, 25, 23, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n# name: test_fetch_consumption_live\n  list([\n    dict({\n      'consumption': 485.0,\n      'datetime': FakeDatetime(2024, 4, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 421.0,\n      'datetime': FakeDatetime(2024, 4, 10, 0, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 451.0,\n      'datetime': FakeDatetime(2024, 4, 10, 0, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 423.0,\n      'datetime': FakeDatetime(2024, 4, 10, 0, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 401.0,\n      'datetime': FakeDatetime(2024, 4, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 422.0,\n      'datetime': FakeDatetime(2024, 4, 10, 1, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 439.0,\n      'datetime': FakeDatetime(2024, 4, 10, 1, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 438.0,\n      'datetime': FakeDatetime(2024, 4, 10, 1, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 437.0,\n      'datetime': FakeDatetime(2024, 4, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 454.0,\n      'datetime': FakeDatetime(2024, 4, 10, 2, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 545.0,\n      'datetime': FakeDatetime(2024, 4, 10, 2, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 487.0,\n      'datetime': FakeDatetime(2024, 4, 10, 2, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 511.0,\n      'datetime': FakeDatetime(2024, 4, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 604.0,\n      'datetime': FakeDatetime(2024, 4, 10, 3, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 560.0,\n      'datetime': FakeDatetime(2024, 4, 10, 3, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 686.0,\n      'datetime': FakeDatetime(2024, 4, 10, 3, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 691.0,\n      'datetime': FakeDatetime(2024, 4, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 706.0,\n      'datetime': FakeDatetime(2024, 4, 10, 4, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 663.0,\n      'datetime': FakeDatetime(2024, 4, 10, 4, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 733.0,\n      'datetime': FakeDatetime(2024, 4, 10, 4, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 654.0,\n      'datetime': FakeDatetime(2024, 4, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 694.0,\n      'datetime': FakeDatetime(2024, 4, 10, 5, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 664.0,\n      'datetime': FakeDatetime(2024, 4, 10, 5, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 670.0,\n      'datetime': FakeDatetime(2024, 4, 10, 5, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 682.0,\n      'datetime': FakeDatetime(2024, 4, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 667.0,\n      'datetime': FakeDatetime(2024, 4, 10, 6, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 649.0,\n      'datetime': FakeDatetime(2024, 4, 10, 6, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 646.0,\n      'datetime': FakeDatetime(2024, 4, 10, 6, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 619.0,\n      'datetime': FakeDatetime(2024, 4, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 636.0,\n      'datetime': FakeDatetime(2024, 4, 10, 7, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 611.0,\n      'datetime': FakeDatetime(2024, 4, 10, 7, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 620.0,\n      'datetime': FakeDatetime(2024, 4, 10, 7, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 608.0,\n      'datetime': FakeDatetime(2024, 4, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 580.0,\n      'datetime': FakeDatetime(2024, 4, 10, 8, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 575.0,\n      'datetime': FakeDatetime(2024, 4, 10, 8, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 569.0,\n      'datetime': FakeDatetime(2024, 4, 10, 8, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 547.0,\n      'datetime': FakeDatetime(2024, 4, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 552.0,\n      'datetime': FakeDatetime(2024, 4, 10, 9, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 548.0,\n      'datetime': FakeDatetime(2024, 4, 10, 9, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 565.0,\n      'datetime': FakeDatetime(2024, 4, 10, 9, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 544.0,\n      'datetime': FakeDatetime(2024, 4, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 549.0,\n      'datetime': FakeDatetime(2024, 4, 10, 10, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 590.0,\n      'datetime': FakeDatetime(2024, 4, 10, 10, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 572.0,\n      'datetime': FakeDatetime(2024, 4, 10, 10, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 572.0,\n      'datetime': FakeDatetime(2024, 4, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 559.0,\n      'datetime': FakeDatetime(2024, 4, 10, 11, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 584.0,\n      'datetime': FakeDatetime(2024, 4, 10, 11, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 568.0,\n      'datetime': FakeDatetime(2024, 4, 10, 11, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 588.0,\n      'datetime': FakeDatetime(2024, 4, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 592.0,\n      'datetime': FakeDatetime(2024, 4, 10, 12, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 618.0,\n      'datetime': FakeDatetime(2024, 4, 10, 12, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 608.0,\n      'datetime': FakeDatetime(2024, 4, 10, 12, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 584.0,\n      'datetime': FakeDatetime(2024, 4, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 606.0,\n      'datetime': FakeDatetime(2024, 4, 10, 13, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 624.0,\n      'datetime': FakeDatetime(2024, 4, 10, 13, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 623.0,\n      'datetime': FakeDatetime(2024, 4, 10, 13, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 625.0,\n      'datetime': FakeDatetime(2024, 4, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 627.0,\n      'datetime': FakeDatetime(2024, 4, 10, 14, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 649.0,\n      'datetime': FakeDatetime(2024, 4, 10, 14, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 636.0,\n      'datetime': FakeDatetime(2024, 4, 10, 14, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 670.0,\n      'datetime': FakeDatetime(2024, 4, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 687.0,\n      'datetime': FakeDatetime(2024, 4, 10, 15, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 675.0,\n      'datetime': FakeDatetime(2024, 4, 10, 15, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 705.0,\n      'datetime': FakeDatetime(2024, 4, 10, 15, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 687.0,\n      'datetime': FakeDatetime(2024, 4, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 700.0,\n      'datetime': FakeDatetime(2024, 4, 10, 16, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 704.0,\n      'datetime': FakeDatetime(2024, 4, 10, 16, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 716.0,\n      'datetime': FakeDatetime(2024, 4, 10, 16, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 726.0,\n      'datetime': FakeDatetime(2024, 4, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 754.0,\n      'datetime': FakeDatetime(2024, 4, 10, 17, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 809.0,\n      'datetime': FakeDatetime(2024, 4, 10, 17, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 794.0,\n      'datetime': FakeDatetime(2024, 4, 10, 17, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 795.0,\n      'datetime': FakeDatetime(2024, 4, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 784.0,\n      'datetime': FakeDatetime(2024, 4, 10, 18, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 766.0,\n      'datetime': FakeDatetime(2024, 4, 10, 18, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 751.0,\n      'datetime': FakeDatetime(2024, 4, 10, 18, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 750.0,\n      'datetime': FakeDatetime(2024, 4, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 708.0,\n      'datetime': FakeDatetime(2024, 4, 10, 19, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 698.0,\n      'datetime': FakeDatetime(2024, 4, 10, 19, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 661.0,\n      'datetime': FakeDatetime(2024, 4, 10, 19, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 680.0,\n      'datetime': FakeDatetime(2024, 4, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 675.0,\n      'datetime': FakeDatetime(2024, 4, 10, 20, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 676.0,\n      'datetime': FakeDatetime(2024, 4, 10, 20, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 536.0,\n      'datetime': FakeDatetime(2024, 4, 10, 20, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 616.0,\n      'datetime': FakeDatetime(2024, 4, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 531.0,\n      'datetime': FakeDatetime(2024, 4, 10, 21, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 579.0,\n      'datetime': FakeDatetime(2024, 4, 10, 21, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 526.0,\n      'datetime': FakeDatetime(2024, 4, 10, 21, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 517.0,\n      'datetime': FakeDatetime(2024, 4, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 549.0,\n      'datetime': FakeDatetime(2024, 4, 10, 22, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 547.0,\n      'datetime': FakeDatetime(2024, 4, 10, 22, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 541.0,\n      'datetime': FakeDatetime(2024, 4, 10, 22, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 446.0,\n      'datetime': FakeDatetime(2024, 4, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 531.0,\n      'datetime': FakeDatetime(2024, 4, 10, 23, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 504.0,\n      'datetime': FakeDatetime(2024, 4, 10, 23, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 490.0,\n      'datetime': FakeDatetime(2024, 4, 10, 23, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 416.0,\n      'datetime': FakeDatetime(2024, 4, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 442.0,\n      'datetime': FakeDatetime(2024, 4, 11, 0, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 490.0,\n      'datetime': FakeDatetime(2024, 4, 11, 0, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 428.0,\n      'datetime': FakeDatetime(2024, 4, 11, 0, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 417.0,\n      'datetime': FakeDatetime(2024, 4, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 398.0,\n      'datetime': FakeDatetime(2024, 4, 11, 1, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 405.0,\n      'datetime': FakeDatetime(2024, 4, 11, 1, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 401.0,\n      'datetime': FakeDatetime(2024, 4, 11, 1, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 496.0,\n      'datetime': FakeDatetime(2024, 4, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 515.0,\n      'datetime': FakeDatetime(2024, 4, 11, 2, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 453.0,\n      'datetime': FakeDatetime(2024, 4, 11, 2, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 511.0,\n      'datetime': FakeDatetime(2024, 4, 11, 2, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 548.0,\n      'datetime': FakeDatetime(2024, 4, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 507.0,\n      'datetime': FakeDatetime(2024, 4, 11, 3, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 621.0,\n      'datetime': FakeDatetime(2024, 4, 11, 3, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 562.0,\n      'datetime': FakeDatetime(2024, 4, 11, 3, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 691.0,\n      'datetime': FakeDatetime(2024, 4, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 637.0,\n      'datetime': FakeDatetime(2024, 4, 11, 4, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 704.0,\n      'datetime': FakeDatetime(2024, 4, 11, 4, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 720.0,\n      'datetime': FakeDatetime(2024, 4, 11, 4, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 738.0,\n      'datetime': FakeDatetime(2024, 4, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 744.0,\n      'datetime': FakeDatetime(2024, 4, 11, 5, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 741.0,\n      'datetime': FakeDatetime(2024, 4, 11, 5, 30, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 674.0,\n      'datetime': FakeDatetime(2024, 4, 11, 5, 45, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 670.0,\n      'datetime': FakeDatetime(2024, 4, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'consumption': 659.0,\n      'datetime': FakeDatetime(2024, 4, 11, 6, 15, tzinfo=datetime.timezone.utc),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n# name: test_fetch_price_live\n  list([\n    dict({\n      'currency': 'MDL',\n      'datetime': FakeDatetime(2024, 4, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 185.0,\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n# name: test_fetch_production_historical\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 350.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 351.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 349.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 348.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 349.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 348.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 349.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 349.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 350.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 350.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 350.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 350.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 350.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 374.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 385.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 385.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 385.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 407.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 450.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 487.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 490.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 504.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 570.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 620.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 621.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 622.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 622.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 622.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 623.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 623.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 622.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 622.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 643.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 646.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 658.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 659.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 660.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 658.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 673.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 680.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 680.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 680.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 680.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 680.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 679.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 683.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 679.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 680.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 680.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 678.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 678.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 678.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 680.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 682.0,\n        'hydro': 49.0,\n      }),\n      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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 666.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 663.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n    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'gas': 660.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 660.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 671.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      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datetime.datetime(2021, 7, 24, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 711.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 709.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 685.0,\n        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'production': dict({\n        'biomass': 2.0,\n        'gas': 468.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 444.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 24, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 419.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      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datetime.datetime(2021, 7, 25, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.0,\n        'gas': 420.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 0.0,\n        'gas': 420.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.0,\n        'gas': 420.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.0,\n        'gas': 421.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.0,\n        'gas': 420.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      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dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 467.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 516.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 524.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 531.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 530.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 530.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 531.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      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'gas': 598.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 608.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 610.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 615.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 618.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 617.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 616.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 610.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 606.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 613.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 618.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 625.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 635.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 639.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 638.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 638.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 642.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 636.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 639.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n   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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 610.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 610.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n   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'gas': 611.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 607.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 608.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 612.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 606.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 609.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 609.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 609.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 609.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 609.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 608.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 610.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 610.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 610.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 611.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 620.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 651.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 650.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 652.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 654.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 670.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 669.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 659.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 595.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 594.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 591.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 573.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 561.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 520.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 509.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 510.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 510.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 509.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 510.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 461.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 458.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 457.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 459.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 434.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 417.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 410.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2021, 7, 25, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 409.0,\n        'hydro': 49.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n# name: test_fetch_production_live\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 474.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 13.0,\n        'gas': 479.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 479.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 478.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 477.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 478.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 480.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 478.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 484.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 508.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 508.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 510.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 526.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 571.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 8.0,\n        'gas': 571.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 571.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 611.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 651.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 658.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 657.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 650.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 652.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 651.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 651.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 649.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 8.0,\n        'gas': 554.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 6, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 541.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 6, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 530.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 533.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 7, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 542.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 7, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 542.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 7, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 13.0,\n        'gas': 541.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 539.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 8, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 511.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 8, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 18.0,\n        'gas': 475.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 8, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 476.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 487.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 9, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 491.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 9, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 492.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 9, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 492.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 13.0,\n        'gas': 490.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 10, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 490.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 10, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 10.0,\n        'gas': 491.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 10, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 8.0,\n        'gas': 490.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 491.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 11, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 8.0,\n        'gas': 489.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 11, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 9.0,\n        'gas': 489.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 11, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 8.0,\n        'gas': 491.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 8.0,\n        'gas': 489.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 12, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 7.0,\n        'gas': 501.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 12, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 7.0,\n        'gas': 503.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 12, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 6.0,\n        'gas': 503.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 7.0,\n        'gas': 504.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 13, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 5.0,\n        'gas': 521.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 13, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 5.0,\n        'gas': 522.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 13, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 4.0,\n        'gas': 521.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 5.0,\n        'gas': 523.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 14, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 4.0,\n        'gas': 603.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 14, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 3.0,\n        'gas': 613.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 14, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 3.0,\n        'gas': 611.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 643.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 15, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 646.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 15, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 647.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 15, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 645.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 647.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 16, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 652.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 16, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 651.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 16, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 650.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 3.0,\n        'gas': 653.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 17, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 3.0,\n        'gas': 652.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 17, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 3.0,\n        'gas': 651.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 17, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 651.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 652.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 18, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 652.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 18, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 652.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 18, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 651.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 638.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 19, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 625.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 19, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 626.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 19, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.0,\n        'gas': 628.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.0,\n        'gas': 626.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 20, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.0,\n        'gas': 625.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 20, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 1.0,\n        'gas': 626.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 20, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 626.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 608.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 21, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 553.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 21, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 551.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 21, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 2.0,\n        'gas': 552.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 3.0,\n        'gas': 472.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 22, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 4.0,\n        'gas': 466.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 22, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 5.0,\n        'gas': 466.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 22, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 6.0,\n        'gas': 467.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 6.0,\n        'gas': 450.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 23, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 7.0,\n        'gas': 450.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 23, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 7.0,\n        'gas': 452.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 10, 23, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 7.0,\n        'gas': 450.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 8.0,\n        'gas': 443.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 0, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 11.0,\n        'gas': 431.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 0, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 432.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 0, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 13.0,\n        'gas': 430.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 437.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 1, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 435.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 1, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 435.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 1, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 436.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 448.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 2, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 461.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 2, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 460.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 2, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 462.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 475.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 3, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 537.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 3, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 536.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 3, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 538.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 625.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 4, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 17.0,\n        'gas': 648.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 4, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 18.0,\n        'gas': 652.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 4, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 19.0,\n        'gas': 655.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 19.0,\n        'gas': 655.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 5, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 20.0,\n        'gas': 656.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 5, 30, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 16.0,\n        'gas': 656.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 5, 45, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 15.0,\n        'gas': 657.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 12.0,\n        'gas': 657.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 4, 11, 6, 15, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'biomass': 14.0,\n        'gas': 648.0,\n        'hydro': 32.0,\n      }),\n      'source': 'moldelectrica.md',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'MD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_NORDPOOL.ambr",
    "content": "# serializer version: 1\n# name: test_exchange_parser_fi_se1\n  list([\n    dict({\n      'datetime': datetime.datetime(2024, 11, 30, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -907.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 11, 30, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -907.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 11, 30, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -907.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 11, 30, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -907.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -960.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -960.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -960.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -960.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -866.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -866.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -866.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -866.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -979.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -979.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -979.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -979.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -769.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -769.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -769.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -769.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -702.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -702.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -702.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -702.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -640.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -640.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -640.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -640.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -692.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -692.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -692.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -692.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 7, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -345.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 7, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -345.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 7, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -345.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 7, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -345.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 8, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -169.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 8, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -169.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 8, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -169.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 8, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -169.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 9, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -97.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 9, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -97.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 9, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -97.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 9, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -97.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 10, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -227.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 10, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -227.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 10, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -227.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 10, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -227.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -97.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 11, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -97.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 11, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -97.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 11, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -97.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 12, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 12, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 12, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': -34.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 13, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 71.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 13, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 71.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 13, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 71.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 13, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 71.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 14, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 438.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 14, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 438.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 14, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 438.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 14, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 438.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 15, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 638.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 15, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 638.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 15, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 638.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 15, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 638.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 16, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 857.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 16, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 857.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 16, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 857.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 16, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 857.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 17, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 610.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 17, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 610.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 17, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 610.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 17, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 610.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 18, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 609.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 18, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 609.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 18, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 609.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 18, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 609.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 19, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 1069.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 19, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 1069.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 19, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 1069.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 19, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 1069.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 20, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 895.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 20, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 895.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 20, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 895.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 20, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 895.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 21, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 1087.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 21, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 1087.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 21, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 1087.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 21, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 1087.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 22, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 1014.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 22, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 1014.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 22, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 1014.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 22, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 1014.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 23, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 667.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 23, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 667.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 23, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 667.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 1, 23, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 667.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 0, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 693.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 0, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 693.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 0, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 693.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 0, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 693.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 1, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 669.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 1, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 669.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 1, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 669.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 1, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 669.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 2, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 595.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 2, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 595.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 2, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 595.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 2, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 595.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 3, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 649.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 3, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 649.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 3, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 649.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 3, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 649.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 4, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 918.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 4, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 918.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 4, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 918.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 4, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 918.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 5, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 938.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 5, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 938.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 5, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 938.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 5, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 938.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 6, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 805.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 6, 15, tzinfo=datetime.timezone.utc),\n      'netFlow': 805.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 6, 30, tzinfo=datetime.timezone.utc),\n      'netFlow': 805.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2024, 12, 2, 6, 45, tzinfo=datetime.timezone.utc),\n      'netFlow': 805.0,\n      'sortedZoneKeys': 'FI->SE-SE1',\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_price_parser_se\n  list([\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 7, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 79.67,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.81,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 72.3,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 75.86,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 74.45,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 78.51,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 24.54,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.14,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.29,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.61,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.56,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.19,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.36,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.74,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.85,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 29.98,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 29.98,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.15,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.74,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 31.46,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 31.17,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.17,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 29.03,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 27.99,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 22, 0, tzinfo=datetime.timezone.utc),\n      'price': 27.46,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 8, 23, 0, tzinfo=datetime.timezone.utc),\n      'price': 26.69,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 0, 0, tzinfo=datetime.timezone.utc),\n      'price': 26.06,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 1, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.65,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 2, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.58,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 3, 0, tzinfo=datetime.timezone.utc),\n      'price': 27.27,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 4, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.52,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 5, 0, tzinfo=datetime.timezone.utc),\n      'price': 32.25,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 6, 0, tzinfo=datetime.timezone.utc),\n      'price': 33.81,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 7, 0, tzinfo=datetime.timezone.utc),\n      'price': 33.65,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 8, 0, tzinfo=datetime.timezone.utc),\n      'price': 31.42,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 9, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.44,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 10, 0, tzinfo=datetime.timezone.utc),\n      'price': 28.83,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 11, 0, tzinfo=datetime.timezone.utc),\n      'price': 25.27,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 12, 0, tzinfo=datetime.timezone.utc),\n      'price': 26.68,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 13, 0, tzinfo=datetime.timezone.utc),\n      'price': 29.72,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 14, 0, tzinfo=datetime.timezone.utc),\n      'price': 32.29,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 15, 0, tzinfo=datetime.timezone.utc),\n      'price': 79.73,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 16, 0, tzinfo=datetime.timezone.utc),\n      'price': 99.27,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 17, 0, tzinfo=datetime.timezone.utc),\n      'price': 110.27,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 18, 0, tzinfo=datetime.timezone.utc),\n      'price': 112.8,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 19, 0, tzinfo=datetime.timezone.utc),\n      'price': 100.32,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 20, 0, tzinfo=datetime.timezone.utc),\n      'price': 31.54,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n    dict({\n      'currency': 'EUR',\n      'datetime': datetime.datetime(2024, 7, 9, 21, 0, tzinfo=datetime.timezone.utc),\n      'price': 30.1,\n      'source': 'nordpool.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'SE-SE4',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_NTESMO.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': 186.0,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 180.19,\n      'datetime': datetime.datetime(2025, 4, 4, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 173.634,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 186.692,\n      'datetime': datetime.datetime(2025, 4, 4, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 180.457,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 174.799,\n      'datetime': datetime.datetime(2025, 4, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 170.747,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 167.989,\n      'datetime': datetime.datetime(2025, 4, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 165.45,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 162.369,\n      'datetime': datetime.datetime(2025, 4, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 161.258,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 160.461,\n      'datetime': datetime.datetime(2025, 4, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 160.127,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 159.687,\n      'datetime': datetime.datetime(2025, 4, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 161.181,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 163.32,\n      'datetime': datetime.datetime(2025, 4, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 169.129,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 172.5,\n      'datetime': datetime.datetime(2025, 4, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 175.068,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 175.208,\n      'datetime': datetime.datetime(2025, 4, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 174.007,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 176.123,\n      'datetime': datetime.datetime(2025, 4, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 173.113,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 163.625,\n      'datetime': datetime.datetime(2025, 4, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 156.971,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 152.591,\n      'datetime': datetime.datetime(2025, 4, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 154.42,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 163.618,\n      'datetime': datetime.datetime(2025, 4, 5, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 168.746,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 157.31,\n      'datetime': datetime.datetime(2025, 4, 5, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 157.494,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 164.937,\n      'datetime': datetime.datetime(2025, 4, 5, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 166.433,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 180.761,\n      'datetime': datetime.datetime(2025, 4, 5, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 192.558,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 208.849,\n      'datetime': datetime.datetime(2025, 4, 5, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 219.735,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 227.093,\n      'datetime': datetime.datetime(2025, 4, 5, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 234.152,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 241.498,\n      'datetime': datetime.datetime(2025, 4, 5, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 245.823,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 247.989,\n      'datetime': datetime.datetime(2025, 4, 5, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 247.08,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 237.041,\n      'datetime': datetime.datetime(2025, 4, 5, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 228.986,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 224.047,\n      'datetime': datetime.datetime(2025, 4, 5, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 217.941,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 209.543,\n      'datetime': datetime.datetime(2025, 4, 5, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 201.387,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 193.991,\n      'datetime': datetime.datetime(2025, 4, 5, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 187.741,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 178.32,\n      'datetime': datetime.datetime(2025, 4, 5, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 172.314,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 168.195,\n      'datetime': datetime.datetime(2025, 4, 6, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 164.297,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 162.365,\n      'datetime': datetime.datetime(2025, 4, 6, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 160.016,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 158.331,\n      'datetime': datetime.datetime(2025, 4, 6, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 156.8,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 154.601,\n      'datetime': datetime.datetime(2025, 4, 6, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 154.188,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 153.526,\n      'datetime': datetime.datetime(2025, 4, 6, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 154.875,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 156.933,\n      'datetime': datetime.datetime(2025, 4, 6, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 161.364,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 165.79,\n      'datetime': datetime.datetime(2025, 4, 6, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 165.913,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 162.963,\n      'datetime': datetime.datetime(2025, 4, 6, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 156.887,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 164.0,\n      'datetime': datetime.datetime(2025, 4, 6, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 172.099,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 174.864,\n      'datetime': datetime.datetime(2025, 4, 6, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 165.76,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 157.611,\n      'datetime': datetime.datetime(2025, 4, 6, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 162.182,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 177.685,\n      'datetime': datetime.datetime(2025, 4, 6, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 199.574,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 178.001,\n      'datetime': datetime.datetime(2025, 4, 6, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 170.268,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 162.105,\n      'datetime': datetime.datetime(2025, 4, 6, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 167.497,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 178.127,\n      'datetime': datetime.datetime(2025, 4, 6, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 188.331,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 208.391,\n      'datetime': datetime.datetime(2025, 4, 6, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 209.752,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 217.502,\n      'datetime': datetime.datetime(2025, 4, 6, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 219.933,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 230.096,\n      'datetime': datetime.datetime(2025, 4, 6, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 230.593,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 243.6,\n      'datetime': datetime.datetime(2025, 4, 6, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 242.793,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 239.542,\n      'datetime': datetime.datetime(2025, 4, 6, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 231.293,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 225.246,\n      'datetime': datetime.datetime(2025, 4, 6, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 216.326,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 206.317,\n      'datetime': datetime.datetime(2025, 4, 6, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 195.843,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 187.786,\n      'datetime': datetime.datetime(2025, 4, 6, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 180.175,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 176.765,\n      'datetime': datetime.datetime(2025, 4, 6, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 171.965,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 167.661,\n      'datetime': datetime.datetime(2025, 4, 7, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 165.538,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 162.659,\n      'datetime': datetime.datetime(2025, 4, 7, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 161.106,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 159.348,\n      'datetime': datetime.datetime(2025, 4, 7, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 158.78,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 158.473,\n      'datetime': datetime.datetime(2025, 4, 7, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 158.51,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 159.317,\n      'datetime': datetime.datetime(2025, 4, 7, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 164.445,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 170.129,\n      'datetime': datetime.datetime(2025, 4, 7, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 184.321,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 197.206,\n      'datetime': datetime.datetime(2025, 4, 7, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 211.01,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 215.396,\n      'datetime': datetime.datetime(2025, 4, 7, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 218.471,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 219.576,\n      'datetime': datetime.datetime(2025, 4, 7, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 210.031,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 206.632,\n      'datetime': datetime.datetime(2025, 4, 7, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 207.391,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 199.46,\n      'datetime': datetime.datetime(2025, 4, 7, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 200.682,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 206.342,\n      'datetime': datetime.datetime(2025, 4, 7, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 201.407,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 210.83,\n      'datetime': datetime.datetime(2025, 4, 7, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 219.771,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 238.039,\n      'datetime': datetime.datetime(2025, 4, 7, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 246.889,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 260.013,\n      'datetime': datetime.datetime(2025, 4, 7, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 264.42,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 268.337,\n      'datetime': datetime.datetime(2025, 4, 7, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 278.199,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 269.028,\n      'datetime': datetime.datetime(2025, 4, 7, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 268.721,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 273.072,\n      'datetime': datetime.datetime(2025, 4, 7, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 271.32,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 272.622,\n      'datetime': datetime.datetime(2025, 4, 7, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 270.275,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 259.475,\n      'datetime': datetime.datetime(2025, 4, 7, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 248.119,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 239.039,\n      'datetime': datetime.datetime(2025, 4, 7, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 229.407,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 218.164,\n      'datetime': datetime.datetime(2025, 4, 7, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 207.895,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 198.601,\n      'datetime': datetime.datetime(2025, 4, 7, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 190.317,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 183.142,\n      'datetime': datetime.datetime(2025, 4, 7, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 177.554,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 172.393,\n      'datetime': datetime.datetime(2025, 4, 8, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 169.695,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 166.761,\n      'datetime': datetime.datetime(2025, 4, 8, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 164.824,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 163.034,\n      'datetime': datetime.datetime(2025, 4, 8, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 162.034,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 161.111,\n      'datetime': datetime.datetime(2025, 4, 8, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 160.969,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 161.46,\n      'datetime': datetime.datetime(2025, 4, 8, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 166.179,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 172.528,\n      'datetime': datetime.datetime(2025, 4, 8, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 185.982,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 197.424,\n      'datetime': datetime.datetime(2025, 4, 8, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 211.293,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 214.915,\n      'datetime': datetime.datetime(2025, 4, 8, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 217.154,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 214.993,\n      'datetime': datetime.datetime(2025, 4, 8, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 205.851,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 202.222,\n      'datetime': datetime.datetime(2025, 4, 8, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 202.478,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 194.661,\n      'datetime': datetime.datetime(2025, 4, 8, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 195.81,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 203.896,\n      'datetime': datetime.datetime(2025, 4, 8, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 200.36,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 210.098,\n      'datetime': datetime.datetime(2025, 4, 8, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 219.015,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 235.891,\n      'datetime': datetime.datetime(2025, 4, 8, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 243.828,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 262.293,\n      'datetime': datetime.datetime(2025, 4, 8, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 266.556,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 271.476,\n      'datetime': datetime.datetime(2025, 4, 8, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 279.406,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 269.305,\n      'datetime': datetime.datetime(2025, 4, 8, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 269.282,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 267.987,\n      'datetime': datetime.datetime(2025, 4, 8, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 266.315,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 271.926,\n      'datetime': datetime.datetime(2025, 4, 8, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 269.945,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 259.696,\n      'datetime': datetime.datetime(2025, 4, 8, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 248.532,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 238.653,\n      'datetime': datetime.datetime(2025, 4, 8, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 229.099,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 217.769,\n      'datetime': datetime.datetime(2025, 4, 8, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 207.416,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 197.476,\n      'datetime': datetime.datetime(2025, 4, 8, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 189.035,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 182.025,\n      'datetime': datetime.datetime(2025, 4, 8, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 176.537,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 172.42,\n      'datetime': datetime.datetime(2025, 4, 9, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 169.551,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 166.691,\n      'datetime': datetime.datetime(2025, 4, 9, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 164.955,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 163.46,\n      'datetime': datetime.datetime(2025, 4, 9, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 162.477,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 161.973,\n      'datetime': datetime.datetime(2025, 4, 9, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 161.817,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 162.514,\n      'datetime': datetime.datetime(2025, 4, 9, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 167.439,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 173.789,\n      'datetime': datetime.datetime(2025, 4, 9, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 187.159,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 198.044,\n      'datetime': datetime.datetime(2025, 4, 9, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 212.051,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 215.021,\n      'datetime': datetime.datetime(2025, 4, 9, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 217.096,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 217.436,\n      'datetime': datetime.datetime(2025, 4, 9, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 209.486,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 205.933,\n      'datetime': datetime.datetime(2025, 4, 9, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 208.257,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 199.966,\n      'datetime': datetime.datetime(2025, 4, 9, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 202.49,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 208.696,\n      'datetime': datetime.datetime(2025, 4, 9, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 204.111,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 212.464,\n      'datetime': datetime.datetime(2025, 4, 9, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 221.266,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 235.614,\n      'datetime': datetime.datetime(2025, 4, 9, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 242.412,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 258.796,\n      'datetime': datetime.datetime(2025, 4, 9, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 262.025,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 263.825,\n      'datetime': datetime.datetime(2025, 4, 9, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 271.42,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 263.911,\n      'datetime': datetime.datetime(2025, 4, 9, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 263.495,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 262.005,\n      'datetime': datetime.datetime(2025, 4, 9, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 260.016,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 264.929,\n      'datetime': datetime.datetime(2025, 4, 9, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 262.757,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 253.252,\n      'datetime': datetime.datetime(2025, 4, 9, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 243.079,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 235.182,\n      'datetime': datetime.datetime(2025, 4, 9, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 225.839,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 215.103,\n      'datetime': datetime.datetime(2025, 4, 9, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 205.155,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 196.242,\n      'datetime': datetime.datetime(2025, 4, 9, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 188.101,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 180.268,\n      'datetime': datetime.datetime(2025, 4, 9, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 174.603,\n      'datetime': datetime.datetime(2025, 4, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 170.759,\n      'datetime': datetime.datetime(2025, 4, 10, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 168.075,\n      'datetime': datetime.datetime(2025, 4, 10, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 165.564,\n      'datetime': datetime.datetime(2025, 4, 10, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 163.62,\n      'datetime': datetime.datetime(2025, 4, 10, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 161.59,\n      'datetime': datetime.datetime(2025, 4, 10, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 160.719,\n      'datetime': datetime.datetime(2025, 4, 10, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 160.055,\n      'datetime': datetime.datetime(2025, 4, 10, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 159.901,\n      'datetime': datetime.datetime(2025, 4, 10, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 160.544,\n      'datetime': datetime.datetime(2025, 4, 10, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 165.276,\n      'datetime': datetime.datetime(2025, 4, 10, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 170.786,\n      'datetime': datetime.datetime(2025, 4, 10, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 183.565,\n      'datetime': datetime.datetime(2025, 4, 10, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 195.168,\n      'datetime': datetime.datetime(2025, 4, 10, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 208.353,\n      'datetime': datetime.datetime(2025, 4, 10, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 212.827,\n      'datetime': datetime.datetime(2025, 4, 10, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 214.515,\n      'datetime': datetime.datetime(2025, 4, 10, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 214.74,\n      'datetime': datetime.datetime(2025, 4, 10, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 205.744,\n      'datetime': datetime.datetime(2025, 4, 10, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 200.317,\n      'datetime': datetime.datetime(2025, 4, 10, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 201.675,\n      'datetime': datetime.datetime(2025, 4, 10, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 191.086,\n      'datetime': datetime.datetime(2025, 4, 10, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 192.773,\n      'datetime': datetime.datetime(2025, 4, 10, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 198.013,\n      'datetime': datetime.datetime(2025, 4, 10, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 193.643,\n      'datetime': datetime.datetime(2025, 4, 10, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 199.533,\n      'datetime': datetime.datetime(2025, 4, 10, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 207.784,\n      'datetime': datetime.datetime(2025, 4, 10, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 226.461,\n      'datetime': datetime.datetime(2025, 4, 10, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 233.957,\n      'datetime': datetime.datetime(2025, 4, 10, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 251.618,\n      'datetime': datetime.datetime(2025, 4, 10, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 256.326,\n      'datetime': datetime.datetime(2025, 4, 10, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 262.612,\n      'datetime': datetime.datetime(2025, 4, 10, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 270.247,\n      'datetime': datetime.datetime(2025, 4, 10, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 262.871,\n      'datetime': datetime.datetime(2025, 4, 10, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 262.423,\n      'datetime': datetime.datetime(2025, 4, 10, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 264.144,\n      'datetime': datetime.datetime(2025, 4, 10, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 262.999,\n      'datetime': datetime.datetime(2025, 4, 10, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 263.996,\n      'datetime': datetime.datetime(2025, 4, 10, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 262.0,\n      'datetime': datetime.datetime(2025, 4, 10, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 254.174,\n      'datetime': datetime.datetime(2025, 4, 10, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 244.784,\n      'datetime': datetime.datetime(2025, 4, 10, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 236.582,\n      'datetime': datetime.datetime(2025, 4, 10, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 227.388,\n      'datetime': datetime.datetime(2025, 4, 10, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 216.373,\n      'datetime': datetime.datetime(2025, 4, 10, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 206.194,\n      'datetime': datetime.datetime(2025, 4, 10, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 196.561,\n      'datetime': datetime.datetime(2025, 4, 10, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 188.396,\n      'datetime': datetime.datetime(2025, 4, 10, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 181.032,\n      'datetime': datetime.datetime(2025, 4, 10, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n    dict({\n      'consumption': 174.95,\n      'datetime': datetime.datetime(2025, 4, 11, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Australia/Darwin')),\n      'source': 'ntesmo.com.au',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'AU-NT',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_NZ.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_price_data\n  list([\n    list([\n      dict({\n        'currency': 'NZD',\n        'datetime': datetime.datetime(2024, 4, 24, 18, 30, tzinfo=datetime.timezone.utc),\n        'price': 79.8623076923077,\n        'source': 'api.em6.co.nz',\n        'sourceType': <EventSourceType.measured: 'measured'>,\n        'zoneKey': 'NZ',\n      }),\n    ]),\n    list([\n      dict({\n        'currency': 'NZD',\n        'datetime': datetime.datetime(2024, 4, 24, 18, 30, tzinfo=datetime.timezone.utc),\n        'price': 79.8623076923077,\n        'source': 'api.em6.co.nz',\n        'sourceType': <EventSourceType.measured: 'measured'>,\n        'zoneKey': 'NZ',\n      }),\n    ]),\n  ])\n# ---\n# name: test_snapshot_production_data\n  list([\n    list([\n      dict({\n        'capacity': dict({\n          'battery storage': 35,\n          'coal': 750,\n          'gas': 1280,\n          'geothermal': 1062,\n          'hydro': 5415,\n          'nuclear': 0,\n          'oil': 156,\n          'solar': 47,\n          'unknown': 168,\n          'wind': 1259,\n        }),\n        'correctedModes': list([\n        ]),\n        'datetime': datetime.datetime(2024, 4, 24, 18, 0, tzinfo=datetime.timezone.utc),\n        'production': dict({\n          'coal': 156,\n          'gas': 252,\n          'geothermal': 964,\n          'hydro': 1644,\n          'nuclear': 0,\n          'oil': 0,\n          'solar': 0,\n          'unknown': 117,\n          'wind': 814,\n        }),\n        'source': 'transpower.co.nz',\n        'sourceType': <EventSourceType.measured: 'measured'>,\n        'storage': dict({\n          'battery': 0,\n        }),\n        'zoneKey': 'NZ',\n      }),\n    ]),\n    list([\n      dict({\n        'capacity': dict({\n          'battery storage': 35,\n          'coal': 750,\n          'gas': 1280,\n          'geothermal': 1062,\n          'hydro': 5415,\n          'nuclear': 0,\n          'oil': 156,\n          'solar': 47,\n          'unknown': 168,\n          'wind': 1259,\n        }),\n        'correctedModes': list([\n        ]),\n        'datetime': datetime.datetime(2024, 4, 24, 18, 0, tzinfo=datetime.timezone.utc),\n        'production': dict({\n          'coal': 156,\n          'gas': 252,\n          'geothermal': 964,\n          'hydro': 1644,\n          'nuclear': 0,\n          'oil': 0,\n          'solar': 0,\n          'unknown': 117,\n          'wind': 814,\n        }),\n        'source': 'transpower.co.nz',\n        'sourceType': <EventSourceType.measured: 'measured'>,\n        'storage': dict({\n          'battery': 0,\n        }),\n        'zoneKey': 'NZ',\n      }),\n    ]),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[AR-BR-S-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[AR-BR-S-BR.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': -0.009936,\n      'sortedZoneKeys': 'AR->BR-S',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[AR-BR-S-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[AR-BR-S-BR_negative_solar.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': -0.009936,\n      'sortedZoneKeys': 'AR->BR-S',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[AR-BR-S-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[AR-BR-S-data.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'netFlow': -942.2021,\n      'sortedZoneKeys': 'AR->BR-S',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-CS-BR-N-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-CS-BR-N-BR.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': -2816.56787,\n      'sortedZoneKeys': 'BR-CS->BR-N',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-CS-BR-N-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-CS-BR-N-BR_negative_solar.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': -2816.56787,\n      'sortedZoneKeys': 'BR-CS->BR-N',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-CS-BR-N-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-CS-BR-N-data.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'netFlow': -3529.24756,\n      'sortedZoneKeys': 'BR-CS->BR-N',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-CS-BR-NE-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-CS-BR-NE-BR.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': 785.116638,\n      'sortedZoneKeys': 'BR-CS->BR-NE',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-CS-BR-NE-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-CS-BR-NE-BR_negative_solar.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': 785.116638,\n      'sortedZoneKeys': 'BR-CS->BR-NE',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-CS-BR-NE-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-CS-BR-NE-data.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'netFlow': -5336.844,\n      'sortedZoneKeys': 'BR-CS->BR-NE',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-CS-BR-S-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-CS-BR-S-BR.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': 203.333054,\n      'sortedZoneKeys': 'BR-CS->BR-S',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-CS-BR-S-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-CS-BR-S-BR_negative_solar.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': 203.333054,\n      'sortedZoneKeys': 'BR-CS->BR-S',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-CS-BR-S-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-CS-BR-S-data.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'netFlow': 4357.55273,\n      'sortedZoneKeys': 'BR-CS->BR-S',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-N-BR-NE-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-N-BR-NE-BR.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': 2967.768,\n      'sortedZoneKeys': 'BR-N->BR-NE',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-N-BR-NE-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-N-BR-NE-BR_negative_solar.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': 2967.768,\n      'sortedZoneKeys': 'BR-N->BR-NE',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-N-BR-NE-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-N-BR-NE-data.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'netFlow': -4413.3833,\n      'sortedZoneKeys': 'BR-N->BR-NE',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-S-PY-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-S-PY-BR.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'BR-S->PY',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-S-PY-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-S-PY-BR_negative_solar.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'BR-S->PY',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-S-PY-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-S-PY-data.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'BR-S->PY',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-S-UY-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-S-UY-BR.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': 14.0,\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-S-UY-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-S-UY-BR_negative_solar.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'netFlow': 14.0,\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_exchange[BR-S-UY-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BR-S-UY-data.json]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'netFlow': -0.9615,\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-CS-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-CS-BR.json]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'production': dict({\n        'hydro': 35888.05363,\n        'nuclear': 1829.29529,\n        'solar': 2.85705,\n        'unknown': 2507.78833,\n        'wind': 4.2,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-CS',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-CS-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-CS-BR_negative_solar.json]\n  list([\n    dict({\n      'correctedModes': list([\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'production': dict({\n        'hydro': 35888.05363,\n        'nuclear': 1829.29529,\n        'solar': 0,\n        'unknown': 2507.78833,\n        'wind': 4.2,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-CS',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-CS-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-CS-data.json]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'hydro': 17603.9198,\n        'nuclear': 2011.05078,\n        'solar': 11259.3008,\n        'unknown': 8401.434,\n        'wind': 165.185547,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-CS',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-N-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-N-BR.json]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'production': dict({\n        'hydro': 9856.75,\n        'nuclear': 0.0,\n        'solar': 0.0,\n        'unknown': 1346.79175,\n        'wind': 156.539352,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-N',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-N-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-N-BR_negative_solar.json]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'production': dict({\n        'hydro': 9856.75,\n        'nuclear': 0.0,\n        'solar': 0.0,\n        'unknown': 1346.79175,\n        'wind': 156.539352,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-N',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-N-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-N-data.json]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'hydro': 2854.34839,\n        'nuclear': 0.0,\n        'solar': 1277.97778,\n        'unknown': 2756.85742,\n        'wind': 324.584167,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-N',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-NE-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-NE-BR.json]\n  list([\n    dict({\n      'correctedModes': list([\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'production': dict({\n        'hydro': 1921.36816,\n        'nuclear': 0.0,\n        'solar': 0,\n        'unknown': 2700.472,\n        'wind': 2837.92188,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-NE',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-NE-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-NE-BR_negative_solar.json]\n  list([\n    dict({\n      'correctedModes': list([\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'production': dict({\n        'hydro': 1921.36816,\n        'nuclear': 0.0,\n        'solar': 0,\n        'unknown': 2700.472,\n        'wind': 2837.92188,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-NE',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-NE-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-NE-data.json]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'hydro': 2081.71338,\n        'nuclear': 0.0,\n        'solar': 7852.72754,\n        'unknown': 153.992935,\n        'wind': 11871.0967,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-NE',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-S-BR.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-S-BR.json]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'production': dict({\n        'hydro': 9273.746,\n        'nuclear': 0.0,\n        'solar': 0.0,\n        'unknown': 855.8522,\n        'wind': 1315.103,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-S',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-S-BR_negative_solar.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-S-BR_negative_solar.json]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2018, 1, 27, 20, 19, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=79200))),\n      'production': dict({\n        'hydro': 9273.746,\n        'nuclear': 0.0,\n        'solar': 0.0,\n        'unknown': 855.8522,\n        'wind': 1315.103,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-S',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_ONS/test_snapshot_fetch_production[BR-S-data.json].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[BR-S-data.json]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 22, 8, 54, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=75600))),\n      'production': dict({\n        'hydro': 8748.055,\n        'nuclear': 0.0,\n        'solar': 1836.314,\n        'unknown': 1583.74609,\n        'wind': 342.625763,\n      }),\n      'source': 'ons.org.br',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'BR-S',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_OPENNEM/test_price[AU-SA].ambr",
    "content": "# serializer version: 1\n# name: test_price[AU-SA]\n  list([\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.27609,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.9388,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.08945,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.42824,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.13545,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.42981,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.38892,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.37482,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.64882,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.63892,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.43,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.32124,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.49598,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.50933,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.14736,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.81343,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.09,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.09564,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.25956,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.96975,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.24331,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.81586,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.95,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.61139,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.44961,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.88964,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 27.76947,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.15833,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.32,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.73842,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.8905,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.74151,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 0.00018,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 9.97618,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 23.73,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 17.39808,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 19.74866,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.62329,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 17.25149,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 19.97849,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 20.03,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 17.20988,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.5862,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.34599,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.93909,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.93689,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.8,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 26.5181,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.93941,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.97947,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.71972,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.60187,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.07,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 26.74894,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.92538,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 24.05591,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 9.59809,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.82915,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 23.65,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 26.72635,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 26.94538,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 23.37569,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 22.18741,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 22.87897,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.15,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 13.47149,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 16.70001,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 18.11506,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 20.90276,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 19.21663,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 17, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 18.29544,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 17.9602,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 27.1076,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 20.12,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.9276,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.5865,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.85655,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.40439,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.78587,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 18, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.72716,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.79805,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.77219,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.97,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 82.19333,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 94.49775,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.29,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.64355,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.19827,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.41,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.18386,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.81194,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.05153,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.69004,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.7,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.04101,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.50103,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.8926,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.96742,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.12253,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.72,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.45874,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.54067,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.81277,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.02511,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.09024,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.71,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.68373,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.93848,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.96626,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.45208,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.64864,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.25,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.8614,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.49661,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.65103,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.24807,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.12404,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.14,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.01733,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.303,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.47554,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.51476,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.06213,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.74,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.07801,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.33681,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.72903,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.85944,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.59071,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 23, 30, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.02099,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.98392,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 25, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.89561,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 0, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.88,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.93929,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.19471,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.60118,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.58084,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.47943,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.14,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.35513,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.23857,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.50781,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.79308,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.47429,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.59,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.53662,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.9006,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.25206,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.61579,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.07004,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.57,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.15904,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.27835,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.57458,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.80689,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.28545,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.68,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.34018,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.49553,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.90418,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.97473,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.97473,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.03,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.90162,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.63727,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.24143,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.63486,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.3486,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.38,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.13887,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.47902,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.03193,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.10507,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.10556,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.85,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.22795,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.09782,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.83573,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.57658,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.30705,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 5, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.02785,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.18918,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.44914,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.6,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.05306,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.65099,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.17928,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.17505,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.45861,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 6, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.59,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.00837,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.47855,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.47655,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.79849,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.41166,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.75,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.77878,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.18659,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 24.78563,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.25645,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.22113,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 27.07,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.45714,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 26.14265,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.65308,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.448,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 15.50246,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.04,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 0.00032,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 8.51221,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 8.47618,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 24.44839,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 24.82375,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 15.11,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.01786,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 24.84295,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.84082,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 24.31466,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.52746,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.94,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.85365,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.85174,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.02955,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.61204,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.87,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.2805,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.42592,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.91178,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.0611,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.23609,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 10, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.44179,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.0168,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.20063,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.74,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.04477,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.83454,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.98334,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.67463,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.86342,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 11, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.09821,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.36243,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.74321,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.33,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.77762,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.03989,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 11, 45, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.45773,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.23067,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.65693,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.50476,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 12, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.6764,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.48944,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.62854,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.74146,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.31,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.43051,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.43394,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.43968,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.20793,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.69868,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.26,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.83447,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.60318,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.57564,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.5788,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.69558,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.66,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.91466,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.17454,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.15993,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.16998,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.17454,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.16,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.11979,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.37494,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.00728,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.74748,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.12647,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.21,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.62656,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.7154,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.40579,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.27896,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.5853,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.94,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.88391,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.20921,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.218,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.38288,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.73,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.66943,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.3278,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.10825,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.43,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.76,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.65519,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.15882,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.11885,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.53886,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.98933,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 17, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.06218,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.67598,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.40319,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.17,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.40107,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.14515,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 17, 45, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.00254,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.90656,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.59374,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.28,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.9715,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.21086,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.00507,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.72243,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 18, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.57917,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.86,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 70.03179,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.79446,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.46551,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.13199,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.47945,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.25,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.52172,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 66.86293,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.98552,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.74849,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.30805,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.57,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.90957,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.98,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.84492,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.91548,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.35,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.89355,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.57156,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.34052,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.334,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.53396,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.59,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.34796,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.18953,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.28844,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.94191,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.22908,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.57043,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.06247,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.86,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.92984,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.88318,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.69,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.03089,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.807,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.72526,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.72003,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.68677,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 23, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.14779,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.9291,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.87018,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 26, 23, 30, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.33,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.43976,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.14324,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.03672,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.35,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.52427,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.59423,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.84585,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.01737,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.33,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.97113,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.30338,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.52099,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.69851,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.96556,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.37,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.17852,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.79717,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.7785,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.19217,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.76666,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.13,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.65072,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.70311,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.52015,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.51682,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.37969,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.57,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.9108,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.90411,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.52207,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.52584,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.67271,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.79,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.77368,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.92214,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.92101,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.18568,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.77017,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.87,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.66578,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.6662,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.66173,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.66196,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.79339,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.77,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.77624,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.05767,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.18441,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.33095,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.46313,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.17,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.60326,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.26561,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.93652,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.93845,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.19741,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 5, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.778,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.79601,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.62747,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.85,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.07527,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.8165,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.92103,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.85547,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.05723,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.94,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.05769,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.30838,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.50356,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.63455,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.27795,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.24,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.94312,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.60626,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.2373,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.22336,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 24.37751,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.81535,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.70551,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.44786,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.87138,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.4011,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.16,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.05618,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.69818,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.58394,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.42542,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.92147,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.42,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.58171,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.02878,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.36767,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.23005,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.39503,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.56,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.50309,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.98516,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.49591,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.60697,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.56346,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.29,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.75325,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.33618,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.47563,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.95642,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.3295,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 10, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.03903,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.05298,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.33207,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.09,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.15928,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.04919,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.36382,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.15054,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.91575,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 11, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.58748,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.53847,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.57533,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.11,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.88454,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.44668,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.81286,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.32999,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.16659,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.68,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.83671,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.98986,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.6109,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.30679,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 66.99943,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.72,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.70982,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.17692,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.7178,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.38898,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.39312,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.04,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.52655,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.70461,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.35632,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.6296,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.7991,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.18,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.59753,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.27387,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.84315,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.40058,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.91927,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.92,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.03981,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.89365,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.88355,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.42183,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.66669,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.38,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 82.47526,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.26866,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 83.25446,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.53462,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 82.47227,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.56,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.90541,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.49389,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 80.84922,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.10999,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.20015,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.17,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 101.76,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 16, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 451.23,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 93.76598,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 91.81525,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 89.39,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 101.01007,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.00007,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 112.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.99983,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.67,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 18, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 124.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 127.6,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 224.88256,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 278.81,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 125.14577,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 300.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 180.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 234.81,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 379.95,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 300.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 249.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 368.81,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 368.81,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 811.84,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 688.77972,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 108.70114,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 107.8621,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 124.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 93.81833,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 202.9,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 124.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 124.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 124.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 82.16104,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.21239,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 99.79,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 124.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 102.17,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.33,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 22, 30, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.71873,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.5283,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.67,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.59897,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.03257,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 66.97,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.9991,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.19728,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.22138,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.79433,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 27, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.1484,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.52,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.56797,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.5931,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.01491,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.40301,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.66057,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.29,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.89778,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.08431,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.89129,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.06,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.79096,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.44417,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.58,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.90529,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.02526,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.52369,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.55047,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.29,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.76837,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.13381,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.75178,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.81209,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.41667,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.53,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.60187,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.47837,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.00221,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.26328,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.90447,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.8,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.9281,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.68935,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.70525,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.69789,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.69313,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.15,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.92206,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.80058,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.20282,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.24,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.76588,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.13509,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.3151,\n      'source': 'opennem.org.au',\n      'sourceType': 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'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.15167,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.27795,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.81,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.26,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.38,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 83.68159,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 85.63561,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.41,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.53984,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.95428,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.78612,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.8,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.9227,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.598,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.1775,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.50192,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.89081,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.76,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.07532,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.05041,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.72806,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.55688,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.85,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.61065,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.60259,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.13035,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.12933,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.81,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.31576,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.84037,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.82732,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.66,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.46483,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.68989,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.35298,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.07895,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.49,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.90661,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.89197,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.11016,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.01339,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.81168,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.21,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.27,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.61,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.86,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.29607,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n     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'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.82017,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.83245,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.70695,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.45505,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.12,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.07734,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.61063,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.73919,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.70053,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.45312,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.04,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.51173,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.48778,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.04068,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.29333,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.13651,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.03,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.7076,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.69823,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.95131,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.31,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.89642,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.63,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.89647,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 80.02447,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.56618,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.05211,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.72,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 80.52989,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 70.8,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.27003,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.90003,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 82.86938,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 84.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 84.9751,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.00005,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 85.83,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.00005,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.8597,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.00005,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.00005,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.64,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.00006,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.33,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.00008,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 85.92007,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.00007,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.49,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.58681,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.58681,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.36,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 82.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.57042,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.92126,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.33,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 83.85,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 70.54,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.92709,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 81.84644,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 81.20748,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.46568,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.84,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.88086,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.81917,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 83.12,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.00009,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 18, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.33,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.95136,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.47472,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 78.61,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 82.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.18498,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.91891,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.58024,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 78.32,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.84379,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.40998,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.04239,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.41617,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 70.89,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.98841,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.78419,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.1924,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.51,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.37328,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.46295,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.97061,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.21944,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.87619,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.55,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.17972,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.12019,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.81206,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.60471,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.19323,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.43,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.49033,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.82711,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.69566,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.73669,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.97367,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.11,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.0737,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.29903,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.41497,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 70.87,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.27,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.51673,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 28, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.46428,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.13,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 83.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.13658,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 91.19,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 95.21995,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 96.79759,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.40293,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.69398,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 78.19,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.88622,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.86605,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.48996,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.56428,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.47835,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.96,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 70.61223,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 81.37803,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 80.71508,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.52451,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.39,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 92.59463,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 91.32385,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.70669,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.397,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 66.17315,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.45,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.10228,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 3, 20, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.69858,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.68401,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.29639,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.55028,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.95523,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 73.41,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 91.51,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 84.15921,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.22128,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.64875,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 76.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.23383,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.21454,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.58744,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 66.14,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.99717,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 66.25981,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.85991,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.28,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.34392,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.66671,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.34,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.84493,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.95878,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.98897,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.98256,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.20347,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.91,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.54434,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.45927,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.71,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.33775,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.01744,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.82732,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.63876,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.7,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.0859,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.86999,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.78,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.93035,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.22973,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.31307,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.09255,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.02052,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.18274,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.26003,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.7745,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.51559,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.96,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.94989,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 9, 10, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.70705,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.75,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.70378,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.14433,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.82732,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.68935,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.63,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.00354,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.56641,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.58091,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.33346,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.3,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 71.57,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 83.9297,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 82.65205,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 81.96557,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 96.72144,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.35,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.54741,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 111.26,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 91.77,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 92.49259,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 94.50211,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.73114,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 97.49087,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 93.47,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 106.69103,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 92.79314,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 99.34926,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 107.31,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 97.4838,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 146.69823,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 108.86,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 148.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 101.67,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.00008,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.16,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 72.59004,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.99987,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 14, 55, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 92.08645,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 104.98584,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 104.91998,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 92.46562,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 95.7,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.99998,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.99998,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 98.71114,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 101.75788,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 95.48484,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 94.20993,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 95.27,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.66667,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 99.45239,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 90.13,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 102.43686,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 120.5313,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 102.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 103.73266,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 105.09092,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 111.45876,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 107.85,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 119.3012,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.00001,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.00001,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.00001,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 135.61009,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 129.13,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 158.07613,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 200.90682,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 299.46,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 246.10735,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 18, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 172.57,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 233.1,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 203.70263,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 156.01001,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 152.29621,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 322.73653,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 316.98069,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 233.45,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.85558,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.99956,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.99989,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 84.81,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 20, 10, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 88.56604,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 96.52,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.1366,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.19653,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.06,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 90.43263,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 90.65253,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 90.31838,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 90.42544,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.88449,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 89.54,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.66687,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.62362,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 85.36,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.55,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.29973,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.50252,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.77842,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.92535,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.05269,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 83.58002,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 81.22006,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.00998,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 29, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 78.89,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 84.2288,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.99998,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.99998,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.37,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 124.08675,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 148.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 129.02686,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 92.53947,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.94,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 98.819,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.60698,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 102.74,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 96.98232,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 133.27001,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 85.90935,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 78.36615,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 92.76,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 78.39557,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.86278,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.24205,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 2, 25, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.6734,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.60329,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.1987,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.93191,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.54,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.44701,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.5692,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.81188,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.65288,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.68,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.39533,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.66946,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.19859,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.50585,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.18375,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.59,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.05762,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.03347,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.51762,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.38013,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 22.72166,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.08,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.20951,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 21.87582,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 21.70063,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 26.68032,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.46559,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.08,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.83398,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.4914,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.52338,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.1725,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.05262,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.85,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.23592,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.97209,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.07716,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.73702,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.75682,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.79,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.91675,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.90699,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.85858,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.39921,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.16173,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.47,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.64231,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.71827,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.45984,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.41464,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.36817,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.34,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.35404,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 7, 10, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 378.85135,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 370.98726,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 130.4146,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.84771,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 205.92,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 299.22273,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 379.95,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 301.68812,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 239.69,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 299.46,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 300.46898,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 264.06814,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 126.91208,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 188.1,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 128.60506,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 302.18361,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 296.88325,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 167.59,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 100.27,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 102.38,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.86586,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 147.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 249.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 256.44861,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 259.09883,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 214.73,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 255.24737,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 119.05173,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 147.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 96.10017,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 143.23,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 144.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 144.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 250.00999,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 144.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 91.45864,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 138.66,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 101.72,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 12, 40, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 109.85,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 87.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 13, 10, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.00001,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 95.59,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 134.00002,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 250.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 231.81877,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 250.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 204.97,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 91.4502,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 94.45518,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.99999,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 148.00001,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 148.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 144.74,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 94.49321,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 278.81853,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 272.87624,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 191.91,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 380.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 380.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 7750.86,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 96.07538,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 95.22405,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 1455.96,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 249.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 97.90532,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 97.40189,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 96.92856,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 115.87,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.55,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.93997,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 98.58,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.55,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 78.78768,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 200.70996,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 129.01,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 250.00999,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 133.84,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.55,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.18,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 138.98999,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 135.98999,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.55,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 18, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 114.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 125.09,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 251.22943,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 102.20688,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 74.31013,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 104.37,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 19, 40, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.06375,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.18,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.75589,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.9192,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.87842,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.00115,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.72477,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.34,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.30669,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.18043,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.48182,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.69532,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.70316,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.95,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.24308,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.18898,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.43708,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.93622,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.09291,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.71607,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.47493,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.47179,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.38,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.45351,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.34422,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.15481,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.29886,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.6,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.16067,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.44593,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.79692,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.58797,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.01612,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.91,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 70.05025,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.4018,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.29192,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.00859,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.17,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.17413,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.52317,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.04049,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.10318,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 30, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.63507,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.19,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.91893,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.0422,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 79.10114,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.39779,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.24,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 86.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n 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dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.42,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.51052,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.90843,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.97044,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.55401,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.70197,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.34,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.96548,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.6311,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.95887,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.81683,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.16316,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.47,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.45516,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.22766,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.69127,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.64186,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.83916,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.66,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.47766,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.87289,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.90213,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.65673,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.3879,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.72,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.43719,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.27901,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.43649,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.7843,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.57732,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.1,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.46967,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.92304,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.12511,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.5985,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.57215,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.3,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.40212,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.21995,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.98749,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.32209,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.74066,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.42,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.36841,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.18935,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.36285,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.47293,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.08407,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.46,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.60031,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.46961,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.5617,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.9621,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.42881,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 6, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.49088,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.63327,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.11524,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.04,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.54153,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.13832,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.85642,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.26266,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.89686,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 7, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.30933,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.62683,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.75519,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.65,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.17925,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.16284,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.53069,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.38834,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.93683,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.44,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.20908,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.83276,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.94811,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.5824,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.40018,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 41.37,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.97599,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.73343,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.80398,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 25.28412,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.18617,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.12,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.30301,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.09611,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.92342,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.43919,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.52973,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.99,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 40.86813,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 37.99602,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.20528,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.19731,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.13203,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.08,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.25458,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.39537,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.9825,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.23502,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.32199,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 11, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 27.88385,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 27.78317,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 27.55864,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 11, 30, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.41732,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.08526,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.34516,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 12, 30, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.46,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.06168,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.24926,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.96191,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.90825,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 27.6739,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.36,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.26492,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.65691,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.82399,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': -32.51874,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 14.68592,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 17.8,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.23958,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.36565,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.78151,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.38292,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 22.87899,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 28.55,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 20.93195,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 19.6097,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 20.01389,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.60543,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 22.60882,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 23.17,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 15.16666,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.16594,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.91463,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 35.1961,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.41785,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.3,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.8992,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.59195,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.12213,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 48.04895,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 50.04258,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.31,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.29312,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 49.15084,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 16, 45, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 66.77378,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 66.22939,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.56749,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.66,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.98734,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.38218,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.54899,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.42593,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.58736,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 18, 0, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 47.44985,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.62105,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.26248,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 18, 30, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.37,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.34421,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.65004,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.42713,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.29405,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.38546,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.05,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.61518,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 66.75124,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.76194,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.86729,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 64.13074,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.15,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.50081,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.94158,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.86768,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.20468,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 51.78274,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.55,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.90652,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.69474,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.25226,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.3134,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.38999,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.2,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.43993,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 54.39939,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.22908,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.64335,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.14186,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.54,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.31407,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.8131,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.16406,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.09211,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.62074,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.02,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.40174,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.97768,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.60728,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 63.35,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.56073,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.58541,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.94581,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.0515,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.67365,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.12,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 67.19353,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 62.43428,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.43005,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.06357,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.83,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.44081,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.89533,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.53054,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.47319,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2019, 12, 31, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 55.262,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.42,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.58,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 148.517,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 77.85052,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.76376,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 75.5762,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 85.95,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.33,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.33,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.77,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.76,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 69.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.42,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.5,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.25,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 68.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.84371,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 65.65,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.01669,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.11461,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.78558,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 61.0,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.32328,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.66,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.4919,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.97251,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.66812,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.68903,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.07398,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 57.42,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.74431,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.78635,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 60.50727,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.4585,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.99933,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.95,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.00738,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.17576,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 58.67595,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 59.03628,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 53.3911,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 56.87,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.90007,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 46.74799,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 52.00225,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.68208,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.80125,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 45.85,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.60422,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.70859,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.21741,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.50278,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.97074,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.27,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.84857,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.41559,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.28613,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.41495,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 44.56478,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.56,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 43.60783,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.97049,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 42.50576,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 34.97241,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.98781,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 38.79,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 32.12925,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 30.94135,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 39.19411,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.33418,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 29.05345,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 31.55,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 0.00028,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 19.94558,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 3e-05,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 0.00033,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 0.00028,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 6.4,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 36.50273,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 26.13077,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 22.47927,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 16.24847,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 12.67393,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 21.7,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 0.00026,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.75579,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 33.5878,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 0.00014,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'currency': 'AUD',\n      'datetime': datetime.datetime(2020, 1, 1, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'price': 0.00034,\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'AU-SA',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_OPENNEM/test_production[AU-NSW].ambr",
    "content": "# serializer version: 1\n# name: test_production[AU-NSW]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 20.0473,\n        'coal': 7271.5768,\n        'gas': 288.99,\n        'hydro': 26.4792,\n        'solar': 0.0532,\n        'wind': 2487.3957,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 10.6189,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 21.2773,\n        'coal': 7257.8559,\n        'gas': 247.87,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2491.0016,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 41.8667,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 17.8339,\n        'coal': 7237.8604,\n        'gas': 231.35,\n        'hydro': 0.0,\n        'solar': 0.0532,\n        'wind': 2493.5302,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 42.2389,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 17.9467,\n        'coal': 7241.2054,\n        'gas': 232.83,\n        'hydro': 0.0,\n        'solar': 0.0532,\n        'wind': 2490.9921,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 41.9955,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 18.0923,\n        'coal': 7243.4516,\n        'gas': 231.42,\n        'hydro': 0.0,\n        'solar': 0.0532,\n        'wind': 2477.4911,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 43.6269,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 17.5281,\n        'coal': 7126.9703,\n        'gas': 231.24,\n        'hydro': 0.0,\n        'solar': 0.0532,\n        'wind': 2477.0357,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 42.1214,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 17.7381,\n        'coal': 7040.8608,\n        'gas': 231.55,\n        'hydro': 0.0,\n        'solar': 0.0532,\n        'wind': 2467.2457,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 48.8177,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 20.4004,\n        'coal': 6920.1559,\n        'gas': 232.57,\n        'hydro': 0.0,\n        'solar': 0.0532,\n        'wind': 2476.8184,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 40.2156,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 22.0266,\n        'coal': 6794.4944,\n        'gas': 231.35,\n        'hydro': 0.0,\n        'solar': 0.0532,\n        'wind': 2449.7739,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 42.8312,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 25.3662,\n        'coal': 6720.1035,\n        'gas': 231.77,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2450.2262,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 52.5282,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 28.4514,\n        'coal': 6659.1167,\n        'gas': 232.83,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2454.4298,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 50.912,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 31.2165,\n        'coal': 6731.3345,\n        'gas': 232.31,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2445.9301,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 63.8778,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 34.7432,\n        'coal': 6804.8464,\n        'gas': 232.07,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2432.0521,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 46.3551,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 35.8163,\n        'coal': 6827.4054,\n        'gas': 167.87,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2413.6221,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 65.8751,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 37.4798,\n        'coal': 6775.4023,\n        'gas': 78.28,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2428.4859,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 63.3254,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 37.7798,\n        'coal': 6841.6144,\n        'gas': 41.56,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2425.0796,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 61.804,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 38.0627,\n        'coal': 6733.8983,\n        'gas': 41.42,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2426.4941,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 60.1893,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 37.6627,\n        'coal': 6719.3959,\n        'gas': 41.65,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2435.5891,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 61.1955,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 38.7827,\n        'coal': 6634.5308,\n        'gas': 41.37,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2428.0651,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 63.5201,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 38.8959,\n        'coal': 6567.7331,\n        'gas': 41.16,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2424.3011,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 63.7531,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 40.012,\n        'coal': 6487.3117,\n        'gas': 41.69,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2414.2415,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 63.9992,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 40.102,\n        'coal': 6339.0666,\n        'gas': 41.38,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2434.4619,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 63.135,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 40.222,\n        'coal': 6179.2497,\n        'gas': 41.5,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2424.901,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 60.7456,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.1974,\n        'coal': 6090.0628,\n        'gas': 41.19,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2412.9573,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 63.0489,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.1574,\n        'coal': 6037.7421,\n        'gas': 41.5,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2419.2998,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 19.1335,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 40.019,\n        'coal': 5928.4135,\n        'gas': 41.16,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2398.063,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 28.7378,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.8104,\n        'coal': 5852.2398,\n        'gas': 41.94,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2406.7297,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 25.4658,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.5132,\n        'coal': 5814.1043,\n        'gas': 41.97,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2400.4029,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 18.5198,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.4632,\n        'coal': 5790.5196,\n        'gas': 41.98,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2380.8953,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 21.4642,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 38.2972,\n        'coal': 5726.578,\n        'gas': 42.09,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2370.3867,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 25.4788,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.0774,\n        'coal': 5726.8962,\n        'gas': 42.23,\n        'hydro': 0.0,\n        'solar': 0.0532,\n        'wind': 2366.1355,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 23.8954,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.1674,\n        'coal': 5533.5331,\n        'gas': 42.08,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2362.103,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 23.81,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.1074,\n        'coal': 5488.4641,\n        'gas': 42.6,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2356.9815,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.7346,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.9133,\n        'coal': 5518.9091,\n        'gas': 42.03,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2316.2278,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 22.8046,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.8547,\n        'coal': 5371.2017,\n        'gas': 42.68,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2337.7166,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 22.0441,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 42.1054,\n        'coal': 5326.9138,\n        'gas': 42.35,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2340.8717,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 7.8863,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 43.0558,\n        'coal': 5347.618,\n        'gas': 42.37,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2351.339,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 20.7291,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 44.2046,\n        'coal': 5227.1564,\n        'gas': 42.53,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2354.2961,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.9137,\n        'hydro': 79.8251,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 41.2179,\n        'coal': 5149.1767,\n        'gas': 42.53,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2330.5196,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 11.2769,\n        'hydro': 80.8475,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 42.5755,\n        'coal': 5081.1093,\n        'gas': 42.33,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2341.2551,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 11.6436,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 43.6444,\n        'coal': 5012.4316,\n        'gas': 42.64,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2370.9084,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 12.7369,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 43.2944,\n        'coal': 4966.4102,\n        'gas': 42.57,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2393.3027,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.3804,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 45.8108,\n        'coal': 4948.368,\n        'gas': 42.75,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2409.9755,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 11.8521,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.3739,\n        'coal': 4858.0103,\n        'gas': 43.1,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2409.827,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 12.1927,\n        'hydro': 80.8475,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.4239,\n        'coal': 4774.3907,\n        'gas': 42.82,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2384.3668,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 22.2335,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.6439,\n        'coal': 4780.4699,\n        'gas': 42.89,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2389.6805,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.3067,\n        'hydro': 80.3363,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 45.4678,\n        'coal': 4742.066,\n        'gas': 42.9,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2391.8596,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 15.5249,\n        'hydro': 80.8475,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 45.2378,\n        'coal': 4766.6513,\n        'gas': 42.86,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2375.6926,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 17.1388,\n        'hydro': 80.5408,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.4239,\n        'coal': 4733.3747,\n        'gas': 42.78,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2371.3896,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.8149,\n        'hydro': 80.4386,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.4439,\n        'coal': 4662.6702,\n        'gas': 43.33,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2351.0952,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 16.9171,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.1357,\n        'coal': 4629.7597,\n        'gas': 43.73,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2370.092,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 12.8444,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 47.9057,\n        'coal': 4643.212,\n        'gas': 43.42,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2341.3634,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.4317,\n        'hydro': 80.4386,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.09,\n        'coal': 4638.5978,\n        'gas': 43.66,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2332.6348,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 11.4829,\n        'hydro': 80.5408,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.9168,\n        'coal': 4563.9628,\n        'gas': 44.01,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2339.1971,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 38.0463,\n        'hydro': 80.8475,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.1457,\n        'coal': 4576.0967,\n        'gas': 43.34,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2319.6625,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 35.0556,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.9197,\n        'coal': 4547.3367,\n        'gas': 43.27,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2326.5627,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 37.3498,\n        'hydro': 80.5408,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.1029,\n        'coal': 4591.8686,\n        'gas': 43.51,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2319.698,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 44.8856,\n        'hydro': 80.8475,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 47.8429,\n        'coal': 4541.3551,\n        'gas': 43.2,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2306.453,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 45.552,\n        'hydro': 80.3363,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.1229,\n        'coal': 4473.1654,\n        'gas': 43.65,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2294.7873,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 42.7995,\n        'hydro': 80.8475,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.7529,\n        'coal': 4392.4751,\n        'gas': 43.78,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2297.2875,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 41.1865,\n        'hydro': 80.4386,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.5047,\n        'coal': 4313.3712,\n        'gas': 43.43,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2286.5334,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 44.7476,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.9974,\n        'coal': 4231.0206,\n        'gas': 43.27,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2276.2807,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 10.0463,\n        'hydro': 80.8475,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.9674,\n        'coal': 4190.1748,\n        'gas': 43.32,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2294.7144,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 24.4785,\n        'hydro': 80.8475,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.4447,\n        'coal': 4146.5949,\n        'gas': 42.44,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2303.1841,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 37.5385,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.6928,\n        'coal': 4182.997,\n        'gas': 42.26,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2299.7111,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 42.1131,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.5628,\n        'coal': 4207.8995,\n        'gas': 42.22,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2299.2595,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 47.5747,\n        'hydro': 80.3363,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.5528,\n        'coal': 4156.8977,\n        'gas': 42.73,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2314.1164,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 40.5409,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.5628,\n        'coal': 4200.0628,\n        'gas': 42.91,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2341.9598,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 35.7283,\n        'hydro': 80.3363,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.8128,\n        'coal': 4197.0106,\n        'gas': 42.64,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2350.8728,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 39.4463,\n        'hydro': 80.4386,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.4138,\n        'coal': 4179.0662,\n        'gas': 42.66,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2323.0947,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 41.6563,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.1782,\n        'coal': 4159.0706,\n        'gas': 42.59,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2327.9273,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 42.7866,\n        'hydro': 80.3363,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.3082,\n        'coal': 4242.1532,\n        'gas': 42.55,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2347.3194,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 82.9132,\n        'hydro': 80.3363,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.0582,\n        'coal': 4273.0616,\n        'gas': 42.96,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2346.4232,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 81.6305,\n        'hydro': 80.5408,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.3782,\n        'coal': 4179.115,\n        'gas': 43.45,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2315.7014,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 85.9426,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.5482,\n        'coal': 4189.54,\n        'gas': 43.52,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2299.4227,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 81.7883,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.5582,\n        'coal': 4174.7935,\n        'gas': 43.17,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2289.2751,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 80.0268,\n        'hydro': 80.4386,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.3582,\n        'coal': 4153.2358,\n        'gas': 42.41,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2292.4539,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 79.6982,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.0982,\n        'coal': 4225.8686,\n        'gas': 42.72,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2287.3388,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 65.8279,\n        'hydro': 80.5408,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.0182,\n        'coal': 4250.7957,\n        'gas': 42.68,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2275.56,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 82.294,\n        'hydro': 80.234,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 50.9524,\n        'coal': 4215.6877,\n        'gas': 42.9,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2246.1151,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 81.6145,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 47.9672,\n        'coal': 4249.8437,\n        'gas': 42.55,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2225.5078,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 72.0497,\n        'hydro': 80.4386,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.9292,\n        'coal': 4228.1392,\n        'gas': 42.85,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2174.6867,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 83.6294,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.8992,\n        'coal': 4236.5377,\n        'gas': 42.79,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2165.6897,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 81.0344,\n        'hydro': 80.5408,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.8392,\n        'coal': 4293.7164,\n        'gas': 42.69,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2141.2252,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 64.8973,\n        'hydro': 80.3363,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.8992,\n        'coal': 4341.3,\n        'gas': 42.78,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2107.3666,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 69.1088,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.1462,\n        'coal': 4333.2435,\n        'gas': 42.74,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2106.9698,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 67.3418,\n        'hydro': 80.4386,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.3462,\n        'coal': 4328.3117,\n        'gas': 42.86,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2093.8647,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 73.2108,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.3462,\n        'coal': 4367.3013,\n        'gas': 42.94,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2096.0049,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 65.3294,\n        'hydro': 80.3363,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 47.6488,\n        'coal': 4410.5149,\n        'gas': 43.13,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2081.0616,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 67.67,\n        'hydro': 80.643,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.4288,\n        'coal': 4453.8749,\n        'gas': 42.61,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2070.5457,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 68.3589,\n        'hydro': 80.5408,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.6988,\n        'coal': 4498.4802,\n        'gas': 42.39,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2074.6826,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 64.0253,\n        'hydro': 80.3363,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.9988,\n        'coal': 4523.3585,\n        'gas': 42.61,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2078.874,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 68.0619,\n        'hydro': 80.4386,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.0988,\n        'coal': 4472.8694,\n        'gas': 42.87,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2049.8039,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 36.8065,\n        'hydro': 80.7453,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.9688,\n        'coal': 4471.2337,\n        'gas': 42.68,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 2025.1167,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.1229,\n        'hydro': 80.1318,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.8388,\n        'coal': 4549.3111,\n        'gas': 42.67,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 1971.0917,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.5878,\n        'hydro': 80.234,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.3688,\n        'coal': 4670.0162,\n        'gas': 42.84,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 1954.3937,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4.6609,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.9588,\n        'coal': 4818.9197,\n        'gas': 43.4,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 1908.5312,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.7834,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.2261,\n        'coal': 4875.1461,\n        'gas': 43.39,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 1907.7598,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 20.5099,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.2661,\n        'coal': 4855.1997,\n        'gas': 43.49,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 1913.1701,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 10.9337,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.0161,\n        'coal': 4881.5182,\n        'gas': 43.64,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 1873.8534,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.1636,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.4661,\n        'coal': 5078.0307,\n        'gas': 42.96,\n        'hydro': 0,\n        'solar': 0.0532,\n        'wind': 1829.8159,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -31.1244,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.7544,\n        'coal': 5265.4614,\n        'gas': 43.42,\n        'hydro': 37.6867,\n        'solar': 0.0532,\n        'wind': 1809.0846,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.1048,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.9134,\n        'coal': 5485.314,\n        'gas': 43.37,\n        'hydro': 48.2991,\n        'solar': 0.0532,\n        'wind': 1789.1013,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.0151,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 50.0034,\n        'coal': 5671.0842,\n        'gas': 43.39,\n        'hydro': 53.417,\n        'solar': 0.0532,\n        'wind': 1774.5076,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.6017,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 50.3434,\n        'coal': 5825.8721,\n        'gas': 43.27,\n        'hydro': 53.8237,\n        'solar': 0.0532,\n        'wind': 1754.9038,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 7.8412,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.5332,\n        'coal': 5977.1933,\n        'gas': 43.49,\n        'hydro': 54.5576,\n        'solar': 0.0532,\n        'wind': 1746.7582,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 7.0715,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.9048,\n        'coal': 6062.1563,\n        'gas': 43.91,\n        'hydro': 53.4616,\n        'solar': 0.0532,\n        'wind': 1730.2509,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 10.1632,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 50.0048,\n        'coal': 6281.4964,\n        'gas': 43.72,\n        'hydro': 43.0174,\n        'solar': 0.0532,\n        'wind': 1728.4698,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.2471,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.6748,\n        'coal': 6434.1115,\n        'gas': 43.75,\n        'hydro': 144.1245,\n        'solar': 0.0532,\n        'wind': 1733.9463,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.6483,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 50.4864,\n        'coal': 6521.7838,\n        'gas': 44.01,\n        'hydro': 151.2545,\n        'solar': 0.0532,\n        'wind': 1708.9785,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.1582,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.1174,\n        'coal': 6595.0273,\n        'gas': 43.81,\n        'hydro': 148.0782,\n        'solar': 0.0532,\n        'wind': 1727.0434,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 5.9261,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.0074,\n        'coal': 6639.0706,\n        'gas': 43.36,\n        'hydro': 142.3631,\n        'solar': 0.0532,\n        'wind': 1702.3533,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 14.6358,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.9274,\n        'coal': 6688.6567,\n        'gas': 43.15,\n        'hydro': 143.5385,\n        'solar': 0.2902,\n        'wind': 1702.8489,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      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'gas': 37.85,\n        'hydro': 0.0314,\n        'solar': 2781.5949,\n        'wind': 1733.7595,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 5.3487,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'hydro',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 35.6877,\n        'coal': 5667.3456,\n        'gas': 37.88,\n        'hydro': 0,\n        'solar': 2981.8519,\n        'wind': 1711.7124,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 9.515,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 35.0472,\n        'coal': 5525.5465,\n        'gas': 37.89,\n        'hydro': 0.0,\n        'solar': 3137.8074,\n        'wind': 1686.6872,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.6172,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 33.3941,\n        'coal': 5449.4225,\n        'gas': 37.89,\n        'hydro': 0.0,\n        'solar': 3178.2065,\n        'wind': 1643.9513,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n  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list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0.4496,\n        'coal': 6253.1027,\n        'gas': 388.27,\n        'hydro': 114.0646,\n        'solar': 946.1933,\n        'wind': 1913.4705,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 24.8635,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 6373.1975,\n        'gas': 452.32,\n        'hydro': 129.5871,\n        'solar': 790.0486,\n        'wind': 1889.4668,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 16.7159,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 6467.0226,\n        'gas': 485.6103,\n        'hydro': 183.0091,\n        'solar': 686.5664,\n        'wind': 1903.1523,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.8116,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 6570.2961,\n        'gas': 536.3947,\n        'hydro': 354.7419,\n        'solar': 543.8899,\n        'wind': 1907.4935,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 21.9321,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 6693.6628,\n        'gas': 571.1734,\n        'hydro': 452.4095,\n        'solar': 424.9291,\n        'wind': 1925.6949,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 14.3572,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0.4611,\n        'coal': 6782.7511,\n        'gas': 615.5245,\n        'hydro': 463.3108,\n        'solar': 308.9783,\n        'wind': 1920.4339,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 19.4535,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 6827.6735,\n        'gas': 609.8406,\n        'hydro': 517.7279,\n        'solar': 191.2163,\n        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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 6966.2745,\n        'gas': 653.4818,\n        'hydro': 612.9177,\n        'solar': 96.5784,\n        'wind': 1909.1219,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 93.0776,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7048.5029,\n        'gas': 651.2085,\n        'hydro': 627.1818,\n        'solar': 62.8869,\n        'wind': 1898.4566,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -6.0491,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7099.504,\n        'gas': 655.5498,\n        'hydro': 648.9787,\n        'solar': 35.075,\n        'wind': 1920.2405,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -105.9618,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7143.9871,\n        'gas': 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'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7249.6529,\n        'gas': 649.4039,\n        'hydro': 637.086,\n        'solar': 0.466,\n        'wind': 1966.3879,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -180.9312,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7295.0883,\n        'gas': 655.5716,\n        'hydro': 933.0109,\n        'solar': 0.3759,\n        'wind': 1993.219,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -132.043,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7328.3404,\n        'gas': 657.4094,\n        'hydro': 1029.6493,\n        'solar': 0.2857,\n        'wind': 1997.5783,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -60.9915,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7365.0843,\n        'gas': 656.4094,\n        'hydro': 1063.5857,\n        'solar': 0.1955,\n        'wind': 1996.9957,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -85.3637,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7372.6287,\n        'gas': 652.2993,\n        'hydro': 954.3403,\n        'solar': 0.1054,\n        'wind': 1988.8919,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -313.7618,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7409.4947,\n        'gas': 656.636,\n        'hydro': 973.5099,\n        'solar': 0.0152,\n        'wind': 1988.098,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -134.4954,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7357.5161,\n        'gas': 650.4894,\n        'hydro': 1003.0453,\n        'solar': 0.0152,\n        'wind': 2003.5789,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -319.9313,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7393.1858,\n        'gas': 653.1692,\n        'hydro': 935.146,\n        'solar': 0.0152,\n        'wind': 2019.7415,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -299.32,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7387.3263,\n        'gas': 653.0372,\n        'hydro': 928.173,\n        'solar': 0.0152,\n        'wind': 2033.5762,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -281.8356,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7410.7886,\n        'gas': 656.2278,\n        'hydro': 939.4622,\n        'solar': 0.0152,\n        'wind': 2018.2117,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -223.4544,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7398.4593,\n        'gas': 651.9082,\n        'hydro': 934.6737,\n        'solar': 0.0152,\n        'wind': 2022.6416,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -270.8223,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7415.403,\n        'gas': 658.3436,\n        'hydro': 954.6937,\n        'solar': 0.0152,\n        'wind': 2037.5405,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -265.7202,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7405.8324,\n        'gas': 652.672,\n        'hydro': 937.5389,\n        'solar': 0.0152,\n        'wind': 2034.1966,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -258.6476,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7407.7612,\n        'gas': 652.2113,\n        'hydro': 953.6613,\n        'solar': 0.0152,\n        'wind': 2027.3509,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -215.0917,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7402.2679,\n        'gas': 651.5711,\n        'hydro': 953.4584,\n        'solar': 0.0152,\n        'wind': 2043.1232,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -260.6564,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7401.0715,\n        'gas': 652.7618,\n        'hydro': 950.276,\n        'solar': 0.0152,\n        'wind': 2005.2768,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -80.8243,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7422.5319,\n        'gas': 657.7351,\n        'hydro': 987.6209,\n        'solar': 0.0152,\n        'wind': 1983.3856,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -86.7937,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7401.4133,\n        'gas': 655.7771,\n        'hydro': 958.3081,\n        'solar': 0.0152,\n        'wind': 1966.5948,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -73.8366,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7413.3033,\n        'gas': 652.2993,\n        'hydro': 957.2414,\n        'solar': 0.0152,\n        'wind': 1957.8995,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -226.7405,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7400.6321,\n        'gas': 652.3552,\n        'hydro': 964.5002,\n        'solar': 0.0152,\n        'wind': 1960.7331,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -49.9065,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7406.0032,\n        'gas': 653.257,\n        'hydro': 965.9018,\n        'solar': 0.0152,\n        'wind': 1953.8184,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -74.2558,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7418.772,\n        'gas': 656.1169,\n        'hydro': 985.12,\n        'solar': 0.0152,\n        'wind': 1969.5941,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -50.1332,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7406.0035,\n        'gas': 655.3728,\n        'hydro': 966.0077,\n        'solar': 0.0152,\n        'wind': 1946.2404,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -46.7036,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7406.101,\n        'gas': 651.9457,\n        'hydro': 966.5788,\n        'solar': 0.0152,\n        'wind': 1939.3038,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -46.4711,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7410.3491,\n        'gas': 654.1658,\n        'hydro': 967.7837,\n        'solar': 0.0152,\n        'wind': 1925.5991,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -89.2574,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7383.5175,\n        'gas': 653.2852,\n        'hydro': 956.537,\n        'solar': 0.0152,\n        'wind': 1932.7237,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -39.4045,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7414.353,\n        'gas': 656.7689,\n        'hydro': 976.2226,\n        'solar': 0.0152,\n        'wind': 1904.26,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -54.7156,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7399.7776,\n        'gas': 653.677,\n        'hydro': 954.5869,\n        'solar': 0.0152,\n        'wind': 1899.4495,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -95.4581,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7419.2604,\n        'gas': 657.5195,\n        'hydro': 967.953,\n        'solar': 0.0152,\n        'wind': 1894.3842,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -71.8653,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7404.7825,\n        'gas': 653.5335,\n        'hydro': 960.1124,\n        'solar': 0.0152,\n        'wind': 1898.1824,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -31.2822,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7402.9759,\n        'gas': 654.7219,\n        'hydro': 954.9912,\n        'solar': 0.0152,\n        'wind': 1884.6183,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.4059,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0.0984,\n        'coal': 7399.6065,\n        'gas': 616.007,\n        'hydro': 968.6162,\n        'solar': 0.0152,\n        'wind': 1879.9849,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -39.2846,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7385.1284,\n        'gas': 660.0916,\n        'hydro': 971.1538,\n        'solar': 0.0152,\n        'wind': 1868.8592,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.1474,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7392.0376,\n        'gas': 660.8603,\n        'hydro': 979.9106,\n        'solar': 0.0152,\n        'wind': 1852.4517,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -19.4944,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0.0684,\n        'coal': 7360.8117,\n        'gas': 607.9682,\n        'hydro': 941.9591,\n        'solar': 0.0152,\n        'wind': 1840.3944,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.6207,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7403.5857,\n        'gas': 564.1763,\n        'hydro': 853.0416,\n        'solar': 0.0152,\n        'wind': 1829.6426,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.549,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7410.202,\n        'gas': 511.7425,\n        'hydro': 933.4463,\n        'solar': 0.0152,\n        'wind': 1835.2322,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.5045,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7416.7696,\n        'gas': 494.03,\n        'hydro': 961.6223,\n        'solar': 0.0152,\n        'wind': 1817.2255,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.7926,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7400.1432,\n        'gas': 488.9,\n        'hydro': 889.2331,\n        'solar': 0.0152,\n        'wind': 1815.905,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.7109,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7398.8495,\n        'gas': 493.46,\n        'hydro': 951.9448,\n        'solar': 0.0152,\n        'wind': 1774.2599,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.2894,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7392.8923,\n        'gas': 486.8,\n        'hydro': 928.9166,\n        'solar': 0.0152,\n        'wind': 1731.7864,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 5.548,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7419.3822,\n        'gas': 494.16,\n        'hydro': 971.1473,\n        'solar': 0.0152,\n        'wind': 1664.6883,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -13.9031,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7391.0613,\n        'gas': 487.72,\n        'hydro': 949.1581,\n        'solar': 0.0152,\n        'wind': 1641.7481,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.892,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n    dict({\n      'correctedModes': list([\n        'biomass',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 0,\n        'coal': 7398.6296,\n        'gas': 488.24,\n        'hydro': 652.7289,\n        'solar': 0.0152,\n        'wind': 1640.1689,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -15.1696,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-NSW',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_OPENNEM/test_production[AU-QLD].ambr",
    "content": "# serializer version: 1\n# name: test_production[AU-QLD]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 68.7,\n        'coal': 5757.7921,\n        'gas': 396.2506,\n        'hydro': 300.6025,\n        'oil': 0.0,\n        'solar': 0.6619,\n        'wind': 1326.0059,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.2903,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 68.3,\n        'coal': 5707.2007,\n        'gas': 394.5688,\n        'hydro': 286.3225,\n        'oil': 0.0,\n        'solar': 0.4619,\n        'wind': 1321.0536,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.8397,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 66.6,\n        'coal': 5643.9034,\n        'gas': 395.4857,\n        'hydro': 287.0375,\n        'oil': 0.0,\n        'solar': 0.4619,\n        'wind': 1329.2355,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.1545,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 70.6,\n        'coal': 5524.3427,\n        'gas': 397.3073,\n        'hydro': 287.115,\n        'oil': 0.0,\n        'solar': 0.4619,\n        'wind': 1358.5795,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.1483,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 71.1,\n        'coal': 5399.1972,\n        'gas': 329.9975,\n        'hydro': 286.08,\n        'oil': 0.0,\n        'solar': 0.4619,\n        'wind': 1360.1322,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.9731,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 71.2,\n        'coal': 5371.4282,\n        'gas': 241.0553,\n        'hydro': 288.2225,\n        'oil': 0.0,\n        'solar': 0.4619,\n        'wind': 1370.9003,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.7674,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 69.5,\n        'coal': 5303.0824,\n        'gas': 207.1699,\n        'hydro': 286.605,\n        'oil': 0.0,\n        'solar': 0.4619,\n        'wind': 1374.4594,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.6637,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 68.9,\n        'coal': 5202.8487,\n        'gas': 200.572,\n        'hydro': 289.34,\n        'oil': 0.0,\n        'solar': 0.4619,\n        'wind': 1354.9609,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.4291,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 68.5,\n        'coal': 5174.2196,\n        'gas': 161.6262,\n        'hydro': 287.815,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1364.8107,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.0448,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 65.4,\n        'coal': 5101.3838,\n        'gas': 121.2984,\n        'hydro': 289.31,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1353.8844,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.7359,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 68.9,\n        'coal': 4974.533,\n        'gas': 82.2348,\n        'hydro': 289.8975,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1360.3776,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.4039,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 65.5,\n        'coal': 4963.2578,\n        'gas': 55.7289,\n        'hydro': 292.2275,\n        'oil': 0.0,\n        'solar': 26.7332,\n        'wind': 1338.6017,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.5733,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.1,\n        'coal': 4918.9446,\n        'gas': 35.6186,\n        'hydro': 290.225,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1339.5594,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -9.8879,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 53.0,\n        'coal': 4968.6982,\n        'gas': 35.6156,\n        'hydro': 289.8,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1330.0388,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.5873,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.6,\n        'coal': 4932.8668,\n        'gas': 35.1936,\n        'hydro': 289.015,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1335.4008,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 21.8706,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.6,\n        'coal': 4939.1821,\n        'gas': 35.8046,\n        'hydro': 289.9875,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1329.0641,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.4015,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.9,\n        'coal': 4906.9616,\n        'gas': 35.8216,\n        'hydro': 287.2525,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1330.0512,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.1335,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.6,\n        'coal': 4925.3666,\n        'gas': 35.4656,\n        'hydro': 122.6775,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1335.0403,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.7915,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.2,\n        'coal': 4896.7154,\n        'gas': 35.7336,\n        'hydro': 121.8225,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1343.0044,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.0099,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.4,\n        'coal': 4922.3799,\n        'gas': 35.9756,\n        'hydro': 121.7475,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1344.085,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -6.5376,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.2,\n        'coal': 4878.4882,\n        'gas': 35.9896,\n        'hydro': 121.7175,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1336.0996,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.8423,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 53.2,\n        'coal': 4873.2592,\n        'gas': 35.8376,\n        'hydro': 121.6425,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1339.9445,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.247,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.2,\n        'coal': 4798.2214,\n        'gas': 36.0906,\n        'hydro': 122.2575,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1359.6897,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.356,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.9,\n        'coal': 4961.0846,\n        'gas': 35.4126,\n        'hydro': 105.545,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1345.382,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.4198,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.9,\n        'coal': 5022.5019,\n        'gas': 35.7636,\n        'hydro': 97.605,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1335.053,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.5136,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.1,\n        'coal': 5021.3514,\n        'gas': 35.9236,\n        'hydro': 96.4825,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1335.1,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.0809,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 50.9,\n        'coal': 4959.6442,\n        'gas': 35.8406,\n        'hydro': 96.8375,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1319.2472,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.3226,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.5,\n        'coal': 4966.8304,\n        'gas': 35.9996,\n        'hydro': 97.6225,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1319.4059,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -23.7206,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.8,\n        'coal': 4961.4267,\n        'gas': 35.5606,\n        'hydro': 97.3425,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1318.8802,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.4159,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 50.5,\n        'coal': 4990.9319,\n        'gas': 35.7796,\n        'hydro': 97.0775,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1309.3278,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -12.9536,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.7,\n        'coal': 4968.3275,\n        'gas': 35.6966,\n        'hydro': 96.4925,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1302.2879,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4.7685,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.6,\n        'coal': 4953.4502,\n        'gas': 36.0396,\n        'hydro': 96.7525,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1303.2459,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -16.5901,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 10, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.3,\n        'coal': 4960.9742,\n        'gas': 35.9636,\n        'hydro': 97.415,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1289.8418,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -29.4694,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.3,\n        'coal': 4948.7712,\n        'gas': 36.1596,\n        'hydro': 97.105,\n        'oil': 0.0,\n        'solar': 0.3259,\n        'wind': 1286.114,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -12.2635,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 47.1,\n        'coal': 4922.4573,\n        'gas': 36.0456,\n        'hydro': 96.0,\n        'oil': 0.0,\n        'solar': 0.4396,\n        'wind': 1276.1834,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 4.766,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n  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0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.2,\n        'coal': 4847.5977,\n        'gas': 36.0416,\n        'hydro': 96.585,\n        'oil': 0.0,\n        'solar': 0.4396,\n        'wind': 1313.7809,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -6.8665,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.1,\n        'coal': 4827.6749,\n        'gas': 36.1866,\n        'hydro': 96.6975,\n        'oil': 0.0,\n        'solar': 0.5396,\n        'wind': 1321.9366,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.724,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.1,\n        'coal': 4817.7965,\n        'gas': 35.9076,\n        'hydro': 96.78,\n        'oil': 0.0,\n        'solar': 0.3332,\n        'wind': 1329.0295,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4.9258,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 54.8,\n        'coal': 4748.4216,\n        'gas': 36.1566,\n        'hydro': 96.68,\n        'oil': 0.0,\n        'solar': 0.3332,\n        'wind': 1350.8138,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.9953,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.4,\n        'coal': 4745.0696,\n        'gas': 35.8296,\n        'hydro': 97.1175,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1357.0459,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0936,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 58.2,\n        'coal': 4735.027,\n        'gas': 36.2116,\n        'hydro': 96.94,\n        'oil': 0.0,\n        'solar': 0.2332,\n        'wind': 1357.4056,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.086,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 58.4,\n        'coal': 4732.5994,\n        'gas': 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    ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 58.2,\n        'coal': 4739.2993,\n        'gas': 36.2106,\n        'hydro': 97.3025,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1399.8209,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4.7469,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 57.3,\n        'coal': 4725.691,\n        'gas': 36.0036,\n        'hydro': 96.4525,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1412.9466,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 4.1015,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 56.2,\n        'coal': 4641.9033,\n        'gas': 35.9206,\n        'hydro': 97.2225,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1427.5405,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -13.242,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n     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'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.7,\n        'coal': 4668.994,\n        'gas': 35.9936,\n        'hydro': 96.285,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1427.175,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.8569,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 54.9,\n        'coal': 4569.284,\n        'gas': 35.8656,\n        'hydro': 96.9225,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1411.9973,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.2346,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 54.2,\n        'coal': 4528.4351,\n        'gas': 36.3606,\n        'hydro': 96.915,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1408.1541,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.799,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 52.0,\n        'coal': 4602.5467,\n        'gas': 36.0836,\n        'hydro': 96.9975,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1394.122,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 15.8041,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 53.1,\n        'coal': 4546.1002,\n        'gas': 35.9586,\n        'hydro': 97.11,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1410.0924,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 12.9443,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 57.3,\n        'coal': 4531.5554,\n        'gas': 36.1066,\n        'hydro': 97.0225,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1428.5022,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 25.5917,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 57.1,\n        'coal': 4616.4984,\n        'gas': 35.7156,\n        'hydro': 96.6675,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1419.5835,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 27.5016,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 56.9,\n        'coal': 4510.465,\n        'gas': 35.9456,\n        'hydro': 96.8375,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1442.7932,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 10.9863,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 56.4,\n        'coal': 4394.9588,\n        'gas': 36.0176,\n        'hydro': 96.59,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1474.0211,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.3356,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.7,\n        'coal': 4395.8958,\n        'gas': 36.0026,\n        'hydro': 96.9225,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1486.9556,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.4374,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 57.4,\n        'coal': 4434.0213,\n        'gas': 36.3636,\n        'hydro': 97.1625,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1478.9037,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.2287,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.6,\n        'coal': 4474.4622,\n        'gas': 35.9976,\n        'hydro': 96.88,\n        'oil': 0.0,\n        'solar': 0.1109,\n        'wind': 1480.85,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.9247,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n        'solar',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.0,\n        'coal': 4534.5205,\n        'gas': 35.7726,\n        'hydro': 96.76,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1484.9911,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.9594,\n        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 }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 56.2,\n        'coal': 4399.5017,\n        'gas': 33.9326,\n        'hydro': 98.0075,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1474.9901,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 44.8997,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 58.9,\n        'coal': 4465.5466,\n        'gas': 33.9506,\n        'hydro': 97.445,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 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  }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 68.5,\n        'coal': 4465.9932,\n        'gas': 34.3006,\n        'hydro': 96.455,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1501.2432,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.1591,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 66.8,\n        'coal': 4509.5586,\n        'gas': 33.9206,\n        'hydro': 96.7225,\n        'oil': 0.0,\n        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'biomass': 60.3,\n        'coal': 4773.6915,\n        'gas': 34.1966,\n        'hydro': 97.76,\n        'oil': 0.0,\n        'solar': 23.8404,\n        'wind': 1442.6328,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -12.4378,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 64.4,\n        'coal': 4835.2738,\n        'gas': 34.2266,\n        'hydro': 97.8325,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1453.328,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -8.2135,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 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'wind': 1451.075,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.6206,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 63.5,\n        'coal': 4884.6148,\n        'gas': 33.5386,\n        'hydro': 97.185,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1432.7369,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.493,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 64.6,\n        'coal': 4919.7749,\n        'gas': 33.9266,\n        'hydro': 97.3325,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1429.0819,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -26.1752,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 63.8,\n        'coal': 5035.3246,\n        'gas': 33.6286,\n        'hydro': 97.07,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1430.5721,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      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'gas': 33.6846,\n        'hydro': 96.9125,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1446.1337,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.2393,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 64.0,\n        'coal': 5094.1403,\n        'gas': 33.4936,\n        'hydro': 96.935,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1444.1692,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -9.0669,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 64.1,\n        'coal': 5093.3975,\n        'gas': 33.6986,\n        'hydro': 100.2525,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1431.0605,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.0738,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 63.5,\n        'coal': 5089.2978,\n        'gas': 34.8506,\n        'hydro': 97.04,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1445.0342,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -10.8372,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 62.3,\n        'coal': 5193.2314,\n        'gas': 35.1516,\n        'hydro': 98.01,\n        'oil': 0.0,\n        'solar': 0.1404,\n        'wind': 1450.5988,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -46.7013,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 63.8,\n        'coal': 5269.6236,\n        'gas': 36.0286,\n        'hydro': 110.96,\n        'oil': 0.0,\n        'solar': 0.1404,\n        'wind': 1435.5309,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -35.623,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 60.9,\n        'coal': 5284.786,\n        'gas': 36.0186,\n        'hydro': 122.485,\n        'oil': 0.0,\n        'solar': 0.1404,\n        'wind': 1418.3254,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -27.4987,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 61.8,\n        'coal': 5319.2856,\n        'gas': 35.1446,\n        'hydro': 297.0675,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1405.7268,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -14.1461,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 61.7,\n        'coal': 5376.9892,\n        'gas': 34.4026,\n        'hydro': 301.19,\n        'oil': 0.0,\n        'solar': 0.0404,\n        'wind': 1416.0409,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.709,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 62.4,\n        'coal': 5294.4621,\n        'gas': 34.5456,\n        'hydro': 299.165,\n        'oil': 0.0,\n        'solar': 5.1352,\n        'wind': 1416.684,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.0,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 64.3,\n        'coal': 5291.9323,\n        'gas': 32.7166,\n        'hydro': 315.16,\n        'oil': 0.0,\n        'solar': 10.2301,\n        'wind': 1412.8213,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -43.051,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 59.5,\n        'coal': 5407.2018,\n        'gas': 33.6956,\n        'hydro': 308.36,\n        'oil': 0.0,\n        'solar': 15.5621,\n        'wind': 1409.9154,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -120.88,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 59.9,\n        'coal': 5528.1283,\n        'gas': 32.4356,\n        'hydro': 307.2375,\n        'oil': 0.0,\n        'solar': 22.051,\n        'wind': 1404.2067,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -142.9513,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 60.6,\n        'coal': 5499.5669,\n        'gas': 34.0096,\n        'hydro': 323.03,\n        'oil': 0.0,\n        'solar': 31.1207,\n        'wind': 1398.9835,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -190.3057,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 62.2,\n        'coal': 5561.9554,\n        'gas': 32.5566,\n        'hydro': 306.54,\n        'oil': 0.0,\n        'solar': 47.0277,\n        'wind': 1382.7271,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -174.1434,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 63.9,\n        'coal': 5594.8208,\n        'gas': 33.6136,\n        'hydro': 306.4825,\n        'oil': 0.0,\n        'solar': 108.2066,\n        'wind': 1365.283,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -167.5523,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 65.3,\n        'coal': 5543.5602,\n        'gas': 33.2486,\n        'hydro': 311.7375,\n        'oil': 0.0,\n        'solar': 193.6961,\n        'wind': 1346.5331,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -204.0111,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 66.4,\n        'coal': 5542.6561,\n        'gas': 32.7196,\n        'hydro': 308.92,\n        'oil': 0.0,\n        'solar': 304.2506,\n        'wind': 1332.0457,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -239.3473,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 67.7,\n        'coal': 5551.5784,\n        'gas': 32.8896,\n        'hydro': 319.9575,\n        'oil': 0.0,\n        'solar': 468.5582,\n        'wind': 1330.9728,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -206.9277,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 66.6,\n        'coal': 5521.239,\n        'gas': 33.3526,\n        'hydro': 304.585,\n        'oil': 0.0,\n        'solar': 642.8708,\n        'wind': 1297.097,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -195.8941,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 68.3,\n        'coal': 5442.6377,\n        'gas': 32.9786,\n        'hydro': 309.5425,\n        'oil': 0.0,\n        'solar': 807.2702,\n        'wind': 1283.5929,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -200.1125,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 75.0,\n        'coal': 5400.3958,\n        'gas': 33.5606,\n        'hydro': 307.9475,\n        'oil': 0.0,\n        'solar': 1043.6117,\n        'wind': 1269.8509,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -162.8317,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 73.1,\n        'coal': 5389.1515,\n        'gas': 33.4036,\n        'hydro': 300.1875,\n        'oil': 0.0,\n        'solar': 1253.1923,\n        'wind': 1234.6911,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -162.5142,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 71.2,\n        'coal': 5308.5332,\n        'gas': 33.5336,\n        'hydro': 300.6075,\n        'oil': 0.0,\n        'solar': 1508.4003,\n        'wind': 1209.6094,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -159.7419,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 71.3,\n        'coal': 5254.9194,\n        'gas': 31.9406,\n        'hydro': 285.6075,\n        'oil': 0.0,\n        'solar': 1756.5092,\n        'wind': 1172.2446,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -151.5462,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 70.9,\n        'coal': 5097.6416,\n        'gas': 33.2726,\n        'hydro': 121.6775,\n        'oil': 0.0,\n        'solar': 2006.2411,\n        'wind': 1141.5484,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -148.7059,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 65.9,\n        'coal': 5011.2234,\n        'gas': 32.7596,\n        'hydro': 121.335,\n        'oil': 0.0,\n        'solar': 2241.1236,\n        'wind': 977.3211,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -143.8528,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.9,\n        'coal': 4866.8758,\n        'gas': 32.2946,\n        'hydro': 122.46,\n        'oil': 0.0,\n        'solar': 2470.8654,\n        'wind': 1077.8838,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n  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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.4,\n        'coal': 4203.5402,\n        'gas': 32.9926,\n        'hydro': 79.5075,\n        'oil': 0.0,\n        'solar': 3785.2656,\n        'wind': 846.8631,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 15.759,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.9,\n        'coal': 4219.0826,\n        'gas': 31.6776,\n        'hydro': 71.7225,\n        'oil': 0.0,\n        'solar': 3901.8377,\n        'wind': 823.0087,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 26.3,\n        'coal': 3901.7673,\n        'gas': 31.7016,\n        'hydro': 71.6,\n        'oil': 0.0,\n        'solar': 4675.841,\n        'wind': 686.735,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.8321,\n        'hydro': 491.94,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 28.1,\n        'coal': 3852.8391,\n        'gas': 33.0246,\n        'hydro': 71.8,\n        'oil': 0.0,\n        'solar': 4795.2726,\n        'wind': 661.9988,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4.7911,\n        'hydro': 490.76,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 30.1,\n        'coal': 3767.3691,\n        'gas': 31.1596,\n        'hydro': 71.1975,\n        'oil': 0.0,\n        'solar': 4892.5432,\n        'wind': 646.2107,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 5.0249,\n        'hydro': 492.06,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 31.0,\n        'coal': 3768.4083,\n    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'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 30.5,\n        'coal': 3782.2236,\n        'gas': 30.7406,\n        'hydro': 71.765,\n        'oil': 0.0,\n        'solar': 4868.723,\n        'wind': 662.0648,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -5.4864,\n        'hydro': 492.08,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 30.5,\n        'coal': 3775.0371,\n        'gas': 34.1126,\n        'hydro': 71.5425,\n        'oil': 0.0,\n        'solar': 4932.3423,\n        'wind': 660.2724,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4.1831,\n        'hydro': 491.96,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 31.1,\n        'coal': 3758.332,\n        'gas': 29.9116,\n        'hydro': 70.76,\n        'oil': 0.0,\n        'solar': 4962.6816,\n        'wind': 667.831,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 137.5079,\n        'hydro': 491.27,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 29.6,\n        'coal': 3781.7782,\n        'gas': 28.3236,\n        'hydro': 71.84,\n        'oil': 0.0,\n        'solar': 5075.0508,\n        'wind': 675.2298,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 125.1473,\n        'hydro': 491.81,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 10, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 28.8,\n        'coal': 3762.3554,\n        'gas': 28.3056,\n        'hydro': 67.5475,\n        'oil': 0.0,\n        'solar': 5084.248,\n        'wind': 655.4865,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n  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3779.7363,\n        'gas': 32.0516,\n        'hydro': 71.52,\n        'oil': 0.0,\n        'solar': 5239.4513,\n        'wind': 671.8684,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 151.4101,\n        'hydro': 491.98,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 27.2,\n        'coal': 3764.0639,\n        'gas': 29.1446,\n        'hydro': 62.56,\n        'oil': 0.0,\n        'solar': 5158.6994,\n        'wind': 670.2002,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 153.9451,\n        'hydro': 492.41,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 29.0,\n        'coal': 3784.1373,\n        'gas': 27.1066,\n        'hydro': 14.5075,\n        'oil': 0.0,\n        'solar': 5199.6344,\n        'wind': 629.1445,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 179.3649,\n        'hydro': 490.15,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 28.5,\n        'coal': 3771.8732,\n        'gas': 27.9846,\n        'hydro': 71.98,\n        'oil': 0.0,\n        'solar': 5284.738,\n        'wind': 625.0092,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 156.5239,\n        'hydro': 491.12,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 29.5,\n        'coal': 3753.8462,\n        'gas': 28.7996,\n        'hydro': 69.335,\n        'oil': 0.0,\n        'solar': 5364.9049,\n        'wind': 632.4464,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 183.6872,\n        'hydro': 492.11,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 31.1,\n        'coal': 3823.4093,\n        'gas': 29.7516,\n        'hydro': 72.07,\n        'oil': 0.0,\n        'solar': 5320.6176,\n        'wind': 642.5827,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 146.0981,\n        'hydro': 489.22,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 34.5,\n        'coal': 3799.2815,\n        'gas': 30.4736,\n        'hydro': 71.6125,\n        'oil': 0.0,\n        'solar': 5344.5522,\n        'wind': 606.3854,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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}),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 11, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 32.8,\n        'coal': 3889.0747,\n        'gas': 29.2306,\n        'hydro': 4.8175,\n        'oil': 0.0,\n        'solar': 5118.4561,\n        'wind': 619.3746,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 183.9294,\n        'hydro': 489.87,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 11, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 29.1,\n        'coal': 3935.1347,\n        'gas': 27.4946,\n        'hydro': 4.715,\n        'oil': 0.0,\n        'solar': 5187.2581,\n        'wind': 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dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 19.4,\n        'coal': 3956.5176,\n        'gas': 29.1936,\n        'hydro': 4.445,\n        'oil': 0.0,\n        'solar': 5330.6149,\n        'wind': 557.0686,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 247.9864,\n        'hydro': 490.44,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 19.9,\n        'coal': 3990.8481,\n        'gas': 30.0076,\n        'hydro': 4.315,\n        'oil': 0.0,\n        'solar': 5215.4711,\n        'wind': 571.6994,\n 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 19.2,\n        'coal': 4011.0986,\n        'gas': 28.5266,\n        'hydro': 4.44,\n        'oil': 0.0,\n        'solar': 5146.4011,\n        'wind': 606.2465,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 187.7707,\n        'hydro': 490.51,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 19.7,\n        'coal': 4036.8966,\n        'gas': 27.7276,\n        'hydro': 4.3875,\n        'oil': 0.0,\n        'solar': 5096.1915,\n        'wind': 609.3092,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n   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dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 18.5,\n        'coal': 4023.2358,\n        'gas': 38.7446,\n        'hydro': 4.6,\n        'oil': 0.0,\n        'solar': 5144.9716,\n        'wind': 679.2993,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 348.7108,\n        'hydro': 488.75,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 16.8,\n        'coal': 4021.3228,\n        'gas': 41.4086,\n        'hydro': 4.81,\n        'oil': 0.0,\n        'solar': 5048.4822,\n        'wind': 678.9623,\n    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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 18.1,\n        'coal': 4005.3887,\n        'gas': 58.7586,\n        'hydro': 4.425,\n        'oil': 0.0,\n        'solar': 4671.8715,\n        'wind': 673.9574,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 290.9984,\n        'hydro': 488.87,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 16.4,\n        'coal': 4004.5745,\n        'gas': 75.2496,\n        'hydro': 4.6975,\n        'oil': 0.0,\n        'solar': 4626.7659,\n        'wind': 665.5938,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n 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dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 19.8,\n        'coal': 3998.8777,\n        'gas': 72.0416,\n        'hydro': 4.5725,\n        'oil': 0.0,\n        'solar': 4322.2924,\n        'wind': 689.5849,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 98.0925,\n        'hydro': 487.86,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 20.7,\n        'coal': 4004.3529,\n        'gas': 73.3886,\n        'hydro': 4.6125,\n        'oil': 0.0,\n        'solar': 4247.4278,\n        'wind': 658.0422,\n 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 19.2,\n        'coal': 3949.6319,\n        'gas': 99.8486,\n        'hydro': 4.6275,\n        'oil': 0.0,\n        'solar': 4346.4655,\n        'wind': 621.9339,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 97.9403,\n        'hydro': 487.41,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 19.8,\n        'coal': 3919.5309,\n        'gas': 97.7186,\n        'hydro': 4.52,\n        'oil': 0.0,\n        'solar': 4378.8901,\n        'wind': 630.3626,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n   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'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 21.0,\n        'coal': 3839.7847,\n        'gas': 97.6346,\n        'hydro': 4.075,\n        'oil': 0.0,\n        'solar': 4286.7844,\n        'wind': 638.9756,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 68.8134,\n        'hydro': 486.77,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 20.3,\n        'coal': 3863.9309,\n        'gas': 98.0816,\n        'hydro': 4.7475,\n        'oil': 0.0,\n        'solar': 4304.5003,\n        'wind': 639.4722,\n      }),\n    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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 18.1,\n        'coal': 3841.1715,\n        'gas': 97.9096,\n        'hydro': 4.7425,\n        'oil': 0.0,\n        'solar': 4405.4941,\n        'wind': 645.4932,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 56.8975,\n        'hydro': 486.45,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 20.2,\n        'coal': 3900.7119,\n        'gas': 98.6186,\n        'hydro': 4.8,\n        'oil': 0.0,\n        'solar': 4324.6291,\n        'wind': 636.6353,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 40.9111,\n        'hydro': 482.88,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 17.2,\n        'coal': 3845.3452,\n        'gas': 122.2907,\n        'hydro': 4.53,\n        'oil': 0.0,\n        'solar': 4395.9161,\n        'wind': 621.8836,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 27.1324,\n        'hydro': 487.81,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 18.3,\n        'coal': 3800.3521,\n  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'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 20.7,\n        'coal': 3826.3233,\n        'gas': 135.5921,\n        'hydro': 4.92,\n        'oil': 0.0,\n        'solar': 4469.2361,\n        'wind': 613.1435,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.0214,\n        'hydro': 485.82,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 23.0,\n        'coal': 3809.4209,\n        'gas': 137.9902,\n        'hydro': 4.25,\n        'oil': 0.0,\n        'solar': 4302.9357,\n        'wind': 625.4403,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 37.3737,\n        'hydro': 486.9,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 23.9,\n        'coal': 3827.8877,\n        'gas': 140.0397,\n        'hydro': 4.2,\n        'oil': 0.0,\n        'solar': 4177.6033,\n        'wind': 610.0714,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.917,\n        'hydro': 485.98,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 24.6,\n        'coal': 3771.8973,\n        'gas': 172.1318,\n        'hydro': 3.92,\n        'oil': 0.0,\n        'solar': 4056.7892,\n        'wind': 645.9828,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 56.9702,\n        'hydro': 487.89,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 24.3,\n        'coal': 3846.6664,\n        'gas': 187.028,\n        'hydro': 9.8225,\n        'oil': 0.0,\n        'solar': 4016.8468,\n        'wind': 631.8868,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n  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'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 33.1,\n        'coal': 3841.8001,\n        'gas': 237.9435,\n        'hydro': 80.4175,\n        'oil': 0.0,\n        'solar': 4079.3002,\n        'wind': 582.8595,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -25.6554,\n        'hydro': 483.89,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 36.4,\n        'coal': 3832.5175,\n        'gas': 240.6257,\n        'hydro': 86.965,\n        'oil': 0.0,\n        'solar': 4107.6752,\n        'wind': 581.0699,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.5797,\n        'hydro': 486.19,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 37.3,\n        'coal': 3815.4547,\n        'gas': 241.4222,\n        'hydro': 92.88,\n        'oil': 0.0,\n        'solar': 4158.8243,\n        'wind': 592.0595,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 11.7952,\n        'hydro': 485.26,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 37.2,\n        'coal': 3856.1926,\n        'gas': 237.129,\n        'hydro': 97.3425,\n        'oil': 0.0,\n        'solar': 4191.5864,\n        'wind': 581.3934,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.1858,\n        'hydro': 485.75,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 39.7,\n        'coal': 3822.2173,\n        'gas': 265.5839,\n        'hydro': 96.56,\n        'oil': 0.0,\n        'solar': 4236.8647,\n        'wind': 556.8981,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.9339,\n        'hydro': 485.58,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 40.3,\n        'coal': 3834.5592,\n        'gas': 319.6621,\n        'hydro': 97.0625,\n        'oil': 0.0,\n        'solar': 4133.8574,\n        'wind': 539.9869,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.3276,\n        'hydro': 484.73,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 41.4,\n        'coal': 3909.3446,\n        'gas': 316.9542,\n        'hydro': 97.0225,\n        'oil': 0.0,\n        'solar': 3991.5756,\n        'wind': 544.3779,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.1052,\n        'hydro': 483.99,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 45.0,\n        'coal': 3860.6206,\n        'gas': 318.8446,\n        'hydro': 96.63,\n        'oil': 0.0,\n        'solar': 3826.3674,\n        'wind': 511.8877,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.2133,\n        'hydro': 243.01,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.3,\n        'coal': 3813.9009,\n        'gas': 316.9774,\n        'hydro': 95.6125,\n        'oil': 0.0,\n        'solar': 3621.3782,\n        'wind': 512.1967,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.5593,\n        'hydro': 243.3,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.5,\n        'coal': 3882.7093,\n        'gas': 322.4332,\n        'hydro': 96.9325,\n        'oil': 0.0,\n        'solar': 3354.9683,\n        'wind': 526.235,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.349,\n        'hydro': 242.48,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.1,\n        'coal': 4047.3847,\n        'gas': 321.3461,\n        'hydro': 110.665,\n        'oil': 0.0,\n        'solar': 3239.3785,\n        'wind': 505.1433,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.8624,\n        'hydro': 243.63,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.7,\n        'coal': 4164.1789,\n        'gas': 320.2854,\n        'hydro': 111.1875,\n        'oil': 0.0,\n        'solar': 3025.6699,\n        'wind': 516.6474,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -5.5475,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.2,\n        'coal': 4361.6361,\n        'gas': 334.8704,\n        'hydro': 111.875,\n        'oil': 0.0,\n        'solar': 2841.5503,\n        'wind': 508.3917,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -8.9153,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 44.0,\n        'coal': 4566.1622,\n        'gas': 388.6743,\n        'hydro': 111.2675,\n        'oil': 0.0,\n        'solar': 2645.5415,\n        'wind': 490.6518,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 9.5084,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 42.1,\n        'coal': 4754.7844,\n        'gas': 435.0611,\n        'hydro': 118.9825,\n        'oil': 0.0,\n        'solar': 2426.4083,\n        'wind': 517.4887,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.4406,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 43.4,\n        'coal': 4956.1881,\n        'gas': 457.328,\n        'hydro': 136.395,\n        'oil': 0.0,\n        'solar': 2206.0612,\n        'wind': 523.549,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 38.7138,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 43.8,\n        'coal': 5046.5246,\n        'gas': 472.346,\n        'hydro': 136.545,\n        'oil': 0.0,\n        'solar': 1979.3044,\n        'wind': 507.9247,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.0749,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.3,\n        'coal': 5190.235,\n        'gas': 474.991,\n        'hydro': 136.915,\n        'oil': 0.0,\n        'solar': 1773.3787,\n        'wind': 497.1348,\n 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 46.0,\n        'coal': 5534.5882,\n        'gas': 495.0648,\n        'hydro': 300.05,\n        'oil': 0.0,\n        'solar': 1347.8235,\n        'wind': 446.6841,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -34.025,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 43.6,\n        'coal': 5732.7641,\n        'gas': 504.5355,\n        'hydro': 305.895,\n        'oil': 0.0,\n        'solar': 1129.0387,\n        'wind': 456.4231,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n 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dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 48.2,\n        'coal': 5959.7547,\n        'gas': 537.4674,\n        'hydro': 676.6725,\n        'oil': 0.0,\n        'solar': 402.1691,\n        'wind': 360.3537,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -34.5664,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 47.6,\n        'coal': 6010.8007,\n        'gas': 548.7323,\n        'hydro': 658.6925,\n        'oil': 0.0,\n        'solar': 318.8372,\n        'wind': 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dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 49.8,\n        'coal': 6160.1416,\n        'gas': 669.8858,\n        'hydro': 681.1625,\n        'oil': 0.0,\n        'solar': 19.0257,\n        'wind': 383.1673,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -310.3008,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 54.4,\n        'coal': 6182.836,\n        'gas': 670.1858,\n        'hydro': 667.8825,\n        'oil': 0.0,\n        'solar': 12.805,\n        'wind': 392.3419,\n 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 53.3,\n        'coal': 6113.1288,\n        'gas': 775.8969,\n        'hydro': 477.32,\n        'oil': 0.0,\n        'solar': 0.5061,\n        'wind': 530.2582,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -247.1723,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 51.4,\n        'coal': 6112.2555,\n        'gas': 779.1979,\n        'hydro': 477.7925,\n        'oil': 0.0,\n        'solar': 0.5061,\n        'wind': 560.5926,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    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    'gas': 841.9849,\n        'hydro': 473.8875,\n        'oil': 0.0,\n        'solar': 0.5061,\n        'wind': 623.3111,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -226.2038,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.0,\n        'coal': 6108.0372,\n        'gas': 835.4176,\n        'hydro': 486.2075,\n        'oil': 0.0,\n        'solar': 0.5061,\n        'wind': 654.8429,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -159.168,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 55.4,\n        'coal': 6123.9227,\n        'gas': 807.4291,\n        'hydro': 472.075,\n        'oil': 0.0,\n        'solar': 0.5838,\n        'wind': 675.3811,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -113.8443,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 54.7,\n        'coal': 6114.3209,\n        'gas': 805.8957,\n        'hydro': 471.4625,\n        'oil': 0.0,\n        'solar': 0.5838,\n        'wind': 860.8427,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -108.5962,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 57.8,\n        'coal': 5996.492,\n        'gas': 776.5549,\n        'hydro': 471.915,\n        'oil': 0.0,\n        'solar': 0.5838,\n        'wind': 859.4893,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -188.4376,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 59.1,\n        'coal': 6092.5857,\n        'gas': 794.7986,\n        'hydro': 478.57,\n        'oil': 0.0,\n        'solar': 0.5838,\n        'wind': 868.5835,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -208.7006,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 59.2,\n        'coal': 6099.0559,\n        'gas': 779.1507,\n        'hydro': 471.825,\n        'oil': 0.0,\n        'solar': 0.5838,\n        'wind': 884.9927,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -209.0136,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 58.4,\n        'coal': 6053.8753,\n        'gas': 778.3203,\n        'hydro': 483.3725,\n        'oil': 0.0,\n        'solar': 0.5838,\n        'wind': 896.9679,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -208.0771,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 59.0,\n        'coal': 6015.4211,\n        'gas': 778.4556,\n        'hydro': 480.225,\n        'oil': 0.0,\n        'solar': 0.5838,\n        'wind': 895.8201,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -174.9425,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 58.1,\n        'coal': 6029.018,\n        'gas': 801.5931,\n        'hydro': 479.0625,\n        'oil': 0.0,\n        'solar': 0.5838,\n        'wind': 888.8759,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -96.605,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 58.4,\n        'coal': 5989.1359,\n        'gas': 781.1428,\n        'hydro': 483.97,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 894.0722,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -101.3094,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 59.1,\n        'coal': 5944.9191,\n        'gas': 779.314,\n        'hydro': 474.5975,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 913.8783,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -97.5907,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 56.0,\n        'coal': 5939.4696,\n        'gas': 782.6974,\n        'hydro': 476.8275,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 935.185,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -100.216,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 58.1,\n        'coal': 5957.2623,\n        'gas': 775.3295,\n        'hydro': 474.9675,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 958.2233,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -50.2498,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 60.9,\n        'coal': 5962.7972,\n        'gas': 776.361,\n        'hydro': 474.1175,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 973.5452,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -49.8502,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 60.6,\n        'coal': 5944.3127,\n        'gas': 784.6043,\n        'hydro': 476.175,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 983.3281,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -49.3719,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 60.0,\n        'coal': 5935.6921,\n        'gas': 780.2169,\n        'hydro': 503.285,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1008.9062,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -49.0926,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 60.0,\n        'coal': 5894.7111,\n        'gas': 753.3501,\n        'hydro': 481.4775,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1017.991,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.3102,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 59.8,\n        'coal': 5902.0929,\n        'gas': 776.9183,\n        'hydro': 487.5925,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1034.1818,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -43.8187,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 60.1,\n        'coal': 5879.4775,\n        'gas': 791.5596,\n        'hydro': 503.74,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1043.407,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.4872,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 59.5,\n        'coal': 5862.6545,\n        'gas': 717.38,\n        'hydro': 479.125,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1065.5216,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0259,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 59.1,\n        'coal': 5902.5748,\n        'gas': 732.8841,\n        'hydro': 319.44,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1045.3571,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.7651,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 61.1,\n        'coal': 5904.5843,\n        'gas': 773.4174,\n        'hydro': 316.7775,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1030.6015,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.4602,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 62.9,\n        'coal': 5908.6251,\n        'gas': 711.4701,\n        'hydro': 312.68,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1053.0754,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.269,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 62.7,\n        'coal': 5892.4941,\n        'gas': 693.727,\n        'hydro': 306.51,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1067.3568,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4.1869,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 62.2,\n        'coal': 5909.0957,\n        'gas': 683.3124,\n        'hydro': 312.1375,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1054.3555,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -6.6587,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 62.7,\n        'coal': 5919.6075,\n        'gas': 710.5691,\n        'hydro': 309.3,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1037.2864,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -47.0046,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 11, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'biomass': 62.6,\n        'coal': 5878.3962,\n        'gas': 651.2619,\n        'hydro': 474.13,\n        'oil': 0.0,\n        'solar': 0.3838,\n        'wind': 1038.9155,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.0434,\n        'hydro': 0.0,\n      }),\n      'zoneKey': 'AU-QLD',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_OPENNEM/test_production[AU-SA].ambr",
    "content": "# serializer version: 1\n# name: test_production[AU-SA]\n  list([\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 253.7443,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1422.545,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.5335,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 254.0265,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1408.7917,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -64.452,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.0932,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1385.5851,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.3273,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 254.5965,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1412.228,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.5092,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 253.5154,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1397.5955,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -14.5306,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 255.8065,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1321.8516,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -9.3291,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.3843,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1296.5468,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 96.4273,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 252.3354,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1280.351,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 158.9846,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 252.3654,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1267.9622,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 56.4318,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.8143,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1247.2572,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 95.8367,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 253.1354,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1259.1316,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 128.4754,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.4143,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1283.931,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 143.9545,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.6443,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1328.6755,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 159.2159,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 254.9043,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1345.1468,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 61.6008,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 253.2565,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1340.1685,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 193.6811,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 253.2965,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1341.9187,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 46.4055,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 253.0776,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1354.9598,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 208.6526,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 256.1765,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1361.6111,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 27.1695,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.9854,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1364.6444,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 163.117,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 253.1565,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1356.1177,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 205.9572,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 252.8654,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1293.3632,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 232.8856,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 254.2076,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1253.6981,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 94.0323,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 254.6287,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1263.2113,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 141.5223,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 254.2565,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1255.5136,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 17.5831,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 252.4654,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1249.0813,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 107.4448,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 253.0565,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1242.1754,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -22.5992,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 252.1354,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1232.6319,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 29.9294,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.2443,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1213.9908,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 14.8711,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.1143,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1201.0397,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 15.8022,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 255.7354,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1195.4965,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -25.3865,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 254.4854,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1187.5913,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -20.0596,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 252.8365,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1194.7307,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.548,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.6943,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1223.6882,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.6019,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 255.1276,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1236.3532,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -10.4791,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 255.9254,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1230.0039,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -21.0307,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 255.4654,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1203.5723,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 26.2747,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.8143,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1175.4334,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.0015,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 252.9543,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1117.6085,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.1194,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.6443,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1137.4112,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.2513,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 252.9565,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1129.9126,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.0896,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 256.7565,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1110.6366,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 21.7171,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 273.1354,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1111.7089,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -23.4412,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 273.8565,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1066.5947,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -31.7912,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 304.9751,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1050.3958,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 41.3244,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 280.8686,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1043.4856,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -43.5303,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 272.7443,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1032.6822,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -32.449,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 275.7198,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1020.9544,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -29.8962,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 272.4354,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1032.8567,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -25.944,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 271.3065,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1063.4204,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -31.217,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 273.4554,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1109.2284,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -8.418,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 273.9354,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1057.7247,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.7161,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 279.3053,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1045.7514,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 4.3856,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 305.7928,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1061.9096,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.8486,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 304.7673,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1055.466,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -74.2413,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 305.0573,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1047.3211,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -46.9507,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 317.8439,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 1029.4565,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.2452,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 341.9536,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1027.5544,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -21.9023,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 304.4695,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1043.781,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': 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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.016,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 374.8817,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1022.1096,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -61.1693,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 431.2595,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1038.3272,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -20.3671,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 488.0013,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1048.6876,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -42.8426,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 506.0589,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1050.7601,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -30.1437,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 538.2367,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1030.1606,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -95.1635,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 548.7756,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1019.9056,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -108.0137,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 603.3578,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1018.7423,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -96.6252,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 616.4567,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 1018.6719,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -94.5052,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 659.2178,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 996.6017,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -91.5025,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 699.5253,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 983.8461,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -64.4725,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 680.7289,\n        'oil': 0,\n        'solar': 0.3632,\n        'wind': 971.7712,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -100.7836,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 704.8989,\n        'oil': 0,\n        'solar': 0.7263,\n        'wind': 946.0172,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -189.0043,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 746.3997,\n        'oil': 0.0,\n        'solar': 1.1095,\n        'wind': 927.4729,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -116.7811,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 740.1067,\n        'oil': 0.0,\n        'solar': 1.8607,\n        'wind': 913.2742,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -191.1962,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 740.6878,\n        'oil': 0.0,\n        'solar': 2.9628,\n        'wind': 933.1897,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -156.1074,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 798.1083,\n        'oil': 0.0,\n        'solar': 5.7913,\n        'wind': 935.948,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -31.6813,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 766.7608,\n        'oil': 0.0,\n        'solar': 16.932,\n        'wind': 937.2266,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -43.4744,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 764.8999,\n        'oil': 0.0,\n        'solar': 29.5418,\n        'wind': 963.3272,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -54.4867,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 734.7789,\n        'oil': 0.0,\n        'solar': 45.2356,\n        'wind': 975.6486,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -115.0161,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 769.097,\n        'oil': 0.0,\n        'solar': 67.0083,\n        'wind': 957.8507,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -98.2691,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 783.5772,\n        'oil': 0.0,\n        'solar': 85.6209,\n        'wind': 940.9974,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -30.4591,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 794.3546,\n        'oil': 0.0,\n        'solar': 107.6851,\n        'wind': 915.4033,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -27.833,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 761.5666,\n        'oil': 0.0,\n        'solar': 141.9015,\n        'wind': 895.7161,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -39.1525,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 768.5118,\n        'oil': 0.0,\n        'solar': 179.7343,\n        'wind': 859.1385,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -53.2358,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 757.3435,\n        'oil': 0,\n        'solar': 223.5701,\n        'wind': 861.1356,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -15.9652,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 665.4199,\n        'oil': 0,\n        'solar': 258.1522,\n        'wind': 814.8761,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -77.0911,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 702.776,\n        'oil': 0,\n        'solar': 299.1124,\n        'wind': 789.0156,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -13.8372,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 679.249,\n        'oil': 0,\n        'solar': 335.5162,\n        'wind': 762.7374,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 7.4054,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 623.5952,\n        'oil': 0,\n        'solar': 384.0147,\n        'wind': 740.3857,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -17.1507,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 467.1853,\n        'oil': 0,\n        'solar': 434.9426,\n        'wind': 747.0383,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -140.7583,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 510.8561,\n        'oil': 0,\n        'solar': 482.2437,\n        'wind': 765.7402,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -92.2379,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 440.7894,\n        'oil': 0,\n        'solar': 530.7465,\n        'wind': 787.3982,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -41.5429,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 401.2314,\n        'oil': 0,\n        'solar': 576.0005,\n        'wind': 800.726,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -9.197,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 370.1447,\n        'oil': 0,\n        'solar': 618.2328,\n        'wind': 791.7191,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.0123,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 382.4915,\n        'oil': 0,\n        'solar': 666.1473,\n        'wind': 784.0167,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -9.8469,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 351.0536,\n        'oil': 0.0,\n        'solar': 707.5219,\n        'wind': 767.7215,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 7.8166,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 300.6134,\n        'oil': 0.0,\n        'solar': 748.3678,\n        'wind': 757.1031,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 42.8411,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 303.4395,\n        'oil': 0.0,\n        'solar': 784.3734,\n        'wind': 753.6555,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 96.7232,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 298.4806,\n        'oil': 0.0,\n        'solar': 813.2073,\n        'wind': 745.9157,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 81.3406,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 266.7443,\n        'oil': 0,\n        'solar': 844.7665,\n        'wind': 726.5472,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 133.277,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 269.0543,\n        'oil': 0,\n        'solar': 881.3549,\n        'wind': 698.712,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 138.0371,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 257.0265,\n        'oil': 0,\n        'solar': 905.8617,\n        'wind': 693.286,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 33.6703,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.0665,\n        'oil': 0,\n        'solar': 927.1847,\n        'wind': 673.782,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 102.3936,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 250.2043,\n        'oil': 0,\n        'solar': 957.4909,\n        'wind': 660.002,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -13.3159,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.9376,\n        'oil': 0,\n        'solar': 986.7244,\n        'wind': 664.405,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 79.4688,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 270.1252,\n        'oil': 0,\n        'solar': 1018.4002,\n        'wind': 660.1731,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 149.4471,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 253.3554,\n        'oil': 0,\n        'solar': 1045.5213,\n        'wind': 650.9803,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 90.3946,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 251.5443,\n        'oil': 0,\n        'solar': 1066.4945,\n        'wind': 626.6657,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 127.0863,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 249.9432,\n        'oil': 0.0,\n        'solar': 1085.8416,\n        'wind': 618.7237,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 96.5873,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 248.1432,\n        'oil': 0.0,\n        'solar': 1108.8282,\n        'wind': 590.3323,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 160.6177,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 252.3743,\n        'oil': 0,\n        'solar': 1129.6426,\n        'wind': 593.81,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 102.3484,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 249.1554,\n        'oil': 0,\n        'solar': 1150.6596,\n        'wind': 580.0825,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 136.1961,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 248.8243,\n        'oil': 0.0,\n        'solar': 1164.4172,\n        'wind': 596.9642,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 179.7855,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 239.0011,\n        'oil': 0.0,\n        'solar': 1156.5793,\n        'wind': 600.2196,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 40.5306,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 234.1589,\n        'oil': 0.0,\n        'solar': 1188.5911,\n        'wind': 565.8046,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 92.9979,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 233.2889,\n        'oil': 0,\n        'solar': 1205.5649,\n        'wind': 532.2413,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 136.4046,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 234.2034,\n        'oil': 0,\n        'solar': 1227.0964,\n        'wind': 532.1332,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 48.4776,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 233.0622,\n        'oil': 0,\n        'solar': 1245.9281,\n        'wind': 542.5191,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 146.6267,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 229.1622,\n        'oil': 0,\n        'solar': 1259.5817,\n        'wind': 536.9887,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 153.5131,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 232.9334,\n        'oil': 0,\n        'solar': 1310.0314,\n        'wind': 527.6133,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 178.8237,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 234.2034,\n        'oil': 0,\n        'solar': 1332.548,\n        'wind': 517.8707,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 196.3994,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 234.4322,\n        'oil': 0,\n        'solar': 1366.9367,\n        'wind': 486.0173,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 165.5061,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 231.4122,\n        'oil': 0,\n        'solar': 1380.9328,\n        'wind': 475.5273,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 243.6437,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 229.4822,\n        'oil': 0.0,\n        'solar': 1413.1536,\n        'wind': 468.559,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 272.0725,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 232.0111,\n        'oil': 0,\n        'solar': 1375.6963,\n        'wind': 467.6655,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 191.6357,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 232.7911,\n        'oil': 0,\n        'solar': 1481.4912,\n        'wind': 470.9742,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 208.1591,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 232.9911,\n        'oil': 0,\n        'solar': 1465.0446,\n        'wind': 499.636,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 131.9682,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 231.4611,\n        'oil': 0,\n        'solar': 1523.5299,\n        'wind': 507.7367,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 104.4994,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 228.09,\n        'oil': 0.0,\n        'solar': 1519.5159,\n        'wind': 511.3018,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 150.7096,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 233.8111,\n        'oil': 0.0,\n        'solar': 1502.7788,\n        'wind': 521.3607,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 68.9541,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 227.69,\n        'oil': 0.0,\n        'solar': 1550.2113,\n        'wind': 508.6278,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 150.8567,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 229.0122,\n        'oil': 0.0,\n        'solar': 1582.1919,\n        'wind': 518.4423,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 264.6143,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 230.5011,\n        'oil': 0.0,\n        'solar': 1574.6264,\n        'wind': 503.0599,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 208.0047,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 227.5811,\n        'oil': 0,\n        'solar': 1546.752,\n        'wind': 510.8517,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 213.1228,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 227.3511,\n        'oil': 0,\n        'solar': 1583.1783,\n        'wind': 492.9552,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 200.4983,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 228.1811,\n        'oil': 0,\n        'solar': 1503.3539,\n        'wind': 495.0107,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 155.4629,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 231.4811,\n        'oil': 0,\n        'solar': 1556.2999,\n        'wind': 511.2043,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 89.7488,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 235.8522,\n        'oil': 0,\n        'solar': 1574.9432,\n        'wind': 511.0358,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 30.4324,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 233.0222,\n        'oil': 0,\n        'solar': 1534.8348,\n        'wind': 500.4108,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 62.4899,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 231.6311,\n        'oil': 0,\n        'solar': 1535.7779,\n        'wind': 511.2536,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 63.8166,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 234.1022,\n        'oil': 0,\n        'solar': 1593.1502,\n        'wind': 528.9713,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -58.4296,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 230.7011,\n        'oil': 0,\n        'solar': 1487.0862,\n        'wind': 525.1226,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 72.4592,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 230.1322,\n        'oil': 0,\n        'solar': 1448.49,\n        'wind': 506.2034,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 28.6909,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 228.6511,\n        'oil': 0,\n        'solar': 1447.8069,\n        'wind': 513.4421,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 123.7645,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 227.8811,\n        'oil': 0,\n        'solar': 1534.7075,\n        'wind': 501.6169,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 126.4536,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 228.3022,\n        'oil': 0.0,\n        'solar': 1508.3721,\n        'wind': 492.4336,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 99.9429,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 228.1511,\n        'oil': 0.0,\n        'solar': 1508.0345,\n        'wind': 480.9009,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 189.2178,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 231.7611,\n        'oil': 0.0,\n        'solar': 1492.0924,\n        'wind': 501.5353,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 136.8774,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 227.0022,\n        'oil': 0,\n        'solar': 1495.6926,\n        'wind': 491.5383,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 274.5722,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 233.8222,\n        'oil': 0,\n        'solar': 1414.7423,\n        'wind': 584.2875,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 224.946,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 226.7511,\n        'oil': 0,\n        'solar': 1388.6942,\n        'wind': 589.6536,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 309.3699,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 228.4522,\n        'oil': 0,\n        'solar': 1468.3239,\n        'wind': 599.1904,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 370.7339,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 231.7222,\n        'oil': 0,\n        'solar': 1375.7314,\n        'wind': 538.4905,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 248.3892,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 232.4922,\n        'oil': 0,\n        'solar': 1463.5664,\n        'wind': 541.1324,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 176.4554,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 228.7722,\n        'oil': 0,\n        'solar': 1452.5837,\n        'wind': 449.298,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 164.327,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 227.9222,\n        'oil': 0.0,\n        'solar': 1452.1035,\n        'wind': 447.152,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 252.3573,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 229.6734,\n        'oil': 0.0,\n        'solar': 1449.1567,\n        'wind': 442.4993,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 221.676,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 227.7722,\n        'oil': 0.0,\n        'solar': 1433.4241,\n        'wind': 429.1503,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 193.6706,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 234.8734,\n        'oil': 0.0,\n        'solar': 1389.3642,\n        'wind': 392.9637,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 28.5794,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 233.1022,\n        'oil': 0.0,\n        'solar': 1386.7831,\n        'wind': 377.5758,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -67.6583,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 227.2222,\n        'oil': 0,\n        'solar': 1413.814,\n        'wind': 330.9941,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 23.7464,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 263.8643,\n        'oil': 0,\n        'solar': 1254.5996,\n        'wind': 320.071,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 199.585,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 263.8932,\n        'oil': 0.0,\n        'solar': 1236.8762,\n        'wind': 284.1869,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 171.0362,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 264.2643,\n        'oil': 0.0,\n        'solar': 1244.2747,\n        'wind': 263.6459,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 174.867,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 264.5932,\n        'oil': 0,\n        'solar': 1307.3707,\n        'wind': 252.3013,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 21.6391,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 271.0554,\n        'oil': 0.0,\n        'solar': 1243.3376,\n        'wind': 226.5491,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 35.1632,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 268.7298,\n        'oil': 0.0,\n        'solar': 1204.3085,\n        'wind': 214.045,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -49.2218,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 327.707,\n        'oil': 0.0,\n        'solar': 1181.5059,\n        'wind': 193.2979,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 37.2175,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 395.3342,\n        'oil': 0.0,\n        'solar': 1103.1491,\n        'wind': 185.1318,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 45.9607,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 423.4195,\n        'oil': 0.0,\n        'solar': 1068.2823,\n        'wind': 178.4089,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -142.7687,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 483.1856,\n        'oil': 0,\n        'solar': 1056.3807,\n        'wind': 169.4154,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 25.4564,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 450.5169,\n        'oil': 0.0,\n        'solar': 1023.5245,\n        'wind': 165.484,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 21.0386,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 473.5656,\n        'oil': 0,\n        'solar': 1020.8941,\n        'wind': 152.9421,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 96.8843,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 494.9019,\n        'oil': 0.0,\n        'solar': 958.2664,\n        'wind': 137.5692,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 175.8149,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 534.2551,\n        'oil': 0,\n        'solar': 912.5766,\n        'wind': 135.5716,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 53.3779,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 564.5691,\n        'oil': 0.0,\n        'solar': 876.5784,\n        'wind': 122.4268,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 73.5888,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 581.8457,\n        'oil': 0.0,\n        'solar': 824.088,\n        'wind': 111.0689,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -37.8036,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 663.9017,\n        'oil': 0.0,\n        'solar': 797.0272,\n        'wind': 99.167,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -22.3889,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 702.0162,\n        'oil': 0.0,\n        'solar': 786.6131,\n        'wind': 87.4483,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -18.3803,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 722.1439,\n        'oil': 0.0,\n        'solar': 729.7129,\n        'wind': 96.4346,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -47.6169,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 725.8927,\n        'oil': 0.0,\n        'solar': 680.3159,\n        'wind': 97.2347,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -69.3373,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 780.112,\n        'oil': 0,\n        'solar': 626.07,\n        'wind': 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'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1518.1808,\n        'oil': 0.0,\n        'solar': 12.967,\n        'wind': 106.8513,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -181.5444,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1426.8697,\n        'oil': 0.0,\n        'solar': 9.425,\n        'wind': 115.4586,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -299.1797,\n      }),\n      'zoneKey': 'AU-SA',\n 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   'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1461.2753,\n        'oil': 0.0,\n        'solar': 0.008,\n        'wind': 123.9784,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -364.0794,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1444.726,\n        'oil': 0.0,\n        'solar': 0.008,\n        'wind': 133.1902,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -136.5613,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1585.1338,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 161.1964,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -212.6249,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1578.2263,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 162.3476,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -210.0133,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1583.2969,\n        'oil': 15.7,\n        'solar': 0.0,\n        'wind': 178.3554,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -202.7537,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1578.5105,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 191.2942,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -213.3721,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1583.2552,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 199.7815,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -130.8927,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1587.8264,\n        'oil': 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1596.6678,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 237.9392,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -247.5941,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 1557.6177,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 250.0575,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -222.876,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': 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dict({\n        'gas': 722.9512,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 544.4554,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 4.3943,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 701.2178,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 545.2074,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 16.5749,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 700.2911,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 533.0656,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.597,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 698.5977,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 536.8306,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0963,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 766.7545,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 552.3913,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 120.8434,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 797.1922,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 555.2427,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 164.7225,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 672.3683,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 557.3982,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.2206,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 624.9955,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 560.3848,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -29.0659,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 651.9903,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 567.0249,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -11.2798,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 567.9864,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 575.4495,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -93.5897,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 651.2625,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 576.9414,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.1035,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 517.4264,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 605.8334,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -71.8466,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 511.5289,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 637.7,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -105.5358,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 545.63,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 647.7322,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.683,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 582.7989,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 645.2196,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 86.406,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 488.2378,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 659.7773,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.8178,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 534.8889,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 643.7264,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -5.9641,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 511.6989,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 661.5812,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.6991,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 425.4478,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 687.8993,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -88.8484,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 459.1295,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 717.1342,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -18.4958,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n        'oil',\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 404.8567,\n        'oil': 0,\n        'solar': 0.0,\n        'wind': 754.5276,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.435,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 374.6789,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 788.4719,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 12.9233,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 355.8611,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 821.4647,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 12.9078,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 309.7783,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 835.6049,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 9.3767,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 312.2572,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 846.6634,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 0.1729,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 308.065,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 824.0975,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.2574,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 272.6443,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 833.6492,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -24.862,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 325.8748,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 818.7476,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 88.003,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 281.3986,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 817.4355,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.5804,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 339.2302,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 795.2654,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 116.5512,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 340.7125,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 773.8168,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 80.3671,\n      }),\n      'zoneKey': 'AU-SA',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_OPENNEM/test_production[AU-TAS].ambr",
    "content": "# serializer version: 1\n# name: test_production[AU-TAS]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 573.0738,\n        'solar': 0.0,\n        'wind': 461.2627,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 587.6082,\n        'solar': 0.0,\n        'wind': 456.0338,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 574.3973,\n        'solar': 0.0,\n        'wind': 469.6334,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 566.6638,\n        'solar': 0.0,\n        'wind': 471.8357,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 578.9818,\n        'solar': 0.0,\n        'wind': 464.572,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 580.8981,\n        'solar': 0.0,\n        'wind': 460.7743,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 593.3594,\n        'solar': 0.0,\n        'wind': 445.0473,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 612.0313,\n        'solar': 0.0,\n        'wind': 429.1799,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 570.3022,\n        'solar': 0.0,\n        'wind': 419.6672,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 587.6766,\n        'solar': 0.0,\n        'wind': 388.961,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 588.6137,\n        'solar': 0.0,\n        'wind': 377.0889,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 593.0833,\n        'solar': 0.0,\n        'wind': 397.2748,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 593.1904,\n        'solar': 0.0,\n        'wind': 380.2733,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 592.1106,\n        'solar': 0.0,\n        'wind': 367.8413,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 579.6494,\n        'solar': 0.0,\n        'wind': 357.2638,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 587.3361,\n        'solar': 0.0,\n        'wind': 380.4764,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 559.8283,\n        'solar': 0.0,\n        'wind': 377.5727,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 571.7576,\n        'solar': 0.0,\n        'wind': 392.5751,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 3, 45, 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1189.5157,\n        'solar': 0.0,\n        'wind': 362.538,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1169.8826,\n        'solar': 0.0,\n        'wind': 356.4634,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1160.3654,\n        'solar': 0.0,\n        'wind': 341.7817,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1119.1218,\n        'solar': 0.0,\n        'wind': 327.4453,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1119.0965,\n        'solar': 0.0,\n        'wind': 323.3941,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1119.6043,\n        'solar': 0.0,\n        'wind': 333.5187,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1110.7032,\n        'solar': 0.0,\n        'wind': 356.1691,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1111.7305,\n        'solar': 0.0,\n        'wind': 387.9625,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1117.4564,\n        'solar': 0.0,\n        'wind': 365.8969,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1126.175,\n        'solar': 0.0,\n        'wind': 303.809,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1132.7765,\n        'solar': 0.0,\n        'wind': 291.334,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1157.8097,\n        'solar': 0.0,\n        'wind': 319.5154,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1113.0038,\n        'solar': 0.0,\n        'wind': 335.6484,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1122.3074,\n        'solar': 0.0,\n        'wind': 317.1775,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1117.9252,\n        'solar': 0.0,\n        'wind': 285.4035,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1054.8211,\n        'solar': 0.0,\n        'wind': 299.0012,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1108.6529,\n        'solar': 0.0,\n        'wind': 318.7593,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1114.7756,\n        'solar': 0.0,\n        'wind': 335.821,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1110.8883,\n        'solar': 0.0,\n        'wind': 306.3942,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 935.3391,\n        'solar': 0.0,\n        'wind': 295.7327,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 934.3944,\n        'solar': 0.0,\n        'wind': 287.79,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 990.6076,\n        'solar': 0.0,\n        'wind': 274.6135,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 916.7098,\n        'solar': 0.0,\n        'wind': 282.8453,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 925.6788,\n        'solar': 0.0,\n        'wind': 270.1957,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 907.492,\n        'solar': 0.0,\n        'wind': 285.843,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 909.1332,\n        'solar': 0.0,\n        'wind': 296.0493,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 23, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 901.6902,\n        'solar': 0.0,\n        'wind': 301.0874,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 888.6125,\n        'solar': 0.0,\n        'wind': 314.1086,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 892.7397,\n        'solar': 0.0,\n        'wind': 308.8416,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1016.9895,\n        'solar': 0.0,\n        'wind': 287.5377,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1059.2091,\n        'solar': 0.0,\n        'wind': 265.717,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1044.1143,\n        'solar': 0.0,\n        'wind': 274.4172,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1058.4882,\n        'solar': 0.0,\n        'wind': 268.8143,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1049.6785,\n        'solar': 0.0,\n        'wind': 278.5585,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1050.2957,\n        'solar': 0.0,\n        'wind': 275.0861,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1087.8553,\n        'solar': 0.0,\n        'wind': 252.9142,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1099.4104,\n        'solar': 0.0,\n        'wind': 228.2095,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1091.54,\n        'solar': 0.0,\n        'wind': 204.616,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1082.3448,\n        'solar': 0.0,\n        'wind': 213.0977,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1040.6272,\n        'solar': 0.0,\n        'wind': 244.4737,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1037.9039,\n        'solar': 0.0,\n        'wind': 258.2245,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1044.9818,\n        'solar': 0.0,\n        'wind': 269.6053,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1044.9936,\n        'solar': 0.0,\n        'wind': 255.362,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1046.0738,\n        'solar': 0.0,\n        'wind': 243.0397,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1042.1559,\n        'solar': 0.0,\n        'wind': 225.5475,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1040.9006,\n        'solar': 0.0,\n        'wind': 221.7178,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1041.4463,\n        'solar': 0.0,\n        'wind': 210.0379,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 24, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'gas': 0.0,\n        'hydro': 1049.3453,\n        'solar': 0.0,\n        'wind': 203.2528,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'AU-TAS',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_OPENNEM/test_production[AU-VIC].ambr",
    "content": "# serializer version: 1\n# name: test_production[AU-VIC]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2355.8751,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 3002.5982,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.1062,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2360.8125,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2839.9642,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 16.7615,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2501.375,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2700.5597,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -5.9616,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2546.2813,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2793.0477,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 24.7872,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2619.0313,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2836.3445,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 57.9304,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2624.2188,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2774.2638,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 25.7424,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2620.5626,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2755.3868,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 29.6973,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2607.1251,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2631.0415,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 9.0981,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2652.0938,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2666.766,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 46.1946,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2636.8125,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2525.9799,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 23.8586,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2632.7188,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2558.4551,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 40.3383,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2636.5938,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2531.3392,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 54.3776,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2630.7813,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2473.9235,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 53.1148,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2646.6563,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2453.1245,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 34.9974,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2703.3438,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2403.2923,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 20.9309,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2701.2813,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2354.6951,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 32.9885,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2646.2188,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2350.4323,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 34.2094,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2640.0938,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2403.7812,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 63.5158,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2641.0,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2344.8375,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 10.6075,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2639.5313,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2268.5337,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 29.627,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2660.0313,\n        'gas': 0.0,\n        'hydro': 0.06,\n        'solar': 0.0,\n        'wind': 2217.9471,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 61.3278,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2682.0626,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2198.8489,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 15.9486,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2713.4376,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2226.4739,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 6.725,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2646.5625,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2215.3032,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 19.2039,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2633.5,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2250.9448,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 32.8145,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2618.3125,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2322.9492,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 50.6906,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2650.75,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2315.7729,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 37.117,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2659.7813,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2317.3835,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 54.0783,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2664.0938,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2335.8081,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 78.6993,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2697.5,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2314.3648,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 46.3322,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2666.0938,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2331.2622,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 51.0928,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2699.5313,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2323.4759,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 16.6288,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2684.2813,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2288.4359,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -5.1673,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2658.5001,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2223.3801,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 27.7294,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2721.9688,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2243.8396,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 14.6484,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2744.1563,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2222.9306,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.9162,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2722.5625,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2233.9063,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 8.2114,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2712.4688,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2248.7849,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 17.2264,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2715.4375,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 2358.0458,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 10.7313,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2732.4688,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2349.5679,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.2036,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2686.9063,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 2353.5748,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.6671,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2736.1875,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 0.0,\n        'wind': 2383.3614,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 4.4258,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2755.0625,\n        'gas': 0.0,\n        'hydro': 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dict({\n        'coal': 3277.8751,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1782.7334,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -48.5283,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3272.875,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1758.2056,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -36.1942,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 1, 25, 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 'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3320.5938,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1753.3994,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -38.7244,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3410.1563,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1732.5284,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -38.1902,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3417.3125,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1667.0836,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -41.157,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3440.6875,\n        'gas': 0.0,\n        'hydro': 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dict({\n        'coal': 3445.2813,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1653.6279,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -34.5068,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3427.5313,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1673.7722,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -29.4247,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3353.9063,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1684.1373,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 35.5369,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3311.5625,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1681.439,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -17.3459,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3272.0938,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1682.1208,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -27.1965,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3275.875,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1669.4237,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -21.2198,\n      }),\n   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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -21.3139,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3274.3125,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1714.5984,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -39.1294,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3293.7813,\n        'gas': 0.0,\n        'hydro': 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dict({\n        'coal': 3402.2813,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1639.3556,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -39.0772,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3423.1876,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1653.6191,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -29.3236,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3458.6563,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1676.1732,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -25.6797,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3432.875,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1633.798,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -45.6967,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3494.6875,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1595.4298,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -43.7444,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3571.6875,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1583.5494,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -41.2868,\n      }),\n  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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -36.6476,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3805.5,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1497.3419,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -29.039,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3907.2813,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1474.3699,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 41.9746,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3964.5313,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1498.3045,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.7336,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n     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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4006.5001,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1312.3678,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.2169,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3979.0,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1348.936,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 27.6135,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3958.9375,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1413.8567,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 4.5695,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3986.0938,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1462.2216,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -18.2575,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4003.0626,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1489.6232,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -43.8788,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3978.75,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 0.0,\n        'wind': 1461.8249,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -13.8041,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4021.0313,\n        'gas': 0.0,\n        'hydro': 13.31,\n        'solar': 0.0,\n        'wind': 1426.5317,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -47.1781,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3980.0626,\n        'gas': 0.0,\n        'hydro': 13.01,\n        'solar': 0.0,\n        'wind': 1418.7339,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -25.0778,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4007.4375,\n        'gas': 0.0,\n        'hydro': 13.01,\n        'solar': 0.0,\n        'wind': 1401.3731,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -15.3802,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4014.1876,\n        'gas': 0.0,\n        'hydro': 12.91,\n        'solar': 0.0,\n        'wind': 1418.7648,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -79.4556,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4061.3438,\n        'gas': 0.0,\n        'hydro': 12.91,\n        'solar': 0.0,\n        'wind': 1417.7381,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -102.6585,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4098.7188,\n        'gas': 0.0,\n        'hydro': 12.91,\n        'solar': 0.0,\n        'wind': 1427.187,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -90.8713,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4133.75,\n        'gas': 0.0,\n        'hydro': 172.21,\n        'solar': 0.0,\n        'wind': 1401.7825,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -154.0882,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4148.6875,\n        'gas': 0.0,\n        'hydro': 177.41,\n        'solar': 0.0,\n        'wind': 1353.151,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -136.0555,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4145.8751,\n        'gas': 0.0,\n        'hydro': 177.31,\n        'solar': 0.0,\n        'wind': 1269.5404,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -163.1052,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4183.9376,\n        'gas': 0.0,\n        'hydro': 176.81,\n        'solar': 0.0,\n        'wind': 1250.7954,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -105.2734,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4170.5938,\n        'gas': 0.0,\n        'hydro': 176.51,\n        'solar': 0.0,\n        'wind': 1249.6075,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -182.5869,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4205.9376,\n        'gas': 0.0,\n        'hydro': 177.81,\n        'solar': 0.4168,\n        'wind': 1214.4456,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -224.9108,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4205.4375,\n        'gas': 0.0,\n        'hydro': 164.41,\n        'solar': 0.8337,\n        'wind': 1166.6412,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': 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'wind': 1125.2203,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -151.6535,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4203.7813,\n        'gas': 0.0,\n        'hydro': 337.61,\n        'solar': 3.3042,\n        'wind': 1076.9925,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -117.0089,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 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}),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3690.5,\n        'gas': 0.0,\n        'hydro': 26.01,\n        'solar': 1956.6464,\n        'wind': 642.3584,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -24.0169,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3553.0938,\n        'gas': 0.0,\n        'hydro': 0.05,\n        'solar': 2125.3563,\n        'wind': 656.9526,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': 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'gas': 0.0,\n        'hydro': 53.28,\n        'solar': 2298.3645,\n        'wind': 862.6092,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -2.6713,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3260.4063,\n        'gas': 0.0,\n        'hydro': 53.41,\n        'solar': 2435.2639,\n        'wind': 938.5637,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 40.4246,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 9, 25, 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'coal': 2295.1875,\n        'gas': 0.0,\n        'hydro': 4.685,\n        'solar': 2881.674,\n        'wind': 905.8004,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 209.0222,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 11, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2256.3438,\n        'gas': 0.0,\n        'hydro': 4.025,\n        'solar': 2858.503,\n        'wind': 998.158,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 157.5372,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2239.2813,\n        'gas': 0.0,\n        'hydro': 2.375,\n        'solar': 2806.6074,\n        'wind': 968.2945,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 228.7431,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2272.1876,\n        'gas': 0.0,\n        'hydro': 0.505,\n        'solar': 2764.2492,\n        'wind': 902.8778,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 209.398,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      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'battery': 270.8639,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2261.5938,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2756.0453,\n        'wind': 816.144,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 211.9611,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2252.9063,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2782.1516,\n        'wind': 790.5104,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 269.2386,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2231.4375,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2891.9154,\n        'wind': 800.5439,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 289.1218,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2230.4063,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2942.6568,\n        'wind': 785.085,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 226.3709,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2230.9063,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2992.4897,\n        'wind': 778.5819,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 220.2071,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2214.5001,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 3025.3451,\n        'wind': 692.8168,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 215.9503,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2160.0626,\n        'gas': 0.0,\n        'hydro': 0.0,\n        'solar': 2991.3271,\n        'wind': 702.2007,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 249.0125,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2197.0313,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 3015.3795,\n        'wind': 758.2061,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 204.6331,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2160.0625,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 3061.8866,\n        'wind': 733.2147,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 235.4142,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2196.125,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 3096.0559,\n        'wind': 751.2622,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 266.2468,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2161.2188,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 3138.9721,\n        'wind': 747.2964,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 288.4827,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2161.25,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 3172.0368,\n        'wind': 740.6178,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 255.8919,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2202.8438,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 3185.7142,\n        'wind': 740.732,\n      }),\n      'source': 'opennem.org.au',\n      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'battery': 60.7136,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2271.2188,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 3226.0899,\n        'wind': 733.3778,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 28.1677,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2258.5313,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 3165.5703,\n        'wind': 779.2774,\n      }),\n      'source': 'opennem.org.au',\n      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'battery': -0.953,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2384.9688,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2914.5862,\n        'wind': 923.2578,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 12.6536,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2443.4375,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2887.7159,\n        'wind': 932.3074,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.9468,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2547.4063,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2841.7879,\n        'wind': 973.9313,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -6.5281,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2600.8751,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2798.3705,\n        'wind': 966.7866,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -45.0205,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2624.8126,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2753.1258,\n        'wind': 977.1666,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -31.5318,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n       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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2761.8125,\n        'gas': 0.0,\n        'hydro': 0.0,\n        'solar': 2650.072,\n        'wind': 985.3539,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 36.3778,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2804.5001,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2603.6624,\n        'wind': 955.3816,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 77.6209,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2887.8438,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2570.8808,\n        'wind': 963.971,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -10.558,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 2962.6875,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2506.4043,\n        'wind': 946.6616,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 11.6528,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3052.5313,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2404.0654,\n        'wind': 903.2006,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 44.3909,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3113.2813,\n        'gas': 0.0,\n        'hydro': 0.01,\n        'solar': 2241.3266,\n        'wind': 877.7577,\n      }),\n      'source': 'opennem.org.au',\n      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3315.1876,\n        'gas': 0.0,\n        'hydro': 61.51,\n        'solar': 2004.8927,\n        'wind': 837.7579,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -8.9455,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3448.0,\n        'gas': 0.0,\n        'hydro': 61.81,\n        'solar': 1994.0327,\n        'wind': 826.0851,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -28.9518,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3490.9375,\n        'gas': 0.0,\n        'hydro': 61.45,\n        'solar': 1892.825,\n        'wind': 786.1018,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 19.4114,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3533.5313,\n        'gas': 0.0,\n        'hydro': 61.25,\n        'solar': 1806.2856,\n        'wind': 791.9112,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.7115,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3523.75,\n        'gas': 0.0,\n        'hydro': 53.85,\n        'solar': 1714.2418,\n        'wind': 782.3454,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -61.8203,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3577.9375,\n        'gas': 39.175,\n        'hydro': 0.05,\n        'solar': 1618.1286,\n        'wind': 786.6993,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -32.0137,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3661.0938,\n        'gas': 79.25,\n        'hydro': 106.55,\n        'solar': 1531.2505,\n        'wind': 737.4983,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 34.075,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3736.5313,\n        'gas': 80.5,\n        'hydro': 161.55,\n        'solar': 1422.8317,\n        'wind': 718.0367,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.1265,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3757.0625,\n        'gas': 80.0,\n        'hydro': 386.25,\n        'solar': 1360.19,\n        'wind': 651.0393,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 41.912,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3792.75,\n        'gas': 78.9,\n        'hydro': 542.75,\n        'solar': 1277.6321,\n        'wind': 638.1702,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 50.585,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3894.0313,\n        'gas': 61.775,\n        'hydro': 638.75,\n        'solar': 1195.4457,\n        'wind': 631.9722,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -11.3348,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3873.6251,\n        'gas': 101.125,\n        'hydro': 641.83,\n        'solar': 1088.4078,\n        'wind': 633.787,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -92.3629,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3920.9688,\n        'gas': 109.65,\n        'hydro': 644.39,\n        'solar': 1007.4247,\n        'wind': 606.7003,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -94.7893,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 3954.7813,\n        'gas': 69.375,\n        'hydro': 722.47,\n        'solar': 957.8459,\n        'wind': 570.3036,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.0192,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4014.4688,\n        'gas': 55.0,\n        'hydro': 791.7101,\n        'solar': 854.2665,\n        'wind': 574.835,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -5.9977,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4062.6251,\n        'gas': 60.15,\n        'hydro': 815.97,\n        'solar': 745.6041,\n        'wind': 569.1928,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -100.6202,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4110.8126,\n        'gas': 168.125,\n        'hydro': 868.43,\n        'solar': 642.6973,\n        'wind': 572.6174,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -100.7046,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4117.7188,\n        'gas': 241.025,\n        'hydro': 920.94,\n        'solar': 538.1776,\n        'wind': 554.6574,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -195.0558,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4189.0313,\n        'gas': 257.625,\n        'hydro': 854.35,\n        'solar': 450.2508,\n        'wind': 558.1933,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -108.0359,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4207.5001,\n        'gas': 361.8,\n        'hydro': 787.91,\n        'solar': 361.522,\n        'wind': 543.2,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -110.0592,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4200.5626,\n        'gas': 375.65,\n        'hydro': 824.8101,\n        'solar': 280.2077,\n        'wind': 530.5716,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -101.0124,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4206.8126,\n        'gas': 335.925,\n        'hydro': 852.87,\n        'solar': 208.4188,\n        'wind': 514.9475,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -127.402,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4231.7188,\n        'gas': 375.45,\n        'hydro': 867.71,\n        'solar': 144.5189,\n        'wind': 505.2213,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -129.3687,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4206.7501,\n        'gas': 374.275,\n        'hydro': 944.07,\n        'solar': 86.7575,\n        'wind': 496.1544,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -114.9157,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4185.3438,\n        'gas': 371.3,\n        'hydro': 899.95,\n        'solar': 62.9401,\n        'wind': 515.9719,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -101.2474,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4212.2501,\n        'gas': 375.2,\n        'hydro': 868.35,\n        'solar': 45.8855,\n        'wind': 519.427,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -138.7419,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4208.1563,\n        'gas': 305.8,\n        'hydro': 866.85,\n        'solar': 31.5965,\n        'wind': 526.4903,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -132.0464,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4199.1251,\n        'gas': 373.025,\n        'hydro': 864.71,\n        'solar': 20.8757,\n        'wind': 508.756,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -101.9782,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4186.1876,\n        'gas': 378.3,\n        'hydro': 855.69,\n        'solar': 10.3848,\n        'wind': 506.6103,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -118.184,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4189.0,\n        'gas': 378.7,\n        'hydro': 965.43,\n        'solar': 0.554,\n        'wind': 519.143,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -95.7553,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4206.9063,\n        'gas': 379.75,\n        'hydro': 971.2101,\n        'solar': 0.4717,\n        'wind': 534.53,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -104.9358,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4201.3126,\n        'gas': 376.9,\n        'hydro': 982.3701,\n        'solar': 0.3693,\n        'wind': 545.6519,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -168.5458,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4232.8125,\n        'gas': 360.1,\n        'hydro': 984.21,\n        'solar': 0.317,\n        'wind': 563.9193,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -129.5304,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4235.6563,\n        'gas': 357.475,\n        'hydro': 983.49,\n        'solar': 0.2247,\n        'wind': 575.1251,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -119.3059,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4205.3438,\n        'gas': 377.075,\n        'hydro': 959.83,\n        'solar': 0.4423,\n        'wind': 580.5936,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -96.0568,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4215.25,\n        'gas': 380.1,\n        'hydro': 963.39,\n        'solar': 0.0,\n        'wind': 601.6158,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -103.0659,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4213.8438,\n        'gas': 376.025,\n        'hydro': 915.45,\n        'solar': 0.0,\n        'wind': 629.8836,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -104.2341,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4208.0001,\n        'gas': 336.4,\n        'hydro': 906.01,\n        'solar': 0.0,\n        'wind': 649.407,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -100.8142,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4209.0625,\n        'gas': 290.125,\n        'hydro': 865.89,\n        'solar': 0.15,\n        'wind': 670.7719,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -102.7743,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4201.5,\n        'gas': 331.175,\n        'hydro': 784.73,\n        'solar': 0.06,\n        'wind': 685.1124,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -99.4486,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4194.4063,\n        'gas': 330.775,\n        'hydro': 742.39,\n        'solar': 0.0,\n        'wind': 707.6277,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -87.9455,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4215.1251,\n        'gas': 278.95,\n        'hydro': 688.39,\n        'solar': 0.0,\n        'wind': 711.9608,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -74.5749,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4195.1876,\n        'gas': 211.1,\n        'hydro': 668.73,\n        'solar': 0.0,\n        'wind': 742.2115,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -100.0142,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4194.7813,\n        'gas': 184.625,\n        'hydro': 802.09,\n        'solar': 0.0,\n        'wind': 792.9081,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -64.3618,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4191.8438,\n        'gas': 185.2,\n        'hydro': 819.65,\n        'solar': 0.0,\n        'wind': 837.2534,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 3.2553,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4211.375,\n        'gas': 184.35,\n        'hydro': 642.57,\n        'solar': 0.0,\n        'wind': 864.1491,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.313,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'production': dict({\n        'coal': 4216.1251,\n        'gas': 185.35,\n        'hydro': 632.93,\n        'solar': 0.02,\n        'wind': 880.0402,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.3987,\n      }),\n      'zoneKey': 'AU-VIC',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_OPENNEM/test_production[AU-WA].ambr",
    "content": "# serializer version: 1\n# name: test_production[AU-WA]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 613.2799,\n        'gas': 845.0935,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 805.2495,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -295.2004,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 605.8526,\n        'gas': 853.0111,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 799.4625,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -227.1905,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 601.5587,\n        'gas': 818.3606,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 800.7106,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -273.2872,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 596.5629,\n        'gas': 817.5112,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 801.6776,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -235.2606,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 594.4502,\n        'gas': 813.5265,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 803.379,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -214.3072,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 593.4562,\n        'gas': 792.6864,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 807.4366,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -226.4105,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 593.8494,\n        'gas': 785.3068,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 811.0527,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -243.4206,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 592.858,\n        'gas': 788.7573,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 809.0102,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -254.7309,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 593.3937,\n        'gas': 754.8736,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 810.8603,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -287.9574,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.18,\n        'coal': 594.146,\n        'gas': 775.495,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 813.6898,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -157.7105,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.2422,\n        'coal': 594.5786,\n        'gas': 782.3333,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 819.565,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -99.9105,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.2422,\n        'coal': 594.4614,\n        'gas': 755.9203,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 828.1418,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -114.534,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 6, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.2422,\n        'coal': 595.3509,\n        'gas': 754.2071,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 835.2807,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -52.2341,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 7, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.316,\n        'coal': 594.7799,\n        'gas': 749.5654,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 835.0068,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -48.6239,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 7, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.316,\n        'coal': 594.5345,\n        'gas': 741.8073,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 827.9155,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -35.744,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 7, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.316,\n        'coal': 594.2564,\n        'gas': 731.519,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 818.8721,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -43.244,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 7, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.359,\n        'coal': 593.8452,\n        'gas': 711.2867,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 809.1301,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -107.084,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 7, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.359,\n        'coal': 593.945,\n        'gas': 681.6724,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 806.395,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -152.4473,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 7, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.359,\n        'coal': 593.6942,\n        'gas': 679.4722,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 811.2496,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -105.5975,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 7, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.359,\n        'coal': 593.6509,\n        'gas': 671.7208,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 816.9755,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -77.4674,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 7, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.359,\n        'coal': 593.7607,\n        'gas': 662.3535,\n        'hydro': 0.001,\n        'oil': 0.5577,\n        'solar': 1.0345,\n        'wind': 818.3803,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -69.4472,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 7, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.359,\n        'coal': 594.3507,\n        'gas': 665.9508,\n        'hydro': 0.0025,\n        'oil': 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tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9618,\n        'coal': 864.4658,\n        'gas': 956.4961,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 590.1441,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 20.3896,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9618,\n        'coal': 851.492,\n        'gas': 972.136,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 581.1649,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      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'solar': 1.9217,\n        'wind': 572.2353,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 13.2536,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 819.7791,\n        'gas': 969.9826,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 568.5658,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 2.1436,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 810.0463,\n        'gas': 964.1445,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 569.1843,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 1.5736,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 811.4341,\n        'gas': 905.519,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 559.1412,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -132.2764,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 818.9691,\n        'gas': 865.9876,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 558.4186,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -187.6933,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 832.9857,\n        'gas': 846.4368,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 557.0206,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -170.0598,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 844.0072,\n        'gas': 845.6655,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 558.451,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -107.1532,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 850.4594,\n        'gas': 845.8886,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 564.5287,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -27.7798,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 849.9578,\n        'gas': 845.8923,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 580.934,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 44.7936,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 846.8938,\n        'gas': 845.5911,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 597.0719,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 106.8936,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 842.222,\n        'gas': 843.2832,\n        'hydro': 0.002,\n        'oil': 0.515,\n      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tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 816.9118,\n        'gas': 844.7623,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 661.8326,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 286.7837,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 808.5477,\n        'gas': 842.0279,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 671.2619,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 318.6133,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.9631,\n        'coal': 808.3156,\n        'gas': 843.8041,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 682.8281,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 413.3034,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.8992,\n        'coal': 808.1938,\n        'gas': 844.7302,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 689.3011,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 466.4667,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.8992,\n        'coal': 813.8213,\n        'gas': 844.3444,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 701.4289,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 517.0366,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.8992,\n        'coal': 832.2165,\n        'gas': 846.2305,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 696.2361,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 617.2031,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0206,\n        'coal': 838.439,\n        'gas': 844.7811,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 688.5722,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 553.0304,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0206,\n        'coal': 838.4802,\n        'gas': 846.2687,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 696.642,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 567.4502,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0206,\n        'coal': 844.1617,\n        'gas': 846.5463,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 706.3689,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 666.1903,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0206,\n        'coal': 843.2264,\n        'gas': 849.6492,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 707.5953,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 694.1434,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0206,\n        'coal': 839.1157,\n        'gas': 847.346,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 703.9169,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 596.96,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0206,\n        'coal': 833.0344,\n        'gas': 848.0578,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 695.0002,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      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tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0206,\n        'coal': 796.1241,\n        'gas': 843.3038,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 695.3997,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 558.1918,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0206,\n        'coal': 796.3057,\n        'gas': 847.6077,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 1.9217,\n        'wind': 682.7661,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n  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tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0139,\n        'coal': 786.4658,\n        'gas': 847.8507,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 641.0276,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 539.519,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0139,\n        'coal': 784.5794,\n        'gas': 847.2095,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 645.6228,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 554.1191,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.0139,\n        'coal': 784.4509,\n        'gas': 846.6059,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 650.7978,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 556.4088,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.1358,\n        'coal': 785.6556,\n        'gas': 846.2134,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 655.8041,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 584.902,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.1358,\n        'coal': 786.5097,\n        'gas': 807.7076,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 654.7401,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 508.6387,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.1358,\n        'coal': 785.8112,\n        'gas': 742.714,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 650.498,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 318.1155,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.1358,\n        'coal': 785.2133,\n        'gas': 728.4552,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 632.1921,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      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'solar': 0.721,\n        'wind': 629.6587,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 227.6555,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.1358,\n        'coal': 784.2739,\n        'gas': 727.6764,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 639.5876,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 258.8219,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.1358,\n        'coal': 784.6892,\n        'gas': 765.1921,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 657.9726,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 468.9155,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.1358,\n        'coal': 784.3838,\n        'gas': 833.2163,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 654.591,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n     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'solar': 0.721,\n        'wind': 607.9675,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 618.4955,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.2495,\n        'coal': 785.113,\n        'gas': 846.353,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 586.6126,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 506.859,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 5, 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   'battery': 484.1388,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.2627,\n        'coal': 784.7593,\n        'gas': 847.5745,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 571.9909,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 496.0321,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.2627,\n        'coal': 784.0833,\n        'gas': 847.509,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 561.906,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 452.8455,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.2627,\n        'coal': 785.017,\n        'gas': 847.3571,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 564.0777,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 466.3387,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.2627,\n        'coal': 781.9184,\n        'gas': 845.3289,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 571.9522,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 508.7586,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.2627,\n        'coal': 783.7369,\n        'gas': 847.8016,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 571.5355,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 511.7285,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.2627,\n        'coal': 784.2529,\n        'gas': 847.4727,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 563.9175,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 444.9922,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.2627,\n        'coal': 784.5496,\n        'gas': 846.7796,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 567.483,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 381.132,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.2627,\n        'coal': 783.9823,\n        'gas': 847.8211,\n        'hydro': 0.002,\n        'oil': 0.515,\n        'solar': 0.721,\n        'wind': 575.5476,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 336.7086,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 4, 55, 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'oil': 4.7737,\n        'solar': 336.3188,\n        'wind': 497.8725,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -172.4691,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 46.0142,\n        'coal': 912.5664,\n        'gas': 845.8092,\n        'hydro': 0.002,\n        'oil': 4.8987,\n        'solar': 334.9865,\n        'wind': 512.9774,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -72.9925,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 7, 25, 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list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 42.9181,\n        'coal': 1047.8557,\n        'gas': 1277.6955,\n        'hydro': 0.002,\n        'oil': 0.525,\n        'solar': 1662.7727,\n        'wind': 216.8856,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 315.2402,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.1281,\n        'coal': 1050.848,\n        'gas': 1284.1038,\n        'hydro': 0.002,\n        'oil': 0.525,\n        'solar': 1634.2166,\n        'wind': 227.9004,\n      }),\n      'source': 'opennem.org.au',\n   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'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 16.096,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.1281,\n        'coal': 1048.0927,\n        'gas': 1256.9744,\n        'hydro': 0.002,\n        'oil': 0.525,\n        'solar': 1587.1261,\n        'wind': 203.8143,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -114.2678,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.1281,\n        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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 306.7402,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.201,\n        'coal': 1052.6421,\n        'gas': 1519.6961,\n        'hydro': 0.002,\n        'oil': 0.525,\n        'solar': 836.8902,\n        'wind': 600.5748,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 303.4066,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.201,\n        'coal': 1051.8519,\n    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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 557.6118,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.428,\n        'coal': 1049.1303,\n        'gas': 1697.2769,\n        'hydro': 0.002,\n        'oil': 0.525,\n        'solar': 659.6372,\n        'wind': 662.1047,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 655.1252,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 9, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.428,\n        'coal': 1053.8653,\n   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'oil': 0.556,\n        'solar': 101.6279,\n        'wind': 627.4476,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -116.1854,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.2899,\n        'coal': 887.5547,\n        'gas': 804.2648,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 101.5056,\n        'wind': 628.8818,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -195.752,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.4993,\n        'coal': 880.6784,\n        'gas': 788.0866,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 101.6619,\n        'wind': 647.3185,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -215.9758,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 43.2591,\n        'coal': 874.8057,\n        'gas': 779.8778,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 126.1758,\n        'wind': 668.2436,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -216.9734,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 41.7133,\n        'coal': 869.4078,\n        'gas': 771.2347,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 126.4355,\n        'wind': 690.835,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -219.8734,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 41.7133,\n        'coal': 857.7199,\n        'gas': 780.0855,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 127.0324,\n        'wind': 697.8462,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -243.1868,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 40.4933,\n        'coal': 850.7174,\n        'gas': 787.8482,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 151.7003,\n        'wind': 704.4738,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -237.4602,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 40.4933,\n        'coal': 842.9829,\n        'gas': 806.6032,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 150.82,\n        'wind': 710.0446,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -240.2134,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 43.5139,\n        'coal': 833.2787,\n        'gas': 797.3211,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 150.563,\n        'wind': 718.6787,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -267.3402,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 45.4138,\n        'coal': 828.7843,\n        'gas': 803.4867,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 172.1371,\n        'wind': 719.9809,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -264.7468,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 44.7754,\n        'coal': 825.0739,\n        'gas': 791.7596,\n        'hydro': 0.001,\n        'oil': 0.556,\n        'solar': 173.8048,\n        'wind': 721.5482,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -292.5534,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2026, 2, 10, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=28800))),\n      'production': dict({\n        'biomass': 43.6036,\n        'coal': 827.644,\n        'gas': 794.462,\n        'hydro': 0.001,\n        'oil': 0.5517,\n        'solar': 176.2084,\n        'wind': 719.8022,\n      }),\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -322.2108,\n      }),\n      'zoneKey': 'AU-WA',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_OPENNEM.ambr",
    "content": "# serializer version: 1\n# name: test_au_nsw_au_qld_exchange\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -534.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -526.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -542.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -532.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -424.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -440.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -422.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -346.1001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -351.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -333.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -272.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -248.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -182.4501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -194.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -196.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -227.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -225.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -171.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -179.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -188.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -211.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -234.2501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -224.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -296.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -327.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -332.2501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -325.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -130.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -352.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -392.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -378.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -390.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -432.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -270.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -247.1001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -297.1001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -263.3501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -295.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -342.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -340.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -292.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -311.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -307.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -322.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -358.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -353.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -382.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -367.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -356.3501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -384.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -383.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -338.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -281.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -322.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -288.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -272.1501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -266.4501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -298.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -279.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -293.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -333.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -371.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -389.2501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -343.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -319.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -333.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -325.1501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -310.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -277.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -299.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -302.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -304.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -300.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -337.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -320.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -379.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -347.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -337.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -356.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -380.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -377.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -373.1501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -348.3501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -343.3501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -349.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -353.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -322.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -333.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -321.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -318.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -330.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -306.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -297.1501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -306.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -308.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -304.2501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -317.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -274.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -290.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -220.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -213.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -241.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -263.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -267.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -227.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -205.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -226.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -198.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -141.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -164.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -207.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -189.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -217.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -176.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -214.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -259.2501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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7, 11, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -206.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -266.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -264.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -358.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -449.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -438.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -482.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -535.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -596.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -576.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -561.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -570.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -585.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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7, 11, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -480.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1001.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1047.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -918.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -999.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -964.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -937.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -971.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -938.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -898.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -984.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -990.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -979.3501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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7, 11, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -995.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -957.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -942.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -962.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -878.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -959.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -896.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -871.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -927.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -960.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -961.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -958.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -971.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -906.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -948.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -905.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -951.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -891.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -909.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -910.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -861.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -872.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -855.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -870.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -886.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': 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'datetime': datetime.datetime(2025, 7, 11, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -839.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -886.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -907.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -948.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -913.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -988.1501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -946.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -993.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -924.1001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -790.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -765.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -765.2501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -845.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': 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'datetime': datetime.datetime(2025, 7, 11, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -866.45,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -862.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -915.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -902.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -903.2501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -869.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -859.1501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -749.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -679.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -706.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -794.3501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -793.1501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -786.3501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -735.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -642.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -619.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -586.8001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -671.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -606.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -339.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -386.4501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -367.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -335.4001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -371.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -376.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -383.4501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -315.5001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -308.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -366.3501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -359.9001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -410.1501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -357.1501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -414.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -432.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -392.0501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -442.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -447.2001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -424.2501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -404.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -380.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -365.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -394.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -383.4501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -401.7001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -423.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -461.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -396.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -457.7501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -451.0001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -418.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -371.8501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -408.5501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -480.6001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -444.3001,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -463.9501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -541.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -546.6501,\n      'sortedZoneKeys': 'AU-NSW->AU-QLD',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_au_nsw_au_vic_exchange\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1638.9452,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1649.5042,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1671.075,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1609.9634,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1473.0838,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1568.8404,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1486.6966,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1531.0558,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 21, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1696.0598,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1660.479,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1614.272,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1592.3448,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1465.393,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1499.3508,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1614.3126,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1499.4394,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1482.563,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1458.994,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1571.2438,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1564.7414,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 22, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1570.5968,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1570.3726,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1739.248,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1828.9454,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1777.3728,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1809.4972,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1805.604,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2169.3938,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1807.0498,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1888.5388,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1715.411,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1886.7404,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 10, 23, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2011.769,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2355.8604,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2357.0802,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2411.1004,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2258.7316,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2426.1242,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2589.13,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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datetime.datetime(2025, 7, 11, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2488.4046,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2620.307,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2703.097,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2630.7814,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2647.0456,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2673.611,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2673.027,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2718.6032,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2709.4054,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2659.8388,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2508.0674,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2569.8088,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2591.3578,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': 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'datetime': datetime.datetime(2025, 7, 11, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2500.0728,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2565.831,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2673.9072,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2734.5834,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2720.0606,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2651.342,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2596.2752,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2651.1386,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2621.111,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2526.239,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2517.5234,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2560.1272,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2468.5304,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2767.285,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2745.961,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2790.4462,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2719.5794,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2679.9696,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2707.7416,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': 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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2737.6014,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2650.9684,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2466.453,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': 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'datetime': datetime.datetime(2025, 7, 11, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2244.3132,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2225.0042,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2115.0572,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2104.757,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2132.073,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2224.5492,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2156.6962,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2246.9476,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2184.269,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2163.8966,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2159.6632,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2145.3176,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2045.5002,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2101.236,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2195.4908,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2162.232,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      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'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2198.0798,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1958.9596,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2081.5732,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': 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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1287.2586,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1429.68,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1429.313,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      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tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1502.9202,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1488.3568,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1466.3954,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      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'datetime': datetime.datetime(2025, 7, 11, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1295.6228,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1537.0544,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1435.3568,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1360.659,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1383.6636,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1452.368,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1510.7376,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1492.8404,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1212.77,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1466.3084,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1218.9476,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1350.949,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1628.7078,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': 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'datetime': datetime.datetime(2025, 7, 11, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1309.2826,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1103.207,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1328.1542,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1608.9888,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1830.6556,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1715.3542,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1645.629,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1679.7684,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1723.7536,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1781.2106,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1829.4326,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1849.3262,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1782.0304,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': 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'datetime': datetime.datetime(2025, 7, 11, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1518.9442,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1470.1102,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1610.6578,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1437.2662,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1510.0034,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1487.6872,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1422.6346,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1729.4464,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1725.5762,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1933.331,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1860.4534,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -2037.0152,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1743.783,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': 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'netFlow': -1294.8688,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1271.0302,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1421.5806,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1377.1142,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1354.8084,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1251.295,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1171.2406,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1159.5354,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1115.036,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -1105.1356,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -939.0392,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -832.7148,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -856.5842,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -767.4528,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -909.3686,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -955.1264,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -902.0392,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -801.607,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -793.102,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -834.1742,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -909.8472,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -627.0916,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 197.7594,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 168.4912,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 331.6336,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 110.5388,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 331.3674,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 239.7266,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 356.7922,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 291.5998,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 299.2394,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 273.573,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 231.818,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 372.8876,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 405.5782,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 185.4508,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 18, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 224.1724,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 220.9618,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 341.7222,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 211.5182,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 212.4236,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 317.6104,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 219.713,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 224.9672,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 260.494,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 293.0918,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 357.1408,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 345.2334,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 19, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 353.4372,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 286.397,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 356.8042,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 302.2506,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 15, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 327.1058,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 20, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 294.5012,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 25, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 185.9602,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 30, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 179.8772,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 35, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 281.041,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 40, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 282.207,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 45, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 171.2042,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 50, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 228.8228,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 20, 55, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 237.4406,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 231.9974,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 21, 5, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': 165.9206,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 7, 11, 21, 10, tzinfo=datetime.timezone(datetime.timedelta(seconds=36000))),\n      'netFlow': -69.3206,\n      'sortedZoneKeys': 'AU-NSW->AU-VIC',\n      'source': 'opennem.org.au',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_PA.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2021, 12, 30, 9, 58, tzinfo=zoneinfo.ZoneInfo(key='America/Panama')),\n      'production': dict({\n        'biomass': 2.75,\n        'coal': 149.6,\n        'gas': 355.88,\n        'hydro': 421.84,\n        'oil': 238.2,\n        'solar': 262.76,\n        'unknown': 0.0,\n        'wind': 115.4,\n      }),\n      'source': 'sitr.cnd.com.pa',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PA',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_PE.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_with_target_datetime\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 57.9,\n        'coal': 0.0,\n        'gas': 2564.9,\n        'hydro': 2894.175,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 440.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.8,\n        'coal': 0.0,\n        'gas': 2562.1,\n        'hydro': 2791.586,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 398.2,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 68.4,\n        'coal': 0.0,\n        'gas': 2566.7,\n        'hydro': 2794.35,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 299.8,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.8,\n        'coal': 0.0,\n        'gas': 2609.8,\n        'hydro': 2757.581,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 227.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.1,\n        'coal': 0.0,\n        'gas': 2611.2,\n        'hydro': 2751.545,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 205.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.5,\n        'coal': 0.0,\n        'gas': 2605.8,\n        'hydro': 2764.811,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 195.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.2,\n        'coal': 0.0,\n        'gas': 2607.7,\n        'hydro': 2794.797,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 165.4,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.1,\n        'coal': 0.0,\n        'gas': 2607.7,\n        'hydro': 2812.719,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 143.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.7,\n        'coal': 0.0,\n        'gas': 2593.5,\n        'hydro': 2832.66,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 130.1,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 71.3,\n        'coal': 0.0,\n        'gas': 2624.3,\n        'hydro': 2792.109,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 119.3,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 73.3,\n        'coal': 0.0,\n        'gas': 2649.6,\n        'hydro': 2900.177,\n        'oil': 0.0,\n        'solar': 0.1,\n        'wind': 115.3,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 78.0,\n        'coal': 0.0,\n        'gas': 2661.8,\n        'hydro': 2977.049,\n        'oil': 0.0,\n        'solar': 17.5,\n        'wind': 116.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 78.9,\n        'coal': 0.0,\n        'gas': 2660.9,\n        'hydro': 2931.098,\n        'oil': 0.0,\n        'solar': 208.4,\n        'wind': 112.2,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 80.4,\n        'coal': 0.0,\n        'gas': 2660.9,\n        'hydro': 2618.37,\n        'oil': 0.0,\n        'solar': 472.2,\n        'wind': 97.3,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 80.4,\n        'coal': 0.0,\n        'gas': 2656.3,\n        'hydro': 2546.013,\n        'oil': 0.0,\n        'solar': 733.2,\n        'wind': 97.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 78.3,\n        'coal': 0.0,\n        'gas': 2652.6,\n        'hydro': 2680.726,\n        'oil': 0.0,\n        'solar': 798.3,\n        'wind': 99.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 76.4,\n        'coal': 0.0,\n        'gas': 2680.5,\n        'hydro': 2923.774,\n        'oil': 0.0,\n        'solar': 812.4,\n        'wind': 91.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 77.3,\n        'coal': 0.0,\n        'gas': 2732.5,\n        'hydro': 2863.517,\n        'oil': 0.0,\n        'solar': 825.7,\n        'wind': 104.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 75.3,\n        'coal': 0.0,\n        'gas': 2800.3,\n        'hydro': 2965.253,\n        'oil': 0.0,\n        'solar': 831.0,\n        'wind': 106.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 74.5,\n        'coal': 0.0,\n        'gas': 2853.4,\n        'hydro': 2925.418,\n        'oil': 0.0,\n        'solar': 830.9,\n        'wind': 137.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 72.7,\n        'coal': 0.0,\n        'gas': 2871.3,\n        'hydro': 2901.0,\n        'oil': 0.0,\n        'solar': 825.6,\n        'wind': 165.3,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 71.2,\n        'coal': 0.0,\n        'gas': 2861.5,\n        'hydro': 2769.1,\n        'oil': 0.0,\n        'solar': 870.9,\n        'wind': 182.7,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 74.8,\n        'coal': 0.0,\n        'gas': 2863.3,\n        'hydro': 2781.436,\n        'oil': 0.0,\n        'solar': 876.0,\n        'wind': 223.3,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 74.4,\n        'coal': 0.0,\n        'gas': 2860.5,\n        'hydro': 2782.444,\n        'oil': 0.0,\n        'solar': 880.5,\n        'wind': 276.4,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 76.6,\n        'coal': 0.0,\n        'gas': 2867.3,\n        'hydro': 2613.536,\n        'oil': 0.0,\n        'solar': 889.7,\n        'wind': 273.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 78.1,\n        'coal': 0.0,\n        'gas': 2868.6,\n        'hydro': 2595.605,\n        'oil': 0.0,\n        'solar': 902.3,\n        'wind': 297.7,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 78.2,\n        'coal': 0.0,\n        'gas': 2866.9,\n        'hydro': 2529.552,\n        'oil': 0.0,\n        'solar': 901.7,\n        'wind': 356.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 78.0,\n        'coal': 0.0,\n        'gas': 2869.0,\n        'hydro': 2427.856,\n        'oil': 0.0,\n        'solar': 897.3,\n        'wind': 378.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 77.7,\n        'coal': 0.0,\n        'gas': 2867.5,\n        'hydro': 2479.46,\n        'oil': 0.0,\n        'solar': 883.9,\n        'wind': 442.7,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 79.5,\n        'coal': 0.0,\n        'gas': 2877.0,\n        'hydro': 2450.538,\n        'oil': 0.0,\n        'solar': 870.8,\n        'wind': 519.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 80.1,\n        'coal': 0.0,\n        'gas': 2869.7,\n        'hydro': 2368.53,\n        'oil': 0.0,\n        'solar': 842.7,\n        'wind': 634.8,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 81.8,\n        'coal': 0.0,\n        'gas': 2878.8,\n        'hydro': 2329.748,\n        'oil': 0.0,\n        'solar': 778.3,\n        'wind': 646.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 82.1,\n        'coal': 0.0,\n        'gas': 2887.3,\n        'hydro': 2517.25,\n        'oil': 0.0,\n        'solar': 542.0,\n        'wind': 683.1,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 81.8,\n        'coal': 0.0,\n        'gas': 2892.4,\n        'hydro': 2812.631,\n        'oil': 0.0,\n        'solar': 231.8,\n        'wind': 686.7,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 81.0,\n        'coal': 0.0,\n        'gas': 2901.6,\n        'hydro': 3071.717,\n        'oil': 0.0,\n        'solar': 21.1,\n        'wind': 667.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 80.3,\n        'coal': 0.0,\n        'gas': 2899.0,\n        'hydro': 3037.118,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 649.3,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 81.0,\n        'coal': 0.0,\n        'gas': 2901.0,\n        'hydro': 3228.483,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 696.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 81.5,\n        'coal': 0.0,\n        'gas': 2899.3,\n        'hydro': 3158.956,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 755.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 81.6,\n        'coal': 0.0,\n        'gas': 2902.1,\n        'hydro': 3131.279,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 803.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 81.8,\n        'coal': 0.0,\n        'gas': 2902.2,\n        'hydro': 3087.98,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 797.2,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 81.4,\n        'coal': 0.0,\n        'gas': 2897.9,\n        'hydro': 3101.956,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 779.4,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 79.0,\n        'coal': 0.0,\n        'gas': 2895.6,\n        'hydro': 3072.529,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 772.2,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 78.4,\n        'coal': 0.0,\n        'gas': 2900.4,\n        'hydro': 2999.837,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 784.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 78.0,\n        'coal': 0.0,\n        'gas': 2901.7,\n        'hydro': 3036.871,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 751.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 79.3,\n        'coal': 0.0,\n        'gas': 2895.3,\n        'hydro': 2864.727,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 741.4,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 79.2,\n        'coal': 0.0,\n        'gas': 2777.6,\n        'hydro': 2714.683,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 741.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 9, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 79.4,\n        'coal': 0.0,\n        'gas': 2740.6,\n        'hydro': 2519.6,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 742.2,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 80.5,\n        'coal': 0.0,\n        'gas': 2700.0,\n        'hydro': 2453.267,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 681.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 67.2,\n        'coal': 0.0,\n        'gas': 2670.56,\n        'hydro': 2378.363,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 646.4,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.2,\n        'coal': 0.0,\n        'gas': 2669.26,\n        'hydro': 2359.61,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 594.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 67.5,\n        'coal': 0.0,\n        'gas': 2671.77,\n        'hydro': 2310.082,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 600.7,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': 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}),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.9,\n        'coal': 0.0,\n        'gas': 2654.28,\n        'hydro': 2465.332,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 468.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.6,\n        'coal': 0.0,\n        'gas': 2662.98,\n        'hydro': 2389.06,\n        'oil': 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'gas': 2679.82,\n        'hydro': 2368.83,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 547.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 67.4,\n        'coal': 0.0,\n        'gas': 2684.58,\n        'hydro': 2321.968,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 563.7,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n 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tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.4,\n        'coal': 0.0,\n        'gas': 2675.58,\n        'hydro': 2346.888,\n        'oil': 0.0,\n        'solar': 206.9,\n        'wind': 751.2,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.5,\n        'coal': 0.0,\n        'gas': 2578.63,\n        'hydro': 2262.673,\n        'oil': 0.0,\n        'solar': 474.5,\n        'wind': 762.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      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'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 68.4,\n        'coal': 0.0,\n        'gas': 2655.24,\n        'hydro': 2440.903,\n        'oil': 0.0,\n        'solar': 665.4,\n        'wind': 771.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.0,\n        'coal': 0.0,\n        'gas': 2653.51,\n        'hydro': 2547.51,\n        'oil': 0.0,\n        'solar': 681.1,\n        'wind': 777.4,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 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'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 67.2,\n        'coal': 0.0,\n        'gas': 2611.65,\n        'hydro': 2552.777,\n        'oil': 0.0,\n        'solar': 791.5,\n        'wind': 814.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 68.6,\n        'coal': 0.0,\n        'gas': 2597.83,\n        'hydro': 2656.748,\n        'oil': 0.0,\n        'solar': 795.2,\n        'wind': 819.2,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 68.3,\n        'coal': 0.0,\n        'gas': 2608.22,\n        'hydro': 2487.844,\n        'oil': 0.0,\n        'solar': 839.5,\n        'wind': 821.3,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 67.7,\n        'coal': 0.0,\n        'gas': 2616.86,\n        'hydro': 2523.757,\n        'oil': 0.0,\n        'solar': 897.0,\n        'wind': 833.4,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 68.9,\n        'coal': 0.0,\n        'gas': 2569.59,\n        'hydro': 2689.933,\n        'oil': 0.0,\n        'solar': 751.4,\n        'wind': 814.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n 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tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 67.5,\n        'coal': 0.0,\n        'gas': 2561.61,\n        'hydro': 2425.157,\n        'oil': 0.0,\n        'solar': 903.0,\n        'wind': 783.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 64.0,\n        'coal': 0.0,\n        'gas': 2579.68,\n        'hydro': 2549.879,\n        'oil': 0.0,\n        'solar': 894.6,\n        'wind': 772.4,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n     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'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 68.3,\n        'coal': 0.0,\n        'gas': 2472.79,\n        'hydro': 2666.166,\n        'oil': 0.0,\n        'solar': 772.2,\n        'wind': 796.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 68.1,\n        'coal': 0.0,\n        'gas': 2474.19,\n        'hydro': 2832.345,\n        'oil': 0.0,\n        'solar': 546.6,\n        'wind': 814.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 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'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.1,\n        'coal': 0.0,\n        'gas': 2647.85,\n        'hydro': 2981.944,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 813.2,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.9,\n        'coal': 0.0,\n        'gas': 2673.63,\n        'hydro': 3214.258,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 802.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.3,\n        'coal': 0.0,\n        'gas': 2673.53,\n        'hydro': 3249.182,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 810.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 67.8,\n        'coal': 0.0,\n        'gas': 2675.05,\n        'hydro': 3249.839,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 810.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.5,\n        'coal': 0.0,\n        'gas': 2671.28,\n        'hydro': 3288.65,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 778.8,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 68.6,\n        'coal': 0.0,\n        'gas': 2664.6,\n        'hydro': 3328.954,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 726.7,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.5,\n        'coal': 0.0,\n        'gas': 2674.22,\n        'hydro': 3334.196,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 684.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 67.6,\n        'coal': 0.0,\n        'gas': 2678.84,\n        'hydro': 3260.097,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 629.7,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.5,\n        'coal': 0.0,\n        'gas': 2677.01,\n        'hydro': 3225.619,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 603.0,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.5,\n        'coal': 0.0,\n        'gas': 2656.47,\n        'hydro': 3191.703,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 576.5,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 69.6,\n        'coal': 0.0,\n        'gas': 2625.7,\n        'hydro': 3173.034,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 477.2,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 10, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.4,\n        'coal': 0.0,\n        'gas': 2629.4,\n        'hydro': 2894.729,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 495.6,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 9, 11, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Lima')),\n      'production': dict({\n        'biomass': 70.4,\n        'coal': 0.0,\n        'gas': 2629.3,\n        'hydro': 2713.826,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 586.9,\n      }),\n      'source': 'coes.org.pe',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PE',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_PF.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production_live\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2024, 1, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Pacific/Tahiti')),\n      'production': dict({\n        'hydro': 0.969,\n        'oil': 54.52,\n        'solar': 6.909,\n      }),\n      'source': 'edt.pf',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'PF',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[AZ-RU-1-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[AZ-RU-1-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': -15.369718551635742,\n      'sortedZoneKeys': 'AZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[BY-RU-1-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[BY-RU-1-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': -42.7039909362793,\n      'sortedZoneKeys': 'BY->RU-1',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[CN-RU-AS-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[CN-RU-AS-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': 10.538268089294434,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[CN-RU-AS-11].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[CN-RU-AS-11]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': 9.51062297821045,\n      'sortedZoneKeys': 'CN->RU-AS',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[GE-RU-1-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[GE-RU-1-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': -33.125675201416016,\n      'sortedZoneKeys': 'GE->RU-1',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[KZ-RU-1-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[KZ-RU-1-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': 2183.0078125,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[KZ-RU-1-11].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[KZ-RU-1-11]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': 2211.9833984375,\n      'sortedZoneKeys': 'KZ->RU-1',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[KZ-RU-2-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[KZ-RU-2-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': -664.8331298828125,\n      'sortedZoneKeys': 'KZ->RU-2',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[MN-RU-2-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[MN-RU-2-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': 132.10043334960938,\n      'sortedZoneKeys': 'MN->RU-2',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[RU-1-FI-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[RU-1-FI-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'FI->RU-1',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[RU-1-RU-2-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[RU-1-RU-2-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': 653.2890014648438,\n      'sortedZoneKeys': 'RU-1->RU-2',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[RU-1-UA-CR-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[RU-1-UA-CR-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': 333.6430969238281,\n      'sortedZoneKeys': 'RU-1->UA-CR',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[RU-KGD-LT-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[RU-KGD-LT-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'LT->RU-KGD',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_exchange[UA-RU-1-10].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange[UA-RU-1-10]\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0),\n      'netFlow': -0.0,\n      'sortedZoneKeys': 'RU-1->UA',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_production[RU-1].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[RU-1]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 4346.501953,\n        'nuclear': 26255.0,\n        'solar': 0.0,\n        'unknown': 50173.64502,\n        'wind': 926.97998,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3537.502197,\n        'nuclear': 26214.0,\n        'solar': 0.0,\n        'unknown': 49450.04541,\n        'wind': 724.518005,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3500.501953,\n        'nuclear': 26224.0,\n        'solar': 1.7,\n        'unknown': 48148.434082,\n        'wind': 898.512024,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3494.501953,\n        'nuclear': 26236.0,\n        'solar': 7.75,\n        'unknown': 47866.341797,\n        'wind': 735.33197,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3546.502197,\n        'nuclear': 26270.0,\n        'solar': 44.263,\n        'unknown': 48896.133789,\n        'wind': 881.731018,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 4343.501953,\n        'nuclear': 26319.0,\n        'solar': 144.781998,\n        'unknown': 50447.544433,\n        'wind': 720.939026,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 5991.301758,\n        'nuclear': 26328.300781,\n        'solar': 331.674011,\n        'unknown': 54911.654297,\n        'wind': 655.276001,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 6839.999512,\n        'nuclear': 26289.300781,\n        'solar': 577.502991,\n        'unknown': 59313.839843,\n        'wind': 648.059998,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 8181.468262,\n        'nuclear': 26260.300781,\n        'solar': 766.291016,\n        'unknown': 62992.39795,\n        'wind': 590.267029,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 8614.632812,\n        'nuclear': 26196.300781,\n        'solar': 881.244019,\n        'unknown': 65757.251953,\n        'wind': 811.273987,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 9778.923828,\n        'nuclear': 26135.300781,\n        'solar': 894.66803,\n        'unknown': 66554.412109,\n        'wind': 980.773987,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 9524.998047,\n        'nuclear': 26070.300781,\n        'solar': 907.239014,\n        'unknown': 66208.286133,\n        'wind': 1093.807007,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 10300.410156,\n        'nuclear': 26025.0,\n        'solar': 811.791016,\n        'unknown': 66690.502441,\n        'wind': 991.333984,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 10797.139648,\n        'nuclear': 26000.0,\n        'solar': 733.091003,\n        'unknown': 66601.081054,\n        'wind': 1008.932983,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 10744.229492,\n        'nuclear': 25977.300781,\n        'solar': 618.656006,\n        'unknown': 66812.897949,\n        'wind': 853.738708,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 10400.150391,\n        'nuclear': 25819.0,\n        'solar': 455.972992,\n        'unknown': 66577.999023,\n        'wind': 621.213867,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 8797.742188,\n        'nuclear': 25763.941406,\n        'solar': 250.949005,\n        'unknown': 67355.156739,\n        'wind': 453.132172,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 9014.041016,\n        'nuclear': 25650.0,\n        'solar': 130.634003,\n        'unknown': 66122.48291,\n        'wind': 575.749207,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 8586.829102,\n        'nuclear': 25590.0,\n        'solar': 35.539001,\n        'unknown': 65198.904296,\n        'wind': 821.947021,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 8125.947266,\n        'nuclear': 25560.0,\n        'solar': 5.1,\n        'unknown': 64339.231934,\n        'wind': 1024.118042,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 8059.025879,\n        'nuclear': 25545.0,\n        'solar': 0.0,\n        'unknown': 64291.926269,\n        'wind': 956.10498,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 7902.702148,\n        'nuclear': 25596.0,\n        'solar': 0.0,\n        'unknown': 61873.375,\n        'wind': 1121.36499,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 7275.902344,\n        'nuclear': 25615.0,\n        'solar': 0.0,\n        'unknown': 56876.41748,\n        'wind': 1262.905029,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 5289.202148,\n        'nuclear': 25607.0,\n        'solar': 0.0,\n        'unknown': 54199.392578,\n        'wind': 1310.967041,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-1',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_production[RU-2].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[RU-2]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 11902.007812,\n        'nuclear': None,\n        'solar': 28.35,\n        'unknown': 7687.402771,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 11968.030273,\n        'nuclear': None,\n        'solar': 72.199997,\n        'unknown': 7693.506775,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 12199.666016,\n        'nuclear': None,\n        'solar': 131.899994,\n        'unknown': 7707.402771,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 12457.5,\n        'nuclear': None,\n        'solar': 192.25,\n        'unknown': 7751.402771,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13121.564453,\n        'nuclear': None,\n        'solar': 184.25,\n        'unknown': 7880.860291,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14036.282227,\n        'nuclear': None,\n        'solar': 248.379456,\n        'unknown': 8061.495483,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13385.181641,\n        'nuclear': None,\n        'solar': 256.149994,\n        'unknown': 8209.99585,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13647.104492,\n        'nuclear': None,\n        'solar': 256.276031,\n        'unknown': 8239.125549,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13966.766602,\n        'nuclear': None,\n        'solar': 258.593689,\n        'unknown': 8300.357544,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14082.213867,\n        'nuclear': None,\n        'solar': 252.336899,\n        'unknown': 8346.084595,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13634.400391,\n        'nuclear': None,\n        'solar': 241.166031,\n        'unknown': 8352.928588,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14025.966797,\n        'nuclear': None,\n        'solar': 213.5,\n        'unknown': 8366.604736,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13690.520508,\n        'nuclear': None,\n        'solar': 169.600006,\n        'unknown': 8418.335877,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13629.388672,\n        'nuclear': None,\n        'solar': 108.550003,\n        'unknown': 8394.960877,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13720.821289,\n        'nuclear': None,\n        'solar': 48.599998,\n        'unknown': 8428.925232,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14000.866211,\n        'nuclear': None,\n        'solar': 12.0,\n        'unknown': 8793.875428,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14406.917969,\n        'nuclear': None,\n        'solar': 3.7,\n        'unknown': 8728.12201,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13838.950195,\n        'nuclear': None,\n        'solar': 1.05,\n        'unknown': 8790.569275,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13639.786133,\n        'nuclear': None,\n        'solar': 0.2,\n        'unknown': 8591.752869,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 12841.951172,\n        'nuclear': None,\n        'solar': 0.0,\n        'unknown': 8571.481385,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 12144.849609,\n        'nuclear': None,\n        'solar': 0.0,\n        'unknown': 8625.721619,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 11886.116211,\n        'nuclear': None,\n        'solar': 0.0,\n        'unknown': 8566.546326,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 11135.402344,\n        'nuclear': None,\n        'solar': 0.6,\n        'unknown': 8507.364197,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 10917.832031,\n        'nuclear': None,\n        'solar': 6.45,\n        'unknown': 8508.051697,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU/test_snapshot_fetch_production[RU-AS].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_production[RU-AS]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3083.657246,\n        'nuclear': 0.0,\n        'unknown': 1631.44506,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3182.169485,\n        'nuclear': 0.0,\n        'unknown': 1819.36316,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3344.528174,\n        'nuclear': 0.0,\n        'unknown': 1874.11754,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3369.626544,\n        'nuclear': 0.0,\n        'unknown': 1944.848604,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3402.629042,\n        'nuclear': 0.0,\n        'unknown': 2006.295669,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3362.047411,\n        'nuclear': 0.0,\n        'unknown': 2046.567408,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3325.311096,\n        'nuclear': 0.0,\n        'unknown': 2086.299776,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3345.680769,\n        'nuclear': 0.0,\n        'unknown': 2063.002318,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3364.623899,\n        'nuclear': 0.0,\n        'unknown': 2062.297261,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3336.32972,\n        'nuclear': 0.0,\n        'unknown': 2058.290767,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3341.319969,\n        'nuclear': 0.0,\n        'unknown': 2053.156575,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3373.015831,\n        'nuclear': 0.0,\n        'unknown': 2024.347291,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3405.095705,\n        'nuclear': 0.0,\n        'unknown': 2003.295351,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3388.80739,\n        'nuclear': 0.0,\n        'unknown': 1942.182221,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3398.377864,\n        'nuclear': 0.0,\n        'unknown': 1921.071672,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3400.495094,\n        'nuclear': 0.0,\n        'unknown': 1720.118612,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3394.743685,\n        'nuclear': 0.0,\n        'unknown': 1527.278429,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3232.661113,\n        'nuclear': 0.0,\n        'unknown': 1403.69665,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 3020.427729,\n        'nuclear': 0.0,\n        'unknown': 1402.398393,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 2901.185758,\n        'nuclear': 0.0,\n        'unknown': 1401.104228,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 2846.328785,\n        'nuclear': 0.0,\n        'unknown': 1414.307315,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 2886.874579,\n        'nuclear': 0.0,\n        'unknown': 1421.490354,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 2947.675003,\n        'nuclear': 0.0,\n        'unknown': 1414.226952,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 2996.120854,\n        'nuclear': 0.0,\n        'unknown': 1529.323405,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-AS',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_RU.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_exchange_live\n  list([\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 123.52476501464844,\n      'sortedZoneKeys': 'MN->RU',\n      'source': 'so-ups.ru',\n    }),\n    dict({\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0, tzinfo=datetime.timezone.utc),\n      'netFlow': 123.52476501464844,\n      'sortedZoneKeys': 'MN->RU',\n      'source': 'so-ups.ru',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_production_live\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 11902.007812,\n        'nuclear': None,\n        'solar': 28.35,\n        'unknown': 7687.402771,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 11968.030273,\n        'nuclear': None,\n        'solar': 72.199997,\n        'unknown': 7693.506775,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 12199.666016,\n        'nuclear': None,\n        'solar': 131.899994,\n        'unknown': 7707.402771,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 12457.5,\n        'nuclear': None,\n        'solar': 192.25,\n        'unknown': 7751.402771,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13121.564453,\n        'nuclear': None,\n        'solar': 184.25,\n        'unknown': 7880.860291,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14036.282227,\n        'nuclear': None,\n        'solar': 248.379456,\n        'unknown': 8061.495483,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13385.181641,\n        'nuclear': None,\n        'solar': 256.149994,\n        'unknown': 8209.99585,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13647.104492,\n        'nuclear': None,\n        'solar': 256.276031,\n        'unknown': 8239.125549,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13966.766602,\n        'nuclear': None,\n        'solar': 258.593689,\n        'unknown': 8300.357544,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14082.213867,\n        'nuclear': None,\n        'solar': 252.336899,\n        'unknown': 8346.084595,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13634.400391,\n        'nuclear': None,\n        'solar': 241.166031,\n        'unknown': 8352.928588,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14025.966797,\n        'nuclear': None,\n        'solar': 213.5,\n        'unknown': 8366.604736,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13690.520508,\n        'nuclear': None,\n        'solar': 169.600006,\n        'unknown': 8418.335877,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13629.388672,\n        'nuclear': None,\n        'solar': 108.550003,\n        'unknown': 8394.960877,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13720.821289,\n        'nuclear': None,\n        'solar': 48.599998,\n        'unknown': 8428.925232,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14000.866211,\n        'nuclear': None,\n        'solar': 12.0,\n        'unknown': 8793.875428,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 14406.917969,\n        'nuclear': None,\n        'solar': 3.7,\n        'unknown': 8728.12201,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13838.950195,\n        'nuclear': None,\n        'solar': 1.05,\n        'unknown': 8790.569275,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 13639.786133,\n        'nuclear': None,\n        'solar': 0.2,\n        'unknown': 8591.752869,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 19, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 12841.951172,\n        'nuclear': None,\n        'solar': 0.0,\n        'unknown': 8571.481385,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 20, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 12144.849609,\n        'nuclear': None,\n        'solar': 0.0,\n        'unknown': 8625.721619,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 21, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 11886.116211,\n        'nuclear': None,\n        'solar': 0.0,\n        'unknown': 8566.546326,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 22, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 11135.402344,\n        'nuclear': None,\n        'solar': 0.6,\n        'unknown': 8507.364197,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': FakeDatetime(2025, 7, 28, 23, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'hydro': 10917.832031,\n        'nuclear': None,\n        'solar': 6.45,\n        'unknown': 8508.051697,\n        'wind': None,\n      }),\n      'source': 'so-ups.ru',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'RU-2',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_SMARTGRIDDASHBOARD.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption\n  list([\n    dict({\n      'consumption': 685.0,\n      'datetime': datetime.datetime(2023, 11, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 670.0,\n      'datetime': datetime.datetime(2023, 11, 4, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 656.0,\n      'datetime': datetime.datetime(2023, 11, 4, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 641.0,\n      'datetime': datetime.datetime(2023, 11, 4, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 634.0,\n      'datetime': datetime.datetime(2023, 11, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 653.0,\n      'datetime': datetime.datetime(2023, 11, 4, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 645.0,\n      'datetime': datetime.datetime(2023, 11, 4, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 632.0,\n      'datetime': datetime.datetime(2023, 11, 4, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 625.0,\n      'datetime': datetime.datetime(2023, 11, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 629.0,\n      'datetime': datetime.datetime(2023, 11, 4, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 620.0,\n      'datetime': datetime.datetime(2023, 11, 4, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 612.0,\n      'datetime': datetime.datetime(2023, 11, 4, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 607.0,\n      'datetime': datetime.datetime(2023, 11, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 604.0,\n      'datetime': datetime.datetime(2023, 11, 4, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 596.0,\n      'datetime': datetime.datetime(2023, 11, 4, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 593.0,\n      'datetime': datetime.datetime(2023, 11, 4, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 591.0,\n      'datetime': datetime.datetime(2023, 11, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 592.0,\n      'datetime': datetime.datetime(2023, 11, 4, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 591.0,\n      'datetime': datetime.datetime(2023, 11, 4, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 588.0,\n      'datetime': datetime.datetime(2023, 11, 4, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 588.0,\n      'datetime': datetime.datetime(2023, 11, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 593.0,\n      'datetime': datetime.datetime(2023, 11, 4, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 596.0,\n      'datetime': datetime.datetime(2023, 11, 4, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 604.0,\n      'datetime': datetime.datetime(2023, 11, 4, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 617.0,\n      'datetime': datetime.datetime(2023, 11, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 642.0,\n      'datetime': datetime.datetime(2023, 11, 4, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 654.0,\n      'datetime': datetime.datetime(2023, 11, 4, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 672.0,\n      'datetime': datetime.datetime(2023, 11, 4, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 694.0,\n      'datetime': datetime.datetime(2023, 11, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 722.0,\n      'datetime': datetime.datetime(2023, 11, 4, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 737.0,\n      'datetime': datetime.datetime(2023, 11, 4, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 757.0,\n      'datetime': datetime.datetime(2023, 11, 4, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 779.0,\n      'datetime': datetime.datetime(2023, 11, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 805.0,\n      'datetime': datetime.datetime(2023, 11, 4, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 830.0,\n      'datetime': datetime.datetime(2023, 11, 4, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 853.0,\n      'datetime': datetime.datetime(2023, 11, 4, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 875.0,\n      'datetime': datetime.datetime(2023, 11, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 902.0,\n      'datetime': datetime.datetime(2023, 11, 4, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 920.0,\n      'datetime': datetime.datetime(2023, 11, 4, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 933.0,\n      'datetime': datetime.datetime(2023, 11, 4, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 939.0,\n      'datetime': datetime.datetime(2023, 11, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 944.0,\n      'datetime': datetime.datetime(2023, 11, 4, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 943.0,\n      'datetime': datetime.datetime(2023, 11, 4, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 940.0,\n      'datetime': datetime.datetime(2023, 11, 4, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 936.0,\n      'datetime': datetime.datetime(2023, 11, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 941.0,\n      'datetime': datetime.datetime(2023, 11, 4, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 932.0,\n      'datetime': datetime.datetime(2023, 11, 4, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 943.0,\n      'datetime': datetime.datetime(2023, 11, 4, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 940.0,\n      'datetime': datetime.datetime(2023, 11, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 947.0,\n      'datetime': datetime.datetime(2023, 11, 4, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 941.0,\n      'datetime': datetime.datetime(2023, 11, 4, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 933.0,\n      'datetime': datetime.datetime(2023, 11, 4, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 924.0,\n      'datetime': datetime.datetime(2023, 11, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 924.0,\n      'datetime': datetime.datetime(2023, 11, 4, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 926.0,\n      'datetime': datetime.datetime(2023, 11, 4, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 916.0,\n      'datetime': datetime.datetime(2023, 11, 4, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 902.0,\n      'datetime': datetime.datetime(2023, 11, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 895.0,\n      'datetime': datetime.datetime(2023, 11, 4, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 887.0,\n      'datetime': datetime.datetime(2023, 11, 4, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 890.0,\n      'datetime': datetime.datetime(2023, 11, 4, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 896.0,\n      'datetime': datetime.datetime(2023, 11, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 903.0,\n      'datetime': datetime.datetime(2023, 11, 4, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 909.0,\n      'datetime': datetime.datetime(2023, 11, 4, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 916.0,\n      'datetime': datetime.datetime(2023, 11, 4, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 932.0,\n      'datetime': datetime.datetime(2023, 11, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 955.0,\n      'datetime': datetime.datetime(2023, 11, 4, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 981.0,\n      'datetime': datetime.datetime(2023, 11, 4, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1020.0,\n      'datetime': datetime.datetime(2023, 11, 4, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1068.0,\n      'datetime': datetime.datetime(2023, 11, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1113.0,\n      'datetime': datetime.datetime(2023, 11, 4, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1133.0,\n      'datetime': datetime.datetime(2023, 11, 4, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1130.0,\n      'datetime': datetime.datetime(2023, 11, 4, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1112.0,\n      'datetime': datetime.datetime(2023, 11, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1091.0,\n      'datetime': datetime.datetime(2023, 11, 4, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1071.0,\n      'datetime': datetime.datetime(2023, 11, 4, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1048.0,\n      'datetime': datetime.datetime(2023, 11, 4, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1023.0,\n      'datetime': datetime.datetime(2023, 11, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 997.0,\n      'datetime': datetime.datetime(2023, 11, 4, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 971.0,\n      'datetime': datetime.datetime(2023, 11, 4, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 954.0,\n      'datetime': datetime.datetime(2023, 11, 4, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 933.0,\n      'datetime': datetime.datetime(2023, 11, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 918.0,\n      'datetime': datetime.datetime(2023, 11, 4, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 903.0,\n      'datetime': datetime.datetime(2023, 11, 4, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 891.0,\n      'datetime': datetime.datetime(2023, 11, 4, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 874.0,\n      'datetime': datetime.datetime(2023, 11, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 854.0,\n      'datetime': datetime.datetime(2023, 11, 4, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 833.0,\n      'datetime': datetime.datetime(2023, 11, 4, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 818.0,\n      'datetime': datetime.datetime(2023, 11, 4, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 796.0,\n      'datetime': datetime.datetime(2023, 11, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 779.0,\n      'datetime': datetime.datetime(2023, 11, 4, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 760.0,\n      'datetime': datetime.datetime(2023, 11, 4, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 735.0,\n      'datetime': datetime.datetime(2023, 11, 4, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 714.0,\n      'datetime': datetime.datetime(2023, 11, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 694.0,\n      'datetime': datetime.datetime(2023, 11, 4, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 677.0,\n      'datetime': datetime.datetime(2023, 11, 4, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 659.0,\n      'datetime': datetime.datetime(2023, 11, 4, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 639.0,\n      'datetime': datetime.datetime(2023, 11, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 625.0,\n      'datetime': datetime.datetime(2023, 11, 5, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 614.0,\n      'datetime': datetime.datetime(2023, 11, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 602.0,\n      'datetime': datetime.datetime(2023, 11, 5, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 597.0,\n      'datetime': datetime.datetime(2023, 11, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 612.0,\n      'datetime': datetime.datetime(2023, 11, 5, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 606.0,\n      'datetime': datetime.datetime(2023, 11, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 599.0,\n      'datetime': datetime.datetime(2023, 11, 5, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 588.0,\n      'datetime': datetime.datetime(2023, 11, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 585.0,\n      'datetime': datetime.datetime(2023, 11, 5, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 577.0,\n      'datetime': datetime.datetime(2023, 11, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 569.0,\n      'datetime': datetime.datetime(2023, 11, 5, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 565.0,\n      'datetime': datetime.datetime(2023, 11, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 557.0,\n      'datetime': datetime.datetime(2023, 11, 5, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 553.0,\n      'datetime': datetime.datetime(2023, 11, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 547.0,\n      'datetime': datetime.datetime(2023, 11, 5, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 548.0,\n      'datetime': datetime.datetime(2023, 11, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 548.0,\n      'datetime': datetime.datetime(2023, 11, 5, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 544.0,\n      'datetime': datetime.datetime(2023, 11, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 541.0,\n      'datetime': datetime.datetime(2023, 11, 5, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 541.0,\n      'datetime': datetime.datetime(2023, 11, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 542.0,\n      'datetime': datetime.datetime(2023, 11, 5, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 546.0,\n      'datetime': datetime.datetime(2023, 11, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 549.0,\n      'datetime': datetime.datetime(2023, 11, 5, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 561.0,\n      'datetime': datetime.datetime(2023, 11, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 580.0,\n      'datetime': datetime.datetime(2023, 11, 5, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 589.0,\n      'datetime': datetime.datetime(2023, 11, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 607.0,\n      'datetime': datetime.datetime(2023, 11, 5, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 620.0,\n      'datetime': datetime.datetime(2023, 11, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 628.0,\n      'datetime': datetime.datetime(2023, 11, 5, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 639.0,\n      'datetime': datetime.datetime(2023, 11, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 652.0,\n      'datetime': datetime.datetime(2023, 11, 5, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 672.0,\n      'datetime': datetime.datetime(2023, 11, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 695.0,\n      'datetime': datetime.datetime(2023, 11, 5, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 718.0,\n      'datetime': datetime.datetime(2023, 11, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 741.0,\n      'datetime': datetime.datetime(2023, 11, 5, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 765.0,\n      'datetime': datetime.datetime(2023, 11, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 787.0,\n      'datetime': datetime.datetime(2023, 11, 5, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 800.0,\n      'datetime': datetime.datetime(2023, 11, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 820.0,\n      'datetime': datetime.datetime(2023, 11, 5, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 835.0,\n      'datetime': datetime.datetime(2023, 11, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 852.0,\n      'datetime': datetime.datetime(2023, 11, 5, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 858.0,\n      'datetime': datetime.datetime(2023, 11, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 857.0,\n      'datetime': datetime.datetime(2023, 11, 5, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 865.0,\n      'datetime': datetime.datetime(2023, 11, 5, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 875.0,\n      'datetime': datetime.datetime(2023, 11, 5, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 872.0,\n      'datetime': datetime.datetime(2023, 11, 5, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 879.0,\n      'datetime': datetime.datetime(2023, 11, 5, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 894.0,\n      'datetime': datetime.datetime(2023, 11, 5, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 903.0,\n      'datetime': datetime.datetime(2023, 11, 5, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 911.0,\n      'datetime': datetime.datetime(2023, 11, 5, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 916.0,\n      'datetime': datetime.datetime(2023, 11, 5, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 918.0,\n      'datetime': datetime.datetime(2023, 11, 5, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 909.0,\n      'datetime': datetime.datetime(2023, 11, 5, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 898.0,\n      'datetime': datetime.datetime(2023, 11, 5, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 889.0,\n      'datetime': datetime.datetime(2023, 11, 5, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 887.0,\n      'datetime': datetime.datetime(2023, 11, 5, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 880.0,\n      'datetime': datetime.datetime(2023, 11, 5, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 881.0,\n      'datetime': datetime.datetime(2023, 11, 5, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 877.0,\n      'datetime': datetime.datetime(2023, 11, 5, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 882.0,\n      'datetime': datetime.datetime(2023, 11, 5, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 893.0,\n      'datetime': datetime.datetime(2023, 11, 5, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 904.0,\n      'datetime': datetime.datetime(2023, 11, 5, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 920.0,\n      'datetime': datetime.datetime(2023, 11, 5, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 950.0,\n      'datetime': datetime.datetime(2023, 11, 5, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 971.0,\n      'datetime': datetime.datetime(2023, 11, 5, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 998.0,\n      'datetime': datetime.datetime(2023, 11, 5, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1034.0,\n      'datetime': datetime.datetime(2023, 11, 5, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1081.0,\n      'datetime': datetime.datetime(2023, 11, 5, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1116.0,\n      'datetime': datetime.datetime(2023, 11, 5, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1140.0,\n      'datetime': datetime.datetime(2023, 11, 5, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1127.0,\n      'datetime': datetime.datetime(2023, 11, 5, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1110.0,\n      'datetime': datetime.datetime(2023, 11, 5, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1085.0,\n      'datetime': datetime.datetime(2023, 11, 5, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1063.0,\n      'datetime': datetime.datetime(2023, 11, 5, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1047.0,\n      'datetime': datetime.datetime(2023, 11, 5, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1016.0,\n      'datetime': datetime.datetime(2023, 11, 5, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1000.0,\n      'datetime': datetime.datetime(2023, 11, 5, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 982.0,\n      'datetime': datetime.datetime(2023, 11, 5, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 967.0,\n      'datetime': datetime.datetime(2023, 11, 5, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 941.0,\n      'datetime': datetime.datetime(2023, 11, 5, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 933.0,\n      'datetime': datetime.datetime(2023, 11, 5, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 909.0,\n      'datetime': datetime.datetime(2023, 11, 5, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 888.0,\n      'datetime': datetime.datetime(2023, 11, 5, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 870.0,\n      'datetime': datetime.datetime(2023, 11, 5, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 844.0,\n      'datetime': datetime.datetime(2023, 11, 5, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 823.0,\n      'datetime': datetime.datetime(2023, 11, 5, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 797.0,\n      'datetime': datetime.datetime(2023, 11, 5, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 774.0,\n      'datetime': datetime.datetime(2023, 11, 5, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 752.0,\n      'datetime': datetime.datetime(2023, 11, 5, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 721.0,\n      'datetime': datetime.datetime(2023, 11, 5, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 695.0,\n      'datetime': datetime.datetime(2023, 11, 5, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 669.0,\n      'datetime': datetime.datetime(2023, 11, 5, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 648.0,\n      'datetime': datetime.datetime(2023, 11, 5, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 626.0,\n      'datetime': datetime.datetime(2023, 11, 5, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 611.0,\n      'datetime': datetime.datetime(2023, 11, 5, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 591.0,\n      'datetime': datetime.datetime(2023, 11, 6, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 574.0,\n      'datetime': datetime.datetime(2023, 11, 6, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 554.0,\n      'datetime': datetime.datetime(2023, 11, 6, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 544.0,\n      'datetime': datetime.datetime(2023, 11, 6, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 559.0,\n      'datetime': datetime.datetime(2023, 11, 6, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 580.0,\n      'datetime': datetime.datetime(2023, 11, 6, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 570.0,\n      'datetime': datetime.datetime(2023, 11, 6, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 567.0,\n      'datetime': datetime.datetime(2023, 11, 6, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 567.0,\n      'datetime': datetime.datetime(2023, 11, 6, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 564.0,\n      'datetime': datetime.datetime(2023, 11, 6, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 562.0,\n      'datetime': datetime.datetime(2023, 11, 6, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 559.0,\n      'datetime': datetime.datetime(2023, 11, 6, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 552.0,\n      'datetime': datetime.datetime(2023, 11, 6, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 553.0,\n      'datetime': datetime.datetime(2023, 11, 6, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 549.0,\n      'datetime': datetime.datetime(2023, 11, 6, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 545.0,\n      'datetime': datetime.datetime(2023, 11, 6, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 547.0,\n      'datetime': datetime.datetime(2023, 11, 6, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 560.0,\n      'datetime': datetime.datetime(2023, 11, 6, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 553.0,\n      'datetime': datetime.datetime(2023, 11, 6, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 556.0,\n      'datetime': datetime.datetime(2023, 11, 6, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 559.0,\n      'datetime': datetime.datetime(2023, 11, 6, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 576.0,\n      'datetime': datetime.datetime(2023, 11, 6, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 582.0,\n      'datetime': datetime.datetime(2023, 11, 6, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 602.0,\n      'datetime': datetime.datetime(2023, 11, 6, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 631.0,\n      'datetime': datetime.datetime(2023, 11, 6, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 683.0,\n      'datetime': datetime.datetime(2023, 11, 6, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 719.0,\n      'datetime': datetime.datetime(2023, 11, 6, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 768.0,\n      'datetime': datetime.datetime(2023, 11, 6, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 815.0,\n      'datetime': datetime.datetime(2023, 11, 6, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 889.0,\n      'datetime': datetime.datetime(2023, 11, 6, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 931.0,\n      'datetime': datetime.datetime(2023, 11, 6, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 968.0,\n      'datetime': datetime.datetime(2023, 11, 6, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1007.0,\n      'datetime': datetime.datetime(2023, 11, 6, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1027.0,\n      'datetime': datetime.datetime(2023, 11, 6, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1035.0,\n      'datetime': datetime.datetime(2023, 11, 6, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1048.0,\n      'datetime': datetime.datetime(2023, 11, 6, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1074.0,\n      'datetime': datetime.datetime(2023, 11, 6, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1080.0,\n      'datetime': datetime.datetime(2023, 11, 6, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1083.0,\n      'datetime': datetime.datetime(2023, 11, 6, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1081.0,\n      'datetime': datetime.datetime(2023, 11, 6, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1080.0,\n      'datetime': datetime.datetime(2023, 11, 6, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1072.0,\n      'datetime': datetime.datetime(2023, 11, 6, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1079.0,\n      'datetime': datetime.datetime(2023, 11, 6, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1071.0,\n      'datetime': datetime.datetime(2023, 11, 6, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1055.0,\n      'datetime': datetime.datetime(2023, 11, 6, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1044.0,\n      'datetime': datetime.datetime(2023, 11, 6, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1035.0,\n      'datetime': datetime.datetime(2023, 11, 6, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1019.0,\n      'datetime': datetime.datetime(2023, 11, 6, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1032.0,\n      'datetime': datetime.datetime(2023, 11, 6, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1035.0,\n      'datetime': datetime.datetime(2023, 11, 6, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1033.0,\n      'datetime': datetime.datetime(2023, 11, 6, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1035.0,\n      'datetime': datetime.datetime(2023, 11, 6, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1027.0,\n      'datetime': datetime.datetime(2023, 11, 6, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1011.0,\n      'datetime': datetime.datetime(2023, 11, 6, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1004.0,\n      'datetime': datetime.datetime(2023, 11, 6, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1000.0,\n      'datetime': datetime.datetime(2023, 11, 6, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1002.0,\n      'datetime': datetime.datetime(2023, 11, 6, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 997.0,\n      'datetime': datetime.datetime(2023, 11, 6, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 994.0,\n      'datetime': datetime.datetime(2023, 11, 6, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 994.0,\n      'datetime': datetime.datetime(2023, 11, 6, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 989.0,\n      'datetime': datetime.datetime(2023, 11, 6, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1010.0,\n      'datetime': datetime.datetime(2023, 11, 6, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1019.0,\n      'datetime': datetime.datetime(2023, 11, 6, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1040.0,\n      'datetime': datetime.datetime(2023, 11, 6, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1053.0,\n      'datetime': datetime.datetime(2023, 11, 6, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1080.0,\n      'datetime': datetime.datetime(2023, 11, 6, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'consumption': 1118.0,\n      'datetime': datetime.datetime(2023, 11, 6, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'GB-NIR',\n    }),\n  ])\n# ---\n# name: test_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': 4407.0,\n      'datetime': datetime.datetime(2023, 11, 9, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4364.0,\n      'datetime': datetime.datetime(2023, 11, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4371.0,\n      'datetime': datetime.datetime(2023, 11, 9, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4358.0,\n      'datetime': datetime.datetime(2023, 11, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4403.0,\n      'datetime': datetime.datetime(2023, 11, 9, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4384.0,\n      'datetime': datetime.datetime(2023, 11, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4345.0,\n      'datetime': datetime.datetime(2023, 11, 9, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4325.0,\n      'datetime': datetime.datetime(2023, 11, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4359.0,\n      'datetime': datetime.datetime(2023, 11, 9, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4410.0,\n      'datetime': datetime.datetime(2023, 11, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4482.0,\n      'datetime': datetime.datetime(2023, 11, 9, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4534.0,\n      'datetime': datetime.datetime(2023, 11, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4650.0,\n      'datetime': datetime.datetime(2023, 11, 9, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4850.0,\n      'datetime': datetime.datetime(2023, 11, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4970.0,\n      'datetime': datetime.datetime(2023, 11, 9, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4976.0,\n      'datetime': datetime.datetime(2023, 11, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4912.0,\n      'datetime': datetime.datetime(2023, 11, 9, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4834.0,\n      'datetime': datetime.datetime(2023, 11, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4753.0,\n      'datetime': datetime.datetime(2023, 11, 9, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4618.0,\n      'datetime': datetime.datetime(2023, 11, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4513.0,\n      'datetime': datetime.datetime(2023, 11, 9, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4454.0,\n      'datetime': datetime.datetime(2023, 11, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4238.0,\n      'datetime': datetime.datetime(2023, 11, 9, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 4096.0,\n      'datetime': datetime.datetime(2023, 11, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 3933.0,\n      'datetime': datetime.datetime(2023, 11, 9, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 3813.0,\n      'datetime': datetime.datetime(2023, 11, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 3717.0,\n      'datetime': datetime.datetime(2023, 11, 9, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'consumption': 3511.0,\n      'datetime': datetime.datetime(2023, 11, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'IE',\n    }),\n  ])\n# ---\n# name: test_fetch_exchange\n  list([\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(369.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(426.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(369.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(344.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(274.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(127.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(173.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(222.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(148.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(72.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-3.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-78.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-5.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(8.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(84.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(160.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(235.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(309.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(380.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(335.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(409.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(406.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(333.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(259.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(195.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(269.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(321.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(347.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(362.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(290.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(216.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(143.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(66.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-4.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-4.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-78.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-152.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-80.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-5.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-78.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-152.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 7, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-228.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-304.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-381.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-381.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-407.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-407.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-407.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-391.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-318.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-273.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-270.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-265.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-264.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-220.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-151.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-77.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-4.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-4.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(70.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(147.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(222.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(296.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(370.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(420.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(340.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(226.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(172.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(189.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(113.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(38.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(45.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(120.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(129.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(147.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(222.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(296.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(370.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(399.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(326.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(252.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(181.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(107.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(32.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 8, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-43.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-118.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-193.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-269.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-345.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-331.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-255.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-212.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-157.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-185.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-224.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-147.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-132.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-209.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-285.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-273.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-233.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-310.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-386.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-408.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-333.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-257.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-184.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-109.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-34.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(-3.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(70.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(147.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(222.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(296.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(370.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(441.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2023, 11, 9, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'netFlow': np.float64(442.0),\n      'sortedZoneKeys': 'GB->GB-NIR',\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n# name: test_fetch_generation\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2180.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2166.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2076.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2046.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2058.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2031.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1990.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1960.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1952.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2007.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1973.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1971.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1954.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1958.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1957.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1928.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1923.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1938.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1926.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1905.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1904.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1913.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1818.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1826.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1826.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1866.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1933.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 1999.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2194.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2407.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2484.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2493.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2525.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2589.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2572.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2634.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2633.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2698.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2756.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2768.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2787.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2821.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2888.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2868.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2817.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2845.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2939.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3039.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3100.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3229.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3277.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3338.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3349.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3383.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3375.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3339.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3393.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3431.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3400.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3437.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3448.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3381.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3339.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3365.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3222.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3111.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3017.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3057.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2943.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 2934.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3064.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3178.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3173.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3087.0,\n      'zoneKey': 'GB-NIR',\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 6, 4, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'value': 3062.0,\n      'zoneKey': 'GB-NIR',\n    }),\n  ])\n# ---\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 649,\n        'wind': 1527,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 654,\n        'wind': 1508,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 638,\n        'wind': 1434,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 683,\n        'wind': 1359,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 678,\n        'wind': 1376,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 688,\n        'wind': 1339,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 681,\n        'wind': 1305,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 676,\n        'wind': 1280,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 666,\n        'wind': 1282,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 685,\n        'wind': 1318,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 683,\n        'wind': 1286,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 675,\n        'wind': 1292,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 679,\n        'wind': 1271,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 684,\n        'wind': 1270,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 677,\n        'wind': 1276,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 665,\n        'wind': 1259,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 686,\n        'wind': 1233,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 695,\n        'wind': 1239,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 681,\n        'wind': 1241,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 688,\n        'wind': 1213,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 4,\n        'unknown': 690,\n        'wind': 1210,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 6,\n        'unknown': 676,\n        'wind': 1231,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 11,\n        'unknown': 678,\n        'wind': 1129,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 21,\n        'unknown': 666,\n        'wind': 1139,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 35,\n        'unknown': 659,\n        'wind': 1132,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 63,\n        'unknown': 716,\n        'wind': 1087,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 84,\n        'unknown': 762,\n        'wind': 1087,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 109,\n        'unknown': 852,\n        'wind': 1038,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 136,\n        'unknown': 985,\n        'wind': 1073,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 181,\n        'unknown': 1158,\n        'wind': 1068,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 221,\n        'unknown': 1242,\n        'wind': 1021,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 267,\n        'unknown': 1249,\n        'wind': 977,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 320,\n        'unknown': 1190,\n        'wind': 1015,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 382,\n        'unknown': 1192,\n        'wind': 1015,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 434,\n        'unknown': 1038,\n        'wind': 1100,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 511,\n        'unknown': 968,\n        'wind': 1155,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 507,\n        'unknown': 898,\n        'wind': 1228,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 537,\n        'unknown': 864,\n        'wind': 1297,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 526,\n        'unknown': 1008,\n        'wind': 1222,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 532,\n        'unknown': 1007,\n        'wind': 1229,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 536,\n        'unknown': 984,\n        'wind': 1267,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 554,\n        'unknown': 969,\n        'wind': 1298,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 539,\n        'unknown': 972,\n        'wind': 1377,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 607,\n        'unknown': 773,\n        'wind': 1488,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 578,\n        'unknown': 799,\n        'wind': 1440,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 572,\n        'unknown': 823,\n        'wind': 1450,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 586,\n        'unknown': 841,\n        'wind': 1512,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 586,\n        'unknown': 828,\n        'wind': 1625,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 565,\n        'unknown': 853,\n        'wind': 1682,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 616,\n        'unknown': 912,\n        'wind': 1701,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 559,\n        'unknown': 1027,\n        'wind': 1691,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 582,\n        'unknown': 1013,\n        'wind': 1743,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 533,\n        'unknown': 1099,\n        'wind': 1717,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 574,\n        'unknown': 1181,\n        'wind': 1628,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 454,\n        'unknown': 1148,\n        'wind': 1773,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 511,\n        'unknown': 1036,\n        'wind': 1792,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 521,\n        'unknown': 1011,\n        'wind': 1861,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 479,\n        'unknown': 1005,\n        'wind': 1947,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 475,\n        'unknown': 1064,\n        'wind': 1861,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 425,\n        'unknown': 1046,\n        'wind': 1966,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 446,\n        'unknown': 1042,\n        'wind': 1960,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 457,\n        'unknown': 978,\n        'wind': 1946,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 428,\n        'unknown': 1065,\n        'wind': 1846,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 466,\n        'unknown': 1080,\n        'wind': 1819,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 467,\n        'unknown': 1046,\n        'wind': 1709,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 488,\n        'unknown': 924,\n        'wind': 1699,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 436,\n        'unknown': 930,\n        'wind': 1651,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 507,\n        'unknown': 926,\n        'wind': 1624,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 477,\n        'unknown': 863,\n        'wind': 1603,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 369,\n        'unknown': 981,\n        'wind': 1584,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 308,\n        'unknown': 1223,\n        'wind': 1533,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 282,\n        'unknown': 1388,\n        'wind': 1508,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 239,\n        'unknown': 1432,\n        'wind': 1502,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 186,\n        'unknown': 1404,\n        'wind': 1497,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 191,\n        'unknown': 1346,\n        'wind': 1525,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n  ])\n# ---\n# name: test_fetch_wind_solar_forecasts\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1419,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1434,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1449,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1464,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1387,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1405,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1423,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1441,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1459,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1466,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1473,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1479,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1486,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1487,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1488,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1489,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1490,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1476,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1463,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1449,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1435,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 5,\n        'wind': 1392,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 10,\n        'wind': 1349,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 15,\n        'wind': 1306,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 20,\n        'wind': 1263,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 53,\n        'wind': 1253,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 87,\n        'wind': 1244,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 120,\n        'wind': 1235,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 168,\n        'wind': 1103,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 220,\n        'wind': 1134,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 272,\n        'wind': 1166,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 324,\n        'wind': 1197,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 376,\n        'wind': 1229,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 417,\n        'wind': 1287,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 458,\n        'wind': 1345,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 499,\n        'wind': 1403,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 540,\n        'wind': 1462,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 568,\n        'wind': 1502,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 597,\n        'wind': 1542,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 625,\n        'wind': 1582,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 654,\n        'wind': 1622,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 666,\n        'wind': 1647,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 679,\n        'wind': 1672,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 691,\n        'wind': 1696,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 704,\n        'wind': 1721,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 11, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 706,\n        'wind': 1763,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 11, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 709,\n        'wind': 1805,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 711,\n        'wind': 1847,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 714,\n        'wind': 1890,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 12, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 711,\n        'wind': 1914,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 12, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 708,\n        'wind': 1938,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 705,\n        'wind': 1963,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 672,\n        'wind': 1840,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 669,\n        'wind': 1856,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 665,\n        'wind': 1873,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 662,\n        'wind': 1889,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 659,\n        'wind': 1906,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 14, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 639,\n        'wind': 1879,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 620,\n        'wind': 1853,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 14, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 600,\n        'wind': 1827,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 581,\n        'wind': 1801,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 522,\n        'wind': 1776,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 462,\n        'wind': 1752,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 403,\n        'wind': 1727,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 344,\n        'wind': 1703,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 318,\n        'wind': 1673,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 293,\n        'wind': 1644,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 267,\n        'wind': 1614,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 242,\n        'wind': 1585,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 222,\n        'wind': 1540,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 202,\n        'wind': 1495,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 182,\n        'wind': 1451,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 162,\n        'wind': 1406,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 141,\n        'wind': 1371,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 121,\n        'wind': 1336,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 101,\n        'wind': 1301,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 80,\n        'wind': 1266,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 67,\n        'wind': 1217,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 53,\n        'wind': 1168,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 40,\n        'wind': 1120,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 26,\n        'wind': 1071,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 20,\n        'wind': 1054,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 13,\n        'wind': 1037,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 7,\n        'wind': 1019,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1002,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1015,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1028,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1040,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1053,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1067,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1081,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1095,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1109,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1097,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1085,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 6, 4, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='Europe/Dublin')),\n      'production': dict({\n        'solar': 0,\n        'wind': 1073,\n      }),\n      'source': 'eirgridgroup.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IE',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_TAIPOWER.ambr",
    "content": "# serializer version: 1\n# name: test_production\n  list([\n    dict({\n      'capacity': dict({\n        'biomass': 60.7,\n        'coal': 13108.6,\n        'gas': 17871.300000000003,\n        'geothermal': 7.2,\n        'hydro': 2123.8999999999996,\n        'nuclear': 951.0,\n        'oil': 1591.9,\n        'solar': 14053.699999999999,\n        'unknown': 631.4,\n        'wind': 2873.8,\n      }),\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 5, 14, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='Asia/Taipei')),\n      'production': dict({\n        'biomass': 31.9,\n        'coal': 8637.7,\n        'gas': 15355.7,\n        'geothermal': 2.3,\n        'hydro': 1157.9,\n        'nuclear': 841.4,\n        'oil': 419.8,\n        'solar': 6775.989,\n        'unknown': 1791.3,\n        'wind': 181.9,\n      }),\n      'source': 'taipower.com.tw',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': 5.2,\n        'hydro': 474.0,\n      }),\n      'zoneKey': 'TW',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_TR/test_fetch_production[None].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production[None]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 891.87,\n        'coal': 15107.56,\n        'gas': 16407.06,\n        'geothermal': 1078.11,\n        'hydro': 11479.21,\n        'oil': 93.95,\n        'solar': 0.01,\n        'unknown': 97.4,\n        'wind': 689.05,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 885.66,\n        'coal': 15035.1,\n        'gas': 16380.9,\n        'geothermal': 1094.75,\n        'hydro': 9585.67,\n        'oil': 93.75,\n        'solar': 0.01,\n        'unknown': 98.15,\n        'wind': 616.6,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 878.79,\n        'coal': 15062.47,\n        'gas': 16634.73,\n        'geothermal': 1114.73,\n        'hydro': 7445.58,\n        'oil': 90.75,\n        'solar': 0.01,\n        'unknown': 97.33,\n        'wind': 629.53,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 885.39,\n        'coal': 15111.17,\n        'gas': 16612.92,\n        'geothermal': 1124.57,\n        'hydro': 6217.93,\n        'oil': 88.75,\n        'solar': 0.01,\n        'unknown': 98.78,\n        'wind': 580.13,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 887.61,\n        'coal': 15177.42,\n        'gas': 16509.65,\n        'geothermal': 1148.29,\n        'hydro': 5312.72,\n        'oil': 89.05,\n        'solar': 0.01,\n        'unknown': 101.66,\n        'wind': 606.15,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 885.41,\n        'coal': 15202.28,\n        'gas': 16147.88,\n        'geothermal': 1161.82,\n        'hydro': 4378.96,\n        'oil': 92.05,\n        'solar': 2.51,\n        'unknown': 96.54,\n        'wind': 531.5,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 874.08,\n        'coal': 15240.35,\n        'gas': 15747.7,\n        'geothermal': 1162.27,\n        'hydro': 3393.91,\n        'oil': 94.46,\n        'solar': 242.4,\n        'unknown': 98.79,\n        'wind': 544.84,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 782.14,\n        'coal': 13667.03,\n        'gas': 15137.64,\n        'geothermal': 994.27,\n        'hydro': 3419.48,\n        'oil': 91.75,\n        'solar': 1119.42,\n        'unknown': 97.46,\n        'wind': 662.94,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 676.7,\n        'coal': 12974.64,\n        'gas': 15493.45,\n        'geothermal': 896.28,\n        'hydro': 6467.39,\n        'oil': 42.94,\n        'solar': 1704.16,\n        'unknown': 94.44,\n        'wind': 610.03,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_TR/test_fetch_production[target_datetime1].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production[target_datetime1]\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 891.87,\n        'coal': 15107.56,\n        'gas': 16407.06,\n        'geothermal': 1078.11,\n        'hydro': 11479.21,\n        'oil': 93.95,\n        'solar': 0.01,\n        'unknown': 97.4,\n        'wind': 689.05,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 885.66,\n        'coal': 15035.1,\n        'gas': 16380.9,\n        'geothermal': 1094.75,\n        'hydro': 9585.67,\n        'oil': 93.75,\n        'solar': 0.01,\n        'unknown': 98.15,\n        'wind': 616.6,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 878.79,\n        'coal': 15062.47,\n        'gas': 16634.73,\n        'geothermal': 1114.73,\n        'hydro': 7445.58,\n        'oil': 90.75,\n        'solar': 0.01,\n        'unknown': 97.33,\n        'wind': 629.53,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 885.39,\n        'coal': 15111.17,\n        'gas': 16612.92,\n        'geothermal': 1124.57,\n        'hydro': 6217.93,\n        'oil': 88.75,\n        'solar': 0.01,\n        'unknown': 98.78,\n        'wind': 580.13,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 887.61,\n        'coal': 15177.42,\n        'gas': 16509.65,\n        'geothermal': 1148.29,\n        'hydro': 5312.72,\n        'oil': 89.05,\n        'solar': 0.01,\n        'unknown': 101.66,\n        'wind': 606.15,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 885.41,\n        'coal': 15202.28,\n        'gas': 16147.88,\n        'geothermal': 1161.82,\n        'hydro': 4378.96,\n        'oil': 92.05,\n        'solar': 2.51,\n        'unknown': 96.54,\n        'wind': 531.5,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 874.08,\n        'coal': 15240.35,\n        'gas': 15747.7,\n        'geothermal': 1162.27,\n        'hydro': 3393.91,\n        'oil': 94.46,\n        'solar': 242.4,\n        'unknown': 98.79,\n        'wind': 544.84,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 782.14,\n        'coal': 13667.03,\n        'gas': 15137.64,\n        'geothermal': 994.27,\n        'hydro': 3419.48,\n        'oil': 91.75,\n        'solar': 1119.42,\n        'unknown': 97.46,\n        'wind': 662.94,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 676.7,\n        'coal': 12974.64,\n        'gas': 15493.45,\n        'geothermal': 896.28,\n        'hydro': 6467.39,\n        'oil': 42.94,\n        'solar': 1704.16,\n        'unknown': 94.44,\n        'wind': 610.03,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 7, 28, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(seconds=10800))),\n      'production': dict({\n        'biomass': 609.08,\n        'coal': 10958.72,\n        'gas': 15111.99,\n        'geothermal': 835.9,\n        'hydro': 7536.73,\n        'oil': 1.74,\n        'solar': 2121.44,\n        'unknown': 91.28,\n        'wind': 531,\n      }),\n      'source': 'epias.com.tr',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'TR',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_US_CA.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': 21213.16,\n      'datetime': datetime.datetime(2025, 2, 19, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20663.34,\n      'datetime': datetime.datetime(2025, 2, 19, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20138.61,\n      'datetime': datetime.datetime(2025, 2, 19, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20079.09,\n      'datetime': datetime.datetime(2025, 2, 19, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20556.03,\n      'datetime': datetime.datetime(2025, 2, 19, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21961.85,\n      'datetime': datetime.datetime(2025, 2, 19, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23967.14,\n      'datetime': datetime.datetime(2025, 2, 19, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24693.13,\n      'datetime': datetime.datetime(2025, 2, 19, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23366.31,\n      'datetime': datetime.datetime(2025, 2, 19, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21464.76,\n      'datetime': datetime.datetime(2025, 2, 19, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19656.13,\n      'datetime': datetime.datetime(2025, 2, 19, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18540.3,\n      'datetime': datetime.datetime(2025, 2, 19, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18150.62,\n      'datetime': datetime.datetime(2025, 2, 19, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18428.91,\n      'datetime': datetime.datetime(2025, 2, 19, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19257.95,\n      'datetime': datetime.datetime(2025, 2, 19, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20632.21,\n      'datetime': datetime.datetime(2025, 2, 19, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22549.41,\n      'datetime': datetime.datetime(2025, 2, 20, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24906.53,\n      'datetime': datetime.datetime(2025, 2, 20, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 26191.41,\n      'datetime': datetime.datetime(2025, 2, 20, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25852.37,\n      'datetime': datetime.datetime(2025, 2, 20, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25262.46,\n      'datetime': datetime.datetime(2025, 2, 20, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24510.65,\n      'datetime': datetime.datetime(2025, 2, 20, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23123.04,\n      'datetime': datetime.datetime(2025, 2, 20, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21708.38,\n      'datetime': datetime.datetime(2025, 2, 20, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21382.89,\n      'datetime': datetime.datetime(2025, 2, 20, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20731.98,\n      'datetime': datetime.datetime(2025, 2, 20, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20174.13,\n      'datetime': datetime.datetime(2025, 2, 20, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20025.92,\n      'datetime': datetime.datetime(2025, 2, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20526.13,\n      'datetime': datetime.datetime(2025, 2, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22041.72,\n      'datetime': datetime.datetime(2025, 2, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24076.63,\n      'datetime': datetime.datetime(2025, 2, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24981.01,\n      'datetime': datetime.datetime(2025, 2, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23771.25,\n      'datetime': datetime.datetime(2025, 2, 20, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21942.57,\n      'datetime': datetime.datetime(2025, 2, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20112.77,\n      'datetime': datetime.datetime(2025, 2, 20, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18919.5,\n      'datetime': datetime.datetime(2025, 2, 20, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18460.87,\n      'datetime': datetime.datetime(2025, 2, 20, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18624.22,\n      'datetime': datetime.datetime(2025, 2, 20, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19541.83,\n      'datetime': datetime.datetime(2025, 2, 20, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21101.48,\n      'datetime': datetime.datetime(2025, 2, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23045.71,\n      'datetime': datetime.datetime(2025, 2, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25347.4,\n      'datetime': datetime.datetime(2025, 2, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 26557.09,\n      'datetime': datetime.datetime(2025, 2, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 26171.69,\n      'datetime': datetime.datetime(2025, 2, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25587.89,\n      'datetime': datetime.datetime(2025, 2, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24827.2,\n      'datetime': datetime.datetime(2025, 2, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23461.32,\n      'datetime': datetime.datetime(2025, 2, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22060.18,\n      'datetime': datetime.datetime(2025, 2, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21374.2,\n      'datetime': datetime.datetime(2025, 2, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20742.17,\n      'datetime': datetime.datetime(2025, 2, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20188.27,\n      'datetime': datetime.datetime(2025, 2, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20038.82,\n      'datetime': datetime.datetime(2025, 2, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20621.26,\n      'datetime': datetime.datetime(2025, 2, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21926.21,\n      'datetime': datetime.datetime(2025, 2, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23895.14,\n      'datetime': datetime.datetime(2025, 2, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24664.26,\n      'datetime': datetime.datetime(2025, 2, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23564.4,\n      'datetime': datetime.datetime(2025, 2, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21612.77,\n      'datetime': datetime.datetime(2025, 2, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19842.83,\n      'datetime': datetime.datetime(2025, 2, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18684.28,\n      'datetime': datetime.datetime(2025, 2, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18206.24,\n      'datetime': datetime.datetime(2025, 2, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18310.7,\n      'datetime': datetime.datetime(2025, 2, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19074.62,\n      'datetime': datetime.datetime(2025, 2, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20664.06,\n      'datetime': datetime.datetime(2025, 2, 21, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22668.84,\n      'datetime': datetime.datetime(2025, 2, 22, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24923.98,\n      'datetime': datetime.datetime(2025, 2, 22, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25845.56,\n      'datetime': datetime.datetime(2025, 2, 22, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25401.27,\n      'datetime': datetime.datetime(2025, 2, 22, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24801.28,\n      'datetime': datetime.datetime(2025, 2, 22, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24175.14,\n      'datetime': datetime.datetime(2025, 2, 22, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23022.49,\n      'datetime': datetime.datetime(2025, 2, 22, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21885.44,\n      'datetime': datetime.datetime(2025, 2, 22, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21073.54,\n      'datetime': datetime.datetime(2025, 2, 22, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20367.53,\n      'datetime': datetime.datetime(2025, 2, 22, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19715.29,\n      'datetime': datetime.datetime(2025, 2, 22, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19405.35,\n      'datetime': datetime.datetime(2025, 2, 22, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19522.0,\n      'datetime': datetime.datetime(2025, 2, 22, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20093.54,\n      'datetime': datetime.datetime(2025, 2, 22, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20895.47,\n      'datetime': datetime.datetime(2025, 2, 22, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20849.71,\n      'datetime': datetime.datetime(2025, 2, 22, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19777.45,\n      'datetime': datetime.datetime(2025, 2, 22, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 17866.79,\n      'datetime': datetime.datetime(2025, 2, 22, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 16293.64,\n      'datetime': datetime.datetime(2025, 2, 22, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 15226.74,\n      'datetime': datetime.datetime(2025, 2, 22, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 14818.93,\n      'datetime': datetime.datetime(2025, 2, 22, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 15000.6,\n      'datetime': datetime.datetime(2025, 2, 22, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 15990.15,\n      'datetime': datetime.datetime(2025, 2, 22, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 17749.57,\n      'datetime': datetime.datetime(2025, 2, 22, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20174.77,\n      'datetime': datetime.datetime(2025, 2, 23, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22820.9,\n      'datetime': datetime.datetime(2025, 2, 23, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24078.8,\n      'datetime': datetime.datetime(2025, 2, 23, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23794.44,\n      'datetime': datetime.datetime(2025, 2, 23, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23309.35,\n      'datetime': datetime.datetime(2025, 2, 23, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22769.59,\n      'datetime': datetime.datetime(2025, 2, 23, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21834.38,\n      'datetime': datetime.datetime(2025, 2, 23, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20810.69,\n      'datetime': datetime.datetime(2025, 2, 23, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20334.89,\n      'datetime': datetime.datetime(2025, 2, 23, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19714.32,\n      'datetime': datetime.datetime(2025, 2, 23, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19098.89,\n      'datetime': datetime.datetime(2025, 2, 23, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18787.73,\n      'datetime': datetime.datetime(2025, 2, 23, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18816.98,\n      'datetime': datetime.datetime(2025, 2, 23, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19191.84,\n      'datetime': datetime.datetime(2025, 2, 23, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19775.2,\n      'datetime': datetime.datetime(2025, 2, 23, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19443.53,\n      'datetime': datetime.datetime(2025, 2, 23, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 17953.72,\n      'datetime': datetime.datetime(2025, 2, 23, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 16057.35,\n      'datetime': datetime.datetime(2025, 2, 23, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 14606.97,\n      'datetime': datetime.datetime(2025, 2, 23, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 13775.34,\n      'datetime': datetime.datetime(2025, 2, 23, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 13665.41,\n      'datetime': datetime.datetime(2025, 2, 23, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 14031.37,\n      'datetime': datetime.datetime(2025, 2, 23, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 15132.83,\n      'datetime': datetime.datetime(2025, 2, 23, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 17062.52,\n      'datetime': datetime.datetime(2025, 2, 23, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19902.16,\n      'datetime': datetime.datetime(2025, 2, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22495.53,\n      'datetime': datetime.datetime(2025, 2, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24066.14,\n      'datetime': datetime.datetime(2025, 2, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23812.41,\n      'datetime': datetime.datetime(2025, 2, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23300.29,\n      'datetime': datetime.datetime(2025, 2, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22613.76,\n      'datetime': datetime.datetime(2025, 2, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21412.12,\n      'datetime': datetime.datetime(2025, 2, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20285.8,\n      'datetime': datetime.datetime(2025, 2, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19746.28,\n      'datetime': datetime.datetime(2025, 2, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19124.88,\n      'datetime': datetime.datetime(2025, 2, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18650.86,\n      'datetime': datetime.datetime(2025, 2, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18558.46,\n      'datetime': datetime.datetime(2025, 2, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19059.28,\n      'datetime': datetime.datetime(2025, 2, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20428.72,\n      'datetime': datetime.datetime(2025, 2, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22322.32,\n      'datetime': datetime.datetime(2025, 2, 24, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23345.28,\n      'datetime': datetime.datetime(2025, 2, 24, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22289.73,\n      'datetime': datetime.datetime(2025, 2, 24, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20660.81,\n      'datetime': datetime.datetime(2025, 2, 24, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19319.09,\n      'datetime': datetime.datetime(2025, 2, 24, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18544.9,\n      'datetime': datetime.datetime(2025, 2, 24, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18301.22,\n      'datetime': datetime.datetime(2025, 2, 24, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18699.81,\n      'datetime': datetime.datetime(2025, 2, 24, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19636.67,\n      'datetime': datetime.datetime(2025, 2, 24, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21348.69,\n      'datetime': datetime.datetime(2025, 2, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23504.7,\n      'datetime': datetime.datetime(2025, 2, 25, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25775.43,\n      'datetime': datetime.datetime(2025, 2, 25, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 26854.75,\n      'datetime': datetime.datetime(2025, 2, 25, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 26230.64,\n      'datetime': datetime.datetime(2025, 2, 25, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25419.54,\n      'datetime': datetime.datetime(2025, 2, 25, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24476.64,\n      'datetime': datetime.datetime(2025, 2, 25, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22928.22,\n      'datetime': datetime.datetime(2025, 2, 25, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21482.71,\n      'datetime': datetime.datetime(2025, 2, 25, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20876.39,\n      'datetime': datetime.datetime(2025, 2, 25, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20377.57,\n      'datetime': datetime.datetime(2025, 2, 25, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19801.02,\n      'datetime': datetime.datetime(2025, 2, 25, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19571.6,\n      'datetime': datetime.datetime(2025, 2, 25, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19961.2,\n      'datetime': datetime.datetime(2025, 2, 25, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21112.13,\n      'datetime': datetime.datetime(2025, 2, 25, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22702.79,\n      'datetime': datetime.datetime(2025, 2, 25, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23309.95,\n      'datetime': datetime.datetime(2025, 2, 25, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22566.16,\n      'datetime': datetime.datetime(2025, 2, 25, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21157.91,\n      'datetime': datetime.datetime(2025, 2, 25, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19749.62,\n      'datetime': datetime.datetime(2025, 2, 25, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18885.25,\n      'datetime': datetime.datetime(2025, 2, 25, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18592.16,\n      'datetime': datetime.datetime(2025, 2, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18774.9,\n      'datetime': datetime.datetime(2025, 2, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19564.52,\n      'datetime': datetime.datetime(2025, 2, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21340.85,\n      'datetime': datetime.datetime(2025, 2, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23559.35,\n      'datetime': datetime.datetime(2025, 2, 26, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25908.95,\n      'datetime': datetime.datetime(2025, 2, 26, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 27085.62,\n      'datetime': datetime.datetime(2025, 2, 26, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 26513.45,\n      'datetime': datetime.datetime(2025, 2, 26, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25725.82,\n      'datetime': datetime.datetime(2025, 2, 26, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24759.64,\n      'datetime': datetime.datetime(2025, 2, 26, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23277.29,\n      'datetime': datetime.datetime(2025, 2, 26, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21807.51,\n      'datetime': datetime.datetime(2025, 2, 26, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21157.86,\n      'datetime': datetime.datetime(2025, 2, 26, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20378.64,\n      'datetime': datetime.datetime(2025, 2, 26, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19694.86,\n      'datetime': datetime.datetime(2025, 2, 26, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19288.13,\n      'datetime': datetime.datetime(2025, 2, 26, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19727.61,\n      'datetime': datetime.datetime(2025, 2, 26, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21006.95,\n      'datetime': datetime.datetime(2025, 2, 26, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22888.88,\n      'datetime': datetime.datetime(2025, 2, 26, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23393.9,\n      'datetime': datetime.datetime(2025, 2, 26, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 22083.35,\n      'datetime': datetime.datetime(2025, 2, 26, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 20518.1,\n      'datetime': datetime.datetime(2025, 2, 26, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19140.9,\n      'datetime': datetime.datetime(2025, 2, 26, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18390.88,\n      'datetime': datetime.datetime(2025, 2, 26, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18276.37,\n      'datetime': datetime.datetime(2025, 2, 26, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 18668.42,\n      'datetime': datetime.datetime(2025, 2, 26, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 19691.99,\n      'datetime': datetime.datetime(2025, 2, 26, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21643.39,\n      'datetime': datetime.datetime(2025, 2, 26, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23948.52,\n      'datetime': datetime.datetime(2025, 2, 27, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 26125.08,\n      'datetime': datetime.datetime(2025, 2, 27, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 27079.34,\n      'datetime': datetime.datetime(2025, 2, 27, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 26352.94,\n      'datetime': datetime.datetime(2025, 2, 27, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 25576.0,\n      'datetime': datetime.datetime(2025, 2, 27, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 24800.72,\n      'datetime': datetime.datetime(2025, 2, 27, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 23287.91,\n      'datetime': datetime.datetime(2025, 2, 27, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'consumption': 21901.0,\n      'datetime': datetime.datetime(2025, 2, 27, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-CAL-CISO',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_wind_solar_forecasts\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1441.49),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1511.57),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1597.35),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1661.9),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1698.41),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1759.98),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(176.29),\n        'wind': np.float64(1805.18),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(3587.88),\n        'wind': np.float64(1823.96),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(9548.31),\n        'wind': np.float64(1856.04),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12510.99),\n        'wind': np.float64(1941.97),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(13077.41),\n        'wind': np.float64(2070.87),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(13176.7),\n        'wind': np.float64(2226.03),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(13021.82),\n        'wind': np.float64(2392.23),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12739.9),\n        'wind': np.float64(2497.63),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12055.46),\n        'wind': np.float64(2512.61),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 4, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(9058.1),\n        'wind': np.float64(2417.22),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(3352.77),\n        'wind': np.float64(2279.12),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(139.82),\n        'wind': np.float64(2186.31),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2137.07),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2172.01),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2272.45),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2365.42),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2391.46),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2348.55),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2282.19),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2016.47),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1769.79),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1557.87),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1370.14),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1256.38),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(250.5),\n        'wind': np.float64(1212.42),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(3329.73),\n        'wind': np.float64(1176.35),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(8457.56),\n        'wind': np.float64(1140.48),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(11312.82),\n        'wind': np.float64(1141.03),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12326.96),\n        'wind': np.float64(1152.42),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12897.99),\n        'wind': np.float64(1187.54),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(13239.03),\n        'wind': np.float64(1265.07),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(13495.39),\n        'wind': np.float64(1332.4),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(13478.47),\n        'wind': np.float64(1350.91),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(10984.17),\n        'wind': np.float64(1324.47),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(4575.01),\n        'wind': np.float64(1272.57),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(323.68),\n        'wind': np.float64(1207.01),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1138.57),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1059.24),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(992.6),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(961.93),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(920.79),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(872.13),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(912.0),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(960.23),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1011.53),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1049.57),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1051.39),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1026.2),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(270.44),\n        'wind': np.float64(1047.76),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(3658.64),\n        'wind': np.float64(1133.33),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(9196.12),\n        'wind': np.float64(1256.3),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(11864.97),\n        'wind': np.float64(1388.49),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12272.21),\n        'wind': np.float64(1535.81),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12210.42),\n        'wind': np.float64(1704.51),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(11951.22),\n        'wind': np.float64(1858.77),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(11560.7),\n        'wind': np.float64(1971.76),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(10828.85),\n        'wind': np.float64(2057.23),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 6, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(8148.44),\n        'wind': np.float64(2063.23),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(3065.89),\n        'wind': np.float64(2023.43),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(135.02),\n        'wind': np.float64(2013.51),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1990.0),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1951.41),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1952.21),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1968.45),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1959.09),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1978.39),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1985.16),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1799.53),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1614.06),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1468.88),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1336.87),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1259.27),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(192.79),\n        'wind': np.float64(1245.53),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(3223.06),\n        'wind': np.float64(1280.01),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(8484.11),\n        'wind': np.float64(1408.27),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(11466.11),\n        'wind': np.float64(1619.73),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12374.91),\n        'wind': np.float64(1889.97),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12600.19),\n        'wind': np.float64(2153.83),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12465.04),\n        'wind': np.float64(2416.71),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12022.63),\n        'wind': np.float64(2677.01),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(11086.98),\n        'wind': np.float64(2872.58),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 7, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(8363.76),\n        'wind': np.float64(2992.15),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(3390.19),\n        'wind': np.float64(3114.2),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(255.59),\n        'wind': np.float64(3211.0),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3237.27),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3271.86),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3321.28),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3344.3),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3315.9),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3283.19),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3188.98),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3113.94),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3002.26),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2869.48),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2757.56),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2645.24),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(219.7),\n        'wind': np.float64(2509.77),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(4084.05),\n        'wind': np.float64(2380.91),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(10775.51),\n        'wind': np.float64(2227.4),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(14151.67),\n        'wind': np.float64(2093.44),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(14821.76),\n        'wind': np.float64(2053.03),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(14891.45),\n        'wind': np.float64(2132.88),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(14773.4),\n        'wind': np.float64(2349.5),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(14591.23),\n        'wind': np.float64(2592.38),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(14026.0),\n        'wind': np.float64(2752.43),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 8, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(11148.07),\n        'wind': np.float64(2841.66),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(4813.87),\n        'wind': np.float64(2844.74),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(453.04),\n        'wind': np.float64(2801.72),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2755.03),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2672.92),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2486.79),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2211.93),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1890.3),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1519.28),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1001.12),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(725.33),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(541.33),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(457.79),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(421.17),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(398.96),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(192.75),\n        'wind': np.float64(368.51),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(3807.61),\n        'wind': np.float64(342.97),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(10127.12),\n        'wind': np.float64(315.87),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(13370.71),\n        'wind': np.float64(314.34),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(14044.48),\n        'wind': np.float64(360.11),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(14085.54),\n        'wind': np.float64(396.91),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(13915.28),\n        'wind': np.float64(385.65),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(13581.42),\n        'wind': np.float64(354.21),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12749.85),\n        'wind': np.float64(327.31),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(9921.97),\n        'wind': np.float64(300.01),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(4316.28),\n        'wind': np.float64(275.9),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(443.97),\n        'wind': np.float64(284.4),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(319.79),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(371.53),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(438.86),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(511.36),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(591.81),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(672.48),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(742.27),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(871.01),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(998.42),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1097.05),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1136.26),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(1077.99),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(332.87),\n        'wind': np.float64(963.83),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(4820.38),\n        'wind': np.float64(832.83),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(11902.0),\n        'wind': np.float64(707.31),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(15023.44),\n        'wind': np.float64(623.77),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(15483.63),\n        'wind': np.float64(627.52),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(15499.21),\n        'wind': np.float64(759.96),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(15477.63),\n        'wind': np.float64(969.88),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(15502.2),\n        'wind': np.float64(1241.26),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(15319.94),\n        'wind': np.float64(1585.51),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 10, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(12784.98),\n        'wind': np.float64(1939.56),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 11, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(5877.83),\n        'wind': np.float64(2257.58),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 11, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(635.05),\n        'wind': np.float64(2588.07),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 11, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2823.56),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 11, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2908.95),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 11, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2915.41),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 11, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2905.07),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 11, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(2954.77),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 11, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': np.float64(0.0),\n        'wind': np.float64(3073.82),\n      }),\n      'source': 'oasis.caiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-CAL-CISO',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_US_ERCOT.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': 43797.769897,\n      'datetime': datetime.datetime(2025, 3, 13, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43078.020325,\n      'datetime': datetime.datetime(2025, 3, 13, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41536.005066,\n      'datetime': datetime.datetime(2025, 3, 13, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41782.957092,\n      'datetime': datetime.datetime(2025, 3, 13, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41419.426758,\n      'datetime': datetime.datetime(2025, 3, 13, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41306.431946,\n      'datetime': datetime.datetime(2025, 3, 13, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43397.499817,\n      'datetime': datetime.datetime(2025, 3, 13, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44732.969971,\n      'datetime': datetime.datetime(2025, 3, 13, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46003.690552,\n      'datetime': datetime.datetime(2025, 3, 13, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46700.22998,\n      'datetime': datetime.datetime(2025, 3, 13, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 48775.109863,\n      'datetime': datetime.datetime(2025, 3, 13, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 50751.0,\n      'datetime': datetime.datetime(2025, 3, 13, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 52053.860107,\n      'datetime': datetime.datetime(2025, 3, 13, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 53909.940063,\n      'datetime': datetime.datetime(2025, 3, 13, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 56259.529785,\n      'datetime': datetime.datetime(2025, 3, 13, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 58365.090576,\n      'datetime': datetime.datetime(2025, 3, 13, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 59874.159546,\n      'datetime': datetime.datetime(2025, 3, 13, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 60126.679565,\n      'datetime': datetime.datetime(2025, 3, 13, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 59017.970581,\n      'datetime': datetime.datetime(2025, 3, 13, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 57414.519531,\n      'datetime': datetime.datetime(2025, 3, 13, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 56714.720703,\n      'datetime': datetime.datetime(2025, 3, 13, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 54896.500854,\n      'datetime': datetime.datetime(2025, 3, 13, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51855.660156,\n      'datetime': datetime.datetime(2025, 3, 13, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 48408.3302,\n      'datetime': datetime.datetime(2025, 3, 13, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45529.040161,\n      'datetime': datetime.datetime(2025, 3, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43619.379028,\n      'datetime': datetime.datetime(2025, 3, 14, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 42114.130371,\n      'datetime': datetime.datetime(2025, 3, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41492.039795,\n      'datetime': datetime.datetime(2025, 3, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41453.910034,\n      'datetime': datetime.datetime(2025, 3, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 42715.399902,\n      'datetime': datetime.datetime(2025, 3, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45052.910156,\n      'datetime': datetime.datetime(2025, 3, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46693.439941,\n      'datetime': datetime.datetime(2025, 3, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47822.429443,\n      'datetime': datetime.datetime(2025, 3, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 49450.939697,\n      'datetime': datetime.datetime(2025, 3, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 50745.329712,\n      'datetime': datetime.datetime(2025, 3, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51552.21936,\n      'datetime': datetime.datetime(2025, 3, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 52654.610107,\n      'datetime': datetime.datetime(2025, 3, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 53836.199585,\n      'datetime': datetime.datetime(2025, 3, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 55012.249878,\n      'datetime': datetime.datetime(2025, 3, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 55877.539429,\n      'datetime': datetime.datetime(2025, 3, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 56460.110352,\n      'datetime': datetime.datetime(2025, 3, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 56196.920654,\n      'datetime': datetime.datetime(2025, 3, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 54509.409668,\n      'datetime': datetime.datetime(2025, 3, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 52802.960205,\n      'datetime': datetime.datetime(2025, 3, 14, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 52486.120728,\n      'datetime': datetime.datetime(2025, 3, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51112.018921,\n      'datetime': datetime.datetime(2025, 3, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 48881.359741,\n      'datetime': datetime.datetime(2025, 3, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46342.360352,\n      'datetime': datetime.datetime(2025, 3, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43576.549194,\n      'datetime': datetime.datetime(2025, 3, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41657.369629,\n      'datetime': datetime.datetime(2025, 3, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 40337.172852,\n      'datetime': datetime.datetime(2025, 3, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39659.717712,\n      'datetime': datetime.datetime(2025, 3, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39474.52594,\n      'datetime': datetime.datetime(2025, 3, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39983.667969,\n      'datetime': datetime.datetime(2025, 3, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41051.110046,\n      'datetime': datetime.datetime(2025, 3, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 42593.570313,\n      'datetime': datetime.datetime(2025, 3, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44407.399902,\n      'datetime': datetime.datetime(2025, 3, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45788.77063,\n      'datetime': datetime.datetime(2025, 3, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46467.950073,\n      'datetime': datetime.datetime(2025, 3, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46626.390137,\n      'datetime': datetime.datetime(2025, 3, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46745.85022,\n      'datetime': datetime.datetime(2025, 3, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46736.380127,\n      'datetime': datetime.datetime(2025, 3, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46828.229492,\n      'datetime': datetime.datetime(2025, 3, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47413.059937,\n      'datetime': datetime.datetime(2025, 3, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47819.370605,\n      'datetime': datetime.datetime(2025, 3, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47859.070435,\n      'datetime': datetime.datetime(2025, 3, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47372.159546,\n      'datetime': datetime.datetime(2025, 3, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46935.379761,\n      'datetime': datetime.datetime(2025, 3, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47146.34082,\n      'datetime': datetime.datetime(2025, 3, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46324.268921,\n      'datetime': datetime.datetime(2025, 3, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44708.949829,\n      'datetime': datetime.datetime(2025, 3, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 42627.579834,\n      'datetime': datetime.datetime(2025, 3, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41005.164673,\n      'datetime': datetime.datetime(2025, 3, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39739.371643,\n      'datetime': datetime.datetime(2025, 3, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 38991.09082,\n      'datetime': datetime.datetime(2025, 3, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 38575.927856,\n      'datetime': datetime.datetime(2025, 3, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 38399.958679,\n      'datetime': datetime.datetime(2025, 3, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 38842.580383,\n      'datetime': datetime.datetime(2025, 3, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39717.749878,\n      'datetime': datetime.datetime(2025, 3, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41085.969727,\n      'datetime': datetime.datetime(2025, 3, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 42819.07019,\n      'datetime': datetime.datetime(2025, 3, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43960.48999,\n      'datetime': datetime.datetime(2025, 3, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43904.760132,\n      'datetime': datetime.datetime(2025, 3, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43444.950073,\n      'datetime': datetime.datetime(2025, 3, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43176.881958,\n      'datetime': datetime.datetime(2025, 3, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43391.800659,\n      'datetime': datetime.datetime(2025, 3, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43817.619812,\n      'datetime': datetime.datetime(2025, 3, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44444.679687,\n      'datetime': datetime.datetime(2025, 3, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45176.530151,\n      'datetime': datetime.datetime(2025, 3, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45855.619873,\n      'datetime': datetime.datetime(2025, 3, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45960.23999,\n      'datetime': datetime.datetime(2025, 3, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45822.669678,\n      'datetime': datetime.datetime(2025, 3, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46514.729858,\n      'datetime': datetime.datetime(2025, 3, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45853.290405,\n      'datetime': datetime.datetime(2025, 3, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44280.629883,\n      'datetime': datetime.datetime(2025, 3, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 42330.400513,\n      'datetime': datetime.datetime(2025, 3, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 40868.850098,\n      'datetime': datetime.datetime(2025, 3, 17, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39720.090576,\n      'datetime': datetime.datetime(2025, 3, 17, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39123.119995,\n      'datetime': datetime.datetime(2025, 3, 17, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 38870.920532,\n      'datetime': datetime.datetime(2025, 3, 17, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39404.589844,\n      'datetime': datetime.datetime(2025, 3, 17, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41001.189697,\n      'datetime': datetime.datetime(2025, 3, 17, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43762.279541,\n      'datetime': datetime.datetime(2025, 3, 17, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45434.519775,\n      'datetime': datetime.datetime(2025, 3, 17, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46324.688843,\n      'datetime': datetime.datetime(2025, 3, 17, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47218.480103,\n      'datetime': datetime.datetime(2025, 3, 17, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47344.430298,\n      'datetime': datetime.datetime(2025, 3, 17, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47474.310547,\n      'datetime': datetime.datetime(2025, 3, 17, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47727.790161,\n      'datetime': datetime.datetime(2025, 3, 17, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 48579.60022,\n      'datetime': datetime.datetime(2025, 3, 17, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 49491.540283,\n      'datetime': datetime.datetime(2025, 3, 17, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 50555.639893,\n      'datetime': datetime.datetime(2025, 3, 17, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51553.990356,\n      'datetime': datetime.datetime(2025, 3, 17, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 52045.73999,\n      'datetime': datetime.datetime(2025, 3, 17, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51613.859619,\n      'datetime': datetime.datetime(2025, 3, 17, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 50978.780151,\n      'datetime': datetime.datetime(2025, 3, 17, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51011.269653,\n      'datetime': datetime.datetime(2025, 3, 17, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 49789.570435,\n      'datetime': datetime.datetime(2025, 3, 17, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47380.990601,\n      'datetime': datetime.datetime(2025, 3, 17, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44657.460327,\n      'datetime': datetime.datetime(2025, 3, 17, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 42308.26001,\n      'datetime': datetime.datetime(2025, 3, 18, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 40727.990845,\n      'datetime': datetime.datetime(2025, 3, 18, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39659.779907,\n      'datetime': datetime.datetime(2025, 3, 18, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39277.610352,\n      'datetime': datetime.datetime(2025, 3, 18, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39555.21936,\n      'datetime': datetime.datetime(2025, 3, 18, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 40872.849609,\n      'datetime': datetime.datetime(2025, 3, 18, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43332.680176,\n      'datetime': datetime.datetime(2025, 3, 18, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44794.00061,\n      'datetime': datetime.datetime(2025, 3, 18, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45620.700073,\n      'datetime': datetime.datetime(2025, 3, 18, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46620.319702,\n      'datetime': datetime.datetime(2025, 3, 18, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46923.680298,\n      'datetime': datetime.datetime(2025, 3, 18, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47172.989746,\n      'datetime': datetime.datetime(2025, 3, 18, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47743.179443,\n      'datetime': datetime.datetime(2025, 3, 18, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 48737.799683,\n      'datetime': datetime.datetime(2025, 3, 18, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 49941.021118,\n      'datetime': datetime.datetime(2025, 3, 18, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51438.069336,\n      'datetime': datetime.datetime(2025, 3, 18, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 52963.49939,\n      'datetime': datetime.datetime(2025, 3, 18, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 53863.180664,\n      'datetime': datetime.datetime(2025, 3, 18, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 53678.300171,\n      'datetime': datetime.datetime(2025, 3, 18, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 53095.550049,\n      'datetime': datetime.datetime(2025, 3, 18, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 52981.009888,\n      'datetime': datetime.datetime(2025, 3, 18, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51834.540161,\n      'datetime': datetime.datetime(2025, 3, 18, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 49424.839966,\n      'datetime': datetime.datetime(2025, 3, 18, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46853.450073,\n      'datetime': datetime.datetime(2025, 3, 18, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44497.549683,\n      'datetime': datetime.datetime(2025, 3, 19, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 42663.118896,\n      'datetime': datetime.datetime(2025, 3, 19, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41333.079468,\n      'datetime': datetime.datetime(2025, 3, 19, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 40697.700317,\n      'datetime': datetime.datetime(2025, 3, 19, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 40728.569946,\n      'datetime': datetime.datetime(2025, 3, 19, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41974.678955,\n      'datetime': datetime.datetime(2025, 3, 19, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44435.250732,\n      'datetime': datetime.datetime(2025, 3, 19, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45947.130249,\n      'datetime': datetime.datetime(2025, 3, 19, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47009.779175,\n      'datetime': datetime.datetime(2025, 3, 19, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 48650.660034,\n      'datetime': datetime.datetime(2025, 3, 19, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 49777.180298,\n      'datetime': datetime.datetime(2025, 3, 19, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 50712.920044,\n      'datetime': datetime.datetime(2025, 3, 19, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51808.040771,\n      'datetime': datetime.datetime(2025, 3, 19, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 53076.219971,\n      'datetime': datetime.datetime(2025, 3, 19, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 53906.790161,\n      'datetime': datetime.datetime(2025, 3, 19, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 54358.829956,\n      'datetime': datetime.datetime(2025, 3, 19, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 54453.860107,\n      'datetime': datetime.datetime(2025, 3, 19, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 53813.710205,\n      'datetime': datetime.datetime(2025, 3, 19, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 52405.990601,\n      'datetime': datetime.datetime(2025, 3, 19, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 51128.740356,\n      'datetime': datetime.datetime(2025, 3, 19, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 50945.189819,\n      'datetime': datetime.datetime(2025, 3, 19, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 49590.790405,\n      'datetime': datetime.datetime(2025, 3, 19, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46948.939087,\n      'datetime': datetime.datetime(2025, 3, 19, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44024.869507,\n      'datetime': datetime.datetime(2025, 3, 19, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41400.489502,\n      'datetime': datetime.datetime(2025, 3, 20, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39836.110474,\n      'datetime': datetime.datetime(2025, 3, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 38700.709717,\n      'datetime': datetime.datetime(2025, 3, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 38553.670532,\n      'datetime': datetime.datetime(2025, 3, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 39175.759766,\n      'datetime': datetime.datetime(2025, 3, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41121.019897,\n      'datetime': datetime.datetime(2025, 3, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44467.6698,\n      'datetime': datetime.datetime(2025, 3, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46457.599854,\n      'datetime': datetime.datetime(2025, 3, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46995.650269,\n      'datetime': datetime.datetime(2025, 3, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 47251.470337,\n      'datetime': datetime.datetime(2025, 3, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 46594.049316,\n      'datetime': datetime.datetime(2025, 3, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45512.65979,\n      'datetime': datetime.datetime(2025, 3, 20, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44563.079956,\n      'datetime': datetime.datetime(2025, 3, 20, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44087.339844,\n      'datetime': datetime.datetime(2025, 3, 20, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43661.440674,\n      'datetime': datetime.datetime(2025, 3, 20, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43713.420288,\n      'datetime': datetime.datetime(2025, 3, 20, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44337.730225,\n      'datetime': datetime.datetime(2025, 3, 20, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44987.580566,\n      'datetime': datetime.datetime(2025, 3, 20, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45073.339966,\n      'datetime': datetime.datetime(2025, 3, 20, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45016.650269,\n      'datetime': datetime.datetime(2025, 3, 20, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 45713.98999,\n      'datetime': datetime.datetime(2025, 3, 20, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 44914.061035,\n      'datetime': datetime.datetime(2025, 3, 20, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 43456.259033,\n      'datetime': datetime.datetime(2025, 3, 20, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'consumption': 41722.789917,\n      'datetime': datetime.datetime(2025, 3, 20, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_wind_solar_forecasts\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24108.1,\n        'wind': 17404.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24563.7,\n        'wind': 17472.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24462.6,\n        'wind': 17674.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23835.0,\n        'wind': 18664.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 21910.4,\n        'wind': 19375.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 12186.0,\n        'wind': 20588.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 1557.0,\n        'wind': 19435.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 19946.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23805.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 26736.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 28962.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29939.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29482.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29125.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 28312.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 27579.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 26225.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 25400.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 59.8,\n        'wind': 23867.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 4192.8,\n        'wind': 22160.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 14689.5,\n        'wind': 18751.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 19139.0,\n        'wind': 16309.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 19303.8,\n        'wind': 16013.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 21844.1,\n        'wind': 18754.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 22095.9,\n        'wind': 21669.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 21043.9,\n        'wind': 24391.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 20919.3,\n        'wind': 24926.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 19945.7,\n        'wind': 26390.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 16420.1,\n        'wind': 25428.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 8206.3,\n        'wind': 24580.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 1185.3,\n        'wind': 23252.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 22204.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23480.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 24359.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 12, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23488.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 22505.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 20849.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 19698.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 19496.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 17818.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 15082.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 13861.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 202.9,\n        'wind': 12934.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 7633.0,\n        'wind': 11826.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 18251.2,\n        'wind': 7297.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23234.9,\n        'wind': 3201.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23758.7,\n        'wind': 2871.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23387.7,\n        'wind': 4123.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23670.1,\n        'wind': 7733.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23137.8,\n        'wind': 11372.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 20485.7,\n        'wind': 14756.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 19022.2,\n        'wind': 17578.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 17999.7,\n        'wind': 19183.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 9795.3,\n        'wind': 19684.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 1209.1,\n        'wind': 19875.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 20963.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 22520.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 24535.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 13, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 26759.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 28615.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 28515.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 28915.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 28980.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 28707.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 28028.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 27405.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 63.8,\n        'wind': 26880.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 3438.3,\n        'wind': 26313.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 13646.9,\n        'wind': 24760.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 18535.6,\n        'wind': 21738.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 21061.8,\n        'wind': 20406.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 22600.1,\n        'wind': 19996.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24275.7,\n        'wind': 20106.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24533.6,\n        'wind': 20679.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24300.5,\n        'wind': 21694.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23928.9,\n        'wind': 22644.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 22008.7,\n        'wind': 23889.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 12692.1,\n        'wind': 25042.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 1060.6,\n        'wind': 26068.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 26829.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 27253.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 27359.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 27349.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 27153.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 26135.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 26403.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 24551.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23245.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 22647.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 22413.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 103.1,\n        'wind': 22537.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 4281.4,\n        'wind': 22465.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 15499.1,\n        'wind': 21967.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 21673.1,\n        'wind': 22657.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23750.2,\n        'wind': 23529.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24405.9,\n        'wind': 23013.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24148.0,\n        'wind': 22438.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24250.3,\n        'wind': 22652.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23752.4,\n        'wind': 23278.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 21878.2,\n        'wind': 23560.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 19608.5,\n        'wind': 22959.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 11252.2,\n        'wind': 21510.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 1233.7,\n        'wind': 18786.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.1,\n        'wind': 15366.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 12752.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 11072.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 9913.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 8919.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 8191.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 7991.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 8401.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 8823.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 9015.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 9147.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 210.6,\n        'wind': 9176.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 6521.2,\n        'wind': 9053.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 20117.0,\n        'wind': 8256.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24391.1,\n        'wind': 7762.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 25765.1,\n        'wind': 8166.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 26119.4,\n        'wind': 7901.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 25585.7,\n        'wind': 7636.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 25744.0,\n        'wind': 7665.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 25623.8,\n        'wind': 7722.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 25281.7,\n        'wind': 7089.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24050.1,\n        'wind': 5806.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 14782.4,\n        'wind': 4963.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 1404.6,\n        'wind': 5532.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.1,\n        'wind': 6365.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 7414.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 9502.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 16, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 12568.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 15461.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 17477.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 18703.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 19910.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 20758.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 21207.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 21640.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 116.1,\n        'wind': 21605.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 7257.4,\n        'wind': 20953.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 21501.8,\n        'wind': 20382.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 25232.2,\n        'wind': 20949.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 25524.9,\n        'wind': 22340.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 25193.3,\n        'wind': 24148.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24117.3,\n        'wind': 25644.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23648.5,\n        'wind': 26637.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23178.4,\n        'wind': 27601.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 22406.7,\n        'wind': 28237.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 20538.8,\n        'wind': 28539.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 11928.1,\n        'wind': 28693.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 1500.4,\n        'wind': 28893.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29205.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29545.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29850.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 17, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 30073.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 30262.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 30276.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 30131.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29983.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29772.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29482.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29190.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 205.1,\n        'wind': 28852.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 5666.3,\n        'wind': 28610.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 16085.7,\n        'wind': 28368.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 21613.0,\n        'wind': 28231.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23041.1,\n        'wind': 28220.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23669.9,\n        'wind': 28216.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23565.8,\n        'wind': 28475.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23775.4,\n        'wind': 29035.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23437.4,\n        'wind': 29601.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 22638.5,\n        'wind': 29948.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 20661.0,\n        'wind': 30028.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 12280.2,\n        'wind': 30271.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 1467.5,\n        'wind': 30297.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.4,\n        'wind': 30281.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 30283.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 30299.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 18, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 30346.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 30400.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 30204.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29705.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 29210.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 28614.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 27888.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 27154.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 199.2,\n        'wind': 26435.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 5619.1,\n        'wind': 26182.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 16556.5,\n        'wind': 25942.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 20258.1,\n        'wind': 25590.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 22161.4,\n        'wind': 25071.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23007.1,\n        'wind': 24410.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 22984.9,\n        'wind': 24000.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 23059.5,\n        'wind': 23732.9,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 22502.4,\n        'wind': 23587.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 21510.9,\n        'wind': 23328.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 19975.2,\n        'wind': 23088.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 12915.5,\n        'wind': 22954.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 1760.1,\n        'wind': 22381.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.4,\n        'wind': 21413.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 20520.7,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 19576.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 19, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 18629.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 17595.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 16727.4,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 16067.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 15408.2,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 14679.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 13894.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 13128.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 350.7,\n        'wind': 12397.8,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 7472.6,\n        'wind': 11659.0,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 19544.4,\n        'wind': 10924.3,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 22947.7,\n        'wind': 10350.5,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 24366.9,\n        'wind': 9954.1,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 20, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='US/Central')),\n      'production': dict({\n        'solar': 25051.6,\n        'wind': 9615.6,\n      }),\n      'source': 'ercot.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-TEX-ERCO',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_US_MISO.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': 64272.0,\n      'datetime': datetime.datetime(2025, 3, 9, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62613.0,\n      'datetime': datetime.datetime(2025, 3, 9, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 61929.0,\n      'datetime': datetime.datetime(2025, 3, 9, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 61620.0,\n      'datetime': datetime.datetime(2025, 3, 9, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 61912.0,\n      'datetime': datetime.datetime(2025, 3, 9, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63010.0,\n      'datetime': datetime.datetime(2025, 3, 9, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 64831.0,\n      'datetime': datetime.datetime(2025, 3, 9, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 66154.0,\n      'datetime': datetime.datetime(2025, 3, 9, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 66220.0,\n      'datetime': datetime.datetime(2025, 3, 9, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 65552.0,\n      'datetime': datetime.datetime(2025, 3, 9, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 64728.0,\n      'datetime': datetime.datetime(2025, 3, 9, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 64043.0,\n      'datetime': datetime.datetime(2025, 3, 9, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63762.0,\n      'datetime': datetime.datetime(2025, 3, 9, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63108.0,\n      'datetime': datetime.datetime(2025, 3, 9, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62592.0,\n      'datetime': datetime.datetime(2025, 3, 9, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62577.0,\n      'datetime': datetime.datetime(2025, 3, 9, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63135.0,\n      'datetime': datetime.datetime(2025, 3, 9, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 64699.0,\n      'datetime': datetime.datetime(2025, 3, 9, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 66874.0,\n      'datetime': datetime.datetime(2025, 3, 9, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69481.0,\n      'datetime': datetime.datetime(2025, 3, 9, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69638.0,\n      'datetime': datetime.datetime(2025, 3, 9, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68126.0,\n      'datetime': datetime.datetime(2025, 3, 9, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 65827.0,\n      'datetime': datetime.datetime(2025, 3, 9, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63928.0,\n      'datetime': datetime.datetime(2025, 3, 9, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63085.0,\n      'datetime': datetime.datetime(2025, 3, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63228.0,\n      'datetime': datetime.datetime(2025, 3, 10, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62411.0,\n      'datetime': datetime.datetime(2025, 3, 10, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 64302.0,\n      'datetime': datetime.datetime(2025, 3, 10, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 66292.0,\n      'datetime': datetime.datetime(2025, 3, 10, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69791.0,\n      'datetime': datetime.datetime(2025, 3, 10, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 75314.0,\n      'datetime': datetime.datetime(2025, 3, 10, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 77348.0,\n      'datetime': datetime.datetime(2025, 3, 10, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 76328.0,\n      'datetime': datetime.datetime(2025, 3, 10, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 74188.0,\n      'datetime': datetime.datetime(2025, 3, 10, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 72120.0,\n      'datetime': datetime.datetime(2025, 3, 10, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70396.0,\n      'datetime': datetime.datetime(2025, 3, 10, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69144.0,\n      'datetime': datetime.datetime(2025, 3, 10, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68060.0,\n      'datetime': datetime.datetime(2025, 3, 10, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67107.0,\n      'datetime': datetime.datetime(2025, 3, 10, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 66641.0,\n      'datetime': datetime.datetime(2025, 3, 10, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67001.0,\n      'datetime': datetime.datetime(2025, 3, 10, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68150.0,\n      'datetime': datetime.datetime(2025, 3, 10, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69893.0,\n      'datetime': datetime.datetime(2025, 3, 10, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71889.0,\n      'datetime': datetime.datetime(2025, 3, 10, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71349.0,\n      'datetime': datetime.datetime(2025, 3, 10, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69195.0,\n      'datetime': datetime.datetime(2025, 3, 10, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 66302.0,\n      'datetime': datetime.datetime(2025, 3, 10, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63708.0,\n      'datetime': datetime.datetime(2025, 3, 10, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62112.0,\n      'datetime': datetime.datetime(2025, 3, 11, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 61964.0,\n      'datetime': datetime.datetime(2025, 3, 11, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62620.0,\n      'datetime': datetime.datetime(2025, 3, 11, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63250.0,\n      'datetime': datetime.datetime(2025, 3, 11, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 65320.0,\n      'datetime': datetime.datetime(2025, 3, 11, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68188.0,\n      'datetime': datetime.datetime(2025, 3, 11, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 73356.0,\n      'datetime': datetime.datetime(2025, 3, 11, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 75196.0,\n      'datetime': datetime.datetime(2025, 3, 11, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 74523.0,\n      'datetime': datetime.datetime(2025, 3, 11, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 72890.0,\n      'datetime': datetime.datetime(2025, 3, 11, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71276.0,\n      'datetime': datetime.datetime(2025, 3, 11, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69909.0,\n      'datetime': datetime.datetime(2025, 3, 11, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68947.0,\n      'datetime': datetime.datetime(2025, 3, 11, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68165.0,\n      'datetime': datetime.datetime(2025, 3, 11, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67484.0,\n      'datetime': datetime.datetime(2025, 3, 11, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67091.0,\n      'datetime': datetime.datetime(2025, 3, 11, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67424.0,\n      'datetime': datetime.datetime(2025, 3, 11, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68470.0,\n      'datetime': datetime.datetime(2025, 3, 11, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69961.0,\n      'datetime': datetime.datetime(2025, 3, 11, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71833.0,\n      'datetime': datetime.datetime(2025, 3, 11, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71471.0,\n      'datetime': datetime.datetime(2025, 3, 11, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69293.0,\n      'datetime': datetime.datetime(2025, 3, 11, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 66483.0,\n      'datetime': datetime.datetime(2025, 3, 11, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63794.0,\n      'datetime': datetime.datetime(2025, 3, 11, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62462.0,\n      'datetime': datetime.datetime(2025, 3, 12, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62550.0,\n      'datetime': datetime.datetime(2025, 3, 12, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62285.0,\n      'datetime': datetime.datetime(2025, 3, 12, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62754.0,\n      'datetime': datetime.datetime(2025, 3, 12, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 64673.0,\n      'datetime': datetime.datetime(2025, 3, 12, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68600.0,\n      'datetime': datetime.datetime(2025, 3, 12, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 72028.0,\n      'datetime': datetime.datetime(2025, 3, 12, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 73871.0,\n      'datetime': datetime.datetime(2025, 3, 12, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 73249.0,\n      'datetime': datetime.datetime(2025, 3, 12, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71826.0,\n      'datetime': datetime.datetime(2025, 3, 12, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70572.0,\n      'datetime': datetime.datetime(2025, 3, 12, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69496.0,\n      'datetime': datetime.datetime(2025, 3, 12, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68808.0,\n      'datetime': datetime.datetime(2025, 3, 12, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68324.0,\n      'datetime': datetime.datetime(2025, 3, 12, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67863.0,\n      'datetime': datetime.datetime(2025, 3, 12, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67587.0,\n      'datetime': datetime.datetime(2025, 3, 12, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67892.0,\n      'datetime': datetime.datetime(2025, 3, 12, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68577.0,\n      'datetime': datetime.datetime(2025, 3, 12, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69522.0,\n      'datetime': datetime.datetime(2025, 3, 12, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70913.0,\n      'datetime': datetime.datetime(2025, 3, 12, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70531.0,\n      'datetime': datetime.datetime(2025, 3, 12, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68285.0,\n      'datetime': datetime.datetime(2025, 3, 12, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 65238.0,\n      'datetime': datetime.datetime(2025, 3, 12, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 63464.0,\n      'datetime': datetime.datetime(2025, 3, 12, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 61658.0,\n      'datetime': datetime.datetime(2025, 3, 13, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 60639.0,\n      'datetime': datetime.datetime(2025, 3, 13, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 60272.0,\n      'datetime': datetime.datetime(2025, 3, 13, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 60667.0,\n      'datetime': datetime.datetime(2025, 3, 13, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62398.0,\n      'datetime': datetime.datetime(2025, 3, 13, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 65101.0,\n      'datetime': datetime.datetime(2025, 3, 13, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69677.0,\n      'datetime': datetime.datetime(2025, 3, 13, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71725.0,\n      'datetime': datetime.datetime(2025, 3, 13, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71567.0,\n      'datetime': datetime.datetime(2025, 3, 13, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70681.0,\n      'datetime': datetime.datetime(2025, 3, 13, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69846.0,\n      'datetime': datetime.datetime(2025, 3, 13, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69236.0,\n      'datetime': datetime.datetime(2025, 3, 13, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68865.0,\n      'datetime': datetime.datetime(2025, 3, 13, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68524.0,\n      'datetime': datetime.datetime(2025, 3, 13, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68184.0,\n      'datetime': datetime.datetime(2025, 3, 13, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68021.0,\n      'datetime': datetime.datetime(2025, 3, 13, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68362.0,\n      'datetime': datetime.datetime(2025, 3, 13, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68943.0,\n      'datetime': datetime.datetime(2025, 3, 13, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69678.0,\n      'datetime': datetime.datetime(2025, 3, 13, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71036.0,\n      'datetime': datetime.datetime(2025, 3, 13, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70285.0,\n      'datetime': datetime.datetime(2025, 3, 13, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67981.0,\n      'datetime': datetime.datetime(2025, 3, 13, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 64976.0,\n      'datetime': datetime.datetime(2025, 3, 13, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62255.0,\n      'datetime': datetime.datetime(2025, 3, 13, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 60411.0,\n      'datetime': datetime.datetime(2025, 3, 14, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 59330.0,\n      'datetime': datetime.datetime(2025, 3, 14, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 59878.0,\n      'datetime': datetime.datetime(2025, 3, 14, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 60238.0,\n      'datetime': datetime.datetime(2025, 3, 14, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 61854.0,\n      'datetime': datetime.datetime(2025, 3, 14, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 64362.0,\n      'datetime': datetime.datetime(2025, 3, 14, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 68759.0,\n      'datetime': datetime.datetime(2025, 3, 14, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70931.0,\n      'datetime': datetime.datetime(2025, 3, 14, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 71161.0,\n      'datetime': datetime.datetime(2025, 3, 14, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70896.0,\n      'datetime': datetime.datetime(2025, 3, 14, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70689.0,\n      'datetime': datetime.datetime(2025, 3, 14, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70410.0,\n      'datetime': datetime.datetime(2025, 3, 14, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70138.0,\n      'datetime': datetime.datetime(2025, 3, 14, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69881.0,\n      'datetime': datetime.datetime(2025, 3, 14, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69531.0,\n      'datetime': datetime.datetime(2025, 3, 14, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69282.0,\n      'datetime': datetime.datetime(2025, 3, 14, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69465.0,\n      'datetime': datetime.datetime(2025, 3, 14, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69595.0,\n      'datetime': datetime.datetime(2025, 3, 14, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69658.0,\n      'datetime': datetime.datetime(2025, 3, 14, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 70347.0,\n      'datetime': datetime.datetime(2025, 3, 14, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 69770.0,\n      'datetime': datetime.datetime(2025, 3, 14, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67723.0,\n      'datetime': datetime.datetime(2025, 3, 14, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 64907.0,\n      'datetime': datetime.datetime(2025, 3, 14, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 62579.0,\n      'datetime': datetime.datetime(2025, 3, 14, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'consumption': 67758.0,\n      'datetime': datetime.datetime(2025, 3, 15, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_wind_solar_forecasts\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 17716.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 17168.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 16628.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 16249.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 16089.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 16192.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 3.0,\n        'wind': 16583.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 1042.0,\n        'wind': 17076.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 6022.0,\n        'wind': 17386.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 10313.0,\n        'wind': 17154.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11437.0,\n        'wind': 16391.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11466.0,\n        'wind': 16389.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11301.0,\n        'wind': 17767.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11206.0,\n        'wind': 19703.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11297.0,\n        'wind': 21282.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11398.0,\n        'wind': 22330.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 10642.0,\n        'wind': 22727.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 6959.0,\n        'wind': 22525.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 1583.0,\n        'wind': 22427.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 8.0,\n        'wind': 23044.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23647.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23981.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 24047.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 10, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23881.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23596.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23196.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23034.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 23022.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 22831.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 22327.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 3.0,\n        'wind': 21393.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 1123.0,\n        'wind': 19830.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 6119.0,\n        'wind': 17808.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 10198.0,\n        'wind': 15679.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11213.0,\n        'wind': 13413.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11234.0,\n        'wind': 11073.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11105.0,\n        'wind': 9176.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11038.0,\n        'wind': 8033.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11119.0,\n        'wind': 7338.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 11229.0,\n        'wind': 6885.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 10441.0,\n        'wind': 6934.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 6848.0,\n        'wind': 7577.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 1586.0,\n        'wind': 8756.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 9.0,\n        'wind': 11393.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 13542.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 14719.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 15219.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 11, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 15321.0,\n      }),\n      'source': 'misoenergy.org',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDW-MISO',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_US_NEISO/test_fetch_exchange[CA-NB-US-NE-ISNE].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[CA-NB-US-NE-ISNE]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(112.412),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(110.903),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(107.148),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(101.507),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(98.284),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(112.183),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(115.144),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(96.47),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(91.746),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(85.547),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(100.552),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(93.338),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(92.39),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(105.896),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(99.81),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(94.271),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(89.001),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(90.666),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(91.308),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(91.203),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(100.057),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(96.381),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(93.143),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(103.362),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(109.792),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(106.697),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(95.124),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(114.237),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(110.767),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(97.051),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(95.803),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(95.683),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(87.176),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(88.65),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(96.673),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(84.698),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(110.44),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(125.289),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(135.389),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(125.625),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(118.219),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(121.849),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(115.325),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(113.28),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(114.722),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(110.308),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(101.052),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(120.189),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(148.005),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(135.854),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(136.659),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(134.433),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(129.62),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(125.894),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(123.555),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(122.405),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(124.316),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(120.508),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(122.791),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(134.303),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(116.949),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(93.451),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(97.424),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(79.291),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(82.406),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(96.43),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(84.626),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(84.198),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(73.988),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(77.18),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(78.621),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(87.012),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(50.387),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(54.353),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(59.165),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(50.074),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(63.29),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(63.695),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(54.765),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(61.71),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(52.312),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(43.045),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(44.368),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(37.078),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(56.327),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(66.166),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(64.35),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(72.711),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(79.453),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(79.463),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(78.857),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(74.018),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(65.309),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(72.825),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(77.787),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(58.767),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(64.511),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(64.797),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(50.82),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(50.474),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(60.0),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(74.343),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(69.318),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(57.057),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(57.277),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(60.494),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(65.567),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(66.526),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(55.482),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(61.342),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(51.072),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(58.8),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(62.134),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(64.424),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(72.06),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(62.309),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(67.569),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(78.242),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(56.95),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(60.446),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(68.138),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(51.868),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(58.685),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(61.556),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(60.763),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(65.015),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(60.978),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(51.84),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(51.485),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(50.776),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(58.997),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(63.461),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(71.552),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(92.357),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(61.816),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(59.239),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(76.608),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(82.405),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(80.048),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(85.752),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(87.617),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(79.424),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(77.197),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(75.517),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(92.562),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(87.938),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(73.08),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(90.784),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(93.431),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(111.936),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(106.097),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(96.882),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(109.77),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(109.578),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(129.744),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(134.532),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(127.764),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(135.112),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(125.54),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(136.37),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(146.241),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(142.829),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(132.609),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(136.879),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(144.549),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(132.764),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(127.488),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(134.519),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(124.554),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(128.46),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(104.406),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(132.979),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(137.258),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(122.33),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(123.685),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(117.773),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(117.211),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(108.844),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(111.239),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(114.119),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(118.561),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(112.779),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(87.014),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(96.383),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(104.8),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(94.36),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(98.873),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(91.599),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(87.534),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(99.934),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(99.007),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(110.897),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(100.605),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(106.986),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(108.895),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(101.182),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(92.462),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(80.992),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(78.46),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(78.28),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(76.246),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(75.83),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(86.939),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(81.199),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(87.462),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(97.752),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(108.587),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(92.0),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(85.099),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(81.643),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(73.908),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(86.647),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(85.83),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(82.646),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(81.907),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(73.97),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(88.419),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(64.949),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(80.706),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(89.219),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(84.237),\n      'sortedZoneKeys': 'CA-NB->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_US_NEISO/test_fetch_exchange[CA-QC-US-NE-ISNE].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[CA-QC-US-NE-ISNE]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.281),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.286),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.286),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.284),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.283),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.278),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.28),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.283),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.279),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.303),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.282),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.281),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.298),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.288),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.286),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.283),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.284),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.278),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 2, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.3),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.28),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.281),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.299),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.294),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 3, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.286),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.281),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.305),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.284),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 4, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.286),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.286),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.282),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.288),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 5, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.288),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.281),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.281),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 6, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(2.66),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(42.947),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.147),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.17),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.17),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.198),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.215),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.189),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.206),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.212),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.162),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(47.161),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 7, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(46.991),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(11.928),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.297),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.303),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.298),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.286),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.307),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.304),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 8, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.297),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.284),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.294),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 9, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.301),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.294),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.297),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.294),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.303),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.294),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 10, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.281),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.283),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.294),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 11, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.294),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.3),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.297),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.297),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.297),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.294),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.288),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 12, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.303),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.288),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.302),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.294),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.298),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.302),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 13, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.3),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.296),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.299),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 14, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.288),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.283),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.281),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.298),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.272),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.301),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.293),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.288),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.283),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.297),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.285),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.299),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.288),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.295),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.297),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.279),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.286),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.289),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.284),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.292),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.291),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.3),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.287),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(0.29),\n      'sortedZoneKeys': 'CA-QC->US-NE-ISNE',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_US_NEISO/test_fetch_exchange[US-NE-ISNE-US-NY-NYIS].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[US-NE-ISNE-US-NY-NYIS]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-272.101),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-185.979),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-187.105),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-135.955),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-26.596),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(43.705),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(52.917),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(44.706),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(28.327),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(27.426),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(115.203),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 0, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(109.702),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(116.782),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(153.629),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 1, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(151.898),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 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'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(138.6),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(100.383),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 15, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-1.449),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(58.454),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-64.7),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(20.016),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(3.391),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(74.242),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(117.618),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(149.162),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(116.448),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(146.979),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(168.558),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(278.169),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 16, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(162.292),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(101.932),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(73.245),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(29.743),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-114.686),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-50.955),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-30.998),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-113.715),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-227.635),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-119.895),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-78.979),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-80.75),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 17, 55, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-20.0),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 0, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(57.037),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 5, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(13.375),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 10, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-55.306),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 15, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-116.457),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 20, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-147.23),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 25, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-159.087),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 30, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-173.813),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 35, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-138.493),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 40, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-182.731),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 45, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-178.869),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 3, 26, 18, 50, tzinfo=datetime.timezone(datetime.timedelta(days=-1, seconds=72000))),\n      'netFlow': np.float64(-116.523),\n      'sortedZoneKeys': 'US-NE-ISNE->US-NY-NYIS',\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_US_NEISO.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': 9950.0,\n      'datetime': datetime.datetime(2025, 3, 17, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 9660.0,\n      'datetime': datetime.datetime(2025, 3, 17, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 9430.0,\n      'datetime': datetime.datetime(2025, 3, 17, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 9560.0,\n      'datetime': datetime.datetime(2025, 3, 17, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 9720.0,\n      'datetime': datetime.datetime(2025, 3, 17, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 10770.0,\n      'datetime': datetime.datetime(2025, 3, 17, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 12110.0,\n      'datetime': datetime.datetime(2025, 3, 17, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13140.0,\n      'datetime': datetime.datetime(2025, 3, 17, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13460.0,\n      'datetime': datetime.datetime(2025, 3, 17, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13550.0,\n      'datetime': datetime.datetime(2025, 3, 17, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13590.0,\n      'datetime': datetime.datetime(2025, 3, 17, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13510.0,\n      'datetime': datetime.datetime(2025, 3, 17, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13450.0,\n      'datetime': datetime.datetime(2025, 3, 17, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13400.0,\n      'datetime': datetime.datetime(2025, 3, 17, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13200.0,\n      'datetime': datetime.datetime(2025, 3, 17, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 12980.0,\n      'datetime': datetime.datetime(2025, 3, 17, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13290.0,\n      'datetime': datetime.datetime(2025, 3, 17, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13900.0,\n      'datetime': datetime.datetime(2025, 3, 17, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 14190.0,\n      'datetime': datetime.datetime(2025, 3, 17, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 14350.0,\n      'datetime': datetime.datetime(2025, 3, 17, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13830.0,\n      'datetime': datetime.datetime(2025, 3, 17, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 12960.0,\n      'datetime': datetime.datetime(2025, 3, 17, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 12010.0,\n      'datetime': datetime.datetime(2025, 3, 17, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 11090.0,\n      'datetime': datetime.datetime(2025, 3, 17, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 10680.0,\n      'datetime': datetime.datetime(2025, 3, 18, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 10400.0,\n      'datetime': datetime.datetime(2025, 3, 18, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 10240.0,\n      'datetime': datetime.datetime(2025, 3, 18, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 10250.0,\n      'datetime': datetime.datetime(2025, 3, 18, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 10630.0,\n      'datetime': datetime.datetime(2025, 3, 18, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 11590.0,\n      'datetime': datetime.datetime(2025, 3, 18, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13120.0,\n      'datetime': datetime.datetime(2025, 3, 18, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13830.0,\n      'datetime': datetime.datetime(2025, 3, 18, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 12860.0,\n      'datetime': datetime.datetime(2025, 3, 18, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 11380.0,\n      'datetime': datetime.datetime(2025, 3, 18, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 10200.0,\n      'datetime': datetime.datetime(2025, 3, 18, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 9390.0,\n      'datetime': datetime.datetime(2025, 3, 18, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 8880.0,\n      'datetime': datetime.datetime(2025, 3, 18, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 8800.0,\n      'datetime': datetime.datetime(2025, 3, 18, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 8910.0,\n      'datetime': datetime.datetime(2025, 3, 18, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 9560.0,\n      'datetime': datetime.datetime(2025, 3, 18, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 10640.0,\n      'datetime': datetime.datetime(2025, 3, 18, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 12380.0,\n      'datetime': datetime.datetime(2025, 3, 18, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13390.0,\n      'datetime': datetime.datetime(2025, 3, 18, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 14100.0,\n      'datetime': datetime.datetime(2025, 3, 18, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 13710.0,\n      'datetime': datetime.datetime(2025, 3, 18, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 12970.0,\n      'datetime': datetime.datetime(2025, 3, 18, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 11980.0,\n      'datetime': datetime.datetime(2025, 3, 18, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'consumption': 11110.0,\n      'datetime': datetime.datetime(2025, 3, 18, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NE-ISNE',\n    }),\n  ])\n# ---\n# name: test_fetch_wind_solar_forecasts\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 661.0,\n        'wind': 234.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 704.0,\n        'wind': 147.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 666.0,\n        'wind': 115.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 545.0,\n        'wind': 109.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 447.0,\n        'wind': 117.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 267.0,\n        'wind': 116.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 69.0,\n        'wind': 117.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 13.0,\n        'wind': 118.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 125.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 153.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 161.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 148.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 152.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 25, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 165.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 205.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 221.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 270.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 340.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 439.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 503.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 21.0,\n        'wind': 568.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 173.0,\n        'wind': 643.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 454.0,\n        'wind': 655.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 705.0,\n        'wind': 694.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 842.0,\n        'wind': 750.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 879.0,\n        'wind': 811.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 887.0,\n        'wind': 895.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 860.0,\n        'wind': 966.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 762.0,\n        'wind': 998.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 520.0,\n        'wind': 1009.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 203.0,\n        'wind': 969.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 30.0,\n        'wind': 920.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 885.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 853.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 747.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 700.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 599.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 26, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 483.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 352.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 242.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 158.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 99.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 66.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 80.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 7.0,\n        'wind': 112.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 33.0,\n        'wind': 147.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 69.0,\n        'wind': 178.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 100.0,\n        'wind': 224.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 100.0,\n        'wind': 275.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 134.0,\n        'wind': 313.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 169.0,\n        'wind': 339.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 191.0,\n        'wind': 365.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 190.0,\n        'wind': 360.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 146.0,\n        'wind': 344.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 88.0,\n        'wind': 323.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 51.0,\n        'wind': 313.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 14.0,\n        'wind': 325.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 328.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 358.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 385.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 400.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 27, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 434.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 470.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 509.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 511.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 519.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 522.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 507.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 495.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 486.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 59.0,\n        'wind': 592.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 366.0,\n        'wind': 682.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 597.0,\n        'wind': 743.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 805.0,\n        'wind': 869.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 860.0,\n        'wind': 966.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 760.0,\n        'wind': 1010.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 781.0,\n        'wind': 1148.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 759.0,\n        'wind': 1248.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 601.0,\n        'wind': 1279.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 222.0,\n        'wind': 1254.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 72.0,\n        'wind': 1226.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 1164.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1052.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 882.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 717.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 28, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 554.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 408.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 289.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 252.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 234.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 224.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 257.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 304.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 367.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 22.0,\n        'wind': 434.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 205.0,\n        'wind': 516.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 304.0,\n        'wind': 611.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 488.0,\n        'wind': 652.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 557.0,\n        'wind': 696.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 630.0,\n        'wind': 734.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 586.0,\n        'wind': 664.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 474.0,\n        'wind': 589.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 388.0,\n        'wind': 530.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 131.0,\n        'wind': 612.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 31.0,\n        'wind': 716.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 2.0,\n        'wind': 823.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 864.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 912.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 966.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 981.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 991.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 991.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 993.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 995.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 992.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1002.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1004.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 1006.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 97.0,\n        'wind': 1059.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 449.0,\n        'wind': 1114.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 657.0,\n        'wind': 1152.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 848.0,\n        'wind': 1160.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 891.0,\n        'wind': 1168.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 910.0,\n        'wind': 1170.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 888.0,\n        'wind': 1154.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 819.0,\n        'wind': 1132.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 611.0,\n        'wind': 1102.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 194.0,\n        'wind': 1080.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 49.0,\n        'wind': 1058.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 1028.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 927.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 817.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 704.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 2, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 698.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 690.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 682.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 686.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 692.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 697.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 710.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 725.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 738.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 84.0,\n        'wind': 818.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 404.0,\n        'wind': 898.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 602.0,\n        'wind': 962.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 791.0,\n        'wind': 939.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 842.0,\n        'wind': 909.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 862.0,\n        'wind': 877.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 845.0,\n        'wind': 836.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 785.0,\n        'wind': 788.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 584.0,\n        'wind': 738.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 180.0,\n        'wind': 676.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 46.0,\n        'wind': 606.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 1.0,\n        'wind': 541.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 455.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 378.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 309.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 3, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 294.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 283.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 275.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 302.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 330.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 367.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 356.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 357.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 356.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 213.0,\n        'wind': 449.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 3, 4, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'solar': 439.0,\n        'wind': 525.0,\n      }),\n      'source': 'iso-ne.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NE-ISNE',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_US_NY.ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': 18054.0,\n      'datetime': FakeDatetime(2025, 2, 19, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17636.0,\n      'datetime': FakeDatetime(2025, 2, 19, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17402.0,\n      'datetime': FakeDatetime(2025, 2, 19, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17330.0,\n      'datetime': FakeDatetime(2025, 2, 19, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17590.0,\n      'datetime': FakeDatetime(2025, 2, 19, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18364.0,\n      'datetime': FakeDatetime(2025, 2, 19, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19717.0,\n      'datetime': FakeDatetime(2025, 2, 19, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20557.0,\n      'datetime': FakeDatetime(2025, 2, 19, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20540.0,\n      'datetime': FakeDatetime(2025, 2, 19, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20263.0,\n      'datetime': FakeDatetime(2025, 2, 19, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19987.0,\n      'datetime': FakeDatetime(2025, 2, 19, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19700.0,\n      'datetime': FakeDatetime(2025, 2, 19, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19465.0,\n      'datetime': FakeDatetime(2025, 2, 19, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19458.0,\n      'datetime': FakeDatetime(2025, 2, 19, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19555.0,\n      'datetime': FakeDatetime(2025, 2, 19, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20068.0,\n      'datetime': FakeDatetime(2025, 2, 19, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20822.0,\n      'datetime': FakeDatetime(2025, 2, 19, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 21587.0,\n      'datetime': FakeDatetime(2025, 2, 19, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 22028.0,\n      'datetime': FakeDatetime(2025, 2, 19, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 21836.0,\n      'datetime': FakeDatetime(2025, 2, 19, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 21329.0,\n      'datetime': FakeDatetime(2025, 2, 19, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20559.0,\n      'datetime': FakeDatetime(2025, 2, 19, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19565.0,\n      'datetime': FakeDatetime(2025, 2, 19, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18621.0,\n      'datetime': FakeDatetime(2025, 2, 19, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17823.0,\n      'datetime': FakeDatetime(2025, 2, 20, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17415.0,\n      'datetime': FakeDatetime(2025, 2, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17175.0,\n      'datetime': FakeDatetime(2025, 2, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17096.0,\n      'datetime': FakeDatetime(2025, 2, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17337.0,\n      'datetime': FakeDatetime(2025, 2, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18100.0,\n      'datetime': FakeDatetime(2025, 2, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19411.0,\n      'datetime': FakeDatetime(2025, 2, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20373.0,\n      'datetime': FakeDatetime(2025, 2, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20688.0,\n      'datetime': FakeDatetime(2025, 2, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20671.0,\n      'datetime': FakeDatetime(2025, 2, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20560.0,\n      'datetime': FakeDatetime(2025, 2, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20357.0,\n      'datetime': FakeDatetime(2025, 2, 20, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20167.0,\n      'datetime': FakeDatetime(2025, 2, 20, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20086.0,\n      'datetime': FakeDatetime(2025, 2, 20, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20054.0,\n      'datetime': FakeDatetime(2025, 2, 20, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20311.0,\n      'datetime': FakeDatetime(2025, 2, 20, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20754.0,\n      'datetime': FakeDatetime(2025, 2, 20, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 21315.0,\n      'datetime': FakeDatetime(2025, 2, 20, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 21706.0,\n      'datetime': FakeDatetime(2025, 2, 20, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 21504.0,\n      'datetime': FakeDatetime(2025, 2, 20, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20988.0,\n      'datetime': FakeDatetime(2025, 2, 20, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20218.0,\n      'datetime': FakeDatetime(2025, 2, 20, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19221.0,\n      'datetime': FakeDatetime(2025, 2, 20, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18284.0,\n      'datetime': FakeDatetime(2025, 2, 20, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17508.0,\n      'datetime': FakeDatetime(2025, 2, 21, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17062.0,\n      'datetime': FakeDatetime(2025, 2, 21, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16783.0,\n      'datetime': FakeDatetime(2025, 2, 21, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16686.0,\n      'datetime': FakeDatetime(2025, 2, 21, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16911.0,\n      'datetime': FakeDatetime(2025, 2, 21, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17639.0,\n      'datetime': FakeDatetime(2025, 2, 21, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18938.0,\n      'datetime': FakeDatetime(2025, 2, 21, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19828.0,\n      'datetime': FakeDatetime(2025, 2, 21, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19944.0,\n      'datetime': FakeDatetime(2025, 2, 21, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19651.0,\n      'datetime': FakeDatetime(2025, 2, 21, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19302.0,\n      'datetime': FakeDatetime(2025, 2, 21, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18939.0,\n      'datetime': FakeDatetime(2025, 2, 21, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18596.0,\n      'datetime': FakeDatetime(2025, 2, 21, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18444.0,\n      'datetime': FakeDatetime(2025, 2, 21, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18451.0,\n      'datetime': FakeDatetime(2025, 2, 21, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18880.0,\n      'datetime': FakeDatetime(2025, 2, 21, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19665.0,\n      'datetime': FakeDatetime(2025, 2, 21, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20441.0,\n      'datetime': FakeDatetime(2025, 2, 21, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20866.0,\n      'datetime': FakeDatetime(2025, 2, 21, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20672.0,\n      'datetime': FakeDatetime(2025, 2, 21, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 20207.0,\n      'datetime': FakeDatetime(2025, 2, 21, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19629.0,\n      'datetime': FakeDatetime(2025, 2, 21, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18887.0,\n      'datetime': FakeDatetime(2025, 2, 21, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18099.0,\n      'datetime': FakeDatetime(2025, 2, 21, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17339.0,\n      'datetime': FakeDatetime(2025, 2, 22, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16906.0,\n      'datetime': FakeDatetime(2025, 2, 22, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16631.0,\n      'datetime': FakeDatetime(2025, 2, 22, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16482.0,\n      'datetime': FakeDatetime(2025, 2, 22, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16521.0,\n      'datetime': FakeDatetime(2025, 2, 22, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16822.0,\n      'datetime': FakeDatetime(2025, 2, 22, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17359.0,\n      'datetime': FakeDatetime(2025, 2, 22, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17864.0,\n      'datetime': FakeDatetime(2025, 2, 22, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18233.0,\n      'datetime': FakeDatetime(2025, 2, 22, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18187.0,\n      'datetime': FakeDatetime(2025, 2, 22, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17911.0,\n      'datetime': FakeDatetime(2025, 2, 22, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17618.0,\n      'datetime': FakeDatetime(2025, 2, 22, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17287.0,\n      'datetime': FakeDatetime(2025, 2, 22, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16735.0,\n      'datetime': FakeDatetime(2025, 2, 22, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16828.0,\n      'datetime': FakeDatetime(2025, 2, 22, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17387.0,\n      'datetime': FakeDatetime(2025, 2, 22, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18299.0,\n      'datetime': FakeDatetime(2025, 2, 22, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18984.0,\n      'datetime': FakeDatetime(2025, 2, 22, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19438.0,\n      'datetime': FakeDatetime(2025, 2, 22, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19267.0,\n      'datetime': FakeDatetime(2025, 2, 22, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18874.0,\n      'datetime': FakeDatetime(2025, 2, 22, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18335.0,\n      'datetime': FakeDatetime(2025, 2, 22, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17694.0,\n      'datetime': FakeDatetime(2025, 2, 22, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17015.0,\n      'datetime': FakeDatetime(2025, 2, 22, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16375.0,\n      'datetime': FakeDatetime(2025, 2, 23, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 15968.0,\n      'datetime': FakeDatetime(2025, 2, 23, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 15711.0,\n      'datetime': FakeDatetime(2025, 2, 23, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 15581.0,\n      'datetime': FakeDatetime(2025, 2, 23, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 15628.0,\n      'datetime': FakeDatetime(2025, 2, 23, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 15889.0,\n      'datetime': FakeDatetime(2025, 2, 23, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16309.0,\n      'datetime': FakeDatetime(2025, 2, 23, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16693.0,\n      'datetime': FakeDatetime(2025, 2, 23, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16964.0,\n      'datetime': FakeDatetime(2025, 2, 23, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16907.0,\n      'datetime': FakeDatetime(2025, 2, 23, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16763.0,\n      'datetime': FakeDatetime(2025, 2, 23, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16723.0,\n      'datetime': FakeDatetime(2025, 2, 23, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16592.0,\n      'datetime': FakeDatetime(2025, 2, 23, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16544.0,\n      'datetime': FakeDatetime(2025, 2, 23, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16720.0,\n      'datetime': FakeDatetime(2025, 2, 23, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17257.0,\n      'datetime': FakeDatetime(2025, 2, 23, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18053.0,\n      'datetime': FakeDatetime(2025, 2, 23, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18689.0,\n      'datetime': FakeDatetime(2025, 2, 23, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19211.0,\n      'datetime': FakeDatetime(2025, 2, 23, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19062.0,\n      'datetime': FakeDatetime(2025, 2, 23, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18686.0,\n      'datetime': FakeDatetime(2025, 2, 23, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18114.0,\n      'datetime': FakeDatetime(2025, 2, 23, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17412.0,\n      'datetime': FakeDatetime(2025, 2, 23, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16694.0,\n      'datetime': FakeDatetime(2025, 2, 23, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16031.0,\n      'datetime': FakeDatetime(2025, 2, 24, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 15695.0,\n      'datetime': FakeDatetime(2025, 2, 24, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 15514.0,\n      'datetime': FakeDatetime(2025, 2, 24, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 15480.0,\n      'datetime': FakeDatetime(2025, 2, 24, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 15766.0,\n      'datetime': FakeDatetime(2025, 2, 24, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16601.0,\n      'datetime': FakeDatetime(2025, 2, 24, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17973.0,\n      'datetime': FakeDatetime(2025, 2, 24, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18983.0,\n      'datetime': FakeDatetime(2025, 2, 24, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19206.0,\n      'datetime': FakeDatetime(2025, 2, 24, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18980.0,\n      'datetime': FakeDatetime(2025, 2, 24, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18661.0,\n      'datetime': FakeDatetime(2025, 2, 24, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18360.0,\n      'datetime': FakeDatetime(2025, 2, 24, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18022.0,\n      'datetime': FakeDatetime(2025, 2, 24, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17875.0,\n      'datetime': FakeDatetime(2025, 2, 24, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17858.0,\n      'datetime': FakeDatetime(2025, 2, 24, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18173.0,\n      'datetime': FakeDatetime(2025, 2, 24, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18764.0,\n      'datetime': FakeDatetime(2025, 2, 24, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19364.0,\n      'datetime': FakeDatetime(2025, 2, 24, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19854.0,\n      'datetime': FakeDatetime(2025, 2, 24, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19650.0,\n      'datetime': FakeDatetime(2025, 2, 24, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 19113.0,\n      'datetime': FakeDatetime(2025, 2, 24, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 18341.0,\n      'datetime': FakeDatetime(2025, 2, 24, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 17349.0,\n      'datetime': FakeDatetime(2025, 2, 24, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'consumption': 16465.0,\n      'datetime': FakeDatetime(2025, 2, 24, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-NY-NYIS',\n    }),\n  ])\n# ---\n# name: test_snapshot_fetch_production_more_than_9_days_in_past\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8406.0,\n        'hydro': 1576.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 214.0,\n        'wind': 268.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8225.0,\n        'hydro': 1565.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 212.0,\n        'wind': 265.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8091.0,\n        'hydro': 1569.0,\n        'nuclear': 3253.0,\n        'oil': 1.0,\n        'unknown': 215.0,\n        'wind': 259.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8028.0,\n        'hydro': 1572.0,\n        'nuclear': 3253.0,\n        'oil': 1.0,\n        'unknown': 205.0,\n        'wind': 259.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7984.0,\n        'hydro': 1550.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 257.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7909.0,\n        'hydro': 1531.0,\n        'nuclear': 3252.0,\n        'oil': 0.0,\n        'unknown': 213.0,\n        'wind': 257.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7854.0,\n        'hydro': 1555.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 207.0,\n        'wind': 258.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7822.0,\n        'hydro': 1565.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 260.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7812.0,\n        'hydro': 1567.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 254.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7827.0,\n        'hydro': 1550.0,\n        'nuclear': 3253.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 252.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 0, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7852.0,\n        'hydro': 1502.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 197.0,\n        'wind': 251.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7905.0,\n        'hydro': 1530.0,\n        'nuclear': 3253.0,\n        'oil': 1.0,\n        'unknown': 194.0,\n        'wind': 245.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8144.0,\n        'hydro': 1672.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 230.0,\n        'wind': 240.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8289.0,\n        'hydro': 1693.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 233.0,\n        'wind': 239.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8291.0,\n        'hydro': 1660.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 232.0,\n        'wind': 236.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8227.0,\n        'hydro': 1642.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 233.0,\n        'wind': 240.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8152.0,\n        'hydro': 1629.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 232.0,\n        'wind': 250.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8081.0,\n        'hydro': 1593.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 235.0,\n        'wind': 256.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8002.0,\n        'hydro': 1583.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 234.0,\n        'wind': 263.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7944.0,\n        'hydro': 1574.0,\n        'nuclear': 3251.0,\n        'oil': 0.0,\n        'unknown': 233.0,\n        'wind': 261.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7870.0,\n        'hydro': 1581.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 232.0,\n        'wind': 259.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7775.0,\n        'hydro': 1599.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 222.0,\n        'wind': 254.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 1, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7732.0,\n        'hydro': 1575.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 199.0,\n        'wind': 248.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7716.0,\n        'hydro': 1554.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 238.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7704.0,\n        'hydro': 1514.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 231.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7687.0,\n        'hydro': 1535.0,\n        'nuclear': 3253.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 229.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7672.0,\n        'hydro': 1557.0,\n        'nuclear': 3253.0,\n        'oil': 1.0,\n        'unknown': 193.0,\n        'wind': 227.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7671.0,\n        'hydro': 1561.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 192.0,\n        'wind': 234.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7671.0,\n        'hydro': 1542.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 191.0,\n        'wind': 240.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7669.0,\n        'hydro': 1506.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 194.0,\n        'wind': 250.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7658.0,\n        'hydro': 1459.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 197.0,\n        'wind': 264.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7640.0,\n        'hydro': 1422.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 271.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7636.0,\n        'hydro': 1412.0,\n        'nuclear': 3253.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 273.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7633.0,\n        'hydro': 1431.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 276.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 2, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7613.0,\n        'hydro': 1422.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 199.0,\n        'wind': 279.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7584.0,\n        'hydro': 1444.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 282.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7552.0,\n        'hydro': 1481.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 287.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7553.0,\n        'hydro': 1486.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 282.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7547.0,\n        'hydro': 1497.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 277.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7524.0,\n        'hydro': 1520.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 274.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7528.0,\n        'hydro': 1518.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 197.0,\n        'wind': 281.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7545.0,\n        'hydro': 1499.0,\n        'nuclear': 3253.0,\n        'oil': 1.0,\n        'unknown': 190.0,\n        'wind': 284.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7560.0,\n        'hydro': 1487.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 192.0,\n        'wind': 285.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7557.0,\n        'hydro': 1485.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 288.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7553.0,\n        'hydro': 1490.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 193.0,\n        'wind': 284.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7568.0,\n        'hydro': 1508.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 281.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 3, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7606.0,\n        'hydro': 1501.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 269.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7584.0,\n        'hydro': 1488.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 263.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7521.0,\n        'hydro': 1437.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 263.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7435.0,\n        'hydro': 1450.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 197.0,\n        'wind': 260.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7458.0,\n        'hydro': 1468.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 256.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7504.0,\n        'hydro': 1493.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 252.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7522.0,\n        'hydro': 1485.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 241.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7551.0,\n        'hydro': 1480.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 232.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7563.0,\n        'hydro': 1447.0,\n        'nuclear': 3243.0,\n        'oil': 1.0,\n        'unknown': 199.0,\n        'wind': 228.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7556.0,\n        'hydro': 1452.0,\n        'nuclear': 3231.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 223.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7576.0,\n        'hydro': 1478.0,\n        'nuclear': 3237.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 221.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7593.0,\n        'hydro': 1425.0,\n        'nuclear': 3245.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 234.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 4, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7600.0,\n        'hydro': 1428.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 210.0,\n        'wind': 249.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7599.0,\n        'hydro': 1456.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 254.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7710.0,\n        'hydro': 1583.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 257.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7849.0,\n        'hydro': 1717.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 255.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7927.0,\n        'hydro': 1736.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 255.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7994.0,\n        'hydro': 1710.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 199.0,\n        'wind': 264.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8005.0,\n        'hydro': 1704.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 197.0,\n        'wind': 272.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8067.0,\n        'hydro': 1725.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 277.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8132.0,\n        'hydro': 1748.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 277.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8176.0,\n        'hydro': 1776.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 279.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8216.0,\n        'hydro': 1832.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 281.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8285.0,\n        'hydro': 1950.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 277.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 5, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8361.0,\n        'hydro': 1984.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 193.0,\n        'wind': 273.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8359.0,\n        'hydro': 2158.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 197.0,\n        'wind': 269.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8534.0,\n        'hydro': 2426.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 269.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8888.0,\n        'hydro': 2575.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 273.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8913.0,\n        'hydro': 2634.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 208.0,\n        'wind': 276.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8885.0,\n        'hydro': 2768.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 271.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8877.0,\n        'hydro': 2930.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 268.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8883.0,\n        'hydro': 3075.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 192.0,\n        'wind': 271.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8884.0,\n        'hydro': 3174.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 195.0,\n        'wind': 277.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8896.0,\n        'hydro': 3275.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 284.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8974.0,\n        'hydro': 3282.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 288.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9092.0,\n        'hydro': 3329.0,\n        'nuclear': 3252.0,\n        'oil': 0.0,\n        'unknown': 210.0,\n        'wind': 290.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 6, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9223.0,\n        'hydro': 3384.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 214.0,\n        'wind': 289.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9152.0,\n        'hydro': 3357.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 209.0,\n        'wind': 290.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8990.0,\n        'hydro': 3391.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 212.0,\n        'wind': 298.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9009.0,\n        'hydro': 3397.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 209.0,\n        'wind': 304.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9037.0,\n        'hydro': 3425.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 234.0,\n        'wind': 301.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9032.0,\n        'hydro': 3439.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 225.0,\n        'wind': 298.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9026.0,\n        'hydro': 3394.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 227.0,\n        'wind': 294.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9046.0,\n        'hydro': 3432.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 230.0,\n        'wind': 289.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9079.0,\n        'hydro': 3444.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 238.0,\n        'wind': 280.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9097.0,\n        'hydro': 3452.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 248.0,\n        'wind': 273.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9094.0,\n        'hydro': 3488.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 269.0,\n        'wind': 268.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9116.0,\n        'hydro': 3498.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 301.0,\n        'wind': 268.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 7, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9180.0,\n        'hydro': 3486.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 305.0,\n        'wind': 258.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9216.0,\n        'hydro': 3485.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 312.0,\n        'wind': 253.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9304.0,\n        'hydro': 3427.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 335.0,\n        'wind': 245.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9339.0,\n        'hydro': 3406.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 351.0,\n        'wind': 235.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9289.0,\n        'hydro': 3364.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 368.0,\n        'wind': 229.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9158.0,\n        'hydro': 3266.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 382.0,\n        'wind': 217.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9058.0,\n        'hydro': 3164.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 387.0,\n        'wind': 215.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9025.0,\n        'hydro': 3153.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 402.0,\n        'wind': 211.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8960.0,\n        'hydro': 3147.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 408.0,\n        'wind': 209.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8873.0,\n        'hydro': 3137.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 418.0,\n        'wind': 207.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8801.0,\n        'hydro': 3175.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 423.0,\n        'wind': 206.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8763.0,\n        'hydro': 3182.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 438.0,\n        'wind': 202.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 8, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8767.0,\n        'hydro': 3119.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 446.0,\n        'wind': 202.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8901.0,\n        'hydro': 3028.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 436.0,\n        'wind': 208.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8941.0,\n        'hydro': 3126.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 435.0,\n        'wind': 216.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8895.0,\n        'hydro': 3218.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 450.0,\n        'wind': 223.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8870.0,\n        'hydro': 3159.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 465.0,\n        'wind': 226.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8880.0,\n        'hydro': 3172.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 475.0,\n        'wind': 235.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8911.0,\n        'hydro': 3179.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 473.0,\n        'wind': 236.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8903.0,\n        'hydro': 3155.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 480.0,\n        'wind': 246.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8931.0,\n        'hydro': 3151.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 481.0,\n        'wind': 258.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8928.0,\n        'hydro': 3153.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 488.0,\n        'wind': 270.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8898.0,\n        'hydro': 3174.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 489.0,\n        'wind': 290.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8845.0,\n        'hydro': 3151.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 491.0,\n        'wind': 299.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 9, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8807.0,\n        'hydro': 3107.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 489.0,\n        'wind': 308.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8820.0,\n        'hydro': 2974.0,\n        'nuclear': 3251.0,\n        'oil': 1.0,\n        'unknown': 488.0,\n        'wind': 318.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8749.0,\n        'hydro': 2773.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 478.0,\n        'wind': 317.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8563.0,\n        'hydro': 2683.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 469.0,\n        'wind': 331.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8436.0,\n        'hydro': 2692.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 480.0,\n        'wind': 346.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8375.0,\n        'hydro': 2653.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 473.0,\n        'wind': 368.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8265.0,\n        'hydro': 2650.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 474.0,\n        'wind': 379.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8140.0,\n        'hydro': 2681.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 465.0,\n        'wind': 390.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8088.0,\n        'hydro': 2666.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 470.0,\n        'wind': 383.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7989.0,\n        'hydro': 2626.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 480.0,\n        'wind': 392.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7960.0,\n        'hydro': 2609.0,\n        'nuclear': 3248.0,\n        'oil': 6.0,\n        'unknown': 487.0,\n        'wind': 394.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7917.0,\n        'hydro': 2593.0,\n        'nuclear': 3247.0,\n        'oil': 57.0,\n        'unknown': 500.0,\n        'wind': 411.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 10, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7817.0,\n        'hydro': 2595.0,\n        'nuclear': 3250.0,\n        'oil': 62.0,\n        'unknown': 503.0,\n        'wind': 428.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 11, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7689.0,\n        'hydro': 2604.0,\n        'nuclear': 3248.0,\n        'oil': 13.0,\n        'unknown': 514.0,\n        'wind': 433.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 11, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7548.0,\n        'hydro': 2562.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 530.0,\n        'wind': 436.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      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'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 11, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7546.0,\n        'hydro': 2549.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 517.0,\n        'wind': 432.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 11, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7585.0,\n        'hydro': 2569.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 506.0,\n        'wind': 433.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      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<EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 11, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7556.0,\n        'hydro': 2682.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 510.0,\n        'wind': 424.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 11, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7569.0,\n        'hydro': 2751.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 510.0,\n        'wind': 424.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 11, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7591.0,\n        'hydro': 2768.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 504.0,\n        'wind': 436.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 11, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7599.0,\n        'hydro': 2770.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 495.0,\n        'wind': 436.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 12, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7626.0,\n        'hydro': 2728.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 487.0,\n        'wind': 426.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 12, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7607.0,\n        'hydro': 2700.0,\n        'nuclear': 3244.0,\n 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'hydro': 2737.0,\n        'nuclear': 3242.0,\n        'oil': 1.0,\n        'unknown': 465.0,\n        'wind': 411.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 12, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7508.0,\n        'hydro': 2778.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 468.0,\n        'wind': 420.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 12, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      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tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7537.0,\n        'hydro': 2808.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 470.0,\n        'wind': 447.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 12, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7626.0,\n        'hydro': 2792.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 476.0,\n        'wind': 450.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 12, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7716.0,\n        'hydro': 2768.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 472.0,\n        'wind': 450.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 12, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7728.0,\n        'hydro': 2735.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 452.0,\n        'wind': 456.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 12, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7775.0,\n        'hydro': 2713.0,\n        'nuclear': 3248.0,\n        'oil': 3.0,\n        'unknown': 446.0,\n        'wind': 462.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7776.0,\n        'hydro': 2661.0,\n        'nuclear': 3248.0,\n        'oil': 6.0,\n        'unknown': 448.0,\n        'wind': 464.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7744.0,\n        'hydro': 2627.0,\n        'nuclear': 3248.0,\n        'oil': 6.0,\n        'unknown': 459.0,\n        'wind': 471.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7710.0,\n        'hydro': 2638.0,\n        'nuclear': 3248.0,\n        'oil': 6.0,\n        'unknown': 458.0,\n        'wind': 457.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7689.0,\n        'hydro': 2648.0,\n        'nuclear': 3247.0,\n        'oil': 6.0,\n        'unknown': 450.0,\n        'wind': 479.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7650.0,\n        'hydro': 2620.0,\n        'nuclear': 3246.0,\n        'oil': 6.0,\n        'unknown': 442.0,\n        'wind': 487.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7606.0,\n        'hydro': 2649.0,\n        'nuclear': 3248.0,\n        'oil': 6.0,\n        'unknown': 436.0,\n        'wind': 494.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7575.0,\n        'hydro': 2668.0,\n        'nuclear': 3250.0,\n        'oil': 6.0,\n        'unknown': 427.0,\n        'wind': 499.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7560.0,\n        'hydro': 2716.0,\n        'nuclear': 3249.0,\n        'oil': 6.0,\n        'unknown': 412.0,\n        'wind': 523.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7560.0,\n        'hydro': 2730.0,\n        'nuclear': 3248.0,\n        'oil': 6.0,\n        'unknown': 410.0,\n        'wind': 545.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7601.0,\n        'hydro': 2718.0,\n        'nuclear': 3249.0,\n        'oil': 6.0,\n        'unknown': 398.0,\n        'wind': 564.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7635.0,\n        'hydro': 2722.0,\n        'nuclear': 3250.0,\n        'oil': 6.0,\n        'unknown': 402.0,\n        'wind': 603.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 13, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7643.0,\n        'hydro': 2724.0,\n        'nuclear': 3248.0,\n        'oil': 6.0,\n        'unknown': 398.0,\n        'wind': 608.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 14, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7682.0,\n     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tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7882.0,\n        'hydro': 2684.0,\n        'nuclear': 3249.0,\n        'oil': 6.0,\n        'unknown': 359.0,\n        'wind': 714.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 14, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7861.0,\n        'hydro': 2657.0,\n        'nuclear': 3250.0,\n        'oil': 2.0,\n        'unknown': 338.0,\n        'wind': 742.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 14, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7860.0,\n        'hydro': 2674.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 321.0,\n        'wind': 763.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 14, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7849.0,\n        'hydro': 2704.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 322.0,\n        'wind': 755.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      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'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 14, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7976.0,\n        'hydro': 2806.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 308.0,\n        'wind': 666.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 14, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8097.0,\n        'hydro': 2763.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 298.0,\n        'wind': 681.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8147.0,\n        'hydro': 2677.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 292.0,\n        'wind': 711.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8098.0,\n        'hydro': 2560.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 285.0,\n        'wind': 695.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8035.0,\n        'hydro': 2544.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 275.0,\n        'wind': 623.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7993.0,\n        'hydro': 2661.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 271.0,\n        'wind': 555.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7970.0,\n        'hydro': 2703.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 262.0,\n        'wind': 557.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7978.0,\n        'hydro': 2667.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 257.0,\n        'wind': 563.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8067.0,\n        'hydro': 2651.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 257.0,\n        'wind': 581.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8168.0,\n        'hydro': 2625.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 264.0,\n        'wind': 588.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8209.0,\n        'hydro': 2603.0,\n        'nuclear': 3247.0,\n        'oil': 0.0,\n        'unknown': 267.0,\n        'wind': 584.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 37, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8233.0,\n        'hydro': 2631.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 263.0,\n        'wind': 591.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8249.0,\n        'hydro': 2671.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 260.0,\n        'wind': 592.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 15, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      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tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8281.0,\n        'hydro': 2685.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 257.0,\n        'wind': 595.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8317.0,\n        'hydro': 2831.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 251.0,\n        'wind': 597.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8421.0,\n        'hydro': 3057.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 252.0,\n        'wind': 614.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8555.0,\n        'hydro': 3138.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 255.0,\n        'wind': 645.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8636.0,\n        'hydro': 3238.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 230.0,\n        'wind': 638.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8767.0,\n        'hydro': 3261.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 230.0,\n        'wind': 642.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8816.0,\n        'hydro': 3233.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 233.0,\n        'wind': 731.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8814.0,\n        'hydro': 3222.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 229.0,\n        'wind': 782.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8807.0,\n        'hydro': 3176.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 226.0,\n        'wind': 802.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8848.0,\n        'hydro': 3158.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 234.0,\n        'wind': 813.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8852.0,\n        'hydro': 3165.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 239.0,\n        'wind': 900.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8883.0,\n        'hydro': 3159.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 241.0,\n        'wind': 996.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 46, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8870.0,\n        'hydro': 3138.0,\n        'nuclear': 3252.0,\n        'oil': 1.0,\n        'unknown': 241.0,\n        'wind': 989.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8875.0,\n        'hydro': 3097.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 235.0,\n        'wind': 984.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 16, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8943.0,\n        'hydro': 3078.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 233.0,\n        'wind': 964.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8996.0,\n        'hydro': 3123.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 228.0,\n        'wind': 960.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8968.0,\n        'hydro': 3135.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 210.0,\n        'wind': 971.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8935.0,\n        'hydro': 3022.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 212.0,\n        'wind': 986.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8896.0,\n        'hydro': 3165.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 217.0,\n        'wind': 964.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8971.0,\n        'hydro': 3197.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 218.0,\n        'wind': 972.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8910.0,\n        'hydro': 3296.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 220.0,\n        'wind': 993.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8996.0,\n        'hydro': 3341.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 210.0,\n        'wind': 974.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9089.0,\n        'hydro': 3362.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 211.0,\n        'wind': 984.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9131.0,\n        'hydro': 3387.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 207.0,\n        'wind': 1010.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9156.0,\n        'hydro': 3447.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 208.0,\n        'wind': 998.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9321.0,\n        'hydro': 3407.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 1013.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 17, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9358.0,\n        'hydro': 3436.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 1031.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9408.0,\n        'hydro': 3507.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 209.0,\n        'wind': 1032.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9488.0,\n        'hydro': 3657.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 212.0,\n        'wind': 1033.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9643.0,\n        'hydro': 3786.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 223.0,\n        'wind': 1044.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9672.0,\n        'hydro': 3722.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 224.0,\n        'wind': 1055.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9766.0,\n        'hydro': 3680.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 207.0,\n        'wind': 1055.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9775.0,\n        'hydro': 3665.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 1067.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9742.0,\n        'hydro': 3660.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 1079.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9726.0,\n        'hydro': 3647.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 1084.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9689.0,\n        'hydro': 3651.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 207.0,\n        'wind': 1098.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9641.0,\n        'hydro': 3651.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 211.0,\n        'wind': 1117.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9606.0,\n        'hydro': 3660.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 212.0,\n        'wind': 1120.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 18, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9584.0,\n        'hydro': 3666.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 210.0,\n        'wind': 1131.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9607.0,\n        'hydro': 3647.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 208.0,\n        'wind': 1158.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9668.0,\n        'hydro': 3442.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 1161.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9611.0,\n        'hydro': 3377.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 1175.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9505.0,\n        'hydro': 3413.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 211.0,\n        'wind': 1183.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9457.0,\n        'hydro': 3419.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 1191.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9435.0,\n        'hydro': 3433.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 195.0,\n        'wind': 1200.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 22, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9423.0,\n        'hydro': 3424.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 1203.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9423.0,\n        'hydro': 3441.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 1208.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9385.0,\n        'hydro': 3416.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 208.0,\n        'wind': 1236.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9320.0,\n        'hydro': 3399.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 208.0,\n        'wind': 1235.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9258.0,\n        'hydro': 3450.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 1242.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 42, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9265.0,\n        'hydro': 3391.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 204.0,\n        'wind': 1241.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9267.0,\n        'hydro': 3400.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 1220.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9298.0,\n        'hydro': 3410.0,\n        'nuclear': 3246.0,\n        'oil': 0.0,\n        'unknown': 197.0,\n        'wind': 1196.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9309.0,\n        'hydro': 3386.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 199.0,\n        'wind': 1219.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 19, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9317.0,\n        'hydro': 3393.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 204.0,\n        'wind': 1248.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9344.0,\n        'hydro': 3366.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 205.0,\n        'wind': 1269.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9542.0,\n        'hydro': 3332.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 213.0,\n        'wind': 1271.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9674.0,\n        'hydro': 3282.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 207.0,\n        'wind': 1265.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9646.0,\n        'hydro': 3275.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 1254.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9654.0,\n        'hydro': 3311.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 1251.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9662.0,\n        'hydro': 3276.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 1255.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9608.0,\n        'hydro': 3258.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 1262.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9576.0,\n        'hydro': 3243.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 1250.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9458.0,\n        'hydro': 3278.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 1240.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9404.0,\n        'hydro': 3288.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 205.0,\n        'wind': 1232.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9346.0,\n        'hydro': 3217.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 205.0,\n        'wind': 1230.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 20, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9260.0,\n        'hydro': 3211.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 204.0,\n        'wind': 1226.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9228.0,\n        'hydro': 3126.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 210.0,\n        'wind': 1215.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9174.0,\n        'hydro': 2923.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 212.0,\n        'wind': 1206.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 9019.0,\n        'hydro': 2820.0,\n        'nuclear': 3245.0,\n        'oil': 1.0,\n        'unknown': 207.0,\n        'wind': 1193.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8969.0,\n        'hydro': 2823.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 211.0,\n        'wind': 1174.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8956.0,\n        'hydro': 2911.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 211.0,\n        'wind': 1159.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8959.0,\n        'hydro': 2926.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 206.0,\n        'wind': 1150.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8936.0,\n        'hydro': 2877.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 207.0,\n        'wind': 1133.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8948.0,\n        'hydro': 2855.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 209.0,\n        'wind': 1122.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8952.0,\n        'hydro': 2839.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 1125.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8916.0,\n        'hydro': 2819.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 1131.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8902.0,\n        'hydro': 2810.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 1134.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 21, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8909.0,\n        'hydro': 2765.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 1137.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8894.0,\n        'hydro': 2670.0,\n        'nuclear': 3245.0,\n        'oil': 1.0,\n        'unknown': 199.0,\n        'wind': 1134.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8678.0,\n        'hydro': 2504.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 197.0,\n        'wind': 1123.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8351.0,\n        'hydro': 2421.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 197.0,\n        'wind': 1092.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8266.0,\n        'hydro': 2446.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 1082.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8294.0,\n        'hydro': 2429.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 197.0,\n        'wind': 1115.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8184.0,\n        'hydro': 2559.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 207.0,\n        'wind': 1109.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 8052.0,\n        'hydro': 2608.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 205.0,\n        'wind': 1103.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7987.0,\n        'hydro': 2600.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 1104.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7932.0,\n        'hydro': 2564.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 1105.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7865.0,\n        'hydro': 2513.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 1102.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7788.0,\n        'hydro': 2469.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 1112.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 22, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7767.0,\n        'hydro': 2379.0,\n        'nuclear': 3250.0,\n        'oil': 1.0,\n        'unknown': 196.0,\n        'wind': 1125.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7745.0,\n        'hydro': 2290.0,\n        'nuclear': 3249.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 1124.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 5, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7673.0,\n        'hydro': 2261.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 1122.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 10, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7617.0,\n        'hydro': 2181.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 202.0,\n        'wind': 1117.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 15, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7606.0,\n        'hydro': 2138.0,\n        'nuclear': 3246.0,\n        'oil': 1.0,\n        'unknown': 203.0,\n        'wind': 1112.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 20, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7568.0,\n        'hydro': 2112.0,\n        'nuclear': 3245.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 1109.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 25, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7526.0,\n        'hydro': 2109.0,\n        'nuclear': 3248.0,\n        'oil': 0.0,\n        'unknown': 197.0,\n        'wind': 1082.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 30, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7476.0,\n        'hydro': 2106.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 1049.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 35, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7432.0,\n        'hydro': 2079.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 195.0,\n        'wind': 1055.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 40, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7373.0,\n        'hydro': 2041.0,\n        'nuclear': 3248.0,\n        'oil': 1.0,\n        'unknown': 199.0,\n        'wind': 1048.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 45, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7323.0,\n        'hydro': 2063.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 201.0,\n        'wind': 1046.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 50, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7307.0,\n        'hydro': 2066.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 200.0,\n        'wind': 1071.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 20, 23, 55, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7307.0,\n        'hydro': 2023.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 198.0,\n        'wind': 1055.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 21, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/New_York')),\n      'production': dict({\n        'gas': 7355.0,\n        'hydro': 1945.0,\n        'nuclear': 3247.0,\n        'oil': 1.0,\n        'unknown': 208.0,\n        'wind': 1040.0,\n      }),\n      'source': 'nyiso.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-NY-NYIS',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_US_PJM.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption_forecast\n  list([\n    dict({\n      'consumption': 76305.0,\n      'datetime': datetime.datetime(2025, 3, 19, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 74852.0,\n      'datetime': datetime.datetime(2025, 3, 19, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 74471.0,\n      'datetime': datetime.datetime(2025, 3, 19, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 74928.0,\n      'datetime': datetime.datetime(2025, 3, 19, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 76951.0,\n      'datetime': datetime.datetime(2025, 3, 19, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 81353.0,\n      'datetime': datetime.datetime(2025, 3, 19, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 88598.0,\n      'datetime': datetime.datetime(2025, 3, 19, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 93469.0,\n      'datetime': datetime.datetime(2025, 3, 19, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 92339.0,\n      'datetime': datetime.datetime(2025, 3, 19, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 89006.0,\n      'datetime': datetime.datetime(2025, 3, 19, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86162.0,\n      'datetime': datetime.datetime(2025, 3, 19, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84080.0,\n      'datetime': datetime.datetime(2025, 3, 19, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 82507.0,\n      'datetime': datetime.datetime(2025, 3, 19, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 81799.0,\n      'datetime': datetime.datetime(2025, 3, 19, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 81303.0,\n      'datetime': datetime.datetime(2025, 3, 19, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 81451.0,\n      'datetime': datetime.datetime(2025, 3, 19, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 82747.0,\n      'datetime': datetime.datetime(2025, 3, 19, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84836.0,\n      'datetime': datetime.datetime(2025, 3, 19, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86744.0,\n      'datetime': datetime.datetime(2025, 3, 19, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 88506.0,\n      'datetime': datetime.datetime(2025, 3, 19, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 89128.0,\n      'datetime': datetime.datetime(2025, 3, 20, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86358.0,\n      'datetime': datetime.datetime(2025, 3, 20, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 81608.0,\n      'datetime': datetime.datetime(2025, 3, 20, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 77019.0,\n      'datetime': datetime.datetime(2025, 3, 20, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 74095.0,\n      'datetime': datetime.datetime(2025, 3, 20, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 72427.0,\n      'datetime': datetime.datetime(2025, 3, 20, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 71681.0,\n      'datetime': datetime.datetime(2025, 3, 20, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 71740.0,\n      'datetime': datetime.datetime(2025, 3, 20, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 73428.0,\n      'datetime': datetime.datetime(2025, 3, 20, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 77789.0,\n      'datetime': datetime.datetime(2025, 3, 20, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84620.0,\n      'datetime': datetime.datetime(2025, 3, 20, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 89089.0,\n      'datetime': datetime.datetime(2025, 3, 20, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 89236.0,\n      'datetime': datetime.datetime(2025, 3, 20, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 87766.0,\n      'datetime': datetime.datetime(2025, 3, 20, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86427.0,\n      'datetime': datetime.datetime(2025, 3, 20, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 85208.0,\n      'datetime': datetime.datetime(2025, 3, 20, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84287.0,\n      'datetime': datetime.datetime(2025, 3, 20, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 83754.0,\n      'datetime': datetime.datetime(2025, 3, 20, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 83121.0,\n      'datetime': datetime.datetime(2025, 3, 20, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 83046.0,\n      'datetime': datetime.datetime(2025, 3, 20, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84164.0,\n      'datetime': datetime.datetime(2025, 3, 20, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86267.0,\n      'datetime': datetime.datetime(2025, 3, 20, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 88340.0,\n      'datetime': datetime.datetime(2025, 3, 20, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 90076.0,\n      'datetime': datetime.datetime(2025, 3, 20, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 90629.0,\n      'datetime': datetime.datetime(2025, 3, 21, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 88398.0,\n      'datetime': datetime.datetime(2025, 3, 21, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84538.0,\n      'datetime': datetime.datetime(2025, 3, 21, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 80618.0,\n      'datetime': datetime.datetime(2025, 3, 21, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 79356.0,\n      'datetime': datetime.datetime(2025, 3, 21, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 78008.0,\n      'datetime': datetime.datetime(2025, 3, 21, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 77643.0,\n      'datetime': datetime.datetime(2025, 3, 21, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 78074.0,\n      'datetime': datetime.datetime(2025, 3, 21, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 79950.0,\n      'datetime': datetime.datetime(2025, 3, 21, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84480.0,\n      'datetime': datetime.datetime(2025, 3, 21, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 91264.0,\n      'datetime': datetime.datetime(2025, 3, 21, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 95522.0,\n      'datetime': datetime.datetime(2025, 3, 21, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 95281.0,\n      'datetime': datetime.datetime(2025, 3, 21, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 92814.0,\n      'datetime': datetime.datetime(2025, 3, 21, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 90336.0,\n      'datetime': datetime.datetime(2025, 3, 21, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 87883.0,\n      'datetime': datetime.datetime(2025, 3, 21, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 85900.0,\n      'datetime': datetime.datetime(2025, 3, 21, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84152.0,\n      'datetime': datetime.datetime(2025, 3, 21, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 82582.0,\n      'datetime': datetime.datetime(2025, 3, 21, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 81760.0,\n      'datetime': datetime.datetime(2025, 3, 21, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 82543.0,\n      'datetime': datetime.datetime(2025, 3, 21, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84391.0,\n      'datetime': datetime.datetime(2025, 3, 21, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86390.0,\n      'datetime': datetime.datetime(2025, 3, 21, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 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'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 81634.0,\n      'datetime': datetime.datetime(2025, 3, 22, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 79101.0,\n      'datetime': datetime.datetime(2025, 3, 22, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 77536.0,\n      'datetime': datetime.datetime(2025, 3, 22, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 76738.0,\n      'datetime': datetime.datetime(2025, 3, 22, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 76623.0,\n      'datetime': datetime.datetime(2025, 3, 22, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 77429.0,\n      'datetime': datetime.datetime(2025, 3, 22, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 79491.0,\n      'datetime': datetime.datetime(2025, 3, 22, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 82521.0,\n      'datetime': datetime.datetime(2025, 3, 22, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 85094.0,\n      'datetime': datetime.datetime(2025, 3, 22, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 85891.0,\n      'datetime': datetime.datetime(2025, 3, 22, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84966.0,\n      'datetime': datetime.datetime(2025, 3, 22, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 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'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 76743.0,\n      'datetime': datetime.datetime(2025, 3, 22, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 76467.0,\n      'datetime': datetime.datetime(2025, 3, 22, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 77608.0,\n      'datetime': datetime.datetime(2025, 3, 22, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 79818.0,\n      'datetime': datetime.datetime(2025, 3, 22, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 82258.0,\n      'datetime': datetime.datetime(2025, 3, 22, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84519.0,\n      'datetime': datetime.datetime(2025, 3, 22, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 85577.0,\n      'datetime': datetime.datetime(2025, 3, 23, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84433.0,\n      'datetime': datetime.datetime(2025, 3, 23, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 82096.0,\n      'datetime': datetime.datetime(2025, 3, 23, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 79290.0,\n      'datetime': datetime.datetime(2025, 3, 23, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 78679.0,\n      'datetime': datetime.datetime(2025, 3, 23, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 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'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 80275.0,\n      'datetime': datetime.datetime(2025, 3, 23, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 83011.0,\n      'datetime': datetime.datetime(2025, 3, 23, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 85561.0,\n      'datetime': datetime.datetime(2025, 3, 23, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86570.0,\n      'datetime': datetime.datetime(2025, 3, 23, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      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'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 89066.0,\n      'datetime': datetime.datetime(2025, 3, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 87465.0,\n      'datetime': datetime.datetime(2025, 3, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 84615.0,\n      'datetime': datetime.datetime(2025, 3, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 81601.0,\n      'datetime': datetime.datetime(2025, 3, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      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'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 85847.0,\n      'datetime': datetime.datetime(2025, 3, 24, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86726.0,\n      'datetime': datetime.datetime(2025, 3, 24, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 88856.0,\n      'datetime': datetime.datetime(2025, 3, 24, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 91135.0,\n      'datetime': datetime.datetime(2025, 3, 24, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 92891.0,\n      'datetime': datetime.datetime(2025, 3, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 93129.0,\n      'datetime': datetime.datetime(2025, 3, 25, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 90566.0,\n      'datetime': datetime.datetime(2025, 3, 25, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86533.0,\n      'datetime': datetime.datetime(2025, 3, 25, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 82573.0,\n      'datetime': datetime.datetime(2025, 3, 25, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 80043.0,\n      'datetime': datetime.datetime(2025, 3, 25, 4, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 78650.0,\n      'datetime': datetime.datetime(2025, 3, 25, 5, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 78099.0,\n      'datetime': datetime.datetime(2025, 3, 25, 6, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 78426.0,\n      'datetime': datetime.datetime(2025, 3, 25, 7, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 80343.0,\n      'datetime': datetime.datetime(2025, 3, 25, 8, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 85072.0,\n      'datetime': datetime.datetime(2025, 3, 25, 9, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 92252.0,\n      'datetime': datetime.datetime(2025, 3, 25, 10, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 96814.0,\n      'datetime': datetime.datetime(2025, 3, 25, 11, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 96723.0,\n      'datetime': datetime.datetime(2025, 3, 25, 12, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 94655.0,\n      'datetime': datetime.datetime(2025, 3, 25, 13, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 92562.0,\n      'datetime': datetime.datetime(2025, 3, 25, 14, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 90539.0,\n      'datetime': datetime.datetime(2025, 3, 25, 15, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 88953.0,\n      'datetime': datetime.datetime(2025, 3, 25, 16, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 87837.0,\n      'datetime': datetime.datetime(2025, 3, 25, 17, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86667.0,\n      'datetime': datetime.datetime(2025, 3, 25, 18, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 86196.0,\n      'datetime': datetime.datetime(2025, 3, 25, 19, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 87336.0,\n      'datetime': datetime.datetime(2025, 3, 25, 20, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 89836.0,\n      'datetime': datetime.datetime(2025, 3, 25, 21, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 92501.0,\n      'datetime': datetime.datetime(2025, 3, 25, 22, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 94627.0,\n      'datetime': datetime.datetime(2025, 3, 25, 23, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 94946.0,\n      'datetime': datetime.datetime(2025, 3, 26, 0, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 92695.0,\n      'datetime': datetime.datetime(2025, 3, 26, 1, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 88839.0,\n      'datetime': datetime.datetime(2025, 3, 26, 2, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'consumption': 85054.0,\n      'datetime': datetime.datetime(2025, 3, 26, 3, 0, tzinfo=datetime.timezone.utc),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n  ])\n# ---\n# name: test_fetch_wind_solar_forecasts\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 5674.163,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 6406.127,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 6771.246,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 6846.105,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 6889.084,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 7046.181,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 7141.57,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 7272.236,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 7393.612,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 7533.526,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 0.0,\n        'wind': 7749.602,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 15.852,\n        'wind': 7933.133,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 1275.265,\n        'wind': 7865.394,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 5048.272,\n        'wind': 7547.31,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7336.233,\n        'wind': 7193.234,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7802.926,\n        'wind': 6876.753,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7680.094,\n        'wind': 6583.043,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7496.111,\n        'wind': 6259.908,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 7269.733,\n        'wind': 5886.133,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6945.879,\n        'wind': 5548.17,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 6374.432,\n        'wind': 5264.66,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3759.787,\n        'wind': 4939.546,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 22, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 637.059,\n        'wind': 4831.753,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 24, 23, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'solar': 3.684,\n        'wind': 5007.297,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.forecasted: 'forecasted'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n  ])\n# ---\n# name: test_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 0, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 16908.0,\n        'gas': 47280.0,\n        'hydro': 2971.0,\n        'nuclear': 32919.0,\n        'oil': 871.0,\n        'solar': 28.0,\n        'unknown': 1838.0,\n        'wind': 2782.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -8.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 1, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 17147.0,\n        'gas': 46725.0,\n        'hydro': 2217.0,\n        'nuclear': 32940.0,\n        'oil': 837.0,\n        'solar': 28.0,\n        'unknown': 1641.0,\n        'wind': 3202.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -3.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 2, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 17055.0,\n        'gas': 45683.0,\n        'hydro': 1464.0,\n        'nuclear': 32965.0,\n        'oil': 566.0,\n        'solar': 28.0,\n        'unknown': 1551.0,\n        'wind': 3504.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -1.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 3, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 16889.0,\n        'gas': 43567.0,\n        'hydro': 980.0,\n        'nuclear': 32987.0,\n        'oil': 206.0,\n        'solar': 28.0,\n        'unknown': 1540.0,\n        'wind': 4030.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 4, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 16373.0,\n        'gas': 42175.0,\n        'hydro': 638.0,\n        'nuclear': 32994.0,\n        'oil': 209.0,\n        'solar': 28.0,\n        'unknown': 841.0,\n        'wind': 4468.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 5, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 15849.0,\n        'gas': 41727.0,\n        'hydro': 521.0,\n        'nuclear': 33001.0,\n        'oil': 206.0,\n        'solar': 28.0,\n        'unknown': 666.0,\n        'wind': 5096.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 6, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 15450.0,\n        'gas': 40800.0,\n        'hydro': 452.0,\n        'nuclear': 33011.0,\n        'oil': 206.0,\n        'solar': 28.0,\n        'unknown': 664.0,\n        'wind': 5070.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 7, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 14787.0,\n        'gas': 40089.0,\n        'hydro': 412.0,\n        'nuclear': 33027.0,\n        'oil': 206.0,\n        'solar': 28.0,\n        'unknown': 665.0,\n        'wind': 4624.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 8, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 14447.0,\n        'gas': 39422.0,\n        'hydro': 445.0,\n        'nuclear': 33054.0,\n        'oil': 207.0,\n        'solar': 28.0,\n        'unknown': 669.0,\n        'wind': 4225.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 9, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 14471.0,\n        'gas': 39989.0,\n        'hydro': 442.0,\n        'nuclear': 33076.0,\n        'oil': 209.0,\n        'solar': 28.0,\n        'unknown': 672.0,\n        'wind': 3883.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 10, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 14664.0,\n        'gas': 40113.0,\n        'hydro': 435.0,\n        'nuclear': 33177.0,\n        'oil': 211.0,\n        'solar': 28.0,\n        'unknown': 671.0,\n        'wind': 3144.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 11, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 15121.0,\n        'gas': 40844.0,\n        'hydro': 470.0,\n        'nuclear': 33293.0,\n        'oil': 212.0,\n        'solar': 28.0,\n        'unknown': 672.0,\n        'wind': 2900.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 12, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 15494.0,\n        'gas': 41543.0,\n        'hydro': 934.0,\n        'nuclear': 33392.0,\n        'oil': 210.0,\n        'solar': 148.0,\n        'unknown': 669.0,\n        'wind': 2861.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 13, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 15427.0,\n        'gas': 41516.0,\n        'hydro': 1015.0,\n        'nuclear': 33499.0,\n        'oil': 211.0,\n        'solar': 2022.0,\n        'unknown': 667.0,\n        'wind': 2575.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 14, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 15530.0,\n        'gas': 41489.0,\n        'hydro': 1080.0,\n        'nuclear': 33581.0,\n        'oil': 210.0,\n        'solar': 4579.0,\n        'unknown': 669.0,\n        'wind': 2100.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 15, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 15649.0,\n        'gas': 42431.0,\n        'hydro': 675.0,\n        'nuclear': 33599.0,\n        'oil': 211.0,\n        'solar': 5452.0,\n        'unknown': 668.0,\n        'wind': 1630.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -5.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 16, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 16072.0,\n        'gas': 43125.0,\n        'hydro': 475.0,\n        'nuclear': 33613.0,\n        'oil': 210.0,\n        'solar': 5622.0,\n        'unknown': 666.0,\n        'wind': 1221.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -7.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 17, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 16384.0,\n        'gas': 42723.0,\n        'hydro': 468.0,\n        'nuclear': 33632.0,\n        'oil': 207.0,\n        'solar': 5502.0,\n        'unknown': 660.0,\n        'wind': 1061.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -4.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 18, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 16411.0,\n        'gas': 42256.0,\n        'hydro': 496.0,\n        'nuclear': 33641.0,\n        'oil': 206.0,\n        'solar': 5407.0,\n        'unknown': 667.0,\n        'wind': 1052.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 19, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 16010.0,\n        'gas': 42027.0,\n        'hydro': 457.0,\n        'nuclear': 33640.0,\n        'oil': 205.0,\n        'solar': 5231.0,\n        'unknown': 724.0,\n        'wind': 1187.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 20, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 15907.0,\n        'gas': 41535.0,\n        'hydro': 522.0,\n        'nuclear': 33629.0,\n        'oil': 205.0,\n        'solar': 4629.0,\n        'unknown': 967.0,\n        'wind': 1221.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 9, 21, 0, tzinfo=datetime.timezone.utc),\n      'production': dict({\n        'coal': 15772.0,\n        'gas': 43252.0,\n        'hydro': 1421.0,\n        'nuclear': 33625.0,\n        'oil': 401.0,\n        'solar': 2719.0,\n        'unknown': 1082.0,\n        'wind': 1341.0,\n      }),\n      'source': 'pjm.com',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n        'battery': -0.0,\n      }),\n      'zoneKey': 'US-MIDA-PJM',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_UY/test_fetch_exchange[AR].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[AR]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(0.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(100.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(100.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(100.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(100.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(100.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(100.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(100.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(200.0),\n      'sortedZoneKeys': 'AR->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_UY/test_fetch_exchange[BR-S].ambr",
    "content": "# serializer version: 1\n# name: test_fetch_exchange[BR-S]\n  list([\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(195.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(198.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(295.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n    dict({\n      'datetime': datetime.datetime(2025, 2, 5, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'netFlow': np.float64(290.93),\n      'sortedZoneKeys': 'BR-S->UY',\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_UY.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_consumption\n  list([\n    dict({\n      'consumption': np.float64(1731.86),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1732.458),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1715.165),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1693.582),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1677.182),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1652.852),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1629.982),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1596.87),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1578.282),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1557.033),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1534.061),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1514.345),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1498.047),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1482.896),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1465.763),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1451.229),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1439.428),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1440.445),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1422.723),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1417.507),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1402.141),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1405.939),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1395.53),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1391.632),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1383.089),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1376.833),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1374.049),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1367.204),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1371.433),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1359.559),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1364.302),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1371.365),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1370.068),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1370.062),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1396.507),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1396.392),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1375.166),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1393.172),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1403.321),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1400.663),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1398.53),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1398.705),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1418.518),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1435.745),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1465.539),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1480.5),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1494.548),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1520.417),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1544.338),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1565.434),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1581.274),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1584.206),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1621.782),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1617.905),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1637.64),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1650.671),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1666.065),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1658.289),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1693.934),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1673.718),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1695.598),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1704.433),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1712.769),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1726.845),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1742.346),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'consumption': np.float64(1748.761),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'zoneKey': 'UY',\n    }),\n  ])\n# ---\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 154.684,\n        'hydro': 395.119,\n        'oil': 128.655,\n        'solar': 0.0,\n        'wind': 767.447,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 152.916,\n        'hydro': 438.238,\n        'oil': 107.852,\n        'solar': 0.0,\n        'wind': 737.566,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 156.361,\n        'hydro': 496.103,\n        'oil': 44.848,\n        'solar': 0.0,\n        'wind': 727.966,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 158.724,\n        'hydro': 511.101,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 742.854,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 157.661,\n        'hydro': 495.455,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 731.919,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 0, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 153.527,\n        'hydro': 480.027,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 732.094,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 157.146,\n        'hydro': 468.138,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 716.079,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 156.906,\n        'hydro': 443.227,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 708.558,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 154.275,\n        'hydro': 432.853,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 701.062,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 160.653,\n        'hydro': 348.463,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 758.637,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 157.933,\n        'hydro': 366.232,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 727.716,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 1, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 157.929,\n        'hydro': 331.258,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 736.23,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 160.459,\n        'hydro': 402.771,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 742.558,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 160.341,\n        'hydro': 377.978,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 752.391,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 166.759,\n        'hydro': 362.938,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 744.802,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 158.675,\n        'hydro': 368.605,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 727.29,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 166.314,\n        'hydro': 345.635,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 730.246,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 2, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 167.451,\n        'hydro': 366.527,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 710.268,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 169.128,\n        'hydro': 325.201,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 734.797,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 166.34,\n        'hydro': 320.64,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 734.006,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 165.49,\n        'hydro': 323.343,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 717.903,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 162.273,\n        'hydro': 342.884,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 700.827,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 169.642,\n        'hydro': 344.291,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 686.315,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 3, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 177.356,\n        'hydro': 345.244,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 677.126,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 173.013,\n        'hydro': 363.81,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 653.183,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 188.317,\n        'hydro': 363.843,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 631.147,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 184.619,\n        'hydro': 312.217,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 680.073,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 192.464,\n        'hydro': 345.923,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 633.524,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 195.199,\n        'hydro': 337.275,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 647.946,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 4, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 196.735,\n        'hydro': 382.406,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 589.045,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 196.365,\n        'hydro': 371.214,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 598.966,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 196.728,\n        'hydro': 370.187,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 606.809,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 185.736,\n        'hydro': 364.725,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 628.117,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 181.378,\n        'hydro': 373.291,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 621.931,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 188.1,\n        'hydro': 423.539,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 591.31,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 5, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 173.091,\n        'hydro': 369.194,\n        'oil': 0.0,\n        'solar': 0.0,\n        'wind': 560.5,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 181.917,\n        'hydro': 363.078,\n        'oil': 0.0,\n        'solar': 0.212,\n        'wind': 548.053,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 179.753,\n        'hydro': 309.621,\n        'oil': 0.0,\n        'solar': 0.212,\n        'wind': 614.1,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 187.779,\n        'hydro': 294.993,\n        'oil': 15.071,\n        'solar': 0.212,\n        'wind': 623.373,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 184.904,\n        'hydro': 318.939,\n        'oil': 52.089,\n        'solar': 0.304,\n        'wind': 562.156,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 184.518,\n        'hydro': 290.988,\n        'oil': 51.813,\n        'solar': 1.709,\n        'wind': 487.726,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 6, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 186.724,\n        'hydro': 318.403,\n        'oil': 52.937,\n        'solar': 4.266,\n        'wind': 451.627,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 187.42,\n        'hydro': 305.701,\n        'oil': 52.7,\n        'solar': 8.82,\n        'wind': 477.918,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 182.009,\n        'hydro': 299.406,\n        'oil': 52.7,\n        'solar': 11.788,\n        'wind': 500.437,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 183.697,\n        'hydro': 338.881,\n        'oil': 52.615,\n        'solar': 18.824,\n        'wind': 484.466,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 176.903,\n        'hydro': 390.792,\n        'oil': 52.709,\n        'solar': 29.037,\n        'wind': 443.233,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 185.75,\n        'hydro': 406.541,\n        'oil': 52.819,\n        'solar': 41.491,\n        'wind': 424.723,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 7, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 180.187,\n        'hydro': 319.997,\n        'oil': 60.421,\n        'solar': 54.594,\n        'wind': 421.825,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 175.953,\n        'hydro': 336.359,\n        'oil': 63.048,\n        'solar': 66.349,\n        'wind': 421.097,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 179.788,\n        'hydro': 346.256,\n        'oil': 63.374,\n        'solar': 74.935,\n        'wind': 418.406,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 182.498,\n        'hydro': 363.599,\n        'oil': 63.073,\n        'solar': 82.804,\n        'wind': 415.858,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 185.117,\n        'hydro': 357.809,\n        'oil': 61.469,\n        'solar': 89.015,\n        'wind': 410.942,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 177.75,\n        'hydro': 391.059,\n        'oil': 58.584,\n        'solar': 97.346,\n        'wind': 411.282,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 8, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 169.57,\n        'hydro': 371.426,\n        'oil': 52.724,\n        'solar': 103.485,\n        'wind': 442.726,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 163.92,\n        'hydro': 353.35,\n        'oil': 52.724,\n        'solar': 113.247,\n        'wind': 472.864,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 181.627,\n        'hydro': 333.571,\n        'oil': 52.675,\n        'solar': 104.28,\n        'wind': 499.774,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 178.753,\n        'hydro': 330.896,\n        'oil': 52.778,\n        'solar': 118.871,\n        'wind': 500.47,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 179.924,\n        'hydro': 306.28,\n        'oil': 52.778,\n        'solar': 121.146,\n        'wind': 521.536,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 178.07,\n        'hydro': 359.407,\n        'oil': 52.54,\n        'solar': 114.736,\n        'wind': 513.176,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 9, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 180.622,\n        'hydro': 328.264,\n        'oil': 60.242,\n        'solar': 120.267,\n        'wind': 512.458,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 0, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 179.054,\n        'hydro': 328.335,\n        'oil': 63.038,\n        'solar': 117.244,\n        'wind': 528.267,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 10, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 170.226,\n        'hydro': 335.477,\n        'oil': 63.038,\n        'solar': 137.639,\n        'wind': 517.805,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 20, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 180.702,\n        'hydro': 329.583,\n        'oil': 63.038,\n        'solar': 157.039,\n        'wind': 507.492,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 30, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 172.105,\n        'hydro': 352.078,\n        'oil': 63.205,\n        'solar': 139.623,\n        'wind': 523.629,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 40, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 171.755,\n        'hydro': 374.389,\n        'oil': 63.205,\n        'solar': 141.951,\n        'wind': 516.94,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2025, 2, 5, 10, 50, tzinfo=zoneinfo.ZoneInfo(key='America/Montevideo')),\n      'production': dict({\n        'biomass': 159.842,\n        'hydro': 347.767,\n        'oil': 73.886,\n        'solar': 165.139,\n        'wind': 530.971,\n      }),\n      'source': 'pronos.adme.com.uy',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'UY',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_amper_landsnet.ambr",
    "content": "# serializer version: 1\n# name: test_fetch_production\n  list([\n    dict({\n      'correctedModes': list([\n      ]),\n      'datetime': datetime.datetime(2023, 12, 19, 15, 53, tzinfo=zoneinfo.ZoneInfo(key='Atlantic/Reykjavik')),\n      'production': dict({\n        'geothermal': 653.1291,\n        'hydro': 1588.2567,\n        'oil': 0.0,\n      }),\n      'source': 'amper.landsnet.is',\n      'sourceType': <EventSourceType.measured: 'measured'>,\n      'storage': dict({\n      }),\n      'zoneKey': 'IS',\n    }),\n  ])\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_config/test_snapshot_emission_factor[FR].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_emission_factor[FR]\n  dict({\n    'emissionFactors': dict({\n      'defaults': dict({\n        'battery charge': dict({\n          'source': 'IPCC 2014',\n          'value': 0,\n        }),\n        'battery discharge': dict({\n          'source': 'IPCC 2014',\n          'value': 48.13,\n        }),\n        'biomass': dict({\n          'source': 'IPCC 2014',\n          'value': 230.0,\n        }),\n        'coal': dict({\n          'source': 'IPCC 2014',\n          'value': 888.47,\n        }),\n        'gas': dict({\n          'source': 'IPCC 2014',\n          'value': 483.32,\n        }),\n        'geothermal': dict({\n          'source': 'IPCC 2014',\n          'value': 38,\n        }),\n        'hydro': dict({\n          'source': 'IPCC 2014',\n          'value': 10.7,\n        }),\n        'hydro charge': dict({\n          'source': 'IPCC 2014',\n          'value': 0,\n        }),\n        'hydro discharge': dict({\n          'source': 'IPCC 2014',\n          'value': 21.06,\n        }),\n        'nuclear': dict({\n          'source': 'IPCC 2014',\n          'value': 5.13,\n        }),\n        'oil': dict({\n          'source': 'IPCC 2014',\n          'value': 1093.33,\n        }),\n        'solar': dict({\n          'source': 'IPCC 2014',\n          'value': 30.075,\n        }),\n        'unknown': dict({\n          'source': 'IPCC 2014',\n          'value': 700,\n        }),\n        'wind': dict({\n          'source': 'IPCC 2014',\n          'value': 12.62,\n        }),\n      }),\n      'zoneOverrides': dict({\n      }),\n    }),\n  })\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/__snapshots__/test_config/test_snapshot_emission_factor[KR].ambr",
    "content": "# serializer version: 1\n# name: test_snapshot_emission_factor[KR]\n  dict({\n    'emissionFactors': dict({\n      'defaults': dict({\n        'battery charge': dict({\n          'source': 'IPCC 2014',\n          'value': 0,\n        }),\n        'battery discharge': dict({\n          'source': 'IPCC 2014',\n          'value': 391.33,\n        }),\n        'biomass': dict({\n          'source': 'IPCC 2014',\n          'value': 230,\n        }),\n        'coal': dict({\n          'source': 'IPCC 2014',\n          'value': 820,\n        }),\n        'gas': dict({\n          'source': 'IPCC 2014',\n          'value': 490,\n        }),\n        'geothermal': dict({\n          'source': 'IPCC 2014',\n          'value': 38,\n        }),\n        'hydro': dict({\n          'source': 'IPCC 2014',\n          'value': 24,\n        }),\n        'hydro charge': dict({\n          'source': 'IPCC 2014',\n          'value': 0,\n        }),\n        'hydro discharge': dict({\n          'source': 'IPCC 2014',\n          'value': 377.43,\n        }),\n        'nuclear': dict({\n          'source': 'IPCC 2014',\n          'value': 12,\n        }),\n        'oil': dict({\n          'source': 'IPCC 2014',\n          'value': 650,\n        }),\n        'solar': dict({\n          'source': 'IPCC 2014',\n          'value': 45,\n        }),\n        'unknown': dict({\n          'source': 'IPCC 2014',\n          'value': 644,\n        }),\n        'wind': dict({\n          'source': 'IPCC 2014',\n          'value': 11,\n        }),\n      }),\n      'zoneOverrides': dict({\n      }),\n    }),\n  })\n# ---\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/conftest.py",
    "content": "\"\"\"\nThis is a configuration file for pytest that defines test fixtures available for\nuse by all tests under this path.\n\nFixtures ref: https://docs.pytest.org/en/stable/explanation/fixtures.html\n\"\"\"\n\nimport pytest\nfrom requests import Session\nfrom requests_mock import Adapter\n\n\n@pytest.fixture\ndef adapter():\n    \"\"\"\n    A `requests.Adapter` enables us to mock responses when making web requests\n    via `requests.Session`.\n\n    Adapter ref: https://requests.readthedocs.io/en/latest/user/advanced/#transport-adapters\n    \"\"\"\n    adapter = Adapter()\n    yield adapter\n\n\n@pytest.fixture\ndef session(adapter):\n    \"\"\"\n    A `request.Session` using the adapter fixture's object whenever http:// or\n    https:// requests are made.\n\n    Session ref: https://requests.readthedocs.io/en/latest/user/advanced/#session-objects\n    \"\"\"\n    session = Session()\n    session.mount(\"http://\", adapter)\n    session.mount(\"https://\", adapter)\n    yield session\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/lib/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/parsers/tests/lib/test_IN.py",
    "content": "from bs4 import BeautifulSoup\n\nfrom electricitymap.contrib.parsers.lib import IN\n\n\ndef test_read_datetime_from_span_id():\n    html_span = '<p><span id=\"lbldate\">9/4/2017 5:17:00 PM</span></p>'\n    html = BeautifulSoup(html_span, \"html.parser\")\n    india_date_time = IN.read_datetime_from_span_id(\n        html, \"lbldate\", \"%d/%m/%Y %I:%M:%S %p\"\n    )\n    assert india_date_time.isoformat() == \"2017-04-09T17:17:00+05:30\"\n\n    html_span = '<p><span id=\"lblPowerStatusDate\">04-09-2017 17:13</span></p>'\n    html = BeautifulSoup(html_span, \"html.parser\")\n    india_date_time = IN.read_datetime_from_span_id(\n        html, \"lblPowerStatusDate\", \"%d-%m-%Y %H:%M\"\n    )\n    assert india_date_time.isoformat() == \"2017-09-04T17:13:00+05:30\"\n\n\ndef test_read_text_from_span_id():\n    html_span = '<span id=\"lblcgs\" style=\"font-weight:bold;\">2998</span>'\n    html = BeautifulSoup(html_span, \"html.parser\")\n    cgs_value = IN.read_text_from_span_id(html, \"lblcgs\")\n    assert cgs_value == \"2998\"\n\n\ndef test_read_value_from_span_id():\n    html_span = '<span id=\"lblcgs\" style=\"font-weight:bold;\">2998</span>'\n    html = BeautifulSoup(html_span, \"html.parser\")\n    cgs_value = IN.read_value_from_span_id(html, \"lblcgs\")\n    assert cgs_value == 2998.0\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/lib/test_exceptions.py",
    "content": "from electricitymap.contrib.parsers.lib.exceptions import ParserException\n\n\ndef test_instance():\n    exception = ParserException(\"ESIOS\", \"Parser exception\")\n    assert isinstance(exception, ParserException)\n    assert str(exception) == \"ESIOS Parser: Parser exception\"\n\n\ndef test_instance_with_zone_key():\n    exception = ParserException(\"ESIOS\", \"Parser exception\", \"ES\")\n    assert isinstance(exception, ParserException)\n    assert str(exception) == \"ESIOS Parser (ES): Parser exception\"\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/lib/test_web.py",
    "content": "from electricitymap.contrib.parsers.lib import web\n\n\ndef test_get_response():\n    assert web.get_response(\"ES\", \"https://www.google.es\")\n\n\ndef test_get_response_text():\n    assert web.get_response_text(\"ES\", \"https://www.google.es\")\n\n\ndef test_get_response_soup():\n    assert web.get_response_soup(\"ES\", \"https://www.google.es\")\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/lib/test_zonekey.py",
    "content": "import pytest\n\nfrom electricitymap.contrib.parsers.lib import zonekey\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\n\ndef test_assert_zone_key():\n    zonekey.assert_zone_key(\"ES\", \"ES\", \"ESIOS\")\n\n    with pytest.raises(ParserException) as exc_info:\n        zonekey.assert_zone_key(\"ES\", \"ES-IB\")\n    assert str(exc_info.value) == \"ES Parser (ES): zone_key expected ES-IB, is ES\"\n\n    with pytest.raises(ParserException) as exc_info:\n        zonekey.assert_zone_key(\"ES\", \"ES-IB\", \"ESIOS\")\n    assert str(exc_info.value) == \"ESIOS Parser (ES): zone_key expected ES-IB, is ES\"\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/AU/AU_TAS_FI_payload1.json",
    "content": "{\n  \"Dashboard\": \"Flinders Island\",\n  \"percentageRenewables\": 65,\n  \"percentageRenewablesAlt\": 0,\n  \"surplusRenewables\": false,\n  \"chargeEvs\": false,\n  \"zdo\": false,\n  \"zdoMinutes\": 0,\n  \"zdoTime\": null,\n  \"percentageCheck\": 100,\n  \"message\": null,\n  \"technologies\": [\n    {\n      \"direction\": 298,\n      \"speed\": 9.8,\n      \"id\": \"wind\",\n      \"title\": \"Wind\",\n      \"value\": 595,\n      \"age\": 0,\n      \"max\": 1500,\n      \"unit\": \"kW\",\n      \"percent\": 67,\n      \"status\": true,\n      \"other\": 9.8,\n      \"otherUnits\": \"m/s\",\n      \"otherName\": \"windSpeed\",\n      \"totalRenewableGeneration\": 0\n    },\n    {\n      \"irradiance\": 32,\n      \"customerSolar\": 7,\n      \"stationSolar\": 4,\n      \"id\": \"solar\",\n      \"title\": \"Solar\",\n      \"value\": 4,\n      \"age\": 0,\n      \"max\": 600,\n      \"unit\": \"kW\",\n      \"percent\": 1,\n      \"status\": true,\n      \"other\": 32,\n      \"otherUnits\": \"W/m²\",\n      \"otherName\": \"irradiance\",\n      \"totalRenewableGeneration\": 0\n    },\n    {\n      \"id\": \"diesel\",\n      \"title\": \"Diesel\",\n      \"value\": 283,\n      \"age\": 0,\n      \"max\": 2100,\n      \"unit\": \"kW\",\n      \"percent\": 32,\n      \"status\": true,\n      \"other\": 0,\n      \"otherUnits\": null,\n      \"otherName\": null,\n      \"totalRenewableGeneration\": 0\n    },\n    {\n      \"id\": \"resistor\",\n      \"title\": \"Resistor\",\n      \"value\": -2,\n      \"age\": 1,\n      \"max\": 500,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": true,\n      \"other\": 0,\n      \"otherUnits\": null,\n      \"otherName\": null,\n      \"totalRenewableGeneration\": 0\n    },\n    {\n      \"soc\": 70,\n      \"id\": \"battery\",\n      \"title\": \"Battery\",\n      \"value\": -1,\n      \"age\": 0,\n      \"max\": 500,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": false,\n      \"other\": 70,\n      \"otherUnits\": \"%\",\n      \"otherName\": \"State of Charge\",\n      \"totalRenewableGeneration\": 0\n    },\n    {\n      \"dups1\": 0,\n      \"dups2\": 0,\n      \"id\": \"flywheel\",\n      \"title\": \"Fly Wheel\",\n      \"value\": -63,\n      \"age\": 0,\n      \"max\": 200,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": true,\n      \"other\": 0,\n      \"otherUnits\": null,\n      \"otherName\": null,\n      \"totalRenewableGeneration\": 0\n    }\n  ],\n  \"output\": {\n    \"generation\": 816,\n    \"load\": 798,\n    \"frequency\": 50,\n    \"target\": 60,\n    \"id\": \"output\",\n    \"title\": \"Output\",\n    \"value\": 823,\n    \"age\": 0,\n    \"max\": 2000,\n    \"unit\": \"kW\",\n    \"percent\": 0,\n    \"status\": false,\n    \"other\": 0,\n    \"otherUnits\": null,\n    \"otherName\": null,\n    \"totalRenewableGeneration\": 65.31862745098039\n  },\n  \"maxAge\": 1,\n  \"minAge\": 0\n}"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/AU/AU_TAS_KI_payload1.json",
    "content": "{\n  \"pollInterval\": 1,\n  \"clients\": 0,\n  \"events\": 0,\n  \"windSpill\": false,\n  \"chargeEv\": false,\n  \"zdo\": false,\n  \"percentageCheck\": 100,\n  \"message\": null,\n  \"technologies\": [\n    {\n      \"direction\": 298,\n      \"speed\": {\n        \"value\": 10,\n        \"units\": \"m/s\",\n        \"speed4\": 10,\n        \"speed5\": 7.6\n      },\n      \"id\": \"wind\",\n      \"title\": \"Wind\",\n      \"value\": 1024,\n      \"unit\": \"kW\",\n      \"percent\": 57,\n      \"status\": true\n    },\n    {\n      \"id\": \"solar\",\n      \"title\": \"Solar\",\n      \"value\": 0,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": false\n    },\n    {\n      \"burn\": false,\n      \"id\": \"diesel\",\n      \"title\": \"Diesel\",\n      \"value\": 779,\n      \"unit\": \"kW\",\n      \"percent\": 43,\n      \"status\": true\n    },\n    {\n      \"id\": \"battery\",\n      \"title\": \"Battery\",\n      \"value\": -3,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": false\n    },\n    {\n      \"id\": \"resistor\",\n      \"title\": \"Resistor\",\n      \"value\": 0,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": false\n    },\n    {\n      \"dups1\": -73,\n      \"dups2\": -73,\n      \"id\": \"flywheel\",\n      \"title\": \"Flywheel (D-UPS)\",\n      \"value\": -146,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": true\n    }\n  ],\n  \"biodiesel\": {\n    \"id\": \"biodiesel\",\n    \"title\": \"Biodiesel\",\n    \"value\": 0,\n    \"unit\": null,\n    \"percent\": 0,\n    \"status\": true\n  },\n  \"output\": {\n    \"value2\": 49.9,\n    \"unit2\": \"Hz\",\n    \"generation\": 1803,\n    \"id\": \"output\",\n    \"title\": \"Output\",\n    \"value\": 1800,\n    \"unit\": \"kW\",\n    \"percent\": 0,\n    \"status\": false\n  },\n  \"smartgrid\": {\n    \"id\": \"smartgrid\",\n    \"unit\": \"kW\",\n    \"status\": false,\n    \"minRange\": 0,\n    \"maxRange\": 2500,\n    \"demandResponse\": {\n      \"minRange\": 0,\n      \"maxRange\": 100,\n      \"available\": 0,\n      \"dispatch\": 0\n    }\n  }\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/AU/AU_WA_RI_payload1.json",
    "content": "{\n  \"percentageRenewables\": 18,\n  \"percentageRenewablesAlt\": 0,\n  \"surplusRenewables\": false,\n  \"chargeEvs\": false,\n  \"zdo\": false,\n  \"zdoMinutes\": 0,\n  \"zdoTime\": null,\n  \"percentageCheck\": 100,\n  \"message\": null,\n  \"technologies\": [\n    {\n      \"direction\": 298,\n      \"speed\": 7.4,\n      \"id\": \"wind\",\n      \"title\": \"Wind\",\n      \"value\": 148,\n      \"age\": 0,\n      \"max\": 600,\n      \"unit\": \"kW\",\n      \"percent\": 18,\n      \"status\": true,\n      \"other\": 0,\n      \"otherUnits\": null,\n      \"otherName\": null,\n      \"totalRenewableGeneration\": 0\n    },\n    {\n      \"irradiance\": 0,\n      \"customerSolar\": 0,\n      \"stationSolar\": 0,\n      \"id\": \"solar\",\n      \"title\": \"Solar\",\n      \"value\": 0,\n      \"age\": 1,\n      \"max\": 600,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": false,\n      \"other\": 0,\n      \"otherUnits\": null,\n      \"otherName\": null,\n      \"totalRenewableGeneration\": 0\n    },\n    {\n      \"id\": \"oil\",\n      \"title\": \"Diesel\",\n      \"value\": 683,\n      \"age\": 0,\n      \"max\": 2100,\n      \"unit\": \"kW\",\n      \"percent\": 82,\n      \"status\": true,\n      \"other\": 0,\n      \"otherUnits\": null,\n      \"otherName\": null,\n      \"totalRenewableGeneration\": 0\n    },\n    {\n      \"id\": \"resistor\",\n      \"title\": \"Resistor\",\n      \"value\": 1,\n      \"age\": 0,\n      \"max\": 500,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": true,\n      \"other\": 0,\n      \"otherUnits\": null,\n      \"otherName\": null,\n      \"totalRenewableGeneration\": 0\n    },\n    {\n      \"renewable\": false,\n      \"capacity\": 94,\n      \"id\": \"desal\",\n      \"title\": \"Desal\",\n      \"value\": 128,\n      \"age\": 1,\n      \"max\": 150,\n      \"unit\": \"kW\",\n      \"percent\": 0,\n      \"status\": true,\n      \"other\": 0,\n      \"otherUnits\": null,\n      \"otherName\": null,\n      \"totalRenewableGeneration\": 0\n    }\n  ],\n  \"output\": {\n    \"generation\": 831,\n    \"load\": 817,\n    \"frequency\": 50,\n    \"target\": 0,\n    \"id\": \"output\",\n    \"title\": \"Output\",\n    \"value\": 832,\n    \"age\": 52,\n    \"max\": 1300,\n    \"unit\": \"kW\",\n    \"percent\": 0,\n    \"status\": false,\n    \"other\": 0,\n    \"otherUnits\": null,\n    \"otherName\": null,\n    \"totalRenewableGeneration\": 0\n  },\n  \"maxAge\": 1,\n  \"minAge\": 0\n}"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/AW/production.json",
    "content": "{\n    \"dashboard_top_data\": {\n        \"TotalPower\": {\n            \"name\": \"CurrentTotalPower\",\n            \"value\": \"113.062271\",\n            \"timestamp\": \"2023-01-01 03:44:00.0\"\n        },\n        \"Wind\": {\n            \"name\": \"CurrentWind\",\n            \"value\": \"4.692129\",\n            \"timestamp\": \"2023-01-01 03:44:00.0\"\n        },\n        \"DailyCarbonRed\": {\n            \"name\": \"CurrentDailyCarbonReduction\",\n            \"value\": \"10156.9131\",\n            \"timestamp\": \"2023-01-01 03:45:00.0\"\n        },\n        \"DailyEquivCars\": {\n            \"name\": \"CurrentEquivCars\",\n            \"value\": \"256.0\",\n            \"timestamp\": \"2023-01-01 03:37:00.0\"\n        },\n        \"TotalSolar\": {\n            \"name\": \"CurrentSolar\",\n            \"value\": 0,\n            \"timestamp\": \"2023-01-01 03:45:00.0\"\n        },\n        \"Fossil\": {\n            \"name\": \"CurrentFossil\",\n            \"value\": \"108.567078\",\n            \"timestamp\": \"2023-01-01 03:45:00.0\"\n        },\n        \"RenewablePerc\": {\n            \"name\": \"CurrentRenewPerc\",\n            \"value\": \"3.67020679\",\n            \"timestamp\": \"2023-01-01 03:44:00.0\"\n        },\n        \"total_bio_gas\": {\n            \"name\": \"CurrentBiogas\",\n            \"value\": \"0.0\",\n            \"timestamp\": \"2023-09-12 03:45:02.384\"\n        }\n    },\n    \"wind_chart_data\": [\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"3:45 am\",\n            \"value\": 3643.72683\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5235.969\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 2666.82935\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 4782.769\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5366.894\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 3230.8116\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"5:14 am\",\n            \"value\": 6545.213000000001\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5930.875999999999\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 6192.724\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 6828.211310000001\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 3955.93119\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 4833.12464\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"6:45 am\",\n            \"value\": 5004.333500000001\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 3935.789\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 7170.629\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5900.66242\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5961.089\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 6697.287\n        },\n        {\n            \"timeStamp\": 202212365,\n            \"time\": \"8:28 pm\",\n            \"value\": 3130.10049\n        },\n        {\n            \"timeStamp\": 202212365,\n            \"time\": \"\",\n            \"value\": 4490.706999999999\n        },\n        {\n            \"timeStamp\": 202212365,\n            \"time\": \"\",\n            \"value\": 4742.485000000001\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 4802.91128\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 2797.75381\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 3361.73582\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"9:45 am\",\n            \"value\": 3190.527\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 4410.138\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 2717.1850000000004\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 3623.58475\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 3986.1445400000002\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 2928.67827\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"11:43 am\",\n            \"value\": 5517.96\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5407.178\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5497.817999999999\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 6112.15544\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 3925.718\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5165.47155\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"12:45 pm\",\n            \"value\": 5437.39128\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 4752.5560000000005\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 7210.91366\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5215.827\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 5105.044999999999\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"\",\n            \"value\": 3955.93119\n        },\n        {\n            \"timeStamp\": 20230101,\n            \"time\": \"2:43 pm\",\n            \"value\": 6233.009\n        },\n        {\n            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    "path": "electricitymap/contrib/parsers/tests/mocks/BE/entsoe_production.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<GL_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-6:generationloaddocument:3:0\">\n  <mRID>test-be-production</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A75</type>\n  <process.processType>A16</process.processType>\n  <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2024-01-01T03:00:00Z</createdDateTime>\n  <time_Period.timeInterval>\n    <start>2024-01-01T00:00Z</start>\n    <end>2024-01-01T02:00Z</end>\n  </time_Period.timeInterval>\n  <!-- B01: Biomass -->\n  <TimeSeries>\n    <mRID>1</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B01</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>70</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>73</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B04: Fossil Gas -->\n  <TimeSeries>\n    <mRID>2</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B04</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>700</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>550</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B06: Fossil Oil -->\n  <TimeSeries>\n    <mRID>3</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B06</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>0</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B10: Hydro Pumped Storage -->\n  <TimeSeries>\n    <mRID>4</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B10</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>-200</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>-180</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B11: Hydro Run-of-river and poundage -->\n  <TimeSeries>\n    <mRID>5</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B11</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>46</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>47</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B14: Nuclear -->\n  <TimeSeries>\n    <mRID>6</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B14</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>3950</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>3948</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B16: Solar -->\n  <TimeSeries>\n    <mRID>7</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B16</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>0</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B17: Waste -->\n  <TimeSeries>\n    <mRID>8</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B17</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>250</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>249</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B18: Wind Offshore -->\n  <TimeSeries>\n    <mRID>9</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B18</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>2090</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>2100</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B19: Wind Onshore -->\n  <TimeSeries>\n    <mRID>10</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B19</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>2140</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>2155</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B20: Other -->\n  <TimeSeries>\n    <mRID>11</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B20</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>560</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>595</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <!-- B25: Energy Storage -->\n  <TimeSeries>\n    <mRID>12</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YBE----------2</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B25</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-01-01T00:00Z</start>\n        <end>2024-01-01T02:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>-30</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>-25</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n</GL_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/BE/production.json",
    "content": "{\n  \"total_count\": 24,\n  \"results\": [\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Nuclear\",\n      \"fueltypepublication\": \"Nuclear\",\n      \"generatedpower\": 3947.71\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Fossil Oil\",\n      \"fueltypepublication\": \"Other Fossil Fuels\",\n      \"generatedpower\": 0.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Hydro Pumped Storage\",\n      \"fueltypepublication\": \"Water\",\n      \"generatedpower\": null\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Waste\",\n      \"fueltypepublication\": \"Other\",\n      \"generatedpower\": 248.56\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Wind Offshore\",\n      \"fueltypepublication\": \"Wind Offshore\",\n      \"generatedpower\": 2098.98\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Wind Onshore\",\n      \"fueltypepublication\": \"Wind Onshore\",\n      \"generatedpower\": 2167.52\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Fossil Gas\",\n      \"fueltypepublication\": \"Natural Gas\",\n      \"generatedpower\": null\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Biomass\",\n      \"fueltypepublication\": \"Biofuels\",\n      \"generatedpower\": 72.09\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Solar\",\n      \"fueltypepublication\": \"Solar\",\n      \"generatedpower\": 0.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Hydro Run-of-river and poundage\",\n      \"fueltypepublication\": \"Water\",\n      \"generatedpower\": 46.86\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Other\",\n      \"fueltypepublication\": \"Other\",\n      \"generatedpower\": 591.49\n    },\n    {\n      \"datetime\": \"2024-01-01T01:45:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Energy Storage\",\n      \"fueltypepublication\": \"Energy Storage\",\n      \"generatedpower\": -50.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Nuclear\",\n      \"fueltypepublication\": \"Nuclear\",\n      \"generatedpower\": 3947.66\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Fossil Oil\",\n      \"fueltypepublication\": \"Other Fossil Fuels\",\n      \"generatedpower\": 0.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Hydro Pumped Storage\",\n      \"fueltypepublication\": \"Water\",\n      \"generatedpower\": null\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Waste\",\n      \"fueltypepublication\": \"Other\",\n      \"generatedpower\": 251.24\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Wind Offshore\",\n      \"fueltypepublication\": \"Wind Offshore\",\n      \"generatedpower\": 2097.65\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Wind Onshore\",\n      \"fueltypepublication\": \"Wind Onshore\",\n      \"generatedpower\": 2154.14\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Fossil Gas\",\n      \"fueltypepublication\": \"Natural Gas\",\n      \"generatedpower\": 560.96\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Biomass\",\n      \"fueltypepublication\": \"Biofuels\",\n      \"generatedpower\": 74.6\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Solar\",\n      \"fueltypepublication\": \"Solar\",\n      \"generatedpower\": 0.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Hydro Run-of-river and poundage\",\n      \"fueltypepublication\": \"Water\",\n      \"generatedpower\": 46.67\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Other\",\n      \"fueltypepublication\": \"Other\",\n      \"generatedpower\": 600.66\n    },\n    {\n      \"datetime\": \"2024-01-01T01:30:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Energy Storage\",\n      \"fueltypepublication\": \"Energy Storage\",\n      \"generatedpower\": -45.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Nuclear\",\n      \"fueltypepublication\": \"Nuclear\",\n      \"generatedpower\": 3948.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Fossil Oil\",\n      \"fueltypepublication\": \"Other Fossil Fuels\",\n      \"generatedpower\": 0.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Hydro Pumped Storage\",\n      \"fueltypepublication\": \"Water\",\n      \"generatedpower\": null\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Waste\",\n      \"fueltypepublication\": \"Other\",\n      \"generatedpower\": 250.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Wind Offshore\",\n      \"fueltypepublication\": \"Wind Offshore\",\n      \"generatedpower\": 2101.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Wind Onshore\",\n      \"fueltypepublication\": \"Wind Onshore\",\n      \"generatedpower\": 2116.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Fossil Gas\",\n      \"fueltypepublication\": \"Natural Gas\",\n      \"generatedpower\": null\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Biomass\",\n      \"fueltypepublication\": \"Biofuels\",\n      \"generatedpower\": 71.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Solar\",\n      \"fueltypepublication\": \"Solar\",\n      \"generatedpower\": 0.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Hydro Run-of-river and poundage\",\n      \"fueltypepublication\": \"Water\",\n      \"generatedpower\": 46.7\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Other\",\n      \"fueltypepublication\": \"Other\",\n      \"generatedpower\": 607.0\n    },\n    {\n      \"datetime\": \"2024-01-01T01:00:00+00:00\",\n      \"resolutioncode\": \"PT15M\",\n      \"fueltypeentsoe\": \"Energy Storage\",\n      \"fueltypepublication\": \"Energy Storage\",\n      \"generatedpower\": -40.0\n    }\n  ]\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/BG/production_live.json",
    "content": "[\n  [\n    \"NPP 47,31%\",\n    2118.06\n  ],\n  [\n    \"CHP 17,04%\",\n    762.85\n  ],\n  [\n    \"Heating TPPs 7,63%\",\n    341.76\n  ],\n  [\n    \"Factory TPPs 2,60%\",\n    116.44\n  ],\n  [\n    \"HPP 11,75%\",\n    525.97\n  ],\n  [\n    \"Small HPPs 5,65%\",\n    252.82\n  ],\n  [\n    \"Wind 3,99%\",\n    178.62\n  ],\n  [\n    \"PV 3,56%\",\n    159.23\n  ],\n  [\n    \"Bio 0,48%\",\n    21.58\n  ]\n]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/CA_AB/solar_rpt_longterm.csv",
    "content": "Forecast Transaction Date,Min,Most Likely,Max,Actual,MCR,Pct Min,Pct Most Likely,Pct Max\n2025-03-18 04:00,0,0,0,0,1825,0,0,0\n2025-03-18 05:00,0,0,0,0,1825,0,0,0\n2025-03-18 06:00,0,0,0,0,1825,0,0,0\n2025-03-18 07:00,2.21,6.45,15.04,0.44,1825,0.12,0.35,0.82\n2025-03-18 08:00,36.13,92.67,231.4,59.33,1825,1.98,5.08,12.68\n2025-03-18 09:00,112.42,255.75,650.52,200.78,1825,6.16,14.01,35.64\n2025-03-18 10:00,215.76,378.89,980.37,448.79,1825,11.82,20.76,53.72\n2025-03-18 11:00,460.35,592.6,1304.94,643.54,1825,25.22,32.47,71.5\n2025-03-18 12:00,665.84,744.04,1288.57,861.41,1825,36.48,40.77,70.61\n2025-03-18 13:00,788.31,945.51,1448.16,912.48,1825,43.2,51.81,79.35\n2025-03-18 14:00,881.15,1044.34,1550.78,935.15,1825,48.28,57.22,84.97\n2025-03-18 15:00,897.48,1017.66,1499.7,1003.65,1825,49.18,55.76,82.18\n2025-03-18 16:00,767.72,1051.89,1367.54,1166.42,1825,42.07,57.64,74.93\n2025-03-18 17:00,458.05,875.65,992.89,1229.85,1825,25.1,47.98,54.4\n2025-03-18 18:00,208.98,438.7,476.88,550.85,1825,11.45,24.04,26.13\n2025-03-18 19:00,25.28,49.55,52.14,34.87,1825,1.39,2.72,2.86\n2025-03-18 20:00,0,0,0,0,1825,0,0,0\n2025-03-18 21:00,0,0,0,0,1825,0,0,0\n2025-03-18 22:00,0,0,0,0,1825,0,0,0\n2025-03-18 23:00,0,0,0,0,1825,0,0,0\n2025-03-19 00:00,0,0,0,0,1825,0,0,0\n2025-03-19 01:00,0,0,0,0,1825,0,0,0\n2025-03-19 02:00,0,0,0,0,1825,0,0,0\n2025-03-19 03:00,0,0,0,0,1825,0,0,0\n2025-03-19 04:00,0,0,0,0,1825,0,0,0\n2025-03-19 05:00,0,0,0,0,1825,0,0,0\n2025-03-19 06:00,0,0,0,0,1825,0,0,0\n2025-03-19 07:00,26.51,37,44.95,9.23,1825,1.45,2.03,2.46\n2025-03-19 08:00,339.03,425.15,502.61,364.68,1825,18.58,23.3,27.54\n2025-03-19 09:00,1000.09,1052.06,1099.48,1130.23,1825,54.8,57.65,60.25\n2025-03-19 10:00,1372.25,1394.69,1414.18,1486.37,1825,75.19,76.42,77.49\n2025-03-19 11:00,1505.36,1542.91,1575.97,1544.01,1825,82.49,84.54,86.35\n2025-03-19 12:00,1506.49,1526.05,1557.53,1508.64,1825,82.55,83.62,85.34\n2025-03-19 13:00,1481.16,1520.99,1555.27,1477.82,1825,81.16,83.34,85.22\n2025-03-19 14:00,1429.41,1459.68,1507.96,1468.3,1825,78.32,79.98,82.63\n2025-03-19 15:00,1408.01,1474.66,1558.46,1329.06,1825,77.15,80.8,85.4\n2025-03-19 16:00,1205.01,1302.4,1410.86,1136.24,1825,66.03,71.36,77.31\n2025-03-19 17:00,771.29,903.29,987.07,699.46,1825,42.26,49.5,54.09\n2025-03-19 18:00,290.39,367.85,419.97,180.81,1825,15.91,20.16,23.01\n2025-03-19 19:00,26.65,34.62,39.5,12.61,1825,1.46,1.9,2.16\n2025-03-19 20:00,0,0,0,0,1825,0,0,0\n2025-03-19 21:00,0,0,0,0,1825,0,0,0\n2025-03-19 22:00,0,0,0,0,1825,0,0,0\n2025-03-19 23:00,0,0,0,0,1825,0,0,0\n2025-03-20 00:00,0,0,0,0,1825,0,0,0\n2025-03-20 01:00,0,0,0,0,1825,0,0,0\n2025-03-20 02:00,0,0,0,0,1825,0,0,0\n2025-03-20 03:00,0,0,0,0,1825,0,0,0\n2025-03-20 04:00,0.16,0.16,0.16,,1825,0.01,0.01,0.01\n2025-03-20 05:00,0,0,0,,1825,0,0,0\n2025-03-20 06:00,0,0,0,,1825,0,0,0\n2025-03-20 07:00,6.74,26.79,30.49,,1825,0.37,1.47,1.67\n2025-03-20 08:00,89.15,270.37,300.34,,1825,4.88,14.81,16.46\n2025-03-20 09:00,247.53,684.02,747.8,,1825,13.56,37.48,40.98\n2025-03-20 10:00,399.28,980.8,1159.28,,1825,21.88,53.74,63.52\n2025-03-20 11:00,514.14,1052.13,1235.66,,1825,28.17,57.65,67.71\n2025-03-20 12:00,598.32,1067.09,1248.44,,1825,32.78,58.47,68.41\n2025-03-20 13:00,663.58,1063.03,1291.25,,1825,36.36,58.25,70.75\n2025-03-20 14:00,651.1,1002.02,1296.85,,1825,35.68,54.91,71.06\n2025-03-20 15:00,562.91,924.19,1254.62,,1825,30.84,50.64,68.75\n2025-03-20 16:00,437.55,793.55,1123.58,,1825,23.98,43.48,61.57\n2025-03-20 17:00,259.28,573.29,811.8,,1825,14.21,31.41,44.48\n2025-03-20 18:00,86.47,248.39,314.91,,1825,4.74,13.61,17.26\n2025-03-20 19:00,7.31,26.89,33.12,,1825,0.4,1.47,1.81\n2025-03-20 20:00,0,0,0,,1825,0,0,0\n2025-03-20 21:00,0,0,0,,1825,0,0,0\n2025-03-20 22:00,0,0,0,,1825,0,0,0\n2025-03-20 23:00,0,0,0,,1825,0,0,0\n2025-03-21 00:00,0,0,0,,1825,0,0,0\n2025-03-21 01:00,0,0,0,,1825,0,0,0\n2025-03-21 02:00,0,0,0,,1825,0,0,0\n2025-03-21 03:00,0,0,0,,1825,0,0,0\n2025-03-21 04:00,0,0,0,,1825,0,0,0\n2025-03-21 05:00,0,0,0,,1825,0,0,0\n2025-03-21 06:00,0,0,0,,1825,0,0,0\n2025-03-21 07:00,21.97,39.76,41.28,,1825,1.2,2.18,2.26\n2025-03-21 08:00,215.08,385.04,389.71,,1825,11.79,21.1,21.35\n2025-03-21 09:00,530.64,957.74,1022.68,,1825,29.08,52.48,56.04\n2025-03-21 10:00,680.75,1198.69,1419.46,,1825,37.3,65.68,77.78\n2025-03-21 11:00,710.28,1275.6,1423.96,,1825,38.92,69.9,78.03\n2025-03-21 12:00,913.12,1377.96,1447.95,,1825,50.03,75.5,79.34\n2025-03-21 13:00,1050.07,1397.03,1467.85,,1825,57.54,76.55,80.43\n2025-03-21 14:00,1047.28,1349.97,1444.59,,1825,57.39,73.97,79.16\n2025-03-21 15:00,969.54,1241.67,1348.45,,1825,53.13,68.04,73.89\n2025-03-21 16:00,754.9,1113.24,1244.62,,1825,41.36,61,68.2\n2025-03-21 17:00,477.64,807.78,924.21,,1825,26.17,44.26,50.64\n2025-03-21 18:00,173.09,338.54,381.38,,1825,9.48,18.55,20.9\n2025-03-21 19:00,17.25,37.67,45.1,,1825,0.95,2.06,2.47\n2025-03-21 20:00,0,0,0,,1825,0,0,0\n2025-03-21 21:00,0,0,0,,1825,0,0,0\n2025-03-21 22:00,0,0,0,,1825,0,0,0\n2025-03-21 23:00,0,0,0,,1825,0,0,0\n2025-03-22 00:00,0,0,0,,1825,0,0,0\n2025-03-22 01:00,0,0,0,,1825,0,0,0\n2025-03-22 02:00,0,0,0,,1825,0,0,0\n2025-03-22 03:00,0,0,0,,1825,0,0,0\n2025-03-22 04:00,0,0,0,,1825,0,0,0\n2025-03-22 05:00,0,0,0,,1825,0,0,0\n2025-03-22 06:00,0,0,0,,1825,0,0,0\n2025-03-22 07:00,18.56,35.84,50.04,,1825,1.02,1.96,2.74\n2025-03-22 08:00,223.7,336.2,458.52,,1825,12.26,18.42,25.12\n2025-03-22 09:00,495.66,883.09,1150.26,,1825,27.16,48.39,63.03\n2025-03-22 10:00,681.81,1176.49,1479.86,,1825,37.36,64.47,81.09\n2025-03-22 11:00,859.37,1271.94,1571.18,,1825,47.09,69.7,86.09\n2025-03-22 12:00,1036.57,1283.86,1570.71,,1825,56.8,70.35,86.07\n2025-03-22 13:00,1136.04,1289.17,1557.55,,1825,62.25,70.64,85.35\n2025-03-22 14:00,1147.41,1283.37,1558.08,,1825,62.87,70.32,85.37\n2025-03-22 15:00,993.7,1224.96,1544.12,,1825,54.45,67.12,84.61\n2025-03-22 16:00,764.88,1118.23,1406.73,,1825,41.91,61.27,77.08\n2025-03-22 17:00,570.9,844.65,1057.84,,1825,31.28,46.28,57.96\n2025-03-22 18:00,307.96,381.27,432.98,,1825,16.87,20.89,23.72\n2025-03-22 19:00,32.83,44.23,53.45,,1825,1.8,2.42,2.93\n2025-03-22 20:00,0,0,0,,1825,0,0,0\n2025-03-22 21:00,0,0,0,,1825,0,0,0\n2025-03-22 22:00,0,0,0,,1825,0,0,0\n2025-03-22 23:00,0,0,0,,1825,0,0,0\n2025-03-23 00:00,0,0,0,,1825,0,0,0\n2025-03-23 01:00,0,0,0,,1825,0,0,0\n2025-03-23 02:00,0,0,0,,1825,0,0,0\n2025-03-23 03:00,0,0,0,,1825,0,0,0\n2025-03-23 04:00,0,0,0,,1825,0,0,0\n2025-03-23 05:00,0,0,0,,1825,0,0,0\n2025-03-23 06:00,0,0,0,,1825,0,0,0\n2025-03-23 07:00,32.55,40.94,55.76,,1825,1.78,2.24,3.06\n2025-03-23 08:00,302.64,343.79,490.62,,1825,16.58,18.84,26.88\n2025-03-23 09:00,712.63,761.01,1221.04,,1825,39.05,41.7,66.91\n2025-03-23 10:00,950.62,1095.24,1519.96,,1825,52.09,60.01,83.29\n2025-03-23 11:00,1053.74,1225.34,1600,,1825,57.74,67.14,87.67\n2025-03-23 12:00,1060.41,1244.38,1599.67,,1825,58.1,68.19,87.65\n2025-03-23 13:00,1021.25,1218.48,1589.23,,1825,55.96,66.77,87.08\n2025-03-23 14:00,914.06,1105.9,1598.39,,1825,50.09,60.6,87.58\n2025-03-23 15:00,748.5,924.7,1605.19,,1825,41.01,50.67,87.96\n2025-03-23 16:00,530.65,715.81,1517,,1825,29.08,39.22,83.12\n2025-03-23 17:00,343.71,500.26,1184.49,,1825,18.83,27.41,64.9\n2025-03-23 18:00,129.54,207.14,523.21,,1825,7.1,11.35,28.67\n2025-03-23 19:00,13.16,22,62.41,,1825,0.72,1.21,3.42\n2025-03-23 20:00,0,0,0,,1825,0,0,0\n2025-03-23 21:00,0,0,0,,1825,0,0,0\n2025-03-23 22:00,0,0,0,,1825,0,0,0\n2025-03-23 23:00,0,0,0,,1825,0,0,0\n2025-03-24 00:00,0,0,0,,1825,0,0,0\n2025-03-24 01:00,0,0,0,,1825,0,0,0\n2025-03-24 02:00,0,0,0,,1825,0,0,0\n2025-03-24 03:00,0,0,0,,1825,0,0,0\n2025-03-24 04:00,0,0,0,,1825,0,0,0\n2025-03-24 05:00,0,0,0,,1825,0,0,0\n2025-03-24 06:00,0,0,0,,1825,0,0,0\n2025-03-24 07:00,29.62,39.21,47.49,,1825,1.62,2.15,2.6\n2025-03-24 08:00,269.31,347.06,405.13,,1825,14.76,19.02,22.2\n2025-03-24 09:00,745.82,839.6,935.3,,1825,40.87,46.01,51.25\n2025-03-24 10:00,1005.74,1099.13,1194.22,,1825,55.11,60.23,65.44\n2025-03-24 11:00,1095.01,1166.37,1236.64,,1825,60,63.91,67.76\n2025-03-24 12:00,1143.9,1181.96,1263.08,,1825,62.68,64.76,69.21\n2025-03-24 13:00,1151.54,1184.72,1277.02,,1825,63.1,64.92,69.97\n2025-03-24 14:00,1095.22,1171.91,1261.41,,1825,60.01,64.21,69.12\n2025-03-24 15:00,980.16,1113.87,1259.6,,1825,53.71,61.03,69.02\n2025-03-24 16:00,814.77,996.96,1195.12,,1825,44.64,54.63,65.49\n2025-03-24 17:00,567.37,737.12,917.05,,1825,31.09,40.39,50.25\n2025-03-24 18:00,229.05,332.57,440.68,,1825,12.55,18.22,24.15\n2025-03-24 19:00,25.18,40.25,55.92,,1825,1.38,2.21,3.06\n2025-03-24 20:00,0,0,0,,1825,0,0,0\n2025-03-24 21:00,0,0,0,,1825,0,0,0\n2025-03-24 22:00,0,0,0,,1825,0,0,0\n2025-03-24 23:00,0,0,0,,1825,0,0,0\n2025-03-25 00:00,0,0,0,,1825,0,0,0\n2025-03-25 01:00,0,0,0,,1825,0,0,0\n2025-03-25 02:00,0,0,0,,1825,0,0,0\n2025-03-25 03:00,0,0,0,,1825,0,0,0\n2025-03-25 04:00,0,0,0,,1825,0,0,0\n2025-03-25 05:00,0,0,0,,1825,0,0,0\n2025-03-25 06:00,0,0,0,,1825,0,0,0\n2025-03-25 07:00,8.07,83.25,83.52,,1825,0.44,4.56,4.58\n2025-03-25 08:00,64.8,608.86,610.37,,1825,3.55,33.36,33.44\n2025-03-25 09:00,176.42,1235.43,1242.32,,1825,9.67,67.69,68.07\n2025-03-25 10:00,307.18,1480.63,1494.85,,1825,16.83,81.13,81.91\n2025-03-25 11:00,479.18,1524.12,1539.52,,1825,26.26,83.51,84.36\n2025-03-25 12:00,690.56,1507.31,1522.56,,1825,37.84,82.59,83.43\n2025-03-25 13:00,914.26,1482.3,1496.33,,1825,50.1,81.22,81.99\n2025-03-25 14:00,955.19,1392.35,1474.39,,1825,52.34,76.29,80.79\n2025-03-25 15:00,895.63,1189.23,1480,,1825,49.08,65.16,81.1\n2025-03-25 16:00,785.39,927.13,1360.62,,1825,43.04,50.8,74.55\n2025-03-25 17:00,552.98,658.17,1060.9,,1825,30.3,36.06,58.13\n2025-03-25 18:00,221.35,299.52,484.27,,1825,12.13,16.41,26.54\n2025-03-25 19:00,25.19,36.22,61.73,,1825,1.38,1.98,3.38\n2025-03-25 20:00,0,0,0,,1825,0,0,0\n2025-03-25 21:00,0,0,0,,1825,0,0,0\n2025-03-25 22:00,0,0,0,,1825,0,0,0\n2025-03-25 23:00,0,0,0,,1825,0,0,0\n2025-03-26 00:00,0,0,0,,1825,0,0,0\n2025-03-26 01:00,0,0,0,,1825,0,0,0\n2025-03-26 02:00,0,0,0,,1825,0,0,0\n2025-03-26 03:00,0,0,0,,1825,0,0,0\n2025-03-26 04:00,0,0,0,,1825,0,0,0\n2025-03-26 05:00,0,0,0,,1825,0,0,0\n2025-03-26 06:00,0,0,0.01,,1825,0,0,0\n2025-03-26 07:00,0,101.49,105.25,,1825,0,5.56,5.77\n2025-03-26 08:00,0,674.47,708.83,,1825,0,36.96,38.84\n2025-03-26 09:00,9.96,1288.7,1343.94,,1825,0.55,70.61,73.64\n2025-03-26 10:00,41.89,1508.01,1567.06,,1825,2.3,82.63,85.87\n2025-03-26 11:00,69.5,1529.61,1584.42,,1825,3.81,83.81,86.82\n2025-03-26 12:00,98.25,1507.52,1555.06,,1825,5.38,82.6,85.21\n2025-03-26 13:00,126.82,1495.4,1527.54,,1825,6.95,81.94,83.7\n2025-03-26 14:00,128.59,1486.39,1494.06,,1825,7.05,81.45,81.87\n2025-03-26 15:00,97.53,1458.18,1458.18,,1825,5.34,79.9,79.9\n2025-03-26 16:00,60.02,1348.36,1348.36,,1825,3.29,73.88,73.88\n2025-03-26 17:00,24.42,1031.83,1036.88,,1825,1.34,56.54,56.82\n2025-03-26 18:00,0.95,492.13,510.34,,1825,0.05,26.97,27.96\n2025-03-26 19:00,0.02,67.68,72.7,,1825,0,3.71,3.98\n2025-03-26 20:00,0,0,0,,1825,0,0,0\n2025-03-26 21:00,0,0,0,,1825,0,0,0\n2025-03-26 22:00,0,0,0,,1825,0,0,0\n2025-03-26 23:00,0,0,0,,1825,0,0,0\n2025-03-27 00:00,0,0,0,,1825,0,0,0\n2025-03-27 01:00,0,0,0,,1825,0,0,0\n2025-03-27 02:00,0,0,0,,1825,0,0,0\n2025-03-27 03:00,0,0,0,,1825,0,0,0\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/CA_AB/wind_rpt_longterm.csv",
    "content": "Forecast Transaction Date,Min,Most Likely,Max,Actual,MCR,Pct Min,Pct Most Likely,Pct Max\n2025-03-18 04:00,1308.25,2075.84,2906.81,2210.66,5688,23,36.5,51.1\n2025-03-18 05:00,940.82,1906.32,3098.39,2226.18,5688,16.54,33.51,54.47\n2025-03-18 06:00,800.17,1835.3,3026.63,1882.7,5688,14.07,32.27,53.21\n2025-03-18 07:00,927.56,1611.24,2531.17,1588.42,5688,16.31,28.33,44.5\n2025-03-18 08:00,987.23,1279.4,1835.96,1381.58,5688,17.36,22.49,32.28\n2025-03-18 09:00,729,951.19,1412.91,1104.6,5688,12.82,16.72,24.84\n2025-03-18 10:00,685.2,896.19,1236.86,889.76,5688,12.05,15.76,21.75\n2025-03-18 11:00,551.66,751.44,1101.88,732.53,5688,9.7,13.21,19.37\n2025-03-18 12:00,470.21,587.83,901.74,428.53,5688,8.27,10.33,15.85\n2025-03-18 13:00,279.04,428.2,680.46,324.73,5688,4.91,7.53,11.96\n2025-03-18 14:00,184.03,318.69,522.63,307.95,5688,3.24,5.6,9.19\n2025-03-18 15:00,200.56,327.06,555.42,264.33,5688,3.53,5.75,9.76\n2025-03-18 16:00,218.99,380.76,827.03,259.44,5688,3.85,6.69,14.54\n2025-03-18 17:00,220.46,400.51,689.73,280.99,5688,3.88,7.04,12.13\n2025-03-18 18:00,258.34,474.17,757.43,428.9,5688,4.54,8.34,13.32\n2025-03-18 19:00,307.76,682.37,912.76,982.45,5688,5.41,12,16.05\n2025-03-18 20:00,704.88,1153.81,1302.47,1795.52,5688,12.39,20.28,22.9\n2025-03-18 21:00,1555.16,1998.39,2135.31,2655.27,5688,27.34,35.13,37.54\n2025-03-18 22:00,2134.93,2734.04,2906.05,3093.58,5688,37.53,48.07,51.09\n2025-03-18 23:00,2555.51,3223.62,3479.69,3349.19,5688,44.93,56.67,61.18\n2025-03-19 00:00,2733.36,3354.24,3657.3,3335.04,5688,48.05,58.97,64.3\n2025-03-19 01:00,2837.53,3343.46,3701.73,3270.24,5688,49.89,58.78,65.08\n2025-03-19 02:00,2594.46,3108.56,3436.18,3155.33,5688,45.61,54.65,60.41\n2025-03-19 03:00,2463.92,2972.83,3375.43,2953.81,5688,43.32,52.26,59.34\n2025-03-19 04:00,2357.18,2815.32,3241.32,2728.18,5688,41.44,49.5,56.99\n2025-03-19 05:00,1948.65,2398.31,2959.23,2586.15,5688,34.26,42.16,52.03\n2025-03-19 06:00,1704.41,2203.6,2832.18,2430.89,5688,29.97,38.74,49.79\n2025-03-19 07:00,1620.86,2179.59,2758.36,2137.66,5688,28.5,38.32,48.49\n2025-03-19 08:00,1303.54,1937.05,2409.11,1884.01,5688,22.92,34.06,42.35\n2025-03-19 09:00,1088.51,1676.27,2174.43,1671.21,5688,19.14,29.47,38.23\n2025-03-19 10:00,1094.45,1571.24,2141.87,1422.44,5688,19.24,27.62,37.66\n2025-03-19 11:00,1181.29,1413.35,1928.76,1416.18,5688,20.77,24.85,33.91\n2025-03-19 12:00,1290.05,1463.77,1814.54,1516.5,5688,22.68,25.73,31.9\n2025-03-19 13:00,1325.05,1599.64,1948.06,1695.78,5688,23.3,28.12,34.25\n2025-03-19 14:00,1366.1,1683.99,2139.41,1892.86,5688,24.02,29.61,37.61\n2025-03-19 15:00,1523.19,1884.76,2462.71,2196.75,5688,26.78,33.14,43.3\n2025-03-19 16:00,1642.1,2054.58,2699.48,2250.42,5688,28.87,36.12,47.46\n2025-03-19 17:00,1659.01,2066.41,2690.02,2211.04,5688,29.17,36.33,47.29\n2025-03-19 18:00,1648.81,2151.22,2681.42,2493.77,5688,28.99,37.82,47.14\n2025-03-19 19:00,1835.05,2446.55,2767.29,2608.72,5688,32.26,43.01,48.65\n2025-03-19 20:00,2284.1,2787.36,3083.33,2718.77,5688,40.16,49,54.21\n2025-03-19 21:00,2299.16,3005.29,3269.45,2700.95,5688,40.42,52.84,57.48\n2025-03-19 22:00,2578.38,2958.56,3246.29,2726.9,5688,45.33,52.01,57.07\n2025-03-19 23:00,2600.04,2728.82,3195.83,2912.43,5688,45.71,47.98,56.19\n2025-03-20 00:00,2574.34,2872.64,3117.41,2863.55,5688,45.26,50.5,54.81\n2025-03-20 01:00,2852.15,3057.42,3331.08,2704.44,5688,50.14,53.75,58.56\n2025-03-20 02:00,2346.45,2760.59,3034.6,2629.73,5688,41.25,48.53,53.35\n2025-03-20 03:00,2184.09,2761.04,3041.31,2581.01,5688,38.4,48.54,53.47\n2025-03-20 04:00,2127.58,2518.45,2744.02,,5688,37.4,44.28,48.24\n2025-03-20 05:00,2215.98,2630.01,2982.63,,5688,38.96,46.24,52.44\n2025-03-20 06:00,2452.57,2684.44,3023.02,,5688,43.12,47.19,53.15\n2025-03-20 07:00,2462.21,2726.33,3072.96,,5688,43.29,47.93,54.03\n2025-03-20 08:00,2392.18,2695.77,3059.71,,5688,42.06,47.39,53.79\n2025-03-20 09:00,2247.24,2608.56,3036.88,,5688,39.51,45.86,53.39\n2025-03-20 10:00,2293.71,2581.71,3005.37,,5688,40.33,45.39,52.84\n2025-03-20 11:00,2401.94,2664.17,2954.2,,5688,42.23,46.84,51.94\n2025-03-20 12:00,2398.68,2723.39,2959.13,,5688,42.17,47.88,52.02\n2025-03-20 13:00,2447.27,2749.84,3028.69,,5688,43.03,48.34,53.25\n2025-03-20 14:00,2428.61,2805.44,3087.55,,5688,42.7,49.32,54.28\n2025-03-20 15:00,2276.73,2819.94,3040.08,,5688,40.03,49.58,53.45\n2025-03-20 16:00,2093.66,2728.52,3015.25,,5688,36.81,47.97,53.01\n2025-03-20 17:00,1948.78,2545.87,2966.85,,5688,34.26,44.76,52.16\n2025-03-20 18:00,1602.64,2336.72,2774.21,,5688,28.18,41.08,48.77\n2025-03-20 19:00,1207.19,2196.89,2492.2,,5688,21.22,38.62,43.82\n2025-03-20 20:00,1082.06,2127.59,2406.08,,5688,19.02,37.4,42.3\n2025-03-20 21:00,1081.69,2085.43,2530.74,,5688,19.02,36.66,44.49\n2025-03-20 22:00,1115.29,2138.91,2562.34,,5688,19.61,37.6,45.05\n2025-03-20 23:00,1103.84,2296.83,2628.5,,5688,19.41,40.38,46.21\n2025-03-21 00:00,1135.9,2501.88,2800.84,,5688,19.97,43.99,49.24\n2025-03-21 01:00,1258.27,2623.14,2928.42,,5688,22.12,46.12,51.48\n2025-03-21 02:00,1529.28,2664.52,2993.16,,5688,26.89,46.84,52.62\n2025-03-21 03:00,1799.67,2609.34,2876.04,,5688,31.64,45.87,50.56\n2025-03-21 04:00,1919.11,2454.05,2689.7,,5688,33.74,43.14,47.29\n2025-03-21 05:00,1931.41,2306.57,2552.69,,5688,33.96,40.55,44.88\n2025-03-21 06:00,1705.93,2229.69,2554.5,,5688,29.99,39.2,44.91\n2025-03-21 07:00,1360.37,2247.47,2697.87,,5688,23.92,39.51,47.43\n2025-03-21 08:00,1295.98,2325.91,2831.66,,5688,22.78,40.89,49.78\n2025-03-21 09:00,1547.29,2402.4,2935.91,,5688,27.2,42.24,51.62\n2025-03-21 10:00,1995.36,2520.28,3014.29,,5688,35.08,44.31,52.99\n2025-03-21 11:00,2293.92,2769,3103.75,,5688,40.33,48.68,54.57\n2025-03-21 12:00,2439.33,3026.26,3194.27,,5688,42.89,53.2,56.16\n2025-03-21 13:00,2569.06,3159.56,3281.52,,5688,45.17,55.55,57.69\n2025-03-21 14:00,2756.85,3224.79,3397.4,,5688,48.47,56.69,59.73\n2025-03-21 15:00,2904.45,3263.18,3478.51,,5688,51.06,57.37,61.16\n2025-03-21 16:00,2691.41,3163.95,3526.36,,5688,47.32,55.63,62\n2025-03-21 17:00,2156.68,3002.09,3581.05,,5688,37.92,52.78,62.96\n2025-03-21 18:00,2130.93,2924.69,3383.94,,5688,37.46,51.42,59.49\n2025-03-21 19:00,2157.74,2905.45,3214.14,,5688,37.93,51.08,56.51\n2025-03-21 20:00,2284.12,2882.94,3344.79,,5688,40.16,50.68,58.8\n2025-03-21 21:00,2439.36,2905.29,3372.89,,5688,42.89,51.08,59.3\n2025-03-21 22:00,2163.8,2888.12,3316.91,,5688,38.04,50.78,58.31\n2025-03-21 23:00,2018.18,2774.21,3493.35,,5688,35.48,48.77,61.42\n2025-03-22 00:00,1847.84,2757.69,3686.56,,5688,32.49,48.48,64.81\n2025-03-22 01:00,1596.12,2693.8,3668.34,,5688,28.06,47.36,64.49\n2025-03-22 02:00,1336.15,2501.02,3659.85,,5688,23.49,43.97,64.34\n2025-03-22 03:00,1328.78,2337.3,3575.52,,5688,23.36,41.09,62.86\n2025-03-22 04:00,1354.53,2289.05,3405.99,,5688,23.81,40.24,59.88\n2025-03-22 05:00,1393.35,2289.41,3232.99,,5688,24.5,40.25,56.84\n2025-03-22 06:00,1332.62,2314.28,3057.92,,5688,23.43,40.69,53.76\n2025-03-22 07:00,1342.77,2359.24,2910.37,,5688,23.61,41.48,51.17\n2025-03-22 08:00,1549.23,2388.96,2875.65,,5688,27.24,42,50.56\n2025-03-22 09:00,1719.48,2263.51,2811.17,,5688,30.23,39.79,49.42\n2025-03-22 10:00,1743.15,2232.78,2958.73,,5688,30.65,39.25,52.02\n2025-03-22 11:00,1701.14,2456.57,3171.32,,5688,29.91,43.19,55.75\n2025-03-22 12:00,1544.65,2661.78,3206.4,,5688,27.16,46.8,56.37\n2025-03-22 13:00,1485.54,2787.19,3278.42,,5688,26.12,49,57.64\n2025-03-22 14:00,1559.37,2863.95,3338.96,,5688,27.42,50.35,58.7\n2025-03-22 15:00,1717.42,2832.66,3254.36,,5688,30.19,49.8,57.21\n2025-03-22 16:00,1683.96,2663.64,3021.57,,5688,29.61,46.83,53.12\n2025-03-22 17:00,1253.92,2308.15,2626.12,,5688,22.05,40.58,46.17\n2025-03-22 18:00,678.28,1846.8,2056.51,,5688,11.92,32.47,36.16\n2025-03-22 19:00,413.37,1466.25,1621.53,,5688,7.27,25.78,28.51\n2025-03-22 20:00,475.65,1286.42,1462.49,,5688,8.36,22.62,25.71\n2025-03-22 21:00,714.12,1350.13,1610.25,,5688,12.55,23.74,28.31\n2025-03-22 22:00,1000.18,1552.23,1779.91,,5688,17.58,27.29,31.29\n2025-03-22 23:00,1193.42,1856.1,2064.56,,5688,20.98,32.63,36.3\n2025-03-23 00:00,1431.83,2172.01,2548.47,,5688,25.17,38.19,44.8\n2025-03-23 01:00,1757.9,2331.96,2919.06,,5688,30.91,41,51.32\n2025-03-23 02:00,1999.8,2443.43,3051.82,,5688,35.16,42.96,53.65\n2025-03-23 03:00,2064.71,2537.34,3095.92,,5688,36.3,44.61,54.43\n2025-03-23 04:00,1959.39,2538.76,3065.18,,5688,34.45,44.63,53.89\n2025-03-23 05:00,1821.02,2474.68,2928.25,,5688,32.02,43.51,51.48\n2025-03-23 06:00,1657.16,2331.5,2737.37,,5688,29.13,40.99,48.13\n2025-03-23 07:00,1509.08,2171.29,2507.22,,5688,26.53,38.17,44.08\n2025-03-23 08:00,1358.74,2046.98,2469.42,,5688,23.89,35.99,43.41\n2025-03-23 09:00,1348.11,1915.01,2530.43,,5688,23.7,33.67,44.49\n2025-03-23 10:00,1283.55,1836.61,2592.78,,5688,22.57,32.29,45.58\n2025-03-23 11:00,1192.83,1865.58,2647.01,,5688,20.97,32.8,46.54\n2025-03-23 12:00,1155.74,1980.43,2750.07,,5688,20.32,34.82,48.35\n2025-03-23 13:00,1092.54,2171.58,2901.38,,5688,19.21,38.18,51.01\n2025-03-23 14:00,1051.25,2365.33,3052.66,,5688,18.48,41.58,53.67\n2025-03-23 15:00,1121.56,2462.26,3186.87,,5688,19.72,43.29,56.03\n2025-03-23 16:00,1192.14,2463.87,3303.11,,5688,20.96,43.32,58.07\n2025-03-23 17:00,1106.06,2476.2,3418.48,,5688,19.45,43.53,60.1\n2025-03-23 18:00,896.41,2549.52,3537.6,,5688,15.76,44.82,62.19\n2025-03-23 19:00,689.89,2682.49,3660.24,,5688,12.13,47.16,64.35\n2025-03-23 20:00,575.99,2824.99,3781,,5688,10.13,49.67,66.47\n2025-03-23 21:00,578.95,3004.88,3899.52,,5688,10.18,52.83,68.56\n2025-03-23 22:00,717.67,3222.3,4016.12,,5688,12.62,56.65,70.61\n2025-03-23 23:00,855.69,3432,4083.61,,5688,15.04,60.34,71.79\n2025-03-24 00:00,930.6,3410.77,3769.49,,5688,16.36,59.96,66.27\n2025-03-24 01:00,980.01,3347.85,3611.84,,5688,17.23,58.86,63.5\n2025-03-24 02:00,1013.47,3336.45,3582.41,,5688,17.82,58.66,62.98\n2025-03-24 03:00,1021.79,3381.71,3605.18,,5688,17.96,59.45,63.38\n2025-03-24 04:00,1001.58,3489.38,3729.28,,5688,17.61,61.35,65.56\n2025-03-24 05:00,956.58,3615.25,3909.12,,5688,16.82,63.56,68.73\n2025-03-24 06:00,953.66,3648.05,4039.61,,5688,16.77,64.14,71.02\n2025-03-24 07:00,960.23,3592.14,4118.14,,5688,16.88,63.15,72.4\n2025-03-24 08:00,1021.99,3544.68,4188.05,,5688,17.97,62.32,73.63\n2025-03-24 09:00,1119.67,3451.86,4135.42,,5688,19.68,60.69,72.7\n2025-03-24 10:00,1219.47,3315.51,3948.88,,5688,21.44,58.29,69.42\n2025-03-24 11:00,1428.24,3203.98,3759.36,,5688,25.11,56.33,66.09\n2025-03-24 12:00,1718.69,3184.4,3726.09,,5688,30.22,55.98,65.51\n2025-03-24 13:00,1970.96,3249.39,3853.9,,5688,34.65,57.13,67.75\n2025-03-24 14:00,2117.65,3305.01,3981.17,,5688,37.23,58.1,69.99\n2025-03-24 15:00,2267.18,3238,3973.85,,5688,39.86,56.93,69.86\n2025-03-24 16:00,2300.29,3050.58,3825.02,,5688,40.44,53.63,67.25\n2025-03-24 17:00,2136.14,2866.87,3676.34,,5688,37.56,50.4,64.63\n2025-03-24 18:00,2061.75,2750.01,3484.42,,5688,36.25,48.35,61.26\n2025-03-24 19:00,2076.98,2677.44,3257,,5688,36.52,47.07,57.26\n2025-03-24 20:00,2072.24,2596.28,3204.07,,5688,36.43,45.64,56.33\n2025-03-24 21:00,1980.19,2434.07,3203.7,,5688,34.81,42.79,56.32\n2025-03-24 22:00,1804.15,2193.09,3207.89,,5688,31.72,38.56,56.4\n2025-03-24 23:00,1608.63,1972.17,3186.2,,5688,28.28,34.67,56.02\n2025-03-25 00:00,1474.55,1954.94,3077.21,,5688,25.92,34.37,54.1\n2025-03-25 01:00,1396.07,1861.77,2809.27,,5688,24.54,32.73,49.39\n2025-03-25 02:00,1313.47,1663.76,2473.96,,5688,23.09,29.25,43.49\n2025-03-25 03:00,1273.37,1487.08,2367.64,,5688,22.39,26.14,41.63\n2025-03-25 04:00,1277.09,1386.28,2220.83,,5688,22.45,24.37,39.04\n2025-03-25 05:00,1280.34,1343.79,2073.56,,5688,22.51,23.63,36.45\n2025-03-25 06:00,1264.77,1285.85,1906.59,,5688,22.24,22.61,33.52\n2025-03-25 07:00,1199.83,1199.83,1719.4,,5688,21.09,21.09,30.23\n2025-03-25 08:00,1117.63,1117.63,1531.44,,5688,19.65,19.65,26.92\n2025-03-25 09:00,981.59,981.59,1366.78,,5688,17.26,17.26,24.03\n2025-03-25 10:00,807.26,807.26,1225.61,,5688,14.19,14.19,21.55\n2025-03-25 11:00,650.55,660.33,1083.91,,5688,11.44,11.61,19.06\n2025-03-25 12:00,525.41,545.48,1003.5,,5688,9.24,9.59,17.64\n2025-03-25 13:00,461.01,461.07,985.92,,5688,8.1,8.11,17.33\n2025-03-25 14:00,387.28,387.29,966.94,,5688,6.81,6.81,17\n2025-03-25 15:00,309.89,343.33,940.57,,5688,5.45,6.04,16.54\n2025-03-25 16:00,244.05,332.73,906.57,,5688,4.29,5.85,15.94\n2025-03-25 17:00,213.77,335.67,871.46,,5688,3.76,5.9,15.32\n2025-03-25 18:00,187.15,384.62,837.07,,5688,3.29,6.76,14.72\n2025-03-25 19:00,161.74,478.75,804.88,,5688,2.84,8.42,14.15\n2025-03-25 20:00,189.05,592.31,900.7,,5688,3.32,10.41,15.84\n2025-03-25 21:00,301.04,738.91,1077.22,,5688,5.29,12.99,18.94\n2025-03-25 22:00,551.13,940.19,1248.9,,5688,9.69,16.53,21.96\n2025-03-25 23:00,831.11,1218.63,1412.85,,5688,14.61,21.42,24.84\n2025-03-26 00:00,780.38,1382.06,1510.9,,5688,13.72,24.3,26.56\n2025-03-26 01:00,610.43,1371.95,1539.14,,5688,10.73,24.12,27.06\n2025-03-26 02:00,439.74,1376.56,1566.63,,5688,7.73,24.2,27.54\n2025-03-26 03:00,395.85,1398.32,1592.88,,5688,6.96,24.58,28\n2025-03-26 04:00,483.04,1424.7,1617.83,,5688,8.49,25.05,28.44\n2025-03-26 05:00,569.2,1466.54,1641.73,,5688,10.01,25.78,28.86\n2025-03-26 06:00,541.59,1418.28,1541.45,,5688,9.52,24.93,27.1\n2025-03-26 07:00,396.85,1269.18,1320.83,,5688,6.98,22.31,23.22\n2025-03-26 08:00,251.35,1126.72,1250.37,,5688,4.42,19.81,21.98\n2025-03-26 09:00,189.06,979.06,1216.08,,5688,3.32,17.21,21.38\n2025-03-26 10:00,212.38,838.16,1197.56,,5688,3.73,14.74,21.05\n2025-03-26 11:00,234.66,725.9,1256.38,,5688,4.13,12.76,22.09\n2025-03-26 12:00,255.59,666.05,1250.74,,5688,4.49,11.71,21.99\n2025-03-26 13:00,274.63,666.97,1196.15,,5688,4.83,11.73,21.03\n2025-03-26 14:00,292.22,694.43,1214.5,,5688,5.14,12.21,21.35\n2025-03-26 15:00,343.92,734.62,1264.49,,5688,6.05,12.92,22.23\n2025-03-26 16:00,431.4,793.65,1357.04,,5688,7.58,13.95,23.86\n2025-03-26 17:00,519,893.54,1556.89,,5688,9.12,15.71,27.37\n2025-03-26 18:00,610.4,1026.32,1690.49,,5688,10.73,18.04,29.72\n2025-03-26 19:00,704.95,1173.18,1696.53,,5688,12.39,20.63,29.83\n2025-03-26 20:00,799.44,1326.32,1713.72,,5688,14.05,23.32,30.13\n2025-03-26 21:00,876.87,1484.26,1735.54,,5688,15.42,26.09,30.51\n2025-03-26 22:00,935.64,1669.98,1827.76,,5688,16.45,29.36,32.13\n2025-03-26 23:00,993.38,1890.94,2033.13,,5688,17.46,33.24,35.74\n2025-03-27 00:00,1028.69,2012.26,2238.51,,5688,18.09,35.38,39.35\n2025-03-27 01:00,1040.24,2015.65,2419.13,,5688,18.29,35.44,42.53\n2025-03-27 02:00,1050.13,2040.9,2646.29,,5688,18.46,35.88,46.52\n2025-03-27 03:00,1123.71,2080.44,3092.52,,5688,19.76,36.58,54.37\n"
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19:15:00\\\",\\\"SPP Biomass\\\":11.12523,\\\"Coal\\\":543.4648,\\\"Major Hydro\\\":716.646001,\\\"SPP Minihydro\\\":5.638295,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":929.2924270000001,\\\"Wind\\\":135.25679000000002},{\\\"DateTime\\\":\\\"2023-08-23 19:30:00\\\",\\\"SPP Biomass\\\":11.51105,\\\"Coal\\\":542.3994,\\\"Major Hydro\\\":686.441861,\\\"SPP Minihydro\\\":4.895565,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":931.541448,\\\"Wind\\\":132.80013},{\\\"DateTime\\\":\\\"2023-08-23 19:45:00\\\",\\\"SPP Biomass\\\":11.09703,\\\"Coal\\\":541.8969,\\\"Major Hydro\\\":642.9240309999999,\\\"SPP Minihydro\\\":5.535989,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":928.4933510000001,\\\"Wind\\\":132.28857000000002},{\\\"DateTime\\\":\\\"2023-08-23 20:00:00\\\",\\\"SPP Biomass\\\":11.03703,\\\"Coal\\\":543.8300999999999,\\\"Major Hydro\\\":608.5129810000001,\\\"SPP Minihydro\\\":5.773077,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":927.780083,\\\"Wind\\\":128.92568},{\\\"DateTime\\\":\\\"2023-08-23 20:15:00\\\",\\\"SPP Biomass\\\":10.75861,\\\"Coal\\\":540.8466,\\\"Major Hydro\\\":496.82939200000004,\\\"SPP Minihydro\\\":7.185144,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":891.211849,\\\"Wind\\\":135.84487000000001},{\\\"DateTime\\\":\\\"2023-08-23 20:30:00\\\",\\\"SPP Biomass\\\":10.71571,\\\"Coal\\\":541.5771,\\\"Major Hydro\\\":459.58078,\\\"SPP Minihydro\\\":12.01009,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":898.348726,\\\"Wind\\\":133.03643},{\\\"DateTime\\\":\\\"2023-08-23 20:45:00\\\",\\\"SPP Biomass\\\":10.78921,\\\"Coal\\\":542.3076,\\\"Major Hydro\\\":509.01743999999997,\\\"SPP Minihydro\\\":10.79686,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":904.29499824,\\\"Wind\\\":136.50999000000002},{\\\"DateTime\\\":\\\"2023-08-23 21:00:00\\\",\\\"SPP Biomass\\\":11.49455,\\\"Coal\\\":543.6475,\\\"Major Hydro\\\":480.16712099999995,\\\"SPP Minihydro\\\":10.35782,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":924.7139950000001,\\\"Wind\\\":128.78328},{\\\"DateTime\\\":\\\"2023-08-23 21:15:00\\\",\\\"SPP Biomass\\\":11.54045,\\\"Coal\\\":542.7495,\\\"Major Hydro\\\":435.28921,\\\"SPP Minihydro\\\":9.968702,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":925.5470730000001,\\\"Wind\\\":132.36974999999998},{\\\"DateTime\\\":\\\"2023-08-23 21:30:00\\\",\\\"SPP Biomass\\\":10.93472,\\\"Coal\\\":542.7344,\\\"Major Hydro\\\":380.0956699999999,\\\"SPP Minihydro\\\":11.80297,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":922.1725479999998,\\\"Wind\\\":134.21474},{\\\"DateTime\\\":\\\"2023-08-23 21:45:00\\\",\\\"SPP Biomass\\\":11.02293,\\\"Coal\\\":542.9169999999999,\\\"Major Hydro\\\":342.427841,\\\"SPP Minihydro\\\":13.71888,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":895.7954170000002,\\\"Wind\\\":138.08055},{\\\"DateTime\\\":\\\"2023-08-23 22:00:00\\\",\\\"SPP Biomass\\\":10.72171,\\\"Coal\\\":542.2620999999999,\\\"Major Hydro\\\":332.64162999999996,\\\"SPP Minihydro\\\":12.13059,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":885.219942,\\\"Wind\\\":134.91349},{\\\"DateTime\\\":\\\"2023-08-23 22:15:00\\\",\\\"SPP Biomass\\\":10.5537,\\\"Coal\\\":543.4648,\\\"Major Hydro\\\":329.115504,\\\"SPP Minihydro\\\":11.58936,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":817.3888109999998,\\\"Wind\\\":139.09804},{\\\"DateTime\\\":\\\"2023-08-23 22:30:00\\\",\\\"SPP Biomass\\\":11.16753,\\\"Coal\\\":542.9622999999999,\\\"Major Hydro\\\":310.223157,\\\"SPP Minihydro\\\":14.22171,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":800.9907450000001,\\\"Wind\\\":137.1403},{\\\"DateTime\\\":\\\"2023-08-23 22:45:00\\\",\\\"SPP Biomass\\\":10.94912,\\\"Coal\\\":541.2420999999999,\\\"Major Hydro\\\":273.050528,\\\"SPP Minihydro\\\":14.66903,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":800.713582,\\\"Wind\\\":140.37154},{\\\"DateTime\\\":\\\"2023-08-23 23:00:00\\\",\\\"SPP Biomass\\\":10.509,\\\"Coal\\\":541.7748,\\\"Major Hydro\\\":238.42526399999997,\\\"SPP Minihydro\\\":13.81158,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":801.5738709999998,\\\"Wind\\\":143.09553},{\\\"DateTime\\\":\\\"2023-08-23 23:15:00\\\",\\\"SPP Biomass\\\":9.970466,\\\"Coal\\\":545.4434,\\\"Major Hydro\\\":203.96566699999997,\\\"SPP Minihydro\\\":14.25381,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":782.1269027999999,\\\"Wind\\\":141.17221},{\\\"DateTime\\\":\\\"2023-08-23 23:30:00\\\",\\\"SPP Biomass\\\":10.36919,\\\"Coal\\\":542.6577,\\\"Major Hydro\\\":200.119667,\\\"SPP Minihydro\\\":15.06626,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":765.7458183999998,\\\"Wind\\\":143.44182},{\\\"DateTime\\\":\\\"2023-08-23 23:45:00\\\",\\\"SPP Biomass\\\":11.19843,\\\"Coal\\\":542.2319,\\\"Major Hydro\\\":174.745667,\\\"SPP Minihydro\\\":14.25201,\\\"Solar\\\":2E-06,\\\"Thermal-Oil\\\":736.4173453999999,\\\"Wind\\\":143.09574}]\""
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/CENACE/DemandaRegional.html",
    "content": "\n<!DOCTYPE html>\n<!-- PUBLIC \"-//W3C//DTD XHTML 1.0 Transitional//EN\" \"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd\">-->\n<html xmlns=\"http://www.w3.org/1999/xhtml\">\n<head id=\"Head1\"><title>\n\tDemanda Regional\n</title><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" /><meta http-equiv=\"X-UA-Compatible\" content=\"IE=edge\" /><meta http-equiv=\"imagetoolbar\" content=\"no\" /><meta name=\"viewport\" content=\"width=device-width, initial-scale=1\" /><link href=\"https://fonts.googleapis.com/css?family=Open+Sans:400,700,600,300\" rel=\"stylesheet\" type=\"text/css\" /><link href=\"https://framework-gb.cdn.gob.mx/assets/styles/main.css\" rel=\"stylesheet\" /><link rel=\"stylesheet\" href=\"/styles/layout.css\" type=\"text/css\" /><link rel=\"stylesheet\" href=\"/styles/responsiveslides.css\" type=\"text/css\" /><link rel=\"stylesheet\" href=\"/styles/megaOne.css\" type=\"text/css\" /><link rel=\"stylesheet\" 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style='margin-bottom: 40px;' />\");\n        });\n    </script>\n\n    <!-- SCRIPT DE GOOGLE ANALYTICS PARA ESTADISTICAS -->\n    <script type=\"text/javascript\">\n        (function (i, s, o, g, r, a, m) {\n            i['GoogleAnalyticsObject'] = r; i[r] = i[r] || function () {\n                (i[r].q = i[r].q || []).push(arguments)\n            }, i[r].l = 1 * new Date(); a = s.createElement(o),\n            m = s.getElementsByTagName(o)[0]; a.async = 1; a.src = g; m.parentNode.insertBefore(a, m)\n        })(window, document, 'script', '//www.google-analytics.com/analytics.js', 'ga');\n\n        ga('create', 'UA-62147574-1', 'auto');\n        ga('send', 'pageview');\n\n        $(document).ready(function () {\n            $('ul.nav li.dropdown').hover(function () {\n                $(this).find('.dropdown-menu').stop(true, true).delay(200).fadeIn(200);\n            }, function () {\n                $(this).find('.dropdown-menu').stop(true, true).delay(200).fadeOut(200);\n            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navbar-inverse sub-navbar fixed-top\" style=\"margin-top: 0px;  position:fixed\">\n        <div class=\"container\">\n            <div class=\"navbar-header\">\n                <button type=\"button\" class=\"navbar-toggle collapsed\" data-toggle=\"collapse\" data-target=\"#subenlaces\">\n                    <span class=\"sr-only\">Interruptor de Navegación</span>\n                    <span class=\"icon-bar\"></span>\n                    <span class=\"icon-bar\"></span>\n                    <span class=\"icon-bar\"></span>\n                </button>\n            </div>\n            <div class=\"collapse navbar-collapse\" id=\"subenlaces\">\n                <ul class=\"nav navbar-nav navbar-right\">\n                    <li><a href=\"http://www.gob.mx/cenace/archivo/articulos\">Blog</a></li>\n                    <li><a href=\"http://www.gob.mx/cenace/archivo/multimedia\">Multimedia</a></li>\n                    <li><a href=\"http://www.gob.mx/cenace/archivo/prensa\">Prensa</a></li>\n    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      <div id=\"contenido\" class=\"wrapper col4\">\n\n    <div class=\"breadcrumbGrafica\" style=\"margin:0px;padding-bottom:30px;padding-left: 0px;\">\n        <div class=\"breadcrumb\" style=\"text-align: left; margin-left: 50px; margin-bottom:0px;\">\n    <span id=\"ContentPlaceHolder1_graficasBreadcrumb_smpMapPath\" style=\"display:inline-block;height:30px;\"><a href=\"#ContentPlaceHolder1_graficasBreadcrumb_smpMapPath_SkipLink\"><img alt=\"Skip Navigation Links\" src=\"/WebResource.axd?d=m_gpC38WsyEnxokFzTvIQdzhxkuAz-klE-fs_46F6nThda_B35yQwghiOPB1h0a1mIAakDgQ3KsmG3bzWRwFHQqhU-9wAoBYgFtkczSERag1&amp;t=637823149705833095\" width=\"0\" height=\"0\" style=\"border-width:0px;\" /></a><span>\n            <a href=\"http://www.gob.mx/cenace\" title=\"Inicio\"><i class=\"icon icon-home\"></i></a>\n        </span><span>\n            <span class=\"divider\"></span>\n        </span><span><a title=\"CENACE\" href=\"/CENACE.aspx\">CENACE</a></span><span>\n            <span class=\"divider\"></span>\n        </span><span style=\"color:#545454;font-weight:bold;\">Demanda del Sistema El&#233;ctrico Nacional</span><a id=\"ContentPlaceHolder1_graficasBreadcrumb_smpMapPath_SkipLink\"></a></span><br />\n     <span id=\"ContentPlaceHolder1_graficasBreadcrumb_SIM_AP\" style=\"font-weight:600; font-size:20px;\"></span>\n</div>\n\n    </div>\n    <div class=\"containerGrafica\" style=\"height: 460px; display: inline-block; width: 1040px\">\n        <div class=\"chartContainer\" style=\"width: 100%; margin-top: 0px;\">\n            <div id=\"tituloContacto\" class=\"titulo\" style=\"margin-left: 0;\">Demanda del Sistema Eléctrico Nacional</div>\n            <div class=\"mapaDemanda\">\n                <div class=\"mapaDemandaInferior\">\n                    <div class=\"instruccion\">Al pasar por cada zona del mapa podrás visualizar la generación y demanda actual de la región.</div>\n                    <img alt=\"mapa\" src=\"/images/MapaInteractivo/MapaAreas3.png\" style=\"width: 803px; height: 568px;\" />\n                </div>\n                <div id=\"demandaBCN\" class=\"demandaRegion divOculto\">\n                    <img alt=\"BCN\" src=\"/images/MapaInteractivo/BCN2.png\" />\n                    <div class=\"datosDemanda\">\n                        <table class=\"datosEncabezado\">\n                            <tr>\n                                <th colspan=\"2\">Baja California Norte</th>\n                            </tr>\n                        </table>\n                        <table class=\"datosCelda\">\n                            <tr>\n                                <td>Generación Neta</td>\n                                <td class=\"num\" id=\"GeneracionBCA\">1,564</td>\n                            </tr>\n                            <tr>\n                                <td>Intercambio Neto</td>\n                                <td class=\"num\" id=\"IntercambioBCA\">23</td>\n                            </tr>\n                            <tr>\n                                <td style=\"border: none;\">Demanda Neta</td>\n                                <td class=\"num\" id=\"DemandaBCA\" style=\"border: none;\">1,587</td>\n                            </tr>\n                        </table>\n                    </div>\n                </div>\n                <div id=\"demandaBCS\" class=\"demandaRegion divOculto\">\n                    <img alt=\"BCS\" src=\"/images/MapaInteractivo/BCS.png\" />\n                    <div class=\"datosDemanda\">\n                        <table class=\"datosEncabezado\">\n                            <tr>\n                                <th colspan=\"2\">Baja California Sur</th>\n                            </tr>\n                        </table>\n                        <table class=\"datosCelda\">\n                            <tr>\n                                <td>Generación Neta</td>\n                                <td class=\"num\" id=\"GeneracionBCS\">340</td>\n                            </tr>\n                            <tr>\n                                <td>Intercambio Neto</td>\n\n                                <td class=\"num\" id=\"IntercambioBCS\">N/A</td>\n                            </tr>\n                            <tr>\n                                <td style=\"border: none;\">Demanda Neta</td>\n                                <td class=\"num\" id=\"DemandaBCS\" style=\"border: none;\">0</td>\n                            </tr>\n                        </table>\n                    </div>\n                </div>\n                <div id=\"demandaNOR\" class=\"demandaRegion divOculto\">\n                    <img alt=\"NOR\" src=\"/images/MapaInteractivo/NOR.png\" />\n                    <div class=\"datosDemanda\">\n                        <table class=\"datosEncabezado\">\n                            <tr>\n                                <th colspan=\"2\">Noroeste</th>\n                            </tr>\n                        </table>\n                        <table class=\"datosCelda\">\n                            <tr>\n                                <td>Generación Neta</td>\n                                <td class=\"num\" id=\"GeneracionNOR\">2,759</td>\n                            </tr>\n                            <tr>\n                                <td>Intercambio Neto</td>\n                                <td class=\"num\" id=\"IntercambioNOR\">&#8208;470</td>\n                            </tr>\n                            <tr>\n                                <td style=\"border: none;\">Demanda Neta</td>\n                                <td class=\"num\" id=\"DemandaNOR\" style=\"border: none;\">2,295</td>\n                            </tr>\n                        </table>\n                    </div>\n                </div>\n                <div id=\"demandaNTE\" class=\"demandaRegion divOculto\">\n                    <img alt=\"NTE\" src=\"/images/MapaInteractivo/NTE.png\" />\n                    <div class=\"datosDemanda\">\n                        <table class=\"datosEncabezado\">\n                            <tr>\n                                <th colspan=\"2\">Norte</th>\n                            </tr>\n                        </table>\n                        <table class=\"datosCelda\">\n                            <tr>\n                                <td>Generación Neta</td>\n                                <td class=\"num\" id=\"GeneracionNTE\">3,988</td>\n                            </tr>\n                            <tr>\n                                <td>Intercambio Neto</td>\n                                <td class=\"num\" id=\"IntercambioNTE\">&#8208;561</td>\n                            </tr>\n                            <tr>\n                                <td style=\"border: none;\">Demanda Neta</td>\n                                <td class=\"num\" id=\"DemandaNTE\" style=\"border: none;\">3,426</td>\n                            </tr>\n                        </table>\n                    </div>\n                </div>\n                <div id=\"demandaNES\" class=\"demandaRegion divOculto\">\n                    <img alt=\"NES\" src=\"/images/MapaInteractivo/NES.png\" />\n                    <div class=\"datosDemanda\">\n                        <table class=\"datosEncabezado\">\n                            <tr>\n                                <th colspan=\"2\">Noreste</th>\n                            </tr>\n                        </table>\n                        <table class=\"datosCelda\">\n                            <tr>\n                                <td>Generación Neta</td>\n                                <td class=\"num\" id=\"GeneracionNES\">9,113</td>\n                            </tr>\n                            <tr>\n                                <td>Intercambio Neto</td>\n                                <td class=\"num\" id=\"IntercambioNES\">&#8208;3,444</td>\n                            </tr>\n                            <tr>\n                                <td style=\"border: none;\">Demanda Neta</td>\n                                <td class=\"num\" id=\"DemandaNES\" style=\"border: none;\">5,677</td>\n                            </tr>\n                        </table>\n                    </div>\n                </div>\n                <div id=\"demandaOCC\" class=\"demandaRegion divOculto\">\n                    <img alt=\"OCC\" src=\"/images/MapaInteractivo/OCC.png\" />\n                    <div class=\"datosDemanda\">\n                        <table class=\"datosEncabezado\">\n                            <tr>\n                                <th colspan=\"2\">Occidental</th>\n                            </tr>\n                        </table>\n                        <table class=\"datosCelda\">\n                            <tr>\n                                <td>Generación Neta</td>\n                                <td class=\"num\" id=\"GeneracionOCC\">7,023</td>\n                            </tr>\n                            <tr>\n                                <td>Intercambio Neto</td>\n                                <td class=\"num\" id=\"IntercambioOCC\">1,514</td>\n                            </tr>\n                            <tr>\n                                <td style=\"border: none;\">Demanda Neta</td>\n                                <td class=\"num\" id=\"DemandaOCC\" style=\"border: none;\">8,519</td>\n                            </tr>\n                        </table>\n                    </div>\n                </div>\n                <div id=\"demandaCEL\" class=\"demandaRegion divOculto\">\n                    <img alt=\"CEL\" src=\"/images/MapaInteractivo/CEL.png\" />\n                    <div class=\"datosDemanda\">\n                        <table class=\"datosEncabezado\">\n                            <tr>\n                                <th colspan=\"2\">Central</th>\n                            </tr>\n                        </table>\n                        <table class=\"datosCelda\">\n                            <tr>\n                                <td>Generación Neta</td>\n                                <td class=\"num\" id=\"GeneracionCEL\">4,190</td>\n                            </tr>\n                            <tr>\n                                <td>Intercambio Neto</td>\n                                <td class=\"num\" id=\"IntercambioCEL\">2,379</td>\n                            </tr>\n                            <tr>\n                                <td style=\"border: none;\">Demanda Neta</td>\n                                <td class=\"num\" id=\"DemandaCEL\" style=\"border: none;\">6,573</td>\n                            </tr>\n                        </table>\n                    </div>\n                </div>\n                <div id=\"demandaORI\" class=\"demandaRegion divOculto\">\n                    <img alt=\"ORI\" src=\"/images/MapaInteractivo/ORI.png\" />\n                    <div class=\"datosDemanda\">\n                        <table class=\"datosEncabezado\">\n                            <tr>\n                                <th colspan=\"2\">Oriental</th>\n                            </tr>\n                        </table>\n                        <table class=\"datosCelda\">\n                            <tr>\n                                <td>Generación Neta</td>\n                                <td class=\"num\" id=\"GeneracionORI\">6,106</td>\n                            </tr>\n                            <tr>\n                                <td>Intercambio Neto</td>\n                                <td class=\"num\" id=\"IntercambioORI\">57</td>\n                            </tr>\n                            <tr>\n                                <td style=\"border: none;\">Demanda Neta</td>\n                                <td class=\"num\" id=\"DemandaORI\" style=\"border: none;\">6,163</td>\n                            </tr>\n                        </table>\n                    </div>\n                </div>\n                <div id=\"demandaPEN\" class=\"demandaRegion divOculto\">\n                    <img alt=\"PEN\" src=\"/images/MapaInteractivo/PEN2.png\" />\n                    <div class=\"datosDemanda\">\n                        <table class=\"datosEncabezado\">\n                            <tr>\n                                <th colspan=\"2\">Peninsular</th>\n                            </tr>\n                        </table>\n                        <table class=\"datosCelda\">\n                            <tr>\n                                <td>Generación Neta</td>\n                                <td class=\"num\" id=\"GeneracionPEN\">1,283</td>\n                            </tr>\n                            <tr>\n                                <td>Intercambio Neto</td>\n                                <td class=\"num\" id=\"IntercambioPEN\">333</td>\n                            </tr>\n                            <tr>\n                                <td style=\"border: none;\">Demanda Neta</td>\n                                <td class=\"num\" id=\"DemandaPEN\" style=\"border: none;\">1,616</td>\n                            </tr>\n                        </table>\n                    </div>\n                </div>\n                <div class=\"mapaDemandaSuperior\">\n                    <img alt=\"\" src=\"/images/MapaInteractivo/capaVacia.png\" usemap=\"#mapRegiones\" />\n                    <map id=\"mapRegiones\" name=\"mapRegiones\">\n                        <area id=\"areaBCN\" href=\"javascript:void(0);\" alt=\"\" title=\"\" shape=\"poly\" coords=\"2,3,60,3,59,10,57,19,55,27,51,33,51,40,61,50,62,55,60,60,59,65,59,70,60,75,62,78,62,83,63,90,62,97,64,104,68,107,69,112,72,112,76,118,86,126,88,133,89,139,92,138,93,142,97,142,99,153,105,154,104,158,106,162,105,165,70,163,72,159,71,156,72,149,65,137,61,130,53,121,48,120,40,112,36,108,34,102,34,93,31,87,29,88,29,76,23,71,23,62,20,57,16,55,18,45,12,39,12,31,9,28\" />\n                        <area id=\"areaBCS\" href=\"javascript:void(0);\" alt=\"\" title=\"\" shape=\"poly\" coords=\"69,165,107,168,106,172,111,179,117,181,117,190,123,195,124,199,135,208,137,214,135,222,139,225,144,243,147,244,155,262,154,272,156,280,161,284,166,285,167,280,172,286,177,290,177,301,184,303,187,310,185,315,181,317,175,325,172,324,169,317,167,308,164,301,156,297,145,285,136,278,129,270,126,272,121,261,120,265,115,259,118,250,120,242,119,233,115,225,113,219,106,218,92,205,87,204,83,209,77,197,73,197,67,189,61,186,60,180,49,172,59,175,64,172\" />\n                        <area id=\"areaNOR\" href=\"javascript:void(0);\" alt=\"\" title=\"\" shape=\"poly\" coords=\"62,12,57,27,53,33,53,40,57,44,64,50,69,54,85,62,92,69,103,72,104,85,112,103,111,111,119,123,123,138,140,158,161,178,164,191,174,200,179,201,184,211,197,218,190,233,191,243,202,250,214,254,225,267,226,273,253,296,265,311,271,322,289,341,297,334,287,322,285,298,270,296,264,284,256,277,256,250,229,231,226,221,214,205,216,183,216,155,218,133,218,117,217,104,223,69,222,63,200,63,177,62,157,59,144,56,134,52\" />\n                        <area id=\"areaNTE\" href=\"javascript:void(0);\" alt=\"\" title=\"\" shape=\"poly\" coords=\"226,62,224,63,224,73,222,84,220,96,219,108,220,129,218,147,218,164,218,178,217,189,217,204,227,220,231,228,257,249,258,276,266,282,272,294,287,296,289,320,299,333,290,340,304,353,310,353,313,345,314,321,316,317,320,316,326,294,326,293,349,293,353,277,365,273,351,260,355,228,348,219,343,200,342,184,346,175,355,165,364,148,381,129,384,119,366,125,362,137,355,145,331,133,318,121,312,97,302,88,297,88,293,80,287,70,273,62,273,57,271,55,267,55,259,50,227,50\" />\n                        <area id=\"areaNES\" href=\"javascript:void(0);\" alt=\"\" title=\"\" shape=\"poly\" coords=\"386,118,383,131,366,150,357,167,348,177,344,185,345,201,351,219,358,228,354,259,367,273,375,279,379,285,386,289,391,295,391,304,388,311,391,314,390,321,388,324,388,327,397,332,394,340,400,340,405,342,410,342,414,348,416,357,419,361,422,366,424,373,431,388,434,396,435,400,444,410,447,407,446,405,450,403,455,407,461,408,462,411,462,414,463,417,466,416,471,412,479,408,490,407,494,411,496,416,501,410,510,409,519,406,530,403,531,398,524,392,523,387,513,372,520,365,505,349,504,334,508,325,507,269,511,265,519,245,520,232,515,232,512,237,506,232,492,232,480,225,465,219,460,211,454,205,450,184,440,179,438,171,428,157,422,141,413,131,407,126,403,120,396,120,391,116\" />\n                        <area id=\"areaOCC\" href=\"javascript:void(0);\" alt=\"\" title=\"\" shape=\"poly\" coords=\"366,275,356,279,351,295,328,296,323,316,320,319,316,321,315,346,312,355,305,355,290,343,290,353,295,365,302,368,300,374,301,381,298,382,301,396,298,398,298,406,305,414,302,419,303,428,318,441,319,439,324,440,325,442,341,453,349,461,385,475,388,470,391,462,394,458,397,457,399,454,404,454,414,449,417,447,424,445,430,445,433,442,436,442,440,438,442,430,443,428,444,426,448,426,449,424,453,424,454,422,457,422,458,420,461,419,460,415,460,411,454,409,449,405,450,409,447,410,443,413,432,401,431,396,428,392,428,388,421,373,420,367,413,360,413,351,408,343,405,344,400,343,394,342,391,339,394,333,385,328,386,322,388,320,389,315,385,311,388,304,389,295,376,285,373,281\" />\n                        <area id=\"areaCEL\" href=\"javascript:void(0);\" alt=\"\" title=\"\" shape=\"poly\" coords=\"387,475,388,473,391,470,393,465,394,462,399,459,401,456,406,456,410,453,414,452,418,449,424,448,431,448,434,444,439,444,442,440,444,432,446,428,451,428,451,427,455,426,456,424,459,424,460,422,464,421,465,419,468,418,472,414,478,411,482,409,488,409,494,413,494,417,497,419,493,420,493,422,489,424,489,428,487,432,487,434,488,436,489,443,490,450,492,454,489,457,483,456,482,459,474,460,473,463,470,461,468,462,461,462,462,460,457,461,454,458,445,460,445,457,430,457,430,460,426,461,421,461,414,465,411,467,408,471,402,470,401,473,395,472,393,474,393,477\" />\n                        <area id=\"areaORI\" href=\"javascript:void(0);\" alt=\"\" title=\"\" shape=\"poly\" coords=\"399,482,395,476,398,475,403,475,410,473,415,470,419,467,423,465,429,465,433,462,433,460,443,459,444,463,454,461,461,465,475,465,477,462,485,462,486,459,492,460,495,455,493,449,492,443,491,435,489,433,491,430,492,426,496,424,496,421,500,420,499,417,500,414,503,412,512,412,522,409,529,405,533,405,534,400,546,415,548,424,552,431,556,432,556,443,559,443,560,449,570,454,580,454,585,458,592,459,603,469,613,470,621,468,629,464,637,462,646,460,651,460,658,449,667,447,678,445,682,451,686,449,697,461,700,462,702,486,691,486,699,492,709,496,713,503,720,506,721,518,685,518,672,542,678,548,674,551,676,560,671,566,657,551,633,532,613,523,595,521,582,523,578,528,558,538,551,538,547,540,535,534,525,532,511,532,498,523,487,522,482,514,470,512,456,511,451,506,418,495\" />\n                        <area id=\"areaPEN\" href=\"javascript:void(0);\" alt=\"\" title=\"\" shape=\"poly\" coords=\"687,447,699,459,703,460,704,469,748,463,748,458,757,459,762,453,762,448,767,442,771,442,773,440,774,432,778,430,780,434,780,441,786,448,792,421,787,419,791,410,786,410,791,401,790,396,789,385,799,370,801,354,797,352,774,348,770,350,762,351,757,355,728,363,722,365,713,372,713,377,710,379,711,402,707,409,706,422,696,431,688,435,686,438,693,440,690,445\" />\n                    </map>\n                </div>\n                <div class=\"mapaIntercambio divOculto\">\n                    <img alt=\"\" src=\"/images/MapaInteractivo/mapaTrazo.png\" />\n                    <div id=\"IntNTE-NOR\" class=\"divIntercambio\">\n                        <div id=\"IntercambioNTE-NOR\" class=\"datoIntercambio\">54</div>\n                        <div class=\"flechaNTE-NOR\"></div>\n                    </div>\n                    <div id=\"IntNES-NTE\" class=\"divIntercambio\">\n                        <div id=\"IntercambioNES-NTE\" class=\"datoIntercambio\">&#8208;352</div>\n                        <div class=\"flechaNES-NTE\"></div>\n                    </div>\n                    <div id=\"IntNES-ORI\">\n                        <div id=\"IntercambioNES-ORI\" class=\"datoIntercambio\">1,433</div>\n                        <div class=\"flechaNES-ORI\"></div>\n                    </div>\n                    <div id=\"IntORI-PEN\">\n                        <div id=\"IntercambioORI-PEN\" class=\"datoIntercambio\">380</div>\n                        <div class=\"flechaORI-PEN\"></div>\n                    </div>\n                    <div id=\"IntORI-CEL\">\n                        <div id=\"IntercambioORI-CEL\" class=\"datoIntercambio\">758</div>\n                        <div class=\"flechaORI-CEL\"></div>\n                    </div>\n                    <div id=\"IntOCC-ORI\">\n                        <div id=\"IntercambioOCC-ORI\" class=\"datoIntercambio\">262</div>\n                        <div class=\"flechaOCC-ORI\"></div>\n                    </div>\n                    <div id=\"IntOCC-CEL\">\n                        <div id=\"IntercambioOCC-CEL\" class=\"datoIntercambio\">1,625</div>\n                        <div class=\"flechaOCC-CEL\"></div>\n                    </div>\n                    <div id=\"IntNES-OCC\">\n                        <div id=\"IntercambioNES-OCC\" class=\"datoIntercambio\">2,456</div>\n                        <div class=\"flechaNES-OCC\"></div>\n                    </div>\n                    <div id=\"IntNTE-OCC\">\n                        <div id=\"IntercambioNTE-OCC\" class=\"datoIntercambio\">0</div>\n                        <div class=\"flechaNTE-OCC\"></div>\n                    </div>\n                    <div id=\"IntNOR-OCC\">\n                        <div id=\"IntercambioNOR-OCC\" class=\"datoIntercambio\">519</div>\n                        <div class=\"flechaNOR-OCC\"></div>\n                    </div>\n                    <div id=\"IntUSA-BCA\" class=\"divIntercambio\">\n                        <div id=\"IntercambioUSA-BCA\" class=\"datoIntercambio\">&#8208;23</div>\n                        <div class=\"flechaUSA-BCA\"></div>\n                    </div>\n                    <div id=\"IntUSA-NTE\" class=\"divIntercambio\">\n                        <div id=\"IntercambioUSA-NTE\" class=\"datoIntercambio\">0</div>\n                        <div class=\"flechaUSA-NTE\"></div>\n                    </div>\n                    <div id=\"IntUSA-NES\" class=\"divIntercambio\">\n                        <div id=\"IntercambioUSA-NES\" class=\"datoIntercambio\">&#8208;31</div>\n                        <div class=\"flechaUSA-NES\"></div>\n                    </div>\n                    <div id=\"IntPEN-BEL\" class=\"divIntercambio\">\n                        <div id=\"IntercambioPEN-BEL\" class=\"datoIntercambio\">48</div>\n                        <div class=\"flechaPEN-BEL\"></div>\n                    </div>\n                    <div id=\"IntORI-GUA\" class=\"divIntercambio\">\n                        <div id=\"IntercambioORI-GUA\" class=\"datoIntercambio\">241</div>\n                        <div class=\"flechaORI-GUA\"></div>\n                    </div>\n                </div>\n                 <table style=\"width:120%\">\n                    <tr >\n                        <td style=\"width:50%\">\n                            <div class=\"nota\">\n                                <span>SIN:</span> Sistema Interconectado Nacional, no incluye las regiones de Baja California y Baja California Sur.<br />\n                                <span>Intercambio neto:</span> intercambio total entre esa región y las vecinas.\n                            </div>\n                        </td>\n                        <td style=\"width:50%\">\n                            <div class=\"nota\">\n                                La información que aquí se presenta es de carácter indicativo, su objetivo es únicamente mostrar el comportamiento de la Operación del Sistema Eléctrico Nacional.\n                                Por lo que esta información no puede ser utilizada para otros efectos diferentes a los demostrativos a los que aquí se mencionan.\n                            </div>\n                        </td>\n                    </tr>\n                </table>\n            </div>\n            <div class=\"tablaResumen\" style=\"float: right\">\n\n\n                <div>\n                    <table>\n                        <tr>\n                            <th colspan=\"4\" class=\"headerDiario\">Demanda Neta máxima instantánea en el día de hoy del SIN</th>\n                        </tr>\n                        <tr>\n                            <td class=\"celdaMargen\"></td>\n                            <td colspan=\"2\"><span id=\"DemandaSIN-MAX-DIARIAValor\">34,935 MW</span></td>\n                            <td class=\"celdaMargen\"></td>\n                        </tr>\n                        <tr>\n                            <td class=\"celdaMargen\"></td>\n                            <td class=\"ultimaFila\">Hora</td>\n                            <td class=\"ultimaFila num\" id=\"DemandaSIN-MAX-DIARIAHora\">12:04:43 hrs</td>\n                            <td class=\"celdaMargen\"></td>\n                        </tr>\n                    </table>\n                </div>\n                <div class=\"botonIntercambio\">Intercambio entre regiones</div>\n            </div>\n        </div>\n    </div>\n    <div style=\"height: 280px;\">&nbsp;</div>\n\n            </div>\n            <script src=\"/scripts/funciones.js\" type=\"text/javascript\"></script>\n            <script type=\"text/javascript\" src=\"/scripts/classie.js\"></script>\n            <script type=\"text/javascript\">\n                var buttons7Click = Array.prototype.slice.call(document.querySelectorAll('#btn-click a')),\n                    totalButtons7Click = buttons7Click.length;\n\n                buttons7Click.forEach(function (el, i) { el.addEventListener('click', activate, 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  {
    "path": "electricitymap/contrib/parsers/tests/mocks/CL/response_historical_20240224.json",
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\"red\"});\n\t\t\t*/\n\t\t\t\t});\n\t\tchart.render();\n\n\t\tchart.subtitles[0].set(\"text\", dateFormat($( \"#fechaGe\" ).val(), 'dddd, d \"de\" mmmm \"de\" yyyy', true) );\n\n\t}\n\nshowNow();\n\nfunction showNow()\n{\n\tupdateChart($(\"#fechaGe\").datepicker({dateFormat: \"yy-mm-dd\"}).datepicker(\"setDate\", $.now()).val());\n}\n\nfunction updateChart(fecha) {\n\t\t$.ajaxSetup({beforeSend: function (xhr) { xhr.setRequestHeader(\"X-Csrf-Token\", ttoken); }});\n\t\t$.getJSON(\"./dat/gene.php\",{ \"fechag\" : fecha }, function(data, status, xhr) {\n\t\t\tif (data.data.length === 0)\n\t\t\t{\n\t\t\t\t//location.reload(true);\n\t\t\t}\n\t\t\telse\n\t\t\t{\n\t\t\t\tttoken = data.ttoken;\n\t\t\t\tsetChart(data.data);\n\t\t\t}\n\t\t\treturn false;\n\t\t});\n\t}\n\n\tsetInterval(function(){showNow()}, 15*60*1000);\n}\n</script>\n\n\n<script>\n$(document).ready(function()\n{\n   $('#OverlayMenu1-overlay').overlay({hideTransition:true});\n   $('.OverlayMenu1').drilldownmenu({backText: 'Back'});\n   $('#OverlayMenu1').on('click', function(e)\n   {\n      $.overlay.show($('#OverlayMenu1-overlay'));\n      return false;\n   });\n});\n</script>\n\n\n</head>\n<body>\n<div id=\"FlexGrid1\">\n<div class=\"header\" style=\"background-color: rgb(0, 33, 139);\">\n<div id=\"wb_Text1\">\n<span style=\"background-color: rgb(0, 33, 139); color: rgb(255, 255, 255); font-family: Arial; font-size: 20px;\">Comité Nacional de Despacho de Carga</span>\n</div>\n</div>\n\n\n<div class=\"nav\">\n</div>\n<div class=\"main\">\n</div>\n<div class=\"sidebar\">\n<div id=\"wb_OverlayMenu1\" style=\"width: 50px; height: 50px; z-index: 1;\">\n<a href=\"#\" id=\"OverlayMenu1\">\n<span class=\"line\"></span>\n<span class=\"line\">\n</span><span class=\"line\"></span>\n</a>\n</div>\n</div>\n<div class=\"footer\">\n</div>\n</div>\n<div id=\"OverlayMenu1-overlay\">\n<div class=\"OverlayMenu1\">\n<ul class=\"drilldown-menu\" role=\"menu\">\n<li><a role=\"menuitem\" href=\"#\" class=\"OverlayMenu1-effect\"><i class=\"fa fa-home overlay-icon\"></i>Inicio</a></li>\n<li>\n<a role=\"menuitem\" href=\"#\" class=\"OverlayMenu1-effect\"><i class=\"fa fa-line-chart overlay-icon\"></i>Graficos</a>\n<ul class=\"drilldown-submenu\" role=\"menu\">\n<li>\n<a role=\"menuitem\" href=\"#\" class=\"OverlayMenu1-effect\"><i class=\"fa fa-line-chart overlay-icon\"></i>Generación</a>\n<ul class=\"drilldown-submenu\" role=\"menu\">\n<li><a role=\"menuitem\" href=\"index.php\" class=\"OverlayMenu1-effect\">Generación&nbsp;horaria</a><br>\n</li>\n</ul>\n        <br>\n</li>\n<li>\n<a role=\"menuitem\" href=\"#\" class=\"OverlayMenu1-effect\">HTML</a>\n<ul class=\"drilldown-submenu\" role=\"menu\">\n<li><a role=\"menuitem\" href=\"#\" class=\"OverlayMenu1-effect\">Test</a><br>\n</li>\n</ul>\n        <br>\n</li>\n</ul>\n</li>\n   </ul>\n</div>\n<a class=\"close-button\" id=\"OverlayMenu1-close\" href=\"#\" role=\"button\" aria-hidden=\"true\"><span></span></a>\n</div>\n\n<div class=\"\" style=\"padding: 5px 5px 5px 5px;\">\n<div id=\"update-nav\" style=\"width:100%;height:50px;\">\n<div id=\"range-selector\" style=\"width:65%;float: left;\">\n</div>\n  <div id=\"date-selector\" class=\"\" style=\"width:35%;float: right;\" >\n      <strong>Fecha :</strong> <input type=\"text\" id=\"fechaGe\" size=\"8\" class=\"ui-widget\">\n  </div>\n</div>\n\n<div id=\"chartContainer\" style=\"height: 550px; max-width: 900px; margin: 0px auto;\"></div>\n</div>\n\n\n\n</body></html>\n\n<style type=\"text/css\">\n<!--\nbody {\n\tbackground-color: #eff0e3;\n}\n-->\n</style>"
  },
  {
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CUY\",\"492\":\"AGPE SUBASTAR SAHAGUN\",\"493\":\"AGPE CESAR JULIO HERNANDEZ\",\"494\":\"AGPE INDUSTRIAS NEGLE II\",\"495\":\"AGPE FUNDACION  OFTALMOLOGICA\",\"496\":\"AGPE CC LA FLORIDA II\",\"497\":\"AGPE RAMON GIRALDO GONZALEZ\",\"498\":\"AGPE MAURICIO VERGARA FRANCO\",\"499\":\"AUTOG BIOS CONTEGRAL CARTAGO\",\"500\":\"AGPE PARROQUIA ESPIRITU SANTO\",\"501\":\"AGPE RODOLFO ANTONIO ONATE\",\"502\":\"AUTOG BIOS CONTEGRAL NEIVA\",\"503\":\"AGPE GRUPO SAN JORGE\",\"504\":\"AUTOG EL COPEY\",\"505\":\"AGPE COLGATE PALMOLIVE PALMIRA\",\"506\":\"AGPE OCCICAUCHO\",\"507\":\"AGPE UNIPLAST SAS\",\"508\":\"AGPE SANTIAGO ARANGO\",\"509\":\"AGPE PRIMAX COLOMBIA FACATATIVA\",\"510\":\"PARQUE SOLAR HONDA II\",\"511\":\"JEQUES\",\"512\":\"CELSIA SOLAR BUGALAGRANDE\",\"513\":\"AGPE COLEGIO PARROQUIAL PABLO VI\",\"514\":\"AGPE CASA EPISCOPAL\",\"515\":\"AGPE SEMINARIO DIOCESANO JUAN PABLO II\",\"516\":\"AGPE AGROZ\",\"517\":\"AGPE LA SELVA\",\"518\":\"AGPE AMERICANA DE CURTIDOS\",\"519\":\"AGPE CABANA 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SAS\",\"546\":\"AGPE GRICOAT COLOMBIA I\",\"547\":\"AGPE TSM PROJECT\",\"548\":\"AGPE FELIX TORRES\",\"549\":\"AGPE FARMATODO LIMONAR\",\"550\":\"AGPE PLEX CORPORATIVO PROPIEDAD HORIZONTAL\",\"551\":\"AGPE BANCO BOGOTA SAN NICOLAS\",\"552\":\"AGPE HUGO ALEJANDRO HERRERA\",\"553\":\"AGPE CLINIDOTACIONES SAS\",\"554\":\"AGPE LA CASA DEL DEPORTE\",\"555\":\"AGPE ERAZO MARTINEZ ASOCIADOS\",\"556\":\"AGPE VINALE S EN C\",\"557\":\"AGPE ANDRES RODRIGO JARAMILLO DURANGO\",\"558\":\"AGPE SUB LIBERTADOR\",\"559\":\"AGPE  ALIMENTOS NARINO MC SAS\",\"560\":\"AGPE PROAGR19\",\"561\":\"AGPE EDS LA PAZ\",\"562\":\"AGPE JORGE ARMANDO SANCHEZ MEJIA\",\"563\":\"AGPE GRUPO FIRENZE SAS LOC 1\",\"564\":\"AGPE AUTOTECNICA COLOMBIANA\",\"565\":\"AGPE INVERSIONES SANTOS HR SAS\",\"566\":\"AGPE ASOCIACION DE MUNICIPIOS DEL SINU SABANA\",\"567\":\"AGPE HERNAN DARIO GONZALEZ\",\"568\":\"AGPE MARIA MERCES GARCIA BURGOS\",\"569\":\"AGPE MELISSA ANDREA GUERRA LOPEZ\",\"570\":\"AGPE SPATARO NAPOLI\",\"571\":\"GD 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ACRILAN\",\"623\":\"AGPE HOTEL EL PASO MONTERIANO\",\"624\":\"AGPE JERONIMO MARTINS COLOMBIA SAS\",\"625\":\"AGPE IBC\",\"626\":\"AGPE WILLIAM ENCINALES\",\"627\":\"AUTOG SOLAR PALMIRA II BERRY\",\"628\":\"AGPE MAKONDO\",\"629\":\"AGPE TEUCALI FLOWERS SA\",\"630\":\"BSB 501\",\"631\":\"BSB 500\",\"632\":\"BSB 502\",\"633\":\"CENTRO SOLAR\",\"634\":\"BUENAVISTA\",\"635\":\"AGPE BERNARDO JOSE REVUELTAS GONZALEZ\",\"636\":\"AUTOG BIOS FINCA BUGA\",\"637\":\"GD ERCO SALDANA I\",\"638\":\"GD ERCO SALDANA II\",\"639\":\"AGPE INERSIONES EJJ SAS\",\"640\":\"AUTOG BIODIANA 1\",\"641\":\"MINIGRANJA LA PAZ VERSO\",\"642\":\"CONDOR\",\"643\":\"AUTOG BIOS CIENAGA ORO\",\"644\":\"AGPE INVERSIONES RIPAS SAS\",\"645\":\"AGPE CEDITITAN\",\"646\":\"AGPE AIDA PIEDAD RAMOS ANAYA\",\"647\":\"AGPE CASA EL UBERRIMO\",\"648\":\"AGPE DISTRIBUIDORA DE BANANOS OCHOA SEDE I\",\"649\":\"GD BOCAS DEL PALO\",\"650\":\"GD FINCA ISABEL LOPEZ\",\"651\":\"AGPE MANUFACTURAS AF SAS\",\"652\":\"AGPE PARROQUIA NUESTRA 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TECNOACEROS SAS\",\"680\":\"AGPE ANA CAROLINA NAVARRO\",\"681\":\"AGPE NASELA SAS\",\"682\":\"AGPE CPANAME\",\"683\":\"AGPE FAMJ1\",\"684\":\"AGPE LOS POTRILLOS RESTAURANTE BAR\",\"685\":\"LA CASCADA ( ABEJORRAL)\",\"686\":\"AGUA FRESCA\",\"687\":\"ALBAN\",\"688\":\"ALTO TULUA\",\"689\":\"AMAIME\",\"690\":\"AMALFI\",\"691\":\"AMERICA\",\"692\":\"FUTURA - PARQUE ALPHA\",\"693\":\"FUTURA - APOTOLORRU\",\"694\":\"AUTOG ARGOS CARTAGENA 1\",\"695\":\"ASNAZU\",\"696\":\"AUTOG AYURA\",\"697\":\"BARROSO\",\"698\":\"FUTURA - PARQUE BETA\",\"699\":\"BELLO\",\"700\":\"BELMONTE\",\"701\":\"EL BOSQUE\",\"702\":\"BAYONA\",\"703\":\"CENTRAL CASTILLA 1\",\"704\":\"COCONUCO\",\"705\":\"FUTURA - CASA ELECTRICA\",\"706\":\"MAYAGUEZ 1\",\"707\":\"BETANIA\",\"708\":\"CHIVOR\",\"709\":\"INGENIO PROVIDENCIA 2\",\"710\":\"INGENIO SAN CARLOS 1\",\"711\":\"NIMA II\",\"712\":\"CALDERAS\",\"713\":\"CARLOS LLERAS\",\"714\":\"CALIMA\",\"715\":\"AUTOG CEMENTOS DEL NARE\",\"716\":\"CAMPESTRE (EPM)\",\"717\":\"COELLO\",\"718\":\"CAMPESTRE (CALARCA)\",\"719\":\"CHARQUITO\",\"720\":\"CARACOLI\",\"721\":\"CASCADA\",\"722\":\"CARTAGENA 1\",\"723\":\"CARTAGENA 2\",\"724\":\"CARTAGENA 3\",\"725\":\"CUCUANA\",\"726\":\"CURRUCUCUES\",\"727\":\"DARIO VALENCIA SAMPER\",\"728\":\"EL PASO\",\"729\":\"ESMERALDA\",\"730\":\"FLORIDA\",\"731\":\"CARUQUIA\",\"732\":\"GUACAICA\",\"733\":\"GECELCA 32\",\"734\":\"GECELCA 3\",\"735\":\"GUANAQUITAS\",\"736\":\"GUATAPE\",\"737\":\"GUATRON\",\"738\":\"GUAVIO\",\"739\":\"GUAYEPO\",\"740\":\"ESCUELA DE MINAS\",\"741\":\"MIEL I\",\"742\":\"HIDROMONTA\\u00d1ITAS\",\"743\":\"LA HERRADURA\",\"744\":\"INCAUCA 1\",\"745\":\"INSULA\",\"746\":\"INTERMEDIA\",\"747\":\"INZA\",\"748\":\"IQUIRA I\",\"749\":\"IQUIRA II\",\"750\":\"INGENIO RISARALDA 1\",\"751\":\"JAGUAS\",\"752\":\"NUEVO LIBARE\",\"753\":\"LA CASCADA (ANTIOQUIA)\",\"754\":\"EL LIMONAR\",\"755\":\"RIO PALO\",\"756\":\"LA TASAJERA\",\"757\":\"LA MATA\",\"758\":\"MIROLINDO\",\"759\":\"MUNICIPAL\",\"760\":\"MONDOMO\",\"761\":\"MANANTIALES\",\"762\":\"AMOYA LA ESPERANZA\",\"763\":\"MERILECTRICA 1\",\"764\":\"LA NAVETA\",\"765\":\"NIMA\",\"766\":\"NIQUIA\",\"767\":\"NUTIBARA\",\"768\":\"OVEJAS\",\"769\":\"ITUANGO\",\"770\":\"PAGUA\",\"771\":\"INGENIO PICHICHI 1\",\"772\":\"PAJARITO\",\"773\":\"PALMAS SAN GIL\",\"774\":\"URRAO\",\"775\":\"PLAYAS\",\"776\":\"REMEDIOS\",\"777\":\"COGENERADOR PROENCA\",\"778\":\"PAIPA 1\",\"779\":\"PAIPA 2\",\"780\":\"PAIPA 3\",\"781\":\"PAIPA 4\",\"782\":\"PAPELES NACIONALES\",\"783\":\"PORCE II\",\"784\":\"PORCE III\",\"785\":\"PRADO IV\",\"786\":\"PRADO\",\"787\":\"PROELECTRICA 1\",\"788\":\"PROELECTRICA 2\",\"789\":\"PROVIDENCIA\",\"790\":\"PASTALES\",\"791\":\"LA PITA\",\"792\":\"PATICO - LA CABRERA\",\"793\":\"PUENTE GUILLERMO\",\"794\":\"FUTURA - PTAR 1\",\"795\":\"EL QUIMBO\",\"796\":\"RIO BOBO\",\"797\":\"RIO RECIO\",\"798\":\"RIO CALI\",\"799\":\"RIO FRIO I\",\"800\":\"RIO FRIO 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CUY\",\"492\":\"AGPE SUBASTAR SAHAGUN\",\"493\":\"AGPE CESAR JULIO HERNANDEZ\",\"494\":\"AGPE INDUSTRIAS NEGLE II\",\"495\":\"AGPE FUNDACION  OFTALMOLOGICA\",\"496\":\"AGPE CC LA FLORIDA II\",\"497\":\"AGPE RAMON GIRALDO GONZALEZ\",\"498\":\"AGPE MAURICIO VERGARA FRANCO\",\"499\":\"AUTOG BIOS CONTEGRAL CARTAGO\",\"500\":\"AGPE PARROQUIA ESPIRITU SANTO\",\"501\":\"AGPE RODOLFO ANTONIO ONATE\",\"502\":\"AUTOG BIOS CONTEGRAL NEIVA\",\"503\":\"AGPE GRUPO SAN JORGE\",\"504\":\"AUTOG EL COPEY\",\"505\":\"AGPE COLGATE PALMOLIVE PALMIRA\",\"506\":\"AGPE OCCICAUCHO\",\"507\":\"AGPE UNIPLAST SAS\",\"508\":\"AGPE SANTIAGO ARANGO\",\"509\":\"AGPE PRIMAX COLOMBIA FACATATIVA\",\"510\":\"PARQUE SOLAR HONDA II\",\"511\":\"JEQUES\",\"512\":\"CELSIA SOLAR BUGALAGRANDE\",\"513\":\"AGPE COLEGIO PARROQUIAL PABLO VI\",\"514\":\"AGPE CASA EPISCOPAL\",\"515\":\"AGPE SEMINARIO DIOCESANO JUAN PABLO II\",\"516\":\"AGPE AGROZ\",\"517\":\"AGPE LA SELVA\",\"518\":\"AGPE AMERICANA DE CURTIDOS\",\"519\":\"AGPE CABANA 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SAS\",\"546\":\"AGPE GRICOAT COLOMBIA I\",\"547\":\"AGPE TSM PROJECT\",\"548\":\"AGPE FELIX TORRES\",\"549\":\"AGPE FARMATODO LIMONAR\",\"550\":\"AGPE PLEX CORPORATIVO PROPIEDAD HORIZONTAL\",\"551\":\"AGPE BANCO BOGOTA SAN NICOLAS\",\"552\":\"AGPE HUGO ALEJANDRO HERRERA\",\"553\":\"AGPE CLINIDOTACIONES SAS\",\"554\":\"AGPE LA CASA DEL DEPORTE\",\"555\":\"AGPE ERAZO MARTINEZ ASOCIADOS\",\"556\":\"AGPE VINALE S EN C\",\"557\":\"AGPE ANDRES RODRIGO JARAMILLO DURANGO\",\"558\":\"AGPE SUB LIBERTADOR\",\"559\":\"AGPE  ALIMENTOS NARINO MC SAS\",\"560\":\"AGPE PROAGR19\",\"561\":\"AGPE EDS LA PAZ\",\"562\":\"AGPE JORGE ARMANDO SANCHEZ MEJIA\",\"563\":\"AGPE GRUPO FIRENZE SAS LOC 1\",\"564\":\"AGPE AUTOTECNICA COLOMBIANA\",\"565\":\"AGPE INVERSIONES SANTOS HR SAS\",\"566\":\"AGPE ASOCIACION DE MUNICIPIOS DEL SINU SABANA\",\"567\":\"AGPE HERNAN DARIO GONZALEZ\",\"568\":\"AGPE MARIA MERCES GARCIA BURGOS\",\"569\":\"AGPE MELISSA ANDREA GUERRA LOPEZ\",\"570\":\"AGPE SPATARO NAPOLI\",\"571\":\"GD 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ACRILAN\",\"623\":\"AGPE HOTEL EL PASO MONTERIANO\",\"624\":\"AGPE JERONIMO MARTINS COLOMBIA SAS\",\"625\":\"AGPE IBC\",\"626\":\"AGPE WILLIAM ENCINALES\",\"627\":\"AUTOG SOLAR PALMIRA II BERRY\",\"628\":\"AGPE MAKONDO\",\"629\":\"AGPE TEUCALI FLOWERS SA\",\"630\":\"BSB 501\",\"631\":\"BSB 500\",\"632\":\"BSB 502\",\"633\":\"CENTRO SOLAR\",\"634\":\"BUENAVISTA\",\"635\":\"AGPE BERNARDO JOSE REVUELTAS GONZALEZ\",\"636\":\"AUTOG BIOS FINCA BUGA\",\"637\":\"GD ERCO SALDANA I\",\"638\":\"GD ERCO SALDANA II\",\"639\":\"AGPE INERSIONES EJJ SAS\",\"640\":\"AUTOG BIODIANA 1\",\"641\":\"MINIGRANJA LA PAZ VERSO\",\"642\":\"CONDOR\",\"643\":\"AUTOG BIOS CIENAGA ORO\",\"644\":\"AGPE INVERSIONES RIPAS SAS\",\"645\":\"AGPE CEDITITAN\",\"646\":\"AGPE AIDA PIEDAD RAMOS ANAYA\",\"647\":\"AGPE CASA EL UBERRIMO\",\"648\":\"AGPE DISTRIBUIDORA DE BANANOS OCHOA SEDE I\",\"649\":\"GD BOCAS DEL PALO\",\"650\":\"GD FINCA ISABEL LOPEZ\",\"651\":\"AGPE MANUFACTURAS AF SAS\",\"652\":\"AGPE PARROQUIA NUESTRA 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TECNOACEROS SAS\",\"680\":\"AGPE ANA CAROLINA NAVARRO\",\"681\":\"AGPE NASELA SAS\",\"682\":\"AGPE CPANAME\",\"683\":\"AGPE FAMJ1\",\"684\":\"AGPE LOS POTRILLOS RESTAURANTE BAR\",\"685\":\"LA CASCADA ( ABEJORRAL)\",\"686\":\"AGUA FRESCA\",\"687\":\"ALBAN\",\"688\":\"ALTO TULUA\",\"689\":\"AMAIME\",\"690\":\"AMALFI\",\"691\":\"AMERICA\",\"692\":\"FUTURA - PARQUE ALPHA\",\"693\":\"FUTURA - APOTOLORRU\",\"694\":\"AUTOG ARGOS CARTAGENA 1\",\"695\":\"ASNAZU\",\"696\":\"AUTOG AYURA\",\"697\":\"BARROSO\",\"698\":\"FUTURA - PARQUE BETA\",\"699\":\"BELLO\",\"700\":\"BELMONTE\",\"701\":\"EL BOSQUE\",\"702\":\"BAYONA\",\"703\":\"CENTRAL CASTILLA 1\",\"704\":\"COCONUCO\",\"705\":\"FUTURA - CASA ELECTRICA\",\"706\":\"MAYAGUEZ 1\",\"707\":\"BETANIA\",\"708\":\"CHIVOR\",\"709\":\"INGENIO PROVIDENCIA 2\",\"710\":\"INGENIO SAN CARLOS 1\",\"711\":\"NIMA II\",\"712\":\"CALDERAS\",\"713\":\"CARLOS LLERAS\",\"714\":\"CALIMA\",\"715\":\"AUTOG CEMENTOS DEL NARE\",\"716\":\"CAMPESTRE (EPM)\",\"717\":\"COELLO\",\"718\":\"CAMPESTRE (CALARCA)\",\"719\":\"CHARQUITO\",\"720\":\"CARACOLI\",\"721\":\"CASCADA\",\"722\":\"CARTAGENA 1\",\"723\":\"CARTAGENA 2\",\"724\":\"CARTAGENA 3\",\"725\":\"CUCUANA\",\"726\":\"CURRUCUCUES\",\"727\":\"DARIO VALENCIA SAMPER\",\"728\":\"EL PASO\",\"729\":\"ESMERALDA\",\"730\":\"FLORIDA\",\"731\":\"CARUQUIA\",\"732\":\"GUACAICA\",\"733\":\"GECELCA 32\",\"734\":\"GECELCA 3\",\"735\":\"GUANAQUITAS\",\"736\":\"GUATAPE\",\"737\":\"GUATRON\",\"738\":\"GUAVIO\",\"739\":\"GUAYEPO\",\"740\":\"ESCUELA DE MINAS\",\"741\":\"MIEL I\",\"742\":\"HIDROMONTA\\u00d1ITAS\",\"743\":\"LA HERRADURA\",\"744\":\"INCAUCA 1\",\"745\":\"INSULA\",\"746\":\"INTERMEDIA\",\"747\":\"INZA\",\"748\":\"IQUIRA I\",\"749\":\"IQUIRA II\",\"750\":\"INGENIO RISARALDA 1\",\"751\":\"JAGUAS\",\"752\":\"NUEVO LIBARE\",\"753\":\"LA CASCADA (ANTIOQUIA)\",\"754\":\"EL LIMONAR\",\"755\":\"RIO PALO\",\"756\":\"LA TASAJERA\",\"757\":\"LA MATA\",\"758\":\"MIROLINDO\",\"759\":\"MUNICIPAL\",\"760\":\"MONDOMO\",\"761\":\"MANANTIALES\",\"762\":\"AMOYA LA ESPERANZA\",\"763\":\"MERILECTRICA 1\",\"764\":\"LA NAVETA\",\"765\":\"NIMA\",\"766\":\"NIQUIA\",\"767\":\"NUTIBARA\",\"768\":\"OVEJAS\",\"769\":\"ITUANGO\",\"770\":\"PAGUA\",\"771\":\"INGENIO PICHICHI 1\",\"772\":\"PAJARITO\",\"773\":\"PALMAS SAN GIL\",\"774\":\"URRAO\",\"775\":\"PLAYAS\",\"776\":\"REMEDIOS\",\"777\":\"COGENERADOR PROENCA\",\"778\":\"PAIPA 1\",\"779\":\"PAIPA 2\",\"780\":\"PAIPA 3\",\"781\":\"PAIPA 4\",\"782\":\"PAPELES NACIONALES\",\"783\":\"PORCE II\",\"784\":\"PORCE III\",\"785\":\"PRADO IV\",\"786\":\"PRADO\",\"787\":\"PROELECTRICA 1\",\"788\":\"PROELECTRICA 2\",\"789\":\"PROVIDENCIA\",\"790\":\"PASTALES\",\"791\":\"LA PITA\",\"792\":\"PATICO - LA CABRERA\",\"793\":\"PUENTE GUILLERMO\",\"794\":\"FUTURA - PTAR 1\",\"795\":\"EL QUIMBO\",\"796\":\"RIO BOBO\",\"797\":\"RIO RECIO\",\"798\":\"RIO CALI\",\"799\":\"RIO FRIO I\",\"800\":\"RIO FRIO 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23:00:00.0\",\n      \"dato\": 0.0318,\n      \"fuente\": \"Hidroeléctrica\",\n      \"planta\": \"Ventanas\",\n      \"grupo\": \"Otras Hidro\"\n    }\n  ],\n  \"_links\": {\n    \"next\": null,\n    \"previous\": null,\n    \"self\": \"https://apps.grupoice.com/CenceWeb/data/sen/json/EnergiaHorariaFuentePlanta?anno=2021&mes=07&dia=16\"\n  },\n  \"fuente\": \"Centro Nacional de Control de Energía. Instituto Costarricense de Electricidad - CENCE.\\r\\nEl CENCE no se hace responsable de ningún error u omisión, pérdidas o daños que resulten de la utilización de la información o material contenidos en este sitio.\\r\\nDeclaración de Privacidad © 2020 ICE Todos los Derechos Reservados.\",\n  \"nombreConsulta\": \"EnergiaHorariaFuentePlanta\"\n}\n"
  },
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Instituto Costarricense de Electricidad - CENCE.\\r\\nEl CENCE no se hace responsable de ningún error u omisión, pérdidas o daños que resulten de la utilización de la información o material contenidos en este sitio.\\r\\nDeclaración de Privacidad © 2020 ICE Todos los Derechos Reservados.\",\n  \"nombreConsulta\": \"EnergiaHorariaFuentePlanta\"\n}\n"
  },
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    "content": "<!DOCTYPE html>\n<html dir=\"ltr\" lang=\"el\" prefix=\"og: https://ogp.me/ns#\">\n\n<head>\n    <meta charset=\"UTF-8\" />\n\n    <title>Αρχείο Ημερήσιας Παραγωγής Ηλεκτρικού Συστήματος (MW) | ΔΣΜΚ</title>\n</head>\n\n<body>\n    <div id=\"page-container\">\n        <div id=\"et-main-area\">\n            <div id=\"main-content\">\n                <div class=\"container\">\n                    <div id=\"content-area\" class=\"clearfix\">\n                        <article id=\"post-568\" class=\"post-568 page type-page status-publish hentry\">\n                            <h1 class=\"entry-title main_title\">Αρχείο Ημερήσιας Παραγωγής Ηλεκτρικού Συστήματος (MW)\n                            </h1>\n                            <div class=\"entry-content\">\n                                <div class=\"dis20\"></div>\n                                <div class=\"row\">\n                                    <div class=\"col-md-12\">\n                                        <p>Επιλέξτε Διάρκεια Παρουσίασης για τις τελευταίες ημέρες</p>\n                                    </div>\n                                </div>\n                                <table id=\"production_graph_static_data\" class=\"display responsive nowrap\"\n                                    style=\"width:100%\">\n                                    <thead>\n                                        <th style=\"background-color: #C9CFE1; width:60%\">Περιγραφή</th>\n                                        <th style=\"background-color: #C9CFE1; width:60%\">Τιμή (MW)</th>\n                                    </thead>\n                                    <tr>\n                                        <td>Συνολική Διαθέσιμη Συμβατική Ικανότητα Παραγωγής</td>\n                                        <td>\n                                            18/03/2024 00:00-18/03/2024 11:45 <strong>&#8594;</strong>\n                                            1108<br>18/03/2024 11:45-18/03/2024 23:45 <strong>&#8594;</strong> 1095<br>\n                                        </td>\n                                    </tr>\n                                </table>\n                                <div class=\"dis20\"></div>\n                                <table id=\"production_graph_data\"\n                                    class=\"display responsive nowrap exportGraphData hidden\" style=\"width:100%\">\n                                    <thead>\n                                        <tr>\n                                            <th>Timestamp</th>\n                                            <th>Συνολική Διαθέσιμη Συμβατική Ικανότητα Παραγωγής</th>\n                                            <th>Αιολική Παραγωγή στο ΣΜ</th>\n                                            <th>Εκτίμηση Διεσπαρμένης Παραγωγής</th>\n                                            <th>Συνολική Ζήτηση</th>\n                                            <th>Συμβατική Παραγωγή στο ΣΜ</th>\n                                        </tr>\n                                    </thead>\n                                    <tbody>\n                                        <tr>\n                                            <td>2024-03-18 00:00:00</td>\n                                            <td>1108</td>\n                                            <td>36</td>\n                                            <td>10</td>\n                                            <td>457</td>\n                                            <td>411</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 00:15:00</td>\n                                            <td>1108</td>\n                                            <td>29</td>\n                                            <td>10</td>\n                                            <td>444</td>\n                                            <td>404</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 00:30:00</td>\n                                            <td>1108</td>\n                                            <td>28</td>\n                                            <td>10</td>\n                                            <td>432</td>\n                                            <td>394</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 00:45:00</td>\n                                            <td>1108</td>\n                                            <td>31</td>\n                                            <td>10</td>\n                                            <td>422</td>\n                                            <td>380</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 01:00:00</td>\n                                            <td>1108</td>\n                                            <td>27</td>\n                                            <td>10</td>\n                                            <td>412</td>\n                                            <td>374</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 01:15:00</td>\n                                            <td>1108</td>\n                                            <td>32</td>\n                                            <td>10</td>\n                                            <td>404</td>\n                                            <td>362</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 01:30:00</td>\n                                            <td>1108</td>\n                                            <td>35</td>\n                                            <td>10</td>\n                                            <td>397</td>\n                                            <td>351</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 01:45:00</td>\n                                            <td>1108</td>\n                                            <td>47</td>\n                                            <td>10</td>\n                                            <td>389</td>\n                                            <td>332</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 02:00:00</td>\n                                            <td>1108</td>\n                                            <td>46</td>\n                                            <td>10</td>\n                                            <td>384</td>\n                                            <td>328</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 02:15:00</td>\n                                            <td>1108</td>\n                                            <td>60</td>\n                                            <td>10</td>\n                                            <td>379</td>\n                                            <td>309</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 02:30:00</td>\n                                            <td>1108</td>\n                                            <td>55</td>\n                                            <td>10</td>\n                                            <td>375</td>\n                                            <td>310</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 02:45:00</td>\n                                            <td>1108</td>\n                                            <td>48</td>\n                                            <td>10</td>\n                                            <td>371</td>\n                                            <td>313</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 03:00:00</td>\n                                            <td>1108</td>\n                                            <td>34</td>\n                                            <td>10</td>\n                                            <td>371</td>\n                                            <td>327</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 03:15:00</td>\n                                            <td>1108</td>\n                                            <td>33</td>\n                                            <td>10</td>\n                                            <td>370</td>\n                                            <td>327</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 03:30:00</td>\n                                            <td>1108</td>\n                                            <td>39</td>\n                                            <td>10</td>\n                                            <td>370</td>\n                                            <td>320</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 03:45:00</td>\n                                            <td>1108</td>\n                                            <td>43</td>\n                                            <td>10</td>\n                                            <td>368</td>\n                                            <td>315</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 04:00:00</td>\n                                            <td>1108</td>\n                                            <td>37</td>\n                                            <td>10</td>\n                                            <td>367</td>\n                                            <td>320</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 04:15:00</td>\n                                            <td>1108</td>\n                                            <td>41</td>\n                                            <td>10</td>\n                                            <td>370</td>\n                                            <td>319</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 04:30:00</td>\n                                            <td>1108</td>\n                                            <td>45</td>\n                                            <td>10</td>\n                                            <td>371</td>\n                                            <td>316</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 04:45:00</td>\n                                            <td>1108</td>\n                                            <td>37</td>\n                                            <td>10</td>\n                                            <td>373</td>\n                                            <td>326</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 05:00:00</td>\n                                            <td>1108</td>\n                                            <td>31</td>\n                                            <td>10</td>\n                                            <td>374</td>\n                                            <td>333</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 05:15:00</td>\n                                            <td>1108</td>\n                                            <td>18</td>\n                                            <td>10</td>\n                                            <td>382</td>\n                                            <td>354</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 05:30:00</td>\n                                            <td>1108</td>\n                                            <td>15</td>\n                                            <td>10</td>\n                                            <td>386</td>\n                                            <td>361</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 05:45:00</td>\n                                            <td>1108</td>\n                                            <td>16</td>\n                                            <td>10</td>\n                                            <td>387</td>\n                                            <td>361</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 06:00:00</td>\n                                            <td>1108</td>\n                                            <td>31</td>\n                                            <td>10</td>\n                                            <td>386</td>\n                                            <td>345</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 06:15:00</td>\n                                            <td>1108</td>\n                                            <td>31</td>\n                                            <td>10</td>\n                                            <td>395</td>\n                                            <td>354</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 06:30:00</td>\n                                            <td>1108</td>\n                                            <td>31</td>\n                                            <td>15</td>\n                                            <td>401</td>\n                                            <td>355</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 06:45:00</td>\n                                            <td>1108</td>\n                                            <td>36</td>\n                                            <td>29</td>\n                                            <td>414</td>\n                                            <td>350</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 07:00:00</td>\n                                            <td>1108</td>\n                                            <td>42</td>\n                                            <td>41</td>\n                                            <td>426</td>\n                                            <td>343</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 07:15:00</td>\n                                            <td>1108</td>\n                                            <td>38</td>\n                                            <td>55</td>\n                                            <td>439</td>\n                                            <td>346</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 07:30:00</td>\n                                            <td>1108</td>\n                                            <td>41</td>\n                                            <td>70</td>\n                                            <td>442</td>\n                                            <td>332</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 07:45:00</td>\n                                            <td>1108</td>\n                                            <td>38</td>\n                                            <td>82</td>\n                                            <td>447</td>\n                                            <td>326</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 08:00:00</td>\n                                            <td>1108</td>\n                                            <td>35</td>\n                                            <td>110</td>\n                                            <td>459</td>\n                                            <td>314</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 08:15:00</td>\n                                            <td>1108</td>\n                                            <td>29</td>\n                                            <td>169</td>\n                                            <td>477</td>\n                                            <td>279</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 08:30:00</td>\n                                            <td>1108</td>\n                                            <td>23</td>\n                                            <td>202</td>\n                                            <td>473</td>\n                                            <td>249</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 08:45:00</td>\n                                            <td>1108</td>\n                                            <td>15</td>\n                                            <td>206</td>\n                                            <td>478</td>\n                                            <td>258</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 09:00:00</td>\n                                            <td>1108</td>\n                                            <td>14</td>\n                                            <td>220</td>\n                                            <td>485</td>\n                                            <td>251</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 09:15:00</td>\n                                            <td>1108</td>\n                                            <td>15</td>\n                                            <td>241</td>\n                                            <td>503</td>\n                                            <td>248</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 09:30:00</td>\n                                            <td>1108</td>\n                                            <td>19</td>\n                                            <td>242</td>\n                                            <td>515</td>\n                                            <td>254</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 09:45:00</td>\n                                            <td>1108</td>\n                                            <td>16</td>\n                                            <td>259</td>\n                                            <td>529</td>\n                                            <td>254</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 10:00:00</td>\n                                            <td>1108</td>\n                                            <td>14</td>\n                                            <td>255</td>\n                                            <td>517</td>\n                                            <td>249</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 10:15:00</td>\n                                            <td>1108</td>\n                                            <td>12</td>\n                                            <td>257</td>\n                                            <td>506</td>\n                                            <td>236</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 10:30:00</td>\n                                            <td>1108</td>\n                                            <td>11</td>\n                                            <td>261</td>\n                                            <td>507</td>\n                                            <td>236</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 10:45:00</td>\n                                            <td>1108</td>\n                                            <td>12</td>\n                                            <td>275</td>\n                                            <td>520</td>\n                                            <td>234</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 11:00:00</td>\n                                            <td>1108</td>\n                                            <td>15</td>\n                                            <td>277</td>\n                                            <td>522</td>\n                                            <td>230</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 11:15:00</td>\n                                            <td>1108</td>\n                                            <td>14</td>\n                                            <td>286</td>\n                                            <td>527</td>\n                                            <td>227</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 11:30:00</td>\n                                            <td>1108</td>\n                                            <td>13</td>\n                                            <td>254</td>\n                                            <td>498</td>\n                                            <td>230</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 11:45:00</td>\n                                            <td>1095</td>\n                                            <td>15</td>\n                                            <td>239</td>\n                                            <td>483</td>\n                                            <td>229</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 12:00:00</td>\n                                            <td>1095</td>\n                                            <td>12</td>\n                                            <td>241</td>\n                                            <td>475</td>\n                                            <td>221</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 12:15:00</td>\n                                            <td>1095</td>\n                                            <td>15</td>\n                                            <td>241</td>\n                                            <td>480</td>\n                                            <td>225</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 12:30:00</td>\n                                            <td>1095</td>\n                                            <td>8</td>\n                                            <td>219</td>\n                                            <td>453</td>\n                                            <td>226</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 12:45:00</td>\n                                            <td>1095</td>\n                                            <td>7</td>\n                                            <td>214</td>\n                                            <td>455</td>\n                                            <td>234</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 13:00:00</td>\n                                            <td>1095</td>\n                                            <td>10</td>\n                                            <td>217</td>\n                                            <td>460</td>\n                                            <td>233</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 13:15:00</td>\n                                            <td>1095</td>\n                                            <td>12</td>\n                                            <td>243</td>\n                                            <td>485</td>\n                                            <td>231</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 13:30:00</td>\n                                            <td>1095</td>\n                                            <td>11</td>\n                                            <td>207</td>\n                                            <td>445</td>\n                                            <td>227</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 13:45:00</td>\n                                            <td>1095</td>\n                                            <td>10</td>\n                                            <td>169</td>\n                                            <td>410</td>\n                                            <td>231</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 14:00:00</td>\n                                            <td>1095</td>\n                                            <td>15</td>\n                                            <td>161</td>\n                                            <td>409</td>\n                                            <td>233</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 14:15:00</td>\n                                            <td>1095</td>\n                                            <td>18</td>\n                                            <td>161</td>\n                                            <td>414</td>\n                                            <td>235</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 14:30:00</td>\n                                            <td>1095</td>\n                                            <td>18</td>\n                                            <td>172</td>\n                                            <td>419</td>\n                                            <td>230</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 14:45:00</td>\n                                            <td>1095</td>\n                                            <td>16</td>\n                                            <td>162</td>\n                                            <td>421</td>\n                                            <td>242</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 15:00:00</td>\n                                            <td>1095</td>\n                                            <td>16</td>\n                                            <td>125</td>\n                                            <td>419</td>\n                                            <td>277</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 15:15:00</td>\n                                            <td>1095</td>\n                                            <td>16</td>\n                                            <td>107</td>\n                                            <td>429</td>\n                                            <td>305</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 15:30:00</td>\n                                            <td>1095</td>\n                                            <td>18</td>\n                                            <td>99</td>\n                                            <td>438</td>\n                                            <td>321</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 15:45:00</td>\n                                            <td>1095</td>\n                                            <td>24</td>\n                                            <td>98</td>\n                                            <td>453</td>\n                                            <td>331</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 16:00:00</td>\n                                            <td>1095</td>\n                                            <td>23</td>\n                                            <td>88</td>\n                                            <td>463</td>\n                                            <td>352</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 16:15:00</td>\n                                            <td>1095</td>\n                                            <td>16</td>\n                                            <td>79</td>\n                                            <td>483</td>\n                                            <td>387</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 16:30:00</td>\n                                            <td>1095</td>\n                                            <td>22</td>\n                                            <td>61</td>\n                                            <td>492</td>\n                                            <td>409</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 16:45:00</td>\n                                            <td>1095</td>\n                                            <td>27</td>\n                                            <td>44</td>\n                                            <td>505</td>\n                                            <td>434</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 17:00:00</td>\n                                            <td>1095</td>\n                                            <td>27</td>\n                                            <td>33</td>\n                                            <td>519</td>\n                                            <td>460</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 17:15:00</td>\n                                            <td>1095</td>\n                                            <td>28</td>\n                                            <td>28</td>\n                                            <td>539</td>\n                                            <td>483</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 17:30:00</td>\n                                            <td>1095</td>\n                                            <td>28</td>\n                                            <td>19</td>\n                                            <td>550</td>\n                                            <td>504</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 17:45:00</td>\n                                            <td>1095</td>\n                                            <td>20</td>\n                                            <td>10</td>\n                                            <td>564</td>\n                                            <td>534</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 18:00:00</td>\n                                            <td>1095</td>\n                                            <td>18</td>\n                                            <td>10</td>\n                                            <td>586</td>\n                                            <td>558</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 18:15:00</td>\n                                            <td>1095</td>\n                                            <td>18</td>\n                                            <td>10</td>\n                                            <td>610</td>\n                                            <td>582</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 18:30:00</td>\n                                            <td>1095</td>\n                                            <td>20</td>\n                                            <td>10</td>\n                                            <td>634</td>\n                                            <td>604</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 18:45:00</td>\n                                            <td>1095</td>\n                                            <td>20</td>\n                                            <td>10</td>\n                                            <td>646</td>\n                                            <td>616</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 19:00:00</td>\n                                            <td>1095</td>\n                                            <td>17</td>\n                                            <td>10</td>\n                                            <td>655</td>\n                                            <td>628</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 19:15:00</td>\n                                            <td>1095</td>\n                                            <td>14</td>\n                                            <td>10</td>\n                                            <td>661</td>\n                                            <td>637</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 19:30:00</td>\n                                            <td>1095</td>\n                                            <td>14</td>\n                                            <td>10</td>\n                                            <td>661</td>\n                                            <td>637</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 19:45:00</td>\n                                            <td>1095</td>\n                                            <td>18</td>\n                                            <td>10</td>\n                                            <td>656</td>\n                                            <td>627</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 20:00:00</td>\n                                            <td>1095</td>\n                                            <td>23</td>\n                                            <td>10</td>\n                                            <td>652</td>\n                                            <td>619</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 20:15:00</td>\n                                            <td>1095</td>\n                                            <td>27</td>\n                                            <td>10</td>\n                                            <td>644</td>\n                                            <td>608</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 20:30:00</td>\n                                            <td>1095</td>\n                                            <td>27</td>\n                                            <td>10</td>\n                                            <td>636</td>\n                                            <td>598</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 20:45:00</td>\n                                            <td>1095</td>\n                                            <td>34</td>\n                                            <td>10</td>\n                                            <td>624</td>\n                                            <td>580</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 21:00:00</td>\n                                            <td>1095</td>\n                                            <td>28</td>\n                                            <td>10</td>\n                                            <td>614</td>\n                                            <td>576</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 21:15:00</td>\n                                            <td>1095</td>\n                                            <td>20</td>\n                                            <td>10</td>\n                                            <td>600</td>\n                                            <td>570</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 21:30:00</td>\n                                            <td>1095</td>\n                                            <td>21</td>\n                                            <td>10</td>\n                                            <td>585</td>\n                                            <td>554</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 21:45:00</td>\n                                            <td>1095</td>\n                                            <td>28</td>\n                                            <td>10</td>\n                                            <td>569</td>\n                                            <td>532</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 22:00:00</td>\n                                            <td>1095</td>\n                                            <td>23</td>\n                                            <td>10</td>\n                                            <td>554</td>\n                                            <td>521</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 22:15:00</td>\n                                            <td>1095</td>\n                                            <td>19</td>\n                                            <td>10</td>\n                                            <td>536</td>\n                                            <td>507</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 22:30:00</td>\n                                            <td>1095</td>\n                                            <td>21</td>\n                                            <td>10</td>\n                                            <td>520</td>\n                                            <td>489</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 22:45:00</td>\n                                            <td>1095</td>\n                                            <td>30</td>\n                                            <td>10</td>\n                                            <td>502</td>\n                                            <td>462</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 23:00:00</td>\n                                            <td>1095</td>\n                                            <td>40</td>\n                                            <td>10</td>\n                                            <td>484</td>\n                                            <td>434</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 23:15:00</td>\n                                            <td>1095</td>\n                                            <td>41</td>\n                                            <td>10</td>\n                                            <td>470</td>\n                                            <td>418</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 23:30:00</td>\n                                            <td>1095</td>\n                                            <td>42</td>\n                                            <td>10</td>\n                                            <td>456</td>\n                                            <td>404</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-03-18 23:45:00</td>\n                                            <td>1095</td>\n                                            <td>33</td>\n                                            <td>10</td>\n                                            <td>446</td>\n                                            <td>402</td>\n                                        </tr>\n                                    </tbody>\n                                </table>\n                                <div class=\"dis20\"></div>\n                            </div> <!-- .entry-content -->\n                        </article> <!-- .et_pb_post -->\n                    </div> <!-- #content-area -->\n                </div> <!-- .container -->\n            </div> <!-- #main-content -->\n        </div> <!-- #et-main-area -->\n    </div> <!-- #page-container -->\n</body>\n\n</html>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/CY/response_realtime_20240401.html",
    "content": "<!DOCTYPE html>\n<html dir=\"ltr\" lang=\"el\" prefix=\"og: https://ogp.me/ns#\">\n\n<head>\n    <meta charset=\"UTF-8\" />\n\n    <title>Ημερήσια Παραγωγή Ηλεκτρικού Συστήματος | ΔΣΜΚ</title>\n</head>\n\n<body>\n    <div id=\"page-container\">\n        <div id=\"et-main-area\">\n            <div id=\"main-content\">\n                <div class=\"container\">\n                    <div id=\"content-area\" class=\"clearfix\">\n                        <article id=\"post-551\" class=\"post-551 page type-page status-publish hentry\">\n                            <h1 class=\"entry-title main_title\">Ημερήσια Παραγωγή Ηλεκτρικού Συστήματος</h1>\n                            <div class=\"entry-content\">\n                                <div class=\"dis20\"></div>\n                                <div class=\"row\">\n                                    <div class=\"col-md-12\">\n                                        <div class=\"text-center\">\n                                            <strong>\n                                                Δευτέρα, 1 Απριλίου 2024<br> </strong>\n                                        </div>\n                                    </div>\n                                </div>\n                                <table id=\"production_graph_static_data1\" class=\"display responsive nowrap\"\n                                    style=\"width:100%\">\n                                    <thead>\n                                        <th style=\"background-color: #C9CFE1; width:60%\">Περιγραφή</th>\n                                        <th style=\"background-color: #C9CFE1; width:60%\">Τιμή (MW)</th>\n                                    </thead>\n                                    <tr>\n                                        <td>Συνολική Διαθέσιμη Συμβατική Ικανότητα Παραγωγής</td>\n                                        <td>\n                                            01/04/2024 00:00-01/04/2024 23:45 <strong>&#8594;</strong> 942<br> </td>\n                                    </tr>\n                                </table>\n                                <div class=\"dis20\"></div>\n                                <p style=\"text-align: center;\"><strong>ΕΓΚΑΤΕΣΤΗΜΕΝΗ ΙΣΧΥΣ ΑΝΑ ΤΕΧΝΟΛΟΓΙΑ</strong></p>\n                                <table id=\"production_graph_static_data2\" class=\"display responsive nowrap\"\n                                    style=\"width:100%\">\n                                    <thead>\n                                        <th style=\"background-color: #C9CFE1; width:60%\">Περιγραφή</th>\n                                        <th style=\"background-color: #C9CFE1; width:60%\">Τιμή (MW)</th>\n                                    </thead>\n                                    <tr>\n                                        <td>Συμβατική Εγκατεστημένη Ισχύς</td>\n                                        <td>1478</td>\n                                    </tr>\n                                    <tr>\n                                        <td>Αιολική Εγκατεστημένη Ισχύς</td>\n                                        <td>155.1</td>\n                                    </tr>\n                                    <tr>\n                                        <td>Φωτοβολταϊκή Εγκατεστημένη Ισχύς</td>\n                                        <td>674.46</td>\n                                    </tr>\n                                    <tr>\n                                        <td>Εγκατεστημένη Ισχύς Βιομάζας</td>\n                                        <td>12.4</td>\n                                    </tr>\n                                </table>\n                                <div class=\"dis20\"></div>\n                                <table id=\"production_graph_data\"\n                                    class=\"display responsive nowrap exportGraphData hidden\" style=\"width:100%\">\n                                    <thead>\n                                        <tr>\n                                            <th>Timestamp</th>\n                                            <th>Συνολική Διαθέσιμη Συμβατική Ικανότητα Παραγωγής</th>\n                                            <th>Αιολική Παραγωγή στο ΣΜ</th>\n                                            <th>Εκτίμηση Διεσπαρμένης Παραγωγής</th>\n                                            <th>Συνολική Ζήτηση</th>\n                                            <th>Συμβατική Παραγωγή στο ΣΜ</th>\n                                        </tr>\n                                    </thead>\n                                    <tbody>\n                                        <tr>\n                                            <td>2024-04-01 00:00:00</td>\n                                            <td>942</td>\n                                            <td>14</td>\n                                            <td>10</td>\n                                            <td>398</td>\n                                            <td>374</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 00:15:00</td>\n                                            <td>942</td>\n                                            <td>9</td>\n                                            <td>10</td>\n                                            <td>388</td>\n                                            <td>369</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 00:30:00</td>\n                                            <td>942</td>\n                                            <td>8</td>\n                                            <td>10</td>\n                                            <td>382</td>\n                                            <td>364</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 00:45:00</td>\n                                            <td>942</td>\n                                            <td>9</td>\n                                            <td>10</td>\n                                            <td>374</td>\n                                            <td>354</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 01:00:00</td>\n                                            <td>942</td>\n                                            <td>12</td>\n                                            <td>10</td>\n                                            <td>364</td>\n                                            <td>342</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 01:15:00</td>\n                                            <td>942</td>\n                                            <td>15</td>\n                                            <td>10</td>\n                                            <td>359</td>\n                                            <td>334</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 01:30:00</td>\n                                            <td>942</td>\n                                            <td>16</td>\n                                            <td>10</td>\n                                            <td>353</td>\n                                            <td>327</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 01:45:00</td>\n                                            <td>942</td>\n                                            <td>22</td>\n                                            <td>10</td>\n                                            <td>349</td>\n                                            <td>317</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 02:00:00</td>\n                                            <td>942</td>\n                                            <td>25</td>\n                                            <td>10</td>\n                                            <td>345</td>\n                                            <td>310</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 02:15:00</td>\n                                            <td>942</td>\n                                            <td>29</td>\n                                            <td>10</td>\n                                            <td>341</td>\n                                            <td>303</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 02:30:00</td>\n                                            <td>942</td>\n                                            <td>24</td>\n                                            <td>10</td>\n                                            <td>338</td>\n                                            <td>304</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 02:45:00</td>\n                                            <td>942</td>\n                                            <td>21</td>\n                                            <td>10</td>\n                                            <td>335</td>\n                                            <td>304</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 03:00:00</td>\n                                            <td>942</td>\n                                            <td>19</td>\n                                            <td>10</td>\n                                            <td>334</td>\n                                            <td>305</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 03:15:00</td>\n                                            <td>942</td>\n                                            <td>21</td>\n                                            <td>10</td>\n                                            <td>332</td>\n                                            <td>301</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 03:30:00</td>\n                                            <td>942</td>\n                                            <td>19</td>\n                                            <td>10</td>\n                                            <td>330</td>\n                                            <td>301</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 03:45:00</td>\n                                            <td>942</td>\n                                            <td>16</td>\n                                            <td>10</td>\n                                            <td>329</td>\n                                            <td>302</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 04:00:00</td>\n                                            <td>942</td>\n                                            <td>12</td>\n                                            <td>10</td>\n                                            <td>328</td>\n                                            <td>305</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 04:15:00</td>\n                                            <td>942</td>\n                                            <td>12</td>\n                                            <td>10</td>\n                                            <td>329</td>\n                                            <td>308</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 04:30:00</td>\n                                            <td>942</td>\n                                            <td>14</td>\n                                            <td>10</td>\n                                            <td>330</td>\n                                            <td>306</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 04:45:00</td>\n                                            <td>942</td>\n                                            <td>14</td>\n                                            <td>10</td>\n                                            <td>331</td>\n                                            <td>307</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 05:00:00</td>\n                                            <td>942</td>\n                                            <td>15</td>\n                                            <td>10</td>\n                                            <td>332</td>\n                                            <td>306</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 05:15:00</td>\n                                            <td>942</td>\n                                            <td>16</td>\n                                            <td>10</td>\n                                            <td>336</td>\n                                            <td>310</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 05:30:00</td>\n                                            <td>942</td>\n                                            <td>20</td>\n                                            <td>10</td>\n                                            <td>338</td>\n                                            <td>308</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 05:45:00</td>\n                                            <td>942</td>\n                                            <td>20</td>\n                                            <td>10</td>\n                                            <td>341</td>\n                                            <td>310</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 06:00:00</td>\n                                            <td>942</td>\n                                            <td>18</td>\n                                            <td>10</td>\n                                            <td>344</td>\n                                            <td>316</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 06:15:00</td>\n                                            <td>942</td>\n                                            <td>19</td>\n                                            <td>10</td>\n                                            <td>353</td>\n                                            <td>324</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 06:30:00</td>\n                                            <td>942</td>\n                                            <td>20</td>\n                                            <td>10</td>\n                                            <td>350</td>\n                                            <td>319</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 06:45:00</td>\n                                            <td>942</td>\n                                            <td>18</td>\n                                            <td>10</td>\n                                            <td>346</td>\n                                            <td>318</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 07:00:00</td>\n                                            <td>942</td>\n                                            <td>16</td>\n                                            <td>19</td>\n                                            <td>354</td>\n                                            <td>318</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 07:15:00</td>\n                                            <td>942</td>\n                                            <td>11</td>\n                                            <td>31</td>\n                                            <td>362</td>\n                                            <td>319</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 07:30:00</td>\n                                            <td>942</td>\n                                            <td>7</td>\n                                            <td>50</td>\n                                            <td>374</td>\n                                            <td>317</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 07:45:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>76</td>\n                                            <td>382</td>\n                                            <td>301</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 08:00:00</td>\n                                            <td>942</td>\n                                            <td>3</td>\n                                            <td>118</td>\n                                            <td>402</td>\n                                            <td>281</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 08:15:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>150</td>\n                                            <td>414</td>\n                                            <td>260</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 08:30:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>189</td>\n                                            <td>424</td>\n                                            <td>231</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 08:45:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>208</td>\n                                            <td>437</td>\n                                            <td>225</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 09:00:00</td>\n                                            <td>942</td>\n                                            <td>3</td>\n                                            <td>218</td>\n                                            <td>448</td>\n                                            <td>226</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 09:15:00</td>\n                                            <td>942</td>\n                                            <td>3</td>\n                                            <td>226</td>\n                                            <td>456</td>\n                                            <td>227</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 09:30:00</td>\n                                            <td>942</td>\n                                            <td>1</td>\n                                            <td>235</td>\n                                            <td>461</td>\n                                            <td>225</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 09:45:00</td>\n                                            <td>942</td>\n                                            <td>1</td>\n                                            <td>246</td>\n                                            <td>472</td>\n                                            <td>225</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 10:00:00</td>\n                                            <td>942</td>\n                                            <td>2</td>\n                                            <td>250</td>\n                                            <td>477</td>\n                                            <td>226</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 10:15:00</td>\n                                            <td>942</td>\n                                            <td>2</td>\n                                            <td>256</td>\n                                            <td>482</td>\n                                            <td>224</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 10:30:00</td>\n                                            <td>942</td>\n                                            <td>2</td>\n                                            <td>257</td>\n                                            <td>484</td>\n                                            <td>225</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 10:45:00</td>\n                                            <td>942</td>\n                                            <td>1</td>\n                                            <td>260</td>\n                                            <td>488</td>\n                                            <td>227</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 11:00:00</td>\n                                            <td>942</td>\n                                            <td>1</td>\n                                            <td>266</td>\n                                            <td>494</td>\n                                            <td>228</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 11:15:00</td>\n                                            <td>942</td>\n                                            <td>2</td>\n                                            <td>272</td>\n                                            <td>504</td>\n                                            <td>230</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 11:30:00</td>\n                                            <td>942</td>\n                                            <td>2</td>\n                                            <td>279</td>\n                                            <td>514</td>\n                                            <td>233</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 11:45:00</td>\n                                            <td>942</td>\n                                            <td>2</td>\n                                            <td>285</td>\n                                            <td>517</td>\n                                            <td>230</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 12:00:00</td>\n                                            <td>942</td>\n                                            <td>3</td>\n                                            <td>288</td>\n                                            <td>518</td>\n                                            <td>227</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 12:15:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>292</td>\n                                            <td>522</td>\n                                            <td>226</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 12:30:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>293</td>\n                                            <td>522</td>\n                                            <td>225</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 12:45:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>294</td>\n                                            <td>523</td>\n                                            <td>225</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 13:00:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>296</td>\n                                            <td>526</td>\n                                            <td>226</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 13:15:00</td>\n                                            <td>942</td>\n                                            <td>5</td>\n                                            <td>298</td>\n                                            <td>523</td>\n                                            <td>220</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 13:30:00</td>\n                                            <td>942</td>\n                                            <td>6</td>\n                                            <td>294</td>\n                                            <td>516</td>\n                                            <td>216</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 13:45:00</td>\n                                            <td>942</td>\n                                            <td>7</td>\n                                            <td>290</td>\n                                            <td>511</td>\n                                            <td>214</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 14:00:00</td>\n                                            <td>942</td>\n                                            <td>7</td>\n                                            <td>285</td>\n                                            <td>504</td>\n                                            <td>213</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 14:15:00</td>\n                                            <td>942</td>\n                                            <td>5</td>\n                                            <td>278</td>\n                                            <td>500</td>\n                                            <td>217</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 14:30:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>272</td>\n                                            <td>496</td>\n                                            <td>220</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 14:45:00</td>\n                                            <td>942</td>\n                                            <td>4</td>\n                                            <td>264</td>\n                                            <td>492</td>\n                                            <td>223</td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 15:00:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 15:15:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 15:30:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 15:45:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 16:00:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 16:15:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 16:30:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 16:45:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 17:00:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 17:15:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 17:30:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 17:45:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 18:00:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 18:15:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 18:30:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 18:45:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 19:00:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 19:15:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 19:30:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 19:45:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 20:00:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 20:15:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 20:30:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 20:45:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 21:00:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 21:15:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 21:30:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 21:45:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 22:00:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 22:15:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 22:30:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 22:45:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 23:00:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 23:15:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 23:30:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                        <tr>\n                                            <td>2024-04-01 23:45:00</td>\n                                            <td>942</td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                            <td></td>\n                                        </tr>\n                                    </tbody>\n                                </table>\n                            </div> <!-- .entry-content -->\n                        </article> <!-- .et_pb_post -->\n                    </div> <!-- #content-area -->\n                </div> <!-- .container -->\n            </div> <!-- #main-content -->\n        </div> <!-- #et-main-area -->\n    </div> <!-- #page-container -->\n</body>\n\n</html>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/CZ/CrossborderPowerFlows.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?><soap:Envelope xmlns:soap=\"http://www.w3.org/2003/05/soap-envelope\" xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\" xmlns:xsd=\"http://www.w3.org/2001/XMLSchema\"><soap:Body><CrossborderPowerFlowsResponse xmlns=\"https://www.ceps.cz/CepsData/\"><CrossborderPowerFlowsResult><root xmlns=\"https://www.ceps.cz/CepsData/StructuredData/1.0\"><information><name>Cross-border power flows</name><date_from>2025-10-29T18:30:00+01:00</date_from><date_to>2025-10-31T18:30:00+01:00</date_to><version>RT</version><function>AVG</function><aggregation>QH</aggregation></information><series><serie id=\"value1\" name=\"PSE Actual [MW]\" /><serie id=\"value2\" name=\"PSE Planned [MW]\" /><serie id=\"value3\" name=\"SEPS Actual [MW]\" /><serie id=\"value4\" name=\"SEPS Planned [MW]\" /><serie id=\"value5\" name=\"APG Actual [MW]\" /><serie id=\"value6\" name=\"APG Planned [MW]\" /><serie id=\"value7\" name=\"TenneT Actual [MW]\" /><serie id=\"value8\" name=\"TenneT Planned [MW]\" /><serie id=\"value9\" name=\"50HzT Actual [MW]\" /><serie id=\"value10\" name=\"50HzT Planned [MW]\" /><serie id=\"value11\" name=\"CEPS Actual [MW]\" /><serie id=\"value12\" name=\"CEPS Planned [MW]\" /></series><data><item date=\"2025-10-29T18:30:00+01:00\" value1=\"-57.34669\" value2=\"-494.95\" value3=\"-1445.036\" value4=\"-634.725\" value5=\"-556.8103\" value6=\"-75.5\" value7=\"-615.8497\" value8=\"248.125\" value9=\"1561.756\" value10=\"-277.125\" value11=\"-1113.287\" value12=\"-1234.175\" /><item date=\"2025-10-29T18:45:00+01:00\" value1=\"21.2968\" value2=\"-494.95\" value3=\"-1498.111\" value4=\"-634.725\" value5=\"-583.4564\" value6=\"-75.5\" value7=\"-648.0423\" value8=\"248.125\" value9=\"1571.332\" value10=\"-277.125\" value11=\"-1136.981\" value12=\"-1234.175\" /><item date=\"2025-10-29T19:00:00+01:00\" value1=\"180.7892\" value2=\"-366.475\" value3=\"-1509.87\" value4=\"-701.975\" value5=\"-701.4858\" value6=\"-592.325\" 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date=\"2025-10-30T01:15:00+01:00\" value1=\"1462.878\" value2=\"603.675\" value3=\"-1734.441\" value4=\"-719.1\" value5=\"-1586.535\" value6=\"-2109\" value7=\"-527.5365\" value8=\"732.675\" value9=\"1738.697\" value10=\"738.95\" value11=\"-646.9374\" value12=\"-752.8\" /><item date=\"2025-10-30T01:30:00+01:00\" value1=\"1488.255\" value2=\"603.675\" value3=\"-1727.686\" value4=\"-719.1\" value5=\"-1641.105\" value6=\"-2109\" value7=\"-562.3533\" value8=\"732.675\" value9=\"1740.065\" value10=\"738.95\" value11=\"-702.8244\" value12=\"-752.8\" /><item date=\"2025-10-30T01:45:00+01:00\" value1=\"1466.427\" value2=\"603.675\" value3=\"-1673.317\" value4=\"-719.1\" value5=\"-1637.637\" value6=\"-2109\" value7=\"-570.1753\" value8=\"732.675\" value9=\"1699.708\" value10=\"738.95\" value11=\"-714.9937\" value12=\"-752.8\" /><item date=\"2025-10-30T02:00:00+01:00\" value1=\"1531.823\" value2=\"725.3\" value3=\"-1679.156\" value4=\"-671.225\" value5=\"-1671.348\" value6=\"-2194.5\" 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value=\"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\" />\n\n<input type=\"hidden\" name=\"__VIEWSTATEGENERATOR\" id=\"__VIEWSTATEGENERATOR\" value=\"19266F06\" />\n<input type=\"hidden\" name=\"__EVENTVALIDATION\" id=\"__EVENTVALIDATION\" value=\"/wEdAANwtWOgjdEEtEuj09/YJ7srqei9Sb2Zdmww74gx0qmQo2zuiI6WQn56CsmHMxVkRiFF+vU12vY105C9w6tSuMpALBH/MNgiGmiAyMGC+mX5vw==\" />\n    <script type=\"text/javascript\">\n        function ImprimirPantalla() {\n            document.getElementById(\"TablaOpciones\").style.visibility = \"hidden\";\n            window.print();\n            document.getElementById(\"TablaOpciones\").style.visibility = \"visible\";\n        }\n    </script>\n    <table style=\"border: 1px solid lightgray; margin: 2px\" id=\"TablaOpciones\">\n        <tr>\n            <td>\n                <p style=\"color: Black; font-family: @Arial Unicode MS; font-size: smaller;\">\n                    Fecha de Consulta:\n                </p>\n            </td>\n            <td>\n                <input type=\"hidden\"/><script id=\"dxis_1354953081\" src=\"/ReportesGraficos/DXR.axd?r=1_16-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1425606452\" src=\"/ReportesGraficos/DXR.axd?r=1_17-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_996127002\" src=\"/ReportesGraficos/DXR.axd?r=1_28-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1354781980\" src=\"/ReportesGraficos/DXR.axd?r=1_66-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_996091193\" src=\"/ReportesGraficos/DXR.axd?r=1_18-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_560092546\" src=\"/ReportesGraficos/DXR.axd?r=1_19-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1139317518\" src=\"/ReportesGraficos/DXR.axd?r=1_20-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_179010321\" src=\"/ReportesGraficos/DXR.axd?r=1_225-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_179185716\" src=\"/ReportesGraficos/DXR.axd?r=1_226-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1354917272\" src=\"/ReportesGraficos/DXR.axd?r=1_26-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1425570643\" src=\"/ReportesGraficos/DXR.axd?r=1_27-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_857471688\" src=\"/ReportesGraficos/DXR.axd?r=1_231-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_857539210\" src=\"/ReportesGraficos/DXR.axd?r=1_233-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1885719164\" src=\"/ReportesGraficos/DXR.axd?r=1_22-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_84779368\" src=\"/ReportesGraficos/DXR.axd?r=1_44-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_857606988\" src=\"/ReportesGraficos/DXR.axd?r=1_235-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_179117938\" src=\"/ReportesGraficos/DXR.axd?r=1_224-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_84986658\" src=\"/ReportesGraficos/DXR.axd?r=1_24-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_388784053\" src=\"/ReportesGraficos/DXR.axd?r=1_254-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_877110821\" src=\"/ReportesGraficos/DXR.axd?r=1_265-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_877286216\" src=\"/ReportesGraficos/DXR.axd?r=1_266-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_388851575\" src=\"/ReportesGraficos/DXR.axd?r=1_252-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_877370618\" src=\"/ReportesGraficos/DXR.axd?r=1_268-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1555882883\" src=\"/ReportesGraficos/DXR.axd?r=1_276-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1555967285\" src=\"/ReportesGraficos/DXR.axd?r=1_278-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1555859668\" src=\"/ReportesGraficos/DXR.axd?r=1_279-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1555815105\" src=\"/ReportesGraficos/DXR.axd?r=1_274-7ufgi\" type=\"text/javascript\"></script><script id=\"dxis_1116114848\" src=\"/ReportesGraficos/DXR.axd?r=1_280-7ufgi\" type=\"text/javascript\"></script><script id=\"dxss_620605281\" type=\"text/javascript\">\n<!--\n(function(){\nvar a = {'abbrDayNames':['dom.','lun.','mar.','mié.','jue.','vie.','sáb.'],'monthNames':['enero','febrero','marzo','abril','mayo','junio','julio','agosto','septiembre','octubre','noviembre','diciembre',''],'longDate':'dddd, d \\'de\\' MMMM \\'de\\' yyyy','abbrMonthNames':['ene.','feb.','mar.','abr.','may.','jun.','jul.','ago.','sep.','oct.','nov.','dic.',''],'pm':'p.m.','am':'a.m.','numPosInf':'∞','numNegInf':'-∞','monthDay':'d \\'de\\' MMMM','yearMonth':'MMMM \\'de\\' yyyy','percentPattern':1,'dayNames':['domingo','lunes','martes','miércoles','jueves','viernes','sábado'],'genMonthNames':['enero','febrero','marzo','abril','mayo','junio','julio','agosto','septiembre','octubre','noviembre','diciembre',''],'shortDate':'d/M/yyyy'};\nfor(var b in a) ASPx.CultureInfo[b] = a[b];\n})();\n\n//-->\n</script><table id=\"FechaConsultaDateEdit_LP\" class=\"dxeLoadingPanel_Office2010Blue dxlpLoadingPanel_Office2010Blue\" cellspacing=\"0\" cellpadding=\"0\" style=\"left:0px;top:0px;z-index:30000;display:none;\">\n\t<tr>\n\t\t<td class=\"dx\" style=\"padding-right:0px;\"><img class=\"dxlp-loadingImage dxlp-imgPosLeft\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"\" align=\"middle\" /></td><td class=\"dx\" style=\"padding-left:0px;\"><span id=\"FechaConsultaDateEdit_TL\">Cargando&hellip;</span></td>\n\t</tr>\n</table><table class=\"dxeButtonEditSys dxeButtonEdit_Office2010Blue\" cellspacing=\"1\" cellpadding=\"0\" id=\"FechaConsultaDateEdit\">\n\t<tr>\n\t\t<td class=\"dxic\" onmousedown=\"return ASPx.DDMC_MD(&#39;FechaConsultaDateEdit&#39;, event)\" width=\"100%\"><input class=\"dxeEditArea_Office2010Blue dxeEditAreaSys\" id=\"FechaConsultaDateEdit_I\" name=\"FechaConsultaDateEdit\" onfocus=\"ASPx.EGotFocus(&#39;FechaConsultaDateEdit&#39;)\" onblur=\"ASPx.ELostFocus(&#39;FechaConsultaDateEdit&#39;)\" onchange=\"ASPx.ETextChanged(&#39;FechaConsultaDateEdit&#39;)\" value=\"14/01/2025\" type=\"text\" /></td><td id=\"FechaConsultaDateEdit_B-1\" class=\"dxeButton dxeButtonEditButton_Office2010Blue\" onmousedown=\"return ASPx.DDDropDown(&#39;FechaConsultaDateEdit&#39;, event)\" style=\"user-select:none;-khtml-user-select:none;-ms-user-select:none;\"><img id=\"FechaConsultaDateEdit_B-1Img\" class=\"dxEditors_edtDropDown_Office2010Blue\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"v\" /></td>\n\t</tr>\n</table><div id=\"FechaConsultaDateEdit_DDD_PW-1\" class=\"dxpcDropDown_Office2010Blue dxpclW dxpc-ie dxpc-ddSys\" style=\"z-index:10000;display:none;visibility:hidden;\">\n\t<div class=\"dxpc-mainDiv dxpc-shadow\">\n\t\t<div class=\"dxpc-contentWrapper\">\n\t\t\t<div class=\"dxpc-content\">\n\t\t\t\t<table style=\"display:none;\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td id=\"FechaConsultaDateEdit_DDD_C_EC_D\" class=\"dxeCalendarDay_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_DS\" class=\"dxeCalendarSelected_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_DA\" class=\"dxeCalendarOtherMonth_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_DW\" class=\"dxeCalendarWeekend_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_DO\" class=\"dxeCalendarOutOfRange_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_DDD\" class=\"dxeCalendarDayDisabled_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_DT\" class=\"dxeCalendarToday_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_DD\" class=\"dxeDisabled_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_FNM\" class=\"dxeCalendarFastNavMonth_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_FNMS\" class=\"dxeCalendarFastNavMonthSelected_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_FNY\" class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td id=\"FechaConsultaDateEdit_DDD_C_EC_FNYS\" class=\"dxeCalendarFastNavYearSelected_Office2010Blue\"></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table><table class=\"dxeCVC dxeCalendar_Office2010Blue\" cellspacing=\"0\" cellpadding=\"0\" id=\"FechaConsultaDateEdit_DDD_C\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td valign=\"top\"><table cellpadding=\"0\" width=\"100%\" style=\"border-collapse:collapse;\">\n\t\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t\t<td class=\"dxeCalendarHeader_Office2010Blue\" style=\"border-top:0;\"><table cellpadding=\"0\" width=\"100%\" style=\"border-collapse:collapse;\">\n\t\t\t\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t\t\t\t<td id=\"FechaConsultaDateEdit_DDD_C_PYC\" class=\"dxe\"><img id=\"FechaConsultaDateEdit_DDD_C_PYCImg\" class=\"dxEditors_edtCalendarPrevYear_Office2010Blue\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"&lt;&lt;\" /></td><td class=\"dxeCHS\"></td><td id=\"FechaConsultaDateEdit_DDD_C_PMC\" class=\"dxe\"><img id=\"FechaConsultaDateEdit_DDD_C_PMCImg\" class=\"dxEditors_edtCalendarPrevMonth_Office2010Blue\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"&lt;\" /></td><td id=\"FechaConsultaDateEdit_DDD_C_TC\" class=\"dxe\" width=\"100%\" style=\"cursor:default;\"><span id=\"FechaConsultaDateEdit_DDD_C_T\" style=\"cursor:pointer;\">enero de 2025</span></td><td id=\"FechaConsultaDateEdit_DDD_C_NMC\" class=\"dxe\"><img id=\"FechaConsultaDateEdit_DDD_C_NMCImg\" class=\"dxEditors_edtCalendarNextMonth_Office2010Blue\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\">\" /></td><td class=\"dxeCHS\"></td><td id=\"FechaConsultaDateEdit_DDD_C_NYC\" class=\"dxe\"><img id=\"FechaConsultaDateEdit_DDD_C_NYCImg\" class=\"dxEditors_edtCalendarNextYear_Office2010Blue\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\">>\" /></td>\n\t\t\t\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t\t\t</table></td>\n\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t<td id=\"FechaConsultaDateEdit_DDD_C_mc\" class=\"dxMonthGridWithWeekNumbers\" style=\"user-select:none;-khtml-user-select:none;-ms-user-select:none;\"><table id=\"FechaConsultaDateEdit_DDD_C_mt\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" style=\"border-collapse:separate;\">\n\t\t\t\t\t\t\t\t\t<tr align=\"center\">\n\t\t\t\t\t\t\t\t\t\t<td></td><td class=\"dxeCalendarDayHeader_Office2010Blue\">dom.</td><td class=\"dxeCalendarDayHeader_Office2010Blue\">lun.</td><td class=\"dxeCalendarDayHeader_Office2010Blue\">mar.</td><td class=\"dxeCalendarDayHeader_Office2010Blue\">mié.</td><td class=\"dxeCalendarDayHeader_Office2010Blue\">jue.</td><td class=\"dxeCalendarDayHeader_Office2010Blue\">vie.</td><td class=\"dxeCalendarDayHeader_Office2010Blue\">sáb.</td>\n\t\t\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarWeekNumber_Office2010Blue\">01</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">29</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">30</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">31</td><td class=\"dxeCalendarDay_Office2010Blue\">1</td><td class=\"dxeCalendarDay_Office2010Blue\">2</td><td class=\"dxeCalendarDay_Office2010Blue\">3</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue\">4</td>\n\t\t\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarWeekNumber_Office2010Blue\">02</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue\">5</td><td class=\"dxeCalendarDay_Office2010Blue\">6</td><td class=\"dxeCalendarDay_Office2010Blue\">7</td><td class=\"dxeCalendarDay_Office2010Blue\">8</td><td class=\"dxeCalendarDay_Office2010Blue\">9</td><td class=\"dxeCalendarDay_Office2010Blue\">10</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue\">11</td>\n\t\t\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarWeekNumber_Office2010Blue\">03</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue\">12</td><td class=\"dxeCalendarDay_Office2010Blue\">13</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarToday_Office2010Blue\">14</td><td class=\"dxeCalendarDay_Office2010Blue\">15</td><td class=\"dxeCalendarDay_Office2010Blue\">16</td><td class=\"dxeCalendarDay_Office2010Blue\">17</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue\">18</td>\n\t\t\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarWeekNumber_Office2010Blue\">04</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue\">19</td><td class=\"dxeCalendarDay_Office2010Blue\">20</td><td class=\"dxeCalendarDay_Office2010Blue\">21</td><td class=\"dxeCalendarDay_Office2010Blue\">22</td><td class=\"dxeCalendarDay_Office2010Blue\">23</td><td class=\"dxeCalendarDay_Office2010Blue\">24</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue\">25</td>\n\t\t\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarWeekNumber_Office2010Blue\">05</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue\">26</td><td class=\"dxeCalendarDay_Office2010Blue\">27</td><td class=\"dxeCalendarDay_Office2010Blue\">28</td><td class=\"dxeCalendarDay_Office2010Blue\">29</td><td class=\"dxeCalendarDay_Office2010Blue\">30</td><td class=\"dxeCalendarDay_Office2010Blue\">31</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">1</td>\n\t\t\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarWeekNumber_Office2010Blue\">06</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">2</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">3</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">4</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">5</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">6</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">7</td><td class=\"dxeCalendarDay_Office2010Blue dxeCalendarWeekend_Office2010Blue dxeCalendarOtherMonth_Office2010Blue\">8</td>\n\t\t\t\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t\t\t</table></td>\n\t\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t</table></td>\n\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t<td id=\"FechaConsultaDateEdit_DDD_C_F\" class=\"dx-ac dxeCalendarFooter_Office2010Blue\"><table cellpadding=\"0\" style=\"border-collapse:collapse;\">\n\t\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t\t<td id=\"FechaConsultaDateEdit_DDD_C_BT\" class=\"dxeCalendarButton_Office2010Blue\" onclick=\"ASPx.CalTodayClick(&#39;FechaConsultaDateEdit_DDD_C&#39;);\">Hoy</td><td class=\"dxeCFS\"></td><td id=\"FechaConsultaDateEdit_DDD_C_BC\" class=\"dxeCalendarButton_Office2010Blue\" onclick=\"ASPx.CalClearClick(&#39;FechaConsultaDateEdit_DDD_C&#39;);\">Vaciar</td>\n\t\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t</table></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table><div id=\"FechaConsultaDateEdit_DDD_C_FNP_PW-1\" class=\"dxpcDropDown_Office2010Blue dxpclW dxpc-ie dxpc-ddSys\" style=\"z-index:10000;display:none;visibility:hidden;\">\n\t\t\t\t\t<div class=\"dxpc-mainDiv dxpc-shadow\">\n\t\t\t\t\t\t<div class=\"dxpc-contentWrapper\">\n\t\t\t\t\t\t\t<div class=\"dxpc-content\">\n\t\t\t\t\t\t\t\t<div class=\"dxeCalendarFastNav_Office2010Blue\">\n\t\t\t\t\t\t\t\t\t<div class=\"dxeCalendarFastNavMonthArea_Office2010Blue\">\n\t\t\t\t\t\t\t\t\t\t<table id=\"FechaConsultaDateEdit_DDD_C_FNP_m\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" style=\"border-collapse:separate;\">\n\t\t\t\t\t\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Ene.</td><td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Feb.</td><td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Mar.</td><td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Abr.</td>\n\t\t\t\t\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarFastNavMonth_Office2010Blue\">May.</td><td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Jun.</td><td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Jul.</td><td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Ago.</td>\n\t\t\t\t\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Sep.</td><td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Oct.</td><td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Nov.</td><td class=\"dxeCalendarFastNavMonth_Office2010Blue\">Dic.</td>\n\t\t\t\t\t\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t\t\t\t\t</table>\n\t\t\t\t\t\t\t\t\t</div><div class=\"dxeCalendarFastNavYearArea_Office2010Blue\">\n\t\t\t\t\t\t\t\t\t\t<table id=\"FechaConsultaDateEdit_DDD_C_FNP_y\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" style=\"border-collapse:separate;\">\n\t\t\t\t\t\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t\t\t\t\t\t<td onclick=\"ASPx.CalFNYShuffle(&#39;FechaConsultaDateEdit_DDD_C&#39;, -10)\" ondblclick=\"ASPx.CalFNYShuffle(&#39;FechaConsultaDateEdit_DDD_C&#39;, -10)\" rowspan=\"2\" style=\"cursor:pointer;\"><img class=\"dxEditors_edtCalendarFNPrevYear_Office2010Blue\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"&lt;\" /></td><td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td onclick=\"ASPx.CalFNYShuffle(&#39;FechaConsultaDateEdit_DDD_C&#39;, 10)\" ondblclick=\"ASPx.CalFNYShuffle(&#39;FechaConsultaDateEdit_DDD_C&#39;, 10)\" rowspan=\"2\" style=\"cursor:pointer;\"><img class=\"dxEditors_edtCalendarFNNextYear_Office2010Blue\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\">\" /></td>\n\t\t\t\t\t\t\t\t\t\t\t</tr><tr>\n\t\t\t\t\t\t\t\t\t\t\t\t<td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td><td class=\"dxeCalendarFastNavYear_Office2010Blue\"></td>\n\t\t\t\t\t\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t\t\t\t\t</table>\n\t\t\t\t\t\t\t\t\t</div>\n\t\t\t\t\t\t\t\t</div><div class=\"dxeCalendarFastNavFooter_Office2010Blue\" align=\"center\">\n\t\t\t\t\t\t\t\t\t<table cellspacing=\"0\" cellpadding=\"0\">\n\t\t\t\t\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t\t\t\t\t<td id=\"FechaConsultaDateEdit_DDD_C_FNP_BO\" class=\"dxeCalendarButton_Office2010Blue\" onclick=\"ASPx.CalFNBClick(&#39;FechaConsultaDateEdit_DDD_C&#39;, &#39;ok&#39;)\">Aceptar</td><td class=\"dxeCFNFS\"></td><td id=\"FechaConsultaDateEdit_DDD_C_FNP_BC\" class=\"dxeCalendarButton_Office2010Blue\" onclick=\"ASPx.CalFNBClick(&#39;FechaConsultaDateEdit_DDD_C&#39;, &#39;cancel&#39;)\">Cancelar</td>\n\t\t\t\t\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t\t\t\t</table>\n\t\t\t\t\t\t\t\t</div>\n\t\t\t\t\t\t\t</div>\n\t\t\t\t\t\t</div>\n\t\t\t\t\t</div>\n\t\t\t\t</div><script id=\"dxss_2143387158\" type=\"text/javascript\">\n<!--\nASPx.AddHoverItems('FechaConsultaDateEdit_DDD_C_FNP',[[['dxpc-closeBtnHover'],[''],['HCB-1']]]);\nASPx.createControl(ASPxClientPopupControl,'FechaConsultaDateEdit_DDD_C_FNP','',{'uniqueID':'FechaConsultaDateEdit$DDD$C$FNP','adjustInnerControlsSizeOnShow':false,'popupAnimationType':'fade','isPopupPositionCorrectionOn':false});\n\n//-->\n</script><script id=\"dxss_1266379014\" type=\"text/javascript\">\n<!--\nASPx.AddHoverItems('FechaConsultaDateEdit_DDD_C',[[['dxeCalendarButtonHover_Office2010Blue'],[''],['BT','BC','BO','BCN','FNP_BO','FNP_BC']],[['dxeCalendarFastNavMonthHover_Office2010Blue'],[''],['FNP_M0','FNP_M1','FNP_M2','FNP_M3','FNP_M4','FNP_M5','FNP_M6','FNP_M7','FNP_M8','FNP_M9','FNP_M10','FNP_M11']],[['dxeCalendarFastNavYearHover_Office2010Blue'],[''],['FNP_Y0','FNP_Y1','FNP_Y2','FNP_Y3','FNP_Y4','FNP_Y5','FNP_Y6','FNP_Y7','FNP_Y8','FNP_Y9']]]);\nASPx.AddPressedItems('FechaConsultaDateEdit_DDD_C',[[['dxeCalendarButtonPressed_Office2010Blue'],[''],['BT','BC','BO','BCN','FNP_BO','FNP_BC']]]);\nASPx.AddDisabledItems('FechaConsultaDateEdit_DDD_C',[[['dxeDisabled_Office2010Blue'],[''],['']],[['dxeDisabled_Office2010Blue dxeButtonDisabled_Office2010Blue'],[''],['BT','BC','BO','BCN','FNP_BO','FNP_BC']],[[''],[''],['PYC','PMC','NMC','NYC'],,[[{'spriteCssClass':'dxEditors_edtCalendarPrevYearDisabled_Office2010Blue'}],[{'spriteCssClass':'dxEditors_edtCalendarPrevMonthDisabled_Office2010Blue'}],[{'spriteCssClass':'dxEditors_edtCalendarNextMonthDisabled_Office2010Blue'}],[{'spriteCssClass':'dxEditors_edtCalendarNextYearDisabled_Office2010Blue'}]],['Img']]]);\nASPx.createControl(ASPxClientCalendar,'FechaConsultaDateEdit_DDD_C','',{'uniqueID':'FechaConsultaDateEdit$DDD$C','scStates':2,'scPostfix':'Office2010Blue','serverCurrentDate':new Date(2025,0,14,0,0,0,0),'visibleDate':new Date(2025,0,14,0,0,0,0),'isDateEditCalendar':true},null,null,{'decorationStyles':[{'key':'F','className':'dxeFocused_Office2010Blue','cssText':''}],'selection':[new Date(2025,0,14,0,0,0,0)]});\n\n//-->\n</script>\n\t\t\t</div>\n\t\t</div>\n\t</div>\n</div><script id=\"dxss_1255765817\" type=\"text/javascript\">\n<!--\nASPx.AddHoverItems('FechaConsultaDateEdit_DDD',[[['dxpc-closeBtnHover'],[''],['HCB-1']]]);\nASPx.createControl(ASPxClientPopupControl,'FechaConsultaDateEdit_DDD','',{'uniqueID':'FechaConsultaDateEdit$DDD','adjustInnerControlsSizeOnShow':false,'popupAnimationType':'slide','closeAction':'CloseButton','popupHorizontalAlign':'LeftSides','popupVerticalAlign':'Below','isPopupPositionCorrectionOn':false},{'Shown':function (s, e) { ASPx.DDBPCShown('FechaConsultaDateEdit', e); }});\n\n//-->\n</script><script id=\"dxss_2133219256\" type=\"text/javascript\">\n<!--\nASPx.AddHoverItems('FechaConsultaDateEdit',[[['dxeButtonEditButtonHover_Office2010Blue'],[''],['B-1']]]);\nASPx.RemoveHoverItems('FechaConsultaDateEdit',[[['B-100']]]);\nASPx.AddPressedItems('FechaConsultaDateEdit',[[['dxeButtonEditButtonPressed_Office2010Blue'],[''],['B-1']]]);\nASPx.RemovePressedItems('FechaConsultaDateEdit',[[['B-100']]]);\nASPx.AddDisabledItems('FechaConsultaDateEdit',[[['dxeDisabled_Office2010Blue'],[''],['','I']],[['dxeDisabled_Office2010Blue dxeButtonDisabled_Office2010Blue'],[''],['B-1'],,[[{'spriteCssClass':'dxEditors_edtDropDownDisabled_Office2010Blue'}]],['Img']]]);\nASPx.RemoveDisabledItems('FechaConsultaDateEdit',[[['B-100'],]]);\nASPx.createControl(ASPxClientDateEdit,'FechaConsultaDateEdit','',{'callBack':function(arg) { WebForm_DoCallback('FechaConsultaDateEdit',arg,ASPx.Callback,'FechaConsultaDateEdit',ASPx.CallbackError,true); },'scStates':2,'scPostfix':'Office2010Blue','stateObject':{'rawValue':'1736812800000'},'displayFormat':'{0:dd/MM/yyyy}','autoCompleteAttribute':{'name':'autocomplete','value':'off'},'outOfRangeWarningClassName':'dxeOutOfRWarn_Office2010Blue dxeOutOfRWarnRight_Office2010Blue','outOfRangeWarningMessages':['La fecha debe estar en el rango de {0}...{1}', 'La fecha debe ser mayor o igual a {0}', 'La fecha debe ser menor o igual a {0}'],'date':new Date(2025,0,14,0,0,0,0),'dateFormatter':ASPx.DateFormatter.Create('d/M/yyyy')},{'DateChanged':function(s, e) {\n\tdocument.getElementById('ConsultarButton').click();\n}},null,{'decorationStyles':[{'key':'F','className':'dxeFocused_Office2010Blue','cssText':''}]});\n\n//-->\n</script>\n            </td>\n            <td>\n                <div class=\"dxbButton_Office2010Blue dxbButtonSys dxbTSys\" id=\"ExportarButton\" style=\"user-select:none;-khtml-user-select:none;-ms-user-select:none;\">\n\t<div class=\"dxb\">\n\t\t<input id=\"ExportarButton_I\" class=\"dxb-hb\" value=\"Exportar\" type=\"submit\" name=\"ExportarButton\" /><span class=\"dx-vam\">Exportar</span>\n\t</div>\n</div><script id=\"dxss_1444205541\" type=\"text/javascript\">\n<!--\nASPx.AddHoverItems('ExportarButton',[[['dxbButtonHover_Office2010Blue'],[''],[''],['','TC']]]);\nASPx.AddPressedItems('ExportarButton',[[['dxbButtonPressed_Office2010Blue'],[''],[''],['','TC']]]);\nASPx.AddSelectedItems('ExportarButton',[[['dxbf'],[''],['CD']]]);\nASPx.createControl(ASPxClientButton,'ExportarButton','',{'autoPostBack':true,'serverEvents':['Click']});\n\n//-->\n</script>\n            </td>\n            <td>\n                <div class=\"dxbButton_Office2010Blue dxbButtonSys dxbTSys\" id=\"ImprimirButton\" style=\"user-select:none;-khtml-user-select:none;-ms-user-select:none;\">\n\t<div class=\"dxb\">\n\t\t<input id=\"ImprimirButton_I\" class=\"dxb-hb\" value=\"Imprimir\" type=\"submit\" name=\"ImprimirButton\" /><span class=\"dx-vam\">Imprimir</span>\n\t</div>\n</div><script id=\"dxss_927814252\" type=\"text/javascript\">\n<!--\nASPx.AddHoverItems('ImprimirButton',[[['dxbButtonHover_Office2010Blue'],[''],[''],['','TC']]]);\nASPx.AddPressedItems('ImprimirButton',[[['dxbButtonPressed_Office2010Blue'],[''],[''],['','TC']]]);\nASPx.AddDisabledItems('ImprimirButton',[[['dxbDisabled_Office2010Blue'],[''],[''],['','TC']]]);\nASPx.AddSelectedItems('ImprimirButton',[[['dxbf'],[''],['CD']]]);\nASPx.createControl(ASPxClientButton,'ImprimirButton','',{'autoPostBack':true},{'Click':function(s, e) {\n\tImprimirPantalla();\n}});\n\n//-->\n</script>\n            </td>\n            <td>\n                <input id=\"ConsultarButton\" type=\"submit\" style=\"visibility: hidden; width: 1px;\" />\n            </td>\n        </tr>\n    </table>\n    \n    <div style=\"padding: 0px; width: 100%;\">\n        <table border=\"0\" cellpadding=\"0\" cellspacing=\"0\" style=\"width: 100%; height: 100%;\">\n            <tr>\n                <td valign=\"top\">\n                    <div style=\"font-family: Tahoma; font-size: 18px; margin: 0px; color: #333333; text-align: left;\">\n                        Postdespacho de Unidades - Información a:14/01/2025\n                    </div>\n                    <!-- GRID -->\n                    <table class=\"dxgvControl_Office2010Blue dxgv\" cellspacing=\"0\" cellpadding=\"0\" id=\"PostdespachoUnidadesTermicasGrid\" width=\"100%\" style=\"border-collapse:separate;\">\n\t<tr>\n\t\t<td style=\"padding-left:0px;padding-right:0px;padding-top:0px;padding-bottom:0px;\"><table id=\"PostdespachoUnidadesTermicasGrid_DXMainTable\" class=\"dxgvTable_Office2010Blue\" cellspacing=\"0\" cellpadding=\"0\" onclick=\"ASPx.GTableClick(&#39;PostdespachoUnidadesTermicasGrid&#39;, event);\" ondblclick=\"ASPx.GVTableDblClick(&#39;PostdespachoUnidadesTermicasGrid&#39;, event);\" oncontextmenu=\"return ASPx.GVContextMenu(&#39;PostdespachoUnidadesTermicasGrid&#39;,event);\" width=\"100%\" style=\"empty-cells:show;\">\n\t\t\t<tr id=\"PostdespachoUnidadesTermicasGrid_DXHeadersRow0\">\n\t\t\t\t<td class=\"dxgvHeader_Office2010Blue\" width=\"0.1%\" style=\"border-top-width:0px;border-left-width:0px;cursor:default;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"\" style=\"visibility:hidden;\" /></td><td class=\"dxgvHeader_Office2010Blue\" width=\"0.1%\" style=\"border-top-width:0px;border-left-width:0px;cursor:default;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"\" style=\"visibility:hidden;\" /></td><td id=\"PostdespachoUnidadesTermicasGrid_col2\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>CENTRAL</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col3\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col4\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col5\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col6\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col7\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col8\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col9\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col10\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col11\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col12\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col13\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col14\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col15\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col16\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col17\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col18\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col19\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col20\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col21\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col22\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col23\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col24\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col25\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td><td id=\"PostdespachoUnidadesTermicasGrid_col26\" class=\"dxgvHeader_Office2010Blue\" style=\"border-top-width:0px;border-left-width:0px;border-right-width:0px;\"><table cellspacing=\"0\" cellpadding=\"0\" width=\"100%\">\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>24</td><td width=\"1\" style=\"text-align:right;\"><span class=\"dx-vam\">&nbsp;</span></td>\n\t\t\t\t\t</tr>\n\t\t\t\t</table></td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp0\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,0,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"26\" style=\"border-right-width:0px;\">GRUPO: E&#243;lica </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp1\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,1,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: AGUA CLARA </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow2\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE E&#211;LICO AGUA CLARA</td><td class=\"dxgv\" align=\"right\">1.69</td><td class=\"dxgv\" align=\"right\">1.43</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">2.22</td><td class=\"dxgv\" align=\"right\">0.65</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">2.21</td><td class=\"dxgv\" align=\"right\">1.97</td><td class=\"dxgv\" align=\"right\">11.76</td><td class=\"dxgv\" align=\"right\">23.05</td><td class=\"dxgv\" align=\"right\">23.74</td><td class=\"dxgv\" align=\"right\">12.71</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow1\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp3\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,3,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: EGEHAINA </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow4\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">JUANCHO LOS COCOS 1</td><td class=\"dxgv\" align=\"right\">3.91</td><td class=\"dxgv\" align=\"right\">4.40</td><td class=\"dxgv\" align=\"right\">4.46</td><td class=\"dxgv\" align=\"right\">0.89</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">0.57</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow5\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LOS COCOS 2</td><td class=\"dxgv\" align=\"right\">3.15</td><td class=\"dxgv\" align=\"right\">3.34</td><td class=\"dxgv\" align=\"right\">3.36</td><td class=\"dxgv\" align=\"right\">0.67</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow6\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE E&#211;LICO LARIMAR</td><td class=\"dxgv\" align=\"right\">26.79</td><td class=\"dxgv\" align=\"right\">28.12</td><td class=\"dxgv\" align=\"right\">28.28</td><td class=\"dxgv\" align=\"right\">16.45</td><td class=\"dxgv\" align=\"right\">10.55</td><td class=\"dxgv\" align=\"right\">7.30</td><td class=\"dxgv\" align=\"right\">5.59</td><td class=\"dxgv\" align=\"right\">4.94</td><td class=\"dxgv\" align=\"right\">4.01</td><td class=\"dxgv\" align=\"right\">3.42</td><td class=\"dxgv\" align=\"right\">3.51</td><td class=\"dxgv\" align=\"right\">3.81</td><td class=\"dxgv\" align=\"right\">4.40</td><td class=\"dxgv\" align=\"right\">6.14</td><td class=\"dxgv\" align=\"right\">7.06</td><td class=\"dxgv\" align=\"right\">4.27</td><td class=\"dxgv\" align=\"right\">2.29</td><td class=\"dxgv\" align=\"right\">1.90</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow7\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE E&#211;LICO LARIMAR II</td><td class=\"dxgv\" align=\"right\">18.46</td><td class=\"dxgv\" align=\"right\">16.92</td><td class=\"dxgv\" align=\"right\">16.74</td><td class=\"dxgv\" align=\"right\">7.92</td><td class=\"dxgv\" align=\"right\">4.58</td><td class=\"dxgv\" align=\"right\">3.12</td><td class=\"dxgv\" align=\"right\">2.46</td><td class=\"dxgv\" align=\"right\">2.04</td><td class=\"dxgv\" align=\"right\">1.66</td><td class=\"dxgv\" align=\"right\">1.39</td><td class=\"dxgv\" align=\"right\">1.20</td><td class=\"dxgv\" align=\"right\">1.17</td><td class=\"dxgv\" align=\"right\">1.39</td><td class=\"dxgv\" align=\"right\">1.71</td><td class=\"dxgv\" align=\"right\">2.28</td><td class=\"dxgv\" align=\"right\">2.22</td><td class=\"dxgv\" align=\"right\">2.73</td><td class=\"dxgv\" align=\"right\">3.04</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow8\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">QUILVIO CABRERA</td><td class=\"dxgv\" align=\"right\">1.23</td><td class=\"dxgv\" align=\"right\">1.35</td><td class=\"dxgv\" align=\"right\">1.36</td><td class=\"dxgv\" align=\"right\">0.53</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">0.60</td><td class=\"dxgv\" align=\"right\">0.82</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow3\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp9\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,9,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: GRUPO E&#211;LICO DOMINICANO </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow10\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE E&#211;LICO DE MATAFONGO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.22</td><td class=\"dxgv\" align=\"right\">3.52</td><td class=\"dxgv\" align=\"right\">0.63</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.16</td><td class=\"dxgv\" align=\"right\">2.99</td><td class=\"dxgv\" align=\"right\">3.55</td><td class=\"dxgv\" align=\"right\">1.33</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow9\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp11\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,11,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: PECASA </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow12\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE E&#211;LICO GUANILLO</td><td class=\"dxgv\" align=\"right\">11.94</td><td class=\"dxgv\" align=\"right\">6.50</td><td class=\"dxgv\" align=\"right\">0.96</td><td class=\"dxgv\" align=\"right\">0.83</td><td class=\"dxgv\" align=\"right\">0.67</td><td class=\"dxgv\" align=\"right\">2.06</td><td class=\"dxgv\" align=\"right\">2.35</td><td class=\"dxgv\" align=\"right\">2.49</td><td class=\"dxgv\" align=\"right\">2.62</td><td class=\"dxgv\" align=\"right\">0.93</td><td class=\"dxgv\" align=\"right\">2.21</td><td class=\"dxgv\" align=\"right\">2.31</td><td class=\"dxgv\" align=\"right\">8.22</td><td class=\"dxgv\" align=\"right\">15.87</td><td class=\"dxgv\" align=\"right\">28.68</td><td class=\"dxgv\" align=\"right\">33.73</td><td class=\"dxgv\" align=\"right\">33.22</td><td class=\"dxgv\" align=\"right\">32.26</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow11\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp13\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,13,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: POSEIDON </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow14\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE E&#211;LICO LOS GUZMANCITOS</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">3.41</td><td class=\"dxgv\" align=\"right\">8.95</td><td class=\"dxgv\" align=\"right\">10.24</td><td class=\"dxgv\" align=\"right\">9.23</td><td class=\"dxgv\" align=\"right\">9.19</td><td class=\"dxgv\" align=\"right\">6.97</td><td class=\"dxgv\" align=\"right\">7.17</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow15\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE E&#211;LICO LOS GUZMANCITOS 2</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.29</td><td class=\"dxgv\" align=\"right\">4.72</td><td class=\"dxgv\" align=\"right\">6.50</td><td class=\"dxgv\" align=\"right\">9.37</td><td class=\"dxgv\" align=\"right\">10.13</td><td class=\"dxgv\" align=\"right\">8.85</td><td class=\"dxgv\" align=\"right\">6.70</td><td class=\"dxgv\" align=\"right\">6.21</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow13\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow0\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0\" style=\"border-left-width:0px;border-right-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp16\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,16,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"26\" style=\"border-right-width:0px;\">GRUPO: Hidroel&#233;ctrica </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp17\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,17,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: EGEHID </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow18\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">AGUACATE 1</td><td class=\"dxgv\" align=\"right\">26.00</td><td class=\"dxgv\" align=\"right\">2.37</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.96</td><td class=\"dxgv\" align=\"right\">26.00</td><td class=\"dxgv\" align=\"right\">26.00</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow19\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">AGUACATE 2</td><td class=\"dxgv\" align=\"right\">26.02</td><td class=\"dxgv\" align=\"right\">26.56</td><td class=\"dxgv\" align=\"right\">26.59</td><td class=\"dxgv\" align=\"right\">14.87</td><td class=\"dxgv\" align=\"right\">26.43</td><td class=\"dxgv\" align=\"right\">26.00</td><td class=\"dxgv\" align=\"right\">25.93</td><td class=\"dxgv\" align=\"right\">16.30</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">4.46</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow20\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ANIANA VARGAS 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow21\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ANIANA VARGAS 2</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow22\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">BAIGUAQUE 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow23\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">BAIGUAQUE 2</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow24\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">BRAZO DERECHO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow25\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">CONTRA EMBALSE MONCI&#211;N 1</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow26\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">CONTRA EMBALSE MONCI&#211;N 2</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">0.80</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow27\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">DOMINGO RODR&#205;GUEZ 1</td><td class=\"dxgv\" align=\"right\">1.34</td><td class=\"dxgv\" align=\"right\">1.34</td><td class=\"dxgv\" align=\"right\">1.34</td><td class=\"dxgv\" align=\"right\">1.34</td><td class=\"dxgv\" align=\"right\">1.34</td><td class=\"dxgv\" align=\"right\">1.34</td><td class=\"dxgv\" align=\"right\">1.34</td><td class=\"dxgv\" align=\"right\">1.35</td><td class=\"dxgv\" align=\"right\">1.38</td><td class=\"dxgv\" align=\"right\">1.38</td><td class=\"dxgv\" align=\"right\">1.38</td><td class=\"dxgv\" align=\"right\">1.38</td><td class=\"dxgv\" align=\"right\">1.38</td><td class=\"dxgv\" align=\"right\">1.38</td><td class=\"dxgv\" align=\"right\">1.35</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow28\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">DOMINGO RODR&#205;GUEZ 2</td><td class=\"dxgv\" align=\"right\">1.21</td><td class=\"dxgv\" align=\"right\">1.21</td><td class=\"dxgv\" align=\"right\">1.21</td><td class=\"dxgv\" align=\"right\">1.21</td><td class=\"dxgv\" align=\"right\">1.20</td><td class=\"dxgv\" align=\"right\">1.20</td><td class=\"dxgv\" align=\"right\">1.20</td><td class=\"dxgv\" align=\"right\">1.23</td><td class=\"dxgv\" align=\"right\">1.26</td><td class=\"dxgv\" align=\"right\">1.26</td><td class=\"dxgv\" align=\"right\">1.26</td><td class=\"dxgv\" align=\"right\">1.26</td><td class=\"dxgv\" align=\"right\">1.26</td><td class=\"dxgv\" align=\"right\">1.26</td><td class=\"dxgv\" align=\"right\">1.23</td><td class=\"dxgv\" align=\"right\">1.24</td><td class=\"dxgv\" align=\"right\">0.54</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow29\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">EL SALTO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow30\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">HATILLO</td><td class=\"dxgv\" align=\"right\">7.06</td><td class=\"dxgv\" align=\"right\">7.05</td><td class=\"dxgv\" align=\"right\">7.04</td><td class=\"dxgv\" align=\"right\">7.03</td><td class=\"dxgv\" align=\"right\">7.03</td><td class=\"dxgv\" align=\"right\">7.05</td><td class=\"dxgv\" align=\"right\">7.05</td><td class=\"dxgv\" align=\"right\">7.04</td><td class=\"dxgv\" align=\"right\">7.02</td><td class=\"dxgv\" align=\"right\">6.99</td><td class=\"dxgv\" align=\"right\">6.71</td><td class=\"dxgv\" align=\"right\">6.95</td><td class=\"dxgv\" align=\"right\">6.99</td><td class=\"dxgv\" align=\"right\">6.99</td><td class=\"dxgv\" align=\"right\">7.00</td><td class=\"dxgv\" align=\"right\">6.97</td><td class=\"dxgv\" align=\"right\">7.03</td><td class=\"dxgv\" align=\"right\">7.03</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow31\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">HATILLO 2</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow32\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">JIGUEY 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">3.55</td><td class=\"dxgv\" align=\"right\">47.00</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow33\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">JIGUEY 2</td><td class=\"dxgv\" align=\"right\">47.00</td><td class=\"dxgv\" align=\"right\">47.00</td><td class=\"dxgv\" align=\"right\">27.78</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow34\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">JIMENOA</td><td class=\"dxgv\" align=\"right\">3.84</td><td class=\"dxgv\" align=\"right\">3.84</td><td class=\"dxgv\" align=\"right\">3.85</td><td class=\"dxgv\" align=\"right\">3.85</td><td class=\"dxgv\" align=\"right\">3.85</td><td class=\"dxgv\" align=\"right\">3.86</td><td class=\"dxgv\" align=\"right\">3.87</td><td class=\"dxgv\" align=\"right\">3.87</td><td class=\"dxgv\" align=\"right\">3.87</td><td class=\"dxgv\" align=\"right\">3.90</td><td class=\"dxgv\" align=\"right\">4.05</td><td class=\"dxgv\" align=\"right\">4.07</td><td class=\"dxgv\" align=\"right\">4.07</td><td class=\"dxgv\" align=\"right\">4.07</td><td class=\"dxgv\" align=\"right\">4.06</td><td class=\"dxgv\" align=\"right\">4.06</td><td class=\"dxgv\" align=\"right\">4.07</td><td class=\"dxgv\" align=\"right\">4.07</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow35\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LAS BAR&#205;AS</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow36\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LAS DAMAS</td><td class=\"dxgv\" align=\"right\">1.62</td><td class=\"dxgv\" align=\"right\">1.65</td><td class=\"dxgv\" align=\"right\">1.65</td><td class=\"dxgv\" align=\"right\">1.65</td><td class=\"dxgv\" align=\"right\">1.65</td><td class=\"dxgv\" align=\"right\">1.65</td><td class=\"dxgv\" align=\"right\">1.65</td><td class=\"dxgv\" align=\"right\">1.65</td><td class=\"dxgv\" align=\"right\">1.67</td><td class=\"dxgv\" align=\"right\">1.72</td><td class=\"dxgv\" align=\"right\">1.63</td><td class=\"dxgv\" align=\"right\">1.63</td><td class=\"dxgv\" align=\"right\">1.65</td><td class=\"dxgv\" align=\"right\">1.67</td><td class=\"dxgv\" align=\"right\">1.71</td><td class=\"dxgv\" align=\"right\">1.71</td><td class=\"dxgv\" align=\"right\">1.71</td><td class=\"dxgv\" align=\"right\">1.72</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow37\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">L&#211;PEZ ANGOSTURA</td><td class=\"dxgv\" align=\"right\">7.66</td><td class=\"dxgv\" align=\"right\">7.63</td><td class=\"dxgv\" align=\"right\">7.59</td><td class=\"dxgv\" align=\"right\">7.64</td><td class=\"dxgv\" align=\"right\">7.62</td><td class=\"dxgv\" align=\"right\">7.59</td><td class=\"dxgv\" align=\"right\">7.55</td><td class=\"dxgv\" align=\"right\">7.52</td><td class=\"dxgv\" align=\"right\">7.54</td><td class=\"dxgv\" align=\"right\">7.72</td><td class=\"dxgv\" align=\"right\">7.67</td><td class=\"dxgv\" align=\"right\">7.52</td><td class=\"dxgv\" align=\"right\">7.66</td><td class=\"dxgv\" align=\"right\">7.64</td><td class=\"dxgv\" align=\"right\">7.60</td><td class=\"dxgv\" align=\"right\">7.61</td><td class=\"dxgv\" align=\"right\">7.65</td><td class=\"dxgv\" align=\"right\">7.68</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow38\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LOS ANONES</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow39\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LOS TOROS 1</td><td class=\"dxgv\" align=\"right\">3.50</td><td class=\"dxgv\" align=\"right\">3.50</td><td class=\"dxgv\" align=\"right\">3.50</td><td class=\"dxgv\" align=\"right\">3.50</td><td class=\"dxgv\" align=\"right\">3.50</td><td class=\"dxgv\" align=\"right\">3.50</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.30</td><td class=\"dxgv\" align=\"right\">3.40</td><td class=\"dxgv\" align=\"right\">3.40</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow40\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LOS TOROS 2</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">2.80</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow41\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">MAGUEYAL 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow42\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">MAGUEYAL 2</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow43\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">MONCI&#211;N 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow44\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">MONCI&#211;N 2</td><td class=\"dxgv\" align=\"right\">26.00</td><td class=\"dxgv\" align=\"right\">2.37</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow45\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">NIZAO NAJAYO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow46\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PALOMINO 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">30.69</td><td class=\"dxgv\" align=\"right\">5.31</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow47\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PALOMINO 2</td><td class=\"dxgv\" align=\"right\">35.41</td><td class=\"dxgv\" align=\"right\">2.13</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow48\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PINALITO 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow49\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PINALITO 2</td><td class=\"dxgv\" align=\"right\">24.18</td><td class=\"dxgv\" align=\"right\">24.19</td><td class=\"dxgv\" align=\"right\">7.95</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow50\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">RINC&#211;N</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">8.13</td><td class=\"dxgv\" align=\"right\">8.80</td><td class=\"dxgv\" align=\"right\">8.78</td><td class=\"dxgv\" align=\"right\">8.74</td><td class=\"dxgv\" align=\"right\">8.20</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow51\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">R&#205;O BLANCO 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">9.63</td><td class=\"dxgv\" align=\"right\">11.70</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow52\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">R&#205;O BLANCO 2</td><td class=\"dxgv\" align=\"right\">12.00</td><td class=\"dxgv\" align=\"right\">12.00</td><td class=\"dxgv\" align=\"right\">11.92</td><td class=\"dxgv\" align=\"right\">11.89</td><td class=\"dxgv\" align=\"right\">11.86</td><td class=\"dxgv\" align=\"right\">12.02</td><td class=\"dxgv\" align=\"right\">12.00</td><td class=\"dxgv\" align=\"right\">11.90</td><td class=\"dxgv\" align=\"right\">11.86</td><td class=\"dxgv\" align=\"right\">11.82</td><td class=\"dxgv\" align=\"right\">11.18</td><td class=\"dxgv\" align=\"right\">11.76</td><td class=\"dxgv\" align=\"right\">11.81</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow53\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ROSA JULIA DE LA CRUZ</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow54\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SABANA YEGUA</td><td class=\"dxgv\" align=\"right\">11.16</td><td class=\"dxgv\" align=\"right\">11.15</td><td class=\"dxgv\" align=\"right\">11.15</td><td class=\"dxgv\" align=\"right\">11.14</td><td class=\"dxgv\" align=\"right\">11.14</td><td class=\"dxgv\" align=\"right\">11.15</td><td class=\"dxgv\" align=\"right\">11.14</td><td class=\"dxgv\" align=\"right\">11.14</td><td class=\"dxgv\" align=\"right\">11.15</td><td class=\"dxgv\" align=\"right\">11.14</td><td class=\"dxgv\" align=\"right\">11.13</td><td class=\"dxgv\" align=\"right\">11.12</td><td class=\"dxgv\" align=\"right\">11.14</td><td class=\"dxgv\" align=\"right\">11.14</td><td class=\"dxgv\" align=\"right\">11.14</td><td class=\"dxgv\" align=\"right\">11.14</td><td class=\"dxgv\" align=\"right\">11.15</td><td class=\"dxgv\" align=\"right\">11.15</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow55\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SABANETA</td><td class=\"dxgv\" align=\"right\">4.28</td><td class=\"dxgv\" align=\"right\">4.28</td><td class=\"dxgv\" align=\"right\">4.28</td><td class=\"dxgv\" align=\"right\">4.28</td><td class=\"dxgv\" align=\"right\">4.27</td><td class=\"dxgv\" align=\"right\">4.27</td><td class=\"dxgv\" align=\"right\">4.27</td><td class=\"dxgv\" align=\"right\">4.27</td><td class=\"dxgv\" align=\"right\">4.27</td><td class=\"dxgv\" align=\"right\">4.26</td><td class=\"dxgv\" align=\"right\">4.26</td><td class=\"dxgv\" align=\"right\">4.26</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow56\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">TAVERA 1</td><td class=\"dxgv\" align=\"right\">12.38</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow57\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">TAVERA 2</td><td class=\"dxgv\" align=\"right\">13.47</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow58\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">VALDESIA 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow59\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">VALDESIA 2</td><td class=\"dxgv\" align=\"right\">23.00</td><td class=\"dxgv\" align=\"right\">2.10</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow17\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow16\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0\" style=\"border-left-width:0px;border-right-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp60\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,60,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"26\" style=\"border-right-width:0px;\">GRUPO: Solar </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp61\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,61,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: AES DOMINICANA RENEWABLE ENERGY, S.R.L. </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow62\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO BAYAHONDA (BAYASOL)</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">0.90</td><td class=\"dxgv\" align=\"right\">8.77</td><td class=\"dxgv\" align=\"right\">18.57</td><td class=\"dxgv\" align=\"right\">25.60</td><td class=\"dxgv\" align=\"right\">28.75</td><td class=\"dxgv\" align=\"right\">30.10</td><td class=\"dxgv\" align=\"right\">29.76</td><td class=\"dxgv\" align=\"right\">26.98</td><td class=\"dxgv\" align=\"right\">21.81</td><td class=\"dxgv\" align=\"right\">14.20</td><td class=\"dxgv\" align=\"right\">8.46</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow63\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO MIRASOL</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">2.23</td><td class=\"dxgv\" align=\"right\">25.95</td><td class=\"dxgv\" align=\"right\">53.87</td><td class=\"dxgv\" align=\"right\">62.02</td><td class=\"dxgv\" align=\"right\">58.78</td><td class=\"dxgv\" align=\"right\">75.33</td><td class=\"dxgv\" align=\"right\">71.87</td><td class=\"dxgv\" align=\"right\">70.49</td><td class=\"dxgv\" align=\"right\">58.84</td><td class=\"dxgv\" align=\"right\">37.39</td><td class=\"dxgv\" align=\"right\">25.83</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow64\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO SANTANASOL</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.52</td><td class=\"dxgv\" align=\"right\">14.14</td><td class=\"dxgv\" align=\"right\">28.18</td><td class=\"dxgv\" align=\"right\">39.40</td><td class=\"dxgv\" align=\"right\">44.99</td><td class=\"dxgv\" align=\"right\">43.93</td><td class=\"dxgv\" align=\"right\">45.42</td><td class=\"dxgv\" align=\"right\">42.85</td><td class=\"dxgv\" align=\"right\">34.79</td><td class=\"dxgv\" align=\"right\">22.78</td><td class=\"dxgv\" align=\"right\">13.84</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow61\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp65\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,65,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: DESARROLLOS FOTOVOLTAICOS DSS </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow66\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO LA VICTORIA</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.18</td><td class=\"dxgv\" align=\"right\">11.55</td><td class=\"dxgv\" align=\"right\">24.41</td><td class=\"dxgv\" align=\"right\">28.24</td><td class=\"dxgv\" align=\"right\">30.56</td><td class=\"dxgv\" align=\"right\">31.87</td><td class=\"dxgv\" align=\"right\">34.46</td><td class=\"dxgv\" align=\"right\">30.17</td><td class=\"dxgv\" align=\"right\">24.47</td><td class=\"dxgv\" align=\"right\">18.34</td><td class=\"dxgv\" align=\"right\">11.70</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow65\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp67\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,67,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: EFD ECOENER FOTOVOLTAICA DOMINICANA, S.R.L. </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow68\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO CUMAYASA 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">3.04</td><td class=\"dxgv\" align=\"right\">23.22</td><td class=\"dxgv\" align=\"right\">39.43</td><td class=\"dxgv\" align=\"right\">34.45</td><td class=\"dxgv\" align=\"right\">25.91</td><td class=\"dxgv\" align=\"right\">29.45</td><td class=\"dxgv\" align=\"right\">36.18</td><td class=\"dxgv\" align=\"right\">37.73</td><td class=\"dxgv\" align=\"right\">36.81</td><td class=\"dxgv\" align=\"right\">30.08</td><td class=\"dxgv\" align=\"right\">11.09</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow69\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO CUMAYASA 2</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">2.11</td><td class=\"dxgv\" align=\"right\">14.39</td><td class=\"dxgv\" align=\"right\">23.48</td><td class=\"dxgv\" align=\"right\">22.79</td><td class=\"dxgv\" align=\"right\">15.64</td><td class=\"dxgv\" align=\"right\">17.95</td><td class=\"dxgv\" align=\"right\">21.12</td><td class=\"dxgv\" align=\"right\">21.57</td><td class=\"dxgv\" align=\"right\">20.49</td><td class=\"dxgv\" align=\"right\">17.90</td><td class=\"dxgv\" align=\"right\">6.47</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow67\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp70\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,70,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: EGEHAINA </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow71\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO SAJOMA</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.68</td><td class=\"dxgv\" align=\"right\">15.59</td><td class=\"dxgv\" align=\"right\">37.36</td><td class=\"dxgv\" align=\"right\">48.32</td><td class=\"dxgv\" align=\"right\">43.96</td><td class=\"dxgv\" align=\"right\">65.58</td><td class=\"dxgv\" align=\"right\">59.06</td><td class=\"dxgv\" align=\"right\">50.08</td><td class=\"dxgv\" align=\"right\">48.13</td><td class=\"dxgv\" align=\"right\">32.03</td><td class=\"dxgv\" align=\"right\">20.47</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow72\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE SOLAR ESPERANZA</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">0.73</td><td class=\"dxgv\" align=\"right\">14.78</td><td class=\"dxgv\" align=\"right\">40.76</td><td class=\"dxgv\" align=\"right\">58.06</td><td class=\"dxgv\" align=\"right\">60.01</td><td class=\"dxgv\" align=\"right\">58.56</td><td class=\"dxgv\" align=\"right\">59.58</td><td class=\"dxgv\" align=\"right\">59.50</td><td class=\"dxgv\" align=\"right\">59.81</td><td class=\"dxgv\" align=\"right\">51.01</td><td class=\"dxgv\" align=\"right\">31.10</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow73\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE SOLAR GIRASOL</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">2.58</td><td class=\"dxgv\" align=\"right\">38.84</td><td class=\"dxgv\" align=\"right\">72.48</td><td class=\"dxgv\" align=\"right\">77.68</td><td class=\"dxgv\" align=\"right\">76.69</td><td class=\"dxgv\" align=\"right\">72.55</td><td class=\"dxgv\" align=\"right\">77.52</td><td class=\"dxgv\" align=\"right\">76.94</td><td class=\"dxgv\" align=\"right\">72.06</td><td class=\"dxgv\" align=\"right\">59.81</td><td class=\"dxgv\" align=\"right\">37.82</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow70\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp74\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,74,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: ELECTRONIC </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow75\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">MONTE PLATA SOLAR</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.81</td><td class=\"dxgv\" align=\"right\">15.83</td><td class=\"dxgv\" align=\"right\">31.18</td><td class=\"dxgv\" align=\"right\">29.63</td><td class=\"dxgv\" align=\"right\">39.81</td><td class=\"dxgv\" align=\"right\">28.47</td><td class=\"dxgv\" align=\"right\">41.31</td><td class=\"dxgv\" align=\"right\">40.50</td><td class=\"dxgv\" align=\"right\">33.80</td><td class=\"dxgv\" align=\"right\">22.20</td><td class=\"dxgv\" align=\"right\">13.34</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow74\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp76\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,76,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: EMERALD </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow77\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE SOLAR CANOA</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">7.20</td><td class=\"dxgv\" align=\"right\">15.82</td><td class=\"dxgv\" align=\"right\">22.33</td><td class=\"dxgv\" align=\"right\">24.75</td><td class=\"dxgv\" align=\"right\">24.74</td><td class=\"dxgv\" align=\"right\">24.75</td><td class=\"dxgv\" align=\"right\">24.70</td><td class=\"dxgv\" align=\"right\">21.61</td><td class=\"dxgv\" align=\"right\">14.77</td><td class=\"dxgv\" align=\"right\">9.68</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow76\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp78\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,78,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: ENERGIA RENOVABLE BAS </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow79\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO WASHINGTON CAPITAL 3</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">7.86</td><td class=\"dxgv\" align=\"right\">7.67</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow78\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp80\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,80,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: ENREN </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow81\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO CALABAZA</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.07</td><td class=\"dxgv\" align=\"right\">13.05</td><td class=\"dxgv\" align=\"right\">25.65</td><td class=\"dxgv\" align=\"right\">33.80</td><td class=\"dxgv\" align=\"right\">40.60</td><td class=\"dxgv\" align=\"right\">42.99</td><td class=\"dxgv\" align=\"right\">42.33</td><td class=\"dxgv\" align=\"right\">36.85</td><td class=\"dxgv\" align=\"right\">32.08</td><td class=\"dxgv\" align=\"right\">21.56</td><td class=\"dxgv\" align=\"right\">13.78</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow80\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp82\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,82,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: KOROR BUSINESS, S.R.L. </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow83\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE SOLAR EL SOCO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.48</td><td class=\"dxgv\" align=\"right\">15.53</td><td class=\"dxgv\" align=\"right\">34.57</td><td class=\"dxgv\" align=\"right\">45.51</td><td class=\"dxgv\" align=\"right\">37.87</td><td class=\"dxgv\" align=\"right\">35.09</td><td class=\"dxgv\" align=\"right\">37.81</td><td class=\"dxgv\" align=\"right\">39.00</td><td class=\"dxgv\" align=\"right\">39.53</td><td class=\"dxgv\" align=\"right\">23.36</td><td class=\"dxgv\" align=\"right\">17.07</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow82\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp84\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,84,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: MARANATHA </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow85\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO MARANATHA FASE I</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.94</td><td class=\"dxgv\" align=\"right\">4.02</td><td class=\"dxgv\" align=\"right\">4.43</td><td class=\"dxgv\" align=\"right\">4.02</td><td class=\"dxgv\" align=\"right\">4.90</td><td class=\"dxgv\" align=\"right\">5.58</td><td class=\"dxgv\" align=\"right\">6.49</td><td class=\"dxgv\" align=\"right\">5.09</td><td class=\"dxgv\" align=\"right\">3.14</td><td class=\"dxgv\" align=\"right\">2.16</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow84\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp86\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,86,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: MATRISOL, S.A.S. </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow87\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO MATRISOL</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">6.33</td><td class=\"dxgv\" align=\"right\">17.72</td><td class=\"dxgv\" align=\"right\">12.69</td><td class=\"dxgv\" align=\"right\">32.48</td><td class=\"dxgv\" align=\"right\">26.16</td><td class=\"dxgv\" align=\"right\">17.60</td><td class=\"dxgv\" align=\"right\">20.65</td><td class=\"dxgv\" align=\"right\">13.56</td><td class=\"dxgv\" align=\"right\">13.22</td><td class=\"dxgv\" align=\"right\">10.05</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow86\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp88\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,88,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: MONTECRISTI SOLAR </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow89\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO MONTECRISTI SOLAR 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">0.51</td><td class=\"dxgv\" align=\"right\">5.88</td><td class=\"dxgv\" align=\"right\">22.88</td><td class=\"dxgv\" align=\"right\">20.37</td><td class=\"dxgv\" align=\"right\">29.28</td><td class=\"dxgv\" align=\"right\">31.19</td><td class=\"dxgv\" align=\"right\">28.83</td><td class=\"dxgv\" align=\"right\">36.86</td><td class=\"dxgv\" align=\"right\">30.75</td><td class=\"dxgv\" align=\"right\">20.61</td><td class=\"dxgv\" align=\"right\">13.21</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow88\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp90\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,90,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: PHINIE &amp; CO DEVELOPMENT S.R.L.  </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow91\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO LOS NEGROS</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">0.55</td><td class=\"dxgv\" align=\"right\">4.53</td><td class=\"dxgv\" align=\"right\">9.62</td><td class=\"dxgv\" align=\"right\">11.95</td><td class=\"dxgv\" align=\"right\">15.15</td><td class=\"dxgv\" align=\"right\">16.89</td><td class=\"dxgv\" align=\"right\">16.74</td><td class=\"dxgv\" align=\"right\">15.10</td><td class=\"dxgv\" align=\"right\">11.86</td><td class=\"dxgv\" align=\"right\">7.53</td><td class=\"dxgv\" align=\"right\">4.60</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow90\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp92\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,92,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: WCG </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow93\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO MATA DE PALMA</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">1.51</td><td class=\"dxgv\" align=\"right\">13.70</td><td class=\"dxgv\" align=\"right\">27.22</td><td class=\"dxgv\" align=\"right\">35.09</td><td class=\"dxgv\" align=\"right\">44.61</td><td class=\"dxgv\" align=\"right\">43.61</td><td class=\"dxgv\" align=\"right\">45.24</td><td class=\"dxgv\" align=\"right\">40.52</td><td class=\"dxgv\" align=\"right\">34.09</td><td class=\"dxgv\" align=\"right\">21.00</td><td class=\"dxgv\" align=\"right\">13.40</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow92\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp94\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,94,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: WCGF SOLAR II </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow95\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE FOTOVOLTAICO WASHINGTON CAPITAL 2</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">7.86</td><td class=\"dxgv\" align=\"right\">7.67</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow94\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow60\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0\" style=\"border-left-width:0px;border-right-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp96\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,96,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"26\" style=\"border-right-width:0px;\">GRUPO: T&#233;rmica </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp97\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,97,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: AES ANDRES </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow98\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">AES ANDR&#201;S FO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow99\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">AES ANDR&#201;S GN</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow97\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp100\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,100,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: BERSAL </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow101\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">BERSAL</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow100\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp102\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,102,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: CESPM </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow103\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">CESPM 1 FO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow104\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">CESPM 1 GN</td><td class=\"dxgv\" align=\"right\">87.26</td><td class=\"dxgv\" align=\"right\">87.28</td><td class=\"dxgv\" align=\"right\">86.56</td><td class=\"dxgv\" align=\"right\">87.15</td><td class=\"dxgv\" align=\"right\">87.02</td><td class=\"dxgv\" align=\"right\">87.32</td><td class=\"dxgv\" align=\"right\">87.25</td><td class=\"dxgv\" align=\"right\">87.07</td><td class=\"dxgv\" align=\"right\">78.96</td><td class=\"dxgv\" align=\"right\">74.45</td><td class=\"dxgv\" align=\"right\">66.97</td><td class=\"dxgv\" align=\"right\">69.53</td><td class=\"dxgv\" align=\"right\">70.42</td><td class=\"dxgv\" align=\"right\">70.41</td><td class=\"dxgv\" align=\"right\">75.70</td><td class=\"dxgv\" align=\"right\">72.16</td><td class=\"dxgv\" align=\"right\">80.07</td><td class=\"dxgv\" align=\"right\">79.60</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow105\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">CESPM 2 FO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow106\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">CESPM 2 GN</td><td class=\"dxgv\" align=\"right\">85.13</td><td class=\"dxgv\" align=\"right\">85.83</td><td class=\"dxgv\" align=\"right\">85.84</td><td class=\"dxgv\" align=\"right\">85.82</td><td class=\"dxgv\" align=\"right\">85.63</td><td class=\"dxgv\" align=\"right\">85.25</td><td class=\"dxgv\" align=\"right\">84.93</td><td class=\"dxgv\" align=\"right\">85.09</td><td class=\"dxgv\" align=\"right\">77.29</td><td class=\"dxgv\" align=\"right\">70.47</td><td class=\"dxgv\" align=\"right\">66.79</td><td class=\"dxgv\" align=\"right\">69.65</td><td class=\"dxgv\" align=\"right\">69.66</td><td class=\"dxgv\" align=\"right\">69.82</td><td class=\"dxgv\" align=\"right\">74.90</td><td class=\"dxgv\" align=\"right\">73.13</td><td class=\"dxgv\" align=\"right\">78.62</td><td class=\"dxgv\" align=\"right\">77.76</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow107\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">CESPM 3 FO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow108\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">CESPM 3 GN</td><td class=\"dxgv\" align=\"right\">86.94</td><td class=\"dxgv\" align=\"right\">86.95</td><td class=\"dxgv\" align=\"right\">86.85</td><td class=\"dxgv\" align=\"right\">86.77</td><td class=\"dxgv\" align=\"right\">86.63</td><td class=\"dxgv\" align=\"right\">86.92</td><td class=\"dxgv\" align=\"right\">86.86</td><td class=\"dxgv\" align=\"right\">86.69</td><td class=\"dxgv\" align=\"right\">82.98</td><td class=\"dxgv\" align=\"right\">72.84</td><td class=\"dxgv\" align=\"right\">66.83</td><td class=\"dxgv\" align=\"right\">69.58</td><td class=\"dxgv\" align=\"right\">69.08</td><td class=\"dxgv\" align=\"right\">69.66</td><td class=\"dxgv\" align=\"right\">73.90</td><td class=\"dxgv\" align=\"right\">72.75</td><td class=\"dxgv\" align=\"right\">79.49</td><td class=\"dxgv\" align=\"right\">79.17</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow102\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp109\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,109,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: DESABASTECIMIENTO </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow110\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SENI</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow109\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp111\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,111,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: DOMICEM GENERACI&#211;N </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow112\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PALENQUE</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow111\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp113\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,113,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: DPP </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow114\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LOS MINA 5</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow115\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LOS MINA 6</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow116\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE ENERGETICO LOS MINA CC PARCIAL</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow117\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PARQUE ENERGETICO LOS MINA CC TOTAL</td><td class=\"dxgv\" align=\"right\">274.05</td><td class=\"dxgv\" align=\"right\">276.04</td><td class=\"dxgv\" align=\"right\">259.14</td><td class=\"dxgv\" align=\"right\">244.62</td><td class=\"dxgv\" align=\"right\">209.84</td><td class=\"dxgv\" align=\"right\">263.57</td><td class=\"dxgv\" align=\"right\">287.57</td><td class=\"dxgv\" align=\"right\">262.62</td><td class=\"dxgv\" align=\"right\">232.02</td><td class=\"dxgv\" align=\"right\">194.18</td><td class=\"dxgv\" align=\"right\">190.44</td><td class=\"dxgv\" align=\"right\">200.43</td><td class=\"dxgv\" align=\"right\">200.26</td><td class=\"dxgv\" align=\"right\">200.70</td><td class=\"dxgv\" align=\"right\">234.53</td><td class=\"dxgv\" align=\"right\">217.83</td><td class=\"dxgv\" align=\"right\">258.43</td><td class=\"dxgv\" align=\"right\">254.73</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow113\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp118\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,118,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: EGEHAINA </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow119\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">BARAHONA CARB&#211;N</td><td class=\"dxgv\" align=\"right\">50.62</td><td class=\"dxgv\" align=\"right\">50.05</td><td class=\"dxgv\" align=\"right\">48.91</td><td class=\"dxgv\" align=\"right\">48.70</td><td class=\"dxgv\" align=\"right\">48.00</td><td class=\"dxgv\" align=\"right\">48.65</td><td class=\"dxgv\" align=\"right\">50.09</td><td class=\"dxgv\" align=\"right\">47.79</td><td class=\"dxgv\" align=\"right\">48.96</td><td class=\"dxgv\" align=\"right\">36.05</td><td class=\"dxgv\" align=\"right\">33.07</td><td class=\"dxgv\" align=\"right\">32.78</td><td class=\"dxgv\" align=\"right\">32.57</td><td class=\"dxgv\" align=\"right\">32.50</td><td class=\"dxgv\" align=\"right\">32.07</td><td class=\"dxgv\" align=\"right\">32.58</td><td class=\"dxgv\" align=\"right\">40.06</td><td class=\"dxgv\" align=\"right\">50.58</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow120\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">HAINA TG</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow121\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">QUISQUEYA 2 FO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow122\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">QUISQUEYA 2 GN</td><td class=\"dxgv\" align=\"right\">182.32</td><td class=\"dxgv\" align=\"right\">191.93</td><td class=\"dxgv\" align=\"right\">164.66</td><td class=\"dxgv\" align=\"right\">119.23</td><td class=\"dxgv\" align=\"right\">177.45</td><td class=\"dxgv\" align=\"right\">180.05</td><td class=\"dxgv\" align=\"right\">183.30</td><td class=\"dxgv\" align=\"right\">161.46</td><td class=\"dxgv\" align=\"right\">120.65</td><td class=\"dxgv\" align=\"right\">82.43</td><td class=\"dxgv\" align=\"right\">66.44</td><td class=\"dxgv\" align=\"right\">70.69</td><td class=\"dxgv\" align=\"right\">69.71</td><td class=\"dxgv\" align=\"right\">70.17</td><td class=\"dxgv\" align=\"right\">73.26</td><td class=\"dxgv\" align=\"right\">72.71</td><td class=\"dxgv\" align=\"right\">136.05</td><td class=\"dxgv\" align=\"right\">137.70</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow123\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SULTANA DEL ESTE</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow118\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp124\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,124,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: EGEITABO </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow125\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ITABO 1</td><td class=\"dxgv\" align=\"right\">105.28</td><td class=\"dxgv\" align=\"right\">105.08</td><td class=\"dxgv\" align=\"right\">105.38</td><td class=\"dxgv\" align=\"right\">105.88</td><td class=\"dxgv\" align=\"right\">106.62</td><td class=\"dxgv\" align=\"right\">105.09</td><td class=\"dxgv\" align=\"right\">104.51</td><td class=\"dxgv\" align=\"right\">103.82</td><td class=\"dxgv\" align=\"right\">105.20</td><td class=\"dxgv\" align=\"right\">105.16</td><td class=\"dxgv\" align=\"right\">95.48</td><td class=\"dxgv\" align=\"right\">94.28</td><td class=\"dxgv\" align=\"right\">95.90</td><td class=\"dxgv\" align=\"right\">96.03</td><td class=\"dxgv\" align=\"right\">98.66</td><td class=\"dxgv\" align=\"right\">103.45</td><td class=\"dxgv\" align=\"right\">104.33</td><td class=\"dxgv\" align=\"right\">104.79</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow126\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ITABO 2</td><td class=\"dxgv\" align=\"right\">125.77</td><td class=\"dxgv\" align=\"right\">125.72</td><td class=\"dxgv\" align=\"right\">126.37</td><td class=\"dxgv\" align=\"right\">126.45</td><td class=\"dxgv\" align=\"right\">125.05</td><td class=\"dxgv\" align=\"right\">124.68</td><td class=\"dxgv\" align=\"right\">124.09</td><td class=\"dxgv\" align=\"right\">122.29</td><td class=\"dxgv\" align=\"right\">120.58</td><td class=\"dxgv\" align=\"right\">121.60</td><td class=\"dxgv\" align=\"right\">108.29</td><td class=\"dxgv\" align=\"right\">102.37</td><td class=\"dxgv\" align=\"right\">99.95</td><td class=\"dxgv\" align=\"right\">102.50</td><td class=\"dxgv\" align=\"right\">108.68</td><td class=\"dxgv\" align=\"right\">120.49</td><td class=\"dxgv\" align=\"right\">125.26</td><td class=\"dxgv\" align=\"right\">125.40</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow127\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SAN LORENZO 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow124\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp128\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,128,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: EMPRESA DE GENERACI&#211;N EL&#201;CTRICA PUNTA CATALINA </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow129\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PUNTA CATALINA 1</td><td class=\"dxgv\" align=\"right\">345.24</td><td class=\"dxgv\" align=\"right\">344.72</td><td class=\"dxgv\" align=\"right\">343.59</td><td class=\"dxgv\" align=\"right\">343.63</td><td class=\"dxgv\" align=\"right\">340.66</td><td class=\"dxgv\" align=\"right\">337.80</td><td class=\"dxgv\" align=\"right\">341.24</td><td class=\"dxgv\" align=\"right\">337.65</td><td class=\"dxgv\" align=\"right\">338.39</td><td class=\"dxgv\" align=\"right\">340.15</td><td class=\"dxgv\" align=\"right\">342.00</td><td class=\"dxgv\" align=\"right\">338.50</td><td class=\"dxgv\" align=\"right\">338.87</td><td class=\"dxgv\" align=\"right\">340.61</td><td class=\"dxgv\" align=\"right\">341.25</td><td class=\"dxgv\" align=\"right\">342.91</td><td class=\"dxgv\" align=\"right\">343.24</td><td class=\"dxgv\" align=\"right\">341.73</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow130\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PUNTA CATALINA 2</td><td class=\"dxgv\" align=\"right\">364.13</td><td class=\"dxgv\" align=\"right\">361.49</td><td class=\"dxgv\" align=\"right\">361.27</td><td class=\"dxgv\" align=\"right\">360.59</td><td class=\"dxgv\" align=\"right\">360.43</td><td class=\"dxgv\" align=\"right\">361.35</td><td class=\"dxgv\" align=\"right\">360.96</td><td class=\"dxgv\" align=\"right\">360.58</td><td class=\"dxgv\" align=\"right\">360.32</td><td class=\"dxgv\" align=\"right\">359.24</td><td class=\"dxgv\" align=\"right\">322.37</td><td class=\"dxgv\" align=\"right\">292.49</td><td class=\"dxgv\" align=\"right\">285.83</td><td class=\"dxgv\" align=\"right\">286.55</td><td class=\"dxgv\" align=\"right\">312.10</td><td class=\"dxgv\" align=\"right\">357.07</td><td class=\"dxgv\" align=\"right\">361.12</td><td class=\"dxgv\" align=\"right\">360.94</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow128\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp131\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,131,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: GPLV </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow132\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LA VEGA</td><td class=\"dxgv\" align=\"right\">19.70</td><td class=\"dxgv\" align=\"right\">53.48</td><td class=\"dxgv\" align=\"right\">65.18</td><td class=\"dxgv\" align=\"right\">65.34</td><td class=\"dxgv\" align=\"right\">49.05</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow133\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PALAMARA</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">54.56</td><td class=\"dxgv\" align=\"right\">69.97</td><td class=\"dxgv\" align=\"right\">16.50</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow131\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp134\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,134,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: KARPOWERSHIP DOMINICAN REPUBLIC, S.A.S. </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow135\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">POWERSHIP AZUA KPS 26</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow136\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">POWERSHIP AZUA KPS 60</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow134\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp137\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,137,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: LAESA LTD </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow138\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PIMENTEL 1</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow139\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PIMENTEL 2</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow140\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PIMENTEL 3</td><td class=\"dxgv\" align=\"right\">16.65</td><td class=\"dxgv\" align=\"right\">16.64</td><td class=\"dxgv\" align=\"right\">26.83</td><td class=\"dxgv\" align=\"right\">6.97</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">2.09</td><td class=\"dxgv\" align=\"right\">30.44</td><td class=\"dxgv\" align=\"right\">24.67</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow141\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">PIMENTEL 4</td><td class=\"dxgv\" align=\"right\">18.14</td><td class=\"dxgv\" align=\"right\">18.11</td><td class=\"dxgv\" align=\"right\">18.13</td><td class=\"dxgv\" align=\"right\">18.13</td><td class=\"dxgv\" align=\"right\">18.13</td><td class=\"dxgv\" align=\"right\">18.13</td><td class=\"dxgv\" align=\"right\">18.13</td><td class=\"dxgv\" align=\"right\">18.13</td><td class=\"dxgv\" align=\"right\">18.13</td><td class=\"dxgv\" align=\"right\">18.13</td><td class=\"dxgv\" align=\"right\">9.55</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">5.17</td><td class=\"dxgv\" align=\"right\">18.14</td><td class=\"dxgv\" align=\"right\">18.13</td><td class=\"dxgv\" align=\"right\">18.11</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow137\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp142\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,142,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: LEAR </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow143\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">MONTE R&#205;O</td><td class=\"dxgv\" align=\"right\">89.29</td><td class=\"dxgv\" align=\"right\">89.32</td><td class=\"dxgv\" align=\"right\">89.29</td><td class=\"dxgv\" align=\"right\">89.25</td><td class=\"dxgv\" align=\"right\">89.24</td><td class=\"dxgv\" align=\"right\">52.71</td><td class=\"dxgv\" align=\"right\">72.21</td><td class=\"dxgv\" align=\"right\">89.31</td><td class=\"dxgv\" align=\"right\">18.47</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">3.82</td><td class=\"dxgv\" align=\"right\">41.55</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow142\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp144\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,144,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: LOS ORIGENES </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow145\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LOS OR&#205;GENES POWER PLANT FUEL OIL</td><td class=\"dxgv\" align=\"right\">30.88</td><td class=\"dxgv\" align=\"right\">30.84</td><td class=\"dxgv\" align=\"right\">29.58</td><td class=\"dxgv\" align=\"right\">26.92</td><td class=\"dxgv\" align=\"right\">19.13</td><td class=\"dxgv\" align=\"right\">15.93</td><td class=\"dxgv\" align=\"right\">15.72</td><td class=\"dxgv\" align=\"right\">26.34</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow146\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">LOS OR&#205;GENES POWER PLANT GAS NATURAL</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow144\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp147\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,147,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: METALDOM </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow148\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">METALDOM</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow147\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp149\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,149,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: MONTE RIO LTD </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow150\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">INCA KM22</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow149\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp151\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,151,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: PVDC </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow152\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">QUISQUEYA 1 FO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow153\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">QUISQUEYA 1 GN</td><td class=\"dxgv\" align=\"right\">132.31</td><td class=\"dxgv\" align=\"right\">123.71</td><td class=\"dxgv\" align=\"right\">117.72</td><td class=\"dxgv\" align=\"right\">117.03</td><td class=\"dxgv\" align=\"right\">115.01</td><td class=\"dxgv\" align=\"right\">132.43</td><td class=\"dxgv\" align=\"right\">132.30</td><td class=\"dxgv\" align=\"right\">131.48</td><td class=\"dxgv\" align=\"right\">124.43</td><td class=\"dxgv\" align=\"right\">82.08</td><td class=\"dxgv\" align=\"right\">81.95</td><td class=\"dxgv\" align=\"right\">85.98</td><td class=\"dxgv\" align=\"right\">87.61</td><td class=\"dxgv\" align=\"right\">87.45</td><td class=\"dxgv\" align=\"right\">99.01</td><td class=\"dxgv\" align=\"right\">94.30</td><td class=\"dxgv\" align=\"right\">108.48</td><td class=\"dxgv\" align=\"right\">120.78</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow154\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">QUISQUEYA 1 SAN PEDRO FO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow155\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">QUISQUEYA 1 SAN PEDRO GN</td><td class=\"dxgv\" align=\"right\">66.60</td><td class=\"dxgv\" align=\"right\">66.69</td><td class=\"dxgv\" align=\"right\">66.30</td><td class=\"dxgv\" align=\"right\">65.96</td><td class=\"dxgv\" align=\"right\">65.77</td><td class=\"dxgv\" align=\"right\">66.67</td><td class=\"dxgv\" align=\"right\">66.61</td><td class=\"dxgv\" align=\"right\">66.15</td><td class=\"dxgv\" align=\"right\">56.02</td><td class=\"dxgv\" align=\"right\">39.27</td><td class=\"dxgv\" align=\"right\">10.38</td><td class=\"dxgv\" align=\"right\">11.03</td><td class=\"dxgv\" align=\"right\">10.70</td><td class=\"dxgv\" align=\"right\">10.40</td><td class=\"dxgv\" align=\"right\">14.51</td><td class=\"dxgv\" align=\"right\">47.66</td><td class=\"dxgv\" align=\"right\">53.25</td><td class=\"dxgv\" align=\"right\">60.91</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow151\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp156\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,156,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: SAN FELIPE </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow157\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SAN FELIPE</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow158\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SAN FELIPE CC</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow159\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SAN FELIPE VAP</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow156\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp160\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,160,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: SAN PEDRO BIO-ENERGY </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow161\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SAN PEDRO BIO-ENERGY</td><td class=\"dxgv\" align=\"right\">30.02</td><td class=\"dxgv\" align=\"right\">30.05</td><td class=\"dxgv\" align=\"right\">30.10</td><td class=\"dxgv\" align=\"right\">30.10</td><td class=\"dxgv\" align=\"right\">29.72</td><td class=\"dxgv\" align=\"right\">30.06</td><td class=\"dxgv\" align=\"right\">28.46</td><td class=\"dxgv\" align=\"right\">28.87</td><td class=\"dxgv\" align=\"right\">27.89</td><td class=\"dxgv\" align=\"right\">25.67</td><td class=\"dxgv\" align=\"right\">27.27</td><td class=\"dxgv\" align=\"right\">29.75</td><td class=\"dxgv\" align=\"right\">29.78</td><td class=\"dxgv\" align=\"right\">29.91</td><td class=\"dxgv\" align=\"right\">30.00</td><td class=\"dxgv\" align=\"right\">28.99</td><td class=\"dxgv\" align=\"right\">29.19</td><td class=\"dxgv\" align=\"right\">30.09</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow160\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp162\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,162,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: SEABOARD </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow163\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ESTRELLA DEL MAR 2 CFO</td><td class=\"dxgv\" align=\"right\">103.93</td><td class=\"dxgv\" align=\"right\">97.89</td><td class=\"dxgv\" align=\"right\">86.22</td><td class=\"dxgv\" align=\"right\">95.52</td><td class=\"dxgv\" align=\"right\">93.19</td><td class=\"dxgv\" align=\"right\">103.58</td><td class=\"dxgv\" align=\"right\">103.46</td><td class=\"dxgv\" align=\"right\">100.15</td><td class=\"dxgv\" align=\"right\">73.84</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">12.33</td><td class=\"dxgv\" align=\"right\">75.60</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow164\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ESTRELLA DEL MAR 2 CGN</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow165\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ESTRELLA DEL MAR 2 SFO</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow166\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ESTRELLA DEL MAR 2 SGN</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow167\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ESTRELLA DEL MAR 3 CCP</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow168\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ESTRELLA DEL MAR 3 CCT</td><td class=\"dxgv\" align=\"right\">148.37</td><td class=\"dxgv\" align=\"right\">140.78</td><td class=\"dxgv\" align=\"right\">107.75</td><td class=\"dxgv\" align=\"right\">148.81</td><td class=\"dxgv\" align=\"right\">148.90</td><td class=\"dxgv\" align=\"right\">149.06</td><td class=\"dxgv\" align=\"right\">149.39</td><td class=\"dxgv\" align=\"right\">149.66</td><td class=\"dxgv\" align=\"right\">149.98</td><td class=\"dxgv\" align=\"right\">101.53</td><td class=\"dxgv\" align=\"right\">97.47</td><td class=\"dxgv\" align=\"right\">97.50</td><td class=\"dxgv\" align=\"right\">97.53</td><td class=\"dxgv\" align=\"right\">97.46</td><td class=\"dxgv\" align=\"right\">97.43</td><td class=\"dxgv\" align=\"right\">97.45</td><td class=\"dxgv\" align=\"right\">128.94</td><td class=\"dxgv\" align=\"right\">144.77</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow169\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">ESTRELLA DEL MAR 3 CS</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow162\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp170\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,170,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: SIBA </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow171\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">SIBA</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow170\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow96\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0\" style=\"border-left-width:0px;border-right-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp172\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,172,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"26\" style=\"border-right-width:0px;\">GRUPO: Totales </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGroupRowExp173\" class=\"dxgvGroupRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0.1%\" style=\"border-right-width:0px;border-bottom-width:0px;\"><img class=\"dxGridView_gvExpandedButton_Office2010Blue\" onclick=\"ASPx.GVCollapseRow(&#39;PostdespachoUnidadesTermicasGrid&#39;,173,event);event.cancelBubble = true\" src=\"/ReportesGraficos/DXR.axd?r=1_112-7ufgi\" alt=\"[Contraer]\" style=\"cursor:pointer;\" /></td><td class=\"dxgv\" colspan=\"25\" style=\"border-right-width:0px;\">EMPRESA: Total </td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow174\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Total T&#233;rmico</td><td class=\"dxgv\" align=\"right\">2362.63</td><td class=\"dxgv\" align=\"right\">2382.69</td><td class=\"dxgv\" align=\"right\">2360.23</td><td class=\"dxgv\" align=\"right\">2342.84</td><td class=\"dxgv\" align=\"right\">2271.97</td><td class=\"dxgv\" align=\"right\">2249.70</td><td class=\"dxgv\" align=\"right\">2297.08</td><td class=\"dxgv\" align=\"right\">2265.15</td><td class=\"dxgv\" align=\"right\">2034.11</td><td class=\"dxgv\" align=\"right\">1723.25</td><td class=\"dxgv\" align=\"right\">1585.30</td><td class=\"dxgv\" align=\"right\">1564.56</td><td class=\"dxgv\" align=\"right\">1557.87</td><td class=\"dxgv\" align=\"right\">1564.17</td><td class=\"dxgv\" align=\"right\">1671.17</td><td class=\"dxgv\" align=\"right\">1753.71</td><td class=\"dxgv\" align=\"right\">1991.26</td><td class=\"dxgv\" align=\"right\">2129.13</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow175\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Total E&#243;lico</td><td class=\"dxgv\" align=\"right\">67.41</td><td class=\"dxgv\" align=\"right\">63.28</td><td class=\"dxgv\" align=\"right\">59.08</td><td class=\"dxgv\" align=\"right\">28.35</td><td class=\"dxgv\" align=\"right\">18.76</td><td class=\"dxgv\" align=\"right\">13.52</td><td class=\"dxgv\" align=\"right\">10.79</td><td class=\"dxgv\" align=\"right\">9.91</td><td class=\"dxgv\" align=\"right\">8.68</td><td class=\"dxgv\" align=\"right\">5.94</td><td class=\"dxgv\" align=\"right\">8.79</td><td class=\"dxgv\" align=\"right\">16.17</td><td class=\"dxgv\" align=\"right\">33.40</td><td class=\"dxgv\" align=\"right\">49.56</td><td class=\"dxgv\" align=\"right\">74.53</td><td class=\"dxgv\" align=\"right\">83.42</td><td class=\"dxgv\" align=\"right\">75.95</td><td class=\"dxgv\" align=\"right\">63.48</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow176\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Total Solar</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">23.90</td><td class=\"dxgv\" align=\"right\">251.22</td><td class=\"dxgv\" align=\"right\">527.22</td><td class=\"dxgv\" align=\"right\">612.36</td><td class=\"dxgv\" align=\"right\">653.86</td><td class=\"dxgv\" align=\"right\">679.36</td><td class=\"dxgv\" align=\"right\">695.16</td><td class=\"dxgv\" align=\"right\">676.98</td><td class=\"dxgv\" align=\"right\">599.58</td><td class=\"dxgv\" align=\"right\">446.65</td><td class=\"dxgv\" align=\"right\">279.41</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow177\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Total Hidroel&#233;ctrica</td><td class=\"dxgv\" align=\"right\">292.13</td><td class=\"dxgv\" align=\"right\">165.37</td><td class=\"dxgv\" align=\"right\">120.85</td><td class=\"dxgv\" align=\"right\">73.40</td><td class=\"dxgv\" align=\"right\">84.89</td><td class=\"dxgv\" align=\"right\">84.63</td><td class=\"dxgv\" align=\"right\">92.43</td><td class=\"dxgv\" align=\"right\">114.06</td><td class=\"dxgv\" align=\"right\">72.41</td><td class=\"dxgv\" align=\"right\">67.23</td><td class=\"dxgv\" align=\"right\">65.77</td><td class=\"dxgv\" align=\"right\">58.30</td><td class=\"dxgv\" align=\"right\">54.27</td><td class=\"dxgv\" align=\"right\">42.51</td><td class=\"dxgv\" align=\"right\">42.39</td><td class=\"dxgv\" align=\"right\">42.53</td><td class=\"dxgv\" align=\"right\">78.93</td><td class=\"dxgv\" align=\"right\">128.41</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow178\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Total Generado</td><td class=\"dxgv\" align=\"right\">2722.17</td><td class=\"dxgv\" align=\"right\">2611.34</td><td class=\"dxgv\" align=\"right\">2540.16</td><td class=\"dxgv\" align=\"right\">2444.59</td><td class=\"dxgv\" align=\"right\">2375.62</td><td class=\"dxgv\" align=\"right\">2347.91</td><td class=\"dxgv\" align=\"right\">2400.36</td><td class=\"dxgv\" align=\"right\">2413.02</td><td class=\"dxgv\" align=\"right\">2366.42</td><td class=\"dxgv\" align=\"right\">2323.64</td><td class=\"dxgv\" align=\"right\">2272.22</td><td class=\"dxgv\" align=\"right\">2292.89</td><td class=\"dxgv\" align=\"right\">2324.90</td><td class=\"dxgv\" align=\"right\">2351.40</td><td class=\"dxgv\" align=\"right\">2465.07</td><td class=\"dxgv\" align=\"right\">2479.24</td><td class=\"dxgv\" align=\"right\">2592.79</td><td class=\"dxgv\" align=\"right\">2600.43</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow179\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Total Programado</td><td class=\"dxgv\" align=\"right\">2722.03</td><td class=\"dxgv\" align=\"right\">2635.83</td><td class=\"dxgv\" align=\"right\">2561.04</td><td class=\"dxgv\" align=\"right\">2504.38</td><td class=\"dxgv\" align=\"right\">2459.50</td><td class=\"dxgv\" align=\"right\">2445.73</td><td class=\"dxgv\" align=\"right\">2443.09</td><td class=\"dxgv\" align=\"right\">2473.60</td><td class=\"dxgv\" align=\"right\">2504.92</td><td class=\"dxgv\" align=\"right\">2443.79</td><td class=\"dxgv\" align=\"right\">2453.26</td><td class=\"dxgv\" align=\"right\">2462.51</td><td class=\"dxgv\" align=\"right\">2575.37</td><td class=\"dxgv\" align=\"right\">2635.77</td><td class=\"dxgv\" align=\"right\">2737.52</td><td class=\"dxgv\" align=\"right\">2833.52</td><td class=\"dxgv\" align=\"right\">2874.20</td><td class=\"dxgv\" align=\"right\">2845.87</td><td class=\"dxgv\" align=\"right\">2909.05</td><td class=\"dxgv\" align=\"right\">3003.88</td><td class=\"dxgv\" align=\"right\">2991.32</td><td class=\"dxgv\" align=\"right\">2935.66</td><td class=\"dxgv\" align=\"right\">2890.41</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">2813.34</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow180\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Disponibilidad Real Sinc.</td><td class=\"dxgv\" align=\"right\">3557.90</td><td class=\"dxgv\" align=\"right\">3299.37</td><td class=\"dxgv\" align=\"right\">3222.17</td><td class=\"dxgv\" align=\"right\">3168.44</td><td class=\"dxgv\" align=\"right\">3167.85</td><td class=\"dxgv\" align=\"right\">3172.57</td><td class=\"dxgv\" align=\"right\">3214.94</td><td class=\"dxgv\" align=\"right\">3277.90</td><td class=\"dxgv\" align=\"right\">3475.99</td><td class=\"dxgv\" align=\"right\">3709.25</td><td class=\"dxgv\" align=\"right\">3797.24</td><td class=\"dxgv\" align=\"right\">3836.62</td><td class=\"dxgv\" align=\"right\">3879.35</td><td class=\"dxgv\" align=\"right\">3894.51</td><td class=\"dxgv\" align=\"right\">3909.20</td><td class=\"dxgv\" align=\"right\">3839.49</td><td class=\"dxgv\" align=\"right\">3752.89</td><td class=\"dxgv\" align=\"right\">3587.28</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow181\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Disponibilidad Real</td><td class=\"dxgv\" align=\"right\">3557.90</td><td class=\"dxgv\" align=\"right\">3299.37</td><td class=\"dxgv\" align=\"right\">3222.17</td><td class=\"dxgv\" align=\"right\">3168.44</td><td class=\"dxgv\" align=\"right\">3167.85</td><td class=\"dxgv\" align=\"right\">3172.57</td><td class=\"dxgv\" align=\"right\">3214.94</td><td class=\"dxgv\" align=\"right\">3277.90</td><td class=\"dxgv\" align=\"right\">3475.99</td><td class=\"dxgv\" align=\"right\">3709.25</td><td class=\"dxgv\" align=\"right\">3797.24</td><td class=\"dxgv\" align=\"right\">3836.62</td><td class=\"dxgv\" align=\"right\">3879.35</td><td class=\"dxgv\" align=\"right\">3894.51</td><td class=\"dxgv\" align=\"right\">3909.20</td><td class=\"dxgv\" align=\"right\">3839.49</td><td class=\"dxgv\" align=\"right\">3752.89</td><td class=\"dxgv\" align=\"right\">3587.28</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow182\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Consumo</td><td class=\"dxgv\" align=\"right\">196.58</td><td class=\"dxgv\" align=\"right\">174.72</td><td class=\"dxgv\" align=\"right\">163.10</td><td class=\"dxgv\" align=\"right\">162.96</td><td class=\"dxgv\" align=\"right\">152.44</td><td class=\"dxgv\" align=\"right\">155.56</td><td class=\"dxgv\" align=\"right\">165.49</td><td class=\"dxgv\" align=\"right\">162.26</td><td class=\"dxgv\" align=\"right\">164.70</td><td class=\"dxgv\" align=\"right\">156.78</td><td class=\"dxgv\" align=\"right\">151.89</td><td class=\"dxgv\" align=\"right\">155.41</td><td class=\"dxgv\" align=\"right\">152.96</td><td class=\"dxgv\" align=\"right\">153.74</td><td class=\"dxgv\" align=\"right\">157.17</td><td class=\"dxgv\" align=\"right\">163.35</td><td class=\"dxgv\" align=\"right\">169.93</td><td class=\"dxgv\" align=\"right\">172.30</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow183\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Potencia No Servida</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">121.37</td><td class=\"dxgv\" align=\"right\">142.92</td><td class=\"dxgv\" align=\"right\">143.50</td><td class=\"dxgv\" align=\"right\">146.85</td><td class=\"dxgv\" align=\"right\">128.45</td><td class=\"dxgv\" align=\"right\">127.29</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow184\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Reserva Caliente</td><td class=\"dxgv\" align=\"right\">248.62</td><td class=\"dxgv\" align=\"right\">259.74</td><td class=\"dxgv\" align=\"right\">235.05</td><td class=\"dxgv\" align=\"right\">268.07</td><td class=\"dxgv\" align=\"right\">296.86</td><td class=\"dxgv\" align=\"right\">250.47</td><td class=\"dxgv\" align=\"right\">141.32</td><td class=\"dxgv\" align=\"right\">188.89</td><td class=\"dxgv\" align=\"right\">390.17</td><td class=\"dxgv\" align=\"right\">460.81</td><td class=\"dxgv\" align=\"right\">600.19</td><td class=\"dxgv\" align=\"right\">598.85</td><td class=\"dxgv\" align=\"right\">609.54</td><td class=\"dxgv\" align=\"right\">598.89</td><td class=\"dxgv\" align=\"right\">509.06</td><td class=\"dxgv\" align=\"right\">462.93</td><td class=\"dxgv\" align=\"right\">567.98</td><td class=\"dxgv\" align=\"right\">346.00</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXDataRow185\" class=\"dxgvDataRow_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dx-nowrap dxgv\" style=\"border-left-width:0px;\">Reserva Fria</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\">&nbsp;</td><td class=\"dxgv\" align=\"right\" style=\"border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow173\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-right-width:0px;\">&nbsp;</td>\n\t\t\t</tr><tr id=\"PostdespachoUnidadesTermicasGrid_DXGFRow172\" class=\"dxgvGroupFooter_Office2010Blue\">\n\t\t\t\t<td class=\"dxgvIndentCell dxgv\" width=\"0\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" width=\"0\" style=\"border-left-width:0px;border-right-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"border-left-width:0px;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" style=\"text-align:Right;border-bottom-width:0px;\">&nbsp;</td><td class=\"dxgv\" 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    "content": "{\n  \"response\": {\n    \"total\": 25,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2020-01-06T06\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -329,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T07\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -323,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T08\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -375,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T09\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -372,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T10\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -394,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T11\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -349,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T12\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -451,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T13\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -679,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T14\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -620,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T15\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -540,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T16\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -489,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T17\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -478,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T18\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -501,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T19\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -492,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T20\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -460,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T21\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -418,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T22\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -314,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T23\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -360,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T00\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -351,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T01\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -300,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T02\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -281,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T03\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -320,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T04\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -342,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T05\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -341,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T06\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"FPL\",\n        \"toba-name\": \"Florida Power & Light Co.\",\n        \"value\": -368,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Daily interchange between neighboring balancing authorities.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"request\": {\n    \"command\": \"/v2/electricity/rto/interchange-data/data/\",\n    \"params\": {\n      \"data\": [\"value\"],\n      \"facets\": { \"fromba\": [\"FPC\"], \"toba\": [\"FPL\"] },\n      \"frequency\": \"hourly\",\n      \"api_key\": \"e36b66258fd3e86e1be559504a49b3cf\",\n      \"start\": \"2020-01-06T06\",\n      \"end\": \"2020-01-07T06\"\n    }\n  },\n  \"apiVersion\": \"2.1.4\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US-FLA-FPC_US-FLA-NSB_exchange.json",
    "content": "{\n  \"response\": {\n    \"total\": 25,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2020-01-06T06\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 16,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T07\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 17,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T08\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 16,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T09\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 17,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T10\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 17,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T11\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 21,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T12\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 27,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T13\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 28,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T14\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 20,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T15\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 17,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T16\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 18,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T17\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 16,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T18\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 16,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T19\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 14,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T20\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 14,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T21\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 11,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T22\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 7,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-06T23\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 8,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T00\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission 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\"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T04\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 6,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T05\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 7,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2020-01-07T06\",\n        \"fromba\": \"FPC\",\n        \"fromba-name\": \"Duke Energy Florida, Inc.\",\n        \"toba\": \"NSB\",\n        \"toba-name\": \"Utilities Commission of New Smyrna Beach\",\n        \"value\": 4,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Daily interchange between neighboring balancing authorities.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"request\": {\n    \"command\": \"/v2/electricity/rto/interchange-data/data/\",\n    \"params\": {\n      \"data\": [\"value\"],\n      \"facets\": { \"fromba\": [\"FPC\"], \"toba\": [\"NSB\"] },\n      \"frequency\": \"hourly\",\n      \"api_key\": \"e36b66258fd3e86e1be559504a49b3cf\",\n      \"start\": \"2020-01-06T06\",\n      \"end\": \"2020-01-07T06\"\n    }\n  },\n  \"apiVersion\": \"2.1.4\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US-NW-BPAT-US-NW-NWMT-exchange.json",
    "content": "{\n  \"response\": {\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2022-02-28T23\",\n        \"fromba\": \"SWPP\",\n        \"fromba-name\": \"Southwest Power Pool\",\n        \"toba\": \"SPC\",\n        \"toba-name\": \"Saskatchewan Power Corporation\",\n        \"value\": -12,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2022-03-01T00\",\n        \"fromba\": \"SWPP\",\n        \"fromba-name\": \"Southwest Power Pool\",\n        \"toba\": \"SPC\",\n        \"toba-name\": \"Saskatchewan Power Corporation\",\n        \"value\": -11,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2022-03-01T01\",\n        \"fromba\": \"SWPP\",\n        \"fromba-name\": \"Southwest Power Pool\",\n        \"toba\": \"SPC\",\n        \"toba-name\": \"Saskatchewan Power Corporation\",\n        \"value\": -2,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Daily interchange between neighboring balancing authorities.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.1.4\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US-NW-PGE-with-nulls.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.008633325,\n    \"count query execution\": 0.021634831,\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2022-10-31T11\",\n        \"respondent\": \"PGE\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"NG\",\n        \"type-name\": \"Natural gas\",\n        \"value\": null,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2022-10-31T12\",\n        \"respondent\": \"PGE\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"NG\",\n        \"type-name\": \"Natural gas\",\n        \"value\": 400,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_CAL_IID-battery_storage.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.008633325,\n    \"count query execution\": 0.021634831,\n    \"total\": 1,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2024-02-27T11\",\n        \"respondent\": \"EIA\",\n        \"respondent-name\": \"ACME corp\",\n        \"fueltype\": \"BAT\",\n        \"type-name\": \"Battery storage\",\n        \"value\": 1,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_CAR_SC-nuclear.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.02875779,\n    \"count query execution\": 0.045858883,\n    \"total\": 0,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_CAR_SCEG-nuclear.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.013917043,\n    \"count query execution\": 0.013379965,\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2022-10-31T11\",\n        \"respondent\": \"SCEG\",\n        \"respondent-name\": \"Dominion Energy South Carolina, Inc.\",\n        \"fueltype\": \"NUC\",\n        \"type-name\": \"Nuclear\",\n        \"value\": 992,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2022-10-31T12\",\n        \"respondent\": \"SCEG\",\n        \"respondent-name\": \"Dominion Energy South Carolina, Inc.\",\n        \"fueltype\": \"NUC\",\n        \"type-name\": \"Nuclear\",\n        \"value\": 991,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_NW_AVRN-gas.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.008633325,\n    \"count query execution\": 0.021634831,\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2022-10-31T11\",\n        \"respondent\": \"AVRN\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"NG\",\n        \"type-name\": \"Natural gas\",\n        \"value\": 300,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2022-10-31T12\",\n        \"respondent\": \"AVRN\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"NG\",\n        \"type-name\": \"Natural gas\",\n        \"value\": 400,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_NW_AVRN-other.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.008633325,\n    \"count query execution\": 0.021634831,\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_NW_AVRN-wind.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.008633325,\n    \"count query execution\": 0.021634831,\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2022-10-31T11\",\n        \"respondent\": \"AVRN\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"WIN\",\n        \"type-name\": \"Wind\",\n        \"value\": 1,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2022-10-31T12\",\n        \"respondent\": \"AVRN\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"WIN\",\n        \"type-name\": \"Wind\",\n        \"value\": 2,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_NW_BPAT-consumption.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.008633325,\n    \"count query execution\": 0.021634831,\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2023-05-01T11\",\n        \"respondent\": \"BPAT\",\n        \"respondent-name\": \"Bonneville Power Administration\",\n        \"type\": \"D\",\n        \"type-name\": \"Demand\",\n        \"value\": 6215,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2023-05-01T10\",\n        \"respondent\": \"BPAT\",\n        \"respondent-name\": \"Bonneville Power Administration\",\n        \"type\": \"D\",\n        \"type-name\": \"Demand\",\n        \"value\": 4792,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_NW_BPAT-wind.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.008633325,\n    \"count query execution\": 0.021634831,\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2022-10-31T11\",\n        \"respondent\": \"BPAT\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"WIND\",\n        \"type-name\": \"Wind\",\n        \"value\": 20,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2022-10-31T12\",\n        \"respondent\": \"BPAT\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"WIND\",\n        \"type-name\": \"Wind\",\n        \"value\": 40,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_NW_PACW-gas.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.008633325,\n    \"count query execution\": 0.021634831,\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2022-10-31T11\",\n        \"respondent\": \"PACW\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"NG\",\n        \"type-name\": \"Natural gas\",\n        \"value\": 30,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2022-10-31T12\",\n        \"respondent\": \"PACW\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"NG\",\n        \"type-name\": \"Natural gas\",\n        \"value\": 50,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/EIA/US_SMTH-coal.json",
    "content": "{\n  \"response\": {\n    \"query execution\": 0.008633325,\n    \"count query execution\": 0.021634831,\n    \"total\": 3,\n    \"dateFormat\": \"YYYY-MM-DD\\\"T\\\"HH24\",\n    \"frequency\": \"hourly\",\n    \"data\": [\n      {\n        \"period\": \"2022-10-31T11\",\n        \"respondent\": \"AVRN\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"COAL\",\n        \"type-name\": \"Natural gas\",\n        \"value\": 300,\n        \"value-units\": \"megawatthours\"\n      },\n      {\n        \"period\": \"2022-10-31T12\",\n        \"respondent\": \"AVRN\",\n        \"respondent-name\": \"Avangrid Renewables, LLC\",\n        \"fueltype\": \"COAL\",\n        \"type-name\": \"Natural gas\",\n        \"value\": 400,\n        \"value-units\": \"megawatthours\"\n      }\n    ],\n    \"description\": \"Hourly net generation by balancing authority and energy source.  \\n    Source: Form EIA-930\\n    Product: Hourly Electric Grid Monitor\"\n  },\n  \"apiVersion\": \"2.0.3\"\n}\n"
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<quantity>880</quantity>\n      </Point>\n      <Point>\n        <position>31</position>\n        <quantity>880</quantity>\n      </Point>\n      <Point>\n        <position>32</position>\n        <quantity>880</quantity>\n      </Point>\n      <Point>\n        <position>33</position>\n        <quantity>1706</quantity>\n      </Point>\n      <Point>\n        <position>34</position>\n        <quantity>1706</quantity>\n      </Point>\n      <Point>\n        <position>35</position>\n        <quantity>1706</quantity>\n      </Point>\n      <Point>\n        <position>36</position>\n        <quantity>1706</quantity>\n      </Point>\n      <Point>\n        <position>37</position>\n        <quantity>1815</quantity>\n      </Point>\n      <Point>\n        <position>38</position>\n        <quantity>1815</quantity>\n      </Point>\n      <Point>\n        <position>39</position>\n        <quantity>1815</quantity>\n      </Point>\n      <Point>\n        <position>40</position>\n        <quantity>1815</quantity>\n      </Point>\n      <Point>\n        <position>41</position>\n        <quantity>1576</quantity>\n      </Point>\n      <Point>\n        <position>42</position>\n        <quantity>1576</quantity>\n      </Point>\n      <Point>\n        <position>43</position>\n        <quantity>1576</quantity>\n      </Point>\n      <Point>\n        <position>44</position>\n        <quantity>1576</quantity>\n      </Point>\n      <Point>\n        <position>45</position>\n        <quantity>1478</quantity>\n      </Point>\n      <Point>\n        <position>46</position>\n        <quantity>1478</quantity>\n      </Point>\n      <Point>\n        <position>47</position>\n        <quantity>1478</quantity>\n      </Point>\n      <Point>\n        <position>48</position>\n        <quantity>1478</quantity>\n      </Point>\n      <Point>\n        <position>49</position>\n        <quantity>1312</quantity>\n      </Point>\n      <Point>\n        <position>50</position>\n        <quantity>1312</quantity>\n      </Point>\n      <Point>\n        <position>51</position>\n        <quantity>1312</quantity>\n      </Point>\n      <Point>\n        <position>52</position>\n        <quantity>1312</quantity>\n      </Point>\n      <Point>\n        <position>53</position>\n        <quantity>1227</quantity>\n      </Point>\n      <Point>\n        <position>54</position>\n        <quantity>1227</quantity>\n      </Point>\n      <Point>\n        <position>55</position>\n        <quantity>1227</quantity>\n      </Point>\n      <Point>\n        <position>56</position>\n        <quantity>1227</quantity>\n      </Point>\n      <Point>\n        <position>57</position>\n        <quantity>1111</quantity>\n      </Point>\n      <Point>\n        <position>58</position>\n        <quantity>1111</quantity>\n      </Point>\n      <Point>\n        <position>59</position>\n        <quantity>1111</quantity>\n      </Point>\n      <Point>\n        <position>60</position>\n        <quantity>1111</quantity>\n      </Point>\n      <Point>\n        <position>61</position>\n        <quantity>1388</quantity>\n      </Point>\n      <Point>\n        <position>62</position>\n        <quantity>1388</quantity>\n      </Point>\n      <Point>\n        <position>63</position>\n        <quantity>1388</quantity>\n      </Point>\n      <Point>\n        <position>64</position>\n        <quantity>1388</quantity>\n      </Point>\n      <Point>\n        <position>65</position>\n        <quantity>1571</quantity>\n      </Point>\n      <Point>\n        <position>66</position>\n        <quantity>1571</quantity>\n      </Point>\n      <Point>\n        <position>67</position>\n        <quantity>1571</quantity>\n      </Point>\n      <Point>\n        <position>68</position>\n        <quantity>1571</quantity>\n      </Point>\n      <Point>\n        <position>69</position>\n        <quantity>1205</quantity>\n      </Point>\n      <Point>\n        <position>70</position>\n        <quantity>1205</quantity>\n      </Point>\n      <Point>\n        <position>71</position>\n        <quantity>1205</quantity>\n      </Point>\n      <Point>\n        <position>72</position>\n        <quantity>1205</quantity>\n      </Point>\n      <Point>\n        <position>73</position>\n        <quantity>1244</quantity>\n      </Point>\n      <Point>\n        <position>74</position>\n        <quantity>1244</quantity>\n      </Point>\n      <Point>\n        <position>75</position>\n        <quantity>1244</quantity>\n      </Point>\n      <Point>\n        <position>76</position>\n        <quantity>1244</quantity>\n      </Point>\n      <Point>\n        <position>77</position>\n        <quantity>1438</quantity>\n      </Point>\n      <Point>\n        <position>78</position>\n        <quantity>1438</quantity>\n      </Point>\n      <Point>\n        <position>79</position>\n        <quantity>1438</quantity>\n      </Point>\n      <Point>\n        <position>80</position>\n        <quantity>1438</quantity>\n      </Point>\n      <Point>\n        <position>81</position>\n        <quantity>1682</quantity>\n      </Point>\n      <Point>\n        <position>82</position>\n        <quantity>1682</quantity>\n      </Point>\n      <Point>\n        <position>83</position>\n        <quantity>1682</quantity>\n      </Point>\n      <Point>\n        <position>84</position>\n        <quantity>1682</quantity>\n      </Point>\n      <Point>\n        <position>85</position>\n        <quantity>2038</quantity>\n      </Point>\n      <Point>\n        <position>86</position>\n        <quantity>2038</quantity>\n      </Point>\n      <Point>\n        <position>87</position>\n        <quantity>2038</quantity>\n      </Point>\n      <Point>\n        <position>88</position>\n        <quantity>2038</quantity>\n      </Point>\n      <Point>\n        <position>89</position>\n        <quantity>1067</quantity>\n      </Point>\n      <Point>\n        <position>90</position>\n        <quantity>1067</quantity>\n      </Point>\n      <Point>\n        <position>91</position>\n        <quantity>1067</quantity>\n      </Point>\n      <Point>\n        <position>92</position>\n        <quantity>1067</quantity>\n      </Point>\n      <Point>\n        <position>93</position>\n        <quantity>1039</quantity>\n      </Point>\n      <Point>\n        <position>94</position>\n        <quantity>1039</quantity>\n      </Point>\n      <Point>\n        <position>95</position>\n        <quantity>1039</quantity>\n      </Point>\n      <Point>\n        <position>96</position>\n        <quantity>1039</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <TimeSeries>\n    <mRID>6</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10YBE----------2</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10YNL----------L</out_Domain.mRID>\n    <contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-25T23:00Z</start>\n        <end>2024-03-26T23:00Z</end>\n      </timeInterval>\n      <resolution>PT15M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>899</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>899</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>899</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>899</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>799</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>799</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>799</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>799</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>743</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>743</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>743</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>743</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>883</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>883</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>883</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>883</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>822</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>822</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>822</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>822</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>997</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>997</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>997</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>997</quantity>\n      </Point>\n      <Point>\n        <position>25</position>\n        <quantity>1189</quantity>\n      </Point>\n      <Point>\n        <position>26</position>\n        <quantity>1189</quantity>\n      </Point>\n      <Point>\n        <position>27</position>\n        <quantity>1189</quantity>\n      </Point>\n      <Point>\n        <position>28</position>\n        <quantity>1189</quantity>\n      </Point>\n      <Point>\n        <position>29</position>\n        <quantity>915</quantity>\n      </Point>\n      <Point>\n        <position>30</position>\n        <quantity>915</quantity>\n      </Point>\n      <Point>\n        <position>31</position>\n        <quantity>915</quantity>\n      </Point>\n      <Point>\n        <position>32</position>\n        <quantity>915</quantity>\n      </Point>\n      <Point>\n        <position>33</position>\n        <quantity>1899</quantity>\n      </Point>\n      <Point>\n        <position>34</position>\n        <quantity>1899</quantity>\n      </Point>\n      <Point>\n        <position>35</position>\n        <quantity>1899</quantity>\n      </Point>\n      <Point>\n        <position>36</position>\n        <quantity>1899</quantity>\n      </Point>\n      <Point>\n        <position>37</position>\n        <quantity>1227</quantity>\n      </Point>\n      <Point>\n        <position>38</position>\n        <quantity>1227</quantity>\n      </Point>\n      <Point>\n        <position>39</position>\n        <quantity>1227</quantity>\n      </Point>\n      <Point>\n        <position>40</position>\n        <quantity>1227</quantity>\n      </Point>\n      <Point>\n        <position>41</position>\n        <quantity>1368</quantity>\n      </Point>\n      <Point>\n        <position>42</position>\n        <quantity>1368</quantity>\n      </Point>\n      <Point>\n        <position>43</position>\n        <quantity>1368</quantity>\n      </Point>\n      <Point>\n        <position>44</position>\n        <quantity>1368</quantity>\n      </Point>\n      <Point>\n        <position>45</position>\n        <quantity>1762</quantity>\n      </Point>\n      <Point>\n        <position>46</position>\n        <quantity>1762</quantity>\n      </Point>\n      <Point>\n        <position>47</position>\n        <quantity>1762</quantity>\n      </Point>\n      <Point>\n        <position>48</position>\n        <quantity>1762</quantity>\n      </Point>\n      <Point>\n        <position>49</position>\n        <quantity>1756</quantity>\n      </Point>\n      <Point>\n        <position>50</position>\n        <quantity>1756</quantity>\n      </Point>\n      <Point>\n        <position>51</position>\n        <quantity>1756</quantity>\n      </Point>\n      <Point>\n        <position>52</position>\n        <quantity>1756</quantity>\n      </Point>\n      <Point>\n        <position>53</position>\n        <quantity>1755</quantity>\n      </Point>\n      <Point>\n        <position>54</position>\n        <quantity>1755</quantity>\n      </Point>\n      <Point>\n        <position>55</position>\n        <quantity>1755</quantity>\n      </Point>\n      <Point>\n        <position>56</position>\n        <quantity>1755</quantity>\n      </Point>\n      <Point>\n        <position>57</position>\n        <quantity>1172</quantity>\n      </Point>\n      <Point>\n        <position>58</position>\n        <quantity>1172</quantity>\n      </Point>\n      <Point>\n        <position>59</position>\n        <quantity>1172</quantity>\n      </Point>\n      <Point>\n        <position>60</position>\n        <quantity>1172</quantity>\n      </Point>\n      <Point>\n        <position>61</position>\n        <quantity>1378</quantity>\n      </Point>\n      <Point>\n        <position>62</position>\n        <quantity>1378</quantity>\n      </Point>\n      <Point>\n        <position>63</position>\n        <quantity>1378</quantity>\n      </Point>\n      <Point>\n        <position>64</position>\n        <quantity>1378</quantity>\n      </Point>\n      <Point>\n        <position>65</position>\n        <quantity>1341</quantity>\n      </Point>\n      <Point>\n        <position>66</position>\n        <quantity>1341</quantity>\n      </Point>\n      <Point>\n        <position>67</position>\n        <quantity>1341</quantity>\n      </Point>\n      <Point>\n        <position>68</position>\n        <quantity>1341</quantity>\n      </Point>\n      <Point>\n        <position>69</position>\n        <quantity>1124</quantity>\n      </Point>\n      <Point>\n        <position>70</position>\n        <quantity>1124</quantity>\n      </Point>\n      <Point>\n        <position>71</position>\n        <quantity>1124</quantity>\n      </Point>\n      <Point>\n        <position>72</position>\n        <quantity>1124</quantity>\n      </Point>\n      <Point>\n        <position>73</position>\n        <quantity>1275</quantity>\n      </Point>\n      <Point>\n        <position>74</position>\n        <quantity>1275</quantity>\n      </Point>\n      <Point>\n        <position>75</position>\n        <quantity>1275</quantity>\n      </Point>\n      <Point>\n        <position>76</position>\n        <quantity>1275</quantity>\n      </Point>\n      <Point>\n        <position>77</position>\n        <quantity>1387</quantity>\n      </Point>\n      <Point>\n        <position>78</position>\n        <quantity>1387</quantity>\n      </Point>\n      <Point>\n        <position>79</position>\n        <quantity>1387</quantity>\n      </Point>\n      <Point>\n        <position>80</position>\n        <quantity>1387</quantity>\n      </Point>\n      <Point>\n        <position>81</position>\n        <quantity>1249</quantity>\n      </Point>\n      <Point>\n        <position>82</position>\n        <quantity>1249</quantity>\n      </Point>\n      <Point>\n        <position>83</position>\n        <quantity>1249</quantity>\n      </Point>\n      <Point>\n        <position>84</position>\n        <quantity>1249</quantity>\n      </Point>\n      <Point>\n        <position>85</position>\n        <quantity>1477</quantity>\n      </Point>\n      <Point>\n        <position>86</position>\n        <quantity>1477</quantity>\n      </Point>\n      <Point>\n        <position>87</position>\n        <quantity>1477</quantity>\n      </Point>\n      <Point>\n        <position>88</position>\n        <quantity>1477</quantity>\n      </Point>\n      <Point>\n        <position>89</position>\n        <quantity>950</quantity>\n      </Point>\n      <Point>\n        <position>90</position>\n        <quantity>950</quantity>\n      </Point>\n      <Point>\n        <position>91</position>\n        <quantity>950</quantity>\n      </Point>\n      <Point>\n        <position>92</position>\n        <quantity>950</quantity>\n      </Point>\n      <Point>\n        <position>93</position>\n        <quantity>815</quantity>\n      </Point>\n      <Point>\n        <position>94</position>\n        <quantity>815</quantity>\n      </Point>\n      <Point>\n        <position>95</position>\n        <quantity>815</quantity>\n      </Point>\n      <Point>\n        <position>96</position>\n        <quantity>815</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/DK-DK1_DK-DK2_capacity_week_ahead_export.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n  <mRID>ac334bcb95c74ca3a62770164b30ce4e</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A61</type>\n  <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2026-03-19T08:29:55Z</createdDateTime>\n  <period.timeInterval>\n    <start>2026-02-16T23:00Z</start>\n    <end>2026-03-29T22:00Z</end>\n  </period.timeInterval>\n      <TimeSeries>\n        <mRID>1</mRID>\n        <businessType>A27</businessType>\n        <in_Domain.mRID codingScheme=\"A01\">10YDK-1--------W</in_Domain.mRID>\n        <out_Domain.mRID codingScheme=\"A01\">10YDK-2--------M</out_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A03</curveType>\n            <Period>\n              <timeInterval>\n                <start>2026-02-16T23:00Z</start>\n                <end>2026-03-29T22:00Z</end>\n              </timeInterval>\n              <resolution>P1D</resolution>\n                  <Point>\n                    <position>1</position>\n                    <quantity>600</quantity>\n                  </Point>\n            </Period>\n      </TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/DK-DK1_DK-DK2_capacity_week_ahead_import.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n  <mRID>b5f2ad979ab24a1f85d9439a207834e7</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A61</type>\n  <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2026-03-19T08:39:18Z</createdDateTime>\n  <period.timeInterval>\n    <start>2026-02-16T23:00Z</start>\n    <end>2026-03-29T22:00Z</end>\n  </period.timeInterval>\n      <TimeSeries>\n        <mRID>1</mRID>\n        <businessType>A27</businessType>\n        <in_Domain.mRID codingScheme=\"A01\">10YDK-2--------M</in_Domain.mRID>\n        <out_Domain.mRID codingScheme=\"A01\">10YDK-1--------W</out_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A03</curveType>\n            <Period>\n              <timeInterval>\n                <start>2026-02-16T23:00Z</start>\n                <end>2026-03-29T22:00Z</end>\n              </timeInterval>\n              <resolution>P1D</resolution>\n                  <Point>\n                    <position>1</position>\n                    <quantity>450</quantity>\n                  </Point>\n            </Period>\n      </TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/DK-DK1_GB_exchange_exports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>dceac22608ba4d82adab1f0e9e6d9b63</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A11</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-22T17:25:00Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-20T17:00Z</start>\n\t\t<end>2023-12-23T00:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A66</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10YGB----------A</in_Domain.mRID>\n\t\t<out_Domain.mRID 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codingScheme=\"A01\">10YGB----------A</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10YDK-1--------W</out_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-22T09:00Z</start>\n\t\t\t\t\t<end>2023-12-22T11:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>1</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>1</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>3</mRID>\n\t\t<businessType>A66</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10YGB----------A</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10YDK-1--------W</out_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-22T13:00Z</start>\n\t\t\t\t\t<end>2023-12-22T16:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/DK-DK1_GB_exchange_imports.xml",
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codingScheme=\"A01\">10YDK-1--------W</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10YGB----------A</out_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-20T17:00Z</start>\n\t\t\t\t\t<end>2023-12-22T08:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>38</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>710</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>732</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>1382</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>1400</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>1402</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>1406</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>1366</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>25</position>\n\t\t\t\t\t\t<quantity>1326</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>26</position>\n\t\t\t\t\t\t<quantity>96</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>27</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>28</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>29</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>30</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>31</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>32</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>33</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>34</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>35</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>36</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>37</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>38</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>39</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>2</mRID>\n\t\t<businessType>A66</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10YDK-1--------W</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10YGB----------A</out_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-22T09:00Z</start>\n\t\t\t\t\t<end>2023-12-22T11:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>3</mRID>\n\t\t<businessType>A66</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10YDK-1--------W</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10YGB----------A</out_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-22T13:00Z</start>\n\t\t\t\t\t<end>2023-12-22T16:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>2</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/DK-DK1_consumption.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<GL_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-6:generationloaddocument:3:0\">\n    <mRID>7b654895c4364b56830be98c45fea709</mRID>\n    <revisionNumber>1</revisionNumber>\n    <type>A65</type>\n    <process.processType>A16</process.processType>\n    <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n    <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n    <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n    <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n    <createdDateTime>2023-12-30T15:03:18Z</createdDateTime>\n    <time_Period.timeInterval>\n        <start>2023-12-28T15:00Z</start>\n        <end>2023-12-31T00:00Z</end>\n    </time_Period.timeInterval>\n    <TimeSeries>\n        <mRID>1</mRID>\n        <businessType>A04</businessType>\n        <objectAggregation>A01</objectAggregation>\n        <outBiddingZone_Domain.mRID codingScheme=\"A01\">10YDK-1--------W</outBiddingZone_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A01</curveType>\n        <Period>\n            <timeInterval>\n                <start>2023-12-28T15:00Z</start>\n                <end>2023-12-30T14:00Z</end>\n            </timeInterval>\n            <resolution>PT60M</resolution>\n            <Point>\n                <position>1</position>\n                <quantity>3031</quantity>\n            </Point>\n            <Point>\n                <position>2</position>\n                <quantity>3152</quantity>\n            </Point>\n            <Point>\n                <position>3</position>\n                <quantity>3069</quantity>\n            </Point>\n            <Point>\n                <position>4</position>\n                <quantity>2918</quantity>\n            </Point>\n            <Point>\n                <position>5</position>\n                <quantity>2818</quantity>\n            </Point>\n            <Point>\n                <position>6</position>\n                <quantity>2756</quantity>\n            </Point>\n            <Point>\n                <position>7</position>\n                <quantity>2685</quantity>\n            </Point>\n            <Point>\n                <position>8</position>\n                <quantity>2693</quantity>\n            </Point>\n            <Point>\n                <position>9</position>\n                <quantity>2693</quantity>\n            </Point>\n            <Point>\n                <position>10</position>\n                <quantity>2617</quantity>\n            </Point>\n            <Point>\n                <position>11</position>\n                <quantity>2522</quantity>\n            </Point>\n            <Point>\n                <position>12</position>\n                <quantity>2554</quantity>\n            </Point>\n            <Point>\n                <position>13</position>\n                <quantity>2493</quantity>\n            </Point>\n            <Point>\n                <position>14</position>\n                <quantity>2501</quantity>\n            </Point>\n            <Point>\n                <position>15</position>\n                <quantity>2576</quantity>\n            </Point>\n            <Point>\n                <position>16</position>\n                <quantity>2769</quantity>\n            </Point>\n            <Point>\n                <position>17</position>\n                <quantity>2960</quantity>\n            </Point>\n            <Point>\n                <position>18</position>\n                <quantity>2998</quantity>\n            </Point>\n            <Point>\n                <position>19</position>\n                <quantity>3042</quantity>\n            </Point>\n            <Point>\n                <position>20</position>\n                <quantity>3115</quantity>\n            </Point>\n            <Point>\n                <position>21</position>\n                <quantity>3087</quantity>\n            </Point>\n            <Point>\n                <position>22</position>\n                <quantity>3085</quantity>\n            </Point>\n            <Point>\n                <position>23</position>\n                <quantity>3018</quantity>\n            </Point>\n            <Point>\n                <position>24</position>\n                <quantity>2913</quantity>\n            </Point>\n            <Point>\n                <position>25</position>\n                <quantity>2990</quantity>\n            </Point>\n            <Point>\n                <position>26</position>\n                <quantity>3117</quantity>\n            </Point>\n            <Point>\n                <position>27</position>\n                <quantity>2938</quantity>\n            </Point>\n            <Point>\n                <position>28</position>\n                <quantity>2817</quantity>\n            </Point>\n            <Point>\n                <position>29</position>\n                <quantity>2662</quantity>\n            </Point>\n            <Point>\n                <position>30</position>\n                <quantity>2575</quantity>\n            </Point>\n            <Point>\n                <position>31</position>\n                <quantity>2467</quantity>\n            </Point>\n            <Point>\n                <position>32</position>\n                <quantity>2399</quantity>\n            </Point>\n            <Point>\n                <position>33</position>\n                <quantity>2300</quantity>\n            </Point>\n            <Point>\n                <position>34</position>\n                <quantity>2379</quantity>\n            </Point>\n            <Point>\n                <position>35</position>\n                <quantity>2339</quantity>\n            </Point>\n            <Point>\n                <position>36</position>\n                <quantity>2290</quantity>\n            </Point>\n            <Point>\n                <position>37</position>\n                <quantity>2346</quantity>\n            </Point>\n            <Point>\n                <position>38</position>\n                <quantity>2390</quantity>\n            </Point>\n            <Point>\n                <position>39</position>\n                <quantity>2399</quantity>\n            </Point>\n            <Point>\n                <position>40</position>\n                <quantity>2491</quantity>\n            </Point>\n            <Point>\n                <position>41</position>\n                <quantity>2644</quantity>\n            </Point>\n            <Point>\n                <position>42</position>\n                <quantity>2731</quantity>\n            </Point>\n            <Point>\n                <position>43</position>\n                <quantity>2753</quantity>\n            </Point>\n            <Point>\n                <position>44</position>\n                <quantity>2785</quantity>\n            </Point>\n            <Point>\n                <position>45</position>\n                <quantity>2772</quantity>\n            </Point>\n            <Point>\n                <position>46</position>\n                <quantity>2759</quantity>\n            </Point>\n            <Point>\n                <position>47</position>\n                <quantity>2723</quantity>\n            </Point>\n        </Period>\n    </TimeSeries>\n</GL_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/DK-DK2_SE-SE4_exchange_forecast_exports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>193626fb23784ea4a5dfaa40d3014339</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A09</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-23T12:28:54Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-20T23:00Z</start>\n\t\t<end>2023-12-24T23:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A47J</in_Domain.mRID>\n\t\t<out_Domain.mRID 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codingScheme=\"A01\">10YDK-2--------M</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-20T23:00Z</start>\n\t\t\t\t\t<end>2023-12-21T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>770</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>805</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>685</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>714</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>775</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>853</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>931</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>913</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>714</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>808</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>817</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>753</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>805</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>846</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>899</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>835</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>734</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>533</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>14</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>377</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>556</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>6</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A47J</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10YDK-2--------M</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-22T23:00Z</start>\n\t\t\t\t\t<end>2023-12-23T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>585</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>1093</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>1192</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>1240</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>1407</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>1465</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>1529</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>1464</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>1413</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>320</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>1398</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>1118</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>93</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/DK-DK2_SE-SE4_exchange_forecast_imports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>98c8dff04ecc45dba48ea39fb0f1adb8</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A09</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-23T12:28:53Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-20T23:00Z</start>\n\t\t<end>2023-12-24T23:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10YDK-2--------M</in_Domain.mRID>\n\t\t<out_Domain.mRID 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codingScheme=\"A01\">10YDK-2--------M</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A47J</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-22T23:00Z</start>\n\t\t\t\t\t<end>2023-12-23T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>1092</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>1170</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>555</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>239</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>1261</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>1261</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>723</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>1174</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>724</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>253</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>322</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/DK-DK2_consumption_forecast.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<GL_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-6:generationloaddocument:3:0\">\n    <mRID>69c589a77c1a4c3c971c1a994bbe8e7a</mRID>\n    <revisionNumber>1</revisionNumber>\n    <type>A65</type>\n    <process.processType>A01</process.processType>\n    <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n    <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n    <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n    <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n    <createdDateTime>2023-12-30T15:04:26Z</createdDateTime>\n    <time_Period.timeInterval>\n        <start>2023-12-27T23:00Z</start>\n        <end>2023-12-31T23:00Z</end>\n    </time_Period.timeInterval>\n    <TimeSeries>\n        <mRID>1</mRID>\n        <businessType>A04</businessType>\n        <objectAggregation>A01</objectAggregation>\n        <outBiddingZone_Domain.mRID codingScheme=\"A01\">10YDK-2--------M</outBiddingZone_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A01</curveType>\n        <Period>\n            <timeInterval>\n                <start>2023-12-27T23:00Z</start>\n                <end>2023-12-28T23:00Z</end>\n            </timeInterval>\n            <resolution>PT60M</resolution>\n            <Point>\n                <position>1</position>\n                <quantity>1554</quantity>\n            </Point>\n            <Point>\n                <position>2</position>\n                <quantity>1530</quantity>\n            </Point>\n            <Point>\n                <position>3</position>\n                <quantity>1485</quantity>\n            </Point>\n            <Point>\n                <position>4</position>\n                <quantity>1464</quantity>\n            </Point>\n            <Point>\n                <position>5</position>\n                <quantity>1411</quantity>\n            </Point>\n            <Point>\n                <position>6</position>\n                <quantity>1418</quantity>\n            </Point>\n            <Point>\n                <position>7</position>\n                <quantity>1476</quantity>\n            </Point>\n            <Point>\n                <position>8</position>\n                <quantity>1574</quantity>\n            </Point>\n            <Point>\n                <position>9</position>\n                <quantity>1700</quantity>\n            </Point>\n            <Point>\n                <position>10</position>\n                <quantity>1755</quantity>\n            </Point>\n            <Point>\n                <position>11</position>\n                <quantity>1836</quantity>\n            </Point>\n            <Point>\n                <position>12</position>\n                <quantity>1872</quantity>\n            </Point>\n            <Point>\n                <position>13</position>\n                <quantity>1847</quantity>\n            </Point>\n            <Point>\n                <position>14</position>\n                <quantity>1845</quantity>\n            </Point>\n            <Point>\n                <position>15</position>\n                <quantity>1841</quantity>\n            </Point>\n            <Point>\n                <position>16</position>\n                <quantity>1847</quantity>\n            </Point>\n            <Point>\n                <position>17</position>\n                <quantity>1901</quantity>\n            </Point>\n            <Point>\n                <position>18</position>\n                <quantity>1962</quantity>\n            </Point>\n            <Point>\n                <position>19</position>\n                <quantity>1924</quantity>\n            </Point>\n            <Point>\n                <position>20</position>\n                <quantity>1835</quantity>\n            </Point>\n            <Point>\n                <position>21</position>\n                <quantity>1763</quantity>\n            </Point>\n            <Point>\n                <position>22</position>\n                <quantity>1680</quantity>\n            </Point>\n            <Point>\n                <position>23</position>\n                <quantity>1601</quantity>\n            </Point>\n            <Point>\n                <position>24</position>\n                <quantity>1552</quantity>\n            </Point>\n        </Period>\n    </TimeSeries>\n    <TimeSeries>\n        <mRID>2</mRID>\n        <businessType>A04</businessType>\n        <objectAggregation>A01</objectAggregation>\n        <outBiddingZone_Domain.mRID codingScheme=\"A01\">10YDK-2--------M</outBiddingZone_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A01</curveType>\n        <Period>\n            <timeInterval>\n                <start>2023-12-28T23:00Z</start>\n                <end>2023-12-29T23:00Z</end>\n            </timeInterval>\n            <resolution>PT60M</resolution>\n            <Point>\n                <position>1</position>\n                <quantity>1454</quantity>\n            </Point>\n            <Point>\n                <position>2</position>\n                <quantity>1418</quantity>\n            </Point>\n            <Point>\n                <position>3</position>\n                <quantity>1391</quantity>\n            </Point>\n            <Point>\n                <position>4</position>\n                <quantity>1382</quantity>\n            </Point>\n            <Point>\n                <position>5</position>\n                <quantity>1363</quantity>\n            </Point>\n            <Point>\n                <position>6</position>\n                <quantity>1348</quantity>\n            </Point>\n            <Point>\n                <position>7</position>\n                <quantity>1447</quantity>\n            </Point>\n            <Point>\n                <position>8</position>\n                <quantity>1587</quantity>\n            </Point>\n            <Point>\n                <position>9</position>\n                <quantity>1704</quantity>\n            </Point>\n            <Point>\n                <position>10</position>\n                <quantity>1764</quantity>\n            </Point>\n            <Point>\n                <position>11</position>\n                <quantity>1810</quantity>\n            </Point>\n            <Point>\n                <position>12</position>\n                <quantity>1806</quantity>\n            </Point>\n            <Point>\n                <position>13</position>\n                <quantity>1809</quantity>\n            </Point>\n            <Point>\n                <position>14</position>\n                <quantity>1814</quantity>\n            </Point>\n            <Point>\n                <position>15</position>\n                <quantity>1801</quantity>\n            </Point>\n            <Point>\n                <position>16</position>\n                <quantity>1821</quantity>\n            </Point>\n            <Point>\n                <position>17</position>\n                <quantity>1883</quantity>\n            </Point>\n            <Point>\n                <position>18</position>\n                <quantity>1932</quantity>\n            </Point>\n            <Point>\n                <position>19</position>\n                <quantity>1903</quantity>\n            </Point>\n            <Point>\n                <position>20</position>\n                <quantity>1828</quantity>\n            </Point>\n            <Point>\n                <position>21</position>\n                <quantity>1739</quantity>\n            </Point>\n            <Point>\n                <position>22</position>\n                <quantity>1655</quantity>\n            </Point>\n            <Point>\n                <position>23</position>\n                <quantity>1536</quantity>\n            </Point>\n            <Point>\n                <position>24</position>\n                <quantity>1435</quantity>\n            </Point>\n        </Period>\n    </TimeSeries>\n    <TimeSeries>\n        <mRID>3</mRID>\n        <businessType>A04</businessType>\n        <objectAggregation>A01</objectAggregation>\n        <outBiddingZone_Domain.mRID codingScheme=\"A01\">10YDK-2--------M</outBiddingZone_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A01</curveType>\n        <Period>\n            <timeInterval>\n                <start>2023-12-29T23:00Z</start>\n                <end>2023-12-30T23:00Z</end>\n            </timeInterval>\n            <resolution>PT60M</resolution>\n            <Point>\n                <position>1</position>\n                <quantity>1420</quantity>\n            </Point>\n            <Point>\n                <position>2</position>\n                <quantity>1385</quantity>\n            </Point>\n            <Point>\n                <position>3</position>\n                <quantity>1384</quantity>\n            </Point>\n            <Point>\n                <position>4</position>\n                <quantity>1369</quantity>\n            </Point>\n            <Point>\n                <position>5</position>\n                <quantity>1349</quantity>\n            </Point>\n            <Point>\n                <position>6</position>\n                <quantity>1343</quantity>\n            </Point>\n            <Point>\n                <position>7</position>\n                <quantity>1373</quantity>\n            </Point>\n            <Point>\n                <position>8</position>\n                <quantity>1444</quantity>\n            </Point>\n            <Point>\n                <position>9</position>\n                <quantity>1543</quantity>\n            </Point>\n            <Point>\n                <position>10</position>\n                <quantity>1641</quantity>\n            </Point>\n            <Point>\n                <position>11</position>\n                <quantity>1718</quantity>\n            </Point>\n            <Point>\n                <position>12</position>\n                <quantity>1738</quantity>\n            </Point>\n            <Point>\n                <position>13</position>\n                <quantity>1733</quantity>\n            </Point>\n            <Point>\n                <position>14</position>\n                <quantity>1713</quantity>\n            </Point>\n            <Point>\n                <position>15</position>\n                <quantity>1710</quantity>\n            </Point>\n            <Point>\n                <position>16</position>\n                <quantity>1743</quantity>\n            </Point>\n            <Point>\n                <position>17</position>\n                <quantity>1865</quantity>\n            </Point>\n            <Point>\n                <position>18</position>\n                <quantity>2034</quantity>\n            </Point>\n            <Point>\n                <position>19</position>\n                <quantity>2007</quantity>\n            </Point>\n            <Point>\n                <position>20</position>\n                <quantity>1866</quantity>\n            </Point>\n            <Point>\n                <position>21</position>\n                <quantity>1733</quantity>\n            </Point>\n            <Point>\n                <position>22</position>\n                <quantity>1624</quantity>\n            </Point>\n            <Point>\n                <position>23</position>\n                <quantity>1534</quantity>\n            </Point>\n            <Point>\n                <position>24</position>\n                <quantity>1452</quantity>\n            </Point>\n        </Period>\n    </TimeSeries>\n    <TimeSeries>\n        <mRID>4</mRID>\n        <businessType>A04</businessType>\n        <objectAggregation>A01</objectAggregation>\n        <outBiddingZone_Domain.mRID codingScheme=\"A01\">10YDK-2--------M</outBiddingZone_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A01</curveType>\n        <Period>\n            <timeInterval>\n                <start>2023-12-30T23:00Z</start>\n                <end>2023-12-31T23:00Z</end>\n            </timeInterval>\n            <resolution>PT60M</resolution>\n            <Point>\n                <position>1</position>\n                <quantity>1372</quantity>\n            </Point>\n            <Point>\n                <position>2</position>\n                <quantity>1305</quantity>\n            </Point>\n            <Point>\n                <position>3</position>\n                <quantity>1259</quantity>\n            </Point>\n            <Point>\n                <position>4</position>\n                <quantity>1235</quantity>\n            </Point>\n            <Point>\n                <position>5</position>\n                <quantity>1230</quantity>\n            </Point>\n            <Point>\n                <position>6</position>\n                <quantity>1266</quantity>\n            </Point>\n            <Point>\n                <position>7</position>\n                <quantity>1330</quantity>\n            </Point>\n            <Point>\n                <position>8</position>\n                <quantity>1414</quantity>\n            </Point>\n            <Point>\n                <position>9</position>\n                <quantity>1510</quantity>\n            </Point>\n            <Point>\n                <position>10</position>\n                <quantity>1609</quantity>\n            </Point>\n            <Point>\n                <position>11</position>\n                <quantity>1688</quantity>\n            </Point>\n            <Point>\n                <position>12</position>\n                <quantity>1730</quantity>\n            </Point>\n            <Point>\n                <position>13</position>\n                <quantity>1751</quantity>\n            </Point>\n            <Point>\n                <position>14</position>\n                <quantity>1761</quantity>\n            </Point>\n            <Point>\n                <position>15</position>\n                <quantity>1748</quantity>\n            </Point>\n            <Point>\n                <position>16</position>\n                <quantity>1773</quantity>\n            </Point>\n            <Point>\n                <position>17</position>\n                <quantity>1861</quantity>\n            </Point>\n            <Point>\n                <position>18</position>\n                <quantity>1935</quantity>\n            </Point>\n            <Point>\n                <position>19</position>\n                <quantity>1894</quantity>\n            </Point>\n            <Point>\n                <position>20</position>\n                <quantity>1752</quantity>\n            </Point>\n            <Point>\n                <position>21</position>\n                <quantity>1619</quantity>\n            </Point>\n            <Point>\n                <position>22</position>\n                <quantity>1540</quantity>\n            </Point>\n            <Point>\n                <position>23</position>\n                <quantity>1481</quantity>\n            </Point>\n            <Point>\n                <position>24</position>\n                <quantity>1432</quantity>\n            </Point>\n        </Period>\n    </TimeSeries>\n</GL_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/EE_FI_exchange_forecast_exports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n  <mRID>2e47d2684f234320b8b53fdc2c7adbab</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A09</type>\n  <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2024-03-25T18:56:06Z</createdDateTime>\n  <period.timeInterval>\n    <start>2024-03-23T23:00Z</start>\n    <end>2024-03-25T23:00Z</end>\n  </period.timeInterval>\n  <TimeSeries>\n    <mRID>1</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</out_Domain.mRID>\n    <contract_MarketAgreement.type>A05</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-23T23:00Z</start>\n        <end>2024-03-24T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>46</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>70</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>90</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>47</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>31</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>0</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <TimeSeries>\n    <mRID>2</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</out_Domain.mRID>\n    <contract_MarketAgreement.type>A05</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-24T23:00Z</start>\n        <end>2024-03-25T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>0</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <TimeSeries>\n    <mRID>3</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</out_Domain.mRID>\n    <contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-23T23:00Z</start>\n        <end>2024-03-24T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>0</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <TimeSeries>\n    <mRID>4</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</out_Domain.mRID>\n    <contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-24T23:00Z</start>\n        <end>2024-03-25T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>0</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <TimeSeries>\n    <mRID>5</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</out_Domain.mRID>\n    <contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-25T23:00Z</start>\n        <end>2024-03-26T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>45</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>73</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>103</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>0</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/EE_FI_exchange_forecast_imports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n  <mRID>0bb4ab34be474b12a3c183209c58e3dd</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A09</type>\n  <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2024-03-25T18:51:18Z</createdDateTime>\n  <period.timeInterval>\n    <start>2024-03-23T23:00Z</start>\n    <end>2024-03-25T23:00Z</end>\n  </period.timeInterval>\n  <TimeSeries>\n    <mRID>1</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</out_Domain.mRID>\n    <contract_MarketAgreement.type>A05</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-23T23:00Z</start>\n        <end>2024-03-24T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>258</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>190</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>176</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>222</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>234</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>154</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>44</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>86</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>43</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>60</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>221</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>334</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>355</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>333</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <TimeSeries>\n    <mRID>2</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</out_Domain.mRID>\n    <contract_MarketAgreement.type>A05</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-24T23:00Z</start>\n        <end>2024-03-25T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>333</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>311</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>266</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>274</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>325</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>323</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>315</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>207</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>92</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>19</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>59</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>106</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>212</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>321</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>353</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>258</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>318</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>290</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>355</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>285</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <TimeSeries>\n    <mRID>3</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</out_Domain.mRID>\n    <contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-23T23:00Z</start>\n        <end>2024-03-24T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>270</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>181</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>201</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>228</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>239</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>157</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>29</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>66</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>2</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>15</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>30</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>28</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>83</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>225</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>358</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <TimeSeries>\n    <mRID>4</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</out_Domain.mRID>\n    <contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-24T23:00Z</start>\n        <end>2024-03-25T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>338</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>325</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>324</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>353</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>329</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>260</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>197</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>104</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>174</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>220</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>276</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>319</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>343</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>355</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>285</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n  <TimeSeries>\n    <mRID>5</mRID>\n    <businessType>A06</businessType>\n    <in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A39I</in_Domain.mRID>\n    <out_Domain.mRID codingScheme=\"A01\">10YFI-1--------U</out_Domain.mRID>\n    <contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <Period>\n      <timeInterval>\n        <start>2024-03-25T23:00Z</start>\n        <end>2024-03-26T23:00Z</end>\n      </timeInterval>\n      <resolution>PT60M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>295</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>219</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>164</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>156</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>30</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>14</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>14</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>14</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>16</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>65</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>85</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>185</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>200</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>276</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>309</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>358</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>358</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/ES_FR_capacity_day_ahead_export.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n  <mRID>74caf66da0314807b7a5836d0fd5f45b</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A61</type>\n  <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2026-03-19T08:44:33Z</createdDateTime>\n  <period.timeInterval>\n    <start>2026-03-19T06:00Z</start>\n    <end>2026-03-20T23:00Z</end>\n  </period.timeInterval>\n      <TimeSeries>\n        <mRID>1</mRID>\n        <businessType>A27</businessType>\n        <in_Domain.mRID codingScheme=\"A01\">10YES-REE------0</in_Domain.mRID>\n        <out_Domain.mRID codingScheme=\"A01\">10YFR-RTE------C</out_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A03</curveType>\n            <Period>\n              <timeInterval>\n                <start>2026-03-19T06:00Z</start>\n                <end>2026-03-20T23:00Z</end>\n              </timeInterval>\n              <resolution>PT60M</resolution>\n                  <Point>\n                    <position>1</position>\n                    <quantity>3006</quantity>\n                  </Point>\n                  <Point>\n                    <position>5</position>\n                    <quantity>2914</quantity>\n                  </Point>\n                  <Point>\n                    <position>9</position>\n                    <quantity>2960</quantity>\n                  </Point>\n                  <Point>\n                    <position>12</position>\n                    <quantity>3607</quantity>\n                  </Point>\n                  <Point>\n                    <position>18</position>\n                    <quantity>3422</quantity>\n                  </Point>\n                  <Point>\n                    <position>22</position>\n                    <quantity>3515</quantity>\n                  </Point>\n                  <Point>\n                    <position>24</position>\n                    <quantity>3469</quantity>\n                  </Point>\n                  <Point>\n                    <position>29</position>\n                    <quantity>3099</quantity>\n                  </Point>\n                  <Point>\n                    <position>36</position>\n                    <quantity>3607</quantity>\n                  </Point>\n            </Period>\n      </TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/ES_FR_capacity_day_ahead_import.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n  <mRID>91b3e52f10c84d8a9b7e62c3f1d40e28</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A61</type>\n  <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2026-03-19T08:44:33Z</createdDateTime>\n  <period.timeInterval>\n    <start>2026-03-19T06:00Z</start>\n    <end>2026-03-20T23:00Z</end>\n  </period.timeInterval>\n      <TimeSeries>\n        <mRID>1</mRID>\n        <businessType>A27</businessType>\n        <in_Domain.mRID codingScheme=\"A01\">10YFR-RTE------C</in_Domain.mRID>\n        <out_Domain.mRID codingScheme=\"A01\">10YES-REE------0</out_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A03</curveType>\n            <Period>\n              <timeInterval>\n                <start>2026-03-19T06:00Z</start>\n                <end>2026-03-20T23:00Z</end>\n              </timeInterval>\n              <resolution>PT60M</resolution>\n                  <Point>\n                    <position>1</position>\n                    <quantity>1400</quantity>\n                  </Point>\n                  <Point>\n                    <position>6</position>\n                    <quantity>1350</quantity>\n                  </Point>\n                  <Point>\n                    <position>12</position>\n                    <quantity>1500</quantity>\n                  </Point>\n                  <Point>\n                    <position>20</position>\n                    <quantity>1450</quantity>\n                  </Point>\n            </Period>\n      </TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/ES_FR_capacity_month_ahead_export.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n  <mRID>a7c2e41b83f94d5e96c1b2d3f4e50a17</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A61</type>\n  <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2026-03-19T08:52:57Z</createdDateTime>\n  <period.timeInterval>\n    <start>2026-03-16T23:00Z</start>\n    <end>2026-05-18T22:00Z</end>\n  </period.timeInterval>\n      <TimeSeries>\n        <mRID>1</mRID>\n        <businessType>A27</businessType>\n        <in_Domain.mRID codingScheme=\"A01\">10YES-REE------0</in_Domain.mRID>\n        <out_Domain.mRID codingScheme=\"A01\">10YFR-RTE------C</out_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A03</curveType>\n            <Period>\n              <timeInterval>\n                <start>2026-03-16T23:00Z</start>\n                <end>2026-05-18T22:00Z</end>\n              </timeInterval>\n              <resolution>P1D</resolution>\n                  <Point>\n                    <position>1</position>\n                    <quantity>3000</quantity>\n                  </Point>\n            </Period>\n      </TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/ES_FR_capacity_month_ahead_import.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n  <mRID>d3dadc2af2034b9787dfacfb8670d159</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A61</type>\n  <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2026-03-19T08:52:57Z</createdDateTime>\n  <period.timeInterval>\n    <start>2026-03-16T23:00Z</start>\n    <end>2026-05-18T22:00Z</end>\n  </period.timeInterval>\n      <TimeSeries>\n        <mRID>1</mRID>\n        <businessType>A27</businessType>\n        <in_Domain.mRID codingScheme=\"A01\">10YFR-RTE------C</in_Domain.mRID>\n        <out_Domain.mRID codingScheme=\"A01\">10YES-REE------0</out_Domain.mRID>\n        <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n        <curveType>A03</curveType>\n            <Period>\n              <timeInterval>\n                <start>2026-03-16T23:00Z</start>\n                <end>2026-05-18T22:00Z</end>\n              </timeInterval>\n              <resolution>P1D</resolution>\n                  <Point>\n                    <position>1</position>\n                    <quantity>2150</quantity>\n                  </Point>\n                  <Point>\n                    <position>3</position>\n                    <quantity>2400</quantity>\n                  </Point>\n                  <Point>\n                    <position>16</position>\n                    <quantity>0</quantity>\n                  </Point>\n            </Period>\n      </TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/ES_day_ahead_price.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n  <Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:3\">\n    <mRID>c9511c61c9bc48f4b33379904faa7f63</mRID>\n    <revisionNumber>1</revisionNumber>\n    <type>A44</type>\n    <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n    <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n    <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n    <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n    <createdDateTime>2025-10-01T22:50:06Z</createdDateTime>\n    <period.timeInterval>\n      <start>2025-09-28T22:00Z</start>\n      <end>2025-10-02T22:00Z</end>\n    </period.timeInterval>\n      <TimeSeries>\n        <mRID>1</mRID>\n        <auction.type>A01</auction.type>\n        <businessType>A62</businessType>\n  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<position>85</position>\n                  <price.amount>180</price.amount>\n              </Point>\n              <Point>\n                <position>86</position>\n                  <price.amount>173.66</price.amount>\n              </Point>\n              <Point>\n                <position>87</position>\n                  <price.amount>147.3</price.amount>\n              </Point>\n              <Point>\n                <position>88</position>\n                  <price.amount>125</price.amount>\n              </Point>\n              <Point>\n                <position>89</position>\n                  <price.amount>128.81</price.amount>\n              </Point>\n              <Point>\n                <position>90</position>\n                  <price.amount>121</price.amount>\n              </Point>\n              <Point>\n                <position>91</position>\n                  <price.amount>115.44</price.amount>\n              </Point>\n              <Point>\n                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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/ES_intraday_price.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n  <Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:3\">\n    <mRID>16b06d53b0d34234b08a6ac43cb6bdc8</mRID>\n    <revisionNumber>1</revisionNumber>\n    <type>A44</type>\n    <sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n    <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n    <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n    <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n    <createdDateTime>2025-10-01T22:58:50Z</createdDateTime>\n    <period.timeInterval>\n      <start>2025-09-28T22:00Z</start>\n      <end>2025-10-02T22:00Z</end>\n    </period.timeInterval>\n      <TimeSeries>\n        <mRID>1</mRID>\n        <auction.type>A01</auction.type>\n        <businessType>A62</businessType>\n  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<in_Domain.mRID codingScheme=\"A01\">10YES-REE------0</in_Domain.mRID>\n        <out_Domain.mRID codingScheme=\"A01\">10YES-REE------0</out_Domain.mRID>\n        <contract_MarketAgreement.type>A07</contract_MarketAgreement.type>\n        <currency_Unit.name>EUR</currency_Unit.name>\n        <price_Measure_Unit.name>MWH</price_Measure_Unit.name>\n          <classificationSequence_AttributeInstanceComponent.position>2</classificationSequence_AttributeInstanceComponent.position>\n        <curveType>A03</curveType>\n          <Period>\n            <timeInterval>\n              <start>2025-09-28T22:00Z</start>\n              <end>2025-09-29T22:00Z</end>\n            </timeInterval>\n            <resolution>PT15M</resolution>\n              <Point>\n                <position>1</position>\n                  <price.amount>77.77</price.amount>\n              </Point>\n              <Point>\n                <position>2</position>\n                  <price.amount>63.85</price.amount>\n            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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FI_production.xml",
    "content": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<GL_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-6:generationloaddocument:3:0\">\n\t<mRID>60112bd699e14e7c81b637a721a6b133</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A75</type>\n\t<process.processType>A16</process.processType>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID 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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR-COR_IT-SAR_AC_exchange_exports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>7d8620b8dcf140bb8b84ddb9a0dcb354</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A11</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-29T10:16:52Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-27T10:00Z</start>\n\t\t<end>2023-12-30T00:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A66</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A74G</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A885</out_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-27T10:00Z</start>\n\t\t\t\t\t<end>2023-12-29T09:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>25</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>26</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>27</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>28</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>29</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>30</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>31</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>32</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>33</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>34</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>35</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>36</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>37</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>38</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>39</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>40</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>41</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>42</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>43</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>44</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>45</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>46</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>47</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR-COR_IT-SAR_AC_exchange_forecast_exports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>484a963ec9124c67816d34957b529b02</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A09</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-29T10:48:28Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-26T23:00Z</start>\n\t\t<end>2023-12-29T23:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A74G</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A885</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A05</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-26T23:00Z</start>\n\t\t\t\t\t<end>2023-12-27T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>2</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID 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codingScheme=\"A01\">10Y1001A1001A885</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-28T23:00Z</start>\n\t\t\t\t\t<end>2023-12-29T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR-COR_IT-SAR_AC_exchange_forecast_imports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>4ed99b70deb9426ebb9403c8504f7b21</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A09</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-29T10:48:27Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-26T23:00Z</start>\n\t\t<end>2023-12-29T23:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A885</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A74G</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A05</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-26T23:00Z</start>\n\t\t\t\t\t<end>2023-12-27T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>99</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>93</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>80</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>73</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>71</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>75</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>85</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>97</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>99</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>80</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>56</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>39</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>31</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>31</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>44</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>68</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>95</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>99</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>99</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>99</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>99</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>99</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>99</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>99</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>2</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A885</in_Domain.mRID>\n\t\t<out_Domain.mRID 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codingScheme=\"A01\">10Y1001A1001A74G</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-28T23:00Z</start>\n\t\t\t\t\t<end>2023-12-29T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>9</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR-COR_IT-SAR_AC_exchange_imports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>7be4a92c644e41e1b9b08084e8dbd2d9</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A11</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-29T10:16:52Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-27T10:00Z</start>\n\t\t<end>2023-12-30T00:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A66</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A885</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A74G</out_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-27T10:00Z</start>\n\t\t\t\t\t<end>2023-12-29T09:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>13</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>8</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>12</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>11</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>13</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>11</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>8</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>7</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>7</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>7</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>3</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>3</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>3</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>9</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>9</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>25</position>\n\t\t\t\t\t\t<quantity>9</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>26</position>\n\t\t\t\t\t\t<quantity>7</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>27</position>\n\t\t\t\t\t\t<quantity>12</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>28</position>\n\t\t\t\t\t\t<quantity>12</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>29</position>\n\t\t\t\t\t\t<quantity>11</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>30</position>\n\t\t\t\t\t\t<quantity>11</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>31</position>\n\t\t\t\t\t\t<quantity>14</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>32</position>\n\t\t\t\t\t\t<quantity>13</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>33</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>34</position>\n\t\t\t\t\t\t<quantity>7</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>35</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>36</position>\n\t\t\t\t\t\t<quantity>7</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>37</position>\n\t\t\t\t\t\t<quantity>7</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>38</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>39</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>40</position>\n\t\t\t\t\t\t<quantity>10</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>41</position>\n\t\t\t\t\t\t<quantity>4</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>42</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>43</position>\n\t\t\t\t\t\t<quantity>5</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>44</position>\n\t\t\t\t\t\t<quantity>9</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>45</position>\n\t\t\t\t\t\t<quantity>9</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>46</position>\n\t\t\t\t\t\t<quantity>8</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>47</position>\n\t\t\t\t\t\t<quantity>6</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR-COR_IT-SAR_DC_exchange_exports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>becb14635b4d4b5aab157c25d6b1b562</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A11</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-29T10:16:53Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-27T10:00Z</start>\n\t\t<end>2023-12-30T00:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A66</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A74G</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A893</out_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-27T10:00Z</start>\n\t\t\t\t\t<end>2023-12-29T09:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>48</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>48</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>49</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>48</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>39</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>76</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>87</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>88</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>88</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>89</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>68</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>88</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>55</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>25</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>26</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>27</position>\n\t\t\t\t\t\t<quantity>34</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>28</position>\n\t\t\t\t\t\t<quantity>39</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>29</position>\n\t\t\t\t\t\t<quantity>35</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>30</position>\n\t\t\t\t\t\t<quantity>31</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>31</position>\n\t\t\t\t\t\t<quantity>74</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>32</position>\n\t\t\t\t\t\t<quantity>83</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>33</position>\n\t\t\t\t\t\t<quantity>83</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>34</position>\n\t\t\t\t\t\t<quantity>58</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>35</position>\n\t\t\t\t\t\t<quantity>29</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>36</position>\n\t\t\t\t\t\t<quantity>21</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>37</position>\n\t\t\t\t\t\t<quantity>37</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>38</position>\n\t\t\t\t\t\t<quantity>76</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>39</position>\n\t\t\t\t\t\t<quantity>89</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>40</position>\n\t\t\t\t\t\t<quantity>85</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>41</position>\n\t\t\t\t\t\t<quantity>92</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>42</position>\n\t\t\t\t\t\t<quantity>92</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>43</position>\n\t\t\t\t\t\t<quantity>92</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>44</position>\n\t\t\t\t\t\t<quantity>92</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>45</position>\n\t\t\t\t\t\t<quantity>46</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>46</position>\n\t\t\t\t\t\t<quantity>29</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>47</position>\n\t\t\t\t\t\t<quantity>28</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR-COR_IT-SAR_DC_exchange_forecast_exports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>8b3c2af3874348f4a60423e5590a72eb</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A09</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-29T10:48:30Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-26T23:00Z</start>\n\t\t<end>2023-12-29T23:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A74G</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A893</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A05</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-26T23:00Z</start>\n\t\t\t\t\t<end>2023-12-27T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>2</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID 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codingScheme=\"A01\">10Y1001A1001A893</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-28T23:00Z</start>\n\t\t\t\t\t<end>2023-12-29T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR-COR_IT-SAR_DC_exchange_forecast_imports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>148d5c2e6700447d91455caac2dd1852</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A09</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-29T10:48:29Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-26T23:00Z</start>\n\t\t<end>2023-12-29T23:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A893</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A74G</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A05</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-26T23:00Z</start>\n\t\t\t\t\t<end>2023-12-27T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>42</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>2</mRID>\n\t\t<businessType>A06</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A893</in_Domain.mRID>\n\t\t<out_Domain.mRID 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codingScheme=\"A01\">10Y1001A1001A74G</out_Domain.mRID>\n\t\t<contract_MarketAgreement.type>A01</contract_MarketAgreement.type>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-28T23:00Z</start>\n\t\t\t\t\t<end>2023-12-29T23:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>47</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR-COR_IT-SAR_DC_exchange_imports.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<mRID>f1bfff2de8cb439388d0731c39042a3c</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A11</type>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-29T10:16:52Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-12-27T10:00Z</start>\n\t\t<end>2023-12-30T00:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A66</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10Y1001A1001A893</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10Y1001A1001A74G</out_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-12-27T10:00Z</start>\n\t\t\t\t\t<end>2023-12-29T09:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>25</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>26</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>27</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>28</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>29</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>30</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>31</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>32</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>33</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>34</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>35</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>36</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>37</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>38</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>39</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>40</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>41</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>42</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>43</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>44</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>45</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>46</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>47</position>\n\t\t\t\t\t\t<quantity>0</quantity>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR_prices.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<Publication_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-3:publicationdocument:7:0\">\n\t<revisionNumber>1</revisionNumber>\n\t<type>A44</type>\n\t<createdDateTime>2023-05-09T11:24:10Z</createdDateTime>\n\t<period.timeInterval>\n\t\t<start>2023-05-06T22:00Z</start>\n\t\t<end>2023-05-08T22:00Z</end>\n\t</period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A62</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10YFR-RTE------C</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10YFR-RTE------C</out_Domain.mRID>\n\t\t<currency_Unit.name>EUR</currency_Unit.name>\n\t\t<price_Measure_Unit.name>MWH</price_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-05-06T22:00Z</start>\n\t\t\t\t\t<end>2023-05-07T22:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<price.amount>106.78</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<price.amount>95.02</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<price.amount>90.00</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<price.amount>84.30</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<price.amount>83.71</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<price.amount>84.86</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<price.amount>85.08</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<price.amount>82.48</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<price.amount>77.51</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<price.amount>76.25</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<price.amount>63.48</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<price.amount>55.13</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<price.amount>60.48</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<price.amount>47.25</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<price.amount>27.40</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<price.amount>24.09</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<price.amount>57.60</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<price.amount>77.75</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<price.amount>95.63</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<price.amount>101.30</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<price.amount>107.43</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<price.amount>109.20</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<price.amount>106.23</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<price.amount>97.99</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>2</mRID>\n\t\t<businessType>A62</businessType>\n\t\t<in_Domain.mRID codingScheme=\"A01\">10YFR-RTE------C</in_Domain.mRID>\n\t\t<out_Domain.mRID codingScheme=\"A01\">10YFR-RTE------C</out_Domain.mRID>\n\t\t<currency_Unit.name>EUR</currency_Unit.name>\n\t\t<price_Measure_Unit.name>MWH</price_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t\t<Period>\n\t\t\t\t<timeInterval>\n\t\t\t\t\t<start>2023-05-07T22:00Z</start>\n\t\t\t\t\t<end>2023-05-08T22:00Z</end>\n\t\t\t\t</timeInterval>\n\t\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>1</position>\n\t\t\t\t\t\t<price.amount>98.24</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>2</position>\n\t\t\t\t\t\t<price.amount>88.58</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>3</position>\n\t\t\t\t\t\t<price.amount>87.23</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>4</position>\n\t\t\t\t\t\t<price.amount>84.01</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>5</position>\n\t\t\t\t\t\t<price.amount>84.16</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>6</position>\n\t\t\t\t\t\t<price.amount>90.91</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>7</position>\n\t\t\t\t\t\t<price.amount>93.96</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>8</position>\n\t\t\t\t\t\t<price.amount>99.74</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>9</position>\n\t\t\t\t\t\t<price.amount>110.97</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>10</position>\n\t\t\t\t\t\t<price.amount>100.01</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>11</position>\n\t\t\t\t\t\t<price.amount>92.04</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>12</position>\n\t\t\t\t\t\t<price.amount>83.49</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>13</position>\n\t\t\t\t\t\t<price.amount>83.00</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>14</position>\n\t\t\t\t\t\t<price.amount>83.71</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>15</position>\n\t\t\t\t\t\t<price.amount>77.99</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>16</position>\n\t\t\t\t\t\t<price.amount>78.00</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>17</position>\n\t\t\t\t\t\t<price.amount>84.01</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>18</position>\n\t\t\t\t\t\t<price.amount>97.05</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>19</position>\n\t\t\t\t\t\t<price.amount>106.50</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>20</position>\n\t\t\t\t\t\t<price.amount>112.82</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>21</position>\n\t\t\t\t\t\t<price.amount>122.76</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>22</position>\n\t\t\t\t\t\t<price.amount>121.99</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>23</position>\n\t\t\t\t\t\t<price.amount>114.71</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t\t\t<Point>\n\t\t\t\t\t\t<position>24</position>\n\t\t\t\t\t\t<price.amount>104.04</price.amount>\n\t\t\t\t\t</Point>\n\t\t\t</Period>\n\t</TimeSeries>\n</Publication_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/LU_production.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<GL_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-6:generationloaddocument:3:0\">\n  <mRID>28000bea51054c1ab24f5b666b28d511</mRID>\n  <revisionNumber>1</revisionNumber>\n  <type>A75</type>\n  <process.processType>A16</process.processType>\n  <sender_MarketParticipant.mRID\n    codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n  <sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n  <receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n  <receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n  <createdDateTime>2024-05-24T10:25:00Z</createdDateTime>\n  <time_Period.timeInterval>\n    <start>2024-05-21T10:00Z</start>\n    <end>2024-05-24T10:00Z</end>\n  </time_Period.timeInterval>\n  <TimeSeries>\n    <mRID>1</mRID>\n    <businessType>A01</businessType>\n    <objectAggregation>A08</objectAggregation>\n    <inBiddingZone_Domain.mRID codingScheme=\"A01\">10YLU-CEGEDEL-NQ</inBiddingZone_Domain.mRID>\n    <quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n    <curveType>A01</curveType>\n    <MktPSRType>\n      <psrType>B01</psrType>\n    </MktPSRType>\n    <Period>\n      <timeInterval>\n        <start>2024-05-21T10:00Z</start>\n        <end>2024-05-24T03:45Z</end>\n      </timeInterval>\n      <resolution>PT15M</resolution>\n      <Point>\n        <position>1</position>\n        <quantity>17</quantity>\n      </Point>\n      <Point>\n        <position>2</position>\n        <quantity>17</quantity>\n      </Point>\n      <Point>\n        <position>3</position>\n        <quantity>17</quantity>\n      </Point>\n      <Point>\n        <position>4</position>\n        <quantity>18</quantity>\n      </Point>\n      <Point>\n        <position>5</position>\n        <quantity>18</quantity>\n      </Point>\n      <Point>\n        <position>6</position>\n        <quantity>18</quantity>\n      </Point>\n      <Point>\n        <position>7</position>\n        <quantity>18</quantity>\n      </Point>\n      <Point>\n        <position>8</position>\n        <quantity>18</quantity>\n      </Point>\n      <Point>\n        <position>9</position>\n        <quantity>19</quantity>\n      </Point>\n      <Point>\n        <position>10</position>\n        <quantity>19</quantity>\n      </Point>\n      <Point>\n        <position>11</position>\n        <quantity>19</quantity>\n      </Point>\n      <Point>\n        <position>12</position>\n        <quantity>22</quantity>\n      </Point>\n      <Point>\n        <position>13</position>\n        <quantity>23</quantity>\n      </Point>\n      <Point>\n        <position>14</position>\n        <quantity>24</quantity>\n      </Point>\n      <Point>\n        <position>15</position>\n        <quantity>29</quantity>\n      </Point>\n      <Point>\n        <position>16</position>\n        <quantity>34</quantity>\n      </Point>\n      <Point>\n        <position>17</position>\n        <quantity>38</quantity>\n      </Point>\n      <Point>\n        <position>18</position>\n        <quantity>39</quantity>\n      </Point>\n      <Point>\n        <position>19</position>\n        <quantity>27</quantity>\n      </Point>\n      <Point>\n        <position>20</position>\n        <quantity>21</quantity>\n      </Point>\n      <Point>\n        <position>21</position>\n        <quantity>21</quantity>\n      </Point>\n      <Point>\n        <position>22</position>\n        <quantity>21</quantity>\n      </Point>\n      <Point>\n        <position>23</position>\n        <quantity>21</quantity>\n      </Point>\n      <Point>\n        <position>24</position>\n        <quantity>18</quantity>\n      </Point>\n      <Point>\n        <position>25</position>\n        <quantity>17</quantity>\n      </Point>\n      <Point>\n        <position>26</position>\n        <quantity>17</quantity>\n      </Point>\n      <Point>\n        <position>27</position>\n        <quantity>17</quantity>\n      </Point>\n      <Point>\n        <position>28</position>\n        <quantity>18</quantity>\n      </Point>\n      <Point>\n        <position>29</position>\n        <quantity>19</quantity>\n      </Point>\n      <Point>\n        <position>30</position>\n        <quantity>18</quantity>\n      </Point>\n      <Point>\n        <position>31</position>\n        <quantity>19</quantity>\n      </Point>\n      <Point>\n        <position>32</position>\n        <quantity>18</quantity>\n      </Point>\n      <Point>\n        <position>33</position>\n        <quantity>17</quantity>\n      </Point>\n      <Point>\n        <position>34</position>\n        <quantity>17</quantity>\n      </Point>\n      <Point>\n        <position>35</position>\n        <quantity>15</quantity>\n      </Point>\n      <Point>\n        <position>36</position>\n        <quantity>17</quantity>\n      </Point>\n      <Point>\n      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</Point>\n      <Point>\n        <position>268</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>269</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>270</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>271</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>272</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>273</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>274</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>275</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>276</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>277</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>278</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>279</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>280</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>281</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>282</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>283</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>284</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>285</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>286</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>287</position>\n        <quantity>0</quantity>\n      </Point>\n      <Point>\n        <position>288</position>\n        <quantity>0</quantity>\n      </Point>\n    </Period>\n  </TimeSeries>\n</GL_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/NO-NO5_production-negatives.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<GL_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-6:generationloaddocument:3:0\">\n\t<mRID>fcde5738d7be426a923846473793e73e</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A75</type>\n\t<process.processType>A16</process.processType>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-05-11T09:40:41Z</createdDateTime>\n\t<time_Period.timeInterval>\n\t\t<start>2023-05-09T09:00Z</start>\n\t\t<end>2023-05-11T09:00Z</end>\n\t</time_Period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A08</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID codingScheme=\"A01\">10Y1001A1001A48H</inBiddingZone_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t<MktPSRType>\n\t\t\t<psrType>B04</psrType>\n\t\t</MktPSRType>\n\t\t<Period>\n\t\t\t<timeInterval>\n\t\t\t\t<start>2023-05-09T09:00Z</start>\n\t\t\t\t<end>2023-05-11T08:00Z</end>\n\t\t\t</timeInterval>\n\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>1</position>\n                        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<quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>26</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>27</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>28</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>29</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>30</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>31</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>32</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>33</position>\n                        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<quantity>1706</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>30</position>\n                        <quantity>2007</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>31</position>\n                        <quantity>2189</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>32</position>\n                        <quantity>2091</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>33</position>\n                        <quantity>2177</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>34</position>\n                        <quantity>2321</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>35</position>\n                        <quantity>2198</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>36</position>\n                        <quantity>2065</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>37</position>\n                        <quantity>2032</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>38</position>\n                        <quantity>1960</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>39</position>\n                        <quantity>1802</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>40</position>\n                        <quantity>1805</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>41</position>\n                        <quantity>1805</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>42</position>\n                        <quantity>1865</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>43</position>\n                        <quantity>2118</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>44</position>\n                        <quantity>2578</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>45</position>\n                        <quantity>2928</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>46</position>\n                        <quantity>3301</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>47</position>\n                        <quantity>3095</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>5</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A08</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID codingScheme=\"A01\">10Y1001A1001A48H</inBiddingZone_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t<MktPSRType>\n\t\t\t<psrType>B17</psrType>\n\t\t</MktPSRType>\n\t\t<Period>\n\t\t\t<timeInterval>\n\t\t\t\t<start>2023-05-09T09:00Z</start>\n\t\t\t\t<end>2023-05-11T08:00Z</end>\n\t\t\t</timeInterval>\n\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>1</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>2</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>3</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>4</position>\n                        <quantity>16</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>5</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>6</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>7</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>8</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>9</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>10</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>11</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>12</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>13</position>\n                        <quantity>16</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>14</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>15</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>16</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>17</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>18</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>19</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>20</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>21</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>22</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>23</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>24</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>25</position>\n                        <quantity>16</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>26</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>27</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>28</position>\n                        <quantity>12</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>29</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>30</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>31</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>32</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>33</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>34</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>35</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>36</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>37</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>38</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>39</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>40</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>41</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>42</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>43</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>44</position>\n                        <quantity>11</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>45</position>\n                        <quantity>11</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>46</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>47</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n</GL_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/NO-NO5_production.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<GL_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-6:generationloaddocument:3:0\">\n\t<mRID>fcde5738d7be426a923846473793e73e</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A75</type>\n\t<process.processType>A16</process.processType>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-05-11T09:40:41Z</createdDateTime>\n\t<time_Period.timeInterval>\n\t\t<start>2023-05-09T09:00Z</start>\n\t\t<end>2023-05-11T09:00Z</end>\n\t</time_Period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A08</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID codingScheme=\"A01\">10Y1001A1001A48H</inBiddingZone_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t<MktPSRType>\n\t\t\t<psrType>B04</psrType>\n\t\t</MktPSRType>\n\t\t<Period>\n\t\t\t<timeInterval>\n\t\t\t\t<start>2023-05-09T09:00Z</start>\n\t\t\t\t<end>2023-05-11T08:00Z</end>\n\t\t\t</timeInterval>\n\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>1</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>2</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>3</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>4</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>5</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>6</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>7</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>8</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>9</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>10</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>11</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>12</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>13</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>14</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>15</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>16</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>17</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>18</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>19</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>20</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>21</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>22</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>23</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>24</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>25</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>26</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>27</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>28</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>29</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>30</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>31</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>32</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>33</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>34</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>35</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>36</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>37</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>38</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>39</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>40</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>41</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>42</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>43</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>44</position>\n                        <quantity>1</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>45</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>46</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>47</position>\n                        <quantity>0</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>2</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A08</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID codingScheme=\"A01\">10Y1001A1001A48H</inBiddingZone_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t<MktPSRType>\n\t\t\t<psrType>B10</psrType>\n\t\t</MktPSRType>\n\t\t<Period>\n\t\t\t<timeInterval>\n\t\t\t\t<start>2023-05-09T09:00Z</start>\n\t\t\t\t<end>2023-05-11T08:00Z</end>\n\t\t\t</timeInterval>\n\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>1</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>2</position>\n                        <quantity>62</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>3</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>4</position>\n                        <quantity>62</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>5</position>\n                        <quantity>62</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>6</position>\n                        <quantity>62</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>7</position>\n                        <quantity>62</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>8</position>\n                        <quantity>62</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>9</position>\n                        <quantity>62</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>10</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>11</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>12</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>13</position>\n                        <quantity>62</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>14</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>15</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>16</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>17</position>\n                        <quantity>60</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>18</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>19</position>\n                        <quantity>61</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>20</position>\n                        <quantity>78</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>21</position>\n                        <quantity>157</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>22</position>\n                        <quantity>161</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>23</position>\n                        <quantity>118</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>24</position>\n                        <quantity>60</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>25</position>\n                        <quantity>60</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>26</position>\n                        <quantity>35</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>27</position>\n                        <quantity>34</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>28</position>\n                        <quantity>34</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>29</position>\n                        <quantity>34</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>30</position>\n                        <quantity>34</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>31</position>\n                        <quantity>34</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>32</position>\n                        <quantity>34</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>33</position>\n                        <quantity>34</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>34</position>\n                        <quantity>33</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>35</position>\n                        <quantity>33</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>36</position>\n                        <quantity>33</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>37</position>\n                        <quantity>34</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>38</position>\n                        <quantity>70</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>39</position>\n                        <quantity>70</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>40</position>\n                        <quantity>71</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>41</position>\n                        <quantity>71</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>42</position>\n                        <quantity>71</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>43</position>\n                        <quantity>73</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>44</position>\n                        <quantity>74</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>45</position>\n                        <quantity>74</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>46</position>\n                        <quantity>190</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>47</position>\n                        <quantity>114</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>3</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A08</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID codingScheme=\"A01\">10Y1001A1001A48H</inBiddingZone_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t<MktPSRType>\n\t\t\t<psrType>B11</psrType>\n\t\t</MktPSRType>\n\t\t<Period>\n\t\t\t<timeInterval>\n\t\t\t\t<start>2023-05-09T09:00Z</start>\n\t\t\t\t<end>2023-05-11T08:00Z</end>\n\t\t\t</timeInterval>\n\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>1</position>\n                        <quantity>296</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>2</position>\n                        <quantity>283</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>3</position>\n                        <quantity>283</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>4</position>\n                        <quantity>292</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>5</position>\n                        <quantity>307</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>6</position>\n                        <quantity>390</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>7</position>\n                        <quantity>413</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>8</position>\n                        <quantity>427</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>9</position>\n                        <quantity>433</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>10</position>\n                        <quantity>432</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>11</position>\n                        <quantity>447</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>12</position>\n                        <quantity>434</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>13</position>\n                        <quantity>439</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>14</position>\n                        <quantity>479</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>15</position>\n                        <quantity>481</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>16</position>\n                        <quantity>469</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>17</position>\n                        <quantity>460</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>18</position>\n                        <quantity>476</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>19</position>\n                        <quantity>506</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>20</position>\n                        <quantity>509</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>21</position>\n                        <quantity>511</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>22</position>\n                        <quantity>509</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>23</position>\n                        <quantity>505</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>24</position>\n                        <quantity>505</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>25</position>\n                        <quantity>516</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>26</position>\n                        <quantity>543</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>27</position>\n                        <quantity>562</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>28</position>\n                        <quantity>562</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>29</position>\n                        <quantity>573</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>30</position>\n                        <quantity>576</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>31</position>\n                        <quantity>544</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>32</position>\n                        <quantity>546</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>33</position>\n                        <quantity>548</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>34</position>\n                        <quantity>559</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>35</position>\n                        <quantity>558</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>36</position>\n                        <quantity>567</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>37</position>\n                        <quantity>571</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>38</position>\n                        <quantity>586</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>39</position>\n                        <quantity>588</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>40</position>\n                        <quantity>588</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>41</position>\n                        <quantity>589</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>42</position>\n                        <quantity>584</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>43</position>\n                        <quantity>582</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>44</position>\n                        <quantity>577</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>45</position>\n                        <quantity>512</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>46</position>\n                        <quantity>518</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>47</position>\n                        <quantity>582</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>4</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A08</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID 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<quantity>1010</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>6</position>\n                        <quantity>1157</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>7</position>\n                        <quantity>1537</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>8</position>\n                        <quantity>1582</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>9</position>\n                        <quantity>1620</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>10</position>\n                        <quantity>1579</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>11</position>\n                        <quantity>1595</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>12</position>\n                        <quantity>1498</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>13</position>\n                        <quantity>1440</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>14</position>\n                        <quantity>1150</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>15</position>\n                        <quantity>1039</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>16</position>\n                        <quantity>1022</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>17</position>\n                        <quantity>1007</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>18</position>\n                        <quantity>1037</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>19</position>\n                        <quantity>1046</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>20</position>\n                        <quantity>1448</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>21</position>\n                        <quantity>1830</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>22</position>\n                        <quantity>1835</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>23</position>\n                        <quantity>1709</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>24</position>\n                        <quantity>1557</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>25</position>\n                        <quantity>1682</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>26</position>\n                        <quantity>1648</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>27</position>\n                        <quantity>1638</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>28</position>\n                        <quantity>1595</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>29</position>\n                        <quantity>1706</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>30</position>\n                        <quantity>2007</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>31</position>\n                        <quantity>2189</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>32</position>\n                        <quantity>2091</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>33</position>\n                        <quantity>2177</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>34</position>\n                        <quantity>2321</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>35</position>\n                        <quantity>2198</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>36</position>\n                        <quantity>2065</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>37</position>\n                        <quantity>2032</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>38</position>\n                        <quantity>1960</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>39</position>\n                        <quantity>1802</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>40</position>\n                        <quantity>1805</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>41</position>\n                        <quantity>1805</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>42</position>\n                        <quantity>1865</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>43</position>\n                        <quantity>2118</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>44</position>\n                        <quantity>2578</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>45</position>\n                        <quantity>2928</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>46</position>\n                        <quantity>3301</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>47</position>\n                        <quantity>3095</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>5</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A08</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID codingScheme=\"A01\">10Y1001A1001A48H</inBiddingZone_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t<MktPSRType>\n\t\t\t<psrType>B17</psrType>\n\t\t</MktPSRType>\n\t\t<Period>\n\t\t\t<timeInterval>\n\t\t\t\t<start>2023-05-09T09:00Z</start>\n\t\t\t\t<end>2023-05-11T08:00Z</end>\n\t\t\t</timeInterval>\n\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>1</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>2</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>3</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>4</position>\n                        <quantity>16</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>5</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>6</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>7</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>8</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>9</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>10</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>11</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>12</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>13</position>\n                        <quantity>16</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>14</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>15</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>16</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>17</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>18</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>19</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>20</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>21</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>22</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>23</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>24</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>25</position>\n                        <quantity>16</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>26</position>\n                        <quantity>15</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>27</position>\n                        <quantity>14</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>28</position>\n                        <quantity>12</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>29</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>30</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>31</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>32</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>33</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>34</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>35</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>36</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>37</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>38</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>39</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>40</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>41</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>42</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>43</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>44</position>\n                        <quantity>11</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>45</position>\n                        <quantity>11</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>46</position>\n                        <quantity>10</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>47</position>\n                        <quantity>9</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n</GL_MarketDocument>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ENTSOE/SE-SE3_generation_forecast.xml",
    "content": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<GL_MarketDocument xmlns=\"urn:iec62325.351:tc57wg16:451-6:generationloaddocument:3:0\">\n\t<mRID>f08ed4c098824b2db99320aac1c91e86</mRID>\n\t<revisionNumber>1</revisionNumber>\n\t<type>A71</type>\n\t<process.processType>A01</process.processType>\n\t<sender_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</sender_MarketParticipant.mRID>\n\t<sender_MarketParticipant.marketRole.type>A32</sender_MarketParticipant.marketRole.type>\n\t<receiver_MarketParticipant.mRID codingScheme=\"A01\">10X1001A1001A450</receiver_MarketParticipant.mRID>\n\t<receiver_MarketParticipant.marketRole.type>A33</receiver_MarketParticipant.marketRole.type>\n\t<createdDateTime>2023-12-30T15:06:25Z</createdDateTime>\n\t<time_Period.timeInterval>\n\t\t<start>2023-12-27T23:00Z</start>\n\t\t<end>2023-12-30T23:00Z</end>\n\t</time_Period.timeInterval>\n\t<TimeSeries>\n\t\t<mRID>1</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A01</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID codingScheme=\"A01\">10Y1001A1001A46L</inBiddingZone_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t<Period>\n\t\t\t<timeInterval>\n\t\t\t\t<start>2023-12-27T23:00Z</start>\n\t\t\t\t<end>2023-12-28T23:00Z</end>\n\t\t\t</timeInterval>\n\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>1</position>\n                        <quantity>9958</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>2</position>\n                        <quantity>10183</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>3</position>\n                        <quantity>10414</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>4</position>\n                        <quantity>10583</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>5</position>\n                        <quantity>10709</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>6</position>\n                        <quantity>10872</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>7</position>\n                        <quantity>10979</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>8</position>\n                        <quantity>11006</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>9</position>\n                        <quantity>10901</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>10</position>\n                        <quantity>10798</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>11</position>\n                        <quantity>10634</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>12</position>\n                        <quantity>10612</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>13</position>\n                        <quantity>10607</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>14</position>\n                        <quantity>10554</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>15</position>\n                        <quantity>10426</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>16</position>\n                        <quantity>10453</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>17</position>\n                        <quantity>10429</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>18</position>\n                        <quantity>10330</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>19</position>\n                        <quantity>10228</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>20</position>\n                        <quantity>10099</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>21</position>\n                        <quantity>9972</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>22</position>\n                        <quantity>9828</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>23</position>\n                        <quantity>9737</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>24</position>\n                        <quantity>9711</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>2</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A01</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID codingScheme=\"A01\">10Y1001A1001A46L</inBiddingZone_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t<Period>\n\t\t\t<timeInterval>\n\t\t\t\t<start>2023-12-28T23:00Z</start>\n\t\t\t\t<end>2023-12-29T23:00Z</end>\n\t\t\t</timeInterval>\n\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>1</position>\n                        <quantity>9693</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>2</position>\n                        <quantity>9765</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>3</position>\n                        <quantity>9900</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>4</position>\n                        <quantity>10031</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>5</position>\n                        <quantity>10097</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>6</position>\n                        <quantity>10147</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>7</position>\n                        <quantity>10259</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>8</position>\n                        <quantity>10273</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>9</position>\n                        <quantity>10242</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>10</position>\n                        <quantity>10169</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>11</position>\n                        <quantity>10058</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>12</position>\n                        <quantity>9996</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>13</position>\n                        <quantity>10004</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>14</position>\n                        <quantity>10014</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>15</position>\n                        <quantity>9961</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>16</position>\n                        <quantity>10115</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>17</position>\n                        <quantity>10130</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>18</position>\n                        <quantity>10090</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>19</position>\n                        <quantity>9999</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>20</position>\n                        <quantity>9887</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>21</position>\n                        <quantity>9764</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>22</position>\n                        <quantity>9627</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>23</position>\n                        <quantity>9522</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>24</position>\n                        <quantity>9449</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n\t<TimeSeries>\n\t\t<mRID>3</mRID>\n\t\t<businessType>A01</businessType>\n\t\t<objectAggregation>A01</objectAggregation>\n\t\t<inBiddingZone_Domain.mRID codingScheme=\"A01\">10Y1001A1001A46L</inBiddingZone_Domain.mRID>\n\t\t<quantity_Measure_Unit.name>MAW</quantity_Measure_Unit.name>\n\t\t<curveType>A01</curveType>\n\t\t<Period>\n\t\t\t<timeInterval>\n\t\t\t\t<start>2023-12-29T23:00Z</start>\n\t\t\t\t<end>2023-12-30T23:00Z</end>\n\t\t\t</timeInterval>\n\t\t\t<resolution>PT60M</resolution>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>1</position>\n                        <quantity>9467</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>2</position>\n                        <quantity>9463</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>3</position>\n                        <quantity>9454</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>4</position>\n                        <quantity>9428</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>5</position>\n                        <quantity>9403</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>6</position>\n                        <quantity>9409</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>7</position>\n                        <quantity>9345</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>8</position>\n                        <quantity>9286</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>9</position>\n                        <quantity>9198</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>10</position>\n                        <quantity>9217</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>11</position>\n                        <quantity>9232</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>12</position>\n                        <quantity>9236</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>13</position>\n                        <quantity>9257</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>14</position>\n                        <quantity>9251</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>15</position>\n                        <quantity>9257</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>16</position>\n                        <quantity>9476</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>17</position>\n                        <quantity>9694</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>18</position>\n                        <quantity>9780</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>19</position>\n                        <quantity>9837</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>20</position>\n                        <quantity>9795</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>21</position>\n                        <quantity>9652</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>22</position>\n                        <quantity>9669</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>23</position>\n                        <quantity>9620</quantity>\n\t\t\t\t</Point>\n\t\t\t\t<Point>\n\t\t\t\t\t<position>24</position>\n                        <quantity>9598</quantity>\n\t\t\t\t</Point>\n\t\t</Period>\n\t</TimeSeries>\n</GL_MarketDocument>"
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    "path": "electricitymap/contrib/parsers/tests/mocks/ERCOT.json",
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00:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5063.9,\n            \"hsl\": 9881.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084,\n            \"hsl\": 5098,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 165.9,\n            \"hsl\": 2113.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21929.9,\n            \"hsl\": 22440.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9940.5,\n            \"hsl\": 13308.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 00:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5019.2,\n            \"hsl\": 9881.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.1,\n            \"hsl\": 5097.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 279.2,\n            \"hsl\": 1422.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21904.4,\n            \"hsl\": 22166.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9780.2,\n            \"hsl\": 13309,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 00:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4974.5,\n            \"hsl\": 9881.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.9,\n            \"hsl\": 5098.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 289.1,\n            \"hsl\": 2678.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21891.5,\n            \"hsl\": 22293.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9678.1,\n            \"hsl\": 13235.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 00:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4924.9,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.9,\n            \"hsl\": 5098,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 250,\n            \"hsl\": 3925.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.2,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21858.4,\n            \"hsl\": 22482.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9714.5,\n            \"hsl\": 13166.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 00:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4978.1,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.9,\n            \"hsl\": 5097.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 354.1,\n            \"hsl\": 5517.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.4,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21828.7,\n            \"hsl\": 22472.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9578.7,\n            \"hsl\": 13152,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 00:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5040.9,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087,\n            \"hsl\": 5098.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 260.8,\n            \"hsl\": 4086.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21816.5,\n            \"hsl\": 22341.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9559.4,\n            \"hsl\": 13145.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 00:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5039,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.6,\n            \"hsl\": 5098.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 200.1,\n            \"hsl\": 1411,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.2,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22074,\n            \"hsl\": 22437,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9489,\n            \"hsl\": 13144.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 00:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5071.1,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.4,\n            \"hsl\": 5098.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 74.8,\n            \"hsl\": 746.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22020.4,\n            \"hsl\": 22412.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9469.3,\n            \"hsl\": 13145.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5097.7,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086,\n            \"hsl\": 5097.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 97.6,\n            \"hsl\": 2376,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.1,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22128.8,\n            \"hsl\": 22346.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9414.7,\n            \"hsl\": 13151.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5091,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.9,\n            \"hsl\": 5097.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 29.1,\n            \"hsl\": 1726.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22249.1,\n            \"hsl\": 22431.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9371.2,\n            \"hsl\": 13146.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5032.5,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.7,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.2,\n            \"hsl\": 5098.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 39.6,\n            \"hsl\": 633.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22185.4,\n            \"hsl\": 22414,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9279.7,\n            \"hsl\": 13154,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4934,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.6,\n            \"hsl\": 5097.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 45.6,\n            \"hsl\": 960.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.1,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22291.8,\n            \"hsl\": 22523.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9286.4,\n            \"hsl\": 13160,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4972.5,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5098,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 79.7,\n            \"hsl\": 2476.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.2,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22266.2,\n            \"hsl\": 22483.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9386.9,\n            \"hsl\": 13086.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4882.9,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.7,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.3,\n            \"hsl\": 5097.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 32.2,\n            \"hsl\": 683.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22210.1,\n            \"hsl\": 22504.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9466.5,\n            \"hsl\": 13157.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4899.7,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.9,\n            \"hsl\": 5098.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 51,\n            \"hsl\": 1577.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22293.4,\n            \"hsl\": 22772.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9425.4,\n            \"hsl\": 13159.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4933.7,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.8,\n            \"hsl\": 5097.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 129.9,\n            \"hsl\": 1313.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22246.5,\n            \"hsl\": 22806,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9413.8,\n            \"hsl\": 13156.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4958.5,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.8,\n            \"hsl\": 5098.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 76.6,\n            \"hsl\": 800.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22194.8,\n            \"hsl\": 22598.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9386.6,\n            \"hsl\": 13156.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4936.4,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.8,\n            \"hsl\": 5098.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 53.4,\n            \"hsl\": 2024.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.2,\n            \"hsl\": 0.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22211.1,\n            \"hsl\": 22542.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9394.1,\n            \"hsl\": 13160.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4858.6,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.7,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.1,\n            \"hsl\": 5098.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 51.6,\n            \"hsl\": 629.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22171.2,\n            \"hsl\": 22419.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9290.5,\n            \"hsl\": 13159.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 01:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4746.6,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.2,\n            \"hsl\": 5098.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 148.5,\n            \"hsl\": 2026.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22116.6,\n            \"hsl\": 22639,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9297,\n            \"hsl\": 13175.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4780.2,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.7,\n            \"hsl\": 5098.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 189.9,\n            \"hsl\": 1936.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1,\n            \"hsl\": 0.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21998.1,\n            \"hsl\": 22404.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9344.8,\n            \"hsl\": 13180.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4852.1,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.2,\n            \"hsl\": 5098.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 211.2,\n            \"hsl\": 2821.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21510.8,\n            \"hsl\": 22506.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9407.9,\n            \"hsl\": 13177.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4718.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.5,\n            \"hsl\": 5098.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 141.4,\n            \"hsl\": 2631,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21627.4,\n            \"hsl\": 22391.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9383.4,\n            \"hsl\": 13175.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4679.8,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 6.3,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.7,\n            \"hsl\": 5098.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 169.4,\n            \"hsl\": 3948.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21565.4,\n            \"hsl\": 22710.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9366.5,\n            \"hsl\": 13178.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4742.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.5,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5097.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 254.1,\n            \"hsl\": 4663.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21523.8,\n            \"hsl\": 22493.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9383.9,\n            \"hsl\": 13179,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4799.9,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 6,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.6,\n            \"hsl\": 5098.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 164.6,\n            \"hsl\": 1240.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21609.4,\n            \"hsl\": 22233.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9375.3,\n            \"hsl\": 13177,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4763.9,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 6.3,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.6,\n            \"hsl\": 5098.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 157.5,\n            \"hsl\": 1139.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21850.7,\n            \"hsl\": 22452.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9343.3,\n            \"hsl\": 13173.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4711.8,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.7,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.4,\n            \"hsl\": 5098.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 176,\n            \"hsl\": 1698.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21771.2,\n            \"hsl\": 22078,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9359.7,\n            \"hsl\": 13184.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4631.5,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.4,\n            \"hsl\": 5097.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 149.6,\n            \"hsl\": 1452,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.1,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21820.4,\n            \"hsl\": 22272.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9335.6,\n            \"hsl\": 13180.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4630.2,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 8.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5097.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 217.6,\n            \"hsl\": 1318.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1,\n            \"hsl\": 0.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21736.8,\n            \"hsl\": 22109.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9340.3,\n            \"hsl\": 13183.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4631.6,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 57.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.2,\n            \"hsl\": 5097.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 213.3,\n            \"hsl\": 2047.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21641.6,\n            \"hsl\": 22092.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9325.9,\n            \"hsl\": 13186.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 02:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4547.1,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.7,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.7,\n            \"hsl\": 5097.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 308.3,\n            \"hsl\": 2676.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.1,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21551.1,\n            \"hsl\": 21827.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9337.8,\n            \"hsl\": 13201.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4454.9,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.4,\n            \"hsl\": 5098.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 337,\n            \"hsl\": 3502.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21593.7,\n            \"hsl\": 22036.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9307.4,\n            \"hsl\": 13197.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4471.7,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.2,\n            \"hsl\": 5099.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 298.3,\n            \"hsl\": 3618.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.1,\n            \"hsl\": 0.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21504.5,\n            \"hsl\": 22130.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9465.7,\n            \"hsl\": 13197.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4499.4,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.8,\n            \"hsl\": 5097.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 219.1,\n            \"hsl\": 1562.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21378.5,\n            \"hsl\": 21766.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9551.5,\n            \"hsl\": 13189.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4496.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.3,\n            \"hsl\": 5098.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 195.7,\n            \"hsl\": 1539.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21363.3,\n            \"hsl\": 21909.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9588.7,\n            \"hsl\": 13195.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4515.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.6,\n            \"hsl\": 5098.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 199.2,\n            \"hsl\": 1354.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21209.8,\n            \"hsl\": 21399.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9574.2,\n            \"hsl\": 13196.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4546.2,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.5,\n            \"hsl\": 5098.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 232.8,\n            \"hsl\": 2791.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21182.8,\n            \"hsl\": 21664.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9575.4,\n            \"hsl\": 13198.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4593.9,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.6,\n            \"hsl\": 5097.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 299.3,\n            \"hsl\": 2875.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21067.5,\n            \"hsl\": 21431.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9605.4,\n            \"hsl\": 13200.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4630.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.4,\n            \"hsl\": 5099.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 242.2,\n            \"hsl\": 2525.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20978.3,\n            \"hsl\": 21366.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9584.3,\n            \"hsl\": 13194.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4715.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.3,\n            \"hsl\": 5098.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 146.6,\n            \"hsl\": 1770.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.3,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20942.8,\n            \"hsl\": 21235.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9729.7,\n            \"hsl\": 13197.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4808.1,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.1,\n            \"hsl\": 5098.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 307.9,\n            \"hsl\": 3471.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20897.6,\n            \"hsl\": 21223.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9476.7,\n            \"hsl\": 13177,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4851.1,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.8,\n            \"hsl\": 5098.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 488.2,\n            \"hsl\": 2669.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20782.1,\n            \"hsl\": 21050.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9654.7,\n            \"hsl\": 13169.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 03:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4876.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.6,\n            \"hsl\": 5098.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 533.3,\n            \"hsl\": 1969.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20729.3,\n            \"hsl\": 21143.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9670.8,\n            \"hsl\": 13174,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4955.2,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.2,\n            \"hsl\": 5099.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 493.5,\n            \"hsl\": 2630.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20860.2,\n            \"hsl\": 20943.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9808.1,\n            \"hsl\": 13183.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5068.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.8,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 464.8,\n            \"hsl\": 1903.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20776.8,\n            \"hsl\": 20916.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9776.6,\n            \"hsl\": 13169.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5143.2,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.3,\n            \"hsl\": 5099,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 478.5,\n            \"hsl\": 4149.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20689.1,\n            \"hsl\": 20812.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9770.5,\n            \"hsl\": 13162.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5205.4,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.8,\n            \"hsl\": 5098.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 426,\n            \"hsl\": 2755.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20577.5,\n            \"hsl\": 20782.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9790.8,\n            \"hsl\": 13163.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5278.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.2,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 403.8,\n            \"hsl\": 2219.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20448,\n            \"hsl\": 20547.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9752.9,\n            \"hsl\": 13153.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5256.4,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.6,\n            \"hsl\": 5099.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 331.3,\n            \"hsl\": 2837,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20543.1,\n            \"hsl\": 20631.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9679,\n            \"hsl\": 13309,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5295.2,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.8,\n            \"hsl\": 5099.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 340.5,\n            \"hsl\": 2175.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20441.5,\n            \"hsl\": 20658.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9764.3,\n            \"hsl\": 13305.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5233.6,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.5,\n            \"hsl\": 5099.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 282.3,\n            \"hsl\": 2594.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20477.2,\n            \"hsl\": 20631,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9831.7,\n            \"hsl\": 13299.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5192.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.5,\n            \"hsl\": 5099.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 294.3,\n            \"hsl\": 3496,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20552.6,\n            \"hsl\": 20795.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9825.5,\n            \"hsl\": 13308.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5137.8,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.5,\n            \"hsl\": 5099.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 348,\n            \"hsl\": 3318.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20544.7,\n            \"hsl\": 20669.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9798.1,\n            \"hsl\": 13313.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5150.8,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.2,\n            \"hsl\": 5099.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 371.1,\n            \"hsl\": 3314.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.3,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20467.5,\n            \"hsl\": 20677.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9835.5,\n            \"hsl\": 13312.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 04:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5179.1,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5099.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 345.5,\n            \"hsl\": 3058.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20465.5,\n            \"hsl\": 20551.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9980.9,\n            \"hsl\": 13324.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5277.8,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5090.1,\n            \"hsl\": 5099.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 482.1,\n            \"hsl\": 4005.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20401,\n            \"hsl\": 20617.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10108.8,\n            \"hsl\": 13328.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5381.3,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087,\n            \"hsl\": 5098.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 565.1,\n            \"hsl\": 3537.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20363.9,\n            \"hsl\": 20488.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10132.9,\n            \"hsl\": 13321.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5511.1,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5090,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 533.4,\n            \"hsl\": 3005.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20205.9,\n            \"hsl\": 20384.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10253.9,\n            \"hsl\": 13310,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5688.7,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.4,\n            \"hsl\": 5098.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 383.4,\n            \"hsl\": 1481.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20145.1,\n            \"hsl\": 20300.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10314,\n            \"hsl\": 13306.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5795.9,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.6,\n            \"hsl\": 5098.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 323.1,\n            \"hsl\": 1906.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20143.8,\n            \"hsl\": 20323.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10232.6,\n            \"hsl\": 13307,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5857.7,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5098.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 404.3,\n            \"hsl\": 3858.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20188.3,\n            \"hsl\": 20306.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10206.5,\n            \"hsl\": 13306,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5944.5,\n            \"hsl\": 10016.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.2,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 386.5,\n            \"hsl\": 1868.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20083.1,\n            \"hsl\": 20291.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10273.6,\n            \"hsl\": 13305.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6035.6,\n            \"hsl\": 10014.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.7,\n            \"hsl\": 5099.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 273.8,\n            \"hsl\": 1825.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20202.6,\n            \"hsl\": 20394.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10246.9,\n            \"hsl\": 13305.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6072.8,\n            \"hsl\": 10014.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.8,\n            \"hsl\": 5099,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 360,\n            \"hsl\": 5431.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20192.4,\n            \"hsl\": 20403.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10241.4,\n            \"hsl\": 13305.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6151.9,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.8,\n            \"hsl\": 5099.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 345.1,\n            \"hsl\": 3205,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20123.7,\n            \"hsl\": 20255.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10225.4,\n            \"hsl\": 13303,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6198,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.1,\n            \"hsl\": 5099.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 401.9,\n            \"hsl\": 4428.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20109,\n            \"hsl\": 20324.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10218.3,\n            \"hsl\": 13308,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 05:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6278.7,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.4,\n            \"hsl\": 5099,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 500.2,\n            \"hsl\": 4360.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19988.7,\n            \"hsl\": 20133,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10232.1,\n            \"hsl\": 13304.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6412.4,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.2,\n            \"hsl\": 5099.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 772.3,\n            \"hsl\": 3969.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19917.7,\n            \"hsl\": 20113.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10379.4,\n            \"hsl\": 13307.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6623.4,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.6,\n            \"hsl\": 5098.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 686.4,\n            \"hsl\": 3085.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19862.7,\n            \"hsl\": 19949.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10502.8,\n            \"hsl\": 13295.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6862,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5098.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 674,\n            \"hsl\": 3599.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19871.1,\n            \"hsl\": 20043.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10534.4,\n            \"hsl\": 13267,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 7029.7,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.2,\n            \"hsl\": 5099.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 702.6,\n            \"hsl\": 3568.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19816.4,\n            \"hsl\": 19966.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10538.3,\n            \"hsl\": 13255.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 7098.3,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.7,\n            \"hsl\": 5098.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 703.8,\n            \"hsl\": 3742.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19792.1,\n            \"hsl\": 19950.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10560.3,\n            \"hsl\": 13235,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 7169.2,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.5,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 605,\n            \"hsl\": 3257.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19670.2,\n            \"hsl\": 19782.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10588.3,\n            \"hsl\": 13232.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 7298.1,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5090.2,\n            \"hsl\": 5099.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 528.5,\n            \"hsl\": 4063.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19693.6,\n            \"hsl\": 19843.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10629.4,\n            \"hsl\": 13234.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 7085.9,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.7,\n            \"hsl\": 5098.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1180.3,\n            \"hsl\": 2968.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19660.1,\n            \"hsl\": 19832.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10255.1,\n            \"hsl\": 13242.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6953,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5098.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1414.5,\n            \"hsl\": 3508.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19679.2,\n            \"hsl\": 19877.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10108.7,\n            \"hsl\": 13244.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6838,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5099.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1535.9,\n            \"hsl\": 3896.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.4,\n            \"hsl\": 1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19648.7,\n            \"hsl\": 19887.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10326.9,\n            \"hsl\": 13243.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6876.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.9,\n            \"hsl\": 5099.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1482.6,\n            \"hsl\": 3294.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 6.1,\n            \"hsl\": 5.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19703.4,\n            \"hsl\": 19857.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10441.4,\n            \"hsl\": 13247.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 06:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 7027.1,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.9,\n            \"hsl\": 5098.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1323.4,\n            \"hsl\": 3360.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18.5,\n            \"hsl\": 18.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19777.3,\n            \"hsl\": 19948.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10478.5,\n            \"hsl\": 13218.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 7094.3,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.9,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.5,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1542.1,\n            \"hsl\": 3536.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 55.4,\n            \"hsl\": 59.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19742,\n            \"hsl\": 19932.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10519.2,\n            \"hsl\": 13282.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6922.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.5,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1447.8,\n            \"hsl\": 3663.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 152.4,\n            \"hsl\": 160.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19949.1,\n            \"hsl\": 20089.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10561.6,\n            \"hsl\": 13244.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6976,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.3,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1222.1,\n            \"hsl\": 3758,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 328.6,\n            \"hsl\": 327.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19958.9,\n            \"hsl\": 20063.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10580.2,\n            \"hsl\": 13337.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6997.9,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.2,\n            \"hsl\": 5099.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 998.3,\n            \"hsl\": 2922.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 603.8,\n            \"hsl\": 607.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19953.3,\n            \"hsl\": 20102.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10518.8,\n            \"hsl\": 13333.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6978.2,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.9,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.6,\n            \"hsl\": 5098.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 626.1,\n            \"hsl\": 2111.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1010.8,\n            \"hsl\": 1020.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20103.4,\n            \"hsl\": 20254.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10505.8,\n            \"hsl\": 13340,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6778.5,\n            \"hsl\": 10018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.2,\n            \"hsl\": 5098.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 441.5,\n            \"hsl\": 1917.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1516.8,\n            \"hsl\": 1535.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20083.2,\n            \"hsl\": 20255.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10453.2,\n            \"hsl\": 13274.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6605.5,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.7,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.7,\n            \"hsl\": 5099.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 417.4,\n            \"hsl\": 1269.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 2172.6,\n            \"hsl\": 2208,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20051.4,\n            \"hsl\": 20139.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10189.5,\n            \"hsl\": 13192.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6370.8,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 279.2,\n            \"hsl\": 1116.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 3011.5,\n            \"hsl\": 3048.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20166,\n            \"hsl\": 20430.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9766.1,\n            \"hsl\": 13206.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6111.2,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.1,\n            \"hsl\": 5099.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 189.9,\n            \"hsl\": 1074.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 3914.1,\n            \"hsl\": 3947.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20185.6,\n            \"hsl\": 20516.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9437.1,\n            \"hsl\": 13215.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5889.7,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.5,\n            \"hsl\": 5099,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 78.5,\n            \"hsl\": 1347.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 4912.6,\n            \"hsl\": 5022.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19992.2,\n            \"hsl\": 20424.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 8966.8,\n            \"hsl\": 13145.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5716.4,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.9,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 21.5,\n            \"hsl\": 1026.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 5872.6,\n            \"hsl\": 6013.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19873.3,\n            \"hsl\": 20053.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 8633.9,\n            \"hsl\": 13198.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 07:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5508,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.5,\n            \"hsl\": 5099.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 17.9,\n            \"hsl\": 700.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 7028.4,\n            \"hsl\": 7216.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19727,\n            \"hsl\": 20103.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 8178.7,\n            \"hsl\": 12582.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5397.6,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.9,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.1,\n            \"hsl\": 5099.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 151.4,\n            \"hsl\": 2767.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 8365.5,\n            \"hsl\": 8485.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19886.3,\n            \"hsl\": 20212.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7755.7,\n            \"hsl\": 12084.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5237.1,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.9,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.3,\n            \"hsl\": 5098.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 19.6,\n            \"hsl\": 1174.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 9571.3,\n            \"hsl\": 9696,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19720.8,\n            \"hsl\": 20085.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7222.4,\n            \"hsl\": 11916.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5087.8,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.4,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 24.7,\n            \"hsl\": 498.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 10675.8,\n            \"hsl\": 10799.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19259.7,\n            \"hsl\": 19528,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6818.2,\n            \"hsl\": 12132.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4952.2,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087,\n            \"hsl\": 5098.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2,\n            \"hsl\": 495.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 11834.1,\n            \"hsl\": 11921.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18981.8,\n            \"hsl\": 19230.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6569.5,\n            \"hsl\": 11568.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4822.4,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.2,\n            \"hsl\": 5099.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1.3,\n            \"hsl\": 720.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 12822,\n            \"hsl\": 13141.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18530,\n            \"hsl\": 18745.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6344.4,\n            \"hsl\": 11384.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4655.9,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.9,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.1,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 10.5,\n            \"hsl\": 1510.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 13476.9,\n            \"hsl\": 14197.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18024.6,\n            \"hsl\": 18619.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6241.1,\n            \"hsl\": 11580.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4573.7,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.9,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.7,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 36.6,\n            \"hsl\": 1997.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 13939.2,\n            \"hsl\": 15154.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17605.9,\n            \"hsl\": 18114.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5911.1,\n            \"hsl\": 11293.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4339.9,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5099.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.3,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 160.5,\n            \"hsl\": 1451.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15001,\n            \"hsl\": 15992.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17245.1,\n            \"hsl\": 17548.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5709.6,\n            \"hsl\": 11007.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4128.9,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.3,\n            \"hsl\": 5098.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 210.2,\n            \"hsl\": 1709.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15397,\n            \"hsl\": 16856,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16885.4,\n            \"hsl\": 17320.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5642.5,\n            \"hsl\": 10883.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3978.6,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.1,\n            \"hsl\": 5100.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 53.7,\n            \"hsl\": 718.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16504.3,\n            \"hsl\": 17639.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16601.5,\n            \"hsl\": 16849.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5592.8,\n            \"hsl\": 11122.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3814,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.8,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.3,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 19.1,\n            \"hsl\": 601.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17408.9,\n            \"hsl\": 18331.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16043.3,\n            \"hsl\": 16370.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5545.4,\n            \"hsl\": 11191.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 08:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3713.4,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 40.9,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.1,\n            \"hsl\": 5099.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 59.5,\n            \"hsl\": 2151.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17299.3,\n            \"hsl\": 18434,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15698.5,\n            \"hsl\": 16150.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5553.4,\n            \"hsl\": 11333.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3626.8,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.7,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 289.7,\n            \"hsl\": 1294.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18055.4,\n            \"hsl\": 19065.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15270.1,\n            \"hsl\": 15432.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5311.9,\n            \"hsl\": 10970.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3540.3,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.4,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 303.9,\n            \"hsl\": 2503.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18722.2,\n            \"hsl\": 19533.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14986,\n            \"hsl\": 15230.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5165.9,\n            \"hsl\": 10951.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3454.3,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.6,\n            \"hsl\": 5098.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 54.3,\n            \"hsl\": 447.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19525.3,\n            \"hsl\": 19834.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14646.5,\n            \"hsl\": 14818.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5034.2,\n            \"hsl\": 10403.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3357.2,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.4,\n            \"hsl\": 5099.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.2,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 60.6,\n            \"hsl\": 210.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19773.5,\n            \"hsl\": 19936.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14340.8,\n            \"hsl\": 14546.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5026.4,\n            \"hsl\": 10399.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3297.5,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088,\n            \"hsl\": 5099.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 55.7,\n            \"hsl\": 275.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19885.1,\n            \"hsl\": 20041.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14177.9,\n            \"hsl\": 14425.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5022.1,\n            \"hsl\": 10577.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3298.8,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.4,\n            \"hsl\": 5098.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 77.1,\n            \"hsl\": 1877.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19882.6,\n            \"hsl\": 20094.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 13975.5,\n            \"hsl\": 14216.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5039.4,\n            \"hsl\": 10394,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3280.7,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.2,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 424,\n            \"hsl\": 3661.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19795.5,\n            \"hsl\": 20125.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 13825.1,\n            \"hsl\": 14060.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5042.5,\n            \"hsl\": 10612,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3246.8,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.5,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 298.5,\n            \"hsl\": 708.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19909.9,\n            \"hsl\": 20019,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 13676.2,\n            \"hsl\": 13864.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4997.2,\n            \"hsl\": 10602.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3222.9,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.1,\n            \"hsl\": 5099.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 74.9,\n            \"hsl\": 463.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19980.9,\n            \"hsl\": 20111.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 13711.3,\n            \"hsl\": 13964.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4992.9,\n            \"hsl\": 10417.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3223.6,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.7,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.6,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 52.3,\n            \"hsl\": 507.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 20053.7,\n            \"hsl\": 20154.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 13909.4,\n            \"hsl\": 14138.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5009.9,\n            \"hsl\": 10607.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3257.6,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5099,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 142.1,\n            \"hsl\": 2587.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19676,\n            \"hsl\": 19866.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 13957,\n            \"hsl\": 14157.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5060.6,\n            \"hsl\": 10608.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 09:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3219.6,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.3,\n            \"hsl\": 5099.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 120.8,\n            \"hsl\": 662.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19700.7,\n            \"hsl\": 19818.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14053.2,\n            \"hsl\": 14251.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4992.5,\n            \"hsl\": 10357.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3210.6,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.8,\n            \"hsl\": 5099,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 84,\n            \"hsl\": 522.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19800,\n            \"hsl\": 19911.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 13878.1,\n            \"hsl\": 14003.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4981.4,\n            \"hsl\": 10538.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3212,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.2,\n            \"hsl\": 5098.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0.1,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 12.2,\n            \"hsl\": 288.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19792.5,\n            \"hsl\": 19898,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14005.3,\n            \"hsl\": 14184.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4975.6,\n            \"hsl\": 10351.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3244.7,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.8,\n            \"hsl\": 5098.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 39.2,\n            \"hsl\": 2223.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19582,\n            \"hsl\": 19754.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14257.3,\n            \"hsl\": 14489.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5015.7,\n            \"hsl\": 10536.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3217.3,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.1,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 389.5,\n            \"hsl\": 1076.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 19056,\n            \"hsl\": 19839.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14252.4,\n            \"hsl\": 14431.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4966.2,\n            \"hsl\": 10342.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3221.9,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.3,\n            \"hsl\": 5099.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 269.4,\n            \"hsl\": 1082.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18912.4,\n            \"hsl\": 19463.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14259.8,\n            \"hsl\": 14363.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4973.5,\n            \"hsl\": 10530.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3225,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.9,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 71.4,\n            \"hsl\": 1098.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18654.4,\n            \"hsl\": 19217.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14343.1,\n            \"hsl\": 14433.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4970.9,\n            \"hsl\": 10525.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3213.1,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.5,\n            \"hsl\": 5099.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 71,\n            \"hsl\": 997.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18538.5,\n            \"hsl\": 19150.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14317.9,\n            \"hsl\": 14479.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4968,\n            \"hsl\": 10426.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3228.3,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.4,\n            \"hsl\": 5098.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 40.6,\n            \"hsl\": 1422.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18554,\n            \"hsl\": 19416.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14424.2,\n            \"hsl\": 14553.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4991,\n            \"hsl\": 10611.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3220.9,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.3,\n            \"hsl\": 5098.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 64.9,\n            \"hsl\": 927.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18597.8,\n            \"hsl\": 19514.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14481.3,\n            \"hsl\": 14626.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4971.5,\n            \"hsl\": 10604.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3232.6,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.4,\n            \"hsl\": 5099.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 38.4,\n            \"hsl\": 3616,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18437.4,\n            \"hsl\": 19089.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14498.7,\n            \"hsl\": 14686.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4995,\n            \"hsl\": 10607.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3217.5,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.8,\n            \"hsl\": 5099.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 10.6,\n            \"hsl\": 618.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18862.1,\n            \"hsl\": 19259.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14425.5,\n            \"hsl\": 14500.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4973.8,\n            \"hsl\": 10872.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 10:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3223,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.7,\n            \"hsl\": 5096.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 22.8,\n            \"hsl\": 934.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18755.1,\n            \"hsl\": 19214.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14577.8,\n            \"hsl\": 14685.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4977.8,\n            \"hsl\": 10636.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3240.5,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.1,\n            \"hsl\": 5098.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 74.2,\n            \"hsl\": 3559,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18273.3,\n            \"hsl\": 18964,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14605.5,\n            \"hsl\": 14796.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5011.7,\n            \"hsl\": 10598.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3215.2,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.6,\n            \"hsl\": 5098.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 298.3,\n            \"hsl\": 2523.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18188.5,\n            \"hsl\": 19005.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14663.3,\n            \"hsl\": 14754.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4976.6,\n            \"hsl\": 10414.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3222,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.4,\n            \"hsl\": 5099.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 4.5,\n            \"hsl\": 951.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18567.3,\n            \"hsl\": 19120,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14697.3,\n            \"hsl\": 14901.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4999.6,\n            \"hsl\": 10621.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3243,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.8,\n            \"hsl\": 5097.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 26.7,\n            \"hsl\": 2447.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18510.6,\n            \"hsl\": 19040,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14762.3,\n            \"hsl\": 15004.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5094.2,\n            \"hsl\": 11165.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3225.2,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.1,\n            \"hsl\": 5098.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 178.3,\n            \"hsl\": 1504.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18099.8,\n            \"hsl\": 18671.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14918,\n            \"hsl\": 15073,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5067.1,\n            \"hsl\": 11164.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3231,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085,\n            \"hsl\": 5097.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 99.8,\n            \"hsl\": 2135.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 18072.8,\n            \"hsl\": 18681.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14961.4,\n            \"hsl\": 15055.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5052.1,\n            \"hsl\": 11117.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3216.4,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.9,\n            \"hsl\": 5097.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 8.2,\n            \"hsl\": 852.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17906.3,\n            \"hsl\": 18451.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14916.8,\n            \"hsl\": 15006.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5039.4,\n            \"hsl\": 10935.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3226.1,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.1,\n            \"hsl\": 5098.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 12.7,\n            \"hsl\": 1121.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17647.8,\n            \"hsl\": 18288.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15110.3,\n            \"hsl\": 15260.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5050,\n            \"hsl\": 11114.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3221.1,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.5,\n            \"hsl\": 5098.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 271.7,\n            \"hsl\": 1146.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17489.4,\n            \"hsl\": 18328.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15079,\n            \"hsl\": 15208.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5050.7,\n            \"hsl\": 10419.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3218.5,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.8,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5098.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 36.3,\n            \"hsl\": 970.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17943.9,\n            \"hsl\": 18505.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15079.1,\n            \"hsl\": 15264.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5052.5,\n            \"hsl\": 10416.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3227.4,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.9,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.9,\n            \"hsl\": 5098.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 269.8,\n            \"hsl\": 1015.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17608.7,\n            \"hsl\": 18270,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 14999,\n            \"hsl\": 15231.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5063.5,\n            \"hsl\": 10599,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 11:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3219.8,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 6.3,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085,\n            \"hsl\": 5098.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 303.8,\n            \"hsl\": 1171.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17313.5,\n            \"hsl\": 18088,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15018.9,\n            \"hsl\": 15166.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5120.1,\n            \"hsl\": 10554.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3224.5,\n            \"hsl\": 10019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.9,\n            \"hsl\": 5098.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 203.5,\n            \"hsl\": 1047.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17712.9,\n            \"hsl\": 18321.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15292.4,\n            \"hsl\": 15433.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5146.9,\n            \"hsl\": 11069.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3228.4,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.6,\n            \"hsl\": 5098.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 202.9,\n            \"hsl\": 751.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17355.6,\n            \"hsl\": 18054.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15328,\n            \"hsl\": 15465.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5156.2,\n            \"hsl\": 10953.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3232.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.2,\n            \"hsl\": 5097.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 210.9,\n            \"hsl\": 1094.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17041.5,\n            \"hsl\": 18367.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15371.8,\n            \"hsl\": 15605.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5368.5,\n            \"hsl\": 10954.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3228.9,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.6,\n            \"hsl\": 5098.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 206.6,\n            \"hsl\": 1259.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16660.7,\n            \"hsl\": 17856.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15613.3,\n            \"hsl\": 15807.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5415.8,\n            \"hsl\": 11309.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3228.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.9,\n            \"hsl\": 5097.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 146,\n            \"hsl\": 2076.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16774,\n            \"hsl\": 18135.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15533.6,\n            \"hsl\": 15847.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5400.7,\n            \"hsl\": 11127.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3223.6,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5098.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 112.5,\n            \"hsl\": 778.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16705.1,\n            \"hsl\": 17777.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15575.4,\n            \"hsl\": 15766.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5413.6,\n            \"hsl\": 11079.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3223.1,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.3,\n            \"hsl\": 5097.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 186.8,\n            \"hsl\": 2120,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16554.8,\n            \"hsl\": 17788.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15602.7,\n            \"hsl\": 15772.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5435.2,\n            \"hsl\": 11263.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3243.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.9,\n            \"hsl\": 5097.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 440.5,\n            \"hsl\": 4862,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16162.1,\n            \"hsl\": 18200.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15724.1,\n            \"hsl\": 16121.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5421.3,\n            \"hsl\": 11269.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3215.6,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.9,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 474.5,\n            \"hsl\": 2796.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16085.3,\n            \"hsl\": 17396.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15850,\n            \"hsl\": 16067.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5377,\n            \"hsl\": 11080.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3213.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.2,\n            \"hsl\": 5097.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 263.7,\n            \"hsl\": 959.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16544.4,\n            \"hsl\": 17713.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15666,\n            \"hsl\": 15846.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5367.4,\n            \"hsl\": 11078.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3217.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.2,\n            \"hsl\": 5097.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 195.8,\n            \"hsl\": 1045,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16580.2,\n            \"hsl\": 17482.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 15841.1,\n            \"hsl\": 15931.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5376.2,\n            \"hsl\": 11079.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 12:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3214.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.8,\n            \"hsl\": 5097.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 192.3,\n            \"hsl\": 1534.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16323,\n            \"hsl\": 17434.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16085,\n            \"hsl\": 16359.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5381.3,\n            \"hsl\": 10992.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3239.4,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.4,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 334.4,\n            \"hsl\": 3830.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15804.6,\n            \"hsl\": 17744.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16253.9,\n            \"hsl\": 16477.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5271.6,\n            \"hsl\": 11244.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3255.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.1,\n            \"hsl\": 5096.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 724,\n            \"hsl\": 6373.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15849.4,\n            \"hsl\": 17952,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16179.7,\n            \"hsl\": 16441.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4975.7,\n            \"hsl\": 11250.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3214,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084,\n            \"hsl\": 5097.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 416.6,\n            \"hsl\": 2504.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16511.1,\n            \"hsl\": 17980.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16105.5,\n            \"hsl\": 16251.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4806.7,\n            \"hsl\": 10614.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3218.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.8,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 113.5,\n            \"hsl\": 1048.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17160.5,\n            \"hsl\": 17826.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16429.5,\n            \"hsl\": 16621.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4716.9,\n            \"hsl\": 10391.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3226.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.1,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 85.9,\n            \"hsl\": 1203.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 17024.4,\n            \"hsl\": 17884.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16558.1,\n            \"hsl\": 16812.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4723.8,\n            \"hsl\": 10106.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3225.7,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.7,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 81.4,\n            \"hsl\": 1155.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16981.3,\n            \"hsl\": 17974,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16618.4,\n            \"hsl\": 16752,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4721.9,\n            \"hsl\": 10102.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3220.8,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.4,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 74.3,\n            \"hsl\": 1260.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16669.7,\n            \"hsl\": 18055.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16761.5,\n            \"hsl\": 16907.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4718.9,\n            \"hsl\": 9972.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3218.6,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.8,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 89.9,\n            \"hsl\": 1211.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16663.4,\n            \"hsl\": 18073,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16888.3,\n            \"hsl\": 16978.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4722.3,\n            \"hsl\": 10152.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3216.4,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.4,\n            \"hsl\": 5096.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 68.6,\n            \"hsl\": 855.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16655.1,\n            \"hsl\": 18215.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 16955,\n            \"hsl\": 17120.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4717.9,\n            \"hsl\": 10152.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3213.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.2,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 77.9,\n            \"hsl\": 1031.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16493.9,\n            \"hsl\": 18188.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17050.3,\n            \"hsl\": 17188.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4791.5,\n            \"hsl\": 10138,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3237.8,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 280.8,\n            \"hsl\": 4373.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15982.4,\n            \"hsl\": 18078.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17078.8,\n            \"hsl\": 17370.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4836.2,\n            \"hsl\": 10144.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 13:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3221.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.7,\n            \"hsl\": 5098,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 236.3,\n            \"hsl\": 1574.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16158.3,\n            \"hsl\": 18149.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17088.8,\n            \"hsl\": 17189.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4799.4,\n            \"hsl\": 10122.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3218.9,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.3,\n            \"hsl\": 5097.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 102.3,\n            \"hsl\": 1024.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16265.7,\n            \"hsl\": 18221.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17335.2,\n            \"hsl\": 17545.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4789.8,\n            \"hsl\": 10119.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3234.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.4,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 128.3,\n            \"hsl\": 3329.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16087,\n            \"hsl\": 18328.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17473.2,\n            \"hsl\": 17829.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4819.1,\n            \"hsl\": 10126.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3240.1,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.6,\n            \"hsl\": 5096.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 385.2,\n            \"hsl\": 4402.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15835.8,\n            \"hsl\": 18470,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17539.8,\n            \"hsl\": 17921.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4813.5,\n            \"hsl\": 10304,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3245.9,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 697.7,\n            \"hsl\": 5750.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15934.7,\n            \"hsl\": 18682.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17207.4,\n            \"hsl\": 18273.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4815,\n            \"hsl\": 10302.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3239.7,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.8,\n            \"hsl\": 5096.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 503.3,\n            \"hsl\": 3250.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15946.9,\n            \"hsl\": 18434,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17724.2,\n            \"hsl\": 18221.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4745,\n            \"hsl\": 10463.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3254.3,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.1,\n            \"hsl\": 5097.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 568.7,\n            \"hsl\": 6198.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16025,\n            \"hsl\": 18928.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17439,\n            \"hsl\": 18471,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4845.2,\n            \"hsl\": 10244.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3218.9,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.6,\n            \"hsl\": 5096.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 170,\n            \"hsl\": 1638.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16278.8,\n            \"hsl\": 18638,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 17681.5,\n            \"hsl\": 18350.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4755,\n            \"hsl\": 10231.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3223,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.1,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 85.3,\n            \"hsl\": 470.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16187.9,\n            \"hsl\": 18442.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18163.2,\n            \"hsl\": 18768.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4761.1,\n            \"hsl\": 10411.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3226.4,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.5,\n            \"hsl\": 5097.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 97,\n            \"hsl\": 959.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16116,\n            \"hsl\": 17971,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18313.3,\n            \"hsl\": 18514.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4773,\n            \"hsl\": 10479.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3223.7,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.5,\n            \"hsl\": 5096.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 84.9,\n            \"hsl\": 512.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 16034.4,\n            \"hsl\": 18230.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18526.9,\n            \"hsl\": 18753.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4783.1,\n            \"hsl\": 10480.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3237.3,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.6,\n            \"hsl\": 5096.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 101.6,\n            \"hsl\": 2373.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15607.7,\n            \"hsl\": 18345.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18729.9,\n            \"hsl\": 19190.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4804.6,\n            \"hsl\": 10482.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 14:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3254.6,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5079.9,\n            \"hsl\": 5096.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 176.2,\n            \"hsl\": 4677.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15171.1,\n            \"hsl\": 18105.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18744,\n            \"hsl\": 19405.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4816.3,\n            \"hsl\": 10516.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3218.4,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.2,\n            \"hsl\": 5096.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 91,\n            \"hsl\": 635.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15389.8,\n            \"hsl\": 17689.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18747.4,\n            \"hsl\": 19169.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4774.1,\n            \"hsl\": 10511.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3216.9,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.3,\n            \"hsl\": 5096,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 76.7,\n            \"hsl\": 531.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15230.2,\n            \"hsl\": 17839.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18914.6,\n            \"hsl\": 19246.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4786.6,\n            \"hsl\": 10560.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3215.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.2,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 107.6,\n            \"hsl\": 947.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15045.9,\n            \"hsl\": 17835.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19063.9,\n            \"hsl\": 19352.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4812.5,\n            \"hsl\": 10397,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3225.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.4,\n            \"hsl\": 5095.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 161,\n            \"hsl\": 1214.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 14742.4,\n            \"hsl\": 17368.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19117.5,\n            \"hsl\": 19603.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4840.6,\n            \"hsl\": 10545.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3236.4,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.7,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 511.2,\n            \"hsl\": 3513.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 14498.6,\n            \"hsl\": 17677.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19106.4,\n            \"hsl\": 19674.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4876.9,\n            \"hsl\": 10600.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3220.7,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.9,\n            \"hsl\": 5097.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 259.6,\n            \"hsl\": 1524.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 14835.7,\n            \"hsl\": 17480.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19251,\n            \"hsl\": 19784.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4877,\n            \"hsl\": 10594.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3235.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.1,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 203.6,\n            \"hsl\": 3637.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15136,\n            \"hsl\": 17866,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 18989.3,\n            \"hsl\": 20398.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4894.6,\n            \"hsl\": 10595.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3256.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.7,\n            \"hsl\": 5096.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 242.2,\n            \"hsl\": 5286.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 14739.5,\n            \"hsl\": 17138.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19357.1,\n            \"hsl\": 20489.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4911.2,\n            \"hsl\": 10593.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3227.3,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.1,\n            \"hsl\": 5096.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 170.9,\n            \"hsl\": 2553,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 14685.7,\n            \"hsl\": 16666.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19420.4,\n            \"hsl\": 20480.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4911.1,\n            \"hsl\": 11107.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3223.8,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.3,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 133.7,\n            \"hsl\": 760,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 14533.8,\n            \"hsl\": 16205.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19435.2,\n            \"hsl\": 20107.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 4984.1,\n            \"hsl\": 11502.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3218.4,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.1,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 187.6,\n            \"hsl\": 666.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 13993,\n            \"hsl\": 15242,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19599.9,\n            \"hsl\": 20232.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5276.5,\n            \"hsl\": 11382.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 15:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3314.2,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.1,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 230.5,\n            \"hsl\": 5633.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 13025,\n            \"hsl\": 14774.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 19891,\n            \"hsl\": 20943.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5733.8,\n            \"hsl\": 11573,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3391.4,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5078.7,\n            \"hsl\": 5095.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 296.6,\n            \"hsl\": 2733.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 12303.1,\n            \"hsl\": 13571.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20025.1,\n            \"hsl\": 20810.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6119.1,\n            \"hsl\": 11878.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3557.8,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.1,\n            \"hsl\": 5096,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 306.9,\n            \"hsl\": 1290.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 11725,\n            \"hsl\": 12686.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20189.1,\n            \"hsl\": 20919.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6584.3,\n            \"hsl\": 12284.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3715.9,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.6,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 449.6,\n            \"hsl\": 3563,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 10550.1,\n            \"hsl\": 11904.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20400.7,\n            \"hsl\": 21151.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7196.7,\n            \"hsl\": 12243.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3895.1,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.4,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 625.8,\n            \"hsl\": 4425.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 9603.5,\n            \"hsl\": 10882.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20602.2,\n            \"hsl\": 20922.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7645,\n            \"hsl\": 12244.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4035.6,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 17.6,\n            \"hsl\": 19,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5079.9,\n            \"hsl\": 5095.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 859,\n            \"hsl\": 6106.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 8852.5,\n            \"hsl\": 9890,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20585.9,\n            \"hsl\": 21227.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 8016.5,\n            \"hsl\": 12318.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4190.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 17.7,\n            \"hsl\": 19,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.7,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 918.2,\n            \"hsl\": 4263,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 8231.7,\n            \"hsl\": 8855.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20674.4,\n            \"hsl\": 20896.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 8496.7,\n            \"hsl\": 12319.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4579.3,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 17.7,\n            \"hsl\": 19,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082,\n            \"hsl\": 5096.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 885,\n            \"hsl\": 4937.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 7443,\n            \"hsl\": 7854.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20630.5,\n            \"hsl\": 20842.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 8875,\n            \"hsl\": 12337.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4947.3,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 17.8,\n            \"hsl\": 19,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.4,\n            \"hsl\": 5097.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 827.8,\n            \"hsl\": 5067.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 6873.7,\n            \"hsl\": 7225.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20558.7,\n            \"hsl\": 20822.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9109.1,\n            \"hsl\": 12386.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5303.9,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 18.1,\n            \"hsl\": 19,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.4,\n            \"hsl\": 5096.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 956.1,\n            \"hsl\": 5294.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 6122.1,\n            \"hsl\": 6243.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 20692.8,\n            \"hsl\": 21137.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9284,\n            \"hsl\": 12388.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5629.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 17.5,\n            \"hsl\": 19,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.7,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1153.6,\n            \"hsl\": 3704,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 5097.3,\n            \"hsl\": 5173,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21139.3,\n            \"hsl\": 21220.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9447.1,\n            \"hsl\": 12377.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5963.9,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 66.4,\n            \"hsl\": 109,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.4,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1408,\n            \"hsl\": 3412.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 4147.2,\n            \"hsl\": 4197.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21175.7,\n            \"hsl\": 21282.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9698.8,\n            \"hsl\": 12379.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 16:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6287.5,\n            \"hsl\": 10021.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 108.5,\n            \"hsl\": 109,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.9,\n            \"hsl\": 5096.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1560.8,\n            \"hsl\": 3671.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 3227.1,\n            \"hsl\": 3271.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21344.9,\n            \"hsl\": 21524.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9853,\n            \"hsl\": 12379,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6450.6,\n            \"hsl\": 9996.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 205.8,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.6,\n            \"hsl\": 5096.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1634.7,\n            \"hsl\": 5312.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 2430.1,\n            \"hsl\": 2478.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21451.5,\n            \"hsl\": 21588.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9897.9,\n            \"hsl\": 12397.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6543.1,\n            \"hsl\": 9996.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 204.4,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.4,\n            \"hsl\": 5096.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1882.9,\n            \"hsl\": 5313.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1778.1,\n            \"hsl\": 1823.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21516.1,\n            \"hsl\": 21642.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10064.3,\n            \"hsl\": 12554.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6579.9,\n            \"hsl\": 10001.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 203.8,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.8,\n            \"hsl\": 5096.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2437.1,\n            \"hsl\": 4890.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1259,\n            \"hsl\": 1292.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21410,\n            \"hsl\": 21654.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10175.4,\n            \"hsl\": 12597.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6621,\n            \"hsl\": 10006.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 204.5,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.4,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2629.5,\n            \"hsl\": 4882.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 841,\n            \"hsl\": 869.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21613.8,\n            \"hsl\": 21986.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10312.7,\n            \"hsl\": 12645.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6677.6,\n            \"hsl\": 10011.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 204.4,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.9,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2799.9,\n            \"hsl\": 5101.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 513.9,\n            \"hsl\": 534,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21793.7,\n            \"hsl\": 21996.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10367.9,\n            \"hsl\": 12646.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6778,\n            \"hsl\": 10011.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 203.1,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.8,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2828,\n            \"hsl\": 5287.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 291.2,\n            \"hsl\": 308.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 21947.3,\n            \"hsl\": 22215.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10446.2,\n            \"hsl\": 12647.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6950.9,\n            \"hsl\": 10011.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 204.2,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2545.8,\n            \"hsl\": 4595.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 142.4,\n            \"hsl\": 150.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22251.3,\n            \"hsl\": 22436.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10505.4,\n            \"hsl\": 12649.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 7051.9,\n            \"hsl\": 10013.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 205.6,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.8,\n            \"hsl\": 5096.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2782.1,\n            \"hsl\": 6327.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 53.4,\n            \"hsl\": 57.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22364.3,\n            \"hsl\": 22600.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10511.7,\n            \"hsl\": 12625.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6617.8,\n            \"hsl\": 9453.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 204,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.3,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 3156.8,\n            \"hsl\": 5760.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 14.9,\n            \"hsl\": 16.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22443.2,\n            \"hsl\": 22978.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10529.7,\n            \"hsl\": 12620.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6726.4,\n            \"hsl\": 9453.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 203.8,\n            \"hsl\": 208,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.5,\n            \"hsl\": 5096.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2883.7,\n            \"hsl\": 5113.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.9,\n            \"hsl\": 3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22299.1,\n            \"hsl\": 22949.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10649.2,\n            \"hsl\": 12726.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6879.3,\n            \"hsl\": 9453.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 203.1,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.9,\n            \"hsl\": 5097.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2248,\n            \"hsl\": 3930.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.3,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 22970.8,\n            \"hsl\": 23462.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10759.8,\n            \"hsl\": 12821.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 17:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6953.5,\n            \"hsl\": 9453.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 203.1,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.8,\n            \"hsl\": 5097.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1824.7,\n            \"hsl\": 3284,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.1,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 23488.4,\n            \"hsl\": 24134.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10728.5,\n            \"hsl\": 12855.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6760,\n            \"hsl\": 9453.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 182.1,\n            \"hsl\": 189.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.3,\n            \"hsl\": 5098.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2152.3,\n            \"hsl\": 3800.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.2,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 23432.9,\n            \"hsl\": 24064.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10640.4,\n            \"hsl\": 12858.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6522.3,\n            \"hsl\": 9453.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 225.9,\n            \"hsl\": 234.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.8,\n            \"hsl\": 5096.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2155.9,\n            \"hsl\": 3645.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.3,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 23633.1,\n            \"hsl\": 24126.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10675.7,\n            \"hsl\": 12860.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6335.5,\n            \"hsl\": 9453.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 181.8,\n            \"hsl\": 189.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084,\n            \"hsl\": 5097.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2197.8,\n            \"hsl\": 3966.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.3,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 23743,\n            \"hsl\": 24489.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10687.9,\n            \"hsl\": 12863.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5865,\n            \"hsl\": 8629.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 229,\n            \"hsl\": 234.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.9,\n            \"hsl\": 5097.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2097.6,\n            \"hsl\": 6298.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 23960.5,\n            \"hsl\": 25661.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10743.6,\n            \"hsl\": 12855.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6051.8,\n            \"hsl\": 8629.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 229.2,\n            \"hsl\": 234.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.3,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2370.5,\n            \"hsl\": 6447.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 23561.7,\n            \"hsl\": 25725.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10741.3,\n            \"hsl\": 12813.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6238.7,\n            \"hsl\": 8629.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 230.1,\n            \"hsl\": 234.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.4,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 2090.7,\n            \"hsl\": 5981,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 23854.8,\n            \"hsl\": 26352.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10788.2,\n            \"hsl\": 12816.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6282.5,\n            \"hsl\": 8629.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 225.6,\n            \"hsl\": 234.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.3,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1777.2,\n            \"hsl\": 3632.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.1,\n            \"hsl\": 0.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24260.1,\n            \"hsl\": 25717.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10727.9,\n            \"hsl\": 12809.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6287,\n            \"hsl\": 8629.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 226,\n            \"hsl\": 234.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080,\n            \"hsl\": 5096.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1143.8,\n            \"hsl\": 3897.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.2,\n            \"hsl\": 1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24901.8,\n            \"hsl\": 26256.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10726.6,\n            \"hsl\": 12816.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 6371.3,\n            \"hsl\": 8626.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 227.9,\n            \"hsl\": 234.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1004.2,\n            \"hsl\": 2349.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25018.9,\n            \"hsl\": 25932.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10678.7,\n            \"hsl\": 12774.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5723.8,\n            \"hsl\": 8020.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 229.7,\n            \"hsl\": 234.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081,\n            \"hsl\": 5096.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1104.5,\n            \"hsl\": 5084.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25256.2,\n            \"hsl\": 27223.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10679,\n            \"hsl\": 12756.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5800.9,\n            \"hsl\": 8020.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 227,\n            \"hsl\": 234.3,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.4,\n            \"hsl\": 5096.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1046.1,\n            \"hsl\": 3917.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25261.1,\n            \"hsl\": 26279.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10601,\n            \"hsl\": 12686.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 18:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5786.8,\n            \"hsl\": 8019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 200.5,\n            \"hsl\": 205.5,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.7,\n            \"hsl\": 5093.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1178.1,\n            \"hsl\": 6334.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24948,\n            \"hsl\": 26848.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10508.3,\n            \"hsl\": 12582.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5791.6,\n            \"hsl\": 8019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 208.2,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.7,\n            \"hsl\": 5094,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 968.1,\n            \"hsl\": 4925.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25200.4,\n            \"hsl\": 26826.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10501.5,\n            \"hsl\": 12571.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5836.5,\n            \"hsl\": 8019.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 209,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.9,\n            \"hsl\": 5093.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 798.3,\n            \"hsl\": 4314.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25493.6,\n            \"hsl\": 26550.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10453.7,\n            \"hsl\": 12574.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5580.8,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 209.8,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.2,\n            \"hsl\": 5093.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 918.5,\n            \"hsl\": 3169.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25595.1,\n            \"hsl\": 26809.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10453.2,\n            \"hsl\": 12582.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5572.2,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 208,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.2,\n            \"hsl\": 5093.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 742.6,\n            \"hsl\": 2229.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25669.4,\n            \"hsl\": 26866.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10399,\n            \"hsl\": 12578.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5511.5,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 209.5,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.9,\n            \"hsl\": 5093.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 708.4,\n            \"hsl\": 2681.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25704.8,\n            \"hsl\": 27425.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10400.7,\n            \"hsl\": 12591,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5457.7,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 209.1,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.6,\n            \"hsl\": 5094.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 641.9,\n            \"hsl\": 4450.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25731.7,\n            \"hsl\": 27426.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10410.8,\n            \"hsl\": 12592.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5250.3,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 209.2,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.6,\n            \"hsl\": 5093.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 672.9,\n            \"hsl\": 2486.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25806.4,\n            \"hsl\": 27230.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10405,\n            \"hsl\": 12593.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5206.2,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 208.4,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.9,\n            \"hsl\": 5093.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 769,\n            \"hsl\": 2281.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25602.2,\n            \"hsl\": 27101.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10281.3,\n            \"hsl\": 12597.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5143.8,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 210.2,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.1,\n            \"hsl\": 5093.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 843.3,\n            \"hsl\": 5592.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25448.9,\n            \"hsl\": 27994.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10265.4,\n            \"hsl\": 12603.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5265.6,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 210.2,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085,\n            \"hsl\": 5094.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 662.9,\n            \"hsl\": 5116.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25559.1,\n            \"hsl\": 27908.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10228.4,\n            \"hsl\": 12481.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5197.7,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 209.8,\n            \"hsl\": 214,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.8,\n            \"hsl\": 5094,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 714.8,\n            \"hsl\": 4666.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25689,\n            \"hsl\": 28257.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10290.5,\n            \"hsl\": 12507.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 19:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5091.7,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 130.1,\n            \"hsl\": 151.4,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.4,\n            \"hsl\": 5094.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 609.5,\n            \"hsl\": 4361.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25794.3,\n            \"hsl\": 27681.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10272.7,\n            \"hsl\": 12509,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5082.2,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 114.5,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084,\n            \"hsl\": 5094,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 594,\n            \"hsl\": 3505.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25692.3,\n            \"hsl\": 27050.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10288.4,\n            \"hsl\": 12511.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5246,\n            \"hsl\": 8018.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 115.5,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.1,\n            \"hsl\": 5094.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 620.6,\n            \"hsl\": 5640.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.2,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25427.2,\n            \"hsl\": 28228.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10288.1,\n            \"hsl\": 12510.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5085.7,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 115,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.5,\n            \"hsl\": 5094.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 380.8,\n            \"hsl\": 1550.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25627,\n            \"hsl\": 27516,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10249.8,\n            \"hsl\": 12506.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4946.6,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 115.4,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.4,\n            \"hsl\": 5094.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 317.3,\n            \"hsl\": 1922.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25833.9,\n            \"hsl\": 27699.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10244.1,\n            \"hsl\": 12514.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4914.7,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 115.1,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.4,\n            \"hsl\": 5094.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 346.4,\n            \"hsl\": 3065,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25756.5,\n            \"hsl\": 27502.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10153.1,\n            \"hsl\": 12513.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4878.1,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 114.1,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.9,\n            \"hsl\": 5094.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 397,\n            \"hsl\": 1488.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25825,\n            \"hsl\": 27272.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10147.5,\n            \"hsl\": 12516.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4792.9,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 115,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5094.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 298.9,\n            \"hsl\": 1790.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25943.6,\n            \"hsl\": 27198,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10111.7,\n            \"hsl\": 12513.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4783.8,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 115.1,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082,\n            \"hsl\": 5093.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 295.5,\n            \"hsl\": 1861.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26043.5,\n            \"hsl\": 27601.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 10011.3,\n            \"hsl\": 12514.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4744.8,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 115.4,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.8,\n            \"hsl\": 5093.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 319.4,\n            \"hsl\": 3403.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25957.4,\n            \"hsl\": 27316.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9917.1,\n            \"hsl\": 12422.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4725,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 114,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.4,\n            \"hsl\": 5094.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 321,\n            \"hsl\": 1646.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25910.3,\n            \"hsl\": 27279.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9869.8,\n            \"hsl\": 12424.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4684.2,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 114.2,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.9,\n            \"hsl\": 5094.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 262.8,\n            \"hsl\": 1869.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26006.5,\n            \"hsl\": 27346.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9898.5,\n            \"hsl\": 12425.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 20:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4610,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 115,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.4,\n            \"hsl\": 5093.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 225.6,\n            \"hsl\": 1611.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26100.5,\n            \"hsl\": 27494.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9883.1,\n            \"hsl\": 12430.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4581.3,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 114.1,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.4,\n            \"hsl\": 5093.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 175.3,\n            \"hsl\": 1086,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25983.7,\n            \"hsl\": 27724.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9655.8,\n            \"hsl\": 12435.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4590.7,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 104.8,\n            \"hsl\": 115,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.8,\n            \"hsl\": 5093.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 395.3,\n            \"hsl\": 5305.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25851,\n            \"hsl\": 27971.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9677.4,\n            \"hsl\": 12437.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4580.9,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084,\n            \"hsl\": 5094.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 347.2,\n            \"hsl\": 2158.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25880.7,\n            \"hsl\": 27521.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9660.1,\n            \"hsl\": 12433.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4540.8,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.5,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.3,\n            \"hsl\": 5094.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 362.5,\n            \"hsl\": 1769.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25856.6,\n            \"hsl\": 27606.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9634.6,\n            \"hsl\": 12437.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4479.4,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.5,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.4,\n            \"hsl\": 5094.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 406.4,\n            \"hsl\": 1843.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25862.3,\n            \"hsl\": 27441.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9488.8,\n            \"hsl\": 12436.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4476.8,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.5,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.6,\n            \"hsl\": 5094.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 243.6,\n            \"hsl\": 3162.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25978.1,\n            \"hsl\": 27805.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9430.3,\n            \"hsl\": 12433.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4391.2,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.6,\n            \"hsl\": 5093.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 488.5,\n            \"hsl\": 2836.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26068.9,\n            \"hsl\": 27620.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9294.1,\n            \"hsl\": 12426.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4339.6,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.5,\n            \"hsl\": 5093.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 255.3,\n            \"hsl\": 1148,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26143.6,\n            \"hsl\": 27595.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9374.1,\n            \"hsl\": 12426.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4249.5,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 51.5,\n            \"hsl\": 51,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.4,\n            \"hsl\": 5094.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 289.8,\n            \"hsl\": 4392.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25938,\n            \"hsl\": 28490.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9433.9,\n            \"hsl\": 12434.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4149.1,\n            \"hsl\": 8028.5,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.5,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.6,\n            \"hsl\": 5094.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 277,\n            \"hsl\": 2444.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26145.3,\n            \"hsl\": 27947.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9298.7,\n            \"hsl\": 12430.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4038.8,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.5,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.5,\n            \"hsl\": 5094,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 311.1,\n            \"hsl\": 2762.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26085.9,\n            \"hsl\": 27900.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9315.2,\n            \"hsl\": 12431.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 21:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3960.1,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.3,\n            \"hsl\": 5093.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 304.3,\n            \"hsl\": 2112.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26088.8,\n            \"hsl\": 27316.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 9290.7,\n            \"hsl\": 12390.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4163.6,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.5,\n            \"hsl\": 5093.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 718,\n            \"hsl\": 2055,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25978.7,\n            \"hsl\": 27538.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 8927.5,\n            \"hsl\": 12398.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4465.3,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.5,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5079.7,\n            \"hsl\": 5092.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 778.5,\n            \"hsl\": 5451.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25865,\n            \"hsl\": 28333.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 8697.1,\n            \"hsl\": 12449.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4826.2,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.5,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.2,\n            \"hsl\": 5093,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 923.4,\n            \"hsl\": 6056.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25893.9,\n            \"hsl\": 28772.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 8082.8,\n            \"hsl\": 12546.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5049.4,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.1,\n            \"hsl\": 5094.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 944.8,\n            \"hsl\": 2346.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25485.1,\n            \"hsl\": 26879.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7904.1,\n            \"hsl\": 12556.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5281.1,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.5,\n            \"hsl\": 5093.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 600,\n            \"hsl\": 2187.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25710.2,\n            \"hsl\": 27508.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7952.3,\n            \"hsl\": 11222,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5507.7,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082,\n            \"hsl\": 5093.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 578.9,\n            \"hsl\": 5706.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25719.2,\n            \"hsl\": 28340.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7812.4,\n            \"hsl\": 10720.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5496,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.1,\n            \"hsl\": 5094.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 386.2,\n            \"hsl\": 1225.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25636.9,\n            \"hsl\": 27614.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7794.4,\n            \"hsl\": 10711.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5508.6,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.3,\n            \"hsl\": 5093.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 314.4,\n            \"hsl\": 1303.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25972.1,\n            \"hsl\": 27729.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7723,\n            \"hsl\": 10773.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5408.3,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.7,\n            \"hsl\": 5094,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 283.2,\n            \"hsl\": 1846.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25923.3,\n            \"hsl\": 27865.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7536.9,\n            \"hsl\": 10772,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5217.4,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.4,\n            \"hsl\": 5094.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 212.6,\n            \"hsl\": 2582.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1.5,\n            \"hsl\": 0.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26138.5,\n            \"hsl\": 27980.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7397.4,\n            \"hsl\": 10650.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 5024.5,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.3,\n            \"hsl\": 5093.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 215.5,\n            \"hsl\": 1317.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26214.7,\n            \"hsl\": 27800.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7423.3,\n            \"hsl\": 10935.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 22:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4913,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5080.3,\n            \"hsl\": 5093.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 238.4,\n            \"hsl\": 1364.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26188.5,\n            \"hsl\": 27984.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7422.7,\n            \"hsl\": 10901.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4916.5,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.5,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.6,\n            \"hsl\": 5093.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 147.2,\n            \"hsl\": 3273.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26238.8,\n            \"hsl\": 28048.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7510.7,\n            \"hsl\": 10851.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4895.3,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.4,\n            \"hsl\": 5094.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 103.6,\n            \"hsl\": 984.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26193.3,\n            \"hsl\": 28121.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7484.4,\n            \"hsl\": 10637.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4799.2,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.7,\n            \"hsl\": 5094.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 105.8,\n            \"hsl\": 1691.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26139,\n            \"hsl\": 28448.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7430.4,\n            \"hsl\": 10600.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4747,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5081.2,\n            \"hsl\": 5093.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 87.3,\n            \"hsl\": 760.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26491.2,\n            \"hsl\": 28259.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7042.5,\n            \"hsl\": 10579.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4682.8,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.1,\n            \"hsl\": 5095.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 108.8,\n            \"hsl\": 667.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26488.1,\n            \"hsl\": 27909.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 7085.5,\n            \"hsl\": 10578.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4606.4,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.1,\n            \"hsl\": 5094.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 85.2,\n            \"hsl\": 534.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26550.1,\n            \"hsl\": 28042.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6961.5,\n            \"hsl\": 10586.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4495.6,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.6,\n            \"hsl\": 5094.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 94.3,\n            \"hsl\": 3613.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26468.1,\n            \"hsl\": 28447.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6907.6,\n            \"hsl\": 10592.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4349.6,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.2,\n            \"hsl\": 5095.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 217.6,\n            \"hsl\": 1165.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26623.5,\n            \"hsl\": 28345.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6782.4,\n            \"hsl\": 10585.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4334.8,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.7,\n            \"hsl\": 5094.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 246.9,\n            \"hsl\": 1480.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26425.9,\n            \"hsl\": 28457.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6766.6,\n            \"hsl\": 10573.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4324.8,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 96.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.9,\n            \"hsl\": 5094.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 255.7,\n            \"hsl\": 1333,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26338.8,\n            \"hsl\": 28272.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6579.2,\n            \"hsl\": 10388.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4293.1,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.1,\n            \"hsl\": 5094.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 189.7,\n            \"hsl\": 1088,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26474,\n            \"hsl\": 27877.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6557.4,\n            \"hsl\": 10394.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-23 23:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4073.3,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 48.4,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.7,\n            \"hsl\": 5095.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 136.4,\n            \"hsl\": 4793.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26612.1,\n            \"hsl\": 28989.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6454.8,\n            \"hsl\": 10513.7,\n            \"seasonalCapacity\": 68234\n          }\n        }\n      },\n      \"2024-11-24\": {\n        \"2024-11-24 00:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4110.7,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.8,\n            \"hsl\": 5094.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 163.8,\n            \"hsl\": 1357.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26330.2,\n            \"hsl\": 28064,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6519.4,\n            \"hsl\": 10487.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4126.8,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085,\n            \"hsl\": 5094.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 127.3,\n            \"hsl\": 540.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26096.4,\n            \"hsl\": 27915.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6674.6,\n            \"hsl\": 10296.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 4141.7,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.5,\n            \"hsl\": 5094.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 342.4,\n            \"hsl\": 2750.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26091.5,\n            \"hsl\": 27743.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6501.9,\n            \"hsl\": 10493.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3965.6,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.7,\n            \"hsl\": 5095.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 393.3,\n            \"hsl\": 1786.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26124.2,\n            \"hsl\": 27824.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6470.1,\n            \"hsl\": 10491.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3940.7,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.3,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.4,\n            \"hsl\": 5094.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 631,\n            \"hsl\": 4937.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26108.2,\n            \"hsl\": 28434.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6233.9,\n            \"hsl\": 10493.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3918.9,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5095.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 487.2,\n            \"hsl\": 1969.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26005.3,\n            \"hsl\": 27433.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6374.6,\n            \"hsl\": 10295,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3938.6,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.9,\n            \"hsl\": 5095.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 240.4,\n            \"hsl\": 1255.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26074.5,\n            \"hsl\": 27474.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6538.5,\n            \"hsl\": 10488.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3953.7,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.4,\n            \"hsl\": 5094.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 307.7,\n            \"hsl\": 4630.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26160.9,\n            \"hsl\": 28276.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6204.4,\n            \"hsl\": 10466.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3872.2,\n            \"hsl\": 8033.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.6,\n            \"hsl\": 5094.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 247.6,\n            \"hsl\": 1676.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26255,\n            \"hsl\": 27657.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6444.8,\n            \"hsl\": 10297.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3817.1,\n            \"hsl\": 8593.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5094.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 228.9,\n            \"hsl\": 1367.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.6,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25978.9,\n            \"hsl\": 27535,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6480.6,\n            \"hsl\": 10488.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3650.5,\n            \"hsl\": 8593.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.8,\n            \"hsl\": 5095,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 160.3,\n            \"hsl\": 1062.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26082.8,\n            \"hsl\": 27477.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6477.7,\n            \"hsl\": 10296.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 00:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3656.8,\n            \"hsl\": 8593.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.8,\n            \"hsl\": 5094.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 51,\n            \"hsl\": 944.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26050.2,\n            \"hsl\": 27586.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6382.5,\n            \"hsl\": 10305.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3689.5,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5082.6,\n            \"hsl\": 5094.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 40.2,\n            \"hsl\": 1029.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26304.4,\n            \"hsl\": 27795.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6154,\n            \"hsl\": 10477.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3675.5,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.7,\n            \"hsl\": 5094.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 116.9,\n            \"hsl\": 1244.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26091.1,\n            \"hsl\": 27743.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5948,\n            \"hsl\": 10282.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3514.4,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.5,\n            \"hsl\": 5094.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 81.4,\n            \"hsl\": 764.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26160.2,\n            \"hsl\": 27491.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5947.8,\n            \"hsl\": 10283.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3436,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.7,\n            \"hsl\": 5095,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 104,\n            \"hsl\": 1146.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26183.2,\n            \"hsl\": 27811.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6041.1,\n            \"hsl\": 10306.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3484.2,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.9,\n            \"hsl\": 5094.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 73.4,\n            \"hsl\": 1301.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26095.6,\n            \"hsl\": 27433.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5997.5,\n            \"hsl\": 10497.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3530.8,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.4,\n            \"hsl\": 5094.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1,\n            \"hsl\": 427.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26090.4,\n            \"hsl\": 27629.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5992.3,\n            \"hsl\": 10574,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3558.3,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.3,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.6,\n            \"hsl\": 5094.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 181.6,\n            \"hsl\": 5398.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25845.6,\n            \"hsl\": 28273.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5973,\n            \"hsl\": 10578.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3518.9,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.4,\n            \"hsl\": 5094.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 145.9,\n            \"hsl\": 2429.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26056.1,\n            \"hsl\": 27881.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5918.9,\n            \"hsl\": 10575.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3498,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.4,\n            \"hsl\": 5095.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 59.2,\n            \"hsl\": 548.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26158.6,\n            \"hsl\": 27668.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5908.3,\n            \"hsl\": 10569.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3495.2,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.1,\n            \"hsl\": 5095,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 28.3,\n            \"hsl\": 1092.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 26093,\n            \"hsl\": 27683.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5980,\n            \"hsl\": 10572.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3500.2,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.2,\n            \"hsl\": 5095,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 51.1,\n            \"hsl\": 582.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25831.8,\n            \"hsl\": 27454.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5972.3,\n            \"hsl\": 10377.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 01:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3458,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.8,\n            \"hsl\": 5095.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 17.3,\n            \"hsl\": 393.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25818.5,\n            \"hsl\": 27134.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5928.7,\n            \"hsl\": 10382.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3488.2,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.8,\n            \"hsl\": 5096,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 22.1,\n            \"hsl\": 777.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25760.2,\n            \"hsl\": 27626.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5904.5,\n            \"hsl\": 10568.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3404,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.8,\n            \"hsl\": 5095,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 31.7,\n            \"hsl\": 1591.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25864.7,\n            \"hsl\": 27642.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5917.8,\n            \"hsl\": 10580.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3386.5,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.1,\n            \"hsl\": 5095.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 84.6,\n            \"hsl\": 895.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25979,\n            \"hsl\": 27638.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5902.8,\n            \"hsl\": 10382.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3471.2,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.7,\n            \"hsl\": 5095,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 50.8,\n            \"hsl\": 663.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25727.1,\n            \"hsl\": 27523.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5897.6,\n            \"hsl\": 10573.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3430.6,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5095.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 29.8,\n            \"hsl\": 889.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25697,\n            \"hsl\": 27300.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5883.3,\n            \"hsl\": 10379.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3379.7,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5094.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 144.1,\n            \"hsl\": 3166,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25712.8,\n            \"hsl\": 27592.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5858,\n            \"hsl\": 10573.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3474.4,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.7,\n            \"hsl\": 5095.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 25.4,\n            \"hsl\": 731.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1,\n            \"hsl\": 0.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25603.8,\n            \"hsl\": 27063.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5854.2,\n            \"hsl\": 10569.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3493.9,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089,\n            \"hsl\": 5096.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 14.9,\n            \"hsl\": 508,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25624.6,\n            \"hsl\": 27464.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5835.5,\n            \"hsl\": 10377.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3359.2,\n            \"hsl\": 8308.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.3,\n            \"hsl\": 5095.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 18.1,\n            \"hsl\": 966.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25634.2,\n            \"hsl\": 27857.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5765,\n            \"hsl\": 10568.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3334.6,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.6,\n            \"hsl\": 5095.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 130.1,\n            \"hsl\": 3194.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25579.7,\n            \"hsl\": 27523.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5775.4,\n            \"hsl\": 10383.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3421.8,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.6,\n            \"hsl\": 5095.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 46.3,\n            \"hsl\": 1880.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25569.6,\n            \"hsl\": 27646.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5754.9,\n            \"hsl\": 10571.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 02:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3444.7,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.3,\n            \"hsl\": 5095.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 34.2,\n            \"hsl\": 722.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25523.3,\n            \"hsl\": 27412,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5728.1,\n            \"hsl\": 10397.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3318.5,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.2,\n            \"hsl\": 5095.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 39.5,\n            \"hsl\": 894.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25533.6,\n            \"hsl\": 27148.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5701.5,\n            \"hsl\": 10398.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3283.4,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.6,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 54.6,\n            \"hsl\": 1650.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25488.5,\n            \"hsl\": 27228.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5755.8,\n            \"hsl\": 10594.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3220.9,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.1,\n            \"hsl\": 5096,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 56.6,\n            \"hsl\": 1215,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25402.7,\n            \"hsl\": 27225.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5763.4,\n            \"hsl\": 10594.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3289.1,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.6,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 188.7,\n            \"hsl\": 5529,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25171.9,\n            \"hsl\": 27800.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5737.3,\n            \"hsl\": 10405.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3339.5,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.1,\n            \"hsl\": 5095.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 169.6,\n            \"hsl\": 2673.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25342.4,\n            \"hsl\": 27124.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5742.2,\n            \"hsl\": 10595.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3348.5,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.5,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 81,\n            \"hsl\": 1033.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25239.3,\n            \"hsl\": 26450.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5820,\n            \"hsl\": 10395.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3274.1,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.8,\n            \"hsl\": 5096,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 50.7,\n            \"hsl\": 1273.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25363.3,\n            \"hsl\": 26799.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5909.5,\n            \"hsl\": 10596.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3258,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.8,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 45.1,\n            \"hsl\": 2840.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25281.6,\n            \"hsl\": 27468.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5889.6,\n            \"hsl\": 10404.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3263.5,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 18.4,\n            \"hsl\": 857.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25275,\n            \"hsl\": 27111.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5833,\n            \"hsl\": 10399.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3195.7,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087,\n            \"hsl\": 5096.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 91.5,\n            \"hsl\": 1175.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25246.8,\n            \"hsl\": 26917.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5858.5,\n            \"hsl\": 10590.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3178.6,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.6,\n            \"hsl\": 5095.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 96.9,\n            \"hsl\": 2551.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25158.4,\n            \"hsl\": 26619.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5898.6,\n            \"hsl\": 10396.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 03:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3212.8,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.3,\n            \"hsl\": 5096.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 47.4,\n            \"hsl\": 1133.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25175.4,\n            \"hsl\": 26884.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5873.2,\n            \"hsl\": 10586.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3217.3,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.1,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 323.1,\n            \"hsl\": 2352.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24930.9,\n            \"hsl\": 26575.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5810.3,\n            \"hsl\": 10590.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3131.7,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087,\n            \"hsl\": 5095.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 50.7,\n            \"hsl\": 767.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.1,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25128.5,\n            \"hsl\": 27060.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5763.9,\n            \"hsl\": 10586.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3209.1,\n            \"hsl\": 8530.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 134.1,\n            \"hsl\": 2319.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24923.2,\n            \"hsl\": 27035,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5872.7,\n            \"hsl\": 10381.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3254.3,\n            \"hsl\": 8530.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.3,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.2,\n            \"hsl\": 5096.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 73.9,\n            \"hsl\": 2707.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24811.7,\n            \"hsl\": 26661.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5826.4,\n            \"hsl\": 10189.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3311.7,\n            \"hsl\": 8530.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5083.6,\n            \"hsl\": 5095.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 140,\n            \"hsl\": 3102.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24811.1,\n            \"hsl\": 26679.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5888.4,\n            \"hsl\": 10190.6,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3292.4,\n            \"hsl\": 8530.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.7,\n            \"hsl\": 5095.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 44.5,\n            \"hsl\": 2121.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24710.4,\n            \"hsl\": 26310,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6055,\n            \"hsl\": 10184,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3280.6,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.2,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.8,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 22.8,\n            \"hsl\": 1038.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24941.7,\n            \"hsl\": 26847,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5932.7,\n            \"hsl\": 10377,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3306.4,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.3,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.4,\n            \"hsl\": 5096.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 52.1,\n            \"hsl\": 2584.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24910.5,\n            \"hsl\": 26676.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5910.1,\n            \"hsl\": 10187.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3331.9,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 5.1,\n            \"hsl\": 6,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.7,\n            \"hsl\": 5096.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 31.2,\n            \"hsl\": 1002.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24935.7,\n            \"hsl\": 26581.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5898.3,\n            \"hsl\": 10186.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3380,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 6.2,\n            \"hsl\": 51,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.7,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 102.1,\n            \"hsl\": 4069.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24834.3,\n            \"hsl\": 27361.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5808.2,\n            \"hsl\": 10385.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3437.8,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 52.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.7,\n            \"hsl\": 5096,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 107.2,\n            \"hsl\": 2365.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24796.3,\n            \"hsl\": 26558.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5850.5,\n            \"hsl\": 10187.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 04:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3415.4,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.1,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.5,\n            \"hsl\": 5096.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 21.2,\n            \"hsl\": 529.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24925.4,\n            \"hsl\": 26376.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5877.9,\n            \"hsl\": 10203.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3406.7,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.4,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 131.2,\n            \"hsl\": 1696.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25036.2,\n            \"hsl\": 26220,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5792.3,\n            \"hsl\": 10207,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3423.3,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.7,\n            \"hsl\": 5096.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 129.5,\n            \"hsl\": 2173.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25011.2,\n            \"hsl\": 26417.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5770.6,\n            \"hsl\": 10203.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3466.1,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.2,\n            \"hsl\": 5096.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 112.5,\n            \"hsl\": 2687.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24961.3,\n            \"hsl\": 26125.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5789.2,\n            \"hsl\": 10398.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3479.1,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.2,\n            \"hsl\": 5095.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 97.2,\n            \"hsl\": 1696.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24985.5,\n            \"hsl\": 26553.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5799.2,\n            \"hsl\": 10392.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3540,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.5,\n            \"hsl\": 5096,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 148.8,\n            \"hsl\": 3106.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.4,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24969.7,\n            \"hsl\": 27321.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5781.6,\n            \"hsl\": 10399.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3556.9,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5084.7,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 324.6,\n            \"hsl\": 4555.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24900.3,\n            \"hsl\": 26590,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5788.7,\n            \"hsl\": 10205.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3574.8,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.1,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087,\n            \"hsl\": 5096.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 274.9,\n            \"hsl\": 1863.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1,\n            \"hsl\": 0.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24679.4,\n            \"hsl\": 25938.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5904.7,\n            \"hsl\": 10214.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3630.1,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.3,\n            \"hsl\": 5096,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 218.8,\n            \"hsl\": 1567.7,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24897.4,\n            \"hsl\": 26364,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5787.8,\n            \"hsl\": 10202.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3684.7,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089,\n            \"hsl\": 5095.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 224.2,\n            \"hsl\": 2930.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24882.5,\n            \"hsl\": 26441,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5937,\n            \"hsl\": 10407.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3649.3,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.8,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 197.3,\n            \"hsl\": 1949.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24823.4,\n            \"hsl\": 26174.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6075.6,\n            \"hsl\": 10218.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3679.3,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.6,\n            \"hsl\": 5095.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 71.9,\n            \"hsl\": 1005.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24853.2,\n            \"hsl\": 26001.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6215.7,\n            \"hsl\": 10416.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 05:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3761.9,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.1,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 55.2,\n            \"hsl\": 3482.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24797.4,\n            \"hsl\": 26834.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6156.2,\n            \"hsl\": 10371.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3854.3,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.1,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 639.6,\n            \"hsl\": 2046.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24366,\n            \"hsl\": 26350.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5962.8,\n            \"hsl\": 10177.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3871.1,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.1,\n            \"hsl\": 5097.7,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 399.7,\n            \"hsl\": 1903.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25022.4,\n            \"hsl\": 26249.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6056.3,\n            \"hsl\": 10197.2,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3837.4,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.1,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 274.3,\n            \"hsl\": 2085.9,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25230.7,\n            \"hsl\": 26612.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6242.5,\n            \"hsl\": 10395,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3681.5,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.8,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 332.5,\n            \"hsl\": 2064.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25351.8,\n            \"hsl\": 26497.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6207.2,\n            \"hsl\": 10201.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3613.2,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5089.7,\n            \"hsl\": 5097,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 312.9,\n            \"hsl\": 1107.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.8,\n            \"hsl\": 0.5,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25303,\n            \"hsl\": 26514.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6374.6,\n            \"hsl\": 10392,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3617.2,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5090,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 284.9,\n            \"hsl\": 1470.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25317.2,\n            \"hsl\": 26729.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6198.1,\n            \"hsl\": 10201.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3594.2,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.3,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5090,\n            \"hsl\": 5097.5,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 399.6,\n            \"hsl\": 2160.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.5,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 25111.7,\n            \"hsl\": 26270.6,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6171.4,\n            \"hsl\": 10398.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3665.3,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.5,\n            \"hsl\": 5097.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1254.6,\n            \"hsl\": 3173.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.7,\n            \"hsl\": 0.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24343.4,\n            \"hsl\": 26147.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6099.2,\n            \"hsl\": 10381,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3728.8,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.1,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.4,\n            \"hsl\": 5096.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1082.9,\n            \"hsl\": 2570.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.6,\n            \"hsl\": 0.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24259.5,\n            \"hsl\": 25778.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6478.1,\n            \"hsl\": 10376.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3771.8,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5088.1,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1008.2,\n            \"hsl\": 2975.2,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 0.9,\n            \"hsl\": 0.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24138.3,\n            \"hsl\": 26099.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6549.4,\n            \"hsl\": 10201.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:54:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3794.3,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.1,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.8,\n            \"hsl\": 5096.8,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 927.7,\n            \"hsl\": 1917.3,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 4.3,\n            \"hsl\": 3.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24057,\n            \"hsl\": 25777.4,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6498.2,\n            \"hsl\": 10383.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 06:59:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3807.2,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.8,\n            \"hsl\": 5095.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 859.7,\n            \"hsl\": 1964.1,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 15,\n            \"hsl\": 15.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24480.6,\n            \"hsl\": 26179.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6152.8,\n            \"hsl\": 10166.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:04:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3807.4,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5096.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1026.6,\n            \"hsl\": 4251.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 40.2,\n            \"hsl\": 41.4,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24573.1,\n            \"hsl\": 26548.7,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5981.2,\n            \"hsl\": 10163.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:09:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3845.2,\n            \"hsl\": 8995.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.3,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 1124.8,\n            \"hsl\": 3291,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 95.7,\n            \"hsl\": 101.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24608.7,\n            \"hsl\": 26289.1,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5918.9,\n            \"hsl\": 10161.8,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:14:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3870.2,\n            \"hsl\": 8985.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.5,\n            \"hsl\": 5096.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 987.7,\n            \"hsl\": 3072.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 221.8,\n            \"hsl\": 225,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24662.3,\n            \"hsl\": 25989.9,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6080,\n            \"hsl\": 10366.9,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:19:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3878.9,\n            \"hsl\": 8985.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.1,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.8,\n            \"hsl\": 5096.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 734.7,\n            \"hsl\": 2769.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 421.3,\n            \"hsl\": 427.7,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24662.6,\n            \"hsl\": 25928.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6172.8,\n            \"hsl\": 10178.1,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:24:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3906.8,\n            \"hsl\": 8985.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.1,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5085.3,\n            \"hsl\": 5096.2,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 500.6,\n            \"hsl\": 3612.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 681.6,\n            \"hsl\": 701.2,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24695.3,\n            \"hsl\": 26205,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6169.8,\n            \"hsl\": 10171.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:29:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3840.2,\n            \"hsl\": 8985.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.9,\n            \"hsl\": 5095.9,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 370.2,\n            \"hsl\": 2537,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1048.9,\n            \"hsl\": 1068.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24626.5,\n            \"hsl\": 25812.5,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6177.4,\n            \"hsl\": 10368.5,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:34:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3637.3,\n            \"hsl\": 8985.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.1,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5086.3,\n            \"hsl\": 5096.3,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 193.9,\n            \"hsl\": 2277.5,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 1525.6,\n            \"hsl\": 1553.3,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24642.8,\n            \"hsl\": 25802.2,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 6108.8,\n            \"hsl\": 10176.7,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:39:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3483.2,\n            \"hsl\": 8985.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.2,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.4,\n            \"hsl\": 5097.1,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 191.7,\n            \"hsl\": 5108.8,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 2018.3,\n            \"hsl\": 2141,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24556.4,\n            \"hsl\": 26312.8,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5877.8,\n            \"hsl\": 10372.3,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:44:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3416.5,\n            \"hsl\": 8985.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.1,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.7,\n            \"hsl\": 5096.6,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 276.3,\n            \"hsl\": 1784.4,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 2596,\n            \"hsl\": 2765.8,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 24268.2,\n            \"hsl\": 25475.3,\n            \"seasonalCapacity\": 39533\n          },\n          \"Natural Gas\": {\n            \"gen\": 5577.9,\n            \"hsl\": 10103.4,\n            \"seasonalCapacity\": 68234\n          }\n        },\n        \"2024-11-24 07:49:57-0600\": {\n          \"Coal and Lignite\": {\n            \"gen\": 3283.6,\n            \"hsl\": 8985.4,\n            \"seasonalCapacity\": 14713\n          },\n          \"Hydro\": {\n            \"gen\": 95.1,\n            \"hsl\": 96,\n            \"seasonalCapacity\": 575\n          },\n          \"Nuclear\": {\n            \"gen\": 5087.1,\n            \"hsl\": 5097.4,\n            \"seasonalCapacity\": 5268\n          },\n          \"Other\": {\n            \"gen\": 0,\n            \"hsl\": 0,\n            \"seasonalCapacity\": 174\n          },\n          \"Power Storage\": {\n            \"gen\": 51.8,\n            \"hsl\": 1112.6,\n            \"seasonalCapacity\": 9514\n          },\n          \"Solar\": {\n            \"gen\": 3193.9,\n            \"hsl\": 3416.9,\n            \"seasonalCapacity\": 27167\n          },\n          \"Wind\": {\n            \"gen\": 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  },
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    "content": "\n<!doctype html>\n<html lang=\"en\">\n<head>\n    <meta charset=\"utf-8\"/>\n<meta name=\"viewport\" content=\"width=device-width, initial-scale=1, viewport-fit=cover\"/>\n<meta http-equiv=\"X-UA-Compatible\" content=\"ie=edge\"/>\n\n\n<meta name=\"msapplication-TileColor\" content=\"\"/>\n\n<meta name=\"apple-mobile-web-app-status-bar-style\" content=\"black-translucent\"/>\n<meta name=\"apple-mobile-web-app-capable\" content=\"yes\"/>\n<meta name=\"mobile-web-app-capable\" content=\"yes\"/>\n<meta name=\"HandheldFriendly\" content=\"True\"/>\n<meta name=\"MobileOptimized\" content=\"320\"/>\n\n<!-- PWA  -->\n<meta name=\"theme-color\" content=\"#6777ef\"/>\n<link rel=\"apple-touch-icon\" href=\"https://erp.pgcb.gov.bd/images/logo_r.png\">\n\n\n\n    <!--<link rel=\"manifest\" href=\"https://erp.pgcb.gov.bd/manifests/transgrid.json\"> -->\n\n\n\n\n\n\n    <title>PGCB Website</title>\n    <link rel=\"icon\" href=\"https://erp.pgcb.gov.bd/favicon.ico\" 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   <div class=\"page-header d-print-none\">\n            <div class=\"container-xl\">\n                    <div class=\"row g-2 align-items-center\">\n        <div class=\"col\">\n            <h2 class=\"page-title\">\n                Hourly generation and Load shed\n            </h2>\n        </div>\n    </div>\n            </div>\n        </div>\n\n        <div class=\"page-body\">\n            <div class=\"container-xl\">\n                    <style>\n        table, th, td {\n            text-align: center;\n            padding: 5px;\n        }\n    </style>\n    <div class=\"row\">\n        <div class=\"col-sm-3\">\n            <form method=\"GET\" action=\"https://erp.pgcb.gov.bd/web/generations/view_generations\" accept-charset=\"UTF-8\">\n            <input type=\"text\" name=\"search\" placeholder=\"Search by Date\" id=\"search\" class=\"form-control\"\n                   style=\"margin: 5px; margin-left: 0px;\" value=\"01-01-2025\">\n            <button type=\"submit\" class=\"btn btn-sm btn-success\" style=\"display: none\">\n                Search\n            </button>\n\n            </form>\n        </div>\n        <div class=\"col-sm-9\">\n        </div>\n\n    </div>\n    <div class=\"card\">\n        <div class=\"card-body\">\n            <table class=\"table-bordered\" style=\" border-color: #e2e8f0; \">\n                <!-- <table class=\"table table-vcenter card-table \">-->\n                <thead>\n                <tr>\n                    <th style=\"width: 80px;\" rowspan=\"2\">Date</th>\n                    <th rowspan=\"2\">Time</th>\n                    <th rowspan=\"2\">Generation(MW)</th>\n                    <th rowspan=\"2\">Demand(MW)</th>\n                    <th rowspan=\"2\">Loadshed</th>\n                    <th rowspan=\"2\">Gas</th>\n                    <th rowspan=\"2\">Liquid Fuel</th>\n                    <th rowspan=\"2\">Coal</th>\n                    <th rowspan=\"2\">Hydro</th>\n                    <th rowspan=\"2\">Solar</th>\n                    <th rowspan=\"2\">Wind</th>\n                    <th rowspan=\"1\" colspan=\"3\">India</th>\n                    <th rowspan=\"2\">Nepal</th>\n                    <th style=\"width: 100px;\" rowspan=\"2\">Remarks</th>\n                </tr>\n                <tr>\n                    <th rowspan=\"1\" colspan=\"1\" >Bheramara HVDC</th>\n                    <th rowspan=\"1\" colspan=\"1\" >Tripura</th>\n                    <th rowspan=\"1\" colspan=\"1\" >Adani</th>\n                </tr>\n                </thead>\n                <tbody>\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>24:00:00</td>\n                        <td>8514</td>\n                        <td>8514</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4132</td>\n                        <td>35</td>\n                        <td>2847</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>19</td>\n                        <td>911</td>\n                        <td>48</td>\n                        <td>482</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>23:00:00</td>\n                        <td>8898</td>\n                        <td>8898</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4161</td>\n                        <td>62</td>\n                        <td>3081</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>19</td>\n                        <td>910</td>\n                        <td>50</td>\n                        <td>575</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>22:00:00</td>\n                        <td>9430</td>\n                        <td>9430</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4204</td>\n                        <td>88</td>\n                        <td>3379</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>18</td>\n                        <td>910</td>\n                        <td>52</td>\n                        <td>739</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>21:00:00</td>\n                        <td>9829</td>\n                        <td>9829</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4228</td>\n                        <td>202</td>\n                        <td>3626</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>11</td>\n                        <td>909</td>\n                        <td>54</td>\n                        <td>759</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>20:00:00</td>\n                        <td>9970</td>\n                        <td>9970</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4295</td>\n                        <td>587</td>\n                        <td>3603</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>7</td>\n                        <td>627</td>\n                        <td>56</td>\n                        <td>755</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>19:30:00</td>\n                        <td>10107</td>\n                        <td>10107</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4371</td>\n                        <td>620</td>\n                        <td>3630</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>9</td>\n                        <td>627</td>\n                        <td>54</td>\n                        <td>756</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>19:00:00</td>\n                        <td>10118</td>\n                        <td>10118</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4422</td>\n                        <td>586</td>\n                        <td>3615</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>13</td>\n                        <td>627</td>\n                        <td>56</td>\n                        <td>759</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>18:00:00</td>\n                        <td>10336</td>\n                        <td>10336</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4307</td>\n                        <td>1256</td>\n                        <td>3364</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>8</td>\n                        <td>680</td>\n                        <td>54</td>\n                        <td>627</td>\n                        <td>0</td>\n                        <td>Evening Peak</td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>17:00:00</td>\n                        <td>9175</td>\n                        <td>9175</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3946</td>\n                        <td>635</td>\n                        <td>3057</td>\n                        <td>30</td>\n                        <td>12</td>\n                        <td>3</td>\n                        <td>907</td>\n                        <td>58</td>\n                        <td>527</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>16:00:00</td>\n                        <td>8829</td>\n                        <td>8829</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4267</td>\n                        <td>252</td>\n                        <td>2765</td>\n                        <td>30</td>\n                        <td>90</td>\n                        <td>7</td>\n                        <td>907</td>\n                        <td>54</td>\n                        <td>457</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>15:00:00</td>\n                        <td>9201</td>\n                        <td>9201</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4257</td>\n                        <td>285</td>\n                        <td>2904</td>\n                        <td>26</td>\n                        <td>205</td>\n                        <td>7</td>\n                        <td>907</td>\n                        <td>56</td>\n                        <td>554</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>14:00:00</td>\n                        <td>9531</td>\n                        <td>9531</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4120</td>\n                        <td>244</td>\n                        <td>3142</td>\n                        <td>26</td>\n                        <td>304</td>\n                        <td>16</td>\n                        <td>907</td>\n                        <td>58</td>\n                        <td>714</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>13:00:00</td>\n                        <td>10087</td>\n                        <td>10087</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4344</td>\n                        <td>261</td>\n                        <td>3406</td>\n                        <td>30</td>\n                        <td>316</td>\n                        <td>6</td>\n                        <td>908</td>\n                        <td>62</td>\n                        <td>754</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>12:00:00</td>\n                        <td>9764</td>\n                        <td>9764</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4078</td>\n                        <td>334</td>\n                        <td>3297</td>\n                        <td>46</td>\n                        <td>288</td>\n                        <td>2</td>\n                        <td>907</td>\n                        <td>58</td>\n                        <td>754</td>\n                        <td>0</td>\n                        <td>Day Peak</td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>11:00:00</td>\n                        <td>9272</td>\n                        <td>9272</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3609</td>\n                        <td>347</td>\n                        <td>3289</td>\n                        <td>46</td>\n                        <td>267</td>\n                        <td>2</td>\n                        <td>906</td>\n                        <td>54</td>\n                        <td>752</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>10:00:00</td>\n                        <td>9048</td>\n                        <td>9048</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3780</td>\n                        <td>274</td>\n                        <td>3407</td>\n                        <td>46</td>\n                        <td>206</td>\n                        <td>1</td>\n                        <td>627</td>\n                        <td>50</td>\n                        <td>657</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>09:00:00</td>\n                        <td>9335</td>\n                        <td>9335</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4496</td>\n                        <td>163</td>\n                        <td>3225</td>\n                        <td>46</td>\n                        <td>127</td>\n                        <td>3</td>\n                        <td>721</td>\n                        <td>42</td>\n                        <td>512</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>08:00:00</td>\n                        <td>8896</td>\n                        <td>8896</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4756</td>\n                        <td>111</td>\n                        <td>2531</td>\n                        <td>26</td>\n                        <td>65</td>\n                        <td>11</td>\n                        <td>910</td>\n                        <td>42</td>\n                        <td>444</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>07:00:00</td>\n                        <td>8038</td>\n                        <td>8038</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4672</td>\n                        <td>15</td>\n                        <td>2130</td>\n                        <td>26</td>\n                        <td>6</td>\n                        <td>11</td>\n                        <td>721</td>\n                        <td>40</td>\n                        <td>417</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>06:00:00</td>\n                        <td>7382</td>\n                        <td>7382</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4131</td>\n                        <td>0</td>\n                        <td>2126</td>\n                        <td>26</td>\n                        <td>0</td>\n                        <td>16</td>\n                        <td>627</td>\n                        <td>40</td>\n                        <td>416</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>05:00:00</td>\n                        <td>6952</td>\n                        <td>6952</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3768</td>\n                        <td>0</td>\n                        <td>2045</td>\n                        <td>26</td>\n                        <td>0</td>\n                        <td>31</td>\n                        <td>627</td>\n                        <td>38</td>\n                        <td>417</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>04:00:00</td>\n                        <td>7082</td>\n                        <td>7082</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3843</td>\n                        <td>0</td>\n                        <td>2103</td>\n                        <td>26</td>\n                        <td>0</td>\n                        <td>29</td>\n                        <td>627</td>\n                        <td>38</td>\n                        <td>416</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>03:00:00</td>\n                        <td>7351</td>\n                        <td>7351</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4021</td>\n                        <td>0</td>\n                        <td>2105</td>\n                        <td>26</td>\n                        <td>0</td>\n                        <td>21</td>\n                        <td>722</td>\n                        <td>40</td>\n                        <td>416</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>02:00:00</td>\n                        <td>7669</td>\n                        <td>7669</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4311</td>\n                        <td>0</td>\n                        <td>2131</td>\n                        <td>26</td>\n                        <td>0</td>\n                        <td>18</td>\n                        <td>721</td>\n                        <td>42</td>\n                        <td>420</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">01-01-2025</td>\n                        <td>01:00:00</td>\n                        <td>8104</td>\n                        <td>8104</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4489</td>\n                        <td>0</td>\n                        <td>2139</td>\n                        <td>26</td>\n                        <td>0</td>\n                        <td>20</td>\n                        <td>910</td>\n                        <td>44</td>\n                        <td>476</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                                </tbody>\n            </table>\n        </div>\n        \n    </div>\n            </div>\n        </div>\n\n        <footer class=\"footer footer-transparent d-print-none\">\n    <div class=\"container-xl\">\n        <div class=\"row text-center align-items-center flex-row-reverse\">\n            <div class=\"col-lg-auto ms-lg-auto\">\n                <ul class=\"list-inline list-inline-dots mb-0\">\n\n                    <li class=\"list-inline-item\">\n                        <a href=\"#\" class=\"link-secondary\">About</a>\n                    </li>\n                    <li 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Libs JS -->\n<script src=\"./dist/libs/fslightbox/index.js?1674944800\" defer></script>\n<!-- Scripts -->\n<script src=\"https://code.jquery.com/jquery-3.7.0.min.js\"\n        integrity=\"sha256-2Pmvv0kuTBOenSvLm6bvfBSSHrUJ+3A7x6P5Ebd07/g=\"\n        crossorigin=\"anonymous\"></script>\n<script src=\"https://cdn.jsdelivr.net/npm/select2@4.1.0-rc.0/dist/js/select2.min.js\"></script>\n<script type=\"text/javascript\" src=\"https://cdn.datatables.net/v/dt/dt-1.10.25/datatables.min.js\"></script>\n<script type=\"text/javascript\" language=\"javascript\" src=\"https://cdn.datatables.net/buttons/2.0.1/js/dataTables.buttons.min.js\"></script>\n<script type=\"text/javascript\" language=\"javascript\" src=\"https://cdnjs.cloudflare.com/ajax/libs/jszip/3.1.3/jszip.min.js\"></script>\n<script type=\"text/javascript\" language=\"javascript\" src=\"https://cdnjs.cloudflare.com/ajax/libs/pdfmake/0.1.53/pdfmake.min.js\"></script>\n<script type=\"text/javascript\" language=\"javascript\" src=\"https://cdnjs.cloudflare.com/ajax/libs/pdfmake/0.1.53/vfs_fonts.js\"></script>\n<script type=\"text/javascript\" language=\"javascript\" src=\"https://cdn.datatables.net/buttons/2.0.1/js/buttons.html5.min.js\"></script>\n<script type=\"text/javascript\" language=\"javascript\" src=\"https://cdn.datatables.net/buttons/2.0.1/js/buttons.print.min.js\"></script>\n\n\n<link id=\"bsdp-css\" href=\"https://unpkg.com/bootstrap-datepicker@1.9.0/dist/css/bootstrap-datepicker3.min.css\" rel=\"stylesheet\">\n<script src=\"https://unpkg.com/bootstrap-datepicker@1.9.0/dist/js/bootstrap-datepicker.min.js\"></script>\n\n<script>\n\n\n    $(document).ready(function () {\n        $(\".readonly\").on('keydown paste focus', function(e){\n            if(e.keyCode != 9) // ignore tab\n                e.preventDefault();\n        });\n        $('input[type=\"number\"]').on('click', function() {\n            $(this).select();\n        });\n        $('.input-source').on('click', function() {\n            $(this).select();\n        });\n        // Function to format the number in the Bangladesh currency format\n        function formatBangladeshiCurrency(amount) {\n            if (!amount) return \"\";\n            amount = amount.toString().replace(/,/g, \"\"); // Remove existing commas\n            const parts = amount.split(\".\");\n            const integerPart = parts[0];\n            const decimalPart = parts[1] ? \".\" + parts[1] : \"\";\n\n            // Format the integer part with commas\n            const lastThree = integerPart.slice(-3);\n            const otherNumbers = integerPart.slice(0, -3);\n            const formattedInteger =\n                otherNumbers.replace(/\\B(?=(\\d{2})+(?!\\d))/g, \",\") + (otherNumbers ? \",\" : \"\") + lastThree;\n\n            return formattedInteger + decimalPart;\n        }\n\n        // On input change, update the formatted value\n        $(\".bdcurrency-input\").on(\"input\", function () {\n            const rawValue = $(this).val();\n            const formattedValue = formatBangladeshiCurrency(rawValue);\n            $(\".bdcurrency-display\").text(formattedValue); // Update the span\n            $(this).val(formattedValue); // Optionally update the input itself\n        });\n\n\n        $('.datepicker').datepicker({\n            format: 'dd-mm-yyyy',\n            autoclose: true,\n            todayBtn: \"linked\",\n            todayHighlight : true,\n            keyboardNavigation : true\n        });\n\n        //$('.msg').fadeOut(5000);\n        $('.select2').select2({\n            theme: \"bootstrap-5\",\n            selectionCssClass: \"select2--small\",\n            dropdownCssClass: \"select2--small\",\n            width: $(this).data('width') ? $(this).data('width') : $(this).hasClass('w-100') ? '100%' : 'style',\n            placeholder: $(this).data('placeholder'),\n            closeOnSelect: true,\n        });\n        $('.select3').select2({\n            theme: \"bootstrap-5\",\n            selectionCssClass: \"select2--small\",\n            dropdownCssClass: \"select2--small\",\n            width: $(this).data('width') ? $(this).data('width') : $(this).hasClass('w-100') ? '100%' : 'style',\n            placeholder: $(this).data('placeholder'),\n            closeOnSelect: false,\n        });\n\n\n        $('.erpdatatable').DataTable({\n\n            select: true,\n            \"bPaginate\": false,\n            \"bLengthChange\": false,\n            \"bFilter\": true,\n            \"bInfo\": false,\n            \"pageLength\": 250,\n            \"ordering\": false\n\n\n        });\n        var t = $('.searchdatatable').DataTable({\n\n            select: true,\n            \"bPaginate\": false,\n            \"bLengthChange\": false,\n            \"bFilter\": true,\n            \"bInfo\": true,\n            \"pageLength\": 250,\n            \"ordering\": true,\n            fixedHeader: true,\n            dom: 'Bfrtip',\n            buttons: [\n                'copy', 'csv', 'excel','print',\n                {\n                    extend: 'pdfHtml5',\n                    text: 'Pdf A4 Portrait',\n\n                    exportOptions: {\n                        columns: ':visible', orthogonal: 'print'\n                    }\n                },\n                {\n                    extend: 'pdfHtml5',\n                    text: 'Pdf A4 Landscape',\n                    orientation: 'landscape',\n\n                    exportOptions: {\n                        columns: ':visible', orthogonal: 'print'\n                    }\n                },\n                {\n                    extend: 'pdfHtml5',\n                    text: 'Pdf Legal Portrait',\n                    pageSize: 'LEGAL',\n\n                    exportOptions: {\n                        columns: ':visible', orthogonal: 'print'\n                    }\n                },\n\n                {\n                    extend: 'pdfHtml5',\n                    text: 'Pdf Legal Landscape',\n                    pageSize: 'LEGAL',\n                    orientation: 'landscape',\n\n                    exportOptions: {\n                        columns: ':visible', orthogonal: 'print'\n                    }\n                }\n            ],\n\n\n        });\n\n\n\n    });\n\n    $.ajaxSetup({\n        headers: {\n            'X-CSRF-TOKEN': $('meta[name=\"_token\"]').attr('content')\n        }\n    });\n\n\n</script>\n<script src=\"https://erp.pgcb.gov.bd/sw.js\"></script>\n<script>\n    if (\"serviceWorker\" in navigator) {\n        // Register a service worker hosted at the root of the\n        // site using the default scope.\n        navigator.serviceWorker.register(\"/sw.js\").then(\n            (registration) => {\n            console.log(\"Service worker registration succeeded:\", registration);\n    },\n        (error) => {\n            console.error('Service worker registration failed: ${error}');\n        },\n    );\n    } else {\n        console.error(\"Service workers are not supported.\");\n    }\n</script>\n\n\n\n\n</body>\n</html>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ERP_PGCB/latest.html",
    "content": "\n<!doctype html>\n<html lang=\"en\">\n<head>\n    <meta charset=\"utf-8\"/>\n<meta name=\"viewport\" content=\"width=device-width, initial-scale=1, viewport-fit=cover\"/>\n<meta http-equiv=\"X-UA-Compatible\" content=\"ie=edge\"/>\n\n\n<meta name=\"msapplication-TileColor\" content=\"\"/>\n\n<meta name=\"apple-mobile-web-app-status-bar-style\" content=\"black-translucent\"/>\n<meta name=\"apple-mobile-web-app-capable\" content=\"yes\"/>\n<meta name=\"mobile-web-app-capable\" content=\"yes\"/>\n<meta name=\"HandheldFriendly\" content=\"True\"/>\n<meta name=\"MobileOptimized\" content=\"320\"/>\n\n<!-- PWA  -->\n<meta name=\"theme-color\" content=\"#6777ef\"/>\n<link rel=\"apple-touch-icon\" href=\"https://erp.pgcb.gov.bd/images/logo_r.png\">\n\n\n\n    <!--<link rel=\"manifest\" href=\"https://erp.pgcb.gov.bd/manifests/transgrid.json\"> -->\n\n\n\n\n\n\n    <title>PGCB Website</title>\n    <link rel=\"icon\" href=\"https://erp.pgcb.gov.bd/favicon.ico\" type=\"image/x-icon\"/>\n<link rel=\"shortcut icon\" href=\"https://erp.pgcb.gov.bd/favicon.ico\" type=\"image/x-icon\"/>\n\n<link href=\"https://erp.pgcb.gov.bd/dist/css/tabler.min.css\" rel=\"stylesheet\"/>\n<link href=\"https://erp.pgcb.gov.bd/dist/css/tabler-flags.min.css\" rel=\"stylesheet\"/>\n<link href=\"https://erp.pgcb.gov.bd/dist/css/tabler-payments.min.css\" rel=\"stylesheet\"/>\n<link href=\"https://erp.pgcb.gov.bd/dist/css/tabler-vendors.min.css\" rel=\"stylesheet\"/>\n<link href=\"https://erp.pgcb.gov.bd/dist/css/demo.min.css\" rel=\"stylesheet\"/>\n<link href=\"https://erp.pgcb.gov.bd/css/bootstrap-datepicker.min.css\" rel=\"stylesheet\"/>\n\n<!-- Styles -->\n\n<link rel=\"stylesheet\" href=\"https://cdn.jsdelivr.net/npm/select2@4.1.0-rc.0/dist/css/select2.min.css\" />\n<link rel=\"stylesheet\" href=\"https://cdn.datatables.net/1.13.4/css/jquery.dataTables.min.css\" />\n<link rel=\"stylesheet\" href=\"https://cdn.jsdelivr.net/npm/select2-bootstrap-5-theme@1.3.0/dist/select2-bootstrap-5-theme.min.css\" />\n\n<link rel=\"stylesheet\" href=\"https://cdn.datatables.net/buttons/2.0.1/css/buttons.dataTables.min.css\">\n\n\n\n\n\n<style>\n    /* Chrome, Safari, Edge, Opera */\n    input[type=number]::-webkit-inner-spin-button,\n    input[type=number]::-webkit-outer-spin-button {\n        -webkit-appearance: none;\n        margin: 0;\n    }\n\n    /* Firefox */\n    input[type=number] {\n        -moz-appearance: textfield;\n    }\n\n    .tooltip-inner {\n        white-space: pre-line;\n    }\n    .svg_small\n    {\n        transform: scale(0.7);\n    }\n    @font-face {\n        font-family: Kalpurush;\n        src: url(https://erp.pgcb.gov.bd/fonts/kalpurush.ttf);\n    }\n    @font-face {\n        font-family: SolaimanLipi;\n        src: url(https://erp.pgcb.gov.bd/fonts/SolaimanLipi.ttf);\n    }\n    .bn{\n        font-family: SolaimanLipi !important;\n    }\n    @import url('https://rsms.me/inter/inter.css');\n\n    :root {\n        --tblr-font-sans-serif: 'Inter Var', -apple-system, BlinkMacSystemFont, San Francisco, Segoe UI, Roboto, Helvetica Neue, sans-serif;\n    }\n\n    body {\n        font-feature-settings: \"cv03\", \"cv04\", \"cv11\";\n    }\n\n    .delbtn{\n        text-decoration: none; border: none; background: none; color: darkred;\n    }\n\n</style>\n<style>\n    @import url('https://rsms.me/inter/inter.css');\n    :root {\n        --tblr-font-sans-serif:  'Inter Var', -apple-system, BlinkMacSystemFont, San Francisco, Segoe UI, Roboto, Helvetica Neue, sans-serif;\n    }\n    body {\n        font-feature-settings: \"cv03\", \"cv04\", \"cv11\";\n    }\n</style>\n\n\n</head>\n<body>\n<!--<body class=\"layout-fluid\">-->\n\n<div class=\"page\">\n    <div class=\"sticky-top\">\n        <header class=\"navbar navbar-expand-md navbar-light d-print-none\">\n    <div class=\"container-xl\">\n        <button class=\"navbar-toggler\" type=\"button\" data-bs-toggle=\"collapse\" data-bs-target=\"#navbar-menu\"\n                aria-controls=\"navbar-menu\" aria-expanded=\"false\" aria-label=\"Toggle navigation\">\n            <span class=\"navbar-toggler-icon\"></span>\n        </button>\n        <h1 class=\"navbar-brand navbar-brand-autodark d-none-navbar-horizontal pe-0 pe-md-3\">\n\n            <a href=\"https://pgcb.gov.bd/\" style=\"font-size: 15px; font-weight: normal; text-decoration: none; font-family: Arial, Helvetica, sans-serif !important;\">\n                <img class=\"navbar-brand-image\" width=\"32\" height=\"32\" alt=\"PGCB\"\n                     src=\"https://erp.pgcb.gov.bd/images/logo_r.png\">\n                Back to Website\n            </a>\n        </h1>\n        <div class=\"navbar-nav flex-row order-md-last\">\n                            <a href=\"https://erp.pgcb.gov.bd/login\" class=\"nav-link d-flex lh-1 text-reset p-0\">\n                    <svg xmlns=\"http://www.w3.org/2000/svg\" class=\"icon icon-tabler icon-tabler-login\" width=\"24\"\n                         height=\"24\" viewBox=\"0 0 24 24\" stroke-width=\"2\" stroke=\"currentColor\" fill=\"none\"\n                         stroke-linecap=\"round\" stroke-linejoin=\"round\">\n                        <path stroke=\"none\" d=\"M0 0h24v24H0z\" fill=\"none\"></path>\n                        <path d=\"M14 8v-2a2 2 0 0 0 -2 -2h-7a2 2 0 0 0 -2 2v12a2 2 0 0 0 2 2h7a2 2 0 0 0 2 -2v-2\"></path>\n                        <path d=\"M20 12h-13l3 -3m0 6l-3 -3\"></path>\n                    </svg> &nbsp; Sign in</a>\n                        </div>\n        <div class=\"collapse navbar-collapse\" id=\"navbar-menu\">\n            <div class=\"d-flex flex-column flex-md-row flex-fill align-items-stretch align-items-md-center\">\n\n                <ul class=\"navbar-nav\">\n                                    </ul>\n\n            </div>\n        </div>\n    </div>\n</header>\n    </div>\n    <div class=\"page-wrapper\">\n        <div class=\"page-header d-print-none\">\n            <div class=\"container-xl\">\n                    <div class=\"row g-2 align-items-center\">\n        <div class=\"col\">\n            <h2 class=\"page-title\">\n                Hourly generation and Load shed\n            </h2>\n        </div>\n    </div>\n            </div>\n        </div>\n\n        <div class=\"page-body\">\n            <div class=\"container-xl\">\n                    <style>\n        table, th, td {\n            text-align: center;\n            padding: 5px;\n        }\n    </style>\n    <div class=\"row\">\n        <div class=\"col-sm-3\">\n            <form method=\"GET\" action=\"https://erp.pgcb.gov.bd/web/generations/view_generations\" accept-charset=\"UTF-8\">\n            <input type=\"text\" name=\"search\" placeholder=\"Search by Date\" id=\"search\" class=\"form-control\"\n                   style=\"margin: 5px; margin-left: 0px;\" value=\"\">\n            <button type=\"submit\" class=\"btn btn-sm btn-success\" style=\"display: none\">\n                Search\n            </button>\n\n            </form>\n        </div>\n        <div class=\"col-sm-9\">\n        </div>\n\n    </div>\n    <div class=\"card\">\n        <div class=\"card-body\">\n            <table class=\"table-bordered\" style=\" border-color: #e2e8f0; \">\n                <!-- <table class=\"table table-vcenter card-table \">-->\n                <thead>\n                <tr>\n                    <th style=\"width: 80px;\" rowspan=\"2\">Date</th>\n                    <th rowspan=\"2\">Time</th>\n                    <th rowspan=\"2\">Generation(MW)</th>\n                    <th rowspan=\"2\">Demand(MW)</th>\n                    <th rowspan=\"2\">Loadshed</th>\n                    <th rowspan=\"2\">Gas</th>\n                    <th rowspan=\"2\">Liquid Fuel</th>\n                    <th rowspan=\"2\">Coal</th>\n                    <th rowspan=\"2\">Hydro</th>\n                    <th rowspan=\"2\">Solar</th>\n                    <th rowspan=\"2\">Wind</th>\n                    <th rowspan=\"1\" colspan=\"3\">India</th>\n                    <th rowspan=\"2\">Nepal</th>\n                    <th style=\"width: 100px;\" rowspan=\"2\">Remarks</th>\n                </tr>\n                <tr>\n                    <th rowspan=\"1\" colspan=\"1\" >Bheramara HVDC</th>\n                    <th rowspan=\"1\" colspan=\"1\" >Tripura</th>\n                    <th rowspan=\"1\" colspan=\"1\" >Adani</th>\n                </tr>\n                </thead>\n                <tbody>\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>23:00:00</td>\n                        <td>9529</td>\n                        <td>9529</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4822</td>\n                        <td>496</td>\n                        <td>3193</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>9</td>\n                        <td>915</td>\n                        <td>54</td>\n                        <td>0</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>22:00:00</td>\n                        <td>10054</td>\n                        <td>10054</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4858</td>\n                        <td>505</td>\n                        <td>3226</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>8</td>\n                        <td>910</td>\n                        <td>58</td>\n                        <td>449</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>21:00:00</td>\n                        <td>10658</td>\n                        <td>10658</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4903</td>\n                        <td>792</td>\n                        <td>3491</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>9</td>\n                        <td>909</td>\n                        <td>56</td>\n                        <td>458</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>20:00:00</td>\n                        <td>10769</td>\n                        <td>10769</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>5093</td>\n                        <td>576</td>\n                        <td>3559</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>8</td>\n                        <td>909</td>\n                        <td>56</td>\n                        <td>528</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>19:30:00</td>\n                        <td>10879</td>\n                        <td>10879</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>5245</td>\n                        <td>480</td>\n                        <td>3557</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>8</td>\n                        <td>909</td>\n                        <td>56</td>\n                        <td>584</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>19:00:00</td>\n                        <td>10893</td>\n                        <td>10893</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4962</td>\n                        <td>673</td>\n                        <td>3520</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>12</td>\n                        <td>910</td>\n                        <td>58</td>\n                        <td>718</td>\n                        <td>0</td>\n                        <td>Evening Peak</td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>18:00:00</td>\n                        <td>10577</td>\n                        <td>10577</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4697</td>\n                        <td>910</td>\n                        <td>3349</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>10</td>\n                        <td>909</td>\n                        <td>60</td>\n                        <td>602</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>17:00:00</td>\n                        <td>9468</td>\n                        <td>9468</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4394</td>\n                        <td>530</td>\n                        <td>3000</td>\n                        <td>40</td>\n                        <td>25</td>\n                        <td>4</td>\n                        <td>909</td>\n                        <td>58</td>\n                        <td>508</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>16:00:00</td>\n                        <td>9347</td>\n                        <td>9347</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4349</td>\n                        <td>479</td>\n                        <td>2883</td>\n                        <td>40</td>\n                        <td>155</td>\n                        <td>7</td>\n                        <td>909</td>\n                        <td>62</td>\n                        <td>463</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>15:00:00</td>\n                        <td>9788</td>\n                        <td>9788</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4246</td>\n                        <td>472</td>\n                        <td>3239</td>\n                        <td>40</td>\n                        <td>341</td>\n                        <td>6</td>\n                        <td>910</td>\n                        <td>58</td>\n                        <td>476</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>14:00:00</td>\n                        <td>10046</td>\n                        <td>10046</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4196</td>\n                        <td>471</td>\n                        <td>3382</td>\n                        <td>40</td>\n                        <td>431</td>\n                        <td>0</td>\n                        <td>910</td>\n                        <td>62</td>\n                        <td>554</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>13:00:00</td>\n                        <td>10403</td>\n                        <td>10434</td>\n                    <!--<td>31.00</td>-->\n                        <td>30</td>\n                        <td>4567</td>\n                        <td>399</td>\n                        <td>3349</td>\n                        <td>40</td>\n                        <td>517</td>\n                        <td>4</td>\n                        <td>909</td>\n                        <td>60</td>\n                        <td>558</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>12:00:00</td>\n                        <td>10149</td>\n                        <td>10149</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4606</td>\n                        <td>345</td>\n                        <td>3102</td>\n                        <td>40</td>\n                        <td>532</td>\n                        <td>7</td>\n                        <td>909</td>\n                        <td>50</td>\n                        <td>558</td>\n                        <td>0</td>\n                        <td>Day Peak</td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>11:00:00</td>\n                        <td>9576</td>\n                        <td>9576</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4257</td>\n                        <td>362</td>\n                        <td>2860</td>\n                        <td>40</td>\n                        <td>532</td>\n                        <td>8</td>\n                        <td>909</td>\n                        <td>50</td>\n                        <td>558</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>10:00:00</td>\n                        <td>9496</td>\n                        <td>9496</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4247</td>\n                        <td>366</td>\n                        <td>2859</td>\n                        <td>40</td>\n                        <td>450</td>\n                        <td>10</td>\n                        <td>909</td>\n                        <td>54</td>\n                        <td>561</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>09:00:00</td>\n                        <td>9682</td>\n                        <td>9682</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4404</td>\n                        <td>296</td>\n                        <td>3007</td>\n                        <td>40</td>\n                        <td>297</td>\n                        <td>16</td>\n                        <td>909</td>\n                        <td>48</td>\n                        <td>665</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>08:00:00</td>\n                        <td>9363</td>\n                        <td>9363</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4374</td>\n                        <td>180</td>\n                        <td>3037</td>\n                        <td>40</td>\n                        <td>111</td>\n                        <td>25</td>\n                        <td>908</td>\n                        <td>42</td>\n                        <td>646</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>07:00:00</td>\n                        <td>8542</td>\n                        <td>8542</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4603</td>\n                        <td>99</td>\n                        <td>2302</td>\n                        <td>40</td>\n                        <td>7</td>\n                        <td>38</td>\n                        <td>858</td>\n                        <td>38</td>\n                        <td>557</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>06:00:00</td>\n                        <td>7908</td>\n                        <td>7908</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4702</td>\n                        <td>0</td>\n                        <td>1948</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>40</td>\n                        <td>721</td>\n                        <td>38</td>\n                        <td>419</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>05:00:00</td>\n                        <td>7365</td>\n                        <td>7365</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4236</td>\n                        <td>0</td>\n                        <td>1973</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>33</td>\n                        <td>627</td>\n                        <td>38</td>\n                        <td>418</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>04:00:00</td>\n                        <td>7426</td>\n                        <td>7426</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4292</td>\n                        <td>0</td>\n                        <td>1976</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>33</td>\n                        <td>627</td>\n                        <td>40</td>\n                        <td>418</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>03:00:00</td>\n                        <td>7687</td>\n                        <td>7687</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4458</td>\n                        <td>0</td>\n                        <td>1979</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>30</td>\n                        <td>721</td>\n                        <td>40</td>\n                        <td>419</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>02:00:00</td>\n                        <td>7967</td>\n                        <td>7967</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4629</td>\n                        <td>24</td>\n                        <td>2063</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>27</td>\n                        <td>722</td>\n                        <td>42</td>\n                        <td>420</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">15-01-2025</td>\n                        <td>01:00:00</td>\n                        <td>8415</td>\n                        <td>8415</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4640</td>\n                        <td>43</td>\n                        <td>2294</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>31</td>\n                        <td>904</td>\n                        <td>44</td>\n                        <td>419</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>24:00:00</td>\n                        <td>8966</td>\n                        <td>8966</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4692</td>\n                        <td>125</td>\n                        <td>2692</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>45</td>\n                        <td>906</td>\n                        <td>48</td>\n                        <td>418</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>23:00:00</td>\n                        <td>9427</td>\n                        <td>9427</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4845</td>\n                        <td>140</td>\n                        <td>2939</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>39</td>\n                        <td>905</td>\n                        <td>54</td>\n                        <td>465</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>22:00:00</td>\n                        <td>10125</td>\n                        <td>10125</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4839</td>\n                        <td>288</td>\n                        <td>3319</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>30</td>\n                        <td>909</td>\n                        <td>56</td>\n                        <td>644</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>21:00:00</td>\n                        <td>10458</td>\n                        <td>10458</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4866</td>\n                        <td>515</td>\n                        <td>3349</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>20</td>\n                        <td>909</td>\n                        <td>58</td>\n                        <td>701</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>20:00:00</td>\n                        <td>10725</td>\n                        <td>10725</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4885</td>\n                        <td>586</td>\n                        <td>3473</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>14</td>\n                        <td>909</td>\n                        <td>64</td>\n                        <td>754</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>19:30:00</td>\n                        <td>10772</td>\n                        <td>10772</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4887</td>\n                        <td>603</td>\n                        <td>3496</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>19</td>\n                        <td>909</td>\n                        <td>63</td>\n                        <td>755</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>19:00:00</td>\n                        <td>10901</td>\n                        <td>10901</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4823</td>\n                        <td>718</td>\n                        <td>3591</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>17</td>\n                        <td>909</td>\n                        <td>66</td>\n                        <td>737</td>\n                        <td>0</td>\n                        <td>Evening Peak</td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>18:00:00</td>\n                        <td>10701</td>\n                        <td>10701</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4684</td>\n                        <td>1020</td>\n                        <td>3328</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>16</td>\n                        <td>909</td>\n                        <td>62</td>\n                        <td>642</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>17:00:00</td>\n                        <td>9714</td>\n                        <td>9714</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4455</td>\n                        <td>564</td>\n                        <td>3083</td>\n                        <td>40</td>\n                        <td>27</td>\n                        <td>18</td>\n                        <td>910</td>\n                        <td>56</td>\n                        <td>561</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>16:00:00</td>\n                        <td>9513</td>\n                        <td>9513</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4287</td>\n                        <td>510</td>\n                        <td>2974</td>\n                        <td>40</td>\n                        <td>150</td>\n                        <td>29</td>\n                        <td>909</td>\n                        <td>54</td>\n                        <td>560</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>15:00:00</td>\n                        <td>9699</td>\n                        <td>9740</td>\n                    <!--<td>41.00</td>-->\n                        <td>39</td>\n                        <td>4293</td>\n                        <td>508</td>\n                        <td>2988</td>\n                        <td>40</td>\n                        <td>298</td>\n                        <td>40</td>\n                        <td>909</td>\n                        <td>62</td>\n                        <td>561</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>14:00:00</td>\n                        <td>10163</td>\n                        <td>10210</td>\n                    <!--<td>47.00</td>-->\n                        <td>45</td>\n                        <td>4435</td>\n                        <td>523</td>\n                        <td>3183</td>\n                        <td>40</td>\n                        <td>405</td>\n                        <td>41</td>\n                        <td>911</td>\n                        <td>62</td>\n                        <td>563</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>13:00:00</td>\n                        <td>10426</td>\n                        <td>10465</td>\n                    <!--<td>39.00</td>-->\n                        <td>37</td>\n                        <td>4407</td>\n                        <td>570</td>\n                        <td>3300</td>\n                        <td>40</td>\n                        <td>454</td>\n                        <td>15</td>\n                        <td>910</td>\n                        <td>70</td>\n                        <td>660</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>12:00:00</td>\n                        <td>10242</td>\n                        <td>10242</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4142</td>\n                        <td>565</td>\n                        <td>3280</td>\n                        <td>40</td>\n                        <td>472</td>\n                        <td>14</td>\n                        <td>910</td>\n                        <td>60</td>\n                        <td>759</td>\n                        <td>0</td>\n                        <td>Day Peak</td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>11:00:00</td>\n                        <td>9681</td>\n                        <td>9710</td>\n                    <!--<td>29.00</td>-->\n                        <td>28</td>\n                        <td>3848</td>\n                        <td>492</td>\n                        <td>3123</td>\n                        <td>40</td>\n                        <td>448</td>\n                        <td>10</td>\n                        <td>909</td>\n                        <td>54</td>\n                        <td>757</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>10:00:00</td>\n                        <td>9644</td>\n                        <td>9675</td>\n                    <!--<td>31.00</td>-->\n                        <td>30</td>\n                        <td>3912</td>\n                        <td>456</td>\n                        <td>3136</td>\n                        <td>40</td>\n                        <td>374</td>\n                        <td>9</td>\n                        <td>908</td>\n                        <td>54</td>\n                        <td>755</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>09:00:00</td>\n                        <td>9854</td>\n                        <td>9854</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3963</td>\n                        <td>450</td>\n                        <td>3430</td>\n                        <td>40</td>\n                        <td>245</td>\n                        <td>13</td>\n                        <td>908</td>\n                        <td>48</td>\n                        <td>757</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>08:00:00</td>\n                        <td>9358</td>\n                        <td>9358</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4007</td>\n                        <td>302</td>\n                        <td>3353</td>\n                        <td>40</td>\n                        <td>101</td>\n                        <td>28</td>\n                        <td>908</td>\n                        <td>40</td>\n                        <td>579</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>07:00:00</td>\n                        <td>8664</td>\n                        <td>8664</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4066</td>\n                        <td>132</td>\n                        <td>2891</td>\n                        <td>40</td>\n                        <td>6</td>\n                        <td>27</td>\n                        <td>908</td>\n                        <td>36</td>\n                        <td>558</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>06:00:00</td>\n                        <td>7854</td>\n                        <td>7854</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>4007</td>\n                        <td>13</td>\n                        <td>2582</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>12</td>\n                        <td>720</td>\n                        <td>52</td>\n                        <td>428</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>05:00:00</td>\n                        <td>7469</td>\n                        <td>7469</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3833</td>\n                        <td>0</td>\n                        <td>2488</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>13</td>\n                        <td>624</td>\n                        <td>50</td>\n                        <td>421</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>04:00:00</td>\n                        <td>7517</td>\n                        <td>7517</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3885</td>\n                        <td>0</td>\n                        <td>2489</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>9</td>\n                        <td>624</td>\n                        <td>50</td>\n                        <td>420</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>03:00:00</td>\n                        <td>7674</td>\n                        <td>7674</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3851</td>\n                        <td>0</td>\n                        <td>2586</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>12</td>\n                        <td>719</td>\n                        <td>44</td>\n                        <td>422</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>02:00:00</td>\n                        <td>8069</td>\n                        <td>8069</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3821</td>\n                        <td>52</td>\n                        <td>2863</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>5</td>\n                        <td>719</td>\n                        <td>50</td>\n                        <td>519</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">14-01-2025</td>\n                        <td>01:00:00</td>\n                        <td>8508</td>\n                        <td>8508</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3821</td>\n                        <td>79</td>\n                        <td>2993</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>0</td>\n                        <td>908</td>\n                        <td>54</td>\n                        <td>613</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">13-01-2025</td>\n                        <td>24:00:00</td>\n                        <td>9093</td>\n                        <td>9093</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3831</td>\n                        <td>177</td>\n                        <td>3368</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>0</td>\n                        <td>907</td>\n                        <td>55</td>\n                        <td>715</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n                \n                    <tr>\n                        <td class=\"text-nowrap\">13-01-2025</td>\n                        <td>23:00:00</td>\n                        <td>9480</td>\n                        <td>9480</td>\n                    <!--<td>0.00</td>-->\n                        <td>0</td>\n                        <td>3932</td>\n                        <td>306</td>\n                        <td>3483</td>\n                        <td>40</td>\n                        <td>0</td>\n                        <td>0</td>\n                        <td>907</td>\n                        <td>56</td>\n                        <td>756</td>\n                        <td>0</td>\n                        <td></td>\n                    </tr>\n\n           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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ES/demandaGeneracionBaleares.json",
    "content": "null({\"valoresHorariosGeneracion\":[{\"ts\":\"2024-10-25 21:00\",\"dem\":601.1,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":395.7,\"cb\":264.3,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":1.3,\"emi\":-100.3,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":15.0,\"residRen\":15.0},{\"ts\":\"2024-10-25 21:05\",\"dem\":599.6,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":419.1,\"cb\":237.9,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":0.9,\"emi\":-98.7,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":15.2,\"residRen\":15.2},{\"ts\":\"2024-10-25 21:10\",\"dem\":593.9,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":422.3,\"cb\":236.3,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-4.2,\"emi\":-100.2,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":14.8,\"residRen\":14.8},{\"ts\":\"2024-10-25 21:15\",\"dem\":593.7,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":426.4,\"cb\":236.4,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-9.5,\"emi\":-98.2,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":14.2,\"residRen\":14.2},{\"ts\":\"2024-10-25 21:20\",\"dem\":584.2,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":421.1,\"cb\":236.6,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-14.7,\"emi\":-98.9,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":15.0,\"residRen\":15.0},{\"ts\":\"2024-10-25 21:25\",\"dem\":581.2,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":417.6,\"cb\":236.7,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-16.6,\"emi\":-97.6,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":15.5,\"residRen\":15.5},{\"ts\":\"2024-10-25 21:30\",\"dem\":574.8,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":407.7,\"cb\":236.4,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-12.9,\"emi\":-96.8,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":15.2,\"residRen\":15.2},{\"ts\":\"2024-10-25 21:35\",\"dem\":566.7,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":399.8,\"cb\":236.6,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-13.7,\"emi\":-96.3,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":15.1,\"residRen\":15.1},{\"ts\":\"2024-10-25 21:40\",\"dem\":559.0,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":391.9,\"cb\":236.5,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-13.7,\"emi\":-95.5,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":14.9,\"residRen\":14.9},{\"ts\":\"2024-10-25 21:45\",\"dem\":556.2,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":386.3,\"cb\":236.6,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-12.9,\"emi\":-93.4,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":14.8,\"residRen\":14.8},{\"ts\":\"2024-10-25 21:50\",\"dem\":543.7,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":373.3,\"cb\":236.5,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-12.3,\"emi\":-93.0,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":14.6,\"residRen\":14.6},{\"ts\":\"2024-10-25 21:55\",\"dem\":541.3,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":367.7,\"cb\":236.5,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-11.4,\"emi\":-90.9,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":14.7,\"residRen\":14.7},{\"ts\":\"2024-10-25 22:00\",\"dem\":530.2,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":364.3,\"cb\":226.9,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-11.6,\"emi\":-88.7,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":6.1,\"eif\":-0.0,\"residNr\":14.6,\"residRen\":14.6},{\"ts\":\"2024-10-25 22:05\",\"dem\":521.5,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":365.1,\"cb\":216.5,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-13.1,\"emi\":-87.6,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":5.3,\"eif\":-0.0,\"residNr\":15.6,\"residRen\":15.6},{\"ts\":\"2024-10-25 22:10\",\"dem\":517.5,\"car\":0.0,\"die\":0.0,\"gas\":0.0,\"cc\":372.0,\"cb\":206.5,\"fot\":1.9,\"tnr\":0.0,\"trn\":0.0,\"eol\":0.0,\"emm\":-13.4,\"emi\":-87.7,\"otrRen\":2.1,\"resid\":0.0,\"genAux\":0.0,\"cogen\":4.6,\"eif\":-0.0,\"residNr\":15.8,\"residRen\":15.8},{\"ts\":\"2024-10-25 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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ES/demandaGeneracionPeninsula.json",
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  {
    "path": "electricitymap/contrib/parsers/tests/mocks/ESKOM/Station_Build_Up.csv",
    "content": "Date_Time_Hour_Beginning,Thermal_Gen_Excl_Pumping_and_SCO,Eskom_OCGT_SCO_Pumping,Eskom_Gas_SCO_Pumping,Hydro_Water_SCO_Pumping,Pumped_Water_SCO_Pumping,Thermal_Generation,Nuclear_Generation,International_Imports,Eskom_OCGT_Generation,Eskom_Gas_Generation,Dispatchable_IPP_OCGT,Hydro_Water_Generation,Pumped_Water_Generation,IOS_Excl_ILS_and_MLR,ILS_Usage,Manual_Load_Reduction_MLR,Wind,PV,CSP,Other_RE\n2023-09-11 00:00:00,14487.159,-0.14699999999999999,-2.1259999999999999,-3.0000000000000001E-3,-2429.0320000000002,16918.467000000001,913.03899999999999,413.87799999999999,1005.265,0,622.35799999999995,4.0000000000000001E-3,-1.8,0,0,1667.117,1773.9549999999999,0,0,14.535\n2023-09-11 01:00:00,14231.942999999999,-3.4660000000000002,-2.137,-3.0000000000000001E-3,-2585.1819999999998,16822.731,913.09199999999998,1114.5219999999999,58.75,0,613.68499999999995,4.0000000000000001E-3,-2.5339999999999998,0,0,1686.873,1801.865,0,0,14.602\n2023-09-11 02:00:00,14354.055,-3.4790000000000001,-2.1389999999999998,-0.002,-2614.5320000000002,16974.206999999999,913.20899999999995,1326.6210000000001,0,0,626.846,4.0000000000000001E-3,0,0,0,1642.454,1702.886,0,0,14.667999999999999\n2023-09-11 03:00:00,14436.056,-3.4790000000000001,-2.1549999999999998,-3.0000000000000001E-3,-2681.1640000000002,17122.857,913.52999999999997,1322.644,0,0,624.06500000000005,4.0000000000000001E-3,0,0,0,1789.25,1661.1400000000001,0,0,14.898999999999999\n2023-09-11 04:00:00,15399.590999999997,-2.0390000000000001,-2.1669999999999998,-3.0000000000000001E-3,-1979.3030000000001,17383.102999999999,911.82799999999997,1331.1759999999999,614.23500000000001,0,627.06700000000001,4.0000000000000001E-3,-4.1890000000000001,0,0,1793.79,1639.818,0,0,14.961\n2023-09-11 05:00:00,17525.653000000002,-1.7330000000000001,-2.1789999999999998,-3.0000000000000001E-3,-327.17200000000003,17856.740000000002,911.88,1341.297,986.52999999999997,0,628.673,4.0039999999999996,410.20999999999998,0,0,1959.8299999999999,1503.038,0,0,15.023\n2023-09-11 06:00:00,17923.762999999999,-1.7330000000000001,-2.1680000000000001,-0.002,-10.082000000000001,17937.748,912.30700000000002,1379.674,877.28999999999996,0,629.00999999999999,243.00399999999999,1901.788,0,0,2172.5279999999998,1630.6110000000001,18.408000000000001,0,15.766999999999999\n2023-09-11 07:00:00,18112.266,-1.7330000000000001,-2.157,-0.001,-28.702000000000002,18144.859,912.48599999999999,1409.634,857.44500000000005,0,623.45699999999999,488.61599999999999,469.90300000000002,0,0,2028.752,1620.9549999999999,436.53699999999998,0,15.724\n2023-09-11 08:00:00,18188.290999999997,-1.7330000000000001,-2.169,-0.001,-34.600999999999999,18226.794999999998,912.50199999999995,1375.8610000000001,903.77999999999997,0,616.75300000000004,212.54499999999999,138.614,0,0,2252.8049999999998,1647.22,1004.686,5.4859999999999998,14.885999999999999\n2023-09-11 09:00:00,18128.401999999998,-1.7330000000000001,-2.1909999999999998,-0.001,-37.579000000000001,18169.905999999999,912.51700000000005,1395.9760000000001,551.69000000000005,0,615.19899999999996,123.21599999999999,-1.284,0,0,2232.1280000000002,1758.5820000000001,1303.9449999999999,95.397000000000006,14.93\n2023-09-17 16:00:00,,,,,,,,,,,,,,,,,,,,\n2023-09-11 10:00:00,17748.254999999997,-1.7330000000000001,-2.177,-0.001,-16.093,17768.258999999998,912.67200000000003,1367.5699999999999,277.58999999999997,0,609.14499999999998,22.004000000000001,1003.449,0,0,2062.3600000000001,1910.8630000000001,1375.7639999999999,121.503,15.332000000000001\n2023-09-11 11:00:00,17492.405999999995,-1.8660000000000001,-2.161,-0.001,-24.507999999999999,17520.941999999999,912.45100000000002,1338.404,302.19499999999999,0,606.08799999999997,4.0000000000000001E-3,572.42499999999995,0,0,2203.9659999999999,2144.018,1512.2180000000001,139.96700000000001,15.788\n2023-09-11 12:00:00,17337.569,-1.7330000000000001,-2.1680000000000001,-0.001,-34.011000000000003,17375.482,911.48000000000002,1370.8689999999999,280.63,0,518.61199999999997,4.0000000000000001E-3,106.386,0,0,2667.777,2371.2570000000001,1536.4549999999999,128.43100000000001,15.795999999999999\n2023-09-11 13:00:00,17367.756000000001,-1.7330000000000001,-2.1709999999999998,-0.001,-30.280999999999999,17401.941999999999,911.90300000000002,1367.5909999999999,304.08999999999997,0,304.68099999999998,4.0000000000000001E-3,146.56100000000001,0,0,2694.107,2365.4749999999999,1412.9680000000001,147.767,15.859999999999999\n2023-09-11 14:00:00,16786.083999999999,-1.7330000000000001,-2.1579999999999999,-0.001,-21.481000000000002,16811.456999999999,912.05499999999995,1373.9200000000001,304.57999999999998,0,308.16500000000002,4.0000000000000001E-3,1042.146,0,0,2858.8380000000002,2297.922,1359.8879999999999,238.346,15.69\n2023-09-11 15:00:00,16304.325000000001,-1.333,-2.169,-0.001,-11.051,16318.879000000001,911.87800000000004,1381.836,535.47000000000003,0,452.99799999999999,4.0000000000000001E-3,2103.8499999999999,0,0,2729.011,2196.6750000000002,1235.422,347.19400000000002,15.657\n2023-09-11 16:00:00,16336.383,0,-2.177,-0.001,-12.824,16351.385,911.54300000000001,1371.6110000000001,1492.76,0,610.05100000000004,4.0000000000000001E-3,1786.509,0,0,2825.402,2206.165,970.50400000000002,387.49099999999999,14.954000000000001\n2023-09-11 17:00:00,16499.065999999999,0,-1.161,-0.002,-4.585,16504.813999999998,911.77599999999995,1397.4200000000001,1758.78,135.31,977.15599999999995,40.003,2178.0309999999999,0,37.25,3097.395,2052.6390000000001,382.54000000000002,391.65800000000002,14.901999999999999\n2023-09-11 18:00:00,16904.072,0,0,-3.0000000000000001E-3,-1.639,16905.714,911.74800000000005,1361.1590000000001,1732.2449999999999,327.517,986.89700000000005,497.00200000000001,2618.1950000000002,239,409.75,3470.5279999999998,1960.5809999999999,8.7330000000000005,347.68000000000001,15.481\n2023-09-11 19:00:00,16994.120999999999,0,0,-0.001,-0.63800000000000001,16994.759999999998,911.86800000000005,1333.4480000000001,1705.7449999999999,328.34500000000003,995.06200000000001,378.10199999999998,2443.2950000000001,239,0,3701.201,1717.6389999999999,0,219.22200000000001,15.680999999999999\n2023-09-11 20:00:00,17140.436999999998,0,-1.629,-3.0000000000000001E-3,-18.079999999999998,17160.149000000001,911.995,1364.4369999999999,1729.7950000000001,95.007000000000005,998.89700000000005,3.0000000000000001E-3,1490.4200000000001,5.5,0,3449.893,1613.9739999999999,0,100,15.712\n2023-09-11 21:00:00,16475.757999999998,0,-2.1960000000000002,-3.0000000000000001E-3,-566.75800000000004,17044.715,911.85699999999997,1332.8330000000001,1724.4200000000001,0,1000.04,3.0000000000000001E-3,74.546000000000006,0,0,3227.895,1504.039,0,100,15.682\n2023-09-11 22:00:00,15568.750999999998,0,-2.1829999999999998,-0.002,-1510.386,17081.322,912.12699999999995,1276.998,1220.52,0,1002.0890000000001,4.0000000000000001E-3,-7.5149999999999997,0,0,2828.0830000000001,1360.8430000000001,0,50,15.712\n2023-09-11 23:00:00,15110.876,0,-2.1920000000000002,-0.002,-2053.9490000000001,17167.019,912.41399999999999,1307.9949999999999,932.83000000000004,0,1004.242,4.0000000000000001E-3,-0.186,0,0,2459.7040000000002,1159.742,0,0,15.906000000000001\n2023-09-12 00:00:00,14860.657000000001,0,-2.1909999999999998,-0.002,-2321.172,17184.022000000001,912.25999999999999,1325.999,797.97000000000003,0,1005.775,4.0000000000000001E-3,-4.9969999999999999,0,0,2209.1619999999998,1005.752,0,0,15.204000000000001\n2023-09-12 01:00:00,14673.782999999996,-1.2,-2.2010000000000001,-0.002,-2752.433,17429.618999999999,911.67899999999997,1315.8219999999999,645.505,0,918.08100000000002,4.0000000000000001E-3,0,0,0,2178.3980000000001,1042.9649999999999,0,0,15.249000000000001\n2023-09-12 02:00:00,15097.238999999998,-1.72,-2.1920000000000002,-0.002,-2219.0929999999998,17320.245999999999,912.07100000000003,1322.4090000000001,640.85500000000002,0,502.92000000000002,4.0000000000000001E-3,-2.2389999999999999,0,0,2083.8989999999999,1027.239,0,0,15.084\n2023-09-12 03:00:00,15131.652999999998,-1.706,-2.2050000000000001,-0.002,-2537,17672.565999999999,912.08399999999995,1320.7260000000001,667.53499999999997,0,501.32400000000001,4.0000000000000001E-3,0,0,0,2227.1460000000002,1005.952,0,0,14.869\n2023-09-12 04:00:00,16554.638000000003,-1.706,-2.2269999999999999,-0.002,-1254.9929999999999,17813.565999999999,912.07399999999996,1344.0119999999999,652.28999999999996,0,501.738,4.0000000000000001E-3,-4.7279999999999998,0,0,2596.1509999999998,1017.813,0,0,14.912000000000001\n2023-09-12 05:00:00,17710.868999999999,-1.6930000000000001,-2.234,-3.0000000000000001E-3,-56.520000000000003,17771.319,912.399,1360.789,749.01999999999998,0,502.48099999999999,4.0000000000000001E-3,1567.3140000000001,0,0,2548.8209999999999,1183.9649999999999,0,0,15.145\n2023-09-17 14:00:00,,,,,,,,,,,,,,,,,,,,\n2023-09-12 06:00:00,17687.171999999999,0,-2.234,-0.002,-0.96999999999999997,17690.378000000001,911.54399999999998,1444.2349999999999,1355.54,0,502.58800000000002,236.00299999999999,2488.54,0,0,2711.5169999999998,1342.8789999999999,38.161000000000001,0,15.815\n2023-09-12 07:00:00,17811.809000000001,0,-2.194,-0.001,-19.571999999999999,17833.576000000001,911.16899999999998,1435.4380000000001,1461.4749999999999,0,501.56799999999998,493.94499999999999,1518.5719999999999,0,0,2293.4029999999998,1277.2760000000001,645.721,0.53500000000000003,15.856999999999999\n2023-09-12 08:00:00,17838.704000000002,0,-2.1709999999999998,0,-20.707000000000001,17861.581999999999,911.16300000000001,1371.3900000000001,1489.3299999999999,0,500.94400000000002,219.27699999999999,936.83000000000004,0,0,2507.6439999999998,1059.567,1432.385,56.481999999999999,15.038\n2023-09-12 09:00:00,17864.873,0,-2.1600000000000001,-0.001,-26.696000000000002,17893.73,909.77200000000005,1397.5050000000001,1429.3,0,497.714,116.18300000000001,505.19799999999998,0,0,2395.4189999999999,1052.3920000000001,1772.183,216.137,14.411\n2023-09-12 10:00:00,17882.138999999996,0,-2.1480000000000001,-0.001,-26.579000000000001,17910.866999999998,909.28200000000004,1426.5989999999999,751.61500000000001,0,492.90199999999999,4.0000000000000001E-3,418.226,0,0,3047.2820000000002,1093.857,1913.4169999999999,247.68899999999999,14.795999999999999\n2023-09-12 11:00:00,17675.814000000002,0,-2.1549999999999998,-0.001,-20.103000000000002,17698.073,910.93100000000004,1456.934,675.35500000000002,0,493.67099999999999,4.0000000000000001E-3,550.70899999999995,0,0,3057.5459999999998,1003.0549999999999,1912.2619999999999,271.52499999999998,15.558999999999999\n2023-09-12 12:00:00,17565.958999999999,0,-2.1440000000000001,-0.001,-18.460000000000001,17586.563999999998,911.13599999999997,1540.413,702.61000000000001,0,491.85000000000002,4.0000000000000001E-3,750.71699999999998,1.8,0,2878.2130000000002,828.31600000000003,1900.8040000000001,270.01100000000002,15.813000000000001\n2023-09-12 13:00:00,17459.713999999996,0,-2.1480000000000001,-0.001,-19.219000000000001,17481.081999999999,910.92899999999997,1554.713,699.41999999999996,0,491.541,4.0000000000000001E-3,639.52099999999996,36,0,2914.9740000000002,721.17499999999995,1842.059,323.16199999999998,15.707000000000001\n2023-09-12 14:00:00,17616.843999999997,0,-2.149,-0.001,-20.972000000000001,17639.966,910.98900000000003,1548.193,699.48500000000001,0,491.27699999999999,4.0000000000000001E-3,457.17399999999998,1.2,0,3760.6970000000001,702.06600000000003,1774.249,385.14100000000002,15.723000000000001\n2023-09-12 15:00:00,17668.651000000002,0,-2.1589999999999998,-0.001,-12.644,17683.455000000002,910.70600000000002,1500.502,837.995,0,545.71600000000001,4.0000000000000001E-3,976.02599999999995,0,0,3770.232,745.11500000000001,1606.4269999999999,460.517,15.705\n2023-09-12 16:00:00,17737.190999999999,0,-2.1619999999999999,-0.001,-17.459,17756.812999999998,910.721,1450.6310000000001,1052.3299999999999,0,663.61300000000006,4.0000000000000001E-3,780.12099999999998,0,0,4721.7929999999997,837.59100000000001,1230.0250000000001,457.22800000000001,14.983000000000001\n2023-09-12 17:00:00,18014.672000000002,0,-2.153,-0.001,-4.7960000000000003,18021.621999999999,910.83600000000001,1396.7829999999999,1319.6300000000001,0,676.96900000000005,4.0000000000000001E-3,1742.268,0,0,5023.6099999999997,941.60599999999999,449.34300000000002,420.69799999999998,14.917\n2023-09-12 18:00:00,18249.953999999998,0,-2.1640000000000001,-3.0000000000000001E-3,-7.3099999999999996,18259.431,910.57600000000002,1395.664,1718.915,0,823.56399999999996,458.21300000000002,1410.9200000000001,0,223.5,5728.3329999999996,1241.682,10.128,369.66000000000003,15.275\n2023-09-12 19:00:00,18301.756999999998,0,-2.177,-0.001,-16.949999999999999,18320.884999999998,910.57600000000002,1419.2550000000001,1680.76,0,835.65800000000002,420.52300000000002,451.77800000000002,0,223.5,5597.7299999999996,1549.8789999999999,0,351.00999999999999,15.339\n2023-09-12 20:00:00,17914.453999999998,0,-2.1869999999999998,-0.002,-294.35300000000001,18210.995999999999,910.28300000000002,1386.655,1595.3050000000001,0,836.25599999999997,46.003999999999998,89.847999999999999,0,0,5122.3490000000002,1560.7260000000001,0,342.55099999999999,15.319000000000001\n2023-09-12 21:00:00,16085.443000000001,0,-2.2090000000000001,-0.002,-1960.3679999999999,18048.022000000001,910.10500000000002,1383.105,1538.7149999999999,0,835.82000000000005,4.0000000000000001E-3,-9.2230000000000008,0,0,4536.6930000000002,1501.79,0,326.46600000000001,15.326000000000001\n2023-09-12 22:00:00,15555.346999999998,-0.253,-2.1949999999999998,-0.002,-2448.3960000000002,18006.192999999999,910.86900000000003,1351.7460000000001,1474.4200000000001,0,835.00099999999998,4.0000000000000001E-3,-2.5739999999999998,0,0,2913.5709999999999,1479.394,0,89.941999999999993,15.363\n2023-09-12 23:00:00,15172.027,-1.6799999999999999,-2.2000000000000002,-0.002,-2775.884,17951.793000000001,911.16399999999999,1367.2539999999999,1026.5999999999999,0,508.803,4.0000000000000001E-3,0,0,0,2533.2689999999998,1507.7180000000001,0,39.890999999999998,15.382999999999999\n2023-09-13 00:00:00,15176.668999999998,-1.6930000000000001,-2.1989999999999998,-0.002,-2780.857,17961.419999999998,911.16300000000001,1289.98,733.42999999999995,0,334.822,4.0000000000000001E-3,0,0,0,2428.915,1490.433,0,39.829999999999998,15.372\n2023-09-13 01:00:00,15309.956000000002,-1.786,-2.1960000000000002,-0.002,-2758.5309999999999,18072.471000000001,911.63900000000001,1277.616,239.38999999999999,0,329.50700000000001,4.0000000000000001E-3,0,0,0,2449.0500000000002,1372.5419999999999,0,39.762999999999998,15.193\n2023-09-17 15:00:00,,,,,,,,,,,,,,,,,,,,\n2023-09-13 02:00:00,15437.735000000001,-1.786,-2.1949999999999998,-0.002,-2709.8049999999998,18151.523000000001,912.322,1286.4349999999999,248.25999999999999,0,39.405999999999999,4.0000000000000001E-3,0,0,0,2460.9659999999999,1437.9390000000001,0,39.774000000000001,15.303000000000001\n2023-09-13 03:00:00,15875.269,-1.8129999999999999,-2.202,-3.0000000000000001E-3,-2338.1970000000001,18217.484,911.82899999999995,1293.2639999999999,0.67500000000000004,0,0,4.0000000000000001E-3,-1.1020000000000001,0,0,2597.8600000000001,1426.0930000000001,0,39.792999999999999,15.262\n2023-09-13 04:00:00,17470.169999999998,-3.5859999999999999,-2.198,-3.0000000000000001E-3,-1076.4159999999999,18552.373,911.85599999999999,1304.498,3.25,0,2.0459999999999998,4.0000000000000001E-3,-7.3620000000000001,0,0,2862.5639999999999,1449.5070000000001,0,20.260000000000002,14.957000000000001\n2023-09-13 05:00:00,18460.215999999997,-1.786,-2.1989999999999998,-3.0000000000000001E-3,-30.539999999999999,18494.743999999999,912.30399999999997,1303.0999999999999,365.46499999999997,0,284.108,4.0039999999999996,815.71000000000004,0,0,3565.0230000000001,1507.8579999999999,0,0,15.18\n2023-09-13 06:00:00,18340.358,-1.7729999999999999,-2.206,-0.002,-18.582000000000001,18362.920999999998,912.26199999999994,1372.8340000000001,420.51499999999999,0,335.58999999999997,243.00399999999999,979.91700000000003,0,0,5093.0969999999998,1888.9469999999999,23.928999999999998,0,14.207000000000001\n2023-09-13 07:00:00,18178.856000000003,-2.319,-2.1890000000000001,-0.001,-20.768000000000001,18204.133000000002,911.86300000000006,1371.377,125.13500000000001,0,161.26900000000001,487.37400000000002,349.87099999999998,0,0,4980.9520000000002,2052.527,517.80999999999995,2.665,14.185\n2023-09-13 08:00:00,18348.253000000001,-3.492,-2.169,-0.001,-24.981000000000002,18378.896000000001,912.03700000000003,1345.6510000000001,0,0,0,212.08600000000001,568.71699999999998,0,0,4981.5959999999995,1900.9280000000001,1224.6410000000001,70.861999999999995,14.196\n2023-09-13 09:00:00,18101.210000000003,-3.492,-2.1589999999999998,-0.001,-145.94200000000001,18252.804,911.75099999999998,1408.8630000000001,0,0,0,123.80800000000001,84.201999999999998,0,0,4918.4269999999997,1863.0920000000001,1578.566,273.51499999999999,13.986000000000001\n2023-09-13 10:00:00,17775.894,-3.4660000000000002,-2.137,-0.002,-593.99599999999998,18375.494999999999,912.06899999999996,1515.587,0,0,0,4.0000000000000001E-3,-4.0229999999999997,0,0,5010.1499999999996,1954.5429999999999,1759.1020000000001,293.024,14.627000000000001\n2023-09-13 11:00:00,16760.894,-3.4660000000000002,-2.141,-0.002,-1211.7149999999999,17978.218000000001,912.61800000000005,1599.951,0,0,0,4.0000000000000001E-3,-6.9009999999999998,0,0,5215.9889999999996,2147.5010000000002,1825.0409999999999,246.315,15.178000000000001\n2023-09-17 10:00:00,,,,,,,,,,,,,,,,,,,,\n2023-09-13 12:00:00,16888.326999999997,-3.319,-2.1259999999999999,-0.002,-955.61199999999997,17849.385999999999,915.90899999999999,1611.3219999999999,0,0,0,4.0000000000000001E-3,-5.1159999999999997,0,0,4901.0370000000003,2292.7330000000002,1837.0309999999999,212.066,15.004\n2023-09-13 13:00:00,16397.378000000001,-3.4660000000000002,-2.1539999999999999,-0.001,-1382.375,17785.374,916.51099999999997,1573.836,0,0,0,4.0000000000000001E-3,-1.2110000000000001,0,0,4948.7120000000004,2333.5970000000002,1793.5260000000001,275.54700000000003,14.981\n2023-09-13 14:00:00,16487.899000000005,-3.4790000000000001,-2.153,-0.001,-1313.761,17807.293000000001,916.36900000000003,1479.9179999999999,0,0,0,4.0000000000000001E-3,-3.2149999999999999,0,0,5307.5870000000004,2299.7890000000002,1678.1969999999999,306.55500000000001,13.962\n2023-09-13 15:00:00,17244.342999999997,-3.3460000000000001,-2.113,-0.001,-552.73900000000003,17802.542000000001,916.25599999999997,1419.5820000000001,0,0,0,4.0000000000000001E-3,-3.387,0,0,5422.0479999999998,2295.9459999999999,1481.8140000000001,385.57799999999997,14.532\n2023-09-13 16:00:00,17855.056,-3.4660000000000002,-2.101,-0.001,-55.628999999999998,17916.253000000001,915.08799999999997,1426.413,0,0,0,4.0000000000000001E-3,674.97199999999998,0,0,5396.7600000000002,2268.529,1090.7950000000001,410.55900000000003,14.83\n2023-09-13 17:00:00,17838.575000000001,-3.492,-2.1110000000000002,-0.001,-10.609,17854.788,911.73800000000006,1408.3309999999999,0,0,0,92.004000000000005,2111.9430000000002,0,0,5583.8029999999999,2258.799,382.36599999999999,393.82100000000003,15.045999999999999\n2023-09-13 18:00:00,17982.059999999998,-3.359,-2.125,-0.001,0,17987.544999999998,911.09500000000003,1350.5,0,0,0,536.59699999999998,2893.0949999999998,0,342.69999999999999,6251.2489999999998,2157.0500000000002,9.4019999999999992,366.06099999999998,15.089\n2023-09-13 19:00:00,18134.697000000004,-3.492,-2.1400000000000001,-0.001,0,18140.330000000002,910.90300000000002,1312.684,0,0,0,329.17899999999997,2295.6060000000002,0,104.3,6330.3299999999999,2008.076,0,347.23099999999999,14.952999999999999\n2023-09-13 20:00:00,18002.872000000003,-3.492,-2.1539999999999999,-0.002,-14.202999999999999,18022.723000000002,910.89200000000005,1401.1600000000001,0,0,0,4.0000000000000001E-3,1764.2159999999999,0,0,5455.5159999999996,2101.3539999999998,0,338.505,14.962\n2023-09-13 21:00:00,17601.118000000002,-3.532,-2.141,-0.002,-242.83500000000001,17849.628000000001,911.03899999999999,1408.3779999999999,0,0,0,4.0000000000000001E-3,257.82600000000002,0,0,4870.0990000000002,2126.596,0,325.101,14.702999999999999\n2023-09-17 11:00:00,,,,,,,,,,,,,,,,,,,,\n2023-09-13 22:00:00,16850.659,-3.5190000000000001,-2.1360000000000001,-0.002,-796.64400000000001,17652.959999999999,910.84500000000003,1320.934,0,0,0,4.0000000000000001E-3,-8.6790000000000003,0,0,3279.0700000000002,2238.3890000000001,0,86.668999999999997,14.191000000000001\n2023-09-13 23:00:00,15743.68,-3.532,-2.1429999999999998,-0.002,-1960.924,17710.280999999999,910.88,1305.672,0,0,0,4.0000000000000001E-3,-5.4340000000000002,0,0,3025.7440000000001,2194.1239999999998,0,36.600000000000001,14.323\n2023-09-14 00:00:00,15305.423000000001,-3.492,-2.1360000000000001,-0.002,-2493.3690000000001,17804.421999999999,911.26599999999996,1275.799,0,0,0,4.0000000000000001E-3,-2.6019999999999999,0,0,2737.8180000000002,2278.174,0,36.564999999999998,14.31\n2023-09-14 01:00:00,14799.502999999999,-3.5059999999999998,-2.1539999999999999,-0.002,-2766.4209999999998,17571.585999999999,910.98000000000002,1281.837,0,0,0,4.0000000000000001E-3,0,0,0,2642.0839999999998,2332.3270000000002,0,19.158999999999999,14.247999999999999\n2023-09-14 02:00:00,14717.301999999998,-3.5190000000000001,-2.1499999999999999,-0.002,-2740.009,17462.982,911.17899999999997,1293.8630000000001,0,0,0,4.0000000000000001E-3,0,0,0,2630.0650000000001,2309.4290000000001,0,0,14.327\n2023-09-14 03:00:00,15175.183999999999,-3.5190000000000001,-2.1539999999999999,-0.002,-2617.384,17798.242999999999,910.84199999999998,1285.019,0,0,0,4.0000000000000001E-3,0,0,0,2662.9830000000002,2113.4789999999998,0,0,32.283000000000001\n2023-09-14 04:00:00,16455.666000000001,-3.5190000000000001,-2.1680000000000001,-0.002,-1736.8489999999999,18198.204000000002,912.077,1290.261,0,0,0,4.0000000000000001E-3,-6.4299999999999997,0,0,3089.877,2242.2170000000001,0,0,38.009\n2023-09-14 05:00:00,18363.392,-3.5059999999999998,-2.1720000000000002,-0.002,-90.224999999999994,18459.296999999999,911.41700000000003,1309.6410000000001,0,0,0,12.004,825.48299999999995,0,0,3794.8069999999998,2062.6700000000001,0,0,39.011000000000003\n2023-09-14 06:00:00,18541.700000000001,-3.5059999999999998,-2.1600000000000001,-0.002,-14.084,18561.452000000001,911.16700000000003,1362.644,376.32499999999999,0,127.559,234.00399999999999,1711.6880000000001,0,0,4308.7340000000004,1785.3630000000001,27.151,0,39.049999999999997\n2023-09-14 07:00:00,18524.117999999999,-3.5059999999999998,-2.169,-0.001,-38.887999999999998,18568.682000000001,911.06100000000004,1377.8130000000001,322.375,0,103.532,490.63299999999998,745.13900000000001,0,0,4173.6790000000001,1601.4200000000001,526.80700000000002,0.56699999999999995,39.081000000000003\n2023-09-17 09:00:00,,,,,,,,,,,,,,,,,,,,\n2023-09-14 08:00:00,18601.262999999999,-3.4790000000000001,-2.169,0,-31.568999999999999,18638.48,910.96900000000005,1366.4970000000001,0.055,0,0,216.02699999999999,951.16600000000005,0,0,4210.7240000000002,1372.768,1211.7840000000001,112.919,37.789000000000001\n2023-09-14 09:00:00,18589.592000000001,-3.4660000000000002,-2.141,-0.001,-164.005,18759.205000000002,910.94500000000005,1353.6300000000001,0,0,0,120.474,2.911,0,0,4286.6260000000002,1495.8889999999999,1554.9960000000001,312.05599999999998,37.648000000000003\n2023-09-14 10:00:00,17969.671999999999,-3.4790000000000001,-2.1139999999999999,-0.001,-893.26900000000001,18868.535,911.58000000000004,1361.644,0,0,0,4.0000000000000001E-3,-3.8130000000000002,0,0,4473.9430000000002,1638.9290000000001,1742.559,416.40499999999997,28.669\n2023-09-14 11:00:00,17167.775000000001,-3.359,-2.121,-0.001,-1449.1990000000001,18622.455000000002,911.59000000000003,1391.4849999999999,0,0,0,4.0000000000000001E-3,-1.7849999999999999,0,0,4671.7790000000005,1818.4580000000001,1824.8309999999999,416.803,14.742000000000001\n2023-09-14 12:00:00,17174.739000000001,-3.492,-2.1190000000000002,-0.001,-1382.8920000000001,18563.242999999999,911.55399999999997,1458.1479999999999,0,0,0,4.0000000000000001E-3,-3.8900000000000001,0,0,4534.9930000000004,1985.1130000000001,1839.2750000000001,428.83800000000002,14.725\n2023-09-14 13:00:00,16933.638000000003,-3.4790000000000001,-2.1219999999999999,-0.001,-1262.1420000000001,18201.382000000001,911.65499999999997,1426.8969999999999,0,0,0,4.0000000000000001E-3,-2.6339999999999999,0,0,4632.9139999999998,1913.9110000000001,1800.847,424.04599999999999,14.34\n2023-09-14 14:00:00,17033.444000000003,-3.4660000000000002,-2.121,-0.001,-1172.6890000000001,18211.721000000001,911.54200000000003,1458.069,0,0,0,4.0000000000000001E-3,-5.9960000000000004,0,0,5146.1559999999999,1805.72,1711.5319999999999,423.733,13.801\n2023-09-14 15:00:00,17707.669999999998,-3.3330000000000002,-2.1150000000000002,-0.001,-618.52200000000005,18331.641,911.87599999999998,1476.2190000000001,0,0,0,4.0000000000000001E-3,-6.3220000000000001,0,0,5298.7070000000003,1706.2329999999999,1537.4639999999999,432.62200000000001,13.800000000000001\n2023-09-14 16:00:00,18335.621999999999,-3.4660000000000002,-2.1389999999999998,-0.001,-60.427999999999997,18401.655999999999,911.84400000000005,1406.126,0,0,0,4.0000000000000001E-3,483.77999999999997,0,0,5437.9570000000003,1675.3979999999999,1143.854,455.101,13.59\n2023-09-14 17:00:00,18505.351000000002,-3.6120000000000001,-2.1549999999999998,-0.001,-18.317,18529.436000000002,911.88499999999999,1354.01,0,0,0,4.0000000000000001E-3,1752.8499999999999,0,0,5679.8509999999997,1519.395,410.334,415.90699999999998,13.638\n2023-09-14 18:00:00,18506.524999999998,-3.3460000000000001,-2.202,-0.001,-1.298,18513.371999999999,911.31799999999998,1376.568,0,0,0,501.70299999999997,2560.3229999999999,174,357.60000000000002,6008.0370000000003,1512.3610000000001,9.891,371.59699999999998,14.537000000000001\n2023-09-14 19:00:00,18482.875,-3.6259999999999999,-2.1720000000000002,-0.001,-4.258,18492.932000000001,911.14999999999998,1341.5350000000001,0,0,0,487.17899999999997,2012.9359999999999,174,89.400000000000006,6018.5190000000002,1525.991,0,357.721,14.581\n2023-09-14 20:00:00,18418.463999999996,-3.359,-2.1600000000000001,-0.002,-8.6500000000000004,18432.634999999998,911.41300000000001,1344.104,0,0,0,20.004000000000001,1874.2090000000001,0,0,5027.8500000000004,1657.748,0,350.06099999999998,14.27\n2023-09-14 21:00:00,18089.856,-3.532,-2.1859999999999999,-0.002,-150.03,18245.606,911.12300000000005,1342.4749999999999,41.399999999999999,0,0,4.0000000000000001E-3,206.94300000000001,0,0,4510.4480000000003,1564.079,0,333.62799999999999,14.723000000000001\n2023-09-14 22:00:00,17487.196,-3.492,-2.1619999999999999,-0.002,-720.39700000000005,18213.249,911.63999999999999,1304.319,46.399999999999999,0,0,4.0000000000000001E-3,-12.055,0,0,3372.8890000000001,1481.886,0,89.256,13.949999999999999\n2023-09-14 23:00:00,16436.021000000001,-3.5190000000000001,-2.1640000000000001,-0.002,-1941.604,18383.310000000001,911.62599999999998,1283.511,0,0,0,4.0000000000000001E-3,0,0,0,2906.3040000000001,1462.6279999999999,0,38.585000000000001,13.462999999999999\n2023-09-15 00:00:00,16161.578,-3.5059999999999998,-2.1579999999999999,-0.002,-1883.385,18050.629000000001,911.63499999999999,1312.4970000000001,0,0,0,4.0000000000000001E-3,-3.661,0,0,2662.8719999999998,1814.5830000000001,0,38.677999999999997,15.891999999999999\n2023-09-15 01:00:00,15331.948,-3.5190000000000001,-2.1720000000000002,-0.002,-2687.4850000000001,18025.126,911.73299999999995,1315.4059999999999,0,0,0,4.0000000000000001E-3,-1.964,0,0,2782.3020000000001,1941.3879999999999,0,38.520000000000003,16.196000000000002\n2023-09-15 02:00:00,15202.562999999998,-3.5190000000000001,-2.1659999999999999,-0.002,-2774.8409999999999,17983.091,911.97900000000004,1274.8520000000001,0,0,0,4.0000000000000001E-3,0,0,0,2856.933,1930.479,0,38.581000000000003,16.004000000000001\n2023-09-15 03:00:00,15449.088999999996,-3.5190000000000001,-2.1859999999999999,-0.002,-2761.0360000000001,18215.831999999999,911.89999999999998,1048.7339999999999,0,0,0,4.0000000000000001E-3,0,0,0,3019.9720000000002,2086.511,0,38.844999999999999,33.820999999999998\n2023-09-15 04:00:00,16558.105000000003,-3.359,-2.226,-0.002,-2276.424,18840.116000000002,912.35599999999999,1297.502,0,0,0,4.0000000000000001E-3,-1.254,0,0,3272.5790000000002,2243.1120000000001,0,38.813000000000002,39.886000000000003\n2023-09-15 05:00:00,18493.691999999999,-3.5059999999999998,-2.194,-0.002,-758.97199999999998,19258.366000000002,912.52700000000004,1328.4090000000001,0,0,0,2.004,8.4779999999999998,0,0,4171.9669999999996,2426.3890000000001,0,5.5099999999999998,40.573\n2023-09-15 06:00:00,19208.302,-3.4790000000000001,-2.2149999999999999,-0.002,-20.876000000000001,19234.874,911.93399999999997,1334.2070000000001,0,0,0,239.00399999999999,583.14300000000003,0,0,4242.5320000000002,2408.1210000000001,51.170000000000002,0,40.488999999999997\n2023-09-15 07:00:00,18859.361000000001,-3.4790000000000001,-2.173,-0.001,-233.64400000000001,19098.657999999999,911.95399999999995,1396.568,0,0,0,485.49000000000001,-0.48199999999999998,0,0,4103.1909999999998,2329.6869999999999,670.56500000000005,3.4569999999999999,40.588999999999999\n2023-09-15 08:00:00,19189.161,-3.4790000000000001,-2.1600000000000001,0,-52.683999999999997,19247.484,911.77099999999996,1353.6769999999999,0,0,0,219.26300000000001,-1.4530000000000001,0,0,4100.0659999999998,2162.8200000000002,1361.7850000000001,96.210999999999999,39.941000000000003\n2023-09-15 09:00:00,18092.421000000002,-3.359,-2.161,-0.001,-954.31500000000005,19052.257000000001,911.49099999999999,1406.1320000000001,0,0,0,123.38800000000001,-10.525,0,0,4341.0690000000004,2317.6280000000002,1611.4190000000001,246.13300000000001,39.826999999999998\n2023-09-15 10:00:00,17567.777000000002,-3.4790000000000001,-2.1230000000000002,-0.001,-1461.634,19035.013999999999,911.73900000000003,1438.367,0,0,0,2.004,-3.5670000000000002,0,0,4429.3149999999996,2500.634,1732.2349999999999,342.75,29.998999999999999\n2023-09-15 11:00:00,17200.021999999997,-3.3460000000000001,-2.1099999999999999,-0.001,-1769.5699999999999,18975.048999999999,911.82399999999996,1437.6600000000001,0,0,0,4.0000000000000001E-3,-0.76600000000000001,0,0,4314.9750000000004,2527.6759999999999,1770.5350000000001,349.68700000000001,15.362\n2023-09-15 12:00:00,17266.279000000002,-3.492,-2.0830000000000002,-0.001,-1647.1559999999999,18919.010999999999,911.69100000000003,1465.114,0,0,0,4.0000000000000001E-3,-3.9369999999999998,0,0,3899.915,2622.9879999999998,1791.6130000000001,351.65699999999998,15.606\n2023-09-15 13:00:00,16634.255000000001,-3.5190000000000001,-2.109,-0.001,-1796.8199999999999,18436.704000000002,910.32399999999996,1506.1659999999999,0,0,0,4.0000000000000001E-3,-0.81299999999999994,0,0,3845.5970000000002,2809.5900000000001,1729.5260000000001,348.99599999999998,15.666\n2023-09-15 14:00:00,17157.189000000002,-3.492,-2.0840000000000001,-0.001,-1172.0229999999999,18334.789000000001,910.91099999999994,1548.54,0,0,0,4.0000000000000001E-3,-2.073,0,0,3153.77,2785.0790000000002,1663.761,302.346,15.502000000000001\n2023-09-15 15:00:00,17042.097000000002,-3.492,-2.081,-0.001,-1106.2850000000001,18153.955999999998,911.37400000000002,1551.7550000000001,0,0,0,4.0000000000000001E-3,-5.9080000000000004,0,0,3348.4270000000001,2887.0700000000002,1507.693,304.81799999999998,15.441000000000001\n2023-09-15 16:00:00,18037.438000000002,-3.4790000000000001,-2.0840000000000001,-0.001,-180.548,18223.549999999999,912.41800000000001,1451.454,0,0,0,4.0000000000000001E-3,105.27,0,0,3399.3049999999998,2888.105,1107.3530000000001,310.15199999999999,15.592000000000001\n2023-09-15 17:00:00,18476.201000000001,-3.5059999999999998,-2.1070000000000002,-0.001,-21.780000000000001,18503.595000000001,911.81500000000005,1354.6310000000001,0,0,0,4.0000000000000001E-3,703.16099999999994,0,0,3542.75,2958.54,411.32600000000002,294.23000000000002,15.587999999999999\n2023-09-15 18:00:00,18699.786000000004,-3.492,-2.1259999999999999,-0.001,-6.423,18711.828000000001,912.08299999999997,1336.0060000000001,0,0,0,353.47199999999998,1885.5419999999999,335,0,3641.018,2833.5749999999998,10.106,264.72699999999998,15.638\n2023-09-15 19:00:00,18745.701999999997,-3.5059999999999998,-2.1320000000000001,0,-13.733000000000001,18765.073,911.67700000000002,1310.6010000000001,0,0,0,508.303,1179.7950000000001,167.5,0,3933.2559999999999,2454.6300000000001,0,248.47200000000001,15.676\n2023-09-15 20:00:00,18941.120999999999,-3.5059999999999998,-2.1400000000000001,-0.002,-3.778,18950.546999999999,911.52099999999996,1364.316,0,0,0,274.25200000000001,1508.8099999999999,0,0,2985.27,2397.7310000000002,0,239.35900000000001,15.66\n2023-09-15 21:00:00,18704.597000000002,-3.6389999999999998,-2.1379999999999999,-0.002,-75.819000000000003,18786.195,911.55399999999997,1380.951,0,0,0,4.0000000000000001E-3,396.06900000000002,0,0,2777.8690000000001,2407.4630000000002,0,230.63999999999999,15.635999999999999\n2023-09-15 22:00:00,18024.108999999997,-3.5190000000000001,-2.1469999999999998,-0.002,-850.37900000000002,18880.155999999999,911.43499999999995,1299.1669999999999,0,0,0,4.0000000000000001E-3,-7.4349999999999996,0,0,2236.5619999999999,2415.2190000000001,0,89.489999999999995,15.586\n2023-09-15 23:00:00,16735.131000000001,-3.492,-2.1619999999999999,-0.002,-2195.0189999999998,18935.806,911.84500000000003,1288.837,0,0,0,4.0000000000000001E-3,-4.0019999999999998,0,0,1939.1859999999999,2505.2109999999998,0,38.978000000000002,15.542999999999999\n2023-09-16 00:00:00,16126.907999999999,-3.6259999999999999,-2.1749999999999998,-0.002,-2380.2539999999999,18512.965,911.67700000000002,1284.597,0,0,0,4.0000000000000001E-3,-3.3530000000000002,0,0,1605.521,2586.9560000000001,0,38.994999999999997,15.536\n2023-09-16 01:00:00,15676.343999999999,-3.5059999999999998,-2.177,-0.002,-2716.7620000000002,18398.791000000001,911.99400000000003,1290.182,0,0,0,4.0000000000000001E-3,0,0,0,1558.8630000000001,2584.1959999999999,0,38.954999999999998,15.552\n2023-09-16 02:00:00,15965.594999999996,-3.5059999999999998,-2.1819999999999999,-3.0000000000000001E-3,-2323.7069999999999,18294.992999999999,912.23500000000001,1301.991,0,0,0,4.0000000000000001E-3,-2.8679999999999999,0,0,894.07000000000005,2662.3969999999999,0,38.241,15.76\n2023-09-16 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Used to compare expressions.','ExpressionEditorStringId.Function_IsNextMonth':'IsNextMonth(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the next month.','ExpressionEditorStringId.Function_GetMinute':'GetMinute(DateTime)\\r\\n\\r\\nExtracts minutes from the defined DateTime.','ExpressionEditorStringId.Function_LocalDateTimeNow':'LocalDateTimeNow()\\r\\n\\r\\nReturns a DateTime value corresponding to the current moment in time.','ExpressionEditorStringId.Function_LocalDateTimeTwoYearsAway':'LocalDateTimeTwoYearsAway()\\r\\n\\r\\nReturns a date-time value corresponding to the first day of the year after next.','ExpressionEditorStringId.Function_Tan':'Tan(Value)\\r\\n\\r\\nReturns the tangent of the angle defined in radians.','ExpressionEditorStringId.Function_Max':'Max(Value1, Value2)\\r\\n\\r\\nReturns the maximum value from the specified values.','ExpressionEditorStringId.Function_Min':'Min(Value1, Value2)\\r\\n\\r\\nReturns the minimum value from the specified values.','ExpressionEditorStringId.Function_Rnd':'Rnd()\\r\\n\\r\\nReturns a random number that is less than 1, but greater than or equal to zero.','ExpressionEditorStringId.Function_Sin':'Sin(Value)\\r\\n\\r\\nReturns the sine of the angle, defined in radians.','ExpressionEditorStringId.Function_Sqr':'Sqr(Value)\\r\\n\\r\\nReturns the square root of a given number Value.','ExpressionEditorStringId.Function_Iif':'Iif(FirstClause, FirstClauseTrueValue, ..., LastClause, LastClauseTrueValue, FalseValue)\\r\\n\\r\\nReturns either a value defined for the first Boolean condition that is True, or the last value if none of these conditions is True.\\r\\n\\r\\nThis function can accept any number of arguments.','ExpressionEditorStringId.Function_Now':'Now()\\r\\n\\r\\nReturns the current system date and time.','ExpressionEditorStringId.Function_Len':'Len(Value)\\r\\n\\r\\nReturns an integer containing either the number of characters in a string or the nominal number of bytes required to store a variable.','ExpressionEditorStringId.Function_Log':'Log(Value)\\r\\n\\r\\nReturns the natural logarithm of a specified number.','ExpressionEditorStringId.Function_Exp':'Exp(Value)\\r\\n\\r\\nReturns the exponential value of the given float expression.','ExpressionEditorStringId.Function_Atn':'Atn(Value)\\r\\n\\r\\nReturns the arctangent of a number (the angle, in radians, whose tangent is the given float expression).','ExpressionEditorStringId.Function_Abs':'Abs(Value)\\r\\n\\r\\nReturns the absolute, positive value of the given numeric expression.','ExpressionEditorStringId.Function_Cos':'Cos(Value)\\r\\n\\r\\nReturns the cosine of the angle defined in radians.','ExpressionEditorStringId.Function_MaxAggregate':'Max()\\r\\n\\r\\nReturns the maximum expression value in a collection.','ExpressionEditorStringId.Exception_InvalidNumericLiteral':'Invalid numeric literal value: \"{0}\".','ExpressionEditorStringId.Function_AddSeconds':'AddSeconds(DateTime, SecondsCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of SecondsCount away from the specified DateTime.','ExpressionEditorStringId.Operator_BitwiseOr':'Compares each bit of its first operand to the corresponding bit of its second operand. If both bits are 0, the corresponding result bit is 0. Otherwise, the corresponding result bit is 1.','ExpressionEditorStringId.Function_IsApril':'IsApril(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within April.','ExpressionEditorStringId.Function_IsMarch':'IsMarch(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within March.','ExpressionEditorStringId.Function_DateDiffMonth':'DateDiffMonth(StartDate, EndDate)\\r\\n\\r\\nReturns the number of month boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_AvgAggregate':'Avg()\\r\\n\\r\\nEvaluates the average of the values in the collection.','ExpressionEditorStringId.Function_GetMilliSecond':'GetMilliSecond(DateTime)\\r\\n\\r\\nExtracts milliseconds from the defined DateTime.','ExpressionEditorStringId.Function_IsDecember':'IsDecember(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within December.','ExpressionEditorStringId.Function_GetSecond':'GetSecond(DateTime)\\r\\n\\r\\nExtracts seconds from the defined DateTime.','ExpressionEditorStringId.Function_IsAugust':'IsAugust(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within August.','ExpressionEditorStringId.Function_Round_2':'Round(Value, Precision)\\r\\n\\r\\nRounds the given Value to the nearest integer, or to a specified Precision.','ExpressionEditorStringId.Function_Tanh':'Tanh(Value)\\r\\n\\r\\nReturns the hyperbolic tangent of the angle defined in radians.','ExpressionEditorStringId.Function_Trim':'Trim(String)\\r\\n\\r\\nRemoves all leading and trailing SPACE characters from String.','ExpressionEditorStringId.Function_Sign':'Sign(Value)\\r\\n\\r\\nReturns the positive (+1), zero (0), or negative (-1) sign of the given Value.','ExpressionEditorStringId.Function_Sinh':'Sinh(Value)\\r\\n\\r\\nReturns the hyperbolic sine of the angle defined in radians.','ExpressionEditorStringId.Function_Join':'Join(Collection)\\r\\n\\r\\nConcatenates elements of the specified Collection, inserting comma between each element.','ExpressionEditorStringId.Function_Atn2':'Atn2(Value1, Value2)\\r\\n\\r\\nReturns the angle whose tangent is the quotient of two specified numbers, in radians.','ExpressionEditorStringId.Function_Asin':'Asin(Value)\\r\\n\\r\\nReturns the arcsine of a number (the angle, in radians, whose sine is the given float expression).','ExpressionEditorStringId.Function_Acos':'Acos(Value)\\r\\n\\r\\nReturns the arccosine of a number (the angle, in radians, whose cosine is the given float expression).','ExpressionEditorStringId.Function_Cosh':'Cosh(Value)\\r\\n\\r\\nReturns the hyperbolic cosine of the angle defined in radians.','ExpressionEditorStringId.Function_Char':'Char(Number)\\r\\n\\r\\nConverts the specified ASCII integer Number to a character.','ExpressionEditorStringId.Operator_Not':'Performs logical negation on an expression.','ExpressionEditorStringId.Operator_And':'Performs a logical conjunction on two expressions.','ExpressionEditorStringId.Exception_WrongArgumentsCount':'Wrong arguments count for function \"{0}(...)\".','ExpressionEditorStringId.Function_ToDecimal':'ToDecimal(Value)\\r\\n\\r\\nConverts Value to an equivalent decimal number.','ExpressionEditorStringId.Operator_NotEqual':'Returns true if the operands do not have the same value; otherwise, it returns false.','ExpressionEditorStringId.Function_IsNull_2':'IsNull(Value1, Value2)\\r\\n\\r\\nReturns the second operand if the first operand is null, otherwise, the first operand is returned.','ExpressionEditorStringId.Function_Replace':'Replace(String, SubString2, String3)\\r\\n\\r\\nReturns a copy of String1, in which SubString2 has been replaced with String3.','ExpressionEditorStringId.Function_Reverse':'Reverse(String)\\r\\n\\r\\nReverses the order of elements within a String.','ExpressionEditorStringId.Exception_InvalidCharacter':'Invalid input character: \"{0}\".','ExpressionEditorStringId.Function_GetHour':'GetHour(DateTime)\\r\\n\\r\\nExtracts an hour from the defined DateTime.','ExpressionEditorStringId.Function_GetDate':'GetDate(DateTime)\\r\\n\\r\\nExtracts a date from the defined DateTime.','ExpressionEditorStringId.Function_GetYear':'GetYear(DateTime)\\r\\n\\r\\nExtracts a year from the defined DateTime','ExpressionEditorStringId.Operator_Minus':'Finds the difference between two numbers.','ExpressionEditorStringId.Operator_Equal':'Returns true if both operands have the same value; otherwise, it returns false.','ExpressionEditorStringId.Function_InRange':'InRange(FirstOperand, SecondOperand, ThirdOperand)\\r\\n\\r\\nSpecifies a range to test. Returns true if the first operand is greater than or equal to the second operand and less than the third operand.','ExpressionEditorStringId.Operator_LessOrEqual':'Less than or equal to operator. Used to compare expressions.','ExpressionEditorStringId.Function_DateDiffHour':'DateDiffHour(StartDate, EndDate)\\r\\n\\r\\nReturns the number of hour boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_DateDiffTick':'DateDiffTick(StartDate, EndDate)\\r\\n\\r\\nReturns the number of tick boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_DateDiffYear':'DateDiffYear(StartDate, EndDate)\\r\\n\\r\\nReturns the number of year boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_ExistsAggregate':'Exists()\\r\\n\\r\\nDetermines whether the object exists in the collection.','ExpressionEditorStringId.Function_IsNextYear':'IsNextYear(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the next year.','ExpressionEditorStringId.Exception_MalformedProperty':'Malformed property name: missing closing \"{0}\".','ExpressionEditorStringId.Constant_False':'Represents the Boolean False value.','ExpressionEditorStringId.Function_MinAggregate':'Min()\\r\\n\\r\\nReturns the minimum expression value in a collection.','ExpressionEditorStringId.Function_Substring_3':'Substring(String, StartPosition, Length)\\r\\n\\r\\nRetrieves a substring from String. The substring starts at StartPosition and has the specified Length.','ExpressionEditorStringId.Function_LocalDateTimeTomorrow':'LocalDateTimeTomorrow()\\r\\n\\r\\nReturns a date-time value corresponding to Tomorrow.','ExpressionEditorStringId.Function_IsSameDay':'IsSameDay(DateTime, DateTime)\\r\\n\\r\\nReturns True if the specified DateTime values fall within the same day.','ExpressionEditorStringId.Function_GetMonth':'GetMonth(DateTime)\\r\\n\\r\\nExtracts a month from the defined DateTime.','ExpressionEditorStringId.Function_LocalDateTimeThisMonth':'LocalDateTimeThisMonth()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the current month.','ExpressionEditorStringId.Function_Ceiling':'Ceiling(Value)\\r\\n\\r\\nReturns the smallest integer that is greater than or equal to the given numeric expression.','ExpressionEditorStringId.Function_CharIndex_3':'CharIndex(String1, String2, StartLocation)\\r\\n\\r\\nReturns the starting position of String1 within String2, beginning from the StartLocation character position to the end of a string.','ExpressionEditorStringId.Function_LocalDateTimeLastYear':'LocalDateTimeLastYear()\\r\\n\\r\\nReturns a date-time value corresponding to the first day of the previous year.','ExpressionEditorStringId.Function_LocalDateTimeLastWeek':'LocalDateTimeLastWeek()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the previous week.','ExpressionEditorStringId.Function_IsNovember':'IsNovember(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within November.','ExpressionEditorStringId.Function_FormatString':'FormatString(Format, Value1, ... , ValueN)\\r\\n\\r\\nReturns the specified string with formatted field values.\\r\\nThis function can accept any number of arguments.\\r\\n\\r\\nExample:\\r\\n\\r\\nFormatString(\\'{0} - {1:c}\\', [Column1], [Column2])','ExpressionEditorStringId.Function_InDateRange':'InDateRange(DateTime, DateTime, DateTime)\\r\\n\\r\\nSpecifies a date range to test. Returns true if a date part of the first operand is greater than or equal to the date part of the second operand and less than or equal the date part of the third operand.','ExpressionEditorStringId.Function_CharIndex':'CharIndex(String1, String2)\\r\\n\\r\\nReturns the starting position of String1 within String2, beginning from the zero character position to the end of a string.','ExpressionEditorStringId.Function_DateDiffMinute':'DateDiffMinute(StartDate, EndDate)\\r\\n\\r\\nReturns the number of minute boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_IsThisMonth':'IsThisMonth(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the current month.','ExpressionEditorStringId.Function_LocalDateTimeTwoWeeksAway':'LocalDateTimeTwoWeeksAway()\\r\\n\\r\\nReturns a date-time value corresponding to the first day of the week that is after next week.','ExpressionEditorStringId.Function_LocalDateTimeToday':'LocalDateTimeToday()\\r\\n\\r\\nReturns a DateTime value corresponding to Today.','ExpressionEditorStringId.Function_LocalDateTimeNextMonth':'LocalDateTimeNextMonth()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of next month.','ExpressionEditorStringId.Function_EndsWith':'EndsWith(String, EndString)\\r\\n\\r\\nReturns True if the end of String matches EndString; otherwise, False is returned.','ExpressionEditorStringId.Function_CountAggregate':'Count()\\r\\n\\r\\nReturns the number of objects in a collection.','ExpressionEditorStringId.Operator_Modulo':'Returns the remainder (modulus) obtained by dividing one numeric expression into another.','ExpressionEditorStringId.Function_DateDiffDay':'DateDiffDay(StartDate, EndDate)\\r\\n\\r\\nReturns the number of day boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_LocalDateTimeNextWeek':'LocalDateTimeNextWeek()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the following week.','ExpressionEditorStringId.Function_LocalDateTimeNextYear':'LocalDateTimeNextYear()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the following year.','ExpressionEditorStringId.Operator_GreaterOrEqual':'Greater than or equal to operator. Used to compare expressions.','ExpressionEditorStringId.Function_IsLastYear':'IsLastYear(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the previous year.','ExpressionEditorStringId.Function_AddTimeSpan':'AddTimeSpan(DateTime, TimeSpan)\\r\\n\\r\\nReturns a date-time value that is away from the specified DateTime for the given TimeSpan.','ExpressionEditorStringId.Function_CreateTable':'CreateTable(Parameter1, ..., ParameterN)\\r\\n\\r\\nPrepares a table from values of several specified multi-value parameters.','ExpressionEditorStringId.Function_DateDiffSecond':'DateDiffSecond(StartDate, EndDate)\\r\\n\\r\\nReturns the number of second boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_DateDiffMilliSecond':'DateDiffMilliSecond(StartDate, EndDate)\\r\\n\\r\\nReturns the number of millisecond boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_NewLine':'NewLine()\\r\\n\\r\\nReturns the newline string defined for this environment.','ExpressionEditorStringId.Operator_Divide':'Divides the first operand by the second.','ExpressionEditorStringId.Function_GetDayOfWeek':'GetDayOfWeek(DateTime)\\r\\n\\r\\nExtracts a day of the week from the defined DateTime.','ExpressionEditorStringId.Function_GetDayOfYear':'GetDayOfYear(DateTime)\\r\\n\\r\\nExtracts a day of the year from the defined DateTime.','ExpressionEditorStringId.Function_AddMilliSeconds':'AddMilliSeconds(DateTime, MilliSecondsCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of MilliSecondsCount away from the specified DateTime.','ExpressionEditorStringId.Function_LocalDateTimeYearBeforeToday':'LocalDateTimeYearBeforeToday()\\r\\n\\r\\nReturns a date-time value corresponding to the day one year ago.','ExpressionEditorStringId.Function_UtcNow':'UtcNow()\\r\\n\\r\\nReturns the current system date and time, expressed as Coordinated Universal Time (UTC).','ExpressionEditorStringId.Function_AddDays':'AddDays(DateTime, DaysCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of DaysCount away from the specified DateTime.','ExpressionEditorStringId.Function_AddMinutes':'AddMinutes(DateTime, MinutesCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of MinutesCount away from the specified DateTime.','ExpressionEditorStringId.Function_ToLong':'ToLong(Value)\\r\\n\\r\\nConverts Value to an equivalent 64-bit signed integer.','ExpressionEditorStringId.Function_ToFloat':'ToFloat(Value)\\r\\n\\r\\nConverts Value to an equivalent 32-bit single-precision floating-point number.','ExpressionEditorStringId.Function_Remove':'Remove(String, StartPosition)\\r\\n\\r\\nDeletes all characters from specified String, beginning at a specified StartPosition.','ExpressionEditorStringId.Function_IsJanuary':'IsJanuary(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within January.','ExpressionEditorStringId.Function_IsNull':'IsNull(Value)\\r\\n\\r\\nReturns True if the specified Value is NULL.','ExpressionEditorStringId.Function_IsJuly':'IsJuly(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within July.','ExpressionEditorStringId.Function_IsJune':'IsJune(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within June.','ExpressionEditorStringId.Function_Insert':'Replace(String1, StartPosition, String2)\\r\\n\\r\\nInserts String2 into String1 at the position specified by StartPositon.','ExpressionEditorStringId.Function_Contains':'Contains(String, SubString)\\r\\n\\r\\nReturns True if SubString occurs within String; otherwise, False is returned.','ExpressionEditorStringId.Function_LocalDateTimeThisWeek':'LocalDateTimeThisWeek()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the current week.','ExpressionEditorStringId.Function_LocalDateTimeThisYear':'LocalDateTimeThisYear()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the current year.','ExpressionEditorStringId.Function_AddMonths':'AddMonths(DateTime, MonthsCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of MonthsCount away from the specified DateTime.','ExpressionEditorStringId.Function_Join_2':'Join(Collection, Separator)\\r\\n\\r\\nConcatenates elements of the specified Collection, using the specified Separator between each element.','ExpressionEditorStringId.Function_SumAggregate':'Sum()\\r\\n\\r\\nReturns the sum of all the expression values in the collection.','ExpressionEditorStringId.Function_IsSeptember':'IsSeptember(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within September.','ExpressionEditorStringId.Function_IsThisYear':'IsThisYear(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the current year.','ExpressionEditorStringId.Function_IsThisWeek':'IsThisWeek(DateTime)\\r\\n\\r\\nReturns True if the specified date falls within the current week.','ExpressionEditorStringId.Function_LocalDateTimeYesterday':'LocalDateTimeYesterday()\\r\\n\\r\\nReturns a date-time value corresponding to Yesterday.','ExpressionEditorStringId.Function_AddYears':'AddYears(DateTime, YearsCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of YearsCount away from the specified DateTime.','ExpressionEditorStringId.Function_StartsWith':'StartsWith(String, StartString)\\r\\n\\r\\nReturns True if the beginning of String matches StartString; otherwise, False is returned.','ExpressionEditorStringId.Function_PadRight_3':'PadRight(String, Length, Char)\\r\\n\\r\\nRight-aligns characters in the defined String, padding its right side with the specified Char up to a specified total Length.','ExpressionEditorStringId.Function_AddTicks':'AddTicks(DateTime, AddTicks)\\r\\n\\r\\nReturns a date-time value that is the specified number of TicksCount away from the specified DateTime.','ExpressionEditorStringId.Function_AddHours':'AddHours(DateTime, HoursCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of HoursCount away from the specified DateTime.','ExpressionEditorStringId.Function_PadRight':'PadRight(String, Length)\\r\\n\\r\\nRight-aligns characters in the defined String, padding its right side with white space characters up to a specified total Length.','ExpressionEditorStringId.Function_GetDay':'GetDay(DateTime)\\r\\n\\r\\nExtracts a day from the defined DateTime.','ExpressionEditorStringId.Function_LocalDateTimeTwoMonthsAway':'LocalDateTimeTwoMonthsAway()\\r\\n\\r\\nReturns a date-time value corresponding to the first day of the month after next.','ExpressionEditorStringId.Function_IsOctober':'IsOctober(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within October.','DataAccessUIStringId.WizardPageConfigureJsonConnection_HeaderValueText':'Header Value','DataAccessUIStringId.DataPreviewForm_Title':'Data Preview','DataAccessUIStringId.WizardPageConnectionProperties':'Select the data provider and specify the connection properties.','DataAccessUIStringId.EFDataSourceDesignerVerbEdit':'Edit...','DataAccessUIStringId.WizardPageChooseJsonSource_SourceType':'JSON Source:','DataAccessUIStringId.Button_Finish':'Finish','DataAccessUIStringId.QueryEditorTitle':'Query Editor','DataAccessUIStringId.FederationDataSourceQueryBuilder_AliasUniqueMessage':'Alias is not unique','DataAccessUIStringId.Button_Cancel':'Cancel','DataAccessUIStringId.WizardPageConfigureExcelFileColumns_ColumnNameEmptyError':'The column name cannot be empty.','DataAccessUIStringId.XPObjectSource_EntityTypeNotSet':'Property collection cannot be populated because EntityType is not set.','DataAccessUIStringId.WizardPageChooseObjectBindingMode_RetrieveData':'Retrieve the actual data','DataAccessUIStringId.WizardPageChooseFileOptions_SkipHiddenColumns':'Skip hidden columns','DataAccessUIStringId.DSTypeExcel':'Excel File','DataAccessUIStringId.ODSEditorsCannotResolveDataSource':'Cannot resolve the specified object type. To specify the object’s assembly, return type, data member and/or constructor parameters, use the Data Source editor.','DataAccessUIStringId.WizardPageChooseObjectAssembly':'Select an assembly containing the class type definition of a data source.','DataAccessUIStringId.WizardPageChooseObjectBindingMode_RetrieveSchema':'Retrieve the data source schema','DataAccessUIStringId.WizardPageChooseJsonSchema_RootElement':'Root element:','DataAccessUIStringId.ConnectionProperties_Port':'Port:','DataAccessUIStringId.WizardPageConfigureFederatedQueryPage_EditingIsNotSupported':'Editing is not supported for this query.','DataAccessUIStringId.SqlDataSourceDesignerVerbRebuildSchema':'Rebuild Result Schema','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeType_Union':'Union','DataAccessUIStringId.LoadingDataCustomError':'Error message:\\r\\n{0}\\r\\n','DataAccessUIStringId.ExpressionEditor_ExpressionContainsErrors':'The expression contains errors.','DataAccessUIStringId.JoinEditorLessOperator':'Is less than','DataAccessUIStringId.UpdateSchemaDataSourceIsNotReady':'The FileName and SourceOptions properties should be assigned.','DataAccessUIStringId.EFStoredProcsEditorTitle':'Manage Stored Procedures','DataAccessUIStringId.WizardPageChooseFileOptions_TrimBlanks':'Trim blanks','DataAccessUIStringId.ExcelDataSourceWizard_WorksheetItem':'Worksheet','DataAccessUIStringId.QueryBuilderColumns_SortingType':'Sorting Type','DataAccessUIStringId.FederatedQueryCollectionList_Title':'Federated Queries','DataAccessUIStringId.FilterStringEditorInvalidQuery':'An error occurred during query validation: {0}\\r\\nUpdate the connection settings so that they match the database schema or discard this query.','DataAccessUIStringId.WizardPageChooseFileOptions_SkipHiddenRows':'Skip hidden rows','DataAccessUIStringId.WizardPageConfigureFederatedQueryPage_InvalidQuery':'The query is invalid.','DataAccessUIStringId.ODSEditorsNoParametersMessage':'The {0} data member cannot receive parameters, because this is a method without parameters.','DataAccessUIStringId.WizardPageChooseEFConnectionString_ChooseConnection':'Yes, let me choose from list','DataAccessUIStringId.WizardPageConfigureFederatedQueryPage':'Create a federated query.','DataAccessUIStringId.WizardPageChooseConnection_SpecifyCustomConnection':'No, I\\'d like to specify the connection parameters myself','DataAccessUIStringId.WizardPageChooseConnection':'Do you want to use an existing data connection?','DataAccessUIStringId.QueryBuilderReverseRelationConfirmation':'The new join direction will be applied to all existing relations between the following two tables: {0}, {1}. Do you wish to continue?','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_AuthenticationType':'Authentication:','DataAccessUIStringId.WizardPageMultipleFederatedQueriesPage':'Create a federated query.\\r\\nData columns selected from specific data sources and/or tables will be automatically included into a separate query.','DataAccessUIStringId.UpdateDBSchemaCaption':'Request Database Schema','DataAccessUIStringId.FiltersView_TopAndSkipText':'records starting with index','DataAccessUIStringId.WizardPageChooseFileOptions_NewLineType':'Newline type:','DataAccessUIStringId.ErrorFormDatasourceInitializationText':'Unable to load data into one or several datasources. See information below for details.','DataAccessUIStringId.QueryBuilderColumn':'Column','DataAccessUIStringId.WaitFormWithCancel_Loading':'Loading Data...','DataAccessUIStringId.WizardPageChooseXPObjectSourceConnectionType':'Do you want to use the default data layer?','DataAccessUIStringId.Parameters_AddNewParameterPlaceholder':'Click the Add button to create a parameter.','DataAccessUIStringId.DSTypeFederation':'Data Federation','DataAccessUIStringId.MasterDetailEditorEditRelation':'Edit Relation','DataAccessUIStringId.QueryFilter_CreateQueryParameter':'Create Query Parameter','DataAccessUIStringId.ParametersColumn_QueryName':'Query','DataAccessUIStringId.QueryFilter_SelectParameter':'<select a parameter>','DataAccessUIStringId.WizardPageChooseXPObjectEntityType':'Choose an entity type.','DataAccessUIStringId.WizardFinishPageText':'Select an object to include in your data source','DataAccessUIStringId.EFConnectionEditorMessageCustomAssembliesProhibited':'The current security policy prohibits loading of third-party assemblies.\\r\\n\\r\\nClick OK to discard the current data source settings and configure them from scratch.\\r\\nClick Cancel to keep the current settings without configuring the data source','DataAccessUIStringId.WizardPageChooseObjectMember_ShowOnlyHighlighted':'Show only highlighted members','DataAccessUIStringId.WizardPageSaveConnection_SaveCredentialsQuestion':'The connection uses server authentication.\\r\\nDo you want to save the user name and password?','DataAccessUIStringId.JsonDataSourceSchemaEditorTitle':'JSON Data Source Schema Editor','DataAccessUIStringId.WizardPageChooseObjectConstructor':'Select a data source constructor.','DataAccessUIStringId.FiltersView_Distinct':'Select only distinct values','DataAccessUIStringId.WizardPageConfigureExcelFileColumns_ColumnExist':'Column with \\'{0}\\' name already exists.','DataAccessUIStringId.ConnectionProperties_Password':'Password:','DataAccessUIStringId.QueryBuilder_DeleteRelation':'Delete Relation','DataAccessUIStringId.MessageBoxCloseDataSourceWizardConfirmation':'Closing the Data Source Wizard will discard changes. Do you want to continue?','DataAccessUIStringId.ODSDataMemberEditorTitle':'Configure Data Member','DataAccessUIStringId.QueryBuilder_RemoveFromSelect':'Remove from Query','DataAccessUIStringId.ConnectionProperties_SslMode':'SSL Mode:','DataAccessUIStringId.QueryBuilderColumns_ColumnName':'Column Name','DataAccessUIStringId.WizardPageChooseFileOptions_Culture':'Culture:','DataAccessUIStringId.ConnectionProperties_AuthenticationType_MSSqlWindows':'Windows authentication','DataAccessUIStringId.WizardPageChooseObjectMember_BindToObject':'Do not select a member, bind to the entire object.','DataAccessUIStringId.Button_OK':'OK','DataAccessUIStringId.ConnectionProperties_Provider':'Provider:','DataAccessUIStringId.WizardPageChooseEFContext':'Choose a data context.','DataAccessUIStringId.MasterDetailEditorAddRelationMessage':'Add a relation to the detail query','DataAccessUIStringId.ConnectionProperties_AdvantageServerTypeLocal':'Local','DataAccessUIStringId.Button_Preview':'Preview...','DataAccessUIStringId.WizardPageChooseDSType':'Select data source type.','DataAccessUIStringId.MessageBoxWarningTitle':'Warning','DataAccessUIStringId.WizardPageObjectMemberParameters':'Specify the method parameters.','DataAccessUIStringId.WizardPageSaveJsonConnection_SaveRequestParametersPrompt':'Request parameters may contain sensitive data.\\r\\nDo you want to save request parameters?','DataAccessUIStringId.ODSEditorsAbstractTypeMessage':'Cannot use a constructor to create an object of the {0} type that is a static or abstract class, or interface.','DataAccessUIStringId.MessageMissingConnection':'No connection has been specified.','DataAccessUIStringId.WizardPageMultipleFederatedQueriesPage_AddQuery':'Add Query...','DataAccessUIStringId.QueryEditorWaitFormValidating':'Validating query...','DataAccessUIStringId.WizardPageChooseObjectMember_BindToMember':'Select a member to bind.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_ServiceName':'Service Name:','DataAccessUIStringId.WizardPageChooseFileOptions_SkipEmptyRows':'Skip empty rows','DataAccessUIStringId.EFFilterCollectionEditor':'Entity Framework Filter Collection Editor','DataAccessUIStringId.WizardPageChooseObjectType':'Select a data source type.','DataAccessUIStringId.LoadingDataException':'Data loading failed because the exception occurred.','DataAccessUIStringId.QueryBuilderColumns_Output':'Output','DataAccessUIStringId.ConnectionProperties_ConnectionString':'Connection string:','DataAccessUIStringId.FiltersView':'Filter Editor','DataAccessUIStringId.QueryDesignControlJoinCommandPattern':'Join {0}','DataAccessUIStringId.QueryBuilderButtons_PreviewResults':'Preview Results...','DataAccessUIStringId.ConnectionErrorFormDetailPattern':'Connection name: {0}\\r\\nError message: {1}','DataAccessUIStringId.WizardPageChooseJsonSchema_Type':'Type','DataAccessUIStringId.QueryBuilder_SortAscending':'Sort Ascending','DataAccessUIStringId.ConnectionProperties_Database':'Database:','DataAccessUIStringId.WizardPageChooseXPObjectSourceConnectionType_UseDefaultDataLayer':'Yes, my data connection is available at runtime only.','DataAccessUIStringId.QueryFilter_BindTo':'Bind To','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeType_UnionAll':'Union All','DataAccessUIStringId.MasterDetailEditorMultipleValidationErrorsMessage':'The following errors occurred during query validation:{0}','DataAccessUIStringId.MasterDetailEditorInvalidColumnQueryNameMessage':'Cannot find the specified query: \"{0}\". Specify an existing query name before selecting a column.','DataAccessUIStringId.QueryFilter_AddQueryParameter':'Add Query Parameter','DataAccessUIStringId.WizardPageConfigureEFFilters_EntityColumnName':'Entity Name','DataAccessUIStringId.QueryBuilderColumns_GroupBy':'Group By','DataAccessUIStringId.UpdateSchemaComplete':'The data source schema has been updated successfully.','DataAccessUIStringId.ConnectionProperties_OracleProviderTypeODP':'ODP','DataAccessUIStringId.ExpressionEditor_InvalidProperty':'Invalid property: \\'{0}\\'.','DataAccessUIStringId.WizardDataSourceNameExistsMessage':'<b>A data source with the specified name already exists</b>','DataAccessUIStringId.XPObjectSource_ConfirmClearProperties':'The Properties collection will be cleared. The data source will load complete objects. Do you want to continue?','DataAccessUIStringId.EFFilterControl_AddParameter':'Add Filter Parameter','DataAccessUIStringId.WizardPageSaveConnection_ConfirmSaving':'Yes, save the connection as:','DataAccessUIStringId.WizardPageConfigureMultiQuery':'Create a query or select a stored procedure.\\r\\nData columns selected from specific tables and/or views will be automatically included into a separate query.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_CanonicalizeHostName':'Canonicalize Host Name','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_Principal':'Principal','DataAccessUIStringId.MasterDetailEditorLabelInvalidRelationsText':'{0} invalid relation(s)','DataAccessUIStringId.JoinEditorEmptyColumnText':'<Select a column>','DataAccessUIStringId.Button_ResetSchema':'Reset Schema...','DataAccessUIStringId.WizardPageEFConnectionProperties_CustomConnection':'Specify a custom connection string','DataAccessUIStringId.FederationDataSourceQueryBuilder_RemovedColumnMessage':'The \"{0}.{1}\" column was removed from the \"{2}\" data source. Remove this column from the federated query to proceed.','DataAccessUIStringId.QueryBuilder_AllowEdit':'Allow Edit SQL','DataAccessUIStringId.MessageCannotLoadDatabasesList':'Error has occurred during loading databases list.','DataAccessUIStringId.JsonDataSourceEditorTitle':'JSON Data Source Editor','DataAccessUIStringId.QueryDesignControlDataPreviewCaption_All':'Data Preview','DataAccessUIStringId.QueryBuilder':'Query Builder','DataAccessUIStringId.WizardPageConfigureStoredProcedures':'Add stored procedures to the data source, configure their parameters and preview the result.','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeType_Select':'Join','DataAccessUIStringId.JsonDataSourceDesignerVerbEdit':'Edit...','DataAccessUIStringId.QueryBuilderColumns_Alias':'Alias','DataAccessUIStringId.WizardPageConfigureJsonConnection_BasicHttpAuthText':'Basic HTTP Authentication','DataAccessUIStringId.FederationDataSourceQueryBuilder_SelectResult':'Join result','DataAccessUIStringId.WizardPageConfigureJsonConnection':'Configure web service endpoint request.','DataAccessUIStringId.JoinEditor':'Join Editor','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeType_Transform':'Transform','DataAccessUIStringId.LoadingDataSqlError':'SQL execution error:\\r\\n{0}\\r\\n','DataAccessUIStringId.WizardPageChooseDataSourceName':'Enter the data source name','DataAccessUIStringId.WizardPageChooseJsonSchema_FieldNameIsEmpty':'A field name cannot be empty.','DataAccessUIStringId.WizardPageChooseFileOptions_FirstRowAsFieldNames':'Use values of the first row as field names','DataAccessUIStringId.WizardPageSaveConnection':'Save the connection string.','DataAccessUIStringId.QueryDesignControlNoSelection':'No column has been selected. Please select at least one column to proceed.','DataAccessUIStringId.WizardPageChooseEFConnectionString':'Do you want to select a connection string from the list of available settings?','DataAccessUIStringId.ExcelDataSourceWizard_Title':'Table','DataAccessUIStringId.ConnectionProperties_ClientID':'Client ID:','DataAccessUIStringId.ODSEditorsNoMembersInType':'The {0} data source type does not provide any members suitable for binding.','DataAccessUIStringId.QueryDesignControlAliasAlreadyExists':'The specified alias already exists. Do you want to correct the value?','DataAccessUIStringId.ExpressionEditor_EmptyExpression':'The expression string cannot be empty.','DataAccessUIStringId.WizardTitleODS':'ObjectDataSource Wizard','DataAccessUIStringId.ParametersColumn_Name':'Name','DataAccessUIStringId.ParametersColumn_Type':'Type','DataAccessUIStringId.WizardCannotRetrieveDatabasesMessage':'Cannot retrieve the list of available databases. See the details below.','DataAccessUIStringId.StoredProcControl_Caption':'Select a stored procedure','DataAccessUIStringId.WizardTitleDatasource':'Data Source Wizard','DataAccessUIStringId.ConnectionProperties_ServerType':'Server type:','DataAccessUIStringId.ConnectionProperties_ServerName':'Server name:','DataAccessUIStringId.WizardPageChooseObjectAssembly_ShowOnlyHighlighted':'Show only highlighted assemblies','DataAccessUIStringId.ConnectionProperties_Hostname':'Hostname:','DataAccessUIStringId.ExcelDataSourceWizard_DefinedNameItem':'Defined Name','DataAccessUIStringId.QueryBuilderColumns_Source':'Source','DataAccessUIStringId.SqlDataSourceDesignerVerbEditConnection':'Configure Connection...','DataAccessUIStringId.WizardPageChooseJsonSource_SourceType_File':'JSON File','DataAccessUIStringId.ExcelDataSourceIncorrectFilePathMessage':'Unable to locate file {0}.\\r\\nPlease specify a valid location and press OK to continue.','DataAccessUIStringId.WizardPageConfigureMongoDBQueries':'Configure queries.','DataAccessUIStringId.ConnectionProperties_AdvantageServerTypeRemote':'Remote','DataAccessUIStringId.SqlDataSourceDesignerVerbManageQueries':'Manage Queries...','DataAccessUIStringId.ConnectionProperties_AuthenticationType_BigQueryKeyFile':'Key file','DataAccessUIStringId.QueryBuilderColumnsOf':'Columns of {0}','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_CollectionNameColumnName':'Collection','DataAccessUIStringId.WizardPageChooseObjectType_ShowOnlyHighlighted':'Show only highlighted types','DataAccessUIStringId.QueryBuilder_Delete':'Delete','DataAccessUIStringId.QueryBuilderRelationBetweenTwoColumnsOfTheSameTable':'Cannot create a relation between two columns that belong to the same table {0}.','DataAccessUIStringId.FiltersView_CheckText':'Select only','DataAccessUIStringId.WizardPageConfigureJsonConnection_ParameterNameText':'Parameter Name','DataAccessUIStringId.ExcelDataSourceDesignerVerbEditSchema':'Edit Schema...','DataAccessUIStringId.WizardPageChooseObjectBindingMode_RetrieveDataDescription':'The object data source automatically creates an instance of the specified type by using one of the available constructors. If only one constructor is available, this constructor will be used.','DataAccessUIStringId.ConnectionProperties_SslModeDefault':'Default','DataAccessUIStringId.WizardPageEFConnectionProperties_SaveToConfig':'Save the connection string to config file as:','DataAccessUIStringId.ExcelDataSourceWizard_TableItem':'Table','DataAccessUIStringId.ODSEditorsNoDataSetMessage':'The current operation cannot be accomplished unless the data source has been specified.','DataAccessUIStringId.MessageBoxErrorTitle':'Error','DataAccessUIStringId.QueryBuilderJoinTypeUpdatingConfirmation':'The new join type will be applied to all existing relations between the following two tables: {0}, {1}. Do you wish to continue?','DataAccessUIStringId.ODSEditorsIsPropertyMessage':'The {0} data member is a property. To be able to receive parameters, a data member must be a method.','DataAccessUIStringId.ExcelDataSourceEditorTitle':'Excel Data Source Editor','DataAccessUIStringId.MasterDetailEditorEditQueryRelations':'Edit Relations for the \\'{0}\\' Query','DataAccessUIStringId.MasterDetailEditorInvalidQueryNameMessage':'Cannot find the specified query: \"{0}\". Specify an existing query name.','DataAccessUIStringId.WizardPageChooseObjectConstructor_ShowOnlyHighlighted':'Show only highlighted constructors','DataAccessUIStringId.WizardPageChooseConnection_ChooseExistingConnection':'Yes, let me choose an existing connection from the list','DataAccessUIStringId.WizardPageEFConnectionProperties_DefaultConnection':'Use default connection string','DataAccessUIStringId.ConnectionEditorTitle':'Connection Editor','DataAccessUIStringId.WizardPageChooseFileOptions':'Specify import settings.','DataAccessUIStringId.WizardPageConfigureQuery_Query':'Query','DataAccessUIStringId.QueryBuilder_ReverseRelation':'Reverse Relation','DataAccessUIStringId.ConnectionProperties_AuthenticationType_MSSqlServer':'Server authentication','DataAccessUIStringId.WizardPageConfigureEFFilters_ChooseEntityPlaceholder':'Choose Entity','DataAccessUIStringId.ConnectionProperties_AuthenticationType_BigQueryOAuth':'OAuth','DataAccessUIStringId.LoadingDatasourceOutOfMemoryError':'Not enough memory to load data','DataAccessUIStringId.PasswordRequest':'File load error','DataAccessUIStringId.QueryDesignControlTableNameAlreadyExists':'A table with the specified name already exists. Please specify a different table name.','DataAccessUIStringId.QueryBuilder_DeleteCondition':'Delete Condition','DataAccessUIStringId.WizardConfirmExecutionMessage':'Do you want to execute the query on the server and obtain the resulting query schema?','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_ChooseCollectionPlaceholder':'Choose Collection','DataAccessUIStringId.WizardPageChooseMongoDBSchema_QueryName':'Query name:','DataAccessUIStringId.WizardUnableToLoadMongoDBDriver':'An attempt to load the \"MongoDB.Driver.dll\" assembly failed.\\r\\nThe \"MongoDB.Driver\" package should be installed in your application project to provide MongoDB data at runtime.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_AuthenticationType_None':'None','DataAccessUIStringId.WizardPageChooseFileOptions_ValueSeparator':'Value separator:','DataAccessUIStringId.EFDataMemberEditorTitle':'Entity Framework Data Member Editor','DataAccessUIStringId.Button_QueryBuilder':'Run Query Builder...','DataAccessUIStringId.JoinEditor_JoinType':'Join type:','DataAccessUIStringId.SqlDataSourceDesignerVerbRequestDatabaseSchema':'Request Database Schema','DataAccessUIStringId.SortingTypeAscending':'Ascending','DataAccessUIStringId.WizardDataSourceEmptyNameMessage':'<b>The data source name cannot be empty.</b>','DataAccessUIStringId.ODSConstructorEditorTitle':'Configure Constructor Settings','DataAccessUIStringId.ODSParametersEditorTitle':'Configure Parameters','DataAccessUIStringId.QueryBuilder_EditSql':'Edit SQL','DataAccessUIStringId.MasterDetailEditorColumnsHasDifferentTypesConfirmation':'The \\'{0}\\'.\\'{1}\\' and \\'{3}\\'.\\'{4}\\' columns have different types ({2} and {5}). Do you wish to continue?','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_AuthenticationDatabase':'Authentication Database:','DataAccessUIStringId.FederationDataSourceQueryBuilder_RemovedTableMessage':'The \"{0}\" table was removed from the \"{1}\" data source. Remove this table from the federated query to proceed.','DataAccessUIStringId.WizardPageChooseFile':'Select an Excel workbook or CSV file.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_PasteConnectionString':'Paste a connection string','DataAccessUIStringId.MasterDetailEditorRemoveRelationMessage':'Remove the relation','DataAccessUIStringId.WizardPageChooseObjectBindingMode_RetrieveSchemaDescription':'Only the data source schema is retrieved from the specified object, without feeding the actual data.\\r\\n\\r\\nTo manually retrieve the actual data, create a data source object’s instance in code and assign it to the ObjectDataSource.DataSource property.','DataAccessUIStringId.JoinEditorGreaterOperator':'Is greater than','DataAccessUIStringId.FederationDataSourceQueryBuilder_RemovedDataSourceMessage':'The \"{0}\" data source was removed. Remove the \"{1}\" table from the federated query to proceed.','DataAccessUIStringId.DSTypeSql':'Database','DataAccessUIStringId.DSTypeXpo':'XPO','DataAccessUIStringId.QueryBuilderTable':'Table','DataAccessUIStringId.Button_Apply':'Apply','DataAccessUIStringId.Button_Close':'Close','DataAccessUIStringId.QueryDesignControlExpressionChanged':'This action will reset the SQL expression, and all your changes will be discarded. Do you want to continue?','DataAccessUIStringId.XPObjectSource_DataProvidersListMustBeNonEmpty':'DataProviders list is empty.','DataAccessUIStringId.ConnectionProperties_DatabaseListLoadingError':'Database List Loading Error','DataAccessUIStringId.LoadingDataSourceOpeningConnectionError':'Connection name: {0}\\r\\nError message:\\r\\n{1}\\r\\n','DataAccessUIStringId.WizardPageChooseExcelFileDataRange':'Select the required worksheet, table or defined name referring to the specified range.','DataAccessUIStringId.WizardPageChooseFileOptions_Options':'Options','DataAccessUIStringId.WizardPageChooseJsonSchema_FieldExists':'{0} field name already exists at this level','DataAccessUIStringId.PasswordRequest_Password':'Password:','DataAccessUIStringId.FederationDataSourceQueryBuilder_TransformationResult':'Transformation result','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_DatabaseNameColumnName':'Database','DataAccessUIStringId.CustomAssemblyWarning':'You are about to load a third-party library: \\'{0}\\'.\\r\\n\\r\\nBefore you proceed, please consider resulting security risks and make sure that this library is supplied from a trusted source.','DataAccessUIStringId.ConnectionProperties_SslModeNone':'None','DataAccessUIStringId.FiltersView_GroupFilter':'Group Filter','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_EnterConnectionFields':'Enter connection fields individually','DataAccessUIStringId.MessageLessThanTwoQueries':'At least two queries are required to create a master-detail relation.','DataAccessUIStringId.FederationDataSourceDesignerVerbManageQueries':'Manage Queries...','DataAccessUIStringId.FederationDataSourceDesignerVerbRebuildSchema':'Rebuild Result Schema','DataAccessUIStringId.JsonDataSourceDesignerVerbEditSchema':'Edit Schema...','DataAccessUIStringId.QueryBuilder_Rename':'Rename','DataAccessUIStringId.ConnectionProperties_ServiceAccountEmail':'Service account email:','DataAccessUIStringId.MessageBoxConfirmationTitle':'Confirmation','DataAccessUIStringId.QueryBuilder_SortDescending':'Sort Descending','DataAccessUIStringId.ExpressionEditor_NavigateToErrors':'To view the errors, click the drop-down button in the editor\\'s status bar.','DataAccessUIStringId.MessageBoxCloseQueryBuilderDialogConfirmation':'All your changes will be discarded if you close the Query Builder dialog. Do you want to continue?','DataAccessUIStringId.WizardPageSaveJsonConnection_SkipSaveRequestParameters':'No, skip the request parameters','DataAccessUIStringId.ExcelDataSourceIncorrectFilePathExceptionMessage':'Unable to locate file {0}.','DataAccessUIStringId.WizardPageConfigureJsonConnection_HttpHeadersText':'HTTP Header Parameters','DataAccessUIStringId.FiltersView_Filter':'Filter','DataAccessUIStringId.WizardPageChooseMongoDBSchema_FieldName':'Field Name','DataAccessUIStringId.DSTypeMongoDB':'MongoDB','DataAccessUIStringId.WizardPageChooseFileOptions_Encoding':'Encoding:','DataAccessUIStringId.QueryEditorMessageInvalidQuery':'An error occurred during query validation: {0}\\r\\n\\r\\nTo discard this query and invoke the wizard, click OK.\\r\\n\\r\\nTo keep this query, click Cancel.','DataAccessUIStringId.JoinEditorEmptyTableText':'<Select a table>','DataAccessUIStringId.ConnectionProperties_ServerTypeEmbedded':'Embedded','DataAccessUIStringId.ParametersColumn_Value':'Value','DataAccessUIStringId.WizardPageSaveJsonConnection_SaveRequestParameters':'Yes, save the specified request parameters','DataAccessUIStringId.ExpressionEditorViewTitle':'Expression Editor','DataAccessUIStringId.ParametersColumn_Selected':'Selected','DataAccessUIStringId.UpdateSchemaCaption':'Update schema','DataAccessUIStringId.WizardPageChooseConnectionNoChoice':'Select a data connection.','DataAccessUIStringId.Button_Add':'Add','DataAccessUIStringId.WizardPageConfigureParameters':'Configure query parameters and preview the result.','DataAccessUIStringId.XPObjectSourceDesignerVerbPopulateProperties':'Populate Properties','DataAccessUIStringId.EFDataSourceEditorTitle':'Entity Framework Data Source Editor','DataAccessUIStringId.ConnectionProperties_ClientSecret':'Client Secret:','DataAccessUIStringId.LoadingDataSourceAborted':'Data loading has been aborted.','DataAccessUIStringId.Button_Previous':'Previous','DataAccessUIStringId.FederatedQueryCollectionEditorForm_Title':'Manage Queries','DataAccessUIStringId.WizardPageConfigureJsonConnection_ParameterValueText':'Parameter Value','DataAccessUIStringId.ConnectionProperties_ClientLibrary':'Client library:','DataAccessUIStringId.DSTypeEF':'Entity Framework','DataAccessUIStringId.QueryBuilderButtons_EditParameters':'Edit Parameters...','DataAccessUIStringId.ConnectionProperties_KeyFileName':'Key file name:','DataAccessUIStringId.QueryBuilder_EditRelation':'Edit Relation','DataAccessUIStringId.ConnectionProperties_ServerTypeServer':'Server','DataAccessUIStringId.WizardCannotCreateDataSourceMessage':'Cannot create an empty data source. Please select an object to include.','DataAccessUIStringId.QueryFilter_BoundTo':'Bound to {0}','DataAccessUIStringId.WizardPageChooseFileOptions_DetectAutomatically':'Detect automatically','DataAccessUIStringId.ConnectionProperties_DataSetID':'DataSet ID:','DataAccessUIStringId.SortingTypeNone':'Unsorted','DataAccessUIStringId.ParametersGridForm_Title':'Query Parameters','DataAccessUIStringId.ParametersColumn_Expression':'Expression','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_QueryAlias':'Alias','DataAccessUIStringId.WizardPageChooseJsonSource_SourceType_Uri':'Web Service Endpoint (URI)','DataAccessUIStringId.Button_Next':'Next','DataAccessUIStringId.XPObjectSourceDesignerVerbClearProperties':'Clear Properties','DataAccessUIStringId.ODSEditorsCannotResolveDataMember':'Cannot resolve the specified data member. To specify the data member and its parameters, use the Data Member editor.','DataAccessUIStringId.MasterDetailEditorInvalidRelationNameMessage':'A relation with the specified name already exists.','DataAccessUIStringId.WizardPageChooseJsonSource_ResultingUri':'Resulting URI:','DataAccessUIStringId.QueryBuilderCustomSqlRequiresParameters':'The query contains parameters and cannot be executed before they are declared. \\r\\nPlease go to the next wizard page to declare the required query parameters and preview the results.','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeTypeLabel':'Query Type:','DataAccessUIStringId.ExcelDataSourceDesignerVerbEdit':'Edit...','DataAccessUIStringId.MasterDetailEditorAddConditionMessage':'Create a new condition','DataAccessUIStringId.MasterDetailEditorInvalidColumnNameMessage':'Cannot find the specified column: \"{0}\". Specify an existing column name.','DataAccessUIStringId.QueryBuilderColumns_SortOrder':'Sort Order','DataAccessUIStringId.WizardPageChooseMongoDBSchema_AnalyzeAllDocumentsButton':'Analyze all documents','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_FilterColumnName':'Filter','DataAccessUIStringId.RebuildResultSchemaComplete':'Result schema is rebuilt successfully.','DataAccessUIStringId.RebuildResultSchemaCaption':'Rebuild Result Schema','DataAccessUIStringId.QueryControl_SqlString':'SQL string:','DataAccessUIStringId.WizardPageChooseJsonSource':'Specify JSON data location.','DataAccessUIStringId.WizardPageEFConnectionProperties':'Specify a connection string.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection':'Specify connection properties.','DataAccessUIStringId.WizardPageChooseJsonSchema':'Select data fields.','DataAccessUIStringId.WizardPageChooseMongoDBSchema_Type':'Type','DataAccessUIStringId.SqlDataSourceDesignerVerbManageRelations':'Manage Relations...','DataAccessUIStringId.JoinInformation':'Join Information','DataAccessUIStringId.WizardPageConfigureQuery_StoredProcedure':'Stored Procedure','DataAccessUIStringId.UpdateDBSchemaComplete':'Database schema is updated successfully.','DataAccessUIStringId.WizardPageChooseXPObjectSourceConnectionType_SpecifyConnection':'No, I\\'d like to specify a connection that applies both at design time and runtime.','DataAccessUIStringId.FederationDataSourceDesignerVerbManageRelations':'Manage Relations...','DataAccessUIStringId.WizardPageChooseEFConnectionString_CustomConnection':'No, specify a custom connection string','DataAccessUIStringId.ConnectionProperties_AuthenticationType':'Authentication type:','DataAccessUIStringId.QueryBuilderButtons_Filter':'Filter...','DataAccessUIStringId.WizardPageSaveConnection_SaveCredentials':'Yes, save all required parameters','DataAccessUIStringId.QueryDesignControlDataPreviewCaption':'Data Preview (First 1000 Rows Displayed)','DataAccessUIStringId.EFEditorsNoStoredProcs':'No stored procedures are available in the data context.','DataAccessUIStringId.WizardPageChooseFileOptions_TextQualifier':'Text qualifier:','DataAccessUIStringId.DSTypeObject':'Object','DataAccessUIStringId.PasswordRequest_SavePassword':'Save password','DataAccessUIStringId.WizardPageChooseJsonSource_UriPathParametersText':'URI Path Parameters','DataAccessUIStringId.DSTypeNoData':'No Data','DataAccessUIStringId.ConnectionProperties_UserName':'User name:','DataAccessUIStringId.Button_Remove':'Remove','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_Dsn':'DSN:','DataAccessUIStringId.ODSEditorsNoDataMemberMessage':'Cannot specify parameters unless the DataMember property has been assigned a value.','DataAccessUIStringId.Button_EditRelations':'Manage Relations...','DataAccessUIStringId.WizardPageConfigureQuery':'Create a query or select a stored procedure.','DataAccessUIStringId.EFFilterParametersForm':'Filter Parameters','DataAccessUIStringId.ExpressionEditor_NoSuggestionsMessage':'No suggestions','DataAccessUIStringId.WizardPageChooseJsonSchema_AnalyzeAllRecordsButton':'Analyze all records','DataAccessUIStringId.ExcelDataSourceDesignerVerbUpdateSchema':'Rebuild Result Schema','DataAccessUIStringId.JoinEditorGreaterOrEqualOperator':'Is greater than or equal to','DataAccessUIStringId.WizardDuplicatingColumnNameMessage':'A data schema contains a duplicated column \\'{0}\\'. Modify the query so that all columns have unique names.','DataAccessUIStringId.ConnectionProperties_OracleProviderTypeODPManaged':'ODP Managed','DataAccessUIStringId.WizardEmptyStoredProceduresListMessage':'There are no stored procedures in the current database.','DataAccessUIStringId.SortingTypeDescending':'Descending','DataAccessUIStringId.ParametersColumn_Version':'Version','DataAccessUIStringId.ODSDataSourceEditorTitle':'Configure Data Source','DataAccessUIStringId.WizardPageChooseObjectMember':'Select a data source member (if required).','DataAccessUIStringId.MasterDetailEditorRemoveConditionMessage':'Remove the condition','DataAccessUIStringId.WizardPageChooseJsonSource_Custom':'JSON String:','DataAccessUIStringId.WizardPageChooseMongoDBSchema_FieldDisplayName':'Field Display Name','DataAccessUIStringId.EFConnectionEditorTitle':'Entity Framework Data Connection Editor','DataAccessUIStringId.WizardPageChooseMongoDBSchema_PartiallyAnalyzedCollectionMessage':'The above field types are generated based on the first {0} MongoDB documents.\\r\\n\\r\\nIf your data contains a field whose type inside this limit differs from the type outside of the limit, the corresponding field type is generated incorrectly. This will lead to type deserialization errors.\\r\\n\\r\\nYou can analyze all MongoDB documents to guarantee correct type generation. Note that this might take more time compared to analyzing a limited number of documents.','DataAccessUIStringId.WizardPageSaveConnection_SaveConnectionString':'Do you want to save the connection string to the application\\'s configuration file?','DataAccessUIStringId.QueryFilter_SelectParameterPlaceholder':'Select a parameter...','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_IsSRVRecord':'SRV Record','DataAccessUIStringId.XPObjectSource_ConfirmReplaceProperties':'The Properties collection will be recreated based on the specified entity type information. Do you want to continue?','DataAccessUIStringId.FederationDataSourceQueryBuilder_TransformationNodeRoot':'Transformation node root: {0}','DataAccessUIStringId.QueryDesignControlTableNameEmpty':'The table name cannot be empty.','DataAccessUIStringId.ODSEditorsStaticMemberMessage':'{0} is a static member. Using a constructor to create an instance of the {1} class is not appropriate.','DataAccessUIStringId.FiltersView_SkipTooltip':'This option is only available when the result set is sorted.','DataAccessUIStringId.RebuildResultSchemaConfirmationText':'Do you want to execute the following queries on the server and obtain the resulting schema?','DataAccessUIStringId.WizardPageObjectConstructorParameters':'Specify the constructor parameters.','DataAccessUIStringId.WizardPageConfigureJsonConnection_PasswordText':'Password:','DataAccessUIStringId.SqlQueryCollectionEditorForm_Title':'Manage Queries','DataAccessUIStringId.DataSourceName':'Data source name: {0}','DataAccessUIStringId.WizardPageChooseMongoDBSchema':'Select data fields.','DataAccessUIStringId.MessageBoxCloseManageQueriesDialogConfirmation':'All your changes will be discarded if you close the Manage Queries dialog. Do you want to continue?','DataAccessUIStringId.MessageCannotLoadServersList':'Cannot find any database servers.','DataAccessUIStringId.ConnectionProperties_RefreshToken':'Refresh Token:','DataAccessUIStringId.WizardPageChooseJsonSource_UriQueryParametersText':'Query Parameters','DataAccessUIStringId.JoinEditorLessOrEqualOperator':'Is less than or equal to','DataAccessUIStringId.WizardPageChooseJsonSource_File':'JSON File:','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_AuthenticationType_NamePassword':'Username / Password','DataAccessUIStringId.WizardPageConfigureExcelFileColumns':'Select required columns and specify their settings.','DataAccessUIStringId.QueryBuilderCircularRelationWarning':'The link between {0}.{1} and {2}.{3} results in a circular relation and cannot be added.','DataAccessUIStringId.WizardPageChooseJsonSource_SourceType_Custom':'JSON String','DataAccessUIStringId.ConnectionProperties_AdvantageServerTypeInternet':'Internet','DataAccessUIStringId.WizardPageChooseJsonSource_URI':'Web Service Endpoint (URI):','DataAccessUIStringId.QueryBuilder_AddToSelect':'Add to Query','DataAccessUIStringId.WizardPageConfigureEFFilters_FilterColumnName':'Filter String','DataAccessUIStringId.WizardPageConfigureJsonConnection_HeaderNameText':'Header Name','DataAccessUIStringId.DSTypeJson':'JSON','DataAccessUIStringId.QueryBuilderColumns_TableName':'Table Name','DataAccessUIStringId.WizardPageChooseJsonSchema_FieldDisplayName':'Field Display Name','DataAccessUIStringId.WizardPageConfigureEFFilters':'Add filter criteria to data source tables and/or views.','DataAccessUIStringId.WizardPageChooseJsonSchema_PartiallyAnalyzedJsonMessage':'The above field types are generated based on the first {0} JSON records.\\r\\n\\r\\nIf your data contains a record whose type inside this limit differs from the type outside of the limit, the corresponding field type is generated incorrectly. This will lead to type deserialization errors.\\r\\n\\r\\nYou can analyze all JSON records to guarantee correct type generation. Note that this might take more time compared to analyzing a limited number of documents.','DataAccessUIStringId.WizardPageChooseEFDataMember':'Select a data member','DataAccessUIStringId.ConnectionProperties_ProjectID':'Project ID:','DataAccessUIStringId.JoinEditorFillAllFieldsException':'Some fields are empty. Please fill all empty fields or remove the corresponding conditions to proceed.','DataAccessUIStringId.JoinEditorEqualOperator':'Equals to','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_ChooseDatabasePlaceholder':'Choose Database','DataAccessUIStringId.Button_Browse':'Browse...','DataAccessUIStringId.WizardPageSaveConnection_SkipSaveCredentials':'No, skip credentials for security reasons','DataAccessUIStringId.QueryDesignControlRemoveTables':'The following tables will be removed from the query.\\r\\n\\r\\n{0}\\r\\nDo you want to continue?','DataAccessUIStringId.QueryBuilderColumns_Aggregate':'Aggregate','DataAccessUIStringId.PasswordRequest_FileName':'File name:','DataAccessUIStringId.WizardCannotConnectMessage':'Cannot connect to the database. See the details below.','DataAccessUIStringId.MasterDetailEditorForm_Title':'Master-Detail Relation Editor','DataAccessUIStringId.WizardPageChooseJsonSchema_FieldName':'Field Name','DataAccessUIStringId.WizardPageChooseObjectBindingMode':'Select the data binding mode.','DataAccessUIStringId.ConnectionProperties_AdvantageServerType':'Server type:','DataAccessUIStringId.JoinEditorNotEqualOperator':'Does not equal to','DataAccessUIStringId.WizardDataSourceCreatedMessage':'The data source has been successfully created','DataAccessUIStringId.ChooseEFStoredProceduresDialog':'Select stored procedures to add','DataAccessUIStringId.WizardPageConfigureJsonConnection_UsernameText':'Username:','DevExpress.DataAccess.Sql.ConnectionOptions.CloseConnection':'Close Connection','DevExpress.DataAccess.MongoDB.MongoDBQuery.FilterString':'Filter String','DevExpress.DataAccess.Sql.SqlDataSource.ConnectionParameters':'Connection Parameters','DevExpress.Xpo.XPObjectSource.TopReturnedRecords':'Top Returned 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Name','DevExpress.DataAccess.Sql.SelectQuery.Distinct':'Distinct','DevExpress.Xpo.XPObjectSource.Parameters':'Parameters','DevExpress.DataAccess.MongoDB.MongoDBQuery.Parameters':'Parameters','DevExpress.Xpo.XPObjectSource.GroupFilterString':'Group Filter','DevExpress.DataAccess.Json.UriJsonSource.QueryParameters':'Query Parameters','DevExpress.DataAccess.Sql.ObjectDataSource':'Object Data Source','DevExpress.DataAccess.Json.UriJsonSource':'Uri Json Source','DevExpress.DataAccess.Excel.ExcelDefinedNameSettings.Scope':'Scope','DevExpress.DataAccess.Sql.SelectQuery.FilterString':'Filter String','DevExpress.DataAccess.Excel.CsvSourceOptions.Encoding':'Encoding','DevExpress.DataAccess.Sql.SelectQuery.GroupFilterString':'Group Filter String','DevExpress.DataAccess.Excel.ExcelSourceOptions.ExcelTableSettings':'Excel Table Settings','DevExpress.DataAccess.Sql.SqlQuery.Name':'Name','DevExpress.Xpo.XPObjectSource.Sorting':'Sorting','DevExpress.DataAccess.MongoDB.MongoDBDataSource':'MongoDB Data Source','DevExpress.DataAccess.EntityFramework.EFDataSource.Connection':'Connection','DevExpress.DataAccess.Parameter.Type':'Type','DevExpress.DataAccess.Parameter.Name':'Name','DevExpress.DataAccess.Sql.StoredProcQuery.StoredProcName':'Stored Procedure Name','DevExpress.DataAccess.Excel.CsvSourceOptions.DetectNewlineType':'Detect Newline Type','DevExpress.DataAccess.Sql.ConnectionOptions.DbCommandTimeout':'Command Timeout','DevExpress.DataAccess.Excel.ExcelDataSource.SourceOptions':'Source Options','DevExpress.DataAccess.ObjectBinding.ObjectDataSource.DataMember':'Data Member','DevExpress.DataAccess.Json.CustomJsonSource':'Custom Json Source','DevExpress.DataAccess.Json.JsonDataSource.JsonSource':'Json Source','DevExpress.DataAccess.Excel.ExcelWorksheetSettings.CellRange':'Cell Range','DevExpress.DataAccess.Json.CustomJsonSource.Json':'Json','DevExpress.Xpo.XPObjectSource.Properties':'Properties','DevExpress.DataAccess.Excel.CsvSourceOptions.ValueSeparator':'Value Separator','DevExpress.DataAccess.Parameter.Value':'Value','DevExpress.DataAccess.ObjectBinding.ObjectDataSource.DataSource':'Data Source','DevExpress.DataAccess.Excel.ExcelDataSource.FileName':'File Name','DevExpress.DataAccess.Sql.SelectQuery.Skip':'Skip','DevExpress.DataAccess.Sql.TableQuery.Skip':'Skip','DevExpress.DataAccess.Excel.ExcelSourceOptionsBase.SkipEmptyRows':'Skip Empty Rows','DevExpress.DataAccess.EntityFramework.EFDataSource.StoredProcedures':'Stored Procedures','DevExpress.DataAccess.EntityFramework.DBSetFilter.Parameters':'Parameters','DevExpress.DataAccess.Excel.ExcelDataSource.ExcelSourceOptions':'Excel Source Options','DevExpress.DataAccess.ConnectionParameters.CustomStringConnectionParameters.ConnectionString':'Connection String','DevExpress.Xpo.XPObjectSource.EntityType':'Entity Type','DevExpress.DataAccess.Sql.SelectQuery.Top':'Top','DevExpress.DataAccess.Sql.SqlDataSource.ConnectionName':'Connection Name','DevExpress.DataAccess.Excel.CsvSourceOptions.DetectEncoding':'Detect Encoding','DevExpress.DataAccess.DataFederation.FederationDataSource':'Federation Data Source','DevExpress.DataAccess.Json.UriJsonSource.Uri':'Uri','DevExpress.DataAccess.Sql.TableQuery.FilterString':'Filter String','DevExpress.Xpo.XPObjectSource.FilterString':'Filter','DevExpress.DataAccess.Json.JsonDataSource.ConnectionName':'Connection Name','DevExpress.DataAccess.Excel.ExcelSourceOptionsBase.UseFirstRowAsHeader':'Use First Row As Header','DevExpress.DataAccess.MongoDB.MongoDBDataSourceBase.ConnectionParameters':'Connection Parameters','DevExpress.DataAccess.Excel.CsvSourceOptions.DetectValueSeparator':'Detect Value Separator','DevExpress.DataAccess.EntityFramework.EFConnectionParameters.Source':'Source','DevExpress.Xpo.XPObjectSource.ConnectionString':'Connection String','DevExpress.DataAccess.MongoDB.MongoDBDataSourceBase.Queries':'Queries','DevExpress.DataAccess.Sql.TableQuery.Top':'Top','DevExpress.DataAccess.Sql.SqlDataSource.Queries':'Queries','DevExpress.DataAccess.Excel.ExcelDataSource':'Excel Data Source','DevExpress.DataAccess.Excel.CsvSourceOptions.CellRange':'Cell Range','DevExpress.DataAccess.Excel.ExcelDefinedNameSettings.DefinedName':'Defined Name','DevExpress.DataAccess.Excel.CsvSourceOptions.Culture':'Culture','DevExpress.DataAccess.MongoDB.MongoDBDataSourceBase.Connection':'Connection','DevExpress.DataAccess.Excel.ExcelSourceOptions.SkipHiddenColumns':'Skip Hidden Columns','DevExpress.DataAccess.EntityFramework.EFConnectionParameters.ConnectionString':'Connection String','DevExpress.DataAccess.Json.JsonDataSource':'Json Data Source','DevExpress.DataAccess.Excel.ExcelSourceOptions.ExcelDefinedNameSettings':'Excel Defined Name Settings','DevExpress.DataAccess.ConnectionParameters.DataConnectionParametersBase':'Connection Parameters','DevExpress.DataAccess.EntityFramework.EFDataSource':'EF DataSource','DevExpress.DataAccess.Excel.CsvSourceOptions.TrimBlanks':'Trim Blanks','DevExpress.DataAccess.Excel.ExcelWorksheetSettings.WorksheetIndex':'Worksheet Index','DevExpress.DataAccess.Sql.SqlDataSource':'Sql Data Source','DevExpress.DataAccess.Excel.CsvSourceOptions.TextQualifier':'Text Qualifier','DevExpress.DataAccess.Sql.SqlDataSource.Relations':'Relations','DevExpress.DataAccess.Json.UriJsonSource.AuthenticationInfo':'Authentication Info','DevExpress.DataAccess.MongoDB.MongoDBQuery.CollectionName':'Collection Name','DevExpress.DataAccess.MongoDB.MongoDBQuery.DatabaseName':'Database Name','DevExpress.DataAccess.Excel.ExcelTableSettings.TableName':'Table Name','DevExpress.DataAccess.Sql.SqlDataSource.ConnectionOptions':'Connection Options','DevExpress.Xpo.XPObjectSource.SkipReturnedRecords':'Skip Returned Records','DevExpress.DataAccess.Sql.CustomSqlQuery.Sql':'SQL','DevExpress.Xpo.XPObjectSource.ConnectionStringName':'Connection String Name','DataAccessStringId.WizardNoEFDataContextsMessage':'The selected assembly does not contain Entity Framework data contexts.','DataAccessStringId.ODSWizardErrorExceptionInCtor':'The default constructor of an ITypedList implementation has thrown an exception.','DataAccessStringId.ConfigureMultiQueryPage_ViewCategory':'Views','DataAccessStringId.WizardDataConnectionNameExistsMessage':'A data connection with the specified name already exists. Please specify a different connection name.','DataAccessStringId.TableNullValidationException':'A table cannot be null.','DataAccessStringId.MongoDB_QueryExecutionException':'Query {0} failed to execute.','DataAccessStringId.GroupByWithoutAggregateValidationException':'Grouping requires at least one aggregated column.','DataAccessStringId.ConfigureMultiQueryPage_TableCategory':'Tables','DataAccessStringId.FileNameFilter_CSV':'CSV Files','DataAccessStringId.PropertyGridBehaviorCategoryName':'Behavior','DataAccessStringId.ProviderNotSupportedLabel':'Certain query features are not supported for the current provider.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Constants':'Constants','DataAccessStringId.LoadingDataSourcePanelText':'Loading data source','DataAccessStringId.ExpressionEditor_DocumentationCategory_Columns':'Columns','DataAccessStringId.ExpressionEditor_DocumentationCategory_Functions':'Functions','DataAccessStringId.LoadingPanelText':'Loading...','DataAccessStringId.SkipWithoutSortingWebValidationException':'The Offset setting is set while records are not sorted. Please apply sorting to be able to skip the first N records.','DataAccessStringId.ConnectingToDatabaseCaption':'Please wait','DataAccessStringId.StoredProcedureParameterTypeValidationException':'Parameter \\'{2}\\' type mismatch: <{0}>, <{1}> is expected.','DataAccessStringId.QueryPropertyGridTableSelectionCategoryName':'Table Selection','DataAccessStringId.XPObjectSource_IncorrectXmlRootElement':'The <{0}> XML root element is incorrect. The <{1}> element is expected.','DataAccessStringId.RelationException':'Cannot set relation between columns \\'{0}\\'.\\'{1}\\' of type {2} and \\'{3}\\'.\\'{4}\\' of type {5}.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Operators':'Operators','DataAccessStringId.ExpressionEditor_Caption':'Expression Editor','DataAccessStringId.EmptyColumnAliasPattern':'Column{0}','DataAccessStringId.ExcelWizard_ValueSeparator_Space':'Space','DataAccessStringId.MessageDuplicateItem':'The collection already contains the \\'{0}\\' item','DataAccessStringId.ExcelWizard_ValueSeparator_Comma':'Comma','DataAccessStringId.ObjectDataSourceWizard_CannotGetTypeProperties':'Cannot get properties for this type.','DataAccessStringId.QueriesFailedToExecute_ExceptionMessage':'One or more queries have failed to execute.','DataAccessStringId.Federation_ConditionColumnMissingInTableValidationErrorMessage':'Column [{0}].[{1}] does not exist in table [{0}]. Condition: [{2}].','DataAccessStringId.LoadingDataSourcePanelCounter':'{0} of {1}...','DataAccessStringId.RunExpressionEditor':'Expression Editor...','DataAccessStringId.ConnectionStringPostfixServerExplorer':' (from the Server Explorer)','DataAccessStringId.ExpressionEditor_DocumentationCategory_ColumnDescriptionFormat':'Type: {0}','DataAccessStringId.ExpressionEditor_DocumentationCategory_Columns_Tooltip':'column','DataAccessStringId.UnnamedColumnValidationException':'The column name is not specified.','DataAccessStringId.CustomExpressionWithColumnOfMissingTableValidationException':'There are no tables containing the column [{0}] that is used in the custom expression.','DataAccessStringId.Type_Object':'Object','DataAccessStringId.ExpressionEditor_InvalidColumn':'Invalid column: \\'{0}\\'.','DataAccessStringId.DatabaseConnectionExceptionMessage':'Connection name: {0}\\r\\n Error message:\\r\\n{1}\\r\\n','DataAccessStringId.SortingBySameColumnTwiceValidationException':'The following column is used as a sorting criterion more than once: \"{0}\".\"{1}\".','DataAccessStringId.RelationEditorRelationTypeLeftOuterJoin':'Left outer join','DataAccessStringId.ExpressionEditor_DocumentationCategory_Custom':'Custom','DataAccessStringId.Federation_ConditionColumnNotExistValidationErrorMessage':'Column [{0}] does not exist in data sources. Condition: [{1}].','DataAccessStringId.ExcelWizard_ValueSeparator_Semicolon':'Semicolon','DataAccessStringId.ProviderNotSupportedException':'The following database provider is not supported: {0}.','DataAccessStringId.StoredProcParamNameValidationException':'Parameter name mismatch: <{0}>, <{1}> is expected.','DataAccessStringId.QueryBuilderAliasAlreadyExists':'The specified alias already exists.','DataAccessStringId.MessageWrongCharacterItemName':'Item name \\'{0}\\' contains wrong characters','DataAccessStringId.GroupByAggregateColumnValidationException':'Cannot group by an aggregate column: \"{0}\".\"{1}\".','DataAccessStringId.Type_Char':'Char','DataAccessStringId.Type_Byte':'Non-negative number (8 bit integer)','DataAccessStringId.Type_UInt':'Non-negative number (32 bit integer)','DataAccessStringId.RelationTableNotSelectedValidationException':'The reference table has not been selected: \"{0}\".','DataAccessStringId.SqlStringEmptyValidationException':'The SQL string is null or empty.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Functions_Tooltip':'function','DataAccessStringId.Type_UShort':'Non-negative number (16 bit integer)','DataAccessStringId.RelationNullValidationException':'A relation cannot be null.','DataAccessStringId.DuplicatingColumnNamesValidationException':'A column with the following name already exists: \"{0}\".\"{1}\".','DataAccessStringId.Wizard_NoDataSourcesForDataFederationMessage':'Provide at least one data source to be used to create a federated data source.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Parameters':'Parameters','DataAccessStringId.ExpressionEditor_FunctionCategory_Logical':'Logical','DataAccessStringId.Type_ByteArray':'Byte array','DataAccessStringId.FilterByAmbiguousColumnValidationException':'The column name [{0}] that is used in the filter string is not unique. Columns with this name exist in the following tables: {1}.','DataAccessStringId.InvalidPortErrorMessage':'Invalid port number. A port number should be between 0 and 65535 inclusive.','DataAccessStringId.ExpressionEditor_InvalidExpression':'Invalid expression.','DataAccessStringId.MongoDB_InvalidDatabaseName':'Invalid database name: \\'{0}\\'.','DataAccessStringId.DefaultNameParameter':'Parameter','DataAccessStringId.RebuildResultSchemaWaitFormText':'Rebuilding the Result Schema...','DataAccessStringId.QueryPropertyGridCommonCategoryName':'Common','DataAccessStringId.QueryBuilderJoinEditorMissingData':'Not all parts of the expression are specified.','DataAccessStringId.ConnectionPropertiesPage_ProviderNotSupported':'Connection parameters were discarded because the {0} provider is not supported. \\r\\nSelect one of the available data providers and specify connection parameters or close the wizard \\r\\nusing the Close button to undo this change.','DataAccessStringId.ExcelEncryptedFileException_EncryptionTypeNotSupported':'The protected file cannot be opened.','DataAccessStringId.NoTablesValidationException':'The collection of tables cannot be empty.','DataAccessStringId.WizardPageChooseJsonSchema_EmptySelection':'Select at least one data field.','DataAccessStringId.SchemaDiscoveryMaxItemCountExceptionMessage':'The value should be greater than or equal to zero.','DataAccessStringId.Federation_NodeIsNotUniqueValidationErrorMessage':'Nodes does not allow duplicates: {0}.','DataAccessStringId.WizardPageChooseMongoDBSchema_EmptySelection':'Select at least one data field for the following queries: {0}.','DataAccessStringId.Federation_EmptySourceNameErrorMessage':'The source name cannot be empty.','DataAccessStringId.GroupFilterStringEditorNoGroups':'Group filtering cannot be applied to data that is not grouped. Please apply data grouping first.','DataAccessStringId.ConfigureMultiQueryPage_QueryCategory':'Queries','DataAccessStringId.ConfigureMultiQueryPage_SpCategory':'Stored Procedures','DataAccessStringId.SkipWithoutSortingValidationException':'The SKIP setting is set while records are not sorted. Please apply sorting to be able to skip the first N records or reset the SKIP setting in the Filter Editor dialog.','DataAccessStringId.ConnectionAborted_ExceptionMessage':'The connection has been canceled.','DataAccessStringId.WizardCustomConnectionString':'Custom connection string','DataAccessStringId.CustomExpressionWithMissingInSchemaColumnValidationException':'Column [{0}].[{1}] is used in the custom expression, but it is missing in DBSchema.','DataAccessStringId.QueryPropertyGridStoredProcCategoryName':'Stored Procedure','DataAccessStringId.ProviderNotSupportedFeatureExceptionHeader':'The following query features are not supported for the current provider:','DataAccessStringId.XmlProviderNotSupportedLabel':'Certain query features are not supported for XML files.','DataAccessStringId.CustomExpressionWithAmbiguousColumnValidationException':'The column name [{0}] that is used in the custom expression is not unique. Columns with this name exist in the following tables: {1}.','DataAccessStringId.MessageCannotRebuildSchema':'An error occurred while rebuilding a data source schema.','DataAccessStringId.StoredProcNameNullValidationException':'The name of a stored procedure cannot be null.','DataAccessStringId.ExpressionNullValidationException':'An expression cannot be null, either column or custom expression expected.','DataAccessStringId.QueryBuilderNoRules':'No rule has been added. Please add at least one rule to proceed.','DataAccessStringId.XPObjectSource_PropertiesCollectionDoesNotContainFetch':'The Properties collection does not contain any item with the enabled Fetch option.','DataAccessStringId.FilterByMissingInSchemaColumnValidationException':'Column [{0}].[{1}] is used in the filter string, but it is missing in DBSchema.','DataAccessStringId.RelationEditorRelationTypeInnerJoin':'Inner join','DataAccessStringId.Federation_FilterColumnMissingInTableValidationErrorMessage':'Column [{0}].[{1}] does not exist in table [{0}]. Filter string: [{2}].','DataAccessStringId.ExcelDataSource_SchemaLoadingText':'Schema loading...','DataAccessStringId.IncompleteRelationValidationException':'The specified relation is incomplete: \"{0}\".','DataAccessStringId.Federation_ColumnTableNotExistValidationErrorMessage':'Column [{0}].[{1}] does not exist in data sources.','DataAccessStringId.ManageQueries_QueryIsNotValid':'The \\'{0}\\' query is invalid. {1}','DataAccessStringId.Federation_UnionWithDifferentColumnTypesErrorMessage':'Union node {0}: related columns must have similar  types: {1}.{2}, {3}.{4}.','DataAccessStringId.Type_SByte':'Number (8 bit integer)','DataAccessStringId.ExcelEncryptedFileException_WrongPassword':'The password is not correct. Please try again.','DataAccessStringId.Type_ULong':'Non-negative number (64 bit integer)','DataAccessStringId.RelationEditorRelationTypeMasterDetail':'Master-detail relation','DataAccessStringId.ResultRelation_ColumnNotFoundError':'Column not found: \\'{0}\\'.\\'{1}\\'.','DataAccessStringId.Federation_ExpressionColumnNotExistValidationErrorMessage':'Column [{0}] does not exist in data sources. Expression: [{1}].','DataAccessStringId.MessageDuplicateQueryName':'A query with the specified name already exists: {0}.','DataAccessStringId.ConnectionStringPostfixAppConfig':' (in the config file)','DataAccessStringId.XPObjectSource_ConnectionStringIsEmpty':'Connection string is empty. To specify the connection, do one of the following: specify the ConnectionString property value; add the connection string to the application configuration file and specify the ConnectionStringName property value; handle the ResolveSession event; setup the default DataLayer.','DataAccessStringId.Federation_TransformationDuplicatedColumnNamesValidationErrorMessage':'The {0} node contains columns with duplicated names: {1}.','DataAccessStringId.MessageEmptyQueryName':'The query name cannot be empty.','DataAccessStringId.ObjectDataSourceWizard_CannotGetPropertiesForThisMethodReturnType':'Cannot get properties for the type returned by this method.','DataAccessStringId.GroupNullValidationException':'A grouping criteria cannot be null.','DataAccessStringId.MessageCannotLoadCustomAssembly':'Unable to load the {0} assembly for the {1} context. Please choose an existing external assembly and/or existing context.','DataAccessStringId.IntegerDivisionValidationMessage':'Please Note:  This Expression engine discards fractions during integer division operations. To return decimal values (floating-point division), use ToDecimal(), ToDouble() or ToFloat() for your expression. For instance, ToDecimal(10)/4 will return 2.5 whereas 10/4 will return 2.','DataAccessStringId.WizardPageChooseJsonSource_DataLocationMismatch':'The specified JSON data location does not correspond to the chosen JSON source.','DataAccessStringId.UnknownType':'Unknown','DataAccessStringId.ConfigureQueryPage_CustomSqlWillBeLost':'Manual editing of custom SQL is not allowed. The current query is represented by a custom SQL query string, \\r\\nwhich will be lost if you proceed with editing the query using the Query Builder dialog. \\r\\n\\r\\nDo you want to discard the custom SQL and proceed with the Query Builder?','DataAccessStringId.NoRelationColumnsValidationException':'Columns are not specified for the relation: \"{0}\".','DataAccessStringId.ExpressionEditor_NotSupportedAggregateFunction':'The following aggregate function is not supported: \\'{0}\\'.','DataAccessStringId.QueryBuilderNoTablesAndViews':'A database does not contain tables or views and does not support SQL editing. To be able to run the Query Builder, make sure that your database contains at least one table or supports SQL editing.','DataAccessStringId.HavingWithoutGroupByValidationException':'Group filtering criteria are defined while data is not grouped. Please apply data grouping or remove group filtering criteria on the Group Filter tab of the Filter Editor dialog.','DataAccessStringId.ParameterlessConstructor':'default','DataAccessStringId.RelationEditorRelationTypeFullOuterJoin':'Full outer join','DataAccessStringId.Federation_ColumnNotExistInTableValidationErrorMessage':'Table [{0}] does not contain the column [{1}].','DataAccessStringId.SortingNullValidationException':'A sorting criteria cannot be null.','DataAccessStringId.TableNotInSchemaValidationException':'The schema does not contain the specified table: \"{0}\".','DataAccessStringId.FilterByColumnOfMissingTableValidationException':'There are no tables containing the column [{0}] that is used in the filter string.','DataAccessStringId.InvalidExpressionStringValidationException':'Cannot parse the following expression string: \"{0}\".','DataAccessStringId.PartialAggregationValidationException':'Certain columns on the select list are invalid because they are not contained in either an aggregate function or in the Group By clause. Apply aggregation/grouping either to all columns or to none of them.','DataAccessStringId.ParameterListEmpty':'none','DataAccessStringId.SortByAggregateColumnValidationException':'Cannot sort by an aggregate column: {0}({1}), because the query is not aggregated.','DataAccessStringId.Federation_NodeWithoutExpressionValidationErrorMessage':'Node without expression: {0}.','DataAccessStringId.QueryBuilder_AllTables':'(All Tables)','DataAccessStringId.ExpressionEditor_InvalidCustomFunction':'Invalid function: \\'{0}\\'.','DataAccessStringId.QueryDesignerJoinExpressionPattern':'{0} on {1}','DataAccessStringId.NegativeTopSkipValidationException':'Top and Skip properties should be non-negative integer.','DataAccessStringId.ExcelDataSource_FileNotFoundMessage':'{0}\\r\\nFile not found.\\r\\nCheck the file name and try again.','DataAccessStringId.Federation_FilterAmbiguousColumnNameValidationErrorMessage':'Column name [{0}] is not unique. The same column name exists in the tables: {1}. Filter string: [{2}].','DataAccessStringId.StoredProcParamCountValidationException':'Parameter count mismatch: <{0}>, <{1}> is expected.','DataAccessStringId.ParameterListNull':'null','DataAccessStringId.XmlProviderNotSupportedFeatureException':'The XML data provider cannot perform actions that require SQL queries. \\r\\nThe following SelectQuery properties and methods are not supported: SelectExpression, SelectAll, SelectRecordsCount, Distinct. \\r\\nDo not use them in the query, or convert the XML data to another data format and use an appropriate data source.','DataAccessStringId.FileNameFilter_Excel':'Excel Workbooks','DataAccessStringId.ODSWizardErrorNoDefaultCtor':'Cannot get item properties from IListSource without default constructor.','DataAccessStringId.PositiveIntegerError':'Only non-negative numeric values are allowed.','DataAccessStringId.ExpressionEditor_FunctionCategory_Aggregate':'Aggregate','DataAccessStringId.Federation_UnionWithDifferentNumberOfColumnsErrorMessage':'Union node {0}: elements must have the same number of columns: {1}, {2}.','DataAccessStringId.MessageCannotCreateSelectStatement':'Select statement creation failed.','DataAccessStringId.CustomSqlQueryValidationException':'A custom SQL query should contain only SELECT statements.','DataAccessStringId.MongoDB_NoQueriesMessage':'No queries.','DataAccessStringId.GatheringTypesPanelText':'Gathering types information...','DataAccessStringId.UnnamedTableValidationException':'The table name is not specified.','DataAccessStringId.WizardEmptyConnectionNameMessage':'The name cannot be null, empty or contain only whitespaces.','DataAccessStringId.ColumnNotInSchemaValidationException':'The schema does not contain the following column: \"{0}\".\"{1}\".','DataAccessStringId.StoredProcParamTypeValidationException':'Parameter type mismatch: <{0}>, <{1}> is expected.','DataAccessStringId.QueriesFailedToValidate_ExceptionMessage':'One or more queries have failed to validate.','DataAccessStringId.ExcelInvalidFileException_WrongFormat':'Incorrect file format','DataAccessStringId.LoadingDataPanelText':'Loading Data...','DataAccessStringId.QueryBuilderCanJoin':'Can join {0}','DataAccessStringId.Federation_ExpressionColumnMissingInTableValidationErrorMessage':'Column [{0}].[{1}] does not exist in table [{0}]. Expression: [{2}].','DataAccessStringId.MessageNonexistentQuery':'Query \\'{0}\\' does not exist.','DataAccessStringId.QueryPropertyGridCustomSqlCategoryName':'Custom SQL','DataAccessStringId.QueryBuilderNothingSelected':'No column has been selected. Please select at least one column to proceed.','DataAccessStringId.Federation_UnionWithNoElementsValidationErrorMessage':'Union node contains no elements: {0}.','DataAccessStringId.MessageWrongCharacterParameterName':'Parameter name \\'{0}\\' contains wrong characters','DataAccessStringId.MessageCannotOpenDatabase':'Unable to open a database.','DataAccessStringId.MessageDuplicateItemName':'This collection already contains an item with the \\'{0}\\' name','DataAccessStringId.DatabaseConnectionExceptionStringId':'Failed to connect to the database. To learn more, see the exception details. \\r\\n\\r\\nException details:\\r\\n {0}','DataAccessStringId.MessageNullItem':'Cannot add a null value to the collection','DataAccessStringId.QueryBuilder_RowCount':'(Row Count)','DataAccessStringId.ConfigureMultiQueryPage_ValidateRelationError':'One or more relations are invalid. \\r\\nTo learn about the error details, click Manage Relations.','DataAccessStringId.Federation_NestedFederatedDataSourceErrorMessage':'Federated data source cannot be used as a data source for another federated data source.','DataAccessStringId.Federation_ConditionAmbiguousColumnNameValidationErrorMessage':'Column name [{0}] is not unique. The same column name exists in the tables: {1}. Condition: [{2}].','DataAccessStringId.ExcelDataSource_WorksheetNotFoundMessage':'{0}\\r\\nWorksheet not found.\\r\\nCheck the worksheet name and try again.','DataAccessStringId.ProviderNotSupportedFeatureParametersInSelect':'parameters in column expressions','DataAccessStringId.MessageNonexistentColumn':'Column \\'{0}\\'.\\'{1}\\' does not exist.','DataAccessStringId.QueryBuilderJoinedOn':'Joined on {0}','DataAccessStringId.FilterByMissingParameterValidationException':'Parameter [{0}] is used in the filter string, but is missing in the query.','DataAccessStringId.Federation_ExpressionNodeNullValidationErrorMessage':'Node contains an expression that is not linked to a node: {0}.','DataAccessStringId.DefaultNameDataSource':'Data Source','DataAccessStringId.CustomExpressionWithMissingParameterValidationException':'Parameter [{0}] is used in the custom expression, but is missing in the query.','DataAccessStringId.XPObjectSource_InvalidEntityTypeString':'\\'{0}\\' is an invalid entity type string. Assign the comma-separated full type name and assembly name to the EntityTypeString property.','DataAccessStringId.FilterEditor_TreeCreationError':'Cannot create a tree for this expression','DataAccessStringId.StoredProcParamNullValidationException':'A parameter cannot be null.','DataAccessStringId.DuplicatingTableNamesValidationException':'A table with the following name already exists: \"{0}\".','DataAccessStringId.SqlQueryExecutionException':'Query {0} failed to execute.','DataAccessStringId.ConnectingToDatabaseMessage':'Connecting to the database...','DataAccessStringId.ExpressionEditor_DocumentationCategory_Parameters_Tooltip':'parameter','DataAccessStringId.PropertyGridDesignCategoryName':'Design','DataAccessStringId.ExcelEncryptedFileException_PasswordRequired':'A password is required to open this workbook.','DataAccessStringId.QueryBuilder_AllColumns':'* (All Columns)','DataAccessStringId.Federation_FilterColumnNotExistValidationErrorMessage':'Column [{0}] does not exist in data sources. Filter string: [{1}].','DataAccessStringId.ExpressionEditor_EmptyExpression':'The expression string cannot be empty.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Constants_Tooltip':'constant','DataAccessStringId.NoColumnsValidationException':'None of the tables contain any columns.','DataAccessStringId.WizardAssemblyLoadingDisallowed':'Cannot load this assembly for security reasons.','DataAccessStringId.ConnectionNotSpecified_ExceptionMessage':'No connection has been specified.','DataAccessStringId.ExcelDataSource_WorksheetIndexNotFoundMessage':'Worksheet {0} not found.\\r\\nCheck the worksheet index and try again.','DataAccessStringId.TablesNotRelatedValidationException':'The following tables have no relations: \"{0}\".','DataAccessStringId.DataSourceFillExceptionMessage':'Failed to load data. Refer to the exception details for more information. \\r\\n\\r\\nException details:\\r\\n {0}','DataAccessStringId.XmlFileStrategy_FileNameFilter':'XML Files','DataAccessStringId.SqlExecutionException':'Error trying to execute an SQL query{0}{1}.{2}Error: {3}','DataAccessStringId.RelationColumnNotInSchemaValidationException':'The schema does not contain the following relation column: \"{0}\".\"{1}\".','DataAccessStringId.XPObjectSource_PropertyCannotBeFetched':'The \\'{1}\\' type of the \\'{0}\\' property is not supported when the Properties collection is specified explicitly.','DataAccessStringId.ODSErrorMissingMember':'A data member \\'{0}\\' does not exist.','DataAccessStringId.MessageInvalidItemName':'Item name cannot be null or an empty string','DataAccessStringId.EFFilterControl_EmptyFilterString':'A filter string cannot be null.','DataAccessStringId.Federation_RootNullValidationErrorMessage':'Root reference is not initialized: {0}.','DataAccessStringId.ObjectDataSourceLoadingWarningMessage':'Loading the data sources referenced in this file may harm your computer. Was this file obtained from a trusted source?\\r\\n\\r\\nClick \\'Yes\\' to load the data source content as is.\\r\\nClick \\'No\\' to load only trusted data source content.','DataAccessStringId.Federation_DuplicatedExpressionNamesValidationErrorMessage':'Node {0} contains expressions with duplicated actual names: {1}.','DataAccessStringId.QueryDesignerJoinExpressionElementSeparator':', ','DataAccessStringId.QueryDesignerJoinTooltipPattern':'[{0}] {1} join [{2}] on {3}','DataAccessStringId.RelationColumnNullValidationException':'The relation column cannot be null.','DataAccessStringId.MongoDB_InvalidCollectionName':'Invalid collection name: \\'{0}\\'.','DataAccessStringId.OdbcDriverDoesNotSupportOAuthErrorMessage':'The ODBC driver does not support the OAuth authentication type. Use the Key file authentication or Install the DevExpress BigQueryProvider to use OAuth.','DataAccessStringId.QueryBuilderNoTablesSelected':'No table has been selected. Please select at least one table to proceed.','DataAccessStringId.StoredProcNotInSchemaValidationException':'Cannot find the specified stored procedure: \"{0}\".','DataAccessStringId.ExpressionEditor_FunctionCategory_Math':'Math','DataAccessStringId.ExpressionEditor_FunctionCategory_Text':'String','DataAccessStringId.PropertyGridDataCategoryName':'Data','DataAccessStringId.PropertyGridConnectionCategoryName':'Connection','DataAccessStringId.Federation_ExpressionAmbiguousColumnNameValidationErrorMessage':'Column name [{0}] is not unique. The same column name exists in the tables: {1}. Expression: [{2}].','DataAccessStringId.ExcelInvalidFileException_CorruptedFile':'The file is corrupt.','DataAccessStringId.FileNameFilter_AllFormats':'All Supported Formats','DataAccessStringId.SqlExecutionException_WithParameters':' with parameters:{0}{1}','DataAccessStringId.ExpressionEditor_DocumentationCategory_Operators_Tooltip':'operator','DataAccessStringId.WizardPageChooseJsonSource_UnknownFormat':'Unable to load data because the format of the specified URI cannot be determined.','DataAccessStringId.CircularRelationsValidationException':'Circular relations have been detected.','DataAccessStringId.MongoDB_DuplicateQueryNameMessage':'A query with the specified name already exists: {0}.','DataAccessStringId.ExcelInvalidFileException_BIFF5Format':'BIFF5 (Excel 5.0/95) XLS file format is not supported.','DataAccessStringId.ExpressionStringNullValidationException':'An expression string cannot be null','DataAccessStringId.QueryBuilderInvalidFilter':'Please click the \\'Filter...\\' button to correct the filter string.','DataAccessStringId.Federation_TransformationNodeWithoutRuleValidationErrorMessage':'Transformation node without rule: {0}.','DataAccessStringId.AggregateQueryInvalidSortingValidationException':'Invalid sorting column \"{0}\".\"{1}\". Results of a TableQuery containing aggregate functions can only be sorted by columns used as grouping criteria.','DataAccessStringId.Federation_SourceNullValidationErrorMessage':'Source reference is not initialized: {0}.','DataAccessStringId.ManageQueries_QueryIsNotValid_Postfix':'Fix the error or remove the query to proceed.','DataAccessStringId.ODSWizardErrorStaticValue':'The type is static and it does not have any members returning IEnumerable.','DataAccessStringId.RelationEditorRelationTypeRightOuterJoin':'Right outer join','DataAccessStringId.TableNotSelectedValidationException':'The following table is not in tables list, but its column is used: \"{0}\".','DataAccessStringId.ODSWizardErrorExceptionInGetItemProperties':'The GetItemProperties method of an ITypedList has thrown an exception.','DataAccessStringId.ExcelWizard_ValueSeparator_Tab':'Tab','DataAccessStringId.Federation_DuplicateSourceNameErrorMessage':'A source with the specified name already exists: {0}.','DataAccessStringId.ColumnNullValidationException':'A column cannot be null.','DataAccessStringId.XPObjectSource_ConnectionStringMissing':'The \\'{0}\\' connection string is missing in the application configuration file.','DataAccessStringId.Type_TimeSpan':'Time interval','DataAccessStringId.ExpressionEditor_InvalidParameter':'Invalid parameter: \\'{0}\\'.','DataAccessStringId.Federation_NodeExpressionNameNullValidationErrorMessage':'Node contains an unnamed expression: {0}.','DataAccessStringId.AggregationWithoutAliasValidationException':'An aggregate column should have an alias.','DataAccessStringId.ExpressionEditor_FunctionCategory_DateTime':'DateTime','DataAccessStringId.NoXpoProviderStringId':'The connection string contains no XpoProvider key or the specified key is invalid. \\r\\n\\r\\nException details:\\r\\n {0}','DataAccessStringId.SkipWithoutSortingPropertyGridError':'The SKIP setting is set while records are not sorted. Please apply sorting to be able to skip the first N records.','DashboardStringId.CalculatedFieldTypeBoolean':'Boolean','DashboardStringId.TextGroupIntervalAlphabetical':'Alphabetical','DashboardStringId.FormatConditionAppearanceFontRed':'Red Font','DashboardStringId.FormatRuleApplyToReadOnlyDescription':'The selected style applies to all layout elements','DashboardStringId.StartDate':'(Start Date)','DashboardStringId.DefaultNameTreemapItem':'Treemap','DashboardStringId.DateTimeFormatYearFormatDefaultCaption':'Default','DashboardStringId.DeltaValueTypeActualValueCaption':'Actual value','DashboardStringId.DataSourceFederationQuery':'Query','DashboardStringId.NumericFormatFormatTypeAutoCaption':'Auto','DashboardStringId.MessageWrongExtractDataSourceConnectionParametersType':'Connection parameters are invalid. An extract data source supports only ExtractDataSourceConnectionParameters.','DashboardStringId.ParameterFalseExportValue':'False','DashboardStringId.FunctionDescriptionWindowMedian':'WindowMedian(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the median of the expression within the window.','DashboardStringId.SparklineArgumentValueSeparator':' - ','DashboardStringId.NumericFormatFormatTypeCustomCaption':'Custom','DashboardStringId.PieCalculationAlongSeries':'Series','DashboardStringId.SparklineTooltipMaxValue':'Max:','DashboardStringId.FunctionDescriptionWindowDefinitionOrderAsc':'asc(column)\\r\\nData rows are sorted by values in the specified column in ascending order. This is the default sort order.','DashboardStringId.ActionRestoreDashboardItem':'Restore','DashboardStringId.DashboardErrorValue':'Error','DashboardStringId.GridCalculationAlongRowsAndSparklineArgument':'Rows / Sparkline Argument','DashboardStringId.MessageDashboardNotFoundError':'Dashboard has not been found.','DashboardStringId.CommandFormatRuleBarRangeColors':'Bar Color Ranges','DashboardStringId.DateTimeFormatDateTimeFormatLongCaption':'Long','DashboardStringId.RangeFilterCustomDateTimePeriod':'Custom Period...','DashboardStringId.FormatConditionAppearanceGradientOrange':'Gradient Orange','DashboardStringId.DescriptionColumns':'Columns','DashboardStringId.DateTimeFormatDateTimeFormatDefaultCaption':'Default','DashboardStringId.DateTimeIntervalMinute':'Minute','DashboardStringId.PaperKindLetter':'Letter','DashboardStringId.PeriodThisDay':'This Day','DashboardStringId.InitialExtent':'Initial Extent','DashboardStringId.MessageDashboardNotRelevantError':'Dashboard object model was changed. Refresh operation is required.','DashboardStringId.ActionExportToExcel':'Export To Excel','DashboardStringId.DateTimeFormatMonthFormatDefaultCaption':'Default','DashboardStringId.ActionAllowMultiselection':'Multi-Select','DashboardStringId.PageLayout':'Page Layout','DashboardStringId.DashboardNullValue':' ','DashboardStringId.ExtractColumnUnsupportedTypeError':'The following columns have unsupported types: \\r\\n{0}','DashboardStringId.ActionExportToImage':'Export To Image','DashboardStringId.ScaleFactor':'Scale Factor','DashboardStringId.FormatConditionAppearanceGradientPurple':'Gradient Purple','DashboardStringId.FormatMasterFilterDisplayText':', {0}','DashboardStringId.RangeFilterIncompatibleDateTimeGroupInterval':'Date-time argument values should identify actual calendar dates or time spans rather than grouping (i.e., they should contain a year part). Change the group interval accordingly','DashboardStringId.DateTimeGroupIntervalQuarterYear':'Quarter-Year','DashboardStringId.SeriesTypeArea':'Area','DashboardStringId.SeriesTypeLine':'Line','DashboardStringId.PieCalculationAlongArguments':'Arguments','DashboardStringId.DefaultFederationDataSourceName':'Federated Data Source','DashboardStringId.CustomExpressionCalculationMeasureCaption':'Calculation','DashboardStringId.MessageDuplicateDataItemId':'A data item identifier with the same name already exists.','DashboardStringId.NumericFormatFormatTypePercentCaption':'Percent','DashboardStringId.RedoText':'Redo','DashboardStringId.RankOrderAscending':'Ascending','DashboardStringId.ParametersSelectorText':'Select...','DashboardStringId.CardRowDataElementTypeDimensionValueCaption':'Dimension','DashboardStringId.CommandFormatRuleContains':'Text that Contains','DashboardStringId.CardRowDataElementTypeSparklineCaption':'Sparkline','DashboardStringId.DefaultNameTabContainerItem':'Tab Container','DashboardStringId.PivotCalculationAlongColumns':'Columns','DashboardStringId.DescriptionArgument':'Argument','DashboardStringId.PeriodThisMonth':'This Month','DashboardStringId.MessageInvalidDataFormat':'Cannot convert the {0} value to the {1} data type.','DashboardStringId.DataSourceQuery':'Query','DashboardStringId.FromDatePeriodCaption':'From {0}','DashboardStringId.DescriptionMapValues':'Map / Values','DashboardStringId.DateTimeGroupIntervalDayOfWeek':'Day of Week','DashboardStringId.DateTimeGroupIntervalDayOfYear':'Day of Year','DashboardStringId.MessageIncorrectLayoutItemWeight':'Layout item weight cannot be negative or equal to zero','DashboardStringId.DataEngineGrandTotal':'Grand Total','DashboardStringId.DefaultNameGaugeItem':'Gauges','DashboardStringId.PeriodNextYear':'Next Year','DashboardStringId.PeriodNextHour':'Next Hour','DashboardStringId.FunctionDescriptionGetDateWeekYear2':'GetDateWeekYear(DateTime, [\\'FirstDay\\', \\'FirstFullWeek\\', \\'FirstFourDayWeek\\'])\\r\\nReturns the date of the first day of the week for a given DateTime. The second parameter determines the rule for calculating the calendar week.','DashboardStringId.DescriptionItemDimension':'Dimension','DashboardStringId.CommandFormatRuleNotBetweenOrEqual':'Not Between Or Equal To','DashboardStringId.CardLayoutTemplateCompactCaption':'Compact','DashboardStringId.DisplayValueCaption':'Display Value','DashboardStringId.DateTimeQuarterFormatSpecifier':'QQ','DashboardStringId.IntegerDivisionValidationMessage':'Please Note:  This Expression engine discards fractions during integer division operations. To return decimal values (floating-point division), use ToDecimal(), ToDouble() or ToFloat() for your expression. For instance, ToDecimal(10)/4 will return 2.5 whereas 10/4 will return 2.','DashboardStringId.FormatConditionAppearanceFontStrikeout':'Strikeout','DashboardStringId.FormatRuleUnableToAddRule_NoItemsToCalculate':'Unable to add a new format rule. There is no data item to calculate the rule.','DashboardStringId.ChoroplethMapUseBindingAttribute':'Use binding attribute','DashboardStringId.FunctionDescriptionStdDev':'StdDev(Value)\\r\\nReturns an estimate of the standard deviation of a population, where the sample is a subset of the entire population.','DashboardStringId.CommandFormatRuleGradientRangeBar':'Bar Gradient Ranges','DashboardStringId.RangeFilterOLAPDataSource':'The Range Filter is not supported in OLAP mode.','DashboardStringId.IntersectionLevelModeFirst':'First level','DashboardStringId.MessageIncorrectNumericPrecision':'The numeric value precision cannot be negative.','DashboardStringId.ActualValueCaption':'Actual','DashboardStringId.CommandFormatRuleExpression':'Expression','DashboardStringId.ActionPrintPreview':'Print Preview...','DashboardStringId.DescriptionItemColumn':'Column','DashboardStringId.FunctionDescriptionRunningCount':'RunningCount(SummaryExpression)\\r\\nReturns the running count of the specified expression from the first row in the window to the current row.','DashboardStringId.CalculatedFieldTypeLong':'Integer','DashboardStringId.CalculatedFieldTypeAuto':'Auto','DashboardStringId.NumericFormatFormatTypeGeneralCaption':'General','DashboardStringId.DefaultFileExtractDataSourceName':'Extract Data Source','DashboardStringId.HiddenDataItemsHeader':'HIDDEN DATA ITEMS','DashboardStringId.ElementNameGauges':'Gauges','DashboardStringId.OpenCaption':'Open','DashboardStringId.FunctionOperatorExFunctionDescriptionMakeDateTime6':'MakeDateTime(Year, Month, Day, Hour, Minute, Second)\\r\\nReturns a date value constructed from the specified Year, Month, Day, Hour, Minute and Second.','DashboardStringId.FunctionOperatorExFunctionDescriptionMakeDateTime5':'MakeDateTime(Year, Month, Day, Hour, Minute)\\r\\nReturns a date value constructed from the specified Year, Month, Day, Hour and Minute.','DashboardStringId.FunctionOperatorExFunctionDescriptionMakeDateTime4':'MakeDateTime(Year, Month, Day, Hour)\\r\\nReturns a date value constructed from the specified Year, Month, Day and Hour.','DashboardStringId.FunctionOperatorExFunctionDescriptionMakeDateTime3':'MakeDateTime(Year, Month, Day)\\r\\nReturns a date value constructed from the specified Year, Month and Day.','DashboardStringId.Resolution':'Resolution (dpi)','DashboardStringId.CalculationTypeNone':'None','DashboardStringId.CalculationTypeRank':'Rank','DashboardStringId.SeriesTypeCandleStick':'Candle Stick','DashboardStringId.RangeFilterSelectRangeFromCaption':'From:','DashboardStringId.GridTotalAutoTemplate':'{0}','DashboardStringId.FunctionDescriptionSize':'Size()\\r\\nReturns the number of rows in the window.','DashboardStringId.FunctionDescriptionVarp':'Varp(Value)\\r\\nReturns the variance of a population, where the population is the entire data to be summarized.','DashboardStringId.FunctionDescriptionAggr':'aggr(SummaryExpression, Dimension1, Dimension2, ...)\\r\\nUses the detail level and summary function to aggregate underlying data. The level depends on the number of dimensions.','DashboardStringId.FunctionDescriptionLast':'Last()\\r\\nReturns the number of rows from the current row to the last row in the window.','DashboardStringId.MessageAggregateFunctionInMasterFilterDimension':'Master filtering cannot be applied by values of the dimension created based on the calculated field with the Aggr function. The following dimensions are created based on such fields: {0}.','DashboardStringId.ActionExportDashboard':'Export Dashboard','DashboardStringId.CommandFormatRuleRangeGradient':'Gradient Ranges','DashboardStringId.ParameterNullExportValue':'null','DashboardStringId.PageLayoutPortrait':'Portrait','DashboardStringId.PeriodLastSecond':'Last Second','DashboardStringId.FormatConditionAppearanceFontBlue':'Blue Font','DashboardStringId.FormatConditionAppearanceFontBold':'Bold','DashboardStringId.DateTimeGroupIntervalDateHour':'Date-Hour','DashboardStringId.DefaultNameTextBoxItem':'Text Box','DashboardStringId.MessageInvalidCardLayoutTemplateMaxWidth':'The maximum width must be greater than zero or equal to null.','DashboardStringId.CalculatedFieldTypeDateTime':'DateTime','DashboardStringId.CommandFormatRuleNotBetween':'Not Between','DashboardStringId.DateTimeFormatQuarterFormatNumericCaption':'Numeric','DashboardStringId.FormatStringDataItemName':'{0} ({1})','DashboardStringId.FormatRuleApplyToColumn':'Apply to column','DashboardStringId.ButtonOK':'OK','DashboardStringId.DateTimeIntervalQuarter':'Quarter','DashboardStringId.FormatRuleUnableToAddRule_NoCardsToApply':'Unable to add a new format rule. There is no card to apply the rule.','DashboardStringId.GridTotalTypeCount':'Count','DashboardStringId.DescriptionTooltipMeasures':'Tooltip measures','DashboardStringId.DashboardDataUpdating':'Updating','DashboardStringId.MessageInvalidDeltaIndicatorSize':'The delta indicator size must be greater than zero.','DashboardStringId.DeltaValueTypePercentVariationCaption':'Percent variation','DashboardStringId.FormatRuleRangeDelete':'Delete','DashboardStringId.IncorrectParameterType':'The dashboard parameter values type does not correspond to Parameter.Type.','DashboardStringId.IncludeExportDashboardState':'Include','DashboardStringId.RangeFilterCalculationAlongSeries':'Series','DashboardStringId.PeriodLastDay':'Last Day','DashboardStringId.TreemapLabelValueTemplate':'{0}: {1}','DashboardStringId.MessageLayoutDuplicatedDashboardItem':'A layout item for the specified dashboard item has already been added to the layout tree','DashboardStringId.ExtractPreprocessorColumnError':'The following columns cannot be processed:\\r\\n{0}','DashboardStringId.PercentOfTotalCalculationMeasureCaptionFormatString':'Percent of {0} Total','DashboardStringId.AggregateExFunctionDescriptionCountNotNull':'CountNotNull(Value)\\r\\nReturns a number of non-null objects in a collection.','DashboardStringId.MessageUnassignedDashboardItemGroup':'The dashboard item group should belong to the dashboard. To add a group to the dashboard, use the Dashboard.Groups property.','DashboardStringId.CommandFormatRuleAboveAverage':'Above Average','DashboardStringId.FunctionOperatorExFunctionDescriptionGetQuarter':'GetQuarter(DateTime)\\r\\nExtracts a quarter from the defined DateTime.','DashboardStringId.SeriesTypeHighLowClose':'High-Low-Close','DashboardStringId.FunctionOperatorExFunctionDescriptionGetWeekOfYear':'GetWeekOfYear(DateTime)\\r\\nExtracts the week of the year from the defined DateTime.','DashboardStringId.ExtractColumnUnsupportedTypeTooltip':'The column has unsupported type','DashboardStringId.CommandFormatRuleRangeColors':'Color Ranges','DashboardStringId.IntersectionLevelModeLast':'Last level','DashboardStringId.IntersectionLevelModeAuto':'(Auto)','DashboardStringId.FormatConditionAppearancePaleOrange':'Pale Orange','DashboardStringId.CalculationTypeRunningTotal':'Running Total','DashboardStringId.GridSortAscending':'Sort Ascending','DashboardStringId.AxisYNameCount':'Count','DashboardStringId.MessageLegacyCardLayoutIsNotSupported':'Card layout is outdated and cannot be displayed. To view this item, specify the layout template in the Dashboard Designer. To know more, see the \\'Designing Dashboard Items > Cards > Layout\\' documentation topic.','DashboardStringId.FunctionCategoryCustomAggregateNames':'Custom Aggregate Names','DashboardStringId.FormatRuleFormatStyle':'Format style','DashboardStringId.ChartCalculationAlongArguments':'Arguments','DashboardStringId.FunctionCategoryWindow':'Window','DashboardStringId.MessageInvalidFontSize':'The font size must be greater than zero.','DashboardStringId.CalculationTypeExpression':'Expression','DashboardStringId.NumericFormatUnitAutoCaption':'Auto','DashboardStringId.DefaultNameCustomItem':'Custom Item','DashboardStringId.DateTimeFormatYearFormatAbbreviatedCaption':'Abbreviated','DashboardStringId.RangeFilterEmptySeries':'Please specify Range Filter values','DashboardStringId.DateTimeIntervalSecond':'Second','DashboardStringId.RankTypeModified':'Modified','DashboardStringId.DateFilterDatePickerButtonDefaultText':'Set Filter...','DashboardStringId.RankCalculationMeasureCaptionFormatString':'Rank of {0}','DashboardStringId.FormatStringDashboardItemCaption':' - {0}','DashboardStringId.CardRowDataElementTypeTargetValueCaption':'Target Value','DashboardStringId.FormatConditionAppearanceGradientRed':'Gradient Red','DashboardStringId.FromToDatePeriodCaption':'{0} - {1}','DashboardStringId.CalculationTypeMovingCalculation':'Moving Calculation','DashboardStringId.SummaryTypeSum':'Sum','DashboardStringId.SummaryTypeMin':'Min','DashboardStringId.SummaryTypeMax':'Max','DashboardStringId.SummaryTypeVar':'Var','DashboardStringId.ExtractCustomDriverNameError':'The name of the custom extract driver cannot be null or empty.','DashboardStringId.PieCalculationAlongSeriesAndArguments':'Series / Arguments','DashboardStringId.ErrorHandlingOrderByCalculationDataMembers':'Sorting by measure cannot be applied if the target measure has calculations. The following dimensions are ordered by measures with calculations','DashboardStringId.FunctionDescriptionVar':'Var(Value)\\r\\nReturns an estimate of the variance of a population, where the sample is a subset of the entire population.','DashboardStringId.NumericFormatUnitOnesCaption':'Ones','DashboardStringId.DescriptionItemWeight':'Weight','DashboardStringId.FormatConditionAppearancePalePurple':'Pale Purple','DashboardStringId.ExactDateDateTimeFormatPattern':'{0}: {1}','DashboardStringId.DateTimeFormatDateFormatLongCaption':'Long','DashboardStringId.DescriptionSparklineArgument':'Argument','DashboardStringId.DefaultOlapDataSourceName':'OLAP Data Source','DashboardStringId.AggregatedDataType':'Aggregated','DashboardStringId.EntireRangePeriodCaption':'Entire Range','DashboardStringId.SeriesTypeSpline':'Spline','DashboardStringId.TooltipDataItemsHeader':'TOOLTIP DATA ITEMS','DashboardStringId.DefaultNameCardItem':'Cards','DashboardStringId.CommandFormatRuleBottomN':'Bottom N','DashboardStringId.CalculationTypePercentageDifference':'Percentage Difference','DashboardStringId.LowCaption':'Low','DashboardStringId.DeltaThresholdTypePercent':'Percent','DashboardStringId.Title':'Title','DashboardStringId.FormatRuleDrawAxis':'Draw axis','DashboardStringId.ExtractDriverNotFoundError':'Cannot find an extract driver with the following name: \\'{0}\\'','DashboardStringId.DescriptionItemSeries':'Series','DashboardStringId.ErrorHandlingRecursiveDataMembers':'The following data items refer to each other','DashboardStringId.UriCaption':'Uri','DashboardStringId.Delta':'Delta','DashboardStringId.RangeFilterSelectRange':'Select Range','DashboardStringId.SeriesTypeSideBySideFullStackedBar':'Full-Stacked Bar Side-by-Side','DashboardStringId.ActionOtherValues':'Values','DashboardStringId.SeriesTypeGroupArea':'Area','DashboardStringId.MessageSummaryCalculatedFieldInDimension':'Cannot change the expression of the \\'{0}\\' calculated field that provides data for the \\'{1}\\' dimension. Summary-based calculated fields can provide data for measures only.','DashboardStringId.FormatRangeFilterDisplayText':'{0} - {1}','DashboardStringId.AxisXNameArguments':'Arguments','DashboardStringId.DeltaValueTypeAbsoluteVariationCaption':'Absolute variation','DashboardStringId.FormatRulePredefinedColor':'Predefined color','DashboardStringId.FormatRuleStyleAppearance':'Appearance','DashboardStringId.PeriodLastMinute':'Last Minute','DashboardStringId.RangeFilterCalculationAlongSeriesAndArgument':'Series / Argument','DashboardStringId.CommandFormatRuleBelowAverage':'Below Average','DashboardStringId.GridCalculationAlongRows':'Rows','DashboardStringId.FunctionDescriptionGetDateWeekYear':'GetDateWeekYear(DateTime)\\r\\nReturns the date of the first day of the week for a given DateTime (uses culture settings).','DashboardStringId.FunctionDescriptionTotal':'Total(SummaryExpression)\\r\\nReturns the total for the specified expression in a table calculation window.','DashboardStringId.DataSourceFilterContainsAggrExceptionText':'Cannot load data because the data source filter should not contain the Aggr function.','DashboardStringId.DateTimeFormatDayOfWeekFormatNumericCaption':'Numeric','DashboardStringId.FunctionDescriptionFirst':'First()\\r\\nReturns the number of rows from the current row to the first row in the window.','DashboardStringId.GaugeScaleLabelFormatCaption':'Scale Label','DashboardStringId.DifferenceCalculationMeasureCaptionFormatString':'Difference of {0}','DashboardStringId.FunctionDescriptionIndex':'Index()\\r\\nReturns the index of the current row in the window.','DashboardStringId.ValueCaption':'Value','DashboardStringId.SeriesTypeSideBySideRangeBar':'Range Bar Side-by-Side','DashboardStringId.DefaultSqlDataSourceName':'SQL Data Source','DashboardStringId.TreemapLabelArgumentTemplate':'{0} - {1}','DashboardStringId.ErrorHandlingNoSuchDataMembers':'The following data items do not exist','DashboardStringId.SeriesTypeSplineArea':'Spline Area','DashboardStringId.MessageMasterFilterIncorrectNumberOfValues':'Cannot identify an element that will be used to perform master filtering due to an incorrect number of provided values.','DashboardStringId.IntersectionLevelModeSpecific':'Specific level','DashboardStringId.FunctionDescriptionStdDevp':'StdDevp(Value)\\r\\nReturns the standard deviation of a population, where the population is the entire data to be summarized.','DashboardStringId.DateFilterInvalidDisplayTextPattern':'Invalid text pattern','DashboardStringId.CardRowDataElementTypeActualValueCaption':'Actual Value','DashboardStringId.MessageCustomItemConfigurationError':'Dashboard item configuration error. Please contact the application vendor or system administrator for assistance.','DashboardStringId.FormatRuleUnableToAddRule':'Unable to add a new format rule.','DashboardStringId.CommandFormatRuleBetween':'Between','DashboardStringId.DateTimeFormatQuarterFormatFullCaption':'Full','DashboardStringId.PieCalculationAlongArgumentsAndSeries':'Arguments / Series','DashboardStringId.CommandDimensionGroupChildValues':'Group Tiles','DashboardStringId.ErrorHandlingTopNByCalculationDataMembers':'Top N cannot be applied if its target measure has a calculation. The following dimensions have Top N applied by measures with calculations','DashboardStringId.FormatRuleStyle':'Style Settings','DashboardStringId.DashboardStatePosition':'Position','DashboardStringId.AutoFitPageCount':'Auto Fit Page Count','DashboardStringId.NewParameterNamePrefix':'Parameter','DashboardStringId.FunctionDescriptionRankModified':'RankModified(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the modified competition rank for the current row in the window.','DashboardStringId.RangeFilterSelectRangeToCaption':'To:','DashboardStringId.FormatRulePercentOf':'% of all values','DashboardStringId.FormatConditionAppearancePaleYellow':'Pale Yellow','DashboardStringId.MessageWrongExcelDataSourceConnectionParametersType':'Connection parameters are invalid. An excel data source supports only ExcelDataSourceConnectionParameters.','DashboardStringId.ScaleModeUseScaleFactor':'Use Scale Factor','DashboardStringId.DateTimeFormatDayOfWeekFormatFullCaption':'Full','DashboardStringId.SeriesTypeBubble':'Bubble','DashboardStringId.CustomItems':'Custom Items','DashboardStringId.DateTimeFormatQuarterFormatDefaultCaption':'Default','DashboardStringId.DescriptionDashboardItemComponentName':'Dashboard item component name','DashboardStringId.MovingCalculationMeasureCaptionFormatString':'Moving of {0}','DashboardStringId.DefaultNameItemGroup':'Group','DashboardStringId.RangeFilterIncompatibleNumericScale':'Range Filter\\'s numeric argument values should produce a continuous axis. Set the numeric scale to Continuous','DashboardStringId.ParametersFormValueColumnCaption':'Value','DashboardStringId.SeriesTypeStackedLine':'Stacked Line','DashboardStringId.SeriesTypeStackedArea':'Stacked Area','DashboardStringId.SeriesTypeGroupRangeFilter':'Range Filter','DashboardStringId.FunctionDescriptionRunningCustomAggregate':'RunningAggregate(SummaryExpression, CustomAggregateName) - Returns the cumulative result of the custom function applied to specified expression from the first row in the window to the current row.','DashboardStringId.CommandFormatRuleRangeSet':'Range Set','DashboardStringId.ExactDateFormatMinute':'Minute','DashboardStringId.CalculatedFieldTypeObject':'Object','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateHour':'GetDateHour(DateTime)\\r\\nExtracts the date part with the hour value from the defined DateTime.','DashboardStringId.MapAttributeDimension':'Attribute','DashboardStringId.FormatRuleCustomColor':'Custom color','DashboardStringId.RangeFilterCalculationAlongArgumentAndSeries':'Argument / Series','DashboardStringId.MessageIncorrectDashboardItemGroupAssign':'A dashboard item group cannot be added to a collection of dashboard items. Use the Dashboard.Groups property to add the group to the dashboard.','DashboardStringId.DateTimeFormatDateTimeFormatShortCaption':'Short','DashboardStringId.FunctionDescriptionWindowCount':'WindowCount(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the count of the expression within the window.','DashboardStringId.PeriodThisYear':'This Year','DashboardStringId.PeriodThisHour':'This Hour','DashboardStringId.DefaultNameRangeFilterItem':'Range Filter','DashboardStringId.PivotCalculationAlongGroupsInRows':'Rows within Groups','DashboardStringId.CustomItemEmptyMeasurePlaceholder':'Measure','DashboardStringId.DefaultNameBoundImageItem':'Bound Image','DashboardStringId.WeightCaption':'Weight','DashboardStringId.GridClearSorting':'Clear Sorting','DashboardStringId.SeriesTypeSideBySideStackedBar':'Stacked Bar Side-by-Side','DashboardStringId.DateTimeGroupIntervalExactDate':'Exact Date','DashboardStringId.ActionClearMasterFilter':'Clear Master Filter','DashboardStringId.CommandFormatRuleAboveBelowAverage':'Average','DashboardStringId.DateTimeFormatDateFormatDefaultCaption':'Default','DashboardStringId.SeriesTypeGroupPointLine':'Point / Line','DashboardStringId.PeriodLastQuarter':'Last Quarter','DashboardStringId.DescriptionSparkline':'Sparkline','DashboardStringId.MessageInvalidLayoutClientWidth':'The layout width must be greater than zero.','DashboardStringId.FormatRuleAppliesToCardBackground':'The selected style applies to a card\\'s background','DashboardStringId.PeriodNextDay':'Next Day','DashboardStringId.FilterStatePresentationSplitSheet':'Separate Sheet','DashboardStringId.FormatRuleApplyToChartElement':'Apply to chart elements','DashboardStringId.GridResetColumnWidths':'Reset column widths','DashboardStringId.SummaryTypeStdDevp':'StdDevP','DashboardStringId.DefaultDataSourceName':'Data Source','DashboardStringId.SummaryTypeCount':'Count','DashboardStringId.NumericFormatFormatTypeNumberCaption':'Number','DashboardStringId.FormatRuleUnableToAddRule_NoXYAxes':'Unable to add a new format rule. X and Y axis are required.','DashboardStringId.DefaultObjectDataSourceName':'Object Data Source','DashboardStringId.FormatConditionNumberValueType':'Number','DashboardStringId.SeriesTypeStepArea':'Step Area','DashboardStringId.SeriesTypeStepLine':'Step Line','DashboardStringId.FormatConditionAppearancePaleRed':'Pale Red','DashboardStringId.ExactDateFormatDay':'Day','DashboardStringId.FormatConditionAppearanceFontUnderline':'Underline','DashboardStringId.PeriodThisSecond':'This Second','DashboardStringId.FunctionDescriptionWindowFirstValue':'WindowFirstValue(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the first value of the expression within the window.','DashboardStringId.FunctionDescriptionLookup':'Lookup(SummaryExpression, Position)\\r\\nReturns the value of the expression in a target position specified as a relative offset from the current position.','DashboardStringId.RankTypeDense':'Dense','DashboardStringId.CalculatedFieldsTreeItemName':'Calculated Fields','DashboardStringId.AxisYNameValues':'Values','DashboardStringId.CardLayoutTemplateCenteredCaption':'Centered','DashboardStringId.DescriptionItemColor':'Color','DashboardStringId.PeriodThisQuarter':'This Quarter','DashboardStringId.PivotCalculationAlongRowsAndColumns':'Rows / Columns','DashboardStringId.DescriptionItemValue':'Value','DashboardStringId.FunctionDescriptionMedian':'Median(Value)\\r\\nReturns the median of the values in a collection.','DashboardStringId.ChartTotalValue':'Total','DashboardStringId.NumericFormatUnitBillionsCaption':'Billions','DashboardStringId.Value1Caption':'Value 1','DashboardStringId.MessageDuplicatedDataItem':'This instance of the \\'{0}\\' data item has already been added to \\'{1}\\'. To add a similar data item to \\'{1}\\', create a new instance of this data item.','DashboardStringId.CalculatedFieldTypeDouble':'Double','DashboardStringId.ExportFilters':'Filters','DashboardStringId.MessageServerModeNotSupportedMedian':'Median is not supported in server mode for','DashboardStringId.RangeFilterIncompatibleArgumentSorting':'Range Filter\\'s argument should not be sorted in the descending order or by another data item','DashboardStringId.PivotGridGrandTotal':'Grand Total','DashboardStringId.ParametersFormCalendarTodayButton':'Today','DashboardStringId.CardLayoutTemplateLightweightCaption':'Lightweight','DashboardStringId.FormatConditionAppearanceCyan':'Cyan','DashboardStringId.FormatConditionAppearanceNone':'None','DashboardStringId.FormatConditionAppearanceGray':'Gray','DashboardStringId.FormatConditionAppearanceBlue':'Blue','DashboardStringId.CustomItemCalculationAlongFirstAxisDimensions':'Dimensions','DashboardStringId.SeriesTypeBar':'Bar','DashboardStringId.DateTimeGroupIntervalDateHourMinute':'Date-Hour-Minute','DashboardStringId.PivotCalculationAlongGroupsInRowsAndColumns':'Rows / Columns within Groups','DashboardStringId.AutoArrangeContent':'Auto Arrange Content','DashboardStringId.ColorAutoAssigned':'Auto','DashboardStringId.ErrorToBooleanDateTimeOperand':'Cannot convert a date-time value to boolean.','DashboardStringId.MessageIncorrectGridDashboardControlOperation':'An invalid operation was performed in GridDashboardControl.','DashboardStringId.CommandFormatRuleRangeIcons':'Icon Ranges','DashboardStringId.ActionClearSelection':'Clear Selection','DashboardStringId.CustomItemMetadataInteractivitySectionsIncorrectOrderExceptionMessage':'The custom \\'{0}\\' item\\'s metadata configuration does not support interactivity. Declare the \\'{1}\\' property before non-interactive data sections. See documentation for more information: https://docs.devexpress.com/Dashboard/DevExpress.DashboardCommon.SupportInteractivityAttribute','DashboardStringId.DescriptionItemMeasure':'Measure','DashboardStringId.FormatConditionAppearanceRed':'Red','DashboardStringId.GridTotalTemplate':'{0} = {1}','DashboardStringId.CardRowDataElementTypePercentOfTargetCaption':'Percent of Target','DashboardStringId.CardLayoutTemplateStretchedCaption':'Stretched','DashboardStringId.ActionDrillUp':'Drill Up','DashboardStringId.CustomItemEmptyDimensionPlaceholder':'Dimension','DashboardStringId.Longitude':'Longitude','DashboardStringId.ColorPaletteIndex':'Palette index:','DashboardStringId.NumericFormatUnitMillionsCaption':'Millions','DashboardStringId.RangeFilterIncompatibleArgument':'Range Filter\\'s argument field should have Numeric, DateTime, or TimeSpan type','DashboardStringId.DateTimeGroupIntervalMonth':'Month','DashboardStringId.DescriptionSeries':'Series','DashboardStringId.DeltaIndicationModeLessIsGoodCaption':'Less is good','DashboardStringId.ChartCalculationAlongSeriesAndArguments':'Series / Arguments','DashboardStringId.IntersectionLevelModeAll':'All levels','DashboardStringId.SparklineIndicationModeWinLoss':'Win/Loss','DashboardStringId.SearchNullValuePrompt':'Enter text to search...','DashboardStringId.MessagePivotHasNoData':'The pivot grid has no data.','DashboardStringId.DataInspectorObjectValue':'[Object]','DashboardStringId.ActionSelectDateTimePeriod':'Select Date Time Period','DashboardStringId.MessageGridHasNoData':'The grid has no data.','DashboardStringId.ErrorHandlingSQLServerModeError':'Server mode is not supported for stored procedures','DashboardStringId.PivotCalculationAlongGroupsInColumnsAndRows':'Columns / Rows within Groups','DashboardStringId.DescriptionArguments':'Arguments','DashboardStringId.PivotCalculationAlongColumnsAndRows':'Columns / Rows','DashboardStringId.CardRowDataElementTypeDeltaIndicatorCaption':'Delta Indicator','DashboardStringId.DefaultNameScatterChartItem':'Scatter Chart','DashboardStringId.MessageLoading':'Loading...','DashboardStringId.PaperKind':'Size','DashboardStringId.DataInspectorButtonClose':'Close','DashboardStringId.CalculatedFieldTypeDecimal':'Decimal','DashboardStringId.SummaryTypeCountDistinct':'Count Distinct','DashboardStringId.RankTypePercentile':'Percentile','DashboardStringId.PageLayoutAuto':'Auto','DashboardStringId.SelectDate':'Select date','DashboardStringId.MessageCustomItemIncorrectDataItemSectionName':'The dashboard definition contains the {0} property that does not exist in the corresponding {1} class. This property will be ignored while the custom item is loading.','DashboardStringId.DeltaIndicationModeGreaterIsGoodCaption':'Greater is good','DashboardStringId.DateTimeIntervalAll':'All','DashboardStringId.DateTimeIntervalDay':'Day','DashboardStringId.FormatRuleUnableToAddRule_NoCardLayout':'Unable to add a new format rule to cards that use a legacy layout.','DashboardStringId.NumericFormatFormatTypeScientificCaption':'Scientific','DashboardStringId.GroupIntervalNone':'No Grouping','DashboardStringId.SizeModeStretch':'Stretch','DashboardStringId.ChartElementLineOrAreaCaption':'Line/Area','DashboardStringId.ErrorHandlingWindowDefinitionServerMode':'The w function cannot be used for server-mode data sources','DashboardStringId.DeltaValueTypePercentOfTargetCaption':'Percent of target','DashboardStringId.ExactDateFormatSecond':'Second','DashboardStringId.SummaryTypeStdDev':'StdDev','DashboardStringId.DateTimeGroupIntervalWeekOfMonth':'Week of Month','DashboardStringId.DateTimeFormatDayOfWeekFormatAbbreviatedCaption':'Abbreviated','DashboardStringId.RunningTotalCalculationMeasureCaptionFormatString':'Running Total of {0}','DashboardStringId.FunctionDescriptionRankUnique':'RankUnique(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the unique rank for the current row in the window.','DashboardStringId.PointLabelContentTypeNone':'None','DashboardStringId.NumericFormatUnitSymbolBillions':'B','DashboardStringId.SizeMode':'Size Mode','DashboardStringId.LayoutDimensionModeAuto':'Auto','DashboardStringId.SparklineIndicationModeArea':'Area','DashboardStringId.SparklineIndicationModeLine':'Line','DashboardStringId.PointLabelContentTypeValue':'Value','DashboardStringId.ExtractEmptyDataFieldsExceptionMessage':'Cannot create the extract file from the Object/Entity Framework data source because the ExtractSourceOptions.DataFields collection is empty.','DashboardStringId.AggregateExFunctionDescriptionMode':'Mode(Value)\\r\\nThe mode of the values. A mode is the value that is repeated more often than any other.','DashboardStringId.PageLayoutLandscape':'Landscape','DashboardStringId.DateTimeFormatMonthFormatAbbreviatedCaption':'Abbreviated','DashboardStringId.FilterElementRadioComboBoxNoDataCaption':'Select...','DashboardStringId.FormatRuleUnableToAddRule_NoSeriesToApply':'Unable to add a new format rule. There is no series to apply the rule.','DashboardStringId.PointLabelContentTypeArgument':'Argument','DashboardStringId.FormatRuleRangeGenerateRanges':'Generate Ranges','DashboardStringId.CardRowDataElementTypeCardNameCaption':'Card Name','DashboardStringId.CommandFormatRuleBetweenOrEqual':'Between Or Equal To','DashboardStringId.SummaryTypeMedian':'Median','DashboardStringId.CardRowDataElementTypeAbsoluteVariationCaption':'Absolute Variation','DashboardStringId.HighCaption':'High','DashboardStringId.ExpressionFieldsTreeItemName':'Expressions','DashboardStringId.ElementNameCards':'Cards','DashboardStringId.FormatRuleApplyToDimensionElement':'Dimension - {0}','DashboardStringId.SeriesTypeStackedBar':'Stacked Bar','DashboardStringId.DefaultNamePivotItem':'Pivot','DashboardStringId.CalculatedFieldTypeUnknown':'Unknown','DashboardStringId.DescriptionValues':'Values','DashboardStringId.RankTypeCompetition':'Competition','DashboardStringId.CommandFormatRuleBelowOrEqualAverage':'Below Or Equal to Average','DashboardStringId.DescriptionItemAxisXMeasure':'X-axis','DashboardStringId.MessageEFNotSupportedMedian':'Median is not supported for the Entity Framework.','DashboardStringId.TargetValueCaption':'Target','DashboardStringId.FormatConditionAppearancePaleBlue':'Pale Blue','DashboardStringId.FormatConditionAppearancePaleCyan':'Pale Cyan','DashboardStringId.FormatConditionAppearancePaleGray':'Pale Gray','DashboardStringId.DeltaIndicationModeWarningIfLessCaption':'Warning if less','DashboardStringId.CommandDimensionSortModeValue':'(Value)','DashboardStringId.SummaryTypeAverage':'Average','DashboardStringId.FormatRuleShowBarOnly':'Show bar only','DashboardStringId.DateTimeGroupIntervalWeekYear':'Week-Year','DashboardStringId.CardCalculationAlongCards':'Cards','DashboardStringId.DateTimeGroupIntervalQuarter':'Quarter','DashboardStringId.CalculatedFieldTypeString':'String','DashboardStringId.SparklineValuesSeparator':', ','DashboardStringId.OlapRaggedHierarchyNoneItemCaption':'(None)','DashboardStringId.DashboardCurrencyUseCurrentCurrency':'Use client system settings','DashboardStringId.LoadingDataError':'The Dashboard encountered an issue while loading data. One or several dashboard items may appear empty.\\r\\nPlease contact the application vendor or your system administrator and provide the following information.\\r\\n\\r\\nThe Web application server failed to establish the following data connections:\\r\\n{0}','DashboardStringId.DescriptionItemMeasureWeight':'Weight','DashboardStringId.PeriodThisMinute':'This Minute','DashboardStringId.DateTimeFormatMonthFormatNumericCaption':'Numeric','DashboardStringId.FunctionDescriptionRankDense':'RankDense(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the dense rank for the current row in the window.','DashboardStringId.FunctionCategoryAdvanced':'Advanced','DashboardStringId.ExactDateFormatQuarter':'Quarter','DashboardStringId.PeriodNextSecond':'Next Second','DashboardStringId.FunctionDescriptionAggrJoinRule':'joinRule(dimension, searchValue)\\r\\nSpecifies the dimension for the \\'aggr\\' function and a column whose values are used in the join operation after aggregation is completed.','DashboardStringId.DefaultNameComboBoxItem':'Combo Box','DashboardStringId.SeriesTypeRangeArea':'Range Area','DashboardStringId.CommandFormatRuleTopN':'Top N','DashboardStringId.MessageWrongAxisName':'A data axis with the specified name does not exist in this dashboard item. See the DevExpress.DashboardCommon.DashboardDataAxisNames static class for valid data axis names.','DashboardStringId.CalculationTypePercentOfTotal':'Percent Of Total','DashboardStringId.CommandFormatRuleLessThanOrEqualTo':'Less Than Or Equal To','DashboardStringId.DateFilterDisplayTextPattern':'Display Text Pattern','DashboardStringId.SeriesTypeGroupRange':'Range','DashboardStringId.MessageWrongDateTimePeriodName':'The DateTimePeriodCollection does not contain the item with the specified name.','DashboardStringId.OLAPUnavailableRawData':'OLAP Data Source - Data Unavailable','DashboardStringId.DataItemsHeader':'DATA ITEMS','DashboardStringId.FitToPageWidth':'Fit to Page Width','DashboardStringId.FormatRuleAllowNegativeAxis':'Allow negative axis','DashboardStringId.FormatRuleDisplayName':'Caption','DashboardStringId.FormatConditionAppearanceYellow':'Yellow','DashboardStringId.SeriesTypeGroupFinancial':'Financial','DashboardStringId.DateTimeGroupIntervalYear':'Year','DashboardStringId.DateTimeGroupIntervalHour':'Hour','DashboardStringId.PointLabelContentTypePercent':'Percent','DashboardStringId.MessageIncorrectDataAssign':'Data cannot be assigned if a data provider is used','DashboardStringId.ErrorHandlingInvalidCustomFunctions':'Calculated Field and Window expressions cannot contain some custom functions. Evaluated expressions contain the following forbidden functions','DashboardStringId.MessageIncorrectFilterValueLength':'The list of values that has been assigned as the filter value has a length that does not match the expected length of the filter value.','DashboardStringId.SparklineIndicationModeBar':'Bar','DashboardStringId.ScatterCalculationAlongArguments':'Arguments','DashboardStringId.DefaultXpoDataSourceName':'XPO Data Source','DashboardStringId.NumericFormatUnitSymbolMillions':'M','DashboardStringId.FormatRuleUnableToAddRule_NoColumnsToApply':'Unable to add a new format rule. There is no column to apply the rule.','DashboardStringId.FormatRuleApplyTo':'Apply to','DashboardStringId.FormatConditionAppearanceFontItalic':'Italic','DashboardStringId.NumericGroupIntervalContinuous':'Continuous','DashboardStringId.DifferenceCalculationTargetPrevious':'Previous','DashboardStringId.CommandDimensionSortModeID':'(ID)','DashboardStringId.DefaultMongoDBDataSourceName':'MongoDB Data Source','DashboardStringId.DescriptionGauges':'Gauges','DashboardStringId.NumericGroupIntervalDiscrete':'Discrete','DashboardStringId.FunctionDescriptionWindowVarp':'WindowVarp(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the biased variance of the expression within the window.','DashboardStringId.FunctionDescriptionWindowMode':'WindowMode(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the mode of the expression within the window.','DashboardStringId.DateTimeGroupIntervalDateHourMinuteSecond':'Date-Hour-Minute-Second','DashboardStringId.DefaultNameDateFilterItem':'Date Filter','DashboardStringId.FormatConditionAutomaticValueType':'Automatic','DashboardStringId.ScaleModeNone':'None','DashboardStringId.DefaultNamePieItem':'Pies','DashboardStringId.EndDate':'(End Date)','DashboardStringId.FunctionOperatorExFunctionDescriptionToDateTime':'ToDateTime(Value)\\r\\nConverts Value to a DateTime value.','DashboardStringId.FormatConditionPercentValueType':'Percent','DashboardStringId.CommandFormatRuleBar':'Bar','DashboardStringId.FormatConditionAppearanceFontGreen':'Green Font','DashboardStringId.DefaultExcelDataSourceName':'Excel Data Source','DashboardStringId.CommandDimensionSortModeDisplayText':'(Display Text)','DashboardStringId.MessageIncorrectMoveTarget':'Cannot move a layout item to a position within its own branch','DashboardStringId.ExactDateFormatHour':'Hour','DashboardStringId.ExactDateFormatYear':'Year','DashboardStringId.DefaultNameMapItem':'Map','DashboardStringId.ExtractSourceDataSourceNamePostfix':'(local copy)','DashboardStringId.FunctionDescriptionAggregateFilter':'filter(SummaryExpression, filterCriteria)\\r\\nFilters underlying data with specified filter criteria and aggregates filtered data using current detail level and the summary function.','DashboardStringId.DescriptionMeasures':'Measures','DashboardStringId.FormatRuleApplyToAllElements':'All elements','DashboardStringId.GridTotalValueTemplate':'{0}','DashboardStringId.MessageServerModeNotSupportedCountDistinct':'Count Distinct is not supported in server mode for','DashboardStringId.DefaultDashboardTitleText':'Dashboard','DashboardStringId.FormatConditionAppearancePaleGreen':'Pale Green','DashboardStringId.FileName':'File Name','DashboardStringId.ResetExactDateFormatToDefault':'Reset to Default','DashboardStringId.LayoutDimensionModeFixed':'Fixed','DashboardStringId.PeriodLastMonth':'Last Month','DashboardStringId.DescriptionBoundImageAttribute':'Attribute','DashboardStringId.MessageInvalidFilterExpression':'Incorrect column identifier: {0}. A valid column identifier must consist of the column name preceeded by the table name (or alias, if specified). These names must be dot-separated.','DashboardStringId.TopNOthersValue':'Others','DashboardStringId.PaperKindExecutive':'Executive','DashboardStringId.FormatConditionAppearancePurple':'Purple','DashboardStringId.ActionMaximizeDashboardItem':'Maximize','DashboardStringId.GridSortDescending':'Sort Descending','DashboardStringId.PeriodLastYear':'Last Year','DashboardStringId.PeriodLastHour':'Last Hour','DashboardStringId.FormatConditionAppearanceFontGrayed':'Gray Font','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateHourMinute':'GetDateHourMinute(DateTime)\\r\\nExtracts the date part with the hour and minute values from the defined DateTime.','DashboardStringId.ErrorHandlingEFServerModeError':'Server mode is not supported for this data member','DashboardStringId.MeasureNamesDimensionName':'MeasureNames','DashboardStringId.Value2Caption':'Value 2','DashboardStringId.FormatRuleDisplayInLegend':'Display in legend','DashboardStringId.FormatRuleRangeReverseStyles':'Reverse','DashboardStringId.CsvValueSeparator':'Separator','DashboardStringId.SeriesTypePoint':'Point','DashboardStringId.ParameterTrueExportValue':'True','DashboardStringId.SeriesTypeStock':'Stock','DashboardStringId.CalculationTypeDifference':'Difference','DashboardStringId.FormatRuleRangeSegmentNumber':'Number of ranges:','DashboardStringId.LegendItemFormatString':'{0} - {1}','DashboardStringId.SizeModeZoom':'Zoom','DashboardStringId.SizeModeNone':'None','DashboardStringId.MessageInvalidStream':'The \\'stream\\' parameter can\\'t be null','DashboardStringId.DateTimeFormatDateFormatShortCaption':'Short','DashboardStringId.CommandFormatRuleDateOccurring':'A Date Occurring','DashboardStringId.ColoringModeNone':'None','DashboardStringId.NumericFormatUnitCaption':'Unit','DashboardStringId.PeriodNextMinute':'Next Minute','DashboardStringId.FormatRuleRangeAdd':'Add','DashboardStringId.CommandFormatRuleAboveOrEqualAverage':'Above Or Equal to Average','DashboardStringId.ScaleMode':'Scale Mode','DashboardStringId.CardRowDataElementTypeSubtitleCaption':'Subtitle','DashboardStringId.DateTimeFormatDayOfWeekFormatDefaultCaption':'Default','DashboardStringId.SeriesTypeFullStackedBar':'Full-Stacked Bar','DashboardStringId.MessageDuplicatedLayoutItem':'This layout item is already contained in the tree','DashboardStringId.DescriptionMapValue':'Map / Value','DashboardStringId.FunctionDescriptionWindowStdDevp':'WindowStdDevp(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the biased standard deviation of the expression within the window.','DashboardStringId.GridCalculationAlongSparklineArgument':'Sparkline Argument','DashboardStringId.FunctionDescriptionWindowDefinitionPartitionBy':'partitionBy(column1, column2, ...)\\r\\nSpecifies the columns by which the data rows are partitioned. The window function is applied to each partition separately.','DashboardStringId.DeltaIndicationModeNoIndicationCaption':'No indication','DashboardStringId.SeriesTypeGroupBar':'Bar','DashboardStringId.ActionShowDataInspector':'Inspect Data','DashboardStringId.ExportParameters':'Parameters','DashboardStringId.FormatStringSeriesName':' - {0}','DashboardStringId.FilterElementCheckedComboBoxNoDataCaption':'(none)','DashboardStringId.DescriptionItemArgument':'Argument','DashboardStringId.DateTimeGroupIntervalSecond':'Second','DashboardStringId.ParametersFormNameColumnCaption':'Parameter','DashboardStringId.FunctionOperatorExFunctionDescriptionToBoolean':'ToBoolean(Value)\\r\\nConverts Value to an equivalent Boolean value.','DashboardStringId.DifferenceCalculationTargetFirst':'First','DashboardStringId.DescriptionItemAxisYMeasure':'Y-axis','DashboardStringId.GaugeCalculationAlongGauges':'Gauges','DashboardStringId.ErrorIncorrectIntervalCount':'The count parameter should be greater or equal to 1.','DashboardStringId.CommandFormatRuleNotEqualTo':'Not Equal To','DashboardStringId.ChartCalculationAlongSeries':'Series','DashboardStringId.FormatRuleInvalidRule':'<Invalid Rule>','DashboardStringId.CardCalculationAlongSparklineArgumentAndCards':'Sparkline Argument / Cards','DashboardStringId.ShowTitle':'Show Title','DashboardStringId.PaperKindLegal':'Legal','DashboardStringId.FormatRuleStyleIcons':'Icons','DashboardStringId.ColorInherited':'(Inherited)','DashboardStringId.FormatRuleApplyToPointSeriesElementOnly':'This option is in effect only for line or area series','DashboardStringId.DescriptionDimensions':'Dimensions','DashboardStringId.CardRowDataElementTypePercentVariationCaption':'Percent Variation','DashboardStringId.ButtonCancel':'Cancel','DashboardStringId.UndoText':'Undo','DashboardStringId.CardLayoutTemplateNoneCaption':'None','DashboardStringId.DefaultNameChartPane':'Pane','DashboardStringId.DefaultNameChartItem':'Chart','DashboardStringId.DateTimeQuarterFormat':'Q{0}','DashboardStringId.ChartElementPointCaption':'Point','DashboardStringId.RawDataType':'Raw','DashboardStringId.CloseCaption':'Close','DashboardStringId.FormatConditionAppearanceFontYellow':'Yellow Font','DashboardStringId.PaperKindA3':'A3','DashboardStringId.PaperKindA4':'A4','DashboardStringId.PaperKindA5':'A5','DashboardStringId.FilterStatePresentationAfterAndSplitPage':'Separate Page','DashboardStringId.CardCalculationAlongSparklineArgument':'Sparkline Argument','DashboardStringId.FormatConditionAppearanceOrange':'Orange','DashboardStringId.RangeFilterHasNoData':'The Range Filter does not contain any data to display.','DashboardStringId.CommandFormatRuleGreaterThanOrEqualTo':'Greater Than Or Equal To','DashboardStringId.DescriptionItemRow':'Row','DashboardStringId.FilterStatePresentationAfter':'Below','DashboardStringId.DateTimeIntervalHour':'Hour','DashboardStringId.DateTimeIntervalYear':'Year','DashboardStringId.DateTimeIntervalWeek':'Week','DashboardStringId.FunctionDescriptionWindowDefinitionOrderBy':'orderBy(column1, column2, ...)\\r\\nSpecifies the columns by which the values are sorted.','DashboardStringId.FunctionDescriptionWindowDefinition':'w(WindowExpression, partitionByFunction, orderByFunction)\\r\\nCalculates aggregated values with the specified window function for the window defined by the specified partitioning and ordering.','DashboardStringId.NumericFormatUnitThousandsCaption':'Thousands','DashboardStringId.DateTimeFormatDateTimeFormatTimeOnlyCaption':'Time only','DashboardStringId.ErrorHandlingJoinRuleFunctionServerMode':'The joinRule function cannot be used for server-mode data sources','DashboardStringId.ScaleModeAutoFitToPagesWidth':'Auto Fit to Pages Width','DashboardStringId.ColoringModeDefault':'Default','DashboardStringId.MessageInternalError':'Internal error. Please contact the application vendor or your system administrator and provide the following information.\\r\\n\\r\\n{0}','DashboardStringId.DefaultJsonDataSourceName':'JSON Data Source','DashboardStringId.CommandFormatRuleValue':'Value','DashboardStringId.FilterElementNoDataToDisplay':'No data to display','DashboardStringId.CommandFormatRuleRange':'Range','DashboardStringId.EmptyColumnAliasPattern':'Column{0}','DashboardStringId.DescriptionItemAuto':'New Column','DashboardStringId.ExtractPreprocessorError':'An error occurred during creation of the data extract:\\r\\n{0}','DashboardStringId.RankTypeUnique':'Unique','DashboardStringId.DateTimeGroupIntervalWeekOfYear':'Week of Year','DashboardStringId.GeoPointMapTooltipPointCount':'{0} points','DashboardStringId.ErrorHandlingDataBindingError':'The following errors occur during data binding:','DashboardStringId.FormatConditionAppearanceCustom':'Custom','DashboardStringId.DefaultNameImageItem':'Image','DashboardStringId.OlapCubeNotFoundError':'The cube with the following name cannot be found:\\r\\n{0}.','DashboardStringId.DescriptionRows':'Rows','DashboardStringId.MapShapeNoneAttribute':'NONE','DashboardStringId.FunctionDescriptionRankPercentile':'RankPercentile(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the percentile rank for the current row in the window.','DashboardStringId.RankOrderDescending':'Descending','DashboardStringId.SeriesTypeStackedSplineArea':'Stacked Spline Area','DashboardStringId.ExtractEmptyDataMemberExceptionMessage':'Cannot create an extract file because ExtractSourceOptions.DataMember is empty or specified incorrectly.','DashboardStringId.DescriptionMaps':'Maps','DashboardStringId.PrintHeadersOnEveryPage':'Print Headers on Every Page','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateMonthYear':'GetDateMonthYear(DateTime)\\r\\nReturns the date of the first day of the month for a given DateTime.','DashboardStringId.FunctionCategoryAggregate':'Aggregate','DashboardStringId.FormatRuleApplyToTextElement':'Text - \"{0}\"','DashboardStringId.ButtonExport':'Export','DashboardStringId.ToDatePeriodCaption':'To {0}','DashboardStringId.ErrorToBooleanCharOperand':'Cannot convert a character to a boolean value.','DashboardStringId.FilterElementShowAllItem':'(All)','DashboardStringId.NumericFormatFormatTypeCurrencyCaption':'Currency','DashboardStringId.FunctionDescriptionFirstValue':'FirstValue(Value)\\r\\nReturns the first value in a collection.','DashboardStringId.ExactDateFormatMonth':'Month','DashboardStringId.UniqueCalculatedFieldNameValidationMessage':'The {0} already contains a field named {1}.','DashboardStringId.ActionExportToPdf':'Export To PDF','DashboardStringId.PivotCalculationAlongGroupsInColumns':'Columns within Groups','DashboardStringId.PivotCalculationAlongRows':'Rows','DashboardStringId.NumericFormatUnitSymbolThousands':'K','DashboardStringId.InvalidCustomPropertyNameMessage':'The property name \\'{0}\\' is invalid. It should contain only letters, numbers, and the underscore symbol and cannot start with a number.','DashboardStringId.PivotGridTotal':'{0} Total','DashboardStringId.MessageInvalidLayoutClientHeight':'The layout height must be greater than zero.','DashboardStringId.FormatConditionAppearanceGradientTransparent':'Gradient Transparent','DashboardStringId.CardLayoutTemplateCustomCaption':'Custom','DashboardStringId.DeltaIndicationModeWarningIfGreaterCaption':'Warning if greater','DashboardStringId.FormatConditionAppearanceGradientGreen':'Gradient Green','DashboardStringId.GridHyperlinkUriPatternErrorMessage':'Invalid placeholder','DashboardStringId.MessageBoxWarningTitle':'Warning','DashboardStringId.InspectedTypeFormatString':'({0} Data)','DashboardStringId.FormatStringKpiElementCaption':'{0} vs {1}','DashboardStringId.CardRowDataElementTypeTitleCaption':'Title','DashboardStringId.RangeFilterIncompatibleTopN':'Range Filter\\'s argument does not support the Top N feature','DashboardStringId.DeltaValueTypeTargetValueCaption':'Target value','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateQuarterYear':'GetDateQuarterYear(DateTime)\\r\\nReturns the date of the first day of the quarter for a given DateTime.','DashboardStringId.DateTimeGroupIntervalDayMonthYear':'Day-Month-Year','DashboardStringId.FormatRuleRangeUsePercent':'Use % ranges','DashboardStringId.GridCalculationAlongSparklineArgumentAndRows':'Sparkline Argument / Rows','DashboardStringId.FormatConditionAppearanceGradientCyan':'Gradient Cyan','DashboardStringId.FormatConditionAppearanceGradientBlue':'Gradient Blue','DashboardStringId.DefaultNameTreeViewItem':'Tree View','DashboardStringId.MessageIncorrectValueTopNCount':'The TopNCount property value cannot be negative or zero.','DashboardStringId.DateTimeFormatMonthFormatFullCaption':'Full','DashboardStringId.DateTimeGroupIntervalMonthYear':'Month-Year','DashboardStringId.ParametersFormCaption':'Dashboard Parameters','DashboardStringId.MessageCustomItemIsNotSupported':'The custom item is not supported by this control.','DashboardStringId.SparklineTooltipMinValue':'Min:','DashboardStringId.FormatRuleDataItemIsNotAvailable':'(N/A)','DashboardStringId.CommandFormatRuleLessThan':'Less Than','DashboardStringId.CommandFormatRuleGreaterThan':'Greater Than','DashboardStringId.SeriesTypeFullStackedSplineArea':'Full-Stacked Spline Area','DashboardStringId.FormatRuleNegativeStyle':'Negative Style Settings','DashboardStringId.CommandFormatRuleEqualTo':'Equal To','DashboardStringId.AggrInMasterFilterDimensionError':'Master filtering cannot be applied by dimension values created using the expression containing the Aggr function.','DashboardStringId.DateTimeGroupIntervalDay':'Day','DashboardStringId.MeasureFilterCaptionFormatString':'Filtered {0}','DashboardStringId.MessageInvalidCultureName':'Cannot find a specific culture with the following name: {0}','DashboardStringId.DefaultPeriodName':'Period','DashboardStringId.ColoringModeHue':'Hue','DashboardStringId.DefaultEFDataSourceName':'EF Data Source','DashboardStringId.NewCalculatedFieldNamePrefix':'Calculated Field','DashboardStringId.ParametersFormAllowNullColumnCaption':'Pass Null','DashboardStringId.ActionExportTemplate':'{0} - {1}','DashboardStringId.PeriodNextQuarter':'Next Quarter','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateHourMinuteSecond':'GetDateHourMinuteSecond(DateTime)\\r\\nExtracts the date part with the hour, minute, and second values from the defined DateTime.','DashboardStringId.ExactDatePeriodCaption':'{0}','DashboardStringId.ButtonSubmit':'Submit','DashboardStringId.DateTimeIntervalMonth':'Month','DashboardStringId.FunctionDescriptionWindowCustomAggregate':'WindowAggregate(SummaryExpression, StartOffset, EndOffset, CustomAggregateName) - Returns the result of the custom function applied to the specified expression in the window.','DashboardStringId.PointLabelContentTypeSeriesName':'Series Name','DashboardStringId.GridTotalTypeSum':'Sum','DashboardStringId.GridTotalTypeAvg':'Avg','DashboardStringId.GridTotalTypeMin':'Min','DashboardStringId.GridTotalTypeMax':'Max','DashboardStringId.DefaultNameGridItem':'Grid','DashboardStringId.InspectedData':'Inspected Data:','DashboardStringId.FunctionDescriptionCountDistinct':'CountDistinct(Value)\\r\\nReturns the number of unique objects in a collection.','DashboardStringId.DefaultNameTabPage':'Page','DashboardStringId.ChartCalculationAlongArgumentsAndSeries':'Arguments / Series','DashboardStringId.ElementNamePies':'Pies','DashboardStringId.SeriesTypeGroupBubble':'Bubble','DashboardStringId.RangeFilterEmptyArgument':'Please specify the Range Filter\\'s argument','DashboardStringId.PeriodNextMonth':'Next Month','DashboardStringId.FunctionDescriptionWindowStdDev':'WindowStdDev(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the sample standard deviation of the expression within the window.','DashboardStringId.DeltaThresholdTypeAbsolute':'Absolute','DashboardStringId.MessageInvalidCardLayoutTemplateMinWidth':'The minimum width must be greater than zero.','DashboardStringId.DataSourceDataMember':'Data Member','DashboardStringId.ImageFormat':'Image Format','DashboardStringId.MessageCollectionTypesNotSupported':'Dashboard does not support collection types.','DashboardStringId.SparklineTooltipEndValue':'End:','DashboardStringId.Latitude':'Latitude','DashboardStringId.FunctionDescriptionRunningSum':'RunningSum(SummaryExpression)\\r\\nReturns the running sum of the specified expression from the first row in the window to the current row.','DashboardStringId.FunctionDescriptionRunningAvg':'RunningAvg(SummaryExpression)\\r\\nReturns the running average of the specified expression from the first row in the window to the current row.','DashboardStringId.FunctionDescriptionRunningMin':'RunningMin(SummaryExpression)\\r\\nReturns the running minimum of the specified expression from the first row in the window to the current row.','DashboardStringId.FunctionDescriptionRunningMax':'RunningMax(SummaryExpression)\\r\\nReturns the running maximum of the specified expression from the first row in the window to the current row.','DashboardStringId.CategoryNameGeneral':'General','DashboardStringId.DateTimeFormatYearFormatFullCaption':'Full','DashboardStringId.RangeFilterIncompatibleSeriesType':'A Range Filter can contain Line, Area and Bar series only','DashboardStringId.CalculationAlongSpecificDimensions':'Specific...','DashboardStringId.SummaryTypeMode':'Mode','DashboardStringId.SummaryTypeVarp':'VarP','DashboardStringId.CommandDimensionSortModeKey':'(Key)','DashboardStringId.SeriesTypeFullStackedLine':'Full-Stacked Line','DashboardStringId.SeriesTypeFullStackedArea':'Full-Stacked Area','DashboardStringId.ColorAutoAssignedNotApplied':'Auto (not applied)','DashboardStringId.DefaultNameListBoxItem':'List Box','DashboardStringId.DescriptionCards':'Cards','DashboardStringId.DescriptionTooltipDimensions':'Tooltip dimensions','DashboardStringId.FormatRuleApplyToRow':'Apply to row','DashboardStringId.FunctionOperatorExFunctionDescriptionGetWeekOfMonth':'GetWeekOfMonth(DateTime)\\r\\nExtracts the week of the month from the defined DateTime.','DashboardStringId.FormatConditionAppearanceGreen':'Green','DashboardStringId.CommandFormatRuleColorRangeBar':'Color Range Bar','DashboardStringId.UniqueNameValidationMessage':'A name should be unique.','DashboardStringId.MessageServerModeNotSupportedMode':'Mode is not supported in server mode for','DashboardStringId.FormatRuleInvalidRuleChanging':'Invalid Rule cannot be enabled.','DashboardStringId.MessageDashboardInternalError':'Dashboard internal error. Please contact the application vendor or your system administrator.','DashboardStringId.FunctionDescriptionRankCompetition':'RankCompetition(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the standard competition rank for the current row in the window.','DashboardStringId.FunctionDescriptionWindowDefinitionOrderDesc':'desc(column)\\r\\nData rows are sorted by values in the specified column in descending order.','DashboardStringId.RangeFilterCalculationAlongArgument':'Argument','DashboardStringId.CommandFormatRuleTopBottom':'Top/Bottom','DashboardStringId.ExcelFormat':'Excel Format','DashboardStringId.DateTimeGroupIntervalMinute':'Minute','DashboardStringId.FormatConditionAppearanceGradientYellow':'Gradient Yellow','DashboardStringId.FunctionDescriptionWindowCountDistinct':'WindowCountDistinct(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the distinct count of the expression within the window.','DashboardStringId.CardCalculationAlongCardsAndSparklineArgument':'Cards / Sparkline Argument','DashboardStringId.FunctionDescriptionWindowVar':'WindowVar(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the variance of the expression within the window.','DashboardStringId.FunctionDescriptionWindowSum':'WindowSum(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the sum of the expression within the window.','DashboardStringId.FunctionDescriptionWindowMax':'WindowMax(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the maximum of the expression within the window.','DashboardStringId.FunctionDescriptionWindowMin':'WindowMin(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the minimum of the expression within the window.','DashboardStringId.FunctionDescriptionWindowAvg':'WindowAvg(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the average of the expression within the window, which is defined using offsets from the current row.','DashboardStringId.DifferenceCalculationTargetLast':'Last','DashboardStringId.DifferenceCalculationTargetNext':'Next','DashboardStringId.MessageIncorrectMapLatitude':'The latitude should be greater than or equal to {0} and less than or equal to {1}.','DashboardStringId.DescriptionDashboardItemName':'Dashboard item name','DashboardStringId.FilterStatePresentationNone':'None','DashboardStringId.ButtonApply':'Apply','DashboardStringId.WindowFunctionValidationMessage':'Please Note: The created field can not be used as a data item. The {0} expression is valid only within the w-function or as a custom expression applied to a measure calculation.','DashboardStringId.ErrorEmptyPeriodName':'The name cannot be null or empty','DashboardStringId.SparklineTooltipStartValue':'Start:','DashboardStringId.ButtonReset':'Reset','DashboardStringId.ActionExportTo':'Export To','DevExpress.DashboardCommon.DimensionSortOrder.Ascending':'Ascending','DevExpress.DashboardCommon.DashboardParameter.AllowMultiselect':'Allow Multiselect','DevExpress.DashboardCommon.DynamicListLookUpSettings.DisplayMember':'Display Member','DevExpress.DashboardCommon.DimensionSortOrder.Descending':'Descending','DevExpress.DashboardCommon.DynamicListLookUpSettings.ValueMember':'Value Member','DevExpress.DashboardCommon.DashboardParameter.LookUpSettings':'Look-Up Settings','DevExpress.DashboardCommon.DashboardParameter.AllowNull':'Allow Null','DevExpress.DashboardCommon.DashboardParameter.SelectAllValues':'Select All Values','DevExpress.DashboardCommon.DashboardParameter.Description':'Description','DevExpress.DashboardCommon.StaticListLookUpSettings.Values':'Values','DevExpress.DashboardCommon.DynamicListLookUpSettings.SortByMember':'Sort By','DevExpress.DashboardCommon.DynamicListLookUpSettings.DataMember':'Data Member','DevExpress.DashboardCommon.DashboardParameter.Visible':'Visible','DevExpress.DashboardCommon.DynamicListLookUpSettings.SortOrder':'Sort Order','DevExpress.DashboardCommon.DynamicListLookUpSettings.DataSource':'Data Source','DashboardWebStringId.Title.ImageLinked':'Linked','DashboardWebStringId.DashboardMenu':'Dashboard Menu','DashboardWebStringId.Grid.DisplayMode.Bar':'Bar','DashboardWebStringId.Chart.Position.TopLeftHorizontal':'Top Left Horizontal','DashboardWebStringId.FormatRuleApplyToDimensionElement':'Dimension','DashboardWebStringId.InteractivityOptions.MasterFilterMode.None':'None','DashboardWebStringId.Parameters.LookUpSettingsType.NoLookUp':'No Look-Up','DashboardWebStringId.ConditionalFormatting.IconType.None':'None','DashboardWebStringId.TopNMode':'Mode','DashboardWebStringId.TopN.Top':'Top','DashboardWebStringId.Map.Viewport.CenterPointLongitude':'Center Point Longitude','DashboardWebStringId.DashboardMenuColorScheme':'Color Scheme','DashboardWebStringId.Image.BindingMode':'Binding Mode','DashboardWebStringId.LimitVisibleData.IncreasePerformanceTooltip':'This dashboard item is bound to a large data set. To increase performance, click this icon to limit visible data.','DashboardWebStringId.ColoringModeOn':'On','DashboardWebStringId.Calculations.RankOrder':'Rank Order','DashboardWebStringId.ConditionalFormatting.ConditionMaximum':'Maximum','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGrayDownInclineArrow':'Directional Gray Down Incline Arrow','DashboardWebStringId.Treemap.TileLabelsValue':'Value','DashboardWebStringId.ButtonHidden':'Hidden','DashboardWebStringId.Treemap.TileLabelsNone':'None','DashboardWebStringId.Image.BindingMode.BinaryArray':'Binary Array','DashboardWebStringId.Calculations.Moving':'Moving of','DashboardWebStringId.Gauge.Scale.Custom':'Custom','DashboardWebStringId.Image.BindingMode.Uri':'Uri','DashboardWebStringId.PivotGrid.ValuesPositionRows':'Rows','DashboardWebStringId.Map.Viewport.CreateViewerPaddings':'Create Viewer Paddings','DashboardWebStringId.Notification.DashboardCanNotBeSaved':'The dashboard cannot be saved','DashboardWebStringId.InteractivityOptions.TargetDimensions.Series':'Series','DashboardWebStringId.Binding.TooltipMeasures':'Tooltip Measures','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalYellowSideArrow':'Directional Yellow Side Arrow','DashboardWebStringId.DataSources.EditCalculatedField':'Edit Calculated Field','DashboardWebStringId.ConditionalFormatting.IconType.ShapeYellowTriangle':'Shape Yellow Triangle','DashboardWebStringId.Grid.Options':'Grid Options','DashboardWebStringId.Chart.Position.BottomRightVertical':'Bottom Right Vertical','DashboardWebStringId.EditInDesigner':'Edit in Designer','DashboardWebStringId.DashboardMenuNew':'New...','DashboardWebStringId.Colorization.NoSelectedSchema':'Select a color scheme to edit','DashboardWebStringId.Currency.DefaultCurrencyWarning':'The currency culture format is based on environmental settings. Specify the culture explicitly to ignore these settings.','DashboardWebStringId.CardLayout.MaxWidth':'Max Width','DashboardWebStringId.ConditionalFormatting.DatesOccurringBeyondThisYear':'Following this year','DashboardWebStringId.PivotGrid.RowGrandTotals':'Row Grand Totals','DashboardWebStringId.Add':'Add','DashboardWebStringId.Pie':'Pie','DashboardWebStringId.ConditionalFormatting.Appearance.ForeColor':'Fore Color','DashboardWebStringId.PivotGrid.RowTotalsPosition':'Row Totals Position','DashboardWebStringId.InteractivityOptions.TargetDimensions.Points':'Points','DashboardWebStringId.Title.Aligment.Center':'Center','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorRedCross':'Indicator Red Cross','DashboardWebStringId.Chart.ShowPointMarkers':'Show point markers','DashboardWebStringId.DataSources.CreateDataSource':'Create','DashboardWebStringId.ColoringOptions':'Coloring','DashboardWebStringId.Grid.FilterClause.EndsWith':'Ends with','DashboardWebStringId.Notification.UnsupportedDataSourceType':'Unsupported data source type','DashboardWebStringId.DataSources.OK':'OK','DashboardWebStringId.Chart.AxisYMeasure':'Axis Y Measure','DashboardWebStringId.AccordionTab.Common':'Common','DashboardWebStringId.Map.Position.TopRight':'Top Right','DashboardWebStringId.Pie.Type':'Pie Type','DashboardWebStringId.ConditionalFormatting.SegmentNumber':'Segment Number','DashboardWebStringId.Binding.ValuesPattern':'Values {0}','DashboardWebStringId.ButtonNo':'NO','DashboardWebStringId.ButtonOn':'ON','DashboardWebStringId.Pie.LabelPositionInside':'Inside','DashboardWebStringId.PivotGrid.LayoutTypeCompact':'Compact','DashboardWebStringId.InteractivityOptions.TargetDimensions':'Target Dimensions','DashboardWebStringId.Cards.LineCount':'Line Count','DashboardWebStringId.Map.TooltipActualValueCaption':'Tooltip Actual Value Caption','DashboardWebStringId.Map.TooltipAttribute':'Tooltip Attribute','DashboardWebStringId.TilesTooltipContentType':'Tile Tooltip','DashboardWebStringId.RangeFilter.UriPattern':'Uri Pattern','DashboardWebStringId.Parameters.LookUpSettingsTypeCaption':'Look-Up Settings Type','DashboardWebStringId.PivotGrid.LayoutTypeTabular':'Tabular','DashboardWebStringId.FormatType':'Format Type','DashboardWebStringId.Dialog.ConfirmSaving':'Confirm saving','DashboardWebStringId.FormatRule':'Format Rule','DashboardWebStringId.Card.SparklineVisible':'Sparkline Visible','DashboardWebStringId.Tabs.Binding':'Binding','DashboardWebStringId.Grid.ColumnHeaders':'Column Headers','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorGreenCheck':'Indicator Green Check','DashboardWebStringId.Map.CustomMapUrl':'Custom Map Url','DashboardWebStringId.RangeFilter.Flow':'Flow','DashboardWebStringId.RangeFilter.None':'None','DashboardWebStringId.Binding.ConfigureMeasure':'Configure Measure','DashboardWebStringId.DashboardMenuCurrency':'Currency','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGrayUpInclineArrow':'Directional Gray Up Incline Arrow','DashboardWebStringId.PivotGrid.RowTotals':'Row Totals','DashboardWebStringId.Calculations.RankType':'Rank Type','DashboardWebStringId.MasterFilterMode':'Master Filter Mode','DashboardWebStringId.PivotGrid.RowTotalsPositionBottom':'Bottom','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGreenArrowUp':'Directional Green Arrow Up','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalRedTriangleDown':'Directional Red Triangle Down','DashboardWebStringId.Grid.DisplayMode.Text':'Text','DashboardWebStringId.Binding.SetColor':'Set Color','DashboardWebStringId.Gauge.Captions':'Show Gauge Captions','DashboardWebStringId.Grid.Delta':'Delta','DashboardWebStringId.Chart.LogarithmicScaleBase5':'5','DashboardWebStringId.Chart.LogarithmicScaleBase2':'2','DashboardWebStringId.Binding.SetValue':'Set Value','DashboardWebStringId.Notification.AttemptToLoadParameterValues':'An error occurred during an attempt to load parameter values for the data source ','DashboardWebStringId.DesignerToolbar.LayoutDimensionValidationError':'The value should be between {0} and {1}','DashboardWebStringId.DashboardMenuNewDashboardCreate':'Create','DashboardWebStringId.DateFilter.FilterTypeExact':'Exact','DashboardWebStringId.Grid.FilterClause.LessOrEqual':'Less than or equal to','DashboardWebStringId.Coloring.Local':'Local','DashboardWebStringId.DateFilter.FilterTypeAfter':'After','DashboardWebStringId.Map.Area.WorldCountries':'World Countries','DashboardWebStringId.ConditionalFormatting.IconType.Rating1Bar':'Rating 1 Bar','DashboardWebStringId.Binding.AddMap':'Add Map','DashboardWebStringId.Binding.AddRow':'Add Row','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGraySideArrow':'Directional Gray Side Arrow','DashboardWebStringId.PivotGrid.ColumnTotalsPosition':'Column Totals Position','DashboardWebStringId.Grid.FilterClause.BetweenEnd':'End','DashboardWebStringId.Map.CustomMapOptionsSource':'Source','DashboardWebStringId.ConditionalFormatting.FontStyle':'Font Style','DashboardWebStringId.Cards.ArrangementMode.Auto':'Auto','DashboardWebStringId.DataSources.CreateNewDataSource':'Create data source...','DashboardWebStringId.Notification.AttemptToLoadDashboards':'An error occurred during an attempt to load the list of available dashboards','DashboardWebStringId.CollectionEditor.Totals.NoItems':'Click + to add a new total.','DashboardWebStringId.InteractivityOptions':'Interactivity Options','DashboardWebStringId.DataSources.RenameDataSource':'Rename Data Source','DashboardWebStringId.Chart.AxisXMeasure':'Axis X Measure','DashboardWebStringId.Map.Viewport.RightLongitude':'Right Longitude','DashboardWebStringId.Errors.AttemptToLoadData':'An error occurred during an attempt to load data','DashboardWebStringId.Binding.ConfigureAttribute':'Configure Attribute','DashboardWebStringId.ConditionalFormatting.DatesOccurringEarlier':'Prior to the month 6 months ago','DashboardWebStringId.Grid.WidthType.FitToContent':'Fit To Content','DashboardWebStringId.Chart.Orientation.RotateLeft':'Rotate Left','DashboardWebStringId.Sparkline.HighlightMinMaxPoints':'Highlight Min/Max Points','DashboardWebStringId.Image.Alignment.Bottom':'Bottom','DashboardWebStringId.ConditionalFormatting.DateType':'Date Type','DashboardWebStringId.WeightedLegendGalleryGroup':'Position','DashboardWebStringId.Dashboard.Groups':'Groups','DashboardWebStringId.Binding.Attribute':'Attribute','DashboardWebStringId.Notification.AttemptToGetColorScheme':'An error occurred during an attempt to get the color scheme','DashboardWebStringId.Image.Alignment.Center':'Center','DashboardWebStringId.DataSources.NoAvailableDataSources':'There are no available datasources.','DashboardWebStringId.Pie.LabelContentType.ArgumentAndPercent':'Argument And Percent','DashboardWebStringId.Dialog.ArgumentMode':'Axis Type','DashboardWebStringId.DataSources.Rename':'Rename','DashboardWebStringId.DimensionSortBy':'Sort by','DashboardWebStringId.Filters':'Filters','DashboardWebStringId.Notification.MethodIsNotAllowedInViewerMode':'This method is not allowed in the viewer mode','DashboardWebStringId.ConditionalFormatting.IntersectionRowDimension':'Intersection Row Dimension','DashboardWebStringId.Chart.Position.Inside':'Inside','DashboardWebStringId.PivotGrid.LayoutType':'Layout','DashboardWebStringId.Binding.RemovePane':'Remove Pane','DashboardWebStringId.Map.TooltipCaption':'Tooltip Caption','DashboardWebStringId.Currency.Currency':'Currency','DashboardWebStringId.Map.Position.BottomLeft':'Bottom Left','DashboardWebStringId.ConditionalFormatting.IconType.Rating2FilledBoxes':'Rating 2 Filled Boxes','DashboardWebStringId.Treemap.GroupTooltipsValue':'Value','DashboardWebStringId.Map.Viewport':'Viewport','DashboardWebStringId.Map.CustomMapOptionsFile':'File','DashboardWebStringId.ConditionalFormatting.IconType.RatingEmptyGrayCircle':'Rating Empty Gray Circle','DashboardWebStringId.Notification.AttemptToLoadDimensionUniqueValues':'An error occurred during an attempt to load dimension unique values for the data source ','DashboardWebStringId.MobileLayout.SwitchToViewer':'You have opened the Web Dashboard in the Designer mode. The control supports a mobile layout only if it works in the Viewer mode. Do you want to switch to the Viewer mode?','DashboardWebStringId.Map.Position.TopCenter':'Top Center','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorRedFlag':'Indicator Red Flag','DashboardWebStringId.Treemap.GroupTooltipsArgument':'Argument','DashboardWebStringId.ConditionalFormatting.IconType.RatingFullGrayStar':'Rating Full Gray Star','DashboardWebStringId.Title.Aligment':'Alignment','DashboardWebStringId.DataSources.CalculatedField.Corrupted':'The calculated field contains errors','DashboardWebStringId.Grid.WidthType':'Width Type','DashboardWebStringId.ConditionalFormatting.DatesOccurringNone':'None','DashboardWebStringId.Treemap.TileTooltipsNone':'None','DashboardWebStringId.Pie.LabelContentType.Argument':'Argument','DashboardWebStringId.ConditionalFormatting.IconType.RatingFullGrayCircle':'Rating Full Gray Circle','DashboardWebStringId.Binding.ConfigureColumn':'Configure Column','DashboardWebStringId.Binding.SetArgument':'Set Argument','DashboardWebStringId.Map.ShapeTitleAttribute':'Shape Title Attribute','DashboardWebStringId.ConditionalFormatting.DatesOccurringYesterday':'Yesterday','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalYellowDownInclineArrow':'Directional Yellow Down Incline Arrow','DashboardWebStringId.Interactivity':'Interactivity','DashboardWebStringId.AccordionTab.WeightedLegend':'Weighted Legend','DashboardWebStringId.Treemap.SquarifiedLayoutAlgorithm':'Squarified','DashboardWebStringId.ConditionalFormatting.IconType.RatingEmptyGrayStar':'Rating Empty Gray Star','DashboardWebStringId.AccordionTab.MeasureFilter':'Filter','DashboardWebStringId.Chart.OverlappingMode':'Overlapping Mode','DevExpressWebStringId.CalculatedFieldDataType':'Data Type','DashboardWebStringId.DashboardItemMenu.Bindings.ChangedDataSourceMessage':'The data source for the {0} item was changed to {1}','DashboardWebStringId.Colorization.ColorSchemeType':'Color Scheme Type','DashboardWebStringId.Chart.IgnoreEmptyPoints':'Ignore empty points','DashboardWebStringId.Chart.Position.TopRightHorizontal':'Top Right Horizontal','DashboardWebStringId.DashboardItemMenu.Bindings.SelectDataSourceButtonTooltip':'To add a data source to the current dashboard, go to Menu | Data Sources.','DashboardWebStringId.LayoutHasBeenChangedDialogMessage':'The dashboard layout has been changed.','DashboardWebStringId.LimitVisibleData.DisplayAllDataTooltip':'This dashboard item is bound to a large dataset and does not currently display all data to retain performance. Click this button to display all data.','DashboardWebStringId.Binding.Gauges':'Gauges','DashboardWebStringId.Chart.Legend':'Legend','DashboardWebStringId.ConditionalFormatting.IconType.ShapeRedTrafficLight':'Shape Red Traffic Light','DashboardWebStringId.Chart.TooltipContent':'Tooltips','DashboardWebStringId.Cards.ArrangementMode.FixedRows':'Fixed Rows','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo4':'During the month 4 months ago','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo5':'During the month 5 months ago','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo6':'During the month 6 months ago','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo1':'Last Month','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo2':'During the month 2 months ago','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo3':'During the month 3 months ago','DashboardWebStringId.Notification.ErrorHasOccuredOn':'An error occurred during an','DashboardWebStringId.Map.Position.BottomCenter':'Bottom Center','DashboardWebStringId.Parameters.DynamicListLookUpSettings':'Dynamic List Look-Up Settings','DashboardWebStringId.ConditionalFormatting.DatesOccurringToday':'Today','DashboardWebStringId.Grid.WordWrap':'Word Wrap','DashboardWebStringId.Coloring.MeasuresColoringMode':'Measures Coloring','DashboardWebStringId.Grid.FilterClause.StartsWith':'Starts with','DashboardWebStringId.Grid.ColumnWidth':'Column Width','DashboardWebStringId.Chart.TitleText':'Title Text','DashboardWebStringId.Gauge.Type':'Gauge Type','DashboardWebStringId.Tabs.DataShaping':'Data Shaping','DashboardWebStringId.MobileLayout.Back':'Back','DashboardWebStringId.ConditionalFormatting.DatesOccurringEmpty':'Empty','DashboardWebStringId.DateFilter.ArrangementModeAutoHeight':'Auto Height','DashboardWebStringId.Map.TooltipDimensions':'Tooltip Dimensions','DashboardWebStringId.Map.Area.Asia':'Asia','DashboardWebStringId.DataSources.CalculatedField.Name':'Name','DashboardWebStringId.BindDataInvitation':'to bind this item to data','DashboardWebStringId.Treemap.TileTooltipsValue':'Value','DashboardWebStringId.DataSources.DataItems':'Data Items','DashboardWebStringId.Chart.Position.BottomLeftHorizontal':'Bottom Left Horizontal','DashboardWebStringId.Map.Orientation.Horizontal':'Horizontal','DashboardWebStringId.ConditionalFormatting.FontRegular':'Regular','DashboardWebStringId.TileOptions':'Tile Options','DashboardWebStringId.Notification.AttemptToConnectionStrings':'An error occurred during an attempt to load connection strings','DashboardWebStringId.Chart.SeriesType':'Series Type','DashboardWebStringId.Parameters.StaticListLookUpSettings':'Static List Look-Up Settings','DashboardWebStringId.Map.Area.NorthAmerica':'North 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year','DashboardWebStringId.TextBox.Text':'Text','DashboardWebStringId.Title.ImageEmbedded':'Embedded','DashboardWebStringId.Treemap.GroupTooltipsArgumentAndValue':'Argument and Value','DashboardWebStringId.FilterItem.Type':'Type','DashboardWebStringId.Treemap.SliceAndDiceLayoutAlgorithm':'Slice and Dice','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorCircledGreenCheck':'Indicator Circled Green Check','DashboardWebStringId.SaveChangesDialogMessage':'Do you want to save changes?','DashboardWebStringId.DataItem':'Data Item','DashboardWebStringId.Binding.Values':'Values','DashboardWebStringId.Binding.AddMeasure':'Add Measure','DashboardWebStringId.ConditionalFormatting.IconType':'Icon Type','DashboardWebStringId.Binding.TooltipDimensions':'Tooltip Dimensions','DashboardWebStringId.Gauge.Type.LinearHorizontal':'Linear Horizontal','DashboardWebStringId.DesignerToolbar.Height':'H:','DashboardWebStringId.Image.HorizontalAlignment':'Horizontal Alignment','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalYellowDash':'Directional Yellow Dash','DashboardWebStringId.ShowOthersValue':'Show \"Others\" Value','DashboardWebStringId.MapLockNavigation':'Lock Navigation','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGreenTriangleUp':'Directional Green Triangle Up','DashboardWebStringId.Binding.DefaultSelectedPlaceholder':'Configure {0}','DashboardWebStringId.Map.DeltaMap':'Delta Map','DashboardWebStringId.Binding.ConfigureWeight':'Configure Weight','DashboardWebStringId.Chart.SecondaryAxisY':'Secondary Axis Y','DashboardWebStringId.Grid.ManualGridColumnWidthMode':'Manual','DashboardWebStringId.Binding.AddDimension':'Add Dimension','DashboardWebStringId.FilterElementCheckedComboBoxSelected':'{0} selected','DashboardWebStringId.Parameters.ParameterNameShouldBeUnique':'A name of the parameter should be unique','DashboardWebStringId.Chart.Position':'Position','DashboardWebStringId.FormatRules':'Format Rules','DashboardWebStringId.RangeFilter.CustomPeriods':'Custom Periods','DashboardWebStringId.Binding.ConfigureValues':'Configure Values','DashboardWebStringId.Parameters.ParameterList':'Parameter List','DashboardWebStringId.Chart.Content':'Content','DashboardWebStringId.Map.Area.Europe':'Europe','DashboardWebStringId.Image.SizeMode.Stretch':'Stretch','DashboardWebStringId.Dimension.SortMode':'Sort Mode','DashboardWebStringId.ConditionalFormatting.DatesOccurringThisWeek':'This Week','DashboardWebStringId.Gauge.Type.HalfCircular':'Half Circular','DashboardWebStringId.Map.Position.TopLeft':'Top Left','DashboardWebStringId.ConditionalFormatting.AppearanceType':'Appearance Type','DashboardWebStringId.Preview':'Preview','DashboardWebStringId.Parameters.Done':'Done','DashboardWebStringId.Treemap.LayoutDirection':'Layout Direction','DashboardWebStringId.TextBoxFormatText':'Format','DashboardWebStringId.Chart.Position.TopRightVertical':'Top Right 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Base','DashboardWebStringId.Image.SizeMode.Squeeze':'Squeeze','DashboardWebStringId.Map.Viewport.CenterPointLatitude':'Center Point Latitude','DashboardWebStringId.DataItem.ShowGrandTotals':'Show Grand Totals','DashboardWebStringId.Delta.ThresholdValue':'Threshold Value','DashboardWebStringId.ColorScheme.Colors':'Colors','DashboardWebStringId.Chart.IsInsideOfDiagram':'Inside diagram','DashboardWebStringId.Gauge.Type.ThreeFourthCircular':'Three-Quarter Circular','DashboardWebStringId.ConditionalFormatting.AboveOrEqual':'Above or Equal','DashboardWebStringId.DesignerToolbar.Pixels':'px','DashboardWebStringId.Calculations.RunningTotal':'Running Total of','DashboardWebStringId.ConditionalFormatting.Appearance.BackColor':'Back Color','DashboardWebStringId.AccordionTab.MapLegend':'Color Legend','DashboardWebStringId.Calculations.Types.Moving':'Moving','DashboardWebStringId.Dashboard.ComponentName':'Component Name','DashboardWebStringId.Chart.LogarithmicScaleBase10':'10','DashboardWebStringId.Map.WeightedLegendType.Linear':'Linear','DashboardWebStringId.Title.Text':'Text','DashboardWebStringId.ConditionalFormatting.DatesOccurringLaterThisWeek':'This week, beyond tomorrow','DashboardWebStringId.ConditionalFormatting.DatesOccurringLaterThisYear':'This year, beyond this month','DashboardWebStringId.Image.VerticalAlignment':'Vertical Alignment','DashboardWebStringId.AccordionTab.PivotInitialState':'Initial State','DashboardWebStringId.Grid.BandedRows':'Banded Rows','DashboardWebStringId.Map.Area.USA':'USA','DashboardWebStringId.CardLayout.ResetTemplate':'Reset','DashboardWebStringId.Binding.DefaultEmptyPlaceholder':'Set {0}','DashboardWebStringId.Grid.Dimension':'Dimension','DashboardWebStringId.Map.WeightedLegendType.Nested':'Nested','DashboardWebStringId.Pie.LabelContentType.Percent':'Percent','DashboardWebStringId.Map.Area.Canada':'Canada','DashboardWebStringId.Title.Visible':'Visible','DashboardWebStringId.RangeFilter.EndMode':'End Mode','DashboardWebStringId.RangeFilter.EndDate':'End Date','DashboardWebStringId.GeoPointMapClusterization':'Enable Clustering','DashboardWebStringId.AccordionTab.ScatterChartPointLabelOptions':'Point Labels','DashboardWebStringId.DateFilter.ArrangementModeVertical':'Vertical','DashboardWebStringId.Map.Area.Custom':'Custom','DashboardWebStringId.Dialog.UnsupportedCalculatedField':'This data item does not support the calculated field you created. This field is available on the Data Sources page of the dashboard menu.','DashboardWebStringId.New.DashboardName':'Dashboard Name:','DashboardWebStringId.Binding.AddSeries':'Add Series','DashboardWebStringId.Calculations.DifferenceType':'Difference Type','DashboardWebStringId.Binding.Columns':'Columns','DashboardWebStringId.ConditionalFormatting.IconType.ShapeYellowCircle':'Shape Yellow Circle','DashboardWebStringId.DesignerToolbar.Width':'W:','DashboardWebStringId.ConditionalFormatting.IconType.Rating1FilledBox':'Rating 1 Filled Box','DashboardWebStringId.Grid.Hyperlink':'Hyperlink','DashboardWebStringId.Duplicate':'Duplicate current item','DashboardWebStringId.Pie.Donut':'Donut','DashboardWebStringId.Binding.ConfigureMap':'Configure Map','DashboardWebStringId.Binding.ConfigureRow':'Configure Row','DashboardWebStringId.DataSources.CalculatedField.FieldType':'Field Type','DashboardWebStringId.RangeFilter.EndIntervalAndOffset':'End Interval and Offset','DashboardWebStringId.Binding.EmptySearchResult':'Nothing was found','DashboardWebStringId.DashboardItemMenu.Bindings.SelectDataSourceButton':'Select a data source','DashboardWebStringId.PivotGrid.AutoExpandColumnGroups':'Auto-Expand Column Groups','DashboardWebStringId.Image.SizeMode.Clip':'Clip','DashboardWebStringId.Image.SizeMode.Zoom':'Zoom','DashboardWebStringId.ButtonContinuous':'Continuous','DashboardWebStringId.ConditionalFormatting.IconType.ShapeGreenCircle':'Shape Green Circle','DashboardWebStringId.Parameters.LookUpSettingsType.DynamicList':'Dynamic List','DashboardWebStringId.RangeFilter.StartIntervalAndOffset':'Start Interval and Offset','DashboardWebStringId.TilesLabelContentType':'Tile Label','DashboardWebStringId.DataItem.IncludeGroupSeparator':'Include Group Separator','DashboardWebStringId.NewDashboard':'New Dashboard','DashboardWebStringId.Map.IncludeSummaryValueToShapeTitle':'Include Summary Value','DashboardWebStringId.ConditionalFormatting.IntersectionLevelMode':'Intersection Level Mode','DashboardWebStringId.DateFilter.DatePickerLocationFar':'Far','DashboardWebStringId.Map.CustomMapFile':'Custom Map File','DashboardWebStringId.StyleSettings':'Style','DashboardWebStringId.DataSources.DataSourceNameExistsMessage':'Duplicate Name: Please enter a unique data source name to proceed.','DashboardWebStringId.Map.Viewport.LeftLongitude':'Left Longitude','DashboardWebStringId.Treemap.GroupLabelsArgumentAndValue':'Argument and Value','DashboardWebStringId.Treemap.BottomRightToTopLeftLayoutDirection':'Bottom Right - Top Left','DashboardWebStringId.Binding.SetWeight':'Set Weight','DashboardWebStringId.DashboardParameters':'Parameters','DashboardWebStringId.DisplayItemAsPage':'Display Item as Page','DashboardWebStringId.RangeFilter.Fixed':'Fixed','DashboardWebStringId.Notification.AttemptToLoadDashboard':'An error occurred during an attempt to load the dashboard ','DashboardWebStringId.FilterItem.Type.Standard':'Standard','DashboardWebStringId.ConditionalFormatting.IconType.Rating0FilledBoxes':'Rating 0 Filled Boxes','DashboardWebStringId.Colorization.MeasureNames':'Measure Names','DashboardWebStringId.Chart.Orientation':'Orientation','DashboardWebStringId.DataSources.UsedDataSources':'Used Data Sources','DashboardWebStringId.DefaultNameBubbleMapItem':'Bubble Map','DashboardWebStringId.ConditionalFormatting.Miscellaneous':'Miscellaneous','DashboardWebStringId.Notification.AttemptToConvertItemToType':'An error occurred during an attempt to convert the item to the type ','DashboardWebStringId.Calculations.WindowDefinitionModePredefined':'Predefined','DashboardWebStringId.ConditionalFormatting.AverageType':'Average Type','DashboardWebStringId.ConditionalFormatting.CalculatedBy':'Calculated by','DashboardWebStringId.Chart.LabelContent':'Data Labels','DashboardWebStringId.Calculations.Rank':'Rank of','DashboardWebStringId.Chart.AlwaysShowZeroLevel':'Always show zero level','DashboardWebStringId.FilterItem.Type.Checked':'Checked','DashboardWebStringId.ConditionalFormatting.Negative':'Negative','DashboardWebStringId.DataSources.Save':'Save','DashboardWebStringId.Binding.AddValues':'Add Values','DashboardWebStringId.DateFilter.FilterType':'Filter Type','DashboardWebStringId.Treemap.TileLabelsArgumentAndValue':'Argument and Value','DashboardWebStringId.AccordionTab.ShowTotals':'Totals','DashboardWebStringId.Calculations.WindowDefinition':'Window Definition','DashboardWebStringId.DataSources.DashboardDataSourceWizard':'Dashboard Data Source Wizard','DashboardWebStringId.CardLayout.LayoutOptions':'Layout Options','DashboardWebStringId.AddItemInvitation':'Drag an item from the Toolbox or click a button below to create a new item.','DashboardWebStringId.DataItem.Precision':'Precision','DashboardWebStringId.Treemap.GroupLabelsArgument':'Argument','DashboardWebStringId.CrossDataSourceFiltering':'Cross-Data-Source Filtering','DashboardWebStringId.ColoringModeOff':'Off','DashboardWebStringId.GroupsTooltipContentType':'Group Tooltip','DashboardWebStringId.Binding.SetLatitude':'Set Latitude','DashboardWebStringId.DashboardMenuSave':'Save','DashboardWebStringId.DashboardMenuOpen':'Open...','DashboardWebStringId.TextBoxItemEditor.DialogClose':'Close','DashboardWebStringId.Chart.AddPane':'Add Pane','DashboardWebStringId.ButtonYes':'YES','DashboardWebStringId.ButtonOff':'OFF','DashboardWebStringId.Chart.Orientation.RotateRight':'Rotate Right','DashboardWebStringId.Binding.Searching':'Start typing to search...','DashboardWebStringId.DateFilter.ArrangementModeHorizontal':'Horizontal','DashboardWebStringId.ConditionalFormatting.BarOptions':'Bar Options','DashboardWebStringId.ConditionalFormatting.Ranges':'Ranges','DashboardWebStringId.TextBoxItemEditor.DialogSaveAndClose':'Save and Close','DashboardWebStringId.Binding.ConfigureLatitude':'Configure Latitude','DashboardWebStringId.Delta.ThresholdType':'Threshold Type','DashboardWebStringId.DataSources.CalculatedField.UniqueNameError':'Calculated field should have a unique name.','DashboardWebStringId.MapLockNavigationLocked':'Locked','DashboardWebStringId.SeriesItem.SeriesDimensions':'Series Dimensions','DashboardWebStringId.ConditionalFormatting.BelowOrEqual':'Below or Equal','DashboardWebStringId.Notification.DashboardSaving':'Dashboard is saving','DashboardWebStringId.Grid.Sparkline':'Sparkline','DashboardWebStringId.Image.Alignment.Right':'Right','DashboardWebStringId.Map.WeightedLegendType':'Type','DashboardWebStringId.GroupsLabelContentType':'Group Label','DashboardWebStringId.Grid.FilterClause.ResetOperation':'Reset','DashboardWebStringId.Parameters.SortByMember':'Sort By','DashboardWebStringId.Chart.Position.TopLeftVertical':'Top Left Vertical','DashboardWebStringId.SummaryType':'Summary Type','DashboardWebStringId.DataSources.CreateDataSource.Tooltip':'Create a new data source...','DashboardWebStringId.Binding.AddArgument':'Add Argument','DashboardWebStringId.DataSources.NoUsedDataSources':'There are no used data sources in this dashboard.','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorCircledRedCross':'Indicator Circled Red Cross','DashboardWebStringId.ShowCaptionText':'Show Caption','DashboardWebStringId.TextBoxItemEditor.EditTextButton':'Edit Text','DashboardWebStringId.Parameters.Reorder':'Reorder','DashboardWebStringId.DashboardMenuNewDashboardNamePlaceholder':'Enter a dashboard name','DashboardWebStringId.Calculations.DefinitionMode':'Definition Mode','DashboardWebStringId.ConditionalFormatting.IconType.Rating2QuartersGrayCircle':'Rating 2 Quarters Gray Circle','DashboardWebStringId.Grid.FilterClause.Between':'Between','DashboardWebStringId.Grid.FilterClause.DoesNotEqual':'Does not equal','DashboardWebStringId.ConditionalFormatting.DatesOccurringEarlierThisYear':'This year, prior to this month','DashboardWebStringId.ConditionalFormatting.DatesOccurringEarlierThisWeek':'This week, prior to yesterday','DashboardWebStringId.Parameters.NoSelectedParameter':'No parameter is selected.','DashboardWebStringId.Chart.VisiblePointsCount':'Visible Points Count','DashboardWebStringId.ConditionalFormatting.DatesOccurringBeyond':'Following the month in 2 months time','DashboardWebStringId.Notification.DashboardSavingIsNotAvailable':'Saving is not available','DashboardWebStringId.TreemapLayoutAlgorithm':'Layout Algorithm','DashboardWebStringId.ConditionalFormatting.Condition':'Condition','DashboardWebStringId.Map.Viewport.TopLatitude':'Top Latitude','DashboardWebStringId.Calculations.PercentOfTotal':'Percent Of Total of','DashboardWebStringId.ConditionalFormatting.DatesOccurringEarlierThisMonth':'This month, prior to previous week','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGrayArrowUp':'Directional Gray Arrow Up','DashboardWebStringId.SaveConfirmationDialogMessage':'If you leave before saving, your changes will be lost.','DashboardWebStringId.TextBoxItemEditor.InsertField':'Insert Field','DashboardWebStringId.Binding.Sparkline':'Sparkline','DashboardWebStringId.Grid.WidthType.Weight':'Weight','DashboardWebStringId.Notification.AttemptToLoadFieldListForDataSource':'An error occurred during an attempt to load the field list for the data source ','DashboardWebStringId.Gauge.Max':'Maximum Value','DashboardWebStringId.Gauge.Min':'Minimum Value','DashboardWebStringId.Title.ImageNone':'None','DashboardWebStringId.CardLayout.MinWidth':'Min Width','DashboardWebStringId.Map.AttributeName':'Attribute Name','DashboardWebStringId.DataItem.ShowValues':'Show Values','DashboardWebStringId.ConditionalFormatting.IconType.ShapeRedDiamond':'Shape Red Diamond','DashboardWebStringId.Chart.Position.BottomCenterHorizontal':'Bottom Center Horizontal','DashboardWebStringId.Map.CustomAttributeFile':'Custom Attribute File','DashboardWebStringId.Binding.ConfigureArgument':'Configure Argument','DashboardWebStringId.Chart.PrimaryAxisY':'Primary Axis Y','DashboardWebStringId.Image.Alignment.Left':'Left','DashboardWebStringId.Dimension.GroupInterval':'Group Interval','DashboardWebStringId.MapLockNavigationUnlocked':'Unlocked','DashboardWebStringId.Coloring.Global':'Global','DashboardWebStringId.Pie.LabelContentType.None':'None','DashboardWebStringId.DateFilter.FilterTypeBefore':'Before','DashboardWebStringId.Gauge.Type.LeftQuarterCircular':'Left-Quarter Circular','DashboardWebStringId.Map.Area.SouthAmerica':'South America','DashboardWebStringId.Viewer':'Viewer','DashboardWebStringId.Gauge.Type.LinearVertical':'Linear Vertical','DashboardWebStringId.Binding.ConfigureColor':'Configure Color','DashboardWebStringId.AccordionTab.ItemFilter':'Item Filter','DashboardWebStringId.Binding.ConfigureGauge':'Configure Gauge','DashboardWebStringId.Chart.LimitVisiblePoints':'Limit visible points','DashboardWebStringId.Colorization.AddColor':'Add Color','DashboardWebStringId.Map.Position.BottomRight':'Bottom Right','DashboardWebStringId.Binding.ConfigureValue':'Configure Value','DashboardWebStringId.TopNEnabled':'Enabled','DashboardWebStringId.Grid.TotalType':'Total Type','DashboardWebStringId.Grid.FilterClause.Contains':'Contains','DashboardWebStringId.Map.ShowWeightedLegend':'Show Weighted Legend','DashboardWebStringId.DateFilter.DatePickerLocationHidden':'Hidden','DashboardWebStringId.Chart.Position.BottomRightHorizontal':'Bottom Right Horizontal','DashboardWebStringId.Grid.FilterClause.Greater':'Greater than','DashboardWebStringId.Dashboards':'Dashboards','DashboardWebStringId.Treemap.GroupLabelsNone':'None','DashboardWebStringId.CardLayout.TemplateElementsEditor':'Value/Element','DashboardWebStringId.Grid.FilterClause.Less':'Less than','DashboardWebStringId.FormatRuleApplyToTextElement':'Text','DashboardWebStringId.ConditionalFormatting.GradientRangeBar':'Gradient Range Bar','DashboardWebStringId.Cards.ArrangementMode':'Content Arrangement Mode','DashboardWebStringId.DataItem.ShowTotals':'Show Totals','DashboardWebStringId.Remove':'Remove','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorGreenFlag':'Indicator Green Flag','DashboardWebStringId.Title.IncludeMasterFilter':'Include Master Filter','DashboardWebStringId.Binding.Cards':'Cards','DashboardWebStringId.Binding.XAxis':'X-axis','DashboardWebStringId.Binding.YAxis':'Y-axis','DashboardWebStringId.Search':'Search...','DashboardWebStringId.InteractivityOptions.TargetDimensions.Arguments':'Arguments','DashboardWebStringId.Chart.Visible':'Visible','DashboardWebStringId.ConditionalFormatting.MinimumType':'Minimum Type','DashboardWebStringId.InteractivityOptions.IsMasterFilter':'Master Filter','DashboardWebStringId.ConditionalFormatting.IconType.Rating4FilledBoxes':'Rating 4 Filled Boxes','DashboardWebStringId.Binding.ConfigureCard':'Configure Card','DashboardWebStringId.Binding.SetAttribute':'Set Attribute','DashboardWebStringId.Chart.EnableZooming':'Enable Zooming','DashboardWebStringId.Pie.LabelContentType.ValueAndPercent':'Value And Percent','DashboardWebStringId.ButtonConfirm':'Confirm','DashboardWebStringId.DateFilter.ArrangementMode':'Arrangement Mode','DashboardWebStringId.Treemap.TopRightToBottomLeftLayoutDirection':'Top Right - Bottom Left','DashboardWebStringId.Grid.HorizontalLines':'Horizontal Lines','DashboardWebStringId.Calculations.DifferenceCalculation':'Difference of','DashboardWebStringId.PivotGrid.ColumnTotalsPositionFar':'Far','DashboardWebStringId.Notification.UnderlyingRequestDataNotLoaded':'The data for the \\'{0}\\' dashboard item has not been loaded yet. Please check whether the \\'getItemData\\' method call returns an initialized non-null value before you request the underlying data.','DashboardWebStringId.Chart.Position.Outside':'Outside','DashboardWebStringId.Binding.HiddenDimensions':'Hidden Dimensions','DashboardWebStringId.Map.UseBindingAttribute':'Use binding attribute','DashboardWebStringId.AccordionTab.ChartLegend':'Legend','DashboardWebStringId.Calculations.PreviousValuesCount':'Start Offset','DashboardWebStringId.Treemap.BottomLeftToTopRightLayoutDirection':'Bottom Left - Top Right','DashboardWebStringId.CardLayout.Editor.FormatOptions':'Format Options','DashboardWebStringId.Chart.Position.TopCenterHorizontal':'Top Center Horizontal','DashboardWebStringId.ConditionalFormatting.IconType.ShapeLightRedCircle':'Shape Light Red Circle','DashboardWebStringId.ConditionalFormatting.ValueComparison':'Value Comparison','DashboardWebStringId.InteractivityOptions.MasterFilterMode.Multiple':'Multiple','DashboardWebStringId.Binding.HiddenMeasures':'Hidden Measures','DashboardWebStringId.Notification.DashboardLoading':'Dashboard is loading...','DashboardWebStringId.Options.Caption':'Caption','DashboardWebStringId.Map.CustomMapOptions':'Custom Map Options','DashboardWebStringId.PivotGrid.ValuesPositionColumns':'Columns','DashboardWebStringId.Chart.Orientation.Default':'Default','DashboardWebStringId.ConditionalFormatting.IconType.ShapeRedCircle':'Shape Red Circle','DashboardWebStringId.ConvertTo':'Convert To','DashboardWebStringId.Binding.SetLongitude':'Set Longitude','DashboardWebStringId.DataSources.ChooseDataSource':'Choose the data source for the dashboard','DashboardWebStringId.ConditionalFormatting.IconType.Rating0Bars':'Rating 0 Bars','DashboardWebStringId.ColorScheme.Empty':'The current dashboard does not contain color 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-Telu-IN\",\"gor\":\"gor-Latn-ID\",\"gos\":\"gos-Latn-NL\",\"got\":\"got-Goth-UA\",\"grb\":\"grb-Latn-ZZ\",\"grc\":\"grc-Cprt-CY\",\"grc-Linb\":\"grc-Linb-GR\",\"grt\":\"grt-Beng-IN\",\"grw\":\"grw-Latn-ZZ\",\"gsw\":\"gsw-Latn-CH\",\"gu\":\"gu-Gujr-IN\",\"gub\":\"gub-Latn-BR\",\"guc\":\"guc-Latn-CO\",\"gud\":\"gud-Latn-ZZ\",\"gur\":\"gur-Latn-GH\",\"guw\":\"guw-Latn-ZZ\",\"gux\":\"gux-Latn-ZZ\",\"guz\":\"guz-Latn-KE\",\"gv\":\"gv-Latn-IM\",\"gvf\":\"gvf-Latn-ZZ\",\"gvr\":\"gvr-Deva-NP\",\"gvs\":\"gvs-Latn-ZZ\",\"gwc\":\"gwc-Arab-ZZ\",\"gwi\":\"gwi-Latn-CA\",\"gwt\":\"gwt-Arab-ZZ\",\"gyi\":\"gyi-Latn-ZZ\",\"ha\":\"ha-Latn-NG\",\"ha-CM\":\"ha-Arab-CM\",\"ha-SD\":\"ha-Arab-SD\",\"hag\":\"hag-Latn-ZZ\",\"hak\":\"hak-Hans-CN\",\"ham\":\"ham-Latn-ZZ\",\"haw\":\"haw-Latn-US\",\"haz\":\"haz-Arab-AF\",\"hbb\":\"hbb-Latn-ZZ\",\"hdy\":\"hdy-Ethi-ZZ\",\"he\":\"he-Hebr-IL\",\"hhy\":\"hhy-Latn-ZZ\",\"hi\":\"hi-Deva-IN\",\"hia\":\"hia-Latn-ZZ\",\"hif\":\"hif-Latn-FJ\",\"hig\":\"hig-Latn-ZZ\",\"hih\":\"hih-Latn-ZZ\",\"hil\":\"hil-Latn-PH\",\"hla\":\"hla-Latn-ZZ\",\"hlu\":\"hlu-Hluw-TR\",\"hmd\":\"hmd-Plrd-CN\",\"hmt\":\"hmt-Latn-ZZ\",\"hnd\":\"hnd-Arab-PK\",\"hne\":\"hne-Deva-IN\",\"hnj\":\"hnj-Hmng-LA\",\"hnn\":\"hnn-Latn-PH\",\"hno\":\"hno-Arab-PK\",\"ho\":\"ho-Latn-PG\",\"hoc\":\"hoc-Deva-IN\",\"hoj\":\"hoj-Deva-IN\",\"hot\":\"hot-Latn-ZZ\",\"hr\":\"hr-Latn-HR\",\"hsb\":\"hsb-Latn-DE\",\"hsn\":\"hsn-Hans-CN\",\"ht\":\"ht-Latn-HT\",\"hu\":\"hu-Latn-HU\",\"hui\":\"hui-Latn-ZZ\",\"hy\":\"hy-Armn-AM\",\"hz\":\"hz-Latn-NA\",\"ia\":\"ia-Latn-FR\",\"ian\":\"ian-Latn-ZZ\",\"iar\":\"iar-Latn-ZZ\",\"iba\":\"iba-Latn-MY\",\"ibb\":\"ibb-Latn-NG\",\"iby\":\"iby-Latn-ZZ\",\"ica\":\"ica-Latn-ZZ\",\"ich\":\"ich-Latn-ZZ\",\"id\":\"id-Latn-ID\",\"idd\":\"idd-Latn-ZZ\",\"idi\":\"idi-Latn-ZZ\",\"idu\":\"idu-Latn-ZZ\",\"ife\":\"ife-Latn-TG\",\"ig\":\"ig-Latn-NG\",\"igb\":\"igb-Latn-ZZ\",\"ige\":\"ige-Latn-ZZ\",\"ii\":\"ii-Yiii-CN\",\"ijj\":\"ijj-Latn-ZZ\",\"ik\":\"ik-Latn-US\",\"ikk\":\"ikk-Latn-ZZ\",\"ikt\":\"ikt-Latn-CA\",\"ikw\":\"ikw-Latn-ZZ\",\"ikx\":\"ikx-Latn-ZZ\",\"ilo\":\"ilo-Latn-PH\",\"imo\":\"imo-Latn-ZZ\",\"in\":\"in-Latn-ID\",\"inh\":\"inh-Cyrl-RU\",\"io\":\"io-Latn-001\",\"iou\":\"iou-Latn-ZZ\",\"iri\":\"iri-Latn-ZZ\",\"is\":\"is-Latn-IS\",\"it\":\"it-Latn-IT\",\"iu\":\"iu-Cans-CA\",\"iw\":\"iw-Hebr-IL\",\"iwm\":\"iwm-Latn-ZZ\",\"iws\":\"iws-Latn-ZZ\",\"izh\":\"izh-Latn-RU\",\"izi\":\"izi-Latn-ZZ\",\"ja\":\"ja-Jpan-JP\",\"jab\":\"jab-Latn-ZZ\",\"jam\":\"jam-Latn-JM\",\"jbo\":\"jbo-Latn-001\",\"jbu\":\"jbu-Latn-ZZ\",\"jen\":\"jen-Latn-ZZ\",\"jgk\":\"jgk-Latn-ZZ\",\"jgo\":\"jgo-Latn-CM\",\"ji\":\"ji-Hebr-UA\",\"jib\":\"jib-Latn-ZZ\",\"jmc\":\"jmc-Latn-TZ\",\"jml\":\"jml-Deva-NP\",\"jra\":\"jra-Latn-ZZ\",\"jut\":\"jut-Latn-DK\",\"jv\":\"jv-Latn-ID\",\"jw\":\"jw-Latn-ID\",\"ka\":\"ka-Geor-GE\",\"kaa\":\"kaa-Cyrl-UZ\",\"kab\":\"kab-Latn-DZ\",\"kac\":\"kac-Latn-MM\",\"kad\":\"kad-Latn-ZZ\",\"kai\":\"kai-Latn-ZZ\",\"kaj\":\"kaj-Latn-NG\",\"kam\":\"kam-Latn-KE\",\"kao\":\"kao-Latn-ML\",\"kbd\":\"kbd-Cyrl-RU\",\"kbm\":\"kbm-Latn-ZZ\",\"kbp\":\"kbp-Latn-ZZ\",\"kbq\":\"kbq-Latn-ZZ\",\"kbx\":\"kbx-Latn-ZZ\",\"kby\":\"kby-Arab-NE\",\"kcg\":\"kcg-Latn-NG\",\"kck\":\"kck-Latn-ZW\",\"kcl\":\"kcl-Latn-ZZ\",\"kct\":\"kct-Latn-ZZ\",\"kde\":\"kde-Latn-TZ\",\"kdh\":\"kdh-Arab-TG\",\"kdl\":\"kdl-Latn-ZZ\",\"kdt\":\"kdt-Thai-TH\",\"kea\":\"kea-Latn-CV\",\"ken\":\"ken-Latn-CM\",\"kez\":\"kez-Latn-ZZ\",\"kfo\":\"kfo-Latn-CI\",\"kfr\":\"kfr-Deva-IN\",\"kfy\":\"kfy-Deva-IN\",\"kg\":\"kg-Latn-CD\",\"kge\":\"kge-Latn-ID\",\"kgf\":\"kgf-Latn-ZZ\",\"kgp\":\"kgp-Latn-BR\",\"kha\":\"kha-Latn-IN\",\"khb\":\"khb-Talu-CN\",\"khn\":\"khn-Deva-IN\",\"khq\":\"khq-Latn-ML\",\"khs\":\"khs-Latn-ZZ\",\"kht\":\"kht-Mymr-IN\",\"khw\":\"khw-Arab-PK\",\"khz\":\"khz-Latn-ZZ\",\"ki\":\"ki-Latn-KE\",\"kij\":\"kij-Latn-ZZ\",\"kiu\":\"kiu-Latn-TR\",\"kiw\":\"kiw-Latn-ZZ\",\"kj\":\"kj-Latn-NA\",\"kjd\":\"kjd-Latn-ZZ\",\"kjg\":\"kjg-Laoo-LA\",\"kjs\":\"kjs-Latn-ZZ\",\"kjy\":\"kjy-Latn-ZZ\",\"kk\":\"kk-Cyrl-KZ\",\"kk-AF\":\"kk-Arab-AF\",\"kk-Arab\":\"kk-Arab-CN\",\"kk-CN\":\"kk-Arab-CN\",\"kk-IR\":\"kk-Arab-IR\",\"kk-MN\":\"kk-Arab-MN\",\"kkc\":\"kkc-Latn-ZZ\",\"kkj\":\"kkj-Latn-CM\",\"kl\":\"kl-Latn-GL\",\"kln\":\"kln-Latn-KE\",\"klq\":\"klq-Latn-ZZ\",\"klt\":\"klt-Latn-ZZ\",\"klx\":\"klx-Latn-ZZ\",\"km\":\"km-Khmr-KH\",\"kmb\":\"kmb-Latn-AO\",\"kmh\":\"kmh-Latn-ZZ\",\"kmo\":\"kmo-Latn-ZZ\",\"kms\":\"kms-Latn-ZZ\",\"kmu\":\"kmu-Latn-ZZ\",\"kmw\":\"kmw-Latn-ZZ\",\"kn\":\"kn-Knda-IN\",\"knf\":\"knf-Latn-GW\",\"knp\":\"knp-Latn-ZZ\",\"ko\":\"ko-Kore-KR\",\"koi\":\"koi-Cyrl-RU\",\"kok\":\"kok-Deva-IN\",\"kol\":\"kol-Latn-ZZ\",\"kos\":\"kos-Latn-FM\",\"koz\":\"koz-Latn-ZZ\",\"kpe\":\"kpe-Latn-LR\",\"kpf\":\"kpf-Latn-ZZ\",\"kpo\":\"kpo-Latn-ZZ\",\"kpr\":\"kpr-Latn-ZZ\",\"kpx\":\"kpx-Latn-ZZ\",\"kqb\":\"kqb-Latn-ZZ\",\"kqf\":\"kqf-Latn-ZZ\",\"kqs\":\"kqs-Latn-ZZ\",\"kqy\":\"kqy-Ethi-ZZ\",\"kr\":\"kr-Latn-ZZ\",\"krc\":\"krc-Cyrl-RU\",\"kri\":\"kri-Latn-SL\",\"krj\":\"krj-Latn-PH\",\"krl\":\"krl-Latn-RU\",\"krs\":\"krs-Latn-ZZ\",\"kru\":\"kru-Deva-IN\",\"ks\":\"ks-Arab-IN\",\"ksb\":\"ksb-Latn-TZ\",\"ksd\":\"ksd-Latn-ZZ\",\"ksf\":\"ksf-Latn-CM\",\"ksh\":\"ksh-Latn-DE\",\"ksj\":\"ksj-Latn-ZZ\",\"ksr\":\"ksr-Latn-ZZ\",\"ktb\":\"ktb-Ethi-ZZ\",\"ktm\":\"ktm-Latn-ZZ\",\"kto\":\"kto-Latn-ZZ\",\"ku\":\"ku-Latn-TR\",\"ku-Arab\":\"ku-Arab-IQ\",\"ku-LB\":\"ku-Arab-LB\",\"kub\":\"kub-Latn-ZZ\",\"kud\":\"kud-Latn-ZZ\",\"kue\":\"kue-Latn-ZZ\",\"kuj\":\"kuj-Latn-ZZ\",\"kum\":\"kum-Cyrl-RU\",\"kun\":\"kun-Latn-ZZ\",\"kup\":\"kup-Latn-ZZ\",\"kus\":\"kus-Latn-ZZ\",\"kv\":\"kv-Cyrl-RU\",\"kvg\":\"kvg-Latn-ZZ\",\"kvr\":\"kvr-Latn-ID\",\"kvx\":\"kvx-Arab-PK\",\"kw\":\"kw-Latn-GB\",\"kwj\":\"kwj-Latn-ZZ\",\"kwo\":\"kwo-Latn-ZZ\",\"kxa\":\"kxa-Latn-ZZ\",\"kxc\":\"kxc-Ethi-ZZ\",\"kxm\":\"kxm-Thai-TH\",\"kxp\":\"kxp-Arab-PK\",\"kxw\":\"kxw-Latn-ZZ\",\"kxz\":\"kxz-Latn-ZZ\",\"ky\":\"ky-Cyrl-KG\",\"ky-Arab\":\"ky-Arab-CN\",\"ky-CN\":\"ky-Arab-CN\",\"ky-Latn\":\"ky-Latn-TR\",\"ky-TR\":\"ky-Latn-TR\",\"kye\":\"kye-Latn-ZZ\",\"kyx\":\"kyx-Latn-ZZ\",\"kzr\":\"kzr-Latn-ZZ\",\"la\":\"la-Latn-VA\",\"lab\":\"lab-Lina-GR\",\"lad\":\"lad-Hebr-IL\",\"lag\":\"lag-Latn-TZ\",\"lah\":\"lah-Arab-PK\",\"laj\":\"laj-Latn-UG\",\"las\":\"las-Latn-ZZ\",\"lb\":\"lb-Latn-LU\",\"lbe\":\"lbe-Cyrl-RU\",\"lbu\":\"lbu-Latn-ZZ\",\"lbw\":\"lbw-Latn-ID\",\"lcm\":\"lcm-Latn-ZZ\",\"lcp\":\"lcp-Thai-CN\",\"ldb\":\"ldb-Latn-ZZ\",\"led\":\"led-Latn-ZZ\",\"lee\":\"lee-Latn-ZZ\",\"lem\":\"lem-Latn-ZZ\",\"lep\":\"lep-Lepc-IN\",\"leq\":\"leq-Latn-ZZ\",\"leu\":\"leu-Latn-ZZ\",\"lez\":\"lez-Cyrl-RU\",\"lg\":\"lg-Latn-UG\",\"lgg\":\"lgg-Latn-ZZ\",\"li\":\"li-Latn-NL\",\"lia\":\"lia-Latn-ZZ\",\"lid\":\"lid-Latn-ZZ\",\"lif\":\"lif-Deva-NP\",\"lif-Limb\":\"lif-Limb-IN\",\"lig\":\"lig-Latn-ZZ\",\"lih\":\"lih-Latn-ZZ\",\"lij\":\"lij-Latn-IT\",\"lis\":\"lis-Lisu-CN\",\"ljp\":\"ljp-Latn-ID\",\"lki\":\"lki-Arab-IR\",\"lkt\":\"lkt-Latn-US\",\"lle\":\"lle-Latn-ZZ\",\"lln\":\"lln-Latn-ZZ\",\"lmn\":\"lmn-Telu-IN\",\"lmo\":\"lmo-Latn-IT\",\"lmp\":\"lmp-Latn-ZZ\",\"ln\":\"ln-Latn-CD\",\"lns\":\"lns-Latn-ZZ\",\"lnu\":\"lnu-Latn-ZZ\",\"lo\":\"lo-Laoo-LA\",\"loj\":\"loj-Latn-ZZ\",\"lok\":\"lok-Latn-ZZ\",\"lol\":\"lol-Latn-CD\",\"lor\":\"lor-Latn-ZZ\",\"los\":\"los-Latn-ZZ\",\"loz\":\"loz-Latn-ZM\",\"lrc\":\"lrc-Arab-IR\",\"lt\":\"lt-Latn-LT\",\"ltg\":\"ltg-Latn-LV\",\"lu\":\"lu-Latn-CD\",\"lua\":\"lua-Latn-CD\",\"luo\":\"luo-Latn-KE\",\"luy\":\"luy-Latn-KE\",\"luz\":\"luz-Arab-IR\",\"lv\":\"lv-Latn-LV\",\"lwl\":\"lwl-Thai-TH\",\"lzh\":\"lzh-Hans-CN\",\"lzz\":\"lzz-Latn-TR\",\"mad\":\"mad-Latn-ID\",\"maf\":\"maf-Latn-CM\",\"mag\":\"mag-Deva-IN\",\"mai\":\"mai-Deva-IN\",\"mak\":\"mak-Latn-ID\",\"man\":\"man-Latn-GM\",\"man-GN\":\"man-Nkoo-GN\",\"man-Nkoo\":\"man-Nkoo-GN\",\"mas\":\"mas-Latn-KE\",\"maw\":\"maw-Latn-ZZ\",\"maz\":\"maz-Latn-MX\",\"mbh\":\"mbh-Latn-ZZ\",\"mbo\":\"mbo-Latn-ZZ\",\"mbq\":\"mbq-Latn-ZZ\",\"mbu\":\"mbu-Latn-ZZ\",\"mbw\":\"mbw-Latn-ZZ\",\"mci\":\"mci-Latn-ZZ\",\"mcp\":\"mcp-Latn-ZZ\",\"mcq\":\"mcq-Latn-ZZ\",\"mcr\":\"mcr-Latn-ZZ\",\"mcu\":\"mcu-Latn-ZZ\",\"mda\":\"mda-Latn-ZZ\",\"mde\":\"mde-Arab-ZZ\",\"mdf\":\"mdf-Cyrl-RU\",\"mdh\":\"mdh-Latn-PH\",\"mdj\":\"mdj-Latn-ZZ\",\"mdr\":\"mdr-Latn-ID\",\"mdx\":\"mdx-Ethi-ZZ\",\"med\":\"med-Latn-ZZ\",\"mee\":\"mee-Latn-ZZ\",\"mek\":\"mek-Latn-ZZ\",\"men\":\"men-Latn-SL\",\"mer\":\"mer-Latn-KE\",\"met\":\"met-Latn-ZZ\",\"meu\":\"meu-Latn-ZZ\",\"mfa\":\"mfa-Arab-TH\",\"mfe\":\"mfe-Latn-MU\",\"mfn\":\"mfn-Latn-ZZ\",\"mfo\":\"mfo-Latn-ZZ\",\"mfq\":\"mfq-Latn-ZZ\",\"mg\":\"mg-Latn-MG\",\"mgh\":\"mgh-Latn-MZ\",\"mgl\":\"mgl-Latn-ZZ\",\"mgo\":\"mgo-Latn-CM\",\"mgp\":\"mgp-Deva-NP\",\"mgy\":\"mgy-Latn-TZ\",\"mh\":\"mh-Latn-MH\",\"mhi\":\"mhi-Latn-ZZ\",\"mhl\":\"mhl-Latn-ZZ\",\"mi\":\"mi-Latn-NZ\",\"mif\":\"mif-Latn-ZZ\",\"min\":\"min-Latn-ID\",\"mis\":\"mis-Hatr-IQ\",\"miw\":\"miw-Latn-ZZ\",\"mk\":\"mk-Cyrl-MK\",\"mki\":\"mki-Arab-ZZ\",\"mkl\":\"mkl-Latn-ZZ\",\"mkp\":\"mkp-Latn-ZZ\",\"mkw\":\"mkw-Latn-ZZ\",\"ml\":\"ml-Mlym-IN\",\"mle\":\"mle-Latn-ZZ\",\"mlp\":\"mlp-Latn-ZZ\",\"mls\":\"mls-Latn-SD\",\"mmo\":\"mmo-Latn-ZZ\",\"mmu\":\"mmu-Latn-ZZ\",\"mmx\":\"mmx-Latn-ZZ\",\"mn\":\"mn-Cyrl-MN\",\"mn-CN\":\"mn-Mong-CN\",\"mn-Mong\":\"mn-Mong-CN\",\"mna\":\"mna-Latn-ZZ\",\"mnf\":\"mnf-Latn-ZZ\",\"mni\":\"mni-Beng-IN\",\"mnw\":\"mnw-Mymr-MM\",\"moa\":\"moa-Latn-ZZ\",\"moe\":\"moe-Latn-CA\",\"moh\":\"moh-Latn-CA\",\"mos\":\"mos-Latn-BF\",\"mox\":\"mox-Latn-ZZ\",\"mpp\":\"mpp-Latn-ZZ\",\"mps\":\"mps-Latn-ZZ\",\"mpt\":\"mpt-Latn-ZZ\",\"mpx\":\"mpx-Latn-ZZ\",\"mql\":\"mql-Latn-ZZ\",\"mr\":\"mr-Deva-IN\",\"mrd\":\"mrd-Deva-NP\",\"mrj\":\"mrj-Cyrl-RU\",\"mro\":\"mro-Mroo-BD\",\"ms\":\"ms-Latn-MY\",\"ms-CC\":\"ms-Arab-CC\",\"ms-ID\":\"ms-Arab-ID\",\"mt\":\"mt-Latn-MT\",\"mtc\":\"mtc-Latn-ZZ\",\"mtf\":\"mtf-Latn-ZZ\",\"mti\":\"mti-Latn-ZZ\",\"mtr\":\"mtr-Deva-IN\",\"mua\":\"mua-Latn-CM\",\"mur\":\"mur-Latn-ZZ\",\"mus\":\"mus-Latn-US\",\"mva\":\"mva-Latn-ZZ\",\"mvn\":\"mvn-Latn-ZZ\",\"mvy\":\"mvy-Arab-PK\",\"mwk\":\"mwk-Latn-ML\",\"mwr\":\"mwr-Deva-IN\",\"mwv\":\"mwv-Latn-ID\",\"mxc\":\"mxc-Latn-ZW\",\"mxm\":\"mxm-Latn-ZZ\",\"my\":\"my-Mymr-MM\",\"myk\":\"myk-Latn-ZZ\",\"mym\":\"mym-Ethi-ZZ\",\"myv\":\"myv-Cyrl-RU\",\"myw\":\"myw-Latn-ZZ\",\"myx\":\"myx-Latn-UG\",\"myz\":\"myz-Mand-IR\",\"mzk\":\"mzk-Latn-ZZ\",\"mzm\":\"mzm-Latn-ZZ\",\"mzn\":\"mzn-Arab-IR\",\"mzp\":\"mzp-Latn-ZZ\",\"mzw\":\"mzw-Latn-ZZ\",\"mzz\":\"mzz-Latn-ZZ\",\"na\":\"na-Latn-NR\",\"nac\":\"nac-Latn-ZZ\",\"naf\":\"naf-Latn-ZZ\",\"nak\":\"nak-Latn-ZZ\",\"nan\":\"nan-Hans-CN\",\"nap\":\"nap-Latn-IT\",\"naq\":\"naq-Latn-NA\",\"nas\":\"nas-Latn-ZZ\",\"nb\":\"nb-Latn-NO\",\"nca\":\"nca-Latn-ZZ\",\"nce\":\"nce-Latn-ZZ\",\"ncf\":\"ncf-Latn-ZZ\",\"nch\":\"nch-Latn-MX\",\"nco\":\"nco-Latn-ZZ\",\"ncu\":\"ncu-Latn-ZZ\",\"nd\":\"nd-Latn-ZW\",\"ndc\":\"ndc-Latn-MZ\",\"nds\":\"nds-Latn-DE\",\"ne\":\"ne-Deva-NP\",\"neb\":\"neb-Latn-ZZ\",\"new\":\"new-Deva-NP\",\"nex\":\"nex-Latn-ZZ\",\"nfr\":\"nfr-Latn-ZZ\",\"ng\":\"ng-Latn-NA\",\"nga\":\"nga-Latn-ZZ\",\"ngb\":\"ngb-Latn-ZZ\",\"ngl\":\"ngl-Latn-MZ\",\"nhb\":\"nhb-Latn-ZZ\",\"nhe\":\"nhe-Latn-MX\",\"nhw\":\"nhw-Latn-MX\",\"nif\":\"nif-Latn-ZZ\",\"nii\":\"nii-Latn-ZZ\",\"nij\":\"nij-Latn-ID\",\"nin\":\"nin-Latn-ZZ\",\"niu\":\"niu-Latn-NU\",\"niy\":\"niy-Latn-ZZ\",\"niz\":\"niz-Latn-ZZ\",\"njo\":\"njo-Latn-IN\",\"nkg\":\"nkg-Latn-ZZ\",\"nko\":\"nko-Latn-ZZ\",\"nl\":\"nl-Latn-NL\",\"nmg\":\"nmg-Latn-CM\",\"nmz\":\"nmz-Latn-ZZ\",\"nn\":\"nn-Latn-NO\",\"nnf\":\"nnf-Latn-ZZ\",\"nnh\":\"nnh-Latn-CM\",\"nnk\":\"nnk-Latn-ZZ\",\"nnm\":\"nnm-Latn-ZZ\",\"no\":\"no-Latn-NO\",\"nod\":\"nod-Lana-TH\",\"noe\":\"noe-Deva-IN\",\"non\":\"non-Runr-SE\",\"nop\":\"nop-Latn-ZZ\",\"nou\":\"nou-Latn-ZZ\",\"nqo\":\"nqo-Nkoo-GN\",\"nr\":\"nr-Latn-ZA\",\"nrb\":\"nrb-Latn-ZZ\",\"nsk\":\"nsk-Cans-CA\",\"nsn\":\"nsn-Latn-ZZ\",\"nso\":\"nso-Latn-ZA\",\"nss\":\"nss-Latn-ZZ\",\"ntm\":\"ntm-Latn-ZZ\",\"ntr\":\"ntr-Latn-ZZ\",\"nui\":\"nui-Latn-ZZ\",\"nup\":\"nup-Latn-ZZ\",\"nus\":\"nus-Latn-SS\",\"nuv\":\"nuv-Latn-ZZ\",\"nux\":\"nux-Latn-ZZ\",\"nv\":\"nv-Latn-US\",\"nwb\":\"nwb-Latn-ZZ\",\"nxq\":\"nxq-Latn-CN\",\"nxr\":\"nxr-Latn-ZZ\",\"ny\":\"ny-Latn-MW\",\"nym\":\"nym-Latn-TZ\",\"nyn\":\"nyn-Latn-UG\",\"nzi\":\"nzi-Latn-GH\",\"oc\":\"oc-Latn-FR\",\"ogc\":\"ogc-Latn-ZZ\",\"okr\":\"okr-Latn-ZZ\",\"okv\":\"okv-Latn-ZZ\",\"om\":\"om-Latn-ET\",\"ong\":\"ong-Latn-ZZ\",\"onn\":\"onn-Latn-ZZ\",\"ons\":\"ons-Latn-ZZ\",\"opm\":\"opm-Latn-ZZ\",\"or\":\"or-Orya-IN\",\"oro\":\"oro-Latn-ZZ\",\"oru\":\"oru-Arab-ZZ\",\"os\":\"os-Cyrl-GE\",\"osa\":\"osa-Osge-US\",\"ota\":\"ota-Arab-ZZ\",\"otk\":\"otk-Orkh-MN\",\"ozm\":\"ozm-Latn-ZZ\",\"pa\":\"pa-Guru-IN\",\"pa-Arab\":\"pa-Arab-PK\",\"pa-PK\":\"pa-Arab-PK\",\"pag\":\"pag-Latn-PH\",\"pal\":\"pal-Phli-IR\",\"pal-Phlp\":\"pal-Phlp-CN\",\"pam\":\"pam-Latn-PH\",\"pap\":\"pap-Latn-AW\",\"pau\":\"pau-Latn-PW\",\"pbi\":\"pbi-Latn-ZZ\",\"pcd\":\"pcd-Latn-FR\",\"pcm\":\"pcm-Latn-NG\",\"pdc\":\"pdc-Latn-US\",\"pdt\":\"pdt-Latn-CA\",\"ped\":\"ped-Latn-ZZ\",\"peo\":\"peo-Xpeo-IR\",\"pex\":\"pex-Latn-ZZ\",\"pfl\":\"pfl-Latn-DE\",\"phl\":\"phl-Arab-ZZ\",\"phn\":\"phn-Phnx-LB\",\"pil\":\"pil-Latn-ZZ\",\"pip\":\"pip-Latn-ZZ\",\"pka\":\"pka-Brah-IN\",\"pko\":\"pko-Latn-KE\",\"pl\":\"pl-Latn-PL\",\"pla\":\"pla-Latn-ZZ\",\"pms\":\"pms-Latn-IT\",\"png\":\"png-Latn-ZZ\",\"pnn\":\"pnn-Latn-ZZ\",\"pnt\":\"pnt-Grek-GR\",\"pon\":\"pon-Latn-FM\",\"ppo\":\"ppo-Latn-ZZ\",\"pra\":\"pra-Khar-PK\",\"prd\":\"prd-Arab-IR\",\"prg\":\"prg-Latn-001\",\"ps\":\"ps-Arab-AF\",\"pss\":\"pss-Latn-ZZ\",\"pt\":\"pt-Latn-BR\",\"ptp\":\"ptp-Latn-ZZ\",\"puu\":\"puu-Latn-GA\",\"pwa\":\"pwa-Latn-ZZ\",\"qu\":\"qu-Latn-PE\",\"quc\":\"quc-Latn-GT\",\"qug\":\"qug-Latn-EC\",\"rai\":\"rai-Latn-ZZ\",\"raj\":\"raj-Deva-IN\",\"rao\":\"rao-Latn-ZZ\",\"rcf\":\"rcf-Latn-RE\",\"rej\":\"rej-Latn-ID\",\"rel\":\"rel-Latn-ZZ\",\"res\":\"res-Latn-ZZ\",\"rgn\":\"rgn-Latn-IT\",\"rhg\":\"rhg-Arab-ZZ\",\"ria\":\"ria-Latn-IN\",\"rif\":\"rif-Tfng-MA\",\"rif-NL\":\"rif-Latn-NL\",\"rjs\":\"rjs-Deva-NP\",\"rkt\":\"rkt-Beng-BD\",\"rm\":\"rm-Latn-CH\",\"rmf\":\"rmf-Latn-FI\",\"rmo\":\"rmo-Latn-CH\",\"rmt\":\"rmt-Arab-IR\",\"rmu\":\"rmu-Latn-SE\",\"rn\":\"rn-Latn-BI\",\"rna\":\"rna-Latn-ZZ\",\"rng\":\"rng-Latn-MZ\",\"ro\":\"ro-Latn-RO\",\"rob\":\"rob-Latn-ID\",\"rof\":\"rof-Latn-TZ\",\"roo\":\"roo-Latn-ZZ\",\"rro\":\"rro-Latn-ZZ\",\"rtm\":\"rtm-Latn-FJ\",\"ru\":\"ru-Cyrl-RU\",\"rue\":\"rue-Cyrl-UA\",\"rug\":\"rug-Latn-SB\",\"rw\":\"rw-Latn-RW\",\"rwk\":\"rwk-Latn-TZ\",\"rwo\":\"rwo-Latn-ZZ\",\"ryu\":\"ryu-Kana-JP\",\"sa\":\"sa-Deva-IN\",\"saf\":\"saf-Latn-GH\",\"sah\":\"sah-Cyrl-RU\",\"saq\":\"saq-Latn-KE\",\"sas\":\"sas-Latn-ID\",\"sat\":\"sat-Latn-IN\",\"sav\":\"sav-Latn-SN\",\"saz\":\"saz-Saur-IN\",\"sba\":\"sba-Latn-ZZ\",\"sbe\":\"sbe-Latn-ZZ\",\"sbp\":\"sbp-Latn-TZ\",\"sc\":\"sc-Latn-IT\",\"sck\":\"sck-Deva-IN\",\"scl\":\"scl-Arab-ZZ\",\"scn\":\"scn-Latn-IT\",\"sco\":\"sco-Latn-GB\",\"scs\":\"scs-Latn-CA\",\"sd\":\"sd-Arab-PK\",\"sd-Deva\":\"sd-Deva-IN\",\"sd-Khoj\":\"sd-Khoj-IN\",\"sd-Sind\":\"sd-Sind-IN\",\"sdc\":\"sdc-Latn-IT\",\"sdh\":\"sdh-Arab-IR\",\"se\":\"se-Latn-NO\",\"sef\":\"sef-Latn-CI\",\"seh\":\"seh-Latn-MZ\",\"sei\":\"sei-Latn-MX\",\"ses\":\"ses-Latn-ML\",\"sg\":\"sg-Latn-CF\",\"sga\":\"sga-Ogam-IE\",\"sgs\":\"sgs-Latn-LT\",\"sgw\":\"sgw-Ethi-ZZ\",\"sgz\":\"sgz-Latn-ZZ\",\"shi\":\"shi-Tfng-MA\",\"shk\":\"shk-Latn-ZZ\",\"shn\":\"shn-Mymr-MM\",\"shu\":\"shu-Arab-ZZ\",\"si\":\"si-Sinh-LK\",\"sid\":\"sid-Latn-ET\",\"sig\":\"sig-Latn-ZZ\",\"sil\":\"sil-Latn-ZZ\",\"sim\":\"sim-Latn-ZZ\",\"sjr\":\"sjr-Latn-ZZ\",\"sk\":\"sk-Latn-SK\",\"skc\":\"skc-Latn-ZZ\",\"skr\":\"skr-Arab-PK\",\"sks\":\"sks-Latn-ZZ\",\"sl\":\"sl-Latn-SI\",\"sld\":\"sld-Latn-ZZ\",\"sli\":\"sli-Latn-PL\",\"sll\":\"sll-Latn-ZZ\",\"sly\":\"sly-Latn-ID\",\"sm\":\"sm-Latn-WS\",\"sma\":\"sma-Latn-SE\",\"smj\":\"smj-Latn-SE\",\"smn\":\"smn-Latn-FI\",\"smp\":\"smp-Samr-IL\",\"smq\":\"smq-Latn-ZZ\",\"sms\":\"sms-Latn-FI\",\"sn\":\"sn-Latn-ZW\",\"snc\":\"snc-Latn-ZZ\",\"snk\":\"snk-Latn-ML\",\"snp\":\"snp-Latn-ZZ\",\"snx\":\"snx-Latn-ZZ\",\"sny\":\"sny-Latn-ZZ\",\"so\":\"so-Latn-SO\",\"sok\":\"sok-Latn-ZZ\",\"soq\":\"soq-Latn-ZZ\",\"sou\":\"sou-Thai-TH\",\"soy\":\"soy-Latn-ZZ\",\"spd\":\"spd-Latn-ZZ\",\"spl\":\"spl-Latn-ZZ\",\"sps\":\"sps-Latn-ZZ\",\"sq\":\"sq-Latn-AL\",\"sr\":\"sr-Cyrl-RS\",\"sr-ME\":\"sr-Latn-ME\",\"sr-RO\":\"sr-Latn-RO\",\"sr-RU\":\"sr-Latn-RU\",\"sr-TR\":\"sr-Latn-TR\",\"srb\":\"srb-Sora-IN\",\"srn\":\"srn-Latn-SR\",\"srr\":\"srr-Latn-SN\",\"srx\":\"srx-Deva-IN\",\"ss\":\"ss-Latn-ZA\",\"ssd\":\"ssd-Latn-ZZ\",\"ssg\":\"ssg-Latn-ZZ\",\"ssy\":\"ssy-Latn-ER\",\"st\":\"st-Latn-ZA\",\"stk\":\"stk-Latn-ZZ\",\"stq\":\"stq-Latn-DE\",\"su\":\"su-Latn-ID\",\"sua\":\"sua-Latn-ZZ\",\"sue\":\"sue-Latn-ZZ\",\"suk\":\"suk-Latn-TZ\",\"sur\":\"sur-Latn-ZZ\",\"sus\":\"sus-Latn-GN\",\"sv\":\"sv-Latn-SE\",\"sw\":\"sw-Latn-TZ\",\"swb\":\"swb-Arab-YT\",\"swc\":\"swc-Latn-CD\",\"swg\":\"swg-Latn-DE\",\"swp\":\"swp-Latn-ZZ\",\"swv\":\"swv-Deva-IN\",\"sxn\":\"sxn-Latn-ID\",\"sxw\":\"sxw-Latn-ZZ\",\"syl\":\"syl-Beng-BD\",\"syr\":\"syr-Syrc-IQ\",\"szl\":\"szl-Latn-PL\",\"ta\":\"ta-Taml-IN\",\"taj\":\"taj-Deva-NP\",\"tal\":\"tal-Latn-ZZ\",\"tan\":\"tan-Latn-ZZ\",\"taq\":\"taq-Latn-ZZ\",\"tbc\":\"tbc-Latn-ZZ\",\"tbd\":\"tbd-Latn-ZZ\",\"tbf\":\"tbf-Latn-ZZ\",\"tbg\":\"tbg-Latn-ZZ\",\"tbo\":\"tbo-Latn-ZZ\",\"tbw\":\"tbw-Latn-PH\",\"tbz\":\"tbz-Latn-ZZ\",\"tci\":\"tci-Latn-ZZ\",\"tcy\":\"tcy-Knda-IN\",\"tdd\":\"tdd-Tale-CN\",\"tdg\":\"tdg-Deva-NP\",\"tdh\":\"tdh-Deva-NP\",\"te\":\"te-Telu-IN\",\"ted\":\"ted-Latn-ZZ\",\"tem\":\"tem-Latn-SL\",\"teo\":\"teo-Latn-UG\",\"tet\":\"tet-Latn-TL\",\"tfi\":\"tfi-Latn-ZZ\",\"tg\":\"tg-Cyrl-TJ\",\"tg-Arab\":\"tg-Arab-PK\",\"tg-PK\":\"tg-Arab-PK\",\"tgc\":\"tgc-Latn-ZZ\",\"tgo\":\"tgo-Latn-ZZ\",\"tgu\":\"tgu-Latn-ZZ\",\"th\":\"th-Thai-TH\",\"thl\":\"thl-Deva-NP\",\"thq\":\"thq-Deva-NP\",\"thr\":\"thr-Deva-NP\",\"ti\":\"ti-Ethi-ET\",\"tif\":\"tif-Latn-ZZ\",\"tig\":\"tig-Ethi-ER\",\"tik\":\"tik-Latn-ZZ\",\"tim\":\"tim-Latn-ZZ\",\"tio\":\"tio-Latn-ZZ\",\"tiv\":\"tiv-Latn-NG\",\"tk\":\"tk-Latn-TM\",\"tkl\":\"tkl-Latn-TK\",\"tkr\":\"tkr-Latn-AZ\",\"tkt\":\"tkt-Deva-NP\",\"tl\":\"tl-Latn-PH\",\"tlf\":\"tlf-Latn-ZZ\",\"tlx\":\"tlx-Latn-ZZ\",\"tly\":\"tly-Latn-AZ\",\"tmh\":\"tmh-Latn-NE\",\"tmy\":\"tmy-Latn-ZZ\",\"tn\":\"tn-Latn-ZA\",\"tnh\":\"tnh-Latn-ZZ\",\"to\":\"to-Latn-TO\",\"tof\":\"tof-Latn-ZZ\",\"tog\":\"tog-Latn-MW\",\"toq\":\"toq-Latn-ZZ\",\"tpi\":\"tpi-Latn-PG\",\"tpm\":\"tpm-Latn-ZZ\",\"tpz\":\"tpz-Latn-ZZ\",\"tqo\":\"tqo-Latn-ZZ\",\"tr\":\"tr-Latn-TR\",\"tru\":\"tru-Latn-TR\",\"trv\":\"trv-Latn-TW\",\"trw\":\"trw-Arab-ZZ\",\"ts\":\"ts-Latn-ZA\",\"tsd\":\"tsd-Grek-GR\",\"tsf\":\"tsf-Deva-NP\",\"tsg\":\"tsg-Latn-PH\",\"tsj\":\"tsj-Tibt-BT\",\"tsw\":\"tsw-Latn-ZZ\",\"tt\":\"tt-Cyrl-RU\",\"ttd\":\"ttd-Latn-ZZ\",\"tte\":\"tte-Latn-ZZ\",\"ttj\":\"ttj-Latn-UG\",\"ttr\":\"ttr-Latn-ZZ\",\"tts\":\"tts-Thai-TH\",\"ttt\":\"ttt-Latn-AZ\",\"tuh\":\"tuh-Latn-ZZ\",\"tul\":\"tul-Latn-ZZ\",\"tum\":\"tum-Latn-MW\",\"tuq\":\"tuq-Latn-ZZ\",\"tvd\":\"tvd-Latn-ZZ\",\"tvl\":\"tvl-Latn-TV\",\"tvu\":\"tvu-Latn-ZZ\",\"twh\":\"twh-Latn-ZZ\",\"twq\":\"twq-Latn-NE\",\"txg\":\"txg-Tang-CN\",\"ty\":\"ty-Latn-PF\",\"tya\":\"tya-Latn-ZZ\",\"tyv\":\"tyv-Cyrl-RU\",\"tzm\":\"tzm-Latn-MA\",\"ubu\":\"ubu-Latn-ZZ\",\"udm\":\"udm-Cyrl-RU\",\"ug\":\"ug-Arab-CN\",\"ug-Cyrl\":\"ug-Cyrl-KZ\",\"ug-KZ\":\"ug-Cyrl-KZ\",\"ug-MN\":\"ug-Cyrl-MN\",\"uga\":\"uga-Ugar-SY\",\"uk\":\"uk-Cyrl-UA\",\"uli\":\"uli-Latn-FM\",\"umb\":\"umb-Latn-AO\",\"und\":\"en-Latn-US\",\"und-002\":\"en-Latn-NG\",\"und-003\":\"en-Latn-US\",\"und-005\":\"pt-Latn-BR\",\"und-009\":\"en-Latn-AU\",\"und-011\":\"en-Latn-NG\",\"und-013\":\"es-Latn-MX\",\"und-014\":\"sw-Latn-TZ\",\"und-015\":\"ar-Arab-EG\",\"und-017\":\"sw-Latn-CD\",\"und-018\":\"en-Latn-ZA\",\"und-019\":\"en-Latn-US\",\"und-021\":\"en-Latn-US\",\"und-029\":\"es-Latn-CU\",\"und-030\":\"zh-Hans-CN\",\"und-034\":\"hi-Deva-IN\",\"und-035\":\"id-Latn-ID\",\"und-039\":\"it-Latn-IT\",\"und-053\":\"en-Latn-AU\",\"und-054\":\"en-Latn-PG\",\"und-057\":\"en-Latn-GU\",\"und-061\":\"sm-Latn-WS\",\"und-142\":\"zh-Hans-CN\",\"und-143\":\"uz-Latn-UZ\",\"und-145\":\"ar-Arab-SA\",\"und-150\":\"ru-Cyrl-RU\",\"und-151\":\"ru-Cyrl-RU\",\"und-154\":\"en-Latn-GB\",\"und-155\":\"de-Latn-DE\",\"und-202\":\"en-Latn-NG\",\"und-419\":\"es-Latn-419\",\"und-AD\":\"ca-Latn-AD\",\"und-Adlm\":\"ff-Adlm-GN\",\"und-AE\":\"ar-Arab-AE\",\"und-AF\":\"fa-Arab-AF\",\"und-Aghb\":\"lez-Aghb-RU\",\"und-Ahom\":\"aho-Ahom-IN\",\"und-AL\":\"sq-Latn-AL\",\"und-AM\":\"hy-Armn-AM\",\"und-AO\":\"pt-Latn-AO\",\"und-AQ\":\"und-Latn-AQ\",\"und-AR\":\"es-Latn-AR\",\"und-Arab\":\"ar-Arab-EG\",\"und-Arab-CC\":\"ms-Arab-CC\",\"und-Arab-CN\":\"ug-Arab-CN\",\"und-Arab-GB\":\"ks-Arab-GB\",\"und-Arab-ID\":\"ms-Arab-ID\",\"und-Arab-IN\":\"ur-Arab-IN\",\"und-Arab-KH\":\"cja-Arab-KH\",\"und-Arab-MN\":\"kk-Arab-MN\",\"und-Arab-MU\":\"ur-Arab-MU\",\"und-Arab-NG\":\"ha-Arab-NG\",\"und-Arab-PK\":\"ur-Arab-PK\",\"und-Arab-TG\":\"apd-Arab-TG\",\"und-Arab-TH\":\"mfa-Arab-TH\",\"und-Arab-TJ\":\"fa-Arab-TJ\",\"und-Arab-TR\":\"az-Arab-TR\",\"und-Arab-YT\":\"swb-Arab-YT\",\"und-Armi\":\"arc-Armi-IR\",\"und-Armn\":\"hy-Armn-AM\",\"und-AS\":\"sm-Latn-AS\",\"und-AT\":\"de-Latn-AT\",\"und-Avst\":\"ae-Avst-IR\",\"und-AW\":\"nl-Latn-AW\",\"und-AX\":\"sv-Latn-AX\",\"und-AZ\":\"az-Latn-AZ\",\"und-BA\":\"bs-Latn-BA\",\"und-Bali\":\"ban-Bali-ID\",\"und-Bamu\":\"bax-Bamu-CM\",\"und-Bass\":\"bsq-Bass-LR\",\"und-Batk\":\"bbc-Batk-ID\",\"und-BD\":\"bn-Beng-BD\",\"und-BE\":\"nl-Latn-BE\",\"und-Beng\":\"bn-Beng-BD\",\"und-BF\":\"fr-Latn-BF\",\"und-BG\":\"bg-Cyrl-BG\",\"und-BH\":\"ar-Arab-BH\",\"und-Bhks\":\"sa-Bhks-IN\",\"und-BI\":\"rn-Latn-BI\",\"und-BJ\":\"fr-Latn-BJ\",\"und-BL\":\"fr-Latn-BL\",\"und-BN\":\"ms-Latn-BN\",\"und-BO\":\"es-Latn-BO\",\"und-Bopo\":\"zh-Bopo-TW\",\"und-BQ\":\"pap-Latn-BQ\",\"und-BR\":\"pt-Latn-BR\",\"und-Brah\":\"pka-Brah-IN\",\"und-Brai\":\"fr-Brai-FR\",\"und-BT\":\"dz-Tibt-BT\",\"und-Bugi\":\"bug-Bugi-ID\",\"und-Buhd\":\"bku-Buhd-PH\",\"und-BV\":\"und-Latn-BV\",\"und-BY\":\"be-Cyrl-BY\",\"und-Cakm\":\"ccp-Cakm-BD\",\"und-Cans\":\"cr-Cans-CA\",\"und-Cari\":\"xcr-Cari-TR\",\"und-CD\":\"sw-Latn-CD\",\"und-CF\":\"fr-Latn-CF\",\"und-CG\":\"fr-Latn-CG\",\"und-CH\":\"de-Latn-CH\",\"und-Cham\":\"cjm-Cham-VN\",\"und-Cher\":\"chr-Cher-US\",\"und-CI\":\"fr-Latn-CI\",\"und-CL\":\"es-Latn-CL\",\"und-CM\":\"fr-Latn-CM\",\"und-CN\":\"zh-Hans-CN\",\"und-CO\":\"es-Latn-CO\",\"und-Copt\":\"cop-Copt-EG\",\"und-CP\":\"und-Latn-CP\",\"und-Cprt\":\"grc-Cprt-CY\",\"und-CR\":\"es-Latn-CR\",\"und-CU\":\"es-Latn-CU\",\"und-CV\":\"pt-Latn-CV\",\"und-CW\":\"pap-Latn-CW\",\"und-CY\":\"el-Grek-CY\",\"und-Cyrl\":\"ru-Cyrl-RU\",\"und-Cyrl-AL\":\"mk-Cyrl-AL\",\"und-Cyrl-BA\":\"sr-Cyrl-BA\",\"und-Cyrl-GE\":\"ab-Cyrl-GE\",\"und-Cyrl-GR\":\"mk-Cyrl-GR\",\"und-Cyrl-MD\":\"uk-Cyrl-MD\",\"und-Cyrl-RO\":\"bg-Cyrl-RO\",\"und-Cyrl-SK\":\"uk-Cyrl-SK\",\"und-Cyrl-TR\":\"kbd-Cyrl-TR\",\"und-Cyrl-XK\":\"sr-Cyrl-XK\",\"und-CZ\":\"cs-Latn-CZ\",\"und-DE\":\"de-Latn-DE\",\"und-Deva\":\"hi-Deva-IN\",\"und-Deva-BT\":\"ne-Deva-BT\",\"und-Deva-FJ\":\"hif-Deva-FJ\",\"und-Deva-MU\":\"bho-Deva-MU\",\"und-Deva-PK\":\"btv-Deva-PK\",\"und-DJ\":\"aa-Latn-DJ\",\"und-DK\":\"da-Latn-DK\",\"und-DO\":\"es-Latn-DO\",\"und-Dupl\":\"fr-Dupl-FR\",\"und-DZ\":\"ar-Arab-DZ\",\"und-EA\":\"es-Latn-EA\",\"und-EC\":\"es-Latn-EC\",\"und-EE\":\"et-Latn-EE\",\"und-EG\":\"ar-Arab-EG\",\"und-Egyp\":\"egy-Egyp-EG\",\"und-EH\":\"ar-Arab-EH\",\"und-Elba\":\"sq-Elba-AL\",\"und-ER\":\"ti-Ethi-ER\",\"und-ES\":\"es-Latn-ES\",\"und-ET\":\"am-Ethi-ET\",\"und-Ethi\":\"am-Ethi-ET\",\"und-EU\":\"en-Latn-GB\",\"und-EZ\":\"de-Latn-EZ\",\"und-FI\":\"fi-Latn-FI\",\"und-FO\":\"fo-Latn-FO\",\"und-FR\":\"fr-Latn-FR\",\"und-GA\":\"fr-Latn-GA\",\"und-GE\":\"ka-Geor-GE\",\"und-Geor\":\"ka-Geor-GE\",\"und-GF\":\"fr-Latn-GF\",\"und-GH\":\"ak-Latn-GH\",\"und-GL\":\"kl-Latn-GL\",\"und-Glag\":\"cu-Glag-BG\",\"und-GN\":\"fr-Latn-GN\",\"und-Gonm\":\"gon-Gonm-IN\",\"und-Goth\":\"got-Goth-UA\",\"und-GP\":\"fr-Latn-GP\",\"und-GQ\":\"es-Latn-GQ\",\"und-GR\":\"el-Grek-GR\",\"und-Gran\":\"sa-Gran-IN\",\"und-Grek\":\"el-Grek-GR\",\"und-Grek-TR\":\"bgx-Grek-TR\",\"und-GS\":\"und-Latn-GS\",\"und-GT\":\"es-Latn-GT\",\"und-Gujr\":\"gu-Gujr-IN\",\"und-Guru\":\"pa-Guru-IN\",\"und-GW\":\"pt-Latn-GW\",\"und-Hanb\":\"zh-Hanb-TW\",\"und-Hang\":\"ko-Hang-KR\",\"und-Hani\":\"zh-Hani-CN\",\"und-Hano\":\"hnn-Hano-PH\",\"und-Hans\":\"zh-Hans-CN\",\"und-Hant\":\"zh-Hant-TW\",\"und-Hatr\":\"mis-Hatr-IQ\",\"und-Hebr\":\"he-Hebr-IL\",\"und-Hebr-CA\":\"yi-Hebr-CA\",\"und-Hebr-GB\":\"yi-Hebr-GB\",\"und-Hebr-SE\":\"yi-Hebr-SE\",\"und-Hebr-UA\":\"yi-Hebr-UA\",\"und-Hebr-US\":\"yi-Hebr-US\",\"und-Hira\":\"ja-Hira-JP\",\"und-HK\":\"zh-Hant-HK\",\"und-Hluw\":\"hlu-Hluw-TR\",\"und-HM\":\"und-Latn-HM\",\"und-Hmng\":\"hnj-Hmng-LA\",\"und-HN\":\"es-Latn-HN\",\"und-HR\":\"hr-Latn-HR\",\"und-HT\":\"ht-Latn-HT\",\"und-HU\":\"hu-Latn-HU\",\"und-Hung\":\"hu-Hung-HU\",\"und-IC\":\"es-Latn-IC\",\"und-ID\":\"id-Latn-ID\",\"und-IL\":\"he-Hebr-IL\",\"und-IN\":\"hi-Deva-IN\",\"und-IQ\":\"ar-Arab-IQ\",\"und-IR\":\"fa-Arab-IR\",\"und-IS\":\"is-Latn-IS\",\"und-IT\":\"it-Latn-IT\",\"und-Ital\":\"ett-Ital-IT\",\"und-Jamo\":\"ko-Jamo-KR\",\"und-Java\":\"jv-Java-ID\",\"und-JO\":\"ar-Arab-JO\",\"und-JP\":\"ja-Jpan-JP\",\"und-Jpan\":\"ja-Jpan-JP\",\"und-Kali\":\"eky-Kali-MM\",\"und-Kana\":\"ja-Kana-JP\",\"und-KE\":\"sw-Latn-KE\",\"und-KG\":\"ky-Cyrl-KG\",\"und-KH\":\"km-Khmr-KH\",\"und-Khar\":\"pra-Khar-PK\",\"und-Khmr\":\"km-Khmr-KH\",\"und-Khoj\":\"sd-Khoj-IN\",\"und-KM\":\"ar-Arab-KM\",\"und-Knda\":\"kn-Knda-IN\",\"und-Kore\":\"ko-Kore-KR\",\"und-KP\":\"ko-Kore-KP\",\"und-KR\":\"ko-Kore-KR\",\"und-Kthi\":\"bho-Kthi-IN\",\"und-KW\":\"ar-Arab-KW\",\"und-KZ\":\"ru-Cyrl-KZ\",\"und-LA\":\"lo-Laoo-LA\",\"und-Lana\":\"nod-Lana-TH\",\"und-Laoo\":\"lo-Laoo-LA\",\"und-Latn-AF\":\"tk-Latn-AF\",\"und-Latn-AM\":\"ku-Latn-AM\",\"und-Latn-CN\":\"za-Latn-CN\",\"und-Latn-CY\":\"tr-Latn-CY\",\"und-Latn-DZ\":\"fr-Latn-DZ\",\"und-Latn-ET\":\"en-Latn-ET\",\"und-Latn-GE\":\"ku-Latn-GE\",\"und-Latn-IR\":\"tk-Latn-IR\",\"und-Latn-KM\":\"fr-Latn-KM\",\"und-Latn-MA\":\"fr-Latn-MA\",\"und-Latn-MK\":\"sq-Latn-MK\",\"und-Latn-MM\":\"kac-Latn-MM\",\"und-Latn-MO\":\"pt-Latn-MO\",\"und-Latn-MR\":\"fr-Latn-MR\",\"und-Latn-RU\":\"krl-Latn-RU\",\"und-Latn-SY\":\"fr-Latn-SY\",\"und-Latn-TN\":\"fr-Latn-TN\",\"und-Latn-TW\":\"trv-Latn-TW\",\"und-Latn-UA\":\"pl-Latn-UA\",\"und-LB\":\"ar-Arab-LB\",\"und-Lepc\":\"lep-Lepc-IN\",\"und-LI\":\"de-Latn-LI\",\"und-Limb\":\"lif-Limb-IN\",\"und-Lina\":\"lab-Lina-GR\",\"und-Linb\":\"grc-Linb-GR\",\"und-Lisu\":\"lis-Lisu-CN\",\"und-LK\":\"si-Sinh-LK\",\"und-LS\":\"st-Latn-LS\",\"und-LT\":\"lt-Latn-LT\",\"und-LU\":\"fr-Latn-LU\",\"und-LV\":\"lv-Latn-LV\",\"und-LY\":\"ar-Arab-LY\",\"und-Lyci\":\"xlc-Lyci-TR\",\"und-Lydi\":\"xld-Lydi-TR\",\"und-MA\":\"ar-Arab-MA\",\"und-Mahj\":\"hi-Mahj-IN\",\"und-Mand\":\"myz-Mand-IR\",\"und-Mani\":\"xmn-Mani-CN\",\"und-Marc\":\"bo-Marc-CN\",\"und-MC\":\"fr-Latn-MC\",\"und-MD\":\"ro-Latn-MD\",\"und-ME\":\"sr-Latn-ME\",\"und-Mend\":\"men-Mend-SL\",\"und-Merc\":\"xmr-Merc-SD\",\"und-Mero\":\"xmr-Mero-SD\",\"und-MF\":\"fr-Latn-MF\",\"und-MG\":\"mg-Latn-MG\",\"und-MK\":\"mk-Cyrl-MK\",\"und-ML\":\"bm-Latn-ML\",\"und-Mlym\":\"ml-Mlym-IN\",\"und-MM\":\"my-Mymr-MM\",\"und-MN\":\"mn-Cyrl-MN\",\"und-MO\":\"zh-Hant-MO\",\"und-Modi\":\"mr-Modi-IN\",\"und-Mong\":\"mn-Mong-CN\",\"und-MQ\":\"fr-Latn-MQ\",\"und-MR\":\"ar-Arab-MR\",\"und-Mroo\":\"mro-Mroo-BD\",\"und-MT\":\"mt-Latn-MT\",\"und-Mtei\":\"mni-Mtei-IN\",\"und-MU\":\"mfe-Latn-MU\",\"und-Mult\":\"skr-Mult-PK\",\"und-MV\":\"dv-Thaa-MV\",\"und-MX\":\"es-Latn-MX\",\"und-MY\":\"ms-Latn-MY\",\"und-Mymr\":\"my-Mymr-MM\",\"und-Mymr-IN\":\"kht-Mymr-IN\",\"und-Mymr-TH\":\"mnw-Mymr-TH\",\"und-MZ\":\"pt-Latn-MZ\",\"und-NA\":\"af-Latn-NA\",\"und-Narb\":\"xna-Narb-SA\",\"und-Nbat\":\"arc-Nbat-JO\",\"und-NC\":\"fr-Latn-NC\",\"und-NE\":\"ha-Latn-NE\",\"und-Newa\":\"new-Newa-NP\",\"und-NI\":\"es-Latn-NI\",\"und-Nkoo\":\"man-Nkoo-GN\",\"und-NL\":\"nl-Latn-NL\",\"und-NO\":\"nb-Latn-NO\",\"und-NP\":\"ne-Deva-NP\",\"und-Nshu\":\"zhx-Nshu-CN\",\"und-Ogam\":\"sga-Ogam-IE\",\"und-Olck\":\"sat-Olck-IN\",\"und-OM\":\"ar-Arab-OM\",\"und-Orkh\":\"otk-Orkh-MN\",\"und-Orya\":\"or-Orya-IN\",\"und-Osge\":\"osa-Osge-US\",\"und-Osma\":\"so-Osma-SO\",\"und-PA\":\"es-Latn-PA\",\"und-Palm\":\"arc-Palm-SY\",\"und-Pauc\":\"ctd-Pauc-MM\",\"und-PE\":\"es-Latn-PE\",\"und-Perm\":\"kv-Perm-RU\",\"und-PF\":\"fr-Latn-PF\",\"und-PG\":\"tpi-Latn-PG\",\"und-PH\":\"fil-Latn-PH\",\"und-Phag\":\"lzh-Phag-CN\",\"und-Phli\":\"pal-Phli-IR\",\"und-Phlp\":\"pal-Phlp-CN\",\"und-Phnx\":\"phn-Phnx-LB\",\"und-PK\":\"ur-Arab-PK\",\"und-PL\":\"pl-Latn-PL\",\"und-Plrd\":\"hmd-Plrd-CN\",\"und-PM\":\"fr-Latn-PM\",\"und-PR\":\"es-Latn-PR\",\"und-Prti\":\"xpr-Prti-IR\",\"und-PS\":\"ar-Arab-PS\",\"und-PT\":\"pt-Latn-PT\",\"und-PW\":\"pau-Latn-PW\",\"und-PY\":\"gn-Latn-PY\",\"und-QA\":\"ar-Arab-QA\",\"und-QO\":\"en-Latn-IO\",\"und-RE\":\"fr-Latn-RE\",\"und-Rjng\":\"rej-Rjng-ID\",\"und-RO\":\"ro-Latn-RO\",\"und-RS\":\"sr-Cyrl-RS\",\"und-RU\":\"ru-Cyrl-RU\",\"und-Runr\":\"non-Runr-SE\",\"und-RW\":\"rw-Latn-RW\",\"und-SA\":\"ar-Arab-SA\",\"und-Samr\":\"smp-Samr-IL\",\"und-Sarb\":\"xsa-Sarb-YE\",\"und-Saur\":\"saz-Saur-IN\",\"und-SC\":\"fr-Latn-SC\",\"und-SD\":\"ar-Arab-SD\",\"und-SE\":\"sv-Latn-SE\",\"und-Sgnw\":\"ase-Sgnw-US\",\"und-Shaw\":\"en-Shaw-GB\",\"und-Shrd\":\"sa-Shrd-IN\",\"und-SI\":\"sl-Latn-SI\",\"und-Sidd\":\"sa-Sidd-IN\",\"und-Sind\":\"sd-Sind-IN\",\"und-Sinh\":\"si-Sinh-LK\",\"und-SJ\":\"nb-Latn-SJ\",\"und-SK\":\"sk-Latn-SK\",\"und-SM\":\"it-Latn-SM\",\"und-SN\":\"fr-Latn-SN\",\"und-SO\":\"so-Latn-SO\",\"und-Sora\":\"srb-Sora-IN\",\"und-Soyo\":\"cmg-Soyo-MN\",\"und-SR\":\"nl-Latn-SR\",\"und-ST\":\"pt-Latn-ST\",\"und-Sund\":\"su-Sund-ID\",\"und-SV\":\"es-Latn-SV\",\"und-SY\":\"ar-Arab-SY\",\"und-Sylo\":\"syl-Sylo-BD\",\"und-Syrc\":\"syr-Syrc-IQ\",\"und-Tagb\":\"tbw-Tagb-PH\",\"und-Takr\":\"doi-Takr-IN\",\"und-Tale\":\"tdd-Tale-CN\",\"un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tn-TR\"},\"timeData\":{\"AX\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"BQ\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"CP\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"CZ\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"DK\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"FI\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"ID\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"IS\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"ML\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"NE\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"RU\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"SE\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"SJ\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"SK\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"AS\":{\"_allowed\":\"h 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expression','AnalyticsCoreStringId.FontOptions_Unit_World':'World','AnalyticsCoreStringId.FontOptions_Unit_Pixel':'Pixel','AnalyticsCoreStringId.ObjectDSWizard_ChooseType_Description':'Choose the type and its constructor.','AnalyticsCoreStringId.Parameter_Type_Int64':'Number (64 bit integer)','AnalyticsCoreStringId.Parameter_Type_Int16':'Number (16 bit integer)','AnalyticsCoreStringId.Parameter_Type_Int32':'Number (32 bit integer)','AnalyticsCoreStringId.Parameter_Type_Float':'Number (floating-point)','AnalyticsCoreStringId.JsonDSWizard_ChooseConnection_Description':'Do you want to use an existing data connection?','DxDesignerStringId.CodeCompletion_Field':'field','AnalyticsCoreStringId.ValueIsRequiredOrInvalidFormat_Error':'The value cannot be empty and should have a valid format.','AnalyticsCoreStringId.Wizard_ChooseDataSource_Description':'Choose a Data Source to use in your report.','AnalyticsCoreStringId.QueryBuilder_Operator':'Operator','AnalyticsCoreStringId.Group_Edit':'Edit','AnalyticsCoreStringId.ExpressionEditor_ItemInfo_Fields':'Fields','AnalyticsCoreStringId.WarningMessage_FieldNotFound':'{0} is not found','AnalyticsCoreStringId.Parameter_Type_Double':'Number (double-precision floating-point)','AnalyticsCoreStringId.ObjectDSWizard_ConfigureParameters_Disabled_Description':'To specify parameters, select a parameterized constructor or method.','AnalyticsCoreStringId.ObjectDSWizard_ChooseDataMember_Disabled_Description':'To select a data member, choose a type that contains at least one data member.','AnalyticsCoreStringId.ParametersPanel_True':'Yes','AnalyticsCoreStringId.Wizard_ConfigureQueryParameters_Placeholder':'To specify query parameters, select a parameterized stored procedure or create a custom query.','AnalyticsCoreStringId.QueryBuilder_SelectAll':'Select All (*)','AnalyticsCoreStringId.QueryBuilder_SelectTop':'Select Top','AnalyticsCoreStringId.Wizard_SelectDataSourceType':'Select Data Source Type','AnalyticsCoreStringId.QueryBuilder_SortType':'Sort Type','AnalyticsCoreStringId.FilePicker_Placeholder':'File','AnalyticsCoreStringId.ExpressionEditor_ExpressionCaption':'Expression Editor','AnalyticsCoreStringId.SqlDSWizard_CustomSqlEditor':'Custom SQL Editor','AnalyticsCoreStringId.QueryBuilder_ColumnProperties':'Column Properties','AnalyticsCoreStringId.FormatStringEditor_Suffix':'Suffix','AnalyticsCoreStringId.Prefix':'Prefix','AnalyticsCoreStringId.QueryBuilder_QueryProperties':'Query Properties','AnalyticsCoreStringId.TooltipButtons_Preview':'Preview','AnalyticsCoreStringId.Wizard_DataSourceAssignment_Description':'The Wizard assigns the selected or a newly created data source to the report.','AnalyticsCoreStringId.QueryBuilder_SelectStatementPreview_Title':'Select Statement Preview','AnalyticsCoreStringId.Cmd_Copy':'Copy','DxDesignerStringId.Error_SchemaLoadingFailed':'Schema loading failed. {0}','AnalyticsCoreStringId.CollectionEditor_Name_Placeholder':'Name','ExpressionEditorStringId.Function_BigMul':'BigMul(Value1, Value2)\\r\\n\\r\\nReturns an Int64 containing the full product of two specified 32-bit numbers.','ExpressionEditorStringId.Function_Substring':'Substring(String, StartPosition)\\r\\n\\r\\nRetrieves a substring from String. The substring starts at StartPosition.','ExpressionEditorStringId.Function_LocalDateTimeDayAfterTomorrow':'LocalDateTimeDayAfterTomorrow()\\r\\n\\r\\nReturns a date-time value corresponding to the day after Tomorrow.','ExpressionEditorStringId.Function_Concat':'Concat(String1, ... ,StringN)\\r\\n\\r\\nReturns a string value containing the concatenation of the current string with any additional strings.','ExpressionEditorStringId.Function_Upper':'Upper(String)\\r\\n\\r\\nReturns String in uppercase.','ExpressionEditorStringId.Function_Today':'Today()\\r\\n\\r\\nReturns the current date. Regardless of the actual time, this function returns midnight of the current date.','ExpressionEditorStringId.Function_ToInt':'ToInt(Value)\\r\\n\\r\\nConverts Value to an equivalent 32-bit signed integer.','ExpressionEditorStringId.Function_ToStr':'ToStr(Value)\\r\\n\\r\\nReturns a string representation of an object.','ExpressionEditorStringId.Function_Round':'Round(Value)\\r\\n\\r\\nRounds the given Value to the nearest integer.','ExpressionEditorStringId.Function_Power':'Power()\\r\\n\\r\\nReturns a specified number Value, raised to a specified Power.','ExpressionEditorStringId.Function_IsMay':'IsMay(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within May.','ExpressionEditorStringId.Function_Lower':'Lower(String)\\r\\n\\r\\nReturns String in lowercase.','ExpressionEditorStringId.Function_Log_2':'Log(Value, Base)\\r\\n\\r\\nReturns the logarithm of a specified number Value in a specified Base.','ExpressionEditorStringId.Function_Log10':'Log10(Value)\\r\\n\\r\\nReturns the base 10 logarithm of a specified number Value.','ExpressionEditorStringId.Function_Ascii':'Ascii(String)\\r\\n\\r\\nReturns the ASCII code value of the leftmost character in a character expression.','ExpressionEditorStringId.Function_Floor':'Floor(Value)\\r\\n\\r\\nReturns the largest integer less than or equal to the given numeric expression.','ExpressionEditorStringId.Function_PadLeft':'PadLeft(String, Length)\\r\\n\\r\\nLeft-aligns characters in the defined String, padding its left side with white space characters up to a specified total Length.','ExpressionEditorStringId.Function_SingleAggregate':'Single()\\r\\n\\r\\nReturns a single object from the collection.','ExpressionEditorStringId.Function_IsYearToDate':'IsYearToDate(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the year-to-date period (starting from the first day of the current year and continuing up to the current date).','ExpressionEditorStringId.Operator_Multiply':'Multiplies the value of two expressions.','ExpressionEditorStringId.Function_Remove_3':'Remove(String, StartPosition, Length)\\r\\n\\r\\nDeletes a specified Length of characters from specified String, beginning at a specified StartPosition.','ExpressionEditorStringId.Function_IsFebruary':'IsFebruary(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within February.','ExpressionEditorStringId.Operator_Or':'Performs a logical disjunction on two Boolean expressions.','ExpressionEditorStringId.Operator_In':'In (,,,)\\r\\nTests for the existence of a property in an object.','ExpressionEditorStringId.Operator_Plus':'Adds the value of one numeric expression to another, or concatenates two strings','ExpressionEditorStringId.Operator_Less':'Less than operator. Used to compare expressions.','ExpressionEditorStringId.Operator_Like':'Compares a string against a pattern. If the value of the string matches the pattern, result is true. If the string does not match the pattern, result is false. If both string and pattern are empty strings, the result is true.','ExpressionEditorStringId.Exception_SyntaxError':'Syntax error.','ExpressionEditorStringId.Function_GetTimeOfDay':'GetTimeOfDay(DateTime)\\r\\n\\r\\nExtracts the time of the day from the defined DateTime, in ticks.','ExpressionEditorStringId.Function_ToDouble':'ToDouble(Value)\\r\\n\\r\\nConverts Value to an equivalent 64-bit double-precision floating-point number.','ExpressionEditorStringId.Function_IsNullOrEmpty':'IsNullOrEmpty(String)\\r\\n\\r\\nReturns True if the specified String object is NULL or an empty string; otherwise, False is returned.','ExpressionEditorStringId.Operator_BitwiseAnd':'Compares each bit of its first operand to the corresponding bit of its second operand. If both bits are 1, the corresponding result bit is 1. Otherwise, the corresponding result bit is 0.','ExpressionEditorStringId.Operator_BitwiseXor':'Compares each bit of its first operand to the corresponding bit of its second operand. If both bits are equal, the corresponding result bit is 0. Otherwise, the corresponding result bit is 1.','ExpressionEditorStringId.Function_IsLastMonth':'IsLastMonth(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the previous month.','ExpressionEditorStringId.Function_PadLeft_3':'PadLeft(String, Length, Char)\\r\\n\\r\\nLeft-aligns characters in the defined String, padding its left side with the specified Char up to a specified total Length.','ExpressionEditorStringId.Constant_Null':'Represents a null reference, one that does not refer to any object.','ExpressionEditorStringId.Constant_True':'Represents the Boolean True value.','ExpressionEditorStringId.Function_LocalDateTimeLastMonth':'LocalDateTimeLastMonth()\\r\\n\\r\\nReturns a date-time value corresponding to the first day of the previous month.','ExpressionEditorStringId.Operator_Between':'Between (,)\\r\\nSpecifies a range to test. Returns true if a value is greater than or equal to the first operand and less than or equal to the second operand.','ExpressionEditorStringId.Operator_Greater':'Greater than operator. Used to compare expressions.','ExpressionEditorStringId.Function_IsNextMonth':'IsNextMonth(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the next month.','ExpressionEditorStringId.Function_GetMinute':'GetMinute(DateTime)\\r\\n\\r\\nExtracts minutes from the defined DateTime.','ExpressionEditorStringId.Function_LocalDateTimeNow':'LocalDateTimeNow()\\r\\n\\r\\nReturns a DateTime value corresponding to the current moment in time.','ExpressionEditorStringId.Function_LocalDateTimeTwoYearsAway':'LocalDateTimeTwoYearsAway()\\r\\n\\r\\nReturns a date-time value corresponding to the first day of the year after next.','ExpressionEditorStringId.Function_Tan':'Tan(Value)\\r\\n\\r\\nReturns the tangent of the angle defined in radians.','ExpressionEditorStringId.Function_Max':'Max(Value1, Value2)\\r\\n\\r\\nReturns the maximum value from the specified values.','ExpressionEditorStringId.Function_Min':'Min(Value1, Value2)\\r\\n\\r\\nReturns the minimum value from the specified values.','ExpressionEditorStringId.Function_Rnd':'Rnd()\\r\\n\\r\\nReturns a random number that is less than 1, but greater than or equal to zero.','ExpressionEditorStringId.Function_Sin':'Sin(Value)\\r\\n\\r\\nReturns the sine of the angle, defined in radians.','ExpressionEditorStringId.Function_Sqr':'Sqr(Value)\\r\\n\\r\\nReturns the square root of a given number Value.','ExpressionEditorStringId.Function_Iif':'Iif(FirstClause, FirstClauseTrueValue, ..., LastClause, LastClauseTrueValue, FalseValue)\\r\\n\\r\\nReturns either a value defined for the first Boolean condition that is True, or the last value if none of these conditions is True.\\r\\n\\r\\nThis function can accept any number of arguments.','ExpressionEditorStringId.Function_Now':'Now()\\r\\n\\r\\nReturns the current system date and time.','ExpressionEditorStringId.Function_Len':'Len(Value)\\r\\n\\r\\nReturns an integer containing either the number of characters in a string or the nominal number of bytes required to store a variable.','ExpressionEditorStringId.Function_Log':'Log(Value)\\r\\n\\r\\nReturns the natural logarithm of a specified number.','ExpressionEditorStringId.Function_Exp':'Exp(Value)\\r\\n\\r\\nReturns the exponential value of the given float expression.','ExpressionEditorStringId.Function_Atn':'Atn(Value)\\r\\n\\r\\nReturns the arctangent of a number (the angle, in radians, whose tangent is the given float expression).','ExpressionEditorStringId.Function_Abs':'Abs(Value)\\r\\n\\r\\nReturns the absolute, positive value of the given numeric expression.','ExpressionEditorStringId.Function_Cos':'Cos(Value)\\r\\n\\r\\nReturns the cosine of the angle defined in radians.','ExpressionEditorStringId.Function_MaxAggregate':'Max()\\r\\n\\r\\nReturns the maximum expression value in a collection.','ExpressionEditorStringId.Exception_InvalidNumericLiteral':'Invalid numeric literal value: \"{0}\".','ExpressionEditorStringId.Function_AddSeconds':'AddSeconds(DateTime, SecondsCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of SecondsCount away from the specified DateTime.','ExpressionEditorStringId.Operator_BitwiseOr':'Compares each bit of its first operand to the corresponding bit of its second operand. If both bits are 0, the corresponding result bit is 0. Otherwise, the corresponding result bit is 1.','ExpressionEditorStringId.Function_IsApril':'IsApril(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within April.','ExpressionEditorStringId.Function_IsMarch':'IsMarch(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within March.','ExpressionEditorStringId.Function_DateDiffMonth':'DateDiffMonth(StartDate, EndDate)\\r\\n\\r\\nReturns the number of month boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_AvgAggregate':'Avg()\\r\\n\\r\\nEvaluates the average of the values in the collection.','ExpressionEditorStringId.Function_GetMilliSecond':'GetMilliSecond(DateTime)\\r\\n\\r\\nExtracts milliseconds from the defined DateTime.','ExpressionEditorStringId.Function_IsDecember':'IsDecember(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within December.','ExpressionEditorStringId.Function_GetSecond':'GetSecond(DateTime)\\r\\n\\r\\nExtracts seconds from the defined DateTime.','ExpressionEditorStringId.Function_IsAugust':'IsAugust(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within August.','ExpressionEditorStringId.Function_Round_2':'Round(Value, Precision)\\r\\n\\r\\nRounds the given Value to the nearest integer, or to a specified Precision.','ExpressionEditorStringId.Function_Tanh':'Tanh(Value)\\r\\n\\r\\nReturns the hyperbolic tangent of the angle defined in radians.','ExpressionEditorStringId.Function_Trim':'Trim(String)\\r\\n\\r\\nRemoves all leading and trailing SPACE characters from String.','ExpressionEditorStringId.Function_Sign':'Sign(Value)\\r\\n\\r\\nReturns the positive (+1), zero (0), or negative (-1) sign of the given Value.','ExpressionEditorStringId.Function_Sinh':'Sinh(Value)\\r\\n\\r\\nReturns the hyperbolic sine of the angle defined in radians.','ExpressionEditorStringId.Function_Join':'Join(Collection)\\r\\n\\r\\nConcatenates elements of the specified Collection, inserting comma between each element.','ExpressionEditorStringId.Function_Atn2':'Atn2(Value1, Value2)\\r\\n\\r\\nReturns the angle whose tangent is the quotient of two specified numbers, in radians.','ExpressionEditorStringId.Function_Asin':'Asin(Value)\\r\\n\\r\\nReturns the arcsine of a number (the angle, in radians, whose sine is the given float expression).','ExpressionEditorStringId.Function_Acos':'Acos(Value)\\r\\n\\r\\nReturns the arccosine of a number (the angle, in radians, whose cosine is the given float expression).','ExpressionEditorStringId.Function_Cosh':'Cosh(Value)\\r\\n\\r\\nReturns the hyperbolic cosine of the angle defined in radians.','ExpressionEditorStringId.Function_Char':'Char(Number)\\r\\n\\r\\nConverts the specified ASCII integer Number to a character.','ExpressionEditorStringId.Operator_Not':'Performs logical negation on an expression.','ExpressionEditorStringId.Operator_And':'Performs a logical conjunction on two expressions.','ExpressionEditorStringId.Exception_WrongArgumentsCount':'Wrong arguments count for function \"{0}(...)\".','ExpressionEditorStringId.Function_ToDecimal':'ToDecimal(Value)\\r\\n\\r\\nConverts Value to an equivalent decimal number.','ExpressionEditorStringId.Operator_NotEqual':'Returns true if the operands do not have the same value; otherwise, it returns false.','ExpressionEditorStringId.Function_IsNull_2':'IsNull(Value1, Value2)\\r\\n\\r\\nReturns the second operand if the first operand is null, otherwise, the first operand is returned.','ExpressionEditorStringId.Function_Replace':'Replace(String, SubString2, String3)\\r\\n\\r\\nReturns a copy of String1, in which SubString2 has been replaced with String3.','ExpressionEditorStringId.Function_Reverse':'Reverse(String)\\r\\n\\r\\nReverses the order of elements within a String.','ExpressionEditorStringId.Exception_InvalidCharacter':'Invalid input character: \"{0}\".','ExpressionEditorStringId.Function_GetHour':'GetHour(DateTime)\\r\\n\\r\\nExtracts an hour from the defined DateTime.','ExpressionEditorStringId.Function_GetDate':'GetDate(DateTime)\\r\\n\\r\\nExtracts a date from the defined DateTime.','ExpressionEditorStringId.Function_GetYear':'GetYear(DateTime)\\r\\n\\r\\nExtracts a year from the defined DateTime','ExpressionEditorStringId.Operator_Minus':'Finds the difference between two numbers.','ExpressionEditorStringId.Operator_Equal':'Returns true if both operands have the same value; otherwise, it returns false.','ExpressionEditorStringId.Function_InRange':'InRange(FirstOperand, SecondOperand, ThirdOperand)\\r\\n\\r\\nSpecifies a range to test. Returns true if the first operand is greater than or equal to the second operand and less than the third operand.','ExpressionEditorStringId.Operator_LessOrEqual':'Less than or equal to operator. Used to compare expressions.','ExpressionEditorStringId.Function_DateDiffHour':'DateDiffHour(StartDate, EndDate)\\r\\n\\r\\nReturns the number of hour boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_DateDiffTick':'DateDiffTick(StartDate, EndDate)\\r\\n\\r\\nReturns the number of tick boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_DateDiffYear':'DateDiffYear(StartDate, EndDate)\\r\\n\\r\\nReturns the number of year boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_ExistsAggregate':'Exists()\\r\\n\\r\\nDetermines whether the object exists in the collection.','ExpressionEditorStringId.Function_IsNextYear':'IsNextYear(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the next year.','ExpressionEditorStringId.Exception_MalformedProperty':'Malformed property name: missing closing \"{0}\".','ExpressionEditorStringId.Constant_False':'Represents the Boolean False value.','ExpressionEditorStringId.Function_MinAggregate':'Min()\\r\\n\\r\\nReturns the minimum expression value in a collection.','ExpressionEditorStringId.Function_Substring_3':'Substring(String, StartPosition, Length)\\r\\n\\r\\nRetrieves a substring from String. The substring starts at StartPosition and has the specified Length.','ExpressionEditorStringId.Function_LocalDateTimeTomorrow':'LocalDateTimeTomorrow()\\r\\n\\r\\nReturns a date-time value corresponding to Tomorrow.','ExpressionEditorStringId.Function_IsSameDay':'IsSameDay(DateTime, DateTime)\\r\\n\\r\\nReturns True if the specified DateTime values fall within the same day.','ExpressionEditorStringId.Function_GetMonth':'GetMonth(DateTime)\\r\\n\\r\\nExtracts a month from the defined DateTime.','ExpressionEditorStringId.Function_LocalDateTimeThisMonth':'LocalDateTimeThisMonth()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the current month.','ExpressionEditorStringId.Function_Ceiling':'Ceiling(Value)\\r\\n\\r\\nReturns the smallest integer that is greater than or equal to the given numeric expression.','ExpressionEditorStringId.Function_CharIndex_3':'CharIndex(String1, String2, StartLocation)\\r\\n\\r\\nReturns the starting position of String1 within String2, beginning from the StartLocation character position to the end of a string.','ExpressionEditorStringId.Function_LocalDateTimeLastYear':'LocalDateTimeLastYear()\\r\\n\\r\\nReturns a date-time value corresponding to the first day of the previous year.','ExpressionEditorStringId.Function_LocalDateTimeLastWeek':'LocalDateTimeLastWeek()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the previous week.','ExpressionEditorStringId.Function_IsNovember':'IsNovember(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within November.','ExpressionEditorStringId.Function_FormatString':'FormatString(Format, Value1, ... , ValueN)\\r\\n\\r\\nReturns the specified string with formatted field values.\\r\\nThis function can accept any number of arguments.\\r\\n\\r\\nExample:\\r\\n\\r\\nFormatString(\\'{0} - {1:c}\\', [Column1], [Column2])','ExpressionEditorStringId.Function_InDateRange':'InDateRange(DateTime, DateTime, DateTime)\\r\\n\\r\\nSpecifies a date range to test. Returns true if a date part of the first operand is greater than or equal to the date part of the second operand and less than or equal the date part of the third operand.','ExpressionEditorStringId.Function_CharIndex':'CharIndex(String1, String2)\\r\\n\\r\\nReturns the starting position of String1 within String2, beginning from the zero character position to the end of a string.','ExpressionEditorStringId.Function_DateDiffMinute':'DateDiffMinute(StartDate, EndDate)\\r\\n\\r\\nReturns the number of minute boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_IsThisMonth':'IsThisMonth(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the current month.','ExpressionEditorStringId.Function_LocalDateTimeTwoWeeksAway':'LocalDateTimeTwoWeeksAway()\\r\\n\\r\\nReturns a date-time value corresponding to the first day of the week that is after next week.','ExpressionEditorStringId.Function_LocalDateTimeToday':'LocalDateTimeToday()\\r\\n\\r\\nReturns a DateTime value corresponding to Today.','ExpressionEditorStringId.Function_LocalDateTimeNextMonth':'LocalDateTimeNextMonth()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of next month.','ExpressionEditorStringId.Function_EndsWith':'EndsWith(String, EndString)\\r\\n\\r\\nReturns True if the end of String matches EndString; otherwise, False is returned.','ExpressionEditorStringId.Function_CountAggregate':'Count()\\r\\n\\r\\nReturns the number of objects in a collection.','ExpressionEditorStringId.Operator_Modulo':'Returns the remainder (modulus) obtained by dividing one numeric expression into another.','ExpressionEditorStringId.Function_DateDiffDay':'DateDiffDay(StartDate, EndDate)\\r\\n\\r\\nReturns the number of day boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_LocalDateTimeNextWeek':'LocalDateTimeNextWeek()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the following week.','ExpressionEditorStringId.Function_LocalDateTimeNextYear':'LocalDateTimeNextYear()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the following year.','ExpressionEditorStringId.Operator_GreaterOrEqual':'Greater than or equal to operator. Used to compare expressions.','ExpressionEditorStringId.Function_IsLastYear':'IsLastYear(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the previous year.','ExpressionEditorStringId.Function_AddTimeSpan':'AddTimeSpan(DateTime, TimeSpan)\\r\\n\\r\\nReturns a date-time value that is away from the specified DateTime for the given TimeSpan.','ExpressionEditorStringId.Function_CreateTable':'CreateTable(Parameter1, ..., ParameterN)\\r\\n\\r\\nPrepares a table from values of several specified multi-value parameters.','ExpressionEditorStringId.Function_DateDiffSecond':'DateDiffSecond(StartDate, EndDate)\\r\\n\\r\\nReturns the number of second boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_DateDiffMilliSecond':'DateDiffMilliSecond(StartDate, EndDate)\\r\\n\\r\\nReturns the number of millisecond boundaries between two non-nullable dates.','ExpressionEditorStringId.Function_NewLine':'NewLine()\\r\\n\\r\\nReturns the newline string defined for this environment.','ExpressionEditorStringId.Operator_Divide':'Divides the first operand by the second.','ExpressionEditorStringId.Function_GetDayOfWeek':'GetDayOfWeek(DateTime)\\r\\n\\r\\nExtracts a day of the week from the defined DateTime.','ExpressionEditorStringId.Function_GetDayOfYear':'GetDayOfYear(DateTime)\\r\\n\\r\\nExtracts a day of the year from the defined DateTime.','ExpressionEditorStringId.Function_AddMilliSeconds':'AddMilliSeconds(DateTime, MilliSecondsCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of MilliSecondsCount away from the specified DateTime.','ExpressionEditorStringId.Function_LocalDateTimeYearBeforeToday':'LocalDateTimeYearBeforeToday()\\r\\n\\r\\nReturns a date-time value corresponding to the day one year ago.','ExpressionEditorStringId.Function_UtcNow':'UtcNow()\\r\\n\\r\\nReturns the current system date and time, expressed as Coordinated Universal Time (UTC).','ExpressionEditorStringId.Function_AddDays':'AddDays(DateTime, DaysCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of DaysCount away from the specified DateTime.','ExpressionEditorStringId.Function_AddMinutes':'AddMinutes(DateTime, MinutesCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of MinutesCount away from the specified DateTime.','ExpressionEditorStringId.Function_ToLong':'ToLong(Value)\\r\\n\\r\\nConverts Value to an equivalent 64-bit signed integer.','ExpressionEditorStringId.Function_ToFloat':'ToFloat(Value)\\r\\n\\r\\nConverts Value to an equivalent 32-bit single-precision floating-point number.','ExpressionEditorStringId.Function_Remove':'Remove(String, StartPosition)\\r\\n\\r\\nDeletes all characters from specified String, beginning at a specified StartPosition.','ExpressionEditorStringId.Function_IsJanuary':'IsJanuary(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within January.','ExpressionEditorStringId.Function_IsNull':'IsNull(Value)\\r\\n\\r\\nReturns True if the specified Value is NULL.','ExpressionEditorStringId.Function_IsJuly':'IsJuly(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within July.','ExpressionEditorStringId.Function_IsJune':'IsJune(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within June.','ExpressionEditorStringId.Function_Insert':'Replace(String1, StartPosition, String2)\\r\\n\\r\\nInserts String2 into String1 at the position specified by StartPositon.','ExpressionEditorStringId.Function_Contains':'Contains(String, SubString)\\r\\n\\r\\nReturns True if SubString occurs within String; otherwise, False is returned.','ExpressionEditorStringId.Function_LocalDateTimeThisWeek':'LocalDateTimeThisWeek()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the current week.','ExpressionEditorStringId.Function_LocalDateTimeThisYear':'LocalDateTimeThisYear()\\r\\n\\r\\nReturns a DateTime value corresponding to the first day of the current year.','ExpressionEditorStringId.Function_AddMonths':'AddMonths(DateTime, MonthsCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of MonthsCount away from the specified DateTime.','ExpressionEditorStringId.Function_Join_2':'Join(Collection, Separator)\\r\\n\\r\\nConcatenates elements of the specified Collection, using the specified Separator between each element.','ExpressionEditorStringId.Function_SumAggregate':'Sum()\\r\\n\\r\\nReturns the sum of all the expression values in the collection.','ExpressionEditorStringId.Function_IsSeptember':'IsSeptember(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within September.','ExpressionEditorStringId.Function_IsThisYear':'IsThisYear(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within the current year.','ExpressionEditorStringId.Function_IsThisWeek':'IsThisWeek(DateTime)\\r\\n\\r\\nReturns True if the specified date falls within the current week.','ExpressionEditorStringId.Function_LocalDateTimeYesterday':'LocalDateTimeYesterday()\\r\\n\\r\\nReturns a date-time value corresponding to Yesterday.','ExpressionEditorStringId.Function_AddYears':'AddYears(DateTime, YearsCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of YearsCount away from the specified DateTime.','ExpressionEditorStringId.Function_StartsWith':'StartsWith(String, StartString)\\r\\n\\r\\nReturns True if the beginning of String matches StartString; otherwise, False is returned.','ExpressionEditorStringId.Function_PadRight_3':'PadRight(String, Length, Char)\\r\\n\\r\\nRight-aligns characters in the defined String, padding its right side with the specified Char up to a specified total Length.','ExpressionEditorStringId.Function_AddTicks':'AddTicks(DateTime, AddTicks)\\r\\n\\r\\nReturns a date-time value that is the specified number of TicksCount away from the specified DateTime.','ExpressionEditorStringId.Function_AddHours':'AddHours(DateTime, HoursCount)\\r\\n\\r\\nReturns a date-time value that is the specified number of HoursCount away from the specified DateTime.','ExpressionEditorStringId.Function_PadRight':'PadRight(String, Length)\\r\\n\\r\\nRight-aligns characters in the defined String, padding its right side with white space characters up to a specified total Length.','ExpressionEditorStringId.Function_GetDay':'GetDay(DateTime)\\r\\n\\r\\nExtracts a day from the defined DateTime.','ExpressionEditorStringId.Function_LocalDateTimeTwoMonthsAway':'LocalDateTimeTwoMonthsAway()\\r\\n\\r\\nReturns a date-time value corresponding to the first day of the month after next.','ExpressionEditorStringId.Function_IsOctober':'IsOctober(DateTime)\\r\\n\\r\\nReturns True if the specified DateTime falls within October.','DataAccessUIStringId.WizardPageConfigureJsonConnection_HeaderValueText':'Header Value','DataAccessUIStringId.DataPreviewForm_Title':'Data Preview','DataAccessUIStringId.WizardPageConnectionProperties':'Select the data provider and specify the connection properties.','DataAccessUIStringId.EFDataSourceDesignerVerbEdit':'Edit...','DataAccessUIStringId.WizardPageChooseJsonSource_SourceType':'JSON Source:','DataAccessUIStringId.Button_Finish':'Finish','DataAccessUIStringId.QueryEditorTitle':'Query Editor','DataAccessUIStringId.FederationDataSourceQueryBuilder_AliasUniqueMessage':'Alias is not unique','DataAccessUIStringId.Button_Cancel':'Cancel','DataAccessUIStringId.WizardPageConfigureExcelFileColumns_ColumnNameEmptyError':'The column name cannot be empty.','DataAccessUIStringId.XPObjectSource_EntityTypeNotSet':'Property collection cannot be populated because EntityType is not set.','DataAccessUIStringId.WizardPageChooseObjectBindingMode_RetrieveData':'Retrieve the actual data','DataAccessUIStringId.WizardPageChooseFileOptions_SkipHiddenColumns':'Skip hidden columns','DataAccessUIStringId.DSTypeExcel':'Excel File','DataAccessUIStringId.ODSEditorsCannotResolveDataSource':'Cannot resolve the specified object type. To specify the object’s assembly, return type, data member and/or constructor parameters, use the Data Source editor.','DataAccessUIStringId.WizardPageChooseObjectAssembly':'Select an assembly containing the class type definition of a data source.','DataAccessUIStringId.WizardPageChooseObjectBindingMode_RetrieveSchema':'Retrieve the data source schema','DataAccessUIStringId.WizardPageChooseJsonSchema_RootElement':'Root element:','DataAccessUIStringId.ConnectionProperties_Port':'Port:','DataAccessUIStringId.WizardPageConfigureFederatedQueryPage_EditingIsNotSupported':'Editing is not supported for this query.','DataAccessUIStringId.SqlDataSourceDesignerVerbRebuildSchema':'Rebuild Result Schema','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeType_Union':'Union','DataAccessUIStringId.LoadingDataCustomError':'Error message:\\r\\n{0}\\r\\n','DataAccessUIStringId.ExpressionEditor_ExpressionContainsErrors':'The expression contains errors.','DataAccessUIStringId.JoinEditorLessOperator':'Is less than','DataAccessUIStringId.UpdateSchemaDataSourceIsNotReady':'The FileName and SourceOptions properties should be assigned.','DataAccessUIStringId.EFStoredProcsEditorTitle':'Manage Stored Procedures','DataAccessUIStringId.WizardPageChooseFileOptions_TrimBlanks':'Trim blanks','DataAccessUIStringId.ExcelDataSourceWizard_WorksheetItem':'Worksheet','DataAccessUIStringId.QueryBuilderColumns_SortingType':'Sorting Type','DataAccessUIStringId.FederatedQueryCollectionList_Title':'Federated Queries','DataAccessUIStringId.FilterStringEditorInvalidQuery':'An error occurred during query validation: {0}\\r\\nUpdate the connection settings so that they match the database schema or discard this query.','DataAccessUIStringId.WizardPageChooseFileOptions_SkipHiddenRows':'Skip hidden rows','DataAccessUIStringId.WizardPageConfigureFederatedQueryPage_InvalidQuery':'The query is invalid.','DataAccessUIStringId.ODSEditorsNoParametersMessage':'The {0} data member cannot receive parameters, because this is a method without parameters.','DataAccessUIStringId.WizardPageChooseEFConnectionString_ChooseConnection':'Yes, let me choose from list','DataAccessUIStringId.WizardPageConfigureFederatedQueryPage':'Create a federated query.','DataAccessUIStringId.WizardPageChooseConnection_SpecifyCustomConnection':'No, I\\'d like to specify the connection parameters myself','DataAccessUIStringId.WizardPageChooseConnection':'Do you want to use an existing data connection?','DataAccessUIStringId.QueryBuilderReverseRelationConfirmation':'The new join direction will be applied to all existing relations between the following two tables: {0}, {1}. Do you wish to continue?','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_AuthenticationType':'Authentication:','DataAccessUIStringId.WizardPageMultipleFederatedQueriesPage':'Create a federated query.\\r\\nData columns selected from specific data sources and/or tables will be automatically included into a separate query.','DataAccessUIStringId.UpdateDBSchemaCaption':'Request Database Schema','DataAccessUIStringId.FiltersView_TopAndSkipText':'records starting with index','DataAccessUIStringId.WizardPageChooseFileOptions_NewLineType':'Newline type:','DataAccessUIStringId.ErrorFormDatasourceInitializationText':'Unable to load data into one or several datasources. See information below for details.','DataAccessUIStringId.QueryBuilderColumn':'Column','DataAccessUIStringId.WaitFormWithCancel_Loading':'Loading Data...','DataAccessUIStringId.WizardPageChooseXPObjectSourceConnectionType':'Do you want to use the default data layer?','DataAccessUIStringId.Parameters_AddNewParameterPlaceholder':'Click the Add button to create a parameter.','DataAccessUIStringId.DSTypeFederation':'Data Federation','DataAccessUIStringId.MasterDetailEditorEditRelation':'Edit Relation','DataAccessUIStringId.QueryFilter_CreateQueryParameter':'Create Query Parameter','DataAccessUIStringId.ParametersColumn_QueryName':'Query','DataAccessUIStringId.QueryFilter_SelectParameter':'<select a parameter>','DataAccessUIStringId.WizardPageChooseXPObjectEntityType':'Choose an entity type.','DataAccessUIStringId.WizardFinishPageText':'Select an object to include in your data source','DataAccessUIStringId.EFConnectionEditorMessageCustomAssembliesProhibited':'The current security policy prohibits loading of third-party assemblies.\\r\\n\\r\\nClick OK to discard the current data source settings and configure them from scratch.\\r\\nClick Cancel to keep the current settings without configuring the data source','DataAccessUIStringId.WizardPageChooseObjectMember_ShowOnlyHighlighted':'Show only highlighted members','DataAccessUIStringId.WizardPageSaveConnection_SaveCredentialsQuestion':'The connection uses server authentication.\\r\\nDo you want to save the user name and password?','DataAccessUIStringId.JsonDataSourceSchemaEditorTitle':'JSON Data Source Schema Editor','DataAccessUIStringId.WizardPageChooseObjectConstructor':'Select a data source constructor.','DataAccessUIStringId.FiltersView_Distinct':'Select only distinct values','DataAccessUIStringId.WizardPageConfigureExcelFileColumns_ColumnExist':'Column with \\'{0}\\' name already exists.','DataAccessUIStringId.ConnectionProperties_Password':'Password:','DataAccessUIStringId.QueryBuilder_DeleteRelation':'Delete Relation','DataAccessUIStringId.MessageBoxCloseDataSourceWizardConfirmation':'Closing the Data Source Wizard will discard changes. Do you want to continue?','DataAccessUIStringId.ODSDataMemberEditorTitle':'Configure Data Member','DataAccessUIStringId.QueryBuilder_RemoveFromSelect':'Remove from Query','DataAccessUIStringId.ConnectionProperties_SslMode':'SSL Mode:','DataAccessUIStringId.QueryBuilderColumns_ColumnName':'Column Name','DataAccessUIStringId.WizardPageChooseFileOptions_Culture':'Culture:','DataAccessUIStringId.ConnectionProperties_AuthenticationType_MSSqlWindows':'Windows authentication','DataAccessUIStringId.WizardPageChooseObjectMember_BindToObject':'Do not select a member, bind to the entire object.','DataAccessUIStringId.Button_OK':'OK','DataAccessUIStringId.ConnectionProperties_Provider':'Provider:','DataAccessUIStringId.WizardPageChooseEFContext':'Choose a data context.','DataAccessUIStringId.MasterDetailEditorAddRelationMessage':'Add a relation to the detail query','DataAccessUIStringId.ConnectionProperties_AdvantageServerTypeLocal':'Local','DataAccessUIStringId.Button_Preview':'Preview...','DataAccessUIStringId.WizardPageChooseDSType':'Select data source type.','DataAccessUIStringId.MessageBoxWarningTitle':'Warning','DataAccessUIStringId.WizardPageObjectMemberParameters':'Specify the method parameters.','DataAccessUIStringId.WizardPageSaveJsonConnection_SaveRequestParametersPrompt':'Request parameters may contain sensitive data.\\r\\nDo you want to save request parameters?','DataAccessUIStringId.ODSEditorsAbstractTypeMessage':'Cannot use a constructor to create an object of the {0} type that is a static or abstract class, or interface.','DataAccessUIStringId.MessageMissingConnection':'No connection has been specified.','DataAccessUIStringId.WizardPageMultipleFederatedQueriesPage_AddQuery':'Add Query...','DataAccessUIStringId.QueryEditorWaitFormValidating':'Validating query...','DataAccessUIStringId.WizardPageChooseObjectMember_BindToMember':'Select a member to bind.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_ServiceName':'Service Name:','DataAccessUIStringId.WizardPageChooseFileOptions_SkipEmptyRows':'Skip empty rows','DataAccessUIStringId.EFFilterCollectionEditor':'Entity Framework Filter Collection Editor','DataAccessUIStringId.WizardPageChooseObjectType':'Select a data source type.','DataAccessUIStringId.LoadingDataException':'Data loading failed because the exception occurred.','DataAccessUIStringId.QueryBuilderColumns_Output':'Output','DataAccessUIStringId.ConnectionProperties_ConnectionString':'Connection string:','DataAccessUIStringId.FiltersView':'Filter Editor','DataAccessUIStringId.QueryDesignControlJoinCommandPattern':'Join {0}','DataAccessUIStringId.QueryBuilderButtons_PreviewResults':'Preview Results...','DataAccessUIStringId.ConnectionErrorFormDetailPattern':'Connection name: {0}\\r\\nError message: {1}','DataAccessUIStringId.WizardPageChooseJsonSchema_Type':'Type','DataAccessUIStringId.QueryBuilder_SortAscending':'Sort Ascending','DataAccessUIStringId.ConnectionProperties_Database':'Database:','DataAccessUIStringId.WizardPageChooseXPObjectSourceConnectionType_UseDefaultDataLayer':'Yes, my data connection is available at runtime only.','DataAccessUIStringId.QueryFilter_BindTo':'Bind To','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeType_UnionAll':'Union All','DataAccessUIStringId.MasterDetailEditorMultipleValidationErrorsMessage':'The following errors occurred during query validation:{0}','DataAccessUIStringId.MasterDetailEditorInvalidColumnQueryNameMessage':'Cannot find the specified query: \"{0}\". Specify an existing query name before selecting a column.','DataAccessUIStringId.QueryFilter_AddQueryParameter':'Add Query Parameter','DataAccessUIStringId.WizardPageConfigureEFFilters_EntityColumnName':'Entity Name','DataAccessUIStringId.QueryBuilderColumns_GroupBy':'Group By','DataAccessUIStringId.UpdateSchemaComplete':'The data source schema has been updated successfully.','DataAccessUIStringId.ConnectionProperties_OracleProviderTypeODP':'ODP','DataAccessUIStringId.ExpressionEditor_InvalidProperty':'Invalid property: \\'{0}\\'.','DataAccessUIStringId.WizardDataSourceNameExistsMessage':'<b>A data source with the specified name already exists</b>','DataAccessUIStringId.XPObjectSource_ConfirmClearProperties':'The Properties collection will be cleared. The data source will load complete objects. Do you want to continue?','DataAccessUIStringId.EFFilterControl_AddParameter':'Add Filter Parameter','DataAccessUIStringId.WizardPageSaveConnection_ConfirmSaving':'Yes, save the connection as:','DataAccessUIStringId.WizardPageConfigureMultiQuery':'Create a query or select a stored procedure.\\r\\nData columns selected from specific tables and/or views will be automatically included into a separate query.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_CanonicalizeHostName':'Canonicalize Host Name','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_Principal':'Principal','DataAccessUIStringId.MasterDetailEditorLabelInvalidRelationsText':'{0} invalid relation(s)','DataAccessUIStringId.JoinEditorEmptyColumnText':'<Select a column>','DataAccessUIStringId.Button_ResetSchema':'Reset Schema...','DataAccessUIStringId.WizardPageEFConnectionProperties_CustomConnection':'Specify a custom connection string','DataAccessUIStringId.FederationDataSourceQueryBuilder_RemovedColumnMessage':'The \"{0}.{1}\" column was removed from the \"{2}\" data source. Remove this column from the federated query to proceed.','DataAccessUIStringId.QueryBuilder_AllowEdit':'Allow Edit SQL','DataAccessUIStringId.MessageCannotLoadDatabasesList':'Error has occurred during loading databases list.','DataAccessUIStringId.JsonDataSourceEditorTitle':'JSON Data Source Editor','DataAccessUIStringId.QueryDesignControlDataPreviewCaption_All':'Data Preview','DataAccessUIStringId.QueryBuilder':'Query Builder','DataAccessUIStringId.WizardPageConfigureStoredProcedures':'Add stored procedures to the data source, configure their parameters and preview the result.','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeType_Select':'Join','DataAccessUIStringId.JsonDataSourceDesignerVerbEdit':'Edit...','DataAccessUIStringId.QueryBuilderColumns_Alias':'Alias','DataAccessUIStringId.WizardPageConfigureJsonConnection_BasicHttpAuthText':'Basic HTTP Authentication','DataAccessUIStringId.FederationDataSourceQueryBuilder_SelectResult':'Join result','DataAccessUIStringId.WizardPageConfigureJsonConnection':'Configure web service endpoint request.','DataAccessUIStringId.JoinEditor':'Join Editor','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeType_Transform':'Transform','DataAccessUIStringId.LoadingDataSqlError':'SQL execution error:\\r\\n{0}\\r\\n','DataAccessUIStringId.WizardPageChooseDataSourceName':'Enter the data source name','DataAccessUIStringId.WizardPageChooseJsonSchema_FieldNameIsEmpty':'A field name cannot be empty.','DataAccessUIStringId.WizardPageChooseFileOptions_FirstRowAsFieldNames':'Use values of the first row as field names','DataAccessUIStringId.WizardPageSaveConnection':'Save the connection string.','DataAccessUIStringId.QueryDesignControlNoSelection':'No column has been selected. Please select at least one column to proceed.','DataAccessUIStringId.WizardPageChooseEFConnectionString':'Do you want to select a connection string from the list of available settings?','DataAccessUIStringId.ExcelDataSourceWizard_Title':'Table','DataAccessUIStringId.ConnectionProperties_ClientID':'Client ID:','DataAccessUIStringId.ODSEditorsNoMembersInType':'The {0} data source type does not provide any members suitable for binding.','DataAccessUIStringId.QueryDesignControlAliasAlreadyExists':'The specified alias already exists. Do you want to correct the value?','DataAccessUIStringId.ExpressionEditor_EmptyExpression':'The expression string cannot be empty.','DataAccessUIStringId.WizardTitleODS':'ObjectDataSource Wizard','DataAccessUIStringId.ParametersColumn_Name':'Name','DataAccessUIStringId.ParametersColumn_Type':'Type','DataAccessUIStringId.WizardCannotRetrieveDatabasesMessage':'Cannot retrieve the list of available databases. See the details below.','DataAccessUIStringId.StoredProcControl_Caption':'Select a stored procedure','DataAccessUIStringId.WizardTitleDatasource':'Data Source Wizard','DataAccessUIStringId.ConnectionProperties_ServerType':'Server type:','DataAccessUIStringId.ConnectionProperties_ServerName':'Server name:','DataAccessUIStringId.WizardPageChooseObjectAssembly_ShowOnlyHighlighted':'Show only highlighted assemblies','DataAccessUIStringId.ConnectionProperties_Hostname':'Hostname:','DataAccessUIStringId.ExcelDataSourceWizard_DefinedNameItem':'Defined Name','DataAccessUIStringId.QueryBuilderColumns_Source':'Source','DataAccessUIStringId.SqlDataSourceDesignerVerbEditConnection':'Configure Connection...','DataAccessUIStringId.WizardPageChooseJsonSource_SourceType_File':'JSON File','DataAccessUIStringId.ExcelDataSourceIncorrectFilePathMessage':'Unable to locate file {0}.\\r\\nPlease specify a valid location and press OK to continue.','DataAccessUIStringId.WizardPageConfigureMongoDBQueries':'Configure queries.','DataAccessUIStringId.ConnectionProperties_AdvantageServerTypeRemote':'Remote','DataAccessUIStringId.SqlDataSourceDesignerVerbManageQueries':'Manage Queries...','DataAccessUIStringId.ConnectionProperties_AuthenticationType_BigQueryKeyFile':'Key file','DataAccessUIStringId.QueryBuilderColumnsOf':'Columns of {0}','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_CollectionNameColumnName':'Collection','DataAccessUIStringId.WizardPageChooseObjectType_ShowOnlyHighlighted':'Show only highlighted types','DataAccessUIStringId.QueryBuilder_Delete':'Delete','DataAccessUIStringId.QueryBuilderRelationBetweenTwoColumnsOfTheSameTable':'Cannot create a relation between two columns that belong to the same table {0}.','DataAccessUIStringId.FiltersView_CheckText':'Select only','DataAccessUIStringId.WizardPageConfigureJsonConnection_ParameterNameText':'Parameter Name','DataAccessUIStringId.ExcelDataSourceDesignerVerbEditSchema':'Edit Schema...','DataAccessUIStringId.WizardPageChooseObjectBindingMode_RetrieveDataDescription':'The object data source automatically creates an instance of the specified type by using one of the available constructors. If only one constructor is available, this constructor will be used.','DataAccessUIStringId.ConnectionProperties_SslModeDefault':'Default','DataAccessUIStringId.WizardPageEFConnectionProperties_SaveToConfig':'Save the connection string to config file as:','DataAccessUIStringId.ExcelDataSourceWizard_TableItem':'Table','DataAccessUIStringId.ODSEditorsNoDataSetMessage':'The current operation cannot be accomplished unless the data source has been specified.','DataAccessUIStringId.MessageBoxErrorTitle':'Error','DataAccessUIStringId.QueryBuilderJoinTypeUpdatingConfirmation':'The new join type will be applied to all existing relations between the following two tables: {0}, {1}. Do you wish to continue?','DataAccessUIStringId.ODSEditorsIsPropertyMessage':'The {0} data member is a property. To be able to receive parameters, a data member must be a method.','DataAccessUIStringId.ExcelDataSourceEditorTitle':'Excel Data Source Editor','DataAccessUIStringId.MasterDetailEditorEditQueryRelations':'Edit Relations for the \\'{0}\\' Query','DataAccessUIStringId.MasterDetailEditorInvalidQueryNameMessage':'Cannot find the specified query: \"{0}\". Specify an existing query name.','DataAccessUIStringId.WizardPageChooseObjectConstructor_ShowOnlyHighlighted':'Show only highlighted constructors','DataAccessUIStringId.WizardPageChooseConnection_ChooseExistingConnection':'Yes, let me choose an existing connection from the list','DataAccessUIStringId.WizardPageEFConnectionProperties_DefaultConnection':'Use default connection string','DataAccessUIStringId.ConnectionEditorTitle':'Connection Editor','DataAccessUIStringId.WizardPageChooseFileOptions':'Specify import settings.','DataAccessUIStringId.WizardPageConfigureQuery_Query':'Query','DataAccessUIStringId.QueryBuilder_ReverseRelation':'Reverse Relation','DataAccessUIStringId.ConnectionProperties_AuthenticationType_MSSqlServer':'Server authentication','DataAccessUIStringId.WizardPageConfigureEFFilters_ChooseEntityPlaceholder':'Choose Entity','DataAccessUIStringId.ConnectionProperties_AuthenticationType_BigQueryOAuth':'OAuth','DataAccessUIStringId.LoadingDatasourceOutOfMemoryError':'Not enough memory to load data','DataAccessUIStringId.PasswordRequest':'File load error','DataAccessUIStringId.QueryDesignControlTableNameAlreadyExists':'A table with the specified name already exists. Please specify a different table name.','DataAccessUIStringId.QueryBuilder_DeleteCondition':'Delete Condition','DataAccessUIStringId.WizardConfirmExecutionMessage':'Do you want to execute the query on the server and obtain the resulting query schema?','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_ChooseCollectionPlaceholder':'Choose Collection','DataAccessUIStringId.WizardPageChooseMongoDBSchema_QueryName':'Query name:','DataAccessUIStringId.WizardUnableToLoadMongoDBDriver':'An attempt to load the \"MongoDB.Driver.dll\" assembly failed.\\r\\nThe \"MongoDB.Driver\" package should be installed in your application project to provide MongoDB data at runtime.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_AuthenticationType_None':'None','DataAccessUIStringId.WizardPageChooseFileOptions_ValueSeparator':'Value separator:','DataAccessUIStringId.EFDataMemberEditorTitle':'Entity Framework Data Member Editor','DataAccessUIStringId.Button_QueryBuilder':'Run Query Builder...','DataAccessUIStringId.JoinEditor_JoinType':'Join type:','DataAccessUIStringId.SqlDataSourceDesignerVerbRequestDatabaseSchema':'Request Database Schema','DataAccessUIStringId.SortingTypeAscending':'Ascending','DataAccessUIStringId.WizardDataSourceEmptyNameMessage':'<b>The data source name cannot be empty.</b>','DataAccessUIStringId.ODSConstructorEditorTitle':'Configure Constructor Settings','DataAccessUIStringId.ODSParametersEditorTitle':'Configure Parameters','DataAccessUIStringId.QueryBuilder_EditSql':'Edit SQL','DataAccessUIStringId.MasterDetailEditorColumnsHasDifferentTypesConfirmation':'The \\'{0}\\'.\\'{1}\\' and \\'{3}\\'.\\'{4}\\' columns have different types ({2} and {5}). Do you wish to continue?','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_AuthenticationDatabase':'Authentication Database:','DataAccessUIStringId.FederationDataSourceQueryBuilder_RemovedTableMessage':'The \"{0}\" table was removed from the \"{1}\" data source. Remove this table from the federated query to proceed.','DataAccessUIStringId.WizardPageChooseFile':'Select an Excel workbook or CSV file.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_PasteConnectionString':'Paste a connection string','DataAccessUIStringId.MasterDetailEditorRemoveRelationMessage':'Remove the relation','DataAccessUIStringId.WizardPageChooseObjectBindingMode_RetrieveSchemaDescription':'Only the data source schema is retrieved from the specified object, without feeding the actual data.\\r\\n\\r\\nTo manually retrieve the actual data, create a data source object’s instance in code and assign it to the ObjectDataSource.DataSource property.','DataAccessUIStringId.JoinEditorGreaterOperator':'Is greater than','DataAccessUIStringId.FederationDataSourceQueryBuilder_RemovedDataSourceMessage':'The \"{0}\" data source was removed. Remove the \"{1}\" table from the federated query to proceed.','DataAccessUIStringId.DSTypeSql':'Database','DataAccessUIStringId.DSTypeXpo':'XPO','DataAccessUIStringId.QueryBuilderTable':'Table','DataAccessUIStringId.Button_Apply':'Apply','DataAccessUIStringId.Button_Close':'Close','DataAccessUIStringId.QueryDesignControlExpressionChanged':'This action will reset the SQL expression, and all your changes will be discarded. Do you want to continue?','DataAccessUIStringId.XPObjectSource_DataProvidersListMustBeNonEmpty':'DataProviders list is empty.','DataAccessUIStringId.ConnectionProperties_DatabaseListLoadingError':'Database List Loading Error','DataAccessUIStringId.LoadingDataSourceOpeningConnectionError':'Connection name: {0}\\r\\nError message:\\r\\n{1}\\r\\n','DataAccessUIStringId.WizardPageChooseExcelFileDataRange':'Select the required worksheet, table or defined name referring to the specified range.','DataAccessUIStringId.WizardPageChooseFileOptions_Options':'Options','DataAccessUIStringId.WizardPageChooseJsonSchema_FieldExists':'{0} field name already exists at this level','DataAccessUIStringId.PasswordRequest_Password':'Password:','DataAccessUIStringId.FederationDataSourceQueryBuilder_TransformationResult':'Transformation result','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_DatabaseNameColumnName':'Database','DataAccessUIStringId.CustomAssemblyWarning':'You are about to load a third-party library: \\'{0}\\'.\\r\\n\\r\\nBefore you proceed, please consider resulting security risks and make sure that this library is supplied from a trusted source.','DataAccessUIStringId.ConnectionProperties_SslModeNone':'None','DataAccessUIStringId.FiltersView_GroupFilter':'Group Filter','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_EnterConnectionFields':'Enter connection fields individually','DataAccessUIStringId.MessageLessThanTwoQueries':'At least two queries are required to create a master-detail relation.','DataAccessUIStringId.FederationDataSourceDesignerVerbManageQueries':'Manage Queries...','DataAccessUIStringId.FederationDataSourceDesignerVerbRebuildSchema':'Rebuild Result Schema','DataAccessUIStringId.JsonDataSourceDesignerVerbEditSchema':'Edit Schema...','DataAccessUIStringId.QueryBuilder_Rename':'Rename','DataAccessUIStringId.ConnectionProperties_ServiceAccountEmail':'Service account email:','DataAccessUIStringId.MessageBoxConfirmationTitle':'Confirmation','DataAccessUIStringId.QueryBuilder_SortDescending':'Sort Descending','DataAccessUIStringId.ExpressionEditor_NavigateToErrors':'To view the errors, click the drop-down button in the editor\\'s status bar.','DataAccessUIStringId.MessageBoxCloseQueryBuilderDialogConfirmation':'All your changes will be discarded if you close the Query Builder dialog. Do you want to continue?','DataAccessUIStringId.WizardPageSaveJsonConnection_SkipSaveRequestParameters':'No, skip the request parameters','DataAccessUIStringId.ExcelDataSourceIncorrectFilePathExceptionMessage':'Unable to locate file {0}.','DataAccessUIStringId.WizardPageConfigureJsonConnection_HttpHeadersText':'HTTP Header Parameters','DataAccessUIStringId.FiltersView_Filter':'Filter','DataAccessUIStringId.WizardPageChooseMongoDBSchema_FieldName':'Field Name','DataAccessUIStringId.DSTypeMongoDB':'MongoDB','DataAccessUIStringId.WizardPageChooseFileOptions_Encoding':'Encoding:','DataAccessUIStringId.QueryEditorMessageInvalidQuery':'An error occurred during query validation: {0}\\r\\n\\r\\nTo discard this query and invoke the wizard, click OK.\\r\\n\\r\\nTo keep this query, click Cancel.','DataAccessUIStringId.JoinEditorEmptyTableText':'<Select a table>','DataAccessUIStringId.ConnectionProperties_ServerTypeEmbedded':'Embedded','DataAccessUIStringId.ParametersColumn_Value':'Value','DataAccessUIStringId.WizardPageSaveJsonConnection_SaveRequestParameters':'Yes, save the specified request parameters','DataAccessUIStringId.ExpressionEditorViewTitle':'Expression Editor','DataAccessUIStringId.ParametersColumn_Selected':'Selected','DataAccessUIStringId.UpdateSchemaCaption':'Update schema','DataAccessUIStringId.WizardPageChooseConnectionNoChoice':'Select a data connection.','DataAccessUIStringId.Button_Add':'Add','DataAccessUIStringId.WizardPageConfigureParameters':'Configure query parameters and preview the result.','DataAccessUIStringId.XPObjectSourceDesignerVerbPopulateProperties':'Populate Properties','DataAccessUIStringId.EFDataSourceEditorTitle':'Entity Framework Data Source Editor','DataAccessUIStringId.ConnectionProperties_ClientSecret':'Client Secret:','DataAccessUIStringId.LoadingDataSourceAborted':'Data loading has been aborted.','DataAccessUIStringId.Button_Previous':'Previous','DataAccessUIStringId.FederatedQueryCollectionEditorForm_Title':'Manage Queries','DataAccessUIStringId.WizardPageConfigureJsonConnection_ParameterValueText':'Parameter Value','DataAccessUIStringId.ConnectionProperties_ClientLibrary':'Client library:','DataAccessUIStringId.DSTypeEF':'Entity Framework','DataAccessUIStringId.QueryBuilderButtons_EditParameters':'Edit Parameters...','DataAccessUIStringId.ConnectionProperties_KeyFileName':'Key file name:','DataAccessUIStringId.QueryBuilder_EditRelation':'Edit Relation','DataAccessUIStringId.ConnectionProperties_ServerTypeServer':'Server','DataAccessUIStringId.WizardCannotCreateDataSourceMessage':'Cannot create an empty data source. Please select an object to include.','DataAccessUIStringId.QueryFilter_BoundTo':'Bound to {0}','DataAccessUIStringId.WizardPageChooseFileOptions_DetectAutomatically':'Detect automatically','DataAccessUIStringId.ConnectionProperties_DataSetID':'DataSet ID:','DataAccessUIStringId.SortingTypeNone':'Unsorted','DataAccessUIStringId.ParametersGridForm_Title':'Query Parameters','DataAccessUIStringId.ParametersColumn_Expression':'Expression','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_QueryAlias':'Alias','DataAccessUIStringId.WizardPageChooseJsonSource_SourceType_Uri':'Web Service Endpoint (URI)','DataAccessUIStringId.Button_Next':'Next','DataAccessUIStringId.XPObjectSourceDesignerVerbClearProperties':'Clear Properties','DataAccessUIStringId.ODSEditorsCannotResolveDataMember':'Cannot resolve the specified data member. To specify the data member and its parameters, use the Data Member editor.','DataAccessUIStringId.MasterDetailEditorInvalidRelationNameMessage':'A relation with the specified name already exists.','DataAccessUIStringId.WizardPageChooseJsonSource_ResultingUri':'Resulting URI:','DataAccessUIStringId.QueryBuilderCustomSqlRequiresParameters':'The query contains parameters and cannot be executed before they are declared. \\r\\nPlease go to the next wizard page to declare the required query parameters and preview the results.','DataAccessUIStringId.FederationDataSourceQueryBuilder_NodeTypeLabel':'Query Type:','DataAccessUIStringId.ExcelDataSourceDesignerVerbEdit':'Edit...','DataAccessUIStringId.MasterDetailEditorAddConditionMessage':'Create a new condition','DataAccessUIStringId.MasterDetailEditorInvalidColumnNameMessage':'Cannot find the specified column: \"{0}\". Specify an existing column name.','DataAccessUIStringId.QueryBuilderColumns_SortOrder':'Sort Order','DataAccessUIStringId.WizardPageChooseMongoDBSchema_AnalyzeAllDocumentsButton':'Analyze all documents','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_FilterColumnName':'Filter','DataAccessUIStringId.RebuildResultSchemaComplete':'Result schema is rebuilt successfully.','DataAccessUIStringId.RebuildResultSchemaCaption':'Rebuild Result Schema','DataAccessUIStringId.QueryControl_SqlString':'SQL string:','DataAccessUIStringId.WizardPageChooseJsonSource':'Specify JSON data location.','DataAccessUIStringId.WizardPageEFConnectionProperties':'Specify a connection string.','DataAccessUIStringId.WizardPageConfigureMongoDBConnection':'Specify connection properties.','DataAccessUIStringId.WizardPageChooseJsonSchema':'Select data fields.','DataAccessUIStringId.WizardPageChooseMongoDBSchema_Type':'Type','DataAccessUIStringId.SqlDataSourceDesignerVerbManageRelations':'Manage Relations...','DataAccessUIStringId.JoinInformation':'Join Information','DataAccessUIStringId.WizardPageConfigureQuery_StoredProcedure':'Stored Procedure','DataAccessUIStringId.UpdateDBSchemaComplete':'Database schema is updated successfully.','DataAccessUIStringId.WizardPageChooseXPObjectSourceConnectionType_SpecifyConnection':'No, I\\'d like to specify a connection that applies both at design time and runtime.','DataAccessUIStringId.FederationDataSourceDesignerVerbManageRelations':'Manage Relations...','DataAccessUIStringId.WizardPageChooseEFConnectionString_CustomConnection':'No, specify a custom connection string','DataAccessUIStringId.ConnectionProperties_AuthenticationType':'Authentication type:','DataAccessUIStringId.QueryBuilderButtons_Filter':'Filter...','DataAccessUIStringId.WizardPageSaveConnection_SaveCredentials':'Yes, save all required parameters','DataAccessUIStringId.QueryDesignControlDataPreviewCaption':'Data Preview (First 1000 Rows Displayed)','DataAccessUIStringId.EFEditorsNoStoredProcs':'No stored procedures are available in the data context.','DataAccessUIStringId.WizardPageChooseFileOptions_TextQualifier':'Text qualifier:','DataAccessUIStringId.DSTypeObject':'Object','DataAccessUIStringId.PasswordRequest_SavePassword':'Save password','DataAccessUIStringId.WizardPageChooseJsonSource_UriPathParametersText':'URI Path Parameters','DataAccessUIStringId.DSTypeNoData':'No Data','DataAccessUIStringId.ConnectionProperties_UserName':'User name:','DataAccessUIStringId.Button_Remove':'Remove','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_Dsn':'DSN:','DataAccessUIStringId.ODSEditorsNoDataMemberMessage':'Cannot specify parameters unless the DataMember property has been assigned a value.','DataAccessUIStringId.Button_EditRelations':'Manage Relations...','DataAccessUIStringId.WizardPageConfigureQuery':'Create a query or select a stored procedure.','DataAccessUIStringId.EFFilterParametersForm':'Filter Parameters','DataAccessUIStringId.ExpressionEditor_NoSuggestionsMessage':'No suggestions','DataAccessUIStringId.WizardPageChooseJsonSchema_AnalyzeAllRecordsButton':'Analyze all records','DataAccessUIStringId.ExcelDataSourceDesignerVerbUpdateSchema':'Rebuild Result Schema','DataAccessUIStringId.JoinEditorGreaterOrEqualOperator':'Is greater than or equal to','DataAccessUIStringId.WizardDuplicatingColumnNameMessage':'A data schema contains a duplicated column \\'{0}\\'. Modify the query so that all columns have unique names.','DataAccessUIStringId.ConnectionProperties_OracleProviderTypeODPManaged':'ODP Managed','DataAccessUIStringId.WizardEmptyStoredProceduresListMessage':'There are no stored procedures in the current database.','DataAccessUIStringId.SortingTypeDescending':'Descending','DataAccessUIStringId.ParametersColumn_Version':'Version','DataAccessUIStringId.ODSDataSourceEditorTitle':'Configure Data Source','DataAccessUIStringId.WizardPageChooseObjectMember':'Select a data source member (if required).','DataAccessUIStringId.MasterDetailEditorRemoveConditionMessage':'Remove the condition','DataAccessUIStringId.WizardPageChooseJsonSource_Custom':'JSON String:','DataAccessUIStringId.WizardPageChooseMongoDBSchema_FieldDisplayName':'Field Display Name','DataAccessUIStringId.EFConnectionEditorTitle':'Entity Framework Data Connection Editor','DataAccessUIStringId.WizardPageChooseMongoDBSchema_PartiallyAnalyzedCollectionMessage':'The above field types are generated based on the first {0} MongoDB documents.\\r\\n\\r\\nIf your data contains a field whose type inside this limit differs from the type outside of the limit, the corresponding field type is generated incorrectly. This will lead to type deserialization errors.\\r\\n\\r\\nYou can analyze all MongoDB documents to guarantee correct type generation. Note that this might take more time compared to analyzing a limited number of documents.','DataAccessUIStringId.WizardPageSaveConnection_SaveConnectionString':'Do you want to save the connection string to the application\\'s configuration file?','DataAccessUIStringId.QueryFilter_SelectParameterPlaceholder':'Select a parameter...','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_IsSRVRecord':'SRV Record','DataAccessUIStringId.XPObjectSource_ConfirmReplaceProperties':'The Properties collection will be recreated based on the specified entity type information. Do you want to continue?','DataAccessUIStringId.FederationDataSourceQueryBuilder_TransformationNodeRoot':'Transformation node root: {0}','DataAccessUIStringId.QueryDesignControlTableNameEmpty':'The table name cannot be empty.','DataAccessUIStringId.ODSEditorsStaticMemberMessage':'{0} is a static member. Using a constructor to create an instance of the {1} class is not appropriate.','DataAccessUIStringId.FiltersView_SkipTooltip':'This option is only available when the result set is sorted.','DataAccessUIStringId.RebuildResultSchemaConfirmationText':'Do you want to execute the following queries on the server and obtain the resulting schema?','DataAccessUIStringId.WizardPageObjectConstructorParameters':'Specify the constructor parameters.','DataAccessUIStringId.WizardPageConfigureJsonConnection_PasswordText':'Password:','DataAccessUIStringId.SqlQueryCollectionEditorForm_Title':'Manage Queries','DataAccessUIStringId.DataSourceName':'Data source name: {0}','DataAccessUIStringId.WizardPageChooseMongoDBSchema':'Select data fields.','DataAccessUIStringId.MessageBoxCloseManageQueriesDialogConfirmation':'All your changes will be discarded if you close the Manage Queries dialog. Do you want to continue?','DataAccessUIStringId.MessageCannotLoadServersList':'Cannot find any database servers.','DataAccessUIStringId.ConnectionProperties_RefreshToken':'Refresh Token:','DataAccessUIStringId.WizardPageChooseJsonSource_UriQueryParametersText':'Query Parameters','DataAccessUIStringId.JoinEditorLessOrEqualOperator':'Is less than or equal to','DataAccessUIStringId.WizardPageChooseJsonSource_File':'JSON File:','DataAccessUIStringId.WizardPageConfigureMongoDBConnection_AuthenticationType_NamePassword':'Username / Password','DataAccessUIStringId.WizardPageConfigureExcelFileColumns':'Select required columns and specify their settings.','DataAccessUIStringId.QueryBuilderCircularRelationWarning':'The link between {0}.{1} and {2}.{3} results in a circular relation and cannot be added.','DataAccessUIStringId.WizardPageChooseJsonSource_SourceType_Custom':'JSON String','DataAccessUIStringId.ConnectionProperties_AdvantageServerTypeInternet':'Internet','DataAccessUIStringId.WizardPageChooseJsonSource_URI':'Web Service Endpoint (URI):','DataAccessUIStringId.QueryBuilder_AddToSelect':'Add to Query','DataAccessUIStringId.WizardPageConfigureEFFilters_FilterColumnName':'Filter String','DataAccessUIStringId.WizardPageConfigureJsonConnection_HeaderNameText':'Header Name','DataAccessUIStringId.DSTypeJson':'JSON','DataAccessUIStringId.QueryBuilderColumns_TableName':'Table Name','DataAccessUIStringId.WizardPageChooseJsonSchema_FieldDisplayName':'Field Display Name','DataAccessUIStringId.WizardPageConfigureEFFilters':'Add filter criteria to data source tables and/or views.','DataAccessUIStringId.WizardPageChooseJsonSchema_PartiallyAnalyzedJsonMessage':'The above field types are generated based on the first {0} JSON records.\\r\\n\\r\\nIf your data contains a record whose type inside this limit differs from the type outside of the limit, the corresponding field type is generated incorrectly. This will lead to type deserialization errors.\\r\\n\\r\\nYou can analyze all JSON records to guarantee correct type generation. Note that this might take more time compared to analyzing a limited number of documents.','DataAccessUIStringId.WizardPageChooseEFDataMember':'Select a data member','DataAccessUIStringId.ConnectionProperties_ProjectID':'Project ID:','DataAccessUIStringId.JoinEditorFillAllFieldsException':'Some fields are empty. Please fill all empty fields or remove the corresponding conditions to proceed.','DataAccessUIStringId.JoinEditorEqualOperator':'Equals to','DataAccessUIStringId.WizardPageConfigureMongoDBQueries_ChooseDatabasePlaceholder':'Choose Database','DataAccessUIStringId.Button_Browse':'Browse...','DataAccessUIStringId.WizardPageSaveConnection_SkipSaveCredentials':'No, skip credentials for security reasons','DataAccessUIStringId.QueryDesignControlRemoveTables':'The following tables will be removed from the query.\\r\\n\\r\\n{0}\\r\\nDo you want to continue?','DataAccessUIStringId.QueryBuilderColumns_Aggregate':'Aggregate','DataAccessUIStringId.PasswordRequest_FileName':'File name:','DataAccessUIStringId.WizardCannotConnectMessage':'Cannot connect to the database. See the details below.','DataAccessUIStringId.MasterDetailEditorForm_Title':'Master-Detail Relation Editor','DataAccessUIStringId.WizardPageChooseJsonSchema_FieldName':'Field Name','DataAccessUIStringId.WizardPageChooseObjectBindingMode':'Select the data binding mode.','DataAccessUIStringId.ConnectionProperties_AdvantageServerType':'Server type:','DataAccessUIStringId.JoinEditorNotEqualOperator':'Does not equal to','DataAccessUIStringId.WizardDataSourceCreatedMessage':'The data source has been successfully created','DataAccessUIStringId.ChooseEFStoredProceduresDialog':'Select stored procedures to add','DataAccessUIStringId.WizardPageConfigureJsonConnection_UsernameText':'Username:','DevExpress.DataAccess.Sql.ConnectionOptions.CloseConnection':'Close Connection','DevExpress.DataAccess.MongoDB.MongoDBQuery.FilterString':'Filter String','DevExpress.DataAccess.Sql.SqlDataSource.ConnectionParameters':'Connection Parameters','DevExpress.Xpo.XPObjectSource.TopReturnedRecords':'Top Returned 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Records','DevExpress.DataAccess.Sql.CustomSqlQuery.Sql':'SQL','DevExpress.Xpo.XPObjectSource.ConnectionStringName':'Connection String Name','DataAccessStringId.WizardNoEFDataContextsMessage':'The selected assembly does not contain Entity Framework data contexts.','DataAccessStringId.ODSWizardErrorExceptionInCtor':'The default constructor of an ITypedList implementation has thrown an exception.','DataAccessStringId.ConfigureMultiQueryPage_ViewCategory':'Views','DataAccessStringId.WizardDataConnectionNameExistsMessage':'A data connection with the specified name already exists. Please specify a different connection name.','DataAccessStringId.TableNullValidationException':'A table cannot be null.','DataAccessStringId.MongoDB_QueryExecutionException':'Query {0} failed to execute.','DataAccessStringId.GroupByWithoutAggregateValidationException':'Grouping requires at least one aggregated column.','DataAccessStringId.ConfigureMultiQueryPage_TableCategory':'Tables','DataAccessStringId.FileNameFilter_CSV':'CSV Files','DataAccessStringId.PropertyGridBehaviorCategoryName':'Behavior','DataAccessStringId.ProviderNotSupportedLabel':'Certain query features are not supported for the current provider.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Constants':'Constants','DataAccessStringId.LoadingDataSourcePanelText':'Loading data source','DataAccessStringId.ExpressionEditor_DocumentationCategory_Columns':'Columns','DataAccessStringId.ExpressionEditor_DocumentationCategory_Functions':'Functions','DataAccessStringId.LoadingPanelText':'Loading...','DataAccessStringId.SkipWithoutSortingWebValidationException':'The Offset setting is set while records are not sorted. Please apply sorting to be able to skip the first N records.','DataAccessStringId.ConnectingToDatabaseCaption':'Please wait','DataAccessStringId.StoredProcedureParameterTypeValidationException':'Parameter \\'{2}\\' type mismatch: <{0}>, <{1}> is expected.','DataAccessStringId.QueryPropertyGridTableSelectionCategoryName':'Table Selection','DataAccessStringId.XPObjectSource_IncorrectXmlRootElement':'The <{0}> XML root element is incorrect. The <{1}> element is expected.','DataAccessStringId.RelationException':'Cannot set relation between columns \\'{0}\\'.\\'{1}\\' of type {2} and \\'{3}\\'.\\'{4}\\' of type {5}.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Operators':'Operators','DataAccessStringId.ExpressionEditor_Caption':'Expression Editor','DataAccessStringId.EmptyColumnAliasPattern':'Column{0}','DataAccessStringId.ExcelWizard_ValueSeparator_Space':'Space','DataAccessStringId.MessageDuplicateItem':'The collection already contains the \\'{0}\\' item','DataAccessStringId.ExcelWizard_ValueSeparator_Comma':'Comma','DataAccessStringId.ObjectDataSourceWizard_CannotGetTypeProperties':'Cannot get properties for this type.','DataAccessStringId.QueriesFailedToExecute_ExceptionMessage':'One or more queries have failed to execute.','DataAccessStringId.Federation_ConditionColumnMissingInTableValidationErrorMessage':'Column [{0}].[{1}] does not exist in table [{0}]. Condition: [{2}].','DataAccessStringId.LoadingDataSourcePanelCounter':'{0} of {1}...','DataAccessStringId.RunExpressionEditor':'Expression Editor...','DataAccessStringId.ConnectionStringPostfixServerExplorer':' (from the Server Explorer)','DataAccessStringId.ExpressionEditor_DocumentationCategory_ColumnDescriptionFormat':'Type: {0}','DataAccessStringId.ExpressionEditor_DocumentationCategory_Columns_Tooltip':'column','DataAccessStringId.UnnamedColumnValidationException':'The column name is not specified.','DataAccessStringId.CustomExpressionWithColumnOfMissingTableValidationException':'There are no tables containing the column [{0}] that is used in the custom expression.','DataAccessStringId.Type_Object':'Object','DataAccessStringId.ExpressionEditor_InvalidColumn':'Invalid column: \\'{0}\\'.','DataAccessStringId.DatabaseConnectionExceptionMessage':'Connection name: {0}\\r\\n Error message:\\r\\n{1}\\r\\n','DataAccessStringId.SortingBySameColumnTwiceValidationException':'The following column is used as a sorting criterion more than once: \"{0}\".\"{1}\".','DataAccessStringId.RelationEditorRelationTypeLeftOuterJoin':'Left outer join','DataAccessStringId.ExpressionEditor_DocumentationCategory_Custom':'Custom','DataAccessStringId.Federation_ConditionColumnNotExistValidationErrorMessage':'Column [{0}] does not exist in data sources. Condition: [{1}].','DataAccessStringId.ExcelWizard_ValueSeparator_Semicolon':'Semicolon','DataAccessStringId.ProviderNotSupportedException':'The following database provider is not supported: {0}.','DataAccessStringId.StoredProcParamNameValidationException':'Parameter name mismatch: <{0}>, <{1}> is expected.','DataAccessStringId.QueryBuilderAliasAlreadyExists':'The specified alias already exists.','DataAccessStringId.MessageWrongCharacterItemName':'Item name \\'{0}\\' contains wrong characters','DataAccessStringId.GroupByAggregateColumnValidationException':'Cannot group by an aggregate column: \"{0}\".\"{1}\".','DataAccessStringId.Type_Char':'Char','DataAccessStringId.Type_Byte':'Non-negative number (8 bit integer)','DataAccessStringId.Type_UInt':'Non-negative number (32 bit integer)','DataAccessStringId.RelationTableNotSelectedValidationException':'The reference table has not been selected: \"{0}\".','DataAccessStringId.SqlStringEmptyValidationException':'The SQL string is null or empty.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Functions_Tooltip':'function','DataAccessStringId.Type_UShort':'Non-negative number (16 bit integer)','DataAccessStringId.RelationNullValidationException':'A relation cannot be null.','DataAccessStringId.DuplicatingColumnNamesValidationException':'A column with the following name already exists: \"{0}\".\"{1}\".','DataAccessStringId.Wizard_NoDataSourcesForDataFederationMessage':'Provide at least one data source to be used to create a federated data source.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Parameters':'Parameters','DataAccessStringId.ExpressionEditor_FunctionCategory_Logical':'Logical','DataAccessStringId.Type_ByteArray':'Byte array','DataAccessStringId.FilterByAmbiguousColumnValidationException':'The column name [{0}] that is used in the filter string is not unique. Columns with this name exist in the following tables: {1}.','DataAccessStringId.InvalidPortErrorMessage':'Invalid port number. A port number should be between 0 and 65535 inclusive.','DataAccessStringId.ExpressionEditor_InvalidExpression':'Invalid expression.','DataAccessStringId.MongoDB_InvalidDatabaseName':'Invalid database name: \\'{0}\\'.','DataAccessStringId.DefaultNameParameter':'Parameter','DataAccessStringId.RebuildResultSchemaWaitFormText':'Rebuilding the Result Schema...','DataAccessStringId.QueryPropertyGridCommonCategoryName':'Common','DataAccessStringId.QueryBuilderJoinEditorMissingData':'Not all parts of the expression are specified.','DataAccessStringId.ConnectionPropertiesPage_ProviderNotSupported':'Connection parameters were discarded because the {0} provider is not supported. \\r\\nSelect one of the available data providers and specify connection parameters or close the wizard \\r\\nusing the Close button to undo this change.','DataAccessStringId.ExcelEncryptedFileException_EncryptionTypeNotSupported':'The protected file cannot be opened.','DataAccessStringId.NoTablesValidationException':'The collection of tables cannot be empty.','DataAccessStringId.WizardPageChooseJsonSchema_EmptySelection':'Select at least one data field.','DataAccessStringId.SchemaDiscoveryMaxItemCountExceptionMessage':'The value should be greater than or equal to zero.','DataAccessStringId.Federation_NodeIsNotUniqueValidationErrorMessage':'Nodes does not allow duplicates: {0}.','DataAccessStringId.WizardPageChooseMongoDBSchema_EmptySelection':'Select at least one data field for the following queries: {0}.','DataAccessStringId.Federation_EmptySourceNameErrorMessage':'The source name cannot be empty.','DataAccessStringId.GroupFilterStringEditorNoGroups':'Group filtering cannot be applied to data that is not grouped. Please apply data grouping first.','DataAccessStringId.ConfigureMultiQueryPage_QueryCategory':'Queries','DataAccessStringId.ConfigureMultiQueryPage_SpCategory':'Stored Procedures','DataAccessStringId.SkipWithoutSortingValidationException':'The SKIP setting is set while records are not sorted. Please apply sorting to be able to skip the first N records or reset the SKIP setting in the Filter Editor dialog.','DataAccessStringId.ConnectionAborted_ExceptionMessage':'The connection has been canceled.','DataAccessStringId.WizardCustomConnectionString':'Custom connection string','DataAccessStringId.CustomExpressionWithMissingInSchemaColumnValidationException':'Column [{0}].[{1}] is used in the custom expression, but it is missing in DBSchema.','DataAccessStringId.QueryPropertyGridStoredProcCategoryName':'Stored Procedure','DataAccessStringId.ProviderNotSupportedFeatureExceptionHeader':'The following query features are not supported for the current provider:','DataAccessStringId.XmlProviderNotSupportedLabel':'Certain query features are not supported for XML files.','DataAccessStringId.CustomExpressionWithAmbiguousColumnValidationException':'The column name [{0}] that is used in the custom expression is not unique. Columns with this name exist in the following tables: {1}.','DataAccessStringId.MessageCannotRebuildSchema':'An error occurred while rebuilding a data source schema.','DataAccessStringId.StoredProcNameNullValidationException':'The name of a stored procedure cannot be null.','DataAccessStringId.ExpressionNullValidationException':'An expression cannot be null, either column or custom expression expected.','DataAccessStringId.QueryBuilderNoRules':'No rule has been added. Please add at least one rule to proceed.','DataAccessStringId.XPObjectSource_PropertiesCollectionDoesNotContainFetch':'The Properties collection does not contain any item with the enabled Fetch option.','DataAccessStringId.FilterByMissingInSchemaColumnValidationException':'Column [{0}].[{1}] is used in the filter string, but it is missing in DBSchema.','DataAccessStringId.RelationEditorRelationTypeInnerJoin':'Inner join','DataAccessStringId.Federation_FilterColumnMissingInTableValidationErrorMessage':'Column [{0}].[{1}] does not exist in table [{0}]. Filter string: [{2}].','DataAccessStringId.ExcelDataSource_SchemaLoadingText':'Schema loading...','DataAccessStringId.IncompleteRelationValidationException':'The specified relation is incomplete: \"{0}\".','DataAccessStringId.Federation_ColumnTableNotExistValidationErrorMessage':'Column [{0}].[{1}] does not exist in data sources.','DataAccessStringId.ManageQueries_QueryIsNotValid':'The \\'{0}\\' query is invalid. {1}','DataAccessStringId.Federation_UnionWithDifferentColumnTypesErrorMessage':'Union node {0}: related columns must have similar  types: {1}.{2}, {3}.{4}.','DataAccessStringId.Type_SByte':'Number (8 bit integer)','DataAccessStringId.ExcelEncryptedFileException_WrongPassword':'The password is not correct. Please try again.','DataAccessStringId.Type_ULong':'Non-negative number (64 bit integer)','DataAccessStringId.RelationEditorRelationTypeMasterDetail':'Master-detail relation','DataAccessStringId.ResultRelation_ColumnNotFoundError':'Column not found: \\'{0}\\'.\\'{1}\\'.','DataAccessStringId.Federation_ExpressionColumnNotExistValidationErrorMessage':'Column [{0}] does not exist in data sources. Expression: [{1}].','DataAccessStringId.MessageDuplicateQueryName':'A query with the specified name already exists: {0}.','DataAccessStringId.ConnectionStringPostfixAppConfig':' (in the config file)','DataAccessStringId.XPObjectSource_ConnectionStringIsEmpty':'Connection string is empty. To specify the connection, do one of the following: specify the ConnectionString property value; add the connection string to the application configuration file and specify the ConnectionStringName property value; handle the ResolveSession event; setup the default DataLayer.','DataAccessStringId.Federation_TransformationDuplicatedColumnNamesValidationErrorMessage':'The {0} node contains columns with duplicated names: {1}.','DataAccessStringId.MessageEmptyQueryName':'The query name cannot be empty.','DataAccessStringId.ObjectDataSourceWizard_CannotGetPropertiesForThisMethodReturnType':'Cannot get properties for the type returned by this method.','DataAccessStringId.GroupNullValidationException':'A grouping criteria cannot be null.','DataAccessStringId.MessageCannotLoadCustomAssembly':'Unable to load the {0} assembly for the {1} context. Please choose an existing external assembly and/or existing context.','DataAccessStringId.IntegerDivisionValidationMessage':'Please Note:  This Expression engine discards fractions during integer division operations. To return decimal values (floating-point division), use ToDecimal(), ToDouble() or ToFloat() for your expression. For instance, ToDecimal(10)/4 will return 2.5 whereas 10/4 will return 2.','DataAccessStringId.WizardPageChooseJsonSource_DataLocationMismatch':'The specified JSON data location does not correspond to the chosen JSON source.','DataAccessStringId.UnknownType':'Unknown','DataAccessStringId.ConfigureQueryPage_CustomSqlWillBeLost':'Manual editing of custom SQL is not allowed. The current query is represented by a custom SQL query string, \\r\\nwhich will be lost if you proceed with editing the query using the Query Builder dialog. \\r\\n\\r\\nDo you want to discard the custom SQL and proceed with the Query Builder?','DataAccessStringId.NoRelationColumnsValidationException':'Columns are not specified for the relation: \"{0}\".','DataAccessStringId.ExpressionEditor_NotSupportedAggregateFunction':'The following aggregate function is not supported: \\'{0}\\'.','DataAccessStringId.QueryBuilderNoTablesAndViews':'A database does not contain tables or views and does not support SQL editing. To be able to run the Query Builder, make sure that your database contains at least one table or supports SQL editing.','DataAccessStringId.HavingWithoutGroupByValidationException':'Group filtering criteria are defined while data is not grouped. Please apply data grouping or remove group filtering criteria on the Group Filter tab of the Filter Editor dialog.','DataAccessStringId.ParameterlessConstructor':'default','DataAccessStringId.RelationEditorRelationTypeFullOuterJoin':'Full outer join','DataAccessStringId.Federation_ColumnNotExistInTableValidationErrorMessage':'Table [{0}] does not contain the column [{1}].','DataAccessStringId.SortingNullValidationException':'A sorting criteria cannot be null.','DataAccessStringId.TableNotInSchemaValidationException':'The schema does not contain the specified table: \"{0}\".','DataAccessStringId.FilterByColumnOfMissingTableValidationException':'There are no tables containing the column [{0}] that is used in the filter string.','DataAccessStringId.InvalidExpressionStringValidationException':'Cannot parse the following expression string: \"{0}\".','DataAccessStringId.PartialAggregationValidationException':'Certain columns on the select list are invalid because they are not contained in either an aggregate function or in the Group By clause. Apply aggregation/grouping either to all columns or to none of them.','DataAccessStringId.ParameterListEmpty':'none','DataAccessStringId.SortByAggregateColumnValidationException':'Cannot sort by an aggregate column: {0}({1}), because the query is not aggregated.','DataAccessStringId.Federation_NodeWithoutExpressionValidationErrorMessage':'Node without expression: {0}.','DataAccessStringId.QueryBuilder_AllTables':'(All Tables)','DataAccessStringId.ExpressionEditor_InvalidCustomFunction':'Invalid function: \\'{0}\\'.','DataAccessStringId.QueryDesignerJoinExpressionPattern':'{0} on {1}','DataAccessStringId.NegativeTopSkipValidationException':'Top and Skip properties should be non-negative integer.','DataAccessStringId.ExcelDataSource_FileNotFoundMessage':'{0}\\r\\nFile not found.\\r\\nCheck the file name and try again.','DataAccessStringId.Federation_FilterAmbiguousColumnNameValidationErrorMessage':'Column name [{0}] is not unique. The same column name exists in the tables: {1}. Filter string: [{2}].','DataAccessStringId.StoredProcParamCountValidationException':'Parameter count mismatch: <{0}>, <{1}> is expected.','DataAccessStringId.ParameterListNull':'null','DataAccessStringId.XmlProviderNotSupportedFeatureException':'The XML data provider cannot perform actions that require SQL queries. \\r\\nThe following SelectQuery properties and methods are not supported: SelectExpression, SelectAll, SelectRecordsCount, Distinct. \\r\\nDo not use them in the query, or convert the XML data to another data format and use an appropriate data source.','DataAccessStringId.FileNameFilter_Excel':'Excel Workbooks','DataAccessStringId.ODSWizardErrorNoDefaultCtor':'Cannot get item properties from IListSource without default constructor.','DataAccessStringId.PositiveIntegerError':'Only non-negative numeric values are allowed.','DataAccessStringId.ExpressionEditor_FunctionCategory_Aggregate':'Aggregate','DataAccessStringId.Federation_UnionWithDifferentNumberOfColumnsErrorMessage':'Union node {0}: elements must have the same number of columns: {1}, {2}.','DataAccessStringId.MessageCannotCreateSelectStatement':'Select statement creation failed.','DataAccessStringId.CustomSqlQueryValidationException':'A custom SQL query should contain only SELECT statements.','DataAccessStringId.MongoDB_NoQueriesMessage':'No queries.','DataAccessStringId.GatheringTypesPanelText':'Gathering types information...','DataAccessStringId.UnnamedTableValidationException':'The table name is not specified.','DataAccessStringId.WizardEmptyConnectionNameMessage':'The name cannot be null, empty or contain only whitespaces.','DataAccessStringId.ColumnNotInSchemaValidationException':'The schema does not contain the following column: \"{0}\".\"{1}\".','DataAccessStringId.StoredProcParamTypeValidationException':'Parameter type mismatch: <{0}>, <{1}> is expected.','DataAccessStringId.QueriesFailedToValidate_ExceptionMessage':'One or more queries have failed to validate.','DataAccessStringId.ExcelInvalidFileException_WrongFormat':'Incorrect file format','DataAccessStringId.LoadingDataPanelText':'Loading Data...','DataAccessStringId.QueryBuilderCanJoin':'Can join {0}','DataAccessStringId.Federation_ExpressionColumnMissingInTableValidationErrorMessage':'Column [{0}].[{1}] does not exist in table [{0}]. Expression: [{2}].','DataAccessStringId.MessageNonexistentQuery':'Query \\'{0}\\' does not exist.','DataAccessStringId.QueryPropertyGridCustomSqlCategoryName':'Custom SQL','DataAccessStringId.QueryBuilderNothingSelected':'No column has been selected. Please select at least one column to proceed.','DataAccessStringId.Federation_UnionWithNoElementsValidationErrorMessage':'Union node contains no elements: {0}.','DataAccessStringId.MessageWrongCharacterParameterName':'Parameter name \\'{0}\\' contains wrong characters','DataAccessStringId.MessageCannotOpenDatabase':'Unable to open a database.','DataAccessStringId.MessageDuplicateItemName':'This collection already contains an item with the \\'{0}\\' name','DataAccessStringId.DatabaseConnectionExceptionStringId':'Failed to connect to the database. To learn more, see the exception details. \\r\\n\\r\\nException details:\\r\\n {0}','DataAccessStringId.MessageNullItem':'Cannot add a null value to the collection','DataAccessStringId.QueryBuilder_RowCount':'(Row Count)','DataAccessStringId.ConfigureMultiQueryPage_ValidateRelationError':'One or more relations are invalid. \\r\\nTo learn about the error details, click Manage Relations.','DataAccessStringId.Federation_NestedFederatedDataSourceErrorMessage':'Federated data source cannot be used as a data source for another federated data source.','DataAccessStringId.Federation_ConditionAmbiguousColumnNameValidationErrorMessage':'Column name [{0}] is not unique. The same column name exists in the tables: {1}. Condition: [{2}].','DataAccessStringId.ExcelDataSource_WorksheetNotFoundMessage':'{0}\\r\\nWorksheet not found.\\r\\nCheck the worksheet name and try again.','DataAccessStringId.ProviderNotSupportedFeatureParametersInSelect':'parameters in column expressions','DataAccessStringId.MessageNonexistentColumn':'Column \\'{0}\\'.\\'{1}\\' does not exist.','DataAccessStringId.QueryBuilderJoinedOn':'Joined on {0}','DataAccessStringId.FilterByMissingParameterValidationException':'Parameter [{0}] is used in the filter string, but is missing in the query.','DataAccessStringId.Federation_ExpressionNodeNullValidationErrorMessage':'Node contains an expression that is not linked to a node: {0}.','DataAccessStringId.DefaultNameDataSource':'Data Source','DataAccessStringId.CustomExpressionWithMissingParameterValidationException':'Parameter [{0}] is used in the custom expression, but is missing in the query.','DataAccessStringId.XPObjectSource_InvalidEntityTypeString':'\\'{0}\\' is an invalid entity type string. Assign the comma-separated full type name and assembly name to the EntityTypeString property.','DataAccessStringId.FilterEditor_TreeCreationError':'Cannot create a tree for this expression','DataAccessStringId.StoredProcParamNullValidationException':'A parameter cannot be null.','DataAccessStringId.DuplicatingTableNamesValidationException':'A table with the following name already exists: \"{0}\".','DataAccessStringId.SqlQueryExecutionException':'Query {0} failed to execute.','DataAccessStringId.ConnectingToDatabaseMessage':'Connecting to the database...','DataAccessStringId.ExpressionEditor_DocumentationCategory_Parameters_Tooltip':'parameter','DataAccessStringId.PropertyGridDesignCategoryName':'Design','DataAccessStringId.ExcelEncryptedFileException_PasswordRequired':'A password is required to open this workbook.','DataAccessStringId.QueryBuilder_AllColumns':'* (All Columns)','DataAccessStringId.Federation_FilterColumnNotExistValidationErrorMessage':'Column [{0}] does not exist in data sources. Filter string: [{1}].','DataAccessStringId.ExpressionEditor_EmptyExpression':'The expression string cannot be empty.','DataAccessStringId.ExpressionEditor_DocumentationCategory_Constants_Tooltip':'constant','DataAccessStringId.NoColumnsValidationException':'None of the tables contain any columns.','DataAccessStringId.WizardAssemblyLoadingDisallowed':'Cannot load this assembly for security reasons.','DataAccessStringId.ConnectionNotSpecified_ExceptionMessage':'No connection has been specified.','DataAccessStringId.ExcelDataSource_WorksheetIndexNotFoundMessage':'Worksheet {0} not found.\\r\\nCheck the worksheet index and try again.','DataAccessStringId.TablesNotRelatedValidationException':'The following tables have no relations: \"{0}\".','DataAccessStringId.DataSourceFillExceptionMessage':'Failed to load data. Refer to the exception details for more information. \\r\\n\\r\\nException details:\\r\\n {0}','DataAccessStringId.XmlFileStrategy_FileNameFilter':'XML Files','DataAccessStringId.SqlExecutionException':'Error trying to execute an SQL query{0}{1}.{2}Error: {3}','DataAccessStringId.RelationColumnNotInSchemaValidationException':'The schema does not contain the following relation column: \"{0}\".\"{1}\".','DataAccessStringId.XPObjectSource_PropertyCannotBeFetched':'The \\'{1}\\' type of the \\'{0}\\' property is not supported when the Properties collection is specified explicitly.','DataAccessStringId.ODSErrorMissingMember':'A data member \\'{0}\\' does not exist.','DataAccessStringId.MessageInvalidItemName':'Item name cannot be null or an empty string','DataAccessStringId.EFFilterControl_EmptyFilterString':'A filter string cannot be null.','DataAccessStringId.Federation_RootNullValidationErrorMessage':'Root reference is not initialized: {0}.','DataAccessStringId.ObjectDataSourceLoadingWarningMessage':'Loading the data sources referenced in this file may harm your computer. Was this file obtained from a trusted source?\\r\\n\\r\\nClick \\'Yes\\' to load the data source content as is.\\r\\nClick \\'No\\' to load only trusted data source content.','DataAccessStringId.Federation_DuplicatedExpressionNamesValidationErrorMessage':'Node {0} contains expressions with duplicated actual names: {1}.','DataAccessStringId.QueryDesignerJoinExpressionElementSeparator':', ','DataAccessStringId.QueryDesignerJoinTooltipPattern':'[{0}] {1} join [{2}] on {3}','DataAccessStringId.RelationColumnNullValidationException':'The relation column cannot be null.','DataAccessStringId.MongoDB_InvalidCollectionName':'Invalid collection name: \\'{0}\\'.','DataAccessStringId.OdbcDriverDoesNotSupportOAuthErrorMessage':'The ODBC driver does not support the OAuth authentication type. Use the Key file authentication or Install the DevExpress BigQueryProvider to use OAuth.','DataAccessStringId.QueryBuilderNoTablesSelected':'No table has been selected. Please select at least one table to proceed.','DataAccessStringId.StoredProcNotInSchemaValidationException':'Cannot find the specified stored procedure: \"{0}\".','DataAccessStringId.ExpressionEditor_FunctionCategory_Math':'Math','DataAccessStringId.ExpressionEditor_FunctionCategory_Text':'String','DataAccessStringId.PropertyGridDataCategoryName':'Data','DataAccessStringId.PropertyGridConnectionCategoryName':'Connection','DataAccessStringId.Federation_ExpressionAmbiguousColumnNameValidationErrorMessage':'Column name [{0}] is not unique. The same column name exists in the tables: {1}. Expression: [{2}].','DataAccessStringId.ExcelInvalidFileException_CorruptedFile':'The file is corrupt.','DataAccessStringId.FileNameFilter_AllFormats':'All Supported Formats','DataAccessStringId.SqlExecutionException_WithParameters':' with parameters:{0}{1}','DataAccessStringId.ExpressionEditor_DocumentationCategory_Operators_Tooltip':'operator','DataAccessStringId.WizardPageChooseJsonSource_UnknownFormat':'Unable to load data because the format of the specified URI cannot be determined.','DataAccessStringId.CircularRelationsValidationException':'Circular relations have been detected.','DataAccessStringId.MongoDB_DuplicateQueryNameMessage':'A query with the specified name already exists: {0}.','DataAccessStringId.ExcelInvalidFileException_BIFF5Format':'BIFF5 (Excel 5.0/95) XLS file format is not supported.','DataAccessStringId.ExpressionStringNullValidationException':'An expression string cannot be null','DataAccessStringId.QueryBuilderInvalidFilter':'Please click the \\'Filter...\\' button to correct the filter string.','DataAccessStringId.Federation_TransformationNodeWithoutRuleValidationErrorMessage':'Transformation node without rule: {0}.','DataAccessStringId.AggregateQueryInvalidSortingValidationException':'Invalid sorting column \"{0}\".\"{1}\". Results of a TableQuery containing aggregate functions can only be sorted by columns used as grouping criteria.','DataAccessStringId.Federation_SourceNullValidationErrorMessage':'Source reference is not initialized: {0}.','DataAccessStringId.ManageQueries_QueryIsNotValid_Postfix':'Fix the error or remove the query to proceed.','DataAccessStringId.ODSWizardErrorStaticValue':'The type is static and it does not have any members returning IEnumerable.','DataAccessStringId.RelationEditorRelationTypeRightOuterJoin':'Right outer join','DataAccessStringId.TableNotSelectedValidationException':'The following table is not in tables list, but its column is used: \"{0}\".','DataAccessStringId.ODSWizardErrorExceptionInGetItemProperties':'The GetItemProperties method of an ITypedList has thrown an exception.','DataAccessStringId.ExcelWizard_ValueSeparator_Tab':'Tab','DataAccessStringId.Federation_DuplicateSourceNameErrorMessage':'A source with the specified name already exists: {0}.','DataAccessStringId.ColumnNullValidationException':'A column cannot be null.','DataAccessStringId.XPObjectSource_ConnectionStringMissing':'The \\'{0}\\' connection string is missing in the application configuration file.','DataAccessStringId.Type_TimeSpan':'Time interval','DataAccessStringId.ExpressionEditor_InvalidParameter':'Invalid parameter: \\'{0}\\'.','DataAccessStringId.Federation_NodeExpressionNameNullValidationErrorMessage':'Node contains an unnamed expression: {0}.','DataAccessStringId.AggregationWithoutAliasValidationException':'An aggregate column should have an alias.','DataAccessStringId.ExpressionEditor_FunctionCategory_DateTime':'DateTime','DataAccessStringId.NoXpoProviderStringId':'The connection string contains no XpoProvider key or the specified key is invalid. \\r\\n\\r\\nException details:\\r\\n {0}','DataAccessStringId.SkipWithoutSortingPropertyGridError':'The SKIP setting is set while records are not sorted. Please apply sorting to be able to skip the first N records.','DashboardStringId.CalculatedFieldTypeBoolean':'Boolean','DashboardStringId.TextGroupIntervalAlphabetical':'Alphabetical','DashboardStringId.FormatConditionAppearanceFontRed':'Red Font','DashboardStringId.FormatRuleApplyToReadOnlyDescription':'The selected style applies to all layout elements','DashboardStringId.StartDate':'(Start Date)','DashboardStringId.DefaultNameTreemapItem':'Treemap','DashboardStringId.DateTimeFormatYearFormatDefaultCaption':'Default','DashboardStringId.DeltaValueTypeActualValueCaption':'Actual value','DashboardStringId.DataSourceFederationQuery':'Query','DashboardStringId.NumericFormatFormatTypeAutoCaption':'Auto','DashboardStringId.MessageWrongExtractDataSourceConnectionParametersType':'Connection parameters are invalid. An extract data source supports only ExtractDataSourceConnectionParameters.','DashboardStringId.ParameterFalseExportValue':'False','DashboardStringId.FunctionDescriptionWindowMedian':'WindowMedian(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the median of the expression within the window.','DashboardStringId.SparklineArgumentValueSeparator':' - ','DashboardStringId.NumericFormatFormatTypeCustomCaption':'Custom','DashboardStringId.PieCalculationAlongSeries':'Series','DashboardStringId.SparklineTooltipMaxValue':'Max:','DashboardStringId.FunctionDescriptionWindowDefinitionOrderAsc':'asc(column)\\r\\nData rows are sorted by values in the specified column in ascending order. This is the default sort order.','DashboardStringId.ActionRestoreDashboardItem':'Restore','DashboardStringId.DashboardErrorValue':'Error','DashboardStringId.GridCalculationAlongRowsAndSparklineArgument':'Rows / Sparkline Argument','DashboardStringId.MessageDashboardNotFoundError':'Dashboard has not been found.','DashboardStringId.CommandFormatRuleBarRangeColors':'Bar Color Ranges','DashboardStringId.DateTimeFormatDateTimeFormatLongCaption':'Long','DashboardStringId.RangeFilterCustomDateTimePeriod':'Custom Period...','DashboardStringId.FormatConditionAppearanceGradientOrange':'Gradient Orange','DashboardStringId.DescriptionColumns':'Columns','DashboardStringId.DateTimeFormatDateTimeFormatDefaultCaption':'Default','DashboardStringId.DateTimeIntervalMinute':'Minute','DashboardStringId.PaperKindLetter':'Letter','DashboardStringId.PeriodThisDay':'This Day','DashboardStringId.InitialExtent':'Initial Extent','DashboardStringId.MessageDashboardNotRelevantError':'Dashboard object model was changed. Refresh operation is required.','DashboardStringId.ActionExportToExcel':'Export To Excel','DashboardStringId.DateTimeFormatMonthFormatDefaultCaption':'Default','DashboardStringId.ActionAllowMultiselection':'Multi-Select','DashboardStringId.PageLayout':'Page Layout','DashboardStringId.DashboardNullValue':' ','DashboardStringId.ExtractColumnUnsupportedTypeError':'The following columns have unsupported types: \\r\\n{0}','DashboardStringId.ActionExportToImage':'Export To Image','DashboardStringId.ScaleFactor':'Scale Factor','DashboardStringId.FormatConditionAppearanceGradientPurple':'Gradient Purple','DashboardStringId.FormatMasterFilterDisplayText':', {0}','DashboardStringId.RangeFilterIncompatibleDateTimeGroupInterval':'Date-time argument values should identify actual calendar dates or time spans rather than grouping (i.e., they should contain a year part). Change the group interval accordingly','DashboardStringId.DateTimeGroupIntervalQuarterYear':'Quarter-Year','DashboardStringId.SeriesTypeArea':'Area','DashboardStringId.SeriesTypeLine':'Line','DashboardStringId.PieCalculationAlongArguments':'Arguments','DashboardStringId.DefaultFederationDataSourceName':'Federated Data Source','DashboardStringId.CustomExpressionCalculationMeasureCaption':'Calculation','DashboardStringId.MessageDuplicateDataItemId':'A data item identifier with the same name already exists.','DashboardStringId.NumericFormatFormatTypePercentCaption':'Percent','DashboardStringId.RedoText':'Redo','DashboardStringId.RankOrderAscending':'Ascending','DashboardStringId.ParametersSelectorText':'Select...','DashboardStringId.CardRowDataElementTypeDimensionValueCaption':'Dimension','DashboardStringId.CommandFormatRuleContains':'Text that Contains','DashboardStringId.CardRowDataElementTypeSparklineCaption':'Sparkline','DashboardStringId.DefaultNameTabContainerItem':'Tab Container','DashboardStringId.PivotCalculationAlongColumns':'Columns','DashboardStringId.DescriptionArgument':'Argument','DashboardStringId.PeriodThisMonth':'This Month','DashboardStringId.MessageInvalidDataFormat':'Cannot convert the {0} value to the {1} data type.','DashboardStringId.DataSourceQuery':'Query','DashboardStringId.FromDatePeriodCaption':'From {0}','DashboardStringId.DescriptionMapValues':'Map / Values','DashboardStringId.DateTimeGroupIntervalDayOfWeek':'Day of Week','DashboardStringId.DateTimeGroupIntervalDayOfYear':'Day of Year','DashboardStringId.MessageIncorrectLayoutItemWeight':'Layout item weight cannot be negative or equal to zero','DashboardStringId.DataEngineGrandTotal':'Grand Total','DashboardStringId.DefaultNameGaugeItem':'Gauges','DashboardStringId.PeriodNextYear':'Next Year','DashboardStringId.PeriodNextHour':'Next Hour','DashboardStringId.FunctionDescriptionGetDateWeekYear2':'GetDateWeekYear(DateTime, [\\'FirstDay\\', \\'FirstFullWeek\\', \\'FirstFourDayWeek\\'])\\r\\nReturns the date of the first day of the week for a given DateTime. The second parameter determines the rule for calculating the calendar week.','DashboardStringId.DescriptionItemDimension':'Dimension','DashboardStringId.CommandFormatRuleNotBetweenOrEqual':'Not Between Or Equal To','DashboardStringId.CardLayoutTemplateCompactCaption':'Compact','DashboardStringId.DisplayValueCaption':'Display Value','DashboardStringId.DateTimeQuarterFormatSpecifier':'QQ','DashboardStringId.IntegerDivisionValidationMessage':'Please Note:  This Expression engine discards fractions during integer division operations. To return decimal values (floating-point division), use ToDecimal(), ToDouble() or ToFloat() for your expression. For instance, ToDecimal(10)/4 will return 2.5 whereas 10/4 will return 2.','DashboardStringId.FormatConditionAppearanceFontStrikeout':'Strikeout','DashboardStringId.FormatRuleUnableToAddRule_NoItemsToCalculate':'Unable to add a new format rule. There is no data item to calculate the rule.','DashboardStringId.ChoroplethMapUseBindingAttribute':'Use binding attribute','DashboardStringId.FunctionDescriptionStdDev':'StdDev(Value)\\r\\nReturns an estimate of the standard deviation of a population, where the sample is a subset of the entire population.','DashboardStringId.CommandFormatRuleGradientRangeBar':'Bar Gradient Ranges','DashboardStringId.RangeFilterOLAPDataSource':'The Range Filter is not supported in OLAP mode.','DashboardStringId.IntersectionLevelModeFirst':'First level','DashboardStringId.MessageIncorrectNumericPrecision':'The numeric value precision cannot be negative.','DashboardStringId.ActualValueCaption':'Actual','DashboardStringId.CommandFormatRuleExpression':'Expression','DashboardStringId.ActionPrintPreview':'Print Preview...','DashboardStringId.DescriptionItemColumn':'Column','DashboardStringId.FunctionDescriptionRunningCount':'RunningCount(SummaryExpression)\\r\\nReturns the running count of the specified expression from the first row in the window to the current row.','DashboardStringId.CalculatedFieldTypeLong':'Integer','DashboardStringId.CalculatedFieldTypeAuto':'Auto','DashboardStringId.NumericFormatFormatTypeGeneralCaption':'General','DashboardStringId.DefaultFileExtractDataSourceName':'Extract Data Source','DashboardStringId.HiddenDataItemsHeader':'HIDDEN DATA ITEMS','DashboardStringId.ElementNameGauges':'Gauges','DashboardStringId.OpenCaption':'Open','DashboardStringId.FunctionOperatorExFunctionDescriptionMakeDateTime6':'MakeDateTime(Year, Month, Day, Hour, Minute, Second)\\r\\nReturns a date value constructed from the specified Year, Month, Day, Hour, Minute and Second.','DashboardStringId.FunctionOperatorExFunctionDescriptionMakeDateTime5':'MakeDateTime(Year, Month, Day, Hour, Minute)\\r\\nReturns a date value constructed from the specified Year, Month, Day, Hour and Minute.','DashboardStringId.FunctionOperatorExFunctionDescriptionMakeDateTime4':'MakeDateTime(Year, Month, Day, Hour)\\r\\nReturns a date value constructed from the specified Year, Month, Day and Hour.','DashboardStringId.FunctionOperatorExFunctionDescriptionMakeDateTime3':'MakeDateTime(Year, Month, Day)\\r\\nReturns a date value constructed from the specified Year, Month and Day.','DashboardStringId.Resolution':'Resolution (dpi)','DashboardStringId.CalculationTypeNone':'None','DashboardStringId.CalculationTypeRank':'Rank','DashboardStringId.SeriesTypeCandleStick':'Candle Stick','DashboardStringId.RangeFilterSelectRangeFromCaption':'From:','DashboardStringId.GridTotalAutoTemplate':'{0}','DashboardStringId.FunctionDescriptionSize':'Size()\\r\\nReturns the number of rows in the window.','DashboardStringId.FunctionDescriptionVarp':'Varp(Value)\\r\\nReturns the variance of a population, where the population is the entire data to be summarized.','DashboardStringId.FunctionDescriptionAggr':'aggr(SummaryExpression, Dimension1, Dimension2, ...)\\r\\nUses the detail level and summary function to aggregate underlying data. The level depends on the number of dimensions.','DashboardStringId.FunctionDescriptionLast':'Last()\\r\\nReturns the number of rows from the current row to the last row in the window.','DashboardStringId.MessageAggregateFunctionInMasterFilterDimension':'Master filtering cannot be applied by values of the dimension created based on the calculated field with the Aggr function. The following dimensions are created based on such fields: {0}.','DashboardStringId.ActionExportDashboard':'Export Dashboard','DashboardStringId.CommandFormatRuleRangeGradient':'Gradient Ranges','DashboardStringId.ParameterNullExportValue':'null','DashboardStringId.PageLayoutPortrait':'Portrait','DashboardStringId.PeriodLastSecond':'Last Second','DashboardStringId.FormatConditionAppearanceFontBlue':'Blue Font','DashboardStringId.FormatConditionAppearanceFontBold':'Bold','DashboardStringId.DateTimeGroupIntervalDateHour':'Date-Hour','DashboardStringId.DefaultNameTextBoxItem':'Text Box','DashboardStringId.MessageInvalidCardLayoutTemplateMaxWidth':'The maximum width must be greater than zero or equal to null.','DashboardStringId.CalculatedFieldTypeDateTime':'DateTime','DashboardStringId.CommandFormatRuleNotBetween':'Not Between','DashboardStringId.DateTimeFormatQuarterFormatNumericCaption':'Numeric','DashboardStringId.FormatStringDataItemName':'{0} ({1})','DashboardStringId.FormatRuleApplyToColumn':'Apply to column','DashboardStringId.ButtonOK':'OK','DashboardStringId.DateTimeIntervalQuarter':'Quarter','DashboardStringId.FormatRuleUnableToAddRule_NoCardsToApply':'Unable to add a new format rule. There is no card to apply the rule.','DashboardStringId.GridTotalTypeCount':'Count','DashboardStringId.DescriptionTooltipMeasures':'Tooltip measures','DashboardStringId.DashboardDataUpdating':'Updating','DashboardStringId.MessageInvalidDeltaIndicatorSize':'The delta indicator size must be greater than zero.','DashboardStringId.DeltaValueTypePercentVariationCaption':'Percent variation','DashboardStringId.FormatRuleRangeDelete':'Delete','DashboardStringId.IncorrectParameterType':'The dashboard parameter values type does not correspond to Parameter.Type.','DashboardStringId.IncludeExportDashboardState':'Include','DashboardStringId.RangeFilterCalculationAlongSeries':'Series','DashboardStringId.PeriodLastDay':'Last Day','DashboardStringId.TreemapLabelValueTemplate':'{0}: {1}','DashboardStringId.MessageLayoutDuplicatedDashboardItem':'A layout item for the specified dashboard item has already been added to the layout tree','DashboardStringId.ExtractPreprocessorColumnError':'The following columns cannot be processed:\\r\\n{0}','DashboardStringId.PercentOfTotalCalculationMeasureCaptionFormatString':'Percent of {0} Total','DashboardStringId.AggregateExFunctionDescriptionCountNotNull':'CountNotNull(Value)\\r\\nReturns a number of non-null objects in a collection.','DashboardStringId.MessageUnassignedDashboardItemGroup':'The dashboard item group should belong to the dashboard. To add a group to the dashboard, use the Dashboard.Groups property.','DashboardStringId.CommandFormatRuleAboveAverage':'Above Average','DashboardStringId.FunctionOperatorExFunctionDescriptionGetQuarter':'GetQuarter(DateTime)\\r\\nExtracts a quarter from the defined DateTime.','DashboardStringId.SeriesTypeHighLowClose':'High-Low-Close','DashboardStringId.FunctionOperatorExFunctionDescriptionGetWeekOfYear':'GetWeekOfYear(DateTime)\\r\\nExtracts the week of the year from the defined DateTime.','DashboardStringId.ExtractColumnUnsupportedTypeTooltip':'The column has unsupported type','DashboardStringId.CommandFormatRuleRangeColors':'Color Ranges','DashboardStringId.IntersectionLevelModeLast':'Last level','DashboardStringId.IntersectionLevelModeAuto':'(Auto)','DashboardStringId.FormatConditionAppearancePaleOrange':'Pale Orange','DashboardStringId.CalculationTypeRunningTotal':'Running Total','DashboardStringId.GridSortAscending':'Sort Ascending','DashboardStringId.AxisYNameCount':'Count','DashboardStringId.MessageLegacyCardLayoutIsNotSupported':'Card layout is outdated and cannot be displayed. To view this item, specify the layout template in the Dashboard Designer. To know more, see the \\'Designing Dashboard Items > Cards > Layout\\' documentation topic.','DashboardStringId.FunctionCategoryCustomAggregateNames':'Custom Aggregate Names','DashboardStringId.FormatRuleFormatStyle':'Format style','DashboardStringId.ChartCalculationAlongArguments':'Arguments','DashboardStringId.FunctionCategoryWindow':'Window','DashboardStringId.MessageInvalidFontSize':'The font size must be greater than zero.','DashboardStringId.CalculationTypeExpression':'Expression','DashboardStringId.NumericFormatUnitAutoCaption':'Auto','DashboardStringId.DefaultNameCustomItem':'Custom Item','DashboardStringId.DateTimeFormatYearFormatAbbreviatedCaption':'Abbreviated','DashboardStringId.RangeFilterEmptySeries':'Please specify Range Filter values','DashboardStringId.DateTimeIntervalSecond':'Second','DashboardStringId.RankTypeModified':'Modified','DashboardStringId.DateFilterDatePickerButtonDefaultText':'Set Filter...','DashboardStringId.RankCalculationMeasureCaptionFormatString':'Rank of {0}','DashboardStringId.FormatStringDashboardItemCaption':' - {0}','DashboardStringId.CardRowDataElementTypeTargetValueCaption':'Target Value','DashboardStringId.FormatConditionAppearanceGradientRed':'Gradient Red','DashboardStringId.FromToDatePeriodCaption':'{0} - {1}','DashboardStringId.CalculationTypeMovingCalculation':'Moving Calculation','DashboardStringId.SummaryTypeSum':'Sum','DashboardStringId.SummaryTypeMin':'Min','DashboardStringId.SummaryTypeMax':'Max','DashboardStringId.SummaryTypeVar':'Var','DashboardStringId.ExtractCustomDriverNameError':'The name of the custom extract driver cannot be null or empty.','DashboardStringId.PieCalculationAlongSeriesAndArguments':'Series / Arguments','DashboardStringId.ErrorHandlingOrderByCalculationDataMembers':'Sorting by measure cannot be applied if the target measure has calculations. The following dimensions are ordered by measures with calculations','DashboardStringId.FunctionDescriptionVar':'Var(Value)\\r\\nReturns an estimate of the variance of a population, where the sample is a subset of the entire population.','DashboardStringId.NumericFormatUnitOnesCaption':'Ones','DashboardStringId.DescriptionItemWeight':'Weight','DashboardStringId.FormatConditionAppearancePalePurple':'Pale Purple','DashboardStringId.ExactDateDateTimeFormatPattern':'{0}: {1}','DashboardStringId.DateTimeFormatDateFormatLongCaption':'Long','DashboardStringId.DescriptionSparklineArgument':'Argument','DashboardStringId.DefaultOlapDataSourceName':'OLAP Data Source','DashboardStringId.AggregatedDataType':'Aggregated','DashboardStringId.EntireRangePeriodCaption':'Entire Range','DashboardStringId.SeriesTypeSpline':'Spline','DashboardStringId.TooltipDataItemsHeader':'TOOLTIP DATA ITEMS','DashboardStringId.DefaultNameCardItem':'Cards','DashboardStringId.CommandFormatRuleBottomN':'Bottom N','DashboardStringId.CalculationTypePercentageDifference':'Percentage Difference','DashboardStringId.LowCaption':'Low','DashboardStringId.DeltaThresholdTypePercent':'Percent','DashboardStringId.Title':'Title','DashboardStringId.FormatRuleDrawAxis':'Draw axis','DashboardStringId.ExtractDriverNotFoundError':'Cannot find an extract driver with the following name: \\'{0}\\'','DashboardStringId.DescriptionItemSeries':'Series','DashboardStringId.ErrorHandlingRecursiveDataMembers':'The following data items refer to each other','DashboardStringId.UriCaption':'Uri','DashboardStringId.Delta':'Delta','DashboardStringId.RangeFilterSelectRange':'Select Range','DashboardStringId.SeriesTypeSideBySideFullStackedBar':'Full-Stacked Bar Side-by-Side','DashboardStringId.ActionOtherValues':'Values','DashboardStringId.SeriesTypeGroupArea':'Area','DashboardStringId.MessageSummaryCalculatedFieldInDimension':'Cannot change the expression of the \\'{0}\\' calculated field that provides data for the \\'{1}\\' dimension. Summary-based calculated fields can provide data for measures only.','DashboardStringId.FormatRangeFilterDisplayText':'{0} - {1}','DashboardStringId.AxisXNameArguments':'Arguments','DashboardStringId.DeltaValueTypeAbsoluteVariationCaption':'Absolute variation','DashboardStringId.FormatRulePredefinedColor':'Predefined color','DashboardStringId.FormatRuleStyleAppearance':'Appearance','DashboardStringId.PeriodLastMinute':'Last Minute','DashboardStringId.RangeFilterCalculationAlongSeriesAndArgument':'Series / Argument','DashboardStringId.CommandFormatRuleBelowAverage':'Below Average','DashboardStringId.GridCalculationAlongRows':'Rows','DashboardStringId.FunctionDescriptionGetDateWeekYear':'GetDateWeekYear(DateTime)\\r\\nReturns the date of the first day of the week for a given DateTime (uses culture settings).','DashboardStringId.FunctionDescriptionTotal':'Total(SummaryExpression)\\r\\nReturns the total for the specified expression in a table calculation window.','DashboardStringId.DataSourceFilterContainsAggrExceptionText':'Cannot load data because the data source filter should not contain the Aggr function.','DashboardStringId.DateTimeFormatDayOfWeekFormatNumericCaption':'Numeric','DashboardStringId.FunctionDescriptionFirst':'First()\\r\\nReturns the number of rows from the current row to the first row in the window.','DashboardStringId.GaugeScaleLabelFormatCaption':'Scale Label','DashboardStringId.DifferenceCalculationMeasureCaptionFormatString':'Difference of {0}','DashboardStringId.FunctionDescriptionIndex':'Index()\\r\\nReturns the index of the current row in the window.','DashboardStringId.ValueCaption':'Value','DashboardStringId.SeriesTypeSideBySideRangeBar':'Range Bar Side-by-Side','DashboardStringId.DefaultSqlDataSourceName':'SQL Data Source','DashboardStringId.TreemapLabelArgumentTemplate':'{0} - {1}','DashboardStringId.ErrorHandlingNoSuchDataMembers':'The following data items do not exist','DashboardStringId.SeriesTypeSplineArea':'Spline Area','DashboardStringId.MessageMasterFilterIncorrectNumberOfValues':'Cannot identify an element that will be used to perform master filtering due to an incorrect number of provided values.','DashboardStringId.IntersectionLevelModeSpecific':'Specific level','DashboardStringId.FunctionDescriptionStdDevp':'StdDevp(Value)\\r\\nReturns the standard deviation of a population, where the population is the entire data to be summarized.','DashboardStringId.DateFilterInvalidDisplayTextPattern':'Invalid text pattern','DashboardStringId.CardRowDataElementTypeActualValueCaption':'Actual Value','DashboardStringId.MessageCustomItemConfigurationError':'Dashboard item configuration error. Please contact the application vendor or system administrator for assistance.','DashboardStringId.FormatRuleUnableToAddRule':'Unable to add a new format rule.','DashboardStringId.CommandFormatRuleBetween':'Between','DashboardStringId.DateTimeFormatQuarterFormatFullCaption':'Full','DashboardStringId.PieCalculationAlongArgumentsAndSeries':'Arguments / Series','DashboardStringId.CommandDimensionGroupChildValues':'Group Tiles','DashboardStringId.ErrorHandlingTopNByCalculationDataMembers':'Top N cannot be applied if its target measure has a calculation. The following dimensions have Top N applied by measures with calculations','DashboardStringId.FormatRuleStyle':'Style Settings','DashboardStringId.DashboardStatePosition':'Position','DashboardStringId.AutoFitPageCount':'Auto Fit Page Count','DashboardStringId.NewParameterNamePrefix':'Parameter','DashboardStringId.FunctionDescriptionRankModified':'RankModified(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the modified competition rank for the current row in the window.','DashboardStringId.RangeFilterSelectRangeToCaption':'To:','DashboardStringId.FormatRulePercentOf':'% of all values','DashboardStringId.FormatConditionAppearancePaleYellow':'Pale Yellow','DashboardStringId.MessageWrongExcelDataSourceConnectionParametersType':'Connection parameters are invalid. An excel data source supports only ExcelDataSourceConnectionParameters.','DashboardStringId.ScaleModeUseScaleFactor':'Use Scale Factor','DashboardStringId.DateTimeFormatDayOfWeekFormatFullCaption':'Full','DashboardStringId.SeriesTypeBubble':'Bubble','DashboardStringId.CustomItems':'Custom Items','DashboardStringId.DateTimeFormatQuarterFormatDefaultCaption':'Default','DashboardStringId.DescriptionDashboardItemComponentName':'Dashboard item component name','DashboardStringId.MovingCalculationMeasureCaptionFormatString':'Moving of {0}','DashboardStringId.DefaultNameItemGroup':'Group','DashboardStringId.RangeFilterIncompatibleNumericScale':'Range Filter\\'s numeric argument values should produce a continuous axis. Set the numeric scale to Continuous','DashboardStringId.ParametersFormValueColumnCaption':'Value','DashboardStringId.SeriesTypeStackedLine':'Stacked Line','DashboardStringId.SeriesTypeStackedArea':'Stacked Area','DashboardStringId.SeriesTypeGroupRangeFilter':'Range Filter','DashboardStringId.FunctionDescriptionRunningCustomAggregate':'RunningAggregate(SummaryExpression, CustomAggregateName) - Returns the cumulative result of the custom function applied to specified expression from the first row in the window to the current row.','DashboardStringId.CommandFormatRuleRangeSet':'Range Set','DashboardStringId.ExactDateFormatMinute':'Minute','DashboardStringId.CalculatedFieldTypeObject':'Object','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateHour':'GetDateHour(DateTime)\\r\\nExtracts the date part with the hour value from the defined DateTime.','DashboardStringId.MapAttributeDimension':'Attribute','DashboardStringId.FormatRuleCustomColor':'Custom color','DashboardStringId.RangeFilterCalculationAlongArgumentAndSeries':'Argument / Series','DashboardStringId.MessageIncorrectDashboardItemGroupAssign':'A dashboard item group cannot be added to a collection of dashboard items. Use the Dashboard.Groups property to add the group to the dashboard.','DashboardStringId.DateTimeFormatDateTimeFormatShortCaption':'Short','DashboardStringId.FunctionDescriptionWindowCount':'WindowCount(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the count of the expression within the window.','DashboardStringId.PeriodThisYear':'This Year','DashboardStringId.PeriodThisHour':'This Hour','DashboardStringId.DefaultNameRangeFilterItem':'Range Filter','DashboardStringId.PivotCalculationAlongGroupsInRows':'Rows within Groups','DashboardStringId.CustomItemEmptyMeasurePlaceholder':'Measure','DashboardStringId.DefaultNameBoundImageItem':'Bound Image','DashboardStringId.WeightCaption':'Weight','DashboardStringId.GridClearSorting':'Clear Sorting','DashboardStringId.SeriesTypeSideBySideStackedBar':'Stacked Bar Side-by-Side','DashboardStringId.DateTimeGroupIntervalExactDate':'Exact Date','DashboardStringId.ActionClearMasterFilter':'Clear Master Filter','DashboardStringId.CommandFormatRuleAboveBelowAverage':'Average','DashboardStringId.DateTimeFormatDateFormatDefaultCaption':'Default','DashboardStringId.SeriesTypeGroupPointLine':'Point / Line','DashboardStringId.PeriodLastQuarter':'Last Quarter','DashboardStringId.DescriptionSparkline':'Sparkline','DashboardStringId.MessageInvalidLayoutClientWidth':'The layout width must be greater than zero.','DashboardStringId.FormatRuleAppliesToCardBackground':'The selected style applies to a card\\'s background','DashboardStringId.PeriodNextDay':'Next Day','DashboardStringId.FilterStatePresentationSplitSheet':'Separate Sheet','DashboardStringId.FormatRuleApplyToChartElement':'Apply to chart elements','DashboardStringId.GridResetColumnWidths':'Reset column widths','DashboardStringId.SummaryTypeStdDevp':'StdDevP','DashboardStringId.DefaultDataSourceName':'Data Source','DashboardStringId.SummaryTypeCount':'Count','DashboardStringId.NumericFormatFormatTypeNumberCaption':'Number','DashboardStringId.FormatRuleUnableToAddRule_NoXYAxes':'Unable to add a new format rule. X and Y axis are required.','DashboardStringId.DefaultObjectDataSourceName':'Object Data Source','DashboardStringId.FormatConditionNumberValueType':'Number','DashboardStringId.SeriesTypeStepArea':'Step Area','DashboardStringId.SeriesTypeStepLine':'Step Line','DashboardStringId.FormatConditionAppearancePaleRed':'Pale Red','DashboardStringId.ExactDateFormatDay':'Day','DashboardStringId.FormatConditionAppearanceFontUnderline':'Underline','DashboardStringId.PeriodThisSecond':'This Second','DashboardStringId.FunctionDescriptionWindowFirstValue':'WindowFirstValue(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the first value of the expression within the window.','DashboardStringId.FunctionDescriptionLookup':'Lookup(SummaryExpression, Position)\\r\\nReturns the value of the expression in a target position specified as a relative offset from the current position.','DashboardStringId.RankTypeDense':'Dense','DashboardStringId.CalculatedFieldsTreeItemName':'Calculated Fields','DashboardStringId.AxisYNameValues':'Values','DashboardStringId.CardLayoutTemplateCenteredCaption':'Centered','DashboardStringId.DescriptionItemColor':'Color','DashboardStringId.PeriodThisQuarter':'This Quarter','DashboardStringId.PivotCalculationAlongRowsAndColumns':'Rows / Columns','DashboardStringId.DescriptionItemValue':'Value','DashboardStringId.FunctionDescriptionMedian':'Median(Value)\\r\\nReturns the median of the values in a collection.','DashboardStringId.ChartTotalValue':'Total','DashboardStringId.NumericFormatUnitBillionsCaption':'Billions','DashboardStringId.Value1Caption':'Value 1','DashboardStringId.MessageDuplicatedDataItem':'This instance of the \\'{0}\\' data item has already been added to \\'{1}\\'. To add a similar data item to \\'{1}\\', create a new instance of this data item.','DashboardStringId.CalculatedFieldTypeDouble':'Double','DashboardStringId.ExportFilters':'Filters','DashboardStringId.MessageServerModeNotSupportedMedian':'Median is not supported in server mode for','DashboardStringId.RangeFilterIncompatibleArgumentSorting':'Range Filter\\'s argument should not be sorted in the descending order or by another data item','DashboardStringId.PivotGridGrandTotal':'Grand Total','DashboardStringId.ParametersFormCalendarTodayButton':'Today','DashboardStringId.CardLayoutTemplateLightweightCaption':'Lightweight','DashboardStringId.FormatConditionAppearanceCyan':'Cyan','DashboardStringId.FormatConditionAppearanceNone':'None','DashboardStringId.FormatConditionAppearanceGray':'Gray','DashboardStringId.FormatConditionAppearanceBlue':'Blue','DashboardStringId.CustomItemCalculationAlongFirstAxisDimensions':'Dimensions','DashboardStringId.SeriesTypeBar':'Bar','DashboardStringId.DateTimeGroupIntervalDateHourMinute':'Date-Hour-Minute','DashboardStringId.PivotCalculationAlongGroupsInRowsAndColumns':'Rows / Columns within Groups','DashboardStringId.AutoArrangeContent':'Auto Arrange Content','DashboardStringId.ColorAutoAssigned':'Auto','DashboardStringId.ErrorToBooleanDateTimeOperand':'Cannot convert a date-time value to boolean.','DashboardStringId.MessageIncorrectGridDashboardControlOperation':'An invalid operation was performed in GridDashboardControl.','DashboardStringId.CommandFormatRuleRangeIcons':'Icon Ranges','DashboardStringId.ActionClearSelection':'Clear Selection','DashboardStringId.CustomItemMetadataInteractivitySectionsIncorrectOrderExceptionMessage':'The custom \\'{0}\\' item\\'s metadata configuration does not support interactivity. Declare the \\'{1}\\' property before non-interactive data sections. See documentation for more information: https://docs.devexpress.com/Dashboard/DevExpress.DashboardCommon.SupportInteractivityAttribute','DashboardStringId.DescriptionItemMeasure':'Measure','DashboardStringId.FormatConditionAppearanceRed':'Red','DashboardStringId.GridTotalTemplate':'{0} = {1}','DashboardStringId.CardRowDataElementTypePercentOfTargetCaption':'Percent of Target','DashboardStringId.CardLayoutTemplateStretchedCaption':'Stretched','DashboardStringId.ActionDrillUp':'Drill Up','DashboardStringId.CustomItemEmptyDimensionPlaceholder':'Dimension','DashboardStringId.Longitude':'Longitude','DashboardStringId.ColorPaletteIndex':'Palette index:','DashboardStringId.NumericFormatUnitMillionsCaption':'Millions','DashboardStringId.RangeFilterIncompatibleArgument':'Range Filter\\'s argument field should have Numeric, DateTime, or TimeSpan type','DashboardStringId.DateTimeGroupIntervalMonth':'Month','DashboardStringId.DescriptionSeries':'Series','DashboardStringId.DeltaIndicationModeLessIsGoodCaption':'Less is good','DashboardStringId.ChartCalculationAlongSeriesAndArguments':'Series / Arguments','DashboardStringId.IntersectionLevelModeAll':'All levels','DashboardStringId.SparklineIndicationModeWinLoss':'Win/Loss','DashboardStringId.SearchNullValuePrompt':'Enter text to search...','DashboardStringId.MessagePivotHasNoData':'The pivot grid has no data.','DashboardStringId.DataInspectorObjectValue':'[Object]','DashboardStringId.ActionSelectDateTimePeriod':'Select Date Time Period','DashboardStringId.MessageGridHasNoData':'The grid has no data.','DashboardStringId.ErrorHandlingSQLServerModeError':'Server mode is not supported for stored procedures','DashboardStringId.PivotCalculationAlongGroupsInColumnsAndRows':'Columns / Rows within Groups','DashboardStringId.DescriptionArguments':'Arguments','DashboardStringId.PivotCalculationAlongColumnsAndRows':'Columns / Rows','DashboardStringId.CardRowDataElementTypeDeltaIndicatorCaption':'Delta Indicator','DashboardStringId.DefaultNameScatterChartItem':'Scatter Chart','DashboardStringId.MessageLoading':'Loading...','DashboardStringId.PaperKind':'Size','DashboardStringId.DataInspectorButtonClose':'Close','DashboardStringId.CalculatedFieldTypeDecimal':'Decimal','DashboardStringId.SummaryTypeCountDistinct':'Count Distinct','DashboardStringId.RankTypePercentile':'Percentile','DashboardStringId.PageLayoutAuto':'Auto','DashboardStringId.SelectDate':'Select date','DashboardStringId.MessageCustomItemIncorrectDataItemSectionName':'The dashboard definition contains the {0} property that does not exist in the corresponding {1} class. This property will be ignored while the custom item is loading.','DashboardStringId.DeltaIndicationModeGreaterIsGoodCaption':'Greater is good','DashboardStringId.DateTimeIntervalAll':'All','DashboardStringId.DateTimeIntervalDay':'Day','DashboardStringId.FormatRuleUnableToAddRule_NoCardLayout':'Unable to add a new format rule to cards that use a legacy layout.','DashboardStringId.NumericFormatFormatTypeScientificCaption':'Scientific','DashboardStringId.GroupIntervalNone':'No Grouping','DashboardStringId.SizeModeStretch':'Stretch','DashboardStringId.ChartElementLineOrAreaCaption':'Line/Area','DashboardStringId.ErrorHandlingWindowDefinitionServerMode':'The w function cannot be used for server-mode data sources','DashboardStringId.DeltaValueTypePercentOfTargetCaption':'Percent of target','DashboardStringId.ExactDateFormatSecond':'Second','DashboardStringId.SummaryTypeStdDev':'StdDev','DashboardStringId.DateTimeGroupIntervalWeekOfMonth':'Week of Month','DashboardStringId.DateTimeFormatDayOfWeekFormatAbbreviatedCaption':'Abbreviated','DashboardStringId.RunningTotalCalculationMeasureCaptionFormatString':'Running Total of {0}','DashboardStringId.FunctionDescriptionRankUnique':'RankUnique(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the unique rank for the current row in the window.','DashboardStringId.PointLabelContentTypeNone':'None','DashboardStringId.NumericFormatUnitSymbolBillions':'B','DashboardStringId.SizeMode':'Size Mode','DashboardStringId.LayoutDimensionModeAuto':'Auto','DashboardStringId.SparklineIndicationModeArea':'Area','DashboardStringId.SparklineIndicationModeLine':'Line','DashboardStringId.PointLabelContentTypeValue':'Value','DashboardStringId.ExtractEmptyDataFieldsExceptionMessage':'Cannot create the extract file from the Object/Entity Framework data source because the ExtractSourceOptions.DataFields collection is empty.','DashboardStringId.AggregateExFunctionDescriptionMode':'Mode(Value)\\r\\nThe mode of the values. A mode is the value that is repeated more often than any other.','DashboardStringId.PageLayoutLandscape':'Landscape','DashboardStringId.DateTimeFormatMonthFormatAbbreviatedCaption':'Abbreviated','DashboardStringId.FilterElementRadioComboBoxNoDataCaption':'Select...','DashboardStringId.FormatRuleUnableToAddRule_NoSeriesToApply':'Unable to add a new format rule. There is no series to apply the rule.','DashboardStringId.PointLabelContentTypeArgument':'Argument','DashboardStringId.FormatRuleRangeGenerateRanges':'Generate Ranges','DashboardStringId.CardRowDataElementTypeCardNameCaption':'Card Name','DashboardStringId.CommandFormatRuleBetweenOrEqual':'Between Or Equal To','DashboardStringId.SummaryTypeMedian':'Median','DashboardStringId.CardRowDataElementTypeAbsoluteVariationCaption':'Absolute Variation','DashboardStringId.HighCaption':'High','DashboardStringId.ExpressionFieldsTreeItemName':'Expressions','DashboardStringId.ElementNameCards':'Cards','DashboardStringId.FormatRuleApplyToDimensionElement':'Dimension - {0}','DashboardStringId.SeriesTypeStackedBar':'Stacked Bar','DashboardStringId.DefaultNamePivotItem':'Pivot','DashboardStringId.CalculatedFieldTypeUnknown':'Unknown','DashboardStringId.DescriptionValues':'Values','DashboardStringId.RankTypeCompetition':'Competition','DashboardStringId.CommandFormatRuleBelowOrEqualAverage':'Below Or Equal to Average','DashboardStringId.DescriptionItemAxisXMeasure':'X-axis','DashboardStringId.MessageEFNotSupportedMedian':'Median is not supported for the Entity Framework.','DashboardStringId.TargetValueCaption':'Target','DashboardStringId.FormatConditionAppearancePaleBlue':'Pale Blue','DashboardStringId.FormatConditionAppearancePaleCyan':'Pale Cyan','DashboardStringId.FormatConditionAppearancePaleGray':'Pale Gray','DashboardStringId.DeltaIndicationModeWarningIfLessCaption':'Warning if less','DashboardStringId.CommandDimensionSortModeValue':'(Value)','DashboardStringId.SummaryTypeAverage':'Average','DashboardStringId.FormatRuleShowBarOnly':'Show bar only','DashboardStringId.DateTimeGroupIntervalWeekYear':'Week-Year','DashboardStringId.CardCalculationAlongCards':'Cards','DashboardStringId.DateTimeGroupIntervalQuarter':'Quarter','DashboardStringId.CalculatedFieldTypeString':'String','DashboardStringId.SparklineValuesSeparator':', ','DashboardStringId.OlapRaggedHierarchyNoneItemCaption':'(None)','DashboardStringId.DashboardCurrencyUseCurrentCurrency':'Use client system settings','DashboardStringId.LoadingDataError':'The Dashboard encountered an issue while loading data. One or several dashboard items may appear empty.\\r\\nPlease contact the application vendor or your system administrator and provide the following information.\\r\\n\\r\\nThe Web application server failed to establish the following data connections:\\r\\n{0}','DashboardStringId.DescriptionItemMeasureWeight':'Weight','DashboardStringId.PeriodThisMinute':'This Minute','DashboardStringId.DateTimeFormatMonthFormatNumericCaption':'Numeric','DashboardStringId.FunctionDescriptionRankDense':'RankDense(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the dense rank for the current row in the window.','DashboardStringId.FunctionCategoryAdvanced':'Advanced','DashboardStringId.ExactDateFormatQuarter':'Quarter','DashboardStringId.PeriodNextSecond':'Next Second','DashboardStringId.FunctionDescriptionAggrJoinRule':'joinRule(dimension, searchValue)\\r\\nSpecifies the dimension for the \\'aggr\\' function and a column whose values are used in the join operation after aggregation is completed.','DashboardStringId.DefaultNameComboBoxItem':'Combo Box','DashboardStringId.SeriesTypeRangeArea':'Range Area','DashboardStringId.CommandFormatRuleTopN':'Top N','DashboardStringId.MessageWrongAxisName':'A data axis with the specified name does not exist in this dashboard item. See the DevExpress.DashboardCommon.DashboardDataAxisNames static class for valid data axis names.','DashboardStringId.CalculationTypePercentOfTotal':'Percent Of Total','DashboardStringId.CommandFormatRuleLessThanOrEqualTo':'Less Than Or Equal To','DashboardStringId.DateFilterDisplayTextPattern':'Display Text Pattern','DashboardStringId.SeriesTypeGroupRange':'Range','DashboardStringId.MessageWrongDateTimePeriodName':'The DateTimePeriodCollection does not contain the item with the specified name.','DashboardStringId.OLAPUnavailableRawData':'OLAP Data Source - Data Unavailable','DashboardStringId.DataItemsHeader':'DATA ITEMS','DashboardStringId.FitToPageWidth':'Fit to Page Width','DashboardStringId.FormatRuleAllowNegativeAxis':'Allow negative axis','DashboardStringId.FormatRuleDisplayName':'Caption','DashboardStringId.FormatConditionAppearanceYellow':'Yellow','DashboardStringId.SeriesTypeGroupFinancial':'Financial','DashboardStringId.DateTimeGroupIntervalYear':'Year','DashboardStringId.DateTimeGroupIntervalHour':'Hour','DashboardStringId.PointLabelContentTypePercent':'Percent','DashboardStringId.MessageIncorrectDataAssign':'Data cannot be assigned if a data provider is used','DashboardStringId.ErrorHandlingInvalidCustomFunctions':'Calculated Field and Window expressions cannot contain some custom functions. Evaluated expressions contain the following forbidden functions','DashboardStringId.MessageIncorrectFilterValueLength':'The list of values that has been assigned as the filter value has a length that does not match the expected length of the filter value.','DashboardStringId.SparklineIndicationModeBar':'Bar','DashboardStringId.ScatterCalculationAlongArguments':'Arguments','DashboardStringId.DefaultXpoDataSourceName':'XPO Data Source','DashboardStringId.NumericFormatUnitSymbolMillions':'M','DashboardStringId.FormatRuleUnableToAddRule_NoColumnsToApply':'Unable to add a new format rule. There is no column to apply the rule.','DashboardStringId.FormatRuleApplyTo':'Apply to','DashboardStringId.FormatConditionAppearanceFontItalic':'Italic','DashboardStringId.NumericGroupIntervalContinuous':'Continuous','DashboardStringId.DifferenceCalculationTargetPrevious':'Previous','DashboardStringId.CommandDimensionSortModeID':'(ID)','DashboardStringId.DefaultMongoDBDataSourceName':'MongoDB Data Source','DashboardStringId.DescriptionGauges':'Gauges','DashboardStringId.NumericGroupIntervalDiscrete':'Discrete','DashboardStringId.FunctionDescriptionWindowVarp':'WindowVarp(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the biased variance of the expression within the window.','DashboardStringId.FunctionDescriptionWindowMode':'WindowMode(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the mode of the expression within the window.','DashboardStringId.DateTimeGroupIntervalDateHourMinuteSecond':'Date-Hour-Minute-Second','DashboardStringId.DefaultNameDateFilterItem':'Date Filter','DashboardStringId.FormatConditionAutomaticValueType':'Automatic','DashboardStringId.ScaleModeNone':'None','DashboardStringId.DefaultNamePieItem':'Pies','DashboardStringId.EndDate':'(End Date)','DashboardStringId.FunctionOperatorExFunctionDescriptionToDateTime':'ToDateTime(Value)\\r\\nConverts Value to a DateTime value.','DashboardStringId.FormatConditionPercentValueType':'Percent','DashboardStringId.CommandFormatRuleBar':'Bar','DashboardStringId.FormatConditionAppearanceFontGreen':'Green Font','DashboardStringId.DefaultExcelDataSourceName':'Excel Data Source','DashboardStringId.CommandDimensionSortModeDisplayText':'(Display Text)','DashboardStringId.MessageIncorrectMoveTarget':'Cannot move a layout item to a position within its own branch','DashboardStringId.ExactDateFormatHour':'Hour','DashboardStringId.ExactDateFormatYear':'Year','DashboardStringId.DefaultNameMapItem':'Map','DashboardStringId.ExtractSourceDataSourceNamePostfix':'(local copy)','DashboardStringId.FunctionDescriptionAggregateFilter':'filter(SummaryExpression, filterCriteria)\\r\\nFilters underlying data with specified filter criteria and aggregates filtered data using current detail level and the summary function.','DashboardStringId.DescriptionMeasures':'Measures','DashboardStringId.FormatRuleApplyToAllElements':'All elements','DashboardStringId.GridTotalValueTemplate':'{0}','DashboardStringId.MessageServerModeNotSupportedCountDistinct':'Count Distinct is not supported in server mode for','DashboardStringId.DefaultDashboardTitleText':'Dashboard','DashboardStringId.FormatConditionAppearancePaleGreen':'Pale Green','DashboardStringId.FileName':'File Name','DashboardStringId.ResetExactDateFormatToDefault':'Reset to Default','DashboardStringId.LayoutDimensionModeFixed':'Fixed','DashboardStringId.PeriodLastMonth':'Last Month','DashboardStringId.DescriptionBoundImageAttribute':'Attribute','DashboardStringId.MessageInvalidFilterExpression':'Incorrect column identifier: {0}. A valid column identifier must consist of the column name preceeded by the table name (or alias, if specified). These names must be dot-separated.','DashboardStringId.TopNOthersValue':'Others','DashboardStringId.PaperKindExecutive':'Executive','DashboardStringId.FormatConditionAppearancePurple':'Purple','DashboardStringId.ActionMaximizeDashboardItem':'Maximize','DashboardStringId.GridSortDescending':'Sort Descending','DashboardStringId.PeriodLastYear':'Last Year','DashboardStringId.PeriodLastHour':'Last Hour','DashboardStringId.FormatConditionAppearanceFontGrayed':'Gray Font','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateHourMinute':'GetDateHourMinute(DateTime)\\r\\nExtracts the date part with the hour and minute values from the defined DateTime.','DashboardStringId.ErrorHandlingEFServerModeError':'Server mode is not supported for this data member','DashboardStringId.MeasureNamesDimensionName':'MeasureNames','DashboardStringId.Value2Caption':'Value 2','DashboardStringId.FormatRuleDisplayInLegend':'Display in legend','DashboardStringId.FormatRuleRangeReverseStyles':'Reverse','DashboardStringId.CsvValueSeparator':'Separator','DashboardStringId.SeriesTypePoint':'Point','DashboardStringId.ParameterTrueExportValue':'True','DashboardStringId.SeriesTypeStock':'Stock','DashboardStringId.CalculationTypeDifference':'Difference','DashboardStringId.FormatRuleRangeSegmentNumber':'Number of ranges:','DashboardStringId.LegendItemFormatString':'{0} - {1}','DashboardStringId.SizeModeZoom':'Zoom','DashboardStringId.SizeModeNone':'None','DashboardStringId.MessageInvalidStream':'The \\'stream\\' parameter can\\'t be null','DashboardStringId.DateTimeFormatDateFormatShortCaption':'Short','DashboardStringId.CommandFormatRuleDateOccurring':'A Date Occurring','DashboardStringId.ColoringModeNone':'None','DashboardStringId.NumericFormatUnitCaption':'Unit','DashboardStringId.PeriodNextMinute':'Next Minute','DashboardStringId.FormatRuleRangeAdd':'Add','DashboardStringId.CommandFormatRuleAboveOrEqualAverage':'Above Or Equal to Average','DashboardStringId.ScaleMode':'Scale Mode','DashboardStringId.CardRowDataElementTypeSubtitleCaption':'Subtitle','DashboardStringId.DateTimeFormatDayOfWeekFormatDefaultCaption':'Default','DashboardStringId.SeriesTypeFullStackedBar':'Full-Stacked Bar','DashboardStringId.MessageDuplicatedLayoutItem':'This layout item is already contained in the tree','DashboardStringId.DescriptionMapValue':'Map / Value','DashboardStringId.FunctionDescriptionWindowStdDevp':'WindowStdDevp(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the biased standard deviation of the expression within the window.','DashboardStringId.GridCalculationAlongSparklineArgument':'Sparkline Argument','DashboardStringId.FunctionDescriptionWindowDefinitionPartitionBy':'partitionBy(column1, column2, ...)\\r\\nSpecifies the columns by which the data rows are partitioned. The window function is applied to each partition separately.','DashboardStringId.DeltaIndicationModeNoIndicationCaption':'No indication','DashboardStringId.SeriesTypeGroupBar':'Bar','DashboardStringId.ActionShowDataInspector':'Inspect Data','DashboardStringId.ExportParameters':'Parameters','DashboardStringId.FormatStringSeriesName':' - {0}','DashboardStringId.FilterElementCheckedComboBoxNoDataCaption':'(none)','DashboardStringId.DescriptionItemArgument':'Argument','DashboardStringId.DateTimeGroupIntervalSecond':'Second','DashboardStringId.ParametersFormNameColumnCaption':'Parameter','DashboardStringId.FunctionOperatorExFunctionDescriptionToBoolean':'ToBoolean(Value)\\r\\nConverts Value to an equivalent Boolean value.','DashboardStringId.DifferenceCalculationTargetFirst':'First','DashboardStringId.DescriptionItemAxisYMeasure':'Y-axis','DashboardStringId.GaugeCalculationAlongGauges':'Gauges','DashboardStringId.ErrorIncorrectIntervalCount':'The count parameter should be greater or equal to 1.','DashboardStringId.CommandFormatRuleNotEqualTo':'Not Equal To','DashboardStringId.ChartCalculationAlongSeries':'Series','DashboardStringId.FormatRuleInvalidRule':'<Invalid Rule>','DashboardStringId.CardCalculationAlongSparklineArgumentAndCards':'Sparkline Argument / Cards','DashboardStringId.ShowTitle':'Show Title','DashboardStringId.PaperKindLegal':'Legal','DashboardStringId.FormatRuleStyleIcons':'Icons','DashboardStringId.ColorInherited':'(Inherited)','DashboardStringId.FormatRuleApplyToPointSeriesElementOnly':'This option is in effect only for line or area series','DashboardStringId.DescriptionDimensions':'Dimensions','DashboardStringId.CardRowDataElementTypePercentVariationCaption':'Percent Variation','DashboardStringId.ButtonCancel':'Cancel','DashboardStringId.UndoText':'Undo','DashboardStringId.CardLayoutTemplateNoneCaption':'None','DashboardStringId.DefaultNameChartPane':'Pane','DashboardStringId.DefaultNameChartItem':'Chart','DashboardStringId.DateTimeQuarterFormat':'Q{0}','DashboardStringId.ChartElementPointCaption':'Point','DashboardStringId.RawDataType':'Raw','DashboardStringId.CloseCaption':'Close','DashboardStringId.FormatConditionAppearanceFontYellow':'Yellow Font','DashboardStringId.PaperKindA3':'A3','DashboardStringId.PaperKindA4':'A4','DashboardStringId.PaperKindA5':'A5','DashboardStringId.FilterStatePresentationAfterAndSplitPage':'Separate Page','DashboardStringId.CardCalculationAlongSparklineArgument':'Sparkline Argument','DashboardStringId.FormatConditionAppearanceOrange':'Orange','DashboardStringId.RangeFilterHasNoData':'The Range Filter does not contain any data to display.','DashboardStringId.CommandFormatRuleGreaterThanOrEqualTo':'Greater Than Or Equal To','DashboardStringId.DescriptionItemRow':'Row','DashboardStringId.FilterStatePresentationAfter':'Below','DashboardStringId.DateTimeIntervalHour':'Hour','DashboardStringId.DateTimeIntervalYear':'Year','DashboardStringId.DateTimeIntervalWeek':'Week','DashboardStringId.FunctionDescriptionWindowDefinitionOrderBy':'orderBy(column1, column2, ...)\\r\\nSpecifies the columns by which the values are sorted.','DashboardStringId.FunctionDescriptionWindowDefinition':'w(WindowExpression, partitionByFunction, orderByFunction)\\r\\nCalculates aggregated values with the specified window function for the window defined by the specified partitioning and ordering.','DashboardStringId.NumericFormatUnitThousandsCaption':'Thousands','DashboardStringId.DateTimeFormatDateTimeFormatTimeOnlyCaption':'Time only','DashboardStringId.ErrorHandlingJoinRuleFunctionServerMode':'The joinRule function cannot be used for server-mode data sources','DashboardStringId.ScaleModeAutoFitToPagesWidth':'Auto Fit to Pages Width','DashboardStringId.ColoringModeDefault':'Default','DashboardStringId.MessageInternalError':'Internal error. Please contact the application vendor or your system administrator and provide the following information.\\r\\n\\r\\n{0}','DashboardStringId.DefaultJsonDataSourceName':'JSON Data Source','DashboardStringId.CommandFormatRuleValue':'Value','DashboardStringId.FilterElementNoDataToDisplay':'No data to display','DashboardStringId.CommandFormatRuleRange':'Range','DashboardStringId.EmptyColumnAliasPattern':'Column{0}','DashboardStringId.DescriptionItemAuto':'New Column','DashboardStringId.ExtractPreprocessorError':'An error occurred during creation of the data extract:\\r\\n{0}','DashboardStringId.RankTypeUnique':'Unique','DashboardStringId.DateTimeGroupIntervalWeekOfYear':'Week of Year','DashboardStringId.GeoPointMapTooltipPointCount':'{0} points','DashboardStringId.ErrorHandlingDataBindingError':'The following errors occur during data binding:','DashboardStringId.FormatConditionAppearanceCustom':'Custom','DashboardStringId.DefaultNameImageItem':'Image','DashboardStringId.OlapCubeNotFoundError':'The cube with the following name cannot be found:\\r\\n{0}.','DashboardStringId.DescriptionRows':'Rows','DashboardStringId.MapShapeNoneAttribute':'NONE','DashboardStringId.FunctionDescriptionRankPercentile':'RankPercentile(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the percentile rank for the current row in the window.','DashboardStringId.RankOrderDescending':'Descending','DashboardStringId.SeriesTypeStackedSplineArea':'Stacked Spline Area','DashboardStringId.ExtractEmptyDataMemberExceptionMessage':'Cannot create an extract file because ExtractSourceOptions.DataMember is empty or specified incorrectly.','DashboardStringId.DescriptionMaps':'Maps','DashboardStringId.PrintHeadersOnEveryPage':'Print Headers on Every Page','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateMonthYear':'GetDateMonthYear(DateTime)\\r\\nReturns the date of the first day of the month for a given DateTime.','DashboardStringId.FunctionCategoryAggregate':'Aggregate','DashboardStringId.FormatRuleApplyToTextElement':'Text - \"{0}\"','DashboardStringId.ButtonExport':'Export','DashboardStringId.ToDatePeriodCaption':'To {0}','DashboardStringId.ErrorToBooleanCharOperand':'Cannot convert a character to a boolean value.','DashboardStringId.FilterElementShowAllItem':'(All)','DashboardStringId.NumericFormatFormatTypeCurrencyCaption':'Currency','DashboardStringId.FunctionDescriptionFirstValue':'FirstValue(Value)\\r\\nReturns the first value in a collection.','DashboardStringId.ExactDateFormatMonth':'Month','DashboardStringId.UniqueCalculatedFieldNameValidationMessage':'The {0} already contains a field named {1}.','DashboardStringId.ActionExportToPdf':'Export To PDF','DashboardStringId.PivotCalculationAlongGroupsInColumns':'Columns within Groups','DashboardStringId.PivotCalculationAlongRows':'Rows','DashboardStringId.NumericFormatUnitSymbolThousands':'K','DashboardStringId.InvalidCustomPropertyNameMessage':'The property name \\'{0}\\' is invalid. It should contain only letters, numbers, and the underscore symbol and cannot start with a number.','DashboardStringId.PivotGridTotal':'{0} Total','DashboardStringId.MessageInvalidLayoutClientHeight':'The layout height must be greater than zero.','DashboardStringId.FormatConditionAppearanceGradientTransparent':'Gradient Transparent','DashboardStringId.CardLayoutTemplateCustomCaption':'Custom','DashboardStringId.DeltaIndicationModeWarningIfGreaterCaption':'Warning if greater','DashboardStringId.FormatConditionAppearanceGradientGreen':'Gradient Green','DashboardStringId.GridHyperlinkUriPatternErrorMessage':'Invalid placeholder','DashboardStringId.MessageBoxWarningTitle':'Warning','DashboardStringId.InspectedTypeFormatString':'({0} Data)','DashboardStringId.FormatStringKpiElementCaption':'{0} vs {1}','DashboardStringId.CardRowDataElementTypeTitleCaption':'Title','DashboardStringId.RangeFilterIncompatibleTopN':'Range Filter\\'s argument does not support the Top N feature','DashboardStringId.DeltaValueTypeTargetValueCaption':'Target value','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateQuarterYear':'GetDateQuarterYear(DateTime)\\r\\nReturns the date of the first day of the quarter for a given DateTime.','DashboardStringId.DateTimeGroupIntervalDayMonthYear':'Day-Month-Year','DashboardStringId.FormatRuleRangeUsePercent':'Use % ranges','DashboardStringId.GridCalculationAlongSparklineArgumentAndRows':'Sparkline Argument / Rows','DashboardStringId.FormatConditionAppearanceGradientCyan':'Gradient Cyan','DashboardStringId.FormatConditionAppearanceGradientBlue':'Gradient Blue','DashboardStringId.DefaultNameTreeViewItem':'Tree View','DashboardStringId.MessageIncorrectValueTopNCount':'The TopNCount property value cannot be negative or zero.','DashboardStringId.DateTimeFormatMonthFormatFullCaption':'Full','DashboardStringId.DateTimeGroupIntervalMonthYear':'Month-Year','DashboardStringId.ParametersFormCaption':'Dashboard Parameters','DashboardStringId.MessageCustomItemIsNotSupported':'The custom item is not supported by this control.','DashboardStringId.SparklineTooltipMinValue':'Min:','DashboardStringId.FormatRuleDataItemIsNotAvailable':'(N/A)','DashboardStringId.CommandFormatRuleLessThan':'Less Than','DashboardStringId.CommandFormatRuleGreaterThan':'Greater Than','DashboardStringId.SeriesTypeFullStackedSplineArea':'Full-Stacked Spline Area','DashboardStringId.FormatRuleNegativeStyle':'Negative Style Settings','DashboardStringId.CommandFormatRuleEqualTo':'Equal To','DashboardStringId.AggrInMasterFilterDimensionError':'Master filtering cannot be applied by dimension values created using the expression containing the Aggr function.','DashboardStringId.DateTimeGroupIntervalDay':'Day','DashboardStringId.MeasureFilterCaptionFormatString':'Filtered {0}','DashboardStringId.MessageInvalidCultureName':'Cannot find a specific culture with the following name: {0}','DashboardStringId.DefaultPeriodName':'Period','DashboardStringId.ColoringModeHue':'Hue','DashboardStringId.DefaultEFDataSourceName':'EF Data Source','DashboardStringId.NewCalculatedFieldNamePrefix':'Calculated Field','DashboardStringId.ParametersFormAllowNullColumnCaption':'Pass Null','DashboardStringId.ActionExportTemplate':'{0} - {1}','DashboardStringId.PeriodNextQuarter':'Next Quarter','DashboardStringId.FunctionOperatorExFunctionDescriptionGetDateHourMinuteSecond':'GetDateHourMinuteSecond(DateTime)\\r\\nExtracts the date part with the hour, minute, and second values from the defined DateTime.','DashboardStringId.ExactDatePeriodCaption':'{0}','DashboardStringId.ButtonSubmit':'Submit','DashboardStringId.DateTimeIntervalMonth':'Month','DashboardStringId.FunctionDescriptionWindowCustomAggregate':'WindowAggregate(SummaryExpression, StartOffset, EndOffset, CustomAggregateName) - Returns the result of the custom function applied to the specified expression in the window.','DashboardStringId.PointLabelContentTypeSeriesName':'Series Name','DashboardStringId.GridTotalTypeSum':'Sum','DashboardStringId.GridTotalTypeAvg':'Avg','DashboardStringId.GridTotalTypeMin':'Min','DashboardStringId.GridTotalTypeMax':'Max','DashboardStringId.DefaultNameGridItem':'Grid','DashboardStringId.InspectedData':'Inspected Data:','DashboardStringId.FunctionDescriptionCountDistinct':'CountDistinct(Value)\\r\\nReturns the number of unique objects in a collection.','DashboardStringId.DefaultNameTabPage':'Page','DashboardStringId.ChartCalculationAlongArgumentsAndSeries':'Arguments / Series','DashboardStringId.ElementNamePies':'Pies','DashboardStringId.SeriesTypeGroupBubble':'Bubble','DashboardStringId.RangeFilterEmptyArgument':'Please specify the Range Filter\\'s argument','DashboardStringId.PeriodNextMonth':'Next Month','DashboardStringId.FunctionDescriptionWindowStdDev':'WindowStdDev(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the sample standard deviation of the expression within the window.','DashboardStringId.DeltaThresholdTypeAbsolute':'Absolute','DashboardStringId.MessageInvalidCardLayoutTemplateMinWidth':'The minimum width must be greater than zero.','DashboardStringId.DataSourceDataMember':'Data Member','DashboardStringId.ImageFormat':'Image Format','DashboardStringId.MessageCollectionTypesNotSupported':'Dashboard does not support collection types.','DashboardStringId.SparklineTooltipEndValue':'End:','DashboardStringId.Latitude':'Latitude','DashboardStringId.FunctionDescriptionRunningSum':'RunningSum(SummaryExpression)\\r\\nReturns the running sum of the specified expression from the first row in the window to the current row.','DashboardStringId.FunctionDescriptionRunningAvg':'RunningAvg(SummaryExpression)\\r\\nReturns the running average of the specified expression from the first row in the window to the current row.','DashboardStringId.FunctionDescriptionRunningMin':'RunningMin(SummaryExpression)\\r\\nReturns the running minimum of the specified expression from the first row in the window to the current row.','DashboardStringId.FunctionDescriptionRunningMax':'RunningMax(SummaryExpression)\\r\\nReturns the running maximum of the specified expression from the first row in the window to the current row.','DashboardStringId.CategoryNameGeneral':'General','DashboardStringId.DateTimeFormatYearFormatFullCaption':'Full','DashboardStringId.RangeFilterIncompatibleSeriesType':'A Range Filter can contain Line, Area and Bar series only','DashboardStringId.CalculationAlongSpecificDimensions':'Specific...','DashboardStringId.SummaryTypeMode':'Mode','DashboardStringId.SummaryTypeVarp':'VarP','DashboardStringId.CommandDimensionSortModeKey':'(Key)','DashboardStringId.SeriesTypeFullStackedLine':'Full-Stacked Line','DashboardStringId.SeriesTypeFullStackedArea':'Full-Stacked Area','DashboardStringId.ColorAutoAssignedNotApplied':'Auto (not applied)','DashboardStringId.DefaultNameListBoxItem':'List Box','DashboardStringId.DescriptionCards':'Cards','DashboardStringId.DescriptionTooltipDimensions':'Tooltip dimensions','DashboardStringId.FormatRuleApplyToRow':'Apply to row','DashboardStringId.FunctionOperatorExFunctionDescriptionGetWeekOfMonth':'GetWeekOfMonth(DateTime)\\r\\nExtracts the week of the month from the defined DateTime.','DashboardStringId.FormatConditionAppearanceGreen':'Green','DashboardStringId.CommandFormatRuleColorRangeBar':'Color Range Bar','DashboardStringId.UniqueNameValidationMessage':'A name should be unique.','DashboardStringId.MessageServerModeNotSupportedMode':'Mode is not supported in server mode for','DashboardStringId.FormatRuleInvalidRuleChanging':'Invalid Rule cannot be enabled.','DashboardStringId.MessageDashboardInternalError':'Dashboard internal error. Please contact the application vendor or your system administrator.','DashboardStringId.FunctionDescriptionRankCompetition':'RankCompetition(SummaryExpression, [\\'asc\\', \\'desc\\'])\\r\\nReturns the standard competition rank for the current row in the window.','DashboardStringId.FunctionDescriptionWindowDefinitionOrderDesc':'desc(column)\\r\\nData rows are sorted by values in the specified column in descending order.','DashboardStringId.RangeFilterCalculationAlongArgument':'Argument','DashboardStringId.CommandFormatRuleTopBottom':'Top/Bottom','DashboardStringId.ExcelFormat':'Excel Format','DashboardStringId.DateTimeGroupIntervalMinute':'Minute','DashboardStringId.FormatConditionAppearanceGradientYellow':'Gradient Yellow','DashboardStringId.FunctionDescriptionWindowCountDistinct':'WindowCountDistinct(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the distinct count of the expression within the window.','DashboardStringId.CardCalculationAlongCardsAndSparklineArgument':'Cards / Sparkline Argument','DashboardStringId.FunctionDescriptionWindowVar':'WindowVar(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the variance of the expression within the window.','DashboardStringId.FunctionDescriptionWindowSum':'WindowSum(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the sum of the expression within the window.','DashboardStringId.FunctionDescriptionWindowMax':'WindowMax(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the maximum of the expression within the window.','DashboardStringId.FunctionDescriptionWindowMin':'WindowMin(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the minimum of the expression within the window.','DashboardStringId.FunctionDescriptionWindowAvg':'WindowAvg(SummaryExpression, StartOffset, EndOffset)\\r\\nReturns the average of the expression within the window, which is defined using offsets from the current row.','DashboardStringId.DifferenceCalculationTargetLast':'Last','DashboardStringId.DifferenceCalculationTargetNext':'Next','DashboardStringId.MessageIncorrectMapLatitude':'The latitude should be greater than or equal to {0} and less than or equal to {1}.','DashboardStringId.DescriptionDashboardItemName':'Dashboard item name','DashboardStringId.FilterStatePresentationNone':'None','DashboardStringId.ButtonApply':'Apply','DashboardStringId.WindowFunctionValidationMessage':'Please Note: The created field can not be used as a data item. The {0} expression is valid only within the w-function or as a custom expression applied to a measure calculation.','DashboardStringId.ErrorEmptyPeriodName':'The name cannot be null or empty','DashboardStringId.SparklineTooltipStartValue':'Start:','DashboardStringId.ButtonReset':'Reset','DashboardStringId.ActionExportTo':'Export To','DevExpress.DashboardCommon.DimensionSortOrder.Ascending':'Ascending','DevExpress.DashboardCommon.DashboardParameter.AllowMultiselect':'Allow Multiselect','DevExpress.DashboardCommon.DynamicListLookUpSettings.DisplayMember':'Display Member','DevExpress.DashboardCommon.DimensionSortOrder.Descending':'Descending','DevExpress.DashboardCommon.DynamicListLookUpSettings.ValueMember':'Value Member','DevExpress.DashboardCommon.DashboardParameter.LookUpSettings':'Look-Up Settings','DevExpress.DashboardCommon.DashboardParameter.AllowNull':'Allow Null','DevExpress.DashboardCommon.DashboardParameter.SelectAllValues':'Select All Values','DevExpress.DashboardCommon.DashboardParameter.Description':'Description','DevExpress.DashboardCommon.StaticListLookUpSettings.Values':'Values','DevExpress.DashboardCommon.DynamicListLookUpSettings.SortByMember':'Sort By','DevExpress.DashboardCommon.DynamicListLookUpSettings.DataMember':'Data Member','DevExpress.DashboardCommon.DashboardParameter.Visible':'Visible','DevExpress.DashboardCommon.DynamicListLookUpSettings.SortOrder':'Sort Order','DevExpress.DashboardCommon.DynamicListLookUpSettings.DataSource':'Data Source','DashboardWebStringId.Title.ImageLinked':'Linked','DashboardWebStringId.DashboardMenu':'Dashboard Menu','DashboardWebStringId.Grid.DisplayMode.Bar':'Bar','DashboardWebStringId.Chart.Position.TopLeftHorizontal':'Top Left Horizontal','DashboardWebStringId.FormatRuleApplyToDimensionElement':'Dimension','DashboardWebStringId.InteractivityOptions.MasterFilterMode.None':'None','DashboardWebStringId.Parameters.LookUpSettingsType.NoLookUp':'No Look-Up','DashboardWebStringId.ConditionalFormatting.IconType.None':'None','DashboardWebStringId.TopNMode':'Mode','DashboardWebStringId.TopN.Top':'Top','DashboardWebStringId.Map.Viewport.CenterPointLongitude':'Center Point Longitude','DashboardWebStringId.DashboardMenuColorScheme':'Color Scheme','DashboardWebStringId.Image.BindingMode':'Binding Mode','DashboardWebStringId.LimitVisibleData.IncreasePerformanceTooltip':'This dashboard item is bound to a large data set. To increase performance, click this icon to limit visible data.','DashboardWebStringId.ColoringModeOn':'On','DashboardWebStringId.Calculations.RankOrder':'Rank Order','DashboardWebStringId.ConditionalFormatting.ConditionMaximum':'Maximum','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGrayDownInclineArrow':'Directional Gray Down Incline Arrow','DashboardWebStringId.Treemap.TileLabelsValue':'Value','DashboardWebStringId.ButtonHidden':'Hidden','DashboardWebStringId.Treemap.TileLabelsNone':'None','DashboardWebStringId.Image.BindingMode.BinaryArray':'Binary Array','DashboardWebStringId.Calculations.Moving':'Moving of','DashboardWebStringId.Gauge.Scale.Custom':'Custom','DashboardWebStringId.Image.BindingMode.Uri':'Uri','DashboardWebStringId.PivotGrid.ValuesPositionRows':'Rows','DashboardWebStringId.Map.Viewport.CreateViewerPaddings':'Create Viewer Paddings','DashboardWebStringId.Notification.DashboardCanNotBeSaved':'The dashboard cannot be saved','DashboardWebStringId.InteractivityOptions.TargetDimensions.Series':'Series','DashboardWebStringId.Binding.TooltipMeasures':'Tooltip Measures','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalYellowSideArrow':'Directional Yellow Side Arrow','DashboardWebStringId.DataSources.EditCalculatedField':'Edit Calculated Field','DashboardWebStringId.ConditionalFormatting.IconType.ShapeYellowTriangle':'Shape Yellow Triangle','DashboardWebStringId.Grid.Options':'Grid Options','DashboardWebStringId.Chart.Position.BottomRightVertical':'Bottom Right Vertical','DashboardWebStringId.EditInDesigner':'Edit in Designer','DashboardWebStringId.DashboardMenuNew':'New...','DashboardWebStringId.Colorization.NoSelectedSchema':'Select a color scheme to edit','DashboardWebStringId.Currency.DefaultCurrencyWarning':'The currency culture format is based on environmental settings. Specify the culture explicitly to ignore these settings.','DashboardWebStringId.CardLayout.MaxWidth':'Max Width','DashboardWebStringId.ConditionalFormatting.DatesOccurringBeyondThisYear':'Following this year','DashboardWebStringId.PivotGrid.RowGrandTotals':'Row Grand Totals','DashboardWebStringId.Add':'Add','DashboardWebStringId.Pie':'Pie','DashboardWebStringId.ConditionalFormatting.Appearance.ForeColor':'Fore Color','DashboardWebStringId.PivotGrid.RowTotalsPosition':'Row Totals Position','DashboardWebStringId.InteractivityOptions.TargetDimensions.Points':'Points','DashboardWebStringId.Title.Aligment.Center':'Center','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorRedCross':'Indicator Red Cross','DashboardWebStringId.Chart.ShowPointMarkers':'Show point markers','DashboardWebStringId.DataSources.CreateDataSource':'Create','DashboardWebStringId.ColoringOptions':'Coloring','DashboardWebStringId.Grid.FilterClause.EndsWith':'Ends with','DashboardWebStringId.Notification.UnsupportedDataSourceType':'Unsupported data source type','DashboardWebStringId.DataSources.OK':'OK','DashboardWebStringId.Chart.AxisYMeasure':'Axis Y Measure','DashboardWebStringId.AccordionTab.Common':'Common','DashboardWebStringId.Map.Position.TopRight':'Top Right','DashboardWebStringId.Pie.Type':'Pie Type','DashboardWebStringId.ConditionalFormatting.SegmentNumber':'Segment Number','DashboardWebStringId.Binding.ValuesPattern':'Values {0}','DashboardWebStringId.ButtonNo':'NO','DashboardWebStringId.ButtonOn':'ON','DashboardWebStringId.Pie.LabelPositionInside':'Inside','DashboardWebStringId.PivotGrid.LayoutTypeCompact':'Compact','DashboardWebStringId.InteractivityOptions.TargetDimensions':'Target Dimensions','DashboardWebStringId.Cards.LineCount':'Line Count','DashboardWebStringId.Map.TooltipActualValueCaption':'Tooltip Actual Value Caption','DashboardWebStringId.Map.TooltipAttribute':'Tooltip Attribute','DashboardWebStringId.TilesTooltipContentType':'Tile Tooltip','DashboardWebStringId.RangeFilter.UriPattern':'Uri Pattern','DashboardWebStringId.Parameters.LookUpSettingsTypeCaption':'Look-Up Settings Type','DashboardWebStringId.PivotGrid.LayoutTypeTabular':'Tabular','DashboardWebStringId.FormatType':'Format Type','DashboardWebStringId.Dialog.ConfirmSaving':'Confirm saving','DashboardWebStringId.FormatRule':'Format Rule','DashboardWebStringId.Card.SparklineVisible':'Sparkline Visible','DashboardWebStringId.Tabs.Binding':'Binding','DashboardWebStringId.Grid.ColumnHeaders':'Column Headers','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorGreenCheck':'Indicator Green Check','DashboardWebStringId.Map.CustomMapUrl':'Custom Map Url','DashboardWebStringId.RangeFilter.Flow':'Flow','DashboardWebStringId.RangeFilter.None':'None','DashboardWebStringId.Binding.ConfigureMeasure':'Configure Measure','DashboardWebStringId.DashboardMenuCurrency':'Currency','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGrayUpInclineArrow':'Directional Gray Up Incline Arrow','DashboardWebStringId.PivotGrid.RowTotals':'Row Totals','DashboardWebStringId.Calculations.RankType':'Rank Type','DashboardWebStringId.MasterFilterMode':'Master Filter Mode','DashboardWebStringId.PivotGrid.RowTotalsPositionBottom':'Bottom','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGreenArrowUp':'Directional Green Arrow Up','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalRedTriangleDown':'Directional Red Triangle Down','DashboardWebStringId.Grid.DisplayMode.Text':'Text','DashboardWebStringId.Binding.SetColor':'Set Color','DashboardWebStringId.Gauge.Captions':'Show Gauge Captions','DashboardWebStringId.Grid.Delta':'Delta','DashboardWebStringId.Chart.LogarithmicScaleBase5':'5','DashboardWebStringId.Chart.LogarithmicScaleBase2':'2','DashboardWebStringId.Binding.SetValue':'Set Value','DashboardWebStringId.Notification.AttemptToLoadParameterValues':'An error occurred during an attempt to load parameter values for the data source ','DashboardWebStringId.DesignerToolbar.LayoutDimensionValidationError':'The value should be between {0} and {1}','DashboardWebStringId.DashboardMenuNewDashboardCreate':'Create','DashboardWebStringId.DateFilter.FilterTypeExact':'Exact','DashboardWebStringId.Grid.FilterClause.LessOrEqual':'Less than or equal to','DashboardWebStringId.Coloring.Local':'Local','DashboardWebStringId.DateFilter.FilterTypeAfter':'After','DashboardWebStringId.Map.Area.WorldCountries':'World Countries','DashboardWebStringId.ConditionalFormatting.IconType.Rating1Bar':'Rating 1 Bar','DashboardWebStringId.Binding.AddMap':'Add Map','DashboardWebStringId.Binding.AddRow':'Add Row','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGraySideArrow':'Directional Gray Side Arrow','DashboardWebStringId.PivotGrid.ColumnTotalsPosition':'Column Totals Position','DashboardWebStringId.Grid.FilterClause.BetweenEnd':'End','DashboardWebStringId.Map.CustomMapOptionsSource':'Source','DashboardWebStringId.ConditionalFormatting.FontStyle':'Font Style','DashboardWebStringId.Cards.ArrangementMode.Auto':'Auto','DashboardWebStringId.DataSources.CreateNewDataSource':'Create data source...','DashboardWebStringId.Notification.AttemptToLoadDashboards':'An error occurred during an attempt to load the list of available dashboards','DashboardWebStringId.CollectionEditor.Totals.NoItems':'Click + to add a new total.','DashboardWebStringId.InteractivityOptions':'Interactivity Options','DashboardWebStringId.DataSources.RenameDataSource':'Rename Data Source','DashboardWebStringId.Chart.AxisXMeasure':'Axis X Measure','DashboardWebStringId.Map.Viewport.RightLongitude':'Right Longitude','DashboardWebStringId.Errors.AttemptToLoadData':'An error occurred during an attempt to load data','DashboardWebStringId.Binding.ConfigureAttribute':'Configure Attribute','DashboardWebStringId.ConditionalFormatting.DatesOccurringEarlier':'Prior to the month 6 months ago','DashboardWebStringId.Grid.WidthType.FitToContent':'Fit To Content','DashboardWebStringId.Chart.Orientation.RotateLeft':'Rotate Left','DashboardWebStringId.Sparkline.HighlightMinMaxPoints':'Highlight Min/Max Points','DashboardWebStringId.Image.Alignment.Bottom':'Bottom','DashboardWebStringId.ConditionalFormatting.DateType':'Date Type','DashboardWebStringId.WeightedLegendGalleryGroup':'Position','DashboardWebStringId.Dashboard.Groups':'Groups','DashboardWebStringId.Binding.Attribute':'Attribute','DashboardWebStringId.Notification.AttemptToGetColorScheme':'An error occurred during an attempt to get the color 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The control supports a mobile layout only if it works in the Viewer mode. Do you want to switch to the Viewer mode?','DashboardWebStringId.Map.Position.TopCenter':'Top Center','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorRedFlag':'Indicator Red Flag','DashboardWebStringId.Treemap.GroupTooltipsArgument':'Argument','DashboardWebStringId.ConditionalFormatting.IconType.RatingFullGrayStar':'Rating Full Gray Star','DashboardWebStringId.Title.Aligment':'Alignment','DashboardWebStringId.DataSources.CalculatedField.Corrupted':'The calculated field contains errors','DashboardWebStringId.Grid.WidthType':'Width Type','DashboardWebStringId.ConditionalFormatting.DatesOccurringNone':'None','DashboardWebStringId.Treemap.TileTooltipsNone':'None','DashboardWebStringId.Pie.LabelContentType.Argument':'Argument','DashboardWebStringId.ConditionalFormatting.IconType.RatingFullGrayCircle':'Rating Full Gray Circle','DashboardWebStringId.Binding.ConfigureColumn':'Configure Column','DashboardWebStringId.Binding.SetArgument':'Set Argument','DashboardWebStringId.Map.ShapeTitleAttribute':'Shape Title Attribute','DashboardWebStringId.ConditionalFormatting.DatesOccurringYesterday':'Yesterday','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalYellowDownInclineArrow':'Directional Yellow Down Incline Arrow','DashboardWebStringId.Interactivity':'Interactivity','DashboardWebStringId.AccordionTab.WeightedLegend':'Weighted Legend','DashboardWebStringId.Treemap.SquarifiedLayoutAlgorithm':'Squarified','DashboardWebStringId.ConditionalFormatting.IconType.RatingEmptyGrayStar':'Rating Empty Gray Star','DashboardWebStringId.AccordionTab.MeasureFilter':'Filter','DashboardWebStringId.Chart.OverlappingMode':'Overlapping Mode','DevExpressWebStringId.CalculatedFieldDataType':'Data Type','DashboardWebStringId.DashboardItemMenu.Bindings.ChangedDataSourceMessage':'The data source for the {0} item was changed to {1}','DashboardWebStringId.Colorization.ColorSchemeType':'Color Scheme Type','DashboardWebStringId.Chart.IgnoreEmptyPoints':'Ignore empty points','DashboardWebStringId.Chart.Position.TopRightHorizontal':'Top Right Horizontal','DashboardWebStringId.DashboardItemMenu.Bindings.SelectDataSourceButtonTooltip':'To add a data source to the current dashboard, go to Menu | Data Sources.','DashboardWebStringId.LayoutHasBeenChangedDialogMessage':'The dashboard layout has been changed.','DashboardWebStringId.LimitVisibleData.DisplayAllDataTooltip':'This dashboard item is bound to a large dataset and does not currently display all data to retain performance. Click this button to display all data.','DashboardWebStringId.Binding.Gauges':'Gauges','DashboardWebStringId.Chart.Legend':'Legend','DashboardWebStringId.ConditionalFormatting.IconType.ShapeRedTrafficLight':'Shape Red Traffic Light','DashboardWebStringId.Chart.TooltipContent':'Tooltips','DashboardWebStringId.Cards.ArrangementMode.FixedRows':'Fixed Rows','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo4':'During the month 4 months ago','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo5':'During the month 5 months ago','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo6':'During the month 6 months ago','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo1':'Last Month','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo2':'During the month 2 months ago','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAgo3':'During the month 3 months ago','DashboardWebStringId.Notification.ErrorHasOccuredOn':'An error occurred during an','DashboardWebStringId.Map.Position.BottomCenter':'Bottom Center','DashboardWebStringId.Parameters.DynamicListLookUpSettings':'Dynamic List Look-Up Settings','DashboardWebStringId.ConditionalFormatting.DatesOccurringToday':'Today','DashboardWebStringId.Grid.WordWrap':'Word Wrap','DashboardWebStringId.Coloring.MeasuresColoringMode':'Measures Coloring','DashboardWebStringId.Grid.FilterClause.StartsWith':'Starts with','DashboardWebStringId.Grid.ColumnWidth':'Column Width','DashboardWebStringId.Chart.TitleText':'Title Text','DashboardWebStringId.Gauge.Type':'Gauge Type','DashboardWebStringId.Tabs.DataShaping':'Data Shaping','DashboardWebStringId.MobileLayout.Back':'Back','DashboardWebStringId.ConditionalFormatting.DatesOccurringEmpty':'Empty','DashboardWebStringId.DateFilter.ArrangementModeAutoHeight':'Auto Height','DashboardWebStringId.Map.TooltipDimensions':'Tooltip Dimensions','DashboardWebStringId.Map.Area.Asia':'Asia','DashboardWebStringId.DataSources.CalculatedField.Name':'Name','DashboardWebStringId.BindDataInvitation':'to bind this item to data','DashboardWebStringId.Treemap.TileTooltipsValue':'Value','DashboardWebStringId.DataSources.DataItems':'Data Items','DashboardWebStringId.Chart.Position.BottomLeftHorizontal':'Bottom Left Horizontal','DashboardWebStringId.Map.Orientation.Horizontal':'Horizontal','DashboardWebStringId.ConditionalFormatting.FontRegular':'Regular','DashboardWebStringId.TileOptions':'Tile Options','DashboardWebStringId.Notification.AttemptToConnectionStrings':'An error occurred during an attempt to load connection strings','DashboardWebStringId.Chart.SeriesType':'Series Type','DashboardWebStringId.Parameters.StaticListLookUpSettings':'Static List Look-Up Settings','DashboardWebStringId.Map.Area.NorthAmerica':'North 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year','DashboardWebStringId.TextBox.Text':'Text','DashboardWebStringId.Title.ImageEmbedded':'Embedded','DashboardWebStringId.Treemap.GroupTooltipsArgumentAndValue':'Argument and Value','DashboardWebStringId.FilterItem.Type':'Type','DashboardWebStringId.Treemap.SliceAndDiceLayoutAlgorithm':'Slice and Dice','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorCircledGreenCheck':'Indicator Circled Green Check','DashboardWebStringId.SaveChangesDialogMessage':'Do you want to save changes?','DashboardWebStringId.DataItem':'Data Item','DashboardWebStringId.Binding.Values':'Values','DashboardWebStringId.Binding.AddMeasure':'Add Measure','DashboardWebStringId.ConditionalFormatting.IconType':'Icon Type','DashboardWebStringId.Binding.TooltipDimensions':'Tooltip Dimensions','DashboardWebStringId.Gauge.Type.LinearHorizontal':'Linear Horizontal','DashboardWebStringId.DesignerToolbar.Height':'H:','DashboardWebStringId.Image.HorizontalAlignment':'Horizontal 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Rules','DashboardWebStringId.RangeFilter.CustomPeriods':'Custom Periods','DashboardWebStringId.Binding.ConfigureValues':'Configure Values','DashboardWebStringId.Parameters.ParameterList':'Parameter List','DashboardWebStringId.Chart.Content':'Content','DashboardWebStringId.Map.Area.Europe':'Europe','DashboardWebStringId.Image.SizeMode.Stretch':'Stretch','DashboardWebStringId.Dimension.SortMode':'Sort Mode','DashboardWebStringId.ConditionalFormatting.DatesOccurringThisWeek':'This Week','DashboardWebStringId.Gauge.Type.HalfCircular':'Half Circular','DashboardWebStringId.Map.Position.TopLeft':'Top Left','DashboardWebStringId.ConditionalFormatting.AppearanceType':'Appearance Type','DashboardWebStringId.Preview':'Preview','DashboardWebStringId.Parameters.Done':'Done','DashboardWebStringId.Treemap.LayoutDirection':'Layout Direction','DashboardWebStringId.TextBoxFormatText':'Format','DashboardWebStringId.Chart.Position.TopRightVertical':'Top Right 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Base','DashboardWebStringId.Image.SizeMode.Squeeze':'Squeeze','DashboardWebStringId.Map.Viewport.CenterPointLatitude':'Center Point Latitude','DashboardWebStringId.DataItem.ShowGrandTotals':'Show Grand Totals','DashboardWebStringId.Delta.ThresholdValue':'Threshold Value','DashboardWebStringId.ColorScheme.Colors':'Colors','DashboardWebStringId.Chart.IsInsideOfDiagram':'Inside diagram','DashboardWebStringId.Gauge.Type.ThreeFourthCircular':'Three-Quarter Circular','DashboardWebStringId.ConditionalFormatting.AboveOrEqual':'Above or Equal','DashboardWebStringId.DesignerToolbar.Pixels':'px','DashboardWebStringId.Calculations.RunningTotal':'Running Total of','DashboardWebStringId.ConditionalFormatting.Appearance.BackColor':'Back Color','DashboardWebStringId.AccordionTab.MapLegend':'Color Legend','DashboardWebStringId.Calculations.Types.Moving':'Moving','DashboardWebStringId.Dashboard.ComponentName':'Component Name','DashboardWebStringId.Chart.LogarithmicScaleBase10':'10','DashboardWebStringId.Map.WeightedLegendType.Linear':'Linear','DashboardWebStringId.Title.Text':'Text','DashboardWebStringId.ConditionalFormatting.DatesOccurringLaterThisWeek':'This week, beyond tomorrow','DashboardWebStringId.ConditionalFormatting.DatesOccurringLaterThisYear':'This year, beyond this month','DashboardWebStringId.Image.VerticalAlignment':'Vertical Alignment','DashboardWebStringId.AccordionTab.PivotInitialState':'Initial State','DashboardWebStringId.Grid.BandedRows':'Banded Rows','DashboardWebStringId.Map.Area.USA':'USA','DashboardWebStringId.CardLayout.ResetTemplate':'Reset','DashboardWebStringId.Binding.DefaultEmptyPlaceholder':'Set {0}','DashboardWebStringId.Grid.Dimension':'Dimension','DashboardWebStringId.Map.WeightedLegendType.Nested':'Nested','DashboardWebStringId.Pie.LabelContentType.Percent':'Percent','DashboardWebStringId.Map.Area.Canada':'Canada','DashboardWebStringId.Title.Visible':'Visible','DashboardWebStringId.RangeFilter.EndMode':'End Mode','DashboardWebStringId.RangeFilter.EndDate':'End Date','DashboardWebStringId.GeoPointMapClusterization':'Enable Clustering','DashboardWebStringId.AccordionTab.ScatterChartPointLabelOptions':'Point Labels','DashboardWebStringId.DateFilter.ArrangementModeVertical':'Vertical','DashboardWebStringId.Map.Area.Custom':'Custom','DashboardWebStringId.Dialog.UnsupportedCalculatedField':'This data item does not support the calculated field you created. This field is available on the Data Sources page of the dashboard menu.','DashboardWebStringId.New.DashboardName':'Dashboard Name:','DashboardWebStringId.Binding.AddSeries':'Add Series','DashboardWebStringId.Calculations.DifferenceType':'Difference Type','DashboardWebStringId.Binding.Columns':'Columns','DashboardWebStringId.ConditionalFormatting.IconType.ShapeYellowCircle':'Shape Yellow Circle','DashboardWebStringId.DesignerToolbar.Width':'W:','DashboardWebStringId.ConditionalFormatting.IconType.Rating1FilledBox':'Rating 1 Filled Box','DashboardWebStringId.Grid.Hyperlink':'Hyperlink','DashboardWebStringId.Duplicate':'Duplicate current item','DashboardWebStringId.Pie.Donut':'Donut','DashboardWebStringId.Binding.ConfigureMap':'Configure Map','DashboardWebStringId.Binding.ConfigureRow':'Configure Row','DashboardWebStringId.DataSources.CalculatedField.FieldType':'Field Type','DashboardWebStringId.RangeFilter.EndIntervalAndOffset':'End Interval and Offset','DashboardWebStringId.Binding.EmptySearchResult':'Nothing was found','DashboardWebStringId.DashboardItemMenu.Bindings.SelectDataSourceButton':'Select a data source','DashboardWebStringId.PivotGrid.AutoExpandColumnGroups':'Auto-Expand Column Groups','DashboardWebStringId.Image.SizeMode.Clip':'Clip','DashboardWebStringId.Image.SizeMode.Zoom':'Zoom','DashboardWebStringId.ButtonContinuous':'Continuous','DashboardWebStringId.ConditionalFormatting.IconType.ShapeGreenCircle':'Shape Green Circle','DashboardWebStringId.Parameters.LookUpSettingsType.DynamicList':'Dynamic List','DashboardWebStringId.RangeFilter.StartIntervalAndOffset':'Start Interval and Offset','DashboardWebStringId.TilesLabelContentType':'Tile Label','DashboardWebStringId.DataItem.IncludeGroupSeparator':'Include Group Separator','DashboardWebStringId.NewDashboard':'New Dashboard','DashboardWebStringId.Map.IncludeSummaryValueToShapeTitle':'Include Summary 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','DashboardWebStringId.FilterItem.Type.Standard':'Standard','DashboardWebStringId.ConditionalFormatting.IconType.Rating0FilledBoxes':'Rating 0 Filled Boxes','DashboardWebStringId.Colorization.MeasureNames':'Measure Names','DashboardWebStringId.Chart.Orientation':'Orientation','DashboardWebStringId.DataSources.UsedDataSources':'Used Data Sources','DashboardWebStringId.DefaultNameBubbleMapItem':'Bubble Map','DashboardWebStringId.ConditionalFormatting.Miscellaneous':'Miscellaneous','DashboardWebStringId.Notification.AttemptToConvertItemToType':'An error occurred during an attempt to convert the item to the type ','DashboardWebStringId.Calculations.WindowDefinitionModePredefined':'Predefined','DashboardWebStringId.ConditionalFormatting.AverageType':'Average Type','DashboardWebStringId.ConditionalFormatting.CalculatedBy':'Calculated by','DashboardWebStringId.Chart.LabelContent':'Data Labels','DashboardWebStringId.Calculations.Rank':'Rank of','DashboardWebStringId.Chart.AlwaysShowZeroLevel':'Always show zero level','DashboardWebStringId.FilterItem.Type.Checked':'Checked','DashboardWebStringId.ConditionalFormatting.Negative':'Negative','DashboardWebStringId.DataSources.Save':'Save','DashboardWebStringId.Binding.AddValues':'Add Values','DashboardWebStringId.DateFilter.FilterType':'Filter Type','DashboardWebStringId.Treemap.TileLabelsArgumentAndValue':'Argument and Value','DashboardWebStringId.AccordionTab.ShowTotals':'Totals','DashboardWebStringId.Calculations.WindowDefinition':'Window Definition','DashboardWebStringId.DataSources.DashboardDataSourceWizard':'Dashboard Data Source Wizard','DashboardWebStringId.CardLayout.LayoutOptions':'Layout Options','DashboardWebStringId.AddItemInvitation':'Drag an item from the Toolbox or click a button below to create a new item.','DashboardWebStringId.DataItem.Precision':'Precision','DashboardWebStringId.Treemap.GroupLabelsArgument':'Argument','DashboardWebStringId.CrossDataSourceFiltering':'Cross-Data-Source Filtering','DashboardWebStringId.ColoringModeOff':'Off','DashboardWebStringId.GroupsTooltipContentType':'Group Tooltip','DashboardWebStringId.Binding.SetLatitude':'Set Latitude','DashboardWebStringId.DashboardMenuSave':'Save','DashboardWebStringId.DashboardMenuOpen':'Open...','DashboardWebStringId.TextBoxItemEditor.DialogClose':'Close','DashboardWebStringId.Chart.AddPane':'Add Pane','DashboardWebStringId.ButtonYes':'YES','DashboardWebStringId.ButtonOff':'OFF','DashboardWebStringId.Chart.Orientation.RotateRight':'Rotate Right','DashboardWebStringId.Binding.Searching':'Start typing to search...','DashboardWebStringId.DateFilter.ArrangementModeHorizontal':'Horizontal','DashboardWebStringId.ConditionalFormatting.BarOptions':'Bar Options','DashboardWebStringId.ConditionalFormatting.Ranges':'Ranges','DashboardWebStringId.TextBoxItemEditor.DialogSaveAndClose':'Save and Close','DashboardWebStringId.Binding.ConfigureLatitude':'Configure Latitude','DashboardWebStringId.Delta.ThresholdType':'Threshold Type','DashboardWebStringId.DataSources.CalculatedField.UniqueNameError':'Calculated field should have a unique name.','DashboardWebStringId.MapLockNavigationLocked':'Locked','DashboardWebStringId.SeriesItem.SeriesDimensions':'Series Dimensions','DashboardWebStringId.ConditionalFormatting.BelowOrEqual':'Below or Equal','DashboardWebStringId.Notification.DashboardSaving':'Dashboard is saving','DashboardWebStringId.Grid.Sparkline':'Sparkline','DashboardWebStringId.Image.Alignment.Right':'Right','DashboardWebStringId.Map.WeightedLegendType':'Type','DashboardWebStringId.GroupsLabelContentType':'Group Label','DashboardWebStringId.Grid.FilterClause.ResetOperation':'Reset','DashboardWebStringId.Parameters.SortByMember':'Sort By','DashboardWebStringId.Chart.Position.TopLeftVertical':'Top Left Vertical','DashboardWebStringId.SummaryType':'Summary Type','DashboardWebStringId.DataSources.CreateDataSource.Tooltip':'Create a new data source...','DashboardWebStringId.Binding.AddArgument':'Add Argument','DashboardWebStringId.DataSources.NoUsedDataSources':'There are no used data sources in this dashboard.','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorCircledRedCross':'Indicator Circled Red Cross','DashboardWebStringId.ShowCaptionText':'Show Caption','DashboardWebStringId.TextBoxItemEditor.EditTextButton':'Edit Text','DashboardWebStringId.Parameters.Reorder':'Reorder','DashboardWebStringId.DashboardMenuNewDashboardNamePlaceholder':'Enter a dashboard name','DashboardWebStringId.Calculations.DefinitionMode':'Definition Mode','DashboardWebStringId.ConditionalFormatting.IconType.Rating2QuartersGrayCircle':'Rating 2 Quarters Gray Circle','DashboardWebStringId.Grid.FilterClause.Between':'Between','DashboardWebStringId.Grid.FilterClause.DoesNotEqual':'Does not equal','DashboardWebStringId.ConditionalFormatting.DatesOccurringEarlierThisYear':'This year, prior to this month','DashboardWebStringId.ConditionalFormatting.DatesOccurringEarlierThisWeek':'This week, prior to yesterday','DashboardWebStringId.Parameters.NoSelectedParameter':'No parameter is selected.','DashboardWebStringId.Chart.VisiblePointsCount':'Visible Points Count','DashboardWebStringId.ConditionalFormatting.DatesOccurringBeyond':'Following the month in 2 months time','DashboardWebStringId.Notification.DashboardSavingIsNotAvailable':'Saving is not available','DashboardWebStringId.TreemapLayoutAlgorithm':'Layout Algorithm','DashboardWebStringId.ConditionalFormatting.Condition':'Condition','DashboardWebStringId.Map.Viewport.TopLatitude':'Top Latitude','DashboardWebStringId.Calculations.PercentOfTotal':'Percent Of Total of','DashboardWebStringId.ConditionalFormatting.DatesOccurringEarlierThisMonth':'This month, prior to previous week','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGrayArrowUp':'Directional Gray Arrow Up','DashboardWebStringId.SaveConfirmationDialogMessage':'If you leave before saving, your changes will be lost.','DashboardWebStringId.TextBoxItemEditor.InsertField':'Insert Field','DashboardWebStringId.Binding.Sparkline':'Sparkline','DashboardWebStringId.Grid.WidthType.Weight':'Weight','DashboardWebStringId.Notification.AttemptToLoadFieldListForDataSource':'An error occurred during an attempt to load the field list for the data source ','DashboardWebStringId.Gauge.Max':'Maximum Value','DashboardWebStringId.Gauge.Min':'Minimum Value','DashboardWebStringId.Title.ImageNone':'None','DashboardWebStringId.CardLayout.MinWidth':'Min Width','DashboardWebStringId.Map.AttributeName':'Attribute Name','DashboardWebStringId.DataItem.ShowValues':'Show Values','DashboardWebStringId.ConditionalFormatting.IconType.ShapeRedDiamond':'Shape Red Diamond','DashboardWebStringId.Chart.Position.BottomCenterHorizontal':'Bottom Center Horizontal','DashboardWebStringId.Map.CustomAttributeFile':'Custom Attribute File','DashboardWebStringId.Binding.ConfigureArgument':'Configure Argument','DashboardWebStringId.Chart.PrimaryAxisY':'Primary Axis Y','DashboardWebStringId.Image.Alignment.Left':'Left','DashboardWebStringId.Dimension.GroupInterval':'Group Interval','DashboardWebStringId.MapLockNavigationUnlocked':'Unlocked','DashboardWebStringId.Coloring.Global':'Global','DashboardWebStringId.Pie.LabelContentType.None':'None','DashboardWebStringId.DateFilter.FilterTypeBefore':'Before','DashboardWebStringId.Gauge.Type.LeftQuarterCircular':'Left-Quarter Circular','DashboardWebStringId.Map.Area.SouthAmerica':'South America','DashboardWebStringId.Viewer':'Viewer','DashboardWebStringId.Gauge.Type.LinearVertical':'Linear Vertical','DashboardWebStringId.Binding.ConfigureColor':'Configure Color','DashboardWebStringId.AccordionTab.ItemFilter':'Item Filter','DashboardWebStringId.Binding.ConfigureGauge':'Configure Gauge','DashboardWebStringId.Chart.LimitVisiblePoints':'Limit visible points','DashboardWebStringId.Colorization.AddColor':'Add Color','DashboardWebStringId.Map.Position.BottomRight':'Bottom Right','DashboardWebStringId.Binding.ConfigureValue':'Configure Value','DashboardWebStringId.TopNEnabled':'Enabled','DashboardWebStringId.Grid.TotalType':'Total Type','DashboardWebStringId.Grid.FilterClause.Contains':'Contains','DashboardWebStringId.Map.ShowWeightedLegend':'Show Weighted Legend','DashboardWebStringId.DateFilter.DatePickerLocationHidden':'Hidden','DashboardWebStringId.Chart.Position.BottomRightHorizontal':'Bottom Right Horizontal','DashboardWebStringId.Grid.FilterClause.Greater':'Greater than','DashboardWebStringId.Dashboards':'Dashboards','DashboardWebStringId.Treemap.GroupLabelsNone':'None','DashboardWebStringId.CardLayout.TemplateElementsEditor':'Value/Element','DashboardWebStringId.Grid.FilterClause.Less':'Less than','DashboardWebStringId.FormatRuleApplyToTextElement':'Text','DashboardWebStringId.ConditionalFormatting.GradientRangeBar':'Gradient Range Bar','DashboardWebStringId.Cards.ArrangementMode':'Content Arrangement Mode','DashboardWebStringId.DataItem.ShowTotals':'Show Totals','DashboardWebStringId.Remove':'Remove','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorGreenFlag':'Indicator Green Flag','DashboardWebStringId.Title.IncludeMasterFilter':'Include Master Filter','DashboardWebStringId.Binding.Cards':'Cards','DashboardWebStringId.Binding.XAxis':'X-axis','DashboardWebStringId.Binding.YAxis':'Y-axis','DashboardWebStringId.Search':'Search...','DashboardWebStringId.InteractivityOptions.TargetDimensions.Arguments':'Arguments','DashboardWebStringId.Chart.Visible':'Visible','DashboardWebStringId.ConditionalFormatting.MinimumType':'Minimum Type','DashboardWebStringId.InteractivityOptions.IsMasterFilter':'Master Filter','DashboardWebStringId.ConditionalFormatting.IconType.Rating4FilledBoxes':'Rating 4 Filled Boxes','DashboardWebStringId.Binding.ConfigureCard':'Configure Card','DashboardWebStringId.Binding.SetAttribute':'Set Attribute','DashboardWebStringId.Chart.EnableZooming':'Enable Zooming','DashboardWebStringId.Pie.LabelContentType.ValueAndPercent':'Value And Percent','DashboardWebStringId.ButtonConfirm':'Confirm','DashboardWebStringId.DateFilter.ArrangementMode':'Arrangement Mode','DashboardWebStringId.Treemap.TopRightToBottomLeftLayoutDirection':'Top Right - Bottom Left','DashboardWebStringId.Grid.HorizontalLines':'Horizontal Lines','DashboardWebStringId.Calculations.DifferenceCalculation':'Difference of','DashboardWebStringId.PivotGrid.ColumnTotalsPositionFar':'Far','DashboardWebStringId.Notification.UnderlyingRequestDataNotLoaded':'The data for the \\'{0}\\' dashboard item has not been loaded yet. Please check whether the \\'getItemData\\' method call returns an initialized non-null value before you request the underlying data.','DashboardWebStringId.Chart.Position.Outside':'Outside','DashboardWebStringId.Binding.HiddenDimensions':'Hidden Dimensions','DashboardWebStringId.Map.UseBindingAttribute':'Use binding attribute','DashboardWebStringId.AccordionTab.ChartLegend':'Legend','DashboardWebStringId.Calculations.PreviousValuesCount':'Start Offset','DashboardWebStringId.Treemap.BottomLeftToTopRightLayoutDirection':'Bottom Left - Top Right','DashboardWebStringId.CardLayout.Editor.FormatOptions':'Format Options','DashboardWebStringId.Chart.Position.TopCenterHorizontal':'Top Center Horizontal','DashboardWebStringId.ConditionalFormatting.IconType.ShapeLightRedCircle':'Shape Light Red Circle','DashboardWebStringId.ConditionalFormatting.ValueComparison':'Value Comparison','DashboardWebStringId.InteractivityOptions.MasterFilterMode.Multiple':'Multiple','DashboardWebStringId.Binding.HiddenMeasures':'Hidden Measures','DashboardWebStringId.Notification.DashboardLoading':'Dashboard is loading...','DashboardWebStringId.Options.Caption':'Caption','DashboardWebStringId.Map.CustomMapOptions':'Custom Map Options','DashboardWebStringId.PivotGrid.ValuesPositionColumns':'Columns','DashboardWebStringId.Chart.Orientation.Default':'Default','DashboardWebStringId.ConditionalFormatting.IconType.ShapeRedCircle':'Shape Red Circle','DashboardWebStringId.ConvertTo':'Convert To','DashboardWebStringId.Binding.SetLongitude':'Set Longitude','DashboardWebStringId.DataSources.ChooseDataSource':'Choose the data source for the dashboard','DashboardWebStringId.ConditionalFormatting.IconType.Rating0Bars':'Rating 0 Bars','DashboardWebStringId.ColorScheme.Empty':'The current dashboard does not contain color schemes','DashboardWebStringId.ConditionalFormatting.IconType.Rating2Bars':'Rating 2 Bars','DashboardWebStringId.Card.SparklineOptions':'Sparkline Options','DashboardWebStringId.ConditionalFormatting.IconType.Rating3Bars':'Rating 3 Bars','DashboardWebStringId.ColorScheme.Color':'Color','DashboardWebStringId.ConditionalFormatting.IconType.Rating4Bars':'Rating 4 Bars','DashboardWebStringId.Grid.AutoFitToContentsColumnWidthMode':'AutoFit to Contents','DashboardWebStringId.InteractivityOptions.MasterFilterMode.Single':'Single','DashboardWebStringId.Colorization.ValidationSelectMeasure':'Select at least one measure','DashboardWebStringId.CollectionEditor.NoItems':'Click + to add a new item.','DashboardWebStringId.Image.Alignment.Top':'Top','DashboardWebStringId.ConditionalFormatting':'Conditional Formatting','DashboardWebStringId.Binding.Maps':'Maps','DashboardWebStringId.Grid.FilterClause.GreaterOrEqual':'Greater than or equal to','DashboardWebStringId.Cards.ArrangementMode.FixedColumns':'Fixed Columns','DashboardWebStringId.Chart.Name':'Name','DashboardWebStringId.ColoringModeAuto':'Auto','DashboardWebStringId.Chart.Position.TopCenterVertical':'Top Center Vertical','DashboardWebStringId.ConditionalFormatting.MaximumType':'Maximum Type','DashboardWebStringId.Pie.LabelContentType.Value':'Value','DashboardWebStringId.Chart.AxisX':'Axis X','DashboardWebStringId.Chart.AxisY':'Axis Y','DashboardWebStringId.Map.AttributeDimension':'Attribute Dimension','DashboardWebStringId.Treemap.GroupTooltipsNone':'None','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorCircledYellowExclamation':'Indicator Circled Yellow Exclamation','DashboardWebStringId.NoDashboards':'There are no dashboards to display.','DashboardWebStringId.Chart.Value':'Value','DashboardWebStringId.Bindings':'Binding','DashboardWebStringId.Chart.Title':'Title','DashboardWebStringId.DateFilter.FilterTypeBetween':'Between','DashboardWebStringId.Chart.Panes':'Panes','DashboardWebStringId.Grid.ShowStartEndValues':'Show Start/End Values','DashboardWebStringId.Map.Area':'Default Map','DashboardWebStringId.Binding.AddGauge':'Add Gauge','DashboardWebStringId.PivotGrid.ColumnGrandTotals':'Column Grand Totals','DashboardWebStringId.RangeFilter.ClearDefaultCustomPeriod':'Clear Default Custom Period','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorYellowFlag':'Indicator Yellow Flag','DashboardWebStringId.ConditionalFormatting.StyleSettingsType':'Style Settings Type','DashboardWebStringId.Binding.AddValue':'Add Value','DashboardWebStringId.DataSources.AddQuery':'Add Query','DashboardWebStringId.InteractivityOptions.IgnoreMasterFilters':'Ignore Master Filters','DashboardWebStringId.Chart.Reverse':'Reverse','DashboardWebStringId.Grid.FilterClause.BetweenStart':'Start','DashboardWebStringId.ButtonVisible':'Visible','DashboardWebStringId.Binding.AddCard':'Add Card','DashboardWebStringId.Pie.LabelContentType.ArgumentValueAndPercent':'Argument, Value And Percent','DashboardWebStringId.Treemap.StripedLayoutAlgorithm':'Striped','DashboardWebStringId.Map.ValueMap':'Value Map','DashboardWebStringId.Grid.FilterClause.Equals':'Equals','DashboardWebStringId.FilterItem.Type.Radio':'Radio','DashboardWebStringId.DataSources.IncludeToTheDashboard':'Add','DashboardWebStringId.DataSources.AddDataSource':'Add Data Source','DashboardWebStringId.Title.Aligment.Left':'Left','DashboardWebStringId.Parameters.LookUpSettingsType.StaticList':'Static List','DashboardWebStringId.Chart.ArgumentAndValues':'Argument and Values','DashboardWebStringId.Title.Image':'Image','DashboardWebStringId.Chart.ShowZeroValues':'Show for zero values','DashboardWebStringId.Delta.ResultIndication':'Result Indication','DashboardWebStringId.AccordionTab.ChoroplethMapShapeLabelsAttribute':'Shape Labels','DashboardWebStringId.ConditionalFormatting.IconType.IndicatorYellowExclamation':'Indicator Yellow Exclamation','DashboardWebStringId.Parameters.AddParameter.Tooltip':'Add new parameter to the dashboard','DashboardWebStringId.ConditionalFormatting.DatesOccurringNextWeek':'Next Week','DashboardWebStringId.Chart.ArgumentAndWeight':'Argument and Weight','DashboardWebStringId.Dialog.Save':'Save','DashboardWebStringId.Chart.OverlappingMode.Hide':'Hide','DashboardWebStringId.Chart.OverlappingMode.None':'None','DashboardWebStringId.PivotGrid.RowTotalsPositionTop':'Top','DashboardWebStringId.CardLayout.Editor.CardLayout':'Card Layout','DashboardWebStringId.Dialog.Warning':'Warning','DashboardWebStringId.ConditionalFormatting.RangeGradient':'Range Gradient','DashboardWebStringId.DashboardMenuDataSources':'Data Sources','DashboardWebStringId.Gauge.Type.RightQuarterCircular':'Right-Quarter Circular','DashboardWebStringId.ConditionalFormatting.Above':'Above','DashboardWebStringId.ConditionalFormatting.Below':'Below','DashboardWebStringId.Treemap.GroupLabelsValue':'Value','DashboardWebStringId.DateFilter.DatePickerLocationNear':'Near','DashboardWebStringId.Pie.ShowCaptions':'Show Pie Captions','DashboardWebStringId.AccordionTab.VisibleDataFilter':'Visible Data Filter','DashboardWebStringId.DataSources.AvailableDataSourcesError':'An error occurred during an attempt to load the list of available data sources','DashboardWebStringId.Currency.CurrencyCulture':'Culture','DashboardWebStringId.ButtonDiscrete':'Discrete','DashboardWebStringId.Treemap.TopLeftToBottomRightLayoutDirection':'Top Left - Bottom Right','DashboardWebStringId.Pie.LabelContentType.ArgumentAndValue':'Argument And Value','DashboardWebStringId.Grid.FilterClause.ApplyFilter':'Apply filter','DashboardWebStringId.Binding.DataSource':'Data Source','DashboardWebStringId.Loading':'LOADING...','DashboardWebStringId.Options':'Options','DashboardWebStringId.More':'More','DashboardWebStringId.Type':'Type','DashboardWebStringId.ConditionalFormatting.IconType.ShapeGreenTrafficLight':'Shape Green Traffic Light','DashboardWebStringId.ConditionalFormatting.DatesOccurringLaterThisMonth':'This month, beyond next week','DashboardWebStringId.DefaultNamePieMapItem':'Pie Map','DashboardWebStringId.ConditionalFormatting.UnsupportedDataType':'This data type is not supported','DashboardWebStringId.ConditionType':'Condition Type','DashboardWebStringId.ConditionalFormatting.DatesOccurringThisMonth':'This Month','DashboardWebStringId.ConditionalFormatting.IconType.Rating3QuartersGrayCircle':'Rating 3 Quarters Gray Circle','DashboardWebStringId.Parameters.LookUpSettingsType':'Look-up Settings','DashboardWebStringId.Chart.AxisYSecondary':'Axis Y Secondary','DashboardWebStringId.ConditionalFormatting.ConditionMinimum':'Minimum','DashboardWebStringId.Treemap.TileTooltipsArgumentAndValue':'Argument and Value','DashboardWebStringId.DateFilter.DatePickerLocation':'Date Picker Location','DashboardWebStringId.AccordionTab.Labels':'Labels','DashboardWebStringId.RangeFilter.SetDefaultCustomPeriod':'Set as Default','DashboardWebStringId.AccordionTab.Layout':'Layout','DashboardWebStringId.Chart.Rotated':'Rotated','DashboardWebStringId.Treemap.TileLabelsArgument':'Argument','DashboardWebStringId.Delta.ValueType':'Value Type','DashboardWebStringId.ConditionalFormatting.IconType.Rating1QuarterGrayCircle':'Rating 1 Quarter Gray Circle','DashboardWebStringId.PivotGrid.ValuesPosition':'Values Position','DashboardWebStringId.Grid.FilterClause.DoesNotContain':'Does not contain','DashboardWebStringId.Chart.Position.BottomLeftVertical':'Bottom Left Vertical','DashboardWebStringId.Map.ShapeFileLoaded':'(SHP File)','DashboardWebStringId.Chart.ShowLegend':'Show Legend','DashboardWebStringId.Dashboard.Items':'Items','DashboardWebStringId.Chart.Position.BottomCenterVertical':'Bottom Center Vertical','DashboardWebStringId.Map.Viewport.BottomLatitude':'Bottom Latitude','DashboardWebStringId.ConditionalFormatting.IconType.ShapeYellowTrafficLight':'Shape Yellow Traffic Light','DashboardWebStringId.ConditionalFormatting.IconType.DirectionalGrayDownArrow':'Directional Gray Down Arrow','DashboardWebStringId.TreeView.AutoExpand':'Auto Expand','DashboardWebStringId.Grid.DisplayMode':'Display Mode','DashboardWebStringId.Grid.DeltaOptions':'Delta Options','DashboardWebStringId.Binding.Argument':'Argument','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAfter1':'Next Month','DashboardWebStringId.ConditionalFormatting.DatesOccurringMonthAfter2':'During the month in 2 months 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-Telu-IN\",\"gor\":\"gor-Latn-ID\",\"gos\":\"gos-Latn-NL\",\"got\":\"got-Goth-UA\",\"grb\":\"grb-Latn-ZZ\",\"grc\":\"grc-Cprt-CY\",\"grc-Linb\":\"grc-Linb-GR\",\"grt\":\"grt-Beng-IN\",\"grw\":\"grw-Latn-ZZ\",\"gsw\":\"gsw-Latn-CH\",\"gu\":\"gu-Gujr-IN\",\"gub\":\"gub-Latn-BR\",\"guc\":\"guc-Latn-CO\",\"gud\":\"gud-Latn-ZZ\",\"gur\":\"gur-Latn-GH\",\"guw\":\"guw-Latn-ZZ\",\"gux\":\"gux-Latn-ZZ\",\"guz\":\"guz-Latn-KE\",\"gv\":\"gv-Latn-IM\",\"gvf\":\"gvf-Latn-ZZ\",\"gvr\":\"gvr-Deva-NP\",\"gvs\":\"gvs-Latn-ZZ\",\"gwc\":\"gwc-Arab-ZZ\",\"gwi\":\"gwi-Latn-CA\",\"gwt\":\"gwt-Arab-ZZ\",\"gyi\":\"gyi-Latn-ZZ\",\"ha\":\"ha-Latn-NG\",\"ha-CM\":\"ha-Arab-CM\",\"ha-SD\":\"ha-Arab-SD\",\"hag\":\"hag-Latn-ZZ\",\"hak\":\"hak-Hans-CN\",\"ham\":\"ham-Latn-ZZ\",\"haw\":\"haw-Latn-US\",\"haz\":\"haz-Arab-AF\",\"hbb\":\"hbb-Latn-ZZ\",\"hdy\":\"hdy-Ethi-ZZ\",\"he\":\"he-Hebr-IL\",\"hhy\":\"hhy-Latn-ZZ\",\"hi\":\"hi-Deva-IN\",\"hia\":\"hia-Latn-ZZ\",\"hif\":\"hif-Latn-FJ\",\"hig\":\"hig-Latn-ZZ\",\"hih\":\"hih-Latn-ZZ\",\"hil\":\"hil-Latn-PH\",\"hla\":\"hla-Latn-ZZ\",\"hlu\":\"hlu-Hluw-TR\",\"hmd\":\"hmd-Plrd-CN\",\"hmt\":\"hmt-Latn-ZZ\",\"hnd\":\"hnd-Arab-PK\",\"hne\":\"hne-Deva-IN\",\"hnj\":\"hnj-Hmng-LA\",\"hnn\":\"hnn-Latn-PH\",\"hno\":\"hno-Arab-PK\",\"ho\":\"ho-Latn-PG\",\"hoc\":\"hoc-Deva-IN\",\"hoj\":\"hoj-Deva-IN\",\"hot\":\"hot-Latn-ZZ\",\"hr\":\"hr-Latn-HR\",\"hsb\":\"hsb-Latn-DE\",\"hsn\":\"hsn-Hans-CN\",\"ht\":\"ht-Latn-HT\",\"hu\":\"hu-Latn-HU\",\"hui\":\"hui-Latn-ZZ\",\"hy\":\"hy-Armn-AM\",\"hz\":\"hz-Latn-NA\",\"ia\":\"ia-Latn-FR\",\"ian\":\"ian-Latn-ZZ\",\"iar\":\"iar-Latn-ZZ\",\"iba\":\"iba-Latn-MY\",\"ibb\":\"ibb-Latn-NG\",\"iby\":\"iby-Latn-ZZ\",\"ica\":\"ica-Latn-ZZ\",\"ich\":\"ich-Latn-ZZ\",\"id\":\"id-Latn-ID\",\"idd\":\"idd-Latn-ZZ\",\"idi\":\"idi-Latn-ZZ\",\"idu\":\"idu-Latn-ZZ\",\"ife\":\"ife-Latn-TG\",\"ig\":\"ig-Latn-NG\",\"igb\":\"igb-Latn-ZZ\",\"ige\":\"ige-Latn-ZZ\",\"ii\":\"ii-Yiii-CN\",\"ijj\":\"ijj-Latn-ZZ\",\"ik\":\"ik-Latn-US\",\"ikk\":\"ikk-Latn-ZZ\",\"ikt\":\"ikt-Latn-CA\",\"ikw\":\"ikw-Latn-ZZ\",\"ikx\":\"ikx-Latn-ZZ\",\"ilo\":\"ilo-Latn-PH\",\"imo\":\"imo-Latn-ZZ\",\"in\":\"in-Latn-ID\",\"inh\":\"inh-Cyrl-RU\",\"io\":\"io-Latn-001\",\"iou\":\"iou-Latn-ZZ\",\"iri\":\"iri-Latn-ZZ\",\"is\":\"is-Latn-IS\",\"it\":\"it-Latn-IT\",\"iu\":\"iu-Cans-CA\",\"iw\":\"iw-Hebr-IL\",\"iwm\":\"iwm-Latn-ZZ\",\"iws\":\"iws-Latn-ZZ\",\"izh\":\"izh-Latn-RU\",\"izi\":\"izi-Latn-ZZ\",\"ja\":\"ja-Jpan-JP\",\"jab\":\"jab-Latn-ZZ\",\"jam\":\"jam-Latn-JM\",\"jbo\":\"jbo-Latn-001\",\"jbu\":\"jbu-Latn-ZZ\",\"jen\":\"jen-Latn-ZZ\",\"jgk\":\"jgk-Latn-ZZ\",\"jgo\":\"jgo-Latn-CM\",\"ji\":\"ji-Hebr-UA\",\"jib\":\"jib-Latn-ZZ\",\"jmc\":\"jmc-Latn-TZ\",\"jml\":\"jml-Deva-NP\",\"jra\":\"jra-Latn-ZZ\",\"jut\":\"jut-Latn-DK\",\"jv\":\"jv-Latn-ID\",\"jw\":\"jw-Latn-ID\",\"ka\":\"ka-Geor-GE\",\"kaa\":\"kaa-Cyrl-UZ\",\"kab\":\"kab-Latn-DZ\",\"kac\":\"kac-Latn-MM\",\"kad\":\"kad-Latn-ZZ\",\"kai\":\"kai-Latn-ZZ\",\"kaj\":\"kaj-Latn-NG\",\"kam\":\"kam-Latn-KE\",\"kao\":\"kao-Latn-ML\",\"kbd\":\"kbd-Cyrl-RU\",\"kbm\":\"kbm-Latn-ZZ\",\"kbp\":\"kbp-Latn-ZZ\",\"kbq\":\"kbq-Latn-ZZ\",\"kbx\":\"kbx-Latn-ZZ\",\"kby\":\"kby-Arab-NE\",\"kcg\":\"kcg-Latn-NG\",\"kck\":\"kck-Latn-ZW\",\"kcl\":\"kcl-Latn-ZZ\",\"kct\":\"kct-Latn-ZZ\",\"kde\":\"kde-Latn-TZ\",\"kdh\":\"kdh-Arab-TG\",\"kdl\":\"kdl-Latn-ZZ\",\"kdt\":\"kdt-Thai-TH\",\"kea\":\"kea-Latn-CV\",\"ken\":\"ken-Latn-CM\",\"kez\":\"kez-Latn-ZZ\",\"kfo\":\"kfo-Latn-CI\",\"kfr\":\"kfr-Deva-IN\",\"kfy\":\"kfy-Deva-IN\",\"kg\":\"kg-Latn-CD\",\"kge\":\"kge-Latn-ID\",\"kgf\":\"kgf-Latn-ZZ\",\"kgp\":\"kgp-Latn-BR\",\"kha\":\"kha-Latn-IN\",\"khb\":\"khb-Talu-CN\",\"khn\":\"khn-Deva-IN\",\"khq\":\"khq-Latn-ML\",\"khs\":\"khs-Latn-ZZ\",\"kht\":\"kht-Mymr-IN\",\"khw\":\"khw-Arab-PK\",\"khz\":\"khz-Latn-ZZ\",\"ki\":\"ki-Latn-KE\",\"kij\":\"kij-Latn-ZZ\",\"kiu\":\"kiu-Latn-TR\",\"kiw\":\"kiw-Latn-ZZ\",\"kj\":\"kj-Latn-NA\",\"kjd\":\"kjd-Latn-ZZ\",\"kjg\":\"kjg-Laoo-LA\",\"kjs\":\"kjs-Latn-ZZ\",\"kjy\":\"kjy-Latn-ZZ\",\"kk\":\"kk-Cyrl-KZ\",\"kk-AF\":\"kk-Arab-AF\",\"kk-Arab\":\"kk-Arab-CN\",\"kk-CN\":\"kk-Arab-CN\",\"kk-IR\":\"kk-Arab-IR\",\"kk-MN\":\"kk-Arab-MN\",\"kkc\":\"kkc-Latn-ZZ\",\"kkj\":\"kkj-Latn-CM\",\"kl\":\"kl-Latn-GL\",\"kln\":\"kln-Latn-KE\",\"klq\":\"klq-Latn-ZZ\",\"klt\":\"klt-Latn-ZZ\",\"klx\":\"klx-Latn-ZZ\",\"km\":\"km-Khmr-KH\",\"kmb\":\"kmb-Latn-AO\",\"kmh\":\"kmh-Latn-ZZ\",\"kmo\":\"kmo-Latn-ZZ\",\"kms\":\"kms-Latn-ZZ\",\"kmu\":\"kmu-Latn-ZZ\",\"kmw\":\"kmw-Latn-ZZ\",\"kn\":\"kn-Knda-IN\",\"knf\":\"knf-Latn-GW\",\"knp\":\"knp-Latn-ZZ\",\"ko\":\"ko-Kore-KR\",\"koi\":\"koi-Cyrl-RU\",\"kok\":\"kok-Deva-IN\",\"kol\":\"kol-Latn-ZZ\",\"kos\":\"kos-Latn-FM\",\"koz\":\"koz-Latn-ZZ\",\"kpe\":\"kpe-Latn-LR\",\"kpf\":\"kpf-Latn-ZZ\",\"kpo\":\"kpo-Latn-ZZ\",\"kpr\":\"kpr-Latn-ZZ\",\"kpx\":\"kpx-Latn-ZZ\",\"kqb\":\"kqb-Latn-ZZ\",\"kqf\":\"kqf-Latn-ZZ\",\"kqs\":\"kqs-Latn-ZZ\",\"kqy\":\"kqy-Ethi-ZZ\",\"kr\":\"kr-Latn-ZZ\",\"krc\":\"krc-Cyrl-RU\",\"kri\":\"kri-Latn-SL\",\"krj\":\"krj-Latn-PH\",\"krl\":\"krl-Latn-RU\",\"krs\":\"krs-Latn-ZZ\",\"kru\":\"kru-Deva-IN\",\"ks\":\"ks-Arab-IN\",\"ksb\":\"ksb-Latn-TZ\",\"ksd\":\"ksd-Latn-ZZ\",\"ksf\":\"ksf-Latn-CM\",\"ksh\":\"ksh-Latn-DE\",\"ksj\":\"ksj-Latn-ZZ\",\"ksr\":\"ksr-Latn-ZZ\",\"ktb\":\"ktb-Ethi-ZZ\",\"ktm\":\"ktm-Latn-ZZ\",\"kto\":\"kto-Latn-ZZ\",\"ku\":\"ku-Latn-TR\",\"ku-Arab\":\"ku-Arab-IQ\",\"ku-LB\":\"ku-Arab-LB\",\"kub\":\"kub-Latn-ZZ\",\"kud\":\"kud-Latn-ZZ\",\"kue\":\"kue-Latn-ZZ\",\"kuj\":\"kuj-Latn-ZZ\",\"kum\":\"kum-Cyrl-RU\",\"kun\":\"kun-Latn-ZZ\",\"kup\":\"kup-Latn-ZZ\",\"kus\":\"kus-Latn-ZZ\",\"kv\":\"kv-Cyrl-RU\",\"kvg\":\"kvg-Latn-ZZ\",\"kvr\":\"kvr-Latn-ID\",\"kvx\":\"kvx-Arab-PK\",\"kw\":\"kw-Latn-GB\",\"kwj\":\"kwj-Latn-ZZ\",\"kwo\":\"kwo-Latn-ZZ\",\"kxa\":\"kxa-Latn-ZZ\",\"kxc\":\"kxc-Ethi-ZZ\",\"kxm\":\"kxm-Thai-TH\",\"kxp\":\"kxp-Arab-PK\",\"kxw\":\"kxw-Latn-ZZ\",\"kxz\":\"kxz-Latn-ZZ\",\"ky\":\"ky-Cyrl-KG\",\"ky-Arab\":\"ky-Arab-CN\",\"ky-CN\":\"ky-Arab-CN\",\"ky-Latn\":\"ky-Latn-TR\",\"ky-TR\":\"ky-Latn-TR\",\"kye\":\"kye-Latn-ZZ\",\"kyx\":\"kyx-Latn-ZZ\",\"kzr\":\"kzr-Latn-ZZ\",\"la\":\"la-Latn-VA\",\"lab\":\"lab-Lina-GR\",\"lad\":\"lad-Hebr-IL\",\"lag\":\"lag-Latn-TZ\",\"lah\":\"lah-Arab-PK\",\"laj\":\"laj-Latn-UG\",\"las\":\"las-Latn-ZZ\",\"lb\":\"lb-Latn-LU\",\"lbe\":\"lbe-Cyrl-RU\",\"lbu\":\"lbu-Latn-ZZ\",\"lbw\":\"lbw-Latn-ID\",\"lcm\":\"lcm-Latn-ZZ\",\"lcp\":\"lcp-Thai-CN\",\"ldb\":\"ldb-Latn-ZZ\",\"led\":\"led-Latn-ZZ\",\"lee\":\"lee-Latn-ZZ\",\"lem\":\"lem-Latn-ZZ\",\"lep\":\"lep-Lepc-IN\",\"leq\":\"leq-Latn-ZZ\",\"leu\":\"leu-Latn-ZZ\",\"lez\":\"lez-Cyrl-RU\",\"lg\":\"lg-Latn-UG\",\"lgg\":\"lgg-Latn-ZZ\",\"li\":\"li-Latn-NL\",\"lia\":\"lia-Latn-ZZ\",\"lid\":\"lid-Latn-ZZ\",\"lif\":\"lif-Deva-NP\",\"lif-Limb\":\"lif-Limb-IN\",\"lig\":\"lig-Latn-ZZ\",\"lih\":\"lih-Latn-ZZ\",\"lij\":\"lij-Latn-IT\",\"lis\":\"lis-Lisu-CN\",\"ljp\":\"ljp-Latn-ID\",\"lki\":\"lki-Arab-IR\",\"lkt\":\"lkt-Latn-US\",\"lle\":\"lle-Latn-ZZ\",\"lln\":\"lln-Latn-ZZ\",\"lmn\":\"lmn-Telu-IN\",\"lmo\":\"lmo-Latn-IT\",\"lmp\":\"lmp-Latn-ZZ\",\"ln\":\"ln-Latn-CD\",\"lns\":\"lns-Latn-ZZ\",\"lnu\":\"lnu-Latn-ZZ\",\"lo\":\"lo-Laoo-LA\",\"loj\":\"loj-Latn-ZZ\",\"lok\":\"lok-Latn-ZZ\",\"lol\":\"lol-Latn-CD\",\"lor\":\"lor-Latn-ZZ\",\"los\":\"los-Latn-ZZ\",\"loz\":\"loz-Latn-ZM\",\"lrc\":\"lrc-Arab-IR\",\"lt\":\"lt-Latn-LT\",\"ltg\":\"ltg-Latn-LV\",\"lu\":\"lu-Latn-CD\",\"lua\":\"lua-Latn-CD\",\"luo\":\"luo-Latn-KE\",\"luy\":\"luy-Latn-KE\",\"luz\":\"luz-Arab-IR\",\"lv\":\"lv-Latn-LV\",\"lwl\":\"lwl-Thai-TH\",\"lzh\":\"lzh-Hans-CN\",\"lzz\":\"lzz-Latn-TR\",\"mad\":\"mad-Latn-ID\",\"maf\":\"maf-Latn-CM\",\"mag\":\"mag-Deva-IN\",\"mai\":\"mai-Deva-IN\",\"mak\":\"mak-Latn-ID\",\"man\":\"man-Latn-GM\",\"man-GN\":\"man-Nkoo-GN\",\"man-Nkoo\":\"man-Nkoo-GN\",\"mas\":\"mas-Latn-KE\",\"maw\":\"maw-Latn-ZZ\",\"maz\":\"maz-Latn-MX\",\"mbh\":\"mbh-Latn-ZZ\",\"mbo\":\"mbo-Latn-ZZ\",\"mbq\":\"mbq-Latn-ZZ\",\"mbu\":\"mbu-Latn-ZZ\",\"mbw\":\"mbw-Latn-ZZ\",\"mci\":\"mci-Latn-ZZ\",\"mcp\":\"mcp-Latn-ZZ\",\"mcq\":\"mcq-Latn-ZZ\",\"mcr\":\"mcr-Latn-ZZ\",\"mcu\":\"mcu-Latn-ZZ\",\"mda\":\"mda-Latn-ZZ\",\"mde\":\"mde-Arab-ZZ\",\"mdf\":\"mdf-Cyrl-RU\",\"mdh\":\"mdh-Latn-PH\",\"mdj\":\"mdj-Latn-ZZ\",\"mdr\":\"mdr-Latn-ID\",\"mdx\":\"mdx-Ethi-ZZ\",\"med\":\"med-Latn-ZZ\",\"mee\":\"mee-Latn-ZZ\",\"mek\":\"mek-Latn-ZZ\",\"men\":\"men-Latn-SL\",\"mer\":\"mer-Latn-KE\",\"met\":\"met-Latn-ZZ\",\"meu\":\"meu-Latn-ZZ\",\"mfa\":\"mfa-Arab-TH\",\"mfe\":\"mfe-Latn-MU\",\"mfn\":\"mfn-Latn-ZZ\",\"mfo\":\"mfo-Latn-ZZ\",\"mfq\":\"mfq-Latn-ZZ\",\"mg\":\"mg-Latn-MG\",\"mgh\":\"mgh-Latn-MZ\",\"mgl\":\"mgl-Latn-ZZ\",\"mgo\":\"mgo-Latn-CM\",\"mgp\":\"mgp-Deva-NP\",\"mgy\":\"mgy-Latn-TZ\",\"mh\":\"mh-Latn-MH\",\"mhi\":\"mhi-Latn-ZZ\",\"mhl\":\"mhl-Latn-ZZ\",\"mi\":\"mi-Latn-NZ\",\"mif\":\"mif-Latn-ZZ\",\"min\":\"min-Latn-ID\",\"mis\":\"mis-Hatr-IQ\",\"miw\":\"miw-Latn-ZZ\",\"mk\":\"mk-Cyrl-MK\",\"mki\":\"mki-Arab-ZZ\",\"mkl\":\"mkl-Latn-ZZ\",\"mkp\":\"mkp-Latn-ZZ\",\"mkw\":\"mkw-Latn-ZZ\",\"ml\":\"ml-Mlym-IN\",\"mle\":\"mle-Latn-ZZ\",\"mlp\":\"mlp-Latn-ZZ\",\"mls\":\"mls-Latn-SD\",\"mmo\":\"mmo-Latn-ZZ\",\"mmu\":\"mmu-Latn-ZZ\",\"mmx\":\"mmx-Latn-ZZ\",\"mn\":\"mn-Cyrl-MN\",\"mn-CN\":\"mn-Mong-CN\",\"mn-Mong\":\"mn-Mong-CN\",\"mna\":\"mna-Latn-ZZ\",\"mnf\":\"mnf-Latn-ZZ\",\"mni\":\"mni-Beng-IN\",\"mnw\":\"mnw-Mymr-MM\",\"moa\":\"moa-Latn-ZZ\",\"moe\":\"moe-Latn-CA\",\"moh\":\"moh-Latn-CA\",\"mos\":\"mos-Latn-BF\",\"mox\":\"mox-Latn-ZZ\",\"mpp\":\"mpp-Latn-ZZ\",\"mps\":\"mps-Latn-ZZ\",\"mpt\":\"mpt-Latn-ZZ\",\"mpx\":\"mpx-Latn-ZZ\",\"mql\":\"mql-Latn-ZZ\",\"mr\":\"mr-Deva-IN\",\"mrd\":\"mrd-Deva-NP\",\"mrj\":\"mrj-Cyrl-RU\",\"mro\":\"mro-Mroo-BD\",\"ms\":\"ms-Latn-MY\",\"ms-CC\":\"ms-Arab-CC\",\"ms-ID\":\"ms-Arab-ID\",\"mt\":\"mt-Latn-MT\",\"mtc\":\"mtc-Latn-ZZ\",\"mtf\":\"mtf-Latn-ZZ\",\"mti\":\"mti-Latn-ZZ\",\"mtr\":\"mtr-Deva-IN\",\"mua\":\"mua-Latn-CM\",\"mur\":\"mur-Latn-ZZ\",\"mus\":\"mus-Latn-US\",\"mva\":\"mva-Latn-ZZ\",\"mvn\":\"mvn-Latn-ZZ\",\"mvy\":\"mvy-Arab-PK\",\"mwk\":\"mwk-Latn-ML\",\"mwr\":\"mwr-Deva-IN\",\"mwv\":\"mwv-Latn-ID\",\"mxc\":\"mxc-Latn-ZW\",\"mxm\":\"mxm-Latn-ZZ\",\"my\":\"my-Mymr-MM\",\"myk\":\"myk-Latn-ZZ\",\"mym\":\"mym-Ethi-ZZ\",\"myv\":\"myv-Cyrl-RU\",\"myw\":\"myw-Latn-ZZ\",\"myx\":\"myx-Latn-UG\",\"myz\":\"myz-Mand-IR\",\"mzk\":\"mzk-Latn-ZZ\",\"mzm\":\"mzm-Latn-ZZ\",\"mzn\":\"mzn-Arab-IR\",\"mzp\":\"mzp-Latn-ZZ\",\"mzw\":\"mzw-Latn-ZZ\",\"mzz\":\"mzz-Latn-ZZ\",\"na\":\"na-Latn-NR\",\"nac\":\"nac-Latn-ZZ\",\"naf\":\"naf-Latn-ZZ\",\"nak\":\"nak-Latn-ZZ\",\"nan\":\"nan-Hans-CN\",\"nap\":\"nap-Latn-IT\",\"naq\":\"naq-Latn-NA\",\"nas\":\"nas-Latn-ZZ\",\"nb\":\"nb-Latn-NO\",\"nca\":\"nca-Latn-ZZ\",\"nce\":\"nce-Latn-ZZ\",\"ncf\":\"ncf-Latn-ZZ\",\"nch\":\"nch-Latn-MX\",\"nco\":\"nco-Latn-ZZ\",\"ncu\":\"ncu-Latn-ZZ\",\"nd\":\"nd-Latn-ZW\",\"ndc\":\"ndc-Latn-MZ\",\"nds\":\"nds-Latn-DE\",\"ne\":\"ne-Deva-NP\",\"neb\":\"neb-Latn-ZZ\",\"new\":\"new-Deva-NP\",\"nex\":\"nex-Latn-ZZ\",\"nfr\":\"nfr-Latn-ZZ\",\"ng\":\"ng-Latn-NA\",\"nga\":\"nga-Latn-ZZ\",\"ngb\":\"ngb-Latn-ZZ\",\"ngl\":\"ngl-Latn-MZ\",\"nhb\":\"nhb-Latn-ZZ\",\"nhe\":\"nhe-Latn-MX\",\"nhw\":\"nhw-Latn-MX\",\"nif\":\"nif-Latn-ZZ\",\"nii\":\"nii-Latn-ZZ\",\"nij\":\"nij-Latn-ID\",\"nin\":\"nin-Latn-ZZ\",\"niu\":\"niu-Latn-NU\",\"niy\":\"niy-Latn-ZZ\",\"niz\":\"niz-Latn-ZZ\",\"njo\":\"njo-Latn-IN\",\"nkg\":\"nkg-Latn-ZZ\",\"nko\":\"nko-Latn-ZZ\",\"nl\":\"nl-Latn-NL\",\"nmg\":\"nmg-Latn-CM\",\"nmz\":\"nmz-Latn-ZZ\",\"nn\":\"nn-Latn-NO\",\"nnf\":\"nnf-Latn-ZZ\",\"nnh\":\"nnh-Latn-CM\",\"nnk\":\"nnk-Latn-ZZ\",\"nnm\":\"nnm-Latn-ZZ\",\"no\":\"no-Latn-NO\",\"nod\":\"nod-Lana-TH\",\"noe\":\"noe-Deva-IN\",\"non\":\"non-Runr-SE\",\"nop\":\"nop-Latn-ZZ\",\"nou\":\"nou-Latn-ZZ\",\"nqo\":\"nqo-Nkoo-GN\",\"nr\":\"nr-Latn-ZA\",\"nrb\":\"nrb-Latn-ZZ\",\"nsk\":\"nsk-Cans-CA\",\"nsn\":\"nsn-Latn-ZZ\",\"nso\":\"nso-Latn-ZA\",\"nss\":\"nss-Latn-ZZ\",\"ntm\":\"ntm-Latn-ZZ\",\"ntr\":\"ntr-Latn-ZZ\",\"nui\":\"nui-Latn-ZZ\",\"nup\":\"nup-Latn-ZZ\",\"nus\":\"nus-Latn-SS\",\"nuv\":\"nuv-Latn-ZZ\",\"nux\":\"nux-Latn-ZZ\",\"nv\":\"nv-Latn-US\",\"nwb\":\"nwb-Latn-ZZ\",\"nxq\":\"nxq-Latn-CN\",\"nxr\":\"nxr-Latn-ZZ\",\"ny\":\"ny-Latn-MW\",\"nym\":\"nym-Latn-TZ\",\"nyn\":\"nyn-Latn-UG\",\"nzi\":\"nzi-Latn-GH\",\"oc\":\"oc-Latn-FR\",\"ogc\":\"ogc-Latn-ZZ\",\"okr\":\"okr-Latn-ZZ\",\"okv\":\"okv-Latn-ZZ\",\"om\":\"om-Latn-ET\",\"ong\":\"ong-Latn-ZZ\",\"onn\":\"onn-Latn-ZZ\",\"ons\":\"ons-Latn-ZZ\",\"opm\":\"opm-Latn-ZZ\",\"or\":\"or-Orya-IN\",\"oro\":\"oro-Latn-ZZ\",\"oru\":\"oru-Arab-ZZ\",\"os\":\"os-Cyrl-GE\",\"osa\":\"osa-Osge-US\",\"ota\":\"ota-Arab-ZZ\",\"otk\":\"otk-Orkh-MN\",\"ozm\":\"ozm-Latn-ZZ\",\"pa\":\"pa-Guru-IN\",\"pa-Arab\":\"pa-Arab-PK\",\"pa-PK\":\"pa-Arab-PK\",\"pag\":\"pag-Latn-PH\",\"pal\":\"pal-Phli-IR\",\"pal-Phlp\":\"pal-Phlp-CN\",\"pam\":\"pam-Latn-PH\",\"pap\":\"pap-Latn-AW\",\"pau\":\"pau-Latn-PW\",\"pbi\":\"pbi-Latn-ZZ\",\"pcd\":\"pcd-Latn-FR\",\"pcm\":\"pcm-Latn-NG\",\"pdc\":\"pdc-Latn-US\",\"pdt\":\"pdt-Latn-CA\",\"ped\":\"ped-Latn-ZZ\",\"peo\":\"peo-Xpeo-IR\",\"pex\":\"pex-Latn-ZZ\",\"pfl\":\"pfl-Latn-DE\",\"phl\":\"phl-Arab-ZZ\",\"phn\":\"phn-Phnx-LB\",\"pil\":\"pil-Latn-ZZ\",\"pip\":\"pip-Latn-ZZ\",\"pka\":\"pka-Brah-IN\",\"pko\":\"pko-Latn-KE\",\"pl\":\"pl-Latn-PL\",\"pla\":\"pla-Latn-ZZ\",\"pms\":\"pms-Latn-IT\",\"png\":\"png-Latn-ZZ\",\"pnn\":\"pnn-Latn-ZZ\",\"pnt\":\"pnt-Grek-GR\",\"pon\":\"pon-Latn-FM\",\"ppo\":\"ppo-Latn-ZZ\",\"pra\":\"pra-Khar-PK\",\"prd\":\"prd-Arab-IR\",\"prg\":\"prg-Latn-001\",\"ps\":\"ps-Arab-AF\",\"pss\":\"pss-Latn-ZZ\",\"pt\":\"pt-Latn-BR\",\"ptp\":\"ptp-Latn-ZZ\",\"puu\":\"puu-Latn-GA\",\"pwa\":\"pwa-Latn-ZZ\",\"qu\":\"qu-Latn-PE\",\"quc\":\"quc-Latn-GT\",\"qug\":\"qug-Latn-EC\",\"rai\":\"rai-Latn-ZZ\",\"raj\":\"raj-Deva-IN\",\"rao\":\"rao-Latn-ZZ\",\"rcf\":\"rcf-Latn-RE\",\"rej\":\"rej-Latn-ID\",\"rel\":\"rel-Latn-ZZ\",\"res\":\"res-Latn-ZZ\",\"rgn\":\"rgn-Latn-IT\",\"rhg\":\"rhg-Arab-ZZ\",\"ria\":\"ria-Latn-IN\",\"rif\":\"rif-Tfng-MA\",\"rif-NL\":\"rif-Latn-NL\",\"rjs\":\"rjs-Deva-NP\",\"rkt\":\"rkt-Beng-BD\",\"rm\":\"rm-Latn-CH\",\"rmf\":\"rmf-Latn-FI\",\"rmo\":\"rmo-Latn-CH\",\"rmt\":\"rmt-Arab-IR\",\"rmu\":\"rmu-Latn-SE\",\"rn\":\"rn-Latn-BI\",\"rna\":\"rna-Latn-ZZ\",\"rng\":\"rng-Latn-MZ\",\"ro\":\"ro-Latn-RO\",\"rob\":\"rob-Latn-ID\",\"rof\":\"rof-Latn-TZ\",\"roo\":\"roo-Latn-ZZ\",\"rro\":\"rro-Latn-ZZ\",\"rtm\":\"rtm-Latn-FJ\",\"ru\":\"ru-Cyrl-RU\",\"rue\":\"rue-Cyrl-UA\",\"rug\":\"rug-Latn-SB\",\"rw\":\"rw-Latn-RW\",\"rwk\":\"rwk-Latn-TZ\",\"rwo\":\"rwo-Latn-ZZ\",\"ryu\":\"ryu-Kana-JP\",\"sa\":\"sa-Deva-IN\",\"saf\":\"saf-Latn-GH\",\"sah\":\"sah-Cyrl-RU\",\"saq\":\"saq-Latn-KE\",\"sas\":\"sas-Latn-ID\",\"sat\":\"sat-Latn-IN\",\"sav\":\"sav-Latn-SN\",\"saz\":\"saz-Saur-IN\",\"sba\":\"sba-Latn-ZZ\",\"sbe\":\"sbe-Latn-ZZ\",\"sbp\":\"sbp-Latn-TZ\",\"sc\":\"sc-Latn-IT\",\"sck\":\"sck-Deva-IN\",\"scl\":\"scl-Arab-ZZ\",\"scn\":\"scn-Latn-IT\",\"sco\":\"sco-Latn-GB\",\"scs\":\"scs-Latn-CA\",\"sd\":\"sd-Arab-PK\",\"sd-Deva\":\"sd-Deva-IN\",\"sd-Khoj\":\"sd-Khoj-IN\",\"sd-Sind\":\"sd-Sind-IN\",\"sdc\":\"sdc-Latn-IT\",\"sdh\":\"sdh-Arab-IR\",\"se\":\"se-Latn-NO\",\"sef\":\"sef-Latn-CI\",\"seh\":\"seh-Latn-MZ\",\"sei\":\"sei-Latn-MX\",\"ses\":\"ses-Latn-ML\",\"sg\":\"sg-Latn-CF\",\"sga\":\"sga-Ogam-IE\",\"sgs\":\"sgs-Latn-LT\",\"sgw\":\"sgw-Ethi-ZZ\",\"sgz\":\"sgz-Latn-ZZ\",\"shi\":\"shi-Tfng-MA\",\"shk\":\"shk-Latn-ZZ\",\"shn\":\"shn-Mymr-MM\",\"shu\":\"shu-Arab-ZZ\",\"si\":\"si-Sinh-LK\",\"sid\":\"sid-Latn-ET\",\"sig\":\"sig-Latn-ZZ\",\"sil\":\"sil-Latn-ZZ\",\"sim\":\"sim-Latn-ZZ\",\"sjr\":\"sjr-Latn-ZZ\",\"sk\":\"sk-Latn-SK\",\"skc\":\"skc-Latn-ZZ\",\"skr\":\"skr-Arab-PK\",\"sks\":\"sks-Latn-ZZ\",\"sl\":\"sl-Latn-SI\",\"sld\":\"sld-Latn-ZZ\",\"sli\":\"sli-Latn-PL\",\"sll\":\"sll-Latn-ZZ\",\"sly\":\"sly-Latn-ID\",\"sm\":\"sm-Latn-WS\",\"sma\":\"sma-Latn-SE\",\"smj\":\"smj-Latn-SE\",\"smn\":\"smn-Latn-FI\",\"smp\":\"smp-Samr-IL\",\"smq\":\"smq-Latn-ZZ\",\"sms\":\"sms-Latn-FI\",\"sn\":\"sn-Latn-ZW\",\"snc\":\"snc-Latn-ZZ\",\"snk\":\"snk-Latn-ML\",\"snp\":\"snp-Latn-ZZ\",\"snx\":\"snx-Latn-ZZ\",\"sny\":\"sny-Latn-ZZ\",\"so\":\"so-Latn-SO\",\"sok\":\"sok-Latn-ZZ\",\"soq\":\"soq-Latn-ZZ\",\"sou\":\"sou-Thai-TH\",\"soy\":\"soy-Latn-ZZ\",\"spd\":\"spd-Latn-ZZ\",\"spl\":\"spl-Latn-ZZ\",\"sps\":\"sps-Latn-ZZ\",\"sq\":\"sq-Latn-AL\",\"sr\":\"sr-Cyrl-RS\",\"sr-ME\":\"sr-Latn-ME\",\"sr-RO\":\"sr-Latn-RO\",\"sr-RU\":\"sr-Latn-RU\",\"sr-TR\":\"sr-Latn-TR\",\"srb\":\"srb-Sora-IN\",\"srn\":\"srn-Latn-SR\",\"srr\":\"srr-Latn-SN\",\"srx\":\"srx-Deva-IN\",\"ss\":\"ss-Latn-ZA\",\"ssd\":\"ssd-Latn-ZZ\",\"ssg\":\"ssg-Latn-ZZ\",\"ssy\":\"ssy-Latn-ER\",\"st\":\"st-Latn-ZA\",\"stk\":\"stk-Latn-ZZ\",\"stq\":\"stq-Latn-DE\",\"su\":\"su-Latn-ID\",\"sua\":\"sua-Latn-ZZ\",\"sue\":\"sue-Latn-ZZ\",\"suk\":\"suk-Latn-TZ\",\"sur\":\"sur-Latn-ZZ\",\"sus\":\"sus-Latn-GN\",\"sv\":\"sv-Latn-SE\",\"sw\":\"sw-Latn-TZ\",\"swb\":\"swb-Arab-YT\",\"swc\":\"swc-Latn-CD\",\"swg\":\"swg-Latn-DE\",\"swp\":\"swp-Latn-ZZ\",\"swv\":\"swv-Deva-IN\",\"sxn\":\"sxn-Latn-ID\",\"sxw\":\"sxw-Latn-ZZ\",\"syl\":\"syl-Beng-BD\",\"syr\":\"syr-Syrc-IQ\",\"szl\":\"szl-Latn-PL\",\"ta\":\"ta-Taml-IN\",\"taj\":\"taj-Deva-NP\",\"tal\":\"tal-Latn-ZZ\",\"tan\":\"tan-Latn-ZZ\",\"taq\":\"taq-Latn-ZZ\",\"tbc\":\"tbc-Latn-ZZ\",\"tbd\":\"tbd-Latn-ZZ\",\"tbf\":\"tbf-Latn-ZZ\",\"tbg\":\"tbg-Latn-ZZ\",\"tbo\":\"tbo-Latn-ZZ\",\"tbw\":\"tbw-Latn-PH\",\"tbz\":\"tbz-Latn-ZZ\",\"tci\":\"tci-Latn-ZZ\",\"tcy\":\"tcy-Knda-IN\",\"tdd\":\"tdd-Tale-CN\",\"tdg\":\"tdg-Deva-NP\",\"tdh\":\"tdh-Deva-NP\",\"te\":\"te-Telu-IN\",\"ted\":\"ted-Latn-ZZ\",\"tem\":\"tem-Latn-SL\",\"teo\":\"teo-Latn-UG\",\"tet\":\"tet-Latn-TL\",\"tfi\":\"tfi-Latn-ZZ\",\"tg\":\"tg-Cyrl-TJ\",\"tg-Arab\":\"tg-Arab-PK\",\"tg-PK\":\"tg-Arab-PK\",\"tgc\":\"tgc-Latn-ZZ\",\"tgo\":\"tgo-Latn-ZZ\",\"tgu\":\"tgu-Latn-ZZ\",\"th\":\"th-Thai-TH\",\"thl\":\"thl-Deva-NP\",\"thq\":\"thq-Deva-NP\",\"thr\":\"thr-Deva-NP\",\"ti\":\"ti-Ethi-ET\",\"tif\":\"tif-Latn-ZZ\",\"tig\":\"tig-Ethi-ER\",\"tik\":\"tik-Latn-ZZ\",\"tim\":\"tim-Latn-ZZ\",\"tio\":\"tio-Latn-ZZ\",\"tiv\":\"tiv-Latn-NG\",\"tk\":\"tk-Latn-TM\",\"tkl\":\"tkl-Latn-TK\",\"tkr\":\"tkr-Latn-AZ\",\"tkt\":\"tkt-Deva-NP\",\"tl\":\"tl-Latn-PH\",\"tlf\":\"tlf-Latn-ZZ\",\"tlx\":\"tlx-Latn-ZZ\",\"tly\":\"tly-Latn-AZ\",\"tmh\":\"tmh-Latn-NE\",\"tmy\":\"tmy-Latn-ZZ\",\"tn\":\"tn-Latn-ZA\",\"tnh\":\"tnh-Latn-ZZ\",\"to\":\"to-Latn-TO\",\"tof\":\"tof-Latn-ZZ\",\"tog\":\"tog-Latn-MW\",\"toq\":\"toq-Latn-ZZ\",\"tpi\":\"tpi-Latn-PG\",\"tpm\":\"tpm-Latn-ZZ\",\"tpz\":\"tpz-Latn-ZZ\",\"tqo\":\"tqo-Latn-ZZ\",\"tr\":\"tr-Latn-TR\",\"tru\":\"tru-Latn-TR\",\"trv\":\"trv-Latn-TW\",\"trw\":\"trw-Arab-ZZ\",\"ts\":\"ts-Latn-ZA\",\"tsd\":\"tsd-Grek-GR\",\"tsf\":\"tsf-Deva-NP\",\"tsg\":\"tsg-Latn-PH\",\"tsj\":\"tsj-Tibt-BT\",\"tsw\":\"tsw-Latn-ZZ\",\"tt\":\"tt-Cyrl-RU\",\"ttd\":\"ttd-Latn-ZZ\",\"tte\":\"tte-Latn-ZZ\",\"ttj\":\"ttj-Latn-UG\",\"ttr\":\"ttr-Latn-ZZ\",\"tts\":\"tts-Thai-TH\",\"ttt\":\"ttt-Latn-AZ\",\"tuh\":\"tuh-Latn-ZZ\",\"tul\":\"tul-Latn-ZZ\",\"tum\":\"tum-Latn-MW\",\"tuq\":\"tuq-Latn-ZZ\",\"tvd\":\"tvd-Latn-ZZ\",\"tvl\":\"tvl-Latn-TV\",\"tvu\":\"tvu-Latn-ZZ\",\"twh\":\"twh-Latn-ZZ\",\"twq\":\"twq-Latn-NE\",\"txg\":\"txg-Tang-CN\",\"ty\":\"ty-Latn-PF\",\"tya\":\"tya-Latn-ZZ\",\"tyv\":\"tyv-Cyrl-RU\",\"tzm\":\"tzm-Latn-MA\",\"ubu\":\"ubu-Latn-ZZ\",\"udm\":\"udm-Cyrl-RU\",\"ug\":\"ug-Arab-CN\",\"ug-Cyrl\":\"ug-Cyrl-KZ\",\"ug-KZ\":\"ug-Cyrl-KZ\",\"ug-MN\":\"ug-Cyrl-MN\",\"uga\":\"uga-Ugar-SY\",\"uk\":\"uk-Cyrl-UA\",\"uli\":\"uli-Latn-FM\",\"umb\":\"umb-Latn-AO\",\"und\":\"en-Latn-US\",\"und-002\":\"en-Latn-NG\",\"und-003\":\"en-Latn-US\",\"und-005\":\"pt-Latn-BR\",\"und-009\":\"en-Latn-AU\",\"und-011\":\"en-Latn-NG\",\"und-013\":\"es-Latn-MX\",\"und-014\":\"sw-Latn-TZ\",\"und-015\":\"ar-Arab-EG\",\"und-017\":\"sw-Latn-CD\",\"und-018\":\"en-Latn-ZA\",\"und-019\":\"en-Latn-US\",\"und-021\":\"en-Latn-US\",\"und-029\":\"es-Latn-CU\",\"und-030\":\"zh-Hans-CN\",\"und-034\":\"hi-Deva-IN\",\"und-035\":\"id-Latn-ID\",\"und-039\":\"it-Latn-IT\",\"und-053\":\"en-Latn-AU\",\"und-054\":\"en-Latn-PG\",\"und-057\":\"en-Latn-GU\",\"und-061\":\"sm-Latn-WS\",\"und-142\":\"zh-Hans-CN\",\"und-143\":\"uz-Latn-UZ\",\"und-145\":\"ar-Arab-SA\",\"und-150\":\"ru-Cyrl-RU\",\"und-151\":\"ru-Cyrl-RU\",\"und-154\":\"en-Latn-GB\",\"und-155\":\"de-Latn-DE\",\"und-202\":\"en-Latn-NG\",\"und-419\":\"es-Latn-419\",\"und-AD\":\"ca-Latn-AD\",\"und-Adlm\":\"ff-Adlm-GN\",\"und-AE\":\"ar-Arab-AE\",\"und-AF\":\"fa-Arab-AF\",\"und-Aghb\":\"lez-Aghb-RU\",\"und-Ahom\":\"aho-Ahom-IN\",\"und-AL\":\"sq-Latn-AL\",\"und-AM\":\"hy-Armn-AM\",\"und-AO\":\"pt-Latn-AO\",\"und-AQ\":\"und-Latn-AQ\",\"und-AR\":\"es-Latn-AR\",\"und-Arab\":\"ar-Arab-EG\",\"und-Arab-CC\":\"ms-Arab-CC\",\"und-Arab-CN\":\"ug-Arab-CN\",\"und-Arab-GB\":\"ks-Arab-GB\",\"und-Arab-ID\":\"ms-Arab-ID\",\"und-Arab-IN\":\"ur-Arab-IN\",\"und-Arab-KH\":\"cja-Arab-KH\",\"und-Arab-MN\":\"kk-Arab-MN\",\"und-Arab-MU\":\"ur-Arab-MU\",\"und-Arab-NG\":\"ha-Arab-NG\",\"und-Arab-PK\":\"ur-Arab-PK\",\"und-Arab-TG\":\"apd-Arab-TG\",\"und-Arab-TH\":\"mfa-Arab-TH\",\"und-Arab-TJ\":\"fa-Arab-TJ\",\"und-Arab-TR\":\"az-Arab-TR\",\"und-Arab-YT\":\"swb-Arab-YT\",\"und-Armi\":\"arc-Armi-IR\",\"und-Armn\":\"hy-Armn-AM\",\"und-AS\":\"sm-Latn-AS\",\"und-AT\":\"de-Latn-AT\",\"und-Avst\":\"ae-Avst-IR\",\"und-AW\":\"nl-Latn-AW\",\"und-AX\":\"sv-Latn-AX\",\"und-AZ\":\"az-Latn-AZ\",\"und-BA\":\"bs-Latn-BA\",\"und-Bali\":\"ban-Bali-ID\",\"und-Bamu\":\"bax-Bamu-CM\",\"und-Bass\":\"bsq-Bass-LR\",\"und-Batk\":\"bbc-Batk-ID\",\"und-BD\":\"bn-Beng-BD\",\"und-BE\":\"nl-Latn-BE\",\"und-Beng\":\"bn-Beng-BD\",\"und-BF\":\"fr-Latn-BF\",\"und-BG\":\"bg-Cyrl-BG\",\"und-BH\":\"ar-Arab-BH\",\"und-Bhks\":\"sa-Bhks-IN\",\"und-BI\":\"rn-Latn-BI\",\"und-BJ\":\"fr-Latn-BJ\",\"und-BL\":\"fr-Latn-BL\",\"und-BN\":\"ms-Latn-BN\",\"und-BO\":\"es-Latn-BO\",\"und-Bopo\":\"zh-Bopo-TW\",\"und-BQ\":\"pap-Latn-BQ\",\"und-BR\":\"pt-Latn-BR\",\"und-Brah\":\"pka-Brah-IN\",\"und-Brai\":\"fr-Brai-FR\",\"und-BT\":\"dz-Tibt-BT\",\"und-Bugi\":\"bug-Bugi-ID\",\"und-Buhd\":\"bku-Buhd-PH\",\"und-BV\":\"und-Latn-BV\",\"und-BY\":\"be-Cyrl-BY\",\"und-Cakm\":\"ccp-Cakm-BD\",\"und-Cans\":\"cr-Cans-CA\",\"und-Cari\":\"xcr-Cari-TR\",\"und-CD\":\"sw-Latn-CD\",\"und-CF\":\"fr-Latn-CF\",\"und-CG\":\"fr-Latn-CG\",\"und-CH\":\"de-Latn-CH\",\"und-Cham\":\"cjm-Cham-VN\",\"und-Cher\":\"chr-Cher-US\",\"und-CI\":\"fr-Latn-CI\",\"und-CL\":\"es-Latn-CL\",\"und-CM\":\"fr-Latn-CM\",\"und-CN\":\"zh-Hans-CN\",\"und-CO\":\"es-Latn-CO\",\"und-Copt\":\"cop-Copt-EG\",\"und-CP\":\"und-Latn-CP\",\"und-Cprt\":\"grc-Cprt-CY\",\"und-CR\":\"es-Latn-CR\",\"und-CU\":\"es-Latn-CU\",\"und-CV\":\"pt-Latn-CV\",\"und-CW\":\"pap-Latn-CW\",\"und-CY\":\"el-Grek-CY\",\"und-Cyrl\":\"ru-Cyrl-RU\",\"und-Cyrl-AL\":\"mk-Cyrl-AL\",\"und-Cyrl-BA\":\"sr-Cyrl-BA\",\"und-Cyrl-GE\":\"ab-Cyrl-GE\",\"und-Cyrl-GR\":\"mk-Cyrl-GR\",\"und-Cyrl-MD\":\"uk-Cyrl-MD\",\"und-Cyrl-RO\":\"bg-Cyrl-RO\",\"und-Cyrl-SK\":\"uk-Cyrl-SK\",\"und-Cyrl-TR\":\"kbd-Cyrl-TR\",\"und-Cyrl-XK\":\"sr-Cyrl-XK\",\"und-CZ\":\"cs-Latn-CZ\",\"und-DE\":\"de-Latn-DE\",\"und-Deva\":\"hi-Deva-IN\",\"und-Deva-BT\":\"ne-Deva-BT\",\"und-Deva-FJ\":\"hif-Deva-FJ\",\"und-Deva-MU\":\"bho-Deva-MU\",\"und-Deva-PK\":\"btv-Deva-PK\",\"und-DJ\":\"aa-Latn-DJ\",\"und-DK\":\"da-Latn-DK\",\"und-DO\":\"es-Latn-DO\",\"und-Dupl\":\"fr-Dupl-FR\",\"und-DZ\":\"ar-Arab-DZ\",\"und-EA\":\"es-Latn-EA\",\"und-EC\":\"es-Latn-EC\",\"und-EE\":\"et-Latn-EE\",\"und-EG\":\"ar-Arab-EG\",\"und-Egyp\":\"egy-Egyp-EG\",\"und-EH\":\"ar-Arab-EH\",\"und-Elba\":\"sq-Elba-AL\",\"und-ER\":\"ti-Ethi-ER\",\"und-ES\":\"es-Latn-ES\",\"und-ET\":\"am-Ethi-ET\",\"und-Ethi\":\"am-Ethi-ET\",\"und-EU\":\"en-Latn-GB\",\"und-EZ\":\"de-Latn-EZ\",\"und-FI\":\"fi-Latn-FI\",\"und-FO\":\"fo-Latn-FO\",\"und-FR\":\"fr-Latn-FR\",\"und-GA\":\"fr-Latn-GA\",\"und-GE\":\"ka-Geor-GE\",\"und-Geor\":\"ka-Geor-GE\",\"und-GF\":\"fr-Latn-GF\",\"und-GH\":\"ak-Latn-GH\",\"und-GL\":\"kl-Latn-GL\",\"und-Glag\":\"cu-Glag-BG\",\"und-GN\":\"fr-Latn-GN\",\"und-Gonm\":\"gon-Gonm-IN\",\"und-Goth\":\"got-Goth-UA\",\"und-GP\":\"fr-Latn-GP\",\"und-GQ\":\"es-Latn-GQ\",\"und-GR\":\"el-Grek-GR\",\"und-Gran\":\"sa-Gran-IN\",\"und-Grek\":\"el-Grek-GR\",\"und-Grek-TR\":\"bgx-Grek-TR\",\"und-GS\":\"und-Latn-GS\",\"und-GT\":\"es-Latn-GT\",\"und-Gujr\":\"gu-Gujr-IN\",\"und-Guru\":\"pa-Guru-IN\",\"und-GW\":\"pt-Latn-GW\",\"und-Hanb\":\"zh-Hanb-TW\",\"und-Hang\":\"ko-Hang-KR\",\"und-Hani\":\"zh-Hani-CN\",\"und-Hano\":\"hnn-Hano-PH\",\"und-Hans\":\"zh-Hans-CN\",\"und-Hant\":\"zh-Hant-TW\",\"und-Hatr\":\"mis-Hatr-IQ\",\"und-Hebr\":\"he-Hebr-IL\",\"und-Hebr-CA\":\"yi-Hebr-CA\",\"und-Hebr-GB\":\"yi-Hebr-GB\",\"und-Hebr-SE\":\"yi-Hebr-SE\",\"und-Hebr-UA\":\"yi-Hebr-UA\",\"und-Hebr-US\":\"yi-Hebr-US\",\"und-Hira\":\"ja-Hira-JP\",\"und-HK\":\"zh-Hant-HK\",\"und-Hluw\":\"hlu-Hluw-TR\",\"und-HM\":\"und-Latn-HM\",\"und-Hmng\":\"hnj-Hmng-LA\",\"und-HN\":\"es-Latn-HN\",\"und-HR\":\"hr-Latn-HR\",\"und-HT\":\"ht-Latn-HT\",\"und-HU\":\"hu-Latn-HU\",\"und-Hung\":\"hu-Hung-HU\",\"und-IC\":\"es-Latn-IC\",\"und-ID\":\"id-Latn-ID\",\"und-IL\":\"he-Hebr-IL\",\"und-IN\":\"hi-Deva-IN\",\"und-IQ\":\"ar-Arab-IQ\",\"und-IR\":\"fa-Arab-IR\",\"und-IS\":\"is-Latn-IS\",\"und-IT\":\"it-Latn-IT\",\"und-Ital\":\"ett-Ital-IT\",\"und-Jamo\":\"ko-Jamo-KR\",\"und-Java\":\"jv-Java-ID\",\"und-JO\":\"ar-Arab-JO\",\"und-JP\":\"ja-Jpan-JP\",\"und-Jpan\":\"ja-Jpan-JP\",\"und-Kali\":\"eky-Kali-MM\",\"und-Kana\":\"ja-Kana-JP\",\"und-KE\":\"sw-Latn-KE\",\"und-KG\":\"ky-Cyrl-KG\",\"und-KH\":\"km-Khmr-KH\",\"und-Khar\":\"pra-Khar-PK\",\"und-Khmr\":\"km-Khmr-KH\",\"und-Khoj\":\"sd-Khoj-IN\",\"und-KM\":\"ar-Arab-KM\",\"und-Knda\":\"kn-Knda-IN\",\"und-Kore\":\"ko-Kore-KR\",\"und-KP\":\"ko-Kore-KP\",\"und-KR\":\"ko-Kore-KR\",\"und-Kthi\":\"bho-Kthi-IN\",\"und-KW\":\"ar-Arab-KW\",\"und-KZ\":\"ru-Cyrl-KZ\",\"und-LA\":\"lo-Laoo-LA\",\"und-Lana\":\"nod-Lana-TH\",\"und-Laoo\":\"lo-Laoo-LA\",\"und-Latn-AF\":\"tk-Latn-AF\",\"und-Latn-AM\":\"ku-Latn-AM\",\"und-Latn-CN\":\"za-Latn-CN\",\"und-Latn-CY\":\"tr-Latn-CY\",\"und-Latn-DZ\":\"fr-Latn-DZ\",\"und-Latn-ET\":\"en-Latn-ET\",\"und-Latn-GE\":\"ku-Latn-GE\",\"und-Latn-IR\":\"tk-Latn-IR\",\"und-Latn-KM\":\"fr-Latn-KM\",\"und-Latn-MA\":\"fr-Latn-MA\",\"und-Latn-MK\":\"sq-Latn-MK\",\"und-Latn-MM\":\"kac-Latn-MM\",\"und-Latn-MO\":\"pt-Latn-MO\",\"und-Latn-MR\":\"fr-Latn-MR\",\"und-Latn-RU\":\"krl-Latn-RU\",\"und-Latn-SY\":\"fr-Latn-SY\",\"und-Latn-TN\":\"fr-Latn-TN\",\"und-Latn-TW\":\"trv-Latn-TW\",\"und-Latn-UA\":\"pl-Latn-UA\",\"und-LB\":\"ar-Arab-LB\",\"und-Lepc\":\"lep-Lepc-IN\",\"und-LI\":\"de-Latn-LI\",\"und-Limb\":\"lif-Limb-IN\",\"und-Lina\":\"lab-Lina-GR\",\"und-Linb\":\"grc-Linb-GR\",\"und-Lisu\":\"lis-Lisu-CN\",\"und-LK\":\"si-Sinh-LK\",\"und-LS\":\"st-Latn-LS\",\"und-LT\":\"lt-Latn-LT\",\"und-LU\":\"fr-Latn-LU\",\"und-LV\":\"lv-Latn-LV\",\"und-LY\":\"ar-Arab-LY\",\"und-Lyci\":\"xlc-Lyci-TR\",\"und-Lydi\":\"xld-Lydi-TR\",\"und-MA\":\"ar-Arab-MA\",\"und-Mahj\":\"hi-Mahj-IN\",\"und-Mand\":\"myz-Mand-IR\",\"und-Mani\":\"xmn-Mani-CN\",\"und-Marc\":\"bo-Marc-CN\",\"und-MC\":\"fr-Latn-MC\",\"und-MD\":\"ro-Latn-MD\",\"und-ME\":\"sr-Latn-ME\",\"und-Mend\":\"men-Mend-SL\",\"und-Merc\":\"xmr-Merc-SD\",\"und-Mero\":\"xmr-Mero-SD\",\"und-MF\":\"fr-Latn-MF\",\"und-MG\":\"mg-Latn-MG\",\"und-MK\":\"mk-Cyrl-MK\",\"und-ML\":\"bm-Latn-ML\",\"und-Mlym\":\"ml-Mlym-IN\",\"und-MM\":\"my-Mymr-MM\",\"und-MN\":\"mn-Cyrl-MN\",\"und-MO\":\"zh-Hant-MO\",\"und-Modi\":\"mr-Modi-IN\",\"und-Mong\":\"mn-Mong-CN\",\"und-MQ\":\"fr-Latn-MQ\",\"und-MR\":\"ar-Arab-MR\",\"und-Mroo\":\"mro-Mroo-BD\",\"und-MT\":\"mt-Latn-MT\",\"und-Mtei\":\"mni-Mtei-IN\",\"und-MU\":\"mfe-Latn-MU\",\"und-Mult\":\"skr-Mult-PK\",\"und-MV\":\"dv-Thaa-MV\",\"und-MX\":\"es-Latn-MX\",\"und-MY\":\"ms-Latn-MY\",\"und-Mymr\":\"my-Mymr-MM\",\"und-Mymr-IN\":\"kht-Mymr-IN\",\"und-Mymr-TH\":\"mnw-Mymr-TH\",\"und-MZ\":\"pt-Latn-MZ\",\"und-NA\":\"af-Latn-NA\",\"und-Narb\":\"xna-Narb-SA\",\"und-Nbat\":\"arc-Nbat-JO\",\"und-NC\":\"fr-Latn-NC\",\"und-NE\":\"ha-Latn-NE\",\"und-Newa\":\"new-Newa-NP\",\"und-NI\":\"es-Latn-NI\",\"und-Nkoo\":\"man-Nkoo-GN\",\"und-NL\":\"nl-Latn-NL\",\"und-NO\":\"nb-Latn-NO\",\"und-NP\":\"ne-Deva-NP\",\"und-Nshu\":\"zhx-Nshu-CN\",\"und-Ogam\":\"sga-Ogam-IE\",\"und-Olck\":\"sat-Olck-IN\",\"und-OM\":\"ar-Arab-OM\",\"und-Orkh\":\"otk-Orkh-MN\",\"und-Orya\":\"or-Orya-IN\",\"und-Osge\":\"osa-Osge-US\",\"und-Osma\":\"so-Osma-SO\",\"und-PA\":\"es-Latn-PA\",\"und-Palm\":\"arc-Palm-SY\",\"und-Pauc\":\"ctd-Pauc-MM\",\"und-PE\":\"es-Latn-PE\",\"und-Perm\":\"kv-Perm-RU\",\"und-PF\":\"fr-Latn-PF\",\"und-PG\":\"tpi-Latn-PG\",\"und-PH\":\"fil-Latn-PH\",\"und-Phag\":\"lzh-Phag-CN\",\"und-Phli\":\"pal-Phli-IR\",\"und-Phlp\":\"pal-Phlp-CN\",\"und-Phnx\":\"phn-Phnx-LB\",\"und-PK\":\"ur-Arab-PK\",\"und-PL\":\"pl-Latn-PL\",\"und-Plrd\":\"hmd-Plrd-CN\",\"und-PM\":\"fr-Latn-PM\",\"und-PR\":\"es-Latn-PR\",\"und-Prti\":\"xpr-Prti-IR\",\"und-PS\":\"ar-Arab-PS\",\"und-PT\":\"pt-Latn-PT\",\"und-PW\":\"pau-Latn-PW\",\"und-PY\":\"gn-Latn-PY\",\"und-QA\":\"ar-Arab-QA\",\"und-QO\":\"en-Latn-IO\",\"und-RE\":\"fr-Latn-RE\",\"und-Rjng\":\"rej-Rjng-ID\",\"und-RO\":\"ro-Latn-RO\",\"und-RS\":\"sr-Cyrl-RS\",\"und-RU\":\"ru-Cyrl-RU\",\"und-Runr\":\"non-Runr-SE\",\"und-RW\":\"rw-Latn-RW\",\"und-SA\":\"ar-Arab-SA\",\"und-Samr\":\"smp-Samr-IL\",\"und-Sarb\":\"xsa-Sarb-YE\",\"und-Saur\":\"saz-Saur-IN\",\"und-SC\":\"fr-Latn-SC\",\"und-SD\":\"ar-Arab-SD\",\"und-SE\":\"sv-Latn-SE\",\"und-Sgnw\":\"ase-Sgnw-US\",\"und-Shaw\":\"en-Shaw-GB\",\"und-Shrd\":\"sa-Shrd-IN\",\"und-SI\":\"sl-Latn-SI\",\"und-Sidd\":\"sa-Sidd-IN\",\"und-Sind\":\"sd-Sind-IN\",\"und-Sinh\":\"si-Sinh-LK\",\"und-SJ\":\"nb-Latn-SJ\",\"und-SK\":\"sk-Latn-SK\",\"und-SM\":\"it-Latn-SM\",\"und-SN\":\"fr-Latn-SN\",\"und-SO\":\"so-Latn-SO\",\"und-Sora\":\"srb-Sora-IN\",\"und-Soyo\":\"cmg-Soyo-MN\",\"und-SR\":\"nl-Latn-SR\",\"und-ST\":\"pt-Latn-ST\",\"und-Sund\":\"su-Sund-ID\",\"und-SV\":\"es-Latn-SV\",\"und-SY\":\"ar-Arab-SY\",\"und-Sylo\":\"syl-Sylo-BD\",\"und-Syrc\":\"syr-Syrc-IQ\",\"und-Tagb\":\"tbw-Tagb-PH\",\"und-Takr\":\"doi-Takr-IN\",\"und-Tale\":\"tdd-Tale-CN\",\"un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tn-TR\"},\"timeData\":{\"AX\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"BQ\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"CP\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"CZ\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"DK\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"FI\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"ID\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"IS\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"ML\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"NE\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"RU\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"SE\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"SJ\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"SK\":{\"_allowed\":\"H\",\"_preferred\":\"H\"},\"AS\":{\"_allowed\":\"h 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4\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 02:00:00\",\n    \"mwh\": 2\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 02:00:00\",\n    \"mwh\": 2.23\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 02:00:00\",\n    \"mwh\": 1\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 02:00:00\",\n    \"mwh\": 1.68\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 02:00:00\",\n    \"mwh\": 7.48\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 02:00:00\",\n    \"mwh\": 7.98\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 02:00:00\",\n    \"mwh\": 2.02\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 12.31\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 0.81\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 4.09\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 2.11\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 2.23\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 0.5\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 1.59\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 7.82\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 8.1\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 03:00:00\",\n    \"mwh\": 2.03\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 14.71\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 0.79\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 3.98\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 3.04\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 0.24\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 1.68\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 6.39\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 7.56\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 04:00:00\",\n    \"mwh\": 2.03\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 14.96\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 0.76\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 4.05\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 3.09\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 0.08\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 3.08\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 6.4\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 7.82\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 05:00:00\",\n    \"mwh\": 0.52\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 17.38\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 1.01\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 4.78\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 3.88\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 2.25\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 2.03\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 4.96\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 7.99\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 06:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 19.22\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 0.53\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 1\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 5.48\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 4.29\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 2.26\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 0.16\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 1.8\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 14.48\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 07:00:00\",\n    \"mwh\": 3.38\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 17.73\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 0.6\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 0.83\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 5.5\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 4.14\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 2.27\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 0.68\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 22.93\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 08:00:00\",\n    \"mwh\": 4.16\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 16.38\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 0.84\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 5.49\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 3.85\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 2.27\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 0.11\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 0.48\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 24.87\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 09:00:00\",\n    \"mwh\": 4.81\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 16.89\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 0.83\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 5.63\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 3.96\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 2.27\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 26.03\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 10:00:00\",\n    \"mwh\": 5.03\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 16.84\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 1.08\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 5.61\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 3.95\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 2.27\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 0.16\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 26.18\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 11:00:00\",\n    \"mwh\": 5.36\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 17.52\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 0.83\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 5.46\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 3.82\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 2.27\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 0.17\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 0.11\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 25.01\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 12:00:00\",\n    \"mwh\": 5.85\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 17.58\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 0.84\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 5.43\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 3.8\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 2.27\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 0.37\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 0.42\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 24.74\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 13:00:00\",\n    \"mwh\": 6.17\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 17.08\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 0.13\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 1.05\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 5.3\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 3.69\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 2.27\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 1.52\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 1.12\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 23.73\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 14:00:00\",\n    \"mwh\": 5.41\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 15.1\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 1.17\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 0.84\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 5.27\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 3.19\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 2.26\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 0.18\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 2.2\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 3.51\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 23.29\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 15:00:00\",\n    \"mwh\": 4.04\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 16.03\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 2.03\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 0.83\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 5.28\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 2.97\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 2.26\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 0.32\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 2.7\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 5.68\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 19.57\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 16:00:00\",\n    \"mwh\": 2.97\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 14.24\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 1.11\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 0.81\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 4.51\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 3.08\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 2.27\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 0.45\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 4.19\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 10.49\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 20.38\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 17:00:00\",\n    \"mwh\": 2.81\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 13.23\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 0.31\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 0.91\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 4.25\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 2.87\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 2.26\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 0.51\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 4.85\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 15.65\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 16.03\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 18:00:00\",\n    \"mwh\": 2.53\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 12.87\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 0.12\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 0.98\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 4.16\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 2.79\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 2.26\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 0.37\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 3.94\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 18.03\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 11.7\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 19:00:00\",\n    \"mwh\": 2.98\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 13.03\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 1.07\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 0.89\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 4.21\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 2.82\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 0.08\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 3.88\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 16.62\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 11.86\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 20:00:00\",\n    \"mwh\": 2.9\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 12.82\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 0.92\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 4.14\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 2.83\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 0.24\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 5.18\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 15.75\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 11.17\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 21:00:00\",\n    \"mwh\": 1.97\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 12.89\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 1.06\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 4.02\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 2.94\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 2.26\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 0.63\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 4.67\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 18.04\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 6.52\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 22:00:00\",\n    \"mwh\": 2.02\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 11.77\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 0.92\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 3.65\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 2.69\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 0.65\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 4.37\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 17.37\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 5.97\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-15 23:00:00\",\n    \"mwh\": 2.26\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 7.66\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 1.24\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 0.83\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 3.86\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 2.71\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 2.22\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 0.64\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 4.27\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 18.64\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 5.22\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 00:00:00\",\n    \"mwh\": 1.94\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 6.63\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 1.24\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 0.8\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 4.28\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 2.68\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 2.22\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 0.65\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 4.25\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 19.63\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 3.77\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 01:00:00\",\n    \"mwh\": 1.88\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 6.65\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 1.24\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 0.91\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 4.29\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 2.69\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 2.22\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 0.59\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 4.05\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 19.01\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 3.78\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 02:00:00\",\n    \"mwh\": 1.93\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 6.7\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 1.24\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 1.07\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 4.29\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 2.69\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 2.22\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 0.49\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 4.21\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 18.62\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 3.8\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 03:00:00\",\n    \"mwh\": 1.92\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 8.35\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 1.24\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 0.9\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 4.38\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 2.76\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 2.23\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 0.43\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 4.22\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 16.26\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 3.96\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 04:00:00\",\n    \"mwh\": 1.85\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 8.42\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 1.24\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 0.86\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 4.39\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 2.77\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 2.23\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 0.63\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 4.3\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 16.31\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 4\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 05:00:00\",\n    \"mwh\": 1.88\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 11.46\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 1.24\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 0.84\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 4.57\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 3.13\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 0.49\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 4.24\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 14.75\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 4.08\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 06:00:00\",\n    \"mwh\": 1.92\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 15.61\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 1.21\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 0.95\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 4.8\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 3.67\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 0.42\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 4\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 13.01\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 6.01\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 07:00:00\",\n    \"mwh\": 2.74\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 15.65\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 0.7\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 1.01\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 4.84\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 3.7\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 0.53\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 3.82\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 14.82\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 8.59\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 08:00:00\",\n    \"mwh\": 3.27\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 15.38\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 0.6\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 0.13\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 0.78\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 4.77\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 3.64\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 2.23\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 0.42\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 4.2\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 16.33\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 9.65\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 09:00:00\",\n    \"mwh\": 2.63\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 15.63\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 0.45\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 0.85\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 4.85\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 3.72\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 0.46\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 4.94\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 16.53\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 9.68\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 10:00:00\",\n    \"mwh\": 2.47\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 14.46\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 0.46\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 4.78\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 2.97\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 2.25\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 0.59\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 4.33\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 16.79\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 12.23\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 11:00:00\",\n    \"mwh\": 2.92\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 14.27\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 0.67\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 4.72\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 2.86\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 2.25\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 0.44\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 3.65\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 16.74\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 11.9\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 12:00:00\",\n    \"mwh\": 3.37\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 15.1\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 0.97\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 4.96\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 3.03\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 3.46\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 16.77\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 9.18\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 13:00:00\",\n    \"mwh\": 3.61\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 14.97\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 0.84\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 4.9\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 3\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 0.69\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 4.36\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 16.65\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 8.84\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 14:00:00\",\n    \"mwh\": 3.72\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 14.78\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 0.58\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 0.85\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 4.86\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 2.96\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 0.99\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 2.88\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 16.76\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 8.63\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 15:00:00\",\n    \"mwh\": 3.19\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 14.85\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 1.84\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 0.99\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 4.88\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 2.98\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 2.24\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 0.94\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 1.95\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 16.71\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 8.69\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 16:00:00\",\n    \"mwh\": 2.61\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 15.8\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 1.14\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 0.9\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 5.13\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 3.18\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 2.25\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 0.77\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 2.53\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 17.64\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 9.65\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 17:00:00\",\n    \"mwh\": 2.59\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 16\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 0.88\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 4.99\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 3.09\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 2.26\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 0.8\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 2.82\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 17.58\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 9.21\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 18:00:00\",\n    \"mwh\": 2.85\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 15.46\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 0.53\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 0.83\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 4.72\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 2.86\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 2.23\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 0.45\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 1.4\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 16.75\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 7.98\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 19:00:00\",\n    \"mwh\": 2.96\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 19.43\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 1.04\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 1.03\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 5.51\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 3.98\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 2.26\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 0.34\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 0.59\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 6.88\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 11.82\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 20:00:00\",\n    \"mwh\": 3.32\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 19.87\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 0.9\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 0.99\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 5.49\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 4.35\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 2.25\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 0.28\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 2.18\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 16.5\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 21:00:00\",\n    \"mwh\": 3.05\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 19.9\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 0.9\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 0.85\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 5.6\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 4.4\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 2.25\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 0.1\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 17.42\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 22:00:00\",\n    \"mwh\": 3.27\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 18.32\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 0.71\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 0.85\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 5.12\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 4.1\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 2.25\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 0.34\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 16.48\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-02-16 23:00:00\",\n    \"mwh\": 3.08\n  }\n]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/FO/sev_api_historical_2023_07_16.json",
    "content": "[\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0.88\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 3.34\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 34.55\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-14 23:00:00\",\n    \"mwh\": 1.8\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0.28\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 1.07\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 4.75\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 32.04\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 00:00:00\",\n    \"mwh\": 1.8\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0.24\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 1.82\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 7.17\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 28.87\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 01:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0.43\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 1.3\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 8.53\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 26.41\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 02:00:00\",\n    \"mwh\": 0.63\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0.22\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0.2\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 1.77\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 8.73\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 25.84\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 03:00:00\",\n    \"mwh\": 0.78\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0.27\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0.15\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 2.85\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 10.89\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 23.46\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 04:00:00\",\n    \"mwh\": 0.2\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0.53\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 2.61\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 12.68\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 21.03\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0.16\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0.63\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 2.56\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 13.78\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 21.11\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0.37\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0.49\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 2.64\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 17.11\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 19.91\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0.43\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 2.78\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 19.18\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 20.68\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0.38\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0.23\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 2.96\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 22.42\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 20.55\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0.13\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0.13\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0.28\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 3.19\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 25.17\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 19.76\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 1.15\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0.46\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 3.25\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 26.11\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 17.81\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0.93\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0.27\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 3.26\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 25.98\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 18.73\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0.91\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0.21\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0.67\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 3.32\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 25.98\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 18.68\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0.94\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0.29\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 3.27\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 25.98\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 18.86\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0.99\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0.44\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0.93\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 3.3\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 25.98\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 19.14\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 1\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0.23\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 1.28\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 3.39\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 25.98\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 19.26\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0.95\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 1.24\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 3.6\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 25.98\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 18.98\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 1.2\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0.2\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 1.09\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 3.31\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 25.1\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 19.23\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 1.66\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0.31\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0.97\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 3.24\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 22.65\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 19.68\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 1.62\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 1.02\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 3.16\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 22.39\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 18.94\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 1.2\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0.08\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 1.12\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 3.2\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 21.9\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 19.91\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0.69\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0.37\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 1.27\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 3.3\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 22.01\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 19.41\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0.53\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 1.29\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 3.04\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 21.4\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 18.72\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0.37\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0.52\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 1.28\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 2.75\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 21.44\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 17.77\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 1.28\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 2.61\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 21.17\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 17.75\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 1.19\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 2.71\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 19.76\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 18.12\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0.41\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 1.13\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 2.73\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 18.46\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 19.1\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0.08\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 2.51\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 17.97\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 18.98\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 1.29\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 2.46\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 17.97\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 18.74\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0.3\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 1.28\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 2.38\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 17.97\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 20.26\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0.34\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 1.29\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 2.55\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 18.45\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 21.26\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 1.29\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 2.82\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 19.39\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 22.08\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0.34\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 1.29\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 3.02\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 19.47\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 24.46\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0.15\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 1.25\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 3.21\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 22.33\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 23.6\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 3.24\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 23.61\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0.06\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 22.4\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0.25\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 1.26\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 3.32\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 23.72\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0.05\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 22.89\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0.19\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 1.29\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 3.2\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 24.97\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 21.26\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 1.3\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 3.05\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 24.93\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 20.36\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0.09\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0.42\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 1.3\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 3.08\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 24.04\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 21.28\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 3.24\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0.11\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0.42\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0.26\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 1.22\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 1.58\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 18.57\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 23.63\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 5.76\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 2.91\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 1.27\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0.56\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 12.34\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 26.35\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 6.79\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 3.02\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0.22\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 1.09\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0.38\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 7.74\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 30.1\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 5.36\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 3.01\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0.28\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0.29\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 9.45\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 30.15\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 4.15\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 2.71\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0.55\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0.42\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 10.68\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 28.98\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 2.42\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 2.12\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0.12\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0.31\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 1.28\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 15.74\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 25.63\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 1.63\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 1.63\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0.32\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0.38\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 1.08\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 16.98\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 24.58\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 5.65\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 1.75\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0.34\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0.73\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 11.7\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 23.72\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-16 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 3.82\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 2.02\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0.54\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0.18\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0.63\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 12.14\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 23.9\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 4.31\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 2.32\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0.58\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 10.15\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 25\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 4.52\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 2.32\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 2.23\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0.54\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 6.87\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 24.34\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 1.83\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 2.32\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0.44\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 1.38\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0.05\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0.32\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 9.8\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 24.6\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 3.35\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 2.14\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 1.54\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0.37\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 6.5\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 26.62\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 2.32\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 1.41\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0.3\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 1.19\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 9.96\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 26.95\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 2.25\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 1.31\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0.33\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 1.43\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 13.36\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 28.6\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 1.78\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 1.21\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0.32\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0.1\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 1.55\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 11.67\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 35.03\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 3.96\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0.9\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 1.57\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0.18\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 2.36\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 9.68\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0.05\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 35.2\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 08:00:00\",\n    \"mwh\": 0.6\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 6.05\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0.77\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0.19\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 3.05\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0.36\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 2.6\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 10.41\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0.05\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 33.22\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 6.27\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0.52\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0.2\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 3.19\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0.48\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 3.06\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 10.11\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0.05\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 34.75\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 6.06\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 3.23\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0.74\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 3.42\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 11.54\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0.09\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 32.14\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 6.15\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0.2\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 3.47\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0.08\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0.52\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 3.39\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 10.69\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0.11\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 32.95\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 6.04\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0.12\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 3.31\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0.39\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 3.47\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 11.32\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0.09\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 32.15\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 5.45\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 2.98\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0.4\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 3.75\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 12.1\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0.06\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 31.51\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 2.87\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0.58\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 2.01\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0.46\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 3.7\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 15.7\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 31.02\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 3.18\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0.07\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0.63\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 3.87\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 16.86\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 32.27\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 3.39\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0.74\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0.94\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 3.68\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 14.81\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 32.41\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 4.83\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0.42\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0.77\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 3.52\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 12.02\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 32.01\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 1.51\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0.81\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 3.32\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 19.51\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 26.67\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 1.47\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0.69\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 3.22\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 24.39\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 20\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 3.31\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0.34\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0.64\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 3.22\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 23.66\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 17.82\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 3.1\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0.06\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0.64\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 3.11\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 23.32\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 17.73\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2023-07-17 22:00:00\",\n    \"mwh\": 0\n  }\n]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/FO/sev_api_live_0.json",
    "content": "[\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 2.44\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0.1\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 1.48\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0.48\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 2.99\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 11.93\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 24.93\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-14 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 2.89\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 2.2\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0.09\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 2.73\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 8.06\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 26.78\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 1.41\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0.79\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 1.28\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0.36\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 2.97\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 9.85\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 28.48\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0.68\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0.62\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0.62\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 2.95\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 12.45\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 22.48\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0.68\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0.62\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0.63\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 2.76\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 12.16\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 23.38\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0.68\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0.62\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0.64\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 2.65\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 13.43\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 22.11\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0.68\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0.62\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0.13\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0.64\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 2.74\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 15.97\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 19.67\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 1.66\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 1.01\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0.31\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0.64\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 3.07\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 16.88\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 21.26\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 8.35\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0.11\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 1.72\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0.63\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0.64\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 3.41\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 18.08\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 18.28\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 7.3\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0.73\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 1.48\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0.69\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0.5\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 3.45\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 22.23\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 16.62\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 8.47\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0.8\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 1.45\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0.7\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0.36\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 2.53\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 24.1\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 15.99\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 09:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 8.29\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 1.44\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 0.06\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 1.51\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 24.71\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 0.08\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 15.95\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 10:00:00\",\n    \"mwh\": 2.47\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 9.87\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 1.39\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0.72\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0.07\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0.58\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 21.3\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 0.08\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 17.26\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 11:00:00\",\n    \"mwh\": 2.77\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 9.82\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 1.39\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0.65\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0.43\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0.05\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 17.25\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 0.1\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 19.77\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 12:00:00\",\n    \"mwh\": 3.24\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 9\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 1.68\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0.38\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0.5\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 8.71\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 0.16\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 29.58\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 13:00:00\",\n    \"mwh\": 3.35\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 9.77\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0.7\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 2.15\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0.07\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0.29\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 2.86\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 0.06\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 32.96\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 14:00:00\",\n    \"mwh\": 3.4\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 11.39\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 1.5\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 3.02\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0.15\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0.07\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 0.06\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 33.07\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 15:00:00\",\n    \"mwh\": 3.29\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 12.74\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 1.5\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 3.06\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0.18\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0.17\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0.19\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 0.06\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 33.02\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 16:00:00\",\n    \"mwh\": 3.16\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 10.55\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0.95\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0.21\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 3\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0.17\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0.17\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0.68\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 0.06\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 33.09\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 17:00:00\",\n    \"mwh\": 2.99\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 9.3\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0.7\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 3.3\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0.23\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0.9\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0.69\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 0.04\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 33.1\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 18:00:00\",\n    \"mwh\": 2.18\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 7.3\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 2.79\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 0.33\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 1.27\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 1.86\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 32.98\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 19:00:00\",\n    \"mwh\": 1.73\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 5.28\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 2.78\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 0.32\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 1.2\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 3.23\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 33.06\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 20:00:00\",\n    \"mwh\": 1.68\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 5.53\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0.33\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 1.77\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0.45\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0.98\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 6.04\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 29.71\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 21:00:00\",\n    \"mwh\": 1.69\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 7.09\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 0.54\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 2.57\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 0.52\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 1.12\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 5.38\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 29.02\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 22:00:00\",\n    \"mwh\": 1.82\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 4.26\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 1.07\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0.47\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0.73\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 5.78\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 29.16\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-15 23:00:00\",\n    \"mwh\": 1.95\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 3.89\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0.41\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0.46\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 6.31\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 29\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 00:00:00\",\n    \"mwh\": 1.95\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 2.29\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0.45\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0.33\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 8.13\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 27.84\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 01:00:00\",\n    \"mwh\": 1.95\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 3.98\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0.49\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0.36\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 6.83\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 23.4\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 02:00:00\",\n    \"mwh\": 2.15\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 5.53\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0.39\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0.32\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 2.8\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 27.75\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 03:00:00\",\n    \"mwh\": 2.32\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 5.11\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0.1\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0.39\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 2.55\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 27.45\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 04:00:00\",\n    \"mwh\": 1.84\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 1.98\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0.55\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0.33\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 4.2\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 31.36\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 05:00:00\",\n    \"mwh\": 1.84\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 4.36\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0.37\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0.12\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 2.05\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 0.02\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 36.59\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 06:00:00\",\n    \"mwh\": 2.8\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 5.37\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0.86\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0.01\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 3.5\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 0.07\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 38.01\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 07:00:00\",\n    \"mwh\": 2.91\n  },\n  {\n    \"powerplant\": \"Eiðisverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 3.88\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið á Strond Vatn\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Elverkið í Botni\",\n    \"motivepower\": \"Water\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Førka Biogas\",\n    \"motivepower\": \"Biogas\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0.75\n  },\n  {\n    \"powerplant\": \"Fossáverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Heygaverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Mýruverkið\",\n    \"motivepower\": \"Water\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Neshagi\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Norðstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0.03\n  },\n  {\n    \"powerplant\": \"Suðuroy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0\n  },\n  {\n    \"powerplant\": \"Suðurstreymoy\",\n    \"motivepower\": \"Wind\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 1.43\n  },\n  {\n    \"powerplant\": \"Sumba\",\n    \"motivepower\": \"Solar\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 0.1\n  },\n  {\n    \"powerplant\": \"Sundsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"Main\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 42.02\n  },\n  {\n    \"powerplant\": \"Vágsverkið\",\n    \"motivepower\": \"Oil\",\n    \"area\": \"South\",\n    \"date\": \"2024-05-16 08:00:00\",\n    \"mwh\": 3.18\n  }\n]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/FO/sev_api_live_1.json",
    "content": "{\n  \"tiden\": \"2024-05-16 12:02\",\n  \"SdDiesel_E\": \"42,37\",\n  \"FoVand_E\": \"2,15\",\n  \"MyVand_E\": \"0,00\",\n  \"HeVand_E\": \"0,00\",\n  \"VnVand_E\": \"2,15\",\n  \"EiVand_E\": \"4,47\",\n  \"StDiesel_E\": \"0,00\",\n  \"StVand_E\": \"0,00\",\n  \"NoDiesel_E\": \"0,00\",\n  \"SorDiesel_E\": \"0,00\",\n  \"HhVind_E\": \"0,00\",\n  \"NeVind_E\": \"0,00\",\n  \"VgDiesel_E\": \"3,77\",\n  \"BoVand_E\": \"0,00\",\n  \"SuSol_E\": \"0,07\",\n  \"PoVind_E\": \"0,00\",\n  \"RoVind_E\": \"0,00\",\n  \"ViRoVind_E\": \"0,00\",\n  \"SuStVind_E\": \"0,09\",\n  \"NoStVind_E\": \"0,00\",\n  \"SuVind_E\": \"0,59\",\n  \"Minesto_E\": \"0,00\",\n  \"Forka_E\": \"0,75\",\n  \"VandH_E\": \"6,62\",\n  \"OlieH_E\": \"42,37\",\n  \"VindH_E\": \"0,09\",\n  \"BiogasH_E\": \"0,75\",\n  \"TidalH_E\": \"0,00\",\n  \"VandS_E\": \"0,00\",\n  \"OlieS_E\": \"3,77\",\n  \"VindS_E\": \"0,59\",\n  \"SolS_E\": \"0,07\",\n  \"VandSev_E\": \"6,62\",\n  \"OlieSev_E\": \"46,14\",\n  \"VindSev_E\": \"0,68\",\n  \"SolSev_E\": \"0,07\",\n  \"BiogasSev_E\": \"0,75\",\n  \"TidalSev_E\": \"0,00\",\n  \"SumS_E\": \"4,43\",\n  \"SumH_E\": \"49,83\",\n  \"SumSev_E\": \"54,26\",\n  \"SumGront_E\": \"8,12\",\n  \"SdDiesel_P\": \"85,03\",\n  \"FoVand_P\": \"4,31\",\n  \"MyVand_P\": \"0,00\",\n  \"HeVand_P\": \"0,00\",\n  \"EiVand_P\": \"8,97\",\n  \"StDiesel_P\": \"0,00\",\n  \"StVand_P\": \"0,00\",\n  \"NoDiesel_P\": \"0,00\",\n  \"SorDiesel_P\": \"0,00\",\n  \"HhVind_P\": \"0,00\",\n  \"NeVind_P\": \"0,00\",\n  \"RoVind_P\": \"0,00\",\n  \"ViRoVind_P\": \"0,00\",\n  \"SuStVind_P\": \"0,18\",\n  \"NoStVind_P\": \"0,00\",\n  \"SuVind_P\": \"13,32\",\n  \"VgDiesel_P\": \"85,10\",\n  \"BoVand_P\": \"0,00\",\n  \"SuSol_P\": \"1,58\",\n  \"PoVind_P\": \"13,32\",\n  \"Minesto_P\": \"0,00\",\n  \"Forka_P\": \"1,51\",\n  \"VandH_P\": \"13,3\",\n  \"VindH_P\": \"0,2\",\n  \"OlieH_P\": \"85,0\",\n  \"BiogasH_P\": \"1,5\",\n  \"TidalH_P\": \"0,0\",\n  \"VandS_P\": \"0,0\",\n  \"OlieS_P\": \"85,1\",\n  \"VindS_P\": \"13,3\",\n  \"SolS_P\": \"1,6\",\n  \"VandSev_P\": \"12,2\",\n  \"OlieSev_P\": \"85,0\",\n  \"VindSev_P\": \"1,3\",\n  \"SolSev_P\": \"0,1\",\n  \"BiogasSev_P\": \"1,4\",\n  \"TidalSev_P\": \"0,0\",\n  \"SumS_P\": \"8,16\",\n  \"SumH_P\": \"91,84\",\n  \"Gront_P\": \"15,00\",\n  \"Vatnid\": \"-5,25\",\n  \"Lomundaroyri\": \"-1,28\",\n  \"Heygadalur\": \"-5,50\",\n  \"Eidisvatn\": \"-6,52\",\n  \"Strandadalur\": \"0,15\",\n  \"Ryskisvatn\": \"0,09\",\n  \"Vatnsnesvatn\": \"-1,42\"\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/FR/response.json",
    "content": "{\n    \"nhits\": 97,\n    \"parameters\": {\n        \"dataset\": \"eco2mix-national-tr\",\n        \"q\": \"date_heure >= 2023-09-21T02:00 AND date_heure <= 2023-09-22T02:00\",\n        \"rows\": 100,\n        \"start\": 0,\n        \"format\": \"json\",\n        \"timezone\": \"Europe/Paris\"\n    },\n    \"records\": [\n        {\n            \"datasetid\": \"eco2mix-national-tr\",\n            \"recordid\": \"0e195ef8ffa25fccd32f6b9017f9008b0623dd29\",\n            \"fields\": {\n                \"consommation\": 35683,\n                \"fioul_cogen\": 113,\n                \"eolien\": 9077,\n                \"bioenergies_dechets\": 60,\n                \"ech_physiques\": -11204,\n                \"fioul_tac\": 1,\n                \"charbon\": 7,\n                \"bioenergies\": 677,\n                \"nucleaire\": 34482,\n                \"prevision_j\": 36200,\n                \"gaz_ccg\": 194,\n                \"hydraulique_step_turbinage\": 3,\n               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0,\n                \"heure\": \"10:30\",\n                \"taux_co2\": 21,\n                \"gaz_cogen\": 345,\n                \"destockage_batterie\": \"6\",\n                \"nature\": \"Donn\\u00e9es temps r\\u00e9el\",\n                \"date_heure\": \"2023-09-21T10:30:00+02:00\",\n                \"pompage\": -3,\n                \"bioenergies_biomasse\": 365,\n                \"bioenergies_biogaz\": 250,\n                \"fioul\": 114,\n                \"eolien_offshore\": \"105\",\n                \"prevision_j1\": 48200,\n                \"ech_comm_italie\": -1548,\n                \"gaz_tac\": 0,\n                \"ech_comm_espagne\": 1100,\n                \"gaz_autres\": 0,\n                \"hydraulique_lacs\": 1204,\n                \"eolien_terrestre\": \"4506\",\n                \"perimetre\": \"France\",\n                \"hydraulique_fil_eau_eclusee\": 3040\n            },\n            \"record_timestamp\": \"2023-11-20T14:00:25.32+01:00\"\n        },\n        {\n            \"datasetid\": \"eco2mix-national-tr\",\n            \"recordid\": \"500970f64d717537f04d193b133f427f62ade09d\",\n            \"fields\": {\n                \"ech_comm_suisse\": -1087,\n                \"consommation\": 49757,\n                \"fioul_cogen\": 113,\n                \"eolien\": 3892,\n                \"bioenergies_dechets\": 52,\n                \"ech_physiques\": -5247,\n                \"fioul_tac\": 73,\n                \"charbon\": 11,\n                \"bioenergies\": 670,\n                \"nucleaire\": 38825,\n                \"prevision_j\": 49700,\n                \"ech_comm_angleterre\": \"-2680\",\n                \"gaz_ccg\": 1215,\n                \"ech_comm_allemagne_belgique\": \"-807\",\n                \"hydraulique_step_turbinage\": 1018,\n                \"date\": \"2023-09-21\",\n                \"gaz\": 1603,\n                \"solaire\": 4120,\n                \"stockage_batterie\": \"-12\",\n                \"hydraulique\": 5746,\n                \"fioul_autres\": 0,\n                \"heure\": \"11:30\",\n                \"taux_co2\": 21,\n                \"gaz_cogen\": 390,\n                \"destockage_batterie\": \"3\",\n                \"nature\": \"Donn\\u00e9es temps r\\u00e9el\",\n                \"date_heure\": \"2023-09-21T11:30:00+02:00\",\n                \"pompage\": -40,\n                \"bioenergies_biomasse\": 367,\n                \"bioenergies_biogaz\": 250,\n                \"fioul\": 186,\n                \"eolien_offshore\": \"260\",\n                \"prevision_j1\": 48500,\n                \"ech_comm_italie\": -1398,\n                \"gaz_tac\": 0,\n                \"ech_comm_espagne\": 1100,\n                \"gaz_autres\": 0,\n                \"hydraulique_lacs\": 1488,\n                \"eolien_terrestre\": \"3633\",\n                \"perimetre\": \"France\",\n                \"hydraulique_fil_eau_eclusee\": 3240\n            },\n            \"record_timestamp\": \"2023-11-20T14:00:25.32+01:00\"\n        },\n        {\n            \"datasetid\": \"eco2mix-national-tr\",\n            \"recordid\": \"6cfe6912441478b3c503b767e7cb7fc7c654b03f\",\n            \"fields\": {\n                \"consommation\": 48739,\n                \"fioul_cogen\": 113,\n                \"eolien\": 4618,\n                \"bioenergies_dechets\": 55,\n                \"ech_physiques\": -5792,\n                \"fioul_tac\": 1,\n                \"charbon\": 11,\n                \"bioenergies\": 672,\n                \"nucleaire\": 38413,\n                \"prevision_j\": 48450,\n                \"gaz_ccg\": 1193,\n                \"hydraulique_step_turbinage\": 340,\n                \"date\": \"2023-09-21\",\n                \"gaz\": 1573,\n                \"solaire\": 4793,\n                \"stockage_batterie\": \"-8\",\n                \"hydraulique\": 4346,\n                \"fioul_autres\": 0,\n                \"heure\": \"14:15\",\n                \"taux_co2\": 20,\n                \"gaz_cogen\": 381,\n                \"destockage_batterie\": \"3\",\n                \"nature\": \"Donn\\u00e9es temps r\\u00e9el\",\n                \"date_heure\": \"2023-09-21T14:15:00+02:00\",\n                \"pompage\": -3,\n                \"bioenergies_biomasse\": 367,\n                \"bioenergies_biogaz\": 250,\n                \"fioul\": 114,\n                \"eolien_offshore\": \"151\",\n                \"prevision_j1\": 48100,\n                \"gaz_tac\": 0,\n                \"gaz_autres\": 0,\n                \"hydraulique_lacs\": 1173,\n                \"eolien_terrestre\": \"4467\",\n                \"perimetre\": \"France\",\n                \"hydraulique_fil_eau_eclusee\": 2832\n            },\n            \"record_timestamp\": \"2023-11-20T14:00:25.32+01:00\"\n        },\n        {\n            \"datasetid\": \"eco2mix-national-tr\",\n            \"recordid\": \"c1a1d0970f66542f7c22851bb9a371d70689a5fe\",\n            \"fields\": {\n                \"ech_comm_suisse\": -2052,\n                \"consommation\": 47998,\n                \"fioul_cogen\": 113,\n                \"eolien\": 5727,\n                \"bioenergies_dechets\": 49,\n                \"ech_physiques\": -6845,\n                \"fioul_tac\": 1,\n                \"charbon\": 11,\n                \"bioenergies\": 664,\n                \"nucleaire\": 37987,\n                \"prevision_j\": 47600,\n                \"ech_comm_angleterre\": \"-1970\",\n                \"gaz_ccg\": 1317,\n                \"ech_comm_allemagne_belgique\": \"-3489\",\n                \"hydraulique_step_turbinage\": 167,\n                \"date\": \"2023-09-21\",\n                \"gaz\": 1661,\n                \"solaire\": 4994,\n                \"stockage_batterie\": \"-15\",\n                \"hydraulique\": 3930,\n                \"fioul_autres\": 0,\n                \"heure\": \"15:00\",\n                \"taux_co2\": 21,\n                \"gaz_cogen\": 344,\n                \"destockage_batterie\": \"6\",\n                \"nature\": \"Donn\\u00e9es temps r\\u00e9el\",\n                \"date_heure\": \"2023-09-21T15:00:00+02:00\",\n                \"pompage\": -238,\n                \"bioenergies_biomasse\": 365,\n                \"bioenergies_biogaz\": 250,\n                \"fioul\": 114,\n                \"eolien_offshore\": \"85\",\n                \"prevision_j1\": 47500,\n                \"ech_comm_italie\": -1425,\n                \"gaz_tac\": 0,\n                \"ech_comm_espagne\": 1600,\n                \"gaz_autres\": 0,\n                \"hydraulique_lacs\": 869,\n                \"eolien_terrestre\": \"5642\",\n                \"perimetre\": \"France\",\n                \"hydraulique_fil_eau_eclusee\": 2894\n            },\n            \"record_timestamp\": \"2023-11-20T14:00:25.32+01:00\"\n        },\n        {\n            \"datasetid\": \"eco2mix-national-tr\",\n            \"recordid\": \"9f869a27a2dc1f50b31ff30ba346f1fd4deb0ed5\",\n    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\"hydraulique_lacs\": 1433,\n                \"eolien_terrestre\": \"5414\",\n                \"perimetre\": \"France\",\n                \"hydraulique_fil_eau_eclusee\": 3672\n            },\n            \"record_timestamp\": \"2023-11-20T14:00:25.32+01:00\"\n        },\n        {\n            \"datasetid\": \"eco2mix-national-tr\",\n            \"recordid\": \"bca2744ce09bbe862a35d6e95ba490d014113d0e\",\n            \"fields\": {\n                \"consommation\": 37045,\n                \"fioul_cogen\": 113,\n                \"eolien\": 6891,\n                \"bioenergies_dechets\": 53,\n                \"ech_physiques\": -13875,\n                \"fioul_tac\": 0,\n                \"charbon\": 7,\n                \"bioenergies\": 653,\n                \"nucleaire\": 37688,\n                \"prevision_j\": 37400,\n                \"gaz_ccg\": 462,\n                \"hydraulique_step_turbinage\": 876,\n                \"date\": \"2023-09-22\",\n                \"gaz\": 712,\n                \"solaire\": 0,\n                \"stockage_batterie\": \"-2\",\n                \"hydraulique\": 5147,\n                \"fioul_autres\": 0,\n                \"heure\": \"01:15\",\n                \"taux_co2\": 14,\n                \"gaz_cogen\": 251,\n                \"destockage_batterie\": \"7\",\n                \"nature\": \"Donn\\u00e9es temps r\\u00e9el\",\n                \"date_heure\": \"2023-09-22T01:15:00+02:00\",\n                \"pompage\": -292,\n                \"bioenergies_biomasse\": 349,\n                \"bioenergies_biogaz\": 250,\n                \"fioul\": 110,\n                \"eolien_offshore\": \"404\",\n                \"prevision_j1\": 37650,\n                \"gaz_tac\": 0,\n                \"gaz_autres\": 0,\n                \"hydraulique_lacs\": 1345,\n                \"eolien_terrestre\": \"6487\",\n                \"perimetre\": \"France\",\n                \"hydraulique_fil_eau_eclusee\": 2925\n            },\n            \"record_timestamp\": \"2023-11-20T14:00:25.32+01:00\"\n        }\n    ]\n}"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/FR_O/FR_COR.json",
    "content": "[\n  {\n    \"date\": \"2024-12-15T10:45:00+00:00\",\n    \"total\": 293.5,\n    \"moteur_diesel\": 105.2,\n    \"tac\": 0,\n    \"hydraulique\": 14.2,\n    \"micro_hydro\": 12.5,\n    \"photovoltaique\": 103.8,\n    \"eolien\": 0,\n    \"bioenergies\": 2,\n    \"liaisons\": 55.7,\n    \"solde_stockage\": 0,\n    \"statut\": \"Estimé\"\n  }, \n  {\n    \"date\": \"2024-12-15T11:00:00+00:00\",\n    \"total\": 294.9,\n    \"moteur_diesel\": 105.3,\n    \"tac\": 0,\n    \"hydraulique\": 14.2,\n    \"micro_hydro\": 11.6,\n    \"photovoltaique\": 104.1,\n    \"eolien\": 0,\n    \"bioenergies\": 2,\n    \"liaisons\": 57.6,\n    \"solde_stockage\": 0,\n    \"statut\": \"Estimé\"\n  }\n]"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/FR_O/FR_GP.json",
    "content": "[\n  {\n    \"date\": \"2022-07-19T23:56:00+00:00\",\n    \"turbines_a_combustion\": 1,\n    \"charbon\": 2,\n    \"diesel\": 3,\n    \"hydraulique\": 4,\n    \"geothermie\": 5,\n    \"eolien\": 6,\n    \"photovoltaique\": 7,\n    \"bioenergies\": 8,\n    \"total\": 9,\n    \"statut\": \"Estimé\",\n    \"solde_stockage\": -1\n  },\n  {\n    \"date\": \"2022-07-20T00:11:00+00:00\",\n    \"turbines_a_combustion\": 10,\n    \"charbon\": 11,\n    \"diesel\": 12,\n    \"hydraulique\": 13,\n    \"geothermie\": 14,\n    \"eolien\": 15,\n    \"photovoltaique\": 16,\n    \"bioenergies\": 17,\n    \"total\": 18,\n    \"statut\": \"Estimé\",\n    \"solde_stockage\": -0.0094\n  }\n]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/FR_O/FR_RE.json",
    "content": "[\n    {\n        \"territoire\": \"Réunion\",\n        \"production_totale_mwh\" :259.9774783,\n        \"bagasse_charbon_mwh\": 196.4090964,\n        \"statut\": \"Validé\",\n        \"hydraulique_mwh\": 32.09856161,\n        \"cout_moyen_de_production_eur_mwh\": 193.7,\n        \"photovoltaique_mwh\": -0.23266477,\n        \"bioenergies_mwh\": 0.955333333,\n        \"date_heure\": \"2018-01-01T00:00:00+00:00\",\n        \"eolien_mwh\": 0.536,\n        \"thermique_mwh\": 30.21115168\n    },\n    {\n        \"territoire\": \"Réunion\",\n        \"production_totale_mwh\": 252.2947686,\n        \"bagasse_charbon_mwh\": 194.6044467,\n        \"statut\": \"Validé\",\n        \"hydraulique_mwh\": 26.79243513,\n        \"cout_moyen_de_production_eur_mwh\": 195.8,\n        \"photovoltaique_mwh\": -0.172447205,\n        \"bioenergies_mwh\": 0.9555,\n        \"date_heure\": \"2018-01-01T01:00:00+00:00\",\n        \"eolien_mwh\": 0.435666667,\n        \"thermique_mwh\": 29.67916731\n    }\n]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GB/bmunits.json",
    "content": "[\n  {\"elexonBmUnit\": \"T_CRAIGB\", \"nationalGridBmUnit\": \"CRAIGB\", \"fuelType\": \"PS\"},\n  {\"elexonBmUnit\": \"T_DINORW\", \"nationalGridBmUnit\": \"DINORW\", \"fuelType\": \"PS\"}\n]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GB/bmvalues.json",
    "content": "{\n  \"data\": [\n    {\n      \"nationalGridBmUnit\": \"CRAIGB\",\n      \"timeFrom\": \"2024-12-16T10:00:00Z\",\n      \"timeTo\": \"2024-12-16T10:30:00Z\",\n      \"levelFrom\": 120,\n      \"levelTo\": 120\n    }\n  ]\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GB/boalf.json",
    "content": "{\n  \"data\": [\n    {\n      \"nationalGridBmUnit\": \"CRAIGB\",\n      \"timeFrom\": \"2024-12-16T10:00:00Z\",\n      \"timeTo\": \"2024-12-16T10:30:00Z\",\n      \"levelFrom\": 120,\n      \"levelTo\": 120,\n      \"acceptanceNumber\": 1\n    }\n  ]\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GB/eco2mix_api_historical_20220716.xml",
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  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GB/eco2mix_api_live.xml",
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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GB/production.json",
    "content": "{\n    \"help\": \"Mock NESO generation data\",\n    \"success\": true,\n    \"result\": {\n      \"records\": [\n        {\n          \"DATETIME\": \"2024-12-16T10:00:00\",\n          \"BIOMASS\": 5.0,\n          \"COAL\": 0.0,\n          \"GAS\": 10.5,\n          \"HYDRO\": 2.0,\n          \"NUCLEAR\": 8.0,\n          \"SOLAR\": 3.5,\n          \"WIND\": 12.0,\n          \"WIND_EMB\": 1.5,\n          \"OTHER\": 0.0,\n          \"STORAGE\": 0.0\n        },\n        {\n          \"DATETIME\": \"2024-12-16T10:30:00\",\n          \"BIOMASS\": 6.0,\n          \"COAL\": 1.0,\n          \"GAS\": 11.0,\n          \"HYDRO\": 2.5,\n          \"NUCLEAR\": 8.0,\n          \"SOLAR\": 4.0,\n          \"WIND\": 13.0,\n          \"WIND_EMB\": 2.0,\n          \"OTHER\": 0.5,\n          \"STORAGE\": 5.0\n        }\n      ]\n    }\n  }\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GT/wl12_api_historical_20230716_0.json",
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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GT/wl12_api_historical_20230716_1.json",
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  \"potencia\": 0,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 0,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 54.32,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 32.62,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 75.09,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 54.32,\n    \"tipo\": \"null\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 609.13,\n    \"tipo\": \"AGUA\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOGAS\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOMASA\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 0,\n    \"tipo\": \"BUNKER\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 244.08,\n    \"tipo\": \"CARBÓN\"\n  },\n  {\n   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},\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 32.21,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 89.69,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 21.92,\n    \"tipo\": \"null\"\n  }\n]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GT/wl12_api_live_0.json",
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\"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 1949.35,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 35.21,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 1918.091,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 0,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 56.6,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 157.28,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 31.3,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 43.5,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"16\",\n    \"potencia\": 157.28,\n    \"tipo\": \"null\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 411.38,\n    \"tipo\": \"AGUA\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOGAS\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 301.45,\n    \"tipo\": \"BIOMASA\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 167.9,\n    \"tipo\": \"BIOMASA/CARBÓN\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 319.67,\n    \"tipo\": \"BUNKER\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 202.23,\n    \"tipo\": \"CARBÓN\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 273.57,\n    \"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 1859.66,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 35.14,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 1879.041,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 0,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 18.86,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 83.74,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 31.32,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 14.4,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"17\",\n    \"potencia\": 83.74,\n    \"tipo\": \"null\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 464.53,\n    \"tipo\": \"AGUA\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOGAS\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 320.6,\n    \"tipo\": \"BIOMASA\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 167.29,\n    \"tipo\": \"BIOMASA/CARBÓN\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 323.18,\n    \"tipo\": \"BUNKER\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 202.27,\n    \"tipo\": \"CARBÓN\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 273.78,\n    \"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 1880.82,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 35.14,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 1820.3,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 0,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 0.74,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 35.55,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 31.66,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 26.08,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"18\",\n    \"potencia\": 35.55,\n    \"tipo\": \"null\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 671.14,\n    \"tipo\": \"AGUA\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOGAS\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 320.97,\n    \"tipo\": \"BIOMASA\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 168.73,\n    \"tipo\": \"BIOMASA/CARBÓN\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 323.8,\n    \"tipo\": \"BUNKER\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 202.33,\n    \"tipo\": \"CARBÓN\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 273.71,\n    \"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 2046.61,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 35.21,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 2040.132,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 2.45,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 0,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 49.17,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 32,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 25.72,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"19\",\n    \"potencia\": 46.26,\n    \"tipo\": \"null\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 628.87,\n    \"tipo\": \"AGUA\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOGAS\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 323.26,\n    \"tipo\": \"BIOMASA\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 168.83,\n    \"tipo\": \"BIOMASA/CARBÓN\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 323.92,\n    \"tipo\": \"BUNKER\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 202.78,\n    \"tipo\": \"CARBÓN\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 274.13,\n    \"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 2066.08,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 0,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 2038.16,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 11.53,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 0,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 92.8,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 31.96,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 27.03,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"20\",\n    \"potencia\": 92.4,\n    \"tipo\": \"null\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 624.92,\n    \"tipo\": \"AGUA\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOGAS\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 316.96,\n    \"tipo\": \"BIOMASA\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 169.17,\n    \"tipo\": \"BIOMASA/CARBÓN\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 324.23,\n    \"tipo\": \"BUNKER\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 203.28,\n    \"tipo\": \"CARBÓN\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 273.5,\n    \"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 2004.28,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 0,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 1974.101,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 13,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 0,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 42.7,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 32.28,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 14.99,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"21\",\n    \"potencia\": 38.76,\n    \"tipo\": \"null\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 460.45,\n    \"tipo\": \"AGUA\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOGAS\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 322.07,\n    \"tipo\": \"BIOMASA\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 162.81,\n    \"tipo\": \"BIOMASA/CARBÓN\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 322.46,\n    \"tipo\": \"BUNKER\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 203.02,\n    \"tipo\": \"CARBÓN\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 273.22,\n    \"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 1783.81,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 0,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 1752.11,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 14.43,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 0,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 0,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 32.22,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 5.04,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"22\",\n    \"potencia\": 0,\n    \"tipo\": \"null\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 304.46,\n    \"tipo\": \"AGUA\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOGAS\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 313.16,\n    \"tipo\": \"BIOMASA\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 167.54,\n    \"tipo\": \"BIOMASA/CARBÓN\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 314.87,\n    \"tipo\": \"BUNKER\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 202.41,\n    \"tipo\": \"CARBÓN\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 273.22,\n    \"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 1548.1,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 34.06,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 1548.979,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 14.38,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 0,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 0,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 32.53,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 2.46,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"23\",\n    \"potencia\": 0,\n    \"tipo\": \"null\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 211.5,\n    \"tipo\": \"AGUA\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"BIOGAS\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 314.84,\n    \"tipo\": \"BIOMASA\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 167.03,\n    \"tipo\": \"BIOMASA/CARBÓN\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 274.99,\n    \"tipo\": \"BUNKER\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 202.81,\n    \"tipo\": \"CARBÓN\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 273.36,\n    \"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 1386.88,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 1417.61,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 14.46,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 32.79,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 1.86,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"null\"\n  }\n]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/GT/wl12_api_live_1.json",
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\"potencia\": 0,\n    \"tipo\": \"CARBÓN/PETCOKE\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"DEM SNI\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"DIESEL\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 1423.899,\n    \"tipo\": \"DEMANDA LOCAL PROG\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"GAS NATURAL\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"IRRADIACIÓN\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"INTERCONEXIÓN\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"SYNGAN\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"VAPOR\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"VIENTO\"\n  },\n  {\n    \"hora\": \"24\",\n    \"potencia\": 0,\n    \"tipo\": \"null\"\n  }\n]\n"
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    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,Guatemala,-27.6,-21.5,-22.7,-23.3,-14.4,-5.9,-5.2,-24.4,,,,,,,,,,,,,,,,\n7/25/2025,Nicaragua,-98.5,-97.4,-98,-91.8,-101.6,-108,-82.7,-66.3,,,,,,,,,,,,,,,,\n7/25/2025,El Salvador,58.5,51.5,33.9,23.8,36.3,45,28.7,20.1,,,,,,,,,,,,,,,,\n"
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    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,Arenal,48.5,46.7,45.6,25.8,24.8,24.9,24.5,3.2,,,,,,,,,,,,,,,,\n7/25/2025,Nispero,22.5,22.5,22.5,22.5,22.5,22.5,22.5,22.5,,,,,,,,,,,,,,,,\n7/25/2025,El Cajon,179.8,163.7,167,190.2,193.8,197.7,166.3,175.9,,,,,,,,,,,,,,,,\n7/25/2025,La Vegona,22.1,22,22,22.1,26.9,39.3,44.8,35.7,,,,,,,,,,,,,,,,\n7/25/2025,Rio Lindo,45.7,45.8,45.2,44.9,49.9,52,44.2,44.1,,,,,,,,,,,,,,,,\n7/25/2025,Ca�averal,10.2,10.2,10.1,10.2,10.1,12.9,14.6,14.6,,,,,,,,,,,,,,,,\n7/25/2025,Patuca III,50,49.9,44.9,49.9,45.6,47.6,49.8,49.8,,,,,,,,,,,,,,,,\n"
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    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,CISA,6.3,6.1,5.6,5.6,5,.7,.6,.5,,,,,,,,,,,,,,,,\n7/25/2025,SHOL,.1,0,0,0,0,0,.8,11,,,,,,,,,,,,,,,,\n7/25/2025,Morja,2.7,2.7,2.7,2.7,2.7,2.7,2.7,2.7,,,,,,,,,,,,,,,,\n7/25/2025,Canjel,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Mezapa,1.6,3.8,4.9,8.3,8.3,8.2,8,7.8,,,,,,,,,,,,,,,,\n7/25/2025,Quilio,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Zacapa,.5,.5,.5,.5,.5,.6,.6,.6,,,,,,,,,,,,,,,,\n7/25/2025,Churune,.9,.9,.9,.9,.9,.9,.9,.9,,,,,,,,,,,,,,,,\n7/25/2025,Coyolar,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Cuyamel,5.1,7.6,7.6,7.6,7.6,7.6,7.6,7.6,,,,,,,,,,,,,,,,\n7/25/2025,Nacaome,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Sazagua,4.5,4.3,4,3.7,3.7,3.9,3.9,4.5,,,,,,,,,,,,,,,,\n7/25/2025,Cececapa,3.2,3.2,3.2,3.2,3.2,3.2,3.2,3.2,,,,,,,,,,,,,,,,\n7/25/2025,Coronado,1.6,1.5,1.5,1.5,1.5,2,2.6,2.5,,,,,,,,,,,,,,,,\n7/25/2025,Cuyagual,.2,0,0,0,.1,.4,3.1,4,,,,,,,,,,,,,,,,\n7/25/2025,Cuyamapa,12.4,12.4,12.4,12.4,12.4,12.4,12.4,12.4,,,,,,,,,,,,,,,,\n7/25/2025,Laureles,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Mangungo,.9,1,1.4,1.4,1.4,1.4,1.4,1.4,,,,,,,,,,,,,,,,\n7/25/2025,Matarras,1.1,1,1.7,1.7,1.7,1.7,1.7,1.7,,,,,,,,,,,,,,,,\n7/25/2025,Rio Frio,.7,.7,.7,.8,.8,.8,.8,.8,,,,,,,,,,,,,,,,\n7/25/2025,San Juan,6.8,6.4,5.8,5.4,5.2,4.9,4.7,4.6,,,,,,,,,,,,,,,,\n7/25/2025,Babilonia,1.5,1.5,1.6,1.5,1.5,1.5,1.5,1.5,,,,,,,,,,,,,,,,\n7/25/2025,Cortesito,1.9,2.3,2,1.9,1.8,1.7,1.7,1.6,,,,,,,,,,,,,,,,\n7/25/2025,La Aurora,1.1,1.1,1.1,1.1,1.1,1.4,1.2,1.2,,,,,,,,,,,,,,,,\n7/25/2025,La Gloria,1.6,.6,1.2,1.3,.7,.8,1.3,1.3,,,,,,,,,,,,,,,,\n7/25/2025,San Alejo,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Agua Verde,.9,.9,.9,.9,.9,.9,.9,.9,,,,,,,,,,,,,,,,\n7/25/2025,Chamelecon,5.5,5.6,5.6,5.6,5.6,5.5,5.5,5.5,,,,,,,,,,,,,,,,\n7/25/2025,Genera Lla,4.5,4.4,2.7,4.4,4.1,4,3.9,3.8,,,,,,,,,,,,,,,,\n7/25/2025,Las Nieves,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Nispero II,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Pencaligue,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Rio Blanco,4.9,4.9,4.7,5,4.8,4.8,4.6,4.4,,,,,,,,,,,,,,,,\n7/25/2025,Rio Guineo,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,San Carlos,1.1,1.3,1.2,1.4,1.4,1.4,1.7,1.7,,,,,,,,,,,,,,,,\n7/25/2025,San Martin,2,2,2,2,2,2,2,2,,,,,,,,,,,,,,,,\n7/25/2025,Zinguizapa,2.1,2.1,2.1,2.1,2.1,2.1,2.1,2.1,,,,,,,,,,,,,,,,\n7/25/2025,Chachaguala,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Hidro Yojoa,.3,.3,.3,.3,.3,.3,.3,.3,,,,,,,,,,,,,,,,\n7/25/2025,Rio Betulia,.8,.8,.8,.8,.8,.8,.8,.8,,,,,,,,,,,,,,,,\n7/25/2025,Santa Maria,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Pe�a Blanca,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Corral de Piedras,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n"
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    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,San Marcos,15,16.7,16.2,14.4,17.1,15.6,16.8,17.5,,,,,,,,,,,,,,,,\n7/25/2025,Chinchayote,32.9,28.4,34.8,30.3,33.9,34.9,35,24,,,,,,,,,,,,,,,,\n7/25/2025,Cerro de Hula,67.2,61.1,63.6,64,54.2,57.3,74.1,65,,,,,,,,,,,,,,,,\n"
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    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,ECSA,0,0,0,0,0,.1,12.4,32.4,,,,,,,,,,,,,,,,\n7/25/2025,Lajas,0,0,0,0,0,0,.7,2.5,,,,,,,,,,,,,,,,\n7/25/2025,Mecer,-.1,-.1,-.1,-.1,-.1,-.1,7.8,16.9,,,,,,,,,,,,,,,,\n7/25/2025,Cihesa,0,0,0,0,0,0,1.4,5.8,,,,,,,,,,,,,,,,\n7/25/2025,Helios,0,0,0,0,0,0,7.4,18.5,,,,,,,,,,,,,,,,\n7/25/2025,Soposa,-.1,-.1,-.1,-.1,-.1,0,4,20.5,,,,,,,,,,,,,,,,\n7/25/2025,Cohessa,-.1,-.1,-.1,-.1,-.1,0,4,19.7,,,,,,,,,,,,,,,,\n7/25/2025,Fotersa,0,0,0,0,0,.1,5.5,12.5,,,,,,,,,,,,,,,,\n7/25/2025,Enerbasa,0,0,0,0,0,0,1.5,5.5,,,,,,,,,,,,,,,,\n7/25/2025,Marcovia,-.1,-.1,-.1,-.1,-.1,.1,10,24.2,,,,,,,,,,,,,,,,\n7/25/2025,Prodersa,-.1,-.1,-.1,-.1,-.1,-.1,3.6,14.3,,,,,,,,,,,,,,,,\n7/25/2025,Nacaome I,-.2,-.2,-.1,-.1,-.1,0,5.9,19.9,,,,,,,,,,,,,,,,\n7/25/2025,El Pollito,0,0,0,0,0,0,.6,3.5,,,,,,,,,,,,,,,,\n7/25/2025,Llanos Sur,0,0,0,0,0,0,.9,3.5,,,,,,,,,,,,,,,,\n7/25/2025,Prados Sur,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Choluteca I,0,0,0,0,0,0,5,13.1,,,,,,,,,,,,,,,,\n7/25/2025,Fray Lazaro,0,0,0,0,0,0,.3,1,,,,,,,,,,,,,,,,\n7/25/2025,Choluteca II,0,0,0,0,0,0,6.9,19.2,,,,,,,,,,,,,,,,\n"
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    "path": "electricitymap/contrib/parsers/tests/mocks/HN/production_index_4_geothermal.csv",
    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,Geoplatanares,27.3,27.6,27.7,27.8,28,28.3,28.2,27.9,,,,,,,,,,,,,,,,\n"
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    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,IHSA,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Cahsa,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Yodeco,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Aceydesa,3,2.9,3,3.1,3,1.9,1.9,3,,,,,,,,,,,,,,,,\n7/25/2025,Ecopalsa,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Chumbagua,2.1,10.4,2.1,2.1,2.1,7.4,9.7,12.5,,,,,,,,,,,,,,,,\n7/25/2025,Los Pinos,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Green Power,0,0,0,0,0,0,0,1.6,,,,,,,,,,,,,,,,\n7/25/2025,Merendon PP,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Tres Valles,12.9,12.8,12.8,12.8,12.9,13,13,13.1,,,,,,,,,,,,,,,,\n7/25/2025,Caracol Knits,17.5,17.3,17.4,17.8,17.4,17.4,17.7,17.2,,,,,,,,,,,,,,,,\n"
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    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,Becosa,106.4,105.8,105.6,106.1,106.3,106,106,106.1,,,,,,,,,,,,,,,,\n7/25/2025,Envasa Naco,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Envasa Formosa,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n"
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    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,EMCE,-.1,-.1,-.1,-.1,-.1,-.1,-.1,-.1,,,,,,,,,,,,,,,,\n7/25/2025,Pecsa,45,44.7,45.3,45.6,45,44.8,44.2,40.4,,,,,,,,,,,,,,,,\n7/25/2025,Elcosa,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Enersa,237.6,237.8,237.9,237.2,236.9,236.5,225.5,200.9,,,,,,,,,,,,,,,,\n7/25/2025,El Faro,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Lufussa II,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,La Ensenada,86,86.1,79,68.8,68.9,68.7,68.9,56.3,,,,,,,,,,,,,,,,\n7/25/2025,Lufussa III,198.8,153.8,89.2,64.4,64.4,64.5,29.2,0,,,,,,,,,,,,,,,,\n7/25/2025,Park Energy,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Laeisz Ceiba,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Ceiba Termica,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Termica Sulzer,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Termica AlsThom,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Laeisz San Isidro,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n"
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    "content": "Fecha,Planta,00,01,02,03,04,05,06,07,08,09,10,11,12,13,14,15,16,17,18,19,20,21,22,23\n7/25/2025,Mochito,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Santa Fe,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Juticalpa,-.1,-.1,-.1,-.1,-.1,-.1,-.1,-.1,,,,,,,,,,,,,,,,\n7/25/2025,Lufussa I,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Brassavola,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,La Ensenada,86,86.1,79,68.8,68.9,68.7,68.9,56.3,,,,,,,,,,,,,,,,\n7/25/2025,Laeisz Danli,0,0,0,0,0,0,0,0,,,,,,,,,,,,,,,,\n7/25/2025,Ceiba Termica,-.1,-.1,-.1,-.1,-.1,-.1,-.1,-.1,,,,,,,,,,,,,,,,\n"
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src=\"../../CORENEW/img/logo.png\" class=\"img-responsive logo\" />\n                </div>\n                <div class='col-xs-12 col-sm-7'>\n                    <div class='navbar navbar-default' role='navigation'>\n                        <div class='navbar-header'>\n                            <button type='button' class='navbar-toggle' data-toggle='collapse' data-target='.navbar-ex1-collapse'>\n                                <span class='sr-only'>Toggle navigation</span> <span class='icon-bar'></span><span\n                                    class='icon-bar'></span><span class='icon-bar'></span>\n                            </button>\n                        </div>\n                        <div class='collapse navbar-collapse navbar-ex1-collapse'>\n                            <ul class='nav navbar-nav'>\n                                <li class='active'><a href=\"../../Index.aspx\">HOME</a></li>\n                                <li><a href=\"../../Aboutus.aspx\">ABOUT US</a></li>\n                                <li><a href=\"../../UpdateFrequencyReports_New2.aspx\" target='_blank'>UPDATE FREQUENCY</a></li>\n                                <li class='dropdown'><a href='#' class='dropdown-toggle' data-toggle='dropdown'>NEW\n                                    FEATURES <b class='caret'></b></a>\n                                    <ul class='dropdown-menu'>\n                                        <li><a href=\"../../MultiStarScoreRules.aspx\" target='_blank'>Multistar Rating Rules</a></li>\n                                        <li><a href='../../UserInterface/MultiStar/MultistarRatingReport.aspx' target='_blank'>\n                                            Multistar Rating Marks</a></li>\n                                        <li><a href='../../UserInterface/PerformanceIndicators/PerformanceIndicatorsReport.aspx'\n                                               target='_blank'>Ranking Of Districts</a></li>\n\n                                        <li><a href=\"../../Starrating.aspx\" target='_blank'>Star Rating</a></li>\n                                        <li><a href='../../UserInterface/IssuesTracker/ChangeRequestLogin.aspx?PageId=1'>Log\n                                            CR/Issue</a></li>\n                                        <li><a href='../../UserInterface/IssuesTracker/ChangeRequestLogin.aspx?PageId=2'>View\n                                            CR/Issue</a></li>\n                                        <li><a href='../../UserInterface/IssuesTracker/ChangeRequestLogin.aspx?PageId=3'>Assign/Update\n                                            CR</a></li>\n                                    </ul>\n                                </li>\n                            </ul>\n                            <span class='searchspan'>\n\n                                <input type='text' placeholder='Search' id='txtSearch_Inner' autocomplete=\"off\" class='form-control searchbox'\n                                       style='margin-top: 20px' />\n                            </span>\n                        </div>\n                    </div>\n                </div>\n                <div class='col-xs-12 col-sm-2'>\n                    <span style='float: right; margin-left: 8px;'>\n\n                    </span>\n                </div>\n            </div>\n        </div>\n\n        <div>\n            <div class=\"col-xs-12\" style=\"padding: 0px 10px; margin-top: 15px;\">\n                <p class=\"breadcrumb_div\">\n                    <a href=\"../../Index.aspx\">Home</a> / <a href=\"powerform.aspx\">Energy</a> / Power\n                    Situation Report\n                    <br />\n                    <br />\n                    <span style=\"font-size: 18px;\">Department : Energy </span><span style=\"float: right;\n                    font-size: 18px;\">Last Updated : <b>\n                        <span id=\"MainContent_lblDate\">20-01-2020 13:12:32</span></b></span>\n                    <input type=\"hidden\" name=\"ctl00$MainContent$hdnDaily\" id=\"MainContent_hdnDaily\" value=\"20-01-2020 13:12:32\" />\n                    <input type=\"hidden\" name=\"ctl00$MainContent$hdnPower\" id=\"MainContent_hdnPower\" value=\"18-09-2019 07:52:26\" />\n                </p>\n            </div>\n            <div class=\"col-xs-12\" style=\"padding: 0px 10px;\">\n                <p class=\"innercolorheading\">\n                    Power Situation Report</p>\n            </div>\n            <div class=\"col-xs-12\">\n                <div class=\"reportrow\" style=\"float: left; width: 100%; margin-bottom: 80px;\">\n                    <div class=\"tabbable custom-tabs tabs-animated  flat flat-all hide-label-980 shadow track-url auto-scroll\">\n                        <ul class=\"nav nav-tabs\">\n                            <li class='active'><a href=\"#tab1primary\" data-toggle=\"tab\"\n                                                  class=\"active \" onclick=\"BindDate('Daily');\">&nbsp;<span>Daily Status<span class=\"arrow\"></span></span></a></li>\n                            <li class=''><a href=\"#tab2primary\" data-toggle=\"tab\"\n                                            onclick=\"BindDate('Power');\">&nbsp;<span>Power Supply Gap<span class=\"arrow\"></span></span></a></li>\n                            <li class=''><a href=\"#tab3primary\" data-toggle=\"tab\">\n                                &nbsp;<span>Graph<span class=\"arrow\"></span></span></a></li>\n                            <li class=''><a href=\"#tab4primary\" data-toggle=\"tab\">\n                                &nbsp;<span>More<span class=\"arrow\"></span></span></a></li>\n                        </ul>\n                        <div class=\"tab-content \">\n                            <div class='tab-pane active' id=\"tab1primary\">\n                                <div class=\"row-fluid table-responsive\">\n                                    <table class=\"table_style\" rules=\"all\" style=\"width: 100%; border-collapse: collapse;\"\n                                           cellspacing=\"0\">\n                                        <tr>\n                                            <td class=\"formbg2\" style=\"vertical-align: top; padding: 0px;\">\n                                                <div id=\"MainContent_UpdatePanel2\">\n\n                                                    <table id=\"MainContent_Table2\" width=\"100%\" border=\"0\" align=\"center\" cellpadding=\"0\" cellspacing=\"0\">\n                                                        <tr>\n                                                            <td align=\"center\" valign=\"middle\" style=\"border: 0px gray solid;\">\n                                                                <table cellpadding=\"0\" cellspacing=\"0\" border=\"1\" width=\"70%\" class=\"table_style table table-striped table-bordered tablestyle\">\n                                                                    <tr>\n                                                                        <th class=\"formminihd\">\n                                                                            Power Supply Status on\n                                                                            <span id=\"MainContent_lblPowerStatusDate\">20-01-2020 13:11</span>\n                                                                        </th>\n                                                                    </tr>\n                                                                    <tr>\n                                                                        <td class=\"formbg2\" style=\"padding: 5px;\">\n                                                                            <table cellpadding=\"0\" cellspacing=\"0\" border=\"1\" width=\"100%\" class=\"table_style table table-striped table-bordered tablestyle\">\n                                                                                <tr>\n                                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" width=\"60%\" style=\"font-weight: bold;\">\n                                                                                        GRID DEMAND (MW)\n                                                                                    </td>\n                                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgright\" width=\"40%\">\n                                                                                        <span id=\"MainContent_lblGridDemand\">8552</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" style=\"font-weight: bold;\">\n                                                                                        FREQUNCY (HZ)\n                                                                                    </td>\n                                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgright\">\n                                                                                        <span id=\"MainContent_lblFrequency\">50.06</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                            </table>\n                                                                        </td>\n                                                                    </tr>\n                                                                    <tr>\n                                                                        <td class=\"formbg2\" style=\"padding: 5px;\">\n                                                                            <table cellpadding=\"0\" cellspacing=\"0\" border=\"1\" width=\"100%\" class=\"table_style table table-striped table-bordered tablestyle\">\n                                                                                <tr>\n                                                                                    <th align=\"left\" valign=\"middle\" colspan=\"2\" class=\"gridhdbg\">\n                                                                                        Generation Details\n                                                                                    </th>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td class=\"gridbgleft\" width=\"60%\">\n                                                                                        HYDEL (MW)\n                                                                                    </td>\n                                                                                    <td class=\"gridbgright\" width=\"40%\">\n                                                                                        <span id=\"MainContent_lblHydel\">61</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td class=\"gridbgleft\">\n                                                                                        THERMAL (MW)\n                                                                                    </td>\n                                                                                    <td class=\"gridbgright\">\n                                                                                        <span id=\"MainContent_lblThermal\">2449</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td class=\"gridbgleft\">\n                                                                                        GAS (MW)\n                                                                                    </td>\n                                                                                    <td class=\"gridbgright\">\n                                                                                        <span id=\"MainContent_lblGas\">146</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td class=\"gridbgleft\">\n                                                                                        WIND (MW)\n                                                                                    </td>\n                                                                                    <td class=\"gridbgright\">\n                                                                                        <span id=\"MainContent_lblWind\">231</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td class=\"gridbgleft\">\n                                                                                        SOLAR (MW)\n                                                                                    </td>\n                                                                                    <td class=\"gridbgright\">\n                                                                                        <span id=\"MainContent_lblSolar\">1644</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td class=\"gridbgleft\">\n                                                                                        IPPs & Others (MW)\n                                                                                    </td>\n                                                                                    <td class=\"gridbgright\">\n                                                                                        <span id=\"MainContent_lblIPPS\">664</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td class=\"gridbgleft\">\n                                                                                        CGS Utilization (MW)\n                                                                                    </td>\n                                                                                    <td class=\"gridbgright\">\n                                                                                        <span id=\"MainContent_lblCGS\">3356</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                            </table>\n                                                                        </td>\n                                                                    </tr>\n                                                                    <tr>\n                                                                        <td class=\"formbg2\" style=\"padding: 5px;\">\n                                                                            <table cellpadding=\"0\" cellspacing=\"0\" border=\"1\" width=\"100%\" class=\"table_style table table-striped table-bordered tablestyle\">\n                                                                                <tr>\n                                                                                    <th align=\"left\" valign=\"middle\" class=\"gridhdbg\">\n                                                                                        DISCOM\n                                                                                    </th>\n                                                                                    <th align=\"left\" valign=\"middle\" class=\"gridhdbg\">\n                                                                                        ACTUAL (MW)\n                                                                                    </th>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td class=\"gridbgleft\" width=\"60%\">\n                                                                                        APSPDCL\n                                                                                    </td>\n                                                                                    <td class=\"gridbgright\" width=\"40%\">\n                                                                                        <span id=\"MainContent_lblAPSPDCL\">5727</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                                <tr>\n                                                                                    <td class=\"gridbgleft\">\n                                                                                        APEPDCL\n                                                                                    </td>\n                                                                                    <td class=\"gridbgright\">\n                                                                                        <span id=\"MainContent_lblAPEPDCL\">2658</span>\n                                                                                    </td>\n                                                                                </tr>\n                                                                            </table>\n                                                                        </td>\n                                                                    </tr>\n                                                                </table>\n                                                            </td>\n                                                        </tr>\n                                                    </table>\n\n\n                                                </div>\n                                            </td>\n                                        </tr>\n                                    </table>\n\n\n\n\n\n                                </div>\n                            </div>\n                            <div class='tab-pane ' id=\"tab2primary\">\n                                <div class=\"row-fluid\">\n                                    <table id=\"Table1\" class=\"table_style\" rules=\"all\" style=\"width: 100%; border-collapse: collapse;\"\n                                           cellspacing=\"0\">\n                                        <tr>\n                                            <td align=\"center\" valign=\"middle\" style=\"border: 1px gray solid;\">\n                                                <table cellpadding=\"0\" cellspacing=\"0\" border=\"1\" width=\"100%\" class=\"table_style table table-striped table-bordered tablestyle\">\n\n                                                    <tr>\n                                                        <td class=\"formbg2\" style=\"padding: 5px;\">\n                                                            <table cellpadding=\"0\" cellspacing=\"0\" border=\"1\" width=\"100%\" class=\"table_style table table-striped table-bordered tablestyle\">\n                                                                <tr>\n                                                                    <th align=\"left\" valign=\"middle\" colspan=\"3\" class=\"gridhdbg\">\n                                                                        Overall State Position (in MU) on&nbsp;<span id=\"MainContent_lblYesterdayDate\">19-01-2020</span>\n                                                                    </th>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" width=\"30%\" style=\"font-weight: bold;\">\n                                                                        Demand\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgright\" width=\"30%\">\n                                                                        <span id=\"MainContent_lblDemand\">168.0</span>\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbg1\" width=\"20%\">\n\n                                                                        <a onclick=\"return confirm('This link will take you to an external web site.')\" href=\"http://203.153.46.111:8099/reports/jsp/reportPSPpdf.htm?state=AP\"\n                                                                           class=\"red-lnk\" target=\"_blank\">Power Supply Position Report</a>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" style=\"font-weight: bold;\">\n                                                                        Supplied\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgright\">\n                                                                        <span id=\"MainContent_lblSupplied\">168.0</span>\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbg1\">\n                                                                        &nbsp;\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" style=\"font-weight: bold;\">\n                                                                        Power Supply Gap\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgright\">\n                                                                        <span id=\"MainContent_lblShortfall\">0.0</span>\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbg1\">\n                                                                        &nbsp;\n                                                                    </td>\n                                                                </tr>\n                                                            </table>\n                                                        </td>\n                                                    </tr>\n                                                    <tr>\n                                                        <td class=\"formbg2\" style=\"padding: 5px;\">\n                                                            <table cellpadding=\"0\" cellspacing=\"0\" border=\"1\" width=\"100%\" class=\"table_style table table-striped table-bordered tablestyle\">\n                                                                <tr>\n                                                                    <th align=\"left\" valign=\"middle\" colspan=\"4\" class=\"gridhdbg\">\n                                                                        Power Situation in the Last Five Days\n                                                                    </th>\n                                                                </tr>\n                                                                <tr>\n                                                                    <th class=\"gridhdbg\" width=\"25%\">\n                                                                        Date\n                                                                    </th>\n                                                                    <th class=\"gridhdbg\" width=\"25%\">\n                                                                        Demand (MU)\n                                                                    </th>\n                                                                    <th class=\"gridhdbg\" width=\"25%\">\n                                                                        Supply (MU)\n                                                                    </th>\n                                                                    <th class=\"gridhdbg\" width=\"25%\">\n                                                                        Deficit (MU)\n                                                                    </th>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td class=\"gridbg1\">\n                                                                        <span id=\"MainContent_lblPSDate1\">13-09-2019</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDemand1\">180.0</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSSupply1\">180.0</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDifict1\">0.0</span>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td class=\"gridbg1\">\n                                                                        <span id=\"MainContent_lblPSDate2\">14-09-2019</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDemand2\">176.0</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSSupply2\">176.0</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDifict2\">0.0</span>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td class=\"gridbg1\">\n                                                                        <span id=\"MainContent_lblPSDate3\">15-09-2019</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDemand3\">172.0</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSSupply3\">172.0</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDifict3\">0.0</span>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td class=\"gridbg1\">\n                                                                        <span id=\"MainContent_lblPSDate4\">16-09-2019</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDemand4\">168.0</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSSupply4\">168.0</span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDifict4\">0.0</span>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td class=\"gridbg1\">\n                                                                        <span id=\"MainContent_lblPSDate5\"></span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDemand5\"></span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSSupply5\"></span>\n                                                                    </td>\n                                                                    <td class=\"gridbgright\" align=\"right\">\n                                                                        <span id=\"MainContent_lblPSDifict5\"></span>\n                                                                    </td>\n                                                                </tr>\n                                                            </table>\n                                                        </td>\n                                                    </tr>\n                                                    <tr>\n                                                        <td class=\"formbg2\" style=\"padding: 5px;\">\n                                                            <table cellpadding=\"0\" cellspacing=\"0\" border=\"1\" width=\"100%\" class=\"table_style table table-striped table-bordered tablestyle\">\n                                                                <tr>\n                                                                    <th colspan=\"2\" class=\"gridhdbg\">\n                                                                        Power Supply Position in Different Sectors\n                                                                    </th>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" style=\"font-weight: bold;\">\n                                                                        Agriculture\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbg1\">\n                                                                        <a onclick=\"return confirm('This link will take you to an external Pdf.')\" href=\"http://203.153.46.111:8099/reports/jsp/agriculturePSPpdf.htm?state=AP\"\n                                                                           class=\"red-lnk\" target=\"_blank\">Report</a>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" style=\"font-weight: bold;\">\n                                                                        Domestic &amp; Commercial\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbg1\">\n                                                                        <a onclick=\"return confirm('This link will take you to an external Pdf.')\" href=\"http://203.153.46.111:8099/reports/jsp/domComPSPpdf.htm?state=AP\"\n                                                                           class=\"red-lnk\" target=\"_blank\">Report</a>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" style=\"font-weight: bold;\">\n                                                                        Industrial\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbg1\">\n                                                                        <a onclick=\"return confirm('This link will take you to an external Pdf.')\" href=\"http://203.153.46.111:8099/reports/jsp/industrialPSPpdf.htm?state=AP\"\n                                                                           class=\"red-lnk\" target=\"_blank\">Report</a>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" style=\"font-weight: bold;\">\n                                                                        Daily Report of Generation (AP Share)\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbg1\">\n                                                                        <a onclick=\"return confirm('This link will take you to an external Pdf.')\" href=\"http://203.153.46.111:8099/reports/jsp/generationsAPdf.htm?state=AP\"\n                                                                           class=\"red-lnk\" target=\"_blank\">Report</a>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" style=\"font-weight: bold;\">\n                                                                        Coal Stock Position\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbg1\">\n                                                                        <a onclick=\"return confirm('This link will take you to an external Pdf.')\" href=\"http://203.153.46.111:8099/reports/jsp/coalStockPositionpdf.htm?state=AP\"\n                                                                           class=\"red-lnk\" target=\"_blank\">Report</a>\n                                                                    </td>\n                                                                </tr>\n                                                                <tr>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbgleft\" style=\"font-weight: bold;\">\n                                                                        Daily Report on Feeder Breakdowns\n                                                                    </td>\n                                                                    <td align=\"left\" valign=\"middle\" class=\"gridbg1\">\n                                                                        <a onclick=\"return confirm('This link will take you to an external Pdf.')\" href=\"http://203.153.46.111:8099/reports/jsp/fdrsbrkds3311kvpdf.htm?state=AP\"\n                                                                           class=\"red-lnk\" target=\"_blank\">Report</a>\n                                                                    </td>\n                                                                </tr>\n                                                            </table>\n                                                        </td>\n                                                    </tr>\n                                                </table>\n                                            </td>\n                                        </tr>\n                                    </table>\n                                </div>\n                            </div>\n                            <div class='tab-pane ' id=\"tab3primary\">\n                                <div class=\"row-fluid table-responsive\">\n                                    <table id=\"Table3\" class=\"table_style table table-striped table-bordered tablestyle\"\n                                           rules=\"all\" style=\"width: 100%; border-collapse: collapse;\" cellspacing=\"0\">\n                                        <tr>\n                                            <td align=\"right\">\n                                                <select name=\"ctl00$MainContent$ddlGraphType\" onchange=\"javascript:setTimeout(&#39;__doPostBack(\\&#39;ctl00$MainContent$ddlGraphType\\&#39;,\\&#39;\\&#39;)&#39;, 0)\" id=\"MainContent_ddlGraphType\">\n                                                    <option selected=\"selected\" value=\"2\">Line</option>\n                                                    <option value=\"1\">Bar</option>\n                                                    <option value=\"3\">Bar - Horizontal</option>\n\n                                                </select>\n                                            </td>\n                                        </tr>\n                                        <tr>\n                                            <td align=\"center\">\n                                                <img id=\"MainContent_chartCrop\" src=\"/CMDashBoard/UserInterface/Power/ChartImg.axd?i=charts_1/chart_1_0.png&amp;g=e3a69e99b08349cc83f27d9ddda4249b\" alt=\"\" usemap=\"#MainContent_chartCropImageMap\" style=\"height:350px;width:750px;border-width:0px;\" />\n                                                <map name=\"MainContent_chartCropImageMap\" id=\"MainContent_chartCropImageMap\">\n\n                                                    <area shape=\"poly\" coords=\"454,158,495,258,509,258,468,158\" title=\"0\" alt=\"0\" />\n                                                    <area shape=\"poly\" coords=\"379,48,420,51,420,65,379,62,413,58,454,158,468,158,427,58\" title=\"168\" alt=\"168\" />\n                                                    <area shape=\"poly\" coords=\"297,44,338,46,338,60,297,58,338,46,379,48,379,62,338,60\" title=\"172\" alt=\"172\" />\n                                                    <area shape=\"poly\" coords=\"215,39,256,41,256,55,215,53,256,41,297,44,297,58,256,55\" title=\"176\" alt=\"176\" />\n                                                    <area shape=\"poly\" coords=\"174,37,215,39,215,53,174,51\" 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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/IN_EA/interregional_exchanges.json",
    "content": "[\n    {\n        \"Id\": 143036,\n        \"Element\": \"765KV-NEW RANCHI-DHARMAJAYAGARH\",\n        \"Type\": \"Import/Export between EAST REGION and WEST REGION\",\n        \"PeakMW\": \"986\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"872\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"1591\",\n        \"ExportMW\": \"0\",\n        \"ImportMU\": \"24.31\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"24.31\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143037,\n        \"Element\": \"400KV-RANCHI-SIPAT(D/C)\",\n        \"Type\": \"Import/Export between EAST REGION and WEST REGION\",\n        \"PeakMW\": \"179\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"130\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"363\",\n        \"ExportMW\": \"-83\",\n        \"ImportMU\": \"4.66\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"4.66\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143038,\n        \"Element\": \"765KV-ANGUL-SRIKAKULAM\",\n        \"Type\": \"Import/Export between EAST REGION and SOUTH REGION\",\n        \"PeakMW\": \"-1797\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-1189\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"-2496\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-38.76\",\n        \"NET\": \"-38.76\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143039,\n        \"Element\": \"765KV-Sasaram-FATEHPUR\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-159\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-174\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"369\",\n        \"ExportMW\": \"-242\",\n        \"ImportMU\": \"0.62\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"0.62\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143040,\n        \"Element\": \"400KV-Sasaram-Allahabad\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-67\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-59\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"36\",\n        \"ExportMW\": \"-93\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-0.51\",\n        \"NET\": \"-0.51\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143041,\n        \"Element\": \"400KV-Pusauli-Varanasi\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-41\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-45\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"-143\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-1.91\",\n        \"NET\": \"-1.91\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143042,\n        \"Element\": \"GAZUWAKA HVDC\",\n        \"Type\": \"Import/Export between EAST REGION and SOUTH REGION\",\n        \"PeakMW\": \"-230\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-230\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"-235\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-5.11\",\n        \"NET\": \"-5.11\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143043,\n        \"Element\": \"220KV-BALIMELA-UPPER-SILERRU\",\n        \"Type\": \"Import/Export between EAST REGION and SOUTH REGION\",\n        \"PeakMW\": \"0\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"0\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"0\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"0\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143044,\n        \"Element\": \"132KV-NAGARUNTARI-RIHAND\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"0\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"0\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"0\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"0\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143045,\n        \"Element\": \"220KV-ALIPURDUAR-Salakati\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH_EAST REGION\",\n        \"PeakMW\": \"-99\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-129\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"-151\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-2.69\",\n        \"NET\": \"-2.69\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143046,\n        \"Element\": \"132KV-Geylegphu-Salakati\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH_EAST REGION\",\n        \"PeakMW\": \"0\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"0\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"0\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-0.68\",\n        \"NET\": \"-0.68\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143047,\n        \"Element\": \"132KV-Deothang-Rangia\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH_EAST REGION\",\n        \"PeakMW\": \"0\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"0\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"0\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-0.25\",\n        \"NET\": \"-0.25\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143048,\n        \"Element\": \"TALCHER STG-II I/C\",\n        \"Type\": \"Import/Export between EAST REGION and SOUTH REGION\",\n        \"PeakMW\": \"117\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"134\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"174\",\n        \"ExportMW\": \"-462\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-3.01\",\n        \"NET\": \"-3.01\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143049,\n        \"Element\": \"765KV-JHARSUGUDA-Raipur (Durg)\",\n        \"Type\": \"Import/Export between EAST REGION and WEST REGION\",\n        \"PeakMW\": \"-22\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-136\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"189\",\n        \"ExportMW\": \"-325\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-1.26\",\n        \"NET\": \"-1.26\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143050,\n        \"Element\": \"400KV-Naubatpur (Bihar)-Balia\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-323\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-167\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"309\",\n        \"ExportMW\": \"-432\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-0.5\",\n        \"NET\": \"-0.5\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143051,\n        \"Element\": \"400KV-Godda_TPS-Rahanpur (Bangladesh)\",\n        \"Type\": \"Import/Export between EAST REGION and BANGLADESH\",\n        \"PeakMW\": \"0\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"0\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"0\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"0\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143052,\n        \"Element\": \"HVDC ALIPURDUAR-Agra\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-1000\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-1500\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"-1501\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-32.36\",\n        \"NET\": \"-32.36\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143053,\n        \"Element\": \"400KV-MUZAFFARPUR-GORAKHPUR\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-562\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-306\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"373\",\n        \"ExportMW\": \"-668\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-2.56\",\n        \"NET\": \"-2.56\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143054,\n        \"Element\": \"400KV-PATNA-Balia\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-331\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-193\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"232\",\n        \"ExportMW\": \"-427\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-1.2\",\n        \"NET\": \"-1.2\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143055,\n        \"Element\": \"400KV-BIHARSARIFF-Balia\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-100\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"35\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"406\",\n        \"ExportMW\": \"-172\",\n        \"ImportMU\": \"3.56\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"3.56\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143056,\n        \"Element\": \"400KV-BINAGURI-BONGAIGAON\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH_EAST REGION\",\n        \"PeakMW\": \"-505\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-625\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"-702\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-13.04\",\n        \"NET\": \"-13.04\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143057,\n        \"Element\": \"400KV-ALIPURDUAR-BONGAIGAON\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH_EAST REGION\",\n        \"PeakMW\": \"-487\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-545\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"-665\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-11.88\",\n        \"NET\": \"-11.88\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143058,\n        \"Element\": \"132KV-KARMANASA-SAHUPURI\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-54\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-29\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"-56\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"0\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143059,\n        \"Element\": \"132KV-KARMANASA-CHANDAULI\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"0\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"0\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"0\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"0\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143060,\n        \"Element\": \"132KV-GARWAH-RIHAND\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"30\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"0\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"30\",\n        \"ExportMW\": \"0\",\n        \"ImportMU\": \"0.78\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"0.78\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143061,\n        \"Element\": \"400KV-MOTIHARI-GORAKHPUR\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-351\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-193\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"206\",\n        \"ExportMW\": \"-392\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-2.05\",\n        \"NET\": \"-2.05\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143062,\n        \"Element\": \"765KV-GAYA-VARANASI\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-61\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-27\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"648\",\n        \"ExportMW\": \"-136\",\n        \"ImportMU\": \"4.49\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"4.49\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143063,\n        \"Element\": \"765KV-GAYA-Balia\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-563\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-496\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"64\",\n        \"ExportMW\": \"-678\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-6.71\",\n        \"NET\": \"-6.71\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143064,\n        \"Element\": \"400KV-BIHARSARIFF-VARANASI\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-107\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-59\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"407\",\n        \"ExportMW\": \"-164\",\n        \"ImportMU\": \"2.67\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"2.67\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143065,\n        \"Element\": \"220KV-KARMANASA-SAHUPURI\",\n        \"Type\": \"Import/Export between EAST REGION and NORTH REGION\",\n        \"PeakMW\": \"-113\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-78\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"19\",\n        \"ExportMW\": \"-134\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-1.18\",\n        \"NET\": \"-1.18\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143066,\n        \"Element\": \"220KV-BUDHIPADAR-RAIGARH\",\n        \"Type\": \"Import/Export between EAST REGION and WEST REGION\",\n        \"PeakMW\": \"-44\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-44\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"0\",\n        \"ExportMW\": \"-44\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-0.58\",\n        \"NET\": \"-0.58\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143067,\n        \"Element\": \"220KV-BUDHIPADAR-KORBA\",\n        \"Type\": \"Import/Export between EAST REGION and WEST REGION\",\n        \"PeakMW\": \"72\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"48\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"124\",\n        \"ExportMW\": \"0\",\n        \"ImportMU\": \"2.01\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"2.01\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143068,\n        \"Element\": \"400KV-JHARSUGUDA-RAIGARH\",\n        \"Type\": \"Import/Export between EAST REGION and WEST REGION\",\n        \"PeakMW\": \"-122\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-156\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"121\",\n        \"ExportMW\": \"-311\",\n        \"ImportMU\": \"0\",\n        \"ExportMU\": \"-2.53\",\n        \"NET\": \"-2.53\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 143069,\n        \"Element\": \"765KV-JHARSUGUDA-DHARMAJAYAGARH\",\n        \"Type\": \"Import/Export between EAST REGION and WEST REGION\",\n        \"PeakMW\": \"863\",\n        \"PeakMWTime\": \"19:00 Hrs\",\n        \"OffPeakMW\": \"-112\",\n        \"OffPeakMWTime\": \"14:00 Hrs\",\n        \"ImportMW\": \"1873\",\n        \"ExportMW\": \"-241\",\n        \"ImportMU\": \"22.05\",\n        \"ExportMU\": \"0\",\n        \"NET\": \"22.05\",\n        \"Date\": \"2023-06-25\"\n    }\n]"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/IN_EA/transnational_exchanges.json",
    "content": "[\n    {\n        \"Id\": 13156,\n        \"Region\": \"BANGLADESH\",\n        \"ScheduledEnergyExchangeMU\": \"-22.51\",\n        \"ActualEnergyExchangeMU\": \"-22.483\",\n        \"DayPeakMW\": \"-940\",\n        \"DayMinMW\": \"-818\",\n        \"DayAverageMW\": \"-936.79\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 13157,\n        \"Region\": \"BHUTAN\",\n        \"ScheduledEnergyExchangeMU\": \"20.83\",\n        \"ActualEnergyExchangeMU\": \"18.474\",\n        \"DayPeakMW\": \"1408.14\",\n        \"DayMinMW\": \"0\",\n        \"DayAverageMW\": \"769.75\",\n        \"Date\": \"2023-06-25\"\n    },\n    {\n        \"Id\": 13158,\n        \"Region\": \"NEPAL\",\n        \"ScheduledEnergyExchangeMU\": \"7.5\",\n        \"ActualEnergyExchangeMU\": \"6.58\",\n        \"DayPeakMW\": \"393\",\n        \"DayMinMW\": \"211\",\n        \"DayAverageMW\": \"274.17\",\n        \"Date\": \"2023-06-25\"\n    }\n]"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/IN_HP.html",
    "content": "<div class=\"row\">\n\t<div class=\"col-md-12 col-sm-12\">\n\t\t<div class=\"print-none top-section-bp mt-10\">\n\t\t\t<div>\n\t\t\t\t<a href=\"https://hpsldc.com\" rel=\"nofollow\">Home</a>&nbsp;&nbsp;&#187;&nbsp;&nbsp;Scheduling\n\t\t\t\t&nbsp;&nbsp;&#187;&nbsp;&nbsp; <a href=\"https://hpsldc.com/intra-state-reports\">\n\t\t\t\t\tIntra State Power Transaction\n\t\t\t\t</a>\n\t\t\t</div>\n\t\t</div>\n\t\t<div class=\"print-none row mb-20 con-tain\" style=\"margin-top: -20px;\">\n\t\t\t<div class=\"col-12 col-sm-12 col-md-12 col-lg-12 col-xl-12 text-center\">\n\t\t\t\t<h1 class=\"pseudo_border\">Intra State Power Transaction (Real Time data​)</h1>\n\t\t\t</div>\n\t\t</div>\n\t\t<div class=\"both_m_y viewsch-header\" style=\"width: auto!important;\">\n\t\t\t<form method=\"post\" action=\"\" class=\"flex sm-flex\">\n\t\t\t\t<div class=\"year_section ml-10\">\n\t\t\t\t\t<div class=\"select_m sm-mb-5\">\n\t\t\t\t\t\t<label class=\"mb-0\">Date</label>\n\t\t\t\t\t\t<input type=\"date\" name=\"get_date\" class=\"date-pick onchange_date\" id=\"input_date\" value=\"2021-05-16\">\n                        </div>\n\t\t\t\t\t</div>\n\t\t\t\t\t<div class=\"months_section\" style=\"margin-left: 25px;\">\n\t\t\t\t\t\t<div class=\"select_m view-ml\">\n\t\t\t\t\t\t\t<label class=\"revision-lab mb-0 ml-10\">Revision</label>\n\t\t\t\t\t\t\t<select id=\"input_revision\" name=\"revision\" class=\"ml-10 revision\">\n                                                                <option  value=\"204\">204</option>\n                                                                <option selected='selected' value=\"203\">203</option>\n                                                            </select>\n\t\t\t\t\t\t\t<label class=\"print-none ml-20 mb-0\">Block</label>\n\t\t\t\t\t\t\t<select id=\"input_block\" name=\"block_no\" class=\"block_no ml-10\">\n                                                                <option selected='selected' value=\"93\">Block 93(23:00-23:15)</option>\n                                                            </select>\n\t\t\t\t\t\t</div>\n\t\t\t\t\t</div>\n\t\t\t</form>\n\t\t</div>\n\t\t<div class=\"all_table mb-20\">\n\t\t\t<div class=\"table_1\">\n\t\t\t\t<table style=\"text-align: center;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td class=\"tc\" colspan=\"2\" style=\"font-size: 16px;\">NR.HP(SCADA System) </td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 170px;\">SCHEDULEOFHP(V)</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">177.76</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 170px;\">DRAWLOFHP(X-Y)</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">111.98</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 170px;\">OD(+)/UD(-)=[(X-Y)-(V)]</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">-73.01</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 170px;\">FC(50HZ)</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">-105.95</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 170px;\">DEMANDOFHP(X-Y)+(Z)</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">915.79</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 170px;\">REGIONALLOAD(NR)</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">50814.19</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\t\t\t<div class=\"table_2\" style=\"margin-left: 10px\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td class=\"tc\" colspan=\"13\" style=\"font-size: 16px;\">(A)NR.HP(NRLDC WEB PORTAL)</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td style=\"width: 96px;\" class=\"tc\" rowspan=\"2\">NR.HPSLDC</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">ISGS</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">STOA</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">IEX</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">PXI</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">LTA</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">URS</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">RRAS</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">SCED</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">REMC</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">RTM_PXI</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">RTM_IEX</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px;\" class=\"tc\">Net SCH(V)</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">1204.66</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-495.80</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-591.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">60.30</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-0.40</td>\n\t\t\t\t\t\t\t<td class=\"tc\">177.76 </td>\n\t\t\t\t\t\t</tr>\n\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\t\t\t<div class=\"table_3\" style=\"margin-left: 10px\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td class=\"tc\" rowspan=\"2\">STATE ENTITY</td>\n\t\t\t\t\t\t\t<td colspan=\"14\" class=\"tc\" style=\"font-size: 16px;\">(B)HPSLDC.SE(HPSLDC WEB PORTAL)</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">ISGS</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">STOA</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">IEX</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">PXI</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">LTA</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">URS</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">RRAS</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">SCED</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">REMC</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">RTM_PXI</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">RTM_IEX</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">Net Sch(V)</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 90px;\">Actual(X-Y)</td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 70px;\">OD/UD</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<!-- HPSEBL -->\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">HPSEBL</td>\n\t\t\t\t\t\t\t<!-- <td class=\"tc\"></td> -->\n\t\t\t\t\t\t\t<td class=\"tc\">777.73</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-282.60</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-225.00</td>\n\t\t\t\t\t\t\t<!-- PIX -->\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">75.85</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">345.98</td>\n\n\t\t\t\t\t\t\t<!--  <td class=\"tc\"><?php// echo sprintf(\"%0.2f\",($response_data['hpseblalltotal']['net_total']+$response_data['hpsebl']['hpseblttl']+$response_data['hpsebl']['OTHERISGS']+$response_data['hpseblenergy18to31']['gohpfinalTotal'])-($response_data['hpseblalltotal']['totalisgs']));?></td> -->\n\n\t\t\t\t\t\t\t<td class=\"tc\">319.14</td>\n\n\t\t\t\t\t\t\t<!-- <td class=\"tc\"></td> -->\n\n\t\t\t\t\t\t\t<td class=\"tc\">-26.83 </td>\n\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<!-- GoHP -->\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">GoHP</td>\n\t\t\t\t\t\t\t<!-- isgs -->\n\t\t\t\t\t\t\t<!-- <td class=\"tc\"></td> -->\n\n\t\t\t\t\t\t\t<td class=\"tc\">426.93</td>\n\t\t\t\t\t\t\t<!-- stoa -->\n\t\t\t\t\t\t\t<td class=\"tc\">-154.70</td>\n\t\t\t\t\t\t\t<!-- iex -->\n\t\t\t\t\t\t\t<td class=\"tc\">-265.10</td>\n\t\t\t\t\t\t\t<!-- PIX -->\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<!-- lta -->\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<!-- urs -->\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">7.13</td>\n\n\t\t\t\t\t\t\t<!-- <td class=\"tc\"></td> -->\n\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t-4.81\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-11.94\n\t\t\t\t\t\t\t</td>\n\n\t\t\t\t\t\t\t<!-- <td class=\"tc\"><?php// echo sprintf(\"%0.2f\",$response_data['gohpDrawal']['value']-($response_data['gohpalltotal']['net_total']-$response_data['gohpalltotal']['totalisgs'])+$response_data['gohp']['gohparr'][4]['block']); ?></td> -->\n\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">OA-(Gen.)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-58.50</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-100.90</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-15.55</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-0.40</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-175.35</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-202.35</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-27.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">OA-(Cons.)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">Total</td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t1204.66 </td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t-495.80 </td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t-591.00 </td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t0.00 </td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t60.30 </td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t0.00 </td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t0.00 </td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t0.00 </td>\n\n\t\t\t\t\t\t\t<!-- Changes -->\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t-0.40 </td>\n\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t177.76 </td>\n\n\t\t\t\t\t\t\t<!--  <td class=\"tc\">-->\n\t\t\t\t\t\t\t<!--  </td> -->\n\t\t\t\t\t\t\t<!-- <td class=\"tc\"> <?php// $total_Actual_X_Y = sprintf(\"%0.2f\",(\n                          //  ($response_data['table1'][1]['value']\n                          //    -$response_data['plantgeneratordata']['total']\n                          //    - $response_data['oaCdata']['contotal']['cnetttl']\n                          //    -$response_data['gohpDrawal']['value']) \n                          //    + $response_data['plantgeneratordata']['total']\n                          //    +$response_data['oaCdata']['contotal']['cnetttl'])\n                          //    +$response_data['gohpDrawal']['value']);\n\n                           // echo $total_Actual_X_Y;?>         <!--  </td> -->\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t111.98\n\t\t\t\t\t\t\t</td>\n\n\t\t\t\t\t\t\t<td class=\"tc\">-65.77</td>\n\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\n\t\t\t<div class=\"table_4\" style=\"margin-left: 10px; height: 250px;\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td class=\"tc\" colspan=\"9\" style=\"font-size: 16px;\">(B1)ISGS(HPSLDC WEB PORTAL)</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td colspan=\"6\"></td>\n\t\t\t\t\t\t\t<td class=\"tc\" colspan=\"4\">HPSLDC.SE</td>\n\t\t\t\t\t\t\t<!-- <td colspan=\"2\">HPSLDC.SE</td> -->\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>COMPANY</td>\n\t\t\t\t\t\t\t<td>STATION</td>\n\t\t\t\t\t\t\t<td>CAPACITY(MW)</td>\n\t\t\t\t\t\t\t<td>PLANTGEN</td>\n\t\t\t\t\t\t\t<td>NR.HPSCHEDULE</td>\n\t\t\t\t\t\t\t<td>GoHPSCHEDULE</td>\n\t\t\t\t\t\t\t<td>HPSEBLSCHEDULE</td>\n\t\t\t\t\t\t\t<td style=\"width: 100px\">GoHP ISGS Sch Share in HPSEBL Sch</td>\n\t\t\t\t\t\t\t<td style=\"width: 137px\">Total HPSEBL Sch = GoHP and HPSEBL Sch</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td rowspan=\"5\">NHPC</td>\n\t\t\t\t\t\t\t<td class=\"tc\">BSIUL</td>\n\t\t\t\t\t\t\t<td class=\"tc\">(3X60)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">126.89</td>\n\t\t\t\t\t\t\t<td class=\"tc\">13.91</td>\n\t\t\t\t\t\t\t<td class=\"tc\">13.91</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">CHAMERA1</td>\n\t\t\t\t\t\t\t<td class=\"tc\">(3X180) static</td>\n\t\t\t\t\t\t\t<td class=\"tc\">528.49</td>\n\t\t\t\t\t\t\t<td class=\"tc\">76.77</td>\n\t\t\t\t\t\t\t<td class=\"tc\">61.83</td>\n\t\t\t\t\t\t\t<td class=\"tc\">14.94</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">14.94</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">CHAMERA2</td>\n\t\t\t\t\t\t\t<td class=\"tc\">(3X100)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">295.70</td>\n\t\t\t\t\t\t\t<td class=\"tc\">44.87</td>\n\t\t\t\t\t\t\t<td class=\"tc\">34.36</td>\n\t\t\t\t\t\t\t<td class=\"tc\">10.51</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">10.51</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">CHAMERA3</td>\n\t\t\t\t\t\t\t<td class=\"tc\">(3X77)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">227.20</td>\n\t\t\t\t\t\t\t<td class=\"tc\">19.09</td>\n\t\t\t\t\t\t\t<td class=\"tc\">19.09</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">PARBATI3</td>\n\t\t\t\t\t\t\t<td class=\"tc\">(4X130)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td rowspan=\"2\">SJVNL</td>\n\t\t\t\t\t\t\t<td class=\"tc\">NJPC</td>\n\t\t\t\t\t\t\t<td class=\"tc\">(6X250)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">1440.17</td>\n\t\t\t\t\t\t\t<td class=\"tc\">493.27</td>\n\t\t\t\t\t\t\t<td class=\"tc\">162.30</td>\n\t\t\t\t\t\t\t<td class=\"tc\">330.97</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">330.97</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">RAMPUR</td>\n\t\t\t\t\t\t\t<td class=\"tc\">(6X68.67)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">398.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">156.03</td>\n\t\t\t\t\t\t\t<td class=\"tc\">48.40</td>\n\t\t\t\t\t\t\t<td class=\"tc\">107.63</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">107.63</td>\n\t\t\t\t\t\t</tr>\n                        <tr>\n                            <td>UNKNOWN ISGS PLANT (added for unit test)</td>\n                            <td></td>\n                            <td></td>\n                            <td class=\"tc\">0</td>\n                            <td class=\"tc\">274.19</td>\n                            <td class=\"tc\">0</td>\n                            <td class=\"tc\">274.19</td>\n                        </tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>NTPC</td>\n\t\t\t\t\t\t\t<td class=\"tc\">KOLDAM</td>\n\t\t\t\t\t\t\t<td class=\"tc\">(4X200)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">734.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">187.46</td>\n\t\t\t\t\t\t\t<td class=\"tc\">87.04</td>\n\t\t\t\t\t\t\t<td class=\"tc\">100.43</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">100.43</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>OTHERISGS</td>\n\t\t\t\t\t\t\t<td></td>\n\t\t\t\t\t\t\t<td></td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">213.25</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">213.25</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0</td>\n\t\t\t\t\t\t\t<td class=\"tc\">213.25</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>TOTAL</td>\n\t\t\t\t\t\t\t<td></td>\n\t\t\t\t\t\t\t<td></td>\n\t\t\t\t\t\t\t<td class=\"tc\">3750.45</td>\n\t\t\t\t\t\t\t<td class=\"tc\">1204.66</td>\n\t\t\t\t\t\t\t<!-- <td class=\"tc\"></td> -->\n\t\t\t\t\t\t\t<td class=\"tc\">426.93</td>\n\t\t\t\t\t\t\t<td class=\"tc\">777.73</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">777.73</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\t\t\t<div class=\"table_5\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td style=\"width: 200px\" class=\"tc\">GENERATION OF HP(Z)</td>\n\t\t\t\t\t\t\t<td style=\"width: 70px\" class=\"tc\">MW</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>BASPA(3X100MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">109.35</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>BHABA(3X40MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">60.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>GIRI(2X30MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">18.74</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>LARJI(3X42MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">64.90</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>BASSI(4X16.5MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">60.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>MALANA(2X43MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">74.36</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>ANDHRA(3X5.65MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">14.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>GHANVI(2X11.25MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">9.22</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>KASHANG(3X65MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">40.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>Sawra Kuddu (3x37MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">37.03</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>MICROP/HMONITORED(HPSEBL)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">18.43</td>\n\t\t\t\t\t\t</tr>\n                        <tr>\n                            <td >UNKNOWN HP PLANT (added for unit test)</td>\n                            <td class=\"tc\">99.00</td>\n                        </tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>IPPsP/HMONITORED</td>\n\t\t\t\t\t\t\t<td class=\"tc\">118.01</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>MICROP/HUNMONITORED</td>\n\t\t\t\t\t\t\t<td class=\"tc\">187.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">Total</td>\n\t\t\t\t\t\t\t<td class=\"tc\">811.04</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\n\t\t\t<div class=\"table_6\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td style=\"width: 400px\" class=\"tc\" colspan=\"2\"><b class=\"bld_dsm\">DSM Rate</b>\n\t\t\t\t\t\t\t\t16-05-2021 11:04:52 PM </td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t466.68 </td>\n\t\t\t\t\t\t\t<td class=\"tc\">Paise/KWh</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\n\t\t\t<div class=\"table_7\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td\n\t\t\t\t\t\t\t\tstyle=\"width: 100px; font-weight: 600; background-color: #92278f !important;color: #fff;\">\n\t\t\t\t\t\t\t\tNRLDCFREQUENCY </td>\n\t\t\t\t\t\t\t<td class=\"tc\" style=\"width: 100px; font-weight: 600;\">\n\t\t\t\t\t\t\t\t49.95 </td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\n\n\t\t\t<div class=\"table_8\" style=\"margin-left: 10px\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td colspan=\"6\" style=\"text-align: center;font-size: 16px;\">( B2) OA-GENERATORS</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">S.No.</td>\n\t\t\t\t\t\t\t<td>HYDRO POWER PLANTS</td>\n\t\t\t\t\t\t\t<td>GENERATION</td>\n\t\t\t\t\t\t\t<td style=\"min-width:106px;\">NET SCHEDULE</td>\n\t\t\t\t\t\t\t<td>ACTUAL</td>\n\t\t\t\t\t\t\t<td>DEVIATION</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">1</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1201-OAG</b> M/s Integrated Kashang HPPCL (Kashang- 3x65 MW HEP)\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">40.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-33.20</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-38.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-4.80</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">2</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1202-OAG</b> M/s Yogindera Power Ltd (Baner Sangam- 2x2.5 MW SHEP)\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">1.99</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-1.40</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-1.89</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-0.49</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">3</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1203-OAG</b> M/s Nanti Hydro Power Pvt Ltd (Upper Nanti- 2x6.75 MW)\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">5.84</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-5.12</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-5.55</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-0.43</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">4</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1204-OAG</b> M/s Sandhya Hydro Power Projects Balargha Pvt. Ltd.\n\t\t\t\t\t\t\t\t(Balargha- 3x3 MW SHEP)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">9.61</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-7.40</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-9.13</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-1.73</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">5</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1205-OAG</b> M/s I A Hydro Energy Pvt. Ltd. (Chanju - 3x12 MW HEP)\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">15.90</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-16.50</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-15.10</td>\n\t\t\t\t\t\t\t<td class=\"tc\">1.40</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">6</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1206-OAG</b> M/s Baragarh Hydro Power Co. Pvt. Ltd. Prini (Lower\n\t\t\t\t\t\t\t\tAleo- 2x1.25 MW SHEP)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">7</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1207-OAG</b> M/s Malana Power Company Ltd (Malana-I- 2x43 MW HEP)\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">59.49</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-35.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-56.52</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-21.52</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">8</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1208-OAG</b> M/s Goodwill Energy Enterprises(Kut- 3x8 MW SHEP)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">16.99</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-16.70</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-16.14</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.56</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">9</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1209-OAG</b> M/s Kanchanjunga Power Company Pvt. Ltd. (Baragaon-\n\t\t\t\t\t\t\t\t3x8 MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">19.84</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-18.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-18.85</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-0.85</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">10</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1210-OAG</b> M/s Suryakanta Hydro Energies Pvt. Ltd. (Lower Nanti-\n\t\t\t\t\t\t\t\t2x7 MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">5.46</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-4.36</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-5.18</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-0.82</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">11</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1212-OAG</b> M/s Taranda Hydro Power Pvt. Ltd.(Rala- 2x6.5 MW)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">5.67</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-6.07</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-5.38</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.69</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">12</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1211-OAG</b> M/s Everest Power Pvt. Ltd (Malana-II HEP- 2x50 MW) S2\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">13</td>\n\t\t\t\t\t\t\t<td class=\"fix_width\"><b>1213-OAG</b> M/s Sawra Kuddu HPPCL (3x37MW HEP)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">32.22</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-31.60</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-30.61</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.99</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\"></td>\n\t\t\t\t\t\t\t<td class=\"tc\">OPGSsHYDROSUM</td>\n\t\t\t\t\t\t\t<td class=\"tc\">213.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-175.35</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-202.35</td>\n\t\t\t\t\t\t\t<td class=\"tc\">-27.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\n\t\t\t<div class=\"table_9\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td class=\"tc\" colspan=\"6\" style=\"font-size: 16px;\"> (B3) OA-CONSUMERS</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">S.No.</td>\n\t\t\t\t\t\t\t<td class=\"tc\">O.A.CONSUMER</td>\n\t\t\t\t\t\t\t<td class=\"tc\">LOAD</td>\n\t\t\t\t\t\t\t<td class=\"tc\">NET SCHEDULE</td>\n\t\t\t\t\t\t\t<td class=\"tc\">ACTUAL</td>\n\t\t\t\t\t\t\t<td class=\"tc\">DEVIATION</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">1</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0401-OAC</b> M/s ACC Ltd., Gagal Cement Works, Barmana</td>\n\t\t\t\t\t\t\t<td class=\"tc\">36.04</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">2</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0402-OAC</b> M/s UltraTech Cement Limited Unit- Bagheri\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">3</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0403-OAC</b> M/s Ambuja Cements Ltd., Unit - Suli</td>\n\t\t\t\t\t\t\t<td class=\"tc\">26.56</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">4</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0404-OAC</b> M/s Amba Shakti Ispat Ltd.</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">5</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0405-OAC</b> M/s Ambuja Cement Ltd. (Unit- Rauri)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">17.06</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">6</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0406-OAC</b> M/s Ambuja Cement Ltd. (Unit- Nalagarh)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">7</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0407-OAC</b> M/s Birla Textile Mills (A Unit of\n\t\t\t\t\t\t\t\tSutlejTextiles and Industries Ltd.)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">8.41</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">8</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0408-OAC</b> M/s H.M. Steels Ltd.</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">9</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0409-OAC</b> M/s Indorama Industries Ltd.</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">10</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0410-OAC</b> M/s INOX Air Products Ltd.</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">11</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0411-OAC</b> M/s J B Rolling Mills Ltd.</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">12</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0412-OAC</b> M/s UltraTech Cement Limited Unit- Baga Cement\n\t\t\t\t\t\t\t\tWorks</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">13</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0413-OAC</b> M/s Pasupati Spinning and Weaving Mills Ltd.\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">14</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0414-OAC</b> M/s Su-Kam Power Systems Ltd.</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">15</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0415-OAC</b> M/s Sun Pharmaceutical Industries Ltd.</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">16</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0416-OAC</b> M/s Winsome Textile Industries Ltd (Unit-I)\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">17</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0417-OAC</b> M/s Dr. Reddys Laboratories Ltd. Formulation\n\t\t\t\t\t\t\t\tBaddi-I</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">18</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0418-OAC</b> M/s Dr. Reddys Laboratories Ltd. Formulation\n\t\t\t\t\t\t\t\tBaddi -II</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">19</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0419-OAC</b> M/s Macleods Pharmaceutical Ltd.</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">20</td>\n\t\t\t\t\t\t\t<td style=\"min-width: 332px;\"><b>0420-OAC</b> M/s Winsome Textile Industries Ltd (Unit-II)\n\t\t\t\t\t\t\t</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\" colspan=\"2\">OACONSUMER`sSUM</td>\n\t\t\t\t\t\t\t<td class=\"tc\">88.07</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\t\t\t<div class=\"table_10\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td class=\"tc\" colspan=\"7\" style=\"font-size: 16px;\"> Intra State Transaction (Inside HP\n\t\t\t\t\t\t\t\tPeriphery)</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">Entity</td>\n\t\t\t\t\t\t\t<td class=\"tc\">Generation</td>\n\n\t\t\t\t\t\t\t<!--  <td class=\"tc\">M/s ACC Ltd., Gagal Cement Works, Barmana </td>\n                <td class=\"tc\">Ambuja Cement Ltd. (Unit- Rauri)</td> -->\n\t\t\t\t\t\t\t<td class=\"tc\">Actual</td>\n\t\t\t\t\t\t\t<td class=\"tc\">Injection</td>\n\t\t\t\t\t\t</tr>\n\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">Good Will</td>\n\t\t\t\t\t\t\t<td class=\"tc\">16.99</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">16.99</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\t\t\t<div class=\"table_11\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td class=\"tc\" colspan=\"4\" style=\"font-size: 16px;\">GOHP Share</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc mw-100\">Hydro Plant</td>\n\t\t\t\t\t\t\t<td class=\"tc mw-100\">Generation</td>\n\t\t\t\t\t\t\t<td class=\"tc mw-100\">GoHP Share</td>\n\t\t\t\t\t\t\t<td class=\"tc\">Injection</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"mw-410\">(1211-OAG) M/s Everest Power Pvt. Ltd (Malana-II HEP- 2x50 MW) S2</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"mw-410\">(1207-OAG) M/s Malana Power Company Ltd (Malana-I- 2x43 MW HEP</td>\n\t\t\t\t\t\t\t<td class=\"tc\">74.36</td>\n\t\t\t\t\t\t\t<td class=\"tc\">14.87</td>\n\t\t\t\t\t\t\t<td class=\"tc\">59.49</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"mw-410\">(1213-OAG) M/s Sawra Kuddu HPPCL (Sawra Kuddu 3x37MW HEP)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">37.03</td>\n\t\t\t\t\t\t\t<td class=\"tc\">4.81</td>\n\t\t\t\t\t\t\t<td class=\"tc\">32.22</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\t\t\t<div class=\"table_12\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td class=\"tc mw-450\" colspan=\"4\" style=\"font-size: 16px;\">Injection of SHP's at 400/220/32\n\t\t\t\t\t\t\t\tkV Substation LAHAL</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td>Salun + Kurwasi -2 (on 33kv Line)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">\n\t\t\t\t\t\t\t\t0.00 </td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\t\t\t<div class=\"table_add_on\">\n\t\t\t\t<table style=\"text-align: center; margin-top: 10px;\">\n\t\t\t\t\t<thead>\n\t\t\t\t\t\t<tr style=\"background-color: #92278f !important; color: #fff; font-weight: 600;\">\n\t\t\t\t\t\t\t<td class=\"tc\" colspan=\"7\" style=\"font-size: 16px;\">Sandhya</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</thead>\n\t\t\t\t\t<tbody>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc\">Entity</td>\n\t\t\t\t\t\t\t<td class=\"tc\">Generation</td>\n\t\t\t\t\t\t\t<td class=\"tc\">ACTUAL</td>\n\t\t\t\t\t\t\t<td class=\"tc\">Injection</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t\t<tr>\n\t\t\t\t\t\t\t<td class=\"tc mw-450\">M/s Sandhya Hydro Power Projects Balargha Pvt. Ltd. (Balargha- 3x3 MW\n\t\t\t\t\t\t\t\tSHEP)</td>\n\t\t\t\t\t\t\t<td class=\"tc\">9.61</td>\n\t\t\t\t\t\t\t<td class=\"tc\">0.00</td>\n\t\t\t\t\t\t\t<td class=\"tc\">9.61</td>\n\t\t\t\t\t\t</tr>\n\t\t\t\t\t</tbody>\n\t\t\t\t</table>\n\t\t\t</div>\n\t\t</div>\n\t</div>\n</div>\n\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/IN_KA_Default.html",
    "content": "<!DOCTYPE html PUBLIC \"-//W3C//DTD XHTML 1.0 Transitional//EN\" \"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd\">\n\n<html xmlns=\"http://www.w3.org/1999/xhtml\" >\n<head id=\"Head1\"><meta http-equiv=\"REFRESH\" content=\"60\" /><title>\n\tKPTCL-SLDC-HOME\n</title></head>\n\n<script type=\"text/javascript\">\n\n  var _gaq = _gaq || [];\n  _gaq.push(['_setAccount', 'UA-35486592-1']);\n  _gaq.push(['_trackPageview']);\n\n  (function() {\n    var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;\n    ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';\n    var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);\n  })();\n\n</script>\n\n<script type=\"text/javascript\">\n\n  var _gaq = _gaq || [];\n  _gaq.push(['_setAccount', 'UA-35486592-1']);\n  _gaq.push(['_trackPageview']);\n\n  (function() {\n    var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;\n    ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';\n    var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);\n  })();\n\nfunction DIV1_onclick() {\n\n}\n\n</script>\n\n<body>\n    <form method=\"post\" action=\"./Default.aspx\" id=\"form1\">\n<div class=\"aspNetHidden\">\n<input type=\"hidden\" name=\"__VIEWSTATE\" id=\"__VIEWSTATE\" value=\"/wEPDwUKMTE1ODkzMzMwOQ9kFgICAw9kFhgCAQ8PFgIeBFRleHQFEDA2LzA5LzIwMTcgMTI6NTdkZAIDDw8WAh8ABQU1MC4wMWRkAgUPDxYCHwAFAzE5MWRkAgcPDxYCHwAFBDc0MzBkZAIJDw8WAh8ABQQzMjMyZGQCCw8PFgIfAAUEMzM0NmRkAg0PDxYCHwAFAzg2NWRkAg8PDxYCHwAFBDM3MzRkZAIRDw8WAh8ABQQxNjk5ZGQCEw8PFgIfAAUDNjU3ZGQCFQ8PFgIfAAUDNjMzZGQCFw8PFgIfAAUDNTU0ZGRkDAjH4+g/IrI4OkltcrsjCsnr2DBGHco46dNFs/kpt1M=\" />\n</div>\n\n<div class=\"aspNetHidden\">\n\n\t<input type=\"hidden\" name=\"__VIEWSTATEGENERATOR\" id=\"__VIEWSTATEGENERATOR\" value=\"CA0B0334\" />\n\t<input type=\"hidden\" name=\"__EVENTVALIDATION\" id=\"__EVENTVALIDATION\" value=\"/wEdAAKcLDyghlWqtfdwLu6MvYFpESCFkFW/RuhzY1oLb/NUVLwjHU6N5aEk602GuYBIihezBbEyZpwZ+BT0RGytZi8j\" />\n</div>\n    <div>\n                <div style=\"width: 1164px; height: 113px; z-index: 1; left: 2px; position: absolute; top: 4px; text-align: center; background: #999; /* for non-css3 browsers */\nfilter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#A3E0FF', endColorstr='#16406B'); /* for IE */\nbackground: -webkit-gradient(linear, left top, left bottom, from(#A3E0FF), to(#16406B)); /* for webkit browsers */\nbackground: -moz-linear-gradient(top,  #A3E0FF,  #16406B);\" /* for firefox 3.6+ */  color: #ccffff;\">\n            <span\n                style=\"font-size: 20pt\"><span style=\"text-decoration: underline; color: #16406B;\"><strong>\n            <img align=\"right\" src=\"KPTCL-Logo.jpg\" style=\"width: 124px; height: 102px; font-weight: bold;\" />KARNATAKA POWER TRANSMISSION\n                    CORPORATION LIMITED<br />\n                </strong>\n                </span><span style=\"font-size: 16pt; color: #16406B;\"><strong>Karnataka State Load Dispatch Centre</strong><br />\n                    <span style=\"font-size: 12pt\"><span style=\"font-family: Calibri\"><span style=\"color: lightcyan\">\n                        Transmission Grid Management<br />\n                        Facilitates Inter state transfer &amp; Intra state transfer of power to Distribution\n                        Companies of Karnataka in a secure and economical manner &nbsp;</span> &nbsp; &nbsp;\n                    </span>&nbsp; &nbsp;</span><span style=\"font-size: 14pt; font-family: Sylfaen\"><em>&nbsp;</em></span></span></span></div>\n\n    </div>\n        &nbsp;\n        <div style=\"z-index: 1; left: 170px; width: 991px; position: absolute; top: 123px;\n            height: 359px; font-size: 12pt;\">\n            &nbsp;\n            <img align=\"right\" src=\"MCC.jpg\" style=\"z-index: 1; left: 682px; width: 310px; position: absolute;\n                top: 1px; height: 357px\" />\n            <table style=\"z-index: 1; left: 342px; width: 340px; position: absolute; top: 0px;\n                height: 333px; background: #999; /* for non-css3 browsers */\nfilter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#A3E0FF', endColorstr='#FFFFFF'); /* for IE */\nbackground: -webkit-gradient(linear, left top, left bottom, from(#A3E0FF), to(#FFFFFF)); /* for webkit browsers */\nbackground: -moz-linear-gradient(top,  #A3E0FF,  #FFFFFF);\" /* for firefox 3.6+ */  border=\"2\" bordercolor=\"#000099\">\n                <tr>\n                    <td colspan=\"3\" style=\"text-align: center; height: 8%; width: 303px;\">\n                        <span id=\"Label6\" style=\"font-size:Large;\">06/09/2017 12:57</span></td>\n                </tr>\n                <tr>\n                    <td height=\"10%\" style=\"font-size: 14pt; width: 160px; text-align: left\">\n                        <strong style=\"font-size: 12pt\">FREQUENCY :\n                            <span id=\"Label1\" style=\"font-size:Large;font-weight:bold;z-index: 1; left: 117px; position: absolute\">50.01</span>\n                        </strong>\n                    </td>\n                    <td height=\"10%\" style=\"font-size: 14pt; width: 160px; text-align: left\">\n                        <strong style=\"font-size: 12pt\">&nbsp;STATE UI :\n                            <span id=\"Label12\" style=\"font-size:Large;font-weight:bold;z-index: 1; left: 260px; position: absolute; top: 35px;\">191</span>\n                        </strong>\n                    </td>\n                </tr>\n                <tr>\n                    <td style=\"width: 160px; font-size: 12pt; height: 35px;\">\n                        <strong>\n                        STATE DEMAND</strong></td>\n                    <td style=\"text-align: center; height: 35px;\">\n                        <span id=\"Label5\" style=\"font-size:Larger;\">7430</span></td>\n                </tr>\n                <tr>\n                    <td style=\"width: 160px; font-size: 12pt;\" height=\"10%\">\n                        <strong>STATE GENERATION</strong></td>\n                    <td style=\"text-align: center\">\n                        <span id=\"Label2\" style=\"font-size:Larger;\">3232</span></td>\n                </tr>\n                <tr>\n                    <td style=\"width: 160px; font-size: 12pt; height: 35px;\">\n                        <strong>\n                        CGS</strong></td>\n                    <td style=\"text-align: center; height: 35px;\">\n                        <span id=\"Label3\" style=\"font-size:Larger;\">3346</span></td>\n                </tr>\n                <tr>\n                    <td style=\"width: 160px; font-size: 12pt; height: 35px;\">\n                        <strong>\n                        NCEP GENERATION</strong></td>\n                    <td style=\"text-align: center; height: 35px;\">\n                        <span id=\"Label4\" style=\"font-size:Larger;\">865</span></td>\n                </tr>\n                 <tr>\n\n                     <td colspan=\"3\" style=\"text-align: center; height: 10%; width: 303px;\">\n                        <strong>BESCOM:&nbsp; &nbsp;</strong><span id=\"Label7\" style=\"font-size:Larger;font-weight:bold;\">3734</span></td>\n                </tr>\n                <tr>\n                    <td height=\"10%\" style=\"font-size: 14pt; width: 160px; text-align: left\">\n                        <strong style=\"font-size: 12pt\">HESCOM :\n                            <span id=\"Label8\" style=\"font-size:Larger;z-index: 1; left: 121px; position: absolute\">1699</span>\n                        </strong>\n                    </td>\n                    <td style=\"height: 20px; text-align: left\">\n                        <strong>GESCOM &nbsp;:&nbsp;\n                            <span id=\"Label9\" style=\"font-size:Larger;z-index: 1; left: 285px; position: absolute\">657</span>\n                        </strong>\n                    </td>\n                </tr>\n                <tr>\n                    <td style=\"width: 160px; font-size: 14pt; text-align: left;\" height=\"10%\">\n                        <strong style=\"font-size: 12pt\">CESC :\n                            <span id=\"Label10\" style=\"font-size:Larger;z-index: 1; left: 121px; position: absolute\">633</span>\n                        </strong>\n                    </td>\n                    <td style=\"height: 20px; font-size: 12pt; text-align: left;\">\n                        <strong>MESCOM &nbsp;:\n                            <span id=\"Label11\" style=\"font-size:Larger;z-index: 1; left: 286px; position: absolute\">554</span>\n                        </strong>\n                    </td>\n                </tr>\n            </table>\n            <img align=\"left\" src=\"LDC.jpg\" style=\"z-index: 1; left: 1px; width: 339px; position: absolute;\n                top: 2px; height: 355px\" />\n        </div>\n        <div style=\"z-index: 1; left: 2px; width: 167px; position: absolute; top: 124px;\n            height: 582px;  background: #999; /* for non-css3 browsers */\nfilter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#A3E0FF', endColorstr='#FFFFFF'); /* for IE */\nbackground: -webkit-gradient(linear, left top, left bottom, from(#A3E0FF), to(#FFFFFF)); /* for webkit browsers */\nbackground: -moz-linear-gradient(top,  #A3E0FF,  #FFFFFF);\" border=\"2\" bordercolor=\"#000099\" id=\"DIV1\" language=\"javascript\" onclick=\"return DIV1_onclick()\">\n            <a id=\"HyperLink3\" href=\"Default.aspx\" style=\"display:inline-block;color:DarkBlue;border-color:White;border-style:None;font-size:Large;font-weight:normal;height:45px;width:166px;vertical-align: baseline; text-align: left\">Home</a>\n            <a id=\"HyperLink4\" href=\"StateGen.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;vertical-align: bottom; text-align: left\">Generation</a>\n            <a id=\"HyperLink5\" href=\"Snapshot.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:38px;width:166px;text-align: left\">Snapshot</a>\n            <a id=\"HyperLink6\" href=\"StateNCEP.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:36px;width:166px;text-align: left\">NCEPs</a>\n                 <a id=\"HyperLink11\" href=\"ipps.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;vertical-align: bottom; text-align: left\">Major Purchases</a>\n            <a id=\"HyperLink7\" href=\"escom.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:51px;width:166px;text-align: left\">ESCOM Wise 220kV Load</a><a id=\"HyperLink8\" href=\"Load%20curve.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:48px;width:166px;text-align: left\">State Vital Information</a>\n                    <a id=\"HyperLink9\" href=\"http://218.248.45.137:8282/LoadCurveUpload/lcdownloadview.asp\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:45px;width:166px;text-align: left\">Load Curve</a>\n            <a id=\"HyperLink1\" href=\"Load_Wind.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">Load-Wind Profile</a><br />\n            <a id=\"HyperLink2\" href=\"stnload.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:41px;width:166px;text-align: left\">ESCOMWISE 110 & 66kV Station Load</a><br />\n            <br />\n            <a id=\"HyperLink10\" href=\"http://www.imd.gov.in/pages/satmet_main.php\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:45px;width:166px;text-align: left\">Weather Today</a>\n            <a id=\"HyperLink12\" href=\"login.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:45px;width:166px;text-align: left\">Vital Information</a></div>\n\n\n        <div style=\"z-index: 1; left: 180px; width: 992px; position: absolute; top: 490px;\n            height: 12px; text-align: center\">\n            <span style=\"color: #0033cc; font-family: Calibri\">\n                <br /><div style=\"z-index: 1; left: 0px; width: 992px; position: absolute; top: 101px;\n            height: 21px; text-align: center\">\n                    <span style=\"color: #0033cc; font-family: Calibri\">\n                        <br />\n                        The State Load Despatch Center(SLDC) under KPTCL is an Apex body to ensure integrated\n                        operation of the power system in Karnataka. SLDC is responsible for the Real time\n                        Load Despatch functions, Operation and Maintenance of the SCADA System and Energy\n                        Accounting.<br />\n                    </span>\n                </div>\n                <a id=\"HyperLink13\" href=\"http:\\\\117.239.142.58\\resch\\default.aspx\" style=\"display:inline-block;color:Crimson;font-size:Large;height:40px;width:434px;text-align: left\">Karntaka Wind & Solar Forecasting and Scheduling Portal</a><img border=\"0\" src=\"new.gif\" style=\"width: 56px; height: 35px;\" /></span></div>\n\n        &nbsp;&nbsp;\n        <input name=\"TextBox1\" type=\"text\" id=\"TextBox1\" />\n\n        <img src=\"\" />\n        <img src=\"\" />\n    </form>\n</body>\n</html>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/IN_KA_StateGen.html",
    "content": "\n\n<!DOCTYPE html PUBLIC \"-//W3C//DTD XHTML 1.0 Transitional//EN\" \"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd\">\n\n<html xmlns=\"http://www.w3.org/1999/xhtml\" >\n<head><title>\n\tState Generation\n</title><meta HTTP-EQUIV=\"REFRESH\" content=\"60\" /></head>\n<body>\n    <form method=\"post\" action=\"./StateGen.aspx\" id=\"form1\">\n<div class=\"aspNetHidden\">\n<input type=\"hidden\" name=\"__VIEWSTATE\" id=\"__VIEWSTATE\" value=\"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\" />\n</div>\n\n<div class=\"aspNetHidden\">\n\n\t<input type=\"hidden\" name=\"__VIEWSTATEGENERATOR\" id=\"__VIEWSTATEGENERATOR\" value=\"4DD75090\" />\n\t<input type=\"hidden\" name=\"__EVENTVALIDATION\" id=\"__EVENTVALIDATION\" value=\"/wEdAAJeRX6M6KXlNmMubj9sCK9MESCFkFW/RuhzY1oLb/NUVN6IRLQd2AvZkKOxLi7QEL8w0g6jwIq5fQ+VTjVFYC4B\" />\n</div>\n    <div>\n                <div style=\"width: 1164px; height: 113px; z-index: 1; left: 2px; position: absolute; top: 5px; text-align: center; background: #999; /* for non-css3 browsers */\nfilter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#A3E0FF', endColorstr='#16406B'); /* for IE */\nbackground: -webkit-gradient(linear, left top, left bottom, from(#A3E0FF), to(#16406B)); /* for webkit browsers */\nbackground: -moz-linear-gradient(top,  #A3E0FF,  #16406B); /* for firefox 3.6+ */  color: #ccffff;\n            left: 2px; width: 1166px; color: #ccffff; position: absolute; top: 5px; height: 141px;\n            text-align: center\">\n            <img align=\"right\" src=\"KPTCL-Logo.jpg\" style=\"font-weight: bold; width: 134px; height: 146px\" /><span\n                style=\"font-size: 20pt\"><span style=\"color: #16406b; text-decoration: underline\"><strong>KARNATAKA\n                    POWER TRANSMISSION CORPORATION LIMITED<br />\n                    <br />\n                </strong></span><span style=\"font-size: 16pt; color: #16406b\"><strong>Karnataka State\n                    Generation<br />\n                </strong>\n                    <br />\n                    <span style=\"font-size: 12pt\"><span style=\"font-family: Calibri\"><span style=\"color: lightcyan\">\n                        Karnataka Power Corporation Limited and Major Independent Power Producers<br />\n                    </span>&nbsp; &nbsp; </span>&nbsp; &nbsp;</span><span style=\"font-size: 14pt; font-family: Sylfaen\"><em>&nbsp;</em></span></span></span></div>\n        <div style=\"z-index: 1;  background: #999; /* for non-css3 browsers */\nfilter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#A3E0FF', endColorstr='#FFFFFF'); /* for IE */\nbackground: -webkit-gradient(linear, left top, left bottom, from(#A3E0FF), to(#FFFFFF)); /* for webkit browsers */\nbackground: -moz-linear-gradient(top,  #A3E0FF,  #FFFFFF);\n            left: 2px; width: 154px; position: absolute; top: 154px; height: 696px\">\n            <a id=\"HyperLink3\" href=\"Default.aspx\" style=\"display:inline-block;color:DarkBlue;border-style:None;font-size:Large;font-weight:normal;height:45px;width:166px;vertical-align: baseline; text-align: left\">Home</a>\n            <a id=\"HyperLink4\" href=\"StateGen.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;vertical-align: bottom; text-align: left\">Generation</a>\n            <a id=\"HyperLink5\" href=\"Snapshot.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">ESCOM Sch&Actual</a>\n            <a id=\"HyperLink6\" href=\"StateNCEP.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">NCEPs</a>\n                 <a id=\"HyperLink9\" href=\"ipps.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;vertical-align: bottom; text-align: left\">Major Purchases</a>\n            <a id=\"HyperLink7\" href=\"escom.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">ESCOM Wise Load</a><br />\n            <a id=\"HyperLink8\" href=\"Load%20curve.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">State Vital Information</a>\n                <a id=\"HyperLink11\" href=\"http://218.248.45.137:8282/LoadCurveUpload/lcdownloadview.asp\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">Load Curve</a>\n            <a id=\"HyperLink1\" href=\"Load_Wind.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">Load-Wind-Solar Profile</a><br />\n            <a id=\"HyperLink10\" href=\"http://www.imd.gov.in/pages/satmet_main.php\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:45px;width:166px;text-align: left\">Weather Today</a></div>\n        <table style=\"z-index: 1; left: 168px; width: 995px; position: absolute; top: 199px;\n            height: 562px; background: #999; /* for non-css3 browsers */\nfilter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#A3E0FF', endColorstr='#FFFFFF'); /* for IE */\nbackground: -webkit-gradient(linear, left top, left bottom, from(#A3E0FF), to(#FFFFFF)); /* for webkit browsers */\nbackground: -moz-linear-gradient(top,  #A3E0FF,  #FFFFFF);\" border=\"2\" bordercolor=\"#000099\">\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px; color: #000000\">\n                    GENERATING STATIONS</td>\n                <td bgcolor=\"#3399cc\" style=\"width: 81px; text-align: center\">\n                    CAP(MW)</td>\n                <td bgcolor=\"#3399cc\" style=\"width: 104px; text-align: center\">\n                    TOTAL GENERATION</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 1</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 2</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 3</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 4</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 5</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 6</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 7</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 8</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 9</td>\n                <td bgcolor=\"#3399cc\" style=\"text-align: center\">\n                    UNIT 10</td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    RTPS</td>\n                <td style=\"width: 81px; text-align: center\">\n                    1720</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblrtptot\">152</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblrtp1\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblrtp2\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblrtp3\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblrtp4\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblrtp5\">172</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblrtp6\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblrtp7\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblrtp8\">0</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    BTPS</td>\n                <td style=\"width: 81px; text-align: center\">\n                    1700</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblbtptot\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblbtp1\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblbtp2\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblbtp3\">364</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n             <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    YTPS</td>\n                <td style=\"width: 81px; text-align: center\">\n                    1600</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"ytptot\">591</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"ytp1\">591</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"ytp2\">0</span></td>\n                \n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px; height: 21px\">\n                    SHARAVATHI</td>\n                <td style=\"width: 81px; height: 21px; text-align: center\">\n                    1035</td>\n                <td style=\"width: 104px; height: 21px; text-align: center\">\n                    <span id=\"lblshvytot\">595</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty1\">69</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty2\">68</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty3\">0</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty4\">69</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty5\">97</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty6\">69</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty7\">68</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty8\">70</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty9\">0</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshvty10\">78</span></td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px; height: 24px;\">\n                    NAGJHARI</td>\n                <td style=\"width: 81px; text-align: center; height: 24px;\">\n                    900</td>\n                <td style=\"width: 104px; text-align: center; height: 24px;\">\n                    <span id=\"lblngjtot\">517</span></td>\n                <td style=\"text-align: center; height: 24px;\">\n                    <span id=\"lblngj1\">96</span></td>\n                <td style=\"text-align: center; height: 24px;\">\n                    <span id=\"lblngj2\">114</span></td>\n                <td style=\"text-align: center; height: 24px;\">\n                    <span id=\"lblngj3\">101</span></td>\n                <td style=\"text-align: center; height: 24px;\">\n                    <span id=\"lblngj4\">99</span></td>\n                <td style=\"text-align: center; height: 24px;\">\n                    <span id=\"lblngj5\">0</span></td>\n                <td style=\"text-align: center; height: 24px;\">\n                    <span id=\"lblngj16\">104</span></td>\n                <td style=\"text-align: center; height: 24px;\">\n                </td>\n                <td style=\"text-align: center; height: 24px;\">\n                </td>\n                <td style=\"text-align: center; height: 24px;\">\n                </td>\n                <td style=\"text-align: center; height: 24px;\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    VARAHI</td>\n                <td style=\"width: 81px; text-align: center\">\n                    460</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblvrhtot\">57</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblvrh1\">14</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblvrh2\">13</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblvrh3\">14</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblvrh4\">14</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    KODSALLI</td>\n                <td style=\"width: 81px; text-align: center\">\n                    120</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblkdsltot\">116</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblkdsl1\">38</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblkdsl2\">39</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblkdsl3\">38</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px; height: 21px\">\n                    KADRA</td>\n                <td style=\"width: 81px; height: 21px; text-align: center\">\n                    150</td>\n                <td style=\"width: 104px; height: 21px; text-align: center\">\n                    <span id=\"lblkdrtot\">96</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblkdr1\">48</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblkdr2\">48</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblkdr3\">0</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    GERUSOPPA</td>\n                <td style=\"width: 81px; text-align: center\">\n                    240</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblgrsptot\">105</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblgrsp1\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblgrsp2\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblgrsp3\">53</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblgrsp4\">52</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    JOG</td>\n                <td style=\"width: 81px; text-align: center\">\n                    139.2</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lbljogtot\">71</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljog1\">10</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljog2\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljog3\">9</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljog4\">10</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljog5\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljog6\">15</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljog7\">15</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljog8\">11</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    LPH</td>\n                <td style=\"width: 81px; text-align: center\">\n                    55</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lbllphtot\">27</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbllph1\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbllph2\">27</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    SUPA</td>\n                <td style=\"width: 81px; text-align: center\">\n                    100</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblsupatot\">98</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblsupa1\">49</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblsupa2\">49</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px; height: 21px\">\n                    SHIMSHA</td>\n                <td style=\"width: 81px; height: 21px; text-align: center\">\n                    17.2</td>\n                <td style=\"width: 104px; height: 21px; text-align: center\">\n                    <span id=\"lblshimtot\">7</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshim1\">3</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                    <span id=\"lblshim2\">3</span></td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n                <td style=\"height: 21px; text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    SHIVASAMUDRA</td>\n                <td style=\"width: 81px; text-align: center\">\n                    42</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblshivtot\">38</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv1\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv2\">6</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv3\">3</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv4\">3</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv5\">3</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv6\">3</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv7\">6</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv8\">2</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv9\">5</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblshiv10\">5</span></td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    MANIDAM</td>\n                <td style=\"width: 81px; text-align: center\">\n                    9</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblmanitot\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblmani1\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblmani2\">0</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    MUNRABAD</td>\n                <td style=\"width: 81px; text-align: center\">\n                    38</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblmbdtot\">37</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblmbd1\">9</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblmbd2\">8</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblmbd3\">9</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblmbd4\"></span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>                \n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    BHADRA</td>\n                <td style=\"width: 81px; text-align: center\">\n                    39.2</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblbdratot\">23</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblbdra1\">5</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblbdra2\">5</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblbdra3\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblbdra4\">11</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblbdra5\">1</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    GHATAPRABHA</td>\n                <td style=\"width: 81px; text-align: center\">\n                    32</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblgtprtot\">32</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblgtp1\">16</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblgtp2\">16</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    ALMATTI</td>\n                <td style=\"width: 81px; text-align: center\">\n                    290</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblalmttot\">218</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblalmt1\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblalmt2\">54</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblalmt3\">53</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblalmt4\">55</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblalmt5\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblalmt6\">55</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    JINDAL</td>\n                <td style=\"width: 81px; text-align: center\">\n                    260+1200</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lbljintot\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljin1\">53</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljin2\">54</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljin3\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lbljin4\">0</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n           \n            \n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    UPCL</td>\n                <td style=\"width: 81px; text-align: center\">\n                    1200</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblupctot\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblupc1\">0</span></td>\n                <td style=\"text-align: center\">\n                    <span id=\"lblupc2\">0</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n            \n            <tr>\n                <td bgcolor=\"#3399cc\" style=\"width: 137px\">\n                    TOTAL</td>\n                <td style=\"width: 81px; text-align: center\">\n                    11336.6</td>\n                <td style=\"width: 104px; text-align: center\">\n                    <span id=\"lblstategen\" style=\"font-size:Larger;font-weight:bold;\">2942</span></td>\n                <td style=\"text-align: center\">\n                </td>\n                <td>\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n                <td style=\"text-align: center\">\n                </td>\n            </tr>\n        </table>\n        <div style=\"z-index: 1; left: 169px; width: 157px; position: absolute; top: 155px;\n            height: 42px; background-color: #3399cc; text-align: center\">\n            <div style=\"z-index: 1; left: 157px; width: 228px; position: absolute; top: 0px;\n                height: 42px; background-color: #3399cc; text-align: center\">\n                <div style=\"z-index: 1; left: 571px; width: 267px; position: absolute; top: 0px;\n                    height: 42px; background-color: #3399cc; text-align: center\">\n                    <strong>TOTAL GENERATION </strong>:\n                    <span id=\"lbltotgen\" style=\"font-size:Larger;font-weight:bold;\">6215</span>MW</div>\n                <strong>\n                   \n                FREQUENCY</strong> :\n                <span id=\"lblfreq\" style=\"font-weight:bold;\">50.04</span>\n                Hz</div>\n            <span id=\"lbldate\">09/09/2021 23:30:37</span></div>\n        <input name=\"TextBox1\" type=\"text\" id=\"TextBox1\" />\n        <div style=\"z-index: 1; left: 711px; width: 186px; position: absolute; top: 155px;\n                    height: 42px; background-color: #3399cc; text-align: center\">\n            <span style=\"font-size: 14pt\"><strong>\n            NCEP</strong></span> :\n            <span id=\"lblncep\" style=\"font-weight:bold;\">2101</span>\n            MW</div>\n        <div style=\"z-index: 1; left: 554px; width: 158px; position: absolute; top: 155px;\n                    height: 42px; background-color: #3399cc; text-align: center\">\n            <strong><span style=\"font-size: 14pt\">\n            CGS</span></strong> :\n            <span id=\"lblcgs\" style=\"font-weight:bold;\">1207</span>\n        MW\n           \n    </form>\n</body>\n</html>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/IN_KA_StateNCEP.html",
    "content": "\n\n<!DOCTYPE html PUBLIC \"-//W3C//DTD XHTML 1.0 Transitional//EN\" \"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd\">\n\n<html xmlns=\"http://www.w3.org/1999/xhtml\" >\n<head><meta HTTP-EQUIV=\"REFRESH\" content=\"60\" /><title>\n\tState NCEP\n</title></head>\n<body>\n    <form method=\"post\" action=\"./StateNCEP.aspx\" id=\"form1\">\n<div class=\"aspNetHidden\">\n<input type=\"hidden\" name=\"__VIEWSTATE\" id=\"__VIEWSTATE\" value=\"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\" />\n</div>\n\n<div class=\"aspNetHidden\">\n\n\t<input type=\"hidden\" name=\"__VIEWSTATEGENERATOR\" id=\"__VIEWSTATEGENERATOR\" value=\"93646EAF\" />\n</div>\n    <div>\n        <div style=\"z-index: 1; background: #999; filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#A3E0FF', endColorstr='#16406B');\n            left: 2px; width: 1222px; color: #ccffff; position: absolute; top: 5px; height: 131px;\n            text-align: center\">\n            <img align=\"right\" src=\"KPTCL-Logo.jpg\" style=\"font-weight: bold; width: 134px; height: 146px\" /><span\n                style=\"font-size: 20pt\"><span style=\"color: #16406b; text-decoration: underline\"><strong>KARNATAKA\n                POWER TRANSMISSION CORPORATION LIMITED<br />\n                    <br />\n                </strong></span><span style=\"font-size: 16pt; color: #16406b\"><strong>Karnataka NCEP Snapshot<br />\n                </strong><span style=\"font-size: 12pt\"><span style=\"font-family: Calibri\"><span style=\"color: lightcyan\">\n                    <br />\n                    State ESCOM Snapshot<br />\n                </span>&nbsp; &nbsp; </span>&nbsp; &nbsp;</span><span style=\"font-size: 14pt; font-family: Sylfaen\"><em>&nbsp;</em></span></span></span></div>\n    \n    </div>\n        <table style=\"z-index: 1; left: 165px; width: 1061px; position: absolute; top: 194px;\n            height: 355px; text-align: center;  background: #999; /* for non-css3 browsers */\nfilter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#A3E0FF', endColorstr='#FFFFFF'); /* for IE */\nbackground: -webkit-gradient(linear, left top, left bottom, from(#A3E0FF), to(#FFFFFF)); /* for webkit browsers */\nbackground: -moz-linear-gradient(top,  #A3E0FF,  #FFFFFF);\" border=\"2\" bordercolor=\"#000099\">\n            <tr>\n                <td style=\"width: 168px\">\n                    <strong>\n                    ESCOMS</strong></td>\n                <td style=\"width: 181px\">\n                    <strong>\n                    BIO-MASS<br />\n                        (140 MW)</strong></td>\n                <td style=\"width: 161px\">\n                    <strong>\n                    COGEN<br />\n                        (1520 MW)</strong></td>\n                <td style=\"width: 157px\">\n                    <strong>\n                    MINI-HYDRO<br />\n                        (846 MW)</strong></td>\n                <td style=\"width: 187px\">\n                    <strong>\n                    WIND<br />\n                        (4794.745 MW)</strong></td>\n                <td style=\"width: 169px\">\n                    <strong>SOLAR<br />\n                        (6972.655MW)</strong></td>\n                <td style=\"width: 169px\">\n                    <strong>\n                    TOTAL<br />\n                        (13544.8MW)</strong></td>\n            </tr>\n            <tr>\n                <td style=\"width: 168px; height: 40px;\">\n                    <strong>\n                    BESCOM</strong></td>\n                <td style=\"width: 181px; height: 29px;\">\n                    <span id=\"lbl_bb\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 161px; height: 29px;\">\n                    <span id=\"lbl_bc\" style=\"font-weight:bold;\">3</span></td>\n                <td style=\"width: 157px; height: 29px;\">\n                    <span id=\"lbl_bm\" style=\"font-weight:bold;\">6</span></td>\n                <td style=\"width: 187px; height: 29px;\">\n                    <span id=\"lbl_bw\" style=\"font-weight:bold;\">355</span></td>\n                <td style=\"width: 187px; height: 29px\">\n                    <span id=\"lbl_bs\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 169px; height: 29px\">\n                    <span id=\"lbl_bt\" style=\"font-weight:bold;\">365</span></td>\n            </tr>\n            <tr>\n                <td style=\"width: 168px; height: 40px;\">\n                    <strong>\n                    MESCOM</strong></td>\n                <td style=\"width: 181px; height: 25px;\">\n                    <span id=\"lbl_mb\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 161px; height: 25px;\">\n                    <span id=\"lbl_mc\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 157px; height: 25px;\">\n                    <span id=\"lbl_mm\" style=\"font-weight:bold;\">125</span></td>\n                <td style=\"width: 187px; height: 25px;\">\n                    <span id=\"lbl_mw\" style=\"font-weight:bold;\">19</span></td>\n                <td style=\"width: 187px; height: 25px\">\n                    <span id=\"lbl_ms\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"height: 25px; width: 169px;\">\n                    <span id=\"lbl_mt\" style=\"font-weight:bold;\">145</span></td>\n            </tr>\n            <tr>\n                <td style=\"width: 168px; height: 40px;\">\n                    <strong>\n                    CESC</strong></td>\n                <td style=\"width: 181px; height: 35px;\">\n                    <span id=\"lbl_cb\" style=\"font-weight:bold;\">1</span></td>\n                <td style=\"width: 161px; height: 35px;\">\n                    <span id=\"lbl_cc\" style=\"font-weight:bold;\">47</span></td>\n                <td style=\"width: 157px; height: 35px;\">\n                    <span id=\"lbl_cm\" style=\"font-weight:bold;\">107</span></td>\n                <td style=\"width: 187px; height: 35px;\">\n                    <span id=\"lbl_cw\" style=\"font-weight:bold;\">28</span></td>\n                <td style=\"width: 169px; height: 35px;\">\n                    <span id=\"lbl_cs\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 169px; height: 35px;\">\n                    <span id=\"lbl_ct\" style=\"font-weight:bold;\">184</span></td>\n            </tr>\n            <tr>\n                <td style=\"width: 168px;height: 40px;\">          \n                    <strong>\n                    GESCOM</strong></td>\n                <td style=\"width: 181px\">\n                    <span id=\"lbl_gb\" style=\"font-weight:bold;\">16</span></td>\n                <td style=\"width: 161px\">\n                    <span id=\"lbl_gc\" style=\"font-weight:bold;\">21</span></td>\n                <td style=\"width: 157px\">\n                    <span id=\"lbl_gm\" style=\"font-weight:bold;\">156</span></td>\n                <td style=\"width: 187px\">\n                    <span id=\"lbl_gw\" style=\"font-weight:bold;\">425</span></td>\n                <td style=\"width: 169px\">\n                    <span id=\"lbl_gs\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 169px\">\n                    <span id=\"lbl_gt\" style=\"font-weight:bold;\">618</span></td>\n            </tr>\n            <tr>\n                <td style=\"width: 168px; height: 40px;\">\n                    <strong>\n                    HESCOM</strong></td>\n                <td style=\"width: 181px\">\n                    <span id=\"lbl_hb\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 161px\">\n                    <span id=\"lbl_hc\" style=\"font-weight:bold;\">4</span></td>\n                <td style=\"width: 157px\">\n                    <span id=\"lbl_hm\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 187px\">\n                    <span id=\"lbl_hw\" style=\"font-weight:bold;\">780</span></td>\n                <td style=\"width: 169px\">\n                    <span id=\"lbl_hs\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 169px\">\n                    <span id=\"lbl_ht\" style=\"font-weight:bold;\">785</span></td>\n            </tr>\n            <tr>\n                <td style=\"width: 168px; height: 45px;\">\n                    <strong>TOTAL_IPPS</strong></td>\n                <td style=\"width: 181px; height: 45px;\">\n                    <span id=\"lbl_tb\" style=\"font-weight:bold;\">18</span></td>\n                <td style=\"width: 161px; height: 45px;\">\n                    <span id=\"lbl_tc\" style=\"font-weight:bold;\">75</span></td>\n                <td style=\"width: 157px; height: 45px;\">\n                    <span id=\"lbl_tm\" style=\"font-weight:bold;\">397</span></td>\n                <td style=\"width: 187px; height: 45px;\">\n                    <span id=\"lbl_tw\" style=\"font-weight:bold;\">1610</span></td>\n                <td style=\"width: 169px; height: 45px\">\n                    <span id=\"lbl_ts\" style=\"font-weight:bold;\">0</span></td>\n                <td style=\"width: 169px; height: 45px\">\n                    <span id=\"lbl_tt\" style=\"font-weight:bold;\">2101</span></td>\n            </tr>\n            <tr>\n                <td style=\"width: 168px; height: 40px;\">\n                    <strong style=\"color: #ff0000\">PAVAGADA SOLAR PARK<br />\n                    </strong></td>\n                <td style=\"width: 181px; height: 45px;\">\n                <strong style=\"color: #ff0000\">SECI(200MW)&nbsp;<br />\n                    <br />\n                </strong>\n                    <span id=\"lbl_seci\" style=\"color:DarkBlue;font-weight:bold;\">0</span></td>\n                <td style=\"width: 161px; height: 45px;\">\n                    <strong><span style=\"color: #ff0000\">KARNATAKA(1850MW)<br />\n                    </span></strong>\n                    <span id=\"lbl_kar_ksp\" style=\"color:DarkBlue;font-weight:bold;\">1</span></td>\n                <td style=\"width: 157px; height: 45px;\"></td>\n                <td style=\"width: 187px; height: 45px;\">\n                    </td>\n                <td style=\"width: 169px; height: 45px\">\n                    <strong style=\"color: #ff0000\"> (Including pavagada 1850MW)\n                        <br />\n                        <span id=\"lbl_kar_slr\" style=\"color:DarkBlue;font-weight:bold;\">1</span></strong></td>\n                <td style=\"width: 169px; height: 45px\">\n                    <span id=\"lbl_kar_ncep\" style=\"color:DarkBlue;font-size:X-Large;font-weight:bold;\">2103</span></td>\n            </tr>\n        </table>\n        <div style=\"z-index: 1;  background: #999; /* for non-css3 browsers */\nfilter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#A3E0FF', endColorstr='#FFFFFF'); /* for IE */\nbackground: -webkit-gradient(linear, left top, left bottom, from(#A3E0FF), to(#FFFFFF)); /* for webkit browsers */\nbackground: -moz-linear-gradient(top,  #A3E0FF,  #FFFFFF);\n            left: 1px; width: 160px; position: absolute; top: 154px; height: 562px\">\n            <a id=\"HyperLink3\" href=\"Default.aspx\" style=\"display:inline-block;color:DarkBlue;border-style:None;font-size:Large;font-weight:normal;height:45px;width:166px;vertical-align: baseline; text-align: left\">Home</a>\n            <a id=\"HyperLink4\" href=\"StateGen.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;vertical-align: bottom; text-align: left\">Generation</a>\n            <a id=\"HyperLink5\" href=\"Snapshot.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">ESCOM Sch&Actual</a>\n            <a id=\"HyperLink6\" href=\"StateNCEP.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">NCEPs</a>\n                \n            <a id=\"HyperLink7\" href=\"escom.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">ESCOM Wise Load</a><br />\n            <a id=\"HyperLink8\" href=\"Load%20curve.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">State Vital Information</a>\n                <a id=\"HyperLink9\" href=\"http://218.248.45.137:8282/LoadCurveUpload/lcdownloadview.asp\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">Load Curve</a>\n            <a id=\"HyperLink1\" href=\"Load_Wind.aspx\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:44px;width:166px;text-align: left\">Load-Wind-Solar Profile</a><br />\n            <a id=\"HyperLink10\" href=\"http://www.imd.gov.in/pages/satmet_main.php\" style=\"display:inline-block;color:DarkBlue;font-size:Large;height:45px;width:166px;text-align: left\">Weather Today</a></div>\n\n        <div style=\"z-index: 1; left: 164px; width: 1063px; position: absolute; top: 154px;\n            height: 41px; background-color: steelblue; text-align: center\">\n            <span style=\"font-size: 20pt\">\n                <span id=\"Label1\" style=\"font-size:Large;z-index: 1; left: 10px;\n                    position: absolute; top: 5px\">09/09/2021 23:30:01</span>\n                <span style=\"font-size: 16pt\">&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;\n                    &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;\n                    &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;\n                    <span style=\"text-decoration: underline\">KARNATAKA NCEPs</span></span>\n                <span id=\"Label2\" style=\"display:inline-block;font-size:Large;height:20px;width:49px;z-index: 1;\n                        left: 999px; position: absolute; top: 7px\">50.03</span>\n                &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;\n                &nbsp; &nbsp; &nbsp; &nbsp; <span style=\"font-size: 16pt\">FREQUENCY:&nbsp;</span></span></div>\n    </form>\n</body>\n</html>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JAO/core_external_atc.json",
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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JAO/nordic_max_bflow.json",
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    "content": "t@CXV,t@CXV,Ώ۔N\n20250415,22:41:31,20250415\nt,ԃR},ԑ_,ԑ_,GAv(kWh),GAd(kWh),GÁEzd(kWh)\n20250415,1,0:00,0:30,1434000,1731270,164500\n20250415,2,0:30,1:00,1407500,1706840,175000\n20250415,3,1:00,1:30,1439000,1737470,185000\n20250415,4,1:30,2:00,1452000,1750250,183000\n20250415,5,2:00,2:30,1486500,1773685,204000\n20250415,6,2:30,3:00,1524000,1772905,220000\n20250415,7,3:00,3:30,1566000,1780515,229500\n20250415,8,3:30,4:00,1599500,1780165,224000\n20250415,9,4:00,4:30,1605500,1787915,208500\n20250415,10,4:30,5:00,1584000,1791690,202000\n20250415,11,5:00,5:30,1592500,1790815,224500\n20250415,12,5:30,6:00,1573500,1782310,217500\n20250415,13,6:00,6:30,1592500,1779895,250500\n20250415,14,6:30,7:00,1620500,1842920,295000\n20250415,15,7:00,7:30,1608500,1789130,361000\n20250415,16,7:30,8:00,1655500,1842435,441000\n20250415,17,8:00,8:30,1741000,2055705,492000\n20250415,18,8:30,9:00,1805000,2136465,557500\n20250415,19,9:00,9:30,1867000,2214370,605500\n20250415,20,9:30,10:00,1848000,2195275,641000\n20250415,21,10:00,10:30,1837000,2290465,663000\n20250415,22,10:30,11:00,1848500,2306155,635500\n20250415,23,11:00,11:30,1868000,2325690,607500\n20250415,24,11:30,12:00,1849500,2288150,581000\n20250415,25,12:00,12:30,1789500,2112945,559000\n20250415,26,12:30,13:00,1740500,1941265,534500\n20250415,27,13:00,13:30,1729500,2000530,514500\n20250415,28,13:30,14:00,1743000,2002415,465000\n20250415,29,14:00,14:30,1716500,2036040,425500\n20250415,30,14:30,15:00,1718500,1999755,358500\n20250415,31,15:00,15:30,1734500,1994230,287000\n20250415,32,15:30,16:00,1765500,2019245,228500\n20250415,33,16:00,16:30,1752000,1915805,170500\n20250415,34,16:30,17:00,1752000,1876550,127500\n20250415,35,17:00,17:30,1729500,1842770,92000\n20250415,36,17:30,18:00,1734500,1813855,82000\n20250415,37,18:00,18:30,1737500,1855055,77000\n20250415,38,18:30,19:00,1740500,1860045,81500\n20250415,39,19:00,19:30,1722500,1857105,82000\n20250415,40,19:30,20:00,1682000,1849310,83500\n20250415,41,20:00,20:30,1636500,1830825,80500\n20250415,42,20:30,21:00,1588000,1846955,79500\n20250415,43,21:00,21:30,1536000,1775475,77000\n20250415,44,21:30,22:00,1498000,1760180,78000\n20250415,45,22:00,22:30,1477500,1663110,76000\n20250415,46,22:30,23:00,1441000,1682880,71500\n20250415,47,23:00,23:30,1461500,1729185,73000\n20250415,48,23:30,24:00,1428000,1686825,95500\n"
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    "path": "electricitymap/contrib/parsers/tests/mocks/JP-HR/yosoku_05_20250415.csv",
    "content": "2025/4/15 22:51 UPDATE\nt,ԃR},ԑ_,ԑ_,GAv(kWh),GAd(kWh),GÁEzd(kWh)\n2025/4/15,1,0:00,0:30,1279166,1615348,10380\n2025/4/15,2,0:30,1:00,1267833,1625934,10234\n2025/4/15,3,1:00,1:30,1277333,1582919,10139\n2025/4/15,4,1:30,2:00,1314250,1616994,10300\n2025/4/15,5,2:00,2:30,1355249,1601734,10850\n2025/4/15,6,2:30,3:00,1402500,1583397,11584\n2025/4/15,7,3:00,3:30,1452750,1607143,12500\n2025/4/15,8,3:30,4:00,1490000,1632214,13519\n2025/4/15,9,4:00,4:30,1518166,1663005,14679\n2025/4/15,10,4:30,5:00,1522666,1653684,16039\n2025/4/15,11,5:00,5:30,1543083,1684053,17550\n2025/4/15,12,5:30,6:00,1524750,1669374,15342\n2025/4/15,13,6:00,6:30,1521083,1668204,25825\n2025/4/15,14,6:30,7:00,1512166,1695457,42420\n2025/4/15,15,7:00,7:30,1520333,1735491,64839\n2025/4/15,16,7:30,8:00,1543083,1684360,96027\n2025/4/15,17,8:00,8:30,1613666,1724993,110154\n2025/4/15,18,8:30,9:00,1692500,1638665,138400\n2025/4/15,19,9:00,9:30,1742166,1796277,214402\n2025/4/15,20,9:30,10:00,1767250,1840567,250897\n2025/4/15,21,10:00,10:30,1752083,1798447,291212\n2025/4/15,22,10:30,11:00,1755583,1956040,316431\n2025/4/15,23,11:00,11:30,1766750,1921969,326005\n2025/4/15,24,11:30,12:00,1754500,2007669,420656\n2025/4/15,25,12:00,12:30,1673416,1808146,355885\n2025/4/15,26,12:30,13:00,1655500,1774943,330934\n2025/4/15,27,13:00,13:30,1732666,1836095,273208\n2025/4/15,28,13:30,14:00,1759333,1795848,142432\n2025/4/15,29,14:00,14:30,1776750,1742821,105090\n2025/4/15,30,14:30,15:00,1792000,1783116,96655\n2025/4/15,31,15:00,15:30,1768083,1776725,64378\n2025/4/15,32,15:30,16:00,1786083,1773309,47385\n2025/4/15,33,16:00,16:30,1798000,1822144,39609\n2025/4/15,34,16:30,17:00,1792250,1826933,36262\n2025/4/15,35,17:00,17:30,1764750,1688472,56353\n2025/4/15,36,17:30,18:00,1757833,1793825,45377\n2025/4/15,37,18:00,18:30,1763416,1866582,32151\n2025/4/15,38,18:30,19:00,1778666,1941347,31721\n2025/4/15,39,19:00,19:30,1747166,1938651,31520\n2025/4/15,40,19:30,20:00,1723666,1856795,31344\n2025/4/15,41,20:00,20:30,1693750,1763599,30839\n2025/4/15,42,20:30,21:00,1670916,1754976,29565\n2025/4/15,43,21:00,21:30,1654916,1771709,27994\n2025/4/15,44,21:30,22:00,1639750,1721953,26590\n2025/4/15,45,22:00,22:30,1616833,1685523,25310\n2025/4/15,46,22:30,23:00,1574250,1666011,23910\n2025/4/15,47,23:00,23:30,1548333,1675431,22565\n2025/4/15,48,23:30,24:00,1515666,1667887,21450\n"
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  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JP-KN/20250416_yosoku.csv",
    "content": "\\li`|QEa|QEa|Tj\nt@CXV,t@CXV,Ώ۔N\n20250416,19:43:11,20250416\nt,ԃR},ԑсQ,ԑсQ,GAv,GAd,GÁEz\n20250416,1,00:00,00:30,6379000,6391000,30064\n20250416,2,00:30,01:00,6221000,6228000,28064\n20250416,3,01:00,01:30,6055000,6072000,28079\n20250416,4,01:30,02:00,6045000,6019000,25907\n20250416,5,02:00,02:30,6120000,6072000,19771\n20250416,6,02:30,03:00,6280000,6309000,18759\n20250416,7,03:00,03:30,6444000,6431000,9718\n20250416,8,03:30,04:00,6556000,6637000,8869\n20250416,9,04:00,04:30,6575000,6715000,7432\n20250416,10,04:30,05:00,6525000,6796000,6218\n20250416,11,05:00,05:30,6546000,6658000,6060\n20250416,12,05:30,06:00,6554000,6782000,11936\n20250416,13,06:00,06:30,6629000,6843000,151710\n20250416,14,06:30,07:00,6770000,6762000,377204\n20250416,15,07:00,07:30,6987000,6387000,668400\n20250416,16,07:30,08:00,7213000,6328000,1235636\n20250416,17,08:00,08:30,7572000,6616000,1637220\n20250416,18,08:30,09:00,7928000,6899000,1894620\n20250416,19,09:00,09:30,8146000,6835000,2082243\n20250416,20,09:30,10:00,8254000,7126000,2148752\n20250416,21,10:00,10:30,8230000,7172000,2334587\n20250416,22,10:30,11:00,8170000,7078000,2626083\n20250416,23,11:00,11:30,8053000,6872000,2703977\n20250416,24,11:30,12:00,7947000,6614000,2708247\n20250416,25,12:00,12:30,7682000,6523000,2618547\n20250416,26,12:30,13:00,7618000,6408000,2628371\n20250416,27,13:00,13:30,7804000,6573000,2664997\n20250416,28,13:30,14:00,7796000,6639000,2668480\n20250416,29,14:00,14:30,7761000,6712000,2558152\n20250416,30,14:30,15:00,7739000,6892000,2319605\n20250416,31,15:00,15:30,7686000,7111000,2013836\n20250416,32,15:30,16:00,7714000,7023000,1647880\n20250416,33,16:00,16:30,7721000,6947000,1241077\n20250416,34,16:30,17:00,7679000,6904000,839665\n20250416,35,17:00,17:30,7574000,7083000,475352\n20250416,36,17:30,18:00,7726000,7007000,198058\n20250416,37,18:00,18:30,7837000,7174000,37936\n20250416,38,18:30,19:00,7763000,7026000,7205\n20250416,39,19:00,19:30,7708000,6989000,8183\n20250416,40,19:30,20:00,7692000,7043000,8844\n20250416,41,20:00,20:30,7565000,6961000,7962\n20250416,42,20:30,21:00,7435000,7024000,7554\n20250416,43,21:00,21:30,7306000,7176000,6904\n20250416,44,21:30,22:00,7094000,7073000,6026\n20250416,45,22:00,22:30,6883000,7025000,4602\n20250416,46,22:30,23:00,6717000,6899000,4269\n20250416,47,23:00,23:30,6571000,6782000,3692\n20250416,48,23:30,24:00,6329000,6534000,3250"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JP-KY/21110_TSO9_0_20250407.csv",
    "content": "t@CXV,t@CXV,Ώ۔N\n20250407,22:50:00,20250407\nt,ԃR},ԑсQ,ԑсQ,GAv,GAd,GÁEzd\n-,-,-,-,v,v,v\n20250407,1,0:00,0:30,3658000,4032000,27346\n20250407,2,0:30,1:00,3575000,3937000,28044\n20250407,3,1:00,1:30,3550000,3936000,25345\n20250407,4,1:30,2:00,3609500,3920500,22662\n20250407,5,2:00,2:30,3753500,4038500,24287\n20250407,6,2:30,3:00,3922000,4237000,23128\n20250407,7,3:00,3:30,4107000,4368000,20699\n20250407,8,3:30,4:00,4264500,4556500,18670\n20250407,9,4:00,4:30,4378000,4639000,16199\n20250407,10,4:30,5:00,4452500,4706500,15964\n20250407,11,5:00,5:30,4482500,4832500,16246\n20250407,12,5:30,6:00,4486500,4809500,15952\n20250407,13,6:00,6:30,4615000,4978000,74769\n20250407,14,6:30,7:00,4542500,4954500,352465\n20250407,15,7:00,7:30,4410000,5027000,887525\n20250407,16,7:30,8:00,4228500,4935500,1558527\n20250407,17,8:00,8:30,4179500,5308500,2179667\n20250407,18,8:30,9:00,4388500,5803500,2734223\n20250407,19,9:00,9:30,4530000,5934000,3041974\n20250407,20,9:30,10:00,4589500,6008500,3146221\n20250407,21,10:00,10:30,4612000,6031000,3297733\n20250407,22,10:30,11:00,4627000,6196000,3487060\n20250407,23,11:00,11:30,4641000,6211000,3543197\n20250407,24,11:30,12:00,4650000,6219000,3495987\n20250407,25,12:00,12:30,4546500,6111500,3432813\n20250407,26,12:30,13:00,4400000,5965000,3344122\n20250407,27,13:00,13:30,4519000,6089000,3325779\n20250407,28,13:30,14:00,4550000,6119000,3366190\n20250407,29,14:00,14:30,4489000,6059000,3303789\n20250407,30,14:30,15:00,4427000,5992000,3201114\n20250407,31,15:00,15:30,4367500,5821000,3057361\n20250407,32,15:30,16:00,4351500,5830000,2877672\n20250407,33,16:00,16:30,4375000,5697500,2599160\n20250407,34,16:30,17:00,4422000,5352500,2000258\n20250407,35,17:00,17:30,4458500,5377000,1273207\n20250407,36,17:30,18:00,4500500,5006000,634453\n20250407,37,18:00,18:30,4560500,4755085,209710\n20250407,38,18:30,19:00,4648000,4965835,30879\n20250407,39,19:00,19:30,4700000,4756085,16544\n20250407,40,19:30,20:00,4676000,4894000,17097\n20250407,41,20:00,20:30,4600500,4786500,16200\n20250407,42,20:30,21:00,4518500,4768500,17202\n20250407,43,21:00,21:30,4432500,4640500,19024\n20250407,44,21:30,22:00,4332500,4554500,18909\n20250407,45,22:00,22:30,4244000,4525000,19397\n20250407,46,22:30,23:00,4154000,4436000,19625\n20250407,47,23:00,23:30,4073000,4402500,19881\n20250407,48,23:30,24:00,3968000,4321500,20034\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JP-ON/jukyu_yosoku_20250415.csv",
    "content": "t@CXV,t@CXV,Ώ۔N\n20250415,23:43:06,20250415\nDATE,ԃR},ԑ_,ԑ_,GAv(kWh),GAd(kWh),GÁEzd(kWh)\n2025/04/15,01,00:00,00:30,347500,347500,2392\n2025/04/15,02,00:30,01:00,342000,342000,2100\n2025/04/15,03,01:00,01:30,333500,333500,2137\n2025/04/15,04,01:30,02:00,336500,336500,2323\n2025/04/15,05,02:00,02:30,333000,333000,2499\n2025/04/15,06,02:30,03:00,349500,349500,2553\n2025/04/15,07,03:00,03:30,351500,351500,1965\n2025/04/15,08,03:30,04:00,362000,362000,1941\n2025/04/15,09,04:00,04:30,358000,358000,1925\n2025/04/15,10,04:30,05:00,366000,366000,1998\n2025/04/15,11,05:00,05:30,362000,362000,2162\n2025/04/15,12,05:30,06:00,362000,362000,2355\n2025/04/15,13,06:00,06:30,362000,362000,2394\n2025/04/15,14,06:30,07:00,373000,373000,9995\n2025/04/15,15,07:00,07:30,385500,385500,21002\n2025/04/15,16,07:30,08:00,395500,395500,41410\n2025/04/15,17,08:00,08:30,418000,418000,62081\n2025/04/15,18,08:30,09:00,411000,411000,83835\n2025/04/15,19,09:00,09:30,407500,407500,106307\n2025/04/15,20,09:30,10:00,416500,416500,123684\n2025/04/15,21,10:00,10:30,422500,422500,139291\n2025/04/15,22,10:30,11:00,427000,427000,150850\n2025/04/15,23,11:00,11:30,431500,431500,159357\n2025/04/15,24,11:30,12:00,440500,440500,165737\n2025/04/15,25,12:00,12:30,435500,435500,168956\n2025/04/15,26,12:30,13:00,431000,431000,169107\n2025/04/15,27,13:00,13:30,438500,438500,165581\n2025/04/15,28,13:30,14:00,438000,438000,158731\n2025/04/15,29,14:00,14:30,432500,432500,148859\n2025/04/15,30,14:30,15:00,425500,425500,136486\n2025/04/15,31,15:00,15:30,416000,416000,121433\n2025/04/15,32,15:30,16:00,411500,411500,104273\n2025/04/15,33,16:00,16:30,408500,408500,84964\n2025/04/15,34,16:30,17:00,406000,406000,64395\n2025/04/15,35,17:00,17:30,402000,402000,43626\n2025/04/15,36,17:30,18:00,400000,400000,23295\n2025/04/15,37,18:00,18:30,410000,410000,7901\n2025/04/15,38,18:30,19:00,420000,420000,337\n2025/04/15,39,19:00,19:30,428000,428000,281\n2025/04/15,40,19:30,20:00,427000,427000,260\n2025/04/15,41,20:00,20:30,422000,422000,201\n2025/04/15,42,20:30,21:00,416000,416000,152\n2025/04/15,43,21:00,21:30,387000,387000,32\n2025/04/15,44,21:30,22:00,387000,387000,32\n2025/04/15,45,22:00,22:30,374000,374000,26\n2025/04/15,46,22:30,23:00,363500,363500,9\n2025/04/15,47,23:00,23:30,357000,357000,1\n2025/04/15,48,23:30,00:00,346500,346500,1\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JP-SK/jp-sk-nuclear-html-page.html",
    "content": "\n<!DOCTYPE html>\n<html lang=\"ja\">\n<head>\n<meta charset=\"UTF-8\">\n<title>発電機出力のグラフ(3号機) | 四国電力</title>\n<meta property=\"og:title\" content=\"発電機出力のグラフ(3号機) | 四国電力\">\n<meta property=\"og:image\" content=\"https://www.yonden.co.jp/assets/img/ogp.png\">\n<meta property=\"og:type\" content=\"article\">\n<meta property=\"og:site_name\" content=\"四国電力\">\n<meta name=\"viewport\" content=\"width=1024\">\n<meta name=\"format-detection\" content=\"telephone=no\">\n<meta http-equiv=\"X-UA-Compatible\" content=\"IE=edge,chrome=1\">\n<meta name=\"copyright\" content=\"YONDEN Shikoku Electric Power CO.,Inc. / Kagawa,Japan\">\n<link href=\"/assets_sys/css/style.css\" rel=\"stylesheet\">\n<link href=\"/assets_sys/css/style.css\" rel=\"stylesheet\"><!--[if lt IE 9]>\n<script src=\"/assets/js/html5shiv.js\"></script><![endif]-->\n<script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':\nnew Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],\nj=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=\n'https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);\n})(window,document,'script','dataLayer','GTM-TG5F54X');</script>\n</head>\n<body>\n<noscript>\n<iframe src=\"https://www.googletagmanager.com/ns.html?id=GTM-TG5F54X\"\nheight=\"0\" width=\"0\" style=\"display:none;visibility:hidden\"></iframe>\n</noscript>\n<header id=\"header\" class=\"header\" role=\"banner\">\n    <div class=\"container01\">\n        <h1 class=\"l-header_logo\"><a href=\"/index.html\"><img src=\"/assets_sys/img/logo.png\" alt=\"四国電力株式会社\"/></a></h1>\n    </div>\n</header>\n\n<main role=\"main\">\n    <div class=\"container01\">\n        <ul class=\"c-breadnav\">\n            <li><a href=\"page_03.html\">現在の発電機出力</a></li>\n            <li>発電機出力のグラフ(3号機)</li>\n        </ul>\n    </div>\n    <div class=\"c-heading_container\">\n        <div class=\"container01\">\n            <h1 class=\"c-heading_lv01\">発電機出力のグラフ(3号機)</h1>\n        </div>\n    </div>\n    <div class=\"container02\">\n        <p class=\"center\"> <img src=\"ikt701da.gif?202402060021\" alt=\"\"> <img src=\"ikt701ti.gif?202402060021\" alt=\"\"> </p>\n        <div class=\"clearfix\">\n            <div class=\"float-box\" style=\"width: 537px;\">\n                <p><img src=\"ikt721-1.gif?202402060021\" border=\"0\" alt=\"現在の発電機出力\"></p>\n            </div>\n            <div class=\"float-box\" style=\"width: 193px; margin-left: 20px;\">\n                <div class=\"word\" style=\"height: 239px;\">\n                    <h2>用語解説</h2>\n                    <ul class=\"word-list\">\n                        <li><a href=\"../word/page_01_utf8.html\" target=\"_blank\">定格熱出力一定運転とは？</a></li>\n                    </ul>\n                </div>\n            </div>\n        </div>\n        <p><img src=\"ikt722-1.gif?202402060021\" alt=\"発電機出力のグラフ一覧\" border=\"0\">\n        </p>\n    </div>\n    <div class=\"container01\">\n        <p>■運転中の蒸気弁の動作テスト、号機間の蒸気融通、復水器水室清掃作業などにより、発電機出力が低下することがあります。<br>\n           ■海水温度が高くなると、発電所の熱効率が低下するため、定格電気出力を下回ることがあります。<br>\n           ■機器点検中の場合はデータが欠測になる場合があります。<br>\n           ■実際の発電機出力は、通常の定格熱出力一定運転中は、定格電気出力と異なる場合があります。<br>\n           ■1号機については2016年5月10日に、2号機については2018年5月23日に運転終了しました。<br>\n<br>\n\n        </p>\n    </div>\n</main>\n\n<footer id=\"footer\" class=\"footer\" role=\"contentinfo\">\n<div id=\"footer_copyright\">\n    <address>\n    Copyright © YONDEN Shikoku Electric Power CO.,Inc. / Kagawa,Japan\n    </address>\n</div>\n</footer>\n</body>\n</html>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JP-SK/yosoku_today.csv",
    "content": "t@CXV,t@CXV,Ώ۔N\n20250416,19:43:35,20250416\nt,ԃR},ԑ_,ԑ_,GAv,GAd,GÁEzd\n20250416,1,0:00,0:30,1238618,1629618,48000\n20250416,2,0:30,1:00,1229043,1616343,40000\n20250416,3,1:00,1:30,1234089,1608689,34500\n20250416,4,1:30,2:00,1253627,1596027,31500\n20250416,5,2:00,2:30,1294439,1578739,24000\n20250416,6,2:30,3:00,1344312,1592412,19000\n20250416,7,3:00,3:30,1398770,1643070,16000\n20250416,8,3:30,4:00,1441026,1657626,13000\n20250416,9,4:00,4:30,1464285,1679985,10000\n20250416,10,4:30,5:00,1482785,1683185,8500\n20250416,11,5:00,5:30,1502156,1728256,5500\n20250416,12,5:30,6:00,1491496,1702296,5000\n20250416,13,6:00,6:30,1497076,1756476,51500\n20250416,14,6:30,7:00,1460652,1881352,197000\n20250416,15,7:00,7:30,1401853,1936053,324000\n20250416,16,7:30,8:00,1401805,1818605,437500\n20250416,17,8:00,8:30,1450914,1798714,532500\n20250416,18,8:30,9:00,1491293,1994493,690500\n20250416,19,9:00,9:30,1503163,2021163,841000\n20250416,20,9:30,10:00,1501067,2098967,951000\n20250416,21,10:00,10:30,1440892,2045192,1024500\n20250416,22,10:30,11:00,1442907,2042607,1027000\n20250416,23,11:00,11:30,1439190,2040490,1067500\n20250416,24,11:30,12:00,1414363,2016063,1086500\n20250416,25,12:00,12:30,1358792,1953992,1044000\n20250416,26,12:30,13:00,1366234,1962134,1038500\n20250416,27,13:00,13:30,1408591,2008091,1064000\n20250416,28,13:30,14:00,1390591,1993091,1039500\n20250416,29,14:00,14:30,1364691,1972191,989500\n20250416,30,14:30,15:00,1338575,1950575,897000\n20250416,31,15:00,15:30,1314715,1916715,788000\n20250416,32,15:30,16:00,1326540,1835140,657500\n20250416,33,16:00,16:30,1356104,1841804,564000\n20250416,34,16:30,17:00,1408900,2053500,409500\n20250416,35,17:00,17:30,1423992,2076492,249000\n20250416,36,17:30,18:00,1433044,2086344,115000\n20250416,37,18:00,18:30,1446640,2030440,33000\n20250416,38,18:30,19:00,1461961,1994561,7000\n20250416,39,19:00,19:30,1424501,1963301,7500\n20250416,40,19:30,20:00,1397758,1842058,8000\n20250416,41,20:00,20:30,1386765,1840065,8000\n20250416,42,20:30,21:00,1366055,1792555,8500\n20250416,43,21:00,21:30,1326618,1795518,9500\n20250416,44,21:30,22:00,1285621,1797621,10500\n20250416,45,22:00,22:30,1251838,1723638,11000\n20250416,46,22:30,23:00,1209863,1711863,11000\n20250416,47,23:00,23:30,1203625,1671925,11000\n20250416,48,23:30,24:00,1181973,1616273,11000\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JP-SK/yosoku_tomorrow.csv",
    "content": "t@CXV,t@CXV,Ώ۔N\n20250416,16:59:00,20250417\nt,ԃR},ԑ_,ԑ_,GAv,GAd,GÁEzd\n20250417,1,0:00,0:30,1137749,1559349,17500\n20250417,2,0:30,1:00,1113211,1528111,16500\n20250417,3,1:00,1:30,1120775,1525675,15500\n20250417,4,1:30,2:00,1139989,1521689,17000\n20250417,5,2:00,2:30,1177108,1550508,19000\n20250417,6,2:30,3:00,1231866,1548566,21000\n20250417,7,3:00,3:30,1290403,1568203,22000\n20250417,8,3:30,4:00,1332353,1592353,22500\n20250417,9,4:00,4:30,1361967,1622867,25500\n20250417,10,4:30,5:00,1373660,1622360,30500\n20250417,11,5:00,5:30,1381788,1626588,32500\n20250417,12,5:30,6:00,1361870,1631670,36500\n20250417,13,6:00,6:30,1342409,1657409,89500\n20250417,14,6:30,7:00,1311069,1812969,200500\n20250417,15,7:00,7:30,1281445,1857145,338500\n20250417,16,7:30,8:00,1290783,1704883,487000\n20250417,17,8:00,8:30,1337342,1627842,587500\n20250417,18,8:30,9:00,1381419,1752019,738000\n20250417,19,9:00,9:30,1404850,1897150,875000\n20250417,20,9:30,10:00,1423907,2036707,991500\n20250417,21,10:00,10:30,1429936,2039236,1084500\n20250417,22,10:30,11:00,1448908,2055708,1150500\n20250417,23,11:00,11:30,1437809,2042609,1192500\n20250417,24,11:30,12:00,1415803,2021003,1213500\n20250417,25,12:00,12:30,1350546,1941946,1216500\n20250417,26,12:30,13:00,1338546,1929146,1204500\n20250417,27,13:00,13:30,1393259,1985459,1177000\n20250417,28,13:30,14:00,1398579,1996179,1130000\n20250417,29,14:00,14:30,1392623,1992323,1058500\n20250417,30,14:30,15:00,1372053,1977853,962500\n20250417,31,15:00,15:30,1350557,1938957,848000\n20250417,32,15:30,16:00,1377100,1870200,720500\n20250417,33,16:00,16:30,1389665,1942565,651000\n20250417,34,16:30,17:00,1398392,1987392,497500\n20250417,35,17:00,17:30,1392705,2018505,344000\n20250417,36,17:30,18:00,1390768,1957468,201000\n20250417,37,18:00,18:30,1398030,1995930,93500\n20250417,38,18:30,19:00,1411133,1951733,55000\n20250417,39,19:00,19:30,1397130,1948330,50500\n20250417,40,19:30,20:00,1378593,1950493,47000\n20250417,41,20:00,20:30,1348667,1935167,45500\n20250417,42,20:30,21:00,1323207,1927907,44000\n20250417,43,21:00,21:30,1293547,1792347,48000\n20250417,44,21:30,22:00,1260070,1793970,53500\n20250417,45,22:00,22:30,1232802,1745502,51500\n20250417,46,22:30,23:00,1199557,1747957,46500\n20250417,47,23:00,23:30,1196574,1703774,42500\n20250417,48,23:30,24:00,1170506,1634206,42500\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JP-TH/area_tso_yosoku_20250416.csv",
    "content": "t@CXV,t@CXV,Ώ۔N\n20250416,19:42:46,20250416\nDATE,ԃR},ԑ_,ԑ_,GAv(kWh),GAd(kWh),GÁEzd(kWh)\n2025/4/16,1,0:00,0:30,3693197,4894778,320029\n2025/4/16,2,0:30,1:00,3692798,4911664,335028\n2025/4/16,3,1:00,1:30,3736924,5117396,520364\n2025/4/16,4,1:30,2:00,3772741,5295138,640871\n2025/4/16,5,2:00,2:30,3838645,5418900,694579\n2025/4/16,6,2:30,3:00,3933255,5576520,761220\n2025/4/16,7,3:00,3:30,3975052,5651553,801323\n2025/4/16,8,3:30,4:00,4068329,6077016,835526\n2025/4/16,9,4:00,4:30,4146534,6116104,868682\n2025/4/16,10,4:30,5:00,4210505,6133600,870345\n2025/4/16,11,5:00,5:30,4257212,6168060,859381\n2025/4/16,12,5:30,6:00,4310801,6235993,985374\n2025/4/16,13,6:00,6:30,4330978,6314766,1219440\n2025/4/16,14,6:30,7:00,4269400,6309689,1486232\n2025/4/16,15,7:00,7:30,4203929,6318930,1794328\n2025/4/16,16,7:30,8:00,4295451,6541518,2112510\n2025/4/16,17,8:00,8:30,4590980,7032591,2274222\n2025/4/16,18,8:30,9:00,4809323,7276879,2514758\n2025/4/16,19,9:00,9:30,4840687,7049716,2769216\n2025/4/16,20,9:30,10:00,4862458,7125067,2989508\n2025/4/16,21,10:00,10:30,4805709,6981559,3118459\n2025/4/16,22,10:30,11:00,4843652,7009578,3223841\n2025/4/16,23,11:00,11:30,4781827,6971502,3264594\n2025/4/16,24,11:30,12:00,4699985,6889279,3261965\n2025/4/16,25,12:00,12:30,4623500,6861624,3215847\n2025/4/16,26,12:30,13:00,4576000,6717073,3065928\n2025/4/16,27,13:00,13:30,4670843,6730048,2986361\n2025/4/16,28,13:30,14:00,4750423,6654772,2872673\n2025/4/16,29,14:00,14:30,4766135,6697248,2779859\n2025/4/16,30,14:30,15:00,4726782,6674987,2565813\n2025/4/16,31,15:00,15:30,4772000,6657989,2312797\n2025/4/16,32,15:30,16:00,4825000,6583529,1963825\n2025/4/16,33,16:00,16:30,4772500,6635849,1770600\n2025/4/16,34,16:30,17:00,4762000,6620891,1417608\n2025/4/16,35,17:00,17:30,4835169,6753125,1146568\n2025/4/16,36,17:30,18:00,4863683,6809026,924737\n2025/4/16,37,18:00,18:30,4909447,6857105,882955\n2025/4/16,38,18:30,19:00,4896995,6806477,869508\n2025/4/16,39,19:00,19:30,4901288,6938871,871267\n2025/4/16,40,19:30,20:00,4783527,6837400,871344\n2025/4/16,41,20:00,20:30,4628989,6680505,865986\n2025/4/16,42,20:30,21:00,4550233,6596943,859643\n2025/4/16,43,21:00,21:30,4365599,6473192,853304\n2025/4/16,44,21:30,22:00,4213183,6312375,849173\n2025/4/16,45,22:00,22:30,4048200,5774819,841371\n2025/4/16,46,22:30,23:00,3933294,5664429,833525\n2025/4/16,47,23:00,23:30,3870860,5493248,819546\n2025/4/16,48,23:30,24:00,3824793,5435073,804221\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/JP-TH/area_tso_yosoku_y.csv",
    "content": "t@CXV,t@CXV,Ώ۔N\n20250416,19:42:46,20250417\nDATE,ԃR},ԑ_,ԑ_,GAv(kWh),GAd(kWh),GÁEzd(kWh)\n2025/4/17,1,0:00,0:30,3669485,5349463,713471\n2025/4/17,2,0:30,1:00,3636599,5312069,712459\n2025/4/17,3,1:00,1:30,3659749,5356967,710486\n2025/4/17,4,1:30,2:00,3684095,5379111,700845\n2025/4/17,5,2:00,2:30,3756230,5403657,682945\n2025/4/17,6,2:30,3:00,3815184,5449841,658040\n2025/4/17,7,3:00,3:30,3903162,5539910,640800\n2025/4/17,8,3:30,4:00,3949510,5698236,628416\n2025/4/17,9,4:00,4:30,4034370,5659117,607780\n2025/4/17,10,4:30,5:00,4098248,5699007,580411\n2025/4/17,11,5:00,5:30,4160171,5769608,561587\n2025/4/17,12,5:30,6:00,4191167,5898904,689116\n2025/4/17,13,6:00,6:30,4204173,5953009,1075323\n2025/4/17,14,6:30,7:00,4196016,6030356,1489384\n2025/4/17,15,7:00,7:30,4153526,6023118,1921485\n2025/4/17,16,7:30,8:00,4209078,6335862,2360079\n2025/4/17,17,8:00,8:30,4376712,6525285,2346902\n2025/4/17,18,8:30,9:00,4533568,6755161,2631129\n2025/4/17,19,9:00,9:30,4538483,6889929,2824001\n2025/4/17,20,9:30,10:00,4561492,6862759,2985050\n2025/4/17,21,10:00,10:30,4453358,6746379,3052284\n2025/4/17,22,10:30,11:00,4475764,6760484,3117608\n2025/4/17,23,11:00,11:30,4408904,6735300,3102333\n2025/4/17,24,11:30,12:00,4290211,6708511,3057332\n2025/4/17,25,12:00,12:30,4076294,6748626,3002219\n2025/4/17,26,12:30,13:00,4039641,6712694,2918022\n2025/4/17,27,13:00,13:30,4240755,6603986,2806077\n2025/4/17,28,13:30,14:00,4298640,6611886,2632236\n2025/4/17,29,14:00,14:30,4356916,6659167,2403812\n2025/4/17,30,14:30,15:00,4341921,6555909,2122552\n2025/4/17,31,15:00,15:30,4263731,6405863,1820194\n2025/4/17,32,15:30,16:00,4263104,6233700,1481372\n2025/4/17,33,16:00,16:30,4300620,6402386,1320263\n2025/4/17,34,16:30,17:00,4296676,6275813,913258\n2025/4/17,35,17:00,17:30,4284516,6037207,571443\n2025/4/17,36,17:30,18:00,4315160,5972811,360647\n2025/4/17,37,18:00,18:30,4450058,5979416,298592\n2025/4/17,38,18:30,19:00,4448781,5993344,279657\n2025/4/17,39,19:00,19:30,4302424,5900678,264568\n2025/4/17,40,19:30,20:00,4215919,5825542,248523\n2025/4/17,41,20:00,20:30,4175919,5834046,234563\n2025/4/17,42,20:30,21:00,4111260,5715951,224465\n2025/4/17,43,21:00,21:30,4009075,5716403,216797\n2025/4/17,44,21:30,22:00,3910857,5615706,213508\n2025/4/17,45,22:00,22:30,3870786,5470862,203288\n2025/4/17,46,22:30,23:00,3797931,5412081,203738\n2025/4/17,47,23:00,23:30,3738475,5251708,201793\n2025/4/17,48,23:30,24:00,3694644,5228820,199938\n"
  },
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    "path": "electricitymap/contrib/parsers/tests/mocks/JP-TK/AREA_ONCE_YOSOKU.csv",
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    "content": "\ng_power_1gouki=�^�]�I��&amp;g_power_2gouki=�^�]�I��&amp;g_power_3gouki=���������&amp;g_power_4gouki=119.7&amp;&amp;g_state1=�Q�O�P�T�N�S���Q�V���^�]�I��&amp;g_state2=�Q�O�P�X�N�S���X���^�]�I��&amp;g_state3=��P�W����������&amp;g_state4=�ʏ�^�]��&amp;s_state1=�ʏ�^�]��&amp;s_state2=�ʏ�^�]��&amp;&amp;lastupdate=2025�N4��25�� 16��02��&amp;wind_sp=3.6m/s&amp;wind_pc=3.6m/s&amp;wind=3.6m/s"
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    "content": "\ns_power_1gouki=96.1&amp;s_power_2gouki=96.1&amp;&amp;g_state1=�Q�O�P�T�N�S���Q�V���^�]�I��&amp;g_state2=�Q�O�P�X�N�S���X���^�]�I��&amp;g_state3=��P�W����������&amp;g_state4=�ʏ�^�]��&amp;s_state1=�ʏ�^�]��&amp;s_state2=�ʏ�^�]��&amp;&amp;lastupdate=2025�N4��25�� 16��00��&amp;wind_sp=5.1m/s&amp;wind_pc=5.1m/s&amp;wind=5.1m/s"
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  {
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{\r\n\t\t\t\t\ttext:'',\r\n\t\t\t\t\tstyle: {\r\n\t\t\t\t\t\tfontSize : '13px', \r\n\t\t\t\t\t\tcolor : 'blue'\r\n\t\t\t\t\t}\r\n\t\t\t\t},\r\n\t\t\t\tlabels:{\r\n\t\t\t\t\tformat:'{value:,.0f}'\r\n\t\t\t\t}\r\n\t\t\t\t//,min:0\r\n\t\t\t\t,minPadding:0\r\n\t\t\t\t,startOnTick:true\r\n\t\t\t\t,minRange:0.5\r\n\t\t\t},\r\n\t\t\tcolors: [\r\n\t\t\t\t'red','green'\r\n\t\t\t],\r\n\t\t\t\r\n\t\t\ttooltip: {\r\n\t\t\t\tformatter:function(){\r\n\t\t\t\t\tvar hr ='';\r\n\t\t\t\t\tvar min = '';\r\n\t\t\t\t\tvar seriesName = '';\r\n\t\t\t\t\tvar week = ['(일)','(월)','(화)','(수)','(목)','(금)','(토)',];\r\n\t\t\t\t\t\r\n\t\t\t\t\tvar currentPoint = this;\r\n\t\t\t\t\tvar currentSeries = currentPoint.series;\r\n\t\t\t\t\tvar chart = currentSeries.chart;\r\n\t\t\t\t\tvar stackName = this.series.userOptions.stack;\r\n\t\t\t\t\tvar stackSeriesVal1 = '';\r\n\t\t\t\t\tvar stackSeriesVal2 = '';\r\n\t\t\t\t\tvar stackSeriesVal3 = '';\r\n\t\t\t\t\tvar stackSeriesVal4 = '';\r\n\t\t\t\t\tvar stackSeriesVal5 = '';\r\n\t\t\t\t\tvar stackSeriesVal6 = '';\r\n\t\t\t\t\tvar stackSeriesVal8 = '';\r\n\t\t\t\t\tvar stackSeriesVal9 = '';\r\n\t\t\t\t\tvar stackSeriesVal10 = '';\r\n\t\t\t\t\t\r\n\t\t\t\t\tchart.series.forEach(function(series){\r\n\t\t\t\t\t\tseries.points.forEach(function(point){\r\n\t\t\t\t\t\t\tif(currentSeries.userOptions.stack === series.userOptions.stack && currentPoint.key === point.category){\r\n\t\t\t\t\t\t\t\tseriesName = x7[point.index].toString();\r\n\t\t\t\t\t\t\t\tseriesNameDash = seriesName.substr(0,4)+'-'+seriesName.substr(4,2)+'-'+seriesName.substr(6,2);\r\n\t\t\t\t\t\t\t\thr = seriesName.substr(8,2);\r\n\t\t\t\t\t\t\t\tmin = seriesName.substr(10,2);\r\n\t\t\t\t\t\t\t\thr = lPad(hr,2,'0');\r\n\t\t\t\t\t\t\t\tmin = lPad(min,2,'0');\r\n\t\t\t\t\t\t\t\tvar dayOfWeek = week[new Date(seriesNameDash).getDay()];\r\n\t\t\t\t\t\t\t\tseriesName = seriesName.substr(0,4)+'.'+seriesName.substr(4,2)+'.'+seriesName.substr(6,2)+dayOfWeek;\r\n\t\t\t\t\t\t\t\tstackSeriesVal1 = x1[point.index];\r\n\t\t\t\t\t\t\t\tstackSeriesVal2 = x2[point.index];\r\n\t\t\t\t\t\t\t\tstackSeriesVal3 = x3[point.index];\r\n\t\t\t\t\t\t\t\tstackSeriesVal4 = x4[point.index];\r\n\t\t\t\t\t\t\t\tstackSeriesVal5 = x5[point.index];\r\n\t\t\t\t\t\t\t\tstackSeriesVal6 = x6[point.index];\r\n\t\t\t\t\t\t\t\tstackSeriesVal8 = x8[point.index];\r\n\t\t\t\t\t\t\t\tstackSeriesVal9 = x9[point.index];\r\n\t\t\t\t\t\t\t\tstackSeriesVal10 = x10[point.index];\r\n\t\t\t\t\t\t\t}\r\n\t\t\t\t\t\t})\r\n\t\t\t\t\t});\r\n\t\t\t\t\t\r\n\t\t\t\t\tvar totStackSeriesVal = stackSeriesVal1+stackSeriesVal2+stackSeriesVal3+stackSeriesVal4+stackSeriesVal5+stackSeriesVal6+stackSeriesVal8+stackSeriesVal9+stackSeriesVal10;\r\n\t\t\t\t\t\r\n\t\t\t\t\tif(totStackSeriesVal == 0){\r\n\t\t\t\t\t\treturn false;\r\n\t\t\t\t\t}\r\n\t\t\t\t\t\r\n\t\t\t\t\tvar s =  seriesName+' '+hr+':'+min\r\n\t\t\t\t\t+'<br>양<span style=\"visibility:hidden\">가</span>수 : '+ commaToString(stackSeriesVal1.toFixed(0)) + 'MW'\r\n\t\t\t\t\t+'<br>수<span style=\"visibility:hidden\">가</span>력 : '+ commaToString(stackSeriesVal9.toFixed(0)) + 'MW'\r\n\t\t\t\t\t+'<br>가<span style=\"visibility:hidden\">가</span>스 : '+ commaToString(stackSeriesVal2.toFixed(0)) + 'MW'\r\n\t\t\t\t\t+'<br>태양광 : '+ commaToString((stackSeriesVal8+0).toFixed(0)) + 'MW'\r\n\t\t\t\t\t+'<br>신재생 : '+ commaToString(stackSeriesVal3.toFixed(0)) + 'MW'\r\n\t\t\t\t\t+'<br>유<span style=\"visibility:hidden\">가</span>류 : '+ commaToString(stackSeriesVal4.toFixed(0)) + 'MW'\r\n\t\t\t\t\t+'<br>국내탄 : '+ commaToString(stackSeriesVal10.toFixed(0)) + 'MW'\r\n\t\t\t\t\t+'<br>유연탄 : '+ commaToString(stackSeriesVal5.toFixed(0)) + 'MW'\r\n\t\t\t\t\t+'<br>원자력 : '+ commaToString(stackSeriesVal6.toFixed(0)) + 'MW'\r\n\t\t\t\t\t+'<br>합<span style=\"visibility:hidden\">가</span>계 : '+ commaToString(totStackSeriesVal.toFixed(0)) + 'MW'\r\n\t\t\t\t\t;\r\n\t\t\t\t\t\r\n\t\t\t\t\treturn s;\r\n\t\t\t\t}\t\t\t\t\t\t\r\n\t\t\t},\r\n\t\t\tchart: {\r\n\t\t\t\tdefaultSeriesType: 'area'\r\n\t\t\t\t//,backgroundColor : 'rgba(255,139,0,0.85)'\r\n\t\t\t},\r\n\t\t\tplotOptions: {\r\n\t\t\t\tarea: {\r\n\t\t\t\t\tstacking : 'normal'\r\n\t\t\t\t\t,pointInterval: 300000\r\n\t\t\t\t\t,softThreshold:false\r\n\t\t\t\t\t,connectNulls : true\r\n\t\t\t\t\t,lineWidth : 0\r\n\t\t\t\t}\r\n\t\t\t},\r\n\t\t\tlegend: {\r\n\t\t\t\t/* align: 'left',\r\n\t\t\t\tverticalAlign: 'top',\r\n\t\t\t\tmargin:25,\r\n\t\t\t\tenabled:false */\r\n\t\t\t},\r\n\t\t\tseries : null\r\n\t\t\t\r\n\t}\r\n\t\r\n\t$('#chart2').highcharts($.extend(true, option,{\r\n\t\t\r\n\t\tseries: [{\r\n\t\t\t\"name\": \"양수발전\",\r\n\t\t\t\"data\": x1_2, \r\n\t\t\t\"color\" : 'rgba(0,155,209,0.85)' //양수:0,155,209,0.85, 수력:172,231,252,0.85, 유류:196,0,20,0.85\r\n\t\t},{\r\n\t\t\t\"name\": \"양수펌핑\",\r\n\t\t\t\"data\": x1_1, \r\n\t\t\t\"color\" : 'rgba(215,215,215,0.85)',\r\n\t\t\t'zIndex' : 1\r\n\t\t},{\r\n\t\t\t\"name\": \"수력\",\r\n\t\t\t\"data\": x9, \r\n\t\t\t\"color\" : 'rgba(88,250,250,0.85)',\r\n\t\t\t'zIndex' : 1\r\n\t\t},{\r\n\t\t\t\"name\": \"가스\",\r\n\t\t\t\"data\": x2,\r\n\t\t\t\"color\" : 'rgba(255,246,0,0.85)'\r\n\t\t},{\r\n\t\t\t\"name\": \"태양광\",\r\n\t\t\t\"data\": x8,\r\n\t\t\t\"color\" : 'rgba(196,0,20,0.85)'\r\n\t\t},{\r\n\t\t\t\"name\": \"신재생\",\r\n\t\t\t\"data\": x3,\r\n\t\t\t\"color\" : 'rgba(120,194,82,0.85)'\r\n\t\t},{\r\n\t\t\t\"name\": \"유류\",\r\n\t\t\t\"data\": x4,\r\n\t\t\t// \"color\" : 'rgba(196,0,20,0.85)'\r\n\t\t\t \"color\" : 'rgba(215,215,215,0.85)'\r\n\t\t},{\r\n\t\t\t\"name\": \"국내탄\",\r\n\t\t\t\"data\": x10,\r\n\t\t\t\"color\" : 'rgba(57,57,57,0.85)' //국내탄:57,57,57,0.85, 유연탄:163,115,81,0.85\r\n\t\t},{\r\n\t\t\t\"name\": \"유연탄\",\r\n\t\t\t\"data\": x5,\r\n\t\t\t\"color\" : 'rgba(163,115,81,0.85)' //국내탄:57,57,57,0.85, 유연탄:163,115,81,0.85\r\n\t\t},{\r\n\t\t\t\"name\": \"원자력\",\r\n\t\t\t\"data\": x6,\r\n\t\t\t\"color\" : 'rgba(255,139,0,0.85)'\r\n\t\t}]\r\n\t}));\r\n}\r\n\r\nfunction fncSearch(){\r\n\tvar fm = document.srhForm;\r\n\t$('#view_edate').val($('#view_sdate').val());\r\n\tfm.submit();\r\n}\r\nfunction commaToString(par){\r\n\treturn par.toString().replace(/\\B(?=(\\d{3})+(?!\\d))/g,\",\");\r\n}\r\n</script>\r\n<link rel=\"stylesheet\" href=\"/css/board.css\" />\r\n\r\n\r\n <form id=\"srhForm\" name=\"srhForm\" action=\"/powerSource.es?mid=a10606030000&amp;device=chart\" method=\"post\">\r\n\t<input type=\"hidden\" name=\"mid\" value=\"a10606030000\" />\r\n\t<input type=\"hidden\" name=\"device\" value=\"chart\" />\r\n\t<div class=\"search_box\">\r\n\t\t<div class=\"box01\">\r\n\t\t\t<input type=\"date\" class=\"form_textbox calendar\" id=\"view_sdate\" name=\"view_sdate\" value=\"2023-09-01\" size=\"10\" maxlength=\"10\" title=\"날짜를 선택하세요.\" placeholder=\"2021-01-01\"/>\r\n\t\t\t<input type=\"hidden\" class=\"form_textbox calendar\" id=\"view_edate\" name=\"view_edate\" value=\"2023-09-01\" size=\"10\" maxlength=\"10\" title=\"날짜를 선택하세요.\" placeholder=\"2021-01-01\"/>\r\n\t\t\t<input type=\"button\" value=\"검색\" onclick=\"fncSearch(); return false;\">\r\n\t\t</div>\r\n\t</div>\r\n\t\r\n<div>\n<input type=\"hidden\" name=\"_csrf\" value=\"1b46d0b3-b065-48b5-88be-a072a716eb30\" />\n</div></form>\r\n<div class=\"conTableGroup\">\r\n\t<span class=\"grape_top\">MW</span>\r\n\t<div id=\"chart2\" class=\"grape2\" style=\"height:85%;\"> \r\n\t\t그래프 영역 <br />640 이상사이즈 100%*306 <br />640 이하사이즈 100%*153\r\n\t</div>\r\n</div>\r\n<div class=\"IR\">\r\n\t<table class=\"conTable tdCenter\">\r\n\t\t<caption>발전원별실시간 전력수급현황 차트 정보를 제공합니다.</caption>\r\n\t\t<thead>\r\n\t\t\t<tr>\r\n\t\t\t\t<th>일시</th>\r\n\t\t\t\t<th>기타</th>\r\n\t\t\t\t<th>가스</th>\r\n\t\t\t\t<th>신재생</th>\r\n\t\t\t\t<th>석탄</th>\r\n\t\t\t\t<th>원자력</th>\r\n\t\t\t</tr>\r\n\t\t</thead>\r\n\t\t<tbody>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 00분</td>\r\n\t\t\t\t\t<td>1,653</td>\r\n\t\t\t\t\t<td>13,845</td>\r\n\t\t\t\t\t<td>3,591</td>\r\n\t\t\t\t\t<td>22,909</td>\r\n\t\t\t\t\t<td>21,038</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 05분</td>\r\n\t\t\t\t\t<td>1,719</td>\r\n\t\t\t\t\t<td>13,555</td>\r\n\t\t\t\t\t<td>3,586</td>\r\n\t\t\t\t\t<td>22,938</td>\r\n\t\t\t\t\t<td>21,012</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 10분</td>\r\n\t\t\t\t\t<td>1,490</td>\r\n\t\t\t\t\t<td>13,276</td>\r\n\t\t\t\t\t<td>3,581</td>\r\n\t\t\t\t\t<td>23,041</td>\r\n\t\t\t\t\t<td>21,026</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 15분</td>\r\n\t\t\t\t\t<td>1,487</td>\r\n\t\t\t\t\t<td>13,092</td>\r\n\t\t\t\t\t<td>3,579</td>\r\n\t\t\t\t\t<td>23,082</td>\r\n\t\t\t\t\t<td>21,037</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 20분</td>\r\n\t\t\t\t\t<td>1,466</td>\r\n\t\t\t\t\t<td>12,740</td>\r\n\t\t\t\t\t<td>3,585</td>\r\n\t\t\t\t\t<td>22,909</td>\r\n\t\t\t\t\t<td>21,036</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 25분</td>\r\n\t\t\t\t\t<td>1,480</td>\r\n\t\t\t\t\t<td>12,580</td>\r\n\t\t\t\t\t<td>3,590</td>\r\n\t\t\t\t\t<td>22,966</td>\r\n\t\t\t\t\t<td>21,020</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 30분</td>\r\n\t\t\t\t\t<td>1,455</td>\r\n\t\t\t\t\t<td>12,370</td>\r\n\t\t\t\t\t<td>3,587</td>\r\n\t\t\t\t\t<td>22,810</td>\r\n\t\t\t\t\t<td>21,038</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 35분</td>\r\n\t\t\t\t\t<td>1,451</td>\r\n\t\t\t\t\t<td>12,196</td>\r\n\t\t\t\t\t<td>3,598</td>\r\n\t\t\t\t\t<td>22,660</td>\r\n\t\t\t\t\t<td>21,039</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 40분</td>\r\n\t\t\t\t\t<td>1,486</td>\r\n\t\t\t\t\t<td>12,057</td>\r\n\t\t\t\t\t<td>3,600</td>\r\n\t\t\t\t\t<td>22,802</td>\r\n\t\t\t\t\t<td>21,030</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 45분</td>\r\n\t\t\t\t\t<td>1,461</td>\r\n\t\t\t\t\t<td>11,852</td>\r\n\t\t\t\t\t<td>3,601</td>\r\n\t\t\t\t\t<td>22,701</td>\r\n\t\t\t\t\t<td>21,031</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 50분</td>\r\n\t\t\t\t\t<td>1,463</td>\r\n\t\t\t\t\t<td>11,672</td>\r\n\t\t\t\t\t<td>3,602</td>\r\n\t\t\t\t\t<td>22,672</td>\r\n\t\t\t\t\t<td>21,039</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 00시 55분</td>\r\n\t\t\t\t\t<td>1,349</td>\r\n\t\t\t\t\t<td>11,507</td>\r\n\t\t\t\t\t<td>3,600</td>\r\n\t\t\t\t\t<td>22,630</td>\r\n\t\t\t\t\t<td>21,038</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 00분</td>\r\n\t\t\t\t\t<td>1,151</td>\r\n\t\t\t\t\t<td>11,554</td>\r\n\t\t\t\t\t<td>3,584</td>\r\n\t\t\t\t\t<td>22,681</td>\r\n\t\t\t\t\t<td>21,030</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 05분</td>\r\n\t\t\t\t\t<td>1,150</td>\r\n\t\t\t\t\t<td>11,538</td>\r\n\t\t\t\t\t<td>3,583</td>\r\n\t\t\t\t\t<td>22,596</td>\r\n\t\t\t\t\t<td>21,031</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 10분</td>\r\n\t\t\t\t\t<td>1,152</td>\r\n\t\t\t\t\t<td>11,496</td>\r\n\t\t\t\t\t<td>3,574</td>\r\n\t\t\t\t\t<td>22,663</td>\r\n\t\t\t\t\t<td>21,036</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 15분</td>\r\n\t\t\t\t\t<td>1,150</td>\r\n\t\t\t\t\t<td>11,291</td>\r\n\t\t\t\t\t<td>3,578</td>\r\n\t\t\t\t\t<td>22,513</td>\r\n\t\t\t\t\t<td>21,032</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 20분</td>\r\n\t\t\t\t\t<td>1,153</td>\r\n\t\t\t\t\t<td>11,000</td>\r\n\t\t\t\t\t<td>3,566</td>\r\n\t\t\t\t\t<td>22,523</td>\r\n\t\t\t\t\t<td>21,022</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 25분</td>\r\n\t\t\t\t\t<td>1,158</td>\r\n\t\t\t\t\t<td>11,000</td>\r\n\t\t\t\t\t<td>3,558</td>\r\n\t\t\t\t\t<td>22,584</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 30분</td>\r\n\t\t\t\t\t<td>1,156</td>\r\n\t\t\t\t\t<td>10,939</td>\r\n\t\t\t\t\t<td>3,560</td>\r\n\t\t\t\t\t<td>22,556</td>\r\n\t\t\t\t\t<td>21,018</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 35분</td>\r\n\t\t\t\t\t<td>1,157</td>\r\n\t\t\t\t\t<td>10,970</td>\r\n\t\t\t\t\t<td>3,553</td>\r\n\t\t\t\t\t<td>22,591</td>\r\n\t\t\t\t\t<td>21,013</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 40분</td>\r\n\t\t\t\t\t<td>1,152</td>\r\n\t\t\t\t\t<td>10,821</td>\r\n\t\t\t\t\t<td>3,550</td>\r\n\t\t\t\t\t<td>22,531</td>\r\n\t\t\t\t\t<td>21,025</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 45분</td>\r\n\t\t\t\t\t<td>1,159</td>\r\n\t\t\t\t\t<td>10,770</td>\r\n\t\t\t\t\t<td>3,544</td>\r\n\t\t\t\t\t<td>22,612</td>\r\n\t\t\t\t\t<td>21,020</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 50분</td>\r\n\t\t\t\t\t<td>1,152</td>\r\n\t\t\t\t\t<td>10,521</td>\r\n\t\t\t\t\t<td>3,541</td>\r\n\t\t\t\t\t<td>22,437</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 01시 55분</td>\r\n\t\t\t\t\t<td>820</td>\r\n\t\t\t\t\t<td>10,556</td>\r\n\t\t\t\t\t<td>3,547</td>\r\n\t\t\t\t\t<td>22,580</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 00분</td>\r\n\t\t\t\t\t<td>523</td>\r\n\t\t\t\t\t<td>10,614</td>\r\n\t\t\t\t\t<td>3,624</td>\r\n\t\t\t\t\t<td>22,749</td>\r\n\t\t\t\t\t<td>21,028</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 05분</td>\r\n\t\t\t\t\t<td>510</td>\r\n\t\t\t\t\t<td>10,728</td>\r\n\t\t\t\t\t<td>3,636</td>\r\n\t\t\t\t\t<td>22,791</td>\r\n\t\t\t\t\t<td>21,027</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 10분</td>\r\n\t\t\t\t\t<td>512</td>\r\n\t\t\t\t\t<td>10,230</td>\r\n\t\t\t\t\t<td>3,644</td>\r\n\t\t\t\t\t<td>22,835</td>\r\n\t\t\t\t\t<td>21,019</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 15분</td>\r\n\t\t\t\t\t<td>516</td>\r\n\t\t\t\t\t<td>9,955</td>\r\n\t\t\t\t\t<td>3,645</td>\r\n\t\t\t\t\t<td>22,973</td>\r\n\t\t\t\t\t<td>21,011</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 20분</td>\r\n\t\t\t\t\t<td>491</td>\r\n\t\t\t\t\t<td>10,116</td>\r\n\t\t\t\t\t<td>3,659</td>\r\n\t\t\t\t\t<td>22,869</td>\r\n\t\t\t\t\t<td>21,022</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 25분</td>\r\n\t\t\t\t\t<td>308</td>\r\n\t\t\t\t\t<td>10,384</td>\r\n\t\t\t\t\t<td>3,668</td>\r\n\t\t\t\t\t<td>22,762</td>\r\n\t\t\t\t\t<td>21,006</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 30분</td>\r\n\t\t\t\t\t<td>-6</td>\r\n\t\t\t\t\t<td>10,453</td>\r\n\t\t\t\t\t<td>3,666</td>\r\n\t\t\t\t\t<td>22,847</td>\r\n\t\t\t\t\t<td>21,009</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 35분</td>\r\n\t\t\t\t\t<td>-34</td>\r\n\t\t\t\t\t<td>10,366</td>\r\n\t\t\t\t\t<td>3,670</td>\r\n\t\t\t\t\t<td>22,863</td>\r\n\t\t\t\t\t<td>21,013</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 40분</td>\r\n\t\t\t\t\t<td>-360</td>\r\n\t\t\t\t\t<td>10,386</td>\r\n\t\t\t\t\t<td>3,679</td>\r\n\t\t\t\t\t<td>23,087</td>\r\n\t\t\t\t\t<td>21,001</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 45분</td>\r\n\t\t\t\t\t<td>-393</td>\r\n\t\t\t\t\t<td>10,409</td>\r\n\t\t\t\t\t<td>3,688</td>\r\n\t\t\t\t\t<td>23,060</td>\r\n\t\t\t\t\t<td>20,993</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 50분</td>\r\n\t\t\t\t\t<td>-401</td>\r\n\t\t\t\t\t<td>10,256</td>\r\n\t\t\t\t\t<td>3,694</td>\r\n\t\t\t\t\t<td>22,996</td>\r\n\t\t\t\t\t<td>21,010</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 02시 55분</td>\r\n\t\t\t\t\t<td>-88</td>\r\n\t\t\t\t\t<td>10,014</td>\r\n\t\t\t\t\t<td>3,703</td>\r\n\t\t\t\t\t<td>22,752</td>\r\n\t\t\t\t\t<td>20,991</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 00분</td>\r\n\t\t\t\t\t<td>-69</td>\r\n\t\t\t\t\t<td>9,986</td>\r\n\t\t\t\t\t<td>3,715</td>\r\n\t\t\t\t\t<td>22,703</td>\r\n\t\t\t\t\t<td>20,983</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 05분</td>\r\n\t\t\t\t\t<td>-75</td>\r\n\t\t\t\t\t<td>9,872</td>\r\n\t\t\t\t\t<td>3,718</td>\r\n\t\t\t\t\t<td>22,644</td>\r\n\t\t\t\t\t<td>20,974</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 10분</td>\r\n\t\t\t\t\t<td>-72</td>\r\n\t\t\t\t\t<td>9,941</td>\r\n\t\t\t\t\t<td>3,729</td>\r\n\t\t\t\t\t<td>22,599</td>\r\n\t\t\t\t\t<td>20,960</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 15분</td>\r\n\t\t\t\t\t<td>-70</td>\r\n\t\t\t\t\t<td>10,045</td>\r\n\t\t\t\t\t<td>3,738</td>\r\n\t\t\t\t\t<td>22,565</td>\r\n\t\t\t\t\t<td>20,987</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 20분</td>\r\n\t\t\t\t\t<td>-80</td>\r\n\t\t\t\t\t<td>9,988</td>\r\n\t\t\t\t\t<td>3,750</td>\r\n\t\t\t\t\t<td>22,483</td>\r\n\t\t\t\t\t<td>20,982</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 25분</td>\r\n\t\t\t\t\t<td>-404</td>\r\n\t\t\t\t\t<td>10,103</td>\r\n\t\t\t\t\t<td>3,764</td>\r\n\t\t\t\t\t<td>22,580</td>\r\n\t\t\t\t\t<td>20,965</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 30분</td>\r\n\t\t\t\t\t<td>-428</td>\r\n\t\t\t\t\t<td>10,148</td>\r\n\t\t\t\t\t<td>3,777</td>\r\n\t\t\t\t\t<td>22,600</td>\r\n\t\t\t\t\t<td>20,963</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 35분</td>\r\n\t\t\t\t\t<td>-429</td>\r\n\t\t\t\t\t<td>10,120</td>\r\n\t\t\t\t\t<td>3,780</td>\r\n\t\t\t\t\t<td>22,894</td>\r\n\t\t\t\t\t<td>20,970</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 40분</td>\r\n\t\t\t\t\t<td>-826</td>\r\n\t\t\t\t\t<td>10,091</td>\r\n\t\t\t\t\t<td>3,798</td>\r\n\t\t\t\t\t<td>22,961</td>\r\n\t\t\t\t\t<td>20,967</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 45분</td>\r\n\t\t\t\t\t<td>-822</td>\r\n\t\t\t\t\t<td>10,287</td>\r\n\t\t\t\t\t<td>3,798</td>\r\n\t\t\t\t\t<td>22,939</td>\r\n\t\t\t\t\t<td>20,960</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 50분</td>\r\n\t\t\t\t\t<td>-823</td>\r\n\t\t\t\t\t<td>10,188</td>\r\n\t\t\t\t\t<td>3,808</td>\r\n\t\t\t\t\t<td>22,945</td>\r\n\t\t\t\t\t<td>20,948</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 03시 55분</td>\r\n\t\t\t\t\t<td>-827</td>\r\n\t\t\t\t\t<td>10,054</td>\r\n\t\t\t\t\t<td>3,805</td>\r\n\t\t\t\t\t<td>22,858</td>\r\n\t\t\t\t\t<td>20,986</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 04시 00분</td>\r\n\t\t\t\t\t<td>-829</td>\r\n\t\t\t\t\t<td>10,155</td>\r\n\t\t\t\t\t<td>3,810</td>\r\n\t\t\t\t\t<td>22,813</td>\r\n\t\t\t\t\t<td>20,981</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 04시 05분</td>\r\n\t\t\t\t\t<td>-826</td>\r\n\t\t\t\t\t<td>10,202</td>\r\n\t\t\t\t\t<td>3,806</td>\r\n\t\t\t\t\t<td>22,693</td>\r\n\t\t\t\t\t<td>20,956</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 04시 10분</td>\r\n\t\t\t\t\t<td>-822</td>\r\n\t\t\t\t\t<td>10,054</td>\r\n\t\t\t\t\t<td>3,809</td>\r\n\t\t\t\t\t<td>22,891</td>\r\n\t\t\t\t\t<td>20,962</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 04시 15분</td>\r\n\t\t\t\t\t<td>-819</td>\r\n\t\t\t\t\t<td>10,111</td>\r\n\t\t\t\t\t<td>3,813</td>\r\n\t\t\t\t\t<td>22,952</td>\r\n\t\t\t\t\t<td>20,962</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 04시 20분</td>\r\n\t\t\t\t\t<td>-823</td>\r\n\t\t\t\t\t<td>9,999</td>\r\n\t\t\t\t\t<td>3,818</td>\r\n\t\t\t\t\t<td>22,705</td>\r\n\t\t\t\t\t<td>20,966</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 04시 25분</td>\r\n\t\t\t\t\t<td>-818</td>\r\n\t\t\t\t\t<td>10,068</td>\r\n\t\t\t\t\t<td>3,822</td>\r\n\t\t\t\t\t<td>22,751</td>\r\n\t\t\t\t\t<td>20,960</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 04시 30분</td>\r\n\t\t\t\t\t<td>-818</td>\r\n\t\t\t\t\t<td>10,201</td>\r\n\t\t\t\t\t<td>3,822</td>\r\n\t\t\t\t\t<td>23,003</td>\r\n\t\t\t\t\t<td>20,957</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 04시 35분</td>\r\n\t\t\t\t\t<td>-816</td>\r\n\t\t\t\t\t<td>10,318</td>\r\n\t\t\t\t\t<td>3,821</td>\r\n\t\t\t\t\t<td>22,982</td>\r\n\t\t\t\t\t<td>20,962</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 04시 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40분</td>\r\n\t\t\t\t\t<td>1,604</td>\r\n\t\t\t\t\t<td>20,124</td>\r\n\t\t\t\t\t<td>3,187</td>\r\n\t\t\t\t\t<td>23,956</td>\r\n\t\t\t\t\t<td>21,006</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 09시 45분</td>\r\n\t\t\t\t\t<td>1,616</td>\r\n\t\t\t\t\t<td>20,148</td>\r\n\t\t\t\t\t<td>3,160</td>\r\n\t\t\t\t\t<td>23,965</td>\r\n\t\t\t\t\t<td>21,018</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 09시 50분</td>\r\n\t\t\t\t\t<td>1,599</td>\r\n\t\t\t\t\t<td>20,190</td>\r\n\t\t\t\t\t<td>3,151</td>\r\n\t\t\t\t\t<td>23,834</td>\r\n\t\t\t\t\t<td>21,007</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 09시 55분</td>\r\n\t\t\t\t\t<td>1,613</td>\r\n\t\t\t\t\t<td>19,957</td>\r\n\t\t\t\t\t<td>3,144</td>\r\n\t\t\t\t\t<td>23,769</td>\r\n\t\t\t\t\t<td>21,009</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 00분</td>\r\n\t\t\t\t\t<td>1,529</td>\r\n\t\t\t\t\t<td>19,850</td>\r\n\t\t\t\t\t<td>3,123</td>\r\n\t\t\t\t\t<td>23,572</td>\r\n\t\t\t\t\t<td>21,009</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 05분</td>\r\n\t\t\t\t\t<td>1,512</td>\r\n\t\t\t\t\t<td>19,684</td>\r\n\t\t\t\t\t<td>3,080</td>\r\n\t\t\t\t\t<td>23,315</td>\r\n\t\t\t\t\t<td>21,033</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 10분</td>\r\n\t\t\t\t\t<td>1,349</td>\r\n\t\t\t\t\t<td>20,171</td>\r\n\t\t\t\t\t<td>3,044</td>\r\n\t\t\t\t\t<td>23,262</td>\r\n\t\t\t\t\t<td>21,011</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 15분</td>\r\n\t\t\t\t\t<td>1,376</td>\r\n\t\t\t\t\t<td>20,376</td>\r\n\t\t\t\t\t<td>2,997</td>\r\n\t\t\t\t\t<td>23,283</td>\r\n\t\t\t\t\t<td>21,005</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 20분</td>\r\n\t\t\t\t\t<td>1,352</td>\r\n\t\t\t\t\t<td>20,444</td>\r\n\t\t\t\t\t<td>2,874</td>\r\n\t\t\t\t\t<td>23,357</td>\r\n\t\t\t\t\t<td>21,020</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 25분</td>\r\n\t\t\t\t\t<td>1,339</td>\r\n\t\t\t\t\t<td>20,277</td>\r\n\t\t\t\t\t<td>2,840</td>\r\n\t\t\t\t\t<td>23,180</td>\r\n\t\t\t\t\t<td>21,019</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 30분</td>\r\n\t\t\t\t\t<td>1,328</td>\r\n\t\t\t\t\t<td>20,204</td>\r\n\t\t\t\t\t<td>2,848</td>\r\n\t\t\t\t\t<td>23,069</td>\r\n\t\t\t\t\t<td>21,032</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 35분</td>\r\n\t\t\t\t\t<td>1,330</td>\r\n\t\t\t\t\t<td>20,270</td>\r\n\t\t\t\t\t<td>2,820</td>\r\n\t\t\t\t\t<td>22,909</td>\r\n\t\t\t\t\t<td>21,031</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 40분</td>\r\n\t\t\t\t\t<td>1,136</td>\r\n\t\t\t\t\t<td>20,476</td>\r\n\t\t\t\t\t<td>2,801</td>\r\n\t\t\t\t\t<td>22,916</td>\r\n\t\t\t\t\t<td>21,025</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 45분</td>\r\n\t\t\t\t\t<td>1,128</td>\r\n\t\t\t\t\t<td>20,341</td>\r\n\t\t\t\t\t<td>2,780</td>\r\n\t\t\t\t\t<td>22,922</td>\r\n\t\t\t\t\t<td>21,025</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 50분</td>\r\n\t\t\t\t\t<td>1,135</td>\r\n\t\t\t\t\t<td>20,362</td>\r\n\t\t\t\t\t<td>2,753</td>\r\n\t\t\t\t\t<td>22,978</td>\r\n\t\t\t\t\t<td>21,027</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 10시 55분</td>\r\n\t\t\t\t\t<td>1,122</td>\r\n\t\t\t\t\t<td>20,195</td>\r\n\t\t\t\t\t<td>2,718</td>\r\n\t\t\t\t\t<td>22,776</td>\r\n\t\t\t\t\t<td>21,035</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 00분</td>\r\n\t\t\t\t\t<td>1,121</td>\r\n\t\t\t\t\t<td>20,062</td>\r\n\t\t\t\t\t<td>2,718</td>\r\n\t\t\t\t\t<td>22,499</td>\r\n\t\t\t\t\t<td>21,042</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 05분</td>\r\n\t\t\t\t\t<td>1,132</td>\r\n\t\t\t\t\t<td>19,737</td>\r\n\t\t\t\t\t<td>2,691</td>\r\n\t\t\t\t\t<td>22,392</td>\r\n\t\t\t\t\t<td>21,034</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 10분</td>\r\n\t\t\t\t\t<td>1,129</td>\r\n\t\t\t\t\t<td>19,831</td>\r\n\t\t\t\t\t<td>2,683</td>\r\n\t\t\t\t\t<td>22,183</td>\r\n\t\t\t\t\t<td>21,018</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 15분</td>\r\n\t\t\t\t\t<td>1,135</td>\r\n\t\t\t\t\t<td>19,856</td>\r\n\t\t\t\t\t<td>2,680</td>\r\n\t\t\t\t\t<td>21,814</td>\r\n\t\t\t\t\t<td>21,021</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 20분</td>\r\n\t\t\t\t\t<td>1,133</td>\r\n\t\t\t\t\t<td>19,977</td>\r\n\t\t\t\t\t<td>2,662</td>\r\n\t\t\t\t\t<td>21,610</td>\r\n\t\t\t\t\t<td>21,020</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 25분</td>\r\n\t\t\t\t\t<td>1,152</td>\r\n\t\t\t\t\t<td>19,920</td>\r\n\t\t\t\t\t<td>2,625</td>\r\n\t\t\t\t\t<td>21,285</td>\r\n\t\t\t\t\t<td>21,029</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 30분</td>\r\n\t\t\t\t\t<td>1,116</td>\r\n\t\t\t\t\t<td>19,738</td>\r\n\t\t\t\t\t<td>2,636</td>\r\n\t\t\t\t\t<td>21,035</td>\r\n\t\t\t\t\t<td>21,027</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 35분</td>\r\n\t\t\t\t\t<td>1,082</td>\r\n\t\t\t\t\t<td>19,722</td>\r\n\t\t\t\t\t<td>2,622</td>\r\n\t\t\t\t\t<td>20,736</td>\r\n\t\t\t\t\t<td>21,029</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 40분</td>\r\n\t\t\t\t\t<td>759</td>\r\n\t\t\t\t\t<td>19,870</td>\r\n\t\t\t\t\t<td>2,598</td>\r\n\t\t\t\t\t<td>20,595</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 45분</td>\r\n\t\t\t\t\t<td>747</td>\r\n\t\t\t\t\t<td>19,668</td>\r\n\t\t\t\t\t<td>2,583</td>\r\n\t\t\t\t\t<td>20,498</td>\r\n\t\t\t\t\t<td>21,009</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 50분</td>\r\n\t\t\t\t\t<td>720</td>\r\n\t\t\t\t\t<td>19,414</td>\r\n\t\t\t\t\t<td>2,598</td>\r\n\t\t\t\t\t<td>20,304</td>\r\n\t\t\t\t\t<td>21,012</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 11시 55분</td>\r\n\t\t\t\t\t<td>378</td>\r\n\t\t\t\t\t<td>19,505</td>\r\n\t\t\t\t\t<td>2,573</td>\r\n\t\t\t\t\t<td>20,119</td>\r\n\t\t\t\t\t<td>21,022</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 00분</td>\r\n\t\t\t\t\t<td>175</td>\r\n\t\t\t\t\t<td>19,413</td>\r\n\t\t\t\t\t<td>2,545</td>\r\n\t\t\t\t\t<td>19,933</td>\r\n\t\t\t\t\t<td>21,021</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 05분</td>\r\n\t\t\t\t\t<td>-35</td>\r\n\t\t\t\t\t<td>19,313</td>\r\n\t\t\t\t\t<td>2,566</td>\r\n\t\t\t\t\t<td>20,068</td>\r\n\t\t\t\t\t<td>21,039</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 10분</td>\r\n\t\t\t\t\t<td>-123</td>\r\n\t\t\t\t\t<td>19,321</td>\r\n\t\t\t\t\t<td>2,623</td>\r\n\t\t\t\t\t<td>20,002</td>\r\n\t\t\t\t\t<td>21,014</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 15분</td>\r\n\t\t\t\t\t<td>-94</td>\r\n\t\t\t\t\t<td>18,933</td>\r\n\t\t\t\t\t<td>2,630</td>\r\n\t\t\t\t\t<td>20,163</td>\r\n\t\t\t\t\t<td>21,026</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 20분</td>\r\n\t\t\t\t\t<td>-179</td>\r\n\t\t\t\t\t<td>19,061</td>\r\n\t\t\t\t\t<td>2,645</td>\r\n\t\t\t\t\t<td>19,993</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 25분</td>\r\n\t\t\t\t\t<td>-511</td>\r\n\t\t\t\t\t<td>19,329</td>\r\n\t\t\t\t\t<td>2,649</td>\r\n\t\t\t\t\t<td>19,916</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 30분</td>\r\n\t\t\t\t\t<td>-513</td>\r\n\t\t\t\t\t<td>19,112</td>\r\n\t\t\t\t\t<td>2,645</td>\r\n\t\t\t\t\t<td>19,982</td>\r\n\t\t\t\t\t<td>21,029</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 35분</td>\r\n\t\t\t\t\t<td>-538</td>\r\n\t\t\t\t\t<td>19,157</td>\r\n\t\t\t\t\t<td>2,653</td>\r\n\t\t\t\t\t<td>19,958</td>\r\n\t\t\t\t\t<td>21,016</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 40분</td>\r\n\t\t\t\t\t<td>-526</td>\r\n\t\t\t\t\t<td>19,151</td>\r\n\t\t\t\t\t<td>2,665</td>\r\n\t\t\t\t\t<td>19,861</td>\r\n\t\t\t\t\t<td>21,016</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 45분</td>\r\n\t\t\t\t\t<td>-523</td>\r\n\t\t\t\t\t<td>19,122</td>\r\n\t\t\t\t\t<td>2,681</td>\r\n\t\t\t\t\t<td>19,949</td>\r\n\t\t\t\t\t<td>21,034</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 50분</td>\r\n\t\t\t\t\t<td>-495</td>\r\n\t\t\t\t\t<td>19,183</td>\r\n\t\t\t\t\t<td>2,705</td>\r\n\t\t\t\t\t<td>20,121</td>\r\n\t\t\t\t\t<td>21,009</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 12시 55분</td>\r\n\t\t\t\t\t<td>-505</td>\r\n\t\t\t\t\t<td>19,145</td>\r\n\t\t\t\t\t<td>2,701</td>\r\n\t\t\t\t\t<td>20,083</td>\r\n\t\t\t\t\t<td>21,030</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 00분</td>\r\n\t\t\t\t\t<td>-171</td>\r\n\t\t\t\t\t<td>19,428</td>\r\n\t\t\t\t\t<td>2,749</td>\r\n\t\t\t\t\t<td>20,290</td>\r\n\t\t\t\t\t<td>21,018</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 05분</td>\r\n\t\t\t\t\t<td>489</td>\r\n\t\t\t\t\t<td>19,481</td>\r\n\t\t\t\t\t<td>2,792</td>\r\n\t\t\t\t\t<td>20,332</td>\r\n\t\t\t\t\t<td>21,027</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 10분</td>\r\n\t\t\t\t\t<td>495</td>\r\n\t\t\t\t\t<td>19,681</td>\r\n\t\t\t\t\t<td>2,834</td>\r\n\t\t\t\t\t<td>20,473</td>\r\n\t\t\t\t\t<td>21,034</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 15분</td>\r\n\t\t\t\t\t<td>494</td>\r\n\t\t\t\t\t<td>19,766</td>\r\n\t\t\t\t\t<td>2,879</td>\r\n\t\t\t\t\t<td>20,576</td>\r\n\t\t\t\t\t<td>21,030</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 20분</td>\r\n\t\t\t\t\t<td>498</td>\r\n\t\t\t\t\t<td>19,973</td>\r\n\t\t\t\t\t<td>2,929</td>\r\n\t\t\t\t\t<td>20,653</td>\r\n\t\t\t\t\t<td>21,032</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 25분</td>\r\n\t\t\t\t\t<td>823</td>\r\n\t\t\t\t\t<td>19,929</td>\r\n\t\t\t\t\t<td>2,987</td>\r\n\t\t\t\t\t<td>20,689</td>\r\n\t\t\t\t\t<td>21,020</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 30분</td>\r\n\t\t\t\t\t<td>1,178</td>\r\n\t\t\t\t\t<td>19,681</td>\r\n\t\t\t\t\t<td>3,016</td>\r\n\t\t\t\t\t<td>20,663</td>\r\n\t\t\t\t\t<td>21,041</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 35분</td>\r\n\t\t\t\t\t<td>1,193</td>\r\n\t\t\t\t\t<td>20,272</td>\r\n\t\t\t\t\t<td>3,042</td>\r\n\t\t\t\t\t<td>20,568</td>\r\n\t\t\t\t\t<td>21,016</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 40분</td>\r\n\t\t\t\t\t<td>1,307</td>\r\n\t\t\t\t\t<td>20,468</td>\r\n\t\t\t\t\t<td>3,034</td>\r\n\t\t\t\t\t<td>20,509</td>\r\n\t\t\t\t\t<td>21,035</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 45분</td>\r\n\t\t\t\t\t<td>1,303</td>\r\n\t\t\t\t\t<td>20,552</td>\r\n\t\t\t\t\t<td>3,057</td>\r\n\t\t\t\t\t<td>20,769</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 50분</td>\r\n\t\t\t\t\t<td>1,278</td>\r\n\t\t\t\t\t<td>20,490</td>\r\n\t\t\t\t\t<td>3,091</td>\r\n\t\t\t\t\t<td>20,775</td>\r\n\t\t\t\t\t<td>21,033</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 13시 55분</td>\r\n\t\t\t\t\t<td>1,278</td>\r\n\t\t\t\t\t<td>20,375</td>\r\n\t\t\t\t\t<td>3,142</td>\r\n\t\t\t\t\t<td>20,902</td>\r\n\t\t\t\t\t<td>21,025</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 00분</td>\r\n\t\t\t\t\t<td>1,291</td>\r\n\t\t\t\t\t<td>20,493</td>\r\n\t\t\t\t\t<td>3,161</td>\r\n\t\t\t\t\t<td>21,076</td>\r\n\t\t\t\t\t<td>21,016</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 05분</td>\r\n\t\t\t\t\t<td>1,288</td>\r\n\t\t\t\t\t<td>20,616</td>\r\n\t\t\t\t\t<td>3,166</td>\r\n\t\t\t\t\t<td>21,089</td>\r\n\t\t\t\t\t<td>21,016</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 10분</td>\r\n\t\t\t\t\t<td>1,263</td>\r\n\t\t\t\t\t<td>20,710</td>\r\n\t\t\t\t\t<td>3,181</td>\r\n\t\t\t\t\t<td>21,162</td>\r\n\t\t\t\t\t<td>21,032</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 15분</td>\r\n\t\t\t\t\t<td>1,251</td>\r\n\t\t\t\t\t<td>20,880</td>\r\n\t\t\t\t\t<td>3,211</td>\r\n\t\t\t\t\t<td>21,102</td>\r\n\t\t\t\t\t<td>21,026</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 20분</td>\r\n\t\t\t\t\t<td>1,251</td>\r\n\t\t\t\t\t<td>21,116</td>\r\n\t\t\t\t\t<td>3,283</td>\r\n\t\t\t\t\t<td>21,037</td>\r\n\t\t\t\t\t<td>21,025</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 25분</td>\r\n\t\t\t\t\t<td>1,279</td>\r\n\t\t\t\t\t<td>21,369</td>\r\n\t\t\t\t\t<td>3,293</td>\r\n\t\t\t\t\t<td>20,933</td>\r\n\t\t\t\t\t<td>21,029</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 30분</td>\r\n\t\t\t\t\t<td>1,244</td>\r\n\t\t\t\t\t<td>21,266</td>\r\n\t\t\t\t\t<td>3,301</td>\r\n\t\t\t\t\t<td>20,846</td>\r\n\t\t\t\t\t<td>21,041</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 35분</td>\r\n\t\t\t\t\t<td>1,267</td>\r\n\t\t\t\t\t<td>21,557</td>\r\n\t\t\t\t\t<td>3,355</td>\r\n\t\t\t\t\t<td>20,879</td>\r\n\t\t\t\t\t<td>21,040</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 40분</td>\r\n\t\t\t\t\t<td>1,264</td>\r\n\t\t\t\t\t<td>21,800</td>\r\n\t\t\t\t\t<td>3,407</td>\r\n\t\t\t\t\t<td>20,633</td>\r\n\t\t\t\t\t<td>21,028</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 45분</td>\r\n\t\t\t\t\t<td>1,272</td>\r\n\t\t\t\t\t<td>21,992</td>\r\n\t\t\t\t\t<td>3,436</td>\r\n\t\t\t\t\t<td>20,605</td>\r\n\t\t\t\t\t<td>21,042</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 50분</td>\r\n\t\t\t\t\t<td>1,317</td>\r\n\t\t\t\t\t<td>22,130</td>\r\n\t\t\t\t\t<td>3,492</td>\r\n\t\t\t\t\t<td>20,682</td>\r\n\t\t\t\t\t<td>21,026</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 14시 55분</td>\r\n\t\t\t\t\t<td>1,318</td>\r\n\t\t\t\t\t<td>22,168</td>\r\n\t\t\t\t\t<td>3,517</td>\r\n\t\t\t\t\t<td>20,635</td>\r\n\t\t\t\t\t<td>21,021</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 00분</td>\r\n\t\t\t\t\t<td>1,299</td>\r\n\t\t\t\t\t<td>22,052</td>\r\n\t\t\t\t\t<td>3,517</td>\r\n\t\t\t\t\t<td>20,668</td>\r\n\t\t\t\t\t<td>21,031</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 05분</td>\r\n\t\t\t\t\t<td>1,341</td>\r\n\t\t\t\t\t<td>22,143</td>\r\n\t\t\t\t\t<td>3,566</td>\r\n\t\t\t\t\t<td>20,380</td>\r\n\t\t\t\t\t<td>21,035</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 10분</td>\r\n\t\t\t\t\t<td>1,373</td>\r\n\t\t\t\t\t<td>22,386</td>\r\n\t\t\t\t\t<td>3,593</td>\r\n\t\t\t\t\t<td>20,401</td>\r\n\t\t\t\t\t<td>21,031</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 15분</td>\r\n\t\t\t\t\t<td>1,358</td>\r\n\t\t\t\t\t<td>22,448</td>\r\n\t\t\t\t\t<td>3,666</td>\r\n\t\t\t\t\t<td>20,465</td>\r\n\t\t\t\t\t<td>21,030</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 20분</td>\r\n\t\t\t\t\t<td>1,412</td>\r\n\t\t\t\t\t<td>22,632</td>\r\n\t\t\t\t\t<td>3,679</td>\r\n\t\t\t\t\t<td>20,674</td>\r\n\t\t\t\t\t<td>21,028</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 25분</td>\r\n\t\t\t\t\t<td>1,785</td>\r\n\t\t\t\t\t<td>22,616</td>\r\n\t\t\t\t\t<td>3,680</td>\r\n\t\t\t\t\t<td>21,100</td>\r\n\t\t\t\t\t<td>21,019</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 30분</td>\r\n\t\t\t\t\t<td>2,153</td>\r\n\t\t\t\t\t<td>22,290</td>\r\n\t\t\t\t\t<td>3,700</td>\r\n\t\t\t\t\t<td>20,975</td>\r\n\t\t\t\t\t<td>21,013</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 35분</td>\r\n\t\t\t\t\t<td>2,185</td>\r\n\t\t\t\t\t<td>22,225</td>\r\n\t\t\t\t\t<td>3,697</td>\r\n\t\t\t\t\t<td>21,088</td>\r\n\t\t\t\t\t<td>21,020</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 40분</td>\r\n\t\t\t\t\t<td>2,189</td>\r\n\t\t\t\t\t<td>22,440</td>\r\n\t\t\t\t\t<td>3,709</td>\r\n\t\t\t\t\t<td>21,210</td>\r\n\t\t\t\t\t<td>21,025</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 45분</td>\r\n\t\t\t\t\t<td>2,346</td>\r\n\t\t\t\t\t<td>22,699</td>\r\n\t\t\t\t\t<td>3,720</td>\r\n\t\t\t\t\t<td>21,439</td>\r\n\t\t\t\t\t<td>21,018</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 50분</td>\r\n\t\t\t\t\t<td>2,384</td>\r\n\t\t\t\t\t<td>22,784</td>\r\n\t\t\t\t\t<td>3,722</td>\r\n\t\t\t\t\t<td>21,558</td>\r\n\t\t\t\t\t<td>21,037</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 15시 55분</td>\r\n\t\t\t\t\t<td>2,421</td>\r\n\t\t\t\t\t<td>22,931</td>\r\n\t\t\t\t\t<td>3,727</td>\r\n\t\t\t\t\t<td>21,687</td>\r\n\t\t\t\t\t<td>21,042</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 00분</td>\r\n\t\t\t\t\t<td>2,424</td>\r\n\t\t\t\t\t<td>22,966</td>\r\n\t\t\t\t\t<td>3,731</td>\r\n\t\t\t\t\t<td>21,766</td>\r\n\t\t\t\t\t<td>21,025</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 05분</td>\r\n\t\t\t\t\t<td>2,346</td>\r\n\t\t\t\t\t<td>22,688</td>\r\n\t\t\t\t\t<td>3,735</td>\r\n\t\t\t\t\t<td>22,134</td>\r\n\t\t\t\t\t<td>21,034</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 10분</td>\r\n\t\t\t\t\t<td>2,387</td>\r\n\t\t\t\t\t<td>22,921</td>\r\n\t\t\t\t\t<td>3,758</td>\r\n\t\t\t\t\t<td>22,313</td>\r\n\t\t\t\t\t<td>21,025</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 15분</td>\r\n\t\t\t\t\t<td>2,591</td>\r\n\t\t\t\t\t<td>23,003</td>\r\n\t\t\t\t\t<td>3,917</td>\r\n\t\t\t\t\t<td>22,439</td>\r\n\t\t\t\t\t<td>21,038</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 20분</td>\r\n\t\t\t\t\t<td>2,605</td>\r\n\t\t\t\t\t<td>22,968</td>\r\n\t\t\t\t\t<td>4,005</td>\r\n\t\t\t\t\t<td>22,627</td>\r\n\t\t\t\t\t<td>21,020</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 25분</td>\r\n\t\t\t\t\t<td>2,479</td>\r\n\t\t\t\t\t<td>23,154</td>\r\n\t\t\t\t\t<td>3,999</td>\r\n\t\t\t\t\t<td>22,791</td>\r\n\t\t\t\t\t<td>21,035</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 30분</td>\r\n\t\t\t\t\t<td>2,518</td>\r\n\t\t\t\t\t<td>23,085</td>\r\n\t\t\t\t\t<td>4,041</td>\r\n\t\t\t\t\t<td>23,072</td>\r\n\t\t\t\t\t<td>21,032</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 35분</td>\r\n\t\t\t\t\t<td>2,409</td>\r\n\t\t\t\t\t<td>23,244</td>\r\n\t\t\t\t\t<td>4,020</td>\r\n\t\t\t\t\t<td>23,109</td>\r\n\t\t\t\t\t<td>21,041</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 40분</td>\r\n\t\t\t\t\t<td>2,452</td>\r\n\t\t\t\t\t<td>23,322</td>\r\n\t\t\t\t\t<td>4,054</td>\r\n\t\t\t\t\t<td>23,290</td>\r\n\t\t\t\t\t<td>21,031</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 45분</td>\r\n\t\t\t\t\t<td>2,429</td>\r\n\t\t\t\t\t<td>23,506</td>\r\n\t\t\t\t\t<td>4,066</td>\r\n\t\t\t\t\t<td>23,205</td>\r\n\t\t\t\t\t<td>21,004</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 50분</td>\r\n\t\t\t\t\t<td>2,431</td>\r\n\t\t\t\t\t<td>23,533</td>\r\n\t\t\t\t\t<td>4,107</td>\r\n\t\t\t\t\t<td>23,297</td>\r\n\t\t\t\t\t<td>21,009</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 16시 55분</td>\r\n\t\t\t\t\t<td>2,640</td>\r\n\t\t\t\t\t<td>23,222</td>\r\n\t\t\t\t\t<td>4,100</td>\r\n\t\t\t\t\t<td>23,239</td>\r\n\t\t\t\t\t<td>21,009</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 00분</td>\r\n\t\t\t\t\t<td>2,643</td>\r\n\t\t\t\t\t<td>22,951</td>\r\n\t\t\t\t\t<td>4,131</td>\r\n\t\t\t\t\t<td>23,508</td>\r\n\t\t\t\t\t<td>21,006</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 05분</td>\r\n\t\t\t\t\t<td>2,599</td>\r\n\t\t\t\t\t<td>22,943</td>\r\n\t\t\t\t\t<td>4,138</td>\r\n\t\t\t\t\t<td>23,436</td>\r\n\t\t\t\t\t<td>21,001</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 10분</td>\r\n\t\t\t\t\t<td>2,610</td>\r\n\t\t\t\t\t<td>23,178</td>\r\n\t\t\t\t\t<td>4,210</td>\r\n\t\t\t\t\t<td>23,386</td>\r\n\t\t\t\t\t<td>21,008</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 15분</td>\r\n\t\t\t\t\t<td>2,662</td>\r\n\t\t\t\t\t<td>23,154</td>\r\n\t\t\t\t\t<td>4,283</td>\r\n\t\t\t\t\t<td>23,556</td>\r\n\t\t\t\t\t<td>21,000</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 20분</td>\r\n\t\t\t\t\t<td>2,662</td>\r\n\t\t\t\t\t<td>23,199</td>\r\n\t\t\t\t\t<td>4,335</td>\r\n\t\t\t\t\t<td>23,795</td>\r\n\t\t\t\t\t<td>21,006</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 25분</td>\r\n\t\t\t\t\t<td>2,622</td>\r\n\t\t\t\t\t<td>23,328</td>\r\n\t\t\t\t\t<td>4,360</td>\r\n\t\t\t\t\t<td>23,828</td>\r\n\t\t\t\t\t<td>21,008</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 30분</td>\r\n\t\t\t\t\t<td>2,625</td>\r\n\t\t\t\t\t<td>23,287</td>\r\n\t\t\t\t\t<td>4,423</td>\r\n\t\t\t\t\t<td>23,924</td>\r\n\t\t\t\t\t<td>21,015</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 35분</td>\r\n\t\t\t\t\t<td>2,608</td>\r\n\t\t\t\t\t<td>23,245</td>\r\n\t\t\t\t\t<td>4,434</td>\r\n\t\t\t\t\t<td>23,882</td>\r\n\t\t\t\t\t<td>21,000</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 40분</td>\r\n\t\t\t\t\t<td>2,554</td>\r\n\t\t\t\t\t<td>23,098</td>\r\n\t\t\t\t\t<td>4,444</td>\r\n\t\t\t\t\t<td>23,920</td>\r\n\t\t\t\t\t<td>21,012</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 45분</td>\r\n\t\t\t\t\t<td>2,594</td>\r\n\t\t\t\t\t<td>23,215</td>\r\n\t\t\t\t\t<td>4,458</td>\r\n\t\t\t\t\t<td>24,209</td>\r\n\t\t\t\t\t<td>20,992</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 50분</td>\r\n\t\t\t\t\t<td>2,555</td>\r\n\t\t\t\t\t<td>23,382</td>\r\n\t\t\t\t\t<td>4,474</td>\r\n\t\t\t\t\t<td>24,046</td>\r\n\t\t\t\t\t<td>21,000</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 17시 55분</td>\r\n\t\t\t\t\t<td>2,547</td>\r\n\t\t\t\t\t<td>23,429</td>\r\n\t\t\t\t\t<td>4,495</td>\r\n\t\t\t\t\t<td>23,921</td>\r\n\t\t\t\t\t<td>21,006</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 00분</td>\r\n\t\t\t\t\t<td>2,472</td>\r\n\t\t\t\t\t<td>23,412</td>\r\n\t\t\t\t\t<td>4,520</td>\r\n\t\t\t\t\t<td>24,070</td>\r\n\t\t\t\t\t<td>21,017</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 05분</td>\r\n\t\t\t\t\t<td>2,391</td>\r\n\t\t\t\t\t<td>23,177</td>\r\n\t\t\t\t\t<td>4,528</td>\r\n\t\t\t\t\t<td>24,029</td>\r\n\t\t\t\t\t<td>20,997</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 10분</td>\r\n\t\t\t\t\t<td>2,451</td>\r\n\t\t\t\t\t<td>23,103</td>\r\n\t\t\t\t\t<td>4,534</td>\r\n\t\t\t\t\t<td>23,989</td>\r\n\t\t\t\t\t<td>21,008</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 15분</td>\r\n\t\t\t\t\t<td>2,452</td>\r\n\t\t\t\t\t<td>23,280</td>\r\n\t\t\t\t\t<td>4,576</td>\r\n\t\t\t\t\t<td>24,049</td>\r\n\t\t\t\t\t<td>21,001</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 20분</td>\r\n\t\t\t\t\t<td>2,458</td>\r\n\t\t\t\t\t<td>23,384</td>\r\n\t\t\t\t\t<td>4,647</td>\r\n\t\t\t\t\t<td>24,003</td>\r\n\t\t\t\t\t<td>20,996</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 25분</td>\r\n\t\t\t\t\t<td>2,456</td>\r\n\t\t\t\t\t<td>23,459</td>\r\n\t\t\t\t\t<td>4,668</td>\r\n\t\t\t\t\t<td>24,088</td>\r\n\t\t\t\t\t<td>20,989</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 30분</td>\r\n\t\t\t\t\t<td>2,449</td>\r\n\t\t\t\t\t<td>23,571</td>\r\n\t\t\t\t\t<td>4,685</td>\r\n\t\t\t\t\t<td>24,015</td>\r\n\t\t\t\t\t<td>21,005</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 35분</td>\r\n\t\t\t\t\t<td>2,473</td>\r\n\t\t\t\t\t<td>23,456</td>\r\n\t\t\t\t\t<td>4,698</td>\r\n\t\t\t\t\t<td>24,082</td>\r\n\t\t\t\t\t<td>20,983</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 40분</td>\r\n\t\t\t\t\t<td>2,470</td>\r\n\t\t\t\t\t<td>23,513</td>\r\n\t\t\t\t\t<td>4,712</td>\r\n\t\t\t\t\t<td>24,030</td>\r\n\t\t\t\t\t<td>20,993</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 45분</td>\r\n\t\t\t\t\t<td>2,463</td>\r\n\t\t\t\t\t<td>23,676</td>\r\n\t\t\t\t\t<td>4,724</td>\r\n\t\t\t\t\t<td>24,070</td>\r\n\t\t\t\t\t<td>20,969</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 50분</td>\r\n\t\t\t\t\t<td>2,460</td>\r\n\t\t\t\t\t<td>23,760</td>\r\n\t\t\t\t\t<td>4,734</td>\r\n\t\t\t\t\t<td>23,979</td>\r\n\t\t\t\t\t<td>20,984</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 18시 55분</td>\r\n\t\t\t\t\t<td>2,498</td>\r\n\t\t\t\t\t<td>23,723</td>\r\n\t\t\t\t\t<td>4,742</td>\r\n\t\t\t\t\t<td>24,091</td>\r\n\t\t\t\t\t<td>20,968</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 00분</td>\r\n\t\t\t\t\t<td>2,463</td>\r\n\t\t\t\t\t<td>23,886</td>\r\n\t\t\t\t\t<td>4,747</td>\r\n\t\t\t\t\t<td>24,051</td>\r\n\t\t\t\t\t<td>20,991</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 05분</td>\r\n\t\t\t\t\t<td>2,464</td>\r\n\t\t\t\t\t<td>23,664</td>\r\n\t\t\t\t\t<td>4,761</td>\r\n\t\t\t\t\t<td>23,964</td>\r\n\t\t\t\t\t<td>20,978</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 10분</td>\r\n\t\t\t\t\t<td>2,492</td>\r\n\t\t\t\t\t<td>23,748</td>\r\n\t\t\t\t\t<td>4,794</td>\r\n\t\t\t\t\t<td>24,166</td>\r\n\t\t\t\t\t<td>20,983</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 15분</td>\r\n\t\t\t\t\t<td>2,479</td>\r\n\t\t\t\t\t<td>23,922</td>\r\n\t\t\t\t\t<td>4,827</td>\r\n\t\t\t\t\t<td>24,169</td>\r\n\t\t\t\t\t<td>20,977</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 20분</td>\r\n\t\t\t\t\t<td>2,462</td>\r\n\t\t\t\t\t<td>23,735</td>\r\n\t\t\t\t\t<td>4,849</td>\r\n\t\t\t\t\t<td>24,029</td>\r\n\t\t\t\t\t<td>20,984</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 25분</td>\r\n\t\t\t\t\t<td>2,459</td>\r\n\t\t\t\t\t<td>23,580</td>\r\n\t\t\t\t\t<td>4,866</td>\r\n\t\t\t\t\t<td>24,087</td>\r\n\t\t\t\t\t<td>20,974</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 30분</td>\r\n\t\t\t\t\t<td>2,410</td>\r\n\t\t\t\t\t<td>23,400</td>\r\n\t\t\t\t\t<td>4,857</td>\r\n\t\t\t\t\t<td>24,084</td>\r\n\t\t\t\t\t<td>20,985</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 35분</td>\r\n\t\t\t\t\t<td>2,428</td>\r\n\t\t\t\t\t<td>23,361</td>\r\n\t\t\t\t\t<td>4,844</td>\r\n\t\t\t\t\t<td>24,127</td>\r\n\t\t\t\t\t<td>20,994</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 40분</td>\r\n\t\t\t\t\t<td>2,421</td>\r\n\t\t\t\t\t<td>23,266</td>\r\n\t\t\t\t\t<td>4,845</td>\r\n\t\t\t\t\t<td>24,170</td>\r\n\t\t\t\t\t<td>20,998</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 45분</td>\r\n\t\t\t\t\t<td>2,403</td>\r\n\t\t\t\t\t<td>23,017</td>\r\n\t\t\t\t\t<td>4,834</td>\r\n\t\t\t\t\t<td>24,004</td>\r\n\t\t\t\t\t<td>20,995</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 50분</td>\r\n\t\t\t\t\t<td>2,373</td>\r\n\t\t\t\t\t<td>22,712</td>\r\n\t\t\t\t\t<td>4,815</td>\r\n\t\t\t\t\t<td>23,999</td>\r\n\t\t\t\t\t<td>20,997</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 19시 55분</td>\r\n\t\t\t\t\t<td>2,388</td>\r\n\t\t\t\t\t<td>22,464</td>\r\n\t\t\t\t\t<td>4,815</td>\r\n\t\t\t\t\t<td>23,904</td>\r\n\t\t\t\t\t<td>20,996</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 00분</td>\r\n\t\t\t\t\t<td>2,361</td>\r\n\t\t\t\t\t<td>22,343</td>\r\n\t\t\t\t\t<td>4,788</td>\r\n\t\t\t\t\t<td>23,904</td>\r\n\t\t\t\t\t<td>21,009</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 05분</td>\r\n\t\t\t\t\t<td>2,280</td>\r\n\t\t\t\t\t<td>22,163</td>\r\n\t\t\t\t\t<td>4,757</td>\r\n\t\t\t\t\t<td>23,736</td>\r\n\t\t\t\t\t<td>21,009</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 10분</td>\r\n\t\t\t\t\t<td>2,344</td>\r\n\t\t\t\t\t<td>22,229</td>\r\n\t\t\t\t\t<td>4,704</td>\r\n\t\t\t\t\t<td>23,789</td>\r\n\t\t\t\t\t<td>20,994</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 15분</td>\r\n\t\t\t\t\t<td>2,302</td>\r\n\t\t\t\t\t<td>22,062</td>\r\n\t\t\t\t\t<td>4,694</td>\r\n\t\t\t\t\t<td>23,716</td>\r\n\t\t\t\t\t<td>20,992</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 20분</td>\r\n\t\t\t\t\t<td>2,283</td>\r\n\t\t\t\t\t<td>21,668</td>\r\n\t\t\t\t\t<td>4,683</td>\r\n\t\t\t\t\t<td>23,865</td>\r\n\t\t\t\t\t<td>20,993</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 25분</td>\r\n\t\t\t\t\t<td>2,282</td>\r\n\t\t\t\t\t<td>21,590</td>\r\n\t\t\t\t\t<td>4,663</td>\r\n\t\t\t\t\t<td>23,678</td>\r\n\t\t\t\t\t<td>21,006</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 30분</td>\r\n\t\t\t\t\t<td>2,255</td>\r\n\t\t\t\t\t<td>21,194</td>\r\n\t\t\t\t\t<td>4,644</td>\r\n\t\t\t\t\t<td>23,573</td>\r\n\t\t\t\t\t<td>21,008</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 35분</td>\r\n\t\t\t\t\t<td>2,295</td>\r\n\t\t\t\t\t<td>21,045</td>\r\n\t\t\t\t\t<td>4,631</td>\r\n\t\t\t\t\t<td>23,715</td>\r\n\t\t\t\t\t<td>20,997</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 40분</td>\r\n\t\t\t\t\t<td>2,273</td>\r\n\t\t\t\t\t<td>20,979</td>\r\n\t\t\t\t\t<td>4,612</td>\r\n\t\t\t\t\t<td>23,680</td>\r\n\t\t\t\t\t<td>21,004</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 45분</td>\r\n\t\t\t\t\t<td>2,276</td>\r\n\t\t\t\t\t<td>20,634</td>\r\n\t\t\t\t\t<td>4,592</td>\r\n\t\t\t\t\t<td>23,674</td>\r\n\t\t\t\t\t<td>20,992</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 50분</td>\r\n\t\t\t\t\t<td>2,264</td>\r\n\t\t\t\t\t<td>20,176</td>\r\n\t\t\t\t\t<td>4,562</td>\r\n\t\t\t\t\t<td>23,598</td>\r\n\t\t\t\t\t<td>20,982</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 20시 55분</td>\r\n\t\t\t\t\t<td>2,290</td>\r\n\t\t\t\t\t<td>20,296</td>\r\n\t\t\t\t\t<td>4,539</td>\r\n\t\t\t\t\t<td>23,779</td>\r\n\t\t\t\t\t<td>20,982</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 00분</td>\r\n\t\t\t\t\t<td>2,147</td>\r\n\t\t\t\t\t<td>20,034</td>\r\n\t\t\t\t\t<td>4,501</td>\r\n\t\t\t\t\t<td>23,730</td>\r\n\t\t\t\t\t<td>21,013</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 05분</td>\r\n\t\t\t\t\t<td>1,922</td>\r\n\t\t\t\t\t<td>20,145</td>\r\n\t\t\t\t\t<td>4,477</td>\r\n\t\t\t\t\t<td>23,673</td>\r\n\t\t\t\t\t<td>20,992</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 10분</td>\r\n\t\t\t\t\t<td>1,934</td>\r\n\t\t\t\t\t<td>20,034</td>\r\n\t\t\t\t\t<td>4,430</td>\r\n\t\t\t\t\t<td>23,726</td>\r\n\t\t\t\t\t<td>21,005</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 15분</td>\r\n\t\t\t\t\t<td>1,927</td>\r\n\t\t\t\t\t<td>19,838</td>\r\n\t\t\t\t\t<td>4,341</td>\r\n\t\t\t\t\t<td>23,810</td>\r\n\t\t\t\t\t<td>21,006</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 20분</td>\r\n\t\t\t\t\t<td>1,920</td>\r\n\t\t\t\t\t<td>19,527</td>\r\n\t\t\t\t\t<td>4,294</td>\r\n\t\t\t\t\t<td>23,538</td>\r\n\t\t\t\t\t<td>21,006</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 25분</td>\r\n\t\t\t\t\t<td>1,906</td>\r\n\t\t\t\t\t<td>19,351</td>\r\n\t\t\t\t\t<td>4,253</td>\r\n\t\t\t\t\t<td>23,561</td>\r\n\t\t\t\t\t<td>21,013</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 30분</td>\r\n\t\t\t\t\t<td>1,926</td>\r\n\t\t\t\t\t<td>19,256</td>\r\n\t\t\t\t\t<td>4,222</td>\r\n\t\t\t\t\t<td>23,505</td>\r\n\t\t\t\t\t<td>20,984</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 35분</td>\r\n\t\t\t\t\t<td>1,818</td>\r\n\t\t\t\t\t<td>19,026</td>\r\n\t\t\t\t\t<td>4,206</td>\r\n\t\t\t\t\t<td>23,554</td>\r\n\t\t\t\t\t<td>21,004</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 40분</td>\r\n\t\t\t\t\t<td>1,639</td>\r\n\t\t\t\t\t<td>18,836</td>\r\n\t\t\t\t\t<td>4,162</td>\r\n\t\t\t\t\t<td>23,537</td>\r\n\t\t\t\t\t<td>21,014</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 45분</td>\r\n\t\t\t\t\t<td>1,638</td>\r\n\t\t\t\t\t<td>18,770</td>\r\n\t\t\t\t\t<td>4,130</td>\r\n\t\t\t\t\t<td>23,514</td>\r\n\t\t\t\t\t<td>20,990</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 50분</td>\r\n\t\t\t\t\t<td>1,643</td>\r\n\t\t\t\t\t<td>18,448</td>\r\n\t\t\t\t\t<td>4,099</td>\r\n\t\t\t\t\t<td>23,489</td>\r\n\t\t\t\t\t<td>21,015</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 21시 55분</td>\r\n\t\t\t\t\t<td>1,642</td>\r\n\t\t\t\t\t<td>18,439</td>\r\n\t\t\t\t\t<td>4,072</td>\r\n\t\t\t\t\t<td>23,470</td>\r\n\t\t\t\t\t<td>21,021</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 00분</td>\r\n\t\t\t\t\t<td>1,643</td>\r\n\t\t\t\t\t<td>18,336</td>\r\n\t\t\t\t\t<td>4,047</td>\r\n\t\t\t\t\t<td>23,534</td>\r\n\t\t\t\t\t<td>20,998</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 05분</td>\r\n\t\t\t\t\t<td>1,648</td>\r\n\t\t\t\t\t<td>18,450</td>\r\n\t\t\t\t\t<td>4,018</td>\r\n\t\t\t\t\t<td>23,452</td>\r\n\t\t\t\t\t<td>20,993</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 10분</td>\r\n\t\t\t\t\t<td>1,638</td>\r\n\t\t\t\t\t<td>18,352</td>\r\n\t\t\t\t\t<td>3,980</td>\r\n\t\t\t\t\t<td>23,646</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 15분</td>\r\n\t\t\t\t\t<td>1,603</td>\r\n\t\t\t\t\t<td>18,242</td>\r\n\t\t\t\t\t<td>3,963</td>\r\n\t\t\t\t\t<td>23,689</td>\r\n\t\t\t\t\t<td>21,025</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 20분</td>\r\n\t\t\t\t\t<td>1,639</td>\r\n\t\t\t\t\t<td>18,129</td>\r\n\t\t\t\t\t<td>3,935</td>\r\n\t\t\t\t\t<td>23,889</td>\r\n\t\t\t\t\t<td>21,018</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 25분</td>\r\n\t\t\t\t\t<td>1,606</td>\r\n\t\t\t\t\t<td>17,946</td>\r\n\t\t\t\t\t<td>3,905</td>\r\n\t\t\t\t\t<td>23,823</td>\r\n\t\t\t\t\t<td>20,999</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 30분</td>\r\n\t\t\t\t\t<td>1,607</td>\r\n\t\t\t\t\t<td>17,660</td>\r\n\t\t\t\t\t<td>3,888</td>\r\n\t\t\t\t\t<td>23,739</td>\r\n\t\t\t\t\t<td>21,017</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 35분</td>\r\n\t\t\t\t\t<td>1,594</td>\r\n\t\t\t\t\t<td>17,515</td>\r\n\t\t\t\t\t<td>3,879</td>\r\n\t\t\t\t\t<td>23,673</td>\r\n\t\t\t\t\t<td>21,019</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 40분</td>\r\n\t\t\t\t\t<td>1,604</td>\r\n\t\t\t\t\t<td>17,398</td>\r\n\t\t\t\t\t<td>3,865</td>\r\n\t\t\t\t\t<td>23,760</td>\r\n\t\t\t\t\t<td>21,026</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 45분</td>\r\n\t\t\t\t\t<td>1,614</td>\r\n\t\t\t\t\t<td>17,109</td>\r\n\t\t\t\t\t<td>3,860</td>\r\n\t\t\t\t\t<td>23,758</td>\r\n\t\t\t\t\t<td>21,016</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 50분</td>\r\n\t\t\t\t\t<td>1,592</td>\r\n\t\t\t\t\t<td>16,936</td>\r\n\t\t\t\t\t<td>3,858</td>\r\n\t\t\t\t\t<td>23,787</td>\r\n\t\t\t\t\t<td>21,018</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 22시 55분</td>\r\n\t\t\t\t\t<td>1,589</td>\r\n\t\t\t\t\t<td>16,769</td>\r\n\t\t\t\t\t<td>3,854</td>\r\n\t\t\t\t\t<td>23,653</td>\r\n\t\t\t\t\t<td>21,023</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 00분</td>\r\n\t\t\t\t\t<td>1,597</td>\r\n\t\t\t\t\t<td>16,684</td>\r\n\t\t\t\t\t<td>3,853</td>\r\n\t\t\t\t\t<td>23,665</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 05분</td>\r\n\t\t\t\t\t<td>1,588</td>\r\n\t\t\t\t\t<td>16,718</td>\r\n\t\t\t\t\t<td>3,851</td>\r\n\t\t\t\t\t<td>23,539</td>\r\n\t\t\t\t\t<td>21,013</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 10분</td>\r\n\t\t\t\t\t<td>1,401</td>\r\n\t\t\t\t\t<td>16,600</td>\r\n\t\t\t\t\t<td>3,835</td>\r\n\t\t\t\t\t<td>23,636</td>\r\n\t\t\t\t\t<td>21,028</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 15분</td>\r\n\t\t\t\t\t<td>1,405</td>\r\n\t\t\t\t\t<td>16,461</td>\r\n\t\t\t\t\t<td>3,820</td>\r\n\t\t\t\t\t<td>23,568</td>\r\n\t\t\t\t\t<td>21,022</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 20분</td>\r\n\t\t\t\t\t<td>1,407</td>\r\n\t\t\t\t\t<td>16,314</td>\r\n\t\t\t\t\t<td>3,813</td>\r\n\t\t\t\t\t<td>23,564</td>\r\n\t\t\t\t\t<td>21,018</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 25분</td>\r\n\t\t\t\t\t<td>1,400</td>\r\n\t\t\t\t\t<td>15,919</td>\r\n\t\t\t\t\t<td>3,811</td>\r\n\t\t\t\t\t<td>23,462</td>\r\n\t\t\t\t\t<td>21,017</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 30분</td>\r\n\t\t\t\t\t<td>1,397</td>\r\n\t\t\t\t\t<td>15,557</td>\r\n\t\t\t\t\t<td>3,812</td>\r\n\t\t\t\t\t<td>23,284</td>\r\n\t\t\t\t\t<td>21,029</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 35분</td>\r\n\t\t\t\t\t<td>1,399</td>\r\n\t\t\t\t\t<td>15,435</td>\r\n\t\t\t\t\t<td>3,804</td>\r\n\t\t\t\t\t<td>23,271</td>\r\n\t\t\t\t\t<td>21,019</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 40분</td>\r\n\t\t\t\t\t<td>1,400</td>\r\n\t\t\t\t\t<td>15,103</td>\r\n\t\t\t\t\t<td>3,789</td>\r\n\t\t\t\t\t<td>23,269</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 45분</td>\r\n\t\t\t\t\t<td>1,390</td>\r\n\t\t\t\t\t<td>14,911</td>\r\n\t\t\t\t\t<td>3,787</td>\r\n\t\t\t\t\t<td>23,302</td>\r\n\t\t\t\t\t<td>21,015</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 50분</td>\r\n\t\t\t\t\t<td>1,370</td>\r\n\t\t\t\t\t<td>14,574</td>\r\n\t\t\t\t\t<td>3,783</td>\r\n\t\t\t\t\t<td>23,196</td>\r\n\t\t\t\t\t<td>21,024</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t\t\t<tr>\r\n\t\t\t\t\t<td>2023년 09월 01일 23시 55분</td>\r\n\t\t\t\t\t<td>1,381</td>\r\n\t\t\t\t\t<td>14,224</td>\r\n\t\t\t\t\t<td>3,788</td>\r\n\t\t\t\t\t<td>22,897</td>\r\n\t\t\t\t\t<td>21,028</td>\r\n\t\t\t\t</tr>\r\n\t\t\t\r\n\t\t</tbody>\r\n\t</table>\r\n</div>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/KPX/realtime.html",
    "content": "\n\n\n\n\n\n\n\n\n<!DOCTYPE html>\n\n\n\n\n\n\n\n\n<html lang=\"ko\">\n<head>\n<meta charset=\"UTF-8\" />\n<meta name=\"_csrf_parameter\" content=\"_csrf\" /><meta name=\"_csrf_header\" content=\"X-XSRF-TOKEN\" /><meta name=\"_csrf\" content=\"cc29bc11-037e-4e72-95ee-c4295424f505\" />\n<meta http-equiv=\"X-UA-Compatible\" content=\"IE=edge\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,user-scalable=yes\" />\n\n<meta name=\"title\" content=\"실시간 전력수급현황 | 전력관련정보 | 부가메뉴 : 전력거래소\" />\n<meta name=\"description\" content=\"전력거래소,실시간 전력수급현황 | 전력관련정보 | 부가메뉴\" />\n<meta name=\"keyword\" content=\"KPX\" />\n<meta name=\"author\" content=\"전력거래소\" />\n\n<meta property=\"og:type\" content=\"website\" />\n<meta property=\"og:site_name\" content=\"전력거래소\" />\n<meta property=\"og:title\" content=\"실시간 전력수급현황 | 전력관련정보 | 부가메뉴 : 전력거래소\" />\n<meta property=\"og:url\" content=\"https://www.kpx.or.kr/powerinfoSubmain.es?mid=a10606030000\" />\n<meta property=\"og:description\" content=\"전력거래소\" />\n\n<title>실시간 전력수급현황 | 전력관련정보 | 부가메뉴 : 전력거래소</title>\n\n<link rel=\"shortcut icon\" href=\"/favicon.ico\" type=\"image/x-icon\" />\n\n\n                   \n<link rel=\"stylesheet\" href=\"/main/css/default.css\" />\n<link rel=\"stylesheet\" href=\"/main/css/layout.css\" />\n<link rel=\"stylesheet\" href=\"/main/css/layout_respond.css\" />\t\n\n                   \n\n<link rel=\"stylesheet\" href=\"/main/css/sub.css\" />\n<link rel=\"stylesheet\" href=\"/main/css/sub_respond.css\" />\n<link rel=\"stylesheet\" href=\"/main/css/sub_es.css\" />\n<link rel=\"stylesheet\" href=\"/main/css/content.css\" />\n<link rel=\"stylesheet\" href=\"/main/css/content_respond.css\" />\n<link rel=\"stylesheet\" href=\"/jquery/css/jquery.mCustomScrollbar.min.css\" />\t\n\n\n\n<link rel=\"stylesheet\" type=\"text/css\" href=\"/jquery/css/slick.css\">\n<link rel=\"stylesheet\" type=\"text/css\" href=\"/jquery/css/fullpage.css\">\n<link rel=\"stylesheet\" href=\"/jquery/css/jquery.bxslider.css\" />\t\n                  \n<script src=\"/jquery/js/jquery-1.12.4.min.js\"></script>\n<script src=\"/jquery/js/jquery.fullPage.min.js\"></script>\n<script src=\"/js/global.js\"></script>\n<script src=\"/jquery/js/jquery.bxslider.min.js\"></script>\n<script src=\"/jquery/js/slick.js\"></script>\n<script src=\"/ease_src/js/captchaboard.js\"></script>\n\n                  \n<script src=\"/ease_src/sEditor/js/HuskyEZCreator.js\" charset=\"UTF-8\"></script>\n\n\n<script src=\"/jquery/js/jquery.mCustomScrollbar.concat.min.js\"></script>\n\n</head>\n<body>\n\n\n\n\n\n\n\n\n<link rel=\"stylesheet\" href=\"/css/modalpopup.css\" />\n\n\t\n\t\n\t\t<div id=\"issue\">\n\t\n\n\n\t\n\t<div class=\"tt\">\n\t\t<a href=\"\" class=\"control open\">\n\t\t\t<em>POPUP</em>\n\t\t\t<span class=\"count\"><strong>0</strong><span>건</span></span>\n\t\t</a>\n\t</div>\n\t\n\t<article class=\"modal group\">\n\t\t<h2 class=\"title\">주요알림</h2>\n\t\t\n\t\t\n\t\t\n\t\t<div class=\"list\">\n\t\t\t\n\t\t\t<div class=\"img\">\n\t\t\t\t\n\t\t\t\t\t<a href=\"/board.es?mid=a10102090000&bid=0151&act=view&list_no=74050\" target=\"_self\"><img src=\"/upload/modalpopup/a1/20250103142126142.png\" onerror=\"this.src='/error/img/noimage.jpg'\" alt=\"국민권익위원회 주관 2022년도 공공기관 종합청렴도 평가 결과\" /></a>\n\t\t\t\t\n\t\t\t\t\n\t\t\t</div>\n\t\t\t\n\t\t\t<div class=\"img\">\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t<img src=\"/upload/modalpopup/a1/20250102160134222.png\" onerror=\"this.src='/error/img/noimage.jpg'\" alt=\"여객기 사고 희생자 애도\" />\n\t\t\t\t\n\t\t\t</div>\n\t\t\t\n\t\t\t<div class=\"img\">\n\t\t\t\t\n\t\t\t\t\t<a href=\"https://edu.kpx.or.kr\" target=\"_blank\" title=\"새창\" rel=\"noopener\"><img src=\"/upload/modalpopup/a1/20241219084635134.png\" onerror=\"this.src='/error/img/noimage.jpg'\" alt=\"25년 제1기 신재생창업스쿨 홍보팝업\" /></a>\n\t\t\t\t\n\t\t\t\t\n\t\t\t</div>\n\t\t\t\n\t\t</div>\n\t\t\n\t\t\n\t\t\n\t    \n\t    <div class=\"item\">\n            <p class=\"label\">팝업건수 : 총 <span class=\"count\">0</span>건</p>\n            \n            <a href=\"\" class=\"control close\">닫기</a>\n            <a href=\"\" class=\"control close oneday\" data-focus=\"popup_focus01\" data-focus-next=\"popup_focus01\">오늘하루열지않기</a>\n        </div>\n        \n    \t<div class=\"close_box\">닫기</div>       \n    </article>\n</div>\n<script src=\"/jquery/jstree/_lib/jquery.cookie.js\"></script>\t\n<script>\n\n// 팝업 갯수\nvar issuecount = $(\"#issue .group .list .img\").length;\n$('#issue .count strong, #issue .item .count').text(issuecount);\n\n// 팝업 열고 닫기\n$('#issue').find('.control').on('click', function() {\n\tif ( $(this).hasClass('open') == true ) {\n\t\t$('#issue').addClass('active');\n\t}\n\telse {\n\t\t$('#issue').removeClass('active');\n\t}\n\treturn false;\n});\n$('#issue .close_box').on('click', function() {\n\t$('#issue').removeClass('active');\n\treturn false;\n});\n\n$('#issue .group .list').slick({\n\tdraggable: true,\n\tarrows: true,\n\tdots: true,\n\tspeed: 700,\n\tmobileFirst: true,\n\tpauseOnDotsHover: true,\n    responsive: [\n       {\n         breakpoint: 640,\n         settings: {\n           slidesToShow: 3,\n           slidesToScroll:1\n         }\n       },\n       {\n           breakpoint: 639,  \n           settings: {\n             slidesToShow: 2,\n             slidesToScroll:1\n           }\n         }\n     ]\n});\n\n\n\n\n$(function(){\n    //  오늘하루열지않기\n    $('.oneday').on('click', function () {\n    \t$('#issue').removeClass(\"active\");\n\t\t    // $('#issue').css(\"display\",\"none\");\n    \tvar name = \"a1.oneday.open\";\n    \tvar value\t= \"1\";\n    \tvar expiredays = 1;    \t\n\t\tvar expire_date = new Date() ;  //오늘날짜를  대입값으로 설정한다.\n\t\tvar secure = location.protocol == 'https:' ? ' secure;' : '';\n\t\texpire_date.setDate(expire_date.getDate() + expiredays) ;\n\t\t$.cookie(name,value,{expires: expiredays});\n\t\t// $.ajax(\"/ondayOpen.es?name=\"+name);\n    });\n    $(\"#popup_cnt\").html('03');\n    if(03 == 0){\n     $(\"#modal_popup\").css(\"display\",\"none\");\n    }\n    \n    // 팝업 열고 닫기\n\t$('#quick').find('.control').on('click', function() {\n\t\tif ( $(this).hasClass('open') == true ) {\n\t\t\t$('#issue').addClass('active');\n\t\t}\n\t\telse {\n\t\t\t$('#issue').removeClass('active');\n\t\t}\n\t\treturn false;\n\t});\n\t//$('.slick-slide').attr(\"tabindex\",\"1\");\n\t//$('.slick-cloned').attr(\"tabindex\",\"-1\");\n\t$('.slick-dots > li > button').attr(\"tabindex\",\"0\");\n\t//$('.modal .prev').attr(\"data-focus-next\",\"popup_focus_arrow01\");\n\t//$('.modal .next').attr(\"data-focus\",\"popup_focus_arrow01\");\n\t\n\t\n})\n</script>\n<p id=\"skip_nav\">\n\t<a href=\"#contents_body\" class=\"cont_link\">본문으로 바로가기</a>\n\t<a href=\"#main\" class=\"main_link\">메인 본문으로 바로가기</a>\n</p>\n\n<div id=\"hiddenLayer\" style=\"display:none\"></div>\n<div class=\"mw\" id=\"mw_temp\" style=\"display:none;\"></div>\n\n<div id=\"wrap\">\n\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t<header id=\"header\">\n\t\t\n\n<h1 class=\"logo\"><a href=\"/main/\">전력거래소</a></h1>\n<div id=\"hnb\">\n    <ul class=\"hnb2\">\n                                                                                                                                                                                                                                                                                                                                                              \n        <li class=\"global\" id=\"global\">\n            <a href=\"#main\" class=\"active\">KOR<span class=\"blind\">언어선택 열기</span></a>\n        \t<div class=\"lang\">\n\t            <a href=\"/main/\">KOR<span class=\"hidden\">국문 사이트</span></a>\n\t            <a href=\"/eng/\">ENG<span class=\"hidden\">영문 사이트</span></a>\n            </div>\n        </li>        \n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\t<li class=\"login\" style=\"z-index: 999;margin:0 25px 0 11px;\"><a href=\"/loginPin_search.es?sid=a1\" title=\"로그인\"><i class=\"xi-lock-o\"></i>로그인</a></li>\n\t\t\t\n\t\t\t\n\n\t\t<li class=\"hnb_search\"><a href=\"\" class=\"label\">검색<span class=\"blind\">열기</span></a></li>\n\t</ul>\n</div>\n<div class=\"search\">\n\t<div class=\"form\">\n\t\t<form id=\"searchForm\" name=\"searchForm\" action=\"/findeepSearch.es?mid=a10700000000\" method=\"post\">\n\t\t\t<label for=\"search\" class=\"IR\">검색</label>\n\t\t\t<input type=\"text\" placeholder=\"검색어를 입력해 주세요\" class=\"search_keyword\" id=\"search\" name=\"allKeyWord\" value=\"\" title=\"검색\">\n\t\t\t<button type=\"submit\" name=\"button\" onclick=\"document.searchForm.submit(); return false;\">검색</button>\n\t\t<div>\n<input type=\"hidden\" name=\"_csrf\" value=\"cc29bc11-037e-4e72-95ee-c4295424f505\" />\n</div></form>\n\t</div>\n\t<button type=\"button\" class=\"close\">닫기</button>\n</div>\n\t\t<nav id=\"gnb\">\n\t\t\t\n\n<ul id=\"head_menu\" class=\"topmenu\">\n\t<li class=\"lnb1 mnfirst\">\n\t\t<a href=\"/menu.es?mid=a10301010000\">KPX소개</a>\n\t\t<div class=\"submenu\" style=\"display:none;\">\n\t\t\t\n\n\t\t\t<ul class=\"sub03\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a10301010000\">전력거래소는?</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301010000\">회사개요</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301020000\">주요역할</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301030000\">비전 및 경영전략</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301060000\">CI소개</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301070100\">찾아오시는 길</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a10303010000\">CEO 소개</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10303010000\">인사말</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10303020000\">약력</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a10302010000\">조직구성</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10302010200\">조직소개</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10302020100\">임원구성 및 선임절차</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a10304000000\">회원사 현황</a></li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"https://kpx.saramin.co.kr/\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"새창으로 이동\" class=\"linkWindow\">채용안내</a></li>\n\t\t\t</ul>\n\t\t\t\n\n\t\t</div>\n\t</li>\n\t<li class=\"lnb2\">\n\t\t<a href=\"/menu.es?mid=a10201000000\">열린경영</a>\n\t\t<div class=\"submenu\" style=\"display:none;\">\n\t\t\t\n\n\t\t\t<ul class=\"sub02\">\n\t\t\t\t<li class=\"sub11 subfirst\"><a href=\"/menu.es?mid=a10211010000\">국민의 의견을 듣습니다</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10211010000\">국민제안 이용안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10211020000\">국민제안 접수 및 조회</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub12\"><a href=\"/menu.es?mid=a10212010000\">적극행정</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212010000\">적극행정이란</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212020000\">전력거래소 적극행정 추진방안</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212030000\">적극행정 우수사례</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212040000\">적극행정 우수직원 추천</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212050000\">소극행정 신고센터</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212060000\">적극행정 소통 게시판</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212070000\">소극행정 혁파 소통 게시판</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub13\"><a href=\"/menu.es?mid=a10213010000\">기업성장응답센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10213010000\">기업성장응답센터는?</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10213020000\">규제애로 접수</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub14\"><a href=\"/menu.es?mid=a10214010000\">행동강령.부패신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10214010000\">신문고이용안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10214020000\">행동강령.부패신고/상담</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub15\"><a href=\"/menu.es?mid=a10215010000\">인권침해신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10215010000\">인권침해 신고접수 및 상담</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10215020000\">인권침해 사건처리 절차</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10215030000\">사건처리 원칙</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub16\"><a href=\"/menu.es?mid=a10216010000\">공익신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10216010000\">공익신고안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10216020000\">공익신고자보호안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10216030000\">구조금.보상금지급안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10216040000\">공익신고/상담</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub17\"><a href=\"/menu.es?mid=a10217010000\">예산낭비신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10217010000\">예산낭비 신고안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10217020000\">예산낭비 신고/상담</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub18\"><a href=\"/menu.es?mid=a10218010000\">안전제안(신고)센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10218010000\">안전제안/신고센터는?</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10218020000\">안전제안/신고접수</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub21\"><a href=\"/menu.es?mid=a10221010000\">인사위반 신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10221010000\">인사위반 신고센터?</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10221020000\">인사위반 신고접수</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub19 sublast\"><a href=\"/menu.es?mid=a10219000000\">신고센터 바로가기</a></li>\n\t\t\t</ul>\n\t\t\t\n\n\t\t</div>\n\t</li>\n\t<li class=\"lnb3\">\n\t\t<a href=\"/menu.es?mid=a10901050000\">ESG경영</a>\n\t\t<div class=\"submenu\" style=\"display:none;\">\n\t\t\t\n\n\t\t\t<ul class=\"sub09\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a10901050000\">ESG경영</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901050000\">CEO 인사말</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901040000\">ESG 추진전략</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901110000\">ESG 추진조직</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901130000\">ESG 성과지표</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901120100\">ESG 수상 및 인증내역</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a10902010000\">E(환경)</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10902010000\">환경경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10902070100\">친환경정책지원</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10902080100\">신재생 및 태양광 지표</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10902090000\">녹색제품 구매</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a10903020000\">S(사회)</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10903020100\">동반성장</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10903030300\">안전경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10903040100\">인권경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10903050000\">다양성 존중</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a10904010000\">G(지배구조)</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904010200\">이사회</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904040100\">ESG전략위원회</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904050100\">윤리경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904070100\">청렴경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904030000\">비상임이사 경영활동</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"/menu.es?mid=a10905000000\">지속가능경영보고서</a></li>\n\t\t\t</ul>\n\t\t\t\n\n\t\t</div>\n\t</li>\n\t<li class=\"lnb4\">\n\t\t<a href=\"/menu.es?mid=a11001010000\">법령·규칙</a>\n\t\t<div class=\"submenu\" style=\"display:none;\">\n\t\t\t\n\n\t\t\t<ul class=\"sub10\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a11001010000\">법령 및 고시</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11001010000\">법령</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11001020000\">고시</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a11002010000\">전력시장운영규칙 및 세부규정</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11002010000\">전력시장운영규칙 아카이브</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11002020000\">세부운영규정</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11002030000\">규칙개정 제안 및 자문</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11002040000\">기타</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"https://marketrule.kpx.or.kr\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"새창으로 이동\" class=\"linkWindow\">전력시장운영규칙 웹서비스</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03 sublast\"><a href=\"/menu.es?mid=a11003010000\">내규</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11003010000\">내규 공개</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11003020000\">내규·제·개정 예고</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t</ul>\n\t\t\t\n\n\t\t</div>\n\t</li>\n\t<li class=\"lnb5\">\n\t\t<a href=\"/menu.es?mid=a10101010000\">정보공개</a>\n\t\t<div class=\"submenu\" style=\"display:none;\">\n\t\t\t\n\n\t\t\t<ul class=\"sub01\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a10101010000\">정보공개제도</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101010000\">정보공개제도란?</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101020000\">정보처리절차흐름도</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101030000\">정보공개 방법</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101040000\">비공개정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101050000\">불복구제절차</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101060000\">정보공개수수료</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub06\"><a href=\"/menu.es?mid=a10106000000\">공공기관정보공개청구</a></li>\n\t\t\t\t<li class=\"sub07\"><a href=\"/menu.es?mid=a10107010000\">공공데이터 제공</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10107010000\">공공데이터 신청 및 안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10107020000\">공공데이터 목록</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10107030000\">전력데이터 큐레이션 서비스</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10107040000\">공공데이터 사업화 상담코너</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub11\"><a href=\"/menu.es?mid=a10111010000\">경영공시</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10111010000\">경영공시 안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10111020000\">ALIO 통합공시</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10111030000\">자율공시</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10111040000\">담당자 현황</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a10102090000\">사전정보공표</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10102090000\">사전정보공표 목록</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10102100000\">즐겨찾기 정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10102110000\">사전정보 모니터링</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub09\"><a href=\"/menu.es?mid=a10109010000\">전력시장·전력계통 운영정보</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109010000\">전력시장 정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109020000\">전력계통 운영정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109040000\">IT시스템 운영정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109050000\">비중앙 출력제어 정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109030000\">기타정보</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub10\"><a href=\"/menu.es?mid=a10110010000\">사업실명제</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10110010000\">사업실명제 개요</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10110020000\">대상사업 리스트</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"/menu.es?mid=a10105000000\">정보목록</a></li>\n\t\t\t</ul>\n\t\t\t\n\n\t\t</div>\n\t</li>\n\t<li class=\"lnb6\">\n\t\t<a href=\"/menu.es?mid=a10401010000\">주요사업</a>\n\t\t<div class=\"submenu\" style=\"display:none;\">\n\t\t\t\n\n\t\t\t<ul class=\"sub04\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a10401010000\">시장운영</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401010000\">전력거래절차</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401040000\">시장가격결정</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401050000\">정산처리일정</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401080000\">정산스마트 매뉴얼</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401060000\">전력시장운영협의체</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401020000\">REC거래</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401030000\">전력거래시스템</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10801000000\">전력거래 준비 안내</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a10402010000\">계통운영</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10402010000\">전력계통운영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10402030000\">단기전력수급운영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10402040000\">급전운영</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a10403010000\">전력수급</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403010000\">전력수급개요</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403020000\">전력수급계획수립절차</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403030100\">전력수요전망</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403040000\">발전소건설현황</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403050100\">계통계획</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403060100\">발전사업허가업무</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403070000\">전력수급기본계획</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403090000\">계통 수용여유량 전망</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a10404010000\">전력관련정보</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404010000\">최대부하전망</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404020000\">최대부하전망(제주)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404030000\">실시간 전력수급현황</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404040000\">실시간 전력수급현황 (제주)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404050000\">비상시 절전참여요령</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404060000\">전일 전력수급실적</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404070000\">전일 전력수급실적(제주)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404080100\">SMP(계통한계가격)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404090100\">하루전 발전계획용 수요예측</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub06\"><a href=\"/menu.es?mid=a10406010000\">제주시범사업 정보</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10406010100\">발전계획용 수요예측</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10406020100\">SMP(계통한계가격)</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"/menu.es?mid=a10405010000\">해외동향</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10405010000\">전력산업동향</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10405020000\">스마트그리드동향</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t</ul>\n\t\t\t\n\n\t\t</div>\n\t</li>\n\t<li class=\"lnb7\">\n\t\t<a href=\"/menu.es?mid=a11101000000\">통합계약정보</a>\n\t\t<div class=\"submenu\" style=\"display:none;\">\n\t\t\t\n\n\t\t\t<ul class=\"sub11\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a11101010000\">입찰공고</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11101010000\">구매.용역.공사</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a11103010000\">계약절차안내</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11103010000\">계약종류및방법</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11103020000\">업무절차도</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11103030000\">계약준비서류</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11103040000\">예상소요일수</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a11104000000\">통합자료실</a></li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"/menu.es?mid=a11105010000\">청렴계약안내</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11105010000\">청렵계약이란</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t</ul>\n\t\t\t\n\n\t\t</div>\n\t</li>\n\t<li class=\"lnb8\">\n\t\t<a href=\"/menu.es?mid=a11201000000\">소식알림</a>\n\t\t<div class=\"submenu\" style=\"display:none;\">\n\t\t\t\n\n\t\t\t<ul class=\"sub12\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a11201000000\">공지사항</a></li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a11202000000\">보도자료</a></li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a11203000000\">시장개선</a></li>\n\t\t\t\t<li class=\"sub04 sublast\"><a href=\"/menu.es?mid=a11204000000\">KPX 종합자료실</a></li>\n\t\t\t</ul>\n\t\t\t\n\n\t\t</div>\n\t</li>\n\t<li class=\"lnb9 mnlast\">\n\t\t<a href=\"/menu.es?mid=a10501010000\">고객지원</a>\n\t\t<div class=\"submenu\" style=\"display:none;\">\n\t\t\t\n\n\t\t\t<ul class=\"sub05\">\n\t\t\t\t<li class=\"sub03 subfirst\"><a href=\"/menu.es?mid=a10503010100\">고객만족</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10503010100\">고객서비스 헌장 및 이행표준</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10503020000\">친절사원을 추천하세요</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a10504010000\">KPX에 물어보세요</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10504010000\">고객질의 이용안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10504020000\">자주 받는 질문(FAQ)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10504030000\">묻고 답하기(Q&A)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10504040000\">분야별 업무담당자</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub21\"><a href=\"/menu.es?mid=a10521000000\">프로그램다운로드</a></li>\n\t\t\t\t<li class=\"sub22\"><a href=\"/menu.es?mid=a10522010000\">개인정보처리방침</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10522010000\">알기 쉬운 개인정보처리방침</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10522020000\">개인정보처리방침</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10522030000\">정보주체 권리행사</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub23\"><a href=\"/menu.es?mid=a10523000000\">이메일 무단수집거부</a></li>\n\t\t\t\t<li class=\"sub24\"><a href=\"https://visit.kpx.or.kr\">방문신청</a></li>\n\t\t\t\t<li class=\"sub26 sublast\"><a href=\"/menu.es?mid=a10526010000\">전력계통 온라인 토론회</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10526010000\">공지사항 및 설명자료 안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10526020000\">토론방</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t</ul>\n\t\t\t\n\n\t\t</div>\n\t</li>\n</ul>\n\n\n\t\t</nav>\n\t\t<nav id=\"gnb2\">\n\t\t\t<a href=\"\" class=\"control open\"><span class=\"bar\"></span>메뉴열기</a>\n\t\t\t<div class=\"gnb_wrap\">\n\t\t\t\t\t\t\n\t\t\t\t<div class=\"gnb_top\">\n\t\t\t\t\t<div class=\"gnb_search\">\n\t\t\t\t\t\t\t<form id=\"searchForm2\" name=\"searchForm\" action=\"/findeepSearch.es?mid=a10700000000\" method=\"post\">\n\t\t\t\t\t\t\t\t<label for=\"search\" class=\"IR\">검색</label>\n\t\t\t\t\t\t\t\t<input type=\"text\" placeholder=\"검색어를 입력해 주세요\" class=\"search_keyword\" id=\"search2\" name=\"allKeyWord\" value=\"\" title=\"검색\">\n\t\t\t\t\t\t\t\t<button type=\"submit\" name=\"button\" onclick=\"document.searchForm.submit(); return false;\">검색</button>\n\t\t\t\t\t\t\t<div>\n<input type=\"hidden\" name=\"_csrf\" value=\"cc29bc11-037e-4e72-95ee-c4295424f505\" />\n</div></form>\n\t\t\t\t\t</div>\t\t\t\t\n\t\t\t\t</div>\n\t\t\t\t\t\t\n\t\t\t\t<div class=\"topmenu_wrap\">\n\t\t\t\t\t\n\n<ul id=\"head_menu_all\" class=\"topmenu_all\">\n\t<li class=\"lnb1 mnfirst\">\n\t\t<a href=\"/menu.es?mid=a10301010000\">KPX소개</a>\n\t\t<div class=\"submenu\">\n\t\t\t<ul class=\"sub03\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a10301010000\">전력거래소는?</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301010000\">회사개요</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301020000\">주요역할</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301030000\">비전 및 경영전략</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301060000\">CI소개</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10301070100\">찾아오시는 길</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a10303010000\">CEO 소개</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10303010000\">인사말</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10303020000\">약력</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a10302010000\">조직구성</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10302010200\">조직소개</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10302020100\">임원구성 및 선임절차</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a10304000000\">회원사 현황</a></li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"https://kpx.saramin.co.kr/\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"새창으로 이동\" class=\"linkWindow\">채용안내</a></li>\n\t\t\t</ul>\n\t\t</div>\n\t</li>\n\t<li class=\"lnb2\">\n\t\t<a href=\"/menu.es?mid=a10201000000\">열린경영</a>\n\t\t<div class=\"submenu\">\n\t\t\t<ul class=\"sub02\">\n\t\t\t\t<li class=\"sub11 subfirst\"><a href=\"/menu.es?mid=a10211010000\">국민의 의견을 듣습니다</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10211010000\">국민제안 이용안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10211020000\">국민제안 접수 및 조회</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub12\"><a href=\"/menu.es?mid=a10212010000\">적극행정</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212010000\">적극행정이란</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212020000\">전력거래소 적극행정 추진방안</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212030000\">적극행정 우수사례</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212040000\">적극행정 우수직원 추천</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212050000\">소극행정 신고센터</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212060000\">적극행정 소통 게시판</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10212070000\">소극행정 혁파 소통 게시판</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub13\"><a href=\"/menu.es?mid=a10213010000\">기업성장응답센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10213010000\">기업성장응답센터는?</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10213020000\">규제애로 접수</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub14\"><a href=\"/menu.es?mid=a10214010000\">행동강령.부패신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10214010000\">신문고이용안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10214020000\">행동강령.부패신고/상담</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub15\"><a href=\"/menu.es?mid=a10215010000\">인권침해신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10215010000\">인권침해 신고접수 및 상담</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10215020000\">인권침해 사건처리 절차</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10215030000\">사건처리 원칙</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub16\"><a href=\"/menu.es?mid=a10216010000\">공익신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10216010000\">공익신고안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10216020000\">공익신고자보호안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10216030000\">구조금.보상금지급안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10216040000\">공익신고/상담</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub17\"><a href=\"/menu.es?mid=a10217010000\">예산낭비신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10217010000\">예산낭비 신고안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10217020000\">예산낭비 신고/상담</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub18\"><a href=\"/menu.es?mid=a10218010000\">안전제안(신고)센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10218010000\">안전제안/신고센터는?</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10218020000\">안전제안/신고접수</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub21\"><a href=\"/menu.es?mid=a10221010000\">인사위반 신고센터</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10221010000\">인사위반 신고센터?</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10221020000\">인사위반 신고접수</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub19 sublast\"><a href=\"/menu.es?mid=a10219000000\">신고센터 바로가기</a></li>\n\t\t\t</ul>\n\t\t</div>\n\t</li>\n\t<li class=\"lnb3\">\n\t\t<a href=\"/menu.es?mid=a10901050000\">ESG경영</a>\n\t\t<div class=\"submenu\">\n\t\t\t<ul class=\"sub09\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a10901050000\">ESG경영</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901050000\">CEO 인사말</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901040000\">ESG 추진전략</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901110000\">ESG 추진조직</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901130000\">ESG 성과지표</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10901120100\">ESG 수상 및 인증내역</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a10902010000\">E(환경)</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10902010000\">환경경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10902070100\">친환경정책지원</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10902080100\">신재생 및 태양광 지표</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10902090000\">녹색제품 구매</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a10903020000\">S(사회)</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10903020100\">동반성장</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10903030300\">안전경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10903040100\">인권경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10903050000\">다양성 존중</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a10904010000\">G(지배구조)</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904010200\">이사회</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904040100\">ESG전략위원회</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904050100\">윤리경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904070100\">청렴경영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10904030000\">비상임이사 경영활동</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"/menu.es?mid=a10905000000\">지속가능경영보고서</a></li>\n\t\t\t</ul>\n\t\t</div>\n\t</li>\n\t<li class=\"lnb4\">\n\t\t<a href=\"/menu.es?mid=a11001010000\">법령·규칙</a>\n\t\t<div class=\"submenu\">\n\t\t\t<ul class=\"sub10\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a11001010000\">법령 및 고시</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11001010000\">법령</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11001020000\">고시</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a11002010000\">전력시장운영규칙 및 세부규정</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11002010000\">전력시장운영규칙 아카이브</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11002020000\">세부운영규정</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11002030000\">규칙개정 제안 및 자문</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11002040000\">기타</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"https://marketrule.kpx.or.kr\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"새창으로 이동\" class=\"linkWindow\">전력시장운영규칙 웹서비스</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03 sublast\"><a href=\"/menu.es?mid=a11003010000\">내규</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11003010000\">내규 공개</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11003020000\">내규·제·개정 예고</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t</ul>\n\t\t</div>\n\t</li>\n\t<li class=\"lnb5\">\n\t\t<a href=\"/menu.es?mid=a10101010000\">정보공개</a>\n\t\t<div class=\"submenu\">\n\t\t\t<ul class=\"sub01\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a10101010000\">정보공개제도</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101010000\">정보공개제도란?</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101020000\">정보처리절차흐름도</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101030000\">정보공개 방법</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101040000\">비공개정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101050000\">불복구제절차</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10101060000\">정보공개수수료</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub06\"><a href=\"/menu.es?mid=a10106000000\">공공기관정보공개청구</a></li>\n\t\t\t\t<li class=\"sub07\"><a href=\"/menu.es?mid=a10107010000\">공공데이터 제공</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10107010000\">공공데이터 신청 및 안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10107020000\">공공데이터 목록</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10107030000\">전력데이터 큐레이션 서비스</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10107040000\">공공데이터 사업화 상담코너</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub11\"><a href=\"/menu.es?mid=a10111010000\">경영공시</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10111010000\">경영공시 안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10111020000\">ALIO 통합공시</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10111030000\">자율공시</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10111040000\">담당자 현황</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a10102090000\">사전정보공표</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10102090000\">사전정보공표 목록</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10102100000\">즐겨찾기 정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10102110000\">사전정보 모니터링</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub09\"><a href=\"/menu.es?mid=a10109010000\">전력시장·전력계통 운영정보</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109010000\">전력시장 정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109020000\">전력계통 운영정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109040000\">IT시스템 운영정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109050000\">비중앙 출력제어 정보</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10109030000\">기타정보</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub10\"><a href=\"/menu.es?mid=a10110010000\">사업실명제</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10110010000\">사업실명제 개요</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10110020000\">대상사업 리스트</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"/menu.es?mid=a10105000000\">정보목록</a></li>\n\t\t\t</ul>\n\t\t</div>\n\t</li>\n\t<li class=\"lnb6\">\n\t\t<a href=\"/menu.es?mid=a10401010000\">주요사업</a>\n\t\t<div class=\"submenu\">\n\t\t\t<ul class=\"sub04\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a10401010000\">시장운영</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401010000\">전력거래절차</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401040000\">시장가격결정</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401050000\">정산처리일정</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401080000\">정산스마트 매뉴얼</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401060000\">전력시장운영협의체</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401020000\">REC거래</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10401030000\">전력거래시스템</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10801000000\">전력거래 준비 안내</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a10402010000\">계통운영</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10402010000\">전력계통운영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10402030000\">단기전력수급운영</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10402040000\">급전운영</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a10403010000\">전력수급</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403010000\">전력수급개요</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403020000\">전력수급계획수립절차</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403030100\">전력수요전망</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403040000\">발전소건설현황</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403050100\">계통계획</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403060100\">발전사업허가업무</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403070000\">전력수급기본계획</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10403090000\">계통 수용여유량 전망</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a10404010000\">전력관련정보</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404010000\">최대부하전망</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404020000\">최대부하전망(제주)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404030000\">실시간 전력수급현황</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404040000\">실시간 전력수급현황 (제주)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404050000\">비상시 절전참여요령</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404060000\">전일 전력수급실적</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404070000\">전일 전력수급실적(제주)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404080100\">SMP(계통한계가격)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10404090100\">하루전 발전계획용 수요예측</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub06\"><a href=\"/menu.es?mid=a10406010000\">제주시범사업 정보</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10406010100\">발전계획용 수요예측</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10406020100\">SMP(계통한계가격)</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"/menu.es?mid=a10405010000\">해외동향</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10405010000\">전력산업동향</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10405020000\">스마트그리드동향</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t</ul>\n\t\t</div>\n\t</li>\n\t<li class=\"lnb7\">\n\t\t<a href=\"/menu.es?mid=a11101000000\">통합계약정보</a>\n\t\t<div class=\"submenu\">\n\t\t\t<ul class=\"sub11\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a11101010000\">입찰공고</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11101010000\">구매.용역.공사</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a11103010000\">계약절차안내</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11103010000\">계약종류및방법</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11103020000\">업무절차도</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11103030000\">계약준비서류</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11103040000\">예상소요일수</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a11104000000\">통합자료실</a></li>\n\t\t\t\t<li class=\"sub05 sublast\"><a href=\"/menu.es?mid=a11105010000\">청렴계약안내</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a11105010000\">청렵계약이란</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t</ul>\n\t\t</div>\n\t</li>\n\t<li class=\"lnb8\">\n\t\t<a href=\"/menu.es?mid=a11201000000\">소식알림</a>\n\t\t<div class=\"submenu\">\n\t\t\t<ul class=\"sub12\">\n\t\t\t\t<li class=\"sub01 subfirst\"><a href=\"/menu.es?mid=a11201000000\">공지사항</a></li>\n\t\t\t\t<li class=\"sub02\"><a href=\"/menu.es?mid=a11202000000\">보도자료</a></li>\n\t\t\t\t<li class=\"sub03\"><a href=\"/menu.es?mid=a11203000000\">시장개선</a></li>\n\t\t\t\t<li class=\"sub04 sublast\"><a href=\"/menu.es?mid=a11204000000\">KPX 종합자료실</a></li>\n\t\t\t</ul>\n\t\t</div>\n\t</li>\n\t<li class=\"lnb9 mnlast\">\n\t\t<a href=\"/menu.es?mid=a10501010000\">고객지원</a>\n\t\t<div class=\"submenu\">\n\t\t\t<ul class=\"sub05\">\n\t\t\t\t<li class=\"sub03 subfirst\"><a href=\"/menu.es?mid=a10503010100\">고객만족</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10503010100\">고객서비스 헌장 및 이행표준</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10503020000\">친절사원을 추천하세요</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub04\"><a href=\"/menu.es?mid=a10504010000\">KPX에 물어보세요</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10504010000\">고객질의 이용안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10504020000\">자주 받는 질문(FAQ)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10504030000\">묻고 답하기(Q&A)</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10504040000\">분야별 업무담당자</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub21\"><a href=\"/menu.es?mid=a10521000000\">프로그램다운로드</a></li>\n\t\t\t\t<li class=\"sub22\"><a href=\"/menu.es?mid=a10522010000\">개인정보처리방침</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10522010000\">알기 쉬운 개인정보처리방침</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10522020000\">개인정보처리방침</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10522030000\">정보주체 권리행사</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t\t<li class=\"sub23\"><a href=\"/menu.es?mid=a10523000000\">이메일 무단수집거부</a></li>\n\t\t\t\t<li class=\"sub24\"><a href=\"https://visit.kpx.or.kr\">방문신청</a></li>\n\t\t\t\t<li class=\"sub26 sublast\"><a href=\"/menu.es?mid=a10526010000\">전력계통 온라인 토론회</a>\n\t\t\t\t\t<div>\n\t\t\t\t\t\t<ul class=\"lnb-detail\">\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10526010000\">공지사항 및 설명자료 안내</a></li>\n\t\t\t\t\t\t\t<li class=\"lnb-detail-item\"><a href=\"/menu.es?mid=a10526020000\">토론방</a></li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</li>\n\t\t\t</ul>\n\t\t</div>\n\t</li>\n</ul>\n\n\n\t\t\t\t</div>\n\t\t\t</div>\n\t\t\t<a href=\"\" class=\"control close\">메뉴닫기</a>\n\t\t</nav>\n\t</header>\n\t<main id=\"main\">\n\t\t<div class=\"main_wrap\">\n\n\n\n\n\n\n\n\n\n\n\n\n\t\t\n\n\n\n\n\n<div id=\"visual\" class=\"visual6\">\n<strong class=\"title\">부가메뉴</strong>\n\n</div>\n\t\t\n\t\t<section id=\"snb\" class=\"sub06\">\n\t\t\t\n\t\t\t\t\n\t\t\t\t\n   \t\t\t<h2 class=\"title\"><span>부가메뉴</span></h2>\n\t\t\t\t\n\t\t\t\n\t\t\t<nav class=\"list\">\n\t\t\n\t\t\t\n\n<ul id=\"left_menu_top\" class=\"head_menu_depth\">\n\t<li id=\"li0601000000\" class=\"first\"><a href=\"/menu.es?mid=a10601000000\">로그인</a>\n\t</li>\n\t<li id=\"li0609000000\"><a href=\"/menu.es?mid=a10609000000\">본인인증 로그인</a>\n\t</li>\n\t<li id=\"li0608000000\" class=\"last\"><a href=\"/menu.es?mid=a10608000000\">사이트맵</a>\n\t</li>\n</ul>\n\n\n\t\t\n\t\t\t</nav>\n\t\t\t\n\t\t</section>\n\t\t<section id=\"contents\">\n\t\t\t<div class=\"contents_util\">\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t<h2 id=\"contents_title\"><span>실시간 전력수급현황</span></h2>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t<nav class=\"location\">\n\t\t\t\t\t<ul class=\"path\">\n\t\t\t\t\t\t<li class=\"icon\"><a href=\"/main\"><span class=\"IR\">홈</span></a></li>\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t<li><a href=\"/menu.es?mid=a10600000000\">부가메뉴</a></li>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t<li><a href=\"/menu.es?mid=a10606000000\">전력관련정보</a></li>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t<li><a href=\"/menu.es?mid=a10606030000\" class=\"active\">실시간 전력수급현황</a></li>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t</ul>\n\t\t\t\t\t<div class=\"nav-depth\">\n\t\t\t\t\t\t<ul>\n\t\t\t\t\t\t\t<li class=\"home\"><a href=\"/main\">HOME</a></li>\n\t\t\t\t\t\t\n\n<li id=\"head_menu_depth1\" class=\"list depth1\">\n<button title=\"클릭시 탭메뉴 목록을 볼 수 있습니다.\" type=\"button\">메뉴</button>\n<ul class=\"sub\">\n\t<li id=\"depth1_li0300000000\"><a href=\"/menu.es?mid=a10301010000\">KPX소개</a></li>\n\t<li id=\"depth1_li0200000000\"><a href=\"/menu.es?mid=a10201000000\">열린경영</a></li>\n\t<li id=\"depth1_li0900000000\"><a href=\"/menu.es?mid=a10901050000\">ESG경영</a></li>\n\t<li id=\"depth1_li1000000000\"><a href=\"/menu.es?mid=a11001010000\">법령·규칙</a></li>\n\t<li id=\"depth1_li0100000000\"><a href=\"/menu.es?mid=a10101010000\">정보공개</a></li>\n\t<li id=\"depth1_li0400000000\"><a href=\"/menu.es?mid=a10401010000\">주요사업</a></li>\n\t<li id=\"depth1_li1100000000\"><a href=\"/menu.es?mid=a11101000000\">통합계약정보</a></li>\n\t<li id=\"depth1_li1200000000\"><a href=\"/menu.es?mid=a11201000000\">소식알림</a></li>\n\t<li id=\"depth1_li0500000000\"><a href=\"/menu.es?mid=a10501010000\">고객지원</a></li>\n\t<li id=\"depth1_li0600000000\"><a href=\"/menu.es?mid=a10608000000\">부가메뉴</a></li>\n\t<li id=\"depth1_li0800000000\"><a href=\"/menu.es?mid=a10801000000\">전력거래 시작하기</a></li>\n\t<li id=\"depth1_li0700000000\"><a href=\"/menu.es?mid=a10700000000\">통합검색</a></li>\n</ul>\n</li>\n\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n<li id=\"head_menu_depth2\" class=\"list depth2\">\n<button title=\"클릭시 탭메뉴 목록을 볼 수 있습니다.\" type=\"button\">메뉴</button>\n<ul class=\"sub\">\n\t<li id=\"depth2_li0601000000\"><a href=\"/menu.es?mid=a10601000000\">로그인</a></li>\n\t<li id=\"depth2_li0609000000\"><a href=\"/menu.es?mid=a10609000000\">본인인증 로그인</a></li>\n\t<li id=\"depth2_li0608000000\" class=\"last\"><a href=\"/menu.es?mid=a10608000000\">사이트맵</a></li>\n</ul>\n</li>\n\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n<li id=\"head_menu_depth3\" class=\"list depth3\">\n<button title=\"클릭시 탭메뉴 목록을 볼 수 있습니다.\" type=\"button\">메뉴</button>\n<ul class=\"sub\">\n\t<li id=\"depth3_li0606010000\"><a href=\"/menu.es?mid=a10606010000\">최대부하전망</a></li>\n\t<li id=\"depth3_li0606020000\"><a href=\"/menu.es?mid=a10606020000\">최대부하전망(제주)</a></li>\n\t<li id=\"depth3_li0606030000\"><a href=\"/menu.es?mid=a10606030000\">실시간 전력수급현황</a></li>\n\t<li id=\"depth3_li0606040000\"><a href=\"/menu.es?mid=a10606040000\">실시간 전력수급현황 (제주)</a></li>\n\t<li id=\"depth3_li0606050000\"><a href=\"/menu.es?mid=a10606050000\">비상시 절전참여요령</a></li>\n\t<li id=\"depth3_li0606060000\"><a href=\"/menu.es?mid=a10606060000\">전일 전력수급실적</a></li>\n\t<li id=\"depth3_li0606070000\"><a href=\"/menu.es?mid=a10606070000\">전일 전력수급실적(제주)</a></li>\n\t<li id=\"depth3_li0606080000\"><a href=\"/menu.es?mid=a10606080100\">SMP(계통한계가격)</a></li>\n\t<li id=\"depth3_li0606090000\" class=\"last\"><a href=\"/menu.es?mid=a10606090100\">하루전 발전계획용 수요예측</a></li>\n</ul>\n</li>\n\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t</nav>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t<div class=\"util\">\n\t\t\t\t\t<span class=\"zoom\">\n\t\t\t\t\t\t<a href=\"#contents_body\" onclick=\"zoomInOut('plus'); return false;\" class=\"btn up\">글자 크게</a>\n\t\t\t\t\t\t<a href=\"#contents_body\" onclick=\"zoomInOut('minus'); return false;\" class=\"btn down\">글자 작게</a>\n\t\t\t\t\t</span>\n\t\t\t\t\t\n\t\t\t\t\t<article class=\"share\" id=\"shareWrap\" title=\"닫힘\">\n\t\t\t\t\t\t<h2 class=\"title\"><a href=\"\" class=\"btn open\" onclick=\"toggleTitle('#shareWrap');\">공유하기</a></h2>\n\t\t\t\t\t\t\n\t\t\t\t\t\t<form id=\"snsForm\" name=\"snsForm\" action=\"/api/sns.es\" method=\"post\">\n\t\t\t\t\t\t<input type=\"hidden\" name=\"title\" value=\"\" />\n\t\t\t\t\t\t<input type=\"hidden\" name=\"mid\" value=\"a10606030000\" />\n\t\t\t\t\t\t<input type=\"hidden\" name=\"url\" value=\"\" />\n\t\t\t\t\t\t<input type=\"submit\" value=\"전송\" style=\"display:none;height:0;width:0;\" />\n\t\t\t\t\t\t<div>\n<input type=\"hidden\" name=\"_csrf\" value=\"cc29bc11-037e-4e72-95ee-c4295424f505\" />\n</div></form>\n\t\t\t\t\t\t<div class=\"item\">\n\t\t\t\t\t\t\t<ul id=\"share\" class=\"list\">\n\t\t\t\t\t\t\t\t<li class=\"facebook\"><a title=\"새 창 열림\" href=\"#share\" onclick=\"snsApi('facebook'); return false;\">페이스북</a></li>\n\t\t\t\t\t\t\t\t<li class=\"twitter\"><a title=\"새 창 열림\" href=\"#share\" onclick=\"snsApi('twitter'); return false;\">트위터</a></li>\n\t\t\t\t\t\t\t\t<li class=\"band\"><a title=\"새 창 열림\" href=\"#share\" onclick=\"snsApi('band'); return false;\">밴드</a></li>\n\t\t\t\t\t\t\t\t<li class=\"kakaostory\"><a title=\"새 창 열림\" href=\"#share\" onclick=\"snsApi('kakao'); return false;\">카카오스토리</a></li>\n                                                                                                                 \n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t<li class=\"urlShare\"><a href=\"#share\" onclick=\"copyURI(document.location.href); return false;\" class=\"url\">URL 복사</a></li>\n\t\t\t\t\t\t\t</ul>\n\t\t\t\t\t\t\t<script type=\"text/javascript\">\n\t\t\t\t\t\t\t//<![CDATA[\n\t\t\t\t\t\t\t\tvar now = escape(document.location.href);\n\t\t\t\t\t\t\t\tvar url = \"/ease_src/kakao.jsp?title=전력거래소&url=\"+now;\n\t\t\t\t\t\t\t\t$(\"#kakao-link-btn\").attr(\"href\",url);\n\t\t\t\t\t\t\t//]]>\n\t\t\t\t\t\t\t</script>\n\t\t\t\t\t\t</div>\n\t\t\t\t\t</article>\n\t\t\t\t\t<a class=\"btn print\" href=\"#contents_detail\" onclick=\"printAreaAction(); return false;\">인쇄</a>\n\t\t\t\t</div>\n\t\t\t\t\n\t\t\t</div>\n\t\t\t\n\t\t\t<div id=\"contents_body\">\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t<div class=\"content_style\">\n\n\n<h3>실시간 전력수급현황</h3>\n\t\n\n\n\n\n\n\n<script>\nsetInterval(function(){document.location.reload(); return false;}, 1000*60*5);\n</script>\n\n<p class=\"info_top\">2025.01.05(일) 23:10 <a href=\"\" onclick=\"document.location.reload(); return false;\"><i class=\"xi-refresh\">새로고침</i></a></p>\n<div class=\"conTableGroup\">\n\t<table class=\"conTable tdCenter\">\n\t\t<caption>실시간 전력수급현황에 대한 공급능력, 현재부하, 공급예비력, 운영예비력 정보를 제공합니다</caption>\n\t\t<colgroup>\n\t\t\t<col style=\"width:40%\"><col>\n\t\t</colgroup>\n\t\t<tbody>\n\t\t\t<tr>\n\t\t\t\t<th scope=\"row\">공급능력</th>\n\t\t\t\t<td id=\"avil\">102,553 MW</td>\n\t\t\t</tr>\n\t\t\t<tr>\n\t\t\t\t<th scope=\"row\">현재수요(전력시장)</th>\n\t\t\t\t<td id=\"load\">64,918 MW</td>\n\t\t\t</tr>\n\t\t\t<tr>\n\t\t\t\t<th scope=\"row\">공급예비력</th>\n\t\t\t\t<td id=\"supPow\">37,635 MW</td>\n\t\t\t</tr>\n\t\t\t<tr>\n\t\t\t\t<th scope=\"row\">공급예비율</th>\n\t\t\t\t<td id=\"supPer\">57.97 %</td>\n\t\t\t</tr>\n\t\t</tbody>\n\t</table>\n</div>\n\n<h4>실시간 전력수급 그래프</h4>\n\t\n\n\n\n\n\n<script type=\"text/javascript\" src=\"/kpx_src/js/highcharts.js\"></script>\n<script type=\"text/javascript\" src=\"/kpx_src/js/exporting.js\"></script>\n\n<script type=\"text/javascript\">\n\t$(document).ready(function(){\n\t\tdrawChart(null, null, null);\n\t});\n\t\n\tfunction lPad(str, num, chr) {  \n\t\tstr = str+\"\";\n\t\tif ( !str || !chr || str.length >= num )\n\t\t\treturn str;\n\t\tvar max = num - str.length;\n\t\tfor ( var i = 0; i < 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                                                                 \n\t\t\t\t\t\t},\n\t\t\t\t\t\tpointInterval: 300000\n\t\t\t\t\t},\n\t\t\t\t\tseries:{\n\t\t\t\t\t\t\n\t\t\t\t\t}\n\t\t\t\t},\n\t\t\t\tlegend: {\n\t\t\t\t\t                                                                                                                                                                                               \t\n\t\t\t\t\titemStyle:{\n\t\t\t\t\t\tfontSize : '13px'\n\t\t\t\t\t}\n\t\t\t\t},\n\t\t\t\tseries : null\n\t\t}\n\t\t$('#chart').highcharts($.extend(true, option,{\n\t\t\tseries: [{\n\t\t\t\t\"name\": '현재수요(총수요)',\n\t\t\t\t\"data\": v,\n\t\t\t\t\"color\" : 'rgb(0,0,255)'\n\t\t\t},{\n\t\t\t\t\"name\": \"현재수요(전력시장)\",\n\t\t\t\t\"data\": x, \n\t\t\t\t\"color\" : 'rgb(223,70,74)',\n\t\t\t\t\"zIndex\" : 1\n\t\t\t},{\n\t\t\t\t\"name\": '과거수요(총수요)',\n\t\t\t\t\"data\": w,\n\t\t\t\t\"color\" : 'rgb(0,0,255,0.7)',\n\t\t\t\t\"dashStyle\" : 'ShortDot',\n\t\t\t\t\"lineWidth\" : 0.7\n\t\t\t\t\t\n\t\t\t},{\n\t\t\t\t\"name\": '과거수요(전력시장)',\n\t\t\t\t\"data\": y,\n\t\t\t\t\"color\" : 'rgb(223,70,74,0.7)',\n\t\t\t\t\"dashStyle\" : 'ShortDot',\n\t\t\t\t\"lineWidth\" : 0.7\n\t\t\t}]\n\t\t}));\n\t\t\n\t\t$($('.highcharts-legend-item')[2]).click();\n\t\t$($('.highcharts-legend-item')[3]).click();\n\t}\n\t\n</script>\n<div class=\"conTableGroup\">\n\t<table class=\"conTable tdCenter\">\n\t\t<caption>실시간 전력수급 그래프</caption>\n\t\t<colgroup>\n\t\t\t<col style=\"width:40%\"></col>\n\t\t\t<col style=\"width:30%\"></col>\n\t\t\t<col style=\"width:30%\"></col>\n\t\t</colgroup>\n\t\t<thead>\n\t\t\t<tr>\n\t\t\t\t<th>구분</th>\n\t\t\t\t<th>현재</th>\n\t\t\t\t<th>과거<br> <span id=\"nearByTime\">('24.12.29. 일)</span></th>\n\t\t\t</tr>\n\t\t</thead>\n\t\t<tbody>\n\t\t\t<tr>\n\t\t\t\t<td>총 수요</td>\n\t\t\t\t<td><span class=\"graph_bar02\"></span></td>\n\t\t\t\t<td><span class=\"graph_bar02d\"></span></td>\n\t\t\t</tr>\n\t\t\t<tr>\n\t\t\t\t<td>시장 수요</td>\n\t\t\t\t<td><span class=\"graph_bar01\"></span></td>\n\t\t\t\t<td><span class=\"graph_bar01d\"></span></td>\n\t\t\t</tr>\t\t\n\t\t\t<tr>\n\t\t\t\t<td>기온(서울)<br>(최고/최저)</td>\n\t\t\t\t<td><span id=\"todayMaxTemp\"> 4 </span>℃ / <span id=\"todayMinTemp\"> 0 </span>℃</td>\n\t\t\t\t<td><span id=\"maxTemp\"> 5.3 </span>℃ / <span id=\"minTemp\"> -4.1 </span>℃</td>\n\t\t\t</tr>\n\t\t</tbody>\t\n\t</table>\n</div>\n<div class=\"MAT10 MAB10\">*실시간 전력수급현황은 5분주기 순시자료 입니다.<br><br>\n\t<span class=\"grape_top\">MW</span>\n\t<div id=\"chart\" class=\"grape2\" style=\"height:520px;\"> \n\t\t그래프 영역 <br />640 이상사이즈 100%*306 <br />640 이하사이즈 100%*153\n\t</div>\n</div>\n<div class=\"FloatLeft MAT10 MAB10\">*과거수요 그래프는 범례에서 선택시 표출됩니다.<br>\n*총수요는 실시간 추정값임을 참고하시기 바라며, 실시간 취득 데이터 누락 또는 지연 등으로 인한 오차가 포함될 수 있습니다.\n</div><br><br><br>\n<div class=\"btn_area graph_btn01_open\" >\n\t<a href=\"javascript:void(0);\" class=\"btn_basic\">표로 보기</a>\n</div>\n<div class=\"conTableGroup graph_table01 IR\">\n\t<div class=\"btn_area graph_btn01_close DisplayNone\">\n\t\t<a href=\"javascript:void(0);\" class=\"btn_basic\">표로보기 닫기</a>\n\t</div>\n\t<div>\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t<div style=\"text-align: right\">단위:MW</div>\n\t\t<table class=\"conTable tdCenter\">\n\t\t\t<caption>실시간 전력수급 그래프 차트 정보를 제공합니다.</caption>\n\t\t\t<thead>\n\t\t\t\t<tr>\n\t\t\t\t\t<th rowspan=\"2\">시간</th>\n\t\t\t\t\t<th colspan=\"2\">2024.12.29(일)</th>\n\t\t\t\t\t<th colspan=\"2\">2025.01.05(일)</th>\n\t\t\t\t</tr>\n\t\t\t\t<tr>\n\t\t\t\t\t<th style=\"border-left: 1px solid #d8dee5;\">총수요</th>\n\t\t\t\t\t<th>시장수요</th>\n\t\t\t\t\t<th>총수요</th>\n\t\t\t\t\t<th>시장수요</th>\n\t\t\t\t</tr>\n\t\t\t</thead>\n\t\t\t<tbody>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 00분 </td>\n\t\t\t\t\t<td>63,807</td>\n\t\t\t\t\t<td>63,807</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,798\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,798\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 05분 </td>\n\t\t\t\t\t<td>63,449</td>\n\t\t\t\t\t<td>63,449</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,505\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,505\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 10분 </td>\n\t\t\t\t\t<td>63,352</td>\n\t\t\t\t\t<td>63,352</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,236\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,236\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 15분 </td>\n\t\t\t\t\t<td>62,890</td>\n\t\t\t\t\t<td>62,890</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,929\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,929\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 20분 </td>\n\t\t\t\t\t<td>62,554</td>\n\t\t\t\t\t<td>62,553</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,680\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,680\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 25분 </td>\n\t\t\t\t\t<td>62,393</td>\n\t\t\t\t\t<td>62,393</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,304\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,305\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 30분 </td>\n\t\t\t\t\t<td>62,338</td>\n\t\t\t\t\t<td>62,338</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,120\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,120\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 35분 </td>\n\t\t\t\t\t<td>62,020</td>\n\t\t\t\t\t<td>62,020</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,837\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,837\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 40분 </td>\n\t\t\t\t\t<td>61,946</td>\n\t\t\t\t\t<td>61,946</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,785\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,785\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 45분 </td>\n\t\t\t\t\t<td>61,850</td>\n\t\t\t\t\t<td>61,850</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,386\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,386\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 50분 </td>\n\t\t\t\t\t<td>61,474</td>\n\t\t\t\t\t<td>61,473</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,165\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,165\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>00시 55분 </td>\n\t\t\t\t\t<td>61,250</td>\n\t\t\t\t\t<td>61,250</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,709\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,709\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 00분 </td>\n\t\t\t\t\t<td>60,760</td>\n\t\t\t\t\t<td>60,760</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,522\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,522\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 05분 </td>\n\t\t\t\t\t<td>60,594</td>\n\t\t\t\t\t<td>60,594</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,325\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,325\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 10분 </td>\n\t\t\t\t\t<td>60,429</td>\n\t\t\t\t\t<td>60,429</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,159\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,159\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 15분 </td>\n\t\t\t\t\t<td>60,186</td>\n\t\t\t\t\t<td>60,186</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,742\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,742\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 20분 </td>\n\t\t\t\t\t<td>60,106</td>\n\t\t\t\t\t<td>60,106</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,441\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,441\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 25분 </td>\n\t\t\t\t\t<td>59,804</td>\n\t\t\t\t\t<td>59,804</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,361\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,361\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 30분 </td>\n\t\t\t\t\t<td>59,860</td>\n\t\t\t\t\t<td>59,860</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,327\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,327\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 35분 </td>\n\t\t\t\t\t<td>59,516</td>\n\t\t\t\t\t<td>59,516</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,246\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,246\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 40분 </td>\n\t\t\t\t\t<td>59,602</td>\n\t\t\t\t\t<td>59,602</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,372\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,372\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 45분 </td>\n\t\t\t\t\t<td>59,411</td>\n\t\t\t\t\t<td>59,411</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,168\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,168\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 50분 </td>\n\t\t\t\t\t<td>59,001</td>\n\t\t\t\t\t<td>59,001</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,833\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,833\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>01시 55분 </td>\n\t\t\t\t\t<td>58,776</td>\n\t\t\t\t\t<td>58,776</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,714\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,714\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 00분 </td>\n\t\t\t\t\t<td>58,828</td>\n\t\t\t\t\t<td>58,828</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,653\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,653\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 05분 </td>\n\t\t\t\t\t<td>58,807</td>\n\t\t\t\t\t<td>58,807</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,393\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,393\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 10분 </td>\n\t\t\t\t\t<td>58,611</td>\n\t\t\t\t\t<td>58,611</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,335\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,335\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 15분 </td>\n\t\t\t\t\t<td>58,264</td>\n\t\t\t\t\t<td>58,264</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,290\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,290\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 20분 </td>\n\t\t\t\t\t<td>58,207</td>\n\t\t\t\t\t<td>58,207</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,828\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,828\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 25분 </td>\n\t\t\t\t\t<td>58,224</td>\n\t\t\t\t\t<td>58,224</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,905\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,905\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 30분 </td>\n\t\t\t\t\t<td>58,216</td>\n\t\t\t\t\t<td>58,216</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,767\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,767\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 35분 </td>\n\t\t\t\t\t<td>57,949</td>\n\t\t\t\t\t<td>57,949</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,524\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,524\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 40분 </td>\n\t\t\t\t\t<td>57,708</td>\n\t\t\t\t\t<td>57,708</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,508\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,508\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 45분 </td>\n\t\t\t\t\t<td>57,605</td>\n\t\t\t\t\t<td>57,605</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,249\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,249\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 50분 </td>\n\t\t\t\t\t<td>57,715</td>\n\t\t\t\t\t<td>57,715</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,001\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,001\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>02시 55분 </td>\n\t\t\t\t\t<td>57,377</td>\n\t\t\t\t\t<td>57,377</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,077\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,077\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 00분 </td>\n\t\t\t\t\t<td>57,222</td>\n\t\t\t\t\t<td>57,222</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,102\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,102\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 05분 </td>\n\t\t\t\t\t<td>57,106</td>\n\t\t\t\t\t<td>57,106</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,072\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,072\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 10분 </td>\n\t\t\t\t\t<td>57,212</td>\n\t\t\t\t\t<td>57,212</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,938\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,938\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 15분 </td>\n\t\t\t\t\t<td>57,128</td>\n\t\t\t\t\t<td>57,128</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,876\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,876\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 20분 </td>\n\t\t\t\t\t<td>57,268</td>\n\t\t\t\t\t<td>57,268</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,982\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,982\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 25분 </td>\n\t\t\t\t\t<td>56,992</td>\n\t\t\t\t\t<td>56,992</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,002\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,001\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 30분 </td>\n\t\t\t\t\t<td>56,977</td>\n\t\t\t\t\t<td>56,977</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,719\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,719\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 35분 </td>\n\t\t\t\t\t<td>57,253</td>\n\t\t\t\t\t<td>57,253</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,569\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,569\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 40분 </td>\n\t\t\t\t\t<td>57,088</td>\n\t\t\t\t\t<td>57,088</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,802\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,802\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 45분 </td>\n\t\t\t\t\t<td>57,115</td>\n\t\t\t\t\t<td>57,115</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,782\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,782\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 50분 </td>\n\t\t\t\t\t<td>57,034</td>\n\t\t\t\t\t<td>57,034</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,789\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,789\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>03시 55분 </td>\n\t\t\t\t\t<td>56,710</td>\n\t\t\t\t\t<td>56,710</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,740\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,740\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 00분 </td>\n\t\t\t\t\t<td>56,656</td>\n\t\t\t\t\t<td>56,656</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,776\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,775\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 05분 </td>\n\t\t\t\t\t<td>56,793</td>\n\t\t\t\t\t<td>56,793</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,780\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,780\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 10분 </td>\n\t\t\t\t\t<td>57,054</td>\n\t\t\t\t\t<td>57,054</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,906\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,906\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 15분 </td>\n\t\t\t\t\t<td>57,140</td>\n\t\t\t\t\t<td>57,140</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,664\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,664\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 20분 </td>\n\t\t\t\t\t<td>57,353</td>\n\t\t\t\t\t<td>57,353</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,698\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,698\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 25분 </td>\n\t\t\t\t\t<td>57,407</td>\n\t\t\t\t\t<td>57,407</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,542\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,542\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 30분 </td>\n\t\t\t\t\t<td>57,111</td>\n\t\t\t\t\t<td>57,111</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,837\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,837\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 35분 </td>\n\t\t\t\t\t<td>57,128</td>\n\t\t\t\t\t<td>57,127</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,748\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,748\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 40분 </td>\n\t\t\t\t\t<td>57,196</td>\n\t\t\t\t\t<td>57,196</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,890\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,890\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 45분 </td>\n\t\t\t\t\t<td>57,177</td>\n\t\t\t\t\t<td>57,177</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,702\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,702\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 50분 </td>\n\t\t\t\t\t<td>57,355</td>\n\t\t\t\t\t<td>57,355</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,882\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t57,882\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>04시 55분 </td>\n\t\t\t\t\t<td>57,204</td>\n\t\t\t\t\t<td>57,205</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,095\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,095\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 00분 </td>\n\t\t\t\t\t<td>57,358</td>\n\t\t\t\t\t<td>57,358</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,259\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,259\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 05분 </td>\n\t\t\t\t\t<td>57,442</td>\n\t\t\t\t\t<td>57,442</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,290\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,290\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 10분 </td>\n\t\t\t\t\t<td>57,668</td>\n\t\t\t\t\t<td>57,669</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,160\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,160\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 15분 </td>\n\t\t\t\t\t<td>57,543</td>\n\t\t\t\t\t<td>57,543</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,285\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,285\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 20분 </td>\n\t\t\t\t\t<td>57,503</td>\n\t\t\t\t\t<td>57,503</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,197\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,197\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 25분 </td>\n\t\t\t\t\t<td>57,640</td>\n\t\t\t\t\t<td>57,640</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,090\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,090\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 30분 </td>\n\t\t\t\t\t<td>57,946</td>\n\t\t\t\t\t<td>57,946</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,270\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,270\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 35분 </td>\n\t\t\t\t\t<td>58,013</td>\n\t\t\t\t\t<td>58,013</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,472\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,472\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 40분 </td>\n\t\t\t\t\t<td>57,972</td>\n\t\t\t\t\t<td>57,972</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,549\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,549\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 45분 </td>\n\t\t\t\t\t<td>57,945</td>\n\t\t\t\t\t<td>57,945</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,790\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,790\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 50분 </td>\n\t\t\t\t\t<td>57,790</td>\n\t\t\t\t\t<td>57,790</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,050\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,050\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>05시 55분 </td>\n\t\t\t\t\t<td>58,372</td>\n\t\t\t\t\t<td>58,372</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,964\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,964\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 00분 </td>\n\t\t\t\t\t<td>58,422</td>\n\t\t\t\t\t<td>58,408</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,882\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t58,867\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 05분 </td>\n\t\t\t\t\t<td>58,596</td>\n\t\t\t\t\t<td>58,582</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,210\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,194\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 10분 </td>\n\t\t\t\t\t<td>58,645</td>\n\t\t\t\t\t<td>58,631</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,172\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,157\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 15분 </td>\n\t\t\t\t\t<td>58,563</td>\n\t\t\t\t\t<td>58,549</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,357\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,342\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 20분 </td>\n\t\t\t\t\t<td>58,860</td>\n\t\t\t\t\t<td>58,842</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,311\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,295\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 25분 </td>\n\t\t\t\t\t<td>58,878</td>\n\t\t\t\t\t<td>58,861</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,520\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,505\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 30분 </td>\n\t\t\t\t\t<td>59,028</td>\n\t\t\t\t\t<td>59,013</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,461\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,446\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 35분 </td>\n\t\t\t\t\t<td>58,920</td>\n\t\t\t\t\t<td>58,905</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,774\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,758\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 40분 </td>\n\t\t\t\t\t<td>59,337</td>\n\t\t\t\t\t<td>59,320</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,771\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,755\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 45분 </td>\n\t\t\t\t\t<td>59,456</td>\n\t\t\t\t\t<td>59,440</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,913\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,897\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 50분 </td>\n\t\t\t\t\t<td>59,223</td>\n\t\t\t\t\t<td>59,207</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,817\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,801\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>06시 55분 </td>\n\t\t\t\t\t<td>59,420</td>\n\t\t\t\t\t<td>59,397</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,737\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t59,722\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 00분 </td>\n\t\t\t\t\t<td>59,676</td>\n\t\t\t\t\t<td>59,653</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,047\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,031\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 05분 </td>\n\t\t\t\t\t<td>60,050</td>\n\t\t\t\t\t<td>60,027</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,280\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,264\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 10분 </td>\n\t\t\t\t\t<td>60,112</td>\n\t\t\t\t\t<td>60,089</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,735\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,718\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 15분 </td>\n\t\t\t\t\t<td>60,195</td>\n\t\t\t\t\t<td>60,172</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,647\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,630\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 20분 </td>\n\t\t\t\t\t<td>59,884</td>\n\t\t\t\t\t<td>59,862</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,384\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,368\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 25분 </td>\n\t\t\t\t\t<td>59,904</td>\n\t\t\t\t\t<td>59,882</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,527\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,510\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 30분 </td>\n\t\t\t\t\t<td>60,157</td>\n\t\t\t\t\t<td>60,133</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,306\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,288\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 35분 </td>\n\t\t\t\t\t<td>60,093</td>\n\t\t\t\t\t<td>60,071</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,474\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,458\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 40분 </td>\n\t\t\t\t\t<td>60,036</td>\n\t\t\t\t\t<td>60,013</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,129\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,112\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 45분 </td>\n\t\t\t\t\t<td>60,337</td>\n\t\t\t\t\t<td>60,313</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,375\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,357\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 50분 </td>\n\t\t\t\t\t<td>60,420</td>\n\t\t\t\t\t<td>60,388</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,617\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,599\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>07시 55분 </td>\n\t\t\t\t\t<td>60,303</td>\n\t\t\t\t\t<td>60,263</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,860\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t60,842\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 00분 </td>\n\t\t\t\t\t<td>60,458</td>\n\t\t\t\t\t<td>60,393</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,207\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,188\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 05분 </td>\n\t\t\t\t\t<td>60,562</td>\n\t\t\t\t\t<td>60,460</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,168\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,145\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 10분 </td>\n\t\t\t\t\t<td>60,696</td>\n\t\t\t\t\t<td>60,537</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,074\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,044\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 15분 </td>\n\t\t\t\t\t<td>60,663</td>\n\t\t\t\t\t<td>60,437</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,391\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,352\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 20분 </td>\n\t\t\t\t\t<td>60,533</td>\n\t\t\t\t\t<td>60,211</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,346\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,294\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 25분 </td>\n\t\t\t\t\t<td>60,777</td>\n\t\t\t\t\t<td>60,344</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,552\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,476\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 30분 </td>\n\t\t\t\t\t<td>60,804</td>\n\t\t\t\t\t<td>60,257</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,782\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t61,680\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 35분 </td>\n\t\t\t\t\t<td>60,791</td>\n\t\t\t\t\t<td>60,106</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,164\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,028\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 40분 </td>\n\t\t\t\t\t<td>60,818</td>\n\t\t\t\t\t<td>59,958</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,458\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,273\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 45분 </td>\n\t\t\t\t\t<td>60,847</td>\n\t\t\t\t\t<td>59,797</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,554\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,332\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 50분 </td>\n\t\t\t\t\t<td>61,013</td>\n\t\t\t\t\t<td>59,787</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,828\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,550\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>08시 55분 </td>\n\t\t\t\t\t<td>60,946</td>\n\t\t\t\t\t<td>59,518</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,797\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,451\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 00분 </td>\n\t\t\t\t\t<td>61,132</td>\n\t\t\t\t\t<td>59,436</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,936\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,502\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 05분 </td>\n\t\t\t\t\t<td>60,727</td>\n\t\t\t\t\t<td>58,795</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,068\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,566\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 10분 </td>\n\t\t\t\t\t<td>60,879</td>\n\t\t\t\t\t<td>58,674</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,744\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,188\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 15분 </td>\n\t\t\t\t\t<td>60,852</td>\n\t\t\t\t\t<td>58,355</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,406\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,735\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 20분 </td>\n\t\t\t\t\t<td>60,940</td>\n\t\t\t\t\t<td>58,158</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,713\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,007\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 25분 </td>\n\t\t\t\t\t<td>61,198</td>\n\t\t\t\t\t<td>58,134</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,763\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,012\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 30분 </td>\n\t\t\t\t\t<td>60,913</td>\n\t\t\t\t\t<td>57,657</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,134\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,269\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 35분 </td>\n\t\t\t\t\t<td>60,999</td>\n\t\t\t\t\t<td>57,413</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,284\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,348\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 40분 </td>\n\t\t\t\t\t<td>61,047</td>\n\t\t\t\t\t<td>57,080</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,281\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,261\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 45분 </td>\n\t\t\t\t\t<td>61,279</td>\n\t\t\t\t\t<td>57,064</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,546\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,359\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 50분 </td>\n\t\t\t\t\t<td>61,547</td>\n\t\t\t\t\t<td>57,072</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,655\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,375\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>09시 55분 </td>\n\t\t\t\t\t<td>62,000</td>\n\t\t\t\t\t<td>57,038</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,850\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,321\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 00분 </td>\n\t\t\t\t\t<td>62,042</td>\n\t\t\t\t\t<td>56,750</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,153\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,541\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 05분 </td>\n\t\t\t\t\t<td>62,276</td>\n\t\t\t\t\t<td>56,610</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,518\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,783\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 10분 </td>\n\t\t\t\t\t<td>62,592</td>\n\t\t\t\t\t<td>56,453</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,481\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,610\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 15분 </td>\n\t\t\t\t\t<td>62,816</td>\n\t\t\t\t\t<td>56,389</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,545\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,514\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 20분 </td>\n\t\t\t\t\t<td>62,894</td>\n\t\t\t\t\t<td>56,039</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,071\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,930\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 25분 </td>\n\t\t\t\t\t<td>62,877</td>\n\t\t\t\t\t<td>55,813</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,166\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,806\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 30분 </td>\n\t\t\t\t\t<td>63,083</td>\n\t\t\t\t\t<td>55,736</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,187\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,693\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 35분 </td>\n\t\t\t\t\t<td>63,114</td>\n\t\t\t\t\t<td>55,463</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,424\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,769\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 40분 </td>\n\t\t\t\t\t<td>63,193</td>\n\t\t\t\t\t<td>55,316</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,363\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,841\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 45분 </td>\n\t\t\t\t\t<td>63,212</td>\n\t\t\t\t\t<td>55,067</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,375\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,711\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 50분 </td>\n\t\t\t\t\t<td>63,322</td>\n\t\t\t\t\t<td>55,019</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,871\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,259\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>10시 55분 </td>\n\t\t\t\t\t<td>63,428</td>\n\t\t\t\t\t<td>54,925</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,175\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,398\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 00분 </td>\n\t\t\t\t\t<td>63,320</td>\n\t\t\t\t\t<td>54,581</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,532\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,675\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 05분 </td>\n\t\t\t\t\t<td>63,086</td>\n\t\t\t\t\t<td>54,248</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,458\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,768\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 10분 </td>\n\t\t\t\t\t<td>63,017</td>\n\t\t\t\t\t<td>53,957</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,410\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,708\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 15분 </td>\n\t\t\t\t\t<td>63,317</td>\n\t\t\t\t\t<td>54,053</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,561\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,730\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 20분 </td>\n\t\t\t\t\t<td>63,535</td>\n\t\t\t\t\t<td>54,025</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,803\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,774\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 25분 </td>\n\t\t\t\t\t<td>63,617</td>\n\t\t\t\t\t<td>53,832</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,207\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,926\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 30분 </td>\n\t\t\t\t\t<td>63,716</td>\n\t\t\t\t\t<td>53,735</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,964\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,822\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 35분 </td>\n\t\t\t\t\t<td>63,799</td>\n\t\t\t\t\t<td>53,677</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,904\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,741\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 40분 </td>\n\t\t\t\t\t<td>63,554</td>\n\t\t\t\t\t<td>53,255</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,463\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,497\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 45분 </td>\n\t\t\t\t\t<td>63,491</td>\n\t\t\t\t\t<td>53,243</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,738\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,799\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 50분 </td>\n\t\t\t\t\t<td>63,767</td>\n\t\t\t\t\t<td>53,352</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,390\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,606\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>11시 55분 </td>\n\t\t\t\t\t<td>63,551</td>\n\t\t\t\t\t<td>52,916</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,186\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,539\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 00분 </td>\n\t\t\t\t\t<td>63,525</td>\n\t\t\t\t\t<td>52,748</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,103\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,443\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 05분 </td>\n\t\t\t\t\t<td>63,435</td>\n\t\t\t\t\t<td>52,614</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,914\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,366\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 10분 </td>\n\t\t\t\t\t<td>63,434</td>\n\t\t\t\t\t<td>52,524</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,912\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,394\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 15분 </td>\n\t\t\t\t\t<td>63,488</td>\n\t\t\t\t\t<td>52,501</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,923\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,346\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 20분 </td>\n\t\t\t\t\t<td>63,200</td>\n\t\t\t\t\t<td>52,279</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,977\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,288\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 25분 </td>\n\t\t\t\t\t<td>63,566</td>\n\t\t\t\t\t<td>52,533</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,367\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,456\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 30분 </td>\n\t\t\t\t\t<td>63,710</td>\n\t\t\t\t\t<td>52,396</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,206\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,314\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 35분 </td>\n\t\t\t\t\t<td>63,692</td>\n\t\t\t\t\t<td>52,344</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,226\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,381\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 40분 </td>\n\t\t\t\t\t<td>63,407</td>\n\t\t\t\t\t<td>52,096</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,332\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,376\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 45분 </td>\n\t\t\t\t\t<td>63,576</td>\n\t\t\t\t\t<td>52,237</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,214\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,265\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 50분 </td>\n\t\t\t\t\t<td>63,575</td>\n\t\t\t\t\t<td>51,981</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,724\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,685\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>12시 55분 </td>\n\t\t\t\t\t<td>63,700</td>\n\t\t\t\t\t<td>52,235</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,581\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,533\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 00분 </td>\n\t\t\t\t\t<td>63,532</td>\n\t\t\t\t\t<td>52,280</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,598\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,555\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 05분 </td>\n\t\t\t\t\t<td>63,726</td>\n\t\t\t\t\t<td>52,470</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,580\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,599\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 10분 </td>\n\t\t\t\t\t<td>63,942</td>\n\t\t\t\t\t<td>52,696</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,877\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,820\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 15분 </td>\n\t\t\t\t\t<td>64,014</td>\n\t\t\t\t\t<td>52,728</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,848\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,733\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 20분 </td>\n\t\t\t\t\t<td>64,614</td>\n\t\t\t\t\t<td>52,944</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,860\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,650\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 25분 </td>\n\t\t\t\t\t<td>64,480</td>\n\t\t\t\t\t<td>52,862</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,681\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,490\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 30분 </td>\n\t\t\t\t\t<td>64,606</td>\n\t\t\t\t\t<td>52,999</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,500\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,357\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 35분 </td>\n\t\t\t\t\t<td>64,543</td>\n\t\t\t\t\t<td>53,038</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,703\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,619\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 40분 </td>\n\t\t\t\t\t<td>64,152</td>\n\t\t\t\t\t<td>52,787</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,716\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,699\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 45분 </td>\n\t\t\t\t\t<td>63,761</td>\n\t\t\t\t\t<td>52,573</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,344\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,383\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 50분 </td>\n\t\t\t\t\t<td>63,921</td>\n\t\t\t\t\t<td>52,879</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,915\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,045\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>13시 55분 </td>\n\t\t\t\t\t<td>63,694</td>\n\t\t\t\t\t<td>52,829</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,319\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,406\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 00분 </td>\n\t\t\t\t\t<td>64,271</td>\n\t\t\t\t\t<td>53,520</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,363\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,435\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 05분 </td>\n\t\t\t\t\t<td>64,231</td>\n\t\t\t\t\t<td>53,680</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,381\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,394\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 10분 </td>\n\t\t\t\t\t<td>64,427</td>\n\t\t\t\t\t<td>53,944</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,999\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,122\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 15분 </td>\n\t\t\t\t\t<td>64,156</td>\n\t\t\t\t\t<td>53,902</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,788\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,966\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 20분 </td>\n\t\t\t\t\t<td>64,230</td>\n\t\t\t\t\t<td>54,092</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,835\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,913\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 25분 </td>\n\t\t\t\t\t<td>64,602</td>\n\t\t\t\t\t<td>54,678</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,157\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,205\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 30분 </td>\n\t\t\t\t\t<td>64,405</td>\n\t\t\t\t\t<td>54,752</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,951\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,233\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 35분 </td>\n\t\t\t\t\t<td>64,199</td>\n\t\t\t\t\t<td>54,840</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,590\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,914\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 40분 </td>\n\t\t\t\t\t<td>64,198</td>\n\t\t\t\t\t<td>54,992</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,283\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,701\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 45분 </td>\n\t\t\t\t\t<td>64,229</td>\n\t\t\t\t\t<td>55,165</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,439\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,883\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 50분 </td>\n\t\t\t\t\t<td>64,306</td>\n\t\t\t\t\t<td>55,529</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,676\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,220\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>14시 55분 </td>\n\t\t\t\t\t<td>64,265</td>\n\t\t\t\t\t<td>55,766</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,562\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,115\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 00분 </td>\n\t\t\t\t\t<td>64,429</td>\n\t\t\t\t\t<td>56,175</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,521\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,082\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 05분 </td>\n\t\t\t\t\t<td>64,175</td>\n\t\t\t\t\t<td>56,291</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,351\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t62,988\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 10분 </td>\n\t\t\t\t\t<td>64,224</td>\n\t\t\t\t\t<td>56,701</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,593\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,295\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 15분 </td>\n\t\t\t\t\t<td>63,654</td>\n\t\t\t\t\t<td>56,730</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,426\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,248\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 20분 </td>\n\t\t\t\t\t<td>63,921</td>\n\t\t\t\t\t<td>57,227</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,301\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,226\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 25분 </td>\n\t\t\t\t\t<td>63,976</td>\n\t\t\t\t\t<td>57,693</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,489\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,468\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 30분 </td>\n\t\t\t\t\t<td>63,768</td>\n\t\t\t\t\t<td>57,871</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,618\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,563\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 35분 </td>\n\t\t\t\t\t<td>63,971</td>\n\t\t\t\t\t<td>58,410</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,452\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,535\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 40분 </td>\n\t\t\t\t\t<td>64,096</td>\n\t\t\t\t\t<td>58,864</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,412\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,543\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 45분 </td>\n\t\t\t\t\t<td>64,069</td>\n\t\t\t\t\t<td>59,187</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,469\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,707\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 50분 </td>\n\t\t\t\t\t<td>63,948</td>\n\t\t\t\t\t<td>59,413</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,549\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,823\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>15시 55분 </td>\n\t\t\t\t\t<td>63,887</td>\n\t\t\t\t\t<td>59,671</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,830\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,123\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 00분 </td>\n\t\t\t\t\t<td>63,716</td>\n\t\t\t\t\t<td>59,855</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,604\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,032\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 05분 </td>\n\t\t\t\t\t<td>63,186</td>\n\t\t\t\t\t<td>59,635</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,263\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,709\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 10분 </td>\n\t\t\t\t\t<td>63,283</td>\n\t\t\t\t\t<td>60,117</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,246\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,796\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 15분 </td>\n\t\t\t\t\t<td>63,660</td>\n\t\t\t\t\t<td>60,823</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,433\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,156\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 20분 </td>\n\t\t\t\t\t<td>63,754</td>\n\t\t\t\t\t<td>61,273</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,585\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,435\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 25분 </td>\n\t\t\t\t\t<td>64,070</td>\n\t\t\t\t\t<td>61,867</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,741\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,650\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 30분 </td>\n\t\t\t\t\t<td>64,122</td>\n\t\t\t\t\t<td>62,182</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,622\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,647\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 35분 </td>\n\t\t\t\t\t<td>64,347</td>\n\t\t\t\t\t<td>62,570</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,469\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,559\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 40분 </td>\n\t\t\t\t\t<td>64,229</td>\n\t\t\t\t\t<td>62,688</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,993\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,162\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 45분 </td>\n\t\t\t\t\t<td>64,411</td>\n\t\t\t\t\t<td>63,084</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,236\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,504\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 50분 </td>\n\t\t\t\t\t<td>64,158</td>\n\t\t\t\t\t<td>63,026</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,769\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,138\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>16시 55분 </td>\n\t\t\t\t\t<td>64,515</td>\n\t\t\t\t\t<td>63,540</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,207\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,670\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 00분 </td>\n\t\t\t\t\t<td>64,585</td>\n\t\t\t\t\t<td>63,757</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,402\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,926\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 05분 </td>\n\t\t\t\t\t<td>64,281</td>\n\t\t\t\t\t<td>63,610</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,802\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,386\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 10분 </td>\n\t\t\t\t\t<td>64,465</td>\n\t\t\t\t\t<td>64,012</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,798\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,475\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 15분 </td>\n\t\t\t\t\t<td>64,936</td>\n\t\t\t\t\t<td>64,637</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,088\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,871\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 20분 </td>\n\t\t\t\t\t<td>65,010</td>\n\t\t\t\t\t<td>64,804</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,816\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,660\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 25분 </td>\n\t\t\t\t\t<td>65,194</td>\n\t\t\t\t\t<td>65,073</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,957\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,955\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 30분 </td>\n\t\t\t\t\t<td>65,666</td>\n\t\t\t\t\t<td>65,594</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,142\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,175\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 35분 </td>\n\t\t\t\t\t<td>65,795</td>\n\t\t\t\t\t<td>65,766</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,428\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,392\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 40분 </td>\n\t\t\t\t\t<td>66,254</td>\n\t\t\t\t\t<td>66,262</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,707\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,686\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 45분 </td>\n\t\t\t\t\t<td>66,245</td>\n\t\t\t\t\t<td>66,226</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,937\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,907\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 50분 </td>\n\t\t\t\t\t<td>66,301</td>\n\t\t\t\t\t<td>66,286</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,226\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,191\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>17시 55분 </td>\n\t\t\t\t\t<td>66,565</td>\n\t\t\t\t\t<td>66,565</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,328\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,287\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 00분 </td>\n\t\t\t\t\t<td>66,436</td>\n\t\t\t\t\t<td>66,436</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,406\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,367\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 05분 </td>\n\t\t\t\t\t<td>66,402</td>\n\t\t\t\t\t<td>66,402</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,220\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,177\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 10분 </td>\n\t\t\t\t\t<td>66,438</td>\n\t\t\t\t\t<td>66,438</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,190\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,147\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 15분 </td>\n\t\t\t\t\t<td>66,499</td>\n\t\t\t\t\t<td>66,499</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,215\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,174\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 20분 </td>\n\t\t\t\t\t<td>66,510</td>\n\t\t\t\t\t<td>66,510</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,255\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,213\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 25분 </td>\n\t\t\t\t\t<td>66,770</td>\n\t\t\t\t\t<td>66,770</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,365\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,331\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 30분 </td>\n\t\t\t\t\t<td>66,561</td>\n\t\t\t\t\t<td>66,561</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,158\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,125\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 35분 </td>\n\t\t\t\t\t<td>66,529</td>\n\t\t\t\t\t<td>66,529</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,058\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t68,011\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 40분 </td>\n\t\t\t\t\t<td>66,521</td>\n\t\t\t\t\t<td>66,521</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,946\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,898\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 45분 </td>\n\t\t\t\t\t<td>66,472</td>\n\t\t\t\t\t<td>66,472</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,846\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,796\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 50분 </td>\n\t\t\t\t\t<td>66,302</td>\n\t\t\t\t\t<td>66,302</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,934\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,887\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>18시 55분 </td>\n\t\t\t\t\t<td>66,293</td>\n\t\t\t\t\t<td>66,293</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,756\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,713\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 00분 </td>\n\t\t\t\t\t<td>66,306</td>\n\t\t\t\t\t<td>66,306</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,662\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,662\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 05분 </td>\n\t\t\t\t\t<td>66,257</td>\n\t\t\t\t\t<td>66,257</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,903\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,903\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 10분 </td>\n\t\t\t\t\t<td>66,267</td>\n\t\t\t\t\t<td>66,267</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,658\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,658\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 15분 </td>\n\t\t\t\t\t<td>66,094</td>\n\t\t\t\t\t<td>66,093</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,420\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,419\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 20분 </td>\n\t\t\t\t\t<td>66,031</td>\n\t\t\t\t\t<td>66,031</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,429\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,429\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 25분 </td>\n\t\t\t\t\t<td>65,971</td>\n\t\t\t\t\t<td>65,971</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,317\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,317\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 30분 </td>\n\t\t\t\t\t<td>66,054</td>\n\t\t\t\t\t<td>66,053</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,296\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,296\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 35분 </td>\n\t\t\t\t\t<td>65,755</td>\n\t\t\t\t\t<td>65,755</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,029\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t67,029\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 40분 </td>\n\t\t\t\t\t<td>65,610</td>\n\t\t\t\t\t<td>65,610</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,917\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,917\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 45분 </td>\n\t\t\t\t\t<td>65,789</td>\n\t\t\t\t\t<td>65,789</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,985\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,985\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 50분 </td>\n\t\t\t\t\t<td>65,723</td>\n\t\t\t\t\t<td>65,723</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,706\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,706\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>19시 55분 </td>\n\t\t\t\t\t<td>65,632</td>\n\t\t\t\t\t<td>65,632</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,583\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,583\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 00분 </td>\n\t\t\t\t\t<td>65,687</td>\n\t\t\t\t\t<td>65,687</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,528\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,528\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 05분 </td>\n\t\t\t\t\t<td>65,736</td>\n\t\t\t\t\t<td>65,736</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,358\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,358\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 10분 </td>\n\t\t\t\t\t<td>65,319</td>\n\t\t\t\t\t<td>65,319</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,433\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,433\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 15분 </td>\n\t\t\t\t\t<td>65,335</td>\n\t\t\t\t\t<td>65,335</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,135\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,135\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 20분 </td>\n\t\t\t\t\t<td>65,352</td>\n\t\t\t\t\t<td>65,352</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,362\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,362\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 25분 </td>\n\t\t\t\t\t<td>65,246</td>\n\t\t\t\t\t<td>65,246</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,158\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,158\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 30분 </td>\n\t\t\t\t\t<td>64,820</td>\n\t\t\t\t\t<td>64,819</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,011\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t66,011\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 35분 </td>\n\t\t\t\t\t<td>64,439</td>\n\t\t\t\t\t<td>64,439</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,735\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,735\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 40분 </td>\n\t\t\t\t\t<td>64,284</td>\n\t\t\t\t\t<td>64,284</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,755\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,755\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 45분 </td>\n\t\t\t\t\t<td>64,139</td>\n\t\t\t\t\t<td>64,139</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,872\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,873\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 50분 </td>\n\t\t\t\t\t<td>64,234</td>\n\t\t\t\t\t<td>64,234</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,764\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,764\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>20시 55분 </td>\n\t\t\t\t\t<td>64,201</td>\n\t\t\t\t\t<td>64,201</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,432\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,432\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 00분 </td>\n\t\t\t\t\t<td>64,186</td>\n\t\t\t\t\t<td>64,187</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,288\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,288\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 05분 </td>\n\t\t\t\t\t<td>63,687</td>\n\t\t\t\t\t<td>63,687</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,873\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,873\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 10분 </td>\n\t\t\t\t\t<td>63,690</td>\n\t\t\t\t\t<td>63,690</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,003\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t65,003\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 15분 </td>\n\t\t\t\t\t<td>63,548</td>\n\t\t\t\t\t<td>63,548</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,668\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,668\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 20분 </td>\n\t\t\t\t\t<td>63,386</td>\n\t\t\t\t\t<td>63,386</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,439\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,439\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 25분 </td>\n\t\t\t\t\t<td>63,437</td>\n\t\t\t\t\t<td>63,437</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,274\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,274\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 30분 </td>\n\t\t\t\t\t<td>63,372</td>\n\t\t\t\t\t<td>63,372</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,602\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,601\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 35분 </td>\n\t\t\t\t\t<td>63,232</td>\n\t\t\t\t\t<td>63,232</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,303\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,303\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 40분 </td>\n\t\t\t\t\t<td>62,974</td>\n\t\t\t\t\t<td>62,974</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,214\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,214\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 45분 </td>\n\t\t\t\t\t<td>63,020</td>\n\t\t\t\t\t<td>63,019</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,287\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,287\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 50분 </td>\n\t\t\t\t\t<td>62,965</td>\n\t\t\t\t\t<td>62,965</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,712\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,712\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>21시 55분 </td>\n\t\t\t\t\t<td>63,076</td>\n\t\t\t\t\t<td>63,076</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,908\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,908\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 00분 </td>\n\t\t\t\t\t<td>63,014</td>\n\t\t\t\t\t<td>63,014</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,144\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,144\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 05분 </td>\n\t\t\t\t\t<td>63,250</td>\n\t\t\t\t\t<td>63,250</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,365\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,365\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 10분 </td>\n\t\t\t\t\t<td>63,125</td>\n\t\t\t\t\t<td>63,125</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,359\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,359\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 15분 </td>\n\t\t\t\t\t<td>63,068</td>\n\t\t\t\t\t<td>63,068</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,458\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,458\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 20분 </td>\n\t\t\t\t\t<td>63,123</td>\n\t\t\t\t\t<td>63,123</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,500\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,500\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 25분 </td>\n\t\t\t\t\t<td>62,844</td>\n\t\t\t\t\t<td>62,844</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,300\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,300\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 30분 </td>\n\t\t\t\t\t<td>62,846</td>\n\t\t\t\t\t<td>62,846</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,174\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,174\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 35분 </td>\n\t\t\t\t\t<td>62,696</td>\n\t\t\t\t\t<td>62,696</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,146\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,146\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 40분 </td>\n\t\t\t\t\t<td>62,781</td>\n\t\t\t\t\t<td>62,781</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,669\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,669\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 45분 </td>\n\t\t\t\t\t<td>62,486</td>\n\t\t\t\t\t<td>62,486</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,678\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,678\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 50분 </td>\n\t\t\t\t\t<td>62,160</td>\n\t\t\t\t\t<td>62,160</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,599\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,599\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>22시 55분 </td>\n\t\t\t\t\t<td>62,321</td>\n\t\t\t\t\t<td>62,321</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,436\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,436\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 00분 </td>\n\t\t\t\t\t<td>62,462</td>\n\t\t\t\t\t<td>62,462</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,838\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t63,838\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 05분 </td>\n\t\t\t\t\t<td>63,173</td>\n\t\t\t\t\t<td>63,173</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,632\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,632\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 10분 </td>\n\t\t\t\t\t<td>63,142</td>\n\t\t\t\t\t<td>63,142</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,918\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t\t64,918\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 15분 </td>\n\t\t\t\t\t<td>63,046</td>\n\t\t\t\t\t<td>63,046</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 20분 </td>\n\t\t\t\t\t<td>62,762</td>\n\t\t\t\t\t<td>62,762</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 25분 </td>\n\t\t\t\t\t<td>62,607</td>\n\t\t\t\t\t<td>62,607</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 30분 </td>\n\t\t\t\t\t<td>62,459</td>\n\t\t\t\t\t<td>62,459</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 35분 </td>\n\t\t\t\t\t<td>62,186</td>\n\t\t\t\t\t<td>62,186</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 40분 </td>\n\t\t\t\t\t<td>61,879</td>\n\t\t\t\t\t<td>61,879</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 45분 </td>\n\t\t\t\t\t<td>61,761</td>\n\t\t\t\t\t<td>61,761</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 50분 </td>\n\t\t\t\t\t<td>61,569</td>\n\t\t\t\t\t<td>61,569</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t<tr>\n\t\t\t\t\t<td>23시 55분 </td>\n\t\t\t\t\t<td>61,180</td>\n\t\t\t\t\t<td>61,181</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t\t<td>\n\t\t\t\t\t\t\n\t\t\t\t\t</td>\n\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t</tbody>\n\t\t</table>\n\t</div>\n</div>\n \n\n<div class=\"btn_area AlignRight\">\n\t<a href=\"/powerinfoGraphSearch.es?mid=a10606030000&device=chart&view_sdate='2024.12.29(일)'&view_edate='2025.01.05(일)'\" target=\"_blank\" title=\"새창열림\" class=\"btn_link02\">차트보기</a>\n</div>\n\n<h4>발전원별실시간 전력수급현황</h4>\n\t\n\n\n\n\n\n\n\n<script type=\"text/javascript\" src=\"/kpx_src/js/highcharts.js\"></script>\n<script type=\"text/javascript\" src=\"/kpx_src/js/exporting.js\"></script>\n\n<script type=\"text/javascript\">\n$(document).ready(function(){\n\tdrawChart2(null, null, null);\n});\n\nfunction lPad(str, num, chr){\n\tstr = str +\"\";\n\tif(!str || !chr || str.length >= num){\n\t\treturn str;\n\t}\n\tvar max = num - str.length;\n\tfor(var i =0; i < max; i++){\n\t\tstr = chr+str;\n\t}\n\treturn str;\n}\n\nfunction drawChart2(par1, par2, par3){\n\tvar ictArr = [{\"localCoal\":\"192.875\",\"ppa\":\"0\",\"windPower\":\"440.859\",\"nuclearPower\":\"24132.1\",\"regDate\":\"2025-01-05 00:00\",\"raisingWater\":\"1168.98\",\"newRenewable\":\"3212.03\",\"sunlight\":\"0.0\",\"oil\":\"361.51\",\"once\":\"20250105000000\",\"gas\":\"21242.1\",\"coal\":\"13998.2\",\"newRenewablePlusWindPower\":\"3652.89\",\"btm\":\"0\",\"waterPower\":\"38.1576\",\"seq\":0},{\"localCoal\":\"193.424\",\"ppa\":\"0\",\"windPower\":\"470.42\",\"nuclearPower\":\"24183.2\",\"regDate\":\"2025-01-05 00:05\",\"raisingWater\":\"1165.73\",\"newRenewable\":\"3214.68\",\"sunlight\":\"0.0\",\"oil\":\"361.527\",\"once\":\"20250105000500\",\"gas\":\"20873.5\",\"coal\":\"13997.1\",\"newRenewablePlusWindPower\":\"3685.1\",\"btm\":\"0\",\"waterPower\":\"36.1821\",\"seq\":0},{\"localCoal\":\"193.955\",\"ppa\":\"0\",\"windPower\":\"461.526\",\"nuclearPower\":\"24169.9\",\"regDate\":\"2025-01-05 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00:20\",\"raisingWater\":\"693.423\",\"newRenewable\":\"3173.52\",\"sunlight\":\"0.0\",\"oil\":\"362.933\",\"once\":\"20250105002000\",\"gas\":\"20407.2\",\"coal\":\"14135.0\",\"newRenewablePlusWindPower\":\"3652.4\",\"btm\":\"0\",\"waterPower\":\"36.0563\",\"seq\":0},{\"localCoal\":\"192.82\",\"ppa\":\"0\",\"windPower\":\"463.816\",\"nuclearPower\":\"24170.2\",\"regDate\":\"2025-01-05 00:25\",\"raisingWater\":\"691.803\",\"newRenewable\":\"3170.81\",\"sunlight\":\"0.0\",\"oil\":\"362.799\",\"once\":\"20250105002500\",\"gas\":\"20069.5\",\"coal\":\"14136.5\",\"newRenewablePlusWindPower\":\"3634.62\",\"btm\":\"0\",\"waterPower\":\"36.0797\",\"seq\":0},{\"localCoal\":\"193.918\",\"ppa\":\"0\",\"windPower\":\"462.251\",\"nuclearPower\":\"24199.9\",\"regDate\":\"2025-01-05 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23:10\",\"raisingWater\":\"742.367\",\"newRenewable\":\"3191.41\",\"sunlight\":\"0.0\",\"oil\":\"364.165\",\"once\":\"20250105231000\",\"gas\":\"20716.8\",\"coal\":\"15089.4\",\"newRenewablePlusWindPower\":\"3582.29\",\"btm\":\"0\",\"waterPower\":\"39.4469\",\"seq\":0},{\"localCoal\":\"0\",\"ppa\":\"0\",\"windPower\":\"0\",\"nuclearPower\":\"0\",\"regDate\":\"0\",\"raisingWater\":\"0\",\"newRenewable\":\"0\",\"sunlight\":\"0\",\"oil\":\"0\",\"once\":\"20250105231500\",\"gas\":\"0\",\"coal\":\"0\",\"newRenewablePlusWindPower\":\"0\",\"btm\":\"0\",\"waterPower\":\"0\",\"seq\":\"99999\"},{\"localCoal\":\"0\",\"ppa\":\"0\",\"windPower\":\"0\",\"nuclearPower\":\"0\",\"regDate\":\"0\",\"raisingWater\":\"0\",\"newRenewable\":\"0\",\"sunlight\":\"0\",\"oil\":\"0\",\"once\":\"20250105232000\",\"gas\":\"0\",\"coal\":\"0\",\"newRenewablePlusWindPower\":\"0\",\"btm\":\"0\",\"waterPower\":\"0\",\"seq\":\"99999\"},{\"localCoal\":\"0\",\"ppa\":\"0\",\"windPower\":\"0\",\"nuclearPower\":\"0\",\"regDate\":\"0\",\"raisingWater\":\"0\",\"newRenewable\":\"0\",\"sunlight\":\"0\",\"oil\":\"0\",\"once\":\"20250105232500\",\"gas\":\"0\",\"coal\":\"0\",\"newRenewablePlusWindPower\":\"0\",\"btm\":\"0\",\"waterPower\":\"0\",\"seq\":\"99999\"},{\"localCoal\":\"0\",\"ppa\":\"0\",\"windPower\":\"0\",\"nuclearPower\":\"0\",\"regDate\":\"0\",\"raisingWater\":\"0\",\"newRenewable\":\"0\",\"sunlight\":\"0\",\"oil\":\"0\",\"once\":\"20250105233000\",\"gas\":\"0\",\"coal\":\"0\",\"newRenewablePlusWindPower\":\"0\",\"btm\":\"0\",\"waterPower\":\"0\",\"seq\":\"99999\"},{\"localCoal\":\"0\",\"ppa\":\"0\",\"windPower\":\"0\",\"nuclearPower\":\"0\",\"regDate\":\"0\",\"raisingWater\":\"0\",\"newRenewable\":\"0\",\"sunlight\":\"0\",\"oil\":\"0\",\"once\":\"20250105233500\",\"gas\":\"0\",\"coal\":\"0\",\"newRenewablePlusWindPower\":\"0\",\"btm\":\"0\",\"waterPower\":\"0\",\"seq\":\"99999\"},{\"localCoal\":\"0\",\"ppa\":\"0\",\"windPower\":\"0\",\"nuclearPower\":\"0\",\"regDate\":\"0\",\"raisingWater\":\"0\",\"newRenewable\":\"0\",\"sunlight\":\"0\",\"oil\":\"0\",\"once\":\"20250105234000\",\"gas\":\"0\",\"coal\":\"0\",\"newRenewablePlusWindPower\":\"0\",\"btm\":\"0\",\"waterPower\":\"0\",\"seq\":\"99999\"},{\"localCoal\":\"0\",\"ppa\":\"0\",\"windPower\":\"0\",\"nuclearPower\":\"0\",\"regDate\":\"0\",\"raisingWater\":\"0\",\"newRenewable\":\"0\",\"sunlight\":\"0\",\"oil\":\"0\",\"once\":\"20250105234500\",\"gas\":\"0\",\"coal\":\"0\",\"newRenewablePlusWindPower\":\"0\",\"btm\":\"0\",\"waterPower\":\"0\",\"seq\":\"99999\"},{\"localCoal\":\"0\",\"ppa\":\"0\",\"windPower\":\"0\",\"nuclearPower\":\"0\",\"regDate\":\"0\",\"raisingWater\":\"0\",\"newRenewable\":\"0\",\"sunlight\":\"0\",\"oil\":\"0\",\"once\":\"20250105235000\",\"gas\":\"0\",\"coal\":\"0\",\"newRenewablePlusWindPower\":\"0\",\"btm\":\"0\",\"waterPower\":\"0\",\"seq\":\"99999\"},{\"localCoal\":\"0\",\"ppa\":\"0\",\"windPower\":\"0\",\"nuclearPower\":\"0\",\"regDate\":\"0\",\"raisingWater\":\"0\",\"newRenewable\":\"0\",\"sunlight\":\"0\",\"oil\":\"0\",\"once\":\"20250105235500\",\"gas\":\"0\",\"coal\":\"0\",\"newRenewablePlusWindPower\":\"0\",\"btm\":\"0\",\"waterPower\":\"0\",\"seq\":\"99999\"}];\n\tvar onceArr = new Array();\n  \tvar raisingWaterArr = new Array();\n  \tvar waterPowerArr = new Array();\n  \tvar windPowerArr = new Array();\n  \tvar gasArr = new Array();\n  \tvar oilArr = new Array();\n  \tvar newRenewableArr = new Array();\n  \tvar localCoalArr = new Array();\n  \tvar coalArr = new Array();\n  \tvar nuclearPowerArr = new Array();\n  \tvar sunligthArr = new Array();\n  \tvar ppaArr = new Array();\n  \tvar btmArr = new Array();\n  \tvar etcArr = new Array();\n  \tfor (var k in ictArr){\n  \t\tvar xobj = ictArr[k];\n  \t\tonceArr.push(Number(xobj.once.replace(/ /gi,\"\")));\n  \t\traisingWaterArr.push(Number(xobj.raisingWater.replace(/ /gi,\"\")));\n  \t\twaterPowerArr.push(Number(xobj.waterPower.replace(/ /gi,\"\")));\n  \t\twindPowerArr.push(Number(xobj.windPower.replace(/ /gi,\"\")));\n  \t\toilArr.push(Number(xobj.oil.replace(/ /gi,\"\")));\n  \t\tlocalCoalArr.push(Number(xobj.localCoal.replace(/ /gi,\"\")));\n  \t\t//etcArr.push(Number(xobj.raisingWater.replace(/ /gi,\"\"))+Number(xobj.waterPower.replace(/ /gi,\"\"))+Number(xobj.oil.replace(/ /gi,\"\")));\n  \t\tgasArr.push(Number(xobj.gas.replace(/ /gi,\"\")));\n  \t\tnewRenewableArr.push(Number(xobj.newRenewable.replace(/ /gi,\"\")));\n  \t\t//localCoalArr.push(Number(xobj.localCoal.replace(/ /gi,\"\")));\n  \t\tcoalArr.push(Number(xobj.coal.replace(/ /gi,\"\")));\n  \t\tnuclearPowerArr.push(Number(xobj.nuclearPower.replace(/ /gi,\"\")));\n  \t\tsunligthArr.push(Number(xobj.sunlight.replace(/ /gi,\"\")));\n  \t\tppaArr.push(Number(xobj.ppa.replace(/ /gi,\"\")));\n  \t\tbtmArr.push(Number(xobj.btm.replace(/ /gi,\"\")));\n  \t}\n\t\n\tvar x1 = raisingWaterArr;\n\tvar xx2 = gasArr;\n\tvar xx3 = newRenewableArr;\n\tvar xx4 = oilArr;\n\tvar xx5 = coalArr; \n\tvar xx6 = nuclearPowerArr;\n\tvar xx7 = onceArr;\n\tvar xx8 = sunligthArr;\n\tvar xx9 = waterPowerArr;\n\tvar xx10 = localCoalArr;\n\tvar xx11 = ppaArr;\n\tvar xx12 = btmArr;\n\tvar xx13 = windPowerArr;\n\t\n\tvar x1_1 = new Array();\n\tvar x1_2 = new Array();\n\t\n\tfor (var x in x1){\n\t\tvar y = x1[x];\n\t\tif(y <= 0){\n\t\t\tif(y == 0) y = null;\n\t\t\tx1_1.push(y);\n\t\t\tx1_2.push(0);\n\t\t}else{\n\t\t\tif(y == 0) y = null;\n\t\t\tx1_1.push(0);\n\t\t\tx1_2.push(y);\n\t\t}\n\t}\n\t\n\tvar x2 = new Array();\n\tvar x3 = new Array();\n\tvar x4 = new Array();\n\tvar x5 = new Array();\n\tvar x6 = new Array();\n\tvar x7 = new Array();\n\tvar x8 = new Array();\n\tvar x9 = new Array();\n\tvar x10 = new Array();\n\tvar x11 = new Array();\n\tvar x12 = new Array();\n\tvar x13 = new Array();\n\t\n\t\n\tfor (var z in xx2){\n\t\t\n\t\tvar y2 = xx2[z];\n\t\tvar y3 = xx3[z];\n\t\tvar y4 = xx4[z];\n\t\tvar y5 = xx5[z];\n\t\tvar y6 = xx6[z];\n\t\tvar y7 = xx7[z];\n\t\tvar y8 = xx8[z];\n\t\tvar y9 = xx9[z];\n\t\tvar y10 = xx10[z];\n\t\tvar y11 = xx11[z];\n\t\tvar y12 = xx12[z];\n\t\tvar y13 = xx13[z];\n\t\n\t\tif(y2 == 0) y2 = null;\n\t\tif(y3 == 0) y3 = null;\n\t\tif(y4 == 0) y4 = null;\n\t\tif(y5 == 0) y5 = null;\n\t\tif(y6 == 0) y6 = null;\n\t\tif(y7 == 0) y7 = null;\n\t\tif(y8 == 0) y8 = null;\n\t\tif(y9 == 0) y9 = null;\n\t\tif(y10 == 0) y10 = null;\n\t\tif(y11 == 0) y11 = null;\n\t\tif(y12 == 0) y12 = null;\n\t\tif(y13 == 0) y13 = null;\n\n\t\tx2.push(y2);\n\t\tx3.push(y3);\n\t\tx4.push(y4);\n\t\tx5.push(y5);\n\t\tx6.push(y6);\n\t\tx7.push(y7);\n\t\tx8.push(y8);\n\t\tx9.push(y9);\n\t\tx10.push(y10);\n\t\tx11.push(y11);\n\t\tx12.push(y12);\n\t\tx13.push(y13);\n\t}\n\t\n\tvar todayTime = '';\n\tvar zz = '';\n\tvar dateType = {\n\t\t'xDateFormat' : '시간:'+'%H:%M'\n\t}\n\t\n\tHighcharts.setOptions({\n\t    lang: {\n\tthousandsSep: ','\n\t    }\n\t})\n\t\n\tvar option = {\n\t\t\t\n\t\t\ttitle : {\n\t\t\t\ttext: ''\n\t\t\t},\n\t\t\tsubtitle : {\n\t\t\t\t//text: '날짜' \n\t\t\t},\n\t\t\txAxis : {\n\t\t\t\ttype: 'datetime',\n\t\t\t\tlabels:{\n\t\t\t\t\tformatter: function(){\n\t\t\t\t\t\tvar ret = Highcharts.dateFormat('%H', this.value);\n\t\t\t\t\t\tvar cnt = 0;\n\t\t\t\t\t\tif(this.value == 86400000){\n\t\t\t\t\t\t\tret = 24;\n\t\t\t\t\t\t}\n\t\t\t\t\t\tif(ret == '01' || ret == '02' \n\t\t\t\t\t\t\t\t|| ret == '04' || ret == '05' \n\t\t\t\t\t\t\t\t|| ret == '07' || ret == '08' \n\t\t\t\t\t\t\t\t|| ret == '10' || ret == '11' \n\t\t\t\t\t\t\t\t|| ret == '13' || ret == '14' \n\t\t\t\t\t\t\t\t|| ret == '16' || ret == '17' \n\t\t\t\t\t\t\t\t|| ret == '19' || ret == '20' \n\t\t\t\t\t\t\t\t|| ret == '22' || ret == '23')ret = '';  \n\t\t\t\t\t\treturn ret;\n\t\t\t\t\t}\n\t\t\t\t},\n\t\t\t\t\n\t\t\t\ttickInterval : 3600000*1, \n\t\t\t\ttitle: {\n\t\t\t\t\ttext:'시간',\n\t\t\t\t\tstyle: {\n\t\t\t\t\t\tfontSize : '12px', \n\t\t\t\t\t\tfontWeight : 'bold',\n\t\t\t\t\t\tcolor : 'blue'\n\t\t\t\t\t}\n\t\t\t\t},\n\t\t\t\tgridLineWidth: 1\n\t\t\t\t\n\t\t\t},\n\t\t\tyAxis: {\n\t\t\t\ttitle: {\n\t\t\t\t\ttext:'',\n\t\t\t\t\tstyle: {\n\t\t\t\t\t\tfontSize : '13px', \n\t\t\t\t\t\tcolor : 'blue'\n\t\t\t\t\t}\n\t\t\t\t},\n\t\t\t\tlabels:{\n\t\t\t\t\tformat:'{value:,.0f}'\n\t\t\t\t}\n\t\t\t\t//,min:0\n\t\t\t\t,minPadding:0\n\t\t\t\t,startOnTick:true\n\t\t\t\t,minRange:0.5\n\t\t\t},\n\t\t\tcolors: [\n\t\t\t\t'red','green'\n\t\t\t],\n\t\t\t\n\t\t\ttooltip: {\n\t\t\t\tformatter:function(){\n\t\t\t\t\tvar hr ='';\n\t\t\t\t\tvar min = '';\n\t\t\t\t\tvar seriesName = '';\n\t\t\t\t\tvar week = ['(일)','(월)','(화)','(수)','(목)','(금)','(토)',];\n\t\t\t\t\t\n\t\t\t\t\tvar currentPoint = this;\n\t\t\t\t\tvar currentSeries = currentPoint.series;\n\t\t\t\t\tvar chart = currentSeries.chart;\n\t\t\t\t\tvar stackName = this.series.userOptions.stack;\n\t\t\t\t\tvar stackSeriesVal1 = '';\n\t\t\t\t\tvar stackSeriesVal2 = '';\n\t\t\t\t\tvar stackSeriesVal3 = '';\n\t\t\t\t\tvar stackSeriesVal4 = '';\n\t\t\t\t\tvar stackSeriesVal5 = '';\n\t\t\t\t\tvar stackSeriesVal6 = '';\n\t\t\t\t\tvar stackSeriesVal8 = '';\n\t\t\t\t\tvar stackSeriesVal9 = '';\n\t\t\t\t\tvar stackSeriesVal10 = '';\n\t\t\t\t\tvar stackSeriesVal11 = '';\n\t\t\t\t\tvar stackSeriesVal12 = '';\n\t\t\t\t\tvar stackSeriesVal13 = '';\n\t\t\t\t\t\n\t\t\t\t\tchart.series.forEach(function(series){\n\t\t\t\t\t\tseries.points.forEach(function(point){\n\t\t\t\t\t\t\tif(currentSeries.userOptions.stack === series.userOptions.stack && currentPoint.key === point.category){\n\t\t\t\t\t\t\t\tseriesName = x7[point.index].toString();\n\t\t\t\t\t\t\t\tseriesNameDash = seriesName.substr(0,4)+'-'+seriesName.substr(4,2)+'-'+seriesName.substr(6,2);\n\t\t\t\t\t\t\t\thr = seriesName.substr(8,2);\n\t\t\t\t\t\t\t\tmin = seriesName.substr(10,2);\n\t\t\t\t\t\t\t\thr = lPad(hr,2,'0');\n\t\t\t\t\t\t\t\tmin = lPad(min,2,'0');\n\t\t\t\t\t\t\t\tvar dayOfWeek = week[new Date(seriesNameDash).getDay()];\n\t\t\t\t\t\t\t\tseriesName = seriesName.substr(0,4)+'.'+seriesName.substr(4,2)+'.'+seriesName.substr(6,2)+dayOfWeek;\n\t\t\t\t\t\t\t\tstackSeriesVal1 = x1[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal2 = x2[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal3 = x3[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal4 = x4[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal5 = x5[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal6 = x6[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal8 = x8[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal9 = x9[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal10 = x10[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal11 = x11[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal12 = x12[point.index];\n\t\t\t\t\t\t\t\tstackSeriesVal13 = x13[point.index];\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t})\n\t\t\t\t\t});\n\t\t\t\t\t\n\t\t\t\t\tvar stackSeriesVal1_1 = 0;\n\t\t\t\t\t\n\t\t\t\t\tif(stackSeriesVal1 > 0){\n\t\t\t\t\t\tstackSeriesVal1_1 = stackSeriesVal1;\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\tvar totStackSeriesVal = stackSeriesVal1+stackSeriesVal2+stackSeriesVal3+stackSeriesVal4+stackSeriesVal5+stackSeriesVal6+stackSeriesVal8+stackSeriesVal9+stackSeriesVal10+stackSeriesVal13;\n\t\t\t\t\tvar totStackSeriesValTot = totStackSeriesVal+stackSeriesVal11+stackSeriesVal12;\n\t\t\t\t\tvar totStackSeriesValSun = stackSeriesVal8+(stackSeriesVal11+0)+(stackSeriesVal12+0);\n\t\t\t\t\tvar totStackSeriesValSunPer = ((totStackSeriesValSun/totStackSeriesValTot)*100).toFixed(1);\n\t\t\t\t\t\n\t\t\t\t\tif(totStackSeriesVal == 0){\n\t\t\t\t\t\treturn false;\n\t\t\t\t\t}\n\t\t\t\t\t\n\t\t\t\t\tvar s =  seriesName+' '+hr+':'+min\n\t\t\t\t\t+'<br><span style=\"visibility:hidden\">KPX</span>'\n\t\t\t\t\t+'<br>태양광(BTM,추정) : '+ commaToString((stackSeriesVal12+0).toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>태양광(PPA,추정) : '+ commaToString((stackSeriesVal11+0).toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>태양광(전력시장) : '+ commaToString((stackSeriesVal8+0).toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>태양광(합계) : '+ commaToString(totStackSeriesValSun.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br><span style=\"visibility:hidden\">태양광(합계) : </span>'+ '(총수요 대비 '+totStackSeriesValSunPer + '%)'\n\t\t\t\t\t+'<br><span style=\"visibility:hidden\">KPX</span>'\n\t\t\t\t\t+'<br>양<span style=\"visibility:hidden\">가</span>수 : '+ commaToString(stackSeriesVal1.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>수<span style=\"visibility:hidden\">가</span>력 : '+ commaToString(stackSeriesVal9.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>가<span style=\"visibility:hidden\">가</span>스 : '+ commaToString(stackSeriesVal2.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>풍<span style=\"visibility:hidden\">가</span>력 : '+ commaToString(stackSeriesVal13.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>신재생 : '+ commaToString(stackSeriesVal3.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>유<span style=\"visibility:hidden\">가</span>류 : '+ commaToString(stackSeriesVal4.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>국내탄 : '+ commaToString(stackSeriesVal10.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>유연탄 : '+ commaToString(stackSeriesVal5.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>원자력 : '+ commaToString(stackSeriesVal6.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br><span style=\"visibility:hidden\">KPX</span>'\n\t\t\t\t\t+'<br>합<span style=\"visibility:hidden\">가</span>계(전력시장) : '+ commaToString(totStackSeriesVal.toFixed(0)) + 'MW'\n\t\t\t\t\t+'<br>합<span style=\"visibility:hidden\">가</span>계(총수요) : '+ commaToString(totStackSeriesValTot.toFixed(0)) + 'MW'\n\t\t\t\t\t;\n\t\t\t\t\t\n\t\t\t\t\treturn s;\n\t\t\t\t}\t\t\t\t\t\t\n\t\t\t},\n\t\t\tchart: {\n\t\t\t\tdefaultSeriesType: 'area'\n\t\t\t\t//,backgroundColor : 'rgba(255,139,0,0.85)'\n\t\t\t},\n\t\t\tplotOptions: {\n\t\t\t\tarea: {\n\t\t\t\t\tstacking : 'normal'\n\t\t\t\t\t,pointInterval: 300000\n\t\t\t\t\t,softThreshold:false\n\t\t\t\t\t,connectNulls : true\n\t\t\t\t\t,lineWidth : 0\n\t\t\t\t}\n\t\t\t},\n\t\t\tlegend: {\n\t\t\t\t                                                                                  \n\t\t\t},\n\t\t\tseries : null\n\t\t\t\n\t}\n\t\n\t$('#chart2').highcharts($.extend(true, option,{\n\t\t\n\t\tseries: [\n\t\t{\n\t\t\t\"name\": \"양수펌핑\",\n\t\t\t\"data\": x1_1, \n\t\t\t\"color\" : 'rgba(215,215,215,0.85)',\n\t\t\t'zIndex' : 1,\n\t\t\t'legendIndex' : 5\n\t\t},{\n\t\t\t\"name\": \"태양광(BTM,추정)\",\n\t\t\t\"data\": x12,\n\t\t\t\"color\" : 'rgba(247,219,180,0.85)',\n\t\t\t'legendIndex' : 1\n\t\t},{\n\t\t\t\"name\": \"태양광(PPA,추정)\",\n\t\t\t\"data\": x11,\n\t\t\t\"color\" : 'rgba(251,183,191,0.85)',\n\t\t\t'legendIndex' : 2\n\t\t},{\n\t\t\t\"name\": \"태양광(전력시장)\",\n\t\t\t\"data\": x8,\n\t\t\t\"color\" : 'rgba(196,0,20,0.85)',\n\t\t\t'legendIndex' : 3\n\t\t},{\n\t\t\t\"name\": \"양수발전\",\n\t\t\t\"data\": x1_2, \n\t\t\t\"color\" : 'rgba(0,155,209,0.85)',\n\t\t\t'legendIndex' : 4\n\t\t},{\n\t\t\t\"name\": \"수력\",\n\t\t\t\"data\": x9, \n\t\t\t\"color\" : 'rgba(88,250,250,0.85)',\n\t\t\t'legendIndex' : 6\n\t\t},{\n\t\t\t\"name\": \"가스\",\n\t\t\t\"data\": x2,\n\t\t\t\"color\" : 'rgba(255,246,0,0.85)',\n\t\t\t'legendIndex' : 7\n\t\t},{\n\t\t\t\"name\": \"풍력\",\n\t\t\t\"data\": x13,\n\t\t\t\"color\" : 'rgba(100,242,121,0.85)',\n\t\t\t'legendIndex' : 8\n\t\t},{\n\t\t\t\"name\": \"신재생\",\n\t\t\t\"data\": x3,\n\t\t\t\"color\" : 'rgba(120,194,82,0.85)',\n\t\t\t'legendIndex' : 9\n\t\t},{\n\t\t\t\"name\": \"유류\",\n\t\t\t\"data\": x4,\n\t\t\t \"color\" : 'rgba(215,215,215,0.85)',\n\t\t\t'legendIndex' : 10\n\t\t},{\n\t\t\t\"name\": \"국내탄\",\n\t\t\t\"data\": x10,\n\t\t\t\"color\" : 'rgba(57,57,57,0.85)',\n\t\t\t'legendIndex' : 11\n\t\t},{\n\t\t\t\"name\": \"유연탄\",\n\t\t\t\"data\": x5,\n\t\t\t\"color\" : 'rgba(163,115,81,0.85)',\n\t\t\t'legendIndex' : 12\n\t\t},{\n\t\t\t\"name\": \"원자력\",\n\t\t\t\"data\": x6,\n\t\t\t\"color\" : 'rgba(255,139,0,0.85)',\n\t\t\t'legendIndex' : 13\n\t\t}]\n\t}));\n}\n\t\n\nfunction commaToString(par){\n\treturn par.toString().replace(/\\B(?=(\\d{3})+(?!\\d))/g,\",\");\n}\n</script>\t\n<div class=\"conTableGroup\">\n\t<span class=\"grape_top\">MW</span>\n\t<div id=\"chart2\" class=\"grape2\" style=\"height:520px;\"> \n\t\t그래프 영역 <br />640 이상사이즈 100%*306 <br />640 이하사이즈 100%*153\n\t</div>\n</div>\n<div class=\"btn_area graph_btn02_open\">\n\t<a href=\"javascript:void(0);\" class=\"btn_basic\">표로 보기</a>\n</div>\n<div class=\"conTableGroup graph_table02 IR\">\n\t<div class=\"btn_area graph_btn02_close DisplayNone\">\n\t\t<a href=\"javascript:void(0);\" class=\"btn_basic\">표로보기 닫기</a>\n\t</div>\n\t<div>\n\t\t<div style=\"text-align: right\">단위:MW</div>\n\t\t<table class=\"conTable tdCenter\">\n\t\t\t<caption>발전원별실시간 전력수급현황 차트 정보를 제공합니다.</caption>\n\t\t\t<thead>\n\t\t\t\t<tr>\n\t\t\t\t\t<th>일시<br>(2025년 01월 05일)</th>\n\t\t\t\t\t<th>태양광<br>(BTM,추정)</th>\n\t\t\t\t\t<th>태양광<br>(PPA,추정)</th>\n\t\t\t\t\t<th>태양광<br>(전력시장)</th>\n\t\t\t\t\t<th>양수</th>\n\t\t\t\t\t<th>수력</th>\n\t\t\t\t\t<th>가스</th>\n\t\t\t\t\t<th>풍력</th>\n\t\t\t\t\t<th>신재생</th>\n\t\t\t\t\t<th>유류</th>\n\t\t\t\t\t<th>국내탄</th>\n\t\t\t\t\t<th>유연탄</th>\n\t\t\t\t\t<th>원자력</th>\n\t\t\t\t</tr>\n\t\t\t</thead>\n\t\t\t<tbody>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,169</td> \n\t\t\t\t\t\t<td>38</td>\n\t\t\t\t\t\t<td>21,242</td>\n\t\t\t\t\t\t<td>441</td>\n\t\t\t\t\t\t<td>3,212</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>13,998</td>\n\t\t\t\t\t\t<td>24,132</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,166</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>20,874</td>\n\t\t\t\t\t\t<td>470</td>\n\t\t\t\t\t\t<td>3,215</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>13,997</td>\n\t\t\t\t\t\t<td>24,183</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,164</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>20,567</td>\n\t\t\t\t\t\t<td>462</td>\n\t\t\t\t\t\t<td>3,198</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,076</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,039</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>20,524</td>\n\t\t\t\t\t\t<td>467</td>\n\t\t\t\t\t\t<td>3,182</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>13,960</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>693</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>20,407</td>\n\t\t\t\t\t\t<td>479</td>\n\t\t\t\t\t\t<td>3,174</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,135</td>\n\t\t\t\t\t\t<td>24,189</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>692</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>20,070</td>\n\t\t\t\t\t\t<td>464</td>\n\t\t\t\t\t\t<td>3,171</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,136</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>694</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>19,836</td>\n\t\t\t\t\t\t<td>462</td>\n\t\t\t\t\t\t<td>3,180</td>\n\t\t\t\t\t\t<td>361</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,147</td>\n\t\t\t\t\t\t<td>24,200</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>400</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>19,897</td>\n\t\t\t\t\t\t<td>469</td>\n\t\t\t\t\t\t<td>3,163</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,155</td>\n\t\t\t\t\t\t<td>24,151</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>399</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>19,804</td>\n\t\t\t\t\t\t<td>462</td>\n\t\t\t\t\t\t<td>3,166</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,205</td>\n\t\t\t\t\t\t<td>24,147</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>398</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>19,471</td>\n\t\t\t\t\t\t<td>465</td>\n\t\t\t\t\t\t<td>3,164</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,166</td>\n\t\t\t\t\t\t<td>24,121</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>397</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>19,210</td>\n\t\t\t\t\t\t<td>461</td>\n\t\t\t\t\t\t<td>3,172</td>\n\t\t\t\t\t\t<td>361</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,159</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>00시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>395</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>18,671</td>\n\t\t\t\t\t\t<td>454</td>\n\t\t\t\t\t\t<td>3,178</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,243</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>243</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>18,609</td>\n\t\t\t\t\t\t<td>456</td>\n\t\t\t\t\t\t<td>3,175</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,279</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>18,662</td>\n\t\t\t\t\t\t<td>450</td>\n\t\t\t\t\t\t<td>3,173</td>\n\t\t\t\t\t\t<td>361</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,282</td>\n\t\t\t\t\t\t<td>24,156</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-14</td> \n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>18,466</td>\n\t\t\t\t\t\t<td>466</td>\n\t\t\t\t\t\t<td>3,176</td>\n\t\t\t\t\t\t<td>361</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,303</td>\n\t\t\t\t\t\t<td>24,163</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-263</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,171</td>\n\t\t\t\t\t\t<td>467</td>\n\t\t\t\t\t\t<td>3,172</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,422</td>\n\t\t\t\t\t\t<td>24,167</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-320</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>17,904</td>\n\t\t\t\t\t\t<td>474</td>\n\t\t\t\t\t\t<td>3,170</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,458</td>\n\t\t\t\t\t\t<td>24,151</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-750</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,198</td>\n\t\t\t\t\t\t<td>469</td>\n\t\t\t\t\t\t<td>3,162</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,499</td>\n\t\t\t\t\t\t<td>24,178</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-1,122</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,476</td>\n\t\t\t\t\t\t<td>464</td>\n\t\t\t\t\t\t<td>3,170</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,566</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-1,445</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,811</td>\n\t\t\t\t\t\t<td>462</td>\n\t\t\t\t\t\t<td>3,164</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,484</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-1,765</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>19,150</td>\n\t\t\t\t\t\t<td>448</td>\n\t\t\t\t\t\t<td>3,170</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,584</td>\n\t\t\t\t\t\t<td>24,180</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-1,773</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>19,087</td>\n\t\t\t\t\t\t<td>432</td>\n\t\t\t\t\t\t<td>3,176</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,501</td>\n\t\t\t\t\t\t<td>24,140</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-1,769</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,790</td>\n\t\t\t\t\t\t<td>426</td>\n\t\t\t\t\t\t<td>3,177</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,456</td>\n\t\t\t\t\t\t<td>24,150</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>01시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-1,952</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,719</td>\n\t\t\t\t\t\t<td>432</td>\n\t\t\t\t\t\t<td>3,183</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,540</td>\n\t\t\t\t\t\t<td>24,186</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,105</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,863</td>\n\t\t\t\t\t\t<td>430</td>\n\t\t\t\t\t\t<td>3,188</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,500</td>\n\t\t\t\t\t\t<td>24,173</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,139</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,588</td>\n\t\t\t\t\t\t<td>436</td>\n\t\t\t\t\t\t<td>3,187</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,548</td>\n\t\t\t\t\t\t<td>24,169</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,363</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,775</td>\n\t\t\t\t\t\t<td>440</td>\n\t\t\t\t\t\t<td>3,187</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,543</td>\n\t\t\t\t\t\t<td>24,147</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,363</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,670</td>\n\t\t\t\t\t\t<td>423</td>\n\t\t\t\t\t\t<td>3,186</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,592</td>\n\t\t\t\t\t\t<td>24,177</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,363</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,336</td>\n\t\t\t\t\t\t<td>408</td>\n\t\t\t\t\t\t<td>3,186</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,490</td>\n\t\t\t\t\t\t<td>24,167</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,367</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,302</td>\n\t\t\t\t\t\t<td>415</td>\n\t\t\t\t\t\t<td>3,183</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,595</td>\n\t\t\t\t\t\t<td>24,172</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,796</td> \n\t\t\t\t\t\t<td>40</td>\n\t\t\t\t\t\t<td>18,605</td>\n\t\t\t\t\t\t<td>417</td>\n\t\t\t\t\t\t<td>3,184</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,616</td>\n\t\t\t\t\t\t<td>24,138</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,799</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,450</td>\n\t\t\t\t\t\t<td>398</td>\n\t\t\t\t\t\t<td>3,190</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,503</td>\n\t\t\t\t\t\t<td>24,179</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,789</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,322</td>\n\t\t\t\t\t\t<td>405</td>\n\t\t\t\t\t\t<td>3,192</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,597</td>\n\t\t\t\t\t\t<td>24,177</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,790</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,175</td>\n\t\t\t\t\t\t<td>411</td>\n\t\t\t\t\t\t<td>3,195</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,504</td>\n\t\t\t\t\t\t<td>24,151</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,793</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>17,938</td>\n\t\t\t\t\t\t<td>427</td>\n\t\t\t\t\t\t<td>3,194</td>\n\t\t\t\t\t\t<td>321</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,503</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>02시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,785</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>17,935</td>\n\t\t\t\t\t\t<td>439</td>\n\t\t\t\t\t\t<td>3,194</td>\n\t\t\t\t\t\t<td>306</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,612</td>\n\t\t\t\t\t\t<td>24,134</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,794</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,006</td>\n\t\t\t\t\t\t<td>452</td>\n\t\t\t\t\t\t<td>3,192</td>\n\t\t\t\t\t\t<td>280</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,512</td>\n\t\t\t\t\t\t<td>24,212</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,790</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,006</td>\n\t\t\t\t\t\t<td>460</td>\n\t\t\t\t\t\t<td>3,189</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>195</td>\n\t\t\t\t\t\t<td>14,523</td>\n\t\t\t\t\t\t<td>24,149</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,791</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,003</td>\n\t\t\t\t\t\t<td>462</td>\n\t\t\t\t\t\t<td>3,194</td>\n\t\t\t\t\t\t<td>288</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,390</td>\n\t\t\t\t\t\t<td>24,151</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,060</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>17,955</td>\n\t\t\t\t\t\t<td>467</td>\n\t\t\t\t\t\t<td>3,203</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,635</td>\n\t\t\t\t\t\t<td>24,145</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,100</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,175</td>\n\t\t\t\t\t\t<td>465</td>\n\t\t\t\t\t\t<td>3,196</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,518</td>\n\t\t\t\t\t\t<td>24,197</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,099</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,190</td>\n\t\t\t\t\t\t<td>479</td>\n\t\t\t\t\t\t<td>3,199</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,531</td>\n\t\t\t\t\t\t<td>24,171</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,101</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,054</td>\n\t\t\t\t\t\t<td>494</td>\n\t\t\t\t\t\t<td>3,197</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,380</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,093</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>17,773</td>\n\t\t\t\t\t\t<td>492</td>\n\t\t\t\t\t\t<td>3,203</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,503</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,084</td> \n\t\t\t\t\t\t<td>40</td>\n\t\t\t\t\t\t<td>17,861</td>\n\t\t\t\t\t\t<td>488</td>\n\t\t\t\t\t\t<td>3,208</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,630</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,094</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>17,964</td>\n\t\t\t\t\t\t<td>490</td>\n\t\t\t\t\t\t<td>3,212</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,534</td>\n\t\t\t\t\t\t<td>24,146</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,098</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>18,029</td>\n\t\t\t\t\t\t<td>492</td>\n\t\t\t\t\t\t<td>3,213</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,445</td>\n\t\t\t\t\t\t<td>24,178</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>03시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,092</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>17,917</td>\n\t\t\t\t\t\t<td>497</td>\n\t\t\t\t\t\t<td>3,215</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,511</td>\n\t\t\t\t\t\t<td>24,162</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,088</td> \n\t\t\t\t\t\t<td>47</td>\n\t\t\t\t\t\t<td>17,857</td>\n\t\t\t\t\t\t<td>511</td>\n\t\t\t\t\t\t<td>3,211</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,558</td>\n\t\t\t\t\t\t<td>24,191</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,122</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,945</td>\n\t\t\t\t\t\t<td>512</td>\n\t\t\t\t\t\t<td>3,214</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,539</td>\n\t\t\t\t\t\t<td>24,154</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,423</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>18,350</td>\n\t\t\t\t\t\t<td>514</td>\n\t\t\t\t\t\t<td>3,213</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,532</td>\n\t\t\t\t\t\t<td>24,182</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,420</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>18,162</td>\n\t\t\t\t\t\t<td>507</td>\n\t\t\t\t\t\t<td>3,213</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,506</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,417</td> \n\t\t\t\t\t\t<td>50</td>\n\t\t\t\t\t\t<td>18,190</td>\n\t\t\t\t\t\t<td>502</td>\n\t\t\t\t\t\t<td>3,203</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,506</td>\n\t\t\t\t\t\t<td>24,172</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,419</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>18,098</td>\n\t\t\t\t\t\t<td>488</td>\n\t\t\t\t\t\t<td>3,204</td>\n\t\t\t\t\t\t<td>289</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,448</td>\n\t\t\t\t\t\t<td>24,184</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,410</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>18,302</td>\n\t\t\t\t\t\t<td>490</td>\n\t\t\t\t\t\t<td>3,201</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,524</td>\n\t\t\t\t\t\t<td>24,191</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,413</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>18,303</td>\n\t\t\t\t\t\t<td>484</td>\n\t\t\t\t\t\t<td>3,196</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,491</td>\n\t\t\t\t\t\t<td>24,149</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,411</td> \n\t\t\t\t\t\t<td>50</td>\n\t\t\t\t\t\t<td>18,398</td>\n\t\t\t\t\t\t<td>479</td>\n\t\t\t\t\t\t<td>3,196</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,530</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,413</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>18,261</td>\n\t\t\t\t\t\t<td>489</td>\n\t\t\t\t\t\t<td>3,198</td>\n\t\t\t\t\t\t<td>289</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,448</td>\n\t\t\t\t\t\t<td>24,186</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,409</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>18,396</td>\n\t\t\t\t\t\t<td>495</td>\n\t\t\t\t\t\t<td>3,201</td>\n\t\t\t\t\t\t<td>289</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,505</td>\n\t\t\t\t\t\t<td>24,157</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>04시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-3,413</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>18,658</td>\n\t\t\t\t\t\t<td>493</td>\n\t\t\t\t\t\t<td>3,195</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,441</td>\n\t\t\t\t\t\t<td>24,184</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,984</td> \n\t\t\t\t\t\t<td>50</td>\n\t\t\t\t\t\t<td>18,412</td>\n\t\t\t\t\t\t<td>505</td>\n\t\t\t\t\t\t<td>3,195</td>\n\t\t\t\t\t\t<td>289</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,417</td>\n\t\t\t\t\t\t<td>24,175</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,973</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>18,393</td>\n\t\t\t\t\t\t<td>497</td>\n\t\t\t\t\t\t<td>3,193</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,496</td>\n\t\t\t\t\t\t<td>24,145</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,978</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>18,322</td>\n\t\t\t\t\t\t<td>503</td>\n\t\t\t\t\t\t<td>3,191</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,430</td>\n\t\t\t\t\t\t<td>24,154</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,970</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>18,274</td>\n\t\t\t\t\t\t<td>497</td>\n\t\t\t\t\t\t<td>3,201</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,579</td>\n\t\t\t\t\t\t<td>24,167</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,663</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>18,086</td>\n\t\t\t\t\t\t<td>470</td>\n\t\t\t\t\t\t<td>3,201</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,379</td>\n\t\t\t\t\t\t<td>24,186</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,336</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>17,675</td>\n\t\t\t\t\t\t<td>470</td>\n\t\t\t\t\t\t<td>3,209</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,387</td>\n\t\t\t\t\t\t<td>24,149</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,076</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,514</td>\n\t\t\t\t\t\t<td>457</td>\n\t\t\t\t\t\t<td>3,201</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,436</td>\n\t\t\t\t\t\t<td>24,199</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-2,074</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,563</td>\n\t\t\t\t\t\t<td>438</td>\n\t\t\t\t\t\t<td>3,262</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,581</td>\n\t\t\t\t\t\t<td>24,160</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-1,766</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>17,315</td>\n\t\t\t\t\t\t<td>435</td>\n\t\t\t\t\t\t<td>3,293</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,579</td>\n\t\t\t\t\t\t<td>24,153</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-1,174</td> \n\t\t\t\t\t\t<td>50</td>\n\t\t\t\t\t\t<td>17,072</td>\n\t\t\t\t\t\t<td>422</td>\n\t\t\t\t\t\t<td>3,299</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,477</td>\n\t\t\t\t\t\t<td>24,150</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-1,136</td> \n\t\t\t\t\t\t<td>50</td>\n\t\t\t\t\t\t<td>17,269</td>\n\t\t\t\t\t\t<td>413</td>\n\t\t\t\t\t\t<td>3,301</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,486</td>\n\t\t\t\t\t\t<td>24,174</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>05시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>-639</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>16,730</td>\n\t\t\t\t\t\t<td>396</td>\n\t\t\t\t\t\t<td>3,305</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,464</td>\n\t\t\t\t\t\t<td>24,167</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 00분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-640</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>16,678</td>\n\t\t\t\t\t\t<td>383</td>\n\t\t\t\t\t\t<td>3,315</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,416</td>\n\t\t\t\t\t\t<td>24,176</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 05분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-639</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>16,835</td>\n\t\t\t\t\t\t<td>377</td>\n\t\t\t\t\t\t<td>3,325</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,585</td>\n\t\t\t\t\t\t<td>24,169</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 10분</td>\n\t\t\t\t\t\t<td>4</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-639</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>16,870</td>\n\t\t\t\t\t\t<td>371</td>\n\t\t\t\t\t\t<td>3,328</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,494</td>\n\t\t\t\t\t\t<td>24,193</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 15분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-381</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>16,841</td>\n\t\t\t\t\t\t<td>400</td>\n\t\t\t\t\t\t<td>3,331</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,451</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 20분</td>\n\t\t\t\t\t\t<td>4</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-381</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>16,759</td>\n\t\t\t\t\t\t<td>394</td>\n\t\t\t\t\t\t<td>3,328</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,481</td>\n\t\t\t\t\t\t<td>24,172</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 25분</td>\n\t\t\t\t\t\t<td>4</td>\n\t\t\t\t\t\t<td>10</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-380</td> \n\t\t\t\t\t\t<td>51</td>\n\t\t\t\t\t\t<td>16,946</td>\n\t\t\t\t\t\t<td>402</td>\n\t\t\t\t\t\t<td>3,333</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>195</td>\n\t\t\t\t\t\t<td>14,485</td>\n\t\t\t\t\t\t<td>24,175</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 30분</td>\n\t\t\t\t\t\t<td>4</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-381</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>16,965</td>\n\t\t\t\t\t\t<td>400</td>\n\t\t\t\t\t\t<td>3,336</td>\n\t\t\t\t\t\t<td>289</td>\n\t\t\t\t\t\t<td>195</td>\n\t\t\t\t\t\t<td>14,399</td>\n\t\t\t\t\t\t<td>24,184</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 35분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>-381</td> \n\t\t\t\t\t\t<td>50</td>\n\t\t\t\t\t\t<td>17,220</td>\n\t\t\t\t\t\t<td>398</td>\n\t\t\t\t\t\t<td>3,332</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>195</td>\n\t\t\t\t\t\t<td>14,476</td>\n\t\t\t\t\t\t<td>24,168</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 40분</td>\n\t\t\t\t\t\t<td>4</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-380</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>17,165</td>\n\t\t\t\t\t\t<td>398</td>\n\t\t\t\t\t\t<td>3,339</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,534</td>\n\t\t\t\t\t\t<td>24,157</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 45분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-380</td> \n\t\t\t\t\t\t<td>50</td>\n\t\t\t\t\t\t<td>17,263</td>\n\t\t\t\t\t\t<td>403</td>\n\t\t\t\t\t\t<td>3,350</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>195</td>\n\t\t\t\t\t\t<td>14,578</td>\n\t\t\t\t\t\t<td>24,139</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 50분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-381</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,302</td>\n\t\t\t\t\t\t<td>410</td>\n\t\t\t\t\t\t<td>3,345</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,409</td>\n\t\t\t\t\t\t<td>24,175</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>06시 55분</td>\n\t\t\t\t\t\t<td>4</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>-379</td> \n\t\t\t\t\t\t<td>50</td>\n\t\t\t\t\t\t<td>17,106</td>\n\t\t\t\t\t\t<td>412</td>\n\t\t\t\t\t\t<td>3,352</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,536</td>\n\t\t\t\t\t\t<td>24,154</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 00분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>5</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>17,126</td>\n\t\t\t\t\t\t<td>383</td>\n\t\t\t\t\t\t<td>3,352</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,489</td>\n\t\t\t\t\t\t<td>24,135</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 05분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,296</td>\n\t\t\t\t\t\t<td>373</td>\n\t\t\t\t\t\t<td>3,353</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,560</td>\n\t\t\t\t\t\t<td>24,141</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 10분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,600</td>\n\t\t\t\t\t\t<td>395</td>\n\t\t\t\t\t\t<td>3,357</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,645</td>\n\t\t\t\t\t\t<td>24,177</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 15분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,694</td>\n\t\t\t\t\t\t<td>401</td>\n\t\t\t\t\t\t<td>3,361</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>195</td>\n\t\t\t\t\t\t<td>14,462</td>\n\t\t\t\t\t\t<td>24,167</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 20분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>17,499</td>\n\t\t\t\t\t\t<td>422</td>\n\t\t\t\t\t\t<td>3,359</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>196</td>\n\t\t\t\t\t\t<td>14,393</td>\n\t\t\t\t\t\t<td>24,150</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 25분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,480</td>\n\t\t\t\t\t\t<td>424</td>\n\t\t\t\t\t\t<td>3,360</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>196</td>\n\t\t\t\t\t\t<td>14,549</td>\n\t\t\t\t\t\t<td>24,151</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 30분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,286</td>\n\t\t\t\t\t\t<td>424</td>\n\t\t\t\t\t\t<td>3,360</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>195</td>\n\t\t\t\t\t\t<td>14,505</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 35분</td>\n\t\t\t\t\t\t<td>4</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>17,477</td>\n\t\t\t\t\t\t<td>435</td>\n\t\t\t\t\t\t<td>3,356</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>195</td>\n\t\t\t\t\t\t<td>14,498</td>\n\t\t\t\t\t\t<td>24,149</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 40분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>48</td>\n\t\t\t\t\t\t<td>17,256</td>\n\t\t\t\t\t\t<td>447</td>\n\t\t\t\t\t\t<td>3,364</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>195</td>\n\t\t\t\t\t\t<td>14,341</td>\n\t\t\t\t\t\t<td>24,161</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 45분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,292</td>\n\t\t\t\t\t\t<td>453</td>\n\t\t\t\t\t\t<td>3,368</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,521</td>\n\t\t\t\t\t\t<td>24,181</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 50분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>49</td>\n\t\t\t\t\t\t<td>17,581</td>\n\t\t\t\t\t\t<td>463</td>\n\t\t\t\t\t\t<td>3,366</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,476</td>\n\t\t\t\t\t\t<td>24,172</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>07시 55분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>13</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>50</td>\n\t\t\t\t\t\t<td>17,853</td>\n\t\t\t\t\t\t<td>468</td>\n\t\t\t\t\t\t<td>3,361</td>\n\t\t\t\t\t\t<td>289</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,444</td>\n\t\t\t\t\t\t<td>24,173</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 00분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>13</td>\n\t\t\t\t\t\t<td>10</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>113</td>\n\t\t\t\t\t\t<td>18,016</td>\n\t\t\t\t\t\t<td>475</td>\n\t\t\t\t\t\t<td>3,364</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,571</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 05분</td>\n\t\t\t\t\t\t<td>6</td>\n\t\t\t\t\t\t<td>16</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>353</td>\n\t\t\t\t\t\t<td>17,810</td>\n\t\t\t\t\t\t<td>479</td>\n\t\t\t\t\t\t<td>3,362</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,474</td>\n\t\t\t\t\t\t<td>24,173</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 10분</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>22</td>\n\t\t\t\t\t\t<td>15</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>450</td>\n\t\t\t\t\t\t<td>17,544</td>\n\t\t\t\t\t\t<td>494</td>\n\t\t\t\t\t\t<td>3,356</td>\n\t\t\t\t\t\t<td>293</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,532</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 15분</td>\n\t\t\t\t\t\t<td>10</td>\n\t\t\t\t\t\t<td>28</td>\n\t\t\t\t\t\t<td>18</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>409</td>\n\t\t\t\t\t\t<td>17,798</td>\n\t\t\t\t\t\t<td>508</td>\n\t\t\t\t\t\t<td>3,354</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,608</td>\n\t\t\t\t\t\t<td>24,172</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 20분</td>\n\t\t\t\t\t\t<td>13</td>\n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>24</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>372</td>\n\t\t\t\t\t\t<td>17,830</td>\n\t\t\t\t\t\t<td>509</td>\n\t\t\t\t\t\t<td>3,362</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,552</td>\n\t\t\t\t\t\t<td>24,161</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 25분</td>\n\t\t\t\t\t\t<td>19</td>\n\t\t\t\t\t\t<td>57</td>\n\t\t\t\t\t\t<td>35</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>392</td>\n\t\t\t\t\t\t<td>18,016</td>\n\t\t\t\t\t\t<td>515</td>\n\t\t\t\t\t\t<td>3,357</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,486</td>\n\t\t\t\t\t\t<td>24,190</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 30분</td>\n\t\t\t\t\t\t<td>25</td>\n\t\t\t\t\t\t<td>77</td>\n\t\t\t\t\t\t<td>45</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>392</td>\n\t\t\t\t\t\t<td>18,245</td>\n\t\t\t\t\t\t<td>523</td>\n\t\t\t\t\t\t<td>3,355</td>\n\t\t\t\t\t\t<td>295</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,456</td>\n\t\t\t\t\t\t<td>24,174</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 35분</td>\n\t\t\t\t\t\t<td>33</td>\n\t\t\t\t\t\t<td>103</td>\n\t\t\t\t\t\t<td>60</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>393</td>\n\t\t\t\t\t\t<td>18,499</td>\n\t\t\t\t\t\t<td>535</td>\n\t\t\t\t\t\t<td>3,347</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,524</td>\n\t\t\t\t\t\t<td>24,182</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 40분</td>\n\t\t\t\t\t\t<td>45</td>\n\t\t\t\t\t\t<td>140</td>\n\t\t\t\t\t\t<td>82</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>419</td>\n\t\t\t\t\t\t<td>18,711</td>\n\t\t\t\t\t\t<td>527</td>\n\t\t\t\t\t\t<td>3,341</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,581</td>\n\t\t\t\t\t\t<td>24,128</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 45분</td>\n\t\t\t\t\t\t<td>54</td>\n\t\t\t\t\t\t<td>168</td>\n\t\t\t\t\t\t<td>97</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>404</td>\n\t\t\t\t\t\t<td>18,749</td>\n\t\t\t\t\t\t<td>549</td>\n\t\t\t\t\t\t<td>3,338</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,542</td>\n\t\t\t\t\t\t<td>24,168</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 50분</td>\n\t\t\t\t\t\t<td>67</td>\n\t\t\t\t\t\t<td>211</td>\n\t\t\t\t\t\t<td>121</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>403</td>\n\t\t\t\t\t\t<td>18,882</td>\n\t\t\t\t\t\t<td>592</td>\n\t\t\t\t\t\t<td>3,342</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,552</td>\n\t\t\t\t\t\t<td>24,173</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>08시 55분</td>\n\t\t\t\t\t\t<td>82</td>\n\t\t\t\t\t\t<td>263</td>\n\t\t\t\t\t\t<td>149</td>\n\t\t\t\t\t\t<td>-21</td> \n\t\t\t\t\t\t<td>401</td>\n\t\t\t\t\t\t<td>18,909</td>\n\t\t\t\t\t\t<td>570</td>\n\t\t\t\t\t\t<td>3,335</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,464</td>\n\t\t\t\t\t\t<td>24,162</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 00분</td>\n\t\t\t\t\t\t<td>101</td>\n\t\t\t\t\t\t<td>333</td>\n\t\t\t\t\t\t<td>182</td>\n\t\t\t\t\t\t<td>-33</td> \n\t\t\t\t\t\t<td>467</td>\n\t\t\t\t\t\t<td>18,982</td>\n\t\t\t\t\t\t<td>556</td>\n\t\t\t\t\t\t<td>3,333</td>\n\t\t\t\t\t\t<td>289</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,378</td>\n\t\t\t\t\t\t<td>24,156</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 05분</td>\n\t\t\t\t\t\t<td>118</td>\n\t\t\t\t\t\t<td>384</td>\n\t\t\t\t\t\t<td>213</td>\n\t\t\t\t\t\t<td>30</td> \n\t\t\t\t\t\t<td>511</td>\n\t\t\t\t\t\t<td>18,688</td>\n\t\t\t\t\t\t<td>568</td>\n\t\t\t\t\t\t<td>3,328</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,605</td>\n\t\t\t\t\t\t<td>24,140</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 10분</td>\n\t\t\t\t\t\t<td>133</td>\n\t\t\t\t\t\t<td>424</td>\n\t\t\t\t\t\t<td>239</td>\n\t\t\t\t\t\t<td>18</td> \n\t\t\t\t\t\t<td>536</td>\n\t\t\t\t\t\t<td>18,449</td>\n\t\t\t\t\t\t<td>568</td>\n\t\t\t\t\t\t<td>3,322</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,398</td>\n\t\t\t\t\t\t<td>24,175</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 15분</td>\n\t\t\t\t\t\t<td>161</td>\n\t\t\t\t\t\t<td>510</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>59</td> \n\t\t\t\t\t\t<td>554</td>\n\t\t\t\t\t\t<td>18,773</td>\n\t\t\t\t\t\t<td>568</td>\n\t\t\t\t\t\t<td>3,341</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,530</td>\n\t\t\t\t\t\t<td>24,136</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 20분</td>\n\t\t\t\t\t\t<td>168</td>\n\t\t\t\t\t\t<td>538</td>\n\t\t\t\t\t\t<td>304</td>\n\t\t\t\t\t\t<td>42</td> \n\t\t\t\t\t\t<td>545</td>\n\t\t\t\t\t\t<td>18,872</td>\n\t\t\t\t\t\t<td>590</td>\n\t\t\t\t\t\t<td>3,359</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,624</td>\n\t\t\t\t\t\t<td>24,184</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 25분</td>\n\t\t\t\t\t\t<td>175</td>\n\t\t\t\t\t\t<td>576</td>\n\t\t\t\t\t\t<td>317</td>\n\t\t\t\t\t\t<td>32</td> \n\t\t\t\t\t\t<td>549</td>\n\t\t\t\t\t\t<td>19,007</td>\n\t\t\t\t\t\t<td>594</td>\n\t\t\t\t\t\t<td>3,357</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,488</td>\n\t\t\t\t\t\t<td>24,182</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 30분</td>\n\t\t\t\t\t\t<td>197</td>\n\t\t\t\t\t\t<td>668</td>\n\t\t\t\t\t\t<td>356</td>\n\t\t\t\t\t\t<td>64</td> \n\t\t\t\t\t\t<td>569</td>\n\t\t\t\t\t\t<td>19,191</td>\n\t\t\t\t\t\t<td>574</td>\n\t\t\t\t\t\t<td>3,350</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,518</td>\n\t\t\t\t\t\t<td>24,162</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 35분</td>\n\t\t\t\t\t\t<td>217</td>\n\t\t\t\t\t\t<td>719</td>\n\t\t\t\t\t\t<td>392</td>\n\t\t\t\t\t\t<td>37</td> \n\t\t\t\t\t\t<td>558</td>\n\t\t\t\t\t\t<td>19,157</td>\n\t\t\t\t\t\t<td>572</td>\n\t\t\t\t\t\t<td>3,346</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,633</td>\n\t\t\t\t\t\t<td>24,165</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 40분</td>\n\t\t\t\t\t\t<td>237</td>\n\t\t\t\t\t\t<td>783</td>\n\t\t\t\t\t\t<td>428</td>\n\t\t\t\t\t\t<td>24</td> \n\t\t\t\t\t\t<td>549</td>\n\t\t\t\t\t\t<td>19,202</td>\n\t\t\t\t\t\t<td>554</td>\n\t\t\t\t\t\t<td>3,335</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,527</td>\n\t\t\t\t\t\t<td>24,159</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 45분</td>\n\t\t\t\t\t\t<td>267</td>\n\t\t\t\t\t\t<td>919</td>\n\t\t\t\t\t\t<td>483</td>\n\t\t\t\t\t\t<td>38</td> \n\t\t\t\t\t\t<td>545</td>\n\t\t\t\t\t\t<td>19,194</td>\n\t\t\t\t\t\t<td>564</td>\n\t\t\t\t\t\t<td>3,323</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,570</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 50분</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>989</td>\n\t\t\t\t\t\t<td>527</td>\n\t\t\t\t\t\t<td>37</td> \n\t\t\t\t\t\t<td>553</td>\n\t\t\t\t\t\t<td>19,200</td>\n\t\t\t\t\t\t<td>538</td>\n\t\t\t\t\t\t<td>3,314</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>189</td>\n\t\t\t\t\t\t<td>14,543</td>\n\t\t\t\t\t\t<td>24,181</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>09시 55분</td>\n\t\t\t\t\t\t<td>327</td>\n\t\t\t\t\t\t<td>1,202</td>\n\t\t\t\t\t\t<td>591</td>\n\t\t\t\t\t\t<td>31</td> \n\t\t\t\t\t\t<td>543</td>\n\t\t\t\t\t\t<td>19,239</td>\n\t\t\t\t\t\t<td>529</td>\n\t\t\t\t\t\t<td>3,304</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,410</td>\n\t\t\t\t\t\t<td>24,194</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 00분</td>\n\t\t\t\t\t\t<td>337</td>\n\t\t\t\t\t\t<td>1,275</td>\n\t\t\t\t\t\t<td>609</td>\n\t\t\t\t\t\t<td>161</td> \n\t\t\t\t\t\t<td>553</td>\n\t\t\t\t\t\t<td>19,327</td>\n\t\t\t\t\t\t<td>521</td>\n\t\t\t\t\t\t<td>3,299</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,422</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 05분</td>\n\t\t\t\t\t\t<td>360</td>\n\t\t\t\t\t\t<td>1,375</td>\n\t\t\t\t\t\t<td>650</td>\n\t\t\t\t\t\t<td>281</td> \n\t\t\t\t\t\t<td>555</td>\n\t\t\t\t\t\t<td>19,472</td>\n\t\t\t\t\t\t<td>512</td>\n\t\t\t\t\t\t<td>3,218</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,467</td>\n\t\t\t\t\t\t<td>24,149</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 10분</td>\n\t\t\t\t\t\t<td>391</td>\n\t\t\t\t\t\t<td>1,480</td>\n\t\t\t\t\t\t<td>706</td>\n\t\t\t\t\t\t<td>354</td> \n\t\t\t\t\t\t<td>547</td>\n\t\t\t\t\t\t<td>19,268</td>\n\t\t\t\t\t\t<td>509</td>\n\t\t\t\t\t\t<td>3,213</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,365</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 15분</td>\n\t\t\t\t\t\t<td>423</td>\n\t\t\t\t\t\t<td>1,608</td>\n\t\t\t\t\t\t<td>764</td>\n\t\t\t\t\t\t<td>362</td> \n\t\t\t\t\t\t<td>558</td>\n\t\t\t\t\t\t<td>19,050</td>\n\t\t\t\t\t\t<td>561</td>\n\t\t\t\t\t\t<td>3,204</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,398</td>\n\t\t\t\t\t\t<td>24,138</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 20분</td>\n\t\t\t\t\t\t<td>451</td>\n\t\t\t\t\t\t<td>1,690</td>\n\t\t\t\t\t\t<td>816</td>\n\t\t\t\t\t\t<td>374</td> \n\t\t\t\t\t\t<td>554</td>\n\t\t\t\t\t\t<td>19,182</td>\n\t\t\t\t\t\t<td>561</td>\n\t\t\t\t\t\t<td>3,199</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,620</td>\n\t\t\t\t\t\t<td>24,144</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 25분</td>\n\t\t\t\t\t\t<td>489</td>\n\t\t\t\t\t\t<td>1,871</td>\n\t\t\t\t\t\t<td>883</td>\n\t\t\t\t\t\t<td>352</td> \n\t\t\t\t\t\t<td>553</td>\n\t\t\t\t\t\t<td>19,082</td>\n\t\t\t\t\t\t<td>573</td>\n\t\t\t\t\t\t<td>3,197</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>189</td>\n\t\t\t\t\t\t<td>14,527</td>\n\t\t\t\t\t\t<td>24,157</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 30분</td>\n\t\t\t\t\t\t<td>513</td>\n\t\t\t\t\t\t<td>1,981</td>\n\t\t\t\t\t\t<td>927</td>\n\t\t\t\t\t\t<td>354</td> \n\t\t\t\t\t\t<td>527</td>\n\t\t\t\t\t\t<td>19,061</td>\n\t\t\t\t\t\t<td>565</td>\n\t\t\t\t\t\t<td>3,194</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,398</td>\n\t\t\t\t\t\t<td>24,186</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 35분</td>\n\t\t\t\t\t\t<td>543</td>\n\t\t\t\t\t\t<td>2,112</td>\n\t\t\t\t\t\t<td>980</td>\n\t\t\t\t\t\t<td>363</td> \n\t\t\t\t\t\t<td>547</td>\n\t\t\t\t\t\t<td>19,027</td>\n\t\t\t\t\t\t<td>570</td>\n\t\t\t\t\t\t<td>3,182</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,429</td>\n\t\t\t\t\t\t<td>24,190</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 40분</td>\n\t\t\t\t\t\t<td>535</td>\n\t\t\t\t\t\t<td>1,987</td>\n\t\t\t\t\t\t<td>967</td>\n\t\t\t\t\t\t<td>429</td> \n\t\t\t\t\t\t<td>548</td>\n\t\t\t\t\t\t<td>18,985</td>\n\t\t\t\t\t\t<td>569</td>\n\t\t\t\t\t\t<td>3,165</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,543</td>\n\t\t\t\t\t\t<td>24,155</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 45분</td>\n\t\t\t\t\t\t<td>567</td>\n\t\t\t\t\t\t<td>2,097</td>\n\t\t\t\t\t\t<td>1,024</td>\n\t\t\t\t\t\t<td>372</td> \n\t\t\t\t\t\t<td>552</td>\n\t\t\t\t\t\t<td>18,881</td>\n\t\t\t\t\t\t<td>576</td>\n\t\t\t\t\t\t<td>3,154</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,497</td>\n\t\t\t\t\t\t<td>24,177</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 50분</td>\n\t\t\t\t\t\t<td>570</td>\n\t\t\t\t\t\t<td>2,042</td>\n\t\t\t\t\t\t<td>1,028</td>\n\t\t\t\t\t\t<td>158</td> \n\t\t\t\t\t\t<td>551</td>\n\t\t\t\t\t\t<td>18,638</td>\n\t\t\t\t\t\t<td>576</td>\n\t\t\t\t\t\t<td>3,145</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,481</td>\n\t\t\t\t\t\t<td>24,201</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>10시 55분</td>\n\t\t\t\t\t\t<td>614</td>\n\t\t\t\t\t\t<td>2,164</td>\n\t\t\t\t\t\t<td>1,109</td>\n\t\t\t\t\t\t<td>154</td> \n\t\t\t\t\t\t<td>554</td>\n\t\t\t\t\t\t<td>18,687</td>\n\t\t\t\t\t\t<td>584</td>\n\t\t\t\t\t\t<td>3,126</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,533</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 00분</td>\n\t\t\t\t\t\t<td>640</td>\n\t\t\t\t\t\t<td>2,217</td>\n\t\t\t\t\t\t<td>1,158</td>\n\t\t\t\t\t\t<td>197</td> \n\t\t\t\t\t\t<td>575</td>\n\t\t\t\t\t\t<td>18,897</td>\n\t\t\t\t\t\t<td>593</td>\n\t\t\t\t\t\t<td>3,123</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,505</td>\n\t\t\t\t\t\t<td>24,149</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 05분</td>\n\t\t\t\t\t\t<td>624</td>\n\t\t\t\t\t\t<td>2,067</td>\n\t\t\t\t\t\t<td>1,127</td>\n\t\t\t\t\t\t<td>135</td> \n\t\t\t\t\t\t<td>540</td>\n\t\t\t\t\t\t<td>19,157</td>\n\t\t\t\t\t\t<td>605</td>\n\t\t\t\t\t\t<td>3,140</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,387</td>\n\t\t\t\t\t\t<td>24,199</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 10분</td>\n\t\t\t\t\t\t<td>629</td>\n\t\t\t\t\t\t<td>2,072</td>\n\t\t\t\t\t\t<td>1,136</td>\n\t\t\t\t\t\t<td>134</td> \n\t\t\t\t\t\t<td>552</td>\n\t\t\t\t\t\t<td>19,175</td>\n\t\t\t\t\t\t<td>616</td>\n\t\t\t\t\t\t<td>3,120</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,321</td>\n\t\t\t\t\t\t<td>24,174</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 15분</td>\n\t\t\t\t\t\t<td>667</td>\n\t\t\t\t\t\t<td>2,165</td>\n\t\t\t\t\t\t<td>1,204</td>\n\t\t\t\t\t\t<td>168</td> \n\t\t\t\t\t\t<td>557</td>\n\t\t\t\t\t\t<td>18,979</td>\n\t\t\t\t\t\t<td>614</td>\n\t\t\t\t\t\t<td>3,106</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,461</td>\n\t\t\t\t\t\t<td>24,159</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 20분</td>\n\t\t\t\t\t\t<td>701</td>\n\t\t\t\t\t\t<td>2,328</td>\n\t\t\t\t\t\t<td>1,266</td>\n\t\t\t\t\t\t<td>143</td> \n\t\t\t\t\t\t<td>538</td>\n\t\t\t\t\t\t<td>18,996</td>\n\t\t\t\t\t\t<td>629</td>\n\t\t\t\t\t\t<td>3,105</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>186</td>\n\t\t\t\t\t\t<td>14,457</td>\n\t\t\t\t\t\t<td>24,161</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 25분</td>\n\t\t\t\t\t\t<td>733</td>\n\t\t\t\t\t\t<td>2,548</td>\n\t\t\t\t\t\t<td>1,323</td>\n\t\t\t\t\t\t<td>120</td> \n\t\t\t\t\t\t<td>530</td>\n\t\t\t\t\t\t<td>19,263</td>\n\t\t\t\t\t\t<td>643</td>\n\t\t\t\t\t\t<td>3,100</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>186</td>\n\t\t\t\t\t\t<td>14,275</td>\n\t\t\t\t\t\t<td>24,192</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 30분</td>\n\t\t\t\t\t\t<td>738</td>\n\t\t\t\t\t\t<td>2,404</td>\n\t\t\t\t\t\t<td>1,332</td>\n\t\t\t\t\t\t<td>149</td> \n\t\t\t\t\t\t<td>504</td>\n\t\t\t\t\t\t<td>19,071</td>\n\t\t\t\t\t\t<td>663</td>\n\t\t\t\t\t\t<td>3,092</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>186</td>\n\t\t\t\t\t\t<td>14,361</td>\n\t\t\t\t\t\t<td>24,172</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 35분</td>\n\t\t\t\t\t\t<td>756</td>\n\t\t\t\t\t\t<td>2,407</td>\n\t\t\t\t\t\t<td>1,365</td>\n\t\t\t\t\t\t<td>182</td> \n\t\t\t\t\t\t<td>509</td>\n\t\t\t\t\t\t<td>18,871</td>\n\t\t\t\t\t\t<td>656</td>\n\t\t\t\t\t\t<td>3,061</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>185</td>\n\t\t\t\t\t\t<td>14,443</td>\n\t\t\t\t\t\t<td>24,176</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 40분</td>\n\t\t\t\t\t\t<td>736</td>\n\t\t\t\t\t\t<td>2,230</td>\n\t\t\t\t\t\t<td>1,329</td>\n\t\t\t\t\t\t<td>142</td> \n\t\t\t\t\t\t<td>501</td>\n\t\t\t\t\t\t<td>18,880</td>\n\t\t\t\t\t\t<td>665</td>\n\t\t\t\t\t\t<td>3,058</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,298</td>\n\t\t\t\t\t\t<td>24,146</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 45분</td>\n\t\t\t\t\t\t<td>734</td>\n\t\t\t\t\t\t<td>2,205</td>\n\t\t\t\t\t\t<td>1,325</td>\n\t\t\t\t\t\t<td>180</td> \n\t\t\t\t\t\t<td>498</td>\n\t\t\t\t\t\t<td>19,033</td>\n\t\t\t\t\t\t<td>669</td>\n\t\t\t\t\t\t<td>3,050</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>187</td>\n\t\t\t\t\t\t<td>14,424</td>\n\t\t\t\t\t\t<td>24,140</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 50분</td>\n\t\t\t\t\t\t<td>704</td>\n\t\t\t\t\t\t<td>2,080</td>\n\t\t\t\t\t\t<td>1,272</td>\n\t\t\t\t\t\t<td>126</td> \n\t\t\t\t\t\t<td>490</td>\n\t\t\t\t\t\t<td>19,138</td>\n\t\t\t\t\t\t<td>660</td>\n\t\t\t\t\t\t<td>3,020</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,267</td>\n\t\t\t\t\t\t<td>24,154</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>11시 55분</td>\n\t\t\t\t\t\t<td>668</td>\n\t\t\t\t\t\t<td>1,979</td>\n\t\t\t\t\t\t<td>1,206</td>\n\t\t\t\t\t\t<td>150</td> \n\t\t\t\t\t\t<td>517</td>\n\t\t\t\t\t\t<td>18,915</td>\n\t\t\t\t\t\t<td>668</td>\n\t\t\t\t\t\t<td>3,031</td>\n\t\t\t\t\t\t<td>293</td>\n\t\t\t\t\t\t<td>189</td>\n\t\t\t\t\t\t<td>14,408</td>\n\t\t\t\t\t\t<td>24,162</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 00분</td>\n\t\t\t\t\t\t<td>678</td>\n\t\t\t\t\t\t<td>1,982</td>\n\t\t\t\t\t\t<td>1,224</td>\n\t\t\t\t\t\t<td>-57</td> \n\t\t\t\t\t\t<td>430</td>\n\t\t\t\t\t\t<td>19,095</td>\n\t\t\t\t\t\t<td>668</td>\n\t\t\t\t\t\t<td>3,044</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,407</td>\n\t\t\t\t\t\t<td>24,151</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 05분</td>\n\t\t\t\t\t\t<td>645</td>\n\t\t\t\t\t\t<td>1,904</td>\n\t\t\t\t\t\t<td>1,164</td>\n\t\t\t\t\t\t<td>-96</td> \n\t\t\t\t\t\t<td>416</td>\n\t\t\t\t\t\t<td>19,036</td>\n\t\t\t\t\t\t<td>675</td>\n\t\t\t\t\t\t<td>3,029</td>\n\t\t\t\t\t\t<td>293</td>\n\t\t\t\t\t\t<td>189</td>\n\t\t\t\t\t\t<td>14,498</td>\n\t\t\t\t\t\t<td>24,162</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 10분</td>\n\t\t\t\t\t\t<td>642</td>\n\t\t\t\t\t\t<td>1,877</td>\n\t\t\t\t\t\t<td>1,159</td>\n\t\t\t\t\t\t<td>-99</td> \n\t\t\t\t\t\t<td>412</td>\n\t\t\t\t\t\t<td>19,154</td>\n\t\t\t\t\t\t<td>665</td>\n\t\t\t\t\t\t<td>3,026</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,427</td>\n\t\t\t\t\t\t<td>24,169</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 15분</td>\n\t\t\t\t\t\t<td>659</td>\n\t\t\t\t\t\t<td>1,918</td>\n\t\t\t\t\t\t<td>1,190</td>\n\t\t\t\t\t\t<td>-93</td> \n\t\t\t\t\t\t<td>415</td>\n\t\t\t\t\t\t<td>19,043</td>\n\t\t\t\t\t\t<td>674</td>\n\t\t\t\t\t\t<td>3,016</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,467</td>\n\t\t\t\t\t\t<td>24,153</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 20분</td>\n\t\t\t\t\t\t<td>692</td>\n\t\t\t\t\t\t<td>1,996</td>\n\t\t\t\t\t\t<td>1,250</td>\n\t\t\t\t\t\t<td>-109</td> \n\t\t\t\t\t\t<td>413</td>\n\t\t\t\t\t\t<td>18,955</td>\n\t\t\t\t\t\t<td>678</td>\n\t\t\t\t\t\t<td>3,027</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,439</td>\n\t\t\t\t\t\t<td>24,155</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 25분</td>\n\t\t\t\t\t\t<td>760</td>\n\t\t\t\t\t\t<td>2,150</td>\n\t\t\t\t\t\t<td>1,373</td>\n\t\t\t\t\t\t<td>-299</td> \n\t\t\t\t\t\t<td>433</td>\n\t\t\t\t\t\t<td>19,135</td>\n\t\t\t\t\t\t<td>661</td>\n\t\t\t\t\t\t<td>3,000</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>188</td>\n\t\t\t\t\t\t<td>14,492</td>\n\t\t\t\t\t\t<td>24,180</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 30분</td>\n\t\t\t\t\t\t<td>755</td>\n\t\t\t\t\t\t<td>2,136</td>\n\t\t\t\t\t\t<td>1,364</td>\n\t\t\t\t\t\t<td>-301</td> \n\t\t\t\t\t\t<td>408</td>\n\t\t\t\t\t\t<td>19,147</td>\n\t\t\t\t\t\t<td>659</td>\n\t\t\t\t\t\t<td>2,990</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>189</td>\n\t\t\t\t\t\t<td>14,387</td>\n\t\t\t\t\t\t<td>24,178</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 35분</td>\n\t\t\t\t\t\t<td>749</td>\n\t\t\t\t\t\t<td>2,096</td>\n\t\t\t\t\t\t<td>1,353</td>\n\t\t\t\t\t\t<td>-303</td> \n\t\t\t\t\t\t<td>429</td>\n\t\t\t\t\t\t<td>19,188</td>\n\t\t\t\t\t\t<td>679</td>\n\t\t\t\t\t\t<td>2,971</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,387</td>\n\t\t\t\t\t\t<td>24,195</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 40분</td>\n\t\t\t\t\t\t<td>771</td>\n\t\t\t\t\t\t<td>2,185</td>\n\t\t\t\t\t\t<td>1,393</td>\n\t\t\t\t\t\t<td>-288</td> \n\t\t\t\t\t\t<td>394</td>\n\t\t\t\t\t\t<td>19,124</td>\n\t\t\t\t\t\t<td>679</td>\n\t\t\t\t\t\t<td>2,973</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,443</td>\n\t\t\t\t\t\t<td>24,173</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 45분</td>\n\t\t\t\t\t\t<td>763</td>\n\t\t\t\t\t\t<td>2,186</td>\n\t\t\t\t\t\t<td>1,379</td>\n\t\t\t\t\t\t<td>-301</td> \n\t\t\t\t\t\t<td>373</td>\n\t\t\t\t\t\t<td>19,064</td>\n\t\t\t\t\t\t<td>693</td>\n\t\t\t\t\t\t<td>2,982</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,408</td>\n\t\t\t\t\t\t<td>24,181</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 50분</td>\n\t\t\t\t\t\t<td>793</td>\n\t\t\t\t\t\t<td>2,246</td>\n\t\t\t\t\t\t<td>1,432</td>\n\t\t\t\t\t\t<td>-302</td> \n\t\t\t\t\t\t<td>390</td>\n\t\t\t\t\t\t<td>19,327</td>\n\t\t\t\t\t\t<td>710</td>\n\t\t\t\t\t\t<td>2,960</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,506</td>\n\t\t\t\t\t\t<td>24,175</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>12시 55분</td>\n\t\t\t\t\t\t<td>788</td>\n\t\t\t\t\t\t<td>2,260</td>\n\t\t\t\t\t\t<td>1,423</td>\n\t\t\t\t\t\t<td>-283</td> \n\t\t\t\t\t\t<td>372</td>\n\t\t\t\t\t\t<td>19,222</td>\n\t\t\t\t\t\t<td>704</td>\n\t\t\t\t\t\t<td>2,945</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,520</td>\n\t\t\t\t\t\t<td>24,144</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 00분</td>\n\t\t\t\t\t\t<td>775</td>\n\t\t\t\t\t\t<td>2,268</td>\n\t\t\t\t\t\t<td>1,400</td>\n\t\t\t\t\t\t<td>-294</td> \n\t\t\t\t\t\t<td>371</td>\n\t\t\t\t\t\t<td>19,242</td>\n\t\t\t\t\t\t<td>723</td>\n\t\t\t\t\t\t<td>2,959</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,493</td>\n\t\t\t\t\t\t<td>24,175</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 05분</td>\n\t\t\t\t\t\t<td>760</td>\n\t\t\t\t\t\t<td>2,221</td>\n\t\t\t\t\t\t<td>1,373</td>\n\t\t\t\t\t\t<td>-287</td> \n\t\t\t\t\t\t<td>373</td>\n\t\t\t\t\t\t<td>19,230</td>\n\t\t\t\t\t\t<td>702</td>\n\t\t\t\t\t\t<td>2,981</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,564</td>\n\t\t\t\t\t\t<td>24,177</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 10분</td>\n\t\t\t\t\t\t<td>781</td>\n\t\t\t\t\t\t<td>2,276</td>\n\t\t\t\t\t\t<td>1,411</td>\n\t\t\t\t\t\t<td>-304</td> \n\t\t\t\t\t\t<td>373</td>\n\t\t\t\t\t\t<td>19,453</td>\n\t\t\t\t\t\t<td>661</td>\n\t\t\t\t\t\t<td>2,990</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,567</td>\n\t\t\t\t\t\t<td>24,182</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 15분</td>\n\t\t\t\t\t\t<td>823</td>\n\t\t\t\t\t\t<td>2,293</td>\n\t\t\t\t\t\t<td>1,487</td>\n\t\t\t\t\t\t<td>-307</td> \n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>19,414</td>\n\t\t\t\t\t\t<td>654</td>\n\t\t\t\t\t\t<td>2,944</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,499</td>\n\t\t\t\t\t\t<td>24,193</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 20분</td>\n\t\t\t\t\t\t<td>859</td>\n\t\t\t\t\t\t<td>2,351</td>\n\t\t\t\t\t\t<td>1,552</td>\n\t\t\t\t\t\t<td>-286</td> \n\t\t\t\t\t\t<td>371</td>\n\t\t\t\t\t\t<td>19,365</td>\n\t\t\t\t\t\t<td>662</td>\n\t\t\t\t\t\t<td>2,908</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,431</td>\n\t\t\t\t\t\t<td>24,163</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 25분</td>\n\t\t\t\t\t\t<td>857</td>\n\t\t\t\t\t\t<td>2,334</td>\n\t\t\t\t\t\t<td>1,548</td>\n\t\t\t\t\t\t<td>-427</td> \n\t\t\t\t\t\t<td>371</td>\n\t\t\t\t\t\t<td>19,326</td>\n\t\t\t\t\t\t<td>664</td>\n\t\t\t\t\t\t<td>2,902</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,434</td>\n\t\t\t\t\t\t<td>24,190</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 30분</td>\n\t\t\t\t\t\t<td>844</td>\n\t\t\t\t\t\t<td>2,300</td>\n\t\t\t\t\t\t<td>1,525</td>\n\t\t\t\t\t\t<td>-427</td> \n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>19,253</td>\n\t\t\t\t\t\t<td>660</td>\n\t\t\t\t\t\t<td>2,890</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,437</td>\n\t\t\t\t\t\t<td>24,171</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 35분</td>\n\t\t\t\t\t\t<td>826</td>\n\t\t\t\t\t\t<td>2,258</td>\n\t\t\t\t\t\t<td>1,491</td>\n\t\t\t\t\t\t<td>-426</td> \n\t\t\t\t\t\t<td>366</td>\n\t\t\t\t\t\t<td>19,589</td>\n\t\t\t\t\t\t<td>656</td>\n\t\t\t\t\t\t<td>2,883</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,420</td>\n\t\t\t\t\t\t<td>24,153</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 40분</td>\n\t\t\t\t\t\t<td>793</td>\n\t\t\t\t\t\t<td>2,224</td>\n\t\t\t\t\t\t<td>1,431</td>\n\t\t\t\t\t\t<td>-422</td> \n\t\t\t\t\t\t<td>374</td>\n\t\t\t\t\t\t<td>19,526</td>\n\t\t\t\t\t\t<td>663</td>\n\t\t\t\t\t\t<td>2,886</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,570</td>\n\t\t\t\t\t\t<td>24,184</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 45분</td>\n\t\t\t\t\t\t<td>768</td>\n\t\t\t\t\t\t<td>2,193</td>\n\t\t\t\t\t\t<td>1,387</td>\n\t\t\t\t\t\t<td>-422</td> \n\t\t\t\t\t\t<td>368</td>\n\t\t\t\t\t\t<td>19,421</td>\n\t\t\t\t\t\t<td>672</td>\n\t\t\t\t\t\t<td>2,917</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,394</td>\n\t\t\t\t\t\t<td>24,160</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 50분</td>\n\t\t\t\t\t\t<td>730</td>\n\t\t\t\t\t\t<td>2,140</td>\n\t\t\t\t\t\t<td>1,318</td>\n\t\t\t\t\t\t<td>-422</td> \n\t\t\t\t\t\t<td>367</td>\n\t\t\t\t\t\t<td>19,162</td>\n\t\t\t\t\t\t<td>656</td>\n\t\t\t\t\t\t<td>2,960</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,366</td>\n\t\t\t\t\t\t<td>24,152</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>13시 55분</td>\n\t\t\t\t\t\t<td>731</td>\n\t\t\t\t\t\t<td>2,182</td>\n\t\t\t\t\t\t<td>1,321</td>\n\t\t\t\t\t\t<td>-423</td> \n\t\t\t\t\t\t<td>391</td>\n\t\t\t\t\t\t<td>19,320</td>\n\t\t\t\t\t\t<td>635</td>\n\t\t\t\t\t\t<td>2,988</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,492</td>\n\t\t\t\t\t\t<td>24,197</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 00분</td>\n\t\t\t\t\t\t<td>730</td>\n\t\t\t\t\t\t<td>2,198</td>\n\t\t\t\t\t\t<td>1,318</td>\n\t\t\t\t\t\t<td>-421</td> \n\t\t\t\t\t\t<td>387</td>\n\t\t\t\t\t\t<td>19,379</td>\n\t\t\t\t\t\t<td>602</td>\n\t\t\t\t\t\t<td>2,990</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,536</td>\n\t\t\t\t\t\t<td>24,159</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 05분</td>\n\t\t\t\t\t\t<td>734</td>\n\t\t\t\t\t\t<td>2,252</td>\n\t\t\t\t\t\t<td>1,326</td>\n\t\t\t\t\t\t<td>-425</td> \n\t\t\t\t\t\t<td>407</td>\n\t\t\t\t\t\t<td>19,398</td>\n\t\t\t\t\t\t<td>609</td>\n\t\t\t\t\t\t<td>2,988</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,449</td>\n\t\t\t\t\t\t<td>24,160</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 10분</td>\n\t\t\t\t\t\t<td>698</td>\n\t\t\t\t\t\t<td>2,180</td>\n\t\t\t\t\t\t<td>1,260</td>\n\t\t\t\t\t\t<td>-421</td> \n\t\t\t\t\t\t<td>416</td>\n\t\t\t\t\t\t<td>19,225</td>\n\t\t\t\t\t\t<td>587</td>\n\t\t\t\t\t\t<td>2,997</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,404</td>\n\t\t\t\t\t\t<td>24,169</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 15분</td>\n\t\t\t\t\t\t<td>675</td>\n\t\t\t\t\t\t<td>2,147</td>\n\t\t\t\t\t\t<td>1,217</td>\n\t\t\t\t\t\t<td>-421</td> \n\t\t\t\t\t\t<td>419</td>\n\t\t\t\t\t\t<td>19,055</td>\n\t\t\t\t\t\t<td>572</td>\n\t\t\t\t\t\t<td>2,990</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,477</td>\n\t\t\t\t\t\t<td>24,173</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 20분</td>\n\t\t\t\t\t\t<td>701</td>\n\t\t\t\t\t\t<td>2,221</td>\n\t\t\t\t\t\t<td>1,266</td>\n\t\t\t\t\t\t<td>-425</td> \n\t\t\t\t\t\t<td>388</td>\n\t\t\t\t\t\t<td>18,994</td>\n\t\t\t\t\t\t<td>582</td>\n\t\t\t\t\t\t<td>2,970</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,483</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 25분</td>\n\t\t\t\t\t\t<td>680</td>\n\t\t\t\t\t\t<td>2,272</td>\n\t\t\t\t\t\t<td>1,229</td>\n\t\t\t\t\t\t<td>-422</td> \n\t\t\t\t\t\t<td>416</td>\n\t\t\t\t\t\t<td>19,251</td>\n\t\t\t\t\t\t<td>588</td>\n\t\t\t\t\t\t<td>2,974</td>\n\t\t\t\t\t\t<td>291</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,515</td>\n\t\t\t\t\t\t<td>24,169</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 30분</td>\n\t\t\t\t\t\t<td>643</td>\n\t\t\t\t\t\t<td>2,074</td>\n\t\t\t\t\t\t<td>1,161</td>\n\t\t\t\t\t\t<td>-421</td> \n\t\t\t\t\t\t<td>410</td>\n\t\t\t\t\t\t<td>19,320</td>\n\t\t\t\t\t\t<td>579</td>\n\t\t\t\t\t\t<td>2,967</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,567</td>\n\t\t\t\t\t\t<td>24,162</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 35분</td>\n\t\t\t\t\t\t<td>628</td>\n\t\t\t\t\t\t<td>2,048</td>\n\t\t\t\t\t\t<td>1,135</td>\n\t\t\t\t\t\t<td>-425</td> \n\t\t\t\t\t\t<td>410</td>\n\t\t\t\t\t\t<td>19,157</td>\n\t\t\t\t\t\t<td>582</td>\n\t\t\t\t\t\t<td>2,965</td>\n\t\t\t\t\t\t<td>290</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,400</td>\n\t\t\t\t\t\t<td>24,206</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 40분</td>\n\t\t\t\t\t\t<td>600</td>\n\t\t\t\t\t\t<td>1,982</td>\n\t\t\t\t\t\t<td>1,084</td>\n\t\t\t\t\t\t<td>-424</td> \n\t\t\t\t\t\t<td>410</td>\n\t\t\t\t\t\t<td>18,948</td>\n\t\t\t\t\t\t<td>596</td>\n\t\t\t\t\t\t<td>2,992</td>\n\t\t\t\t\t\t<td>292</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,434</td>\n\t\t\t\t\t\t<td>24,174</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 45분</td>\n\t\t\t\t\t\t<td>598</td>\n\t\t\t\t\t\t<td>1,959</td>\n\t\t\t\t\t\t<td>1,080</td>\n\t\t\t\t\t\t<td>-419</td> \n\t\t\t\t\t\t<td>418</td>\n\t\t\t\t\t\t<td>18,963</td>\n\t\t\t\t\t\t<td>581</td>\n\t\t\t\t\t\t<td>3,002</td>\n\t\t\t\t\t\t<td>295</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,601</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 50분</td>\n\t\t\t\t\t\t<td>594</td>\n\t\t\t\t\t\t<td>1,862</td>\n\t\t\t\t\t\t<td>1,073</td>\n\t\t\t\t\t\t<td>-422</td> \n\t\t\t\t\t\t<td>413</td>\n\t\t\t\t\t\t<td>19,227</td>\n\t\t\t\t\t\t<td>574</td>\n\t\t\t\t\t\t<td>3,009</td>\n\t\t\t\t\t\t<td>297</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,675</td>\n\t\t\t\t\t\t<td>24,178</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>14시 55분</td>\n\t\t\t\t\t\t<td>593</td>\n\t\t\t\t\t\t<td>1,854</td>\n\t\t\t\t\t\t<td>1,072</td>\n\t\t\t\t\t\t<td>-422</td> \n\t\t\t\t\t\t<td>415</td>\n\t\t\t\t\t\t<td>19,308</td>\n\t\t\t\t\t\t<td>574</td>\n\t\t\t\t\t\t<td>2,999</td>\n\t\t\t\t\t\t<td>295</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,497</td>\n\t\t\t\t\t\t<td>24,182</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 00분</td>\n\t\t\t\t\t\t<td>595</td>\n\t\t\t\t\t\t<td>1,844</td>\n\t\t\t\t\t\t<td>1,075</td>\n\t\t\t\t\t\t<td>-420</td> \n\t\t\t\t\t\t<td>415</td>\n\t\t\t\t\t\t<td>19,195</td>\n\t\t\t\t\t\t<td>573</td>\n\t\t\t\t\t\t<td>2,993</td>\n\t\t\t\t\t\t<td>299</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,575</td>\n\t\t\t\t\t\t<td>24,183</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 05분</td>\n\t\t\t\t\t\t<td>586</td>\n\t\t\t\t\t\t<td>1,776</td>\n\t\t\t\t\t\t<td>1,058</td>\n\t\t\t\t\t\t<td>-421</td> \n\t\t\t\t\t\t<td>407</td>\n\t\t\t\t\t\t<td>19,293</td>\n\t\t\t\t\t\t<td>537</td>\n\t\t\t\t\t\t<td>2,997</td>\n\t\t\t\t\t\t<td>305</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,450</td>\n\t\t\t\t\t\t<td>24,168</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 10분</td>\n\t\t\t\t\t\t<td>568</td>\n\t\t\t\t\t\t<td>1,731</td>\n\t\t\t\t\t\t<td>1,025</td>\n\t\t\t\t\t\t<td>-422</td> \n\t\t\t\t\t\t<td>414</td>\n\t\t\t\t\t\t<td>19,480</td>\n\t\t\t\t\t\t<td>517</td>\n\t\t\t\t\t\t<td>3,040</td>\n\t\t\t\t\t\t<td>307</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,559</td>\n\t\t\t\t\t\t<td>24,182</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 15분</td>\n\t\t\t\t\t\t<td>540</td>\n\t\t\t\t\t\t<td>1,639</td>\n\t\t\t\t\t\t<td>974</td>\n\t\t\t\t\t\t<td>-424</td> \n\t\t\t\t\t\t<td>410</td>\n\t\t\t\t\t\t<td>19,487</td>\n\t\t\t\t\t\t<td>496</td>\n\t\t\t\t\t\t<td>3,077</td>\n\t\t\t\t\t\t<td>309</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,544</td>\n\t\t\t\t\t\t<td>24,180</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 20분</td>\n\t\t\t\t\t\t<td>520</td>\n\t\t\t\t\t\t<td>1,555</td>\n\t\t\t\t\t\t<td>939</td>\n\t\t\t\t\t\t<td>-421</td> \n\t\t\t\t\t\t<td>400</td>\n\t\t\t\t\t\t<td>19,548</td>\n\t\t\t\t\t\t<td>508</td>\n\t\t\t\t\t\t<td>3,118</td>\n\t\t\t\t\t\t<td>311</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,441</td>\n\t\t\t\t\t\t<td>24,187</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 25분</td>\n\t\t\t\t\t\t<td>505</td>\n\t\t\t\t\t\t<td>1,516</td>\n\t\t\t\t\t\t<td>912</td>\n\t\t\t\t\t\t<td>-420</td> \n\t\t\t\t\t\t<td>405</td>\n\t\t\t\t\t\t<td>19,702</td>\n\t\t\t\t\t\t<td>494</td>\n\t\t\t\t\t\t<td>3,127</td>\n\t\t\t\t\t\t<td>321</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,556</td>\n\t\t\t\t\t\t<td>24,177</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 30분</td>\n\t\t\t\t\t\t<td>496</td>\n\t\t\t\t\t\t<td>1,559</td>\n\t\t\t\t\t\t<td>896</td>\n\t\t\t\t\t\t<td>-421</td> \n\t\t\t\t\t\t<td>374</td>\n\t\t\t\t\t\t<td>19,811</td>\n\t\t\t\t\t\t<td>491</td>\n\t\t\t\t\t\t<td>3,129</td>\n\t\t\t\t\t\t<td>332</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,590</td>\n\t\t\t\t\t\t<td>24,167</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 35분</td>\n\t\t\t\t\t\t<td>465</td>\n\t\t\t\t\t\t<td>1,452</td>\n\t\t\t\t\t\t<td>840</td>\n\t\t\t\t\t\t<td>-421</td> \n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>19,924</td>\n\t\t\t\t\t\t<td>479</td>\n\t\t\t\t\t\t<td>3,122</td>\n\t\t\t\t\t\t<td>341</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,522</td>\n\t\t\t\t\t\t<td>24,172</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 40분</td>\n\t\t\t\t\t\t<td>445</td>\n\t\t\t\t\t\t<td>1,423</td>\n\t\t\t\t\t\t<td>805</td>\n\t\t\t\t\t\t<td>-422</td> \n\t\t\t\t\t\t<td>367</td>\n\t\t\t\t\t\t<td>20,016</td>\n\t\t\t\t\t\t<td>452</td>\n\t\t\t\t\t\t<td>3,129</td>\n\t\t\t\t\t\t<td>341</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,477</td>\n\t\t\t\t\t\t<td>24,183</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 45분</td>\n\t\t\t\t\t\t<td>419</td>\n\t\t\t\t\t\t<td>1,343</td>\n\t\t\t\t\t\t<td>758</td>\n\t\t\t\t\t\t<td>-420</td> \n\t\t\t\t\t\t<td>372</td>\n\t\t\t\t\t\t<td>20,132</td>\n\t\t\t\t\t\t<td>466</td>\n\t\t\t\t\t\t<td>3,133</td>\n\t\t\t\t\t\t<td>350</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,535</td>\n\t\t\t\t\t\t<td>24,188</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 50분</td>\n\t\t\t\t\t\t<td>400</td>\n\t\t\t\t\t\t<td>1,326</td>\n\t\t\t\t\t\t<td>723</td>\n\t\t\t\t\t\t<td>-420</td> \n\t\t\t\t\t\t<td>345</td>\n\t\t\t\t\t\t<td>20,302</td>\n\t\t\t\t\t\t<td>452</td>\n\t\t\t\t\t\t<td>3,139</td>\n\t\t\t\t\t\t<td>356</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,544</td>\n\t\t\t\t\t\t<td>24,189</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>15시 55분</td>\n\t\t\t\t\t\t<td>389</td>\n\t\t\t\t\t\t<td>1,318</td>\n\t\t\t\t\t\t<td>703</td>\n\t\t\t\t\t\t<td>-420</td> \n\t\t\t\t\t\t<td>286</td>\n\t\t\t\t\t\t<td>20,642</td>\n\t\t\t\t\t\t<td>450</td>\n\t\t\t\t\t\t<td>3,140</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,591</td>\n\t\t\t\t\t\t<td>24,173</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 00분</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>1,209</td>\n\t\t\t\t\t\t<td>658</td>\n\t\t\t\t\t\t<td>-418</td> \n\t\t\t\t\t\t<td>314</td>\n\t\t\t\t\t\t<td>20,492</td>\n\t\t\t\t\t\t<td>433</td>\n\t\t\t\t\t\t<td>3,136</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,679</td>\n\t\t\t\t\t\t<td>24,180</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 05분</td>\n\t\t\t\t\t\t<td>367</td>\n\t\t\t\t\t\t<td>1,186</td>\n\t\t\t\t\t\t<td>665</td>\n\t\t\t\t\t\t<td>-419</td> \n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>20,185</td>\n\t\t\t\t\t\t<td>431</td>\n\t\t\t\t\t\t<td>3,183</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,562</td>\n\t\t\t\t\t\t<td>24,184</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 10분</td>\n\t\t\t\t\t\t<td>341</td>\n\t\t\t\t\t\t<td>1,108</td>\n\t\t\t\t\t\t<td>616</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>342</td>\n\t\t\t\t\t\t<td>19,945</td>\n\t\t\t\t\t\t<td>409</td>\n\t\t\t\t\t\t<td>3,216</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,544</td>\n\t\t\t\t\t\t<td>24,168</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 15분</td>\n\t\t\t\t\t\t<td>301</td>\n\t\t\t\t\t\t<td>976</td>\n\t\t\t\t\t\t<td>544</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>372</td>\n\t\t\t\t\t\t<td>20,046</td>\n\t\t\t\t\t\t<td>412</td>\n\t\t\t\t\t\t<td>3,455</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,608</td>\n\t\t\t\t\t\t<td>24,163</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 20분</td>\n\t\t\t\t\t\t<td>269</td>\n\t\t\t\t\t\t<td>881</td>\n\t\t\t\t\t\t<td>486</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>340</td>\n\t\t\t\t\t\t<td>20,254</td>\n\t\t\t\t\t\t<td>397</td>\n\t\t\t\t\t\t<td>3,639</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,600</td>\n\t\t\t\t\t\t<td>24,163</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 25분</td>\n\t\t\t\t\t\t<td>255</td>\n\t\t\t\t\t\t<td>837</td>\n\t\t\t\t\t\t<td>461</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>20,360</td>\n\t\t\t\t\t\t<td>386</td>\n\t\t\t\t\t\t<td>3,707</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,627</td>\n\t\t\t\t\t\t<td>24,188</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 30분</td>\n\t\t\t\t\t\t<td>227</td>\n\t\t\t\t\t\t<td>748</td>\n\t\t\t\t\t\t<td>410</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>376</td>\n\t\t\t\t\t\t<td>20,398</td>\n\t\t\t\t\t\t<td>392</td>\n\t\t\t\t\t\t<td>3,725</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,636</td>\n\t\t\t\t\t\t<td>24,152</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 35분</td>\n\t\t\t\t\t\t<td>214</td>\n\t\t\t\t\t\t<td>696</td>\n\t\t\t\t\t\t<td>387</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>372</td>\n\t\t\t\t\t\t<td>20,502</td>\n\t\t\t\t\t\t<td>376</td>\n\t\t\t\t\t\t<td>3,700</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,510</td>\n\t\t\t\t\t\t<td>24,156</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 40분</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>640</td>\n\t\t\t\t\t\t<td>345</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>371</td>\n\t\t\t\t\t\t<td>20,947</td>\n\t\t\t\t\t\t<td>370</td>\n\t\t\t\t\t\t<td>3,698</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,699</td>\n\t\t\t\t\t\t<td>24,177</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 45분</td>\n\t\t\t\t\t\t<td>170</td>\n\t\t\t\t\t\t<td>562</td>\n\t\t\t\t\t\t<td>308</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>370</td>\n\t\t\t\t\t\t<td>21,314</td>\n\t\t\t\t\t\t<td>373</td>\n\t\t\t\t\t\t<td>3,684</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,728</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 50분</td>\n\t\t\t\t\t\t<td>147</td>\n\t\t\t\t\t\t<td>484</td>\n\t\t\t\t\t\t<td>265</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>346</td>\n\t\t\t\t\t\t<td>21,164</td>\n\t\t\t\t\t\t<td>366</td>\n\t\t\t\t\t\t<td>3,656</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,630</td>\n\t\t\t\t\t\t<td>24,152</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>16시 55분</td>\n\t\t\t\t\t\t<td>124</td>\n\t\t\t\t\t\t<td>413</td>\n\t\t\t\t\t\t<td>223</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>366</td>\n\t\t\t\t\t\t<td>21,714</td>\n\t\t\t\t\t\t<td>359</td>\n\t\t\t\t\t\t<td>3,628</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,657</td>\n\t\t\t\t\t\t<td>24,164</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 00분</td>\n\t\t\t\t\t\t<td>111</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>200</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>330</td>\n\t\t\t\t\t\t<td>22,011</td>\n\t\t\t\t\t\t<td>371</td>\n\t\t\t\t\t\t<td>3,592</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,706</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 05분</td>\n\t\t\t\t\t\t<td>100</td>\n\t\t\t\t\t\t<td>315</td>\n\t\t\t\t\t\t<td>181</td>\n\t\t\t\t\t\t<td>164</td> \n\t\t\t\t\t\t<td>324</td>\n\t\t\t\t\t\t<td>22,335</td>\n\t\t\t\t\t\t<td>374</td>\n\t\t\t\t\t\t<td>3,554</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,720</td>\n\t\t\t\t\t\t<td>24,176</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 10분</td>\n\t\t\t\t\t\t<td>80</td>\n\t\t\t\t\t\t<td>243</td>\n\t\t\t\t\t\t<td>144</td>\n\t\t\t\t\t\t<td>394</td> \n\t\t\t\t\t\t<td>328</td>\n\t\t\t\t\t\t<td>22,305</td>\n\t\t\t\t\t\t<td>357</td>\n\t\t\t\t\t\t<td>3,525</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,717</td>\n\t\t\t\t\t\t<td>24,145</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 15분</td>\n\t\t\t\t\t\t<td>54</td>\n\t\t\t\t\t\t<td>163</td>\n\t\t\t\t\t\t<td>97</td>\n\t\t\t\t\t\t<td>520</td> \n\t\t\t\t\t\t<td>318</td>\n\t\t\t\t\t\t<td>22,564</td>\n\t\t\t\t\t\t<td>345</td>\n\t\t\t\t\t\t<td>3,507</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,797</td>\n\t\t\t\t\t\t<td>24,164</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 20분</td>\n\t\t\t\t\t\t<td>37</td>\n\t\t\t\t\t\t<td>119</td>\n\t\t\t\t\t\t<td>67</td>\n\t\t\t\t\t\t<td>522</td> \n\t\t\t\t\t\t<td>311</td>\n\t\t\t\t\t\t<td>22,382</td>\n\t\t\t\t\t\t<td>342</td>\n\t\t\t\t\t\t<td>3,502</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,818</td>\n\t\t\t\t\t\t<td>24,157</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>13</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>530</td> \n\t\t\t\t\t\t<td>325</td>\n\t\t\t\t\t\t<td>22,765</td>\n\t\t\t\t\t\t<td>343</td>\n\t\t\t\t\t\t<td>3,490</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,780</td>\n\t\t\t\t\t\t<td>24,164</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>536</td> \n\t\t\t\t\t\t<td>325</td>\n\t\t\t\t\t\t<td>23,011</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>3,467</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,771</td>\n\t\t\t\t\t\t<td>24,144</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 35분</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>26</td>\n\t\t\t\t\t\t<td>17</td>\n\t\t\t\t\t\t<td>937</td> \n\t\t\t\t\t\t<td>319</td>\n\t\t\t\t\t\t<td>22,779</td>\n\t\t\t\t\t\t<td>368</td>\n\t\t\t\t\t\t<td>3,421</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,859</td>\n\t\t\t\t\t\t<td>24,135</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 40분</td>\n\t\t\t\t\t\t<td>5</td>\n\t\t\t\t\t\t<td>17</td>\n\t\t\t\t\t\t<td>10</td>\n\t\t\t\t\t\t<td>940</td> \n\t\t\t\t\t\t<td>328</td>\n\t\t\t\t\t\t<td>23,010</td>\n\t\t\t\t\t\t<td>376</td>\n\t\t\t\t\t\t<td>3,459</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,839</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 45분</td>\n\t\t\t\t\t\t<td>9</td>\n\t\t\t\t\t\t<td>22</td>\n\t\t\t\t\t\t<td>16</td>\n\t\t\t\t\t\t<td>1,376</td> \n\t\t\t\t\t\t<td>326</td>\n\t\t\t\t\t\t<td>22,862</td>\n\t\t\t\t\t\t<td>373</td>\n\t\t\t\t\t\t<td>3,447</td>\n\t\t\t\t\t\t<td>361</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,823</td>\n\t\t\t\t\t\t<td>24,131</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 50분</td>\n\t\t\t\t\t\t<td>10</td>\n\t\t\t\t\t\t<td>25</td>\n\t\t\t\t\t\t<td>18</td>\n\t\t\t\t\t\t<td>1,389</td> \n\t\t\t\t\t\t<td>286</td>\n\t\t\t\t\t\t<td>23,043</td>\n\t\t\t\t\t\t<td>367</td>\n\t\t\t\t\t\t<td>3,438</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,888</td>\n\t\t\t\t\t\t<td>24,206</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>17시 55분</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>29</td>\n\t\t\t\t\t\t<td>21</td>\n\t\t\t\t\t\t<td>1,389</td> \n\t\t\t\t\t\t<td>280</td>\n\t\t\t\t\t\t<td>23,098</td>\n\t\t\t\t\t\t<td>370</td>\n\t\t\t\t\t\t<td>3,418</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,973</td>\n\t\t\t\t\t\t<td>24,183</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 00분</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>27</td>\n\t\t\t\t\t\t<td>21</td>\n\t\t\t\t\t\t<td>1,391</td> \n\t\t\t\t\t\t<td>287</td>\n\t\t\t\t\t\t<td>23,232</td>\n\t\t\t\t\t\t<td>369</td>\n\t\t\t\t\t\t<td>3,412</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,929</td>\n\t\t\t\t\t\t<td>24,169</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 05분</td>\n\t\t\t\t\t\t<td>13</td>\n\t\t\t\t\t\t<td>31</td>\n\t\t\t\t\t\t<td>23</td>\n\t\t\t\t\t\t<td>1,374</td> \n\t\t\t\t\t\t<td>285</td>\n\t\t\t\t\t\t<td>23,109</td>\n\t\t\t\t\t\t<td>396</td>\n\t\t\t\t\t\t<td>3,405</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,851</td>\n\t\t\t\t\t\t<td>24,174</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 10분</td>\n\t\t\t\t\t\t<td>13</td>\n\t\t\t\t\t\t<td>31</td>\n\t\t\t\t\t\t<td>23</td>\n\t\t\t\t\t\t<td>1,380</td> \n\t\t\t\t\t\t<td>282</td>\n\t\t\t\t\t\t<td>23,083</td>\n\t\t\t\t\t\t<td>407</td>\n\t\t\t\t\t\t<td>3,393</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,864</td>\n\t\t\t\t\t\t<td>24,159</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 15분</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>30</td>\n\t\t\t\t\t\t<td>19</td>\n\t\t\t\t\t\t<td>1,392</td> \n\t\t\t\t\t\t<td>279</td>\n\t\t\t\t\t\t<td>22,970</td>\n\t\t\t\t\t\t<td>409</td>\n\t\t\t\t\t\t<td>3,418</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,961</td>\n\t\t\t\t\t\t<td>24,169</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 20분</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>31</td>\n\t\t\t\t\t\t<td>20</td>\n\t\t\t\t\t\t<td>1,382</td> \n\t\t\t\t\t\t<td>277</td>\n\t\t\t\t\t\t<td>23,131</td>\n\t\t\t\t\t\t<td>403</td>\n\t\t\t\t\t\t<td>3,432</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,876</td>\n\t\t\t\t\t\t<td>24,135</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 25분</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>26</td>\n\t\t\t\t\t\t<td>15</td>\n\t\t\t\t\t\t<td>1,377</td> \n\t\t\t\t\t\t<td>278</td>\n\t\t\t\t\t\t<td>23,168</td>\n\t\t\t\t\t\t<td>397</td>\n\t\t\t\t\t\t<td>3,441</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,907</td>\n\t\t\t\t\t\t<td>24,190</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 30분</td>\n\t\t\t\t\t\t<td>8</td>\n\t\t\t\t\t\t<td>26</td>\n\t\t\t\t\t\t<td>14</td>\n\t\t\t\t\t\t<td>1,403</td> \n\t\t\t\t\t\t<td>286</td>\n\t\t\t\t\t\t<td>22,968</td>\n\t\t\t\t\t\t<td>396</td>\n\t\t\t\t\t\t<td>3,436</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,911</td>\n\t\t\t\t\t\t<td>24,153</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 35분</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>21</td>\n\t\t\t\t\t\t<td>1,383</td> \n\t\t\t\t\t\t<td>282</td>\n\t\t\t\t\t\t<td>22,968</td>\n\t\t\t\t\t\t<td>394</td>\n\t\t\t\t\t\t<td>3,421</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,810</td>\n\t\t\t\t\t\t<td>24,177</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 40분</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>36</td>\n\t\t\t\t\t\t<td>22</td>\n\t\t\t\t\t\t<td>1,367</td> \n\t\t\t\t\t\t<td>279</td>\n\t\t\t\t\t\t<td>22,839</td>\n\t\t\t\t\t\t<td>393</td>\n\t\t\t\t\t\t<td>3,415</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,831</td>\n\t\t\t\t\t\t<td>24,195</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 45분</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>37</td>\n\t\t\t\t\t\t<td>22</td>\n\t\t\t\t\t\t<td>1,381</td> \n\t\t\t\t\t\t<td>280</td>\n\t\t\t\t\t\t<td>22,764</td>\n\t\t\t\t\t\t<td>384</td>\n\t\t\t\t\t\t<td>3,419</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,818</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 50분</td>\n\t\t\t\t\t\t<td>12</td>\n\t\t\t\t\t\t<td>35</td>\n\t\t\t\t\t\t<td>22</td>\n\t\t\t\t\t\t<td>1,391</td> \n\t\t\t\t\t\t<td>209</td>\n\t\t\t\t\t\t<td>22,827</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>3,425</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,915</td>\n\t\t\t\t\t\t<td>24,180</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>18시 55분</td>\n\t\t\t\t\t\t<td>11</td>\n\t\t\t\t\t\t<td>31</td>\n\t\t\t\t\t\t<td>21</td>\n\t\t\t\t\t\t<td>1,376</td> \n\t\t\t\t\t\t<td>207</td>\n\t\t\t\t\t\t<td>22,673</td>\n\t\t\t\t\t\t<td>370</td>\n\t\t\t\t\t\t<td>3,422</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,873</td>\n\t\t\t\t\t\t<td>24,214</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,381</td> \n\t\t\t\t\t\t<td>211</td>\n\t\t\t\t\t\t<td>22,621</td>\n\t\t\t\t\t\t<td>380</td>\n\t\t\t\t\t\t<td>3,415</td>\n\t\t\t\t\t\t<td>361</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,901</td>\n\t\t\t\t\t\t<td>24,176</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,547</td> \n\t\t\t\t\t\t<td>213</td>\n\t\t\t\t\t\t<td>22,655</td>\n\t\t\t\t\t\t<td>371</td>\n\t\t\t\t\t\t<td>3,410</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,978</td>\n\t\t\t\t\t\t<td>24,157</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,521</td> \n\t\t\t\t\t\t<td>210</td>\n\t\t\t\t\t\t<td>22,522</td>\n\t\t\t\t\t\t<td>382</td>\n\t\t\t\t\t\t<td>3,421</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,871</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,305</td> \n\t\t\t\t\t\t<td>214</td>\n\t\t\t\t\t\t<td>22,458</td>\n\t\t\t\t\t\t<td>380</td>\n\t\t\t\t\t\t<td>3,428</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,907</td>\n\t\t\t\t\t\t<td>24,155</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,259</td> \n\t\t\t\t\t\t<td>210</td>\n\t\t\t\t\t\t<td>22,468</td>\n\t\t\t\t\t\t<td>385</td>\n\t\t\t\t\t\t<td>3,434</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,938</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,259</td> \n\t\t\t\t\t\t<td>205</td>\n\t\t\t\t\t\t<td>22,442</td>\n\t\t\t\t\t\t<td>368</td>\n\t\t\t\t\t\t<td>3,422</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,878</td>\n\t\t\t\t\t\t<td>24,171</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,303</td> \n\t\t\t\t\t\t<td>215</td>\n\t\t\t\t\t\t<td>22,404</td>\n\t\t\t\t\t\t<td>380</td>\n\t\t\t\t\t\t<td>3,424</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,839</td>\n\t\t\t\t\t\t<td>24,159</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,229</td> \n\t\t\t\t\t\t<td>202</td>\n\t\t\t\t\t\t<td>22,216</td>\n\t\t\t\t\t\t<td>360</td>\n\t\t\t\t\t\t<td>3,424</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,825</td>\n\t\t\t\t\t\t<td>24,202</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,238</td> \n\t\t\t\t\t\t<td>206</td>\n\t\t\t\t\t\t<td>22,052</td>\n\t\t\t\t\t\t<td>395</td>\n\t\t\t\t\t\t<td>3,414</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,868</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,092</td> \n\t\t\t\t\t\t<td>211</td>\n\t\t\t\t\t\t<td>22,184</td>\n\t\t\t\t\t\t<td>409</td>\n\t\t\t\t\t\t<td>3,422</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,931</td>\n\t\t\t\t\t\t<td>24,165</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,039</td> \n\t\t\t\t\t\t<td>209</td>\n\t\t\t\t\t\t<td>21,947</td>\n\t\t\t\t\t\t<td>401</td>\n\t\t\t\t\t\t<td>3,420</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,962</td>\n\t\t\t\t\t\t<td>24,156</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>19시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,073</td> \n\t\t\t\t\t\t<td>210</td>\n\t\t\t\t\t\t<td>21,826</td>\n\t\t\t\t\t\t<td>408</td>\n\t\t\t\t\t\t<td>3,418</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,907</td>\n\t\t\t\t\t\t<td>24,169</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,064</td> \n\t\t\t\t\t\t<td>208</td>\n\t\t\t\t\t\t<td>21,716</td>\n\t\t\t\t\t\t<td>388</td>\n\t\t\t\t\t\t<td>3,409</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>15,014</td>\n\t\t\t\t\t\t<td>24,156</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,028</td> \n\t\t\t\t\t\t<td>242</td>\n\t\t\t\t\t\t<td>21,674</td>\n\t\t\t\t\t\t<td>369</td>\n\t\t\t\t\t\t<td>3,408</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,897</td>\n\t\t\t\t\t\t<td>24,168</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,070</td> \n\t\t\t\t\t\t<td>251</td>\n\t\t\t\t\t\t<td>21,683</td>\n\t\t\t\t\t\t<td>388</td>\n\t\t\t\t\t\t<td>3,414</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,883</td>\n\t\t\t\t\t\t<td>24,171</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,035</td> \n\t\t\t\t\t\t<td>246</td>\n\t\t\t\t\t\t<td>21,440</td>\n\t\t\t\t\t\t<td>386</td>\n\t\t\t\t\t\t<td>3,414</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,870</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,089</td> \n\t\t\t\t\t\t<td>257</td>\n\t\t\t\t\t\t<td>21,532</td>\n\t\t\t\t\t\t<td>390</td>\n\t\t\t\t\t\t<td>3,411</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,924</td>\n\t\t\t\t\t\t<td>24,186</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,068</td> \n\t\t\t\t\t\t<td>250</td>\n\t\t\t\t\t\t<td>21,449</td>\n\t\t\t\t\t\t<td>373</td>\n\t\t\t\t\t\t<td>3,411</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,850</td>\n\t\t\t\t\t\t<td>24,181</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,041</td> \n\t\t\t\t\t\t<td>245</td>\n\t\t\t\t\t\t<td>21,344</td>\n\t\t\t\t\t\t<td>370</td>\n\t\t\t\t\t\t<td>3,397</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,866</td>\n\t\t\t\t\t\t<td>24,173</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,039</td> \n\t\t\t\t\t\t<td>247</td>\n\t\t\t\t\t\t<td>21,099</td>\n\t\t\t\t\t\t<td>373</td>\n\t\t\t\t\t\t<td>3,396</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,840</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,103</td> \n\t\t\t\t\t\t<td>258</td>\n\t\t\t\t\t\t<td>20,972</td>\n\t\t\t\t\t\t<td>367</td>\n\t\t\t\t\t\t<td>3,395</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,893</td>\n\t\t\t\t\t\t<td>24,192</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,061</td> \n\t\t\t\t\t\t<td>251</td>\n\t\t\t\t\t\t<td>21,057</td>\n\t\t\t\t\t\t<td>362</td>\n\t\t\t\t\t\t<td>3,399</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>15,000</td>\n\t\t\t\t\t\t<td>24,169</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,090</td> \n\t\t\t\t\t\t<td>253</td>\n\t\t\t\t\t\t<td>21,002</td>\n\t\t\t\t\t\t<td>355</td>\n\t\t\t\t\t\t<td>3,393</td>\n\t\t\t\t\t\t<td>366</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,910</td>\n\t\t\t\t\t\t<td>24,184</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>20시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,078</td> \n\t\t\t\t\t\t<td>252</td>\n\t\t\t\t\t\t<td>20,742</td>\n\t\t\t\t\t\t<td>355</td>\n\t\t\t\t\t\t<td>3,391</td>\n\t\t\t\t\t\t<td>366</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,875</td>\n\t\t\t\t\t\t<td>24,160</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,055</td> \n\t\t\t\t\t\t<td>253</td>\n\t\t\t\t\t\t<td>20,534</td>\n\t\t\t\t\t\t<td>369</td>\n\t\t\t\t\t\t<td>3,388</td>\n\t\t\t\t\t\t<td>366</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,969</td>\n\t\t\t\t\t\t<td>24,145</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,083</td> \n\t\t\t\t\t\t<td>252</td>\n\t\t\t\t\t\t<td>20,195</td>\n\t\t\t\t\t\t<td>367</td>\n\t\t\t\t\t\t<td>3,382</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,845</td>\n\t\t\t\t\t\t<td>24,172</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,095</td> \n\t\t\t\t\t\t<td>261</td>\n\t\t\t\t\t\t<td>20,152</td>\n\t\t\t\t\t\t<td>382</td>\n\t\t\t\t\t\t<td>3,380</td>\n\t\t\t\t\t\t<td>366</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,969</td>\n\t\t\t\t\t\t<td>24,188</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,015</td> \n\t\t\t\t\t\t<td>240</td>\n\t\t\t\t\t\t<td>20,060</td>\n\t\t\t\t\t\t<td>377</td>\n\t\t\t\t\t\t<td>3,373</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,852</td>\n\t\t\t\t\t\t<td>24,177</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,073</td> \n\t\t\t\t\t\t<td>250</td>\n\t\t\t\t\t\t<td>19,798</td>\n\t\t\t\t\t\t<td>368</td>\n\t\t\t\t\t\t<td>3,372</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,828</td>\n\t\t\t\t\t\t<td>24,176</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>994</td> \n\t\t\t\t\t\t<td>240</td>\n\t\t\t\t\t\t<td>19,778</td>\n\t\t\t\t\t\t<td>359</td>\n\t\t\t\t\t\t<td>3,368</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,777</td>\n\t\t\t\t\t\t<td>24,183</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,105</td> \n\t\t\t\t\t\t<td>251</td>\n\t\t\t\t\t\t<td>19,914</td>\n\t\t\t\t\t\t<td>367</td>\n\t\t\t\t\t\t<td>3,348</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,887</td>\n\t\t\t\t\t\t<td>24,158</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,031</td> \n\t\t\t\t\t\t<td>245</td>\n\t\t\t\t\t\t<td>19,654</td>\n\t\t\t\t\t\t<td>375</td>\n\t\t\t\t\t\t<td>3,349</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,872</td>\n\t\t\t\t\t\t<td>24,204</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>1,079</td> \n\t\t\t\t\t\t<td>250</td>\n\t\t\t\t\t\t<td>19,575</td>\n\t\t\t\t\t\t<td>367</td>\n\t\t\t\t\t\t<td>3,343</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,872</td>\n\t\t\t\t\t\t<td>24,155</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>852</td> \n\t\t\t\t\t\t<td>242</td>\n\t\t\t\t\t\t<td>19,798</td>\n\t\t\t\t\t\t<td>378</td>\n\t\t\t\t\t\t<td>3,344</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,904</td>\n\t\t\t\t\t\t<td>24,194</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>799</td> \n\t\t\t\t\t\t<td>233</td>\n\t\t\t\t\t\t<td>19,370</td>\n\t\t\t\t\t\t<td>382</td>\n\t\t\t\t\t\t<td>3,336</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,830</td>\n\t\t\t\t\t\t<td>24,189</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>21시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>863</td> \n\t\t\t\t\t\t<td>240</td>\n\t\t\t\t\t\t<td>19,446</td>\n\t\t\t\t\t\t<td>380</td>\n\t\t\t\t\t\t<td>3,335</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,916</td>\n\t\t\t\t\t\t<td>24,156</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>875</td> \n\t\t\t\t\t\t<td>248</td>\n\t\t\t\t\t\t<td>19,615</td>\n\t\t\t\t\t\t<td>392</td>\n\t\t\t\t\t\t<td>3,328</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,945</td>\n\t\t\t\t\t\t<td>24,166</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>854</td> \n\t\t\t\t\t\t<td>242</td>\n\t\t\t\t\t\t<td>19,896</td>\n\t\t\t\t\t\t<td>400</td>\n\t\t\t\t\t\t<td>3,320</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,909</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>836</td> \n\t\t\t\t\t\t<td>238</td>\n\t\t\t\t\t\t<td>19,938</td>\n\t\t\t\t\t\t<td>405</td>\n\t\t\t\t\t\t<td>3,312</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,907</td>\n\t\t\t\t\t\t<td>24,151</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>815</td> \n\t\t\t\t\t\t<td>248</td>\n\t\t\t\t\t\t<td>19,972</td>\n\t\t\t\t\t\t<td>380</td>\n\t\t\t\t\t\t<td>3,306</td>\n\t\t\t\t\t\t<td>365</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>15,016</td>\n\t\t\t\t\t\t<td>24,147</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>730</td> \n\t\t\t\t\t\t<td>200</td>\n\t\t\t\t\t\t<td>20,130</td>\n\t\t\t\t\t\t<td>386</td>\n\t\t\t\t\t\t<td>3,298</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,995</td>\n\t\t\t\t\t\t<td>24,188</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>728</td> \n\t\t\t\t\t\t<td>198</td>\n\t\t\t\t\t\t<td>19,948</td>\n\t\t\t\t\t\t<td>398</td>\n\t\t\t\t\t\t<td>3,306</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,978</td>\n\t\t\t\t\t\t<td>24,170</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>736</td> \n\t\t\t\t\t\t<td>201</td>\n\t\t\t\t\t\t<td>19,859</td>\n\t\t\t\t\t\t<td>409</td>\n\t\t\t\t\t\t<td>3,300</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>194</td>\n\t\t\t\t\t\t<td>14,959</td>\n\t\t\t\t\t\t<td>24,134</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>737</td> \n\t\t\t\t\t\t<td>116</td>\n\t\t\t\t\t\t<td>19,950</td>\n\t\t\t\t\t\t<td>407</td>\n\t\t\t\t\t\t<td>3,293</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,918</td>\n\t\t\t\t\t\t<td>24,151</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>721</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>19,576</td>\n\t\t\t\t\t\t<td>407</td>\n\t\t\t\t\t\t<td>3,289</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>193</td>\n\t\t\t\t\t\t<td>14,890</td>\n\t\t\t\t\t\t<td>24,174</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>739</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>19,605</td>\n\t\t\t\t\t\t<td>390</td>\n\t\t\t\t\t\t<td>3,282</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>14,898</td>\n\t\t\t\t\t\t<td>24,155</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>735</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>19,548</td>\n\t\t\t\t\t\t<td>383</td>\n\t\t\t\t\t\t<td>3,278</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>190</td>\n\t\t\t\t\t\t<td>14,900</td>\n\t\t\t\t\t\t<td>24,147</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>22시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>730</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>19,408</td>\n\t\t\t\t\t\t<td>376</td>\n\t\t\t\t\t\t<td>3,268</td>\n\t\t\t\t\t\t<td>363</td>\n\t\t\t\t\t\t<td>192</td>\n\t\t\t\t\t\t<td>14,872</td>\n\t\t\t\t\t\t<td>24,171</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 00분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>769</td> \n\t\t\t\t\t\t<td>40</td>\n\t\t\t\t\t\t<td>19,565</td>\n\t\t\t\t\t\t<td>382</td>\n\t\t\t\t\t\t<td>3,257</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>15,066</td>\n\t\t\t\t\t\t<td>24,187</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 05분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>750</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>20,394</td>\n\t\t\t\t\t\t<td>372</td>\n\t\t\t\t\t\t<td>3,188</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>15,148</td>\n\t\t\t\t\t\t<td>24,168</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 10분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>742</td> \n\t\t\t\t\t\t<td>39</td>\n\t\t\t\t\t\t<td>20,717</td>\n\t\t\t\t\t\t<td>391</td>\n\t\t\t\t\t\t<td>3,191</td>\n\t\t\t\t\t\t<td>364</td>\n\t\t\t\t\t\t<td>191</td>\n\t\t\t\t\t\t<td>15,089</td>\n\t\t\t\t\t\t<td>24,175</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 15분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 20분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 25분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 30분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 35분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 40분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 45분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 50분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t<tr>\n\t\t\t\t\t\t<td>23시 55분</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td> \n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t\t<td>0</td>\n\t\t\t\t\t</tr>\n\t\t\t\t\n\t\t\t</tbody>\n\t\t</table>\n\t</div>\n</div>\n<div class=\"FloatLeft MAT10 MAB10\">\n*태양광(PPA,BTM)은 공식적인 계량 수치가 아닌 태양광(전력시장) 데이터에 기반한 실시간 추정값임을 참고하시기 바라며, 태양광(전력시장) 데이터의 누락이나 취득 지연 등으로 인한 오차가 포함될수 있습니다.<br>\n*국가 총수요 데이터는 '24.11.23일 이후 데이터만 조회 가능합니다.<br>\n*'24.11.23일 이후에는 신재생으로부터 풍력을 분리하였습니다.\n</div>\n<div class=\"btn_area AlignRight\">\n\t<a href=\"/powerSource.es?mid=a10606030000&device=chart\" target=\"_blank\" title=\"새창열림\" class=\"btn_link\">차트보기</a>\n</div>\n\n<h4>최근 5년 최대 전력 실적</h4>\n\t\n\n\n\n\n\n\n<p class=\"info_top\">단위 : MW,%</p>\n<div class=\"conTableGroup scroll\"> \n\t<table class=\"conTable tdCenter\" style=\"min-width:500px\">\n\t\t<caption>최근 5년 최대 전력 실적</caption>\n\t\t<colgroup>\n\t\t\t<col>\n\t\t\t<col>\n\t\t\t<col>\n\t\t\t<col>\n\t\t\t<col>\n\t\t</colgroup>\n\t\t<thead>\n\t\t\t<tr>\n\t\t\t\t<th rowspan=\"2\">일시</th>\n\t\t\t\t<th colspan=\"4\">전력시장</th>\n\t\t\t\t<th rowspan=\"2\">비고<br>(총수요 추정)</th>\n\t\t\t</tr>\n\t\t\t<tr>\n\t\t\t\t<th style=\"border-left: 1px solid #d8dee5;\">공급능력</th>\n\t\t\t\t<th>최대수요</th>\n\t\t\t\t<th>예비전력</th>\n\t\t\t\t<th>예비율</th>\n\t\t\t</tr>\t\t\t\n\t\t</thead>\n\t\t<tbody>\n\n\n\t\n\t\t\t<tr>\n\t\t\t\t<td>2024년 08월 20일</td>\n\t\t\t\t<td>105,360</td>\n\t\t\t\t<td>97,115</td>\n\t\t\t\t<td>8,245</td>\n\t\t\t\t<td>8.5</td>\n\t\t\t\t<td>103,553</td>\n\t\t\t</tr>\n\t\n\t\t\t<tr>\n\t\t\t\t<td>2023년 12월 21일</td>\n\t\t\t\t<td>105,213</td>\n\t\t\t\t<td>91,556</td>\n\t\t\t\t<td>13,657</td>\n\t\t\t\t<td>14.9</td>\n\t\t\t\t<td></td>\n\t\t\t</tr>\n\t\n\t\t\t<tr>\n\t\t\t\t<td>2023년 08월 07일</td>\n\t\t\t\t<td>104,297</td>\n\t\t\t\t<td>93,615</td>\n\t\t\t\t<td>10,682</td>\n\t\t\t\t<td>11.4</td>\n\t\t\t\t<td></td>\n\t\t\t</tr>\n\t\n\t\t\t<tr>\n\t\t\t\t<td>2022년 12월 23일</td>\n\t\t\t\t<td>105,628</td>\n\t\t\t\t<td>94,509</td>\n\t\t\t\t<td>11,119</td>\n\t\t\t\t<td>11.8</td>\n\t\t\t\t<td></td>\n\t\t\t</tr>\n\t\n\t\t\t<tr>\n\t\t\t\t<td>2022년 07월 07일</td>\n\t\t\t\t<td>99,716</td>\n\t\t\t\t<td>92,990</td>\n\t\t\t\t<td>6,726</td>\n\t\t\t\t<td>7.2</td>\n\t\t\t\t<td></td>\n\t\t\t</tr>\n\t\n\t\t\t<tr>\n\t\t\t\t<td>2021년 12월 27일</td>\n\t\t\t\t<td>103,554</td>\n\t\t\t\t<td>90,708</td>\n\t\t\t\t<td>12,846</td>\n\t\t\t\t<td>14.2</td>\n\t\t\t\t<td></td>\n\t\t\t</tr>\n\t\n\t\t\t<tr>\n\t\t\t\t<td>2021년 07월 27일</td>\n\t\t\t\t<td>100,739</td>\n\t\t\t\t<td>91,141</td>\n\t\t\t\t<td>9,598</td>\n\t\t\t\t<td>10.5</td>\n\t\t\t\t<td></td>\n\t\t\t</tr>\n\t\n\t\t\t<tr>\n\t\t\t\t<td>2021년 01월 11일</td>\n\t\t\t\t<td>99,189</td>\n\t\t\t\t<td>90,564</td>\n\t\t\t\t<td>8,625</td>\n\t\t\t\t<td>9.5</td>\n\t\t\t\t<td></td>\n\t\t\t</tr>\n\t\n\n\n\n\t\t</tbody>\n\t</table>\t\n</div>\t\t\t\n\n\n\n\n\n\n\n\t\t\t\t</div>\n\t\t\t</div>\n\t\t\t<div class=\"contents_info\">\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t<article class=\"duty\">\n\t\t\t\t\t\t<h2 class=\"title\">콘텐츠 정보책임자</h2>\n\t\t\t\t\t\t<ul class=\"list\">\n\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<strong class=\"label\">담당부서</strong>\n\t\t\t\t\t\t\t\t<span class=\"part\"></span>\n\t\t\t\t\t\t\t</li>\n\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<strong class=\"label\">담당자</strong>\n\t\t\t\t\t\t\t\t<span class=\"name\"></span>\n\t\t\t\t\t\t\t</li>\n\t\t\t\t\t\t\t<li>\n\t\t\t\t\t\t\t\t<strong class=\"label\">문의전화</strong>\n\t\t\t\t\t\t\t\t<span class=\"tel\"><a href=\"tel:\"></a></span>\n\t\t\t\t\t\t\t</li>\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t\t<p class=\"date\">\n\t\t\t\t\t\t\t<strong class=\"label\">업데이트</strong>\n\t\t\t\t\t\t\t<span>2021/11/22</span>\n\t\t\t\t\t\t</p>\n\t\t\t\t\t</article>\n\t\t\t\t\n\t\t\t\t<div class=\"group\">\n\t\t\t\t\n\t\t\t\t<article id=\"satisfy\" class=\"item\">\n\t\t\t\t\t\n\n\n\n\n\n<script type=\"text/javascript\">\n//<![CDATA[\n\tfunction satisfy_confirm(){\n\t\tvar fm = document.s_form;\n\t\tvar selChk = document.getElementsByName(\"chk_point\");\n\t\tfor(var i = 0 ; i < selChk.length ; i++){\n\t\t\tif(selChk[i].checked == true){\n\t\t\t\tfm.point.value = selChk[i].value;\n\t\t\t}\n\t\t}\n\t\tfm.action = \"/satisfy.es?mid=a10606030000&act=ins\";\n\t\tfm.submit();\n\t}\n//]]>\n</script>\n\n<fieldset>\n\t<legend>콘텐츠 만족도 조사</legend>\n\t<h2 class=\"title\">\n\t\t\n\t\t<strong>이 페이지에서 제공하는 정보에 대하여 만족하십니까?</strong>\n\t\t\n\t\t\n\t</h2>\n\t<div class=\"cont\">\n\t\t\n\t\t\n\t\t\n\t\t<form id=\"s_form\" name=\"s_form\" action=\"/satisfy.es\" method=\"post\">\n\t\t<input type=\"hidden\" name=\"mid\" value=\"a10606030000\" />\n\t\t<input type=\"hidden\" name=\"act\" value=\"ins\" />\n\t\t<input type=\"hidden\" name=\"point\" value=\"0\" />\n\t\t<ul class=\"list\">\n\t\t\t<li class=\"form_radio\"><input type=\"radio\" name=\"chk_point\" id=\"q1\" value=\"5\" checked=\"checked\" /><label for=\"q1\"> 매우만족</label></li>\n\t\t\t<li class=\"form_radio\"><input type=\"radio\" name=\"chk_point\" id=\"q2\" value=\"4\" /><label for=\"q2\"> 만족</label></li>\n\t\t\t<li class=\"form_radio\"><input type=\"radio\" name=\"chk_point\" id=\"q3\" value=\"3\" /><label for=\"q3\"> 보통</label></li>\n\t\t\t<li class=\"form_radio\"><input type=\"radio\" name=\"chk_point\" id=\"q4\" value=\"2\" /><label for=\"q4\"> 불만족</label></li>\n\t\t\t<li class=\"form_radio\"><input type=\"radio\" name=\"chk_point\" id=\"q5\" value=\"1\" /><label for=\"q5\"> 매우불만족</label></li>\n\t\t</ul>\n\t\t<p class=\"form\">\n\t\t\t<label for=\"opinionContents\" class=\"IR\">의견을 남겨주세요</label>\n\t\t\t<input type=\"text\" class=\"form_textbox\" name=\"contents\" id=\"opinionContents\" onkeyup=\"insertContentsMax('opinionLength2', '100', document.s_form.contents); return false;\" title=\"의견을 남겨주세요\" placeholder=\"의견을 남겨주세요\" />\n\t\t\t<input type=\"submit\" class=\"btn\" onclick=\"satisfy_confirm(); return false;\" value=\"의견등록\"  />\n\t\t\t<span class=\"length\"><strong><span id=\"opinionLength2\">0</span></strong>/100</span>\n\t\t</p>\n\t\t<div>\n<input type=\"hidden\" name=\"_csrf\" value=\"cc29bc11-037e-4e72-95ee-c4295424f505\" />\n</div></form>\n\t\t\n\t\t\n\t</div>\n</fieldset>\n\n\t\t\t\t</article>\n\t\t\t\t\n\t\t\t\t</div>\n\t\t\t</div>\n\t\t</section>\n\n\n\n\n\n\n\t\t</div>\n\t</main>\n\t\n\t<footer id=\"footer\">\n\t\t<div class=\"footer_wrap\">\n\t\t\t\n\t\t<span class='visually_hidden'>smartKPX 전력거래소</span>\n\t\t                                 \n\t\t<div class=\"ismsp_icon\">\n\t\t\t<div class=\"ismsp_pop remove\">\n\t\t\t\t<ul>\n\t\t\t\t\t<li><span>[인증범위] </span>\n\t\t\t\t\t\t<div>\n\t\t\t\t\t\t 대국민서비스(대표홈페이지, 방문예약시스템) 및 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href=\"http://www.unikorea.go.kr/\" target=\"_blank\" title=\"새창\">통일부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.moj.go.kr/\" target=\"_blank\" title=\"새창\">법무부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.mnd.go.kr/\" target=\"_blank\" title=\"새창\">국방부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.mois.go.kr\" target=\"_blank\" title=\"새창\">행정안전부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.mcst.go.kr/\" target=\"_blank\" title=\"새창\">문화체육관광부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.mafra.go.kr\" target=\"_blank\" title=\"새창\">농림축산식품부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.mohw.go.kr/\" target=\"_blank\" title=\"새창\">보건복지부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.me.go.kr/\" target=\"_blank\" title=\"새창\">환경부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.moel.go.kr\" target=\"_blank\" title=\"새창\">고용노동부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.mogef.go.kr/\" target=\"_blank\" title=\"새창\">여성부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.molit.go.kr/\" target=\"_blank\" title=\"새창\">국토교통부</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.moleg.go.kr/\" target=\"_blank\" title=\"새창\">법제처</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.mpva.go.kr/\" target=\"_blank\" title=\"새창\">국가보훈처</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.police.go.kr/\" target=\"_blank\" title=\"새창\">경찰청</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.ftc.go.kr/\" target=\"_blank\" title=\"새창\">공정거래위원회</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.acrc.go.kr/\" target=\"_blank\" title=\"새창\">국민권익위원회</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.nts.go.kr/\" target=\"_blank\" title=\"새창\">국세청</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.nis.go.kr/\" target=\"_blank\" title=\"새창\">국가정보원</a>\n\t\t</li>\n\t\n\t\t<li>\n\t\t\t<a href=\"http://www.assembly.go.kr/\" target=\"_blank\" 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}\n\ttry { init5DepthComboMenu('0606030000'); } catch (e) { console.log(\"\"); }\n\ttry { init1DepthComboMenu2('06'); } catch (e) { console.log(\"\"); }\n\ttry { init2DepthComboMenu2('0606'); } catch (e) { console.log(\"\"); }\n\ttry { init3DepthComboMenu2('060603'); } catch (e) { console.log(\"\"); }\n\t$.ajax({ url:'/logInsert.es?mid=a10606030000' });\t\t// 로그기록\n</script>\n\t\n\t\n\n</body>\n</html>\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/MD/moldoelectrica_api_historical_20210725.json",
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  {
    "path": "electricitymap/contrib/parsers/tests/mocks/NORDPOOL/se_next_day_price.json",
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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/NORDPOOL/token.json",
    "content": "{\"access_token\": \"token\", \"expires_in\": 3600, \"token_type\": \"Bearer\"}"
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    "path": "electricitymap/contrib/parsers/tests/mocks/NTESMO/as-7-days-forecast.json",
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   \n"
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    "path": "electricitymap/contrib/parsers/tests/mocks/NTESMO/dk-7-days-forecast.json",
    "content": 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   \n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/NTESMO/tc-7-days-forecast.json",
    "content": 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   \n"
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    "path": "electricitymap/contrib/parsers/tests/mocks/NZ/response_2024_04_24_17_30.html",
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data-drupal-link-system-path=\"node/15184\">Contact</a>\n                  </li>\n                      \n                \n        <li rel=\"nofollow\" class=\"nav-item\">\n                      <a href=\"/user/login-ad\" class=\"nav-link\">Log in</a>\n                  </li>\n                      \n                \n        <li class=\"nav-item\">\n                      <a href=\"/user/register\" class=\"nav-link\" data-drupal-link-system-path=\"user/register\">Register</a>\n                  </li>\n            </ul>\n\n\n      \n  </div>\n\n  <div class=\"block block--tpow-main-menu container\">\n\n  \n    \n\n            \n  \n\n\n  <ul data-block=\"tpow_main_menu\" class=\"nav navbar-nav\">\n                                          <li class=\"nav-item dropdown\">\n                      <a href=\"/about-us\" class=\"nav-link dropdown-bs-toggle\" data-bs-toggle=\"dropdown\" data-drupal-link-system-path=\"node/15183\">About us</a>\n                          <div class=\"dropdown-menu\">\n  <ul>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/about-us/who-we-are\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15268\">Who we are</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/about-us/what-we-do\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15269\">What we do</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/about-us/our-strategy\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15270\">Our strategy</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/about-us/careers-transpower\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15945\">Careers at Transpower</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/about-us/our-work-community\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15271\">Our work in the community</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/about-us/sustainability\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15272\">Sustainability</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/about-us/celebrating-our-people\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15521\">Celebrating our people</a>\n              </li>\n      </ul>\n</div>\n                              </li>\n                                      <li class=\"nav-item dropdown\">\n                      <a href=\"/connect-grid\" class=\"nav-link dropdown-bs-toggle\" data-bs-toggle=\"dropdown\" data-drupal-link-system-path=\"node/15190\">Connect to the grid</a>\n                          <div class=\"dropdown-menu\">\n  <ul>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/connect-grid/what-do-you-need\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15198\">What do you need?</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/connect-grid/our-connection-process\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15197\">Our connection process</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/connect-grid/customer-information\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15200\">Customer information</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/connect-grid/envision-spatial-tools\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15194\">Envision spatial tools</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/connect-grid/connection-enquiry-information\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15535\">Connection enquiry information</a>\n              </li>\n      </ul>\n</div>\n                              </li>\n                                      <li class=\"nav-item dropdown\">\n                      <a href=\"/our-work\" class=\"nav-link dropdown-bs-toggle\" data-bs-toggle=\"dropdown\" data-drupal-link-system-path=\"node/15181\">Our work</a>\n                          <div class=\"dropdown-menu\">\n  <ul>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/our-work/industry\" title=\"Specialist information for those within the electricity industry\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15278\">Industry</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/our-work/landowners-and-developers\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15279\">Landowners and developers</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/our-work/consultations-webinars\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15300\">Consultations &amp; Webinars</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/our-work/distributed-energy-resources\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15310\">Distributed Energy Resources</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/our-work/investors\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15282\">Investors</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/our-work/grid-skills\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15520\">Grid Skills Training</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/subscribe\" title=\"Stay current with Transpower&#039;s activities by subscribing to our mailing lists and following our social channels\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15636\">Subscribe and Updates</a>\n              </li>\n      </ul>\n</div>\n                              </li>\n                                      <li class=\"nav-item dropdown\">\n                      <a href=\"/your-safety\" class=\"nav-link dropdown-bs-toggle\" data-bs-toggle=\"dropdown\" data-drupal-link-system-path=\"node/15358\">Your safety</a>\n                          <div class=\"dropdown-menu\">\n  <ul>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/your-safety/safety-submission-form\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15359\">Safety submission form</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/your-safety/star-awards\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15379\">STAR Awards</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/your-safety/safety-others\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15385\">Safety for others</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/your-safety/safety-transpower\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15386\">Safety at Transpower</a>\n              </li>\n      </ul>\n</div>\n                              </li>\n                                      <li class=\"nav-item\">\n                      <a href=\"/projects\" class=\"nav-link\" data-drupal-link-system-path=\"projects\">Projects</a>\n                  </li>\n                                      <li class=\"nav-item active dropdown\">\n                      <a href=\"/system-operator\" class=\"nav-link active dropdown-bs-toggle\" data-bs-toggle=\"dropdown\" data-drupal-link-system-path=\"node/15205\">System Operator</a>\n                          <div class=\"dropdown-menu\">\n  <ul>\n                      <li class=\"nav-item active dropdown\">\n        <a href=\"/system-operator/our-system-operator-role\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15206\">Our System Operator role</a>\n              </li>\n                      <li class=\"nav-item active dropdown\">\n        <a href=\"/system-operator/planning-future\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15207\">Planning for the future</a>\n              </li>\n                      <li class=\"nav-item active dropdown\">\n        <a href=\"/system-operator/information-industry\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15208\">Information for industry</a>\n              </li>\n                      <li class=\"nav-item active dropdown\">\n        <a href=\"/system-operator/notices-and-reporting\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15210\">Notices and  reporting</a>\n              </li>\n                      <li class=\"nav-item active dropdown\">\n        <a href=\"/system-operator/learning-centre\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15215\">Learning centre</a>\n              </li>\n                      <li class=\"nav-item active dropdown\">\n        <a href=\"/system-operator/live-system-and-market-data\" class=\"dropdown-item active\" data-drupal-link-system-path=\"node/15350\">Live system  and market data</a>\n              </li>\n      </ul>\n</div>\n                              </li>\n                                      <li class=\"nav-item\">\n                      <a href=\"/resources\" class=\"nav-link\" data-drupal-link-system-path=\"resources\">Resources</a>\n                  </li>\n            </ul>\n\n\n      \n  </div>\n\n\n            </div>\n\n      </div>\n  </nav>\n\n  <main>\n        <div class=\"pattern-background-container has-sidebar\">\n      <div class=\"pattern\"></div>\n    </div>\n    <a id=\"main-content\" tabindex=\"-1\"></a>\n          <header class=\"page__header\">\n        <div class=\"container\">\n          <div class=\"block block--tpow-breadcrumbs\">\n\n  \n    \n\n              <nav aria-label=\"breadcrumb\" class=\"\">\n    <ol class=\"breadcrumb\">\n              <li class=\"breadcrumb-item \">\n                      <a href=\"/system-operator\">System Operator</a>\n                  </li>\n              <li class=\"breadcrumb-item \">\n                      <a href=\"/system-operator/live-system-and-market-data\">Live system and market data</a>\n                  </li>\n              <li class=\"breadcrumb-item active\">\n                      Consolidated live data \n                  </li>\n          </ol>\n  </nav>\n\n      \n  </div>\n        </div>\n      </header>\n    \n    \n              <div class=\"container\">\n                  <div class=\"row\">\n        \n              \n      <div class=\"page__content col-lg-9\">\n        <a id=\"page-content\" tab-index=\"-1\"></a>\n          <div data-drupal-messages-fallback class=\"hidden\"></div>\n\n  <div class=\"block block--tpow-page-title\">\n\n  \n    \n\n            \n\n\n  \n\n\n  <h1  class=\"page-title\">\n                  \n<span>Consolidated live data </span>\n\n            </h1>\n\n\n      \n  </div>\n\n  <div class=\"block block--tpow-content block--system-main\">\n\n  \n    \n\n            \n\n\n<article class=\"node page page--full\">\n  \n  \n\n      \n    \n    <div class=\"node__content\">\n      \n            <div class=\"field field--name-body field--type-text-with-summary field--label-hidden field__item\"><p>HVDC data and Generation data sourced from <a href=\"https://app.em6.co.nz/\" target=\"_blank\">em6</a>.</p>\n\n<p><div class=\"row\">\n  <div class=\"col-md-4 col-12\">\n    \n  <div class=\"block block--livedatasummary\">\n\n  \n            <h2>Live Data Summary</h2>\n        \n\n            <div class=\"live-data-summary\">\n  <span class=\"ajax-progress\"><span class=\"throbber\"></span>Updating...</span>\n  <span class=\"last-updated\" style=\"display: none;\">Updated: <time datetime=\"\"></time></span>\n  <div class=\"content\">\n    \n  </div>\n</div>\n\n      \n  </div>\n\n    \n  <div class=\"block block--renewablesgenerating\">\n\n  \n            <h2>% Renewables Generating</h2>\n        \n\n            <div class=\"renewables-gauge\">\n  <div class=\"renewables-updated renewables-update-time\">\n    <span class=\"update-text\">% Renewables (as at)</span>:\n    <time><span class=\"update-time\"></span></time>\n    <div class=\"ajax-progress\"><span></span></div>\n  </div>\n  <div id=\"renewable-pgen-gauge\"></div>\n</div>\n\n      \n  </div>\n\n    \n  <div class=\"block block--currentgenerationtable\">\n\n  \n            <h2>Current Generation (MW)</h2>\n        \n\n            <div class=\"power-generation\">\n  <table id=\"pgen-table\" class=\"table table-striped totals\">\n    <thead>\n    <tr>\n      <th>Power Generation</th>\n      <th><span class=\"pgen-date\">(as at) 25 Apr 2024 05:30</span></th>\n    </tr>\n    </thead>\n    <tbody>\n          <tr id=\"newzealandbattery\" class=\"battery\">\n        <td><span class=\"name\">Battery</span></td>\n        <td class=\"value\"><span class=\"generation\">0</span> MW</td>\n      </tr>\n          <tr id=\"newzealandcogen\" class=\"cogen\">\n        <td><span class=\"name\">Co-Gen</span></td>\n        <td class=\"value\"><span class=\"generation\">118</span> MW</td>\n      </tr>\n          <tr id=\"newzealandcoal\" class=\"coal\">\n        <td><span class=\"name\">Coal</span></td>\n        <td class=\"value\"><span class=\"generation\">156</span> MW</td>\n      </tr>\n          <tr id=\"newzealandgas\" class=\"gas\">\n        <td><span class=\"name\">Gas</span></td>\n        <td class=\"value\"><span class=\"generation\">188</span> MW</td>\n      </tr>\n          <tr id=\"newzealandgeothermal\" class=\"geothermal\">\n        <td><span class=\"name\">Geothermal</span></td>\n        <td class=\"value\"><span class=\"generation\">968</span> MW</td>\n      </tr>\n          <tr id=\"newzealandhydro\" class=\"hydro\">\n        <td><span class=\"name\">Hydro</span></td>\n        <td class=\"value\"><span class=\"generation\">1560</span> MW</td>\n      </tr>\n          <tr id=\"newzealanddieseloil\" class=\"dieseloil\">\n        <td><span class=\"name\">Diesel/Oil</span></td>\n        <td class=\"value\"><span class=\"generation\">0</span> MW</td>\n      </tr>\n          <tr id=\"newzealandsolar\" class=\"solar\">\n        <td><span class=\"name\">Solar</span></td>\n        <td class=\"value\"><span class=\"generation\">0</span> MW</td>\n      </tr>\n          <tr id=\"newzealandwind\" class=\"wind\">\n        <td><span class=\"name\">Wind</span></td>\n        <td class=\"value\"><span class=\"generation\">784</span> MW</td>\n      </tr>\n        </tbody>\n  </table>\n</div>\n\n      \n  </div>\n\n  </div>\n  <div class=\"col-md-8 col-12\">\n    \n  <div class=\"block block--loaddatagraph\">\n\n  \n            <h2>Load Data Totals</h2>\n        \n\n            <div class=\"live-data-date load-data-graph-update-time\">\n  <div class=\"ajax-progress\"><span></span></div>\n  <span class=\"update-text\">Updated</span>:\n  <time></time>\n</div>\n<div id=\"load-data-chart\"></div>\n\n      \n  </div>\n\n    \n  <div class=\"block block--hvdctransfersummary\">\n\n  \n            <h2>Today&#039;s HVDC Transfer Summary</h2>\n        \n\n            <div class=\"hvdc-today-wrapper\">\n  <div id=\"hvdc-today\"></div>\n</div>\n\n      \n  </div>\n\n    \n  <div class=\"block block--currentgenerationgraph\">\n\n  \n            <h2>Current Generation (MW)</h2>\n        \n\n            <div class=\"power-generation\">\n  <div id=\"pgen-graph\"></div>\n  <div class=\"info\">\n    <label for=\"pgen-date\">Total generation</label>\n    <span class=\"pgen-date\"></span>\n    <div class=\"totals\">\n      <div class=\"pgen-total\"><span class=\"total\"></span> MW</div>\n    </div>\n  </div>\n</div>\n\n      \n  </div>\n\n  </div>\n  <div class=\"col-12\">\n    \n  <div class=\"block block--recentnotices\">\n\n  \n            <h2>Recent Notices</h2>\n        \n\n            <div class=\"views-element-container\">\n<div class=\"view js-view-dom-id-5d9056abdb8cf6dd17e783fdb6ab3620c42241a04f1dd8b217749397becc0490 view-latest-notices\">\n       \n            <div class=\"view-header\">\n        <h3>Recent Customer Advice Notices</h3> <span>|</span> <a href=\"/system-operator/notices-and-power-system-reporting/customer-advice-notices-can\">View All</a>\n      </div>\n      \n        \n        \n            <div class=\"view-content\">\n        \n\n<div class=\"table-responsive\">\n  <table class=\"cols-2 table table-bordered\">\n    \n          <thead class=\"bg-light\">\n        <tr>\n                                                          <th id=\"view-nothing-table-column\" class=\"views-field views-field-nothing\" scope=\"col\">Notice</th>\n                                                          <th id=\"view-changed-table-column\" class=\"views-field views-field-changed\" scope=\"col\">Date</th>\n                  </tr>\n      </thead>\n    \n    <tbody>\n              <tr>\n                                                                                                      <td headers=\"view-nothing-table-column\" class=\"views-field views-field-nothing\">\n                        <span class=\"table-cell-header\">\n              Notice\n            </span><span class=\"file\">\n  <a href=\"https://static.transpower.co.nz/public/interfaces/can/CAN%20WPI%20Station%203%20to%20be%20classified%20as%20a%20Secondary%20Risk%205345998928.pdf?VersionId=jFL_XLNV8aAiMvSVEqHNxRsUuveMyN9G\" type=\"application/pdf\" target=\"_blank\"><span class=\"icon icon-pdf\" aria-hidden=\"true\"></span>\n<span class=\"description\">CAN WPI Station 3 to be classified as a Secondary Risk whilecommissioning</span></a>\n  <span>(PDF 132.09 KB)</span>\n<span>            </td>\n                                                                                                      <td headers=\"view-changed-table-column\" class=\"views-field views-field-changed\">\n                        <span class=\"table-cell-header\">\n              Date\n            </span><time datetime=\"2024-04-23T16:30:29+12:00\">23/04/2024</time>\n            </td>\n                  </tr>\n          </tbody>\n  </table>\n</div>\n\n      </div>\n      \n        \n        \n        \n        \n        </div>\n</div>\n<div class=\"views-element-container\">\n<div class=\"view js-view-dom-id-d712a50be557fc5038472a8a4e5f3ba0d03de62846c84c18624851b166c71fa4 view-latest-notices\">\n       \n            <div class=\"view-header\">\n        <h3>Recent CANs (CE/ECE)</h3> <span>|</span> <a href=\"/system-operator/notices-and-reporting/information-under-frequency-reserves-and-secondary-risk\">View All</a>\n      </div>\n      \n        \n        \n            <div class=\"view-content\">\n        \n\n<div class=\"table-responsive\">\n  <table class=\"cols-2 table table-bordered\">\n    \n          <thead class=\"bg-light\">\n        <tr>\n                                                          <th id=\"view-nothing-table-column--2\" class=\"views-field views-field-nothing\" scope=\"col\">Notice</th>\n                                                          <th id=\"view-changed-table-column--2\" class=\"views-field views-field-changed\" scope=\"col\">Date</th>\n                  </tr>\n      </thead>\n    \n    <tbody>\n              <tr>\n                                                                                                      <td headers=\"view-nothing-table-column--2\" class=\"views-field views-field-nothing\">\n                        <span class=\"table-cell-header\">\n              Notice\n            </span><span class=\"file\">\n  <a href=\"https://static.transpower.co.nz/public/interfaces/can/CAN%20Changes%20to%20the%20Reserve%20Management%20Tool%20%28RMT%29%203958261605.pdf?VersionId=IEW0NwBIE5yhm_AydD_iV3aMrnyApqWd\" type=\"application/pdf\" target=\"_blank\"><span class=\"icon icon-pdf\" aria-hidden=\"true\"></span>\n<span class=\"description\">CAN Changes to the Reserve Management Tool (RMT)</span></a>\n  <span>(PDF 139.62 KB)</span>\n<span>            </td>\n                                                                                                      <td headers=\"view-changed-table-column--2\" class=\"views-field views-field-changed\">\n                        <span class=\"table-cell-header\">\n              Date\n            </span><time datetime=\"2021-06-16T12:34:34+12:00\">16/06/2021</time>\n            </td>\n                  </tr>\n          </tbody>\n  </table>\n</div>\n\n      </div>\n      \n        \n        \n        \n        \n        </div>\n</div>\n<div class=\"views-element-container\">\n<div class=\"view js-view-dom-id-177d4e03c81ab96791f6d0d0a88c7e49cbdc657420d5f7de0c522ae33431d124 view-latest-notices\">\n       \n            <div class=\"view-header\">\n        <h3>Recent Excursion Notices</h3> <span>|</span> <a href=\"/system-operator/notices-and-power-system-reporting/excursion-notices\">View All</a>\n      </div>\n      \n        \n        \n            <div class=\"view-content\">\n        \n\n<div class=\"table-responsive\">\n  <table class=\"cols-2 table table-bordered\">\n    \n          <thead class=\"bg-light\">\n        <tr>\n                                                          <th id=\"view-nothing-table-column--3\" class=\"views-field views-field-nothing\" scope=\"col\">Notice</th>\n                                                          <th id=\"view-changed-table-column--3\" class=\"views-field views-field-changed\" scope=\"col\">Date</th>\n                  </tr>\n      </thead>\n    \n    <tbody>\n              <tr>\n                                                                                                      <td headers=\"view-nothing-table-column--3\" class=\"views-field views-field-nothing\">\n                        <span class=\"table-cell-header\">\n              Notice\n            </span><span class=\"file\">\n  <a href=\"https://static.transpower.co.nz/public/interfaces/exn/EXN%20Voltage%20South%20Island%20Highbank%20Generation%20Tripped%205347672514.pdf?VersionId=Y3g97Z2StQUtVr83fGXxN.F8giFc1c8a\" type=\"application/pdf\" target=\"_blank\"><span class=\"icon icon-pdf\" aria-hidden=\"true\"></span>\n<span class=\"description\">EXN Voltage South Island Highbank Generation Tripped</span></a>\n  <span>(PDF 30.15 KB)</span>\n<span>            </td>\n                                                                                                      <td headers=\"view-changed-table-column--3\" class=\"views-field views-field-changed\">\n                        <span class=\"table-cell-header\">\n              Date\n            </span><time datetime=\"2024-04-24T11:22:01+12:00\">24/04/2024</time>\n            </td>\n                  </tr>\n          </tbody>\n  </table>\n</div>\n\n      </div>\n      \n        \n        \n        \n        \n        </div>\n</div>\n<div class=\"views-element-container\">\n<div class=\"view js-view-dom-id-569eec2203f4ebbb9b9af844bd798e8cc952ee8d1253adfae7921a3509e7ff70 view-latest-notices\">\n       \n            <div class=\"view-header\">\n        <h3>Recent Formal Notices</h3> <span>|</span> <a href=\"/system-operator/notices-and-power-system-reporting/formal-notices\">View All</a>\n      </div>\n      \n        \n        \n            <div class=\"view-content\">\n        \n\n<div class=\"table-responsive\">\n  <table class=\"cols-2 table table-bordered\">\n    \n          <thead class=\"bg-light\">\n        <tr>\n                                                          <th id=\"view-nothing-table-column--4\" class=\"views-field views-field-nothing\" scope=\"col\">Notice</th>\n                                                          <th id=\"view-changed-table-column--4\" class=\"views-field views-field-changed\" scope=\"col\">Date</th>\n                  </tr>\n      </thead>\n    \n    <tbody>\n              <tr>\n                                                                                                      <td headers=\"view-nothing-table-column--4\" class=\"views-field views-field-nothing\">\n                        <span class=\"table-cell-header\">\n              Notice\n            </span><span class=\"file\">\n  <a href=\"https://static.transpower.co.nz/public/interfaces/gen-rpt/GEN%20RPT%20for%20Unplanned%20outage%20Bombay%204823615185.pdf?VersionId=LTnuaLqQ.ArmIe2y0eCdMqjG5DN07_6J\" type=\"application/pdf\" target=\"_blank\"><span class=\"icon icon-pdf\" aria-hidden=\"true\"></span>\n<span class=\"description\">GEN RPT for Unplanned outage Bombay</span></a>\n  <span>(PDF 45.49 KB)</span>\n<span>            </td>\n                                                                                                      <td headers=\"view-changed-table-column--4\" class=\"views-field views-field-changed\">\n                        <span class=\"table-cell-header\">\n              Date\n            </span><time datetime=\"2023-06-12T09:33:06+12:00\">12/06/2023</time>\n            </td>\n                  </tr>\n          </tbody>\n  </table>\n</div>\n\n      </div>\n      \n        \n        \n        \n        \n        </div>\n</div>\n\n      \n  </div>\n\n  </div>\n</div>\n\n</p></div>\n      \n    </div>\n  </article>\n\n      \n  </div>\n\n\n      </div>\n\n                        <div class=\"page__sidebar col-lg-3\">\n              \n  <div class=\"block block--tpow-secondary-menu\">\n\n  \n            <h2>System Operator</h2>\n        \n\n            \n  \n\n\n  <ul 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    "path": "electricitymap/contrib/parsers/tests/mocks/NZ/response_2024_04_24_18_00.html",
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by subscribing to our mailing lists and following our social channels\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15636\">Subscribe and Updates</a>\n              </li>\n      </ul>\n</div>\n                              </li>\n                                      <li class=\"nav-item dropdown\">\n                      <a href=\"/your-safety\" class=\"nav-link dropdown-bs-toggle\" data-bs-toggle=\"dropdown\" data-drupal-link-system-path=\"node/15358\">Your safety</a>\n                          <div class=\"dropdown-menu\">\n  <ul>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/your-safety/safety-submission-form\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15359\">Safety submission form</a>\n              </li>\n                      <li class=\"nav-item dropdown\">\n        <a href=\"/your-safety/star-awards\" class=\"dropdown-item\" data-drupal-link-system-path=\"node/15379\">STAR Awards</a>\n              </li>\n        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tabindex=\"-1\"></a>\n          <header class=\"page__header\">\n        <div class=\"container\">\n          <div class=\"block block--tpow-breadcrumbs\">\n\n  \n    \n\n              <nav aria-label=\"breadcrumb\" class=\"\">\n    <ol class=\"breadcrumb\">\n              <li class=\"breadcrumb-item \">\n                      <a href=\"/system-operator\">System Operator</a>\n                  </li>\n              <li class=\"breadcrumb-item \">\n                      <a href=\"/system-operator/live-system-and-market-data\">Live system and market data</a>\n                  </li>\n              <li class=\"breadcrumb-item active\">\n                      Consolidated live data \n                  </li>\n          </ol>\n  </nav>\n\n      \n  </div>\n        </div>\n      </header>\n    \n    \n              <div class=\"container\">\n                  <div class=\"row\">\n        \n              \n      <div class=\"page__content col-lg-9\">\n        <a id=\"page-content\" tab-index=\"-1\"></a>\n          <div data-drupal-messages-fallback class=\"hidden\"></div>\n\n  <div class=\"block block--tpow-page-title\">\n\n  \n    \n\n            \n\n\n  \n\n\n  <h1  class=\"page-title\">\n                  \n<span>Consolidated live data </span>\n\n            </h1>\n\n\n      \n  </div>\n\n  <div class=\"block block--tpow-content block--system-main\">\n\n  \n    \n\n            \n\n\n<article class=\"node page page--full\">\n  \n  \n\n      \n    \n    <div class=\"node__content\">\n      \n            <div class=\"field field--name-body field--type-text-with-summary field--label-hidden field__item\"><p>HVDC data and Generation data sourced from <a href=\"https://app.em6.co.nz/\" target=\"_blank\">em6</a>.</p>\n\n<p><div class=\"row\">\n  <div class=\"col-md-4 col-12\">\n    \n  <div class=\"block block--livedatasummary\">\n\n  \n            <h2>Live Data Summary</h2>\n        \n\n            <div class=\"live-data-summary\">\n  <span class=\"ajax-progress\"><span class=\"throbber\"></span>Updating...</span>\n  <span class=\"last-updated\" style=\"display: none;\">Updated: <time datetime=\"\"></time></span>\n  <div class=\"content\">\n    \n  </div>\n</div>\n\n      \n  </div>\n\n    \n  <div class=\"block block--renewablesgenerating\">\n\n  \n            <h2>% Renewables Generating</h2>\n        \n\n            <div class=\"renewables-gauge\">\n  <div class=\"renewables-updated renewables-update-time\">\n    <span class=\"update-text\">% Renewables (as at)</span>:\n    <time><span class=\"update-time\"></span></time>\n    <div class=\"ajax-progress\"><span></span></div>\n  </div>\n  <div id=\"renewable-pgen-gauge\"></div>\n</div>\n\n      \n  </div>\n\n    \n  <div class=\"block block--currentgenerationtable\">\n\n  \n            <h2>Current Generation (MW)</h2>\n        \n\n            <div class=\"power-generation\">\n  <table id=\"pgen-table\" class=\"table table-striped totals\">\n    <thead>\n    <tr>\n      <th>Power Generation</th>\n      <th><span class=\"pgen-date\">(as at) 25 Apr 2024 06:00</span></th>\n    </tr>\n    </thead>\n    <tbody>\n          <tr id=\"newzealandbattery\" class=\"battery\">\n        <td><span class=\"name\">Battery</span></td>\n        <td class=\"value\"><span class=\"generation\">0</span> MW</td>\n      </tr>\n          <tr id=\"newzealandcogen\" class=\"cogen\">\n        <td><span class=\"name\">Co-Gen</span></td>\n        <td class=\"value\"><span class=\"generation\">117</span> MW</td>\n      </tr>\n          <tr id=\"newzealandcoal\" class=\"coal\">\n        <td><span class=\"name\">Coal</span></td>\n        <td class=\"value\"><span class=\"generation\">156</span> MW</td>\n      </tr>\n          <tr id=\"newzealandgas\" class=\"gas\">\n        <td><span class=\"name\">Gas</span></td>\n        <td class=\"value\"><span class=\"generation\">252</span> MW</td>\n      </tr>\n          <tr id=\"newzealandgeothermal\" class=\"geothermal\">\n        <td><span class=\"name\">Geothermal</span></td>\n        <td class=\"value\"><span class=\"generation\">964</span> MW</td>\n      </tr>\n          <tr id=\"newzealandhydro\" class=\"hydro\">\n        <td><span class=\"name\">Hydro</span></td>\n        <td class=\"value\"><span class=\"generation\">1644</span> MW</td>\n      </tr>\n          <tr id=\"newzealanddieseloil\" class=\"dieseloil\">\n        <td><span class=\"name\">Diesel/Oil</span></td>\n        <td class=\"value\"><span class=\"generation\">0</span> MW</td>\n      </tr>\n          <tr id=\"newzealandsolar\" class=\"solar\">\n        <td><span class=\"name\">Solar</span></td>\n        <td class=\"value\"><span class=\"generation\">0</span> MW</td>\n      </tr>\n          <tr id=\"newzealandwind\" class=\"wind\">\n        <td><span class=\"name\">Wind</span></td>\n        <td class=\"value\"><span class=\"generation\">814</span> MW</td>\n      </tr>\n        </tbody>\n  </table>\n</div>\n\n      \n  </div>\n\n  </div>\n  <div class=\"col-md-8 col-12\">\n    \n  <div class=\"block block--loaddatagraph\">\n\n  \n            <h2>Load Data Totals</h2>\n        \n\n            <div class=\"live-data-date load-data-graph-update-time\">\n  <div class=\"ajax-progress\"><span></span></div>\n  <span class=\"update-text\">Updated</span>:\n  <time></time>\n</div>\n<div id=\"load-data-chart\"></div>\n\n      \n  </div>\n\n    \n  <div class=\"block block--hvdctransfersummary\">\n\n  \n            <h2>Today&#039;s HVDC Transfer Summary</h2>\n        \n\n            <div class=\"hvdc-today-wrapper\">\n  <div id=\"hvdc-today\"></div>\n</div>\n\n      \n  </div>\n\n    \n  <div class=\"block block--currentgenerationgraph\">\n\n  \n            <h2>Current Generation (MW)</h2>\n        \n\n            <div class=\"power-generation\">\n  <div id=\"pgen-graph\"></div>\n  <div class=\"info\">\n    <label for=\"pgen-date\">Total generation</label>\n    <span class=\"pgen-date\"></span>\n    <div class=\"totals\">\n      <div class=\"pgen-total\"><span class=\"total\"></span> MW</div>\n    </div>\n  </div>\n</div>\n\n      \n  </div>\n\n  </div>\n  <div class=\"col-12\">\n    \n  <div class=\"block block--recentnotices\">\n\n  \n            <h2>Recent Notices</h2>\n        \n\n            <div class=\"views-element-container\">\n<div class=\"view js-view-dom-id-5d9056abdb8cf6dd17e783fdb6ab3620c42241a04f1dd8b217749397becc0490 view-latest-notices\">\n       \n            <div class=\"view-header\">\n        <h3>Recent Customer Advice Notices</h3> <span>|</span> <a href=\"/system-operator/notices-and-power-system-reporting/customer-advice-notices-can\">View All</a>\n      </div>\n      \n        \n        \n            <div class=\"view-content\">\n        \n\n<div class=\"table-responsive\">\n  <table class=\"cols-2 table table-bordered\">\n    \n          <thead class=\"bg-light\">\n        <tr>\n                                                          <th id=\"view-nothing-table-column\" class=\"views-field views-field-nothing\" scope=\"col\">Notice</th>\n                                                          <th id=\"view-changed-table-column\" class=\"views-field views-field-changed\" scope=\"col\">Date</th>\n                  </tr>\n      </thead>\n    \n    <tbody>\n              <tr>\n                                                                                                      <td headers=\"view-nothing-table-column\" class=\"views-field views-field-nothing\">\n                        <span class=\"table-cell-header\">\n              Notice\n            </span><span class=\"file\">\n  <a href=\"https://static.transpower.co.nz/public/interfaces/can/CAN%20WPI%20Station%203%20to%20be%20classified%20as%20a%20Secondary%20Risk%205345998928.pdf?VersionId=jFL_XLNV8aAiMvSVEqHNxRsUuveMyN9G\" type=\"application/pdf\" target=\"_blank\"><span class=\"icon icon-pdf\" aria-hidden=\"true\"></span>\n<span class=\"description\">CAN WPI Station 3 to be classified as a Secondary Risk whilecommissioning</span></a>\n  <span>(PDF 132.09 KB)</span>\n<span>            </td>\n                                                                                                      <td headers=\"view-changed-table-column\" class=\"views-field views-field-changed\">\n                        <span class=\"table-cell-header\">\n              Date\n            </span><time datetime=\"2024-04-23T16:30:29+12:00\">23/04/2024</time>\n            </td>\n                  </tr>\n          </tbody>\n  </table>\n</div>\n\n      </div>\n      \n        \n        \n        \n        \n        </div>\n</div>\n<div class=\"views-element-container\">\n<div class=\"view js-view-dom-id-d712a50be557fc5038472a8a4e5f3ba0d03de62846c84c18624851b166c71fa4 view-latest-notices\">\n       \n            <div class=\"view-header\">\n        <h3>Recent CANs (CE/ECE)</h3> <span>|</span> <a href=\"/system-operator/notices-and-reporting/information-under-frequency-reserves-and-secondary-risk\">View All</a>\n      </div>\n      \n        \n        \n            <div class=\"view-content\">\n        \n\n<div class=\"table-responsive\">\n  <table class=\"cols-2 table table-bordered\">\n    \n          <thead class=\"bg-light\">\n        <tr>\n                                                          <th id=\"view-nothing-table-column--2\" class=\"views-field views-field-nothing\" scope=\"col\">Notice</th>\n                                                          <th id=\"view-changed-table-column--2\" class=\"views-field views-field-changed\" scope=\"col\">Date</th>\n                  </tr>\n      </thead>\n    \n    <tbody>\n              <tr>\n                                                                                                      <td headers=\"view-nothing-table-column--2\" class=\"views-field views-field-nothing\">\n                        <span class=\"table-cell-header\">\n              Notice\n            </span><span class=\"file\">\n  <a href=\"https://static.transpower.co.nz/public/interfaces/can/CAN%20Changes%20to%20the%20Reserve%20Management%20Tool%20%28RMT%29%203958261605.pdf?VersionId=IEW0NwBIE5yhm_AydD_iV3aMrnyApqWd\" type=\"application/pdf\" target=\"_blank\"><span class=\"icon icon-pdf\" aria-hidden=\"true\"></span>\n<span class=\"description\">CAN Changes to the Reserve Management Tool (RMT)</span></a>\n  <span>(PDF 139.62 KB)</span>\n<span>            </td>\n                                                                                                      <td headers=\"view-changed-table-column--2\" class=\"views-field views-field-changed\">\n                        <span class=\"table-cell-header\">\n              Date\n            </span><time datetime=\"2021-06-16T12:34:34+12:00\">16/06/2021</time>\n            </td>\n                  </tr>\n          </tbody>\n  </table>\n</div>\n\n      </div>\n      \n        \n        \n        \n        \n        </div>\n</div>\n<div class=\"views-element-container\">\n<div class=\"view js-view-dom-id-177d4e03c81ab96791f6d0d0a88c7e49cbdc657420d5f7de0c522ae33431d124 view-latest-notices\">\n       \n            <div class=\"view-header\">\n        <h3>Recent Excursion Notices</h3> <span>|</span> <a href=\"/system-operator/notices-and-power-system-reporting/excursion-notices\">View All</a>\n      </div>\n      \n        \n        \n            <div class=\"view-content\">\n        \n\n<div class=\"table-responsive\">\n  <table class=\"cols-2 table table-bordered\">\n    \n          <thead class=\"bg-light\">\n        <tr>\n                                                          <th id=\"view-nothing-table-column--3\" class=\"views-field views-field-nothing\" scope=\"col\">Notice</th>\n                                                          <th id=\"view-changed-table-column--3\" class=\"views-field views-field-changed\" scope=\"col\">Date</th>\n                  </tr>\n      </thead>\n    \n    <tbody>\n              <tr>\n                                                                                                      <td headers=\"view-nothing-table-column--3\" class=\"views-field views-field-nothing\">\n                        <span class=\"table-cell-header\">\n              Notice\n            </span><span class=\"file\">\n  <a href=\"https://static.transpower.co.nz/public/interfaces/exn/EXN%20Voltage%20South%20Island%20Highbank%20Generation%20Tripped%205347672514.pdf?VersionId=Y3g97Z2StQUtVr83fGXxN.F8giFc1c8a\" type=\"application/pdf\" target=\"_blank\"><span class=\"icon icon-pdf\" aria-hidden=\"true\"></span>\n<span class=\"description\">EXN Voltage South Island Highbank Generation Tripped</span></a>\n  <span>(PDF 30.15 KB)</span>\n<span>            </td>\n                                                                                                      <td headers=\"view-changed-table-column--3\" class=\"views-field views-field-changed\">\n                        <span class=\"table-cell-header\">\n              Date\n            </span><time datetime=\"2024-04-24T11:22:01+12:00\">24/04/2024</time>\n            </td>\n                  </tr>\n          </tbody>\n  </table>\n</div>\n\n      </div>\n      \n        \n        \n        \n        \n        </div>\n</div>\n<div class=\"views-element-container\">\n<div class=\"view js-view-dom-id-569eec2203f4ebbb9b9af844bd798e8cc952ee8d1253adfae7921a3509e7ff70 view-latest-notices\">\n       \n            <div class=\"view-header\">\n        <h3>Recent Formal Notices</h3> <span>|</span> <a href=\"/system-operator/notices-and-power-system-reporting/formal-notices\">View All</a>\n      </div>\n      \n        \n        \n            <div class=\"view-content\">\n        \n\n<div class=\"table-responsive\">\n  <table class=\"cols-2 table table-bordered\">\n    \n          <thead class=\"bg-light\">\n        <tr>\n                                                          <th id=\"view-nothing-table-column--4\" class=\"views-field views-field-nothing\" scope=\"col\">Notice</th>\n                                                          <th id=\"view-changed-table-column--4\" class=\"views-field views-field-changed\" scope=\"col\">Date</th>\n                  </tr>\n      </thead>\n    \n    <tbody>\n              <tr>\n                                                                                                      <td headers=\"view-nothing-table-column--4\" class=\"views-field views-field-nothing\">\n                        <span class=\"table-cell-header\">\n              Notice\n            </span><span class=\"file\">\n  <a href=\"https://static.transpower.co.nz/public/interfaces/gen-rpt/GEN%20RPT%20for%20Unplanned%20outage%20Bombay%204823615185.pdf?VersionId=LTnuaLqQ.ArmIe2y0eCdMqjG5DN07_6J\" type=\"application/pdf\" target=\"_blank\"><span class=\"icon icon-pdf\" aria-hidden=\"true\"></span>\n<span class=\"description\">GEN RPT for Unplanned outage Bombay</span></a>\n  <span>(PDF 45.49 KB)</span>\n<span>            </td>\n                                                                                                      <td headers=\"view-changed-table-column--4\" class=\"views-field views-field-changed\">\n                        <span class=\"table-cell-header\">\n              Date\n            </span><time datetime=\"2023-06-12T09:33:06+12:00\">12/06/2023</time>\n            </td>\n                  </tr>\n          </tbody>\n  </table>\n</div>\n\n      </div>\n      \n        \n        \n        \n        \n        </div>\n</div>\n\n      \n  </div>\n\n  </div>\n</div>\n\n</p></div>\n      \n    </div>\n  </article>\n\n      \n  </div>\n\n\n      </div>\n\n                        <div class=\"page__sidebar col-lg-3\">\n              \n  <div class=\"block block--tpow-secondary-menu\">\n\n  \n            <h2>System Operator</h2>\n        \n\n            \n  \n\n\n  <ul 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    "content": "{\n    \"Data\": \"2018-01-27T20:19:00-02:00\",\n    \"sudesteECentroOeste\": {\n        \"geracao\": {\n            \"total\": 40224.28,\n            \"hidraulica\": 24344.7949,\n            \"termica\": 2507.78833,\n            \"eolica\": 4.2,\n            \"nuclear\": 1829.29529,\n            \"solar\": 2.85705,\n            \"itaipu50HzBrasil\": 4684.81,\n            \"itaipu60Hz\": 6858.44873\n        },\n        \"cargaVerificada\": 42052.4,\n        \"importacao\": 2816.56787,\n        \"exportacao\": 988.4497\n    },\n    \"sul\": {\n        \"geracao\": {\n            \"total\": 11444.7012,\n            \"hidraulica\": 9273.746,\n            \"termica\": 855.8522,\n            \"eolica\": 1315.103,\n            \"nuclear\": 0.0,\n            \"solar\": 0.0\n        },\n        \"cargaVerificada\": 11648.0244,\n        \"importacao\": 203.333054,\n        \"exportacao\": 0.00993589\n    },\n    \"nordeste\": {\n        \"geracao\": {\n            \"total\": 7459.687,\n            \"hidraulica\": 1921.36816,\n            \"termica\": 2700.472,\n            \"eolica\": 2837.92188,\n            \"nuclear\": 0.0,\n            \"solar\": -0.0751945451\n        },\n        \"cargaVerificada\": 11212.625,\n        \"importacao\": 3752.88477,\n        \"exportacao\": 0.0\n    },\n    \"norte\": {\n        \"geracao\": {\n            \"total\": 11360.0811,\n            \"hidraulica\": 9856.75,\n            \"termica\": 1346.79175,\n            \"eolica\": 156.539352,\n            \"nuclear\": 0.0,\n            \"solar\": 0.0\n        },\n        \"cargaVerificada\": 5575.745,\n        \"importacao\": 0.0,\n        \"exportacao\": 5784.336\n    },\n    \"internacional\": {\n        \"argentina\": 0.00993589,\n        \"paraguai\": 0.0,\n        \"uruguai\": 14.0\n    },\n    \"intercambio\": {\n        \"internacional_sul\": -0.00993589,\n        \"sul_sudeste\": -203.333054,\n        \"sudeste_nordeste\": 785.116638,\n        \"sudeste_norteFic\": -2816.56787,\n        \"norte_norteFic\": 5784.336,\n        \"norteFic_nordeste\": 2967.768\n    }\n}"
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    "content": "{\n    \"Data\": \"2018-01-27T20:19:00-02:00\",\n    \"sudesteECentroOeste\": {\n        \"geracao\": {\n            \"total\": 40224.28,\n            \"hidraulica\": 24344.7949,\n            \"termica\": 2507.78833,\n            \"eolica\": 4.2,\n            \"nuclear\": 1829.29529,\n            \"solar\": -2.85705,\n            \"itaipu50HzBrasil\": 4684.81,\n            \"itaipu60Hz\": 6858.44873\n        },\n        \"cargaVerificada\": 42052.4,\n        \"importacao\": 2816.56787,\n        \"exportacao\": 988.4497\n    },\n    \"sul\": {\n        \"geracao\": {\n            \"total\": 11444.7012,\n            \"hidraulica\": 9273.746,\n            \"termica\": 855.8522,\n            \"eolica\": 1315.103,\n            \"nuclear\": 0.0,\n            \"solar\": 0.0\n        },\n        \"cargaVerificada\": 11648.0244,\n        \"importacao\": 203.333054,\n        \"exportacao\": 0.00993589\n    },\n    \"nordeste\": {\n        \"geracao\": {\n            \"total\": 7459.687,\n            \"hidraulica\": 1921.36816,\n            \"termica\": 2700.472,\n            \"eolica\": 2837.92188,\n            \"nuclear\": 0.0,\n            \"solar\": -0.0751945451\n        },\n        \"cargaVerificada\": 11212.625,\n        \"importacao\": 3752.88477,\n        \"exportacao\": 0.0\n    },\n    \"norte\": {\n        \"geracao\": {\n            \"total\": 11360.0811,\n            \"hidraulica\": 9856.75,\n            \"termica\": 1346.79175,\n            \"eolica\": 156.539352,\n            \"nuclear\": 0.0,\n            \"solar\": 0.0\n        },\n        \"cargaVerificada\": 5575.745,\n        \"importacao\": 0.0,\n        \"exportacao\": 5784.336\n    },\n    \"internacional\": {\n        \"argentina\": 0.00993589,\n        \"paraguai\": 0.0,\n        \"uruguai\": 14.0\n    },\n    \"intercambio\": {\n        \"internacional_sul\": -0.00993589,\n        \"sul_sudeste\": -203.333054,\n        \"sudeste_nordeste\": 785.116638,\n        \"sudeste_norteFic\": -2816.56787,\n        \"norte_norteFic\": 5784.336,\n        \"norteFic_nordeste\": 2967.768\n    }\n}"
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    "content": "{\n  \"Data\": \"2025-07-22T08:54:00-03:00\",\n  \"sudesteECentroOeste\": {\n    \"geracao\": {\n      \"total\": 39440.89,\n      \"hidraulica\": 14335.7988,\n      \"termica\": 8401.434,\n      \"eolica\": 165.185547,\n      \"nuclear\": 2011.05078,\n      \"solar\": 11259.3008,\n      \"itaipu50HzBrasil\": 901.34,\n      \"itaipu60Hz\": 2366.781\n    },\n    \"cargaVerificada\": 43949.43,\n    \"importacao\": 8866.092,\n    \"exportacao\": 4357.55273\n  },\n  \"sul\": {\n    \"geracao\": {\n      \"total\": 12510.74,\n      \"hidraulica\": 8748.055,\n      \"termica\": 1583.74609,\n      \"eolica\": 342.625763,\n      \"nuclear\": 0.0,\n      \"solar\": 1836.314\n    },\n    \"cargaVerificada\": 15927.1436,\n    \"importacao\": 4357.55273,\n    \"exportacao\": 941.1496\n  },\n  \"nordeste\": {\n    \"geracao\": {\n      \"total\": 21959.5313,\n      \"hidraulica\": 2081.71338,\n      \"termica\": 153.992935,\n      \"eolica\": 11871.0967,\n      \"nuclear\": 0.0,\n      \"solar\": 7852.72754\n    },\n    \"cargaVerificada\": 12208.2559,\n    \"importacao\": 0.0,\n    \"exportacao\": 9750.228\n  },\n  \"norte\": {\n    \"geracao\": {\n      \"total\": 7213.76758,\n      \"hidraulica\": 2854.34839,\n      \"termica\": 2756.85742,\n      \"eolica\": 324.584167,\n      \"nuclear\": 0.0,\n      \"solar\": 1277.97778\n    },\n    \"cargaVerificada\": 8097.90332,\n    \"importacao\": 884.135559,\n    \"exportacao\": 0.0\n  },\n  \"internacional\": {\n    \"argentina\": 942.2021,\n    \"paraguai\": 0.0,\n    \"uruguai\": -0.9615\n  },\n  \"intercambio\": {\n    \"internacional_sul\": -941.1496,\n    \"sul_sudeste\": -4357.55273,\n    \"sudeste_nordeste\": -5336.844,\n    \"sudeste_norteFic\": -3529.24756,\n    \"norte_norteFic\": -884.135559,\n    \"norteFic_nordeste\": -4413.3833\n  }\n}"
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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/OPENNEM/OPENNEM_AU-NSW.v4.json",
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  {
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  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/OPENNEM/OPENNEM_AU-QLD.v4.json",
    "content": "{\n  \"version\": \"4.4.5\",\n  \"created_at\": \"2025-07-17T21:16:04+10:00\",\n  \"success\": true,\n  \"error\": null,\n  \"data\": [\n    {\n      \"network_code\": \"NEM\",\n      \"metric\": \"power\",\n      \"unit\": \"MW\",\n      \"interval\": \"5m\",\n      \"date_start\": \"2025-07-10T21:15:00+10:00\",\n      \"date_end\": \"2025-07-11T21:10:00+10:00\",\n      \"groupings\": [\n        \"network_region\",\n        \"fueltech\"\n      ],\n      \"results\": [\n        {\n          \"name\": \"power_QLD1|BATTERY_CHARGING\",\n          \"date_start\": \"2025-07-10T21:15:00+10:00\",\n          \"date_end\": \"2025-07-11T21:10:00+10:00\",\n          \"columns\": {\n            \"region\": \"QLD1\",\n            \"fueltech\": \"BATTERY_CHARGING\"\n          },\n          \"data\": [\n            [\n              \"2025-07-10T21:15:00+10:00\",\n              4.3509\n            ],\n            [\n              \"2025-07-10T21:20:00+10:00\",\n              0.1838\n   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  {
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  {
    "path": "electricitymap/contrib/parsers/tests/mocks/OPENNEM/OPENNEM_price_AU-SA.json",
    "content": "{\n    \"version\": \"4.3.2\",\n    \"created_at\": \"2025-12-10T17:05:12+11:00\",\n    \"success\": true,\n    \"error\": null,\n    \"data\": [\n        {\n            \"network_code\": \"NEM\",\n            \"metric\": \"price\",\n            \"unit\": \"$/MWh\",\n            \"interval\": \"5m\",\n            \"date_start\": \"2019-12-25T11:00:00+10:00\",\n            \"date_end\": \"2020-01-01T10:55:00+10:00\",\n            \"groupings\": [],\n            \"results\": [\n                {\n                    \"name\": \"price_SA1\",\n                    \"date_start\": \"2019-12-25T11:00:00+10:00\",\n                    \"date_end\": \"2020-01-01T10:55:00+10:00\",\n                    \"columns\": {\n                        \"region\": \"SA1\"\n                    },\n                    \"data\": [\n                        [\n                            \"2019-12-25T11:00:00+10:00\",\n                            40.01\n                        ],\n                 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    "path": "electricitymap/contrib/parsers/tests/mocks/PA_nominal_generation.html",
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4.19 19.35 17.79 15.17 30.36zm14.66 57.2l15.52-46.55c3.47-1.29 7.13-2.23 11.05-2.23 17.67 0 32 14.33 32 32s-14.33 32-32 32c-11.38-.01-20.89-6.28-26.57-15.22zM480 384c-17.67 0-32-14.33-32-32s14.33-32 32-32 32 14.33 32 32-14.33 32-32 32z\"></path></svg></i><span class=\"app-menu__label pace\">Datos del <span class=\"notranslate\">SIN</span></span>\n                </a>\n            </li>\n            <li>\n                <a class=\"app-menu__item active\">\n                    <i class=\"app-menu__icon\" data-fa-i2svg=\"\"><svg class=\"svg-inline--fa fa-chart-pie fa-w-17 fa-1x\" aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"chart-pie\" role=\"img\" xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 544 512\" data-fa-i2svg=\"\"><path fill=\"currentColor\" d=\"M527.79 288H290.5l158.03 158.03c6.04 6.04 15.98 6.53 22.19.68 38.7-36.46 65.32-85.61 73.13-140.86 1.34-9.46-6.51-17.85-16.06-17.85zm-15.83-64.8C503.72 103.74 408.26 8.28 288.8.04 279.68-.59 272 7.1 272 16.24V240h223.77c9.14 0 16.82-7.68 16.19-16.8zM224 288V50.71c0-9.55-8.39-17.4-17.84-16.06C86.99 51.49-4.1 155.6.14 280.37 4.5 408.51 114.83 513.59 243.03 511.98c50.4-.63 96.97-16.87 135.26-44.03 7.9-5.6 8.42-17.23 1.57-24.08L224 288z\"></path></svg></i><span class=\"app-menu__label pace\">Generación</span>\n                </a>\n            </li>\n            <li>\n                <a class=\"app-menu__item\">\n                    <i class=\"app-menu__icon\" data-fa-i2svg=\"\"><svg class=\"svg-inline--fa fa-water fa-w-18 fa-1x\" aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"water\" role=\"img\" xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 576 512\" data-fa-i2svg=\"\"><path fill=\"currentColor\" d=\"M562.1 383.9c-21.5-2.4-42.1-10.5-57.9-22.9-14.1-11.1-34.2-11.3-48.2 0-37.9 30.4-107.2 30.4-145.7-1.5-13.5-11.2-33-9.1-46.7 1.8-38 30.1-106.9 30-145.2-1.7-13.5-11.2-33.3-8.9-47.1 2-15.5 12.2-36 20.1-57.7 22.4-7.9.8-13.6 7.8-13.6 15.7v32.2c0 9.1 7.6 16.8 16.7 16 28.8-2.5 56.1-11.4 79.4-25.9 56.5 34.6 137 34.1 192 0 56.5 34.6 137 34.1 192 0 23.3 14.2 50.9 23.3 79.1 25.8 9.1.8 16.7-6.9 16.7-16v-31.6c.1-8-5.7-15.4-13.8-16.3zm0-144c-21.5-2.4-42.1-10.5-57.9-22.9-14.1-11.1-34.2-11.3-48.2 0-37.9 30.4-107.2 30.4-145.7-1.5-13.5-11.2-33-9.1-46.7 1.8-38 30.1-106.9 30-145.2-1.7-13.5-11.2-33.3-8.9-47.1 2-15.5 12.2-36 20.1-57.7 22.4-7.9.8-13.6 7.8-13.6 15.7v32.2c0 9.1 7.6 16.8 16.7 16 28.8-2.5 56.1-11.4 79.4-25.9 56.5 34.6 137 34.1 192 0 56.5 34.6 137 34.1 192 0 23.3 14.2 50.9 23.3 79.1 25.8 9.1.8 16.7-6.9 16.7-16v-31.6c.1-8-5.7-15.4-13.8-16.3zm0-144C540.6 93.4 520 85.4 504.2 73 490.1 61.9 470 61.7 456 73c-37.9 30.4-107.2 30.4-145.7-1.5-13.5-11.2-33-9.1-46.7 1.8-38 30.1-106.9 30-145.2-1.7-13.5-11.2-33.3-8.9-47.1 2-15.5 12.2-36 20.1-57.7 22.4-7.9.8-13.6 7.8-13.6 15.7v32.2c0 9.1 7.6 16.8 16.7 16 28.8-2.5 56.1-11.4 79.4-25.9 56.5 34.6 137 34.1 192 0 56.5 34.6 137 34.1 192 0 23.3 14.2 50.9 23.3 79.1 25.8 9.1.8 16.7-6.9 16.7-16v-31.6c.1-8-5.7-15.4-13.8-16.3z\"></path></svg></i><span class=\"app-menu__label pace\">Seguimiento a la MRG</span>\n                </a>\n            </li>\n            <li>\n                <a class=\"app-menu__item\">\n                    <i class=\"app-menu__icon\" data-fa-i2svg=\"\"><svg class=\"svg-inline--fa fa-sitemap fa-w-20 fa-1x\" aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"sitemap\" role=\"img\" xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 640 512\" data-fa-i2svg=\"\"><path fill=\"currentColor\" d=\"M128 352H32c-17.67 0-32 14.33-32 32v96c0 17.67 14.33 32 32 32h96c17.67 0 32-14.33 32-32v-96c0-17.67-14.33-32-32-32zm-24-80h192v48h48v-48h192v48h48v-57.59c0-21.17-17.23-38.41-38.41-38.41H344v-64h40c17.67 0 32-14.33 32-32V32c0-17.67-14.33-32-32-32H256c-17.67 0-32 14.33-32 32v96c0 17.67 14.33 32 32 32h40v64H94.41C73.23 224 56 241.23 56 262.41V320h48v-48zm264 80h-96c-17.67 0-32 14.33-32 32v96c0 17.67 14.33 32 32 32h96c17.67 0 32-14.33 32-32v-96c0-17.67-14.33-32-32-32zm240 0h-96c-17.67 0-32 14.33-32 32v96c0 17.67 14.33 32 32 32h96c17.67 0 32-14.33 32-32v-96c0-17.67-14.33-32-32-32z\"></path></svg></i><span class=\"app-menu__label pace\">Interconexión</span>\n                </a>\n            </li>\n            <li>\n                <a class=\"app-menu__item\">\n                    <i class=\"app-menu__icon\" data-fa-i2svg=\"\"><svg class=\"svg-inline--fa fa-route fa-w-16 fa-1x\" aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"route\" role=\"img\" xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 512 512\" data-fa-i2svg=\"\"><path fill=\"currentColor\" d=\"M416 320h-96c-17.6 0-32-14.4-32-32s14.4-32 32-32h96s96-107 96-160-43-96-96-96-96 43-96 96c0 25.5 22.2 63.4 45.3 96H320c-52.9 0-96 43.1-96 96s43.1 96 96 96h96c17.6 0 32 14.4 32 32s-14.4 32-32 32H185.5c-16 24.8-33.8 47.7-47.3 64H416c52.9 0 96-43.1 96-96s-43.1-96-96-96zm0-256c17.7 0 32 14.3 32 32s-14.3 32-32 32-32-14.3-32-32 14.3-32 32-32zM96 256c-53 0-96 43-96 96s96 160 96 160 96-107 96-160-43-96-96-96zm0 128c-17.7 0-32-14.3-32-32s14.3-32 32-32 32 14.3 32 32-14.3 32-32 32z\"></path></svg></i><span class=\"app-menu__label pace\">Flujo Occidente</span>\n                </a>\n            </li>\n            <li>\n                <a class=\"app-menu__item\">\n                    <i class=\"app-menu__icon\" data-fa-i2svg=\"\"><svg class=\"svg-inline--fa fa-user-lock fa-w-20 fa-1x\" aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"user-lock\" role=\"img\" xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 640 512\" data-fa-i2svg=\"\"><path fill=\"currentColor\" d=\"M224 256A128 128 0 1 0 96 128a128 128 0 0 0 128 128zm96 64a63.08 63.08 0 0 1 8.1-30.5c-4.8-.5-9.5-1.5-14.5-1.5h-16.7a174.08 174.08 0 0 1-145.8 0h-16.7A134.43 134.43 0 0 0 0 422.4V464a48 48 0 0 0 48 48h280.9a63.54 63.54 0 0 1-8.9-32zm288-32h-32v-80a80 80 0 0 0-160 0v80h-32a32 32 0 0 0-32 32v160a32 32 0 0 0 32 32h224a32 32 0 0 0 32-32V320a32 32 0 0 0-32-32zM496 432a32 32 0 1 1 32-32 32 32 0 0 1-32 32zm32-144h-64v-80a32 32 0 0 1 64 0z\"></path></svg></i><span class=\"app-menu__label pace\">Privado</span>\n                </a>\n            </li>\n        </ul>\n    </aside>\n    <main class=\"app-content\">\n        <div class=\"app-title\">\n            <div>\n                <h1>Centro Nacional de Despacho</h1>\n                <h3>\n                    <i class=\"\" data-fa-i2svg=\"\"><svg class=\"svg-inline--fa fa-chart-pie fa-w-17\" aria-hidden=\"true\" focusable=\"false\" data-prefix=\"fas\" data-icon=\"chart-pie\" role=\"img\" xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 544 512\" data-fa-i2svg=\"\"><path fill=\"currentColor\" d=\"M527.79 288H290.5l158.03 158.03c6.04 6.04 15.98 6.53 22.19.68 38.7-36.46 65.32-85.61 73.13-140.86 1.34-9.46-6.51-17.85-16.06-17.85zm-15.83-64.8C503.72 103.74 408.26 8.28 288.8.04 279.68-.59 272 7.1 272 16.24V240h223.77c9.14 0 16.82-7.68 16.19-16.8zM224 288V50.71c0-9.55-8.39-17.4-17.84-16.06C86.99 51.49-4.1 155.6.14 280.37 4.5 408.51 114.83 513.59 243.03 511.98c50.4-.63 96.97-16.87 135.26-44.03 7.9-5.6 8.42-17.23 1.57-24.08L224 288z\"></path></svg></i> Generación\n                </h3>\n                <!-- <p>Start a beautiful journey here</p> -->\n            </div>\n            <!-- <ul class=\"app-breadcrumb breadcrumb\">\n              <li class=\"breadcrumb-item\"><i class=\"fa fa-home fa-lg\"></i></li>\n              <li class=\"breadcrumb-item\"><a href=\"#\">Blank Page</a></li>\n            </ul> -->\n            <h3 class=\"app-breadcrumb breadcrumb sitr-update\">30-diciembre-2021 9:58:37</h3>\n        </div>\n\n        <div class=\"app-title-msg sr-only\" role=\"alert\">\n            <span></span>\n        </div>\n\n\n        <div class=\"row\">\n            <div class=\"col-md-6\">\n                <div class=\"tile\">\n                    <h3 class=\"tile-title\">Energía Renovable vs. Energía Térmica</h3>\n                    <div class=\"tile-body\">\n                        <div class=\"sitr-pie\" id=\"sitr-energy-pie\" style=\"height: 42.5vh; min-height: 250px; width: 100%; user-select: none; position: relative;\" _echarts_instance_=\"ec_1640876263963\"><div style=\"position: relative; width: 1038px; height: 564px; padding: 0px; margin: 0px; border-width: 0px;\"><canvas style=\"position: absolute; left: 0px; top: 0px; width: 1038px; height: 564px; user-select: none; padding: 0px; margin: 0px; border-width: 0px;\" data-zr-dom-id=\"zr_0\" width=\"1038\" height=\"564\"></canvas></div><div class=\"\"></div></div>\n\n                    </div>\n                </div>\n            </div>\n            <div class=\"col-md-6\">\n                <div class=\"tile\">\n                    <div class=\"tile-title\">\n                        <h3 class=\"title\">Tipos de Generación</h3>\n                    </div>\n                    <div class=\"tile-body\">\n                        <div class=\"sitr-pie\" id=\"sitr-gen-pie\" style=\"height: 42.5vh; min-height: 272px; width: 100%; user-select: none; position: relative;\" _echarts_instance_=\"ec_1640876263964\"><div style=\"position: relative; width: 1038px; height: 564px; padding: 0px; margin: 0px; border-width: 0px;\"><canvas style=\"position: absolute; left: 0px; top: 0px; width: 1038px; height: 564px; user-select: none; padding: 0px; margin: 0px; border-width: 0px;\" data-zr-dom-id=\"zr_0\" width=\"1038\" height=\"564\"></canvas></div><div class=\"\"></div></div>\n                    </div>\n                </div>\n            </div>\n        </div>\n\n        <div class=\"row\">\n            <div class=\"col-md\">\n                <div class=\"tile\">\n                    <h3 class=\"tile-title\">\n                        Código de colores de las mediciones de generación\n                    </h3>\n                    <div class=\"tile-body\">\n\n                        <div class=\"d-flex bd-highlight\">\n                            <div class=\"p-2 w-100 bd-highlight align-middle text-center\">\n                                <span class=\"badge badge-pill badge-primary\" style=\"background-color:black;\">Normal.</span>\n                            </div>\n                            <div class=\"p-2 w-100 bd-highlight text-center\">\n                                <span class=\"badge badge-pill badge-primary\" style=\"background-color:ORCHID;\">Sin telemetría.</span>\n                            </div>\n                            <div class=\"p-2 w-100 bd-highlight align-middle text-center\">\n                                <span class=\"badge badge-pill badge-primary\" style=\"background-color:ROYALBLUE;\">Entrada manual.</span>\n                            </div>\n                        </div>\n                    </div>\n                </div>\n            </div>\n        </div>\n\n        <div class=\"row\">\n            <div class=\"col-md\">\n                <div class=\"tile\">\n                    <h3 class=\"tile-title\">\n                        Hidroeléctricas (MW)\n                    </h3>\n                    <div class=\"tile-body\">\n\n                        <!-- Units -->\n                        <div class=\"table-responsive-sm moreSmall\">\n                            <table class=\"table sitr-table-gen\" cellspacing=\"0\" cellpadding=\"0\">\n                                <tbody>\n                                    <tr>\n                                        <td>\n                                            <table class=\"table sitr-gen-group table-hover table-striped table-sm\">\n                                                <tbody><tr><td><span>Algarrobos 1</span></td><td><span style=\"color:#222\" ;=\"\">2.32</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Algarrobos 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Baitún 1</span></td><td><span style=\"color:#222\" ;=\"\">34.16</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Baitún 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Baitún 4</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Bajo del Totuma</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Bajo Mina 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Bajo Mina 2</span></td><td><span style=\"color:#222\" ;=\"\">20.10</span></td></tr>\n                                                <tr><td><span>Bajo Mina 3</span></td><td><span style=\"color:#222\" ;=\"\">0.42</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Barro Blanco 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Barro Blanco 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Barro Blanco 3</span></td><td><span style=\"color:#222\" ;=\"\">1.55</span></td></tr>\n                                                <tr><td><span>Bayano 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Bayano 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Bayano 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Bonyic 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Bonyic 2</span></td><td><span style=\"color:#222\" ;=\"\">10.75</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Bonyic 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Bugaba I 1</span></td><td><span style=\"color:#222\" ;=\"\">1.39</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Bugaba I 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Bugaba I 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Bugaba II 1</span></td><td><span style=\"color:#222\" ;=\"\">1.60</span></td></tr>\n                                                <tr><td><span>Bugaba II 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Bugaba II 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Changuinola 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Changuinola 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Changuinola 3</span></td><td><span style=\"color:#222\" ;=\"\">9.39</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Cochea 1</span></td><td><span style=\"color:#222\" ;=\"\">6.79</span></td></tr>\n                                                <tr><td><span>Cochea 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Concepción 1</span></td><td><span style=\"color:ORCHID\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Concepción 2</span></td><td><span style=\"color:ORCHID\" ;=\"\">4.72</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Dolega 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Dolega 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Dolega 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Eco Hidro Tizingal</span></td><td><span style=\"color:ROYALBLUE\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>El Alto 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>El Alto 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>El Alto 3</span></td><td><span style=\"color:#222\" ;=\"\">18.37</span></td></tr>\n                                                <tr><td><span>Estí 1</span></td><td><span style=\"color:#222\" ;=\"\">45.28</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Estí 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Estrella 1</span></td><td><span style=\"color:#222\" ;=\"\">13.92</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Estrella 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Fortuna 1</span></td><td><span style=\"color:#222\" ;=\"\">24.54</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Fortuna 2</span></td><td><span style=\"color:#222\" ;=\"\">29.46</span></td></tr>\n                                                <tr><td><span>Fortuna 3</span></td><td><span style=\"color:#222\" ;=\"\">27.06</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Fraile 1</span></td><td><span style=\"color:#222\" ;=\"\">2.09</span></td></tr>\n                                                <tr><td><span>Fraile 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Fraile 3</span></td><td><span style=\"color:#222\" ;=\"\">1.20</span></td></tr>\n                                                <tr><td><span>Gatún 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Gatún 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Gatún 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Gatún 4</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Gatún 5</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Gatún 6</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Gualaca 1</span></td><td><span style=\"color:#222\" ;=\"\">6.24</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Gualaca 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>La Cuchilla 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>La Cuchilla 2</span></td><td><span style=\"color:#222\" ;=\"\">3.47</span></td></tr>\n                                            </tbody></table>\n                                        </td>\n\n                                        <td>\n                                            <table class=\"table table-hover table-striped table-sm sitr-gen-group\">\n                                                <tbody><tr><td><span>La Potra 1</span></td><td><span style=\"color:#222\" ;=\"\">9.10</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>La Potra 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>La Potra 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>La Potra 4</span></td><td><span style=\"color:#222\" ;=\"\">1.82</span></td></tr>\n                                                <tr><td><span>Las Cruces 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Las Cruces 2</span></td><td><span style=\"color:#222\" ;=\"\">9.45</span></td></tr>\n                                                <tr><td><span>Las Cruces 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Lorena 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Lorena 2</span></td><td><span style=\"color:#222\" ;=\"\">5.86</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Macano 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Macano 2</span></td><td><span style=\"color:#222\" ;=\"\">1.92</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Macano 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Madden 1</span></td><td><span style=\"color:#222\" ;=\"\">6.17</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Madden 2</span></td><td><span style=\"color:#222\" ;=\"\">6.06</span></td></tr>\n                                                <tr><td><span>Madden 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Mendre 1</span></td><td><span style=\"color:#222\" ;=\"\">4.00</span></td></tr>\n                                                <tr><td><span>Mendre 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Mendre II 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Mendre II 2</span></td><td><span style=\"color:#222\" ;=\"\">1.88</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>M. Monte 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>M. Monte 2</span></td><td><span style=\"color:#222\" ;=\"\">1.06</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Monte Lirio 1</span></td><td><span style=\"color:#222\" ;=\"\">8.43</span></td></tr>\n                                                <tr><td><span>Monte Lirio 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Monte Lirio 3</span></td><td><span style=\"color:#222\" ;=\"\">15.39</span></td></tr>\n                                                <tr><td><span>Pando 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Pando 2</span></td><td><span style=\"color:#222\" ;=\"\">12.07</span></td></tr>\n                                                <tr><td><span>Paso Ancho 1</span></td><td><span style=\"color:#222\" ;=\"\">2.02</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Paso Ancho 2</span></td><td><span style=\"color:#222\" ;=\"\">2.19</span></td></tr>\n                                                <tr><td><span>Pedregalito I 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Pedregalito I 2</span></td><td><span style=\"color:#222\" ;=\"\">5.00</span></td></tr>\n                                                <tr><td><span>Pedregalito I 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Pedregalito II 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Pedregalito II 2</span></td><td><span style=\"color:#222\" ;=\"\">3.27</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Perlas Norte 1</span></td><td><span style=\"color:ORCHID\" ;=\"\">0.01</span></td></tr>\n                                                <tr><td><span>Perlas Norte 2</span></td><td><span style=\"color:ORCHID\" ;=\"\">4.50</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Perlas Sur 1</span></td><td><span style=\"color:ORCHID\" ;=\"\">0.01</span></td></tr>\n                                                <tr><td><span>Perlas Sur 2</span></td><td><span style=\"color:ORCHID\" ;=\"\">4.53</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Planetas I 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Planetas I 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Planetas I 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Planetas II 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Planetas II 2</span></td><td><span style=\"color:#222\" ;=\"\">2.99</span></td></tr>\n                                                <tr><td><span>Prudencia 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Prudencia 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>RP-490 1</span></td><td><span style=\"color:#222\" ;=\"\">4.95</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>RP-490 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Salsipuedes 1</span></td><td><span style=\"color:#222\" ;=\"\">9.26</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Salsipuedes 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Salsipuedes 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>San Andrés 1</span></td><td><span style=\"color:#222\" ;=\"\">2.08</span></td></tr>\n                                                <tr><td><span>San Andrés 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>San Lorenzo 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>San Lorenzo 2</span></td><td><span style=\"color:#222\" ;=\"\">3.61</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Valles 1</span></td><td><span style=\"color:#222\" ;=\"\">19.57</span></td></tr>\n                                                <tr><td><span>Valles 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Yeguada 1</span></td><td><span style=\"color:#222\" ;=\"\">2.59</span></td></tr>\n                                                <tr><td><span>Yeguada 2</span></td><td><span style=\"color:#222\" ;=\"\">2.56</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Yeguada 3</span></td><td><span style=\"color:#222\" ;=\"\">0.53</span></td></tr>\n                                            </tbody></table>\n                                        </td>\n                                    </tr>\n                                </tbody>\n                            </table>\n                        </div>\n\n                    </div>\n                </div>\n            </div>\n        </div>\n\n        <div class=\"row\">\n            <div class=\"col-md\">\n                <div class=\"tile\">\n                    <h3 class=\"tile-title\">\n                        Térmicas (MW)\n                    </h3>\n                    <div class=\"tile-body\">\n\n                        <div class=\"table-responsive-sm moreSmall\">\n                            <!-- Units -->\n                            <table class=\"table sitr-table-gen\" cellspacing=\"0\" cellpadding=\"0\">\n                                <tbody>\n                                    <tr>\n                                        <td>\n                                            <table class=\"table table-hover table-striped table-sm sitr-gen-group\">\n                                                <tbody><tr><td><span>ACP Miraflores 5</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>ACP Miraflores 9</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>ACP Miraflores 10</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>BLM 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>BLM 3</span></td><td><span style=\"color:ROYALBLUE\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>BLM 4</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>BLM 5</span></td><td><span style=\"color:ROYALBLUE\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>BLM 6</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>BLM 8</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>BLM 9</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>CADASA 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>CADASA 2</span></td><td><span style=\"color:#222\" ;=\"\">0.05</span></td></tr>\n                                                <tr><td><span>Cativá 1</span></td><td><span style=\"color:#222\" ;=\"\">7.03</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Cativá 2</span></td><td><span style=\"color:#222\" ;=\"\">6.89</span></td></tr>\n                                                <tr><td><span>Cativá 3</span></td><td><span style=\"color:#222\" ;=\"\">6.56</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Cativá 4</span></td><td><span style=\"color:#222\" ;=\"\">6.30</span></td></tr>\n                                                <tr><td><span>Cativá 5</span></td><td><span style=\"color:#222\" ;=\"\">7.06</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Cativá 6</span></td><td><span style=\"color:#222\" ;=\"\">6.51</span></td></tr>\n                                                <tr><td><span>Cativá 7</span></td><td><span style=\"color:#222\" ;=\"\">1.37</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Cativá 8</span></td><td><span style=\"color:#222\" ;=\"\">6.62</span></td></tr>\n                                                <tr><td><span>Cativá 9</span></td><td><span style=\"color:#222\" ;=\"\">7.07</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Cativá 10</span></td><td><span style=\"color:#222\" ;=\"\">6.57</span></td></tr>\n                                                <tr><td><span>Cobre Panamá 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Cobre Panamá 2</span></td><td><span style=\"color:#222\" ;=\"\">149.60</span></td></tr>\n                                                <tr><td><span>Costa Norte 1</span></td><td><span style=\"color:#222\" ;=\"\">75.64</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Costa Norte 2</span></td><td><span style=\"color:#222\" ;=\"\">127.68</span></td></tr>\t\t\t\n                                                <tr><td><span>Costa Norte 3</span></td><td><span style=\"color:#222\" ;=\"\">76.21</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Costa Norte 4</span></td><td><span style=\"color:#222\" ;=\"\">76.35</span></td></tr>\t\t\t\t\t\t\t\t\t\t\t\t\t\n                                            </tbody></table>\n                                        </td>\n                                        <td>\n                                            <table class=\"table table-hover table-striped table-sm sitr-gen-group\">\n                                                <tbody><tr><td><span>PanAm 1</span></td><td><span style=\"color:#222\" ;=\"\">15.51</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>PanAm 2</span></td><td><span style=\"color:#222\" ;=\"\">15.61</span></td></tr>\n                                                <tr><td><span>PanAm 3</span></td><td><span style=\"color:#222\" ;=\"\">15.44</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>PanAm 4</span></td><td><span style=\"color:#222\" ;=\"\">15.53</span></td></tr>\n                                                <tr><td><span>PanAm 5</span></td><td><span style=\"color:#222\" ;=\"\">15.58</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>PanAm 6</span></td><td><span style=\"color:#222\" ;=\"\">15.63</span></td></tr>\n                                                <tr><td><span>PanAm 7</span></td><td><span style=\"color:#222\" ;=\"\">16.32</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>PanAm 8</span></td><td><span style=\"color:#222\" ;=\"\">16.13</span></td></tr>\n                                                <tr><td><span>PanAm 9</span></td><td><span style=\"color:#222\" ;=\"\">16.21</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Sparkle Power 1</span></td><td><span style=\"color:#222\" ;=\"\">2.79</span></td></tr>\n                                                <tr><td><span>Sparkle Power 2</span></td><td><span style=\"color:#222\" ;=\"\">2.92</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Sparkle Power 3</span></td><td><span style=\"color:#222\" ;=\"\">2.93</span></td></tr>\n                                                <tr><td><span>Sparkle Power 4</span></td><td><span style=\"color:#222\" ;=\"\">3.20</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Sparkle Power 5</span></td><td><span style=\"color:#222\" ;=\"\">7.51</span></td></tr>\n                                                <tr><td><span>Sparkle Power 6</span></td><td><span style=\"color:#222\" ;=\"\">7.49</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Sparkle Power 7</span></td><td><span style=\"color:#222\" ;=\"\">7.42</span></td></tr>\n                                                <tr><td><span>Sparkle Power 8</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Termocolón 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Termocolón 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Termocolón 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Tropitérmica 1</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Tropitérmica 2</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Tropitérmica 3</span></td><td><span style=\"color:#222\" ;=\"\">0.00</span></td></tr>\n\t\t\t\t\t\t\t\t\t\t\n                                            </tbody></table>\n                                        </td>\n                                    </tr>\n                                </tbody>\n                            </table>\n                        </div>\n                    </div>\n                </div>\n            </div>\n        </div>\n\n        <div class=\"row\">\n            <div class=\"col-md\">\n                <div class=\"tile\">\n                    <h3 class=\"tile-title\">\n                        Solares (MW)\n                    </h3>\n                    <div class=\"tile-body\">\n                        <div class=\"table-responsive-sm moreSmall\">\n                            <!-- Units -->\n                            <table class=\"table sitr-table-gen\" cellspacing=\"0\" cellpadding=\"0\">\n                                <tbody>\n                                    <tr>\n                                        <td>\n                                            <table class=\"table table-hover table-striped table-sm sitr-gen-group\">\n                                                <tbody><tr><td><span>Bejuco Solar</span></td><td><span style=\"color:#222\" ;=\"\">0.60</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Coclé Solar 1</span></td><td><span style=\"color:#222\" ;=\"\">0.41</span></td></tr>\n                                                <tr><td><span>Daconan Solar</span></td><td><span style=\"color:#222\" ;=\"\">-2.15</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Divisa Solar</span></td><td><span style=\"color:#222\" ;=\"\">5.73</span></td></tr>\n                                                <tr><td><span>Don Félix</span></td><td><span style=\"color:#222\" ;=\"\">5.95</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Ecosolar</span></td><td><span style=\"color:#222\" ;=\"\">6.45</span></td></tr>\n                                                <tr><td><span>Ecosolar 2</span></td><td><span style=\"color:#222\" ;=\"\">6.57</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>El Espinal</span></td><td><span style=\"color:ORCHID\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>El Fraile Solar 1</span></td><td><span style=\"color:#222\" ;=\"\">0.31</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Estrella Solar</span></td><td><span style=\"color:#222\" ;=\"\">3.78</span></td></tr>\n                                                <tr><td><span>Farallón II</span></td><td><span style=\"color:#222\" ;=\"\">3.70</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Fotovoltaica Santiago Gen 1</span></td><td><span style=\"color:#222\" ;=\"\">3.64</span></td></tr>\n                                                <tr><td><span>Ikako</span></td><td><span style=\"color:#222\" ;=\"\">7.93</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Ikako I</span></td><td><span style=\"color:#222\" ;=\"\">5.76</span></td></tr>\n                                                <tr><td><span>Ikako II</span></td><td><span style=\"color:#222\" ;=\"\">7.27</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Ikako III</span></td><td><span style=\"color:#222\" ;=\"\">7.67</span></td></tr>\t\t\t\n                                                <tr><td><span>Jagüito Solar</span></td><td><span style=\"color:#222\" ;=\"\">3.95</span></td></tr>\t\t\t\t\t\t\t\t\t\t\t\t\n                                                <tr class=\"sitr-alt-row\"><td><span>La Esperanza Solar 20 MW</span></td><td><span style=\"color:#222\" ;=\"\">3.42</span></td></tr>\n                                                <tr><td><span>Las Mendozas Solar</span></td><td><span style=\"color:#222\" ;=\"\">2.45</span></td></tr>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t</tbody></table>\n                                        </td>\n                                        <td>\n                                            <table class=\"table table-hover table-striped table-sm sitr-gen-group\">\n                                                <tbody><tr><td><span>Macano Solar</span></td><td><span style=\"color:#222\" ;=\"\">1.53</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Mayorca Solar</span></td><td><span style=\"color:#222\" ;=\"\">9.62</span></td></tr>\n                                                <tr><td><span>Milton Solar</span></td><td><span style=\"color:#222\" ;=\"\">6.02</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Pacora II</span></td><td><span style=\"color:ORCHID\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Panasolar</span></td><td><span style=\"color:#222\" ;=\"\">6.45</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Parque Solar Prudencia</span></td><td><span style=\"color:ORCHID\" ;=\"\">0.00</span></td></tr>\n                                                <tr><td><span>Pesé Solar</span></td><td><span style=\"color:#222\" ;=\"\">9.03</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Sarigua</span></td><td><span style=\"color:#222\" ;=\"\">0.53</span></td></tr>\n                                                <tr><td><span>Sol de David</span></td><td><span style=\"color:#222\" ;=\"\">3.72</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Sol Real</span></td><td><span style=\"color:#222\" ;=\"\">6.66</span></td></tr>\n                                                <tr><td><span>Solar Bugaba</span></td><td><span style=\"color:#222\" ;=\"\">1.30</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Solar Caldera</span></td><td><span style=\"color:#222\" ;=\"\">2.15</span></td></tr>\n                                                <tr><td><span>Solar Chiriquí</span></td><td><span style=\"color:#222\" ;=\"\">6.39</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Solar Coclé</span></td><td><span style=\"color:#222\" ;=\"\">7.78</span></td></tr>\n                                                <tr><td><span>Solar Fotovoltaica Penonomé</span></td><td><span style=\"color:#222\" ;=\"\">94.45</span></td></tr>\t\n                                                <tr class=\"sitr-alt-row\"><td><span>Solar Los Ángeles</span></td><td><span style=\"color:#222\" ;=\"\">7.84</span></td></tr>\t\t\t\t\t\t\t\t\t\t\t\n                                                <tr><td><span>Solar Paris</span></td><td><span style=\"color:#222\" ;=\"\">6.40</span></td></tr>\n                                                <tr class=\"sitr-alt-row\"><td><span>Solar Pocrí</span></td><td><span style=\"color:#222\" ;=\"\">12.24</span></td></tr>\n                                                <tr><td><span>Vista Alegre</span></td><td><span style=\"color:#222\" ;=\"\">5.14</span></td></tr>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t</tbody></table>\n                                        </td>\n                                    </tr>\n                                </tbody>\n                            </table>\n\n                        </div>\n\n                    </div>\n                </div>\n            </div>\n        </div>\n\n        <div class=\"row\">\n            <div class=\"col-md\">\n                <div class=\"tile\">\n                    <h3 class=\"tile-title\">\n                        Eólicas (MW)\n                    </h3>\n                    <div class=\"tile-body\">\n                        <div class=\"table-responsive-sm moreSmall sitr-table-gen\">\n                            <!-- Units -->\n                            <table class=\"table table-hover table-striped table-sm sitr-gen-group\">\n                                <tbody>\n\n                                    <tr><td><span>Marañón GGC1</span></td><td><span style=\"color:#222\" ;=\"\">13.60</span></td></tr>\n                                    <tr class=\"sitr-alt-row\"><td><span>Nvo. Chagres I GGC1</span></td><td><span style=\"color:#222\" ;=\"\">6.50</span></td></tr>\n                                    <tr><td><span>Nvo. Chagres I GGC2</span></td><td><span style=\"color:#222\" ;=\"\">7.90</span></td></tr>\n                                    <tr class=\"sitr-alt-row\"><td><span>Nvo. Chagres I GGC3</span></td><td><span style=\"color:#222\" ;=\"\">3.60</span></td></tr>\n                                    <tr><td><span>Nvo. Chagres II GGC1</span></td><td><span style=\"color:#222\" ;=\"\">6.70</span></td></tr>\n                                    <tr class=\"sitr-alt-row\"><td><span>Nvo. Chagres II GGC2</span></td><td><span style=\"color:#222\" ;=\"\">15.50</span></td></tr>\n                                    <tr><td><span>Nvo. Chagres II GGC3</span></td><td><span style=\"color:#222\" ;=\"\">9.60</span></td></tr>\n                                    <tr class=\"sitr-alt-row\"><td><span>Portobelo GGC1</span></td><td><span style=\"color:#222\" ;=\"\">11.30</span></td></tr>\n                                    <tr><td><span>R. Vientos I GGC1</span></td><td><span style=\"color:#222\" ;=\"\">16.70</span></td></tr>\n                                    <tr class=\"sitr-alt-row\"><td><span>R. Vientos I GGC2</span></td><td><span style=\"color:#222\" ;=\"\">14.00</span></td></tr>\n                                    <tr><td><span>R. Vientos II GGC1</span></td><td><span style=\"color:#222\" ;=\"\">9.50</span></td></tr>\n                                    <tr class=\"sitr-alt-row\"><td><span>R. Vientos II GGC2</span></td><td><span style=\"color:#222\" ;=\"\">10.80</span></td></tr>\n\n                                </tbody>\n                            </table>\n                        </div>\n\n                    </div>\n                </div>\n            </div>\n        </div>\n\n\n        <div class=\"row\">\n            <div class=\"col-md\">\n                <div class=\"tile\">\n                    <h3 class=\"tile-title\">\n                        Biogás (MW)\n                    </h3>\n                    <div class=\"tile-body\">\n                        <!-- Biogas -->\n                        <!-- Units -->\n                        <div class=\"table-responsive-sm moreSmall sitr-table-gen\">\n                            <table class=\"table table-hover table-striped table-sm sitr-gen-group\">\n                                <tbody>\n\n                                    <tr><td><span>Cerro Patacón</span></td><td><span style=\"color:#222\" ;=\"\">2.70</span></td></tr>\n\n\n                                </tbody>\n                            </table>\n\n                        </div>\n                    </div>\n                </div>\n            </div>\n        </div>\n\n        <div class=\"row pt-1 my-md-2 pt-md-5\">\n            <div class=\"col-md-4 text-center\">\n                <a href=\"http://www.cnd.com.pa/\" target=\"_blank\"><img class=\"mb-2\" src=\"PA_nominal_generation_files/LogoPlanoCNDE.png\" alt=\"\" width=\"150\" height=\"150\"></a>\n            </div>\n            <div class=\"col-md-7 py-3 px-lg-5\">\n                <ul class=\"list-unstyled text-small text-justify footerCND\">\n                    <li>\n                        <small>\n                            “Por mandato de lo establecido en la Ley No.\n 6 de 1997, se pone a disposición de los interesados la información \ncontenida en este sitio, para su utilización por cualquier medio legal, \npero su uso deberá citar la fuente: EMPRESA DE TRANSMISIÓN ELÉCTRICA, \nS.A. (ETESA). Nuestra empresa no se hace responsable de ningún error, \nomisión, interpretación, pérdidas o daños que resulten de la utilización\n de la información o material contenidos en este sitio, por parte de \nusuarios, visitantes o terceras personas y su uso indebido y sin \nconfirmar, estará sujeto a sanciones penales (Artículos 289, 290 y 291 \ndel Código Penal) y/o administrativas. Además, en algunos casos que les \nsea aplicable, dicha información puede ser actualizada por ETESA, para \ncorregir errores o imprecisiones”.\n                        </small>\n                    </li>\n                    <li><small>Declaración de Privacidad © <span class=\"pace\" id=\"year\">2021</span> ETESA - Todos los Derechos Reservados.</small></li>\n                </ul>\n            </div>\n        </div>\n\n    </main>\n    <!-- Essential javascripts for application to work-->\n    <script src=\"PA_nominal_generation_files/jquery.js\"></script>\n    <script src=\"PA_nominal_generation_files/popper.js\"></script>\n    <script src=\"PA_nominal_generation_files/bootstrap.js\"></script>\n\n    <script src=\"PA_nominal_generation_files/main.js\"></script>\n\n    <script defer=\"defer\" src=\"PA_nominal_generation_files/scriptsnew.js\"></script>\n\n    <script src=\"PA_nominal_generation_files/echarts.js\"></script>\n\n    <script>\n        var localPie = [{name:\"Hídrica 421.84 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    "content": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\t<!DOCTYPE html>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<html class=\"ltr\" dir=\"ltr\" lang=\"fr-FR\">\n\n<head>\n\t<title>Transition énergétique - AEL EDT</title>\n\n\t<!-- CSS pour le Google FONT -->\n\t<link href=\"https://fonts.googleapis.com/css?family=Lato+Condensed:400,400i,700,700i|Lato:300,400,400i,500,700,700i\"; rel=\"stylesheet\">\n\n\t<meta charset=\"utf-8\">\n    <meta http-equiv=\"X-UA-Compatible\" content=\"IE=edge\">\n\t<meta name=\"viewport\" content=\"width=device-width, initial-scale=1, shrink-to-fit=no\">\n\t\n\t<script src=\"https://www.edt.pf/o/AEL-Theme/js/jquery-3.7.1.min.js\"></script>\n\t<script src=\"https://www.edt.pf/o/AEL-Theme/js/popper.min.js\"></script>\n\t<script 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#\n}\n\n\n\n\n\t\t\t\t\n\n\t\t\t\n\n\t\t\n\n\t\t\t\n\n\t\t\n\n\t\t\t\n\n\t\t\n\n\t\t\t\n\n\t\t\n\n\t\t\t\n\n\t\t\n\n\t\t\t\n\n\t\t\t\t\n\n\t\t\t\t\t\n\n#p_p_id_com_liferay_site_navigation_menu_web_portlet_SiteNavigationMenuPortlet_ .portlet-content {\n\n}\n\n\n\n\n\t\t\t\t\n\n\t\t\t\n\n\t\t\n\n\t\t\t\n\n\t\t\n\n\t\t\t\n\n\t\t\n\n\t</style>\n\n\n<style data-senna-track=\"temporary\" type=\"text/css\">\n</style>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<script data-senna-track=\"temporary\" type=\"text/javascript\">\n\tif (window.Analytics) {\n\t\twindow._com_liferay_document_library_analytics_isViewFileEntry = false;\n\t}\n</script>\n\n\n\n\n\n\n\n<script type=\"text/javascript\">\n// <![CDATA[\nLiferay.on(\n\t'ddmFieldBlur', function(event) {\n\t\tif (window.Analytics) {\n\t\t\tAnalytics.send(\n\t\t\t\t'fieldBlurred',\n\t\t\t\t'Form',\n\t\t\t\t{\n\t\t\t\t\tfieldName: event.fieldName,\n\t\t\t\t\tfocusDuration: event.focusDuration,\n\t\t\t\t\tformId: event.formId,\n\t\t\t\t\tpage: event.page\n\t\t\t\t}\n\t\t\t);\n\t\t}\n\t}\n);\n\nLiferay.on(\n\t'ddmFieldFocus', function(event) {\n\t\tif (window.Analytics) {\n\t\t\tAnalytics.send(\n\t\t\t\t'fieldFocused',\n\t\t\t\t'Form',\n\t\t\t\t{\n\t\t\t\t\tfieldName: event.fieldName,\n\t\t\t\t\tformId: event.formId,\n\t\t\t\t\tpage: event.page\n\t\t\t\t}\n\t\t\t);\n\t\t}\n\t}\n);\n\nLiferay.on(\n\t'ddmFormPageShow', function(event) {\n\t\tif (window.Analytics) {\n\t\t\tAnalytics.send(\n\t\t\t\t'pageViewed',\n\t\t\t\t'Form',\n\t\t\t\t{\n\t\t\t\t\tformId: event.formId,\n\t\t\t\t\tpage: event.page,\n\t\t\t\t\ttitle: event.title\n\t\t\t\t}\n\t\t\t);\n\t\t}\n\t}\n);\n\nLiferay.on(\n\t'ddmFormSubmit', function(event) {\n\t\tif (window.Analytics) {\n\t\t\tAnalytics.send(\n\t\t\t\t'formSubmitted',\n\t\t\t\t'Form',\n\t\t\t\t{\n\t\t\t\t\tformId: event.formId\n\t\t\t\t}\n\t\t\t);\n\t\t}\n\t}\n);\n\nLiferay.on(\n\t'ddmFormView', function(event) {\n\t\tif (window.Analytics) {\n\t\t\tAnalytics.send(\n\t\t\t\t'formViewed',\n\t\t\t\t'Form',\n\t\t\t\t{\n\t\t\t\t\tformId: event.formId,\n\t\t\t\t\ttitle: event.title\n\t\t\t\t}\n\t\t\t);\n\t\t}\n\t}\n);\n// ]]>\n</script>\n\n\n\n\n\n\n\n\t\n\t<script type=\"text/javascript\" src=\"https://tarteaucitron.io/load.js?domain=www.edt.pf&uuid=816949965c27396681282c50f33d17b6e5ef12a9\"></script>\n\t\n</head>\n\n<body class=\"other controls-visible groupe yui3-skin-sam guest-site signed-out public-page site \">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"closed d-print-none lfr-product-menu-panel sidenav-fixed sidenav-menu-slider\" id=\"_com_liferay_product_navigation_product_menu_web_portlet_ProductMenuPortlet_sidenavSliderId\"><div class=\"product-menu sidebar sidenav-menu\">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t<div class=\"portlet-boundary portlet-boundary_com_liferay_product_navigation_product_menu_web_portlet_ProductMenuPortlet_  portlet-static portlet-static-end portlet-decorate  \" id=\"p_p_id_com_liferay_product_navigation_product_menu_web_portlet_ProductMenuPortlet_\">\n\t\t<span id=\"p_com_liferay_product_navigation_product_menu_web_portlet_ProductMenuPortlet\"></span>\n\n\n\n\n\t\n\n\t\n\t\t\n\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"lfr-product-menu-sidebar lfr-applications-menu\" id=\"productMenuSidebar\">\n\t\n\n\t<div class=\"sidebar-body\">\n\t\t\n\t\t\t\n\t\t\t\n\t\t\n\t</div>\n</div>\n\t\t\n\t\n\n\n\n\n\n\n\n\t</div>\n\n\n\n\n</div></div>\n\t\t\n<div class=\"header\" class=\"navbar-edt container-wrap\">\t\n\t\n\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"journal-content-article \" data-analytics-asset-id=\"39705\" data-analytics-asset-title=\"Header\" data-analytics-asset-type=\"web-content\">\n\t\n\n\t<div class=\"bg-edt\">\n\t<div class=\"container\">\n\t\t<div class=\"row align-items-start\">\n\t\t\t<div class=\"col-6 col-md-4\">\n\t\t\t\t<div class=\"logo\">\n\t\t\t\t\t<a href=\"/\" title=\"Agence en ligne EDT\">\n\t\t\t\t\t\t<img alt=\"Logo EDT\" src=\"https://www.edt.pf/o/AEL-Theme/images/logo-edt-engie.png\" height=\"85\" class=\"img-fluid\"> \n\t\t\t\t\t</a> \n\t\t\t\t</div>\n\t\t\t</div>\n\t\t\t\t\n\t\t\t<div class=\"col-6 col-md-8 text-right\">\n\t\t\t\t<div class=\"row align-items-center justify-content-end\">\n\t\t\t\t\t<div class=\"col-sm-6 rsocial\">\n\t\t\t\t\t\t<ul class=\"menu-inline\">\n\t\t\t\t\t\t\t<li><a href=\"https://www.facebook.com/ElectriciteDeTahiti/\" class=\"facebook\"><i class=\"fa fa-facebook-f\"></i></a></li>\n\t\t\t\t\t\t\t<li><a href=\"https://www.linkedin.com/company/edt-engie/\" class=\"linkedin\"><i class=\"fa fa-linkedin\"> </i></a></li>\n\t\t\t\t\t\t\t<li><a href=\"https://www.youtube.com/channel/UCHCjCMVGbDEP0dTtbTdYSHQ\" class=\"youtube\"><i class=\"fa fa-youtube-play\"> </i> </a></li>\n\t\t\t\t\t\t\t<li><a href=\"https://www.instagram.com/edt_engie/\" class=\"instagram\"><i class=\"fa fa-instagram\"></i></a></li>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t</ul>\n\t\t\t\t\t</div>\n\t\t\t\t\t\n\t\t\t\t\t<div class=\"col-sm-6 rclient\">\n\t\t\t\t\t\t<div class=\"row\">\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<div class=\"col-sm-7\"> \n\t\t\t\t\t\t\t\t\t<a id=\"sign-in\" href=\"https://www.edt.pf/c/portal/login?p_l_id=364803\" class=\"btn btn-lg btn-yellow btn-uppercase espace-client\" rel=\"nofollow\"><i class=\"fa fa-lock fa-lg btn-a-middle\"></i>Mon espace client</a> \n\t\t\t\t\t\t\t</div>\n\t\t\t\t\t\t</div>\n\t\t\t\t\t</div>\n\t\t\t\t\t\t\t  \n\t\t\t\t\t<div class=\"col-12 col-md-4 rmenumobile\">\n\t\t\t\t\t\t<button type=\"button\" class=\"navbar-toggler collapsed\" data-toggle=\"collapse\" data-target=\"#navbar\" aria-expanded=\"false\" aria-controls=\"navbar\" aria-label=\"Toggle navigation\">\n\t\t\t\t\t\t\t<span class=\"icon-text\" >Menu</span>\n\t\t\t\t\t\t\t<div class=\"block-icon-bar\"> <span class=\"icon-bar top-bar\"></span> <span class=\"icon-bar middle-bar\"></span> <span class=\"icon-bar bottom-bar\"></span> </div>\n\t\t\t\t\t\t</button>\n\t\t\t\t\t</div>\n\t\t\t\t\t\n\t\t\t\t\t<div class=\"col-12 menu-service\">\n\t\t\t\t\t\t<ul class=\"nav-inline\">\n\t\t\t\t\t\t\t<li><a href=\"/particulier/e-services\">Vos e-services</a></li>\n\t\t\t\t\t\t\t<li> | </li>\n\t\t\t\t\t\t\t<li><a href=\"/nous-connaitre\">Nous connaitre</a></li>\n\t\t\t\t\t\t\t<li> | </li>\n\t\t\t\t\t\t\t<li><a href=\"/mes-tarifs\">Tarifs</a></li>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t<li class=\"search\"><a id=\"search_zone\" href=\"javascript:void(0)\" ><i class=\"fa fa-search fa-lg btn-a-middle\"></i></a><div id=\"searchZone\">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t<div class=\"portlet-boundary portlet-boundary_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_  portlet-static portlet-static-end portlet-barebone portlet-search-bar \" id=\"p_p_id_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_\">\n\t\t<span id=\"p_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch\"></span>\n\n\n\n\n\t\n\n\t\n\t\t\n\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\t\n<section class=\"portlet\" id=\"portlet_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch\">\n\n\n\t<div class=\"portlet-content\">\n\n\t\t<div class=\"autofit-float autofit-row portlet-header\">\n\n\t\t\t<div class=\"autofit-col autofit-col-end\">\n\t\t\t\t<div class=\"autofit-section\">\n\t\t\t\t</div>\n\t\t\t</div>\n\t\t</div>\n\n\t\t\n\t\t\t<div class=\" portlet-content-container\">\n\t\t\t\t\n\n\n\t<div class=\"portlet-body\">\n\n\n\n\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\n\n\t\n\n\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\n\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<form action=\"https://www.edt.pf/search\" class=\"form  \" data-fm-namespace=\"_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_\" id=\"_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_fm\" method=\"get\" name=\"_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_fm\" >\n\t\n\n\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\n\n\t\t\n\t\t\t\n\t\t\t\t<input  class=\"field form-control\"  id=\"_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_formDate\"    name=\"_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_formDate\"     type=\"hidden\" value=\"1711822990475\"   />\n\t\t\t\n\t\t\n\n\t\t\n\t\n\n\n\n\n\n\n\n\n\n\t\t\t\n\n\t\t\t\n\n\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\t\t\t<fieldset class=\"fieldset search-bar\" ><div class=\"\">\n\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\n\n\t\t\n\t\t\t\n\t\t\t\t<input  class=\"field search-bar-empty-search-input form-control\"  id=\"_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_emptySearchEnabled\"    name=\"_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_emptySearchEnabled\"     type=\"hidden\" value=\"false\"   />\n\t\t\t\n\t\t\n\n\t\t\n\t\n\n\n\n\n\n\n\n\n\n\n\t\t\t\t\t<div class=\"input-group search-bar-simple\">\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t<div class=\"input-group-item search-bar-keywords-input-wrapper\">\n\t\t\t\t\t\t\t\t\t<input class=\"form-control input-group-inset input-group-inset-after search-bar-keywords-input\" data-qa-id=\"searchInput\" id=\"dkrk___q\" name=\"q\" placeholder=\"Recherche...\" title=\"Rechercher\" type=\"text\" value=\"\" />\n\n\t\t\t\t\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\n\n\t\t\n\t\t\t\n\t\t\t\t<input  class=\"field form-control\"  id=\"_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_scope\"    name=\"_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_scope\"     type=\"hidden\" value=\"\"   />\n\t\t\t\n\t\t\n\n\t\t\n\t\n\n\n\n\n\n\n\n\n\n\n\t\t\t\t\t\t\t\t\t<div class=\"input-group-inset-item input-group-inset-item-after\">\n\t\t\t\t\t\t\t\t\t\t<button class=\"btn btn-monospaced btn-unstyled\"type=\"submit\" aria-label=\"Valider\" ><span class=\"inline-item\"><svg class=\"lexicon-icon lexicon-icon-search\" role=\"presentation\" viewBox=\"0 0 512 512\"><use xlink:href=\"https://www.edt.pf/o/AEL-Theme/images/clay/icons.svg#search\" /></svg></span></button>\n\t\t\t\t\t\t\t\t\t</div>\n\t\t\t\t\t\t\t\t</div>\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t</div>\n\t\t\t\t</div></fieldset>\n\t\t\t\n\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\n</form>\n\n\n\n<script type=\"text/javascript\">\n// <![CDATA[\nAUI().use('liferay-form', function(A) {(function() {var $ = AUI.$;var _ = AUI._;\n\tLiferay.Form.register(\n\t\t{\n\t\t\tid: '_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_fm'\n\n\t\t\t\n\t\t\t\t, fieldRules: [\n\n\t\t\t\t\t\n\n\t\t\t\t]\n\t\t\t\n\n\t\t\t\n\n\t\t\t, validateOnBlur: true\n\t\t}\n\t);\n\n\tvar onDestroyPortlet = function(event) {\n\t\tif (event.portletId === 'com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch') {\n\t\t\tdelete Liferay.Form._INSTANCES['_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_fm'];\n\t\t}\n\t};\n\n\tLiferay.on('destroyPortlet', onDestroyPortlet);\n\n\t\n\n\tLiferay.fire(\n\t\t'_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_formReady',\n\t\t{\n\t\t\tformName: '_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_fm'\n\t\t}\n\t);\n})();});\n// ]]>\n</script>\n\n\t\t<script type=\"text/javascript\">\n// <![CDATA[\nAUI().use('liferay-search-bar', function(A) {(function() {var $ = AUI.$;var _ = AUI._;\n\t\t\tnew Liferay.Search.SearchBar(A.one('#_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_fm'));\n\t\t})();});\n// ]]>\n</script>\n\t\n\n\n\t\n\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\t\n\n\n\t</div>\n\n\t\t\t</div>\n\t\t\n\t</div>\n</section>\n\t\n\n\t\t\n\t\t\n\n\n\n\n\n\n\n\t</div>\n\n\n\n\n</div></li> </ul> </div> </div> </div> </div> </div> </div>\n</div>\n\n\n\n</div>\n\n\t<div class=\"navbar-edt\">\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t<div class=\"portlet-boundary portlet-boundary_com_liferay_site_navigation_menu_web_portlet_SiteNavigationMenuPortlet_  portlet-static portlet-static-end portlet-barebone portlet-navigation \" id=\"p_p_id_com_liferay_site_navigation_menu_web_portlet_SiteNavigationMenuPortlet_INSTANCE_main_navigation_menu_\">\n\t\t<span id=\"p_com_liferay_site_navigation_menu_web_portlet_SiteNavigationMenuPortlet_INSTANCE_main_navigation_menu\"></span>\n\n\n\n\n\t\n\n\t\n\t\t\n\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\t\n<section class=\"portlet\" id=\"portlet_com_liferay_site_navigation_menu_web_portlet_SiteNavigationMenuPortlet_INSTANCE_main_navigation_menu\">\n\n\n\t<div class=\"portlet-content\">\n\n\t\t<div class=\"autofit-float autofit-row portlet-header\">\n\n\t\t\t<div class=\"autofit-col autofit-col-end\">\n\t\t\t\t<div class=\"autofit-section\">\n\t\t\t\t</div>\n\t\t\t</div>\n\t\t</div>\n\n\t\t\n\t\t\t<div class=\" portlet-content-container\">\n\t\t\t\t\n\n\n\t<div class=\"portlet-body\">\n\n\n\n\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\n\n\t\n\n\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\n\n\t\t\n\t\t\t\n\t\t\t\t              <!----------------------  DEBUT SPECIFICITE MOBILE  -->\n<div class=\"container \">\n\n\t<div class=\"row justify-content-center mobile-version-on\">\n\t\t<div class=\"col-12 col-sm-6 m1\">\n\t\t\t<ul class=\"navbar navbar-right\">\n\t\t\t\t<li class=\"nav-item dropdown profilbouton\"> <a\n\t\t\t\t\t\tclass=\"nav-link dropdown-toggle profil-link\" href=\"https://www.edt.pf/nous-connaitre\" id=\"profilmobile\" data-toggle=\"dropdown\"\n\t\t\t\t\t\taria-haspopup=\"true\" aria-expanded=\"false\"><i class=\"fa fa-user fa-lg btn-a-middle \"></i>Nous connaître<span\n\t\t\t\t\t\tclass=\"fa fa-angle-down fa-2x btn-a-middle\"></span> </a> \n\n\t\t\t\t\t<div class=\"dropdown-menu\" aria-labelledby=\"profilmobile\">\n\t\t\t\t\t\t    \t\t\t\t\t\t <a class=\"dropdown-item\"\n\t\t\t\t\t\t\taria-labelledby=\"layout_2120080\"\n\t\t\t\t\t\t\t  role=\"menuitem\" href=\"https://www.edt.pf/particulier\">Particulier</a>\n\t\t\t\t\t\t   \t\t\t\t\t\t <a class=\"dropdown-item\"\n\t\t\t\t\t\t\taria-labelledby=\"layout_2120113\"\n\t\t\t\t\t\t\t  role=\"menuitem\" href=\"https://www.edt.pf/professionnel\">Professionnel</a>\n\t\t\t\t\t\t   \t\t\t\t\t\t <a class=\"dropdown-item\"\n\t\t\t\t\t\t\taria-labelledby=\"layout_2120144\"\n\t\t\t\t\t\t\t  role=\"menuitem\" href=\"https://www.edt.pf/producteur\">Producteur</a>\n\t\t\t\t\t\t   \t\t\t\t\t\t <a class=\"dropdown-item\"\n\t\t\t\t\t\t\taria-labelledby=\"layout_2120163\"\n\t\t\t\t\t\t\t  role=\"menuitem\" href=\"https://www.edt.pf/collectivite\">Collectivité</a>\n\t\t\t\t\t\t \n\t\t\t\t\t</div></li>\n\t\t\t</ul>\n\t\t</div>\n\t\t<div class=\"col-12 col-sm-6 m2\">\n\t\t\t <a id=\"sign-in2\" href=\"https://www.edt.pf/c/portal/login?p_l_id=364803\"\n\t\t\t\tclass=\"btn btn-lg btn-yellow btn-uppercase espace-client\" rel=\"nofollow\"><i\n\t\t\t\tclass=\"fa fa-lock fa-lg btn-a-middle\"></i>Mon espace client</a> \n\t\t</div>\n\t</div>\n</div>\n<!---------------------- FIN SPECIFICITE MOBILE -->\n<div class=\"container-wrap nav-profil\">\n\t<div class=\"navbar navbar-expand-xl container\">\n\t\t<div class=\"collapse navbar-collapse\" id=\"navbar\">\n\t\t\t<ul class=\"navbar-nav mr-auto\">\n\t\t\t\t<li class=\"nav-item dropdown profilbouton mobile-version\"> <a\n\t\t\t\t\t\tclass=\"nav-link dropdown-toggle profil-link\" href=\"https://www.edt.pf/nous-connaitre\" id=\"profil\" data-toggle=\"dropdown\"\n\t\t\t\t\t\taria-haspopup=\"true\" aria-expanded=\"false\"><i class=\"fa fa-user fa-lg btn-a-middle \"></i>Nous connaître<span\n\t\t\t\t\t\tclass=\"fa fa-angle-down fa-2x btn-a-middle\"></span> </a>\n\t\t\t\t\t<div class=\"dropdown-menu\" aria-labelledby=\"profil\">\n\t\t\t\t\t\t    \t\t\t\t\t\t <a class=\"dropdown-item\"\n\t\t\t\t\t\t\taria-labelledby=\"layout_2120080\"\n\t\t\t\t\t\t\t  role=\"menuitem\" href=\"https://www.edt.pf/particulier\">Particulier</a>\n\t\t\t\t\t\t   \t\t\t\t\t\t <a class=\"dropdown-item\"\n\t\t\t\t\t\t\taria-labelledby=\"layout_2120113\"\n\t\t\t\t\t\t\t  role=\"menuitem\" href=\"https://www.edt.pf/professionnel\">Professionnel</a>\n\t\t\t\t\t\t   \t\t\t\t\t\t <a class=\"dropdown-item\"\n\t\t\t\t\t\t\taria-labelledby=\"layout_2120144\"\n\t\t\t\t\t\t\t  role=\"menuitem\" href=\"https://www.edt.pf/producteur\">Producteur</a>\n\t\t\t\t\t\t   \t\t\t\t\t\t <a class=\"dropdown-item\"\n\t\t\t\t\t\t\taria-labelledby=\"layout_2120163\"\n\t\t\t\t\t\t\t  role=\"menuitem\" href=\"https://www.edt.pf/collectivite\">Collectivité</a>\n\t\t\t\t\t\t \n\t\t\t\t\t</div>\n\t\t\t\t\t</li>\n\t\t\t</ul>\n\t\t\t<ul class=\"navbar-nav justify-content-end menu-principal\">\n\t\t\t\t \n\t\t\t\t   \t\t\t\t<li class=\"nav-item dropdown\"><a class=\"nav-link dropdown-toggle\" href=\"https://www.edt.pf/nous-connaitre/actualites\" id=\"autoreleve\"\n\t\t\t\t\tdata-toggle=\"dropdown\" aria-haspopup=\"true\" aria-expanded=\"false\">Actualités<span\n\t\t\t\t\t\tclass=\"fa fa-lg fa-angle-down float-right arrow-down\"></span></a>\n\t\t\t\t\t<div class=\"dropdown-menu\" aria-labelledby=\"autoreleve\">\n\t\t\t\t\t\t <a class=\"dropdown-item\" href=\"https://blog.edt.pf/category/actus-edt/communiques-de-presse/\">Communiqués de presse</a>\n <a class=\"dropdown-item\" href=\"https://blog.edt.pf/category/actus-edt/monde-de-lenergie/\">Monde de l&#39;énergie</a>\n <a class=\"dropdown-item\" href=\"https://blog.edt.pf/category/actus-edt/nos-engagements/\">Nos engagements</a>\n\t\t\t\t\t</div></li>\n  \n\t\t\t\t   \t\t\t\t<li class=\"nav-item dropdown\"><a class=\"nav-link dropdown-toggle\" href=\"https://www.edt.pf/groupe/engie-polynesie-pole-electricite\" id=\"autoreleve\"\n\t\t\t\t\tdata-toggle=\"dropdown\" aria-haspopup=\"true\" aria-expanded=\"false\">Pôle électricité<span\n\t\t\t\t\t\tclass=\"fa fa-lg fa-angle-down float-right arrow-down\"></span></a>\n\t\t\t\t\t<div class=\"dropdown-menu\" aria-labelledby=\"autoreleve\">\n\t\t\t\t\t\t <a class=\"dropdown-item\" href=\"https://www.edt.pf/edt-engie\">EDT ENGIE</a>\n <a class=\"dropdown-item\" href=\"https://www.edt.pf/tahiti-sud-energie\">Tahiti Sud Énergie</a>\n <a class=\"dropdown-item\" href=\"https://www.edt.pf/marama-nui\">Marama Nui</a>\n <a class=\"dropdown-item\" href=\"https://www.edt.pf/edm\">Electricité des Marquises</a>\n\t\t\t\t\t</div></li>\n  \n\t\t\t\t   \t\t\t\t<li class=\"nav-item dropdown\"><a class=\"nav-link dropdown-toggle\" href=\"https://www.edt.pf/pole-services\" id=\"autoreleve\"\n\t\t\t\t\tdata-toggle=\"dropdown\" aria-haspopup=\"true\" aria-expanded=\"false\">Pôle services<span\n\t\t\t\t\t\tclass=\"fa fa-lg fa-angle-down float-right arrow-down\"></span></a>\n\t\t\t\t\t<div class=\"dropdown-menu\" aria-labelledby=\"autoreleve\">\n\t\t\t\t\t\t <a class=\"dropdown-item\" href=\"https://www.edt.pf/engie-services-polynesie\">ENGIE Services Polynésie</a>\n <a class=\"dropdown-item\" href=\"https://www.edt.pf/poly-diesel\">POLY-DIESEL</a>\n\t\t\t\t\t</div></li>\n  \n\t\t\t\t   \t\t\t\t<li class=\"nav-item dropdown\"><a class=\"nav-link dropdown-toggle\" href=\"https://www.edt.pf/nos-engagements\" id=\"autoreleve\"\n\t\t\t\t\tdata-toggle=\"dropdown\" aria-haspopup=\"true\" aria-expanded=\"false\">Nos engagements<span\n\t\t\t\t\t\tclass=\"fa fa-lg fa-angle-down float-right arrow-down\"></span></a>\n\t\t\t\t\t<div class=\"dropdown-menu\" aria-labelledby=\"autoreleve\">\n\t\t\t\t\t\t <a class=\"dropdown-item\" href=\"https://www.edt.pf/notre-charte-ethique1\">Notre charte éthique</a>\n <a class=\"dropdown-item\" href=\"https://www.edt.pf/actions-sociales-solidaires\">Nos Partenariats</a>\n\t\t\t\t\t</div></li>\n  \n\t\t\t\t    \t\t\t\t<li aria-selected='true' id=\"layout_2120217\" role=\"presentation\" class=\"nav-item\"><a\n\t\t\t\t\taria-labelledby=\"layout_2120217\" href=\"https://www.edt.pf/transition-energetique-innovation\" class=\"nav-link lnk-sub\"\n\t\t\t\t\thref=\"https://www.edt.pf/transition-energetique-innovation\"  class=\"nav-link\">Transition énergétique</a></li>  \n\t\t\t\t  \t\t\t\t<li  id=\"layout_2120218\" role=\"presentation\" class=\"nav-item\"><a\n\t\t\t\t\taria-labelledby=\"layout_2120218\" href=\"https://www.edt.pf/groupe/engie-polynesie-pole-electricite/notre-histoire\" class=\"nav-link lnk-sub\"\n\t\t\t\t\thref=\"https://www.edt.pf/groupe/engie-polynesie-pole-electricite/notre-histoire\"  class=\"nav-link\">Notre histoire</a></li>  \n\t\t\t\t   \t\t\t\t<li class=\"nav-item dropdown\"><a class=\"nav-link dropdown-toggle\" href=\"https://www.edt.pf/nous-connaitre/nous-rejoindre\" id=\"autoreleve\"\n\t\t\t\t\tdata-toggle=\"dropdown\" aria-haspopup=\"true\" aria-expanded=\"false\">Nous rejoindre<span\n\t\t\t\t\t\tclass=\"fa fa-lg fa-angle-down float-right arrow-down\"></span></a>\n\t\t\t\t\t<div class=\"dropdown-menu\" aria-labelledby=\"autoreleve\">\n\t\t\t\t\t\t <a class=\"dropdown-item\" href=\"https://www.edt.pf/nos-metiers\">Nos métiers</a>\n <a class=\"dropdown-item\" href=\"https://www.edt.pf/elagages\">Elagages</a>\n\t\t\t\t\t</div></li>\n \n\t\t\t</ul>\n\t\t</div>\n\t</div>\n</div>\n\n\t\t\t\n\t\t\t\n\t\t\n\t\n\t\n\t\n\t\n\n\n\t\n\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\t\n\n\n\t</div>\n\n\t\t\t</div>\n\t\t\n\t</div>\n</section>\n\t\n\n\t\t\n\t\t\n\n\n\n\n\n\n\n\t</div>\n\n\n\n\n\t</div>\t\n\n\n<div class=\"container-wrap subheader\">\n\t<div class=\"container text-center\">\n\t\t<div class=\"row\">\n  \t\t\t<div class=\"col-12\">\n\t\t\t\t<h1 class=\"titre\">Transition énergétique</h1>\n\t\t\t</div>\n\t\t\t<div class=\"col-12\">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t<div class=\"portlet-boundary portlet-boundary_com_liferay_site_navigation_breadcrumb_web_portlet_SiteNavigationBreadcrumbPortlet_  portlet-static portlet-static-end portlet-barebone portlet-breadcrumb \" id=\"p_p_id_com_liferay_site_navigation_breadcrumb_web_portlet_SiteNavigationBreadcrumbPortlet_\">\n\t\t<span id=\"p_com_liferay_site_navigation_breadcrumb_web_portlet_SiteNavigationBreadcrumbPortlet\"></span>\n\n\n\n\n\t\n\n\t\n\t\t\n\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\t\n<section class=\"portlet\" id=\"portlet_com_liferay_site_navigation_breadcrumb_web_portlet_SiteNavigationBreadcrumbPortlet\">\n\n\n\t<div class=\"portlet-content\">\n\n\t\t<div class=\"autofit-float autofit-row portlet-header\">\n\n\t\t\t<div class=\"autofit-col autofit-col-end\">\n\t\t\t\t<div class=\"autofit-section\">\n\t\t\t\t</div>\n\t\t\t</div>\n\t\t</div>\n\n\t\t\n\t\t\t<div class=\" portlet-content-container\">\n\t\t\t\t\n\n\n\t<div class=\"portlet-body\">\n\n\n\n\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\n\n\t\n\n\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<nav aria-label=\"Fil d&#39;Ariane\" id=\"_com_liferay_site_navigation_breadcrumb_web_portlet_SiteNavigationBreadcrumbPortlet_breadcrumbs-defaultScreen\">\n\t\n\n\t\t\n\n\t\t    <nav aria-label=\"breadcrumb \">\n        <ol class=\"breadcrumb justify-content-center\">\n                <li class=\"breadcrumb-item\">\n                        <a href=\"https://www.edt.pf/nous-connaitre\">Nous connaître</a>\n                </li>\n                <li class=\"breadcrumb-item\">\n                        Transition énergétique\n                </li>\n        </ol>\n    </nav>\n\n\t\n</nav>\n\n\t\n\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\t\n\n\n\t</div>\n\n\t\t\t</div>\n\t\t\n\t</div>\n</section>\n\t\n\n\t\t\n\t\t\n\n\n\n\n\n\n\n\t</div>\n\n\n\n\n\t\t\t\t</nav>\n\t\t\t</div>\n\t\t</div>\n\t</div>\n</div>\n\n<div id=\"contenuPage\" class=\"container-fluid content\">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\n\t\t<style type=\"text/css\">\n\t\t\t.master-layout-fragment .portlet-header {\n\t\t\t\tdisplay: none;\n\t\t\t}\n\t\t</style>\n\n\t\t\n\n\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n\t\t\t<div class=\"columns-1\" id=\"main-content\" role=\"main\">\n\t<div class=\"portlet-layout row\">\n\t\t<div class=\"col-md-12 portlet-column portlet-column-only\" id=\"column-1\">\n\t\t\t<div class=\"portlet-dropzone portlet-column-content portlet-column-content-only\" id=\"layout-column_column-1\">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t<div class=\"portlet-boundary portlet-boundary_com_liferay_journal_content_web_portlet_JournalContentPortlet_  portlet-static portlet-static-end portlet-barebone portlet-journal-content \" id=\"p_p_id_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_cK13JT3JAIEv_\">\n\t\t<span id=\"p_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_cK13JT3JAIEv\"></span>\n\n\n\n\n\t\n\n\t\n\t\t\n\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\t\n<section class=\"portlet\" id=\"portlet_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_cK13JT3JAIEv\">\n\n\n\t<div class=\"portlet-content\">\n\n\t\t<div class=\"autofit-float autofit-row portlet-header\">\n\n\t\t\t<div class=\"autofit-col autofit-col-end\">\n\t\t\t\t<div class=\"autofit-section\">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"visible-interaction\">\n\t\n\t\t\n\n\t\t\n\n\t\t\n\n\t\t\n\t\n</div>\t\t\t\t</div>\n\t\t\t</div>\n\t\t</div>\n\n\t\t\n\t\t\t<div class=\" portlet-content-container\">\n\t\t\t\t\n\n\n\t<div class=\"portlet-body\">\n\n\n\n\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\n\n\t\n\n\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t<div class=\"\" data-fragments-editor-item-id=\"32119-1175251\" data-fragments-editor-item-type=\"fragments-editor-mapped-item\" >\n\t\t\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"journal-content-article \" data-analytics-asset-id=\"1175249\" data-analytics-asset-title=\"Transition énergétique Nous connaitre\" data-analytics-asset-type=\"web-content\">\n\t\n\n\t\t<div class=\"image-head\" style=\"background-image: url(/documents/20126/39792/header-transition.jpg/aaa58cd9-b25c-b654-6b1f-d107ec2cae9d?t=1562589135068);\">\n\t</div>\n\n</div>\n\n\n\n\n\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t</div>\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\n\n\n\n\t\n\n\t\n\n\t\n\n\t\n\n\t\n\n\t\n\n\n\n\n\t\n\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\t\n\n\n\t</div>\n\n\t\t\t</div>\n\t\t\n\t</div>\n</section>\n\t\n\n\t\t\n\t\t\n\n\n\n\n\n\n\n\t</div>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t<div class=\"portlet-boundary portlet-boundary_detailMesurePortlet_WAR_EDTAEL2018_  portlet-static portlet-static-end portlet-barebone  container\" id=\"p_p_id_detailMesurePortlet_WAR_EDTAEL2018_\">\n\t\t<span id=\"p_detailMesurePortlet_WAR_EDTAEL2018\"></span>\n\n\n\n\n\t\n\n\t\n\t\t\n\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\t\n<section class=\"portlet\" id=\"portlet_detailMesurePortlet_WAR_EDTAEL2018\">\n\n\n\t<div class=\"portlet-content\">\n\n\t\t<div class=\"autofit-float autofit-row portlet-header\">\n\n\t\t\t<div class=\"autofit-col autofit-col-end\">\n\t\t\t\t<div class=\"autofit-section\">\n\t\t\t\t</div>\n\t\t\t</div>\n\t\t</div>\n\n\t\t\n\t\t\t<div class=\" portlet-content-container\">\n\t\t\t\t\n\n\n\t<div class=\"portlet-body\">\n\n\n\n\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\n\n\t\n\n\t\t\n\n<script type=\"text/javascript\" src=\"https://www.gstatic.com/charts/loader.js\"></script>\n<script type=\"text/javascript\" id=\"id1____detailMesurePortlet__WAR__EDTAEL2018__Script\">\n/*<![CDATA[*/\ngoogle.charts.load('current', {\"packages\":[\"corechart\"],\"language\":\"fr\"});\ngoogle.charts.setOnLoadCallback(drawpieChart);\nfunction drawpieChart() {\nvar data = new google.visualization.DataTable({\"cols\":[{\"label\":\"Titre\",\"type\":\"string\"},{\"label\":\"Valeur\",\"type\":\"number\"}],\"rows\":[{\"c\":[{\"v\":\"Thermique\"},{\"v\":54520}]},{\"c\":[{\"v\":\"Hydro électricité\"},{\"v\":969}]},{\"c\":[{\"v\":\"Solaire\"},{\"v\":6909}]}]})\n\nvar options = {\"pieSliceText\":\"percentage\",\"slices\":{\"0\":{\"color\":\"#552382\"},\"1\":{\"color\":\"#00aaff\"},\"2\":{\"color\":\"#ffc300\"}},\"legend\":{\"position\":\"bottom\",\"maxLines\":3,\"textStyle\":{\"fontSize\":15}},\"is3D\":true,\"chartArea\":{\"left\":0,\"width\":\"100%\"},\"titleTextStyle\":{\"fontSize\":20},\"colors\":[\"#552382\",\"#00aaff\",\"#ffc300\"],\"height\":500};\n\nvar pieChartChart = new google.visualization.PieChart(document.getElementById('id1____detailMesurePortlet__WAR__EDTAEL2018__'))\npieChartChart.draw(data, options);\n}\n\n/*]]>*/\n</script>\n<script type=\"text/javascript\" src=\"/AEL-portlet-1.21/detailMesurePortlet/ps:ZGV0YWlsTWVzdXJlUG9ydGxldF9XQVJfRURUQUVMMjAxOF9MQVlPVVRfMzY0ODAz/wicket/resource/pf.edt.ael2018.porlet.AbstractDefaultApplication/jquery-vide-ver-D41D8CD98F00B204E9800998ECF8427E.js\"></script>\n<script type=\"text/javascript\" id=\"pieChartRedrawScript\">\n/*<![CDATA[*/\n$(window).resize(function(){drawpieChart();});\n/*]]>*/\n</script>\n\n<script type=\"text/javascript\" id=\"ChartLibLoaderBehavior\">\n/*<![CDATA[*/\ngoogle.charts.load('current', {\"packages\":[\"corechart\"],\"language\":\"fr\"});\n\n/*]]>*/\n</script>\n\n\n\n\t<div class=\"row justify-content-center\">\n\t\t<div class=\"col-12 col-lg-4 text-center mb-4\">\n\t\t\t<h4 class=\"mb-3\">Puissance instantanée (en kW)</h4>\n\t\t\t<div class=\"dropshadow rounded10\"><div id=\"id1____detailMesurePortlet__WAR__EDTAEL2018__\"></div></div>\n\t\t</div>\n\t</div>\n\n\n\n\n\t\n\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\t\n\n\n\t</div>\n\n\t\t\t</div>\n\t\t\n\t</div>\n</section>\n\t\n\n\t\t\n\t\t\n\n\n\n\n\n\n\n\t</div>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t<div class=\"portlet-boundary portlet-boundary_com_liferay_journal_content_web_portlet_JournalContentPortlet_  portlet-static portlet-static-end portlet-barebone portlet-journal-content container\" id=\"p_p_id_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_prAhRcnsbKV9_\">\n\t\t<span id=\"p_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_prAhRcnsbKV9\"></span>\n\n\n\n\n\t\n\n\t\n\t\t\n\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\t\n<section class=\"portlet\" id=\"portlet_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_prAhRcnsbKV9\">\n\n\n\t<div class=\"portlet-content\">\n\n\t\t<div class=\"autofit-float autofit-row portlet-header\">\n\n\t\t\t<div class=\"autofit-col autofit-col-end\">\n\t\t\t\t<div class=\"autofit-section\">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"visible-interaction\">\n\t\n\t\t\n\n\t\t\n\n\t\t\n\n\t\t\n\t\n</div>\t\t\t\t</div>\n\t\t\t</div>\n\t\t</div>\n\n\t\t\n\t\t\t<div class=\" portlet-content-container\">\n\t\t\t\t\n\n\n\t<div class=\"portlet-body\">\n\n\n\n\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\n\n\t\n\n\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t<div class=\"\" data-fragments-editor-item-id=\"32119-1175222\" data-fragments-editor-item-type=\"fragments-editor-mapped-item\" >\n\t\t\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"journal-content-article \" data-analytics-asset-id=\"1175220\" data-analytics-asset-title=\"Transition énergétique Nous connaitre\" data-analytics-asset-type=\"web-content\">\n\t\n\n\t<p><span style=\"font-size:11pt\"><span style=\"font-family:&quot;Calibri&quot;,sans-serif\"></span></span></p><p class=\"txt-22\">EDT : 1ER PRODUCTEUR D’ÉNERGIES RENOUVELABLES</p><p>EDT et sa filiale MARAMA NUI œuvrent en partenariat avec le Pays afin d’atteindre les objectifs du Plan de Transition Énergétique de la Polynésie.</p><p>En tant que premiers producteurs d’énergies renouvelables en Polynésie, EDT et sa filiale MARAMA NUI confirment leur positionnement à la pointe du renouvelable. Le projet « Cote 95 » dans la vallée de Papenoʻo en est un remarquable exemple, il permettra de produire +4,5 GWh d’hydroélectricit, au sein de la concession existante Moyenne Papeno’o.</p><p>Par ailleurs, le développement de solutions de production photovoltaïque avec stockage est une des priorités d’EDT pour assurer une croissance neutre en carbone dans toutes les îles et communes où elle intervient. EDT est implanté à Tahiti et dans 10 îles. Le professionnalisme de ses équipes, fortes d’une expérience pluridécennale, est reconnu en tous ces sites. Cela constitue toute sa force.</p><p>La mise en service de Putu Uira, facilite depuis fin 2022 le placement des énergies hydroélectrique et solaire conformément au souhait du Pays et permet la réduction de l’utilisation d’hydrocarbure et les émissions de CO2</p><p>L’intégration au sein du Groupe ENGIE, un des leaders mondiaux de l’énergie et des énergies renouvelables, renforce encore plus les compétences d’EDT et ses capacités à répondre dès à présent aux enjeux énergétiques de la Polynésie.</p><p>Parce que ce challenge est celui de tout un pays, parce que ce challenge conditionne l’avenir de plusieurs générations, parce que ce challenge demande d’innover aujourd’hui avec les solutions de demain, EDT répond présent.</p><strong><p>45 % d’énergies renouvelables (37% d’hydroélectricité et 8% de solaire)</p></strong><p><a class=\"btn btn-transition btn-yellow\" target=\"\" href=\"/edt-engie\"><i class=\"fa fa-lg fa-angle-right mr-2\"></i>À propos d’EDT ENGIE</a></p>\n</div>\n\n\n\n\n\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t</div>\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\n\n\n\n\t\n\n\t\n\n\t\n\n\t\n\n\t\n\n\t\n\n\n\n\n\t\n\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\t\n\n\n\t</div>\n\n\t\t\t</div>\n\t\t\n\t</div>\n</section>\n\t\n\n\t\t\n\t\t\n\n\n\n\n\n\n\n\t</div>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t<div class=\"portlet-boundary portlet-boundary_com_liferay_journal_content_web_portlet_JournalContentPortlet_  portlet-static portlet-static-end portlet-barebone portlet-journal-content container\" id=\"p_p_id_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_8FP2P3lp2rfi_\">\n\t\t<span id=\"p_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_8FP2P3lp2rfi\"></span>\n\n\n\n\n\t\n\n\t\n\t\t\n\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\t\n<section class=\"portlet\" id=\"portlet_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_8FP2P3lp2rfi\">\n\n\n\t<div class=\"portlet-content\">\n\n\t\t<div class=\"autofit-float autofit-row portlet-header\">\n\n\t\t\t<div class=\"autofit-col autofit-col-end\">\n\t\t\t\t<div class=\"autofit-section\">\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"visible-interaction\">\n\t\n\t\t\n\n\t\t\n\n\t\t\n\n\t\t\n\t\n</div>\t\t\t\t</div>\n\t\t\t</div>\n\t\t</div>\n\n\t\t\n\t\t\t<div class=\" portlet-content-container\">\n\t\t\t\t\n\n\n\t<div class=\"portlet-body\">\n\n\n\n\t\n\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\n\n\t\n\n\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\n\t\t\n\t\t\t\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t<div class=\"\" data-fragments-editor-item-id=\"32119-3239032\" data-fragments-editor-item-type=\"fragments-editor-mapped-item\" >\n\t\t\t\t\t\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"journal-content-article \" data-analytics-asset-id=\"3239030\" data-analytics-asset-title=\"Transition énergétique Nous connaitre Putu uira\" data-analytics-asset-type=\"web-content\">\n\t\n\n\t<p><span style=\"font-size:11pt\"><span style=\"font-family:&quot;Calibri&quot;,sans-serif\"></span></span></p><p class=\"txt-22\">PUTU UIRA</p><p>Putu Uira est une puissante batterie de 10 MWh. Elle est installée dans la vallée de la Punaruu dans 2 containers de 40 pieds. En plus, 4 containers de même taille d’onduleurs et 1 container poste 30 kV lui permettent de fournir une puissance totale de 15 MW et 20 MVAR dans des délais records de quelques centièmes de seconde.</p><p>Putu Uira permet de réguler la fréquence et d’assurer la stabilité de la tension du réseau. Elle joue le rôle de « réserve tournante » jusqu’alors attribué à l’un des groupes de la centrale Émile Martin. De ce fait, chaque année, <strong>les groupes économisent 6 000 heures de marche, ce qui réduit la consommation de ressources fossiles, les émissions de CO2 et prolonge leur durée de vie. </strong></p><p>Putu Uira permet également de réduire le minimum thermique qui est nécessaire pour le pilotage du réseau et donc d’écouler davantage d’hydroélectricité, principalement la nuit et les week-ends. Elle facilite le placement des énergies hydroélectrique et solaire conformément au souhait du Pays.</p><p>Elle a été mise en service fin 2022. Depuis, des pics d’énergie renouvelable (EnR) sont atteints le week-end dans le mix énergétique à Tahiti. En journée, au pic d’ensoleillement de midi et selon les conditions météorologiques, le pourcentage d’Enr peut aller jusqu’à 95 % (59 % hydro et 36 % solaire). Ce type de mix énergétique deviendra une normalité en 2024 avec la mise en service des fermes solaire de l’appel à projet lancé par le Pays il y a 2 ans.</p><p>Putu uira a un impact positif sur l’environnement. Avec ce projet emblématique représentant un investissement de 1,5 milliard  FCFP, EDT affirme sa volonté de décarboner sa production d’électricité et contribue à atteindre les objectifs fixés par le Pays afin de réussir la transition énergétique.</p>\n</div>\n\n\n\n\n\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t</div>\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\n\n\n\n\t\n\n\t\n\n\t\n\n\t\n\n\t\n\n\t\n\n\n\n\n\t\n\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\n\t\t\n\t\n\t\n\n\n\t</div>\n\n\t\t\t</div>\n\t\t\n\t</div>\n</section>\n\t\n\n\t\t\n\t\t\n\n\n\n\n\n\n\n\t</div>\n\n\n\n\n</div>\n\t\t</div>\n\t</div>\n</div>\n\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\n\n\n\t\n\n\n<form action=\"#\" aria-hidden=\"true\" class=\"hide\" id=\"hrefFm\" method=\"post\" name=\"hrefFm\"><span></span><input hidden type=\"submit\"/></form></div>\n\n<section class=\"home-assistance container-wrap\">\n  <div class=\"container text-center\">\n    <div class=\"row\">\n      <div class=\"col-xs-12\">\n        <h1  class=\"headline\"><span>Assistance et dépannage</span></h1>\n      </div>\n    </div>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"journal-content-article \" data-analytics-asset-id=\"40310\" data-analytics-asset-title=\"Assitance et dépannage Nous connaitre\" data-analytics-asset-type=\"web-content\">\n\t\n\n\t<div class=\"row\">\n\t\t\t\t<article class=\"col-lg-2 col-sm-4 col-12 text-center\">\n\t\t\t\t<a href=\"/nous-connaitre/que-faire-en-cas-de-panne\" class=\"lnk-assistance\">\n\t\t\t\t\t\t<picture data-fileentryid=\"39871\"><source media=\"(max-width:120px)\" srcset=\"/o/adaptive-media/image/39871/Preview-1000x0/vig-en-cas-panne.png?t=1528547006890\" /><source media=\"(max-width:120px) and (min-width:120px)\" srcset=\"/o/adaptive-media/image/39871/thumbnail-300x300/vig-en-cas-panne.png?t=1528547006890\" /><img data-fileentryid=\"39871\" alt=\"Cas de panne\" src=\"/documents/20126/39768/vig-en-cas-panne.png/45ca4c63-a0f1-f655-d086-3c5b10307efc?t=1528547006890\" width=\"120\" height=\"120\" /></picture>\n\t\t\t\t\t<div class=\"txt-vig-assistance\">Que faire<br />\nen cas de panne</div>\n\t\t\t\t</a>\n\t\t\t</article>\n\t\t\t<article class=\"col-lg-2 col-sm-4 col-12 text-center\">\n\t\t\t\t<a href=\"/nous-connaitre/contacter-notre-service-depannage\" class=\"lnk-assistance\">\n\t\t\t\t\t\t<picture data-fileentryid=\"39886\"><source media=\"(max-width:120px)\" srcset=\"/o/adaptive-media/image/39886/Preview-1000x0/vig-service-depannage.png?t=1528547007166\" /><source media=\"(max-width:120px) and (min-width:120px)\" srcset=\"/o/adaptive-media/image/39886/thumbnail-300x300/vig-service-depannage.png?t=1528547007166\" /><img data-fileentryid=\"39886\" alt=\"Service Dépannage\" src=\"/documents/20126/39768/vig-service-depannage.png/b8cbe6d7-343b-cb92-78e3-edcc07676df0?t=1528547007166\" width=\"120\" height=\"120\" /></picture>\n\t\t\t\t\t<div class=\"txt-vig-assistance\">Contacter notre<br />\nservice Dépannage</div>\n\t\t\t\t</a>\n\t\t\t</article>\n\t\t\t<article class=\"col-lg-2 col-sm-4 col-12 text-center\">\n\t\t\t\t<a href=\"/nous-connaitre/nos-conseils-securite-et-branchements\" class=\"lnk-assistance\">\n\t\t\t\t\t\t<picture data-fileentryid=\"39861\"><source media=\"(max-width:120px)\" srcset=\"/o/adaptive-media/image/39861/Preview-1000x0/vig-conseil-securite.png?t=1528547006677\" /><source media=\"(max-width:120px) and (min-width:120px)\" srcset=\"/o/adaptive-media/image/39861/thumbnail-300x300/vig-conseil-securite.png?t=1528547006677\" /><img data-fileentryid=\"39861\" alt=\"Branchements\" src=\"/documents/20126/39768/vig-conseil-securite.png/6868fc1a-8a7c-3f62-1840-9544e9f20dd6?t=1528547006677\" width=\"120\" height=\"120\" /></picture>\n\t\t\t\t\t<div class=\"txt-vig-assistance\">Nos conseils sécurité<br />\net branchements</div>\n\t\t\t\t</a>\n\t\t\t</article>\n\t\t\t<article class=\"col-lg-2 col-sm-4 col-12 text-center\">\n\t\t\t\t<a href=\"/nous-connaitre/nos-conseils-elagage\" class=\"lnk-assistance\">\n\t\t\t\t\t\t<picture data-fileentryid=\"39866\"><source media=\"(max-width:120px)\" srcset=\"/o/adaptive-media/image/39866/Preview-1000x0/vig-elagage.png?t=1528547006793\" /><source media=\"(max-width:120px) and (min-width:120px)\" srcset=\"/o/adaptive-media/image/39866/thumbnail-300x300/vig-elagage.png?t=1528547006793\" /><img data-fileentryid=\"39866\" alt=\"Elagage\" src=\"/documents/20126/39768/vig-elagage.png/dcd89b0f-88a6-7798-c443-404717cd9eda?t=1528547006793\" width=\"120\" height=\"120\" /></picture>\n\t\t\t\t\t<div class=\"txt-vig-assistance\">Nos conseils<br />\nélagage</div>\n\t\t\t\t</a>\n\t\t\t</article>\n\t\t\t<article class=\"col-lg-2 col-sm-4 col-12 text-center\">\n\t\t\t\t<a href=\"/nous-connaitre/faq\" class=\"lnk-assistance\">\n\t\t\t\t\t\t<picture data-fileentryid=\"39876\"><source media=\"(max-width:120px)\" srcset=\"/o/adaptive-media/image/39876/Preview-1000x0/vig-question-reponses.png?t=1528547006983\" /><source media=\"(max-width:120px) and (min-width:120px)\" srcset=\"/o/adaptive-media/image/39876/thumbnail-300x300/vig-question-reponses.png?t=1528547006983\" /><img data-fileentryid=\"39876\" alt=\"Questions\" src=\"/documents/20126/39768/vig-question-reponses.png/a4b497bd-f699-4298-284d-6d94aeeafe27?t=1528547006983\" width=\"120\" height=\"120\" /></picture>\n\t\t\t\t\t<div class=\"txt-vig-assistance\">FAQ<br /></div>\n\t\t\t\t</a>\n\t\t\t</article>\n</div>\n</div>\n\n\n\n  </div>\n</section>\n\n<footer id=\"footer\" role=\"contentinfo\" class=\"footer\">\t\t\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"journal-content-article \" data-analytics-asset-id=\"39720\" data-analytics-asset-title=\"Footer\" data-analytics-asset-type=\"web-content\">\n\t\n\n\t<div class=\"flux-bar container-wrap\"><span></span> <span></span> <span></span> <span></span> <span></span> <span></span> 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href=\"https://www.edt.pf/collectivite\">\n\t\t\t\t\t\t\t\t\t\t\tCollectivité\n\t\t\t\t\t\t\t\t\t\t</a>\n\t\t\t\t\t\t\t</div>\n\t\t\t\t\t\t</li>\t\t\t\t\t\t\n\t\t\t\t\t</ul>\n\t\t\t\t</div>\n\t\t\t\n\t\t\t\t<div class=\"col-12\">\n\t\t\t\t\t<ul class=\"menu\">\n\t\t\t\t\t\t\t\t<li><a href=\"/nous-connaitre\"> > Nous connaître</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/nous-connaitre/nous-rejoindre\"> > Nous rejoindre</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/nous-connaitre/nos-agences\"> > Nos agences</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/nous-connaitre/mentions-legales\"> > Mentions légales</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/mentions-rgpd\"> > Mentions RGPD</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/nous-connaitre/cgvedt\"> > Cgv EDT</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/cgv-edt-%C3%8Eles\"> > Cgv EDT ÎLES</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/cgv-edp\"> > Cgv EDP</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/cgv-tse\"> > Cgv TSE</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/nous-connaitre/cgu\"> > Cgu</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/nous-connaitre/charte-cookies\"> > Cookies</a></li>\n\t\t\t\t\t\t\t\t<li><a href=\"/nous-connaitre/plan-du-site\"> > Plan du site</a></li>\n\t\t\t\t\t</ul>\n\t\t\t\t</div>\n\t\t\t</div>\n\t\t</div>\n\t</div>\n</div>\n\n<div class=\"container-fluid\">\n\t<div class=\"row\">\n\t\t<div class=\"copyrightbar col-12\"> </div>  \n\t\t<div class=\"col-12 text-center copyright-text\">\n\t\t\t<img src=\"https://www.edt.pf/o/AEL-Theme/images/logo-edt-engie-footer-copyright.png\" width=\"77\" height=\"35\" alt=\"\"/>Notre métier, votre énergie </div> </div> </div> \n</div>\n\n\n\n</footer>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div id=\"myAffix\" class=\"scroll-to-top float-right\"><a href=\"javaScript: void(0);\" onclick=\"window.history.back();\" class=\"smooth-scroll\"><i class=\"fa fa-chevron-left\"></i></a><a href=\"javaScript: void(0);\" onclick=\"$('html, body').animate({ scrollTop: 0 }, 'slow');\" class=\"smooth-scroll\"><i class=\"fa fa-chevron-up\"></i></a></div>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\n\n\n\n\n\n\t\n\n\n\n\t\n\n\n\n\n\n\n\n\n\n\t\n\n\t\n\n\n\n\n\n\t\n\n\n\n\t\n\n\n\n\n\n\n\n\n\n<script type=\"text/javascript\">\n// <![CDATA[\n\n\t\n\t\t\n\n\t\t\t\n\n\t\t\t\n\t\t\n\t\n\n// ]]>\n</script>\n\n\n\n\n\n\n\n\n\n\n\n\n\n<script type=\"text/javascript\">\n\t// <![CDATA[\n\n\t\t\n\n\t\tLiferay.currentURL = '\\x2ftransition-energetique-innovation';\n\t\tLiferay.currentURLEncoded = '\\x252Ftransition-energetique-innovation';\n\n\t// ]]>\n</script>\n\n\n\n\t\n\n\t\n\n\t<script type=\"text/javascript\">\n\t\t// <![CDATA[\n\t\t\t\n\t\t\t\t\n\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\n\t\t// ]]>\n\t</script>\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\n\t\n\n\t\t\n\n\t\t\n\t\n\n\n<script type=\"text/javascript\">\n// <![CDATA[\n(function() {var $ = AUI.$;var _ = AUI._;\n\tvar onDestroyPortlet = function () {\n\t\tLiferay.detach('messagePosted', onMessagePosted);\n\t\tLiferay.detach('destroyPortlet', onDestroyPortlet);\n\t};\n\n\tLiferay.on('destroyPortlet', onDestroyPortlet);\n\n\tvar onMessagePosted = function (event) {\n\t\tif (window.Analytics) {\n\t\t\tAnalytics.send('posted', 'Comment', {\n\t\t\t\tclassName: event.className,\n\t\t\t\tclassPK: event.classPK,\n\t\t\t\tcommentId: event.commentId,\n\t\t\t\ttext: event.text,\n\t\t\t});\n\t\t}\n\t};\n\n\tLiferay.on('messagePosted', onMessagePosted);\n})();(function() {var $ = AUI.$;var _ = AUI._;\n\tvar pathnameRegexp = /\\/documents\\/(\\d+)\\/(\\d+)\\/(.+?)\\/([^&]+)/;\n\n\tfunction handleDownloadClick(event) {\n\t\tif (event.target.nodeName.toLowerCase() === 'a' && window.Analytics) {\n\t\t\tvar anchor = event.target;\n\t\t\tvar match = pathnameRegexp.exec(anchor.pathname);\n\n\t\t\tvar fileEntryId =\n\t\t\t\tanchor.dataset.analyticsFileEntryId ||\n\t\t\t\t(anchor.parentElement &&\n\t\t\t\t\tanchor.parentElement.dataset.analyticsFileEntryId);\n\n\t\t\tif (fileEntryId && match) {\n\t\t\t\tvar getParameterValue = function (parameterName) {\n\t\t\t\t\tvar result = null;\n\n\t\t\t\t\tanchor.search\n\t\t\t\t\t\t.substr(1)\n\t\t\t\t\t\t.split('&')\n\t\t\t\t\t\t.forEach(function (item) {\n\t\t\t\t\t\t\tvar tmp = item.split('=');\n\n\t\t\t\t\t\t\tif (tmp[0] === parameterName) {\n\t\t\t\t\t\t\t\tresult = decodeURIComponent(tmp[1]);\n\t\t\t\t\t\t\t}\n\t\t\t\t\t\t});\n\n\t\t\t\t\treturn result;\n\t\t\t\t};\n\n\t\t\t\tAnalytics.send('documentDownloaded', 'Document', {\n\t\t\t\t\tgroupId: match[1],\n\t\t\t\t\tfileEntryId: fileEntryId,\n\t\t\t\t\tpreview: !!window._com_liferay_document_library_analytics_isViewFileEntry,\n\t\t\t\t\ttitle: decodeURIComponent(match[3].replace(/\\+/gi, ' ')),\n\t\t\t\t\tversion: getParameterValue('version'),\n\t\t\t\t});\n\t\t\t}\n\t\t}\n\t}\n\n\tdocument.addEventListener('DOMContentLoaded', function () {\n\t\tdocument.body.addEventListener('click', handleDownloadClick);\n\t});\n\n\tvar onDestroyPortlet = function () {\n\t\tdocument.body.removeEventListener('click', handleDownloadClick);\n\t\tLiferay.detach('destroyPortlet', onDestroyPortlet);\n\t};\n\n\tLiferay.on('destroyPortlet', onDestroyPortlet);\n})();(function() {var $ = AUI.$;var _ = AUI._;\n\tvar onShare = function (data) {\n\t\tif (window.Analytics) {\n\t\t\tAnalytics.send('shared', 'SocialBookmarks', {\n\t\t\t\tclassName: data.className,\n\t\t\t\tclassPK: data.classPK,\n\t\t\t\ttype: data.type,\n\t\t\t\turl: data.url,\n\t\t\t});\n\t\t}\n\t};\n\n\tvar onDestroyPortlet = function () {\n\t\tLiferay.detach('socialBookmarks:share', onShare);\n\t\tLiferay.detach('destroyPortlet', onDestroyPortlet);\n\t};\n\n\tLiferay.on('socialBookmarks:share', onShare);\n\tLiferay.on('destroyPortlet', onDestroyPortlet);\n})();(function() {var $ = AUI.$;var _ = AUI._;\n\tvar onVote = function (event) {\n\t\tif (window.Analytics) {\n\t\t\tAnalytics.send('VOTE', 'Ratings', {\n\t\t\t\tclassName: event.className,\n\t\t\t\tclassPK: event.classPK,\n\t\t\t\tratingType: event.ratingType,\n\t\t\t\tscore: event.score,\n\t\t\t});\n\t\t}\n\t};\n\n\tvar onDestroyPortlet = function () {\n\t\tLiferay.detach('ratings:vote', onVote);\n\t\tLiferay.detach('destroyPortlet', onDestroyPortlet);\n\t};\n\n\tLiferay.on('ratings:vote', onVote);\n\tLiferay.on('destroyPortlet', onDestroyPortlet);\n})();\n\tif (Liferay.Data.ICONS_INLINE_SVG) {\n\t\tsvg4everybody(\n\t\t\t{\n\t\t\t\tattributeName: 'data-href',\n\t\t\t\tpolyfill: true,\n\t\t\t\tvalidate: function (src, svg, use) {\n\t\t\t\t\treturn !src || !src.startsWith('#');\n\t\t\t\t}\n\t\t\t}\n\t\t);\n\t}\n\n\t\n\t\tLiferay.Portlet.register('com_liferay_site_navigation_breadcrumb_web_portlet_SiteNavigationBreadcrumbPortlet');\n\t\n\n\tLiferay.Portlet.onLoad(\n\t\t{\n\t\t\tcanEditTitle: false,\n\t\t\tcolumnPos: 0,\n\t\t\tisStatic: 'end',\n\t\t\tnamespacedId: 'p_p_id_com_liferay_site_navigation_breadcrumb_web_portlet_SiteNavigationBreadcrumbPortlet_',\n\t\t\tportletId: 'com_liferay_site_navigation_breadcrumb_web_portlet_SiteNavigationBreadcrumbPortlet',\n\t\t\trefreshURL: '\\x2fc\\x2fportal\\x2frender_portlet\\x3fp_l_id\\x3d364803\\x26p_p_id\\x3dcom_liferay_site_navigation_breadcrumb_web_portlet_SiteNavigationBreadcrumbPortlet\\x26p_p_lifecycle\\x3d0\\x26p_t_lifecycle\\x3d0\\x26p_p_state\\x3dnormal\\x26p_p_mode\\x3dview\\x26p_p_col_id\\x3dnull\\x26p_p_col_pos\\x3dnull\\x26p_p_col_count\\x3dnull\\x26p_p_static\\x3d1\\x26p_p_isolated\\x3d1\\x26currentURL\\x3d\\x252Ftransition-energetique-innovation\\x26settingsScope\\x3dportletInstance',\n\t\t\trefreshURLData: {}\n\t\t}\n\t);\n\n\t\n\t\tLiferay.Portlet.register('com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_prAhRcnsbKV9');\n\t\n\n\tLiferay.Portlet.onLoad(\n\t\t{\n\t\t\tcanEditTitle: false,\n\t\t\tcolumnPos: 2,\n\t\t\tisStatic: 'end',\n\t\t\tnamespacedId: 'p_p_id_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_prAhRcnsbKV9_',\n\t\t\tportletId: 'com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_prAhRcnsbKV9',\n\t\t\trefreshURL: '\\x2fc\\x2fportal\\x2frender_portlet\\x3fp_l_id\\x3d364803\\x26p_p_id\\x3dcom_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_prAhRcnsbKV9\\x26p_p_lifecycle\\x3d0\\x26p_t_lifecycle\\x3d0\\x26p_p_state\\x3dnormal\\x26p_p_mode\\x3dview\\x26p_p_col_id\\x3dcolumn-1\\x26p_p_col_pos\\x3d2\\x26p_p_col_count\\x3d4\\x26p_p_isolated\\x3d1\\x26currentURL\\x3d\\x252Ftransition-energetique-innovation',\n\t\t\trefreshURLData: {}\n\t\t}\n\t);\n\n\t\n\t\tLiferay.Portlet.register('com_liferay_site_navigation_menu_web_portlet_SiteNavigationMenuPortlet_INSTANCE_main_navigation_menu');\n\t\n\n\tLiferay.Portlet.onLoad(\n\t\t{\n\t\t\tcanEditTitle: false,\n\t\t\tcolumnPos: 0,\n\t\t\tisStatic: 'end',\n\t\t\tnamespacedId: 'p_p_id_com_liferay_site_navigation_menu_web_portlet_SiteNavigationMenuPortlet_INSTANCE_main_navigation_menu_',\n\t\t\tportletId: 'com_liferay_site_navigation_menu_web_portlet_SiteNavigationMenuPortlet_INSTANCE_main_navigation_menu',\n\t\t\trefreshURL: '\\x2fc\\x2fportal\\x2frender_portlet\\x3fp_l_id\\x3d364803\\x26p_p_id\\x3dcom_liferay_site_navigation_menu_web_portlet_SiteNavigationMenuPortlet_INSTANCE_main_navigation_menu\\x26p_p_lifecycle\\x3d0\\x26p_t_lifecycle\\x3d0\\x26p_p_state\\x3dnormal\\x26p_p_mode\\x3dview\\x26p_p_col_id\\x3dnull\\x26p_p_col_pos\\x3dnull\\x26p_p_col_count\\x3dnull\\x26p_p_static\\x3d1\\x26p_p_isolated\\x3d1\\x26currentURL\\x3d\\x252Ftransition-energetique-innovation\\x26settingsScope\\x3dportletInstance',\n\t\t\trefreshURLData: {}\n\t\t}\n\t);\n\n\t\n\t\tLiferay.Portlet.register('com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_cK13JT3JAIEv');\n\t\n\n\tLiferay.Portlet.onLoad(\n\t\t{\n\t\t\tcanEditTitle: false,\n\t\t\tcolumnPos: 0,\n\t\t\tisStatic: 'end',\n\t\t\tnamespacedId: 'p_p_id_com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_cK13JT3JAIEv_',\n\t\t\tportletId: 'com_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_cK13JT3JAIEv',\n\t\t\trefreshURL: '\\x2fc\\x2fportal\\x2frender_portlet\\x3fp_l_id\\x3d364803\\x26p_p_id\\x3dcom_liferay_journal_content_web_portlet_JournalContentPortlet_INSTANCE_cK13JT3JAIEv\\x26p_p_lifecycle\\x3d0\\x26p_t_lifecycle\\x3d0\\x26p_p_state\\x3dnormal\\x26p_p_mode\\x3dview\\x26p_p_col_id\\x3dcolumn-1\\x26p_p_col_pos\\x3d0\\x26p_p_col_count\\x3d4\\x26p_p_isolated\\x3d1\\x26currentURL\\x3d\\x252Ftransition-energetique-innovation',\n\t\t\trefreshURLData: {}\n\t\t}\n\t);\n\n\t\n\t\tLiferay.Portlet.register('newsletterPortlet_WAR_EDTAEL2018');\n\t\n\n\tLiferay.Portlet.onLoad(\n\t\t{\n\t\t\tcanEditTitle: false,\n\t\t\tcolumnPos: 0,\n\t\t\tisStatic: 'end',\n\t\t\tnamespacedId: 'p_p_id_newsletterPortlet_WAR_EDTAEL2018_',\n\t\t\tportletId: 'newsletterPortlet_WAR_EDTAEL2018',\n\t\t\trefreshURL: '\\x2fc\\x2fportal\\x2frender_portlet\\x3fp_l_id\\x3d364803\\x26p_p_id\\x3dnewsletterPortlet_WAR_EDTAEL2018\\x26p_p_lifecycle\\x3d0\\x26p_t_lifecycle\\x3d0\\x26p_p_state\\x3dnormal\\x26p_p_mode\\x3dview\\x26p_p_col_id\\x3dnull\\x26p_p_col_pos\\x3dnull\\x26p_p_col_count\\x3dnull\\x26p_p_static\\x3d1\\x26p_p_isolated\\x3d1\\x26currentURL\\x3d\\x252Ftransition-energetique-innovation\\x26settingsScope\\x3dportletInstance',\n\t\t\trefreshURLData: {}\n\t\t}\n\t);\n\n\t\n\t\tLiferay.Portlet.register('detailMesurePortlet_WAR_EDTAEL2018');\n\t\n\n\tLiferay.Portlet.onLoad(\n\t\t{\n\t\t\tcanEditTitle: false,\n\t\t\tcolumnPos: 1,\n\t\t\tisStatic: 'end',\n\t\t\tnamespacedId: 'p_p_id_detailMesurePortlet_WAR_EDTAEL2018_',\n\t\t\tportletId: 'detailMesurePortlet_WAR_EDTAEL2018',\n\t\t\trefreshURL: '\\x2fc\\x2fportal\\x2frender_portlet\\x3fp_l_id\\x3d364803\\x26p_p_id\\x3ddetailMesurePortlet_WAR_EDTAEL2018\\x26p_p_lifecycle\\x3d0\\x26p_t_lifecycle\\x3d0\\x26p_p_state\\x3dnormal\\x26p_p_mode\\x3dview\\x26p_p_col_id\\x3dcolumn-1\\x26p_p_col_pos\\x3d1\\x26p_p_col_count\\x3d4\\x26p_p_isolated\\x3d1\\x26currentURL\\x3d\\x252Ftransition-energetique-innovation',\n\t\t\trefreshURLData: {}\n\t\t}\n\t);\n\n\t\n\t\tLiferay.Portlet.register('com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch');\n\t\n\n\tLiferay.Portlet.onLoad(\n\t\t{\n\t\t\tcanEditTitle: false,\n\t\t\tcolumnPos: 0,\n\t\t\tisStatic: 'end',\n\t\t\tnamespacedId: 'p_p_id_com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch_',\n\t\t\tportletId: 'com_liferay_portal_search_web_search_bar_portlet_SearchBarPortlet_INSTANCE_templateSearch',\n\t\t\trefreshURL: 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21:30:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"06-Nov-2023 21:45:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"06-Nov-2023 22:00:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"06-Nov-2023 22:15:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"06-Nov-2023 22:30:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"06-Nov-2023 22:45:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"06-Nov-2023 23:00:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"06-Nov-2023 23:15:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"06-Nov-2023 23:30:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"06-Nov-2023 23:45:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null},{\"EffectiveTime\":\"07-Nov-2023 00:00:00\",\"FieldName\":\"SYSTEM_DEMAND\",\"Region\":\"NI\",\"Value\":null}],\"Status\":\"Success\"}"
  },
  {
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    "path": "electricitymap/contrib/parsers/tests/mocks/SMARTGRIDDASHBOARD/windProduction.json",
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02:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1318,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 02:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1286,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 02:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1292,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 02:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1271,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 03:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1270,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 03:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1276,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 03:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1259,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 03:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1233,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 04:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1239,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 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06:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1038,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 06:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1073,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 07:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1068,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 07:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1021,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 07:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":977,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 07:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1015,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 08:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1015,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 08:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1100,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 08:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1155,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 08:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1228,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 09:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1297,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 09:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1222,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 09:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1229,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 09:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1267,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 10:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1298,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 10:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1377,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 10:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1488,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 10:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1440,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 11:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1450,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 11:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1512,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 11:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1625,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 11:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1682,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 12:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1701,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 12:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1691,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 12:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1743,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 12:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1717,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 13:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1628,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 13:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1773,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 13:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1792,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 13:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1861,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 14:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1947,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 14:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1861,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 14:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1966,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 14:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1960,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 15:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1946,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 15:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1846,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 15:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1819,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 15:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1709,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 16:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1699,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 16:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1651,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 16:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1624,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 16:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1603,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 17:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1584,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 17:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1533,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 17:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1508,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 17:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1502,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 18:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1497,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 18:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1525,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 18:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":1447,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 18:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 19:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 19:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 19:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 19:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 20:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 20:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 20:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 20:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 21:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 21:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 21:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 21:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 22:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 22:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 22:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 22:45:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 23:00:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 23:15:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 23:30:00\",\"FieldName\":\"WIND_ACTUAL\"},{\"Value\":null,\"Region\":\"ROI\",\"EffectiveTime\":\"04-Jun-2025 23:45:00\",\"FieldName\":\"WIND_ACTUAL\"}]}"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/TAIPOWER/genary.json",
    "content": "{\n    \"\": \"2025-05-14 15:30\",\n    \"dataset\": [\n        [\n            \"<A NAME='nuclear'></A><b>NUCLEAR</b>\",\n            \"\",\n            \"NPP3#2\",\n            \"951.0\",\n            \"841.4\",\n            \"88.475%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='nuclear'></A><b>NUCLEAR</b>\",\n            \"\",\n            \"Subtotal\",\n            \"951.0(1.685%)\",\n            \"841.4(2.424%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Linkou#1\",\n            \"800.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"1\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Linkou#2\",\n            \"800.0\",\n            \"757.9\",\n            \"94.738%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Linkou#3\",\n            \"800.0\",\n            \"764.8\",\n            \"95.600%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#1\",\n            \"550.0\",\n            \"407.7\",\n            \"74.127%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#2\",\n            \"550.0\",\n            \"430.3\",\n            \"78.236%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#3\",\n            \"550.0\",\n            \"515.6\",\n            \"93.745%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#4\",\n            \"550.0\",\n            \"424.9\",\n            \"77.255%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#5\",\n            \"550.0\",\n            \"523.9\",\n            \"95.255%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#6\",\n            \"550.0\",\n            \"420.7\",\n            \"76.491%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#7\",\n            \"550.0\",\n            \"422.4\",\n            \"76.800%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#8\",\n            \"550.0\",\n            \"428.9\",\n            \"77.982%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#9\",\n            \"550.0\",\n            \"419.8\",\n            \"76.327%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Taichung#10\",\n            \"550.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"1\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Xinda#1(Remark XV)\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Xingda#2(Remark XV)\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Xingda#3(Remark XII)\",\n            \"550.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"28\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Xingda#4(Remark XII)\",\n            \"550.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"28\",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Dalin#1\",\n            \"800.0\",\n            \"761.0\",\n            \"95.125%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Dalin#2\",\n            \"800.0\",\n            \"757.9\",\n            \"94.738%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='coal'></A><b>COAL</b>\",\n            \"\",\n            \"Subtotal\",\n            \"10600.0(18.778%)\",\n            \"7035.8(20.266%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='cogen'></A><b>COGEN</b>\",\n            \"\",\n            \"Co-Generation\",\n            \"631.4\",\n            \"1791.3\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='cogen'></A><b>COGEN</b>\",\n            \"\",\n            \"Subtotal\",\n            \"631.4(1.119%)\",\n            \"1791.3(5.160%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='ippcoal'></A><b>IPPCOAL</b>\",\n            \"\",\n            \"Hoping#1\",\n            \"648.6\",\n            \"608.1\",\n            \"93.763%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='ippcoal'></A><b>IPPCOAL</b>\",\n            \"\",\n            \"Hoping#2\",\n            \"660.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"3\",\n            \"\"\n        ],\n        [\n            \"<A NAME='ippcoal'></A><b>IPPCOAL</b>\",\n            \"\",\n            \"Mailiao#1\",\n            \"600.0\",\n            \"420.1\",\n            \"70.017%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='ippcoal'></A><b>IPPCOAL</b>\",\n            \"\",\n            \"Mailiao#3\",\n            \"600.0\",\n            \"573.7\",\n            \"95.617%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='ippcoal'></A><b>IPPCOAL</b>\",\n            \"\",\n            \"Subtotal\",\n            \"2508.6(4.444%)\",\n            \"1601.9(4.614%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Datan#1\",\n            \"742.7\",\n            \"0.0\",\n            \"0.000%\",\n            \"16\",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Datan#2\",\n            \"742.7\",\n            \"687.9\",\n            \"92.622%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Datan#3\",\n            \"724.7\",\n            \"659.6\",\n            \"91.017%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Datan#4\",\n            \"724.7\",\n            \"677.2\",\n            \"93.446%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Datan#5\",\n            \"724.7\",\n            \"690.3\",\n            \"95.253%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Datan#6\",\n            \"724.7\",\n            \"686.3\",\n            \"94.701%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Datan#7(Remark X)\",\n            \"-\",\n            \"887.8\",\n            \"-\",\n            \"19\",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Datan#8\",\n            \"1123.6\",\n            \"1059.9\",\n            \"94.331%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Datan#9(Remark X)\",\n            \"-\",\n            \"537.7\",\n            \"-\",\n            \"17\",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Tongxiao#1\",\n            \"892.6\",\n            \"866.0\",\n            \"97.020%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Tongxiao#2\",\n            \"892.6\",\n            \"870.9\",\n            \"97.569%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Tongxiao#3\",\n            \"892.6\",\n            \"875.9\",\n            \"98.129%\",\n            \"3\",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Tongxiao#6\",\n            \"321.2\",\n            \"337.1\",\n            \"104.950%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"TongxiaoGT#9\",\n            \"180.9\",\n            \"0.0\",\n            \"0.000%\",\n            \"17\",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Xingda New CC#1(Remark X)\",\n            \"-\",\n            \"0.7\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Xingda CC#1\",\n            \"445.2\",\n            \"429.9\",\n            \"96.566%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Xingda CC#2\",\n            \"445.2\",\n            \"0.0\",\n            \"0.000%\",\n            \"1\",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Xingda CC#3\",\n            \"445.2\",\n            \"392.0\",\n            \"88.052%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Xingda CC#4\",\n            \"445.2\",\n            \"333.0\",\n            \"74.800%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Xingda CC#5\",\n            \"445.2\",\n            \"431.8\",\n            \"96.992%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Nanbu#1\",\n            \"288.8\",\n            \"274.6\",\n            \"95.083%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Nanbu#2\",\n            \"288.8\",\n            \"83.9\",\n            \"29.051%\",\n            \"16\",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Nanbu#3\",\n            \"288.8\",\n            \"296.7\",\n            \"102.735%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Nanbu#4\",\n            \"251.4\",\n            \"230.3\",\n            \"91.607%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Dalin#5\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Dalin#6\",\n            \"550.0\",\n            \"223.3\",\n            \"40.600%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='lng'></A><b>LNG</b>\",\n            \"\",\n            \"Subtotal\",\n            \"12581.4(22.288%)\",\n            \"11532.8(33.220%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Haihu#1\",\n            \"450.0\",\n            \"442.6\",\n            \"98.356%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Haihu#2\",\n            \"450.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"6\",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Hsintao#1\",\n            \"630.0\",\n            \"637.6\",\n            \"101.206%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Guoguang#1\",\n            \"480.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"6\",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Xingzhang#1\",\n            \"506.9\",\n            \"174.4\",\n            \"34.408%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Xingyuan#1\",\n            \"549.1\",\n            \"0.0\",\n            \"0.000%\",\n            \"1\",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Jiahui#1\",\n            \"700.0\",\n            \"689.0\",\n            \"98.429%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Jiahui#2\",\n            \"510.0\",\n            \"447.4\",\n            \"87.725%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Fongde#1\",\n            \"506.9\",\n            \"478.3\",\n            \"94.366%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Fongde#2\",\n            \"506.9\",\n            \"0.0\",\n            \"0.000%\",\n            \"6\",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Fongde#3(Remark X)\",\n            \"-\",\n            \"953.6\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='ipplng'></A><b>IPPLNG</b>\",\n            \"\",\n            \"Subtotal\",\n            \"5289.7(9.371%)\",\n            \"3822.9(11.012%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='oil'></A><b>OIL</b>\",\n            \"\",\n            \"Xiehe#3\",\n            \"500.0\",\n            \"138.3\",\n            \"27.660%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='oil'></A><b>OIL</b>\",\n            \"\",\n            \"Xiehe#4\",\n            \"500.0\",\n            \"142.1\",\n            \"28.420%\",\n            \"4\",\n            \"\"\n        ],\n        [\n            \"<A NAME='oil'></A><b>OIL</b>\",\n            \"\",\n            \"Penghu-Jianshan(Remark IV)\",\n            \"129.8\",\n            \"44.0\",\n            \"33.898%\",\n            \"17\",\n            \"\"\n        ],\n        [\n            \"<A NAME='oil'></A><b>OIL</b>\",\n            \"\",\n            \"Subtotal\",\n            \"1129.8(2.001%)\",\n            \"324.4(0.934%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"NPP2 Gas1\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"NPP2 Gas2\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"NPP3 Gas1\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"NPP3 Gas2\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"Taichung Gas1&amp;2\",\n            \"140.0\",\n            \"58.5\",\n            \"41.786%\",\n            \"31\",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"Taichung Gas3&amp;4\",\n            \"140.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"Kinmen-Tashan(Remark IV)\",\n            \"113.3\",\n            \"28.8\",\n            \"25.421%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"Masu-Zhushan(Remark IV)\",\n            \"28.6\",\n            \"8.1\",\n            \"28.282%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"Other outlying Islands(Remark IV)\",\n            \"40.2\",\n            \"N/A\",\n            \"N/A\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='diesel'></A><b>DIESEL</b>\",\n            \"\",\n            \"Subtotal(Remark V)\",\n            \"462.2(0.819%)\",\n            \"95.4(0.275%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Deji#1\",\n            \"78.0\",\n            \"33.0\",\n            \"42.308%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Deji#2\",\n            \"78.0\",\n            \"32.3\",\n            \"41.410%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Deji#3\",\n            \"78.0\",\n            \"32.7\",\n            \"41.923%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Qingshan#1\",\n            \"92.0\",\n            \"44.7\",\n            \"48.587%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Qingshan#2\",\n            \"92.0\",\n            \"44.5\",\n            \"48.370%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Qingshan#3\",\n            \"92.0\",\n            \"43.9\",\n            \"47.717%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Qingshan#4\",\n            \"92.0\",\n            \"43.2\",\n            \"46.957%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Guguan#1\",\n            \"54.4\",\n            \"42.5\",\n            \"78.053%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Guguan#2\",\n            \"54.4\",\n            \"41.6\",\n            \"76.400%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Guguan#3\",\n            \"54.4\",\n            \"41.6\",\n            \"76.400%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Guguan#4\",\n            \"54.4\",\n            \"41.0\",\n            \"75.298%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Tienlun#1\",\n            \"22.5\",\n            \"20.8\",\n            \"92.444%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Tienlun#2\",\n            \"22.5\",\n            \"20.6\",\n            \"91.556%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Tienlun#3\",\n            \"22.5\",\n            \"21.5\",\n            \"95.556%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Tienlun#4\",\n            \"22.5\",\n            \"18.8\",\n            \"83.556%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Tienlun#5\",\n            \"105.0\",\n            \"101.6\",\n            \"96.762%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Ma-an#1\",\n            \"66.7\",\n            \"65.6\",\n            \"98.292%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Ma-an#2\",\n            \"66.7\",\n            \"63.0\",\n            \"94.396%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Zhuolan#1\",\n            \"40.0\",\n            \"42.3\",\n            \"105.750%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Zhuolan#2\",\n            \"40.0\",\n            \"41.7\",\n            \"104.250%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Wanda#1\",\n            \"10.4\",\n            \"10.0\",\n            \"96.618%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Wanda#2\",\n            \"10.4\",\n            \"10.0\",\n            \"96.618%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Wanda#3\",\n            \"15.3\",\n            \"0.0\",\n            \"0.000%\",\n            \"1\",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Wanda#4\",\n            \"19.7\",\n            \"0.0\",\n            \"0.000%\",\n            \"2\",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Songlin#1&amp;2\",\n            \"20.9\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Daguan1#1\",\n            \"22.0\",\n            \"4.9\",\n            \"22.273%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Daguan1#2\",\n            \"22.0\",\n            \"5.0\",\n            \"22.727%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Daguan1#3\",\n            \"22.0\",\n            \"5.5\",\n            \"25.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Daguan1#4\",\n            \"22.0\",\n            \"5.0\",\n            \"22.727%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Daguan1#5\",\n            \"22.0\",\n            \"4.7\",\n            \"21.364%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Jugong#1\",\n            \"21.8\",\n            \"3.9\",\n            \"17.931%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Jugong#2\",\n            \"21.8\",\n            \"5.9\",\n            \"27.126%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Shuili#1\",\n            \"12.8\",\n            \"2.5\",\n            \"19.608%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Liwu#1&amp;#2\",\n            \"32.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"2\",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Longjian#1\",\n            \"48.6\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Longjian#2\",\n            \"48.6\",\n            \"10.3\",\n            \"21.193%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Bihai\",\n            \"61.2\",\n            \"10.2\",\n            \"16.667%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Wulai&amp;Gueishan&amp;Cukeng\",\n            \"40.5\",\n            \"34.5\",\n            \"85.185%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Small hydro in the northern region(Remark VI)\",\n            \"31.1\",\n            \"22.4\",\n            \"71.978%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Small hydro in the central region(Remark VI)\",\n            \"31.3\",\n            \"17.8\",\n            \"56.878%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Small hydro in the southern region(Remark VI)\",\n            \"7.2\",\n            \"2.6\",\n            \"36.262%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Small hydro in the eastern region(Remark VI)\",\n            \"54.6\",\n            \"33.8\",\n            \"61.905%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Feicuei#1\",\n            \"70.0\",\n            \"61.4\",\n            \"87.714%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Shihmen#1\",\n            \"45.0\",\n            \"25.1\",\n            \"55.778%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Shihmen#2\",\n            \"45.0\",\n            \"30.2\",\n            \"67.111%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Zengwun#1\",\n            \"50.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"2\",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Yising#1\",\n            \"40.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"2\",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Mingjian\",\n            \"16.7\",\n            \"8.0\",\n            \"47.904%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Jiananxikou&amp;Wushantou&amp;Batian\",\n            \"22.5\",\n            \"6.3\",\n            \"28.042%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Beinan\",\n            \"2.0\",\n            \"1.0\",\n            \"50.505%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"GuanShan\",\n            \"1.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Remaining Small Hydropower Purchases\",\n            \"5.5\",\n            \"N/A\",\n            \"N/A\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='hydro'></A><b>HYDRO</b>\",\n            \"\",\n            \"Subtotal\",\n            \"2123.9(3.762%)\",\n            \"1157.9(3.335%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind TPC(Remark XIII)\",\n            \"Guanyuan\",\n            \"30.0\",\n            \"2.5\",\n            \"8.333%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind TPC(Remark XIII)\",\n            \"Taichung Harbor\",\n            \"35.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind TPC(Remark XIII)\",\n            \"Wanggong\",\n            \"23.0\",\n            \"2.4\",\n            \"10.435%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind TPC(Remark XIII)\",\n            \"Zhanggong\",\n            \"86.2\",\n            \"6.3\",\n            \"7.309%\",\n            \"17\",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind TPC(Remark XIII)\",\n            \"Yunmai\",\n            \"46.0\",\n            \"2.6\",\n            \"5.652%\",\n            \"17\",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind TPC(Remark XIII)\",\n            \"Sihhu\",\n            \"28.0\",\n            \"3.3\",\n            \"11.786%\",\n            \"17\",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind TPC(Remark XIII)\",\n            \"Remaining Wind TPC\",\n            \"91.0\",\n            \"2.9\",\n            \"3.185%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind Purchases(Remark XIII)\",\n            \"Miaoli-Dapong\",\n            \"42.0\",\n            \"1.0\",\n            \"2.381%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind Purchases(Remark XIII)\",\n            \"Luwei-Zhangbin\",\n            \"55.2\",\n            \"4.2\",\n            \"7.609%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind Purchases(Remark XIII)\",\n            \"Guanwei-Guanyin&amp;Taowei-Xinwu\",\n            \"48.3\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind Purchases(Remark XIII)\",\n            \"Zhongwei Da-an\",\n            \"75.9\",\n            \"6.2\",\n            \"8.169%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind Purchases(Remark XIII)\",\n            \"ChuangWei Wind\",\n            \"49.2\",\n            \"4.0\",\n            \"8.130%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind Purchases(Remark XIII)\",\n            \"wpd,SinYuan-Lunbei\",\n            \"25.2\",\n            \"4.7\",\n            \"18.651%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Onshore Wind Purchases(Remark XIII)\",\n            \"Remaining Wind Purchases\",\n            \"178.4\",\n            \"4.3\",\n            \"2.410%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind TPC(Remark XIII)\",\n            \"Offshore Wind Generation Project Phase I\",\n            \"109.2\",\n            \"11.5\",\n            \"10.531%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind Purchases(Remark XIII)\",\n            \"Formosa 1 Offshore Wind Farm,HaiYang Zhunan\",\n            \"128.0\",\n            \"5.0\",\n            \"3.906%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind Purchases(Remark XIII)\",\n            \"Formosa 2 Offshore Wind Farm,HaiNeng Wind\",\n            \"376.0\",\n            \"16.2\",\n            \"4.309%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind Purchases(Remark XIII)\",\n            \"Orsted Greater Changhua-southeast,WoYi Wind\",\n            \"605.2\",\n            \"11.2\",\n            \"1.851%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind Purchases(Remark XIII)\",\n            \"Orsted Greater Changhua-southwest,WoEr Wind\",\n            \"294.8\",\n            \"0.6\",\n            \"0.190%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind Purchases(Remark XIII)\",\n            \"CHANGFANG-XIDAO OFFSHORE WIND FARMS I,FangYi Wind\",\n            \"96.0\",\n            \"6.4\",\n            \"6.708%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind Purchases(Remark XIII)\",\n            \"Changfang - phase II Offshore Wind Farm,FangEr Wind\",\n            \"451.2\",\n            \"25.5\",\n            \"5.652%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind Purchases(Remark XIII)\",\n            \"OWF Yunlin,YunHu(Remark X)\",\n            \"-\",\n            \"9.8\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind Purchases(Remark XIII)\",\n            \"OWF Yunlin,YunSi(Remark X)\",\n            \"-\",\n            \"27.7\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"Offshore Wind Purchases(Remark XIII)\",\n            \"ZHONGNENG OFFSHORE WIND FARM(Remark X)\",\n            \"-\",\n            \"23.6\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='wind'></A><b>WIND</b>\",\n            \"\",\n            \"Subtotal\",\n            \"2873.8(5.091%)\",\n            \"181.9(0.524%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR TPC(Remark XIII)\",\n            \"Jhangbin Solar Power\",\n            \"100.0\",\n            \"50.260\",\n            \"50.261%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR TPC(Remark XIII)\",\n            \"Tainan Salt Field Solar\",\n            \"150.0\",\n            \"72.735\",\n            \"48.490%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR TPC(Remark XIII)\",\n            \"Remaining Solar TPC\",\n            \"24.3\",\n            \"5.539\",\n            \"22.794%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"Lunwei Solar Power\",\n            \"-\",\n            \"113.680\",\n            \"-\",\n            \"43\",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"TianChon PV\",\n            \"-\",\n            \"117.600\",\n            \"-\",\n            \"43\",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"TianPeng PV\",\n            \"80.0\",\n            \"39.760\",\n            \"49.712%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"Pau Shing PV(Remark X)\",\n            \"-\",\n            \"27.720\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"URECO/HuahSuan Green Energy/HEXA Renewables Taiwan,LianHua Solar\",\n            \"-\",\n            \"95.328\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"SunnyRichPower,SianYang PV(Remark X)\",\n            \"-\",\n            \"83.017\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"SingWeiPV(Remark X)\",\n            \"-\",\n            \"38.080\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"Shuo Li PV(Remark X)\",\n            \"-\",\n            \"141.848\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"TianYing Solar(Remark X)\",\n            \"-\",\n            \"66.640\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"JhihGuang Solar(Remark X)\",\n            \"-\",\n            \"44.240\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"YongYao Solar Power Plant(Remark X)\",\n            \"-\",\n            \"21.504\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"GreenPeak Renewables,Yu Chang Solar(Remark X)\",\n            \"-\",\n            \"11.550\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"ASTER RENEWABLE ENERGY, SinLun Solar(Remark X)\",\n            \"-\",\n            \"56.280\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"ARK Solar Energy Corp.,Sin He Solar(Remark X)\",\n            \"-\",\n            \"54.040\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"StarShiningEnergy,ShengLi PV(Remark X)\",\n            \"-\",\n            \"20.440\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"Ting Jie Electric Power,TingHe Solar(Remark X)\",\n            \"-\",\n            \"25.480\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"STAR Energy,SingGu Solar(Remark X)\",\n            \"-\",\n            \"20.720\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"SOLAR Purchases(Remark XIII)\",\n            \"Remaining Solar Purchases\",\n            \"13699.4\",\n            \"5669.528\",\n            \"41.385%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='solar'></A><b>SOLAR</b>\",\n            \"\",\n            \"Subtotal\",\n            \"14053.7(24.896%)\",\n            \"6776.0(19.518%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='OtherRenewableEnergy'></A><b>OTHERRENEWABLEENERGY</b>\",\n            \"\",\n            \"TPC Geothermal\",\n            \"0.8\",\n            \"0.3\",\n            \"35.714%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='OtherRenewableEnergy'></A><b>OTHERRENEWABLEENERGY</b>\",\n            \"\",\n            \"Geothermal Purchases\",\n            \"6.4\",\n            \"2.0\",\n            \"31.013%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='OtherRenewableEnergy'></A><b>OTHERRENEWABLEENERGY</b>\",\n            \"\",\n            \"Biofuel\",\n            \"60.7\",\n            \"31.9\",\n            \"52.588%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='OtherRenewableEnergy'></A><b>OTHERRENEWABLEENERGY</b>\",\n            \"\",\n            \"Subtotal\",\n            \"67.9(0.120%)\",\n            \"34.2(0.099%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"DaGuan2#1\",\n            \"250.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"DaGuan2#2\",\n            \"250.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"DaGuan2#3\",\n            \"250.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"DaGuan2#4\",\n            \"250.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#1\",\n            \"267.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#2\",\n            \"267.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#3\",\n            \"267.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#4\",\n            \"267.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#5\",\n            \"267.0\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#6\",\n            \"267.0\",\n            \"0.0\",\n            \"0.000%\",\n            \"1\",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"Battery\",\n            \"Battery(Remark XVI)\",\n            \"573.3\",\n            \"0.0\",\n            \"0.000%\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystem'></A><b>ENERGYSTORAGESYSTEM</b>\",\n            \"\",\n            \"Subtotal\",\n            \"3175.3(5.625%)\",\n            \"0.0(0.000%)\",\n            \"\",\n            \"\",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"DaGuan2#1\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"DaGuan2#2\",\n            \"-\",\n            \"-238.4\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"DaGuan2#3\",\n            \"-\",\n            \"-235.6\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"DaGuan2#4\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#1\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#2\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#3\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#4\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#5\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \" \",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Pumped Hydro\",\n            \"Mingtan#6\",\n            \"-\",\n            \"0.0\",\n            \"-\",\n            \"1\",\n            \"\"\n        ],\n        [\n            \"<A NAME='EnergyStorageSystemLoad'></A><b>ENERGYSTORAGESYSTEMLOAD</b>\",\n            \"Battery\",\n            \"Battery(Remark XVI)\",\n            \"-\",\n            \"-5.2\",\n            \"-\",\n            \" \",\n            \"\"\n        ]\n    ],\n    \"SubUnitSet\": []\n}"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/TR/raw_production_response.json",
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    "content": "{\"MktDay\":\"03-10-2025\",\"RefId\":\"10-Mar-2025 - Interval 04:00 EST\",\"Forecast\":[{\"DateTimeEST\":\"2025-03-10 12:00:00 AM\",\"HourEndingEST\":\"1\",\"Value\":\"17716.00\"},{\"DateTimeEST\":\"2025-03-10 1:00:00 AM\",\"HourEndingEST\":\"2\",\"Value\":\"17168.00\"},{\"DateTimeEST\":\"2025-03-10 2:00:00 AM\",\"HourEndingEST\":\"3\",\"Value\":\"16628.00\"},{\"DateTimeEST\":\"2025-03-10 3:00:00 AM\",\"HourEndingEST\":\"4\",\"Value\":\"16249.00\"},{\"DateTimeEST\":\"2025-03-10 4:00:00 AM\",\"HourEndingEST\":\"5\",\"Value\":\"16089.00\"},{\"DateTimeEST\":\"2025-03-10 5:00:00 AM\",\"HourEndingEST\":\"6\",\"Value\":\"16192.00\"},{\"DateTimeEST\":\"2025-03-10 6:00:00 AM\",\"HourEndingEST\":\"7\",\"Value\":\"16583.00\"},{\"DateTimeEST\":\"2025-03-10 7:00:00 AM\",\"HourEndingEST\":\"8\",\"Value\":\"17076.00\"},{\"DateTimeEST\":\"2025-03-10 8:00:00 AM\",\"HourEndingEST\":\"9\",\"Value\":\"17386.00\"},{\"DateTimeEST\":\"2025-03-10 9:00:00 AM\",\"HourEndingEST\":\"10\",\"Value\":\"17154.00\"},{\"DateTimeEST\":\"2025-03-10 10:00:00 AM\",\"HourEndingEST\":\"11\",\"Value\":\"16391.00\"},{\"DateTimeEST\":\"2025-03-10 11:00:00 AM\",\"HourEndingEST\":\"12\",\"Value\":\"16389.00\"},{\"DateTimeEST\":\"2025-03-10 12:00:00 PM\",\"HourEndingEST\":\"13\",\"Value\":\"17767.00\"},{\"DateTimeEST\":\"2025-03-10 1:00:00 PM\",\"HourEndingEST\":\"14\",\"Value\":\"19703.00\"},{\"DateTimeEST\":\"2025-03-10 2:00:00 PM\",\"HourEndingEST\":\"15\",\"Value\":\"21282.00\"},{\"DateTimeEST\":\"2025-03-10 3:00:00 PM\",\"HourEndingEST\":\"16\",\"Value\":\"22330.00\"},{\"DateTimeEST\":\"2025-03-10 4:00:00 PM\",\"HourEndingEST\":\"17\",\"Value\":\"22727.00\"},{\"DateTimeEST\":\"2025-03-10 5:00:00 PM\",\"HourEndingEST\":\"18\",\"Value\":\"22525.00\"},{\"DateTimeEST\":\"2025-03-10 6:00:00 PM\",\"HourEndingEST\":\"19\",\"Value\":\"22427.00\"},{\"DateTimeEST\":\"2025-03-10 7:00:00 PM\",\"HourEndingEST\":\"20\",\"Value\":\"23044.00\"},{\"DateTimeEST\":\"2025-03-10 8:00:00 PM\",\"HourEndingEST\":\"21\",\"Value\":\"23647.00\"},{\"DateTimeEST\":\"2025-03-10 9:00:00 PM\",\"HourEndingEST\":\"22\",\"Value\":\"23981.00\"},{\"DateTimeEST\":\"2025-03-10 10:00:00 PM\",\"HourEndingEST\":\"23\",\"Value\":\"24047.00\"},{\"DateTimeEST\":\"2025-03-10 11:00:00 PM\",\"HourEndingEST\":\"24\",\"Value\":\"23881.00\"},{\"DateTimeEST\":\"2025-03-11 12:00:00 AM\",\"HourEndingEST\":\"1\",\"Value\":\"23596.00\"},{\"DateTimeEST\":\"2025-03-11 1:00:00 AM\",\"HourEndingEST\":\"2\",\"Value\":\"23196.00\"},{\"DateTimeEST\":\"2025-03-11 2:00:00 AM\",\"HourEndingEST\":\"3\",\"Value\":\"23034.00\"},{\"DateTimeEST\":\"2025-03-11 3:00:00 AM\",\"HourEndingEST\":\"4\",\"Value\":\"23022.00\"},{\"DateTimeEST\":\"2025-03-11 4:00:00 AM\",\"HourEndingEST\":\"5\",\"Value\":\"22831.00\"},{\"DateTimeEST\":\"2025-03-11 5:00:00 AM\",\"HourEndingEST\":\"6\",\"Value\":\"22327.00\"},{\"DateTimeEST\":\"2025-03-11 6:00:00 AM\",\"HourEndingEST\":\"7\",\"Value\":\"21393.00\"},{\"DateTimeEST\":\"2025-03-11 7:00:00 AM\",\"HourEndingEST\":\"8\",\"Value\":\"19830.00\"},{\"DateTimeEST\":\"2025-03-11 8:00:00 AM\",\"HourEndingEST\":\"9\",\"Value\":\"17808.00\"},{\"DateTimeEST\":\"2025-03-11 9:00:00 AM\",\"HourEndingEST\":\"10\",\"Value\":\"15679.00\"},{\"DateTimeEST\":\"2025-03-11 10:00:00 AM\",\"HourEndingEST\":\"11\",\"Value\":\"13413.00\"},{\"DateTimeEST\":\"2025-03-11 11:00:00 AM\",\"HourEndingEST\":\"12\",\"Value\":\"11073.00\"},{\"DateTimeEST\":\"2025-03-11 12:00:00 PM\",\"HourEndingEST\":\"13\",\"Value\":\"9176.00\"},{\"DateTimeEST\":\"2025-03-11 1:00:00 PM\",\"HourEndingEST\":\"14\",\"Value\":\"8033.00\"},{\"DateTimeEST\":\"2025-03-11 2:00:00 PM\",\"HourEndingEST\":\"15\",\"Value\":\"7338.00\"},{\"DateTimeEST\":\"2025-03-11 3:00:00 PM\",\"HourEndingEST\":\"16\",\"Value\":\"6885.00\"},{\"DateTimeEST\":\"2025-03-11 4:00:00 PM\",\"HourEndingEST\":\"17\",\"Value\":\"6934.00\"},{\"DateTimeEST\":\"2025-03-11 5:00:00 PM\",\"HourEndingEST\":\"18\",\"Value\":\"7577.00\"},{\"DateTimeEST\":\"2025-03-11 6:00:00 PM\",\"HourEndingEST\":\"19\",\"Value\":\"8756.00\"},{\"DateTimeEST\":\"2025-03-11 7:00:00 PM\",\"HourEndingEST\":\"20\",\"Value\":\"11393.00\"},{\"DateTimeEST\":\"2025-03-11 8:00:00 PM\",\"HourEndingEST\":\"21\",\"Value\":\"13542.00\"},{\"DateTimeEST\":\"2025-03-11 9:00:00 PM\",\"HourEndingEST\":\"22\",\"Value\":\"14719.00\"},{\"DateTimeEST\":\"2025-03-11 10:00:00 PM\",\"HourEndingEST\":\"23\",\"Value\":\"15219.00\"},{\"DateTimeEST\":\"2025-03-11 11:00:00 PM\",\"HourEndingEST\":\"24\",\"Value\":\"15321.00\"}]}"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_NEISO/day_ahead_load_forecast_20250317.xml",
    "content": 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  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_NEISO/seven_day_solar_power_forecast_20250225.csv",
    "content": "\"C\",\"ISO New England Inc. Seven Day Solar Power Forecast Report\"\n\"C\",\"Filename: seven_day_solar_power_forecast_20250225.csv\"\n\"C\",\"Report for 02/25/2025\"\n\"C\",\"Report generated 02/25/2025 10:02:35 EST\"\n\"H\",\"\",,\"Day 1\",\"Day 2\",\"Day 3\",\"Day 4\",\"Day 5\",\"Day 6\",\"Day 7\",\"Day 8\"\n\"D\",\"Day\",,\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\",\"Sun\",\"Mon\",\"Tue\"\n\"D\",\"Date\",\"Hour Ending\",\"02/25/2025\",\"02/26/2025\",\"02/27/2025\",\"02/28/2025\",\"03/01/2025\",\"03/02/2025\",\"03/03/2025\",\"03/04/2025\"\n\"D\",,01,,0,0,0,0,0,0,0\n\"D\",,02,,0,0,0,0,0,0,0\n\"D\",,03,,0,0,0,0,0,0,0\n\"D\",,04,,0,0,0,0,0,0,0\n\"D\",,05,,0,0,0,0,0,0,0\n\"D\",,06,,0,0,0,0,0,0,0\n\"D\",,07,,21,7,0,0,0,0,0\n\"D\",,08,,173,33,0,0,0,0,0\n\"D\",,09,,454,69,59,22,97,84,213\n\"D\",,10,,705,100,366,205,449,404,439\n\"D\",,11,661,842,100,597,304,657,602,\n\"D\",,12,704,879,134,805,488,848,791,\n\"D\",,13,666,887,169,860,557,891,842,\n\"D\",,14,545,860,191,760,630,910,862,\n\"D\",,15,447,762,190,781,586,888,845,\n\"D\",,16,267,520,146,759,474,819,785,\n\"D\",,17,69,203,88,601,388,611,584,\n\"D\",,18,13,30,51,222,131,194,180,\n\"D\",,19,1,1,14,72,31,49,46,\n\"D\",,20,0,0,0,2,2,1,1,\n\"D\",,21,0,0,0,0,0,0,0,\n\"D\",,22,0,0,0,0,0,0,0,\n\"D\",,23,0,0,0,0,0,0,0,\n\"D\",,24,0,0,0,0,0,0,0,\n\"T\",\"24 lines\""
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  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_NEISO/seven_day_wind_power_forecast_20250225.csv",
    "content": "\"C\",\"ISO New England Inc. Seven Day Wind Power Forecast Report\"\n\"C\",\"Filename: seven_day_wind_power_forecast_20250225.csv\"\n\"C\",\"Report for 02/25/2025\"\n\"C\",\"Report generated 02/25/2025 10:08:14 EST\"\n\"H\",\"\",,\"Day 1\",\"Day 2\",\"Day 3\",\"Day 4\",\"Day 5\",\"Day 6\",\"Day 7\",\"Day 8\"\n\"D\",\"Day\",,\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\",\"Sun\",\"Mon\",\"Tue\"\n\"D\",\"Date\",\"Hour Ending\",\"02/25/2025\",\"02/26/2025\",\"02/27/2025\",\"02/28/2025\",\"03/01/2025\",\"03/02/2025\",\"03/03/2025\",\"03/04/2025\"\n\"D\",,01,,205,352,470,408,991,690,283\n\"D\",,02,,221,242,509,289,991,682,275\n\"D\",,03,,270,158,511,252,993,686,302\n\"D\",,04,,340,99,519,234,995,692,330\n\"D\",,05,,439,66,522,224,992,697,367\n\"D\",,06,,503,80,507,257,1002,710,356\n\"D\",,07,,568,112,495,304,1004,725,357\n\"D\",,08,,643,147,486,367,1006,738,356\n\"D\",,09,,655,178,592,434,1059,818,449\n\"D\",,10,,694,224,682,516,1114,898,525\n\"D\",,11,234,750,275,743,611,1152,962,\n\"D\",,12,147,811,313,869,652,1160,939,\n\"D\",,13,115,895,339,966,696,1168,909,\n\"D\",,14,109,966,365,1010,734,1170,877,\n\"D\",,15,117,998,360,1148,664,1154,836,\n\"D\",,16,116,1009,344,1248,589,1132,788,\n\"D\",,17,117,969,323,1279,530,1102,738,\n\"D\",,18,118,920,313,1254,612,1080,676,\n\"D\",,19,125,885,325,1226,716,1058,606,\n\"D\",,20,153,853,328,1164,823,1028,541,\n\"D\",,21,161,747,358,1052,864,927,455,\n\"D\",,22,148,700,385,882,912,817,378,\n\"D\",,23,152,599,400,717,966,704,309,\n\"D\",,24,165,483,434,554,981,698,294,\n\"T\",\"24 lines\""
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_NY/20250219isolf.csv",
    "content": "\"Time Stamp\",\"Capitl\",\"Centrl\",\"Dunwod\",\"Genese\",\"Hud Vl\",\"Longil\",\"Mhk Vl\",\"Millwd\",\"N.Y.C.\",\"North\",\"West\",\"NYISO\"\n\"02/19/2025 00:00\",1492,1882,700,1132,1215,2257,1051,364,5527,653,1781,18054\n\"02/19/2025 01:00\",1470,1850,682,1121,1189,2184,1028,359,5339,657,1757,17636\n\"02/19/2025 02:00\",1461,1836,669,1110,1177,2141,1029,355,5227,656,1741,17402\n\"02/19/2025 03:00\",1465,1829,663,1112,1176,2130,1029,352,5180,658,1736,17330\n\"02/19/2025 04:00\",1497,1869,672,1138,1191,2171,1053,359,5227,663,1750,17590\n\"02/19/2025 05:00\",1568,1953,699,1195,1245,2286,1109,380,5448,673,1808,18364\n\"02/19/2025 06:00\",1681,2089,760,1282,1320,2462,1194,418,5916,691,1904,19717\n\"02/19/2025 07:00\",1723,2173,808,1329,1345,2523,1231,433,6333,699,1960,20557\n\"02/19/2025 08:00\",1640,2148,805,1343,1274,2447,1230,416,6545,700,1992,20540\n\"02/19/2025 09:00\",1528,2072,798,1320,1191,2385,1211,398,6669,694,1997,20263\n\"02/19/2025 10:00\",1460,2038,786,1304,1141,2328,1185,385,6680,686,1994,19987\n\"02/19/2025 11:00\",1425,1978,776,1284,1121,2264,1167,371,6653,685,1976,19700\n\"02/19/2025 12:00\",1393,1947,769,1264,1108,2220,1149,363,6616,680,1956,19465\n\"02/19/2025 13:00\",1414,1951,769,1254,1107,2247,1134,362,6593,679,1948,19458\n\"02/19/2025 14:00\",1446,1956,773,1246,1127,2312,1132,366,6587,676,1934,19555\n\"02/19/2025 15:00\",1538,1993,787,1259,1218,2455,1140,382,6682,680,1934,20068\n\"02/19/2025 16:00\",1666,2100,807,1292,1332,2624,1190,400,6771,686,1954,20822\n\"02/19/2025 17:00\",1780,2206,837,1348,1430,2791,1242,424,6852,695,1982,21587\n\"02/19/2025 18:00\",1823,2272,862,1384,1483,2894,1271,445,6847,705,2042,22028\n\"02/19/2025 19:00\",1803,2254,857,1368,1474,2870,1258,440,6770,704,2038,21836\n\"02/19/2025 20:00\",1755,2196,832,1326,1444,2794,1231,429,6617,700,2005,21329\n\"02/19/2025 21:00\",1682,2116,806,1269,1389,2662,1186,412,6405,689,1943,20559\n\"02/19/2025 22:00\",1601,2008,760,1195,1322,2509,1131,384,6108,679,1868,19565\n\"02/19/2025 23:00\",1545,1926,712,1138,1256,2349,1085,360,5776,675,1799,18621\n\"02/20/2025 00:00\",1490,1855,675,1107,1195,2198,1045,355,5467,675,1761,17823\n\"02/20/2025 01:00\",1471,1824,659,1094,1170,2128,1021,350,5282,679,1737,17415\n\"02/20/2025 02:00\",1463,1805,645,1082,1159,2084,1019,346,5173,677,1722,17175\n\"02/20/2025 03:00\",1469,1794,637,1085,1163,2072,1017,342,5123,678,1716,17096\n\"02/20/2025 04:00\",1498,1832,646,1110,1175,2113,1037,349,5167,682,1728,17337\n\"02/20/2025 05:00\",1567,1918,676,1165,1228,2227,1088,371,5384,693,1783,18100\n\"02/20/2025 06:00\",1676,2054,736,1250,1301,2395,1169,408,5833,712,1877,19411\n\"02/20/2025 07:00\",1734,2145,788,1297,1358,2502,1210,427,6257,720,1935,20373\n\"02/20/2025 08:00\",1716,2146,799,1315,1370,2519,1218,420,6493,719,1973,20688\n\"02/20/2025 09:00\",1679,2096,803,1299,1345,2497,1198,409,6643,713,1989,20671\n\"02/20/2025 10:00\",1643,2074,798,1288,1314,2477,1170,401,6692,708,1995,20560\n\"02/20/2025 11:00\",1614,2015,793,1274,1293,2448,1153,390,6686,704,1987,20357\n\"02/20/2025 12:00\",1572,1993,782,1265,1280,2414,1133,384,6670,701,1973,20167\n\"02/20/2025 13:00\",1558,2000,779,1266,1268,2412,1117,377,6642,699,1968,20086\n\"02/20/2025 14:00\",1555,1995,778,1258,1269,2434,1113,378,6625,694,1955,20054\n\"02/20/2025 15:00\",1600,2014,784,1260,1307,2509,1118,387,6685,696,1951,20311\n\"02/20/2025 16:00\",1675,2089,794,1275,1355,2620,1157,398,6735,700,1956,20754\n\"02/20/2025 17:00\",1745,2171,818,1320,1418,2747,1207,419,6785,709,1976,21315\n\"02/20/2025 18:00\",1776,2231,842,1355,1462,2847,1238,436,6771,717,2031,21706\n\"02/20/2025 19:00\",1760,2202,838,1338,1451,2827,1229,431,6688,714,2026,21504\n\"02/20/2025 20:00\",1714,2140,813,1296,1421,2752,1198,420,6534,707,1993,20988\n\"02/20/2025 21:00\",1642,2058,786,1238,1367,2624,1153,401,6324,696,1929,20218\n\"02/20/2025 22:00\",1559,1945,739,1164,1299,2475,1097,373,6032,686,1852,19221\n\"02/20/2025 23:00\",1501,1861,693,1107,1231,2322,1048,349,5711,677,1784,18284\n\"02/21/2025 00:00\",1444,1803,658,1078,1165,2179,1009,345,5403,676,1748,17508\n\"02/21/2025 01:00\",1418,1771,641,1064,1137,2104,982,338,5210,675,1722,17062\n\"02/21/2025 02:00\",1406,1749,625,1052,1121,2054,976,335,5087,672,1706,16783\n\"02/21/2025 03:00\",1408,1744,616,1054,1122,2037,971,331,5030,672,1701,16686\n\"02/21/2025 04:00\",1434,1784,622,1081,1134,2073,991,337,5067,676,1712,16911\n\"02/21/2025 05:00\",1494,1863,653,1136,1182,2183,1037,357,5278,689,1767,17639\n\"02/21/2025 06:00\",1591,1999,710,1221,1250,2363,1110,392,5734,710,1858,18938\n\"02/21/2025 07:00\",1638,2095,759,1270,1285,2446,1152,407,6136,722,1918,19828\n\"02/21/2025 08:00\",1592,2106,758,1293,1237,2386,1161,391,6334,727,1959,19944\n\"02/21/2025 09:00\",1500,2063,743,1283,1132,2285,1147,368,6437,719,1974,19651\n\"02/21/2025 10:00\",1432,2049,722,1271,1040,2202,1124,347,6429,712,1974,19302\n\"02/21/2025 11:00\",1388,1989,704,1256,986,2123,1103,329,6389,710,1962,18939\n\"02/21/2025 12:00\",1342,1958,690,1243,952,2041,1080,317,6328,706,1939,18596\n\"02/21/2025 13:00\",1336,1945,685,1233,971,2006,1064,313,6260,704,1927,18444\n\"02/21/2025 14:00\",1363,1926,691,1220,998,2038,1060,317,6231,699,1908,18451\n\"02/21/2025 15:00\",1446,1936,713,1212,1082,2178,1065,336,6314,702,1896,18880\n\"02/21/2025 16:00\",1571,2009,739,1232,1218,2384,1115,363,6414,712,1908,19665\n\"02/21/2025 17:00\",1668,2083,775,1267,1327,2583,1160,391,6544,718,1925,20441\n\"02/21/2025 18:00\",1706,2135,799,1298,1376,2705,1184,412,6556,724,1971,20866\n\"02/21/2025 19:00\",1688,2104,793,1280,1371,2693,1171,409,6482,722,1959,20672\n\"02/21/2025 20:00\",1652,2046,771,1241,1351,2635,1141,400,6324,720,1926,20207\n\"02/21/2025 21:00\",1603,1991,750,1195,1315,2541,1107,388,6146,712,1881,19629\n\"02/21/2025 22:00\",1545,1905,718,1134,1270,2439,1065,370,5915,705,1821,18887\n\"02/21/2025 23:00\",1499,1826,681,1081,1220,2315,1021,351,5651,698,1756,18099\n\"02/22/2025 00:00\",1435,1784,648,1053,1159,2161,983,343,5348,706,1719,17339\n\"02/22/2025 01:00\",1406,1760,628,1037,1130,2081,964,334,5167,706,1693,16906\n\"02/22/2025 02:00\",1392,1750,609,1023,1110,2036,956,332,5046,704,1673,16631\n\"02/22/2025 03:00\",1392,1736,601,1016,1109,2009,956,331,4965,704,1663,16482\n\"02/22/2025 04:00\",1401,1747,600,1022,1113,2020,967,331,4950,703,1667,16521\n\"02/22/2025 05:00\",1425,1791,614,1043,1132,2067,987,342,5022,712,1687,16822\n\"02/22/2025 06:00\",1474,1845,639,1080,1164,2151,1020,357,5184,718,1727,17359\n\"02/22/2025 07:00\",1523,1891,663,1114,1194,2189,1062,373,5369,730,1756,17864\n\"02/22/2025 08:00\",1531,1918,681,1150,1197,2185,1084,381,5569,742,1795,18233\n\"02/22/2025 09:00\",1498,1889,683,1148,1137,2136,1069,372,5701,741,1813,18187\n\"02/22/2025 10:00\",1458,1823,668,1131,1061,2060,1051,357,5758,734,1810,17911\n\"02/22/2025 11:00\",1418,1760,656,1121,1006,2007,1021,341,5773,727,1788,17618\n\"02/22/2025 12:00\",1369,1723,645,1098,972,1946,994,332,5721,719,1768,17287\n\"02/22/2025 13:00\",1327,1632,633,999,921,1912,909,321,5663,707,1711,16735\n\"02/22/2025 14:00\",1336,1645,637,998,942,1977,904,324,5656,702,1707,16828\n\"02/22/2025 15:00\",1390,1710,655,1039,1050,2112,948,338,5709,704,1732,17387\n\"02/22/2025 16:00\",1497,1840,682,1117,1186,2294,1018,362,5800,713,1790,18299\n\"02/22/2025 17:00\",1565,1921,708,1176,1259,2457,1071,379,5888,723,1837,18984\n\"02/22/2025 18:00\",1593,1971,728,1213,1298,2548,1097,389,5991,731,1879,19438\n\"02/22/2025 19:00\",1570,1953,721,1198,1289,2509,1086,384,5961,728,1868,19267\n\"02/22/2025 20:00\",1534,1901,710,1163,1264,2450,1066,377,5861,720,1828,18874\n\"02/22/2025 21:00\",1487,1835,691,1121,1226,2365,1033,361,5728,711,1777,18335\n\"02/22/2025 22:00\",1438,1763,666,1073,1184,2265,995,341,5543,705,1721,17694\n\"02/22/2025 23:00\",1396,1707,633,1023,1130,2149,957,323,5330,697,1670,17015\n\"02/23/2025 00:00\",1347,1683,606,1004,1082,2003,914,317,5069,693,1657,16375\n\"02/23/2025 01:00\",1317,1660,587,990,1053,1929,897,306,4903,691,1635,15968\n\"02/23/2025 02:00\",1303,1652,570,978,1031,1885,889,304,4788,690,1621,15711\n\"02/23/2025 03:00\",1302,1641,561,972,1030,1860,889,303,4719,690,1614,15581\n\"02/23/2025 04:00\",1307,1653,561,977,1034,1871,899,302,4713,692,1619,15628\n\"02/23/2025 05:00\",1324,1694,574,995,1053,1909,915,312,4777,700,1636,15889\n\"02/23/2025 06:00\",1363,1743,594,1027,1082,1971,944,324,4891,704,1666,16309\n\"02/23/2025 07:00\",1395,1787,613,1051,1104,2005,975,339,5029,710,1685,16693\n\"02/23/2025 08:00\",1396,1819,627,1074,1100,2000,981,349,5190,718,1710,16964\n\"02/23/2025 09:00\",1376,1806,631,1059,1032,1958,960,343,5304,716,1722,16907\n\"02/23/2025 10:00\",1365,1768,623,1039,979,1909,943,335,5377,709,1716,16763\n\"02/23/2025 11:00\",1367,1735,619,1040,967,1902,927,327,5433,703,1703,16723\n\"02/23/2025 12:00\",1353,1719,613,1032,974,1860,912,322,5419,697,1691,16592\n\"02/23/2025 13:00\",1348,1700,610,1022,981,1860,900,318,5417,691,1697,16544\n\"02/23/2025 14:00\",1363,1721,618,1027,1012,1925,896,321,5450,688,1699,16720\n\"02/23/2025 15:00\",1409,1782,632,1069,1090,2053,938,332,5529,693,1730,17257\n\"02/23/2025 16:00\",1495,1879,659,1129,1189,2223,994,354,5647,705,1779,18053\n\"02/23/2025 17:00\",1551,1934,689,1170,1256,2391,1038,370,5762,715,1813,18689\n\"02/23/2025 18:00\",1580,1982,715,1208,1298,2501,1066,382,5896,722,1861,19211\n\"02/23/2025 19:00\",1552,1964,710,1193,1284,2475,1056,380,5880,716,1852,19062\n\"02/23/2025 20:00\",1506,1911,703,1160,1250,2421,1031,373,5800,710,1821,18686\n\"02/23/2025 21:00\",1444,1838,681,1116,1203,2331,995,355,5676,701,1774,18114\n\"02/23/2025 22:00\",1385,1763,649,1067,1155,2223,955,332,5470,691,1722,17412\n\"02/23/2025 23:00\",1339,1712,611,1019,1098,2097,921,311,5221,686,1679,16694\n\"02/24/2025 00:00\",1297,1667,583,993,1046,1949,885,305,4954,680,1672,16031\n\"02/24/2025 01:00\",1278,1642,569,986,1022,1887,869,300,4804,679,1659,15695\n\"02/24/2025 02:00\",1273,1633,556,980,1011,1853,869,297,4712,680,1650,15514\n\"02/24/2025 03:00\",1278,1632,551,987,1015,1848,870,295,4670,681,1653,15480\n\"02/24/2025 04:00\",1307,1677,559,1016,1031,1893,894,302,4730,685,1672,15766\n\"02/24/2025 05:00\",1381,1775,589,1080,1088,2013,949,323,4967,698,1738,16601\n\"02/24/2025 06:00\",1496,1927,643,1176,1167,2195,1034,363,5400,723,1849,17973\n\"02/24/2025 07:00\",1561,2024,697,1231,1229,2311,1082,381,5812,736,1919,18983\n\"02/24/2025 08:00\",1549,2021,707,1245,1233,2305,1076,372,6020,734,1944,19206\n\"02/24/2025 09:00\",1511,1971,704,1220,1180,2206,1046,355,6119,726,1942,18980\n\"02/24/2025 10:00\",1481,1935,692,1201,1123,2109,1010,339,6114,718,1939,18661\n\"02/24/2025 11:00\",1457,1874,680,1183,1087,2045,991,325,6088,710,1920,18360\n\"02/24/2025 12:00\",1413,1843,665,1167,1054,1973,964,314,6029,704,1896,18022\n\"02/24/2025 13:00\",1390,1835,662,1158,1038,1978,935,309,5985,698,1887,17875\n\"02/24/2025 14:00\",1381,1820,664,1149,1042,2027,930,312,5959,697,1877,17858\n\"02/24/2025 15:00\",1417,1833,677,1155,1094,2133,946,324,6016,698,1880,18173\n\"02/24/2025 16:00\",1494,1914,695,1179,1170,2274,994,341,6095,707,1901,18764\n\"02/24/2025 17:00\",1568,1994,717,1219,1242,2434,1038,362,6164,715,1911,19364\n\"02/24/2025 18:00\",1612,2058,741,1253,1300,2570,1073,383,6181,723,1960,19854\n\"02/24/2025 19:00\",1589,2027,735,1235,1294,2558,1063,379,6106,718,1946,19650\n\"02/24/2025 20:00\",1538,1963,710,1191,1261,2482,1032,369,5949,711,1907,19113\n\"02/24/2025 21:00\",1467,1880,683,1131,1205,2351,988,352,5741,699,1844,18341\n\"02/24/2025 22:00\",1389,1773,641,1059,1137,2198,936,323,5439,685,1769,17349\n\"02/24/2025 23:00\",1332,1696,597,1005,1075,2053,896,301,5130,678,1702,16465\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_PJM/gen_by_fuel.json",
    "content": "{\n  \"links\": [\n    {\n      \"rel\": \"self\",\n      \"href\": \"https://api.pjm.com/api/v1/gen_by_fuel?RowCount=500&Order=Asc&StartRow=1&IsActiveMetadata=True&Fields=datetime_beginning_utc%2Cfuel_type%2Cmw&datetime_beginning_utc=2025-02-09T00%3A00%3A00.0000000\"\n    },\n    {\n      \"rel\": \"metadata\",\n      \"href\": \"https://api.pjm.com/api/v1/gen_by_fuel/metadata\"\n    }\n  ],\n  \"items\": [\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Coal\",\n      \"mw\": 16908.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Gas\",\n      \"mw\": 47280.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Hydro\",\n      \"mw\": 2971.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Multiple Fuels\",\n      \"mw\": 1179.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Nuclear\",\n      \"mw\": 32919.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Oil\",\n      \"mw\": 871.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Other Renewables\",\n      \"mw\": 659.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Solar\",\n      \"mw\": 28.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Storage\",\n      \"mw\": 8.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T00:00:00\",\n      \"fuel_type\": \"Wind\",\n      \"mw\": 2782.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T01:00:00\",\n      \"fuel_type\": \"Coal\",\n      \"mw\": 17147.0\n    },\n    {\n      \"datetime_beginning_utc\": \"2025-02-09T01:00:00\",\n      \"fuel_type\": \"Gas\",\n      \"mw\": 46725.0\n    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01:00:00,03/19/2025 06:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,19.3693,0.1711,7.4833,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,COWP,COWP_LA,10.3507,0.1178,-1.4819,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,10.3507,0.1178,-1.4819,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,10.3507,0.1178,-1.4819,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CPLE,VACS,9.2392,0.1223,-2.5980,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CPLW,VACS,9.2392,0.1223,-2.5980,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,11.4044,0.2099,-0.5203,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,11.4044,0.2099,-0.5203,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,11.4044,0.2099,-0.5203,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,11.4044,0.2099,-0.5203,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CRTH_SPA,WRCRTH_SPA_LA,16.0160,0.0168,4.2843,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,18.9651,0.5904,6.6598,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-12.7286,-0.6415,-23.8019,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,20.1359,-0.1050,8.5261,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,19.8398,0.1965,7.9284,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,18.9665,0.5848,6.6669,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,18.9295,0.2341,6.9805,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,19.0143,0.4878,6.8116,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,19.0143,0.4878,6.8116,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,19.3365,0.2724,7.3493,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,19.3365,0.2724,7.3493,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,19.3366,0.2724,7.3493,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,19.3366,0.2724,7.3493,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,20.1359,-0.1050,8.5261,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,23.1065,0.3839,11.0078,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,39.7853,-0.0458,28.1163,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,39.6987,-0.1324,28.1163,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,23.0706,0.0641,11.2917,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,19.2078,0.1588,7.3342,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,19.2078,0.1588,7.3342,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,19.2105,0.1588,7.3369,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,19.2105,0.1588,7.3369,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-19.8328,-0.7037,-30.8439,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,-11.9651,-0.5202,-23.1597,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,30.4273,0.0037,18.7088,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-16.5128,-0.6262,-27.6015,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-16.5239,-0.6372,-27.6015,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-15.8439,-0.5794,-26.9793,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.GRID.CDL1,CDL1_DDR,24.9561,0.1497,13.0916,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-14.5339,-0.5667,-25.6821,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-11.6923,-0.6624,-22.7447,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,24.9561,0.1497,13.0916,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.NUEN.CSI1,CSI1_DDR,22.8830,0.2531,10.9151,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.NUEN.CSI2,CSI2_DDR,22.8864,0.2564,10.9151,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,19.3706,0.1725,7.4833,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.NUEN.GAZA,GAZA_DDR,24.9561,0.1497,13.0916,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,95.0000,0.3718,82.9134,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.NUEN.T201,NT201_DDR,20.1855,0.1688,8.3018,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-14.4131,-0.8187,-25.3092,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-14.4131,-0.8187,-25.3092,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,20.1359,-0.1050,8.5261,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,19.8071,0.6628,7.4295,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-15.8439,-0.5794,-26.9793,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-15.8439,-0.5794,-26.9793,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-17.8202,-0.7029,-28.8322,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-16.5239,-0.6372,-27.6015,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,18.4579,0.2167,6.5264,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,16.5043,0.0952,4.6943,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,16.5043,0.0952,4.6943,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,16.5043,0.0952,4.6943,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,-1.4310,-0.0734,-13.0725,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,-1.4310,-0.0734,-13.0725,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,19.0373,0.2120,7.1105,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,20.5498,0.1654,8.6696,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,18.9892,0.1990,7.0753,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,20.0463,0.8604,7.4710,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,25.2391,0.0937,13.4306,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,22.8864,0.2564,10.9151,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0057,OKMU_DDR,22.6105,0.2499,10.6457,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0060,LEHIGH_DDR,95.0000,0.3718,82.9134,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0086,WARRENM_DDR,19.6603,0.1984,7.7470,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,20.0713,0.5776,7.7788,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,31.2117,0.1624,19.3344,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0121,V121_DDR,19.0373,0.2120,7.1105,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0122,V122_DDR,29.6797,0.1508,17.8141,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0124,V124_DDR,48.9416,0.0875,37.1392,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0135,V135_DDR,20.6510,0.2011,8.7350,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0144,V144_DDR,-12.0906,-0.4712,-23.3342,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0145,V145_DDR,-12.2516,-0.5271,-23.4394,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,19.0884,0.2402,7.1333,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,20.5236,0.0742,8.7346,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0175,V175_DDR,19.3706,0.1725,7.4833,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,20.5236,0.0742,8.7346,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,20.5632,0.1419,8.7065,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,20.6510,0.2011,8.7350,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,21.0004,0.1816,9.1039,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,20.5916,0.1553,8.7215,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,35.7502,0.0365,23.9989,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,19.3038,0.1520,7.4370,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,21.0004,0.1816,9.1039,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0211,V211_DDR,19.0493,0.3475,6.9869,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,31.9606,0.1513,20.0944,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0213,V213_DDR,20.4533,0.1884,8.5500,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0215,V215_DDR,30.7133,0.1507,18.8478,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0217,V217_DDR,32.0210,0.1434,20.1628,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0218,V218_DDR,35.3005,0.0437,23.5420,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0228,V228_DDR,21.1356,0.1523,9.2685,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0232,V232_DDR,19.9864,0.1994,8.0722,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0233,V233_DDR,21.1339,0.1935,9.2256,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0240,V240_DDR,27.1609,0.1322,15.3138,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0244,V244_DDR,21.0004,0.1816,9.1039,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0246,MDT1_DDR,95.0000,0.3718,82.9134,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0249,V249_DDR,20.3962,0.1966,8.4848,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0250,V250_DDR,-13.0451,-0.6141,-24.1459,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0251,V251_DDR,19.7324,0.1737,7.8438,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.VOLT.0252,V252_DDR,35.7502,0.0365,23.9989,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-21.6735,-0.7187,-32.6696,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,-4.8448,-0.8027,-15.7570,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-19.6566,-1.0651,-30.3064,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,18.7360,-0.0219,7.0431,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-30.4545,-1.7603,-40.4091,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-22.8472,-0.7443,-33.8178,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-22.8472,-0.7443,-33.8178,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-22.8472,-0.7443,-33.8178,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-22.8472,-0.7443,-33.8178,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-22.8472,-0.7443,-33.8178,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,20.1359,-0.1050,8.5261,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,17.6950,0.5895,5.3906,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,19.9763,0.1893,8.0722,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,19.9587,0.1716,8.0722,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,25.4193,0.2546,13.4499,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,25.4193,0.2546,13.4499,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWWELSH1,CSWSWELSHUN1_RA,19.7708,0.1475,7.9085,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWWELSH3,CSWSWELSHUN3_RA,19.7708,0.1475,7.9085,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWWILKES1,CSWSWILKESUN1_RA,19.7596,0.3089,7.7358,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWWILKES2,CSWSWILKESUN2_RA,19.7596,0.3089,7.7358,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,CSWWILKES3,CSWSWILKESUN3_RA,19.5068,0.2796,7.5123,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-16.5128,-0.6262,-27.6015,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,DENL,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,DERS,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,DOE,DOE,7.0036,0.0346,-4.7458,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,-5.0739,-0.2754,-16.5133,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,DPC,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,DUK,VACS,9.2392,0.1223,-2.5980,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDDY,EDDY,111.7272,1.6578,98.3546,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,15.1425,-0.0760,3.5036,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-19.1874,-0.2917,-30.6105,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,21.0611,-0.2149,9.5612,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE.SLCC,EDESTL4391_PLT,17.7788,-0.0745,6.1385,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,17.5655,-0.0490,5.8996,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,7.3588,-0.2756,-4.0804,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_EC_01,EDELAR3821UN1_RA,15.1425,-0.0760,3.5036,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_EC_02,EDELAR3821UN2_RA,15.1425,-0.0760,3.5036,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_EC_03,EDELAR3821UN3_RA,15.1425,-0.0760,3.5036,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_EC_04,EDELAR3821UN4_RA,15.1425,-0.0760,3.5036,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_EDE,EDE_LA,18.3651,0.1301,6.5201,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_ERW,EDEERWFUNG1_RA,-21.5292,-0.7108,-32.5332,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-14.2141,-0.8572,-25.0718,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,33.1200,0.3877,21.0175,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,33.1200,0.3877,21.0175,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,33.1200,0.3877,21.0175,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,33.1200,0.3877,21.0175,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,10.1396,0.1551,-1.7303,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_RIV_10,EDERIV1671UN10_RA,17.9702,-0.1244,6.3798,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_RIV_11,EDERIV1671UN11_RA,17.9702,-0.1244,6.3798,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_RIV_12,EDERIV453UN12_PLT,17.7633,-0.3313,6.3798,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_SL_01,EDESTL4391UN1_RA,17.7788,-0.0745,6.1385,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EDE_SWMP,EDE_SWMP_LA,13.1457,0.2095,1.2213,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,EEI,EEI,6.9683,0.0332,-4.7797,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EES,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-17.1711,-0.7555,-28.1305,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,ERCOTE,ERCOTE,19.7708,0.1475,7.9085,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,ERCOTN,ERCOTN,-14.3605,-0.7661,-25.3092,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,-7.3601,-0.6620,-18.4129,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,FMPP,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,FPC,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,FPL,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,FREM_50T,OPPDFREM_GUN1_RA,-5.3251,-0.5451,-16.4949,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,FREM_6,OPPDFREM_AUN6_RA,-5.3299,-0.5479,-16.4968,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,FREM_7,OPPDFREM_AUN7_RA,-5.3299,-0.5479,-16.4968,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,FREM_8,OPPDFREM_AUN8_RA,-5.3665,-0.5845,-16.4968,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,FREM_LOAD,FREM_LOAD_LA,-5.3358,-0.5538,-16.4968,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-22.5335,-0.6292,-33.6192,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,18.4579,0.2167,6.5264,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-18.5664,-0.5869,-29.6943,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-39.1889,-0.9881,-49.9157,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,19.3693,0.1711,7.4833,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,19.3693,0.1711,7.4833,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,19.3693,0.1711,7.4833,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,23.0712,0.1053,11.2511,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,23.0712,0.1053,11.2511,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,23.2069,0.1021,11.3899,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,23.2069,0.1021,11.3899,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-28.5971,-0.8991,-39.4129,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,39.8000,0.0016,28.0836,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,39.8000,0.0016,28.0836,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,39.8000,0.0016,28.0836,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.VOLT.0130,V130_DDR,23.8196,0.2326,11.8722,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA.VOLT.0237,V237_DDR,24.0745,0.1572,12.2024,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDAHUB2,GRDAHUB2_H,7.8363,-0.1489,-3.7297,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDAHUB3,GRDAHUB3_H,3.2889,-0.2406,-8.1853,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA_GRDA,GRDA_LA,24.3255,0.1482,12.4625,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA_HUB,GRDA_H,14.4204,-0.0286,2.7342,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRDA_HUBSA,GRDASA_H,13.9765,-0.0413,2.3030,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GRE,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-9.6496,1.0169,-22.3814,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GSEC_SPS,SPS_GSEC_LA,78.3501,0.7210,65.9143,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GSPR2014HUB,GSPR2014HUB_H,46.3570,0.5045,34.1377,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,GSPR2015HUB,GSPR2015HUB_H,43.8306,0.4683,31.6474,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,0.0000,0.2458,-11.9606,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,HARRISON,CSWSLEBROCKPLT1,18.8465,0.1373,6.9943,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,HAST_TNSK_HUB,HAST_TNSK_H,-7.5981,-0.7283,-18.5847,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,HQST,PJM,3.6788,-0.1215,-7.9145,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,HST,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,-4.7465,-0.0849,-16.3764,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,-4.7465,-0.0849,-16.3764,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,-4.7824,-0.0923,-16.4050,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,-4.7824,-0.0923,-16.4050,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,-4.7067,-0.0855,-16.3361,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,-4.7067,-0.0855,-16.3361,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,INDN_INDN,INDN_LA,-4.7508,-0.0868,-16.3788,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-18.9432,-0.9389,-29.7191,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,ISNE,PJM,3.6788,-0.1215,-7.9145,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,JEA,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,-5.1678,-0.5318,-16.3508,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,-5.1678,-0.5318,-16.3508,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-8.3871,-0.3095,-19.7924,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KACYCT4,KACYNEARMANUNCT4_RA,-6.0372,-0.1500,-17.6020,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,46.1000,-0.1917,34.5769,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,-6.0372,-0.1500,-17.6020,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,-6.0094,-0.1396,-17.5847,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,-6.0145,-0.1399,-17.5895,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KACY_KACY,KACY_LA,-6.0078,-0.1402,-17.5824,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,-5.5573,-0.2022,-17.0700,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,-1.2963,0.1646,-13.1757,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-30.0430,-0.4508,-41.3070,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-49.4264,-0.9418,-60.1995,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.VOLT.0222,V222_DDR,-5.9179,-0.2847,-17.3480,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.VOLT.0223,V223_DDR,-5.6837,-0.2813,-17.1172,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.VOLT.0241,V241_DDR,0.2740,0.1295,-11.5704,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.VOLT.0243,V243_DDR,12.0086,-0.0463,0.3401,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.VOLT.0247,V247_DDR,-5.1324,-0.2049,-16.6423,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.VOLT.0253,V253_DDR,-5.5328,-0.1987,-17.0489,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-14.0000,-0.9825,-24.7323,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,-7.5264,-0.3960,-18.8453,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,-7.5264,-0.3960,-18.8453,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,-7.5264,-0.3960,-18.8453,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,-7.5264,-0.3960,-18.8453,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,-5.5484,-0.2042,-17.0591,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,-5.5484,-0.2042,-17.0591,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHUB,KCPLHUB_H,-11.0571,-0.6013,-22.1706,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHUB17,KCPLHUB17_H,-11.8891,-0.6347,-22.9693,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHUB18,KCPLHUB18_H,-11.6110,-0.6426,-22.6832,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHUB19,KCPLHUB19_H,-11.7823,-0.6195,-22.8776,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHUB20,KCPLHUB20_H,-12.2929,-0.6498,-23.3579,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHUB21,KCPLHUB21_H,-12.3697,-0.6248,-23.4598,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHUB22,KCPLHUB22_H,-11.6820,-0.6288,-22.7680,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHUB23,KCPLHUB23_H,-12.2398,-0.6456,-23.3091,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLHUB24,KCPLHUB24_H,-12.6551,-0.6606,-23.7094,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,-6.7206,-0.3066,-18.1288,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,-6.7206,-0.3066,-18.1288,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,-6.1058,-0.5405,-17.2802,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,-6.1058,-0.5405,-17.2802,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,-5.5573,-0.2022,-17.0700,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,-5.5573,-0.2022,-17.0700,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,-5.6878,-0.1760,-17.2266,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,-5.6878,-0.1760,-17.2266,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,-5.6878,-0.1760,-17.2266,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,-5.6878,-0.1760,-17.2266,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,-5.6878,-0.1760,-17.2266,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,-5.6878,-0.1760,-17.2266,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,-5.6878,-0.1760,-17.2266,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,-5.6878,-0.1760,-17.2266,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,-13.1460,-0.3501,-24.5108,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,-5.3644,-0.1959,-16.8834,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KCPL_KCPL,KCPL_LA,-6.1368,-0.2159,-17.6357,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KENN,KENN_LA,9.9618,0.1440,-1.8971,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KEP2_SECI,KEP2_SECI_LA,-23.3874,-0.2735,-34.8288,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KERR_1,GRDAKERR_HYDUN1_RA,23.6665,0.1424,11.8093,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KERR_2,GRDAKERR_HYDUN2_RA,23.5302,0.1500,11.6654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KERR_3,GRDAKERR_HYDUN3_RA,23.5302,0.1500,11.6654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KERR_4,GRDAKERR_HYDUN4_RA,23.6665,0.1424,11.8093,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,-7.5265,-0.3960,-18.8453,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,-7.5265,-0.3960,-18.8453,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,-7.2695,-0.3433,-18.6410,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,-7.2695,-0.3433,-18.6410,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,-9.4189,-0.3780,-20.7557,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,-10.7525,-0.3542,-22.1132,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,-10.7525,-0.3542,-22.1132,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-21.5480,-0.3503,-32.9125,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-21.5480,-0.3503,-32.9125,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-21.5480,-0.3503,-32.9125,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-14.8434,-0.2500,-26.3083,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-14.8434,-0.2500,-26.3083,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-21.9650,-0.3772,-33.3027,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-16.5242,-0.4611,-27.7780,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-13.6804,-0.6187,-24.7766,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,39.1426,-0.1889,27.6167,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,39.1426,-0.1889,27.6167,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-8.9923,-0.5359,-20.1712,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-8.9923,-0.5359,-20.1712,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-8.9923,-0.5359,-20.1712,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-15.9314,-0.7441,-26.9021,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-15.3297,-0.3648,-26.6797,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,-8.0400,-0.5025,-19.2523,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-7.8820,-0.2750,-19.3218,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,LAFA,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,LAM345,LAM345,-22.0121,-0.5065,-33.2204,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,LEPA,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,-5.2517,-0.6011,-16.3655,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_LES,LES_LA,-5.2689,-0.6060,-16.3777,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,-5.2030,-0.6416,-16.2763,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,-5.3728,-0.6297,-16.4580,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,-5.3728,-0.6297,-16.4580,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,-5.3728,-0.6297,-16.4580,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,-5.1950,-0.6335,-16.2763,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,-5.2030,-0.6416,-16.2763,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_WAVERLY,LES_WAVERLY_H,-5.2395,-0.6241,-16.3302,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,-5.0125,-0.5920,-16.1354,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,-5.0125,-0.5920,-16.1354,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,LGEE,LGEE,5.2833,-0.0460,-6.3856,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MALDEN,MALDEN_LA,9.5244,0.1282,-2.3187,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MCWEST,MCWEST,-2.5308,-0.1216,-14.1240,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MDU,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-8.6873,-0.0894,-20.3127,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,-6.5926,-0.4659,-17.8415,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,-4.9699,-0.1549,-16.5298,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MEAN_NPPD,NPPD_MEAN_LA,-8.8139,-0.7961,-19.7327,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MEC,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MHEB,MHEB,-2.0797,-0.2171,-13.5775,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-18.0000,-0.9489,-28.7659,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-16.1714,-0.8863,-27.0000,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-18.0000,-0.9489,-28.7659,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-18.0000,-0.9489,-28.7659,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-16.1714,-0.8863,-27.0000,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-18.7437,-0.6396,-29.8190,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MISO,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-23.2182,-0.0905,-34.8425,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-23.2182,-0.0905,-34.8425,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-11.9224,-0.7900,-22.8472,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-20.7187,-0.7870,-31.6465,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-14.9748,-0.8163,-25.8734,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-20.5776,-0.7418,-31.5507,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-19.1114,-0.6740,-30.1522,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-20.5182,-0.7055,-31.5276,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-18.5386,-0.6801,-29.5734,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-18.5386,-0.6801,-29.5734,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-18.5386,-0.6801,-29.5734,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-18.5386,-0.6801,-29.5734,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-18.5386,-0.6801,-29.5734,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,-2.1377,-0.2392,-13.6133,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,6.1539,0.0080,-5.5690,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,6.1539,0.0080,-5.5690,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,3.2308,-0.0926,-8.3914,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,0.4761,0.1741,-11.4128,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MOWR,AECI,10.6506,0.0048,-1.0691,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,3.4635,-0.1053,-8.1461,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,6.4188,0.0182,-5.3142,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-5.4548,-0.7682,-16.4015,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-5.1264,-0.5466,-16.2947,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-21.2279,-0.9095,-32.0332,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-5.4297,-0.7431,-16.4015,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,-5.0695,-0.2710,-16.5133,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,-5.0695,-0.2710,-16.5133,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,-5.0683,-0.2699,-16.5133,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,-5.0683,-0.2699,-16.5133,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,-5.9179,-0.2847,-17.3480,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,-5.9179,-0.2847,-17.3480,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,-5.9179,-0.2847,-17.3480,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,-5.9516,-0.3184,-17.3480,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,-5.9179,-0.2847,-17.3480,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,-5.9179,-0.2847,-17.3480,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,-5.9179,-0.2847,-17.3480,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,4.5188,0.1205,-7.3166,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,-4.5089,-0.2664,-15.9574,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,-5.3743,-0.2997,-16.7895,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,-5.3743,-0.2997,-16.7895,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,-5.3743,-0.2996,-16.7895,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,-5.7416,-0.2003,-17.2561,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,-5.7416,-0.2003,-17.2561,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,MPS_MPS,MPS_LA,-4.0154,-0.1608,-15.5695,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MSTNG,SPSMSTNGPLT1,110.4461,1.2254,97.5058,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MSTNG4,SPSMSTNGUN4_RA,110.3858,1.1651,97.5058,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MSTNG5,SPSMSTNGUN5_RA,110.4461,1.2254,97.5058,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,110.4461,1.2254,97.5058,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NBSO,PJM,3.6788,-0.1215,-7.9145,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,-5.5299,-0.7375,-16.5072,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,-5.5311,-0.7387,-16.5072,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-2.9579,-0.2308,-14.4420,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NHC1,VACS,9.2392,0.1223,-2.5980,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,-5.1880,-0.5568,-16.3461,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,-5.1880,-0.5568,-16.3461,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,-5.1880,-0.5568,-16.3461,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-8.8830,-0.8703,-19.7275,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,-8.2568,-1.0854,-18.8862,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,-6.5077,-0.7620,-17.4606,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-8.3371,-0.8037,-19.2482,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,-8.2568,-1.0854,-18.8862,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.HUB.PY2018,NPPDPY18_H,-8.1708,-0.6988,-19.1868,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,-8.0446,-0.7025,-19.0570,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,-8.1204,-0.6968,-19.1384,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,-8.0127,-0.6954,-19.0322,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-9.7276,-0.8376,-20.6048,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-9.8045,-0.5092,-21.0101,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-9.8045,-0.5092,-21.0101,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-11.7282,-0.8018,-22.6412,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-9.7276,-0.8376,-20.6048,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,-4.2970,-1.4176,-14.5942,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,-8.7980,-1.0741,-19.4388,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-12.2596,-0.3858,-23.5886,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,-8.7980,-1.0741,-19.4388,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,-7.8922,-1.0639,-18.5432,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-9.0938,-0.8866,-19.9220,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,-5.8221,-0.5366,-17.0003,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,-8.2568,-1.0854,-18.8862,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-11.8793,-0.4364,-23.1578,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-9.8045,-0.5092,-21.0101,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-9.8045,-0.5092,-21.0101,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-9.3484,-0.5146,-20.5487,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-9.3881,-0.5087,-20.5943,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-9.3881,-0.5087,-20.5943,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,-8.9768,-0.4901,-20.2015,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-15.5505,-0.5994,-26.6659,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,-7.9589,-0.9376,-18.7361,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-8.6869,-0.7526,-19.6491,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-8.3529,-0.5545,-19.5133,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-9.0585,-0.5724,-20.2009,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.NELI.DDR,NELI_DDR,-9.4623,-0.9698,-20.2074,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.NPPM.1058,SH1058_DDR,-0.2507,-0.6445,-11.3210,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,-8.9765,-0.5617,-20.1296,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,-8.2568,-1.0854,-18.8862,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,-6.5077,-0.7620,-17.4606,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-9.7276,-0.8376,-20.6048,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.TECH.1,KEARNE_DDR,-8.5512,-0.4448,-19.8212,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,-6.9699,-1.1921,-17.4927,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,-6.9699,-1.1921,-17.4927,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-9.8836,-0.9272,-20.6712,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD.VOLT.0236,V236_DDR,-6.2651,-0.5675,-17.4124,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD2017HUB,NPPD2017HUB_H,-8.1519,-0.6975,-19.1692,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,-1.3201,-0.8514,-12.1835,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-8.8830,-0.8703,-19.7275,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,-8.8344,-1.2654,-19.2838,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,-8.8344,-1.2654,-19.2838,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,-6.1693,-0.5822,-17.3019,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,-6.2581,-0.5605,-17.4124,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-11.3337,-0.8272,-22.2214,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-9.2762,-0.5447,-20.4464,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,-0.4394,-0.8332,-11.3210,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,-0.4394,-0.8332,-11.3210,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,-0.4394,-0.8332,-11.3210,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,-7.5857,-0.7266,-18.5740,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,-5.6576,-0.7570,-16.6154,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,-7.5160,-0.7408,-18.4901,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-9.8500,-1.5132,-20.0516,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-8.7379,-1.4525,-19.0003,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-10.4810,-0.5679,-21.6280,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-10.7040,-0.5760,-21.8428,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,-6.9554,-0.6878,-17.9824,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,-6.9638,-0.6962,-17.9824,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,-6.9638,-0.6962,-17.9824,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,-7.0009,-0.6812,-18.0345,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,-4.2970,-1.4176,-14.5942,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,-7.0637,-0.6799,-18.0986,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,-5.7490,-0.6697,-16.7942,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,-7.5900,-0.7062,-18.5987,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,-7.5999,-0.7119,-18.6028,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,-7.5985,-0.7062,-18.6071,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,-7.5985,-0.7062,-18.6071,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,-7.5857,-0.7266,-18.5740,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,-7.6064,-0.7472,-18.5740,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,-7.6964,-0.4780,-18.9333,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,-6.9987,-0.6447,-18.0689,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-10.4594,-0.5076,-21.6666,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,-7.8627,-1.3599,-18.2177,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-12.5701,-0.4308,-23.8542,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,-0.1115,-0.5053,-11.3210,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-9.4623,-0.9698,-20.2074,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-10.2748,-0.5598,-21.4298,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-10.2748,-0.5598,-21.4298,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_NPPD,NPPD_LA,-6.1163,-0.6585,-17.1726,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,-5.7490,-0.6697,-16.7942,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,-5.7490,-0.6697,-16.7942,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,-7.8186,-0.8367,-18.6967,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-8.2696,-0.9286,-19.0558,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NSB,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NSP,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NSSO,PJM,3.6788,-0.1215,-7.9145,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,NYIS,PJM,3.6788,-0.1215,-7.9145,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-20.5925,-0.7474,-31.5600,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-28.5849,-0.9234,-39.3764,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-36.0249,-0.8366,-46.9032,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-36.0249,-0.8366,-46.9032,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-27.9474,-0.5786,-39.0836,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-39.1889,-0.9881,-49.9157,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-96.7910,-0.6119,-107.8940,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-50.9671,-0.9987,-61.6833,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-30.0000,-0.8946,-40.8202,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-28.8752,-0.9575,-39.6325,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-15.6203,-0.3320,-27.0031,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-30.0000,-0.8946,-40.8202,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-25.8451,-0.6313,-36.9286,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-18.7437,-0.6396,-29.8190,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-18.1214,-0.8340,-29.0023,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,-23.5588,-0.2469,-35.0268,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-28.8752,-0.9575,-39.6325,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-24.0282,-0.7996,-34.9434,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-23.7859,-0.8991,-34.6016,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-18.2304,-0.6447,-29.3005,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-25.1312,-0.3115,-36.5345,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-18.7437,-0.6396,-29.8190,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-18.7437,-0.6396,-29.8190,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-28.8752,-0.9575,-39.6325,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-18.0201,-0.5125,-29.2224,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.NUEN.LAM1,LAM1_DDR,19.4310,0.6666,7.0496,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-15.6203,-0.3320,-27.0031,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-15.6203,-0.3320,-27.0031,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-18.6304,-0.5247,-29.8206,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-15.7888,-0.3655,-27.1381,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-15.7888,-0.3655,-27.1381,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-15.7888,-0.3655,-27.1381,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-15.8489,-0.3224,-27.2414,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-15.8489,-0.3224,-27.2414,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-15.7888,-0.3655,-27.1381,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-15.7888,-0.3655,-27.1381,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-28.8752,-0.9575,-39.6325,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,13.6061,0.2727,1.6186,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-25.8451,-0.6313,-36.9286,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-20.0059,-0.5243,-31.1964,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-24.0282,-0.7996,-34.9434,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,16.0489,0.3472,3.9868,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-19.8882,-0.6377,-30.9653,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-19.8882,-0.6377,-30.9653,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-19.8882,-0.6377,-30.9653,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-19.8882,-0.6377,-30.9653,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-38.2429,-1.2865,-48.6712,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-30.6300,-0.8494,-41.4954,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-28.5849,-0.9234,-39.3764,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-33.5529,-0.8252,-44.4426,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-33.5529,-0.8252,-44.4426,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-20.5000,-0.3277,-31.8871,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-19.0872,-0.6874,-30.1146,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-19.0872,-0.6874,-30.1146,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-19.0872,-0.6874,-30.1146,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0033,FOSTER_DDR,-14.7691,-0.3129,-26.1710,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,6.5949,0.2363,-5.3563,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0035,TARBY_DDR,19.1912,0.5167,6.9596,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,6.5949,0.2363,-5.3563,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,4.4903,0.0975,-7.3221,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,4.4903,0.0975,-7.3221,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-20.1058,-0.3705,-31.4501,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0040,TROSPER_DDR,-14.5565,-0.2995,-25.9718,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,-14.8442,-0.3004,-26.2586,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,17.1439,0.4498,4.9792,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0115,V115_DDR,-15.5599,-0.3286,-26.9461,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0116,V116_DDR,-24.5637,-0.2508,-36.0277,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0118,V118_DDR,-28.8479,-0.0911,-40.4716,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0125,V125_DDR,17.6704,0.5578,5.3978,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0126,V126_DDR,18.4489,0.2821,6.4520,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0129,V129_DDR,-14.5333,-0.5660,-25.6821,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,-15.1168,-0.3737,-26.4579,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0134,V134_DDR,19.7255,0.3688,7.6419,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0138,V138_DDR,17.6231,0.2382,5.6701,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,-15.3202,-0.3498,-26.6852,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0143,V143_DDR,9.8213,0.1274,-2.0210,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0149,V149_DDR,-17.3005,-0.5591,-28.4562,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0150,V150_DDR,-17.1637,-0.5559,-28.3226,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0155,V155_DDR,16.9395,0.1891,5.0355,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0156,V156_DDR,-15.1168,-0.3737,-26.4579,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0166,V166_DDR,18.3437,0.5638,6.0651,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,-15.1574,-0.3413,-26.5309,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-17.1637,-0.5559,-28.3226,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0170,V170_DDR,-18.7963,-0.5215,-29.9896,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-16.6097,-0.5425,-27.7820,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0176,V176_DDR,-17.1637,-0.5559,-28.3226,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0177,V177_DDR,-26.5881,-0.9689,-37.3341,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,-15.0576,-0.3242,-26.4482,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-21.4255,-0.7655,-32.3748,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0195,V195_DDR,101.8918,0.3446,89.8324,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0197,V197_DDR,17.1406,0.3770,5.0487,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0198,V198_DDR,18.3437,0.5638,6.0651,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0208,V208_DDR,102.0783,0.3552,90.0083,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0209,V209_DDR,102.0783,0.3552,90.0083,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,17.7559,0.2632,5.7778,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0216,V216_DDR,-14.9169,-0.3012,-26.3306,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0219,V219_DDR,16.9395,0.1891,5.0355,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0220,V220_DDR,-17.1637,-0.5559,-28.3226,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0224,V224_DDR,-15.6742,-0.3414,-27.0477,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0225,V225_DDR,-15.6736,-0.3407,-27.0477,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0226,V226_DDR,-15.6742,-0.3414,-27.0477,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0227,V227_DDR,-15.6742,-0.3414,-27.0477,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0229,V229_DDR,-19.9231,-0.3443,-31.2936,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0231,V231_DDR,-19.1070,-0.0831,-30.7387,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0238,V238_DDR,-36.0709,-0.9872,-46.7986,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.VOLT.0242,V242_DDR,17.2275,0.2138,5.2989,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-31.7954,-1.4046,-42.1056,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-18.7437,-0.6396,-29.8190,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-28.2806,-0.8689,-39.1265,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-18.1112,-0.8238,-29.0023,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-31.7954,-1.4046,-42.1056,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-15.8521,-0.9071,-26.6599,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-56.5634,-1.4353,-66.8430,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEHL7,OKGEHL7_H,-11.8484,-0.2841,-23.2791,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEHL8,OKGEHSL1UN8_RA,-11.8484,-0.2841,-23.2791,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEHL910,OKGEHSL1PLT2,-11.8484,-0.2841,-23.2791,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-17.2856,-0.8631,-28.1373,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEMCC,OKGEMCCLAIPLT1,-15.7820,-0.4476,-27.0492,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,14.1695,0.1310,2.3237,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,14.1695,0.1310,2.3237,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,14.1695,0.1310,2.3237,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,-11.2066,-0.4209,-22.5005,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,-11.2066,-0.4209,-22.5005,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,-11.2066,-0.4209,-22.5005,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,-11.2066,-0.4209,-22.5005,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGESM1,OKGESEMINOLEUN1_RA,-14.6815,-0.2402,-26.1561,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGESM2,OKGESEMINOLEUN2_RA,-10.6066,-0.2621,-22.0593,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGESM3,OKGESEMINOLEUN3_RA,-10.6066,-0.2621,-22.0593,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGESO1,OKGESONR1UN1_RA,-58.9691,-0.7812,-69.9028,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGESO2,OKGESONR1UN2_RA,-33.5529,-0.8252,-44.4426,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-17.3899,-0.9675,-28.1373,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-23.0098,-1.2390,-33.4857,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGETINK5A,OKGETINK5UN1_RA,-14.0612,-0.3180,-25.4581,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGETINK5B,OKGETINK5UN2_RA,-14.0612,-0.3180,-25.4581,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-18.6275,-0.8330,-29.5093,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-28.5849,-0.9234,-39.3764,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,16.9453,0.6858,4.5446,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-18.7437,-0.6396,-29.8190,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE_OKGE,OKGE_LA,-9.2285,-0.1965,-20.7469,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-20.0059,-0.5243,-31.1964,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-18.6674,-0.8730,-29.5093,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMLP,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,22.5721,0.1175,10.7397,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,17.1082,0.6626,4.7308,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-17.5739,-0.3826,-28.9061,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-96.7130,-0.5338,-107.8940,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-23.1636,-0.8928,-33.9857,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-30.0000,-0.8946,-40.8202,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-28.8539,-1.4188,-39.1500,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-14.7475,-0.8445,-25.6178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,151.0017,0.0490,139.2378,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-96.7319,-0.5527,-107.8940,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-96.7319,-0.5527,-107.8940,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_SPP,OMPA_SPP_LA,-24.0936,-0.4975,-35.3110,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-31.7954,-1.4046,-42.1056,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,18.9797,0.0871,7.1777,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,18.9797,0.0871,7.1777,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,18.9797,0.0871,7.1777,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,18.9797,0.0871,7.1777,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,ONT,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,-5.2479,-0.5630,-16.3998,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,-5.2479,-0.5630,-16.3998,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,-5.2479,-0.5630,-16.3998,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,-5.2479,-0.5630,-16.3998,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,-5.2479,-0.5630,-16.3998,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,-5.2479,-0.5630,-16.3998,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,-5.2479,-0.5630,-16.3998,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,-5.2479,-0.5630,-16.3998,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,-5.2479,-0.5630,-16.3998,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,-5.1866,-0.5473,-16.3542,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,-5.1880,-0.5568,-16.3461,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,-5.1583,-0.4791,-16.3940,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,-5.1813,-0.5249,-16.3713,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,-5.1813,-0.5249,-16.3713,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD_GLDN,OPPD_GLDN_LA,-5.1882,-0.5460,-16.3571,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,-5.2096,-0.5514,-16.3730,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,-4.2970,-1.4176,-14.5942,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,-5.8657,-0.6486,-16.9319,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,-5.1879,-0.5556,-16.3471,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD_OPPD,OPPD_LA,-5.1961,-0.5336,-16.3773,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,-5.1642,-0.5123,-16.3668,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,-5.1697,-0.5159,-16.3687,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,OTP,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,OVEC,OVEC,4.6520,-0.0745,-6.9883,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PARAGOULD,PARAGOULD_LA,10.6843,0.1697,-1.2002,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,23.4518,0.0542,11.6827,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,23.4518,0.0542,11.6827,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,23.4518,0.0542,11.6827,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,23.1118,0.0968,11.3002,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,23.1118,0.0968,11.3002,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,23.1118,0.0968,11.3002,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PIGGOTT,PIGGOTT_LA,9.8059,0.1384,-2.0473,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PJM,PJM,3.6788,-0.1215,-7.9145,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PLUM,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,POPLARBLUFF,POPLARBLUFF_LA,9.0197,0.1017,-2.7968,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,-2.7405,-0.2730,-14.1823,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,-2.7405,-0.2730,-14.1823,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,-2.5948,-0.2612,-14.0484,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,-2.5948,-0.2612,-14.0484,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,-1.7719,0.4043,-13.8911,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,-1.7719,0.4043,-13.8911,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,-2.5177,-0.1236,-14.1090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,-3.5448,-0.5082,-14.7514,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-21.2556,-0.6699,-32.3006,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,68.9261,0.0758,57.1355,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,-5.4693,-0.2130,-16.9711,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-17.5212,-0.1048,-29.1313,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,27.9384,0.2927,15.9308,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,19.5117,0.3167,7.4802,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,-3.6817,-0.6425,-14.7541,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,-2.2321,-0.1310,-13.8159,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,-4.6516,-0.8074,-15.5590,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,4.3900,0.3289,-7.6537,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,-1.9398,-0.1058,-13.5489,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,-4.0089,-0.5739,-15.1498,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,PUPP,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,RCEAST,RCEAST,-5.7238,-0.4643,-16.9743,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SALINA_1,GRDASALINA1UN1_RA,23.6678,0.1436,11.8093,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SALINA_2,GRDASALINA1UN2_RA,23.6678,0.1436,11.8093,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SALINA_3,GRDASALINA1UN3_RA,23.6678,0.1436,11.8093,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SALINA_4,GRDASALINA1UN4_RA,23.6678,0.1436,11.8093,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SALINA_5,GRDASALINA1UN5_RA,23.6678,0.1436,11.8093,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SALINA_6,GRDASALINA1UN6_RA,23.6678,0.1436,11.8093,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SARPY_1,OPPDSARPYUN1_RA,-5.1880,-0.5481,-16.3548,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SARPY_2,OPPDSARPYUN2_RA,-5.1736,-0.5296,-16.3588,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SARPY_3,OPPDSARPYUN3_RA,-5.1821,-0.5642,-16.3328,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SARPY_4,OPPDSARPYUN4_RA,-5.1821,-0.5642,-16.3328,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SARPY_5,OPPDSARPYUN5_RA,-5.1821,-0.5642,-16.3328,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SC,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SCEG,VACS,9.2392,0.1223,-2.5980,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SCSE,SCSE,-9.9031,-0.3520,-21.2659,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SEC,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-20.9377,-0.9176,-31.7349,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-20.9377,-0.9176,-31.7349,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-20.9377,-0.9176,-31.7349,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-21.9554,0.0085,-33.6787,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-20.9377,-0.9176,-31.7349,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-21.3871,-0.6731,-32.4289,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-19.5039,-0.8483,-30.3705,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-19.5039,-0.8483,-30.3705,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-18.5398,-0.6813,-29.5734,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-20.9646,-0.8881,-31.7914,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-14.8882,-0.2948,-26.3083,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-22.6175,-0.1145,-34.2178,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-17.4074,-0.4607,-28.6615,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-20.8932,-0.8901,-31.7179,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-17.3364,-0.4649,-28.5863,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-31.1900,-0.9274,-41.9774,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-20.4356,-0.5068,-31.6437,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-21.6714,-0.4001,-32.9861,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-21.6714,-0.4001,-32.9861,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-21.6714,-0.4001,-32.9861,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-21.6714,-0.4001,-32.9861,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-21.9293,-0.4550,-33.1892,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-21.3871,-0.6731,-32.4289,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI_SECI,SECI_LA,-20.8424,-0.3578,-32.1995,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-18.9432,-0.9389,-29.7191,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-18.9432,-0.9389,-29.7191,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-18.5398,-0.6813,-29.5734,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SEHA,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-18.6674,-0.8730,-29.5093,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SERU,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SETH,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SGE,SGE,-9.0932,-0.3258,-20.4822,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SMEP,MISO,4.4448,-0.1046,-7.1654,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SOCO,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPA,SPA,16.8950,0.2884,4.8917,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPC,SPC,-1.9914,0.0554,-13.7616,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPPNORTH_HUB,SPPNORTH_H,-5.5147,-0.5996,-16.6299,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-16.2005,-0.5575,-27.3579,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,13.5203,0.2043,1.6011,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,13.5203,0.2043,1.6011,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,12.9828,0.1866,1.0814,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,12.9828,0.1866,1.0814,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_NIXA,SPRM_NIXA_LA,13.9815,0.2200,2.0467,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_SPRM,SPRM_LA,13.5440,0.2346,1.5946,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,13.6850,0.1556,1.8146,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,13.6850,0.1556,1.8146,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,13.6563,0.1268,1.8146,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,13.6850,0.1556,1.8146,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,114.3633,0.9924,101.6561,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,121.0215,0.7686,108.5380,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-3.3935,0.0848,-15.1931,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-3.3935,0.0848,-15.1931,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,110.6192,0.1874,98.7169,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,110.2428,0.6749,97.8530,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,113.8982,-0.6383,102.8216,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,111.8540,1.8012,98.3380,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,108.6914,0.6428,96.3337,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,110.7124,1.2626,97.7349,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,110.8253,1.3627,97.7478,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,110.8253,1.3627,97.7478,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,110.7124,1.2626,97.7349,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-3.1574,0.2280,-15.1002,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,121.0215,0.7686,108.5380,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-3.3617,0.1518,-15.2283,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-15.6332,-0.4336,-26.9144,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-7.7848,0.1669,-19.6665,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-4.1875,0.4128,-16.3152,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-5.0156,0.1526,-16.8831,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-25.0000,-0.5112,-36.2036,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-25.0000,-0.5112,-36.2036,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-25.0000,-0.5112,-36.2036,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-25.0000,-0.5112,-36.2036,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GRID.WRAB,WRAB_DDR,-0.5314,0.3206,-12.5668,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-25.0000,-0.5112,-36.2036,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,107.2173,0.6707,94.8317,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,107.2173,0.6707,94.8317,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,103.4352,0.6734,91.0469,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,103.4352,0.6734,91.0469,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,103.4352,0.6734,91.0469,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,107.2173,0.6707,94.8317,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,0.9758,0.1282,-10.8672,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,0.9708,0.1282,-10.8722,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,0.9843,0.1282,-10.8588,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-2.9579,-0.2308,-14.4420,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,110.6749,1.2481,97.7120,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,108.6500,0.6314,96.3038,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,108.6500,0.6314,96.3038,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,108.6500,0.6314,96.3038,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,108.6500,0.6314,96.3038,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,110.5537,1.2077,97.6312,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,110.6599,1.2167,97.7284,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,110.6599,1.2167,97.7284,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-18.6082,-0.8137,-29.5093,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,0.0055,0.1371,-11.8464,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,0.0055,0.1371,-11.8464,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,0.8187,0.1288,-11.0249,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-0.5314,0.3206,-12.5668,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-14.2944,-0.2448,-25.7645,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-5.3415,0.0654,-17.1218,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-27.9474,-0.5786,-39.0836,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,0.1909,0.3225,-11.8464,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.PLANTX1,SPS.PLANTX1_H,117.0609,0.9341,104.4119,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.PLANTX2,SPS.PLANTX2_H,117.0609,0.9341,104.4119,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,116.2962,0.9100,103.6714,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,110.2821,0.3994,98.1679,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-19.8147,-0.3990,-31.1306,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,114.2112,-0.3252,102.8216,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,110.3158,0.4330,98.1679,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-3.1604,0.2250,-15.1002,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,113.6514,1.0851,100.8515,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,111.8540,1.8012,98.3380,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,113.6514,1.0851,100.8515,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,111.8550,1.7980,98.3422,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-69.6506,0.0282,-81.3936,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,111.6702,2.0661,97.8893,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,111.7213,2.1172,97.8893,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,111.5493,1.9995,97.8349,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,110.8084,1.3658,97.7277,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,111.7914,1.9597,98.1169,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-22.0121,-0.5065,-33.2204,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-0.5323,0.2655,-12.5126,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,115.0851,0.9515,102.4187,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,115.0851,0.9515,102.4187,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,113.6514,1.0851,100.8515,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,108.8380,0.6995,96.4236,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,110.8184,1.5693,97.5343,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,116.1085,1.4878,102.9058,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,116.1833,1.1978,103.2706,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,117.3625,0.6380,105.0096,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,111.6702,2.0661,97.8893,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,112.0736,2.3128,98.0459,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,111.9114,2.1506,98.0459,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,110.3969,0.5142,98.1679,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,115.7141,1.1867,102.8125,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-18.6523,-0.3615,-30.0057,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-18.6430,-0.3790,-29.9788,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0163,V163_DDR,1.6200,0.2840,-10.3789,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0168,V168_DDR,-7.8603,-0.3517,-19.2235,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0180,V180_DDR,112.0736,2.3128,98.0459,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0181,V181_DDR,-19.1823,-0.2471,-30.6500,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0182,V182_DDR,111.8211,1.9977,98.1086,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0199,V199_DDR,110.7239,1.4633,97.5458,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0200,V200_DDR,111.1085,1.5978,97.7959,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.VOLT.0235,V235_DDR,-14.2944,-0.2448,-25.7645,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,113.8982,-0.6383,102.8216,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,111.8540,1.8012,98.3380,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-0.0200,0.2258,-11.9606,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-0.6108,0.2223,-12.5480,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS_SPS,SPS_LA,83.3000,1.3100,70.2752,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,113.3221,1.0626,100.5447,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SSCN_NPPD,SSCN_NPPD_LA,-7.5982,-0.7580,-18.5550,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,8.2362,0.0813,-3.5599,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,8.2362,0.0813,-3.5599,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,TAL,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,TEC,SOUC,9.6667,0.1410,-2.1891,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,-7.8627,-1.3599,-18.2177,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,TVA,TVA,8.7883,0.1026,-3.0292,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,UCUHUB,UCUHUB_H,-9.9841,-0.4634,-21.2355,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,UCUHUB17,UCUHUB17_H,-14.8795,-0.6199,-25.9745,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,UCUHUB18,UCUHUB18_H,-11.5963,-0.5940,-22.7172,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,UCUHUB19,UCUHUB19_H,-14.4858,-0.6056,-25.5951,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,UCUHUB20,UCUHUB20_H,-14.6879,-0.5790,-25.8237,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,UCUHUB21,UCUHUB21_H,-16.0113,-0.6174,-27.1088,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,UCUHUB22,UCUHUB22_H,-15.5037,-0.6525,-26.5661,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,UCUHUB23,UCUHUB23_H,-15.7536,-0.6562,-26.8123,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,UCUHUB24,UCUHUB24_H,-13.7343,-0.5869,-24.8622,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,-1.9119,0.1437,-13.7705,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,-1.9119,0.1437,-13.7705,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,-2.5817,-0.5187,-13.7778,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,-2.5817,-0.5187,-13.7778,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,-2.3246,-0.5267,-13.5127,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,-2.6630,-0.3668,-14.0110,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,-2.6630,-0.3668,-14.0110,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,-1.9119,0.1437,-13.7705,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,-2.3093,-0.5242,-13.4999,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,-2.0319,-0.1313,-13.6154,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,-4.4489,-0.7862,-15.3775,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,-5.8325,-1.2911,-16.2563,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,-2.0034,0.1400,-13.8583,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,-2.0034,0.1400,-13.8583,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,0.4893,-1.4191,-9.8065,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,-4.5545,-0.7047,-15.5647,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,0.9606,-0.3041,-10.4502,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,-4.7812,-0.8141,-15.6820,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,-4.3955,-0.7030,-15.4073,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,-5.2346,-0.7606,-16.1889,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,1.0805,-0.8278,-9.8065,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,1.0805,-0.8278,-9.8065,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,-4.9025,-0.6449,-15.9724,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,-5.8310,-1.2945,-16.2514,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,-4.2206,-0.5566,-15.3788,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,5.2700,-0.3195,-6.1253,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,5.2700,-0.3195,-6.1253,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,5.2700,-0.3195,-6.1253,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,-2.3308,-0.2403,-13.8053,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,-2.3308,-0.2403,-13.8053,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,-2.3308,-0.2403,-13.8053,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,-1.7436,0.2997,-13.7581,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,-2.4607,-0.5107,-13.6649,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,-2.5243,-0.5271,-13.7120,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-9.5058,-0.3494,-20.8713,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,-5.6082,-0.6704,-16.6526,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,-2.1634,-0.1273,-13.7510,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,-6.1503,-0.8064,-17.0587,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,-6.1266,-1.4394,-16.4020,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,1.1338,-0.7018,-9.8793,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,-2.0663,0.0279,-13.8090,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,-2.0663,0.0279,-13.8090,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,-2.0682,0.0259,-13.8090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,-2.0663,0.0279,-13.8090,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,-2.0360,0.0463,-13.7971,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,-2.0360,0.0463,-13.7971,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,-2.0360,0.0463,-13.7971,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,-2.0360,0.0463,-13.7971,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,-2.0360,0.0463,-13.7971,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,-2.0360,0.0463,-13.7971,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,-2.0360,0.0463,-13.7971,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,-6.3256,-1.2544,-16.7860,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,-2.2033,-0.3270,-13.5911,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,-5.5367,-0.6447,-16.6068,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,-5.5367,-0.6447,-16.6068,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,-7.0228,-0.9428,-17.7948,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,-7.0228,-0.9428,-17.7948,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,-2.3469,-0.3968,-13.6649,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,-2.4183,-0.3628,-13.7703,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,-4.7109,-0.9687,-15.4571,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,-5.4136,-1.1236,-16.0049,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,-3.2827,-0.4832,-14.5144,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,-2.3246,-0.5267,-13.5127,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,-2.3246,-0.5267,-13.5127,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,-4.7812,-0.8141,-15.6820,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,-5.7411,-0.4757,-16.9803,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,-2.1874,-0.7613,-13.1409,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,-5.6671,-1.1305,-16.2514,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,-5.1005,-0.7699,-16.0454,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.FSE,WAUE.FSE_H,-6.9411,-0.8335,-17.8225,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,-2.3946,-0.1288,-13.9807,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,-2.4244,-0.1362,-14.0030,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,-6.3004,-1.3731,-16.6421,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,-5.9027,-1.2998,-16.3178,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,-2.3388,-0.5192,-13.5345,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,-2.4096,-0.5622,-13.5622,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-21.7900,-1.3771,-32.1277,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,-5.8325,-1.2911,-16.2563,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-12.0000,-0.4334,-23.2814,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,-4.6354,-0.7389,-15.6113,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,-4.5765,-0.6800,-15.6113,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,-4.5758,-0.6794,-15.6113,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,-7.3335,-0.6824,-18.3660,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,-5.7411,-0.4757,-16.9803,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,-3.6513,-0.4902,-14.8760,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,-4.8552,-0.8368,-15.7332,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,-4.2075,-0.5436,-15.3788,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,-3.9072,-0.1933,-15.4287,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,-4.2724,-0.6522,-15.3350,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,-2.3289,-0.4089,-13.6349,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,-4.5878,-0.7606,-15.5420,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,-4.6844,-0.8903,-15.5090,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,-6.1503,-0.8064,-17.0587,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,-1.7378,-0.1346,-13.3180,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,-4.7918,-0.8235,-15.6831,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,-1.8516,-0.2111,-13.3553,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,-3.8683,-0.5165,-15.0667,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,-5.0125,-0.5920,-16.1354,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NTWK,WAUE.NTWK_H,-3.9713,-0.5267,-15.1594,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,-3.2451,-0.0383,-14.9216,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,-3.2451,-0.0383,-14.9216,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,-5.9658,-1.4251,-16.2555,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,-6.7806,-1.6034,-16.8921,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,-3.8035,-0.6219,-14.8965,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,-5.9658,-1.4251,-16.2555,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,-2.1276,-0.3123,-13.5301,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,-4.6973,-0.7949,-15.6173,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,-6.1503,-0.8064,-17.0587,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,-4.0761,-0.4949,-15.2960,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,-5.3721,-1.4697,-15.6173,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,-6.2719,-1.0233,-16.9634,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,-5.9710,-0.9970,-16.6888,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,-2.5324,-0.5368,-13.7104,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,-6.7749,-1.2862,-17.2035,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,-3.9713,-0.4708,-15.2154,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,-5.2739,-0.9702,-16.0185,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,-5.4136,-1.1236,-16.0049,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.VOLT.0152,V152_DDR,-1.5855,0.4330,-13.7333,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE.VOLT.0172,V172_DDR,-1.9968,0.0868,-13.7984,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_BEPM,WAUE_BEPM_LA,-2.2885,-0.1577,-13.8456,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,-3.9405,-0.5861,-15.0692,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,-3.9047,-0.1880,-15.4315,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_EWA,WAUE_EWA_LA,-5.6672,-0.4333,-16.9487,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,-4.7427,-0.8405,-15.6171,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_HMMU,WAUE_HMMU_LA,-4.4896,-0.3377,-15.8667,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,-2.2897,-0.4416,-13.5630,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_MECB,WAUE_MECB_LA,-4.4346,-0.3160,-15.8334,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_MMPA,WAUE_MMPA_LA,-1.8283,-0.0502,-13.4929,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_MRES,WAUE_MRES_LA,-4.7586,-0.5264,-15.9470,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,-1.7550,0.2190,-13.6888,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,-2.3946,-0.1288,-13.9807,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,-5.2037,-0.8126,-16.1059,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_OTP,WAUE_OTP_LA,-1.6950,0.1596,-13.5694,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_OTPW,WAUE_OTPW_LA,-1.4752,-0.1283,-13.0617,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM,WAUE_UGPM_LA,-3.7683,-0.5449,-14.9383,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,-2.9040,-0.2962,-14.3227,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,-4.3840,-0.6137,-15.4852,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,-4.2709,-0.6093,-15.3765,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,-5.6672,-0.4333,-16.9487,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,-4.4896,-0.3377,-15.8667,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,-4.4128,-0.8715,-15.2562,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,-2.3946,-0.1288,-13.9807,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,-1.8283,-0.0502,-13.4929,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,-4.2723,-0.4635,-15.5237,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,-5.1854,-0.9033,-15.9970,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,-1.6081,0.2400,-13.5630,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-31.5263,-1.2496,-41.9916,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-28.4522,-1.1882,-38.9788,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,-10.3100,-0.7040,-21.3208,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,94.8001,0.1718,82.9134,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,94.8001,0.1718,82.9134,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-17.0504,-1.2282,-27.5371,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,84.3797,0.2383,72.4265,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,72.2355,0.2246,60.2961,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,2.0300,-0.7006,-8.9842,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,2.0300,-0.7006,-8.9842,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,2.0300,-0.7006,-8.9842,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,2.0026,-0.7280,-8.9842,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,2.0043,-0.7263,-8.9842,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,2.0300,-0.7006,-8.9842,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,2.0300,-0.7006,-8.9842,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,2.0300,-0.7006,-8.9842,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,-3.5175,-0.6693,-14.5631,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-27.9474,-0.5786,-39.0836,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-25.0000,-1.1004,-35.6144,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-29.2474,-1.6377,-39.3246,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,114.1294,-0.4071,102.8216,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_ENMC,WFEC_ENMC_LA,112.1047,1.4223,98.9676,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-28.8752,-0.9575,-39.6325,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,29.6418,0.0077,17.9192,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,110.5043,1.1310,97.6585,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-31.5263,-1.2496,-41.9916,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-31.5263,-1.2496,-41.9916,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-31.5263,-1.2496,-41.9916,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_OKGE,WFEC_OKGE_LA,-17.7372,-0.2133,-29.2387,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,11.4050,0.1891,-0.4989,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-20.6975,-1.1884,-31.2239,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-16.7816,-1.2785,-27.2179,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_WFEC,WFEC_LA,1.5913,-0.3327,-9.7908,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,110.5043,1.1310,97.6585,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-19.4706,-0.9727,-30.2127,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-20.1590,-0.4679,-31.4059,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-12.8051,-0.6447,-23.8753,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-12.8051,-0.6447,-23.8753,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-12.8052,-0.6447,-23.8753,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-12.8052,-0.6447,-23.8753,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-12.8052,-0.6447,-23.8753,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-12.8052,-0.6447,-23.8753,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-12.8052,-0.6447,-23.8753,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,-2.9793,0.1517,-14.8458,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-13.6995,-0.8111,-24.6033,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-25.5750,-0.9209,-36.3690,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-25.5750,-0.9209,-36.3690,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-25.5750,-0.9209,-36.3690,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-21.2582,-0.9013,-32.0718,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-21.2582,-0.9013,-32.0718,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-21.6880,-0.8445,-32.5583,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-21.6880,-0.8445,-32.5583,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-21.6880,-0.8445,-32.5583,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-13.6995,-0.8111,-24.6033,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,-7.2287,-0.3159,-18.6277,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-16.9070,-0.7122,-27.9096,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-16.9070,-0.7122,-27.9096,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-16.9070,-0.7122,-27.9096,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-16.9067,-0.7119,-27.9096,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,-7.2287,-0.3159,-18.6277,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-20.8238,-0.8475,-31.6912,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-42.3978,-0.4940,-53.6187,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.JEC.1,WRJEFFUN10_RA,-11.3094,-0.6475,-22.3767,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.JEC.2,WRJEFFUN11_RA,-11.2126,-0.6486,-22.2789,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.JEC.3,WRJEFFUN12_RA,-11.2638,-0.6997,-22.2789,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-28.5971,-0.8991,-39.4129,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-21.2182,-0.8999,-32.0332,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-21.2182,-0.8999,-32.0332,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.LEC.4,WRLECUN26_RA,-8.4615,-0.3568,-19.8196,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.LEC.5,WRLECUN27_RA,-8.8919,-0.3324,-20.2744,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-15.6146,-0.5735,-26.7560,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-15.6146,-0.5735,-26.7560,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-15.6146,-0.5735,-26.7560,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-15.5707,-0.5527,-26.7329,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-18.9432,-0.9389,-29.7191,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-18.9432,-0.9389,-29.7191,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-17.3864,-0.3765,-28.7248,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-18.2749,-0.9502,-29.0395,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-18.2749,-0.9502,-29.0395,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-15.3359,-0.3711,-26.6797,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-18.9432,-0.9389,-29.7191,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-9.2211,-0.9020,-20.0340,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-14.2141,-0.8572,-25.0718,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-21.2234,-0.9050,-32.0332,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,71.9393,0.2555,59.9690,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-15.1664,-0.2661,-26.6152,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-12.8052,-0.6447,-23.8753,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-14.9071,-1.0005,-25.6214,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,-7.2287,-0.3159,-18.6277,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-13.6995,-0.8111,-24.6033,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-23.2458,-0.7635,-34.1971,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.THAYERLD,WR.THAYERLD_LA,10.2810,0.1366,-1.5704,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-24.0401,-0.7535,-35.0015,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0106,V106_DDR,-23.1206,-0.7368,-34.0986,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-7.0600,-0.2459,-18.5289,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-14.4541,-0.6690,-25.4999,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-8.2676,-0.2758,-19.7067,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-8.2676,-0.2758,-19.7067,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-7.5202,-0.2861,-18.9489,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-22.5487,-0.6427,-33.6208,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0157,V157_DDR,-8.3209,-0.2863,-19.7494,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0158,V158_DDR,-8.2676,-0.2758,-19.7067,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-8.2676,-0.2758,-19.7067,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-23.2693,-0.7949,-34.1893,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0173,V173_DDR,-15.5152,-0.4983,-26.7317,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0174,V174_DDR,-23.0061,-0.7383,-33.9827,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0184,V184_DDR,-22.6497,-0.8044,-33.5601,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-23.3640,-0.7552,-34.3236,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0186,V186_DDR,-23.3487,-0.7789,-34.2847,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-22.8528,-0.7842,-33.7834,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-23.8913,-0.7454,-34.8607,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-16.8953,-0.6112,-27.9989,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-13.7032,-0.5894,-24.8286,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-13.0493,-0.6146,-24.1496,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-13.0493,-0.6146,-24.1496,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-13.7032,-0.5894,-24.8286,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0245,V245_DDR,-23.3746,-0.7549,-34.3346,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.VOLT.0248,V248_DDR,-23.1206,-0.7368,-34.0986,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-25.7705,-0.8609,-36.6244,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-9.4002,-0.4109,-20.7041,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.WOLF,WRWOLFUN15_RA,-15.5408,-1.0606,-26.1950,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-20.8238,-0.8475,-31.6912,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,-3.0303,0.1007,-14.8458,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-25.5750,-0.9209,-36.3690,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-25.5750,-0.9209,-36.3690,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-25.5750,-0.9209,-36.3690,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-25.5750,-0.9209,-36.3690,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-23.7253,-0.7248,-34.7154,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-14.4002,-0.6727,-25.4423,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-24.2172,-0.7628,-35.1692,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-24.2172,-0.7628,-35.1692,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-24.2172,-0.7628,-35.1692,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-24.2172,-0.7628,-35.1692,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-13.0889,-0.5678,-24.2359,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-13.0889,-0.5678,-24.2359,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-13.0889,-0.5678,-24.2359,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-13.0889,-0.5678,-24.2359,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-13.0889,-0.5678,-24.2359,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-13.0889,-0.5678,-24.2359,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-37.9374,-0.7444,-48.9079,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-37.9374,-0.7444,-48.9079,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-40.3519,-0.7592,-51.3075,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-40.3519,-0.7592,-51.3075,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_MIDW,WR_MIDW_LA,-16.9903,-0.5867,-28.1185,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,-0.5193,0.0161,-12.2502,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,-4.0362,-0.1785,-15.5725,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-15.3401,-0.7249,-26.3300,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_SEG,WR_SEG_LA,-5.0889,0.0153,-16.8190,11.7148\n03/19/2025 01:00:00,03/19/2025 06:00:00,WR_WR,WR_LA,-14.7583,-0.5587,-25.9145,11.7149\n03/19/2025 01:00:00,03/19/2025 06:00:00,YAD,VACS,9.2392,0.1223,-2.5980,11.7149\n03/19/2025 02:00:00,03/19/2025 07:00:00,AEC,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,AECC_CSWS,CSWS_AECC_LA,17.8212,0.0923,15.2482,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,18.6304,0.0639,16.0858,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,16.3313,0.1375,13.7131,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,18.9545,0.0402,16.4336,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,17.1170,0.0556,14.5806,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,16.8383,0.0455,14.3121,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,18.2695,0.0249,15.7639,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,AECI,AECI,10.4491,0.0123,7.9561,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,AEPM_CSWS,CSWS_LA,18.4948,0.0686,15.9455,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,ALTW,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,AMRN,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,28.6933,0.0897,26.1229,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,BBA,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,BCA,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,BEPM.ER01.DDR,ER01_DDR,-4.1607,-0.1851,-6.4564,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,BEPM_ER01,BEPM_ER01_LA,-4.1607,-0.1851,-6.4564,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,-6.0944,-0.0883,-8.4869,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-8.7255,-0.0363,-11.1699,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,BEPM_UM01,BEPM_UM01_LA,-0.4281,0.0547,-2.9635,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,BLKW,BLKW,31.9929,0.1603,29.3519,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-26.2491,-0.2444,-28.4854,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-26.2491,-0.2444,-28.4854,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,-1.4775,-0.2161,-3.7422,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-26.2464,-0.2417,-28.4854,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,BRAZ,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,BUBA,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-20.0487,-0.1633,-22.3662,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-19.8560,-0.1529,-22.1839,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-19.8560,-0.1529,-22.1839,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-19.8560,-0.1529,-22.1839,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-19.8560,-0.1529,-22.1839,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-19.8560,-0.1529,-22.1839,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-21.3062,-0.1452,-23.6418,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,-4.9119,-0.1060,-7.2867,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,-4.9119,-0.1060,-7.2867,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CLEC,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,18.7649,0.0363,16.2478,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,COWP,COWP_LA,10.8148,0.0409,8.2931,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,10.8148,0.0409,8.2931,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,10.8148,0.0409,8.2931,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CPLE,VACS,8.7909,0.0478,6.2624,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CPLW,VACS,8.7909,0.0478,6.2624,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,10.8600,0.0662,8.3131,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,10.8600,0.0662,8.3131,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,10.8600,0.0662,8.3131,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,10.8600,0.0662,8.3131,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CRTH_SPA,WRCRTH_SPA_LA,13.7217,0.0049,11.2360,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,16.8438,0.1729,14.1901,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-12.4494,-0.1429,-14.7873,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,18.2695,0.0249,15.7639,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,18.9545,0.0402,16.4336,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,16.8483,0.1718,14.1957,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,17.0495,0.1259,14.4429,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,16.9469,0.1536,14.3125,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,16.9469,0.1536,14.3125,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,18.3224,0.0557,15.7860,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,18.3224,0.0557,15.7860,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,18.3224,0.0557,15.7860,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,18.3224,0.0557,15.7860,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,18.2695,0.0249,15.7639,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,20.9492,0.1241,18.3444,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,39.8913,-0.0231,37.4336,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,39.8700,-0.0444,37.4336,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,22.5887,0.0101,20.0979,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,18.5968,0.0292,16.0869,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,18.5968,0.0292,16.0869,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,18.5988,0.0292,16.0889,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,18.5988,0.0292,16.0889,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-21.7992,-0.1695,-24.1105,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,-12.9825,-0.1270,-15.3362,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,31.5081,0.0152,29.0121,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-20.1435,-0.1829,-22.4414,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-20.1355,-0.1749,-22.4414,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-14.6789,-0.1231,-17.0366,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.GRID.CDL1,CDL1_DDR,26.1022,0.0355,23.5859,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-16.1266,-0.1354,-18.4720,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-11.7746,-0.1512,-14.1041,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,26.1022,0.0355,23.5859,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.NUEN.CSI1,CSI1_DDR,21.9331,0.0498,19.4025,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.NUEN.CSI2,CSI2_DDR,21.9338,0.0505,19.4025,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,18.7652,0.0366,16.2478,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.NUEN.GAZA,GAZA_DDR,26.1022,0.0355,23.5859,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,109.9524,0.0857,107.3860,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.NUEN.T201,NT201_DDR,19.5111,0.0326,16.9978,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-14.0112,-0.1802,-16.3117,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-14.0112,-0.1802,-16.3117,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,18.2695,0.0249,15.7639,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,17.5027,0.1938,14.8281,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-14.6789,-0.1231,-17.0366,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-14.6789,-0.1231,-17.0366,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-18.4483,-0.1600,-20.7691,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-20.1355,-0.1749,-22.4414,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,16.6511,0.0985,14.0718,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,15.7525,0.0156,13.2561,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,15.7525,0.0156,13.2561,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,15.7525,0.0156,13.2561,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,-5.7098,-0.0105,-8.1800,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,-5.7098,-0.0105,-8.1800,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,17.1515,0.1226,14.5481,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,19.8196,0.0301,17.3087,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,17.1301,0.1288,14.5205,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,17.5724,0.2398,14.8518,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,23.0535,0.0455,20.5272,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,21.9338,0.0505,19.4025,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0057,OKMU_DDR,22.9168,0.0504,20.3856,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0060,LEHIGH_DDR,109.9524,0.0857,107.3860,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0086,WARRENM_DDR,19.0199,0.0373,16.5019,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,17.7741,0.1765,15.1169,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,30.8554,0.0277,28.3469,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0121,V121_DDR,17.1515,0.1226,14.5481,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0122,V122_DDR,29.2968,0.0253,26.7907,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0124,V124_DDR,49.1502,0.0114,46.6580,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0135,V135_DDR,20.0049,0.0377,17.4864,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0144,V144_DDR,-13.5044,-0.1147,-15.8705,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0145,V145_DDR,-13.8356,-0.1257,-16.1906,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,17.1722,0.1250,14.5665,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,18.4787,0.0573,15.9407,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0175,V175_DDR,18.7652,0.0366,16.2478,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,18.4787,0.0573,15.9407,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,18.4804,0.0713,15.9283,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,20.0049,0.0377,17.4864,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,20.3728,0.0336,17.8584,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,19.9571,0.0284,17.4479,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,35.6552,-0.0020,33.1764,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,18.6667,0.0276,16.1583,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,20.3728,0.0336,17.8584,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0211,V211_DDR,17.0794,0.1508,14.4478,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,31.6471,0.0253,29.1411,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0213,V213_DDR,19.8259,0.0352,17.3100,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0215,V215_DDR,30.3615,0.0253,27.8554,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0217,V217_DDR,31.7158,0.0237,29.2114,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0218,V218_DDR,35.1840,-0.0001,32.7033,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0228,V228_DDR,20.4153,0.0273,17.9073,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0232,V232_DDR,19.3246,0.0375,16.8063,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0233,V233_DDR,20.5066,0.0359,17.9899,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0240,V240_DDR,26.6503,0.0227,24.1469,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0244,V244_DDR,20.3728,0.0336,17.8584,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0246,MDT1_DDR,109.9524,0.0857,107.3860,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0249,V249_DDR,19.7620,0.0365,17.2447,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0250,V250_DDR,-12.9733,-0.1371,-15.3169,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0251,V251_DDR,19.1121,0.0322,16.5992,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.VOLT.0252,V252_DDR,35.6552,-0.0020,33.1764,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-22.5961,-0.1633,-24.9135,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,-4.5431,-0.1819,-6.8420,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-21.0774,-0.2491,-23.3091,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,17.0911,0.1175,14.4929,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-29.0707,-0.4010,-31.1505,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-24.2501,-0.1708,-26.5601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-24.2501,-0.1708,-26.5601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-24.2501,-0.1708,-26.5601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-24.2501,-0.1708,-26.5601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-24.2501,-0.1708,-26.5601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,18.2695,0.0249,15.7639,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,15.8598,0.1685,13.2106,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,19.3223,0.0353,16.8063,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,19.3186,0.0316,16.8063,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,26.5599,0.0535,24.0257,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,26.5599,0.0535,24.0257,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWWELSH1,CSWSWELSHUN1_RA,17.7506,0.0852,15.1847,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWWELSH3,CSWSWELSHUN3_RA,17.7506,0.0852,15.1847,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWWILKES1,CSWSWILKESUN1_RA,17.6762,0.1178,15.0777,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWWILKES2,CSWSWILKESUN2_RA,17.6762,0.1178,15.0777,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,CSWWILKES3,CSWSWILKESUN3_RA,17.4701,0.1109,14.8784,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-20.1329,-0.1722,-22.4414,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,DENL,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,DERS,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,DOE,DOE,6.7435,0.0278,4.2349,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,-6.1260,-0.0436,-8.5632,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,DPC,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,DUK,VACS,8.7909,0.0478,6.2624,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDDY,EDDY,30.3698,0.2934,27.5957,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,12.3759,-0.0171,9.9123,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-18.4225,-0.0590,-20.8443,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,18.9046,-0.0452,16.4690,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE.SLCC,EDESTL4391_PLT,15.7272,-0.0169,13.2633,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,15.3639,-0.0112,12.8944,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,5.7856,-0.0577,3.3625,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_EC_01,EDELAR3821UN1_RA,12.3759,-0.0171,9.9123,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_EC_02,EDELAR3821UN2_RA,12.3759,-0.0171,9.9123,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_EC_03,EDELAR3821UN3_RA,12.3759,-0.0171,9.9123,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_EC_04,EDELAR3821UN4_RA,12.3759,-0.0171,9.9123,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_EDE,EDE_LA,16.6165,0.0302,14.1055,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_ERW,EDEERWFUNG1_RA,-21.7010,-0.1547,-24.0271,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-14.8738,-0.1758,-17.1788,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,31.5200,0.0949,28.9444,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,31.5200,0.0949,28.9444,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,31.5200,0.0949,28.9444,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,31.5200,0.0949,28.9444,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,9.7629,0.0538,7.2284,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_RIV_10,EDERIV1671UN10_RA,16.1932,-0.0281,13.7405,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_RIV_11,EDERIV1671UN11_RA,16.1932,-0.0281,13.7405,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_RIV_12,EDERIV453UN12_PLT,16.1440,-0.0772,13.7405,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_SL_01,EDESTL4391UN1_RA,15.7272,-0.0169,13.2633,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EDE_SWMP,EDE_SWMP_LA,8.7250,0.0452,6.1990,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EEI,EEI,6.7104,0.0275,4.2022,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,EES,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-18.0545,-0.1581,-20.3771,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,ERCOTE,ERCOTE,17.7506,0.0852,15.1847,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,ERCOTN,ERCOTN,-14.0000,-0.1690,-16.3117,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,-7.5601,-0.1271,-9.9137,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,FMPP,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,FPC,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,FPL,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,FREM_50T,OPPDFREM_GUN1_RA,-4.9600,-0.0998,-7.3409,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,FREM_6,OPPDFREM_AUN6_RA,-4.9610,-0.1004,-7.3414,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,FREM_7,OPPDFREM_AUN7_RA,-4.9610,-0.1004,-7.3414,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,FREM_8,OPPDFREM_AUN8_RA,-4.9688,-0.1082,-7.3414,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,FREM_LOAD,FREM_LOAD_LA,-4.9623,-0.1016,-7.3414,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-23.4864,-0.1381,-25.8290,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,16.6511,0.0985,14.0718,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-22.5133,-0.1816,-24.8125,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-40.5461,-0.2231,-42.8038,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,18.7649,0.0363,16.2478,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,18.7649,0.0363,16.2478,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,18.7649,0.0363,16.2478,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,22.5080,0.0190,20.0083,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,22.5080,0.0190,20.0083,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,22.6500,0.0183,20.1510,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,22.6500,0.0183,20.1510,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-29.6681,-0.1981,-31.9508,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,37.0364,-0.0080,34.5637,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,37.0364,-0.0080,34.5637,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,37.0364,-0.0080,34.5637,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.VOLT.0130,V130_DDR,23.0572,0.0452,20.5313,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA.VOLT.0237,V237_DDR,23.4644,0.0295,20.9541,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDAHUB2,GRDAHUB2_H,6.9291,-0.0386,4.4869,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDAHUB3,GRDAHUB3_H,2.3119,-0.0589,-0.1099,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA_GRDA,GRDA_LA,23.4991,0.0278,20.9905,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA_HUB,GRDA_H,13.6003,-0.0119,11.1315,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRDA_HUBSA,GRDASA_H,13.0423,-0.0151,10.5767,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GRE,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-14.7711,0.1681,-17.4199,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GSEC_SPS,SPS_GSEC_LA,16.8180,0.0927,14.2446,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GSPR2014HUB,GSPR2014HUB_H,4.7753,0.0533,2.2413,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GSPR2015HUB,GSPR2015HUB_H,4.4071,0.0470,1.8794,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-15.5932,-0.0029,-18.0710,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,HARRISON,CSWSLEBROCKPLT1,17.0187,0.0874,14.4506,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,HAST_TNSK_HUB,HAST_TNSK_H,-6.8093,-0.1486,-9.1415,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,HQST,PJM,3.6285,-0.0049,1.1526,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,HST,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,-5.7765,-0.0043,-8.2529,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,-5.7765,-0.0043,-8.2529,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,-5.8121,-0.0060,-8.2869,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,-5.8121,-0.0060,-8.2869,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,-5.7334,-0.0045,-8.2097,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,-5.7334,-0.0045,-8.2097,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,INDN_INDN,INDN_LA,-5.7816,-0.0048,-8.2575,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-14.7344,-0.1933,-17.0219,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,ISNE,PJM,3.6285,-0.0049,1.1526,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,JEA,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,-4.8902,-0.0968,-7.2741,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,-4.8902,-0.0968,-7.2741,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-9.4183,-0.0522,-11.8468,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KACYCT4,KACYNEARMANUNCT4_RA,-7.1019,-0.0176,-9.5650,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,42.8574,-0.0419,40.4185,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,-7.1019,-0.0176,-9.5650,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,-7.0824,-0.0153,-9.5478,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,-7.0867,-0.0154,-9.5520,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KACY_KACY,KACY_LA,-7.0800,-0.0156,-9.5451,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,-6.5346,-0.0284,-8.9869,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,-2.2779,0.0505,-4.8092,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-29.5571,-0.0931,-31.9448,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-51.2901,-0.2044,-53.5665,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.VOLT.0222,V222_DDR,-6.6045,-0.0452,-9.0400,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.VOLT.0223,V223_DDR,-6.7828,-0.0450,-9.2186,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.VOLT.0241,V241_DDR,-0.5820,0.0424,-3.1051,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.VOLT.0243,V243_DDR,11.2316,-0.0078,8.7587,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.VOLT.0247,V247_DDR,-6.1946,-0.0288,-8.6465,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.VOLT.0253,V253_DDR,-6.5106,-0.0277,-8.9637,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-15.1535,-0.2031,-17.4311,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,-8.6453,-0.0692,-11.0569,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,-8.6453,-0.0692,-11.0569,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,-8.6453,-0.0692,-11.0569,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,-8.6453,-0.0692,-11.0569,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,-6.5225,-0.0289,-8.9744,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,-6.5225,-0.0289,-8.9744,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHUB,KCPLHUB_H,-11.9688,-0.1203,-14.3292,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHUB17,KCPLHUB17_H,-12.6576,-0.1295,-15.0088,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHUB18,KCPLHUB18_H,-12.3654,-0.1300,-14.7162,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHUB19,KCPLHUB19_H,-12.5115,-0.1252,-14.8671,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHUB20,KCPLHUB20_H,-13.0019,-0.1327,-15.3499,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHUB21,KCPLHUB21_H,-13.0292,-0.1282,-15.3818,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHUB22,KCPLHUB22_H,-12.4188,-0.1279,-14.7716,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHUB23,KCPLHUB23_H,-12.9217,-0.1317,-15.2708,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLHUB24,KCPLHUB24_H,-13.3541,-0.1353,-15.6996,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,-7.5556,-0.0498,-9.9865,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,-7.5556,-0.0498,-9.9865,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,-7.7822,-0.0991,-10.1639,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,-7.7822,-0.0991,-10.1639,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,-6.5346,-0.0284,-8.9869,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,-6.5346,-0.0284,-8.9869,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,-6.7023,-0.0230,-9.1601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,-6.7023,-0.0230,-9.1601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,-6.7023,-0.0230,-9.1601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,-6.7023,-0.0230,-9.1601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,-6.7023,-0.0230,-9.1601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,-6.7023,-0.0230,-9.1601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,-6.7023,-0.0230,-9.1601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,-6.7023,-0.0230,-9.1601,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,-13.8405,-0.0622,-16.2590,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,-6.3533,-0.0275,-8.8065,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KCPL_KCPL,KCPL_LA,-7.1520,-0.0316,-9.6012,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KENN,KENN_LA,9.7086,0.0510,7.1768,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KEP2_SECI,KEP2_SECI_LA,-21.7463,-0.1081,-24.1189,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KERR_1,GRDAKERR_HYDUN1_RA,23.0107,0.0265,20.5035,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KERR_2,GRDAKERR_HYDUN2_RA,22.8349,0.0280,20.3262,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KERR_3,GRDAKERR_HYDUN3_RA,22.8349,0.0280,20.3262,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KERR_4,GRDAKERR_HYDUN4_RA,23.0107,0.0265,20.5035,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,-8.6453,-0.0692,-11.0569,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,-8.6453,-0.0692,-11.0569,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,-8.3931,-0.0583,-10.8155,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,-8.3931,-0.0583,-10.8155,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,-10.3105,-0.0665,-12.7247,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,-11.6384,-0.0617,-14.0575,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,-11.6384,-0.0617,-14.0575,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-19.7215,-0.1330,-22.0693,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-19.7215,-0.1330,-22.0693,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-19.7215,-0.1330,-22.0693,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-16.2491,-0.0726,-18.6573,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-16.2491,-0.0726,-18.6573,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-20.0995,-0.1376,-22.4426,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-16.9465,-0.1123,-19.3149,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-14.6194,-0.1152,-16.9849,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,36.4455,-0.0400,34.0048,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,36.4455,-0.0400,34.0048,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-9.6701,-0.0972,-12.0536,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-9.6701,-0.0972,-12.0536,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-9.6701,-0.0972,-12.0536,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-17.2467,-0.1613,-19.5662,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-16.7407,-0.1074,-19.1140,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,-9.1034,-0.1028,-11.4814,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-8.9156,-0.0445,-11.3518,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,LAFA,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,LAM345,LAM345,-20.0487,-0.1633,-22.3662,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,LEPA,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,-5.1842,-0.1145,-7.5504,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_LES,LES_LA,-5.1868,-0.1155,-7.5521,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,-5.0832,-0.1225,-7.4414,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,-5.2667,-0.1206,-7.6268,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,-5.2667,-0.1206,-7.6268,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,-5.2667,-0.1206,-7.6268,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,-5.0815,-0.1208,-7.4414,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,-5.0832,-0.1225,-7.4414,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_WAVERLY,LES_WAVERLY_H,-5.1183,-0.1188,-7.4802,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,-4.7005,-0.1102,-7.0711,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,-4.7005,-0.1102,-7.0711,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,LGEE,LGEE,5.1193,0.0110,2.6275,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MALDEN,MALDEN_LA,9.2698,0.0476,6.7415,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MCWEST,MCWEST,-0.9024,-0.0027,-3.3805,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MDU,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-7.7615,-0.0422,-10.2001,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,-6.8321,-0.0863,-9.2265,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,-5.0724,-0.0167,-7.5364,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MEAN_NPPD,NPPD_MEAN_LA,-7.7588,-0.1686,-10.0710,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MEC,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MHEB,MHEB,-1.0642,-0.0155,-3.5294,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-13.4680,-0.1888,-15.7599,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-17.1989,-0.1994,-19.4802,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-13.4680,-0.1888,-15.7599,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-13.4680,-0.1888,-15.7599,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-17.1989,-0.1994,-19.4802,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-20.3106,-0.1502,-22.6412,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MISO,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-21.1695,-0.0760,-23.5743,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-21.1695,-0.0760,-23.5743,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-12.2578,-0.1565,-14.5820,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-20.3454,-0.2008,-22.6253,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-16.9559,-0.1781,-19.2585,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-20.6992,-0.1856,-22.9943,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-19.9470,-0.1628,-22.2649,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-20.7809,-0.1772,-23.0845,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-19.7922,-0.1591,-22.1138,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-19.7922,-0.1591,-22.1138,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-19.7922,-0.1591,-22.1138,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-19.7922,-0.1591,-22.1138,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-19.7922,-0.1591,-22.1138,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,-2.6146,-0.0333,-5.0620,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,5.9592,0.0211,3.4573,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,5.9592,0.0211,3.4573,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,3.0628,-0.0003,0.5824,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,-0.3114,0.0524,-2.8445,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MOWR,AECI,10.4491,0.0123,7.9561,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,3.1245,-0.0068,0.6506,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,6.2109,0.0230,3.7071,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-5.4380,-0.1489,-7.7699,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-5.5025,-0.1007,-7.8825,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-22.0244,-0.2021,-24.3031,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-5.4322,-0.1430,-7.7699,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,-6.1251,-0.0427,-8.5632,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,-6.1251,-0.0427,-8.5632,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,-6.1249,-0.0424,-8.5632,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,-6.1249,-0.0424,-8.5632,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,-6.6045,-0.0452,-9.0400,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,-6.6045,-0.0452,-9.0400,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,-6.6045,-0.0452,-9.0400,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,-6.6116,-0.0524,-9.0400,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,-6.6045,-0.0452,-9.0400,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,-6.6045,-0.0452,-9.0400,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,-6.6045,-0.0452,-9.0400,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,3.4543,0.0324,0.9412,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,-5.5242,-0.0418,-7.9631,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,-6.4740,-0.0490,-8.9057,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,-6.4740,-0.0490,-8.9057,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,-6.4740,-0.0490,-8.9057,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,-6.6893,-0.0276,-9.1424,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,-6.6893,-0.0276,-9.1424,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MPS_MPS,MPS_LA,-4.9497,-0.0203,-7.4101,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MSTNG,SPSMSTNGPLT1,29.9257,0.2044,27.2406,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MSTNG4,SPSMSTNGUN4_RA,29.9130,0.1917,27.2406,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MSTNG5,SPSMSTNGUN5_RA,29.9257,0.2044,27.2406,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,29.9257,0.2044,27.2406,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NBSO,PJM,3.6285,-0.0049,1.1526,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,-5.3195,-0.1419,-7.6583,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,-5.3197,-0.1422,-7.6583,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-16.5862,-0.1010,-18.9660,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NHC1,VACS,8.7909,0.0478,6.2624,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,-4.8768,-0.1015,-7.2560,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,-4.8768,-0.1015,-7.2560,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,-4.8768,-0.1015,-7.2560,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-7.2112,-0.1870,-9.5050,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,-7.1241,-0.2202,-9.3846,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,-5.9981,-0.1514,-8.3274,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-6.4500,-0.1539,-8.7768,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,-7.1241,-0.2202,-9.3846,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.HUB.PY2018,NPPDPY18_H,-7.4501,-0.1496,-9.7812,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,-7.3511,-0.1497,-9.6821,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,-7.4162,-0.1489,-9.7481,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,-7.3366,-0.1479,-9.6694,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-7.3919,-0.1615,-9.7111,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-8.7709,-0.1246,-11.1271,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-8.7709,-0.1246,-11.1271,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-9.5459,-0.1652,-11.8615,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-7.3919,-0.1615,-9.7111,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,-3.8220,-0.2823,-6.0204,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,-7.5797,-0.2311,-9.8294,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-11.0938,-0.1136,-13.4610,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,-7.5797,-0.2311,-9.8294,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,-6.8448,-0.2241,-9.1014,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-7.9274,-0.1958,-10.2123,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,-5.6806,-0.1028,-8.0586,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,-7.1241,-0.2202,-9.3846,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-10.7129,-0.1208,-13.0728,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-8.7709,-0.1246,-11.1271,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-8.7709,-0.1246,-11.1271,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-8.3777,-0.1183,-10.7401,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-8.4156,-0.1177,-10.7787,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-8.4156,-0.1177,-10.7787,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,-7.9791,-0.1040,-10.3559,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-16.1466,-0.1107,-18.5166,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,-7.0174,-0.1890,-9.3091,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-7.0856,-0.1604,-9.4060,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-6.6243,-0.1015,-9.0035,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-7.0477,-0.1054,-9.4231,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.NELI.DDR,NELI_DDR,-7.2352,-0.1893,-9.5266,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.NPPM.1058,SH1058_DDR,-1.9920,-0.1235,-4.3493,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,-7.8937,-0.1174,-10.2570,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,-7.1241,-0.2202,-9.3846,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,-5.9981,-0.1514,-8.3274,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-7.3919,-0.1615,-9.7111,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.TECH.1,KEARNE_DDR,-7.6917,-0.0947,-10.0778,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,-5.5822,-0.2424,-7.8206,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,-5.5822,-0.2424,-7.8206,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-7.4690,-0.1804,-9.7694,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD.VOLT.0236,V236_DDR,-6.1970,-0.1082,-8.5696,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD2017HUB,NPPD2017HUB_H,-7.4393,-0.1493,-9.7707,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,-2.5531,-0.1655,-4.8684,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-7.2112,-0.1870,-9.5050,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,-7.4935,-0.2707,-9.7035,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,-7.4935,-0.2707,-9.7035,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,-6.0828,-0.1112,-8.4523,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,-6.1955,-0.1067,-8.5696,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-10.1142,-0.1586,-12.4364,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-8.2964,-0.1237,-10.6534,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,-2.0305,-0.1620,-4.3493,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,-2.0305,-0.1620,-4.3493,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,-2.0305,-0.1620,-4.3493,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,-6.8014,-0.1482,-9.1340,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,-5.4948,-0.1461,-7.8295,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,-6.8520,-0.1477,-9.1850,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-10.3900,-0.3043,-12.5664,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-6.3550,-0.2914,-8.5444,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-9.3031,-0.1388,-11.6450,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-9.4938,-0.1406,-11.8340,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,-6.3671,-0.1406,-8.7073,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,-6.3689,-0.1423,-8.7073,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,-6.3689,-0.1423,-8.7073,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,-6.4044,-0.1392,-8.7459,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,-3.8220,-0.2823,-6.0204,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,-6.4507,-0.1389,-8.7926,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,-5.5604,-0.1295,-7.9117,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,-6.8144,-0.1440,-9.1512,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,-6.8185,-0.1452,-9.1541,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,-6.8204,-0.1440,-9.1572,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,-6.8204,-0.1440,-9.1572,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,-6.8014,-0.1482,-9.1340,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,-6.8058,-0.1526,-9.1340,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,-6.3498,-0.0945,-8.7360,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,-6.6195,-0.1278,-8.9725,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-9.2975,-0.1297,-11.6486,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,-6.2495,-0.2755,-8.4548,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-11.3627,-0.1228,-13.7207,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,-1.9627,-0.0941,-4.3493,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-7.2352,-0.1893,-9.5266,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-9.1343,-0.1360,-11.4791,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-9.1343,-0.1360,-11.4791,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_NPPD,NPPD_LA,-5.8195,-0.1338,-8.1664,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,-5.5604,-0.1295,-7.9117,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,-5.5604,-0.1295,-7.9117,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,-7.6528,-0.1670,-9.9665,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-7.3649,-0.1955,-9.6502,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NSB,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,NSP,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NSSO,PJM,3.6285,-0.0049,1.1526,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,NYIS,PJM,3.6285,-0.0049,1.1526,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-21.2441,-0.1978,-23.5270,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-29.8461,-0.2070,-32.1199,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-36.9983,-0.1897,-39.2894,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-36.9983,-0.1897,-39.2894,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-23.9670,-0.1770,-26.2708,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-40.5461,-0.2231,-42.8038,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-100.9260,-0.1387,-103.2680,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-52.8889,-0.2124,-55.1573,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-31.1857,-0.1978,-33.4686,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-30.0394,-0.2119,-32.3083,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-17.4217,-0.0867,-19.8157,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-31.1857,-0.1978,-33.4686,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-23.1894,-0.1847,-25.4854,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-20.3106,-0.1502,-22.6412,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-20.3240,-0.2108,-22.5940,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,-11.9463,-0.0441,-14.3829,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-30.0394,-0.2119,-32.3083,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-25.5024,-0.1843,-27.7989,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-27.7176,-0.2052,-29.9931,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-19.8560,-0.1529,-22.1839,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-25.7071,-0.0482,-28.1396,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-20.3106,-0.1502,-22.6412,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-20.3106,-0.1502,-22.6412,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-30.0394,-0.2119,-32.3083,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-19.6543,-0.1298,-22.0052,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.NUEN.LAM1,LAM1_DDR,18.9773,0.1434,16.3531,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-17.4217,-0.0867,-19.8157,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-17.4217,-0.0867,-19.8157,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-20.2020,-0.1323,-22.5504,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-17.5500,-0.0941,-19.9366,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-17.5500,-0.0941,-19.9366,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-17.5500,-0.0941,-19.9366,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-17.6644,-0.0852,-20.0600,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-17.6644,-0.0852,-20.0600,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-17.5500,-0.0941,-19.9366,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-17.5500,-0.0941,-19.9366,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-30.0394,-0.2119,-32.3083,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,13.4476,0.0782,10.8887,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-23.1894,-0.1847,-25.4854,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-19.9494,-0.1006,-22.3295,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-25.5024,-0.1843,-27.7989,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,15.4252,0.0885,12.8560,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-21.4741,-0.1505,-23.8044,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-21.4741,-0.1505,-23.8044,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-21.4741,-0.1505,-23.8044,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-21.4741,-0.1505,-23.8044,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-37.0717,-0.2855,-39.2669,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-32.0700,-0.1915,-34.3592,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-29.8461,-0.2070,-32.1199,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-35.0783,-0.1851,-37.3740,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-35.0783,-0.1851,-37.3740,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-16.2142,-0.0590,-18.6360,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-20.7061,-0.1629,-23.0240,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-20.7061,-0.1629,-23.0240,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-20.7061,-0.1629,-23.0240,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0033,FOSTER_DDR,-16.6158,-0.0815,-19.0151,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,5.3708,0.0412,2.8489,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0035,TARBY_DDR,18.8203,0.1131,16.2264,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,5.3708,0.0412,2.8489,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,3.2878,0.0106,0.7964,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,3.2878,0.0106,0.7964,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-20.5481,-0.0680,-22.9608,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0040,TROSPER_DDR,-16.3700,-0.0792,-18.7716,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,-16.6462,-0.0796,-19.0473,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,16.5274,0.1065,13.9402,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0115,V115_DDR,-17.3699,-0.0859,-19.7647,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0116,V116_DDR,1.5100,-0.0417,-0.9290,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0118,V118_DDR,-36.6377,-0.0220,-39.0965,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0125,V125_DDR,16.9366,0.1270,14.3289,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0126,V126_DDR,17.7724,0.0598,15.2318,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0129,V129_DDR,-16.1265,-0.1353,-18.4720,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,-16.7650,-0.0954,-19.1503,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0134,V134_DDR,19.0175,0.0791,16.4577,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0138,V138_DDR,16.9305,0.0500,14.3998,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,-17.0202,-0.0907,-19.4103,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0143,V143_DDR,8.7854,0.0197,6.2850,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0149,V149_DDR,-18.9355,-0.1359,-21.2804,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0150,V150_DDR,-18.7566,-0.1371,-21.1002,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0155,V155_DDR,16.2361,0.0393,13.7160,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0156,V156_DDR,-16.7650,-0.0954,-19.1503,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0166,V166_DDR,17.4816,0.1172,14.8836,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,-16.8595,-0.0889,-19.2514,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-18.7566,-0.1371,-21.1002,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0170,V170_DDR,-20.3595,-0.1317,-22.7086,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-18.2233,-0.1314,-20.5727,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0176,V176_DDR,-18.7566,-0.1371,-21.1002,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0177,V177_DDR,-27.1683,-0.2286,-29.4204,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,-16.7923,-0.0851,-19.1880,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-23.6564,-0.1781,-25.9590,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0195,V195_DDR,86.3326,0.0906,83.7613,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0197,V197_DDR,16.2163,0.0746,13.6609,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0198,V198_DDR,17.4816,0.1172,14.8836,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0208,V208_DDR,86.4449,0.0928,83.8714,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0209,V209_DDR,86.4449,0.0928,83.8714,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,16.9741,0.0505,14.4428,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0216,V216_DDR,-16.7154,-0.0799,-19.1162,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0219,V219_DDR,16.2361,0.0393,13.7160,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0220,V220_DDR,-18.7566,-0.1371,-21.1002,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0224,V224_DDR,-17.4503,-0.0890,-19.8420,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0225,V225_DDR,-17.4501,-0.0889,-19.8420,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0226,V226_DDR,-17.4503,-0.0890,-19.8420,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0227,V227_DDR,-17.4503,-0.0890,-19.8420,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0229,V229_DDR,-20.1520,-0.0615,-22.5712,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0231,V231_DDR,-14.7157,-0.0190,-17.1775,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0238,V238_DDR,-37.2965,-0.2234,-39.5539,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.VOLT.0242,V242_DDR,16.5247,0.0446,13.9994,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-30.0951,-0.3262,-32.2497,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-20.3106,-0.1502,-22.6412,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-29.6516,-0.1968,-31.9355,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-20.3219,-0.2086,-22.5940,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-30.0951,-0.3262,-32.2497,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-19.3400,-0.2319,-21.5889,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-58.2407,-0.2000,-60.5214,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEHL7,OKGEHL7_H,-13.4962,-0.0747,-15.9022,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEHL8,OKGEHSL1UN8_RA,-13.4962,-0.0747,-15.9022,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEHL910,OKGEHSL1PLT2,-13.4962,-0.0747,-15.9022,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-20.0293,-0.2190,-22.2910,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEMCC,OKGEMCCLAIPLT1,-17.5902,-0.1095,-19.9615,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,13.3185,0.0272,10.8105,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,13.3185,0.0272,10.8105,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,13.3185,0.0272,10.8105,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,-12.7139,-0.1024,-15.0922,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,-12.7139,-0.1024,-15.0922,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,-12.7139,-0.1024,-15.0922,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,-12.7139,-0.1024,-15.0922,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGESM1,OKGESEMINOLEUN1_RA,-17.0261,-0.0579,-19.4490,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGESM2,OKGESEMINOLEUN2_RA,-12.9005,-0.0632,-15.3180,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGESM3,OKGESEMINOLEUN3_RA,-12.9005,-0.0632,-15.3180,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGESO1,OKGESONR1UN1_RA,-61.2875,-0.1747,-63.5936,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGESO2,OKGESONR1UN2_RA,-35.0783,-0.1851,-37.3740,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-20.0510,-0.2407,-22.2910,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-23.7552,-0.2923,-25.9436,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGETINK5A,OKGETINK5UN1_RA,-15.9229,-0.0814,-18.3222,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGETINK5B,OKGETINK5UN2_RA,-15.9229,-0.0814,-18.3222,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-20.5121,-0.2028,-22.7901,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-29.8461,-0.2070,-32.1199,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,16.1024,0.1560,13.4657,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-20.3106,-0.1502,-22.6412,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE_OKGE,OKGE_LA,-8.5081,-0.0473,-10.9415,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-19.9494,-0.1006,-22.3295,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-20.5204,-0.2111,-22.7901,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMLP,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,21.8776,0.0200,19.3769,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,16.2872,0.1475,13.6590,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-19.4218,-0.0876,-21.8150,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-100.9107,-0.1234,-103.2680,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-25.5744,-0.2050,-27.8502,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-31.1857,-0.1978,-33.4686,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-28.1748,-0.3298,-30.3257,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-15.7062,-0.1993,-17.9877,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,155.3954,0.0009,152.9138,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-100.9143,-0.1271,-103.2680,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-100.9143,-0.1271,-103.2680,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_SPP,OMPA_SPP_LA,-25.2050,-0.1176,-27.5681,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-30.0951,-0.3262,-32.2497,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,18.3228,0.0147,15.8274,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,18.3228,0.0147,15.8274,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,18.3228,0.0147,15.8274,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,18.3228,0.0147,15.8274,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,ONT,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,-4.9147,-0.1037,-7.2917,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,-4.9147,-0.1037,-7.2917,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,-4.9147,-0.1037,-7.2917,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,-4.9147,-0.1037,-7.2917,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,-4.9147,-0.1037,-7.2917,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,-4.9147,-0.1037,-7.2917,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,-4.9147,-0.1037,-7.2917,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,-4.9147,-0.1037,-7.2917,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,-4.9147,-0.1037,-7.2917,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,-4.8852,-0.0996,-7.2664,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,-4.8768,-0.1015,-7.2560,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,-4.9413,-0.0864,-7.3356,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,-4.9241,-0.0958,-7.3090,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,-4.9241,-0.0958,-7.3090,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD_GLDN,OPPD_GLDN_LA,-4.9068,-0.1003,-7.2872,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,-4.8942,-0.1010,-7.2740,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,-3.8220,-0.2823,-6.0204,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,-5.7296,-0.1229,-8.0875,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,-4.8777,-0.1013,-7.2571,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD_OPPD,OPPD_LA,-4.9150,-0.0975,-7.2983,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,-4.9137,-0.0930,-7.3014,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,-4.9174,-0.0939,-7.3043,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OTP,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,OVEC,OVEC,4.5290,0.0050,2.0433,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PARAGOULD,PARAGOULD_LA,10.4459,0.0565,7.9087,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,22.5783,0.0076,20.0900,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,22.5783,0.0076,20.0900,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,22.5783,0.0076,20.0900,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,22.2626,0.0167,19.7652,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,22.2626,0.0167,19.7652,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,22.2626,0.0167,19.7652,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PIGGOTT,PIGGOTT_LA,9.5528,0.0498,7.0222,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PJM,PJM,3.6285,-0.0049,1.1526,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PLUM,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,POPLARBLUFF,POPLARBLUFF_LA,8.9315,0.0410,6.4097,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,-1.0014,-0.0356,-3.4465,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,-1.0014,-0.0356,-3.4465,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,-0.8443,-0.0341,-3.2909,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,-0.8443,-0.0341,-3.2909,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,-0.4883,0.1181,-3.0872,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,-0.4883,0.1181,-3.0872,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,-0.8856,-0.0040,-3.3623,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,-1.6971,-0.0895,-4.0883,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-21.3062,-0.1452,-23.6418,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,70.0859,0.0062,67.5989,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,-6.1147,-0.0301,-8.5654,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-19.1423,-0.0262,-21.5969,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,29.3963,0.0621,26.8534,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,18.4599,0.0647,15.9144,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,-3.0644,-0.1159,-5.4293,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,-0.5412,0.0015,-3.0234,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,-3.8452,-0.1553,-6.1706,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,11.0000,0.1048,8.4145,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,-0.5274,0.0107,-3.0189,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,-3.4173,-0.1033,-5.7947,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,PUPP,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,RCEAST,RCEAST,-4.2205,-0.0928,-6.6084,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SALINA_1,GRDASALINA1UN1_RA,23.0110,0.0267,20.5035,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SALINA_2,GRDASALINA1UN2_RA,23.0110,0.0267,20.5035,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SALINA_3,GRDASALINA1UN3_RA,23.0110,0.0267,20.5035,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SALINA_4,GRDASALINA1UN4_RA,23.0110,0.0267,20.5035,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SALINA_5,GRDASALINA1UN5_RA,23.0110,0.0267,20.5035,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SALINA_6,GRDASALINA1UN6_RA,23.0110,0.0267,20.5035,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SARPY_1,OPPDSARPYUN1_RA,-4.9073,-0.1008,-7.2873,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SARPY_2,OPPDSARPYUN2_RA,-4.9113,-0.0969,-7.2952,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SARPY_3,OPPDSARPYUN3_RA,-4.8909,-0.1041,-7.2675,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SARPY_4,OPPDSARPYUN4_RA,-4.8909,-0.1041,-7.2675,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SARPY_5,OPPDSARPYUN5_RA,-4.8909,-0.1041,-7.2675,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SC,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SCEG,VACS,8.7909,0.0478,6.2624,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SCSE,SCSE,-8.8511,-0.1085,-11.2234,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SEC,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-21.0167,-0.2230,-23.2744,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-21.0167,-0.2230,-23.2744,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-21.0167,-0.2230,-23.2744,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-20.0495,-0.0616,-22.4686,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-21.0167,-0.2230,-23.2744,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-20.2100,-0.1903,-22.5005,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-19.6555,-0.2147,-21.9215,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-19.6555,-0.2147,-21.9215,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-19.7924,-0.1594,-22.1138,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-21.7649,-0.2087,-24.0370,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-16.2585,-0.0820,-18.6573,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-20.5521,-0.0852,-22.9476,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-15.8141,-0.1417,-18.1531,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-20.7841,-0.2198,-23.0450,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-15.7571,-0.1413,-18.0966,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-28.7800,-0.2248,-31.0359,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-20.2894,-0.1452,-22.6249,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-19.7900,-0.1431,-22.1277,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-19.7900,-0.1431,-22.1277,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-19.7900,-0.1431,-22.1277,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-19.7900,-0.1431,-22.1277,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-19.9632,-0.1549,-22.2891,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-20.2100,-0.1903,-22.5005,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI_SECI,SECI_LA,-19.5374,-0.1192,-21.8990,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-14.7344,-0.1933,-17.0219,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-14.7344,-0.1933,-17.0219,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-19.7924,-0.1594,-22.1138,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SEHA,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-20.5204,-0.2111,-22.7901,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SERU,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SETH,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SGE,SGE,-7.9988,-0.0976,-10.3819,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SMEP,MISO,4.4006,0.0008,1.9190,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SOCO,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPA,SPA,17.9071,0.0726,15.3537,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPC,SPC,-0.4223,0.0470,-2.9500,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPPNORTH_HUB,SPPNORTH_H,-5.2388,-0.1147,-7.6049,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-17.1320,-0.1348,-19.4779,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,14.6462,0.0544,12.1111,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,14.6462,0.0544,12.1111,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,13.9604,0.0520,11.4276,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,13.9604,0.0520,11.4276,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_NIXA,SPRM_NIXA_LA,15.9240,0.0574,13.3859,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_SPRM,SPRM_LA,14.6026,0.0607,12.0611,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,14.8325,0.0435,12.3083,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,14.8325,0.0435,12.3083,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,14.8264,0.0374,12.3083,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,14.8325,0.0435,12.3083,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,31.6090,0.1526,28.9757,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,34.4117,0.0774,31.8535,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-16.8089,-0.0352,-19.2544,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-16.8089,-0.0352,-19.2544,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,30.2170,-0.0111,27.7473,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,29.9553,0.0888,27.3858,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,31.7586,-0.1852,29.4630,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,30.3918,0.3229,27.5881,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,29.3147,0.0837,26.7503,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,30.0293,0.2122,27.3364,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,30.0551,0.2328,27.3416,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,30.0551,0.2328,27.3416,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,30.0293,0.2122,27.3364,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-16.7453,-0.0081,-19.2179,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,34.4117,0.0774,31.8535,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-16.7865,-0.0314,-19.2359,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-21.4153,-0.1489,-23.7471,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-18.4875,-0.0265,-20.9418,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-17.1548,0.0150,-19.6505,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-17.4275,-0.0363,-19.8719,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-25.0000,-0.1633,-27.3174,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-25.0000,-0.1633,-27.3174,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-25.0000,-0.1633,-27.3174,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-25.0000,-0.1633,-27.3174,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GRID.WRAB,WRAB_DDR,-15.7636,0.0130,-18.2574,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-25.0000,-0.1633,-27.3174,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,28.6933,0.0897,26.1229,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,28.6933,0.0897,26.1229,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,27.1110,0.0903,24.5399,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,27.1110,0.0903,24.5399,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,27.1110,0.0903,24.5399,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,28.6933,0.0897,26.1229,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-15.1467,-0.0290,-17.5985,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-15.1486,-0.0290,-17.6003,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-15.1429,-0.0289,-17.5947,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-16.5862,-0.1010,-18.9660,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,30.0165,0.2090,27.3267,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,29.3001,0.0812,26.7382,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,29.3001,0.0812,26.7382,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,29.3001,0.0812,26.7382,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,29.3001,0.0812,26.7382,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,29.9749,0.2012,27.2930,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,30.0170,0.2026,27.3336,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,30.0170,0.2026,27.3336,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-20.5081,-0.1987,-22.7901,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-15.5308,-0.0270,-17.9846,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-15.5308,-0.0270,-17.9846,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-15.2112,-0.0288,-17.6632,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-15.7636,0.0130,-18.2574,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-20.9264,-0.1113,-23.2959,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-17.5541,-0.0417,-19.9931,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-23.9670,-0.1770,-26.2708,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-15.4928,0.0110,-17.9846,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.PLANTX1,SPS.PLANTX1_H,32.7464,0.1375,30.1282,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.PLANTX2,SPS.PLANTX2_H,32.7464,0.1375,30.1282,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,32.4333,0.1343,29.8182,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,30.0319,0.0334,27.5178,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-23.0256,-0.1417,-25.3646,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,31.8231,-0.1206,29.4630,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,30.0384,0.0399,27.5178,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-16.7461,-0.0089,-19.2179,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,31.2917,0.1717,28.6393,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,30.3918,0.3229,27.5881,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,31.2917,0.1717,28.6393,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,30.3929,0.3223,27.5898,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-43.3397,-0.0505,-45.7699,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,30.2616,0.3801,27.4007,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,30.2720,0.3906,27.4007,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,30.2261,0.3674,27.3780,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,30.0480,0.2339,27.3333,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,30.3325,0.3556,27.4961,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-20.0487,-0.1633,-22.3662,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-15.7547,0.0015,-18.2369,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,31.9189,0.1435,29.2947,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,31.9189,0.1435,29.2947,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,31.2917,0.1717,28.6393,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,29.3647,0.0955,26.7884,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,30.0100,0.2770,27.2523,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,32.2333,0.2546,29.4980,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,32.3262,0.1954,29.6501,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,32.9383,0.0785,30.3790,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,30.2616,0.3801,27.4007,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,30.3795,0.4322,27.4666,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,30.3444,0.3970,27.4666,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,30.0562,0.0577,27.5178,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,32.1314,0.1919,29.4587,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-22.5856,-0.1340,-24.9323,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-22.5795,-0.1378,-24.9225,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0163,V163_DDR,-14.8626,0.0007,-17.3441,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0168,V168_DDR,-18.8797,-0.1167,-21.2438,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0180,V180_DDR,30.3795,0.4322,27.4666,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0181,V181_DDR,-22.8102,-0.1110,-25.1800,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0182,V182_DDR,30.3379,0.3646,27.4925,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0199,V199_DDR,29.9929,0.2548,27.2573,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0200,V200_DDR,30.1254,0.2827,27.3619,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.VOLT.0235,V235_DDR,-20.9264,-0.1113,-23.2959,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,31.7586,-0.1852,29.4630,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,30.3918,0.3229,27.5881,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-15.5960,-0.0057,-18.0710,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-15.8256,-0.0095,-18.2968,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS_SPS,SPS_LA,19.0055,0.2220,16.3028,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,31.1591,0.1706,28.5077,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SSCN_NPPD,SSCN_NPPD_LA,-5.9864,-0.1441,-8.3231,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,7.9977,0.0375,5.4795,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,7.9977,0.0375,5.4795,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,TAL,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,TEC,SOUC,9.1584,0.0522,6.6255,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,-6.2495,-0.2755,-8.4548,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,TVA,TVA,8.4029,0.0432,5.8790,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,UCUHUB,UCUHUB_H,-10.4318,-0.0855,-12.8270,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,UCUHUB17,UCUHUB17_H,-14.7794,-0.1305,-17.1296,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,UCUHUB18,UCUHUB18_H,-11.6871,-0.1182,-14.0497,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,UCUHUB19,UCUHUB19_H,-14.6325,-0.1253,-16.9879,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,UCUHUB20,UCUHUB20_H,-14.7964,-0.1200,-17.1571,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,UCUHUB21,UCUHUB21_H,-16.1198,-0.1323,-18.4682,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,UCUHUB22,UCUHUB22_H,-15.6287,-0.1390,-17.9704,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,UCUHUB23,UCUHUB23_H,-15.8780,-0.1401,-18.2186,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,UCUHUB24,UCUHUB24_H,-13.8919,-0.1243,-16.2484,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,-0.4037,0.0678,-2.9522,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,-0.4037,0.0678,-2.9522,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,-0.4178,-0.0809,-2.8177,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,-0.4178,-0.0809,-2.8177,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,-0.4563,-0.0833,-2.8538,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,-0.8377,-0.0543,-3.2641,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,-0.8377,-0.0543,-3.2641,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,-0.4037,0.0678,-2.9522,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,-0.5001,-0.0805,-2.9004,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,-0.4168,0.0045,-2.9021,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,-3.6615,-0.1473,-5.9950,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,-3.9030,-0.2538,-6.1300,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,-0.5010,0.0639,-3.0457,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,-0.5010,0.0639,-3.0457,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,7.1955,-0.2753,4.9901,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,-5.1430,-0.1250,-7.4987,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,5.6406,-0.0336,3.1935,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,-3.9362,-0.1548,-6.2621,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,-3.6819,-0.1272,-6.0354,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,-5.3923,-0.1366,-7.7365,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,7.3214,-0.1494,4.9901,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,7.3214,-0.1494,4.9901,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,-2.6388,-0.1121,-5.0074,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,-3.7592,-0.2513,-5.9887,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,-3.6204,-0.0944,-6.0067,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,9.6700,-0.0342,7.2235,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,9.6700,-0.0342,7.2235,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,9.6700,-0.0342,7.2235,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,-0.4871,-0.0144,-2.9535,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,-0.4871,-0.0144,-2.9535,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,-0.4871,-0.0144,-2.9535,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,-0.3691,0.1014,-2.9512,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,-0.3825,-0.0791,-2.7841,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,-0.3328,-0.0827,-2.7308,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-8.4223,-0.1035,-10.7995,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,-5.0081,-0.1168,-7.3720,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,-0.5360,0.0051,-3.0219,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,-5.0678,-0.1529,-7.3956,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,-3.9546,-0.2854,-6.1500,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,7.1452,-0.1220,4.7864,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,-0.4524,0.0495,-2.9826,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,-0.4524,0.0495,-2.9826,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,-0.4528,0.0490,-2.9826,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,-0.4524,0.0495,-2.9826,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,-0.4316,0.0453,-2.9576,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,-0.4316,0.0453,-2.9576,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,-0.4316,0.0453,-2.9576,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,-0.4316,0.0453,-2.9576,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,-0.4316,0.0453,-2.9576,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,-0.4316,0.0453,-2.9576,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,-0.4316,0.0453,-2.9576,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,-4.7816,-0.2466,-7.0157,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,-0.5235,-0.0397,-2.9646,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,-4.6476,-0.1176,-7.0107,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,-4.6476,-0.1176,-7.0107,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,-5.4410,-0.1820,-7.7398,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,-5.4410,-0.1820,-7.7398,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,-0.3575,-0.0541,-2.7841,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,-0.7342,-0.0481,-3.1668,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,-3.7882,-0.1841,-6.0849,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,-3.4355,-0.2174,-5.6989,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,-2.8388,-0.0838,-5.2358,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,-0.4563,-0.0833,-2.8538,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,-0.4563,-0.0833,-2.8538,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,-3.9362,-0.1548,-6.2621,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,-4.2332,-0.0952,-6.6188,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,1.7866,-0.1354,-0.5587,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,-3.7272,-0.2192,-5.9887,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,-8.2000,-0.1375,-10.5432,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.FSE,WAUE.FSE_H,-5.7591,-0.1666,-8.0732,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,-0.7305,-0.0041,-3.2071,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,-0.7622,-0.0056,-3.2374,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,-4.5273,-0.2728,-6.7353,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,-4.3319,-0.2568,-6.5559,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,-0.3752,-0.0805,-2.7755,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,-0.4924,-0.0905,-2.8826,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-21.3600,-0.2748,-23.5659,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,-3.9030,-0.2538,-6.1300,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-12.0000,-0.0824,-14.3983,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,-3.9885,-0.1394,-6.3298,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,-3.9759,-0.1269,-6.3298,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,-3.9758,-0.1267,-6.3298,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,-6.5191,-0.1196,-8.8803,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,-4.2332,-0.0952,-6.6188,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,-3.1482,-0.0843,-5.5446,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,-3.9799,-0.1604,-6.3002,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,-3.6180,-0.0920,-6.0067,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,-3.6615,-0.0222,-6.1200,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,-3.6000,-0.1178,-5.9630,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,-1.9893,-0.0648,-4.4053,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,-3.8003,-0.1425,-6.1386,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,-3.8234,-0.1679,-6.1362,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,-5.0678,-0.1529,-7.3956,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,-1.5577,-0.0036,-4.0348,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,-3.9397,-0.1568,-6.2636,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,-1.6251,-0.0191,-4.0867,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,-3.3278,-0.0907,-5.7178,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,-4.7005,-0.1102,-7.0711,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NTWK,WAUE.NTWK_H,-2.4252,-0.0882,-4.8178,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,-2.2989,0.0184,-4.7981,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,-2.2989,0.0184,-4.7981,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,-3.8686,-0.2842,-6.0652,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,-4.7447,-0.3190,-6.9065,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,-3.5848,-0.1065,-5.9590,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,-3.8686,-0.2842,-6.0652,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,-0.8669,-0.0372,-3.3104,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,-2.3830,-0.1437,-4.7200,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,-5.0678,-0.1529,-7.3956,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,-2.2705,-0.0796,-4.6717,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,-2.5335,-0.2943,-4.7200,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,-4.4963,-0.1986,-6.7785,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,-4.1691,-0.1934,-6.4564,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,-0.3278,-0.0850,-2.7236,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,-5.1810,-0.2604,-7.4013,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,-3.1967,-0.0757,-5.6017,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,-3.1125,-0.1831,-5.4102,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,-3.4355,-0.2174,-5.6989,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.VOLT.0152,V152_DDR,-0.3324,0.1297,-2.9428,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE.VOLT.0172,V172_DDR,-0.4281,0.0547,-2.9635,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_BEPM,WAUE_BEPM_LA,-0.5735,-0.0034,-3.0509,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,-3.3190,-0.1034,-5.6963,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,-3.6635,-0.0210,-6.1232,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_EWA,WAUE_EWA_LA,-4.1884,-0.0862,-6.5829,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,-2.7605,-0.1547,-5.0866,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_HMMU,WAUE_HMMU_LA,-4.2835,-0.0592,-6.7051,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,-1.8952,-0.0719,-4.3040,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_MECB,WAUE_MECB_LA,-4.0560,-0.0466,-6.4902,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_MMPA,WAUE_MMPA_LA,-0.6832,0.0229,-3.1868,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_MRES,WAUE_MRES_LA,-3.6802,-0.0887,-6.0723,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,-0.3798,0.0823,-2.9428,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,-0.7305,-0.0041,-3.2071,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,-3.4888,-0.1495,-5.8200,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_OTP,WAUE_OTP_LA,-0.4612,0.0687,-3.0107,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_OTPW,WAUE_OTPW_LA,0.2330,0.0046,-2.2524,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM,WAUE_UGPM_LA,-2.3371,-0.0907,-4.7272,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,-0.9536,-0.0352,-3.3992,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,-3.7530,-0.1122,-6.1215,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,-2.5259,-0.1124,-4.8943,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,-4.1884,-0.0862,-6.5829,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,-4.2835,-0.0592,-6.7051,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,-2.0899,-0.1618,-4.4088,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,-0.7305,-0.0041,-3.2071,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,-0.6832,0.0229,-3.1868,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,-3.0916,-0.0760,-5.4963,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,-3.6428,-0.1720,-5.9516,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,-0.4520,0.0857,-3.0184,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-30.0000,-0.2936,-32.1871,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-31.5000,-0.2675,-33.7132,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,-10.4130,-0.1619,-12.7318,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,109.9100,0.0433,107.3860,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,109.9100,0.0433,107.3860,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-17.5942,-0.2828,-19.7921,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,97.2813,0.0566,94.7439,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,82.6542,0.0534,80.1200,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,2.7254,-0.1613,0.4060,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,2.7254,-0.1613,0.4060,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,2.7254,-0.1613,0.4060,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,2.7197,-0.1671,0.4060,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,2.7200,-0.1667,0.4060,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,2.7254,-0.1613,0.4060,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,2.7254,-0.1613,0.4060,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,2.7254,-0.1613,0.4060,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,-3.1219,-0.1540,-5.4487,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-23.9670,-0.1770,-26.2708,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-26.2491,-0.2444,-28.4854,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-28.5547,-0.3756,-30.6598,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,31.8063,-0.1374,29.4630,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_ENMC,WFEC_ENMC_LA,30.5788,0.2444,27.8536,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-30.0394,-0.2119,-32.3083,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,26.4475,0.0266,23.9401,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,29.9702,0.1851,27.3043,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-30.0000,-0.2936,-32.1871,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-30.0000,-0.2936,-32.1871,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-30.0000,-0.2936,-32.1871,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_OKGE,WFEC_OKGE_LA,-19.4966,-0.0432,-21.9341,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,16.5578,0.0472,14.0299,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-21.9421,-0.2795,-24.1433,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-17.6967,-0.2964,-19.8811,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_WFEC,WFEC_LA,1.7027,-0.0796,-0.6984,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,29.9702,0.1851,27.3043,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-14.1814,-0.1933,-16.4689,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-18.4911,-0.1541,-20.8178,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-13.7379,-0.1240,-16.0947,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-13.7379,-0.1240,-16.0947,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-13.7379,-0.1240,-16.0947,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-13.7379,-0.1240,-16.0947,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-13.7379,-0.1240,-16.0947,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-13.7379,-0.1240,-16.0947,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-13.7379,-0.1240,-16.0947,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,-3.6593,0.0325,-6.1725,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-14.5006,-0.1601,-16.8213,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-26.5729,-0.2034,-28.8502,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-26.5729,-0.2034,-28.8502,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-26.5729,-0.2034,-28.8502,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-22.0620,-0.2114,-24.3313,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-22.0620,-0.2114,-24.3313,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-22.5505,-0.1864,-24.8448,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-22.5505,-0.1864,-24.8448,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-22.5505,-0.1864,-24.8448,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-14.5006,-0.1601,-16.8213,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,-8.1106,-0.0517,-10.5396,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-18.0766,-0.1523,-20.4051,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-18.0766,-0.1523,-20.4051,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-18.0766,-0.1523,-20.4051,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-18.0765,-0.1522,-20.4051,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,-8.1106,-0.0517,-10.5396,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-20.4232,-0.2148,-22.6891,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-41.1500,-0.1067,-43.5240,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.JEC.1,WRJEFFUN10_RA,-12.1254,-0.1161,-14.4901,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.JEC.2,WRJEFFUN11_RA,-12.0153,-0.1163,-14.3798,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.JEC.3,WRJEFFUN12_RA,-12.0222,-0.1231,-14.3798,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-29.6681,-0.1981,-31.9508,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-22.0224,-0.2001,-24.3031,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-22.0224,-0.2001,-24.3031,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.LEC.4,WRLECUN26_RA,-9.4577,-0.0632,-11.8753,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.LEC.5,WRLECUN27_RA,-9.9496,-0.0567,-12.3737,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-16.8232,-0.1240,-19.1799,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-16.8232,-0.1240,-19.1799,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-16.8232,-0.1240,-19.1799,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-16.7986,-0.1196,-19.1598,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-14.7344,-0.1933,-17.0219,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-14.7344,-0.1933,-17.0219,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-15.7666,-0.1240,-18.1233,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-13.9213,-0.1864,-16.2156,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-13.9213,-0.1864,-16.2156,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-16.7420,-0.1087,-19.1140,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-14.7344,-0.1933,-17.0219,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-9.3446,-0.1812,-11.6441,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-14.8738,-0.1758,-17.1788,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-22.0235,-0.2011,-24.3031,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,82.3449,0.0587,79.8055,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-16.6879,-0.1107,-19.0580,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-13.7379,-0.1240,-16.0947,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-15.2338,-0.2080,-17.5066,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,-8.1106,-0.0517,-10.5396,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-14.5006,-0.1601,-16.8213,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-24.1469,-0.1692,-26.4585,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.THAYERLD,WR.THAYERLD_LA,10.3561,0.0472,7.8282,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-24.9880,-0.1672,-27.3015,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0106,V106_DDR,-24.0161,-0.1629,-26.3339,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-8.0824,-0.0377,-10.5254,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-15.4089,-0.1375,-17.7521,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-9.3213,-0.0451,-11.7569,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-9.3213,-0.0451,-11.7569,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-8.4670,-0.0458,-10.9020,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-23.4913,-0.1411,-25.8310,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0157,V157_DDR,-9.3688,-0.0473,-11.8023,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0158,V158_DDR,-9.3213,-0.0451,-11.7569,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-9.3213,-0.0451,-11.7569,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-24.0867,-0.1742,-26.3932,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0173,V173_DDR,-16.7924,-0.1148,-19.1584,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0174,V174_DDR,-23.8712,-0.1617,-26.1902,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0184,V184_DDR,-23.4494,-0.1761,-25.7540,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-24.2748,-0.1672,-26.5884,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0186,V186_DDR,-24.2597,-0.1727,-26.5678,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-23.6843,-0.1723,-25.9928,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-24.8265,-0.1652,-27.1420,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-17.9585,-0.1269,-20.3123,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-14.6652,-0.1114,-17.0345,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-13.9917,-0.1172,-16.3552,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-13.9917,-0.1172,-16.3552,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-14.6652,-0.1114,-17.0345,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0245,V245_DDR,-24.2878,-0.1672,-26.6013,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.VOLT.0248,V248_DDR,-24.0161,-0.1629,-26.3339,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-26.6523,-0.1888,-28.9442,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-10.3293,-0.0698,-12.7402,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.WOLF,WRWOLFUN15_RA,-15.9323,-0.2207,-18.1924,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-20.4232,-0.2148,-22.6891,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,-3.6700,0.0218,-6.1725,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-26.5729,-0.2034,-28.8502,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-26.5729,-0.2034,-28.8502,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-26.5729,-0.2034,-28.8502,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-26.5729,-0.2034,-28.8502,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-23.8261,-0.1481,-26.1587,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-15.3466,-0.1383,-17.6891,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-25.1169,-0.1678,-27.4298,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-25.1169,-0.1678,-27.4298,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-25.1169,-0.1678,-27.4298,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-25.1169,-0.1678,-27.4298,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-14.0392,-0.1049,-16.4150,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-14.0392,-0.1049,-16.4150,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-14.0392,-0.1049,-16.4150,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-14.0392,-0.1049,-16.4150,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-14.0392,-0.1049,-16.4150,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-14.0392,-0.1049,-16.4150,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-39.4872,-0.1652,-41.8028,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-39.4872,-0.1652,-41.8028,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-41.9770,-0.1673,-44.2904,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-41.9770,-0.1673,-44.2904,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_MIDW,WR_MIDW_LA,-15.9616,-0.1393,-18.3030,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,-1.2362,0.0215,-3.7385,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,-5.0495,-0.0235,-7.5068,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-17.1992,-0.1588,-19.5212,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_SEG,WR_SEG_LA,-5.6437,0.0038,-8.1282,2.4807\n03/19/2025 02:00:00,03/19/2025 07:00:00,WR_WR,WR_LA,-15.7305,-0.1157,-18.0956,2.4808\n03/19/2025 02:00:00,03/19/2025 07:00:00,YAD,VACS,8.7909,0.0478,6.2624,2.4807\n03/19/2025 03:00:00,03/19/2025 08:00:00,AEC,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,AECC_CSWS,CSWS_AECC_LA,15.9502,0.0418,14.9445,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,15.9702,0.0274,14.9789,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,13.9962,0.0588,12.9735,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,16.2214,0.0184,15.2392,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,16.5538,0.0320,15.5580,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,14.4780,0.0226,13.4916,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,18.0512,0.0209,17.0665,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,AECI,AECI,8.1510,0.0095,7.1777,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,AEPM_CSWS,CSWS_LA,16.8471,0.0337,15.8495,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,ALTW,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,AMRN,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,24.9655,0.0084,23.9933,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,BBA,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,BCA,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,BEPM.ER01.DDR,ER01_DDR,-4.8686,-0.0652,-5.7673,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,BEPM_ER01,BEPM_ER01_LA,-4.8686,-0.0652,-5.7673,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,-7.0170,-0.0263,-7.9545,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-9.0680,-0.0118,-10.0201,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,BEPM_UM01,BEPM_UM01_LA,-1.3925,0.0293,-2.3856,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,BLKW,BLKW,27.7496,0.0339,26.7518,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-27.2910,-0.0902,-28.1647,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-27.2910,-0.0902,-28.1647,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,-2.4800,-0.0765,-3.3673,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-27.2900,-0.0891,-28.1647,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,BRAZ,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,BUBA,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-20.1128,-0.0691,-21.0076,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-20.7473,-0.0598,-21.6513,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-20.7473,-0.0598,-21.6513,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-20.7473,-0.0598,-21.6513,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-20.7473,-0.0598,-21.6513,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-20.7473,-0.0598,-21.6513,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-21.5015,-0.0544,-22.4110,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,-5.6365,-0.0347,-6.5656,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,-5.6365,-0.0347,-6.5656,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CLEC,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,15.3073,0.0173,14.3262,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,COWP,COWP_LA,7.8364,0.0215,6.8510,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,7.8364,0.0215,6.8510,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,7.8364,0.0215,6.8510,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CPLE,VACS,7.1300,0.0260,6.1401,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CPLW,VACS,7.1300,0.0260,6.1401,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,9.0946,0.0334,8.0974,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,9.0946,0.0334,8.0974,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,9.0946,0.0334,8.0974,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,9.0946,0.0334,8.0974,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CRTH_SPA,WRCRTH_SPA_LA,12.3676,0.0059,11.3979,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,16.2443,0.0793,15.2012,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-13.2935,-0.0496,-14.2077,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,18.0512,0.0209,17.0665,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,16.2214,0.0184,15.2392,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,16.2507,0.0788,15.2080,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,16.5456,0.0617,15.5200,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,16.3880,0.0720,15.3522,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,16.3880,0.0720,15.3522,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,15.6922,0.0243,14.7041,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,15.6922,0.0243,14.7041,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,15.6923,0.0243,14.7041,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,15.6923,0.0243,14.7041,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,18.0512,0.0209,17.0665,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,20.6927,0.0595,19.6694,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,36.1056,-0.0086,35.1504,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,36.0967,-0.0175,35.1504,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,19.2693,0.0062,18.2992,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,15.7512,0.0135,14.7739,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,15.7512,0.0135,14.7739,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,15.7527,0.0135,14.7754,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,15.7527,0.0135,14.7754,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-22.3348,-0.0579,-23.2407,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,-14.1721,-0.0466,-15.0894,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,30.0240,0.0119,29.0482,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-20.0112,-0.0546,-20.9205,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-20.0122,-0.0555,-20.9205,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-14.7333,-0.0423,-15.6549,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.GRID.CDL1,CDL1_DDR,24.0505,0.0177,23.0690,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-17.1888,-0.0511,-18.1016,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-12.5491,-0.0481,-13.4648,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,24.0505,0.0177,23.0690,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.NUEN.CSI1,CSI1_DDR,19.1055,0.0222,18.1195,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.NUEN.CSI2,CSI2_DDR,19.1058,0.0225,18.1195,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,15.3074,0.0174,14.3262,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.NUEN.GAZA,GAZA_DDR,24.0505,0.0177,23.0690,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,106.3865,0.0372,105.3855,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.NUEN.T201,NT201_DDR,16.5922,0.0150,15.6133,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-14.4592,-0.0648,-15.3582,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-14.4592,-0.0648,-15.3582,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,18.0512,0.0209,17.0665,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,17.0208,0.0874,15.9696,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-14.7333,-0.0423,-15.6549,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-14.7333,-0.0423,-15.6549,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-19.1001,-0.0574,-20.0065,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-20.0122,-0.0555,-20.9205,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,16.0846,0.0512,15.0695,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,13.0387,0.0082,12.0667,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,13.0387,0.0082,12.0667,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,13.0387,0.0082,12.0667,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,-6.6389,0.0000,-7.6027,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,-6.6389,0.0000,-7.6027,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,16.6740,0.0605,15.6497,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,16.7906,0.0137,15.8131,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,16.6411,0.0630,15.6143,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,17.0801,0.1058,16.0104,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,23.0860,0.0259,22.0963,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,19.1058,0.0225,18.1195,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0057,OKMU_DDR,20.1476,0.0222,19.1616,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0060,LEHIGH_DDR,106.3865,0.0372,105.3855,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0086,WARRENM_DDR,16.1460,0.0165,15.1656,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,17.3648,0.0819,16.3191,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,27.3837,0.0125,26.4074,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0121,V121_DDR,16.6740,0.0605,15.6497,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0122,V122_DDR,25.9121,0.0116,24.9367,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0124,V124_DDR,44.7788,0.0059,43.8091,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0135,V135_DDR,17.0700,0.0167,16.0895,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0144,V144_DDR,-14.6633,-0.0416,-15.5856,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0145,V145_DDR,-14.9653,-0.0457,-15.8834,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,16.6977,0.0615,15.6723,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,18.2773,0.0331,17.2804,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0175,V175_DDR,15.3074,0.0174,14.3262,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,18.2773,0.0331,17.2804,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,18.2571,0.0386,17.2547,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,17.0700,0.0167,16.0895,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,17.4226,0.0152,16.4436,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,17.0248,0.0131,16.0478,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,31.9802,0.0002,31.0162,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,15.7987,0.0129,14.8220,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,17.4226,0.0152,16.4436,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0211,V211_DDR,16.5614,0.0714,15.5262,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,28.1024,0.0114,27.1272,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0213,V213_DDR,16.9081,0.0158,15.9285,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0215,V215_DDR,26.9014,0.0116,25.9260,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0217,V217_DDR,28.1676,0.0108,27.1929,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0218,V218_DDR,31.5217,0.0011,30.5568,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0228,V228_DDR,17.3405,0.0126,16.3641,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0232,V232_DDR,16.4201,0.0166,15.4397,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0233,V233_DDR,17.5501,0.0160,16.5703,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0240,V240_DDR,23.2781,0.0107,22.3036,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0244,V244_DDR,17.4226,0.0152,16.4436,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0246,MDT1_DDR,106.3865,0.0372,105.3855,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0249,V249_DDR,16.8469,0.0162,15.8668,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0250,V250_DDR,-13.6893,-0.0469,-14.6063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0251,V251_DDR,16.2354,0.0146,15.2570,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.VOLT.0252,V252_DDR,31.9802,0.0002,31.0162,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-23.2826,-0.0588,-24.1877,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,-5.4958,-0.0658,-6.3938,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-21.7977,-0.0855,-22.6760,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,16.6040,0.0584,15.5817,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-30.7218,-0.1563,-31.5293,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-25.3091,-0.0617,-26.2113,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-25.3091,-0.0617,-26.2113,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-25.3091,-0.0617,-26.2113,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-25.3091,-0.0617,-26.2113,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-25.3091,-0.0617,-26.2113,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,18.0512,0.0209,17.0665,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,15.0350,0.0774,13.9937,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,16.4193,0.0157,15.4397,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,16.4178,0.0143,15.4397,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,23.8647,0.0238,22.8771,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,23.8647,0.0238,22.8771,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWWELSH1,CSWSWELSHUN1_RA,17.4515,0.0464,16.4412,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWWELSH3,CSWSWELSHUN3_RA,17.4515,0.0464,16.4412,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWWILKES1,CSWSWILKESUN1_RA,17.2986,0.0589,16.2758,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWWILKES2,CSWSWILKESUN2_RA,17.2986,0.0589,16.2758,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,CSWWILKES3,CSWSWILKESUN3_RA,17.0696,0.0559,16.0498,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-20.0112,-0.0546,-20.9205,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,DENL,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,DERS,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,DOE,DOE,5.0407,0.0176,4.0593,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,-6.3445,-0.0121,-7.2962,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,DPC,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,DUK,VACS,7.1300,0.0260,6.1401,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDDY,EDDY,26.3008,0.0840,25.2530,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,11.5588,-0.0021,10.5971,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-18.9900,-0.0200,-19.9338,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,17.2681,-0.0136,16.3178,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE.SLCC,EDESTL4391_PLT,14.0700,-0.0032,13.1093,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,13.8546,-0.0010,12.8917,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,4.7551,-0.0186,3.8098,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_EC_01,EDELAR3821UN1_RA,11.5588,-0.0021,10.5971,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_EC_02,EDELAR3821UN2_RA,11.5588,-0.0021,10.5971,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_EC_03,EDELAR3821UN3_RA,11.5588,-0.0021,10.5971,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_EC_04,EDELAR3821UN4_RA,11.5588,-0.0021,10.5971,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_EDE,EDE_LA,14.9598,0.0153,13.9806,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_ERW,EDEERWFUNG1_RA,-21.8464,-0.0581,-22.7522,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-14.9015,-0.0674,-15.7980,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,31.3600,0.0426,30.3536,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,31.3600,0.0426,30.3536,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,31.3600,0.0426,30.3536,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,31.3600,0.0426,30.3536,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,7.9273,0.0282,6.9353,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_RIV_10,EDERIV1671UN10_RA,14.2786,-0.0077,13.3224,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_RIV_11,EDERIV1671UN11_RA,14.2786,-0.0077,13.3224,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_RIV_12,EDERIV453UN12_PLT,14.2594,-0.0268,13.3224,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_SL_01,EDESTL4391UN1_RA,14.0700,-0.0032,13.1093,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,EDE_SWMP,EDE_SWMP_LA,9.3081,0.0218,8.3225,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EEI,EEI,5.0083,0.0174,4.0271,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EES,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-18.0297,-0.0587,-18.9348,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,ERCOTE,ERCOTE,17.4515,0.0464,16.4412,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,ERCOTN,ERCOTN,-14.4548,-0.0605,-15.3582,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,-7.8710,-0.0404,-8.7944,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,FMPP,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,FPC,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,FPL,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,FREM_50T,OPPDFREM_GUN1_RA,-5.7700,-0.0319,-6.7019,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,FREM_6,OPPDFREM_AUN6_RA,-5.7723,-0.0322,-6.7040,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,FREM_7,OPPDFREM_AUN7_RA,-5.7723,-0.0322,-6.7040,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,FREM_8,OPPDFREM_AUN8_RA,-5.7753,-0.0351,-6.7040,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,FREM_LOAD,FREM_LOAD_LA,-5.7728,-0.0326,-6.7040,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-23.4334,-0.0530,-24.3443,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,16.0846,0.0512,15.0695,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-21.8350,-0.0963,-22.7025,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-40.2148,-0.0875,-41.0911,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,15.3073,0.0173,14.3262,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,15.3073,0.0173,14.3262,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,15.3073,0.0173,14.3262,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,19.3935,0.0098,18.4199,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,19.3935,0.0098,18.4199,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,19.5271,0.0095,18.5537,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,19.5271,0.0095,18.5537,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-29.5800,-0.0763,-30.4675,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,30.8085,-0.0023,29.8470,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,30.8085,-0.0023,29.8470,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,30.8085,-0.0023,29.8470,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.VOLT.0130,V130_DDR,20.0596,0.0201,19.0756,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA.VOLT.0237,V237_DDR,20.3867,0.0139,19.4089,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDAHUB2,GRDAHUB2_H,4.6413,-0.0135,3.6910,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDAHUB3,GRDAHUB3_H,0.2981,-0.0216,-0.6441,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA_GRDA,GRDA_LA,20.1261,0.0133,19.1490,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA_HUB,GRDA_H,10.9499,-0.0028,9.9889,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRDA_HUBSA,GRDASA_H,10.5289,-0.0041,9.5691,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,GRE,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-14.5531,0.0621,-15.5790,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GSEC_SPS,SPS_GSEC_LA,13.9240,0.0090,12.9512,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GSPR2014HUB,GSPR2014HUB_H,3.8115,-0.0037,2.8513,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,GSPR2015HUB,GSPR2015HUB_H,3.4919,-0.0053,2.5334,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-12.7940,-0.0329,-13.7250,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,HARRISON,CSWSLEBROCKPLT1,16.5447,0.0468,15.5341,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,HAST_TNSK_HUB,HAST_TNSK_H,-6.9495,-0.0515,-7.8618,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,HQST,PJM,2.1139,0.0045,1.1455,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,HST,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,-6.1632,0.0032,-7.1302,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,-6.1632,0.0032,-7.1302,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,-6.1918,0.0025,-7.1581,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,-6.1918,0.0025,-7.1581,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,-6.1248,0.0032,-7.0918,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,-6.1248,0.0032,-7.0918,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,INDN_INDN,INDN_LA,-6.1656,0.0030,-7.1324,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-14.7699,-0.0724,-15.6614,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,ISNE,PJM,2.1139,0.0045,1.1455,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,JEA,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,-5.6461,-0.0313,-6.5787,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,-5.6461,-0.0313,-6.5787,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-9.5324,-0.0150,-10.4813,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KACYCT4,KACYNEARMANUNCT4_RA,-7.3421,-0.0018,-8.3041,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,40.6011,-0.0129,39.6501,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,-7.3421,-0.0018,-8.3041,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,-7.3242,-0.0010,-8.2870,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,-7.3285,-0.0009,-8.2914,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KACY_KACY,KACY_LA,-7.3223,-0.0009,-8.2852,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,-6.8253,-0.0061,-7.7830,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,-3.1462,0.0246,-4.1346,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-30.0300,-0.0330,-30.9608,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-50.3291,-0.0796,-51.2133,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.VOLT.0222,V222_DDR,-6.9814,-0.0122,-7.9330,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.VOLT.0223,V223_DDR,-6.9173,-0.0127,-7.8684,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.VOLT.0241,V241_DDR,-1.6730,0.0216,-2.6585,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.VOLT.0243,V243_DDR,8.1555,-0.0006,7.1923,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.VOLT.0247,V247_DDR,-6.4506,-0.0065,-7.4080,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.VOLT.0253,V253_DDR,-6.8044,-0.0058,-7.7624,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-14.6900,-0.0759,-15.5779,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,-8.5785,-0.0221,-9.5203,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,-8.5785,-0.0221,-9.5203,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,-8.5785,-0.0221,-9.5203,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,-8.5785,-0.0221,-9.5203,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,-6.8144,-0.0062,-7.7721,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,-6.8144,-0.0062,-7.7721,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHUB,KCPLHUB_H,-11.7759,-0.0430,-12.6968,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHUB17,KCPLHUB17_H,-12.5154,-0.0468,-13.4324,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHUB18,KCPLHUB18_H,-12.2372,-0.0469,-13.1541,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHUB19,KCPLHUB19_H,-12.4385,-0.0450,-13.3573,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHUB20,KCPLHUB20_H,-12.9023,-0.0481,-13.8180,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHUB21,KCPLHUB21_H,-12.9232,-0.0468,-13.8402,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHUB22,KCPLHUB22_H,-12.2656,-0.0466,-13.1828,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHUB23,KCPLHUB23_H,-12.8013,-0.0481,-13.7170,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLHUB24,KCPLHUB24_H,-13.2289,-0.0496,-14.1431,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,-7.8302,-0.0139,-8.7801,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,-7.8302,-0.0139,-8.7801,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,-7.0157,-0.0340,-7.9455,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,-7.0157,-0.0340,-7.9455,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,-6.8253,-0.0061,-7.7830,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,-6.8253,-0.0061,-7.7830,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,-6.9765,-0.0039,-7.9364,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,-6.9765,-0.0039,-7.9364,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,-6.9765,-0.0039,-7.9364,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,-6.9765,-0.0039,-7.9364,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,-6.9765,-0.0039,-7.9364,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,-6.9765,-0.0039,-7.9364,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,-6.9765,-0.0039,-7.9364,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,-6.9765,-0.0039,-7.9364,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,-13.9811,-0.0198,-14.9252,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,-6.6435,-0.0056,-7.6018,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KCPL_KCPL,KCPL_LA,-7.3579,-0.0073,-8.3145,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KENN,KENN_LA,7.7588,0.0269,6.7681,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KEP2_SECI,KEP2_SECI_LA,-21.0937,-0.0505,-22.0071,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KERR_1,GRDAKERR_HYDUN1_RA,19.9951,0.0127,19.0185,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KERR_2,GRDAKERR_HYDUN2_RA,19.8508,0.0133,18.8736,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KERR_3,GRDAKERR_HYDUN3_RA,19.8508,0.0133,18.8736,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KERR_4,GRDAKERR_HYDUN4_RA,19.9951,0.0127,19.0185,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,-8.5785,-0.0221,-9.5203,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,-8.5785,-0.0221,-9.5203,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,-8.3757,-0.0178,-9.3218,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,-8.3757,-0.0178,-9.3218,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,-10.4468,-0.0212,-11.3895,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,-11.6934,-0.0194,-12.6378,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,-11.6934,-0.0194,-12.6378,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-19.8060,-0.0575,-20.7123,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-19.8060,-0.0575,-20.7123,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-19.8060,-0.0575,-20.7123,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-16.3980,-0.0571,-17.3047,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-16.3980,-0.0571,-17.3047,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-19.8640,-0.0590,-20.7689,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-16.8245,-0.0533,-17.7350,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-14.6714,-0.0392,-15.5960,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,33.9902,-0.0120,33.0384,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,33.9902,-0.0120,33.0384,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-9.8304,-0.0288,-10.7654,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-9.8304,-0.0288,-10.7654,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-9.8304,-0.0288,-10.7654,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-17.3085,-0.0504,-18.2219,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-16.8618,-0.0913,-17.7343,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,-9.6371,-0.0408,-10.5601,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-9.0565,-0.0122,-10.0082,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,LAFA,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LAM345,LAM345,-20.1128,-0.0691,-21.0076,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,LEPA,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,-5.4512,-0.0375,-6.3775,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_LES,LES_LA,-5.4722,-0.0378,-6.3982,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,-5.4165,-0.0392,-6.3412,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,-5.5375,-0.0398,-6.4615,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,-5.5375,-0.0398,-6.4615,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,-5.5375,-0.0398,-6.4615,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,-5.4162,-0.0388,-6.3412,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,-5.4165,-0.0392,-6.3412,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_WAVERLY,LES_WAVERLY_H,-5.4666,-0.0389,-6.3915,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,-5.4630,-0.0364,-6.3904,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,-5.4630,-0.0364,-6.3904,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,LGEE,LGEE,3.5309,0.0109,2.5561,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MALDEN,MALDEN_LA,7.3511,0.0255,6.3617,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MCWEST,MCWEST,-1.8384,0.0043,-2.8065,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MDU,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-8.2017,-0.0136,-9.1519,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,-7.2268,-0.0253,-8.1654,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,-5.7397,0.0007,-6.7042,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MEAN_NPPD,NPPD_MEAN_LA,-8.0440,-0.0601,-8.9478,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MEC,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MHEB,MHEB,-2.1999,0.0001,-3.1638,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-13.5472,-0.0669,-14.4442,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-17.2383,-0.0651,-18.1371,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-13.5472,-0.0669,-14.4442,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-13.5472,-0.0669,-14.4442,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-17.2383,-0.0651,-18.1371,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-21.2360,-0.0567,-22.1431,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MISO,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-21.2732,-0.0416,-22.1955,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-21.2732,-0.0416,-22.1955,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-12.3517,-0.0458,-13.2698,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-20.3942,-0.0759,-21.2821,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-17.0160,-0.0669,-17.9129,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-20.7623,-0.0708,-21.6553,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-20.0283,-0.0634,-20.9287,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-20.8506,-0.0678,-21.7467,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-19.8681,-0.0614,-20.7706,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-19.8681,-0.0614,-20.7706,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-19.8681,-0.0614,-20.7706,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-19.8681,-0.0614,-20.7706,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-19.8681,-0.0614,-20.7706,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,-3.4707,-0.0075,-4.4270,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,4.1812,0.0145,3.2029,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,4.1812,0.0145,3.2029,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,1.5121,0.0058,0.5425,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,-1.4581,0.0257,-2.4476,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MOWR,AECI,8.1510,0.0095,7.1777,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,1.5289,0.0026,0.5624,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,4.3882,0.0152,3.4092,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-5.8762,-0.0530,-6.7870,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-5.9082,-0.0338,-6.8383,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-22.0128,-0.0780,-22.8987,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-5.8739,-0.0507,-6.7870,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,-6.3442,-0.0118,-7.2962,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,-6.3442,-0.0118,-7.2962,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,-6.3441,-0.0117,-7.2962,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,-6.3441,-0.0117,-7.2962,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,-6.9814,-0.0122,-7.9330,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,-6.9814,-0.0122,-7.9330,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,-6.9814,-0.0122,-7.9330,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,-6.9841,-0.0149,-7.9330,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,-6.9814,-0.0122,-7.9330,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,-6.9814,-0.0122,-7.9330,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,-6.9814,-0.0122,-7.9330,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,1.9409,0.0169,0.9601,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,-5.8361,-0.0114,-6.7885,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,-6.6282,-0.0143,-7.5778,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,-6.6282,-0.0143,-7.5778,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,-6.6282,-0.0143,-7.5778,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,-6.9933,-0.0055,-7.9517,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,-6.9933,-0.0055,-7.9517,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MPS_MPS,MPS_LA,-5.4076,-0.0026,-6.3689,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MSTNG,SPSMSTNGPLT1,25.9646,0.0507,24.9500,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MSTNG4,SPSMSTNGUN4_RA,25.9598,0.0459,24.9500,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MSTNG5,SPSMSTNGUN5_RA,25.9646,0.0507,24.9500,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,25.9646,0.0507,24.9500,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NBSO,PJM,2.1139,0.0045,1.1455,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,-5.8216,-0.0491,-6.7363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,-5.8217,-0.0492,-6.7363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-14.3870,-0.0621,-15.2887,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NHC1,VACS,7.1300,0.0260,6.1401,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,-5.6448,-0.0330,-6.5756,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,-5.6448,-0.0330,-6.5756,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,-5.6448,-0.0330,-6.5756,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-8.1122,-0.0660,-9.0100,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,-7.2545,-0.0785,-8.1399,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,-6.2508,-0.0524,-7.1622,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-8.2847,-0.0527,-9.1959,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,-7.2545,-0.0785,-8.1399,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.HUB.PY2018,NPPDPY18_H,-7.7888,-0.0533,-8.6993,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,-7.6948,-0.0533,-8.6054,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,-7.7519,-0.0529,-8.6628,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,-7.6751,-0.0525,-8.5865,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-9.4609,-0.0553,-10.3694,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-8.9799,-0.0452,-9.8985,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-8.9799,-0.0452,-9.8985,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-9.6936,-0.0585,-10.5989,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-9.4609,-0.0553,-10.3694,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,-3.6560,-0.0959,-4.5239,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,-7.7552,-0.0841,-8.6349,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-11.2992,-0.0441,-12.2189,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,-7.7552,-0.0841,-8.6349,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,-7.0499,-0.0807,-7.9331,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-8.1444,-0.0712,-9.0370,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,-5.9565,-0.0329,-6.8875,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,-7.2545,-0.0785,-8.1399,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-10.9188,-0.0462,-11.8364,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-8.9799,-0.0452,-9.8985,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-8.9799,-0.0452,-9.8985,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-8.5669,-0.0418,-9.4889,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-8.6070,-0.0416,-9.5292,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-8.6070,-0.0416,-9.5292,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,-8.1734,-0.0349,-9.1023,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-16.4446,-0.0361,-17.3723,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,-7.1705,-0.0659,-8.0685,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-8.0458,-0.0552,-8.9545,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-8.5129,-0.0324,-9.4443,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-9.1314,-0.0337,-10.0615,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.NELI.DDR,NELI_DDR,-9.0045,-0.0660,-9.9024,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.NPPM.1058,SH1058_DDR,-0.6879,-0.0394,-1.6124,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,-8.0700,-0.0400,-8.9938,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,-7.2545,-0.0785,-8.1399,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,-6.2508,-0.0524,-7.1622,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-9.4609,-0.0553,-10.3694,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.TECH.1,KEARNE_DDR,-7.8735,-0.0312,-8.8062,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,-5.8721,-0.0877,-6.7483,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,-5.8721,-0.0877,-6.7483,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-9.4657,-0.0626,-10.3670,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD.VOLT.0236,V236_DDR,-6.4757,-0.0319,-7.4076,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD2017HUB,NPPD2017HUB_H,-7.7773,-0.0532,-8.6880,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,-1.5108,-0.0562,-2.4184,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-8.1122,-0.0660,-9.0100,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,-7.6491,-0.0994,-8.5136,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,-7.6491,-0.0994,-8.5136,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,-6.3616,-0.0336,-7.2918,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,-6.4751,-0.0313,-7.4076,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-11.4984,-0.0544,-12.4078,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-8.4802,-0.0437,-9.4003,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,-0.7033,-0.0547,-1.6124,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,-0.7033,-0.0547,-1.6124,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,-0.7033,-0.0547,-1.6124,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,-6.9434,-0.0513,-7.8559,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,-5.9600,-0.0506,-6.8732,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,-7.0364,-0.0491,-7.9511,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-8.6400,-0.1110,-9.4928,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-7.9411,-0.1059,-8.7990,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-9.5158,-0.0513,-10.4284,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-9.6987,-0.0519,-10.6106,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,-6.4440,-0.0485,-7.3593,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,-6.4446,-0.0492,-7.3593,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,-6.4446,-0.0492,-7.3593,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,-6.4877,-0.0479,-7.4036,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,-3.6560,-0.0959,-4.5239,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,-6.5372,-0.0478,-7.4532,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,-5.8395,-0.0432,-6.7601,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,-6.9554,-0.0497,-7.8695,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,-6.9585,-0.0502,-7.8722,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,-6.9603,-0.0497,-7.8744,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,-6.9603,-0.0497,-7.8744,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,-6.9434,-0.0513,-7.8559,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,-6.9451,-0.0531,-7.8559,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,-7.2839,-0.0286,-8.2191,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,-6.8269,-0.0406,-7.7501,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-9.5317,-0.0485,-10.4471,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,-7.1138,-0.0996,-7.9780,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-11.5516,-0.0477,-12.4677,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,-0.6760,-0.0275,-1.6124,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-9.0045,-0.0660,-9.9024,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-9.3575,-0.0499,-10.2715,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-9.3575,-0.0499,-10.2715,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_NPPD,NPPD_LA,-5.8504,-0.0456,-6.7686,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,-5.8395,-0.0432,-6.7601,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,-5.8395,-0.0432,-6.7601,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,-7.8434,-0.0479,-8.7593,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-7.8275,-0.0674,-8.7239,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NSB,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NSP,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,NSSO,PJM,2.1139,0.0045,1.1455,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,NYIS,PJM,2.1139,0.0045,1.1455,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-21.4631,-0.0893,-22.3377,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-29.9021,-0.0799,-30.7860,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-36.5317,-0.0741,-37.4215,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-36.5317,-0.0741,-37.4215,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-24.0096,-0.0897,-24.8837,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-40.2148,-0.0875,-41.0911,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-98.2495,-0.0537,-99.1596,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-52.0024,-0.0809,-52.8853,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-31.0885,-0.0763,-31.9760,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-30.0000,-0.0811,-30.8827,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-18.5901,-0.0340,-19.5200,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-31.0885,-0.0763,-31.9760,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-23.2817,-0.0907,-24.1548,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-21.2360,-0.0567,-22.1431,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-20.5995,-0.0912,-21.4721,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,-21.9302,-0.0145,-22.8796,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-30.0000,-0.0811,-30.8827,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-25.9438,-0.0722,-26.8354,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-23.2800,-0.0806,-24.1632,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-20.7473,-0.0598,-21.6513,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-23.0000,-0.0152,-23.9486,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-21.2360,-0.0567,-22.1431,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-21.2360,-0.0567,-22.1431,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-30.0000,-0.0811,-30.8827,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-20.5471,-0.0468,-21.4641,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.NUEN.LAM1,LAM1_DDR,16.5765,0.0596,15.5531,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-18.5901,-0.0340,-19.5200,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-18.5901,-0.0340,-19.5200,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-21.0805,-0.0493,-21.9951,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-18.6879,-0.0369,-19.6149,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-18.6879,-0.0369,-19.6149,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-18.6879,-0.0369,-19.6149,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-18.7386,-0.0334,-19.6690,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-18.7386,-0.0334,-19.6690,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-18.6879,-0.0369,-19.6149,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-18.6879,-0.0369,-19.6149,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-30.0000,-0.0811,-30.8827,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,11.1744,0.0378,10.1727,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-23.2817,-0.0907,-24.1548,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-18.0326,-0.0333,-18.9632,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-25.9438,-0.0722,-26.8354,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,13.1750,0.0409,12.1703,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-22.2463,-0.0590,-23.1511,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-22.2463,-0.0590,-23.1511,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-22.2463,-0.0590,-23.1511,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-22.2463,-0.0590,-23.1511,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-38.5518,-0.1113,-39.4044,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-32.1031,-0.0744,-32.9925,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-29.9021,-0.0799,-30.7860,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-34.9633,-0.0718,-35.8553,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-34.9633,-0.0718,-35.8553,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-16.3658,-0.0170,-17.3127,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-21.4855,-0.0644,-22.3849,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-21.4855,-0.0644,-22.3849,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-21.4855,-0.0644,-22.3849,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0033,FOSTER_DDR,-17.9126,-0.0316,-18.8448,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,3.0046,0.0168,2.0239,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0035,TARBY_DDR,16.4126,0.0481,15.4007,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,3.0046,0.0168,2.0239,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,1.0185,0.0051,0.0496,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,1.0185,0.0051,0.0496,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-17.7054,-0.0203,-18.6489,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0040,TROSPER_DDR,-17.6698,-0.0309,-18.6028,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,-17.9049,-0.0311,-18.8376,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,14.1968,0.0472,13.1858,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0115,V115_DDR,-18.5499,-0.0336,-19.4801,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0116,V116_DDR,-17.2200,-0.0107,-18.1731,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0118,V118_DDR,-38.9589,-0.0064,-39.9164,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0125,V125_DDR,14.5309,0.0546,13.5125,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0126,V126_DDR,15.1297,0.0266,14.1393,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0129,V129_DDR,-17.1888,-0.0510,-18.1016,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,-17.9588,-0.0375,-18.8851,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0134,V134_DDR,16.3171,0.0345,15.3187,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0138,V138_DDR,14.3218,0.0226,13.3353,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,-18.1977,-0.0358,-19.1258,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0143,V143_DDR,6.3087,0.0091,5.3357,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0149,V149_DDR,-19.8515,-0.0521,-20.7633,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0150,V150_DDR,-19.6852,-0.0512,-20.5979,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0155,V155_DDR,13.6579,0.0183,12.6757,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0156,V156_DDR,-17.9588,-0.0375,-18.8851,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0166,V166_DDR,14.8449,0.0484,13.8326,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,-18.0562,-0.0349,-18.9851,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-19.6852,-0.0512,-20.5979,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0170,V170_DDR,-21.2335,-0.0489,-22.1485,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-19.2584,-0.0515,-20.1708,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0176,V176_DDR,-19.6852,-0.0512,-20.5979,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0177,V177_DDR,-27.7180,-0.0913,-28.5906,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,-18.0077,-0.0334,-18.9381,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-22.9034,-0.0696,-23.7977,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0195,V195_DDR,87.3395,0.0414,86.3342,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0197,V197_DDR,13.4147,0.0310,12.4198,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0198,V198_DDR,14.8449,0.0484,13.8326,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0208,V208_DDR,87.4824,0.0423,86.4763,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0209,V209_DDR,87.4824,0.0423,86.4763,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,14.1997,0.0216,13.2143,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0216,V216_DDR,-17.9636,-0.0312,-18.8962,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0219,V219_DDR,13.6579,0.0183,12.6757,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0220,V220_DDR,-19.6852,-0.0512,-20.5979,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0224,V224_DDR,-18.6019,-0.0350,-19.5307,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0225,V225_DDR,-18.6018,-0.0349,-19.5307,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0226,V226_DDR,-18.6019,-0.0350,-19.5307,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0227,V227_DDR,-18.6019,-0.0350,-19.5307,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0229,V229_DDR,-17.8964,-0.0177,-18.8426,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0231,V231_DDR,-19.9849,-0.0051,-20.9436,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0238,V238_DDR,-37.0984,-0.0876,-37.9746,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.VOLT.0242,V242_DDR,13.9324,0.0204,12.9482,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-32.2100,-0.1264,-33.0474,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-21.2360,-0.0567,-22.1431,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-29.8040,-0.0766,-30.6912,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-20.5986,-0.0904,-21.4721,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-32.2100,-0.1264,-33.0474,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-18.4148,-0.0999,-19.2788,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-57.1578,-0.0764,-58.0453,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEHL7,OKGEHL7_H,-15.0258,-0.0291,-15.9606,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEHL8,OKGEHSL1UN8_RA,-15.0258,-0.0291,-15.9606,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEHL910,OKGEHSL1PLT2,-15.0258,-0.0291,-15.9606,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-19.7759,-0.0949,-20.6448,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEMCC,OKGEMCCLAIPLT1,-18.7970,-0.0423,-19.7186,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,10.9004,0.0136,9.9230,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,10.9004,0.0136,9.9230,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,10.9004,0.0136,9.9230,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,-14.0720,-0.0397,-14.9961,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,-14.0720,-0.0397,-14.9961,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,-14.0720,-0.0397,-14.9961,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,-14.0720,-0.0397,-14.9961,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGESM1,OKGESEMINOLEUN1_RA,-19.3198,-0.0207,-20.2629,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGESM2,OKGESEMINOLEUN2_RA,-14.5004,-0.0230,-15.4412,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGESM3,OKGESEMINOLEUN3_RA,-14.5004,-0.0230,-15.4412,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGESO1,OKGESONR1UN1_RA,-60.0091,-0.0677,-60.9053,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGESO2,OKGESONR1UN2_RA,-34.9633,-0.0718,-35.8553,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-19.7835,-0.1025,-20.6448,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-24.4450,-0.1178,-25.2911,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGETINK5A,OKGETINK5UN1_RA,-17.2914,-0.0313,-18.2240,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGETINK5B,OKGETINK5UN2_RA,-17.2914,-0.0313,-18.2240,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-21.0085,-0.0844,-21.8879,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-29.9021,-0.0799,-30.7860,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,13.7865,0.0670,12.7557,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-21.2360,-0.0567,-22.1431,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE_OKGE,OKGE_LA,-11.4288,-0.0169,-12.3757,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-18.0326,-0.0333,-18.9632,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-21.0116,-0.0876,-21.8879,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMLP,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,18.6911,0.0098,17.7175,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,13.9525,0.0629,12.9257,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-20.2238,-0.0326,-21.1550,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-98.2438,-0.0480,-99.1596,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-24.1833,-0.0805,-25.0666,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-31.0885,-0.0763,-31.9760,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-29.5699,-0.1290,-30.4047,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-16.3689,-0.0608,-17.2720,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,146.9000,0.0007,145.9355,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-98.2451,-0.0494,-99.1596,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-98.2451,-0.0494,-99.1596,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_SPP,OMPA_SPP_LA,-25.9231,-0.0432,-26.8437,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-32.2100,-0.1264,-33.0474,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,15.4673,0.0080,14.4954,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,15.4673,0.0080,14.4954,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,15.4673,0.0080,14.4954,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,15.4673,0.0080,14.4954,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,ONT,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,-5.6893,-0.0339,-6.6192,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,-5.6893,-0.0339,-6.6192,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,-5.6893,-0.0339,-6.6192,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,-5.6893,-0.0339,-6.6192,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,-5.6893,-0.0339,-6.6192,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,-5.6893,-0.0339,-6.6192,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,-5.6893,-0.0339,-6.6192,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,-5.6893,-0.0339,-6.6192,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,-5.6893,-0.0339,-6.6192,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,-5.6498,-0.0323,-6.5813,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,-5.6448,-0.0330,-6.5756,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,-5.6481,-0.0265,-6.5854,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,-5.6417,-0.0306,-6.5749,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,-5.6417,-0.0306,-6.5749,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD_GLDN,OPPD_GLDN_LA,-5.6398,-0.0325,-6.5711,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,-5.6654,-0.0328,-6.5965,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,-3.6560,-0.0959,-4.5239,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,-6.2720,-0.0409,-7.1950,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,-5.6453,-0.0330,-6.5762,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD_OPPD,OPPD_LA,-5.6612,-0.0313,-6.5937,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,-5.6407,-0.0296,-6.5749,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,-5.6406,-0.0299,-6.5745,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OTP,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,OVEC,OVEC,2.9698,0.0085,1.9975,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PARAGOULD,PARAGOULD_LA,8.4331,0.0291,7.4401,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,19.8018,0.0054,18.8326,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,19.8018,0.0054,18.8326,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,19.8018,0.0054,18.8326,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,19.4328,0.0090,18.4600,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,19.4328,0.0090,18.4600,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,19.4328,0.0090,18.4600,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PIGGOTT,PIGGOTT_LA,7.6138,0.0264,6.6236,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PJM,PJM,2.1139,0.0045,1.1455,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PLUM,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,POPLARBLUFF,POPLARBLUFF_LA,6.8423,0.0226,5.8559,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,-1.9158,-0.0087,-2.8709,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,-1.9158,-0.0087,-2.8709,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,-1.7623,-0.0082,-2.7179,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,-1.7623,-0.0082,-2.7179,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,-1.4953,0.0531,-2.5122,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,-1.4953,0.0531,-2.5122,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,-1.8209,0.0036,-2.7884,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,-2.5635,-0.0297,-3.4976,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-21.5015,-0.0544,-22.4110,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,65.0803,0.0033,64.1132,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,-6.5806,-0.0060,-7.5384,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-20.0673,-0.0081,-21.0230,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,26.6431,0.0272,25.6520,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,15.8287,0.0277,14.8371,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,-4.2954,-0.0392,-5.2201,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,-1.5808,0.0070,-2.5517,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,-5.0390,-0.0545,-5.9484,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,11.0000,0.0487,9.9875,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,-1.5579,0.0095,-2.5313,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,-4.6596,-0.0346,-5.5889,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,PUPP,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,RCEAST,RCEAST,-4.9417,-0.0309,-5.8746,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SALINA_1,GRDASALINA1UN1_RA,19.9952,0.0129,19.0185,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SALINA_2,GRDASALINA1UN2_RA,19.9952,0.0129,19.0185,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SALINA_3,GRDASALINA1UN3_RA,19.9952,0.0129,19.0185,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SALINA_4,GRDASALINA1UN4_RA,19.9952,0.0129,19.0185,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SALINA_5,GRDASALINA1UN5_RA,19.9952,0.0129,19.0185,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SALINA_6,GRDASALINA1UN6_RA,19.9952,0.0129,19.0185,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SARPY_1,OPPDSARPYUN1_RA,-5.6513,-0.0327,-6.5824,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SARPY_2,OPPDSARPYUN2_RA,-5.6528,-0.0312,-6.5854,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SARPY_3,OPPDSARPYUN3_RA,-5.6338,-0.0340,-6.5636,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SARPY_4,OPPDSARPYUN4_RA,-5.6338,-0.0340,-6.5636,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SARPY_5,OPPDSARPYUN5_RA,-5.6338,-0.0340,-6.5636,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SC,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SCEG,VACS,7.1300,0.0260,6.1401,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SCSE,SCSE,-9.1366,-0.0401,-10.0604,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SEC,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-21.0753,-0.0866,-21.9525,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-21.0753,-0.0866,-21.9525,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-21.0753,-0.0866,-21.9525,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-20.1734,-0.0349,-21.1024,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-21.0753,-0.0866,-21.9525,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-20.2665,-0.0770,-21.1533,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-19.7023,-0.0831,-20.5830,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-19.7023,-0.0831,-20.5830,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-19.8682,-0.0615,-20.7706,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-21.8511,-0.0824,-22.7325,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-16.4015,-0.0607,-17.3047,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-20.6542,-0.0422,-21.5758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-15.9364,-0.0576,-16.8427,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-20.8396,-0.0855,-21.7179,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-15.8827,-0.0573,-16.7892,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-20.6634,-0.0820,-21.5452,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-20.3721,-0.0542,-21.2817,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-19.8677,-0.0614,-20.7701,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-19.8677,-0.0614,-20.7701,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-19.8677,-0.0614,-20.7701,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-19.8677,-0.0614,-20.7701,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-20.0317,-0.0662,-20.9294,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-20.2665,-0.0770,-21.1533,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI_SECI,SECI_LA,-19.6207,-0.0520,-20.5326,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-14.7699,-0.0724,-15.6614,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-14.7699,-0.0724,-15.6614,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-19.8682,-0.0615,-20.7706,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SEHA,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-21.0116,-0.0876,-21.8879,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SERU,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SETH,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SGE,SGE,-8.3733,-0.0357,-9.3015,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SMEP,MISO,2.9766,0.0074,2.0054,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SOCO,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPA,SPA,14.2015,0.0337,13.2039,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPC,SPC,-1.3903,0.0259,-2.3801,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPPNORTH_HUB,SPPNORTH_H,-5.6693,-0.0377,-6.5955,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-18.2454,-0.0502,-19.1590,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,10.2779,0.0258,9.2883,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,10.2779,0.0258,9.2883,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,9.8153,0.0249,8.8266,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,9.8153,0.0249,8.8266,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_NIXA,SPRM_NIXA_LA,10.7267,0.0271,9.7358,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_SPRM,SPRM_LA,10.2652,0.0283,9.2731,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,10.4562,0.0217,9.4707,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,10.4562,0.0217,9.4707,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,10.4543,0.0197,9.4707,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,10.4562,0.0217,9.4707,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,27.4255,0.0311,26.4306,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,29.8467,0.0026,28.8802,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-14.7277,-0.0374,-15.6542,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-14.7277,-0.0374,-15.6542,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,26.3103,-0.0296,25.3760,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,26.0442,0.0071,25.0733,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,27.7126,-0.0971,26.8459,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,26.3057,0.0951,25.2467,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,25.4987,0.0059,24.5289,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,26.0487,0.0532,25.0316,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,26.0612,0.0612,25.0361,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,26.0612,0.0612,25.0361,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,26.0487,0.0532,25.0316,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-14.6725,-0.0271,-15.6092,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,29.8467,0.0026,28.8802,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-14.7830,-0.0369,-15.7099,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-20.4711,-0.0835,-21.3514,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-16.9347,-0.0357,-17.8629,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-15.2976,-0.0198,-16.2416,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-15.5876,-0.0386,-16.5128,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-24.9776,-0.0872,-25.8542,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-24.9776,-0.0872,-25.8542,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-24.9776,-0.0872,-25.8542,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-24.9776,-0.0872,-25.8542,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GRID.WRAB,WRAB_DDR,-13.4111,-0.0189,-14.3561,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-24.9776,-0.0872,-25.8542,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,24.9655,0.0084,23.9933,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,24.9655,0.0084,23.9933,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,23.6193,0.0088,22.6466,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,23.6193,0.0088,22.6466,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,23.6193,0.0088,22.6466,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,24.9655,0.0084,23.9933,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-12.6196,-0.0350,-13.5484,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-12.6212,-0.0350,-13.5500,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-12.6153,-0.0349,-13.5442,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-14.3870,-0.0621,-15.2887,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,26.0396,0.0521,25.0236,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,25.4874,0.0050,24.5186,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,25.4874,0.0050,24.5186,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,25.4874,0.0050,24.5186,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,25.4874,0.0050,24.5186,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,26.0079,0.0494,24.9947,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,26.0427,0.0495,25.0293,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,26.0427,0.0495,25.0293,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-21.0069,-0.0829,-21.8879,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-13.0677,-0.0342,-13.9974,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-13.0677,-0.0342,-13.9974,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-12.6954,-0.0348,-13.6244,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-13.4111,-0.0189,-14.3561,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-19.9109,-0.0690,-20.8057,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-15.6682,-0.0403,-16.5918,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-24.0096,-0.0897,-24.8837,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-13.0535,-0.0199,-13.9974,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.PLANTX1,SPS.PLANTX1_H,28.4016,0.0253,27.4124,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.PLANTX2,SPS.PLANTX2_H,28.4016,0.0253,27.4124,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,28.1382,0.0241,27.1503,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,26.1320,-0.0128,25.1809,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-22.5156,-0.0804,-23.3991,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,27.7371,-0.0727,26.8459,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,26.1343,-0.0104,25.1809,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-14.6728,-0.0274,-15.6092,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,27.1452,0.0378,26.1436,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,26.3057,0.0951,25.2467,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,27.1452,0.0378,26.1436,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,26.3067,0.0949,25.2480,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-44.1249,-0.0440,-45.0448,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,26.1673,0.1168,25.0867,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,26.1711,0.1206,25.0867,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,26.1433,0.1121,25.0674,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,26.0542,0.0614,25.0290,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,26.2397,0.1078,25.1681,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-20.1128,-0.0691,-21.0076,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-13.3885,-0.0233,-14.3291,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,27.6945,0.0276,26.7031,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,27.6945,0.0276,26.7031,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,27.1452,0.0378,26.1436,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,25.5354,0.0103,24.5612,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,26.0014,0.0781,24.9595,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,27.9098,0.0700,26.8760,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,28.0166,0.0472,27.0056,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,28.5793,0.0043,27.6111,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,26.1673,0.1168,25.0867,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,26.2432,0.1366,25.1428,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,26.2300,0.1234,25.1428,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,26.1410,-0.0038,25.1809,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,27.8525,0.0460,26.8427,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-21.9665,-0.0768,-22.8536,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-21.9553,-0.0781,-22.8410,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0163,V163_DDR,-12.4582,-0.0252,-13.3969,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0168,V168_DDR,-18.1903,-0.0383,-19.1158,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0180,V180_DDR,26.2432,0.1366,25.1428,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0181,V181_DDR,-22.2707,-0.0684,-23.1661,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0182,V182_DDR,26.2402,0.1112,25.1652,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0199,V199_DDR,25.9971,0.0697,24.9636,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0200,V200_DDR,26.0970,0.0798,25.0534,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.VOLT.0235,V235_DDR,-19.9109,-0.0690,-20.8057,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,27.7126,-0.0971,26.8459,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,26.3057,0.0951,25.2467,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-12.7978,-0.0367,-13.7250,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-13.2093,-0.0282,-14.1449,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS_SPS,SPS_LA,16.3287,0.0578,15.3070,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,27.0041,0.0387,26.0015,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SSCN_NPPD,SSCN_NPPD_LA,-7.6634,-0.0489,-8.5784,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,6.1527,0.0213,5.1675,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,6.1527,0.0213,5.1675,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,TAL,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,TEC,SOUC,7.5281,0.0280,6.5363,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,-7.1138,-0.0996,-7.9780,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,TVA,TVA,6.7103,0.0240,5.7224,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,UCUHUB,UCUHUB_H,-9.8082,-0.0271,-10.7449,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,UCUHUB17,UCUHUB17_H,-13.1884,-0.0450,-14.1072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,UCUHUB18,UCUHUB18_H,-10.7041,-0.0403,-11.6277,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,UCUHUB19,UCUHUB19_H,-13.9646,-0.0442,-14.8842,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,UCUHUB20,UCUHUB20_H,-14.1463,-0.0421,-15.0680,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,UCUHUB21,UCUHUB21_H,-15.4413,-0.0472,-16.3579,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,UCUHUB22,UCUHUB22_H,-14.9943,-0.0500,-15.9081,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,UCUHUB23,UCUHUB23_H,-15.2494,-0.0505,-16.1628,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,UCUHUB24,UCUHUB24_H,-13.4216,-0.0442,-14.3413,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,-1.3814,0.0346,-2.3799,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,-1.3814,0.0346,-2.3799,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,-1.2714,-0.0245,-2.2107,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,-1.2714,-0.0245,-2.2107,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,-1.3990,-0.0271,-2.3357,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,-1.7482,-0.0162,-2.6958,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,-1.7482,-0.0162,-2.6958,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,-1.3814,0.0346,-2.3799,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,-1.4594,-0.0255,-2.3977,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,-1.3917,0.0088,-2.3644,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,-4.8983,-0.0512,-5.8110,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,-4.7309,-0.0919,-5.6028,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,-1.4741,0.0321,-2.4701,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,-1.4741,0.0321,-2.4701,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,7.1753,-0.1012,6.3127,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,-6.5801,-0.0429,-7.5010,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,5.2452,-0.0065,4.2879,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,-5.1828,-0.0542,-6.0924,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,-4.9383,-0.0434,-5.8588,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,-6.7741,-0.0475,-7.6905,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,7.2248,-0.0517,6.3127,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,7.2248,-0.0517,6.3127,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,-3.6111,-0.0377,-4.5373,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,-4.4747,-0.0906,-5.3479,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,-4.8943,-0.0303,-5.8278,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,4.8900,-0.0008,3.9270,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,4.8900,-0.0008,3.9270,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,4.8900,-0.0008,3.9270,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,-1.4056,0.0020,-2.3714,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,-1.4056,0.0020,-2.3714,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,-1.4056,0.0020,-2.3714,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,-1.3717,0.0477,-2.3833,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,-1.2606,-0.0238,-2.2007,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,-1.1809,-0.0252,-2.1195,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-8.7524,-0.0380,-9.6783,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,-6.2705,-0.0388,-7.1955,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,-1.5014,0.0083,-2.4735,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,-6.3966,-0.0528,-7.3076,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,-4.6329,-0.1042,-5.4925,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,7.0064,-0.0407,6.0832,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,-1.4147,0.0278,-2.4063,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,-1.4147,0.0278,-2.4063,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,-1.4148,0.0276,-2.4063,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,-1.4147,0.0278,-2.4063,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,-1.3901,0.0255,-2.3794,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,-1.3901,0.0255,-2.3794,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,-1.3901,0.0255,-2.3794,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,-1.3901,0.0255,-2.3794,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,-1.3901,0.0255,-2.3794,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,-1.3901,0.0255,-2.3794,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,-1.3901,0.0255,-2.3794,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,-5.8669,-0.0886,-6.7422,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,-1.4962,-0.0098,-2.4503,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,-5.9434,-0.0397,-6.8676,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,-5.9434,-0.0397,-6.8676,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,-6.8621,-0.0630,-7.7629,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,-6.8621,-0.0630,-7.7629,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,-1.2516,-0.0147,-2.2007,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,-1.6970,-0.0131,-2.6478,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,-5.0147,-0.0655,-5.9131,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,-4.1264,-0.0777,-5.0125,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,-4.0536,-0.0265,-4.9910,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,-1.3990,-0.0271,-2.3357,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,-1.3990,-0.0271,-2.3357,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,-5.1828,-0.0542,-6.0924,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,-4.9534,-0.0319,-5.8853,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,1.2744,-0.0454,0.3559,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,-4.4624,-0.0784,-5.3479,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,-10.0000,-0.0472,-10.9166,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.FSE,WAUE.FSE_H,-6.6505,-0.0584,-7.5559,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,-1.6668,0.0035,-2.6341,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,-1.6978,0.0031,-2.6647,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,-5.3685,-0.0978,-6.2346,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,-5.0981,-0.0917,-5.9702,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,-1.2921,-0.0250,-2.2309,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,-1.4212,-0.0288,-2.3562,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-19.0900,-0.0995,-19.9543,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,-4.7309,-0.0919,-5.6028,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-12.0000,-0.0269,-12.9369,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,-5.0663,-0.0480,-5.9822,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,-5.0614,-0.0431,-5.9822,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,-5.0614,-0.0430,-5.9822,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,-7.7934,-0.0405,-8.7167,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,-4.9534,-0.0319,-5.8853,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,-4.4002,-0.0265,-5.3375,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,-5.2092,-0.0566,-6.1165,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,-4.8933,-0.0294,-5.8278,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,-4.8471,-0.0020,-5.8089,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,-4.8559,-0.0396,-5.7801,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,-3.2227,-0.0189,-4.1676,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,-5.0340,-0.0509,-5.9469,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,-5.0628,-0.0592,-5.9675,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,-6.3966,-0.0528,-7.3076,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,-2.8763,0.0047,-3.8449,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,-5.1853,-0.0550,-6.0942,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,-2.9301,0.0002,-3.8942,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,-4.5824,-0.0291,-5.5171,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,-5.4630,-0.0364,-6.3904,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NTWK,WAUE.NTWK_H,-3.4532,-0.0278,-4.3892,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,-3.4022,0.0122,-4.3782,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,-3.4022,0.0122,-4.3782,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,-4.6850,-0.1033,-5.5455,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,-5.8244,-0.1162,-6.6720,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,-4.8700,-0.0359,-5.7979,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,-4.6850,-0.1033,-5.5455,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,-1.9454,-0.0086,-2.9006,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,-3.2080,-0.0493,-4.1226,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,-6.3966,-0.0528,-7.3076,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,-3.1955,-0.0242,-4.1351,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,-3.2699,-0.1111,-4.1226,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,-5.1644,-0.0705,-6.0577,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,-4.8719,-0.0685,-5.7673,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,-1.1730,-0.0261,-2.1108,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,-5.5466,-0.0944,-6.4160,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,-4.4090,-0.0236,-5.3492,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,-3.8818,-0.0644,-4.7812,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,-4.1264,-0.0777,-5.0125,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.VOLT.0152,V152_DDR,-1.3569,0.0589,-2.3797,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE.VOLT.0172,V172_DDR,-1.3925,0.0293,-2.3856,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_BEPM,WAUE_BEPM_LA,-1.7044,0.0059,-2.6742,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,-4.5439,-0.0337,-5.4741,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,-4.8500,-0.0016,-5.8122,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_EWA,WAUE_EWA_LA,-4.9162,-0.0284,-5.8517,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,-3.6777,-0.0534,-4.5881,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_HMMU,WAUE_HMMU_LA,-5.2370,-0.0162,-6.1846,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,-3.1585,-0.0221,-4.1003,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_MECB,WAUE_MECB_LA,-5.2235,-0.0124,-6.1749,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_MMPA,WAUE_MMPA_LA,-1.7845,0.0150,-2.7633,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_MRES,WAUE_MRES_LA,-4.8151,-0.0284,-5.7506,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,-1.3889,0.0400,-2.3928,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,-1.6668,0.0035,-2.6341,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,-4.5165,-0.0517,-5.4286,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_OTP,WAUE_OTP_LA,-1.4582,0.0327,-2.4548,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_OTPW,WAUE_OTPW_LA,-0.4000,0.0080,-1.3719,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM,WAUE_UGPM_LA,-3.2484,-0.0278,-4.1845,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,-1.8733,-0.0066,-2.8305,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,-4.9758,-0.0384,-5.9013,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,-3.5134,-0.0377,-4.4395,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,-4.9162,-0.0284,-5.8517,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,-5.2370,-0.0162,-6.1846,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,-2.8938,-0.0559,-3.8017,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,-1.6668,0.0035,-2.6341,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,-1.7845,0.0150,-2.7633,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,-4.1244,-0.0232,-5.0650,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,-4.5694,-0.0601,-5.4731,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,-1.5235,0.0397,-2.5270,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-32.0938,-0.1137,-32.9439,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-28.1420,-0.1053,-29.0005,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,-11.2477,-0.0504,-12.1612,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,106.3700,0.0207,105.3855,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,106.3700,0.0207,105.3855,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-18.3522,-0.1048,-19.2112,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,93.9640,0.0262,92.9739,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,79.6061,0.0252,78.6170,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,1.6377,-0.0575,0.7313,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,1.6377,-0.0575,0.7313,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,1.6377,-0.0575,0.7313,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,1.6377,-0.0575,0.7313,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,1.6356,-0.0596,0.7313,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,1.6377,-0.0575,0.7313,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,1.6377,-0.0575,0.7313,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,1.6377,-0.0575,0.7313,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,-4.3646,-0.0544,-5.2740,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-24.0096,-0.0897,-24.8837,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-27.2910,-0.0902,-28.1647,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-29.7470,-0.1471,-30.5638,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,27.7307,-0.0790,26.8459,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_ENMC,WFEC_ENMC_LA,26.5044,0.0658,25.4748,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-30.0000,-0.0811,-30.8827,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,27.0148,0.0183,26.0326,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,26.0107,0.0431,25.0038,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-32.0938,-0.1137,-32.9439,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-32.0938,-0.1137,-32.9439,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-32.0938,-0.1137,-32.9439,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_OKGE,WFEC_OKGE_LA,-20.0031,-0.0139,-20.9530,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,7.9317,0.0219,6.9460,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-22.5919,-0.0725,-23.4832,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-18.2422,-0.0814,-19.1246,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_WFEC,WFEC_LA,-0.1161,-0.0270,-1.0530,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,26.0107,0.0431,25.0038,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-14.2510,-0.0681,-15.1467,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-18.5766,-0.0646,-19.4758,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-13.7061,-0.0436,-14.6264,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-13.7061,-0.0436,-14.6264,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-13.7061,-0.0436,-14.6264,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-13.7061,-0.0436,-14.6264,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-13.7061,-0.0436,-14.6264,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-13.7061,-0.0436,-14.6264,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-13.7061,-0.0436,-14.6264,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,-5.7062,0.0137,-6.6837,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-14.5098,-0.0588,-15.4148,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-26.5202,-0.0768,-27.4072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-26.5202,-0.0768,-27.4072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-26.5202,-0.0768,-27.4072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-22.1242,-0.0833,-23.0048,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-22.1242,-0.0833,-23.0048,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-22.5203,-0.0716,-23.4125,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-22.5203,-0.0716,-23.4125,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-22.5203,-0.0716,-23.4125,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-14.5098,-0.0588,-15.4148,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,-8.3423,-0.0146,-9.2915,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-18.1099,-0.0595,-19.0142,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-18.1100,-0.0596,-19.0142,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-18.1100,-0.0596,-19.0142,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-18.1099,-0.0596,-19.0142,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,-8.3423,-0.0146,-9.2915,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-20.4737,-0.0837,-21.3538,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-41.7080,-0.0380,-42.6339,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.JEC.1,WRJEFFUN10_RA,-12.1793,-0.0379,-13.1052,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.JEC.2,WRJEFFUN11_RA,-12.0813,-0.0379,-13.0072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.JEC.3,WRJEFFUN12_RA,-12.0826,-0.0392,-13.0072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-29.5800,-0.0763,-30.4675,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-22.0120,-0.0772,-22.8987,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-22.0120,-0.0772,-22.8987,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.LEC.4,WRLECUN26_RA,-9.5636,-0.0186,-10.5088,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.LEC.5,WRLECUN27_RA,-10.0240,-0.0167,-10.9712,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-16.8851,-0.0553,-17.7936,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-16.8851,-0.0553,-17.7936,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-16.8851,-0.0553,-17.7936,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-16.8635,-0.0534,-17.7739,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-14.7699,-0.0724,-15.6614,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-14.7699,-0.0724,-15.6614,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-15.8961,-0.0505,-16.8094,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-13.9976,-0.0654,-14.8961,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-13.9976,-0.0654,-14.8961,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-16.8623,-0.0918,-17.7343,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-14.7699,-0.0724,-15.6614,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-9.4729,-0.0321,-10.4047,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-14.9015,-0.0674,-15.7980,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-22.0125,-0.0776,-22.8987,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,79.0700,0.0264,78.0797,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-16.8476,-0.1288,-17.6826,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-13.7061,-0.0436,-14.6264,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-15.1988,-0.0782,-16.0844,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,-8.3423,-0.0146,-9.2915,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-14.5098,-0.0588,-15.4148,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-24.0811,-0.0647,-24.9803,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.THAYERLD,WR.THAYERLD_LA,7.9076,0.0248,6.9190,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-24.9070,-0.0638,-25.8070,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0106,V106_DDR,-23.9530,-0.0626,-24.8543,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-8.2586,-0.0095,-9.2129,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-15.4541,-0.0536,-16.3643,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-9.4438,-0.0124,-10.3952,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-9.4438,-0.0124,-10.3952,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-8.6668,-0.0124,-9.6182,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-23.4363,-0.0540,-24.3461,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0157,V157_DDR,-9.4878,-0.0133,-10.4384,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0158,V158_DDR,-9.4438,-0.0124,-10.3952,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-9.4438,-0.0124,-10.3952,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-24.0119,-0.0666,-24.9091,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0173,V173_DDR,-16.8745,-0.0632,-17.7751,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0174,V174_DDR,-23.8021,-0.0619,-24.7040,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0184,V184_DDR,-23.3842,-0.0674,-24.2806,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-24.2077,-0.0640,-25.1076,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0186,V186_DDR,-24.1933,-0.0662,-25.0909,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-23.6190,-0.0660,-24.5169,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-24.7486,-0.0629,-25.6496,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-17.9812,-0.0483,-18.8967,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-14.6453,-0.0386,-15.5706,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-13.9698,-0.0408,-14.8929,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-13.9698,-0.0408,-14.8929,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-14.6453,-0.0386,-15.5706,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0245,V245_DDR,-24.2208,-0.0640,-25.1207,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.VOLT.0248,V248_DDR,-23.9530,-0.0626,-24.8543,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-26.5892,-0.0724,-27.4806,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-10.4387,-0.0209,-11.3816,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.WOLF,WRWOLFUN15_RA,-15.6549,-0.0830,-16.5357,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-20.4737,-0.0837,-21.3538,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,-5.7102,0.0097,-6.6837,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-26.5202,-0.0768,-27.4072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-26.5202,-0.0768,-27.4072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-26.5202,-0.0768,-27.4072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-26.5202,-0.0768,-27.4072,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-23.8079,-0.0521,-24.7197,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-15.3912,-0.0537,-16.3013,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-25.0080,-0.0643,-25.9075,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-25.0080,-0.0643,-25.9075,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-25.0080,-0.0643,-25.9075,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-25.0080,-0.0643,-25.9075,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-14.0967,-0.0357,-15.0249,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-14.0967,-0.0357,-15.0249,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-14.0967,-0.0357,-15.0249,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-14.0967,-0.0357,-15.0249,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-14.0967,-0.0357,-15.0249,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-14.0967,-0.0357,-15.0249,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-38.9364,-0.0636,-39.8366,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-38.9364,-0.0636,-39.8366,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-41.3451,-0.0652,-42.2437,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-41.3451,-0.0652,-42.2437,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_MIDW,WR_MIDW_LA,-16.0784,-0.0629,-16.9793,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,-2.2883,0.0138,-3.2659,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,-5.4678,-0.0045,-6.4271,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-17.2705,-0.0593,-18.1750,0.9638\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_SEG,WR_SEG_LA,-7.3971,0.0039,-8.3649,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,WR_WR,WR_LA,-15.9912,-0.0430,-16.9121,0.9639\n03/19/2025 03:00:00,03/19/2025 08:00:00,YAD,VACS,7.1300,0.0260,6.1401,0.9639\n03/19/2025 04:00:00,03/19/2025 09:00:00,AEC,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,AECC_CSWS,CSWS_AECC_LA,15.9412,0.0319,15.1104,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,15.6851,0.0209,14.8653,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,13.8423,0.0449,12.9985,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,15.9518,0.0135,15.1394,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,17.0228,0.0251,16.1988,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,14.2785,0.0162,13.4634,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,18.5941,0.0162,17.7790,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,AECI,AECI,8.0000,0.0056,7.1954,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,AEPM_CSWS,CSWS_LA,16.8522,0.0261,16.0272,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,ALTW,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,AMRN,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,23.0292,0.0194,22.2109,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BBA,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BCA,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BEPM.ER01.DDR,ER01_DDR,-4.9749,-0.0558,-5.7180,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BEPM_ER01,BEPM_ER01_LA,-4.9749,-0.0558,-5.7180,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,-6.7741,-0.0202,-7.5528,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-9.1727,-0.0082,-9.9634,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BEPM_UM01,BEPM_UM01_LA,-1.9597,0.0231,-2.7817,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BLKW,BLKW,25.5320,0.0412,24.6919,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-29.0442,-0.0781,-29.7650,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-29.0442,-0.0781,-29.7650,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,3.7370,-0.0695,3.0076,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.0434,-0.0773,-29.7650,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BRAZ,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BUBA,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-19.7197,-0.0508,-20.4678,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-20.0230,-0.0497,-20.7722,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-20.0230,-0.0497,-20.7722,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-20.0230,-0.0497,-20.7722,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-20.0230,-0.0497,-20.7722,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-20.0230,-0.0497,-20.7722,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-21.2356,-0.0469,-21.9877,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,-5.5067,-0.0318,-6.2738,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,-5.5067,-0.0318,-6.2738,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CLEC,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,15.2418,0.0129,14.4300,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,COWP,COWP_LA,8.1950,0.0157,7.3804,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,8.1950,0.0157,7.3804,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,8.1950,0.0157,7.3804,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CPLE,VACS,7.3676,0.0194,6.5494,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,CPLW,VACS,7.3676,0.0194,6.5494,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,9.3187,0.0255,8.4943,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,9.3187,0.0255,8.4943,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,9.3187,0.0255,8.4943,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,9.3187,0.0255,8.4943,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CRTH_SPA,WRCRTH_SPA_LA,12.1631,0.0056,11.3586,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,16.7185,0.0642,15.8554,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-11.4251,-0.0453,-12.1788,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,18.5941,0.0162,17.7790,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,15.9518,0.0135,15.1394,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,16.7258,0.0638,15.8631,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,17.0384,0.0499,16.1896,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,16.8696,0.0582,16.0125,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,16.8696,0.0582,16.0125,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,15.4103,0.0183,14.5931,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,15.4103,0.0183,14.5931,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,15.4103,0.0183,14.5931,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,15.4103,0.0183,14.5931,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,18.5941,0.0162,17.7790,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,21.1692,0.0484,20.3219,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,35.1030,-0.0090,34.3131,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,35.0957,-0.0163,34.3131,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,18.8737,0.0034,18.0714,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,15.2607,0.0095,14.4523,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,15.2607,0.0095,14.4523,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,15.2622,0.0095,14.4538,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,15.2622,0.0095,14.4538,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-22.7799,-0.0548,-23.5240,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,-10.9999,-0.0414,-11.7574,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,29.1704,0.0084,28.3631,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-19.7146,-0.0600,-20.4535,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-19.7118,-0.0572,-20.4535,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-14.5179,-0.0383,-15.2785,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.GRID.CDL1,CDL1_DDR,23.1130,0.0130,22.3010,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-14.8952,-0.0441,-15.6500,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-10.1016,-0.0485,-10.8520,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,23.1130,0.0130,22.3010,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.NUEN.CSI1,CSI1_DDR,18.6996,0.0167,17.8840,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.NUEN.CSI2,CSI2_DDR,18.6998,0.0169,17.8840,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,15.2420,0.0131,14.4300,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.NUEN.GAZA,GAZA_DDR,23.1130,0.0130,22.3010,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,99.5537,0.0291,98.7257,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.NUEN.T201,NT201_DDR,16.1737,0.0107,15.3641,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-13.2092,-0.0573,-13.9508,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-13.2092,-0.0573,-13.9508,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,18.5941,0.0162,17.7790,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,17.5202,0.0699,16.6514,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-14.5179,-0.0383,-15.2785,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-14.5179,-0.0383,-15.2785,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-18.9051,-0.0512,-19.6528,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-19.7118,-0.0572,-20.4535,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,16.5619,0.0413,15.7217,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,12.6923,0.0051,11.8883,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,12.6923,0.0051,11.8883,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,12.6923,0.0051,11.8883,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,-4.8336,-0.0015,-5.6310,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,-4.8336,-0.0015,-5.6310,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,17.1720,0.0489,16.3242,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,16.0736,0.0097,15.2650,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,17.1372,0.0508,16.2875,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,17.5814,0.0863,16.6962,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,23.6341,0.0198,22.8154,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,18.6998,0.0169,17.8840,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0057,OKMU_DDR,19.3105,0.0167,18.4949,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0060,LEHIGH_DDR,99.5537,0.0291,98.7257,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0086,WARRENM_DDR,15.6489,0.0120,14.8380,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,17.8790,0.0666,17.0135,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,26.5795,0.0084,25.7722,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0121,V121_DDR,17.1720,0.0489,16.3242,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0122,V122_DDR,25.1805,0.0078,24.3738,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0124,V124_DDR,43.2148,0.0030,42.4129,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0135,V135_DDR,16.5530,0.0121,15.7420,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0144,V144_DDR,-11.2834,-0.0372,-12.0451,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0145,V145_DDR,-11.4603,-0.0407,-12.2185,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,17.1968,0.0497,16.3482,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,18.8237,0.0261,17.9987,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0175,V175_DDR,15.2420,0.0131,14.4300,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,18.8237,0.0261,17.9987,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,18.7986,0.0306,17.9691,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,16.5530,0.0121,15.7420,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,16.9180,0.0108,16.1083,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,16.5616,0.0092,15.7535,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,31.0671,-0.0017,30.2699,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,15.2865,0.0089,14.4787,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,16.9180,0.0108,16.1083,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0211,V211_DDR,17.0527,0.0578,16.1960,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,27.2841,0.0076,26.4776,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0213,V213_DDR,16.3992,0.0114,15.5889,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0215,V215_DDR,26.1288,0.0077,25.3221,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0217,V217_DDR,27.3474,0.0071,26.5414,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0218,V218_DDR,30.6184,-0.0010,29.8205,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0228,V228_DDR,16.5656,0.0088,15.7579,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0232,V232_DDR,15.9043,0.0122,15.0932,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0233,V233_DDR,17.0320,0.0115,16.2215,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0240,V240_DDR,22.3921,0.0071,21.5861,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0244,V244_DDR,16.9180,0.0108,16.1083,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0246,MDT1_DDR,99.5537,0.0291,98.7257,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0249,V249_DDR,16.3389,0.0117,15.5283,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0250,V250_DDR,-11.8597,-0.0435,-12.6151,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0251,V251_DDR,15.7373,0.0104,14.9280,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.VOLT.0252,V252_DDR,31.0671,-0.0017,30.2699,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-24.4427,-0.0523,-25.1893,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,-0.1887,-0.0599,-0.9277,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-21.4029,-0.0812,-22.1206,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,17.1001,0.0472,16.2540,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-29.3165,-0.1296,-29.9858,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-26.3835,-0.0546,-27.1278,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-26.3835,-0.0546,-27.1278,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-26.3835,-0.0546,-27.1278,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-26.3835,-0.0546,-27.1278,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-26.3835,-0.0546,-27.1278,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,18.5941,0.0162,17.7790,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,15.5137,0.0624,14.6523,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,15.9035,0.0114,15.0932,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,15.9023,0.0102,15.0932,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,22.7356,0.0178,21.9188,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,22.7356,0.0178,21.9188,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWWELSH1,CSWSWELSHUN1_RA,17.9875,0.0371,17.1515,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWWELSH3,CSWSWELSHUN3_RA,17.9875,0.0371,17.1515,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWWILKES1,CSWSWILKESUN1_RA,17.8161,0.0475,16.9697,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWWILKES2,CSWSWILKESUN2_RA,17.8161,0.0475,16.9697,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,CSWWILKES3,CSWSWILKESUN3_RA,17.5827,0.0449,16.7389,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-19.7112,-0.0566,-20.4535,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,DENL,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,DERS,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,DOE,DOE,5.2620,0.0123,4.4508,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,-6.5501,-0.0132,-7.3358,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,DPC,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,DUK,VACS,7.3676,0.0194,6.5494,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDDY,EDDY,24.2260,0.0827,23.3444,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,11.1966,0.0019,10.3958,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-18.9900,-0.0188,-19.7701,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,17.3873,-0.0100,16.5984,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE.SLCC,EDESTL4391_PLT,13.8817,-0.0028,13.0856,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,13.6231,-0.0008,12.8250,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,4.6578,-0.0157,3.8746,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_EC_01,EDELAR3821UN1_RA,11.1966,0.0019,10.3958,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_EC_02,EDELAR3821UN2_RA,11.1966,0.0019,10.3958,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_EC_03,EDELAR3821UN3_RA,11.1966,0.0019,10.3958,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_EC_04,EDELAR3821UN4_RA,11.1966,0.0019,10.3958,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_EDE,EDE_LA,14.8893,0.0121,14.0782,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_ERW,EDEERWFUNG1_RA,-21.5441,-0.0499,-22.2931,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-14.7655,-0.0597,-15.5047,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,31.3800,0.0336,30.5475,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,31.3800,0.0336,30.5475,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,31.3800,0.0336,30.5475,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,31.3800,0.0336,30.5475,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,8.1579,0.0212,7.3378,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_RIV_10,EDERIV1671UN10_RA,14.1464,-0.0069,13.3544,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_RIV_11,EDERIV1671UN11_RA,14.1464,-0.0069,13.3544,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_RIV_12,EDERIV453UN12_PLT,14.1299,-0.0234,13.3544,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_SL_01,EDESTL4391UN1_RA,13.8817,-0.0028,13.0856,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EDE_SWMP,EDE_SWMP_LA,8.5272,0.0185,7.7098,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EEI,EEI,5.2296,0.0122,4.4185,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EES,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-17.7751,-0.0505,-18.5235,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,ERCOTE,ERCOTE,17.9875,0.0371,17.1515,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,ERCOTN,ERCOTN,-13.2056,-0.0537,-13.9508,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,-7.9165,-0.0434,-8.6720,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FMPP,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FPC,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FPL,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FREM_50T,OPPDFREM_GUN1_RA,-5.5659,-0.0295,-6.3353,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FREM_6,OPPDFREM_AUN6_RA,-5.5668,-0.0298,-6.3359,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FREM_7,OPPDFREM_AUN7_RA,-5.5668,-0.0298,-6.3359,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FREM_8,OPPDFREM_AUN8_RA,-5.5693,-0.0323,-6.3359,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FREM_LOAD,FREM_LOAD_LA,-5.5672,-0.0302,-6.3359,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-22.9769,-0.0454,-23.7304,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,16.5619,0.0413,15.7217,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-20.9563,-0.0681,-21.6871,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-38.4260,-0.0742,-39.1507,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,15.2418,0.0129,14.4300,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,15.2418,0.0129,14.4300,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,15.2418,0.0129,14.4300,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,19.0066,0.0063,18.2014,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,19.0066,0.0063,18.2014,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,19.1330,0.0060,18.3281,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,19.1330,0.0060,18.3281,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-28.7059,-0.0646,-29.4402,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,25.0000,-0.0037,24.2048,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,25.0000,-0.0037,24.2048,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,25.0000,-0.0037,24.2048,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.VOLT.0130,V130_DDR,19.6126,0.0149,18.7988,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA.VOLT.0237,V237_DDR,19.9358,0.0097,19.1272,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDAHUB2,GRDAHUB2_H,4.7587,-0.0126,3.9723,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDAHUB3,GRDAHUB3_H,0.5380,-0.0193,-0.2416,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA_GRDA,GRDA_LA,19.3095,0.0093,18.5013,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA_HUB,GRDA_H,10.8648,-0.0038,10.0698,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRDA_HUBSA,GRDASA_H,10.4499,-0.0047,9.6557,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GRE,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-12.7337,0.0529,-13.5855,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GSEC_SPS,SPS_GSEC_LA,12.6905,0.0193,11.8722,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,GSPR2014HUB,GSPR2014HUB_H,3.5568,0.0081,2.7498,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,GSPR2015HUB,GSPR2015HUB_H,3.2907,0.0064,2.4853,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-11.0104,-0.0114,-11.7979,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,HARRISON,CSWSLEBROCKPLT1,17.0414,0.0375,16.2050,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,HAST_TNSK_HUB,HAST_TNSK_H,-7.2240,-0.0443,-7.9786,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,HQST,PJM,2.3457,0.0013,1.5455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,HST,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,-6.3071,-0.0008,-7.1052,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,-6.3071,-0.0008,-7.1052,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,-6.3370,-0.0014,-7.1345,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,-6.3370,-0.0014,-7.1345,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,-6.2675,-0.0008,-7.0656,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,-6.2675,-0.0008,-7.0656,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,INDN_INDN,INDN_LA,-6.3113,-0.0010,-7.1092,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-14.6425,-0.0612,-15.3803,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,ISNE,PJM,2.3457,0.0013,1.5455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,JEA,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,-5.4948,-0.0290,-6.2647,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,-5.4948,-0.0290,-6.2647,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-9.6335,-0.0163,-10.4162,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,KACYCT4,KACYNEARMANUNCT4_RA,-7.5071,-0.0051,-8.3009,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,41.9618,-0.0096,41.1725,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,-7.5071,-0.0051,-8.3009,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,-7.4902,-0.0044,-8.2847,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,-7.4941,-0.0044,-8.2886,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KACY_KACY,KACY_LA,-7.4888,-0.0044,-8.2833,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,-6.9807,-0.0085,-7.7711,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,-3.2031,0.0174,-4.0194,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-31.6075,-0.0298,-32.3766,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-48.9441,-0.0690,-49.6740,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.VOLT.0222,V222_DDR,-7.0623,-0.0138,-7.8474,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.VOLT.0223,V223_DDR,-7.1489,-0.0137,-7.9341,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.VOLT.0241,V241_DDR,-1.6924,0.0152,-2.5065,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.VOLT.0243,V243_DDR,8.4423,-0.0023,7.6457,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.VOLT.0247,V247_DDR,-6.6435,-0.0086,-7.4338,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.VOLT.0253,V253_DDR,-6.9590,-0.0083,-7.7496,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-14.7100,-0.0649,-15.4440,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,-8.8521,-0.0213,-9.6297,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,-8.8521,-0.0213,-9.6297,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,-8.8521,-0.0213,-9.6297,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,-8.8521,-0.0213,-9.6297,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,-6.9698,-0.0087,-7.7600,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,-6.9698,-0.0087,-7.7600,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHUB,KCPLHUB_H,-11.8724,-0.0380,-12.6334,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHUB17,KCPLHUB17_H,-12.5649,-0.0409,-13.3229,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHUB18,KCPLHUB18_H,-12.2903,-0.0412,-13.0480,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHUB19,KCPLHUB19_H,-12.4929,-0.0396,-13.2522,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHUB20,KCPLHUB20_H,-12.9648,-0.0420,-13.7216,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHUB21,KCPLHUB21_H,-12.9834,-0.0407,-13.7416,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHUB22,KCPLHUB22_H,-12.3545,-0.0407,-13.1127,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHUB23,KCPLHUB23_H,-12.8634,-0.0419,-13.6204,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLHUB24,KCPLHUB24_H,-13.2765,-0.0432,-14.0322,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,-7.9304,-0.0151,-8.7142,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,-7.9304,-0.0151,-8.7142,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,-7.4863,-0.0309,-8.2543,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,-7.4863,-0.0309,-8.2543,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,-6.9807,-0.0085,-7.7711,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,-6.9807,-0.0085,-7.7711,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,-7.1368,-0.0068,-7.9289,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,-7.1368,-0.0068,-7.9289,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,-7.1368,-0.0068,-7.9289,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,-7.1368,-0.0068,-7.9289,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,-7.1368,-0.0068,-7.9289,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,-7.1368,-0.0068,-7.9289,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,-7.1368,-0.0068,-7.9289,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,-7.1368,-0.0068,-7.9289,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,-14.6133,-0.0193,-15.3929,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,-6.8119,-0.0079,-7.6029,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KCPL_KCPL,KCPL_LA,-7.5601,-0.0094,-8.3496,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KENN,KENN_LA,8.0057,0.0201,7.1867,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KEP2_SECI,KEP2_SECI_LA,-20.6600,-0.0381,-21.4207,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,KERR_1,GRDAKERR_HYDUN1_RA,19.5617,0.0088,18.7540,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KERR_2,GRDAKERR_HYDUN2_RA,19.4218,0.0092,18.6137,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KERR_3,GRDAKERR_HYDUN3_RA,19.4218,0.0092,18.6137,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KERR_4,GRDAKERR_HYDUN4_RA,19.5617,0.0088,18.7540,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,-8.8521,-0.0213,-9.6297,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,-8.8521,-0.0213,-9.6297,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,-8.6349,-0.0179,-9.4159,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,-8.6349,-0.0179,-9.4159,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,-10.7500,-0.0204,-11.5285,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,-12.1741,-0.0191,-12.9539,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,-12.1741,-0.0191,-12.9539,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-19.4287,-0.0407,-20.1869,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-19.4287,-0.0407,-20.1869,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-19.4287,-0.0407,-20.1869,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-16.1930,-0.0481,-16.9438,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-16.1930,-0.0481,-16.9438,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-19.4850,-0.0420,-20.2419,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-16.5963,-0.0441,-17.3511,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-14.5525,-0.0363,-15.3151,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,35.1333,-0.0091,34.3435,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,35.1333,-0.0091,34.3435,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-9.8792,-0.0311,-10.6470,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-9.8792,-0.0311,-10.6470,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-9.8792,-0.0311,-10.6470,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-17.0596,-0.0407,-17.8178,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-16.6374,-0.0774,-17.3589,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,-9.3732,-0.0384,-10.1337,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-9.1734,-0.0139,-9.9584,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LAFA,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LAM345,LAM345,-19.7197,-0.0508,-20.4678,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LEPA,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,-5.6983,-0.0339,-6.4633,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_LES,LES_LA,-5.7030,-0.0342,-6.4676,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,-5.6057,-0.0354,-6.3692,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,-5.7733,-0.0359,-6.5363,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,-5.7733,-0.0359,-6.5363,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,-5.7733,-0.0359,-6.5363,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,-5.6054,-0.0351,-6.3692,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,-5.6057,-0.0354,-6.3692,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_WAVERLY,LES_WAVERLY_H,-5.6433,-0.0352,-6.4070,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,-5.3113,-0.0333,-6.0769,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,-5.3113,-0.0333,-6.0769,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,LGEE,LGEE,3.7578,0.0067,2.9522,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MALDEN,MALDEN_LA,7.5937,0.0189,6.7759,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MCWEST,MCWEST,-2.3237,-0.0001,-3.1225,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MDU,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-8.3076,-0.0099,-9.0966,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,-15.0000,-0.0285,-15.7704,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,-5.6986,-0.0024,-6.4951,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MEAN_NPPD,NPPD_MEAN_LA,-8.1556,-0.0495,-8.9050,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MEC,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MHEB,MHEB,-2.2774,-0.0023,-3.0740,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-13.4722,-0.0546,-14.2165,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-16.9882,-0.0504,-17.7367,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-13.4722,-0.0546,-14.2165,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-13.4722,-0.0546,-14.2165,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-16.9882,-0.0504,-17.7367,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-21.0887,-0.0486,-21.8390,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MISO,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-20.8277,-0.0257,-21.6009,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-20.8277,-0.0257,-21.6009,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-12.3176,-0.0517,-13.0649,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-19.9964,-0.0657,-20.7296,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-16.7793,-0.0548,-17.5234,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-20.3951,-0.1086,-21.0854,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-19.6618,-0.0732,-20.3875,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-20.4749,-0.1017,-21.1721,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-19.4994,-0.0524,-20.2459,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-19.4994,-0.0524,-20.2459,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-19.4994,-0.0524,-20.2459,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-19.4994,-0.0524,-20.2459,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-19.4994,-0.0524,-20.2459,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,-3.4557,-0.0091,-4.2455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,4.3909,0.0097,3.5823,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,4.3909,0.0097,3.5823,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,1.6956,0.0024,0.8943,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,-1.4395,0.0185,-2.2569,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MOWR,AECI,8.0000,0.0056,7.1954,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,1.4654,-0.0003,0.6668,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,4.5921,0.0102,3.7830,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-5.9278,-0.0488,-6.6779,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-5.9976,-0.0318,-6.7647,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-21.5635,-0.0651,-22.2973,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-5.9257,-0.0467,-6.6779,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,-6.5499,-0.0130,-7.3358,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,-6.5499,-0.0130,-7.3358,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,-6.5498,-0.0129,-7.3358,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,-6.5498,-0.0129,-7.3358,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,-7.0623,-0.0138,-7.8474,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,-7.0623,-0.0138,-7.8474,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,-7.0623,-0.0138,-7.8474,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,-7.0645,-0.0160,-7.8474,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,-7.0623,-0.0138,-7.8474,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,-7.0623,-0.0138,-7.8474,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,-7.0623,-0.0138,-7.8474,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,1.8903,0.0118,1.0796,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,-6.0256,-0.0127,-6.8118,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,-6.8646,-0.0149,-7.6486,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,-6.8646,-0.0149,-7.6486,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,-6.8646,-0.0149,-7.6486,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,-7.1307,-0.0082,-7.9214,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,-7.1307,-0.0082,-7.9214,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MPS_MPS,MPS_LA,-5.5239,-0.0054,-6.3175,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,MSTNG,SPSMSTNGPLT1,23.9255,0.0546,23.0720,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MSTNG4,SPSMSTNGUN4_RA,23.9214,0.0505,23.0720,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MSTNG5,SPSMSTNGUN5_RA,23.9255,0.0546,23.0720,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,23.9255,0.0546,23.0720,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NBSO,PJM,2.3457,0.0013,1.5455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,-5.8375,-0.0444,-6.5920,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,-5.8375,-0.0444,-6.5920,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-12.9007,-0.0407,-13.6589,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NHC1,VACS,7.3676,0.0194,6.5494,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,-5.4818,-0.0304,-6.2503,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,-5.4818,-0.0304,-6.2503,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,-5.4818,-0.0304,-6.2503,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-7.7281,-0.0521,-8.4749,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,-7.4750,-0.0659,-8.2080,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,-6.4531,-0.0456,-7.2064,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-7.0981,-0.0460,-7.8511,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,-7.4750,-0.0659,-8.2080,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.HUB.PY2018,NPPDPY18_H,-7.8398,-0.0454,-8.5933,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,-7.7455,-0.0455,-8.4989,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,-7.8071,-0.0452,-8.5608,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,-7.7317,-0.0450,-8.4856,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-8.0300,-0.0479,-8.7810,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-9.1154,-0.0360,-9.8783,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-9.1154,-0.0360,-9.8783,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-9.8000,-0.0486,-10.5503,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-8.0300,-0.0479,-8.7810,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,-4.2847,-0.0773,-5.0063,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,-7.9185,-0.0677,-8.6497,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-11.3189,-0.0331,-12.0847,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,-7.9185,-0.0677,-8.6497,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,-7.2247,-0.0652,-7.9584,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-8.2763,-0.0571,-9.0181,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,-6.1806,-0.0304,-6.9491,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,-7.4750,-0.0659,-8.2080,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-10.9546,-0.0353,-11.7182,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-9.1154,-0.0360,-9.8783,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-9.1154,-0.0360,-9.8783,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-8.7400,-0.0338,-9.5051,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-8.7769,-0.0336,-9.5422,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-8.7769,-0.0336,-9.5422,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,-8.3648,-0.0290,-9.1347,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-15.8982,-0.0326,-16.6645,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,-7.3926,-0.0560,-8.1355,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-7.6326,-0.0430,-8.3885,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-7.3030,-0.0295,-8.0724,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-7.7324,-0.0304,-8.5009,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.NELI.DDR,NELI_DDR,-7.8318,-0.0565,-8.5742,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.NPPM.1058,SH1058_DDR,-2.4347,-0.0335,-3.2001,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,-8.2741,-0.0336,-9.0394,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,-7.4750,-0.0659,-8.2080,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,-6.4531,-0.0456,-7.2064,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-8.0300,-0.0479,-8.7810,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.TECH.1,KEARNE_DDR,-8.0982,-0.0262,-8.8709,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,-6.1169,-0.0751,-6.8407,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,-6.1169,-0.0751,-6.8407,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-8.0898,-0.0538,-8.8349,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD.VOLT.0236,V236_DDR,-6.6594,-0.0328,-7.4255,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD2017HUB,NPPD2017HUB_H,-7.8294,-0.0453,-8.5830,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,-2.9838,-0.0481,-3.7346,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-7.7281,-0.0521,-8.4749,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,-7.8111,-0.0799,-8.5301,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,-7.8111,-0.0799,-8.5301,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,-6.5505,-0.0336,-7.3158,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,-6.6589,-0.0323,-7.4255,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-10.4332,-0.0474,-11.1847,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-8.6595,-0.0356,-9.4228,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,-2.4479,-0.0467,-3.2001,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,-2.4479,-0.0467,-3.2001,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,-2.4479,-0.0467,-3.2001,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,-7.2166,-0.0441,-7.9714,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,-5.9945,-0.0455,-6.7479,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,-7.2600,-0.0431,-8.0159,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-8.0300,-0.0936,-8.7353,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-6.9240,-0.0894,-7.6335,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-9.6179,-0.0411,-10.3757,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-9.7952,-0.0417,-10.5524,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,-6.8055,-0.0415,-7.5629,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,-6.8061,-0.0421,-7.5629,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,-6.8061,-0.0421,-7.5629,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,-6.8434,-0.0410,-7.6012,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,-4.2847,-0.0773,-5.0063,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,-6.8872,-0.0410,-7.6451,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,-6.0492,-0.0389,-6.8092,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,-7.2316,-0.0427,-7.9878,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,-7.2354,-0.0431,-7.9913,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,-7.2377,-0.0427,-7.9939,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,-7.2377,-0.0427,-7.9939,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,-7.2166,-0.0441,-7.9714,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,-7.2182,-0.0457,-7.9714,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,-6.9962,-0.0217,-7.7734,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,-7.0502,-0.0380,-7.8111,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-9.6285,-0.0388,-10.3886,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,-6.7178,-0.0836,-7.4331,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-11.5627,-0.0362,-12.3254,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,-2.4247,-0.0235,-3.2001,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-7.8318,-0.0565,-8.5742,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-9.4598,-0.0400,-10.2187,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-9.4598,-0.0400,-10.2187,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_NPPD,NPPD_LA,-6.2938,-0.0389,-7.0538,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,-6.0492,-0.0389,-6.8092,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,-6.0492,-0.0389,-6.8092,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,-7.9875,-0.0538,-8.7326,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-8.0002,-0.0542,-8.7449,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NSB,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NSP,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NSSO,PJM,2.3457,0.0013,1.5455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,NYIS,PJM,2.3457,0.0013,1.5455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-20.9771,-0.0671,-21.7089,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-28.8861,-0.0679,-29.6171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-34.1934,-0.0629,-34.9294,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-34.1934,-0.0629,-34.9294,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-23.4233,-0.0647,-24.1575,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-38.4260,-0.0742,-39.1507,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-95.4512,-0.0461,-96.2040,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-50.4452,-0.0680,-51.1762,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-30.1120,-0.0646,-30.8463,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-29.0674,-0.0690,-29.7973,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-17.6019,-0.0287,-18.3721,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-30.1120,-0.0646,-30.8463,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-22.7236,-0.0663,-23.4562,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-21.0887,-0.0486,-21.8390,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-20.1477,-0.0696,-20.8770,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,-23.6949,-0.0150,-24.4788,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-29.0674,-0.0690,-29.7973,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-24.9981,-0.0603,-25.7367,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-21.3353,-0.0671,-22.0671,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-20.0230,-0.0497,-20.7722,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-24.1264,-0.0158,-24.9095,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-21.0887,-0.0486,-21.8390,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-21.0887,-0.0486,-21.8390,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-29.0674,-0.0690,-29.7973,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-19.5870,-0.0426,-20.3434,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.NUEN.LAM1,LAM1_DDR,16.1988,0.0468,15.3531,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-17.6019,-0.0287,-18.3721,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-17.6019,-0.0287,-18.3721,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-20.0846,-0.0433,-20.8402,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-17.7002,-0.0311,-18.4680,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-17.7002,-0.0311,-18.4680,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-17.7002,-0.0311,-18.4680,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-17.7355,-0.0284,-18.5060,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-17.7355,-0.0284,-18.5060,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-17.7002,-0.0311,-18.4680,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-17.7002,-0.0311,-18.4680,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-29.0674,-0.0690,-29.7973,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,11.4500,0.0292,10.6219,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-22.7236,-0.0663,-23.4562,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-18.8683,-0.0305,-19.6367,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-24.9981,-0.0603,-25.7367,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,13.0820,0.0318,12.2512,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-21.3731,-0.0491,-22.1229,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-21.3731,-0.0491,-22.1229,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-21.3731,-0.0491,-22.1229,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-21.3731,-0.0491,-22.1229,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-36.6666,-0.0947,-37.3708,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-30.9438,-0.0628,-31.6800,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-28.8861,-0.0679,-29.6171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-33.7264,-0.0607,-34.4647,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-33.7264,-0.0607,-34.4647,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-18.4454,-0.0169,-19.2274,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-20.7156,-0.0530,-21.4615,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-20.7156,-0.0530,-21.4615,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-20.7156,-0.0530,-21.4615,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0033,FOSTER_DDR,-16.9133,-0.0269,-17.6853,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,3.0113,0.0120,2.2004,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0035,TARBY_DDR,16.0394,0.0374,15.2031,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,3.0113,0.0120,2.2004,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,1.1251,0.0026,0.3236,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,1.1251,0.0026,0.3236,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-18.7236,-0.0198,-19.5027,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0040,TROSPER_DDR,-16.6827,-0.0262,-17.4554,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,-16.9168,-0.0264,-17.6893,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,14.0131,0.0368,13.1774,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0115,V115_DDR,-17.5612,-0.0285,-18.3316,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0116,V116_DDR,-22.3542,-0.0120,-23.1412,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0118,V118_DDR,-34.2838,-0.0068,-35.0759,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0125,V125_DDR,14.3151,0.0432,13.4730,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0126,V126_DDR,14.8071,0.0200,13.9882,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0129,V129_DDR,-14.8951,-0.0440,-15.6500,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,-16.9635,-0.0316,-17.7308,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0134,V134_DDR,15.9781,0.0261,15.1531,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0138,V138_DDR,14.0241,0.0168,13.2084,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,-17.2089,-0.0301,-17.9777,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0143,V143_DDR,6.2004,0.0060,5.3955,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0149,V149_DDR,-18.8196,-0.0445,-19.5740,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0150,V150_DDR,-18.6025,-0.0450,-19.3565,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0155,V155_DDR,13.3873,0.0134,12.5750,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0156,V156_DDR,-16.9635,-0.0316,-17.7308,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0166,V166_DDR,14.5118,0.0384,13.6745,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,-17.0656,-0.0294,-17.8351,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-18.6025,-0.0450,-19.3565,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0170,V170_DDR,-20.2420,-0.0432,-20.9978,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-18.2748,-0.0431,-19.0306,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0176,V176_DDR,-18.6025,-0.0450,-19.3565,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0177,V177_DDR,-26.7686,-0.0738,-27.4937,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,-17.0180,-0.0282,-17.7887,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-21.5827,-0.0582,-22.3234,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0195,V195_DDR,95.8362,0.0323,95.0050,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0197,V197_DDR,12.9839,0.0241,12.1609,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0198,V198_DDR,14.5118,0.0384,13.6745,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0208,V208_DDR,96.0000,0.0330,95.1681,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0209,V209_DDR,96.0000,0.0330,95.1681,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,13.7759,0.0163,12.9607,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0216,V216_DDR,-16.9756,-0.0265,-17.7480,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0219,V219_DDR,13.3873,0.0134,12.5750,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0220,V220_DDR,-18.6025,-0.0450,-19.3565,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0224,V224_DDR,-17.6139,-0.0295,-18.3833,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0225,V225_DDR,-17.6139,-0.0295,-18.3833,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0226,V226_DDR,-17.6139,-0.0295,-18.3833,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0227,V227_DDR,-17.6139,-0.0295,-18.3833,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0229,V229_DDR,-18.8042,-0.0176,-19.5855,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0231,V231_DDR,-20.3191,-0.0069,-21.1112,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0238,V238_DDR,-35.3691,-0.0741,-36.0939,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.VOLT.0242,V242_DDR,13.6497,0.0151,12.8356,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-30.6700,-0.1045,-31.3644,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-21.0887,-0.0486,-21.8390,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-28.7070,-0.0645,-29.4414,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-20.1470,-0.0689,-20.8770,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-30.6700,-0.1045,-31.3644,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-18.1004,-0.0745,-18.8249,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-55.4340,-0.0652,-56.1677,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEHL7,OKGEHL7_H,-14.1196,-0.0248,-14.8937,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEHL8,OKGEHSL1UN8_RA,-14.1196,-0.0248,-14.8937,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEHL910,OKGEHSL1PLT2,-14.1196,-0.0248,-14.8937,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-19.3607,-0.0718,-20.0878,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEMCC,OKGEMCCLAIPLT1,-17.8199,-0.0358,-18.5830,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,10.7735,0.0097,9.9649,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,10.7735,0.0097,9.9649,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,10.7735,0.0097,9.9649,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,-13.2560,-0.0334,-14.0215,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,-13.2560,-0.0334,-14.0215,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,-13.2560,-0.0334,-14.0215,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,-13.2560,-0.0334,-14.0215,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGESM1,OKGESEMINOLEUN1_RA,-17.6425,-0.0184,-18.4230,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGESM2,OKGESEMINOLEUN2_RA,-13.3170,-0.0202,-14.0957,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGESM3,OKGESEMINOLEUN3_RA,-13.3170,-0.0202,-14.0957,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGESO1,OKGESONR1UN1_RA,-57.7870,-0.0573,-58.5286,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGESO2,OKGESONR1UN2_RA,-33.7264,-0.0607,-34.4647,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-19.3665,-0.0776,-20.0878,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-23.4316,-0.0943,-24.1362,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGETINK5A,OKGETINK5UN1_RA,-16.2984,-0.0267,-17.0706,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGETINK5B,OKGETINK5UN2_RA,-16.2984,-0.0267,-17.0706,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-20.4095,-0.0654,-21.1430,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-28.8861,-0.0679,-29.6171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,13.6579,0.0519,12.8071,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-21.0887,-0.0486,-21.8390,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE_OKGE,OKGE_LA,-10.9873,-0.0154,-11.7708,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-18.8683,-0.0305,-19.6367,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-20.4121,-0.0680,-21.1430,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMLP,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,17.7729,0.0064,16.9676,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,13.8031,0.0482,12.9560,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-19.2490,-0.0280,-20.0199,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-95.4465,-0.0415,-96.2040,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-22.7522,-0.0673,-23.4838,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-30.1120,-0.0646,-30.8463,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-28.2728,-0.1067,-28.9650,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-14.5288,-0.0653,-15.2624,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,142.9400,-0.0018,142.1429,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-95.4476,-0.0425,-96.2040,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-95.4476,-0.0425,-96.2040,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_SPP,OMPA_SPP_LA,-24.8246,-0.0387,-25.5849,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-30.6700,-0.1045,-31.3644,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,15.1059,0.0050,14.3020,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,15.1059,0.0050,14.3020,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,15.1059,0.0050,14.3020,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,15.1059,0.0050,14.3020,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,ONT,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,-5.5166,-0.0311,-6.2844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,-5.5166,-0.0311,-6.2844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,-5.5166,-0.0311,-6.2844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,-5.5166,-0.0311,-6.2844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,-5.5166,-0.0311,-6.2844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,-5.5166,-0.0311,-6.2844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,-5.5166,-0.0311,-6.2844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,-5.5166,-0.0311,-6.2844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,-5.5166,-0.0311,-6.2844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,-5.4895,-0.0299,-6.2585,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,-5.4818,-0.0304,-6.2503,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,-5.5418,-0.0249,-6.3158,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,-5.5224,-0.0284,-6.2929,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,-5.5224,-0.0284,-6.2929,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD_GLDN,OPPD_GLDN_LA,-5.5058,-0.0300,-6.2747,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,-5.4990,-0.0302,-6.2677,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,-4.2847,-0.0773,-5.0063,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,-6.2384,-0.0387,-6.9986,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,-5.4827,-0.0304,-6.2513,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD_OPPD,OPPD_LA,-5.5206,-0.0290,-6.2905,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,-5.5154,-0.0275,-6.2868,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,-5.5179,-0.0277,-6.2891,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OTP,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,OVEC,OVEC,3.1978,0.0046,2.3943,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PARAGOULD,PARAGOULD_LA,8.6881,0.0220,7.8672,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,19.3861,0.0029,18.5843,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,19.3861,0.0029,18.5843,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,19.3861,0.0029,18.5843,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,19.0326,0.0058,18.2279,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,19.0326,0.0058,18.2279,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,19.0326,0.0058,18.2279,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PIGGOTT,PIGGOTT_LA,7.8588,0.0197,7.0402,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PJM,PJM,2.3457,0.0013,1.5455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PLUM,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,POPLARBLUFF,POPLARBLUFF_LA,7.1048,0.0165,6.2894,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,-2.3904,-0.0107,-3.1787,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,-2.3904,-0.0107,-3.1787,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,-2.2599,-0.0105,-3.0483,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,-2.2599,-0.0105,-3.0483,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,-2.0414,0.0418,-2.8821,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,-2.0414,0.0418,-2.8821,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,-2.3094,-0.0008,-3.1076,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,-2.9485,-0.0270,-3.7204,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-21.2356,-0.0469,-21.9877,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,63.3257,0.0008,62.5260,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,-6.6273,-0.0085,-7.4177,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-19.1478,-0.0082,-19.9384,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,25.2994,0.0204,24.4801,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,15.5430,0.0212,14.7229,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,-3.8276,-0.0341,-4.5924,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,-2.2239,0.0036,-3.0264,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,-4.5321,-0.0467,-5.2844,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,6.5400,0.0359,5.7052,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,-1.9488,0.0056,-2.7534,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,-4.1631,-0.0306,-4.9315,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,PUPP,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,RCEAST,RCEAST,-5.1269,-0.0266,-5.8992,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SALINA_1,GRDASALINA1UN1_RA,19.5617,0.0088,18.7540,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SALINA_2,GRDASALINA1UN2_RA,19.5617,0.0088,18.7540,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SALINA_3,GRDASALINA1UN3_RA,19.5617,0.0088,18.7540,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SALINA_4,GRDASALINA1UN4_RA,19.5617,0.0088,18.7540,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SALINA_5,GRDASALINA1UN5_RA,19.5617,0.0088,18.7540,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SALINA_6,GRDASALINA1UN6_RA,19.5617,0.0088,18.7540,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SARPY_1,OPPDSARPYUN1_RA,-5.5076,-0.0303,-6.2762,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SARPY_2,OPPDSARPYUN2_RA,-5.5128,-0.0289,-6.2828,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SARPY_3,OPPDSARPYUN3_RA,-5.4901,-0.0313,-6.2577,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SARPY_4,OPPDSARPYUN4_RA,-5.4901,-0.0313,-6.2577,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SARPY_5,OPPDSARPYUN5_RA,-5.4901,-0.0313,-6.2577,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SC,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SCEG,VACS,7.3676,0.0194,6.5494,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,SCSE,SCSE,-9.2405,-0.0319,-10.0075,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SEC,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-20.6354,-0.0688,-21.3655,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-20.6354,-0.0688,-21.3655,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-20.6354,-0.0688,-21.3655,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-19.7802,-0.0206,-20.5585,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-20.6354,-0.0688,-21.3655,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-19.8670,-0.0591,-20.6068,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-19.3319,-0.0671,-20.0637,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-19.3319,-0.0671,-20.0637,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-19.4995,-0.0525,-20.2459,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-21.3756,-0.0667,-22.1078,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-16.1958,-0.0509,-16.9438,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-20.2379,-0.0271,-21.0097,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-15.7406,-0.0426,-16.4969,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-20.4122,-0.0678,-21.1433,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-15.6889,-0.0427,-16.4452,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-20.2439,-0.0620,-20.9808,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-19.9782,-0.0482,-20.7289,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-19.4871,-0.0440,-20.2420,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-19.4871,-0.0440,-20.2420,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-19.4871,-0.0440,-20.2420,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-19.4871,-0.0440,-20.2420,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-19.6429,-0.0478,-20.3940,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-19.8670,-0.0591,-20.6068,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI_SECI,SECI_LA,-19.2410,-0.0396,-20.0003,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-14.6425,-0.0612,-15.3803,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-14.6425,-0.0612,-15.3803,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-19.4995,-0.0525,-20.2459,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SEHA,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-20.4121,-0.0680,-21.1430,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SERU,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SETH,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SGE,SGE,-8.4877,-0.0283,-9.2583,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SMEP,MISO,3.2273,0.0037,2.4247,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SOCO,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPA,SPA,14.4853,0.0258,13.6605,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPC,SPC,-1.9451,0.0201,-2.7641,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPPNORTH_HUB,SPPNORTH_H,-5.7782,-0.0335,-6.5436,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-16.6994,-0.0440,-17.4543,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,10.7691,0.0193,9.9509,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,10.7691,0.0193,9.9509,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,10.2717,0.0185,9.4543,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,10.2717,0.0185,9.4543,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_NIXA,SPRM_NIXA_LA,11.4123,0.0204,10.5930,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_SPRM,SPRM_LA,10.7458,0.0213,9.9256,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,10.9418,0.0158,10.1271,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,10.9418,0.0158,10.1271,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,10.9400,0.0140,10.1271,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,10.9418,0.0158,10.1271,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,25.2409,0.0386,24.4034,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,27.4150,0.0150,26.6011,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-13.2761,-0.0205,-14.0545,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-13.2761,-0.0205,-14.0545,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,24.2374,-0.0129,23.4513,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,23.9998,0.0182,23.1827,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,25.5061,-0.0691,24.7763,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,24.2301,0.0920,23.3392,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,23.5088,0.0173,22.6926,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,24.0011,0.0565,23.1457,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,24.0122,0.0633,23.1500,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,24.0122,0.0633,23.1500,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,24.0011,0.0565,23.1457,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-13.2190,-0.0117,-14.0062,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,27.4150,0.0150,26.6011,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-13.3610,-0.0180,-14.1419,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-19.4821,-0.0575,-20.2236,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-15.6879,-0.0170,-16.4698,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-13.9240,-0.0029,-14.7200,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-14.2301,-0.0189,-15.0102,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-24.3533,-0.0614,-25.0908,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-24.3533,-0.0614,-25.0908,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-24.3533,-0.0614,-25.0908,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-24.3533,-0.0614,-25.0908,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GRID.WRAB,WRAB_DDR,-11.8400,-0.0035,-12.6354,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-24.3533,-0.0614,-25.0908,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,23.0292,0.0194,22.2109,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,23.0292,0.0194,22.2109,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,21.8223,0.0196,21.0038,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,21.8223,0.0196,21.0038,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,21.8223,0.0196,21.0038,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,23.0292,0.0194,22.2109,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-10.9923,-0.0182,-11.7730,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-10.9937,-0.0182,-11.7744,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-10.9877,-0.0182,-11.7684,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-12.9007,-0.0407,-13.6589,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,23.9929,0.0556,23.1384,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,23.4984,0.0165,22.6830,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,23.4984,0.0165,22.6830,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,23.4984,0.0165,22.6830,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,23.4984,0.0165,22.6830,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,23.9653,0.0538,23.1126,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,23.9959,0.0535,23.1435,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,23.9959,0.0535,23.1435,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-20.4079,-0.0638,-21.1430,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-11.4615,-0.0177,-12.2427,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-11.4615,-0.0177,-12.2427,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-11.0734,-0.0182,-11.8541,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-11.8400,-0.0035,-12.6354,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-18.8873,-0.0449,-19.6413,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-14.2931,-0.0225,-15.0695,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-23.4233,-0.0647,-24.1575,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-11.4502,-0.0064,-12.2427,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.PLANTX1,SPS.PLANTX1_H,26.1168,0.0339,25.2840,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.PLANTX2,SPS.PLANTX2_H,26.1168,0.0339,25.2840,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,25.8819,0.0329,25.0501,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,24.0776,0.0016,23.2771,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-21.6954,-0.0549,-22.4394,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,25.5268,-0.0485,24.7763,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,24.0796,0.0035,23.2771,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-13.2192,-0.0120,-14.0062,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,24.9883,0.0444,24.1450,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,24.2301,0.0920,23.3392,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,24.9883,0.0444,24.1450,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,24.2312,0.0918,23.3405,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-43.5608,-0.0250,-44.3347,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,24.1041,0.1101,23.1951,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,24.1074,0.1133,23.1951,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,24.0825,0.1059,23.1777,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,24.0055,0.0632,23.1434,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,24.1700,0.1027,23.2684,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-19.7197,-0.0508,-20.4678,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-11.8144,-0.0071,-12.6062,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,25.4823,0.0358,24.6476,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,25.4823,0.0358,24.6476,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,24.9883,0.0444,24.1450,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,23.5415,0.0213,22.7213,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,23.9572,0.0775,23.0808,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,25.6746,0.0721,24.8036,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,25.7709,0.0524,24.9196,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,26.2684,0.0157,25.4538,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,24.1041,0.1101,23.1951,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,24.1711,0.1267,23.2455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,24.1600,0.1156,23.2455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,24.0850,0.0090,23.2771,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,25.6238,0.0515,24.7734,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-21.1028,-0.0520,-21.8497,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-21.0904,-0.0532,-21.8361,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0163,V163_DDR,-10.8765,-0.0087,-11.6667,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0168,V168_DDR,-17.5571,-0.0398,-18.3162,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0180,V180_DDR,24.1711,0.1267,23.2455,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0181,V181_DDR,-21.4337,-0.0445,-22.1881,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0182,V182_DDR,24.1695,0.1052,23.2654,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0199,V199_DDR,23.9540,0.0705,23.0846,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0200,V200_DDR,24.0431,0.0785,23.1657,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.VOLT.0235,V235_DDR,-18.8873,-0.0449,-19.6413,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,25.5061,-0.0691,24.7763,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,24.2301,0.0920,23.3392,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-11.0118,-0.0128,-11.7979,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-11.5207,-0.0122,-12.3074,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS_SPS,SPS_LA,15.0251,0.0601,14.1661,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,24.9050,0.0429,24.0632,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SSCN_NPPD,SSCN_NPPD_LA,-6.6389,-0.0434,-7.3944,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,6.3840,0.0155,5.5696,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,6.3840,0.0155,5.5696,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,TAL,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,TEC,SOUC,7.7711,0.0210,6.9512,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,-6.7178,-0.0836,-7.4331,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,TVA,TVA,6.9422,0.0177,6.1256,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,UCUHUB,UCUHUB_H,-9.8129,-0.0249,-10.5869,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,UCUHUB17,UCUHUB17_H,-13.0732,-0.0388,-13.8333,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,UCUHUB18,UCUHUB18_H,-10.6679,-0.0357,-11.4311,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,UCUHUB19,UCUHUB19_H,-13.9932,-0.0388,-14.7534,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,UCUHUB20,UCUHUB20_H,-14.2150,-0.0369,-14.9770,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,UCUHUB21,UCUHUB21_H,-15.4361,-0.0407,-16.1943,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,UCUHUB22,UCUHUB22_H,-14.9620,-0.0428,-15.7181,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,UCUHUB23,UCUHUB23_H,-15.2212,-0.0432,-15.9769,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,UCUHUB24,UCUHUB24_H,-13.3876,-0.0380,-14.1485,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,-1.9410,0.0278,-2.7677,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,-1.9410,0.0278,-2.7677,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,-1.9094,-0.0229,-2.6854,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,-1.9094,-0.0229,-2.6854,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,-1.8738,-0.0261,-2.6466,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,-2.2404,-0.0168,-3.0225,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,-2.2404,-0.0168,-3.0225,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,-1.9410,0.0278,-2.7677,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,-1.8980,-0.0242,-2.6727,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,-1.8956,0.0048,-2.6993,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,-4.3618,-0.0444,-5.1163,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,-4.6641,-0.0784,-5.3846,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,-2.0235,0.0254,-2.8478,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,-2.0235,0.0254,-2.8478,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,3.7955,-0.0867,3.0833,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,-5.4101,-0.0384,-6.1706,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,2.6070,-0.0094,1.8175,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,-4.6127,-0.0466,-5.3650,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,-4.3882,-0.0378,-5.1494,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,-5.6245,-0.0424,-6.3811,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,3.8365,-0.0457,3.0833,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,3.8365,-0.0457,3.0833,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,-3.6042,-0.0341,-4.3690,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,-4.5675,-0.0768,-5.2896,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,-4.3512,-0.0268,-5.1233,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,-1.9877,-0.0019,-2.7848,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,-1.9877,-0.0019,-2.7848,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,-1.9877,-0.0019,-2.7848,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,-1.9783,-0.0002,-2.7770,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,-1.9783,-0.0002,-2.7770,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,-1.9783,-0.0002,-2.7770,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,-1.9271,0.0385,-2.7645,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,-1.8625,-0.0227,-2.6387,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,-1.8424,-0.0237,-2.6176,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-8.8611,-0.0303,-9.6297,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,-5.4715,-0.0350,-6.2354,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,-2.0030,0.0040,-2.8059,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,-5.6963,-0.0464,-6.4488,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,-4.7269,-0.0884,-5.4374,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,3.7025,-0.0364,2.9399,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,-1.9726,0.0248,-2.7963,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,-1.9594,0.0198,-2.7781,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,-1.9594,0.0198,-2.7781,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,-1.9594,0.0198,-2.7781,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,-1.9594,0.0198,-2.7781,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,-1.9594,0.0198,-2.7781,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,-1.9594,0.0198,-2.7781,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,-1.9594,0.0198,-2.7781,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,-5.3911,-0.0752,-6.1148,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,-1.9436,-0.0119,-2.7306,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,-5.3120,-0.0347,-6.0762,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,-5.3120,-0.0347,-6.0762,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,-6.0737,-0.0540,-6.8186,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,-6.0737,-0.0540,-6.8186,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,-1.8547,-0.0149,-2.6387,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,-2.1177,-0.0140,-2.9027,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,-4.4515,-0.0563,-5.1941,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,-4.3253,-0.0665,-5.0577,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,-3.6367,-0.0244,-4.4113,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,-1.8738,-0.0261,-2.6466,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,-1.8738,-0.0261,-2.6466,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,-4.6127,-0.0466,-5.3650,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,-5.1356,-0.0275,-5.9070,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,-0.3527,-0.0400,-1.1116,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,-4.5577,-0.0670,-5.2896,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,-7.6398,-0.0420,-8.3967,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.FSE,WAUE.FSE_H,-6.3315,-0.0500,-7.0804,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,-2.1807,-0.0003,-2.9793,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,-2.2052,-0.0006,-3.0035,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,-5.1781,-0.0823,-5.8948,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,-4.9834,-0.0772,-5.7051,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,-1.8272,-0.0238,-2.6023,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,-1.9021,-0.0270,-2.6740,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-19.0900,-0.0840,-19.8049,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,-4.6641,-0.0784,-5.3846,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-12.0000,-0.0238,-12.7751,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,-4.6701,-0.0426,-5.4265,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,-4.6661,-0.0385,-5.4265,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,-4.6660,-0.0384,-5.4265,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,-6.5239,-0.0364,-7.2864,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,-5.1356,-0.0275,-5.9070,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,-3.9243,-0.0247,-4.6985,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,-4.6551,-0.0482,-5.4058,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,-4.3504,-0.0261,-5.1233,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,-4.4398,-0.0048,-5.2340,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,-4.3208,-0.0351,-5.0846,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,-2.8637,-0.0186,-3.6440,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,-4.4954,-0.0413,-5.2530,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,-4.4922,-0.0513,-5.2398,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,-5.6963,-0.0464,-6.4488,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,-2.5087,0.0013,-3.3089,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,-4.6146,-0.0473,-5.3662,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,-2.5572,-0.0026,-3.3535,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,-4.0863,-0.0266,-4.8586,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,-5.3113,-0.0333,-6.0769,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NTWK,WAUE.NTWK_H,-3.5682,-0.0253,-4.3418,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,-3.3927,0.0076,-4.1992,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,-3.3927,0.0076,-4.1992,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,-4.6289,-0.0877,-5.3401,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,-5.3549,-0.0969,-6.0569,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,-4.2304,-0.0327,-4.9966,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,-4.6289,-0.0877,-5.3401,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,-2.1358,-0.0099,-2.9248,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,-3.5068,-0.0433,-4.2624,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,-5.6963,-0.0464,-6.4488,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,-3.3954,-0.0217,-4.1726,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,-3.5640,-0.1005,-4.2624,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,-5.2681,-0.0603,-6.0067,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,-4.9777,-0.0586,-5.7180,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,-1.8389,-0.0244,-2.6134,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,-5.7688,-0.0802,-6.4875,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,-3.9606,-0.0226,-4.7369,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,-4.0716,-0.0556,-4.8149,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,-4.3253,-0.0665,-5.0577,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.VOLT.0152,V152_DDR,-1.9070,0.0475,-2.7534,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE.VOLT.0172,V172_DDR,-1.9597,0.0231,-2.7817,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_BEPM,WAUE_BEPM_LA,-2.4260,0.0028,-3.2277,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,-4.0479,-0.0301,-4.8167,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,-4.4419,-0.0044,-5.2364,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_EWA,WAUE_EWA_LA,-5.1019,-0.0246,-5.8762,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,-3.6908,-0.0463,-4.4435,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_HMMU,WAUE_HMMU_LA,-4.9723,-0.0165,-5.7548,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,-2.7738,-0.0212,-3.5515,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_MECB,WAUE_MECB_LA,-4.7780,-0.0129,-5.5641,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_MMPA,WAUE_MMPA_LA,-2.0376,0.0098,-2.8463,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_MRES,WAUE_MRES_LA,-4.4737,-0.0260,-5.2466,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,-1.9116,0.0316,-2.7421,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,-2.1807,-0.0003,-2.9793,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,-4.3499,-0.0451,-5.1037,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_OTP,WAUE_OTP_LA,-1.8526,0.0248,-2.6764,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_OTPW,WAUE_OTPW_LA,-0.7100,0.0043,-1.5133,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM,WAUE_UGPM_LA,-3.4291,-0.0263,-4.2017,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,-2.4804,-0.0080,-3.2714,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,-4.4688,-0.0338,-5.2339,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,-3.8575,-0.0374,-4.6190,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,-5.1019,-0.0246,-5.8762,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,-4.9723,-0.0165,-5.7548,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,-3.1060,-0.0487,-3.8562,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,-2.1807,-0.0003,-2.9793,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,-2.0376,0.0098,-2.8463,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,-4.0451,-0.0215,-4.8225,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,-4.4701,-0.0518,-5.2172,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,-1.9269,0.0311,-2.7569,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-30.5645,-0.0947,-31.2687,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-26.3695,-0.0876,-27.0808,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,-8.2229,-0.0522,-8.9696,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,99.5400,0.0154,98.7257,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,99.5400,0.0154,98.7257,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-16.6397,-0.0934,-17.3452,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,88.0360,0.0201,87.2170,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,74.7229,0.0191,73.9048,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,9.3800,-0.0517,8.6328,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,9.3800,-0.0517,8.6328,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,9.3800,-0.0517,8.6328,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,9.3800,-0.0517,8.6328,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,9.3783,-0.0535,8.6328,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,9.3800,-0.0517,8.6328,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,9.3800,-0.0517,8.6328,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,9.3800,-0.0517,8.6328,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,1.2760,-0.0492,0.5263,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-23.4233,-0.0647,-24.1575,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-29.0442,-0.0781,-29.7650,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-28.4666,-0.1211,-29.1444,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,25.5214,-0.0538,24.7763,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_ENMC,WFEC_ENMC_LA,24.4075,0.0673,23.5413,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-29.0674,-0.0690,-29.7973,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,28.0593,0.0134,27.2470,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,23.9683,0.0484,23.1210,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-30.5645,-0.0947,-31.2687,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-30.5645,-0.0947,-31.2687,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-30.5645,-0.0947,-31.2687,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_OKGE,WFEC_OKGE_LA,-17.7916,-0.0111,-18.5794,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,10.9425,0.0163,10.1272,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-21.9856,-0.0907,-22.6938,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-16.9604,-0.0964,-17.6629,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_WFEC,WFEC_LA,1.9133,-0.0253,1.1397,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,23.9683,0.0484,23.1210,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-14.1433,-0.0553,-14.8869,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-18.2559,-0.0470,-19.0078,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-13.6569,-0.0387,-14.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-13.6569,-0.0387,-14.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-13.6569,-0.0387,-14.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-13.6569,-0.0387,-14.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-13.6569,-0.0387,-14.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-13.6569,-0.0387,-14.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-13.6569,-0.0387,-14.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,-5.9979,0.0099,-6.8067,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-14.4024,-0.0518,-15.1495,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-25.8232,-0.0660,-26.5561,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-25.8232,-0.0660,-26.5561,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-25.8232,-0.0660,-26.5561,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-21.6396,-0.0679,-22.3706,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-21.6396,-0.0679,-22.3706,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-22.0592,-0.0604,-22.7978,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-22.0592,-0.0604,-22.7978,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-22.0592,-0.0604,-22.7978,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-14.4024,-0.0518,-15.1495,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,-8.4430,-0.0158,-9.2261,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-17.8364,-0.0509,-18.5844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-17.8365,-0.0510,-18.5844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-17.8365,-0.0510,-18.5844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-17.8364,-0.0509,-18.5844,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,-8.4430,-0.0158,-9.2261,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-20.0644,-0.0662,-20.7971,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-43.9694,-0.0304,-44.7379,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.JEC.1,WRJEFFUN10_RA,-12.1652,-0.0348,-12.9294,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.JEC.2,WRJEFFUN11_RA,-12.0661,-0.0348,-12.8302,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.JEC.3,WRJEFFUN12_RA,-12.0673,-0.0360,-12.8302,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-28.7059,-0.0646,-29.4402,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-21.5629,-0.0645,-22.2973,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-21.5629,-0.0645,-22.2973,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.LEC.4,WRLECUN26_RA,-9.6635,-0.0198,-10.4426,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.LEC.5,WRLECUN27_RA,-10.1163,-0.0176,-10.8976,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-16.6659,-0.0477,-17.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-16.6659,-0.0477,-17.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-16.6659,-0.0477,-17.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-16.6456,-0.0462,-17.3983,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-14.6425,-0.0612,-15.3803,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-14.6425,-0.0612,-15.3803,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-15.7037,-0.0365,-16.4661,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-13.9018,-0.0534,-14.6474,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-13.9018,-0.0534,-14.6474,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-16.6378,-0.0778,-17.3589,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-14.6425,-0.0612,-15.3803,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-9.5532,-0.0617,-10.2904,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-14.7655,-0.0597,-15.5047,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-21.5632,-0.0648,-22.2973,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,74.1198,0.0201,73.3008,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-16.6180,-0.1085,-17.3084,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-13.6569,-0.0387,-14.4171,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-15.2920,-0.0666,-16.0243,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,-8.4430,-0.0158,-9.2261,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-14.4024,-0.0518,-15.1495,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-23.5799,-0.0550,-24.3238,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.THAYERLD,WR.THAYERLD_LA,8.2043,0.0183,7.3871,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-24.3703,-0.0545,-25.1147,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0106,V106_DDR,-23.4643,-0.0535,-24.2098,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-8.4062,-0.0115,-9.1936,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-15.2985,-0.0467,-16.0507,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-9.5483,-0.0141,-10.3331,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-9.5483,-0.0141,-10.3331,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-8.7698,-0.0140,-9.5547,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-22.9799,-0.0463,-23.7325,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0157,V157_DDR,-9.5905,-0.0148,-10.3746,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0158,V158_DDR,-9.5483,-0.0141,-10.3331,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-9.5483,-0.0141,-10.3331,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-23.5298,-0.0567,-24.2720,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0173,V173_DDR,-16.6546,-0.0543,-17.3992,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0174,V174_DDR,-23.3297,-0.0528,-24.0758,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0184,V184_DDR,-22.9259,-0.0573,-23.6675,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-23.7019,-0.0545,-24.4463,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0186,V186_DDR,-23.6816,-0.0563,-24.4242,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-23.1489,-0.0561,-23.8917,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-24.2222,-0.0537,-24.9674,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-17.7212,-0.0418,-18.4783,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-14.5554,-0.0346,-15.3197,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-13.9074,-0.0363,-14.6700,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-13.9074,-0.0363,-14.6700,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-14.5554,-0.0346,-15.3197,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0245,V245_DDR,-23.7144,-0.0545,-24.4588,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.VOLT.0248,V248_DDR,-23.4643,-0.0535,-24.2098,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-25.9170,-0.0614,-26.6545,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-10.4912,-0.0213,-11.2688,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.WOLF,WRWOLFUN15_RA,-15.6722,-0.0706,-16.4005,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-20.0644,-0.0662,-20.7971,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,-6.0012,0.0066,-6.8067,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-25.8232,-0.0660,-26.5561,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-25.8232,-0.0660,-26.5561,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-25.8232,-0.0660,-26.5561,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-25.8232,-0.0660,-26.5561,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-23.0453,-0.0480,-23.7962,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-15.2386,-0.0467,-15.9908,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-24.4920,-0.0549,-25.2360,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-24.4920,-0.0549,-25.2360,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-24.4920,-0.0549,-25.2360,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-24.4920,-0.0549,-25.2360,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-14.0028,-0.0329,-14.7688,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-14.0028,-0.0329,-14.7688,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-14.0028,-0.0329,-14.7688,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-14.0028,-0.0329,-14.7688,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-14.0028,-0.0329,-14.7688,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-14.0028,-0.0329,-14.7688,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-37.9292,-0.0543,-38.6738,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-37.9292,-0.0543,-38.6738,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-40.2594,-0.0566,-41.0017,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-40.2594,-0.0566,-41.0017,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_MIDW,WR_MIDW_LA,-15.8757,-0.0513,-16.6233,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,-2.2683,0.0088,-3.0760,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,-5.6209,-0.0068,-6.4129,0.7988\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-17.0232,-0.0489,-17.7732,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_SEG,WR_SEG_LA,-7.7568,0.0009,-8.5566,0.7989\n03/19/2025 04:00:00,03/19/2025 09:00:00,WR_WR,WR_LA,-15.7765,-0.0382,-16.5373,0.7990\n03/19/2025 04:00:00,03/19/2025 09:00:00,YAD,VACS,7.3676,0.0194,6.5494,0.7988\n03/19/2025 05:00:00,03/19/2025 10:00:00,AEC,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,AECC_CSWS,CSWS_AECC_LA,21.8258,0.1530,18.1118,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,19.4295,0.1076,15.7609,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,22.6823,0.2142,18.9071,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,19.4678,0.0757,15.8311,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,24.7639,0.1190,21.0839,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,22.1189,0.0878,18.4700,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,25.3704,0.0715,21.7379,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,AECI,AECI,13.7779,0.0475,10.1694,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,AEPM_CSWS,CSWS_LA,22.6770,0.1269,18.9891,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,ALTW,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,AMRN,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,15.7337,-0.0457,12.2184,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,BBA,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BCA,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BEPM.ER01.DDR,ER01_DDR,0.3909,-0.2095,-2.9606,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,BEPM_ER01,BEPM_ER01_LA,0.3909,-0.2095,-2.9606,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,-2.5335,-0.0497,-6.0448,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-4.6284,-0.0234,-8.1661,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BEPM_UM01,BEPM_UM01_LA,3.2584,0.1481,-0.4507,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,BLKW,BLKW,17.7552,0.0590,14.1351,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-26.1498,-0.3355,-29.3754,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-26.1498,-0.3355,-29.3754,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,5.8618,-0.2894,2.5901,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-26.1460,-0.3317,-29.3754,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BRAZ,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BUBA,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-17.0392,-0.2841,-20.3161,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-17.4552,-0.2210,-20.7952,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-17.4552,-0.2210,-20.7952,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-17.4552,-0.2210,-20.7952,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-17.4552,-0.2210,-20.7952,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-17.4552,-0.2210,-20.7952,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-23.4700,-0.1975,-26.8335,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,-1.4231,-0.1075,-4.8766,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,-1.4231,-0.1075,-4.8766,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CLEC,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,21.2411,0.0716,17.6085,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,COWP,COWP_LA,20.1773,0.0957,16.5206,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,20.1773,0.0957,16.5206,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,20.1773,0.0957,16.5206,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CPLE,VACS,16.8261,0.1130,13.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CPLW,VACS,16.8261,0.1130,13.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,20.0873,0.1397,16.3866,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,20.0873,0.1397,16.3866,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,20.0873,0.1397,16.3866,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,20.0873,0.1397,16.3866,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CRTH_SPA,WRCRTH_SPA_LA,11.3246,0.0444,7.7191,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,24.4464,0.3023,20.5831,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-9.1842,-0.1878,-12.5574,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,25.3704,0.0715,21.7379,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,19.4678,0.0757,15.8311,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,24.4491,0.3007,20.5874,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,24.5390,0.2359,20.7421,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,24.5016,0.2747,20.6658,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,24.5016,0.2747,20.6658,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,19.1556,0.0949,15.4996,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,19.1556,0.0949,15.4996,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,19.1556,0.0949,15.4996,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,19.1556,0.0949,15.4996,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,25.3704,0.0715,21.7379,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,27.5606,0.2139,23.7857,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,41.3988,-0.0309,37.8686,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,41.3660,-0.0636,37.8686,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,24.8374,0.0234,21.2530,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,20.9489,0.0424,17.3454,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,20.9489,0.0424,17.3454,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,20.9509,0.0424,17.3474,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,20.9509,0.0424,17.3474,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-20.3772,-0.2316,-23.7066,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,-7.9708,-0.1731,-11.3587,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,33.6459,0.0441,30.0408,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-17.8464,-0.2650,-21.1424,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-17.8333,-0.2520,-21.1424,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-12.7654,-0.1603,-16.1662,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.GRID.CDL1,CDL1_DDR,27.4433,0.0639,23.8184,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-11.8978,-0.1900,-15.2688,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-7.9076,-0.1963,-11.2723,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,27.4433,0.0639,23.8184,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.NUEN.CSI1,CSI1_DDR,22.8006,0.0882,19.1514,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.NUEN.CSI2,CSI2_DDR,22.8017,0.0892,19.1514,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,21.2431,0.0736,17.6085,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.NUEN.GAZA,GAZA_DDR,27.4433,0.0639,23.8184,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,96.8127,0.1352,93.1165,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.NUEN.T201,NT201_DDR,21.9005,0.0520,18.2875,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-11.1476,-0.2433,-14.4654,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-11.1476,-0.2433,-14.4654,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,25.3704,0.0715,21.7379,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,24.9147,0.3234,21.0303,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-12.7654,-0.1603,-16.1662,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-12.7654,-0.1603,-16.1662,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-16.5018,-0.2161,-19.8468,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-17.8333,-0.2520,-21.1424,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,24.2335,0.2015,20.4710,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,18.3069,0.0220,14.7239,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,18.3069,0.0220,14.7239,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,18.2654,-0.0195,14.7239,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,1.2563,-0.0014,-2.3034,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,1.2563,-0.0014,-2.3034,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,24.6055,0.2305,20.8140,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,22.2459,0.0442,18.6407,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,24.5963,0.2396,20.7956,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,24.9940,0.3994,21.0335,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,29.2747,0.0949,25.6188,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,22.8017,0.0892,19.1514,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0057,OKMU_DDR,24.5640,0.0769,20.9261,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0060,LEHIGH_DDR,96.8127,0.1352,93.1165,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0086,WARRENM_DDR,21.3596,0.0539,17.7447,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,25.1016,0.3104,21.2301,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,32.6988,0.0468,29.0910,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0121,V121_DDR,24.6055,0.2305,20.8140,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0122,V122_DDR,31.1628,0.0435,27.5583,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0124,V124_DDR,50.7405,0.0222,47.1573,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0135,V135_DDR,22.3179,0.0559,18.7009,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0144,V144_DDR,-8.0915,-0.1551,-11.4974,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0145,V145_DDR,-8.1909,-0.1707,-11.5813,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,24.6221,0.2338,20.8272,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,25.5153,0.1197,21.8345,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0175,V175_DDR,21.2431,0.0736,17.6085,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,25.5153,0.1197,21.8345,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,25.5335,0.1413,21.8311,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,22.3179,0.0559,18.7009,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,22.6718,0.0511,19.0597,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,22.2971,0.0444,18.6916,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,37.3542,0.0019,33.7913,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,21.0415,0.0401,17.4403,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,22.6718,0.0511,19.0597,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0211,V211_DDR,24.5785,0.2718,20.7456,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,33.5061,0.0441,29.9009,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0213,V213_DDR,22.1354,0.0520,18.5223,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0215,V215_DDR,32.2330,0.0439,28.6281,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0217,V217_DDR,33.5734,0.0416,29.9707,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0218,V218_DDR,36.9040,0.0049,33.3380,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0228,V228_DDR,22.8427,0.0401,19.2415,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0232,V232_DDR,21.6734,0.0557,18.0566,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0233,V233_DDR,22.7922,0.0540,19.1772,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0240,V240_DDR,28.8168,0.0356,25.2201,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0244,V244_DDR,22.6718,0.0511,19.0597,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0246,MDT1_DDR,96.8127,0.1352,93.1165,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0249,V249_DDR,22.0744,0.0540,18.4593,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0250,V250_DDR,-9.6241,-0.1792,-13.0059,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0251,V251_DDR,21.4464,0.0472,17.8382,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.VOLT.0252,V252_DDR,37.3542,0.0019,33.7913,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-21.9101,-0.2209,-25.2502,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,2.1348,-0.2521,-1.1742,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-19.1356,-0.3394,-22.3572,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,24.5609,0.2232,20.7767,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-28.4232,-0.3596,-31.6246,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-23.4388,-0.2302,-26.7697,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-23.4388,-0.2302,-26.7697,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-23.4388,-0.2302,-26.7697,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-23.4388,-0.2302,-26.7697,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-23.4388,-0.2302,-26.7697,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,25.3704,0.0715,21.7379,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,23.7780,0.3015,19.9154,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,21.6697,0.0521,18.0566,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,21.6644,0.0467,18.0566,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,27.6056,0.0854,23.9592,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,27.6056,0.0854,23.9592,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWWELSH1,CSWSWELSHUN1_RA,24.9785,0.1717,21.2457,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWWELSH3,CSWSWELSHUN3_RA,24.9785,0.1717,21.2457,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWWILKES1,CSWSWILKESUN1_RA,24.9835,0.2221,21.2004,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWWILKES2,CSWSWILKESUN2_RA,24.9835,0.2221,21.2004,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,CSWWILKES3,CSWSWILKESUN3_RA,24.8222,0.2104,21.0507,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-17.8313,-0.2500,-21.1424,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,DENL,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,DERS,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,DOE,DOE,13.8604,0.0817,10.2177,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,-3.8319,-0.0363,-7.3566,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,DPC,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,DUK,VACS,16.8261,0.1130,13.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDDY,EDDY,16.9024,0.2469,13.0944,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,8.2484,0.0277,4.6596,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-24.0000,-0.0717,-27.4893,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,17.6896,-0.0247,14.1533,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE.SLCC,EDESTL4391_PLT,14.1829,0.0056,10.6162,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,13.5041,0.0149,9.9282,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,5.0731,-0.0518,1.5639,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_EC_01,EDELAR3821UN1_RA,8.2484,0.0277,4.6596,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_EC_02,EDELAR3821UN2_RA,8.2484,0.0277,4.6596,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_EC_03,EDELAR3821UN3_RA,8.2484,0.0277,4.6596,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_EC_04,EDELAR3821UN4_RA,8.2484,0.0277,4.6596,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_EDE,EDE_LA,15.6688,0.0761,12.0317,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_ERW,EDEERWFUNG1_RA,-23.3936,-0.2116,-26.7430,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-12.8765,-0.2521,-16.1855,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,33.1600,0.1759,29.4231,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,33.1600,0.1759,29.4231,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,33.1600,0.1759,29.4231,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,33.1600,0.1759,29.4231,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,19.1127,0.1205,15.4311,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_RIV_10,EDERIV1671UN10_RA,15.2021,-0.0136,11.6546,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_RIV_11,EDERIV1671UN11_RA,15.2021,-0.0136,11.6546,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_RIV_12,EDERIV453UN12_PLT,15.1281,-0.0875,11.6546,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_SL_01,EDESTL4391UN1_RA,14.1829,0.0056,10.6162,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EDE_SWMP,EDE_SWMP_LA,2.2821,0.1038,-1.3827,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EEI,EEI,13.8083,0.0812,10.1661,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,EES,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-16.5425,-0.2123,-19.8912,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,ERCOTE,ERCOTE,24.9785,0.1717,21.2457,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,ERCOTN,ERCOTN,-11.1315,-0.2272,-14.4654,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,-4.4917,-0.1482,-7.9045,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,FMPP,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,FPC,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,FPL,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,FREM_50T,OPPDFREM_GUN1_RA,-1.6005,-0.0972,-5.0643,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,FREM_6,OPPDFREM_AUN6_RA,-1.6044,-0.0982,-5.0672,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,FREM_7,OPPDFREM_AUN7_RA,-1.6044,-0.0982,-5.0672,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,FREM_8,OPPDFREM_AUN8_RA,-1.6167,-0.1105,-5.0672,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,FREM_LOAD,FREM_LOAD_LA,-1.6064,-0.1002,-5.0672,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-22.8517,-0.1910,-26.2217,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,24.2335,0.2015,20.4710,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-18.6226,-0.3938,-21.7899,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-38.7231,-0.3151,-41.9690,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,21.2411,0.0716,17.6085,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,21.2411,0.0716,17.6085,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,21.2411,0.0716,17.6085,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,23.8686,0.0417,20.2659,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,23.8686,0.0417,20.2659,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,24.0227,0.0404,20.4212,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,24.0227,0.0404,20.4212,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-28.6931,-0.2790,-31.9752,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,41.2900,-0.0107,37.7397,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,41.2900,-0.0107,37.7397,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,41.2900,-0.0107,37.7397,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.VOLT.0130,V130_DDR,24.3633,0.0799,20.7223,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA.VOLT.0237,V237_DDR,24.9376,0.0571,21.3195,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDAHUB2,GRDAHUB2_H,8.6614,-0.0462,5.1466,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDAHUB3,GRDAHUB3_H,4.0489,-0.0764,0.5642,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA_GRDA,GRDA_LA,25.1837,0.0546,21.5681,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA_HUB,GRDA_H,15.2591,-0.0065,11.7046,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRDA_HUBSA,GRDASA_H,14.5640,-0.0106,11.0135,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GRE,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-10.7158,0.1742,-14.4510,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GSEC_SPS,SPS_GSEC_LA,7.8568,-0.0309,4.3267,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,GSPR2014HUB,GSPR2014HUB_H,1.1193,-0.0731,-2.3687,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GSPR2015HUB,GSPR2015HUB_H,1.1980,-0.0777,-2.2854,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-10.4659,-0.2027,-13.8243,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,HARRISON,CSWSLEBROCKPLT1,24.4825,0.1806,20.7409,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,HAST_TNSK_HUB,HAST_TNSK_H,-2.4111,-0.1628,-5.8094,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,HQST,PJM,9.2413,0.0343,5.6460,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,HST,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,-3.2323,0.0219,-6.8152,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,-3.2323,0.0219,-6.8152,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,-3.2736,0.0194,-6.8540,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,-3.2736,0.0194,-6.8540,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,-3.1868,0.0216,-6.7694,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,-3.1868,0.0216,-6.7694,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,INDN_INDN,INDN_LA,-3.2405,0.0211,-6.8226,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-12.3597,-0.2533,-15.6675,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,ISNE,PJM,9.2413,0.0343,5.6460,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,JEA,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,-1.4431,-0.0949,-4.9092,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,-1.4431,-0.0949,-4.9092,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-7.1045,-0.0486,-10.6170,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KACYCT4,KACYNEARMANUNCT4_RA,-4.6426,0.0015,-8.2051,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,42.9500,-0.0194,39.4084,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,-4.6426,0.0015,-8.2051,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,-4.6219,0.0049,-8.1878,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,-4.6266,0.0045,-8.1921,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KACY_KACY,KACY_LA,-4.6212,0.0043,-8.1865,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,-4.0185,-0.0134,-7.5661,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,0.5201,0.1044,-3.1453,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-29.4060,-0.1298,-32.8372,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-49.6984,-0.2923,-52.9671,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.VOLT.0222,V222_DDR,-3.7832,-0.0351,-7.3091,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.VOLT.0223,V223_DDR,-4.5318,-0.0389,-8.0539,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.VOLT.0241,V241_DDR,2.1630,0.0931,-1.4912,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.VOLT.0243,V243_DDR,13.1392,0.0055,9.5727,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.VOLT.0247,V247_DDR,-3.8290,-0.0149,-7.3752,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.VOLT.0253,V253_DDR,-3.9927,-0.0124,-7.5414,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-13.5385,-0.2759,-16.8236,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,-6.4940,-0.0743,-9.9807,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,-6.4940,-0.0743,-9.9807,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,-6.4940,-0.0743,-9.9807,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,-6.4940,-0.0743,-9.9807,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,-4.0051,-0.0139,-7.5522,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,-4.0051,-0.0139,-7.5522,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHUB,KCPLHUB_H,-10.2000,-0.1557,-13.6053,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHUB17,KCPLHUB17_H,-10.9125,-0.1708,-14.3028,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHUB18,KCPLHUB18_H,-10.5650,-0.1700,-13.9561,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHUB19,KCPLHUB19_H,-10.6788,-0.1628,-14.0770,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHUB20,KCPLHUB20_H,-11.2824,-0.1754,-14.6680,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHUB21,KCPLHUB21_H,-11.2154,-0.1708,-14.6057,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHUB22,KCPLHUB22_H,-10.6066,-0.1695,-13.9982,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHUB23,KCPLHUB23_H,-11.1930,-0.1747,-14.5793,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLHUB24,KCPLHUB24_H,-11.6568,-0.1815,-15.0363,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,-4.9670,-0.0433,-8.4848,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,-4.9670,-0.0433,-8.4848,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,-5.8402,-0.1190,-9.2823,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,-5.8402,-0.1190,-9.2823,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,-4.0185,-0.0134,-7.5661,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,-4.0185,-0.0134,-7.5661,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,-4.2070,-0.0057,-7.7623,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,-4.2070,-0.0057,-7.7623,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,-4.2070,-0.0057,-7.7623,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,-4.2070,-0.0057,-7.7623,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,-4.2070,-0.0057,-7.7623,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,-4.2070,-0.0057,-7.7623,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,-4.2070,-0.0057,-7.7623,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,-4.2070,-0.0057,-7.7623,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,-12.2219,-0.0687,-15.7142,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,-3.8704,-0.0113,-7.4201,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KCPL_KCPL,KCPL_LA,-4.7473,-0.0184,-8.2900,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KENN,KENN_LA,20.0656,0.1158,16.3887,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KEP2_SECI,KEP2_SECI_LA,-18.1628,-0.2292,-21.4946,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KERR_1,GRDAKERR_HYDUN1_RA,24.3521,0.0527,20.7384,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KERR_2,GRDAKERR_HYDUN2_RA,24.0985,0.0548,20.4827,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KERR_3,GRDAKERR_HYDUN3_RA,24.0985,0.0548,20.4827,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KERR_4,GRDAKERR_HYDUN4_RA,24.3521,0.0527,20.7384,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,-6.4940,-0.0744,-9.9807,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,-6.4940,-0.0744,-9.9807,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,-6.2012,-0.0584,-9.7038,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,-6.2012,-0.0584,-9.7038,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,-8.2808,-0.0709,-11.7709,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,-9.7923,-0.0653,-13.2880,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,-9.7923,-0.0653,-13.2880,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-16.6698,-0.2407,-19.9901,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-16.6698,-0.2407,-19.9901,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-16.6698,-0.2407,-19.9901,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-13.9396,-0.2047,-17.2960,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-13.9396,-0.2047,-17.2960,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-16.7471,-0.2460,-20.0621,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-14.3131,-0.1961,-17.6780,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-12.5733,-0.1385,-15.9958,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,36.9424,-0.0195,33.4008,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,36.9424,-0.0195,33.4008,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-7.1438,-0.1022,-10.6026,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-7.1438,-0.1022,-10.6026,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-7.1438,-0.1022,-10.6026,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-14.7327,-0.2250,-18.0687,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-14.8912,-0.3320,-18.1202,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,-6.6537,-0.1408,-10.0739,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-6.5648,-0.0378,-10.0880,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LAFA,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,LAM345,LAM345,-17.0392,-0.2841,-20.3161,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LEPA,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,-0.8675,-0.1127,-4.3159,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_LES,LES_LA,-0.9114,-0.1141,-4.3584,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,-0.8855,-0.1149,-4.3316,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,-0.9887,-0.1216,-4.4281,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,-0.9887,-0.1216,-4.4281,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,-0.9887,-0.1216,-4.4281,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,-0.8853,-0.1148,-4.3316,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,-0.8855,-0.1149,-4.3316,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_WAVERLY,LES_WAVERLY_H,-0.9615,-0.1180,-4.4045,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,-1.2293,-0.1152,-4.6751,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,-1.2293,-0.1152,-4.6751,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,LGEE,LGEE,11.4066,0.0575,7.7880,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MALDEN,MALDEN_LA,19.0502,0.1107,15.3785,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MCWEST,MCWEST,2.9186,0.0420,-0.6844,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MDU,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-3.5894,-0.0254,-7.1250,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,-3.5731,-0.0825,-7.0516,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,-1.4125,0.0319,-5.0054,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MEAN_NPPD,NPPD_MEAN_LA,-3.7019,-0.1950,-7.0680,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MEC,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MHEB,MHEB,2.4581,0.0243,-1.1272,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-10.4730,-0.2209,-13.8132,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-14.6183,-0.2626,-17.9168,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-10.4730,-0.2209,-13.8132,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-10.4730,-0.2209,-13.8132,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-14.6183,-0.2626,-17.9168,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-18.3173,-0.2095,-21.6689,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MISO,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-18.1217,-0.1832,-21.4996,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-18.1217,-0.1832,-21.4996,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-9.6786,-0.1582,-13.0814,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-17.9464,-0.3405,-21.1670,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-14.5165,-0.2485,-17.8290,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-18.7297,-0.5143,-21.7765,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-17.9630,-0.3402,-21.1838,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-18.8440,-0.4802,-21.9249,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-17.8313,-0.2402,-21.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-17.8313,-0.2402,-21.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-17.8313,-0.2402,-21.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-17.8313,-0.2402,-21.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-17.8313,-0.2402,-21.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,0.6812,-0.0135,-2.8663,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,12.1764,0.0703,8.5451,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,12.1764,0.0703,8.5451,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,7.6896,0.0385,4.0901,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,2.8683,0.1092,-0.8020,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MOWR,AECI,13.7779,0.0475,10.1694,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,5.5218,0.0238,1.9370,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,12.1974,0.0722,8.5641,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-2.2022,-0.1906,-5.5726,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-2.5257,-0.1154,-5.9713,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-20.7895,-0.2823,-24.0682,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-2.1923,-0.1808,-5.5726,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,-3.8307,-0.0352,-7.3566,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,-3.8307,-0.0352,-7.3566,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,-3.8305,-0.0349,-7.3566,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,-3.8305,-0.0349,-7.3566,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,-3.7832,-0.0351,-7.3091,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,-3.7832,-0.0351,-7.3091,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,-3.7832,-0.0351,-7.3091,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,-3.7928,-0.0448,-7.3091,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,-3.7832,-0.0351,-7.3091,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,-3.7832,-0.0351,-7.3091,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,-3.7832,-0.0351,-7.3091,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,4.5142,0.0724,0.8808,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,-3.2522,-0.0346,-6.7787,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,-4.2990,-0.0445,-7.8155,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,-4.2990,-0.0445,-7.8155,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,-4.2989,-0.0445,-7.8155,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,-4.1299,-0.0115,-7.6794,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,-4.1299,-0.0115,-7.6794,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MPS_MPS,MPS_LA,-2.3606,0.0009,-5.9225,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MSTNG,SPSMSTNGPLT1,16.5769,0.1320,12.8839,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MSTNG4,SPSMSTNGUN4_RA,16.5592,0.1143,12.8839,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MSTNG5,SPSMSTNGUN5_RA,16.5769,0.1320,12.8839,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,16.5769,0.1320,12.8839,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NBSO,PJM,9.2413,0.0343,5.6460,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,-1.7834,-0.1649,-5.1795,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,-1.7838,-0.1653,-5.1795,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-12.0769,-0.2887,-15.3492,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NHC1,VACS,16.8261,0.1130,13.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,-1.4488,-0.1019,-4.9080,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,-1.4488,-0.1019,-4.9080,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,-1.4488,-0.1019,-4.9080,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-4.1181,-0.2029,-7.4762,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,-2.9285,-0.2662,-6.2233,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,-1.8397,-0.1695,-5.2313,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-5.1334,-0.1673,-8.5271,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,-2.9285,-0.2662,-6.2233,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.HUB.PY2018,NPPDPY18_H,-3.6835,-0.1792,-7.0653,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,-3.5943,-0.1790,-6.9763,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,-3.6418,-0.1777,-7.0251,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,-3.5667,-0.1760,-6.9518,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-6.7862,-0.1740,-10.1732,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-4.6622,-0.1470,-8.0762,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-4.6622,-0.1470,-8.0762,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-5.7509,-0.1912,-9.1207,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-6.7862,-0.1740,-10.1732,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,1.8909,-0.2699,-1.4003,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,-3.3606,-0.2745,-6.6471,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-7.2538,-0.1617,-10.6531,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,-3.3606,-0.2745,-6.6471,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,-2.5554,-0.2590,-5.8575,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-3.7838,-0.2317,-7.1131,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,-1.4631,-0.0959,-4.9283,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,-2.9285,-0.2662,-6.2233,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-6.8360,-0.1651,-10.2319,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-4.6622,-0.1470,-8.0762,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-4.6622,-0.1470,-8.0762,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-4.1868,-0.1306,-7.6173,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-4.2320,-0.1301,-7.6629,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-4.2320,-0.1301,-7.6629,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,-3.7923,-0.1017,-7.2516,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-4.3066,-0.1090,-7.7586,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,-2.8247,-0.2188,-6.1669,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-4.0371,-0.1606,-7.4375,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-5.4652,-0.0941,-8.9322,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-6.3436,-0.0973,-9.8074,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.NELI.DDR,NELI_DDR,-6.0133,-0.2121,-9.3622,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.NPPM.1058,SH1058_DDR,6.2391,-0.0985,2.7766,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,-3.6935,-0.1229,-7.1317,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,-2.9285,-0.2662,-6.2233,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,-1.8397,-0.1695,-5.2313,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-6.7862,-0.1740,-10.1732,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.TECH.1,KEARNE_DDR,-3.3926,-0.0886,-6.8650,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,-1.0361,-0.2905,-4.3067,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,-1.0361,-0.2905,-4.3067,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-6.7235,-0.2001,-10.0845,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD.VOLT.0236,V236_DDR,-2.2139,-0.0953,-5.6797,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD2017HUB,NPPD2017HUB_H,-3.6742,-0.1787,-7.0565,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,4.9816,-0.1693,1.5899,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-4.1181,-0.2029,-7.4762,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,-3.2778,-0.3283,-6.5106,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,-3.2778,-0.3283,-6.5106,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,-2.0667,-0.1012,-5.5265,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,-2.2114,-0.0928,-5.6797,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-5.1860,-0.1734,-8.5737,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-4.0919,-0.1371,-7.5158,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,6.1759,-0.1618,2.7766,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,6.1759,-0.1618,2.7766,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,6.1759,-0.1618,2.7766,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,-2.4069,-0.1622,-5.8058,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,-1.9939,-0.1705,-5.3844,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,-2.6687,-0.1563,-6.0735,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-4.5639,-0.3771,-7.7478,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-4.5449,-0.3581,-7.7478,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-5.2767,-0.1728,-8.6649,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-5.4854,-0.1759,-8.8705,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,-1.6937,-0.1496,-5.1051,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,-1.6963,-0.1523,-5.1051,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,-1.6963,-0.1523,-5.1051,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,-1.7483,-0.1472,-5.1621,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,1.8909,-0.2699,-1.4003,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,-1.8128,-0.1470,-5.2269,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,-1.3931,-0.1348,-4.8194,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,-2.4090,-0.1559,-5.8141,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,-2.4122,-0.1575,-5.8157,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,-2.4118,-0.1561,-5.8168,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,-2.4118,-0.1561,-5.8168,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,-2.4069,-0.1622,-5.8058,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,-2.4135,-0.1687,-5.8058,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,-2.9109,-0.0574,-6.4145,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,-2.4772,-0.1235,-5.9148,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-5.2753,-0.1623,-8.6741,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,-3.2174,-0.3343,-6.4441,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-7.5468,-0.1753,-10.9326,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,6.2867,-0.0509,2.7766,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-6.0133,-0.2121,-9.3622,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-5.0997,-0.1659,-8.4949,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-5.0997,-0.1659,-8.4949,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_NPPD,NPPD_LA,-0.8664,-0.1391,-4.2883,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,-1.3931,-0.1348,-4.8194,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,-1.3931,-0.1348,-4.8194,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,-4.0208,-0.1610,-7.4208,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-3.8506,-0.2035,-7.2081,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NSB,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NSP,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,NSSO,PJM,9.2413,0.0343,5.6460,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,NYIS,PJM,9.2413,0.0343,5.6460,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-18.8758,-0.3453,-22.0915,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-28.1316,-0.2923,-31.4004,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-35.5069,-0.2691,-38.7989,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-35.5069,-0.2691,-38.7989,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-20.6545,-0.3656,-23.8500,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-38.7231,-0.3151,-41.9690,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-98.0099,-0.1957,-101.3752,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-50.9516,-0.2833,-54.2293,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-30.0000,-0.2792,-33.2818,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-28.4568,-0.2918,-31.7260,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-14.6263,-0.1252,-18.0622,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-30.0000,-0.2792,-33.2818,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-20.1489,-0.3638,-23.3462,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-18.3173,-0.2095,-21.6689,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-18.2788,-0.3455,-21.4943,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,-21.2596,-0.0628,-24.7578,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-28.4568,-0.2918,-31.7260,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-23.4344,-0.2650,-26.7305,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-21.1827,-0.2893,-24.4544,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-17.4552,-0.2210,-20.7952,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-22.6915,-0.0656,-26.1870,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-18.3173,-0.2095,-21.6689,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-18.3173,-0.2095,-21.6689,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-28.4568,-0.2918,-31.7260,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-17.1258,-0.1777,-20.5091,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.NUEN.LAM1,LAM1_DDR,24.1096,0.2201,20.3284,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-14.6263,-0.1252,-18.0622,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-14.6263,-0.1252,-18.0622,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-17.7272,-0.1810,-21.1072,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-14.7944,-0.1360,-18.2194,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-14.7944,-0.1360,-18.2194,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-14.7944,-0.1360,-18.2194,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-14.8637,-0.1237,-18.3010,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-14.8637,-0.1237,-18.3010,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-14.7944,-0.1360,-18.2194,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-14.7944,-0.1360,-18.2194,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-28.4568,-0.2918,-31.7260,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,30.7700,0.1559,27.0531,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-20.1489,-0.3638,-23.3462,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-17.2726,-0.1291,-20.7045,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-23.4344,-0.2650,-26.7305,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,22.1071,0.1618,18.3842,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-19.1606,-0.2178,-22.5039,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-19.1606,-0.2178,-22.5039,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-19.1606,-0.2178,-22.5039,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-19.1606,-0.2178,-22.5039,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-36.7836,-0.3956,-39.9491,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-30.2719,-0.2722,-33.5607,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-28.1316,-0.2923,-31.4004,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-33.3463,-0.2625,-36.6448,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-33.3463,-0.2625,-36.6448,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-17.7184,-0.0676,-21.2118,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-18.3845,-0.2381,-21.7075,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-18.3845,-0.2381,-21.7075,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-18.3845,-0.2381,-21.7075,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0033,FOSTER_DDR,-13.6774,-0.1161,-17.1223,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,7.8085,0.0589,4.1886,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0035,TARBY_DDR,23.8643,0.1798,20.1234,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,7.8085,0.0589,4.1886,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,5.7479,0.0163,2.1705,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,5.7479,0.0163,2.1705,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-17.3810,-0.0807,-20.8613,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0040,TROSPER_DDR,-13.4893,-0.1133,-16.9370,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,-13.8132,-0.1143,-17.2599,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,22.5040,0.1830,18.7600,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0115,V115_DDR,-14.5587,-0.1238,-17.9960,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0116,V116_DDR,-22.0557,-0.0470,-25.5698,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0118,V118_DDR,-26.4289,-0.0257,-29.9642,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0125,V125_DDR,22.3547,0.2106,18.5830,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0126,V126_DDR,20.8067,0.0996,17.1461,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0129,V129_DDR,-11.8976,-0.1898,-15.2688,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,-14.1230,-0.1386,-17.5455,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0134,V134_DDR,22.1787,0.1298,18.4879,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0138,V138_DDR,19.9389,0.0834,16.2944,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,-14.3473,-0.1315,-17.7768,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0143,V143_DDR,11.3358,0.0305,7.7442,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0149,V149_DDR,-16.2104,-0.1930,-19.5785,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0150,V150_DDR,-16.0266,-0.1926,-19.3950,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0155,V155_DDR,19.2488,0.0664,15.6213,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0156,V156_DDR,-14.1230,-0.1386,-17.5455,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0166,V166_DDR,20.7116,0.1785,16.9720,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,-14.1762,-0.1287,-17.6086,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-16.0266,-0.1926,-19.3950,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0170,V170_DDR,-17.9161,-0.1795,-21.2977,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-15.5659,-0.1903,-18.9367,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0176,V176_DDR,-16.0266,-0.1926,-19.3950,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0177,V177_DDR,-25.7955,-0.3302,-29.0263,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,-14.0651,-0.1231,-17.5030,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-19.8729,-0.2457,-23.1882,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0195,V195_DDR,105.8186,0.1515,102.1060,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0197,V197_DDR,18.6821,0.1040,15.0171,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0198,V198_DDR,20.7116,0.1785,16.9720,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0208,V208_DDR,106.0000,0.1547,102.2843,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0209,V209_DDR,106.0000,0.1547,102.2843,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,19.5178,0.0724,15.8843,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0216,V216_DDR,-13.8945,-0.1147,-17.3409,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0219,V219_DDR,19.2488,0.0664,15.6213,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0220,V220_DDR,-16.0266,-0.1926,-19.3950,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0224,V224_DDR,-14.6910,-0.1287,-18.1233,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0225,V225_DDR,-14.6908,-0.1285,-18.1233,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0226,V226_DDR,-14.6910,-0.1287,-18.1233,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0227,V227_DDR,-14.6910,-0.1287,-18.1233,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0229,V229_DDR,-17.2743,-0.0710,-20.7644,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0231,V231_DDR,-17.2335,-0.0258,-20.7687,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0238,V238_DDR,-35.5275,-0.3152,-38.7733,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.VOLT.0242,V242_DDR,19.5329,0.0748,15.8971,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-29.9766,-0.4081,-33.1295,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-18.3173,-0.2095,-21.6689,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-27.8015,-0.2800,-31.0826,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-18.2757,-0.3424,-21.4943,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-29.9766,-0.4081,-33.1295,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-16.1516,-0.3716,-19.3410,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-56.1979,-0.2744,-59.4845,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEHL7,OKGEHL7_H,-10.6701,-0.1072,-14.1239,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEHL8,OKGEHSL1UN8_RA,-10.6701,-0.1072,-14.1239,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEHL910,OKGEHSL1PLT2,-10.6701,-0.1072,-14.1239,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-17.4711,-0.3581,-20.6741,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEMCC,OKGEMCCLAIPLT1,-14.6519,-0.1560,-18.0569,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,16.5002,0.0494,12.8898,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,16.5002,0.0494,12.8898,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,16.5002,0.0494,12.8898,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,-10.0595,-0.1479,-13.4727,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,-10.0595,-0.1479,-13.4727,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,-10.0595,-0.1479,-13.4727,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,-10.0595,-0.1479,-13.4727,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGESM1,OKGESEMINOLEUN1_RA,-12.7701,-0.0778,-16.2533,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGESM2,OKGESEMINOLEUN2_RA,-8.9538,-0.0859,-12.4290,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGESM3,OKGESEMINOLEUN3_RA,-8.9538,-0.0859,-12.4290,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGESO1,OKGESONR1UN1_RA,-59.2202,-0.2472,-62.5340,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGESO2,OKGESONR1UN2_RA,-33.3463,-0.2625,-36.6448,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-17.4984,-0.3854,-20.6741,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-21.9216,-0.3978,-25.0849,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGETINK5A,OKGETINK5UN1_RA,-12.8988,-0.1150,-16.3449,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGETINK5B,OKGETINK5UN2_RA,-12.8988,-0.1150,-16.3449,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-18.3420,-0.3119,-21.5911,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-28.1316,-0.2923,-31.4004,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,22.8279,0.2492,19.0177,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-18.3173,-0.2095,-21.6689,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE_OKGE,OKGE_LA,-7.4873,-0.0638,-10.9845,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-17.2726,-0.1291,-20.7045,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-18.3531,-0.3230,-21.5911,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMLP,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,24.3069,0.0302,20.7157,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,22.7209,0.2290,18.9308,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-16.3905,-0.1184,-19.8332,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-97.9889,-0.1747,-101.3752,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-21.4160,-0.2830,-24.6940,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-30.0000,-0.2792,-33.2818,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-27.2697,-0.3221,-30.5087,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-12.4614,-0.2544,-15.7681,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,155.0000,-0.0020,151.4410,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-97.9938,-0.1796,-101.3752,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-97.9938,-0.1796,-101.3752,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_SPP,OMPA_SPP_LA,-24.1070,-0.1624,-27.5057,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-29.9766,-0.4081,-33.1295,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,20.7812,0.0264,17.1937,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,20.7812,0.0264,17.1937,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,20.7812,0.0264,17.1937,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,20.7812,0.0264,17.1937,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,ONT,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,-1.5020,-0.1043,-4.9588,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,-1.5020,-0.1043,-4.9588,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,-1.5020,-0.1043,-4.9588,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,-1.5020,-0.1043,-4.9588,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,-1.5020,-0.1043,-4.9588,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,-1.5020,-0.1043,-4.9588,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,-1.5020,-0.1043,-4.9588,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,-1.5020,-0.1043,-4.9588,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,-1.5020,-0.1043,-4.9588,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,-1.4515,-0.0991,-4.9134,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,-1.4488,-0.1019,-4.9080,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,-1.3828,-0.0732,-4.8706,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,-1.4037,-0.0916,-4.8732,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,-1.4037,-0.0916,-4.8732,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD_GLDN,OPPD_GLDN_LA,-1.4226,-0.0993,-4.8843,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,-1.4722,-0.1005,-4.9327,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,1.8909,-0.2699,-1.4003,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,-2.3272,-0.1362,-5.7521,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,-1.4491,-0.1016,-4.9085,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD_OPPD,OPPD_LA,-1.4433,-0.0938,-4.9105,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,-1.4070,-0.0878,-4.8802,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,-1.4055,-0.0889,-4.8777,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OTP,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,OVEC,OVEC,10.5282,0.0488,6.9184,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PARAGOULD,PARAGOULD_LA,21.8491,0.1240,18.1641,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,23.2808,0.0279,19.6919,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,23.2808,0.0279,19.6919,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,23.2808,0.0279,19.6919,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,23.1584,0.0405,19.5569,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,23.1584,0.0405,19.5569,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,23.1584,0.0405,19.5569,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PIGGOTT,PIGGOTT_LA,19.7034,0.1140,16.0284,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PJM,PJM,9.2413,0.0343,5.6460,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PLUM,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,POPLARBLUFF,POPLARBLUFF_LA,18.9187,0.0999,15.2578,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,2.8383,-0.0061,-0.7166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,2.8383,-0.0061,-0.7166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,2.9165,-0.0055,-0.6390,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,2.9165,-0.0055,-0.6390,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,3.2675,0.2291,-0.5226,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,3.2675,0.2291,-0.5226,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,2.9251,0.0389,-0.6749,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,2.4527,-0.0821,-1.0262,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-23.4700,-0.1975,-26.8335,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,71.0459,0.0126,67.4723,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,-3.1968,-0.0122,-6.7456,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-15.6549,-0.0261,-19.1898,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,30.1621,0.0972,26.5039,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,19.2431,0.1083,15.5738,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,0.2871,-0.1141,-3.1598,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,2.9484,0.0570,-0.6697,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,-0.7240,-0.1690,-4.1160,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,9.1400,0.1960,5.3830,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,2.9602,0.0659,-0.6667,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,-0.1816,-0.0965,-3.6461,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,PUPP,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,RCEAST,RCEAST,0.2344,-0.0847,-3.2419,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SALINA_1,GRDASALINA1UN1_RA,24.3525,0.0530,20.7384,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SALINA_2,GRDASALINA1UN2_RA,24.3525,0.0530,20.7384,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SALINA_3,GRDASALINA1UN3_RA,24.3525,0.0530,20.7384,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SALINA_4,GRDASALINA1UN4_RA,24.3525,0.0530,20.7384,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SALINA_5,GRDASALINA1UN5_RA,24.3525,0.0530,20.7384,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SALINA_6,GRDASALINA1UN6_RA,24.3525,0.0530,20.7384,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SARPY_1,OPPDSARPYUN1_RA,-1.4532,-0.1007,-4.9136,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SARPY_2,OPPDSARPYUN2_RA,-1.4487,-0.0947,-4.9150,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SARPY_3,OPPDSARPYUN3_RA,-1.4361,-0.1057,-4.8914,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SARPY_4,OPPDSARPYUN4_RA,-1.4361,-0.1057,-4.8914,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SARPY_5,OPPDSARPYUN5_RA,-1.4361,-0.1057,-4.8914,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SC,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SCEG,VACS,16.8261,0.1130,13.1521,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SCSE,SCSE,-4.7856,-0.1288,-8.2179,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SEC,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-18.9689,-0.3396,-22.1903,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-18.9689,-0.3396,-22.1903,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-18.9689,-0.3396,-22.1903,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-16.9163,-0.1607,-20.3166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-18.9689,-0.3396,-22.1903,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-17.5298,-0.3203,-20.7706,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-17.2839,-0.3520,-20.4929,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-17.2839,-0.3520,-20.4929,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-17.8316,-0.2406,-21.1521,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-20.1177,-0.3115,-23.3672,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-13.9530,-0.2180,-17.2960,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-17.4411,-0.1855,-20.8166,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-12.5076,-0.2260,-15.8426,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-18.6172,-0.3411,-21.8372,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-12.4029,-0.2259,-15.7380,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-18.0225,-0.3204,-21.2632,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-17.8690,-0.2630,-21.1670,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-16.7440,-0.2553,-20.0498,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-16.7440,-0.2553,-20.0498,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-16.7440,-0.2553,-20.0498,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-16.7440,-0.2553,-20.0498,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-16.9266,-0.2724,-20.2153,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-17.5298,-0.3203,-20.7706,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI_SECI,SECI_LA,-16.7270,-0.2224,-20.0656,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-12.3597,-0.2533,-15.6675,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-12.3597,-0.2533,-15.6675,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-17.8316,-0.2406,-21.1521,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SEHA,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-18.3531,-0.3230,-21.5911,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SERU,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SETH,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SGE,SGE,-3.8683,-0.1110,-7.3183,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SMEP,MISO,10.3872,0.0457,6.7804,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SOCO,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPA,SPA,32.2451,0.1350,28.5490,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPC,SPC,3.2263,0.1296,-0.4643,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPPNORTH_HUB,SPPNORTH_H,-1.1500,-0.1123,-4.5988,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-14.3190,-0.1828,-17.6973,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,12.5282,0.1112,8.8560,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,12.5282,0.1112,8.8560,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,12.3601,0.1073,8.6918,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,12.3601,0.1073,8.6918,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_NIXA,SPRM_NIXA_LA,12.9396,0.1161,9.2624,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_SPRM,SPRM_LA,12.3759,0.1205,8.6943,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,12.5401,0.0955,8.8836,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,12.5401,0.0955,8.8836,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,12.5341,0.0895,8.8836,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,12.5401,0.0955,8.8836,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,17.5214,0.0482,13.9122,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,19.1102,-0.0594,15.6085,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-12.3068,-0.2009,-15.6669,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-12.3068,-0.2009,-15.6669,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,16.5453,-0.1926,13.1768,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,16.4979,-0.0327,12.9696,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,17.3613,-0.4000,14.2002,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,16.9399,0.2882,13.0906,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,16.0984,-0.0533,12.5907,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,16.6408,0.1390,12.9407,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,16.6714,0.1658,12.9445,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,16.6714,0.1658,12.9445,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,16.6408,0.1390,12.9407,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-12.2293,-0.1624,-15.6279,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,19.1102,-0.0594,15.6085,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-12.3667,-0.1911,-15.7366,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-17.4045,-0.3500,-20.6156,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-14.2259,-0.1827,-17.6043,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-12.7635,-0.1239,-16.2007,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-13.0662,-0.1936,-16.4337,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-21.3212,-0.3619,-24.5203,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-21.3212,-0.3619,-24.5203,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-21.3212,-0.3619,-24.5203,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-21.3212,-0.3619,-24.5203,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GRID.WRAB,WRAB_DDR,-11.0900,-0.1240,-14.5270,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-21.3212,-0.3619,-24.5203,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,15.7337,-0.0457,12.2184,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,15.7337,-0.0457,12.2184,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,14.8064,-0.0420,11.2874,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,14.8064,-0.0420,11.2874,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,14.8064,-0.0420,11.2874,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,15.7337,-0.0457,12.2184,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-10.4692,-0.1934,-13.8368,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-10.4701,-0.1935,-13.8376,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-10.4654,-0.1935,-13.8330,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-12.0769,-0.2887,-15.3492,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,16.6310,0.1344,12.9355,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,16.0881,-0.0562,12.5832,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,16.0881,-0.0562,12.5832,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,16.0881,-0.0562,12.5832,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,16.0881,-0.0562,12.5832,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,16.6165,0.1398,12.9157,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,16.6265,0.1261,12.9394,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,16.6265,0.1261,12.9394,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-18.3346,-0.3045,-21.5911,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-10.8444,-0.1941,-14.2113,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-10.8444,-0.1941,-14.2113,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-10.5343,-0.1930,-13.9024,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-11.0900,-0.1240,-14.5270,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-16.8847,-0.2970,-20.1488,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-13.1280,-0.2077,-16.4813,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-20.6545,-0.3656,-23.8500,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-10.7973,-0.1470,-14.2113,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.PLANTX1,SPS.PLANTX1_H,18.1786,0.0256,14.5920,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.PLANTX2,SPS.PLANTX2_H,18.1786,0.0256,14.5920,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,17.9940,0.0210,14.4119,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,16.4689,-0.1340,13.0418,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-19.1671,-0.3347,-22.3935,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,17.4506,-0.3107,14.2002,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,16.4775,-0.1253,13.0418,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-12.2303,-0.1634,-15.6279,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,17.3475,0.0737,13.7127,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,16.9399,0.2882,13.0906,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,17.3475,0.0737,13.7127,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,16.9400,0.2874,13.0916,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-36.4673,-0.2208,-39.8076,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,16.9100,0.3698,12.9792,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,16.9245,0.3843,12.9792,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,16.8780,0.3512,12.9657,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,16.6685,0.1682,12.9393,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,16.9356,0.3385,13.0361,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-17.0392,-0.2841,-20.3161,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-11.0822,-0.1398,-14.5034,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,17.6960,0.0342,14.1008,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,17.6960,0.0342,14.1008,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,17.3475,0.0737,13.7127,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,16.1380,-0.0360,12.6130,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,16.6813,0.2294,12.8908,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,17.9758,0.1935,14.2212,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,17.9792,0.1073,14.3109,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,18.2272,-0.0550,14.7212,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,16.9100,0.3698,12.9792,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,17.0170,0.4378,13.0181,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,16.9692,0.3901,13.0181,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,16.5024,-0.1004,13.0418,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,17.8640,0.1050,14.1980,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-18.6803,-0.3210,-21.9204,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-18.6744,-0.3261,-21.9094,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0163,V163_DDR,-10.3429,-0.1525,-13.7515,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0168,V168_DDR,-15.9636,-0.1929,-19.3317,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0180,V180_DDR,17.0170,0.4378,13.0181,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0181,V181_DDR,-18.9177,-0.2870,-22.1917,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0182,V182_DDR,16.9405,0.3460,13.0335,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0199,V199_DDR,16.6537,0.1988,12.8938,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0200,V200_DDR,16.7511,0.2336,12.9564,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.VOLT.0235,V235_DDR,-16.8847,-0.2970,-20.1488,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,17.3613,-0.4000,14.2002,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,16.9399,0.2882,13.0906,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-10.4874,-0.2241,-13.8243,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-10.8569,-0.1701,-14.2479,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS_SPS,SPS_LA,9.7333,0.1497,6.0225,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,17.2423,0.0697,13.6115,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SSCN_NPPD,SSCN_NPPD_LA,-4.2434,-0.1576,-7.6468,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,16.4330,0.0954,12.7765,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,16.4330,0.0954,12.7765,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,TAL,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,TEC,SOUC,17.2121,0.1201,13.5310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,-3.2174,-0.3343,-6.4441,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,TVA,TVA,16.4165,0.1055,12.7500,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,UCUHUB,UCUHUB_H,-6.9073,-0.0948,-10.3735,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,UCUHUB17,UCUHUB17_H,-10.5102,-0.1739,-13.8974,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,UCUHUB18,UCUHUB18_H,-7.8236,-0.1484,-11.2362,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,UCUHUB19,UCUHUB19_H,-11.4763,-0.1646,-14.8727,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,UCUHUB20,UCUHUB20_H,-11.5037,-0.1573,-14.9075,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,UCUHUB21,UCUHUB21_H,-13.0445,-0.1808,-16.4248,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,UCUHUB22,UCUHUB22_H,-12.5721,-0.1884,-15.9447,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,UCUHUB23,UCUHUB23_H,-12.8665,-0.1902,-16.2373,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,UCUHUB24,UCUHUB24_H,-10.4354,-0.1658,-13.8307,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,3.2683,0.1667,-0.4594,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,3.2683,0.1667,-0.4594,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,3.1947,-0.0647,-0.3016,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,3.1947,-0.0647,-0.3016,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,2.8712,-0.0867,-0.6032,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,2.8886,-0.0365,-0.6359,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,2.8886,-0.0365,-0.6359,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,3.2683,0.1667,-0.4594,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,2.8143,-0.0770,-0.6698,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,3.0871,0.0566,-0.5306,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,-0.5315,-0.1615,-3.9310,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,0.5792,-0.3115,-2.6704,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,3.2189,0.1586,-0.5007,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,3.2189,0.1586,-0.5007,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,7.1146,-0.3535,3.9070,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,-3.2932,-0.1370,-6.7173,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,6.2277,-0.0107,2.6774,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,-0.8973,-0.1692,-4.2891,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,-0.5717,-0.1355,-3.9973,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,-1.4665,-0.1546,-4.8729,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,7.3000,-0.1680,3.9070,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,7.3000,-0.1680,3.9070,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,6.1787,-0.1174,2.7351,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,1.0436,-0.3000,-2.2174,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,-0.4803,-0.0856,-3.9558,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,3.1516,0.0335,-0.4429,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,3.1516,0.0335,-0.4429,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,3.1516,0.0335,-0.4429,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,3.1956,0.0688,-0.4343,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,3.1956,0.0688,-0.4343,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,3.1956,0.0688,-0.4343,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,3.3066,0.2141,-0.4686,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,3.1134,-0.0644,-0.3833,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,3.1932,-0.0682,-0.2996,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-4.3241,-0.1204,-7.7647,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,-0.2994,-0.1183,-3.7421,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,3.0809,0.0525,-0.5326,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,-2.5504,-0.1720,-5.9395,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,0.7319,-0.3555,-2.4736,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,7.2035,-0.1254,3.7678,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,3.2633,0.1675,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,3.2633,0.1675,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,3.2631,0.1673,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,3.2633,0.1675,-0.4653,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,3.2479,0.1325,-0.4456,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,3.2479,0.1325,-0.4456,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,3.2479,0.1325,-0.4456,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,3.2479,0.1325,-0.4456,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,3.2479,0.1325,-0.4456,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,3.2479,0.1325,-0.4456,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,3.2479,0.1325,-0.4456,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,-1.4698,-0.2954,-4.7354,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,2.9497,-0.0202,-0.5911,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,-1.7303,-0.1170,-5.1743,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,-1.7303,-0.1170,-5.1743,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,-2.8108,-0.2012,-6.1706,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,-2.8108,-0.2012,-6.1706,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,3.1501,-0.0276,-0.3833,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,2.8163,-0.0301,-0.7147,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,-0.7280,-0.2208,-4.0682,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,1.1396,-0.2569,-2.1645,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,0.6133,-0.0761,-2.8716,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,2.8712,-0.0867,-0.6032,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,2.8712,-0.0867,-0.6032,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,-0.8973,-0.1692,-4.2891,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,0.2194,-0.0887,-3.2530,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,5.2067,-0.1398,1.7855,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,1.0849,-0.2588,-2.2174,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,-10.0000,-0.1517,-13.4093,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.FSE,WAUE.FSE_H,-2.4154,-0.1881,-5.7884,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,3.0064,0.0393,-0.5940,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,2.9881,0.0379,-0.6109,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,-0.5475,-0.3214,-3.7872,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,-0.1794,-0.2998,-3.4406,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,2.9973,-0.0729,-0.4908,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,2.9188,-0.0886,-0.5537,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-15.5300,-0.3338,-18.7572,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,0.5792,-0.3115,-2.6704,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-12.0000,-0.0705,-15.4905,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,-0.7592,-0.1244,-4.1958,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,-0.7592,-0.1244,-4.1958,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,-0.7590,-0.1242,-4.1958,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,5.1977,-0.1266,1.7632,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,0.2194,-0.0887,-3.2530,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,0.1651,-0.0763,-3.3197,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,-0.9392,-0.1756,-4.3247,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,-0.4766,-0.0818,-3.9558,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,-0.3748,0.0146,-3.9504,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,-0.4550,-0.1222,-3.8939,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,1.7235,-0.0533,-1.7842,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,-0.6738,-0.1286,-4.1063,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,-0.7777,-0.1991,-4.1397,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,-2.5504,-0.1720,-5.9395,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,2.2409,0.0410,-1.3611,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,-0.9027,-0.1727,-4.2910,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,2.1643,0.0241,-1.4208,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,-0.0741,-0.0831,-3.5520,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,-1.2293,-0.1152,-4.6751,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NTWK,WAUE.NTWK_H,1.2516,-0.0750,-2.2344,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,1.9406,0.0857,-1.7061,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,1.9406,0.0857,-1.7061,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,0.6412,-0.3524,-2.5674,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,-1.3479,-0.3860,-4.5229,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,-1.0784,-0.1098,-4.5297,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,0.6412,-0.3524,-2.5674,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,2.6600,-0.0120,-0.8891,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,3.3588,-0.1557,-0.0466,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,-2.5504,-0.1720,-5.9395,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,2.9437,-0.0554,-0.5620,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,3.1072,-0.4072,-0.0466,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,-0.1428,-0.2289,-3.4749,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,0.3785,-0.2220,-2.9606,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,3.1935,-0.0714,-0.2961,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,-0.6095,-0.3135,-3.8570,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,1.7071,-0.0676,-1.7864,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,2.5543,-0.2090,-0.7978,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,1.1396,-0.2569,-2.1645,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.VOLT.0152,V152_DDR,3.3367,0.2539,-0.4783,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE.VOLT.0172,V172_DDR,3.2584,0.1481,-0.4507,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_BEPM,WAUE_BEPM_LA,2.4875,0.0516,-1.1251,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,-0.0180,-0.0968,-3.4823,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,-0.3773,0.0164,-3.9547,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_EWA,WAUE_EWA_LA,0.2646,-0.0754,-3.2211,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,1.4765,-0.1669,-1.9176,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_HMMU,WAUE_HMMU_LA,-0.9189,-0.0401,-4.4399,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,1.8061,-0.0630,-1.6919,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_MECB,WAUE_MECB_LA,-0.8820,-0.0166,-4.4264,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_MMPA,WAUE_MMPA_LA,2.6950,0.0726,-0.9387,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_MRES,WAUE_MRES_LA,0.9372,-0.0795,-2.5444,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,3.2355,0.1816,-0.5071,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,3.0064,0.0393,-0.5940,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,0.9056,-0.1591,-2.4964,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_OTP,WAUE_OTP_LA,3.1285,0.1531,-0.5857,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_OTPW,WAUE_OTPW_LA,3.8749,0.0535,0.2603,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM,WAUE_UGPM_LA,1.3755,-0.0746,-2.1109,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,2.3119,0.0025,-1.2516,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,-0.6151,-0.1131,-4.0631,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,1.1009,-0.1266,-2.3335,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,0.2646,-0.0754,-3.2211,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,-0.9189,-0.0401,-4.4399,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,1.2865,-0.1797,-2.0949,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,3.0064,0.0393,-0.5940,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,2.6950,0.0726,-0.9387,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,0.3948,-0.0574,-3.1088,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,0.5603,-0.1862,-2.8146,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,3.0867,0.1820,-0.6564,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-29.8352,-0.3690,-33.0273,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-26.1727,-0.3714,-29.3623,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,-6.0564,-0.2099,-9.4075,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,96.7521,0.0745,93.1165,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,96.7521,0.0745,93.1165,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-14.6130,-0.3702,-17.8039,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,86.3966,0.0955,82.7400,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,74.3900,0.0918,70.7372,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,11.5700,-0.2140,8.2230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,11.5700,-0.2140,8.2230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,11.5700,-0.2140,8.2230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,11.5700,-0.2140,8.2230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,11.5700,-0.2140,8.2230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,11.5700,-0.2140,8.2230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,11.5700,-0.2140,8.2230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,11.5700,-0.2140,8.2230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,3.6020,-0.2025,0.2435,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-20.6545,-0.3656,-23.8500,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-26.1498,-0.3355,-29.3754,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-27.5216,-0.3482,-30.7345,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,17.4261,-0.3351,14.2002,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_ENMC,WFEC_ENMC_LA,16.9921,0.1837,13.2474,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-28.4568,-0.2918,-31.7260,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,33.5332,0.0662,29.9060,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,16.6043,0.1210,12.9223,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-29.8352,-0.3690,-33.0273,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-29.8352,-0.3690,-33.0273,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-29.8352,-0.3690,-33.0273,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_OKGE,WFEC_OKGE_LA,-13.5941,-0.0306,-17.1245,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,16.7071,0.0798,13.0663,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-20.1228,-0.3177,-23.3662,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-15.0114,-0.3959,-18.1765,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_WFEC,WFEC_LA,5.3456,-0.0964,1.8810,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,16.6043,0.1210,12.9223,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-11.2891,-0.2257,-14.6245,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-15.4015,-0.2700,-18.6926,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-11.8523,-0.1558,-15.2576,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-11.8523,-0.1558,-15.2576,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-11.8523,-0.1558,-15.2576,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-11.8523,-0.1558,-15.2576,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-11.8523,-0.1558,-15.2576,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-11.8523,-0.1558,-15.2576,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-11.8523,-0.1558,-15.2576,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,-2.5089,0.0578,-6.1278,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-12.4977,-0.2134,-15.8453,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-25.2237,-0.2759,-28.5089,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-25.2237,-0.2759,-28.5089,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-25.2237,-0.2759,-28.5089,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-20.4118,-0.3162,-23.6566,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-20.4118,-0.3162,-23.6566,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-21.4154,-0.2593,-24.7171,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-21.4154,-0.2593,-24.7171,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-21.4154,-0.2593,-24.7171,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-12.4977,-0.2134,-15.8453,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,-5.6046,-0.0466,-9.1191,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-16.2897,-0.2144,-19.6363,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-16.2897,-0.2145,-19.6363,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-16.2897,-0.2145,-19.6363,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-16.2895,-0.2143,-19.6363,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,-5.6046,-0.0466,-9.1191,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-18.0706,-0.3433,-21.2884,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-41.9000,-0.1162,-45.3448,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.JEC.1,WRJEFFUN10_RA,-9.9809,-0.1338,-13.4081,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.JEC.2,WRJEFFUN11_RA,-9.8561,-0.1341,-13.2831,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.JEC.3,WRJEFFUN12_RA,-9.8609,-0.1389,-13.2831,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-28.6931,-0.2790,-31.9752,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-20.7868,-0.2796,-24.0682,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-20.7868,-0.2796,-24.0682,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.LEC.4,WRLECUN26_RA,-7.1482,-0.0621,-10.6471,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.LEC.5,WRLECUN27_RA,-7.6966,-0.0549,-11.2028,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-14.9052,-0.1977,-18.2685,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-14.9052,-0.1977,-18.2685,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-14.9052,-0.1977,-18.2685,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-14.8761,-0.1904,-18.2467,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-12.3597,-0.2533,-15.6675,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-12.3597,-0.2533,-15.6675,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-12.5235,-0.1988,-15.8857,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-10.9560,-0.2126,-14.3044,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-10.9560,-0.2126,-14.3044,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-14.8929,-0.3338,-18.1202,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-12.3597,-0.2533,-15.6675,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-6.3336,-0.1116,-9.7831,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-12.8765,-0.2521,-16.1855,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-20.7881,-0.2809,-24.0682,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,73.9564,0.0957,70.2997,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-14.9175,-0.4711,-18.0074,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-11.8523,-0.1558,-15.2576,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-15.1416,-0.2839,-18.4187,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,-5.6046,-0.0466,-9.1191,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-12.4977,-0.2134,-15.8453,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-23.3702,-0.2337,-26.6976,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.THAYERLD,WR.THAYERLD_LA,20.0431,0.1076,16.3745,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-24.1591,-0.2306,-27.4896,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0106,V106_DDR,-23.3393,-0.2267,-26.6736,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-5.6825,-0.0277,-9.2158,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-13.4023,-0.1910,-16.7723,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-6.9986,-0.0390,-10.5207,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-6.9986,-0.0390,-10.5207,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-6.0128,-0.0385,-9.5354,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-22.8581,-0.1951,-26.2240,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0157,V157_DDR,-7.0501,-0.0420,-10.5691,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0158,V158_DDR,-6.9986,-0.0390,-10.5207,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-6.9986,-0.0390,-10.5207,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-23.5612,-0.2415,-26.8807,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0173,V173_DDR,-14.8758,-0.2266,-18.2102,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0174,V174_DDR,-23.3049,-0.2242,-26.6417,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0184,V184_DDR,-22.8862,-0.2443,-26.2029,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-23.4999,-0.2313,-26.8296,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0186,V186_DDR,-23.4010,-0.2395,-26.7225,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-23.0814,-0.2389,-26.4035,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-24.0555,-0.2275,-27.3891,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-16.3019,-0.1706,-19.6923,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-12.8997,-0.1377,-16.3230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-12.1421,-0.1458,-15.5573,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-12.1421,-0.1458,-15.5573,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-12.8997,-0.1377,-16.3230,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0245,V245_DDR,-23.5068,-0.2313,-26.8366,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.VOLT.0248,V248_DDR,-23.3393,-0.2267,-26.6736,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-26.0890,-0.2641,-29.3859,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-8.0181,-0.0707,-11.5084,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.WOLF,WRWOLFUN15_RA,-15.9419,-0.3019,-19.2010,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-18.0706,-0.3433,-21.2884,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,-2.5246,0.0421,-6.1278,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-25.2237,-0.2759,-28.5089,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-25.2237,-0.2759,-28.5089,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-25.2237,-0.2759,-28.5089,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-25.2237,-0.2759,-28.5089,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-22.6435,-0.1864,-26.0181,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-13.3387,-0.1915,-16.7082,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-24.4980,-0.2324,-27.8266,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-24.4980,-0.2324,-27.8266,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-24.4980,-0.2324,-27.8266,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-24.4980,-0.2324,-27.8266,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-11.9854,-0.1257,-15.4208,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-11.9854,-0.1257,-15.4208,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-11.9854,-0.1257,-15.4208,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-11.9854,-0.1257,-15.4208,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-11.9854,-0.1257,-15.4208,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-11.9854,-0.1257,-15.4208,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-38.1982,-0.2295,-41.5298,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-38.1982,-0.2295,-41.5298,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-40.6789,-0.2372,-44.0027,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-40.6789,-0.2372,-44.0027,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_MIDW,WR_MIDW_LA,-13.2703,-0.2302,-16.6012,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,2.0060,0.0666,-1.6217,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,-2.8246,-0.0069,-6.3787,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-14.7865,-0.2224,-18.1252,3.5611\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_SEG,WR_SEG_LA,-4.5558,0.0210,-8.1378,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,WR_WR,WR_LA,-14.2055,-0.1525,-17.6140,3.5610\n03/19/2025 05:00:00,03/19/2025 10:00:00,YAD,VACS,16.8261,0.1130,13.1521,3.5610\n03/19/2025 06:00:00,03/19/2025 11:00:00,AEC,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AECC_CSWS,CSWS_AECC_LA,27.2309,0.3193,19.7066,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,24.4167,0.2409,16.9708,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,29.1153,0.4375,21.4728,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,24.3356,0.1792,16.9514,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,30.0158,0.2241,22.5867,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,28.1427,0.1845,20.7532,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,30.0440,0.1156,22.7234,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AECI,AECI,19.2590,0.1321,11.9219,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AEPM_CSWS,CSWS_LA,27.7941,0.2339,20.3552,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ALTW,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,AMRN,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,8.4724,-0.2496,1.5171,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,BBA,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BCA,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BEPM.ER01.DDR,ER01_DDR,3.8585,-0.3755,-2.9710,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BEPM_ER01,BEPM_ER01_LA,3.8585,-0.3755,-2.9710,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,2.1933,-0.0203,-4.9913,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-0.9457,-0.0227,-8.1280,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BEPM_UM01,BEPM_UM01_LA,6.9353,0.3273,-0.5970,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BLKW,BLKW,9.6478,-0.0044,2.4472,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-25.0000,-0.7229,-31.4821,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-25.0000,-0.7229,-31.4821,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,14.7744,-0.6089,8.1783,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-24.9918,-0.7147,-31.4821,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BRAZ,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BUBA,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-14.4765,-0.6480,-21.0335,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-14.6931,-0.4724,-21.4256,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-14.6931,-0.4724,-21.4256,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-14.6931,-0.4724,-21.4256,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-14.6931,-0.4724,-21.4256,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-14.6931,-0.4724,-21.4256,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-27.4616,-0.3675,-34.2991,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,4.0008,-0.1471,-3.0571,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,4.0008,-0.1471,-3.0571,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CLEC,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,26.5831,0.1626,19.2156,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,COWP,COWP_LA,27.3220,0.2319,19.8851,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,27.3220,0.2319,19.8851,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,27.3220,0.2319,19.8851,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CPLE,VACS,23.6736,0.2542,16.2144,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CPLW,VACS,23.6736,0.2542,16.2144,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,27.2843,0.3041,19.7752,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,27.2843,0.3041,19.7752,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,27.2843,0.3041,19.7752,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,27.2843,0.3041,19.7752,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CRTH_SPA,WRCRTH_SPA_LA,15.9208,0.1289,8.5869,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,29.8263,0.5862,22.0351,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-4.1228,-0.4147,-10.9131,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,30.0440,0.1156,22.7234,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,24.3356,0.1792,16.9514,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,29.8247,0.5829,22.0368,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,29.6944,0.3982,22.0912,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,29.8040,0.5256,22.0734,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,29.8040,0.5256,22.0734,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,24.1204,0.2101,16.7053,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,24.1204,0.2101,16.7053,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,24.1204,0.2101,16.7053,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,24.1204,0.2101,16.7053,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,30.0440,0.1156,22.7234,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,32.2052,0.4429,24.5573,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,47.4632,-0.0508,40.3090,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,47.3969,-0.1171,40.3090,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,30.1975,0.0503,22.9423,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,26.0069,0.0608,18.7412,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,26.0069,0.0608,18.7412,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,26.0089,0.0607,18.7432,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,26.0089,0.0607,18.7432,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-17.9921,-0.5229,-24.6742,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,-2.0323,-0.3731,-8.8641,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,37.9046,0.0729,30.6267,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-14.6696,-0.6184,-21.2562,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-14.6438,-0.5926,-21.2562,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-9.0413,-0.3587,-15.8876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.GRID.CDL1,CDL1_DDR,31.8602,0.1130,24.5422,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-7.2454,-0.4107,-14.0397,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-2.4079,-0.4352,-9.1776,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,31.8602,0.1130,24.5422,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.NUEN.CSI1,CSI1_DDR,28.0051,0.1999,20.6002,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.NUEN.CSI2,CSI2_DDR,28.0073,0.2021,20.6002,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,26.5874,0.1668,19.2156,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.NUEN.GAZA,GAZA_DDR,31.8602,0.1130,24.5422,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,99.5770,0.2585,92.1135,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.NUEN.T201,NT201_DDR,27.0900,0.0902,19.7948,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-6.8393,-0.5275,-13.5168,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-6.8393,-0.5275,-13.5168,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,30.0440,0.1156,22.7234,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,30.1051,0.6260,22.2741,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-9.0413,-0.3587,-15.8876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-9.0413,-0.3587,-15.8876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-13.3773,-0.4750,-20.1073,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-14.6438,-0.5926,-21.2562,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,29.5186,0.3714,21.9422,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,23.2749,0.0160,16.0539,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,23.1738,-0.0851,16.0539,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,23.1762,-0.0827,16.0539,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,5.8694,-0.0252,-1.3104,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,5.8694,-0.0252,-1.3104,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,29.7152,0.3847,22.1255,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,27.3467,0.0679,20.0738,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,29.7095,0.3866,22.1179,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,30.2421,0.7834,22.2537,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,33.3855,0.1671,26.0134,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,28.0073,0.2021,20.6002,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0057,OKMU_DDR,29.4857,0.1375,22.1433,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0060,LEHIGH_DDR,99.5770,0.2585,92.1135,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0086,WARRENM_DDR,26.4546,0.0857,19.1639,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,30.1825,0.5999,22.3776,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,38.3874,0.1026,31.0798,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0121,V121_DDR,29.7152,0.3847,22.1255,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0122,V122_DDR,36.7773,0.0946,29.4777,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0124,V124_DDR,57.2540,0.0519,49.9971,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0135,V135_DDR,27.4774,0.0952,20.1772,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0144,V144_DDR,-2.0862,-0.3392,-8.9520,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0145,V145_DDR,-2.1711,-0.3715,-9.0046,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,29.7348,0.3979,22.1319,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,30.1740,0.2134,22.7556,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0175,V175_DDR,26.5874,0.1668,19.2156,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,30.1740,0.2134,22.7556,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,30.2334,0.2584,22.7701,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,27.4774,0.0952,20.1772,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,27.8565,0.0876,20.5639,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,27.4773,0.0753,20.1970,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,43.2430,0.0145,36.0235,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,26.1049,0.0563,18.8436,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,27.8565,0.0876,20.5639,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0211,V211_DDR,29.7700,0.4722,22.0928,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,39.2418,0.1008,31.9360,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0213,V213_DDR,27.2784,0.0852,19.9882,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0215,V215_DDR,37.9041,0.0976,30.6015,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0217,V217_DDR,39.3093,0.0953,32.0090,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0218,V218_DDR,42.7727,0.0206,35.5471,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0228,V228_DDR,27.9590,0.0606,20.6934,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0232,V232_DDR,26.7947,0.0939,19.4958,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0233,V233_DDR,27.9793,0.0932,20.6811,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0240,V240_DDR,34.2446,0.0602,26.9794,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0244,V244_DDR,27.8565,0.0876,20.5639,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0246,MDT1_DDR,99.5770,0.2585,92.1135,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0249,V249_DDR,27.2175,0.0912,19.9213,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0250,V250_DDR,-4.6821,-0.3967,-11.4904,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0251,V251_DDR,26.5404,0.0724,19.2630,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.VOLT.0252,V252_DDR,43.2430,0.0145,36.0235,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-20.0823,-0.4847,-26.8026,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,10.1396,-0.5359,3.4705,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-16.2097,-0.7512,-22.6634,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,29.5993,0.2870,22.1073,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-24.2000,-0.7660,-30.6390,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-21.5381,-0.5030,-28.2400,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-21.5381,-0.5030,-28.2400,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-21.5381,-0.5030,-28.2400,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-21.5381,-0.5030,-28.2400,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-21.5381,-0.5030,-28.2400,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,30.0440,0.1156,22.7234,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,29.4919,0.5916,21.6953,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,26.7861,0.0853,19.4958,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,26.7753,0.0745,19.4958,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,32.3891,0.1602,25.0239,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,32.3891,0.1602,25.0239,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWWELSH1,CSWSWELSHUN1_RA,29.8241,0.3014,22.3177,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWWELSH3,CSWSWELSHUN3_RA,29.8241,0.3014,22.3177,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWWILKES1,CSWSWILKESUN1_RA,29.9719,0.4109,22.3560,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWWILKES2,CSWSWILKESUN2_RA,29.9719,0.4109,22.3560,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,CSWWILKES3,CSWSWILKESUN3_RA,29.8468,0.3877,22.2541,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-14.6401,-0.5889,-21.2562,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,DENL,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,DERS,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,DOE,DOE,20.5372,0.1970,13.1352,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,2.0319,-0.0119,-5.1612,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,DPC,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,DUK,VACS,23.6736,0.2542,16.2144,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDDY,EDDY,16.4427,0.3879,8.8498,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,12.4783,0.0919,5.1814,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-33.6500,-0.1153,-40.7397,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,22.7008,-0.0161,15.5119,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE.SLCC,EDESTL4391_PLT,19.0248,0.0519,11.7679,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,18.3208,0.0712,11.0447,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,8.9254,-0.0621,1.7826,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_EC_01,EDELAR3821UN1_RA,12.4783,0.0919,5.1814,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_EC_02,EDELAR3821UN2_RA,12.4783,0.0919,5.1814,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_EC_03,EDELAR3821UN3_RA,12.4783,0.0919,5.1814,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_EC_04,EDELAR3821UN4_RA,12.4783,0.0919,5.1814,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_EDE,EDE_LA,21.0011,0.1991,13.5971,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_ERW,EDEERWFUNG1_RA,-26.6008,-0.3941,-33.4117,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-9.5333,-0.4668,-16.2714,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,42.7100,0.3944,35.1106,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,42.7100,0.3944,35.1106,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,42.7100,0.3944,35.1106,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,42.7100,0.3944,35.1106,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,26.4436,0.2692,18.9694,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_RIV_10,EDERIV1671UN10_RA,20.0846,0.0128,12.8668,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_RIV_11,EDERIV1671UN11_RA,20.0846,0.0128,12.8668,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_RIV_12,EDERIV453UN12_PLT,19.9456,-0.1262,12.8668,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_SL_01,EDESTL4391UN1_RA,19.0248,0.0519,11.7679,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EDE_SWMP,EDE_SWMP_LA,6.6600,0.2628,-0.8078,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EEI,EEI,20.4800,0.1961,13.0789,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EES,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-13.8928,-0.4030,-20.6948,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ERCOTE,ERCOTE,29.8241,0.3014,22.3177,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ERCOTN,ERCOTN,-6.8069,-0.4951,-13.5168,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,0.3882,-0.2293,-6.5875,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FMPP,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FPC,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FPL,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FREM_50T,OPPDFREM_GUN1_RA,3.9760,-0.1254,-3.1036,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FREM_6,OPPDFREM_AUN6_RA,3.9732,-0.1277,-3.1041,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FREM_7,OPPDFREM_AUN7_RA,3.9732,-0.1277,-3.1041,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FREM_8,OPPDFREM_AUN8_RA,3.9448,-0.1561,-3.1041,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FREM_LOAD,FREM_LOAD_LA,3.9686,-0.1323,-3.1041,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-22.2129,-0.3674,-29.0505,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,29.5186,0.3714,21.9422,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-15.4716,-0.8891,-21.7875,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-37.3361,-0.6303,-43.9108,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,26.5831,0.1626,19.2156,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,26.5831,0.1626,19.2156,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,26.5831,0.1626,19.2156,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,29.0545,0.1052,21.7443,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,29.0545,0.1052,21.7443,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,29.2168,0.1027,21.9091,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,29.2168,0.1027,21.9091,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-28.2187,-0.5547,-34.8690,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,46.3520,-0.0256,39.1726,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,46.3520,-0.0256,39.1726,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,46.3520,-0.0256,39.1726,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.VOLT.0130,V130_DDR,29.6556,0.1809,22.2697,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA.VOLT.0237,V237_DDR,30.2355,0.1357,22.8948,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDAHUB2,GRDAHUB2_H,12.9612,-0.0863,5.8425,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDAHUB3,GRDAHUB3_H,8.0179,-0.1490,0.9619,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA_GRDA,GRDA_LA,30.4598,0.1278,23.1270,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA_HUB,GRDA_H,20.0133,-0.0028,12.8112,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRDA_HUBSA,GRDASA_H,19.3053,-0.0108,12.1111,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GRE,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-5.6927,0.1972,-13.0948,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,GSEC_SPS,SPS_GSEC_LA,3.5520,-0.1871,-3.4658,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,GSPR2014HUB,GSPR2014HUB_H,2.0245,-0.2630,-4.9175,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,GSPR2015HUB,GSPR2015HUB_H,2.3288,-0.2704,-4.6057,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-5.3404,-0.5349,-12.0105,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,HARRISON,CSWSLEBROCKPLT1,29.6022,0.3163,22.0809,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,HAST_TNSK_HUB,HAST_TNSK_H,1.4493,-0.2630,-5.4927,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,HQST,PJM,15.5570,0.1053,8.2467,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,HST,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,2.4901,0.1150,-4.8299,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,2.4901,0.1150,-4.8299,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,2.4504,0.1108,-4.8654,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,2.4504,0.1108,-4.8654,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,2.5350,0.1148,-4.7848,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,2.5350,0.1148,-4.7848,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,INDN_INDN,INDN_LA,2.4826,0.1140,-4.8364,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-9.1895,-0.4800,-15.9145,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ISNE,PJM,15.5570,0.1053,8.2467,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,JEA,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,4.0468,-0.1191,-3.0391,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,4.0468,-0.1191,-3.0391,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-1.9610,-0.0354,-9.1306,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KACYCT4,KACYNEARMANUNCT4_RA,1.0219,0.0737,-6.2568,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,49.1311,-0.0019,41.9280,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,1.0219,0.0737,-6.2568,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,1.0496,0.0801,-6.2355,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,1.0442,0.0800,-6.2408,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KACY_KACY,KACY_LA,1.0512,0.0800,-6.2338,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,1.6562,0.0410,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,6.2754,0.2740,-1.2036,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-25.6034,-0.1930,-32.6154,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-49.8667,-0.5632,-56.5085,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.VOLT.0222,V222_DDR,1.6139,-0.0013,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.VOLT.0223,V223_DDR,1.3717,-0.0180,-5.8153,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.VOLT.0241,V241_DDR,7.8027,0.2372,0.3605,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.VOLT.0243,V243_DDR,18.1279,0.0491,10.8738,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.VOLT.0247,V247_DDR,1.9989,0.0353,-5.2413,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.VOLT.0253,V253_DDR,1.6834,0.0430,-5.5646,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-8.7954,-0.5263,-15.4741,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,-0.6290,-0.0936,-7.7404,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,-0.6290,-0.0936,-7.7404,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,-0.6290,-0.0936,-7.7404,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,-0.6290,-0.0936,-7.7404,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,1.6692,0.0399,-5.5757,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,1.6692,0.0399,-5.5757,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHUB,KCPLHUB_H,-5.6896,-0.2752,-12.6194,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHUB17,KCPLHUB17_H,-6.8062,-0.3098,-13.7014,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHUB18,KCPLHUB18_H,-6.3922,-0.3050,-13.2922,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHUB19,KCPLHUB19_H,-6.5357,-0.2889,-13.4518,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHUB20,KCPLHUB20_H,-7.2996,-0.3182,-14.1864,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHUB21,KCPLHUB21_H,-7.0861,-0.3097,-13.9814,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHUB22,KCPLHUB22_H,-6.2532,-0.3061,-13.1521,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHUB23,KCPLHUB23_H,-7.1311,-0.3158,-14.0202,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLHUB24,KCPLHUB24_H,-7.6523,-0.3322,-14.5251,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,0.3703,-0.0197,-6.8150,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,0.3703,-0.0197,-6.8150,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,1.4710,-0.1932,-5.5408,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,1.4710,-0.1932,-5.5408,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,1.6562,0.0410,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,1.6562,0.0410,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,1.4750,0.0576,-5.7876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,1.4750,0.0576,-5.7876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,1.4750,0.0576,-5.7876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,1.4750,0.0576,-5.7876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,1.4750,0.0576,-5.7876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,1.4750,0.0576,-5.7876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,1.4750,0.0576,-5.7876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,1.4750,0.0576,-5.7876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,-6.8723,-0.0756,-14.0017,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,1.7512,0.0403,-5.4941,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KCPL_KCPL,KCPL_LA,0.9740,0.0286,-6.2596,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KENN,KENN_LA,27.7851,0.2616,20.3185,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KEP2_SECI,KEP2_SECI_LA,-15.7375,-0.6148,-22.3278,7.2051\n03/19/2025 06:00:00,03/19/2025 11:00:00,KERR_1,GRDAKERR_HYDUN1_RA,29.6111,0.1276,22.2785,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KERR_2,GRDAKERR_HYDUN2_RA,29.3444,0.1311,22.0083,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KERR_3,GRDAKERR_HYDUN3_RA,29.3444,0.1311,22.0083,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KERR_4,GRDAKERR_HYDUN4_RA,29.6111,0.1276,22.2785,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,-0.6290,-0.0936,-7.7404,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,-0.6290,-0.0936,-7.7404,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,-0.3581,-0.0585,-7.5046,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,-0.3581,-0.0585,-7.5046,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,-2.5217,-0.0842,-9.6424,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,-4.2159,-0.0694,-11.3515,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,-4.2159,-0.0694,-11.3515,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-14.0256,-0.5565,-20.6741,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-14.0256,-0.5565,-20.6741,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-14.0256,-0.5565,-20.6741,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-11.0342,-0.3950,-17.8442,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-11.0342,-0.3950,-17.8442,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-14.1237,-0.5708,-20.7578,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-11.4522,-0.3933,-18.2639,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-9.0200,-0.2311,-15.9939,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,42.8813,-0.0050,35.6813,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,42.8813,-0.0050,35.6813,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-2.3756,-0.1436,-9.4370,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-2.3756,-0.1436,-9.4370,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-2.3756,-0.1436,-9.4370,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-12.0401,-0.4811,-18.7640,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-12.1768,-0.6461,-18.7357,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,-2.4219,-0.2339,-9.3930,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-1.3030,-0.0113,-8.4967,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LAFA,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LAM345,LAM345,-14.4765,-0.6480,-21.0335,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LEPA,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,3.6364,-0.1517,-3.4169,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_LES,LES_LA,3.6294,-0.1553,-3.4203,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,3.7754,-0.1582,-3.2713,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,3.5146,-0.1712,-3.5192,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,3.5146,-0.1712,-3.5192,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,3.5146,-0.1712,-3.5192,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,3.7757,-0.1580,-3.2713,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,3.7754,-0.1582,-3.2713,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_WAVERLY,LES_WAVERLY_H,3.7161,-0.1651,-3.3238,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,4.2557,-0.1642,-2.7851,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,4.2557,-0.1642,-2.7851,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,LGEE,LGEE,17.8744,0.1502,10.5192,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MALDEN,MALDEN_LA,26.5773,0.2520,19.1203,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MCWEST,MCWEST,6.4982,0.1200,-0.8267,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,MDU,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,0.0916,-0.0172,-7.0962,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,1.4451,-0.0814,-5.6785,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,3.9654,0.1629,-3.4024,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,MEAN_NPPD,NPPD_MEAN_LA,0.4177,-0.3412,-6.4460,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,MEC,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MHEB,MHEB,7.5631,0.0681,0.2900,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-7.2625,-0.4217,-14.0458,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-11.9337,-0.5566,-18.5821,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-7.2625,-0.4217,-14.0458,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-7.2625,-0.4217,-14.0458,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-11.9337,-0.5566,-18.5821,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-15.7312,-0.4579,-22.4783,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MISO,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-15.5004,-0.4658,-22.2396,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-15.5004,-0.4658,-22.2396,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-5.8186,-0.2523,-12.7713,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-15.8435,-0.8394,-22.2091,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-11.8156,-0.5169,-18.5037,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-16.9187,-1.1382,-22.9855,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-15.8675,-0.7264,-22.3461,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-17.0307,-1.0607,-23.1750,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-15.6532,-0.4910,-22.3672,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-15.6532,-0.4910,-22.3672,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-15.6532,-0.4910,-22.3672,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-15.6532,-0.4910,-22.3672,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-15.6532,-0.4910,-22.3672,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,6.3133,0.0297,-0.9214,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,18.5774,0.1777,11.1947,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,18.5774,0.1777,11.1947,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,13.6800,0.1189,6.3561,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,8.6204,0.2716,1.1438,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MOWR,AECI,19.2590,0.1321,11.9219,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,10.8202,0.0967,3.5185,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,18.4353,0.1818,11.0484,7.2051\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,3.0171,-0.3291,-3.8588,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,2.9266,-0.1732,-4.1052,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-19.3507,-0.5561,-25.9996,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,3.0383,-0.3079,-3.8588,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,2.0343,-0.0094,-5.1612,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,2.0343,-0.0094,-5.1612,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,2.0348,-0.0090,-5.1612,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,2.0348,-0.0090,-5.1612,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,1.6139,-0.0013,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,1.6139,-0.0013,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,1.6139,-0.0013,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,1.5942,-0.0210,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,1.6139,-0.0013,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,1.6139,-0.0013,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,1.6139,-0.0013,-5.5898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,9.6309,0.1902,2.2357,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,2.5536,-0.0113,-4.6401,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,1.6086,-0.0311,-5.5653,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,1.6086,-0.0310,-5.5653,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,1.6087,-0.0310,-5.5653,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,1.4659,0.0466,-5.7857,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,1.4659,0.0466,-5.7857,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MPS_MPS,MPS_LA,3.1255,0.0609,-4.1404,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MSTNG,SPSMSTNGPLT1,9.8527,0.1956,2.4522,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,MSTNG4,SPSMSTNGUN4_RA,9.8171,0.1599,2.4522,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,MSTNG5,SPSMSTNGUN5_RA,9.8527,0.1956,2.4522,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,9.8527,0.1956,2.4522,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,NBSO,PJM,15.5570,0.1053,8.2467,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,3.3211,-0.2679,-3.6160,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,3.3203,-0.2687,-3.6160,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-7.6690,-0.7126,-14.1614,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NHC1,VACS,23.6736,0.2542,16.2144,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,4.0576,-0.1344,-3.0130,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,4.0576,-0.1344,-3.0130,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,4.0576,-0.1344,-3.0130,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,0.7951,-0.3421,-6.0678,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,0.9260,-0.4787,-5.8003,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,2.4944,-0.2771,-4.4335,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,2.0700,-0.2672,-4.8678,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,0.9260,-0.4787,-5.8003,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.HUB.PY2018,NPPDPY18_H,0.6420,-0.3140,-6.2490,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,0.7656,-0.3128,-6.1266,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,0.6870,-0.3104,-6.2076,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,0.7884,-0.3060,-6.1106,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,0.7691,-0.2788,-6.1571,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-0.9894,-0.2643,-7.9301,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-0.9894,-0.2643,-7.9301,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-2.1173,-0.3415,-8.9808,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,0.7691,-0.2788,-6.1571,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,5.2470,-0.4405,-1.5175,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,0.3970,-0.5036,-6.3044,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-3.8378,-0.3357,-10.7071,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,0.3970,-0.5036,-6.3044,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,1.3713,-0.4618,-5.3719,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-0.0060,-0.4226,-6.7884,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,2.9937,-0.1170,-4.0943,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,0.9260,-0.4787,-5.8003,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-3.3692,-0.3322,-10.2420,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-0.9894,-0.2643,-7.9301,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-0.9894,-0.2643,-7.9301,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-0.4689,-0.2210,-7.4529,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-0.5155,-0.2206,-7.4999,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-0.5155,-0.2206,-7.4999,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,0.0519,-0.1452,-7.0079,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,2.6287,-0.1454,-4.4309,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,1.1191,-0.3782,-5.7077,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,0.9988,-0.2518,-5.9543,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,1.8768,-0.1144,-5.2138,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,1.3145,-0.1183,-5.7721,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.NELI.DDR,NELI_DDR,0.9086,-0.3507,-5.9457,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.NPPM.1058,SH1058_DDR,7.9618,-0.1045,0.8613,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,0.1122,-0.1950,-6.8978,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,0.9260,-0.4787,-5.8003,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,2.4944,-0.2771,-4.4335,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,0.7691,-0.2788,-6.1571,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.TECH.1,KEARNE_DDR,0.4225,-0.1227,-6.6598,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,2.4887,-0.5195,-4.1968,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,2.4887,-0.5195,-4.1968,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,0.6172,-0.3281,-6.2597,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD.VOLT.0236,V236_DDR,2.3132,-0.1147,-4.7770,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD2017HUB,NPPD2017HUB_H,0.6551,-0.3130,-6.2369,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,7.1147,-0.2616,0.1713,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,0.7951,-0.3421,-6.0678,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,0.4480,-0.6139,-6.1431,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,0.4480,-0.6139,-6.1431,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,2.4571,-0.1274,-4.6205,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,2.3190,-0.1090,-4.7770,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,1.9865,-0.2760,-4.9425,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-0.3750,-0.2327,-7.3473,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,7.8229,-0.2434,0.8613,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,7.8229,-0.2434,0.8613,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,7.8229,-0.2434,0.8613,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,1.4596,-0.2620,-5.4834,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,3.0695,-0.2789,-3.8566,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,1.4034,-0.2457,-5.5558,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,0.1100,-0.6884,-6.4066,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,1.8682,-0.6495,-4.6872,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-1.6915,-0.3219,-8.5746,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-1.9238,-0.3286,-8.8001,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,2.0297,-0.2357,-4.9396,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,2.0243,-0.2411,-4.9396,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,2.0243,-0.2411,-4.9396,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,1.9850,-0.2303,-4.9897,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,5.2470,-0.4405,-1.5175,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,1.9281,-0.2300,-5.0469,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,3.1049,-0.1993,-3.9008,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,1.4518,-0.2485,-5.5047,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,1.4442,-0.2523,-5.5085,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,1.4436,-0.2490,-5.5124,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,1.4436,-0.2490,-5.5124,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,1.4596,-0.2620,-5.4834,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,1.4465,-0.2751,-5.4834,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,1.9234,-0.0347,-5.2469,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,1.7338,-0.1754,-5.2958,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-1.7008,-0.2966,-8.6092,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,2.0747,-0.5951,-4.5352,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-4.1588,-0.3628,-11.0010,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,8.0736,0.0073,0.8613,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,0.9086,-0.3507,-5.9457,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-1.4645,-0.3045,-8.3649,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-1.4645,-0.3045,-8.3649,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_NPPD,NPPD_LA,2.9881,-0.2157,-4.0012,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,3.1049,-0.1993,-3.9008,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,3.1049,-0.1993,-3.9008,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,0.3187,-0.2530,-6.6333,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,0.0857,-0.3702,-6.7491,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NSB,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NSP,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NSSO,PJM,15.5570,0.1053,8.2467,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,NYIS,PJM,15.5570,0.1053,8.2467,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-17.1400,-0.7496,-23.5954,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-26.6186,-0.6004,-33.2232,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-33.7975,-0.5450,-40.4575,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-33.7975,-0.5450,-40.4575,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-18.2311,-0.8295,-24.6066,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-37.3361,-0.6303,-43.9108,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-100.0448,-0.3933,-106.8565,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-50.6921,-0.5704,-57.3267,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-29.3483,-0.5578,-35.9954,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-27.0964,-0.5961,-33.7053,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-11.2259,-0.2743,-18.1566,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-29.3483,-0.5578,-35.9954,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-17.9271,-0.8148,-24.3173,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-15.7312,-0.4579,-22.4783,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-16.7835,-0.7367,-23.2517,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,-12.1245,-0.1514,-19.1781,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-27.0964,-0.5961,-33.7053,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-21.3452,-0.5506,-27.9996,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-18.2000,-0.5924,-24.8126,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-14.6931,-0.4724,-21.4256,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-21.3988,-0.1586,-28.4452,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-15.7312,-0.4579,-22.4783,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-15.7312,-0.4579,-22.4783,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-27.0964,-0.5961,-33.7053,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-13.8424,-0.4030,-20.6443,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.NUEN.LAM1,LAM1_DDR,30.1790,0.4452,22.5288,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-11.2259,-0.2743,-18.1566,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-11.2259,-0.2743,-18.1566,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-14.4965,-0.4073,-21.2942,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-11.4381,-0.2966,-18.3465,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-11.4381,-0.2966,-18.3465,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-11.4381,-0.2966,-18.3465,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-11.4867,-0.2719,-18.4198,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-11.4867,-0.2719,-18.4198,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-11.4381,-0.2966,-18.3465,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-11.4381,-0.2966,-18.3465,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-27.0964,-0.5961,-33.7053,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,41.0308,0.3380,33.4878,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-17.9271,-0.8148,-24.3173,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-15.3821,-0.2941,-22.2930,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-21.3452,-0.5506,-27.9996,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,28.5594,0.3392,21.0152,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-16.5892,-0.4612,-23.3330,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-16.5892,-0.4612,-23.3330,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-16.5892,-0.4612,-23.3330,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-16.5892,-0.4612,-23.3330,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-33.0821,-0.8036,-39.4835,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-28.8384,-0.5552,-35.4881,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-26.6186,-0.6004,-33.2232,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-32.2192,-0.5312,-38.8930,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-32.2192,-0.5312,-38.8930,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-14.7269,-0.1671,-21.7648,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-15.8158,-0.5062,-22.5145,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-15.8158,-0.5062,-22.5145,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-15.8158,-0.5062,-22.5145,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0033,FOSTER_DDR,-10.1125,-0.2557,-17.0618,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,12.2952,0.1052,4.9850,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0035,TARBY_DDR,29.8779,0.3638,22.3091,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,12.2952,0.1052,4.9850,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,10.1213,0.0189,2.8974,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,10.1213,0.0189,2.8974,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-16.0400,-0.1972,-23.0478,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0040,TROSPER_DDR,-9.9380,-0.2491,-16.8939,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,-10.3149,-0.2511,-17.2688,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,28.7887,0.3831,21.2006,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0115,V115_DDR,-11.1434,-0.2713,-18.0770,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0116,V116_DDR,-8.2500,-0.1234,-15.3316,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0118,V118_DDR,-19.9699,-0.0736,-27.1013,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0125,V125_DDR,28.5214,0.4371,20.8793,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0126,V126_DDR,26.1520,0.2003,18.7467,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0129,V129_DDR,-7.2450,-0.4103,-14.0397,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,-10.7628,-0.3003,-17.6675,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0134,V134_DDR,27.7037,0.2710,20.2277,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0138,V138_DDR,25.1996,0.1619,17.8327,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,-10.9888,-0.2855,-17.9083,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0143,V143_DDR,16.0059,0.0456,8.7553,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0149,V149_DDR,-12.9559,-0.4194,-19.7415,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0150,V150_DDR,-12.6613,-0.4246,-19.4417,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0155,V155_DDR,24.4489,0.1224,17.1215,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0156,V156_DDR,-10.7628,-0.3003,-17.6675,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0166,V166_DDR,26.1435,0.3529,18.5856,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,-10.7929,-0.2797,-17.7182,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-12.6613,-0.4246,-19.4417,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0170,V170_DDR,-14.6879,-0.4054,-21.4875,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-12.3736,-0.4086,-19.1700,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0176,V176_DDR,-12.6613,-0.4246,-19.4417,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0177,V177_DDR,-23.4225,-0.6972,-29.9302,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,-10.6468,-0.2685,-17.5833,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-16.8288,-0.5067,-23.5270,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0195,V195_DDR,111.6066,0.2904,104.1112,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0197,V197_DDR,23.7215,0.1935,16.3230,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0198,V198_DDR,26.1435,0.3529,18.5856,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0208,V208_DDR,111.7772,0.2968,104.2754,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0209,V209_DDR,111.7772,0.2968,104.2754,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,24.5906,0.1270,17.2586,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0216,V216_DDR,-10.4096,-0.2519,-17.3627,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0219,V219_DDR,24.4489,0.1224,17.1215,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0220,V220_DDR,-12.6613,-0.4246,-19.4417,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0224,V224_DDR,-11.3186,-0.2816,-18.2420,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0225,V225_DDR,-11.3182,-0.2812,-18.2420,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0226,V226_DDR,-11.3186,-0.2816,-18.2420,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0227,V227_DDR,-11.3186,-0.2816,-18.2420,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0229,V229_DDR,-15.5557,-0.1789,-22.5818,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0231,V231_DDR,-10.8503,-0.0741,-17.9812,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0238,V238_DDR,-33.9475,-0.6353,-40.5172,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.VOLT.0242,V242_DDR,24.7587,0.1415,17.4122,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-25.2514,-0.8699,-31.5865,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-15.7312,-0.4579,-22.4783,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-26.1212,-0.5745,-32.7517,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-16.7774,-0.7307,-23.2517,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-25.2514,-0.8699,-31.5865,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-15.6703,-0.7506,-22.1247,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-56.1769,-0.5526,-62.8293,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEHL7,OKGEHL7_H,-6.9256,-0.2354,-13.8952,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEHL8,OKGEHSL1UN8_RA,-6.9256,-0.2354,-13.8952,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEHL910,OKGEHSL1PLT2,-6.9256,-0.2354,-13.8952,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-16.3811,-0.7499,-22.8362,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEMCC,OKGEMCCLAIPLT1,-11.2051,-0.3400,-18.0701,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,21.5612,0.0866,14.2696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,21.5612,0.0866,14.2696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,21.5612,0.0866,14.2696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,-6.5909,-0.3212,-13.4747,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,-6.5909,-0.3212,-13.4747,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,-6.5909,-0.3212,-13.4747,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,-6.5909,-0.3212,-13.4747,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGESM1,OKGESEMINOLEUN1_RA,-7.7689,-0.1796,-14.7943,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGESM2,OKGESEMINOLEUN2_RA,-4.7562,-0.1958,-11.7654,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGESM3,OKGESEMINOLEUN3_RA,-4.7562,-0.1958,-11.7654,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGESO1,OKGESONR1UN1_RA,-59.2244,-0.5000,-65.9294,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGESO2,OKGESONR1UN2_RA,-32.2192,-0.5312,-38.8930,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-16.3811,-0.7499,-22.8362,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-19.0491,-0.8417,-25.4124,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGETINK5A,OKGETINK5UN1_RA,-9.2476,-0.2539,-16.1987,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGETINK5B,OKGETINK5UN2_RA,-9.2476,-0.2539,-16.1987,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-16.3758,-0.6650,-22.9158,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-26.6186,-0.6004,-33.2232,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,29.4085,0.5138,21.6897,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-15.7312,-0.4579,-22.4783,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE_OKGE,OKGE_LA,-2.6379,-0.1456,-9.6972,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-15.3821,-0.2941,-22.2930,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-16.3974,-0.6866,-22.9158,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMLP,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,29.4602,0.0402,22.2151,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,29.1928,0.4678,21.5200,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-13.3789,-0.2539,-20.3301,7.2051\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-100.0000,-0.3485,-106.8565,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-18.4732,-0.5742,-25.1040,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-29.3483,-0.5578,-35.9954,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-23.4128,-0.6851,-29.9327,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-7.7613,-0.5791,-14.3872,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,166.8764,-0.0002,159.6716,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-100.0105,-0.3590,-106.8565,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-100.0105,-0.3590,-106.8565,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_SPP,OMPA_SPP_LA,-21.4173,-0.3483,-28.2740,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-25.2514,-0.8699,-31.5865,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,25.9074,0.0394,18.6630,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,25.9074,0.0394,18.6630,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,25.9074,0.0394,18.6630,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,25.9074,0.0394,18.6630,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,ONT,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,4.0126,-0.1398,-3.0526,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,4.0126,-0.1398,-3.0526,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,4.0126,-0.1398,-3.0526,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,4.0126,-0.1398,-3.0526,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,4.0126,-0.1398,-3.0526,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,4.0126,-0.1398,-3.0526,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,4.0126,-0.1398,-3.0526,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,4.0126,-0.1398,-3.0526,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,4.0126,-0.1398,-3.0526,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,4.0509,-0.1282,-3.0259,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,4.0576,-0.1344,-3.0130,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,4.0178,-0.0717,-3.1155,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,4.0068,-0.1137,-3.0844,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,4.0068,-0.1137,-3.0844,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD_GLDN,OPPD_GLDN_LA,4.0173,-0.1306,-3.0571,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,4.0401,-0.1323,-3.0325,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,5.2470,-0.4405,-1.5175,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,2.8450,-0.2054,-4.1546,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,4.0571,-0.1339,-3.0140,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD_OPPD,OPPD_LA,4.0258,-0.1165,-3.0627,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,4.0241,-0.1061,-3.0747,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,4.0188,-0.1083,-3.0779,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OTP,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,OVEC,OVEC,16.9280,0.1333,9.5897,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PARAGOULD,PARAGOULD_LA,29.9231,0.2769,22.4412,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,28.4850,0.0826,21.1975,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,28.4850,0.0826,21.1975,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,28.4850,0.0826,21.1975,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,28.3703,0.1070,21.0583,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,28.3703,0.1070,21.0583,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,28.3703,0.1070,21.0583,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PIGGOTT,PIGGOTT_LA,27.3552,0.2582,19.8920,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PJM,PJM,15.5570,0.1053,8.2467,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PLUM,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,POPLARBLUFF,POPLARBLUFF_LA,26.5350,0.2336,19.0964,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,6.3522,0.0216,-0.8743,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,6.3522,0.0216,-0.8743,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,6.4655,0.0270,-0.7665,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,6.4655,0.0270,-0.7665,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,7.0339,0.4863,-0.6573,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,7.0339,0.4863,-0.6573,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,6.5056,0.1150,-0.8144,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,5.7119,-0.1469,-1.3462,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-27.4616,-0.3675,-34.2991,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,78.6597,0.0353,71.4194,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,2.2721,0.0399,-4.9728,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-12.3325,-0.0541,-19.4834,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,34.9373,0.1846,27.5477,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,24.2290,0.2405,16.7835,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,6.5454,-0.1849,-0.4746,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,6.6373,0.1426,-0.7103,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,5.4943,-0.2783,-1.4323,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,7.2489,0.4364,-0.3924,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,7.2380,0.1468,-0.1138,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,6.1443,-0.1407,-0.9200,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,PUPP,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,RCEAST,RCEAST,3.6039,-0.1358,-3.4653,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SALINA_1,GRDASALINA1UN1_RA,29.6118,0.1283,22.2785,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SALINA_2,GRDASALINA1UN2_RA,29.6118,0.1283,22.2785,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SALINA_3,GRDASALINA1UN3_RA,29.6118,0.1283,22.2785,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SALINA_4,GRDASALINA1UN4_RA,29.6118,0.1283,22.2785,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SALINA_5,GRDASALINA1UN5_RA,29.6118,0.1283,22.2785,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SALINA_6,GRDASALINA1UN6_RA,29.6118,0.1283,22.2785,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SARPY_1,OPPDSARPYUN1_RA,4.0150,-0.1314,-3.0586,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SARPY_2,OPPDSARPYUN2_RA,4.0162,-0.1184,-3.0704,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SARPY_3,OPPDSARPYUN3_RA,4.0282,-0.1426,-3.0342,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SARPY_4,OPPDSARPYUN4_RA,4.0282,-0.1426,-3.0342,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SARPY_5,OPPDSARPYUN5_RA,4.0282,-0.1426,-3.0342,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SC,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SCEG,VACS,23.6736,0.2542,16.2144,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SCSE,SCSE,-1.1947,-0.2329,-8.1668,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SEC,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-17.0663,-0.7411,-23.5302,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-17.0663,-0.7411,-23.5302,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-17.0663,-0.7411,-23.5302,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-14.1769,-0.4098,-20.9721,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-17.0663,-0.7411,-23.5302,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-15.1965,-0.7268,-21.6747,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-15.0822,-0.8013,-21.4859,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-15.0822,-0.8013,-21.4859,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-15.6539,-0.4917,-22.3672,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-18.4632,-0.6490,-25.0192,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-11.0626,-0.4233,-17.8442,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-14.7545,-0.4550,-21.5045,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-9.5404,-0.4945,-16.2509,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-16.6311,-0.7531,-23.0830,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-9.4295,-0.4943,-16.1402,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-15.8170,-0.8043,-22.2177,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-16.4077,-1.4030,-22.2096,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-14.1200,-0.5875,-20.7375,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-14.1200,-0.5875,-20.7375,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-14.1200,-0.5875,-20.7375,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-14.1200,-0.5875,-20.7375,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-14.3328,-0.6254,-20.9123,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-15.1965,-0.7268,-21.6747,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI_SECI,SECI_LA,-14.1799,-0.5430,-20.8419,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-9.1895,-0.4800,-15.9145,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-9.1895,-0.4800,-15.9145,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-15.6539,-0.4917,-22.3672,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SEHA,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-16.3974,-0.6866,-22.9158,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SERU,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SETH,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SGE,SGE,-0.2964,-0.1987,-7.3026,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SMEP,MISO,16.6970,0.1224,9.3696,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SOCO,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPA,SPA,40.7563,0.2912,33.2601,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPC,SPC,6.9475,0.2868,-0.5443,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPPNORTH_HUB,SPPNORTH_H,3.5783,-0.1526,-3.4740,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-10.2260,-0.3948,-17.0362,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,14.6679,0.2685,7.1944,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,14.6679,0.2685,7.1944,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,14.8303,0.2613,7.3640,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,14.8303,0.2613,7.3640,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_NIXA,SPRM_NIXA_LA,14.1058,0.2774,6.6233,7.2051\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_SPRM,SPRM_LA,14.5086,0.2879,7.0157,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,14.6077,0.2353,7.1674,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,14.6077,0.2353,7.1674,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,14.5959,0.2235,7.1674,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,14.6077,0.2353,7.1674,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,9.5689,-0.0243,2.3882,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,10.2561,-0.2384,3.2895,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-7.8698,-0.5367,-14.5381,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-7.8698,-0.5367,-14.5381,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,8.7181,-0.5505,2.0636,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,9.4101,-0.1671,2.3722,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,8.7989,-0.8937,2.4876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,16.5210,0.4759,8.8401,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,8.7426,-0.2538,1.7914,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,15.0037,0.1816,7.6171,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,15.9679,0.2327,8.5302,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,15.9679,0.2327,8.5302,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,15.0037,0.1816,7.6171,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-7.7481,-0.4595,-14.4936,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,10.2561,-0.2384,3.2895,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-8.0128,-0.5046,-14.7132,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-13.9989,-0.8059,-20.3980,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-10.1852,-0.4763,-16.9139,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-8.4257,-0.3609,-15.2698,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-8.8345,-0.5052,-15.5343,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-18.6122,-0.8255,-24.9917,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-18.6122,-0.8255,-24.9917,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-18.6122,-0.8255,-24.9917,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-18.6122,-0.8255,-24.9917,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GRID.WRAB,WRAB_DDR,-6.3279,-0.3874,-13.1455,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-18.6122,-0.8255,-24.9917,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,8.4724,-0.2496,1.5171,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,8.4724,-0.2496,1.5171,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,7.9663,-0.2360,0.9973,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,7.9663,-0.2360,0.9973,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,7.9663,-0.2360,0.9973,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,8.4724,-0.2496,1.5171,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-5.6883,-0.5263,-12.3670,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-5.6893,-0.5263,-12.3679,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-5.6849,-0.5264,-12.3635,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-7.6690,-0.7126,-14.1614,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,15.3041,0.1719,7.9272,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,8.7333,-0.2581,1.7864,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,8.7333,-0.2581,1.7864,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,8.7333,-0.2581,1.7864,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,8.7333,-0.2581,1.7864,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,12.0970,0.1920,4.7000,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,14.8632,0.1565,7.5017,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,14.8632,0.1565,7.5017,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-16.3617,-0.6508,-22.9158,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-6.0948,-0.5449,-12.7549,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-6.0948,-0.5449,-12.7549,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-5.7550,-0.5259,-12.4341,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-6.3279,-0.3874,-13.1455,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-13.3707,-0.7003,-19.8753,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-8.8425,-0.5444,-15.5031,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-18.2311,-0.8295,-24.6066,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-6.0062,-0.4563,-12.7549,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.PLANTX1,SPS.PLANTX1_H,9.8599,-0.0742,2.7292,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.PLANTX2,SPS.PLANTX2_H,9.8599,-0.0742,2.7292,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,9.7496,-0.0843,2.6289,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,8.7663,-0.4398,2.0011,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-16.0605,-0.7673,-22.4982,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,8.9779,-0.7147,2.4876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,8.7827,-0.4233,2.0011,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-7.7501,-0.4615,-14.4936,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,9.0889,0.0235,1.8604,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,16.5210,0.4759,8.8401,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,9.0889,0.0235,1.8604,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,16.5210,0.4738,8.8422,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-32.2173,-0.5678,-38.8544,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,16.1643,0.6390,8.3203,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,16.1935,0.6682,8.3203,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,15.8202,0.6022,8.0131,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,14.9100,0.2426,7.4624,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,16.5331,0.5674,8.7607,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-14.4765,-0.6480,-21.0335,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-6.3305,-0.4193,-13.1162,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,9.5744,-0.0577,2.4271,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,9.5744,-0.0577,2.4271,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,9.0889,0.0235,1.8604,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,8.7939,-0.2182,1.8071,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,10.3382,0.3751,2.7581,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,9.9871,0.2818,2.5003,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,9.8532,0.0925,2.5557,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,9.7807,-0.2510,2.8268,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,16.1643,0.6390,8.3203,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,16.6400,0.7686,8.6664,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,16.5457,0.6743,8.6664,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,8.8360,-0.3701,2.0011,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,9.7840,0.0929,2.4862,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-15.4775,-0.7409,-21.9416,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-15.4748,-0.7511,-21.9287,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0163,V163_DDR,-5.6916,-0.4315,-12.4651,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0168,V168_DDR,-12.3219,-0.4817,-19.0452,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0180,V180_DDR,16.6400,0.7686,8.6664,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0181,V181_DDR,-15.7198,-0.6644,-22.2604,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0182,V182_DDR,16.5845,0.5853,8.7942,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0199,V199_DDR,10.3940,0.3196,2.8694,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0200,V200_DDR,15.3187,0.3677,7.7460,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.VOLT.0235,V235_DDR,-13.3707,-0.7003,-19.8753,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,8.7989,-0.8937,2.4876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,16.5210,0.4759,8.8401,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-5.3826,-0.5771,-12.0105,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-5.8619,-0.4763,-12.5906,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS_SPS,SPS_LA,8.3364,0.1859,0.9455,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,9.7342,0.0197,2.5095,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SSCN_NPPD,SSCN_NPPD_LA,2.7034,-0.2428,-4.2588,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,23.5322,0.2236,16.1036,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,23.5322,0.2236,16.1036,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,TAL,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,TEC,SOUC,24.0219,0.2672,16.5497,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,2.0747,-0.5951,-4.5352,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,TVA,TVA,23.3027,0.2405,15.8573,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,UCUHUB,UCUHUB_H,-2.1290,-0.1576,-9.1764,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,UCUHUB17,UCUHUB17_H,-6.6606,-0.4686,-13.3970,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,UCUHUB18,UCUHUB18_H,-3.3733,-0.3182,-10.2601,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,UCUHUB19,UCUHUB19_H,-7.5522,-0.3638,-14.3934,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,UCUHUB20,UCUHUB20_H,-7.5509,-0.3521,-14.4038,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,UCUHUB21,UCUHUB21_H,-9.4400,-0.4397,-16.2052,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,UCUHUB22,UCUHUB22_H,-8.9227,-0.4156,-15.7121,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,UCUHUB23,UCUHUB23_H,-9.2616,-0.4200,-16.0465,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,UCUHUB24,UCUHUB24_H,-6.5387,-0.3677,-13.3760,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,7.0107,0.3644,-0.5586,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,7.0107,0.3644,-0.5586,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,6.4276,-0.1030,-0.6744,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,6.4276,-0.1030,-0.6744,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,6.8185,-0.1630,-0.2235,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,6.4365,-0.0449,-0.7236,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,6.4365,-0.0449,-0.7236,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,7.0107,0.3644,-0.5586,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,6.8879,-0.1525,-0.1646,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,7.0059,0.1403,-0.3394,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,5.7946,-0.2774,-1.1330,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,4.3158,-0.5797,-2.3095,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,6.9263,0.3546,-0.6333,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,6.9263,0.3546,-0.6333,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,5.6469,-0.6838,-0.8742,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,6.1376,-0.2435,-0.8239,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,6.7615,-0.0175,-0.4260,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,5.4572,-0.2959,-1.4519,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,5.8572,-0.1998,-1.1480,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,5.9786,-0.2805,-0.9459,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,6.0251,-0.3057,-0.8742,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,6.0251,-0.3057,-0.8742,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,6.2325,-0.2011,-0.7714,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,4.2117,-0.5614,-2.4318,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,6.0077,-0.0759,-1.1214,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,6.6849,0.0950,-0.6150,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,6.6849,0.0950,-0.6150,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,6.6849,0.0950,-0.6150,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,6.7564,0.1666,-0.6151,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,6.7564,0.1666,-0.6151,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,6.7564,0.1666,-0.6151,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,7.1284,0.4612,-0.5378,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,6.5735,-0.1037,-0.5278,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,6.4399,-0.1104,-0.6547,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-0.7436,-0.2168,-7.7318,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,5.3115,-0.1853,-1.7082,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,6.8650,0.1202,-0.4602,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,3.9502,-0.2886,-2.9662,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,3.9160,-0.6715,-2.6175,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,6.1654,-0.2165,-0.8231,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,6.9721,0.3660,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,6.9721,0.3660,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,6.9717,0.3656,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,6.9721,0.3660,-0.5989,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,6.9016,0.2956,-0.5990,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,6.9016,0.2956,-0.5990,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,6.9016,0.2956,-0.5990,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,6.9016,0.2956,-0.5990,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,6.9016,0.2956,-0.5990,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,6.9016,0.2956,-0.5990,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,6.9016,0.2956,-0.5990,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,3.9637,-0.5367,-2.7046,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,6.9550,-0.0129,-0.2370,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,4.6087,-0.1771,-2.4191,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,4.6087,-0.1771,-2.4191,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,3.3750,-0.3267,-3.5033,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,3.3750,-0.3267,-3.5033,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,6.6508,-0.0264,-0.5278,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,6.7667,-0.0469,-0.3914,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,5.6265,-0.3835,-1.1950,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,4.3702,-0.4709,-2.3639,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,6.8330,-0.0991,-0.2729,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,6.8185,-0.1630,-0.2235,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,6.8185,-0.1630,-0.2235,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,5.4572,-0.2959,-1.4519,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,3.5922,-0.1442,-3.4686,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,5.6415,-0.2423,-1.3212,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,4.3001,-0.4731,-2.4318,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,6.0612,-0.2724,-0.8714,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.FSE,WAUE.FSE_H,2.7990,-0.3208,-4.0853,7.2051\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,6.6072,0.1189,-0.7167,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,6.5884,0.1152,-0.7318,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,3.8617,-0.5808,-2.7625,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,4.1713,-0.5405,-2.4932,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,6.7551,-0.1283,-0.3215,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,6.7799,-0.1579,-0.2672,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-13.2700,-0.6014,-19.8736,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,4.3158,-0.5797,-2.3095,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-3.3600,-0.1116,-10.4534,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,5.2584,-0.1876,-1.7590,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,5.2584,-0.1876,-1.7590,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,5.2588,-0.1872,-1.7590,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,6.0271,-0.2172,-0.9606,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,3.5922,-0.1442,-3.4686,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,6.4976,-0.1017,-0.6057,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,5.3523,-0.3025,-1.5502,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,6.0122,-0.0714,-1.1214,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,5.8420,0.0965,-1.4595,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,5.9373,-0.1874,-1.0803,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,7.8854,-0.0591,0.7395,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,5.6392,-0.2221,-1.3437,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,5.6146,-0.3451,-1.2452,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,3.9502,-0.2886,-2.9662,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,8.5588,0.1273,1.2265,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,5.4483,-0.3028,-1.4539,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,8.4846,0.1072,1.1724,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,6.2788,-0.1145,-0.8117,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,4.2557,-0.1642,-2.7851,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NTWK,WAUE.NTWK_H,5.5662,-0.1069,-1.5319,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,6.4946,0.2260,-0.9364,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,6.4946,0.2260,-0.9364,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,4.2343,-0.6510,-2.3197,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,3.7179,-0.7203,-2.7668,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,6.4436,-0.1913,-0.5700,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,4.2343,-0.6510,-2.3197,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,7.3975,-0.0066,0.1991,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,5.2412,-0.2734,-1.6904,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,3.9502,-0.2886,-2.9662,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,5.7698,-0.0817,-1.3535,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,4.7645,-0.7501,-1.6904,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,3.5009,-0.4143,-3.2898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,3.8327,-0.4013,-2.9710,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,6.4295,-0.1164,-0.6591,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,2.8224,-0.5678,-3.8147,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,6.6291,-0.0986,-0.4773,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,4.7947,-0.3777,-2.0326,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,4.3702,-0.4709,-2.3639,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.VOLT.0152,V152_DDR,7.2457,0.5424,-0.5017,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE.VOLT.0172,V172_DDR,6.9353,0.3273,-0.5970,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_BEPM,WAUE_BEPM_LA,6.4389,0.1344,-0.9005,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,6.3673,-0.1355,-0.7023,7.2051\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,5.8423,0.1001,-1.4628,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_EWA,WAUE_EWA_LA,3.6498,-0.1166,-3.4386,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,5.1628,-0.2949,-1.7474,7.2051\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_HMMU,WAUE_HMMU_LA,4.9305,0.0033,-2.2778,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,8.0246,-0.0863,0.9059,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_MECB,WAUE_MECB_LA,5.3659,0.0363,-1.8754,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_MMPA,WAUE_MMPA_LA,7.4673,0.1529,0.1094,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_MRES,WAUE_MRES_LA,5.5080,-0.1186,-1.5784,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,7.1774,0.3979,-0.4255,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,6.6072,0.1189,-0.7167,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,4.9168,-0.2715,-2.0167,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_OTP,WAUE_OTP_LA,7.3797,0.3439,-0.1692,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_OTPW,WAUE_OTPW_LA,7.2135,0.1800,-0.1716,7.2051\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM,WAUE_UGPM_LA,5.9539,-0.1043,-1.1468,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,5.9951,0.0361,-1.2460,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,5.6976,-0.1793,-1.3281,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,5.2222,-0.1841,-1.7987,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,3.6498,-0.1166,-3.4386,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,4.9305,0.0033,-2.2778,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,5.0560,-0.3130,-1.8360,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,6.6072,0.1189,-0.7167,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,7.4673,0.1529,0.1094,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,5.3971,-0.0671,-1.7408,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,4.8243,-0.3120,-2.0686,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,7.4525,0.3865,-0.1390,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-25.1116,-0.7890,-31.5275,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-23.5363,-0.7484,-29.9929,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,-0.0228,-0.4644,-6.7633,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,99.4549,0.1364,92.1135,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,99.4549,0.1364,92.1135,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-10.3420,-0.8037,-16.7433,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,89.3971,0.1793,82.0128,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,77.7059,0.1718,70.3291,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,21.9305,-0.4643,15.1898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,21.9305,-0.4643,15.1898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,21.9305,-0.4643,15.1898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,21.9305,-0.4643,15.1898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,21.9305,-0.4643,15.1898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,21.9305,-0.4643,15.1898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,21.9305,-0.4643,15.1898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,21.9305,-0.4643,15.1898,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,12.0724,-0.4413,5.3087,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-18.2311,-0.8295,-24.6066,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-25.0000,-0.7229,-31.4821,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-23.9391,-0.7398,-30.4042,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,8.9270,-0.7656,2.4876,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_ENMC,WFEC_ENMC_LA,12.8292,0.2691,5.3551,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-27.0964,-0.5961,-33.7053,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,37.3362,0.1040,30.0272,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,12.8941,0.1528,5.5363,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-25.1116,-0.7890,-31.5275,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-25.1116,-0.7890,-31.5275,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-25.1116,-0.7890,-31.5275,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_OKGE,WFEC_OKGE_LA,-9.2472,-0.0596,-16.3926,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,24.9398,0.1452,17.5896,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-16.7701,-0.8284,-23.1467,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-10.9931,-0.8923,-17.3057,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_WFEC,WFEC_LA,11.1561,-0.2198,4.1710,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,12.8941,0.1528,5.5363,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-8.1830,-0.4437,-14.9443,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-12.7057,-0.6122,-19.2984,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-7.8584,-0.2748,-14.7886,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-7.8584,-0.2748,-14.7886,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-7.8584,-0.2748,-14.7886,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-7.8584,-0.2748,-14.7886,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-7.8584,-0.2748,-14.7886,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-7.8584,-0.2748,-14.7886,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-7.8584,-0.2748,-14.7886,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,1.7013,0.1599,-5.6636,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-8.9434,-0.3921,-15.7563,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-23.9301,-0.5533,-30.5818,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-23.9301,-0.5533,-30.5818,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-23.9301,-0.5533,-30.5818,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-18.7597,-0.6531,-25.3116,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-18.7597,-0.6531,-25.3116,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-20.0942,-0.5097,-26.7895,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-20.0942,-0.5097,-26.7895,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-20.0942,-0.5097,-26.7895,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-8.9434,-0.3921,-15.7563,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,-0.3348,-0.0267,-7.5130,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-13.7774,-0.4094,-20.5730,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-13.7774,-0.4094,-20.5730,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-13.7774,-0.4094,-20.5730,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-13.7774,-0.4094,-20.5730,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,-0.3348,-0.0267,-7.5130,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-15.9552,-0.7718,-22.3883,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-39.0000,-0.2074,-45.9976,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.JEC.1,WRJEFFUN10_RA,-5.6851,-0.2217,-12.6684,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.JEC.2,WRJEFFUN11_RA,-5.5556,-0.2224,-12.5382,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.JEC.3,WRJEFFUN12_RA,-5.5661,-0.2329,-12.5382,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-28.2187,-0.5547,-34.8690,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-19.3456,-0.5510,-25.9996,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-19.3456,-0.5510,-25.9996,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.LEC.4,WRLECUN26_RA,-2.0260,-0.0636,-9.1674,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.LEC.5,WRLECUN27_RA,-2.6351,-0.0483,-9.7918,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-12.0544,-0.3685,-18.8909,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-12.0544,-0.3685,-18.8909,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-12.0544,-0.3685,-18.8909,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-12.0133,-0.3544,-18.8639,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-9.1895,-0.4800,-15.9145,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-9.1895,-0.4800,-15.9145,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-9.5267,-0.4395,-16.2921,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-7.7755,-0.4039,-14.5765,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-7.7755,-0.4039,-14.5765,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-12.1806,-0.6499,-18.7357,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-9.1895,-0.4800,-15.9145,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-1.8202,-0.1498,-8.8754,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-9.5333,-0.4668,-16.2714,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-19.3479,-0.5533,-25.9996,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,77.3827,0.1804,69.9973,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-12.3397,-0.9290,-18.6157,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-7.8584,-0.2748,-14.7886,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-13.6157,-0.5432,-20.2775,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,-0.3348,-0.0267,-7.5130,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-8.9434,-0.3921,-15.7563,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-22.6562,-0.4538,-29.4074,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.THAYERLD,WR.THAYERLD_LA,27.4100,0.2500,19.9550,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-23.4425,-0.4488,-30.1987,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0106,V106_DDR,-22.7422,-0.4368,-29.5104,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-0.2158,0.0116,-7.4324,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-10.1501,-0.3496,-17.0055,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-1.8248,-0.0145,-9.0153,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-1.8248,-0.0145,-9.0153,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-0.7617,-0.0091,-7.9575,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-22.2229,-0.3754,-29.0525,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0157,V157_DDR,-1.8894,-0.0212,-9.0732,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0158,V158_DDR,-1.8248,-0.0145,-9.0153,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-1.8248,-0.0145,-9.0153,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-23.1979,-0.4677,-29.9352,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0173,V173_DDR,-12.0531,-0.4267,-18.8314,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0174,V174_DDR,-22.8359,-0.4332,-29.6077,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0184,V184_DDR,-22.4032,-0.4741,-29.1341,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-22.7970,-0.4486,-29.5534,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0186,V186_DDR,-22.5885,-0.4666,-29.3269,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-22.5632,-0.4631,-29.3051,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-23.4041,-0.4396,-30.1695,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-13.6399,-0.3046,-20.5403,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-9.2341,-0.2355,-16.2036,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-8.2559,-0.2528,-15.2081,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-8.2559,-0.2528,-15.2081,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-9.2341,-0.2355,-16.2036,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0245,V245_DDR,-22.7959,-0.4489,-29.5520,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.VOLT.0248,V248_DDR,-22.7422,-0.4368,-29.5104,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-25.9527,-0.5194,-32.6383,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-3.2072,-0.0852,-10.3270,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.WOLF,WRWOLFUN15_RA,-14.7512,-0.5803,-21.3759,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-15.9552,-0.7718,-22.3883,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,1.6674,0.1260,-5.6636,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-23.9301,-0.5533,-30.5818,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-23.9301,-0.5533,-30.5818,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-23.9301,-0.5533,-30.5818,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-23.9301,-0.5533,-30.5818,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-20.0084,-0.3316,-26.8817,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-10.0679,-0.3506,-16.9223,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-24.0524,-0.4464,-30.8110,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-24.0524,-0.4464,-30.8110,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-24.0524,-0.4464,-30.8110,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-24.0524,-0.4464,-30.8110,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-8.2447,-0.2078,-15.2419,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-8.2447,-0.2078,-15.2419,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-8.2447,-0.2078,-15.2419,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-8.2447,-0.2078,-15.2419,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-8.2447,-0.2078,-15.2419,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-8.2447,-0.2078,-15.2419,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-37.8887,-0.4319,-44.6618,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-37.8887,-0.4319,-44.6618,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-40.5478,-0.4526,-47.3002,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-40.5478,-0.4526,-47.3002,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_MIDW,WR_MIDW_LA,-10.3701,-0.4650,-17.1101,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,7.8030,0.1900,0.4080,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,2.9999,0.0539,-4.2590,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-12.1005,-0.4611,-18.8443,7.2049\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_SEG,WR_SEG_LA,2.5246,0.0798,-4.7602,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,WR_WR,WR_LA,-11.3221,-0.2708,-18.2563,7.2050\n03/19/2025 06:00:00,03/19/2025 11:00:00,YAD,VACS,23.6736,0.2542,16.2144,7.2050\n03/19/2025 07:00:00,03/19/2025 12:00:00,AEC,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,AECC_CSWS,CSWS_AECC_LA,35.8403,0.7590,19.7666,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,36.1758,0.6097,20.2514,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,38.6721,1.0296,22.3279,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,36.2056,0.4483,20.4426,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,31.6791,0.5060,15.8584,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,38.2156,0.4733,22.4276,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,30.7817,0.2783,15.1887,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,AECI,AECI,30.4551,0.3019,14.8385,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,AEPM_CSWS,CSWS_LA,34.8867,0.5588,19.0132,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,ALTW,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,AMRN,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-2.8323,-0.4845,-17.6625,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BBA,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,BCA,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,BEPM.ER01.DDR,ER01_DDR,5.3919,-1.8963,-8.0265,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BEPM_ER01,BEPM_ER01_LA,5.3919,-1.8963,-8.0265,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,5.2903,-0.3457,-9.6787,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,4.8662,-0.2172,-10.2313,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BEPM_UM01,BEPM_UM01_LA,10.0884,0.3660,-5.5923,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BLKW,BLKW,-2.9442,0.0450,-18.3039,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-21.8000,-1.4789,-35.6358,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-21.8000,-1.4789,-35.6358,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,27.7739,-1.1677,13.6269,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-21.7800,-1.4589,-35.6358,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,BRAZ,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,BUBA,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-6.8690,-1.4216,-20.7620,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-8.2186,-0.9205,-22.6128,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-8.2186,-0.9205,-22.6128,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-8.2186,-0.9205,-22.6128,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-8.2186,-0.9205,-22.6128,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-8.2186,-0.9205,-22.6128,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-16.3472,-0.7278,-30.9341,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,11.9266,-0.3625,-3.0256,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,11.9266,-0.3625,-3.0256,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CLEC,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,37.1887,0.3936,21.4804,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,COWP,COWP_LA,35.3188,0.5014,19.5027,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,35.3188,0.5014,19.5027,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,35.3188,0.5014,19.5027,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CPLE,VACS,28.9579,0.5247,13.1185,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CPLW,VACS,28.9579,0.5247,13.1185,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,32.1919,0.6442,16.2330,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,32.1919,0.6442,16.2330,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,32.1919,0.6442,16.2330,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,32.1919,0.6442,16.2330,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CRTH_SPA,WRCRTH_SPA_LA,26.9901,0.2701,11.4053,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,31.8279,1.2715,15.2417,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,4.9085,-0.7753,-9.6309,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,30.7817,0.2783,15.1887,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,36.2056,0.4483,20.4426,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,31.8187,1.2641,15.2399,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,31.2395,0.8008,15.1240,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,31.6564,1.1376,15.2041,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,31.6564,1.1376,15.2041,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,35.7951,0.5398,19.9406,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,35.7951,0.5398,19.9406,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,35.7951,0.5398,19.9406,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,35.7951,0.5398,19.9406,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,30.7817,0.2783,15.1887,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,33.8844,1.0774,17.4923,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,58.6310,-0.0252,43.3415,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,58.4892,-0.1670,43.3415,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,40.9353,0.1794,25.4413,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,38.6094,0.2224,23.0723,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,38.6094,0.2224,23.0723,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,38.6073,0.2224,23.0702,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,38.6073,0.2224,23.0702,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-13.0602,-1.0127,-27.3622,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,6.7505,-0.6738,-7.8904,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,48.2498,0.2528,32.6824,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-10.1318,-1.2175,-24.2290,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-10.0790,-1.1646,-24.2290,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,0.2615,-0.6660,-14.3872,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.GRID.CDL1,CDL1_DDR,47.0340,0.3349,31.3844,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,0.4371,-0.7750,-14.1026,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,6.9370,-0.7998,-7.5779,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,47.0340,0.3349,31.3844,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.NUEN.CSI1,CSI1_DDR,39.5272,0.4899,23.7226,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.NUEN.CSI2,CSI2_DDR,39.5326,0.4953,23.7226,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,37.2014,0.4063,21.4804,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.NUEN.GAZA,GAZA_DDR,47.0340,0.3349,31.3844,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,96.0800,0.6673,80.0980,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.NUEN.T201,NT201_DDR,38.3709,0.2776,22.7786,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,1.9298,-1.0228,-12.3621,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,1.9298,-1.0228,-12.3621,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,30.7817,0.2783,15.1887,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,31.8330,1.3703,15.1480,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,0.2615,-0.6660,-14.3872,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,0.2615,-0.6660,-14.3872,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-6.5929,-0.9127,-20.9949,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-10.0790,-1.1646,-24.2290,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,31.2842,0.7786,15.1909,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,34.3143,0.1221,18.8775,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,34.1026,-0.0896,18.8775,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,34.0910,-0.1012,18.8775,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,7.3218,0.0285,-8.0214,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,7.3218,0.0285,-8.0214,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,31.1803,0.7738,15.0918,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,38.5574,0.2418,23.0009,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,31.1721,0.7531,15.1043,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,32.1659,1.7753,15.0759,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,34.0348,0.4344,18.2857,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,39.5326,0.4953,23.7226,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0057,OKMU_DDR,53.7456,0.3943,38.0366,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0060,LEHIGH_DDR,96.0800,0.6673,80.0980,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0086,WARRENM_DDR,38.9554,0.2798,23.3609,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,31.7396,1.3285,15.0964,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,49.6164,0.3049,33.9968,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0121,V121_DDR,31.1803,0.7738,15.0918,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0122,V122_DDR,48.0970,0.2863,32.4960,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0124,V124_DDR,67.7068,0.1946,52.1975,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0135,V135_DDR,39.5644,0.3005,23.9493,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0144,V144_DDR,6.6471,-0.6085,-8.0590,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0145,V145_DDR,6.4737,-0.6810,-8.1600,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,31.2154,0.8133,15.0874,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,30.9620,0.4992,15.1481,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0175,V175_DDR,37.2014,0.4063,21.4804,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,30.9620,0.4992,15.1481,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,31.1242,0.6042,15.2053,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,39.5644,0.3005,23.9493,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,39.7769,0.2817,24.1805,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,39.0786,0.2518,23.5121,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,54.3379,0.1138,38.9094,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,38.3321,0.2129,22.8045,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,39.7769,0.2817,24.1805,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0211,V211_DDR,31.4072,0.9704,15.1222,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,50.3840,0.3042,34.7651,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0213,V213_DDR,39.5132,0.2782,23.9203,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0215,V215_DDR,49.1273,0.2941,33.5185,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0217,V217_DDR,50.4400,0.2918,34.8336,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0218,V218_DDR,53.8575,0.1262,38.4166,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0228,V228_DDR,39.0526,0.2261,23.5118,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0232,V232_DDR,38.9626,0.2997,23.3482,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0233,V233_DDR,40.0038,0.2955,24.3936,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0240,V240_DDR,45.1671,0.2205,29.6319,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0244,V244_DDR,39.7769,0.2817,24.1805,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0246,MDT1_DDR,96.0800,0.6673,80.0980,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0249,V249_DDR,39.4836,0.2926,23.8763,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0250,V250_DDR,4.3469,-0.7336,-10.2342,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0251,V251_DDR,38.9890,0.2490,23.4253,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.VOLT.0252,V252_DDR,54.3379,0.1138,38.9094,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-14.9472,-0.9333,-29.3285,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,22.1453,-1.0412,7.8718,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-10.5306,-1.4713,-24.3740,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,30.8740,0.4504,15.1089,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-15.2798,-1.5235,-29.0710,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-17.2619,-0.9741,-31.6025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-17.2619,-0.9741,-31.6025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-17.2619,-0.9741,-31.6025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-17.2619,-0.9741,-31.6025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-17.2619,-0.9741,-31.6025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,30.7817,0.2783,15.1887,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,32.0093,1.2699,15.4248,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,38.9423,0.2794,23.3482,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,38.9192,0.2563,23.3482,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,66.4715,0.4475,50.7093,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,66.4715,0.4475,50.7093,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWWELSH1,CSWSWELSHUN1_RA,30.8177,0.6403,14.8627,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWWELSH3,CSWSWELSHUN3_RA,30.8177,0.6403,14.8627,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWWILKES1,CSWSWILKESUN1_RA,31.2832,0.8861,15.0824,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWWILKES2,CSWSWILKESUN2_RA,31.2832,0.8861,15.0824,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,CSWWILKES3,CSWSWILKESUN3_RA,31.1854,0.8345,15.0362,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-10.0686,-1.1543,-24.2290,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,DENL,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,DERS,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,DOE,DOE,26.7135,0.3967,11.0021,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,12.3015,0.0249,-3.0381,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,DPC,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,DUK,VACS,28.9579,0.5247,13.1185,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDDY,EDDY,39.6955,0.9449,23.4359,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,23.2921,0.1320,7.8454,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-19.7000,-0.1982,-34.8165,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,33.3442,-0.0388,18.0683,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE.SLCC,EDESTL4391_PLT,29.5875,0.1024,14.1704,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,28.8576,0.1446,13.3983,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,18.6846,-0.1573,3.5272,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_EC_01,EDELAR3821UN1_RA,23.2921,0.1320,7.8454,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_EC_02,EDELAR3821UN2_RA,23.2921,0.1320,7.8454,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_EC_03,EDELAR3821UN3_RA,23.2921,0.1320,7.8454,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_EC_04,EDELAR3821UN4_RA,23.2921,0.1320,7.8454,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_EDE,EDE_LA,32.8747,0.4503,17.1097,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_ERW,EDEERWFUNG1_RA,-15.8725,-0.7877,-30.3995,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-1.4615,-0.9085,-15.8677,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,57.0000,0.8842,40.8011,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,57.0000,0.8842,40.8011,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,57.0000,0.8842,40.8011,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,57.0000,0.8842,40.8011,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,31.4816,0.5649,15.6021,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_RIV_10,EDERIV1671UN10_RA,30.6514,0.0156,15.3211,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_RIV_11,EDERIV1671UN11_RA,30.6514,0.0156,15.3211,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_RIV_12,EDERIV453UN12_PLT,30.2814,-0.3544,15.3211,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_SL_01,EDESTL4391UN1_RA,29.5875,0.1024,14.1704,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EDE_SWMP,EDE_SWMP_LA,16.3210,0.5620,0.4443,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EEI,EEI,26.6672,0.3946,10.9579,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,EES,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-5.3624,-0.7975,-19.8796,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,ERCOTE,ERCOTE,30.8177,0.6403,14.8627,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,ERCOTN,ERCOTN,1.9991,-0.9535,-12.3621,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,7.4490,-0.5543,-7.3113,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,FMPP,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,FPC,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,FPL,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,FREM_50T,OPPDFREM_GUN1_RA,12.0820,-0.3156,-2.9171,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,FREM_6,OPPDFREM_AUN6_RA,12.0790,-0.3212,-2.9145,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,FREM_7,OPPDFREM_AUN7_RA,12.0790,-0.3212,-2.9145,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,FREM_8,OPPDFREM_AUN8_RA,12.0122,-0.3880,-2.9145,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,FREM_LOAD,FREM_LOAD_LA,12.0682,-0.3320,-2.9145,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-13.1347,-0.7104,-27.7390,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,31.2842,0.7786,15.1909,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-8.9381,-1.9264,-22.3264,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-28.4179,-1.2537,-42.4789,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,37.1887,0.3936,21.4804,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,37.1887,0.3936,21.4804,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,37.1887,0.3936,21.4804,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,40.4770,0.2794,24.8829,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,40.4770,0.2794,24.8829,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,40.6222,0.2739,25.0336,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,40.6222,0.2739,25.0336,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-19.6068,-1.1079,-33.8136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,42.0100,0.0126,26.6827,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,42.0100,0.0126,26.6827,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,42.0100,0.0126,26.6827,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.VOLT.0130,V130_DDR,41.1763,0.4524,25.4093,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA.VOLT.0237,V237_DDR,41.6837,0.3459,26.0231,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDAHUB2,GRDAHUB2_H,22.9040,-0.1154,7.7047,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDAHUB3,GRDAHUB3_H,17.6766,-0.2474,2.6093,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA_GRDA,GRDA_LA,40.6943,0.3344,25.0452,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA_HUB,GRDA_H,30.3735,0.0588,15.0000,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRDA_HUBSA,GRDASA_H,29.5534,0.0426,14.1961,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GRE,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,1.1194,0.5489,-14.7443,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,GSEC_SPS,SPS_GSEC_LA,-2.8529,-0.3424,-17.8251,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,GSPR2014HUB,GSPR2014HUB_H,8.7033,-0.4585,-6.1530,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,GSPR2015HUB,GSPR2015HUB_H,8.9696,-0.4779,-5.8672,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-3.5515,-1.0833,-17.7829,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,HARRISON,CSWSLEBROCKPLT1,31.0717,0.6601,15.0969,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,HAST_TNSK_HUB,HAST_TNSK_H,7.2219,-0.6315,-7.4613,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,HQST,PJM,21.4613,0.1715,5.9752,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,HST,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,30.4498,0.2935,14.8416,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,30.4498,0.2935,14.8416,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,30.0223,0.2877,14.4199,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,30.0223,0.2877,14.4199,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,30.8723,0.2939,15.2637,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,30.8723,0.2939,15.2637,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,INDN_INDN,INDN_LA,30.3378,0.2946,14.7285,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-1.5369,-0.9810,-15.8706,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,ISNE,PJM,21.4613,0.1715,5.9752,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,JEA,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,12.0674,-0.2972,-2.9501,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,12.0674,-0.2972,-2.9501,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,7.4755,-0.0067,-7.8325,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KACYCT4,KACYNEARMANUNCT4_RA,18.5210,0.2192,2.9871,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,60.0000,0.0216,44.6637,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,18.5210,0.2192,2.9871,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,18.7444,0.2360,3.1937,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,18.6861,0.2335,3.1379,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KACY_KACY,KACY_LA,18.7747,0.2313,3.2286,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,25.0100,0.1375,9.5578,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,27.2870,0.6343,11.3380,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-17.0307,-0.5953,-31.7501,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-41.7604,-1.0938,-55.9813,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.VOLT.0222,V222_DDR,7.6416,0.0257,-7.6988,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.VOLT.0223,V223_DDR,13.2087,0.0174,-2.1234,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.VOLT.0241,V241_DDR,24.6200,0.5393,8.7660,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.VOLT.0243,V243_DDR,23.3823,0.2728,7.7948,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.VOLT.0247,V247_DDR,18.5940,0.1311,3.1482,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.VOLT.0253,V253_DDR,25.2390,0.1416,9.7827,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-0.5075,-1.0594,-14.7628,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,10.0608,-0.1407,-5.1132,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,10.0608,-0.1407,-5.1132,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,10.0608,-0.1407,-5.1132,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,10.0608,-0.1407,-5.1132,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,25.1771,0.1346,9.7278,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,25.1771,0.1346,9.7278,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHUB,KCPLHUB_H,5.3363,-0.5371,-9.4413,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHUB17,KCPLHUB17_H,4.0391,-0.6160,-10.6596,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHUB18,KCPLHUB18_H,3.7168,-0.6091,-10.9888,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHUB19,KCPLHUB19_H,3.8415,-0.5770,-10.8962,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHUB20,KCPLHUB20_H,2.9774,-0.6405,-11.6967,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHUB21,KCPLHUB21_H,2.9463,-0.6224,-11.7461,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHUB22,KCPLHUB22_H,3.7994,-0.6129,-10.9023,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHUB23,KCPLHUB23_H,3.1389,-0.6330,-11.5429,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLHUB24,KCPLHUB24_H,2.3726,-0.6667,-12.2754,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,7.2625,0.0064,-8.0586,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,7.2625,0.0064,-8.0586,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,10.1470,-0.3558,-4.8119,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,10.1470,-0.3558,-4.8119,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,25.0101,0.1376,9.5578,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,25.0100,0.1375,9.5578,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,22.6331,0.1774,7.1410,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,22.6331,0.1774,7.1410,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,22.6331,0.1774,7.1410,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,22.6331,0.1774,7.1410,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,22.6331,0.1774,7.1410,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,22.6331,0.1774,7.1410,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,22.6331,0.1774,7.1410,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,22.6331,0.1774,7.1410,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,3.4714,-0.1539,-11.6894,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,18.4373,0.1367,2.9859,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KCPL_KCPL,KCPL_LA,18.3283,0.1148,2.8988,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KENN,KENN_LA,32.5214,0.5489,16.6578,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KEP2_SECI,KEP2_SECI_LA,-7.8833,-1.3269,-21.8711,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KERR_1,GRDAKERR_HYDUN1_RA,41.0544,0.3306,25.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KERR_2,GRDAKERR_HYDUN2_RA,40.7909,0.3385,25.1377,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KERR_3,GRDAKERR_HYDUN3_RA,40.7909,0.3385,25.1377,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KERR_4,GRDAKERR_HYDUN4_RA,41.0544,0.3306,25.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,10.0608,-0.1407,-5.1132,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,10.0608,-0.1407,-5.1132,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,10.8728,-0.0618,-4.3801,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,10.8728,-0.0618,-4.3801,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,8.1986,-0.1344,-6.9817,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,6.3004,-0.1078,-8.9065,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,6.3004,-0.1078,-8.9065,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-6.3539,-1.2203,-20.4483,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-6.3539,-1.2203,-20.4483,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-6.3539,-1.2203,-20.4483,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-3.1956,-0.7577,-17.7526,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-3.1956,-0.7577,-17.7526,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-6.4596,-1.2514,-20.5229,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-3.6568,-0.7879,-18.1836,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-0.6536,-0.4071,-15.5612,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,53.8498,0.0039,38.5312,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,53.8498,0.0039,38.5312,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,5.6113,-0.3133,-9.3901,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,5.6113,-0.3133,-9.3901,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,5.6113,-0.3133,-9.3901,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-4.4168,-1.0115,-18.7200,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-4.3478,-1.2965,-18.3660,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,5.5737,-0.4621,-9.2789,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,8.6627,0.0446,-6.6966,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LAFA,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,LAM345,LAM345,-6.8690,-1.4216,-20.7620,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,LEPA,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,9.9957,-0.3590,-4.9600,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_LES,LES_LA,10.0385,-0.3679,-4.9084,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,10.4297,-0.3745,-4.5105,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,9.8455,-0.4057,-5.0635,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,9.8455,-0.4057,-5.0635,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,9.8455,-0.4057,-5.0635,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,10.4302,-0.3740,-4.5105,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,10.4297,-0.3745,-4.5105,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_WAVERLY,LES_WAVERLY_H,10.3440,-0.3914,-4.5793,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,11.8341,-0.3985,-3.0821,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,11.8341,-0.3985,-3.0821,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,LGEE,LGEE,23.8884,0.2812,8.2925,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MALDEN,MALDEN_LA,31.6198,0.5268,15.7783,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MCWEST,MCWEST,9.4985,-0.1598,-5.6564,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MDU,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,5.3554,-0.2800,-9.6793,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,8.4653,-0.1851,-6.6643,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,11.8357,0.3714,-3.8504,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MEAN_NPPD,NPPD_MEAN_LA,5.7279,-0.7604,-8.8264,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MEC,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,MHEB,MHEB,10.4864,-0.1242,-4.7041,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-0.1711,-0.9063,-14.5794,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-4.4346,-1.1835,-18.5657,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-0.1711,-0.9063,-14.5794,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-0.1711,-0.9063,-14.5794,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-4.4346,-1.1835,-18.5657,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-9.9960,-0.8834,-24.4272,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MISO,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-7.4323,-1.0143,-21.7327,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-7.4323,-1.0143,-21.7327,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,1.7990,-0.6658,-12.8499,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-8.3489,-1.7664,-21.8972,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-4.2198,-1.0794,-18.4551,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-9.4852,-2.1517,-22.6482,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-8.0382,-1.3659,-21.9870,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-9.5036,-1.9866,-22.8317,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-7.7011,-0.9623,-22.0535,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-7.7011,-0.9623,-22.0535,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-7.7011,-0.9623,-22.0535,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-7.7011,-0.9623,-22.0535,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-7.7011,-0.9623,-22.0535,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,17.6853,0.0614,2.3092,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,25.8681,0.3584,10.1950,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,25.8681,0.3584,10.1950,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,21.7587,0.2238,6.2202,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,23.7143,0.6103,7.7893,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MOWR,AECI,30.4551,0.3019,14.8385,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,21.8683,0.2079,6.3457,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,26.1345,0.3706,10.4493,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,4.4598,-0.7521,-10.1028,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,0.5300,-0.3786,-14.4061,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-10.9919,-1.1266,-25.1800,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,4.5086,-0.7033,-10.1028,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,12.3073,0.0307,-3.0381,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,12.3073,0.0307,-3.0381,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,12.3082,0.0316,-3.0381,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,12.3082,0.0316,-3.0381,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,7.6416,0.0257,-7.6988,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,7.6416,0.0257,-7.6988,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,7.6416,0.0257,-7.6988,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,7.6009,-0.0150,-7.6988,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,7.6416,0.0257,-7.6988,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,7.6416,0.0257,-7.6988,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,7.6416,0.0257,-7.6988,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,22.8468,0.4572,7.0749,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,14.9395,0.0316,-0.4068,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,11.9817,-0.0130,-3.3200,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,11.9818,-0.0129,-3.3200,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,11.9818,-0.0129,-3.3200,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,20.0488,0.1449,4.5893,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,20.0488,0.1449,4.5893,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MPS_MPS,MPS_LA,18.6312,0.1757,3.1407,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,MSTNG,SPSMSTNGPLT1,1.6281,0.5454,-14.2319,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MSTNG4,SPSMSTNGUN4_RA,1.5530,0.4703,-14.2319,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MSTNG5,SPSMSTNGUN5_RA,1.6281,0.5454,-14.2319,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,1.6281,0.5454,-14.2319,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NBSO,PJM,21.4613,0.1715,5.9752,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,8.8220,-0.6349,-5.8578,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,8.8233,-0.6336,-5.8578,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-5.0333,-1.4362,-18.9118,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NHC1,VACS,28.9579,0.5247,13.1185,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,12.1472,-0.3364,-2.8311,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,12.1472,-0.3364,-2.8311,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,12.1472,-0.3364,-2.8311,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,3.9600,-0.8332,-10.5215,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,6.7634,-0.9398,-7.6115,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,8.4708,-0.6430,-6.2009,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,2.2675,-0.6385,-12.4087,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,6.7634,-0.9398,-7.6115,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.HUB.PY2018,NPPDPY18_H,6.2849,-0.7563,-8.2735,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,6.4113,-0.7519,-8.1516,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,6.3532,-0.7479,-8.2137,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,6.4704,-0.7373,-8.1070,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,0.9587,-0.6591,-13.6969,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,4.7323,-0.7495,-9.8329,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,4.7323,-0.7495,-9.8329,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,4.1497,-0.7678,-10.3972,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,0.9587,-0.6591,-13.6969,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,8.8549,-1.0792,-5.3806,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,5.4189,-1.0964,-8.7994,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,2.3580,-0.7897,-12.1670,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,5.4189,-1.0964,-8.7994,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,6.0344,-0.9794,-8.3008,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,5.1581,-0.9524,-9.2042,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,9.2851,-0.2919,-5.7376,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,6.7634,-0.9398,-7.6115,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,2.7323,-0.7941,-11.7883,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,4.7323,-0.7495,-9.8329,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,4.7323,-0.7495,-9.8329,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,5.4060,-0.5586,-9.3501,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,5.3532,-0.5632,-9.3983,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,5.3532,-0.5632,-9.3983,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,6.1538,-0.3320,-8.8289,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,4.7636,-0.3499,-10.2012,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,7.0839,-0.7418,-7.4890,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,4.1163,-0.6421,-10.5563,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,3.9829,-0.2704,-11.0614,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,2.9494,-0.2813,-12.0840,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.NELI.DDR,NELI_DDR,1.8671,-0.7739,-12.6737,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.NPPM.1058,SH1058_DDR,13.9553,-0.2459,-1.1135,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,6.1321,-0.4621,-8.7204,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,6.7634,-0.9398,-7.6115,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,8.4708,-0.6430,-6.2009,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,0.9587,-0.6591,-13.6969,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.TECH.1,KEARNE_DDR,6.4046,-0.3259,-8.5842,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,6.6495,-1.3344,-7.3308,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,6.6495,-1.3344,-7.3308,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,1.1655,-0.7378,-13.4114,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD.VOLT.0236,V236_DDR,8.7955,-0.3131,-6.2061,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD2017HUB,NPPD2017HUB_H,6.3091,-0.7538,-8.2517,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,12.6269,-0.6304,-2.0573,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,3.9600,-0.8332,-10.5215,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,5.2800,-1.3209,-8.7137,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,5.2800,-1.3209,-8.7137,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,8.9004,-0.3369,-6.0774,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,8.8109,-0.2976,-6.2061,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,2.5693,-0.6587,-12.0868,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,5.4688,-0.5853,-9.2606,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,13.6172,-0.5840,-1.1135,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,13.6172,-0.5840,-1.1135,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,13.6172,-0.5840,-1.1135,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,7.2356,-0.6307,-7.4484,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,8.8205,-0.6462,-5.8480,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,7.5287,-0.4984,-7.2876,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,2.1862,-1.5472,-11.5813,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,2.2682,-1.4652,-11.5813,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,4.1001,-0.8111,-10.4035,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,3.9277,-0.8246,-10.5624,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,7.6105,-0.5954,-7.1088,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,7.5988,-0.6071,-7.1088,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,7.5988,-0.6071,-7.1088,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,7.5736,-0.5792,-7.1619,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,8.8549,-1.0792,-5.3806,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,7.5397,-0.5792,-7.1958,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,9.3540,-0.4772,-5.4834,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,7.2383,-0.5982,-7.4782,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,7.2246,-0.6072,-7.4829,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,7.2263,-0.5998,-7.4886,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,7.2263,-0.5998,-7.4886,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,7.2356,-0.6307,-7.4484,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,7.2082,-0.6581,-7.4484,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,5.0744,-0.3306,-9.9097,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,7.9429,-0.4297,-6.9421,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,4.0693,-0.7657,-10.4797,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,4.3703,-1.2227,-9.7217,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,2.0745,-0.8507,-12.3895,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,14.2500,0.0488,-1.1135,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,1.8671,-0.7739,-12.6737,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,4.2624,-0.7796,-10.2727,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,4.2624,-0.7796,-10.2727,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_NPPD,NPPD_LA,7.9519,-0.5277,-6.8351,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,9.3540,-0.4772,-5.4834,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,9.3540,-0.4772,-5.4834,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,6.8763,-0.7019,-7.7365,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,5.3779,-0.8196,-9.1171,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NSB,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NSP,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,NSSO,PJM,21.4613,0.1715,5.9752,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,NYIS,PJM,21.4613,0.1715,5.9752,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-10.2878,-1.5666,-24.0359,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-18.6756,-1.1986,-32.7917,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-22.6589,-1.0728,-36.9008,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-22.6589,-1.0728,-36.9008,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-10.2954,-1.7724,-23.8377,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-28.4179,-1.2537,-42.4789,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-92.9224,-0.7427,-107.4944,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-42.8456,-1.1298,-57.0305,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-20.8847,-1.1130,-35.0864,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-19.0351,-1.1961,-33.1537,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-4.5126,-0.4765,-19.3508,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-20.8847,-1.1130,-35.0864,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-10.3101,-1.7307,-23.8941,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-9.9960,-0.8834,-24.4272,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-10.3168,-1.5281,-24.1034,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,6.4100,-0.2147,-8.6900,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-19.0351,-1.1961,-33.1537,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-14.0373,-1.0928,-28.2592,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-14.0000,-1.1268,-28.1879,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-8.2186,-0.9205,-22.6128,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-16.0000,-0.2311,-31.0836,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-9.9960,-0.8834,-24.4272,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-9.9960,-0.8834,-24.4272,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-19.0351,-1.1961,-33.1537,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-6.9803,-0.7159,-21.5791,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.NUEN.LAM1,LAM1_DDR,42.2826,1.0575,25.9104,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-4.5126,-0.4765,-19.3508,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-4.5126,-0.4765,-19.3508,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-7.4520,-0.6969,-22.0698,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-4.6913,-0.5248,-19.4812,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-4.6913,-0.5248,-19.4812,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-4.6913,-0.5248,-19.4812,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-4.7378,-0.4686,-19.5839,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-4.7378,-0.4686,-19.5839,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-4.6913,-0.5248,-19.4812,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-4.6913,-0.5248,-19.4812,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-19.0351,-1.1961,-33.1537,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,42.1840,0.7275,26.1418,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-10.3101,-1.7307,-23.8941,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-8.6240,-0.5369,-23.4017,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-14.0373,-1.0928,-28.2592,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,37.2911,0.7639,21.2125,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-9.5954,-0.8968,-24.0133,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-9.5954,-0.8968,-24.0133,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-9.5954,-0.8968,-24.0133,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-9.5954,-0.8968,-24.0133,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-23.0818,-1.6080,-36.7885,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-20.8647,-1.1015,-35.0779,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-18.6756,-1.1986,-32.7917,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-24.1000,-1.0516,-38.3631,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-24.1000,-1.0516,-38.3631,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-5.0398,-0.2587,-20.0958,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-9.1194,-0.9980,-23.4361,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-9.1194,-0.9980,-23.4361,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-9.1194,-0.9980,-23.4361,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0033,FOSTER_DDR,-3.6331,-0.4344,-18.5134,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,21.8053,0.3263,6.1643,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0035,TARBY_DDR,42.2064,0.8751,26.0166,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,21.8053,0.3263,6.1643,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,19.1309,0.1445,3.6717,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,19.1309,0.1445,3.6717,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-9.5457,-0.3296,-24.5308,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0040,TROSPER_DDR,-3.4376,-0.4179,-18.3344,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,-3.7042,-0.4218,-18.5971,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,38.7313,0.8823,22.5343,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0115,V115_DDR,-4.4507,-0.4697,-19.2957,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0116,V116_DDR,20.8754,-0.1587,5.7194,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0118,V118_DDR,-8.7548,-0.0576,-24.0119,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0125,V125_DDR,38.9915,1.0120,22.6648,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0126,V126_DDR,37.8604,0.5162,22.0295,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0129,V129_DDR,0.4380,-0.7741,-14.1026,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,-3.8467,-0.5311,-18.6303,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0134,V134_DDR,39.2442,0.6658,23.2637,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0138,V138_DDR,36.7339,0.4318,20.9874,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,-4.1094,-0.4971,-18.9270,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0143,V143_DDR,25.9146,0.2001,10.3998,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0149,V149_DDR,-6.1921,-0.7847,-20.7221,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0150,V150_DDR,-5.7973,-0.7855,-20.3265,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0155,V155_DDR,35.7204,0.3451,20.0606,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0156,V156_DDR,-3.8467,-0.5311,-18.6303,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0166,V166_DDR,38.2413,0.8548,22.0718,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,-3.9294,-0.4841,-18.7600,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-5.7973,-0.7855,-20.3265,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0170,V170_DDR,-7.6123,-0.6895,-22.2375,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-5.6049,-0.7749,-20.1447,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0176,V176_DDR,-5.7973,-0.7855,-20.3265,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0177,V177_DDR,-15.4107,-1.4445,-29.2809,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,-3.8575,-0.4595,-18.7127,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-10.8364,-0.9426,-25.2085,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0195,V195_DDR,114.8610,0.7893,98.7571,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0197,V197_DDR,35.4244,0.5161,19.5936,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0198,V198_DDR,38.2413,0.8548,22.0718,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0208,V208_DDR,114.8900,0.8067,98.7686,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0209,V209_DDR,114.8900,0.8067,98.7686,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,36.4302,0.3771,20.7384,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0216,V216_DDR,-3.7720,-0.4234,-18.6633,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0219,V219_DDR,35.7204,0.3451,20.0606,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0220,V220_DDR,-5.7973,-0.7855,-20.3265,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0224,V224_DDR,-4.5627,-0.4921,-19.3853,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0225,V225_DDR,-4.5619,-0.4913,-19.3853,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0226,V226_DDR,-4.5627,-0.4921,-19.3853,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0227,V227_DDR,-4.5627,-0.4921,-19.3853,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0229,V229_DDR,-8.8089,-0.2894,-23.8342,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0231,V231_DDR,0.9073,-0.0447,-14.3627,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0238,V238_DDR,-24.9382,-1.2583,-38.9946,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.VOLT.0242,V242_DDR,36.1442,0.3868,20.4427,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-15.9819,-1.7741,-29.5225,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-9.9960,-0.8834,-24.4272,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-18.2640,-1.1415,-32.4372,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-10.3040,-1.5153,-24.1034,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-15.9819,-1.7741,-29.5225,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-10.3872,-1.5427,-24.1591,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-48.3628,-1.0996,-62.5779,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEHL7,OKGEHL7_H,-1.0380,-0.3921,-15.9606,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEHL8,OKGEHSL1UN8_RA,-1.0380,-0.3921,-15.9606,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEHL910,OKGEHSL1PLT2,-1.0380,-0.3921,-15.9606,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-10.4264,-1.5454,-24.1957,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEMCC,OKGEMCCLAIPLT1,-4.8160,-0.6252,-19.5054,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,31.8268,0.2647,16.2474,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,31.8268,0.2647,16.2474,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,31.8268,0.2647,16.2474,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,0.6642,-0.5914,-14.0590,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,0.6642,-0.5914,-14.0590,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,0.6642,-0.5914,-14.0590,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,0.6642,-0.5914,-14.0590,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGESM1,OKGESEMINOLEUN1_RA,-5.5738,-0.2881,-20.6004,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGESM2,OKGESEMINOLEUN2_RA,-0.1647,-0.3226,-15.1568,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGESM3,OKGESEMINOLEUN3_RA,-0.1647,-0.3226,-15.1568,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGESO1,OKGESONR1UN1_RA,-50.4075,-0.9830,-64.7392,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGESO2,OKGESONR1UN2_RA,-24.1000,-1.0516,-38.3631,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-10.4264,-1.5454,-24.1957,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-11.5673,-1.3747,-25.5073,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGETINK5A,OKGETINK5UN1_RA,-3.0376,-0.4337,-17.9186,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGETINK5B,OKGETINK5UN2_RA,-3.0376,-0.4337,-17.9186,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-9.8554,-1.3705,-23.7996,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-18.6756,-1.1986,-32.7917,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,38.6493,1.1869,22.1477,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-9.9960,-0.8834,-24.4272,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE_OKGE,OKGE_LA,8.3975,-0.2125,-6.7047,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-8.6240,-0.5369,-23.4017,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-9.9013,-1.4164,-23.7996,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMLP,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,40.2613,0.1787,24.7679,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,38.7014,1.0991,22.2876,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-6.5232,-0.4528,-21.3851,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-92.8065,-0.6268,-107.4944,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-12.7814,-1.0784,-27.0177,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-20.8847,-1.1130,-35.0864,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-14.7548,-1.3462,-28.7233,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,0.0329,-1.1013,-14.1805,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,179.8087,0.0903,164.4037,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-92.8391,-0.6594,-107.4944,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-92.8391,-0.6594,-107.4944,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_SPP,OMPA_SPP_LA,-13.0297,-0.6243,-27.7201,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-15.9819,-1.7741,-29.5225,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,36.9166,0.1650,21.4369,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,36.9166,0.1650,21.4369,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,36.9166,0.1650,21.4369,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,36.9166,0.1650,21.4369,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,ONT,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,12.1832,-0.3448,-2.7867,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,12.1832,-0.3448,-2.7867,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,12.1832,-0.3448,-2.7867,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,12.1832,-0.3448,-2.7867,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,12.1832,-0.3448,-2.7867,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,12.1832,-0.3448,-2.7867,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,12.1832,-0.3448,-2.7867,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,12.1832,-0.3448,-2.7867,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,12.1832,-0.3448,-2.7867,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,12.1379,-0.3217,-2.8551,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,12.1472,-0.3364,-2.8311,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,11.9458,-0.1846,-3.1843,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,11.9582,-0.2885,-3.0680,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,11.9582,-0.2885,-3.0680,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD_GLDN,OPPD_GLDN_LA,11.9844,-0.3276,-3.0027,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,12.2319,-0.3313,-2.7515,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,8.8549,-1.0792,-5.3806,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,9.8641,-0.4868,-4.9638,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,12.1469,-0.3359,-2.8319,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD_OPPD,OPPD_LA,12.1237,-0.2885,-2.9025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,11.9970,-0.2725,-3.0452,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,11.9835,-0.2770,-3.0542,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,OTP,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,OVEC,OVEC,22.9398,0.2402,7.3849,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PARAGOULD,PARAGOULD_LA,34.1384,0.5848,18.2388,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,39.7469,0.2282,24.2040,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,39.7469,0.2282,24.2040,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,39.7469,0.2282,24.2040,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,39.6735,0.2824,24.0764,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,39.6735,0.2824,24.0764,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,39.6735,0.2824,24.0764,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PIGGOTT,PIGGOTT_LA,32.2004,0.5410,16.3447,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PJM,PJM,21.4613,0.1715,5.9752,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,PLUM,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,POPLARBLUFF,POPLARBLUFF_LA,31.9591,0.4883,16.1561,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,9.2656,-0.3728,-5.6763,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,9.2656,-0.3728,-5.6763,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,9.3094,-0.3722,-5.6331,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,9.3094,-0.3722,-5.6331,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,10.3650,0.6553,-5.6050,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,10.3650,0.6553,-5.6050,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,9.4954,-0.1676,-5.6517,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,8.6720,-0.7646,-5.8781,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-16.3472,-0.7278,-30.9341,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,90.4708,0.1651,74.9910,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,9.1712,0.1235,-6.2670,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-3.8051,-0.0225,-19.0973,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,64.3165,0.5009,48.5009,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,35.9653,0.6101,20.0405,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,8.9171,-0.4769,-5.9207,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,9.9323,-0.0901,-5.2923,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,7.3576,-0.6746,-7.2825,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,22.5200,0.6443,6.5610,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,10.2022,-0.0274,-5.0852,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,8.0350,-0.3738,-6.9059,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,PUPP,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,RCEAST,RCEAST,6.7881,-0.9339,-7.5927,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SALINA_1,GRDASALINA1UN1_RA,41.0563,0.3325,25.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SALINA_2,GRDASALINA1UN2_RA,41.0563,0.3325,25.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SALINA_3,GRDASALINA1UN3_RA,41.0563,0.3325,25.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SALINA_4,GRDASALINA1UN4_RA,41.0563,0.3325,25.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SALINA_5,GRDASALINA1UN5_RA,41.0563,0.3325,25.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SALINA_6,GRDASALINA1UN6_RA,41.0563,0.3325,25.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SARPY_1,OPPDSARPYUN1_RA,11.9555,-0.3230,-3.0362,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SARPY_2,OPPDSARPYUN2_RA,11.9467,-0.2926,-3.0754,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SARPY_3,OPPDSARPYUN3_RA,11.9140,-0.3497,-3.0509,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SARPY_4,OPPDSARPYUN4_RA,11.9140,-0.3497,-3.0509,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SARPY_5,OPPDSARPYUN5_RA,11.9140,-0.3497,-3.0509,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SC,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SCEG,VACS,28.9579,0.5247,13.1185,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SCSE,SCSE,4.4169,-0.6682,-10.2296,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SEC,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-9.4705,-1.5827,-23.2025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-9.4705,-1.5827,-23.2025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-9.4705,-1.5827,-23.2025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-6.2474,-0.8968,-20.6653,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-9.4705,-1.5827,-23.2025,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-7.6618,-1.5786,-21.3979,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-7.6537,-1.7193,-21.2491,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-7.6537,-1.7193,-21.2491,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-7.7029,-0.9640,-22.0535,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-10.6760,-1.3483,-24.6424,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-3.2596,-0.8217,-17.7526,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-6.8001,-1.0012,-21.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-2.5521,-1.1362,-16.7306,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-9.0677,-1.6126,-22.7698,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-2.4678,-1.1247,-16.6578,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-8.2552,-1.7203,-21.8496,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-9.5244,-2.9422,-21.8968,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-6.4766,-1.2895,-20.5018,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-6.4766,-1.2895,-20.5018,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-6.4766,-1.2895,-20.5018,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-6.4766,-1.2895,-20.5018,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-6.7085,-1.3740,-20.6491,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-7.6618,-1.5786,-21.3979,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI_SECI,SECI_LA,-6.3870,-1.1617,-20.5400,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-1.5369,-0.9810,-15.8706,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-1.5369,-0.9810,-15.8706,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-7.7029,-0.9640,-22.0535,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SEHA,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-9.9013,-1.4164,-23.7996,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SERU,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SETH,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SGE,SGE,4.9375,-0.6133,-9.7639,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SMEP,MISO,21.1965,0.1874,5.6943,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,SOCO,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPA,SPA,48.7983,0.6884,32.7952,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPC,SPC,10.0786,0.3043,-5.5404,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPPNORTH_HUB,SPPNORTH_H,10.1282,-0.3735,-4.8130,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-2.4450,-0.7228,-17.0370,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,32.3317,0.6038,16.4132,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,32.3317,0.6038,16.4132,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,31.8341,0.5859,15.9335,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,31.8341,0.5859,15.9335,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_NIXA,SPRM_NIXA_LA,33.9752,0.6269,18.0336,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_SPRM,SPRM_LA,32.1879,0.6460,16.2272,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,32.3212,0.5273,16.4792,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,32.3212,0.5273,16.4792,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,32.2823,0.4884,16.4792,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,32.3212,0.5273,16.4792,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-2.6293,-0.0041,-17.9399,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-3.1000,-0.4389,-17.9758,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-4.8308,-1.0653,-19.0802,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-4.8308,-1.0653,-19.0802,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-3.2629,-1.1224,-17.4552,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,0.0731,-0.2584,-14.9832,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-4.7456,-1.7879,-18.2724,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,39.8574,1.1502,23.3925,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-2.3832,-0.4775,-17.2204,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,32.4596,0.5989,16.5460,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,37.9930,0.6693,22.0090,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,37.9930,0.6693,22.0090,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,32.4596,0.5989,16.5460,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-4.6434,-0.8982,-19.0599,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-3.1000,-0.4389,-17.9758,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-4.8600,-1.0199,-19.1548,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-8.1211,-1.7318,-21.7040,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-5.8007,-0.9739,-20.1415,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-4.7822,-0.6920,-19.4048,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-5.2321,-1.0236,-19.5232,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-10.2219,-1.7752,-23.7614,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-10.2219,-1.7752,-23.7614,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-10.2219,-1.7752,-23.7614,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-10.2219,-1.7752,-23.7614,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GRID.WRAB,WRAB_DDR,-3.8670,-0.7301,-18.4516,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-10.2219,-1.7752,-23.7614,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-2.8323,-0.4845,-17.6625,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-2.8323,-0.4845,-17.6625,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-2.9330,-0.4511,-17.7965,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-2.9330,-0.4511,-17.7965,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-2.9330,-0.4511,-17.7965,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-2.8323,-0.4845,-17.6625,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-3.8520,-1.0578,-18.1089,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-3.8520,-1.0578,-18.1089,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-3.8501,-1.0578,-18.1070,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-5.0333,-1.4362,-18.9118,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,34.3060,0.5689,18.4224,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-2.4001,-0.4865,-17.2283,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-2.4001,-0.4865,-17.2283,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-2.4001,-0.4865,-17.2283,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-2.4001,-0.4865,-17.2283,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,15.0525,0.5944,-0.8566,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,31.7271,0.5543,15.8581,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,31.7271,0.5543,15.8581,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-9.8315,-1.3466,-23.7996,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-4.0501,-1.0899,-18.2749,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-4.0501,-1.0899,-18.2749,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-3.8847,-1.0560,-18.1434,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-3.8670,-0.7301,-18.4516,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-7.6509,-1.4969,-21.4686,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-5.2993,-1.1022,-19.5118,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-10.2954,-1.7724,-23.8377,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-3.8494,-0.8892,-18.2749,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-2.8826,-0.1151,-18.0822,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-2.8826,-0.1151,-18.0822,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-2.9408,-0.1384,-18.1171,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-2.9698,-0.8846,-17.3998,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-9.5645,-2.2351,-22.6441,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-4.3555,-1.3978,-18.2724,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-2.9456,-0.8605,-17.3998,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-4.6478,-0.9026,-19.0599,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-5.1032,0.0398,-20.4577,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,39.8574,1.1502,23.3925,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-5.1032,0.0398,-20.4577,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,39.8626,1.1447,23.4032,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-15.0606,-1.1684,-29.2069,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,37.4802,1.5300,20.6355,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,37.5445,1.5943,20.6355,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,35.6198,1.4673,18.8378,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,31.6735,0.7355,15.6233,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,39.7535,1.3461,23.0927,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-6.8690,-1.4216,-20.7620,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-3.9230,-0.7991,-18.4386,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-3.0937,-0.0878,-18.3206,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-3.0937,-0.0878,-18.3206,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-5.1032,0.0398,-20.4577,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-2.2804,-0.3973,-17.1978,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,3.8345,0.9337,-12.4139,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-2.2079,0.7397,-18.2623,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-2.6602,0.2436,-18.2185,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-2.9603,-0.4800,-17.7950,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,37.4802,1.5300,20.6355,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,39.6754,1.7755,22.5852,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,39.4741,1.5742,22.5852,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-2.8000,-0.7149,-17.3998,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-2.6781,0.2806,-18.2734,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-8.7569,-1.6765,-22.3951,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-8.7817,-1.7070,-22.3894,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0163,V163_DDR,-3.6929,-0.8604,-18.1472,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0168,V168_DDR,-8.2665,-0.9317,-22.6495,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0180,V180_DDR,39.6754,1.7755,22.5852,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0181,V181_DDR,-9.2130,-1.9893,-22.5384,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0182,V182_DDR,40.0000,1.3848,23.3005,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0199,V199_DDR,4.3690,0.8114,-11.7571,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0200,V200_DDR,33.5688,0.9847,17.2694,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.VOLT.0235,V235_DDR,-7.6509,-1.4969,-21.4686,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-4.7456,-1.7879,-18.2724,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,39.8574,1.1502,23.3925,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-3.6416,-1.1734,-17.7829,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-3.7435,-0.9477,-18.1105,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS_SPS,SPS_LA,15.9980,0.4915,0.1918,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,-0.6499,0.1347,-16.0993,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SSCN_NPPD,SSCN_NPPD_LA,3.2025,-0.5879,-11.5243,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,29.3107,0.4614,13.5346,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,29.3107,0.4614,13.5346,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,TAL,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,TEC,SOUC,29.1928,0.5537,13.3245,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,4.3703,-1.2227,-9.7217,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,TVA,TVA,28.7066,0.4942,12.8977,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,UCUHUB,UCUHUB_H,5.1598,-0.2920,-9.8628,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,UCUHUB17,UCUHUB17_H,-0.9738,-0.9674,-15.3211,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,UCUHUB18,UCUHUB18_H,1.9449,-0.6575,-12.7123,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,UCUHUB19,UCUHUB19_H,-1.5554,-0.7659,-16.1042,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,UCUHUB20,UCUHUB20_H,-1.3970,-0.7474,-15.9643,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,UCUHUB21,UCUHUB21_H,-2.8022,-0.9256,-17.1912,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,UCUHUB22,UCUHUB22_H,-2.5994,-0.8766,-17.0374,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,UCUHUB23,UCUHUB23_H,-2.9582,-0.8870,-17.3858,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,UCUHUB24,UCUHUB24_H,-0.2302,-0.7774,-14.7675,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,10.2115,0.4522,-5.5554,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,10.2115,0.4522,-5.5554,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,9.0384,-0.5452,-5.7311,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,9.0384,-0.5452,-5.7311,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,9.4498,-0.6700,-5.1949,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,9.2568,-0.4531,-5.6048,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,9.2568,-0.4531,-5.6048,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,10.2115,0.4522,-5.5554,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,9.5446,-0.6400,-5.1300,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,9.9614,-0.0308,-5.3225,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,7.2269,-0.6742,-7.4136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,5.7084,-1.6918,-7.9145,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,10.0717,0.3536,-5.5966,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,10.0717,0.3536,-5.5966,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,7.1637,-1.6831,-6.4679,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,7.7954,-0.7065,-6.8128,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,11.3232,-0.3724,-3.6191,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,6.5657,-0.7466,-8.0024,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,7.3184,-0.4854,-7.5109,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,7.5559,-0.7788,-6.9800,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,7.9603,-0.8865,-6.4679,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,7.9603,-0.8865,-6.4679,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,8.1468,-0.6357,-6.5322,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,5.8800,-1.7762,-7.6585,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,7.8123,-0.0545,-7.4478,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,22.8300,-0.1228,7.6381,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,22.8300,-0.1228,7.6381,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,22.8300,-0.1228,7.6381,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,9.7221,0.0242,-5.6168,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,9.7221,0.0242,-5.6168,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,9.7221,0.0242,-5.6168,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,10.4421,0.6603,-5.5329,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,9.2123,-0.5412,-5.5612,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,9.0409,-0.5616,-5.7122,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,4.6748,-0.6443,-9.9955,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,6.7187,-0.5976,-7.9984,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,9.7780,-0.0929,-5.4438,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,2.2582,-0.7054,-12.3511,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,5.3676,-2.1621,-7.7850,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,8.4780,-0.6916,-6.1451,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,10.1818,0.4533,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,10.1818,0.4533,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,10.1810,0.4525,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,10.1818,0.4533,-5.5862,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,10.0161,0.2982,-5.5968,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,10.0161,0.2982,-5.5968,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,10.0161,0.2982,-5.5968,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,10.0161,0.2982,-5.5968,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,10.0161,0.2982,-5.5968,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,10.0161,0.2982,-5.5968,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,10.0161,0.2982,-5.5968,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,4.7401,-1.3585,-9.2161,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,9.7681,-0.3281,-5.2185,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,5.2586,-0.4892,-9.5669,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,5.2586,-0.4892,-9.5669,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,4.2893,-0.8080,-10.2174,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,4.2893,-0.8080,-10.2174,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,9.3955,-0.3580,-5.5612,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,9.5638,-0.4190,-5.3319,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,6.7947,-0.9013,-7.6187,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,6.4651,-1.5278,-7.3218,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,9.5655,-0.2918,-5.4574,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,9.4498,-0.6700,-5.1949,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,9.4498,-0.6700,-5.1949,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,6.5657,-0.7466,-8.0024,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,6.7510,-0.9532,-7.6105,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,7.5694,-0.8641,-6.8812,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,6.0078,-1.6484,-7.6585,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,7.9275,-0.8183,-6.5689,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.FSE,WAUE.FSE_H,4.5042,-0.8364,-9.9741,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,9.3592,-0.3386,-5.6169,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,9.3194,-0.3752,-5.6201,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,5.2093,-1.5913,-8.5141,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,5.6010,-1.5198,-8.1939,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,9.3737,-0.6380,-5.3030,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,9.4011,-0.6694,-5.2441,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-12.7100,-1.3907,-26.6340,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,5.7084,-1.6918,-7.9145,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-3.0000,-0.8462,-17.4685,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,9.2001,-0.4355,-5.6791,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,9.2004,-0.4352,-5.6791,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,9.2009,-0.4347,-5.6791,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,7.6280,-0.6870,-6.9997,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,6.7510,-0.9532,-7.6105,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,8.5885,-0.2919,-6.4343,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,6.5549,-0.7532,-8.0066,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,7.7977,-0.0692,-7.4478,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,9.6875,0.1888,-5.8160,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,7.5072,-0.4547,-7.3528,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,11.7939,-0.1942,-3.3266,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,7.0990,-0.5719,-7.6438,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,6.7344,-0.8514,-7.7289,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,2.2582,-0.7054,-12.3511,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,12.0721,0.1230,-3.3656,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,6.5471,-0.7611,-8.0065,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,12.0752,0.1344,-3.3739,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,8.2044,-0.3143,-6.7960,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,11.8341,-0.3985,-3.0821,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NTWK,WAUE.NTWK_H,8.0401,-0.5085,-6.7661,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,9.0965,0.2173,-6.4355,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,9.0965,0.2173,-6.4355,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,5.5368,-1.7666,-8.0113,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,4.4199,-1.7532,-9.1416,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,8.4024,-0.6141,-6.2981,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,5.5368,-1.7666,-8.0113,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,10.2860,-0.2859,-4.7428,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,7.0393,-1.0048,-7.2706,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,2.2582,-0.7054,-12.3511,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,7.8063,-0.6342,-6.8742,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,6.1516,-1.8925,-7.2706,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,4.9053,-2.0262,-8.3832,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,5.2653,-2.0229,-8.0265,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,9.0235,-0.5734,-5.7178,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,6.4630,-1.4858,-7.3659,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,8.7691,-0.3693,-6.1763,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,6.6188,-1.3070,-7.3889,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,6.4651,-1.5278,-7.3218,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.VOLT.0152,V152_DDR,10.6439,0.8269,-5.4977,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE.VOLT.0172,V172_DDR,10.0884,0.3660,-5.5923,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_BEPM,WAUE_BEPM_LA,9.7741,-0.0227,-5.5179,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,8.4096,-0.3591,-6.5460,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,9.6854,0.1967,-5.8260,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_EWA,WAUE_EWA_LA,6.8391,-0.8897,-7.5859,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,6.5999,-0.9274,-7.7873,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_HMMU,WAUE_HMMU_LA,10.9935,0.0446,-4.3658,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,11.3775,-0.2665,-3.6707,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_MECB,WAUE_MECB_LA,8.5712,0.0546,-6.7981,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_MMPA,WAUE_MMPA_LA,10.4557,0.0187,-4.8777,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_MRES,WAUE_MRES_LA,7.8597,-0.5057,-6.9493,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,10.4295,0.5338,-5.4190,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,9.3592,-0.3386,-5.6169,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,6.4561,-0.8897,-7.9689,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_OTP,WAUE_OTP_LA,10.9171,0.4376,-4.8352,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_OTPW,WAUE_OTPW_LA,13.0995,0.0591,-2.2743,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM,WAUE_UGPM_LA,8.6293,-0.3948,-6.2905,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,8.8125,-0.2414,-6.2608,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,7.5986,-0.4838,-7.2323,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,6.5928,-0.9504,-7.7715,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,6.8391,-0.8897,-7.5859,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,10.9935,0.0446,-4.3658,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,6.4962,-0.8963,-7.9222,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,9.3592,-0.3386,-5.6169,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,10.4557,0.0187,-4.8777,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,8.3956,-0.4206,-6.4985,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,6.6038,-0.9860,-7.7249,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,10.6886,0.4875,-5.1136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-15.7600,-1.5675,-29.5072,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-18.7636,-1.4518,-32.6265,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,9.7285,-0.8520,-4.7342,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,95.8186,0.4059,80.0980,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,95.8186,0.4059,80.0980,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-2.9632,-1.6428,-16.6351,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,88.9425,0.4965,73.1313,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,80.8652,0.4780,65.0725,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,36.7100,-0.8815,22.2768,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,36.7100,-0.8815,22.2768,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,36.7100,-0.8815,22.2768,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,36.7100,-0.8815,22.2768,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,36.7100,-0.8815,22.2768,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,36.7100,-0.8815,22.2768,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,36.7100,-0.8815,22.2768,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,36.7100,-0.8815,22.2768,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,24.3986,-0.8308,9.9147,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-10.2954,-1.7724,-23.8377,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-21.8000,-1.4789,-35.6358,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-15.4239,-1.4784,-29.2602,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-4.4729,-1.5152,-18.2724,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_ENMC,WFEC_ENMC_LA,18.1383,0.7168,2.1069,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-19.0351,-1.1961,-33.1537,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,35.7360,0.2918,20.1295,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,19.9739,0.5233,4.1359,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-15.7600,-1.5675,-29.5072,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-15.7600,-1.5675,-29.5072,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-15.7600,-1.5675,-29.5072,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_OKGE,WFEC_OKGE_LA,3.2251,0.0034,-12.0931,15.3148\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,39.7728,0.4292,24.0289,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-10.7347,-1.6399,-24.4095,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-4.2611,-1.7719,-17.8039,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_WFEC,WFEC_LA,18.8651,-0.3502,3.9006,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,19.9739,0.5233,4.1359,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-0.9901,-0.9444,-15.3604,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-5.3409,-1.3634,-19.2921,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,0.7350,-0.5237,-14.0560,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,0.7350,-0.5237,-14.0560,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,0.7350,-0.5237,-14.0560,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,0.7350,-0.5237,-14.0560,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,0.7350,-0.5237,-14.0560,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,0.7349,-0.5237,-14.0560,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,0.7349,-0.5237,-14.0560,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,3.8930,0.5686,-11.9903,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-0.7225,-0.7708,-15.2664,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-15.6373,-1.1111,-29.8409,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-15.6373,-1.1111,-29.8409,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-15.6373,-1.1111,-29.8409,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-10.9354,-1.3515,-24.8986,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-10.9354,-1.3515,-24.8986,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-11.5809,-1.0232,-25.8724,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-11.5809,-1.0232,-25.8724,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-11.5809,-1.0232,-25.8724,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-0.7225,-0.7708,-15.2664,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,7.6787,-0.0037,-7.6323,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-5.5457,-0.8023,-20.0581,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-5.5457,-0.8023,-20.0581,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-5.5457,-0.8023,-20.0581,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-5.5456,-0.8022,-20.0581,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,7.6787,-0.0037,-7.6323,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-8.4421,-1.6587,-22.0981,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-30.5138,-0.4139,-45.4146,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.JEC.1,WRJEFFUN10_RA,2.6825,-0.4044,-12.2278,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.JEC.2,WRJEFFUN11_RA,2.7582,-0.4073,-12.1492,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.JEC.3,WRJEFFUN12_RA,2.7374,-0.4281,-12.1492,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-19.6068,-1.1079,-33.8136,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-10.9814,-1.1161,-25.1800,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-10.9814,-1.1161,-25.1800,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.LEC.4,WRLECUN26_RA,7.3238,-0.0681,-7.9228,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.LEC.5,WRLECUN27_RA,6.5970,-0.0360,-8.6816,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-3.8516,-0.7082,-18.4580,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-3.8516,-0.7082,-18.4580,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-3.8516,-0.7082,-18.4580,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-3.7959,-0.6787,-18.4319,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-1.5369,-0.9810,-15.8706,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-1.5369,-0.9810,-15.8706,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-2.4354,-1.0217,-16.7284,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-0.5884,-0.8622,-15.0409,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-0.5884,-0.8622,-15.0409,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-4.3557,-1.3044,-18.3660,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-1.5369,-0.9810,-15.8706,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,5.1550,-0.8656,-9.2941,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-1.4615,-0.9085,-15.8677,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-10.9861,-1.1208,-25.1800,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,85.1582,0.4971,69.3464,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-4.8759,-1.9018,-18.2888,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,0.7349,-0.5237,-14.0560,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-5.2115,-1.0941,-19.4321,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,7.6787,-0.0037,-7.6323,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-0.7225,-0.7708,-15.2664,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-13.8017,-0.8902,-28.2262,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.THAYERLD,WR.THAYERLD_LA,33.8588,0.5329,18.0113,15.3146\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-14.6224,-0.8785,-29.0586,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0106,V106_DDR,-13.7885,-0.8485,-28.2547,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0139,WR.VOLT.0139_H,10.5997,0.0861,-4.8011,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-1.9447,-0.6667,-16.5927,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0146,WR.VOLT.0146_H,7.7291,0.0404,-7.6260,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0147,WR.VOLT.0147_H,7.7291,0.0404,-7.6260,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0148,WR.VOLT.0148_H,8.0088,0.0398,-7.3457,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-13.1535,-0.7267,-27.7415,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0157,V157_DDR,7.6111,0.0257,-7.7293,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0158,V158_DDR,7.7291,0.0404,-7.6260,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0159,WR.VOLT.0159_H,7.7291,0.0404,-7.6260,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-14.1791,-0.9233,-28.5705,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0173,V173_DDR,-3.9412,-0.8281,-18.4278,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0174,V174_DDR,-13.7935,-0.8486,-28.2596,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0184,V184_DDR,-13.4223,-0.9391,-27.7979,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-13.9365,-0.8795,-28.3717,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0186,V186_DDR,-13.8131,-0.9198,-28.2080,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-13.5970,-0.9135,-27.9982,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-14.5259,-0.8551,-28.9855,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-5.1115,-0.5567,-19.8695,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-0.5357,-0.4413,-15.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0191,WR.VOLT.0191_H,0.3835,-0.4766,-14.4546,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0192,WR.VOLT.0192_H,0.3835,-0.4766,-14.4546,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-0.5357,-0.4413,-15.4091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0245,V245_DDR,-13.9405,-0.8804,-28.3748,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.VOLT.0248,V248_DDR,-13.7885,-0.8485,-28.2547,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-17.0119,-1.0360,-31.2906,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,5.2889,-0.1176,-9.9082,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.WOLF,WRWOLFUN15_RA,-5.5717,-1.1744,-19.7120,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-8.4421,-1.6587,-22.0981,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,3.8162,0.4918,-11.9903,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-15.6373,-1.1111,-29.8409,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-15.6373,-1.1111,-29.8409,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-15.6373,-1.1111,-29.8409,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-15.6373,-1.1111,-29.8409,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-13.0567,-0.6742,-27.6972,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-1.8632,-0.6688,-16.5091,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-15.0609,-0.8676,-29.5080,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-15.0609,-0.8676,-29.5080,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-15.0609,-0.8676,-29.5080,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-15.0609,-0.8676,-29.5080,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,0.1561,-0.3652,-14.7934,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,0.1561,-0.3652,-14.7934,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,0.1561,-0.3652,-14.7934,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,0.1561,-0.3652,-14.7934,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,0.1561,-0.3652,-14.7934,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,0.1561,-0.3652,-14.7934,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-29.3820,-0.8174,-43.8793,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-29.3820,-0.8174,-43.8793,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-32.0663,-0.8502,-46.5308,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-32.0663,-0.8502,-46.5308,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_MIDW,WR_MIDW_LA,-2.8845,-0.9746,-17.2246,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,24.3660,0.4249,8.6264,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,16.9374,0.1739,1.4488,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-4.4009,-0.9463,-18.7693,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_SEG,WR_SEG_LA,8.9093,0.3195,-6.7249,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,WR_WR,WR_LA,-2.7916,-0.5055,-17.6008,15.3147\n03/19/2025 07:00:00,03/19/2025 12:00:00,YAD,VACS,28.9579,0.5247,13.1185,15.3147\n03/19/2025 08:00:00,03/19/2025 13:00:00,AEC,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,AECC_CSWS,CSWS_AECC_LA,37.0382,0.9006,18.3821,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,40.5496,0.7229,22.0713,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,37.3579,1.2115,18.3910,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,40.4769,0.5221,22.1994,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,29.1708,0.6312,10.7842,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,37.7097,0.5687,19.3855,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,28.4135,0.3547,10.3034,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,AECI,AECI,29.1022,0.3966,10.9502,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,AEPM_CSWS,CSWS_LA,35.5218,0.6903,17.0761,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,ALTW,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,AMRN,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-5.6861,-0.9059,-22.5356,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BBA,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BCA,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BEPM.ER01.DDR,ER01_DDR,8.1484,-1.9150,-7.6920,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BEPM_ER01,BEPM_ER01_LA,8.1484,-1.9150,-7.6920,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,7.7283,-0.0783,-9.9488,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,6.8955,-0.2698,-10.5901,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BEPM_UM01,BEPM_UM01_LA,12.8517,0.8152,-5.7190,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,BLKW,BLKW,-5.9967,-0.4731,-23.2791,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-22.3384,-1.8237,-38.2701,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-22.3384,-1.8237,-38.2701,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,31.7340,-1.4055,15.3840,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-22.3133,-1.7986,-38.2701,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BRAZ,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BUBA,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-7.1787,-1.8020,-23.1321,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-12.4725,-1.1469,-29.0810,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-12.4725,-1.1469,-29.0810,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-12.4725,-1.1469,-29.0810,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-12.4725,-1.1469,-29.0810,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-12.4725,-1.1469,-29.0810,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-12.8453,-0.8645,-29.7362,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,10.2657,-0.3145,-7.1753,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,10.2657,-0.3145,-7.1753,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CLEC,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,40.2891,0.4487,22.0850,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,COWP,COWP_LA,28.6042,0.6341,10.2146,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,28.6042,0.6341,10.2146,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,28.6042,0.6341,10.2146,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CPLE,VACS,26.1371,0.7161,7.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CPLW,VACS,26.1371,0.7161,7.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,28.6413,0.8440,10.0419,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,28.6413,0.8440,10.0419,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,28.6413,0.8440,10.0419,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,28.6413,0.8440,10.0419,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CRTH_SPA,WRCRTH_SPA_LA,36.1193,0.3153,18.0486,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,33.9027,1.8000,14.3473,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,5.3973,-0.9323,-11.4258,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,28.4135,0.3547,10.3034,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,40.4769,0.5221,22.1994,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,33.2021,1.7905,13.6561,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,28.9888,0.9596,10.2738,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,26.5178,1.5793,7.1831,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,26.5178,1.5793,7.1831,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,40.2779,0.6385,21.8840,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,40.2779,0.6385,21.8840,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,40.2780,0.6386,21.8840,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,40.2780,0.6386,21.8840,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,28.4135,0.3547,10.3034,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,31.9898,1.3174,12.9170,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,60.0620,-0.0260,42.3326,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,59.9008,-0.1872,42.3326,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,44.1179,0.1946,26.1679,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,42.4547,0.2304,24.4689,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,42.4547,0.2304,24.4689,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,42.4557,0.2304,24.4699,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,42.4557,0.2304,24.4699,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-14.4769,-1.2701,-30.9622,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,10.9134,-0.8484,-5.9936,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,44.8824,0.3005,26.8265,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-11.6819,-1.5773,-27.8601,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-11.6250,-1.5203,-27.8601,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-2.5628,-0.7951,-19.5231,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.GRID.CDL1,CDL1_DDR,44.1564,0.3733,26.0277,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,0.8206,-1.0701,-15.8647,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,7.7842,-0.9706,-9.0006,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,44.1564,0.3733,26.0277,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.NUEN.CSI1,CSI1_DDR,43.5835,0.5393,25.2888,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.NUEN.CSI2,CSI2_DDR,43.5900,0.5458,25.2888,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,40.3045,0.4640,22.0850,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.NUEN.GAZA,GAZA_DDR,44.1564,0.3733,26.0277,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,92.7062,0.5404,74.4104,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.NUEN.T201,NT201_DDR,42.4404,0.3104,24.3746,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,0.9198,-1.2256,-15.6100,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,0.9198,-1.2256,-15.6100,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,28.4135,0.3547,10.3034,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,28.0642,1.7473,8.5615,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-2.5628,-0.7951,-19.5231,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-2.5628,-0.7951,-19.5231,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-7.7497,-1.1167,-24.3884,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-11.6250,-1.5203,-27.8601,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,28.4247,0.9321,9.7371,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,39.7401,0.1166,21.8681,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,39.4911,-0.1324,21.8681,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,39.4815,-0.1420,21.8681,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,17.1011,0.0150,-0.6694,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,17.1011,0.0150,-0.6694,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,28.4523,0.9218,9.7750,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,43.1303,0.2582,25.1167,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,28.6671,0.8855,10.0262,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,29.2382,2.1333,9.3494,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,32.7402,0.5165,14.4682,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,43.5900,0.5458,25.2888,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0057,OKMU_DDR,49.1755,0.4366,30.9835,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0060,LEHIGH_DDR,92.7062,0.5404,74.4104,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0086,WARRENM_DDR,42.7956,0.2983,24.7419,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,28.4798,1.6657,9.0587,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,52.1423,0.3460,34.0408,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0121,V121_DDR,28.4523,0.9218,9.7750,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0122,V122_DDR,50.7992,0.3238,32.7200,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0124,V124_DDR,68.0708,0.2168,50.0985,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0135,V135_DDR,43.4270,0.3091,25.3625,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0144,V144_DDR,11.3169,-0.7889,-5.6496,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0145,V145_DDR,11.4328,-0.8799,-5.4427,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,28.4705,0.9617,9.7534,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,28.4522,0.6024,10.0944,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0175,V175_DDR,40.3045,0.4640,22.0850,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,28.4522,0.6024,10.0944,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,28.5722,0.7372,10.0796,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,43.4270,0.3091,25.3625,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,43.5981,0.3007,25.5420,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,43.0126,0.2720,24.9852,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,56.2668,0.1332,38.3782,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,42.3997,0.2164,24.4279,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,43.5981,0.3007,25.5420,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0211,V211_DDR,29.1593,1.1540,10.2498,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,52.8083,0.3541,34.6988,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0213,V213_DDR,43.3235,0.2956,25.2724,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0215,V215_DDR,51.7083,0.3375,33.6153,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0217,V217_DDR,52.8514,0.3375,34.7585,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0218,V218_DDR,55.8414,0.1468,37.9391,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0228,V228_DDR,43.5153,0.2415,25.5184,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0232,V232_DDR,42.9332,0.2981,24.8797,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0233,V233_DDR,43.7887,0.3139,25.7194,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0240,V240_DDR,48.5040,0.2396,30.5090,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0244,V244_DDR,43.5981,0.3007,25.5420,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0246,MDT1_DDR,92.7062,0.5404,74.4104,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0249,V249_DDR,43.2992,0.3140,25.2298,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0250,V250_DDR,4.5850,-0.8817,-12.2888,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0251,V251_DDR,42.8219,0.2618,24.8047,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.VOLT.0252,V252_DDR,56.2668,0.1332,38.3782,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-16.7916,-1.1405,-33.4065,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,25.6895,-1.2994,9.2335,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-12.1968,-1.8173,-28.1349,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,28.3288,0.5401,10.0333,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-14.6626,-2.1129,-30.3051,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-17.2088,-1.2106,-33.7536,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-17.2088,-1.2106,-33.7536,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-17.2088,-1.2106,-33.7536,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-17.2088,-1.2106,-33.7536,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-17.2088,-1.2106,-33.7536,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,28.4135,0.3547,10.3034,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,31.6372,1.6228,12.2589,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,42.9070,0.2719,24.8797,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,42.7915,0.1564,24.8797,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,54.7522,0.4968,36.5000,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,54.7522,0.4968,36.5000,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWWELSH1,CSWSWELSHUN1_RA,27.7862,0.7453,9.2854,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWWELSH3,CSWSWELSHUN3_RA,27.7862,0.7453,9.2854,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWWILKES1,CSWSWILKESUN1_RA,27.6377,1.1498,8.7325,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWWILKES2,CSWSWILKESUN2_RA,27.6377,1.1498,8.7325,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,CSWWILKES3,CSWSWILKESUN3_RA,27.1134,1.0843,8.2737,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-11.6093,-1.5047,-27.8601,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,DENL,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,DERS,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,DOE,DOE,23.9274,0.5613,5.6107,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,13.9208,0.0733,-3.9079,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,DPC,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,DUK,VACS,26.1371,0.7161,7.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDDY,EDDY,46.6656,0.4717,28.4384,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,35.1149,0.1564,17.2031,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-13.8000,-0.2411,-31.3143,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,41.3016,-0.0531,23.5992,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE.SLCC,EDESTL4391_PLT,37.9998,0.1088,20.1356,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,37.7896,0.1617,19.8725,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,24.8888,-0.1851,7.3185,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_EC_01,EDELAR3821UN1_RA,35.1149,0.1564,17.2031,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_EC_02,EDELAR3821UN2_RA,35.1149,0.1564,17.2031,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_EC_03,EDELAR3821UN3_RA,35.1149,0.1564,17.2031,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_EC_04,EDELAR3821UN4_RA,35.1149,0.1564,17.2031,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_EDE,EDE_LA,38.6908,0.5439,20.3915,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_ERW,EDEERWFUNG1_RA,-12.7013,-0.9379,-29.5188,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-0.1746,-1.0363,-16.8938,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,52.2600,1.0406,33.4640,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,52.2600,1.0406,33.4640,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,52.2600,1.0406,33.4640,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,52.2600,1.0406,33.4640,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,27.3794,0.7499,8.8741,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_RIV_10,EDERIV1671UN10_RA,38.1804,0.0020,20.4230,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_RIV_11,EDERIV1671UN11_RA,38.1804,0.0020,20.4230,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_RIV_12,EDERIV453UN12_PLT,37.7190,-0.4594,20.4230,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_SL_01,EDESTL4391UN1_RA,37.9998,0.1088,20.1356,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EDE_SWMP,EDE_SWMP_LA,33.1801,0.6708,14.7539,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EEI,EEI,23.8892,0.5589,5.5749,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EES,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-3.9771,-0.9474,-20.7851,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,ERCOTE,ERCOTE,27.7862,0.7453,9.2854,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,ERCOTN,ERCOTN,1.0000,-1.1454,-15.6100,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,8.3110,-0.5889,-8.8555,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,FMPP,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,FPC,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,FPL,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,FREM_50T,OPPDFREM_GUN1_RA,9.9826,-0.2495,-7.5233,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,FREM_6,OPPDFREM_AUN6_RA,9.9686,-0.2575,-7.5294,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,FREM_7,OPPDFREM_AUN7_RA,9.9686,-0.2575,-7.5294,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,FREM_8,OPPDFREM_AUN8_RA,9.8792,-0.3468,-7.5294,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,FREM_LOAD,FREM_LOAD_LA,9.9543,-0.2717,-7.5294,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-11.2670,-0.8494,-28.1730,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,28.4247,0.9321,9.7371,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-11.0957,-2.4543,-26.3968,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-21.9836,-1.4951,-38.2439,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,40.2891,0.4487,22.0850,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,40.2891,0.4487,22.0850,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,40.2891,0.4487,22.0850,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,43.6299,0.3099,25.5646,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,43.6299,0.3099,25.5646,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,43.7621,0.3034,25.7032,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,43.7621,0.3034,25.7032,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-18.9215,-1.3241,-35.3528,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,46.9767,-0.0015,29.2228,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,46.9767,-0.0015,29.2228,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,46.9767,-0.0015,29.2228,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.VOLT.0130,V130_DDR,44.6578,0.5074,26.3950,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA.VOLT.0237,V237_DDR,44.7791,0.3832,26.6405,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDAHUB2,GRDAHUB2_H,31.2408,-0.1620,13.6474,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDAHUB3,GRDAHUB3_H,24.6619,-0.3198,7.2263,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA_GRDA,GRDA_LA,44.0972,0.3749,25.9670,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA_HUB,GRDA_H,38.4416,0.0437,20.6425,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRDA_HUBSA,GRDASA_H,38.2771,0.0185,20.5031,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,GRE,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,0.5607,0.3609,-17.5556,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GSEC_SPS,SPS_GSEC_LA,-5.3558,-0.7517,-22.3596,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,GSPR2014HUB,GSPR2014HUB_H,9.0087,-0.9666,-7.7801,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GSPR2015HUB,GSPR2015HUB_H,9.2817,-0.9722,-7.5015,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-6.4767,-1.6954,-22.5367,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,HARRISON,CSWSLEBROCKPLT1,28.0508,0.7856,9.5098,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,HAST_TNSK_HUB,HAST_TNSK_H,9.7534,-0.6226,-7.3794,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,HQST,PJM,20.0799,0.3287,1.9959,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,HST,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,18.6081,0.4171,0.4356,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,18.6081,0.4171,0.4356,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,18.7915,0.4138,0.6223,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,18.7915,0.4138,0.6223,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,18.4039,0.4180,0.2305,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,18.4039,0.4180,0.2305,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,INDN_INDN,INDN_LA,18.6657,0.4210,0.4893,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-0.1965,-1.1032,-16.8487,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,ISNE,PJM,20.0799,0.3287,1.9959,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,JEA,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,10.2798,-0.2347,-7.2409,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,10.2798,-0.2347,-7.2409,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,8.7454,0.0429,-9.0529,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KACYCT4,KACYNEARMANUNCT4_RA,17.8600,0.3251,-0.2205,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,67.3765,0.0609,49.5602,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,17.8600,0.3251,-0.2205,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,18.0896,0.3446,-0.0104,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,18.0295,0.3424,-0.0683,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KACY_KACY,KACY_LA,18.1245,0.3393,0.0298,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,23.9186,0.2257,5.9375,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,17.8287,0.8133,-0.7400,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-13.6182,-0.7629,-30.6107,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-36.9263,-1.2846,-53.3971,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.VOLT.0222,V222_DDR,8.5816,0.0997,-9.2735,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.VOLT.0223,V223_DDR,14.4119,0.0603,-3.4038,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.VOLT.0241,V241_DDR,18.8532,0.6950,0.4028,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.VOLT.0243,V243_DDR,27.1444,0.3258,9.0632,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.VOLT.0247,V247_DDR,15.3204,0.2060,-2.6410,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.VOLT.0253,V253_DDR,23.9907,0.2309,6.0044,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,1.6202,-1.2468,-14.8884,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,11.7296,-0.1338,-5.8920,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,11.7296,-0.1338,-5.8920,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,11.7296,-0.1338,-5.8920,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,11.7296,-0.1338,-5.8920,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,24.0852,0.2222,6.1076,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,24.0852,0.2222,6.1076,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHUB,KCPLHUB_H,6.7546,-0.6168,-10.3840,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHUB17,KCPLHUB17_H,5.5719,-0.7124,-11.4711,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHUB18,KCPLHUB18_H,5.4981,-0.7011,-11.5562,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHUB19,KCPLHUB19_H,5.4968,-0.6620,-11.5966,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHUB20,KCPLHUB20_H,4.6360,-0.7422,-12.3773,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHUB21,KCPLHUB21_H,4.5282,-0.7249,-12.5023,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHUB22,KCPLHUB22_H,5.4735,-0.7134,-11.5686,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHUB23,KCPLHUB23_H,4.7965,-0.7354,-12.2235,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLHUB24,KCPLHUB24_H,4.0813,-0.7774,-12.8967,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,8.4652,0.0627,-9.3530,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,8.4652,0.0627,-9.3530,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,12.7303,-0.4163,-4.6088,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,12.7303,-0.4163,-4.6088,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,23.9192,0.2263,5.9375,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,23.9186,0.2257,5.9375,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,21.5480,0.2745,3.5181,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,21.5480,0.2745,3.5181,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,21.5480,0.2745,3.5181,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,21.5480,0.2745,3.5181,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,21.5480,0.2745,3.5181,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,21.5480,0.2745,3.5181,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,21.5480,0.2745,3.5181,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,21.5480,0.2745,3.5181,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,5.5965,-0.1648,-11.9941,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,16.5210,0.2192,-1.4536,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KCPL_KCPL,KCPL_LA,17.3678,0.1908,-0.5783,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,KENN,KENN_LA,27.2762,0.7267,8.7941,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KEP2_SECI,KEP2_SECI_LA,-8.3227,-1.7139,-24.3642,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KERR_1,GRDAKERR_HYDUN1_RA,44.3375,0.3511,26.2310,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KERR_2,GRDAKERR_HYDUN2_RA,44.1875,0.3526,26.0794,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,KERR_3,GRDAKERR_HYDUN3_RA,44.1875,0.3526,26.0794,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,KERR_4,GRDAKERR_HYDUN4_RA,44.3375,0.3511,26.2310,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,11.7294,-0.1340,-5.8920,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,11.7294,-0.1340,-5.8920,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,12.3293,-0.0329,-5.3932,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,12.3293,-0.0329,-5.3932,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,10.0695,-0.1296,-7.5563,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,8.2465,-0.0977,-9.4112,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,8.2465,-0.0977,-9.4112,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-6.5678,-1.5573,-22.7659,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-6.5678,-1.5573,-22.7659,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-6.5678,-1.5573,-22.7659,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-2.0750,-0.8400,-18.9904,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-2.0750,-0.8400,-18.9904,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-6.6850,-1.5940,-22.8464,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-2.6082,-0.8963,-19.4674,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,0.7310,-0.4534,-16.5710,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,60.4700,0.0115,42.7031,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,60.4700,0.0115,42.7031,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,6.8407,-0.3201,-10.5946,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,6.8407,-0.3201,-10.5946,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,6.8407,-0.3201,-10.5946,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-3.6460,-1.2372,-20.1642,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-3.2164,-1.5009,-19.4709,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,7.9747,-0.5421,-9.2387,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,9.7853,0.1100,-8.0801,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LAFA,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LAM345,LAM345,-7.1787,-1.8020,-23.1321,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LEPA,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,11.7112,-0.2972,-5.7470,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_LES,LES_LA,11.6115,-0.3131,-5.8308,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,11.5263,-0.3348,-5.8943,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,11.5136,-0.3595,-5.8823,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,11.5136,-0.3595,-5.8823,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,11.5136,-0.3595,-5.8823,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,11.5269,-0.3342,-5.8943,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,11.5263,-0.3348,-5.8943,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_WAVERLY,LES_WAVERLY_H,11.3995,-0.3559,-6.0001,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,10.3775,-0.3643,-7.0137,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,10.3775,-0.3643,-7.0137,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,LGEE,LGEE,21.9114,0.4430,3.7130,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MALDEN,MALDEN_LA,26.7925,0.7021,8.3350,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MCWEST,MCWEST,12.2502,0.2537,-5.7590,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,MDU,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,7.5566,-0.2689,-9.9299,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,9.3092,-0.1096,-8.3367,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,11.2887,0.6028,-7.0695,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MEAN_NPPD,NPPD_MEAN_LA,7.8004,-0.8104,-9.1447,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,MEC,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MHEB,MHEB,12.8253,0.1764,-5.1065,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,1.2827,-0.9743,-15.4984,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-3.7328,-1.4578,-20.0304,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,1.2827,-0.9743,-15.4984,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,1.2827,-0.9743,-15.4984,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-3.7328,-1.4578,-20.0304,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-11.0038,-1.0936,-27.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MISO,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-7.9507,-1.3228,-24.3833,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-7.9507,-1.3228,-24.3833,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,3.1576,-0.6942,-13.9036,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-8.4398,-2.1874,-24.0078,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-3.3043,-1.2513,-19.8084,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-9.7986,-2.8906,-24.6634,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-7.7173,-1.7858,-23.6869,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-9.7573,-2.6892,-24.8235,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-7.1379,-1.2105,-23.6828,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-7.1379,-1.2105,-23.6828,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-7.1379,-1.2105,-23.6828,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-7.1379,-1.2105,-23.6828,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-7.1379,-1.2105,-23.6828,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,14.7045,0.1405,-3.1914,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,23.2087,0.5057,4.9476,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,23.2087,0.5057,4.9476,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,19.9445,0.3508,1.8383,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,18.6428,0.7824,0.1050,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MOWR,AECI,29.1022,0.3966,10.9502,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,20.2814,0.2937,2.2323,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,23.5606,0.5155,5.2897,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,9.0873,-0.8328,-7.8353,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,8.9337,-0.3962,-8.4256,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-9.9511,-1.3624,-26.3441,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,9.1437,-0.7764,-7.8353,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,13.9277,0.0802,-3.9079,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,13.9277,0.0802,-3.9079,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,13.9286,0.0811,-3.9079,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,13.9286,0.0811,-3.9079,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,8.5816,0.0997,-9.2735,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,8.5816,0.0997,-9.2735,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,8.5816,0.0997,-9.2735,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,8.5302,0.0483,-9.2735,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,8.5816,0.0997,-9.2735,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,8.5816,0.0997,-9.2735,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,8.5816,0.0997,-9.2735,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,24.0423,0.5368,5.7501,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,14.9305,0.0806,-2.9055,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,13.9299,0.0193,-3.8448,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,13.9300,0.0194,-3.8448,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,13.9300,0.0194,-3.8448,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,17.9286,0.2366,-0.0634,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,17.9286,0.2366,-0.0634,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MPS_MPS,MPS_LA,15.0357,0.2691,-2.9888,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MSTNG,SPSMSTNGPLT1,-0.3801,0.1300,-18.2655,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MSTNG4,SPSMSTNGUN4_RA,-0.4669,0.0431,-18.2655,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,MSTNG5,SPSMSTNGUN5_RA,-0.3801,0.1300,-18.2655,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,-0.3801,0.1300,-18.2655,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NBSO,PJM,20.0799,0.3287,1.9959,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,9.7795,-0.7228,-7.2531,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,9.7767,-0.7256,-7.2531,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-7.8174,-2.1109,-23.4619,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NHC1,VACS,26.1371,0.7161,7.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,10.2052,-0.2835,-7.2667,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,10.2052,-0.2835,-7.2667,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,10.2052,-0.2835,-7.2667,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,5.7632,-0.8104,-11.1818,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,8.9934,-0.9364,-7.8257,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,10.2674,-0.6508,-6.8372,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,3.6889,-0.5439,-13.5227,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,8.9934,-0.9364,-7.8257,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.HUB.PY2018,NPPDPY18_H,7.7080,-0.8823,-9.1651,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,7.8107,-0.8737,-9.0711,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,7.7781,-0.8706,-9.1067,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,7.8774,-0.8559,-9.0221,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,1.2690,-0.5773,-15.9091,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,6.7497,-0.9282,-10.0775,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,6.7497,-0.9282,-10.0775,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,6.0707,-0.8242,-10.8605,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,1.2690,-0.5773,-15.9091,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,14.3415,-1.0449,-2.3691,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,8.0238,-1.1898,-8.5418,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,3.8381,-1.0354,-12.8819,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,8.0238,-1.1898,-8.5418,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,9.0701,-1.0049,-7.6804,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,7.5683,-1.0697,-9.1174,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,11.1038,-0.2153,-6.4363,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,8.9934,-0.9364,-7.8257,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,4.3026,-1.0291,-12.4237,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,6.7497,-0.9282,-10.0775,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,6.7497,-0.9282,-10.0775,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,7.6274,-0.6372,-9.4908,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,7.5577,-0.6487,-9.5491,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,7.5577,-0.6487,-9.5491,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,8.4415,-0.3045,-9.0094,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,5.3197,-0.2206,-12.2151,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,9.3102,-0.7027,-7.7425,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,5.9509,-0.5605,-11.2440,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,3.5928,-0.1376,-14.0251,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,2.1955,-0.1394,-15.4205,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.NELI.DDR,NELI_DDR,2.5089,-0.6936,-14.5529,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.NPPM.1058,SH1058_DDR,22.9234,-0.0650,5.2330,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,8.4355,-0.4712,-8.8487,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,8.9934,-0.9364,-7.8257,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,10.2674,-0.6508,-6.8372,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,1.2690,-0.5773,-15.9091,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.TECH.1,KEARNE_DDR,8.8617,-0.3076,-8.5861,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,9.3502,-1.3676,-7.0376,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,9.3502,-1.3676,-7.0376,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,1.3145,-0.6622,-15.7787,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD.VOLT.0236,V236_DDR,10.3665,-0.2962,-7.0927,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD2017HUB,NPPD2017HUB_H,7.7240,-0.8793,-9.1521,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,20.5337,-0.5559,3.3342,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,5.7632,-0.8104,-11.1818,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,7.9217,-1.4407,-8.3930,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,7.9217,-1.4407,-8.3930,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,10.4808,-0.3186,-6.9560,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,10.3919,-0.2708,-7.0927,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,3.4860,-0.5394,-13.7300,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,7.7151,-0.6632,-9.3771,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,22.4989,-0.4895,5.2330,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,22.4989,-0.4895,5.2330,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,22.4989,-0.4895,5.2330,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,9.7574,-0.6217,-7.3763,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,9.6813,-0.6891,-7.3850,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,9.7266,-0.4225,-7.6063,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,3.4896,-1.5338,-12.7320,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,3.5862,-1.4372,-12.7320,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,5.9357,-1.0324,-10.7873,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,5.7176,-1.0457,-10.9921,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,10.6422,-0.5737,-6.5395,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,10.6279,-0.5880,-6.5395,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,10.6279,-0.5880,-6.5395,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,10.5887,-0.5535,-6.6132,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,14.3415,-1.0449,-2.3691,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,10.5167,-0.5544,-6.6843,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,10.9758,-0.4536,-6.3260,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,9.7894,-0.5827,-7.3833,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,9.7773,-0.5935,-7.3847,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,9.7843,-0.5853,-7.3859,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,9.7843,-0.5853,-7.3859,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,9.7574,-0.6217,-7.3763,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,9.7249,-0.6542,-7.3763,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,7.3956,-0.0762,-10.2836,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,10.0284,-0.3539,-7.3731,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,5.8959,-0.9719,-10.8876,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,6.9436,-1.2019,-9.6100,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,3.5117,-1.1017,-13.1420,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,23.2949,0.3065,5.2330,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,2.5089,-0.6936,-14.5529,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,6.1607,-0.9819,-10.6128,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,6.1607,-0.9819,-10.6128,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_NPPD,NPPD_LA,12.0528,-0.4908,-5.2117,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,10.9758,-0.4536,-6.3260,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,10.9758,-0.4536,-6.3260,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,8.4115,-0.7340,-8.6099,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,7.1575,-0.8591,-9.7388,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NSB,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,NSP,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,NSSO,PJM,20.0799,0.3287,1.9959,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,NYIS,PJM,20.0799,0.3287,1.9959,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-12.9748,-2.0637,-28.6665,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-18.4440,-1.4219,-34.7775,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-15.4949,-1.2763,-31.9740,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-15.4949,-1.2763,-31.9740,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-12.4470,-2.2865,-27.9159,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-21.9836,-1.4951,-38.2439,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-81.5900,-0.8810,-98.4644,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-38.3542,-1.3271,-54.7825,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-20.4898,-1.3325,-36.9127,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-18.1651,-1.4229,-34.4976,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,4.1618,-0.5896,-13.0040,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-20.4898,-1.3325,-36.9127,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-12.6185,-2.2428,-28.1311,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-11.0038,-1.0936,-27.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-13.1919,-2.0254,-28.9219,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,23.3700,-0.2432,5.8578,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-18.1651,-1.4229,-34.4976,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-16.8224,-1.3371,-33.2407,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-10.2385,-1.3216,-26.6723,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-12.4725,-1.1469,-29.0810,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-21.6690,-0.2552,-39.1692,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-11.0038,-1.0936,-27.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-11.0038,-1.0936,-27.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-18.1651,-1.4229,-34.4976,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-9.6101,-0.9808,-26.3847,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.NUEN.LAM1,LAM1_DDR,40.2896,1.2413,21.2929,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.NUEN.MDT2,MDT2_DDR,4.1618,-0.5896,-13.0040,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.NUEN.MDT3,MDT3_DDR,4.1618,-0.5896,-13.0040,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-10.0146,-1.0127,-26.7573,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,1.3367,-0.6517,-15.7670,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,1.3367,-0.6517,-15.7670,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,1.3367,-0.6517,-15.7670,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,8.2185,-0.5728,-8.9641,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,8.2185,-0.5728,-8.9641,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,1.3367,-0.6517,-15.7670,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,1.3367,-0.6517,-15.7670,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-18.1651,-1.4229,-34.4976,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,31.4882,0.9182,12.8146,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-12.6185,-2.2428,-28.1311,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-13.3538,-0.6138,-30.4954,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-16.8224,-1.3371,-33.2407,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,36.0590,0.9288,17.3747,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-18.1388,-1.1123,-34.7819,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-18.1388,-1.1123,-34.7819,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-18.1388,-1.1123,-34.7819,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-18.1388,-1.1123,-34.7819,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-18.1375,-1.8655,-34.0274,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-21.2403,-1.3255,-37.6702,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-18.4440,-1.4219,-34.7775,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-24.4389,-1.2663,-40.9280,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-24.4389,-1.2663,-40.9280,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-10.6560,-0.2830,-28.1284,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-14.6412,-1.2459,-31.1507,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-14.6412,-1.2459,-31.1507,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-14.6412,-1.2459,-31.1507,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0033,FOSTER_DDR,15.2058,-0.5261,-2.0235,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,33.1297,0.3660,15.0083,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0035,TARBY_DDR,40.2278,1.0297,21.4427,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,33.1297,0.3660,15.0083,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,31.8595,0.1535,13.9506,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,31.8595,0.1535,13.9506,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-17.1687,-0.3706,-34.5535,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0040,TROSPER_DDR,19.2683,-0.5001,2.0130,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,19.3781,-0.5022,2.1249,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,37.6007,1.0641,18.7812,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0115,V115_DDR,5.3363,-0.5792,-11.8399,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0116,V116_DDR,42.8985,-0.1628,25.3059,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0118,V118_DDR,10.5312,-0.1014,-7.1228,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0125,V125_DDR,38.4079,1.2045,19.4480,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0126,V126_DDR,40.1935,0.5942,21.8438,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0129,V129_DDR,0.8215,-1.0692,-15.8647,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,49.6379,-0.6034,32.4859,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0134,V134_DDR,41.0733,0.7673,22.5506,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0138,V138_DDR,39.4906,0.4940,21.2412,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,41.8298,-0.5188,24.5932,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0143,V143_DDR,35.6908,0.2219,17.7135,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0149,V149_DDR,-9.3082,-0.9950,-26.0686,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0150,V150_DDR,-8.8239,-1.0166,-25.5627,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0155,V155_DDR,38.8332,0.3926,20.6852,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0156,V156_DDR,49.6379,-0.6034,32.4859,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0166,V166_DDR,40.3570,1.0070,21.5945,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,40.8972,-0.5257,23.6675,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-8.8239,-1.0166,-25.5627,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0170,V170_DDR,-10.0933,-1.0059,-26.8429,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-20.6068,-0.9891,-37.3731,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0176,V176_DDR,-8.8239,-1.0166,-25.5627,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0177,V177_DDR,-14.9284,-1.8306,-30.8532,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,32.5542,-0.5232,15.3220,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-8.7970,-1.1448,-25.4076,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0195,V195_DDR,135.9767,1.0133,117.2079,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0197,V197_DDR,40.9248,0.5772,22.5922,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0198,V198_DDR,40.3570,1.0070,21.5945,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0208,V208_DDR,136.0000,1.0381,117.2065,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0209,V209_DDR,136.0000,1.0381,117.2065,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,40.9889,0.4246,22.8089,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0216,V216_DDR,19.4049,-0.5035,2.1530,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0219,V219_DDR,38.8332,0.3926,20.6852,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0220,V220_DDR,-8.8239,-1.0166,-25.5627,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0224,V224_DDR,4.5158,-0.6083,-12.6313,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0225,V225_DDR,4.5167,-0.6074,-12.6313,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0226,V226_DDR,4.5158,-0.6083,-12.6313,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0227,V227_DDR,4.5158,-0.6083,-12.6313,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0229,V229_DDR,-14.6090,-0.3146,-32.0498,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0231,V231_DDR,16.0090,-0.0346,-1.7118,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0238,V238_DDR,-18.7158,-1.4899,-34.9813,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.VOLT.0242,V242_DDR,39.1212,0.4411,20.9247,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-15.0000,-2.3967,-30.3587,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-11.0038,-1.0936,-27.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-18.6689,-1.3731,-35.0512,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-13.1765,-2.0100,-28.9219,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-15.0000,-2.3967,-30.3587,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-13.6032,-2.2762,-29.0824,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-42.8832,-1.2903,-59.3483,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEHL7,OKGEHL7_H,29.9783,-0.4735,12.6964,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEHL8,OKGEHSL1UN8_RA,29.9783,-0.4735,12.6964,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEHL910,OKGEHSL1PLT2,29.9783,-0.4735,12.6964,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-13.3608,-2.1291,-28.9871,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEMCC,OKGEMCCLAIPLT1,1.6300,-0.7752,-15.3502,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,35.8583,0.2955,17.8074,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,35.8583,0.2955,17.8074,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,35.8583,0.2955,17.8074,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,22.9973,-0.7365,5.9784,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,22.9973,-0.7365,5.9784,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,22.9973,-0.7365,5.9784,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,22.9973,-0.7365,5.9784,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGESM1,OKGESEMINOLEUN1_RA,11.8210,-0.3723,-5.5622,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGESM2,OKGESEMINOLEUN2_RA,11.6947,-0.4122,-5.6485,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGESM3,OKGESEMINOLEUN3_RA,11.6947,-0.4122,-5.6485,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGESO1,OKGESONR1UN1_RA,-44.6441,-1.1746,-61.2249,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGESO2,OKGESONR1UN2_RA,-24.4389,-1.2663,-40.9280,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-13.5041,-2.2725,-28.9871,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-13.3517,-2.3672,-28.7399,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGETINK5A,OKGETINK5UN1_RA,16.6630,-0.5310,-0.5614,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGETINK5B,OKGETINK5UN2_RA,16.6630,-0.5310,-0.5614,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-13.9485,-1.7663,-29.9376,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-18.4440,-1.4219,-34.7775,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,37.1244,1.4067,17.9623,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-11.0038,-1.0936,-27.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE_OKGE,OKGE_LA,19.5151,-0.2738,2.0334,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-13.3538,-0.6138,-30.4954,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-14.0000,-1.8178,-29.9376,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMLP,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,44.4436,0.1835,26.5047,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,37.3481,1.2961,18.2966,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_GENHUB,OMPA_GENHUB_H,4.0041,-0.5621,-13.1893,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-81.4481,-0.7391,-98.4644,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-11.0896,-1.2884,-27.5566,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-20.4898,-1.3325,-36.9127,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-14.4098,-1.9038,-30.2614,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,0.3658,-1.4177,-15.9720,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,166.7998,0.0975,148.9469,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-81.4917,-0.7827,-98.4644,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-81.4917,-0.7827,-98.4644,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_SPP,OMPA_SPP_LA,2.6519,-0.7630,-14.3404,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-15.0000,-2.3967,-30.3587,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,41.1689,0.1737,23.2398,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,41.1689,0.1737,23.2398,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,41.1689,0.1737,23.2398,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,41.1689,0.1737,23.2398,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,ONT,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,10.1234,-0.2868,-7.3452,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,10.1234,-0.2868,-7.3452,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,10.1234,-0.2868,-7.3452,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,10.1234,-0.2868,-7.3452,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,10.1234,-0.2868,-7.3452,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,10.1234,-0.2868,-7.3452,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,10.1234,-0.2868,-7.3452,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,10.1234,-0.2868,-7.3452,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,10.1234,-0.2868,-7.3452,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,10.2250,-0.2642,-7.2662,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,10.2052,-0.2835,-7.2667,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,10.5555,-0.0923,-7.1076,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,10.3867,-0.2263,-7.1424,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,10.3867,-0.2263,-7.1424,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD_GLDN,OPPD_GLDN_LA,10.2908,-0.2749,-7.1897,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,10.1787,-0.2731,-7.3036,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,14.3415,-1.0449,-2.3691,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,9.6458,-0.4884,-7.6212,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,10.2062,-0.2825,-7.2667,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD_OPPD,OPPD_LA,10.3328,-0.2184,-7.2043,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,10.3844,-0.2078,-7.1633,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,10.3868,-0.2130,-7.1556,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OTP,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,OVEC,OVEC,21.1956,0.3997,3.0405,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PARAGOULD,PARAGOULD_LA,28.0939,0.7663,9.5722,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,43.9779,0.2463,25.9762,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,43.9779,0.2463,25.9762,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,43.9779,0.2463,25.9762,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,43.7045,0.3078,25.6413,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,43.7045,0.3078,25.6413,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,43.7045,0.3078,25.6413,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PIGGOTT,PIGGOTT_LA,27.1038,0.7180,8.6304,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PJM,PJM,20.0799,0.3287,1.9959,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,PLUM,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,POPLARBLUFF,POPLARBLUFF_LA,26.4061,0.6501,8.0006,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,11.9635,-0.0196,-5.7724,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,11.9635,-0.0196,-5.7724,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,11.9956,-0.0161,-5.7437,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,11.9956,-0.0161,-5.7437,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,13.2165,1.1875,-5.7265,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,13.2165,1.1875,-5.7265,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,12.2453,0.2457,-5.7558,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,11.3305,-0.5190,-5.9059,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-12.8453,-0.8645,-29.7362,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,88.1189,0.1907,70.1728,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,9.4030,0.1782,-8.5306,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,5.5140,-0.0302,-12.2112,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,54.7357,0.5530,36.4273,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,40.4352,0.7261,21.9537,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,11.3164,-0.3303,-6.1087,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,12.3014,0.2843,-5.7383,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,10.0579,-0.5645,-7.1330,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,25.0000,1.1367,6.1079,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,12.7090,0.3170,-5.3634,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,10.9782,-0.1580,-6.6193,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,PUPP,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,RCEAST,RCEAST,9.4360,-0.7993,-7.5201,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SALINA_1,GRDASALINA1UN1_RA,44.3395,0.3531,26.2310,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SALINA_2,GRDASALINA1UN2_RA,44.3395,0.3531,26.2310,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SALINA_3,GRDASALINA1UN3_RA,44.3395,0.3531,26.2310,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SALINA_4,GRDASALINA1UN4_RA,44.3395,0.3531,26.2310,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SALINA_5,GRDASALINA1UN5_RA,44.3395,0.3531,26.2310,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SALINA_6,GRDASALINA1UN6_RA,44.3395,0.3531,26.2310,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SARPY_1,OPPDSARPYUN1_RA,10.2605,-0.2688,-7.2261,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SARPY_2,OPPDSARPYUN2_RA,10.3077,-0.2310,-7.2167,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SARPY_3,OPPDSARPYUN3_RA,10.2487,-0.3021,-7.2046,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SARPY_4,OPPDSARPYUN4_RA,10.2487,-0.3021,-7.2046,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SARPY_5,OPPDSARPYUN5_RA,10.2487,-0.3021,-7.2046,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SC,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SCEG,VACS,26.1371,0.7161,7.6656,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SCSE,SCSE,6.3459,-0.8158,-10.5937,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SEC,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-9.5000,-1.9584,-25.2970,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-9.5000,-1.9584,-25.2970,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-9.5000,-1.9584,-25.2970,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-6.5554,-1.2009,-23.1099,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-9.5000,-1.9584,-25.2970,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-7.8528,-1.9704,-23.6378,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-7.5642,-2.1146,-23.2050,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-7.5642,-2.1146,-23.2050,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-7.1402,-1.2128,-23.6828,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-10.6366,-1.6849,-26.7072,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-2.1538,-0.9188,-18.9904,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-7.2157,-1.3170,-23.6541,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-1.9689,-1.4433,-18.2810,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-9.1118,-1.9939,-24.8733,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-1.8885,-1.4302,-18.2137,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-8.4622,-2.1012,-24.1164,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-9.7921,-3.5399,-24.0076,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-6.7183,-1.6421,-22.8317,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-6.7183,-1.6421,-22.8317,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-6.7183,-1.6421,-22.8317,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-6.7183,-1.6421,-22.8317,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-7.0077,-1.7495,-23.0137,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-7.8528,-1.9704,-23.6378,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI_SECI,SECI_LA,-6.3616,-1.4598,-22.6572,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-0.1965,-1.1032,-16.8487,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-0.1965,-1.1032,-16.8487,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-7.1402,-1.2128,-23.6828,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SEHA,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-14.0000,-1.8178,-29.9376,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SERU,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SETH,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SGE,SGE,6.9660,-0.7417,-10.0477,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SMEP,MISO,20.4728,0.3819,2.3355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SOCO,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPA,SPA,35.7264,0.8253,17.1457,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPC,SPC,12.7951,0.7220,-5.6823,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPPNORTH_HUB,SPPNORTH_H,11.0545,-0.3008,-6.4001,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPPSOUTH_HUB,SPPSOUTH_H,8.0446,-0.9193,-8.7915,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,33.1117,0.7279,14.6284,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,33.1117,0.7279,14.6284,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,32.4530,0.7044,13.9931,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,32.4530,0.7044,13.9931,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_NIXA,SPRM_NIXA_LA,33.6116,0.7524,15.1038,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_SPRM,SPRM_LA,33.1754,0.7798,14.6403,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,33.2961,0.6352,14.9055,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,33.2961,0.6352,14.9055,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,33.2516,0.5907,14.9055,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,33.2961,0.6352,14.9055,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-5.6258,-0.5470,-22.8342,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-6.0605,-0.9893,-22.8266,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-7.5391,-1.6874,-23.6071,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-7.5391,-1.6874,-23.6071,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-6.0587,-1.5641,-22.2500,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,-2.2244,-0.7854,-19.1945,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-7.8618,-2.3793,-23.2379,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,46.8682,0.7283,28.3845,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-4.9373,-0.7156,-21.9772,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,37.7530,0.1060,19.8916,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,44.6160,0.1954,26.6652,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,44.6160,0.1954,26.6652,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,37.7530,0.1060,19.8916,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-7.3304,-1.4960,-23.5898,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-6.0605,-0.9893,-22.8266,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-7.4946,-1.5778,-23.6722,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-10.3721,-2.2654,-25.8621,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-8.2446,-1.4790,-24.5210,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-7.3333,-1.2006,-23.8881,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-7.8051,-1.5715,-23.9891,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-12.1683,-2.2939,-27.6298,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-12.1683,-2.2939,-27.6298,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-12.1683,-2.2939,-27.6298,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-12.1683,-2.2939,-27.6298,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GRID.WRAB,WRAB_DDR,-6.6102,-1.3025,-23.0631,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-12.1683,-2.2939,-27.6298,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-5.6861,-0.9059,-22.5356,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-5.6861,-0.9059,-22.5356,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-5.8511,-0.8753,-22.7313,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-5.8511,-0.8753,-22.7313,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-5.8511,-0.8753,-22.7313,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-5.6861,-0.9059,-22.5356,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-6.7119,-1.6941,-22.7733,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-6.7124,-1.6940,-22.7738,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-6.7106,-1.6940,-22.7720,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-7.8174,-2.1109,-23.4619,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,40.0509,0.0769,22.2186,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-4.9611,-0.7296,-21.9869,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-4.9611,-0.7296,-21.9869,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-4.9611,-0.7296,-21.9869,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-4.9611,-0.7296,-21.9869,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,16.2152,0.1435,-1.6837,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,36.8485,0.0533,19.0398,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,36.8485,0.0533,19.0398,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-13.9216,-1.7394,-29.9376,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-6.8691,-1.7150,-22.9095,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-6.8691,-1.7150,-22.9095,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-6.7366,-1.6893,-22.8027,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-6.6102,-1.3025,-23.0631,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-9.9099,-2.0049,-25.6604,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-7.9269,-1.7039,-23.9784,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-12.4470,-2.2865,-27.9159,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-6.6284,-1.4743,-22.9095,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-5.8992,-0.6647,-22.9899,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-5.8992,-0.6647,-22.9899,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-5.9732,-0.6887,-23.0399,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-5.6827,-1.2526,-22.1855,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-11.0399,-2.1248,-26.6705,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-7.4113,-1.9288,-23.2379,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-5.6675,-1.2374,-22.1855,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-7.3354,-1.5010,-23.5898,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-8.8587,-0.6520,-25.9621,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,46.8682,0.7283,28.3845,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-8.8587,-0.6520,-25.9621,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,46.8735,0.7203,28.3978,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-16.4338,-1.7511,-32.4381,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,43.8692,1.1505,24.9633,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,43.9407,1.2220,24.9633,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,41.5666,1.0769,22.7343,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,36.7667,0.2626,18.7487,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,46.7209,0.9546,28.0109,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-7.1787,-1.8020,-23.1321,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-6.6787,-1.3824,-23.0517,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-6.1969,-0.6518,-23.3005,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-6.1969,-0.6518,-23.3005,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-8.8587,-0.6520,-25.9621,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-4.8082,-0.6145,-21.9491,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,2.3344,0.5904,-16.0114,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-5.0612,0.4078,-23.2244,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-5.6852,-0.2728,-23.1678,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-5.8470,-0.9838,-22.6186,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,43.8692,1.1505,24.9633,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,46.5538,1.4165,27.3819,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,46.3300,1.1927,27.3819,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-5.4682,-1.0381,-22.1855,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-5.6361,-0.1526,-23.2389,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-10.7557,-2.0547,-26.4564,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-10.7777,-2.0818,-26.4513,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0163,V163_DDR,-6.4693,-1.4158,-22.8090,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0168,V168_DDR,-10.0677,-1.3073,-26.5158,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0180,V180_DDR,46.5538,1.4165,27.3819,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0181,V181_DDR,-10.6639,-1.8403,-26.5790,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0182,V182_DDR,47.0057,0.9821,28.2682,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0199,V199_DDR,2.9882,0.4300,-15.1972,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0200,V200_DDR,39.0867,0.5422,20.7891,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.VOLT.0235,V235_DDR,-9.9099,-2.0049,-25.6604,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-7.8618,-2.3793,-23.2379,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,46.8682,0.7283,28.3845,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-6.5783,-1.7970,-22.5367,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-6.5970,-1.5626,-22.7898,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS_SPS,SPS_LA,17.3208,0.0423,-0.4769,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,-3.0023,-0.2272,-20.5305,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SSCN_NPPD,SSCN_NPPD_LA,5.0851,-0.4688,-12.2016,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,25.3818,0.6281,6.9983,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,25.3818,0.6281,6.9983,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,TAL,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,TEC,SOUC,26.5155,0.7518,8.0082,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,6.9436,-1.2019,-9.6100,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,TVA,TVA,25.7372,0.6784,7.3033,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,UCUHUB,UCUHUB_H,6.1120,-0.3089,-11.3345,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,UCUHUB17,UCUHUB17_H,1.1318,-1.1391,-15.4845,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,UCUHUB18,UCUHUB18_H,4.2916,-0.7520,-12.7118,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,UCUHUB19,UCUHUB19_H,0.5931,-0.8963,-16.2660,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,UCUHUB20,UCUHUB20_H,0.5659,-0.8770,-16.3124,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,UCUHUB21,UCUHUB21_H,-1.1998,-1.1003,-17.8549,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,UCUHUB22,UCUHUB22_H,-0.7808,-1.0405,-17.4957,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,UCUHUB23,UCUHUB23_H,-1.0707,-1.0539,-17.7722,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,UCUHUB24,UCUHUB24_H,1.3069,-0.9189,-15.5296,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,12.9781,0.9156,-5.6929,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,12.9781,0.9156,-5.6929,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,11.6703,-0.2677,-5.8174,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,11.6703,-0.2677,-5.8174,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,11.8777,-0.4491,-5.4286,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,11.8737,-0.1576,-5.7241,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,11.8737,-0.1576,-5.7241,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,12.9781,0.9156,-5.6929,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,11.9515,-0.4210,-5.3829,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,12.5596,0.3306,-5.5264,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,10.3534,-0.4665,-6.9355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,8.6886,-1.6759,-7.3909,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,12.8607,0.8258,-5.7205,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,12.8607,0.8258,-5.7205,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,9.8112,-1.6286,-6.3157,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,10.7662,-0.4867,-6.5025,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,13.9219,-0.0729,-3.7606,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,9.8125,-0.5971,-7.3458,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,10.5712,-0.2136,-6.9706,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,10.5462,-0.5513,-6.6579,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,10.7635,-0.6762,-6.3157,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,10.7635,-0.6762,-6.3157,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,10.9924,-0.4018,-6.3612,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,8.7702,-1.7813,-7.2039,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,11.2983,0.4769,-6.9340,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,12.2617,0.2388,-5.7325,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,12.2617,0.2388,-5.7325,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,12.2617,0.2388,-5.7325,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,12.4272,0.4076,-5.7358,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,12.4272,0.4076,-5.7358,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,12.4272,0.4076,-5.7358,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,13.2415,1.1633,-5.6773,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,11.7839,-0.2739,-5.6976,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,11.6598,-0.2916,-5.8040,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,6.6539,-0.7818,-10.3197,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,9.9290,-0.3493,-7.4772,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,12.3891,0.2498,-5.6161,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,7.7454,-0.6210,-9.3890,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,8.1463,-2.2375,-7.3716,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,11.2907,-0.4385,-6.0262,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,12.9642,0.9231,-5.7143,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,12.9642,0.9231,-5.7143,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,12.9633,0.9221,-5.7143,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,12.9642,0.9231,-5.7143,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,12.7674,0.7340,-5.7220,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,12.7674,0.7340,-5.7220,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,12.7674,0.7340,-5.7220,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,12.7674,0.7340,-5.7220,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,12.7674,0.7340,-5.7220,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,12.7674,0.7340,-5.7220,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,12.7674,0.7340,-5.7220,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,7.9637,-1.3036,-8.4882,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,12.2849,-0.0143,-5.4562,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,8.9344,-0.2643,-8.5567,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,8.9344,-0.2643,-8.5567,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,6.6432,-0.6243,-10.4879,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,6.6432,-0.6243,-10.4879,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,12.0231,-0.0347,-5.6976,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,12.0795,-0.1426,-5.5333,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,9.9911,-0.7302,-7.0342,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,9.2970,-1.4889,-6.9695,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,11.8637,-0.1421,-5.7496,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,11.8777,-0.4491,-5.4286,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,11.8777,-0.4491,-5.4286,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,9.8125,-0.5971,-7.3458,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,9.3930,-0.8275,-7.5349,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,10.4668,-0.6573,-6.6313,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,8.9193,-1.6322,-7.2039,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,10.7707,-0.6051,-6.3796,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.FSE,WAUE.FSE_H,8.0139,-0.7950,-8.9465,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,12.0675,0.0454,-5.7334,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,12.0275,0.0078,-5.7357,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,8.3517,-1.5865,-7.8173,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,9.0694,-1.5044,-7.1816,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,11.8487,-0.4009,-5.5058,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,11.8466,-0.4394,-5.4694,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-12.0300,-1.3371,-28.4484,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,8.6886,-1.6759,-7.3909,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-0.8600,-0.6588,-17.9566,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,10.3441,-0.3937,-7.0176,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,10.3445,-0.3933,-7.0176,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,10.3445,-0.3933,-7.0176,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,10.5620,-0.4382,-6.7553,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,9.3930,-0.8275,-7.5349,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,11.4166,-0.0729,-6.2659,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,9.7090,-0.6336,-7.4128,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,11.2525,0.4311,-6.9340,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,11.2250,0.2997,-6.8301,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,10.6717,-0.2054,-6.8783,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,13.0109,-0.0990,-4.6455,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,10.2090,-0.3990,-7.1474,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,9.9462,-0.7073,-7.1020,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,7.7454,-0.6210,-9.3890,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,13.8948,0.4803,-4.3409,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,9.7913,-0.6162,-7.3479,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,13.8104,0.4309,-4.3759,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,11.1645,-0.0727,-6.5182,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,10.3775,-0.3643,-7.0137,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NTWK,WAUE.NTWK_H,10.6953,-0.2743,-6.7859,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,12.1351,0.6855,-6.3059,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,12.1351,0.6855,-6.3059,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,8.5415,-1.7545,-7.4594,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,7.2426,-1.7115,-8.8013,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,11.2076,-0.3805,-6.1673,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,8.5415,-1.7545,-7.4594,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,12.6012,-0.0160,-5.1382,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,9.9943,-0.8256,-6.9355,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,7.7454,-0.6210,-9.3890,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,10.7118,-0.4108,-6.6328,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,9.1147,-1.7053,-6.9355,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,7.5965,-2.0645,-8.0944,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,7.9980,-2.0655,-7.6920,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,11.6405,-0.3067,-5.8083,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,9.1889,-1.5183,-7.0483,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,11.5605,-0.1056,-6.0893,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,9.5383,-1.2102,-7.0069,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,9.2970,-1.4889,-6.9695,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.VOLT.0152,V152_DDR,13.4625,1.3586,-5.6515,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE.VOLT.0172,V172_DDR,12.8517,0.8152,-5.7190,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_BEPM,WAUE_BEPM_LA,11.9069,0.3095,-6.1581,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,11.2967,-0.1199,-6.3388,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,11.2298,0.3095,-6.8351,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_EWA,WAUE_EWA_LA,9.4999,-0.7439,-7.5116,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,9.4834,-0.7634,-7.5086,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_HMMU,WAUE_HMMU_LA,10.8990,0.1404,-6.9968,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,13.0455,-0.0967,-4.6132,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_MECB,WAUE_MECB_LA,10.7390,0.3566,-7.3731,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_MMPA,WAUE_MMPA_LA,12.9099,0.3597,-5.2053,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_MRES,WAUE_MRES_LA,10.7184,-0.2735,-6.7635,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,13.1714,1.0134,-5.5974,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,12.0675,0.0454,-5.7334,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,9.3186,-0.6657,-7.7712,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_OTP,WAUE_OTP_LA,13.4986,0.9002,-5.1570,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_OTPW,WAUE_OTPW_LA,14.6191,0.3580,-3.4943,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM,WAUE_UGPM_LA,11.3246,-0.1410,-6.2898,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,11.5082,0.0492,-6.2965,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,10.3526,-0.3550,-7.0479,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,9.9048,-0.6266,-7.2240,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,9.4999,-0.7439,-7.5116,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,10.8990,0.1404,-6.9968,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,9.4847,-0.7151,-7.5555,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,12.0675,0.0454,-5.7334,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,12.9099,0.3597,-5.2053,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,11.1069,-0.1754,-6.4731,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,9.7018,-0.8086,-7.2450,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,13.3280,0.9557,-5.3831,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-14.7617,-2.1568,-30.3603,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-18.1800,-1.7156,-34.2198,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,11.1314,-1.0343,-5.5897,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,92.5800,0.4142,74.4104,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,92.5800,0.4142,74.4104,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-2.7523,-2.3144,-18.1934,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,85.5518,0.5257,67.2707,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,77.2797,0.5127,59.0116,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,41.8647,-1.1058,25.2151,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,41.8647,-1.1058,25.2151,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,41.8647,-1.1058,25.2151,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,41.8647,-1.1058,25.2151,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,41.8259,-1.1447,25.2151,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,41.8647,-1.1058,25.2151,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,41.8647,-1.1058,25.2151,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,41.8647,-1.1058,25.2151,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,28.3143,-1.0366,11.5955,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-12.4470,-2.2865,-27.9159,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-22.3384,-1.8237,-38.2701,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-14.9267,-2.0536,-30.6285,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-7.5601,-2.0776,-23.2379,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_ENMC,WFEC_ENMC_LA,19.7402,0.2801,1.7047,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-18.1651,-1.4229,-34.4976,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,35.5595,0.3509,17.4532,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,22.3137,0.0514,4.5068,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-14.7617,-2.1568,-30.3603,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-14.7617,-2.1568,-30.3603,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-14.7617,-2.1568,-30.3603,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_OKGE,WFEC_OKGE_LA,10.7826,0.0292,-7.0020,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,52.0185,0.4807,33.7824,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-11.4861,-2.0351,-27.2064,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-4.5610,-2.1538,-20.1626,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_WFEC,WFEC_LA,23.4098,-0.4657,6.1202,17.7553\n03/19/2025 08:00:00,03/19/2025 13:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,22.3137,0.0514,4.5068,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,0.3679,-1.0171,-16.3704,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-5.3221,-1.7275,-21.3501,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,2.3187,-0.6017,-14.8350,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,2.3187,-0.6017,-14.8350,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,2.3188,-0.6017,-14.8350,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,2.3188,-0.6017,-14.8350,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,2.3187,-0.6017,-14.8350,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,2.3186,-0.6018,-14.8350,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,2.3186,-0.6018,-14.8350,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,7.5421,0.6611,-10.8744,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,0.6505,-0.8815,-16.2234,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-14.5019,-1.3321,-30.9252,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-14.5019,-1.3321,-30.9252,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-14.5019,-1.3321,-30.9252,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-10.7561,-1.7040,-26.8075,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-10.7561,-1.7040,-26.8075,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-10.2886,-1.2304,-26.8136,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-10.2886,-1.2304,-26.8136,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-10.2886,-1.2304,-26.8136,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,0.6505,-0.8815,-16.2234,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,8.8094,0.0471,-8.9931,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-4.3362,-0.9449,-21.1467,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-4.3362,-0.9449,-21.1467,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-4.3362,-0.9449,-21.1467,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-4.3362,-0.9449,-21.1467,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,8.8094,0.0471,-8.9931,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-8.5097,-2.0490,-24.2161,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-26.1408,-0.4947,-43.4016,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.JEC.1,WRJEFFUN10_RA,4.0753,-0.4479,-13.2322,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.JEC.2,WRJEFFUN11_RA,4.1162,-0.4512,-13.1880,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.JEC.3,WRJEFFUN12_RA,4.0901,-0.4774,-13.1880,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-18.9215,-1.3241,-35.3528,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-9.9397,-1.3510,-26.3441,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-9.9397,-1.3510,-26.3441,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.LEC.4,WRLECUN26_RA,8.5940,-0.0306,-9.1308,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.LEC.5,WRLECUN27_RA,8.0192,0.0056,-9.7419,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-2.5992,-0.8253,-19.5293,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-2.5992,-0.8253,-19.5293,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-2.5992,-0.8253,-19.5293,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-2.5400,-0.7915,-19.5039,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-0.1965,-1.1032,-16.8487,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-0.1965,-1.1032,-16.8487,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-1.7936,-1.3016,-18.2474,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,0.8052,-0.9104,-16.0398,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,0.8052,-0.9104,-16.0398,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-3.2257,-1.5103,-19.4709,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-0.1965,-1.1032,-16.8487,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,6.3893,-0.9179,-10.4482,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-0.1746,-1.0363,-16.8938,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-9.9449,-1.3562,-26.3441,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,79.7154,0.5304,61.4296,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-3.8678,-2.2074,-19.4158,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,2.3186,-0.6018,-14.8350,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-2.8507,-1.2878,-19.3183,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,8.8094,0.0471,-8.9931,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,0.6505,-0.8815,-16.2234,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-12.0893,-1.0516,-28.7931,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.THAYERLD,WR.THAYERLD_LA,28.0796,0.6893,9.6349,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-12.8765,-1.0430,-29.5890,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0106,V106_DDR,-12.0046,-1.0000,-28.7600,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0139,WR.VOLT.0139_H,11.4908,0.1570,-6.4216,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-0.6164,-0.7599,-17.6119,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0146,WR.VOLT.0146_H,8.9814,0.1024,-8.8764,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0147,WR.VOLT.0147_H,8.9814,0.1024,-8.8764,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0148,WR.VOLT.0148_H,9.1350,0.0996,-8.7200,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-11.2884,-0.8680,-28.1758,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0157,V157_DDR,8.8758,0.0842,-8.9638,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0158,V158_DDR,8.9814,0.1024,-8.8764,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0159,WR.VOLT.0159_H,8.9814,0.1024,-8.8764,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-12.3128,-1.0984,-28.9698,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0173,V173_DDR,-2.7217,-0.9615,-19.5156,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0174,V174_DDR,-11.9161,-1.0117,-28.6598,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0184,V184_DDR,-11.6381,-1.1179,-28.2756,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-12.2147,-1.0428,-28.9273,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0186,V186_DDR,-12.1651,-1.0926,-28.8279,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-11.8133,-1.0849,-28.4838,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-12.7417,-1.0081,-29.4891,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-3.7330,-0.6400,-20.8485,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0190,WR.VOLT.0190_H,1.0928,-0.5001,-16.1625,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0191,WR.VOLT.0191_H,1.9784,-0.5446,-15.2324,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0192,WR.VOLT.0192_H,1.9784,-0.5446,-15.2324,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0196,WR.VOLT.0196_H,1.0928,-0.5001,-16.1625,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0245,V245_DDR,-12.2229,-1.0441,-28.9342,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.VOLT.0248,V248_DDR,-12.0046,-1.0000,-28.7600,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-15.7427,-1.2370,-32.2611,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,6.6748,-0.0979,-10.9827,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.WOLF,WRWOLFUN15_RA,-3.3815,-1.3811,-19.7558,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-8.5097,-2.0490,-24.2161,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,7.4513,0.5703,-10.8744,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-14.5019,-1.3321,-30.9252,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-14.5019,-1.3321,-30.9252,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-14.5019,-1.3321,-30.9252,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-14.5019,-1.3321,-30.9252,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-11.1475,-0.7747,-28.1283,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-0.5338,-0.7617,-17.5275,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-13.0641,-1.0269,-29.7926,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-13.0641,-1.0269,-29.7926,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-13.0641,-1.0269,-29.7926,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-13.0641,-1.0269,-29.7926,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,1.5763,-0.3818,-15.7973,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,1.5763,-0.3818,-15.7973,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,1.5763,-0.3818,-15.7973,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,1.5763,-0.3818,-15.7973,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,1.5763,-0.3818,-15.7973,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,1.5763,-0.3818,-15.7973,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-25.9126,-0.9527,-42.7154,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-25.9126,-0.9527,-42.7154,17.7555\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-28.2780,-0.9928,-45.0406,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-28.2780,-0.9928,-45.0406,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_MIDW,WR_MIDW_LA,-1.8307,-1.1373,-18.4488,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,18.1055,0.5645,-0.2144,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,15.4500,0.2511,-2.5565,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-3.4950,-1.1010,-20.1494,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_SEG,WR_SEG_LA,6.2589,0.4191,-11.9156,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,WR_WR,WR_LA,-0.7727,-0.5822,-17.9459,17.7554\n03/19/2025 08:00:00,03/19/2025 13:00:00,YAD,VACS,26.1371,0.7161,7.6656,17.7554\n03/19/2025 09:00:00,03/19/2025 14:00:00,AEC,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,AECC_CSWS,CSWS_AECC_LA,32.3180,0.7364,16.7773,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,35.0402,0.6067,19.6292,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,31.0686,0.9591,15.3052,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,35.0964,0.4292,19.8629,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,27.6749,0.5090,12.3615,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,31.5250,0.4533,16.2674,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,28.0478,0.2993,12.9442,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,AECI,AECI,24.6294,0.2570,9.5681,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,AEPM_CSWS,CSWS_LA,31.6905,0.5907,16.2955,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,ALTW,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,AMRN,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-14.3683,-0.5916,-28.5811,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,BBA,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BCA,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BEPM.ER01.DDR,ER01_DDR,6.4228,-1.7506,-6.6309,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BEPM_ER01,BEPM_ER01_LA,6.4228,-1.7506,-6.6309,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,6.1233,-0.2308,-8.4502,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,4.6072,-0.3311,-9.8661,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,BEPM_UM01,BEPM_UM01_LA,10.5049,0.4230,-4.7224,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BLKW,BLKW,-8.1589,-0.2415,-22.7217,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-30.4583,-1.2925,-43.9701,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-30.4583,-1.2925,-43.9701,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,25.2722,-1.1321,11.6000,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-30.4362,-1.2705,-43.9701,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,BRAZ,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BUBA,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-7.8850,-1.3377,-21.3517,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-12.1651,-0.8695,-26.0999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-12.1651,-0.8695,-26.0999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-12.1651,-0.8695,-26.0999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-12.1651,-0.8695,-26.0999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-12.1651,-0.8695,-26.0999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-10.8293,-0.7178,-24.9158,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,8.3826,-0.3913,-6.0304,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,8.3826,-0.3913,-6.0304,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CLEC,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,34.4663,0.3785,19.2835,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,COWP,COWP_LA,23.7002,0.4251,8.4708,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,23.7002,0.4251,8.4708,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,23.7002,0.4251,8.4708,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CPLE,VACS,21.8270,0.4953,6.5273,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CPLW,VACS,21.8270,0.4953,6.5273,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,23.7968,0.6092,8.3832,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,23.7968,0.6092,8.3832,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,23.7968,0.6092,8.3832,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,23.7968,0.6092,8.3832,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CRTH_SPA,WRCRTH_SPA_LA,34.1048,0.1271,19.1733,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,28.5300,1.4604,12.2653,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,6.4264,-0.6852,-7.6928,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,28.0478,0.2993,12.9442,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,35.0964,0.4292,19.8629,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,28.4496,1.4514,12.1939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,27.7010,0.7878,12.1088,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,27.6638,1.2787,11.5808,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,27.6638,1.2787,11.5808,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,34.7856,0.5426,19.4387,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,34.7856,0.5426,19.4387,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,34.7857,0.5426,19.4387,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,34.7857,0.5426,19.4387,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,28.0478,0.2993,12.9442,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,31.2017,1.1125,15.2849,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,53.8821,0.0255,39.0523,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,53.7533,-0.1033,39.0523,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,38.2569,0.1934,23.2592,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,35.6764,0.2643,20.6078,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,35.6764,0.2643,20.6078,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,35.6776,0.2643,20.6089,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,35.6776,0.2643,20.6089,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-18.7548,-0.8698,-32.6893,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,13.5330,-0.4987,-0.7727,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,39.8465,0.3033,24.7388,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-16.9964,-1.0312,-30.7696,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-16.9487,-0.9834,-30.7696,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-7.5874,-0.5709,-21.8208,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.GRID.CDL1,CDL1_DDR,37.1300,0.3706,21.9551,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,2.6194,-0.7444,-11.4406,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,7.1537,-0.8340,-6.8166,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,37.1300,0.3706,21.9551,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.NUEN.CSI1,CSI1_DDR,38.1043,0.4550,22.8450,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.NUEN.CSI2,CSI2_DDR,38.1097,0.4603,22.8450,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,34.4781,0.3903,19.2835,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.NUEN.GAZA,GAZA_DDR,37.1300,0.3706,21.9551,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,91.2274,0.7165,75.7066,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.NUEN.T201,NT201_DDR,36.4511,0.3187,21.3281,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,0.2247,-0.9618,-13.6178,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,0.2247,-0.9618,-13.6178,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,28.0478,0.2993,12.9442,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,28.3192,1.4095,12.1054,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-7.5874,-0.5709,-21.8208,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-7.5874,-0.5709,-21.8208,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-11.0701,-0.8267,-25.0477,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-16.9487,-0.9834,-30.7696,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,27.4089,0.7360,11.8686,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,33.8189,0.1573,18.8573,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,33.6063,-0.0554,18.8573,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,33.6015,-0.0601,18.8573,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,17.2485,0.0732,2.3710,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,17.2485,0.0732,2.3710,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,27.6915,0.7566,12.1306,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,37.2429,0.2815,22.1571,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,27.6753,0.7344,12.1365,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,28.8381,1.7729,12.2609,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,32.3729,0.4897,17.0789,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,38.1097,0.4603,22.8450,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0057,OKMU_DDR,37.9894,0.4299,22.7551,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0060,LEHIGH_DDR,91.2274,0.7165,75.7066,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0086,WARRENM_DDR,36.1088,0.3251,20.9794,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,28.5498,1.3746,12.3709,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,46.0313,0.3338,30.8932,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0121,V121_DDR,27.6915,0.7566,12.1306,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0122,V122_DDR,44.7093,0.3153,29.5897,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0124,V124_DDR,61.6224,0.2235,46.5946,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0135,V135_DDR,37.1521,0.3559,21.9919,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0144,V144_DDR,14.0632,-0.4494,-0.2917,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0145,V145_DDR,14.2748,-0.5274,-0.0022,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,27.7513,0.8026,12.1443,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,28.3401,0.5118,13.0240,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0175,V175_DDR,34.4781,0.3903,19.2835,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,28.3401,0.5118,13.0240,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,28.4491,0.6209,13.0239,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,37.1521,0.3559,21.9919,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,37.3181,0.3316,22.1822,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,36.8768,0.2976,21.7749,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,50.1511,0.1516,35.1951,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,35.8252,0.2503,20.7706,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,37.3181,0.3316,22.1822,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0211,V211_DDR,27.8733,0.9591,12.1098,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,46.7264,0.3380,31.5840,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0213,V213_DDR,36.8349,0.3276,21.7030,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0215,V215_DDR,45.6221,0.3253,30.4924,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0217,V217_DDR,46.7710,0.3227,31.6439,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0218,V218_DDR,49.7329,0.1623,34.7663,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0228,V228_DDR,37.6789,0.2508,22.6238,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0232,V232_DDR,36.7242,0.3616,21.5583,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0233,V233_DDR,37.4641,0.3475,22.3123,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0240,V240_DDR,42.6484,0.2390,27.6051,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0244,V244_DDR,37.3181,0.3316,22.1822,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0246,MDT1_DDR,91.2274,0.7165,75.7066,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0249,V249_DDR,36.7931,0.3440,21.6448,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0250,V250_DDR,5.3027,-0.6494,-8.8522,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0251,V251_DDR,36.1643,0.2944,21.0656,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.VOLT.0252,V252_DDR,50.1511,0.1516,35.1951,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-21.5722,-0.8467,-35.5299,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,21.4467,-1.0000,7.6424,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-13.6228,-1.7359,-26.6913,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,27.3810,0.4570,12.1197,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-16.1045,-2.6373,-28.2715,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,9.9972,-0.5463,-4.2608,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,9.9972,-0.5463,-4.2608,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,9.9972,-0.5463,-4.2608,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,9.9972,-0.5463,-4.2608,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,9.9972,-0.5463,-4.2608,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,28.0478,0.2993,12.9442,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,27.6548,1.2831,11.5674,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,36.7006,0.3380,21.5583,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,35.8498,0.2610,20.7845,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,39.8523,0.4745,24.5735,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,39.8523,0.4745,24.5735,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWWELSH1,CSWSWELSHUN1_RA,27.8634,0.6139,12.4452,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWWELSH3,CSWSWELSHUN3_RA,27.8634,0.6139,12.4452,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWWILKES1,CSWSWILKESUN1_RA,28.0336,0.9355,12.2938,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWWILKES2,CSWSWILKESUN2_RA,28.0336,0.9355,12.2938,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,CSWWILKES3,CSWSWILKESUN3_RA,27.7836,0.8820,12.0973,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-16.9345,-0.9693,-30.7696,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,DENL,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,DERS,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,DOE,DOE,20.0594,0.3594,4.8957,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,11.3628,-0.0428,-3.3987,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,DPC,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,DUK,VACS,21.8270,0.4953,6.5273,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDDY,EDDY,38.0704,0.7234,22.5426,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,32.3287,0.0319,17.4925,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-9.1500,-0.2306,-23.7237,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,36.9908,-0.1300,22.3165,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE.SLCC,EDESTL4391_PLT,33.9082,0.0103,19.0935,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,33.8148,0.0534,18.9571,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,21.4843,-0.2342,6.9141,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_EC_01,EDELAR3821UN1_RA,32.3287,0.0319,17.4925,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_EC_02,EDELAR3821UN2_RA,32.3287,0.0319,17.4925,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_EC_03,EDELAR3821UN3_RA,32.3287,0.0319,17.4925,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_EC_04,EDELAR3821UN4_RA,32.3287,0.0319,17.4925,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_EDE,EDE_LA,32.0804,0.3786,16.8975,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_ERW,EDEERWFUNG1_RA,-11.0510,-0.7753,-25.0801,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-3.6370,-0.8843,-17.5570,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,29.7692,0.7562,14.2086,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,29.7692,0.7562,14.2086,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,29.7692,0.7562,14.2086,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,29.7692,0.7562,14.2086,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,22.7192,0.5261,7.3888,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_RIV_10,EDERIV1671UN10_RA,33.8741,-0.0737,19.1435,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_RIV_11,EDERIV1671UN11_RA,33.8741,-0.0737,19.1435,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_RIV_12,EDERIV453UN12_PLT,33.4640,-0.4839,19.1435,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_SL_01,EDESTL4391UN1_RA,33.9082,0.0103,19.0935,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EDE_SWMP,EDE_SWMP_LA,31.1823,0.4915,15.8864,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EEI,EEI,20.0295,0.3573,4.8678,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,EES,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-6.3259,-0.7989,-20.3314,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,ERCOTE,ERCOTE,27.8634,0.6139,12.4452,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,ERCOTN,ERCOTN,0.2884,-0.8982,-13.6178,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,4.4122,-0.6186,-9.7736,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,FMPP,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,FPC,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,FPL,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,FREM_50T,OPPDFREM_GUN1_RA,8.2016,-0.3321,-6.2706,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,FREM_6,OPPDFREM_AUN6_RA,8.1912,-0.3386,-6.2746,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,FREM_7,OPPDFREM_AUN7_RA,8.1912,-0.3386,-6.2746,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,FREM_8,OPPDFREM_AUN8_RA,8.1135,-0.4163,-6.2746,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,FREM_LOAD,FREM_LOAD_LA,8.1789,-0.3508,-6.2746,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-11.6861,-0.6778,-25.8127,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,27.4089,0.7360,11.8686,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-12.3387,-1.9169,-25.2262,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-27.4682,-1.2646,-41.0080,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,34.4663,0.3785,19.2835,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,34.4663,0.3785,19.2835,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,34.4663,0.3785,19.2835,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,37.9935,0.2684,22.9208,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,37.9935,0.2684,22.9208,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,38.1195,0.2637,23.0515,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,38.1195,0.2637,23.0515,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-18.4885,-1.0721,-32.2207,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,41.7314,0.0594,26.8677,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,41.7314,0.0594,26.8677,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,41.7314,0.0594,26.8677,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.VOLT.0130,V130_DDR,39.0501,0.4332,23.8125,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA.VOLT.0237,V237_DDR,39.0488,0.3319,23.9126,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDAHUB2,GRDAHUB2_H,26.2304,-0.1047,11.5308,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDAHUB3,GRDAHUB3_H,20.2531,-0.2341,5.6829,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA_GRDA,GRDA_LA,38.4159,0.3290,23.2826,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA_HUB,GRDA_H,33.0591,0.0638,18.1909,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRDA_HUBSA,GRDASA_H,32.9638,0.0405,18.1189,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,GRE,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-4.4583,0.3302,-19.5928,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GSEC_SPS,SPS_GSEC_LA,-9.5553,-0.5019,-23.8578,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,GSPR2014HUB,GSPR2014HUB_H,4.4656,-0.5815,-9.7572,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,GSPR2015HUB,GSPR2015HUB_H,4.5652,-0.5958,-9.6434,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-11.8868,-1.2778,-25.4133,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,HARRISON,CSWSLEBROCKPLT1,27.5021,0.6269,12.0709,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,HAST_TNSK_HUB,HAST_TNSK_H,7.0019,-0.6517,-7.1507,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,HQST,PJM,16.9083,0.1567,1.9473,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,HST,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,12.4274,0.2502,-2.6272,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,12.4274,0.2502,-2.6272,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,12.4355,0.2466,-2.6154,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,12.4355,0.2466,-2.6154,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,12.4119,0.2501,-2.6425,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,12.4119,0.2501,-2.6425,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,INDN_INDN,INDN_LA,12.4341,0.2547,-2.6249,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-3.0305,-0.9455,-16.8893,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,ISNE,PJM,16.9083,0.1567,1.9473,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,JEA,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,8.4023,-0.3177,-6.0844,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,8.4023,-0.3177,-6.0844,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-3.0894,-0.0627,-17.8311,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KACYCT4,KACYNEARMANUNCT4_RA,19.8466,0.1730,4.8693,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,60.2263,-0.0167,45.4386,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,19.8466,0.1730,4.8693,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,19.2801,0.1882,4.2876,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,19.4361,0.1874,4.4444,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KACY_KACY,KACY_LA,19.1700,0.1853,4.1804,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,12.8278,0.0858,-2.0623,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,14.5616,0.5582,-0.8009,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-13.6191,-0.7167,-27.7068,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-36.8904,-1.0740,-50.6207,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.VOLT.0222,V222_DDR,6.5349,-0.0230,-8.2464,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.VOLT.0223,V223_DDR,11.1342,-0.0510,-3.6192,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.VOLT.0241,V241_DDR,15.7349,0.4557,0.4748,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.VOLT.0243,V243_DDR,22.6311,0.2276,7.5992,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.VOLT.0247,V247_DDR,11.8112,0.0701,-3.0632,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.VOLT.0253,V253_DDR,12.7558,0.0919,-2.1404,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-0.5758,-1.0821,-14.2980,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,9.6459,-0.2113,-4.9471,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,9.6459,-0.2113,-4.9471,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,9.6459,-0.2113,-4.9471,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,9.6459,-0.2113,-4.9471,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,12.7581,0.0843,-2.1306,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,12.7581,0.0843,-2.1306,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHUB,KCPLHUB_H,2.7847,-0.5730,-11.4466,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHUB17,KCPLHUB17_H,1.8965,-0.6434,-12.2645,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHUB18,KCPLHUB18_H,2.0982,-0.6438,-12.0623,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHUB19,KCPLHUB19_H,1.8810,-0.6117,-12.3117,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHUB20,KCPLHUB20_H,1.2997,-0.6705,-12.8341,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHUB21,KCPLHUB21_H,1.2009,-0.6562,-12.9473,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHUB22,KCPLHUB22_H,2.1303,-0.6522,-12.0218,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHUB23,KCPLHUB23_H,1.4841,-0.6699,-12.6504,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLHUB24,KCPLHUB24_H,0.9607,-0.6995,-13.1441,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,3.9275,-0.0483,-10.8286,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,3.9275,-0.0483,-10.8286,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,9.4178,-0.4542,-4.9323,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,9.4178,-0.4542,-4.9323,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,12.8314,0.0894,-2.0623,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,12.8278,0.0858,-2.0623,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,13.8371,0.1297,-1.0969,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,13.8371,0.1297,-1.0969,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,13.8371,0.1297,-1.0969,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,13.8371,0.1297,-1.0969,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,13.8371,0.1297,-1.0969,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,13.8371,0.1297,-1.0969,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,13.8371,0.1297,-1.0969,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,13.8371,0.1297,-1.0969,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,3.4658,-0.2387,-11.0998,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,12.3295,0.0816,-2.5564,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KCPL_KCPL,KCPL_LA,12.8098,0.0616,-2.0562,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KENN,KENN_LA,22.5263,0.5039,7.2181,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KEP2_SECI,KEP2_SECI_LA,-8.8249,-1.1566,-22.4726,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KERR_1,GRDAKERR_HYDUN1_RA,38.6712,0.3026,23.5643,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KERR_2,GRDAKERR_HYDUN2_RA,38.5577,0.3048,23.4485,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KERR_3,GRDAKERR_HYDUN3_RA,38.5577,0.3048,23.4485,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KERR_4,GRDAKERR_HYDUN4_RA,38.6712,0.3026,23.5643,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,9.6458,-0.2115,-4.9471,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,9.6458,-0.2115,-4.9471,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,10.4751,-0.1268,-4.2024,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,10.4751,-0.1268,-4.2024,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,7.8384,-0.2077,-6.7582,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,6.1262,-0.1822,-8.4959,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,6.1262,-0.1822,-8.4959,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-7.3700,-1.1268,-21.0475,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-7.3700,-1.1268,-21.0475,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-7.3700,-1.1268,-21.0475,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-4.2951,-0.5971,-18.5023,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-4.2951,-0.5971,-18.5023,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-7.4747,-1.1522,-21.1268,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-4.7228,-0.6695,-18.8575,14.8042\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-3.0392,-0.4698,-17.3737,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,53.7027,-0.0597,38.9581,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,53.7027,-0.0597,38.9581,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,1.1843,-0.3849,-13.2351,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,1.1843,-0.3849,-13.2351,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,1.1843,-0.3849,-13.2351,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-5.6139,-0.9691,-19.4491,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-5.5429,-1.1392,-19.2080,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,3.9691,-0.5014,-10.3338,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-3.9956,-0.0042,-18.7957,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,LAFA,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,LAM345,LAM345,-7.8850,-1.3377,-21.3517,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,LEPA,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,9.0049,-0.3855,-5.4140,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_LES,LES_LA,8.9467,-0.3999,-5.4577,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,8.9611,-0.4222,-5.4210,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,8.8274,-0.4397,-5.5373,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,8.8274,-0.4397,-5.5373,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,8.8274,-0.4397,-5.5373,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,8.9616,-0.4217,-5.4210,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,8.9611,-0.4222,-5.4210,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_WAVERLY,LES_WAVERLY_H,8.8706,-0.4399,-5.4938,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,8.5175,-0.4245,-5.8624,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,8.5175,-0.4245,-5.8624,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,LGEE,LGEE,18.4077,0.2559,3.3474,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MALDEN,MALDEN_LA,22.1859,0.4826,6.8989,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MCWEST,MCWEST,10.0312,-0.0135,-4.7596,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MDU,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,5.3309,-0.3392,-9.1343,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,5.9615,-0.1887,-8.6542,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,8.9902,0.3726,-6.1866,14.8042\n03/19/2025 09:00:00,03/19/2025 14:00:00,MEAN_NPPD,NPPD_MEAN_LA,5.5051,-0.7745,-8.5247,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MEC,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MHEB,MHEB,10.6729,-0.0334,-4.0980,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-1.0932,-0.8433,-15.0543,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-5.7284,-1.1767,-19.3561,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-1.0932,-0.8433,-15.0543,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-1.0932,-0.8433,-15.0543,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-5.7284,-1.1767,-19.3561,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-12.4677,-0.8164,-26.4556,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MISO,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-8.5444,-0.8980,-22.4508,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-8.5444,-0.8980,-22.4508,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-0.5001,-0.6588,-14.6456,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-9.0362,-1.4857,-22.3548,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-5.2371,-0.9749,-19.0665,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-9.4758,-1.2856,-22.9946,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-8.5795,-1.0255,-22.3583,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-9.5467,-1.1999,-23.1511,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-8.4575,-0.8911,-22.3707,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-8.4575,-0.8911,-22.3707,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-8.4575,-0.8911,-22.3707,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-8.4575,-0.8911,-22.3707,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-8.4575,-0.8911,-22.3707,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,11.9701,0.0056,-2.8399,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,19.5670,0.3101,4.4526,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,19.5670,0.3101,4.4526,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,17.0020,0.1722,2.0255,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,15.6020,0.5307,0.2670,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MOWR,AECI,24.6294,0.2570,9.5681,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,17.0577,0.1422,2.1111,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,19.8720,0.3197,4.7480,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,8.5998,-0.8522,-5.3524,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,9.6286,-0.4707,-4.7051,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-10.9264,-1.1272,-24.6036,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,8.6471,-0.8048,-5.3524,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,11.3694,-0.0363,-3.3987,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,11.3694,-0.0363,-3.3987,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,11.3700,-0.0356,-3.3987,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,11.3700,-0.0356,-3.3987,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,6.5349,-0.0230,-8.2464,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,6.5349,-0.0230,-8.2464,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,6.5349,-0.0230,-8.2464,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,6.4910,-0.0669,-8.2464,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,6.5349,-0.0230,-8.2464,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,6.5349,-0.0230,-8.2464,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,6.5349,-0.0230,-8.2464,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,20.1407,0.3974,4.9390,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,11.9269,-0.0344,-2.8430,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,10.9890,-0.0857,-3.7296,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,10.9890,-0.0857,-3.7296,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,10.9891,-0.0856,-3.7296,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,12.0819,0.0961,-2.8186,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,12.0819,0.0961,-2.8186,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MPS_MPS,MPS_LA,11.4643,0.1176,-3.4576,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MSTNG,SPSMSTNGPLT1,11.1346,0.5845,-4.2542,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MSTNG4,SPSMSTNGUN4_RA,11.0690,0.5188,-4.2542,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,MSTNG5,SPSMSTNGUN5_RA,11.1346,0.5845,-4.2542,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,11.1346,0.5845,-4.2542,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NBSO,PJM,16.9083,0.1567,1.9473,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,8.0135,-0.7999,-5.9910,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,8.0105,-0.8028,-5.9910,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-12.6039,-1.6196,-25.7887,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NHC1,VACS,21.8270,0.4953,6.5273,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,8.3600,-0.3579,-6.0864,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,8.3600,-0.3579,-6.0864,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,8.3600,-0.3579,-6.0864,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,4.5101,-0.8043,-9.4899,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,6.4067,-0.8647,-7.5329,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,7.7522,-0.6699,-6.3822,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,3.8564,-0.5770,-10.3709,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,6.4067,-0.8647,-7.5329,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.HUB.PY2018,NPPDPY18_H,5.6221,-0.8678,-8.3144,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,5.7293,-0.8614,-8.2137,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,5.6733,-0.8578,-8.2732,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,5.7682,-0.8465,-8.1897,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,2.0700,-0.6073,-12.1270,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,4.4097,-0.8828,-9.5118,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,4.4097,-0.8828,-9.5118,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,3.6044,-0.7654,-10.4346,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,2.0700,-0.6073,-12.1270,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,10.8212,-1.0063,-2.9769,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,5.6141,-1.1105,-8.0797,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,1.8987,-0.8712,-12.0344,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,5.6141,-1.1105,-8.0797,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,6.5799,-0.9558,-7.2687,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,5.2260,-1.0066,-8.5717,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,8.3852,-0.3108,-6.1084,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,6.4067,-0.8647,-7.5329,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,2.2903,-0.8963,-11.6177,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,4.4097,-0.8828,-9.5118,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,4.4097,-0.8828,-9.5118,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,5.1547,-0.6308,-9.0188,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,5.0962,-0.6408,-9.0674,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,5.0962,-0.6408,-9.0674,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,5.8503,-0.3451,-8.6089,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,5.0450,-0.3037,-9.4556,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,6.6518,-0.6731,-7.4794,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,4.7185,-0.6000,-9.4858,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,3.8408,-0.2331,-10.7304,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,2.8599,-0.2368,-11.7076,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.NELI.DDR,NELI_DDR,2.7976,-0.7042,-11.3026,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.NPPM.1058,SH1058_DDR,16.7487,-0.1922,2.1365,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,5.8324,-0.4846,-8.4873,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,6.4067,-0.8647,-7.5329,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,7.7522,-0.6699,-6.3822,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,2.0700,-0.6073,-12.1270,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.TECH.1,KEARNE_DDR,6.2028,-0.3572,-8.2443,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,7.0079,-1.2571,-6.5394,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,7.0079,-1.2571,-6.5394,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,2.0311,-0.6776,-12.0957,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD.VOLT.0236,V236_DDR,7.4727,-0.3760,-6.9556,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD2017HUB,NPPD2017HUB_H,5.6354,-0.8650,-8.3040,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,15.0517,-0.5936,0.8410,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,4.5101,-0.8043,-9.4899,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,5.5431,-1.3221,-7.9391,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,5.5431,-1.3221,-7.9391,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,7.6282,-0.3966,-6.7795,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,7.4933,-0.3554,-6.9556,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,3.7270,-0.5718,-10.5055,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,5.2297,-0.6564,-8.9182,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,16.4036,-0.5373,2.1365,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,16.4036,-0.5373,2.1365,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,16.4036,-0.5373,2.1365,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,7.0104,-0.6479,-7.1460,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,7.7186,-0.7265,-6.3593,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,6.9692,-0.4446,-7.3905,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,3.5213,-1.3949,-9.8881,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,3.6012,-1.3151,-9.8881,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,3.7008,-0.9716,-10.1320,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,3.4985,-0.9808,-10.3250,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,7.7286,-0.5987,-6.4771,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,7.7167,-0.6105,-6.4771,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,7.7167,-0.6105,-6.4771,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,7.6856,-0.5804,-6.5383,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,10.8212,-1.0063,-2.9769,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,7.6249,-0.5823,-6.5972,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,8.3165,-0.5197,-5.9681,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,7.0351,-0.6127,-7.1566,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,7.0231,-0.6227,-7.1585,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,7.0296,-0.6140,-7.1608,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,7.0296,-0.6140,-7.1608,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,7.0104,-0.6479,-7.1460,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,6.9736,-0.6847,-7.1460,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,5.8607,-0.2238,-8.7199,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,7.1598,-0.4058,-7.2388,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,3.6848,-0.9197,-10.1998,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,5.6281,-1.1289,-8.0474,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,1.5976,-0.9266,-12.2801,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,17.0464,0.1056,2.1365,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,2.7976,-0.7042,-11.3026,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,3.9119,-0.9317,-9.9608,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,3.9119,-0.9317,-9.9608,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_NPPD,NPPD_LA,8.7964,-0.5276,-5.4803,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,8.3165,-0.5197,-5.9681,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,8.3165,-0.5197,-5.9681,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,5.1952,-0.7052,-8.9040,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,4.8101,-0.7954,-9.1988,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NSB,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NSP,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NSSO,PJM,16.9083,0.1567,1.9473,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,NYIS,PJM,16.9083,0.1567,1.9473,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-13.0584,-1.6258,-26.2370,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-18.3411,-1.1224,-32.0230,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-15.8724,-1.0169,-29.6598,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-15.8724,-1.0169,-29.6598,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-12.3404,-1.7835,-25.3613,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-27.4682,-1.2646,-41.0080,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-80.8800,-0.6844,-94.9999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-38.3180,-1.0577,-52.0646,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-20.0223,-1.0757,-33.7510,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-18.3061,-1.1323,-31.9781,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,2.5564,-0.3959,-11.8520,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-20.0223,-1.0757,-33.7510,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-12.5630,-1.7554,-25.6120,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-12.4677,-0.8164,-26.4556,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-13.3336,-1.6027,-26.5353,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,30.5516,-0.1100,15.8573,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-18.3061,-1.1323,-31.9781,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-16.3493,-1.0436,-30.1100,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-13.3388,-1.0494,-27.0937,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-12.1651,-0.8695,-26.0999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-36.3521,-0.1204,-51.0360,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-12.4677,-0.8164,-26.4556,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-12.4677,-0.8164,-26.4556,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-18.3061,-1.1323,-31.9781,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-9.9952,-0.8393,-23.9603,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.NUEN.LAM1,LAM1_DDR,33.2716,1.0324,17.4348,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.NUEN.MDT2,MDT2_DDR,2.5564,-0.3959,-11.8520,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.NUEN.MDT3,MDT3_DDR,2.5564,-0.3959,-11.8520,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-10.2463,-0.8408,-24.2099,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,0.1855,-0.4486,-14.1703,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,0.1855,-0.4486,-14.1703,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,0.1855,-0.4486,-14.1703,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,5.7745,-0.3798,-8.6501,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,5.7745,-0.3798,-8.6501,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,0.1855,-0.4486,-14.1703,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,0.1855,-0.4486,-14.1703,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-18.3061,-1.1323,-31.9781,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,25.0184,0.6558,9.5582,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-12.5630,-1.7554,-25.6120,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-26.0266,-0.4298,-40.4012,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-16.3493,-1.0436,-30.1100,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,30.0505,0.7428,14.5034,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-16.8046,-0.8475,-30.7614,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-16.8046,-0.8475,-30.7614,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-16.8046,-0.8475,-30.7614,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-16.8046,-0.8475,-30.7614,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-19.8982,-1.5615,-33.1410,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-20.8171,-1.0501,-34.5713,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-18.3411,-1.1224,-32.0230,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-23.8901,-1.0077,-37.6867,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-23.8901,-1.0077,-37.6867,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-21.1401,-0.1509,-35.7935,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-14.0000,-0.9541,-27.8502,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-14.0000,-0.9541,-27.8502,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-14.0000,-0.9541,-27.8502,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0033,FOSTER_DDR,11.9275,-0.3400,-2.5368,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,27.5750,0.4408,12.3299,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0035,TARBY_DDR,33.1314,0.8512,17.4759,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,27.5750,0.4408,12.3299,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,26.6217,0.2732,11.5441,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,26.6217,0.2732,11.5441,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-32.0747,-0.2255,-46.6535,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0040,TROSPER_DDR,15.2749,-0.3179,0.7885,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,15.2524,-0.3196,0.7676,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,31.2822,0.8656,15.6123,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0115,V115_DDR,3.5416,-0.3873,-10.8754,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0116,V116_DDR,61.6293,-0.0496,46.8746,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0118,V118_DDR,11.4229,0.0091,-3.3906,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0125,V125_DDR,32.0386,0.9861,16.2482,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0126,V126_DDR,34.0409,0.5233,18.7133,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0129,V129_DDR,2.6202,-0.7435,-11.4406,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,39.8318,-0.4077,25.4352,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0134,V134_DDR,34.9080,0.6490,19.4547,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0138,V138_DDR,33.4466,0.4489,18.1933,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,33.4637,-0.3340,18.9934,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0143,V143_DDR,29.4394,0.3026,14.3325,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0149,V149_DDR,-9.1270,-0.7682,-23.1631,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0150,V150_DDR,-8.9674,-0.8226,-22.9491,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0155,V155_DDR,32.9284,0.3711,17.7530,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0156,V156_DDR,39.8318,-0.4077,25.4352,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0166,V166_DDR,34.0019,0.8929,18.3046,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,32.7116,-0.3399,18.2471,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-8.9674,-0.8226,-22.9491,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0170,V170_DDR,-10.3751,-0.8390,-24.3404,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-18.0063,-0.7391,-32.0715,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0176,V176_DDR,-8.9674,-0.8226,-22.9491,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0177,V177_DDR,-15.5765,-1.5103,-28.8705,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,25.9193,-0.3377,11.4526,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-10.0035,-0.8905,-23.9174,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0195,V195_DDR,135.8973,0.8562,120.2367,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0197,V197_DDR,33.6118,0.5922,18.2153,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0198,V198_DDR,34.0019,0.8929,18.3046,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0208,V208_DDR,136.0000,0.8706,120.3251,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0209,V209_DDR,136.0000,0.8706,120.3251,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,34.0152,0.4566,18.7543,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0216,V216_DDR,15.2469,-0.3207,0.7633,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0219,V219_DDR,32.9284,0.3711,17.7530,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0220,V220_DDR,-8.9674,-0.8226,-22.9491,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0224,V224_DDR,2.8159,-0.4110,-11.5774,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0225,V225_DDR,2.8167,-0.4102,-11.5774,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0226,V226_DDR,2.8159,-0.4110,-11.5774,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0227,V227_DDR,2.8159,-0.4110,-11.5774,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0229,V229_DDR,-28.1634,-0.1722,-42.7955,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0231,V231_DDR,17.4913,0.0758,2.6112,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0238,V238_DDR,-20.8700,-1.2172,-34.4572,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.VOLT.0242,V242_DDR,33.1514,0.4087,17.9384,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-15.7000,-2.2011,-28.3032,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-12.4677,-0.8164,-26.4556,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-18.3472,-1.0842,-32.0673,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-13.3213,-1.5903,-26.5353,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-15.7000,-2.2011,-28.3032,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-14.0151,-1.8569,-26.9625,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-42.9456,-1.0283,-56.7216,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEHL7,OKGEHL7_H,24.7798,-0.3010,10.2765,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEHL8,OKGEHSL1UN8_RA,24.7798,-0.3010,10.2765,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEHL910,OKGEHSL1PLT2,24.7798,-0.3010,10.2765,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-13.6341,-1.7018,-26.7366,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEMCC,OKGEMCCLAIPLT1,0.5115,-0.5562,-13.7366,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,30.5751,0.2923,15.4784,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,30.5751,0.2923,15.4784,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,30.5751,0.2923,15.4784,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,18.3258,-0.5327,4.0542,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,18.3258,-0.5327,4.0542,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,18.3258,-0.5327,4.0542,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,18.3258,-0.5327,4.0542,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGESM1,OKGESEMINOLEUN1_RA,13.4929,-0.2255,-1.0859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGESM2,OKGESEMINOLEUN2_RA,10.9211,-0.2616,-3.6216,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGESM3,OKGESEMINOLEUN3_RA,10.9211,-0.2616,-3.6216,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGESO1,OKGESONR1UN1_RA,-44.3418,-0.9310,-58.2152,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGESO2,OKGESONR1UN2_RA,-23.8901,-1.0077,-37.6867,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-13.7554,-1.8231,-26.7366,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-13.8802,-2.0469,-26.6376,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGETINK5A,OKGETINK5UN1_RA,13.3605,-0.3471,-1.0967,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGETINK5B,OKGETINK5UN2_RA,13.3605,-0.3471,-1.0967,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-13.7175,-1.3876,-27.1342,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-18.3411,-1.1224,-32.0230,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,30.8427,1.1041,14.9342,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-12.4677,-0.8164,-26.4556,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE_OKGE,OKGE_LA,17.4979,-0.1562,2.8498,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-26.0266,-0.4298,-40.4012,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-13.7593,-1.4295,-27.1342,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMLP,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,38.7638,0.1892,23.7703,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,31.0517,1.0237,15.2237,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_GENHUB,OMPA_GENHUB_H,1.5614,-0.4127,-12.8303,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-80.7534,-0.5578,-94.9999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-12.4385,-1.0185,-26.2243,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-20.0223,-1.0757,-33.7510,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-15.6273,-2.1927,-28.2389,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-2.7676,-1.4017,-16.1702,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,157.6063,0.1349,142.6670,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-80.7947,-0.5991,-94.9999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-80.7947,-0.5991,-94.9999,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_SPP,OMPA_SPP_LA,-0.0658,-0.5817,-14.2884,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-15.7000,-2.2011,-28.3032,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,35.3189,0.1993,20.3153,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,35.3189,0.1993,20.3153,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,35.3189,0.1993,20.3153,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,35.3189,0.1993,20.3153,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,ONT,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,8.2980,-0.3660,-6.1403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,8.2980,-0.3660,-6.1403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,8.2980,-0.3660,-6.1403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,8.2980,-0.3660,-6.1403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,8.2980,-0.3660,-6.1403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,8.2980,-0.3660,-6.1403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,8.2980,-0.3660,-6.1403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,8.2980,-0.3660,-6.1403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,8.2980,-0.3660,-6.1403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,8.3719,-0.3418,-6.0906,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,8.3600,-0.3579,-6.0864,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,8.5462,-0.2206,-6.0375,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,8.4509,-0.3201,-6.0333,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,8.4509,-0.3201,-6.0333,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD_GLDN,OPPD_GLDN_LA,8.4025,-0.3591,-6.0427,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,8.3405,-0.3529,-6.1109,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,10.8212,-1.0063,-2.9769,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,7.2293,-0.5434,-7.0316,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,8.3603,-0.3576,-6.0865,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD_OPPD,OPPD_LA,8.4125,-0.3105,-6.0814,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,8.4583,-0.3041,-6.0419,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,8.4577,-0.3087,-6.0379,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OTP,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,OVEC,OVEC,17.8228,0.2181,2.8004,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PARAGOULD,PARAGOULD_LA,23.0924,0.5380,7.7501,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,38.5790,0.1989,23.5757,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,38.5790,0.1989,23.5757,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,38.5790,0.1989,23.5757,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,38.2597,0.2537,23.2016,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,38.2597,0.2537,23.2016,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,38.2597,0.2537,23.2016,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PIGGOTT,PIGGOTT_LA,22.4056,0.4964,7.1049,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PJM,PJM,16.9083,0.1567,1.9473,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PLUM,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,POPLARBLUFF,POPLARBLUFF_LA,21.8609,0.4367,6.6198,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,9.7818,-0.2507,-4.7718,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,9.7818,-0.2507,-4.7718,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,9.8136,-0.2447,-4.7460,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,9.8136,-0.2447,-4.7460,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,10.8396,0.7657,-4.7304,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,10.8396,0.7657,-4.7304,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,10.0305,-0.0167,-4.7571,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,9.2661,-0.6425,-4.8957,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-10.8293,-0.7178,-24.9158,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,81.0282,0.2152,66.0087,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,7.3055,0.0005,-7.4993,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,2.0449,0.0220,-12.7814,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,41.5188,0.5201,26.1943,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,34.9260,0.6149,19.5067,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,9.6095,-0.3801,-4.8148,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,10.0805,0.0131,-4.7369,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,8.5493,-0.5926,-5.6624,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,31.7700,1.1873,15.7784,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,10.5106,0.0592,-4.3529,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,9.3395,-0.2321,-5.2328,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,PUPP,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,RCEAST,RCEAST,7.4233,-0.8547,-6.5264,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SALINA_1,GRDASALINA1UN1_RA,38.6728,0.3042,23.5643,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SALINA_2,GRDASALINA1UN2_RA,38.6728,0.3042,23.5643,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SALINA_3,GRDASALINA1UN3_RA,38.6728,0.3042,23.5643,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SALINA_4,GRDASALINA1UN4_RA,38.6728,0.3042,23.5643,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SALINA_5,GRDASALINA1UN5_RA,38.6728,0.3042,23.5643,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SALINA_6,GRDASALINA1UN6_RA,38.6728,0.3042,23.5643,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SARPY_1,OPPDSARPYUN1_RA,8.3688,-0.3485,-6.0870,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SARPY_2,OPPDSARPYUN2_RA,8.3980,-0.3169,-6.0894,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SARPY_3,OPPDSARPYUN3_RA,8.3645,-0.3778,-6.0621,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SARPY_4,OPPDSARPYUN4_RA,8.3645,-0.3778,-6.0621,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SARPY_5,OPPDSARPYUN5_RA,8.3645,-0.3778,-6.0621,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SC,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SCEG,VACS,21.8270,0.4953,6.5273,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SCSE,SCSE,4.1315,-0.7904,-9.8824,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SEC,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-10.2019,-1.4780,-23.5282,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-10.2019,-1.4780,-23.5282,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-10.2019,-1.4780,-23.5282,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-7.3699,-0.8609,-21.3133,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-10.2019,-1.4780,-23.5282,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-8.5428,-1.4422,-21.9049,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-8.4562,-1.5482,-21.7123,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-8.4562,-1.5482,-21.7123,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-8.4594,-0.8930,-22.3707,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-11.3594,-1.3234,-24.8403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-4.3624,-0.6644,-18.5023,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-7.9095,-0.9199,-21.7939,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-3.2562,-1.1424,-16.9182,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-9.8201,-1.4900,-23.1344,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-3.2022,-1.1279,-16.8786,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-9.0357,-1.4577,-22.3824,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-10.1750,-2.6247,-22.3547,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-7.4994,-1.2015,-21.1022,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-7.4994,-1.2015,-21.1022,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-7.4994,-1.2015,-21.1022,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-7.4994,-1.2015,-21.1022,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-7.7361,-1.2865,-21.2539,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-8.5428,-1.4422,-21.9049,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI_SECI,SECI_LA,-7.3283,-1.0311,-21.1015,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-3.0305,-0.9455,-16.8893,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-3.0305,-0.9455,-16.8893,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-8.4594,-0.8930,-22.3707,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SEHA,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-13.7593,-1.4295,-27.1342,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SERU,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SETH,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SGE,SGE,4.7948,-0.7316,-9.2779,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SMEP,MISO,17.1924,0.2022,2.1859,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SOCO,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPA,SPA,28.8503,0.6201,13.4259,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPC,SPC,10.4897,0.3613,-4.6759,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPPNORTH_HUB,SPPNORTH_H,8.5933,-0.3797,-5.8314,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPPSOUTH_HUB,SPPSOUTH_H,6.0772,-0.7285,-7.9987,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,28.3029,0.5172,12.9813,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,28.3029,0.5172,12.9813,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,27.7003,0.4900,12.4059,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,27.7003,0.4900,12.4059,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_NIXA,SPRM_NIXA_LA,28.5700,0.5320,13.2336,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_SPRM,SPRM_LA,28.3871,0.5635,13.0192,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,28.4876,0.4434,13.2398,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,28.4876,0.4434,13.2398,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,28.4506,0.4065,13.2398,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,28.4876,0.4434,13.2398,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-5.5643,-0.2628,-20.1059,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-10.7176,-0.6913,-24.8306,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-12.2244,-1.2689,-25.7598,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-12.2244,-1.2689,-25.7598,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-15.7813,-1.1896,-29.3960,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,1.8124,-0.6912,-12.3008,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-9.9793,-1.8860,-22.8976,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,38.1155,0.7582,22.5530,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-16.2017,-0.5150,-30.4910,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,34.6959,0.5343,19.3573,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,38.6617,0.5787,23.2786,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,38.6617,0.5787,23.2786,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,34.6959,0.5343,19.3573,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-12.0629,-1.1069,-25.7603,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-10.7176,-0.6913,-24.8306,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-12.0108,-1.1878,-25.6273,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-12.2826,-1.7588,-25.3281,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-11.7884,-1.1086,-25.4841,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-11.6590,-0.8829,-25.5804,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-11.9659,-1.1958,-25.5744,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-12.0080,-1.7853,-25.0271,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-12.0080,-1.7853,-25.0271,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-12.0080,-1.7853,-25.0271,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-12.0080,-1.7853,-25.0271,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GRID.WRAB,WRAB_DDR,-12.0301,-0.9453,-25.8891,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-12.0080,-1.7853,-25.0271,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-14.3683,-0.5916,-28.5811,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-14.3683,-0.5916,-28.5811,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-14.2596,-0.5500,-28.5139,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-14.2596,-0.5500,-28.5139,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-14.2596,-0.5500,-28.5139,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-14.3683,-0.5916,-28.5811,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-12.3961,-1.2720,-25.9285,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-12.3962,-1.2720,-25.9285,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-12.3948,-1.2720,-25.9271,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-12.6039,-1.6196,-25.7887,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,36.0980,0.5037,20.7899,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-16.1187,-0.5248,-30.3983,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-16.1187,-0.5248,-30.3983,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-16.1187,-0.5248,-30.3983,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-16.1187,-0.5248,-30.3983,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,21.9094,0.6323,6.4727,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,34.1893,0.4980,18.8870,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,34.1893,0.4980,18.8870,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-13.6949,-1.3650,-27.1342,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-12.4203,-1.2971,-25.9276,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-12.4203,-1.2971,-25.9276,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-12.4123,-1.2679,-25.9488,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-12.0301,-0.9453,-25.8891,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-12.0703,-1.5456,-25.3291,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-12.1690,-1.2853,-25.6880,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-12.3404,-1.7835,-25.3613,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-12.1922,-1.0689,-25.9276,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-9.5730,-0.4237,-23.9537,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-9.5730,-0.4237,-23.9537,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-9.0214,-0.4463,-23.3795,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-15.8641,-0.9407,-29.7277,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-12.0082,-1.6335,-25.1791,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-9.6012,-1.5079,-22.8976,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-15.8387,-0.9154,-29.7277,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-12.0672,-1.1112,-25.7603,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-5.8879,-0.3693,-20.3229,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,38.2038,0.8465,22.5530,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-5.8879,-0.3693,-20.3229,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,38.2044,0.8496,22.5505,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-12.0358,-1.3262,-25.5140,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,37.9374,1.3635,21.7696,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,37.9953,1.4213,21.7696,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,36.7484,1.2829,20.6611,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,34.1878,0.6585,18.7250,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,38.7749,1.1541,22.8164,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-7.8850,-1.3377,-21.3517,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-12.1023,-1.0146,-25.8920,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-8.2214,-0.3959,-22.6298,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-8.2214,-0.3959,-22.6298,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-5.8879,-0.3693,-20.3229,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-16.4069,-0.4360,-30.7752,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,18.9500,0.9706,3.1751,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-7.6463,0.5027,-22.9534,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-8.4677,-0.0766,-23.1955,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-12.6497,-0.6729,-26.7811,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,37.9374,1.3635,21.7696,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,39.0000,1.5764,22.6193,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,38.8053,1.3816,22.6193,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-15.6889,-0.7655,-29.7277,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-8.0483,0.0389,-22.8915,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-11.9780,-1.5658,-25.2165,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-12.0023,-1.5895,-25.2171,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0163,V163_DDR,-11.9138,-1.0441,-25.6741,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0168,V168_DDR,-15.4801,-0.8252,-29.4592,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0180,V180_DDR,39.0000,1.5764,22.6193,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0181,V181_DDR,-11.7834,-1.3924,-25.1953,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0182,V182_DDR,38.9545,1.2093,22.9409,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0199,V199_DDR,15.7713,0.8518,0.1152,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0200,V200_DDR,35.3776,0.8950,19.6783,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.VOLT.0235,V235_DDR,-12.0703,-1.5456,-25.3291,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-9.9793,-1.8860,-22.8976,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,38.1155,0.7582,22.5530,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-11.9726,-1.3636,-25.4133,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-12.2121,-1.1582,-25.8582,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS_SPS,SPS_LA,15.1072,0.3692,-0.0663,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,7.1325,0.0797,-7.7515,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SSCN_NPPD,SSCN_NPPD_LA,4.8668,-0.5117,-9.4259,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,21.1498,0.4178,5.9277,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,21.1498,0.4178,5.9277,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,TAL,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,TEC,SOUC,22.1518,0.5261,6.8214,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,5.6281,-1.1289,-8.0474,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,TVA,TVA,21.4839,0.4629,6.2166,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,UCUHUB,UCUHUB_H,2.2759,-0.3256,-12.2028,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,UCUHUB17,UCUHUB17_H,-1.1668,-0.9245,-15.0467,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,UCUHUB18,UCUHUB18_H,1.7125,-0.6703,-12.4215,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,UCUHUB19,UCUHUB19_H,-1.4459,-0.7733,-15.4769,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,UCUHUB20,UCUHUB20_H,-1.4582,-0.7534,-15.5091,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,UCUHUB21,UCUHUB21_H,-3.2933,-0.9059,-17.1918,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,UCUHUB22,UCUHUB22_H,-2.7377,-0.8697,-16.6723,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,UCUHUB23,UCUHUB23_H,-2.9378,-0.8803,-16.8618,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,UCUHUB24,UCUHUB24_H,-0.6443,-0.7718,-14.6768,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,10.6115,0.4968,-4.6896,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,10.6115,0.4968,-4.6896,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,9.5234,-0.4389,-4.8420,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,9.5234,-0.4389,-4.8420,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,9.8318,-0.5452,-4.4273,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,9.7184,-0.3588,-4.7271,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,9.7184,-0.3588,-4.7271,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,10.6115,0.4968,-4.6896,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,9.9029,-0.5095,-4.3919,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,10.3567,0.0612,-4.5088,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,8.9124,-0.4111,-5.4809,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,7.1034,-1.5351,-6.1659,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,10.5228,0.4416,-4.7231,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,10.5228,0.4416,-4.7231,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,8.1755,-1.5346,-5.0943,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,9.1039,-0.5458,-5.1546,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,9.5865,-0.5507,-4.6671,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,8.3716,-0.6231,-5.8096,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,8.9651,-0.3314,-5.5078,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,8.9481,-0.6018,-5.2545,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,8.9616,-0.7484,-5.0943,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,8.9616,-0.7484,-5.0943,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,9.2705,-0.4874,-5.0464,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,7.0460,-1.6459,-6.1124,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,9.6233,0.2972,-5.4783,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,10.0222,-0.0418,-4.7403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,10.0222,-0.0418,-4.7403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,10.0222,-0.0418,-4.7403,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,10.1591,0.0989,-4.7441,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,10.1591,0.0989,-4.7441,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,10.1591,0.0989,-4.7441,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,10.8326,0.6983,-4.6700,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,9.7544,-0.4455,-4.6044,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,9.7544,-0.4455,-4.6044,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,4.4615,-0.7640,-9.5789,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,8.4156,-0.4201,-5.9686,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,10.2256,0.0401,-4.6188,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,6.7637,-0.6379,-7.4027,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,6.4988,-2.0146,-6.2910,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,9.1759,-0.5823,-5.0461,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,10.5699,0.4820,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,10.5699,0.4820,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,10.5692,0.4813,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,10.5699,0.4820,-4.7164,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,10.4373,0.3593,-4.7264,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,10.4373,0.3593,-4.7264,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,10.4373,0.3593,-4.7264,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,10.4373,0.3593,-4.7264,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,10.4373,0.3593,-4.7264,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,10.4373,0.3593,-4.7264,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,10.4373,0.3593,-4.7264,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,6.7309,-1.2044,-6.8691,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,10.1611,-0.2083,-4.4350,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,7.6687,-0.3371,-6.7986,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,7.6687,-0.3371,-6.7986,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,5.9048,-0.6448,-8.2547,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,5.9048,-0.6448,-8.2547,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,9.9370,-0.2629,-4.6044,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,9.9970,-0.2746,-4.5327,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,8.4762,-0.7701,-5.5580,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,7.4430,-1.3958,-5.9655,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,10.0043,-0.2562,-4.5438,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,9.8318,-0.5452,-4.4273,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,9.8318,-0.5452,-4.4273,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,8.3716,-0.6231,-5.8096,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,7.3819,-0.8834,-6.5391,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,8.6647,-0.7253,-5.4143,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,7.1814,-1.5106,-6.1124,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,9.0172,-0.6730,-5.1141,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.FSE,WAUE.FSE_H,6.4665,-0.7854,-7.5524,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,9.9005,-0.1682,-4.7356,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,9.8649,-0.2020,-4.7375,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,6.8329,-1.4526,-6.5188,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,7.3487,-1.3858,-6.0699,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,9.7941,-0.5234,-4.4868,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,9.7834,-0.5696,-4.4514,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-13.3300,-1.2322,-26.9021,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,7.1034,-1.5351,-6.1659,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-3.1900,-0.7442,-17.2501,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,8.6996,-0.4458,-5.6589,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,8.6999,-0.4455,-5.6589,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,8.6999,-0.4455,-5.6589,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,9.0844,-0.5163,-5.2036,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,7.3819,-0.8834,-6.5391,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,9.6852,-0.1751,-4.9440,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,8.2894,-0.6463,-5.8686,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,9.5794,0.2534,-5.4783,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,9.4799,0.1454,-5.4699,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,9.0900,-0.2803,-5.4340,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,10.9934,-0.1854,-3.6255,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,8.7510,-0.3965,-5.6569,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,8.4360,-0.7561,-5.6122,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,6.7637,-0.6379,-7.4027,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,11.6873,0.2378,-3.3549,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,8.3526,-0.6401,-5.8116,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,11.6440,0.2234,-3.3837,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,9.4935,-0.1633,-5.1475,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,8.5175,-0.4245,-5.8624,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NTWK,WAUE.NTWK_H,9.1100,-0.3732,-5.3211,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,10.1225,0.4359,-5.1177,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,10.1225,0.4359,-5.1177,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,7.0190,-1.5918,-6.1935,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,6.2079,-1.5190,-7.0774,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,9.4475,-0.4489,-4.9079,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,7.0190,-1.5918,-6.1935,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,10.5054,-0.1826,-4.1163,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,8.2373,-0.8639,-5.7031,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,6.7637,-0.6379,-7.4027,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,8.8670,-0.5083,-5.4291,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,7.3711,-1.7301,-5.7031,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,5.8827,-1.8733,-7.0484,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,6.2987,-1.8747,-6.6309,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,9.4932,-0.4743,-4.8368,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,6.9863,-1.3848,-6.4332,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,9.7409,-0.2373,-4.8261,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,7.7709,-1.1702,-5.8632,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,7.4430,-1.3958,-5.9655,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.VOLT.0152,V152_DDR,11.0296,0.8661,-4.6409,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE.VOLT.0172,V172_DDR,10.5049,0.4230,-4.7224,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_BEPM,WAUE_BEPM_LA,9.8831,0.0634,-4.9846,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,9.6442,-0.2033,-4.9569,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,9.4840,0.1534,-5.4738,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_EWA,WAUE_EWA_LA,7.4791,-0.8095,-6.5157,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,7.9561,-0.7897,-6.0585,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_HMMU,WAUE_HMMU_LA,9.0122,-0.0399,-5.7523,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,11.0108,-0.2097,-3.5838,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_MECB,WAUE_MECB_LA,9.0899,0.2023,-5.9167,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_MMPA,WAUE_MMPA_LA,10.6818,0.1194,-4.2420,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_MRES,WAUE_MRES_LA,9.5525,-0.3402,-4.9116,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,10.8151,0.5892,-4.5784,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,9.9005,-0.1682,-4.7356,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,7.8140,-0.6993,-6.2909,14.8042\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_OTP,WAUE_OTP_LA,11.6797,0.5626,-3.6872,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_OTPW,WAUE_OTPW_LA,14.3968,0.2511,-0.6586,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM,WAUE_UGPM_LA,9.3964,-0.2904,-5.1175,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,10.3406,-0.0667,-4.3970,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,8.8119,-0.4048,-5.5876,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,6.9024,-0.6500,-7.2518,14.8042\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,7.4791,-0.8095,-6.5157,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,9.0122,-0.0399,-5.7523,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,7.9277,-0.7469,-6.1298,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,9.9005,-0.1682,-4.7356,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,10.6818,0.1194,-4.2420,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,10.0982,-0.2500,-4.4561,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,8.0097,-0.8032,-5.9914,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,11.0169,0.5839,-4.3714,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-15.5147,-2.0074,-28.3116,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-19.9700,-1.3974,-33.3769,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,9.5739,-0.9173,-4.3132,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,90.9700,0.4591,75.7066,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,90.9700,0.4591,75.7066,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-6.6941,-2.0283,-19.4701,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,82.9820,0.5445,67.6331,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,73.6215,0.5234,58.2938,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,32.8400,-0.8504,18.8861,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,32.8400,-0.8504,18.8861,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,32.8400,-0.8504,18.8861,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,32.8400,-0.8504,18.8861,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,32.7686,-0.9218,18.8861,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,32.8400,-0.8504,18.8861,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,32.8400,-0.8504,18.8861,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,32.8400,-0.8504,18.8861,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,20.7973,-0.7923,6.7853,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-12.3404,-1.7835,-25.3613,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-30.4583,-1.2925,-43.9701,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-16.3190,-2.4620,-28.6614,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-9.7286,-1.6353,-22.8976,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_ENMC,WFEC_ENMC_LA,19.4071,0.5920,4.0108,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-18.3061,-1.1323,-31.9781,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,36.1528,0.3360,21.0125,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,25.5489,0.5595,10.1851,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-15.5147,-2.0074,-28.3116,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-15.5147,-2.0074,-28.3116,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-15.5147,-2.0074,-28.3116,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_OKGE,WFEC_OKGE_LA,3.4903,0.0148,-11.3288,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,53.1241,0.5099,37.8098,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-11.8698,-2.1328,-24.5413,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-5.4545,-2.1658,-18.0931,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_WFEC,WFEC_LA,22.8614,-0.3446,8.4017,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,25.5489,0.5595,10.1851,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-1.9104,-0.8585,-15.8562,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-6.3306,-1.3052,-19.8297,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-1.6073,-0.5687,-15.8430,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-1.6073,-0.5687,-15.8430,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-1.6073,-0.5687,-15.8430,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-1.6073,-0.5687,-15.8430,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-1.6073,-0.5687,-15.8430,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-1.6074,-0.5687,-15.8430,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-1.6074,-0.5687,-15.8430,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,5.3147,0.5134,-10.0030,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-3.0396,-0.7877,-17.0562,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-14.9925,-1.0853,-28.7115,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-14.9925,-1.0853,-28.7115,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-14.9925,-1.0853,-28.7115,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-11.4691,-1.3156,-24.9578,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-11.4691,-1.3156,-24.9578,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-11.1376,-0.9871,-24.9548,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-11.1376,-0.9871,-24.9548,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-11.1376,-0.9871,-24.9548,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-3.0396,-0.7877,-17.0562,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,1.6976,-0.0608,-13.0459,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-6.5203,-0.7752,-20.5494,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-6.5203,-0.7752,-20.5494,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-6.5203,-0.7752,-20.5494,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-6.5203,-0.7752,-20.5494,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,1.6976,-0.0608,-13.0459,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-9.2274,-1.5086,-22.5231,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-24.8000,-0.4692,-39.1351,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.JEC.1,WRJEFFUN10_RA,-1.0210,-0.4969,-15.3284,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.JEC.2,WRJEFFUN11_RA,-1.0198,-0.5001,-15.3240,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.JEC.3,WRJEFFUN12_RA,-1.0660,-0.5464,-15.3240,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-18.4885,-1.0721,-32.2207,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-10.9169,-1.1177,-24.6036,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-10.9169,-1.1177,-24.6036,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.LEC.4,WRLECUN26_RA,-3.0071,-0.1330,-17.6785,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.LEC.5,WRLECUN27_RA,-1.7947,-0.0952,-16.5039,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-5.2023,-0.6751,-19.3316,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-5.2023,-0.6751,-19.3316,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-5.2023,-0.6751,-19.3316,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-5.1541,-0.6465,-19.3119,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-3.0305,-0.9455,-16.8893,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-3.0305,-0.9455,-16.8893,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-3.1334,-1.0214,-16.9164,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-1.5075,-0.7898,-15.5221,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-1.5075,-0.7898,-15.5221,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-5.5503,-1.1466,-19.2080,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-3.0305,-0.9455,-16.8893,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,2.1493,-0.8677,-11.7874,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-3.6370,-0.8843,-17.5570,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-10.9211,-1.1218,-24.6036,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,74.0919,0.5367,58.7509,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-5.9689,-1.6595,-19.1138,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-1.6074,-0.5687,-15.8430,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-3.2400,-1.1099,-16.9344,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,1.6976,-0.0608,-13.0459,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-3.0396,-0.7877,-17.0562,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-12.4793,-0.8422,-26.4415,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.THAYERLD,WR.THAYERLD_LA,23.2433,0.4726,7.9664,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-13.2525,-0.8368,-27.2200,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0106,V106_DDR,-12.3221,-0.8019,-26.3245,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-4.9333,0.0337,-19.7714,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-3.8542,-0.6510,-18.0075,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-3.2139,-0.0113,-18.0069,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-3.2139,-0.0113,-18.0069,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-1.6953,-0.0162,-16.4834,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-11.7041,-0.6941,-25.8143,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0157,V157_DDR,-3.1221,-0.0274,-17.8990,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0158,V158_DDR,-3.2139,-0.0113,-18.0069,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-3.2139,-0.0113,-18.0069,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-12.4794,-0.8915,-26.3922,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0173,V173_DDR,-5.2433,-0.7641,-19.2835,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0174,V174_DDR,-12.1923,-0.8175,-26.1791,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0184,V184_DDR,-11.8789,-0.9056,-25.7776,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-12.5941,-0.8359,-26.5626,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0186,V186_DDR,-12.6177,-0.8767,-26.5454,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-12.0751,-0.8756,-26.0038,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-13.0822,-0.8088,-27.0777,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-6.2370,-0.5518,-20.4895,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-2.6410,-0.4895,-16.9558,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-1.9847,-0.5183,-16.2708,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-1.9847,-0.5183,-16.2708,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-2.6410,-0.4895,-16.9558,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0245,V245_DDR,-12.6068,-0.8365,-26.5746,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.VOLT.0248,V248_DDR,-12.3221,-0.8019,-26.3245,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-15.3919,-1.0054,-29.1909,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,0.2700,-0.1847,-14.3496,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.WOLF,WRWOLFUN15_RA,-3.6177,-1.1876,-17.2344,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-9.2274,-1.5086,-22.5231,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,5.2398,0.4385,-10.0030,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-14.9925,-1.0853,-28.7115,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-14.9925,-1.0853,-28.7115,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-14.9925,-1.0853,-28.7115,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-14.9925,-1.0853,-28.7115,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-12.2005,-0.6750,-26.3298,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-3.8018,-0.6526,-17.9535,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-13.3205,-0.8322,-27.2926,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-13.3205,-0.8322,-27.2926,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-13.3205,-0.8322,-27.2926,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-13.3205,-0.8322,-27.2926,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-2.4929,-0.3901,-16.9071,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-2.4929,-0.3901,-16.9071,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-2.4929,-0.3901,-16.9071,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-2.4929,-0.3901,-16.9071,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-2.4929,-0.3901,-16.9071,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-2.4929,-0.3901,-16.9071,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-26.1160,-0.7781,-40.1422,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-26.1160,-0.7781,-40.1422,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-28.3756,-0.8150,-42.3650,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-28.3756,-0.8150,-42.3650,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_MIDW,WR_MIDW_LA,-3.7225,-0.8891,-17.6378,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,14.6918,0.3514,-0.4639,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,12.4222,0.1179,-2.5000,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-5.4191,-0.8451,-19.3783,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_SEG,WR_SEG_LA,4.2501,0.3103,-10.8646,14.8044\n03/19/2025 09:00:00,03/19/2025 14:00:00,WR_WR,WR_LA,-5.0821,-0.5114,-19.3750,14.8043\n03/19/2025 09:00:00,03/19/2025 14:00:00,YAD,VACS,21.8270,0.4953,6.5273,14.8044\n03/19/2025 10:00:00,03/19/2025 15:00:00,AEC,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,AECC_CSWS,CSWS_AECC_LA,39.5611,0.8406,19.8526,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,42.9382,0.6628,23.4076,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,39.1882,1.1395,19.1808,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,42.7959,0.4425,23.4855,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,33.2022,0.5748,13.7595,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,39.6491,0.4939,20.2873,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,33.1306,0.3149,13.9479,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,AECI,AECI,30.8131,0.2819,11.6633,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,AEPM_CSWS,CSWS_LA,38.8327,0.6597,19.3051,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,ALTW,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,AMRN,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-12.8369,-0.6262,-31.0786,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BBA,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BCA,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BEPM.ER01.DDR,ER01_DDR,10.9857,-2.2743,-5.6078,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,BEPM_ER01,BEPM_ER01_LA,10.9857,-2.2743,-5.6078,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,11.5832,-0.4128,-6.8718,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,7.7154,-0.2997,-10.8528,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BEPM_UM01,BEPM_UM01_LA,16.4671,0.5260,-2.9268,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BLKW,BLKW,-3.6591,-0.2377,-22.2893,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-29.9660,-1.6340,-47.1999,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-29.9660,-1.6340,-47.1999,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,33.3111,-1.4303,15.8735,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.9367,-1.6047,-47.1999,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BRAZ,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BUBA,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-5.5999,-1.7293,-22.7384,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-9.5255,-1.0897,-27.3037,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-9.5255,-1.0897,-27.3037,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-9.5255,-1.0897,-27.3037,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-9.5255,-1.0897,-27.3037,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-9.5255,-1.0897,-27.3037,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-5.6330,-0.9147,-23.5862,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,12.8866,-0.5252,-5.4560,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,12.8866,-0.5252,-5.4560,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CLEC,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,41.6916,0.3941,22.4297,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,COWP,COWP_LA,28.2975,0.4952,8.9345,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,28.2975,0.4952,8.9345,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,28.2975,0.4952,8.9345,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CPLE,VACS,29.9855,0.5657,10.5520,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CPLW,VACS,29.9855,0.5657,10.5520,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,30.6231,0.6986,11.0567,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,30.6231,0.6986,11.0567,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,30.6231,0.6986,11.0567,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,30.6231,0.6986,11.0567,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CRTH_SPA,WRCRTH_SPA_LA,39.6799,-0.0369,20.8489,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,33.9784,1.7583,13.3523,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,11.7976,-0.8686,-6.2016,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,33.1306,0.3149,13.9479,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,42.7959,0.4425,23.4855,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,33.9671,1.7458,13.3535,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,33.2399,0.9302,13.4418,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,33.7886,1.5315,13.3892,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,33.7886,1.5315,13.3892,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,42.7039,0.5854,23.2507,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,42.7039,0.5854,23.2507,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,42.7040,0.5854,23.2507,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,42.7040,0.5854,23.2507,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,33.1306,0.3149,13.9479,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,36.3779,1.2870,16.2230,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,64.9309,-0.0885,46.1515,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,64.7568,-0.2626,46.1515,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,46.8521,0.1494,27.8348,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,45.4789,0.2175,26.3936,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,45.4789,0.2175,26.3936,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,45.4800,0.2175,26.3947,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,45.4800,0.2175,26.3947,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-16.8467,-1.0846,-34.6300,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,20.4330,-0.6033,2.1684,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,46.4341,0.3428,27.2235,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-14.8969,-1.2720,-32.4928,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-14.8355,-1.2106,-32.4928,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-4.3820,-0.7329,-22.5170,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.GRID.CDL1,CDL1_DDR,45.1587,0.4179,25.8730,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,7.8527,-0.9250,-10.0902,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,12.5114,-1.1490,-5.2075,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,45.1587,0.4179,25.8730,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.NUEN.CSI1,CSI1_DDR,46.2656,0.4675,26.9303,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.NUEN.CSI2,CSI2_DDR,46.2725,0.4744,26.9303,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,41.7038,0.4062,22.4297,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.NUEN.GAZA,GAZA_DDR,45.1587,0.4179,25.8730,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,88.3206,0.8684,68.5843,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.NUEN.T201,NT201_DDR,45.6656,0.2994,26.4983,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,4.5968,-1.2204,-13.0507,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,4.5968,-1.2204,-13.0507,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,33.1306,0.3149,13.9479,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,34.1407,1.6980,13.5748,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-4.3820,-0.7329,-22.5170,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-4.3820,-0.7329,-22.5170,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-8.1291,-1.0412,-25.9558,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-14.8355,-1.2106,-32.4928,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,33.0855,0.8601,13.3575,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,42.9768,0.0964,24.0125,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,42.6903,-0.1901,24.0125,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,42.6816,-0.1988,24.0125,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,23.6127,0.0511,4.6937,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,23.6127,0.0511,4.6937,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,33.2165,0.8791,13.4695,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,47.2790,0.2593,28.1518,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,33.1929,0.8611,13.4639,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,34.6384,2.1993,13.5713,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,37.0470,0.5601,17.6190,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,46.2725,0.4744,26.9303,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0057,OKMU_DDR,49.7724,0.4564,30.4481,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0060,LEHIGH_DDR,88.3206,0.8684,68.5843,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0086,WARRENM_DDR,45.9064,0.2995,26.7391,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,34.1979,1.6579,13.6722,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,56.2773,0.3229,37.0865,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0121,V121_DDR,33.2165,0.8791,13.4695,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0122,V122_DDR,54.7487,0.2967,35.5842,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0124,V124_DDR,74.2890,0.2020,55.2191,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0135,V135_DDR,46.8829,0.3395,27.6755,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0144,V144_DDR,21.1320,-0.5444,2.8085,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0145,V145_DDR,21.4140,-0.6466,3.1928,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,33.2846,0.9404,13.4764,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,33.4700,0.5887,14.0134,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0175,V175_DDR,41.7038,0.4062,22.4297,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,33.4700,0.5887,14.0134,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,33.6298,0.7230,14.0389,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,46.8829,0.3395,27.6755,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,46.9610,0.3106,27.7825,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,46.3073,0.2689,27.1705,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,60.7942,0.0864,41.8399,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,45.5913,0.1969,26.5265,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,46.9610,0.3106,27.7825,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0211,V211_DDR,33.4751,1.1639,13.4433,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,57.0106,0.3337,37.8090,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0213,V213_DDR,46.5829,0.3032,27.4118,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0215,V215_DDR,55.7795,0.3141,36.5975,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0217,V217_DDR,57.0566,0.3134,37.8754,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0218,V218_DDR,60.3304,0.1015,41.3611,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0228,V228_DDR,47.8254,0.2300,28.7275,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0232,V232_DDR,46.4795,0.3447,27.2669,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0233,V233_DDR,47.1767,0.3302,27.9786,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0240,V240_DDR,53.0339,0.2228,33.9432,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0244,V244_DDR,46.9610,0.3106,27.7825,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0246,MDT1_DDR,88.3206,0.8684,68.5843,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0249,V249_DDR,46.5511,0.3255,27.3577,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0250,V250_DDR,10.5197,-0.8173,-7.5309,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0251,V251_DDR,45.9458,0.2583,26.8196,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.VOLT.0252,V252_DDR,60.7942,0.0864,41.8399,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-20.0532,-1.0666,-37.8545,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,29.0823,-1.2219,11.4363,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-11.0911,-2.1172,-27.8418,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,32.8126,0.4893,13.4554,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-13.6662,-2.1592,-30.3749,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,16.2447,-0.6791,-1.9441,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,16.2447,-0.6791,-1.9441,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,16.2447,-0.6791,-1.9441,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,16.2447,-0.6791,-1.9441,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,16.2447,-0.6791,-1.9441,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,33.1306,0.3149,13.9479,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,33.5640,1.5250,13.1711,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,46.4494,0.3147,27.2669,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,45.4197,0.0149,26.5370,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,53.2909,0.5409,33.8822,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,53.2909,0.5409,33.8822,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWWELSH1,CSWSWELSHUN1_RA,33.1667,0.7059,13.5929,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWWELSH3,CSWSWELSHUN3_RA,33.1667,0.7059,13.5929,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWWILKES1,CSWSWILKESUN1_RA,33.6125,1.1005,13.6441,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWWILKES2,CSWSWILKESUN2_RA,33.6125,1.1005,13.6441,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,CSWWILKES3,CSWSWILKESUN3_RA,33.4441,1.0356,13.5407,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-14.8178,-1.1929,-32.4928,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,DENL,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,DERS,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,DOE,DOE,26.8010,0.4072,7.5259,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,15.7171,-0.0503,-3.1005,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,DPC,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,DUK,VACS,29.9855,0.5657,10.5520,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDDY,EDDY,15.5317,1.0274,-4.3635,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,37.6877,-0.1502,18.9701,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-0.0530,-0.3428,-18.5781,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,42.0734,-0.3757,23.5812,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE.SLCC,EDESTL4391_PLT,39.6169,-0.2434,20.9925,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,39.5429,-0.1783,20.8533,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,25.9398,-0.4585,7.5304,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_EC_01,EDELAR3821UN1_RA,37.6877,-0.1502,18.9701,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_EC_02,EDELAR3821UN2_RA,37.6877,-0.1502,18.9701,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_EC_03,EDELAR3821UN3_RA,37.6877,-0.1502,18.9701,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_EC_04,EDELAR3821UN4_RA,37.6877,-0.1502,18.9701,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_EDE,EDE_LA,38.6594,0.3290,19.4626,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_ERW,EDEERWFUNG1_RA,-6.3931,-0.9844,-24.2766,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-0.9223,-1.0578,-18.7323,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,40.4000,0.9126,20.6195,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,40.4000,0.9126,20.6195,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,40.4000,0.9126,20.6195,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,40.4000,0.9126,20.6195,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,19.2520,0.6023,-0.2182,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_RIV_10,EDERIV1671UN10_RA,39.6492,-0.3064,21.0878,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_RIV_11,EDERIV1671UN11_RA,39.6492,-0.3064,21.0878,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_RIV_12,EDERIV453UN12_PLT,39.1267,-0.8290,21.0878,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_SL_01,EDESTL4391UN1_RA,39.2756,-0.5848,20.9925,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EDE_SWMP,EDE_SWMP_LA,36.4563,0.5015,17.0869,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EEI,EEI,26.7104,0.4048,7.4378,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,EES,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-3.7277,-0.9797,-21.6159,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,ERCOTE,ERCOTE,33.1667,0.7059,13.5929,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,ERCOTN,ERCOTN,4.6775,-1.1396,-13.0507,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,7.7947,-0.7669,-10.3062,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,FMPP,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,FPC,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,FPL,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,FREM_50T,OPPDFREM_GUN1_RA,13.0320,-0.4760,-5.3599,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,FREM_6,OPPDFREM_AUN6_RA,13.0254,-0.4853,-5.3572,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,FREM_7,OPPDFREM_AUN7_RA,13.0254,-0.4853,-5.3572,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,FREM_8,OPPDFREM_AUN8_RA,12.9180,-0.5927,-5.3572,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,FREM_LOAD,FREM_LOAD_LA,13.0085,-0.5022,-5.3572,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-9.3687,-0.8278,-27.4088,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,33.0855,0.8601,13.3575,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-10.0806,-2.4487,-26.4997,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-25.3730,-1.5007,-42.7402,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,41.6916,0.3941,22.4297,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,41.6916,0.3941,22.4297,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,41.6916,0.3941,22.4297,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,46.2564,0.2376,27.1509,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,46.2564,0.2376,27.1509,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,46.4118,0.2318,27.3121,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,46.4118,0.2318,27.3121,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-18.8331,-1.3614,-36.3396,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,58.6934,0.1309,39.6946,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,58.6934,0.1309,39.6946,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,58.6934,0.1309,39.6946,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.VOLT.0130,V130_DDR,47.5109,0.4423,28.2007,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA.VOLT.0237,V237_DDR,47.6205,0.3161,28.4365,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDAHUB2,GRDAHUB2_H,33.4301,-0.1933,14.7555,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDAHUB3,GRDAHUB3_H,26.6825,-0.3450,8.1597,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA_GRDA,GRDA_LA,47.4514,0.3287,28.2548,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA_HUB,GRDA_H,41.0241,0.0012,22.1551,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRDA_HUBSA,GRDASA_H,40.8915,-0.0347,22.0583,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GRE,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,0.0323,0.6325,-19.4680,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,GSEC_SPS,SPS_GSEC_LA,-6.1100,-0.5215,-24.4564,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GSPR2014HUB,GSPR2014HUB_H,0.8550,-0.6016,-17.4112,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,GSPR2015HUB,GSPR2015HUB_H,1.4912,-0.6264,-16.7503,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-9.0682,-1.5361,-26.4000,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,HARRISON,CSWSLEBROCKPLT1,33.0334,0.7178,13.4477,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,HAST_TNSK_HUB,HAST_TNSK_H,9.2072,-0.8312,-8.8295,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,HQST,PJM,23.3916,0.1678,4.3560,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,HST,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,17.1227,0.3404,-2.0856,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,17.1227,0.3404,-2.0856,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,17.1351,0.3361,-2.0689,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,17.1351,0.3361,-2.0689,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,17.1007,0.3396,-2.1068,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,17.1007,0.3396,-2.1068,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,INDN_INDN,INDN_LA,17.1332,0.3485,-2.0832,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-0.4199,-1.1202,-18.1676,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,ISNE,PJM,23.3916,0.1678,4.3560,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,JEA,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,13.0352,-0.4280,-5.4046,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,13.0352,-0.4280,-5.4046,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-0.3462,-0.0520,-19.1620,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KACYCT4,KACYNEARMANUNCT4_RA,25.4300,0.2397,6.3224,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,63.7200,-0.2337,45.0858,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,25.4300,0.2397,6.3224,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,24.8034,0.2606,5.6749,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,24.9761,0.2585,5.8498,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KACY_KACY,KACY_LA,24.6630,0.2542,5.5410,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,17.6682,0.1240,-1.3236,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,19.4940,0.7006,-0.0745,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-7.1914,-1.0426,-25.0167,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-41.1397,-1.3145,-58.6931,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.VOLT.0222,V222_DDR,10.3587,-0.0110,-8.4981,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.VOLT.0223,V223_DDR,15.4991,-0.0626,-3.3062,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.VOLT.0241,V241_DDR,20.7728,0.5816,1.3234,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.VOLT.0243,V243_DDR,27.8828,0.2116,8.8033,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.VOLT.0247,V247_DDR,16.3017,0.0967,-2.6629,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.VOLT.0253,V253_DDR,17.5918,0.1339,-1.4100,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,1.7934,-1.3757,-15.6988,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,13.8688,-0.2648,-4.7342,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,13.8688,-0.2648,-4.7342,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,13.8688,-0.2648,-4.7342,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,13.8688,-0.2648,-4.7342,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,17.5949,0.1240,-1.3970,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,17.5949,0.1240,-1.3970,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHUB,KCPLHUB_H,6.2838,-0.7252,-11.8588,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHUB17,KCPLHUB17_H,5.3718,-0.8146,-12.6815,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHUB18,KCPLHUB18_H,5.5579,-0.8135,-12.4965,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHUB19,KCPLHUB19_H,5.3839,-0.7725,-12.7115,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHUB20,KCPLHUB20_H,4.8251,-0.8499,-13.1928,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHUB21,KCPLHUB21_H,4.6510,-0.8317,-13.3852,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHUB22,KCPLHUB22_H,5.6321,-0.8266,-12.4092,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHUB23,KCPLHUB23_H,5.0102,-0.8478,-13.0099,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLHUB24,KCPLHUB24_H,4.4365,-0.8860,-13.5454,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,7.4429,-0.0467,-11.3782,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,7.4429,-0.0467,-11.3782,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,12.9343,-0.5856,-5.3480,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,12.9343,-0.5856,-5.3480,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,17.6764,0.1322,-1.3236,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,17.6682,0.1240,-1.3236,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,18.7645,0.1832,-0.2866,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,18.7645,0.1832,-0.2866,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,18.7645,0.1832,-0.2866,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,18.7645,0.1832,-0.2866,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,18.7645,0.1832,-0.2866,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,18.7645,0.1832,-0.2866,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,18.7645,0.1832,-0.2866,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,18.7645,0.1832,-0.2866,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,8.3326,-0.3358,-10.1994,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,17.0509,0.1199,-1.9369,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KCPL_KCPL,KCPL_LA,17.6287,0.0941,-1.3333,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KENN,KENN_LA,21.4553,0.5780,2.0094,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KEP2_SECI,KEP2_SECI_LA,-6.4761,-1.4873,-23.8567,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KERR_1,GRDAKERR_HYDUN1_RA,47.1184,0.2761,27.9745,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KERR_2,GRDAKERR_HYDUN2_RA,46.9525,0.2788,27.8059,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KERR_3,GRDAKERR_HYDUN3_RA,46.9525,0.2788,27.8059,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KERR_4,GRDAKERR_HYDUN4_RA,47.1184,0.2761,27.9745,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,13.8687,-0.2649,-4.7342,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,13.8687,-0.2649,-4.7342,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,14.8160,-0.1547,-3.8972,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,14.8160,-0.1547,-3.8972,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,12.1611,-0.2732,-6.4336,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,10.7365,-0.2446,-7.8868,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,10.7365,-0.2446,-7.8868,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-5.0382,-1.4770,-22.4291,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-5.0382,-1.4770,-22.4291,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-5.0382,-1.4770,-22.4291,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-1.6678,-0.6878,-19.8478,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-1.6678,-0.6878,-19.8478,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-5.1445,-1.5029,-22.5095,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-2.2359,-0.8277,-20.2761,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-0.2480,-0.5868,-18.5291,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,57.4882,-0.2721,38.8924,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,57.4882,-0.2721,38.8924,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,4.3194,-0.4704,-14.0780,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,4.3194,-0.4704,-14.0780,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,4.3194,-0.4704,-14.0780,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-3.1591,-1.1797,-20.8473,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-2.9618,-1.3005,-20.5292,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,7.3249,-0.6130,-10.9299,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-1.3475,0.0189,-20.2343,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LAFA,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LAM345,LAM345,-5.5999,-1.7293,-22.7384,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,LEPA,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,11.6183,-0.5085,-6.7410,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_LES,LES_LA,11.6385,-0.5293,-6.7001,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,11.8228,-0.5974,-6.4477,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,11.4711,-0.5780,-6.8188,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,11.4711,-0.5780,-6.8188,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,11.4711,-0.5780,-6.8188,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,11.8298,-0.5904,-6.4477,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,11.8228,-0.5974,-6.4477,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_WAVERLY,LES_WAVERLY_H,11.8081,-0.5963,-6.4635,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,13.1367,-0.5720,-5.1591,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,13.1367,-0.5720,-5.1591,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,LGEE,LGEE,25.2116,0.2847,6.0590,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MALDEN,MALDEN_LA,21.8744,0.5530,2.4535,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MCWEST,MCWEST,15.8194,-0.0149,-3.0336,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MDU,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,8.8366,-0.3597,-9.6716,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,9.5721,-0.2264,-9.0693,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,13.2797,0.4503,-6.0385,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MEAN_NPPD,NPPD_MEAN_LA,8.4765,-0.9833,-9.4080,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MEC,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MHEB,MHEB,16.8151,0.0061,-2.0589,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,1.4211,-1.0287,-16.4181,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-3.3259,-1.4446,-20.7492,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,1.4211,-1.0287,-16.4181,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,1.4211,-1.0287,-16.4181,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-3.3259,-1.4446,-20.7492,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-9.7361,-1.0236,-27.5803,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MISO,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-6.1610,-1.1913,-23.8376,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-6.1610,-1.1913,-23.8376,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,2.3451,-0.7757,-15.7470,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-6.8615,-1.9142,-23.8152,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-2.8025,-1.2132,-20.4572,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-7.2817,-1.6417,-24.5079,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-6.2375,-1.2535,-23.8519,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-7.3386,-1.5303,-24.6761,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-6.1245,-1.1019,-23.8905,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-6.1245,-1.1019,-23.8905,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-6.1245,-1.1019,-23.8905,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-6.1245,-1.1019,-23.8905,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-6.1245,-1.1019,-23.8905,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,16.6506,0.0036,-2.2209,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,24.6305,0.3506,5.4121,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,24.6305,0.3506,5.4121,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,22.6110,0.1866,3.5565,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,20.7346,0.6694,1.1974,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MOWR,AECI,30.8131,0.2819,11.6633,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,22.3402,0.1618,3.3105,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,24.9100,0.3624,5.6797,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,12.4684,-1.0608,-5.3387,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,13.6700,-0.5861,-4.6118,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-8.7115,-1.3951,-26.1843,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,12.5288,-1.0004,-5.3387,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,15.7245,-0.0429,-3.1005,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,15.7245,-0.0429,-3.1005,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,15.7250,-0.0424,-3.1005,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,15.7250,-0.0424,-3.1005,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,10.3587,-0.0110,-8.4981,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,10.3587,-0.0110,-8.4981,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,10.3587,-0.0110,-8.4981,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,10.2992,-0.0706,-8.4981,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,10.3587,-0.0110,-8.4981,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,10.3587,-0.0110,-8.4981,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,10.3587,-0.0110,-8.4981,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,25.2367,0.4343,5.9345,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,16.3645,-0.0394,-2.4640,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,15.2941,-0.1099,-3.4638,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,15.2942,-0.1099,-3.4638,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,15.2943,-0.1098,-3.4638,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,16.7258,0.1335,-2.2756,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,16.7258,0.1335,-2.2756,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MPS_MPS,MPS_LA,16.0171,0.1660,-3.0168,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MSTNG,SPSMSTNGPLT1,18.2493,0.9946,-1.6131,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MSTNG4,SPSMSTNGUN4_RA,18.1824,0.9276,-1.6131,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,MSTNG5,SPSMSTNGUN5_RA,18.2493,0.9946,-1.6131,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,18.2493,0.9946,-1.6131,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NBSO,PJM,23.3916,0.1678,4.3560,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,11.7775,-1.0348,-6.0556,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,11.7746,-1.0377,-6.0556,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-10.0918,-1.9711,-26.9885,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NHC1,VACS,29.9855,0.5657,10.5520,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,13.0341,-0.4817,-5.3520,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,13.0341,-0.4817,-5.3520,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,13.0341,-0.4817,-5.3520,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,10.0906,-1.0811,-7.6961,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,8.8023,-1.0381,-9.0274,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,10.4246,-0.8505,-7.5928,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,13.2468,-0.7602,-4.8609,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,8.8023,-1.0381,-9.0274,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.HUB.PY2018,NPPDPY18_H,8.8284,-1.0935,-8.9460,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,8.9569,-1.0869,-8.8241,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,8.8666,-1.0803,-8.9210,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,8.9727,-1.0663,-8.8289,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,12.7184,-0.8061,-5.3434,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,6.9194,-1.0978,-10.8507,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,6.9194,-1.0978,-10.8507,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,6.0785,-0.9456,-11.8437,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,12.7184,-0.8061,-5.3434,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,11.5274,-1.3907,-5.9497,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,8.0333,-1.4572,-9.3774,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,4.4636,-1.0943,-13.3099,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,8.0333,-1.4572,-9.3774,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,9.0638,-1.2804,-8.5237,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,7.8084,-1.3036,-9.7558,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,11.1106,-0.3956,-7.3617,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,8.8023,-1.0381,-9.0274,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,4.8531,-1.1210,-12.8938,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,6.9194,-1.0978,-10.8507,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,6.9194,-1.0978,-10.8507,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,7.5877,-0.7956,-10.4846,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,7.5397,-0.8071,-10.5211,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,7.5397,-0.8071,-10.5211,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,8.3500,-0.4232,-10.0947,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,12.0000,-0.4086,-6.4593,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,9.1160,-0.7992,-8.9527,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,10.5327,-0.8293,-7.5059,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,12.2373,-0.3119,-6.3187,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,12.0000,-0.3174,-6.5505,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.NELI.DDR,NELI_DDR,12.1727,-0.9487,-5.7465,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.NPPM.1058,SH1058_DDR,11.9821,-0.3296,-6.5561,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,8.2513,-0.5968,-10.0197,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,8.8023,-1.0381,-9.0274,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,10.4246,-0.8505,-7.5928,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,12.7184,-0.8061,-5.3434,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.TECH.1,KEARNE_DDR,8.5942,-0.4403,-9.8334,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,9.9800,-1.6052,-7.2826,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,9.9800,-1.6052,-7.2826,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,12.4195,-0.9044,-5.5440,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD.VOLT.0236,V236_DDR,10.3663,-0.4291,-8.0724,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD2017HUB,NPPD2017HUB_H,8.8399,-1.0898,-8.9382,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,11.5385,-0.8134,-6.5160,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,10.0906,-1.0811,-7.6961,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,7.8971,-1.7408,-9.2300,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,7.8971,-1.7408,-9.2300,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,10.4959,-0.4651,-7.9069,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,10.3872,-0.4082,-8.0724,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,12.7952,-0.7522,-5.3205,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,7.6460,-0.8260,-10.3958,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,11.5665,-0.7452,-6.5561,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,11.5665,-0.7452,-6.5561,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,11.5665,-0.7452,-6.5561,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,9.2255,-0.8245,-8.8179,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,11.3938,-0.9411,-6.5329,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,9.5205,-0.5173,-8.8301,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,12.0442,-1.8203,-5.0034,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,12.1458,-1.7187,-5.0034,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,6.2892,-1.1934,-11.3853,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,6.0681,-1.2038,-11.5960,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,9.6024,-0.7617,-8.5038,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,9.5874,-0.7766,-8.5038,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,9.5874,-0.7766,-8.5038,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,9.5918,-0.7360,-8.5401,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,11.5274,-1.3907,-5.9497,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,9.5510,-0.7393,-8.5776,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,11.0518,-0.6721,-7.1440,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,9.2443,-0.7793,-8.8443,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,9.2272,-0.7925,-8.8482,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,9.2335,-0.7803,-8.8540,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,9.2335,-0.7803,-8.8540,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,9.2255,-0.8245,-8.8179,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,9.1737,-0.8762,-8.8179,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,11.4345,-0.3978,-7.0356,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,9.7513,-0.4969,-8.6197,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,6.3867,-1.1051,-11.3761,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,10.9794,-1.5364,-6.3521,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,4.1074,-1.1672,-13.5933,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,12.3313,0.0196,-6.5561,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,12.1727,-0.9487,-5.7465,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,6.5331,-1.1503,-11.1845,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,6.5331,-1.1503,-11.1845,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_NPPD,NPPD_LA,10.2550,-0.6846,-7.9283,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,11.0518,-0.6721,-7.1440,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,11.0518,-0.6721,-7.1440,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,8.0135,-0.8281,-10.0263,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,7.5301,-1.0538,-10.2840,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NSB,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NSP,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,NSSO,PJM,23.3916,0.1678,4.3560,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,NYIS,PJM,23.3916,0.1678,4.3560,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-10.7710,-2.0427,-27.5961,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-17.3500,-1.3650,-34.8529,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,1.3150,-1.0652,-16.4876,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,1.3150,-1.0652,-16.4876,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-10.0885,-2.2738,-26.6826,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-25.3730,-1.5007,-42.7402,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-95.7911,-0.9117,-113.7473,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-42.7635,-1.3043,-60.3271,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-21.0599,-1.3692,-38.5586,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-17.4589,-1.3791,-34.9476,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,7.6337,-0.4857,-10.7484,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-21.0599,-1.3692,-38.5586,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-10.3049,-2.2282,-26.9445,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-9.7361,-1.0236,-27.5803,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-11.0426,-2.0035,-27.9069,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,42.5013,-0.1617,23.7951,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-17.4589,-1.3791,-34.9476,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-14.6974,-1.2930,-32.2723,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-8.7620,-1.2320,-26.3979,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-9.5255,-1.0897,-27.3037,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-36.8647,-0.1731,-55.5595,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-9.7361,-1.0236,-27.5803,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-9.7361,-1.0236,-27.5803,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-17.4589,-1.3791,-34.9476,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-6.8240,-1.0081,-24.6838,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.NUEN.LAM1,LAM1_DDR,41.9016,1.2803,21.7535,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.NUEN.MDT2,MDT2_DDR,7.6337,-0.4857,-10.7484,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.NUEN.MDT3,MDT3_DDR,7.6337,-0.4857,-10.7484,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-7.1349,-1.0074,-24.9954,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,4.9250,-0.5513,-13.3916,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,4.9250,-0.5513,-13.3916,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,4.9250,-0.5513,-13.3916,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,11.2968,-0.4645,-7.1066,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,11.2968,-0.4645,-7.1066,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,4.9250,-0.5513,-13.3916,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,4.9250,-0.5513,-13.3916,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-17.4589,-1.3791,-34.9476,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,27.2255,0.7544,7.6033,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-10.3049,-2.2282,-26.9445,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-25.5747,-0.5605,-43.8820,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-14.6974,-1.2930,-32.2723,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,37.9562,0.8412,18.2472,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-15.3364,-1.0661,-33.1382,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-15.3364,-1.0661,-33.1382,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-15.3364,-1.0661,-33.1382,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-15.3364,-1.0661,-33.1382,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-17.6700,-1.8587,-34.6792,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-21.4401,-1.3108,-38.9972,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-17.3500,-1.3650,-34.8529,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-26.6874,-1.2862,-44.2691,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-26.6874,-1.2862,-44.2691,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-19.7558,-0.2120,-38.4116,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-11.7279,-1.1949,-29.4009,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-11.7279,-1.1949,-29.4009,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-11.7279,-1.1949,-29.4009,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0033,FOSTER_DDR,18.3515,-0.4215,-0.0948,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,42.6997,0.7418,23.0901,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0035,TARBY_DDR,41.8204,1.0389,21.9136,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,42.6997,0.7418,23.0901,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,42.3725,0.5674,22.9372,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,42.3725,0.5674,22.9372,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-32.7103,-0.3036,-51.2745,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0040,TROSPER_DDR,22.1444,-0.3913,3.6678,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,22.0814,-0.3913,3.6048,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,39.4674,1.0039,19.5956,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0115,V115_DDR,8.7571,-0.4757,-9.6351,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0116,V116_DDR,79.1500,-0.0815,60.3636,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0118,V118_DDR,23.3185,-0.0117,4.4623,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0125,V125_DDR,40.3769,1.1733,20.3358,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0126,V126_DDR,42.8247,0.5784,23.3784,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0129,V129_DDR,7.8538,-0.9239,-10.0902,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,49.7988,-0.5018,31.4327,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0134,V134_DDR,43.5773,0.7279,23.9816,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0138,V138_DDR,42.2323,0.4857,22.8787,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,42.6181,-0.4065,24.1567,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0143,V143_DDR,41.6728,0.3908,22.4141,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0149,V149_DDR,-5.7883,-0.9486,-23.7076,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0150,V150_DDR,-5.6258,-1.0054,-23.4883,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0155,V155_DDR,41.6710,0.3864,22.4167,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0156,V156_DDR,49.7988,-0.5018,31.4327,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0166,V166_DDR,42.9649,1.0513,23.0457,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,41.7697,-0.4140,23.3158,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-5.6258,-1.0054,-23.4883,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0170,V170_DDR,-7.2924,-1.0047,-25.1556,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-15.7798,-0.9229,-33.7248,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0176,V176_DDR,-5.6258,-1.0054,-23.4883,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0177,V177_DDR,-13.9117,-1.8157,-30.9639,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,34.1008,-0.4114,15.6443,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-6.0000,-1.0432,-23.8247,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0195,V195_DDR,144.7100,1.0361,124.8060,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0197,V197_DDR,44.3768,0.6266,24.8823,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0198,V198_DDR,42.9649,1.0513,23.0457,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0208,V208_DDR,144.7996,1.0524,124.8793,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0209,V209_DDR,144.7996,1.0524,124.8793,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,44.1169,0.4534,24.7956,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0216,V216_DDR,22.0648,-0.3923,3.5892,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0219,V219_DDR,41.6710,0.3864,22.4167,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0220,V220_DDR,-5.6258,-1.0054,-23.4883,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0224,V224_DDR,7.9144,-0.5030,-10.4505,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0225,V225_DDR,7.9154,-0.5020,-10.4505,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0226,V226_DDR,7.9144,-0.5030,-10.4505,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0227,V227_DDR,7.9144,-0.5030,-10.4505,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0229,V229_DDR,-28.0819,-0.2367,-46.7131,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0231,V231_DDR,26.1600,0.0884,7.2037,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0238,V238_DDR,-16.6177,-1.4366,-34.0489,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.VOLT.0242,V242_DDR,41.9217,0.4342,22.6196,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-14.1994,-2.4766,-30.5906,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-9.7361,-1.0236,-27.5803,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-17.2221,-1.3306,-34.7594,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-11.0269,-1.9879,-27.9069,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-14.1994,-2.4766,-30.5906,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-11.1448,-2.2865,-27.7261,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-48.3401,-1.2616,-65.9463,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEHL7,OKGEHL7_H,33.1276,-0.3860,14.6457,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEHL8,OKGEHSL1UN8_RA,33.1276,-0.3860,14.6457,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEHL910,OKGEHSL1PLT2,33.1276,-0.3860,14.6457,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-11.0792,-2.1196,-27.8275,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEMCC,OKGEMCCLAIPLT1,5.2984,-0.6977,-12.8718,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,38.9530,0.2855,19.7996,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,38.9530,0.2855,19.7996,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,38.9530,0.2855,19.7996,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,25.4246,-0.6818,7.2385,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,25.4246,-0.6818,7.2385,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,25.4246,-0.6818,7.2385,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,25.4246,-0.6818,7.2385,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGESM1,OKGESEMINOLEUN1_RA,20.1594,-0.3057,1.5972,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGESM2,OKGESEMINOLEUN2_RA,16.9780,-0.3490,-1.5409,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGESM3,OKGESEMINOLEUN3_RA,16.9780,-0.3490,-1.5409,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGESO1,OKGESONR1UN1_RA,-59.0854,-1.2210,-76.7323,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGESO2,OKGESONR1UN2_RA,-26.6874,-1.2862,-44.2691,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-11.2289,-2.2693,-27.8275,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-11.5737,-2.4538,-27.9878,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGETINK5A,OKGETINK5UN1_RA,20.0137,-0.4358,1.5817,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGETINK5B,OKGETINK5UN2_RA,20.0137,-0.4358,1.5817,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-11.4576,-1.7377,-28.5877,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-17.3500,-1.3650,-34.8529,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,38.8746,1.2950,18.7117,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-9.7361,-1.0236,-27.5803,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE_OKGE,OKGE_LA,24.5151,-0.2200,5.8672,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-25.5747,-0.5605,-43.8820,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-11.5086,-1.7888,-28.5877,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMLP,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,49.1711,0.1623,30.1409,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,39.1594,1.2138,19.0778,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_GENHUB,OMPA_GENHUB_H,4.5894,-0.5347,-13.7437,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-95.6248,-0.7454,-113.7473,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-8.5026,-1.1813,-26.1892,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-21.0599,-1.3692,-38.5586,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-13.2557,-1.9109,-30.2127,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,1.2360,-1.7299,-15.9019,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,182.8304,0.1237,163.8388,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-95.6789,-0.7995,-113.7473,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-95.6789,-0.7995,-113.7473,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_SPP,OMPA_SPP_LA,4.3139,-0.7180,-13.8360,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-14.1994,-2.4766,-30.5906,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,44.2876,0.1450,25.2747,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,44.2876,0.1450,25.2747,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,44.2876,0.1450,25.2747,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,44.2876,0.1450,25.2747,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,ONT,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,13.0054,-0.4922,-5.3703,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,13.0054,-0.4922,-5.3703,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,13.0054,-0.4922,-5.3703,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,13.0054,-0.4922,-5.3703,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,13.0054,-0.4922,-5.3703,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,13.0054,-0.4922,-5.3703,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,13.0054,-0.4922,-5.3703,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,13.0054,-0.4922,-5.3703,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,13.0054,-0.4922,-5.3703,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,13.0359,-0.4606,-5.3714,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,13.0341,-0.4817,-5.3520,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,12.9526,-0.3277,-5.5876,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,12.9151,-0.4352,-5.5175,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,12.9151,-0.4352,-5.5175,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD_GLDN,OPPD_GLDN_LA,12.9343,-0.4839,-5.4497,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,13.0306,-0.4755,-5.3618,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,11.5274,-1.3907,-5.9497,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,11.1933,-0.7036,-6.9710,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,13.0342,-0.4813,-5.3524,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD_OPPD,OPPD_LA,12.9854,-0.4255,-5.4570,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,12.9611,-0.4144,-5.4924,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,12.9458,-0.4203,-5.5018,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OTP,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,OVEC,OVEC,24.4829,0.2402,5.3749,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,PARAGOULD,PARAGOULD_LA,20.8038,0.6184,1.3175,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,46.6101,0.1190,27.6232,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,46.6101,0.1190,27.6232,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,46.6101,0.1190,27.6232,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,46.3131,0.1929,27.2524,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,46.3131,0.1929,27.2524,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,46.3131,0.1929,27.2524,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,PIGGOTT,PIGGOTT_LA,21.6044,0.5692,2.1673,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PJM,PJM,23.3916,0.1678,4.3560,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,PLUM,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,POPLARBLUFF,POPLARBLUFF_LA,23.7039,0.5017,4.3343,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,15.4987,-0.3087,-3.0605,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,15.4987,-0.3087,-3.0605,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,15.5647,-0.3010,-3.0022,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,15.5647,-0.3010,-3.0022,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,16.9055,0.9913,-2.9537,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,16.9055,0.9913,-2.9537,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,15.8206,-0.0199,-3.0274,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,14.7278,-0.8165,-3.3236,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-5.6330,-0.9147,-23.5862,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,95.8575,0.1778,76.8118,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,11.3072,-0.0167,-7.5440,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,3.1967,-0.0363,-15.6349,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,53.7667,0.6053,34.2935,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,42.8347,0.6787,23.2881,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,15.7591,-0.5137,-2.5951,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,16.1444,0.0298,-2.7532,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,14.7267,-0.7829,-3.3582,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,34.2100,1.5668,13.7753,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,16.5935,0.1442,-2.4186,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,15.6168,-0.3093,-2.9418,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,PUPP,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,RCEAST,RCEAST,11.9949,-1.2009,-5.6721,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SALINA_1,GRDASALINA1UN1_RA,47.1203,0.2780,27.9745,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SALINA_2,GRDASALINA1UN2_RA,47.1203,0.2780,27.9745,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SALINA_3,GRDASALINA1UN3_RA,47.1203,0.2780,27.9745,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SALINA_4,GRDASALINA1UN4_RA,47.1203,0.2780,27.9745,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SALINA_5,GRDASALINA1UN5_RA,47.1203,0.2780,27.9745,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SALINA_6,GRDASALINA1UN6_RA,47.1203,0.2780,27.9745,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SARPY_1,OPPDSARPYUN1_RA,12.9562,-0.4686,-5.4431,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SARPY_2,OPPDSARPYUN2_RA,12.9740,-0.4285,-5.4654,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SARPY_3,OPPDSARPYUN3_RA,12.9444,-0.5072,-5.4163,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SARPY_4,OPPDSARPYUN4_RA,12.9444,-0.5072,-5.4163,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SARPY_5,OPPDSARPYUN5_RA,12.9444,-0.5072,-5.4163,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SC,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SCEG,VACS,29.9855,0.5657,10.5520,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SCSE,SCSE,7.1145,-0.8608,-10.8926,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SEC,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-8.0529,-1.8795,-25.0413,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-8.0529,-1.8795,-25.0413,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-8.0529,-1.8795,-25.0413,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-5.1405,-1.3216,-22.6868,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-8.0529,-1.8795,-25.0413,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-6.3381,-1.8753,-23.3306,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-6.2898,-1.9978,-23.1599,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-6.2898,-1.9978,-23.1599,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-6.1269,-1.1043,-23.8905,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-9.2018,-1.6565,-26.4132,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-1.7488,-0.7689,-19.8478,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-5.5634,-1.2591,-23.1721,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-0.8517,-1.4585,-18.2611,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-7.6635,-1.9024,-24.6289,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-0.7943,-1.4405,-18.2216,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-6.7984,-1.8446,-23.8217,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-8.3216,-3.3742,-23.8153,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-5.1887,-1.5719,-22.4846,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-5.1887,-1.5719,-22.4846,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-5.1887,-1.5719,-22.4846,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-5.1887,-1.5719,-22.4846,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-5.4438,-1.6743,-22.6374,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-6.3381,-1.8753,-23.3306,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI_SECI,SECI_LA,-4.9499,-1.3452,-22.4726,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-0.4199,-1.1202,-18.1676,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-0.4199,-1.1202,-18.1676,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-6.1269,-1.1043,-23.8905,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SEHA,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-11.5086,-1.7888,-28.5877,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SERU,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SETH,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SGE,SGE,8.1073,-0.8293,-9.9313,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SMEP,MISO,23.2593,0.2262,4.1652,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SOCO,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPA,SPA,35.1363,0.7340,15.5345,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPC,SPC,16.4627,0.4573,-2.8624,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPPNORTH_HUB,SPPNORTH_H,11.8564,-0.5118,-6.4996,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPPSOUTH_HUB,SPPSOUTH_H,11.7397,-0.8682,-6.2600,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,34.2964,0.6070,14.8215,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,34.2964,0.6070,14.8215,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,33.6362,0.5758,14.1925,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,33.6362,0.5758,14.1925,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_NIXA,SPRM_NIXA_LA,34.6183,0.6160,15.1344,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_SPRM,SPRM_LA,34.3941,0.6707,14.8555,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,34.4940,0.5090,15.1171,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,34.4940,0.5090,15.1171,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,34.4442,0.4593,15.1171,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,34.4940,0.5090,15.1171,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-0.4985,-0.2222,-19.1442,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-7.4293,-0.7899,-25.5072,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-9.6303,-1.5351,-26.9631,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-9.6303,-1.5351,-26.9631,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-14.9061,-1.4002,-32.3737,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,7.0448,-0.7703,-11.0528,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-6.4283,-2.7359,-22.5603,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,15.0636,0.5001,-4.3044,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-15.7539,-0.5342,-34.0875,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,18.3204,0.9848,-1.5322,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,17.9559,0.9832,-1.8952,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,17.9559,0.9832,-1.8952,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,18.3204,0.9848,-1.5322,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-9.5687,-1.4734,-26.9632,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-7.4293,-0.7899,-25.5072,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-9.3800,-1.4265,-26.8214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-9.9495,-2.2287,-26.5887,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-9.1832,-1.3495,-26.7016,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-8.9309,-1.0183,-26.7805,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-9.3520,-1.4420,-26.7779,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-9.7379,-2.2719,-26.3339,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-9.7379,-2.2719,-26.3339,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-9.7379,-2.2719,-26.3339,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-9.7379,-2.2719,-26.3339,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GRID.WRAB,WRAB_DDR,-9.2875,-1.0788,-27.0766,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-9.7379,-2.2719,-26.3339,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-12.8369,-0.6262,-31.0786,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-12.8369,-0.6262,-31.0786,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-12.5975,-0.5685,-30.8969,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-12.5975,-0.5685,-30.8969,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-12.5975,-0.5685,-30.8969,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-12.8369,-0.6262,-31.0786,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-9.7458,-1.4996,-27.1141,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-9.7457,-1.4996,-27.1139,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-9.7440,-1.4996,-27.1123,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-10.0918,-1.9711,-26.9885,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,18.2615,0.9357,-1.5421,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-15.6277,-0.5455,-33.9501,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-15.6277,-0.5455,-33.9501,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-15.6277,-0.5455,-33.9501,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-15.6277,-0.5455,-33.9501,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,19.0536,1.1077,-0.9220,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,18.3672,0.9549,-1.4555,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,18.3672,0.9549,-1.4555,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-11.4282,-1.7084,-28.5877,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-9.7196,-1.4774,-27.1101,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-9.7196,-1.4774,-27.1101,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-9.7618,-1.4922,-27.1375,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-9.2875,-1.0788,-27.0766,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-9.6622,-1.9493,-26.5808,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-9.5871,-1.5536,-26.9014,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-10.0885,-2.2738,-26.6826,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-9.4181,-1.1759,-27.1101,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-5.7665,-0.4459,-24.1885,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-5.7665,-0.4459,-24.1885,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-4.9506,-0.4737,-23.3447,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-15.0956,-1.0810,-32.8824,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-9.6798,-2.0873,-26.4603,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-5.9672,-2.2747,-22.5603,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-15.0704,-1.0559,-32.8824,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-9.5344,-1.4391,-26.9632,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,1.6591,-0.3895,-16.8193,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,15.4464,0.8830,-4.3044,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,1.6591,-0.3895,-16.8193,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,15.4648,0.9159,-4.3189,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-9.4828,-1.6413,-26.7094,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,18.2423,1.8758,-2.5014,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,18.2735,1.9070,-2.5014,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,18.4803,1.7523,-2.1399,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,18.5288,1.0918,-1.4309,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,16.7615,1.5275,-3.6339,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-5.5999,-1.7293,-22.7384,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-9.3767,-1.1653,-27.0793,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-3.6907,-0.4107,-22.1478,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-3.6907,-0.4107,-22.1478,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,1.6591,-0.3895,-16.8193,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-16.0776,-0.4367,-34.5088,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,27.0513,1.4896,6.6938,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-3.1127,0.6658,-22.6464,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-4.1402,0.0113,-23.0193,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-10.2983,-0.7439,-28.4223,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,18.2423,1.8758,-2.5014,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,17.6914,2.1891,-3.3655,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,17.4325,1.9302,-3.3655,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-14.8720,-0.8575,-32.8824,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-3.5968,0.0857,-22.5504,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-9.6212,-1.9979,-26.4912,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-9.6535,-2.0292,-26.4922,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0163,V163_DDR,-9.2048,-1.2350,-26.8377,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0168,V168_DDR,-13.1570,-0.9911,-31.0337,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0180,V180_DDR,17.6914,2.1891,-3.3655,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0181,V181_DDR,-9.3920,-1.7863,-26.4735,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0182,V182_DDR,16.8900,1.6952,-3.6731,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0199,V199_DDR,22.0284,1.3397,1.8209,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0200,V200_DDR,18.4451,1.4246,-1.8474,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.VOLT.0235,V235_DDR,-9.6622,-1.9493,-26.5808,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-6.4283,-2.7359,-22.5603,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,15.0636,0.5001,-4.3044,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-9.1792,-1.6471,-26.4000,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-9.5092,-1.3618,-27.0152,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS_SPS,SPS_LA,8.4846,0.6224,-11.0057,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,15.3371,0.3105,-3.8412,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,SSCN_NPPD,SSCN_NPPD_LA,13.3855,-0.6665,-4.8159,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,23.3050,0.4768,3.9603,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,23.3050,0.4768,3.9603,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,TAL,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,TEC,SOUC,30.0267,0.6017,10.5571,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,10.9794,-1.5364,-6.3521,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,TVA,TVA,29.9337,0.5278,10.5381,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,UCUHUB,UCUHUB_H,5.6500,-0.4078,-12.8101,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,UCUHUB17,UCUHUB17_H,1.7794,-1.1746,-15.9139,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,UCUHUB18,UCUHUB18_H,4.9576,-0.8433,-13.0670,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,UCUHUB19,UCUHUB19_H,1.8986,-0.9820,-15.9873,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,UCUHUB20,UCUHUB20_H,2.0675,-0.9643,-15.8361,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,UCUHUB21,UCUHUB21_H,-0.1020,-1.1576,-17.8123,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,UCUHUB22,UCUHUB22_H,0.4346,-1.1058,-17.3274,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,UCUHUB23,UCUHUB23_H,0.2433,-1.1196,-17.5050,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,UCUHUB24,UCUHUB24_H,2.8458,-0.9873,-15.0347,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,16.5926,0.6051,-2.8803,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,16.5926,0.6051,-2.8803,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,15.2583,-0.5372,-3.0723,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,15.2583,-0.5372,-3.0723,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,15.7718,-0.5916,-2.5045,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,15.4664,-0.4297,-2.9717,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,15.4664,-0.4297,-2.9717,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,16.5926,0.6051,-2.8803,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,15.8518,-0.5612,-2.4549,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,16.3771,0.1385,-2.6292,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,15.3611,-0.4246,-3.0822,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,12.2858,-1.9760,-4.6061,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,16.4866,0.5575,-2.9387,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,16.4866,0.5575,-2.9387,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,13.8179,-1.9212,-3.1288,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,15.2813,-0.6341,-2.9525,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,15.5761,-0.6003,-2.6915,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,14.7666,-0.7876,-3.3136,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,15.3880,-0.3902,-3.0897,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,15.1007,-0.6952,-3.0720,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,14.8198,-0.9192,-3.1288,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,14.8198,-0.9192,-3.1288,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,15.3006,-0.5752,-2.9921,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,11.8224,-2.1457,-4.8998,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,16.2055,0.4083,-3.0707,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,25.0400,-0.0449,6.2170,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,25.0400,-0.0449,6.2170,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,25.0400,-0.0449,6.2170,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,15.8939,-0.0194,-2.9545,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,15.8939,-0.0194,-2.9545,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,15.8939,-0.0194,-2.9545,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,16.8705,0.8568,-2.8542,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,15.5839,-0.5292,-2.7548,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,15.5839,-0.5292,-2.7548,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,7.6004,-0.8596,-10.4078,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,14.6430,-0.5193,-3.7056,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,16.1899,0.1118,-2.7898,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,13.7223,-0.8334,-4.3122,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,11.1241,-2.5993,-5.1444,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,15.0670,-0.7218,-3.0791,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,16.5471,0.6006,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,16.5471,0.6006,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,16.5462,0.5997,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,16.5471,0.6006,-2.9214,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,16.3836,0.4464,-2.9306,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,16.3836,0.4464,-2.9306,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,16.3836,0.4464,-2.9306,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,16.3836,0.4464,-2.9306,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,16.3836,0.4464,-2.9306,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,16.3836,0.4464,-2.9306,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,16.3836,0.4464,-2.9306,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,12.7898,-1.5726,-4.5055,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,16.1202,-0.2168,-2.5308,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,14.3927,-0.4299,-4.0452,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,14.3927,-0.4299,-4.0452,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,13.4514,-0.8515,-4.5650,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,13.4514,-0.8515,-4.5650,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,15.8224,-0.2907,-2.7548,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,15.9187,-0.2722,-2.6770,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,14.7975,-0.9478,-3.1226,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,12.1762,-1.7970,-4.8947,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,16.0778,-0.3099,-2.4802,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,15.7718,-0.5916,-2.5045,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,15.7718,-0.5916,-2.5045,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,14.7666,-0.7876,-3.3136,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,11.9324,-1.2522,-5.6833,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,14.3471,-0.9151,-3.6057,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,12.0185,-1.9496,-4.8998,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,14.9477,-0.8181,-3.1021,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.FSE,WAUE.FSE_H,11.7455,-1.0163,-6.1061,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,15.6956,-0.1957,-2.9766,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,15.6475,-0.2371,-2.9832,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,11.9761,-1.9455,-4.9462,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,12.0895,-1.8715,-4.9069,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,15.7375,-0.5418,-2.5885,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,15.6997,-0.6196,-2.5486,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-12.2600,-1.6112,-29.5167,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,12.2858,-1.9760,-4.6061,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-1.3700,-1.0266,-19.2113,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,14.4923,-0.6019,-3.7737,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,14.4927,-0.6015,-3.7737,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,14.4927,-0.6015,-3.7737,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,15.0928,-0.6081,-3.1669,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,11.9324,-1.2522,-5.6833,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,15.9667,-0.2028,-2.6984,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,14.6267,-0.8415,-3.3997,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,16.1463,0.3492,-3.0707,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,15.4935,0.1246,-3.4989,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,15.4899,-0.3364,-3.0415,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,16.9195,-0.2743,-1.6740,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,15.0203,-0.5959,-3.2517,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,14.7678,-0.9415,-3.1586,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,13.7223,-0.8334,-4.3122,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,17.9686,0.3435,-1.2428,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,14.7445,-0.8088,-3.3145,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,17.8888,0.3068,-1.2859,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,15.8160,-0.2006,-2.8513,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,13.1367,-0.5720,-5.1591,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NTWK,WAUE.NTWK_H,15.0665,-0.4717,-3.3297,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,16.3679,0.7054,-3.2054,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,16.3679,0.7054,-3.2054,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,12.2446,-2.0651,-4.5581,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,12.4501,-1.9724,-4.4453,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,15.6063,-0.4977,-2.7639,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,12.2446,-2.0651,-4.5581,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,16.5651,-0.1711,-2.1317,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,13.7431,-1.1516,-3.9731,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,13.7223,-0.8334,-4.3122,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,14.5328,-0.6910,-3.6441,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,11.6907,-3.2041,-3.9731,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,10.2961,-2.4261,-6.1457,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,10.8305,-2.4295,-5.6078,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,15.2258,-0.5756,-3.0665,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,10.3341,-1.7579,-6.7759,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,15.9247,-0.2519,-2.6913,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,12.9280,-1.5059,-4.4340,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,12.1762,-1.7970,-4.8947,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.VOLT.0152,V152_DDR,17.1392,1.0845,-2.8132,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE.VOLT.0172,V172_DDR,16.4671,0.5260,-2.9268,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_BEPM,WAUE_BEPM_LA,16.2341,0.0815,-2.7152,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,15.9758,-0.2456,-2.6465,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,15.5019,0.1352,-3.5011,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_EWA,WAUE_EWA_LA,12.0705,-1.1471,-5.6502,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,14.0516,-1.0114,-3.8049,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_HMMU,WAUE_HMMU_LA,14.3061,-0.0819,-4.4799,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,17.0958,-0.2655,-1.5066,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_MECB,WAUE_MECB_LA,15.1522,0.1390,-3.8546,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_MMPA,WAUE_MMPA_LA,16.8751,0.2294,-2.2222,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_MRES,WAUE_MRES_LA,15.5303,-0.4097,-2.9279,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,16.8824,0.7411,-2.7266,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,15.6956,-0.1957,-2.9766,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,13.9441,-0.8893,-4.0345,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_OTP,WAUE_OTP_LA,17.7649,0.7384,-1.8414,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_OTPW,WAUE_OTPW_LA,21.1150,0.4948,1.7523,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM,WAUE_UGPM_LA,15.4738,-0.2448,-3.1493,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,16.2323,-0.0792,-2.5563,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,15.0652,-0.5492,-3.2535,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,11.8378,-0.8405,-6.1896,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,12.0705,-1.1471,-5.6502,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,14.3061,-0.0819,-4.4799,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,14.0902,-0.9569,-3.8208,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,15.6956,-0.1957,-2.9766,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,16.8751,0.2294,-2.2222,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,15.9298,-0.2963,-2.6418,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,13.5571,-1.0178,-4.2929,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,17.1915,0.7665,-2.4429,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-13.9320,-2.2207,-30.5792,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-16.2945,-1.6418,-33.5206,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,15.2722,-1.2505,-2.3452,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,87.9900,0.5378,68.5843,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,87.9900,0.5378,68.5843,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-3.1704,-2.4480,-19.5903,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,81.7986,0.6482,62.2826,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,74.4808,0.6202,54.9927,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,42.0400,-1.0430,24.2151,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,42.0400,-1.0430,24.2151,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,42.0400,-1.0430,24.2151,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,42.0400,-1.0430,24.2151,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,41.9882,-1.0948,24.2151,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,42.0400,-1.0430,24.2151,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,42.0400,-1.0430,24.2151,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,42.0400,-1.0430,24.2151,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,28.3380,-0.9745,10.4446,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-10.0885,-2.2738,-26.6826,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-29.9660,-1.6340,-47.1999,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-13.8423,-2.0725,-30.6377,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-6.1166,-2.4242,-22.5603,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_ENMC,WFEC_ENMC_LA,12.7369,0.9027,-7.0337,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-17.4589,-1.3791,-34.9476,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,40.2435,0.3783,20.9973,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,18.8121,1.0203,-1.0760,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-13.9320,-2.2207,-30.5792,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-13.9320,-2.2207,-30.5792,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-13.9320,-2.2207,-30.5792,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_OKGE,WFEC_OKGE_LA,10.9148,0.1094,-8.0625,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,66.0309,0.6316,46.5314,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-9.2913,-2.5290,-25.6302,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-1.9445,-2.6579,-18.1544,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_WFEC,WFEC_LA,29.8212,-0.3880,11.3414,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,18.8121,1.0203,-1.0760,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,0.5919,-1.0514,-17.2246,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-4.0212,-1.6870,-21.2021,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,1.3626,-0.6883,-16.8169,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,1.3626,-0.6883,-16.8169,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,1.3626,-0.6884,-16.8169,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,1.3626,-0.6884,-16.8169,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,1.3626,-0.6884,-16.8169,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,1.3626,-0.6884,-16.8169,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,1.3626,-0.6884,-16.8169,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,11.1510,0.5673,-8.2842,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-0.2789,-0.9627,-18.1841,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-13.5383,-1.3211,-31.0851,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-13.5383,-1.3211,-31.0851,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-13.5383,-1.3211,-31.0851,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-9.3872,-1.6467,-26.6084,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-9.3872,-1.6467,-26.6084,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-8.9610,-1.2161,-26.6127,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-8.9610,-1.2161,-26.6127,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-8.9610,-1.2161,-26.6127,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-0.2789,-0.9627,-18.1841,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,4.9707,-0.0627,-13.8345,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-3.9987,-0.9370,-21.9296,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-3.9987,-0.9370,-21.9296,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-3.9987,-0.9370,-21.9296,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-3.9987,-0.9370,-21.9296,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,4.9707,-0.0627,-13.8345,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-7.0595,-1.9381,-23.9893,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-17.2178,-0.8088,-35.2768,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.JEC.1,WRJEFFUN10_RA,1.9366,-0.6284,-16.3029,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.JEC.2,WRJEFFUN11_RA,1.9396,-0.6328,-16.2954,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.JEC.3,WRJEFFUN12_RA,1.8696,-0.7028,-16.2954,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-18.8331,-1.3614,-36.3396,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-8.6996,-1.3832,-26.1843,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-8.6996,-1.3832,-26.1843,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.LEC.4,WRLECUN26_RA,-0.2560,-0.1317,-18.9921,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.LEC.5,WRLECUN27_RA,1.0936,-0.0945,-17.6798,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-2.5669,-0.7906,-20.6442,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-2.5669,-0.7906,-20.6442,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-2.5669,-0.7906,-20.6442,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-2.5101,-0.7547,-20.6233,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-0.4199,-1.1202,-18.1676,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-0.4199,-1.1202,-18.1676,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-0.6944,-1.3022,-18.2601,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,1.0287,-0.9584,-16.8808,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,1.0287,-0.9584,-16.8808,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-2.9710,-1.3097,-20.5292,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-0.4199,-1.1202,-18.1676,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,5.1407,-1.0212,-12.7059,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-0.9223,-1.0578,-18.7323,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-8.7046,-1.3881,-26.1843,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,76.3527,0.6318,56.8531,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-3.4690,-1.8971,-20.4397,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,1.3626,-0.6884,-16.8169,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,1.1727,-1.4123,-16.2829,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,4.9707,-0.0627,-13.8345,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-0.2789,-0.9627,-18.1841,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-10.3695,-1.0325,-28.2049,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.THAYERLD,WR.THAYERLD_LA,24.2093,0.5455,4.7959,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-11.3337,-1.0251,-29.1765,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0106,V106_DDR,-10.1274,-0.9840,-28.0113,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-2.3906,0.0571,-21.3156,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-1.1280,-0.7709,-19.2250,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-0.4769,0.0133,-19.3580,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-0.4769,0.0133,-19.3580,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0148,WR.VOLT.0148_H,1.1976,-0.0027,-17.6675,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-9.3927,-0.8493,-27.4113,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0157,V157_DDR,-0.3761,-0.0070,-19.2370,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0158,V158_DDR,-0.4769,0.0133,-19.3580,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-0.4769,0.0133,-19.3580,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-10.2558,-1.1083,-28.0154,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0173,V173_DDR,-2.6129,-0.8800,-20.6008,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0174,V174_DDR,-9.9460,-1.0124,-27.8015,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0184,V184_DDR,-9.5464,-1.1246,-27.2897,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-10.5065,-1.0239,-28.3505,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0186,V186_DDR,-10.5803,-1.0745,-28.3736,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-9.7989,-1.0833,-27.5835,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-11.0953,-0.9913,-28.9719,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-3.6322,-0.6614,-21.8387,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0190,WR.VOLT.0190_H,0.2809,-0.5857,-18.0013,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0191,WR.VOLT.0191_H,0.9748,-0.6180,-17.2751,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0192,WR.VOLT.0192_H,0.9748,-0.6180,-17.2751,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0196,WR.VOLT.0196_H,0.2809,-0.5857,-18.0013,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0245,V245_DDR,-10.5253,-1.0241,-28.3691,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.VOLT.0248,V248_DDR,-10.1274,-0.9840,-28.0113,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-14.3453,-1.2702,-31.9429,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,3.3854,-0.2137,-15.2688,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.WOLF,WRWOLFUN15_RA,0.5764,-1.5084,-16.7831,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-7.0595,-1.9381,-23.9893,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,11.0573,0.4736,-8.2842,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-13.5383,-1.3211,-31.0851,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-13.5383,-1.3211,-31.0851,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-13.5383,-1.3211,-31.0851,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-13.5383,-1.3211,-31.0851,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-10.8720,-0.8280,-28.9118,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-1.0709,-0.7730,-19.1657,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-11.3696,-1.0334,-29.2041,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-11.3696,-1.0334,-29.2041,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-11.3696,-1.0334,-29.2041,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-11.3696,-1.0334,-29.2041,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,0.3770,-0.4751,-18.0158,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,0.3770,-0.4751,-18.0158,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,0.3770,-0.4751,-18.0158,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,0.3770,-0.4751,-18.0158,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,0.3770,-0.4751,-18.0158,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,0.3770,-0.4751,-18.0158,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-27.5690,-0.9514,-45.4854,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-27.5690,-0.9514,-45.4854,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-30.3652,-0.9818,-48.2513,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-30.3652,-0.9818,-48.2513,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_MIDW,WR_MIDW_LA,-1.2045,-1.0837,-18.9887,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,19.7116,0.4353,0.4085,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,16.9019,0.1515,-2.1174,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-2.9546,-1.0438,-20.7787,18.8679\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_SEG,WR_SEG_LA,12.1092,0.2875,-7.0461,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,WR_WR,WR_LA,-2.5799,-0.6313,-20.8164,18.8678\n03/19/2025 10:00:00,03/19/2025 15:00:00,YAD,VACS,29.9855,0.5657,10.5520,18.8678\n03/19/2025 11:00:00,03/19/2025 16:00:00,AEC,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,AECC_CSWS,CSWS_AECC_LA,34.0126,0.6849,17.8097,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,37.4342,0.5372,21.3790,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,33.5513,0.8888,17.1445,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,37.3054,0.3545,21.4329,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,27.7050,0.5208,11.6662,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,34.1206,0.3789,18.2237,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,27.7579,0.3297,11.9102,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,AECI,AECI,26.3846,0.2479,10.6188,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,AEPM_CSWS,CSWS_LA,33.1727,0.5815,17.0731,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,ALTW,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,AMRN,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-13.3482,-0.7689,-28.0973,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BBA,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BCA,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BEPM.ER01.DDR,ER01_DDR,7.9843,-1.7877,-5.7460,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BEPM_ER01,BEPM_ER01_LA,7.9843,-1.7877,-5.7460,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,8.3140,-0.3397,-6.8644,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,5.0337,-0.2076,-10.2766,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,BEPM_UM01,BEPM_UM01_LA,12.4871,0.5877,-3.6186,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BLKW,BLKW,-5.5073,-0.5115,-20.5137,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-25.3692,-1.3895,-39.4977,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-25.3692,-1.3895,-39.4977,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,22.3135,-1.2363,8.0318,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-25.3446,-1.3649,-39.4977,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BRAZ,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BUBA,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-6.7734,-1.4425,-20.8489,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-10.9163,-0.9196,-25.5147,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-10.9163,-0.9196,-25.5147,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-10.9163,-0.9196,-25.5147,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-10.9163,-0.9196,-25.5147,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-10.9163,-0.9196,-25.5147,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-5.5290,-0.7395,-20.3075,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,9.4474,-0.3298,-5.7408,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,9.4474,-0.3298,-5.7408,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CLEC,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,36.2776,0.3300,20.4297,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,COWP,COWP_LA,24.7592,0.4096,8.8316,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,24.7592,0.4096,8.8316,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,24.7592,0.4096,8.8316,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CPLE,VACS,22.9236,0.4922,6.9134,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CPLW,VACS,22.9236,0.4922,6.9134,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,24.9757,0.5871,8.8706,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,24.9757,0.5871,8.8706,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,24.9757,0.5871,8.8706,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,24.9757,0.5871,8.8706,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CRTH_SPA,WRCRTH_SPA_LA,35.1156,-0.0267,19.6243,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,28.1786,1.5099,11.1507,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,5.1596,-0.7733,-9.5851,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,27.7579,0.3297,11.9102,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,37.3054,0.3545,21.4329,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,28.1705,1.4989,11.1536,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,27.7139,0.9116,11.2844,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,28.0533,1.3317,11.2036,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,28.0533,1.3317,11.2036,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,37.2537,0.4743,21.2614,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,37.2537,0.4743,21.2614,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,37.2538,0.4744,21.2614,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,37.2538,0.4744,21.2614,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,27.7579,0.3297,11.9102,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,30.8220,1.0956,14.2084,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,56.8226,-0.0706,41.3752,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,56.6794,-0.2138,41.3752,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,40.9691,0.1238,25.3273,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,40.0664,0.1922,24.3562,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,40.0664,0.1922,24.3562,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,40.0679,0.1922,24.3577,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,40.0679,0.1922,24.3577,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-15.9365,-0.9359,-30.5186,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,13.3532,-0.5123,-1.6525,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,40.8873,0.2963,25.0730,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-14.4538,-1.1214,-28.8504,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-14.4030,-1.0706,-28.8504,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-9.3860,-0.6126,-24.2914,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.GRID.CDL1,CDL1_DDR,39.6617,0.3477,23.7960,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,3.2093,-0.7819,-11.5268,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,5.6634,-1.0886,-8.7660,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,39.6617,0.3477,23.7960,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.NUEN.CSI1,CSI1_DDR,40.4022,0.3737,24.5105,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.NUEN.CSI2,CSI2_DDR,40.4080,0.3795,24.5105,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,36.2868,0.3391,20.4297,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.NUEN.GAZA,GAZA_DDR,39.6617,0.3477,23.7960,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,84.6400,0.7068,68.4152,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.NUEN.T201,NT201_DDR,40.1408,0.2553,24.3675,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-1.1040,-1.0324,-15.5896,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-1.1040,-1.0324,-15.5896,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,27.7579,0.3297,11.9102,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,28.4614,1.5021,11.4413,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-9.3860,-0.6126,-24.2914,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-9.3860,-0.6126,-24.2914,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-9.9236,-0.8877,-24.5539,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-14.4030,-1.0706,-28.8504,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,27.4883,0.8029,11.1675,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,38.0238,0.0867,22.4191,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,37.7909,-0.1461,22.4191,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,37.7835,-0.1536,22.4191,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,20.5091,0.0507,4.9404,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,20.5091,0.0507,4.9404,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,27.7260,0.8830,11.3250,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,41.6976,0.2255,25.9541,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,27.7132,0.8801,11.3151,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,28.8420,1.8732,11.4508,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,31.6924,0.5019,15.6725,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,40.4080,0.3795,24.5105,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0057,OKMU_DDR,43.0847,0.3775,27.1892,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0060,LEHIGH_DDR,84.6400,0.7068,68.4152,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0086,WARRENM_DDR,40.4281,0.2622,24.6479,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,28.5185,1.4324,11.5681,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,49.2796,0.2681,33.4935,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0121,V121_DDR,27.7260,0.8830,11.3250,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0122,V122_DDR,47.9530,0.2470,32.1880,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0124,V124_DDR,64.9776,0.1667,49.2930,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0135,V135_DDR,41.2564,0.2948,25.4436,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0144,V144_DDR,14.0444,-0.4669,-1.0067,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0145,V145_DDR,14.3450,-0.5541,-0.6189,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,27.7787,0.9268,11.3339,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,28.0431,0.5508,11.9743,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0175,V175_DDR,36.2868,0.3391,20.4297,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,28.0431,0.5508,11.9743,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,28.1776,0.6634,11.9962,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,41.2564,0.2948,25.4436,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,41.3055,0.2687,25.5188,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,40.7192,0.2316,24.9696,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,53.2131,0.0737,37.6214,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,40.1865,0.1766,24.4919,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,41.3055,0.2687,25.5188,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0211,V211_DDR,27.9081,1.1038,11.2863,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,49.9134,0.2793,34.1161,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0213,V213_DDR,40.9988,0.2647,25.2161,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0215,V215_DDR,48.8478,0.2624,33.0674,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0217,V217_DDR,49.9532,0.2616,34.1736,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0218,V218_DDR,52.8083,0.0861,37.2042,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0228,V228_DDR,42.1792,0.1970,26.4642,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0232,V232_DDR,40.9247,0.3007,25.1060,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0233,V233_DDR,41.4978,0.2862,25.6936,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0240,V240_DDR,46.6062,0.1879,30.9003,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0244,V244_DDR,41.3055,0.2687,25.5188,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0246,MDT1_DDR,84.6400,0.7068,68.4152,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0249,V249_DDR,40.9715,0.2834,25.1701,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0250,V250_DDR,3.9830,-0.7558,-10.7792,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0251,V251_DDR,40.4612,0.2268,24.7164,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.VOLT.0252,V252_DDR,53.2131,0.0737,37.6214,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-18.8657,-0.9086,-33.4751,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,19.0590,-1.0526,4.5936,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-12.1799,-1.7969,-25.9010,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,27.4859,0.6634,11.3046,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-17.1960,-2.6834,-30.0305,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,9.4844,-0.5758,-5.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,9.4844,-0.5758,-5.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,9.4844,-0.5758,-5.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,9.4844,-0.5758,-5.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,9.4844,-0.5758,-5.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,27.7579,0.3297,11.9102,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,27.6930,1.3071,10.8679,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,40.8987,0.2747,25.1060,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,40.1078,0.0873,24.5025,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,45.5405,0.4339,29.5886,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,45.5405,0.4339,29.5886,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWWELSH1,CSWSWELSHUN1_RA,27.7013,0.6720,11.5113,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWWELSH3,CSWSWELSHUN3_RA,27.7013,0.6720,11.5113,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWWILKES1,CSWSWILKESUN1_RA,28.0367,0.9825,11.5362,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWWILKES2,CSWSWILKESUN2_RA,28.0367,0.9825,11.5362,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,CSWWILKES3,CSWSWILKESUN3_RA,27.8640,0.9290,11.4170,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-14.3871,-1.0547,-28.8504,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,DENL,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,DERS,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,DOE,DOE,21.1680,0.3689,5.2811,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,11.5495,-0.0060,-3.9625,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,DPC,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,DUK,VACS,22.9236,0.4922,6.9134,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDDY,EDDY,7.8875,0.4468,-8.0773,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,33.3989,-0.1101,17.9910,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-0.4972,-0.2739,-15.7413,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,37.5838,-0.2985,22.3643,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE.SLCC,EDESTL4391_PLT,34.9337,-0.1929,19.6086,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,34.8795,-0.1386,19.5001,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,23.3827,-0.3651,8.2298,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_EC_01,EDELAR3821UN1_RA,33.3989,-0.1101,17.9910,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_EC_02,EDELAR3821UN2_RA,33.3989,-0.1101,17.9910,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_EC_03,EDELAR3821UN3_RA,33.3989,-0.1101,17.9910,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_EC_04,EDELAR3821UN4_RA,33.3989,-0.1101,17.9910,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_EDE,EDE_LA,33.3277,0.2675,17.5422,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_ERW,EDEERWFUNG1_RA,-6.2185,-0.7998,-20.9367,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-0.1201,-0.8535,-14.7846,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,31.0585,0.6809,14.8596,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,31.0585,0.6809,14.8596,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,31.0585,0.6809,14.8596,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,31.0585,0.6809,14.8596,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,23.9082,0.5127,7.8775,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_RIV_10,EDERIV1671UN10_RA,34.9091,-0.2445,19.6356,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_RIV_11,EDERIV1671UN11_RA,34.9091,-0.2445,19.6356,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_RIV_12,EDERIV453UN12_PLT,34.4792,-0.6744,19.6356,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_SL_01,EDESTL4391UN1_RA,34.6528,-0.4738,19.6086,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EDE_SWMP,EDE_SWMP_LA,32.4177,0.4442,16.4554,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,EEI,EEI,21.1375,0.3671,5.2524,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EES,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-3.0801,-0.8063,-17.7918,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,ERCOTE,ERCOTE,27.7013,0.6720,11.5113,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,ERCOTN,ERCOTN,-1.0377,-0.9661,-15.5896,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,6.9373,-0.5715,-8.0092,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FMPP,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FPC,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FPL,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FREM_50T,OPPDFREM_GUN1_RA,9.5664,-0.3039,-5.6477,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FREM_6,OPPDFREM_AUN6_RA,9.5601,-0.3124,-5.6455,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FREM_7,OPPDFREM_AUN7_RA,9.5601,-0.3124,-5.6455,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FREM_8,OPPDFREM_AUN8_RA,9.4641,-0.4084,-5.6455,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FREM_LOAD,FREM_LOAD_LA,9.5450,-0.3275,-5.6455,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-8.6967,-0.6775,-23.5372,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,27.4883,0.8029,11.1675,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-10.7315,-2.0897,-24.1598,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-23.1091,-1.2369,-37.3902,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,36.2776,0.3300,20.4297,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,36.2776,0.3300,20.4297,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,36.2776,0.3300,20.4297,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,40.3378,0.1862,24.6336,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,40.3378,0.1862,24.6336,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,40.4765,0.1817,24.7768,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,40.4765,0.1817,24.7768,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-17.8872,-1.1267,-32.2784,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,51.9193,0.0913,36.3101,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,51.9193,0.0913,36.3101,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,51.9193,0.0913,36.3101,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.VOLT.0130,V130_DDR,41.4754,0.3510,25.6064,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA.VOLT.0237,V237_DDR,41.5620,0.2510,25.7930,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDAHUB2,GRDAHUB2_H,29.8163,-0.1699,14.4682,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDAHUB3,GRDAHUB3_H,23.5502,-0.2953,8.3275,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA_GRDA,GRDA_LA,41.4048,0.2637,25.6231,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA_HUB,GRDA_H,36.5393,-0.0100,21.0313,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRDA_HUBSA,GRDASA_H,36.5169,-0.0391,21.0380,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GRE,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-3.4511,0.2929,-19.2620,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GSEC_SPS,SPS_GSEC_LA,-7.7825,-0.6686,-22.6318,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,GSPR2014HUB,GSPR2014HUB_H,-2.2783,-0.7661,-17.0302,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GSPR2015HUB,GSPR2015HUB_H,-1.5869,-0.7734,-16.3315,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-10.0903,-1.5763,-24.0320,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,HARRISON,CSWSLEBROCKPLT1,27.5117,0.6960,11.2977,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,HAST_TNSK_HUB,HAST_TNSK_H,6.4571,-0.6158,-8.4452,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,HQST,PJM,18.2071,0.1998,2.4892,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,HST,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,14.8740,0.3263,-0.9703,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,14.8740,0.3263,-0.9703,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,14.9896,0.3238,-0.8521,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,14.9896,0.3238,-0.8521,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,14.7464,0.3250,-1.0966,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,14.7464,0.3250,-1.0966,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,INDN_INDN,INDN_LA,14.9036,0.3348,-0.9491,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-0.4183,-0.8758,-15.0605,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,ISNE,PJM,18.2071,0.1998,2.4892,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,JEA,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,9.5928,-0.2491,-5.6761,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,9.5928,-0.2491,-5.6761,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,7.0655,-0.0190,-8.4335,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KACYCT4,KACYNEARMANUNCT4_RA,14.2208,0.2401,-1.5373,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,59.1800,-0.1926,43.8546,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,14.2208,0.2401,-1.5373,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,14.3702,0.2579,-1.4057,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,14.3320,0.2561,-1.4421,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KACY_KACY,KACY_LA,14.4000,0.2530,-1.3710,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,18.2155,0.1467,2.5508,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,15.2421,0.5904,-0.8663,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-10.9599,-0.8607,-25.6172,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-36.9618,-1.1379,-51.3419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.VOLT.0222,V222_DDR,7.7145,0.0396,-7.8431,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.VOLT.0223,V223_DDR,11.7263,-0.0201,-3.7715,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.VOLT.0241,V241_DDR,16.3679,0.4985,0.3514,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.VOLT.0243,V243_DDR,23.5505,0.1831,7.8494,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.VOLT.0247,V247_DDR,12.5156,0.1182,-3.1206,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.VOLT.0253,V253_DDR,18.2714,0.1544,2.5990,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,0.5835,-1.1229,-13.8116,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,9.4705,-0.1928,-5.8547,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,9.4705,-0.1928,-5.8547,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,9.4705,-0.1928,-5.8547,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,9.4705,-0.1928,-5.8547,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,18.3300,0.1461,2.6659,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,18.3300,0.1461,2.6659,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHUB,KCPLHUB_H,5.4427,-0.5755,-9.4998,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHUB17,KCPLHUB17_H,4.5200,-0.6487,-10.3492,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHUB18,KCPLHUB18_H,4.5147,-0.6448,-10.3584,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHUB19,KCPLHUB19_H,4.4260,-0.6107,-10.4813,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHUB20,KCPLHUB20_H,3.8033,-0.6763,-11.0384,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHUB21,KCPLHUB21_H,3.6394,-0.6642,-11.2144,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHUB22,KCPLHUB22_H,4.4209,-0.6588,-10.4383,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHUB23,KCPLHUB23_H,3.9350,-0.6768,-10.9062,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLHUB24,KCPLHUB24_H,3.3337,-0.7085,-11.4757,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,7.3954,-0.0025,-8.1201,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,7.3954,-0.0025,-8.1201,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,10.0222,-0.4635,-5.0323,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,10.0222,-0.4635,-5.0323,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,18.2219,0.1531,2.5508,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,18.2155,0.1467,2.5508,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,16.6311,0.1955,0.9176,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,16.6311,0.1955,0.9176,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,16.6311,0.1955,0.9176,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,16.6311,0.1955,0.9176,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,16.6311,0.1955,0.9176,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,16.6311,0.1955,0.9176,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,16.6311,0.1955,0.9176,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,16.6311,0.1955,0.9176,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,4.5608,-0.2560,-10.7012,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,13.3837,0.1364,-2.2707,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KCPL_KCPL,KCPL_LA,13.8080,0.1174,-1.8274,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KENN,KENN_LA,23.7048,0.4918,7.6950,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KEP2_SECI,KEP2_SECI_LA,-7.3841,-1.0607,-21.8414,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KERR_1,GRDAKERR_HYDUN1_RA,41.1309,0.2176,25.3953,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KERR_2,GRDAKERR_HYDUN2_RA,40.9906,0.2197,25.2529,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KERR_3,GRDAKERR_HYDUN3_RA,40.9906,0.2197,25.2529,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KERR_4,GRDAKERR_HYDUN4_RA,41.1309,0.2176,25.3953,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,9.4704,-0.1929,-5.8547,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,9.4704,-0.1929,-5.8547,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,9.9660,-0.0982,-5.4538,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,9.9660,-0.0982,-5.4538,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,7.7594,-0.2052,-7.5533,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,6.6913,-0.1765,-8.6502,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,6.6913,-0.1765,-8.6502,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-6.2631,-1.2379,-20.5432,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-6.2631,-1.2379,-20.5432,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-6.2631,-1.2379,-20.5432,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-2.0480,-0.5298,-17.0362,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-2.0480,-0.5298,-17.0362,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-6.3523,-1.2531,-20.6173,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-2.7672,-0.6600,-17.6253,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,0.4996,-0.4907,-14.5277,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,52.9649,-0.2205,37.6674,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,52.9649,-0.2205,37.6674,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,5.6442,-0.3618,-9.5120,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,5.6442,-0.3618,-9.5120,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,5.6442,-0.3618,-9.5120,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-3.7943,-0.9280,-18.3843,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-2.5985,-1.0319,-17.0846,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,7.3740,-0.4857,-7.6584,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,7.8584,0.0428,-7.7024,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LAFA,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LAM345,LAM345,-6.7734,-1.4425,-20.8489,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LEPA,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,8.4706,-0.3139,-6.7335,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_LES,LES_LA,8.4834,-0.3311,-6.7035,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,8.6219,-0.3791,-6.5170,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,8.3594,-0.3738,-6.7848,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,8.3594,-0.3738,-6.7848,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,8.3594,-0.3738,-6.7848,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,8.6256,-0.3754,-6.5170,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,8.6219,-0.3791,-6.5170,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_WAVERLY,LES_WAVERLY_H,8.5993,-0.3856,-6.5331,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,9.6601,-0.3741,-5.4838,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,9.6601,-0.3741,-5.4838,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,LGEE,LGEE,19.6114,0.2829,3.8104,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,MALDEN,MALDEN_LA,23.3465,0.4735,7.3550,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MCWEST,MCWEST,11.8853,0.1316,-3.7643,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MDU,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,5.9260,-0.2874,-9.3045,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,7.8684,-0.1151,-7.5345,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,9.8810,0.4744,-6.1114,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MEAN_NPPD,NPPD_MEAN_LA,5.7300,-0.7444,-9.0436,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MEC,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MHEB,MHEB,12.8141,0.1568,-2.8607,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,0.3684,-0.7921,-14.3575,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-3.9272,-1.1186,-18.3266,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,0.3684,-0.7921,-14.3575,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,0.3684,-0.7921,-14.3575,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-3.9272,-1.1186,-18.3266,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-10.1075,-0.8674,-24.7581,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MISO,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-7.3058,-1.0086,-21.8152,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-7.3058,-1.0086,-21.8152,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,2.4574,-0.5739,-12.4866,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-7.6900,-1.4014,-21.8066,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-3.3649,-0.9590,-17.9239,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-8.1733,-1.2446,-22.4467,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-7.0019,-0.9969,-21.5230,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-8.2518,-1.1668,-22.6030,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-6.8516,-0.9118,-21.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-6.8516,-0.9118,-21.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-6.8516,-0.9118,-21.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-6.8516,-0.9118,-21.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-6.8516,-0.9118,-21.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,12.9390,0.0401,-2.6191,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,20.5819,0.3214,4.7426,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,20.5819,0.3214,4.7426,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,17.9321,0.1988,2.2153,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,16.2826,0.5645,0.2001,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MOWR,AECI,26.3846,0.2479,10.6188,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,18.2386,0.1587,2.5619,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,20.8745,0.3293,5.0272,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,8.0163,-0.7791,-6.7226,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,8.0900,-0.4100,-7.0180,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-10.6195,-1.1521,-24.9854,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,8.0663,-0.7291,-6.7226,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,11.5553,-0.0002,-3.9625,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,11.5553,-0.0002,-3.9625,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,11.5556,0.0001,-3.9625,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,11.5556,0.0001,-3.9625,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,7.7145,0.0396,-7.8431,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,7.7145,0.0396,-7.8431,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,7.7145,0.0396,-7.8431,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,7.6665,-0.0084,-7.8431,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,7.7145,0.0396,-7.8431,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,7.7145,0.0396,-7.8431,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,7.7145,0.0396,-7.8431,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,20.8769,0.3556,5.0033,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,12.3928,0.0001,-3.1252,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,11.4638,-0.0618,-3.9924,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,11.4639,-0.0617,-3.9924,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,11.4639,-0.0617,-3.9924,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,14.1441,0.1492,-1.5231,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,14.1441,0.1492,-1.5231,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MPS_MPS,MPS_LA,12.6061,0.1713,-3.0832,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MSTNG,SPSMSTNGPLT1,12.8857,0.5008,-3.1331,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MSTNG4,SPSMSTNGUN4_RA,12.8394,0.4545,-3.1331,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MSTNG5,SPSMSTNGUN5_RA,12.8857,0.5008,-3.1331,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,12.8857,0.5008,-3.1331,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NBSO,PJM,18.2071,0.1998,2.4892,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,8.3264,-0.7610,-6.4306,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,8.3239,-0.7634,-6.4306,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-10.8483,-1.8322,-24.5341,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NHC1,VACS,22.9236,0.4922,6.9134,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,9.5828,-0.2964,-5.6388,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,9.5828,-0.2964,-5.6388,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,9.5828,-0.2964,-5.6388,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,7.1048,-0.8900,-7.5232,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,6.1644,-0.7840,-8.5696,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,7.4610,-0.6023,-7.4547,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,9.5695,-0.5014,-5.4471,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,6.1644,-0.7840,-8.5696,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.HUB.PY2018,NPPDPY18_H,6.0417,-0.8418,-8.6345,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,6.1512,-0.8349,-8.5319,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,6.0825,-0.8301,-8.6054,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,6.1753,-0.8174,-8.5253,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,9.5473,-0.5456,-5.4251,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,4.4065,-0.8803,-10.2312,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,4.4065,-0.8803,-10.2312,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,3.9528,-0.7205,-10.8447,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,9.5473,-0.5456,-5.4251,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,8.3798,-1.0781,-6.0601,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,5.3972,-1.1690,-8.9518,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,2.2072,-0.9023,-12.4085,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,5.3972,-1.1690,-8.9518,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,6.2831,-1.0265,-8.2084,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,5.1831,-1.0505,-9.2844,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,8.1252,-0.2131,-7.1797,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,6.1644,-0.7840,-8.5696,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,2.5626,-0.9164,-12.0390,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,4.4065,-0.8803,-10.2312,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,4.4065,-0.8803,-10.2312,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,5.0000,-0.6176,-9.9003,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,4.9564,-0.6289,-9.9327,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,4.9564,-0.6289,-9.9327,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,5.7080,-0.2927,-9.5173,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,4.0989,-0.2156,-11.2035,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,6.4648,-0.5808,-8.4724,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,7.4773,-0.6808,-7.3599,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,0.7214,-0.1342,-14.6624,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-0.5800,-0.1385,-15.9595,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.NELI.DDR,NELI_DDR,9.0943,-0.6682,-5.7555,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.NPPM.1058,SH1058_DDR,8.8102,-0.1777,-6.5301,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,5.6497,-0.4290,-9.4393,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,6.1644,-0.7840,-8.5696,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,7.4610,-0.6023,-7.4547,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,9.5473,-0.5456,-5.4251,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.TECH.1,KEARNE_DDR,5.9193,-0.2902,-9.3085,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,7.0658,-1.2599,-7.1923,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,7.0658,-1.2599,-7.1923,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,9.3157,-0.6296,-5.5727,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD.VOLT.0236,V236_DDR,7.7579,-0.2725,-7.4876,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD2017HUB,NPPD2017HUB_H,6.0534,-0.8387,-8.6258,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,8.4605,-0.5601,-6.4974,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,7.1048,-0.8900,-7.5232,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,5.2911,-1.4034,-8.8235,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,5.2911,-1.4034,-8.8235,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,7.8180,-0.2993,-7.4007,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,7.7762,-0.2542,-7.4876,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,8.3570,-0.4890,-6.6720,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,5.0560,-0.6392,-9.8228,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,8.4787,-0.5092,-6.5301,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,8.4787,-0.5092,-6.5301,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,8.4787,-0.5092,-6.5301,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,6.4742,-0.6090,-8.4348,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,8.2190,-0.6868,-6.6122,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,6.8629,-0.3416,-8.3135,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,8.8628,-1.3846,-5.2706,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,8.9471,-1.3003,-5.2706,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,3.8537,-0.9569,-10.7074,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,3.6651,-0.9632,-10.8897,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,6.7646,-0.5593,-8.1941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,6.7514,-0.5725,-8.1941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,6.7514,-0.5725,-8.1941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,6.7558,-0.5355,-8.2267,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,8.3798,-1.0781,-6.0601,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,6.7232,-0.5398,-8.2550,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,8.0645,-0.4529,-7.0006,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,6.4856,-0.5739,-8.4585,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,6.4714,-0.5843,-8.4624,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,6.4766,-0.5742,-8.4672,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,6.4766,-0.5742,-8.4672,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,6.4742,-0.6090,-8.4348,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,6.4301,-0.6531,-8.4348,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,8.1960,-0.3309,-6.9911,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,7.1602,-0.3175,-8.0403,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,3.9204,-0.8871,-10.7105,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,8.0128,-1.2028,-6.3024,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,1.9024,-0.9604,-12.6552,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,9.0859,0.0980,-6.5301,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,9.0943,-0.6682,-5.7555,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,4.0639,-0.9216,-10.5325,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,4.0639,-0.9216,-10.5325,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_NPPD,NPPD_LA,7.2366,-0.4847,-7.7966,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,8.0645,-0.4529,-7.0006,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,8.0645,-0.4529,-7.0006,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,6.3510,-0.5715,-8.5955,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,5.0534,-0.8451,-9.6195,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NSB,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NSP,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,NSSO,PJM,18.2071,0.1998,2.4892,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,NYIS,PJM,18.2071,0.1998,2.4892,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-11.4216,-1.7392,-25.2004,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-16.7422,-1.1437,-31.1165,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,0.7635,-0.9014,-13.8531,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,0.7635,-0.9014,-13.8531,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-10.7838,-1.9456,-24.3562,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-23.1091,-1.2369,-37.3902,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-85.0387,-0.7606,-99.7961,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-38.7352,-1.0995,-53.1537,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-20.0000,-1.1351,-34.3829,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-16.5623,-1.1556,-30.9247,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,6.4876,-0.4173,-8.6131,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-20.0000,-1.1351,-34.3829,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-10.9823,-1.9018,-24.5985,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-10.1075,-0.8674,-24.7581,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-11.6714,-1.7020,-25.4874,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,39.5934,-0.1131,24.1885,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-16.5623,-1.1556,-30.9247,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-15.1547,-1.0847,-29.5880,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-5.7657,-1.0435,-20.2402,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-10.9163,-0.9196,-25.5147,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-39.9700,-0.1124,-55.3756,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-10.1075,-0.8674,-24.7581,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-10.1075,-0.8674,-24.7581,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-16.5623,-1.1556,-30.9247,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-8.7647,-0.8690,-23.4137,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.NUEN.LAM1,LAM1_DDR,36.0997,1.0460,19.5357,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.NUEN.MDT2,MDT2_DDR,6.4876,-0.4173,-8.6131,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.NUEN.MDT3,MDT3_DDR,6.4876,-0.4173,-8.6131,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-9.0442,-0.8729,-23.6893,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,3.5826,-0.4716,-11.4638,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,3.5826,-0.4716,-11.4638,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,3.5826,-0.4716,-11.4638,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,10.5905,-0.3992,-4.5283,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,10.5905,-0.3992,-4.5283,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,3.5826,-0.4716,-11.4638,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,3.5826,-0.4716,-11.4638,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-16.5623,-1.1556,-30.9247,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,26.3938,0.6207,10.2551,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-10.9823,-1.9018,-24.5985,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-28.7498,-0.3321,-43.9356,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-15.1547,-1.0847,-29.5880,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,32.4618,0.6672,16.2766,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-16.9417,-0.8979,-31.5618,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-16.9417,-0.8979,-31.5618,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-16.9417,-0.8979,-31.5618,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-16.9417,-0.8979,-31.5618,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-19.0891,-1.5837,-33.0233,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-20.6644,-1.0945,-35.0879,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-16.7422,-1.1437,-31.1165,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-25.3485,-1.0700,-39.7965,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-25.3485,-1.0700,-39.7965,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-23.8133,-0.1572,-39.1741,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-13.0965,-1.0077,-27.6068,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-13.0965,-1.0077,-27.6068,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-13.0965,-1.0077,-27.6068,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0033,FOSTER_DDR,17.9366,-0.3642,2.7828,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,38.3224,0.5479,22.2565,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0035,TARBY_DDR,36.0224,0.8396,19.6648,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,38.3224,0.5479,22.2565,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,38.0435,0.3856,22.1399,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,38.0435,0.3856,22.1399,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-36.2122,-0.1928,-51.5374,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0040,TROSPER_DDR,22.0579,-0.3394,6.8793,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,22.0774,-0.3390,6.8984,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,33.8589,0.7977,17.5432,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0115,V115_DDR,7.6966,-0.4089,-7.4125,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0116,V116_DDR,75.0100,-0.0506,59.5426,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0118,V118_DDR,20.9244,-0.0181,5.4245,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0125,V125_DDR,34.7180,0.9344,18.2656,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0126,V126_DDR,37.3598,0.4637,21.3781,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0129,V129_DDR,3.2102,-0.7810,-11.5268,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,52.5655,-0.4306,37.4781,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0134,V134_DDR,37.9045,0.5794,21.8071,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0138,V138_DDR,36.9064,0.3917,20.9967,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,44.6737,-0.3516,29.5073,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0143,V143_DDR,37.4184,0.3015,21.5989,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0149,V149_DDR,-7.7857,-0.8055,-22.4982,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0150,V150_DDR,-7.7701,-0.8581,-22.4300,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0155,V155_DDR,36.4626,0.3143,20.6304,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0156,V156_DDR,52.5655,-0.4306,37.4781,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0166,V166_DDR,37.4665,0.8662,21.0823,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,43.7378,-0.3577,28.5775,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-7.7701,-0.8581,-22.4300,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0170,V170_DDR,-9.1908,-0.8715,-23.8373,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-18.8078,-0.7802,-33.5456,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0176,V176_DDR,-7.7701,-0.8581,-22.4300,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0177,V177_DDR,-14.9668,-1.5616,-28.9232,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,35.3208,-0.3557,20.1585,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-6.0000,-0.8845,-20.6335,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0195,V195_DDR,142.5500,0.9512,126.0808,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0197,V197_DDR,39.3166,0.5408,23.2578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0198,V198_DDR,37.4665,0.8662,21.0823,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0208,V208_DDR,142.6215,0.9711,126.1324,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0209,V209_DDR,142.6215,0.9711,126.1324,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,38.9434,0.3930,23.0324,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0216,V216_DDR,22.0818,-0.3400,6.9038,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0219,V219_DDR,36.4626,0.3143,20.6304,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0220,V220_DDR,-7.7701,-0.8581,-22.4300,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0224,V224_DDR,6.8201,-0.4315,-8.2664,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0225,V225_DDR,6.8209,-0.4307,-8.2664,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0226,V226_DDR,6.8201,-0.4315,-8.2664,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0227,V227_DDR,6.8201,-0.4315,-8.2664,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0229,V229_DDR,-31.4497,-0.1206,-46.8471,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0231,V231_DDR,23.9307,0.0845,8.3282,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0238,V238_DDR,-15.4092,-1.2005,-29.7267,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.VOLT.0242,V242_DDR,36.6640,0.3516,20.7944,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-17.5535,-2.2687,-30.8028,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-10.1075,-0.8674,-24.7581,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-16.8996,-1.1143,-31.3033,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-11.6586,-1.6892,-25.4874,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-17.5535,-2.2687,-30.8028,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-10.3244,-1.9527,-23.8897,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-43.5714,-1.0611,-58.0283,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEHL7,OKGEHL7_H,33.4621,-0.3366,18.2807,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEHL8,OKGEHSL1UN8_RA,33.4621,-0.3366,18.2807,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEHL910,OKGEHSL1PLT2,33.4621,-0.3366,18.2807,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-11.0788,-1.7994,-24.7974,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEMCC,OKGEMCCLAIPLT1,3.9914,-0.5936,-10.9330,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,34.1328,0.2309,18.3839,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,34.1328,0.2309,18.3839,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,34.1328,0.2309,18.3839,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,25.1602,-0.5772,10.2194,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,25.1602,-0.5772,10.2194,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,25.1602,-0.5772,10.2194,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,25.1602,-0.5772,10.2194,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGESM1,OKGESEMINOLEUN1_RA,18.7860,-0.2624,3.5304,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGESM2,OKGESEMINOLEUN2_RA,15.3065,-0.2982,0.0867,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGESM3,OKGESEMINOLEUN3_RA,15.3065,-0.2982,0.0867,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGESO1,OKGESONR1UN1_RA,-53.3294,-1.0153,-67.8321,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGESO2,OKGESONR1UN2_RA,-25.3485,-1.0700,-39.7965,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-11.1865,-1.9071,-24.7974,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-13.0377,-2.1223,-26.4334,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGETINK5A,OKGETINK5UN1_RA,19.5874,-0.3771,4.4465,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGETINK5B,OKGETINK5UN2_RA,19.5874,-0.3771,4.4465,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-12.4046,-1.4699,-26.4527,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-16.7422,-1.1437,-31.1165,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,33.2225,1.0100,16.6945,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-10.1075,-0.8674,-24.7581,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE_OKGE,OKGE_LA,23.0813,-0.1862,7.7496,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-28.7498,-0.3321,-43.9356,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-12.4453,-1.5106,-26.4527,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMLP,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,43.3705,0.1367,27.7158,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,33.5075,0.9437,17.0458,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_GENHUB,OMPA_GENHUB_H,4.3312,-0.4538,-10.7331,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-84.9015,-0.6234,-99.7961,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-7.9438,-1.0007,-22.4611,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-20.0000,-1.1351,-34.3829,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-16.1305,-2.1827,-29.4658,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-2.8337,-1.5289,-16.8228,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,159.5306,0.1013,143.9113,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-84.9462,-0.6681,-99.7961,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-84.9462,-0.6681,-99.7961,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_SPP,OMPA_SPP_LA,3.4567,-0.6322,-11.4291,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-17.5535,-2.2687,-30.8028,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,38.9431,0.1243,23.3008,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,38.9431,0.1243,23.3008,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,38.9431,0.1243,23.3008,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,38.9431,0.1243,23.3008,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,ONT,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,9.5558,-0.3010,-5.6612,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,9.5558,-0.3010,-5.6612,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,9.5558,-0.3010,-5.6612,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,9.5558,-0.3010,-5.6612,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,9.5558,-0.3010,-5.6612,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,9.5558,-0.3010,-5.6612,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,9.5558,-0.3010,-5.6612,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,9.5558,-0.3010,-5.6612,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,9.5558,-0.3010,-5.6612,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,9.5861,-0.2775,-5.6544,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,9.5828,-0.2964,-5.6388,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,9.4941,-0.1959,-5.8280,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,9.4814,-0.2555,-5.7811,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,9.4814,-0.2555,-5.7811,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD_GLDN,OPPD_GLDN_LA,9.4896,-0.2958,-5.7326,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,9.5784,-0.2879,-5.6517,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,8.3798,-1.0781,-6.0601,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,8.4646,-0.4942,-6.5592,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,9.5829,-0.2956,-5.6394,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD_OPPD,OPPD_LA,9.5538,-0.2498,-5.7144,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,9.5195,-0.2381,-5.7604,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,9.5066,-0.2431,-5.7683,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OTP,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,OVEC,OVEC,19.0560,0.2511,3.2869,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PARAGOULD,PARAGOULD_LA,24.2975,0.5209,8.2587,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,40.7590,0.0912,25.1498,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,40.7590,0.0912,25.1498,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,40.7590,0.0912,25.1498,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,40.4821,0.1518,24.8123,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,40.4821,0.1518,24.8123,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,40.4821,0.1518,24.8123,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PIGGOTT,PIGGOTT_LA,23.5773,0.4853,7.5740,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PJM,PJM,18.2071,0.1998,2.4892,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,PLUM,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,POPLARBLUFF,POPLARBLUFF_LA,22.9687,0.4306,7.0201,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,11.6160,-0.1062,-3.7958,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,11.6160,-0.1062,-3.7958,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,11.6924,-0.1010,-3.7246,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,11.6924,-0.1010,-3.7246,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,12.8242,0.9634,-3.6572,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,12.8242,0.9634,-3.6572,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,11.8884,0.1261,-3.7557,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,10.8664,-0.5399,-4.1117,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-5.5290,-0.7395,-20.3075,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,83.7589,0.1480,68.0929,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,8.4313,0.0633,-7.1500,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,3.0234,-0.0495,-12.4451,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,46.4872,0.4792,30.4900,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,37.3493,0.5513,21.2800,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,11.9396,-0.2707,-3.3078,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,12.3091,0.1738,-3.3827,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,11.0583,-0.4940,-3.9656,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,22.0000,1.4505,5.0315,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,12.6065,0.2604,-3.1719,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,11.8272,-0.0834,-3.6073,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,PUPP,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,RCEAST,RCEAST,8.5278,-0.9807,-6.0095,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SALINA_1,GRDASALINA1UN1_RA,41.1326,0.2193,25.3953,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SALINA_2,GRDASALINA1UN2_RA,41.1326,0.2193,25.3953,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SALINA_3,GRDASALINA1UN3_RA,41.1326,0.2193,25.3953,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SALINA_4,GRDASALINA1UN4_RA,41.1326,0.2193,25.3953,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SALINA_5,GRDASALINA1UN5_RA,41.1326,0.2193,25.3953,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SALINA_6,GRDASALINA1UN6_RA,41.1326,0.2193,25.3953,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SARPY_1,OPPDSARPYUN1_RA,9.5320,-0.2841,-5.7019,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SARPY_2,OPPDSARPYUN2_RA,9.5507,-0.2510,-5.7163,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SARPY_3,OPPDSARPYUN3_RA,9.5174,-0.3169,-5.6837,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SARPY_4,OPPDSARPYUN4_RA,9.5174,-0.3169,-5.6837,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SARPY_5,OPPDSARPYUN5_RA,9.5174,-0.3169,-5.6837,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SC,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SCEG,VACS,22.9236,0.4922,6.9134,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SCSE,SCSE,4.5156,-0.6939,-10.3085,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SEC,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-9.2209,-1.5415,-23.1974,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-9.2209,-1.5415,-23.1974,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-9.2209,-1.5415,-23.1974,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-6.4255,-1.1789,-20.7645,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-9.2209,-1.5415,-23.1974,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-7.4576,-1.5478,-21.4278,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-7.2080,-1.6171,-21.1089,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-7.2080,-1.6171,-21.1089,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-6.8536,-0.9138,-21.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-10.5200,-1.3752,-24.6628,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-2.1142,-0.5960,-17.0362,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-6.7675,-1.0715,-21.2140,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-2.4169,-1.2031,-16.7318,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-8.7954,-1.5562,-22.7572,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-2.4154,-1.1902,-16.7432,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-7.6560,-1.3653,-21.8087,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-7.2688,-0.9801,-21.8067,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-6.3932,-1.3160,-20.5952,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-6.3932,-1.3160,-20.5952,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-6.3932,-1.3160,-20.5952,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-6.3932,-1.3160,-20.5952,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-6.6242,-1.4014,-20.7408,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-7.4576,-1.5478,-21.4278,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI_SECI,SECI_LA,-5.9341,-1.0476,-20.4044,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-0.4183,-0.8758,-15.0605,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-0.4183,-0.8758,-15.0605,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-6.8536,-0.9138,-21.4578,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SEHA,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-12.4453,-1.5106,-26.4527,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SERU,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SETH,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SGE,SGE,5.3242,-0.6792,-9.5146,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SMEP,MISO,18.6205,0.2606,2.8419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SOCO,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPA,SPA,31.0027,0.5684,14.9163,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPC,SPC,12.4808,0.5238,-3.5610,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPPNORTH_HUB,SPPNORTH_H,8.6217,-0.3317,-6.5647,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPPSOUTH_HUB,SPPSOUTH_H,9.3986,-0.7707,-5.3488,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,29.5314,0.4873,13.5261,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,29.5314,0.4873,13.5261,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,28.9002,0.4649,12.9173,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,28.9002,0.4649,12.9173,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_NIXA,SPRM_NIXA_LA,29.7862,0.4789,13.7893,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_SPRM,SPRM_LA,29.6305,0.5438,13.5687,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,29.7229,0.4053,13.7996,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,29.7229,0.4053,13.7996,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,29.6820,0.3644,13.7996,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,29.7229,0.4053,13.7996,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-2.8145,-0.4796,-17.8529,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-8.5485,-0.7876,-23.2789,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-10.4772,-1.4801,-24.5151,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-10.4772,-1.4801,-24.5151,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-15.0919,-1.3991,-29.2108,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,3.4914,-0.9212,-11.1054,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-8.0015,-2.7723,-20.7472,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,7.2292,-0.2655,-8.0233,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-15.8779,-0.7003,-30.6956,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,10.7789,0.4437,-5.1828,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,10.0932,0.4455,-5.8703,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,10.0932,0.4455,-5.8703,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,10.7789,0.4437,-5.1828,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-10.4300,-1.4332,-24.5148,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-8.5485,-0.7876,-23.2789,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-10.2503,-1.3666,-24.4017,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-10.6415,-1.9314,-24.2281,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-10.0576,-1.2649,-24.3106,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-9.8521,-1.0001,-24.3700,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-10.1965,-1.3457,-24.3688,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-10.4696,-1.9528,-24.0348,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-10.4696,-1.9528,-24.0348,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-10.4696,-1.9528,-24.0348,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-10.4696,-1.9528,-24.0348,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GRID.WRAB,WRAB_DDR,-10.2178,-1.1333,-24.6025,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-10.4696,-1.9528,-24.0348,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-13.3482,-0.7689,-28.0973,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-13.3482,-0.7689,-28.0973,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-13.1447,-0.7206,-27.9421,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-13.1447,-0.7206,-27.9421,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-13.1447,-0.7206,-27.9421,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-13.3482,-0.7689,-28.0973,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-10.5764,-1.4635,-24.6309,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-10.5769,-1.4635,-24.6313,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-10.5755,-1.4636,-24.6299,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-10.8483,-1.8322,-24.5341,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,10.6037,0.4067,-5.3210,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-15.7686,-0.7092,-30.5774,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-15.7686,-0.7092,-30.5774,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-15.7686,-0.7092,-30.5774,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-15.7686,-0.7092,-30.5774,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,12.5669,0.5104,-3.4615,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,10.8659,0.4180,-5.0701,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,10.8659,0.4180,-5.0701,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-12.3805,-1.4458,-26.4527,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-10.5604,-1.4490,-24.6294,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-10.5604,-1.4490,-24.6294,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-10.5888,-1.4571,-24.6497,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-10.2178,-1.1333,-24.6025,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-10.4082,-1.7057,-24.2204,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-10.4270,-1.4776,-24.4673,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-10.7838,-1.9456,-24.3562,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-10.3495,-1.2381,-24.6294,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-7.2761,-0.6445,-22.1496,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-7.2761,-0.6445,-22.1496,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-6.5824,-0.6750,-21.4254,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-15.2789,-1.1461,-29.6508,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-10.6260,-2.0139,-24.1301,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-7.6400,-2.4108,-20.7472,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-15.2617,-1.1289,-29.6508,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-10.4023,-1.4055,-24.5148,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-0.8084,-0.6338,-15.6926,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,7.6715,0.1768,-8.0233,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-0.8084,-0.6338,-15.6926,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,7.6988,0.2177,-8.0369,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-10.4274,-1.6321,-24.3133,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,10.3450,1.1197,-6.2927,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,10.3497,1.1244,-6.2927,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,10.5080,0.8502,-5.8602,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,10.9556,0.4704,-5.0328,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,8.9204,0.8326,-7.4302,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-6.7734,-1.4425,-20.8489,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-10.2908,-1.2043,-24.6045,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-5.5051,-0.6309,-20.3922,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-5.5051,-0.6309,-20.3922,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-0.8084,-0.6338,-15.6926,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-16.1595,-0.6196,-31.0579,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,20.2684,0.8978,3.8526,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-5.1233,0.1802,-20.8215,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-5.9204,-0.2956,-21.1428,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-11.1354,-0.8593,-25.7941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,10.3450,1.1197,-6.2927,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,9.7447,1.3917,-7.1650,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,9.5419,1.1889,-7.1650,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-15.1069,-0.9741,-29.6508,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-5.5092,-0.2884,-20.7388,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-10.3781,-1.7425,-24.1536,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-10.4077,-1.7715,-24.1542,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0163,V163_DDR,-10.1325,-1.2409,-24.4096,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0168,V168_DDR,-13.1166,-0.9214,-27.7131,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0180,V180_DDR,9.7447,1.3917,-7.1650,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0181,V181_DDR,-10.3922,-1.7703,-24.1399,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0182,V182_DDR,9.0495,1.0090,-7.4775,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0199,V199_DDR,15.9339,0.7776,-0.3617,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0200,V200_DDR,10.8111,0.7952,-5.5021,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.VOLT.0235,V235_DDR,-10.4082,-1.7057,-24.2204,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-8.0015,-2.7723,-20.7472,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,7.2292,-0.2655,-8.0233,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-10.1800,-1.6660,-24.0320,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-10.3918,-1.3592,-24.5506,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS_SPS,SPS_LA,3.5258,0.1847,-12.1769,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,10.4999,-0.0487,-4.9694,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SSCN_NPPD,SSCN_NPPD_LA,8.9578,-0.4227,-6.1375,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,22.2656,0.4172,6.3304,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,22.2656,0.4172,6.3304,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,TAL,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,TEC,SOUC,23.2105,0.5209,7.1716,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,8.0128,-1.2028,-6.3024,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,TVA,TVA,22.6201,0.4620,6.6402,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,UCUHUB,UCUHUB_H,5.2457,-0.2961,-9.9762,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,UCUHUB17,UCUHUB17_H,1.0816,-0.6727,-13.7637,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,UCUHUB18,UCUHUB18_H,3.7564,-0.5529,-11.2087,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,UCUHUB19,UCUHUB19_H,0.3692,-0.6469,-14.5018,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,UCUHUB20,UCUHUB20_H,0.3864,-0.6311,-14.5005,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,UCUHUB21,UCUHUB21_H,-1.1639,-0.7353,-15.9465,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,UCUHUB22,UCUHUB22_H,-0.9238,-0.7725,-15.6692,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,UCUHUB23,UCUHUB23_H,-1.1966,-0.7820,-15.9325,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,UCUHUB24,UCUHUB24_H,0.8710,-0.6790,-13.9680,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,12.5850,0.6437,-3.5767,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,12.5850,0.6437,-3.5767,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,11.5008,-0.2884,-3.7288,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,11.5008,-0.2884,-3.7288,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,11.9612,-0.3108,-3.2459,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,11.6341,-0.1907,-3.6932,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,11.6341,-0.1907,-3.6932,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,12.5850,0.6437,-3.5767,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,12.0216,-0.2933,-3.2031,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,12.4302,0.2672,-3.3549,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,11.6440,-0.1395,-3.7345,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,9.0290,-1.5019,-4.9871,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,12.4889,0.6100,-3.6390,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,12.4889,0.6100,-3.6390,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,10.3766,-1.3789,-3.7625,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,11.6039,-0.2989,-3.6152,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,11.7908,-0.3301,-3.3971,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,11.1415,-0.4368,-3.9396,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,11.7028,-0.0744,-3.7408,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,11.4771,-0.3249,-3.7160,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,11.2036,-0.5519,-3.7625,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,11.2036,-0.5519,-3.7625,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,11.6087,-0.2657,-3.6436,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,8.6507,-1.6507,-5.2165,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,12.4055,0.6114,-3.7239,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,24.3600,0.1177,8.7243,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,24.3600,0.1177,8.7243,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,24.3600,0.1177,8.7243,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,12.0144,0.1383,-3.6419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,12.0144,0.1383,-3.6419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,12.0144,0.1383,-3.6419,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,12.8107,0.8470,-3.5543,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,11.7786,-0.2823,-3.4571,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,11.7786,-0.2823,-3.4571,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,4.9121,-0.6980,-9.9079,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,11.0622,-0.1972,-4.2586,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,12.2682,0.2505,-3.5003,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,10.2175,-0.5474,-4.7531,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,8.0778,-2.0413,-5.3989,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,11.3967,-0.4007,-3.7206,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,12.5515,0.6494,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,12.5515,0.6494,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,12.5507,0.6486,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,12.5515,0.6494,-3.6159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,12.4180,0.5216,-3.6216,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,12.4180,0.5216,-3.6216,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,12.4180,0.5216,-3.6216,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,12.4180,0.5216,-3.6216,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,12.4180,0.5216,-3.6216,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,12.4180,0.5216,-3.6216,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,12.4180,0.5216,-3.6216,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,9.4065,-1.1590,-4.9525,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,12.2185,-0.0309,-3.2686,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,10.7204,-0.2008,-4.5967,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,10.7204,-0.2008,-4.5967,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,9.9769,-0.5707,-4.9704,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,9.9769,-0.5707,-4.9704,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,11.9613,-0.0996,-3.4571,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,12.0451,-0.0588,-3.4141,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,11.2183,-0.5300,-3.7697,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,8.9380,-1.3644,-5.2156,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,12.1916,-0.1290,-3.1974,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,11.9612,-0.3108,-3.2459,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,11.9612,-0.3108,-3.2459,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,11.1415,-0.4368,-3.9396,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,8.4717,-1.0320,-6.0143,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,10.7766,-0.5848,-4.1566,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,8.8071,-1.4944,-5.2165,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,11.3033,-0.4748,-3.7399,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.FSE,WAUE.FSE_H,8.5192,-0.7370,-6.2618,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,11.7997,-0.0262,-3.6921,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,11.7551,-0.0616,-3.7013,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,8.7322,-1.5000,-5.2858,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,8.8306,-1.4318,-5.2556,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,11.9145,-0.2866,-3.3169,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,11.8821,-0.3513,-3.2846,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-12.4800,-1.2102,-26.7878,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,9.0290,-1.5019,-4.9871,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,0.0900,-0.8057,-14.6223,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,10.8168,-0.4016,-4.2996,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,10.8170,-0.4014,-4.2996,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,10.8171,-0.4013,-4.2996,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,11.4393,-0.2862,-3.7925,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,8.4717,-1.0320,-6.0143,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,12.1212,-0.0014,-3.3954,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,10.9784,-0.5275,-4.0121,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,12.3486,0.5545,-3.7239,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,11.6265,0.1785,-4.0700,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,11.7506,-0.0693,-3.6981,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,12.8744,-0.1384,-2.5052,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,11.3070,-0.3300,-3.8810,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,11.1749,-0.5417,-3.8014,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,10.2175,-0.5474,-4.7531,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,13.8297,0.4609,-2.1492,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,11.1249,-0.4525,-3.9406,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,13.7274,0.3932,-2.1838,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,12.0061,0.0177,-3.5296,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,9.6601,-0.3741,-5.4838,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NTWK,WAUE.NTWK_H,11.2739,-0.2444,-3.9997,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,12.4977,0.8020,-3.8222,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,12.4977,0.8020,-3.8222,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,8.9702,-1.5938,-4.9540,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,9.1615,-1.4771,-4.8794,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,11.8553,-0.2069,-3.4558,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,8.9702,-1.5938,-4.9540,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,12.6022,0.0124,-2.9282,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,10.2623,-0.7947,-4.4610,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,10.2175,-0.5474,-4.7531,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,10.9180,-0.4136,-4.1864,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,8.6065,-2.4505,-4.4610,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,7.5030,-1.9080,-6.1070,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,7.8573,-1.9147,-5.7460,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,11.4785,-0.3194,-3.7201,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,7.3634,-1.3825,-6.7721,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,12.1216,-0.0054,-3.3910,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,9.5731,-1.1095,-4.8354,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,8.9380,-1.3644,-5.2156,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.VOLT.0152,V152_DDR,13.0389,1.0384,-3.5175,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE.VOLT.0172,V172_DDR,12.4871,0.5877,-3.6186,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_BEPM,WAUE_BEPM_LA,12.5063,0.2206,-3.2322,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,12.1690,-0.0130,-3.3360,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,11.6329,0.1871,-4.0722,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_EWA,WAUE_EWA_LA,8.5909,-0.9394,-5.9877,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,10.5346,-0.6468,-4.3366,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_HMMU,WAUE_HMMU_LA,10.5969,-0.0303,-4.8908,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,13.0424,-0.1059,-2.3697,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_MECB,WAUE_MECB_LA,11.3663,0.2163,-4.3681,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_MMPA,WAUE_MMPA_LA,12.8598,0.3423,-3.0005,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_MRES,WAUE_MRES_LA,11.4832,-0.1916,-3.8432,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,12.8286,0.7513,-3.4406,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,11.7997,-0.0262,-3.6921,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,10.4345,-0.5677,-4.5158,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_OTP,WAUE_OTP_LA,13.3378,0.7089,-2.8890,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_OTPW,WAUE_OTPW_LA,15.5563,0.6287,-0.5904,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM,WAUE_UGPM_LA,11.7993,0.0119,-3.7306,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,12.1002,0.0957,-3.5135,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,11.3649,-0.2751,-3.8780,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,9.0004,-0.5596,-5.9580,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,8.5909,-0.9394,-5.9877,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,10.5969,-0.0303,-4.8908,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,10.5506,-0.6125,-4.3549,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,11.7997,-0.0262,-3.6921,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,12.8598,0.3423,-3.0005,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,11.6684,-0.1299,-3.7198,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,10.0788,-0.7039,-4.7354,15.5181\n03/19/2025 11:00:00,03/19/2025 16:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,13.0461,0.7214,-3.1933,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-17.2861,-2.0641,-30.7400,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-13.9941,-1.3853,-28.1268,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,7.9689,-1.1653,-6.3838,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,84.3654,0.4322,68.4152,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,84.3654,0.4322,68.4152,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-5.9462,-2.0961,-19.3681,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,77.8068,0.5260,61.7628,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,70.0921,0.5059,54.0682,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,29.2100,-0.8952,14.5872,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,29.2100,-0.8952,14.5872,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,29.2100,-0.8952,14.5872,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,29.2100,-0.8952,14.5872,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,29.1729,-0.9322,14.5872,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,29.2100,-0.8952,14.5872,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,29.2100,-0.8952,14.5872,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,29.2100,-0.8952,14.5872,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,18.9625,-0.8391,4.2836,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-10.7838,-1.9456,-24.3562,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-25.3692,-1.3895,-39.4977,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-16.3284,-2.2522,-29.5942,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-7.7517,-2.5225,-20.7472,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_ENMC,WFEC_ENMC_LA,7.1332,0.3636,-8.7484,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-16.5623,-1.1556,-30.9247,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,34.9817,0.3562,19.1075,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,12.0320,0.4511,-3.9371,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-17.2861,-2.0641,-30.7400,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-17.2861,-2.0641,-30.7400,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-17.2861,-2.0641,-30.7400,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_OKGE,WFEC_OKGE_LA,9.7599,0.0475,-5.8056,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,62.1580,0.5259,46.1141,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-11.5727,-2.1748,-24.9159,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-5.5691,-2.2824,-18.8047,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_WFEC,WFEC_LA,25.4704,-0.3522,10.3046,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,12.0320,0.4511,-3.9371,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-0.3718,-0.8183,-15.0715,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-5.2841,-1.4061,-19.3960,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,1.9418,-0.5620,-13.0142,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,1.9418,-0.5620,-13.0142,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,1.9418,-0.5620,-13.0142,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,1.9418,-0.5620,-13.0142,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,1.9418,-0.5620,-13.0142,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,1.9418,-0.5620,-13.0142,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,1.9418,-0.5620,-13.0142,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,7.3954,0.4722,-8.5948,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,0.4887,-0.7811,-14.2482,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-12.6838,-1.1077,-27.0941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-12.6838,-1.1077,-27.0941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-12.6838,-1.1077,-27.0941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-10.4048,-1.3693,-24.5535,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-10.4048,-1.3693,-24.5535,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-7.8396,-1.0049,-22.3527,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-7.8396,-1.0049,-22.3527,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-7.8396,-1.0049,-22.3527,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,0.4887,-0.7811,-14.2482,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,7.4651,-0.0184,-8.0345,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-3.5814,-0.7641,-18.3353,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-3.5814,-0.7641,-18.3353,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-3.5814,-0.7641,-18.3353,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-3.5814,-0.7641,-18.3353,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,7.4651,-0.0184,-8.0345,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-8.1352,-1.5790,-22.0742,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-21.1507,-0.6776,-35.9911,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.JEC.1,WRJEFFUN10_RA,3.2847,-0.5335,-11.6998,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.JEC.2,WRJEFFUN11_RA,3.3376,-0.5365,-11.6439,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.JEC.3,WRJEFFUN12_RA,3.2671,-0.6070,-11.6439,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-17.8872,-1.1267,-32.2784,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-10.6100,-1.1426,-24.9854,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-10.6100,-1.1426,-24.9854,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.LEC.4,WRLECUN26_RA,6.9449,-0.0853,-8.4878,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.LEC.5,WRLECUN27_RA,6.4958,-0.0547,-8.9675,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-2.1672,-0.6367,-17.0485,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-2.1672,-0.6367,-17.0485,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-2.1672,-0.6367,-17.0485,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-2.1180,-0.6070,-17.0290,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-0.4183,-0.8758,-15.0605,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-0.4183,-0.8758,-15.0605,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-2.1958,-1.0748,-16.6390,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,0.0056,-0.7314,-14.7810,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,0.0056,-0.7314,-14.7810,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-2.6059,-1.0392,-17.0846,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-0.4183,-0.8758,-15.0605,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,5.1232,-0.7691,-9.6257,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-0.1201,-0.8535,-14.7846,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-10.6138,-1.1464,-24.9854,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,71.4565,0.5076,55.4309,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-3.0838,-1.5058,-17.0960,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,1.9418,-0.5620,-13.0142,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-0.1721,-1.1522,-14.5379,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,7.4651,-0.0184,-8.0345,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,0.4887,-0.7811,-14.2482,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-9.4818,-0.8491,-24.1507,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.THAYERLD,WR.THAYERLD_LA,24.3660,0.4575,8.3905,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-10.3356,-0.8487,-25.0049,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0106,V106_DDR,-9.3399,-0.8060,-24.0518,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0139,WR.VOLT.0139_H,9.1566,0.0826,-6.4440,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-0.5323,-0.6231,-15.4272,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0146,WR.VOLT.0146_H,7.2539,0.0368,-8.3009,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0147,WR.VOLT.0147_H,7.2539,0.0368,-8.3009,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0148,WR.VOLT.0148_H,7.5455,0.0281,-8.0006,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-8.7168,-0.6952,-23.5395,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0157,V157_DDR,7.1715,0.0194,-8.3659,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0158,V158_DDR,7.2539,0.0368,-8.3009,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0159,WR.VOLT.0159_H,7.2539,0.0368,-8.3009,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-9.5416,-0.9119,-24.1477,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0173,V173_DDR,-2.2615,-0.7039,-17.0756,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0174,V174_DDR,-9.2373,-0.8322,-23.9231,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0184,V184_DDR,-8.8993,-0.9244,-23.4929,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-9.6075,-0.8405,-24.2850,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0186,V186_DDR,-9.6058,-0.8852,-24.2386,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-9.0983,-0.8904,-23.7259,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-10.1522,-0.8150,-24.8552,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-2.8831,-0.5436,-17.8575,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0190,WR.VOLT.0190_H,0.9883,-0.4777,-14.0520,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0191,WR.VOLT.0191_H,1.6826,-0.5173,-13.3181,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0192,WR.VOLT.0192_H,1.6826,-0.5173,-13.3181,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0196,WR.VOLT.0196_H,0.9883,-0.4777,-14.0520,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0245,V245_DDR,-9.6198,-0.8410,-24.2968,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.VOLT.0248,V248_DDR,-9.3399,-0.8060,-24.0518,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-13.6408,-1.0485,-28.1103,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,5.5079,-0.1637,-9.8464,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.WOLF,WRWOLFUN15_RA,-0.4460,-1.2328,-14.7312,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-8.1352,-1.5790,-22.0742,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,7.3180,0.3948,-8.5948,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-12.6838,-1.1077,-27.0941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-12.6838,-1.1077,-27.0941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-12.6838,-1.1077,-27.0941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-12.6838,-1.1077,-27.0941,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-10.0702,-0.6907,-24.8975,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-0.4617,-0.6252,-15.3545,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-10.5129,-0.8567,-25.1742,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-10.5129,-0.8567,-25.1742,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-10.5129,-0.8567,-25.1742,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-10.5129,-0.8567,-25.1742,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,1.2637,-0.3961,-13.8582,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,1.2637,-0.3961,-13.8582,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,1.2637,-0.3961,-13.8582,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,1.2637,-0.3961,-13.8582,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,1.2637,-0.3961,-13.8582,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,1.2637,-0.3961,-13.8582,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-24.8252,-0.7999,-39.5433,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-24.8252,-0.7999,-39.5433,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-27.4192,-0.8444,-42.0928,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-27.4192,-0.8444,-42.0928,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_MIDW,WR_MIDW_LA,-1.9997,-0.8591,-16.6586,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,15.5979,0.3647,-0.2848,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,12.9168,0.1635,-2.7647,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-3.5423,-0.8206,-18.2397,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_SEG,WR_SEG_LA,13.4165,0.2045,-2.3060,15.5180\n03/19/2025 11:00:00,03/19/2025 16:00:00,WR_WR,WR_LA,-0.7298,-0.5180,-15.7297,15.5179\n03/19/2025 11:00:00,03/19/2025 16:00:00,YAD,VACS,22.9236,0.4922,6.9134,15.5180\n03/19/2025 12:00:00,03/19/2025 17:00:00,AEC,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,AECC_CSWS,CSWS_AECC_LA,32.3758,0.6034,18.8676,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,35.4440,0.4808,22.0585,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,31.7612,0.7665,18.0899,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,35.4246,0.3258,22.1941,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,27.2391,0.4734,13.8610,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,32.3353,0.3357,19.0949,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,27.2878,0.3216,14.0615,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,AECI,AECI,23.9336,0.2317,10.7972,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,AEPM_CSWS,CSWS_LA,31.8515,0.5334,18.4133,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,ALTW,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,AMRN,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-13.8369,-0.8021,-25.9395,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BBA,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BCA,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BEPM.ER01.DDR,ER01_DDR,5.6256,-1.4824,-5.7967,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BEPM_ER01,BEPM_ER01_LA,5.6256,-1.4824,-5.7967,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,5.5569,-0.3637,-6.9841,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,1.9681,-0.2937,-10.6429,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BEPM_UM01,BEPM_UM01_LA,10.3293,0.5355,-3.1109,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BLKW,BLKW,-9.4918,-0.6245,-21.7720,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-25.0000,-1.1535,-36.7512,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-25.0000,-1.1535,-36.7512,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,18.0643,-1.0458,6.2054,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-24.9797,-1.1332,-36.7512,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BRAZ,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BUBA,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-8.9371,-1.1640,-20.6778,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-11.7356,-0.7475,-23.8928,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-11.7356,-0.7475,-23.8928,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-11.7356,-0.7475,-23.8928,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-11.7356,-0.7475,-23.8928,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-11.7356,-0.7475,-23.8928,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-8.3988,-0.5683,-20.7353,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,6.6081,-0.2428,-6.0538,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,6.6081,-0.2428,-6.0538,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CLEC,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,34.6400,0.3160,21.4193,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,COWP,COWP_LA,20.1033,0.3683,6.8303,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,20.1033,0.3683,6.8303,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,20.1033,0.3683,6.8303,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CPLE,VACS,25.6894,0.4365,12.3481,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CPLW,VACS,25.6894,0.4365,12.3481,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,24.5920,0.5123,11.1750,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,24.5920,0.5123,11.1750,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,24.5920,0.5123,11.1750,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,24.5920,0.5123,11.1750,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CRTH_SPA,WRCRTH_SPA_LA,33.5455,0.0171,20.6237,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,27.8063,1.3125,13.5891,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,2.1667,-0.6377,-10.1004,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,27.2878,0.3216,14.0615,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,35.4246,0.3258,22.1941,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,27.7983,1.3029,13.5906,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,27.4550,0.8937,13.6565,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,27.6936,1.1718,13.6171,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,27.6936,1.1718,13.6171,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,35.2310,0.4297,21.8966,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,35.2310,0.4297,21.8966,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,35.2311,0.4298,21.8966,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,35.2311,0.4298,21.8966,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,27.2878,0.3216,14.0615,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,30.1236,0.9440,16.2748,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,55.7124,-0.0243,42.8319,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,55.5930,-0.1437,42.8319,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,39.1730,0.1402,26.1280,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,37.4136,0.2100,24.2988,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,37.4136,0.2100,24.2988,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,37.4154,0.2100,24.3007,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,37.4154,0.2100,24.3007,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-16.8402,-0.7861,-28.9589,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,9.5898,-0.4292,-2.8858,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,39.9640,0.2791,26.7802,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-15.6269,-0.9700,-27.5617,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-15.5847,-0.9278,-27.5617,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-11.9865,-0.4939,-24.3974,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.GRID.CDL1,CDL1_DDR,37.9573,0.3227,24.7298,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,0.7605,-0.6409,-11.5033,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,2.7621,-0.9231,-9.2195,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,37.9573,0.3227,24.7298,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.NUEN.CSI1,CSI1_DDR,38.6622,0.3472,25.4102,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.NUEN.CSI2,CSI2_DDR,38.6669,0.3520,25.4102,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,34.6511,0.3271,21.4193,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.NUEN.GAZA,GAZA_DDR,37.9573,0.3227,24.7298,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,89.9001,0.6152,76.3802,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.NUEN.T201,NT201_DDR,37.7941,0.2543,24.6351,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-3.8772,-0.8524,-15.9295,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-3.8772,-0.8524,-15.9295,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,27.2878,0.3216,14.0615,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,28.0172,1.3447,13.7678,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-11.9865,-0.4939,-24.3974,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-11.9865,-0.4939,-24.3974,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-11.5532,-0.7380,-23.7199,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-15.5847,-0.9278,-27.5617,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,27.2492,0.7446,13.5998,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,35.2767,0.1168,22.2552,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,35.0849,-0.0750,22.2552,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,35.0785,-0.0814,22.2552,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,17.2935,0.0732,4.3155,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,17.2935,0.0732,4.3155,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,27.4348,0.8535,13.6765,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,39.1254,0.2368,25.9839,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,27.4656,0.8878,13.6730,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,28.3335,1.6694,13.7593,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,31.0165,0.4497,17.6621,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,38.6669,0.3520,25.4102,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0057,OKMU_DDR,40.1184,0.3570,26.8567,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0060,LEHIGH_DDR,89.9001,0.6152,76.3802,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0086,WARRENM_DDR,37.8159,0.2685,24.6427,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,28.0082,1.2575,13.8459,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,47.6190,0.2605,34.4537,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0121,V121_DDR,27.4348,0.8535,13.6765,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0122,V122_DDR,46.2224,0.2425,33.0752,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0124,V124_DDR,64.1392,0.1757,51.0587,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0135,V135_DDR,38.7774,0.2942,25.5785,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0144,V144_DDR,10.1182,-0.3867,-2.3998,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0145,V145_DDR,10.3391,-0.4580,-2.1076,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,27.4644,0.8783,13.6814,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,27.5456,0.5052,14.1356,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0175,V175_DDR,34.6511,0.3271,21.4193,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,27.5456,0.5052,14.1356,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,27.6675,0.5994,14.1634,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,38.7774,0.2942,25.5785,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,38.8865,0.2705,25.7113,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,38.3406,0.2376,25.1982,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,51.8627,0.0979,38.8601,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,37.5542,0.1988,24.4507,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,38.8865,0.2705,25.7113,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0211,V211_DDR,27.6314,1.0688,13.6579,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,48.3129,0.2672,35.1410,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0213,V213_DDR,38.4863,0.2695,25.3120,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0215,V215_DDR,47.1740,0.2542,34.0151,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0217,V217_DDR,48.3592,0.2515,35.2029,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0218,V218_DDR,51.4316,0.1083,38.4186,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0228,V228_DDR,39.6291,0.2096,26.5148,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0232,V232_DDR,38.3828,0.2999,25.1782,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0233,V233_DDR,39.0657,0.2859,25.8750,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0240,V240_DDR,44.5418,0.1958,31.4412,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0244,V244_DDR,38.8865,0.2705,25.7113,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0246,MDT1_DDR,89.9001,0.6152,76.3802,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0249,V249_DDR,38.4468,0.2846,25.2575,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0250,V250_DDR,0.9928,-0.6192,-11.2927,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0251,V251_DDR,37.8668,0.2386,24.7234,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.VOLT.0252,V252_DDR,51.8627,0.0979,38.8601,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-19.6272,-0.7553,-31.7766,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,14.8851,-0.8704,2.8507,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-12.6111,-1.4895,-24.0264,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,27.3429,0.7719,13.6663,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-16.2455,-2.2780,-26.8722,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,5.9010,-0.4820,-6.5217,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,5.9010,-0.4820,-6.5217,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,5.9010,-0.4820,-6.5217,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,5.9010,-0.4820,-6.5217,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,5.9010,-0.4820,-6.5217,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,27.2878,0.3216,14.0615,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,27.5500,1.1586,13.4867,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,38.3611,0.2781,25.1782,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,37.5699,0.2023,24.4629,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,42.3207,0.3932,29.0228,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,42.3207,0.3932,29.0228,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWWELSH1,CSWSWELSHUN1_RA,27.2897,0.6248,13.7602,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWWELSH3,CSWSWELSHUN3_RA,27.2897,0.6248,13.7602,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWWILKES1,CSWSWILKESUN1_RA,27.6053,0.8787,13.8219,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWWILKES2,CSWSWILKESUN2_RA,27.6053,0.8787,13.8219,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,CSWWILKES3,CSWSWILKESUN3_RA,27.4688,0.8337,13.7304,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-15.5739,-0.9170,-27.5617,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,DENL,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,DERS,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,DOE,DOE,21.3345,0.3358,8.0940,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,14.4147,0.0149,1.4951,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,DPC,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,DUK,VACS,25.6894,0.4365,12.3481,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDDY,EDDY,-1.8855,0.1508,-14.9410,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,31.7265,-0.0450,18.8667,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-3.1632,-0.1905,-15.8775,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,36.3120,-0.1985,23.6057,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE.SLCC,EDESTL4391_PLT,33.4220,-0.1231,20.6404,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,33.3331,-0.0774,20.5058,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,19.2063,-0.2687,6.5704,12.9046\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_EC_01,EDELAR3821UN1_RA,31.7265,-0.0450,18.8667,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_EC_02,EDELAR3821UN2_RA,31.7265,-0.0450,18.8667,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_EC_03,EDELAR3821UN3_RA,31.7265,-0.0450,18.8667,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_EC_04,EDELAR3821UN4_RA,31.7265,-0.0450,18.8667,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_EDE,EDE_LA,31.5030,0.2518,18.3465,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_ERW,EDEERWFUNG1_RA,-9.1201,-0.6203,-21.4046,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-6.5854,-0.6894,-18.8007,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,27.8248,0.5903,14.3298,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,27.8248,0.5903,14.3298,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,27.8248,0.5903,14.3298,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,27.8248,0.5903,14.3298,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,2.9800,0.4520,-10.3767,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_RIV_10,EDERIV1671UN10_RA,33.4416,-0.1667,20.7036,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_RIV_11,EDERIV1671UN11_RA,33.4416,-0.1667,20.7036,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_RIV_12,EDERIV453UN12_PLT,33.0804,-0.5279,20.7036,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_SL_01,EDESTL4391UN1_RA,33.1877,-0.3574,20.6404,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EDE_SWMP,EDE_SWMP_LA,30.5045,0.3736,17.2261,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,EEI,EEI,21.1880,0.3344,7.9489,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EES,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-7.9483,-0.6525,-20.2005,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,ERCOTE,ERCOTE,27.2897,0.6248,13.7602,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,ERCOTN,ERCOTN,-3.8220,-0.7972,-15.9295,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,0.4776,-0.4538,-11.9733,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,FMPP,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,FPC,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,FPL,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,FREM_50T,OPPDFREM_GUN1_RA,6.7461,-0.2204,-5.9382,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,FREM_6,OPPDFREM_AUN6_RA,6.7420,-0.2272,-5.9356,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,FREM_7,OPPDFREM_AUN7_RA,6.7420,-0.2272,-5.9356,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,FREM_8,OPPDFREM_AUN8_RA,6.6619,-0.3072,-5.9356,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,FREM_LOAD,FREM_LOAD_LA,6.7294,-0.2397,-5.9356,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-12.2755,-0.5241,-24.6562,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,27.2492,0.7446,13.5998,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-12.4180,-1.7809,-23.5419,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-26.7881,-0.9865,-38.7063,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,34.6400,0.3160,21.4193,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,34.6400,0.3160,21.4193,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,34.6400,0.3160,21.4193,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,38.6548,0.1856,25.5644,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,38.6548,0.1856,25.5644,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,38.7964,0.1820,25.7097,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,38.7964,0.1820,25.7097,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-20.5391,-0.9020,-32.5419,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,48.7639,0.1128,35.7464,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,48.7639,0.1128,35.7464,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,48.7639,0.1128,35.7464,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.VOLT.0130,V130_DDR,39.7578,0.3221,26.5310,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA.VOLT.0237,V237_DDR,39.8501,0.2401,26.7053,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDAHUB2,GRDAHUB2_H,26.8164,-0.1119,14.0236,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDAHUB3,GRDAHUB3_H,20.7177,-0.2162,8.0293,12.9046\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA_GRDA,GRDA_LA,39.5698,0.2515,26.4135,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA_HUB,GRDA_H,33.7459,0.0208,20.8203,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRDA_HUBSA,GRDASA_H,33.6442,-0.0020,20.7415,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GRE,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-5.5743,0.1078,-18.5868,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GSEC_SPS,SPS_GSEC_LA,-10.6879,-0.7289,-22.8638,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,GSPR2014HUB,GSPR2014HUB_H,-6.9613,-0.8050,-19.0610,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GSPR2015HUB,GSPR2015HUB_H,-6.0277,-0.8036,-18.1288,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-12.2537,-1.4630,-23.6955,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,HARRISON,CSWSLEBROCKPLT1,27.2332,0.6674,13.6610,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,HAST_TNSK_HUB,HAST_TNSK_H,3.3399,-0.5476,-9.0172,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,HQST,PJM,17.9173,0.1990,4.8135,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,HST,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,19.6843,0.2859,6.4936,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,19.6843,0.2859,6.4936,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,19.9002,0.2850,6.7105,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,19.9002,0.2850,6.7105,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,19.4154,0.2849,6.2257,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,19.4154,0.2849,6.2257,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,INDN_INDN,INDN_LA,19.7127,0.2948,6.5133,12.9046\n03/19/2025 12:00:00,03/19/2025 17:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-5.5773,-0.7137,-17.7683,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,ISNE,PJM,17.9173,0.1990,4.8135,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,JEA,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,6.7201,-0.1743,-6.0104,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,6.7201,-0.1743,-6.0104,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-13.4973,-0.0148,-26.3872,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KACYCT4,KACYNEARMANUNCT4_RA,38.1200,0.2155,24.9998,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,57.5480,-0.1078,44.7511,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,38.1200,0.2155,24.9998,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,36.9718,0.2287,23.8384,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,37.2834,0.2287,24.1500,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KACY_KACY,KACY_LA,36.7144,0.2267,23.5830,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,26.3188,0.1389,13.2752,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,16.8334,0.5095,3.4192,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-9.2000,-0.6840,-21.4207,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-41.2400,-0.8805,-53.2642,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.VOLT.0222,V222_DDR,1.9978,0.0451,-10.9520,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.VOLT.0223,V223_DDR,15.4800,0.0038,2.5715,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.VOLT.0241,V241_DDR,17.1916,0.4396,3.8472,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.VOLT.0243,V243_DDR,22.4733,0.1941,9.3745,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.VOLT.0247,V247_DDR,16.5704,0.1185,3.5472,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.VOLT.0253,V253_DDR,26.1592,0.1442,13.1103,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-0.8541,-0.8999,-12.8589,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,14.1176,-0.1425,1.3553,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,14.1176,-0.1425,1.3553,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,14.1176,-0.1425,1.3553,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,14.1176,-0.1425,1.3553,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,26.2740,0.1374,13.2318,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,26.2740,0.1374,13.2318,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHUB,KCPLHUB_H,4.4089,-0.4505,-8.0454,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHUB17,KCPLHUB17_H,3.7236,-0.5100,-8.6711,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHUB18,KCPLHUB18_H,3.3986,-0.5086,-8.9975,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHUB19,KCPLHUB19_H,3.2806,-0.4810,-9.1431,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHUB20,KCPLHUB20_H,2.7491,-0.5333,-9.6223,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHUB21,KCPLHUB21_H,2.2511,-0.5262,-10.1275,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHUB22,KCPLHUB22_H,3.4424,-0.5217,-8.9405,12.9046\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHUB23,KCPLHUB23_H,3.0266,-0.5369,-9.3412,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLHUB24,KCPLHUB24_H,2.3523,-0.5605,-9.9920,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,-2.0412,0.0075,-14.9535,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,-2.0412,0.0075,-14.9535,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,10.0573,-0.3610,-2.4864,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,10.0573,-0.3610,-2.4864,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,26.3234,0.1434,13.2752,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,26.3188,0.1389,13.2752,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,26.9834,0.1792,13.8994,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,26.9834,0.1792,13.8994,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,26.9834,0.1792,13.8994,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,26.9834,0.1792,13.8994,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,26.9834,0.1792,13.8994,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,26.9834,0.1792,13.8994,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,26.9834,0.1792,13.8994,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,26.9834,0.1792,13.8994,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,7.4556,-0.1916,-5.2575,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,19.5814,0.1303,6.5464,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KCPL_KCPL,KCPL_LA,22.7344,0.1151,9.7145,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KENN,KENN_LA,7.5598,0.4351,-5.7801,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KEP2_SECI,KEP2_SECI_LA,-9.5934,-0.8623,-21.6358,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KERR_1,GRDAKERR_HYDUN1_RA,39.4228,0.2180,26.3001,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KERR_2,GRDAKERR_HYDUN2_RA,39.2820,0.2201,26.1571,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KERR_3,GRDAKERR_HYDUN3_RA,39.2820,0.2201,26.1571,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KERR_4,GRDAKERR_HYDUN4_RA,39.4228,0.2180,26.3001,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,14.1175,-0.1426,1.3553,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,14.1175,-0.1426,1.3553,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,15.8352,-0.0635,2.9940,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,15.8352,-0.0635,2.9940,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,12.0268,-0.1477,-0.7302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,10.3180,-0.1279,-2.4588,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,10.3180,-0.1279,-2.4588,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-8.5170,-0.9951,-20.4266,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-8.5170,-0.9951,-20.4266,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-8.5170,-0.9951,-20.4266,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-6.4288,-0.4105,-18.9230,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-6.4288,-0.4105,-18.9230,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-8.5969,-1.0069,-20.4948,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-6.8615,-0.5245,-19.2417,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-6.1541,-0.3977,-18.6611,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,51.4149,-0.1336,38.6437,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,51.4149,-0.1336,38.6437,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-3.9455,-0.2870,-16.5633,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-3.9455,-0.2870,-16.5633,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-3.9455,-0.2870,-16.5633,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-7.3364,-0.7161,-19.5250,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-7.6293,-0.8332,-19.7008,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,1.9518,-0.3751,-10.5777,12.9046\n03/19/2025 12:00:00,03/19/2025 17:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-15.9485,0.0411,-28.8943,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LAFA,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LAM345,LAM345,-8.9371,-1.1640,-20.6778,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LEPA,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,5.3970,-0.2381,-7.2696,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_LES,LES_LA,5.4183,-0.2523,-7.2342,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,5.6186,-0.2920,-6.9941,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,5.2604,-0.2887,-7.3556,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,5.2604,-0.2887,-7.3556,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,5.2604,-0.2887,-7.3556,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,5.6217,-0.2890,-6.9941,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,5.6186,-0.2920,-6.9941,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_WAVERLY,LES_WAVERLY_H,5.5933,-0.2974,-7.0140,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,6.8736,-0.2806,-5.7506,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,6.8736,-0.2806,-5.7506,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,LGEE,LGEE,19.9474,0.2663,6.7764,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MALDEN,MALDEN_LA,8.8362,0.4204,-4.4889,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MCWEST,MCWEST,9.8729,0.1584,-3.1903,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MDU,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,2.9320,-0.3690,-9.6038,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,2.3569,-0.0703,-10.4776,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,6.6304,0.4135,-6.6879,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MEAN_NPPD,NPPD_MEAN_LA,2.4807,-0.6634,-9.7606,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MEC,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MHEB,MHEB,10.8600,0.1833,-2.2280,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-3.6193,-0.6759,-15.8481,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-7.4019,-0.8833,-19.4234,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-3.6193,-0.6759,-15.8481,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-3.6193,-0.6759,-15.8481,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-7.4019,-0.8833,-19.4234,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-11.2965,-0.7095,-23.4917,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MISO,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-9.5005,-0.8357,-21.5695,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-9.5005,-0.8357,-21.5695,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-3.8264,-0.4363,-16.2948,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-9.8944,-1.0715,-21.7276,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-7.1160,-0.7641,-19.2566,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-10.4041,-0.9633,-22.3455,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-9.8493,-0.7885,-21.9656,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-10.4949,-0.9032,-22.4964,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-9.8424,-0.7299,-22.0172,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-9.8424,-0.7299,-22.0172,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-9.8424,-0.7299,-22.0172,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-9.8424,-0.7299,-22.0172,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-9.8424,-0.7299,-22.0172,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,11.4211,0.0503,-1.5339,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,17.7170,0.2970,4.5152,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,17.7170,0.2970,4.5152,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,16.7306,0.1975,3.6284,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,16.5928,0.4881,3.1999,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MOWR,AECI,23.9336,0.2317,10.7972,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,16.7618,0.1534,3.7037,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,17.9894,0.3033,4.7814,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,6.3363,-0.6328,-5.9356,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,7.5410,-0.3187,-5.0451,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-12.0177,-0.9246,-23.9978,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,6.3778,-0.5914,-5.9356,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,14.4196,0.0197,1.4951,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,14.4196,0.0197,1.4951,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,14.4201,0.0203,1.4951,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,14.4201,0.0203,1.4951,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,1.9978,0.0451,-10.9520,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,1.9978,0.0451,-10.9520,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,1.9978,0.0451,-10.9520,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,1.9561,0.0033,-10.9520,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,1.9978,0.0451,-10.9520,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,1.9978,0.0451,-10.9520,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,1.9978,0.0451,-10.9520,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,21.3124,0.3208,8.0869,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,15.3007,0.0181,2.3779,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,14.1431,-0.0307,1.2691,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,14.1432,-0.0306,1.2691,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,14.1432,-0.0306,1.2691,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,20.6294,0.1392,7.5854,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,20.6294,0.1392,7.5854,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MPS_MPS,MPS_LA,13.6649,0.1586,0.6016,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MSTNG,SPSMSTNGPLT1,0.8836,0.2040,-12.2251,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MSTNG4,SPSMSTNGUN4_RA,0.8458,0.1661,-12.2251,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,MSTNG5,SPSMSTNGUN5_RA,0.8836,0.2040,-12.2251,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,0.8836,0.2040,-12.2251,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NBSO,PJM,17.9173,0.1990,4.8135,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,5.4788,-0.6119,-6.8141,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,5.4768,-0.6138,-6.8141,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-13.1589,-2.1079,-23.9558,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NHC1,VACS,25.6894,0.4365,12.3481,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,6.7408,-0.2146,-5.9494,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,6.7408,-0.2146,-5.9494,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,6.7408,-0.2146,-5.9494,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,4.3970,-0.8146,-7.6931,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,2.9707,-0.6807,-9.2534,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,4.3792,-0.4925,-8.0330,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,6.8044,-0.3679,-5.7324,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,2.9707,-0.6807,-9.2534,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.HUB.PY2018,NPPDPY18_H,2.9087,-0.7202,-9.2759,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,3.0046,-0.7126,-9.1875,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,2.9348,-0.7089,-9.2610,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,3.0140,-0.6962,-9.1946,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,7.0923,-0.4139,-5.3985,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,1.4242,-0.8006,-10.6799,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,1.4242,-0.8006,-10.6799,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,0.5691,-0.6267,-11.7089,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,7.0923,-0.4139,-5.3985,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,5.8008,-0.8792,-6.2247,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,2.5469,-1.0126,-9.3452,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-0.6456,-0.7892,-12.7611,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,2.5469,-1.0126,-9.3452,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,3.4743,-0.8796,-8.5509,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,2.3007,-0.9278,-9.6762,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,4.8602,-0.1622,-7.8823,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,2.9707,-0.6807,-9.2534,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-0.3109,-0.8091,-12.4066,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,1.4242,-0.8006,-10.6799,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,1.4242,-0.8006,-10.6799,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,1.9605,-0.5623,-10.3819,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,1.9193,-0.5740,-10.4114,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,1.9193,-0.5740,-10.4114,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,2.5227,-0.2809,-10.1011,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-5.3800,-0.1299,-18.1548,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,3.1771,-0.5044,-9.2232,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,4.7500,-0.6401,-7.5146,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-10.0000,-0.0653,-22.8394,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-12.3872,-0.0688,-25.2231,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.NELI.DDR,NELI_DDR,6.6433,-0.5155,-5.7459,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.NPPM.1058,SH1058_DDR,5.9828,-0.1260,-6.7959,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,2.4771,-0.3838,-10.0438,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,2.9707,-0.6807,-9.2534,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,4.3792,-0.4925,-8.0330,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,7.0923,-0.4139,-5.3985,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.TECH.1,KEARNE_DDR,2.7812,-0.2715,-9.8521,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,4.3320,-1.0786,-7.4941,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,4.3320,-1.0786,-7.4941,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,6.8904,-0.4822,-5.5321,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD.VOLT.0236,V236_DDR,3.9769,-0.1716,-8.7563,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD2017HUB,NPPD2017HUB_H,2.9092,-0.7174,-9.2782,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,5.6995,-0.4386,-6.7667,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,4.3970,-0.8146,-7.6931,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,2.4929,-1.2044,-9.2075,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,2.4929,-1.2044,-9.2075,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,4.1360,-0.1995,-8.5693,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,3.9895,-0.1590,-8.7563,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,3.8927,-0.3551,-8.6569,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,2.0199,-0.5792,-10.3057,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,5.7098,-0.3990,-6.7959,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,5.7098,-0.3990,-6.7959,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,5.7098,-0.3990,-6.7959,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,3.3567,-0.5387,-9.0093,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,4.8039,-0.5501,-7.5507,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,3.4386,-0.2923,-9.1738,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,6.5227,-1.1161,-5.2660,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,6.5929,-1.0458,-5.2660,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,0.9102,-0.8636,-11.1309,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,0.7214,-0.8669,-11.3164,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,3.7462,-0.4860,-8.6725,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,3.7349,-0.4974,-8.6725,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,3.7349,-0.4974,-8.6725,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,3.7320,-0.4672,-8.7056,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,5.8008,-0.8792,-6.2247,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,3.6918,-0.4712,-8.7417,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,4.8424,-0.3546,-7.7077,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,3.3690,-0.5082,-9.0276,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,3.3573,-0.5171,-9.0303,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,3.3632,-0.5078,-9.0338,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,3.3632,-0.5078,-9.0338,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,3.3567,-0.5387,-9.0093,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,3.3109,-0.5845,-9.0093,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,5.4248,-0.3607,-7.1192,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,3.5584,-0.2572,-9.0892,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,0.9634,-0.8253,-11.1160,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,5.5146,-0.9859,-6.4043,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-0.9342,-0.8351,-13.0038,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,6.1963,0.0875,-6.7959,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,6.6433,-0.5155,-5.7459,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,1.1187,-0.8350,-10.9511,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,1.1187,-0.8350,-10.9511,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_NPPD,NPPD_LA,4.1776,-0.4046,-8.3226,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,4.8424,-0.3546,-7.7077,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,4.8424,-0.3546,-7.7077,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,1.6689,-0.3907,-10.8452,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,1.9369,-0.7262,-10.2417,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NSB,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NSP,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,NSSO,PJM,17.9173,0.1990,4.8135,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,NYIS,PJM,17.9173,0.1990,4.8135,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-12.8400,-1.4601,-24.2846,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-19.3000,-0.9202,-31.2845,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-2.7056,-0.7249,-14.8854,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-2.7056,-0.7249,-14.8854,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-12.3941,-1.6583,-23.6405,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-26.7881,-0.9865,-38.7063,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-91.4158,-0.5959,-103.7247,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-42.6998,-0.8820,-54.7225,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-22.5676,-0.9098,-34.5625,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-19.4898,-0.9270,-31.4675,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,3.1326,-0.3311,-9.4410,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-22.5676,-0.9098,-34.5625,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-12.5343,-1.6143,-23.8248,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-11.2965,-0.7095,-23.4917,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-13.0192,-1.4203,-24.5037,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,37.0983,-0.0665,24.2601,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-19.4898,-0.9270,-31.4675,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-16.6370,-0.8778,-28.6639,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-1.7660,-0.8502,-13.8206,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-11.7356,-0.7475,-23.8928,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-42.6606,-0.0648,-55.5006,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-11.2965,-0.7095,-23.4917,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-11.2965,-0.7095,-23.4917,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-19.4898,-0.9270,-31.4675,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-9.5639,-0.7161,-21.7526,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.NUEN.LAM1,LAM1_DDR,34.2013,0.8951,20.4015,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.NUEN.MDT2,MDT2_DDR,3.1326,-0.3311,-9.4410,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.NUEN.MDT3,MDT3_DDR,3.1326,-0.3311,-9.4410,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-9.7981,-0.7178,-21.9850,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,0.7437,-0.3759,-11.7851,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,0.7437,-0.3759,-11.7851,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,0.7437,-0.3759,-11.7851,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,6.5041,-0.3155,-6.0851,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,6.5041,-0.3155,-6.0851,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,0.7437,-0.3759,-11.7851,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,0.7437,-0.3759,-11.7851,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-19.4898,-0.9270,-31.4675,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,16.0669,0.5379,2.6243,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-12.5343,-1.6143,-23.8248,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-31.3353,-0.1655,-44.0745,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-16.6370,-0.8778,-28.6639,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,30.7626,0.5722,17.2856,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-17.0795,-0.7265,-29.2577,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-17.0795,-0.7265,-29.2577,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-17.0795,-0.7265,-29.2577,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-17.0795,-0.7265,-29.2577,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-19.8898,-1.3032,-31.4914,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-22.9391,-0.8808,-34.9630,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-19.3000,-0.9202,-31.2845,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-27.7151,-0.8587,-39.7611,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-27.7151,-0.8587,-39.7611,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-25.5146,-0.1048,-38.3146,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-13.7608,-0.8206,-25.8450,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-13.7608,-0.8206,-25.8450,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-13.7608,-0.8206,-25.8450,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0033,FOSTER_DDR,12.6286,-0.2861,0.0100,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,34.4596,0.4820,21.0728,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0035,TARBY_DDR,34.1116,0.7243,20.4826,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,34.4596,0.4820,21.0728,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,34.1919,0.3501,20.9371,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,34.1919,0.3501,20.9371,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-38.7400,-0.1040,-51.5407,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0040,TROSPER_DDR,16.0008,-0.2654,3.3614,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,15.9320,-0.2652,3.2925,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,32.0540,0.6802,18.4690,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0115,V115_DDR,4.1282,-0.3241,-8.4525,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0116,V116_DDR,74.9793,-0.0140,62.0885,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0118,V118_DDR,13.6999,0.0081,0.7871,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0125,V125_DDR,32.8128,0.7856,19.1225,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0126,V126_DDR,35.1316,0.4171,21.8098,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0129,V129_DDR,0.7613,-0.6402,-11.5033,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,40.4600,-0.3390,27.8942,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0134,V134_DDR,35.8508,0.5076,22.4384,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0138,V138_DDR,34.5965,0.3600,21.3317,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,34.0947,-0.2745,21.4645,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0143,V143_DDR,33.7565,0.2841,20.5677,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0149,V149_DDR,-8.6817,-0.6564,-20.9300,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0150,V150_DDR,-8.6703,-0.7022,-20.8729,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0155,V155_DDR,34.1064,0.2975,20.9042,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0156,V156_DDR,40.4600,-0.3390,27.8942,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0166,V166_DDR,35.1239,0.7536,21.4656,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,33.3442,-0.2795,20.7189,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-8.6703,-0.7022,-20.8729,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0170,V170_DDR,-9.9283,-0.7167,-22.1163,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-17.5617,-0.6314,-29.8350,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0176,V176_DDR,-8.6703,-0.7022,-20.8729,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0177,V177_DDR,-16.0168,-1.2818,-27.6397,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,26.5609,-0.2783,13.9345,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-6.0000,-0.7318,-18.1729,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0195,V195_DDR,135.9194,0.7859,122.2287,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0197,V197_DDR,36.3019,0.5021,22.8951,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0198,V198_DDR,35.1239,0.7536,21.4656,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0208,V208_DDR,136.0000,0.7994,122.2959,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0209,V209_DDR,136.0000,0.7994,122.2959,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,36.1568,0.3786,22.8735,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0216,V216_DDR,15.9146,-0.2659,3.2757,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0219,V219_DDR,34.1064,0.2975,20.9042,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0220,V220_DDR,-8.6703,-0.7022,-20.8729,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0224,V224_DDR,3.3833,-0.3427,-9.1787,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0225,V225_DDR,3.3840,-0.3420,-9.1787,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0226,V226_DDR,3.3833,-0.3427,-9.1787,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0227,V227_DDR,3.3833,-0.3427,-9.1787,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0229,V229_DDR,-34.0622,-0.0326,-46.9343,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0231,V231_DDR,20.3579,0.0981,7.3550,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0238,V238_DDR,-18.8302,-0.9702,-30.7647,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.VOLT.0242,V242_DDR,34.3234,0.3278,21.0908,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-16.1686,-1.8965,-27.1768,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-11.2965,-0.7095,-23.4917,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-19.0996,-0.8987,-31.1057,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-13.0085,-1.4095,-24.5037,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-16.1686,-1.8965,-27.1768,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-12.4486,-1.6323,-23.7210,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-47.8210,-0.8418,-59.8839,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEHL7,OKGEHL7_H,25.9097,-0.2605,13.2654,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEHL8,OKGEHSL1UN8_RA,25.9097,-0.2605,13.2654,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEHL910,OKGEHSL1PLT2,25.9097,-0.2605,13.2654,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-12.7361,-1.5018,-24.1390,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEMCC,OKGEMCCLAIPLT1,1.1158,-0.4762,-11.3127,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,31.6650,0.2276,18.5327,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,31.6650,0.2276,18.5327,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,31.6650,0.2276,18.5327,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,19.0937,-0.4568,6.6457,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,19.0937,-0.4568,6.6457,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,19.0937,-0.4568,6.6457,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,19.0937,-0.4568,6.6457,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGESM1,OKGESEMINOLEUN1_RA,14.5874,-0.1962,1.8788,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGESM2,OKGESEMINOLEUN2_RA,11.6754,-0.2251,-1.0042,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGESM3,OKGESEMINOLEUN3_RA,11.6754,-0.2251,-1.0042,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGESO1,OKGESONR1UN1_RA,-57.5532,-0.8116,-69.6463,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGESO2,OKGESONR1UN2_RA,-27.7151,-0.8587,-39.7611,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-12.8167,-1.5824,-24.1390,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-13.2463,-1.7564,-24.3946,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGETINK5A,OKGETINK5UN1_RA,14.1559,-0.2963,1.5474,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGETINK5B,OKGETINK5UN2_RA,14.1559,-0.2963,1.5474,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-13.4231,-1.2131,-25.1147,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-19.3000,-0.9202,-31.2845,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,31.4344,0.8591,17.6706,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-11.2965,-0.7095,-23.4917,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE_OKGE,OKGE_LA,19.5016,-0.1281,6.7249,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-31.3353,-0.1655,-44.0745,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-13.4565,-1.2465,-25.1147,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMLP,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,40.8789,0.1562,27.8180,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,31.7129,0.8102,17.9980,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_GENHUB,OMPA_GENHUB_H,0.4865,-0.3516,-12.0666,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-91.3024,-0.4824,-103.7247,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-7.1576,-0.8270,-19.2353,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-22.5676,-0.9098,-34.5625,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-15.6255,-1.8775,-26.6528,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-4.3980,-1.2737,-16.0290,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,163.7923,0.1270,150.7606,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-91.3395,-0.5196,-103.7247,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-91.3395,-0.5196,-103.7247,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_SPP,OMPA_SPP_LA,-1.2083,-0.5094,-13.6036,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-16.1686,-1.8965,-27.1768,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,36.5854,0.1447,23.5360,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,36.5854,0.1447,23.5360,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,36.5854,0.1447,23.5360,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,36.5854,0.1447,23.5360,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,ONT,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,6.7266,-0.2169,-5.9613,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,6.7266,-0.2169,-5.9613,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,6.7266,-0.2169,-5.9613,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,6.7266,-0.2169,-5.9613,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,6.7266,-0.2169,-5.9613,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,6.7266,-0.2169,-5.9613,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,6.7266,-0.2169,-5.9613,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,6.7266,-0.2169,-5.9613,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,6.7266,-0.2169,-5.9613,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,6.7356,-0.1979,-5.9713,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,6.7408,-0.2146,-5.9494,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,6.5688,-0.1587,-6.1773,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,6.6113,-0.1820,-6.1114,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,6.6113,-0.1820,-6.1114,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD_GLDN,OPPD_GLDN_LA,6.6427,-0.2147,-6.0474,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,6.7424,-0.2063,-5.9561,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,5.8008,-0.8792,-6.2247,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,4.5712,-0.3859,-7.9477,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,6.7405,-0.2139,-5.9503,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD_OPPD,OPPD_LA,6.6758,-0.1764,-6.0526,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,6.6485,-0.1671,-6.0891,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,6.6358,-0.1714,-6.0975,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OTP,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,OVEC,OVEC,19.1275,0.2404,5.9823,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PARAGOULD,PARAGOULD_LA,5.5293,0.4587,-7.8341,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,39.1227,0.1069,26.1111,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,39.1227,0.1069,26.1111,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,39.1227,0.1069,26.1111,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,38.8193,0.1580,25.7565,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,38.8193,0.1580,25.7565,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,38.8193,0.1580,25.7565,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PIGGOTT,PIGGOTT_LA,8.0148,0.4299,-5.3199,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PJM,PJM,17.9173,0.1990,4.8135,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PLUM,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,POPLARBLUFF,POPLARBLUFF_LA,12.8938,0.3859,-0.3968,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,9.6606,-0.0320,-3.2121,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,9.6606,-0.0320,-3.2121,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,9.7241,-0.0159,-3.1647,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,9.7241,-0.0159,-3.1647,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,10.6257,0.8513,-3.1303,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,10.6257,0.8513,-3.1303,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,9.8747,0.1550,-3.1851,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,9.0377,-0.4349,-3.4321,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-8.3988,-0.5683,-20.7353,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,83.9927,0.1591,70.9290,12.9046\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,3.6432,0.0984,-9.3599,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-1.0774,-0.0194,-13.9627,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,43.7382,0.4266,30.4069,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,35.3387,0.4960,21.9380,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,9.8451,-0.1432,-2.9165,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,10.2782,0.1918,-2.8183,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,8.7906,-0.3404,-3.7737,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,22.0000,1.2714,7.8239,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,10.5933,0.2825,-2.5939,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,9.6284,0.0219,-3.2983,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,PUPP,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,RCEAST,RCEAST,5.9657,-0.8880,-6.0510,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SALINA_1,GRDASALINA1UN1_RA,39.4241,0.2193,26.3001,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SALINA_2,GRDASALINA1UN2_RA,39.4241,0.2193,26.3001,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SALINA_3,GRDASALINA1UN3_RA,39.4241,0.2193,26.3001,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SALINA_4,GRDASALINA1UN4_RA,39.4241,0.2193,26.3001,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SALINA_5,GRDASALINA1UN5_RA,39.4241,0.2193,26.3001,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SALINA_6,GRDASALINA1UN6_RA,39.4241,0.2193,26.3001,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SARPY_1,OPPDSARPYUN1_RA,6.6449,-0.2032,-6.0566,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SARPY_2,OPPDSARPYUN2_RA,6.6460,-0.1767,-6.0820,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SARPY_3,OPPDSARPYUN3_RA,6.6444,-0.2319,-6.0284,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SARPY_4,OPPDSARPYUN4_RA,6.6444,-0.2319,-6.0284,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SARPY_5,OPPDSARPYUN5_RA,6.6444,-0.2319,-6.0284,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SC,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SCEG,VACS,25.6894,0.4365,12.3481,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SCSE,SCSE,1.4797,-0.7386,-10.6865,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SEC,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-11.0777,-1.2257,-22.7568,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-11.0777,-1.2257,-22.7568,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-11.0777,-1.2257,-22.7568,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-8.6801,-0.9677,-20.6171,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-11.0777,-1.2257,-22.7568,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-9.5524,-1.2165,-21.2406,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-9.5780,-1.2448,-21.2379,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-9.5780,-1.2448,-21.2379,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-9.8440,-0.7316,-22.0172,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-12.1349,-1.1099,-23.9298,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-6.4856,-0.4673,-18.9230,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-8.9754,-0.8666,-21.0136,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-5.0848,-1.0074,-16.9821,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-10.7307,-1.2306,-22.4048,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-5.0114,-0.9947,-16.9214,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-9.8530,-1.0762,-21.6815,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-9.5392,-0.7165,-21.7274,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-8.6254,-1.0594,-20.4707,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-8.6254,-1.0594,-20.4707,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-8.6254,-1.0594,-20.4707,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-8.6254,-1.0594,-20.4707,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-8.8168,-1.1284,-20.5931,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-9.5524,-1.2165,-21.2406,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI_SECI,SECI_LA,-8.6037,-0.8406,-20.6678,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-5.5773,-0.7137,-17.7683,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-5.5773,-0.7137,-17.7683,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-9.8440,-0.7316,-22.0172,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SEHA,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-13.4565,-1.2465,-25.1147,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SERU,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SETH,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SGE,SGE,2.3668,-0.7089,-9.8290,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SMEP,MISO,17.1559,0.2510,4.0002,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SOCO,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPA,SPA,26.8229,0.4997,13.4184,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPC,SPC,10.3506,0.4919,-3.0460,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPPNORTH_HUB,SPPNORTH_H,5.6395,-0.2615,-7.0038,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPPSOUTH_HUB,SPPSOUTH_H,5.7500,-0.6332,-6.5215,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,27.4984,0.4284,14.1653,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,27.4984,0.4284,14.1653,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,26.8909,0.4079,13.5783,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,26.8909,0.4079,13.5783,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_NIXA,SPRM_NIXA_LA,27.6823,0.4198,14.3578,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_SPRM,SPRM_LA,27.6045,0.4751,14.2247,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,27.7358,0.3608,14.4703,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,27.7358,0.3608,14.4703,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,27.7018,0.3267,14.4703,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,27.7358,0.3608,14.4703,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-7.9909,-0.5854,-20.3103,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-11.2124,-0.8265,-23.2906,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-12.5316,-1.5018,-23.9345,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-12.5316,-1.5018,-23.9345,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-14.9730,-1.3267,-26.5510,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,-4.6338,-0.9344,-16.6041,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-11.6076,-2.6124,-21.8999,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,-2.5070,-0.5006,-14.9111,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-15.2185,-0.7565,-27.3667,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,-0.2921,0.1542,-13.3511,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,-0.6655,0.1585,-13.7288,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,-0.6655,0.1585,-13.7288,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,-0.2921,0.1542,-13.3511,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-12.4875,-1.4574,-23.9348,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-11.2124,-0.8265,-23.2906,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-12.2016,-1.2675,-23.8388,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-12.3855,-1.6733,-23.6169,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-11.9874,-1.1591,-23.7330,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-11.8600,-0.9603,-23.8045,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-12.1404,-1.2452,-23.8000,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-12.1644,-1.6742,-23.3949,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-12.1644,-1.6742,-23.3949,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-12.1644,-1.6742,-23.3949,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-12.1644,-1.6742,-23.3949,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GRID.WRAB,WRAB_DDR,-12.3047,-1.1810,-24.0284,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-12.1644,-1.6742,-23.3949,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-13.8369,-0.8021,-25.9395,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-13.8369,-0.8021,-25.9395,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-13.7101,-0.7613,-25.8535,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-13.7101,-0.7613,-25.8535,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-13.7101,-0.7613,-25.8535,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-13.8369,-0.8021,-25.9395,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-12.5316,-1.3773,-24.0591,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-12.5315,-1.3772,-24.0590,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-12.5301,-1.3773,-24.0575,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-13.1589,-2.1079,-23.9558,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,-0.3963,0.1261,-13.4271,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-15.1591,-0.7630,-27.3009,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-15.1591,-0.7630,-27.3009,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-15.1591,-0.7630,-27.3009,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-15.1591,-0.7630,-27.3009,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,0.6756,0.1763,-12.4054,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,-0.2521,0.1322,-13.2890,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,-0.2521,0.1322,-13.2890,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-13.4014,-1.1915,-25.1147,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-12.5229,-1.3712,-24.0564,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-12.5229,-1.3712,-24.0564,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-12.5418,-1.3729,-24.0737,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-12.3047,-1.1810,-24.0284,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-12.2003,-1.4871,-23.6179,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-12.3810,-1.4040,-23.8818,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-12.3941,-1.6583,-23.6405,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-12.3588,-1.2071,-24.0564,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-10.4840,-0.7179,-22.6708,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-10.4840,-0.7179,-22.6708,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-10.1096,-0.7418,-22.2725,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-15.0109,-1.1234,-26.7922,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-12.6115,-2.0085,-23.5077,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-11.3161,-2.3209,-21.8999,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-14.9965,-1.1090,-26.7922,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-12.4653,-1.4352,-23.9348,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-6.9298,-0.7106,-19.1239,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,-2.1207,-0.1144,-14.9111,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-6.9298,-0.7106,-19.1239,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,-2.0907,-0.0769,-14.9185,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-12.3374,-1.4858,-23.7564,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,-0.3539,0.7023,-13.9610,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,-0.3516,0.7047,-13.9610,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,-0.3707,0.4479,-13.7233,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,-0.2265,0.1373,-13.2686,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,-1.2087,0.4718,-14.5852,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-8.9371,-1.1640,-20.6778,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-12.3604,-1.2347,-24.0304,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-9.5077,-0.7076,-21.7048,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-9.5077,-0.7076,-21.7048,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-6.9298,-0.7106,-19.1239,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-15.3547,-0.6942,-27.5653,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,5.0317,0.5144,-8.3875,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-9.1329,-0.0971,-21.9405,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-9.6509,-0.4383,-22.1173,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-12.6495,-0.8797,-24.6745,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,-0.3539,0.7023,-13.9610,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,-0.6132,0.9218,-14.4398,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,-0.7750,0.7600,-14.4398,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-14.8717,-0.9843,-26.7922,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-9.4556,-0.4647,-21.8956,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-12.1608,-1.5307,-23.5349,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-12.1888,-1.5585,-23.5350,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0163,V163_DDR,-12.1465,-1.1759,-23.8753,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0168,V168_DDR,-14.5310,-0.8301,-26.6057,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0180,V180_DDR,-0.6132,0.9218,-14.4398,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0181,V181_DDR,-12.4284,-1.8141,-23.5190,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0182,V182_DDR,-1.0823,0.6242,-14.6112,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0199,V199_DDR,2.6285,0.4265,-10.7027,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0200,V200_DDR,-0.1784,0.4434,-13.5266,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.VOLT.0235,V235_DDR,-12.2003,-1.4871,-23.6179,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-11.6076,-2.6124,-21.8999,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,-2.5070,-0.5006,-14.9111,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-12.3275,-1.5368,-23.6955,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-12.3953,-1.2914,-24.0087,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS_SPS,SPS_LA,-4.3174,-0.0490,-17.1732,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,-0.2982,-0.2156,-12.9873,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SSCN_NPPD,SSCN_NPPD_LA,5.5077,-0.2898,-7.1072,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,13.0038,0.3748,-0.2758,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,13.0038,0.3748,-0.2758,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,TAL,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,TEC,SOUC,25.4487,0.4602,12.0837,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,5.5146,-0.9859,-6.4043,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,TVA,TVA,25.9277,0.4116,12.6114,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,UCUHUB,UCUHUB_H,-1.9684,-0.2329,-14.6403,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,UCUHUB17,UCUHUB17_H,-3.9174,-0.5274,-16.2948,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,UCUHUB18,UCUHUB18_H,-1.7280,-0.4383,-14.1945,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,UCUHUB19,UCUHUB19_H,-3.8610,-0.5111,-16.2546,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,UCUHUB20,UCUHUB20_H,-3.4569,-0.4967,-15.8649,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,UCUHUB21,UCUHUB21_H,-5.4055,-0.5789,-17.7313,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,UCUHUB22,UCUHUB22_H,-4.9497,-0.6121,-17.2423,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,UCUHUB23,UCUHUB23_H,-5.0176,-0.6196,-17.3028,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,UCUHUB24,UCUHUB24_H,-2.1078,-0.5333,-14.4792,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,10.4327,0.5925,-3.0645,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,10.4327,0.5925,-3.0645,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,9.4288,-0.2075,-3.2684,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,9.4288,-0.2075,-3.2684,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,10.0060,-0.2144,-2.6843,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,9.6507,-0.1179,-3.1361,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,9.6507,-0.1179,-3.1361,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,10.4327,0.5925,-3.0645,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,10.0745,-0.1968,-2.6335,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,10.3558,0.2605,-2.8094,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,9.4259,-0.0247,-3.4541,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,6.7821,-1.2186,-4.9040,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,10.3526,0.5649,-3.1170,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,10.3526,0.5649,-3.1170,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,8.4347,-1.0991,-3.3709,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,9.4722,-0.2103,-3.2222,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,9.7835,-0.2224,-2.8988,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,8.9263,-0.2635,-3.7149,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,9.5050,0.0570,-3.4568,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,9.3242,-0.2329,-3.3477,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,9.1096,-0.4242,-3.3709,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,9.1096,-0.4242,-3.3709,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,9.4795,-0.1839,-3.2414,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,6.3971,-1.3447,-5.1629,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,10.1007,0.6322,-3.4363,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,23.3190,0.1393,10.2750,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,23.3190,0.1393,10.2750,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,23.3190,0.1393,10.2750,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,9.9221,0.1577,-3.1404,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,9.9221,0.1577,-3.1404,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,9.9221,0.1577,-3.1404,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,10.6304,0.7635,-3.0379,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,9.7643,-0.1988,-2.9416,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,9.7643,-0.1988,-2.9416,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,1.9258,-0.7248,-10.2541,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,8.7530,-0.1098,-4.0419,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,10.1800,0.2451,-2.9698,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,7.7766,-0.4014,-4.7267,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,5.8414,-1.6819,-5.3814,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,9.2863,-0.3015,-3.3169,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,10.3655,0.5647,-3.1039,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,10.3655,0.5647,-3.1039,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,10.3645,0.5636,-3.1039,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,10.3655,0.5647,-3.1039,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,10.2690,0.4805,-3.1163,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,10.2690,0.4805,-3.1163,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,10.2690,0.4805,-3.1163,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,10.2690,0.4805,-3.1163,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,10.2690,0.4805,-3.1163,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,10.2690,0.4805,-3.1163,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,10.2690,0.4805,-3.1163,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,7.0423,-0.9231,-4.9394,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,10.2280,0.0322,-2.7089,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,8.2658,-0.0870,-4.5520,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,8.2658,-0.0870,-4.5520,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,7.5322,-0.4333,-4.9392,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,7.5322,-0.4333,-4.9392,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,9.9092,-0.0540,-2.9416,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,10.0459,-0.0096,-2.8492,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,9.0885,-0.3250,-3.4913,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,6.6486,-1.1147,-5.1414,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,10.0454,-0.0754,-2.7839,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,10.0060,-0.2144,-2.6843,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,10.0060,-0.2144,-2.6843,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,8.9263,-0.2635,-3.7149,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,5.9139,-0.9346,-6.0562,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,8.5674,-0.4772,-3.8601,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,6.5302,-1.2116,-5.1629,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,9.1945,-0.3598,-3.3504,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.FSE,WAUE.FSE_H,5.8795,-0.6052,-6.4200,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,9.7962,0.0367,-3.1452,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,9.7618,0.0064,-3.1493,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,6.3963,-1.2194,-5.2890,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,6.4735,-1.1620,-5.2692,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,9.9344,-0.1995,-2.7709,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,9.9153,-0.2615,-2.7279,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-12.6100,-0.9693,-24.5454,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,6.7821,-1.2186,-4.9040,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-4.5500,-0.7180,-16.7367,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,8.3171,-0.3038,-4.2838,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,8.3174,-0.3036,-4.2838,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,8.3175,-0.3034,-4.2838,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,9.2719,-0.2070,-3.4259,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,5.9139,-0.9346,-6.0562,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,9.9538,0.0723,-3.0232,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,8.7357,-0.3493,-3.8197,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,10.0494,0.5810,-3.4363,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,9.1325,0.1747,-3.9469,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,9.5354,0.0364,-3.4057,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,10.9087,-0.0967,-1.8994,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,9.1272,-0.1281,-3.6494,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,9.0374,-0.3371,-3.5302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,7.7766,-0.4014,-4.7267,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,12.0303,0.5244,-1.3989,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,8.9120,-0.2765,-3.7162,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,11.8612,0.4080,-1.4515,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,9.8087,0.0992,-3.1952,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,6.8736,-0.2806,-5.7506,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NTWK,WAUE.NTWK_H,9.0393,-0.1641,-3.7013,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,10.1416,0.6815,-3.4447,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,10.1416,0.6815,-3.4447,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,6.7359,-1.2999,-4.8689,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,6.8689,-1.2144,-4.8215,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,9.7615,-0.1347,-3.0085,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,6.7359,-1.2999,-4.8689,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,10.6643,0.0531,-2.2935,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,8.0291,-0.6334,-4.2422,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,7.7766,-0.4014,-4.7267,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,8.6827,-0.3243,-3.8978,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,6.6752,-1.9873,-4.2422,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,5.0792,-1.5808,-6.2448,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,5.5195,-1.5885,-5.7967,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,9.4084,-0.2320,-3.2643,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,4.7228,-1.1857,-6.9962,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,10.0075,0.0334,-2.9306,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,7.3124,-0.8981,-4.6943,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,6.6486,-1.1147,-5.1414,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.VOLT.0152,V152_DDR,10.8278,0.9191,-2.9961,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE.VOLT.0172,V172_DDR,10.3293,0.5355,-3.1109,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_BEPM,WAUE_BEPM_LA,10.3774,0.2302,-2.7574,12.9046\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,10.0694,0.0872,-2.9226,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,9.1376,0.1821,-3.9493,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_EWA,WAUE_EWA_LA,6.0052,-0.8547,-6.0448,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,8.2846,-0.4982,-4.1219,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_HMMU,WAUE_HMMU_LA,7.8741,-0.0135,-5.0171,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,11.1545,-0.0492,-1.7010,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_MECB,WAUE_MECB_LA,8.8423,0.2364,-4.2988,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_MMPA,WAUE_MMPA_LA,10.8457,0.3409,-2.3999,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_MRES,WAUE_MRES_LA,9.2219,-0.1092,-3.5737,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,10.6731,0.6774,-2.9090,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,9.7962,0.0367,-3.1452,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,8.0355,-0.4950,-4.3743,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_OTP,WAUE_OTP_LA,11.4273,0.6503,-2.1277,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_OTPW,WAUE_OTPW_LA,14.4490,0.6099,0.9343,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM,WAUE_UGPM_LA,9.6720,0.1085,-3.3412,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,10.0225,0.1321,-3.0143,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,9.1307,-0.1215,-3.6525,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,6.9273,-0.4334,-5.5440,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,6.0052,-0.8547,-6.0448,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,7.8741,-0.0135,-5.0171,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,8.2948,-0.4668,-4.1431,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,9.7962,0.0367,-3.1452,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,10.8457,0.3409,-2.3999,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,9.4769,-0.0611,-3.3667,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,7.7370,-0.5707,-4.5970,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,10.9371,0.6516,-2.6192,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-15.9700,-1.7270,-27.1477,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-10.7575,-1.1334,-22.5289,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,4.9981,-1.0066,-6.9001,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,89.6700,0.3851,76.3802,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,89.6700,0.3851,76.3802,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-7.0175,-1.7256,-18.1966,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,82.0113,0.4632,68.6434,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,73.0468,0.4476,59.6944,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,24.2870,-0.7479,12.1302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,24.2870,-0.7479,12.1302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,24.2870,-0.7479,12.1302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,24.2870,-0.7479,12.1302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,24.2458,-0.7891,12.1302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,24.2870,-0.7479,12.1302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,24.2870,-0.7479,12.1302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,24.2870,-0.7479,12.1302,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,15.2338,-0.7020,3.0310,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-12.3941,-1.6583,-23.6405,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-25.0000,-1.1535,-36.7512,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-16.2280,-2.0695,-27.0633,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-11.4014,-2.4062,-21.8999,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_ENMC,WFEC_ENMC_LA,-2.3338,0.0745,-15.3130,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-19.4898,-0.9270,-31.4675,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,34.2530,0.3326,21.0156,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,0.3728,0.1347,-12.6666,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-15.9700,-1.7270,-27.1477,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-15.9700,-1.7270,-27.1477,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-15.9700,-1.7270,-27.1477,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_OKGE,WFEC_OKGE_LA,6.1088,0.1105,-6.9064,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,57.9593,0.4548,44.5997,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-11.7912,-1.7966,-22.8993,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-6.7062,-1.8976,-17.7133,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_WFEC,WFEC_LA,23.7001,-0.2807,11.0761,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,0.3728,0.1347,-12.6666,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-4.3189,-0.6960,-16.5276,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-7.6721,-1.1482,-19.4286,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-4.0236,-0.4656,-16.4628,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-4.0236,-0.4656,-16.4628,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-4.0236,-0.4656,-16.4628,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-4.0236,-0.4656,-16.4628,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-4.0236,-0.4656,-16.4628,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-4.0236,-0.4656,-16.4628,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-4.0236,-0.4656,-16.4628,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,6.9335,0.4453,-6.4165,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-5.9086,-0.6343,-18.1791,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-16.0523,-0.8838,-28.0732,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-16.0523,-0.8838,-28.0732,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-16.0523,-0.8838,-28.0732,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-12.3353,-1.1061,-24.1339,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-12.3353,-1.1061,-24.1339,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-12.0048,-0.8022,-24.1073,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-12.0048,-0.8022,-24.1073,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-12.0048,-0.8022,-24.1073,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-5.9086,-0.6343,-18.1791,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,-5.5317,-0.0056,-18.4308,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-8.4517,-0.6101,-20.7464,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-8.4517,-0.6101,-20.7464,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-8.4517,-0.6101,-20.7464,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-8.4517,-0.6101,-20.7464,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,-5.5317,-0.0056,-18.4308,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-10.1914,-1.2384,-21.8577,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-19.9405,-0.5163,-32.3289,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.JEC.1,WRJEFFUN10_RA,-5.2129,-0.4417,-17.6759,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.JEC.2,WRJEFFUN11_RA,-5.3792,-0.4441,-17.8399,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.JEC.3,WRJEFFUN12_RA,-5.4423,-0.5071,-17.8399,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-20.5391,-0.9020,-32.5419,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-12.0100,-0.9169,-23.9978,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-12.0100,-0.9169,-23.9978,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.LEC.4,WRLECUN26_RA,-13.2233,-0.0842,-26.0438,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.LEC.5,WRLECUN27_RA,-10.0138,-0.0440,-22.8746,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-7.4530,-0.5055,-19.8522,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-7.4530,-0.5055,-19.8522,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-7.4530,-0.5055,-19.8522,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-7.4132,-0.4802,-19.8377,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-5.5773,-0.7137,-17.7683,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-5.5773,-0.7137,-17.7683,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-5.0335,-0.9041,-17.0341,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-3.9536,-0.6255,-16.2328,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-3.9536,-0.6255,-16.2328,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-7.6356,-0.8396,-19.7008,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-5.5773,-0.7137,-17.7683,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-1.9087,-0.5979,-14.2155,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-6.5854,-0.6894,-18.8007,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-12.0131,-0.9201,-23.9978,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,73.9913,0.4493,60.6372,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-7.9162,-1.2302,-19.5908,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-4.0236,-0.4656,-16.4628,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-1.5476,-0.9230,-13.5293,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,-5.5317,-0.0056,-18.4308,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-5.9086,-0.6343,-18.1791,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-13.1320,-0.6672,-25.3695,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.THAYERLD,WR.THAYERLD_LA,12.3663,0.4071,-0.9456,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-14.0145,-0.6661,-26.2532,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0106,V106_DDR,-12.8912,-0.6365,-25.1594,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-18.7060,0.0834,-31.6941,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-6.5744,-0.4981,-18.9810,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-13.9057,0.0343,-26.8447,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-13.9057,0.0343,-26.8447,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-12.1398,0.0330,-25.0776,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-12.2927,-0.5392,-24.6582,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0157,V157_DDR,-13.6476,0.0189,-26.5713,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0158,V158_DDR,-13.9057,0.0343,-26.8447,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-13.9057,0.0343,-26.8447,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-12.9299,-0.7198,-25.1149,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0173,V173_DDR,-7.4443,-0.5602,-19.7888,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0174,V174_DDR,-12.7157,-0.6531,-24.9673,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0184,V184_DDR,-12.2933,-0.7312,-24.4669,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-13.2520,-0.6594,-25.4973,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0186,V186_DDR,-13.3446,-0.6987,-25.5506,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-12.5436,-0.7029,-24.7454,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-13.7873,-0.6405,-26.0516,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-8.2541,-0.4317,-20.7271,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-5.0712,-0.3970,-17.5790,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-4.5569,-0.4277,-17.0339,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-4.5569,-0.4277,-17.0339,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-5.0712,-0.3970,-17.5790,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0245,V245_DDR,-13.2715,-0.6599,-25.5163,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.VOLT.0248,V248_DDR,-12.8912,-0.6365,-25.1594,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-16.4704,-0.8355,-28.5396,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-5.1732,-0.1172,-17.9608,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.WOLF,WRWOLFUN15_RA,-2.0319,-0.9913,-13.9454,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-10.1914,-1.2384,-21.8577,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,6.8684,0.3802,-6.4165,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-16.0523,-0.8838,-28.0732,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-16.0523,-0.8838,-28.0732,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-16.0523,-0.8838,-28.0732,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-16.0523,-0.8838,-28.0732,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-15.0513,-0.5327,-27.4233,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-6.5463,-0.5003,-18.9507,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-14.0150,-0.6720,-26.2477,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-14.0150,-0.6720,-26.2477,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-14.0150,-0.6720,-26.2477,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-14.0150,-0.6720,-26.2477,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-5.8447,-0.3186,-18.4309,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-5.8447,-0.3186,-18.4309,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-5.8447,-0.3186,-18.4309,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-5.8447,-0.3186,-18.4309,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-5.8447,-0.3186,-18.4309,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-5.8447,-0.3186,-18.4309,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-28.8970,-0.6171,-41.1846,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-28.8970,-0.6171,-41.1846,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-31.4308,-0.6396,-43.6960,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-31.4308,-0.6396,-43.6960,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_MIDW,WR_MIDW_LA,-5.7997,-0.7089,-17.9955,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,16.4197,0.3263,3.1887,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,15.5608,0.1588,2.4973,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-7.2562,-0.6469,-19.5141,12.9048\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_SEG,WR_SEG_LA,12.9209,0.2205,-0.2043,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,WR_WR,WR_LA,-9.0212,-0.4028,-21.5231,12.9047\n03/19/2025 12:00:00,03/19/2025 17:00:00,YAD,VACS,25.6894,0.4365,12.3481,12.9048\n03/19/2025 13:00:00,03/19/2025 18:00:00,AEC,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,AECC_CSWS,CSWS_AECC_LA,29.7295,0.5083,17.6088,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,29.8212,0.4523,17.7564,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,33.0543,0.6688,20.7731,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,29.3873,0.3184,17.4565,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,27.8350,0.3005,15.9220,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,32.5721,0.2724,20.6872,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,26.4971,0.1422,14.7424,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,AECI,AECI,23.3716,0.2269,11.5322,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,AEPM_CSWS,CSWS_LA,30.2820,0.3936,18.2760,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,ALTW,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,AMRN,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-14.9426,-0.7162,-25.8389,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BBA,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BCA,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BEPM.ER01.DDR,ER01_DDR,5.4701,-1.3090,-4.8334,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BEPM_ER01,BEPM_ER01_LA,5.4701,-1.3090,-4.8334,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,4.9149,-0.3624,-6.3352,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,0.9440,-0.2732,-10.3953,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BEPM_UM01,BEPM_UM01_LA,10.4280,0.5171,-1.7015,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,BLKW,BLKW,-13.2452,-0.5056,-24.3520,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-22.2876,-1.2044,-32.6957,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-22.2876,-1.2044,-32.6957,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,11.7248,-0.9828,1.0951,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-22.2695,-1.1862,-32.6957,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,BRAZ,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BUBA,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-11.0167,-1.0354,-21.5938,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-13.4166,-0.6651,-24.3639,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-13.4166,-0.6651,-24.3639,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-13.4166,-0.6651,-24.3639,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-13.4166,-0.6651,-24.3639,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-13.4166,-0.6651,-24.3639,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-12.2390,-0.4693,-23.3822,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,5.4309,-0.1991,-5.9825,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,5.4309,-0.1991,-5.9825,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CLEC,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,31.6907,0.3054,19.7729,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,COWP,COWP_LA,41.4340,0.3576,29.4640,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,41.4340,0.3576,29.4640,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,41.4340,0.3576,29.4640,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CPLE,VACS,33.5123,0.3646,21.5353,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CPLW,VACS,33.5123,0.3646,21.5353,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,31.7352,0.4232,19.6996,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,31.7352,0.4232,19.6996,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,31.7352,0.4232,19.6996,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,31.7352,0.4232,19.6996,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CRTH_SPA,WRCRTH_SPA_LA,22.4418,0.1184,10.7109,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,28.6937,1.0210,16.0603,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-2.0606,-0.6260,-13.0471,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,26.4971,0.1422,14.7424,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,29.3873,0.3184,17.4565,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,28.6769,1.0122,16.0522,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,27.6680,0.5316,15.5240,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,28.3895,0.8837,15.8934,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,28.3895,0.8837,15.8934,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,29.6999,0.3969,17.6905,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,29.6999,0.3969,17.6905,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,29.6999,0.3970,17.6905,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,29.6999,0.3970,17.6905,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,26.4971,0.1422,14.7424,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,28.3519,0.7098,16.0296,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,54.6851,-0.0043,43.0770,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,54.5775,-0.1119,43.0770,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,36.9691,0.1361,25.2206,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,35.9298,0.1710,24.1464,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,35.9298,0.1710,24.1464,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,35.9325,0.1710,24.1490,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,35.9325,0.1710,24.1490,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-16.7686,-0.7304,-27.6506,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,6.4210,-0.4195,-4.7719,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,35.1225,0.1779,23.3322,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-16.1577,-0.8798,-26.8904,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-16.1202,-0.8423,-26.8904,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-16.1138,-0.5141,-27.2122,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.GRID.CDL1,CDL1_DDR,33.5746,0.2508,21.7113,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-1.5719,-0.5878,-12.5966,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-1.4147,-0.8782,-12.1490,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,33.5746,0.2508,21.7113,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.NUEN.CSI1,CSI1_DDR,33.6740,0.3382,21.7233,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.NUEN.CSI2,CSI2_DDR,33.6782,0.3424,21.7233,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,31.7007,0.3153,19.7729,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.NUEN.GAZA,GAZA_DDR,33.5746,0.2508,21.7113,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,69.9100,0.4783,57.8192,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.NUEN.T201,NT201_DDR,36.1783,0.2238,24.3421,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-7.9034,-0.8194,-18.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-7.9034,-0.8194,-18.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,26.4971,0.1422,14.7424,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,28.0654,1.0355,15.4174,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-16.1138,-0.5141,-27.2122,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-16.1138,-0.5141,-27.2122,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-13.0483,-0.7024,-23.9583,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-16.1202,-0.8423,-26.8904,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,27.8702,0.4818,15.7759,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,34.1015,0.0936,22.3955,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,33.9335,-0.0744,22.3955,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,33.9291,-0.0789,22.3955,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,19.1967,0.0178,7.5665,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,19.1967,0.0178,7.5665,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,27.4995,0.4915,15.3956,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,37.8806,0.1976,26.0706,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,27.5391,0.4888,15.4378,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,28.1052,1.2806,15.2121,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,28.1656,0.2943,16.2588,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,33.6782,0.3424,21.7233,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0057,OKMU_DDR,36.8977,0.2990,24.9863,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0060,LEHIGH_DDR,69.9100,0.4783,57.8192,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0086,WARRENM_DDR,36.3125,0.2240,24.4761,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,27.6700,0.9343,15.1232,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,46.0281,0.2460,34.1696,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0121,V121_DDR,27.4995,0.4915,15.3956,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0122,V122_DDR,44.5145,0.2285,32.6736,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0124,V124_DDR,64.2208,0.1726,52.4357,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0135,V135_DDR,37.2550,0.2529,25.3896,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0144,V144_DDR,7.2040,-0.3785,-4.0300,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0145,V145_DDR,7.5866,-0.4407,-3.5852,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,27.5096,0.5279,15.3692,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,26.5868,0.3156,14.6588,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0175,V175_DDR,31.7007,0.3153,19.7729,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,26.5868,0.3156,14.6588,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,26.7469,0.3991,14.7353,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,37.2550,0.2529,25.3896,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,37.3320,0.2344,25.4851,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,36.7586,0.2063,24.9398,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,50.6022,0.1049,38.8848,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,36.1280,0.1590,24.3565,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,37.3320,0.2344,25.4851,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0211,V211_DDR,27.8150,0.6847,15.5178,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,46.8066,0.2533,34.9409,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0213,V213_DDR,36.9599,0.2282,25.1192,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0215,V215_DDR,45.5769,0.2409,33.7236,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0217,V217_DDR,46.8596,0.2394,35.0077,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0218,V218_DDR,50.1453,0.1141,38.4188,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0228,V228_DDR,38.4337,0.1765,26.6448,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0232,V232_DDR,36.8947,0.2569,25.0253,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0233,V233_DDR,37.5186,0.2471,25.6590,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0240,V240_DDR,43.2911,0.1729,31.5058,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0244,V244_DDR,37.3320,0.2344,25.4851,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0246,MDT1_DDR,69.9100,0.4783,57.8192,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0249,V249_DDR,36.9233,0.2445,25.0663,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0250,V250_DDR,-3.1585,-0.6058,-14.1652,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0251,V251_DDR,36.3647,0.1984,24.5539,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.VOLT.0252,V252_DDR,50.6022,0.1049,38.8848,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-19.3466,-0.7180,-30.2411,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,9.2447,-0.8039,-1.5639,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-13.3617,-1.3196,-23.6546,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,27.3335,0.2593,15.4617,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-16.4824,-1.2904,-26.8044,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,2.5218,-0.4847,-8.6060,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,2.5218,-0.4847,-8.6060,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,2.5218,-0.4847,-8.6060,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,2.5218,-0.4847,-8.6060,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,2.5218,-0.4847,-8.6060,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,26.4971,0.1422,14.7424,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,29.0667,0.8810,16.5732,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,36.8750,0.2372,25.0253,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,36.0527,0.0667,24.3736,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,37.6381,0.3269,25.6987,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,37.6381,0.3269,25.6987,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWWELSH1,CSWSWELSHUN1_RA,26.7324,0.3786,14.7413,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWWELSH3,CSWSWELSHUN3_RA,26.7324,0.3786,14.7413,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWWILKES1,CSWSWILKESUN1_RA,27.3785,0.6109,15.1552,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWWILKES2,CSWSWILKESUN2_RA,27.3785,0.6109,15.1552,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,CSWWILKES3,CSWSWILKESUN3_RA,27.4342,0.5755,15.2463,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-16.1101,-0.8321,-26.8904,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,DENL,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,DERS,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,DOE,DOE,27.3668,0.2915,15.4629,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,10.0050,0.0552,-1.6627,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,DPC,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,DUK,VACS,33.5123,0.3646,21.5353,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDDY,EDDY,-2.1400,0.0551,-13.8075,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,17.9266,0.0952,6.2190,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-9.1753,-0.1283,-20.6595,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,27.4077,-0.0893,15.8846,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE.SLCC,EDESTL4391_PLT,23.7432,-0.0192,12.1499,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,23.1298,0.0232,11.4942,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,12.1014,-0.1587,0.6477,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_EC_01,EDELAR3821UN1_RA,17.9266,0.0952,6.2190,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_EC_02,EDELAR3821UN2_RA,17.9266,0.0952,6.2190,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_EC_03,EDELAR3821UN3_RA,17.9266,0.0952,6.2190,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_EC_04,EDELAR3821UN4_RA,17.9266,0.0952,6.2190,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_EDE,EDE_LA,20.1878,0.2908,8.2846,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_ERW,EDEERWFUNG1_RA,-12.6619,-0.5166,-23.7578,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-4.2810,-0.5686,-15.3249,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,26.2168,0.6095,13.9948,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,26.2168,0.6095,13.9948,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,26.2168,0.6095,13.9948,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,26.2168,0.6095,13.9948,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,1.7900,0.3806,-10.2031,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_RIV_10,EDERIV1671UN10_RA,24.6557,-0.0706,13.1138,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_RIV_11,EDERIV1671UN11_RA,24.6557,-0.0706,13.1138,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_RIV_12,EDERIV453UN12_PLT,24.3283,-0.3979,13.1138,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_SL_01,EDESTL4391UN1_RA,23.5840,-0.1784,12.1499,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EDE_SWMP,EDE_SWMP_LA,12.9000,0.4316,0.8560,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EEI,EEI,27.1434,0.2904,15.2406,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,EES,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-7.3034,-0.5346,-18.3813,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,ERCOTE,ERCOTE,26.7324,0.3786,14.7413,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,ERCOTN,ERCOTN,-7.8540,-0.7701,-18.6964,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,2.6416,-0.3648,-8.6060,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,FMPP,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,FPC,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,FPL,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,FREM_50T,OPPDFREM_GUN1_RA,5.6655,-0.1800,-5.7669,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,FREM_6,OPPDFREM_AUN6_RA,5.6638,-0.1861,-5.7625,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,FREM_7,OPPDFREM_AUN7_RA,5.6638,-0.1861,-5.7625,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,FREM_8,OPPDFREM_AUN8_RA,5.5917,-0.2582,-5.7625,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,FREM_LOAD,FREM_LOAD_LA,5.6525,-0.1974,-5.7625,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-13.9850,-0.4352,-25.1622,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,27.8702,0.4818,15.7759,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-14.6089,-1.5496,-24.6717,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-30.0730,-0.8426,-40.8428,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,31.6907,0.3054,19.7729,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,31.6907,0.3054,19.7729,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,31.6907,0.3054,19.7729,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,34.6488,0.1893,22.8470,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,34.6488,0.1893,22.8470,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,34.8350,0.1859,23.0366,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,34.8350,0.1859,23.0366,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-23.6002,-0.7761,-34.4365,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,50.3868,0.1119,38.6624,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,50.3868,0.1119,38.6624,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,50.3868,0.1119,38.6624,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.VOLT.0130,V130_DDR,35.6462,0.3094,23.7244,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA.VOLT.0237,V237_DDR,36.1987,0.2371,24.3491,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDAHUB2,GRDAHUB2_H,24.4666,-0.0820,12.9362,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDAHUB3,GRDAHUB3_H,18.2879,-0.1746,6.8500,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA_GRDA,GRDA_LA,36.4778,0.2431,24.6223,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA_HUB,GRDA_H,31.1259,0.0367,19.4768,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRDA_HUBSA,GRDASA_H,30.8796,0.0180,19.2492,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GRE,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-8.1227,0.1149,-19.8501,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GSEC_SPS,SPS_GSEC_LA,-13.5378,-0.6252,-24.5250,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,GSPR2014HUB,GSPR2014HUB_H,-9.1172,-0.6835,-20.0462,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GSPR2015HUB,GSPR2015HUB_H,-8.1429,-0.6833,-19.0721,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-14.5952,-1.2588,-24.9489,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,HARRISON,CSWSLEBROCKPLT1,27.4156,0.3875,15.4157,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,HAST_TNSK_HUB,HAST_TNSK_H,2.3818,-0.5042,-8.7264,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,HQST,PJM,21.2309,0.1774,9.4410,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,HST,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,21.0747,0.2946,9.1676,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,21.0747,0.2946,9.1676,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,21.5432,0.2946,9.6361,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,21.5432,0.2946,9.6361,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,20.5301,0.2933,8.6243,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,20.5301,0.2933,8.6243,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,INDN_INDN,INDN_LA,21.1213,0.3038,9.2050,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-4.6134,-0.6044,-15.6214,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,ISNE,PJM,21.2309,0.1774,9.4410,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,JEA,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,5.6026,-0.1361,-5.8738,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,5.6026,-0.1361,-5.8738,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,4.3803,0.0512,-7.2833,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KACYCT4,KACYNEARMANUNCT4_RA,21.3341,0.2394,9.4822,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,51.9000,-0.0196,40.3071,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,21.3341,0.2394,9.4822,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,21.8090,0.2526,9.9439,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,21.6798,0.2515,9.8158,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KACY_KACY,KACY_LA,21.9400,0.2489,10.0786,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,35.0169,0.1661,23.2384,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,14.1222,0.4838,2.0259,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-17.8806,-0.5529,-28.9401,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-45.7998,-0.7370,-56.6753,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.VOLT.0222,V222_DDR,0.2102,0.0749,-11.4771,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.VOLT.0223,V223_DDR,12.0367,0.0467,0.3776,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.VOLT.0241,V241_DDR,14.1594,0.4236,2.1234,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.VOLT.0243,V243_DDR,17.1212,0.2152,5.2936,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.VOLT.0247,V247_DDR,13.5364,0.1496,1.7743,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.VOLT.0253,V253_DDR,35.1458,0.1703,23.3631,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-3.5794,-0.7663,-14.4255,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,8.7290,-0.0811,-2.8023,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,8.7290,-0.0811,-2.8023,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,8.7290,-0.0811,-2.8023,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,8.7290,-0.0811,-2.8023,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,35.4020,0.1642,23.6253,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,35.4020,0.1642,23.6253,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHUB,KCPLHUB_H,4.8217,-0.3658,-6.4249,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHUB17,KCPLHUB17_H,3.9395,-0.4215,-7.2514,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHUB18,KCPLHUB18_H,3.2184,-0.4205,-7.9736,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHUB19,KCPLHUB19_H,3.4091,-0.3951,-7.8083,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHUB20,KCPLHUB20_H,2.5150,-0.4425,-8.6550,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHUB21,KCPLHUB21_H,2.0033,-0.4349,-9.1742,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHUB22,KCPLHUB22_H,2.9564,-0.4308,-8.2252,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHUB23,KCPLHUB23_H,2.6873,-0.4439,-8.4813,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLHUB24,KCPLHUB24_H,1.7555,-0.4650,-9.3920,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,1.0325,0.0504,-10.6304,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,1.0325,0.0504,-10.6304,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,6.8170,-0.2801,-4.5153,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,6.8170,-0.2801,-4.5153,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,35.0188,0.1679,23.2384,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,35.0169,0.1661,23.2384,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,29.5510,0.2036,17.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,29.5510,0.2036,17.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,29.5510,0.2036,17.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,29.5510,0.2036,17.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,29.5510,0.2036,17.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,29.5510,0.2036,17.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,29.5510,0.2036,17.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,29.5510,0.2036,17.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,2.2592,-0.1245,-9.2288,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,17.4506,0.1582,5.6800,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KCPL_KCPL,KCPL_LA,20.5195,0.1474,8.7596,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KENN,KENN_LA,12.8443,0.3726,0.8592,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KEP2_SECI,KEP2_SECI_LA,-11.7908,-0.7546,-22.6487,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KERR_1,GRDAKERR_HYDUN1_RA,35.4765,0.2181,23.6459,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KERR_2,GRDAKERR_HYDUN2_RA,35.1680,0.2195,23.3361,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KERR_3,GRDAKERR_HYDUN3_RA,35.1680,0.2195,23.3361,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KERR_4,GRDAKERR_HYDUN4_RA,35.4765,0.2181,23.6459,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,8.7289,-0.0812,-2.8023,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,8.7289,-0.0812,-2.8023,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,9.7620,-0.0100,-1.8405,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,9.7620,-0.0100,-1.8405,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,6.5720,-0.0875,-4.9529,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,5.0341,-0.0690,-6.5094,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,5.0341,-0.0690,-6.5094,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-10.5416,-0.8844,-21.2697,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-10.5416,-0.8844,-21.2697,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-10.5416,-0.8844,-21.2697,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-6.5142,-0.3892,-17.7374,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-6.5142,-0.3892,-17.7374,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-10.6284,-0.8955,-21.3453,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-7.1963,-0.4739,-18.3348,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-3.6866,-0.2827,-15.0163,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,45.8992,-0.0452,34.3320,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,45.8992,-0.0452,34.3320,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,1.5328,-0.1988,-9.8808,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,1.5328,-0.1988,-9.8808,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,1.5328,-0.1988,-9.8808,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-8.1856,-0.6364,-19.1617,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-6.9254,-0.7611,-17.7767,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,2.6299,-0.2902,-8.6923,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,5.8308,0.0975,-5.8792,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LAFA,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LAM345,LAM345,-11.0167,-1.0354,-21.5938,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LEPA,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,4.2325,-0.2026,-7.1774,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_LES,LES_LA,4.2485,-0.2141,-7.1499,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,4.4282,-0.2424,-6.9419,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,4.1235,-0.2480,-7.2410,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,4.1235,-0.2480,-7.2410,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,4.1235,-0.2480,-7.2410,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,4.4298,-0.2408,-6.9419,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,4.4282,-0.2424,-6.9419,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_WAVERLY,LES_WAVERLY_H,4.3860,-0.2514,-6.9751,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,5.7804,-0.2335,-5.5986,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,5.7804,-0.2335,-5.5986,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,LGEE,LGEE,24.5213,0.2327,12.6761,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MALDEN,MALDEN_LA,13.8552,0.3610,1.8817,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MCWEST,MCWEST,9.8473,0.1342,-1.8993,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MDU,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,2.0818,-0.3496,-9.1810,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,3.3190,-0.0385,-8.2549,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,5.5488,0.3870,-6.4507,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MEAN_NPPD,NPPD_MEAN_LA,1.5420,-0.6082,-9.4623,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MEC,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MHEB,MHEB,11.2621,0.1858,-0.5362,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-3.9214,-0.6087,-14.9252,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-8.2939,-0.8161,-19.0903,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-3.9214,-0.6087,-14.9252,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-3.9214,-0.6087,-14.9252,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-8.2939,-0.8161,-19.0903,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-11.7651,-0.6455,-22.7321,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MISO,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-11.6759,-0.7244,-22.5640,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-11.6759,-0.7244,-22.5640,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-1.7325,-0.3517,-12.9932,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-12.1367,-0.9707,-22.7785,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-7.7614,-0.6865,-18.6874,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-12.7741,-0.8615,-23.5251,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-11.6215,-0.6929,-22.5411,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-12.9053,-0.8103,-23.7074,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-11.5524,-0.6333,-22.5316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-11.5524,-0.6333,-22.5316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-11.5524,-0.6333,-22.5316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-11.5524,-0.6333,-22.5316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-11.5524,-0.6333,-22.5316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,10.1129,0.0721,-1.5716,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,21.2584,0.2678,9.3782,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,21.2584,0.2678,9.3782,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,17.4479,0.1880,5.6474,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,14.3818,0.4587,2.3107,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MOWR,AECI,23.3716,0.2269,11.5322,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,14.6114,0.1647,2.8343,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,21.1518,0.2742,9.2652,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,1.5953,-0.5529,-9.4642,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,0.0300,-0.2563,-11.3262,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-16.2636,-0.7858,-27.0902,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,1.6335,-0.5148,-9.4642,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,10.0094,0.0597,-1.6627,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,10.0094,0.0597,-1.6627,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,10.0098,0.0600,-1.6627,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,10.0098,0.0600,-1.6627,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,0.2102,0.0749,-11.4771,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,0.2102,0.0749,-11.4771,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,0.2102,0.0749,-11.4771,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,0.1711,0.0357,-11.4771,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,0.2102,0.0749,-11.4771,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,0.2102,0.0749,-11.4771,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,0.2102,0.0749,-11.4771,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,15.6054,0.3319,3.6611,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,11.4925,0.0579,-0.1779,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,10.2251,0.0151,-1.4025,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,10.2251,0.0152,-1.4025,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,10.2251,0.0152,-1.4025,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,21.3282,0.1675,9.5483,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,21.3282,0.1675,9.5483,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,MPS_MPS,MPS_LA,11.5991,0.1787,-0.1921,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MSTNG,SPSMSTNGPLT1,-8.5455,0.1470,-20.3050,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MSTNG4,SPSMSTNGUN4_RA,-8.5795,0.1130,-20.3050,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MSTNG5,SPSMSTNGUN5_RA,-8.5455,0.1470,-20.3050,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,-8.5455,0.1470,-20.3050,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NBSO,PJM,21.2309,0.1774,9.4410,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,3.4510,-0.5347,-7.6267,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,3.4492,-0.5366,-7.6267,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-14.8131,-1.4406,-24.9850,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NHC1,VACS,33.5123,0.3646,21.5353,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,5.6269,-0.1729,-5.8126,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,5.6269,-0.1729,-5.8126,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,5.6269,-0.1729,-5.8126,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,3.6397,-0.7693,-7.2034,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,2.0064,-0.6737,-8.9323,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,3.1928,-0.4378,-7.9819,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,6.2621,-0.3078,-5.0426,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,2.0064,-0.6737,-8.9323,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.HUB.PY2018,NPPDPY18_H,1.6405,-0.6460,-9.3259,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,1.7221,-0.6387,-9.2516,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,1.6812,-0.6355,-9.2958,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,1.7537,-0.6235,-9.2352,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,6.4118,-0.3544,-4.8462,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,0.3598,-0.7319,-10.5208,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,0.3598,-0.7319,-10.5208,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-0.2226,-0.5711,-11.2640,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,6.4118,-0.3544,-4.8462,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,5.1465,-0.7908,-5.6752,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,1.5965,-0.9294,-9.0866,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-1.8616,-0.7184,-12.7556,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,1.5965,-0.9294,-9.0866,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,2.5706,-0.8082,-8.2337,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,1.3263,-0.8527,-9.4335,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,3.8350,-0.1305,-7.6470,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,2.0064,-0.6737,-8.9323,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-1.5008,-0.7381,-12.3752,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,0.3598,-0.7319,-10.5208,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,0.3598,-0.7319,-10.5208,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,0.8667,-0.5211,-10.2247,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,0.8261,-0.5325,-10.2539,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,0.8261,-0.5325,-10.2539,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,1.4756,-0.2676,-9.8693,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-6.2700,-0.0959,-17.7866,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,2.2609,-0.5082,-8.8434,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,3.9925,-0.6138,-7.0061,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-10.6331,-0.0413,-22.2043,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-13.0000,-0.0457,-24.5668,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.NELI.DDR,NELI_DDR,5.9587,-0.4471,-5.2066,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.NPPM.1058,SH1058_DDR,5.0661,-0.1062,-6.4402,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,1.4691,-0.3527,-9.7906,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,2.0064,-0.6737,-8.9323,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,3.1928,-0.4378,-7.9819,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,6.4118,-0.3544,-4.8462,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.TECH.1,KEARNE_DDR,1.6733,-0.2555,-9.6837,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,3.6647,-0.9578,-6.9900,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,3.6647,-0.9578,-6.9900,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,6.2218,-0.4157,-4.9750,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD.VOLT.0236,V236_DDR,3.4858,-0.1363,-7.9904,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD2017HUB,NPPD2017HUB_H,1.6407,-0.6434,-9.3283,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,4.8100,-0.3831,-6.4193,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,3.6397,-0.7693,-7.2034,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,1.5700,-1.1031,-8.9393,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,1.5700,-1.1031,-8.9393,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,3.5478,-0.1625,-7.9021,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,3.4954,-0.1266,-7.9904,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,3.2477,-0.2961,-8.0687,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,0.9290,-0.5365,-10.1469,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,4.8235,-0.3487,-6.4402,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,4.8235,-0.3487,-6.4402,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,4.8235,-0.3487,-6.4402,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,2.3991,-0.4939,-8.7194,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,3.1930,-0.4820,-7.9374,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,2.6153,-0.3005,-8.6966,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,6.0854,-0.9888,-4.5383,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,6.1487,-0.9255,-4.5383,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-0.1481,-0.7873,-10.9732,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-0.3433,-0.7889,-11.1669,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,2.8671,-0.4212,-8.3242,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,2.8567,-0.4315,-8.3242,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,2.8567,-0.4315,-8.3242,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,2.8739,-0.3999,-8.3386,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,5.1465,-0.7908,-5.6752,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,2.8378,-0.4021,-8.3725,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,3.8074,-0.3072,-7.4978,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,2.4127,-0.4643,-8.7355,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,2.4016,-0.4727,-8.7382,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,2.4077,-0.4635,-8.7413,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,2.4077,-0.4635,-8.7413,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,2.3991,-0.4939,-8.7194,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,2.3506,-0.5424,-8.7194,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,4.7424,-0.3637,-6.5064,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,2.9326,-0.2347,-8.4451,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-0.0784,-0.7534,-10.9375,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,4.7898,-0.8870,-5.9357,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-2.1763,-0.7590,-13.0297,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,5.2469,0.0747,-6.4402,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,5.9587,-0.4471,-5.2066,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,0.0579,-0.7637,-10.7908,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,0.0579,-0.7637,-10.7908,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_NPPD,NPPD_LA,3.3509,-0.3582,-7.9033,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,3.8074,-0.3072,-7.4978,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,3.8074,-0.3072,-7.4978,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,2.2366,-0.3106,-9.0653,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,0.7225,-0.6596,-10.2304,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NSB,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,NSP,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NSSO,PJM,21.2309,0.1774,9.4410,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,NYIS,PJM,21.2309,0.1774,9.4410,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-15.2583,-1.2631,-25.6076,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-21.6887,-0.7945,-32.5067,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-3.9829,-0.6211,-14.9743,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-3.9829,-0.6211,-14.9743,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-14.6757,-1.4426,-24.8455,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-30.0730,-0.8426,-40.8428,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-101.2503,-0.5072,-112.3556,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-47.4221,-0.7558,-58.2787,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-25.7818,-0.7848,-36.6094,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-21.7380,-0.7960,-32.5544,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,4.3827,-0.2986,-6.9312,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-25.7818,-0.7848,-36.6094,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-14.8535,-1.4027,-25.0633,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-11.7651,-0.6455,-22.7321,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-15.4818,-1.2271,-25.8671,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,37.2596,-0.1269,25.7741,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-21.7380,-0.7960,-32.5544,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-18.9703,-0.7687,-29.8141,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-3.2458,-0.7469,-14.1114,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-13.4166,-0.6651,-24.3639,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-45.9229,-0.1401,-57.3953,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-11.7651,-0.6455,-22.7321,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-11.7651,-0.6455,-22.7321,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-21.7380,-0.7960,-32.5544,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-11.2050,-0.6302,-22.1873,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.NUEN.LAM1,LAM1_DDR,34.2070,0.7841,21.8105,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.NUEN.MDT2,MDT2_DDR,4.3827,-0.2986,-6.9312,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.NUEN.MDT3,MDT3_DDR,4.3827,-0.2986,-6.9312,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-11.5127,-0.6264,-22.4987,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,1.8400,-0.3359,-9.4366,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,1.8400,-0.3359,-9.4366,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,1.8400,-0.3359,-9.4366,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,8.0339,-0.2840,-3.2946,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,8.0339,-0.2840,-3.2946,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,1.8400,-0.3359,-9.4366,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,1.8400,-0.3359,-9.4366,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-21.7380,-0.7960,-32.5544,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,21.8927,0.4470,9.8332,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-14.8535,-1.4027,-25.0633,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-34.7738,-0.2927,-46.0936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-18.9703,-0.7687,-29.8141,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,32.5276,0.4656,20.4496,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-19.8239,-0.6417,-30.7947,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-19.8239,-0.6417,-30.7947,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-19.8239,-0.6417,-30.7947,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-19.8239,-0.6417,-30.7947,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-21.2500,-1.1173,-31.7452,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-25.9522,-0.7637,-36.8010,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-21.6887,-0.7945,-32.5067,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-31.3306,-0.7431,-42.2000,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-31.3306,-0.7431,-42.2000,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-30.4385,-0.1945,-41.8564,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-15.8722,-0.7257,-26.7589,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-15.8722,-0.7257,-26.7589,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-15.8722,-0.7257,-26.7589,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0033,FOSTER_DDR,14.6342,-0.2610,3.2827,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,34.8059,0.4395,22.7539,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0035,TARBY_DDR,34.0766,0.6296,21.8345,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,34.8059,0.4395,22.7539,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,34.5664,0.3189,22.6351,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,34.5664,0.3189,22.6351,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-42.8481,-0.2089,-54.2516,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0040,TROSPER_DDR,18.4630,-0.2400,7.0906,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,18.5146,-0.2391,7.1413,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,33.0569,0.5708,20.8737,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0115,V115_DDR,5.4443,-0.2925,-5.8756,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0116,V116_DDR,72.3665,-0.1134,60.8674,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0118,V118_DDR,21.9313,-0.0247,10.3435,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0125,V125_DDR,33.1796,0.6662,20.9010,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0126,V126_DDR,33.5167,0.3596,21.5446,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0129,V129_DDR,-1.5712,-0.5871,-12.5966,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,46.3217,-0.3004,35.0097,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0134,V134_DDR,34.1355,0.4421,22.0810,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0138,V138_DDR,33.0882,0.3077,21.1680,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,39.1214,-0.2442,27.7532,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0143,V143_DDR,33.7214,0.2468,21.8621,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0149,V149_DDR,-10.4277,-0.5841,-21.4560,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0150,V150_DDR,-10.4601,-0.6215,-21.4511,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0155,V155_DDR,32.6974,0.2505,20.8344,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0156,V156_DDR,46.3217,-0.3004,35.0097,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0166,V166_DDR,33.7043,0.6647,21.4272,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,38.2725,-0.2486,26.9087,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-10.4601,-0.6215,-21.4511,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0170,V170_DDR,-11.6420,-0.6261,-22.6283,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-21.1040,-0.5614,-32.1551,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0176,V176_DDR,-10.4601,-0.6215,-21.4511,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0177,V177_DDR,-18.3279,-1.0718,-28.8686,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,30.6114,-0.2483,19.2472,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-7.1502,-0.6419,-18.1208,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0195,V195_DDR,135.9369,0.5572,123.7672,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0197,V197_DDR,35.2876,0.4255,23.2496,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0198,V198_DDR,33.7043,0.6647,21.4272,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0208,V208_DDR,136.0000,0.5673,123.8202,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0209,V209_DDR,136.0000,0.5673,123.8202,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,34.9476,0.3210,23.0141,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0216,V216_DDR,18.5271,-0.2396,7.1542,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0219,V219_DDR,32.6974,0.2505,20.8344,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0220,V220_DDR,-10.4601,-0.6215,-21.4511,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0224,V224_DDR,4.7646,-0.3061,-6.5417,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0225,V225_DDR,4.7652,-0.3055,-6.5417,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0226,V226_DDR,4.7646,-0.3061,-6.5417,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0227,V227_DDR,4.7646,-0.3061,-6.5417,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0229,V229_DDR,-37.7615,-0.1557,-49.2183,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0231,V231_DDR,21.0300,0.0511,9.3664,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0238,V238_DDR,-21.3296,-0.8373,-32.1047,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.VOLT.0242,V242_DDR,32.8747,0.2784,20.9839,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-16.6717,-1.4880,-26.7961,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-11.7651,-0.6455,-22.7321,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-21.6283,-0.7803,-32.4605,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-15.4721,-1.2174,-25.8671,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-16.6717,-1.4880,-26.7961,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-15.3983,-1.3337,-25.6770,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-53.0970,-0.7186,-63.9908,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEHL7,OKGEHL7_H,29.1202,-0.2327,17.7404,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEHL8,OKGEHSL1UN8_RA,29.1202,-0.2327,17.7404,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEHL910,OKGEHSL1PLT2,29.1202,-0.2327,17.7404,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-15.4103,-1.2827,-25.7400,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEMCC,OKGEMCCLAIPLT1,1.3792,-0.4305,-9.8027,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,30.5942,0.1857,18.7960,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,30.5942,0.1857,18.7960,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,30.5942,0.1857,18.7960,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,20.7377,-0.4076,9.5329,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,20.7377,-0.4076,9.5329,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,20.7377,-0.4076,9.5329,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,20.7377,-0.4076,9.5329,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGESM1,OKGESEMINOLEUN1_RA,17.4805,-0.1937,6.0618,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGESM2,OKGESEMINOLEUN2_RA,13.0645,-0.2187,1.6707,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGESM3,OKGESEMINOLEUN3_RA,13.0645,-0.2187,1.6707,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGESO1,OKGESONR1UN1_RA,-64.0708,-0.7027,-74.9805,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGESO2,OKGESONR1UN2_RA,-31.3306,-0.7431,-42.2000,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-15.4865,-1.3589,-25.7400,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-14.8920,-1.4719,-25.0326,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGETINK5A,OKGETINK5UN1_RA,16.1807,-0.2700,4.8383,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGETINK5B,OKGETINK5UN2_RA,16.1807,-0.2700,4.8383,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-15.7192,-1.0585,-26.2732,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-21.6887,-0.7945,-32.5067,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,33.0145,0.7401,20.6619,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-11.7651,-0.6455,-22.7321,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE_OKGE,OKGE_LA,19.3313,-0.1312,7.8501,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-34.7738,-0.2927,-46.0936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-15.7486,-1.0879,-26.2732,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMLP,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,39.7973,0.1310,28.0539,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,33.0681,0.7073,20.7483,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-0.8314,-0.3163,-12.1277,11.6126\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-101.1492,-0.4060,-112.3556,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-8.5400,-0.7178,-19.4347,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-25.7818,-0.7848,-36.6094,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-16.3424,-1.1397,-26.8152,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-6.8577,-1.1576,-17.3126,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,174.1500,0.1424,162.3951,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-101.1822,-0.4390,-112.3556,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-101.1822,-0.4390,-112.3556,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_SPP,OMPA_SPP_LA,-1.8372,-0.4563,-12.9934,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-16.6717,-1.4880,-26.7961,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,34.9703,0.1249,23.2329,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,34.9703,0.1249,23.2329,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,34.9703,0.1249,23.2329,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,34.9703,0.1249,23.2329,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,ONT,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,5.6061,-0.1748,-5.8316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,5.6061,-0.1748,-5.8316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,5.6061,-0.1748,-5.8316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,5.6061,-0.1748,-5.8316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,5.6061,-0.1748,-5.8316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,5.6061,-0.1748,-5.8316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,5.6061,-0.1748,-5.8316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,5.6061,-0.1748,-5.8316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,5.6061,-0.1748,-5.8316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,5.6193,-0.1577,-5.8354,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,5.6269,-0.1729,-5.8126,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,5.4187,-0.1407,-6.0531,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,5.4534,-0.1451,-6.0140,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,5.4534,-0.1451,-6.0140,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD_GLDN,OPPD_GLDN_LA,5.4733,-0.1738,-5.9654,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,5.6208,-0.1652,-5.8265,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,5.1465,-0.7908,-5.6752,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,4.0938,-0.3251,-7.1935,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,5.6268,-0.1725,-5.8132,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD_OPPD,OPPD_LA,5.5737,-0.1397,-5.8991,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,5.4907,-0.1314,-5.9903,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,5.4775,-0.1353,-5.9996,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,OTP,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,OVEC,OVEC,23.1344,0.2116,11.3103,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PARAGOULD,PARAGOULD_LA,11.6671,0.3916,-0.3370,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,34.0145,0.1287,22.2734,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,34.0145,0.1287,22.2734,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,34.0145,0.1287,22.2734,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,34.0115,0.1721,22.2269,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,34.0115,0.1721,22.2269,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,34.0115,0.1721,22.2269,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PIGGOTT,PIGGOTT_LA,13.2045,0.3685,1.2236,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PJM,PJM,21.2309,0.1774,9.4410,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PLUM,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,POPLARBLUFF,POPLARBLUFF_LA,24.6618,0.3430,12.7064,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,9.6403,-0.0277,-1.9444,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,9.6403,-0.0277,-1.9444,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,9.7494,-0.0178,-1.8453,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,9.7494,-0.0178,-1.8453,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,10.6561,0.7969,-1.7532,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,10.6561,0.7969,-1.7532,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,9.8520,0.1278,-1.8883,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,8.8404,-0.3833,-2.3888,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-12.2390,-0.4693,-23.3822,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,85.9591,0.1595,74.1871,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,1.8258,0.1197,-9.9063,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-2.5331,-0.0240,-14.1215,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,38.8986,0.3571,26.9290,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,29.6585,0.4557,17.5904,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,9.8982,-0.0995,-1.6147,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,10.2532,0.1884,-1.5476,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,8.5769,-0.2851,-2.7505,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,22.0000,1.1681,9.2194,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,10.8880,0.2859,-1.0104,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,9.5549,0.0484,-2.1059,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,PUPP,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,RCEAST,RCEAST,5.8145,-0.8038,-4.9941,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SALINA_1,GRDASALINA1UN1_RA,35.4777,0.2194,23.6459,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SALINA_2,GRDASALINA1UN2_RA,35.4777,0.2194,23.6459,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SALINA_3,GRDASALINA1UN3_RA,35.4777,0.2194,23.6459,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SALINA_4,GRDASALINA1UN4_RA,35.4777,0.2194,23.6459,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SALINA_5,GRDASALINA1UN5_RA,35.4777,0.2194,23.6459,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SALINA_6,GRDASALINA1UN6_RA,35.4777,0.2194,23.6459,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SARPY_1,OPPDSARPYUN1_RA,5.5338,-0.1628,-5.9159,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SARPY_2,OPPDSARPYUN2_RA,5.5384,-0.1391,-5.9350,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SARPY_3,OPPDSARPYUN3_RA,5.5285,-0.1888,-5.8952,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SARPY_4,OPPDSARPYUN4_RA,5.5285,-0.1888,-5.8952,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SARPY_5,OPPDSARPYUN5_RA,5.5285,-0.1888,-5.8952,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SC,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SCEG,VACS,33.5123,0.3646,21.5353,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SCSE,SCSE,0.4948,-0.6797,-10.4380,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SEC,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-13.8472,-1.0877,-24.3720,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-13.8472,-1.0877,-24.3720,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-13.8472,-1.0877,-24.3720,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-10.7087,-0.8544,-21.4667,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-13.8472,-1.0877,-24.3720,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-11.7792,-1.0875,-22.3042,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-11.5724,-1.1270,-22.0579,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-11.5724,-1.1270,-22.0579,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-11.5539,-0.6348,-22.5316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-15.3980,-0.9625,-26.0479,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-6.5645,-0.4395,-17.7374,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-11.0854,-0.7649,-21.9330,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-6.5922,-0.9052,-17.2995,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-13.3527,-1.0964,-23.8687,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-6.5867,-0.8931,-17.3061,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-12.0815,-0.9781,-22.7158,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-11.8162,-0.6499,-22.7787,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-10.6540,-0.9426,-21.3238,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-10.6540,-0.9426,-21.3238,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-10.6540,-0.9426,-21.3238,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-10.6540,-0.9426,-21.3238,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-10.8653,-1.0041,-21.4736,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-11.7792,-1.0875,-22.3042,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI_SECI,SECI_LA,-10.3577,-0.7437,-21.2265,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-4.6134,-0.6044,-15.6214,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-4.6134,-0.6044,-15.6214,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-11.5539,-0.6348,-22.5316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SEHA,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-15.7486,-1.0879,-26.2732,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SERU,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SETH,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SGE,SGE,1.5254,-0.6525,-9.4345,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SMEP,MISO,20.2018,0.2111,8.3782,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SOCO,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPA,SPA,66.1553,0.4588,54.0840,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPC,SPC,10.4722,0.4726,-1.6129,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPPNORTH_HUB,SPPNORTH_H,4.6333,-0.2244,-6.7547,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPPSOUTH_HUB,SPPSOUTH_H,5.1100,-0.5525,-5.9499,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,16.2059,0.4273,4.1662,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,16.2059,0.4273,4.1662,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,16.5663,0.4018,4.5520,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,16.5663,0.4018,4.5520,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_NIXA,SPRM_NIXA_LA,14.6835,0.4244,2.6466,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_SPRM,SPRM_LA,16.0539,0.4695,3.9720,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,16.0715,0.3702,4.0888,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,16.0715,0.3702,4.0888,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,16.0511,0.3499,4.0888,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,16.0715,0.3702,4.0888,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-12.7837,-0.5164,-23.8797,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-14.0149,-0.7115,-24.9158,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-14.5422,-1.1851,-24.9696,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-14.5422,-1.1851,-24.9696,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-15.5456,-1.1817,-25.9763,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,-11.3365,-0.8431,-22.1059,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-14.6766,-1.8943,-24.3948,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,-3.0887,-0.6831,-14.0180,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-15.3487,-0.6766,-26.2846,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,-2.8516,0.0837,-14.5477,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,-1.8913,0.0870,-13.5908,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,-1.8913,0.0870,-13.5908,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,-2.8516,0.0837,-14.5477,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-14.5094,-1.1518,-24.9701,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-14.0149,-0.7115,-24.9158,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-14.3831,-1.0816,-24.9140,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-14.5619,-1.4458,-24.7286,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-14.2061,-0.9871,-24.8315,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-14.0877,-0.8108,-24.8893,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-14.3324,-1.0607,-24.8841,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-14.3982,-1.4561,-24.5545,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-14.3982,-1.4561,-24.5545,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-14.3982,-1.4561,-24.5545,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-14.3982,-1.4561,-24.5545,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GRID.WRAB,WRAB_DDR,-14.3611,-0.9380,-25.0356,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-14.3982,-1.4561,-24.5545,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-14.9426,-0.7162,-25.8389,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-14.9426,-0.7162,-25.8389,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-14.9072,-0.6790,-25.8407,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-14.9072,-0.6790,-25.8407,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-14.9072,-0.6790,-25.8407,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-14.9426,-0.7162,-25.8389,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-14.6163,-1.1652,-25.0636,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-14.6164,-1.1652,-25.0636,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-14.6156,-1.1652,-25.0628,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-14.8131,-1.4406,-24.9850,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,-2.5252,0.0594,-14.1971,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-15.3342,-0.6832,-26.2635,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-15.3342,-0.6832,-26.2635,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-15.3342,-0.6832,-26.2635,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-15.3342,-0.6832,-26.2635,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,-5.9754,0.1087,-17.6965,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,-2.9857,0.0645,-14.6627,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,-2.9857,0.0645,-14.6627,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-15.6992,-1.0384,-26.2732,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-14.5995,-1.1564,-25.0555,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-14.5995,-1.1564,-25.0555,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-14.6184,-1.1605,-25.0703,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-14.3611,-0.9380,-25.0356,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-14.4061,-1.2835,-24.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-14.4856,-1.1678,-24.9302,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-14.6757,-1.4426,-24.8455,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-14.4437,-1.0006,-25.0555,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-13.8065,-0.6317,-24.7873,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-13.8065,-0.6317,-24.7873,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-13.6453,-0.6478,-24.6100,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-15.4576,-1.0046,-26.0655,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-14.3736,-1.3409,-24.6451,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-14.4083,-1.6259,-24.3948,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-15.4459,-0.9929,-26.0655,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-14.4891,-1.1314,-24.9701,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-13.0556,-0.6428,-24.0252,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,-2.7492,-0.3436,-14.0180,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-13.0556,-0.6428,-24.0252,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,-12.8501,-0.4648,-23.9977,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-14.5232,-1.2735,-24.8622,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,-1.7678,0.5739,-13.9542,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,-1.7661,0.5756,-13.9542,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,-2.2584,0.3560,-14.2268,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,-3.0187,0.0711,-14.7022,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,-1.7213,0.3767,-13.7105,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-11.0167,-1.0354,-21.5938,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-14.4146,-0.9899,-25.0372,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-13.4496,-0.6195,-24.4425,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-13.4496,-0.6195,-24.4425,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-13.0556,-0.6428,-24.0252,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-15.3547,-0.6168,-26.3503,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,-6.4904,0.4218,-18.5247,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-12.8940,-0.0986,-24.4079,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-13.3593,-0.3819,-24.5899,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-14.4341,-0.7279,-25.3187,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,-1.7678,0.5739,-13.9542,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,-1.3618,0.7686,-13.7429,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,-1.5099,0.6205,-13.7429,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-15.3397,-0.8866,-26.0655,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-13.1635,-0.3799,-24.3960,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-14.3218,-1.2677,-24.6666,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-14.3417,-1.2874,-24.6668,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0163,V163_DDR,-14.3410,-0.9936,-24.9599,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0168,V168_DDR,-15.4933,-0.7442,-26.3615,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0180,V180_DDR,-1.3618,0.7686,-13.7429,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0181,V181_DDR,-14.2102,-1.1680,-24.6546,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0182,V182_DDR,-1.5684,0.4878,-13.6687,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0199,V199_DDR,-7.2915,0.3454,-19.2494,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0200,V200_DDR,-2.5144,0.3435,-14.4703,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.VOLT.0235,V235_DDR,-14.4061,-1.2835,-24.7350,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-14.6766,-1.8943,-24.3948,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,-3.0887,-0.6831,-14.0180,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-14.6619,-1.3255,-24.9489,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-14.5361,-1.0953,-25.0532,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS_SPS,SPS_LA,-7.5403,-0.0554,-19.0974,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,-9.3048,-0.1857,-20.7316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,SSCN_NPPD,SSCN_NPPD_LA,4.9999,-0.2331,-6.3794,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,17.9776,0.3256,6.0396,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,17.9776,0.3256,6.0396,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,TAL,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,TEC,SOUC,32.7300,0.3819,20.7357,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,4.7898,-0.8870,-5.9357,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,TVA,TVA,34.3086,0.3464,22.3498,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,UCUHUB,UCUHUB_H,0.0728,-0.1614,-11.3783,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,UCUHUB17,UCUHUB17_H,-4.2638,-0.4368,-15.4395,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,UCUHUB18,UCUHUB18_H,-1.9196,-0.3564,-13.1756,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,UCUHUB19,UCUHUB19_H,-5.4747,-0.4227,-16.6644,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,UCUHUB20,UCUHUB20_H,-5.0885,-0.4114,-16.2895,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,UCUHUB21,UCUHUB21_H,-6.6378,-0.4841,-17.7662,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,UCUHUB22,UCUHUB22_H,-6.5030,-0.5146,-17.6009,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,UCUHUB23,UCUHUB23_H,-6.8024,-0.5213,-17.8936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,UCUHUB24,UCUHUB24_H,-3.6886,-0.4507,-14.8503,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,10.5422,0.5675,-1.6377,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,10.5422,0.5675,-1.6377,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,9.5729,-0.1577,-1.8819,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,9.5729,-0.1577,-1.8819,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,10.3012,-0.1828,-1.1284,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,9.7227,-0.0912,-1.7986,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,9.7227,-0.0912,-1.7986,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,10.5422,0.5675,-1.6377,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,10.3749,-0.1741,-1.0634,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,10.5702,0.2530,-1.2952,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,9.3332,0.0041,-2.2833,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,6.6438,-1.0661,-3.9025,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,10.4193,0.5344,-1.7276,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,10.4193,0.5344,-1.7276,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,8.6168,-0.9805,-2.0151,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,9.5652,-0.1888,-1.8585,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,10.0150,-0.1908,-1.4066,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,8.7963,-0.2086,-2.6076,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,9.4238,0.0879,-2.2766,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,9.3891,-0.2106,-2.0128,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,9.2260,-0.3714,-2.0151,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,9.2260,-0.3714,-2.0151,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,9.5934,-0.1625,-1.8566,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,6.2561,-1.1753,-4.1811,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,9.9748,0.6157,-2.2534,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,19.7700,0.1530,8.0045,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,19.7700,0.1530,8.0045,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,19.7700,0.1530,8.0045,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,10.0480,0.1732,-1.7376,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,10.0480,0.1732,-1.7376,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,10.0480,0.1732,-1.7376,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,10.7276,0.7166,-1.6015,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,10.0012,-0.1548,-1.4564,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,10.0012,-0.1548,-1.4564,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,1.0144,-0.6666,-9.9315,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,8.6271,-0.0874,-2.8979,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,10.3382,0.2419,-1.5162,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,7.2997,-0.3349,-3.9779,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,5.7243,-1.4825,-4.4056,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,9.4067,-0.2597,-1.9461,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,10.4800,0.5640,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,10.4800,0.5640,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,10.4794,0.5634,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,10.4800,0.5640,-1.6964,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,10.3717,0.4663,-1.7071,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,10.3717,0.4663,-1.7071,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,10.3717,0.4663,-1.7071,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,10.3717,0.4663,-1.7071,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,10.3717,0.4663,-1.7071,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,10.3717,0.4663,-1.7071,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,10.3717,0.4663,-1.7071,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,6.7493,-0.8126,-4.0506,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,10.5136,0.0620,-1.1608,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,7.9153,-0.0691,-3.6281,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,7.9153,-0.0691,-3.6281,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,7.1674,-0.3698,-4.0753,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,7.1674,-0.3698,-4.0753,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,10.1253,-0.0308,-1.4564,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,10.2346,0.0005,-1.3783,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,9.0455,-0.2492,-2.3178,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,6.4890,-0.9716,-4.1518,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,10.0936,-0.0370,-1.4818,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,10.3012,-0.1828,-1.1284,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,10.3012,-0.1828,-1.1284,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,8.7963,-0.2086,-2.6076,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,5.7622,-0.8465,-5.0038,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,8.5985,-0.4003,-2.6137,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,6.3832,-1.0482,-4.1811,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,9.3027,-0.3143,-1.9955,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.FSE,WAUE.FSE_H,5.2767,-0.5306,-5.8051,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,9.8542,0.0411,-1.7994,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,9.8173,0.0171,-1.8122,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,6.1071,-1.0777,-4.4277,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,6.1714,-1.0254,-4.4156,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,10.2130,-0.1606,-1.2388,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,10.2029,-0.2229,-1.1866,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-13.4600,-0.8566,-24.2159,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,6.6438,-1.0661,-3.9025,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-5.6800,-0.6467,-16.6458,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,7.8529,-0.2573,-3.5022,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,7.8532,-0.2571,-3.5022,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,7.8538,-0.2565,-3.5022,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,9.3390,-0.1824,-2.0910,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,5.7622,-0.8465,-5.0038,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,9.9575,0.0899,-1.7448,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,8.5596,-0.2862,-2.7667,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,9.9256,0.5666,-2.2534,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,8.7231,0.1673,-3.0566,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,9.4614,0.0666,-2.2176,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,11.1989,-0.0795,-0.3341,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,8.9877,-0.0725,-2.5522,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,8.9847,-0.2641,-2.3637,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,7.2997,-0.3349,-3.9779,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,12.5794,0.5164,0.4505,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,8.7848,-0.2194,-2.6083,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,12.3508,0.3805,0.3578,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,9.7691,0.1186,-1.9619,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,5.7804,-0.2335,-5.5986,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NTWK,WAUE.NTWK_H,8.9358,-0.1343,-2.5423,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,10.0665,0.5475,-2.0934,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,10.0665,0.5475,-2.0934,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,6.5895,-1.1425,-3.8804,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,6.6432,-1.0800,-3.8892,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,9.9127,-0.1281,-1.5716,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,6.5895,-1.1425,-3.8804,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,11.0573,0.0615,-0.6166,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,8.0231,-0.5039,-3.0854,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,7.2997,-0.3349,-3.9779,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,8.7124,-0.2454,-2.6547,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,7.4185,-1.1085,-3.0854,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,4.9105,-1.3965,-5.3055,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,5.3750,-1.4041,-4.8334,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,9.5617,-0.1818,-1.8690,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,4.1722,-1.0504,-6.3898,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,10.1652,0.0225,-1.4698,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,7.2219,-0.7725,-3.6180,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,6.4890,-0.9716,-4.1518,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.VOLT.0152,V152_DDR,10.9271,0.8603,-1.5457,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE.VOLT.0172,V172_DDR,10.4280,0.5171,-1.7015,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_BEPM,WAUE_BEPM_LA,10.2548,0.2346,-1.5922,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,10.0987,0.1032,-1.6169,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,8.7273,0.1741,-3.0592,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_EWA,WAUE_EWA_LA,5.8701,-0.7748,-4.9676,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,8.2027,-0.4305,-2.9793,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_HMMU,WAUE_HMMU_LA,7.0630,0.0034,-4.5529,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,11.5701,-0.0418,-0.0006,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_MECB,WAUE_MECB_LA,8.2929,0.1581,-3.4777,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_MMPA,WAUE_MMPA_LA,11.1839,0.3321,-0.7606,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_MRES,WAUE_MRES_LA,9.2814,-0.0692,-2.2618,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,10.8229,0.6377,-1.4272,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,9.8542,0.0411,-1.7994,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,7.9194,-0.4140,-3.2791,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_OTP,WAUE_OTP_LA,11.8070,0.6164,-0.4219,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_OTPW,WAUE_OTPW_LA,16.6531,0.7460,4.2946,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM,WAUE_UGPM_LA,9.6457,0.0587,-2.0254,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,9.9874,0.1448,-1.7699,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,8.9654,-0.0720,-2.5751,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,6.4553,-0.3452,-4.8120,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,5.8701,-0.7748,-4.9676,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,7.0630,0.0034,-4.5529,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,8.2015,-0.3998,-3.0111,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,9.8542,0.0411,-1.7994,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,11.1839,0.3321,-0.7606,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,9.1097,-0.1043,-2.3985,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,7.5502,-0.5170,-3.5452,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,11.1830,0.6146,-1.0440,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-16.5095,-1.3307,-26.7913,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-12.8755,-0.9796,-23.5084,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,0.6250,-0.9625,-10.0250,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,69.7134,0.2818,57.8192,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,69.7134,0.2818,57.8192,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-8.7996,-1.5467,-18.8654,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,64.4307,0.3542,52.4641,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,58.2254,0.3433,46.2696,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,17.0000,-0.7061,6.0936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,17.0000,-0.7061,6.0936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,17.0000,-0.7061,6.0936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,17.0000,-0.7061,6.0936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,16.9745,-0.7315,6.0936,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,17.0000,-0.7061,6.0936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,17.0000,-0.7061,6.0936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,17.0000,-0.7061,6.0936,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,9.8703,-0.6737,-1.0684,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-14.6757,-1.4426,-24.8455,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-22.2876,-1.2044,-32.6957,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-17.0155,-1.2358,-27.3922,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-14.4830,-1.7007,-24.3948,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_ENMC,WFEC_ENMC_LA,-6.6314,0.0293,-18.2731,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-21.7380,-0.7960,-32.5544,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,30.8163,0.1843,19.0196,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,-5.1049,0.0721,-16.7894,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-16.5095,-1.3307,-26.7913,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-16.5095,-1.3307,-26.7913,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-16.5095,-1.3307,-26.7913,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_OKGE,WFEC_OKGE_LA,4.3715,0.0969,-7.3378,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,57.2303,0.3395,45.2783,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-12.8023,-1.5395,-22.8753,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-8.7584,-1.6790,-18.6918,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_WFEC,WFEC_LA,21.4757,-0.2633,10.1265,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,-5.1049,0.0721,-16.7894,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-4.6935,-0.6289,-15.6771,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-9.4971,-1.0268,-20.0827,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-1.7922,-0.3565,-13.0481,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-1.7922,-0.3565,-13.0481,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-1.7922,-0.3565,-13.0481,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-1.7922,-0.3565,-13.0481,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-1.7922,-0.3565,-13.0481,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-1.7922,-0.3565,-13.0481,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-1.7922,-0.3565,-13.0481,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,0.5629,0.4430,-11.4925,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-3.5089,-0.5050,-14.6164,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-17.7071,-0.7534,-28.5661,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-17.7071,-0.7534,-28.5661,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-17.7071,-0.7534,-28.5661,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-15.2686,-0.9605,-25.9205,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-15.2686,-0.9605,-25.9205,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-12.4501,-0.6783,-23.3843,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-12.4501,-0.6783,-23.3843,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-12.4501,-0.6783,-23.3843,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-3.5089,-0.5050,-14.6164,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,2.6717,0.0424,-8.9832,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-8.0212,-0.5080,-19.1257,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-8.0212,-0.5080,-19.1257,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-8.0212,-0.5080,-19.1257,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-8.0210,-0.5077,-19.1257,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,2.6717,0.0424,-8.9832,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-12.5846,-1.1100,-23.0871,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-31.0027,-0.3890,-42.2262,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.JEC.1,WRJEFFUN10_RA,-0.6887,-0.3096,-11.9915,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.JEC.2,WRJEFFUN11_RA,-0.7257,-0.3120,-12.0261,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.JEC.3,WRJEFFUN12_RA,-0.7684,-0.3547,-12.0261,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-23.6002,-0.7761,-34.4365,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-16.2576,-0.7798,-27.0902,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-16.2576,-0.7798,-27.0902,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.LEC.4,WRLECUN26_RA,4.2011,0.0007,-7.4120,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.LEC.5,WRLECUN27_RA,3.5658,0.0245,-8.0711,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-6.5416,-0.4198,-17.7342,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-6.5416,-0.4198,-17.7342,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-6.5416,-0.4198,-17.7342,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-6.4977,-0.3965,-17.7137,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-4.6134,-0.6044,-15.6214,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-4.6134,-0.6044,-15.6214,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-6.4129,-0.8132,-17.2121,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-4.3136,-0.5643,-15.3617,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-4.3136,-0.5643,-15.3617,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-6.9311,-0.7668,-17.7767,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-4.6134,-0.6044,-15.6214,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,1.0255,-0.5193,-10.0676,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-4.2810,-0.5686,-15.3249,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-16.2600,-0.7823,-27.0902,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,59.1985,0.3522,47.2338,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-7.3294,-1.1518,-17.7901,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-1.7922,-0.3565,-13.0481,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-4.7651,-0.7876,-15.5899,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,2.6717,0.0424,-8.9832,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-3.5089,-0.5050,-14.6164,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-14.6426,-0.5610,-25.6941,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.THAYERLD,WR.THAYERLD_LA,23.7099,0.3683,11.7291,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-15.5697,-0.5588,-26.6233,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0106,V106_DDR,-14.5825,-0.5356,-25.6594,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0139,WR.VOLT.0139_H,8.2302,0.1224,-3.5046,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-4.7684,-0.3997,-15.9811,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0146,WR.VOLT.0146_H,4.6788,0.0947,-7.0284,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0147,WR.VOLT.0147_H,4.6788,0.0947,-7.0284,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0148,WR.VOLT.0148_H,3.8363,0.0797,-7.8558,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-14.0008,-0.4486,-25.1647,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0157,V157_DDR,4.5390,0.0815,-7.1549,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0158,V158_DDR,4.6788,0.0947,-7.0284,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0159,WR.VOLT.0159_H,4.6788,0.0947,-7.0284,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-14.8743,-0.6072,-25.8795,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0173,V173_DDR,-6.6344,-0.4812,-17.7657,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0174,V174_DDR,-14.5588,-0.5492,-25.6220,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0184,V184_DDR,-14.1156,-0.6173,-25.1108,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-14.7889,-0.5536,-25.8477,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0186,V186_DDR,-14.7040,-0.5893,-25.7272,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-14.3239,-0.5925,-25.3438,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-15.4231,-0.5373,-26.4982,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-7.2558,-0.3397,-18.5286,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-2.9444,-0.2920,-14.2649,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-2.1261,-0.3162,-13.4224,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-2.1261,-0.3162,-13.4224,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-2.9444,-0.2920,-14.2649,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0245,V245_DDR,-14.7967,-0.5541,-25.8551,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.VOLT.0248,V248_DDR,-14.5825,-0.5356,-25.6594,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-19.2334,-0.7143,-30.1316,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,1.6219,-0.0394,-9.9512,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.WOLF,WRWOLFUN15_RA,-4.7003,-0.8492,-15.4636,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-12.5846,-1.1100,-23.0871,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,0.5058,0.3858,-11.4925,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-17.7071,-0.7534,-28.5661,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-17.7071,-0.7534,-28.5661,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-17.7071,-0.7534,-28.5661,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-17.7071,-0.7534,-28.5661,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-15.6499,-0.4242,-26.8382,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-4.6924,-0.4018,-15.9030,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-15.9802,-0.5661,-27.0266,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-15.9802,-0.5661,-27.0266,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-15.9802,-0.5661,-27.0266,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-15.9802,-0.5661,-27.0266,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-2.8990,-0.2137,-14.2977,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-2.8990,-0.2137,-14.2977,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-2.8990,-0.2137,-14.2977,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-2.8990,-0.2137,-14.2977,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-2.8990,-0.2137,-14.2977,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-2.8990,-0.2137,-14.2977,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-32.0906,-0.5140,-43.1891,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-32.0906,-0.5140,-43.1891,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-35.0630,-0.5269,-46.1485,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-35.0630,-0.5269,-46.1485,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_MIDW,WR_MIDW_LA,-6.3883,-0.6431,-17.3577,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,15.0777,0.3166,3.1487,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,11.6673,0.1842,-0.1293,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-7.9959,-0.5817,-19.0266,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_SEG,WR_SEG_LA,6.7024,0.2478,-5.1578,11.6124\n03/19/2025 13:00:00,03/19/2025 18:00:00,WR_WR,WR_LA,-5.2684,-0.3131,-16.5678,11.6125\n03/19/2025 13:00:00,03/19/2025 18:00:00,YAD,VACS,33.5123,0.3646,21.5353,11.6124\n03/19/2025 14:00:00,03/19/2025 19:00:00,AEC,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,AECC_CSWS,CSWS_AECC_LA,32.4000,0.5772,19.5320,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,35.6655,0.4052,22.9695,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,31.3492,0.7572,18.3012,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,35.6861,0.2936,23.1018,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,27.3557,0.4926,14.5723,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,32.0452,0.3257,19.4287,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,27.6965,0.3588,15.0469,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,AECI,AECI,22.5182,0.2401,9.9874,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,AEPM_CSWS,CSWS_LA,31.9080,0.5352,19.0820,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,ALTW,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,AMRN,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-16.4454,-0.8438,-27.8923,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,BBA,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BCA,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BEPM.ER01.DDR,ER01_DDR,3.1028,-1.3803,-7.8077,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BEPM_ER01,BEPM_ER01_LA,3.1028,-1.3803,-7.8077,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,2.9389,-0.4342,-8.9176,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-0.3235,-0.3469,-12.2674,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BEPM_UM01,BEPM_UM01_LA,7.6213,0.5612,-5.2306,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,BLKW,BLKW,-9.3904,-0.6270,-21.0541,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-25.6877,-1.1188,-36.8597,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-25.6877,-1.1188,-36.8597,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,13.6436,-1.0308,2.3836,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-25.6679,-1.0990,-36.8597,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BRAZ,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BUBA,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-10.7285,-1.1841,-21.8351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-14.0000,-0.7223,-25.5685,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-14.0000,-0.7223,-25.5685,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-14.0000,-0.7223,-25.5685,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-14.0000,-0.7223,-25.5685,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-14.0000,-0.7223,-25.5685,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-10.6270,-0.5484,-22.3694,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,3.6702,-0.1858,-8.4348,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,3.6702,-0.1858,-8.4348,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CLEC,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,35.0528,0.2859,22.4761,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,COWP,COWP_LA,18.1964,0.3772,5.5285,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,18.1964,0.3772,5.5285,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,18.1964,0.3772,5.5285,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CPLE,VACS,24.2738,0.4424,11.5406,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CPLW,VACS,24.2738,0.4424,11.5406,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,23.3086,0.5113,10.5066,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,23.3086,0.5113,10.5066,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,23.3086,0.5113,10.5066,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,23.3086,0.5113,10.5066,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CRTH_SPA,WRCRTH_SPA_LA,34.0116,0.0941,21.6267,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,27.8180,1.3101,14.2171,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-1.2623,-0.6190,-12.9340,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,27.6965,0.3588,15.0469,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,35.6861,0.2936,23.1018,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,27.8111,1.3008,14.2195,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,27.6534,0.9560,14.4066,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,27.7591,1.1838,14.2845,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,27.7591,1.1838,14.2845,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,35.4262,0.3283,22.8071,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,35.4262,0.3283,22.8071,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,35.3498,0.2519,22.8071,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,35.3498,0.2519,22.8071,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,27.6965,0.3588,15.0469,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,30.5864,0.9322,17.3635,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,58.0639,-0.0289,45.8020,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,57.9502,-0.1426,45.8020,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,40.0034,0.1283,27.5843,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,37.9195,0.1920,25.4367,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,37.9195,0.1920,25.4367,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,37.9218,0.1921,25.4389,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,37.9218,0.1921,25.4389,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-18.3016,-0.7587,-29.8337,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,6.4543,-0.4367,-5.3998,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,39.6832,0.2806,27.1119,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-17.1328,-0.9333,-28.4903,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-17.0935,-0.8940,-28.4903,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-15.1257,-0.4738,-26.9426,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.GRID.CDL1,CDL1_DDR,37.3041,0.3109,24.7025,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-1.8871,-0.6278,-13.5501,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-0.7334,-0.9168,-12.1074,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,37.3041,0.3109,24.7025,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.NUEN.CSI1,CSI1_DDR,39.2862,0.3225,26.6729,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.NUEN.CSI2,CSI2_DDR,39.2906,0.3270,26.6729,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,35.0574,0.2905,22.4761,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.NUEN.GAZA,GAZA_DDR,37.3041,0.3109,24.7025,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,88.3088,0.5836,75.4344,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.NUEN.T201,NT201_DDR,38.4461,0.2325,25.9229,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-7.0609,-0.8219,-18.5298,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-7.0609,-0.8219,-18.5298,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,27.6965,0.3588,15.0469,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,28.2309,1.3801,14.5601,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-15.1257,-0.4738,-26.9426,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-15.1257,-0.4738,-26.9426,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-13.7268,-0.7134,-25.3042,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-17.0935,-0.8940,-28.4903,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,27.3615,0.7844,14.2863,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,35.7892,0.1046,23.3939,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,35.6148,-0.0699,23.3939,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,35.6106,-0.0741,23.3939,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,17.9323,0.0764,5.5652,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,17.9323,0.0764,5.5652,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,27.6747,0.9272,14.4567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,39.8623,0.2171,27.3544,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,27.7003,0.9656,14.4439,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,28.5610,1.6771,14.5931,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,31.7720,0.4688,19.0125,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,39.2906,0.3270,26.6729,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0057,OKMU_DDR,39.5708,0.3348,26.9453,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0060,LEHIGH_DDR,88.3088,0.5836,75.4344,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0086,WARRENM_DDR,38.3601,0.2459,25.8234,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,28.2814,1.2777,14.7129,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,49.1602,0.2421,36.6273,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0121,V121_DDR,27.6747,0.9272,14.4567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0122,V122_DDR,47.6304,0.2235,35.1161,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0124,V124_DDR,67.2791,0.1625,54.8259,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0135,V135_DDR,39.4442,0.2716,26.8818,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0144,V144_DDR,7.1047,-0.3924,-4.7937,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0145,V145_DDR,7.4048,-0.4573,-4.4287,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,27.7057,0.9470,14.4680,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,27.9748,0.5349,15.1491,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0175,V175_DDR,35.0574,0.2905,22.4761,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,27.9748,0.5349,15.1491,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,28.0812,0.6247,15.1657,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,39.4442,0.2716,26.8818,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,39.5801,0.2497,27.0397,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,39.0160,0.2183,26.5070,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,53.8386,0.0875,41.4603,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,38.1052,0.1810,25.6334,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,39.5801,0.2497,27.0397,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0211,V211_DDR,27.8221,1.1220,14.4093,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,49.9273,0.2461,37.3905,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0213,V213_DDR,39.1156,0.2484,26.5764,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0215,V215_DDR,48.6778,0.2346,36.1524,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0217,V217_DDR,49.9810,0.2317,37.4585,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0218,V218_DDR,53.3661,0.0973,40.9781,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0228,V228_DDR,40.4205,0.1921,27.9377,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0232,V232_DDR,39.0075,0.2769,26.4398,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0233,V233_DDR,39.7645,0.2642,27.2095,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0240,V240_DDR,45.8111,0.1810,33.3394,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0244,V244_DDR,39.5801,0.2497,27.0397,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0246,MDT1_DDR,88.3088,0.5836,75.4344,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0249,V249_DDR,39.0684,0.2631,26.5146,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0250,V250_DDR,-2.3623,-0.5961,-14.0570,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0251,V251_DDR,38.4243,0.2192,25.9143,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.VOLT.0252,V252_DDR,53.8386,0.0875,41.4603,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-21.1066,-0.7298,-32.6676,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,10.8475,-0.8234,-0.6199,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-14.9023,-1.4350,-25.7581,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,27.6281,0.9060,14.4314,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-19.3993,-1.7673,-29.9228,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,2.7777,-0.4935,-9.0196,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,2.7777,-0.4935,-9.0196,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,2.7777,-0.4935,-9.0196,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,2.7777,-0.4935,-9.0196,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,2.7777,-0.4935,-9.0196,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,27.6965,0.3588,15.0469,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,27.4208,1.1598,13.9703,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,38.9869,0.2564,26.4398,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,38.1103,0.1703,25.6492,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,40.8870,0.3729,28.2233,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,40.8870,0.3729,28.2233,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWWELSH1,CSWSWELSHUN1_RA,27.6555,0.6731,14.6917,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWWELSH3,CSWSWELSHUN3_RA,27.6555,0.6731,14.6917,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWWILKES1,CSWSWILKESUN1_RA,27.8766,0.9083,14.6775,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWWILKES2,CSWSWILKESUN2_RA,27.8766,0.9083,14.6775,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,CSWWILKES3,CSWSWILKESUN3_RA,27.7065,0.8638,14.5519,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-17.0821,-0.8826,-28.4903,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,DENL,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,DERS,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,DOE,DOE,19.3162,0.3480,6.6774,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,10.5380,0.0284,-1.7812,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,DPC,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,DUK,VACS,24.2738,0.4424,11.5406,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDDY,EDDY,1.9320,-0.0535,-10.3053,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,31.9045,0.0807,19.5331,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-5.7960,-0.1708,-17.9160,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,37.4497,-0.1266,25.2855,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE.SLCC,EDESTL4391_PLT,33.8539,-0.0674,21.6306,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,33.7305,-0.0207,21.4604,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,19.3129,-0.2043,7.2265,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_EC_01,EDELAR3821UN1_RA,31.9045,0.0807,19.5331,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_EC_02,EDELAR3821UN2_RA,31.9045,0.0807,19.5331,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_EC_03,EDELAR3821UN3_RA,31.9045,0.0807,19.5331,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_EC_04,EDELAR3821UN4_RA,31.9045,0.0807,19.5331,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_EDE,EDE_LA,31.4921,0.2730,18.9283,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_ERW,EDEERWFUNG1_RA,-11.2897,-0.5976,-22.9828,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-4.8194,-0.6660,-16.4442,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,30.0200,0.5992,17.1300,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,30.0200,0.5992,17.1300,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,30.0200,0.5992,17.1300,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,30.0200,0.5992,17.1300,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,0.1000,0.4551,-12.6459,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_RIV_10,EDERIV1671UN10_RA,33.8921,-0.1159,21.7173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_RIV_11,EDERIV1671UN11_RA,33.8921,-0.1159,21.7173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_RIV_12,EDERIV453UN12_PLT,33.5468,-0.4612,21.7173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_SL_01,EDESTL4391UN1_RA,33.6299,-0.2915,21.6306,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EDE_SWMP,EDE_SWMP_LA,30.3819,0.4303,17.6609,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EEI,EEI,19.1564,0.3467,6.5190,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,EES,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-7.5773,-0.6215,-19.2466,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,ERCOTE,ERCOTE,27.6555,0.6731,14.6917,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,ERCOTN,ERCOTN,-7.0084,-0.7694,-18.5298,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,1.4202,-0.3869,-10.4837,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,FMPP,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,FPC,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,FPL,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,FREM_50T,OPPDFREM_GUN1_RA,3.8511,-0.1611,-8.2786,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,FREM_6,OPPDFREM_AUN6_RA,3.8475,-0.1674,-8.2759,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,FREM_7,OPPDFREM_AUN7_RA,3.8475,-0.1674,-8.2759,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,FREM_8,OPPDFREM_AUN8_RA,3.7709,-0.2439,-8.2759,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,FREM_LOAD,FREM_LOAD_LA,3.8355,-0.1794,-8.2759,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-13.8461,-0.5127,-25.6241,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,27.3615,0.7844,14.2863,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-14.1618,-1.7427,-24.7098,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-30.4338,-0.9342,-41.7903,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,35.0528,0.2859,22.4761,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,35.0528,0.2859,22.4761,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,35.0528,0.2859,22.4761,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,39.2905,0.1699,26.8298,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,39.2905,0.1699,26.8298,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,39.4476,0.1666,26.9902,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,39.4476,0.1666,26.9902,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-23.3971,-0.8629,-34.8250,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,50.9471,0.1004,38.5559,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,50.9471,0.1004,38.5559,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,50.9471,0.1004,38.5559,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.VOLT.0130,V130_DDR,40.4853,0.2976,27.8969,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA.VOLT.0237,V237_DDR,40.5871,0.2200,28.0764,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDAHUB2,GRDAHUB2_H,26.9738,-0.1133,14.7964,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDAHUB3,GRDAHUB3_H,20.4725,-0.2124,8.3941,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA_GRDA,GRDA_LA,40.3808,0.2297,27.8604,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA_HUB,GRDA_H,34.3142,0.0125,22.0110,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRDA_HUBSA,GRDASA_H,34.2463,-0.0080,21.9636,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,GRE,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-8.9652,-0.1473,-21.1087,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GSEC_SPS,SPS_GSEC_LA,-11.8251,-0.7603,-23.3556,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GSPR2014HUB,GSPR2014HUB_H,-6.6351,-0.8139,-18.1120,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GSPR2015HUB,GSPR2015HUB_H,-5.8342,-0.8111,-17.3139,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-13.7681,-1.4207,-24.6381,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,HARRISON,CSWSLEBROCKPLT1,27.4416,0.7163,14.4346,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,HAST_TNSK_HUB,HAST_TNSK_H,0.9971,-0.5156,-10.7781,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,HQST,PJM,15.5656,0.2212,3.0537,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,HST,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,20.6806,0.2865,8.1033,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,20.6806,0.2865,8.1033,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,21.1341,0.2856,8.5577,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,21.1341,0.2856,8.5577,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,20.1614,0.2850,7.5856,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,20.1614,0.2850,7.5856,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,INDN_INDN,INDN_LA,20.7239,0.2961,8.1371,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-5.1441,-0.7021,-16.7328,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,ISNE,PJM,15.5656,0.2212,3.0537,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,JEA,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,3.8269,-0.1167,-8.3471,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,3.8269,-0.1167,-8.3471,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,2.6372,0.0081,-9.6617,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KACYCT4,KACYNEARMANUNCT4_RA,22.5200,0.2180,10.0112,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,62.8859,-0.0609,50.6560,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,22.5200,0.2180,10.0112,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,22.8580,0.2331,10.3341,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,22.7655,0.2310,10.2437,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KACY_KACY,KACY_LA,22.9544,0.2283,10.4353,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,33.9188,0.1457,21.4823,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,13.8987,0.5033,1.1046,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-16.5589,-0.6178,-28.2318,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-45.7415,-0.8264,-57.2059,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.VOLT.0222,V222_DDR,-0.3431,0.0517,-12.6856,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.VOLT.0223,V223_DDR,12.4922,0.0169,0.1845,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.VOLT.0241,V241_DDR,14.1471,0.4450,1.4114,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.VOLT.0243,V243_DDR,21.4732,0.1918,8.9906,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.VOLT.0247,V247_DDR,13.8098,0.1281,1.3909,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.VOLT.0253,V253_DDR,34.0223,0.1502,21.5814,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-2.8678,-0.8531,-14.3055,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,9.3285,-0.1241,-2.8382,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,9.3285,-0.1241,-2.8382,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,9.3285,-0.1241,-2.8382,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,9.3285,-0.1241,-2.8382,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,34.2636,0.1437,21.8292,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,34.2636,0.1437,21.8292,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHUB,KCPLHUB_H,4.9461,-0.4294,-6.9152,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHUB17,KCPLHUB17_H,4.0197,-0.4889,-7.7822,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHUB18,KCPLHUB18_H,3.2692,-0.4846,-8.5370,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHUB19,KCPLHUB19_H,3.4273,-0.4577,-8.4058,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHUB20,KCPLHUB20_H,2.6342,-0.5098,-9.1467,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHUB21,KCPLHUB21_H,2.1291,-0.5026,-9.6591,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHUB22,KCPLHUB22_H,3.1472,-0.4970,-8.6465,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHUB23,KCPLHUB23_H,2.8381,-0.5104,-8.9423,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLHUB24,KCPLHUB24_H,1.9565,-0.5336,-9.8006,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,0.3200,0.0155,-11.9863,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,0.3200,0.0155,-11.9863,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,7.8685,-0.3337,-4.0886,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,7.8685,-0.3337,-4.0886,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,33.9198,0.1467,21.4823,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,33.9188,0.1457,21.4823,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,29.0233,0.1838,16.5488,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,29.0233,0.1838,16.5488,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,29.0233,0.1838,16.5488,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,29.0233,0.1838,16.5488,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,29.0233,0.1838,16.5488,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,29.0233,0.1838,16.5488,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,29.0233,0.1838,16.5488,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,29.0233,0.1838,16.5488,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,2.9976,-0.1664,-9.1268,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,17.4626,0.1381,5.0338,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KCPL_KCPL,KCPL_LA,20.5082,0.1229,8.0945,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KENN,KENN_LA,4.9176,0.4397,-7.8129,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KEP2_SECI,KEP2_SECI_LA,-11.8927,-0.9277,-23.2557,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KERR_1,GRDAKERR_HYDUN1_RA,40.1248,0.1981,27.6359,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KERR_2,GRDAKERR_HYDUN2_RA,39.9716,0.2000,27.4809,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KERR_3,GRDAKERR_HYDUN3_RA,39.9716,0.2000,27.4809,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KERR_4,GRDAKERR_HYDUN4_RA,40.1248,0.1981,27.6359,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,9.3284,-0.1242,-2.8382,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,9.3284,-0.1242,-2.8382,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,10.3781,-0.0483,-1.8644,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,10.3781,-0.0483,-1.8644,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,7.3403,-0.1275,-4.8230,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,5.7154,-0.1093,-6.4660,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,5.7154,-0.1093,-6.4660,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-10.3000,-1.0259,-21.5648,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-10.3000,-1.0259,-21.5648,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-10.3000,-1.0259,-21.5648,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-6.8137,-0.5165,-18.5880,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-6.8137,-0.5165,-18.5880,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-10.5853,-1.0404,-21.8357,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-7.6457,-0.5893,-19.3472,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-4.2007,-0.3756,-16.1159,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,55.6502,-0.0824,43.4418,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,55.6502,-0.0824,43.4418,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,0.5557,-0.2525,-11.4826,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,0.5557,-0.2525,-11.4826,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,0.5557,-0.2525,-11.4826,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-8.2315,-0.7307,-19.7915,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-7.3138,-0.8922,-18.7123,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,3.6365,-0.3601,-8.2942,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,3.7475,0.0572,-8.6005,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,LAFA,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,LAM345,LAM345,-10.7285,-1.1841,-21.8351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,LEPA,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,2.6828,-0.2012,-9.4067,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_LES,LES_LA,2.6946,-0.2127,-9.3834,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,2.8473,-0.2344,-9.2091,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,2.5801,-0.2513,-9.4593,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,2.5801,-0.2513,-9.4593,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,2.5801,-0.2513,-9.4593,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,2.8477,-0.2340,-9.2091,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,2.8473,-0.2344,-9.2091,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_WAVERLY,LES_WAVERLY_H,2.8056,-0.2488,-9.2364,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,3.9454,-0.2213,-8.1241,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,3.9454,-0.2213,-8.1241,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,LGEE,LGEE,17.7895,0.2836,5.2151,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MALDEN,MALDEN_LA,6.2307,0.4260,-6.4861,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MCWEST,MCWEST,7.0426,0.0984,-5.3466,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MDU,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,0.5805,-0.4346,-11.2756,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,2.0290,-0.0517,-10.2101,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,3.9079,0.4251,-8.8080,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MEAN_NPPD,NPPD_MEAN_LA,0.1541,-0.6711,-11.4655,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MEC,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MHEB,MHEB,8.1711,0.2150,-4.3347,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-4.5530,-0.7122,-16.1316,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-8.3875,-0.9512,-19.7271,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-4.5530,-0.7122,-16.1316,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-4.5530,-0.7122,-16.1316,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-8.3875,-0.9512,-19.7271,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-13.0194,-0.6862,-24.6240,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MISO,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-11.3043,-0.8962,-22.6988,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-11.3043,-0.8962,-22.6988,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-2.5009,-0.4025,-14.3892,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-11.6030,-1.1371,-22.7567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-7.9073,-0.8114,-19.3867,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-12.1032,-1.0003,-23.3937,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-11.1178,-0.7998,-22.6087,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-12.1980,-0.9394,-23.5494,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-11.0625,-0.7265,-22.6268,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-11.0625,-0.7265,-22.6268,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-11.0625,-0.7265,-22.6268,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-11.0625,-0.7265,-22.6268,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-11.0625,-0.7265,-22.6268,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,8.7805,0.0719,-3.5822,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,15.2521,0.3116,2.6497,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,15.2521,0.3116,2.6497,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,13.8376,0.2201,1.3268,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,13.5220,0.4862,0.7450,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MOWR,AECI,22.5182,0.2401,9.9874,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,14.8538,0.1714,2.3916,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,15.5659,0.3169,2.9583,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,0.7964,-0.5769,-10.9175,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-0.1645,-0.2770,-12.1783,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-14.0000,-0.8889,-25.4019,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,0.8368,-0.5365,-10.9175,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,10.5424,0.0329,-1.7812,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,10.5424,0.0329,-1.7812,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,10.5426,0.0330,-1.7812,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,10.5426,0.0330,-1.7812,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,-0.3431,0.0517,-12.6856,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,-0.3431,0.0517,-12.6856,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,-0.3431,0.0517,-12.6856,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,-0.3849,0.0100,-12.6856,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,-0.3431,0.0517,-12.6856,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,-0.3431,0.0517,-12.6856,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,-0.3431,0.0517,-12.6856,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,19.3257,0.3256,6.7093,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,12.0402,0.0298,-0.2804,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,10.8883,-0.0160,-1.3865,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,10.8883,-0.0160,-1.3865,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,10.8883,-0.0160,-1.3865,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,20.8812,0.1444,8.4460,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,20.8812,0.1444,8.4460,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MPS_MPS,MPS_LA,11.6773,0.1670,-0.7804,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,MSTNG,SPSMSTNGPLT1,3.7342,0.0520,-8.6086,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MSTNG4,SPSMSTNGUN4_RA,3.6985,0.0163,-8.6086,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MSTNG5,SPSMSTNGUN5_RA,3.7342,0.0520,-8.6086,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,3.7342,0.0520,-8.6086,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NBSO,PJM,15.5656,0.2212,3.0537,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,2.0613,-0.5552,-9.6742,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,2.0594,-0.5571,-9.6742,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-14.3430,-1.6140,-25.0198,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NHC1,VACS,24.2738,0.4424,11.5406,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,3.8354,-0.1562,-8.2992,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,3.8354,-0.1562,-8.2992,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,3.8354,-0.1562,-8.2992,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,1.8254,-0.8649,-9.6004,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,0.5633,-0.7825,-10.9450,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,1.7190,-0.4735,-10.0983,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,4.0045,-0.2845,-8.0018,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,0.5633,-0.7825,-10.9450,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.HUB.PY2018,NPPDPY18_H,0.3435,-0.7025,-11.2448,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,0.4208,-0.6936,-11.1764,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,0.3817,-0.6908,-11.2183,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,0.4514,-0.6770,-11.1624,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,4.3686,-0.3428,-7.5793,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-0.8765,-0.8215,-12.3458,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-0.8765,-0.8215,-12.3458,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-1.3301,-0.6507,-12.9702,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,4.3686,-0.3428,-7.5793,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,3.2112,-0.8198,-8.2598,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,0.1647,-1.0134,-11.1127,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-2.8004,-0.8239,-14.2673,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,0.1647,-1.0134,-11.1127,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,1.0347,-0.8790,-10.3770,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-0.0663,-0.9416,-11.4154,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,2.3532,-0.1291,-9.8085,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,0.5633,-0.7825,-10.9450,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-2.4913,-0.8422,-13.9399,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-0.8765,-0.8215,-12.3458,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-0.8765,-0.8215,-12.3458,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-0.3830,-0.5892,-12.0845,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-0.4222,-0.6022,-12.1108,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-0.4222,-0.6022,-12.1108,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,0.1968,-0.3251,-11.7689,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-8.7300,-0.0625,-20.9583,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,0.8294,-0.5981,-10.8633,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,2.1545,-0.6987,-9.4375,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-14.1800,-0.0084,-26.4624,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-16.7487,-0.0163,-29.0231,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.NELI.DDR,NELI_DDR,3.9673,-0.4376,-7.8859,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.NPPM.1058,SH1058_DDR,3.4977,-0.0945,-8.6986,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,0.1823,-0.4070,-11.7015,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,0.5633,-0.7825,-10.9450,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,1.7190,-0.4735,-10.0983,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,4.3686,-0.3428,-7.5793,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.TECH.1,KEARNE_DDR,0.3763,-0.3002,-11.6142,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,1.8561,-1.0231,-9.4116,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,1.8561,-1.0231,-9.4116,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,4.1838,-0.4052,-7.7018,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD.VOLT.0236,V236_DDR,2.0716,-0.1374,-10.0818,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD2017HUB,NPPD2017HUB_H,0.3456,-0.6998,-11.2454,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,3.1989,-0.3750,-8.7168,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,1.8254,-0.8649,-9.6004,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,0.1100,-1.1958,-10.9850,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,0.1100,-1.1958,-10.9850,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,2.1162,-0.1651,-10.0094,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,2.0811,-0.1279,-10.0818,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,0.9815,-0.2693,-11.0399,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-0.3315,-0.6042,-12.0180,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,3.2526,-0.3395,-8.6986,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,3.2526,-0.3395,-8.6986,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,3.2526,-0.3395,-8.6986,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,1.0085,-0.5104,-10.7718,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,1.8405,-0.5032,-9.9471,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,1.2007,-0.3600,-10.7301,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,3.8362,-1.0090,-7.4456,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,3.9034,-0.9418,-7.4456,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-1.3299,-0.8812,-12.7395,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-1.4969,-0.8823,-12.9053,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,1.3951,-0.4561,-10.4396,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,1.3843,-0.4668,-10.4396,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,1.3843,-0.4668,-10.4396,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,1.4049,-0.4339,-10.4520,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,3.2112,-0.8198,-8.2598,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,1.3753,-0.4347,-10.4808,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,2.2995,-0.3171,-9.6742,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,1.0212,-0.4831,-10.7865,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,1.0111,-0.4910,-10.7887,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,1.0161,-0.4834,-10.7912,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,1.0161,-0.4834,-10.7912,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,1.0085,-0.5104,-10.7718,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,0.9745,-0.5445,-10.7718,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,2.8022,-0.4404,-9.0482,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,1.5328,-0.2573,-10.5006,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-1.2734,-0.8480,-12.7162,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,2.9228,-0.9211,-8.4469,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-3.0728,-0.8645,-14.4991,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,3.6851,0.0930,-8.6986,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,3.9673,-0.4376,-7.8859,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-1.1487,-0.8561,-12.5834,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-1.1487,-0.8561,-12.5834,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_NPPD,NPPD_LA,1.7836,-0.3803,-10.1269,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,2.2995,-0.3171,-9.6742,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,2.2995,-0.3171,-9.6742,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,0.9729,-0.3269,-10.9909,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-0.7100,-0.7301,-12.2707,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NSB,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NSP,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,NSSO,PJM,15.5656,0.2212,3.0537,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,NYIS,PJM,15.5656,0.2212,3.0537,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-14.7398,-1.4067,-25.6238,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-21.9141,-0.8823,-33.3225,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-4.3600,-0.6909,-15.9599,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-4.3600,-0.6909,-15.9599,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-14.2136,-1.6179,-24.8865,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-30.4338,-0.9342,-41.7903,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-100.9736,-0.5723,-112.6921,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-47.4855,-0.8401,-58.9362,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-25.6396,-0.8707,-37.0596,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-21.9468,-0.8877,-33.3499,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,1.9791,-0.3308,-9.9809,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-25.6396,-0.8707,-37.0596,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-14.3776,-1.5707,-25.0976,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-13.0194,-0.6862,-24.6240,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-14.9240,-1.3400,-25.8747,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,29.4466,-0.0671,17.2230,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-21.9468,-0.8877,-33.3499,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-19.2578,-0.8442,-30.7043,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-1.5700,-0.8228,-13.0380,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-14.0000,-0.7223,-25.5685,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-44.1986,-0.0658,-56.4235,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-13.0194,-0.6862,-24.6240,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-13.0194,-0.6862,-24.6240,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-21.9468,-0.8877,-33.3499,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-11.9557,-0.7045,-23.5419,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.NUEN.LAM1,LAM1_DDR,33.7191,0.8753,20.5531,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.NUEN.MDT2,MDT2_DDR,1.9791,-0.3308,-9.9809,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.NUEN.MDT3,MDT3_DDR,1.9791,-0.3308,-9.9809,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-12.2025,-0.7046,-23.7887,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-0.6450,-0.3737,-12.5621,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-0.6450,-0.3737,-12.5621,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-0.6450,-0.3737,-12.5621,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,5.7080,-0.3198,-6.2630,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,5.7080,-0.3198,-6.2630,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-0.6450,-0.3737,-12.5621,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-0.6450,-0.3737,-12.5621,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-21.9468,-0.8877,-33.3499,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,14.2946,0.5330,1.4709,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-14.3776,-1.5707,-25.0976,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-33.1226,-0.1483,-45.2651,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-19.2578,-0.8442,-30.7043,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,30.3092,0.5522,17.4663,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-19.9710,-0.7015,-31.5603,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-19.9710,-0.7015,-31.5603,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-19.9710,-0.7015,-31.5603,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-19.9710,-0.7015,-31.5603,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-23.9614,-1.2394,-35.0127,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-26.0909,-0.8456,-37.5360,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-21.9141,-0.8823,-33.3225,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-31.3446,-0.8244,-42.8109,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-31.3446,-0.8244,-42.8109,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-29.3195,-0.0916,-41.5187,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-16.2132,-0.7911,-27.7128,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-16.2132,-0.7911,-27.7128,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-16.2132,-0.7911,-27.7128,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0033,FOSTER_DDR,12.3976,-0.2882,0.3951,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,35.2422,0.4457,22.5057,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0035,TARBY_DDR,33.6476,0.7069,20.6500,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,35.2422,0.4457,22.5057,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,34.9799,0.3255,22.3636,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,34.9799,0.3255,22.3636,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-40.3454,-0.0929,-52.5433,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0040,TROSPER_DDR,16.1038,-0.2683,4.0814,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,16.0462,-0.2682,4.0236,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,31.6443,0.6583,18.6952,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0115,V115_DDR,3.0734,-0.3238,-8.8935,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0116,V116_DDR,60.6900,-0.0055,48.4047,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0118,V118_DDR,13.5837,0.0051,1.2879,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0125,V125_DDR,32.4858,0.7565,19.4386,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0126,V126_DDR,35.2929,0.3891,22.6131,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0129,V129_DDR,-1.8864,-0.6271,-13.5501,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,43.1458,-0.3363,31.1914,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0134,V134_DDR,36.0300,0.4777,23.2616,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0138,V138_DDR,34.7667,0.3353,22.1407,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,36.1101,-0.2761,24.0954,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0143,V143_DDR,34.3824,0.2573,21.8343,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0149,V149_DDR,-10.9848,-0.6423,-22.6333,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0150,V150_DDR,-11.0528,-0.6883,-22.6552,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0155,V155_DDR,34.2893,0.2763,21.7223,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0156,V156_DDR,43.1458,-0.3363,31.1914,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0166,V166_DDR,35.1963,0.7143,22.1912,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,35.2805,-0.2807,23.2704,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-11.0528,-0.6883,-22.6552,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0170,V170_DDR,-12.3454,-0.7037,-23.9325,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-20.7689,-0.6136,-32.4461,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0176,V176_DDR,-11.0528,-0.6883,-22.6552,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0177,V177_DDR,-18.7133,-1.2086,-29.7955,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,27.7921,-0.2799,15.7812,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-7.4722,-0.7276,-19.0353,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0195,V195_DDR,144.2200,0.8161,131.1131,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0197,V197_DDR,36.8130,0.4567,24.0655,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0198,V198_DDR,35.1963,0.7143,22.1912,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0208,V208_DDR,144.3394,0.8327,131.2159,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0209,V209_DDR,144.3394,0.8327,131.2159,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,36.6064,0.3515,23.9641,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0216,V216_DDR,16.0314,-0.2688,4.0094,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0219,V219_DDR,34.2893,0.2763,21.7223,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0220,V220_DDR,-11.0528,-0.6883,-22.6552,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0224,V224_DDR,2.2574,-0.3424,-9.6909,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0225,V225_DDR,2.2581,-0.3418,-9.6909,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0226,V226_DDR,2.2574,-0.3424,-9.6909,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0227,V227_DDR,2.2574,-0.3424,-9.6909,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0229,V229_DDR,-35.7898,-0.0280,-48.0526,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0231,V231_DDR,16.3997,0.1003,4.0086,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0238,V238_DDR,-21.7705,-0.9273,-33.1340,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.VOLT.0242,V242_DDR,34.5030,0.3052,21.9071,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-20.0000,-1.7236,-30.5672,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-13.0194,-0.6862,-24.6240,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-21.8676,-0.8626,-33.2957,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-14.9240,-1.3401,-25.8747,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-20.0000,-1.7236,-30.5672,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-13.6321,-1.5575,-24.3654,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-53.1377,-0.8073,-64.6212,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEHL7,OKGEHL7_H,26.8742,-0.2614,14.8449,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEHL8,OKGEHSL1UN8_RA,26.8742,-0.2614,14.8449,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEHL910,OKGEHSL1PLT2,26.8742,-0.2614,14.8449,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-14.3548,-1.4392,-25.2064,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEMCC,OKGEMCCLAIPLT1,-0.1948,-0.4659,-12.0196,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,31.7961,0.2093,19.2961,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,31.7961,0.2093,19.2961,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,31.7961,0.2093,19.2961,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,19.4353,-0.4446,7.5892,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,19.4353,-0.4446,7.5892,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,19.4353,-0.4446,7.5892,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,19.4353,-0.4446,7.5892,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGESM1,OKGESEMINOLEUN1_RA,14.0046,-0.1936,1.9074,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGESM2,OKGESEMINOLEUN2_RA,11.1980,-0.2216,-0.8712,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGESM3,OKGESEMINOLEUN3_RA,11.1980,-0.2216,-0.8712,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGESO1,OKGESONR1UN1_RA,-63.9499,-0.7792,-75.4614,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGESO2,OKGESONR1UN2_RA,-31.3446,-0.8244,-42.8109,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-14.4513,-1.5356,-25.2064,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-15.7935,-1.6711,-26.4131,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGETINK5A,OKGETINK5UN1_RA,14.0585,-0.2956,2.0634,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGETINK5B,OKGETINK5UN2_RA,14.0585,-0.2956,2.0634,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-15.5867,-1.1657,-26.7118,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-21.9141,-0.8823,-33.3225,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,30.9804,0.8450,17.8446,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-13.0194,-0.6862,-24.6240,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE_OKGE,OKGE_LA,18.3966,-0.1194,6.2252,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-33.1226,-0.1483,-45.2651,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-15.6180,-1.1969,-26.7118,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMLP,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,41.8037,0.1429,29.3700,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,31.2926,0.8006,18.2012,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-1.0673,-0.3352,-13.0228,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-100.8674,-0.4661,-112.6921,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-8.5245,-0.8141,-20.0012,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-25.6396,-0.8707,-37.0596,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-18.6621,-1.4971,-29.4558,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-7.3937,-1.2472,-18.4373,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,176.3603,0.1191,163.9504,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-100.9019,-0.5005,-112.6921,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-100.9019,-0.5005,-112.6921,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_SPP,OMPA_SPP_LA,-3.0428,-0.5008,-14.8328,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-20.0000,-1.7236,-30.5672,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,37.1643,0.1292,24.7443,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,37.1643,0.1292,24.7443,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,37.1643,0.1292,24.7443,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,37.1643,0.1292,24.7443,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,ONT,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,3.8114,-0.1584,-8.3209,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,3.8114,-0.1584,-8.3209,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,3.8114,-0.1584,-8.3209,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,3.8114,-0.1584,-8.3209,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,3.8114,-0.1584,-8.3209,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,3.8114,-0.1584,-8.3209,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,3.8114,-0.1584,-8.3209,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,3.8114,-0.1584,-8.3209,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,3.8114,-0.1584,-8.3209,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,3.8326,-0.1395,-8.3186,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,3.8354,-0.1562,-8.2992,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,3.6562,-0.1372,-8.4973,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,3.6983,-0.1294,-8.4630,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,3.6983,-0.1294,-8.4630,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD_GLDN,OPPD_GLDN_LA,3.7100,-0.1591,-8.4217,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,3.8294,-0.1479,-8.3135,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,3.2112,-0.8198,-8.2598,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,2.5809,-0.3327,-9.3771,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,3.8352,-0.1551,-8.3004,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD_OPPD,OPPD_LA,3.7980,-0.1217,-8.3711,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,3.7329,-0.1148,-8.4431,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,3.7210,-0.1190,-8.4507,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,OTP,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,OVEC,OVEC,16.8842,0.2596,4.3339,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PARAGOULD,PARAGOULD_LA,2.8272,0.4614,-9.9250,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,39.8670,0.1032,27.4731,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,39.8670,0.1032,27.4731,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,39.8670,0.1032,27.4731,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,39.5175,0.1497,27.0771,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,39.5175,0.1497,27.0771,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,39.5175,0.1497,27.0771,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PIGGOTT,PIGGOTT_LA,5.3852,0.4349,-7.3404,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PJM,PJM,15.5656,0.2212,3.0537,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PLUM,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,POPLARBLUFF,POPLARBLUFF_LA,10.4441,0.3942,-2.2409,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,6.8498,-0.0663,-5.3747,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,6.8498,-0.0663,-5.3747,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,6.9156,-0.0627,-5.3125,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,6.9156,-0.0627,-5.3125,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,7.8570,0.8264,-5.2601,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,7.8570,0.8264,-5.2601,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,7.0393,0.0880,-5.3394,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,6.1974,-0.4379,-5.6555,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-10.6270,-0.5484,-22.3694,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,88.9841,0.1430,76.5503,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,1.0938,0.1020,-11.2989,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-3.2371,-0.0229,-15.5049,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,42.5342,0.4056,29.8378,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,35.5402,0.4070,22.8424,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,7.1191,-0.0668,-5.1049,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,7.2573,0.1865,-5.2200,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,6.0511,-0.2502,-5.9894,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,22.0000,1.2229,8.4863,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,7.9050,0.3170,-4.7028,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,6.9060,0.1102,-5.4950,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,PUPP,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,RCEAST,RCEAST,3.5931,-0.8966,-7.8010,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SALINA_1,GRDASALINA1UN1_RA,40.1260,0.1994,27.6359,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SALINA_2,GRDASALINA1UN2_RA,40.1260,0.1994,27.6359,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SALINA_3,GRDASALINA1UN3_RA,40.1260,0.1994,27.6359,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SALINA_4,GRDASALINA1UN4_RA,40.1260,0.1994,27.6359,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SALINA_5,GRDASALINA1UN5_RA,40.1260,0.1994,27.6359,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SALINA_6,GRDASALINA1UN6_RA,40.1260,0.1994,27.6359,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SARPY_1,OPPDSARPYUN1_RA,3.7638,-0.1472,-8.3797,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SARPY_2,OPPDSARPYUN2_RA,3.7745,-0.1217,-8.3946,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SARPY_3,OPPDSARPYUN3_RA,3.7544,-0.1745,-8.3619,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SARPY_4,OPPDSARPYUN4_RA,3.7544,-0.1745,-8.3619,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SARPY_5,OPPDSARPYUN5_RA,3.7544,-0.1745,-8.3619,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SC,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SCEG,VACS,24.2738,0.4424,11.5406,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SCSE,SCSE,-0.7888,-0.7770,-12.3025,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SEC,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-12.8954,-1.2121,-23.9741,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-12.8954,-1.2121,-23.9741,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-12.8954,-1.2121,-23.9741,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-10.4781,-1.0127,-21.7562,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-12.8954,-1.2121,-23.9741,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-11.3200,-1.2383,-22.3725,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-11.1403,-1.2948,-22.1362,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-11.1403,-1.2948,-22.1362,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-11.0641,-0.7281,-22.6268,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-14.0705,-1.0772,-25.2841,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-6.8637,-0.5664,-18.5880,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-10.7788,-0.9129,-22.1567,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-6.8957,-1.0281,-18.1584,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-12.5204,-1.2304,-23.5808,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-6.8903,-1.0176,-18.1634,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-16.6039,-1.1965,-27.6982,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-11.2730,-0.8065,-22.7572,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-10.4069,-1.0866,-21.6111,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-10.4069,-1.0866,-21.6111,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-10.4069,-1.0866,-21.6111,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-10.4069,-1.0866,-21.6111,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-10.5995,-1.1512,-21.7391,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-11.3200,-1.2383,-22.3725,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI_SECI,SECI_LA,-10.1323,-0.8877,-21.5354,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-5.1441,-0.7021,-16.7328,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-5.1441,-0.7021,-16.7328,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-11.0641,-0.7281,-22.6268,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SEHA,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-15.6180,-1.1969,-26.7118,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SERU,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SETH,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SGE,SGE,0.0680,-0.7481,-11.4747,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SMEP,MISO,15.0630,0.2700,2.5022,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SOCO,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPA,SPA,26.3122,0.4934,13.5280,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPC,SPC,7.6386,0.5116,-5.1638,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPPNORTH_HUB,SPPNORTH_H,2.9516,-0.2253,-9.1138,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPPSOUTH_HUB,SPPSOUTH_H,4.0212,-0.6099,-7.6596,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,26.6487,0.4306,13.9273,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,26.6487,0.4306,13.9273,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,25.9241,0.4099,13.2234,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,25.9241,0.4099,13.2234,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_NIXA,SPRM_NIXA_LA,26.8789,0.4249,14.1632,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_SPRM,SPRM_LA,26.7567,0.4752,13.9907,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,26.9442,0.3653,14.2881,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,26.9442,0.3653,14.2881,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,26.9128,0.3339,14.2881,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,26.9442,0.3653,14.2881,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-8.2292,-0.6399,-19.8801,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-12.6759,-0.8485,-24.1181,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-14.0523,-1.3396,-25.0035,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-14.0523,-1.3396,-25.0035,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-17.6740,-1.3388,-28.6260,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,-3.3359,-0.9831,-14.6435,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-11.0864,-2.0894,-21.2878,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,-0.3567,-0.8210,-11.8265,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-18.5008,-0.8009,-29.9907,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,4.2502,-0.0185,-8.0220,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,4.0910,-0.0183,-8.1815,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,4.0910,-0.0183,-8.1815,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,4.2502,-0.0185,-8.0220,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-14.0190,-1.3059,-25.0039,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-12.6759,-0.8485,-24.1181,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-13.8647,-1.2424,-24.9131,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-14.1059,-1.6310,-24.7657,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-13.6910,-1.1452,-24.8366,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-13.5636,-0.9671,-24.8873,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-13.8215,-1.2267,-24.8855,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-13.9520,-1.6376,-24.6052,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-13.9520,-1.6376,-24.6052,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-13.9520,-1.6376,-24.6052,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-13.9520,-1.6376,-24.6052,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GRID.WRAB,WRAB_DDR,-13.8559,-1.0703,-25.0764,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-13.9520,-1.6376,-24.6052,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-16.4454,-0.8438,-27.8923,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-16.4454,-0.8438,-27.8923,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-16.2884,-0.8058,-27.7734,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-16.2884,-0.8058,-27.7734,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-16.2884,-0.8058,-27.7734,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-16.4454,-0.8438,-27.8923,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-14.1289,-1.3199,-25.0998,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-14.1288,-1.3198,-25.0998,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-14.1274,-1.3199,-25.0983,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-14.3430,-1.6140,-25.0198,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,4.2641,-0.0448,-7.9819,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-18.4133,-0.8079,-29.8962,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-18.4133,-0.8079,-29.8962,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-18.4133,-0.8079,-29.8962,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-18.4133,-0.8079,-29.8962,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,4.3898,0.0328,-7.9337,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,4.2725,-0.0381,-7.9802,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,4.2725,-0.0381,-7.9802,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-15.5652,-1.1442,-26.7118,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-14.1168,-1.3098,-25.0978,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-14.1168,-1.3098,-25.0978,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-14.1383,-1.3147,-25.1144,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-13.8559,-1.0703,-25.0764,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-13.9313,-1.4612,-24.7609,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-13.9965,-1.3228,-24.9645,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-14.2136,-1.6179,-24.8865,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-13.9463,-1.1393,-25.0978,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-11.8735,-0.7604,-23.4039,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-11.8735,-0.7604,-23.4039,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-11.1192,-0.7769,-22.6330,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-17.8797,-1.1535,-29.0170,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-14.2537,-1.8597,-24.6847,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-10.8095,-1.8125,-21.2878,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-17.8709,-1.1446,-29.0170,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-13.9977,-1.2845,-25.0039,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-7.2949,-0.7724,-18.8133,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,0.0000,-0.4643,-11.8265,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-7.2949,-0.7724,-18.8133,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,-6.7294,-0.5828,-18.4374,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-13.9899,-1.4388,-24.8419,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,4.1357,0.4847,-8.6398,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,4.1366,0.4856,-8.6398,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,4.1462,0.2710,-8.4155,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,4.2986,-0.0260,-7.9662,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,3.0200,0.2817,-9.5525,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-10.7285,-1.1841,-21.8351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-13.9118,-1.1246,-25.0780,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-10.2507,-0.7471,-21.7943,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-10.2507,-0.7471,-21.7943,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-7.2949,-0.7724,-18.8133,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-18.7257,-0.7380,-30.2785,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,9.8958,0.3435,-2.7384,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-9.2709,-0.2057,-21.3560,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-10.6960,-0.5050,-22.4818,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-14.4052,-0.8643,-25.8317,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,4.1357,0.4847,-8.6398,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,3.7532,0.6877,-9.2253,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,3.5940,0.5286,-9.2253,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-17.7561,-1.0299,-29.0170,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-9.4977,-0.4949,-21.2935,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-13.9068,-1.4930,-24.7046,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-13.9323,-1.5181,-24.7050,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0163,V163_DDR,-13.7754,-1.1438,-24.9223,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0168,V168_DDR,-16.0867,-0.8038,-27.5737,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0180,V180_DDR,3.7532,0.6877,-9.2253,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0181,V181_DDR,-14.0693,-1.6668,-24.6932,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0182,V182_DDR,3.1914,0.3816,-9.4809,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0199,V199_DDR,6.4142,0.2620,-6.1385,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0200,V200_DDR,4.2870,0.2504,-8.2542,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.VOLT.0235,V235_DDR,-13.9313,-1.4612,-24.7609,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-11.0864,-2.0894,-21.2878,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,-0.3567,-0.8210,-11.8265,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-13.8380,-1.4906,-24.6381,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-13.9950,-1.2472,-25.0386,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS_SPS,SPS_LA,-2.3298,-0.1717,-14.4488,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,3.2995,-0.2872,-8.7041,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SSCN_NPPD,SSCN_NPPD_LA,2.5954,-0.1986,-9.4967,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,10.5229,0.3839,-2.1518,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,10.5229,0.3839,-2.1518,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,TAL,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,TEC,SOUC,24.0730,0.4650,11.3173,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,2.9228,-0.9211,-8.4469,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,TVA,TVA,24.4690,0.4186,11.7596,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,UCUHUB,UCUHUB_H,-1.1617,-0.2301,-13.2223,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,UCUHUB17,UCUHUB17_H,-5.5213,-0.5447,-17.2674,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,UCUHUB18,UCUHUB18_H,-3.0972,-0.4350,-14.9530,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,UCUHUB19,UCUHUB19_H,-5.8981,-0.5023,-17.6866,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,UCUHUB20,UCUHUB20_H,-5.6982,-0.4888,-17.5002,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,UCUHUB21,UCUHUB21_H,-7.0027,-0.5767,-18.7167,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,UCUHUB22,UCUHUB22_H,-6.8084,-0.6031,-18.4961,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,UCUHUB23,UCUHUB23_H,-7.0353,-0.6100,-18.7161,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,UCUHUB24,UCUHUB24_H,-4.4381,-0.5252,-16.2037,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,7.7173,0.6090,-5.1825,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,7.7173,0.6090,-5.1825,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,6.7612,-0.1496,-5.3800,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,6.7612,-0.1496,-5.3800,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,7.3105,-0.1858,-4.7944,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,6.9035,-0.1067,-5.2805,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,6.9035,-0.1067,-5.2805,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,7.7173,0.6090,-5.1825,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,7.3644,-0.1834,-4.7430,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,7.6472,0.2780,-4.9216,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,6.7088,0.0669,-5.6489,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,4.1938,-1.1017,-6.9952,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,7.5958,0.5490,-5.2439,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,7.5958,0.5490,-5.2439,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,5.7710,-1.0300,-5.4897,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,6.7383,-0.1933,-5.3592,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,7.0407,-0.2374,-5.0127,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,6.2084,-0.1695,-5.9129,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,6.7823,0.1396,-5.6481,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,6.5859,-0.2214,-5.4835,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,6.4179,-0.3831,-5.4897,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,6.4179,-0.3831,-5.4897,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,6.7683,-0.1586,-5.3639,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,3.8415,-1.2247,-7.2246,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,7.3765,0.7135,-5.6277,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,9.6700,0.1686,-2.7894,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,9.6700,0.1686,-2.7894,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,9.6700,0.1686,-2.7894,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,7.3245,0.2934,-5.2597,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,7.3245,0.2934,-5.2597,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,7.3245,0.2934,-5.2597,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,7.8942,0.7584,-5.1550,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,7.0949,-0.1453,-5.0505,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,7.0949,-0.1453,-5.0505,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-0.3566,-0.7625,-11.8849,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,6.0320,-0.0736,-6.1851,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,7.4709,0.2680,-5.0878,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,5.0269,-0.3045,-6.9593,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,3.3113,-1.5538,-7.4257,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,6.5865,-0.2685,-5.4358,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,7.6754,0.6101,-5.2255,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,7.6754,0.6101,-5.2255,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,7.6747,0.6095,-5.2255,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,7.6754,0.6101,-5.2255,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,7.5632,0.5076,-5.2351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,7.5632,0.5076,-5.2351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,7.5632,0.5076,-5.2351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,7.5632,0.5076,-5.2351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,7.5632,0.5076,-5.2351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,7.5632,0.5076,-5.2351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,7.5632,0.5076,-5.2351,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,4.3823,-0.8103,-7.0981,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,7.5433,0.0710,-4.8185,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,5.5128,-0.0230,-6.7550,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,5.5128,-0.0230,-6.7550,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,4.8269,-0.3495,-7.1144,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,4.8269,-0.3495,-7.1144,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,7.2372,-0.0030,-5.0505,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,7.3240,0.0067,-4.9735,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,6.3789,-0.2295,-5.6824,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,4.0870,-1.0100,-7.1938,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,7.3203,0.0080,-4.9784,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,7.3105,-0.1858,-4.7944,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,7.3105,-0.1858,-4.7944,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,6.2084,-0.1695,-5.9129,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,3.5344,-0.9440,-7.8123,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,5.9131,-0.4104,-5.9673,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,3.9768,-1.0893,-7.2246,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,6.4960,-0.3219,-5.4729,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.FSE,WAUE.FSE_H,3.2804,-0.5400,-8.4704,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,7.0003,-0.0055,-5.2850,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,6.9678,-0.0306,-5.2923,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,3.8186,-1.0812,-7.3910,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,3.8999,-1.0146,-7.3763,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,7.2526,-0.1572,-4.8809,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,7.2290,-0.2235,-4.8383,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-13.4000,-0.8639,-24.8269,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,4.1938,-1.1017,-6.9952,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-7.7500,-0.7273,-19.3135,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,5.5444,-0.2388,-6.5076,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,5.5444,-0.2387,-6.5076,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,5.5452,-0.2380,-6.5076,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,6.5573,-0.1846,-5.5489,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,3.5344,-0.9440,-7.8123,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,7.2366,0.1571,-5.2113,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,6.0128,-0.2508,-6.0272,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,7.3224,0.6594,-5.6277,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,6.3054,0.1963,-6.1816,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,6.8224,0.1297,-5.5981,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,8.1518,-0.0667,-4.0723,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,6.4074,-0.0294,-5.8539,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,6.3362,-0.2335,-5.7210,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,5.0269,-0.3045,-6.9593,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,9.3734,0.6060,-3.5233,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,6.1969,-0.1800,-5.9139,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,9.1547,0.4473,-3.5834,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,7.0932,0.1883,-5.3859,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,3.9454,-0.2213,-8.1241,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NTWK,WAUE.NTWK_H,6.3283,-0.1240,-5.8384,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,7.2629,0.5289,-5.5568,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,7.2629,0.5289,-5.5568,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,4.1450,-1.1771,-6.9686,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,4.2402,-1.0800,-6.9706,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,7.0169,-0.1360,-5.1378,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,4.1450,-1.1771,-6.9686,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,7.9746,0.0827,-4.3989,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,5.4331,-0.5142,-6.3435,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,5.0269,-0.3045,-6.9593,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,6.0433,-0.2455,-6.0019,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,4.6505,-1.2967,-6.3435,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,2.5595,-1.4710,-8.2603,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,3.0025,-1.4805,-7.8077,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,6.7429,-0.1750,-5.3729,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,2.2318,-1.1151,-8.9438,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,7.2776,0.0445,-5.0576,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,4.7195,-0.7985,-6.7728,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,4.0870,-1.0100,-7.1938,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.VOLT.0152,V152_DDR,8.0969,0.9191,-5.1129,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE.VOLT.0172,V172_DDR,7.6213,0.5612,-5.2306,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_BEPM,WAUE_BEPM_LA,7.2016,0.2629,-5.3520,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,7.3266,0.1645,-5.1287,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,6.3104,0.2037,-6.1840,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_EWA,WAUE_EWA_LA,3.6423,-0.8665,-7.7819,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,5.6011,-0.4341,-6.2556,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_HMMU,WAUE_HMMU_LA,5.0109,0.0287,-7.3086,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,8.4414,-0.0007,-3.8486,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_MECB,WAUE_MECB_LA,5.9504,0.1798,-6.5201,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_MMPA,WAUE_MMPA_LA,8.1578,0.3762,-4.5092,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_MRES,WAUE_MRES_LA,6.6985,-0.0551,-5.5372,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,7.9483,0.6803,-5.0228,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,7.0003,-0.0055,-5.2850,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,5.3553,-0.4356,-6.4999,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_OTP,WAUE_OTP_LA,9.1334,0.6570,-3.8144,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_OTPW,WAUE_OTPW_LA,14.8538,0.7552,1.8078,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM,WAUE_UGPM_LA,6.8533,0.0664,-5.5038,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,7.4241,0.1674,-5.0340,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,6.3949,-0.0322,-5.8637,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,5.7194,-0.4149,-6.1564,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,3.6423,-0.8665,-7.7819,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,5.0109,0.0287,-7.3086,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,5.6091,-0.3983,-6.2834,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,7.0003,-0.0055,-5.2850,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,8.1578,0.3762,-4.5092,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,6.7668,-0.1026,-5.4214,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,5.0555,-0.5335,-6.7017,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,8.2180,0.6558,-4.7285,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-19.7787,-1.5598,-30.5097,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-11.7915,-1.0839,-22.9983,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,1.3263,-1.0348,-9.9297,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,88.1000,0.3748,75.4344,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,88.1000,0.3748,75.4344,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-9.7023,-1.6648,-20.3282,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,80.5753,0.4476,67.8369,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,71.7728,0.4323,59.0498,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,19.5200,-0.7220,7.9512,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,19.5200,-0.7220,7.9512,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,19.5200,-0.7220,7.9512,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,19.5200,-0.7220,7.9512,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,19.4930,-0.7490,7.9512,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,19.5200,-0.7220,7.9512,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,19.5200,-0.7220,7.9512,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,19.5200,-0.7220,7.9512,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,11.1850,-0.6810,-0.4248,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-14.2136,-1.6179,-24.8865,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-25.6877,-1.1188,-36.8597,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-19.0738,-1.5777,-29.7868,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-10.8843,-1.8873,-21.2878,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_ENMC,WFEC_ENMC_LA,0.5248,-0.0752,-11.6908,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-21.9468,-0.8877,-33.3499,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,35.6287,0.3506,22.9873,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,4.3331,-0.0147,-7.9430,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-19.7787,-1.5598,-30.5097,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-19.7787,-1.5598,-30.5097,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-19.7787,-1.5598,-30.5097,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_OKGE,WFEC_OKGE_LA,3.8091,0.1029,-8.5846,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,55.8199,0.4493,43.0798,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-14.6240,-1.7016,-25.2131,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-9.6769,-1.8217,-20.1459,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_WFEC,WFEC_LA,22.2905,-0.2592,10.2589,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,4.3331,-0.0147,-7.9430,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-5.2291,-0.7382,-16.7817,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-9.4254,-1.1699,-20.5462,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-2.1268,-0.4350,-13.9825,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-2.1268,-0.4350,-13.9825,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-2.1268,-0.4350,-13.9825,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-2.1268,-0.4350,-13.9825,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-2.1268,-0.4350,-13.9825,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-2.1268,-0.4350,-13.9825,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-2.1268,-0.4350,-13.9825,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,3.3361,0.4269,-9.3815,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-3.9805,-0.5896,-15.6817,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-17.8904,-0.8463,-29.3349,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-17.8904,-0.8463,-29.3349,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-17.8904,-0.8463,-29.3349,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-14.1857,-1.0717,-25.4048,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-14.1857,-1.0717,-25.4048,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-13.0131,-0.7717,-24.5322,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-13.0131,-0.7717,-24.5322,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-13.0131,-0.7717,-24.5322,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-3.9805,-0.5896,-15.6817,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,1.5861,0.0029,-10.7075,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-8.3377,-0.6004,-20.0281,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-8.3377,-0.6004,-20.0281,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-8.3377,-0.6004,-20.0281,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-8.3376,-0.6002,-20.0281,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,1.5861,0.0029,-10.7075,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-11.9385,-1.2588,-22.9704,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-29.4200,-0.4456,-41.2652,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.JEC.1,WRJEFFUN10_RA,-1.3600,-0.4057,-13.2451,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.JEC.2,WRJEFFUN11_RA,-1.4248,-0.4078,-13.3078,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.JEC.3,WRJEFFUN12_RA,-1.4800,-0.4630,-13.3078,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-23.3971,-0.8629,-34.8250,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-13.9931,-0.8819,-25.4019,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-13.9931,-0.8819,-25.4019,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.LEC.4,WRLECUN26_RA,2.4947,-0.0455,-9.7505,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.LEC.5,WRLECUN27_RA,2.2301,-0.0214,-10.0393,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-6.9157,-0.5111,-18.6954,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-6.9157,-0.5111,-18.6954,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-6.9157,-0.5111,-18.6954,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-6.8692,-0.4858,-18.6742,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-5.1441,-0.7021,-16.7328,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-5.1441,-0.7021,-16.7328,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-6.7232,-0.9289,-18.0851,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-4.8842,-0.6682,-16.5068,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-4.8842,-0.6682,-16.5068,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-7.3198,-0.8982,-18.7123,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-5.1441,-0.7021,-16.7328,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-0.0526,-0.5665,-11.7769,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-4.8194,-0.6660,-16.4442,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-13.9959,-0.8847,-25.4019,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,72.5384,0.4330,59.8146,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-7.7354,-1.3159,-18.7102,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-2.1268,-0.4350,-13.9825,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-3.8657,-0.8754,-15.2811,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,1.5861,0.0029,-10.7075,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-3.9805,-0.5896,-15.6817,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-14.7264,-0.6439,-26.3733,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.THAYERLD,WR.THAYERLD_LA,10.0119,0.4133,-2.6922,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-15.6949,-0.6422,-27.3435,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0106,V106_DDR,-14.5507,-0.6143,-26.2272,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0139,WR.VOLT.0139_H,5.7153,0.0901,-6.6655,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-5.2303,-0.4858,-17.0353,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0146,WR.VOLT.0146_H,2.8756,0.0541,-9.4692,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0147,WR.VOLT.0147_H,2.8756,0.0541,-9.4692,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0148,WR.VOLT.0148_H,2.1377,0.0401,-10.1932,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-13.8625,-0.5266,-25.6266,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0157,V157_DDR,2.7703,0.0398,-9.5603,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0158,V158_DDR,2.8756,0.0541,-9.4692,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0159,WR.VOLT.0159_H,2.8756,0.0541,-9.4692,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-14.6980,-0.6915,-26.2973,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0173,V173_DDR,-7.0052,-0.5819,-18.7140,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0174,V174_DDR,-14.3929,-0.6310,-26.0527,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0184,V184_DDR,-13.9652,-0.7029,-25.5531,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-14.8694,-0.6366,-26.5236,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0186,V186_DDR,-14.8859,-0.6748,-26.5019,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-14.2168,-0.6768,-25.8308,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-15.4895,-0.6189,-27.1613,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-7.6891,-0.4233,-19.5566,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-3.2620,-0.3699,-15.1828,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-2.4806,-0.3947,-14.3766,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-2.4806,-0.3947,-14.3766,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-3.2620,-0.3699,-15.1828,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0245,V245_DDR,-14.8844,-0.6371,-26.5381,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.VOLT.0248,V248_DDR,-14.5507,-0.6143,-26.2272,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-18.9070,-0.8002,-30.3975,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,0.7351,-0.1016,-11.4540,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.WOLF,WRWOLFUN15_RA,-4.0259,-0.9410,-15.3757,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-11.9385,-1.2588,-22.9704,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,3.2766,0.3673,-9.3815,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-17.8904,-0.8463,-29.3349,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-17.8904,-0.8463,-29.3349,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-17.8904,-0.8463,-29.3349,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-17.8904,-0.8463,-29.3349,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-15.6079,-0.4986,-27.4001,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-5.1582,-0.4878,-16.9611,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-15.8271,-0.6484,-27.4695,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-15.8271,-0.6484,-27.4695,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-15.8271,-0.6484,-27.4695,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-15.8271,-0.6484,-27.4695,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-3.4421,-0.3017,-15.4312,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-3.4421,-0.3017,-15.4312,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-3.4421,-0.3017,-15.4312,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-3.4421,-0.3017,-15.4312,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-3.4421,-0.3017,-15.4312,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-3.4421,-0.3017,-15.4312,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-32.1359,-0.5937,-43.8330,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-32.1359,-0.5937,-43.8330,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-34.9899,-0.6045,-46.6761,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-34.9899,-0.6045,-46.6761,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_MIDW,WR_MIDW_LA,-6.7164,-0.7578,-18.2494,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,13.9551,0.3333,1.3311,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,12.3077,0.1594,-0.1425,12.2908\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-8.0868,-0.6980,-19.6795,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_SEG,WR_SEG_LA,10.0996,0.2246,-2.4157,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,WR_WR,WR_LA,-5.5631,-0.3864,-17.4674,12.2907\n03/19/2025 14:00:00,03/19/2025 19:00:00,YAD,VACS,24.2738,0.4424,11.5406,12.2908\n03/19/2025 15:00:00,03/19/2025 20:00:00,AEC,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,AECC_CSWS,CSWS_AECC_LA,31.1166,0.4759,20.3162,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,33.7977,0.3477,23.1256,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,30.0542,0.6157,19.1141,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,33.8648,0.2583,23.2820,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,26.8336,0.4194,16.0898,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,30.7663,0.2695,20.1724,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,27.3405,0.3075,16.7086,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,AECI,AECI,21.2660,0.2053,10.7363,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,AEPM_CSWS,CSWS_LA,30.2215,0.4579,19.4392,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,ALTW,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,AMRN,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-18.3514,-0.7111,-27.9647,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BBA,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BCA,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BEPM.ER01.DDR,ER01_DDR,2.0057,-1.0430,-7.2757,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BEPM_ER01,BEPM_ER01_LA,2.0057,-1.0430,-7.2757,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,1.1186,-0.3733,-8.8326,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-1.5577,-0.2787,-11.6035,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,BEPM_UM01,BEPM_UM01_LA,6.0643,0.4672,-4.7273,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BLKW,BLKW,-17.7866,-0.5125,-27.5985,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-27.3700,-0.9659,-36.7285,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-27.3700,-0.9659,-36.7285,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,9.7539,-0.8882,0.3176,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-27.3527,-0.9487,-36.7285,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,BRAZ,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BUBA,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-15.1085,-0.9595,-24.4735,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-15.4657,-0.6149,-25.1752,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-15.4657,-0.6149,-25.1752,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-15.4657,-0.6149,-25.1752,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-15.4657,-0.6149,-25.1752,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-15.4657,-0.6149,-25.1752,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-8.5605,-0.4537,-18.4312,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,2.7719,-0.1520,-7.4005,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,2.7719,-0.1520,-7.4005,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CLEC,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,33.4090,0.2643,22.8203,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,COWP,COWP_LA,16.9957,0.3201,6.3512,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,16.9957,0.3201,6.3512,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,16.9957,0.3201,6.3512,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CPLE,VACS,23.2722,0.3762,12.5715,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CPLW,VACS,23.2722,0.3762,12.5715,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,22.2427,0.4338,11.4845,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,22.2427,0.4338,11.4845,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,22.2427,0.4338,11.4845,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,22.2427,0.4338,11.4845,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CRTH_SPA,WRCRTH_SPA_LA,32.5948,0.1366,22.1338,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,27.1623,1.1248,15.7131,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-4.4023,-0.5332,-14.1935,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,27.3405,0.3075,16.7086,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,33.8648,0.2583,23.2820,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,27.1589,1.1170,15.7175,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,27.1143,0.8280,15.9619,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,27.1416,1.0179,15.7993,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,27.1416,1.0179,15.7993,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,33.5537,0.2829,22.9464,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,33.5537,0.2829,22.9464,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,33.4895,0.2187,22.9464,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,33.4895,0.2187,22.9464,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,27.3405,0.3075,16.7086,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,30.1966,0.7581,19.1141,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,54.8147,-0.0175,44.5078,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,54.7191,-0.1131,44.5078,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,37.8827,0.1173,27.4410,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,36.0014,0.1693,25.5077,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,36.0014,0.1693,25.5077,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,36.0029,0.1692,25.5093,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,36.0029,0.1692,25.5093,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-20.4592,-0.6533,-30.1303,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,2.8178,-0.3718,-7.1348,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,39.4179,0.1811,28.9123,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-19.8694,-0.8016,-29.3922,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-19.8366,-0.7689,-29.3922,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-17.4138,-0.4224,-27.3158,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.GRID.CDL1,CDL1_DDR,37.0662,0.2467,26.4951,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-4.4681,-0.4806,-14.3119,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-3.7514,-0.7803,-13.2955,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,37.0662,0.2467,26.4951,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.NUEN.CSI1,CSI1_DDR,37.3049,0.2900,26.6905,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.NUEN.CSI2,CSI2_DDR,37.3086,0.2937,26.6905,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,33.4131,0.2683,22.8203,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.NUEN.GAZA,GAZA_DDR,37.0662,0.2467,26.4951,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,82.9209,0.4756,72.1209,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.NUEN.T201,NT201_DDR,36.2578,0.1994,25.7340,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-9.6953,-0.7084,-19.3114,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-9.6953,-0.7084,-19.3114,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,27.3405,0.3075,16.7086,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,27.6404,1.1818,16.1342,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-17.4138,-0.4224,-27.3158,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-17.4138,-0.4224,-27.3158,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-15.9323,-0.6155,-25.6412,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-19.8366,-0.7689,-29.3922,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,26.8235,0.6850,15.8141,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,33.5697,0.0943,23.1510,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,33.4264,-0.0490,23.1510,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,33.4238,-0.0516,23.1510,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,15.2275,0.0563,4.8468,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,15.2275,0.0563,4.8468,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,27.1527,0.8023,16.0260,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,37.6442,0.1868,27.1329,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,27.1685,0.8355,16.0086,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,27.9317,1.4207,16.1866,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,31.5660,0.3599,20.8817,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,37.3086,0.2937,26.6905,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0057,OKMU_DDR,40.4501,0.2806,29.8451,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0060,LEHIGH_DDR,82.9209,0.4756,72.1209,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0086,WARRENM_DDR,36.3886,0.2135,25.8507,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,27.7376,1.0910,16.3222,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,46.4230,0.2088,35.8898,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0121,V121_DDR,27.1527,0.8023,16.0260,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0122,V122_DDR,44.9972,0.1947,34.4781,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0124,V124_DDR,63.3572,0.1410,52.8918,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0135,V135_DDR,37.3363,0.2355,26.7764,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0144,V144_DDR,3.4875,-0.3299,-6.5070,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0145,V145_DDR,3.8145,-0.3804,-6.1295,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,27.1835,0.8190,16.0401,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,27.6035,0.4511,16.8280,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0175,V175_DDR,33.4131,0.2683,22.8203,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,27.6035,0.4511,16.8280,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,27.6893,0.5253,16.8396,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,37.3363,0.2355,26.7764,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,37.4439,0.2169,26.9026,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,36.8606,0.1910,26.3452,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,50.8323,0.0797,40.4282,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,36.1066,0.1599,25.6223,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,37.4439,0.2169,26.9026,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0211,V211_DDR,27.2573,0.9678,15.9651,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,47.1395,0.2104,36.6047,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0213,V213_DDR,37.0585,0.2159,26.5182,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0215,V215_DDR,45.9709,0.2024,35.4441,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0217,V217_DDR,47.1916,0.1987,36.6685,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0218,V218_DDR,50.3866,0.0879,39.9743,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0228,V228_DDR,38.1623,0.1657,27.6722,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0232,V232_DDR,36.9340,0.2442,26.3654,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0233,V233_DDR,37.6339,0.2291,27.0804,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0240,V240_DDR,43.2383,0.1562,32.7576,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0244,V244_DDR,37.4439,0.2169,26.9026,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0246,MDT1_DDR,82.9209,0.4756,72.1209,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0249,V249_DDR,37.0171,0.2282,26.4644,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0250,V250_DDR,-5.3463,-0.5085,-15.1622,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0251,V251_DDR,36.4473,0.1917,25.9312,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.VOLT.0252,V252_DDR,50.8323,0.0797,40.4282,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-22.9329,-0.6293,-32.6280,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,7.1218,-0.6969,-2.5058,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-16.5546,-1.2462,-25.6328,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,27.1031,0.7849,15.9938,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-20.1000,-1.8490,-28.5754,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-0.5354,-0.4235,-10.4363,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-0.5354,-0.4235,-10.4363,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-0.5354,-0.4235,-10.4363,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-0.5354,-0.4235,-10.4363,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-0.5354,-0.4235,-10.4363,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,27.3405,0.3075,16.7086,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,26.7116,0.9892,15.3979,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,36.9134,0.2236,26.3654,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,36.1217,0.1657,25.6316,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,44.1500,0.3070,33.5186,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,44.1500,0.3070,33.5186,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWWELSH1,CSWSWELSHUN1_RA,27.2418,0.5870,16.3304,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWWELSH3,CSWSWELSHUN3_RA,27.2418,0.5870,16.3304,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWWILKES1,CSWSWILKESUN1_RA,27.3915,0.7855,16.2815,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWWILKES2,CSWSWILKESUN2_RA,27.3915,0.7855,16.2815,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,CSWWILKES3,CSWSWILKESUN3_RA,27.2093,0.7463,16.1386,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-19.8253,-0.7576,-29.3922,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,DENL,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,DERS,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,DOE,DOE,18.2537,0.2957,7.6336,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,10.9032,0.0204,0.5584,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,DPC,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,DUK,VACS,23.2722,0.3762,12.5715,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDDY,EDDY,0.4894,-0.0343,-9.8007,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,30.5445,0.1213,20.0988,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-4.5032,-0.1294,-14.6982,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,36.0295,-0.0442,25.7493,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE.SLCC,EDESTL4391_PLT,32.4998,0.0400,22.1354,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,32.3592,0.0735,21.9612,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,18.7381,-0.1152,8.5288,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_EC_01,EDELAR3821UN1_RA,30.5445,0.1213,20.0988,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_EC_02,EDELAR3821UN2_RA,30.5445,0.1213,20.0988,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_EC_03,EDELAR3821UN3_RA,30.5445,0.1213,20.0988,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_EC_04,EDELAR3821UN4_RA,30.5445,0.1213,20.0988,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_EDE,EDE_LA,30.1107,0.2702,19.5161,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_ERW,EDEERWFUNG1_RA,-9.1183,-0.4970,-18.9457,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-3.4773,-0.5792,-13.2225,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,27.6200,0.5038,16.7918,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,27.6200,0.5038,16.7918,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,27.6200,0.5038,16.7918,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,27.6200,0.5038,16.7918,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,-1.3500,0.3861,-12.0605,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_RIV_10,EDERIV1671UN10_RA,32.5301,-0.0239,22.2296,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_RIV_11,EDERIV1671UN11_RA,32.5301,-0.0239,22.2296,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_RIV_12,EDERIV453UN12_PLT,32.2358,-0.3182,22.2296,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_SL_01,EDESTL4391UN1_RA,32.4998,0.0400,22.1354,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EDE_SWMP,EDE_SWMP_LA,29.0040,0.3876,18.2920,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EEI,EEI,18.0910,0.2946,7.4720,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EES,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-5.1710,-0.5310,-14.9645,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,ERCOTE,ERCOTE,27.2418,0.5870,16.3304,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,ERCOTN,ERCOTN,-9.6513,-0.6644,-19.3114,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,1.6017,-0.3313,-8.3914,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,FMPP,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,FPC,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,FPL,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,FREM_50T,OPPDFREM_GUN1_RA,2.7697,-0.1407,-7.4141,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,FREM_6,OPPDFREM_AUN6_RA,2.7637,-0.1461,-7.4147,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,FREM_7,OPPDFREM_AUN7_RA,2.7637,-0.1461,-7.4147,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,FREM_8,OPPDFREM_AUN8_RA,2.6993,-0.2104,-7.4147,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,FREM_LOAD,FREM_LOAD_LA,2.7536,-0.1562,-7.4147,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-10.8364,-0.4389,-20.7220,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,26.8228,0.6843,15.8141,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-18.3403,-1.4276,-27.2371,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-29.9695,-0.7988,-39.4951,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,33.4090,0.2643,22.8203,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,33.4090,0.2643,22.8203,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,33.4090,0.2643,22.8203,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,37.2998,0.1575,26.8179,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,37.2998,0.1575,26.8179,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,37.4456,0.1545,26.9667,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,37.4456,0.1545,26.9667,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-21.4869,-0.7289,-31.0824,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,46.8958,0.0987,36.4727,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,46.8958,0.0987,36.4727,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,46.8958,0.0987,36.4727,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.VOLT.0130,V130_DDR,38.4207,0.2625,27.8338,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA.VOLT.0237,V237_DDR,38.5209,0.2001,27.9964,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDAHUB2,GRDAHUB2_H,24.7038,-0.0885,14.4679,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDAHUB3,GRDAHUB3_H,18.5253,-0.1734,8.3743,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA_GRDA,GRDA_LA,38.1544,0.2071,27.6229,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA_HUB,GRDA_H,31.8026,0.0208,21.4574,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRDA_HUBSA,GRDASA_H,31.6930,0.0075,21.3610,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,GRE,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-12.5531,-0.2038,-22.6737,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GSEC_SPS,SPS_GSEC_LA,-17.4895,-0.6393,-27.1746,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GSPR2014HUB,GSPR2014HUB_H,-11.3192,-0.6858,-20.9579,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,GSPR2015HUB,GSPR2015HUB_H,-10.3294,-0.6849,-19.9689,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-18.4651,-1.2070,-27.5825,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,HARRISON,CSWSLEBROCKPLT1,26.9573,0.6318,16.0010,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,HAST_TNSK_HUB,HAST_TNSK_H,0.7637,-0.4724,-9.0884,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,HQST,PJM,14.4237,0.1883,3.9110,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,HST,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,21.8344,0.2327,11.2772,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,21.8344,0.2327,11.2772,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,22.3376,0.2333,11.7799,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,22.3376,0.2333,11.7799,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,21.2613,0.2324,10.7044,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,21.2613,0.2324,10.7044,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,INDN_INDN,INDN_LA,21.8674,0.2427,11.3003,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-4.6684,-0.6141,-14.3787,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,ISNE,PJM,14.4237,0.1883,3.9110,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,JEA,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,2.8795,-0.0932,-7.3517,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,2.8795,-0.0932,-7.3517,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,4.1529,-0.0223,-6.1492,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KACYCT4,KACYNEARMANUNCT4_RA,23.1626,0.1748,12.6634,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,60.4450,0.0074,50.1132,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,23.1626,0.1748,12.6634,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,23.5954,0.1876,13.0834,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,23.4763,0.1857,12.9662,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KACY_KACY,KACY_LA,23.7200,0.1835,13.2121,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,36.4549,0.1159,26.0146,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,13.7885,0.4191,3.0450,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-15.0517,-0.4819,-24.8942,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-41.9100,-0.6996,-51.5348,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.VOLT.0222,V222_DDR,-0.6563,0.0336,-11.0143,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.VOLT.0223,V223_DDR,13.1454,0.0106,2.8104,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.VOLT.0241,V241_DDR,13.7970,0.3673,3.1053,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.VOLT.0243,V243_DDR,20.9135,0.1742,10.4148,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.VOLT.0247,V247_DDR,14.4327,0.1036,4.0047,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.VOLT.0253,V253_DDR,36.5736,0.1194,26.1298,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-1.1748,-0.7186,-10.7806,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,10.0289,-0.1091,-0.1864,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,10.0289,-0.1091,-0.1864,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,10.0289,-0.1091,-0.1864,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,10.0289,-0.1091,-0.1864,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,36.8407,0.1141,26.4022,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,36.8407,0.1141,26.4022,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHUB,KCPLHUB_H,5.8533,-0.3595,-4.1116,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHUB17,KCPLHUB17_H,4.8322,-0.4079,-5.0843,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHUB18,KCPLHUB18_H,4.0797,-0.4054,-5.8393,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHUB19,KCPLHUB19_H,3.9731,-0.3831,-5.9683,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHUB20,KCPLHUB20_H,3.0915,-0.4249,-6.8081,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHUB21,KCPLHUB21_H,2.4767,-0.4198,-7.4280,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHUB22,KCPLHUB22_H,3.5424,-0.4151,-6.3669,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHUB23,KCPLHUB23_H,3.3229,-0.4274,-6.5742,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLHUB24,KCPLHUB24_H,2.3185,-0.4450,-7.5610,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,0.5468,0.0022,-9.7798,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,0.5468,0.0022,-9.7798,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,8.5340,-0.2812,-1.5092,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,8.5340,-0.2812,-1.5092,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,36.4558,0.1168,26.0146,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,36.4549,0.1159,26.0146,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,30.9639,0.1475,20.4920,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,30.9639,0.1475,20.4920,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,30.9639,0.1475,20.4920,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,30.9639,0.1475,20.4920,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,30.9639,0.1475,20.4920,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,30.9639,0.1475,20.4920,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,30.9639,0.1475,20.4920,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,30.9639,0.1475,20.4920,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,3.9046,-0.1342,-6.2856,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,18.3670,0.1092,7.9334,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KCPL_KCPL,KCPL_LA,21.6824,0.0965,11.2615,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KENN,KENN_LA,3.5481,0.3727,-7.1490,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KEP2_SECI,KEP2_SECI_LA,-16.3264,-0.7346,-25.9162,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KERR_1,GRDAKERR_HYDUN1_RA,38.0958,0.1873,27.5841,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KERR_2,GRDAKERR_HYDUN2_RA,37.9572,0.1926,27.4402,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KERR_3,GRDAKERR_HYDUN3_RA,37.9572,0.1926,27.4402,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KERR_4,GRDAKERR_HYDUN4_RA,38.0958,0.1873,27.5841,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,10.0288,-0.1092,-0.1864,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,10.0288,-0.1092,-0.1864,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,11.0515,-0.0452,0.7723,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,11.0515,-0.0452,0.7723,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,7.9180,-0.1106,-2.2958,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,6.5282,-0.0920,-3.7043,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,6.5282,-0.0920,-3.7043,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-14.5133,-0.8254,-24.0123,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-14.5133,-0.8254,-24.0123,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-14.5133,-0.8254,-24.0123,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-7.5565,-0.4191,-17.4618,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-7.5565,-0.4191,-17.4618,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-14.7212,-0.8381,-24.2075,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-8.7637,-0.4842,-18.6039,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-2.9760,-0.3450,-12.9554,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,53.5312,-0.0159,43.2226,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,53.5312,-0.0159,43.2226,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,1.3650,-0.2348,-8.7247,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,1.3650,-0.2348,-8.7247,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,1.3650,-0.2348,-8.7247,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-10.2484,-0.6225,-19.9503,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-6.5041,-0.7575,-16.0711,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,4.2445,-0.3151,-5.7649,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,5.4097,0.0238,-4.9385,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LAFA,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LAM345,LAM345,-15.1085,-0.9595,-24.4735,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,LEPA,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,2.6180,-0.1770,-7.5294,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_LES,LES_LA,2.5948,-0.1861,-7.5435,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,2.6645,-0.2018,-7.4581,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,2.5010,-0.2193,-7.6041,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,2.5010,-0.2193,-7.6041,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,2.5010,-0.2193,-7.6041,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,2.6649,-0.2015,-7.4581,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,2.6645,-0.2018,-7.4581,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_WAVERLY,LES_WAVERLY_H,2.5952,-0.2137,-7.5155,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,3.0194,-0.1784,-7.1266,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,3.0194,-0.1784,-7.1266,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,LGEE,LGEE,16.6948,0.2412,6.1291,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MALDEN,MALDEN_LA,4.8946,0.3613,-5.7911,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MCWEST,MCWEST,5.6622,0.1423,-4.8045,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MDU,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-0.6578,-0.3576,-10.6247,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,1.9246,-0.0620,-8.3378,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,3.1118,0.3466,-7.5593,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MEAN_NPPD,NPPD_MEAN_LA,-0.6890,-0.5776,-10.4358,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MEC,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MHEB,MHEB,6.6272,0.1770,-3.8742,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-5.2484,-0.6067,-14.9661,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-10.4187,-0.8021,-19.9411,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-5.2484,-0.6067,-14.9661,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-5.2484,-0.6067,-14.9661,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-10.4187,-0.8021,-19.9411,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-14.9270,-0.5875,-24.6640,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MISO,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-15.8508,-0.7058,-25.4694,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-15.8508,-0.7058,-25.4694,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-1.7245,-0.3539,-11.6950,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-16.7308,-0.8947,-26.1605,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-9.5095,-0.6547,-19.1792,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-17.5574,-0.8021,-27.0798,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-15.4495,-0.6627,-25.1113,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-17.7341,-0.7544,-27.3042,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-15.0253,-0.6170,-24.7328,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-15.0253,-0.6170,-24.7328,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-15.0253,-0.6170,-24.7328,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-15.0253,-0.6170,-24.7328,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-15.0253,-0.6170,-24.7328,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,8.3848,0.0577,-1.9973,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,14.1546,0.2649,3.5652,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,14.1546,0.2649,3.5652,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,12.8013,0.1875,2.2894,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,13.0418,0.4048,2.3126,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MOWR,AECI,21.2660,0.2053,10.7363,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,14.1235,0.1451,3.6540,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,14.4717,0.2694,3.8779,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,0.1866,-0.4764,-9.6615,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-0.9101,-0.2328,-11.0017,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-26.9713,-0.7542,-36.5415,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,0.2202,-0.4427,-9.6615,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,10.9071,0.0243,0.5584,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,10.9071,0.0243,0.5584,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,10.9074,0.0246,0.5584,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,10.9074,0.0246,0.5584,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,-0.6563,0.0336,-11.0143,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,-0.6563,0.0336,-11.0143,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,-0.6563,0.0336,-11.0143,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,-0.6903,-0.0004,-11.0143,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,-0.6563,0.0336,-11.0143,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,-0.6563,0.0336,-11.0143,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,-0.6563,0.0336,-11.0143,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,18.8907,0.2829,8.2834,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,12.4434,0.0227,2.0962,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,11.3849,-0.0166,1.0770,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,11.3849,-0.0165,1.0770,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,11.3849,-0.0165,1.0770,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,22.1846,0.1133,11.7469,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,22.1846,0.1133,11.7469,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MPS_MPS,MPS_LA,12.0431,0.1335,1.5852,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MSTNG,SPSMSTNGPLT1,-13.6328,0.0477,-24.0050,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MSTNG4,SPSMSTNGUN4_RA,-13.6628,0.0178,-24.0050,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,MSTNG5,SPSMSTNGUN5_RA,-13.6328,0.0477,-24.0050,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,-13.6328,0.0477,-24.0050,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NBSO,PJM,14.4237,0.1883,3.9110,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,1.5170,-0.4678,-8.3396,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,1.5159,-0.4689,-8.3396,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-18.9972,-1.7589,-27.5627,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NHC1,VACS,23.2722,0.3762,12.5715,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,2.8668,-0.1254,-7.3323,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,2.8668,-0.1254,-7.3323,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,2.8668,-0.1254,-7.3323,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-0.1806,-0.7481,-9.7569,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,0.3029,-0.7007,-9.3208,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,1.4932,-0.4160,-8.4152,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,0.5955,-0.2373,-9.4916,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,0.3029,-0.7007,-9.3208,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.HUB.PY2018,NPPDPY18_H,-0.4738,-0.5934,-10.2048,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,-0.3777,-0.5858,-10.1163,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,-0.4160,-0.5836,-10.1568,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,-0.3262,-0.5720,-10.0786,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,0.1800,-0.2897,-9.8547,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-1.8001,-0.6993,-11.4252,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-1.8001,-0.6993,-11.4252,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-1.9046,-0.5637,-11.6653,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,0.1800,-0.2897,-9.8547,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,4.0300,-0.7110,-5.5834,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,-0.4433,-0.8679,-9.8998,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-4.4282,-0.6872,-14.0654,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,-0.4433,-0.8679,-9.8998,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,0.5515,-0.7573,-9.0156,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-0.8349,-0.8059,-10.3535,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,2.1938,-0.1226,-8.0080,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,0.3029,-0.7007,-9.3208,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-4.0036,-0.7048,-13.6232,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-1.8001,-0.6993,-11.4252,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-1.8001,-0.6993,-11.4252,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-1.1650,-0.5036,-10.9858,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-1.2199,-0.5148,-11.0295,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-1.2199,-0.5148,-11.0295,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,-0.4096,-0.2914,-10.4427,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-15.3600,-0.0499,-25.6345,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,0.5767,-0.5444,-9.2033,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,0.0592,-0.6095,-9.6557,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-15.6800,-0.0077,-25.9967,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-18.4494,-0.0161,-28.7577,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.NELI.DDR,NELI_DDR,0.3542,-0.3708,-9.5994,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.NPPM.1058,SH1058_DDR,7.0772,-0.0988,-3.1485,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,-0.3377,-0.3598,-10.3024,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,0.3029,-0.7007,-9.3208,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,1.4932,-0.4160,-8.4152,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,0.1800,-0.2897,-9.8547,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.TECH.1,KEARNE_DDR,-0.1807,-0.2619,-10.2432,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,1.3683,-0.8764,-8.0798,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,1.3683,-0.8764,-8.0798,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,0.0857,-0.3423,-9.8964,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD.VOLT.0236,V236_DDR,1.9910,-0.1233,-8.2102,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD2017HUB,NPPD2017HUB_H,-0.4657,-0.5911,-10.1990,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,6.1645,-0.3234,-3.8365,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-0.1806,-0.7481,-9.7569,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,-0.4430,-1.0212,-9.7462,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,-0.4430,-1.0212,-9.7462,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,2.0281,-0.1468,-8.1496,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,1.9986,-0.1156,-8.2102,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-4.1036,-0.2245,-14.2036,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-1.0843,-0.5158,-10.8929,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,6.8801,-0.2958,-3.1485,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,6.8801,-0.2958,-3.1485,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,6.8801,-0.2958,-3.1485,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,0.7772,-0.4652,-9.0820,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,1.3883,-0.4225,-8.5136,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,0.9768,-0.3374,-9.0103,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,0.1100,-0.8505,-9.3639,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,0.8227,-0.7941,-8.7076,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-2.4293,-0.7454,-12.0083,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-2.6308,-0.7461,-12.2091,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,1.3563,-0.4140,-8.5541,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,1.3473,-0.4230,-8.5541,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,1.3473,-0.4230,-8.5541,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,1.3450,-0.3989,-8.5805,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,4.0300,-0.7110,-5.5834,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,1.3043,-0.4020,-8.6181,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,2.1779,-0.2751,-7.8714,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,0.7854,-0.4421,-9.0970,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,0.7766,-0.4487,-9.0991,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,0.7812,-0.4416,-9.1016,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,0.7812,-0.4416,-9.1016,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,0.7772,-0.4652,-9.0820,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,0.7414,-0.5010,-9.0820,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,0.8969,-0.3829,-9.0446,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,1.4053,-0.2390,-8.6801,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-2.4317,-0.7168,-12.0393,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,1.2804,-0.7889,-8.2552,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-4.7491,-0.7209,-14.3526,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,7.2286,0.0527,-3.1485,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,0.3542,-0.3708,-9.5994,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-2.2262,-0.7255,-11.8251,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-2.2262,-0.7255,-11.8251,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_NPPD,NPPD_LA,2.0103,-0.3337,-7.9804,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,2.1779,-0.2751,-7.8714,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,2.1779,-0.2751,-7.8714,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,1.1385,-0.2699,-8.9160,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-1.7290,-0.6190,-11.4345,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NSB,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,NSP,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NSSO,PJM,14.4237,0.1883,3.9110,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,NYIS,PJM,14.4237,0.1883,3.9110,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-18.8585,-1.1776,-28.0053,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-20.9542,-0.7522,-30.5264,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-5.5049,-0.5841,-15.2452,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-5.5049,-0.5841,-15.2452,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-18.3619,-1.3262,-27.3601,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-29.9695,-0.7988,-39.4951,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-95.1435,-0.4870,-104.9810,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-44.6863,-0.7295,-54.2812,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-23.8853,-0.7355,-33.4742,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-20.3966,-0.7588,-29.9622,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-0.9911,-0.2887,-11.0268,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-23.8853,-0.7355,-33.4742,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-18.5171,-1.2963,-27.5452,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-14.9270,-0.5875,-24.6640,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-19.0483,-1.1482,-28.2245,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,16.4993,-0.0841,6.2590,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-20.3966,-0.7588,-29.9622,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-19.6397,-0.7179,-29.2462,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-6.0001,-0.7162,-15.6083,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-15.4657,-0.6149,-25.1752,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-44.1164,-0.0854,-54.3555,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-14.9270,-0.5875,-24.6640,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-14.9270,-0.5875,-24.6640,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-20.3966,-0.7588,-29.9622,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-13.8107,-0.6129,-23.5222,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.NUEN.LAM1,LAM1_DDR,32.7955,0.7373,21.7337,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-0.9911,-0.2887,-11.0268,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-0.9911,-0.2887,-11.0268,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-14.1197,-0.6109,-23.8332,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-3.3313,-0.3234,-13.3323,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-3.3313,-0.3234,-13.3323,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-3.3313,-0.3234,-13.3323,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,2.3304,-0.2777,-7.7163,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,2.3304,-0.2777,-7.7163,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-3.3313,-0.3234,-13.3323,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-3.3313,-0.3234,-13.3323,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-20.3966,-0.7588,-29.9622,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,13.0017,0.4507,2.2265,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-18.5171,-1.2963,-27.5452,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-33.7243,-0.2410,-43.8077,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-19.6397,-0.7179,-29.2462,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,29.0010,0.4612,18.2154,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-20.4883,-0.5967,-30.2161,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-20.4883,-0.5967,-30.2161,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-20.4883,-0.5967,-30.2161,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-20.4883,-0.5967,-30.2161,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-22.6317,-1.0561,-31.9001,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-25.2820,-0.7179,-34.8886,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-20.9542,-0.7522,-30.5264,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-30.0026,-0.6983,-39.6287,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-30.0026,-0.6983,-39.6287,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-31.9400,-0.1122,-42.1522,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-17.4785,-0.6725,-27.1304,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-17.4785,-0.6725,-27.1304,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-17.4785,-0.6725,-27.1304,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0033,FOSTER_DDR,8.3426,-0.2500,-1.7318,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,31.9986,0.3759,21.2983,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0035,TARBY_DDR,32.7731,0.5936,21.8551,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,31.9986,0.3759,21.2983,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,31.7392,0.2735,21.1413,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,31.7392,0.2735,21.1413,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-39.9025,-0.1411,-50.0858,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0040,TROSPER_DDR,11.6888,-0.2339,1.5983,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,11.6411,-0.2339,1.5506,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,30.4047,0.5499,19.5303,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0115,V115_DDR,-0.0149,-0.2833,-10.0560,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0116,V116_DDR,38.6900,-0.0403,28.4059,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0118,V118_DDR,9.4690,-0.0060,-0.8494,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0125,V125_DDR,31.1738,0.6311,20.2183,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0126,V126_DDR,33.5915,0.3292,22.9379,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0129,V129_DDR,-4.4676,-0.4801,-14.3119,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,36.0000,-0.2910,25.9666,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0134,V134_DDR,34.3436,0.4034,23.6157,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0138,V138_DDR,33.0061,0.2844,22.3973,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,29.6731,-0.2407,19.5894,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0143,V143_DDR,31.4147,0.2173,20.8730,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0149,V149_DDR,-12.7746,-0.5501,-22.5489,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0150,V150_DDR,-12.8672,-0.5937,-22.5979,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0155,V155_DDR,32.4670,0.2348,21.9078,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0156,V156_DDR,36.0000,-0.2910,25.9666,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0166,V166_DDR,33.5453,0.6097,22.6112,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,28.9290,-0.2448,18.8494,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-12.8672,-0.5937,-22.5979,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0170,V170_DDR,-14.2787,-0.6107,-23.9925,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-21.3469,-0.5221,-31.1492,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0176,V176_DDR,-12.8672,-0.5937,-22.5979,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0177,V177_DDR,-21.9765,-1.0458,-31.2551,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,22.2014,-0.2442,12.1211,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-10.0820,-0.6312,-19.7752,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0195,V195_DDR,145.4157,0.6227,134.4685,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0197,V197_DDR,34.5190,0.4048,23.7898,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0198,V198_DDR,33.5453,0.6097,22.6112,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0208,V208_DDR,145.5671,0.6342,134.6084,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0209,V209_DDR,145.5671,0.6342,134.6084,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,34.5045,0.3098,23.8703,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0216,V216_DDR,11.6288,-0.2346,1.5390,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0219,V219_DDR,32.4670,0.2348,21.9078,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0220,V220_DDR,-12.8672,-0.5937,-22.5979,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0224,V224_DDR,-0.7276,-0.2972,-10.7548,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0225,V225_DDR,-0.7271,-0.2967,-10.7548,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0226,V226_DDR,-0.7276,-0.2972,-10.7548,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0227,V227_DDR,-0.7276,-0.2972,-10.7548,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0229,V229_DDR,-35.9869,-0.0990,-46.2123,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0231,V231_DDR,8.2319,0.0539,-2.1464,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0238,V238_DDR,-21.9279,-0.7896,-31.4627,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.VOLT.0242,V242_DDR,32.7027,0.2591,22.1192,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-19.7767,-1.5421,-28.5590,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-14.9270,-0.5875,-24.6640,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-21.4877,-0.7337,-31.0784,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-19.0396,-1.1395,-28.2245,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-19.7767,-1.5421,-28.5590,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-18.7619,-1.3124,-27.7740,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-50.2087,-0.8331,-59.7000,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEHL7,OKGEHL7_H,21.4513,-0.2271,11.3540,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEHL8,OKGEHSL1UN8_RA,21.4513,-0.2271,11.3540,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEHL910,OKGEHSL1PLT2,21.4513,-0.2271,11.3540,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-18.8361,-1.2097,-27.9508,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEMCC,OKGEMCCLAIPLT1,-3.0197,-0.4001,-12.9440,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,29.7930,0.1773,19.2913,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,29.7930,0.1773,19.2913,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,29.7930,0.1773,19.2913,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,15.3915,-0.3796,5.4466,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,15.3915,-0.3796,5.4466,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,15.3915,-0.3796,5.4466,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,15.3915,-0.3796,5.4466,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGESM1,OKGESEMINOLEUN1_RA,8.3793,-0.1698,-1.7753,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGESM2,OKGESEMINOLEUN2_RA,7.4552,-0.1941,-2.6751,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGESM3,OKGESEMINOLEUN3_RA,7.4552,-0.1941,-2.6751,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGESO1,OKGESONR1UN1_RA,-60.4940,-0.6604,-70.1580,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGESO2,OKGESONR1UN2_RA,-30.0026,-0.6983,-39.6287,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-18.8372,-1.2108,-27.9508,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-17.9340,-1.4410,-26.8174,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGETINK5A,OKGETINK5UN1_RA,9.8455,-0.2584,-0.2205,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGETINK5B,OKGETINK5UN2_RA,9.8455,-0.2584,-0.2205,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-18.3876,-0.9860,-27.7260,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-20.9542,-0.7522,-30.5264,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,29.6825,0.6963,18.6617,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-14.9270,-0.5875,-24.6640,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE_OKGE,OKGE_LA,13.7191,-0.1184,3.5130,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-33.7243,-0.2410,-43.8077,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-18.4148,-1.0132,-27.7260,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMLP,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,39.4456,0.1249,28.9963,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,29.9922,0.6534,19.0143,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-2.6725,-0.2885,-12.7084,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-95.0545,-0.3979,-104.9810,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-11.2137,-0.7085,-20.8296,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-23.8853,-0.7355,-33.4742,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-19.8059,-1.5338,-28.5965,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-9.8467,-1.0896,-19.0815,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,165.5993,0.0951,155.1798,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-95.0834,-0.4268,-104.9810,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-95.0834,-0.4268,-104.9810,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_SPP,OMPA_SPP_LA,-5.5078,-0.4359,-15.3963,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-19.7767,-1.5421,-28.5590,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,35.0180,0.1162,24.5774,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,35.0180,0.1162,24.5774,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,35.0180,0.1162,24.5774,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,35.0180,0.1162,24.5774,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,ONT,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,2.8161,-0.1287,-7.3797,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,2.8161,-0.1287,-7.3797,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,2.8161,-0.1287,-7.3797,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,2.8161,-0.1287,-7.3797,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,2.8161,-0.1287,-7.3797,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,2.8161,-0.1287,-7.3797,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,2.8161,-0.1287,-7.3797,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,2.8161,-0.1287,-7.3797,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,2.8161,-0.1287,-7.3797,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,2.8682,-0.1118,-7.3444,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,2.8668,-0.1254,-7.3323,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,2.7846,-0.1302,-7.4096,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,2.8149,-0.1061,-7.4034,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,2.8149,-0.1061,-7.4034,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD_GLDN,OPPD_GLDN_LA,2.7995,-0.1296,-7.3953,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,2.8472,-0.1193,-7.3580,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,4.0300,-0.7110,-5.5834,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,2.0897,-0.2792,-7.9555,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,2.8668,-0.1250,-7.3327,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD_OPPD,OPPD_LA,2.8574,-0.0994,-7.3677,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,2.8339,-0.0933,-7.3972,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,2.8278,-0.0971,-7.3996,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,OTP,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,OVEC,OVEC,15.7732,0.2209,5.2279,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PARAGOULD,PARAGOULD_LA,1.4021,0.3910,-9.3133,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,37.8999,0.1131,27.4624,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,37.8999,0.1131,27.4624,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,37.8999,0.1131,27.4624,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,37.5661,0.1506,27.0910,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,37.5661,0.1506,27.0910,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,37.5661,0.1506,27.0910,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,PIGGOTT,PIGGOTT_LA,4.0279,0.3687,-6.6652,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PJM,PJM,14.4237,0.1883,3.9110,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PLUM,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,POPLARBLUFF,POPLARBLUFF_LA,9.1866,0.3343,-1.4722,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,5.4943,-0.0038,-4.8263,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,5.4943,-0.0038,-4.8263,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,5.5601,0.0156,-4.7799,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,5.5601,0.0156,-4.7799,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,6.3034,0.7248,-4.7458,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,6.3034,0.7248,-4.7458,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,5.6588,0.1342,-4.7998,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,4.9514,-0.3334,-5.0397,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-8.5605,-0.4537,-18.4312,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,83.7632,0.1228,73.3161,10.3243\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,0.6982,0.0791,-9.7053,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-3.9873,-0.0253,-14.2864,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,44.7679,0.3329,34.1106,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,33.6692,0.3487,22.9960,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,5.5427,-0.0324,-4.7492,10.3243\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,5.7490,0.1842,-4.7596,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,4.3905,-0.2074,-5.7265,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,13.9500,0.9932,2.6324,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,6.3643,0.2636,-4.2237,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,5.2244,0.1009,-5.2009,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,PUPP,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,RCEAST,RCEAST,2.4368,-0.7091,-7.1786,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SALINA_1,GRDASALINA1UN1_RA,38.0968,0.1883,27.5841,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SALINA_2,GRDASALINA1UN2_RA,38.0968,0.1883,27.5841,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SALINA_3,GRDASALINA1UN3_RA,38.0968,0.1883,27.5841,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SALINA_4,GRDASALINA1UN4_RA,38.0968,0.1883,27.5841,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SALINA_5,GRDASALINA1UN5_RA,38.0968,0.1883,27.5841,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SALINA_6,GRDASALINA1UN6_RA,38.0968,0.1883,27.5841,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SARPY_1,OPPDSARPYUN1_RA,2.8403,-0.1188,-7.3653,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SARPY_2,OPPDSARPYUN2_RA,2.8565,-0.0979,-7.3700,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SARPY_3,OPPDSARPYUN3_RA,2.8355,-0.1415,-7.3474,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SARPY_4,OPPDSARPYUN4_RA,2.8355,-0.1415,-7.3474,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SARPY_5,OPPDSARPYUN5_RA,2.8355,-0.1415,-7.3474,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SC,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SCEG,VACS,23.2722,0.3762,12.5715,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SCSE,SCSE,-1.9540,-0.6555,-11.6230,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SEC,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-19.7910,-1.0032,-29.1122,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-19.7910,-1.0032,-29.1122,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-19.7910,-1.0032,-29.1122,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-14.6322,-0.8058,-24.1509,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-19.7910,-1.0032,-29.1122,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-16.3142,-0.9973,-25.6413,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-15.7866,-1.0005,-25.1105,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-15.7866,-1.0005,-25.1105,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-15.0266,-0.6183,-24.7328,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-22.5551,-0.9057,-31.9739,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-7.5999,-0.4625,-17.4618,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-15.1223,-0.7234,-24.7233,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-9.7249,-0.8472,-19.2021,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-18.9339,-1.0056,-28.2527,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-9.8128,-0.8378,-19.2994,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-19.0494,-0.9904,-28.3834,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-16.4469,-0.6104,-26.1609,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-14.6351,-0.8773,-24.0822,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-14.6351,-0.8773,-24.0822,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-14.6351,-0.8773,-24.0822,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-14.6351,-0.8773,-24.0822,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-14.8814,-0.9310,-24.2749,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-16.3142,-0.9973,-25.6413,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI_SECI,SECI_LA,-13.8958,-0.7078,-23.5125,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-4.6684,-0.6141,-14.3787,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-4.6684,-0.6141,-14.3787,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-15.0266,-0.6183,-24.7328,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SEHA,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-18.4148,-1.0132,-27.7260,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SERU,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SETH,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SGE,SGE,-1.1157,-0.6282,-10.8119,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SMEP,MISO,13.8425,0.2296,3.2885,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SOCO,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPA,SPA,25.1458,0.4106,14.4108,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPC,SPC,6.0841,0.4240,-4.6643,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPPNORTH_HUB,SPPNORTH_H,2.5305,-0.1968,-7.5971,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPPSOUTH_HUB,SPPSOUTH_H,0.5774,-0.5340,-9.2130,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,25.3485,0.3664,14.6577,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,25.3485,0.3664,14.6577,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,24.6518,0.3484,13.9790,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,24.6518,0.3484,13.9790,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_NIXA,SPRM_NIXA_LA,25.5723,0.3630,14.8849,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_SPRM,SPRM_LA,25.4483,0.4029,14.7210,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,25.6455,0.3123,15.0088,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,25.6455,0.3123,15.0088,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,25.6197,0.2865,15.0088,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,25.6455,0.3123,15.0088,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-17.2766,-0.5311,-27.0699,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-18.0186,-0.7211,-27.6219,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-18.4694,-1.2476,-27.5462,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-18.4694,-1.2476,-27.5462,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-18.8015,-1.1329,-27.9931,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,-15.8927,-0.8172,-25.3999,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-18.7805,-1.5063,-27.5987,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,0.0000,-0.6770,-9.6474,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-18.4345,-0.6762,-28.0827,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,-1.9146,-0.0064,-12.2326,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,0.1434,-0.0064,-10.1746,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,0.1434,-0.0064,-10.1746,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,-1.9146,-0.0064,-12.2326,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-18.4347,-1.2124,-27.5467,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-18.0186,-0.7211,-27.6219,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-18.2179,-1.0483,-27.4941,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-18.3202,-1.3482,-27.2965,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-18.0349,-0.9515,-27.4078,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-17.9627,-0.8186,-27.4686,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-18.1701,-1.0323,-27.4622,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-18.1331,-1.3433,-27.1142,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-18.1331,-1.3433,-27.1142,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-18.1331,-1.3433,-27.1142,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-18.1331,-1.3433,-27.1142,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GRID.WRAB,WRAB_DDR,-18.2506,-0.9612,-27.6138,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-18.1331,-1.3433,-27.1142,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-18.3514,-0.7111,-27.9647,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-18.3514,-0.7111,-27.9647,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-18.3388,-0.6783,-27.9849,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-18.3388,-0.6783,-27.9849,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-18.3388,-0.6783,-27.9849,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-18.3514,-0.7111,-27.9647,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-18.4526,-1.1342,-27.6428,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-18.4525,-1.1342,-27.6427,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-18.4523,-1.1342,-27.6425,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-18.9972,-1.7589,-27.5627,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,-1.2206,-0.0285,-11.5166,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-18.4317,-0.6814,-28.0747,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-18.4317,-0.6814,-28.0747,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-18.4317,-0.6814,-28.0747,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-18.4317,-0.6814,-28.0747,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,-8.4661,0.0418,-18.8323,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,-2.1868,-0.0225,-12.4887,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,-2.1868,-0.0225,-12.4887,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-18.3695,-0.9679,-27.7260,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-18.4347,-1.1256,-27.6335,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-18.4347,-1.1256,-27.6335,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-18.4554,-1.1308,-27.6491,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-18.2506,-0.9612,-27.6138,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-18.1823,-1.2016,-27.3051,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-18.3385,-1.1581,-27.5049,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-18.3619,-1.3262,-27.3601,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-18.2958,-0.9868,-27.6335,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-17.9106,-0.6348,-27.6003,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-17.9106,-0.6348,-27.6003,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-17.8539,-0.6483,-27.5301,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-18.6757,-0.9784,-28.0217,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-18.1233,-1.2382,-27.2095,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-18.5713,-1.2970,-27.5987,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-18.6787,-0.9815,-28.0217,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-18.4149,-1.1926,-27.5467,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-18.1000,-0.6362,-27.7882,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,0.2990,-0.3780,-9.6474,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-18.1000,-0.6362,-27.7882,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,-18.0294,-0.4769,-27.8769,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-18.3326,-1.2143,-27.4427,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,-0.0105,0.4198,-10.7547,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,-0.0074,0.4229,-10.7547,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,-0.8503,0.2349,-11.4097,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,-2.2637,-0.0120,-12.5762,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,0.6832,0.2489,-9.8901,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-15.1085,-0.9595,-24.4735,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-18.2935,-1.0026,-27.6153,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-17.7961,-0.6208,-27.4997,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-17.7961,-0.6208,-27.4997,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-18.1000,-0.6362,-27.7882,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-18.4082,-0.6248,-28.1079,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,-11.9791,0.2918,-22.5954,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-17.4528,-0.1784,-27.5988,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-17.6357,-0.4176,-27.5426,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-18.1722,-0.7331,-27.7635,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,-0.0105,0.4198,-10.7547,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,0.8343,0.5954,-10.0855,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,0.6965,0.4576,-10.0855,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-18.5747,-0.8774,-28.0217,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-17.6653,-0.3911,-27.5987,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-18.0934,-1.1863,-27.2315,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-18.1100,-1.2022,-27.2322,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0163,V163_DDR,-18.1932,-0.9713,-27.5464,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0168,V168_DDR,-19.2466,-0.6949,-28.8761,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0180,V180_DDR,0.8343,0.5954,-10.0855,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0181,V181_DDR,-17.9811,-1.0865,-27.2190,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0182,V182_DDR,0.8268,0.3332,-9.8308,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0199,V199_DDR,-12.2249,0.2234,-22.7727,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0200,V200_DDR,-1.4343,0.2214,-11.9801,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.VOLT.0235,V235_DDR,-18.1823,-1.2016,-27.3051,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-18.7805,-1.5063,-27.5987,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,0.0000,-0.6770,-9.6474,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-18.5238,-1.2657,-27.5825,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-18.3831,-1.0697,-27.6378,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS_SPS,SPS_LA,-9.1301,-0.1445,-19.3100,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,-14.7826,-0.2583,-24.8488,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,SSCN_NPPD,SSCN_NPPD_LA,-0.2187,-0.1621,-10.3810,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,9.2888,0.3259,-1.3615,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,9.2888,0.3259,-1.3615,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,TAL,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,TEC,SOUC,23.0746,0.3957,12.3544,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,1.2804,-0.7889,-8.2552,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,TVA,TVA,23.4640,0.3557,12.7838,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,UCUHUB,UCUHUB_H,-1.0734,-0.2064,-11.1914,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,UCUHUB17,UCUHUB17_H,-6.5160,-0.4567,-16.3837,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,UCUHUB18,UCUHUB18_H,-3.5785,-0.3688,-13.5341,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,UCUHUB19,UCUHUB19_H,-8.2546,-0.4194,-18.1596,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,UCUHUB20,UCUHUB20_H,-7.9502,-0.4063,-17.8683,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,UCUHUB21,UCUHUB21_H,-9.4955,-0.4790,-19.3409,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,UCUHUB22,UCUHUB22_H,-9.5584,-0.5034,-19.3794,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,UCUHUB23,UCUHUB23_H,-9.9779,-0.5089,-19.7935,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,UCUHUB24,UCUHUB24_H,-7.3033,-0.4363,-17.1915,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,6.1478,0.5051,-4.6818,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,6.1478,0.5051,-4.6818,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,5.3206,-0.1233,-4.8806,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,5.3206,-0.1233,-4.8806,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,5.8497,-0.1580,-4.3167,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,5.4983,-0.0738,-4.7523,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,5.4983,-0.0738,-4.7523,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,6.1478,0.5051,-4.6818,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,5.8988,-0.1571,-4.2685,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,6.1201,0.2302,-4.4346,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,4.9574,0.0567,-5.4237,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,2.8711,-0.9049,-6.5484,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,6.0951,0.5037,-4.7331,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,6.0951,0.5037,-4.7331,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,4.3548,-0.8792,-5.0904,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,5.0870,-0.1837,-5.0537,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,5.5092,-0.2368,-4.5784,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,4.4308,-0.1368,-5.7568,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,5.0114,0.1225,-5.4355,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,4.9313,-0.2136,-5.1795,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,4.8975,-0.3365,-5.0904,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,4.8975,-0.3365,-5.0904,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,5.1799,-0.1507,-4.9939,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,2.6797,-0.9971,-6.6477,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,5.5037,0.5874,-5.4081,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,5.7125,0.1396,-4.7516,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,5.7125,0.1396,-4.7516,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,5.7125,0.1396,-4.7516,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,5.8147,0.2460,-4.7557,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,5.8147,0.2460,-4.7557,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,5.8147,0.2460,-4.7557,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,6.2940,0.6253,-4.6557,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,5.6410,-0.1221,-4.5614,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,5.6410,-0.1221,-4.5614,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-1.5313,-0.6416,-11.2142,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,4.2620,-0.0835,-5.9789,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,5.9609,0.2250,-4.5886,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,2.8876,-0.2489,-7.1879,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,2.2147,-1.2460,-6.8638,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,5.0496,-0.2424,-5.0324,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,6.1037,0.4991,-4.7199,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,6.1037,0.4991,-4.7199,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,6.1030,0.4985,-4.7199,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,6.1037,0.4991,-4.7199,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,6.0156,0.4233,-4.7321,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,6.0156,0.4233,-4.7321,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,6.0156,0.4233,-4.7321,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,6.0156,0.4233,-4.7321,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,6.0156,0.4233,-4.7321,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,6.0156,0.4233,-4.7321,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,6.0156,0.4233,-4.7321,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,2.6395,-0.6779,-7.0070,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,6.0322,0.0425,-4.3348,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,3.5100,-0.0206,-6.7939,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,3.5100,-0.0206,-6.7939,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,2.3177,-0.2938,-7.7129,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,2.3177,-0.2938,-7.7129,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,5.7572,-0.0059,-4.5614,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,5.8568,0.0064,-4.4740,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,4.6610,-0.1815,-5.4820,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,2.9597,-0.8241,-6.5406,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,5.8068,0.0115,-4.5291,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,5.8497,-0.1580,-4.3167,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,5.8497,-0.1580,-4.3167,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,4.4308,-0.1368,-5.7568,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,2.3814,-0.7507,-7.1923,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,4.4387,-0.3443,-5.5415,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,2.7920,-0.8847,-6.6477,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,4.9479,-0.2837,-5.0928,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.FSE,WAUE.FSE_H,1.7438,-0.4535,-8.1271,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,5.7355,0.1714,-4.7603,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,5.7292,0.1697,-4.7649,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,2.4546,-0.9000,-6.9698,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,2.7487,-0.8437,-6.7320,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,5.7914,-0.1339,-4.3991,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,5.7808,-0.1883,-4.3554,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-16.4800,-0.7271,-26.0773,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,2.8711,-0.9049,-6.5484,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-10.3600,-0.5639,-20.1205,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,4.1226,-0.1854,-6.0165,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,4.1226,-0.1853,-6.0165,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,4.1233,-0.1847,-6.0165,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,4.9634,-0.1738,-5.1873,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,2.3814,-0.7507,-7.1923,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,5.5821,0.1345,-4.8768,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,4.2633,-0.2021,-5.8591,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,5.4587,0.5424,-5.4081,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,4.7656,0.1796,-5.7384,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,5.0682,0.1106,-5.3669,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,6.7825,-0.0333,-3.5086,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,4.7057,0.0228,-5.6415,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,4.6127,-0.1790,-5.5327,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,2.8876,-0.2489,-7.1879,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,7.7916,0.4861,-3.0189,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,4.4204,-0.1456,-5.7585,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,7.6047,0.3549,-3.0746,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,5.3956,0.1614,-5.0902,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,3.0194,-0.1784,-7.1266,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NTWK,WAUE.NTWK_H,4.5839,-0.0988,-5.6418,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,5.5973,0.4146,-5.1417,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,5.5973,0.4146,-5.1417,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,2.7979,-0.9779,-6.5486,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,2.3989,-0.9021,-7.0235,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,5.4039,-0.1328,-4.7878,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,2.7979,-0.9779,-6.5486,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,6.4736,0.0675,-3.9183,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,3.9837,-0.4242,-5.9165,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,2.8876,-0.2489,-7.1879,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,4.5506,-0.2046,-5.5692,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,3.3064,-1.1015,-5.9165,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,1.4281,-1.1173,-7.7791,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,1.9362,-1.1125,-7.2757,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,5.3047,-0.1452,-4.8745,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,1.6143,-0.9459,-7.7643,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,5.6437,0.0166,-4.6973,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,3.4229,-0.6511,-6.2505,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,2.9597,-0.8241,-6.5406,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.VOLT.0152,V152_DDR,6.4729,0.7635,-4.6150,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE.VOLT.0172,V172_DDR,6.0643,0.4672,-4.7273,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_BEPM,WAUE_BEPM_LA,5.4929,0.2209,-5.0525,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,5.6133,0.1356,-4.8468,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,4.7682,0.1856,-5.7419,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_EWA,WAUE_EWA_LA,2.4785,-0.6837,-7.1623,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,3.8782,-0.3724,-6.0739,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_HMMU,WAUE_HMMU_LA,3.8008,0.0289,-6.5525,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,6.9821,0.0002,-3.3425,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_MECB,WAUE_MECB_LA,4.3099,0.1328,-6.1473,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_MMPA,WAUE_MMPA_LA,6.5887,0.3179,-4.0537,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_MRES,WAUE_MRES_LA,4.6223,-0.0682,-5.6340,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,6.3558,0.5615,-4.5301,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,5.7355,0.1714,-4.7603,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,3.6397,-0.3537,-6.3310,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_OTP,WAUE_OTP_LA,7.1432,0.5224,-3.7036,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_OTPW,WAUE_OTPW_LA,11.0019,0.7095,-0.0320,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM,WAUE_UGPM_LA,5.2858,0.0317,-5.0703,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,5.4164,0.1432,-5.0512,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,4.7198,0.0051,-5.6097,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,2.6928,-0.2274,-7.4042,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,2.4785,-0.6837,-7.1623,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,3.8008,0.0289,-6.5525,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,3.8353,-0.3401,-6.1490,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,5.7355,0.1714,-4.7603,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,6.5887,0.3179,-4.0537,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,4.7882,-0.0306,-5.5056,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,3.5919,-0.4498,-6.2828,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,6.6166,0.5408,-4.2486,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-19.6320,-1.4074,-28.5491,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-14.7138,-0.9389,-24.0994,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,-1.8070,-0.8887,-11.2427,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,82.7442,0.2988,72.1209,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,82.7442,0.2988,72.1209,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-12.0628,-1.4511,-20.9361,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,76.0701,0.3588,65.3869,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,68.2659,0.3446,57.5969,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,15.2748,-0.6250,5.5753,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,15.2748,-0.6250,5.5753,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,15.2748,-0.6250,5.5753,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,15.2748,-0.6250,5.5753,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,15.2406,-0.6591,5.5753,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,15.2748,-0.6250,5.5753,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,15.2748,-0.6250,5.5753,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,15.2748,-0.6250,5.5753,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,7.3265,-0.5918,-2.4062,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-18.3619,-1.3262,-27.3601,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-27.3700,-0.9659,-36.7285,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-20.4747,-1.6943,-29.1048,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-18.6340,-1.3598,-27.5987,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_ENMC,WFEC_ENMC_LA,-8.2437,-0.0500,-18.5181,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-20.3966,-0.7588,-29.9622,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,35.7327,0.2778,25.1305,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,-6.6110,0.0016,-16.9370,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-19.6320,-1.4074,-28.5491,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-19.6320,-1.4074,-28.5491,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-19.6320,-1.4074,-28.5491,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_OKGE,WFEC_OKGE_LA,3.4435,0.0677,-6.9486,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,51.4627,0.3632,40.7751,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-16.0061,-1.5033,-24.8273,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-11.6910,-1.5826,-20.4328,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_WFEC,WFEC_LA,18.5136,-0.2470,8.4362,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,-6.6110,0.0016,-16.9370,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-6.1127,-0.6214,-15.8158,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-13.1631,-0.9601,-22.5274,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-0.5147,-0.3751,-10.4640,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-0.5147,-0.3751,-10.4640,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-0.5147,-0.3751,-10.4640,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-0.5147,-0.3751,-10.4640,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-0.5147,-0.3751,-10.4640,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-0.5147,-0.3751,-10.4640,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-0.5147,-0.3751,-10.4640,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,3.7995,0.3610,-6.8859,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-2.6830,-0.5141,-12.4934,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-15.5380,-0.7231,-25.1394,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-15.5380,-0.7231,-25.1394,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-15.5380,-0.7231,-25.1394,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-21.0460,-0.9044,-30.4660,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-21.0460,-0.9044,-30.4660,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-7.5608,-0.6570,-17.2282,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-7.5608,-0.6570,-17.2282,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-7.5608,-0.6570,-17.2282,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-2.6830,-0.5141,-12.4934,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,2.2710,-0.0100,-8.0434,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-6.9660,-0.5185,-16.7720,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-6.9660,-0.5184,-16.7720,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-6.9660,-0.5184,-16.7720,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-6.9660,-0.5184,-16.7720,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,2.2710,-0.0100,-8.0434,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-17.6036,-1.0095,-26.9185,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-27.5600,-0.3174,-37.5670,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.JEC.1,WRJEFFUN10_RA,-0.1472,-0.3705,-10.1012,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.JEC.2,WRJEFFUN11_RA,-0.2301,-0.3728,-10.1817,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.JEC.3,WRJEFFUN12_RA,-0.2827,-0.4254,-10.1817,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-21.4869,-0.7289,-31.0824,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-26.9648,-0.7477,-36.5415,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-26.9648,-0.7477,-36.5415,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.LEC.4,WRLECUN26_RA,3.9753,-0.0890,-6.2602,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.LEC.5,WRLECUN27_RA,3.6427,-0.0455,-6.6362,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-5.8106,-0.4473,-15.6877,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-5.8106,-0.4473,-15.6877,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-5.8106,-0.4473,-15.6877,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-5.7777,-0.4269,-15.6752,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-4.6684,-0.6141,-14.3787,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-4.6684,-0.6141,-14.3787,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-9.3683,-0.7650,-18.9277,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-5.7577,-0.5689,-15.5132,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-5.7577,-0.5689,-15.5132,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-6.5093,-0.7626,-16.0711,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-4.6684,-0.6141,-14.3787,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,0.4994,-0.4856,-9.3394,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-3.4773,-0.5792,-13.2225,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-26.9674,-0.7503,-36.5415,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,69.7902,0.3510,59.1148,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-7.0983,-1.1070,-16.3157,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-0.5147,-0.3751,-10.4640,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-2.1862,-0.7372,-11.7734,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,2.2710,-0.0100,-8.0434,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-2.6830,-0.5141,-12.4934,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-10.8418,-0.5497,-20.6166,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.THAYERLD,WR.THAYERLD_LA,8.7001,0.3506,-1.9749,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-11.6588,-0.5492,-21.4341,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0106,V106_DDR,-11.0348,-0.5230,-20.8362,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0139,WR.VOLT.0139_H,7.5816,0.0650,-2.8078,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-4.0405,-0.4290,-13.9359,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0146,WR.VOLT.0146_H,4.4134,0.0184,-5.9294,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0147,WR.VOLT.0147_H,4.4134,0.0184,-5.9294,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0148,WR.VOLT.0148_H,3.3107,0.0194,-7.0331,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-10.8494,-0.4503,-20.7236,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0157,V157_DDR,4.2943,0.0055,-6.0356,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0158,V158_DDR,4.4134,0.0184,-5.9294,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0159,WR.VOLT.0159_H,4.4134,0.0184,-5.9294,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-11.5954,-0.5862,-21.3337,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0173,V173_DDR,-6.0554,-0.5055,-15.8743,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0174,V174_DDR,-11.3473,-0.5365,-21.1352,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0184,V184_DDR,-10.8900,-0.5961,-20.6184,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-10.9891,-0.5430,-20.7705,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0186,V186_DDR,-10.6809,-0.5762,-20.4291,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-10.9787,-0.5753,-20.7278,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-11.6243,-0.5284,-21.4203,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-5.0955,-0.3736,-15.0463,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-1.5254,-0.3208,-11.5290,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-0.8379,-0.3443,-10.8180,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-0.8379,-0.3443,-10.8180,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-1.5254,-0.3208,-11.5290,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0245,V245_DDR,-10.9816,-0.5435,-20.7625,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.VOLT.0248,V248_DDR,-11.0348,-0.5230,-20.8362,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-16.6957,-0.6758,-26.3443,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,1.7449,-0.1447,-8.4348,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.WOLF,WRWOLFUN15_RA,-2.2200,-0.7926,-11.7518,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-17.6036,-1.0095,-26.9185,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,3.7510,0.3125,-6.8859,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-15.5380,-0.7231,-25.1394,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-15.5380,-0.7231,-25.1394,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-15.5380,-0.7231,-25.1394,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-15.5380,-0.7231,-25.1394,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-13.7703,-0.4355,-23.6592,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-3.9635,-0.4307,-13.8572,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-12.7318,-0.5516,-22.5046,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-12.7318,-0.5516,-22.5046,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-12.7318,-0.5516,-22.5046,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-12.7318,-0.5516,-22.5046,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-2.1843,-0.2839,-12.2248,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-2.1843,-0.2839,-12.2248,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-2.1843,-0.2839,-12.2248,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-2.1843,-0.2839,-12.2248,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-2.1843,-0.2839,-12.2248,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-2.1843,-0.2839,-12.2248,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-28.1612,-0.5074,-37.9783,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-28.1612,-0.5074,-37.9783,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-31.4519,-0.5154,-41.2610,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-31.4519,-0.5154,-41.2610,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_MIDW,WR_MIDW_LA,-8.0621,-0.6327,-17.7538,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,13.7350,0.2775,3.1330,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,12.6184,0.1308,2.1631,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-9.8558,-0.5658,-19.6144,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_SEG,WR_SEG_LA,7.3632,0.2131,-3.1743,10.3244\n03/19/2025 15:00:00,03/19/2025 20:00:00,WR_WR,WR_LA,-3.0542,-0.3385,-13.0402,10.3245\n03/19/2025 15:00:00,03/19/2025 20:00:00,YAD,VACS,23.2722,0.3762,12.5715,10.3245\n03/19/2025 16:00:00,03/19/2025 21:00:00,AEC,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,AECC_CSWS,CSWS_AECC_LA,31.8336,0.4526,21.2402,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,33.6716,0.3314,23.1994,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,31.2881,0.6008,20.5465,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,33.7005,0.2411,23.3186,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,28.0303,0.3845,17.5050,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,31.8797,0.2602,21.4787,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,28.4863,0.2705,18.0750,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,AECI,AECI,22.1985,0.1700,11.8876,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,AEPM_CSWS,CSWS_LA,31.2308,0.4425,20.6475,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,ALTW,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,AMRN,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-22.1654,-0.4812,-31.8250,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BBA,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BCA,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BEPM.ER01.DDR,ER01_DDR,0.7252,-1.1681,-8.2475,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BEPM_ER01,BEPM_ER01_LA,0.7252,-1.1681,-8.2475,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,-0.3974,-0.5022,-10.0360,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-2.9771,-0.3380,-12.7799,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BEPM_UM01,BEPM_UM01_LA,4.9568,0.3273,-5.5113,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BLKW,BLKW,-15.1098,-0.2455,-25.0051,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-30.0000,-0.9693,-39.1715,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-30.0000,-0.9693,-39.1715,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,6.6005,-0.8521,-2.6882,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.9826,-0.9519,-39.1715,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BRAZ,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BUBA,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-16.3961,-0.9000,-25.6369,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-18.5658,-0.5807,-28.1259,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-18.5658,-0.5807,-28.1259,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-18.5658,-0.5807,-28.1259,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-18.5658,-0.5807,-28.1259,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-18.5658,-0.5807,-28.1259,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-9.7328,-0.4481,-19.4255,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,1.1146,-0.2447,-8.7815,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,1.1146,-0.2447,-8.7815,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CLEC,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,32.7474,0.2442,22.3624,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,COWP,COWP_LA,18.5532,0.2853,8.1271,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,18.5532,0.2853,8.1271,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,18.5532,0.2853,8.1271,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CPLE,VACS,23.5201,0.3312,13.0481,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CPLW,VACS,23.5201,0.3312,13.0481,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,23.2738,0.3963,12.7367,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,23.2738,0.3963,12.7367,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,23.2738,0.3963,12.7367,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,23.2738,0.3963,12.7367,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CRTH_SPA,WRCRTH_SPA_LA,31.9492,0.1215,21.6869,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,30.5329,1.0806,19.3115,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-6.4336,-0.5153,-16.0591,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,28.4863,0.2705,18.0750,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,33.7005,0.2411,23.3186,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,30.1424,1.0732,18.9283,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,28.2665,0.7737,17.3520,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,26.5105,0.9739,15.3958,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,26.5105,0.9739,15.3958,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,33.4193,0.2674,23.0111,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,33.4193,0.2674,23.0111,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,33.3554,0.2035,23.0111,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,33.3554,0.2035,23.0111,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,28.4863,0.2705,18.0750,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,31.8331,0.7110,20.9813,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,53.9539,-0.0304,43.8434,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,53.8601,-0.1241,43.8434,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,37.3795,0.1054,27.1333,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,36.3857,0.1574,26.0875,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,36.3857,0.1574,26.0875,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,36.3858,0.1574,26.0876,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,36.3858,0.1574,26.0876,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-22.6120,-0.6084,-32.1445,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,-1.0667,-0.3573,-10.8502,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,44.0374,0.1629,33.7337,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-21.7760,-0.7166,-31.2002,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-21.7435,-0.6842,-31.2002,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-17.3119,-0.4093,-27.0434,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.GRID.CDL1,CDL1_DDR,41.4049,0.2363,31.0277,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-8.3222,-0.4523,-18.0107,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-5.9660,-0.7407,-15.3661,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,41.4049,0.2363,31.0277,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.NUEN.CSI1,CSI1_DDR,37.0041,0.2718,26.5914,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.NUEN.CSI2,CSI2_DDR,37.0078,0.2756,26.5914,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,32.7510,0.2477,22.3624,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.NUEN.GAZA,GAZA_DDR,41.4049,0.2363,31.0277,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,97.9900,0.4758,87.3734,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.NUEN.T201,NT201_DDR,36.1344,0.1864,25.8071,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-11.0435,-0.6862,-20.4981,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-11.0435,-0.6862,-20.4981,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,28.4863,0.2705,18.0750,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,27.8009,1.1265,16.5336,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-17.3119,-0.4093,-27.0434,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-17.3119,-0.4093,-27.0434,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-17.8276,-0.5884,-27.3800,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-21.7435,-0.6842,-31.2002,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,27.6658,0.6356,16.8894,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,33.4858,0.0851,23.2599,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,33.3437,-0.0570,23.2599,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,33.3395,-0.0612,23.2599,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,11.1882,0.0514,0.9960,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,11.1882,0.0514,0.9960,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,28.0352,0.7436,17.1508,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,37.7421,0.1742,27.4271,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,28.1891,0.7790,17.2692,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,28.5734,1.3606,17.0719,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,33.6221,0.3305,23.1508,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,37.0078,0.2756,26.5914,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0057,OKMU_DDR,44.7877,0.2700,34.3769,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0060,LEHIGH_DDR,97.9900,0.4758,87.3734,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0086,WARRENM_DDR,36.7102,0.2004,26.3690,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,28.1941,1.0277,17.0256,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,45.9066,0.1878,35.5780,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0121,V121_DDR,28.0352,0.7436,17.1508,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0122,V122_DDR,44.5476,0.1781,34.2287,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0124,V124_DDR,62.1722,0.1262,51.9052,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0135,V135_DDR,37.4710,0.2203,27.1099,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0144,V144_DDR,-0.6888,-0.3130,-10.5167,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0145,V145_DDR,-0.5347,-0.3597,-10.3158,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,28.0553,0.7583,17.1562,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,28.6349,0.4097,18.0844,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0175,V175_DDR,32.7510,0.2477,22.3624,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,28.6349,0.4097,18.0844,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,28.6883,0.4826,18.0649,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,37.4710,0.2203,27.1099,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,37.5135,0.2031,27.1696,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,36.8395,0.1784,26.5203,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,50.1053,0.0650,39.8995,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,36.3917,0.1481,26.1028,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,37.5135,0.2031,27.1696,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0211,V211_DDR,28.3991,0.9158,17.3425,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,46.5554,0.1918,36.2228,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0213,V213_DDR,37.2597,0.2025,26.9164,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0215,V215_DDR,45.4566,0.1844,35.1314,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0217,V217_DDR,46.6045,0.1812,36.2825,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0218,V218_DDR,49.6752,0.0731,39.4613,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0228,V228_DDR,38.2349,0.1541,27.9400,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0232,V232_DDR,37.1129,0.2240,26.7481,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0233,V233_DDR,37.7331,0.2146,27.3777,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0240,V240_DDR,42.9628,0.1447,32.6773,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0244,V244_DDR,37.5135,0.2031,27.1696,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0246,MDT1_DDR,97.9900,0.4758,87.3734,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0249,V249_DDR,37.2272,0.2144,26.8720,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0250,V250_DDR,-7.3043,-0.4947,-16.9504,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0251,V251_DDR,36.7538,0.1791,26.4339,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.VOLT.0252,V252_DDR,50.1053,0.0650,39.8995,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-24.7347,-0.6019,-34.2736,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,3.9939,-0.6687,-5.4782,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-19.1479,-1.1907,-28.0980,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,28.1241,0.7274,17.2558,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-20.7942,-1.1043,-29.8307,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-3.7759,-0.3991,-13.5176,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-3.7759,-0.3991,-13.5176,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-3.7759,-0.3991,-13.5176,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-3.7759,-0.3991,-13.5176,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-3.7759,-0.3991,-13.5176,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,28.4863,0.2705,18.0750,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,28.8000,0.9518,17.7074,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,37.0970,0.2081,26.7481,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,36.3978,0.1530,26.1040,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,51.8384,0.3003,41.3973,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,51.8384,0.3003,41.3973,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWWELSH1,CSWSWELSHUN1_RA,27.9354,0.5308,17.2638,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWWELSH3,CSWSWELSHUN3_RA,27.9354,0.5308,17.2638,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWWILKES1,CSWSWILKESUN1_RA,27.6774,0.7323,16.8043,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWWILKES2,CSWSWILKESUN2_RA,27.6774,0.7323,16.8043,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,CSWWILKES3,CSWSWILKESUN3_RA,27.2575,0.6948,16.4219,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-21.7334,-0.6740,-31.2002,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,DENL,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,DERS,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,DOE,DOE,18.7185,0.2457,8.3320,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,10.1682,-0.0115,0.0389,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,DPC,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,DUK,VACS,23.5201,0.3312,13.0481,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDDY,EDDY,-1.9339,0.2253,-12.3001,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,29.8389,0.1019,19.5962,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-4.8366,-0.1373,-14.8401,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,35.4041,-0.0521,25.3154,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE.SLCC,EDESTL4391_PLT,31.8255,0.0251,21.6596,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,31.6797,0.0578,21.4811,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,18.2277,-0.1310,8.2179,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_EC_01,EDELAR3821UN1_RA,29.8389,0.1019,19.5962,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_EC_02,EDELAR3821UN2_RA,29.8389,0.1019,19.5962,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_EC_03,EDELAR3821UN3_RA,29.8389,0.1019,19.5962,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_EC_04,EDELAR3821UN4_RA,29.8389,0.1019,19.5962,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_EDE,EDE_LA,30.1733,0.2516,19.7808,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_ERW,EDEERWFUNG1_RA,-10.4066,-0.4902,-20.0572,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-5.3462,-0.5977,-14.8893,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,29.4500,0.4932,18.8160,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,29.4500,0.4932,18.8160,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,29.4500,0.4932,18.8160,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,29.4500,0.4932,18.8160,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,3.4580,0.3450,-7.0278,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_RIV_10,EDERIV1671UN10_RA,31.8590,-0.0377,21.7559,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_RIV_11,EDERIV1671UN11_RA,31.8590,-0.0377,21.7559,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_RIV_12,EDERIV453UN12_PLT,31.5704,-0.3263,21.7559,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_SL_01,EDESTL4391UN1_RA,31.8255,0.0251,21.6596,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EDE_SWMP,EDE_SWMP_LA,27.9369,0.3500,17.4461,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EEI,EEI,18.5744,0.2444,8.1891,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,EES,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-7.1270,-0.5312,-16.7366,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,ERCOTE,ERCOTE,27.9354,0.5308,17.2638,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,ERCOTN,ERCOTN,-11.0000,-0.6427,-20.4981,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,-0.1981,-0.3745,-9.9644,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FMPP,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FPC,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FPL,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FREM_50T,OPPDFREM_GUN1_RA,1.1142,-0.2519,-8.7747,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FREM_6,OPPDFREM_AUN6_RA,1.1085,-0.2573,-8.7750,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FREM_7,OPPDFREM_AUN7_RA,1.1085,-0.2573,-8.7750,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FREM_8,OPPDFREM_AUN8_RA,1.0459,-0.3199,-8.7750,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FREM_LOAD,FREM_LOAD_LA,1.0986,-0.2672,-8.7750,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-12.7075,-0.4343,-22.4141,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,27.6649,0.6347,16.8894,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-19.8381,-1.2913,-28.6876,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-31.3747,-0.7849,-40.7306,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,32.7474,0.2442,22.3624,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,32.7474,0.2442,22.3624,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,32.7474,0.2442,22.3624,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,36.9901,0.1422,26.7070,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,36.9901,0.1422,26.7070,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,37.1294,0.1394,26.8492,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,37.1294,0.1394,26.8492,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-23.3595,-0.7103,-32.7900,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,45.4812,0.0942,35.2461,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,45.4812,0.0942,35.2461,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,45.4812,0.0942,35.2461,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.VOLT.0130,V130_DDR,38.1225,0.2453,27.7364,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA.VOLT.0237,V237_DDR,38.2575,0.1842,27.9325,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDAHUB2,GRDAHUB2_H,23.7829,-0.0900,13.7321,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDAHUB3,GRDAHUB3_H,17.4208,-0.1711,7.4512,10.1407\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA_GRDA,GRDA_LA,37.6597,0.1923,27.3266,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA_HUB,GRDA_H,31.0855,0.0147,20.9300,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRDA_HUBSA,GRDASA_H,30.9391,0.0022,20.7961,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GRE,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-14.2567,-0.0094,-24.3881,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GSEC_SPS,SPS_GSEC_LA,-17.8375,-0.4126,-27.5657,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GSPR2014HUB,GSPR2014HUB_H,-11.6493,-0.4386,-21.3515,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,GSPR2015HUB,GSPR2015HUB_H,-10.7953,-0.4460,-20.4902,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-19.2801,-0.9489,-28.4720,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,HARRISON,CSWSLEBROCKPLT1,27.6954,0.5717,16.9829,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,HAST_TNSK_HUB,HAST_TNSK_H,-0.6845,-0.5246,-10.3007,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,HQST,PJM,14.4435,0.1212,4.1815,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,HST,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,27.9992,0.1858,17.6726,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,27.9992,0.1858,17.6726,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,28.2419,0.1875,17.9136,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,28.2419,0.1875,17.9136,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,27.6929,0.1858,17.3663,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,27.6929,0.1858,17.3663,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,INDN_INDN,INDN_LA,28.0245,0.1954,17.6884,10.1407\n03/19/2025 16:00:00,03/19/2025 21:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-6.4325,-0.6584,-15.9150,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,ISNE,PJM,14.4435,0.1212,4.1815,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,JEA,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,1.2414,-0.1873,-8.7121,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,1.2414,-0.1873,-8.7121,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,1.9243,-0.0373,-8.1793,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KACYCT4,KACYNEARMANUNCT4_RA,25.0953,0.1348,14.8197,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,60.0000,-0.0053,49.8645,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,25.0953,0.1348,14.8197,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,25.4739,0.1464,15.1867,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,25.3703,0.1453,15.0842,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KACY_KACY,KACY_LA,25.5700,0.1434,15.2857,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,38.2807,0.0747,28.0652,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,18.3933,0.3756,7.8768,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-16.0585,-0.4787,-25.7206,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-43.0288,-0.6796,-52.4901,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.VOLT.0222,V222_DDR,-2.3197,-0.0128,-12.4477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.VOLT.0223,V223_DDR,12.7616,-0.0185,2.6393,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.VOLT.0241,V241_DDR,16.6706,0.3172,6.2126,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.VOLT.0243,V243_DDR,19.9885,0.1569,9.6908,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.VOLT.0247,V247_DDR,16.2232,0.0698,6.0126,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.VOLT.0253,V253_DDR,38.4678,0.0779,28.2491,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-2.7728,-0.7167,-12.1969,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,9.3376,-0.1327,-0.6706,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,9.3376,-0.1327,-0.6706,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,9.3376,-0.1327,-0.6706,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,9.3376,-0.1327,-0.6706,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,38.6737,0.0727,28.4602,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,38.6737,0.0727,28.4602,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHUB,KCPLHUB_H,4.9274,-0.3739,-4.8395,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHUB17,KCPLHUB17_H,3.8417,-0.4208,-5.8783,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHUB18,KCPLHUB18_H,2.8962,-0.4207,-6.8239,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHUB19,KCPLHUB19_H,2.8973,-0.3995,-6.8440,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHUB20,KCPLHUB20_H,2.0071,-0.4380,-7.6957,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHUB21,KCPLHUB21_H,1.3440,-0.4304,-8.3664,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHUB22,KCPLHUB22_H,2.3978,-0.4265,-7.3165,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHUB23,KCPLHUB23_H,2.2130,-0.4385,-7.4894,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLHUB24,KCPLHUB24_H,1.1552,-0.4541,-8.5316,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,-1.2887,-0.0370,-11.3926,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,-1.2887,-0.0370,-11.3926,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,7.0989,-0.2968,-2.7451,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,7.0989,-0.2968,-2.7451,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,38.2813,0.0753,28.0652,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,38.2807,0.0747,28.0652,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,32.6848,0.1060,22.4380,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,32.6848,0.1060,22.4380,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,32.6848,0.1060,22.4380,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,32.6848,0.1060,22.4380,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,32.6848,0.1060,22.4380,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,32.6848,0.1060,22.4380,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,32.6848,0.1060,22.4380,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,32.6848,0.1060,22.4380,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,3.1380,-0.1543,-6.8485,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,19.7495,0.0699,9.5389,10.1407\n03/19/2025 16:00:00,03/19/2025 21:00:00,KCPL_KCPL,KCPL_LA,22.8186,0.0598,12.6181,10.1407\n03/19/2025 16:00:00,03/19/2025 21:00:00,KENN,KENN_LA,7.4206,0.3316,-3.0518,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KEP2_SECI,KEP2_SECI_LA,-18.0281,-0.6687,-27.5003,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KERR_1,GRDAKERR_HYDUN1_RA,37.8305,0.1717,27.5180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KERR_2,GRDAKERR_HYDUN2_RA,37.6866,0.1769,27.3688,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KERR_3,GRDAKERR_HYDUN3_RA,37.6866,0.1769,27.3688,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KERR_4,GRDAKERR_HYDUN4_RA,37.8305,0.1717,27.5180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,9.3375,-0.1327,-0.6706,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,9.3375,-0.1327,-0.6706,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,10.5647,-0.0712,0.4950,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,10.5647,-0.0712,0.4950,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,7.2874,-0.1330,-2.7204,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,5.7912,-0.1157,-4.2340,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,5.7912,-0.1157,-4.2340,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-15.8190,-0.7685,-25.1913,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-15.8190,-0.7685,-25.1913,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-15.8190,-0.7685,-25.1913,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-9.2301,-0.4849,-18.8860,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-9.2301,-0.4849,-18.8860,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-16.2054,-0.7848,-25.5615,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-10.6012,-0.5168,-20.2252,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-4.8361,-0.3653,-14.6116,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,53.0078,-0.0232,42.8902,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,53.0078,-0.0232,42.8902,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-0.5026,-0.2664,-10.3770,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-0.5026,-0.2664,-10.3770,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-0.5026,-0.2664,-10.3770,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-11.7951,-0.6893,-21.2466,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-8.3610,-0.8275,-17.6743,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,2.6840,-0.3394,-7.1174,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,3.1336,0.0031,-7.0103,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LAFA,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LAM345,LAM345,-16.3961,-0.9000,-25.6369,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LEPA,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,1.0314,-0.2702,-8.8392,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_LES,LES_LA,1.0001,-0.2778,-8.8629,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,1.0630,-0.2901,-8.7877,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,0.9085,-0.3094,-8.9229,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,0.9085,-0.3094,-8.9229,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,0.9085,-0.3094,-8.9229,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,1.0634,-0.2897,-8.7877,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,1.0630,-0.2901,-8.7877,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_WAVERLY,LES_WAVERLY_H,0.9816,-0.3016,-8.8577,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,1.4295,-0.2655,-8.4458,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,1.4295,-0.2655,-8.4458,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,LGEE,LGEE,16.8553,0.1823,6.5322,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MALDEN,MALDEN_LA,8.4159,0.3190,-2.0439,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MCWEST,MCWEST,4.5282,0.0087,-5.6213,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MDU,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-2.0657,-0.4339,-11.7727,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,0.1564,-0.1012,-9.8832,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,1.4478,0.2427,-8.9357,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MEAN_NPPD,NPPD_MEAN_LA,-2.1302,-0.6429,-11.6282,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MEC,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MHEB,MHEB,5.6463,0.0497,-4.5443,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-6.8499,-0.6653,-16.3254,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-11.9475,-0.8518,-21.2365,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-6.8499,-0.6653,-16.3254,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-6.8499,-0.6653,-16.3254,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-11.9475,-0.8518,-21.2365,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-17.7672,-0.5567,-27.3513,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MISO,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-17.1614,-0.6243,-26.6780,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-17.1614,-0.6243,-26.6780,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-3.5375,-0.3945,-13.2838,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-17.8831,-0.8702,-27.1537,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-11.0397,-0.6775,-20.5030,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-18.6435,-0.7737,-28.0106,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-16.6675,-0.6430,-26.1653,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-18.8055,-0.7270,-28.2194,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-16.2501,-0.5972,-25.7937,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-16.2501,-0.5972,-25.7937,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-16.2501,-0.5972,-25.7937,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-16.2501,-0.5972,-25.7937,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-16.2501,-0.5972,-25.7937,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,9.2374,0.0077,-0.9111,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,15.1540,0.2157,4.7975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,15.1540,0.2157,4.7975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,13.2635,0.1318,2.9909,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,15.4132,0.3553,4.9171,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MOWR,AECI,22.1985,0.1700,11.8876,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,14.9100,0.1070,4.6622,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,15.5131,0.2215,5.1508,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-3.3737,-0.5253,-12.9892,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-6.0000,-0.2845,-15.8563,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-26.7482,-0.7435,-36.1455,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-3.3409,-0.4926,-12.9892,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,10.1724,-0.0073,0.0389,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,10.1724,-0.0073,0.0389,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,10.1728,-0.0069,0.0389,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,10.1728,-0.0069,0.0389,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,-2.3197,-0.0128,-12.4477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,-2.3197,-0.0128,-12.4477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,-2.3197,-0.0128,-12.4477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,-2.3536,-0.0467,-12.4477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,-2.3197,-0.0128,-12.4477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,-2.3197,-0.0128,-12.4477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,-2.3197,-0.0128,-12.4477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,19.3330,0.2730,8.9192,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,12.5810,-0.0088,2.4490,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,10.5486,-0.0441,0.4519,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,10.5486,-0.0441,0.4519,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,10.5486,-0.0441,0.4519,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,23.7770,0.0708,13.5653,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,23.7770,0.0708,13.5653,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MPS_MPS,MPS_LA,13.8514,0.0893,3.6213,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MSTNG,SPSMSTNGPLT1,-1.8761,0.2978,-12.3147,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MSTNG4,SPSMSTNGUN4_RA,-1.9062,0.2676,-12.3147,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,MSTNG5,SPSMSTNGUN5_RA,-1.8761,0.2978,-12.3147,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,-1.8761,0.2978,-12.3147,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NBSO,PJM,14.4435,0.1212,4.1815,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,-0.5524,-0.5319,-10.1614,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,-0.5540,-0.5334,-10.1614,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-19.8450,-1.1453,-28.8406,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NHC1,VACS,23.5201,0.3312,13.0481,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,1.2366,-0.2182,-8.6861,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,1.2366,-0.2182,-8.6861,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,1.2366,-0.2182,-8.6861,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-1.7443,-0.8260,-11.0591,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,-1.2238,-0.7866,-10.5780,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,-0.1059,-0.4969,-9.7498,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-1.1795,-0.3745,-10.9458,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,-1.2238,-0.7866,-10.5780,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.HUB.PY2018,NPPDPY18_H,-2.0932,-0.6488,-11.5853,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,-2.0042,-0.6417,-11.5034,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,-2.0340,-0.6394,-11.5354,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,-1.9520,-0.6282,-11.4647,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-1.8283,-0.4176,-11.5515,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-3.2305,-0.7484,-12.6229,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-3.2305,-0.7484,-12.6229,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-3.4313,-0.6294,-12.9427,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-1.8283,-0.4176,-11.5515,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,2.8353,-0.8533,-6.4522,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,-1.8667,-0.9317,-11.0758,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-5.8098,-0.6925,-15.2582,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,-1.8667,-0.9317,-11.0758,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,-0.8710,-0.8353,-10.1765,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-2.2616,-0.8638,-11.5386,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,0.5944,-0.2141,-9.3323,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,-1.2238,-0.7866,-10.5780,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-5.3971,-0.7200,-14.8179,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-3.2305,-0.7484,-12.6229,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-3.2305,-0.7484,-12.6229,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-2.6089,-0.5644,-12.1854,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-2.6625,-0.5748,-12.2286,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-2.6625,-0.5748,-12.2286,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,-1.8900,-0.3611,-11.6697,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-13.0000,-0.1816,-22.9592,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,-0.9602,-0.6313,-10.4697,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-1.5203,-0.6967,-10.9644,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-16.5829,-0.1331,-26.5906,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-19.3000,-0.1435,-29.2973,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.NELI.DDR,NELI_DDR,-1.5664,-0.5031,-11.2041,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.NPPM.1058,SH1058_DDR,6.2703,-0.2209,-3.6496,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,-1.8133,-0.4262,-11.5279,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,-1.2238,-0.7866,-10.5780,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,-0.1059,-0.4969,-9.7498,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-1.8283,-0.4176,-11.5515,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.TECH.1,KEARNE_DDR,-1.6436,-0.3353,-11.4491,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,-0.0253,-0.9745,-9.1916,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,-0.0253,-0.9745,-9.1916,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-1.9075,-0.4731,-11.5753,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD.VOLT.0236,V236_DDR,0.3614,-0.1933,-9.5861,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD2017HUB,NPPD2017HUB_H,-2.0841,-0.6463,-11.5786,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,5.2369,-0.4471,-4.4568,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-1.7443,-0.8260,-11.0591,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,-1.8619,-1.0828,-10.9200,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,-1.8619,-1.0828,-10.9200,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,0.4018,-0.2193,-9.5197,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,0.3687,-0.1860,-9.5861,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-4.4167,-0.3689,-14.1887,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-2.5279,-0.5783,-12.0904,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,6.0720,-0.4192,-3.6496,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,6.0720,-0.4192,-3.6496,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,6.0720,-0.4192,-3.6496,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,-0.6780,-0.5227,-10.2961,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,-0.4198,-0.4870,-10.0736,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,-0.5728,-0.4212,-10.2924,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-0.9681,-0.9805,-10.1284,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-0.9135,-0.9259,-10.1284,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-3.8501,-0.7875,-13.2034,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-4.0537,-0.7885,-13.4060,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,-0.0534,-0.4940,-9.7002,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,-0.0624,-0.5030,-9.7002,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,-0.0624,-0.5030,-9.7002,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,-0.0667,-0.4793,-9.7283,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,2.8353,-0.8533,-6.4522,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,-0.1118,-0.4819,-9.7707,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,0.5651,-0.3618,-9.2139,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,-0.6681,-0.5026,-10.3063,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,-0.6759,-0.5084,-10.3084,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,-0.6726,-0.5029,-10.3105,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,-0.6726,-0.5029,-10.3105,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,-0.6780,-0.5227,-10.2961,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,-0.6986,-0.5434,-10.2961,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,-0.6401,-0.5065,-10.2744,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,-0.1613,-0.3137,-9.9884,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-3.8480,-0.7606,-13.2282,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,-0.3316,-0.8976,-9.5748,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-6.1332,-0.7273,-15.5467,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,6.4158,-0.0754,-3.6496,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-1.5664,-0.5031,-11.2041,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-3.6505,-0.7702,-13.0211,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-3.6505,-0.7702,-13.0211,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_NPPD,NPPD_LA,0.7077,-0.4254,-9.0077,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,0.5651,-0.3618,-9.2139,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,0.5651,-0.3618,-9.2139,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,-0.4869,-0.2829,-10.3448,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-3.0814,-0.6714,-12.5508,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NSB,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NSP,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NSSO,PJM,14.4435,0.1212,4.1815,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,NYIS,PJM,14.4435,0.1212,4.1815,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-20.7992,-1.0508,-29.8892,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-23.0859,-0.7281,-32.4986,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-7.2659,-0.5709,-16.8358,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-7.2659,-0.5709,-16.8358,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-20.0332,-1.1888,-28.9852,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-31.3747,-0.7849,-40.7306,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-94.6640,-0.4780,-104.3268,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-45.8181,-0.7110,-55.2479,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-25.7915,-0.7152,-35.2171,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-22.4048,-0.7379,-31.8077,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-3.9891,-0.2710,-13.8589,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-25.7915,-0.7152,-35.2171,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-20.2659,-1.1626,-29.2441,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-17.7672,-0.5567,-27.3513,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-21.0804,-1.0252,-30.1960,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,9.1559,-0.0894,-0.8956,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-22.4048,-0.7379,-31.8077,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-22.2371,-0.6851,-31.6928,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-6.6174,-0.6798,-16.0784,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-18.5658,-0.5807,-28.1259,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-41.3728,-0.0957,-51.4180,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-17.7672,-0.5567,-27.3513,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-17.7672,-0.5567,-27.3513,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-22.4048,-0.7379,-31.8077,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-16.7221,-0.5704,-26.2926,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.NUEN.LAM1,LAM1_DDR,34.8600,0.7175,24.0016,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-3.9891,-0.2710,-13.8589,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-3.9891,-0.2710,-13.8589,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-16.9264,-0.5611,-26.5061,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-6.3822,-0.3037,-16.2193,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-6.3822,-0.3037,-16.2193,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-6.3822,-0.3037,-16.2193,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-0.3926,-0.2611,-10.2723,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-0.3926,-0.2611,-10.2723,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-6.3822,-0.3037,-16.2193,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-6.3822,-0.3037,-16.2193,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-22.4048,-0.7379,-31.8077,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,15.9229,0.4174,5.3647,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-20.2659,-1.1626,-29.2441,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-31.4923,-0.2593,-41.3738,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-22.2371,-0.6851,-31.6928,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,30.1131,0.4520,19.5203,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-23.5964,-0.5650,-33.1722,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-23.5964,-0.5650,-33.1722,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-23.5964,-0.5650,-33.1722,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-23.5964,-0.5650,-33.1722,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-23.8597,-1.0175,-32.9830,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-27.4204,-0.6931,-36.8681,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-23.0859,-0.7281,-32.4986,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-32.0000,-0.6763,-41.4645,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-32.0000,-0.6763,-41.4645,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-29.4135,-0.1113,-39.4430,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-20.4761,-0.6326,-29.9843,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-20.4761,-0.6326,-29.9843,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-20.4761,-0.6326,-29.9843,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0033,FOSTER_DDR,5.5381,-0.2335,-4.3692,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,30.9629,0.3632,20.4589,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0035,TARBY_DDR,34.8140,0.5771,24.0961,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,30.9629,0.3632,20.4589,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,30.6903,0.2633,20.2862,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,30.6903,0.2633,20.2862,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-36.4825,-0.1485,-46.4748,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0040,TROSPER_DDR,9.0966,-0.2181,-0.8261,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,9.1430,-0.2181,-0.7797,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,31.7040,0.5387,21.0245,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0115,V115_DDR,-2.9906,-0.2662,-12.8652,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0116,V116_DDR,29.1900,-0.0389,19.0881,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0118,V118_DDR,-1.2616,-0.0039,-11.3985,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0125,V125_DDR,32.3627,0.6154,21.6065,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0126,V126_DDR,34.1135,0.3164,23.6563,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0129,V129_DDR,-8.3216,-0.4517,-18.0107,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,35.0000,-0.2730,25.1322,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0134,V134_DDR,34.8672,0.3904,24.3360,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0138,V138_DDR,33.4342,0.2717,23.0217,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,28.3079,-0.2247,18.3917,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0143,V143_DDR,30.6556,0.2084,20.3064,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0149,V149_DDR,-15.9341,-0.5205,-25.5544,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0150,V150_DDR,-15.9763,-0.5585,-25.5586,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0155,V155_DDR,32.7890,0.2229,22.4253,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0156,V156_DDR,35.0000,-0.2730,25.1322,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0166,V166_DDR,34.2335,0.5841,23.5086,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,27.5139,-0.2286,17.6017,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-15.9763,-0.5585,-25.5586,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0170,V170_DDR,-17.0457,-0.5616,-26.6249,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-25.1297,-0.4942,-34.7763,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0176,V176_DDR,-15.9763,-0.5585,-25.5586,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0177,V177_DDR,-23.2224,-0.9546,-32.4086,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,20.3891,-0.2280,10.4763,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-12.2375,-0.5948,-21.7835,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0195,V195_DDR,143.1100,0.6676,132.3016,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0197,V197_DDR,34.4964,0.3838,23.9718,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0198,V198_DDR,34.2335,0.5841,23.5086,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0208,V208_DDR,143.2757,0.6833,132.4515,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0209,V209_DDR,143.2757,0.6833,132.4515,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,34.6574,0.2907,24.2259,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0216,V216_DDR,9.1540,-0.2188,-0.7680,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0219,V219_DDR,32.7890,0.2229,22.4253,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0220,V220_DDR,-15.9763,-0.5585,-25.5586,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0224,V224_DDR,-3.6613,-0.2784,-13.5238,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0225,V225_DDR,-3.6608,-0.2778,-13.5238,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0226,V226_DDR,-3.6613,-0.2784,-13.5238,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0227,V227_DDR,-3.6613,-0.2784,-13.5238,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0229,V229_DDR,-33.2986,-0.1116,-43.3278,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0231,V231_DDR,3.1192,0.0481,-7.0697,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0238,V238_DDR,-23.5572,-0.7692,-32.9289,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.VOLT.0242,V242_DDR,33.0669,0.2468,22.6793,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-20.8479,-1.2810,-29.7077,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-17.7672,-0.5567,-27.3513,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-23.7393,-0.7066,-33.1736,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-21.0715,-1.0163,-30.1960,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-20.8479,-1.2810,-29.7077,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-20.8392,-1.0701,-29.9100,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-51.0209,-0.6823,-60.4794,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEHL7,OKGEHL7_H,19.0608,-0.2114,9.1314,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEHL8,OKGEHSL1UN8_RA,19.0608,-0.2114,9.1314,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEHL910,OKGEHSL1PLT2,19.0608,-0.2114,9.1314,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-20.9029,-1.0505,-29.9932,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEMCC,OKGEMCCLAIPLT1,-6.2971,-0.3770,-16.0609,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,29.7472,0.1680,19.4384,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,29.7472,0.1680,19.4384,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,29.7472,0.1680,19.4384,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,13.4794,-0.3586,3.6971,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,13.4794,-0.3586,3.6971,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,13.4794,-0.3586,3.6971,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,13.4794,-0.3586,3.6971,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGESM1,OKGESEMINOLEUN1_RA,1.8902,-0.1598,-8.0908,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGESM2,OKGESEMINOLEUN2_RA,3.4427,-0.1822,-6.5159,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGESM3,OKGESEMINOLEUN3_RA,3.4427,-0.1822,-6.5159,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGESO1,OKGESONR1UN1_RA,-61.3342,-0.6425,-70.8325,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGESO2,OKGESONR1UN2_RA,-32.0000,-0.6763,-41.4645,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-20.9029,-1.0505,-29.9932,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-19.8128,-1.2649,-28.6887,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGETINK5A,OKGETINK5UN1_RA,6.9500,-0.2414,-2.9494,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGETINK5B,OKGETINK5UN2_RA,6.9500,-0.2414,-2.9494,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-20.8622,-0.9032,-30.0998,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-23.0859,-0.7281,-32.4986,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,30.9134,0.6770,20.0956,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-17.7672,-0.5567,-27.3513,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE_OKGE,OKGE_LA,12.0596,-0.0974,2.0162,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-31.4923,-0.2593,-41.3738,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-20.8906,-0.9316,-30.0998,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMLP,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,39.4566,0.1161,29.1997,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,31.2271,0.6387,20.4476,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-4.1701,-0.2723,-14.0386,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-94.5792,-0.3932,-104.3268,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-13.0609,-0.6677,-22.5341,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-25.7915,-0.7152,-35.2171,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-20.7628,-0.9726,-29.9310,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-12.1872,-1.0429,-21.2851,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,160.8301,0.0880,150.6013,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-94.6069,-0.4209,-104.3268,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-94.6069,-0.4209,-104.3268,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_SPP,OMPA_SPP_LA,-6.4765,-0.4085,-16.2089,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-20.8479,-1.2810,-29.7077,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,34.8615,0.1054,24.6153,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,34.8615,0.1054,24.6153,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,34.8615,0.1054,24.6153,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,34.8615,0.1054,24.6153,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,ONT,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,1.1708,-0.2240,-8.7460,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,1.1708,-0.2240,-8.7460,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,1.1708,-0.2240,-8.7460,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,1.1708,-0.2240,-8.7460,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,1.1708,-0.2240,-8.7460,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,1.1708,-0.2240,-8.7460,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,1.1708,-0.2240,-8.7460,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,1.1708,-0.2240,-8.7460,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,1.1708,-0.2240,-8.7460,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,1.2338,-0.2059,-8.7012,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,1.2366,-0.2182,-8.6861,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,1.1403,-0.2283,-8.7722,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,1.1652,-0.2005,-8.7752,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,1.1652,-0.2005,-8.7752,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD_GLDN,OPPD_GLDN_LA,1.1450,-0.2225,-8.7733,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,1.2065,-0.2143,-8.7200,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,2.8353,-0.8533,-6.4522,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,0.3691,-0.3476,-9.4241,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,1.2365,-0.2179,-8.6864,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD_OPPD,OPPD_LA,1.2155,-0.1963,-8.7290,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,1.1838,-0.1880,-8.7690,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,1.1782,-0.1917,-8.7709,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OTP,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,OVEC,OVEC,15.8877,0.1591,5.5878,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PARAGOULD,PARAGOULD_LA,5.8365,0.3516,-4.6559,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,37.5215,0.0983,27.2824,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,37.5215,0.0983,27.2824,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,37.5215,0.0983,27.2824,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,37.2183,0.1351,26.9424,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,37.2183,0.1351,26.9424,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,37.2183,0.1351,26.9424,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PIGGOTT,PIGGOTT_LA,7.7750,0.3270,-2.6928,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PJM,PJM,14.4435,0.1212,4.1815,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PLUM,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,POPLARBLUFF,POPLARBLUFF_LA,11.8118,0.2919,1.3791,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,4.3632,-0.1282,-5.6495,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,4.3632,-0.1282,-5.6495,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,4.4448,-0.1080,-5.5880,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,4.4448,-0.1080,-5.5880,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,5.1851,0.5825,-5.5382,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,5.1851,0.5825,-5.5382,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,4.5264,0.0002,-5.6146,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,3.7612,-0.4506,-5.9291,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-9.7328,-0.4481,-19.4255,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,81.9217,0.1100,71.6708,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,-0.6177,0.0362,-10.7948,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-4.6280,-0.0211,-14.7477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,51.8846,0.3264,41.4173,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,33.5424,0.3318,23.0698,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,4.4036,-0.1818,-5.5554,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,4.6371,0.0519,-5.5557,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,3.0919,-0.3666,-6.6824,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,12.0400,0.8221,1.0771,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,5.3371,0.1351,-4.9388,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,3.9887,-0.0727,-6.0795,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,PUPP,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,RCEAST,RCEAST,1.1055,-0.8418,-8.1935,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SALINA_1,GRDASALINA1UN1_RA,37.8315,0.1727,27.5180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SALINA_2,GRDASALINA1UN2_RA,37.8315,0.1727,27.5180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SALINA_3,GRDASALINA1UN3_RA,37.8315,0.1727,27.5180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SALINA_4,GRDASALINA1UN4_RA,37.8315,0.1727,27.5180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SALINA_5,GRDASALINA1UN5_RA,37.8315,0.1727,27.5180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SALINA_6,GRDASALINA1UN6_RA,37.8315,0.1727,27.5180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SARPY_1,OPPDSARPYUN1_RA,1.2012,-0.2097,-8.7299,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SARPY_2,OPPDSARPYUN2_RA,1.2173,-0.1899,-8.7336,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SARPY_3,OPPDSARPYUN3_RA,1.1999,-0.2320,-8.7089,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SARPY_4,OPPDSARPYUN4_RA,1.1999,-0.2320,-8.7089,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SARPY_5,OPPDSARPYUN5_RA,1.1999,-0.2320,-8.7089,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SC,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SCEG,VACS,23.5201,0.3312,13.0481,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SCSE,SCSE,-3.3662,-0.7080,-12.7990,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SEC,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-20.6780,-0.9619,-29.8569,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-20.6780,-0.9619,-29.8569,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-20.6780,-0.9619,-29.8569,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-15.7946,-0.5694,-25.3660,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-20.6780,-0.9619,-29.8569,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-17.4905,-0.9465,-26.6848,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-16.9483,-0.9612,-26.1279,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-16.9483,-0.9612,-26.1279,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-16.2513,-0.5984,-25.7937,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-23.2122,-0.8616,-32.4915,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-9.2719,-0.5267,-18.8860,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-16.4240,-0.6287,-25.9361,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-11.0926,-0.8310,-20.4024,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-19.8887,-0.9641,-29.0654,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-11.1692,-0.8201,-20.4899,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-25.0000,-0.9829,-34.1579,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-17.6092,-0.5964,-27.1536,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-15.9356,-0.8162,-25.2602,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-15.9356,-0.8162,-25.2602,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-15.9356,-0.8162,-25.2602,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-15.9356,-0.8162,-25.2602,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-16.1779,-0.8668,-25.4519,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-17.4905,-0.9465,-26.6848,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI_SECI,SECI_LA,-15.2482,-0.6601,-24.7289,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-6.4325,-0.6584,-15.9150,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-6.4325,-0.6584,-15.9150,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-16.2513,-0.5984,-25.7937,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SEHA,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-20.8906,-0.9316,-30.0998,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SERU,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SETH,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SGE,SGE,-2.5015,-0.6825,-11.9598,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SMEP,MISO,14.0772,0.1547,3.7817,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SOCO,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPA,SPA,27.2489,0.3895,16.7186,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPC,SPC,4.9898,0.2880,-5.4390,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPPNORTH_HUB,SPPNORTH_H,1.0000,-0.2927,-8.8481,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-1.9099,-0.4832,-11.5675,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,26.0228,0.3435,15.5385,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,26.0228,0.3435,15.5385,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,25.3371,0.3223,14.8739,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,25.3371,0.3223,14.8739,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_NIXA,SPRM_NIXA_LA,26.4535,0.3512,15.9615,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_SPRM,SPRM_LA,26.1010,0.3771,15.5831,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,26.2876,0.2908,15.8560,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,26.2876,0.2908,15.8560,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,26.2617,0.2649,15.8560,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,26.2876,0.2908,15.8560,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-13.9205,-0.2759,-23.7854,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-18.3302,-0.4666,-28.0044,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-19.5953,-0.9034,-28.8327,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-19.5953,-0.9034,-28.8327,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-23.2984,-0.9033,-32.5359,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,-8.8553,-0.5626,-18.4335,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-16.0222,-0.9287,-25.2343,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,-4.0629,-0.4235,-13.7802,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-24.2050,-0.4424,-33.9034,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,0.0517,0.2502,-10.3393,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,0.1374,0.2494,-10.2528,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,0.1374,0.2494,-10.2528,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,0.0517,0.2502,-10.3393,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-19.5678,-0.8768,-28.8318,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-18.3302,-0.4666,-28.0044,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-19.4473,-0.8178,-28.7703,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-19.7653,-1.1905,-28.7157,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-19.3423,-0.7467,-28.7364,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-19.2109,-0.5939,-28.7578,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-19.4261,-0.8083,-28.7586,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-19.7007,-1.2004,-28.6411,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-19.7007,-1.2004,-28.6411,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-19.7007,-1.2004,-28.6411,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-19.7007,-1.2004,-28.6411,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GRID.WRAB,WRAB_DDR,-19.3604,-0.6358,-28.8654,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-19.7007,-1.2004,-28.6411,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-22.1654,-0.4812,-31.8250,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-22.1654,-0.4812,-31.8250,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-22.0357,-0.4498,-31.7267,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-22.0357,-0.4498,-31.7267,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-22.0357,-0.4498,-31.7267,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-22.1654,-0.4812,-31.8250,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-19.6235,-0.8807,-28.8836,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-19.6243,-0.8807,-28.8844,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-19.6235,-0.8807,-28.8836,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-19.8450,-1.1453,-28.8406,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,0.1540,0.2278,-10.2146,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-24.1167,-0.4477,-33.8098,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-24.1167,-0.4477,-33.8098,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-24.1167,-0.4477,-33.8098,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-24.1167,-0.4477,-33.8098,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,-0.5834,0.3107,-11.0349,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,0.0471,0.2342,-10.3279,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,0.0471,0.2342,-10.3279,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-20.8453,-0.8863,-30.0998,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-19.6061,-0.8717,-28.8752,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-19.6061,-0.8717,-28.8752,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-19.6311,-0.8770,-28.8950,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-19.3604,-0.6358,-28.8654,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-19.6067,-1.0401,-28.7074,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-19.5701,-0.8972,-28.8137,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-20.0332,-1.1888,-28.9852,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-19.4639,-0.7295,-28.8752,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-17.5544,-0.3800,-27.3152,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-17.5544,-0.3800,-27.3152,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-16.8009,-0.3934,-26.5483,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-23.5361,-0.7497,-32.9272,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-19.6359,-1.1002,-28.6765,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-15.8431,-0.7496,-25.2343,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-15.2900,-0.7485,-24.6823,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-19.5499,-0.8590,-28.8318,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-13.0548,-0.3753,-22.8203,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,-3.7572,-0.1178,-13.7802,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-13.0548,-0.3753,-22.8203,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,-12.5295,-0.2092,-22.4611,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-19.5239,-0.9370,-28.7277,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,0.0527,0.6847,-10.7728,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,0.0554,0.6874,-10.7728,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,0.0000,0.4877,-10.6285,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,0.0603,0.2440,-10.3245,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,-0.9287,0.4999,-11.5694,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-16.3961,-0.9000,-25.6369,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-19.4065,-0.6809,-28.8665,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-15.9464,-0.3647,-25.7225,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-15.9464,-0.3647,-25.7225,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-13.0548,-0.3753,-22.8203,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-24.4402,-0.3910,-34.1900,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,4.3272,0.5403,-6.3539,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-15.0669,0.0943,-25.3020,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-16.4245,-0.1621,-26.4032,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-20.0715,-0.4882,-29.7241,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,0.0527,0.6847,-10.7728,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,-0.2647,0.8646,-11.2702,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,-0.4047,0.7247,-11.2702,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-23.4264,-0.6400,-32.9272,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-15.2113,-0.1119,-25.2402,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-19.5966,-1.0517,-28.6857,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-19.6134,-1.0680,-28.6862,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0163,V163_DDR,-19.3484,-0.7284,-28.7608,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0168,V168_DDR,-20.9877,-0.5799,-30.5486,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0180,V180_DDR,-0.2647,0.8646,-11.2702,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0181,V181_DDR,-19.4833,-0.9438,-28.6803,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0182,V182_DDR,-0.7617,0.5898,-11.4923,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0199,V199_DDR,0.8818,0.4725,-9.7315,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0200,V200_DDR,0.0787,0.4752,-10.5373,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.VOLT.0235,V235_DDR,-19.6067,-1.0401,-28.7074,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-16.0222,-0.9287,-25.2343,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,-4.0629,-0.4235,-13.7802,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-19.3387,-1.0075,-28.4720,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-19.5097,-0.8168,-28.8337,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS_SPS,SPS_LA,-7.1952,0.1116,-17.4477,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,-2.4522,-0.0230,-12.5701,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,SSCN_NPPD,SSCN_NPPD_LA,-1.8333,-0.3150,-11.6591,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,11.6899,0.2804,1.2687,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,11.6899,0.2804,1.2687,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,TAL,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,TEC,SOUC,23.5075,0.3518,13.0149,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,-0.3316,-0.8976,-9.5748,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,TVA,TVA,23.5200,0.3096,13.0696,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,UCUHUB,UCUHUB_H,-3.2141,-0.2339,-13.1210,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,UCUHUB17,UCUHUB17_H,-9.7662,-0.4733,-19.4337,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,UCUHUB18,UCUHUB18_H,-6.6598,-0.3962,-16.4044,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,UCUHUB19,UCUHUB19_H,-10.6134,-0.4388,-20.3154,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,UCUHUB20,UCUHUB20_H,-10.1722,-0.4243,-19.8887,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,UCUHUB21,UCUHUB21_H,-11.6172,-0.4889,-21.2691,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,UCUHUB22,UCUHUB22_H,-11.7542,-0.5141,-21.3809,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,UCUHUB23,UCUHUB23_H,-12.1547,-0.5192,-21.7763,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,UCUHUB24,UCUHUB24_H,-9.2118,-0.4486,-18.9040,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,5.0481,0.3660,-5.4588,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,5.0481,0.3660,-5.4588,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,4.2089,-0.2537,-5.6782,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,4.2089,-0.2537,-5.6782,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,4.8148,-0.2818,-5.0442,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,4.3875,-0.1987,-5.5546,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,4.3875,-0.1987,-5.5546,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,5.0481,0.3660,-5.4588,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,4.8728,-0.2783,-4.9897,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,5.0588,0.0956,-5.1776,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,3.6820,-0.1249,-6.3339,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,1.5668,-1.0398,-7.5342,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,4.9809,0.3621,-5.5220,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,4.9809,0.3621,-5.5220,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,3.2149,-1.0067,-5.9192,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,3.9143,-0.3347,-5.8919,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,4.4267,-0.3738,-5.3403,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,3.1008,-0.3254,-6.7146,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,3.6998,-0.0934,-6.3476,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,3.7371,-0.3714,-6.0324,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,3.7394,-0.4822,-5.9192,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,3.7394,-0.4822,-5.9192,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,4.0261,-0.3012,-5.8136,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,1.3948,-1.1242,-7.6219,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,4.1891,0.3650,-6.3167,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,4.6085,0.0060,-5.5383,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,4.6085,0.0060,-5.5383,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,4.6085,0.0060,-5.5383,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,4.7090,0.1108,-5.5426,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,4.7090,0.1108,-5.5426,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,4.7090,0.1108,-5.5426,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,5.1922,0.4805,-5.4292,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,4.5730,-0.2498,-5.3180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,4.5730,-0.2498,-5.3180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-2.9306,-0.6954,-12.3760,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,2.9504,-0.2538,-6.9366,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,4.8743,0.0876,-5.3541,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,1.3451,-0.3852,-8.4105,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,0.9384,-1.3649,-7.8375,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,3.8973,-0.3898,-5.8538,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,5.0003,0.3634,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,5.0003,0.3634,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,4.9998,0.3629,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,5.0003,0.3634,-5.5039,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,4.9089,0.2843,-5.5162,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,4.9089,0.2843,-5.5162,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,4.9089,0.2843,-5.5162,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,4.9089,0.2843,-5.5162,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,4.9089,0.2843,-5.5162,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,4.9089,0.2843,-5.5162,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,4.9089,0.2843,-5.5162,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,1.2154,-0.8200,-8.1054,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,4.9803,-0.0958,-5.0647,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,2.0657,-0.1902,-7.8849,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,2.0657,-0.1902,-7.8849,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,0.7433,-0.4524,-8.9451,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,0.7433,-0.4524,-8.9451,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,4.6857,-0.1371,-5.3180,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,4.7863,-0.1240,-5.2305,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,3.3514,-0.3885,-6.4009,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,1.6819,-0.9552,-7.5037,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,4.7285,-0.1024,-5.3099,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,4.8148,-0.2818,-5.0442,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,4.8148,-0.2818,-5.0442,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,3.1008,-0.3254,-6.7146,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,1.0476,-0.8858,-8.2074,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,3.2286,-0.4956,-6.4166,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,1.5021,-1.0168,-7.6219,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,3.7864,-0.4296,-5.9248,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.FSE,WAUE.FSE_H,0.2522,-0.5702,-9.3184,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,4.6184,0.0390,-5.5614,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,4.6101,0.0377,-5.5684,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,1.0744,-1.0342,-8.0322,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,1.4011,-0.9784,-7.7613,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,4.7459,-0.2585,-5.1364,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,4.7400,-0.3130,-5.0878,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-16.4400,-0.8642,-25.7166,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,1.5668,-1.0398,-7.5342,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-11.2700,-0.6982,-20.7126,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,2.9060,-0.2740,-6.9608,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,2.9060,-0.2740,-6.9608,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,2.9066,-0.2734,-6.9608,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,3.7805,-0.3299,-6.0304,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,1.0476,-0.8858,-8.2074,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,4.4088,-0.0236,-5.7084,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,2.9302,-0.3775,-6.8331,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,4.1464,0.3223,-6.3167,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,3.5675,0.1150,-6.6883,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,3.7965,-0.0752,-6.2691,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,5.9335,-0.0871,-4.1202,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,3.3578,-0.1983,-6.5847,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,3.2989,-0.3825,-6.4594,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,1.3451,-0.3852,-8.4105,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,6.8892,0.3145,-3.5662,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,3.0911,-0.3333,-6.7164,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,6.7289,0.2158,-3.6277,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,4.1769,-0.0121,-5.9518,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,1.4295,-0.2655,-8.4458,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NTWK,WAUE.NTWK_H,3.3305,-0.2426,-6.5677,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,4.4135,0.2445,-5.9718,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,4.4135,0.2445,-5.9718,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,1.4826,-1.1112,-7.5470,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,0.9750,-1.0382,-8.1276,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,4.2785,-0.2757,-5.5867,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,1.4826,-1.1112,-7.5470,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,5.4888,-0.0585,-4.5935,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,2.7304,-0.5769,-6.8335,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,1.3451,-0.3852,-8.4105,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,3.3383,-0.3569,-6.4456,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,2.0905,-1.2168,-6.8335,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,0.1594,-1.2428,-8.7386,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,0.6574,-1.2359,-8.2475,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,4.1958,-0.2757,-5.6693,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,0.2442,-1.0503,-8.8463,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,4.5267,-0.1316,-5.4826,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,2.1318,-0.8187,-7.1903,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,1.6819,-0.9552,-7.5037,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.VOLT.0152,V152_DDR,5.3746,0.6167,-5.3829,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE.VOLT.0172,V172_DDR,4.9568,0.3273,-5.5113,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_BEPM,WAUE_BEPM_LA,4.3496,0.0824,-5.8736,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,4.4705,-0.0296,-5.6408,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,3.5689,0.1207,-6.6927,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_EWA,WAUE_EWA_LA,1.1467,-0.8185,-8.1756,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,2.5855,-0.5228,-7.0325,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_HMMU,WAUE_HMMU_LA,2.4112,-0.0439,-7.6857,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,6.0836,-0.1216,-3.9356,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_MECB,WAUE_MECB_LA,2.9611,0.0106,-7.1903,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_MMPA,WAUE_MMPA_LA,5.5806,0.1872,-4.7475,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_MRES,WAUE_MRES_LA,3.2972,-0.2220,-6.6216,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,5.2739,0.4188,-5.2857,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,4.6184,0.0390,-5.5614,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,2.3765,-0.4817,-7.2826,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_OTP,WAUE_OTP_LA,6.0749,0.3887,-4.4547,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_OTPW,WAUE_OTPW_LA,9.3360,0.5506,-1.3554,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM,WAUE_UGPM_LA,4.0734,-0.1663,-5.9012,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,4.1795,-0.0037,-5.9576,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,3.4207,-0.1704,-6.5497,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,0.9877,-0.3978,-8.7553,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,1.1467,-0.8185,-8.1756,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,2.4112,-0.0439,-7.6857,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,2.5376,-0.4937,-7.1095,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,4.6184,0.0390,-5.5614,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,5.5806,0.1872,-4.7475,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,3.4630,-0.1744,-6.5034,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,2.2953,-0.5933,-7.2522,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,5.5781,0.4043,-4.9670,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-20.7086,-1.1441,-29.7053,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-15.6135,-0.8932,-24.8612,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,-4.2273,-0.8338,-13.5343,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,97.8176,0.3034,87.3734,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,97.8176,0.3034,87.3734,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-14.5201,-1.4067,-23.2542,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,89.5739,0.3590,79.0741,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,79.9558,0.3416,69.4734,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,11.7903,-0.5964,2.2458,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,11.7903,-0.5964,2.2458,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,11.7903,-0.5964,2.2458,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,11.7903,-0.5964,2.2458,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,11.7680,-0.6186,2.2458,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,11.7903,-0.5964,2.2458,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,11.7903,-0.5964,2.2458,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,11.7903,-0.5964,2.2458,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,3.9812,-0.5677,-5.5919,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-20.0332,-1.1888,-28.9852,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-30.0000,-0.9693,-39.1715,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-21.3327,-1.0566,-30.4169,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-15.9076,-0.8141,-25.2343,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_ENMC,WFEC_ENMC_LA,-4.3440,0.2248,-14.7096,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-22.4048,-0.7379,-31.8077,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,37.8050,0.2576,27.4065,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,-0.4082,0.2701,-10.8191,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-20.7086,-1.1441,-29.7053,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-20.7086,-1.1441,-29.7053,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-20.7086,-1.1441,-29.7053,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_OKGE,WFEC_OKGE_LA,4.5026,0.0660,-5.7041,10.1407\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,48.7879,0.3676,38.2794,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-18.1203,-1.4072,-26.8539,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-13.9761,-1.5227,-22.5942,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_WFEC,WFEC_LA,16.7151,-0.2099,6.7842,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,-0.4082,0.2701,-10.8191,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-7.6989,-0.6719,-17.1678,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-14.4948,-0.9225,-23.7131,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-2.3428,-0.3861,-12.0975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-2.3428,-0.3861,-12.0975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-2.3428,-0.3861,-12.0975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-2.3428,-0.3861,-12.0975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-2.3428,-0.3861,-12.0975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-2.3428,-0.3861,-12.0975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-2.3428,-0.3861,-12.0975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,2.6992,0.3511,-7.7927,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-4.5332,-0.5352,-14.1388,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-17.5492,-0.7079,-26.9821,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-17.5492,-0.7079,-26.9821,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-17.5492,-0.7079,-26.9821,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-21.8966,-0.8599,-31.1775,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-21.8966,-0.8599,-31.1775,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-9.9570,-0.6483,-19.4495,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-9.9570,-0.6483,-19.4495,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-9.9570,-0.6483,-19.4495,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-4.5332,-0.5352,-14.1388,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,0.3724,-0.0471,-9.7213,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-8.8419,-0.5275,-18.4552,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-8.8419,-0.5275,-18.4552,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-8.8419,-0.5275,-18.4552,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-8.8419,-0.5275,-18.4552,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,0.3724,-0.0471,-9.7213,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-18.6636,-0.9674,-27.8370,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-28.7057,-0.3098,-38.5367,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.JEC.1,WRJEFFUN10_RA,-2.0059,-0.3852,-11.7616,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.JEC.2,WRJEFFUN11_RA,-2.0915,-0.3876,-11.8447,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.JEC.3,WRJEFFUN12_RA,-2.1409,-0.4370,-11.8447,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-23.3595,-0.7103,-32.7900,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-26.7412,-0.7365,-36.1455,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-26.7412,-0.7365,-36.1455,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.LEC.4,WRLECUN26_RA,1.7741,-0.0872,-8.2795,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.LEC.5,WRLECUN27_RA,1.5427,-0.0618,-8.5363,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-7.6627,-0.4698,-17.3337,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-7.6627,-0.4698,-17.3337,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-7.6627,-0.4698,-17.3337,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-7.6293,-0.4499,-17.3202,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-6.4325,-0.6584,-15.9150,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-6.4325,-0.6584,-15.9150,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-10.7602,-0.7535,-20.1475,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-7.3577,-0.6318,-16.8668,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-7.3577,-0.6318,-16.8668,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-8.3660,-0.8325,-17.6743,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-6.4325,-0.6584,-15.9150,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-1.2924,-0.5236,-10.9096,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-5.3462,-0.5977,-14.8893,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-26.7442,-0.7395,-36.1455,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,82.1559,0.3511,71.6640,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-8.9602,-1.2115,-17.8896,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-2.3428,-0.3861,-12.0975,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-3.7356,-0.7354,-13.1410,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,0.3724,-0.0471,-9.7213,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-4.5332,-0.5352,-14.1388,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-12.8853,-0.5424,-22.4837,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.THAYERLD,WR.THAYERLD_LA,11.7288,0.3131,1.2749,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-13.7177,-0.5414,-23.3171,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0106,V106_DDR,-13.0011,-0.5161,-22.6258,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0139,WR.VOLT.0139_H,5.2868,0.0302,-4.8843,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-5.8926,-0.4494,-15.5840,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0146,WR.VOLT.0146_H,2.1749,0.0011,-7.9670,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0147,WR.VOLT.0147_H,2.1749,0.0011,-7.9670,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0148,WR.VOLT.0148_H,1.1169,-0.0148,-9.0092,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-12.7204,-0.4455,-22.4157,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0157,V157_DDR,2.0632,-0.0106,-8.0670,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0158,V158_DDR,2.1749,0.0011,-7.9670,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0159,WR.VOLT.0159_H,2.1749,0.0011,-7.9670,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-13.4565,-0.5767,-23.0206,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0173,V173_DDR,-7.9007,-0.5410,-17.5005,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0174,V174_DDR,-13.2040,-0.5287,-22.8161,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0184,V184_DDR,-12.7728,-0.5875,-22.3261,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-13.0287,-0.5362,-22.6333,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0186,V186_DDR,-12.7914,-0.5689,-22.3633,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-12.8918,-0.5672,-22.4654,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-13.6465,-0.5206,-23.2667,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-7.1274,-0.3863,-16.8819,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-3.3685,-0.3351,-13.1742,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-2.6751,-0.3556,-12.4603,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-2.6751,-0.3556,-12.4603,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-3.3685,-0.3351,-13.1742,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0245,V245_DDR,-13.0269,-0.5368,-22.6309,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.VOLT.0248,V248_DDR,-13.0011,-0.5161,-22.6258,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-18.5002,-0.6610,-27.9800,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-0.1440,-0.1670,-10.1178,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.WOLF,WRWOLFUN15_RA,-3.8348,-0.7886,-13.1870,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-18.6636,-0.9674,-27.8370,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,2.6508,0.3027,-7.7927,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-17.5492,-0.7079,-26.9821,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-17.5492,-0.7079,-26.9821,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-17.5492,-0.7079,-26.9821,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-17.5492,-0.7079,-26.9821,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-16.1607,-0.4455,-25.8560,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-5.8159,-0.4510,-15.5057,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-14.5602,-0.5404,-24.1606,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-14.5602,-0.5404,-24.1606,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-14.5602,-0.5404,-24.1606,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-14.5602,-0.5404,-24.1606,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-4.0641,-0.3186,-13.8864,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-4.0641,-0.3186,-13.8864,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-4.0641,-0.3186,-13.8864,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-4.0641,-0.3186,-13.8864,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-4.0641,-0.3186,-13.8864,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-4.0641,-0.3186,-13.8864,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-29.7344,-0.5054,-39.3698,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-29.7344,-0.5054,-39.3698,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-32.8520,-0.5022,-42.4906,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-32.8520,-0.5022,-42.4906,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_MIDW,WR_MIDW_LA,-9.6008,-0.6714,-19.0703,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,16.7559,0.2318,6.3832,10.1409\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,13.4033,0.1014,3.1611,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-11.3729,-0.5891,-20.9246,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_SEG,WR_SEG_LA,1.4721,0.2244,-8.8931,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,WR_WR,WR_LA,-4.9538,-0.3469,-14.7477,10.1408\n03/19/2025 16:00:00,03/19/2025 21:00:00,YAD,VACS,23.5201,0.3312,13.0481,10.1408\n03/19/2025 17:00:00,03/19/2025 22:00:00,AEC,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AECC_CSWS,CSWS_AECC_LA,33.2231,0.5673,21.1670,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,35.0825,0.4474,23.1463,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,31.9889,0.7609,19.7392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,35.2734,0.3416,23.4430,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,29.7080,0.4257,17.7935,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,32.5727,0.3576,20.7263,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,30.5872,0.2795,18.8189,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AECI,AECI,26.2687,0.2080,14.5719,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AEPM_CSWS,CSWS_LA,31.8176,0.5368,19.7920,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,ALTW,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,AMRN,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-21.8620,-0.4128,-32.9380,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BBA,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BCA,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BEPM.ER01.DDR,ER01_DDR,0.9812,-1.6501,-8.8575,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BEPM_ER01,BEPM_ER01_LA,0.9812,-1.6501,-8.8575,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,-0.5289,-0.7777,-11.2399,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-1.2786,-0.5001,-12.2673,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BEPM_UM01,BEPM_UM01_LA,5.3759,0.1914,-6.3043,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BLKW,BLKW,-12.5421,-0.1204,-23.9105,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-30.0000,-1.0113,-40.4775,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-30.0000,-1.0113,-40.4775,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,6.6803,-0.9238,-3.8847,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.9798,-0.9911,-40.4775,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BRAZ,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BUBA,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-15.4768,-1.0467,-25.9189,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-17.3536,-0.6167,-28.2257,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-17.3536,-0.6167,-28.2257,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-17.3536,-0.6167,-28.2257,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-17.3536,-0.6167,-28.2257,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-17.3536,-0.6167,-28.2257,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-7.4334,-0.4850,-18.4372,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,1.8739,-0.3632,-9.2517,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,1.8739,-0.3632,-9.2517,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CLEC,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,34.3051,0.3267,22.4896,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,COWP,COWP_LA,23.2818,0.3605,11.4325,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,23.2818,0.3605,11.4325,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,23.2818,0.3605,11.4325,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CPLE,VACS,22.1467,0.3696,10.2884,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CPLW,VACS,22.1467,0.3696,10.2884,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,23.7871,0.4560,11.8423,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,23.7871,0.4560,11.8423,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,23.7871,0.4560,11.8423,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,23.7871,0.4560,11.8423,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CRTH_SPA,WRCRTH_SPA_LA,34.8272,0.2027,23.1357,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,29.8888,1.2285,17.1716,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-5.9602,-0.5145,-16.9345,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,30.5872,0.2795,18.8189,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,35.2734,0.3416,23.4430,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,29.8871,1.2202,17.1781,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,29.9510,0.8472,17.6150,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,29.8924,1.1026,17.3010,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,29.8924,1.1026,17.3010,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,34.7655,0.3734,22.9033,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,34.7655,0.3734,22.9033,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,34.6927,0.3006,22.9033,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,34.6927,0.3006,22.9033,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,30.5872,0.2795,18.8189,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,33.8273,0.8122,21.5263,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,53.2037,0.0626,41.6523,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,53.1090,-0.0321,41.6523,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,38.2909,0.1870,26.6152,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,36.5510,0.2551,24.8071,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,36.5510,0.2551,24.8071,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,36.5497,0.2551,24.8058,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,36.5497,0.2551,24.8058,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-21.9324,-0.6250,-32.7962,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,-0.8480,-0.3456,-11.9912,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,43.9839,0.2735,32.2216,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-20.9801,-0.7442,-31.7247,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-20.9432,-0.7073,-31.7247,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-15.7032,-0.3824,-26.8096,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.GRID.CDL1,CDL1_DDR,41.1850,0.3328,29.3634,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-7.7143,-0.4622,-18.7409,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-5.5317,-0.7740,-16.2465,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,41.1850,0.3328,29.3634,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.NUEN.CSI1,CSI1_DDR,38.3110,0.3824,26.4398,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.NUEN.CSI2,CSI2_DDR,38.3164,0.3878,26.4398,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,34.3069,0.3285,22.4896,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.NUEN.GAZA,GAZA_DDR,41.1850,0.3328,29.3634,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,85.4000,0.6113,73.2999,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.NUEN.T201,NT201_DDR,36.4094,0.2835,24.6371,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-10.0150,-0.7168,-20.7870,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-10.0150,-0.7168,-20.7870,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,30.5872,0.2795,18.8189,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,30.6256,1.2695,17.8673,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-15.7032,-0.3824,-26.8096,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-15.7032,-0.3824,-26.8096,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-17.0300,-0.5974,-27.9214,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-20.9432,-0.7073,-31.7247,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,29.5403,0.7066,17.3450,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,33.5579,0.1720,21.8971,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,33.4181,0.0322,21.8971,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,33.4154,0.0295,21.8971,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,12.4596,0.1111,0.8597,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,12.4596,0.1111,0.8597,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,30.0360,0.8142,17.7330,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,36.7850,0.2962,25.0000,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,30.0334,0.8471,17.6975,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,30.9996,1.5221,17.9887,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,35.5778,0.4233,23.6658,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,38.3164,0.3878,26.4398,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0057,OKMU_DDR,46.0119,0.3784,34.1447,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0060,LEHIGH_DDR,85.4000,0.6113,73.2999,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0086,WARRENM_DDR,36.8618,0.3031,25.0699,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,30.8232,1.1419,18.1926,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,46.0623,0.2822,34.2913,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0121,V121_DDR,30.0360,0.8142,17.7330,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0122,V122_DDR,44.6830,0.2753,32.9189,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0124,V124_DDR,61.8206,0.2046,50.1272,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0135,V135_DDR,37.4686,0.3192,25.6606,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0144,V144_DDR,-0.3449,-0.2958,-11.5379,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0145,V145_DDR,-0.1260,-0.3496,-11.2652,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,30.0683,0.8256,17.7540,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,30.9231,0.4586,18.9757,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0175,V175_DDR,34.3069,0.3285,22.4896,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,30.9231,0.4586,18.9757,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,31.0059,0.5470,18.9701,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,37.4686,0.3192,25.6606,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,37.6231,0.3021,25.8322,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,37.0266,0.2755,25.2623,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,49.8639,0.1578,38.2173,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,36.4740,0.2484,24.7368,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,37.6231,0.3021,25.8322,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0211,V211_DDR,30.1095,1.0009,17.6198,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,46.7029,0.2877,34.9264,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0213,V213_DDR,37.3742,0.3031,25.5823,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0215,V215_DDR,45.6019,0.2805,33.8326,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0217,V217_DDR,46.7507,0.2756,34.9863,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0218,V218_DDR,49.4896,0.1654,37.8354,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0228,V228_DDR,37.9140,0.2630,26.1622,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0232,V232_DDR,36.9921,0.3212,25.1821,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0233,V233_DDR,37.8176,0.3146,26.0142,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0240,V240_DDR,43.7098,0.2291,31.9919,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0244,V244_DDR,37.6231,0.3021,25.8322,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0246,MDT1_DDR,85.4000,0.6113,73.2999,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0249,V249_DDR,37.3466,0.3166,25.5412,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0250,V250_DDR,-6.6262,-0.4959,-17.6191,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0251,V251_DDR,36.8975,0.2784,25.1303,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.VOLT.0252,V252_DDR,49.8639,0.1578,38.2173,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-24.0063,-0.6128,-34.8823,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,4.3261,-0.7047,-6.4580,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-18.8798,-1.3119,-29.0567,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,29.9358,0.7754,17.6716,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-20.5516,-1.2402,-30.8002,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,-3.2000,-0.3866,-14.3022,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,-3.2000,-0.3866,-14.3022,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,-3.2000,-0.3866,-14.3022,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,-3.2000,-0.3866,-14.3022,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,-3.2000,-0.3866,-14.3022,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,30.5872,0.2795,18.8189,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,29.1356,1.0757,16.5710,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,36.9739,0.3030,25.1821,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,36.9565,0.2856,25.1821,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,53.9500,0.4084,42.0528,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,53.9500,0.4084,42.0528,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWWELSH1,CSWSWELSHUN1_RA,30.3731,0.5841,18.3003,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWWELSH3,CSWSWELSHUN3_RA,30.3731,0.5841,18.3003,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWWILKES1,CSWSWILKESUN1_RA,30.4381,0.8169,18.1324,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWWILKES2,CSWSWILKESUN2_RA,30.4381,0.8169,18.1324,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,CSWWILKES3,CSWSWILKESUN3_RA,30.1883,0.7760,17.9235,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-20.9303,-0.6944,-31.7247,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,DENL,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,DERS,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,DOE,DOE,19.5584,0.2669,7.8027,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,12.2478,-0.0233,0.7823,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,DPC,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,DUK,VACS,22.1467,0.3696,10.2884,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDDY,EDDY,3.4300,0.4583,-8.5171,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,33.0803,0.1710,21.4205,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-4.0484,-0.1144,-15.4228,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,38.1876,0.0124,26.6864,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE.SLCC,EDESTL4391_PLT,34.4620,0.0871,22.8861,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,34.3741,0.1239,22.7614,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,21.7733,-0.1154,10.3999,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_EC_01,EDELAR3821UN1_RA,33.0803,0.1710,21.4205,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_EC_02,EDELAR3821UN2_RA,33.0803,0.1710,21.4205,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_EC_03,EDELAR3821UN3_RA,33.0803,0.1710,21.4205,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_EC_04,EDELAR3821UN4_RA,33.0803,0.1710,21.4205,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_EDE,EDE_LA,32.6135,0.3435,20.7812,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_ERW,EDEERWFUNG1_RA,-7.8969,-0.5333,-18.8523,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-2.4778,-0.7143,-13.2523,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,29.5957,0.5857,17.5212,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,29.5957,0.5857,17.5212,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,29.5957,0.5857,17.5212,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,29.5957,0.5857,17.5212,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,17.9164,0.3922,6.0354,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_RIV_10,EDERIV1671UN10_RA,34.3774,0.0148,22.8738,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_RIV_11,EDERIV1671UN11_RA,34.3774,0.0148,22.8738,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_RIV_12,EDERIV453UN12_PLT,34.0488,-0.3138,22.8738,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_SL_01,EDESTL4391UN1_RA,34.4620,0.0871,22.8861,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EDE_SWMP,EDE_SWMP_LA,31.8093,0.4454,19.8751,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EEI,EEI,19.4976,0.2654,7.7434,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EES,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-4.2013,-0.6097,-15.0804,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,ERCOTE,ERCOTE,30.3731,0.5841,18.3003,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,ERCOTN,ERCOTN,-9.9627,-0.6645,-20.7870,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,1.5312,-0.4661,-9.4915,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FMPP,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FPC,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FPL,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FREM_50T,OPPDFREM_GUN1_RA,1.6275,-0.3904,-9.4709,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FREM_6,OPPDFREM_AUN6_RA,1.6161,-0.3966,-9.4761,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FREM_7,OPPDFREM_AUN7_RA,1.6161,-0.3966,-9.4761,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FREM_8,OPPDFREM_AUN8_RA,1.5458,-0.4669,-9.4761,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FREM_LOAD,FREM_LOAD_LA,1.6049,-0.4078,-9.4761,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-9.1447,-0.4790,-20.1545,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,29.5394,0.7056,17.3450,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-18.8716,-1.4425,-28.9179,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-27.3281,-0.8860,-37.9309,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,34.3051,0.3267,22.4896,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,34.3051,0.3267,22.4896,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,34.3051,0.3267,22.4896,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,38.2394,0.2309,26.5197,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,38.2394,0.2309,26.5197,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,38.3672,0.2277,26.6507,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,38.3672,0.2277,26.6507,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-18.2992,-0.7638,-29.0242,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,65.6596,0.0432,54.1276,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,65.6596,0.0432,54.1276,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,65.6596,0.0432,54.1276,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.VOLT.0130,V130_DDR,39.1763,0.3575,27.3300,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA.VOLT.0237,V237_DDR,39.3019,0.2807,27.5324,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDAHUB2,GRDAHUB2_H,24.1586,-0.0438,12.7136,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDAHUB3,GRDAHUB3_H,18.1370,-0.1401,6.7883,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA_GRDA,GRDA_LA,40.4520,0.2748,28.6884,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA_HUB,GRDA_H,31.2583,0.0805,19.6890,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRDA_HUBSA,GRDASA_H,31.0176,0.0669,19.4619,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GRE,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-13.7135,0.0151,-25.2174,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GSEC_SPS,SPS_GSEC_LA,-16.5199,-0.3509,-27.6578,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GSPR2014HUB,GSPR2014HUB_H,-9.0997,-0.3811,-20.2074,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GSPR2015HUB,GSPR2015HUB_H,-8.3979,-0.3919,-19.4948,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-17.9768,-0.9592,-28.5064,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,HARRISON,CSWSLEBROCKPLT1,29.8062,0.6281,17.6893,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,HAST_TNSK_HUB,HAST_TNSK_H,1.6817,-0.7092,-9.0979,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,HQST,PJM,15.3036,0.0976,3.7171,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,HST,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,39.9426,0.1898,28.2640,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,39.9426,0.1898,28.2640,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,39.6448,0.1901,27.9659,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,39.6448,0.1901,27.9659,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,40.2059,0.1901,28.5270,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,40.2059,0.1901,28.5270,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,INDN_INDN,INDN_LA,39.8878,0.1987,28.2003,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-12.0300,-0.8343,-22.6845,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,ISNE,PJM,15.3036,0.0976,3.7171,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,JEA,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,1.9664,-0.2980,-9.2244,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,1.9664,-0.2980,-9.2244,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,3.9709,-0.0577,-7.4602,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KACYCT4,KACYNEARMANUNCT4_RA,27.5800,0.1188,15.9724,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,63.0757,0.0704,51.5165,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,27.5800,0.1188,15.9724,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,27.8963,0.1319,16.2756,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,27.8111,0.1305,16.1918,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KACY_KACY,KACY_LA,27.9700,0.1284,16.3528,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,39.9470,0.0575,28.4007,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,29.1526,0.4314,17.2324,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-13.9500,-0.4253,-25.0135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-33.7800,-0.7525,-44.5163,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.VOLT.0222,V222_DDR,0.1249,-0.0504,-11.3135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.VOLT.0223,V223_DDR,15.0440,-0.0283,3.5835,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.VOLT.0241,V241_DDR,24.5000,0.3703,12.6409,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.VOLT.0243,V243_DDR,22.4761,0.2246,10.7627,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.VOLT.0247,V247_DDR,21.9690,0.0678,10.4124,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.VOLT.0253,V253_DDR,40.2580,0.0613,28.7079,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,0.4157,-0.8013,-10.2718,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,12.0949,-0.1539,0.7600,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,12.0949,-0.1539,0.7600,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,12.0949,-0.1539,0.7600,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,12.0949,-0.1539,0.7600,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,40.3078,0.0553,28.7637,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,40.3078,0.0553,28.7637,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHUB,KCPLHUB_H,7.1223,-0.4324,-3.9341,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHUB17,KCPLHUB17_H,5.8249,-0.4874,-5.1765,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHUB18,KCPLHUB18_H,4.7730,-0.4882,-6.2275,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHUB19,KCPLHUB19_H,4.7403,-0.4642,-6.2843,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHUB20,KCPLHUB20_H,3.8398,-0.5054,-7.1436,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHUB21,KCPLHUB21_H,3.2460,-0.4961,-7.7467,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHUB22,KCPLHUB22_H,4.2303,-0.4909,-6.7675,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHUB23,KCPLHUB23_H,4.0382,-0.5042,-6.9464,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLHUB24,KCPLHUB24_H,2.9501,-0.5202,-8.0186,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,1.0801,-0.0714,-10.3373,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,1.0801,-0.0714,-10.3373,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,9.3300,-0.3304,-1.8284,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,9.3300,-0.3304,-1.8284,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,39.9476,0.0581,28.4007,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,39.9470,0.0575,28.4007,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,34.8189,0.0915,23.2386,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,34.8189,0.0915,23.2386,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,34.8189,0.0915,23.2386,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,34.8189,0.0915,23.2386,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,34.8189,0.0915,23.2386,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,34.8189,0.0915,23.2386,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,34.8189,0.0915,23.2386,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,34.8189,0.0915,23.2386,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,5.4293,-0.1532,-5.9063,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,23.8015,0.0622,12.2505,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KCPL_KCPL,KCPL_LA,25.7977,0.0478,14.2611,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KENN,KENN_LA,18.7892,0.3760,6.9244,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KEP2_SECI,KEP2_SECI_LA,-17.1989,-0.7856,-27.9021,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KERR_1,GRDAKERR_HYDUN1_RA,38.9370,0.2665,27.1817,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KERR_2,GRDAKERR_HYDUN2_RA,38.8235,0.2727,27.0620,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KERR_3,GRDAKERR_HYDUN3_RA,38.8235,0.2727,27.0620,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KERR_4,GRDAKERR_HYDUN4_RA,38.9370,0.2665,27.1817,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,12.0948,-0.1540,0.7600,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,12.0948,-0.1540,0.7600,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,13.3476,-0.0865,1.9453,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,13.3476,-0.0865,1.9453,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,10.0698,-0.1439,-1.2751,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,8.2794,-0.1244,-3.0850,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,8.2794,-0.1244,-3.0850,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-14.8757,-0.8997,-25.4648,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-14.8757,-0.8997,-25.4648,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-14.8757,-0.8997,-25.4648,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-8.1394,-0.6579,-18.9703,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-8.1394,-0.6579,-18.9703,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-15.2878,-0.9202,-25.8565,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-9.5863,-0.6730,-20.4022,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-1.6300,-0.4162,-12.7026,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,55.9820,0.0519,44.4413,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,55.9820,0.0519,44.4413,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,1.6777,-0.3387,-9.4724,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,1.6777,-0.3387,-9.4724,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,1.6777,-0.3387,-9.4724,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-11.1002,-0.8657,-21.7233,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-5.9360,-1.0054,-16.4194,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,5.6616,-0.3997,-5.4275,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,5.1293,-0.0142,-6.3453,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LAFA,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LAM345,LAM345,-15.4768,-1.0467,-25.9189,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LEPA,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,3.2326,-0.3975,-7.8587,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_LES,LES_LA,3.1309,-0.4044,-7.9535,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,3.0321,-0.4111,-8.0456,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,3.0666,-0.4409,-7.9813,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,3.0666,-0.4409,-7.9813,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,3.0666,-0.4409,-7.9813,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,3.0324,-0.4108,-8.0456,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,3.0321,-0.4111,-8.0456,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_WAVERLY,LES_WAVERLY_H,2.8924,-0.4247,-8.1717,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,2.1833,-0.3801,-8.9254,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,2.1833,-0.3801,-8.9254,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,LGEE,LGEE,17.4203,0.1805,5.7510,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MALDEN,MALDEN_LA,18.7724,0.3606,6.9230,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MCWEST,MCWEST,4.9060,-0.2415,-6.3413,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MDU,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-0.6200,-0.6347,-11.4740,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,1.7820,-0.1695,-9.5373,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,2.5980,0.1753,-9.0661,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MEAN_NPPD,NPPD_MEAN_LA,-0.4303,-0.8317,-11.0873,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,MEC,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MHEB,MHEB,5.9639,-0.1070,-5.4180,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-8.8034,-0.8901,-19.4021,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-11.3030,-1.0515,-21.7403,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-8.8034,-0.8901,-19.4021,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-8.8034,-0.8901,-19.4021,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-11.3030,-1.0515,-21.7403,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-17.1004,-0.5794,-28.0098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MISO,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-16.2335,-0.7267,-26.9956,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-16.2335,-0.7267,-26.9956,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-1.1710,-0.5375,-12.1223,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-17.1346,-1.0316,-27.5918,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-10.4807,-0.8558,-21.1137,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-17.7866,-0.9083,-28.3671,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-15.6786,-0.7576,-26.4098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-17.9198,-0.8526,-28.5560,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-15.1000,-0.6994,-25.8894,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-15.1000,-0.6994,-25.8894,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-15.1000,-0.6994,-25.8894,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-15.1000,-0.6994,-25.8894,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-15.1000,-0.6994,-25.8894,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,14.0269,-0.0117,2.5498,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,18.5440,0.2371,6.8181,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,18.5440,0.2371,6.8181,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,15.9866,0.1318,4.3660,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,22.2600,0.4151,10.3561,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MOWR,AECI,26.2687,0.2080,14.5719,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,18.7290,0.1272,7.1131,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,19.0397,0.2471,7.3038,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-5.0330,-0.6360,-15.8858,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-10.0000,-0.3567,-21.1321,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-26.5267,-0.8424,-37.1731,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-4.9954,-0.5984,-15.8858,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,12.2528,-0.0183,0.7823,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,12.2528,-0.0183,0.7823,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,12.2530,-0.0181,0.7823,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,12.2530,-0.0181,0.7823,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,0.1249,-0.0504,-11.3135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,0.1249,-0.0504,-11.3135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,0.1249,-0.0504,-11.3135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,0.0883,-0.0870,-11.3135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,0.1249,-0.0504,-11.3135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,0.1249,-0.0504,-11.3135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,0.1249,-0.0504,-11.3135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,23.3170,0.3607,11.4675,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,15.9357,-0.0185,4.4654,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,12.4933,-0.0542,1.0587,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,12.4933,-0.0542,1.0587,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,12.4933,-0.0542,1.0587,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,27.3462,0.0487,15.8087,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,27.3462,0.0487,15.8087,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MPS_MPS,MPS_LA,20.0236,0.0894,8.4454,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MSTNG,SPSMSTNGPLT1,3.8347,0.5294,-8.1835,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MSTNG4,SPSMSTNGUN4_RA,3.7999,0.4947,-8.1835,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,MSTNG5,SPSMSTNGUN5_RA,3.8347,0.5294,-8.1835,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,3.8347,0.5294,-8.1835,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NBSO,PJM,15.3036,0.0976,3.7171,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,0.1214,-0.6565,-10.7109,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,0.1208,-0.6570,-10.7109,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-18.7601,-1.2279,-29.0210,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NHC1,VACS,22.1467,0.3696,10.2884,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,1.9253,-0.3317,-9.2318,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,1.9253,-0.3317,-9.2318,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,1.9253,-0.3317,-9.2318,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-2.1376,-1.0633,-12.5631,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,0.9789,-0.9919,-9.5180,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,1.9221,-0.6580,-8.9087,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-4.2347,-0.5713,-15.1522,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,0.9789,-0.9919,-9.5180,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.HUB.PY2018,NPPDPY18_H,-0.6387,-0.8171,-11.3104,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,-0.5539,-0.8080,-11.2347,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,-0.5586,-0.8068,-11.2406,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,-0.4775,-0.7934,-11.1729,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-6.1865,-0.6139,-17.0614,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-1.2511,-0.9451,-11.7948,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-1.2511,-0.9451,-11.7948,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-5.3076,-0.8287,-15.9677,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-6.1865,-0.6139,-17.0614,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,6.4892,-1.1529,-3.8467,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,0.1238,-1.1678,-10.1972,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-4.1370,-0.8479,-14.7779,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,0.1238,-1.1678,-10.1972,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,1.1330,-1.0697,-9.2861,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-0.3784,-1.0846,-10.7826,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,2.7251,-0.3412,-8.4225,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,0.9789,-0.9919,-9.5180,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-3.6903,-0.8882,-14.2909,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-1.2511,-0.9451,-11.7948,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-1.2511,-0.9451,-11.7948,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-0.4462,-0.7414,-11.1936,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-0.5171,-0.7531,-11.2528,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-0.5171,-0.7531,-11.2528,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,0.3371,-0.5147,-10.6370,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-16.5200,-0.3359,-27.6729,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,1.2499,-0.8225,-9.4164,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-2.0407,-0.9249,-12.6046,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-16.2911,-0.2748,-27.5051,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-19.3000,-0.2937,-30.4951,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.NELI.DDR,NELI_DDR,-4.9493,-0.7153,-15.7228,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.NPPM.1058,SH1058_DDR,14.6531,-0.3933,3.5576,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,0.4657,-0.5880,-10.4351,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,0.9789,-0.9919,-9.5180,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,1.9221,-0.6580,-8.9087,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-6.1865,-0.6139,-17.0614,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.TECH.1,KEARNE_DDR,0.7730,-0.4863,-10.2295,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,1.6592,-1.2676,-8.5620,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,1.6592,-1.2676,-8.5620,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-6.0932,-0.6782,-16.9038,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD.VOLT.0236,V236_DDR,2.4159,-0.3233,-8.7496,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD2017HUB,NPPD2017HUB_H,-0.6200,-0.8139,-11.2948,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,12.4900,-0.6476,1.6488,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-2.1376,-1.0633,-12.5631,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,0.1100,-1.3388,-10.0400,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,0.1100,-1.3388,-10.0400,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,2.4578,-0.3505,-8.6805,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,2.4248,-0.3144,-8.7496,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-8.3144,-0.5747,-19.2285,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-0.3457,-0.7586,-11.0759,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,14.4271,-0.6193,3.5576,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,14.4271,-0.6193,3.5576,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,14.4271,-0.6193,3.5576,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,1.6835,-0.7083,-9.0970,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,0.8675,-0.6099,-10.0114,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,1.6433,-0.5956,-9.2499,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-3.6955,-1.2703,-13.9140,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-3.6346,-1.2094,-13.9140,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-2.0214,-0.9856,-12.5246,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-2.2392,-0.9882,-12.7398,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,2.5361,-0.6895,-8.2631,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,2.5257,-0.7000,-8.2631,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,2.5257,-0.7000,-8.2631,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,2.4731,-0.6747,-8.3410,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,6.4892,-1.1529,-3.8467,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,2.4063,-0.6781,-8.4044,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,2.6237,-0.5023,-8.3628,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,1.7035,-0.6863,-9.0990,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,1.6966,-0.6924,-9.0998,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,1.7024,-0.6866,-9.0998,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,1.7024,-0.6866,-9.0998,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,1.6835,-0.7083,-9.0970,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,1.6636,-0.7282,-9.0970,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,-0.8766,-0.7710,-11.5944,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,2.0353,-0.4882,-8.9653,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-2.0808,-0.9583,-12.6113,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,-0.6179,-1.1568,-10.9499,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-4.4652,-0.8884,-15.0656,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,14.8142,-0.2322,3.5576,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-4.9493,-0.7153,-15.7228,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-1.8213,-0.9671,-12.3430,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-1.8213,-0.9671,-12.3430,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_NPPD,NPPD_LA,3.7291,-0.6031,-7.1566,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,2.6237,-0.5023,-8.3628,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,2.6237,-0.5023,-8.3628,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,1.5758,-0.4813,-9.4317,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-1.0207,-0.8643,-11.6452,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NSB,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NSP,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,NSSO,PJM,15.3036,0.0976,3.7171,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,NYIS,PJM,15.3036,0.0976,3.7171,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-19.8664,-1.1678,-30.1874,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-20.2373,-0.8177,-30.9084,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-24.2254,-0.7495,-34.9647,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-24.2254,-0.7495,-34.9647,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-19.0858,-1.3236,-29.2510,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-27.3281,-0.8860,-37.9309,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-74.9524,-0.4362,-86.0050,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-37.0527,-0.8048,-47.7367,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-20.3178,-0.7640,-31.0426,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-19.0161,-0.8412,-29.6637,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-5.0644,-0.2635,-16.2897,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-20.3178,-0.7640,-31.0426,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-19.3253,-1.2945,-29.5196,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-17.1004,-0.5794,-28.0098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-20.1560,-1.1390,-30.5058,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,-5.1029,0.0679,-16.6596,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-19.0161,-0.8412,-29.6637,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-20.2880,-0.7495,-31.0273,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-14.0000,-0.7667,-24.7221,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-17.3536,-0.6167,-28.2257,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-35.3648,0.0354,-46.8890,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-17.1004,-0.5794,-28.0098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-17.1004,-0.5794,-28.0098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-19.0161,-0.8412,-29.6637,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-16.1925,-0.6044,-27.0769,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.NUEN.LAM1,LAM1_DDR,35.5315,0.8892,23.1535,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-5.0644,-0.2635,-16.2897,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-5.0644,-0.2635,-16.2897,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-16.4094,-0.5954,-27.3028,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-7.1532,-0.3018,-18.3402,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-7.1532,-0.3018,-18.3402,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-7.1532,-0.3018,-18.3402,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-2.1314,-0.2527,-13.3675,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-2.1314,-0.2527,-13.3675,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-7.1532,-0.3018,-18.3402,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-7.1532,-0.3018,-18.3402,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-19.0161,-0.8412,-29.6637,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,22.9547,0.4882,10.9777,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-19.3253,-1.2945,-29.5196,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-26.8385,-0.0947,-38.2326,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-20.2880,-0.7495,-31.0273,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,30.6789,0.5560,18.6341,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-21.1176,-0.5971,-32.0093,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-21.1176,-0.5971,-32.0093,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-21.1176,-0.5971,-32.0093,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-21.1176,-0.5971,-32.0093,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-23.6474,-1.1617,-33.9745,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-23.2161,-0.7475,-33.9574,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-20.2373,-0.8177,-30.9084,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-25.4542,-0.7058,-36.2372,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-25.4542,-0.7058,-36.2372,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-28.2776,-0.0225,-39.7439,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-18.9497,-0.6794,-29.7591,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-18.9497,-0.6794,-29.7591,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-18.9497,-0.6794,-29.7591,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0033,FOSTER_DDR,3.1860,-0.2176,-8.0852,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,20.7750,0.2570,9.0292,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0035,TARBY_DDR,35.5234,0.7272,23.3074,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,20.7750,0.2570,9.0292,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,19.0071,0.1431,7.3752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,19.0071,0.1431,7.3752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-30.3497,-0.0335,-41.8050,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0040,TROSPER_DDR,6.1560,-0.2024,-5.1304,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,6.1573,-0.2035,-5.1280,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,32.3303,0.6643,20.1772,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0115,V115_DDR,-4.1945,-0.2575,-15.4258,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0116,V116_DDR,0.1579,0.0738,-11.4047,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0118,V118_DDR,-0.2019,0.0679,-11.7586,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0125,V125_DDR,33.0621,0.7582,20.8151,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0126,V126_DDR,34.6397,0.4280,22.7229,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0129,V129_DDR,-7.7137,-0.4616,-18.7409,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,28.0300,-0.2687,16.8099,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0134,V134_DDR,35.5783,0.5138,23.5757,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0138,V138_DDR,33.8459,0.3763,21.9808,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,22.3637,-0.2130,11.0879,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0143,V143_DDR,25.7338,0.2166,14.0284,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0149,V149_DDR,-15.3535,-0.5477,-26.2946,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0150,V150_DDR,-15.3837,-0.5906,-26.2819,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0155,V155_DDR,33.1149,0.3195,21.3066,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0156,V156_DDR,28.0300,-0.2687,16.8099,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0166,V166_DDR,34.7672,0.7412,22.5372,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,21.6939,-0.2174,10.4225,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-15.3837,-0.5906,-26.2819,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0170,V170_DDR,-16.5353,-0.5955,-27.4286,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-23.2458,-0.5183,-34.2163,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0176,V176_DDR,-15.3837,-0.5906,-26.2819,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0177,V177_DDR,-22.1095,-1.0859,-32.5124,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,15.6541,-0.2166,4.3819,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-14.2210,-0.6577,-25.0521,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0195,V195_DDR,143.9400,0.8302,131.6210,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0197,V197_DDR,33.7374,0.5067,21.7419,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0198,V198_DDR,34.7672,0.7412,22.5372,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0208,V208_DDR,144.1569,0.8474,131.8207,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0209,V209_DDR,144.1569,0.8474,131.8207,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,34.4770,0.4005,22.5877,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0216,V216_DDR,6.1570,-0.2043,-5.1275,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0219,V219_DDR,33.1149,0.3195,21.3066,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0220,V220_DDR,-15.3837,-0.5906,-26.2819,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0224,V224_DDR,-4.8269,-0.2730,-16.0427,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0225,V225_DDR,-4.8263,-0.2724,-16.0427,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0226,V226_DDR,-4.8269,-0.2730,-16.0427,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0227,V227_DDR,-4.8269,-0.2730,-16.0427,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0229,V229_DDR,-28.0879,0.0241,-39.6008,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0231,V231_DDR,-4.0200,0.1756,-15.6844,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0238,V238_DDR,-24.7354,-0.8833,-35.3409,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.VOLT.0242,V242_DDR,33.4255,0.3473,21.5894,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-20.6896,-1.4395,-30.7389,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-17.1004,-0.5794,-28.0098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-21.4177,-0.7810,-32.1255,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-20.1457,-1.1287,-30.5058,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-20.6896,-1.4395,-30.7389,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-20.2454,-1.1962,-30.5380,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-41.2319,-0.7604,-51.9603,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEHL7,OKGEHL7_H,14.4717,-0.1945,3.1774,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEHL8,OKGEHSL1UN8_RA,14.4717,-0.1945,3.1774,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEHL910,OKGEHSL1PLT2,14.4717,-0.1945,3.1774,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-20.1597,-1.1703,-30.4782,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEMCC,OKGEMCCLAIPLT1,-6.8251,-0.3784,-17.9355,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,29.8840,0.2567,18.1385,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,29.8840,0.2567,18.1385,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,29.8840,0.2567,18.1385,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,10.4915,-0.3609,-0.6364,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,10.4915,-0.3609,-0.6364,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,10.4915,-0.3609,-0.6364,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,10.4915,-0.3609,-0.6364,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGESM1,OKGESEMINOLEUN1_RA,-0.3472,-0.1211,-11.7149,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGESM2,OKGESEMINOLEUN2_RA,2.5090,-0.1497,-8.8301,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGESM3,OKGESEMINOLEUN3_RA,2.5090,-0.1497,-8.8301,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGESO1,OKGESONR1UN1_RA,-43.9000,-0.6288,-54.7600,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGESO2,OKGESONR1UN2_RA,-25.4542,-0.7058,-36.2372,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-20.1597,-1.1703,-30.4782,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-19.5433,-1.4190,-29.6131,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGETINK5A,OKGETINK5UN1_RA,4.4629,-0.2239,-6.8020,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGETINK5B,OKGETINK5UN2_RA,4.4629,-0.2239,-6.8020,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-19.6725,-0.9957,-30.1656,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-20.2373,-0.8177,-30.9084,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,31.6347,0.8481,19.2978,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-17.1004,-0.5794,-28.0098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE_OKGE,OKGE_LA,8.5177,-0.0638,-2.9073,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-26.8385,-0.0947,-38.2326,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-19.7063,-1.0295,-30.1656,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMLP,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,40.7016,0.1970,29.0158,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,31.9392,0.8085,19.6419,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-2.0524,-0.2579,-13.2833,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-74.8552,-0.3390,-86.0050,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-15.6677,-0.7531,-26.4034,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-20.3178,-0.7640,-31.0426,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-20.4502,-1.0921,-30.8469,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-12.0052,-1.1403,-22.3537,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,147.6364,0.1740,135.9736,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-74.8867,-0.3705,-86.0050,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-74.8867,-0.3705,-86.0050,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_SPP,OMPA_SPP_LA,-6.6046,-0.4092,-17.6842,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-20.6896,-1.4395,-30.7389,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,35.1811,0.1933,23.4990,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,35.1811,0.1933,23.4990,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,35.1811,0.1933,23.4990,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,35.1811,0.1933,23.4990,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,ONT,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,1.8063,-0.3417,-9.3408,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,1.8063,-0.3417,-9.3408,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,1.8063,-0.3417,-9.3408,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,1.8063,-0.3417,-9.3408,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,1.8063,-0.3417,-9.3408,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,1.8063,-0.3417,-9.3408,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,1.8063,-0.3417,-9.3408,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,1.8063,-0.3417,-9.3408,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,1.8063,-0.3417,-9.3408,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,1.9280,-0.3191,-9.2417,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,1.9253,-0.3317,-9.2318,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,2.0239,-0.3362,-9.1287,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,1.9863,-0.3137,-9.1888,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,1.9863,-0.3137,-9.1888,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD_GLDN,OPPD_GLDN_LA,1.8991,-0.3374,-9.2523,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,1.8667,-0.3302,-9.2919,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,6.4892,-1.1529,-3.8467,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,1.5597,-0.4556,-9.4735,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,1.9254,-0.3312,-9.2322,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD_OPPD,OPPD_LA,1.9457,-0.3122,-9.2308,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,1.9827,-0.2994,-9.2067,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,1.9851,-0.3036,-9.2001,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OTP,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,OVEC,OVEC,16.6085,0.1495,4.9701,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,PARAGOULD,PARAGOULD_LA,18.8398,0.4008,6.9502,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,38.8476,0.1836,27.1752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,38.8476,0.1836,27.1752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,38.8476,0.1836,27.1752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,38.5351,0.2249,26.8214,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,38.5351,0.2249,26.8214,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,38.5351,0.2249,26.8214,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PIGGOTT,PIGGOTT_LA,18.7830,0.3705,6.9237,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PJM,PJM,15.3036,0.0976,3.7171,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,PLUM,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,POPLARBLUFF,POPLARBLUFF_LA,19.4901,0.3304,7.6709,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,4.7486,-0.3838,-6.3564,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,4.7486,-0.3838,-6.3564,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,4.7881,-0.3751,-6.3256,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,4.7881,-0.3751,-6.3256,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,5.6280,0.4503,-6.3111,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,5.6280,0.4503,-6.3111,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,4.8999,-0.2510,-6.3379,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,4.2415,-0.7409,-6.5064,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-7.4334,-0.4850,-18.4372,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,77.8918,0.2015,66.2015,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,2.0193,0.0136,-9.4831,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-0.3763,0.0479,-11.9130,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,53.3844,0.4365,41.4591,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,34.9395,0.4467,23.0040,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,4.4830,-0.3599,-6.6459,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,5.0223,-0.1539,-6.3126,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,2.9295,-0.5806,-7.9787,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,13.8047,0.7286,1.5874,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,5.6823,-0.0284,-5.7780,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,3.9315,-0.2567,-7.3006,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,PUPP,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,RCEAST,RCEAST,1.7554,-1.2042,-8.5292,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SALINA_1,GRDASALINA1UN1_RA,38.9381,0.2676,27.1817,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SALINA_2,GRDASALINA1UN2_RA,38.9381,0.2676,27.1817,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SALINA_3,GRDASALINA1UN3_RA,38.9381,0.2676,27.1817,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SALINA_4,GRDASALINA1UN4_RA,38.9381,0.2676,27.1817,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SALINA_5,GRDASALINA1UN5_RA,38.9381,0.2676,27.1817,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SALINA_6,GRDASALINA1UN6_RA,38.9381,0.2676,27.1817,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SARPY_1,OPPDSARPYUN1_RA,1.9497,-0.3201,-9.2190,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SARPY_2,OPPDSARPYUN2_RA,1.9830,-0.2991,-9.2067,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SARPY_3,OPPDSARPYUN3_RA,1.9474,-0.3454,-9.1960,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SARPY_4,OPPDSARPYUN4_RA,1.9474,-0.3454,-9.1960,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SARPY_5,OPPDSARPYUN5_RA,1.9474,-0.3454,-9.1960,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SC,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SCEG,VACS,22.1467,0.3696,10.2884,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,SCSE,SCSE,-1.6809,-0.9106,-12.2591,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SEC,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-20.0000,-1.1136,-30.3752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-20.0000,-1.1136,-30.3752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-20.0000,-1.1136,-30.3752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-14.8128,-0.6580,-25.6436,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-20.0000,-1.1136,-30.3752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-16.6686,-1.1005,-27.0569,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-16.2858,-1.1215,-26.6531,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-16.2858,-1.1215,-26.6531,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-15.1014,-0.7008,-25.8894,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-22.5736,-0.9819,-33.0805,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-8.1826,-0.7011,-18.9703,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-15.4722,-0.7369,-26.2241,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-10.0460,-0.9997,-20.5351,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-19.1922,-1.1180,-29.5630,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-10.0125,-0.9847,-20.5166,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-25.0000,-1.2020,-35.2868,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-16.8256,-0.7227,-27.5917,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-14.9990,-0.9526,-25.5352,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-14.9990,-0.9526,-25.5352,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-14.9990,-0.9526,-25.5352,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-14.9990,-0.9526,-25.5352,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-15.2495,-1.0077,-25.7305,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-16.6686,-1.1005,-27.0569,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI_SECI,SECI_LA,-14.3832,-0.7893,-25.0827,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-12.0300,-0.8343,-22.6845,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-12.0300,-0.8343,-22.6845,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-15.1014,-0.7008,-25.8894,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SEHA,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-19.7063,-1.0295,-30.1656,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SERU,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SETH,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SGE,SGE,-0.9902,-0.8844,-11.5946,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SMEP,MISO,14.9987,0.1185,3.3914,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SOCO,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPA,SPA,30.1120,0.4718,18.1514,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPC,SPC,5.4066,0.1568,-6.2390,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPPNORTH_HUB,SPPNORTH_H,2.7438,-0.4373,-8.3077,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-3.6053,-0.5062,-14.5879,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,28.8100,0.4401,16.8812,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,28.8100,0.4401,16.8812,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,28.2333,0.4130,16.3315,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,28.2333,0.4130,16.3315,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_NIXA,SPRM_NIXA_LA,29.0339,0.4511,17.0939,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_SPRM,SPRM_LA,28.8918,0.4771,16.9259,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,29.0061,0.3775,17.1398,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,29.0061,0.3775,17.1398,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,28.9773,0.3487,17.1398,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,29.0061,0.3775,17.1398,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-11.0756,-0.1470,-22.4174,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-16.6446,-0.4019,-27.7315,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-18.4774,-0.9506,-29.0156,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-18.4774,-0.9506,-29.0156,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-23.2547,-0.8925,-33.8510,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,-5.9624,-0.3917,-17.0595,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-13.9184,-1.2274,-24.1798,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,0.8232,-0.3010,-10.3646,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-24.6219,-0.3642,-35.7465,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,5.9723,0.4889,-6.0054,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,6.0206,0.4842,-5.9524,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,6.0206,0.4842,-5.9524,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,5.9723,0.4889,-6.0054,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-18.4456,-0.9201,-29.0143,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-16.6446,-0.4019,-27.7315,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-18.3219,-0.8641,-28.9466,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-18.7686,-1.3208,-28.9366,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-18.2396,-0.8005,-28.9279,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-18.0676,-0.6191,-28.9373,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-18.3156,-0.8635,-28.9409,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-18.7411,-1.3355,-28.8944,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-18.7411,-1.3355,-28.8944,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-18.7411,-1.3355,-28.8944,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-18.7411,-1.3355,-28.8944,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GRID.WRAB,WRAB_DDR,-18.1757,-0.6253,-29.0392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-18.7411,-1.3355,-28.8944,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-21.8620,-0.4128,-32.9380,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-21.8620,-0.4128,-32.9380,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-21.6809,-0.3763,-32.7934,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-21.6809,-0.3763,-32.7934,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-21.6809,-0.3763,-32.7934,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-21.8620,-0.4128,-32.9380,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-18.4857,-0.9205,-29.0540,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-18.4859,-0.9205,-29.0542,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-18.4850,-0.9205,-29.0533,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-18.7601,-1.2279,-29.0210,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,6.0810,0.4618,-5.8695,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-24.5072,-0.3701,-35.6259,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-24.5072,-0.3701,-35.6259,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-24.5072,-0.3701,-35.6259,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-24.5072,-0.3701,-35.6259,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,5.3750,0.5885,-6.7023,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,5.9758,0.4709,-5.9839,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,5.9758,0.4709,-5.9839,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-19.6532,-0.9764,-30.1656,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-18.4675,-0.9097,-29.0466,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-18.4675,-0.9097,-29.0466,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-18.4944,-0.9162,-29.0670,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-18.1757,-0.6253,-29.0392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-18.5832,-1.1494,-28.9226,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-18.4640,-0.9498,-29.0030,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-19.0858,-1.3236,-29.2510,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-18.3052,-0.7474,-29.0466,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-15.4189,-0.2873,-26.6204,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-15.4189,-0.2873,-26.6204,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-14.7329,-0.2914,-25.9303,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-23.6041,-0.7088,-34.3841,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-18.6494,-1.2266,-28.9115,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-13.7376,-1.0466,-24.1798,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-23.5859,-0.6906,-34.3841,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-18.4253,-0.8998,-29.0143,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-9.9383,-0.2350,-21.1921,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,1.1821,0.0579,-10.3646,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-9.9383,-0.2350,-21.1921,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,-9.2910,-0.0464,-20.7334,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-18.4074,-0.9918,-28.9044,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,5.8953,0.9918,-6.5853,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,5.9094,1.0059,-6.5853,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,5.8583,0.7583,-6.3888,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,5.9903,0.4787,-5.9772,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,4.6271,0.7408,-7.6025,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-15.4768,-1.0467,-25.9189,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-18.2265,-0.6753,-29.0400,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-13.5836,-0.2518,-24.8206,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-13.5836,-0.2518,-24.8206,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-9.9383,-0.2350,-21.1921,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-24.9320,-0.3048,-36.1160,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,11.5977,0.8100,-0.7011,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-12.5044,0.2658,-24.2590,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-12.4489,-0.0245,-23.9132,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-19.0358,-0.4356,-30.0890,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,5.8953,0.9918,-6.5853,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,5.4607,1.1969,-7.2250,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,5.2973,1.0335,-7.2250,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-23.4826,-0.5873,-34.3841,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-12.6824,0.0151,-24.1863,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-18.5996,-1.1718,-28.9165,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-18.6191,-1.1911,-28.9167,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0163,V163_DDR,-18.1799,-0.7538,-28.9149,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0168,V168_DDR,-20.0878,-0.5870,-30.9896,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0180,V180_DDR,5.4607,1.1969,-7.2250,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0181,V181_DDR,-18.4759,-1.0511,-28.9136,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0182,V182_DDR,4.8594,0.8792,-7.5086,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0199,V199_DDR,7.2315,0.7362,-4.9935,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0200,V200_DDR,5.9793,0.7504,-6.2599,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.VOLT.0235,V235_DDR,-18.5832,-1.1494,-28.9226,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-13.9184,-1.2274,-24.1798,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,0.8232,-0.3010,-10.3646,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-18.0434,-1.0258,-28.5064,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-18.3376,-0.8427,-28.9837,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS_SPS,SPS_LA,-3.0162,0.2937,-14.7987,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,1.8766,0.1060,-9.7182,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SSCN_NPPD,SSCN_NPPD_LA,-3.8962,-0.5197,-14.8653,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,18.7808,0.3130,6.9790,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,18.7808,0.3130,6.9790,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,TAL,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,TEC,SOUC,22.4221,0.3941,10.5392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,-0.6179,-1.1568,-10.9499,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,TVA,TVA,21.8524,0.3437,10.0199,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,UCUHUB,UCUHUB_H,-1.0931,-0.2990,-12.2828,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,UCUHUB17,UCUHUB17_H,-9.2702,-0.5810,-20.1779,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,UCUHUB18,UCUHUB18_H,-6.0890,-0.4900,-17.0879,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,UCUHUB19,UCUHUB19_H,-9.9759,-0.5196,-20.9451,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,UCUHUB20,UCUHUB20_H,-9.4682,-0.4978,-20.4593,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,UCUHUB21,UCUHUB21_H,-10.6723,-0.5754,-21.5857,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,UCUHUB22,UCUHUB22_H,-11.0398,-0.6055,-21.9231,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,UCUHUB23,UCUHUB23_H,-11.5093,-0.6100,-22.3880,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,UCUHUB24,UCUHUB24_H,-8.6231,-0.5268,-19.5851,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,5.4733,0.2420,-6.2575,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,5.4733,0.2420,-6.2575,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,4.5330,-0.4762,-6.4796,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,4.5330,-0.4762,-6.4796,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,5.1096,-0.4921,-5.8871,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,4.7676,-0.4209,-6.3003,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,4.7676,-0.4209,-6.3003,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,5.4733,0.2420,-6.2575,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,5.1770,-0.4746,-5.8372,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,5.4224,-0.0654,-6.0010,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,3.4795,-0.3344,-7.6749,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,1.6642,-1.3957,-8.4289,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,5.3641,0.1776,-6.3023,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,5.3641,0.1776,-6.3023,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,3.2773,-1.3040,-6.9075,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,3.8884,-0.5441,-7.0563,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,4.6216,-0.6041,-6.2631,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,2.7281,-0.5805,-8.1801,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,3.4361,-0.3438,-7.7089,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,3.7012,-0.5884,-7.1992,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,3.8607,-0.7206,-6.9075,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,3.8607,-0.7206,-6.9075,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,4.1207,-0.5108,-6.8572,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,1.7159,-1.5019,-8.2710,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,3.9933,0.1701,-7.6656,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,4.9877,-0.1712,-6.3299,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,4.9877,-0.1712,-6.3299,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,4.9877,-0.1712,-6.3299,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,5.0961,-0.0575,-6.3352,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,5.0961,-0.0575,-6.3352,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,5.0961,-0.0575,-6.3352,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,5.6314,0.3728,-6.2302,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,4.8872,-0.4623,-6.1392,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,4.8872,-0.4623,-6.1392,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-1.3350,-0.8984,-11.9254,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,2.7483,-0.4631,-8.2774,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,5.2439,-0.0900,-6.1548,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,0.2988,-0.5821,-10.6078,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,1.2119,-1.8037,-8.4732,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,4.0368,-0.6172,-6.8347,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,5.4426,0.2485,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,5.4426,0.2485,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,5.4419,0.2478,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,5.4426,0.2485,-6.2947,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,5.3206,0.1416,-6.3098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,5.3206,0.1416,-6.3098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,5.3206,0.1416,-6.3098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,5.3206,0.1416,-6.3098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,5.3206,0.1416,-6.3098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,5.3206,0.1416,-6.3098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,5.3206,0.1416,-6.3098,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,0.7156,-1.1098,-9.6634,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,5.2984,-0.2953,-5.8951,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,1.3940,-0.4031,-9.6917,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,1.3940,-0.4031,-9.6917,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,-0.8363,-0.6930,-11.6321,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,-0.8363,-0.6930,-11.6321,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,5.0217,-0.3279,-6.1392,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,5.1343,-0.3236,-6.0309,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,3.0205,-0.6840,-7.7843,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,2.1514,-1.3089,-8.0285,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,5.0043,-0.2442,-6.2403,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,5.1096,-0.4921,-5.8871,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,5.1096,-0.4921,-5.8871,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,2.7281,-0.5805,-8.1801,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,1.6867,-1.2535,-8.5486,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,3.3657,-0.7704,-7.3527,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,1.8301,-1.3877,-8.2710,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,3.8781,-0.6620,-6.9487,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.FSE,WAUE.FSE_H,0.3492,-0.7970,-10.3426,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,4.8429,-0.3321,-6.3137,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,4.8195,-0.3540,-6.3153,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,1.1204,-1.3699,-8.9985,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,1.7976,-1.3060,-8.3852,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,5.0499,-0.4674,-5.9715,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,5.0606,-0.5086,-5.9196,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-15.9100,-1.1483,-26.2505,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,1.6642,-1.3957,-8.4289,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-11.5200,-1.0434,-21.9654,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,3.2589,-0.3946,-7.8353,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,3.2589,-0.3946,-7.8353,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,3.2595,-0.3940,-7.8353,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,3.8481,-0.5524,-7.0883,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,1.6867,-1.2535,-8.5486,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,4.4509,-0.1902,-6.8477,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,2.5863,-0.6151,-8.2874,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,3.9470,0.1238,-7.6656,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,3.8878,0.0896,-7.6905,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,3.6030,-0.2866,-7.5992,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,6.5198,-0.1700,-4.7990,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,3.1113,-0.4196,-7.9579,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,2.9522,-0.6716,-7.8650,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,0.2988,-0.5821,-10.6078,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,7.2919,0.1450,-4.3419,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,2.7148,-0.5903,-8.1837,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,7.2002,0.1030,-4.3916,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,4.1327,-0.1937,-7.1624,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,2.1833,-0.3801,-8.9254,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NTWK,WAUE.NTWK_H,3.3671,-0.4621,-7.6596,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,4.6264,0.0679,-6.9303,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,4.6264,0.0679,-6.9303,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,1.5260,-1.4635,-8.4993,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,0.2252,-1.3615,-9.9021,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,4.3419,-0.4779,-6.6690,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,1.5260,-1.4635,-8.4993,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,5.8263,-0.2321,-5.4304,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,2.8391,-0.8845,-7.7652,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,0.2988,-0.5821,-10.6078,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,3.4908,-0.6292,-7.3688,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,2.1607,-1.5629,-7.7652,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,0.3856,-1.7381,-9.3651,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,0.8898,-1.7415,-8.8575,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,4.5160,-0.5001,-6.4727,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,1.6450,-1.3686,-8.4752,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,4.6411,-0.3027,-6.5450,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,2.3447,-1.1996,-7.9445,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,2.1514,-1.3089,-8.0285,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.VOLT.0152,V152_DDR,5.8246,0.5241,-6.1883,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE.VOLT.0172,V172_DDR,5.3759,0.1914,-6.3043,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_BEPM,WAUE_BEPM_LA,4.6241,-0.0856,-6.7792,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,4.4609,-0.2155,-6.8125,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,3.8873,0.0956,-7.6971,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_EWA,WAUE_EWA_LA,1.7912,-1.1780,-8.5196,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,2.3109,-0.7787,-8.3991,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_HMMU,WAUE_HMMU_LA,3.0509,-0.0938,-8.3441,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,6.5397,-0.2364,-4.7127,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_MECB,WAUE_MECB_LA,3.0213,-0.0922,-8.3752,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_MMPA,WAUE_MMPA_LA,5.8961,0.0387,-5.6314,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_MRES,WAUE_MRES_LA,3.1674,-0.4423,-7.8791,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,5.6904,0.3009,-6.0993,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,4.8429,-0.3321,-6.3137,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,2.0532,-0.7536,-8.6821,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_OTP,WAUE_OTP_LA,6.5953,0.2536,-5.1472,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_OTPW,WAUE_OTPW_LA,10.4015,0.4231,-1.5103,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM,WAUE_UGPM_LA,4.2440,-0.3763,-6.8685,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,4.4018,-0.1927,-6.8943,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,3.2846,-0.3612,-7.8430,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,1.3505,-0.7247,-9.4136,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,1.7912,-1.1780,-8.5196,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,3.0509,-0.0938,-8.3441,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,2.1727,-0.7439,-8.5722,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,4.8429,-0.3321,-6.3137,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,5.8961,0.0387,-5.6314,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,3.4517,-0.3902,-7.6469,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,2.3939,-0.8788,-8.2162,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,5.9551,0.2706,-5.8043,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-20.5375,-1.2844,-30.7419,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-20.1253,-1.0225,-30.5916,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,-3.9682,-0.8812,-14.5758,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,85.2040,0.4153,73.2999,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,85.2040,0.4153,73.2999,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-14.5854,-1.5833,-24.4909,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,78.9420,0.4792,66.9740,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,71.6053,0.4598,59.6567,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,11.9162,-0.6165,1.0439,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,11.9162,-0.6165,1.0439,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,11.9162,-0.6165,1.0439,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,11.9162,-0.6165,1.0439,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,11.8908,-0.6419,1.0439,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,11.9162,-0.6165,1.0439,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,11.9162,-0.6165,1.0439,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,11.9162,-0.6165,1.0439,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,3.8311,-0.5799,-7.0778,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-19.0858,-1.3236,-29.2510,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-30.0000,-1.0113,-40.4775,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-20.9164,-1.1903,-31.2149,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-13.8090,-1.1180,-24.1798,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_ENMC,WFEC_ENMC_LA,0.7343,0.4478,-11.2023,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-19.0161,-0.8412,-29.6637,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,40.0804,0.3362,28.2554,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,5.5437,0.5372,-6.4823,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-20.5375,-1.2844,-30.7419,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-20.5375,-1.2844,-30.7419,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-20.5375,-1.2844,-30.7419,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_OKGE,WFEC_OKGE_LA,6.2795,0.1323,-5.3416,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,43.7829,0.4914,31.8028,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-17.9668,-1.5738,-27.8818,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-13.8177,-1.6932,-23.6133,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_WFEC,WFEC_LA,13.9497,-0.1766,2.6375,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,5.5437,0.5372,-6.4823,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-9.1525,-0.9028,-19.7385,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-13.5435,-1.0889,-23.9434,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,0.2496,-0.4526,-10.7866,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,0.2496,-0.4526,-10.7866,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,0.2496,-0.4526,-10.7866,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,0.2496,-0.4526,-10.7866,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,0.2496,-0.4526,-10.7866,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,0.2496,-0.4526,-10.7866,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,0.2496,-0.4526,-10.7866,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,4.9932,0.4664,-6.9620,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-1.4546,-0.6396,-12.3038,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-14.1188,-0.8052,-24.8023,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-14.1188,-0.8052,-24.8023,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-14.1188,-0.8052,-24.8023,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-20.9085,-0.9798,-31.4175,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-20.9085,-0.9798,-31.4175,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-6.2193,-0.7363,-16.9718,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-6.2193,-0.7363,-16.9718,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-6.2193,-0.7363,-16.9718,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-1.4546,-0.6396,-12.3038,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,2.6790,-0.0832,-8.7266,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-6.1338,-0.6196,-17.0030,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-6.1338,-0.6196,-17.0030,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-6.1338,-0.6196,-17.0030,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-6.1338,-0.6196,-17.0030,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,2.6790,-0.0832,-8.7266,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-17.9377,-1.1248,-28.3016,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-26.7466,-0.2573,-37.9780,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.JEC.1,WRJEFFUN10_RA,0.5674,-0.4623,-10.4591,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.JEC.2,WRJEFFUN11_RA,0.4923,-0.4653,-10.5312,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.JEC.3,WRJEFFUN12_RA,0.4346,-0.5230,-10.5312,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-18.2992,-0.7638,-29.0242,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-26.5192,-0.8348,-37.1731,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-26.5192,-0.8348,-37.1731,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.LEC.4,WRLECUN26_RA,3.8252,-0.1115,-7.5521,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.LEC.5,WRLECUN27_RA,3.6646,-0.0874,-7.7368,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-4.8313,-0.5640,-15.7561,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-4.8313,-0.5640,-15.7561,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-4.8313,-0.5640,-15.7561,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-4.7930,-0.5412,-15.7406,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-12.0300,-0.8343,-22.6845,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-12.0300,-0.8343,-22.6845,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-9.9047,-0.9186,-20.4749,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-8.8420,-0.8597,-19.4711,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-8.8420,-0.8597,-19.4711,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-5.9417,-1.0111,-16.4194,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-12.0300,-0.8343,-22.6845,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,0.7620,-0.6818,-10.0450,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-2.4778,-0.7143,-13.2523,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-26.5221,-0.8378,-37.1731,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,74.3800,0.4685,62.4227,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-6.8228,-1.4641,-16.8475,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,0.2496,-0.4526,-10.7866,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-1.9216,-0.8206,-12.5897,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,2.6790,-0.0832,-8.7266,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-1.4546,-0.6396,-12.3038,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-9.1533,-0.6082,-20.0339,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.THAYERLD,WR.THAYERLD_LA,20.8341,0.3741,8.9712,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-9.8204,-0.6041,-20.7051,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0106,V106_DDR,-9.3374,-0.5715,-20.2547,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0139,WR.VOLT.0139_H,7.2073,0.0123,-4.2938,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-2.6182,-0.5462,-13.5608,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0146,WR.VOLT.0146_H,4.2164,-0.0140,-7.2584,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0147,WR.VOLT.0147_H,4.2164,-0.0140,-7.2584,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0148,WR.VOLT.0148_H,3.2269,-0.0437,-8.2182,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-9.1587,-0.4915,-20.1560,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0157,V157_DDR,4.1097,-0.0271,-7.3520,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0158,V158_DDR,4.2164,-0.0140,-7.2584,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0159,WR.VOLT.0159_H,4.2164,-0.0140,-7.2584,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-9.8531,-0.6380,-20.7039,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0173,V173_DDR,-5.2390,-0.6518,-16.0760,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0174,V174_DDR,-9.6078,-0.5835,-20.5131,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0184,V184_DDR,-9.2956,-0.6534,-20.1310,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-9.2762,-0.6011,-20.1639,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0186,V186_DDR,-8.9976,-0.6410,-19.8454,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-9.3455,-0.6316,-20.2027,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-9.7939,-0.5769,-20.7058,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-4.0376,-0.4485,-15.0779,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-0.6977,-0.3976,-11.7889,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-0.0714,-0.4185,-11.1417,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-0.0714,-0.4185,-11.1417,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-0.6977,-0.3976,-11.7889,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0245,V245_DDR,-9.2682,-0.6023,-20.1547,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.VOLT.0248,V248_DDR,-9.3374,-0.5715,-20.2547,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-14.2547,-0.7181,-25.0254,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,2.0751,-0.2189,-9.1948,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.WOLF,WRWOLFUN15_RA,-2.0641,-0.8825,-12.6704,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-17.9377,-1.1248,-28.3016,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,4.9355,0.4087,-6.9620,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-14.1188,-0.8052,-24.8023,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-14.1188,-0.8052,-24.8023,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-14.1188,-0.8052,-24.8023,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-14.1188,-0.8052,-24.8023,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-11.2058,-0.5152,-22.1794,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-2.5408,-0.5487,-13.4809,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-10.7144,-0.5920,-21.6112,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-10.7144,-0.5920,-21.6112,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-10.7144,-0.5920,-21.6112,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-10.7144,-0.5920,-21.6112,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-0.9620,-0.3695,-12.0813,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-0.9620,-0.3695,-12.0813,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-0.9620,-0.3695,-12.0813,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-0.9620,-0.3695,-12.0813,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-0.9620,-0.3695,-12.0813,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-0.9620,-0.3695,-12.0813,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-22.8773,-0.5742,-33.7919,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-22.8773,-0.5742,-33.7919,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-25.5534,-0.5562,-36.4859,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-25.5534,-0.5562,-36.4859,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_MIDW,WR_MIDW_LA,-9.2800,-0.8553,-19.9135,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,24.5447,0.2623,12.7936,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,17.9741,0.1094,6.3760,11.4887\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-10.6949,-0.7494,-21.4343,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_SEG,WR_SEG_LA,3.7391,0.3146,-8.0644,11.4889\n03/19/2025 17:00:00,03/19/2025 22:00:00,WR_WR,WR_LA,-1.9410,-0.3995,-13.0303,11.4888\n03/19/2025 17:00:00,03/19/2025 22:00:00,YAD,VACS,22.1467,0.3696,10.2884,11.4887\n03/19/2025 18:00:00,03/19/2025 23:00:00,AEC,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,AECC_CSWS,CSWS_AECC_LA,34.8004,0.6225,20.3872,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,36.9248,0.4268,22.7073,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,32.6914,0.8497,18.0511,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,37.2080,0.2842,23.1331,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,32.0589,0.5538,17.7144,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,33.1744,0.3767,19.0071,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,32.9860,0.4051,18.7902,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,AECI,AECI,28.7597,0.1480,14.8210,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,AEPM_CSWS,CSWS_LA,33.9833,0.6172,19.5754,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,ALTW,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,AMRN,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,-22.1891,-0.2536,-35.7262,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BBA,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BCA,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BEPM.ER01.DDR,ER01_DDR,1.5013,-2.0863,-10.2031,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BEPM_ER01,BEPM_ER01_LA,1.5013,-2.0863,-10.2031,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,0.5453,-1.0020,-12.2433,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-1.5091,-0.5116,-14.7881,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,BEPM_UM01,BEPM_UM01_LA,9.0258,0.1626,-4.9274,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,BLKW,BLKW,-5.9309,0.2143,-19.9359,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-29.7711,-1.1660,-42.3958,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-29.7711,-1.1660,-42.3958,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,11.8207,-1.0429,-0.9270,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.7460,-1.1409,-42.3958,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BRAZ,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BUBA,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-14.2203,-1.1159,-26.8951,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-15.9000,-0.6880,-29.0027,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-15.9000,-0.6880,-29.0027,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-15.9000,-0.6880,-29.0027,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-15.9000,-0.6880,-29.0027,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-15.9000,-0.6880,-29.0027,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-8.6723,-0.6221,-21.8409,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,3.1617,-0.5516,-10.0773,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,3.1617,-0.5516,-10.0773,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CLEC,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,35.5439,0.2667,21.4865,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,COWP,COWP_LA,25.4794,0.3220,11.3668,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,25.4794,0.3220,11.3668,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,25.4794,0.3220,11.3668,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CPLE,VACS,25.0079,0.3864,10.8307,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,CPLW,VACS,25.0079,0.3864,10.8307,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,26.1517,0.5036,11.8574,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,26.1517,0.5036,11.8574,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,26.1517,0.5036,11.8574,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,26.1517,0.5036,11.8574,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CRTH_SPA,WRCRTH_SPA_LA,36.1199,0.0617,22.2675,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,32.4672,1.5091,17.1674,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,-1.7464,-0.5399,-14.9971,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,32.9860,0.4051,18.7902,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,37.2080,0.2842,23.1331,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,32.4637,1.4996,17.1735,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,32.4649,1.0531,17.6211,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,32.4576,1.3706,17.2963,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,32.4576,1.3706,17.2963,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,36.5401,0.3396,22.4098,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,36.5401,0.3396,22.4098,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,36.4522,0.2517,22.4098,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,36.4522,0.2517,22.4098,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,32.9860,0.4051,18.7902,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,36.1295,1.0581,21.2807,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,59.4385,-0.0688,45.7166,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,59.3113,-0.1960,45.7166,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,40.4092,0.1188,26.4997,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,36.6821,0.2016,22.6899,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,36.6821,0.2016,22.6899,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,36.6842,0.2016,22.6920,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,36.6842,0.2016,22.6920,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-20.4691,-0.6822,-33.5776,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,3.3044,-0.3759,-10.1104,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,43.3618,0.3036,29.2675,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-19.2762,-0.7928,-32.2740,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-19.2315,-0.7482,-32.2740,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-11.4457,-0.4075,-24.8289,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.GRID.CDL1,CDL1_DDR,38.7310,0.3647,24.5756,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,-4.6941,-0.5119,-17.9729,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,-1.4809,-0.7950,-14.4766,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,38.7310,0.3647,24.5756,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.NUEN.CSI1,CSI1_DDR,40.5903,0.3169,26.4827,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.NUEN.CSI2,CSI2_DDR,40.5970,0.3236,26.4827,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,35.5470,0.2698,21.4865,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.NUEN.GAZA,GAZA_DDR,38.7310,0.3647,24.5756,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,99.0300,0.7155,84.5238,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.NUEN.T201,NT201_DDR,37.7841,0.2396,23.7539,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-6.0630,-0.8010,-19.0527,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-6.0630,-0.8010,-19.0527,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,32.9860,0.4051,18.7902,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,33.2130,1.5611,17.8613,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-11.4457,-0.4075,-24.8289,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-11.4457,-0.4075,-24.8289,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-14.5670,-0.6586,-27.6991,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-19.2315,-0.7482,-32.2740,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,32.0327,0.8861,17.3559,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,34.2559,0.1101,20.3551,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,34.0583,-0.0875,20.3551,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,34.0508,-0.0949,20.3551,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,15.5582,0.1283,1.6392,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,15.5582,0.1283,1.6392,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,32.5526,1.0211,17.7408,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,37.3550,0.2557,23.3086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,32.5519,1.0563,17.7050,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,33.6670,1.8851,17.9912,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,37.7946,0.5152,23.4888,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,40.5970,0.3236,26.4827,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0057,OKMU_DDR,39.1535,0.3719,24.9909,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0060,LEHIGH_DDR,99.0300,0.7155,84.5238,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0086,WARRENM_DDR,37.1926,0.2585,23.1434,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,33.3920,1.4138,18.1876,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,49.9721,0.2179,35.9635,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0121,V121_DDR,32.5526,1.0211,17.7408,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0122,V122_DDR,48.2532,0.2081,34.2544,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0124,V124_DDR,69.8549,0.1432,55.9210,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0135,V135_DDR,38.2790,0.2595,24.2288,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0144,V144_DDR,3.7538,-0.3151,-9.7218,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0145,V145_DDR,3.9229,-0.3799,-9.4879,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,32.5860,1.0337,17.7617,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,33.3269,0.5854,18.9509,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0175,V175_DDR,35.5470,0.2698,21.4865,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,33.3269,0.5854,18.9509,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,33.4116,0.6796,18.9413,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,38.2790,0.2595,24.2288,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,38.6759,0.2483,24.6369,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,38.2287,0.2223,24.2157,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,54.9994,0.0603,41.1484,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,36.7770,0.1913,22.7950,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,38.6759,0.2483,24.6369,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0211,V211_DDR,32.6437,1.2260,17.6270,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,50.8255,0.2254,36.8094,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0213,V213_DDR,38.0708,0.2527,24.0274,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0215,V215_DDR,49.4225,0.2156,35.4162,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0217,V217_DDR,50.8881,0.2114,36.8860,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0218,V218_DDR,54.5025,0.0712,40.6406,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0228,V228_DDR,38.5605,0.2195,24.5503,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0232,V232_DDR,37.5410,0.2542,23.4961,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0233,V233_DDR,38.8219,0.2602,24.7710,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0240,V240_DDR,46.1199,0.1796,32.1497,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0244,V244_DDR,38.6759,0.2483,24.6369,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0246,MDT1_DDR,99.0300,0.7155,84.5238,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0249,V249_DDR,38.0123,0.2658,23.9558,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0250,V250_DDR,-2.4917,-0.5077,-15.7747,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0251,V251_DDR,37.2672,0.2269,23.2496,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.VOLT.0252,V252_DDR,54.9994,0.0603,41.1484,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-22.4608,-0.6773,-35.5741,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,9.2638,-0.8079,-3.7190,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-17.4255,-1.4602,-29.7560,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,32.4476,0.9778,17.6791,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-20.0552,-1.2751,-32.5708,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,0.8852,-0.4150,-12.4904,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,0.8852,-0.4150,-12.4904,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,0.8852,-0.4150,-12.4904,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,0.8852,-0.4150,-12.4904,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,0.8852,-0.4150,-12.4904,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,32.9860,0.4051,18.7902,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,31.6995,1.3211,16.5878,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,37.5198,0.2330,23.4961,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,37.4356,0.1489,23.4961,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,41.1601,0.4296,26.9399,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,41.1601,0.4296,26.9399,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWWELSH1,CSWSWELSHUN1_RA,32.8535,0.7476,18.3153,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWWELSH3,CSWSWELSHUN3_RA,32.8535,0.7476,18.3153,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWWILKES1,CSWSWILKESUN1_RA,32.9441,1.0248,18.1287,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWWILKES2,CSWSWILKESUN2_RA,32.9441,1.0248,18.1287,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,CSWWILKES3,CSWSWILKESUN3_RA,32.6902,0.9725,17.9270,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-19.2160,-0.7327,-32.2740,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,DENL,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,DERS,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,DOE,DOE,22.4319,0.2431,8.3981,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,11.4209,-0.0936,-2.2761,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,DPC,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,DUK,VACS,25.0079,0.3864,10.8307,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDDY,EDDY,27.2728,0.9402,12.5419,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,34.4474,-0.0250,20.6817,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-2.7964,-0.2253,-16.3618,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,39.1692,-0.1387,25.5172,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE.SLCC,EDESTL4391_PLT,35.7326,-0.0381,21.9801,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,35.6883,0.0038,21.8938,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,21.9203,-0.2703,8.3998,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_EC_01,EDELAR3821UN1_RA,34.4474,-0.0250,20.6817,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_EC_02,EDELAR3821UN2_RA,34.4474,-0.0250,20.6817,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_EC_03,EDELAR3821UN3_RA,34.4474,-0.0250,20.6817,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_EC_04,EDELAR3821UN4_RA,34.4474,-0.0250,20.6817,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_EDE,EDE_LA,34.1805,0.2745,20.1153,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_ERW,EDEERWFUNG1_RA,-9.4800,-0.6753,-22.5954,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-6.9882,-0.9109,-19.8680,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,31.4103,0.5650,17.0546,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,31.4103,0.5650,17.0546,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,31.4103,0.5650,17.0546,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,31.4103,0.5650,17.0546,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,18.7212,0.4142,4.5164,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_RIV_10,EDERIV1671UN10_RA,35.5883,-0.1179,21.9156,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_RIV_11,EDERIV1671UN11_RA,35.5883,-0.1179,21.9156,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_RIV_12,EDERIV453UN12_PLT,35.1963,-0.5100,21.9156,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_SL_01,EDESTL4391UN1_RA,35.7326,-0.0381,21.9801,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,EDE_SWMP,EDE_SWMP_LA,33.3676,0.3622,19.2147,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EEI,EEI,22.3652,0.2411,8.3334,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EES,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-8.4979,-0.7472,-21.5414,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,ERCOTE,ERCOTE,32.8535,0.7476,18.3153,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,ERCOTN,ERCOTN,-6.0000,-0.7380,-19.0527,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,-0.7646,-0.6703,-13.8850,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,FMPP,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,FPC,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,FPL,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,FREM_50T,OPPDFREM_GUN1_RA,3.1227,-0.5859,-10.0821,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,FREM_6,OPPDFREM_AUN6_RA,3.1146,-0.5935,-10.0826,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,FREM_7,OPPDFREM_AUN7_RA,3.1146,-0.5935,-10.0826,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,FREM_8,OPPDFREM_AUN8_RA,3.0310,-0.6771,-10.0826,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,FREM_LOAD,FREM_LOAD_LA,3.1011,-0.6069,-10.0826,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-12.8332,-0.5844,-26.0394,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,32.0316,0.8850,17.3559,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-17.2137,-1.5389,-29.4655,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-31.7573,-1.0627,-44.4853,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,35.5439,0.2667,21.4865,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,35.5439,0.2667,21.4865,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,35.5439,0.2667,21.4865,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,40.5987,0.1509,26.6571,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,40.5987,0.1509,26.6571,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,40.7515,0.1473,26.8135,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,40.7515,0.1473,26.8135,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-21.4096,-0.9240,-34.2763,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,62.6077,-0.0333,48.8503,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,62.6077,-0.0333,48.8503,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,62.6077,-0.0333,48.8503,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.VOLT.0130,V130_DDR,41.5580,0.2964,27.4709,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA.VOLT.0237,V237_DDR,41.7567,0.2071,27.7589,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDAHUB2,GRDAHUB2_H,25.3165,-0.1258,11.6516,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDAHUB3,GRDAHUB3_H,18.9539,-0.2287,5.3920,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA_GRDA,GRDA_LA,42.1550,0.2124,28.1520,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA_HUB,GRDA_H,33.0255,0.0055,19.2292,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRDA_HUBSA,GRDASA_H,32.7514,-0.0129,18.9737,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,GRE,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-10.7225,0.2753,-24.7884,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,GSEC_SPS,SPS_GSEC_LA,-12.8561,-0.1657,-26.4811,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GSPR2014HUB,GSPR2014HUB_H,0.0352,-0.1725,-13.5829,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,GSPR2015HUB,GSPR2015HUB_H,0.1442,-0.1997,-13.4468,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,-15.1041,-0.8413,-28.0535,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,HARRISON,CSWSLEBROCKPLT1,32.2861,0.7958,17.6997,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,HAST_TNSK_HUB,HAST_TNSK_H,1.1997,-0.9257,-11.6654,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,HQST,PJM,18.2335,0.0290,4.4139,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,HST,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,41.0572,0.1593,27.1072,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,41.0572,0.1593,27.1072,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,40.0819,0.1623,26.1290,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,40.0819,0.1623,26.1290,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,42.0498,0.1598,28.0993,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,42.0498,0.1598,28.0993,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,INDN_INDN,INDN_LA,40.8941,0.1710,26.9324,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-9.1000,-1.0617,-21.8290,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,ISNE,PJM,18.2335,0.0290,4.4139,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,JEA,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,3.3206,-0.4781,-9.9920,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,3.3206,-0.4781,-9.9920,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-8.7172,-0.1085,-22.3994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KACYCT4,KACYNEARMANUNCT4_RA,31.1200,0.0839,17.2454,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,64.1163,-0.0667,50.3923,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,31.1200,0.0839,17.2454,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,30.4006,0.0992,16.5107,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,30.5981,0.0974,16.7101,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KACY_KACY,KACY_LA,30.2855,0.0945,16.4004,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,25.5848,0.0038,11.7904,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,35.2746,0.4364,21.0476,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-13.9500,-0.6495,-27.0912,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-43.0318,-0.9269,-55.8955,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.VOLT.0222,V222_DDR,1.4719,-0.1303,-12.1884,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.VOLT.0223,V223_DDR,12.9866,-0.0975,-0.7066,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.VOLT.0241,V241_DDR,29.1800,0.3495,15.0398,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.VOLT.0243,V243_DDR,26.9638,0.0674,13.1057,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.VOLT.0247,V247_DDR,22.3283,0.0158,8.5218,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.VOLT.0253,V253_DDR,25.8041,0.0080,12.0055,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-2.6492,-0.9965,-15.4434,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,11.0736,-0.2381,-2.4789,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,11.0736,-0.2381,-2.4789,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,11.0736,-0.2381,-2.4789,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,11.0736,-0.2381,-2.4789,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,25.5903,0.0007,11.7989,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,25.5903,0.0007,11.7989,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHUB,KCPLHUB_H,2.7152,-0.5602,-10.5153,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHUB17,KCPLHUB17_H,1.5020,-0.6211,-11.6676,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHUB18,KCPLHUB18_H,0.8332,-0.6263,-12.3311,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHUB19,KCPLHUB19_H,0.6906,-0.5991,-12.5011,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHUB20,KCPLHUB20_H,0.1052,-0.6459,-13.0396,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHUB21,KCPLHUB21_H,-0.3106,-0.6302,-13.4710,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHUB22,KCPLHUB22_H,0.6826,-0.6267,-12.4814,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHUB23,KCPLHUB23_H,0.2972,-0.6426,-12.8509,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLHUB24,KCPLHUB24_H,-0.5782,-0.6619,-13.7070,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,-1.2975,-0.1451,-14.9431,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,-1.2975,-0.1451,-14.9431,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,7.0643,-0.4551,-6.2713,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,7.0643,-0.4551,-6.2713,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,25.5857,0.0046,11.7904,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,25.5848,0.0038,11.7904,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,25.5119,0.0454,11.6758,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,25.5119,0.0454,11.6758,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,25.5119,0.0454,11.6758,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,25.5119,0.0454,11.6758,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,25.5119,0.0454,11.6758,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,25.5119,0.0454,11.6758,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,25.5119,0.0454,11.6758,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,25.5119,0.0454,11.6758,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,4.0874,-0.2586,-9.4447,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,21.6973,0.0106,7.8960,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KCPL_KCPL,KCPL_LA,21.7440,-0.0060,7.9594,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KENN,KENN_LA,20.0383,0.3880,5.8596,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KEP2_SECI,KEP2_SECI_LA,-15.1105,-0.8375,-28.0637,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KERR_1,GRDAKERR_HYDUN1_RA,41.3230,0.1836,27.3488,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KERR_2,GRDAKERR_HYDUN2_RA,41.1861,0.1854,27.2100,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KERR_3,GRDAKERR_HYDUN3_RA,41.1861,0.1854,27.2100,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KERR_4,GRDAKERR_HYDUN4_RA,41.3230,0.1836,27.3488,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,11.0736,-0.2382,-2.4789,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,11.0736,-0.2382,-2.4789,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,12.6750,-0.1579,-0.9577,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,12.6750,-0.1579,-0.9577,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,8.9691,-0.2334,-4.5882,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,7.0835,-0.2103,-6.4968,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,7.0835,-0.2103,-6.4968,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-13.6526,-0.9307,-26.5126,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-13.6526,-0.9307,-26.5126,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-13.6526,-0.9307,-26.5126,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-9.3955,-0.8373,-22.3489,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-9.3955,-0.8373,-22.3489,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-13.7683,-0.9611,-26.5978,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-10.0932,-0.8383,-23.0456,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-6.3362,-0.5147,-19.6122,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,56.4923,-0.0839,42.7856,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,56.4923,-0.0839,42.7856,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-3.3912,-0.4652,-16.7167,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-3.3912,-0.4652,-16.7167,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-3.3912,-0.4652,-16.7167,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-11.2919,-1.0562,-24.0263,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-9.2240,-1.2345,-21.7802,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,2.3761,-0.5529,-10.8617,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-9.8200,-0.0598,-23.5509,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LAFA,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LAM345,LAM345,-14.2203,-1.1159,-26.8951,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LEPA,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,3.1622,-0.5852,-10.0433,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_LES,LES_LA,3.1149,-0.5933,-10.0825,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,3.1939,-0.6003,-9.9965,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,2.9901,-0.6357,-10.1649,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,2.9901,-0.6357,-10.1649,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,2.9901,-0.6357,-10.1649,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,3.1943,-0.5999,-9.9965,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,3.1939,-0.6003,-9.9965,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_WAVERLY,LES_WAVERLY_H,3.0854,-0.6161,-10.0892,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,3.5932,-0.5745,-9.6230,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,3.5932,-0.5745,-9.6230,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,LGEE,LGEE,20.3536,0.1347,6.4283,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MALDEN,MALDEN_LA,20.2028,0.3669,6.0452,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MCWEST,MCWEST,9.9187,-0.2895,-3.5824,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MDU,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-1.1818,-0.6908,-14.2817,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,0.5149,-0.3278,-12.9479,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,3.5303,0.0733,-10.3337,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MEAN_NPPD,NPPD_MEAN_LA,-0.2716,-1.0247,-13.0376,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MEC,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MHEB,MHEB,9.0248,-0.2063,-4.5596,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-7.3651,-1.1749,-19.9808,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-11.4550,-1.2789,-23.9668,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-7.3651,-1.1749,-19.9808,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-7.3651,-1.1749,-19.9808,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-11.4550,-1.2789,-23.9668,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-15.6231,-0.6476,-28.7661,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MISO,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-14.8551,-0.7410,-27.9048,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-14.8551,-0.7410,-27.9048,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-4.7306,-0.7740,-17.7473,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-15.8700,-1.2050,-28.4557,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-10.8080,-1.0814,-23.5173,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-16.5378,-1.0555,-29.2730,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-15.1701,-0.8809,-28.0798,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-16.6706,-0.9886,-29.4726,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-14.8557,-0.8184,-27.8280,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-14.8557,-0.8184,-27.8280,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-14.8557,-0.8184,-27.8280,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-14.8557,-0.8184,-27.8280,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-14.8557,-0.8184,-27.8280,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,16.9301,-0.1133,3.2528,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,21.3402,0.1940,7.3556,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,21.3402,0.1940,7.3556,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,19.2431,0.0531,5.3994,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,26.6814,0.4000,12.4908,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MOWR,AECI,28.7597,0.1480,14.8210,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,21.1851,0.0453,7.3491,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,21.8309,0.2045,7.8358,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-4.4925,-0.8582,-17.4249,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-9.6233,-0.5083,-22.9057,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-22.4978,-1.0187,-35.2698,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-4.4447,-0.8105,-17.4249,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,11.4276,-0.0870,-2.2761,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,11.4276,-0.0870,-2.2761,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,11.4279,-0.0867,-2.2761,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,11.4279,-0.0867,-2.2761,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,1.4719,-0.1303,-12.1884,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,1.4719,-0.1303,-12.1884,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,1.4719,-0.1303,-12.1884,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,1.4281,-0.1742,-12.1884,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,1.4719,-0.1303,-12.1884,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,1.4719,-0.1303,-12.1884,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,1.4719,-0.1303,-12.1884,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,24.5346,0.3244,10.4195,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,15.5462,-0.0840,1.8396,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,10.8659,-0.1302,-2.7946,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,10.8660,-0.1301,-2.7946,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,10.8660,-0.1301,-2.7946,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,22.3627,-0.0044,8.5764,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,22.3627,-0.0044,8.5764,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MPS_MPS,MPS_LA,21.6120,0.0409,7.7804,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MSTNG,SPSMSTNGPLT1,23.3418,0.9864,8.5647,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MSTNG4,SPSMSTNGUN4_RA,23.2991,0.9437,8.5647,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MSTNG5,SPSMSTNGUN5_RA,23.3418,0.9864,8.5647,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,23.3418,0.9864,8.5647,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NBSO,PJM,18.2335,0.0290,4.4139,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,0.8931,-0.8791,-12.0185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,0.8927,-0.8794,-12.0185,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,-16.4782,-1.1932,-29.0756,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NHC1,VACS,25.0079,0.3864,10.8307,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,3.3243,-0.5176,-9.9488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,3.3243,-0.5176,-9.9488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,3.3243,-0.5176,-9.9488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-0.6372,-1.2918,-13.1361,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,0.4504,-1.2821,-12.0582,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,1.8475,-0.8772,-11.0659,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,0.1381,-0.8216,-12.8310,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,0.4504,-1.2821,-12.0582,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.HUB.PY2018,NPPDPY18_H,-0.3099,-0.9835,-13.1171,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,-0.2017,-0.9769,-13.0155,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,-0.2485,-0.9743,-13.0648,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,-0.1626,-0.9629,-12.9904,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-1.1856,-0.8660,-14.1103,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-1.4042,-1.0400,-14.1549,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-1.4042,-1.0400,-14.1549,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-3.0431,-1.0509,-15.7829,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-1.1856,-0.8660,-14.1103,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,5.3429,-1.5408,-6.9070,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,-0.0931,-1.4074,-12.4764,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-3.9922,-0.8829,-16.9000,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,-0.0931,-1.4074,-12.4764,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,0.9797,-1.3239,-11.4871,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,-0.4923,-1.2693,-13.0137,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,2.5618,-0.5181,-10.7108,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,0.4504,-1.2821,-12.0582,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-3.5778,-0.9368,-16.4317,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-1.4042,-1.0400,-14.1549,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-1.4042,-1.0400,-14.1549,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,-0.6867,-0.8593,-13.6180,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,-0.7482,-0.8674,-13.6714,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,-0.7482,-0.8674,-13.6714,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,-0.0146,-0.6565,-13.1488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-5.8878,-0.5449,-19.1336,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,0.7095,-1.0893,-11.9919,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-0.4199,-1.1389,-13.0716,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-11.0066,-0.4698,-24.3275,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-13.3600,-0.4927,-26.6580,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.NELI.DDR,NELI_DDR,-0.7968,-0.9975,-13.5900,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.NPPM.1058,SH1058_DDR,10.1667,-0.6146,-3.0093,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,0.0401,-0.7517,-12.9989,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,0.4504,-1.2821,-12.0582,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,1.8475,-0.8772,-11.0659,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-1.1856,-0.8660,-14.1103,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.TECH.1,KEARNE_DDR,0.3972,-0.6220,-12.7715,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,1.7862,-1.6220,-10.3825,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,1.7862,-1.6220,-10.3825,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-1.3007,-0.9509,-14.1405,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD.VOLT.0236,V236_DDR,1.8089,-0.5483,-11.4334,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD2017HUB,NPPD2017HUB_H,-0.2898,-0.9801,-13.1004,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,8.7726,-0.9048,-4.1132,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-0.6372,-1.2918,-13.1361,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,-0.1327,-1.6182,-12.3051,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,-0.1327,-1.6182,-12.3051,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,1.9359,-0.5723,-11.2824,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,1.8202,-0.5370,-11.4334,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-1.4111,-0.8352,-14.3666,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,-0.6045,-0.8848,-13.5104,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,9.9095,-0.8719,-3.0093,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,9.9095,-0.8719,-3.0093,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,9.9095,-0.8719,-3.0093,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,1.2055,-0.9242,-11.6610,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,1.6728,-0.8289,-11.2890,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,1.0736,-0.8323,-11.8847,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,0.0378,-1.6736,-12.0793,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,0.1100,-1.6014,-12.0793,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-2.1426,-1.0720,-14.8613,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-2.3574,-1.0772,-15.0709,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,1.9214,-0.8968,-10.9725,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,1.9090,-0.9092,-10.9725,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,1.9090,-0.9092,-10.9725,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,1.8758,-0.8804,-11.0345,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,5.3429,-1.5408,-6.9070,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,1.8125,-0.8841,-11.0941,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,2.4919,-0.7099,-10.5889,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,1.2211,-0.8983,-11.6713,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,1.2130,-0.9048,-11.6729,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,1.2177,-0.8985,-11.6745,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,1.2177,-0.8985,-11.6745,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,1.2055,-0.9242,-11.6610,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,1.1811,-0.9486,-11.6610,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,0.3423,-0.9873,-12.4611,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,1.3751,-0.7149,-11.7006,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-2.2468,-1.0398,-14.9977,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,1.0819,-1.5061,-11.2027,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-4.2870,-0.9333,-17.1444,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,10.3500,-0.4314,-3.0093,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-0.7968,-0.9975,-13.5900,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-1.9120,-1.0579,-14.6448,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-1.9120,-1.0579,-14.6448,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_NPPD,NPPD_LA,2.9938,-0.8005,-9.9963,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,2.4919,-0.7099,-10.5889,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,2.4919,-0.7099,-10.5889,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,-0.1047,-0.8288,-13.0666,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,-1.0669,-1.0101,-13.8475,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NSB,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NSP,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,NSSO,PJM,18.2335,0.0290,4.4139,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,NYIS,PJM,18.2335,0.0290,4.4139,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-18.5339,-1.2352,-31.0894,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-22.9961,-0.9673,-35.8195,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-26.7558,-0.8962,-39.6502,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-26.7558,-0.8962,-39.6502,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-17.6580,-1.4020,-30.0467,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-31.7573,-1.0627,-44.4853,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-95.1744,-0.5323,-108.4327,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-45.8103,-0.9865,-58.6145,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-23.4786,-0.9210,-36.3482,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-22.4952,-1.0034,-35.2824,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-3.8394,-0.3371,-17.2929,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-23.4786,-0.9210,-36.3482,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-17.9283,-1.3737,-30.3453,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-15.6231,-0.6476,-28.7661,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-18.8608,-1.2075,-31.4439,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,1.6373,-0.0205,-12.1329,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-22.4952,-1.0034,-35.2824,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-20.8370,-0.8607,-33.7670,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-14.0000,-0.8940,-26.8967,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-15.9000,-0.6880,-29.0027,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-31.3988,-0.0273,-45.1622,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-15.6231,-0.6476,-28.7661,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-15.6231,-0.6476,-28.7661,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-22.4952,-1.0034,-35.2824,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-14.4105,-0.5922,-27.6090,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.NUEN.LAM1,LAM1_DDR,35.0210,0.9907,20.2396,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-3.8381,-0.3358,-17.2929,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-3.8381,-0.3358,-17.2929,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-14.6994,-0.5403,-27.9498,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-5.7666,-0.3483,-19.2089,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-5.7666,-0.3483,-19.2089,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-5.7666,-0.3483,-19.2089,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-1.2509,-0.2892,-14.7524,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-1.2509,-0.2892,-14.7524,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-5.7666,-0.3483,-19.2089,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-5.7666,-0.3483,-19.2089,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-22.4952,-1.0034,-35.2824,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,24.3016,0.5456,9.9653,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-17.9283,-1.3737,-30.3453,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-23.0050,-0.2788,-36.5169,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-20.8370,-0.8607,-33.7670,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,31.6166,0.6536,17.1724,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-20.0488,-0.6744,-33.1651,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-20.0488,-0.6744,-33.1651,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-20.0488,-0.6744,-33.1651,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-20.0488,-0.6744,-33.1651,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-25.9400,-1.4087,-38.3220,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-25.8148,-0.8829,-38.7226,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-22.9961,-0.9673,-35.8195,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-28.7313,-0.8414,-41.6805,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-28.7313,-0.8414,-41.6805,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-22.9737,-0.0032,-36.7612,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-17.7556,-0.7544,-30.7919,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-17.7556,-0.7544,-30.7919,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-17.7556,-0.7544,-30.7919,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0033,FOSTER_DDR,3.9981,-0.2423,-9.5503,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,21.0475,0.2853,6.9715,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0035,TARBY_DDR,34.8523,0.7995,20.2621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,21.0475,0.2853,6.9715,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,19.3189,0.1537,5.3746,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,19.3189,0.1537,5.3746,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-26.4220,-0.0810,-40.1317,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0040,TROSPER_DDR,6.6901,-0.2258,-6.8748,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,6.5637,-0.2283,-6.9986,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,32.8699,0.7703,18.3089,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0115,V115_DDR,-3.0148,-0.3207,-16.4848,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0116,V116_DDR,10.9400,0.0948,-2.9455,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0118,V118_DDR,-1.1075,0.0692,-14.9674,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0125,V125_DDR,33.6189,0.8741,18.9541,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0126,V126_DDR,35.2524,0.4300,21.0317,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0129,V129_DDR,-4.6934,-0.5111,-17.9729,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,26.0000,-0.2991,12.5084,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0134,V134_DDR,36.5507,0.5331,22.2269,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0138,V138_DDR,34.4218,0.3714,20.2598,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,20.9427,-0.2357,7.3877,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0143,V143_DDR,26.2044,0.2168,12.1969,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0149,V149_DDR,-13.5292,-0.5900,-26.7299,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0150,V150_DDR,-13.4845,-0.6181,-26.6571,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0155,V155_DDR,33.7360,0.3093,19.6360,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0156,V156_DDR,26.0000,-0.2991,12.5084,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0166,V166_DDR,35.1135,0.8069,20.5159,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,20.3512,-0.2412,6.8018,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-13.4845,-0.6181,-26.6571,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0170,V170_DDR,-14.8478,-0.5367,-28.1018,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-20.5406,-0.5789,-33.7524,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0176,V176_DDR,-13.4845,-0.6181,-26.6571,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0177,V177_DDR,-21.9563,-1.2087,-34.5383,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,14.9625,-0.2419,1.4137,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-13.6982,-0.7362,-26.7526,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0195,V195_DDR,145.5740,1.0453,130.7381,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0197,V197_DDR,34.0795,0.4910,19.7978,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0198,V198_DDR,35.1135,0.8069,20.5159,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0208,V208_DDR,145.7800,1.0672,130.9221,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0209,V209_DDR,145.7800,1.0672,130.9221,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,34.8154,0.3669,20.6578,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0216,V216_DDR,6.5311,-0.2296,-7.0300,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0219,V219_DDR,33.7360,0.3093,19.6360,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0220,V220_DDR,-13.4845,-0.6181,-26.6571,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0224,V224_DDR,-3.6368,-0.3137,-17.1138,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0225,V225_DDR,-3.6361,-0.3130,-17.1138,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0226,V226_DDR,-3.6368,-0.3137,-17.1138,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0227,V227_DDR,-3.6368,-0.3137,-17.1138,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0229,V229_DDR,-24.1443,-0.0339,-37.9011,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0231,V231_DDR,0.6447,0.1681,-13.3140,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0238,V238_DDR,-28.3041,-1.0540,-41.0408,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.VOLT.0242,V242_DDR,34.0272,0.3394,19.8972,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-20.2235,-1.5167,-32.4975,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-15.6231,-0.6476,-28.7661,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-23.4702,-0.9161,-36.3447,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-18.8483,-1.1950,-31.4439,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-20.2235,-1.5167,-32.4975,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-19.2360,-1.2132,-31.8135,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-51.1891,-0.9206,-64.0592,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEHL7,OKGEHL7_H,14.9835,-0.2177,1.4105,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEHL8,OKGEHSL1UN8_RA,14.9835,-0.2177,1.4105,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEHL910,OKGEHSL1PLT2,14.9835,-0.2177,1.4105,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-19.0147,-1.2188,-31.5866,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEMCC,OKGEMCCLAIPLT1,-5.2745,-0.4231,-18.6421,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,30.7296,0.2464,16.6926,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,30.7296,0.2464,16.6926,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,30.7296,0.2464,16.6926,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,10.5067,-0.4170,-2.8669,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,10.5067,-0.4170,-2.8669,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,10.5067,-0.4170,-2.8669,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,10.5067,-0.4170,-2.8669,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGESM1,OKGESEMINOLEUN1_RA,4.6599,-0.1423,-8.9884,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGESM2,OKGESEMINOLEUN2_RA,5.1618,-0.1735,-8.4553,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGESM3,OKGESEMINOLEUN3_RA,5.1618,-0.1735,-8.4553,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGESO1,OKGESONR1UN1_RA,-52.8200,-0.7579,-65.8527,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGESO2,OKGESONR1UN2_RA,-28.7313,-0.8414,-41.6805,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-19.0147,-1.2188,-31.5866,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-18.1941,-1.1138,-30.8709,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGETINK5A,OKGETINK5UN1_RA,5.4210,-0.2451,-8.1245,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGETINK5B,OKGETINK5UN2_RA,5.4210,-0.2451,-8.1245,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-18.3681,-1.0116,-31.1472,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-22.9961,-0.9673,-35.8195,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,32.4720,0.9760,17.7054,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-15.6231,-0.6476,-28.7661,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE_OKGE,OKGE_LA,8.9904,-0.0741,-4.7263,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-23.0050,-0.2788,-36.5169,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-18.4157,-1.0592,-31.1472,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMLP,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,41.5368,0.1471,27.5990,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,32.6749,0.9092,17.9750,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-3.7721,-0.2998,-17.2630,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-95.0566,-0.4146,-108.4327,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-15.5065,-0.8617,-28.4354,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-23.4786,-0.9210,-36.3482,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-19.9263,-1.0953,-32.6217,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-9.3641,-1.2287,-21.9260,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,183.2556,0.1494,169.3155,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-95.0946,-0.4526,-108.4327,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-95.0946,-0.4526,-108.4327,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_SPP,OMPA_SPP_LA,-8.7512,-0.4586,-22.0833,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-20.2235,-1.5167,-32.4975,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,36.4356,0.1320,22.5129,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,36.4356,0.1320,22.5129,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,36.4356,0.1320,22.5129,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,36.4356,0.1320,22.5129,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,ONT,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,3.2254,-0.5272,-10.0380,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,3.2254,-0.5272,-10.0380,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,3.2254,-0.5272,-10.0380,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,3.2254,-0.5272,-10.0380,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,3.2254,-0.5272,-10.0380,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,3.2254,-0.5272,-10.0380,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,3.2254,-0.5272,-10.0380,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,3.2254,-0.5272,-10.0380,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,3.2254,-0.5272,-10.0380,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,3.3139,-0.5035,-9.9733,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,3.3243,-0.5176,-9.9488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,3.2357,-0.4946,-10.0603,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,3.2372,-0.4912,-10.0623,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,3.2372,-0.4912,-10.0623,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD_GLDN,OPPD_GLDN_LA,3.2025,-0.5209,-10.0673,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,3.2745,-0.5147,-10.0015,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,5.3429,-1.5408,-6.9070,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,1.8183,-0.6554,-11.3170,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,3.3238,-0.5170,-9.9499,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD_OPPD,OPPD_LA,3.2745,-0.4923,-10.0239,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,3.2577,-0.4749,-10.0581,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,3.2512,-0.4797,-10.0598,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OTP,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,OVEC,OVEC,19.5455,0.0949,5.6599,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PARAGOULD,PARAGOULD_LA,19.7982,0.4215,5.5861,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,41.2387,0.0849,27.3631,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,41.2387,0.0849,27.3631,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,41.2387,0.0849,27.3631,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,40.8236,0.1360,26.8969,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,40.8236,0.1360,26.8969,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,40.8236,0.1360,26.8969,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PIGGOTT,PIGGOTT_LA,20.0971,0.3805,5.9260,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,PJM,PJM,18.2335,0.0290,4.4139,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,PLUM,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,POPLARBLUFF,POPLARBLUFF_LA,21.3824,0.3170,7.2748,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,9.9870,-0.4457,-3.3580,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,9.9870,-0.4457,-3.3580,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,9.4730,-0.4362,-3.8814,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,9.4730,-0.4362,-3.8814,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,9.7213,0.4709,-4.5402,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,9.7213,0.4709,-4.5402,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,9.8479,-0.2994,-3.6434,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,11.7608,-0.8520,-1.1779,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-8.6723,-0.6221,-21.8409,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,91.8868,0.1314,77.9647,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,3.6773,-0.0582,-10.0552,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-3.3505,0.0468,-17.1880,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,43.3838,0.4612,29.1319,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,36.7523,0.4248,22.5368,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,7.1355,-0.5585,-6.0967,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,9.2475,-0.2217,-4.3214,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,5.5151,-0.8240,-7.4516,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,21.5167,0.7708,6.9552,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,8.9036,-0.1069,-4.7802,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,6.6068,-0.4453,-6.7386,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,PUPP,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,RCEAST,RCEAST,-0.7743,-1.4371,-13.1279,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SALINA_1,GRDASALINA1UN1_RA,41.3244,0.1849,27.3488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SALINA_2,GRDASALINA1UN2_RA,41.3244,0.1849,27.3488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SALINA_3,GRDASALINA1UN3_RA,41.3244,0.1849,27.3488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SALINA_4,GRDASALINA1UN4_RA,41.3244,0.1849,27.3488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SALINA_5,GRDASALINA1UN5_RA,41.3244,0.1849,27.3488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SALINA_6,GRDASALINA1UN6_RA,41.3244,0.1849,27.3488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SARPY_1,OPPDSARPYUN1_RA,3.2675,-0.5017,-10.0214,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SARPY_2,OPPDSARPYUN2_RA,3.2847,-0.4775,-10.0285,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SARPY_3,OPPDSARPYUN3_RA,3.2701,-0.5317,-9.9889,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SARPY_4,OPPDSARPYUN4_RA,3.2701,-0.5317,-9.9889,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SARPY_5,OPPDSARPYUN5_RA,3.2701,-0.5317,-9.9889,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SC,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SCEG,VACS,25.0079,0.3864,10.8307,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,SCSE,SCSE,-1.9878,-0.9950,-14.7835,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SEC,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-18.1208,-1.2851,-30.6264,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-18.1208,-1.2851,-30.6264,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-18.1208,-1.2851,-30.6264,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-13.5183,-0.6288,-26.6802,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-18.1208,-1.2851,-30.6264,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-15.3014,-1.2191,-27.8729,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-15.1681,-1.2906,-27.6681,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-15.1681,-1.2906,-27.6681,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-14.8573,-0.8199,-27.8280,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-20.1686,-1.1312,-32.8280,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-9.4465,-0.8883,-22.3489,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-14.1492,-0.7405,-27.1994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-9.3149,-1.0407,-22.0649,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-17.4599,-1.2853,-29.9652,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-9.2899,-1.0288,-22.0518,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-15.9633,-1.4578,-28.2962,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-15.5060,-0.8411,-28.4556,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-13.7788,-0.9963,-26.5732,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-13.7788,-0.9963,-26.5732,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-13.7788,-0.9963,-26.5732,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-13.7788,-0.9963,-26.5732,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-14.0220,-1.0708,-26.7419,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-15.3014,-1.2191,-27.8729,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI_SECI,SECI_LA,-13.5292,-0.8622,-26.4576,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-9.1000,-1.0617,-21.8290,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-9.1000,-1.0617,-21.8290,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-14.8573,-0.8199,-27.8280,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SEHA,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-18.4157,-1.0592,-31.1472,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SERU,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SETH,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SGE,SGE,-1.5876,-0.9691,-14.4091,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SMEP,MISO,17.6797,0.0705,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SOCO,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPA,SPA,31.1519,0.4777,16.8835,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPC,SPC,8.9798,0.1240,-4.9349,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPPNORTH_HUB,SPPNORTH_H,3.0986,-0.6302,-10.0618,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-2.1218,-0.5352,-15.3773,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,30.6907,0.3957,16.5043,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,30.6907,0.3957,16.5043,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,30.1739,0.3619,16.0214,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,30.1739,0.3619,16.0214,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_NIXA,SPRM_NIXA_LA,30.8970,0.4104,16.6959,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_SPRM,SPRM_LA,30.7721,0.4366,16.5447,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,30.8479,0.3217,16.7355,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,30.8479,0.3217,16.7355,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,30.8117,0.2855,16.7355,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,30.8479,0.3217,16.7355,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,-3.2212,0.1580,-17.1698,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,-13.1262,-0.2920,-26.6248,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,-16.1616,-0.8583,-29.0940,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,-16.1616,-0.8583,-29.0940,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,-24.4100,-0.8531,-37.3476,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,6.4133,0.0128,-7.3902,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,-7.5687,-0.9557,-20.4037,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,23.2347,0.0670,9.3771,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,-27.1160,-0.2403,-40.6664,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,30.8680,0.9484,16.1289,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,31.6183,0.9457,16.8819,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,31.6183,0.9457,16.8819,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,30.8680,0.9484,16.1289,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,-16.0115,-0.7118,-29.0904,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,-13.1262,-0.2920,-26.6248,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-16.0317,-0.7882,-29.0342,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-16.9840,-1.3804,-29.3943,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-16.0890,-0.7193,-29.1604,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-15.7606,-0.4888,-29.0624,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-16.0845,-0.7925,-29.0827,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-17.2702,-1.4121,-29.6488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-17.2702,-1.4121,-29.6488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-17.2702,-1.4121,-29.6488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-17.2702,-1.4121,-29.6488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GRID.WRAB,WRAB_DDR,-15.6576,-0.4309,-29.0174,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-17.2702,-1.4121,-29.6488,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,-22.1891,-0.2536,-35.7262,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,-22.1891,-0.2536,-35.7262,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,-21.8741,-0.2055,-35.4593,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,-21.8741,-0.2055,-35.4593,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,-21.8741,-0.2055,-35.4593,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,-22.1891,-0.2536,-35.7262,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,-16.0568,-0.8496,-28.9979,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,-16.0569,-0.8496,-28.9980,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,-16.0553,-0.8496,-28.9964,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,-16.4782,-1.1932,-29.0756,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,31.3003,0.9140,16.5956,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,-26.9099,-0.2460,-40.4545,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,-26.9099,-0.2460,-40.4545,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,-26.9099,-0.2460,-40.4545,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,-26.9099,-0.2460,-40.4545,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,27.6746,1.0845,12.7994,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,30.8000,0.9252,16.0842,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,30.8000,0.9252,16.0842,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-18.3725,-1.0159,-31.1472,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,-16.0392,-0.8348,-28.9951,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,-16.0392,-0.8348,-28.9951,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,-16.0694,-0.8446,-29.0155,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,-15.6576,-0.4309,-29.0174,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-16.7236,-1.1678,-29.3465,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-16.2381,-0.8838,-29.1450,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-17.6580,-1.4020,-30.0467,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,-15.8387,-0.6342,-28.9951,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.PLANTX1,SPS.PLANTX1_H,-10.8881,-0.0340,-24.6448,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.PLANTX2,SPS.PLANTX2_H,-10.8881,-0.0340,-24.6448,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,-9.6767,-0.0298,-23.4376,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,-25.1283,-0.6387,-38.2803,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-16.9927,-1.2786,-29.5048,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,-7.3628,-0.7498,-20.4037,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,-25.1079,-0.6182,-38.2803,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,-16.0162,-0.7165,-29.0904,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,-1.3793,0.0980,-15.2679,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,23.6502,0.4824,9.3771,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,-1.3793,0.0980,-15.2679,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,-0.3563,0.3518,-14.4988,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-16.7268,-0.9303,-29.5872,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,30.9839,1.5984,15.5948,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,31.0548,1.6693,15.5948,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,30.8208,1.3041,15.7261,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,30.8012,0.9433,16.0673,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,29.1862,1.2921,14.1034,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-14.2203,-1.1159,-26.8951,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,-15.7151,-0.4903,-29.0155,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,-7.6673,0.0299,-21.4878,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,-7.6673,0.0299,-21.4878,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,-1.3793,0.0980,-15.2679,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,-27.6975,-0.1705,-41.3177,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,37.1400,1.3301,22.0192,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,-6.0613,0.6893,-20.5413,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,-5.7267,0.2979,-19.8153,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,-17.2232,-0.2572,-30.7567,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,30.9839,1.5984,15.5948,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,30.3251,1.8366,14.6978,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,30.1257,1.6372,14.6978,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,-24.9821,-0.4925,-38.2803,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,-6.2375,0.3869,-20.4151,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-16.9001,-1.2170,-29.4738,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-16.9233,-1.2406,-29.4734,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0163,V163_DDR,-15.7151,-0.6460,-28.8598,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0168,V168_DDR,-18.1667,-0.5758,-31.3816,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0180,V180_DDR,30.3251,1.8366,14.6978,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0181,V181_DDR,-16.7626,-1.0623,-29.4910,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0182,V182_DDR,29.5346,1.4576,14.2863,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0199,V199_DDR,29.5358,1.2437,14.5014,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0200,V200_DDR,30.8345,1.2756,15.7682,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.VOLT.0235,V235_DDR,-16.7236,-1.1678,-29.3465,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,-7.5687,-0.9557,-20.4037,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,23.2347,0.0670,9.3771,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,-15.1756,-0.9128,-28.0535,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,-15.8344,-0.7512,-28.8739,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS_SPS,SPS_LA,13.0508,0.6966,-1.4365,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,20.4416,0.4274,6.2236,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,SSCN_NPPD,SSCN_NPPD_LA,0.0866,-0.7725,-12.9316,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,20.7851,0.3016,6.6928,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,20.7851,0.3016,6.6928,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,TAL,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,TEC,SOUC,25.2193,0.4200,11.0086,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,1.0819,-1.5061,-11.2027,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,TVA,TVA,24.7800,0.3511,10.6382,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,UCUHUB,UCUHUB_H,-2.3450,-0.3994,-15.7363,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,UCUHUB17,UCUHUB17_H,-9.0232,-0.7233,-22.0906,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,UCUHUB18,UCUHUB18_H,-6.3983,-0.6331,-19.5558,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,UCUHUB19,UCUHUB19_H,-9.4177,-0.6715,-22.5369,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,UCUHUB20,UCUHUB20_H,-8.7641,-0.6468,-21.9079,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,UCUHUB21,UCUHUB21_H,-10.2539,-0.7229,-23.3217,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,UCUHUB22,UCUHUB22_H,-10.4685,-0.7596,-23.4996,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,UCUHUB23,UCUHUB23_H,-10.8255,-0.7657,-23.8505,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,UCUHUB24,UCUHUB24_H,-7.6489,-0.6683,-20.7713,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,9.0862,0.2341,-4.9385,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,9.0862,0.2341,-4.9385,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,7.7146,-0.6482,-5.4279,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,7.7146,-0.6482,-5.4279,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,8.2643,-0.6487,-4.8777,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,9.2657,-0.5322,-3.9928,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,9.2657,-0.5322,-3.9928,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,9.0862,0.2341,-4.9385,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,8.3452,-0.6191,-4.8264,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,8.7423,-0.1533,-4.8950,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,6.2078,-0.5238,-7.0590,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,3.3674,-1.8053,-8.6180,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,9.2845,0.1574,-4.6636,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,9.2845,0.1574,-4.6636,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,5.8615,-1.6430,-6.2861,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,6.6154,-0.7496,-6.4257,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,7.5628,-0.7647,-5.4631,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,5.4512,-0.8116,-7.5279,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,6.1769,-0.5364,-7.0773,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,6.3882,-0.8035,-6.5989,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,6.5518,-0.9528,-6.2861,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,6.5518,-0.9528,-6.2861,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,6.7798,-0.7077,-6.3031,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,3.0897,-1.9298,-8.7712,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,6.8247,0.0726,-7.0386,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,8.5730,-0.2765,-4.9412,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,8.5730,-0.2765,-4.9412,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,8.5730,-0.2765,-4.9412,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,8.6801,-0.1366,-4.9740,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,8.6801,-0.1366,-4.9740,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,8.6801,-0.1366,-4.9740,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,9.2543,0.3919,-4.9283,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,8.0015,-0.6327,-5.1564,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,8.0015,-0.6327,-5.1564,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-1.7885,-0.9836,-14.5956,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,5.3447,-0.6662,-7.7798,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,8.7768,-0.1856,-4.8282,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,3.2325,-0.8280,-9.7302,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,2.2461,-2.2799,-9.2647,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,6.7662,-0.8318,-6.1927,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,9.1527,0.2240,-4.8620,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,9.1527,0.2240,-4.8620,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,9.1519,0.2233,-4.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,9.1527,0.2240,-4.8620,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,8.9466,0.1037,-4.9478,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,8.9466,0.1037,-4.9478,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,8.9466,0.1037,-4.9478,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,8.9466,0.1037,-4.9478,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,8.9466,0.1037,-4.9478,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,8.9466,0.1037,-4.9478,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,8.9466,0.1037,-4.9478,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,3.0337,-1.4720,-9.2850,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,8.5233,-0.4153,-4.8521,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,4.1851,-0.6316,-8.9740,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,4.1851,-0.6316,-8.9740,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,2.3458,-0.9957,-10.4491,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,2.3458,-0.9957,-10.4491,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,8.1522,-0.4821,-5.1564,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,8.8903,-0.4458,-4.4546,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,5.6956,-0.9513,-7.1437,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,3.6364,-1.6954,-8.4589,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,7.5840,-0.4272,-5.7795,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,8.2643,-0.6487,-4.8777,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,8.2643,-0.6487,-4.8777,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,5.4512,-0.8116,-7.5279,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,-0.7613,-1.4929,-13.0590,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,5.7461,-1.0426,-7.0020,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,3.2035,-1.8160,-8.7712,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,6.5729,-0.8843,-6.3335,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.FSE,WAUE.FSE_H,1.9521,-1.0501,-10.7885,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,9.2186,-0.4193,-4.1528,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,9.2890,-0.4437,-4.0580,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,2.7437,-1.7871,-9.2599,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,3.2404,-1.7058,-8.8444,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,8.1942,-0.6316,-4.9648,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,8.2310,-0.6839,-4.8758,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-15.8300,-1.5322,-28.0885,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,3.3674,-1.8053,-8.6180,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-7.2500,-1.2368,-19.8039,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,5.6337,-0.6011,-7.5559,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,5.6339,-0.6009,-7.5559,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,5.6341,-0.6007,-7.5559,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,6.4703,-0.7618,-6.5585,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,-0.7613,-1.4929,-13.0590,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,7.1466,-0.3551,-6.2890,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,5.2578,-0.8674,-7.6655,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,6.7694,0.0173,-7.0386,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,6.3942,-0.0263,-7.3702,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,6.3434,-0.4666,-6.9807,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,9.1301,-0.3292,-4.3314,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,5.7670,-0.6653,-7.3584,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,5.6450,-0.9300,-7.2157,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,3.2325,-0.8280,-9.7302,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,10.0986,0.0318,-3.7238,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,5.4368,-0.8231,-7.5307,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,10.0046,0.0086,-3.7947,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,6.8431,-0.3604,-6.5872,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,3.5932,-0.5745,-9.6230,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NTWK,WAUE.NTWK_H,5.9664,-0.6540,-7.1703,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,7.3185,-0.0450,-6.4271,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,7.3185,-0.0450,-6.4271,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,3.2942,-1.8892,-8.6073,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,2.6267,-1.8171,-9.3468,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,7.1401,-0.6619,-5.9887,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,3.2942,-1.8892,-8.6073,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,8.9896,-0.3550,-4.4460,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,5.0034,-1.1883,-7.5990,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,3.2325,-0.8280,-9.7302,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,5.8313,-0.8892,-7.0702,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,4.0840,-2.1076,-7.5990,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,0.7450,-2.1955,-10.8502,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,1.3939,-2.1936,-10.2031,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,7.5883,-0.6784,-5.5240,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,2.0293,-1.7530,-10.0084,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,7.4294,-0.4504,-5.9109,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,4.0881,-1.5704,-8.1322,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,3.6364,-1.6954,-8.4589,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.VOLT.0152,V152_DDR,9.4183,0.5581,-4.9304,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE.VOLT.0172,V172_DDR,9.0258,0.1626,-4.9274,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_BEPM,WAUE_BEPM_LA,7.7930,-0.1857,-5.8120,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,7.1362,-0.3935,-6.2609,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,6.3949,-0.0192,-7.3765,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_EWA,WAUE_EWA_LA,-1.0915,-1.4059,-13.4763,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,4.8450,-1.0536,-7.8922,13.7908\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_HMMU,WAUE_HMMU_LA,4.9848,-0.2352,-8.5706,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,9.2544,-0.3845,-4.1518,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_MECB,WAUE_MECB_LA,5.5031,-0.1836,-8.1039,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_MMPA,WAUE_MMPA_LA,8.9932,-0.0421,-4.7554,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_MRES,WAUE_MRES_LA,5.8385,-0.6477,-7.3044,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,9.1629,0.2931,-4.9208,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,9.2186,-0.4193,-4.1528,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,4.4926,-1.0595,-8.2385,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_OTP,WAUE_OTP_LA,10.3851,0.2282,-3.6337,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_OTPW,WAUE_OTPW_LA,17.0306,0.4774,2.7625,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM,WAUE_UGPM_LA,6.9105,-0.5845,-6.2957,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,7.5250,-0.3274,-5.9383,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,5.9187,-0.5786,-7.2934,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,4.7122,-0.9502,-8.1283,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,-1.0915,-1.4059,-13.4763,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,4.9848,-0.2352,-8.5706,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,4.7748,-1.0163,-7.9996,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,9.2186,-0.4193,-4.1528,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,8.9932,-0.0421,-4.7554,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,6.2413,-0.5698,-6.9796,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,4.4048,-1.1898,-8.1961,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,9.2342,0.2390,-4.7954,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-20.0447,-1.3276,-32.5078,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-21.0701,-1.2062,-33.6545,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,0.1395,-0.9012,-12.7499,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,98.7947,0.4802,84.5238,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,98.7947,0.4802,84.5238,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-12.5160,-1.7317,-24.5750,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,89.9241,0.5553,75.5781,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,79.5509,0.5292,65.2311,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,17.6171,-0.6864,4.5128,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,17.6171,-0.6864,4.5128,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,17.6171,-0.6864,4.5128,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,17.6171,-0.6864,4.5128,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,17.5819,-0.7216,4.5128,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,17.6171,-0.6864,4.5128,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,17.6171,-0.6864,4.5128,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,17.6171,-0.6864,4.5128,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,8.4797,-0.6421,-4.6689,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-17.6580,-1.4020,-30.0467,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-29.7711,-1.1660,-42.3958,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-20.6330,-1.2236,-33.2000,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,-7.4529,-0.8398,-20.4037,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_ENMC,WFEC_ENMC_LA,20.0098,0.9233,5.2958,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-22.4952,-1.0034,-35.2824,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,42.7421,0.4267,28.5248,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,28.6026,1.0214,13.7905,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-20.0447,-1.3276,-32.5078,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-20.0447,-1.3276,-32.5078,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-20.0447,-1.3276,-32.5078,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_OKGE,WFEC_OKGE_LA,2.3309,0.1181,-11.5779,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,44.0833,0.5855,29.7071,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-16.5079,-1.7573,-28.5413,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-11.5146,-1.8996,-23.4057,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_WFEC,WFEC_LA,17.4631,-0.1461,3.8185,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,28.6026,1.0214,13.7905,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-8.1016,-1.2043,-20.6880,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-12.4820,-1.0929,-25.1798,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-4.4950,-0.5684,-17.7173,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-4.4950,-0.5684,-17.7173,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-4.4950,-0.5684,-17.7173,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-4.4950,-0.5684,-17.7173,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-4.4950,-0.5684,-17.7173,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-4.4950,-0.5684,-17.7173,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-4.4950,-0.5684,-17.7173,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,11.9305,0.3080,-2.1682,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-6.2570,-0.7938,-19.2539,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-17.8685,-0.9675,-30.6917,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-17.8685,-0.9675,-30.6917,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-17.8685,-0.9675,-30.6917,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-19.3710,-1.1287,-32.0330,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-19.3710,-1.1287,-32.0330,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-11.2518,-0.8906,-24.1519,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-11.2518,-0.8906,-24.1519,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-11.2518,-0.8906,-24.1519,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-6.2570,-0.7938,-19.2539,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,-3.3400,-0.1553,-16.9754,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-9.5860,-0.7647,-22.6119,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-9.5860,-0.7647,-22.6119,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-9.5860,-0.7647,-22.6119,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-9.5860,-0.7647,-22.6119,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,-3.3400,-0.1553,-16.9754,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-16.4342,-1.2856,-28.9393,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-26.3975,-0.4603,-39.7279,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.JEC.1,WRJEFFUN10_RA,-4.7900,-0.5639,-18.0168,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.JEC.2,WRJEFFUN11_RA,-4.8406,-0.5680,-18.0633,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.JEC.3,WRJEFFUN12_RA,-4.8990,-0.6264,-18.0633,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-21.4096,-0.9240,-34.2763,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-22.4872,-1.0081,-35.2698,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-22.4872,-1.0081,-35.2698,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.LEC.4,WRLECUN26_RA,-8.5889,-0.1693,-22.2103,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.LEC.5,WRLECUN27_RA,-6.7794,-0.1457,-20.4244,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-8.5110,-0.7011,-21.6006,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-8.5110,-0.7011,-21.6006,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-8.5110,-0.7011,-21.6006,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-8.4694,-0.6735,-21.5865,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-9.1000,-1.0617,-21.8290,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-9.1000,-1.0617,-21.8290,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-9.1592,-0.9439,-22.0060,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-7.7342,-1.1522,-20.3727,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-7.7342,-1.1522,-20.3727,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-9.2308,-1.2413,-21.7802,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-9.1000,-1.0617,-21.8290,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-2.6725,-0.9478,-15.5154,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-6.9882,-0.9109,-19.8680,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-22.4924,-1.0133,-35.2698,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,79.8638,0.5291,65.5440,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-9.8865,-1.7865,-21.8906,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-4.4950,-0.5684,-17.7173,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-2.6618,-1.0238,-15.4287,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,-3.3400,-0.1553,-16.9754,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-6.2570,-0.7938,-19.2539,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-13.3320,-0.7431,-26.3795,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.THAYERLD,WR.THAYERLD_LA,22.4081,0.3635,8.2539,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-14.1913,-0.7296,-27.2524,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0106,V106_DDR,-13.2564,-0.6996,-26.3475,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-10.8151,-0.0417,-24.5640,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-7.1058,-0.6845,-20.2120,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-8.8748,-0.0568,-22.6087,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-8.8748,-0.0568,-22.6087,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-7.6323,-0.1043,-21.3186,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-12.8501,-0.5999,-26.0409,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0157,V157_DDR,-8.7547,-0.0718,-22.4736,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0158,V158_DDR,-8.8748,-0.0568,-22.6087,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-8.8748,-0.0568,-22.6087,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-13.4927,-0.7787,-26.5047,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0173,V173_DDR,-8.7099,-0.8084,-21.6922,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0174,V174_DDR,-13.2796,-0.7120,-26.3583,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0184,V184_DDR,-12.8684,-0.7974,-25.8617,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-13.4616,-0.7326,-26.5197,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0186,V186_DDR,-13.3930,-0.7769,-26.4068,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-13.0464,-0.7708,-26.0663,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-14.0262,-0.7002,-27.1167,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-8.4742,-0.5537,-21.7112,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-5.4501,-0.5035,-18.7373,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-4.9116,-0.5278,-18.1745,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-4.9116,-0.5278,-18.1745,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-5.4501,-0.5035,-18.7373,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0245,V245_DDR,-13.4703,-0.7336,-26.5274,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.VOLT.0248,V248_DDR,-13.2564,-0.6996,-26.3475,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-17.2534,-0.8734,-30.1707,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-4.0531,-0.2925,-17.5513,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.WOLF,WRWOLFUN15_RA,-3.7052,-1.0921,-16.4038,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-16.4342,-1.2856,-28.9393,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,11.8577,0.2352,-2.1682,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-17.8685,-0.9675,-30.6917,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-17.8685,-0.9675,-30.6917,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-17.8685,-0.9675,-30.6917,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-17.8685,-0.9675,-30.6917,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-15.6486,-0.6596,-28.7797,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-7.0551,-0.6874,-20.1583,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-14.6262,-0.7183,-27.6985,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-14.6262,-0.7183,-27.6985,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-14.6262,-0.7183,-27.6985,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-14.6262,-0.7183,-27.6985,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-5.8412,-0.4573,-19.1746,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-5.8412,-0.4573,-19.1746,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-5.8412,-0.4573,-19.1746,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-5.8412,-0.4573,-19.1746,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-5.8412,-0.4573,-19.1746,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-5.8412,-0.4573,-19.1746,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-29.9611,-0.6983,-43.0534,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-29.9611,-0.6983,-43.0534,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-32.8495,-0.6843,-45.9559,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-32.8495,-0.6843,-45.9559,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_MIDW,WR_MIDW_LA,-9.3655,-1.0353,-22.1209,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,28.7086,0.2140,14.7040,13.7906\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,18.2471,0.0650,4.3914,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-11.0203,-0.9489,-23.8621,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_SEG,WR_SEG_LA,11.6113,0.1376,-2.3170,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,WR_WR,WR_LA,-7.8226,-0.5167,-21.0966,13.7907\n03/19/2025 18:00:00,03/19/2025 23:00:00,YAD,VACS,25.0079,0.3864,10.8307,13.7908\n03/19/2025 19:00:00,03/20/2025 00:00:00,AEC,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,AECC_CSWS,CSWS_AECC_LA,38.3520,0.7993,18.1231,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,39.2812,0.4836,19.3679,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,36.3914,1.0861,15.8756,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,39.6787,0.2762,19.9729,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,37.3128,0.7946,17.0886,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,36.4572,0.4321,16.5955,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,38.2867,0.6075,18.2495,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,AECI,AECI,33.2299,0.0856,13.7146,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,AEPM_CSWS,CSWS_LA,37.6666,0.7945,17.4424,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,ALTW,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,AMRN,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,4.7803,-0.0168,-14.6326,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BBA,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BCA,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BEPM.ER01.DDR,ER01_DDR,-0.7335,-2.9186,-17.2446,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BEPM_ER01,BEPM_ER01_LA,-0.7335,-2.9186,-17.2446,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,-0.4420,-1.3527,-18.5190,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,-1.6072,-0.6473,-20.3896,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BEPM_UM01,BEPM_UM01_LA,20.4195,0.3376,0.6523,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,BLKW,BLKW,14.9735,0.9096,-5.3658,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-30.0000,-1.6131,-47.8166,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-30.0000,-1.6131,-47.8166,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,17.4242,-1.4089,-0.5966,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.9641,-1.5772,-47.8166,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BRAZ,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BUBA,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-16.6671,-1.4820,-34.6148,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-10.2908,-0.9616,-28.7589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-10.2908,-0.9616,-28.7589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-10.2908,-0.9616,-28.7589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-10.2908,-0.9616,-28.7589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-10.2908,-0.9616,-28.7589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-7.6283,-0.9698,-26.0881,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,4.9325,-0.9369,-13.5602,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,4.9325,-0.9369,-13.5602,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CLEC,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,37.9059,0.2580,18.2182,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,COWP,COWP_LA,30.4865,0.3274,10.7294,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,30.4865,0.3274,10.7294,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,30.4865,0.3274,10.7294,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CPLE,VACS,31.0505,0.4491,11.1717,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CPLW,VACS,31.0505,0.4491,11.1717,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,31.1431,0.6237,11.0897,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,31.1431,0.6237,11.0897,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,31.1431,0.6237,11.0897,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,31.1431,0.6237,11.0897,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CRTH_SPA,WRCRTH_SPA_LA,37.9600,-0.0186,18.5490,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,38.2272,1.9179,16.8796,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,1.8692,-0.6675,-16.8930,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,38.2867,0.6075,18.2495,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,39.6787,0.2762,19.9729,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,38.2197,1.9052,16.8848,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,37.9491,1.4125,17.1069,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,38.1657,1.7651,16.9709,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,38.1657,1.7651,16.9709,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,38.7343,0.3566,18.9480,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,38.7343,0.3566,18.9480,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,38.6112,0.2335,18.9480,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,38.6112,0.2335,18.9480,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,38.2867,0.6075,18.2495,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,41.5663,1.5543,20.5824,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,63.2821,-0.2077,44.0602,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,63.1039,-0.3860,44.0602,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,42.4725,0.0518,22.9911,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,36.6701,0.1765,17.0640,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,36.6701,0.1765,17.0640,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,36.6729,0.1765,17.0668,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,36.6729,0.1765,17.0668,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-16.3047,-0.8934,-34.8410,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,7.5007,-0.5016,-11.4274,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,44.7246,0.3941,24.9008,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-10.9533,-0.9797,-29.4033,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-10.8897,-0.9160,-29.4033,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,-9.3002,-0.4963,-28.2336,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.GRID.CDL1,CDL1_DDR,38.5761,0.4387,18.7077,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,0.6763,-0.7048,-18.0486,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,2.5832,-0.9032,-15.9432,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,38.5761,0.4387,18.7077,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.NUEN.CSI1,CSI1_DDR,42.9923,0.3215,23.2411,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.NUEN.CSI2,CSI2_DDR,43.0016,0.3308,23.2411,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,37.9098,0.2620,18.2182,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.NUEN.GAZA,GAZA_DDR,38.5761,0.4387,18.7077,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,92.4900,0.9991,72.0612,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.NUEN.T201,NT201_DDR,38.5411,0.2206,18.8909,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,-2.6201,-1.0474,-21.0024,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,-2.6201,-1.0474,-21.0024,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,38.2867,0.6075,18.2495,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,38.9618,2.0955,17.4367,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,-9.3002,-0.4963,-28.2336,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,-9.3002,-0.4963,-28.2336,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-11.7782,-0.8708,-30.3371,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-10.8897,-0.9160,-29.4033,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,37.4822,1.2669,16.7856,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,33.7884,0.0500,14.3087,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,33.5115,-0.2268,14.3087,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,33.5229,-0.2155,14.3087,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,18.1195,0.1444,-1.4545,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,18.1195,0.1444,-1.4545,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,38.0301,1.4010,17.1995,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,37.3910,0.2539,17.7075,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,37.9963,1.3913,17.1753,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,39.5593,2.6609,17.4688,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,43.1314,0.7472,22.9545,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,43.0016,0.3308,23.2411,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0057,OKMU_DDR,38.7150,0.4296,18.8558,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0060,LEHIGH_DDR,92.4900,0.9991,72.0612,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0086,WARRENM_DDR,37.3309,0.2578,17.6434,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,39.0971,1.9652,17.7022,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,52.6772,0.1899,33.0576,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0121,V121_DDR,38.0301,1.4010,17.1995,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0122,V122_DDR,50.7154,0.1757,31.1100,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0124,V124_DDR,75.0611,0.0943,55.5371,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0135,V135_DDR,38.7153,0.2594,19.0263,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0144,V144_DDR,8.2186,-0.4190,-10.7921,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0145,V145_DDR,8.5072,-0.5127,-10.4098,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,38.0910,1.4448,17.2165,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,38.7295,0.8705,18.4293,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0175,V175_DDR,37.9098,0.2620,18.2182,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,38.7295,0.8705,18.4293,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,38.8501,1.0033,18.4171,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,38.7153,0.2594,19.0263,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,39.2794,0.2391,19.6106,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,38.8980,0.2004,19.2679,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,58.3631,-0.0292,38.9626,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,36.7836,0.1627,17.1913,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,39.2794,0.2391,19.6106,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0211,V211_DDR,38.1897,1.6486,17.1115,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,53.7086,0.2002,34.0788,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0213,V213_DDR,38.4484,0.2477,18.7710,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0215,V215_DDR,52.0720,0.1856,32.4567,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0217,V217_DDR,53.7782,0.1814,34.1672,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0218,V218_DDR,57.8119,-0.0142,38.3964,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0228,V228_DDR,38.8061,0.2032,19.1732,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0232,V232_DDR,37.7697,0.2518,18.0883,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0233,V233_DDR,39.4073,0.2574,19.7203,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0240,V240_DDR,47.9112,0.1488,28.3328,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0244,V244_DDR,39.2794,0.2391,19.6106,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0246,MDT1_DDR,92.4900,0.9991,72.0612,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0249,V249_DDR,38.3746,0.2651,18.6799,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0250,V250_DDR,1.3314,-0.6083,-17.4900,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0251,V251_DDR,37.4197,0.2115,17.7785,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.VOLT.0252,V252_DDR,58.3631,-0.0292,38.9626,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-20.9086,-0.8973,-39.4410,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,14.5701,-1.1185,-3.7411,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-14.6728,-1.9979,-32.1046,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,37.7124,1.1309,17.1518,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-19.7581,-1.7370,-37.4507,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,5.1035,-0.5392,-13.7870,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,5.1035,-0.5392,-13.7870,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,5.1035,-0.5392,-13.7870,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,5.1035,-0.5392,-13.7870,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,5.1035,-0.5392,-13.7870,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,38.2867,0.6075,18.2495,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,37.2872,1.7895,16.0680,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,37.7429,0.2249,18.0883,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,37.6436,0.1256,18.0883,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,40.3222,0.5196,20.3730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,40.3222,0.5196,20.3730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWWELSH1,CSWSWELSHUN1_RA,38.3062,1.1064,17.7701,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWWELSH3,CSWSWELSHUN3_RA,38.3062,1.1064,17.7701,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWWILKES1,CSWSWILKESUN1_RA,38.5031,1.4063,17.6671,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWWILKES2,CSWSWILKESUN2_RA,38.5031,1.4063,17.6671,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,CSWWILKES3,CSWSWILKESUN3_RA,38.2527,1.3322,17.4908,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-10.8679,-0.8943,-29.4033,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,DENL,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,DERS,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,DOE,DOE,27.7141,0.2357,8.0487,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,13.5179,-0.2495,-5.6623,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,DPC,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,DUK,VACS,31.0505,0.4491,11.1717,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDDY,EDDY,79.8634,1.8556,58.5781,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,35.7377,-0.1364,16.4445,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-2.7547,-0.4331,-21.7512,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,41.3424,-0.3023,22.2150,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE.SLCC,EDESTL4391_PLT,37.6729,-0.1581,18.4013,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,37.5631,-0.0978,18.2313,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,23.8535,-0.4865,4.9103,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_EC_01,EDELAR3821UN1_RA,35.7377,-0.1364,16.4445,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_EC_02,EDELAR3821UN2_RA,35.7377,-0.1364,16.4445,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_EC_03,EDELAR3821UN3_RA,35.7377,-0.1364,16.4445,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_EC_04,EDELAR3821UN4_RA,35.7377,-0.1364,16.4445,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_EDE,EDE_LA,38.8695,0.2722,19.1677,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_ERW,EDEERWFUNG1_RA,-8.2968,-1.0410,-26.6855,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,-5.6299,-1.4340,-23.6256,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,65.7400,0.6545,45.6558,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,65.7400,0.6545,45.6558,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,65.7400,0.6545,45.6558,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,65.7400,0.6545,45.6558,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,17.2570,0.4899,-2.6626,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_RIV_10,EDERIV1671UN10_RA,37.6220,-0.2717,18.4641,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_RIV_11,EDERIV1671UN11_RA,37.6220,-0.2717,18.4641,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_RIV_12,EDERIV453UN12_PLT,37.0728,-0.8210,18.4641,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_SL_01,EDESTL4391UN1_RA,37.6729,-0.1581,18.4013,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EDE_SWMP,EDE_SWMP_LA,33.8200,0.4070,13.9833,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EEI,EEI,27.6109,0.2326,7.9486,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EES,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,-6.6640,-1.1509,-24.9427,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,ERCOTE,ERCOTE,38.3062,1.1064,17.7701,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,ERCOTN,ERCOTN,-2.5332,-0.9605,-21.0024,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,0.4920,-1.1238,-17.8138,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,FMPP,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,FPC,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,FPL,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,FREM_50T,OPPDFREM_GUN1_RA,4.7921,-0.9402,-13.6974,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,FREM_6,OPPDFREM_AUN6_RA,4.7794,-0.9496,-13.7006,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,FREM_7,OPPDFREM_AUN7_RA,4.7794,-0.9496,-13.7006,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,FREM_8,OPPDFREM_AUN8_RA,4.6713,-1.0577,-13.7006,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,FREM_LOAD,FREM_LOAD_LA,4.7620,-0.9670,-13.7006,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-10.7470,-0.9058,-29.2709,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,37.4807,1.2654,16.7856,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-14.2598,-1.9824,-31.7071,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-34.4728,-1.5329,-52.3696,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,37.9059,0.2580,18.2182,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,37.9059,0.2580,18.2182,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,37.9059,0.2580,18.2182,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,43.1205,0.0871,23.6037,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,43.1205,0.0871,23.6037,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,43.2799,0.0822,23.7681,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,43.2799,0.0822,23.7681,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-19.9842,-1.3649,-38.0490,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,68.1700,-0.1249,48.8652,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,68.1700,-0.1249,48.8652,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,68.1700,-0.1249,48.8652,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.VOLT.0130,V130_DDR,43.8911,0.2917,24.1697,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA.VOLT.0237,V237_DDR,44.1380,0.1643,24.5440,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDAHUB2,GRDAHUB2_H,23.9642,-0.2649,4.7995,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDAHUB3,GRDAHUB3_H,18.2134,-0.4016,-0.8147,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA_GRDA,GRDA_LA,44.6684,0.1808,25.0580,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA_HUB,GRDA_H,32.1703,-0.0917,12.8324,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRDA_HUBSA,GRDASA_H,31.5782,-0.1173,12.2659,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,GRE,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-0.0148,0.7851,-20.2296,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GSEC_SPS,SPS_GSEC_LA,7.3974,0.1818,-12.2141,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GSPR2014HUB,GSPR2014HUB_H,24.3690,0.1557,4.7836,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,GSPR2015HUB,GSPR2015HUB_H,23.5951,0.0978,4.0677,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,5.5749,-0.6681,-13.1867,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,HARRISON,CSWSLEBROCKPLT1,37.7093,1.1617,17.1179,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,HAST_TNSK_HUB,HAST_TNSK_H,3.0135,-1.3798,-15.0363,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,HQST,PJM,23.0175,-0.0716,3.6594,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,HST,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,52.5242,0.1119,32.9827,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,52.5242,0.1119,32.9827,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,50.8710,0.1142,31.3271,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,50.8710,0.1142,31.3271,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,54.2294,0.1122,34.6875,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,54.2294,0.1122,34.6875,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,INDN_INDN,INDN_LA,52.1697,0.1245,32.6155,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-19.0825,-1.6155,-36.8967,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,ISNE,PJM,23.0175,-0.0716,3.6594,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,JEA,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,5.1119,-0.8388,-13.4789,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,5.1119,-0.8388,-13.4789,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,-10.3785,-0.2726,-29.5356,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KACYCT4,KACYNEARMANUNCT4_RA,35.7217,-0.0012,16.2932,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,67.6904,-0.2049,48.4657,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,35.7217,-0.0012,16.2932,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,34.6190,0.0213,15.1680,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,34.9224,0.0178,15.4749,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KACY_KACY,KACY_LA,34.4500,0.0131,15.0072,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,23.4390,-0.1162,4.1256,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,47.3800,0.4919,27.4584,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-13.8669,-1.0156,-32.2810,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-43.9991,-1.4339,-61.9949,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.VOLT.0222,V222_DDR,4.7135,-0.3050,-14.4112,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.VOLT.0223,V223_DDR,14.8397,-0.2548,-4.3352,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.VOLT.0241,V241_DDR,38.2578,0.3427,18.4854,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.VOLT.0243,V243_DDR,29.4359,-0.0193,10.0256,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.VOLT.0247,V247_DDR,28.0365,-0.0944,8.7013,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.VOLT.0253,V253_DDR,23.7294,-0.1098,4.4096,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,-1.2181,-1.4961,-19.1517,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,13.0787,-0.4522,-5.8988,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,13.0787,-0.4522,-5.8988,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,13.0787,-0.4522,-5.8988,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,13.0787,-0.4522,-5.8988,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,23.2982,-0.1205,3.9890,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,23.2982,-0.1205,3.9890,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHUB,KCPLHUB_H,3.1060,-0.8874,-15.4362,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHUB17,KCPLHUB17_H,1.6256,-0.9678,-16.8363,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHUB18,KCPLHUB18_H,1.0563,-0.9801,-17.3932,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHUB19,KCPLHUB19_H,0.6901,-0.9426,-17.7970,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHUB20,KCPLHUB20_H,0.0988,-1.0049,-18.3260,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHUB21,KCPLHUB21_H,-0.2303,-0.9778,-18.6822,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHUB22,KCPLHUB22_H,0.7887,-0.9758,-17.6653,19.4298\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHUB23,KCPLHUB23_H,0.3358,-0.9986,-18.0952,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLHUB24,KCPLHUB24_H,-0.6149,-1.0268,-19.0178,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,0.6367,-0.3247,-18.4683,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,0.6367,-0.3247,-18.4683,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,8.3744,-0.7524,-10.3029,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,8.3744,-0.7524,-10.3029,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,23.4398,-0.1155,4.1256,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,23.4390,-0.1162,4.1256,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,25.4371,-0.0586,6.0661,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,25.4371,-0.0586,6.0661,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,25.4371,-0.0586,6.0661,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,25.4371,-0.0586,6.0661,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,25.4371,-0.0586,6.0661,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,25.4371,-0.0586,6.0661,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,25.4371,-0.0586,6.0661,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,25.4371,-0.0586,6.0661,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,5.3748,-0.4716,-13.5833,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,25.3291,-0.1104,6.0099,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KCPL_KCPL,KCPL_LA,23.8910,-0.1304,4.5917,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KENN,KENN_LA,20.2532,0.4490,0.3746,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KEP2_SECI,KEP2_SECI_LA,-17.6570,-1.0990,-35.9877,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KERR_1,GRDAKERR_HYDUN1_RA,43.6791,0.1248,24.1247,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KERR_2,GRDAKERR_HYDUN2_RA,43.5398,0.1279,23.9822,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KERR_3,GRDAKERR_HYDUN3_RA,43.5398,0.1279,23.9822,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KERR_4,GRDAKERR_HYDUN4_RA,43.6791,0.1248,24.1247,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,13.0786,-0.4523,-5.8988,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,13.0786,-0.4523,-5.8988,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,14.9205,-0.3408,-4.1683,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,14.9205,-0.3408,-4.1683,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,10.4578,-0.4487,-8.5232,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,8.6899,-0.4086,-10.3312,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,8.6899,-0.4086,-10.3312,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-15.9417,-1.2173,-34.1541,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-15.9417,-1.2173,-34.1541,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-15.9417,-1.2173,-34.1541,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-10.5778,-1.2437,-28.7637,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-10.5778,-1.2437,-28.7637,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-16.0941,-1.2640,-34.2597,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-11.3177,-1.2339,-29.5134,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,-4.6087,-0.8495,-23.1889,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,59.8306,-0.2264,40.6274,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,59.8306,-0.2264,40.6274,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,-2.5655,-0.7930,-21.2022,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,-2.5655,-0.7930,-21.2022,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,-2.5655,-0.7930,-21.2022,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-13.5049,-1.6227,-31.3119,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-8.5431,-1.8437,-26.1291,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,3.6824,-0.8965,-14.8508,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,-12.2561,-0.2041,-31.4816,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,LAFA,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,LAM345,LAM345,-16.6671,-1.4820,-34.6148,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,LEPA,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,5.5783,-0.9665,-12.8848,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_LES,LES_LA,5.4909,-0.9789,-12.9598,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,5.5154,-0.9921,-12.9221,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,5.3431,-1.0359,-13.0507,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,5.3431,-1.0359,-13.0507,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,5.3431,-1.0359,-13.0507,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,5.5161,-0.9915,-12.9221,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,5.5154,-0.9921,-12.9221,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_WAVERLY,LES_WAVERLY_H,5.3567,-1.0141,-13.0589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,5.4405,-0.9740,-13.0151,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,5.4405,-0.9740,-13.0151,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,LGEE,LGEE,25.4953,0.0803,5.9853,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MALDEN,MALDEN_LA,20.9318,0.4175,1.0846,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MCWEST,MCWEST,24.7403,-0.1832,5.4939,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MDU,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,-2.1955,-0.8220,-20.8032,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,2.1123,-0.6557,-16.6617,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,5.6670,-0.0475,-13.7151,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MEAN_NPPD,NPPD_MEAN_LA,0.6658,-1.4773,-17.2865,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MEC,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MHEB,MHEB,13.3884,-0.3155,-5.7257,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-12.4422,-1.8062,-30.0657,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-13.7674,-1.9033,-31.2937,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-12.4422,-1.8062,-30.0657,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-12.4422,-1.8062,-30.0657,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-13.7674,-1.9033,-31.2937,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-12.4424,-0.8941,-30.9780,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MISO,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-17.2685,-0.9336,-35.7646,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-17.2685,-0.9336,-35.7646,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,-3.5692,-1.2207,-21.7781,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-18.9550,-1.7040,-36.6807,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-13.0707,-1.6308,-30.8695,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-19.5979,-1.5022,-37.5254,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-17.5792,-1.2805,-35.7284,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-19.7115,-1.4100,-37.7312,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-17.0884,-1.1999,-35.3181,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-17.0884,-1.1999,-35.3181,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-17.0884,-1.1999,-35.3181,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-17.0884,-1.1999,-35.3181,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-17.0884,-1.1999,-35.3181,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,22.9493,-0.2944,3.8141,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,25.8230,0.1580,6.2353,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,25.8230,0.1580,6.2353,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,24.2655,-0.0517,4.8876,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,35.0231,0.4198,15.1737,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MOWR,AECI,33.2299,0.0856,13.7146,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,26.2370,-0.0654,6.8727,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,26.4123,0.1713,6.8113,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-5.2157,-1.3670,-23.2784,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-12.2906,-0.8543,-30.8660,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-30.0158,-1.5136,-47.9318,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-5.1493,-1.3005,-23.2784,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,13.5281,-0.2393,-5.6623,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,13.5281,-0.2393,-5.6623,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,13.5286,-0.2388,-5.6623,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,13.5286,-0.2388,-5.6623,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,4.7135,-0.3050,-14.4112,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,4.7135,-0.3050,-14.4112,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,4.7135,-0.3050,-14.4112,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,4.6503,-0.3681,-14.4112,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,4.7135,-0.3050,-14.4112,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,4.7135,-0.3050,-14.4112,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,4.7135,-0.3050,-14.4112,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,28.6909,0.3400,8.9213,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,18.8833,-0.2310,-0.3154,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,12.4890,-0.3011,-6.6395,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,12.4891,-0.3010,-6.6395,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,12.4891,-0.3010,-6.6395,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,24.8400,-0.1263,5.5367,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,24.8400,-0.1263,5.5367,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MPS_MPS,MPS_LA,27.9582,-0.0740,8.6026,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,MSTNG,SPSMSTNGPLT1,39.5414,1.7296,18.3821,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MSTNG4,SPSMSTNGUN4_RA,39.4495,1.6377,18.3821,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MSTNG5,SPSMSTNGUN5_RA,39.5414,1.7296,18.3821,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,39.5414,1.7296,18.3821,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NBSO,PJM,23.0175,-0.0716,3.6594,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,2.2516,-1.3854,-15.7927,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,2.2511,-1.3858,-15.7927,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,0.3453,-1.1255,-17.9589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NHC1,VACS,31.0505,0.4491,11.1717,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,5.0904,-0.8934,-13.4459,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,5.0904,-0.8934,-13.4459,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,5.0904,-0.8934,-13.4459,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-1.3973,-1.7766,-19.0503,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,1.9679,-1.9245,-15.5372,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,3.8210,-1.3531,-14.2555,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-0.7625,-1.3095,-18.8827,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,1.9679,-1.9245,-15.5372,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.HUB.PY2018,NPPDPY18_H,0.7392,-1.4146,-17.2758,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,0.8927,-1.4110,-17.1259,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,0.8324,-1.4043,-17.1930,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,0.9562,-1.3932,-17.0803,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-3.2071,-1.3692,-21.2676,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,-0.6378,-1.3666,-18.7009,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,-0.6378,-1.3666,-18.7009,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-7.3900,-1.5648,-25.2549,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-3.2071,-1.3692,-21.2676,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,8.4461,-2.3280,-8.6556,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,0.9641,-1.9907,-16.4749,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,-4.0626,-1.1382,-22.3541,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,0.9641,-1.9907,-16.4749,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,2.3662,-1.9057,-15.1577,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,0.4020,-1.7572,-17.2704,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,4.7844,-0.8727,-13.7725,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,1.9679,-1.9245,-15.5372,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,-3.5026,-1.2162,-21.7161,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,-0.6378,-1.3666,-18.7009,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,-0.6378,-1.3666,-18.7009,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,0.4010,-1.1817,-17.8470,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,0.3113,-1.1865,-17.9318,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,0.3113,-1.1865,-17.9318,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,1.3751,-0.9829,-17.0717,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-10.9700,-0.9373,-29.4624,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,2.3361,-1.6539,-15.4396,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-1.2026,-1.5681,-19.0641,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-9.1719,-0.8346,-27.7670,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-11.7200,-0.8638,-30.2859,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.NELI.DDR,NELI_DDR,-2.3972,-1.5654,-20.2615,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.NPPM.1058,SH1058_DDR,16.9939,-0.9984,-1.4374,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,1.4812,-1.1241,-16.8244,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,1.9679,-1.9245,-15.5372,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,3.8210,-1.3531,-14.2555,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-3.2071,-1.3692,-21.2676,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.TECH.1,KEARNE_DDR,1.9205,-0.9241,-16.5850,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,2.9931,-2.3602,-14.0764,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,2.9931,-2.3602,-14.0764,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-3.3708,-1.4984,-21.3021,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD.VOLT.0236,V236_DDR,3.8765,-0.9047,-14.6484,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD2017HUB,NPPD2017HUB_H,0.7742,-1.4105,-17.2449,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,14.6960,-1.4179,-3.3158,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-1.3973,-1.7766,-19.0503,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,0.8895,-2.2929,-16.2473,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,0.8895,-2.2929,-16.2473,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,4.0268,-0.9391,-14.4638,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,3.8914,-0.8899,-14.6484,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-4.5048,-1.3345,-22.6000,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,0.5066,-1.2237,-17.6994,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,16.6202,-1.3720,-1.4374,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,16.6202,-1.3720,-1.4374,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,16.6202,-1.3720,-1.4374,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,3.0207,-1.3785,-15.0305,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,3.5828,-1.3177,-14.5292,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,2.8601,-1.2902,-15.2794,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-1.1462,-2.5120,-18.0639,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-1.0454,-2.4112,-18.0639,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,-1.7578,-1.4105,-19.7770,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,-2.0138,-1.4221,-20.0214,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,4.0080,-1.3273,-14.0944,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,3.9910,-1.3442,-14.0944,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,3.9910,-1.3442,-14.0944,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,3.9427,-1.3080,-14.1789,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,8.4461,-2.3280,-8.6556,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,3.8542,-1.3112,-14.2642,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,4.6775,-1.1367,-13.6155,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,3.0467,-1.3396,-15.0433,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,3.0344,-1.3488,-15.0465,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,3.0408,-1.3402,-15.0487,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,3.0408,-1.3402,-15.0487,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,3.0207,-1.3785,-15.0305,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,2.9862,-1.4130,-15.0305,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,-0.5642,-1.3341,-18.6598,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,3.3100,-1.1152,-15.0044,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,-2.0888,-1.3548,-20.1637,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,1.3877,-2.2501,-15.7919,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,-4.3747,-1.2162,-22.5882,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,17.2487,-0.7436,-1.4374,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-2.3972,-1.5654,-20.2615,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,-1.4352,-1.3867,-19.4782,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,-1.4352,-1.3867,-19.4782,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_NPPD,NPPD_LA,5.4342,-1.2086,-12.7868,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,4.6775,-1.1367,-13.6155,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,4.6775,-1.1367,-13.6155,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,1.5613,-1.2900,-16.5783,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,0.0214,-1.4313,-17.9770,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NSB,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,NSP,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NSSO,PJM,23.0175,-0.0716,3.6594,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,NYIS,PJM,23.0175,-0.0716,3.6594,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-18.4391,-1.6369,-36.2318,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-21.1445,-1.4069,-39.1673,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-29.8104,-1.3018,-47.9382,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-29.8104,-1.3018,-47.9382,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-19.4904,-1.8150,-37.1050,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-34.4728,-1.5329,-52.3696,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-101.6555,-0.8102,-120.2749,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-47.1210,-1.4771,-65.0736,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-22.1130,-1.3564,-40.1863,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-20.8999,-1.4704,-38.8592,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,-5.5103,-0.4735,-24.4665,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-22.1130,-1.3564,-40.1863,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-19.2172,-1.7920,-36.8548,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-12.4424,-0.8941,-30.9780,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-18.1217,-1.6170,-35.9343,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,-15.0000,0.0198,-34.4495,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-20.8999,-1.4704,-38.8592,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-16.9000,-1.2249,-35.1048,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-16.1200,-1.2922,-34.2575,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-10.2908,-0.9616,-28.7589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-29.8783,0.0231,-49.3310,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-12.4424,-0.8941,-30.9780,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-12.4424,-0.8941,-30.9780,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-20.8999,-1.4704,-38.8592,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-9.9178,-0.7947,-28.5528,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.NUEN.LAM1,LAM1_DDR,37.8883,1.2656,17.1930,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.NUEN.MDT2,MDT2_DDR,-5.5085,-0.4717,-24.4665,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.NUEN.MDT3,MDT3_DDR,-5.5085,-0.4717,-24.4665,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-10.4732,-0.7230,-29.1799,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,-5.8246,-0.4888,-24.7655,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,-5.8246,-0.4888,-24.7655,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,-5.8246,-0.4888,-24.7655,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,-5.7598,-0.4051,-24.7843,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,-5.7598,-0.4051,-24.7843,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,-5.8246,-0.4888,-24.7655,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,-5.8246,-0.4888,-24.7655,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-20.8999,-1.4704,-38.8592,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,26.1038,0.6873,5.9869,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-19.2172,-1.7920,-36.8548,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-21.4344,-0.2929,-40.5711,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-16.9000,-1.2249,-35.1048,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,35.1714,0.8505,14.8912,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-11.7242,-0.9544,-30.1995,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-11.7242,-0.9544,-30.1995,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-11.7242,-0.9544,-30.1995,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-11.7242,-0.9544,-30.1995,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-27.5232,-2.0395,-44.9134,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-24.0905,-1.2821,-42.2381,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-21.1445,-1.4069,-39.1673,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-27.4876,-1.2316,-45.6857,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-27.4876,-1.2316,-45.6857,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-25.1818,0.0952,-44.7066,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-11.6919,-1.0531,-30.0685,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-11.6919,-1.0531,-30.0685,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-11.6919,-1.0531,-30.0685,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0033,FOSTER_DDR,-3.8240,-0.3458,-22.9078,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,17.9814,0.3452,-1.7935,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0035,TARBY_DDR,37.6661,1.0016,17.2349,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,17.9814,0.3452,-1.7935,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,15.4569,0.1616,-4.1343,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,15.4569,0.1616,-4.1343,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-23.4753,-0.0194,-42.8855,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0040,TROSPER_DDR,-3.6562,-0.3237,-22.7622,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,-4.1406,-0.3267,-23.2436,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,36.2772,1.0010,15.8465,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0115,V115_DDR,-5.3615,-0.4506,-24.3405,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0116,V116_DDR,-21.0652,0.2310,-40.7258,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0118,V118_DDR,0.0400,0.0807,-19.4704,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0125,V125_DDR,36.8859,1.1380,16.3182,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0126,V126_DDR,35.8586,0.4710,15.9579,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0129,V129_DDR,0.6774,-0.7037,-18.0486,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,-4.6158,-0.4282,-23.6173,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0134,V134_DDR,36.9054,0.6290,16.8468,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0138,V138_DDR,34.9799,0.3834,15.1668,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,-4.5536,-0.3366,-23.6467,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0143,V143_DDR,23.6315,0.2247,3.9771,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0149,V149_DDR,-8.2563,-0.8157,-26.8703,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0150,V150_DDR,-8.3143,-0.8447,-26.8992,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0155,V155_DDR,34.1747,0.2926,14.4524,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0156,V156_DDR,-4.6158,-0.4282,-23.6173,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0166,V166_DDR,36.0667,0.9632,15.6738,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,-4.5260,-0.3448,-23.6108,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-8.3143,-0.8447,-26.8992,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0170,V170_DDR,-10.7540,-0.7172,-29.4665,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-7.4332,-0.8105,-26.0524,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0176,V176_DDR,-8.3143,-0.8447,-26.8992,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0177,V177_DDR,-23.2466,-1.6851,-40.9911,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,-4.4859,-0.3456,-23.5700,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-12.7699,-1.0368,-31.1627,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0195,V195_DDR,167.5338,1.6496,146.4545,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0197,V197_DDR,33.5630,0.5744,13.5589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0198,V198_DDR,36.0667,0.9632,15.6738,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0208,V208_DDR,167.8400,1.6886,146.7217,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0209,V209_DDR,167.8400,1.6886,146.7217,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,34.6400,0.4031,14.8073,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0216,V216_DDR,-4.2632,-0.3283,-23.3645,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0219,V219_DDR,34.1747,0.2926,14.4524,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0220,V220_DDR,-8.3143,-0.8447,-26.8992,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0224,V224_DDR,-5.6191,-0.4405,-24.6083,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0225,V225_DDR,-5.6181,-0.4394,-24.6083,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0226,V226_DDR,-5.6191,-0.4405,-24.6083,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0227,V227_DDR,-5.6191,-0.4405,-24.6083,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0229,V229_DDR,-21.9672,0.0608,-41.4577,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0231,V231_DDR,-9.1050,0.2689,-28.8036,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0238,V238_DDR,-30.8434,-1.5224,-48.7507,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.VOLT.0242,V242_DDR,34.5123,0.3367,14.7459,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-20.0001,-2.0819,-37.3479,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-12.4424,-0.8941,-30.9780,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-21.3608,-1.3226,-39.4679,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-18.1040,-1.5993,-35.9343,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-20.0001,-2.0819,-37.3479,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-18.5687,-1.5970,-36.4014,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-53.2106,-1.3694,-71.2709,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEHL7,OKGEHL7_H,-0.2888,-0.3250,-19.3935,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEHL8,OKGEHSL1UN8_RA,-0.2888,-0.3250,-19.3935,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEHL910,OKGEHSL1PLT2,-0.2888,-0.3250,-19.3935,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-18.2823,-1.6229,-36.0890,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEMCC,OKGEMCCLAIPLT1,-5.3574,-0.5946,-24.1925,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,31.0134,0.1930,11.3907,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,31.0134,0.1930,11.3907,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,30.9793,0.1590,11.3907,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,-0.2458,-0.6095,-19.0660,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,-0.2458,-0.6095,-19.0660,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,-0.2458,-0.6095,-19.0660,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,-0.2458,-0.6095,-19.0660,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGESM1,OKGESEMINOLEUN1_RA,2.0211,-0.2294,-17.1791,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGESM2,OKGESEMINOLEUN2_RA,3.6004,-0.2718,-15.5574,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGESM3,OKGESEMINOLEUN3_RA,3.6004,-0.2718,-15.5574,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGESO1,OKGESONR1UN1_RA,-53.9500,-1.1211,-72.2586,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGESO2,OKGESONR1UN2_RA,-27.4876,-1.2316,-45.6857,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-18.2823,-1.6229,-36.0890,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-16.7419,-1.5008,-34.6707,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGETINK5A,OKGETINK5UN1_RA,-2.7321,-0.3536,-21.8082,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGETINK5B,OKGETINK5UN2_RA,-2.7321,-0.3536,-21.8082,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-15.1977,-1.3646,-33.2628,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-21.1445,-1.4069,-39.1673,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,36.2930,1.2928,15.5705,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-12.4424,-0.8941,-30.9780,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE_OKGE,OKGE_LA,4.8100,-0.1229,-14.4968,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-21.4344,-0.2929,-40.5711,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-15.2677,-1.4346,-33.2628,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMLP,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,42.3054,0.1046,22.7711,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,36.4123,1.1742,15.8084,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_GENHUB,OMPA_GENHUB_H,-7.1128,-0.4477,-26.0948,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-101.4886,-0.6433,-120.2749,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-14.8316,-1.2284,-33.0328,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-22.1130,-1.3564,-40.1863,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-19.5708,-1.4785,-37.5219,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,-5.9378,-1.6118,-23.7557,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,201.2500,0.1299,181.6904,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-101.5424,-0.6971,-120.2749,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-101.5424,-0.6971,-120.2749,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_SPP,OMPA_SPP_LA,-16.7100,-0.6440,-35.4957,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-20.0001,-2.0819,-37.3479,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,37.0425,0.0697,17.5431,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,37.0425,0.0697,17.5431,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,37.0425,0.0697,17.5431,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,37.0425,0.0697,17.5431,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,ONT,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,4.9443,-0.9035,-13.5818,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,4.9443,-0.9035,-13.5818,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,4.9443,-0.9035,-13.5818,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,4.9443,-0.9035,-13.5818,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,4.9443,-0.9035,-13.5818,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,4.9443,-0.9035,-13.5818,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,4.9443,-0.9035,-13.5818,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,4.9443,-0.9035,-13.5818,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,4.9443,-0.9035,-13.5818,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,5.0826,-0.8742,-13.4728,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,5.0904,-0.8934,-13.4459,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,5.1453,-0.7849,-13.4995,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,5.0578,-0.8497,-13.5222,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,5.0578,-0.8497,-13.5222,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD_GLDN,OPPD_GLDN_LA,4.9823,-0.8940,-13.5534,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,5.0185,-0.8873,-13.5238,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,8.4461,-2.3280,-8.6556,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,3.5280,-1.0869,-14.8148,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,5.0900,-0.8924,-13.4472,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD_OPPD,OPPD_LA,5.0613,-0.8511,-13.5173,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,5.0751,-0.8279,-13.5267,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,5.0703,-0.8343,-13.5251,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OTP,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,OVEC,OVEC,24.5505,0.0230,5.0979,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PARAGOULD,PARAGOULD_LA,19.1969,0.4988,-0.7316,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,43.6529,-0.0046,24.2278,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,43.6529,-0.0046,24.2278,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,43.6529,-0.0046,24.2278,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,43.1780,0.0659,23.6824,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,43.1780,0.0659,23.6824,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,43.1780,0.0659,23.6824,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PIGGOTT,PIGGOTT_LA,20.4947,0.4378,0.6272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PJM,PJM,23.0175,-0.0716,3.6594,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PLUM,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,POPLARBLUFF,POPLARBLUFF_LA,23.7686,0.3388,4.0002,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,25.3865,-0.3900,6.3468,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,25.3865,-0.3900,6.3468,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,23.4351,-0.3854,4.3909,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,23.4351,-0.3854,4.3909,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,22.3545,0.7982,2.1266,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,22.3545,0.7982,2.1266,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,24.5072,-0.1924,5.2700,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,33.2000,-0.8627,14.6330,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-7.6283,-0.9698,-26.0881,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,99.5156,0.0828,80.0031,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,7.2333,-0.2114,-11.9850,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,-5.9770,0.0064,-25.4131,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,42.6187,0.5598,22.6293,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,39.0692,0.4776,19.1620,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,9.3865,-0.9392,-9.1040,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,21.2034,-0.1627,1.9365,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,7.2812,-1.2801,-10.8684,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,34.4043,1.0793,13.8954,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,14.3298,-0.1548,-4.9451,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,8.7326,-0.7624,-9.9347,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,PUPP,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,RCEAST,RCEAST,-6.4715,-1.7597,-24.1414,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SALINA_1,GRDASALINA1UN1_RA,43.6809,0.1266,24.1247,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SALINA_2,GRDASALINA1UN2_RA,43.6809,0.1266,24.1247,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SALINA_3,GRDASALINA1UN3_RA,43.6809,0.1266,24.1247,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SALINA_4,GRDASALINA1UN4_RA,43.6809,0.1266,24.1247,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SALINA_5,GRDASALINA1UN5_RA,43.6809,0.1266,24.1247,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SALINA_6,GRDASALINA1UN6_RA,43.6809,0.1266,24.1247,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SARPY_1,OPPDSARPYUN1_RA,5.0563,-0.8718,-13.5016,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SARPY_2,OPPDSARPYUN2_RA,5.0893,-0.8378,-13.5026,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SARPY_3,OPPDSARPYUN3_RA,5.0575,-0.9123,-13.4598,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SARPY_4,OPPDSARPYUN4_RA,5.0575,-0.9123,-13.4598,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SARPY_5,OPPDSARPYUN5_RA,5.0575,-0.9123,-13.4598,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SC,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SCEG,VACS,31.0505,0.4491,11.1717,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SCSE,SCSE,-2.1603,-1.2571,-20.3329,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SEC,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-21.8789,-1.8173,-39.4913,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-21.8789,-1.8173,-39.4913,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-21.8789,-1.8173,-39.4913,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-15.6611,-0.7690,-34.3218,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-21.8789,-1.8173,-39.4913,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-18.1671,-1.6685,-35.9282,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-18.2479,-1.8139,-35.8636,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-18.2479,-1.8139,-35.8636,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-17.0906,-1.2022,-35.3181,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-24.4702,-1.6146,-42.2853,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-10.6514,-1.3174,-28.7637,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-16.4456,-0.9481,-34.9272,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-10.8396,-1.3520,-28.9173,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-21.0335,-1.8111,-38.6521,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-10.7010,-1.3468,-28.7839,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-19.0591,-2.0717,-36.4170,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-18.4398,-1.1875,-36.6820,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-16.1061,-1.3096,-34.2262,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-16.1061,-1.3096,-34.2262,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-16.1061,-1.3096,-34.2262,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-16.1061,-1.3096,-34.2262,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-16.4096,-1.4150,-34.4243,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-18.1671,-1.6685,-35.9282,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI_SECI,SECI_LA,-15.7428,-1.1756,-33.9968,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-19.0825,-1.6155,-36.8967,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-19.0825,-1.6155,-36.8967,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-17.0906,-1.2022,-35.3181,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SEHA,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-15.2677,-1.4346,-33.2628,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SERU,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SETH,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SGE,SGE,-2.5987,-1.2151,-20.8133,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SMEP,MISO,21.9535,0.0036,2.5202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SOCO,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPA,SPA,35.3716,0.5598,15.3821,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPC,SPC,19.1456,0.2538,-0.5378,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPPNORTH_HUB,SPPNORTH_H,5.1700,-1.0137,-13.2460,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPPSOUTH_HUB,SPPSOUTH_H,-5.3626,-0.7234,-24.0689,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,34.6748,0.4247,14.8204,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,34.6748,0.4247,14.8204,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,34.2778,0.3744,14.4737,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,34.2778,0.3744,14.4737,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_NIXA,SPRM_NIXA_LA,35.0108,0.4460,15.1351,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_SPRM,SPRM_LA,34.7167,0.4829,14.8041,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,34.7012,0.3228,14.9487,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,34.7012,0.3228,14.9487,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,34.6533,0.2749,14.9487,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,34.7012,0.3228,14.9487,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,17.5924,0.7492,-2.5865,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,10.9089,0.1781,-8.6988,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,0.0813,-0.7088,-18.6395,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,0.0813,-0.7088,-18.6395,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,3.0917,-0.8749,-15.4630,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,26.2531,0.7795,6.0440,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,13.5794,-0.2635,-5.5868,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,77.8780,1.0176,57.4307,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,1.8651,-0.0776,-17.4870,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,74.8540,1.6136,53.8107,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,80.8320,1.6848,59.7176,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,80.8320,1.6848,59.7176,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,74.8540,1.6136,53.8107,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,0.3734,-0.4955,-18.5608,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,10.9089,0.1781,-8.6988,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,-0.3758,-0.7115,-19.0940,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-11.4854,-1.7135,-29.2016,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,-4.2940,-0.6795,-23.0442,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,-0.9622,-0.2815,-20.1104,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,-1.8740,-0.7341,-20.5696,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-19.8139,-1.8059,-37.4376,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-19.8139,-1.8059,-37.4376,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-19.8139,-1.8059,-37.4376,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-19.8139,-1.8059,-37.4376,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GRID.WRAB,WRAB_DDR,3.6411,0.2686,-16.0571,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-19.8139,-1.8059,-37.4376,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,4.7803,-0.0168,-14.6326,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,4.7803,-0.0168,-14.6326,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,4.8729,0.0474,-14.6042,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,4.8729,0.0474,-14.6042,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,4.8729,0.0474,-14.6042,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,4.7803,-0.0168,-14.6326,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,3.9803,-0.7246,-14.7248,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,3.9792,-0.7246,-14.7259,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,3.9849,-0.7246,-14.7202,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,0.3453,-1.1255,-17.9589,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,76.9708,1.5762,55.9650,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,1.9863,-0.0847,-17.3587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,1.9863,-0.0847,-17.3587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,1.9863,-0.0847,-17.3587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,1.9863,-0.0847,-17.3587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,55.6565,1.8188,34.4080,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,74.0908,1.5618,53.0993,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,74.0908,1.5618,53.0993,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-15.1999,-1.3667,-33.2628,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,3.3948,-0.7079,-15.3269,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,3.3948,-0.7079,-15.3269,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,3.8831,-0.7186,-14.8279,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,3.6411,0.2686,-16.0571,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-10.2778,-1.4024,-28.3051,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,-1.7608,-0.8113,-20.3792,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-19.4904,-1.8150,-37.1050,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,3.6858,-0.4170,-15.3269,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.PLANTX1,SPS.PLANTX1_H,12.3378,0.5008,-7.5926,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.PLANTX2,SPS.PLANTX2_H,12.3378,0.5008,-7.5926,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,12.9886,0.4973,-6.9383,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,2.8000,-0.5948,-16.0349,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-15.1782,-1.6280,-32.9798,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,13.8604,0.0176,-5.5868,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,2.8356,-0.5592,-16.0349,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,0.3669,-0.5020,-18.5608,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,16.6312,0.7805,-3.5790,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,78.2727,1.4123,57.4307,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,16.6312,0.7805,-3.5790,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,17.1712,1.1750,-3.4334,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-36.8219,-0.8978,-55.3537,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,79.6951,2.7443,57.5211,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,79.8384,2.8876,57.5211,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,77.7140,2.4612,55.8231,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,73.9901,1.7054,52.8550,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,80.9519,2.4145,59.1078,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-16.6671,-1.4820,-34.6148,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,3.6244,0.1968,-16.0021,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,14.1520,0.5956,-5.8732,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,14.1520,0.5956,-5.8732,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,16.6312,0.7805,-3.5790,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,1.5659,0.0194,-17.8831,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,50.5815,2.2478,28.9041,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,15.3961,1.6182,-5.6518,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,16.1735,0.9848,-4.2409,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,8.1655,0.0880,-11.3521,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,79.6951,2.7443,57.5211,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,81.4011,3.0941,58.8773,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,81.1078,2.8009,58.8773,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,3.0098,-0.3849,-16.0349,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,15.0108,1.1735,-5.5924,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-14.0880,-1.5359,-31.9818,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-14.0985,-1.5698,-31.9583,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0163,V163_DDR,3.7537,-0.4788,-15.1972,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0168,V168_DDR,-6.9792,-0.6087,-25.8002,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0180,V180_DDR,81.4011,3.0941,58.8773,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0181,V181_DDR,-14.4500,-1.3253,-32.5544,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0182,V182_DDR,81.3444,2.5567,59.3580,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0199,V199_DDR,46.1924,2.1159,24.6468,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0200,V200_DDR,75.8606,2.1214,54.3095,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.VOLT.0235,V235_DDR,-10.2778,-1.4024,-28.3051,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,13.5794,-0.2635,-5.5868,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,77.8780,1.0176,57.4307,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,5.5091,-0.7339,-13.1867,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,4.1322,-0.5801,-14.7173,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS_SPS,SPS_LA,44.9099,1.4379,24.0423,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,35.0877,1.0072,14.6509,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,SSCN_NPPD,SSCN_NPPD_LA,-0.0048,-1.2366,-18.1979,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,23.1800,0.3203,3.4300,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,23.1800,0.3203,3.4300,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,TAL,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,TEC,SOUC,31.1009,0.4983,11.1730,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,1.3877,-2.2501,-15.7919,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,TVA,TVA,30.9878,0.3973,11.1608,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,UCUHUB,UCUHUB_H,-0.9484,-0.6716,-19.7065,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,UCUHUB17,UCUHUB17_H,-9.9815,-1.1050,-28.3062,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,UCUHUB18,UCUHUB18_H,-6.6208,-1.0007,-25.0498,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,UCUHUB19,UCUHUB19_H,-10.7163,-1.0464,-29.0995,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,UCUHUB20,UCUHUB20_H,-9.8963,-1.0087,-28.3173,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,UCUHUB21,UCUHUB21_H,-11.5792,-1.1025,-29.9063,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,UCUHUB22,UCUHUB22_H,-12.0045,-1.1578,-30.2763,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,UCUHUB23,UCUHUB23_H,-12.5317,-1.1662,-30.7952,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,UCUHUB24,UCUHUB24_H,-8.9067,-1.0283,-27.3081,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,19.6661,0.4577,-0.2212,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,19.6661,0.4577,-0.2212,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,10.1602,-0.8644,-8.4051,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,10.1602,-0.8644,-8.4051,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,13.1635,-0.8750,-5.3911,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,22.6924,-0.5966,3.8594,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,22.6924,-0.5966,3.8594,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,19.6661,0.4577,-0.2212,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,13.3298,-0.8221,-5.2777,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,15.4155,-0.1543,-3.8599,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,8.1836,-0.8680,-10.3781,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,3.8175,-2.6084,-13.0037,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,21.2907,0.3694,1.4916,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,21.2907,0.3694,1.4916,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,7.9867,-2.3476,-9.0953,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,8.9549,-1.1695,-9.3052,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,11.3131,-0.9690,-7.1476,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,7.1592,-1.2491,-11.0214,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,8.1917,-0.8418,-10.3961,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,8.5880,-1.2588,-9.5829,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,8.9377,-1.3967,-9.0953,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,8.9377,-1.3967,-9.0953,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,9.1621,-1.0958,-9.1718,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,3.2885,-2.7366,-13.4046,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,9.0881,0.0041,-10.3457,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,20.2838,-0.2911,1.1452,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,20.2838,-0.2911,1.1452,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,20.2838,-0.2911,1.1452,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,20.3415,-0.0974,1.0092,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,20.3415,-0.0974,1.0092,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,20.3415,-0.0974,1.0092,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,19.4989,0.6978,-0.6286,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,12.0635,-0.8594,-6.5067,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,12.0635,-0.8594,-6.5067,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,-2.3874,-1.2400,-20.5770,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,6.9381,-1.0725,-11.4191,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,19.0984,-0.2339,-0.0974,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,4.0000,-1.3203,-14.1094,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,1.4878,-3.2129,-14.7290,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,9.3332,-1.2216,-8.8748,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,20.5789,0.4306,0.7186,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,20.5789,0.4306,0.7186,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,20.5778,0.4296,0.7185,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,20.5789,0.4306,0.7186,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,20.3526,0.2527,0.6702,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,20.3526,0.2527,0.6702,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,20.3526,0.2527,0.6702,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,20.3526,0.2527,0.6702,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,20.3526,0.2527,0.6702,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,20.3526,0.2527,0.6702,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,20.3526,0.2527,0.6702,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,3.6031,-2.2148,-13.6118,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,14.3631,-0.5085,-4.5581,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,5.3081,-1.0425,-13.0790,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,5.3081,-1.0425,-13.0790,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,2.3509,-1.5559,-15.5228,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,2.3509,-1.5559,-15.5228,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,12.2816,-0.6414,-6.5067,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,18.1145,-0.5944,-0.7208,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,7.5240,-1.4231,-10.4826,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,4.3474,-2.4158,-12.6665,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,10.0341,-0.7570,-8.6386,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,13.1635,-0.8750,-5.3911,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,13.1635,-0.8750,-5.3911,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,7.1592,-1.2491,-11.0214,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,-6.3324,-1.8229,-23.9392,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,7.5498,-1.5395,-10.3404,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,3.4336,-2.5915,-13.4046,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,8.9172,-1.3089,-9.2036,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.FSE,WAUE.FSE_H,2.5510,-1.5665,-15.3121,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,22.4028,-0.3943,3.3674,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,22.7155,-0.4260,3.7118,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,3.1349,-2.6241,-13.6707,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,4.0115,-2.5050,-12.9131,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,12.9828,-0.8624,-5.5845,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,13.5733,-0.9408,-4.9155,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-15.9900,-2.3113,-33.1084,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,3.8175,-2.6084,-13.0037,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-30.1472,-1.4566,-48.1203,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,7.6197,-1.0123,-10.7977,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,7.6200,-1.0119,-10.7977,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,7.6202,-1.0118,-10.7977,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,8.7059,-1.1682,-9.5555,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,-6.3324,-1.8229,-23.9392,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,9.4523,-0.6417,-9.3356,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,6.8893,-1.3393,-11.2011,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,9.0106,-0.0734,-10.3457,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,8.5713,-0.2187,-10.6397,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,8.3850,-0.7756,-10.2690,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,11.9340,-0.7044,-6.7913,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,7.5944,-1.0565,-10.7788,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,7.4600,-1.3912,-10.5785,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,4.0000,-1.3203,-14.1094,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,13.4809,0.0020,-5.9507,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,7.1386,-1.2661,-11.0250,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,13.2779,-0.0750,-6.0768,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,9.0524,-0.6395,-9.7377,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,5.4405,-0.9740,-13.0151,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NTWK,WAUE.NTWK_H,8.7183,-0.9713,-9.7400,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,10.2804,-0.0766,-9.0726,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,10.2804,-0.0766,-9.0726,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,3.8401,-2.7427,-12.8468,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,2.8069,-2.7841,-13.8387,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,9.9863,-1.0104,-8.4330,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,3.8401,-2.7427,-12.8468,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,14.1419,-0.5277,-4.7600,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,6.3301,-1.7451,-11.3544,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,4.0000,-1.3203,-14.1094,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,7.7708,-1.3101,-10.3488,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,4.5632,-3.5121,-11.3544,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,-2.8929,-3.0842,-19.2384,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,-0.8848,-3.0699,-17.2446,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,10.4143,-0.9161,-8.0993,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,3.0316,-2.5409,-13.8572,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,10.1534,-0.7475,-8.5287,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,4.8776,-2.2257,-12.3264,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,4.3474,-2.4158,-12.6665,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.VOLT.0152,V152_DDR,19.0320,0.9132,-1.3108,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE.VOLT.0172,V172_DDR,20.4195,0.3376,0.6523,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_BEPM,WAUE_BEPM_LA,14.5978,-0.2246,-4.6072,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,9.3902,-0.6853,-9.3542,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,8.5734,-0.2086,-10.6476,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_EWA,WAUE_EWA_LA,-7.7060,-1.7113,-25.4244,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,6.2652,-1.5806,-11.5839,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_HMMU,WAUE_HMMU_LA,7.0734,-0.4863,-11.8699,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,12.2096,-0.6646,-6.5555,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_MECB,WAUE_MECB_LA,7.4393,-0.4123,-11.5781,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_MMPA,WAUE_MMPA_LA,13.4740,-0.0971,-5.8586,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_MRES,WAUE_MRES_LA,7.7980,-1.0066,-10.6251,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,17.3914,0.5218,-2.5601,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,22.4028,-0.3943,3.3674,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,5.6658,-1.5946,-12.1692,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_OTP,WAUE_OTP_LA,16.4912,0.3588,-3.2973,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_OTPW,WAUE_OTPW_LA,28.2976,0.7555,8.1124,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM,WAUE_UGPM_LA,10.0743,-0.8488,-8.5066,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,13.3893,-0.4549,-5.5855,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,7.8381,-0.9402,-10.6514,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,13.1978,-1.1887,-5.0432,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,-7.7060,-1.7113,-25.4244,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,7.0734,-0.4863,-11.8699,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,6.1327,-1.5419,-11.7551,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,22.4028,-0.3943,3.3674,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,13.4740,-0.0971,-5.8586,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,8.3647,-0.8754,-10.1896,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,5.6811,-1.7442,-12.0043,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,15.0297,0.3646,-4.7646,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-19.7483,-1.8164,-37.3615,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-21.1453,-1.7440,-38.8310,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,4.4019,-1.0455,-13.9823,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,92.1534,0.6625,72.0612,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,92.1534,0.6625,72.0612,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,-10.2999,-2.3946,-27.3350,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,84.3768,0.7614,64.1857,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,75.2197,0.7155,55.0746,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,24.1453,-0.9439,5.6596,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,24.1453,-0.9439,5.6596,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,24.1453,-0.9439,5.6596,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,24.0808,-1.0085,5.6596,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,24.1022,-0.9871,5.6596,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,24.1453,-0.9439,5.6596,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,24.1453,-0.9439,5.6596,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,24.1453,-0.9439,5.6596,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,13.5173,-0.8771,-5.0353,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-19.4904,-1.8150,-37.1050,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-30.0000,-1.6131,-47.8166,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-20.5664,-1.6586,-38.3375,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,13.7221,-0.1207,-5.5868,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_ENMC,WFEC_ENMC_LA,53.7919,1.7811,32.5812,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-20.8999,-1.4704,-38.8592,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,49.5233,0.6414,29.4523,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,61.1061,1.6794,39.9971,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-19.7483,-1.8164,-37.3615,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-19.7483,-1.8164,-37.3615,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-19.7483,-1.8164,-37.3615,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_OKGE,WFEC_OKGE_LA,0.7509,0.0524,-18.7312,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,44.9619,0.8508,24.6814,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-14.6700,-2.4515,-31.6481,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,-8.8938,-2.6037,-25.7197,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_WFEC,WFEC_LA,18.5406,-0.1751,-0.7139,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,61.1061,1.6794,39.9971,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-12.6474,-1.8658,-30.2113,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-14.5820,-1.4354,-32.5763,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,-3.2497,-0.9207,-21.7587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,-3.2497,-0.9207,-21.7587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,-3.2497,-0.9207,-21.7587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,-3.2497,-0.9207,-21.7587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,-3.2497,-0.9207,-21.7587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,-3.2497,-0.9207,-21.7587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,-3.2497,-0.9207,-21.7587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,13.8290,0.3294,-5.9301,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,-4.5870,-1.2297,-22.7870,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-15.9782,-1.4326,-33.9753,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-15.9782,-1.4326,-33.9753,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-15.9782,-1.4326,-33.9753,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-22.8368,-1.6120,-40.6545,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-22.8368,-1.6120,-40.6545,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,-7.4885,-1.3336,-25.5845,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,-7.4885,-1.3336,-25.5845,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,-7.4885,-1.3336,-25.5845,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,-4.5870,-1.2297,-22.7870,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,-2.6537,-0.3379,-21.7455,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-8.3056,-1.1787,-26.5565,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-8.3056,-1.1787,-26.5565,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-8.3056,-1.1787,-26.5565,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-8.3056,-1.1787,-26.5565,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,-2.6537,-0.3379,-21.7455,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-19.7213,-1.8014,-37.3496,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-27.0000,-0.7536,-45.6761,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.JEC.1,WRJEFFUN10_RA,-3.7879,-0.9144,-22.3032,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.JEC.2,WRJEFFUN11_RA,-3.8182,-0.9209,-22.3269,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.JEC.3,WRJEFFUN12_RA,-3.9031,-1.0059,-22.3269,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-19.9842,-1.3649,-38.0490,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-30.0000,-1.4979,-47.9318,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-30.0000,-1.4979,-47.9318,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.LEC.4,WRLECUN26_RA,-10.1770,-0.3573,-29.2493,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.LEC.5,WRLECUN27_RA,-7.6725,-0.3252,-26.7770,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,-7.1112,-1.0929,-25.4480,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,-7.1112,-1.0929,-25.4480,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,-7.1112,-1.0929,-25.4480,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,-7.0597,-1.0550,-25.4344,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-19.0825,-1.6155,-36.8967,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-19.0825,-1.6155,-36.8967,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-10.8468,-1.2064,-29.0700,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-12.2698,-1.7880,-29.9115,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-12.2698,-1.7880,-29.9115,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-8.5525,-1.8531,-26.1291,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-19.0825,-1.6155,-36.8967,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,-1.5947,-1.4441,-19.5802,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,-5.6299,-1.4340,-23.6256,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-30.0082,-1.5060,-47.9318,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,75.2528,0.7062,55.1169,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-9.7757,-2.6370,-26.5684,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,-3.2497,-0.9207,-21.7587,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,-1.2656,-1.5332,-19.1620,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,-2.6537,-0.3379,-21.7455,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,-4.5870,-1.2297,-22.7870,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-10.7119,-1.1304,-29.0112,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.THAYERLD,WR.THAYERLD_LA,24.4525,0.4014,4.6214,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-11.5259,-1.1081,-29.8474,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0106,V106_DDR,-10.8709,-1.0705,-29.2300,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0139,WR.VOLT.0139_H,-14.3324,-0.1789,-33.5832,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0141,WR.VOLT.0141_H,-5.1566,-1.0768,-23.5095,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0146,WR.VOLT.0146_H,-10.6606,-0.2000,-29.8902,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0147,WR.VOLT.0147_H,-10.6606,-0.2000,-29.8902,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0148,WR.VOLT.0148_H,-8.6382,-0.2670,-27.8008,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-10.7707,-0.9274,-29.2730,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0157,V157_DDR,-10.4661,-0.2211,-29.6746,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0158,V158_DDR,-10.6606,-0.2000,-29.8902,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0159,WR.VOLT.0159_H,-10.6606,-0.2000,-29.8902,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-11.4560,-1.1781,-29.7076,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0173,V173_DDR,-7.5877,-1.2412,-25.7762,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0174,V174_DDR,-11.2503,-1.0807,-29.5993,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0184,V184_DDR,-10.7860,-1.2054,-29.0102,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-10.8505,-1.1154,-29.1647,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0186,V186_DDR,-10.5681,-1.1763,-28.8215,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-10.8560,-1.1683,-29.1173,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-11.4625,-1.0703,-29.8218,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0189,WR.VOLT.0189_H,-6.3374,-0.8841,-24.8829,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0190,WR.VOLT.0190_H,-4.1521,-0.8306,-22.7512,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0191,WR.VOLT.0191_H,-3.6803,-0.8612,-22.2487,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0192,WR.VOLT.0192_H,-3.6803,-0.8612,-22.2487,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0196,WR.VOLT.0196_H,-4.1521,-0.8306,-22.7512,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0245,V245_DDR,-10.8445,-1.1169,-29.1573,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.VOLT.0248,V248_DDR,-10.8709,-1.0705,-29.2300,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-15.6877,-1.3012,-33.8161,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,-3.4080,-0.5330,-22.3047,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.WOLF,WRWOLFUN15_RA,-2.2779,-1.6288,-20.0787,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-19.7213,-1.8014,-37.3496,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,13.7248,0.2252,-5.9301,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-15.9782,-1.4326,-33.9753,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-15.9782,-1.4326,-33.9753,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-15.9782,-1.4326,-33.9753,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-15.9782,-1.4326,-33.9753,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-13.5733,-1.0268,-31.9761,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,-5.1135,-1.0807,-23.4625,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-12.7071,-1.0918,-31.0450,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-12.7071,-1.0918,-31.0450,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-12.7071,-1.0918,-31.0450,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-12.7071,-1.0918,-31.0450,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,-4.3249,-0.7650,-22.9895,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,-4.3249,-0.7650,-22.9895,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,-4.3249,-0.7650,-22.9895,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,-4.3249,-0.7650,-22.9895,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,-4.3249,-0.7650,-22.9895,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,-4.3249,-0.7650,-22.9895,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-29.1789,-1.0876,-47.5210,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-29.1789,-1.0876,-47.5210,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-32.6709,-1.0775,-51.0230,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-32.6709,-1.0775,-51.0230,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_MIDW,WR_MIDW_LA,-11.6656,-1.5249,-29.5703,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,37.9827,0.1704,18.3826,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,22.9935,-0.0206,3.5845,19.4296\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-13.1482,-1.4418,-31.1361,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_SEG,WR_SEG_LA,17.2042,0.0656,-2.2911,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,WR_WR,WR_LA,-6.6283,-0.8303,-25.2277,19.4297\n03/19/2025 19:00:00,03/20/2025 00:00:00,YAD,VACS,31.0505,0.4491,11.1717,19.4297\n03/19/2025 20:00:00,03/20/2025 01:00:00,AEC,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,AECC_CSWS,CSWS_AECC_LA,60.9456,1.4955,24.7022,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,42.5746,0.9178,6.9089,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,94.9700,2.0118,58.2103,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,41.7729,0.5377,6.4872,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,50.8007,1.4620,14.5907,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,90.7331,0.8707,55.1145,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,47.2517,1.0825,11.4213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,AECI,AECI,40.2433,0.1447,5.3506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,AEPM_CSWS,CSWS_LA,47.3074,1.4850,11.0745,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,ALTW,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,AMRN,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,107.0586,0.1966,72.1140,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,BBA,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,BCA,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,BEPM.ER01.DDR,ER01_DDR,-1.6337,-5.1177,-31.2640,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,BEPM_ER01,BEPM_ER01_LA,-1.6337,-5.1177,-31.2640,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,-0.0480,-2.1999,-32.5960,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,3.7357,-0.6257,-30.3865,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,BEPM_UM01,BEPM_UM01_LA,32.5340,0.5395,-2.7535,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,BLKW,BLKW,114.2918,2.1094,77.4345,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-30.0000,-2.7778,-61.9701,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-30.0000,-2.7778,-61.9701,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,44.8976,-2.3786,12.5282,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.9365,-2.7143,-61.9701,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,BRAZ,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,BUBA,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-15.6580,-2.3890,-48.0170,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,-4.2555,-1.6646,-37.3388,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,-4.2555,-1.6646,-37.3388,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,-4.2555,-1.6646,-37.3388,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,-4.2555,-1.6646,-37.3388,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,-4.2555,-1.6646,-37.3388,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-3.2371,-1.7981,-36.1869,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,20.6185,-1.8286,-12.3008,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,20.6185,-1.8286,-12.3008,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CLEC,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,41.7832,0.5501,6.4851,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,COWP,COWP_LA,36.5614,0.5937,1.2198,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,36.5614,0.5937,1.2198,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,36.5614,0.5937,1.2198,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CPLE,VACS,56.0418,0.8449,20.4490,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CPLW,VACS,56.0418,0.8449,20.4490,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,56.0082,1.1979,20.0623,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,56.0082,1.1979,20.0623,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,56.0082,1.1979,20.0623,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,56.0082,1.1979,20.0623,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CRTH_SPA,WRCRTH_SPA_LA,41.8878,0.0161,7.1237,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,52.0230,3.4784,13.7967,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,22.4025,-1.0632,-11.2823,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,47.2517,1.0825,11.4213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,41.7729,0.5377,6.4872,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,51.9884,3.4552,13.7852,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,50.3621,2.4091,13.2050,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,51.5217,3.1848,13.5890,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,51.5217,3.1848,13.5890,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,41.5820,0.6859,6.1482,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,41.5820,0.6859,6.1482,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,41.3588,0.4626,6.1482,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,41.3588,0.4626,6.1482,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,47.2517,1.0825,11.4213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,49.3301,2.8082,11.7740,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,64.5929,-0.3280,30.1729,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,64.2735,-0.6473,30.1729,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,45.1820,0.1353,10.2988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,40.7230,0.3802,5.5949,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,40.7230,0.3802,5.5949,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,40.7250,0.3802,5.5968,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,40.7250,0.3802,5.5968,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-8.9914,-1.4885,-42.2508,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,29.4339,-0.8870,-4.4270,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,50.4673,0.7440,14.9754,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-0.2770,-1.6088,-33.4162,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-0.1586,-1.4903,-33.4162,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,8.6954,-0.7815,-25.2711,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.GRID.CDL1,CDL1_DDR,44.9418,0.8126,9.3812,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,15.1618,-1.4106,-18.1755,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,22.8843,-1.3578,-10.5059,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,44.9418,0.8126,9.3812,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.NUEN.CSI1,CSI1_DDR,41.9796,0.6256,6.6060,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.NUEN.CSI2,CSI2_DDR,41.9959,0.6419,6.6060,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,41.7908,0.5577,6.4851,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.NUEN.GAZA,GAZA_DDR,44.9418,0.8126,9.3812,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,87.7290,1.8218,51.1593,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.NUEN.T201,NT201_DDR,41.8813,0.4425,6.6909,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,15.8719,-1.6063,-17.2698,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,15.8719,-1.6063,-17.2698,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,47.2517,1.0825,11.4213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,51.2426,3.7902,12.7044,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,8.6954,-0.7815,-25.2711,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,8.6954,-0.7815,-25.2711,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,-0.6667,-1.4424,-33.9722,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-0.1586,-1.4903,-33.4162,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,50.8621,2.2503,13.8638,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,37.9510,0.1428,3.0603,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,37.4519,-0.3563,3.0603,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,37.4886,-0.3197,3.0603,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,27.5954,0.2833,-7.4359,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,27.5954,0.2833,-7.4359,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,50.1414,2.4008,12.9927,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,41.0943,0.5142,5.8322,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,50.1393,2.3348,13.0565,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,51.9639,4.6994,12.5165,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,46.8965,1.3577,10.7908,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,41.9959,0.6419,6.6060,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0057,OKMU_DDR,45.1618,0.8206,9.5932,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0060,LEHIGH_DDR,87.7290,1.8218,51.1593,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0086,WARRENM_DDR,41.3063,0.5295,6.0289,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,50.3991,3.4854,12.1658,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,53.8775,0.3891,18.7404,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0121,V121_DDR,50.1414,2.4008,12.9927,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0122,V122_DDR,52.0652,0.3653,16.9519,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0124,V124_DDR,75.2926,0.2083,40.3364,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0135,V135_DDR,42.3473,0.5572,7.0421,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0144,V144_DDR,30.1609,-0.7490,-3.8381,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0145,V145_DDR,30.3433,-0.9203,-3.4844,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,50.1949,2.4917,12.9552,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,47.3540,1.5564,11.0496,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0175,V175_DDR,41.7908,0.5577,6.4851,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,47.3540,1.5564,11.0496,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,47.7284,1.8044,11.1761,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,42.3473,0.5572,7.0421,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,42.7178,0.5016,7.4683,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,42.2673,0.4215,7.0979,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,59.8259,-0.0101,25.0881,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,40.7165,0.3590,5.6096,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,42.7178,0.5016,7.4683,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0211,V211_DDR,50.7666,2.8233,13.1953,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,55.3089,0.4016,20.1594,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0213,V213_DDR,42.1387,0.5158,6.8750,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0215,V215_DDR,53.5764,0.3797,18.4487,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0217,V217_DDR,55.3734,0.3719,20.2536,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0218,V218_DDR,59.2875,0.0163,24.5233,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0228,V228_DDR,42.0210,0.4136,6.8595,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0232,V232_DDR,41.6097,0.5562,6.3055,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0233,V233_DDR,42.8738,0.5395,7.5863,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0240,V240_DDR,49.7857,0.3088,14.7290,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0244,V244_DDR,42.7178,0.5016,7.4683,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0246,MDT1_DDR,87.7290,1.8218,51.1593,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0249,V249_DDR,42.1029,0.5483,6.8066,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0250,V250_DDR,21.4132,-0.9763,-12.3585,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0251,V251_DDR,41.3246,0.4463,6.1304,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.VOLT.0252,V252_DDR,59.8259,-0.0101,25.0881,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-14.8674,-1.4899,-48.1254,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,40.6348,-1.9241,7.8110,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-7.9435,-3.3891,-39.3023,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,49.6048,1.7535,13.1033,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-13.7324,-2.9863,-45.4940,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,26.1070,-0.9170,-7.7239,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,26.1070,-0.9170,-7.7239,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,26.1070,-0.9170,-7.7239,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,26.1070,-0.9170,-7.7239,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,26.1070,-0.9170,-7.7239,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,47.2517,1.0825,11.4213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,53.6929,3.2634,15.6816,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,41.5639,0.5104,6.3055,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,41.5117,0.4582,6.3055,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,48.7004,0.9741,12.9783,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,48.7004,0.9741,12.9783,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWWELSH1,CSWSWELSHUN1_RA,48.3038,1.9353,11.6206,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWWELSH3,CSWSWELSHUN3_RA,48.3038,1.9353,11.6206,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWWILKES1,CSWSWILKESUN1_RA,49.4178,2.4734,12.1964,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWWILKES2,CSWSWILKESUN2_RA,49.4178,2.4734,12.1964,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,CSWWILKES3,CSWSWILKESUN3_RA,49.4975,2.3435,12.4060,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-0.1323,-1.4640,-33.4162,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,DENL,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,DERS,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,DOE,DOE,46.2584,0.4272,11.0833,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,20.7646,-0.5268,-13.4566,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,DPC,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,DUK,VACS,56.0418,0.8449,20.4490,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDDY,EDDY,113.2608,3.4837,75.0292,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,39.8237,-0.2110,5.2867,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-0.8000,-0.7891,-34.7588,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,45.6285,-0.4912,11.3718,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE.SLCC,EDESTL4391_PLT,41.1123,-0.2352,6.5996,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,41.0576,-0.1250,6.4347,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,27.9944,-0.8586,-5.8949,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_EC_01,EDELAR3821UN1_RA,39.8237,-0.2110,5.2867,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_EC_02,EDELAR3821UN2_RA,39.8237,-0.2110,5.2867,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_EC_03,EDELAR3821UN3_RA,39.8237,-0.2110,5.2867,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_EC_04,EDELAR3821UN4_RA,39.8237,-0.2110,5.2867,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_EDE,EDE_LA,43.1903,0.5362,7.9061,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_ERW,EDEERWFUNG1_RA,-3.5494,-1.9141,-36.3833,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,2.3559,-2.5689,-29.8231,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,86.0000,1.1824,50.0697,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,86.0000,1.1824,50.0697,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,86.0000,1.1824,50.0697,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,86.0000,1.1824,50.0697,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,10.2408,0.9332,-25.4403,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_RIV_10,EDERIV1671UN10_RA,40.8930,-0.4430,6.5881,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_RIV_11,EDERIV1671UN11_RA,40.8930,-0.4430,6.5881,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_RIV_12,EDERIV453UN12_PLT,39.9094,-1.4266,6.5881,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_SL_01,EDESTL4391UN1_RA,41.1123,-0.2352,6.5996,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EDE_SWMP,EDE_SWMP_LA,38.5850,0.7958,3.0412,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,EEI,EEI,45.9282,0.4210,10.7593,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,EES,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,1.0819,-1.9989,-31.6671,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,ERCOTE,ERCOTE,48.3038,1.9353,11.6206,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,ERCOTN,ERCOTN,16.0244,-1.4538,-17.2698,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,11.1732,-2.1592,-21.4156,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,FMPP,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,FPC,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,FPL,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,FREM_50T,OPPDFREM_GUN1_RA,20.7681,-1.7944,-12.1854,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,FREM_6,OPPDFREM_AUN6_RA,20.7567,-1.8091,-12.1821,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,FREM_7,OPPDFREM_AUN7_RA,20.7567,-1.8091,-12.1821,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,FREM_8,OPPDFREM_AUN8_RA,20.5799,-1.9859,-12.1821,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,FREM_LOAD,FREM_LOAD_LA,20.7283,-1.8376,-12.1821,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-3.7457,-1.6243,-36.8694,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,50.8593,2.2476,13.8638,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-13.2352,-3.1553,-44.8279,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-24.3384,-2.7091,-56.3772,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,41.7832,0.5501,6.4851,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,41.7832,0.5501,6.4851,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,41.7832,0.5501,6.4851,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,42.5805,0.1936,7.6390,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,42.5805,0.1936,7.6390,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,42.7771,0.1848,7.8443,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,42.7771,0.1848,7.8443,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-13.4012,-2.4415,-45.7076,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,48.5500,-0.1877,13.9898,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,48.5500,-0.1877,13.9898,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,48.5500,-0.1877,13.9898,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.VOLT.0130,V130_DDR,42.1558,0.5685,6.8394,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA.VOLT.0237,V237_DDR,41.2687,0.3341,6.1866,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDAHUB2,GRDAHUB2_H,29.0410,-0.4334,-5.2736,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDAHUB3,GRDAHUB3_H,23.4151,-0.6783,-10.6545,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA_GRDA,GRDA_LA,41.3202,0.3704,6.2019,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA_HUB,GRDA_H,35.8944,-0.1222,1.2686,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRDA_HUBSA,GRDASA_H,35.0799,-0.1647,0.4966,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GRE,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,18.1800,1.8527,-18.4206,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GSEC_SPS,SPS_GSEC_LA,79.9644,0.6357,44.5807,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GSPR2014HUB,GSPR2014HUB_H,58.4541,0.4052,23.3010,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,GSPR2015HUB,GSPR2015HUB_H,56.4237,0.2987,21.3770,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,24.8325,-0.8981,-9.0173,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,HARRISON,CSWSLEBROCKPLT1,49.8933,2.0073,13.1381,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,HAST_TNSK_HUB,HAST_TNSK_H,9.9070,-2.4693,-22.3717,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,HQST,PJM,37.1210,-0.1882,2.5612,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,HST,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,70.4829,0.0789,35.6561,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,70.4829,0.0789,35.6561,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,68.3267,0.0767,33.5020,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,68.3267,0.0767,33.5020,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,72.7094,0.0857,37.8757,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,72.7094,0.0857,37.8757,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,INDN_INDN,INDN_LA,69.9749,0.0986,35.1284,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-13.3300,-2.9282,-45.1497,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,ISNE,PJM,37.1210,-0.1882,2.5612,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,JEA,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,20.9293,-1.6568,-12.1618,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,20.9293,-1.6568,-12.1618,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,2.2650,-0.5522,-31.9307,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KACYCT4,KACYNEARMANUNCT4_RA,40.7078,-0.1154,6.0752,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,74.1010,-0.2891,39.6422,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,40.7078,-0.1154,6.0752,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,39.9044,-0.0747,5.2311,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,40.1282,-0.0821,5.4624,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KACY_KACY,KACY_LA,39.7600,-0.0919,5.1040,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,32.1783,-0.3753,-2.1944,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,64.4328,0.8612,28.8236,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-10.9300,-1.6804,-43.9975,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-37.9510,-2.6949,-70.0040,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.VOLT.0222,V222_DDR,15.0833,-0.6625,-19.0021,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.VOLT.0223,V223_DDR,22.1670,-0.5291,-12.0518,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.VOLT.0241,V241_DDR,52.3549,0.6051,17.0019,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.VOLT.0243,V243_DDR,34.3069,-0.0148,-0.4262,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.VOLT.0247,V247_DDR,39.0521,-0.2610,4.5652,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.VOLT.0253,V253_DDR,32.6438,-0.3646,-1.7396,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,4.6581,-2.7133,-27.3765,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,19.4620,-0.8545,-14.4314,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,19.4620,-0.8545,-14.4314,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,19.4620,-0.8545,-14.4314,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,19.4620,-0.8545,-14.4314,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,32.0709,-0.3850,-2.2921,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,32.0709,-0.3850,-2.2921,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHUB,KCPLHUB_H,10.1112,-1.6462,-22.9905,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHUB17,KCPLHUB17_H,8.3039,-1.7808,-24.6633,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHUB18,KCPLHUB18_H,7.8175,-1.8073,-25.1231,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHUB19,KCPLHUB19_H,7.5218,-1.7425,-25.4836,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHUB20,KCPLHUB20_H,6.6679,-1.8437,-26.2363,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHUB21,KCPLHUB21_H,6.2656,-1.7892,-26.6931,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHUB22,KCPLHUB22_H,7.2098,-1.7882,-25.7499,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHUB23,KCPLHUB23_H,6.7470,-1.8331,-26.1678,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLHUB24,KCPLHUB24_H,5.7022,-1.8834,-27.1624,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,11.2010,-0.6933,-22.8536,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,11.2010,-0.6933,-22.8536,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,14.3933,-1.3863,-18.9684,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,14.3933,-1.3863,-18.9684,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,32.1806,-0.3729,-2.1944,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,32.1783,-0.3753,-2.1944,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,33.6888,-0.2535,-0.8056,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,33.6888,-0.2535,-0.8056,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,33.6888,-0.2535,-0.8056,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,33.6888,-0.2535,-0.8056,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,33.6888,-0.2535,-0.8056,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,33.6888,-0.2535,-0.8056,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,33.6888,-0.2535,-0.8056,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,33.6888,-0.2535,-0.8056,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,11.2082,-0.8507,-22.6890,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,35.0034,-0.2949,0.5504,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KCPL_KCPL,KCPL_LA,32.0497,-0.3409,-2.3574,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KENN,KENN_LA,19.1179,0.8514,-16.4815,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KEP2_SECI,KEP2_SECI_LA,-17.4572,-1.6996,-50.5055,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KERR_1,GRDAKERR_HYDUN1_RA,41.1352,0.2649,6.1223,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KERR_2,GRDAKERR_HYDUN2_RA,41.2201,0.2721,6.2001,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KERR_3,GRDAKERR_HYDUN3_RA,41.2201,0.2721,6.2001,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KERR_4,GRDAKERR_HYDUN4_RA,41.1352,0.2649,6.1223,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,19.4618,-0.8547,-14.4314,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,19.4618,-0.8547,-14.4314,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,21.3625,-0.6644,-12.7210,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,21.3625,-0.6644,-12.7210,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,16.7279,-0.8343,-17.1857,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,14.7952,-0.7578,-19.1949,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,14.7952,-0.7578,-19.1949,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-14.5399,-1.9082,-47.3796,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-14.5399,-1.9082,-47.3796,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-14.5399,-1.9082,-47.3796,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,-2.5103,-2.1705,-35.0878,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,-2.5103,-2.1705,-35.0878,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-15.1027,-1.9935,-47.8572,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,-4.4783,-2.1491,-37.0772,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,3.8225,-1.5125,-29.4129,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,65.8543,-0.3493,31.4556,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,65.8543,-0.3493,31.4556,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,7.6033,-1.4947,-25.6499,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,7.6033,-1.4947,-25.6499,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,7.6033,-1.4947,-25.6499,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-5.7302,-2.8250,-37.6531,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-1.0214,-3.2785,-32.4908,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,11.7385,-1.6010,-21.4085,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,1.3212,-0.4405,-32.9862,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,LAFA,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LAM345,LAM345,-15.6580,-2.3890,-48.0170,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LEPA,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,16.4401,-1.8413,-16.4666,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_LES,LES_LA,16.5317,-1.8614,-16.3548,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,17.4025,-1.8820,-15.4635,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,16.0949,-1.9622,-16.6909,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,16.0949,-1.9622,-16.6909,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,16.0949,-1.9622,-16.6909,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,17.4036,-1.8808,-15.4635,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,17.4025,-1.8820,-15.4635,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_WAVERLY,LES_WAVERLY_H,17.1943,-1.9212,-15.6324,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,20.1658,-1.9002,-12.6820,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,20.1658,-1.9002,-12.6820,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,LGEE,LGEE,42.3620,0.1159,7.4982,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MALDEN,MALDEN_LA,21.4717,0.7889,-14.0651,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MCWEST,MCWEST,36.3775,-0.0470,1.6765,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MDU,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,2.5901,-0.8175,-31.3403,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,13.4557,-1.3066,-19.9856,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,20.5176,-0.2099,-14.0204,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MEAN_NPPD,NPPD_MEAN_LA,5.7298,-2.6108,-26.4073,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MEC,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MHEB,MHEB,16.9826,-0.7642,-17.0012,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-9.8895,-3.3534,-41.2840,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-6.3902,-3.3097,-37.8284,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-9.8895,-3.3534,-41.2840,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-9.8895,-3.3534,-41.2840,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-6.3902,-3.3097,-37.8284,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-5.5460,-1.5282,-38.7657,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MISO,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-16.5844,-1.3638,-49.9686,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-16.5844,-1.3638,-49.9686,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,5.0350,-2.2576,-27.4554,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-15.9603,-2.8860,-47.8222,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,-4.2157,-2.9160,-36.0477,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-16.0507,-2.5474,-48.2512,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-12.4322,-2.1968,-44.9833,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-15.9954,-2.3865,-48.3568,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-10.9955,-2.0687,-43.6748,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-10.9955,-2.0687,-43.6748,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-10.9955,-2.0687,-43.6748,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-10.9955,-2.0687,-43.6748,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-10.9955,-2.0687,-43.6748,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,35.3336,-0.5958,1.1815,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,37.8426,0.2758,2.8189,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,37.8426,0.2758,2.8189,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,36.2016,-0.1345,1.5881,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,48.9244,0.7436,13.4328,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MOWR,AECI,40.2433,0.1447,5.3506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,36.2107,-0.1378,1.6006,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,38.1623,0.3032,3.1111,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,1.9114,-2.5429,-30.2936,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-8.7878,-1.6221,-41.9137,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-28.5170,-2.6913,-60.5736,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,2.0293,-2.4250,-30.2936,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,20.7826,-0.5087,-13.4566,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,20.7826,-0.5087,-13.4566,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,20.7833,-0.5080,-13.4566,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,20.7833,-0.5080,-13.4566,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,15.0833,-0.6625,-19.0021,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,15.0833,-0.6625,-19.0021,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,15.0833,-0.6625,-19.0021,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,14.9718,-0.7740,-19.0021,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,15.0833,-0.6625,-19.0021,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,15.0833,-0.6625,-19.0021,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,15.0833,-0.6625,-19.0021,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,36.8169,0.6386,1.4304,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,27.4061,-0.4754,-6.8664,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,19.3611,-0.6024,-14.7844,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,19.3612,-0.6023,-14.7844,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,19.3612,-0.6023,-14.7844,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,34.7460,-0.3519,0.3500,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,34.7460,-0.3519,0.3500,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MPS_MPS,MPS_LA,40.3060,-0.2125,5.7705,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,MSTNG,SPSMSTNGPLT1,111.3230,2.5875,73.9876,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MSTNG4,SPSMSTNGUN4_RA,111.1549,2.4194,73.9876,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MSTNG5,SPSMSTNGUN5_RA,111.2011,2.4656,73.9876,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,111.3230,2.5875,73.9876,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NBSO,PJM,37.1210,-0.1882,2.5612,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,13.3938,-2.5245,-18.8296,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,13.3951,-2.5233,-18.8296,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,16.2652,-2.3086,-16.1741,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NHC1,VACS,56.0418,0.8449,20.4490,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,21.1009,-1.7552,-11.8919,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,21.1009,-1.7552,-11.8919,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,21.1009,-1.7552,-11.8919,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-1.2735,-2.9839,-33.0375,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,8.7270,-3.4555,-22.5655,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,12.9103,-2.4902,-19.3475,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-6.8569,-2.6419,-38.9629,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,8.7270,-3.4555,-22.5655,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.HUB.PY2018,NPPDPY18_H,8.1113,-2.4284,-24.2083,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,8.4112,-2.4325,-23.9042,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,8.2838,-2.4151,-24.0490,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,8.5629,-2.4034,-23.7816,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-9.9700,-2.7838,-41.9341,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,4.6968,-2.1089,-27.9422,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,4.6968,-2.1089,-27.9422,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,-0.6571,-2.7940,-32.6110,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-9.9700,-2.7838,-41.9341,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,11.3767,-4.4869,-18.8844,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,5.3038,-3.4631,-25.9810,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,0.5472,-1.6825,-32.5183,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,5.3038,-3.4631,-25.9810,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,6.2609,-3.4092,-25.0778,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,4.8564,-2.9562,-26.9353,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,14.9110,-1.6324,-18.2045,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,8.7270,-3.4555,-22.5655,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,1.1717,-1.8251,-31.7512,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,4.6968,-2.1089,-27.9422,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,4.6968,-2.1089,-27.9422,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,6.1351,-1.8997,-26.7132,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,6.0157,-1.8966,-26.8356,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,6.0157,-1.8966,-26.8356,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,7.6369,-1.6793,-25.4317,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-10.9700,-1.9074,-43.8105,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,9.5559,-2.9686,-22.2234,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-1.2084,-2.6348,-33.3216,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-4.5009,-1.7285,-37.5203,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-7.7200,-1.8067,-40.6612,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.NELI.DDR,NELI_DDR,-7.6141,-3.3632,-38.9988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.NPPM.1058,SH1058_DDR,26.6221,-2.0414,-6.0845,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,7.6196,-1.9483,-25.1800,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,8.7270,-3.4555,-22.5655,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,12.9103,-2.4902,-19.3475,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-9.9700,-2.7838,-41.9341,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.TECH.1,KEARNE_DDR,8.2264,-1.5608,-24.9607,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,6.6914,-4.2597,-23.7968,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,6.6914,-4.2597,-23.7968,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-9.6220,-3.2324,-41.1376,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD.VOLT.0236,V236_DDR,14.1572,-1.7041,-18.8866,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD2017HUB,NPPD2017HUB_H,8.1882,-2.4223,-24.1374,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,23.2257,-2.7965,-8.7257,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-1.2735,-2.9839,-33.0375,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,4.9010,-4.0215,-25.8254,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,4.9010,-4.0215,-25.8254,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,14.3242,-1.7677,-18.6561,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,14.1839,-1.6774,-18.8866,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-9.8222,-2.7016,-41.8685,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,6.2290,-1.9894,-26.5295,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,25.9406,-2.7228,-6.0845,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,25.9406,-2.7228,-6.0845,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,25.9406,-2.7228,-6.0845,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,9.9415,-2.4678,-22.3386,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,14.2071,-2.4702,-18.0706,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,10.7641,-2.3212,-21.6626,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-6.9590,-4.8736,-36.8333,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-6.7810,-4.6957,-36.8333,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,3.2373,-2.1783,-29.3324,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,2.9580,-2.2088,-29.5811,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,10.7065,-2.3533,-21.6881,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,10.6752,-2.3846,-21.6881,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,10.6752,-2.3846,-21.6881,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,10.6134,-2.3239,-21.8106,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,11.3767,-4.4869,-18.8844,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,10.5432,-2.3280,-21.8767,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,15.0145,-2.1353,-17.5981,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,9.9417,-2.3918,-22.4144,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,9.9096,-2.4095,-22.4288,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,9.9135,-2.3927,-22.4418,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,9.9135,-2.3927,-22.4418,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,9.9415,-2.4678,-22.3386,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,9.8767,-2.5326,-22.3386,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,-0.2124,-2.1746,-32.7857,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,12.0145,-2.0314,-20.7021,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,2.8191,-2.0558,-29.8730,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,-0.0035,-4.3955,-30.3559,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,0.1347,-1.8382,-32.7751,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,27.0916,-1.5718,-6.0845,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-7.6141,-3.3632,-38.9988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,3.5482,-2.1385,-29.0612,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,3.5482,-2.1385,-29.0612,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_NPPD,NPPD_LA,11.0539,-2.2038,-21.4903,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,15.0145,-2.1353,-17.5981,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,15.0145,-2.1353,-17.5981,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,11.0384,-2.3712,-21.3383,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,5.5922,-2.7123,-26.4435,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NSB,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,NSP,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NSSO,PJM,37.1210,-0.1882,2.5612,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,NYIS,PJM,37.1210,-0.1882,2.5612,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-15.2456,-2.7527,-47.2409,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-14.1427,-2.4962,-46.3944,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-15.9972,-2.2964,-48.4487,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-15.9972,-2.2964,-48.4487,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-22.3995,-2.9443,-54.2031,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-24.3384,-2.7091,-56.3772,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-96.5330,-1.4409,-129.8401,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-40.9208,-2.6568,-73.0120,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-15.3948,-2.4221,-47.7207,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-14.0138,-2.6160,-46.1457,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,6.9859,-0.7821,-26.9800,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-15.3948,-2.4221,-47.7207,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-20.3997,-2.9389,-52.2088,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-5.5460,-1.5282,-38.7657,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-12.8827,-2.7563,-44.8743,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,34.7400,-0.0247,0.0168,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-14.0138,-2.6160,-46.1457,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-10.6190,-2.1491,-43.2178,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-10.2400,-2.2782,-42.7097,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,-4.2555,-1.6646,-37.3388,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-20.5709,-0.1905,-55.1283,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-5.5460,-1.5282,-38.7657,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-5.5460,-1.5282,-38.7657,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-14.0138,-2.6160,-46.1457,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.NUEN.ADA1,ADA1_DDR,-2.1995,-1.3122,-35.6352,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.NUEN.LAM1,LAM1_DDR,84.3522,2.3143,47.2900,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.NUEN.MDT2,MDT2_DDR,6.9891,-0.7788,-26.9800,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.NUEN.MDT3,MDT3_DDR,6.9891,-0.7788,-26.9800,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.NUEN.WWO1,WWO1_DDR,-2.9372,-1.1917,-36.4935,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,5.5580,-0.8121,-28.3779,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,5.5580,-0.8121,-28.3779,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,5.5580,-0.8121,-28.3779,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,8.4495,-0.6596,-25.6389,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,8.4495,-0.6596,-25.6389,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,5.5580,-0.8121,-28.3779,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,5.5580,-0.8121,-28.3779,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-14.0138,-2.6160,-46.1457,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,40.7581,1.3341,4.6761,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-20.3997,-2.9389,-52.2088,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-9.9700,-0.4202,-44.2977,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-10.6190,-2.1491,-43.2178,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,86.6720,1.6910,50.2330,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-7.5674,-1.6579,-40.6574,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-7.5674,-1.6579,-40.6574,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-7.5674,-1.6579,-40.6574,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-7.5674,-1.6579,-40.6574,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-19.3962,-3.5835,-50.5607,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-16.9513,-2.2704,-49.4288,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-14.1427,-2.4962,-46.3944,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-20.3400,-2.1875,-52.9004,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-20.3400,-2.1875,-52.9004,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-5.9107,0.2288,-40.8874,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-6.3505,-1.8290,-39.2694,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-6.3505,-1.8290,-39.2694,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-6.3505,-1.8290,-39.2694,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0033,FOSTER_DDR,12.9745,-0.5559,-21.2175,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,27.1097,0.6606,-8.2989,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0035,TARBY_DDR,85.3379,1.8485,48.7415,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,27.1097,0.6606,-8.2989,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,25.5067,0.3483,-9.5896,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,25.5067,0.3483,-9.5896,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-14.2343,0.0397,-49.0220,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0040,TROSPER_DDR,14.6601,-0.5158,-19.5720,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,14.3294,-0.5208,-19.8977,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,89.3943,1.9450,52.7013,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0115,V115_DDR,7.6148,-0.7407,-26.3924,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0116,V116_DDR,58.7392,0.4454,23.5459,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0118,V118_DDR,24.7555,0.1715,-10.1639,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0125,V125_DDR,86.1687,2.1784,49.2423,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0126,V126_DDR,20.0543,0.8700,-15.5636,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0129,V129_DDR,15.1638,-1.4086,-18.1755,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,26.2328,-0.7047,-7.8104,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0134,V134_DDR,-11.8254,1.1960,-47.7693,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0138,V138_DDR,28.1081,0.7030,-7.3428,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,23.1544,-0.5382,-11.0553,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0143,V143_DDR,31.3145,0.4555,-3.8889,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0149,V149_DDR,-0.7142,-1.3950,-34.0672,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0150,V150_DDR,-0.4276,-1.4242,-33.7513,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0155,V155_DDR,29.6846,0.5363,-5.5996,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0156,V156_DDR,26.2328,-0.7047,-7.8104,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0166,V166_DDR,36.5771,1.7736,0.0556,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,22.7882,-0.5537,-11.4060,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,-0.4276,-1.4242,-33.7513,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0170,V170_DDR,-3.2265,-1.1788,-36.7956,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-4.9083,-1.3960,-38.2603,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0176,V176_DDR,-0.4276,-1.4242,-33.7513,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0177,V177_DDR,-18.1208,-2.9381,-49.9306,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,19.4098,-0.5548,-14.7834,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,-4.9813,-1.8166,-37.9126,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0195,V195_DDR,155.6322,2.8954,117.9888,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0197,V197_DDR,38.2042,1.0997,2.3566,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0198,V198_DDR,36.5771,1.7736,0.0556,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0208,V208_DDR,155.7469,2.9584,118.0406,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0209,V209_DDR,155.7469,2.9584,118.0406,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,37.2213,0.7837,1.6897,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0216,V216_DDR,14.2439,-0.5238,-19.9802,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0219,V219_DDR,29.6846,0.5363,-5.5996,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0220,V220_DDR,-0.4276,-1.4242,-33.7513,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0224,V224_DDR,7.0463,-0.7245,-26.9772,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0225,V225_DDR,7.0480,-0.7227,-26.9772,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0226,V226_DDR,7.0463,-0.7245,-26.9772,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0227,V227_DDR,7.0463,-0.7245,-26.9772,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0229,V229_DDR,-11.1719,0.1872,-46.1071,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0231,V231_DDR,23.3329,0.4878,-11.9028,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0238,V238_DDR,-20.4298,-2.6891,-52.4886,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.VOLT.0242,V242_DDR,29.0927,0.6173,-6.2725,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-15.0800,-3.5924,-46.2355,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-5.5460,-1.5282,-38.7657,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-14.2264,-2.3370,-46.6374,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-12.8523,-2.7259,-44.8743,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-15.0800,-3.5924,-46.2355,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-12.8879,-2.7162,-44.9196,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-46.9011,-2.4647,-79.1843,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEHL7,OKGEHL7_H,20.8904,-0.5222,-13.3354,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEHL8,OKGEHSL1UN8_RA,20.8904,-0.5222,-13.3354,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEHL910,OKGEHSL1PLT2,20.8904,-0.5222,-13.3354,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-12.8101,-2.7689,-44.7891,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEMCC,OKGEMCCLAIPLT1,6.2438,-1.0060,-27.4981,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,34.4430,0.3544,-0.6593,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,34.4430,0.3544,-0.6593,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,34.3535,0.2649,-0.6593,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,16.4333,-1.0383,-17.2764,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,16.4333,-1.0383,-17.2764,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,16.4333,-1.0383,-17.2764,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,16.4333,-1.0383,-17.2764,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGESM1,OKGESEMINOLEUN1_RA,20.6111,-0.3744,-13.7625,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGESM2,OKGESEMINOLEUN2_RA,16.8676,-0.4450,-17.4353,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGESM3,OKGESEMINOLEUN3_RA,16.8676,-0.4450,-17.4353,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGESO1,OKGESONR1UN1_RA,-44.8406,-1.9949,-77.5936,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGESO2,OKGESONR1UN2_RA,-20.3400,-2.1875,-52.9004,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-12.8101,-2.7689,-44.7891,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-10.4537,-2.5647,-42.6369,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGETINK5A,OKGETINK5UN1_RA,14.2939,-0.5711,-19.8830,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGETINK5B,OKGETINK5UN2_RA,14.2939,-0.5711,-19.8830,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-9.9697,-2.3970,-42.3207,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-14.1427,-2.4962,-46.3944,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,92.5920,2.4467,55.3974,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-5.5460,-1.5282,-38.7657,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE_OKGE,OKGE_LA,25.4438,-0.1798,-9.1244,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-9.9700,-0.4202,-44.2977,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-10.0887,-2.5160,-42.3207,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMLP,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,44.3631,0.2331,9.3820,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,94.5126,2.1772,57.5875,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_GENHUB,OMPA_GENHUB_H,3.3675,-0.7602,-30.6202,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-96.2283,-1.1362,-129.8401,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,-7.9261,-2.1695,-40.5045,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-15.3948,-2.4221,-47.7207,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-13.3643,-2.5143,-45.5979,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,8.0149,-2.6602,-24.0728,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,209.0000,0.2513,174.0008,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-96.3267,-1.2345,-129.8401,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-96.3267,-1.2345,-129.8401,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_SPP,OMPA_SPP_LA,1.6461,-1.0827,-32.0191,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-15.0800,-3.5924,-46.2355,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,40.4185,0.1718,5.4988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,40.4185,0.1718,5.4988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,40.4185,0.1718,5.4988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,40.4185,0.1718,5.4988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,ONT,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,21.1915,-1.7747,-11.7817,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,21.1915,-1.7747,-11.7817,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,21.1915,-1.7747,-11.7817,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,21.1915,-1.7747,-11.7817,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,21.1915,-1.7747,-11.7817,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,21.1915,-1.7747,-11.7817,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,21.1915,-1.7747,-11.7817,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,21.1915,-1.7747,-11.7817,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,21.1915,-1.7747,-11.7817,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,21.0835,-1.7223,-11.9422,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,21.1009,-1.7552,-11.8919,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,20.6048,-1.4931,-12.6500,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,20.7099,-1.6676,-12.3704,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,20.7099,-1.6676,-12.3704,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD_GLDN,OPPD_GLDN_LA,20.7430,-1.7510,-12.2539,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,21.3153,-1.7470,-11.6856,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,11.3767,-4.4869,-18.8844,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,16.2924,-2.0807,-16.3749,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,21.1005,-1.7545,-11.8929,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD_OPPD,OPPD_LA,21.0700,-1.6739,-12.0040,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,20.7841,-1.6300,-12.3338,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,20.7596,-1.6408,-12.3475,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,OTP,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,OVEC,OVEC,40.2978,0.0015,5.5484,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PARAGOULD,PARAGOULD_LA,15.3100,0.9505,-20.3885,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,42.6425,0.0380,7.8565,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,42.6425,0.0380,7.8565,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,42.6425,0.0380,7.8565,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,41.7165,0.1640,6.8045,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,41.7165,0.1640,6.8045,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,41.7165,0.1640,6.8045,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PIGGOTT,PIGGOTT_LA,19.9558,0.8292,-15.6213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PJM,PJM,37.1210,-0.1882,2.5612,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PLUM,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,POPLARBLUFF,POPLARBLUFF_LA,27.9972,0.6303,-7.3810,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,36.8363,-0.3965,2.4849,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,36.8363,-0.3965,2.4849,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,35.0177,-0.3845,0.6543,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,35.0177,-0.3845,0.6543,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,34.9402,1.4496,-1.2574,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,34.9402,1.4496,-1.2574,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,36.1732,-0.0430,1.4682,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,44.0312,-1.0681,10.3513,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-3.2371,-1.7981,-36.1869,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,102.3300,0.1902,67.3919,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,18.1556,-0.4884,-16.1039,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,18.1571,0.0849,-16.6758,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,50.9000,1.0430,15.1090,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,42.3689,0.9041,6.7169,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,10.0492,-1.8640,-22.8348,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,31.5320,-0.1984,-3.0175,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,6.3811,-2.5178,-25.8491,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,36.8286,1.7726,0.3081,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,18.9950,-0.4669,-15.2860,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,7.9954,-1.6002,-25.1523,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,PUPP,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,RCEAST,RCEAST,-4.1134,-2.4233,-36.4380,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SALINA_1,GRDASALINA1UN1_RA,41.1384,0.2682,6.1223,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SALINA_2,GRDASALINA1UN2_RA,41.1384,0.2682,6.1223,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SALINA_3,GRDASALINA1UN3_RA,41.1384,0.2682,6.1223,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SALINA_4,GRDASALINA1UN4_RA,41.1384,0.2682,6.1223,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SALINA_5,GRDASALINA1UN5_RA,41.1384,0.2682,6.1223,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SALINA_6,GRDASALINA1UN6_RA,41.1384,0.2682,6.1223,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SARPY_1,OPPDSARPYUN1_RA,20.6782,-1.7136,-12.3561,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SARPY_2,OPPDSARPYUN2_RA,20.6545,-1.6522,-12.4412,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SARPY_3,OPPDSARPYUN3_RA,20.5574,-1.7851,-12.4054,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SARPY_4,OPPDSARPYUN4_RA,20.5574,-1.7851,-12.4054,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SARPY_5,OPPDSARPYUN5_RA,20.5574,-1.7851,-12.4054,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SC,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SCEG,VACS,56.0418,0.8449,20.4490,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SCSE,SCSE,2.8741,-1.6279,-30.2459,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SEC,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-19.1660,-3.1143,-50.7996,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-19.1660,-3.1143,-50.7996,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-19.1660,-3.1143,-50.7996,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-14.4062,-1.0481,-48.1060,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-19.1660,-3.1143,-50.7996,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-16.3288,-2.7650,-48.3118,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-14.1449,-3.0774,-45.8154,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-14.1449,-3.0774,-45.8154,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-10.9997,-2.0729,-43.6748,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-21.5348,-2.8059,-53.4769,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,-2.6470,-2.3071,-35.0878,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-15.5934,-1.3908,-48.9506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-7.9458,-2.1082,-40.5856,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-18.3386,-3.0908,-49.9957,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-7.8456,-2.1099,-40.4836,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-27.2200,-3.5039,-58.4640,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-15.0291,-1.9571,-47.8200,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-14.8198,-2.0721,-47.4956,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-14.8198,-2.0721,-47.4956,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-14.8198,-2.0721,-47.4956,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-14.8198,-2.0721,-47.4956,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-15.3262,-2.2582,-47.8159,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-16.3288,-2.7650,-48.3118,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI_SECI,SECI_LA,-13.0920,-1.8972,-45.9427,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-13.3300,-2.9282,-45.1497,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-13.3300,-2.9282,-45.1497,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-10.9997,-2.0729,-43.6748,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SEHA,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-10.0887,-2.5160,-42.3207,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SERU,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SETH,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SGE,SGE,2.0123,-1.5434,-31.1923,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SMEP,MISO,34.1394,-0.0585,-0.5501,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SOCO,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPA,SPA,49.7270,1.0412,13.9379,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPC,SPC,29.6868,0.3548,-5.4159,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPPNORTH_HUB,SPPNORTH_H,16.1750,-1.9257,-16.6472,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPPSOUTH_HUB,SPPSOUTH_H,10.9000,-1.2073,-22.6407,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,40.2898,0.7789,4.7630,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,40.2898,0.7789,4.7630,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,40.1537,0.6885,4.7173,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,40.1537,0.6885,4.7173,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_NIXA,SPRM_NIXA_LA,40.5211,0.8174,4.9557,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_SPRM,SPRM_LA,40.3739,0.8831,4.7428,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,40.1278,0.5944,4.7855,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,40.1278,0.5944,4.7855,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,40.0422,0.5087,4.7855,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,40.1278,0.5944,4.7855,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,113.4313,1.6132,77.0702,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,117.8423,0.7753,82.3190,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,16.0086,-1.1492,-17.5901,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,16.0086,-1.1492,-17.5901,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,108.7511,-1.1494,75.1526,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,111.6274,1.8288,75.0506,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,113.4871,1.1518,77.5874,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,113.3758,3.0593,75.5685,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,108.2000,0.0632,73.3889,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,111.4923,2.4064,74.3380,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,111.8967,2.7793,74.3695,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,111.8967,2.7793,74.3695,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,111.4923,2.4064,74.3380,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,16.2798,-1.0433,-17.4248,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,117.8423,0.7753,82.3190,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,15.5306,-0.9425,-18.2749,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-7.5514,-2.6930,-39.6063,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,7.3562,-0.8562,-26.5356,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,14.2614,-0.1210,-20.3655,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,12.4085,-0.9829,-21.3566,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-25.0000,-2.8900,-56.8579,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-25.0000,-2.8900,-56.8579,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-25.0000,-2.8900,-56.8579,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-25.0000,-2.8900,-56.8579,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GRID.WRAB,WRAB_DDR,23.0812,0.7007,-12.3674,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-25.0000,-2.8900,-56.8579,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,107.0586,0.1966,72.1140,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,107.0586,0.1966,72.1140,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,104.2469,0.2793,69.2197,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,104.2469,0.2793,69.2197,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,104.2469,0.2793,69.2197,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,107.0586,0.1966,72.1140,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,24.3338,-0.9770,-9.4372,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,24.3289,-0.9769,-9.4422,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,24.3450,-0.9769,-9.4260,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,16.2652,-2.3086,-16.1741,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,111.5301,2.4615,74.3206,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,108.1603,0.0461,73.3662,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,108.1603,0.0461,73.3662,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,108.1603,0.0461,73.3662,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,108.1603,0.0461,73.3662,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,111.8074,2.8641,74.1953,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,111.4227,2.3452,74.3296,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,111.4227,2.3452,74.3296,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-9.9806,-2.4078,-42.3207,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,22.8332,-1.0093,-10.9054,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,22.8332,-1.0093,-10.9054,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,24.1079,-0.9720,-9.6680,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,23.0812,0.7007,-12.3674,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,-5.0333,-2.1324,-37.6488,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,12.3532,-1.1779,-21.2169,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-22.3995,-2.9443,-54.2031,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,23.3427,-0.4998,-10.9054,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.PLANTX1,SPS.PLANTX1_H,115.0011,1.2811,78.9721,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.PLANTX2,SPS.PLANTX2_H,115.0011,1.2811,78.9721,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,114.6662,1.2557,78.6626,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,108.8126,-0.6790,74.7437,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-15.2994,-2.5525,-47.4949,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,114.0071,1.6718,77.5874,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,108.8865,-0.6051,74.7437,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,16.3446,-0.9785,-17.4248,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,113.1756,1.8324,76.5953,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,113.5690,3.2526,75.5685,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,113.1756,1.8324,76.5953,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,113.9486,2.6933,76.5074,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-79.1637,-1.2794,-112.6323,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,114.1024,4.8671,74.4874,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,114.3060,5.0706,74.4874,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,113.7321,4.5510,74.4332,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,115.7000,2.7992,78.1529,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,114.0441,4.5499,74.7463,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-15.6580,-2.3890,-48.0170,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,23.0657,0.5755,-12.2577,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,113.8260,1.4379,77.6402,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,113.8260,1.4379,77.6402,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,113.1756,1.8324,76.5953,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,108.4450,0.2392,73.4579,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,112.4983,3.6511,74.0993,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,115.8051,3.4250,77.6322,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,114.5188,2.1502,77.6207,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,115.0358,0.4857,79.8022,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,114.1024,4.8671,74.4874,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,114.9521,5.5719,74.6323,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,114.4186,5.0383,74.6323,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,109.1957,-0.2959,74.7437,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,115.0032,2.6640,77.5912,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-13.0216,-2.3658,-45.4038,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-13.0354,-2.4276,-45.3558,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0163,V163_DDR,24.3896,-0.5120,-9.8464,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0168,V168_DDR,6.3015,-0.8765,-27.5700,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0180,V180_DDR,114.9521,5.5719,74.6323,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0181,V181_DDR,-13.8980,-2.0431,-46.6028,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0182,V182_DDR,114.0667,4.6126,74.7062,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0199,V199_DDR,112.2160,3.3709,74.0972,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0200,V200_DDR,112.6007,3.4519,74.4009,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.VOLT.0235,V235_DDR,-5.0333,-2.1324,-37.6488,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,113.4871,1.1518,77.5874,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,113.3758,3.0593,75.5685,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,24.7757,-0.9549,-9.0173,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,23.2973,-0.7092,-10.7414,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS_SPS,SPS_LA,88.6191,2.6133,51.2579,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,113.0791,1.8331,76.4981,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SSCN_NPPD,SSCN_NPPD_LA,-4.6244,-2.4905,-36.8819,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,29.3721,0.5961,-5.9719,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,29.3721,0.5961,-5.9719,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,TAL,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,TEC,SOUC,55.4649,0.9399,19.7771,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,-0.0035,-4.3955,-30.3559,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,TVA,TVA,56.6145,0.7449,21.1217,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,UCUHUB,UCUHUB_H,7.4323,-1.2453,-26.0703,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,UCUHUB17,UCUHUB17_H,-6.1590,-1.9500,-38.9569,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,UCUHUB18,UCUHUB18_H,-0.8499,-1.8157,-33.7821,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,UCUHUB19,UCUHUB19_H,-5.7663,-1.8778,-38.6365,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,UCUHUB20,UCUHUB20_H,-4.6740,-1.7974,-37.6246,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,UCUHUB21,UCUHUB21_H,-6.8407,-1.9459,-39.6427,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,UCUHUB22,UCUHUB22_H,-7.3639,-2.0540,-40.0579,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,UCUHUB23,UCUHUB23_H,-8.0909,-2.0684,-40.7704,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,UCUHUB24,UCUHUB24_H,-3.2160,-1.8164,-36.1475,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,30.8318,0.7659,-4.6821,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,30.8318,0.7659,-4.6821,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,9.2973,-1.6445,-23.8061,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,9.2973,-1.6445,-23.8061,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,16.7915,-1.6359,-16.3206,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,33.8800,-0.9289,0.0610,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,33.8800,-0.9289,0.0610,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,30.8318,0.7659,-4.6821,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,17.1981,-1.4575,-16.0923,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,21.4609,-0.3759,-12.9112,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,6.4788,-1.8507,-26.4185,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,1.7490,-4.7731,-28.2258,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,33.2910,0.6646,-2.1215,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,33.2910,0.6646,-2.1215,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,11.3606,-4.3693,-19.0180,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,7.3674,-2.4705,-24.9101,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,15.7523,-1.6367,-17.3589,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,4.3683,-2.5315,-27.8482,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,6.2356,-1.8576,-26.6548,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,6.3205,-2.6839,-25.7436,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,12.9806,-2.7493,-19.0180,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,12.9806,-2.7493,-19.0180,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,7.8085,-2.2844,-24.6551,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,2.0761,-4.8730,-27.7988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,7.9170,-0.3264,-26.5045,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,32.6272,-0.5732,-1.5476,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,32.6272,-0.5732,-1.5476,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,32.6272,-0.5732,-1.5476,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,32.7857,-0.2291,-1.7331,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,32.7857,-0.2291,-1.7331,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,32.7857,-0.2291,-1.7331,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,30.3171,1.2146,-5.6455,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,14.2585,-1.6827,-18.8067,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,14.2585,-1.6827,-18.8067,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,2.4097,-1.6118,-30.7264,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,4.0077,-2.3242,-28.4160,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,29.6980,-0.5374,-4.5125,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,-6.5506,-2.6440,-38.6546,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,0.0872,-5.6677,-28.9930,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,13.5057,-2.4130,-18.8292,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,32.4576,0.6252,-2.9156,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,32.4576,0.6252,-2.9156,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,32.4540,0.6217,-2.9157,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,32.4576,0.6252,-2.9156,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,32.5191,0.3925,-2.6213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,32.5191,0.3925,-2.6213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,32.5191,0.3925,-2.6213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,32.5191,0.3925,-2.6213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,32.5191,0.3925,-2.6213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,32.5191,0.3925,-2.6213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,32.5191,0.3925,-2.6213,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,-0.4484,-4.2491,-30.9472,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,19.3211,-0.9845,-14.4424,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,0.7602,-2.1953,-31.7925,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,0.7602,-2.1953,-31.7925,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,-1.9579,-3.1285,-33.5773,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,-1.9579,-3.1285,-33.5773,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,14.6494,-1.2919,-18.8067,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,25.9553,-1.1457,-7.6469,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,4.9250,-2.9077,-26.9152,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,3.8958,-4.3549,-26.4972,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,11.5318,-1.5857,-21.6304,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,16.7915,-1.6359,-16.3206,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,16.7915,-1.6359,-16.3206,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,4.3683,-2.5315,-27.8482,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,-3.9902,-2.4796,-36.2585,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,8.7280,-2.9106,-23.1093,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,2.2766,-4.6725,-27.7988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,7.1308,-2.5990,-25.0181,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.FSE,WAUE.FSE_H,0.0939,-2.8971,-31.7569,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,33.8992,-0.5161,-0.3327,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,34.1579,-0.5823,-0.0078,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,0.6283,-4.8761,-29.2435,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,1.8342,-4.6697,-28.2440,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,16.3717,-1.6688,-16.7075,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,17.6407,-1.8097,-15.2975,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-16.6200,-4.4697,-46.8983,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,1.7490,-4.7731,-28.2258,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-30.3700,-1.9585,-63.1594,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,11.2922,-2.4441,-21.0116,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,11.4660,-2.2703,-21.0116,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,11.2931,-2.4432,-21.0116,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,4.9739,-2.4125,-27.3615,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,-3.9902,-2.4796,-36.2585,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,9.2661,-1.4157,-24.0661,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,4.3309,-2.6203,-27.7968,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,7.7818,-0.4616,-26.5045,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,12.4207,-0.6020,-21.7252,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,6.7859,-1.6863,-26.2758,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,16.6520,-1.4026,-16.6933,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,5.8714,-1.9550,-26.9215,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,4.7111,-2.8557,-27.1811,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,-6.5506,-2.6440,-38.6546,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,17.5621,-0.2547,-16.9311,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,4.3228,-2.5659,-27.8592,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,17.4015,-0.3435,-17.0030,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,8.4109,-1.4119,-24.9252,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,20.1658,-1.9002,-12.6820,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NTWK,WAUE.NTWK_H,10.0061,-1.9058,-22.8360,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,11.4654,-0.3397,-22.9428,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,11.4654,-0.3397,-22.9428,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,1.4899,-5.0322,-28.2259,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,-1.4564,-5.3035,-30.9009,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,9.8586,-2.1266,-22.7627,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,1.4899,-5.0322,-28.2259,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,18.5148,-1.1217,-15.1115,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,5.2239,-3.2199,-26.3041,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,-6.5506,-2.6440,-38.6546,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,7.4918,-2.4713,-24.7848,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,2.8451,-5.5988,-26.3041,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,-3.9790,-5.4435,-33.2834,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,-1.9066,-5.3906,-31.2640,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,10.6290,-1.7571,-22.3618,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,5.6432,-4.5923,-24.5124,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,9.8584,-1.6883,-23.2013,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,3.7296,-3.9972,-27.0211,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,3.8958,-4.3549,-26.4972,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.VOLT.0152,V152_DDR,29.1765,1.5884,-7.1599,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE.VOLT.0172,V172_DDR,32.5340,0.5395,-2.7535,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_BEPM,WAUE_BEPM_LA,20.9188,-0.4993,-13.3299,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,9.2056,-1.4788,-24.0636,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,12.4129,-0.5832,-21.7519,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_EWA,WAUE_EWA_LA,-5.4723,-2.3184,-37.9018,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,4.4297,-3.1051,-27.2131,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_HMMU,WAUE_HMMU_LA,17.0190,-0.9657,-16.7633,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,15.6772,-1.4023,-17.6684,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_MECB,WAUE_MECB_LA,9.8430,-0.9279,-23.9770,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_MMPA,WAUE_MMPA_LA,17.2266,-0.4043,-17.1170,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_MRES,WAUE_MRES_LA,6.2951,-2.0564,-26.3965,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,25.6634,0.8741,-9.9587,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,33.8992,-0.5161,-0.3327,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,3.7744,-3.0593,-27.9142,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_OTP,WAUE_OTP_LA,21.5786,0.5080,-13.6773,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_OTPW,WAUE_OTPW_LA,31.7247,1.1236,-4.1469,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM,WAUE_UGPM_LA,11.6635,-1.6138,-21.4707,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,18.0492,-0.9418,-15.7570,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,7.1953,-1.8679,-25.6847,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,20.3593,-2.0753,-12.3133,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,-5.4723,-2.3184,-37.9018,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,17.0190,-0.9657,-16.7633,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,4.5623,-3.0491,-27.1365,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,33.8992,-0.5161,-0.3327,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,17.2266,-0.4043,-17.1170,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,8.1110,-1.7733,-24.8636,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,4.4493,-3.2987,-26.9999,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,20.4053,0.5284,-14.8710,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-13.7441,-3.1296,-45.3625,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-16.8940,-3.0997,-48.5422,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,25.3759,-1.5877,-7.7843,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,87.1279,1.2206,51.1593,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,87.1279,1.2206,51.1593,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,0.6619,-4.0468,-30.0392,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,81.4027,1.3988,45.2559,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,74.4916,1.3171,38.4265,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,55.0877,-1.6151,21.9549,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,55.0877,-1.6151,21.9549,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,55.0877,-1.6151,21.9549,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,54.9250,-1.7779,21.9549,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,55.0104,-1.6924,21.9549,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,55.0877,-1.6151,21.9549,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,55.0877,-1.6151,21.9549,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,55.0877,-1.6151,21.9549,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,38.4117,-1.4925,5.1562,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-22.3995,-2.9443,-54.2031,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-30.0000,-2.7778,-61.9701,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-14.5065,-2.8498,-46.4047,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,113.7334,1.3981,77.5874,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_ENMC,WFEC_ENMC_LA,113.1606,3.2241,75.1885,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-14.0138,-2.6160,-46.1457,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,49.6096,1.1629,13.6988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,111.5804,2.5995,74.2330,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-13.7441,-3.1296,-45.3625,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-13.7441,-3.1296,-45.3625,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-13.7441,-3.1296,-45.3625,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_OKGE,WFEC_OKGE_LA,29.2134,0.1728,-5.7073,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,65.4900,1.5160,29.2260,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,-6.6813,-4.2672,-37.1621,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,2.8951,-4.4874,-27.3654,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_WFEC,WFEC_LA,33.3307,-0.2574,-1.1598,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,111.5804,2.5995,74.2330,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-11.6621,-3.4420,-42.9681,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-12.5467,-2.2858,-45.0089,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,5.0970,-1.5391,-28.1118,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,5.0970,-1.5391,-28.1118,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,5.0970,-1.5391,-28.1118,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,5.0970,-1.5391,-28.1118,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,5.0970,-1.5391,-28.1118,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,5.0970,-1.5392,-28.1118,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,5.0970,-1.5392,-28.1118,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,18.7687,0.6447,-16.6239,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,3.4250,-2.1747,-29.1483,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-9.0266,-2.5521,-41.2224,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-9.0266,-2.5521,-41.2224,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-9.0266,-2.5521,-41.2224,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-19.2491,-2.7994,-51.1976,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-19.2491,-2.7994,-51.1976,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,0.4860,-2.3705,-31.8914,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,0.4860,-2.3705,-31.8914,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,0.4860,-2.3705,-31.8914,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,3.4250,-2.1747,-29.1483,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,8.6224,-0.7136,-25.4119,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.HEC.GT1,WRHECGTUN32_RA,-0.2937,-2.0979,-32.9438,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.HEC.GT2,WRHECGTUN33_RA,-0.2937,-2.0979,-32.9438,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.HEC.GT3,WRHECGTUN34_RA,-0.2937,-2.0979,-32.9438,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.HEC.GT4,WRHECGTUN35_RA,-0.2937,-2.0979,-32.9438,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,8.6224,-0.7136,-25.4119,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-17.0540,-3.0543,-48.7476,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-25.5831,-1.2675,-59.0635,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.JEC.1,WRJEFFUN10_RA,5.3676,-1.6434,-27.7370,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.JEC.2,WRJEFFUN11_RA,5.4223,-1.6572,-27.6684,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.JEC.3,WRJEFFUN12_RA,5.2676,-1.8120,-27.6684,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-13.4012,-2.4415,-45.7076,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-28.4879,-2.6622,-60.5736,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-28.4879,-2.6622,-60.5736,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.LEC.4,WRLECUN26_RA,2.2818,-0.7222,-31.7439,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.LEC.5,WRLECUN27_RA,3.8394,-0.6424,-30.2661,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,0.9528,-1.9424,-31.8527,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,0.9528,-1.9424,-31.8527,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,0.9528,-1.9424,-31.8527,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,1.0372,-1.8756,-31.8351,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-13.3300,-2.9282,-45.1497,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-13.3300,-2.9282,-45.1497,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-7.7441,-1.8491,-40.6430,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-9.9726,-3.3415,-41.3790,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-9.9726,-3.3415,-41.3790,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-1.0384,-3.2955,-32.4908,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-13.3300,-2.9282,-45.1497,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,7.8229,-2.7423,-24.1827,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,2.3559,-2.5689,-29.8231,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-28.5035,-2.6778,-60.5736,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,74.8700,1.3024,38.8197,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,-2.8518,-4.6983,-32.9014,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,5.0970,-1.5392,-28.1118,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,3.8806,-2.7735,-28.0938,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,8.6224,-0.7136,-25.4119,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,3.4250,-2.1747,-29.1483,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-3.5084,-2.0271,-36.2292,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.THAYERLD,WR.THAYERLD_LA,24.9876,0.7498,-10.5101,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-4.2442,-1.9865,-37.0056,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0106,V106_DDR,-3.8349,-1.9289,-36.6539,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0139,WR.VOLT.0139_H,0.3898,-0.4192,-33.9389,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0141,WR.VOLT.0141_H,2.8062,-1.9189,-30.0229,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0146,WR.VOLT.0146_H,2.1974,-0.4268,-32.1237,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0147,WR.VOLT.0147_H,2.1974,-0.4268,-32.1237,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0148,WR.VOLT.0148_H,4.0951,-0.5785,-30.0744,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-3.7867,-1.6635,-36.8711,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0157,V157_DDR,2.2865,-0.4626,-31.9988,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0158,V158_DDR,2.1974,-0.4268,-32.1237,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0159,WR.VOLT.0159_H,2.1974,-0.4268,-32.1237,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-4.7769,-2.1220,-37.4029,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0173,V173_DDR,0.3815,-2.2045,-32.1619,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0174,V174_DDR,-4.4584,-1.9445,-37.2619,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0184,V184_DDR,-4.0796,-2.1670,-36.6606,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-3.6456,-2.0027,-36.3909,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0186,V186_DDR,-3.2212,-2.1056,-35.8635,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-4.0398,-2.1003,-36.6874,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-4.2607,-1.9277,-37.0809,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0189,WR.VOLT.0189_H,2.0110,-1.5512,-31.1857,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0190,WR.VOLT.0190_H,4.2420,-1.3711,-29.1349,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0191,WR.VOLT.0191_H,4.7830,-1.4281,-28.5368,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0192,WR.VOLT.0192_H,4.7830,-1.4281,-28.5368,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0196,WR.VOLT.0196_H,4.2420,-1.3711,-29.1349,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0245,V245_DDR,-3.6269,-2.0045,-36.3703,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.VOLT.0248,V248_DDR,-3.8349,-1.9289,-36.6539,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-9.3074,-2.3353,-41.7200,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,6.6370,-0.9745,-27.1364,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.WOLF,WRWOLFUN15_RA,3.0975,-2.9478,-28.7026,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-17.0540,-3.0543,-48.7476,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,18.5797,0.4557,-16.6239,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-9.0266,-2.5521,-41.2224,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-9.0266,-2.5521,-41.2224,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-9.0266,-2.5521,-41.2224,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-9.0266,-2.5521,-41.2224,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,-5.1755,-1.8797,-38.0437,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,2.8608,-1.9255,-29.9616,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-5.9373,-1.9733,-38.7120,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-5.9373,-1.9733,-38.7120,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-5.9373,-1.9733,-38.7120,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-5.9373,-1.9733,-38.7120,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,4.4075,-1.3602,-28.9802,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,4.4075,-1.3602,-28.9802,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,4.4075,-1.3602,-28.9802,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,4.4075,-1.3602,-28.9802,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,4.4075,-1.3602,-28.9802,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,4.4075,-1.3602,-28.9802,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-22.3304,-1.9795,-55.0989,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-22.3304,-1.9795,-55.0989,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-26.1455,-2.0228,-58.8707,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-26.1455,-2.0228,-58.8707,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_MIDW,WR_MIDW_LA,-6.8906,-2.6866,-38.9520,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,52.8235,0.2744,17.8012,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,32.7955,-0.1169,-1.8355,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,-4.5695,-2.5789,-36.7385,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_SEG,WR_SEG_LA,16.3133,0.2136,-18.6482,34.7479\n03/19/2025 20:00:00,03/20/2025 01:00:00,WR_WR,WR_LA,2.3668,-1.4884,-30.8928,34.7480\n03/19/2025 20:00:00,03/20/2025 01:00:00,YAD,VACS,56.0418,0.8449,20.4490,34.7479\n03/19/2025 21:00:00,03/20/2025 02:00:00,AEC,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,AECC_CSWS,CSWS_AECC_LA,56.0033,1.1899,4.1603,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,47.8044,0.7915,-3.6402,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,71.4889,0.9244,19.9114,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,47.2824,0.2969,-3.6676,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,49.5539,0.9957,-2.0949,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,69.7050,0.2963,18.7557,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,47.7058,0.2430,-3.1903,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,AECI,AECI,44.3787,-0.2283,-6.0461,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,AEPM_CSWS,CSWS_LA,49.3560,1.2998,-2.5969,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,ALTW,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,AMRN,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,216.6691,2.5473,163.4687,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BBA,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,BCA,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,BEPM.ER01.DDR,ER01_DDR,-1.3408,-6.5101,-45.4838,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BEPM_ER01,BEPM_ER01_LA,-1.3408,-6.5101,-45.4838,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,1.6994,-1.8257,-47.1280,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,8.2384,0.2557,-42.6704,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BEPM_UM01,BEPM_UM01_LA,38.9605,1.1824,-12.8750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BLKW,BLKW,230.8897,5.6085,174.6281,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-30.0000,-4.8188,-75.8343,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-30.0000,-4.8188,-75.8343,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,61.6804,-3.6736,14.7009,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.9135,-4.7323,-75.8343,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,BRAZ,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,BUBA,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-10.4981,-2.0712,-59.0800,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,1.1483,-3.0417,-46.4631,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,1.1483,-3.0417,-46.4631,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,1.1483,-3.0417,-46.4631,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,1.1483,-3.0417,-46.4631,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,1.1483,-3.0417,-46.4631,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-5.1869,-3.0793,-52.7606,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,21.1396,-2.5035,-27.0099,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,21.1396,-2.5035,-27.0099,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CLEC,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,46.9651,0.2709,-3.9588,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,COWP,COWP_LA,41.7609,0.4667,-9.3589,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,41.7609,0.4667,-9.3589,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,41.7609,0.4667,-9.3589,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CPLE,VACS,48.1679,0.7966,-3.2818,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CPLW,VACS,48.1679,0.7966,-3.2818,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,49.9102,1.2346,-1.9775,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,49.9102,1.2346,-1.9775,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,49.9102,1.2346,-1.9775,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,49.9102,1.2346,-1.9775,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CRTH_SPA,WRCRTH_SPA_LA,49.4706,-0.3947,-0.7878,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,51.8705,3.8724,-2.6550,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,33.9928,-1.9614,-14.6989,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,47.7058,0.2430,-3.1903,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,47.2824,0.2969,-3.6676,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,51.8616,3.8664,-2.6579,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,50.1165,2.3051,-2.8417,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,51.4436,3.5049,-2.7144,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,51.4436,3.5049,-2.7144,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,47.0069,0.4314,-4.0776,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,47.0069,0.4314,-4.0776,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,46.6808,0.1053,-4.0776,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,46.6808,0.1053,-4.0776,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,47.7058,0.2430,-3.1903,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,51.0293,2.5931,-2.2169,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,60.3170,-0.8139,10.4779,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,59.9471,-1.1838,10.4779,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,48.5772,-0.3963,-1.6795,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,46.0515,-0.1601,-4.4414,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,46.0515,-0.1601,-4.4414,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,46.0522,-0.1602,-4.4407,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,46.0522,-0.1602,-4.4407,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-3.9679,-2.3935,-52.2275,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,42.9201,-1.8020,-5.9310,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,52.1680,-0.3471,1.8620,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,7.4440,-1.7212,-41.4879,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,7.4025,-1.7626,-41.4879,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,16.4851,-1.7191,-32.4489,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.GRID.CDL1,CDL1_DDR,48.8665,0.1884,-1.9750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,24.9021,-2.6232,-23.1278,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,34.9405,-2.3327,-13.3799,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,48.8665,0.1884,-1.9750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.NUEN.CSI1,CSI1_DDR,48.0115,0.4367,-3.0783,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.NUEN.CSI2,CSI2_DDR,48.0297,0.4549,-3.0783,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,46.9781,0.2838,-3.9588,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.NUEN.GAZA,GAZA_DDR,48.8665,0.1884,-1.9750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,85.9914,1.5080,33.8303,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.NUEN.T201,NT201_DDR,46.7401,-0.0304,-3.8826,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,25.8147,-2.5959,-22.2424,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,25.8147,-2.5959,-22.2424,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,47.7058,0.2430,-3.1903,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,52.0338,4.3193,-2.9386,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,16.4851,-1.7191,-32.4489,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,16.4851,-1.7191,-32.4489,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,5.8727,-2.4763,-42.3040,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,7.4025,-1.7626,-41.4879,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,50.2377,2.2645,-2.6799,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,44.1627,-0.4992,-5.9912,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,43.5487,-1.1132,-5.9912,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,43.5406,-1.1213,-5.9912,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,35.4472,-0.6318,-14.5740,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,35.4472,-0.6318,-14.5740,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,50.0180,2.2661,-2.9012,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,46.2368,0.0333,-4.4495,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,49.9181,2.1471,-2.8820,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,53.2976,5.6561,-3.0116,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,48.9748,0.4300,-2.1083,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,48.0297,0.4549,-3.0783,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0057,OKMU_DDR,49.4769,0.3825,-1.5586,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0060,LEHIGH_DDR,85.9914,1.5080,33.8303,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0086,WARRENM_DDR,46.5340,0.0618,-4.1809,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,51.4713,3.8978,-3.0796,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,54.2298,0.0277,3.5490,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0121,V121_DDR,50.0180,2.2661,-2.9012,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0122,V122_DDR,53.1423,-0.0096,2.4988,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0124,V124_DDR,66.6475,-0.2813,16.2757,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0135,V135_DDR,47.1899,0.1198,-3.5830,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0144,V144_DDR,43.8950,-1.6162,-5.1418,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0145,V145_DDR,44.1137,-1.8706,-4.6688,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,50.1445,2.4024,-2.9110,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,48.3194,0.9774,-3.3110,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0175,V175_DDR,46.9781,0.2838,-3.9588,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,48.3194,0.9774,-3.3110,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,48.7369,1.3420,-3.2582,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,47.1899,0.1198,-3.5830,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,47.3691,0.0489,-3.3329,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,46.9935,-0.0644,-3.5951,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,57.5404,-0.4579,7.3452,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,46.0072,-0.1886,-4.4572,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,47.3691,0.0489,-3.3329,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0211,V211_DDR,50.6951,2.8863,-2.8443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,55.0544,0.0551,4.3462,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0213,V213_DDR,47.0262,0.0484,-3.6753,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0215,V215_DDR,54.0208,0.0155,3.3522,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0217,V217_DDR,55.0672,0.0137,4.4005,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0218,V218_DDR,57.2186,-0.4315,6.9970,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0228,V228_DDR,46.6709,-0.1135,-3.8687,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0232,V232_DDR,46.7271,0.1072,-4.0331,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0233,V233_DDR,47.5059,0.1019,-3.2490,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0240,V240_DDR,51.3236,-0.2322,0.9027,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0244,V244_DDR,47.3691,0.0489,-3.3329,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0246,MDT1_DDR,85.9914,1.5080,33.8303,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0249,V249_DDR,47.0441,0.1072,-3.7162,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0250,V250_DDR,32.8151,-1.8529,-15.9851,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0251,V251_DDR,46.4724,-0.0597,-4.1210,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.VOLT.0252,V252_DDR,57.5404,-0.4579,7.3452,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-11.4029,-2.5451,-59.5109,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,56.3317,-3.1212,8.7998,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-2.0139,-5.2929,-47.3740,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,48.9406,1.1576,-2.8701,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-5.7825,-6.9505,-49.4851,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,38.7257,-1.8255,-10.1019,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,38.7257,-1.8255,-10.1019,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,38.7257,-1.8255,-10.1019,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,38.7257,-1.8255,-10.1019,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,38.7257,-1.8255,-10.1019,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,47.7058,0.2430,-3.1903,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,52.3472,3.8902,-2.1961,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,46.6641,0.0441,-4.0331,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,46.5890,-0.0310,-4.0331,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,52.0475,0.5118,0.8826,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,52.0475,0.5118,0.8826,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWWELSH1,CSWSWELSHUN1_RA,48.9697,1.6125,-3.2959,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWWELSH3,CSWSWELSHUN3_RA,48.9697,1.6125,-3.2959,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWWILKES1,CSWSWILKESUN1_RA,49.9743,2.3991,-3.0778,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWWILKES2,CSWSWILKESUN2_RA,49.9743,2.3991,-3.0778,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,CSWWILKES3,CSWSWILKESUN3_RA,49.8313,2.2269,-3.0486,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,7.4440,-1.7212,-41.4879,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,DENL,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,DERS,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,DOE,DOE,42.9668,0.2619,-7.9482,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,23.7123,-1.4010,-25.5398,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,DPC,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,DUK,VACS,48.1679,0.7966,-3.2818,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDDY,EDDY,235.1451,7.5463,176.9457,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,47.7779,-0.7210,-2.1542,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-8.9930,-1.6317,-58.0144,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,53.2837,-1.1506,3.7812,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE.SLCC,EDESTL4391_PLT,48.2518,-0.7256,-1.6757,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,48.3140,-0.5665,-1.7725,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,34.5315,-1.6847,-14.4369,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_EC_01,EDELAR3821UN1_RA,47.7779,-0.7210,-2.1542,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_EC_02,EDELAR3821UN2_RA,47.7779,-0.7210,-2.1542,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_EC_03,EDELAR3821UN3_RA,47.7779,-0.7210,-2.1542,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_EC_04,EDELAR3821UN4_RA,47.7779,-0.7210,-2.1542,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_EDE,EDE_LA,48.1006,0.3642,-2.9167,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_ERW,EDEERWFUNG1_RA,-4.6147,-3.2309,-52.0368,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,5.6289,-4.2528,-40.7714,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,96.0000,1.2646,44.0823,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,96.0000,1.2646,44.0823,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,96.0000,1.2646,44.0823,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,96.0000,1.2646,44.0823,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,30.0027,0.8979,-21.5483,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_RIV_10,EDERIV1671UN10_RA,47.7795,-1.0218,-1.8517,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_RIV_11,EDERIV1671UN11_RA,47.7795,-1.0218,-1.8517,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_RIV_12,EDERIV453UN12_PLT,46.4489,-2.3525,-1.8517,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_SL_01,EDESTL4391UN1_RA,48.2518,-0.7256,-1.6757,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EDE_SWMP,EDE_SWMP_LA,48.0266,0.7962,-3.4226,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,EEI,EEI,42.8053,0.2541,-8.1019,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,EES,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,4.3189,-3.4010,-42.9332,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,ERCOTE,ERCOTE,48.9697,1.6125,-3.2959,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,ERCOTN,ERCOTN,25.9901,-2.4206,-22.2424,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,13.4117,-3.3889,-33.8524,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,FMPP,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,FPC,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,FPL,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,FREM_50T,OPPDFREM_GUN1_RA,21.2070,-2.2760,-27.1701,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,FREM_6,OPPDFREM_AUN6_RA,21.1892,-2.2912,-27.1726,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,FREM_7,OPPDFREM_AUN7_RA,21.1892,-2.2912,-27.1726,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,FREM_8,OPPDFREM_AUN8_RA,20.9671,-2.5134,-27.1726,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,FREM_LOAD,FREM_LOAD_LA,21.1535,-2.3270,-27.1726,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-0.3630,-2.7465,-48.2696,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,50.2335,2.2604,-2.6799,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,-9.5571,-2.2769,-57.9333,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-9.0747,-4.3915,-55.3363,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,46.9651,0.2709,-3.9588,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,46.9651,0.2709,-3.9588,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,46.9651,0.2709,-3.9588,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,47.6176,-0.2077,-2.8278,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,47.6176,-0.2077,-2.8278,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,47.7184,-0.2217,-2.7129,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,47.7184,-0.2217,-2.7129,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-6.3156,-4.0024,-52.9663,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,46.4090,-0.8727,-3.3714,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,46.4090,-0.8727,-3.3714,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,46.4090,-0.8727,-3.3714,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.VOLT.0130,V130_DDR,47.9716,0.3378,-3.0192,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA.VOLT.0237,V237_DDR,47.2205,-0.0061,-3.4265,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDAHUB2,GRDAHUB2_H,37.4627,-1.3160,-11.8744,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDAHUB3,GRDAHUB3_H,31.7646,-1.6418,-17.2467,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA_GRDA,GRDA_LA,46.9169,0.0119,-3.7481,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA_HUB,GRDA_H,43.5862,-0.8487,-6.2181,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRDA_HUBSA,GRDASA_H,43.2779,-0.9159,-6.4593,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GRE,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,32.9836,5.1558,-22.8253,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GSEC_SPS,SPS_GSEC_LA,164.2433,3.3005,110.2897,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GSPR2014HUB,GSPR2014HUB_H,129.5205,2.5823,76.2851,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,GSPR2015HUB,GSPR2015HUB_H,124.9359,2.3753,71.9076,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,38.7173,1.2578,-13.1936,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,HARRISON,CSWSLEBROCKPLT1,49.5913,1.8090,-2.8708,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,HAST_TNSK_HUB,HAST_TNSK_H,13.1621,-2.8487,-34.6422,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,HQST,PJM,35.1242,-0.5021,-15.0268,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,HST,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,81.9288,-0.5604,31.8362,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,81.9288,-0.5604,31.8362,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,79.3458,-0.5864,29.2791,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,79.3458,-0.5864,29.2791,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,84.5983,-0.5393,34.4845,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,84.5983,-0.5393,34.4845,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,INDN_INDN,INDN_LA,81.3272,-0.5470,31.2211,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-12.0300,-4.4732,-58.2099,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,ISNE,PJM,35.1242,-0.5021,-15.0268,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,JEA,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,21.4645,-2.2635,-26.9250,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,21.4645,-2.2635,-26.9250,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,7.7580,-1.6527,-41.2424,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KACYCT4,KACYNEARMANUNCT4_RA,41.9395,-1.3628,-7.3508,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,85.2603,-0.8759,35.4831,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,41.9395,-1.3628,-7.3508,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,41.4030,-1.2124,-8.0377,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,41.5442,-1.2620,-7.8469,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KACY_KACY,KACY_LA,41.3200,-1.1695,-8.1636,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,35.7882,-1.3395,-13.5254,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,74.6043,0.7958,23.1554,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-10.9232,-2.8033,-58.7730,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-20.5446,-4.3586,-66.8391,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.VOLT.0222,V222_DDR,18.0279,-1.6123,-31.0129,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.VOLT.0223,V223_DDR,25.3778,-1.4297,-23.8456,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.VOLT.0241,V241_DDR,60.0347,0.4805,8.9011,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.VOLT.0243,V243_DDR,41.3052,-0.4784,-8.8694,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.VOLT.0247,V247_DDR,45.0810,-1.0424,-4.5297,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.VOLT.0253,V253_DDR,36.3900,-1.3207,-12.9424,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,9.2950,-4.4079,-36.9502,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,22.2019,-1.9296,-26.5216,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,22.2019,-1.9296,-26.5216,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,22.2019,-1.9296,-26.5216,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,22.2019,-1.9296,-26.5216,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,35.6947,-1.3523,-13.6061,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,35.6947,-1.3523,-13.6061,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHUB,KCPLHUB_H,13.6834,-2.8971,-34.0726,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHUB17,KCPLHUB17_H,11.6096,-3.0158,-36.0276,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHUB18,KCPLHUB18_H,10.8807,-3.0582,-36.7142,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHUB19,KCPLHUB19_H,10.8516,-2.9829,-36.8186,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHUB20,KCPLHUB20_H,9.9516,-3.0947,-37.6067,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHUB21,KCPLHUB21_H,9.7262,-2.9892,-37.9377,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHUB22,KCPLHUB22_H,10.5832,-2.9954,-37.0745,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHUB23,KCPLHUB23_H,9.9594,-3.0720,-37.6217,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLHUB24,KCPLHUB24_H,9.0173,-3.1388,-38.4970,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,14.6709,-1.9341,-34.0481,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,14.6709,-1.9341,-34.0481,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,18.6686,-2.5558,-29.4287,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,18.6686,-2.5558,-29.4287,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,35.7951,-1.3326,-13.5254,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,35.7882,-1.3395,-13.5254,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,37.0867,-1.1914,-12.3750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,37.0867,-1.1914,-12.3750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,37.0867,-1.1914,-12.3750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,37.0867,-1.1914,-12.3750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,37.0867,-1.1914,-12.3750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,37.0867,-1.1914,-12.3750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,37.0867,-1.1914,-12.3750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,37.0867,-1.1914,-12.3750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,13.4532,-1.8206,-35.3793,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,39.5481,-1.1435,-9.9615,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KCPL_KCPL,KCPL_LA,35.6411,-1.2663,-13.7457,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KENN,KENN_LA,33.5920,0.7932,-17.8543,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KEP2_SECI,KEP2_SECI_LA,-11.6219,-0.8683,-61.4067,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KERR_1,GRDAKERR_HYDUN1_RA,47.1033,-0.1055,-3.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KERR_2,GRDAKERR_HYDUN2_RA,47.1734,-0.0941,-3.3855,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,KERR_3,GRDAKERR_HYDUN3_RA,47.1734,-0.0941,-3.3855,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,KERR_4,GRDAKERR_HYDUN4_RA,47.1033,-0.1055,-3.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,22.2017,-1.9298,-26.5216,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,22.2017,-1.9298,-26.5216,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,24.0754,-1.6796,-24.8981,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,24.0754,-1.6796,-24.8981,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,18.9927,-1.8688,-29.7916,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,17.2850,-1.7370,-31.6311,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,17.2850,-1.7370,-31.6311,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-9.2336,-1.3058,-58.5809,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-9.2336,-1.3058,-58.5809,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-9.2336,-1.3058,-58.5809,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,2.0683,-3.1694,-45.4153,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,2.0683,-3.1694,-45.4153,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-9.8508,-1.4381,-59.0657,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,0.4241,-2.9257,-47.3033,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,7.4850,-2.9367,-40.2314,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,76.1329,-0.9645,26.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,76.1329,-0.9645,26.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,11.0981,-2.7749,-36.7801,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,11.0981,-2.7749,-36.7801,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,11.0981,-2.7749,-36.7801,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,-0.3048,-3.6455,-47.3124,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,2.3956,-5.1049,-43.1526,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,16.0500,-2.8462,-31.7569,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,7.3169,-1.5014,-41.8348,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LAFA,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,LAM345,LAM345,-10.4981,-2.0712,-59.0800,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LEPA,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,18.9814,-2.3066,-29.3651,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_LES,LES_LA,18.9648,-2.3533,-29.3349,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,19.5247,-2.4492,-28.6792,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,18.5547,-2.4885,-29.6099,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,18.5547,-2.4885,-29.6099,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,18.5547,-2.4885,-29.6099,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,19.5263,-2.4476,-28.6792,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,19.5247,-2.4492,-28.6792,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_WAVERLY,LES_WAVERLY_H,19.2548,-2.5018,-28.8965,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,20.5489,-2.6756,-27.4286,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,20.5489,-2.6756,-27.4286,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,LGEE,LGEE,39.2220,-0.1241,-11.3071,50.6532\n03/19/2025 21:00:00,03/20/2025 02:00:00,MALDEN,MALDEN_LA,34.3428,0.7145,-17.0248,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MCWEST,MCWEST,42.1103,0.8159,-9.3587,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MDU,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,6.9519,0.0635,-43.7646,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,15.7877,-2.0150,-32.8503,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,22.3881,-0.0288,-28.2361,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,MEAN_NPPD,NPPD_MEAN_LA,8.5706,-3.1614,-38.9211,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MEC,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,MHEB,MHEB,17.9487,-0.7977,-31.9066,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-7.5345,-4.4586,-53.7290,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,-1.2131,-4.2313,-47.6349,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-7.5345,-4.4586,-53.7290,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-7.5345,-4.4586,-53.7290,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,-1.2131,-4.2313,-47.6349,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-0.0629,-2.8147,-47.9013,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MISO,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-11.1153,-0.1508,-61.6176,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-11.1153,-0.1508,-61.6176,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,8.2539,-3.5576,-38.8416,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,-8.5586,-3.3249,-55.8867,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,1.0790,-3.8897,-45.6844,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,-7.6490,-3.1476,-55.1545,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,-4.4604,-2.9919,-52.1216,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,-7.2843,-2.9600,-54.9774,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,-2.9152,-3.0108,-50.5575,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,-2.9152,-3.0108,-50.5575,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,-2.9152,-3.0108,-50.5575,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,-2.9152,-3.0108,-50.5575,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,-2.9152,-3.0108,-50.5575,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,39.6811,-1.2511,-9.7209,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,39.7560,0.0642,-10.9613,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,39.7560,0.0642,-10.9613,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,37.5788,-0.4587,-12.6156,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,55.4709,0.6941,4.1237,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MOWR,AECI,44.3787,-0.2283,-6.0461,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,40.7908,-0.5301,-9.3322,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,40.3939,0.0957,-10.3549,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,0.4042,-3.7469,-46.5019,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-12.0000,-2.6511,-60.0020,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-12.8810,-4.0762,-59.4579,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,0.5754,-3.5758,-46.5019,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,23.7399,-1.3734,-25.5398,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,23.7399,-1.3734,-25.5398,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,23.7435,-1.3698,-25.5398,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,23.7435,-1.3698,-25.5398,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,18.0279,-1.6123,-31.0129,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,18.0279,-1.6123,-31.0129,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,18.0279,-1.6123,-31.0129,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,17.8734,-1.7668,-31.0129,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,18.0279,-1.6123,-31.0129,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,18.0279,-1.6123,-31.0129,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,18.0279,-1.6123,-31.0129,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,42.9723,0.4320,-8.1128,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,31.2744,-1.5018,-17.8769,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,22.3383,-1.5071,-26.8077,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,22.3385,-1.5069,-26.8077,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,22.3385,-1.5069,-26.8077,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,39.0481,-1.3325,-10.2725,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,39.0481,-1.3325,-10.2725,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MPS_MPS,MPS_LA,46.4711,-0.9259,-3.2561,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MSTNG,SPSMSTNGPLT1,224.4989,5.6790,168.1668,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MSTNG4,SPSMSTNGUN4_RA,224.2416,5.4217,168.1668,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MSTNG5,SPSMSTNGUN5_RA,224.2434,5.4235,168.1668,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,224.4989,5.6790,168.1668,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NBSO,PJM,35.1242,-0.5021,-15.0268,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,14.0929,-3.3750,-33.1851,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,14.0936,-3.3744,-33.1851,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,29.0369,-0.6755,-20.9407,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NHC1,VACS,48.1679,0.7966,-3.2818,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,21.5405,-2.4007,-26.7119,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,21.5405,-2.4007,-26.7119,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,21.5405,-2.4007,-26.7119,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,-0.2093,-3.0302,-47.8321,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,11.2274,-4.4589,-34.9668,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,15.2559,-3.1859,-32.2113,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-9.8524,-3.5475,-56.9580,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,11.2274,-4.4589,-34.9668,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.HUB.PY2018,NPPDPY18_H,10.4473,-2.9646,-37.2412,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,10.6943,-2.9926,-36.9661,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,10.6285,-2.9543,-37.0703,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,10.8745,-2.9548,-36.8238,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-14.0000,-3.6693,-60.9838,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,8.4234,-2.0683,-40.1614,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,8.4234,-2.0683,-40.1614,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,1.7762,-3.4620,-45.4149,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-14.0000,-3.6693,-60.9838,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,15.4424,-4.9060,-30.3047,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,8.0687,-4.1907,-38.3937,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,4.8428,-1.2998,-44.5105,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,8.0687,-4.1907,-38.3937,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,8.8844,-4.1548,-37.6139,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,7.8813,-3.3909,-39.3809,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,17.6919,-1.9237,-31.0374,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,11.2274,-4.4589,-34.9668,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,5.3163,-1.5406,-43.7962,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,8.4234,-2.0683,-40.1614,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,8.4234,-2.0683,-40.1614,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,9.9037,-1.8416,-38.9077,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,9.7924,-1.8285,-39.0321,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,9.7924,-1.8285,-39.0321,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,11.2473,-1.7082,-37.6976,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,-2.1095,-2.5717,-50.1909,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,12.2756,-3.7369,-34.6405,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,-0.1736,-2.5560,-48.2707,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-5.0027,-2.2951,-53.3606,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-8.5729,-2.3675,-56.8585,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.NELI.DDR,NELI_DDR,-10.9300,-4.5213,-57.0617,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.NPPM.1058,SH1058_DDR,35.3601,-2.2713,-13.0217,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,11.0809,-2.1461,-37.4261,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,11.2274,-4.4589,-34.9668,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,15.2559,-3.1859,-32.2113,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-14.0000,-3.6693,-60.9838,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.TECH.1,KEARNE_DDR,12.0079,-1.4812,-37.1640,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,8.5859,-5.1389,-36.9283,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,8.5859,-5.1389,-36.9283,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-13.6852,-4.3409,-59.9974,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD.VOLT.0236,V236_DDR,16.7864,-2.2252,-31.6415,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD2017HUB,NPPD2017HUB_H,10.5282,-2.9618,-37.1631,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,30.4906,-3.4496,-16.7129,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,-0.2093,-3.0302,-47.8321,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,7.3672,-5.0274,-38.2585,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,7.3672,-5.0274,-38.2585,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,16.9096,-2.2998,-31.4437,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,16.8255,-2.1861,-31.6415,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-9.0587,-3.6302,-56.0815,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,9.9448,-1.9837,-38.7245,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,34.3176,-3.3137,-13.0217,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,34.3176,-3.3137,-13.0217,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,34.3176,-3.3137,-13.0217,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,13.1873,-2.8494,-34.6164,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,15.4145,-3.4842,-31.7544,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,13.7586,-2.7892,-34.1053,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-10.4500,-6.6616,-54.4415,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-10.1879,-6.3995,-54.4415,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,6.9477,-2.1847,-41.5207,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,6.6811,-2.2303,-41.7417,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,14.3323,-2.6205,-33.7002,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,14.2856,-2.6673,-33.7002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,14.2856,-2.6673,-33.7002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,14.2414,-2.5746,-33.8371,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,15.4424,-4.9060,-30.3047,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,14.1536,-2.5821,-33.9174,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,17.3933,-2.7297,-30.5301,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,13.2416,-2.7360,-34.6755,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,13.2028,-2.7641,-34.6862,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,13.2175,-2.7386,-34.6969,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,13.2175,-2.7386,-34.6969,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,13.1873,-2.8494,-34.6164,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,13.0980,-2.9387,-34.6164,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,1.4379,-1.7862,-47.4290,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,15.0600,-2.4040,-33.1891,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,6.6179,-1.9709,-42.0643,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,-0.6089,-5.8909,-45.3711,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,4.3898,-1.5302,-44.7331,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,36.0977,-1.5337,-13.0217,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-10.9300,-4.5213,-57.0617,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,7.2297,-2.1213,-41.3021,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,7.2297,-2.1213,-41.3021,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_NPPD,NPPD_LA,14.7130,-2.5691,-33.3710,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,17.3933,-2.7297,-30.5301,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,17.3933,-2.7297,-30.5301,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,13.5127,-3.4719,-33.6684,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,9.3240,-3.5721,-37.7570,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NSB,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NSP,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,NSSO,PJM,35.1242,-0.5021,-15.0268,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,NYIS,PJM,35.1242,-0.5021,-15.0268,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-7.2465,-3.1657,-54.7339,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-5.7322,-4.0755,-52.3098,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-2.0735,-3.8174,-48.9092,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-2.0735,-3.8174,-48.9092,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-20.1207,-2.3966,-68.3772,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-9.0747,-4.3915,-55.3363,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-53.2014,-2.6784,-101.1761,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-21.7423,-4.4851,-67.9103,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-7.1593,-3.9886,-53.8237,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-5.9082,-4.2127,-52.3486,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,17.5153,-2.0523,-31.0855,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-7.1593,-3.9886,-53.8237,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-16.4671,-2.6498,-64.4704,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-0.0629,-2.8147,-47.9013,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,-2.9669,-3.5236,-50.0964,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,49.5516,-0.4896,-0.6119,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-5.9082,-4.2127,-52.3486,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-3.8499,-3.6388,-50.8642,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,2.7172,-4.0337,-43.9022,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,1.1483,-3.0417,-46.4631,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-16.0000,-0.8006,-65.8525,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-0.0629,-2.8147,-47.9013,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-0.0629,-2.8147,-47.9013,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-5.9082,-4.2127,-52.3486,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.NUEN.ADA1,ADA1_DDR,4.7310,-2.5680,-43.3541,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.NUEN.LAM1,LAM1_DDR,68.3103,2.4499,15.2073,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.NUEN.MDT2,MDT2_DDR,17.5214,-2.0462,-31.0855,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.NUEN.MDT3,MDT3_DDR,17.5214,-2.0462,-31.0855,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.NUEN.WWO1,WWO1_DDR,4.3146,-2.5139,-43.8245,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,15.1582,-2.0087,-33.4861,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,15.1582,-2.0087,-33.4861,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,15.1582,-2.0087,-33.4861,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,21.1000,-1.8090,-27.7441,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,21.1000,-1.8090,-27.7441,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,15.1582,-2.0087,-33.4861,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,15.1582,-2.0087,-33.4861,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-5.9082,-4.2127,-52.3486,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,44.6282,1.3915,-7.4163,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-16.4671,-2.6498,-64.4704,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-5.3339,-1.2970,-54.6900,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-3.8499,-3.6388,-50.8642,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,68.1085,1.7808,15.6746,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,-3.3230,-3.0585,-50.9176,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,-3.3230,-3.0585,-50.9176,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,-3.3230,-3.0585,-50.9176,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,-3.3230,-3.0585,-50.9176,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-7.2184,-5.6192,-52.2523,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-7.0936,-3.7995,-53.9472,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-5.7322,-4.0755,-52.3098,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-9.0693,-3.6914,-56.0309,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-9.0693,-3.6914,-56.0309,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,-0.6461,-0.4384,-50.8608,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,-0.9186,-3.2121,-48.3596,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,-0.9186,-3.2121,-48.3596,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,-0.9186,-3.2121,-48.3596,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0033,FOSTER_DDR,27.4533,-1.7115,-21.4883,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,36.8575,0.2528,-14.0484,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0035,TARBY_DDR,68.3580,1.7560,15.9489,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,36.8575,0.2528,-14.0484,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,35.8028,-0.2652,-14.5851,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,35.8028,-0.2652,-14.5851,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-10.6254,-0.6777,-60.6008,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0040,TROSPER_DDR,30.7918,-1.6345,-18.2268,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,30.7407,-1.6364,-18.2760,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,69.9435,2.0019,17.2885,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0115,V115_DDR,18.5768,-2.0014,-30.0749,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0116,V116_DDR,77.6663,-0.0270,27.0402,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0118,V118_DDR,38.8732,-0.7391,-11.0408,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0125,V125_DDR,68.7379,2.2768,15.8080,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0126,V126_DDR,35.6093,0.4923,-15.5360,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0129,V129_DDR,24.9050,-2.6203,-23.1278,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,55.4325,-1.8715,6.6509,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0134,V134_DDR,20.1781,0.9615,-31.4365,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0138,V138_DDR,39.3549,0.2554,-11.5536,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,49.1452,-1.6422,0.1343,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0143,V143_DDR,40.0886,-0.0998,-10.4647,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0149,V149_DDR,5.6977,-2.7215,-42.2338,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0150,V150_DDR,6.1575,-2.7181,-41.7774,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0155,V155_DDR,39.8864,0.0197,-10.7864,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0156,V156_DDR,55.4325,-1.8715,6.6509,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0166,V166_DDR,44.5947,1.8054,-7.8638,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,48.3642,-1.6656,-0.6233,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,6.1575,-2.7181,-41.7774,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0170,V170_DDR,4.1230,-2.5083,-44.0218,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,-3.8693,-2.7318,-51.7906,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0176,V176_DDR,6.1575,-2.7181,-41.7774,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0177,V177_DDR,-6.6666,-4.1650,-53.1547,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,41.4840,-1.6684,-7.5006,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,6.6266,-3.2691,-40.7574,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0195,V195_DDR,159.8900,3.1728,106.0641,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0197,V197_DDR,45.0026,0.8836,-6.5341,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0198,V198_DDR,44.5947,1.8054,-7.8638,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0208,V208_DDR,160.0590,3.2754,106.1305,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0209,V209_DDR,160.0590,3.2754,106.1305,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,44.3062,0.4307,-6.7776,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0216,V216_DDR,30.7251,-1.6396,-18.2884,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0219,V219_DDR,39.8864,0.0197,-10.7864,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0220,V220_DDR,6.1575,-2.7181,-41.7774,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0224,V224_DDR,17.9113,-1.8886,-30.8532,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0225,V225_DDR,17.9139,-1.8860,-30.8532,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0226,V226_DDR,17.9113,-1.8886,-30.8532,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0227,V227_DDR,17.9113,-1.8886,-30.8532,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0229,V229_DDR,-6.7617,-0.4609,-56.9539,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0231,V231_DDR,36.6900,0.0149,-13.9780,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0238,V238_DDR,-6.6995,-4.3684,-52.9842,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.VOLT.0242,V242_DDR,39.7098,0.1349,-11.0781,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-10.0000,-5.7772,-54.8759,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-0.0629,-2.8147,-47.9013,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-5.5056,-3.8864,-52.2723,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,-2.9302,-3.4869,-50.0964,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-10.0000,-5.7772,-54.8759,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,-2.5879,-3.5921,-49.6489,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-27.3389,-6.6154,-71.3766,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEHL7,OKGEHL7_H,39.8674,-1.6468,-9.1389,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEHL8,OKGEHSL1UN8_RA,39.8674,-1.6468,-9.1389,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEHL910,OKGEHSL1PLT2,39.8674,-1.6468,-9.1389,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,-2.7075,-3.5848,-49.7758,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEMCC,OKGEMCCLAIPLT1,15.1578,-2.7258,-32.7695,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,41.4979,-0.2367,-8.9185,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,41.4979,-0.2367,-8.9185,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,41.3762,-0.3584,-8.9185,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,31.7183,-2.7226,-16.2122,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,31.7183,-2.7226,-16.2122,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,31.7183,-2.7226,-16.2122,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,31.8965,-2.5444,-16.2122,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGESM1,OKGESEMINOLEUN1_RA,32.0959,-1.5945,-16.9627,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGESM2,OKGESEMINOLEUN2_RA,27.0600,-1.5829,-22.0102,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGESM3,OKGESEMINOLEUN3_RA,27.0600,-1.5829,-22.0102,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGESO1,OKGESONR1UN1_RA,-22.1840,-3.4264,-69.4107,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGESO2,OKGESONR1UN2_RA,-9.0693,-3.6914,-56.0309,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,-3.0008,-3.8780,-49.7758,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,-2.1154,-5.0887,-47.6798,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGETINK5A,OKGETINK5UN1_RA,28.9110,-1.6904,-20.0517,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGETINK5B,OKGETINK5UN2_RA,28.9110,-1.6904,-20.0517,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,-2.2960,-3.6442,-49.3049,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-5.7322,-4.0755,-52.3098,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,70.8845,1.8544,18.3771,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-0.0629,-2.8147,-47.9013,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE_OKGE,OKGE_LA,36.0525,-1.0355,-13.5651,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-5.3339,-1.2970,-54.6900,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,-2.4800,-3.8282,-49.3049,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMLP,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,47.8308,-0.3821,-2.4402,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,71.3914,1.1665,19.5718,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_GENHUB,OMPA_GENHUB_H,17.4700,-2.1567,-31.0264,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-52.7684,-2.2454,-101.1761,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,4.6643,-3.7485,-42.2403,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-7.1593,-3.9886,-53.8237,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-4.4273,-5.4785,-49.6018,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,17.7516,-4.2482,-28.6532,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,146.6700,-0.4145,96.4314,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-52.9002,-2.3772,-101.1761,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-52.9002,-2.3772,-101.1761,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_SPP,OMPA_SPP_LA,22.2200,-2.2757,-26.1574,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-10.0000,-5.7772,-54.8759,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,45.5870,-0.4210,-4.6450,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,45.5870,-0.4210,-4.6450,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,45.5870,-0.4210,-4.6450,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,45.5870,-0.4210,-4.6450,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,ONT,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,21.5644,-2.4287,-26.6600,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,21.5644,-2.4287,-26.6600,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,21.5644,-2.4287,-26.6600,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,21.5644,-2.4287,-26.6600,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,21.5644,-2.4287,-26.6600,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,21.5644,-2.4287,-26.6600,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,21.5644,-2.4287,-26.6600,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,21.5644,-2.4287,-26.6600,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,21.5644,-2.4287,-26.6600,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,21.5533,-2.3492,-26.7506,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,21.5405,-2.4007,-26.7119,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,21.4954,-1.9376,-27.2201,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,21.3809,-2.2564,-27.0157,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,21.3809,-2.2564,-27.0157,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD_GLDN,OPPD_GLDN_LA,21.2866,-2.3915,-26.9750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,21.7227,-2.3899,-26.5405,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,15.4424,-4.9060,-30.3047,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,17.4641,-3.0013,-30.1877,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,21.5409,-2.3991,-26.7131,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD_OPPD,OPPD_LA,21.6367,-2.2638,-26.7526,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,21.4398,-2.2066,-27.0067,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,21.4224,-2.2204,-27.0103,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,OTP,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,OVEC,OVEC,37.6686,-0.2667,-12.7178,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PARAGOULD,PARAGOULD_LA,32.3958,0.9174,-19.1746,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,48.0954,-0.3957,-2.1619,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,48.0954,-0.3957,-2.1619,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,48.0954,-0.3957,-2.1619,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,47.6169,-0.2226,-2.8136,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,47.6169,-0.2226,-2.8136,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,47.6169,-0.2226,-2.8136,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PIGGOTT,PIGGOTT_LA,33.8593,0.7652,-17.5590,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PJM,PJM,35.1242,-0.5021,-15.0268,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PLUM,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,POPLARBLUFF,POPLARBLUFF_LA,36.9248,0.5126,-14.2408,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,42.2599,0.2944,-8.6876,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,42.2599,0.2944,-8.6876,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,40.7789,0.3115,-10.1857,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,40.7789,0.3115,-10.1857,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,41.8825,2.7945,-11.5651,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,41.8825,2.7945,-11.5651,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,41.9675,0.8423,-9.5279,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,47.8921,-0.6151,-2.1459,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-5.1869,-3.0793,-52.7606,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,83.1694,-0.2660,32.7823,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,21.1086,-1.3575,-28.1870,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,26.1087,-0.6255,-23.9189,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,53.5107,0.6049,2.2527,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,47.6416,0.7560,-3.7675,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,9.5456,-2.6527,-38.4547,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,36.6473,0.3363,-14.3421,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,5.7313,-3.4715,-41.4503,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,36.8182,3.0117,-16.8466,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,21.0305,-0.1845,-29.4381,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,7.6399,-2.2346,-40.7786,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,PUPP,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,RCEAST,RCEAST,-0.6524,-2.2716,-49.0339,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SALINA_1,GRDASALINA1UN1_RA,47.1083,-0.1005,-3.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SALINA_2,GRDASALINA1UN2_RA,47.1083,-0.1005,-3.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SALINA_3,GRDASALINA1UN3_RA,47.1083,-0.1005,-3.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SALINA_4,GRDASALINA1UN4_RA,47.1083,-0.1005,-3.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SALINA_5,GRDASALINA1UN5_RA,47.1083,-0.1005,-3.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SALINA_6,GRDASALINA1UN6_RA,47.1083,-0.1005,-3.4443,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SARPY_1,OPPDSARPYUN1_RA,21.2101,-2.3622,-27.0808,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SARPY_2,OPPDSARPYUN2_RA,21.2448,-2.2669,-27.1414,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SARPY_3,OPPDSARPYUN3_RA,21.0594,-2.4650,-27.1287,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SARPY_4,OPPDSARPYUN4_RA,21.0594,-2.4650,-27.1287,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SARPY_5,OPPDSARPYUN5_RA,21.0594,-2.4650,-27.1287,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SC,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SCEG,VACS,48.1679,0.7966,-3.2818,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SCSE,SCSE,6.9187,-1.2457,-42.4887,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SEC,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-9.4747,-3.9869,-56.1409,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-9.4747,-3.9869,-56.1409,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-9.4747,-3.9869,-56.1409,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-8.9788,0.2331,-59.8650,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-9.4747,-3.9869,-56.1409,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-9.7618,-2.8410,-57.5739,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,-6.8295,-3.6467,-53.8359,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,-6.8295,-3.6467,-53.8359,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,-2.9219,-3.0174,-50.5575,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-9.3871,-3.9171,-56.1230,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,1.8718,-3.3660,-45.4153,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-10.4028,-0.3561,-60.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,-3.1504,-1.6897,-52.1137,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-9.3470,-3.8537,-56.1464,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,-3.1016,-1.7607,-51.9940,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-22.2000,-3.8738,-68.9793,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,-7.1781,-1.9491,-55.8821,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-9.5957,-1.5490,-58.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-9.5957,-1.5490,-58.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-9.5957,-1.5490,-58.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-9.5957,-1.5490,-58.6997,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-10.1990,-1.8219,-59.0302,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-9.7618,-2.8410,-57.5739,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI_SECI,SECI_LA,-7.4324,-1.5877,-56.4978,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-12.0300,-4.4732,-58.2099,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-12.0300,-4.4732,-58.2099,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,-2.9219,-3.0174,-50.5575,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SEHA,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,-2.4800,-3.8282,-49.3049,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SERU,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SETH,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SGE,SGE,5.9840,-1.1280,-43.5411,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SMEP,MISO,32.7042,-0.2963,-17.6525,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SOCO,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPA,SPA,49.8021,0.7859,-1.6369,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPC,SPC,35.1857,0.8961,-16.3635,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPPNORTH_HUB,SPPNORTH_H,18.2000,-2.3967,-30.0563,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPPSOUTH_HUB,SPPSOUTH_H,24.2453,-2.3932,-24.0147,50.6532\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,46.0000,0.7254,-5.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,46.0000,0.7254,-5.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,45.7290,0.6235,-5.5476,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,45.7290,0.6235,-5.5476,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_NIXA,SPRM_NIXA_LA,46.1208,0.7710,-5.3033,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_SPRM,SPRM_LA,46.1909,0.8746,-5.3367,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,45.8434,0.4546,-5.2643,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,45.8434,0.4546,-5.2643,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,45.7195,0.3307,-5.2643,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,45.8434,0.4546,-5.2643,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,229.4310,4.7588,174.0192,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,240.2244,4.2801,185.2912,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,28.3833,0.4969,-22.7667,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,28.3833,0.4969,-22.7667,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,221.8312,1.1535,170.0246,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,225.6473,4.8882,170.1060,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,229.4866,3.8621,174.9714,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,236.3485,7.4385,178.2570,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,219.3252,2.4168,166.2553,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,230.5268,5.6432,174.2306,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,232.1567,6.2626,175.2411,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,232.1567,6.2626,175.2411,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,230.5268,5.6432,174.2306,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,28.7547,0.6479,-22.5463,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,240.2244,4.2801,185.2912,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,28.1598,0.7924,-23.2857,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,-2.1754,-1.6373,-51.1911,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,17.6774,1.0208,-33.9965,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,26.7438,2.0480,-25.9573,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,24.1586,0.7865,-27.2809,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,-25.0000,-2.0717,-73.5814,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,-25.0000,-2.0717,-73.5814,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,-25.0000,-2.0717,-73.5814,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,-25.0000,-2.0717,-73.5814,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GRID.WRAB,WRAB_DDR,37.6643,3.2016,-16.1904,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,-25.0000,-2.0717,-73.5814,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,216.6691,2.5473,163.4687,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,216.6691,2.5473,163.4687,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,210.5096,2.6308,157.2258,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,210.5096,2.6308,157.2258,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,210.5096,2.6308,157.2258,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,216.6691,2.5473,163.4687,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,38.9174,0.5204,-12.2560,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,38.9089,0.5204,-12.2646,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,38.9340,0.5204,-12.2395,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,29.0369,-0.6755,-20.9407,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,230.8965,5.7278,174.5157,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,219.2374,2.3789,166.2054,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,219.2374,2.3789,166.2054,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,219.2374,2.3789,166.2054,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,219.2374,2.3789,166.2054,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,227.5398,5.9655,170.9212,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,230.2814,5.5348,174.0935,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,230.2814,5.5348,174.0935,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,-2.2335,-3.5817,-49.3049,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,36.7150,0.4273,-14.3654,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,36.7150,0.4273,-14.3654,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,38.5857,0.5251,-12.5925,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,37.6643,3.2016,-16.1904,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,1.3262,-0.7809,-48.5460,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,23.5730,0.3660,-27.4461,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-20.1207,-2.3966,-68.3772,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,37.4336,1.1459,-14.3654,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.PLANTX1,SPS.PLANTX1_H,233.1207,4.3879,178.0797,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.PLANTX2,SPS.PLANTX2_H,233.1207,4.3879,178.0797,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,232.3205,4.2963,177.3711,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,221.5649,1.7593,169.1526,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,-12.1676,-1.4259,-61.3948,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,230.3943,4.7698,174.9714,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,221.6893,1.8836,169.1526,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,28.8538,0.7470,-22.5463,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,228.4892,5.2204,172.6157,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,236.3485,7.4385,178.2570,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,228.4892,5.2204,172.6157,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,229.5201,6.5004,172.3666,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-111.8729,0.2041,-162.7301,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,235.4192,9.5094,175.2567,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,235.6722,9.7624,175.2567,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,234.5357,9.0511,174.8315,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,230.9563,6.2539,174.0493,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,236.1027,9.1941,176.2555,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-10.4981,-2.0712,-59.0800,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,37.5974,2.9978,-16.0535,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,230.3736,4.5661,175.1544,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,230.3736,4.5661,175.1544,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,228.4892,5.2204,172.6157,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,219.7454,2.6843,166.4080,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,226.7726,7.4058,168.7137,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,233.4040,7.6789,175.0720,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,231.5629,5.6928,175.2170,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,233.7114,3.0438,180.0145,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,235.4192,9.5094,175.2567,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,237.2153,10.6565,175.9057,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,236.4008,9.8420,175.9057,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,222.1780,2.3724,169.1526,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,232.1275,6.4947,174.9797,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,-9.1729,-1.1444,-58.6816,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,-9.2033,-1.2380,-58.6183,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0163,V163_DDR,40.0604,1.4133,-12.0060,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0168,V168_DDR,15.6999,-0.5683,-34.3849,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0180,V180_DDR,237.2153,10.6565,175.9057,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0181,V181_DDR,-10.2566,-0.6731,-60.2366,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0182,V182_DDR,236.0759,9.2285,176.1943,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0199,V199_DDR,226.4038,6.9320,168.8188,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0200,V200_DDR,232.4168,7.2706,174.4931,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.VOLT.0235,V235_DDR,1.3262,-0.7809,-48.5460,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,229.4866,3.8621,174.9714,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,236.3485,7.4385,178.2570,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,38.6572,1.1978,-13.1936,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,36.6197,0.9959,-15.0293,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS_SPS,SPS_LA,180.1800,6.0803,123.4467,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,228.7373,4.9762,173.1080,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SSCN_NPPD,SSCN_NPPD_LA,-6.7816,-3.3684,-54.0663,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,36.9492,0.4716,-14.1754,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,36.9492,0.4716,-14.1754,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,TAL,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,TEC,SOUC,48.1943,0.9197,-3.3785,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,-0.6089,-5.8909,-45.3711,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,TVA,TVA,48.1246,0.6671,-3.1956,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,UCUHUB,UCUHUB_H,10.7562,-2.3885,-37.5084,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,UCUHUB17,UCUHUB17_H,-2.9923,-2.8771,-50.7684,50.6532\n03/19/2025 21:00:00,03/20/2025 02:00:00,UCUHUB18,UCUHUB18_H,1.4683,-2.8903,-46.2944,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,UCUHUB19,UCUHUB19_H,-1.5238,-2.9529,-49.2239,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,UCUHUB20,UCUHUB20_H,-0.7458,-2.8261,-48.5728,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,UCUHUB21,UCUHUB21_H,-1.9720,-2.9528,-49.6723,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,UCUHUB22,UCUHUB22_H,-2.4909,-3.1085,-50.0355,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,UCUHUB23,UCUHUB23_H,-3.0880,-3.1237,-50.6174,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,UCUHUB24,UCUHUB24_H,0.9882,-2.7667,-46.8982,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,36.7838,1.5238,-15.3931,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,36.7838,1.5238,-15.3931,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,8.3740,-1.9502,-40.3289,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,8.3740,-1.9502,-40.3289,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,18.0775,-1.8851,-30.6905,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,39.2750,-0.6170,-10.7611,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,39.2750,-0.6170,-10.7611,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,36.7838,1.5238,-15.3931,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,18.7508,-1.4676,-30.4347,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,24.2588,-0.1638,-26.2305,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,5.9226,-2.6034,-42.1271,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,1.1317,-6.1594,-43.3619,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,39.6229,1.4647,-12.4949,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,39.6229,1.4647,-12.4949,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,14.2007,-6.1660,-30.2863,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,6.1966,-3.4429,-41.0136,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,18.7554,-1.7964,-30.1013,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,3.5390,-3.4974,-43.6167,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,5.6880,-2.5784,-42.3867,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,4.5778,-3.7799,-42.2953,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,16.3531,-4.0136,-30.2863,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,16.3531,-4.0136,-30.2863,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,6.3537,-3.1536,-41.1458,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,1.8765,-6.1475,-42.6291,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,8.1056,-0.3204,-42.2271,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,39.0062,-0.3853,-11.2616,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,39.0062,-0.3853,-11.2616,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,39.0062,-0.3853,-11.2616,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,38.9082,-0.2875,-11.4574,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,38.9082,-0.2875,-11.4574,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,38.9082,-0.2875,-11.4574,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,36.1786,2.2012,-16.6757,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,14.8103,-2.0678,-33.7750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,14.8103,-2.0678,-33.7750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,6.4004,-1.2287,-43.0239,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,2.7268,-3.1489,-44.7774,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,35.0158,-0.3556,-15.2817,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,-7.6467,-3.6875,-54.6122,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,-0.1777,-7.2173,-43.6134,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,16.9213,-3.4663,-30.2654,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,38.5687,1.1157,-13.2000,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,38.5687,1.1157,-13.2000,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,38.5600,1.1071,-13.2002,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,38.5687,1.1157,-13.2000,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,38.9650,0.9804,-12.6685,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,38.9650,0.9804,-12.6685,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,38.9650,0.9804,-12.6685,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,38.9650,0.9804,-12.6685,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,38.9650,0.9804,-12.6685,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,38.9650,0.9804,-12.6685,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,38.9650,0.9804,-12.6685,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,-1.6865,-5.7194,-46.6202,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,21.3408,-1.0332,-28.2791,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,0.0000,-2.9202,-47.7329,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,0.0000,-2.9202,-47.7329,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,-3.7739,-4.0931,-50.3338,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,-3.7739,-4.0931,-50.3338,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,15.4403,-1.4378,-33.7750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,29.4649,-1.1667,-20.0214,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,3.8704,-4.1219,-42.6608,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,3.8688,-5.5032,-41.2811,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,11.2550,-2.2857,-37.1124,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,18.0775,-1.8851,-30.6905,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,18.0775,-1.8851,-30.6905,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,3.5390,-3.4974,-43.6167,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,-0.5737,-2.3383,-48.8885,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,10.0744,-3.8163,-36.7624,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,2.0535,-5.9705,-42.6291,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,5.3200,-3.6357,-41.6974,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.FSE,WAUE.FSE_H,0.5490,-3.6667,-46.4374,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,39.6715,0.0346,-11.0162,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,39.8398,-0.0640,-10.7493,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,0.1056,-6.2924,-44.2551,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,1.6722,-6.0214,-42.9595,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,17.4927,-2.0376,-31.1228,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,19.0134,-2.2639,-29.3758,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-12.7300,-6.0487,-57.3344,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,1.1317,-6.1594,-43.3619,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-25.4054,-1.6517,-74.4068,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,10.8563,-3.6045,-36.1923,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,11.1095,-3.3513,-36.1923,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,10.8595,-3.6013,-36.1923,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,1.5545,-3.3073,-45.7913,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,-0.5737,-2.3383,-48.8885,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,8.9501,-2.0211,-39.6819,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,3.5423,-3.5906,-43.5202,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,7.9085,-0.5175,-42.2271,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,12.5830,-0.9905,-37.0796,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,6.2945,-2.3728,-41.9857,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,16.2128,-2.2360,-32.2043,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,5.4391,-2.6045,-42.6095,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,3.6554,-4.0568,-42.9409,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,-7.6467,-3.6875,-54.6122,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,17.6571,-0.3643,-32.6317,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,3.4672,-3.5574,-43.6284,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,17.4605,-0.5091,-32.6835,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,8.1072,-1.9774,-40.5685,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,20.5489,-2.6756,-27.4286,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NTWK,WAUE.NTWK_H,10.7580,-2.3638,-37.5312,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,12.6509,0.2249,-38.2271,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,12.6509,0.2249,-38.2271,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,0.7542,-6.4912,-43.4077,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,-3.4135,-7.2315,-46.8351,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,9.3972,-2.8662,-38.3896,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,0.7542,-6.4912,-43.4077,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,19.7705,-1.3147,-29.5679,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,5.0192,-3.9308,-41.7031,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,-7.6467,-3.6875,-54.6122,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,7.8487,-2.6785,-40.1259,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,4.7875,-4.1625,-41.7031,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,-3.6434,-7.0033,-47.2932,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,-1.7523,-6.9216,-45.4838,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,10.3537,-2.1284,-38.1710,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,6.9658,-5.6876,-37.9997,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,9.0526,-2.3693,-39.2311,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,3.3772,-5.0402,-42.2357,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,3.8688,-5.5032,-41.2811,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.VOLT.0152,V152_DDR,34.7331,2.7376,-18.6576,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE.VOLT.0172,V172_DDR,38.9605,1.1824,-12.8750,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_BEPM,WAUE_BEPM_LA,24.2132,-0.3350,-26.1048,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,8.6570,-2.1076,-39.8885,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,12.5848,-0.9610,-37.1073,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_EWA,WAUE_EWA_LA,-1.8899,-2.1008,-50.4422,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,4.0362,-4.0582,-42.5587,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_HMMU,WAUE_HMMU_LA,17.5814,-1.3695,-31.7022,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,15.3116,-2.0392,-33.3023,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_MECB,WAUE_MECB_LA,10.0839,-1.3786,-39.1906,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_MMPA,WAUE_MMPA_LA,18.6469,-0.2130,-31.7932,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_MRES,WAUE_MRES_LA,5.4604,-2.6665,-42.5261,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,29.9977,1.6845,-22.3398,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,39.6715,0.0346,-11.0162,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,3.6911,-3.5591,-43.4029,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_OTP,WAUE_OTP_LA,23.7405,1.0915,-28.0041,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_OTPW,WAUE_OTPW_LA,32.7405,1.9629,-19.8756,50.6532\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM,WAUE_UGPM_LA,12.1262,-1.7977,-36.7292,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,20.5769,-0.9451,-29.1310,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,6.8773,-2.5762,-41.1995,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,22.7094,-2.2642,-25.6795,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,-1.8899,-2.1008,-50.4422,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,17.5814,-1.3695,-31.7022,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,4.3249,-4.1199,-42.2082,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,39.6715,0.0346,-11.0162,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,18.6469,-0.2130,-31.7932,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,7.8764,-2.2057,-40.5709,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,4.4927,-4.0107,-42.1497,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,23.1947,1.4231,-28.8814,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-3.9050,-5.2200,-49.3381,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-1.2875,-5.1020,-46.8386,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,38.1531,-2.6174,-9.8826,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,85.1180,0.6346,33.8303,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,85.1180,0.6346,33.8303,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,9.5040,-5.8753,-35.2738,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,80.1986,0.8922,28.6533,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,74.0975,0.7792,22.6652,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,74.1465,-2.6264,26.1198,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,74.1465,-2.6264,26.1198,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,74.1465,-2.6264,26.1198,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,74.1465,-2.6264,26.1198,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,74.1465,-2.6264,26.1198,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,74.1465,-2.6264,26.1198,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,74.1465,-2.6264,26.1198,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,74.1465,-2.6264,26.1198,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,53.9704,-2.4544,5.7717,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-20.1207,-2.3966,-68.3772,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-30.0000,-4.8188,-75.8343,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-5.9921,-6.4655,-50.1797,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,229.9451,4.3206,174.9714,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_ENMC,WFEC_ENMC_LA,231.2096,6.9810,173.5755,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-5.9082,-4.2127,-52.3486,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,52.0821,-0.0596,1.4886,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,228.0697,5.5527,171.8639,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-3.9050,-5.2200,-49.3381,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-3.9050,-5.2200,-49.3381,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-3.9050,-5.2200,-49.3381,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_OKGE,WFEC_OKGE_LA,34.3650,-0.5091,-15.7789,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,76.4511,1.2076,24.5904,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,0.6095,-6.6912,-43.3524,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,11.1913,-6.9670,-32.4948,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_WFEC,WFEC_LA,42.9699,-1.1076,-6.5756,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,228.0697,5.5527,171.8639,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-9.1982,-4.5944,-55.2569,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,-7.3775,-1.8515,-56.1791,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,8.4734,-2.9946,-39.1850,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,8.4734,-2.9946,-39.1850,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,8.4798,-2.9883,-39.1850,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,8.4798,-2.9883,-39.1850,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,8.4861,-2.9820,-39.1850,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,8.4861,-2.9820,-39.1850,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,8.4861,-2.9820,-39.1850,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,23.4967,0.4857,-27.6421,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,6.8835,-3.7812,-39.9884,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-3.2526,-4.0559,-49.8498,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-3.2526,-4.0559,-49.8498,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-3.2526,-4.0559,-49.8498,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-8.3493,-4.0040,-54.9984,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-8.3493,-4.0040,-54.9984,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,1.9737,-3.7184,-44.9610,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,1.9737,-3.7184,-44.9610,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,1.9737,-3.7184,-44.9610,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,6.8835,-3.7812,-39.9884,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,12.7554,-1.9437,-35.9540,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.HEC.GT1,WRHECGTUN32_RA,3.4964,-3.4059,-43.7508,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.HEC.GT2,WRHECGTUN33_RA,3.4964,-3.4059,-43.7508,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.HEC.GT3,WRHECGTUN34_RA,3.4964,-3.4059,-43.7508,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.HEC.GT4,WRHECGTUN35_RA,3.4964,-3.4059,-43.7508,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,12.7554,-1.9437,-35.9540,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-9.1483,-3.6459,-56.1555,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-27.0544,-2.3233,-75.3842,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.JEC.1,WRJEFFUN10_RA,8.9647,-3.1347,-38.5537,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.JEC.2,WRJEFFUN11_RA,9.0227,-3.1499,-38.4805,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.JEC.3,WRJEFFUN12_RA,8.7820,-3.3906,-38.4805,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-6.3156,-4.0024,-52.9663,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-12.8400,-4.0352,-59.4579,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-12.8400,-4.0352,-59.4579,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.LEC.4,WRLECUN26_RA,7.6472,-1.8944,-41.1115,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.LEC.5,WRLECUN27_RA,8.8102,-1.7752,-40.0677,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,4.7966,-3.2482,-42.6083,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,4.7966,-3.2482,-42.6083,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,4.7966,-3.2482,-42.6083,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,4.9141,-3.1530,-42.5860,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-12.0300,-4.4732,-58.2099,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-12.0300,-4.4732,-58.2099,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,-2.8229,-1.2656,-52.2104,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-7.4768,-4.4802,-53.6497,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-7.4768,-4.4802,-53.6497,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,2.3711,-5.1294,-43.1526,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-12.0300,-4.4732,-58.2099,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,10.3794,-4.3464,-35.9273,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,5.6289,-4.2528,-40.7714,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-12.8623,-4.0575,-59.4579,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,74.5034,0.8274,23.0230,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,0.0000,-7.1549,-43.4982,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,8.4861,-2.9820,-39.1850,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,3.7468,-4.4754,-42.4309,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,12.7554,-1.9437,-35.9540,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,6.8835,-3.7812,-39.9884,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-0.5115,-3.2739,-47.8907,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.THAYERLD,WR.THAYERLD_LA,36.6326,0.6635,-14.6840,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-0.8976,-3.2297,-48.3210,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0106,V106_DDR,-0.7429,-3.1643,-48.2317,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0139,WR.VOLT.0139_H,7.0010,-1.4787,-42.1734,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0141,WR.VOLT.0141_H,6.5900,-3.2523,-40.8108,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0146,WR.VOLT.0146_H,7.8224,-1.4794,-41.3513,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0147,WR.VOLT.0147_H,7.8224,-1.4794,-41.3513,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0148,WR.VOLT.0148_H,9.2350,-1.7470,-39.6711,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-0.4214,-2.8033,-48.2712,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0157,V157_DDR,7.8519,-1.5281,-41.2731,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0158,V158_DDR,7.8224,-1.4794,-41.3513,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0159,WR.VOLT.0159_H,7.8224,-1.4794,-41.3513,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-1.6470,-3.4633,-48.8368,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0173,V173_DDR,4.1369,-3.6404,-42.8757,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0174,V174_DDR,-1.2003,-3.2112,-48.6422,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0184,V184_DDR,-1.1708,-3.5126,-48.3113,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-0.5873,-3.2466,-47.9937,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0186,V186_DDR,-0.3285,-3.3795,-47.6021,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-1.0610,-3.4098,-48.3042,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-0.9450,-3.1729,-48.4252,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0189,WR.VOLT.0189_H,5.2221,-2.7312,-42.6998,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0190,WR.VOLT.0190_H,7.6999,-2.7354,-40.2178,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0191,WR.VOLT.0191_H,8.2388,-2.8207,-39.5936,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0192,WR.VOLT.0192_H,8.2388,-2.8207,-39.5936,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0196,WR.VOLT.0196_H,7.6999,-2.7354,-40.2178,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0245,V245_DDR,-0.5699,-3.2475,-47.9755,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.VOLT.0248,V248_DDR,-0.7429,-3.1643,-48.2317,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-4.4390,-3.8256,-51.2665,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,10.5962,-2.2037,-37.8532,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.WOLF,WRWOLFUN15_RA,2.5342,-4.7367,-43.3821,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-9.1483,-3.6459,-56.1555,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,23.2283,0.2174,-27.6421,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-3.2526,-4.0559,-49.8498,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-3.2526,-4.0559,-49.8498,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-3.2526,-4.0559,-49.8498,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-3.2526,-4.0559,-49.8498,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,1.7366,-3.2304,-45.6860,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,6.6427,-3.2587,-40.7517,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-2.0498,-3.2553,-49.4476,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-2.0498,-3.2553,-49.4476,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-2.0498,-3.2553,-49.4476,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-2.0498,-3.2553,-49.4476,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,8.1533,-2.6779,-39.8219,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,8.1533,-2.6779,-39.8219,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,8.1533,-2.6779,-39.8219,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,8.1533,-2.6779,-39.8219,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,8.1533,-2.6779,-39.8219,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,8.1533,-2.6779,-39.8219,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-11.0037,-3.2121,-58.4446,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-11.0037,-3.2121,-58.4446,50.6530\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-13.3414,-3.3804,-60.6141,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-13.3414,-3.3804,-60.6141,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_MIDW,WR_MIDW_LA,-2.8242,-3.4601,-50.0172,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,59.9628,0.0093,9.3004,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,37.3574,-0.7882,-12.5075,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,0.9627,-3.4623,-46.2281,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_SEG,WR_SEG_LA,20.4842,-0.1349,-30.0340,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,WR_WR,WR_LA,6.4650,-2.6813,-41.5068,50.6531\n03/19/2025 21:00:00,03/20/2025 02:00:00,YAD,VACS,48.1679,0.7966,-3.2818,50.6531\n03/19/2025 22:00:00,03/20/2025 03:00:00,AEC,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,AECC_CSWS,CSWS_AECC_LA,53.6700,0.2138,16.0375,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,36.4398,-0.1358,-0.8431,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,85.3147,0.1869,47.7091,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,35.9285,-0.3948,-1.0954,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,44.0596,-0.5906,7.2315,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,81.8112,-0.2822,44.6747,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,41.2956,-0.7183,4.5952,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,AECI,AECI,39.0373,-0.6066,2.2252,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,AEPM_CSWS,CSWS_LA,41.2659,0.2947,3.5525,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,ALTW,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,AMRN,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,124.4885,3.0849,83.9848,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,BBA,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,BCA,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,BEPM.ER01.DDR,ER01_DDR,2.8108,-4.4076,-30.2003,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,BEPM_ER01,BEPM_ER01_LA,2.8108,-4.4076,-30.2003,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,5.3586,-0.1826,-31.8775,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,9.0894,0.8261,-29.1555,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,BEPM_UM01,BEPM_UM01_LA,41.3393,0.7642,3.1564,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,BLKW,BLKW,133.3406,5.2211,90.7008,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-29.5965,-3.1077,-63.9075,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-29.5965,-3.1077,-63.9075,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,57.8079,-1.4454,21.8346,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.5377,-3.0489,-63.9075,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,BRAZ,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,BUBA,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-1.3920,-0.7978,-38.0129,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,2.9800,-2.2558,-32.1829,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,2.9800,-2.2558,-32.1829,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,2.9800,-2.2558,-32.1829,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,2.9800,-2.2558,-32.1829,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,2.9800,-2.2558,-32.1829,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-6.7951,-2.4379,-41.7759,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,15.2806,-1.7157,-20.4225,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,15.2806,-1.7157,-20.4225,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CLEC,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,36.2786,-0.3924,-0.7477,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,COWP,COWP_LA,39.6362,-0.1305,2.3480,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,39.6362,-0.1305,2.3480,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,39.6362,-0.1305,2.3480,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CPLE,VACS,44.0196,0.1463,6.4546,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CPLW,VACS,44.0196,0.1463,6.4546,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,49.5189,0.4259,11.6743,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,49.5189,0.4259,11.6743,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,49.5189,0.4259,11.6743,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,49.5189,0.4259,11.6743,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CRTH_SPA,WRCRTH_SPA_LA,39.6778,-1.0702,3.3293,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,45.5154,1.9406,6.1561,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,30.9915,-1.3833,-5.0439,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,41.2956,-0.7183,4.5952,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,35.9285,-0.3948,-1.0954,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,45.5036,1.9363,6.1486,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,43.6646,0.5471,5.6987,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,45.0766,1.6548,6.0031,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,45.0766,1.6548,6.0031,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,35.1691,-0.7004,-1.5492,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,35.1691,-0.7004,-1.5492,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,35.1662,-0.7033,-1.5492,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,35.1662,-0.7033,-1.5492,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,41.2956,-0.7183,4.5952,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,43.7875,1.0065,5.3623,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,46.8979,-1.1589,10.6381,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,46.6288,-1.4280,10.6381,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,37.0617,-0.8118,0.4547,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,33.5321,-0.6824,-3.2042,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,33.5321,-0.6824,-3.2042,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,33.3680,-0.8464,-3.2043,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,33.3680,-0.8464,-3.2043,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-7.0701,-1.6929,-42.7960,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,36.8522,-1.2387,0.6722,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,47.7114,-0.7410,11.0337,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-0.0534,-1.1613,-36.3108,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-0.0805,-1.1884,-36.3108,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,16.1716,-1.3543,-19.8928,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.GRID.CDL1,CDL1_DDR,42.6297,-0.2830,5.4940,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,22.1865,-1.9000,-13.3322,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,32.0418,-1.3909,-3.9860,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,42.6297,-0.2830,5.4940,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.NUEN.CSI1,CSI1_DDR,34.9839,-0.2466,-2.1882,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.NUEN.CSI2,CSI2_DDR,34.9984,-0.2321,-2.1882,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,36.2855,-0.3855,-0.7477,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.NUEN.GAZA,GAZA_DDR,42.6297,-0.2830,5.4940,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,98.6272,0.6423,60.5662,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.NUEN.T201,NT201_DDR,34.1368,-0.5261,-2.7558,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,24.0930,-1.7497,-11.5760,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,24.0930,-1.7497,-11.5760,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,41.2956,-0.7183,4.5952,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,45.0263,2.2222,5.3854,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,16.1716,-1.3543,-19.8928,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,16.1716,-1.3543,-19.8928,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,4.4160,-1.7756,-31.2271,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-0.0805,-1.1884,-36.3108,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,44.2824,0.7251,6.1386,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,31.1140,-0.8508,-5.4539,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,30.7226,-1.2422,-5.4539,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,30.6604,-1.3044,-5.4539,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,21.8576,-0.8478,-14.7133,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,21.8576,-0.8478,-14.7133,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,43.5735,0.6101,5.5447,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,34.1361,-0.4896,-2.7930,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,43.4921,0.4814,5.5919,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,45.6243,2.9821,5.2235,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,41.9865,-0.2644,4.8322,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,34.9984,-0.2321,-2.1882,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0057,OKMU_DDR,40.1306,-0.2260,2.9379,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0060,LEHIGH_DDR,98.6272,0.6423,60.5662,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0086,WARRENM_DDR,33.9309,-0.5222,-2.9656,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,44.2888,1.8717,4.9984,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,41.3349,-0.5253,4.4415,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0121,V121_DDR,43.5735,0.6101,5.5447,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0122,V122_DDR,40.1700,-0.5540,3.3053,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0124,V124_DDR,53.9982,-0.7579,17.3374,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0135,V135_DDR,34.5459,-0.4612,-2.4116,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0144,V144_DDR,37.2109,-1.1309,0.9231,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0145,V145_DDR,37.1587,-1.3335,1.0735,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,43.6619,0.7248,5.5183,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,41.5947,-0.0952,4.2711,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0175,V175_DDR,36.2855,-0.3855,-0.7477,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,41.5947,-0.0952,4.2711,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,41.9628,0.1701,4.3740,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,34.5459,-0.4612,-2.4116,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,34.7168,-0.5063,-2.1956,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,34.3834,-0.5730,-2.4623,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,44.6291,-0.8906,8.1010,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,33.5385,-0.6755,-3.2047,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,34.7168,-0.5063,-2.1956,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0211,V211_DDR,44.0437,0.9337,5.6913,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,42.3714,-0.5116,5.4643,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0213,V213_DDR,34.3918,-0.5254,-2.5015,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0215,V215_DDR,41.2084,-0.5367,4.3263,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0217,V217_DDR,42.4035,-0.5425,5.5272,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0218,V218_DDR,44.3682,-0.8698,7.8193,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0228,V228_DDR,35.0643,-0.5791,-1.7753,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0232,V232_DDR,34.1284,-0.4709,-2.8194,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0233,V233_DDR,34.8328,-0.4755,-2.1104,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0240,V240_DDR,39.9449,-0.6583,3.1845,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0244,V244_DDR,34.7168,-0.5063,-2.1956,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0246,MDT1_DDR,98.6272,0.6423,60.5662,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0249,V249_DDR,34.3998,-0.4803,-2.5386,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0250,V250_DDR,29.8833,-1.2884,-6.2471,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0251,V251_DDR,33.9005,-0.6071,-2.9111,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.VOLT.0252,V252_DDR,44.6291,-0.8906,8.1010,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-11.9674,-1.8265,-47.5596,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,51.3711,-2.0791,16.0314,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,-1.0419,-3.4845,-34.9761,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,42.8211,-0.2224,5.6248,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-1.4015,-2.9451,-35.8751,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,33.5399,-1.3409,-2.5379,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,33.5399,-1.3409,-2.5379,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,33.5399,-1.3409,-2.5379,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,33.5399,-1.3409,-2.5379,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,33.5399,-1.3409,-2.5379,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,41.2956,-0.7183,4.5952,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,47.0202,2.0141,7.5874,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,34.0852,-0.5141,-2.8194,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,34.0306,-0.5688,-2.8194,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,45.4858,-0.0729,8.1400,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,45.4858,-0.0729,8.1400,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWWELSH1,CSWSWELSHUN1_RA,42.2444,0.2829,4.5428,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWWELSH3,CSWSWELSHUN3_RA,42.2444,0.2829,4.5428,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWWILKES1,CSWSWILKESUN1_RA,43.2838,0.8496,5.0155,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWWILKES2,CSWSWILKESUN2_RA,43.2838,0.8496,5.0155,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,CSWWILKES3,CSWSWILKESUN3_RA,43.2975,0.7374,5.1414,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-0.0534,-1.1613,-36.3108,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,DENL,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,DERS,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,DOE,DOE,40.4294,-0.1991,3.2098,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,18.8911,-1.9423,-16.5853,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,DPC,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,DUK,VACS,44.0196,0.1463,6.4546,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDDY,EDDY,133.4002,6.7767,89.2048,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,38.5858,-1.3247,2.4918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-11.6000,-1.6342,-47.3845,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,43.4278,-1.6241,7.6332,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE.SLCC,EDESTL4391_PLT,38.2493,-1.3413,2.1718,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,38.3241,-1.2160,2.1214,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,29.2981,-1.7901,-6.3305,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_EC_01,EDELAR3821UN1_RA,38.5858,-1.3247,2.4918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_EC_02,EDELAR3821UN2_RA,38.5480,-1.3626,2.4918,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_EC_03,EDELAR3821UN3_RA,38.5858,-1.3247,2.4918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_EC_04,EDELAR3821UN4_RA,38.5858,-1.3247,2.4918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_EDE,EDE_LA,38.7664,-0.4239,1.7716,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_ERW,EDEERWFUNG1_RA,-6.1013,-2.5168,-41.0032,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,5.2847,-2.5017,-29.6323,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,96.0000,0.3833,58.1980,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,96.0000,0.3833,58.1980,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,96.0000,0.3833,58.1980,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,96.0000,0.3833,58.1980,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,46.7890,0.2087,9.1616,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_RIV_10,EDERIV1671UN10_RA,37.8554,-1.4707,1.9074,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_RIV_11,EDERIV1671UN11_RA,37.8554,-1.4707,1.9074,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_RIV_12,EDERIV453UN12_PLT,36.9583,-2.3678,1.9074,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_SL_01,EDESTL4391UN1_RA,37.7208,-1.8697,2.1718,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EDE_SWMP,EDE_SWMP_LA,38.9289,-0.1370,1.6472,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EEI,EEI,40.3553,-0.2041,3.1407,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,EES,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,3.0087,-2.4021,-32.0079,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,ERCOTE,ERCOTE,42.2444,0.2829,4.5428,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,ERCOTN,ERCOTN,24.1856,-1.6571,-11.5760,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,11.0625,-1.9723,-24.3839,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FMPP,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FPC,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FPL,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FREM_50T,OPPDFREM_GUN1_RA,15.1208,-1.5405,-20.7574,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FREM_6,OPPDFREM_AUN6_RA,15.1025,-1.5520,-20.7642,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FREM_7,OPPDFREM_AUN7_RA,15.1025,-1.5520,-20.7642,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FREM_8,OPPDFREM_AUN8_RA,14.9336,-1.7209,-20.7642,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FREM_LOAD,FREM_LOAD_LA,15.0753,-1.5792,-20.7642,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,FRONTIER,WRGETTUNFRONTIER_RA,-1.7212,-1.9818,-37.1581,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,44.2796,0.7223,6.1386,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,12.4199,-1.1166,-23.8822,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-12.5580,-3.1340,-46.8427,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,36.2786,-0.3924,-0.7477,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,36.2786,-0.3924,-0.7477,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,36.2786,-0.3924,-0.7477,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,35.1633,-0.6924,-1.5630,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,35.1633,-0.6924,-1.5630,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,35.2799,-0.7027,-1.4361,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,35.2799,-0.7027,-1.4361,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-6.4550,-3.0082,-40.8655,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,60.7700,-1.1438,24.4951,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,60.7700,-1.1438,24.4951,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,60.7700,-1.1438,24.4951,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.VOLT.0130,V130_DDR,34.4625,-0.3018,-2.6545,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA.VOLT.0237,V237_DDR,33.4146,-0.5478,-3.4563,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDAHUB2,GRDAHUB2_H,23.6493,-1.3476,-12.4218,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDAHUB3,GRDAHUB3_H,20.0147,-1.5341,-15.8700,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA_GRDA,GRDA_LA,35.7924,-0.5353,-1.0910,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA_HUB,GRDA_H,28.7077,-1.0734,-7.6375,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRDA_HUBSA,GRDASA_H,27.9077,-1.1330,-8.3780,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GRE,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,21.8971,4.1985,-19.7201,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GSEC_SPS,SPS_GSEC_LA,98.8597,3.3593,58.0817,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GSPR2014HUB,GSPR2014HUB_H,80.0126,2.7013,39.8926,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GSPR2015HUB,GSPR2015HUB_H,77.5439,2.5118,37.6134,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,34.5726,1.2125,-4.0587,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,HARRISON,CSWSLEBROCKPLT1,43.3420,0.2882,5.6351,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,HAST_TNSK_HUB,HAST_TNSK_H,12.4114,-1.4800,-23.5273,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,HQST,PJM,33.2229,-0.6612,-3.5346,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,HST,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,71.0291,-0.8347,34.4451,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,71.0291,-0.8347,34.4451,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,68.7332,-0.8602,32.1747,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,68.7332,-0.8602,32.1747,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,73.3883,-0.8255,36.7951,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,73.3883,-0.8255,36.7951,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,INDN_INDN,INDN_LA,70.4848,-0.8333,33.8995,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-9.0066,-2.7673,-43.6580,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,ISNE,PJM,33.2229,-0.6612,-3.5346,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,JEA,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,15.4846,-1.5667,-20.3674,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,15.4846,-1.5667,-20.3674,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,5.0481,-1.5446,-30.8261,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,KACYCT4,KACYNEARMANUNCT4_RA,35.9020,-1.4333,-0.0834,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,72.9318,-1.4495,36.9626,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,35.9020,-1.4333,-0.0834,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,35.3776,-1.3275,-0.7136,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,35.5178,-1.3619,-0.5390,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KACY_KACY,KACY_LA,35.2800,-1.2946,-0.8441,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,30.1154,-1.5343,-5.7690,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,63.3800,-1.3890,27.3503,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-13.8400,-2.7157,-48.5430,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-19.8203,-3.1576,-54.0814,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.VOLT.0222,V222_DDR,14.4509,-1.4356,-21.5323,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.VOLT.0223,V223_DDR,20.5193,-1.7754,-15.1240,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.VOLT.0241,V241_DDR,52.1037,-0.2103,14.8953,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.VOLT.0243,V243_DDR,32.5952,-1.0045,-3.8190,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.VOLT.0247,V247_DDR,37.9779,-1.5378,2.0970,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.VOLT.0253,V253_DDR,30.7506,-1.4143,-5.2538,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,6.8380,-3.4785,-27.1022,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,17.7832,-2.0681,-17.5674,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,17.7832,-2.0681,-17.5674,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,17.7832,-2.0681,-17.5674,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,17.7832,-2.0681,-17.5674,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,30.1404,-1.4364,-5.8419,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,30.1404,-1.4364,-5.8419,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHUB,KCPLHUB_H,11.2419,-2.3706,-23.8062,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHUB17,KCPLHUB17_H,9.6879,-2.4053,-25.3255,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHUB18,KCPLHUB18_H,8.8362,-2.4495,-26.1330,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHUB19,KCPLHUB19_H,8.9138,-2.3921,-26.1128,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHUB20,KCPLHUB20_H,8.2703,-2.4554,-26.6930,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHUB21,KCPLHUB21_H,8.2012,-2.3766,-26.8408,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHUB22,KCPLHUB22_H,8.8284,-2.4062,-26.1841,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHUB23,KCPLHUB23_H,8.2355,-2.4611,-26.7220,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLHUB24,KCPLHUB24_H,7.5235,-2.5040,-27.3912,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,11.4464,-1.7260,-24.2463,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,11.4464,-1.7260,-24.2463,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,14.5669,-2.3498,-20.5020,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,14.5669,-2.3498,-20.5020,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,29.6398,-2.0099,-5.7690,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,30.1154,-1.5343,-5.7690,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,31.3676,-1.3218,-4.7293,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,31.3676,-1.3218,-4.7293,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,31.3676,-1.3218,-4.7293,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,31.3676,-1.3218,-4.7293,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,31.3676,-1.3218,-4.7293,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,31.3676,-1.3218,-4.7293,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,31.3676,-1.3218,-4.7293,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,31.3676,-1.3218,-4.7293,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,9.2116,-2.1263,-26.0808,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,33.3878,-1.3477,-2.6832,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KCPL_KCPL,KCPL_LA,30.0577,-1.4178,-5.9432,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KENN,KENN_LA,45.8088,0.1379,8.2522,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KEP2_SECI,KEP2_SECI_LA,-1.0031,0.1093,-38.5312,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,KERR_1,GRDAKERR_HYDUN1_RA,33.5099,-0.6331,-3.2757,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KERR_2,GRDAKERR_HYDUN2_RA,33.6980,-0.6205,-3.1002,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KERR_3,GRDAKERR_HYDUN3_RA,33.6980,-0.6205,-3.1002,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KERR_4,GRDAKERR_HYDUN4_RA,33.5099,-0.6331,-3.2757,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,17.8166,-2.0347,-17.5674,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,17.8166,-2.0347,-17.5674,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,19.5123,-1.8251,-16.0814,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,19.5123,-1.8251,-16.0814,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,14.3559,-2.0498,-21.0130,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,12.9542,-1.9863,-22.4782,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,12.9542,-1.9863,-22.4782,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-0.4927,-0.2402,-37.6712,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-0.4927,-0.2402,-37.6712,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-0.4927,-0.2402,-37.6712,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,8.5103,-0.0515,-28.8570,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,8.5103,-0.0515,-28.8570,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-0.5971,-0.3311,-37.6846,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,5.6726,-0.8527,-30.8933,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,6.1791,-2.0425,-29.1971,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,64.5860,-1.4663,28.6336,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,64.5860,-1.4663,28.6336,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,8.8735,-1.8575,-26.6877,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,8.8735,-1.8575,-26.6877,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,8.8735,-1.8575,-26.6877,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,8.5219,-1.1065,-27.7903,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-0.5688,-0.5853,-37.4023,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,12.7801,-1.6197,-23.0189,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,4.5514,-1.4524,-31.4150,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,LAFA,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,LAM345,LAM345,-1.3920,-0.7978,-38.0129,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,LEPA,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,16.1736,-1.3505,-19.8946,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_LES,LES_LA,16.0383,-1.4019,-19.9785,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,16.0597,-1.5503,-19.8088,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,15.8115,-1.4803,-20.1269,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,15.8115,-1.4803,-20.1269,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,15.8115,-1.4803,-20.1269,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,16.0609,-1.5490,-19.8088,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,16.0597,-1.5503,-19.8088,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_WAVERLY,LES_WAVERLY_H,15.8080,-1.5835,-20.0273,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,15.2722,-1.8877,-20.2588,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,15.2722,-1.8877,-20.2588,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,LGEE,LGEE,36.6775,-0.4316,-0.3096,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MALDEN,MALDEN_LA,44.9799,0.0867,7.4745,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MCWEST,MCWEST,44.9873,0.8072,6.7614,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MDU,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,8.0438,0.6373,-30.0122,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,12.6753,-1.1453,-23.5981,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,16.7882,0.1057,-20.7361,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,MEAN_NPPD,NPPD_MEAN_LA,9.0986,-1.5424,-26.7777,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MEC,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,MHEB,MHEB,20.3876,-0.6721,-16.3590,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-7.4692,-2.4870,-42.4009,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,8.2357,-1.2354,-27.9476,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-7.4692,-2.4870,-42.4009,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-7.4692,-2.4870,-42.4009,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,8.2357,-1.2354,-27.9476,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-1.1995,-2.0652,-36.5530,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MISO,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-1.2834,0.5941,-39.2962,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-1.2834,0.5941,-39.2962,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,7.6482,-1.8474,-27.9231,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,0.1146,-1.5351,-35.7690,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,9.5977,-1.9512,-25.8698,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,0.0000,-1.5490,-35.8697,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,1.8321,-1.4993,-34.0874,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,0.0853,-1.4382,-35.8952,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,2.9471,-1.6272,-32.8444,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,2.9471,-1.6272,-32.8444,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,2.9471,-1.6272,-32.8444,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,2.9471,-1.6272,-32.8444,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,2.9471,-1.6272,-32.8444,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,34.6509,-1.2197,-1.5481,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,38.8517,-0.3412,1.7742,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,38.8517,-0.3412,1.7742,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,34.7277,-0.6678,-2.0232,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,48.3930,-0.0783,11.0526,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MOWR,AECI,39.0373,-0.6066,2.2252,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,35.3366,-0.8014,-1.2808,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,39.1642,-0.3300,2.0755,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-1.2372,-2.9178,-35.7381,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-12.1819,-2.2667,-47.3339,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-5.1312,-2.6812,-39.8687,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-1.1113,-2.7920,-35.7381,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,18.9112,-1.9222,-16.5853,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,18.9112,-1.9222,-16.5853,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,18.9154,-1.9181,-16.5853,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,18.9154,-1.9181,-16.5853,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,14.4509,-1.4356,-21.5323,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,14.4509,-1.4356,-21.5323,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,14.4509,-1.4356,-21.5323,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,14.3394,-1.5471,-21.5323,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,14.4509,-1.4356,-21.5323,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,14.4509,-1.4356,-21.5323,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,14.4509,-1.4356,-21.5323,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,35.3484,-0.4589,-1.6114,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,25.6529,-2.0230,-9.7428,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,17.1235,-2.4947,-17.8005,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,17.0222,-2.5961,-17.8005,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,17.1236,-2.4946,-17.8005,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,33.1779,-1.3356,-2.9052,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,33.1779,-1.3356,-2.9052,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MPS_MPS,MPS_LA,39.2619,-1.2241,3.0673,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MSTNG,SPSMSTNGPLT1,131.5729,5.3334,88.8208,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MSTNG4,SPSMSTNGUN4_RA,131.3736,5.1341,88.8208,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MSTNG5,SPSMSTNGUN5_RA,131.3750,5.1355,88.8208,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,131.5729,5.3334,88.8208,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NBSO,PJM,33.2229,-0.6612,-3.5346,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,10.7360,-2.3832,-24.2995,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,10.7322,-2.3870,-24.2995,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,30.3550,0.4582,-7.5220,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NHC1,VACS,44.0196,0.1463,6.4546,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,15.4583,-1.6694,-20.2910,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,15.4583,-1.6694,-20.2910,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,15.4583,-1.6694,-20.2910,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,4.3452,-0.3074,-32.7661,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,11.3111,-1.8817,-24.2259,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,13.4172,-1.7355,-22.2660,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-3.6177,-2.1059,-38.9305,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,11.3111,-1.8817,-24.2259,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.HUB.PY2018,NPPDPY18_H,9.8573,-1.7283,-25.8332,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,9.9940,-1.7651,-25.6597,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,9.9868,-1.7240,-25.7079,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,10.1219,-1.7371,-25.5598,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-7.7868,-1.9941,-43.2114,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,9.1836,-0.8749,-27.3602,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,9.1836,-0.8749,-27.3602,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,4.5551,-1.8493,-31.0143,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-7.7868,-1.9941,-43.2114,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,17.9263,-3.0880,-16.4044,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,9.5861,-2.3043,-25.5283,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,7.0411,-0.3157,-30.0619,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,9.5861,-2.3043,-25.5283,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,10.7546,-2.1406,-24.5235,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,9.3189,-1.7294,-26.3704,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,15.2172,-0.9995,-21.2020,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,11.3111,-1.8817,-24.2259,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,7.3238,-0.4876,-29.6073,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,9.1836,-0.8749,-27.3602,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,9.1836,-0.8749,-27.3602,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,10.1773,-0.7091,-26.5323,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,10.1051,-0.6995,-26.6141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,10.1051,-0.6995,-26.6141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,10.5500,-0.5822,-26.2866,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,0.8960,-1.6718,-34.8509,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,12.0053,-1.4525,-23.9609,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,4.2228,-0.1109,-33.0850,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-2.1236,-1.4348,-38.1076,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-5.0000,-1.3966,-41.0221,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.NELI.DDR,NELI_DDR,-4.8719,-2.1318,-40.1588,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.NPPM.1058,SH1058_DDR,35.2131,-1.0224,-1.1832,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,10.2667,-0.9220,-26.2300,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,11.3111,-1.8817,-24.2259,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,13.4172,-1.7355,-22.2660,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-7.7868,-1.9941,-43.2114,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.TECH.1,KEARNE_DDR,11.4272,-0.4400,-25.5515,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,10.1189,-3.1639,-24.1360,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,10.1189,-3.1639,-24.1360,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-7.3401,-2.0883,-42.6705,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD.VOLT.0236,V236_DDR,14.3699,-1.1608,-21.8880,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD2017HUB,NPPD2017HUB_H,9.9074,-1.7325,-25.7787,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,30.7600,-1.9229,-4.7358,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,4.3452,-0.3074,-32.7661,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,9.1559,-2.9081,-25.3547,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,9.1559,-2.9081,-25.3547,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,14.4726,-1.2309,-21.7152,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,14.3965,-1.1342,-21.8880,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-3.3348,-2.0957,-38.6578,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,10.2123,-0.8143,-26.3921,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,34.4367,-1.7988,-1.1832,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,34.4367,-1.7988,-1.1832,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,34.4367,-1.7988,-1.1832,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,12.4224,-1.4782,-23.5181,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,12.4064,-2.4623,-22.5500,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,12.9341,-0.9577,-23.5269,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,-2.3706,-2.6145,-37.1748,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,-2.3706,-2.6145,-37.1748,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,8.1235,-0.9727,-28.3226,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,7.9023,-1.0068,-28.5096,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,13.9781,-1.3420,-22.0986,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,13.9439,-1.3762,-22.0986,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,13.9439,-1.3762,-22.0986,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,13.8957,-1.3061,-22.2169,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,17.9263,-3.0880,-16.4044,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,13.7671,-1.3086,-22.3430,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,14.8778,-1.6226,-20.9183,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,12.4855,-1.3941,-23.5391,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,12.4611,-1.4140,-23.5436,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,12.4768,-1.3950,-23.5470,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,12.4768,-1.3950,-23.5470,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,12.4224,-1.4782,-23.5181,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,12.3502,-1.5504,-23.5181,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,5.2066,-0.0156,-32.1965,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,13.5722,-1.0629,-22.7836,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,7.8062,-0.8976,-28.7149,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,4.6611,-2.6777,-30.0799,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,6.7777,-0.4825,-30.1585,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,35.7506,-0.4849,-1.1832,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-4.8719,-2.1318,-40.1588,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,8.3952,-0.9084,-28.1151,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,8.3952,-0.9084,-28.1151,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_NPPD,NPPD_LA,15.6248,-1.2196,-20.5743,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,14.8778,-1.6226,-20.9183,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,14.8778,-1.6226,-20.9183,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,12.0556,-1.7913,-23.5719,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,10.9234,-1.8818,-24.6135,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NSB,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NSP,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,NSSO,PJM,33.2229,-0.6612,-3.5346,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,NYIS,PJM,33.2229,-0.6612,-3.5346,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,-1.2413,-1.8014,-36.8587,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-5.1166,-2.8749,-39.6604,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-10.9477,-2.7976,-45.5688,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-10.9477,-2.7976,-45.5688,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-7.3752,-1.2296,-43.5643,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-12.5580,-3.1340,-46.8427,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-50.2400,-2.2897,-85.3690,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-20.3836,-3.1765,-54.6258,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-7.1084,-3.0107,-41.5165,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-5.4145,-2.9099,-39.9233,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,7.7702,-1.8119,-27.8366,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-7.1084,-3.0107,-41.5165,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-5.6396,-1.4141,-41.6442,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-1.1995,-2.0652,-36.5530,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,0.8281,-2.0112,-34.5794,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,46.8833,-0.6242,10.0888,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-5.4145,-2.9099,-39.9233,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,-1.5609,-2.6371,-36.3425,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,-1.1405,-3.0333,-35.5259,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,2.9800,-2.2558,-32.1829,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-16.9949,-0.8544,-53.5593,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-1.1995,-2.0652,-36.5530,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-1.1995,-2.0652,-36.5530,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-5.4145,-2.9099,-39.9233,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.NUEN.ADA1,ADA1_DDR,5.5319,-1.7316,-30.1552,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.NUEN.LAM1,LAM1_DDR,76.8459,1.3551,38.0720,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.NUEN.MDT2,MDT2_DDR,7.7747,-1.8074,-27.8366,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.NUEN.MDT3,MDT3_DDR,7.7747,-1.8074,-27.8366,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.NUEN.WWO1,WWO1_DDR,5.2513,-1.6962,-30.4712,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,7.4617,-1.8955,-28.0615,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,7.4617,-1.8955,-28.0615,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,7.5361,-1.8211,-28.0615,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,7.4217,-1.9576,-28.0394,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,7.4217,-1.9576,-28.0394,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,7.5361,-1.8211,-28.0615,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,7.5361,-1.8211,-28.0615,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-5.4145,-2.9099,-39.9233,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,53.9859,0.5295,16.0377,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-5.6396,-1.4141,-41.6442,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-5.9715,-1.1744,-42.2158,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,-1.5609,-2.6371,-36.3425,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,78.3880,0.7778,40.1915,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,1.9526,-2.5175,-32.9486,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,1.9526,-2.5175,-32.9486,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,1.9625,-2.5076,-32.9486,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,1.9625,-2.5076,-32.9486,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-8.1701,-3.9260,-41.6628,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-6.4701,-2.7975,-41.0913,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-5.1166,-2.8749,-39.6604,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-8.5595,-2.7877,-43.1905,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-8.5595,-2.7877,-43.1905,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,2.5586,-0.6197,-34.2405,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,2.2638,-2.3453,-32.8096,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,2.2638,-2.3453,-32.8096,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,2.2638,-2.3453,-32.8096,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0033,FOSTER_DDR,9.3201,-1.4841,-26.6145,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,22.3942,-0.1602,-14.8643,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0035,TARBY_DDR,77.5827,0.8280,39.3360,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,22.3942,-0.1602,-14.8643,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,20.7024,-0.5698,-16.1466,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,20.7024,-0.5698,-16.1466,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-10.1383,-0.7545,-46.8026,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0040,TROSPER_DDR,9.3918,-1.4613,-26.5656,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,8.9728,-1.4781,-26.9679,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,80.9175,0.9348,42.5639,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0115,V115_DDR,7.9184,-1.7581,-27.7422,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0116,V116_DDR,84.3345,-0.3353,47.2511,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0118,V118_DDR,17.2591,-0.8068,-19.3528,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0125,V125_DDR,77.7611,1.1252,39.2172,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0126,V126_DDR,15.2411,-0.0782,-22.0994,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0129,V129_DDR,22.1887,-1.8978,-13.3322,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,8.2177,-1.6235,-27.5775,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0134,V134_DDR,-14.7393,0.2081,-52.3662,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0138,V138_DDR,22.8081,-0.2316,-14.3790,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,8.4043,-1.4946,-27.5198,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0143,V143_DDR,25.5411,-0.5031,-11.3745,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0149,V149_DDR,6.4153,-2.0426,-28.9609,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0150,V150_DDR,6.9706,-1.9437,-28.5044,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0155,V155_DDR,24.2867,-0.3931,-12.7389,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0156,V156_DDR,8.2177,-1.6235,-27.5775,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0166,V166_DDR,31.0419,0.9054,-7.2822,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,8.4278,-1.5066,-27.4843,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,6.9706,-1.9437,-28.5044,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0170,V170_DDR,5.0676,-1.6923,-30.6589,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,6.3247,-2.1225,-28.9715,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0176,V176_DDR,6.9706,-1.9437,-28.5044,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0177,V177_DDR,-3.1839,-2.4500,-38.1526,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,8.5360,-1.5102,-27.3725,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,2.7193,-2.3264,-32.3730,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0195,V195_DDR,135.9418,1.7550,96.7681,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0197,V197_DDR,31.5316,0.0349,-5.9220,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0198,V198_DDR,31.0419,0.9054,-7.2822,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0208,V208_DDR,136.0000,1.8242,96.7571,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0209,V209_DDR,136.0000,1.8242,96.7571,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,30.6240,-0.2868,-6.5079,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0216,V216_DDR,8.8659,-1.4842,-27.0686,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0219,V219_DDR,24.2867,-0.3931,-12.7389,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0220,V220_DDR,6.9706,-1.9437,-28.5044,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0224,V224_DDR,7.7320,-1.7257,-27.9610,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0225,V225_DDR,7.7339,-1.7238,-27.9610,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0226,V226_DDR,7.7320,-1.7257,-27.9610,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0227,V227_DDR,7.7320,-1.7257,-27.9610,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0229,V229_DDR,-7.1422,-0.5891,-43.9719,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0231,V231_DDR,28.1710,-0.2187,-9.0290,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0238,V238_DDR,-10.4512,-3.1156,-44.7543,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.VOLT.0242,V242_DDR,23.7282,-0.3146,-13.3759,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-1.7444,-3.3523,-35.8108,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-1.1995,-2.0652,-36.5530,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-4.7901,-2.8053,-39.4035,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,0.8281,-2.0112,-34.5794,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-1.7444,-3.3523,-35.8108,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,0.5641,-1.8463,-35.0083,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-25.3180,-4.6640,-58.0727,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEHL7,OKGEHL7_H,11.7792,-1.5693,-24.0702,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEHL8,OKGEHSL1UN8_RA,11.7792,-1.5693,-24.0702,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEHL910,OKGEHSL1PLT2,11.3190,-2.0295,-24.0702,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,0.6598,-2.0149,-34.7441,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEMCC,OKGEMCCLAIPLT1,7.7416,-2.0907,-27.5864,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,29.0140,-0.5559,-7.8488,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,29.0140,-0.5559,-7.8488,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,28.9648,-0.6051,-7.8488,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,9.9278,-2.1727,-25.3182,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,9.9278,-2.1727,-25.3182,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,9.9278,-2.1727,-25.3182,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,10.0544,-2.0461,-25.3182,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGESM1,OKGESEMINOLEUN1_RA,17.9922,-1.3910,-18.0355,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGESM2,OKGESEMINOLEUN2_RA,14.6606,-1.3806,-21.3775,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGESM3,OKGESEMINOLEUN3_RA,14.6606,-1.3806,-21.3775,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGESO1,OKGESONR1UN1_RA,-25.4680,-2.6497,-60.2370,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGESO2,OKGESONR1UN2_RA,-8.5595,-2.7877,-43.1905,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,0.4954,-2.1792,-34.7441,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,0.5333,-2.9953,-33.8901,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGETINK5A,OKGETINK5UN1_RA,10.1260,-1.4551,-25.8376,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGETINK5B,OKGETINK5UN2_RA,10.1260,-1.4551,-25.8376,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,1.2772,-2.3684,-33.7731,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-5.1166,-2.8749,-39.6604,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,83.4051,0.8488,45.1376,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-1.1995,-2.0652,-36.5530,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE_OKGE,OKGE_LA,26.4739,-1.0237,-9.9212,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-5.9715,-1.1744,-42.2158,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,1.1384,-2.5072,-33.7731,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMLP,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,37.3875,-0.7548,0.7236,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,84.9224,0.3638,47.1399,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_GENHUB,OMPA_GENHUB_H,6.7503,-1.8803,-28.7881,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-50.0986,-2.1483,-85.3690,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,1.0194,-2.6433,-33.7560,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-7.1084,-3.0107,-41.5165,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-0.9455,-2.4478,-35.9164,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,16.5894,-2.2290,-18.6003,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,123.0957,-0.9627,86.6397,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-50.2466,-2.2963,-85.3690,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-50.2466,-2.2963,-85.3690,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_SPP,OMPA_SPP_LA,7.2248,-1.7329,-28.4610,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-1.7444,-3.3523,-35.8108,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,33.1206,-0.8058,-3.4923,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,33.1206,-0.8058,-3.4923,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,33.1206,-0.8058,-3.4923,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,33.1206,-0.8058,-3.4923,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,ONT,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,15.3560,-1.6709,-20.3918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,15.3560,-1.6709,-20.3918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,15.3560,-1.6709,-20.3918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,15.3560,-1.6709,-20.3918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,15.3560,-1.6709,-20.3918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,15.3560,-1.6709,-20.3918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,15.3560,-1.6709,-20.3918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,15.3560,-1.6709,-20.3918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,15.3560,-1.6709,-20.3918,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,15.4740,-1.6280,-20.3167,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,15.4583,-1.6694,-20.2910,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,15.7611,-1.2682,-20.3895,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,15.5295,-1.5266,-20.3627,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,15.5295,-1.5266,-20.3627,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD_GLDN,OPPD_GLDN_LA,15.3735,-1.6345,-20.4107,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,15.4846,-1.6469,-20.2872,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,17.9263,-3.0880,-16.4044,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,13.4037,-2.0184,-21.9967,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,15.4590,-1.6676,-20.2922,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD_OPPD,OPPD_LA,15.5722,-1.5446,-20.3019,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,15.5464,-1.4943,-20.3780,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,15.5439,-1.5027,-20.3721,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,OTP,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,OVEC,OVEC,35.3529,-0.5189,-1.5469,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PARAGOULD,PARAGOULD_LA,47.1271,0.2181,9.4903,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,35.3855,-0.8913,-1.1419,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,35.3855,-0.8913,-1.1419,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,35.3855,-0.8913,-1.1419,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,34.6388,-0.7549,-2.0251,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,34.6388,-0.7549,-2.0251,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,34.6388,-0.7549,-2.0251,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,PIGGOTT,PIGGOTT_LA,45.5139,0.1196,7.9755,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,PJM,PJM,33.2229,-0.6612,-3.5346,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PLUM,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,POPLARBLUFF,POPLARBLUFF_LA,42.5934,-0.0551,5.2298,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,45.2979,0.4294,7.4498,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,45.2979,0.4294,7.4498,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,43.7995,0.4683,5.9125,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,43.7995,0.4683,5.9125,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,43.9898,2.0740,4.4971,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,43.9898,2.0740,4.4971,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,44.8500,0.8433,6.5880,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,51.3513,-0.2317,14.1642,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-6.7951,-2.4379,-41.7759,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,66.7191,-0.7890,30.0893,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,17.1608,-1.2531,-19.0048,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,20.9806,-0.8071,-15.6310,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,48.0215,-0.0026,10.6054,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,36.2251,-0.1953,-0.9983,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,12.7920,-1.9494,-22.6773,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,39.3755,0.3007,1.6560,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,9.7888,-2.3797,-25.2502,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,34.0000,2.0469,-5.4656,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,23.3885,-0.2042,-13.8260,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,11.5099,-1.6315,-24.2774,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,PUPP,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,RCEAST,RCEAST,1.7501,-1.2558,-34.4128,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SALINA_1,GRDASALINA1UN1_RA,33.5134,-0.6297,-3.2757,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SALINA_2,GRDASALINA1UN2_RA,33.5134,-0.6297,-3.2757,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SALINA_3,GRDASALINA1UN3_RA,33.5134,-0.6297,-3.2757,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SALINA_4,GRDASALINA1UN4_RA,33.5134,-0.6297,-3.2757,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SALINA_5,GRDASALINA1UN5_RA,33.5134,-0.6297,-3.2757,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SALINA_6,GRDASALINA1UN6_RA,33.5134,-0.6297,-3.2757,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SARPY_1,OPPDSARPYUN1_RA,15.3571,-1.6377,-20.4240,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SARPY_2,OPPDSARPYUN2_RA,15.4150,-1.5685,-20.4353,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SARPY_3,OPPDSARPYUN3_RA,15.2910,-1.7112,-20.4165,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SARPY_4,OPPDSARPYUN4_RA,15.2910,-1.7112,-20.4165,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SARPY_5,OPPDSARPYUN5_RA,15.2910,-1.7112,-20.4165,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SC,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SCEG,VACS,44.0196,0.1463,6.4546,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SCSE,SCSE,8.0601,-0.3020,-29.0566,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SEC,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-1.6207,-2.1003,-36.9391,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-1.6207,-2.1003,-36.9391,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-1.6207,-2.1003,-36.9391,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,-0.1892,0.8453,-38.4533,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-1.6207,-2.1003,-36.9391,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,-1.0022,-1.3080,-37.1129,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,1.8271,-1.8126,-33.7790,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,1.8271,-1.8126,-33.7790,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,2.9423,-1.6320,-32.8444,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-2.7053,-2.3364,-37.7877,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,8.3600,-0.2017,-28.8570,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-1.0069,0.4441,-38.8698,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,2.1435,-0.5429,-34.7323,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-1.2655,-2.0000,-36.6842,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,2.4219,-0.6002,-34.3967,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-1.2699,-1.9022,-36.7864,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,1.1322,-0.5201,-35.7664,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-0.7435,-0.4161,-37.7461,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-0.7435,-0.4161,-37.7461,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-0.7435,-0.4161,-37.7461,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-0.7435,-0.4161,-37.7461,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-1.1507,-0.6163,-37.9532,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,-1.0022,-1.3080,-37.1129,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI_SECI,SECI_LA,0.1867,-0.3166,-36.9155,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-9.0066,-2.7673,-43.6580,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-9.0066,-2.7673,-43.6580,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,2.9423,-1.6320,-32.8444,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SEHA,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,1.1384,-2.5072,-33.7731,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SERU,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SETH,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SGE,SGE,7.3042,-0.2465,-29.8680,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SMEP,MISO,32.7232,-0.5073,-4.1881,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,SOCO,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPA,SPA,48.6690,0.0921,11.1582,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPC,SPC,37.5630,0.5575,-0.4133,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPPNORTH_HUB,SPPNORTH_H,15.3734,-1.3516,-20.6936,37.4186\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPPSOUTH_HUB,SPPSOUTH_H,14.1142,-1.6586,-21.6459,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,38.0118,-0.2481,0.8411,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,38.0207,-0.2391,0.8411,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,38.1526,-0.1706,0.9045,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,38.1526,-0.1706,0.9045,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_NIXA,SPRM_NIXA_LA,38.2418,-0.0463,0.8694,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_SPRM,SPRM_LA,38.2848,0.0249,0.8411,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,37.9642,-0.2328,0.7783,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,37.9642,-0.2328,0.7783,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,37.8741,-0.3229,0.7783,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,37.9642,-0.2328,0.7783,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,132.4943,4.6024,90.4731,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,136.8161,3.9709,95.4265,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,30.0278,0.9369,-8.3278,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,30.0278,0.9369,-8.3278,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,127.1007,2.5786,87.1033,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,131.0569,4.7061,88.9321,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,131.8660,3.6172,90.8301,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,133.6191,6.6599,89.5405,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,125.4180,3.0033,84.9959,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,131.6195,5.3019,88.8989,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,132.0413,5.7826,88.8400,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,132.0413,5.7826,88.8400,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,131.6195,5.3019,88.8989,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,30.2314,1.0405,-8.2278,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,136.8161,3.9709,95.4265,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,30.0854,1.0862,-8.4195,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,15.8652,-0.6538,-20.8997,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,25.5313,1.2878,-13.1753,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,29.9085,2.0821,-9.5924,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,28.3497,1.1250,-10.1940,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,5.5799,-0.9932,-30.8456,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,5.5799,-0.9932,-30.8456,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,5.5799,-0.9932,-30.8456,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,5.5799,-0.9932,-30.8456,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GRID.WRAB,WRAB_DDR,34.8122,2.8615,-5.4680,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,5.5799,-0.9932,-30.8456,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,124.4885,3.0849,83.9848,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,124.4885,3.0849,83.9848,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,121.4684,3.1274,80.9223,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,121.4684,3.1274,80.9223,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,121.4684,3.1274,80.9223,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,124.4885,3.0849,83.9848,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,34.5410,0.8080,-3.6857,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,34.5371,0.8080,-3.6896,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,34.5506,0.8080,-3.6761,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,30.3550,0.4582,-7.5220,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,131.6491,5.3675,88.8629,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,125.3699,2.9648,84.9864,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,125.3699,2.9648,84.9864,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,125.3699,2.9648,84.9864,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,125.3699,2.9648,84.9864,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,131.8870,5.4921,88.9762,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,131.5394,5.2159,88.9047,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,131.5394,5.2159,88.9047,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,1.3175,-2.3281,-33.7731,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,33.4173,0.6779,-4.6793,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,33.4173,0.6779,-4.6793,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,34.3696,0.8101,-3.8592,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,34.8122,2.8615,-5.4680,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,17.7154,-0.0180,-19.6853,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,27.7892,0.7672,-10.3967,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-7.3752,-1.2296,-43.5643,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,33.9391,1.1997,-4.6793,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.PLANTX1,SPS.PLANTX1_H,133.6763,4.2557,92.0019,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.PLANTX2,SPS.PLANTX2_H,133.6763,4.2557,92.0019,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,133.3719,4.2055,91.7477,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,126.9292,2.9063,86.6042,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,11.4852,-0.5143,-25.4193,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,132.6057,4.3569,90.8301,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,127.0212,2.9983,86.6042,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,30.3058,1.1149,-8.2278,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,132.6179,5.0429,90.1563,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,133.6191,6.6599,89.5405,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,132.6179,5.0429,90.1563,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,133.4495,5.9066,90.1242,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,-36.0000,0.6223,-74.0410,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,134.6210,8.2877,88.9146,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,134.8135,8.4802,88.9146,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,134.2564,7.9237,88.9140,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,132.0817,5.7551,88.9079,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,134.4886,8.0475,89.0224,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-1.3920,-0.7978,-38.0129,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,34.7101,2.7005,-5.4091,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,132.6686,4.4489,90.8010,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,132.6686,4.4489,90.8010,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,132.6179,5.0429,90.1563,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,125.6479,3.2047,85.0244,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,133.8700,6.6543,89.7970,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,135.1104,6.8237,90.8680,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,133.6044,5.3032,90.8825,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,133.1056,3.1679,92.5189,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,134.6210,8.2877,88.9146,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,135.5298,9.1532,88.9578,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,134.9086,8.5321,88.9578,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,127.4057,3.3828,86.6042,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,134.1127,5.8607,90.8333,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,12.9416,-0.2625,-24.2146,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,12.8980,-0.3340,-24.1867,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0163,V163_DDR,35.6474,1.5142,-3.2856,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0168,V168_DDR,20.4378,-0.2673,-16.7137,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0180,V180_DDR,135.5298,9.1532,88.9578,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0181,V181_DDR,12.5401,0.0264,-24.9050,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0182,V182_DDR,134.4685,8.0606,88.9891,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0199,V199_DDR,132.9841,6.2923,89.2731,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0200,V200_DDR,132.8694,6.5288,88.9219,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.VOLT.0235,V235_DDR,17.7154,-0.0180,-19.6853,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,131.8660,3.6172,90.8301,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,133.6191,6.6599,89.5405,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,34.5301,1.1701,-4.0587,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,33.5842,1.1947,-5.0292,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS_SPS,SPS_LA,107.1746,5.5078,64.2480,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,133.4768,4.8488,91.2093,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SSCN_NPPD,SSCN_NPPD_LA,-0.9925,-2.0867,-36.3245,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,42.5914,-0.0706,5.2433,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,42.5914,-0.0706,5.2433,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,TAL,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,TEC,SOUC,44.4571,0.2243,6.8141,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,4.6611,-2.6777,-30.0799,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,TVA,TVA,43.5538,0.0643,6.0708,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,UCUHUB,UCUHUB_H,10.4851,-1.8401,-25.0935,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,UCUHUB17,UCUHUB17_H,1.5613,-1.8622,-33.9953,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,UCUHUB18,UCUHUB18_H,3.3128,-2.0678,-32.0381,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,UCUHUB19,UCUHUB19_H,0.9075,-2.1312,-34.3800,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,UCUHUB20,UCUHUB20_H,1.7312,-2.0613,-33.6262,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,UCUHUB21,UCUHUB21_H,1.2640,-2.0083,-34.1465,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,UCUHUB22,UCUHUB22_H,0.6984,-2.1280,-34.5923,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,UCUHUB23,UCUHUB23_H,0.2158,-2.1425,-35.0605,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,UCUHUB24,UCUHUB24_H,3.9777,-1.9818,-31.4592,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,39.0099,1.0122,0.5789,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,39.0099,1.0122,0.5789,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,11.1268,-1.4675,-24.8244,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,11.1268,-1.4675,-24.8244,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,20.9914,-1.3575,-15.0698,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,42.3953,-0.3452,5.3218,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,42.3953,-0.3452,5.3218,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,39.0099,1.0122,0.5789,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,21.6354,-0.9725,-14.8108,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,26.7141,-0.1868,-10.5178,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,10.2987,-1.9032,-25.2169,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,5.9353,-4.1671,-27.3163,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,42.0025,1.0379,3.5459,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,42.0025,1.0379,3.5459,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,18.8049,-4.2327,-14.3811,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,10.4674,-2.5535,-24.3978,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,21.7267,-1.3333,-14.3588,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,8.5826,-2.4818,-26.3544,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,10.1858,-1.8813,-25.3516,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,8.9211,-2.8197,-25.6779,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,20.1568,-2.8808,-14.3811,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,20.1568,-2.8808,-14.3811,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,10.2126,-2.3399,-24.8662,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,6.2616,-4.0796,-27.0775,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,11.9183,-0.2586,-25.2418,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,41.6500,-0.5751,4.8064,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,41.6500,-0.5751,4.8064,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,41.6500,-0.5751,4.8064,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,41.6796,-0.3465,4.6074,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,41.6796,-0.3465,4.6074,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,41.6796,-0.3465,4.6074,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,38.1758,1.4905,-0.7334,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,17.6482,-1.5697,-18.2008,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,17.6482,-1.5697,-18.2008,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,7.6421,-0.3059,-29.4707,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,7.2567,-2.2987,-27.8634,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,37.7775,-0.3135,0.6723,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,1.4907,-2.4934,-33.4347,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,4.4578,-4.8071,-28.1538,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,20.5562,-2.4841,-14.3784,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,40.8100,0.5678,2.8234,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,40.8100,0.5678,2.8234,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,40.8038,0.5617,2.8233,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,40.8100,0.5678,2.8234,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,41.4139,0.6269,3.3683,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,41.4139,0.6269,3.3683,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,41.4139,0.6269,3.3683,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,41.4139,0.6269,3.3683,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,41.4139,0.6269,3.3683,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,41.4139,0.6269,3.3683,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,41.4139,0.6269,3.3683,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,4.1362,-3.8264,-29.4561,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,23.9555,-0.8358,-12.6275,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,5.7344,-1.9739,-29.7104,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,5.7344,-1.9739,-29.7104,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,2.1727,-2.1555,-33.0905,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,2.1727,-2.1555,-33.0905,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,18.0923,-1.1256,-18.2008,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,32.3732,-0.8808,-4.1647,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,8.8688,-3.0095,-25.5404,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,7.6725,-3.6936,-26.0526,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,14.0420,-1.6766,-21.7001,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,20.9914,-1.3575,-15.0698,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,20.9914,-1.3575,-15.0698,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,8.5826,-2.4818,-26.3544,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,1.8571,-1.3081,-34.2535,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,13.8295,-2.7665,-20.8227,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,6.2952,-4.0460,-27.0775,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,9.3424,-2.6306,-25.4458,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.FSE,WAUE.FSE_H,5.3538,-2.2341,-29.8309,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,42.6649,0.1847,5.0615,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,42.8576,0.1037,5.3351,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,5.1345,-4.2517,-28.0325,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,6.5715,-4.0504,-26.7969,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,20.3780,-1.5338,-15.5069,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,21.9812,-1.6982,-13.7393,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-10.0700,-3.3128,-44.1760,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,5.9353,-4.1671,-27.3163,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-23.9700,-0.8461,-60.5426,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,11.9731,-2.6183,-22.8273,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,12.1599,-2.4315,-22.8273,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,11.9754,-2.6161,-22.8273,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,5.5959,-2.4559,-29.3669,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,1.8571,-1.3081,-34.2535,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,12.5326,-1.5277,-23.3585,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,8.5117,-2.4805,-26.4265,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,11.7710,-0.4059,-25.2418,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,13.5529,-0.7426,-23.1232,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,10.5954,-1.7469,-25.0764,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,17.4036,-1.7436,-18.2715,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,9.8897,-1.8177,-25.7113,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,8.7372,-2.9445,-25.7370,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,1.4907,-2.4934,-33.4347,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,19.1686,-0.4209,-17.8293,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,8.5262,-2.5302,-26.3623,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,18.9196,-0.5396,-17.9596,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,11.8987,-1.4723,-24.0477,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,15.2722,-1.8877,-20.2588,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NTWK,WAUE.NTWK_H,14.1651,-1.6274,-21.6262,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,13.1771,-2.0452,-22.1964,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,13.1771,-2.0452,-22.1964,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,5.7594,-4.4082,-27.2511,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,2.6032,-4.9292,-29.8863,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,13.2046,-2.1497,-22.0645,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,5.7594,-4.4082,-27.2511,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,22.3201,-1.0399,-14.0587,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,8.6160,-3.1226,-25.6801,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,1.4907,-2.4934,-33.4347,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,10.9815,-2.3037,-24.1335,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,8.6120,-3.1266,-25.6801,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,0.5310,-4.7774,-32.1103,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,2.5008,-4.7176,-30.2003,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,13.1913,-1.5886,-22.6388,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,9.1397,-3.6242,-24.6548,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,12.6489,-1.7978,-22.9720,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,7.4442,-3.4662,-26.5083,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,7.6725,-3.6936,-26.0526,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.VOLT.0152,V152_DDR,36.5680,1.9115,-2.7622,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE.VOLT.0172,V172_DDR,41.3393,0.7642,3.1564,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_BEPM,WAUE_BEPM_LA,27.0206,-0.2409,-10.1573,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,12.2294,-1.5749,-23.6145,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,13.5582,-0.7188,-23.1417,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_EWA,WAUE_EWA_LA,0.4311,-1.1315,-35.8561,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,8.6561,-2.8689,-25.8937,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_HMMU,WAUE_HMMU_LA,14.9352,-1.0206,-21.4629,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,17.2280,-1.6100,-18.5807,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_MECB,WAUE_MECB_LA,11.9285,-0.8361,-24.6541,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_MMPA,WAUE_MMPA_LA,20.9953,-0.2526,-16.1709,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_MRES,WAUE_MRES_LA,9.4708,-1.8370,-26.1109,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,32.0310,1.1466,-6.5344,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,42.6649,0.1847,5.0615,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,7.6187,-2.8818,-26.9182,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_OTP,WAUE_OTP_LA,25.4639,0.7024,-12.6572,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_OTPW,WAUE_OTPW_LA,31.6491,1.3237,-7.0933,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM,WAUE_UGPM_LA,15.1660,-1.8986,-20.3542,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,23.8151,-0.6085,-12.9951,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,10.6194,-1.8282,-24.9711,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,23.9839,-1.6496,-11.7853,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,0.4311,-1.1315,-35.8561,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,14.9352,-1.0206,-21.4629,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,9.1614,-2.7987,-25.4587,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,42.6649,0.1847,5.0615,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,20.9953,-0.2526,-16.1709,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,11.1985,-1.4582,-24.7621,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,8.1042,-3.3167,-25.9978,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,25.1777,1.0121,-13.2531,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-1.4203,-3.0165,-35.8225,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,-4.2799,-3.6532,-38.0454,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,35.1437,-1.4398,-0.8352,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,97.9901,0.0052,60.5662,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,97.9901,0.0052,60.5662,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,10.7573,-2.1671,-24.4943,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,90.1772,0.1879,52.5706,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,80.8443,0.1042,43.3214,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,68.1091,-1.6627,32.3531,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,68.1091,-1.6627,32.3531,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,68.1091,-1.6627,32.3531,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,68.1091,-1.6627,32.3531,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,68.1091,-1.6627,32.3531,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,68.1091,-1.6627,32.3531,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,68.1091,-1.6627,32.3531,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,68.1091,-1.6627,32.3531,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,49.2908,-1.5478,13.4199,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-7.3752,-1.2296,-43.5643,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-29.5965,-3.1077,-63.9075,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-2.4367,-3.3359,-36.5195,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,132.2507,4.0019,90.8301,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_ENMC,WFEC_ENMC_LA,133.2151,6.3029,89.4934,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-5.4145,-2.9099,-39.9233,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,44.0288,-0.6502,7.2603,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,131.5741,5.2018,88.9536,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-1.4594,-3.0556,-35.8225,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-1.4203,-3.0165,-35.8225,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-1.4203,-3.0165,-35.8225,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_OKGE,WFEC_OKGE_LA,29.9625,-0.7824,-6.6738,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,63.3986,0.5068,25.4731,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,1.6745,-4.3851,-31.3592,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,11.1789,-4.6176,-21.6223,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_WFEC,WFEC_LA,35.9580,-0.8023,-0.6584,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,131.5741,5.2018,88.9536,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-10.5612,-2.5631,-45.4169,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,0.5027,-0.6429,-36.2731,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,6.4467,-2.2573,-28.7147,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,6.4467,-2.2573,-28.7147,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,6.4514,-2.2526,-28.7147,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,6.4514,-2.2526,-28.7147,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,6.4561,-2.2480,-28.7147,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,6.4561,-2.2480,-28.7147,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,6.4561,-2.2480,-28.7147,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,15.8771,-1.0438,-20.4979,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,5.7530,-2.5805,-29.0852,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,-3.2814,-2.7842,-37.9159,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,-3.2814,-2.7842,-37.9159,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,-3.2814,-2.7842,-37.9159,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-2.3010,-2.3891,-37.3306,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-2.3010,-2.3891,-37.3306,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,0.2006,-2.4996,-34.7185,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,0.2006,-2.4996,-34.7185,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,0.2006,-2.4996,-34.7185,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,5.7530,-2.5805,-29.0852,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,9.7051,-1.7209,-25.9927,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.HEC.GT1,WRHECGTUN32_RA,4.5920,-2.0486,-30.7781,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.HEC.GT2,WRHECGTUN33_RA,4.5920,-2.0486,-30.7781,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.HEC.GT3,WRHECGTUN34_RA,4.5920,-2.0486,-30.7781,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.HEC.GT4,WRHECGTUN35_RA,4.5920,-2.0486,-30.7781,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,9.7051,-1.7209,-25.9927,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-0.7137,-1.8438,-36.2886,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-29.3900,-2.4561,-64.3526,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.JEC.1,WRJEFFUN10_RA,7.1499,-2.2075,-28.0614,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.JEC.2,WRJEFFUN11_RA,7.1972,-2.2170,-28.0046,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.JEC.3,WRJEFFUN12_RA,7.0628,-2.3513,-28.0046,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-6.4550,-3.0082,-40.8655,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-5.1022,-2.6523,-39.8687,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-5.1022,-2.6523,-39.8687,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.LEC.4,WRLECUN26_RA,5.0019,-1.7139,-30.7029,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.LEC.5,WRLECUN27_RA,6.0735,-1.6288,-29.7164,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,5.8878,-1.5720,-29.9589,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,5.8878,-1.5720,-29.9589,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,5.8878,-1.5720,-29.9589,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,5.9741,-1.5132,-29.9314,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-9.0066,-2.7673,-43.6580,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-9.0066,-2.7673,-43.6580,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,1.9017,-0.2135,-35.3035,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-7.2700,-2.4974,-42.1913,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-7.2700,-2.4974,-42.1913,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-0.5637,-0.5801,-37.4023,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-9.0066,-2.7673,-43.6580,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,10.0070,-1.6471,-25.7646,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,5.2847,-2.5017,-29.6323,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-5.1181,-2.6681,-39.8687,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,81.0313,0.1511,43.4615,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,0.0000,-0.2058,-37.2129,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,6.4561,-2.2480,-28.7147,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,1.5743,-3.5258,-32.3186,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,9.7051,-1.7209,-25.9927,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,5.7530,-2.5805,-29.0852,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,-1.8739,-2.2848,-37.0078,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.THAYERLD,WR.THAYERLD_LA,43.1686,0.0248,5.7251,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0102,WR.VOLT.0102_H,-2.2760,-2.2585,-37.4363,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0106,V106_DDR,-2.0815,-2.2702,-37.2301,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0139,WR.VOLT.0139_H,4.1126,-1.5007,-31.8054,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0141,WR.VOLT.0141_H,5.9696,-1.9324,-29.5167,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0146,WR.VOLT.0146_H,5.0498,-1.4350,-30.9339,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0147,WR.VOLT.0147_H,5.0498,-1.4350,-30.9339,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0148,WR.VOLT.0148_H,6.4098,-1.6002,-29.4087,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0153,WR.VOLT.0153_H,-1.7652,-2.0248,-37.1591,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0157,V157_DDR,5.0968,-1.4635,-30.8585,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0158,V158_DDR,5.0498,-1.4350,-30.9339,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0159,WR.VOLT.0159_H,5.0498,-1.4350,-30.9339,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-2.7971,-2.5221,-37.6937,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0173,V173_DDR,6.3133,-1.2551,-29.8503,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0174,V174_DDR,-2.4285,-2.3372,-37.5101,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0184,V184_DDR,-2.2972,-2.5335,-37.1824,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0185,WR.VOLT.0185_H,-1.9607,-2.2786,-37.1009,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0186,V186_DDR,-1.7364,-2.3343,-36.8209,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0187,WR.VOLT.0187_H,-2.2460,-2.4445,-37.2202,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0188,WR.VOLT.0188_H,-2.3387,-2.2627,-37.4947,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0189,WR.VOLT.0189_H,4.1848,-1.8179,-31.4160,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0190,WR.VOLT.0190_H,5.6614,-2.0715,-29.6858,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0191,WR.VOLT.0191_H,6.1641,-2.1485,-29.1062,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0192,WR.VOLT.0192_H,6.1641,-2.1485,-29.1062,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0196,WR.VOLT.0196_H,5.6614,-2.0715,-29.6858,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0245,V245_DDR,-1.9428,-2.2719,-37.0896,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.VOLT.0248,V248_DDR,-2.0815,-2.2702,-37.2301,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-5.0155,-2.8579,-39.5763,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,8.1015,-1.7214,-27.5958,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.WOLF,WRWOLFUN15_RA,0.7757,-3.6961,-32.9469,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-0.7137,-1.8438,-36.2886,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,15.6386,-1.2822,-20.4979,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,-3.2814,-2.7842,-37.9159,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,-3.2814,-2.7842,-37.9159,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,-3.2814,-2.7842,-37.9159,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,-3.2814,-2.7842,-37.9159,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,0.6903,-2.2222,-34.5062,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,5.9830,-1.9432,-29.4925,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-3.2046,-2.3855,-38.2378,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-3.2046,-2.3855,-38.2378,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-3.2046,-2.3855,-38.2378,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-3.2046,-2.3855,-38.2378,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,6.6381,-1.8248,-28.9558,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,6.6381,-1.8248,-28.9558,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,6.6381,-1.8248,-28.9558,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,6.6381,-1.8248,-28.9558,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,6.6381,-1.8248,-28.9558,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,6.6381,-1.8248,-28.9558,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-11.3540,-2.2231,-46.5496,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-11.3540,-2.2231,-46.5496,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-13.3955,-2.4417,-48.3725,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-13.3955,-2.4417,-48.3725,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_MIDW,WR_MIDW_LA,-0.0806,-1.1875,-36.3118,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,52.2073,-0.7240,15.5125,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,30.5927,-1.4677,-5.3584,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,9.0332,-1.6390,-26.7465,37.4187\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_SEG,WR_SEG_LA,13.5837,-1.2527,-22.5824,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,WR_WR,WR_LA,4.4125,-1.9374,-31.0689,37.4188\n03/19/2025 22:00:00,03/20/2025 03:00:00,YAD,VACS,44.0196,0.1463,6.4546,37.4187\n03/19/2025 23:00:00,03/20/2025 04:00:00,AEC,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,AECC_CSWS,CSWS_AECC_LA,33.9552,-0.1977,-3.0531,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,37.0828,-0.5022,0.3791,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,32.4971,-0.1658,-4.5430,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,37.4685,-0.7219,0.9844,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,27.9366,-1.0729,-8.1964,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,32.8103,-0.6599,-3.7357,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,27.6600,-1.2065,-8.3394,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,AECI,AECI,33.7335,-0.8289,-2.6435,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,AEPM_CSWS,CSWS_LA,33.4449,-0.1453,-3.6158,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,ALTW,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,AMRN,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,137.5717,3.2888,97.0769,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,BBA,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,BCA,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,BEPM.ER01.DDR,ER01_DDR,7.4471,-1.4023,-28.3565,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,BEPM_ER01,BEPM_ER01_LA,7.4471,-1.4023,-28.3565,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,8.8578,1.4859,-29.8340,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,11.0499,1.3244,-27.4804,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,BEPM_UM01,BEPM_UM01_LA,44.7587,1.7815,5.7713,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,BLKW,BLKW,145.2008,5.3396,102.6553,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-29.6140,-3.3631,-63.4568,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-29.6140,-3.3631,-63.4568,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,57.4124,-1.6891,21.8955,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-29.5617,-3.3108,-63.4568,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,BRAZ,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,BUBA,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,0.7774,-0.9053,-35.5232,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,4.8942,-2.4664,-29.8454,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,4.8942,-2.4664,-29.8454,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,4.8942,-2.4664,-29.8454,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,4.8942,-2.4664,-29.8454,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,4.8942,-2.4664,-29.8454,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-5.5967,-2.6449,-40.1578,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,10.4798,-1.6069,-25.1192,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,10.4798,-1.6069,-25.1192,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CLEC,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,37.2183,-0.7142,0.7266,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,COWP,COWP_LA,32.3301,-0.3777,-4.4981,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,32.3301,-0.3777,-4.4981,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,32.3301,-0.3777,-4.4981,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CPLE,VACS,27.8077,-0.0724,-9.3258,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CPLW,VACS,27.8077,-0.0724,-9.3258,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,28.9828,0.1409,-8.3640,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,28.9828,0.1409,-8.3640,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,28.9828,0.1409,-8.3640,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,28.9828,0.1409,-8.3640,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CRTH_SPA,WRCRTH_SPA_LA,39.9148,-1.4535,4.1624,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,30.1204,1.3568,-8.4423,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,30.3888,-1.6089,-5.2082,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,27.6600,-1.2065,-8.3394,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,37.4685,-0.7219,0.9844,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,30.1162,1.3530,-8.4428,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,28.7287,-0.0075,-8.4698,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,29.8338,1.0752,-8.4474,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,29.8338,1.0752,-8.4474,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,36.2579,-1.0556,0.1076,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,36.2579,-1.0556,0.1076,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,36.2551,-1.0584,0.1076,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,36.2551,-1.0584,0.1076,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,27.6600,-1.2065,-8.3394,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,30.6387,0.3692,-6.9365,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,46.7020,-1.4753,10.9714,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,46.4368,-1.7405,10.9714,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,38.0264,-1.1311,1.9516,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,34.2224,-1.0359,-1.9476,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,34.2224,-1.0359,-1.9476,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,34.0625,-1.1974,-1.9460,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,34.0625,-1.1974,-1.9460,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-11.7479,-1.9508,-47.0031,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,37.6586,-1.3934,1.8461,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,35.5532,-1.1569,-0.4959,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-13.3290,-1.4374,-49.0975,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-13.3546,-1.4630,-49.0975,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,15.2802,-1.6063,-20.3194,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.GRID.CDL1,CDL1_DDR,34.4520,-0.6611,-2.0929,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,23.8100,-2.0697,-11.3262,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,31.4127,-1.6224,-4.1708,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,34.4520,-0.6611,-2.0929,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.NUEN.CSI1,CSI1_DDR,39.3110,-0.5458,2.6508,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.NUEN.CSI2,CSI2_DDR,39.3235,-0.5332,2.6508,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,37.2256,-0.7069,0.7266,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.NUEN.GAZA,GAZA_DDR,34.4520,-0.6611,-2.0929,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,68.6370,0.2034,31.2277,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.NUEN.T201,NT201_DDR,35.3482,-0.8684,-0.9893,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,23.5146,-1.8362,-11.8551,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,23.5146,-1.8362,-11.8551,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,27.6600,-1.2065,-8.3394,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,30.3964,1.6180,-8.4275,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,15.2802,-1.6063,-20.3194,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,15.2802,-1.6063,-20.3194,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,3.7504,-2.0126,-31.4429,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-13.3546,-1.4630,-49.0975,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,28.9224,0.1808,-8.4643,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,32.4514,-1.1899,-3.5647,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,32.0115,-1.6297,-3.5647,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,32.0248,-1.6164,-3.5647,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,21.5619,-1.2111,-14.4329,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,21.5619,-1.2111,-14.4329,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,28.7683,0.0380,-8.4757,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,34.8761,-0.8437,-1.4861,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,28.6556,-0.0781,-8.4723,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,30.9449,2.1962,-8.4572,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,30.3615,-0.7154,-6.1290,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,39.3235,-0.5332,2.6508,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0057,OKMU_DDR,36.0234,-0.5851,-0.5975,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0060,LEHIGH_DDR,68.6370,0.2034,31.2277,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0086,WARRENM_DDR,34.6718,-0.8816,-1.6526,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,29.9924,1.2110,-8.4246,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,42.3807,-0.8503,6.0250,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0121,V121_DDR,28.7683,0.0380,-8.4757,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0122,V122_DDR,41.4304,-0.8804,5.1049,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0124,V124_DDR,52.3817,-1.0751,16.2509,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0135,V135_DDR,35.4376,-0.8191,-0.9492,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0144,V144_DDR,38.2867,-1.3177,2.3984,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0145,V145_DDR,38.4019,-1.5346,2.7306,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,28.8751,0.1457,-8.4765,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,28.2903,-0.5886,-8.3271,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0175,V175_DDR,37.2256,-0.7069,0.7266,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,28.2903,-0.5886,-8.3271,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,28.5671,-0.3388,-8.3000,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,35.4376,-0.8191,-0.9492,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,35.6963,-0.8624,-0.6473,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,35.4706,-0.9250,-0.8104,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,44.7336,-1.2134,8.7410,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,34.2949,-1.0269,-1.8841,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,35.6963,-0.8624,-0.6473,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0211,V211_DDR,29.0956,0.3600,-8.4703,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,42.9183,-0.8384,6.5508,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0213,V213_DDR,35.2423,-0.8851,-1.0786,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0215,V215_DDR,42.0999,-0.8619,5.7558,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0217,V217_DDR,42.9323,-0.8680,6.5944,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0218,V218_DDR,44.5071,-1.1920,8.4931,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0228,V228_DDR,35.5644,-0.9241,-0.7175,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0232,V232_DDR,34.9480,-0.8307,-1.4272,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0233,V233_DDR,35.7773,-0.8333,-0.5953,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0240,V240_DDR,40.0375,-0.9908,3.8224,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0244,V244_DDR,35.6963,-0.8624,-0.6473,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0246,MDT1_DDR,68.6370,0.2034,31.2277,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0249,V249_DDR,35.2396,-0.8412,-1.1251,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0250,V250_DDR,29.3198,-1.5118,-6.3743,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0251,V251_DDR,34.6587,-0.9638,-1.5834,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.VOLT.0252,V252_DDR,44.7336,-1.2134,8.7410,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-12.5514,-2.0621,-47.6953,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,51.2437,-2.3247,16.3625,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,0.1880,-3.5431,-33.4748,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,27.9688,-0.7647,-8.4725,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,1.1682,-3.1749,-32.8628,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,34.0123,-1.5309,-1.6627,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,34.0123,-1.5309,-1.6627,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,34.0123,-1.5309,-1.6627,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,34.0123,-1.5309,-1.6627,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,34.0123,-1.5309,-1.6627,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,27.6600,-1.2065,-8.3394,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,30.2594,1.4541,-8.4006,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,34.9070,-0.8717,-1.4272,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,34.8532,-0.9255,-1.4272,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,37.3120,-0.4397,0.5458,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,37.3120,-0.4397,0.5458,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWWELSH1,CSWSWELSHUN1_RA,28.4297,-0.2482,-8.5281,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWWELSH3,CSWSWELSHUN3_RA,28.4297,-0.2482,-8.5281,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWWILKES1,CSWSWILKESUN1_RA,29.0528,0.2819,-8.4350,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWWILKES2,CSWSWILKESUN2_RA,29.0528,0.2819,-8.4350,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,CSWWILKES3,CSWSWILKESUN3_RA,28.9179,0.1875,-8.4755,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-13.3290,-1.4374,-49.0975,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,DENL,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,DERS,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,DOE,DOE,27.3367,-0.3572,-9.5120,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,16.0275,-2.1356,-19.0428,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,DPC,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,DUK,VACS,27.8077,-0.0724,-9.3258,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDDY,EDDY,144.2178,6.8968,100.1150,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,38.1850,-1.6870,2.6661,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-11.9222,-1.9030,-47.2252,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,43.8918,-2.0587,8.7445,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE.SLCC,EDESTL4391_PLT,38.9505,-1.6864,3.4309,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,38.9311,-1.5693,3.2945,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,28.3868,-2.0754,-6.7437,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_EC_01,EDELAR3821UN1_RA,38.1850,-1.6870,2.6661,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_EC_02,EDELAR3821UN2_RA,38.1478,-1.7242,2.6661,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_EC_03,EDELAR3821UN3_RA,38.1850,-1.6870,2.6661,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_EC_04,EDELAR3821UN4_RA,38.1850,-1.6870,2.6661,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_EDE,EDE_LA,38.3310,-0.7842,1.9092,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_ERW,EDEERWFUNG1_RA,-4.6995,-2.7207,-39.1847,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,7.1223,-2.6475,-27.4361,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,86.0000,0.0459,48.7482,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,86.0000,0.0459,48.7482,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,86.0000,0.0459,48.7482,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,86.0000,0.0459,48.7482,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,28.6231,-0.0349,-8.5479,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_RIV_10,EDERIV1671UN10_RA,38.7394,-1.8050,3.3385,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_RIV_11,EDERIV1671UN11_RA,38.7394,-1.8050,3.3385,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_RIV_12,EDERIV453UN12_PLT,37.8603,-2.6842,3.3385,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_SL_01,EDESTL4391UN1_RA,38.4627,-2.1741,3.4309,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EDE_SWMP,EDE_SWMP_LA,38.0068,-0.5006,1.3015,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,EEI,EEI,27.3228,-0.3612,-9.5220,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,EES,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,5.4386,-2.5711,-29.1962,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,ERCOTE,ERCOTE,28.4297,-0.2482,-8.5281,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,ERCOTN,ERCOTN,23.5711,-1.7797,-11.8551,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,10.5459,-2.0191,-24.6410,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,FMPP,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,FPC,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,FPL,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,FREM_50T,OPPDFREM_GUN1_RA,10.1329,-1.3980,-25.6750,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,FREM_6,OPPDFREM_AUN6_RA,10.1110,-1.4084,-25.6865,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,FREM_7,OPPDFREM_AUN7_RA,10.1110,-1.4084,-25.6865,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,FREM_8,OPPDFREM_AUN8_RA,9.9554,-1.5640,-25.6865,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,FREM_LOAD,FREM_LOAD_LA,10.0859,-1.4335,-25.6865,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,FRONTIER,WRGETTUNFRONTIER_RA,0.9504,-2.1842,-34.0713,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,28.9192,0.1775,-8.4643,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,57.1136,-1.2135,21.1212,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-7.3030,-3.2472,-41.2617,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,37.2183,-0.7142,0.7266,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,37.2183,-0.7142,0.7266,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,37.2183,-0.7142,0.7266,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,38.7684,-0.9829,2.5454,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,38.7684,-0.9829,2.5454,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,38.8231,-0.9936,2.6108,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,38.8231,-0.9936,2.6108,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,-3.5754,-3.1851,-37.5962,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,54.6049,-1.4336,18.8326,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,54.6049,-1.4336,18.8326,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,54.6049,-1.4336,18.8326,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.VOLT.0130,V130_DDR,39.3739,-0.6014,2.7693,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA.VOLT.0237,V237_DDR,39.1969,-0.8395,2.8304,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDAHUB2,GRDAHUB2_H,26.8836,-1.6137,-8.7086,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDAHUB3,GRDAHUB3_H,23.2820,-1.7871,-12.1369,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA_GRDA,GRDA_LA,40.0956,-0.8417,3.7314,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA_HUB,GRDA_H,32.0305,-1.3550,-3.8205,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRDA_HUBSA,GRDASA_H,31.7277,-1.4144,-4.0639,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,GRE,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,5.6852,3.8722,-35.3929,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GSEC_SPS,SPS_GSEC_LA,115.9429,3.3721,75.3649,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GSPR2014HUB,GSPR2014HUB_H,94.7708,2.6684,54.8965,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GSPR2015HUB,GSPR2015HUB_H,92.0359,2.4691,52.3609,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,45.2674,1.0385,7.0229,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,HARRISON,CSWSLEBROCKPLT1,28.4734,-0.2526,-8.4799,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,HAST_TNSK_HUB,HAST_TNSK_H,12.5169,-1.2796,-23.4094,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,HQST,PJM,24.0292,-0.6661,-12.5107,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,HST,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,57.9836,-1.0570,21.8346,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,57.9836,-1.0570,21.8346,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,56.0861,-1.0885,19.9686,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,56.0861,-1.0885,19.9686,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,59.9352,-1.0517,23.7810,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,59.9352,-1.0517,23.7810,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,INDN_INDN,INDN_LA,57.4669,-1.0663,21.3272,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,-0.8814,-2.8032,-35.2841,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,ISNE,PJM,24.0292,-0.6661,-12.5107,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,JEA,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,10.6044,-1.4677,-25.1339,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,10.6044,-1.4677,-25.1339,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,10.3902,-1.7461,-25.0697,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KACYCT4,KACYNEARMANUNCT4_RA,24.7051,-1.6376,-10.8632,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,74.5396,-1.9427,39.2764,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,24.7051,-1.6376,-10.8632,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,24.6127,-1.5382,-11.0550,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,24.6385,-1.5677,-10.9998,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KACY_KACY,KACY_LA,24.5968,-1.4982,-11.1109,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,23.8011,-1.7242,-11.6807,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,51.8346,-1.6422,16.2709,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-16.2459,-2.7396,-50.7122,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-13.9011,-3.3282,-47.7789,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.VOLT.0222,V222_DDR,13.5409,-1.5942,-22.0709,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.VOLT.0223,V223_DDR,17.2403,-1.9755,-17.9901,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.VOLT.0241,V241_DDR,42.9844,-0.4590,6.2375,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.VOLT.0243,V243_DDR,33.3456,-1.3044,-2.5559,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.VOLT.0247,V247_DDR,31.2815,-1.7468,-4.1777,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.VOLT.0253,V253_DDR,24.3898,-1.6060,-11.2101,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,8.7241,-3.6450,-24.8369,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,14.6681,-2.2526,-20.2852,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,14.6681,-2.2526,-20.2852,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,14.6681,-2.2526,-20.2852,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,14.6681,-2.2526,-20.2852,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,23.8764,-1.6276,-11.7019,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,23.8764,-1.6276,-11.7019,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHUB,KCPLHUB_H,10.6448,-2.5394,-24.0218,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHUB17,KCPLHUB17_H,9.1108,-2.5653,-25.5298,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHUB18,KCPLHUB18_H,8.4303,-2.6044,-26.1712,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHUB19,KCPLHUB19_H,8.2694,-2.5481,-26.3884,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHUB20,KCPLHUB20_H,7.6544,-2.6114,-26.9401,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHUB21,KCPLHUB21_H,7.8629,-2.5307,-26.8124,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHUB22,KCPLHUB22_H,8.4138,-2.5618,-26.2303,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHUB23,KCPLHUB23_H,7.7381,-2.6173,-26.8505,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLHUB24,KCPLHUB24_H,7.0893,-2.6712,-27.4455,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,12.3492,-1.9136,-22.9432,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,12.3492,-1.9136,-22.9432,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,14.8489,-2.5118,-19.8452,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,14.8489,-2.5118,-19.8452,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,23.3336,-2.1916,-11.6807,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,23.8011,-1.7242,-11.6807,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,24.3082,-1.5197,-11.3780,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,24.3082,-1.5197,-11.3780,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,24.3082,-1.5197,-11.3780,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,24.3082,-1.5197,-11.3780,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,24.3082,-1.5197,-11.3780,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,24.3082,-1.5197,-11.3780,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,24.3082,-1.5197,-11.3780,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,24.3082,-1.5197,-11.3780,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,6.5506,-2.2857,-28.3696,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,26.8592,-1.5452,-8.8014,37.2058\n03/19/2025 23:00:00,03/20/2025 04:00:00,KCPL_KCPL,KCPL_LA,23.6286,-1.6158,-11.9616,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KENN,KENN_LA,28.8212,-0.0977,-8.2871,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KEP2_SECI,KEP2_SECI_LA,1.0372,-0.0358,-36.1329,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KERR_1,GRDAKERR_HYDUN1_RA,39.0227,-0.9140,2.7308,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KERR_2,GRDAKERR_HYDUN2_RA,39.0240,-0.9001,2.7182,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KERR_3,GRDAKERR_HYDUN3_RA,39.0240,-0.9001,2.7182,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KERR_4,GRDAKERR_HYDUN4_RA,39.0227,-0.9140,2.7308,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,14.7012,-2.2195,-20.2852,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,14.7012,-2.2195,-20.2852,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,15.7595,-2.0223,-19.4241,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,15.7595,-2.0223,-19.4241,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,11.3605,-2.2286,-23.6169,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,10.0917,-2.1657,-24.9485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,10.0917,-2.1657,-24.9485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,1.6396,-0.3685,-35.1978,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,1.6396,-0.3685,-35.1978,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,1.6396,-0.3685,-35.1978,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,8.4626,-0.2346,-28.5088,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,8.4626,-0.2346,-28.5088,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,1.5190,-0.4516,-35.2353,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,6.4578,-0.9626,-29.7855,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,7.8966,-2.1992,-27.1102,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,66.0264,-1.9259,30.7464,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,66.0264,-1.9259,30.7464,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,10.4306,-1.9636,-24.8117,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,10.4306,-1.9636,-24.8117,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,10.4306,-1.9636,-24.8117,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,7.1893,-1.2358,-28.7808,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,-0.3591,-0.7889,-36.7762,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,13.7070,-1.7967,-21.7022,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,10.7577,-1.6594,-24.7888,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,LAFA,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LAM345,LAM345,0.7774,-0.9053,-35.5232,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,LEPA,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,13.8676,-1.3530,-21.9853,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_LES,LES_LA,13.6476,-1.4018,-22.1566,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,13.2148,-1.5443,-22.4469,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,13.5617,-1.4814,-22.1629,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,13.5617,-1.4814,-22.1629,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,13.5617,-1.4814,-22.1629,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,13.2160,-1.5430,-22.4469,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,13.2148,-1.5443,-22.4469,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_WAVERLY,LES_WAVERLY_H,12.9892,-1.5734,-22.6434,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,10.6739,-1.7744,-24.7577,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,10.6739,-1.7744,-24.7577,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,LGEE,LGEE,25.5529,-0.5112,-11.1419,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MALDEN,MALDEN_LA,28.6766,-0.1389,-8.3905,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MCWEST,MCWEST,46.7912,2.1269,7.4584,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MDU,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,10.6294,1.3381,-27.9147,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,11.3879,-1.2502,-24.5679,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,12.7629,0.0634,-24.5064,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MEAN_NPPD,NPPD_MEAN_LA,10.2836,-0.9151,-26.0073,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MEC,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MHEB,MHEB,20.1130,0.1237,-17.2167,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,-0.1841,-2.3807,-35.0093,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,7.0159,-1.3288,-28.8612,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,-0.1841,-2.3807,-35.0093,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,-0.1841,-2.3807,-35.0093,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,7.0159,-1.3288,-28.8612,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,-0.3383,-2.3193,-35.2249,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MISO,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,1.2488,0.4473,-36.4044,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,1.2488,0.4473,-36.4044,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,8.8590,-1.9079,-26.4390,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,0.4392,-1.7226,-35.0442,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,7.6481,-2.0255,-27.5324,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,0.0061,-1.7761,-35.4237,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,1.5577,-1.7350,-33.9132,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,0.0114,-1.6783,-35.5162,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,2.3064,-1.8690,-33.0306,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,2.3064,-1.8690,-33.0306,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,2.3064,-1.8690,-33.0306,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,2.3064,-1.8690,-33.0306,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,2.3064,-1.8690,-33.0306,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,28.4010,-1.3698,-7.4351,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,28.0350,-0.4966,-8.6743,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,28.0350,-0.4966,-8.6743,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,26.6772,-0.7660,-9.7627,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,39.5148,-0.3295,2.6384,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MOWR,AECI,33.7335,-0.8289,-2.6435,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,30.0685,-1.0104,-6.1270,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,28.6255,-0.4979,-8.0825,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,-1.4487,-3.0218,-35.6329,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,-10.0000,-2.4054,-44.8005,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,-8.5811,-2.8593,-42.9277,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,-1.3240,-2.8971,-35.6329,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,16.0459,-2.1172,-19.0428,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,16.0459,-2.1172,-19.0428,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,16.0501,-2.1130,-19.0428,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,16.0501,-2.1130,-19.0428,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,13.5409,-1.5942,-22.0709,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,13.5409,-1.5942,-22.0709,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,13.5409,-1.5942,-22.0709,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,13.4302,-1.7049,-22.0709,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,13.5409,-1.5942,-22.0709,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,13.5409,-1.5942,-22.0709,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,13.5409,-1.5942,-22.0709,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,31.8481,-0.7957,-4.5622,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,21.5170,-2.2230,-13.4659,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,14.7085,-2.6846,-19.8128,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,14.6083,-2.7848,-19.8128,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,14.7086,-2.6845,-19.8128,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,26.5590,-1.5158,-9.1311,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,26.5590,-1.5158,-9.1311,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MPS_MPS,MPS_LA,32.5708,-1.4205,-3.2146,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MSTNG,SPSMSTNGPLT1,141.6464,5.4236,99.0168,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,MSTNG4,SPSMSTNGUN4_RA,141.4448,5.2221,99.0168,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MSTNG5,SPSMSTNGUN5_RA,141.4462,5.2235,99.0168,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,141.6464,5.4236,99.0168,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NBSO,PJM,24.0292,-0.6661,-12.5107,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,8.2438,-2.3735,-26.5887,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,8.2399,-2.3773,-26.5887,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,49.4086,0.5271,11.6756,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NHC1,VACS,27.8077,-0.0724,-9.3258,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,10.4559,-1.5629,-25.1872,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,10.4559,-1.5629,-25.1872,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,10.4559,-1.5629,-25.1872,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,7.7141,1.3355,-30.8273,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,11.2658,-1.8466,-24.0935,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,11.9730,-1.8333,-23.3997,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,-0.7733,-1.7915,-36.1877,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,11.2658,-1.8466,-24.0935,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.HUB.PY2018,NPPDPY18_H,9.7052,-1.4522,-26.0485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,9.7473,-1.4981,-25.9605,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,9.7934,-1.4568,-25.9557,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,9.8365,-1.4857,-25.8838,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,-4.6532,-1.7227,-40.1364,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,10.7343,-0.2514,-26.2202,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,10.7343,-0.2514,-26.2202,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,7.2520,-1.7128,-28.2411,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,-4.6532,-1.7227,-40.1364,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,17.1935,-3.6029,-16.4096,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,12.8433,0.3363,-24.6989,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,8.5528,-0.2014,-28.4517,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,12.8433,0.3363,-24.6989,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,13.8799,0.4847,-23.8107,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,12.0499,0.2388,-25.3948,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,13.5095,-0.9753,-22.7212,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,11.2658,-1.8466,-24.0935,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,8.8327,-0.2899,-28.0834,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,10.7343,-0.2514,-26.2202,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,10.7343,-0.2514,-26.2202,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,11.3972,-0.2430,-25.5658,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,11.3490,-0.2262,-25.6307,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,11.3490,-0.2262,-25.6307,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,11.4058,-0.4435,-25.3566,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,1.8281,-1.4550,-33.9228,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,11.8476,-1.4027,-23.9556,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,7.5344,1.4293,-31.1008,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,-1.1183,-1.2883,-37.0359,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,-3.4828,-1.2397,-39.4491,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.NELI.DDR,NELI_DDR,-2.0030,-1.6273,-37.5816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.NPPM.1058,SH1058_DDR,33.6994,-0.8789,-2.6276,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,11.1890,-0.7783,-25.2387,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,11.2658,-1.8466,-24.0935,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,11.9730,-1.8333,-23.3997,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,-4.6532,-1.7227,-40.1364,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.TECH.1,KEARNE_DDR,12.2960,-0.1597,-24.7503,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,10.7326,-2.5090,-23.9644,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,10.7326,-2.5090,-23.9644,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,-4.3458,-1.7224,-39.8293,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD.VOLT.0236,V236_DDR,12.8279,-1.1998,-23.1783,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD2017HUB,NPPD2017HUB_H,9.7373,-1.4599,-26.0088,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,29.4304,-1.7953,-5.9802,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,7.7141,1.3355,-30.8273,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,13.0228,0.3623,-24.5455,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,13.0228,0.3623,-24.5455,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,12.8509,-1.2644,-23.0906,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,12.8517,-1.1760,-23.1783,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,-0.8570,-1.7204,-36.3426,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,11.4309,-0.3230,-25.4521,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,32.9398,-1.6385,-2.6276,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,32.9398,-1.6385,-2.6276,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,32.9398,-1.6385,-2.6276,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,12.5174,-1.2755,-23.4131,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,10.1958,-2.4397,-24.5704,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,12.5897,-0.8868,-23.7294,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,0.1100,-2.1441,-34.9518,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,0.1100,-2.1441,-34.9518,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,9.6077,-0.6280,-26.9702,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,9.3967,-0.6847,-27.1245,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,14.0899,-1.0414,-22.0746,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,14.0573,-1.0741,-22.0746,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,14.0573,-1.0741,-22.0746,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,14.0528,-0.9859,-22.1672,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,17.1935,-3.6029,-16.4096,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,13.9240,-1.0006,-22.2813,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,12.9005,-1.6207,-22.6848,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,12.6060,-1.1952,-23.4047,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,12.5902,-1.2127,-23.4031,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,12.6080,-1.1965,-23.4014,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,12.6080,-1.1965,-23.4014,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,12.5174,-1.2755,-23.4131,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,12.4431,-1.3498,-23.4131,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,8.6818,1.6461,-30.1703,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,12.9027,-0.9613,-23.3419,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,9.4153,-0.5514,-27.2392,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,7.6880,-0.9287,-28.5893,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,8.2994,-0.3494,-28.5571,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,34.2076,-0.3708,-2.6276,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,-2.0030,-1.6273,-37.5816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,9.9079,-0.4815,-26.8165,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,9.9079,-0.4815,-26.8165,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_NPPD,NPPD_LA,15.8797,-0.8895,-20.4367,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,12.9005,-1.6207,-22.6848,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,12.9005,-1.6207,-22.6848,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,11.3877,-1.8710,-23.9472,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,13.3159,0.2196,-24.1097,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NSB,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NSP,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NSSO,PJM,24.0292,-0.6661,-12.5107,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,NYIS,PJM,24.0292,-0.6661,-12.5107,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,2.0391,-1.9477,-33.2191,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,-1.6892,-3.0377,-35.8575,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,-5.5046,-2.9426,-39.7679,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,-5.5046,-2.9426,-39.7679,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-2.2564,-1.3373,-38.1250,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-7.3030,-3.2472,-41.2617,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-38.6953,-2.5004,-73.4008,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-14.3329,-3.2942,-48.2446,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,-4.0643,-3.1858,-38.0845,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,-1.8905,-3.0707,-36.0257,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,9.7891,-2.0715,-25.3453,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,-4.0643,-3.1858,-38.0845,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,-1.0263,-1.5121,-36.7201,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,-0.3383,-2.3193,-35.2249,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,3.4159,-2.2381,-31.5519,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,44.9639,-0.9555,8.7135,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,-1.8905,-3.0707,-36.0257,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,1.2401,-2.8150,-33.1508,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,3.4001,-3.1737,-30.6322,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,4.8942,-2.4664,-29.8454,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-14.4280,-1.1720,-50.4619,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,-0.3383,-2.3193,-35.2249,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,-0.3383,-2.3193,-35.2249,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,-1.8905,-3.0707,-36.0257,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.NUEN.ADA1,ADA1_DDR,7.3739,-1.8882,-27.9439,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.NUEN.LAM1,LAM1_DDR,34.7923,0.9611,-3.3747,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.NUEN.MDT2,MDT2_DDR,9.7935,-2.0671,-25.3453,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.NUEN.MDT3,MDT3_DDR,9.7935,-2.0671,-25.3453,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.NUEN.WWO1,WWO1_DDR,7.2873,-1.8543,-28.0643,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,9.5060,-2.1450,-25.5550,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,9.5060,-2.1450,-25.5550,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,9.5794,-2.0715,-25.5550,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,9.5069,-2.2151,-25.4839,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,9.5069,-2.2151,-25.4839,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,9.5794,-2.0715,-25.5550,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,9.5794,-2.0715,-25.5550,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,-1.8905,-3.0707,-36.0257,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,29.8757,0.2155,-7.5458,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,-1.0263,-1.5121,-36.7201,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-5.1970,-1.4246,-40.9784,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,1.2401,-2.8150,-33.1508,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,32.4163,0.3533,-5.1429,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,4.2884,-2.7244,-30.1931,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,4.2884,-2.7244,-30.1931,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,4.2988,-2.7140,-30.1931,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,4.2988,-2.7140,-30.1931,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-4.0660,-3.9491,-37.3229,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,-3.0822,-2.9695,-37.3186,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,-1.6892,-3.0377,-35.8575,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,-5.1000,-2.9657,-39.3402,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,-5.1000,-2.9657,-39.3402,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,1.6219,-0.9680,-34.6161,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,4.4486,-2.5416,-30.2157,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,4.4486,-2.5416,-30.2157,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,4.4486,-2.5416,-30.2157,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0033,FOSTER_DDR,11.2935,-1.7656,-24.1469,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,26.5310,-0.4798,-10.1951,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0035,TARBY_DDR,34.3486,0.4472,-3.3045,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,26.5310,-0.4798,-10.1951,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,24.9305,-0.8909,-11.3845,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,24.9305,-0.8909,-11.3845,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-9.4223,-1.0542,-45.5741,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0040,TROSPER_DDR,11.4065,-1.7393,-24.0602,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,11.0105,-1.7534,-24.4420,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,33.2989,0.4989,-4.4059,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0115,V115_DDR,9.9262,-2.0229,-25.2569,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0116,V116_DDR,77.1938,-0.7030,40.6909,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0118,V118_DDR,23.7211,-1.1484,-12.3364,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0125,V125_DDR,34.0271,0.6897,-3.8685,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0126,V126_DDR,34.3815,-0.4248,-2.3996,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0129,V129_DDR,23.8122,-2.0675,-11.3262,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,10.4345,-1.8871,-24.8844,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0134,V134_DDR,35.6056,-0.1556,-1.4447,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0138,V138_DDR,33.6527,-0.5766,-2.9766,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,10.5753,-1.7669,-24.8637,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0143,V143_DDR,28.3714,-0.8475,-7.9870,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0149,V149_DDR,8.3633,-2.2515,-26.5912,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0150,V150_DDR,8.8000,-2.1320,-26.2739,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0155,V155_DDR,33.0396,-0.7413,-3.4250,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0156,V156_DDR,10.4345,-1.8871,-24.8844,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0166,V166_DDR,34.8824,0.5252,-2.8488,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,10.5937,-1.7780,-24.8342,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,8.8000,-2.1320,-26.2739,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0170,V170_DDR,7.1077,-1.8508,-28.2474,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,8.3772,-2.3450,-26.4838,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0176,V176_DDR,8.8000,-2.1320,-26.2739,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0177,V177_DDR,-1.3253,-2.6136,-35.9176,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,10.6610,-1.7807,-24.7642,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,5.6858,-2.4626,-29.0575,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0195,V195_DDR,111.2100,1.0732,72.9309,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0197,V197_DDR,33.3369,-0.3561,-3.5129,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0198,V198_DDR,34.8824,0.5252,-2.8488,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0208,V208_DDR,111.2520,1.1303,72.9158,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0209,V209_DDR,111.2520,1.1303,72.9158,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,33.5338,-0.6643,-3.0079,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0216,V216_DDR,10.9091,-1.7589,-24.5379,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0219,V219_DDR,33.0396,-0.7413,-3.4250,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0220,V220_DDR,8.8000,-2.1320,-26.2739,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0224,V224_DDR,9.7811,-1.9787,-25.4461,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0225,V225_DDR,9.7831,-1.9767,-25.4461,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0226,V226_DDR,9.7811,-1.9787,-25.4461,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0227,V227_DDR,9.7811,-1.9787,-25.4461,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0229,V229_DDR,-6.4229,-0.8900,-42.7388,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0231,V231_DDR,28.1910,-0.5874,-8.4276,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0238,V238_DDR,-5.5500,-3.2314,-39.5246,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.VOLT.0242,V242_DDR,33.3046,-0.6618,-3.2396,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,0.9841,-3.4263,-32.7955,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,-0.3383,-2.3193,-35.2249,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,-1.4601,-2.9726,-35.6935,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,3.4458,-2.2083,-31.5519,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,0.9841,-3.4263,-32.7955,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,3.2388,-1.9697,-31.9975,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-18.4911,-4.6572,-51.0398,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEHL7,OKGEHL7_H,13.8708,-1.8481,-21.4870,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEHL8,OKGEHSL1UN8_RA,13.8708,-1.8481,-21.4870,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEHL910,OKGEHSL1PLT2,13.4174,-2.3016,-21.4870,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,3.3092,-2.1640,-31.7327,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEMCC,OKGEMCCLAIPLT1,9.5600,-2.3915,-25.2544,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,30.9204,-0.9193,-5.3662,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,30.9204,-0.9193,-5.3662,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,30.8627,-0.9770,-5.3662,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,12.0390,-2.4275,-22.7395,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,12.0390,-2.4275,-22.7395,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,12.0390,-2.4275,-22.7395,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,12.1672,-2.2992,-22.7395,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGESM1,OKGESEMINOLEUN1_RA,20.1745,-1.6979,-15.3335,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGESM2,OKGESEMINOLEUN2_RA,16.2506,-1.6852,-19.2701,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGESM3,OKGESEMINOLEUN3_RA,16.2506,-1.6852,-19.2701,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGESO1,OKGESONR1UN1_RA,-20.0820,-2.8301,-54.4578,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGESO2,OKGESONR1UN2_RA,-5.1000,-2.9657,-39.3402,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,3.1573,-2.3159,-31.7327,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,3.1729,-2.9849,-31.0482,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGETINK5A,OKGETINK5UN1_RA,12.0603,-1.7422,-23.4034,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGETINK5B,OKGETINK5UN2_RA,12.0603,-1.7422,-23.4034,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,3.7374,-2.5257,-30.9428,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,-1.6892,-3.0377,-35.8575,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,32.8743,0.4472,-4.7788,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,-0.3383,-2.3193,-35.2249,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE_OKGE,OKGE_LA,22.9452,-1.3352,-12.9255,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-5.1970,-1.4246,-40.9784,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,3.6114,-2.6517,-30.9428,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMLP,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,37.2872,-1.0877,1.1690,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,32.6120,0.0011,-4.5951,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_GENHUB,OMPA_GENHUB_H,8.6257,-2.1659,-26.4143,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-38.5857,-2.3908,-73.4008,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,4.3444,-2.7424,-30.1192,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,-4.0643,-3.1858,-38.0845,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,1.6522,-2.6469,-32.9068,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,15.6510,-2.4450,-19.1100,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,106.0000,-1.2820,70.0761,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-38.7141,-2.5192,-73.4008,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-38.7141,-2.5192,-73.4008,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_SPP,OMPA_SPP_LA,9.9413,-1.9759,-25.2888,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,0.9841,-3.4263,-32.7955,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,34.4128,-1.1377,-1.6554,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,34.4128,-1.1377,-1.6554,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,34.4128,-1.1377,-1.6554,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,34.4128,-1.1377,-1.6554,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,ONT,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,10.2657,-1.5586,-25.3816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,10.2657,-1.5586,-25.3816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,10.2657,-1.5586,-25.3816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,10.2657,-1.5586,-25.3816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,10.2657,-1.5586,-25.3816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,10.2657,-1.5586,-25.3816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,10.2657,-1.5586,-25.3816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,10.2657,-1.5586,-25.3816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,10.2657,-1.5586,-25.3816,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,10.4951,-1.5197,-25.1911,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,10.4559,-1.5629,-25.1872,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,11.1257,-1.2035,-24.8767,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,10.7795,-1.4302,-24.9962,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,10.7795,-1.4302,-24.9962,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD_GLDN,OPPD_GLDN_LA,10.5462,-1.5286,-25.1311,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,10.3821,-1.5317,-25.2922,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,17.1935,-3.6029,-16.4096,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,10.4744,-1.9949,-24.7366,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,10.4580,-1.5605,-25.1874,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD_OPPD,OPPD_LA,10.6215,-1.4433,-25.1412,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,10.7693,-1.3963,-25.0403,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,10.7771,-1.4054,-25.0234,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,OTP,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,OVEC,OVEC,25.0027,-0.5719,-11.6313,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PARAGOULD,PARAGOULD_LA,29.0956,-0.0339,-8.0764,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,39.4270,-1.1940,3.4151,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,39.4270,-1.1940,3.4151,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,39.4270,-1.1940,3.4151,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,39.2155,-1.0575,3.0670,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,39.2155,-1.0575,3.0670,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,39.2155,-1.0575,3.0670,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PIGGOTT,PIGGOTT_LA,28.7695,-0.1123,-8.3242,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PJM,PJM,24.0292,-0.6661,-12.5107,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PLUM,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,POPLARBLUFF,POPLARBLUFF_LA,29.1661,-0.2677,-7.7722,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,46.8188,1.7770,7.8358,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,46.8188,1.7770,7.8358,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,46.0752,1.8369,7.0323,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,46.0752,1.8369,7.0323,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,47.1342,3.3147,6.6135,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,47.1342,3.3147,6.6135,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,46.7371,2.1605,7.3707,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,49.9678,1.2397,11.5221,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-5.5967,-2.6449,-40.1578,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,62.5019,-1.1139,26.4099,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,15.3094,-1.4051,-20.4915,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,9.9983,-1.1206,-26.0871,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,38.5395,-0.3733,1.7069,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,36.8931,-0.5643,0.2515,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,12.2323,-1.6553,-23.3183,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,41.5238,1.5047,2.8132,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,10.2001,-1.9843,-25.0215,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,43.6364,3.0167,3.4137,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,24.0174,0.7872,-13.9758,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,11.7478,-1.2818,-24.1763,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,PUPP,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,RCEAST,RCEAST,7.5222,0.6419,-30.3256,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SALINA_1,GRDASALINA1UN1_RA,39.0260,-0.9107,2.7308,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SALINA_2,GRDASALINA1UN2_RA,39.0260,-0.9107,2.7308,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SALINA_3,GRDASALINA1UN3_RA,39.0260,-0.9107,2.7308,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SALINA_4,GRDASALINA1UN4_RA,39.0260,-0.9107,2.7308,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SALINA_5,GRDASALINA1UN5_RA,39.0260,-0.9107,2.7308,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SALINA_6,GRDASALINA1UN6_RA,39.0260,-0.9107,2.7308,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SARPY_1,OPPDSARPYUN1_RA,10.5652,-1.5441,-25.0966,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SARPY_2,OPPDSARPYUN2_RA,10.6643,-1.4791,-25.0625,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SARPY_3,OPPDSARPYUN3_RA,10.5286,-1.6120,-25.0653,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SARPY_4,OPPDSARPYUN4_RA,10.5286,-1.6120,-25.0653,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SARPY_5,OPPDSARPYUN5_RA,10.5286,-1.6120,-25.0653,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SC,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SCEG,VACS,27.8077,-0.0724,-9.3258,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SCSE,SCSE,9.9592,0.1594,-27.4061,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SEC,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,-1.9512,-2.3531,-36.8040,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,-1.9512,-2.3531,-36.8040,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,-1.9512,-2.3531,-36.8040,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,2.2799,0.6693,-35.5953,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,-1.9512,-2.3531,-36.8040,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,0.2073,-1.4616,-35.5371,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,1.4943,-2.0220,-33.6896,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,1.4943,-2.0220,-33.6896,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,2.3021,-1.8732,-33.0306,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,-3.6726,-2.5406,-38.3379,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,8.3199,-0.3773,-28.5088,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,1.5429,0.3097,-35.9727,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,4.4490,-0.4481,-32.3089,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,-1.3704,-2.2333,-36.3430,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,4.5000,-0.5361,-32.1698,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,-0.1611,-1.9310,-35.4361,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,1.3919,-0.7707,-35.0434,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,1.4136,-0.5358,-35.2565,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,1.4136,-0.5358,-35.2565,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,1.4136,-0.5358,-35.2565,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,1.4136,-0.5358,-35.2565,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,1.0523,-0.7342,-35.4195,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,0.2073,-1.4616,-35.5371,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI_SECI,SECI_LA,1.9888,-0.4310,-34.7862,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,-0.8814,-2.8032,-35.2841,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,-0.8814,-2.8032,-35.2841,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,2.3021,-1.8732,-33.0306,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SEHA,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,3.6114,-2.6517,-30.9428,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SERU,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SETH,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SGE,SGE,9.6213,0.2440,-27.8287,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SMEP,MISO,23.1154,-0.4518,-13.6388,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SOCO,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPA,SPA,34.1238,-0.2248,-2.8573,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPC,SPC,40.3274,1.4634,1.6580,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPPNORTH_HUB,SPPNORTH_H,13.0121,-1.1038,-23.0901,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPPSOUTH_HUB,SPPSOUTH_H,15.6427,-1.8859,-19.6773,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,35.6587,-0.5784,-0.9688,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,35.6675,-0.5696,-0.9688,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,35.4847,-0.4777,-1.2435,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,35.4847,-0.4777,-1.2435,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_NIXA,SPRM_NIXA_LA,35.9652,-0.3880,-0.8527,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_SPRM,SPRM_LA,35.9591,-0.3138,-0.9330,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,35.7939,-0.5814,-0.8307,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,35.7939,-0.5814,-0.8307,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,35.7107,-0.6646,-0.8307,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,35.8047,-0.5705,-0.8307,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,144.1984,4.7237,102.2688,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,148.9797,3.8901,107.8836,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,50.1143,0.7615,12.1469,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,50.1143,0.7615,12.1469,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,140.7569,3.2304,100.3206,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,142.2814,4.9273,100.1481,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,144.0213,3.9964,102.8189,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,144.6609,6.7708,100.6842,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,138.8411,3.2137,98.4215,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,141.9578,5.3657,99.3862,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,142.4972,5.8727,99.4186,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,142.4972,5.8727,99.4186,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,141.9578,5.3657,99.3862,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,50.1662,0.8569,12.1034,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,148.9797,3.8901,107.8836,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,51.1410,0.9041,13.0309,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,55.8361,-0.7711,19.4013,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,54.0152,1.1416,15.6676,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,52.9190,1.9452,13.7678,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,52.2131,0.9924,14.0147,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,60.9700,-1.1137,24.8778,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,60.9700,-1.1137,24.8778,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,60.9700,-1.1137,24.8778,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,60.9700,-1.1137,24.8778,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GRID.WRAB,WRAB_DDR,49.9732,2.6091,10.1582,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,60.9700,-1.1137,24.8778,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,137.5717,3.2888,97.0769,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,137.5717,3.2888,97.0769,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,134.4942,3.3176,93.9706,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,134.4942,3.3176,93.9706,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,134.4942,3.3176,93.9706,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,137.5717,3.2888,97.0769,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,47.1817,0.5551,9.4206,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,47.1798,0.5551,9.4188,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,47.1844,0.5552,9.4233,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,49.4086,0.5271,11.6756,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,142.0146,5.4410,99.3677,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,138.7715,3.1680,98.3975,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,138.7715,3.1680,98.3975,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,138.7715,3.1680,98.3975,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,138.7715,3.1680,98.3975,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,141.9488,5.5071,99.2357,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,141.8613,5.2781,99.3772,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,141.8613,5.2781,99.3772,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,3.7737,-2.4894,-30.9428,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,47.2073,0.4260,9.5753,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,47.2073,0.4260,9.5753,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,47.1833,0.5586,9.4187,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,49.9732,2.6091,10.1582,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,56.0448,-0.1311,18.9700,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,51.1103,0.5600,13.3443,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-2.2564,-1.3373,-38.1250,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,47.6805,0.8993,9.5753,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.PLANTX1,SPS.PLANTX1_H,145.8502,4.3380,104.3063,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.PLANTX2,SPS.PLANTX2_H,145.8502,4.3380,104.3063,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,145.4562,4.3055,103.9448,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,140.5213,3.4340,99.8814,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,58.5205,-0.6537,21.9683,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,144.7015,4.6766,102.8189,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,140.6208,3.5335,99.8814,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,50.2399,0.9306,12.1034,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,144.2137,5.2401,101.7676,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,144.6609,6.7708,100.6842,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,144.2137,5.2401,101.7676,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,144.9105,6.0285,101.6761,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,51.8658,0.4282,14.2317,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,145.1151,8.3661,99.5431,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,145.2943,8.5453,99.5431,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,144.6711,7.9785,99.4867,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,142.3961,5.8149,99.3753,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,145.1759,8.1533,99.8167,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,0.7774,-0.9053,-35.5232,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,49.7688,2.4480,10.1149,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,144.6500,4.5735,102.8706,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,144.6500,4.5735,102.8706,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,144.2137,5.2401,101.7676,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,139.1141,3.4136,98.4946,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,143.0914,6.7456,99.1399,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,146.9538,6.8804,102.8674,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,145.4743,5.4051,102.8632,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,145.7527,3.1898,105.3570,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,145.1151,8.3661,99.5431,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,146.1614,9.2589,99.6965,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,145.5483,8.6458,99.6965,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,140.9818,3.8945,99.8814,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,145.9936,5.9646,102.8231,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,58.1077,-0.4014,21.3031,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,58.0239,-0.4701,21.2880,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0163,V163_DDR,49.4751,1.3080,10.9612,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0168,V168_DDR,51.1215,-0.5590,14.4745,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0180,V180_DDR,146.1614,9.2589,99.6965,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0181,V181_DDR,58.7671,-0.1238,21.6850,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0182,V182_DDR,145.1544,8.1738,99.7747,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0199,V199_DDR,142.7224,6.3815,99.1349,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0200,V200_DDR,143.2444,6.5861,99.4524,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.VOLT.0235,V235_DDR,56.0448,-0.1311,18.9700,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,144.0213,3.9964,102.8189,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,144.6609,6.7708,100.6842,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,45.2330,1.0042,7.0229,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,46.2667,0.9526,8.1081,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS_SPS,SPS_LA,120.5818,5.5471,77.8287,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,143.9064,4.9542,101.7463,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SSCN_NPPD,SSCN_NPPD_LA,1.5555,-1.6934,-33.9571,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,28.2517,-0.2661,-8.6881,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,28.2517,-0.2661,-8.6881,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,TAL,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,TEC,SOUC,27.9341,-0.0096,-9.2623,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,7.6880,-0.9287,-28.5893,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,TVA,TVA,27.6734,-0.1385,-9.3940,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,UCUHUB,UCUHUB_H,10.7928,-1.9767,-24.4365,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,UCUHUB17,UCUHUB17_H,3.0071,-1.9813,-32.2176,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,UCUHUB18,UCUHUB18_H,4.3983,-2.1896,-30.6180,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,UCUHUB19,UCUHUB19_H,0.9227,-2.2636,-34.0196,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,UCUHUB20,UCUHUB20_H,1.0723,-2.1939,-33.9397,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,UCUHUB21,UCUHUB21_H,1.3375,-2.1515,-33.7170,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,UCUHUB22,UCUHUB22_H,0.7732,-2.2716,-34.1611,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,UCUHUB23,UCUHUB23_H,0.2265,-2.2855,-34.6940,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,UCUHUB24,UCUHUB24_H,2.3273,-2.1383,-32.7403,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,41.9911,1.9739,2.8113,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,41.9911,1.9739,2.8113,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,10.4838,-0.4273,-26.2948,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,10.4838,-0.4273,-26.2948,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,21.5120,-0.4413,-15.2526,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,44.5984,0.8254,6.5670,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,44.5984,0.8254,6.5670,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,41.9911,1.9739,2.8113,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,22.1476,-0.0520,-15.0063,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,27.8837,0.7090,-10.0312,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,10.9303,-1.5147,-24.7609,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,7.9502,-2.7326,-26.5231,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,45.1880,2.2457,5.7364,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,45.1880,2.2457,5.7364,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,25.3739,-3.0707,-8.7614,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,10.2659,-1.8807,-25.0594,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,25.1187,-0.5031,-11.5841,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,9.6793,-2.0234,-25.5033,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,10.9739,-1.4051,-24.8269,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,8.1531,-2.1533,-26.8995,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,26.4622,-1.9823,-8.7614,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,26.4622,-1.9823,-8.7614,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,9.2016,-1.6020,-26.4024,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,8.4906,-2.3644,-26.3509,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,12.6495,0.2037,-24.7601,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,45.3600,0.4456,7.7085,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,45.3600,0.4456,7.7085,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,45.3600,0.4456,7.7085,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,45.4147,0.6780,7.5307,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,45.4147,0.6780,7.5307,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,45.4147,0.6780,7.5307,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,40.8884,2.4051,1.2774,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,17.9053,-0.6312,-18.6694,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,17.9053,-0.6312,-18.6694,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,9.7589,0.1759,-27.6229,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,7.1709,-1.9500,-28.0850,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,40.6395,0.6501,2.7835,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,6.0453,-2.1290,-29.0316,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,7.5488,-2.6147,-27.0425,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,26.5139,-1.6106,-9.0814,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,44.0462,1.5741,5.2662,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,44.0462,1.5741,5.2662,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,44.0399,1.5679,5.2660,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,44.0462,1.5741,5.2662,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,44.9039,1.6461,6.0519,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,44.9039,1.6461,6.0519,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,44.9039,1.6461,6.0519,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,44.9039,1.6461,6.0519,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,44.9039,1.6461,6.0519,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,44.9039,1.6461,6.0519,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,44.9039,1.6461,6.0519,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,6.1468,-3.1510,-27.9081,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,24.7599,0.0781,-12.5241,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,7.8723,-1.4828,-27.8509,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,7.8723,-1.4828,-27.8509,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,4.1777,-1.6329,-31.3953,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,4.1777,-1.6329,-31.3953,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,18.3501,-0.1865,-18.6694,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,33.7933,0.0589,-3.4715,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,9.7440,-2.5195,-24.9425,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,9.4368,-2.1388,-25.6304,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,13.1564,-1.4130,-22.6365,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,21.5120,-0.4413,-15.2526,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,21.5120,-0.4413,-15.2526,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,9.6793,-2.0234,-25.5033,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,7.5650,0.5867,-30.2277,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,17.1878,-1.6534,-18.3647,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,8.6241,-2.2309,-26.3509,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,8.2845,-1.7572,-27.1642,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.FSE,WAUE.FSE_H,7.8314,-1.7363,-27.6383,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,45.6288,1.8715,6.5514,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,45.7514,1.8514,6.6940,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,7.0501,-3.3546,-26.8012,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,8.4051,-3.1198,-25.6810,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,20.9002,-0.6382,-15.6676,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,22.6136,-0.8313,-13.7610,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-8.9100,-2.7992,-43.3167,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,7.9502,-2.7326,-26.5231,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-12.2700,0.9954,-50.4713,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,11.0754,-1.9439,-24.1867,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,11.0757,-1.9436,-24.1867,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,11.0779,-1.9414,-24.1867,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,2.1568,-1.6301,-33.4190,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,7.5650,0.5867,-30.2277,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,12.4541,-1.1910,-23.5608,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,9.5594,-2.0566,-25.5899,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,12.4920,0.0461,-24.7601,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,12.3718,-0.5620,-24.2721,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,11.2059,-1.3415,-24.6585,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,14.7534,-1.6525,-20.8000,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,10.6108,-1.4780,-25.1171,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,9.7073,-2.4336,-25.0651,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,6.0453,-2.1290,-29.0316,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,17.1299,0.0929,-20.1690,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,9.6250,-2.0727,-25.5082,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,16.6665,-0.2348,-20.3047,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,12.0890,-1.1076,-24.0094,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,10.6739,-1.7744,-24.7577,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NTWK,WAUE.NTWK_H,15.7882,-0.7263,-20.6914,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,13.7193,-1.1265,-22.3601,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,13.7193,-1.1265,-22.3601,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,7.6967,-3.0893,-26.4200,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,4.4927,-4.1749,-28.5383,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,13.2317,-1.4274,-22.5469,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,7.6967,-3.0893,-26.4200,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,22.2453,-0.2564,-14.7042,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,9.9011,-1.8507,-25.4541,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,6.0453,-2.1290,-29.0316,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,11.9444,-1.1591,-24.1024,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,10.3364,-1.4155,-25.4541,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,5.8236,-1.6521,-29.7302,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,7.3098,-1.5396,-28.3565,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,13.1796,-0.5586,-23.4678,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,10.0167,-2.7928,-24.3964,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,11.9637,-1.2113,-24.0309,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,8.9725,-1.9887,-26.2448,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,9.4368,-2.1388,-25.6304,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.VOLT.0152,V152_DDR,39.0228,2.8750,-1.0582,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE.VOLT.0172,V172_DDR,44.7587,1.7815,5.7713,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_BEPM,WAUE_BEPM_LA,29.4721,0.7079,-8.4417,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,12.1708,-1.2181,-23.8171,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,12.3873,-0.5365,-24.2821,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_EWA,WAUE_EWA_LA,6.5077,0.7589,-31.4571,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,10.1394,-2.0245,-25.0420,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_HMMU,WAUE_HMMU_LA,11.8388,-0.9680,-24.3991,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,15.1223,-1.3379,-20.7457,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_MECB,WAUE_MECB_LA,11.3338,-0.6904,-25.1817,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_MMPA,WAUE_MMPA_LA,21.2422,0.6645,-16.6283,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_MRES,WAUE_MRES_LA,10.2978,-0.9872,-25.9210,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,33.8554,2.0737,-5.4242,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,45.6288,1.8715,6.5514,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,8.9892,-1.8796,-26.3371,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_OTP,WAUE_OTP_LA,26.6961,1.7034,-12.2132,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_OTPW,WAUE_OTPW_LA,33.7702,1.6570,-5.0927,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM,WAUE_UGPM_LA,15.0232,-1.0946,-21.0881,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,27.4639,0.4064,-10.1484,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,10.9241,-1.4533,-24.8286,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,24.6248,-0.3723,-12.2088,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,6.5077,0.7589,-31.4571,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,11.8388,-0.9680,-24.3991,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,11.2868,-2.0067,-23.9125,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,45.6288,1.8715,6.5514,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,21.2422,0.6645,-16.6283,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,12.5526,-0.5776,-24.0757,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,9.6160,-2.2831,-25.3068,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,25.9543,2.0481,-13.2998,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,1.2747,-3.1237,-32.8075,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,0.0845,-3.7110,-33.4105,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,34.4793,-1.6818,-1.0448,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,68.0000,-0.4336,31.2277,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,68.0000,-0.4336,31.2277,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,11.1109,-2.3387,-23.7563,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,63.2052,-0.2567,26.2559,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,57.3759,-0.3351,20.5051,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,67.8583,-1.9102,32.5626,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,67.8583,-1.9102,32.5626,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,67.8583,-1.9102,32.5626,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,67.8583,-1.9102,32.5626,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,67.8583,-1.9102,32.5626,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,67.8583,-1.9102,32.5626,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,67.8583,-1.9102,32.5626,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,67.8583,-1.9102,32.5626,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,49.0870,-1.8056,13.6867,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-2.2564,-1.3373,-38.1250,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-29.6140,-3.3631,-63.4568,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,0.1577,-3.5407,-33.5075,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,144.3667,4.3419,102.8189,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_ENMC,WFEC_ENMC_LA,143.9252,6.3897,100.3296,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,-1.8905,-3.0707,-36.0257,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,32.5020,-1.1106,-3.5934,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,141.6940,5.2123,99.2758,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,1.2360,-3.1625,-32.8075,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,1.2747,-3.1237,-32.8075,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,1.2747,-3.1237,-32.8075,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_OKGE,WFEC_OKGE_LA,12.8582,-1.1483,-23.1994,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,56.2263,0.0676,18.9527,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,2.7626,-4.4735,-29.9699,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,11.3849,-4.7584,-21.0626,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_WFEC,WFEC_LA,33.0489,-1.1114,-3.0457,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,141.6940,5.2123,99.2758,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,-2.1114,-2.4845,-36.8328,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,2.4852,-0.6711,-34.0497,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,8.2841,-2.4107,-26.5111,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,8.2841,-2.4107,-26.5111,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,8.2888,-2.4061,-26.5111,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,8.2888,-2.4061,-26.5111,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,8.2934,-2.4014,-26.5111,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,8.2934,-2.4014,-26.5111,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,8.2934,-2.4014,-26.5111,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,15.6466,-1.3548,-20.2045,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,7.4634,-2.7164,-27.0262,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,0.0000,-2.9574,-34.2485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,0.0000,-2.9574,-34.2485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,0.0000,-2.9574,-34.2485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,-2.7771,-2.6024,-37.3806,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,-2.7771,-2.6024,-37.3806,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,4.1510,-2.6865,-30.3685,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,4.1510,-2.6865,-30.3685,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,4.1510,-2.6865,-30.3685,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,7.4634,-2.7164,-27.0262,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,11.9491,-1.9122,-23.3446,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.HEC.GT1,WRHECGTUN32_RA,5.9778,-2.2239,-29.0043,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.HEC.GT2,WRHECGTUN33_RA,5.9778,-2.2239,-29.0043,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.HEC.GT3,WRHECGTUN34_RA,5.9778,-2.2239,-29.0043,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.HEC.GT4,WRHECGTUN35_RA,5.9778,-2.2239,-29.0043,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,11.9491,-1.9122,-23.3446,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,-0.4685,-2.0465,-35.6279,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-32.4242,-2.9462,-66.6840,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.JEC.1,WRJEFFUN10_RA,9.2119,-2.2990,-25.6951,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.JEC.2,WRJEFFUN11_RA,9.2697,-2.3061,-25.6302,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.JEC.3,WRJEFFUN12_RA,9.1712,-2.4046,-25.6302,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,-3.5754,-3.1851,-37.5962,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,-8.5542,-2.8325,-42.9277,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,-8.5542,-2.8325,-42.9277,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.LEC.4,WRLECUN26_RA,10.2284,-1.9113,-25.0663,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.LEC.5,WRLECUN27_RA,10.3115,-1.8244,-25.0701,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,7.1341,-1.7517,-28.3201,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,7.1341,-1.7517,-28.3201,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,7.1341,-1.7517,-28.3201,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,7.2100,-1.6923,-28.3036,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,-0.8814,-2.8032,-35.2841,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,-0.8814,-2.8032,-35.2841,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,4.5951,-0.0973,-32.5136,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,-0.2364,-2.3874,-35.0549,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,-0.2364,-2.3874,-35.0549,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,-0.3541,-0.7839,-36.7762,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,-0.8814,-2.8032,-35.2841,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,10.5779,-1.6863,-24.9418,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,7.1223,-2.6475,-27.4361,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,-8.5689,-2.8472,-42.9277,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,58.0527,-0.2662,21.1129,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,0.0000,-0.4250,-36.7809,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,8.2934,-2.4014,-26.5111,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,1.5590,-3.6899,-31.9570,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,11.9491,-1.9122,-23.3446,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,7.4634,-2.7164,-27.0262,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,1.3211,-2.4964,-33.3884,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.THAYERLD,WR.THAYERLD_LA,30.6291,-0.2218,-6.3551,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0102,WR.VOLT.0102_H,1.0969,-2.4747,-33.6343,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0106,V106_DDR,0.8726,-2.4881,-33.8452,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0139,WR.VOLT.0139_H,11.3443,-1.7080,-24.1537,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0141,WR.VOLT.0141_H,7.5243,-2.0903,-27.5913,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0146,WR.VOLT.0146_H,10.5422,-1.6447,-25.0190,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0147,WR.VOLT.0147_H,10.5422,-1.6447,-25.0190,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0148,WR.VOLT.0148_H,11.0320,-1.8033,-24.3707,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0153,WR.VOLT.0153_H,0.9069,-2.2271,-34.0720,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0157,V157_DDR,10.4978,-1.6709,-25.0372,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0158,V158_DDR,10.5422,-1.6447,-25.0190,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0159,WR.VOLT.0159_H,10.5422,-1.6447,-25.0190,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0165,WR.VOLT.0165_H,-0.0971,-2.7275,-34.5755,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0173,V173_DDR,7.4172,-1.4498,-28.3389,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0174,V174_DDR,0.2534,-2.5413,-34.4113,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0184,V184_DDR,0.3449,-2.7351,-34.1259,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0185,WR.VOLT.0185_H,1.2451,-2.4898,-33.4711,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0186,V186_DDR,1.6660,-2.5397,-33.0002,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0187,WR.VOLT.0187_H,0.5160,-2.6495,-34.0404,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0188,WR.VOLT.0188_H,0.9076,-2.4811,-33.8172,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0189,WR.VOLT.0189_H,6.5317,-2.0127,-28.6615,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0190,WR.VOLT.0190_H,7.6546,-2.2199,-27.3315,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0191,WR.VOLT.0191_H,8.0986,-2.2994,-26.8080,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0192,WR.VOLT.0192_H,8.0986,-2.2994,-26.8080,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0196,WR.VOLT.0196_H,7.6546,-2.2199,-27.3315,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0245,V245_DDR,1.2786,-2.4825,-33.4449,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.VOLT.0248,V248_DDR,0.8726,-2.4881,-33.8452,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,-2.4665,-3.0431,-36.6293,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,10.3112,-1.8881,-25.0066,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.WOLF,WRWOLFUN15_RA,0.8466,-3.8612,-32.4981,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,-0.4685,-2.0465,-35.6279,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,15.4213,-1.5801,-20.2045,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,0.0000,-2.9574,-34.2485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,0.0000,-2.9574,-34.2485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,0.0000,-2.9574,-34.2485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,0.0000,-2.9574,-34.2485,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,3.2721,-2.3558,-31.5780,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,7.5517,-2.0999,-27.5543,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,-0.3833,-2.6091,-34.9801,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,-0.3833,-2.6091,-34.9801,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,-0.3833,-2.6091,-34.9801,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,-0.3833,-2.6091,-34.9801,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,8.4944,-1.9635,-26.7480,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,8.4944,-1.9635,-26.7480,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,8.4944,-1.9635,-26.7480,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,8.4944,-1.9635,-26.7480,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,8.4944,-1.9635,-26.7480,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,8.4944,-1.9635,-26.7480,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-6.5333,-2.4234,-41.3159,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-6.5333,-2.4234,-41.3159,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-8.5507,-2.6451,-43.1115,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-8.5507,-2.6451,-43.1115,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_MIDW,WR_MIDW_LA,2.6668,-1.2089,-33.3302,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,42.3884,-0.9391,6.1216,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,25.5883,-1.6846,-9.9330,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,7.3380,-1.7407,-28.1272,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_SEG,WR_SEG_LA,13.2362,-1.5429,-22.4269,37.2060\n03/19/2025 23:00:00,03/20/2025 04:00:00,WR_WR,WR_LA,7.5479,-2.1297,-27.5283,37.2059\n03/19/2025 23:00:00,03/20/2025 04:00:00,YAD,VACS,27.8077,-0.0724,-9.3258,37.2059\n03/20/2025 00:00:00,03/20/2025 05:00:00,AEC,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,AECC_CSWS,CSWS_AECC_LA,30.0327,-0.0328,-6.2164,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,31.8933,-0.4959,-3.8928,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,28.6797,0.0380,-7.6403,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,32.1506,-0.7208,-3.4106,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,26.5072,-0.5763,-9.1985,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,28.6940,-0.5424,-7.0456,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,26.5987,-0.6605,-9.0228,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,AECI,AECI,26.8474,-0.9294,-8.5053,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,AEPM_CSWS,CSWS_LA,30.6052,0.1775,-5.8543,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,ALTW,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,AMRN,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,137.8864,3.5174,98.0870,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BBA,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,BCA,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,BEPM.ER01.DDR,ER01_DDR,9.8810,-1.4684,-24.9326,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BEPM_ER01,BEPM_ER01_LA,9.8810,-1.4684,-24.9326,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,11.9466,0.4811,-24.8165,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,12.7346,0.8905,-24.4379,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BEPM_UM01,BEPM_UM01_LA,41.6806,1.5692,3.8294,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BLKW,BLKW,145.5701,5.4826,103.8055,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,-26.7603,-3.1032,-59.9391,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,-26.7603,-3.1032,-59.9391,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,57.9822,-2.3587,24.0589,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,-26.7123,-3.0552,-59.9391,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,BRAZ,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,BUBA,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,5.4419,-0.9473,-29.8928,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,7.6068,-2.2070,-26.4682,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,7.6068,-2.2070,-26.4682,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,7.6068,-2.2070,-26.4682,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,7.6068,-2.2070,-26.4682,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,7.6068,-2.2070,-26.4682,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,-5.1755,-2.6919,-38.7655,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,13.4204,-1.8439,-21.0177,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,13.4204,-1.8439,-21.0177,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CLEC,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,32.5983,-0.6829,-3.0008,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,COWP,COWP_LA,27.3594,-0.5031,-8.4195,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,27.3594,-0.5031,-8.4195,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,27.3594,-0.5031,-8.4195,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CPLE,VACS,24.8917,-0.0817,-11.3085,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CPLW,VACS,24.8917,-0.0817,-11.3085,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,25.9298,0.1625,-10.5147,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,25.9298,0.1625,-10.5147,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,25.9298,0.1625,-10.5147,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,25.9298,0.1625,-10.5147,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CRTH_SPA,WRCRTH_SPA_LA,34.9376,-1.5697,0.2253,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,28.6782,1.7781,-9.3819,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,32.5201,-1.2866,-2.4753,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,26.5987,-0.6605,-9.0228,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,32.1506,-0.7208,-3.4106,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,28.6755,1.7745,-9.3810,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,27.8616,0.9249,-9.3453,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,28.4558,1.5381,-9.3643,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,28.4558,1.5381,-9.3643,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,31.1651,-1.0103,-4.1065,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,31.1651,-1.0103,-4.1065,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,31.1624,-1.0131,-4.1065,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,31.1624,-1.0131,-4.1065,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,26.5987,-0.6605,-9.0228,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,29.2827,0.8554,-7.8547,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,39.1505,-1.3807,4.2493,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,38.8915,-1.6398,4.2493,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,32.5851,-1.0206,-2.6763,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,29.2193,-0.8481,-6.2146,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,29.2193,-0.8481,-6.2146,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,29.0616,-1.0063,-6.2141,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,29.0616,-1.0063,-6.2141,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-8.8935,-1.7412,-43.4343,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,39.3075,-1.1307,4.1562,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,31.8722,-0.7680,-3.6418,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-10.3951,-1.4845,-45.1926,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-10.3224,-1.4118,-45.1926,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,18.1726,-1.1949,-16.9145,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.GRID.CDL1,CDL1_DDR,30.5865,-0.3836,-5.3119,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,25.8289,-1.7916,-8.6615,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,33.3795,-1.4966,-1.4058,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,30.5865,-0.3836,-5.3119,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.NUEN.CSI1,CSI1_DDR,33.7258,-0.5071,-2.0490,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.NUEN.CSI2,CSI2_DDR,33.7394,-0.4935,-2.0490,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,32.6055,-0.6757,-3.0008,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.NUEN.GAZA,GAZA_DDR,30.5865,-0.3836,-5.3119,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,57.6921,0.5148,20.8953,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.NUEN.T201,NT201_DDR,30.3625,-0.6941,-5.2254,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,26.1123,-1.3533,-8.8164,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,26.1123,-1.3533,-8.8164,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,26.5987,-0.6605,-9.0228,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,29.1067,2.0748,-9.2501,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,18.1726,-1.1949,-16.9145,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,18.1726,-1.1949,-16.9145,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,6.3723,-1.7105,-28.1992,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-10.3224,-1.4118,-45.1926,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,27.6314,0.7658,-9.4164,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,27.9471,-0.9911,-7.3438,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,27.5759,-1.3623,-7.3438,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,27.5669,-1.3713,-7.3438,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,21.4072,-0.8742,-14.0006,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,21.4072,-0.8742,-14.0006,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,27.8954,0.9407,-9.3273,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,29.1407,-0.6652,-6.4761,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,27.9591,1.0084,-9.3313,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,29.7383,2.7147,-9.2583,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,29.0922,-0.2097,-6.9801,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,33.7394,-0.4935,-2.0490,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0057,OKMU_DDR,30.8508,-0.3922,-5.0390,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0060,LEHIGH_DDR,57.6921,0.5148,20.8953,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0086,WARRENM_DDR,29.6103,-0.6998,-5.9719,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,28.8094,1.7177,-9.1903,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,35.6012,-0.7496,0.0689,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0121,V121_DDR,27.8954,0.9407,-9.3273,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0122,V122_DDR,34.9526,-0.7767,-0.5527,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0124,V124_DDR,42.6449,-0.9680,7.3309,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0135,V135_DDR,30.2113,-0.6526,-5.4181,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0144,V144_DDR,39.9014,-1.0708,4.6902,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0145,V145_DDR,39.9989,-1.2941,5.0110,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,27.9408,0.9828,-9.3239,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,27.2232,-0.0780,-8.9808,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0175,V175_DDR,32.6055,-0.6757,-3.0008,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,27.2232,-0.0780,-8.9808,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,27.4730,0.1618,-8.9708,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,30.2113,-0.6526,-5.4181,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,30.4652,-0.6983,-5.1185,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,30.3544,-0.7583,-5.1693,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,37.4754,-1.1251,2.3185,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,29.1970,-0.8390,-6.2459,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,30.4652,-0.6983,-5.1185,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0211,V211_DDR,28.2661,1.3288,-9.3447,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,36.0207,-0.7506,0.4894,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0213,V213_DDR,30.0694,-0.7125,-5.5001,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0215,V215_DDR,35.4242,-0.7655,-0.0922,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0217,V217_DDR,36.0255,-0.7776,0.5211,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0218,V218_DDR,37.2822,-1.1035,2.1038,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0228,V228_DDR,29.4287,-0.7434,-6.1099,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0232,V232_DDR,29.7746,-0.6619,-5.8454,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0233,V233_DDR,30.5091,-0.6710,-5.1019,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0240,V240_DDR,32.9769,-0.8313,-2.4738,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0244,V244_DDR,30.4652,-0.6983,-5.1185,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0246,MDT1_DDR,57.6921,0.5148,20.8953,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0249,V249_DDR,30.0671,-0.6771,-5.5378,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0250,V250_DDR,31.5228,-1.2042,-3.5550,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0251,V251_DDR,29.5838,-0.7824,-5.9157,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.VOLT.0252,V252_DDR,37.4754,-1.1251,2.3185,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,-9.6814,-1.7576,-44.2058,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,52.7541,-2.1508,18.6229,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,2.4172,-3.7978,-30.0670,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,27.7904,0.8450,-9.3365,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,5.1000,-2.7552,-28.4268,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,35.9030,-1.2479,0.8689,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,35.9030,-1.2479,0.8689,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,35.9030,-1.2479,0.8689,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,35.9030,-1.2479,0.8689,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,35.9030,-1.2479,0.8689,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,26.5987,-0.6605,-9.0228,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,28.4908,1.8016,-9.5928,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,29.7368,-0.6998,-5.8454,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,29.6841,-0.7525,-5.8454,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,32.0022,-0.2366,-4.0431,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,32.0022,-0.2366,-4.0431,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWWELSH1,CSWSWELSHUN1_RA,27.3948,0.3371,-9.2243,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWWELSH3,CSWSWELSHUN3_RA,27.3948,0.3371,-9.2243,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWWILKES1,CSWSWILKESUN1_RA,27.8979,0.8189,-9.2030,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWWILKES2,CSWSWILKESUN2_RA,27.8979,0.8189,-9.2030,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,CSWWILKES3,CSWSWILKESUN3_RA,27.7414,0.7206,-9.2612,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-10.2996,-1.3890,-45.1926,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,DENL,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,DERS,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,DOE,DOE,24.0696,-0.4257,-11.7867,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,15.5692,-2.3986,-18.3142,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,DPC,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,DUK,VACS,24.8917,-0.0817,-11.3085,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDDY,EDDY,144.5180,7.0346,101.2014,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,33.0474,-1.8321,-1.4025,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,-12.9900,-1.9622,-47.3098,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,39.1431,-2.1703,5.0315,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE.SLCC,EDESTL4391_PLT,34.0746,-1.7784,-0.4290,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,34.0034,-1.6703,-0.6083,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,24.8936,-2.1954,-9.1929,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_EC_01,EDELAR3821UN1_RA,33.0474,-1.8321,-1.4025,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_EC_02,EDELAR3821UN2_RA,33.0113,-1.8682,-1.4025,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_EC_03,EDELAR3821UN3_RA,33.0474,-1.8321,-1.4025,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_EC_04,EDELAR3821UN4_RA,33.0474,-1.8321,-1.4025,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_EDE,EDE_LA,33.1080,-0.9003,-2.2737,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_ERW,EDEERWFUNG1_RA,-4.0676,-2.7612,-37.5884,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,8.2217,-2.9567,-25.1036,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,64.9700,-0.0911,28.7791,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,64.9700,-0.0911,28.7791,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,64.9700,-0.0911,28.7791,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,64.9700,-0.0911,28.7791,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,25.4251,-0.0480,-10.8088,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_RIV_10,EDERIV1671UN10_RA,33.9488,-1.8821,-0.4511,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_RIV_11,EDERIV1671UN11_RA,33.9488,-1.8821,-0.4511,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_RIV_12,EDERIV453UN12_PLT,33.0945,-2.7364,-0.4511,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_SL_01,EDESTL4391UN1_RA,33.6008,-2.2522,-0.4290,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EDE_SWMP,EDE_SWMP_LA,32.7157,-0.6402,-2.9261,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EEI,EEI,24.0550,-0.4303,-11.7967,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,EES,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,6.2407,-2.7316,-27.3097,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,ERCOTE,ERCOTE,27.3948,0.3371,-9.2243,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,ERCOTN,ERCOTN,26.1358,-1.3298,-8.8164,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,12.0700,-2.4288,-21.7832,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FMPP,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FPC,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FPL,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FREM_50T,OPPDFREM_GUN1_RA,13.3785,-1.6355,-21.2680,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FREM_6,OPPDFREM_AUN6_RA,13.3647,-1.6444,-21.2729,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FREM_7,OPPDFREM_AUN7_RA,13.3647,-1.6444,-21.2729,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FREM_8,OPPDFREM_AUN8_RA,13.2237,-1.7854,-21.2729,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FREM_LOAD,FREM_LOAD_LA,13.3420,-1.6671,-21.2729,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,FRONTIER,WRGETTUNFRONTIER_RA,2.1000,-2.2454,-31.9366,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,27.6278,0.7622,-9.4164,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,55.0641,-1.0697,19.8518,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,-0.6241,-3.0599,-33.8462,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,32.5983,-0.6829,-3.0008,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,32.5983,-0.6829,-3.0008,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,32.5983,-0.6829,-3.0008,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,33.0948,-0.9352,-2.2520,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,33.0948,-0.9352,-2.2520,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,33.1276,-0.9446,-2.2098,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,33.1276,-0.9446,-2.2098,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,0.0864,-3.1145,-33.0811,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,26.9390,-1.2957,-8.0473,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,26.9390,-1.2957,-8.0473,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,26.9390,-1.2957,-8.0473,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.VOLT.0130,V130_DDR,33.6838,-0.5458,-2.0524,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA.VOLT.0237,V237_DDR,33.4463,-0.7855,-2.0502,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDAHUB2,GRDAHUB2_H,24.2304,-1.4969,-10.5546,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDAHUB3,GRDAHUB3_H,21.5271,-1.6620,-13.0929,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA_GRDA,GRDA_LA,32.7164,-0.7815,-2.7840,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA_HUB,GRDA_H,28.1040,-1.2550,-6.9229,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRDA_HUBSA,GRDASA_H,27.9371,-1.3133,-7.0316,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GRE,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,8.0319,3.4825,-31.7325,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,GSEC_SPS,SPS_GSEC_LA,114.8878,3.4743,75.1315,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,GSPR2014HUB,GSPR2014HUB_H,93.9650,2.7239,54.9592,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,GSPR2015HUB,GSPR2015HUB_H,91.1086,2.5256,52.3011,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,42.5099,1.0833,5.1446,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,HARRISON,CSWSLEBROCKPLT1,27.3353,0.4015,-9.3482,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,HAST_TNSK_HUB,HAST_TNSK_H,13.1963,-1.6563,-21.4294,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,HQST,PJM,21.9259,-0.7638,-13.5922,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,HST,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,30.3292,-1.3925,-4.5603,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,30.3292,-1.3925,-4.5603,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,29.6602,-1.4304,-5.1913,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,29.6602,-1.4304,-5.1913,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,30.9945,-1.3888,-3.8986,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,30.9945,-1.3888,-3.8986,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,INDN_INDN,INDN_LA,30.1609,-1.4057,-4.7154,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,0.0000,-3.1084,-33.1736,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,ISNE,PJM,21.9259,-0.7638,-13.5922,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,JEA,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,13.5512,-1.7089,-21.0219,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,13.5512,-1.7089,-21.0219,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,10.9682,-2.0844,-23.2294,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KACYCT4,KACYNEARMANUNCT4_RA,19.4715,-1.9715,-14.8390,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,68.8800,-2.0689,34.6669,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,19.4715,-1.9715,-14.8390,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,19.4250,-1.8760,-14.9810,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,19.4367,-1.9040,-14.9413,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KACY_KACY,KACY_LA,19.4276,-1.8377,-15.0167,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,18.3302,-2.0350,-15.9168,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,28.9643,-1.9392,-5.3785,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,-16.8145,-2.8221,-50.2744,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,-8.3975,-3.2930,-41.3865,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.VOLT.0222,V222_DDR,14.0049,-1.9006,-20.3765,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.VOLT.0223,V223_DDR,15.8637,-2.2345,-18.1838,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.VOLT.0241,V241_DDR,27.4000,-0.7223,-8.1597,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.VOLT.0243,V243_DDR,29.9862,-1.4081,-4.8877,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.VOLT.0247,V247_DDR,20.8742,-2.0378,-13.3700,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.VOLT.0253,V253_DDR,18.5988,-1.9196,-15.7635,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,9.3800,-3.7170,-23.1850,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,14.1476,-2.4995,-19.6349,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,14.1476,-2.4995,-19.6349,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,14.1476,-2.4995,-19.6349,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,14.1476,-2.4995,-19.6349,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,18.4114,-1.9404,-15.9302,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,18.4114,-1.9404,-15.9302,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHUB,KCPLHUB_H,10.8535,-2.7189,-22.7097,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHUB17,KCPLHUB17_H,9.8683,-2.7398,-23.6739,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHUB18,KCPLHUB18_H,9.7087,-2.7854,-23.7879,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHUB19,KCPLHUB19_H,9.5522,-2.7351,-23.9947,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHUB20,KCPLHUB20_H,8.9805,-2.7833,-24.5181,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHUB21,KCPLHUB21_H,9.2166,-2.7025,-24.3629,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHUB22,KCPLHUB22_H,9.7897,-2.7314,-23.7608,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHUB23,KCPLHUB23_H,9.1478,-2.7844,-24.3498,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLHUB24,KCPLHUB24_H,8.7707,-2.8251,-24.6862,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,12.8636,-2.2354,-21.1829,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,12.8636,-2.2354,-21.1829,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,15.5942,-2.6759,-18.0119,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,15.5942,-2.6759,-18.0119,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,17.8747,-2.4905,-15.9168,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,18.3302,-2.0350,-15.9168,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,18.7112,-1.8430,-15.7277,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,18.7112,-1.8430,-15.7277,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,18.7112,-1.8430,-15.7277,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,18.7112,-1.8430,-15.7277,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,18.7112,-1.8430,-15.7277,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,18.7112,-1.8430,-15.7277,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,18.7112,-1.8430,-15.7277,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,18.7112,-1.8430,-15.7277,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,5.9216,-2.5120,-27.8483,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,19.3927,-1.8435,-15.0457,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KCPL_KCPL,KCPL_LA,18.1657,-1.9221,-16.1942,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KENN,KENN_LA,25.4281,-0.1278,-10.7261,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KEP2_SECI,KEP2_SECI_LA,5.7947,-0.1103,-30.3770,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KERR_1,GRDAKERR_HYDUN1_RA,33.3271,-0.8631,-2.0918,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KERR_2,GRDAKERR_HYDUN2_RA,33.3512,-0.8458,-2.0849,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KERR_3,GRDAKERR_HYDUN3_RA,33.3512,-0.8458,-2.0849,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KERR_4,GRDAKERR_HYDUN4_RA,33.3271,-0.8631,-2.0918,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,14.1796,-2.4675,-19.6349,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,14.1796,-2.4675,-19.6349,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,14.7975,-2.2936,-19.1909,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,14.7975,-2.2936,-19.1909,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,10.5618,-2.4721,-23.2482,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,9.4880,-2.4216,-24.3723,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,9.4880,-2.4216,-24.3723,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,6.1126,-0.4154,-29.7540,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,6.1126,-0.4154,-29.7540,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,6.1126,-0.4154,-29.7540,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,7.5141,-2.1045,-26.6634,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,7.5141,-2.1045,-26.6634,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,6.0200,-0.4931,-29.7688,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,7.3413,-1.8567,-27.0840,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,9.0384,-2.5710,-24.6726,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,60.8285,-2.0398,26.5863,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,60.8285,-2.0398,26.5863,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,11.2595,-2.3837,-22.6387,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,11.2595,-2.3837,-22.6387,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,11.2595,-2.3837,-22.6387,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,7.5689,-1.5256,-27.1875,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,1.5277,-3.6214,-31.1329,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,13.3062,-2.4992,-20.4766,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,11.1006,-2.0027,-23.1787,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,LAFA,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,LAM345,LAM345,5.4419,-0.9473,-29.8928,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,LEPA,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,14.6001,-1.6532,-20.0287,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_LES,LES_LA,14.4975,-1.6978,-20.0868,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,14.3181,-1.8278,-20.1361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,14.3801,-1.7777,-20.1241,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,14.3801,-1.7777,-20.1241,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,14.3801,-1.7777,-20.1241,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,14.3193,-1.8266,-20.1361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,14.3181,-1.8278,-20.1361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_WAVERLY,LES_WAVERLY_H,14.2057,-1.8549,-20.2214,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,13.4961,-1.9857,-20.8002,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,13.4961,-1.9857,-20.8002,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,LGEE,LGEE,22.9297,-0.5924,-12.7598,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MALDEN,MALDEN_LA,25.2625,-0.1759,-10.8436,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MCWEST,MCWEST,44.4961,1.8272,6.3869,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MDU,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,12.2108,0.8899,-24.9610,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,13.1371,-1.6483,-21.4966,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,15.0527,-0.3305,-20.8988,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MEAN_NPPD,NPPD_MEAN_LA,11.8112,-1.8019,-22.6689,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MEC,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,MHEB,MHEB,21.4882,0.0297,-14.8235,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,4.9129,-2.6838,-28.6853,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,7.4359,-1.6068,-27.2392,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,4.9129,-2.6838,-28.6853,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,4.9129,-2.6838,-28.6853,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,7.4359,-1.6068,-27.2392,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,2.1909,-2.0404,-32.0507,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MISO,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,6.0507,0.5033,-30.7346,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,6.0507,0.5033,-30.7346,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,9.7522,-2.5348,-23.9949,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,5.2031,-1.9862,-29.0927,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,7.1464,-2.3286,-26.8070,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,3.1768,-4.1376,-28.9676,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,5.0491,-2.8329,-28.4000,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,3.5782,-3.7664,-28.9374,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,6.1977,-2.0194,-28.0649,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,6.1977,-2.0194,-28.0649,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,6.1977,-2.0194,-28.0649,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,6.1977,-2.0194,-28.0649,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,6.1977,-2.0194,-28.0649,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,20.8571,-1.6223,-13.8026,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,24.1174,-0.6015,-11.5630,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,24.1174,-0.6015,-11.5630,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,22.6449,-0.9196,-12.7175,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,26.3050,-0.5738,-9.4031,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MOWR,AECI,26.8474,-0.9294,-8.5053,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,24.3762,-1.1882,-10.7175,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,24.4344,-0.6047,-11.2429,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,8.6241,-3.2845,-24.3733,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,6.3543,-2.6786,-27.2490,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,3.7138,-2.8830,-29.6852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,8.7436,-3.1651,-24.3733,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,15.5854,-2.3823,-18.3142,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,15.5854,-2.3823,-18.3142,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,15.5895,-2.3783,-18.3142,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,15.5895,-2.3783,-18.3142,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,14.0049,-1.9006,-20.3765,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,14.0049,-1.9006,-20.3765,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,14.0049,-1.9006,-20.3765,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,13.8972,-2.0083,-20.3765,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,14.0049,-1.9006,-20.3765,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,14.0049,-1.9006,-20.3765,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,14.0049,-1.9006,-20.3765,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,25.6267,-0.8770,-9.7783,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,17.5584,-2.4800,-16.2436,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,14.6671,-2.9074,-18.7075,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,14.5703,-3.0042,-18.7075,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,14.6672,-2.9073,-18.7075,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,19.2268,-1.8360,-15.2192,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,19.2268,-1.8360,-15.2192,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MPS_MPS,MPS_LA,21.5628,-1.7045,-13.0147,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MSTNG,SPSMSTNGPLT1,141.9321,5.5743,100.0758,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MSTNG4,SPSMSTNGUN4_RA,141.7329,5.3751,100.0758,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MSTNG5,SPSMSTNGUN5_RA,141.7342,5.3764,100.0758,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,141.9321,5.5743,100.0758,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NBSO,PJM,21.9259,-0.7638,-13.5922,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,12.1227,-2.6232,-21.5361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,12.1201,-2.6258,-21.5361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,44.4453,-1.7670,9.9303,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NHC1,VACS,24.8917,-0.0817,-11.3085,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,13.4495,-1.7948,-21.0377,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,13.4495,-1.7948,-21.0377,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,13.4495,-1.7948,-21.0377,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,10.7518,-0.5727,-24.9575,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,12.1135,-2.4265,-21.7420,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,13.2254,-2.1326,-20.9239,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,8.2643,-2.0297,-25.9879,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,12.1135,-2.4265,-21.7420,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.HUB.PY2018,NPPDPY18_H,11.8303,-1.9077,-22.5440,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,11.8768,-1.9463,-22.4589,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,11.8820,-1.9081,-22.4920,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,11.9349,-1.9253,-22.4218,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,6.4884,-1.9840,-27.8096,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,12.0812,-0.8229,-23.3779,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,12.0812,-0.8229,-23.3779,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,9.7889,-2.0656,-24.4275,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,6.4884,-1.9840,-27.8096,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,15.7930,-2.7176,-17.7714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,11.7290,-2.2767,-22.2763,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,10.8016,-0.5141,-24.9663,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,11.7290,-2.2767,-22.2763,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,12.5382,-2.1223,-21.6215,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,11.7984,-1.7645,-22.7191,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,14.4231,-1.3239,-20.5350,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,12.1135,-2.4265,-21.7420,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,10.9340,-0.6601,-24.6878,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,12.0812,-0.8229,-23.3779,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,12.0812,-0.8229,-23.3779,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,12.5035,-0.8450,-22.9334,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,12.4777,-0.8267,-22.9776,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,12.4777,-0.8267,-22.9776,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,12.6819,-0.9172,-22.6829,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,9.6448,-1.6961,-24.9411,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,12.6703,-1.9729,-21.6388,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,10.9388,-0.2942,-25.0490,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,8.4080,-1.5480,-26.3260,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,7.3651,-1.5104,-27.4065,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.NELI.DDR,NELI_DDR,7.1850,-2.2217,-26.8753,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.NPPM.1058,SH1058_DDR,23.4799,-1.0935,-11.7086,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,12.4926,-1.1821,-22.6073,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,12.1135,-2.4265,-21.7420,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,13.2254,-2.1326,-20.9239,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,6.4884,-1.9840,-27.8096,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.TECH.1,KEARNE_DDR,13.2833,-0.6387,-22.3600,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,11.8992,-2.8657,-21.5171,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,11.8992,-2.8657,-21.5171,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,6.3132,-2.1813,-27.7875,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD.VOLT.0236,V236_DDR,13.8378,-1.5966,-20.8476,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD2017HUB,NPPD2017HUB_H,11.8478,-1.9112,-22.5229,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,21.2121,-1.9125,-13.1574,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,10.7518,-0.5727,-24.9575,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,11.3009,-2.8179,-22.1632,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,11.3009,-2.8179,-22.1632,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,13.8629,-1.6456,-20.7735,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,13.8587,-1.5757,-20.8476,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,8.1526,-2.0683,-26.0611,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,12.4817,-0.9409,-22.8594,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,22.7903,-1.7831,-11.7086,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,22.7903,-1.7831,-11.7086,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,22.7903,-1.7831,-11.7086,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,13.2053,-1.6510,-21.4257,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,12.6809,-2.6773,-20.9238,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,13.3896,-1.4226,-21.4698,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,6.8044,-3.8248,-25.6528,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,6.9851,-3.6441,-25.6528,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,11.2835,-1.0761,-23.9224,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,11.1487,-1.1042,-24.0290,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,14.0347,-1.4538,-20.7935,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,14.0038,-1.4847,-20.7935,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,14.0038,-1.4847,-20.7935,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,14.0158,-1.4227,-20.8435,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,15.7930,-2.7176,-17.7714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,13.9558,-1.4230,-20.9032,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,13.9325,-1.9176,-20.4319,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,13.2710,-1.5767,-21.4343,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,13.2529,-1.5930,-21.4360,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,13.2668,-1.5781,-21.4371,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,13.2668,-1.5781,-21.4371,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,13.2053,-1.6510,-21.4257,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,13.1332,-1.7231,-21.4257,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,11.8835,0.4803,-24.8788,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,13.6846,-1.4169,-21.1805,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,11.1433,-0.9775,-24.1612,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,10.4676,-2.7247,-23.0897,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,10.5917,-0.6614,-25.0289,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,23.9389,-0.6345,-11.7086,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,7.1850,-2.2217,-26.8753,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,11.4872,-1.0115,-23.7833,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,11.4872,-1.0115,-23.7833,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_NPPD,NPPD_LA,15.0880,-1.3551,-19.8389,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,13.9325,-1.9176,-20.4319,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,13.9325,-1.9176,-20.4319,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,12.1783,-2.4855,-21.6182,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,12.4746,-1.7429,-22.0645,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NSB,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,NSP,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,NSSO,PJM,21.9259,-0.7638,-13.5922,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,NYIS,PJM,21.9259,-0.7638,-13.5922,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,7.3369,-1.7417,-27.2034,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,2.1897,-2.9328,-31.1595,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,2.6789,-2.7803,-30.8228,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,2.6789,-2.7803,-30.8228,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,2.6621,-1.2126,-32.4073,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,-0.6241,-3.0599,-33.8462,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,-26.3579,-2.3854,-60.2545,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,-7.7788,-3.1745,-40.8863,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,0.1217,-3.0958,-33.0645,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,1.5297,-3.0050,-31.7473,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,11.7838,-1.8280,-22.6702,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,0.1217,-3.0958,-33.0645,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,3.9888,-1.3759,-30.9172,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,2.1909,-2.0404,-32.0507,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,8.9087,-1.9383,-25.4350,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,40.7875,-0.7783,5.2838,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,1.5297,-3.0050,-31.7473,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,4.9929,-2.6111,-28.6780,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,8.5723,-2.8459,-24.8637,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,7.6068,-2.2070,-26.4682,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,-8.3588,-0.8632,-43.7776,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,2.1909,-2.0404,-32.0507,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,2.1909,-2.0404,-32.0507,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,1.5297,-3.0050,-31.7473,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.NUEN.ADA1,ADA1_DDR,9.9938,-1.7729,-24.5153,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.NUEN.LAM1,LAM1_DDR,30.5313,1.0288,-6.7795,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.NUEN.MDT2,MDT2_DDR,11.7882,-1.8236,-22.6702,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.NUEN.MDT3,MDT3_DDR,11.7882,-1.8236,-22.6702,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.NUEN.WWO1,WWO1_DDR,10.1805,-1.6774,-24.4241,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,11.5683,-1.9106,-22.8031,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,11.5683,-1.9106,-22.8031,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,11.6416,-1.8373,-22.8031,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,11.5691,-1.9870,-22.7259,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,11.5691,-1.9870,-22.7259,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,11.6416,-1.8373,-22.8031,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,11.6416,-1.8373,-22.8031,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,1.5297,-3.0050,-31.7473,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,26.5805,0.2370,-9.9385,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,3.9888,-1.3759,-30.9172,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,-0.3710,-0.8986,-35.7544,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,4.9929,-2.6111,-28.6780,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,28.6199,0.4147,-8.0768,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,7.3554,-2.4853,-26.4413,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,7.3554,-2.4853,-26.4413,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,7.3656,-2.4751,-26.4413,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,7.3656,-2.4751,-26.4413,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,0.5313,-3.7216,-32.0291,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,1.7836,-2.8279,-31.6705,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,2.1897,-2.9328,-31.1595,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,0.4206,-2.8396,-33.0218,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,0.4206,-2.8396,-33.0218,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,5.4000,-0.4954,-30.3866,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,7.5210,-2.2843,-26.4767,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,7.5210,-2.2843,-26.4767,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,7.5210,-2.2843,-26.4767,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0033,FOSTER_DDR,12.9047,-1.5254,-21.8519,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,21.6489,-0.3207,-14.3124,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0035,TARBY_DDR,30.0666,0.5371,-6.7525,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,21.6489,-0.3207,-14.3124,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,20.3912,-0.7225,-15.1683,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,20.3912,-0.7225,-15.1683,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,-3.8361,-0.5556,-39.5625,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0040,TROSPER_DDR,12.9832,-1.5089,-21.7899,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,12.7137,-1.5243,-22.0440,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,29.2921,0.5559,-7.5458,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0115,V115_DDR,11.8909,-1.7772,-22.6139,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0116,V116_DDR,67.8200,-0.2679,31.8059,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0118,V118_DDR,24.1564,-0.8929,-11.2327,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0125,V125_DDR,29.8955,0.7732,-7.1597,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0126,V126_DDR,29.8741,-0.2723,-6.1355,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0129,V129_DDR,25.8311,-1.7894,-8.6615,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,12.3173,-1.6667,-22.2980,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0134,V134_DDR,30.8631,-0.0496,-5.3692,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0138,V138_DDR,29.2930,-0.4001,-6.5889,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,12.4385,-1.5498,-22.2937,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0143,V143_DDR,23.9413,-0.6677,-11.6730,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0149,V149_DDR,10.8666,-2.0312,-23.3842,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0150,V150_DDR,11.2544,-1.9728,-23.0548,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0155,V155_DDR,28.8037,-0.5463,-6.9319,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0156,V156_DDR,12.3173,-1.6667,-22.2980,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0166,V166_DDR,30.4403,0.6695,-6.5111,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,12.4467,-1.5593,-22.2760,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,11.2544,-1.9728,-23.0548,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0170,V170_DDR,10.0511,-1.6774,-24.5535,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,10.7448,-2.1014,-23.4358,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0176,V176_DDR,11.2544,-1.9728,-23.0548,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0177,V177_DDR,4.5245,-2.4936,-29.2639,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,12.4824,-1.5587,-22.2409,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,9.2025,-2.2001,-24.8794,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0195,V195_DDR,95.9180,1.7400,57.8960,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0197,V197_DDR,28.3097,-0.1885,-7.7838,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0198,V198_DDR,30.4403,0.6695,-6.5111,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0208,V208_DDR,96.0000,1.8120,57.9060,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0209,V209_DDR,96.0000,1.8120,57.9060,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,28.6269,-0.5048,-7.1503,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0216,V216_DDR,12.6442,-1.5298,-22.1080,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0219,V219_DDR,28.8037,-0.5463,-6.9319,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0220,V220_DDR,11.2544,-1.9728,-23.0548,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0224,V224_DDR,11.8080,-1.7464,-22.7276,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0225,V225_DDR,11.8099,-1.7445,-22.7276,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0226,V226_DDR,11.8080,-1.7464,-22.7276,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0227,V227_DDR,11.8080,-1.7464,-22.7276,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0229,V229_DDR,-1.3108,-0.3798,-37.2130,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0231,V231_DDR,27.0293,-0.3884,-8.8643,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0238,V238_DDR,0.8100,-3.0450,-32.4270,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.VOLT.0242,V242_DDR,29.0136,-0.4749,-6.7935,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,4.4725,-3.0678,-28.7416,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,2.1909,-2.0404,-32.0507,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,2.8788,-2.8183,-30.5849,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,8.9087,-1.9383,-25.4350,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,4.4725,-3.0678,-28.7416,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,9.3883,-1.6901,-25.2036,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,-11.1341,-4.4712,-42.9449,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEHL7,OKGEHL7_H,14.5777,-1.6281,-20.0762,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEHL8,OKGEHSL1UN8_RA,14.5777,-1.6281,-20.0762,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEHL910,OKGEHSL1PLT2,14.1333,-2.0725,-20.0762,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,9.0064,-1.9104,-25.3651,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEMCC,OKGEMCCLAIPLT1,11.5015,-2.0691,-22.7114,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,27.2827,-0.7043,-8.2950,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,27.2827,-0.7043,-8.2950,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,27.2401,-0.7469,-8.2950,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,13.2542,-2.1717,-20.8561,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,13.2542,-2.1717,-20.8561,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,13.2542,-2.1717,-20.8561,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,13.3751,-2.0508,-20.8561,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGESM1,OKGESEMINOLEUN1_RA,20.3040,-1.4392,-14.5388,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGESM2,OKGESEMINOLEUN2_RA,16.8028,-1.4221,-18.0571,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGESM3,OKGESEMINOLEUN3_RA,16.8028,-1.4221,-18.0571,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGESO1,OKGESONR1UN1_RA,-8.3483,-2.7082,-41.9220,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGESO2,OKGESONR1UN2_RA,0.4206,-2.8396,-33.0218,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,8.8712,-2.0457,-25.3651,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,7.4789,-2.5987,-26.2044,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGETINK5A,OKGETINK5UN1_RA,13.4172,-1.5024,-21.3624,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGETINK5B,OKGETINK5UN2_RA,13.4172,-1.5024,-21.3624,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,8.1089,-2.2633,-25.9098,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,2.1897,-2.9328,-31.1595,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,29.0660,0.5922,-7.8082,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,2.1909,-2.0404,-32.0507,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE_OKGE,OKGE_LA,22.9408,-1.0912,-12.2500,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,-0.3710,-0.8986,-35.7544,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,7.9576,-2.4145,-25.9098,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMLP,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,30.1716,-0.8996,-5.2108,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,28.8016,0.1966,-7.6770,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_GENHUB,OMPA_GENHUB_H,10.6981,-1.9071,-23.6768,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,-26.2586,-2.2861,-60.2545,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,8.3031,-2.4575,-25.5214,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,0.1217,-3.0958,-33.0645,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,5.7964,-2.2956,-28.1899,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,18.0280,-2.3718,-15.8822,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,88.0000,-1.1716,52.8896,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,-26.3822,-2.4097,-60.2545,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,-26.3822,-2.4097,-60.2545,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_SPP,OMPA_SPP_LA,13.0798,-1.8037,-21.3984,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,4.4725,-3.0678,-28.7416,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,29.6374,-0.9540,-5.6906,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,29.6374,-0.9540,-5.6906,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,29.6374,-0.9540,-5.6906,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,29.6374,-0.9540,-5.6906,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,ONT,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,13.3561,-1.7990,-21.1269,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,13.3561,-1.7990,-21.1269,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,13.3561,-1.7990,-21.1269,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,13.3561,-1.7990,-21.1269,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,13.3561,-1.7990,-21.1269,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,13.3561,-1.7990,-21.1269,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,13.3561,-1.7990,-21.1269,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,13.3561,-1.7990,-21.1269,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,13.3561,-1.7990,-21.1269,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,13.4840,-1.7553,-21.0426,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,13.4495,-1.7948,-21.0377,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,13.8392,-1.4812,-20.9616,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,13.6165,-1.6785,-20.9869,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,13.6165,-1.6785,-20.9869,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD_GLDN,OPPD_GLDN_LA,13.4899,-1.7678,-21.0243,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,13.4291,-1.7682,-21.0847,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,15.7930,-2.7176,-17.7714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,12.8679,-2.2717,-21.1424,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,13.4522,-1.7917,-21.0381,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD_OPPD,OPPD_LA,13.5442,-1.6935,-21.0443,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,13.6389,-1.6438,-20.9992,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,13.6341,-1.6533,-20.9945,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,OTP,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,OVEC,OVEC,22.5512,-0.6602,-13.0706,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PARAGOULD,PARAGOULD_LA,25.7147,-0.0544,-10.5129,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,33.7834,-1.1630,-1.3356,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,33.7834,-1.1630,-1.3356,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,33.7834,-1.1630,-1.3356,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,33.6240,-1.0220,-1.6360,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,33.6240,-1.0220,-1.6360,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,33.6240,-1.0220,-1.6360,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PIGGOTT,PIGGOTT_LA,25.3690,-0.1449,-10.7681,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PJM,PJM,21.9259,-0.7638,-13.5922,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,PLUM,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,POPLARBLUFF,POPLARBLUFF_LA,25.3493,-0.3362,-10.5965,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,44.6635,1.4819,6.8996,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,44.6635,1.4819,6.8996,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,43.5821,1.5308,5.7694,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,43.5821,1.5308,5.7694,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,44.1382,3.0196,4.8367,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,44.1382,3.0196,4.8367,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,44.3954,1.8526,6.2608,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,49.1724,0.9906,11.8998,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,-5.1755,-2.6919,-38.7655,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,52.3015,-1.0166,17.0361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,14.8805,-1.7375,-19.6640,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,12.1444,-0.9892,-23.1484,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,32.8132,-0.1755,-3.2933,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,31.7425,-0.5477,-3.9918,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,14.7751,-1.8318,-19.6751,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,39.6257,1.2720,2.0718,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,13.3921,-2.2466,-20.6433,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,42.3636,2.8695,3.2122,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,24.9726,0.6915,-12.0009,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,14.6526,-1.4914,-20.1380,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,PUPP,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,RCEAST,RCEAST,8.5823,0.3519,-28.0516,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SALINA_1,GRDASALINA1UN1_RA,33.3306,-0.8595,-2.0918,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SALINA_2,GRDASALINA1UN2_RA,33.3306,-0.8595,-2.0918,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SALINA_3,GRDASALINA1UN3_RA,33.3306,-0.8595,-2.0918,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SALINA_4,GRDASALINA1UN4_RA,33.3306,-0.8595,-2.0918,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SALINA_5,GRDASALINA1UN5_RA,33.3306,-0.8595,-2.0918,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SALINA_6,GRDASALINA1UN6_RA,33.3306,-0.8595,-2.0918,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SARPY_1,OPPDSARPYUN1_RA,13.4837,-1.7873,-21.0110,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SARPY_2,OPPDSARPYUN2_RA,13.5568,-1.7239,-21.0012,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SARPY_3,OPPDSARPYUN3_RA,13.4443,-1.8474,-20.9903,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SARPY_4,OPPDSARPYUN4_RA,13.4443,-1.8474,-20.9903,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SARPY_5,OPPDSARPYUN5_RA,13.4443,-1.8474,-20.9903,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SC,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SCEG,VACS,24.8917,-0.0817,-11.3085,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SCSE,SCSE,11.6093,-0.2907,-24.3819,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SEC,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,5.1045,-2.2583,-28.9192,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,5.1045,-2.2583,-28.9192,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,5.1045,-2.2583,-28.9192,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,6.8275,0.6975,-30.1520,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,5.1045,-2.2583,-28.9192,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,5.3233,-1.5021,-29.4566,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,5.7060,-2.0155,-28.5605,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,5.7060,-2.0155,-28.5605,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,6.1937,-2.0234,-28.0649,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,5.0366,-2.4867,-28.7587,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,7.3806,-2.2380,-26.6634,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,6.1903,0.3268,-30.4184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,8.0345,-0.6236,-27.6239,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,5.1484,-2.1664,-28.9671,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,8.0154,-0.7171,-27.5494,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,4.7565,-1.9595,-29.5660,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,6.1255,-1.0646,-29.0919,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,5.9172,-0.5751,-29.7897,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,5.9172,-0.5751,-29.7897,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,5.9172,-0.5751,-29.7897,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,5.9172,-0.5751,-29.7897,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,5.6360,-0.7584,-29.8876,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,5.3233,-1.5021,-29.4566,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI_SECI,SECI_LA,6.0965,-0.6497,-29.5357,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,0.0000,-3.1084,-33.1736,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,0.0000,-3.1084,-33.1736,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,6.1937,-2.0234,-28.0649,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SEHA,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,7.9576,-2.4145,-25.9098,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SERU,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SETH,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SGE,SGE,11.1827,-0.1954,-24.9038,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SMEP,MISO,22.0641,-0.4949,-13.7231,36.2821\n03/20/2025 00:00:00,03/20/2025 05:00:00,SOCO,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPA,SPA,29.0668,-0.2034,-7.0118,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPC,SPC,38.1093,1.2725,0.5549,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPPNORTH_HUB,SPPNORTH_H,14.1942,-1.5260,-20.5617,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPPSOUTH_HUB,SPPSOUTH_H,17.9887,-1.6898,-16.6035,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,30.2220,-0.7231,-5.3369,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,30.2306,-0.7145,-5.3369,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,29.9881,-0.6374,-5.6565,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,29.9881,-0.6374,-5.6565,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_NIXA,SPRM_NIXA_LA,30.5376,-0.5355,-5.2089,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_SPRM,SPRM_LA,30.5055,-0.4667,-5.3098,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,30.3723,-0.7129,-5.1968,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,30.3723,-0.7129,-5.1968,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,30.3026,-0.7826,-5.1968,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,30.3829,-0.7023,-5.1968,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,144.5859,4.8948,103.4091,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,149.5147,4.0694,109.1634,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,46.8467,0.1390,10.4257,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,46.8467,0.1390,10.4257,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,141.3725,3.6794,101.4111,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,142.7886,5.2716,101.2351,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,144.3276,4.0723,103.9733,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,144.9440,6.8766,101.7854,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,139.1947,3.4477,99.4650,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,142.2427,5.5061,100.4546,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,142.7865,6.0168,100.4877,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,142.7865,6.0168,100.4877,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,142.2427,5.5061,100.4546,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,46.9237,0.2618,10.3799,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,149.5147,4.0694,109.1634,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,48.5400,0.8886,11.3694,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,53.6327,-0.6948,18.0455,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,51.5927,1.1733,14.1375,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,50.3490,1.9224,12.1446,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,49.6519,0.9675,12.4024,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,59.0711,-1.0033,23.7924,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,59.0711,-1.0033,23.7924,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,59.0711,-1.0033,23.7924,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,59.0711,-1.0033,23.7924,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GRID.WRAB,WRAB_DDR,46.8030,2.1937,8.3274,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,59.0711,-1.0033,23.7924,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,137.8864,3.5174,98.0870,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,137.8864,3.5174,98.0870,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,134.7242,3.5387,94.9035,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,134.7242,3.5387,94.9035,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,134.7242,3.5387,94.9035,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,137.8864,3.5174,98.0870,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,44.3524,0.5065,7.5639,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,44.3508,0.5066,7.5623,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,44.3562,0.5066,7.5677,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,44.4453,-1.7670,9.9303,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,142.2995,5.5825,100.4350,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,139.1217,3.3991,99.4407,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,139.1217,3.3991,99.4407,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,139.1217,3.3991,99.4407,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,139.1217,3.3991,99.4407,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,142.1980,5.6159,100.3001,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,142.1433,5.4161,100.4453,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,142.1433,5.4161,100.4453,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,8.1368,-2.2354,-25.9098,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,44.3767,0.3826,7.7121,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,44.3767,0.3826,7.7121,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,44.3444,0.5048,7.5577,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,46.8030,2.1937,8.3274,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,53.8437,-0.0358,17.5975,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,48.3232,0.3574,11.6838,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,2.6621,-1.2126,-32.4073,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,44.8231,0.8290,7.7121,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.PLANTX1,SPS.PLANTX1_H,146.2780,4.4991,105.4969,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.PLANTX2,SPS.PLANTX2_H,146.2780,4.4991,105.4969,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,145.8784,4.4692,105.1272,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,141.0822,3.8395,100.9607,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,56.4651,-0.5580,20.7411,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,144.9901,4.7348,103.9733,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,141.2230,3.9803,100.9607,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,46.9943,0.3324,10.3799,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,144.6351,5.4577,102.8954,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,144.9440,6.8766,101.7854,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,144.6351,5.4577,102.8954,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,145.2339,6.1502,102.8017,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,49.3691,0.4458,12.6413,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,145.3704,8.4733,100.6152,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,145.5402,8.6431,100.6152,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,144.9541,8.1147,100.5574,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,142.6641,5.9387,100.4434,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,145.3895,8.2121,100.8954,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,5.4419,-0.9473,-29.8928,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,46.6249,2.0614,8.2815,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,145.0555,4.7474,104.0261,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,145.0555,4.7474,104.0261,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,144.6351,5.4577,102.8954,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,139.4631,3.6412,99.5399,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,143.3465,6.8627,100.2018,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,147.2734,6.9685,104.0229,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,145.8463,5.5460,104.0184,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,146.1558,3.3018,106.5721,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,145.3704,8.4733,100.6152,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,146.4348,9.3804,100.7724,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,145.8229,8.7685,100.7724,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,141.5066,4.2639,100.9607,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,146.3361,6.0765,103.9776,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,56.0165,-0.3083,20.0428,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,55.9350,-0.3740,20.0270,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0163,V163_DDR,46.7782,1.2830,9.2132,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0168,V168_DDR,47.6539,-0.5384,11.9103,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0180,V180_DDR,146.4348,9.3804,100.7724,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0181,V181_DDR,56.6199,-0.1052,20.4431,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0182,V182_DDR,145.4292,8.2946,100.8526,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0199,V199_DDR,143.0012,6.5224,100.1968,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0200,V200_DDR,143.5166,6.7124,100.5222,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.VOLT.0235,V235_DDR,53.8437,-0.0358,17.5975,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,144.3276,4.0723,103.9733,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,144.9440,6.8766,101.7854,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,42.4896,1.0630,5.1446,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,43.4222,0.9189,6.2213,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS_SPS,SPS_LA,120.2236,5.6152,78.3265,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,144.2617,5.1280,102.8517,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SSCN_NPPD,SSCN_NPPD_LA,9.3791,-1.9194,-24.9835,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,24.7561,-0.3252,-11.2007,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,24.7561,-0.3252,-11.2007,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,TAL,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,TEC,SOUC,25.0661,-0.0055,-11.2104,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,10.4676,-2.7247,-23.0897,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,TVA,TVA,24.7075,-0.1619,-11.4126,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,UCUHUB,UCUHUB_H,11.7248,-2.2729,-22.2843,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,UCUHUB17,UCUHUB17_H,8.1082,-2.2486,-25.9252,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,UCUHUB18,UCUHUB18_H,9.2501,-2.4672,-24.5647,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,UCUHUB19,UCUHUB19_H,6.4127,-2.4844,-27.3849,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,UCUHUB20,UCUHUB20_H,6.0570,-2.3998,-27.8252,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,UCUHUB21,UCUHUB21_H,6.0229,-2.3516,-27.9075,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,UCUHUB22,UCUHUB22_H,6.2321,-2.4562,-27.5937,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,UCUHUB23,UCUHUB23_H,5.9376,-2.4661,-27.8783,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,UCUHUB24,UCUHUB24_H,7.4468,-2.2959,-26.5392,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,39.4916,1.7412,1.4684,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,39.4916,1.7412,1.4684,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,14.4853,-0.5474,-21.2493,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,14.4853,-0.5474,-21.2493,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,22.8418,-0.5192,-12.9210,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,42.1357,0.5766,5.2772,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,42.1357,0.5766,5.2772,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,39.4916,1.7412,1.4684,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,23.3825,-0.1492,-12.7502,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,28.0702,0.5443,-8.7561,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,14.1300,-1.7086,-20.4434,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,11.2450,-2.6952,-22.3418,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,42.3076,1.9894,4.0362,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,42.3076,1.9894,4.0362,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,26.4232,-2.9305,-6.9283,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,13.4609,-1.8977,-20.9234,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,26.0948,-0.5545,-9.6327,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,13.2227,-2.2078,-20.8515,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,14.2376,-1.5734,-20.4710,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,11.6696,-2.1453,-22.4671,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,27.3578,-1.9959,-6.9283,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,27.3578,-1.9959,-6.9283,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,12.4204,-1.6569,-22.2047,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,11.3874,-2.3640,-22.5306,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,15.8148,-0.0314,-20.4358,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,41.9100,0.2786,5.3494,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,41.9100,0.2786,5.3494,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,41.9100,0.2786,5.3494,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,41.9746,0.5033,5.1893,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,41.9746,0.5033,5.1893,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,41.9746,0.5033,5.1893,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,38.6658,2.1284,0.2554,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,20.0374,-0.7386,-15.5060,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,20.0374,-0.7386,-15.5060,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,11.3688,-0.2661,-24.6471,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,11.0927,-2.0381,-23.1512,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,38.1743,0.4793,1.4130,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,11.3228,-2.3076,-22.6516,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,10.3842,-2.5388,-23.3590,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,27.4020,-1.6453,-7.2347,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,41.1413,1.3740,3.4853,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,41.1413,1.3740,3.4853,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,41.1352,1.3680,3.4852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,41.1413,1.3740,3.4853,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,41.7554,1.4377,4.0357,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,41.7554,1.4377,4.0357,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,41.7554,1.4377,4.0357,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,41.7554,1.4377,4.0357,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,41.7554,1.4377,4.0357,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,41.7554,1.4377,4.0357,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,41.7554,1.4377,4.0357,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,10.4615,-3.2541,-22.5664,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,25.4529,-0.0403,-10.7888,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,12.3499,-1.7028,-22.2293,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,12.3499,-1.7028,-22.2293,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,9.9268,-2.2659,-24.0893,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,9.9268,-2.2659,-24.0893,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,20.4388,-0.3372,-15.5060,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,32.9501,-0.0758,-3.2561,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,13.1080,-2.6417,-20.5323,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,12.2146,-2.1778,-21.8896,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,15.3483,-1.6071,-19.3266,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,22.8418,-0.5192,-12.9210,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,22.8418,-0.5192,-12.9210,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,13.2227,-2.2078,-20.8515,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,8.6588,0.3025,-27.9257,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,19.3521,-1.6953,-15.2346,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,11.4893,-2.2620,-22.5306,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,11.7888,-1.7828,-22.7103,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.FSE,WAUE.FSE_H,11.4589,-2.0141,-22.8090,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,42.9976,1.5767,5.1389,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,43.1831,1.5648,5.3363,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,10.6394,-3.2423,-22.4002,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,11.3963,-3.0351,-21.8506,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,22.3311,-0.7416,-13.2093,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,23.6267,-0.9274,-11.7279,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,-1.3800,-3.5306,-34.1314,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,11.2450,-2.6952,-22.3418,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,-12.0000,0.7059,-48.9879,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,13.7367,-2.1288,-20.4165,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,13.7370,-2.1285,-20.4165,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,13.7392,-2.1263,-20.4165,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,6.4625,-1.6764,-28.1431,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,8.6588,0.3025,-27.9257,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,15.1231,-1.3721,-19.7868,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,13.0812,-2.2867,-20.9141,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,15.6597,-0.1865,-20.4358,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,15.1493,-0.7834,-20.3493,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,14.3765,-1.5232,-20.3823,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,16.1520,-1.8063,-18.3237,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,13.8932,-1.7322,-20.6566,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,13.1374,-2.5472,-20.5974,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,11.3228,-2.3076,-22.6516,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,18.4514,-0.0403,-17.7903,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,13.1727,-2.2556,-20.8537,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,17.9318,-0.4395,-17.9107,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,14.9461,-1.3012,-20.0346,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,13.4961,-1.9857,-20.8002,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NTWK,WAUE.NTWK_H,18.0449,-0.8797,-17.3574,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,16.3871,-1.0792,-18.8157,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,16.3871,-1.0792,-18.8157,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,11.2411,-2.9032,-22.1377,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,9.2275,-4.2032,-22.8512,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,15.9264,-1.4306,-18.9250,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,11.2411,-2.9032,-22.1377,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,23.2020,-0.3587,-12.7213,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,13.0553,-1.9019,-21.3248,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,11.3228,-2.3076,-22.6516,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,14.8855,-1.1478,-20.2487,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,13.6305,-1.3267,-21.3248,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,8.1420,-1.7031,-26.4369,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,9.7464,-1.6029,-24.9326,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,16.4861,-0.6677,-19.1282,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,11.5819,-3.0343,-21.6658,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,14.7118,-1.3201,-20.2501,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,12.0129,-2.0093,-22.2597,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,12.2146,-2.1778,-21.8896,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.VOLT.0152,V152_DDR,37.2982,2.6239,-1.6077,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE.VOLT.0172,V172_DDR,41.6806,1.5692,3.8294,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_BEPM,WAUE_BEPM_LA,29.5345,0.5463,-7.2938,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,14.9195,-1.4169,-19.9456,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,15.1697,-0.7580,-20.3542,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_EWA,WAUE_EWA_LA,7.5388,0.4662,-29.2094,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,13.7200,-2.0866,-20.4754,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_HMMU,WAUE_HMMU_LA,14.6008,-1.1086,-20.5726,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,16.6022,-1.4765,-18.2032,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_MECB,WAUE_MECB_LA,14.4909,-1.0010,-20.7901,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_MMPA,WAUE_MMPA_LA,22.6478,0.6059,-14.2401,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_MRES,WAUE_MRES_LA,13.8483,-1.0893,-21.3444,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,33.0337,1.8447,-5.0930,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,42.9976,1.5767,5.1389,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,12.8374,-1.9488,-21.4957,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_OTP,WAUE_OTP_LA,27.4441,1.6204,-10.4582,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_OTPW,WAUE_OTPW_LA,33.1104,1.4952,-4.6668,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM,WAUE_UGPM_LA,17.0614,-1.1446,-18.0760,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,27.9150,0.2592,-8.6261,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,14.1163,-1.6352,-20.5304,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,23.8905,-0.8497,-11.5418,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,7.5388,0.4662,-29.2094,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,14.6008,-1.1086,-20.5726,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,14.7681,-2.1408,-19.3731,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,42.9976,1.5767,5.1389,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,22.6478,0.6059,-14.2401,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,15.4845,-0.7404,-20.0571,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,12.8889,-2.1838,-21.2093,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,26.7430,1.9193,-11.4583,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,4.7539,-2.8035,-28.7246,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,5.4015,-3.3687,-27.5118,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,36.2391,-1.6819,1.6390,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,57.0600,-0.1173,20.8953,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,57.0600,-0.1173,20.8953,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,13.8217,-2.1628,-20.2974,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,53.3063,0.0501,16.9743,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,48.6870,-0.0329,12.4379,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,69.0000,-1.7868,34.5048,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,69.0000,-1.7868,34.5048,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,69.0000,-1.7868,34.5048,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,69.0000,-1.7868,34.5048,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,69.0000,-1.7868,34.5048,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,69.0000,-1.7868,34.5048,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,69.0000,-1.7868,34.5048,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,69.0000,-1.7868,34.5048,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,50.5038,-1.6770,15.8988,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,2.6621,-1.2126,-32.4073,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,-26.7603,-3.1032,-59.9391,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,4.5660,-3.1981,-28.5179,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,144.6713,4.4160,103.9733,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_ENMC,WFEC_ENMC_LA,144.1815,6.4938,101.4057,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,1.5297,-3.0050,-31.7473,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,31.3044,-0.4663,-4.5113,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,141.9397,5.3166,100.3411,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,4.7158,-2.8415,-28.7246,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,4.7539,-2.8035,-28.7246,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,4.7539,-2.8035,-28.7246,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_OKGE,WFEC_OKGE_LA,13.5201,-1.0709,-21.6910,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,51.2578,0.4202,14.5556,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,5.6550,-4.1649,-26.4621,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,13.8138,-4.6236,-17.8446,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_WFEC,WFEC_LA,32.9717,-0.8745,-2.4358,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,141.9397,5.3166,100.3411,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,4.4368,-2.7716,-29.0736,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,6.5324,-0.7365,-29.0131,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,9.1520,-2.6776,-24.4524,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,9.1520,-2.6776,-24.4524,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,9.1565,-2.6731,-24.4524,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,9.1565,-2.6731,-24.4524,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,9.1610,-2.6686,-24.4524,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,9.1610,-2.6686,-24.4524,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,9.1610,-2.6686,-24.4524,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,13.6062,-1.5024,-21.1734,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,8.7065,-3.0357,-24.5397,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,2.1673,-2.9433,-31.1714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,2.1673,-2.9433,-31.1714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,2.1673,-2.9433,-31.1714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,4.7398,-2.5551,-28.9871,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,4.7398,-2.5551,-28.9871,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,3.2895,-2.7537,-30.2388,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,3.2895,-2.7537,-30.2388,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,3.2895,-2.7537,-30.2388,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,8.7065,-3.0357,-24.5397,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,12.2965,-2.2463,-21.7392,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.HEC.GT1,WRHECGTUN32_RA,6.5878,-2.5488,-27.1454,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.HEC.GT2,WRHECGTUN33_RA,6.5878,-2.5488,-27.1454,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.HEC.GT3,WRHECGTUN34_RA,6.5878,-2.5488,-27.1454,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.HEC.GT4,WRHECGTUN35_RA,6.5880,-2.5486,-27.1454,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,12.2965,-2.2463,-21.7392,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,5.2168,-2.0233,-29.0419,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,-32.8788,-2.9531,-66.2077,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.JEC.1,WRJEFFUN10_RA,9.9690,-2.6837,-23.6292,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.JEC.2,WRJEFFUN11_RA,9.9964,-2.6893,-23.5962,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.JEC.3,WRJEFFUN12_RA,9.8727,-2.8131,-23.5962,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,0.0864,-3.1145,-33.0811,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,3.7390,-2.8578,-29.6852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,3.7390,-2.8578,-29.6852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.LEC.4,WRLECUN26_RA,10.8287,-2.2416,-23.2116,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.LEC.5,WRLECUN27_RA,10.9890,-2.1626,-23.1304,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,7.6422,-2.4577,-26.1821,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,7.6422,-2.4577,-26.1821,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,7.6422,-2.4577,-26.1821,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,7.7312,-2.3869,-26.1639,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,0.0000,-3.1084,-33.1736,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,0.0000,-3.1084,-33.1736,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,8.2888,-0.2711,-27.7221,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,4.9639,-2.6926,-28.6255,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,4.9639,-2.6926,-28.6255,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,1.5322,-3.6169,-31.1329,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,0.0000,-3.1084,-33.1736,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,10.8619,-2.8988,-22.5213,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,8.2217,-2.9567,-25.1036,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,3.7253,-2.8715,-29.6852,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,48.9053,0.0076,12.6157,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,0.0000,-5.0902,-31.1918,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,9.1610,-2.6686,-24.4524,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,2.7847,-3.7604,-29.7368,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,12.2965,-2.2463,-21.7392,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,8.7065,-3.0357,-24.5397,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,1.8969,-2.5642,-31.8208,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.THAYERLD,WR.THAYERLD_LA,26.4505,-0.2956,-9.5359,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0102,WR.VOLT.0102_H,1.7070,-2.5332,-32.0418,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0106,V106_DDR,1.7059,-2.5544,-32.0217,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0139,WR.VOLT.0139_H,11.2921,-2.0413,-22.9485,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0141,WR.VOLT.0141_H,8.7915,-2.5060,-24.9845,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0146,WR.VOLT.0146_H,11.0700,-1.9915,-23.2205,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0147,WR.VOLT.0147_H,11.0700,-1.9915,-23.2205,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0148,WR.VOLT.0148_H,11.4932,-2.1501,-22.6387,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0153,WR.VOLT.0153_H,2.0557,-2.2890,-31.9373,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0157,V157_DDR,11.0468,-2.0158,-23.2193,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0158,V158_DDR,11.0700,-1.9915,-23.2205,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0159,WR.VOLT.0159_H,11.0700,-1.9915,-23.2205,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0165,WR.VOLT.0165_H,1.0858,-2.7717,-32.4245,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0173,V173_DDR,7.3194,-2.7202,-26.2423,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0174,V174_DDR,1.4413,-2.5967,-32.2439,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0184,V184_DDR,1.4454,-2.7858,-32.0508,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0185,WR.VOLT.0185_H,1.8471,-2.5553,-31.8796,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0186,V186_DDR,2.0260,-2.6020,-31.6540,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0187,WR.VOLT.0187_H,1.5228,-2.7043,-32.0549,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0188,WR.VOLT.0188_H,1.6111,-2.5447,-32.1262,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0189,WR.VOLT.0189_H,6.8257,-2.2945,-27.1618,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0190,WR.VOLT.0190_H,8.4974,-2.5219,-25.2627,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0191,WR.VOLT.0191_H,8.9475,-2.5904,-24.7441,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0192,WR.VOLT.0192_H,8.9475,-2.5904,-24.7441,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0196,WR.VOLT.0196_H,8.4974,-2.5219,-25.2627,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0245,V245_DDR,1.8657,-2.5477,-31.8686,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.VOLT.0248,V248_DDR,1.7059,-2.5544,-32.0217,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,0.1524,-3.0155,-33.1141,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,11.0500,-2.2487,-22.9833,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.WOLF,WRWOLFUN15_RA,2.4997,-3.9212,-29.8610,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,5.2168,-2.0233,-29.0419,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,13.3950,-1.7136,-21.1734,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,2.1673,-2.9433,-31.1714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,2.1673,-2.9433,-31.1714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,2.1673,-2.9433,-31.1714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,2.1673,-2.9433,-31.1714,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,5.0321,-2.6338,-28.6161,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,8.8232,-2.5095,-24.9493,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,0.9897,-2.6562,-32.6361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,0.9897,-2.6562,-32.6361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,0.9897,-2.6562,-32.6361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,0.9897,-2.6562,-32.6361,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,9.4945,-2.3288,-24.4586,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,9.4945,-2.3288,-24.4586,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,9.4945,-2.3288,-24.4586,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,9.4945,-2.3288,-24.4586,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,9.4945,-2.3288,-24.4586,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,9.4945,-2.3288,-24.4586,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,-3.3731,-2.5235,-37.1316,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,-3.3731,-2.5235,-37.1316,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,-4.5274,-2.6433,-38.1661,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,-4.5274,-2.6433,-38.1661,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_MIDW,WR_MIDW_LA,5.6793,-2.0619,-28.5408,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,26.4786,-1.2146,-8.5888,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,19.3916,-1.9470,-14.9433,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,7.2667,-2.0553,-26.9600,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_SEG,WR_SEG_LA,11.3773,-1.7198,-23.1849,36.2820\n03/20/2025 00:00:00,03/20/2025 05:00:00,WR_WR,WR_LA,7.7801,-2.3732,-26.1286,36.2819\n03/20/2025 00:00:00,03/20/2025 05:00:00,YAD,VACS,24.8917,-0.0817,-11.3085,36.2819\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_SPP/RTBM-LMP-SL-202503310840.csv",
    "content": "Interval,GMTIntervalEnd,Settlement Location,Pnode,LMP,MLC,MCC,MEC\n03/31/2025 08:40:00,03/31/2025 13:40:00,AEC,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,AECC_CSWS,CSWS_AECC_LA,38.8023,-4.7899,-246.4665,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,41.0293,-3.2396,-245.7899,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,32.7556,-10.8170,-246.4862,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,38.2818,-6.0038,-245.7732,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,34.9581,-7.3443,-247.7564,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,AECC_HYDRO13,CSWSLD13UN1_RA,30.1722,-13.5285,-246.3581,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,39.5077,-2.6387,-247.9124,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,AECI,AECI,34.8382,-8.5989,-246.6216,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,AEPM_CSWS,CSWS_LA,39.7611,-1.7648,-248.5329,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ALTW,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,AMRN,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ANTELOPE,SPSANTELOPEUNANT1_RA,2120.1068,21.0276,1809.0204,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BBA,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BCA,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BEPM.ER01.DDR,ER01_DDR,22.2030,-17.0396,-250.8162,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BEPM_ER01,BEPM_ER01_LA,22.2030,-17.0396,-250.8162,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,54.1238,16.1452,-252.0802,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,34.7984,1.1831,-256.4435,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BEPM_UM01,BEPM_UM01_LA,61.4523,21.2459,-249.8524,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BLKW,BLKW,2211.6089,38.7273,1882.8228,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,8.0699,-24.4000,-257.5889,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,8.0699,-24.4000,-257.5889,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,9.7849,-20.0207,-260.2532,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,8.4748,-23.9951,-257.5889,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BRAZ,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BUBA,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,-0.9771,-14.2917,-276.7442,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,30.9739,-15.2058,-243.8791,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,30.9739,-15.2058,-243.8791,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,30.9739,-15.2058,-243.8791,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,30.9739,-15.2058,-243.8791,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,30.9739,-15.2058,-243.8791,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,25.6266,-20.5587,-243.8735,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,31.5737,-9.3541,-249.1310,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,31.5737,-9.3541,-249.1310,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CLEC,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,38.4149,-6.3331,-245.3108,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,COWP,COWP_LA,35.6277,-7.5855,-246.8456,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,35.6277,-7.5855,-246.8456,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,35.6277,-7.5855,-246.8456,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CPLE,VACS,35.4043,-7.2616,-247.3929,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CPLW,VACS,35.4043,-7.2616,-247.3929,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,34.7785,-8.0211,-247.2592,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,34.7785,-8.0211,-247.2592,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,34.7785,-8.0211,-247.2592,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,34.7785,-8.0211,-247.2592,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CRTH_SPA,WRCRTH_SPA_LA,33.2127,-11.0590,-245.7871,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,46.5860,4.2961,-247.7689,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,21.2196,-13.0070,-255.8322,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,39.5077,-2.6387,-247.9124,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,38.2818,-6.0038,-245.7732,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWJLSTALL,CSWSSTALL_PPPLT1,46.5203,4.2332,-247.7717,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,46.2276,3.9767,-247.8079,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,45.9992,3.7288,-247.7884,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,45.9992,3.7288,-247.7884,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWMATTISON1,CSWSMATTISONUN1_RA,35.7656,-8.5075,-245.7857,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWMATTISON2,CSWSMATTISONUN2_RA,35.7656,-8.5075,-245.7857,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWMATTISON3,CSWSMATTISONUN3_RA,35.7972,-8.4759,-245.7857,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWMATTISON4,CSWSMATTISONUN4_RA,35.7972,-8.4759,-245.7857,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,39.5077,-2.6387,-247.9124,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWNARROWS1,CSWSNARROWSUN1_RA,43.3528,1.2147,-247.9207,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,35.0471,-9.5477,-245.4640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,33.2692,-11.3257,-245.4640,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,36.4340,-8.1455,-245.4793,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,36.9385,-7.5505,-245.5698,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,35.7206,-8.7684,-245.5698,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,35.6513,-8.8377,-245.5698,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,35.6513,-8.8377,-245.5698,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,-1.1052,-15.5061,-275.6579,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,26.2740,-10.8211,-252.9637,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,33.2650,-9.5458,-247.2480,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,-44.0252,-11.5642,-322.5198,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,-43.9913,-11.5303,-322.5198,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,23.1084,-13.1928,-253.7576,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.GRID.CDL1,CDL1_DDR,37.2861,-6.0887,-246.6840,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,27.0764,-14.0812,-248.9012,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,6.2007,-14.7612,-269.0969,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,37.2861,-6.0887,-246.6840,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.NUEN.CSI1,CSI1_DDR,40.6336,-3.7384,-245.6868,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.NUEN.CSI2,CSI2_DDR,40.7342,-3.6378,-245.6868,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.NUEN.CSI3,NCSI3_DDR,37.8227,-6.9476,-245.2885,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.NUEN.GAZA,GAZA_DDR,37.2861,-6.0887,-246.6840,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,42.4527,0.5040,-248.1101,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.NUEN.T201,NT201_DDR,38.8764,-5.5847,-245.5977,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,19.9772,-14.8519,-255.2297,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,19.9772,-14.8519,-255.2297,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,39.5077,-2.6387,-247.9124,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,49.8526,7.6365,-247.8427,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,23.1084,-13.1928,-253.7576,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,23.1084,-13.1928,-253.7576,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,18.6221,-15.3087,-256.1280,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,-43.9913,-11.5303,-322.5198,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,43.4519,1.1759,-247.7828,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,36.4029,-8.1223,-245.5336,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,36.4029,-8.1223,-245.5336,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,32.1619,-12.3633,-245.5336,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,31.9231,-11.3584,-246.7773,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,33.8018,-9.4797,-246.7773,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,46.0712,3.8370,-247.8246,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,38.3140,-6.2155,-245.5294,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,46.7636,4.5225,-247.8177,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,59.6944,17.4811,-247.8455,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,36.7257,-5.2439,-248.0892,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0056,PRYORCRK_DDR,40.7342,-3.6378,-245.6868,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0057,OKMU_DDR,39.6938,-4.2673,-246.0977,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0060,LEHIGH_DDR,40.6163,-1.4521,-247.9904,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0086,WARRENM_DDR,38.2147,-6.2758,-245.5684,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,50.8064,8.6098,-247.8622,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,39.4190,-5.1215,-245.5183,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0121,V121_DDR,46.0712,3.8370,-247.8246,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0122,V122_DDR,38.9465,-5.5801,-245.5322,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0124,V124_DDR,38.0436,-6.7058,-245.3094,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0135,V135_DDR,39.1067,-5.3934,-245.5587,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0144,V144_DDR,27.0184,-10.4833,-252.5571,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0145,V145_DDR,25.7085,-12.0370,-252.3133,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,46.4352,4.2024,-247.8260,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,40.6433,-1.4822,-247.9333,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0175,V175_DDR,37.8227,-6.9476,-245.2885,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,40.6433,-1.4822,-247.9333,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,41.9685,-0.1640,-247.9263,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,39.1067,-5.3934,-245.5587,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,38.9569,-5.5349,-245.5670,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,38.2222,-6.2389,-245.5977,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,36.6214,-7.9692,-245.4682,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,37.2563,-7.2438,-245.5587,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,38.9569,-5.5349,-245.5670,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0211,V211_DDR,48.9890,6.7339,-247.8037,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,39.6191,-4.9688,-245.4709,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0213,V213_DDR,38.3791,-6.1154,-245.5643,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0215,V215_DDR,38.9859,-5.5546,-245.5183,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0217,V217_DDR,39.3944,-5.1935,-245.4709,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0218,V218_DDR,36.7338,-7.8568,-245.4682,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0228,V228_DDR,38.3544,-6.1791,-245.5253,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0232,V232_DDR,38.8503,-5.6540,-245.5545,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0233,V233_DDR,39.1312,-5.3662,-245.5615,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0240,V240_DDR,38.1677,-6.3951,-245.4960,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0244,V244_DDR,38.9569,-5.5349,-245.5670,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0246,MDT1_DDR,42.4527,0.5040,-248.1101,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0249,V249_DDR,38.8890,-5.6056,-245.5643,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0250,V250_DDR,22.2367,-12.3334,-255.4887,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0251,V251_DDR,37.6146,-6.8772,-245.5670,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.VOLT.0252,V252_DDR,36.6214,-7.9692,-245.4682,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,18.4879,-15.4429,-256.1280,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,14.1548,-18.7691,-257.1349,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,8.7022,-15.8362,-265.5204,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,44.6308,2.3869,-247.8149,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,39.1027,-17.7312,-233.2249,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,24.7271,-13.0184,-252.3133,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,24.7271,-13.0184,-252.3133,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,24.5167,-13.2288,-252.3133,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,14.7886,-17.8080,-257.4622,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,14.7886,-17.8080,-257.4622,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,39.5077,-2.6387,-247.9124,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,46.5401,4.1766,-247.6954,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,38.6135,-5.8908,-245.5545,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,38.1553,-6.3491,-245.5545,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,39.0907,-4.6462,-246.3219,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,39.0907,-4.6462,-246.3219,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWWELSH1,CSWSWELSHUN1_RA,41.1660,-0.9999,-247.8929,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWWELSH3,CSWSWELSHUN3_RA,41.1660,-0.9999,-247.8929,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWWILKES1,CSWSWILKESUN1_RA,42.9316,0.7350,-247.8622,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWWILKES2,CSWSWILKESUN2_RA,42.9316,0.7350,-247.8622,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,CSWWILKES3,CSWSWILKESUN3_RA,42.5733,0.3670,-247.8525,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,-44.0350,-11.5740,-322.5198,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,DENL,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,DERS,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,DOE,DOE,34.8112,-7.8185,-247.4291,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,25.4828,-18.2249,-246.3511,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,DPC,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,DUK,VACS,35.4043,-7.2616,-247.3929,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDDY,EDDY,2189.3292,47.5426,1851.7278,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,29.8603,-14.3557,-245.8428,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,29.3760,-15.7383,-244.9445,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,27.8289,-16.5347,-245.6952,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE.SLCC,EDESTL4391_PLT,25.3870,-18.9906,-245.6812,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE.VOLT.0234,EDE.VOLT.0234_H,28.8126,-15.5371,-245.7091,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,26.3368,-18.0021,-245.7199,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_EC_01,EDELAR3821UN1_RA,29.8603,-14.3557,-245.8428,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_EC_02,EDELAR3821UN2_RA,29.5803,-14.6357,-245.8428,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_EC_03,EDELAR3821UN3_RA,29.8603,-14.3557,-245.8428,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_EC_04,EDELAR3821UN4_RA,29.8603,-14.3557,-245.8428,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_EDE,EDE_LA,36.2389,-7.9431,-245.8768,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_ERW,EDEERWFUNG1_RA,25.2430,-21.0899,-243.7259,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,23.0947,-20.6366,-246.3275,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_OZD_5,EDEOZRK_BUN5_RA,37.9091,-5.8403,-246.3094,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_OZD_6,EDEOZRK_BUN6_RA,37.9091,-5.8403,-246.3094,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_OZD_7,EDEOZRK_BUN7_RA,37.9091,-5.8403,-246.3094,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_OZD_8,EDEOZRK_BUN8_RA,37.9091,-5.8403,-246.3094,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,35.0986,-7.6899,-247.2703,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_RIV_10,EDERIV1671UN10_RA,29.2579,-15.1614,-245.6395,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_RIV_11,EDERIV1671UN11_RA,29.2579,-15.1614,-245.6395,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_RIV_12,EDERIV453UN12_PLT,29.2579,-15.1614,-245.6395,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_SL_01,EDESTL4391UN1_RA,23.2264,-21.1512,-245.6812,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EDE_SWMP,EDE_SWMP_LA,38.5241,-5.6408,-245.8939,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EEI,EEI,34.8066,-7.8217,-247.4305,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EES,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,23.4951,-22.8406,-243.7231,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ERCOTE,ERCOTE,41.1660,-0.9999,-247.8929,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ERCOTN,ERCOTN,20.6186,-14.2105,-255.2297,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,26.0174,-15.9313,-248.1101,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,FMPP,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,FPC,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,FPL,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,FREM_50T,OPPDFREM_GUN1_RA,35.1676,-5.3856,-249.5056,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,FREM_6,OPPDFREM_AUN6_RA,34.7222,-5.8296,-249.5070,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,FREM_7,OPPDFREM_AUN7_RA,34.7222,-5.8296,-249.5070,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,FREM_8,OPPDFREM_AUN8_RA,33.5228,-7.0290,-249.5070,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,FREM_LOAD,FREM_LOAD_LA,34.8513,-5.7005,-249.5070,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,FRONTIER,WRGETTUNFRONTIER_RA,30.0538,-17.0075,-242.9975,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GATEWAY_LOAD,CSWS_TENASKA_LA,43.4519,1.1759,-247.7828,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,1136.6965,-9.9747,856.6124,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,31.5179,-17.5197,-241.0212,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,38.4149,-6.3331,-245.3108,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,38.4149,-6.3331,-245.3108,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,38.4149,-6.3331,-245.3108,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.GREC2,GRDAGRDA17UN2_RA,36.2558,-8.1580,-245.6450,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,36.2558,-8.1580,-245.6450,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,36.1977,-8.2202,-245.6409,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,36.1977,-8.2202,-245.6409,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,24.4655,-22.7351,-242.8582,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,35.3411,-10.7007,-244.0170,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,35.3411,-10.7007,-244.0170,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,35.3411,-10.7007,-244.0170,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.VOLT.0130,V130_DDR,40.0368,-4.3630,-245.6590,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA.VOLT.0237,V237_DDR,37.8055,-6.5902,-245.6631,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDAHUB2,GRDAHUB2_H,33.5112,-11.8024,-244.7451,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDAHUB3,GRDAHUB3_H,33.0385,-12.6999,-244.3204,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA_GRDA,GRDA_LA,37.7575,-6.7277,-245.5736,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA_HUB,GRDA_H,33.1183,-12.1489,-244.7916,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRDA_HUBSA,GRDASA_H,35.1591,-9.7170,-245.1827,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GRE,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,-95.4817,12.1009,-397.6414,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,GSEC_SPS,SPS_GSEC_LA,1853.9929,22.7450,1541.1890,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,GSPR2014HUB,GSPR2014HUB_H,1588.4983,15.8522,1282.5872,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,GSPR2015HUB,GSPR2015HUB_H,1570.5879,14.8586,1265.6704,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,983.2696,6.2471,686.9637,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,HARRISON,CSWSLEBROCKPLT1,43.9677,1.7252,-247.8163,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,HAST_TNSK_HUB,HAST_TNSK_H,39.3482,1.6986,-252.4092,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,HQST,PJM,34.6187,-7.5852,-247.8549,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,HST,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,INDNSUB_H_5,INDNSUB_HUN5_RA,32.4242,-11.0286,-246.6060,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,INDNSUB_H_6,INDNSUB_HUN6_RA,32.4242,-11.0286,-246.6060,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,INDNSUB_I_3,INDNSUBIUN3_RA,33.2511,-10.2087,-246.5990,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,INDNSUB_I_4,INDNSUBIUN4_RA,33.2511,-10.2087,-246.5990,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,INDNSUB_J_1,INDNSUBJUN1_RA,33.2687,-10.1799,-246.6102,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,INDNSUB_J_2,INDNSUBJUN2_RA,33.2687,-10.1799,-246.6102,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,INDN_INDN,INDN_LA,33.1496,-10.3052,-246.6040,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,25.9506,-15.2154,-248.8928,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ISNE,PJM,34.6187,-7.5852,-247.8549,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,JEA,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,JONES_STREET_1,OPPDJONES_STUN1_RA,33.6714,-7.2898,-249.0976,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,JONES_STREET_2,OPPDJONES_STUN2_RA,33.6714,-7.2898,-249.0976,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,26.3487,-17.5344,-246.1757,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KACYCT4,KACYNEARMANUNCT4_RA,28.8143,-14.7638,-246.4807,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,28.4431,-15.9832,-245.6325,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,28.8143,-14.7638,-246.4807,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,29.7491,-13.8290,-246.4807,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,29.4375,-14.1406,-246.4807,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KACY_KACY,KACY_LA,30.0666,-13.5116,-246.4805,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,30.0480,-13.4354,-246.5754,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,39.3155,-3.9897,-246.7536,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,20.8869,-23.3959,-245.7760,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,24.2004,-23.4249,-242.4335,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.VOLT.0222,V222_DDR,28.4977,-14.3757,-247.1854,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.VOLT.0223,V223_DDR,25.9727,-17.8478,-246.2383,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.VOLT.0241,V241_DDR,36.7757,-6.4417,-246.8414,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.VOLT.0243,V243_DDR,36.0779,-8.6910,-245.2899,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.VOLT.0247,V247_DDR,27.6106,-16.0831,-246.3651,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.VOLT.0253,V253_DDR,30.1629,-13.3177,-246.5782,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,15.5744,-30.1791,-244.3053,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,24.5077,-19.5091,-246.0420,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,24.5077,-19.5091,-246.0420,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,24.5077,-19.5091,-246.0420,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,24.5054,-19.5114,-246.0420,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,30.0255,-13.4551,-246.5782,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,30.0255,-13.4551,-246.5782,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHUB,KCPLHUB_H,21.0146,-22.3052,-246.7390,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHUB17,KCPLHUB17_H,20.6250,-22.2661,-247.1677,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHUB18,KCPLHUB18_H,20.8733,-22.2594,-246.9261,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHUB19,KCPLHUB19_H,21.5147,-21.6912,-246.8529,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHUB20,KCPLHUB20_H,20.8274,-22.2988,-246.9326,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHUB21,KCPLHUB21_H,20.4747,-21.8334,-247.7507,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHUB22,KCPLHUB22_H,20.4991,-22.0985,-247.4613,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHUB23,KCPLHUB23_H,20.5093,-22.2710,-247.2785,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLHUB24,KCPLHUB24_H,20.2644,-22.4346,-247.3598,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,25.7327,-17.5753,-246.7508,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,25.7327,-17.5753,-246.7508,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,20.1302,-24.4437,-245.4849,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,20.1302,-24.4437,-245.4849,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,30.0967,-13.3867,-246.5754,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,30.0480,-13.4354,-246.5754,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,30.6173,-12.8996,-246.5419,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,30.6173,-12.8996,-246.5419,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,30.6168,-12.9001,-246.5419,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,30.6168,-12.9001,-246.5419,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,30.6165,-12.9004,-246.5419,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,30.6165,-12.9004,-246.5419,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,30.6162,-12.9007,-246.5419,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,30.6162,-12.9007,-246.5419,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,23.8330,-20.2173,-246.0085,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,29.6957,-13.8588,-246.5043,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KCPL_KCPL,KCPL_LA,29.1411,-14.5208,-246.3969,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KENN,KENN_LA,34.9988,-7.8342,-247.2258,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KEP2_SECI,KEP2_SECI_LA,-3.4937,-7.8099,-285.7426,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KERR_1,GRDAKERR_HYDUN1_RA,37.6751,-6.7122,-245.6715,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KERR_2,GRDAKERR_HYDUN2_RA,37.8590,-6.5255,-245.6743,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KERR_3,GRDAKERR_HYDUN3_RA,37.8590,-6.5255,-245.6743,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KERR_4,GRDAKERR_HYDUN4_RA,37.6751,-6.7122,-245.6715,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,24.5039,-19.5129,-246.0420,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,24.5039,-19.5129,-246.0420,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,25.9720,-17.9808,-246.1060,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,25.9720,-17.9808,-246.1060,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,24.6160,-19.4101,-246.0327,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,25.1788,-18.8575,-246.0225,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,25.1788,-18.8575,-246.0225,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,-0.2066,-12.9056,-277.3598,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,-0.2066,-12.9056,-277.3598,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,-0.2066,-12.9056,-277.3598,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,35.1266,-4.1801,-250.7521,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,35.1266,-4.1801,-250.7521,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,-0.6931,-13.3019,-277.4500,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,30.2600,-7.9937,-251.8051,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,23.4762,-20.3108,-246.2718,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,28.8497,-15.6365,-245.5726,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,28.8497,-15.6365,-245.5726,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,24.9606,-18.8445,-246.2537,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,24.9606,-18.8445,-246.2537,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,24.9606,-18.8445,-246.2537,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,31.5282,-4.4276,-254.1030,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,29.7860,-13.0122,-247.2606,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,27.7434,-16.2066,-246.1088,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,KMEA_EUDORA,KMEA_EUDORA_LA,27.5090,-16.2808,-246.2690,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LAFA,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LAM345,LAM345,-0.9771,-14.2917,-276.7442,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LEPA,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_JSTREET,LES8_NUNJ_STREET_RA,32.3499,-8.1058,-249.6031,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_LES,LES_LA,31.9968,-8.4722,-249.5898,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,29.8897,-10.6161,-249.5530,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_ROKEBY_1,LESROKEBYUN1_RA,30.8318,-9.6211,-249.6059,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_ROKEBY_2,LESROKEBYUN2_RA,31.2567,-9.1962,-249.6059,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_ROKEBY_3,LESROKEBYUN3_RA,31.2567,-9.1962,-249.6059,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_TBGS_CC1,LES84_BLUFPLT1,30.0574,-10.4484,-249.5530,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,29.8897,-10.6161,-249.5530,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_WAVERLY,LES_WAVERLY_H,30.9389,-9.5753,-249.5446,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,31.1639,-9.8684,-249.0265,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,31.1755,-9.8568,-249.0265,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,LGEE,LGEE,34.6911,-7.7030,-247.6647,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MALDEN,MALDEN_LA,34.9563,-7.8614,-247.2411,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MCWEST,MCWEST,45.7266,6.0230,-250.3552,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MDU,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,33.7917,-0.8383,-255.4288,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,34.4136,-7.2788,-248.3664,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,48.0312,7.1322,-249.1598,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MEAN_NPPD,NPPD_MEAN_LA,38.0474,1.1764,-253.1878,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MEC,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MHEB,MHEB,45.2473,4.4181,-249.2296,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,29.9506,-7.5177,-252.5905,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,28.6787,-6.1575,-255.2227,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,29.9506,-7.5177,-252.5905,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,29.9506,-7.5177,-252.5905,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,28.6787,-6.1575,-255.2227,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,25.3620,-15.3736,-249.3232,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MISO,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,-8.4401,-4.2636,-294.2353,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,-8.4401,-4.2636,-294.2353,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,25.1196,-17.0533,-247.8859,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,12.0420,-15.5771,-262.4397,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,26.9520,-10.5081,-252.5988,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,12.5626,-22.1398,-255.3564,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKEC_KPP,SECI_MKEC_KPP_LA,25.5120,-15.8861,-248.6606,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,16.0908,-20.3065,-253.6615,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,31.3695,-12.7253,-245.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,31.3695,-12.7253,-245.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,31.3695,-12.7253,-245.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,31.3695,-12.7253,-245.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,31.3695,-12.7253,-245.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,30.9223,-11.9219,-247.2146,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,34.4188,-8.3099,-247.3302,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,34.4188,-8.3099,-247.3302,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,33.8649,-8.6617,-247.5322,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,38.4726,-4.5902,-246.9960,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MOWR,AECI,34.8382,-8.5989,-246.6216,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,33.1061,-10.0344,-246.9183,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,34.5935,-8.2343,-247.2311,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,24.3921,-17.4869,-248.1798,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,26.3469,-16.2034,-247.5085,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,25.6536,-22.4954,-241.9098,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,24.5947,-17.2843,-248.1798,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,26.0223,-17.6547,-246.3818,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,26.0223,-17.6547,-246.3818,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,25.3632,-18.3138,-246.3818,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,25.3632,-18.3138,-246.3818,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,28.4977,-14.3757,-247.1854,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,28.4977,-14.3757,-247.1854,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,28.4977,-14.3757,-247.1854,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,28.0099,-14.8635,-247.1854,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,28.4977,-14.3757,-247.1854,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,28.4977,-14.3757,-247.1854,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,28.4977,-14.3757,-247.1854,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,36.2962,-7.7151,-246.0475,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,23.9206,-19.7648,-246.3734,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,19.8883,-23.9753,-246.1952,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,19.0451,-24.8185,-246.1952,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,19.8836,-23.9800,-246.1952,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSTWA1UN1,MPSTWA1UN1_RA,30.0049,-13.4047,-246.6492,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPSTWA1UN2,MPSTWA1UN2_RA,30.0049,-13.4047,-246.6492,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MPS_MPS,MPS_LA,30.6007,-12.7785,-246.6796,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MSTNG,SPSMSTNGPLT1,2168.8993,39.2479,1839.5926,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MSTNG4,SPSMSTNGUN4_RA,2164.6629,35.3912,1839.2129,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MSTNG5,SPSMSTNGUN5_RA,2166.2072,36.9355,1839.2129,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,2166.2072,36.9355,1839.2129,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NBSO,PJM,34.6187,-7.5852,-247.8549,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,23.8715,-17.3460,-248.8413,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,23.8584,-17.3591,-248.8413,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,1023.4504,2.2135,731.1781,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NHC1,VACS,35.4043,-7.2616,-247.3929,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,33.0591,-7.8896,-249.1101,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,33.0591,-7.8896,-249.1101,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,33.0591,-7.8896,-249.1101,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,49.1920,11.8253,-252.6921,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,36.5292,-1.2692,-252.2604,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,29.6455,-10.7364,-249.6769,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,31.6281,-8.7802,-249.6505,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,36.5292,-1.2692,-252.2604,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.HUB.PY2018,NPPDPY18_H,26.7618,-14.1678,-249.1292,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,26.6736,-14.2820,-249.1032,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,26.7444,-14.1893,-249.1251,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,26.5590,-14.4168,-249.0831,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,32.8011,-7.4499,-249.8078,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,29.8676,-4.2401,-255.9511,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,29.8676,-4.2401,-255.9511,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,31.7184,-4.5995,-253.7409,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,32.8011,-7.4499,-249.8078,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,30.8646,-8.8724,-250.3218,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,41.5715,5.4987,-253.9860,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,25.2080,-4.7787,-260.0721,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,41.5715,5.4987,-253.9860,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,44.9194,7.8020,-252.9414,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,39.1745,3.6950,-254.5793,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,33.9296,-6.5330,-249.5962,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,36.5292,-1.2692,-252.2604,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,26.0845,-4.6097,-259.3646,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,29.8676,-4.2401,-255.9511,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,29.8676,-4.2401,-255.9511,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,34.4176,-0.4394,-255.2018,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,34.2977,-0.4869,-255.2742,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,34.2977,-0.4869,-255.2742,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,40.4167,4.3926,-254.0347,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,36.3055,-4.2560,-249.4973,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,38.8175,0.7768,-252.0181,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,50.3073,12.7248,-252.4763,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,37.5084,-3.0141,-249.5363,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,38.1533,-2.3135,-249.5920,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.NELI.DDR,NELI_DDR,33.4453,-6.4436,-250.1699,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.NPPM.1058,SH1058_DDR,37.9953,-1.9228,-250.1407,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,37.5634,1.2956,-253.7910,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,36.5292,-1.2692,-252.2604,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,29.6455,-10.7364,-249.6769,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,33.0051,-7.2459,-249.8078,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.TECH.1,KEARNE_DDR,40.8858,4.7002,-253.8732,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,33.3503,-5.0372,-251.6713,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,33.3503,-5.0372,-251.6713,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,32.8482,-7.1855,-250.0251,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD.VOLT.0236,V236_DDR,30.7063,-9.8385,-249.5140,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD2017HUB,NPPD2017HUB_H,26.6430,-14.3165,-249.0994,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,33.3204,-6.4960,-250.2424,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,49.1920,11.8253,-252.6921,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,41.8288,5.5749,-253.8049,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,41.8288,5.5749,-253.8049,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_BPS,NPPDBEAPWRSTPLT1,30.5678,-9.9617,-249.5293,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,31.0429,-9.5019,-249.5140,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,35.4410,-4.9603,-249.6576,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,34.1654,-0.8364,-255.0570,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,32.4505,-7.2963,-250.3120,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,34.8081,-4.9387,-250.3120,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,32.4674,-7.2794,-250.3120,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,39.1209,1.4339,-252.3718,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_COOPR,NPPDCOOPERUN1_RA,24.9581,-16.4237,-248.6770,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_COSN_NPPD,NPPD_COSN_LA,41.3438,2.8964,-251.6114,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,34.4826,-5.6583,-249.9179,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,34.7342,-5.4067,-249.9179,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,28.3516,-4.8578,-256.8494,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,27.8667,-5.0656,-257.1265,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,38.3169,0.5965,-252.3384,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,38.0616,0.3412,-252.3384,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,38.0616,0.3412,-252.3384,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,38.8533,1.1789,-252.3844,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,30.8646,-8.8724,-250.3218,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,38.7827,1.1264,-252.4025,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,29.4868,-10.9758,-249.5962,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,39.5658,1.9290,-252.4220,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,39.3612,1.7274,-252.4250,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,39.4668,1.8481,-252.4401,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,39.4668,1.8481,-252.4401,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,39.1209,1.4339,-252.3718,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,39.1209,1.4339,-252.3718,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,55.1346,17.2568,-252.1810,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,39.2325,0.0887,-250.9150,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,26.9802,-6.0983,-256.9803,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,37.9827,-1.4243,-250.6518,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,24.0575,-5.5406,-260.4607,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,37.3832,-2.8846,-249.7911,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_NELI_LD,NPPD_NELIGH_LA,33.4453,-6.4436,-250.1699,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,29.8967,-3.5927,-256.5694,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,29.8967,-3.5927,-256.5694,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_NPPD,NPPD_LA,35.8655,-2.3490,-251.8443,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,29.4868,-10.9758,-249.5962,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,29.4868,-10.9758,-249.5962,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,24.6483,-16.1249,-249.2856,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,41.2206,5.1046,-253.9428,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NSB,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,NSP,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NSSO,PJM,34.6187,-7.5852,-247.8549,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,NYIS,PJM,34.6187,-7.5852,-247.8549,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,39.0376,-13.5931,-237.4281,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,26.1060,-22.0514,-241.9014,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,25.2211,-22.7218,-242.1159,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,25.2211,-22.7218,-242.1159,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,-15.5204,-10.6295,-294.9497,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,31.5179,-17.5197,-241.0212,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,29.1911,-18.2811,-242.5866,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,17.2670,-31.1522,-241.6396,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,24.6799,-22.5946,-242.7844,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,24.6834,-23.5325,-241.8429,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,33.6079,-11.3100,-245.1409,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,24.6799,-22.5946,-242.7844,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,0.0477,-11.5343,-278.4768,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,25.3620,-15.3736,-249.3232,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,57.5493,-14.6337,-217.8758,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,30.7158,-10.3234,-249.0196,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,24.6834,-23.5325,-241.8429,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,29.8761,-18.3996,-241.7831,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,30.6346,-17.1704,-242.2538,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,30.9739,-15.2058,-243.8791,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,27.8081,-12.4819,-249.7688,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,25.3620,-15.3736,-249.3232,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,25.3620,-15.3736,-249.3232,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,24.6834,-23.5325,-241.8429,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.NUEN.ADA1,ADA1_DDR,31.8628,-8.9828,-249.2132,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.NUEN.LAM1,LAM1_DDR,46.0815,2.4449,-246.4222,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.NUEN.MDT2,MDT2_DDR,33.6511,-11.2668,-245.1409,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.NUEN.MDT3,MDT3_DDR,33.6511,-11.2668,-245.1409,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.NUEN.WWO1,WWO1_DDR,36.1966,-9.0054,-244.8568,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,33.9090,-11.1106,-245.0392,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,33.9044,-11.1152,-245.0392,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,34.1901,-10.8295,-245.0392,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,34.8166,-10.1445,-245.0977,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,34.8166,-10.1445,-245.0977,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,34.1890,-10.8306,-245.0392,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,34.1890,-10.8306,-245.0392,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,24.6834,-23.5325,-241.8429,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,35.1348,-7.8821,-247.0419,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,0.0477,-11.5343,-278.4768,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,22.3703,-17.3208,-250.3677,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,29.8761,-18.3996,-241.7831,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,34.8728,-8.6594,-246.5266,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,28.7637,-18.3255,-242.9696,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,28.7637,-18.3255,-242.9696,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,30.8651,-16.2241,-242.9696,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,30.8651,-16.2241,-242.9696,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,29.0881,-22.4925,-238.4782,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,26.8781,-20.9367,-242.2440,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,26.1060,-22.0514,-241.9014,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,26.2485,-21.2125,-242.5978,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,26.2485,-21.2125,-242.5978,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,28.8032,-10.0342,-251.2214,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,32.7773,-15.7032,-241.5783,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,32.7773,-15.7032,-241.5783,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,32.7773,-15.7032,-241.5783,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0033,FOSTER_DDR,34.9363,-9.6808,-245.4417,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0034,CUSHOIL_DDR,45.2651,-0.3325,-244.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0035,TARBY_DDR,41.2802,-2.3926,-246.3860,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0036,CUSHFLI_DDR,45.2651,-0.3325,-244.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,41.4931,-4.0975,-244.4682,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,41.4931,-4.0975,-244.4682,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,27.4805,-11.7970,-250.7813,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0040,TROSPER_DDR,35.5940,-9.1791,-245.2857,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,35.7109,-9.1680,-245.1799,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,36.9769,-6.6305,-246.4514,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0115,V115_DDR,33.8688,-11.0059,-245.1841,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0116,V116_DDR,31.1840,-8.5182,-250.3566,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0118,V118_DDR,35.2654,-7.5412,-247.2522,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0125,V125_DDR,39.2876,-4.3978,-246.3734,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0126,V126_DDR,37.8685,-6.2528,-245.9375,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0129,V129_DDR,27.0906,-14.0670,-248.9012,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,34.4047,-11.1915,-244.4626,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0134,V134_DDR,38.2101,-5.8792,-245.9695,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0138,V138_DDR,37.6238,-6.5212,-245.9138,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,35.6523,-9.6333,-244.7732,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0143,V143_DDR,39.2872,-5.3494,-245.4222,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0149,V149_DDR,31.2609,-12.6459,-246.1520,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0150,V150_DDR,30.2564,-11.1700,-248.6324,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0155,V155_DDR,37.2100,-6.9517,-245.8971,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0156,V156_DDR,34.4047,-11.1915,-244.4626,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0166,V166_DDR,49.4761,5.3813,-245.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,35.7612,-9.4478,-244.8498,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,30.2564,-11.1700,-248.6324,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0170,V170_DDR,36.3339,-9.0199,-244.7050,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,31.7080,-13.5163,-244.8345,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0176,V176_DDR,30.2564,-11.1700,-248.6324,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0177,V177_DDR,39.7813,-17.9579,-232.3196,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,35.7654,-9.3698,-244.9236,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,33.5089,-12.5928,-243.9571,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0195,V195_DDR,44.3897,4.1680,-249.8371,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0197,V197_DDR,42.3055,-2.2559,-245.4974,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0198,V198_DDR,49.4761,5.3813,-245.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0208,V208_DDR,44.5980,4.3735,-249.8343,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0209,V209_DDR,44.5980,4.3735,-249.8343,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,40.0990,-4.3621,-245.5977,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0216,V216_DDR,35.7188,-9.1866,-245.1534,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0219,V219_DDR,37.2100,-6.9517,-245.8971,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0220,V220_DDR,30.2564,-11.1700,-248.6324,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0224,V224_DDR,34.7910,-10.2286,-245.0392,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0225,V225_DDR,34.8006,-10.2190,-245.0392,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0226,V226_DDR,34.7910,-10.2286,-245.0392,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0227,V227_DDR,34.7910,-10.2286,-245.0392,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0229,V229_DDR,27.6653,-11.8447,-250.5488,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0231,V231_DDR,37.1310,-4.9639,-247.9639,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0238,V238_DDR,30.7827,-18.3008,-240.9753,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.VOLT.0242,V242_DDR,37.4178,-6.7383,-245.9027,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,37.7643,-18.4318,-233.8627,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,25.3620,-15.3736,-249.3232,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,27.6906,-20.4083,-241.9599,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,57.6122,-14.5708,-217.8758,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,37.7643,-18.4318,-233.8627,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,52.8057,-12.8357,-224.4174,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,14.4896,-33.8321,-241.7371,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEHL7,OKGEHL7_H,35.1520,-9.8634,-245.0434,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEHL8,OKGEHSL1UN8_RA,35.1520,-9.8634,-245.0434,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEHL910,OKGEHSL1PLT2,35.1520,-9.8634,-245.0434,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,54.8609,-13.6453,-221.5526,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEMCC,OKGEMCCLAIPLT1,28.8794,-15.4383,-245.7411,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,35.7603,-8.3652,-245.9333,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,35.7603,-8.3652,-245.9333,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,35.3600,-8.7655,-245.9333,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,31.4975,-14.3563,-244.2050,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,30.0622,-15.7916,-244.2050,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,30.0518,-15.8020,-244.2050,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,31.4975,-14.3563,-244.2050,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGESM1,OKGESEMINOLEUN1_RA,32.7826,-10.6159,-246.6603,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGESM2,OKGESEMINOLEUN2_RA,32.9136,-11.0155,-246.1297,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGESM3,OKGESEMINOLEUN3_RA,32.9136,-11.0155,-246.1297,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGESO1,OKGESONR1UN1_RA,25.7652,-21.5760,-242.7176,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGESO2,OKGESONR1UN2_RA,26.2485,-21.2125,-242.5978,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,54.4407,-14.0655,-221.5526,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,41.3550,-15.5667,-233.1371,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGETINK5A,OKGETINK5UN1_RA,34.7619,-9.7828,-245.5141,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGETINK5B,OKGETINK5UN2_RA,34.7619,-9.7828,-245.5141,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,45.7025,-15.6814,-228.6749,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,26.1060,-22.0514,-241.9014,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,34.0798,-9.4454,-246.5336,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,25.3620,-15.3736,-249.3232,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE_OKGE,OKGE_LA,35.0613,-9.5544,-245.4431,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,22.3703,-17.3208,-250.3677,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,45.4491,-15.9348,-228.6749,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMLP,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,37.3902,-7.1531,-245.5155,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,33.3339,-10.2289,-246.4960,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_GENHUB,OMPA_GENHUB_H,29.7067,-15.6423,-244.7098,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_KAW,OKGEOMKAWUN2_RA,30.4745,-16.9977,-242.5866,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,33.0595,-13.7525,-243.2468,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,24.6799,-22.5946,-242.7844,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,43.8442,-13.5928,-232.6218,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,1.0999,-13.3664,-275.5925,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,38.6191,-6.9047,-244.5350,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,30.4989,-16.9733,-242.5866,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,30.4989,-16.9733,-242.5866,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_SPP,OMPA_SPP_LA,29.4213,-12.4701,-248.1674,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,37.7643,-18.4318,-233.8627,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ONETA,CSWSCALPINEUNONETA_1_RA,36.9827,-7.4673,-245.6088,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,36.9827,-7.4673,-245.6088,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,36.9827,-7.4673,-245.6088,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,36.9827,-7.4673,-245.6088,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,ONT,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,33.0094,-7.9142,-249.1352,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,33.0094,-7.9142,-249.1352,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,33.0094,-7.9142,-249.1352,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,33.0094,-7.9142,-249.1352,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,33.0094,-7.9142,-249.1352,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,33.0094,-7.9142,-249.1352,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,33.0094,-7.9142,-249.1352,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,33.0094,-7.9142,-249.1352,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,33.0094,-7.9142,-249.1352,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,32.5241,-8.4246,-249.1101,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,33.0591,-7.8896,-249.1101,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,31.3071,-9.5553,-249.1964,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,32.9407,-7.9634,-249.1547,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,32.9407,-7.9634,-249.1547,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD_GLDN,OPPD_GLDN_LA,32.9719,-7.9489,-249.1380,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD_GLDN2,OPPD_GLDN2_LA,33.3031,-7.6345,-249.1212,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,30.8646,-8.8724,-250.3218,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD_NC_HST,OPPD_NC_HST_LA,28.0810,-13.2242,-248.7536,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD_NO_HST,OPPD_NO_HST_LA,32.9315,-8.0172,-249.1101,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD_OPPD,OPPD_LA,33.9066,-7.0082,-249.1440,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD_PAPIO,OPPD_PAPIO_LA,33.0940,-7.8241,-249.1407,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,33.0609,-7.8516,-249.1463,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OTP,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,OVEC,OVEC,34.6484,-7.6777,-247.7327,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PARAGOULD,PARAGOULD_LA,35.0811,-7.7858,-247.1918,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,PENSACOLA_1,GRDAPENSA1UN1_RA,37.1478,-7.2409,-245.6701,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PENSACOLA_2,GRDAPENSA1UN2_RA,37.1478,-7.2409,-245.6701,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PENSACOLA_3,GRDAPENSA1UN3_RA,37.1478,-7.2409,-245.6701,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PENSACOLA_4,GRDAPENSA1UN4_RA,37.3441,-7.0502,-245.6645,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PENSACOLA_5,GRDAPENSA1UN5_RA,37.3441,-7.0502,-245.6645,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PENSACOLA_6,GRDAPENSA1UN6_RA,37.3441,-7.0502,-245.6645,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PIGGOTT,PIGGOTT_LA,34.9837,-7.8438,-247.2313,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PJM,PJM,34.6187,-7.5852,-247.8549,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PLUM,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,POPLARBLUFF,POPLARBLUFF_LA,35.0153,-7.8623,-247.1812,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,46.7590,7.1111,-250.4109,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,46.7590,7.1111,-250.4109,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,46.3702,6.5844,-250.2730,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,46.3702,6.5844,-250.2730,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,68.0987,28.0483,-250.0084,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,68.1149,28.0645,-250.0084,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,45.6382,5.9193,-250.3399,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,44.4504,5.2899,-250.8983,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,25.6266,-20.5587,-243.8735,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,38.5710,-6.2838,-245.2040,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,27.8645,-14.8209,-247.3734,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,34.6886,-10.6127,-244.7574,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,39.1205,-4.8239,-246.1144,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,39.9254,-4.3421,-245.7913,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,36.4485,-4.6257,-248.9846,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,53.1017,13.1296,-250.0868,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,38.5389,-2.4112,-249.1087,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,54.7331,14.1841,-249.5098,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,52.8091,12.3805,-249.6302,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,41.4482,0.4619,-249.0725,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,PUPP,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,RCEAST,RCEAST,32.3449,-5.5426,-252.1713,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SALINA_1,GRDASALINA1UN1_RA,37.7102,-6.6771,-245.6715,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SALINA_2,GRDASALINA1UN2_RA,37.7102,-6.6771,-245.6715,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SALINA_3,GRDASALINA1UN3_RA,37.7102,-6.6771,-245.6715,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SALINA_4,GRDASALINA1UN4_RA,37.7102,-6.6771,-245.6715,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SALINA_5,GRDASALINA1UN5_RA,37.7102,-6.6771,-245.6715,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SALINA_6,GRDASALINA1UN6_RA,37.7102,-6.6771,-245.6715,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SARPY_1,OPPDSARPYUN1_RA,32.8012,-8.1698,-249.0878,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SARPY_2,OPPDSARPYUN2_RA,33.4327,-7.5398,-249.0864,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SARPY_3,OPPDSARPYUN3_RA,32.1280,-8.8527,-249.0781,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SARPY_4,OPPDSARPYUN4_RA,32.1280,-8.8527,-249.0781,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SARPY_5,OPPDSARPYUN5_RA,32.1280,-8.8527,-249.0781,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SC,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SCEG,VACS,35.4043,-7.2616,-247.3929,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SCSE,SCSE,24.1238,-9.3976,-256.5374,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SEC,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,20.2002,-20.1274,-249.7312,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,20.2002,-20.1274,-249.7312,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,20.2002,-20.1274,-249.7312,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,5.5880,-1.7672,-282.7036,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,20.2002,-20.1274,-249.7312,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,6.1258,-16.2971,-267.6359,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,14.1210,-17.8768,-258.0610,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,14.1210,-17.8768,-258.0610,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,31.3255,-12.7693,-245.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,31.8275,-19.6153,-238.6160,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,34.1579,-5.1488,-250.7521,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,-1.8540,-6.4516,-285.4612,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,14.9576,-7.7522,-267.3490,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,19.9869,-20.3407,-249.7312,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,13.6427,-8.5351,-267.8810,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,2.4847,-15.4411,-272.1330,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,11.2301,-16.4029,-262.4258,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,-2.0528,-14.5429,-277.5687,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,-2.0398,-14.5299,-277.5687,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,-2.0398,-14.5299,-277.5687,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,-2.0398,-14.5299,-277.5687,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,-3.6121,-15.5145,-278.1564,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,6.1258,-16.2971,-267.6359,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI_SECI,SECI_LA,9.2043,-8.6211,-272.2334,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,25.9506,-15.2154,-248.8928,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,25.9506,-15.2154,-248.8928,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,31.3255,-12.7693,-245.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SEHA,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,45.4491,-15.9348,-228.6749,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SERU,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SETH,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SGE,SGE,22.8649,-11.4643,-255.7296,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SMEP,MISO,36.3942,-5.5728,-248.0918,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SOCO,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPA,SPA,35.8570,-7.6015,-246.6003,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPC,SPC,57.5623,17.3350,-249.8315,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPPNORTH_HUB,SPPNORTH_H,36.0854,-3.8271,-250.1463,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPPSOUTH_HUB,SPPSOUTH_H,30.6668,-11.1922,-248.1999,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,37.2467,-6.6629,-246.1492,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,37.3156,-6.5940,-246.1492,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,38.1001,-5.7621,-246.1966,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,38.1001,-5.7621,-246.1966,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_NIXA,SPRM_NIXA_LA,38.3908,-5.5247,-246.1433,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_SPRM,SPRM_LA,39.4996,-4.4162,-246.1430,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,37.3590,-6.5826,-246.1172,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,37.3590,-6.5826,-246.1172,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,36.8404,-7.1012,-246.1172,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,37.3590,-6.5826,-246.1172,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,2201.6226,33.3913,1878.1725,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,2271.7646,30.5247,1951.1811,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,1037.5818,-0.4177,747.9407,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,1037.5818,-0.4177,747.9407,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,2160.9756,21.2001,1849.7167,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,2179.2436,40.2452,1848.9396,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,2220.8262,46.4710,1884.2963,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,2193.5625,43.5283,1859.9754,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,2129.6289,14.6673,1824.9028,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,2169.0211,36.0657,1842.8966,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,2172.9433,39.6522,1843.2323,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,2172.9430,39.6519,1843.2323,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,2169.0211,36.0657,1842.8966,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,1038.5854,1.2809,747.2457,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,2271.7646,30.5247,1951.1811,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,1052.6651,3.5950,759.0113,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,1119.3692,-6.8681,836.1785,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,1088.0850,7.2444,790.7818,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,1071.8310,13.9381,767.8341,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,1066.8885,5.4790,771.3507,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,1175.2443,-9.4130,894.5985,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,1175.2440,-9.4133,894.5985,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,1175.2440,-9.4133,894.5985,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,1175.2440,-9.4133,894.5985,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GRID.WRAB,WRAB_DDR,1030.5700,13.4068,727.1044,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,1175.2440,-9.4133,894.5985,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,2120.1068,21.0276,1809.0204,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,2120.1068,21.0276,1809.0204,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,2081.4619,21.3493,1770.0538,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,2081.4619,21.3493,1770.0538,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,2081.4619,21.3493,1770.0538,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,2120.1068,21.0276,1809.0204,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,1009.8252,-0.7101,720.4765,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,1009.8029,-0.7101,720.4542,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,1009.8480,-0.7040,720.4932,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,1023.4504,2.2135,731.1781,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.HOBBS.CC,SPSHOBBSPLT1,2168.8980,36.2254,1842.6138,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.JONES1,SPSJONESSUBUN1_RA,2129.1261,14.4305,1824.6368,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.JONES2,SPSJONESSUBUN2_RA,2129.1299,14.4343,1824.6368,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.JONES3,SPSJONESSUBUN3_RA,2129.1273,14.4317,1824.6368,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.JONES4,SPSJONESSUBUN4_RA,2129.1273,14.4317,1824.6368,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,2170.0379,38.7412,1841.2379,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,2169.3866,36.4256,1842.9022,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,2169.3872,36.4262,1842.9022,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,45.8549,-15.5290,-228.6749,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,1011.3968,-1.9364,723.2744,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,1011.3968,-1.9364,723.2744,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,1010.2325,-0.6440,720.8177,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,1030.5700,13.4068,727.1044,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,1119.1552,-1.5837,830.6801,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,1053.3257,0.2209,763.0460,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,-15.5204,-10.6295,-294.9497,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,1020.6387,1.9115,728.6684,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.PLANTX1,SPS.PLANTX1_H,2226.0163,32.0435,1903.9140,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.PLANTX2,SPS.PLANTX2_H,2226.0163,32.0435,1903.9140,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,2220.1356,31.1989,1898.8779,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,2154.1283,20.7523,1843.3172,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,1148.9984,-9.0707,868.0103,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,2223.6701,49.3150,1884.2963,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,2155.0451,21.6691,1843.3172,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,1040.0714,2.7669,747.2457,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,2198.7933,36.8431,1871.8914,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,2195.5868,45.5526,1859.9754,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,2198.7933,36.8431,1871.8914,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,2202.1792,40.5786,1871.5418,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,1062.4115,-0.4339,772.7866,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,2190.8725,56.0467,1844.7670,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,2191.8331,57.0073,1844.7670,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,2184.7709,50.6219,1844.0902,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,2172.7629,39.8409,1842.8632,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,2194.7582,56.7473,1847.9521,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,-0.9771,-14.2917,-276.7442,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,1029.0016,12.1253,726.8175,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,2208.2672,32.8620,1885.3464,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,2208.2672,32.8620,1885.3464,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,2198.7933,36.8431,1871.8914,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,2131.2017,15.4003,1825.7426,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0006,SPS.VOLT.0006_H,2175.3816,45.8160,1839.5068,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0023,SPS.VOLT.0023_H,2226.1735,38.9971,1897.1176,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0025,SPS.VOLT.0025_H,2215.8270,41.0444,1884.7238,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0033,SPS.VOLT.0033_H,2231.5910,22.2943,1919.2379,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0045,SPS.VOLT.0045_H,2190.8725,56.0467,1844.7670,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0046,SPS.VOLT.0046_H,2202.9252,66.2652,1846.6012,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0047,SPS.VOLT.0047_H,2196.9466,60.2866,1846.6012,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0052,SPS.VOLT.0052_H,2157.5810,24.2050,1843.3172,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0113,SPS.VOLT.0113_H,2219.4660,45.0051,1884.4021,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0136,SPS.VOLT.0136_H,1149.6082,-4.4332,863.9826,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0137,SPS.VOLT.0137_H,1148.9956,-4.9775,863.9143,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0163,V163_DDR,1033.6688,7.9307,735.6793,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0168,V168_DDR,1132.6980,-6.3174,848.9566,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0180,V180_DDR,2202.9252,66.2652,1846.6012,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0181,V181_DDR,1150.8582,-5.8655,866.6649,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0182,V182_DDR,2194.7817,57.2791,1847.4438,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0199,V199_DDR,2173.3609,43.4123,1839.8898,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0200,V200_DDR,2179.1871,45.3598,1843.7685,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.VOLT.0235,V235_DDR,1119.1552,-1.5837,830.6801,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,2220.8262,46.4710,1884.2963,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,2193.5625,43.5283,1859.9754,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,983.0310,6.0085,686.9637,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,2232.2597,22.9630,1919.2379,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS_SPS,SPS_LA,1882.8597,36.3569,1556.4441,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,2194.1260,33.2880,1870.7793,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,SSCN_NPPD,SSCN_NPPD_LA,34.1971,-6.2711,-249.5906,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,34.8135,-7.9805,-247.2648,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,34.8135,-7.9805,-247.2648,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,TAL,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,TEC,SOUC,35.6875,-6.9891,-247.3823,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,37.9827,-1.4243,-250.6518,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,TVA,TVA,35.1063,-7.5481,-247.4044,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,UCUHUB,UCUHUB_H,22.0419,-18.0805,-249.9364,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,UCUHUB17,UCUHUB17_H,16.7929,-17.5598,-255.7061,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,UCUHUB18,UCUHUB18_H,20.2767,-17.7395,-252.0426,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,UCUHUB19,UCUHUB19_H,21.1913,-18.7082,-250.1593,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,UCUHUB20,UCUHUB20_H,20.8236,-18.8586,-250.3766,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,UCUHUB21,UCUHUB21_H,19.9246,-18.9454,-251.1887,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,UCUHUB22,UCUHUB22_H,20.6977,-19.0419,-250.3191,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,UCUHUB23,UCUHUB23_H,20.8085,-18.9960,-250.2543,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,UCUHUB24,UCUHUB24_H,20.6341,-19.2404,-250.1844,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,62.5864,22.3633,-249.8357,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,62.5864,22.3633,-249.8357,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,44.6710,4.4604,-249.8482,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,44.6710,4.4604,-249.8482,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,45.0921,4.7297,-249.6964,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,45.8069,6.0531,-250.3050,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,45.8069,6.0531,-250.3050,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,62.5864,22.3633,-249.8357,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,48.7081,8.3360,-249.6867,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,53.0656,12.7506,-249.7438,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,37.3133,-3.6048,-249.1407,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,32.7040,-7.1890,-250.1658,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,61.9449,21.8430,-249.9569,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,61.9449,21.8430,-249.9569,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,30.1404,-10.2874,-249.6310,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,35.5756,-5.0723,-249.4109,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,50.4653,9.9706,-249.5641,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,35.6824,-5.1618,-249.2146,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,45.5075,4.6103,-249.1616,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,35.1160,-5.4859,-249.4569,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,34.8788,-5.5490,-249.6310,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,34.8788,-5.5490,-249.6310,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,36.4198,-4.1598,-249.4792,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,33.2736,-6.4899,-250.2953,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,52.5452,11.6425,-249.1561,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,53.0910,12.8818,-249.8496,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,53.0910,12.8818,-249.8496,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,53.0910,12.8818,-249.8496,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,53.0910,12.8818,-249.8496,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,53.0910,12.8818,-249.8496,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,53.0910,12.8818,-249.8496,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,65.6258,25.3999,-249.8329,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,42.8485,2.5544,-249.7647,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,42.8268,2.5327,-249.7647,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,20.5117,-13.4164,-256.1307,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,42.1495,1.6785,-249.5878,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,52.2996,12.0584,-249.8176,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,32.7395,-7.9446,-249.3747,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,28.9031,-10.6292,-250.5265,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,38.3481,-2.0825,-249.6282,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,59.2723,19.0854,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,59.2723,19.0854,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,59.2404,19.0535,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,59.2723,19.0854,-249.8719,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,60.4249,20.2143,-249.8482,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,60.4249,20.2143,-249.8482,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,60.4249,20.2143,-249.8482,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,60.4249,20.2143,-249.8482,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,60.4249,20.2143,-249.8482,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,60.4249,20.2143,-249.8482,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,60.4249,20.2143,-249.8482,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,32.2935,-7.9380,-249.8273,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,55.3714,15.0299,-249.7173,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,41.6662,1.0921,-249.4847,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,41.6662,1.0921,-249.4847,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,41.5895,1.3469,-249.8162,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,41.5895,1.3469,-249.8162,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,46.4678,6.1737,-249.7647,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,45.6371,5.5714,-249.9931,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,39.1497,-1.7266,-249.1825,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,33.0179,-6.6049,-250.4360,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,35.6897,-5.4526,-248.9165,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,45.0921,4.7297,-249.6964,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,45.0921,4.7297,-249.6964,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,35.6824,-5.1618,-249.2146,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,32.5036,-5.3992,-252.1560,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,37.5636,-2.6776,-249.8176,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,29.8064,-9.8791,-250.3733,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,36.3948,-4.0790,-249.5850,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.FSE,WAUE.FSE_H,32.7428,-6.3599,-250.9561,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,46.6316,6.7511,-250.1783,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,46.1606,6.3205,-250.2187,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,26.6872,-13.1264,-250.2452,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,26.4275,-13.4878,-250.1435,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,41.8429,1.4958,-249.7117,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,40.7613,0.4156,-249.7131,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,31.8564,-8.3263,-249.8761,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,32.7040,-7.1890,-250.1658,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,27.4214,-10.8477,-251.7897,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,26.1560,-14.9835,-248.9193,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,25.1369,-16.0026,-248.9193,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,24.9001,-16.2394,-248.9193,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,37.3996,-3.0993,-249.5599,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,32.5036,-5.3992,-252.1560,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,39.9748,-1.0672,-249.0168,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,37.3145,-3.5520,-249.1923,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,51.9287,11.0260,-249.1561,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,40.4627,-0.6197,-248.9764,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,39.9528,-0.9680,-249.1380,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,28.7949,-12.5479,-248.7160,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,44.4644,3.5617,-249.1561,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,34.5841,-6.2755,-249.1992,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,32.7395,-7.9446,-249.3747,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,46.9997,5.7056,-248.7647,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,35.2859,-5.5583,-249.2146,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,43.0321,1.7185,-248.7452,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,41.0563,0.0589,-249.0614,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,31.1755,-9.8568,-249.0265,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NTWK,WAUE.NTWK_H,42.1165,1.7815,-249.7238,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,44.9817,4.5929,-249.6700,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,44.9817,4.5929,-249.6700,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,34.2958,-5.5123,-250.2507,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,33.2830,-6.9122,-249.8636,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,37.9228,-2.6889,-249.4471,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,34.2958,-5.5123,-250.2507,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,45.4344,5.0149,-249.6393,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,35.4486,-4.6645,-249.9457,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,32.7395,-7.9446,-249.3747,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,39.1708,-1.0426,-249.8454,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,51.7562,11.6431,-249.9457,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,21.0465,-18.1042,-250.9081,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,20.2574,-18.9852,-250.8162,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,43.5869,3.3680,-249.8399,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,32.9775,-5.6691,-251.4122,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,36.7736,-3.9147,-249.3705,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,33.5675,-6.3186,-250.1727,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,33.0179,-6.6049,-250.4360,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.VOLT.0152,V152_DDR,68.1792,27.9352,-249.8148,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE.VOLT.0172,V172_DDR,61.4523,21.2459,-249.8524,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_BEPM,WAUE_BEPM_LA,51.9505,11.6801,-249.7884,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,40.0336,-0.9791,-249.0462,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,40.7059,-0.3765,-248.9764,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_EWA,WAUE_EWA_LA,33.2307,-4.6903,-252.1378,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,37.8161,-2.5448,-249.6979,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_HMMU,WAUE_HMMU_LA,36.1520,-4.9193,-248.9875,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,34.6944,-6.6067,-248.7577,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_MECB,WAUE_MECB_LA,37.7621,-3.2739,-249.0228,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_MMPA,WAUE_MMPA_LA,49.7021,9.0765,-249.4332,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_MRES,WAUE_MRES_LA,40.3774,-0.0472,-249.6342,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,64.3891,24.1131,-249.7828,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,46.6316,6.7511,-250.1783,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,39.2938,-0.9087,-249.8563,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_OTP,WAUE_OTP_LA,60.5826,20.1770,-249.6532,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_OTPW,WAUE_OTPW_LA,50.2165,9.6608,-249.5030,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM,WAUE_UGPM_LA,38.3305,-1.8793,-249.8490,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,48.6019,8.3949,-249.8518,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,39.2432,-1.6665,-249.1490,290.0587\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,43.5325,3.6876,-250.2139,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,33.2307,-4.6903,-252.1378,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,36.1520,-4.9193,-248.9875,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,38.4080,-1.9695,-249.6813,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,46.6316,6.7511,-250.1783,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,49.7021,9.0765,-249.4332,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,42.5316,2.2065,-249.7337,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,36.8090,-3.2046,-250.0453,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,64.4375,24.0194,-249.6407,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,38.3094,-17.7460,-234.0034,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,29.7375,-19.1274,-241.1939,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,8.2622,-13.2262,-268.5704,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,38.9208,-3.1476,-247.9904,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,38.9208,-3.1476,-247.9904,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,4.0471,-25.4173,-260.5944,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,40.0750,-2.1828,-247.8010,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,39.5685,-2.9094,-247.5809,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,13.5299,-19.8132,-256.7157,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,13.5352,-19.8079,-256.7157,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,13.5624,-19.7807,-256.7157,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,15.0560,-18.2871,-256.7157,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,15.0560,-18.2871,-256.7157,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,15.0560,-18.2871,-256.7157,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,15.0560,-18.2871,-256.7157,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,15.0560,-18.2871,-256.7157,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,15.7553,-17.7967,-256.5068,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,-15.5204,-10.6295,-294.9497,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,8.0699,-24.4000,-257.5889,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,41.5969,-15.5504,-232.9115,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,2221.0290,46.6739,1884.2963,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_ENMC,WFEC_ENMC_LA,2192.9521,46.6614,1856.2319,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,24.6834,-23.5325,-241.8429,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,34.2303,-7.3646,-248.4639,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,2168.1638,36.4451,1841.6599,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,38.0042,-18.0512,-234.0034,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,38.3094,-17.7460,-234.0034,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,38.3094,-17.7460,-234.0034,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_OKGE,WFEC_OKGE_LA,36.1274,-9.3409,-244.5906,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,40.9760,-0.3899,-248.6929,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,0.0000,-12.8076,-277.2512,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,6.1226,-12.2781,-271.6581,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_WFEC,WFEC_LA,32.8466,-7.0862,-250.1261,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,2168.1638,36.4451,1841.6599,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,29.3389,-8.0333,-252.6866,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,5.6014,-11.2590,-273.1984,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,22.2531,-22.6899,-245.1158,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,22.2531,-22.6899,-245.1158,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,22.1273,-22.8157,-245.1158,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,22.1273,-22.8157,-245.1158,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,22.2513,-22.6917,-245.1158,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,22.2505,-22.6925,-245.1158,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,22.2505,-22.6925,-245.1158,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,35.2427,-9.5095,-245.3066,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,22.8166,-21.0192,-246.2230,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,24.4188,-23.5102,-242.1298,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,24.4188,-23.5102,-242.1298,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,24.4188,-23.5102,-242.1298,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,30.0430,-19.8121,-240.2037,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,30.0430,-19.8121,-240.2037,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.GEEC.GT1,WRGORDUNG1_RA,25.2188,-22.2659,-242.5741,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.GEEC.GT2,WRGORDUNG2_RA,25.2188,-22.2659,-242.5741,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.GEEC.GT3,WRGORDUNGT3_RA,24.3180,-23.1667,-242.5741,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,22.8166,-21.0192,-246.2230,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,25.4546,-17.9926,-246.6116,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.HEC.GT1,WRHECGTUN32_RA,25.6409,-18.3342,-246.0837,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.HEC.GT2,WRHECGTUN33_RA,25.7775,-18.1976,-246.0837,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.HEC.GT3,WRHECGTUN34_RA,25.8291,-18.1460,-246.0837,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.HEC.GT4,WRHECGTUN35_RA,25.8438,-18.1313,-246.0837,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,25.4546,-17.9926,-246.6116,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,19.8243,-20.5033,-249.7312,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,21.3416,-23.0151,-245.7021,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.JEC.1,WRJEFFUN10_RA,21.8437,-22.1968,-246.0183,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.JEC.2,WRJEFFUN11_RA,20.4888,-23.5475,-246.0225,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.JEC.3,WRJEFFUN12_RA,21.7922,-22.2441,-246.0225,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,24.4655,-22.7351,-242.8582,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,25.8023,-22.3467,-241.9098,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,25.8023,-22.3467,-241.9098,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.LEC.4,WRLECUN26_RA,24.5232,-19.3753,-246.1603,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.LEC.5,WRLECUN27_RA,26.0979,-17.9162,-246.0447,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MCPH.CT1,WRCMCPHUN37_RA,27.1017,-16.2898,-246.6673,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MCPH.CT2,WRCMCPHUN38_RA,27.1017,-16.2898,-246.6673,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MCPH.CT3,WRCMCPHUN48_RA,27.0547,-16.3368,-246.6673,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MCPH.CT4,WRCJOHNUN1_RA,27.7315,-15.6391,-246.6882,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,25.9506,-15.2154,-248.8928,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,25.9506,-15.2154,-248.8928,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,19.3383,-4.5720,-266.1485,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,29.1797,-7.5310,-253.3481,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,29.1797,-7.5310,-253.3481,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,29.8326,-12.9656,-247.2606,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,25.9506,-15.2154,-248.8928,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,20.7327,-21.1937,-248.1324,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,23.0947,-20.6366,-246.3275,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,25.7177,-22.4313,-241.9098,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,39.7318,-2.9063,-247.4207,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,30.0160,-12.5190,-247.5238,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.READ.READ,WREMPECUNREADINGWF_RA,22.2505,-22.6925,-245.1158,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,15.6955,-30.0511,-244.3122,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,25.4546,-17.9926,-246.6116,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,22.8166,-21.0192,-246.2230,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,27.5643,-19.8772,-242.6173,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.THAYERLD,WR.THAYERLD_LA,35.3650,-7.6950,-246.9988,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0102,WR.VOLT.0102_H,27.7239,-19.7120,-242.6229,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0106,V106_DDR,27.5475,-19.6921,-242.8192,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0139,WR.VOLT.0139_H,27.8407,-15.8099,-246.4082,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0141,WR.VOLT.0141_H,26.7821,-16.7362,-246.5405,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0146,WR.VOLT.0146_H,27.2514,-16.6150,-246.1924,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0147,WR.VOLT.0147_H,27.2514,-16.6150,-246.1924,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0148,WR.VOLT.0148_H,26.2178,-17.2907,-246.5503,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0153,WR.VOLT.0153_H,29.6926,-17.3701,-242.9961,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0157,V157_DDR,26.9803,-16.8959,-246.1826,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0158,V158_DDR,27.2514,-16.6150,-246.1924,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0159,WR.VOLT.0159_H,27.2514,-16.6150,-246.1924,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0165,WR.VOLT.0165_H,26.0503,-21.1015,-242.9070,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0173,V173_DDR,28.0588,-15.0806,-246.9194,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0174,V174_DDR,27.2294,-19.8584,-242.9710,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0184,V184_DDR,25.4320,-21.7505,-242.8763,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0185,WR.VOLT.0185_H,27.4649,-19.9195,-242.6744,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0186,V186_DDR,26.7655,-20.6760,-242.6173,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0187,WR.VOLT.0187_H,26.0955,-21.1789,-242.7844,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0188,WR.VOLT.0188_H,27.8055,-19.5775,-242.6758,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0189,WR.VOLT.0189_H,31.5379,-14.1920,-244.3289,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0190,WR.VOLT.0190_H,23.8793,-21.2155,-244.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0191,WR.VOLT.0191_H,22.9514,-21.9972,-245.1102,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0192,WR.VOLT.0192_H,22.9514,-21.9972,-245.1102,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0196,WR.VOLT.0196_H,23.8793,-21.2155,-244.9640,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0245,V245_DDR,27.4774,-19.9126,-242.6688,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.VOLT.0248,V248_DDR,27.5475,-19.6921,-242.8192,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,24.2258,-22.8313,-243.0017,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,26.2635,-17.5695,-246.2258,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.WOLF,WRWOLFUN15_RA,14.4277,-31.4484,-244.1827,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,19.8243,-20.5033,-249.7312,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,31.0762,-13.6760,-245.3066,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,24.4188,-23.5102,-242.1298,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,24.4188,-23.5102,-242.1298,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,24.4188,-23.5102,-242.1298,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,24.4188,-23.5102,-242.1298,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KPP_NITS,WR_KPP_NITS_LA,25.0803,-20.3594,-244.6191,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,26.8259,-16.7049,-246.5280,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,27.1940,-19.9509,-242.9139,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,27.1940,-19.9509,-242.9139,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,27.1940,-19.9509,-242.9139,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,27.1940,-19.9509,-242.9139,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,25.3703,-18.5880,-246.1005,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,25.3703,-18.5880,-246.1005,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,25.3703,-18.5880,-246.1005,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,25.3703,-18.5880,-246.1005,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,25.3703,-18.5880,-246.1005,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,25.3703,-18.5880,-246.1005,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,28.6597,-18.9016,-242.4975,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,28.6597,-18.9016,-242.4975,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,25.7910,-21.7717,-242.4961,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,25.7910,-21.7717,-242.4961,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_MIDW,WR_MIDW_LA,27.7143,-6.9383,-255.4063,290.0589\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,35.3444,-7.7098,-247.0046,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,29.9573,-13.7409,-246.3606,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,29.2458,-8.5568,-252.2562,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_SEG,WR_SEG_LA,31.7675,-12.9608,-245.3305,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,WR_WR,WR_LA,27.3189,-17.8448,-244.8951,290.0588\n03/31/2025 08:40:00,03/31/2025 13:40:00,YAD,VACS,35.4043,-7.2616,-247.3929,290.0588\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_SPP/RTBM-LMP-SL-202503310845.csv",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_SPP/RTBM-LMP-SL-202503310850.csv",
    "content": "Interval,GMTIntervalEnd,Settlement Location,Pnode,LMP,MLC,MCC,MEC\n03/31/2025 08:50:00,03/31/2025 13:50:00,AEC,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,AECC_CSWS,CSWS_AECC_LA,29.1745,-0.5457,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,29.3360,-0.3841,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,28.5509,-1.1692,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,29.0536,-0.6665,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,28.8504,-0.8697,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,AECC_HYDRO13,CSWSLD13UN1_RA,28.2953,-1.4249,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,29.3756,-0.3445,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,AECI,AECI,28.8137,-0.9064,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,AEPM_CSWS,CSWS_LA,29.4825,-0.2376,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ALTW,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,AMRN,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ANTELOPE,SPSANTELOPEUNANT1_RA,32.4594,2.0760,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BBA,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BCA,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BEPM.ER01.DDR,ER01_DDR,28.1029,-1.6172,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BEPM_ER01,BEPM_ER01_LA,28.1029,-1.6172,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,31.5667,1.8466,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,30.0694,0.3493,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BEPM_UM01,BEPM_UM01_LA,31.9684,2.2483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BLKW,BLKW,34.2027,3.8193,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,27.0714,-2.6487,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,27.0714,-2.6487,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,27.3159,-2.4042,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,27.1120,-2.6081,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BRAZ,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BUBA,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,28.4702,-1.2499,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,28.1387,-1.5814,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,28.1387,-1.5814,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,28.1387,-1.5814,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,28.1387,-1.5814,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,28.1387,-1.5814,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,27.6068,-2.1133,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,28.8372,-0.8829,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,28.8372,-0.8829,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CLEC,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,29.0013,-0.7188,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,COWP,COWP_LA,28.9281,-0.7920,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,28.9281,-0.7920,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,28.9281,-0.7920,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CPLE,VACS,28.9771,-0.7430,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CPLW,VACS,28.9771,-0.7430,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,28.8929,-0.8272,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,28.8929,-0.8272,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,28.8929,-0.8272,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,28.8929,-0.8272,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CRTH_SPA,WRCRTH_SPA_LA,28.5117,-1.2084,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,30.1198,0.3997,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,28.2776,-1.4426,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,29.3756,-0.3445,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,29.0536,-0.6665,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWJLSTALL,CSWSSTALL_PPPLT1,30.1144,0.3943,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,30.0921,0.3720,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,30.0600,0.3399,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,30.0600,0.3399,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWMATTISON1,CSWSMATTISONUN1_RA,28.7954,-0.9247,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWMATTISON2,CSWSMATTISONUN2_RA,28.7954,-0.9247,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWMATTISON3,CSWSMATTISONUN3_RA,28.7990,-0.9211,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWMATTISON4,CSWSMATTISONUN4_RA,28.7990,-0.9211,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,29.3756,-0.3445,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWNARROWS1,CSWSNARROWSUN1_RA,29.7898,0.0697,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,28.6182,-1.1019,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,28.4141,-1.3060,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,28.8199,-0.9002,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,28.8853,-0.8348,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,28.7606,-0.9595,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,28.7538,-0.9664,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,28.7538,-0.9664,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,28.0220,-1.6981,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,28.7420,-0.9781,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,28.7690,-0.9511,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,28.4103,-1.3098,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,28.4108,-1.3093,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,28.2985,-1.4216,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.GRID.CDL1,CDL1_DDR,29.0523,-0.6678,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,28.3106,-1.4095,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,27.6400,-2.0801,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,29.0523,-0.6678,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.NUEN.CSI1,CSI1_DDR,29.2784,-0.4417,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.NUEN.CSI2,CSI2_DDR,29.2885,-0.4316,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.NUEN.CSI3,NCSI3_DDR,28.9362,-0.7839,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.NUEN.GAZA,GAZA_DDR,29.0523,-0.6678,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,29.6918,-0.0283,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.NUEN.T201,NT201_DDR,29.0844,-0.6357,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,28.1642,-1.5559,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,28.1642,-1.5559,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,29.3756,-0.3445,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,30.4475,0.7274,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,28.2985,-1.4216,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,28.2985,-1.4216,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,28.0676,-1.6525,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,28.4108,-1.3093,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,29.8192,0.0990,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,28.8284,-0.8917,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,28.8284,-0.8917,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,28.3935,-1.3266,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,28.4980,-1.2221,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,28.6916,-1.0285,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,30.0726,0.3525,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,29.0237,-0.6964,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,30.1438,0.4237,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,31.4706,1.7505,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,29.1128,-0.6073,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0056,PRYORCRK_DDR,29.2885,-0.4316,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0057,OKMU_DDR,29.2232,-0.4969,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0060,LEHIGH_DDR,29.5056,-0.2145,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0086,WARRENM_DDR,29.0162,-0.7039,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,30.5421,0.8220,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,29.1215,-0.5986,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0121,V121_DDR,30.0726,0.3525,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0122,V122_DDR,29.0743,-0.6459,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0124,V124_DDR,28.9534,-0.7667,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0135,V135_DDR,29.1076,-0.6125,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0144,V144_DDR,28.7578,-0.9623,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0145,V145_DDR,28.5861,-1.1340,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,30.1076,0.3875,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,29.5021,-0.2180,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0175,V175_DDR,28.9362,-0.7839,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,29.5021,-0.2180,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,29.6367,-0.0834,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,29.1076,-0.6125,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,29.0922,-0.6279,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,29.0182,-0.7019,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,28.8052,-0.9149,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,28.9173,-0.8028,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,29.0922,-0.6279,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0211,V211_DDR,30.3770,0.6569,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,29.1349,-0.5853,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0213,V213_DDR,29.0333,-0.6868,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0215,V215_DDR,29.0766,-0.6435,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0217,V217_DDR,29.1127,-0.6074,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0218,V218_DDR,28.8197,-0.9004,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0228,V228_DDR,29.0255,-0.6947,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0232,V232_DDR,29.0816,-0.6386,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0233,V233_DDR,29.1095,-0.6106,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0240,V240_DDR,28.9998,-0.7203,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0244,V244_DDR,29.0922,-0.6279,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0246,MDT1_DDR,29.6918,-0.0283,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0249,V249_DDR,29.0851,-0.6350,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0250,V250_DDR,28.3363,-1.3838,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0251,V251_DDR,28.9548,-0.7653,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.VOLT.0252,V252_DDR,28.8052,-0.9149,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,28.0542,-1.6659,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,27.6516,-2.0685,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,28.0005,-1.7197,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,29.9193,0.1992,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,28.0352,-1.6849,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,28.4841,-1.2360,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,28.4841,-1.2360,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,28.4618,-1.2583,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,27.7526,-1.9676,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,27.7526,-1.9676,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,29.3756,-0.3445,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,30.1333,0.4132,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,29.0572,-0.6629,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,29.0165,-0.7036,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,29.1904,-0.5297,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,29.1904,-0.5297,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWWELSH1,CSWSWELSHUN1_RA,29.5602,-0.1599,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWWELSH3,CSWSWELSHUN3_RA,29.5602,-0.1599,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWWILKES1,CSWSWILKESUN1_RA,29.7249,0.0048,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWWILKES2,CSWSWILKESUN2_RA,29.7249,0.0048,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,CSWWILKES3,CSWSWILKESUN3_RA,29.6952,-0.0249,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,28.4096,-1.3105,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,DENL,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,DERS,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,DOE,DOE,28.9228,-0.7973,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,27.6895,-2.0307,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,DPC,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,DUK,VACS,28.9771,-0.7430,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDDY,EDDY,35.0638,4.6804,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,28.1660,-1.5541,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,28.0747,-1.6454,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,27.9920,-1.7281,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE.SLCC,EDESTL4391_PLT,27.5627,-2.1574,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE.VOLT.0234,EDE.VOLT.0234_H,27.9724,-1.7477,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,27.7735,-1.9466,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_EC_01,EDELAR3821UN1_RA,28.1660,-1.5541,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_EC_02,EDELAR3821UN2_RA,28.1372,-1.5829,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_EC_03,EDELAR3821UN3_RA,28.1660,-1.5541,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_EC_04,EDELAR3821UN4_RA,28.1660,-1.5541,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_EDE,EDE_LA,28.8122,-0.9079,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_ERW,EDEERWFUNG1_RA,27.5539,-2.1662,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,27.6376,-2.0825,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_OZD_5,EDEOZRK_BUN5_RA,29.0890,-0.6311,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_OZD_6,EDEOZRK_BUN6_RA,29.0890,-0.6311,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_OZD_7,EDEOZRK_BUN7_RA,29.0890,-0.6311,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_OZD_8,EDEOZRK_BUN8_RA,29.0890,-0.6311,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,28.9286,-0.7915,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_RIV_10,EDERIV1671UN10_RA,28.0338,-1.6863,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_RIV_11,EDERIV1671UN11_RA,28.0338,-1.6863,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_RIV_12,EDERIV453UN12_PLT,28.0338,-1.6863,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_SL_01,EDESTL4391UN1_RA,27.3785,-2.3417,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,EDE_SWMP,EDE_SWMP_LA,29.0399,-0.6802,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EEI,EEI,28.9225,-0.7976,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EES,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,27.4370,-2.2831,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ERCOTE,ERCOTE,29.5602,-0.1599,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ERCOTN,ERCOTN,28.2172,-1.5029,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,28.1843,-1.5358,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,FMPP,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,FPC,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,FPL,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,FREM_50T,OPPDFREM_GUN1_RA,29.2476,-0.4725,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,FREM_6,OPPDFREM_AUN6_RA,29.2019,-0.5182,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,FREM_7,OPPDFREM_AUN7_RA,29.2019,-0.5182,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,FREM_8,OPPDFREM_AUN8_RA,29.0813,-0.6388,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,FREM_LOAD,FREM_LOAD_LA,29.2162,-0.5039,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,FRONTIER,WRGETTUNFRONTIER_RA,28.0023,-1.7178,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GATEWAY_LOAD,CSWS_TENASKA_LA,29.8192,0.0990,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,29.5342,-0.8492,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,27.8838,-1.8363,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,29.0013,-0.7188,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,29.0013,-0.7188,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,29.0013,-0.7188,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.GREC2,GRDAGRDA17UN2_RA,28.8285,-0.8916,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,28.8285,-0.8916,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,28.8219,-0.8983,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,28.8219,-0.8983,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,27.3602,-2.3599,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,28.5603,-1.1599,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,28.5603,-1.1599,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,28.5603,-1.1599,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.VOLT.0130,V130_DDR,29.2205,-0.4996,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA.VOLT.0237,V237_DDR,28.9876,-0.7325,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDAHUB2,GRDAHUB2_H,28.4654,-1.2547,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDAHUB3,GRDAHUB3_H,28.3769,-1.3432,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA_GRDA,GRDA_LA,28.9710,-0.7491,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA_HUB,GRDA_H,28.4353,-1.2848,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRDA_HUBSA,GRDASA_H,28.6764,-1.0437,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GRE,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,30.9428,1.2227,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GSEC_SPS,SPS_GSEC_LA,32.6995,2.3169,0.5728,29.8098\n03/31/2025 08:50:00,03/31/2025 13:50:00,GSPR2014HUB,GSPR2014HUB_H,31.9266,1.5803,0.5364,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GSPR2015HUB,GSPR2015HUB_H,31.8299,1.4845,0.5355,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,31.0968,0.7134,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,HARRISON,CSWSLEBROCKPLT1,29.8613,0.1412,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,HAST_TNSK_HUB,HAST_TNSK_H,30.0619,0.3418,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,HQST,PJM,28.9703,-0.7498,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,HST,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,INDNSUB_H_5,INDNSUB_HUN5_RA,28.7393,-0.9808,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,INDNSUB_H_6,INDNSUB_HUN6_RA,28.7393,-0.9808,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,INDNSUB_I_3,INDNSUBIUN3_RA,28.7163,-1.0038,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,INDNSUB_I_4,INDNSUBIUN4_RA,28.7163,-1.0038,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,INDNSUB_J_1,INDNSUBJUN1_RA,28.7565,-0.9636,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,INDNSUB_J_2,INDNSUBJUN2_RA,28.7565,-0.9636,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,INDN_INDN,INDN_LA,28.7238,-0.9963,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,28.2219,-1.4982,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ISNE,PJM,28.9703,-0.7498,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,JEA,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,JONES_STREET_1,OPPDJONES_STUN1_RA,29.0467,-0.6734,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,JONES_STREET_2,OPPDJONES_STUN2_RA,29.0467,-0.6734,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,27.9235,-1.7966,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KACYCT4,KACYNEARMANUNCT4_RA,28.1640,-1.5562,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,28.0623,-1.6578,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,28.1640,-1.5562,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,28.2640,-1.4561,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,28.2304,-1.4897,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KACY_KACY,KACY_LA,28.3011,-1.4190,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,28.3067,-1.4134,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,29.2590,-0.4611,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,27.3370,-2.3832,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,27.2427,-2.4774,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.VOLT.0222,V222_DDR,28.2549,-1.4652,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.VOLT.0223,V223_DDR,27.8259,-1.8942,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.VOLT.0241,V241_DDR,29.0396,-0.6805,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.VOLT.0243,V243_DDR,28.7627,-0.9574,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.VOLT.0247,V247_DDR,27.9436,-1.7766,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.VOLT.0253,V253_DDR,28.3241,-1.3960,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,26.6179,-3.1022,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,27.6963,-2.0238,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,27.6963,-2.0238,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,27.6963,-2.0238,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,27.6960,-2.0241,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,28.3088,-1.4113,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,28.3088,-1.4113,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHUB,KCPLHUB_H,27.4334,-2.2867,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHUB17,KCPLHUB17_H,27.4452,-2.2749,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHUB18,KCPLHUB18_H,27.4431,-2.2770,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHUB19,KCPLHUB19_H,27.5030,-2.2171,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHUB20,KCPLHUB20_H,27.4451,-2.2750,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHUB21,KCPLHUB21_H,27.4934,-2.2267,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHUB22,KCPLHUB22_H,27.4623,-2.2578,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHUB23,KCPLHUB23_H,27.4431,-2.2770,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLHUB24,KCPLHUB24_H,27.4299,-2.2902,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,27.9185,-1.8016,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,27.9185,-1.8016,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,27.1828,-2.5373,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,27.1828,-2.5373,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,28.3152,-1.4049,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,28.3067,-1.4134,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,28.3661,-1.3540,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,28.3661,-1.3540,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,28.3660,-1.3541,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,28.3660,-1.3541,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,28.3660,-1.3541,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,28.3660,-1.3541,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,28.3659,-1.3542,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,28.3659,-1.3542,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,27.6214,-2.0987,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,28.2663,-1.4538,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KCPL_KCPL,KCPL_LA,28.2045,-1.5156,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KENN,KENN_LA,28.9125,-0.8076,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KEP2_SECI,KEP2_SECI_LA,29.1702,-0.5499,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KERR_1,GRDAKERR_HYDUN1_RA,28.9739,-0.7462,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KERR_2,GRDAKERR_HYDUN2_RA,28.9931,-0.7270,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KERR_3,GRDAKERR_HYDUN3_RA,28.9931,-0.7270,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KERR_4,GRDAKERR_HYDUN4_RA,28.9739,-0.7462,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,27.6959,-2.0242,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,27.6959,-2.0242,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,27.8527,-1.8674,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,27.8527,-1.8674,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,27.7092,-2.0109,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,27.7641,-1.9561,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,27.7641,-1.9561,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,28.6164,-1.1037,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,28.6164,-1.1037,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,28.6164,-1.1037,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,29.0587,-0.6614,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,29.0587,-0.6614,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,28.5815,-1.1386,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,28.9058,-0.8143,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,27.6489,-2.0713,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,28.0827,-1.6374,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,28.0827,-1.6374,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,27.8021,-1.9180,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,27.8021,-1.9180,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,27.8021,-1.9180,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,29.4198,-0.3003,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,28.3913,-1.3288,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,28.0830,-1.6371,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,KMEA_EUDORA,KMEA_EUDORA_LA,28.0501,-1.6700,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LAFA,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LAM345,LAM345,28.4702,-1.2499,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LEPA,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_JSTREET,LES8_NUNJ_STREET_RA,28.9851,-0.7350,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_LES,LES_LA,28.9466,-0.7735,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,28.7386,-0.9815,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_ROKEBY_1,LESROKEBYUN1_RA,28.8234,-0.8967,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_ROKEBY_2,LESROKEBYUN2_RA,28.8723,-0.8478,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_ROKEBY_3,LESROKEBYUN3_RA,28.8723,-0.8478,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_TBGS_CC1,LES84_BLUFPLT1,28.7512,-0.9689,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,28.7386,-0.9815,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_WAVERLY,LES_WAVERLY_H,28.8326,-0.8875,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,28.7790,-0.9412,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,28.7803,-0.9398,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,LGEE,LGEE,28.9472,-0.7729,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MALDEN,MALDEN_LA,28.9103,-0.8098,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MCWEST,MCWEST,30.3858,0.6657,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MDU,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,29.8551,0.1350,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,29.0547,-0.6654,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,30.5622,0.8421,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MEAN_NPPD,NPPD_MEAN_LA,30.0232,0.3031,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MEC,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MHEB,MHEB,30.3096,0.5895,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,29.0917,-0.6284,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,29.2540,-0.4661,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,29.0917,-0.6284,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,29.0917,-0.6284,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,29.2540,-0.4661,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,28.0943,-1.6258,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MISO,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,29.4968,-0.2233,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,29.4968,-0.2233,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,28.1484,-1.5717,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,28.4358,-1.2843,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,28.7745,-0.9456,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,27.9719,-1.7483,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKEC_KPP,SECI_MKEC_KPP_LA,28.3708,-1.3493,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,28.1086,-1.6115,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,28.5638,-1.1563,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,28.5638,-1.1563,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,28.5638,-1.1563,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,28.5638,-1.1563,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,28.5638,-1.1563,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,28.4863,-1.2338,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,28.8674,-0.8527,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,28.8674,-0.8527,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,28.8380,-0.8821,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,29.2244,-0.4957,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MOWR,AECI,28.8137,-0.9064,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,28.6750,-1.0451,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,28.8711,-0.8490,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,27.9604,-1.7597,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,28.0623,-1.6578,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,27.4966,-2.2235,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,27.9782,-1.7419,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,27.7618,-1.9583,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,27.7618,-1.9583,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,27.6945,-2.0256,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,27.6945,-2.0256,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,28.2549,-1.4652,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,28.2549,-1.4652,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,28.2549,-1.4652,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,28.2027,-1.5174,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,28.2549,-1.4652,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,28.2549,-1.4652,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,28.2549,-1.4652,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,28.8850,-0.8351,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,27.5428,-2.1773,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,27.1957,-2.5244,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,27.1098,-2.6103,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,27.1959,-2.5242,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSTWA1UN1,MPSTWA1UN1_RA,28.3257,-1.3944,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPSTWA1UN2,MPSTWA1UN2_RA,28.3257,-1.3944,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MPS_MPS,MPS_LA,28.3647,-1.3554,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MSTNG,SPSMSTNGPLT1,34.2647,3.8813,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MSTNG4,SPSMSTNGUN4_RA,33.8715,3.4881,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MSTNG5,SPSMSTNGUN5_RA,34.0308,3.6474,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,34.0308,3.6474,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NBSO,PJM,28.9703,-0.7498,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,27.9828,-1.7373,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,27.9814,-1.7387,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,30.6641,0.2807,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NHC1,VACS,28.9771,-0.7430,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,28.9858,-0.7343,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,28.9858,-0.7343,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,28.9858,-0.7343,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,31.1146,1.3945,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,29.8344,0.1143,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,28.7261,-0.9940,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,29.0043,-0.7158,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,29.8344,0.1143,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.HUB.PY2018,NPPDPY18_H,28.3454,-1.3747,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,28.3325,-1.3876,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,28.3436,-1.3765,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,28.3176,-1.4025,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,29.0978,-0.6223,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,29.4826,-0.2375,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,29.4826,-0.2375,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,29.4299,-0.2902,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,29.0978,-0.6223,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,28.9750,-0.7451,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,30.5215,0.8014,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,29.4324,-0.2877,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,30.5215,0.8014,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,30.7460,1.0258,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,30.3264,0.6063,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,29.1603,-0.5598,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,29.8344,0.1143,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,29.4529,-0.2672,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,29.4826,-0.2375,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,29.4826,-0.2375,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,29.8597,0.1396,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,29.8560,0.1359,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,29.8560,0.1359,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,30.3470,0.6269,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,29.4165,-0.3036,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,30.0321,0.3120,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,31.2061,1.4860,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,29.5394,-0.1807,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,29.6240,-0.0961,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.NELI.DDR,NELI_DDR,29.2063,-0.5138,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.NPPM.1058,SH1058_DDR,29.6457,-0.0744,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,30.0344,0.3143,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,29.8344,0.1143,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,28.7261,-0.9940,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,29.1175,-0.6027,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.TECH.1,KEARNE_DDR,30.3780,0.6579,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,29.3752,-0.3449,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,29.3752,-0.3449,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,29.1276,-0.5926,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD.VOLT.0236,V236_DDR,28.8382,-0.8819,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD2017HUB,NPPD2017HUB_H,28.3287,-1.3914,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,29.1938,-0.5263,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,31.1146,1.3945,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,30.5486,0.8284,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,30.5486,0.8284,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_BPS,NPPDBEAPWRSTPLT1,28.8210,-0.8991,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,28.8732,-0.8469,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,29.3772,-0.3429,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,29.8187,0.0986,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,29.1128,-0.6073,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,29.3565,-0.3636,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,29.1128,-0.6073,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,30.0364,0.3163,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_COOPR,NPPDCOOPERUN1_RA,28.0902,-1.6299,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_COSN_NPPD,NPPD_COSN_LA,30.2276,0.5075,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,29.3291,-0.3910,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,29.3485,-0.3716,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,29.4268,-0.2933,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,29.4062,-0.3139,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,29.9407,0.2206,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,29.9138,0.1937,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,29.9138,0.1937,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,30.0041,0.2840,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,28.9750,-0.7451,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,29.9967,0.2765,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,28.6955,-1.0246,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,30.0831,0.3630,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,30.0640,0.3439,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,30.0769,0.3568,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,30.0769,0.3568,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,30.0364,0.3163,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,30.0364,0.3163,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,31.6846,1.9645,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,29.9086,0.1884,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,29.3099,-0.4102,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,29.7337,0.0136,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,29.3553,-0.3649,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,29.4961,-0.2240,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_NELI_LD,NPPD_NELIGH_LA,29.2063,-0.5138,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,29.5552,-0.1649,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,29.5552,-0.1649,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_NPPD,NPPD_LA,29.6373,-0.0829,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,28.6955,-1.0246,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,28.6955,-1.0246,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,28.2888,-1.4313,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,30.5342,0.8140,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NSB,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,NSP,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NSSO,PJM,28.9703,-0.7498,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,NYIS,PJM,28.9703,-0.7498,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,28.4517,-1.2685,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,27.4619,-2.2582,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,27.3509,-2.3692,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,27.3509,-2.3692,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,28.7822,-0.9379,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,27.8838,-1.8363,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,27.7695,-1.9506,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,26.4350,-3.2851,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,27.3687,-2.3514,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,27.3346,-2.3855,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,28.5143,-1.2058,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,27.3687,-2.3514,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,28.6837,-1.0364,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,28.0943,-1.6258,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,28.3283,-1.3918,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,28.6694,-1.0507,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,27.3346,-2.3855,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,27.8225,-1.8976,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,28.0734,-1.6468,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,28.1387,-1.5814,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,28.4360,-1.2841,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,28.0943,-1.6258,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,28.0943,-1.6258,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,27.3346,-2.3855,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.NUEN.ADA1,ADA1_DDR,28.7409,-0.9792,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.NUEN.LAM1,LAM1_DDR,29.9506,0.2305,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.NUEN.MDT2,MDT2_DDR,28.5189,-1.2012,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.NUEN.MDT3,MDT3_DDR,28.5189,-1.2012,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.NUEN.WWO1,WWO1_DDR,28.7460,-0.9741,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,28.5368,-1.1833,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,28.5363,-1.1838,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,28.5701,-1.1500,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,28.6379,-1.0822,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,28.6379,-1.0822,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,28.5700,-1.1501,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,28.5700,-1.1501,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,27.3346,-2.3855,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,28.9020,-0.8181,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,28.6837,-1.0364,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,27.9164,-1.8038,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,27.8225,-1.8976,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,28.8023,-0.9178,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,27.8485,-1.8716,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,27.8485,-1.8716,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,28.0393,-1.6808,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,28.0393,-1.6808,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,27.4409,-2.2792,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,27.5381,-2.1820,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,27.4619,-2.2582,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,27.5009,-2.2192,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,27.5009,-2.2192,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,28.6280,-1.0921,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,28.1000,-1.6201,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,28.1000,-1.6201,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,28.1000,-1.6201,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0033,FOSTER_DDR,28.6871,-1.0330,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0034,CUSHOIL_DDR,29.6269,-0.0932,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0035,TARBY_DDR,29.4465,-0.2736,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0036,CUSHFLI_DDR,29.6269,-0.0932,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,29.2427,-0.4774,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,29.2427,-0.4774,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,28.4674,-1.2527,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0040,TROSPER_DDR,28.7409,-0.9792,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,28.7423,-0.9778,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,29.0044,-0.7157,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0115,V115_DDR,28.5454,-1.1747,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0116,V116_DDR,28.7928,-0.9273,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0118,V118_DDR,28.9162,-0.8039,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0125,V125_DDR,29.2373,-0.4829,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0126,V126_DDR,29.0240,-0.6961,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0129,V129_DDR,28.3121,-1.4080,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,28.5481,-1.1720,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0134,V134_DDR,29.0743,-0.6458,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0138,V138_DDR,28.9936,-0.7265,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,28.7003,-1.0198,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0143,V143_DDR,29.1092,-0.6109,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0149,V149_DDR,28.3889,-1.3313,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0150,V150_DDR,28.5273,-1.1928,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0155,V155_DDR,28.9481,-0.7721,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0156,V156_DDR,28.5481,-1.1720,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0166,V166_DDR,30.2395,0.5194,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,28.7190,-1.0012,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,28.5273,-1.1928,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0170,V170_DDR,28.7405,-0.9796,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,28.3078,-1.4123,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0176,V176_DDR,28.5273,-1.1928,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0177,V177_DDR,27.9916,-1.7285,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,28.7259,-0.9942,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,28.4250,-1.2951,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0195,V195_DDR,29.9876,0.2675,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0197,V197_DDR,29.4248,-0.2953,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0198,V198_DDR,30.2395,0.5194,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0208,V208_DDR,30.0087,0.2886,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0209,V209_DDR,30.0087,0.2886,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,29.2104,-0.5097,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0216,V216_DDR,28.7405,-0.9796,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0219,V219_DDR,28.9481,-0.7721,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0220,V220_DDR,28.5273,-1.1928,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0224,V224_DDR,28.6325,-1.0876,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0225,V225_DDR,28.6336,-1.0865,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0226,V226_DDR,28.6325,-1.0876,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0227,V227_DDR,28.6325,-1.0876,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0229,V229_DDR,28.4644,-1.2557,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0231,V231_DDR,29.2067,-0.5134,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0238,V238_DDR,27.8222,-1.8979,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.VOLT.0242,V242_DDR,28.9708,-0.7493,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,27.8992,-1.8209,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,28.0943,-1.6258,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,27.6088,-2.1113,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,28.3372,-1.3829,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,27.8992,-1.8209,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,28.5392,-1.1809,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,26.4091,-3.3110,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEHL7,OKGEHL7_H,28.6763,-1.0438,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEHL8,OKGEHSL1UN8_RA,28.6763,-1.0438,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEHL910,OKGEHSL1PLT2,28.6763,-1.0438,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,28.4517,-1.2685,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEMCC,OKGEMCCLAIPLT1,28.0717,-1.6484,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,28.7977,-0.9224,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,28.7977,-0.9224,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,28.7504,-0.9698,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,28.2219,-1.4982,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,28.0727,-1.6474,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,28.0748,-1.6453,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,28.2219,-1.4982,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGESM1,OKGESEMINOLEUN1_RA,28.5935,-1.1266,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGESM2,OKGESEMINOLEUN2_RA,28.5484,-1.1717,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGESM3,OKGESEMINOLEUN3_RA,28.5484,-1.1717,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGESO1,OKGESONR1UN1_RA,27.4376,-2.2825,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGESO2,OKGESONR1UN2_RA,27.5009,-2.2192,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,28.4191,-1.3010,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,28.1517,-1.5684,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGETINK5A,OKGETINK5UN1_RA,28.6782,-1.0419,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGETINK5B,OKGETINK5UN2_RA,28.6782,-1.0419,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,28.1876,-1.5325,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,27.4619,-2.2582,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,28.6933,-1.0268,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,28.0943,-1.6258,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE_OKGE,OKGE_LA,28.6967,-1.0234,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,27.9164,-1.8038,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,28.1698,-1.5503,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMLP,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,28.9261,-0.7940,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,28.6090,-1.1111,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_GENHUB,OMPA_GENHUB_H,28.0651,-1.6550,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_KAW,OKGEOMKAWUN2_RA,27.9033,-1.8168,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,28.3276,-1.3925,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,27.3687,-2.3514,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,28.4387,-1.2814,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,27.8569,-1.8632,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,28.9054,-0.8147,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,27.9050,-1.8151,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,27.9050,-1.8151,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_SPP,OMPA_SPP_LA,28.3348,-1.3853,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,27.8992,-1.8209,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ONETA,CSWSCALPINEUNONETA_1_RA,28.8920,-0.8281,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,28.8920,-0.8281,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,28.8920,-0.8281,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,28.8920,-0.8281,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,ONT,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,28.9856,-0.7345,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,28.9856,-0.7345,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,28.9856,-0.7345,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,28.9856,-0.7345,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,28.9856,-0.7345,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,28.9856,-0.7345,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,28.9856,-0.7345,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,28.9856,-0.7345,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,28.9856,-0.7345,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,28.9330,-0.7871,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,28.9858,-0.7343,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,28.7473,-0.9728,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,28.9802,-0.7399,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,28.9802,-0.7399,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD_GLDN,OPPD_GLDN_LA,28.9816,-0.7385,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD_GLDN2,OPPD_GLDN2_LA,29.0149,-0.7052,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,28.9750,-0.7451,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD_NC_HST,OPPD_NC_HST_LA,28.4339,-1.2862,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD_NO_HST,OPPD_NO_HST_LA,28.9728,-0.7473,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD_OPPD,OPPD_LA,29.0793,-0.6408,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD_PAPIO,OPPD_PAPIO_LA,28.9944,-0.7258,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,28.9916,-0.7286,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,OTP,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,OVEC,OVEC,28.9536,-0.7665,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PARAGOULD,PARAGOULD_LA,28.9163,-0.8039,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,PENSACOLA_1,GRDAPENSA1UN1_RA,28.9021,-0.8180,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PENSACOLA_2,GRDAPENSA1UN2_RA,28.9021,-0.8180,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PENSACOLA_3,GRDAPENSA1UN3_RA,28.9021,-0.8180,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PENSACOLA_4,GRDAPENSA1UN4_RA,28.9256,-0.7945,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PENSACOLA_5,GRDAPENSA1UN5_RA,28.9256,-0.7945,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PENSACOLA_6,GRDAPENSA1UN6_RA,28.9256,-0.7945,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PIGGOTT,PIGGOTT_LA,28.9118,-0.8083,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PJM,PJM,28.9703,-0.7498,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PLUM,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,POPLARBLUFF,POPLARBLUFF_LA,28.9086,-0.8115,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,30.4980,0.7779,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,30.4980,0.7779,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,30.4364,0.7163,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,30.4364,0.7163,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,32.5986,2.8785,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,32.5917,2.8716,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,30.3695,0.6494,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,30.3167,0.5965,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,27.6068,-2.1133,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,28.9790,-0.7412,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,28.2032,-1.5169,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,28.5837,-1.1364,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,29.1740,-0.5461,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,29.2242,-0.4959,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,29.3436,-0.3765,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,31.1378,1.4176,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,29.6560,-0.0641,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,31.2918,1.5717,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,31.2603,1.5402,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,29.7762,0.0561,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,PUPP,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,RCEAST,RCEAST,29.2392,-0.4809,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SALINA_1,GRDASALINA1UN1_RA,28.9777,-0.7424,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SALINA_2,GRDASALINA1UN2_RA,28.9777,-0.7424,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SALINA_3,GRDASALINA1UN3_RA,28.9777,-0.7424,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SALINA_4,GRDASALINA1UN4_RA,28.9777,-0.7424,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SALINA_5,GRDASALINA1UN5_RA,28.9777,-0.7424,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SALINA_6,GRDASALINA1UN6_RA,28.9777,-0.7424,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SARPY_1,OPPDSARPYUN1_RA,28.9556,-0.7645,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SARPY_2,OPPDSARPYUN2_RA,29.0209,-0.6992,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SARPY_3,OPPDSARPYUN3_RA,28.8852,-0.8349,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SARPY_4,OPPDSARPYUN4_RA,28.8852,-0.8349,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SARPY_5,OPPDSARPYUN5_RA,28.8852,-0.8349,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SC,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SCEG,VACS,28.9771,-0.7430,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SCSE,SCSE,28.9952,-0.7249,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SEC,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,27.8744,-1.8457,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,27.8744,-1.8457,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,27.8744,-1.8457,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,29.7398,0.0197,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,27.8744,-1.8457,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,28.2725,-1.4476,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,28.1280,-1.5921,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,28.1280,-1.5921,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,28.5592,-1.1609,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,27.8462,-1.8739,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,28.9590,-0.7611,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,29.2718,-0.4483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,29.1517,-0.5685,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,27.8572,-1.8630,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,29.0626,-0.6575,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,28.4875,-1.2326,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,28.5392,-1.1809,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,28.4469,-1.2732,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,28.4482,-1.2719,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,28.4482,-1.2719,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,28.4482,-1.2719,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,28.3453,-1.3748,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,28.2725,-1.4476,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI_SECI,SECI_LA,29.0572,-0.6629,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,28.2219,-1.4982,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,28.2219,-1.4982,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,28.5592,-1.1609,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SEHA,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,28.1698,-1.5503,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SERU,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SETH,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SGE,SGE,28.7789,-0.9412,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SMEP,MISO,29.1937,-0.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SOCO,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPA,SPA,28.9090,-0.8111,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPC,SPC,31.5666,1.8465,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPPNORTH_HUB,SPPNORTH_H,29.4415,-0.2787,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPPSOUTH_HUB,SPPSOUTH_H,28.4967,-1.2235,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,29.0001,-0.7200,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,29.0079,-0.7123,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,29.0965,-0.6236,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,29.0965,-0.6236,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_NIXA,SPRM_NIXA_LA,29.1183,-0.6019,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_SPRM,SPRM_LA,29.2344,-0.4857,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,29.0068,-0.7133,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,29.0068,-0.7133,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,28.9498,-0.7703,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,29.0068,-0.7133,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,33.6915,3.3081,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,33.4613,3.0779,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,30.3964,0.0130,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,30.3964,0.0130,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,32.5878,2.2044,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,34.4048,4.0214,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,34.6990,4.3156,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,34.4027,4.0193,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,31.8229,1.4395,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,33.9102,3.5268,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,34.2804,3.8970,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,34.2804,3.8970,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,33.9102,3.5268,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,30.5799,0.1965,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,33.4613,3.0779,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,30.8389,0.4554,0.5735,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,29.8332,-0.5502,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,31.2419,0.8585,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,31.9095,1.5261,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,31.0466,0.6632,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,29.5736,-0.8099,0.5735,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,29.5735,-0.8099,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,29.5735,-0.8099,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,29.5735,-0.8099,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GRID.WRAB,WRAB_DDR,31.8209,1.4375,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,29.5735,-0.8099,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,32.4594,2.0760,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,32.4594,2.0760,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,32.4924,2.1089,0.5735,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,32.4924,2.1089,0.5735,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,32.4924,2.1089,0.5735,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,32.4594,2.0760,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,30.3674,-0.0160,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,30.3674,-0.0160,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,30.3680,-0.0154,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,30.6641,0.2807,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.HOBBS.CC,SPSHOBBSPLT1,33.9260,3.5426,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.JONES1,SPSJONESSUBUN1_RA,31.7896,1.4061,0.5735,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.JONES2,SPSJONESSUBUN2_RA,31.7899,1.4065,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.JONES3,SPSJONESSUBUN3_RA,31.7896,1.4062,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.JONES4,SPSJONESSUBUN4_RA,31.7896,1.4062,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,34.1691,3.7857,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,33.9465,3.5631,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,33.9466,3.5632,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,28.1964,-1.5237,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,30.2417,-0.1417,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,30.2417,-0.1417,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,30.3735,-0.0099,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,31.8209,1.4375,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,30.3635,-0.0199,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,30.4783,0.0948,0.5735,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,28.7822,-0.9379,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,30.6333,0.2499,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.PLANTX1,SPS.PLANTX1_H,33.5711,3.1877,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.PLANTX2,SPS.PLANTX2_H,33.5711,3.1877,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,33.4819,3.0985,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,32.5039,2.1205,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,29.7490,-0.6344,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,34.9768,4.5934,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,32.6033,2.2199,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,30.7258,0.3424,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,34.0183,3.6349,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,34.7575,4.3741,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,34.0183,3.6349,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,34.3379,3.9545,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,30.4156,0.0322,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,35.9162,5.5328,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,35.9827,5.5992,0.5735,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,35.3344,4.9510,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,34.2831,3.8997,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,35.9688,5.5854,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,28.4702,-1.2499,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,31.6887,1.3053,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,33.6390,3.2556,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,33.6390,3.2556,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,34.0183,3.6349,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,31.8933,1.5099,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0006,SPS.VOLT.0006_H,34.9445,4.5611,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0023,SPS.VOLT.0023_H,34.2522,3.8688,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0025,SPS.VOLT.0025_H,34.4968,4.1134,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0033,SPS.VOLT.0033_H,32.6236,2.2402,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0045,SPS.VOLT.0045_H,35.9162,5.5328,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0046,SPS.VOLT.0046_H,37.0394,6.6560,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0047,SPS.VOLT.0047_H,36.3792,5.9958,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0052,SPS.VOLT.0052_H,32.8579,2.4745,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0113,SPS.VOLT.0113_H,34.8148,4.4314,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0136,SPS.VOLT.0136_H,30.1247,-0.2587,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0137,SPS.VOLT.0137_H,30.0709,-0.3125,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0163,V163_DDR,31.2724,0.8890,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0168,V168_DDR,29.6507,-0.7328,0.5735,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0180,V180_DDR,37.0394,6.6560,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0181,V181_DDR,30.1039,-0.2795,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0182,V182_DDR,36.0689,5.6855,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0199,V199_DDR,34.6892,4.3058,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0200,V200_DDR,34.8420,4.4586,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.VOLT.0235,V235_DDR,30.3635,-0.0199,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,34.6990,4.3156,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,34.4027,4.0193,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,31.0808,0.6974,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,32.6956,2.3122,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS_SPS,SPS_LA,33.9978,3.6144,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,33.7323,3.3489,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SSCN_NPPD,SSCN_NPPD_LA,29.2485,-0.4717,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,28.8990,-0.8211,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,28.8990,-0.8211,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,TAL,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,TEC,SOUC,29.0038,-0.7164,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,29.7337,0.0136,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,TVA,TVA,28.9492,-0.7710,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,UCUHUB,UCUHUB_H,27.9138,-1.8063,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,UCUHUB17,UCUHUB17_H,28.0932,-1.6269,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,UCUHUB18,UCUHUB18_H,27.9951,-1.7250,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,UCUHUB19,UCUHUB19_H,27.8975,-1.8226,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,UCUHUB20,UCUHUB20_H,27.8860,-1.8341,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,UCUHUB21,UCUHUB21_H,27.9107,-1.8094,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,UCUHUB22,UCUHUB22_H,27.8823,-1.8379,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,UCUHUB23,UCUHUB23_H,27.8880,-1.8322,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,UCUHUB24,UCUHUB24_H,27.8567,-1.8634,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,32.0571,2.3370,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,32.0571,2.3370,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,30.3071,0.5870,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,30.3071,0.5870,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,30.3324,0.6123,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,30.3985,0.6784,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,30.3985,0.6784,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,32.0571,2.3370,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,30.7053,0.9852,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,31.0912,1.3710,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,29.3539,-0.3662,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,29.1217,-0.5984,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,32.0358,2.3157,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,32.0358,2.3157,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,28.9451,-0.7750,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,29.3739,-0.3462,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,30.9189,1.1988,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,29.3793,-0.3408,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,30.2152,0.4951,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,29.3492,-0.3709,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,29.3437,-0.3764,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,29.3437,-0.3764,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,29.4788,-0.2413,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,29.1823,-0.5378,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,30.8909,1.1708,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,31.1222,1.4021,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,31.1222,1.4021,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,31.1222,1.4021,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,31.1222,1.4021,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,31.1222,1.4021,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,31.1222,1.4021,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,32.3562,2.6361,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,30.1140,0.3939,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,30.1115,0.3914,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,28.6031,-1.1170,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,30.0576,0.3375,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,31.0713,1.3512,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,29.0291,-0.6910,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,28.7400,-0.9801,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,29.6943,-0.0258,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,31.7451,2.0250,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,31.7451,2.0250,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,31.7418,2.0217,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,31.7451,2.0250,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,31.8607,2.1406,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,31.8607,2.1406,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,31.8607,2.1406,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,31.8607,2.1406,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,31.8607,2.1406,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,31.8607,2.1406,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,31.8607,2.1406,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,29.0797,-0.6404,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,31.3693,1.6492,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,29.9948,0.2747,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,29.9948,0.2747,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,30.0367,0.3166,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,30.0367,0.3166,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,30.4858,0.7656,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,30.4112,0.6910,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,29.6805,-0.0396,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,29.1834,-0.5368,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,29.2623,-0.4578,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,30.3324,0.6123,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,30.3324,0.6123,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,29.3793,-0.3408,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,29.2564,-0.4637,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,29.6071,-0.1130,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,28.8418,-0.8784,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,29.4855,-0.2346,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.FSE,WAUE.FSE_H,29.2227,-0.4974,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,30.4481,0.7280,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,30.4103,0.6901,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,28.5423,-1.1778,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,28.4950,-1.2251,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,29.9879,0.2678,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,29.8524,0.1323,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,29.0396,-0.6805,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,29.1217,-0.5984,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,28.4692,-1.2509,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,28.4394,-1.2807,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,28.4418,-1.2783,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,28.4127,-1.3074,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,29.5808,-0.1393,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,29.2564,-0.4637,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,29.6486,-0.0715,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,29.5342,-0.1859,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,30.8257,1.1055,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,29.7697,0.0496,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,29.5969,-0.1232,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,28.5004,-1.2197,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,30.2062,0.4861,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,29.2305,-0.4896,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,29.0291,-0.6910,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,30.3692,0.6491,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,29.3372,-0.3829,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,29.9835,0.2634,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,29.7281,0.0080,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,28.7803,-0.9398,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NTWK,WAUE.NTWK_H,30.0409,0.3208,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,30.3547,0.6346,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,30.3547,0.6346,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,29.2948,-0.4253,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,29.1694,-0.5507,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,29.6190,-0.1011,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,29.2948,-0.4253,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,30.3697,0.6496,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,29.3901,-0.3301,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,29.0291,-0.6910,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,29.7451,0.0250,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,31.0426,1.3225,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,27.9974,-1.7227,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,27.9056,-1.8146,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,30.1980,0.4779,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,29.3117,-0.4084,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,29.4510,-0.2691,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,29.2182,-0.5019,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,29.1834,-0.5368,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.VOLT.0152,V152_DDR,32.6191,2.8989,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE.VOLT.0172,V172_DDR,31.9684,2.2483,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_BEPM,WAUE_BEPM_LA,31.0354,1.3153,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,29.6832,-0.0369,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,29.7943,0.0742,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_EWA,WAUE_EWA_LA,29.3216,-0.3985,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,29.6269,-0.0932,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_HMMU,WAUE_HMMU_LA,29.2520,-0.4681,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,29.1047,-0.6154,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_MECB,WAUE_MECB_LA,29.4507,-0.2694,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_MMPA,WAUE_MMPA_LA,30.7748,1.0547,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_MRES,WAUE_MRES_LA,29.8669,0.1468,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,32.2281,2.5079,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,30.4481,0.7280,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,29.7817,0.0616,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_OTP,WAUE_OTP_LA,31.9805,2.2604,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_OTPW,WAUE_OTPW_LA,30.8881,1.1680,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM,WAUE_UGPM_LA,29.6360,-0.0841,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,30.7072,0.9871,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,29.6805,-0.0397,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,30.1390,0.4189,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,29.3216,-0.3985,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,29.2520,-0.4681,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,29.6949,-0.0252,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,30.4481,0.7280,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,30.7748,1.0547,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,30.0933,0.3732,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,29.5511,-0.1690,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,32.4607,2.7406,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,27.9582,-1.7619,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,27.8046,-1.9155,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,27.6195,-2.1006,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,29.3305,-0.3896,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,29.3305,-0.3896,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,26.8396,-2.8805,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,29.4378,-0.2823,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,29.3712,-0.3489,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,27.5120,-2.2081,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,27.5133,-2.2068,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,27.5154,-2.2047,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,27.6681,-2.0520,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,27.6681,-2.0520,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,27.6681,-2.0520,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,27.6681,-2.0520,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,27.6681,-2.0520,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,27.7019,-2.0182,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,28.7822,-0.9379,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,27.0714,-2.6487,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,28.2374,-1.4827,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,34.7180,4.3346,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_ENMC,WFEC_ENMC_LA,34.9636,4.5802,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,27.3346,-2.3855,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,28.8675,-0.8526,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,33.9242,3.5408,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,27.9227,-1.7974,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,27.9582,-1.7619,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,27.9582,-1.7619,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_OKGE,WFEC_OKGE_LA,28.7627,-0.9574,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,29.6188,-0.1013,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,28.2291,-1.4910,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,27.8284,-1.8917,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_WFEC,WFEC_LA,28.8991,-0.8211,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,33.9242,3.5408,0.5735,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,29.0323,-0.6878,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,28.7942,-0.9259,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,27.4308,-2.2893,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,27.4308,-2.2893,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,27.4179,-2.3022,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,27.4179,-2.3022,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,27.4307,-2.2894,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,27.4307,-2.2894,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,27.4307,-2.2894,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,28.7356,-0.9845,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,27.5830,-2.1371,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,27.3747,-2.3454,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,27.3747,-2.3454,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,27.3747,-2.3454,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,27.8345,-1.8857,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,27.8345,-1.8857,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.GEEC.GT1,WRGORDUNG1_RA,27.5027,-2.2174,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.GEEC.GT2,WRGORDUNG2_RA,27.5027,-2.2174,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.GEEC.GT3,WRGORDUNGT3_RA,27.4075,-2.3126,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,27.5830,-2.1371,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,27.8866,-1.8335,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.HEC.GT1,WRHECGTUN32_RA,27.8892,-1.8309,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.HEC.GT2,WRHECGTUN33_RA,27.9038,-1.8163,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.HEC.GT3,WRHECGTUN34_RA,27.9094,-1.8108,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.HEC.GT4,WRHECGTUN35_RA,27.9109,-1.8092,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,27.8866,-1.8335,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,27.8441,-1.8760,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,27.3933,-2.3268,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.JEC.1,WRJEFFUN10_RA,27.4667,-2.2534,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.JEC.2,WRJEFFUN11_RA,27.3274,-2.3927,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.JEC.3,WRJEFFUN12_RA,27.4618,-2.2583,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,27.3602,-2.3599,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,27.5107,-2.2094,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,27.5107,-2.2094,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.LEC.4,WRLECUN26_RA,27.7333,-1.9869,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.LEC.5,WRLECUN27_RA,27.8843,-1.8358,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MCPH.CT1,WRCMCPHUN37_RA,28.0833,-1.6368,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MCPH.CT2,WRCMCPHUN38_RA,28.0833,-1.6368,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MCPH.CT3,WRCMCPHUN48_RA,28.0783,-1.6418,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MCPH.CT4,WRCJOHNUN1_RA,28.1516,-1.5685,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,28.2219,-1.4982,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,28.2219,-1.4982,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,29.4841,-0.2360,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,29.0885,-0.6316,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,29.0885,-0.6316,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,28.3952,-1.3249,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,28.2219,-1.4982,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,27.8172,-1.9029,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,27.6376,-2.0825,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,27.5025,-2.2176,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,29.3607,-0.3594,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,28.4038,-1.3163,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.READ.READ,WREMPECUNREADINGWF_RA,27.4307,-2.2894,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,26.6314,-3.0887,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,27.8866,-1.8335,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,27.5830,-2.1371,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,27.7286,-1.9915,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.THAYERLD,WR.THAYERLD_LA,28.9206,-0.7995,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0102,WR.VOLT.0102_H,27.7451,-1.9750,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0106,V106_DDR,27.7318,-1.9883,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0139,WR.VOLT.0139_H,28.0820,-1.6381,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0141,WR.VOLT.0141_H,28.0438,-1.6763,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0146,WR.VOLT.0146_H,28.0187,-1.7014,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0147,WR.VOLT.0147_H,28.0187,-1.7014,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0148,WR.VOLT.0148_H,27.9557,-1.7644,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0153,WR.VOLT.0153_H,27.9649,-1.7552,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0157,V157_DDR,27.9893,-1.7308,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0158,V158_DDR,28.0187,-1.7014,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0159,WR.VOLT.0159_H,28.0187,-1.7014,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0165,WR.VOLT.0165_H,27.5778,-2.1423,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0173,V173_DDR,28.1937,-1.5264,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0174,V174_DDR,27.7032,-2.0169,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0184,V184_DDR,27.5208,-2.1993,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0185,WR.VOLT.0185_H,27.7133,-2.0068,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0186,V186_DDR,27.6528,-2.0673,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0187,WR.VOLT.0187_H,27.5873,-2.1328,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0188,WR.VOLT.0188_H,27.7536,-1.9665,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0189,WR.VOLT.0189_H,28.3296,-1.3905,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0190,WR.VOLT.0190_H,27.5852,-2.1350,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0191,WR.VOLT.0191_H,27.5047,-2.2155,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0192,WR.VOLT.0192_H,27.5047,-2.2155,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0196,WR.VOLT.0196_H,27.5852,-2.1350,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0245,V245_DDR,27.7177,-2.0024,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.VOLT.0248,V248_DDR,27.7318,-1.9883,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,27.3647,-2.3554,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,27.9338,-1.7863,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.WOLF,WRWOLFUN15_RA,26.4871,-3.2330,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,27.8441,-1.8760,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,28.3067,-1.4134,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,27.3747,-2.3454,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,27.3747,-2.3454,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,27.3747,-2.3454,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,27.3747,-2.3454,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KPP_NITS,WR_KPP_NITS_LA,27.6649,-2.0552,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,28.0468,-1.6734,-0.0898,29.8100\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,27.6857,-2.0344,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,27.6857,-2.0344,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,27.6857,-2.0344,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,27.6857,-2.0344,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,27.8367,-1.8834,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,27.8367,-1.8834,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,27.8367,-1.8834,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,27.8367,-1.8834,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,27.8367,-1.8834,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,27.8367,-1.8834,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,27.7876,-1.9325,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,27.7876,-1.9325,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,27.4336,-2.2865,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,27.4336,-2.2865,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_MIDW,WR_MIDW_LA,29.1513,-0.5688,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,28.9020,-0.8181,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,28.1999,-1.5202,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,28.9788,-0.7413,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_SEG,WR_SEG_LA,28.3817,-1.3384,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,WR_WR,WR_LA,27.9104,-1.8097,-0.0898,29.8099\n03/31/2025 08:50:00,03/31/2025 13:50:00,YAD,VACS,28.9771,-0.7430,-0.0898,29.8099\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_SPP/RTBM-LMP-SL-202503310855.csv",
    "content": "Interval,GMTIntervalEnd,Settlement Location,Pnode,LMP,MLC,MCC,MEC\n03/31/2025 08:55:00,03/31/2025 13:55:00,AEC,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,AECC_CSWS,CSWS_AECC_LA,34.1830,-0.6551,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,34.3979,-0.4402,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,33.4538,-1.3842,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,34.0727,-0.7654,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,33.7892,-1.0489,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,AECC_HYDRO13,CSWSLD13UN1_RA,33.1637,-1.6744,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,34.3671,-0.4709,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,AECI,AECI,33.7810,-1.0571,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,AEPM_CSWS,CSWS_LA,34.5097,-0.3284,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ALTW,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,AMRN,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ANTELOPE,SPSANTELOPEUNANT1_RA,37.2307,2.3926,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BBA,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BCA,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BEPM.ER01.DDR,ER01_DDR,32.9735,-1.8646,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BEPM_ER01,BEPM_ER01_LA,32.9735,-1.8646,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,36.9525,2.1145,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,35.2002,0.3622,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,BEPM_UM01,BEPM_UM01_LA,37.5354,2.6974,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,BLKW,BLKW,39.2225,4.3844,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,31.6155,-3.2226,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,31.6155,-3.2226,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,31.8499,-2.9881,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,31.6654,-3.1726,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,BRAZ,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BUBA,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,33.4751,-1.3630,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,32.9949,-1.8431,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,32.9949,-1.8431,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,32.9949,-1.8431,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,32.9949,-1.8431,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,32.9949,-1.8431,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,32.4185,-2.4196,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,33.7850,-1.0531,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,33.7850,-1.0531,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CLEC,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,34.0187,-0.8193,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,COWP,COWP_LA,33.9052,-0.9329,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,33.9052,-0.9329,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,33.9052,-0.9329,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CPLE,VACS,33.9468,-0.8912,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CPLW,VACS,33.9468,-0.8912,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,33.8477,-0.9904,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,33.8477,-0.9904,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,33.8477,-0.9904,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,33.8477,-0.9904,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CRTH_SPA,WRCRTH_SPA_LA,33.4646,-1.3734,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,35.2057,0.3677,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,33.0788,-1.7593,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,34.3671,-0.4709,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,34.0727,-0.7654,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWJLSTALL,CSWSSTALL_PPPLT1,35.2015,0.3635,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,35.1971,0.3590,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,35.1374,0.2993,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,35.1374,0.2993,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWMATTISON1,CSWSMATTISONUN1_RA,33.7631,-1.0750,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWMATTISON2,CSWSMATTISONUN2_RA,33.7631,-1.0750,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWMATTISON3,CSWSMATTISONUN3_RA,33.7674,-1.0707,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWMATTISON4,CSWSMATTISONUN4_RA,33.7674,-1.0707,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,34.3671,-0.4709,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWNARROWS1,CSWSNARROWSUN1_RA,34.8447,0.0066,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,33.5386,-1.2995,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,33.2915,-1.5465,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,33.7928,-1.0453,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,33.8605,-0.9776,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,33.7149,-1.1232,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,33.7062,-1.1319,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,33.7062,-1.1319,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,32.7411,-2.0970,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,33.6907,-1.1474,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,33.6841,-1.1539,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,33.0780,-1.7601,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,32.9900,-1.8481,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,33.1170,-1.7210,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.GRID.CDL1,CDL1_DDR,34.0395,-0.7986,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,33.1559,-1.6822,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,32.1194,-2.7186,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,34.0395,-0.7986,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.NUEN.CSI1,CSI1_DDR,34.3432,-0.4948,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.NUEN.CSI2,CSI2_DDR,34.3552,-0.4829,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.NUEN.CSI3,NCSI3_DDR,33.9481,-0.8900,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.NUEN.GAZA,GAZA_DDR,34.0395,-0.7986,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,34.7509,-0.0872,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.NUEN.T201,NT201_DDR,34.0937,-0.7444,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,32.9647,-1.8733,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,32.9647,-1.8733,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,34.3671,-0.4709,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,35.5839,0.7459,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,33.1170,-1.7210,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,33.1170,-1.7210,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,32.8474,-1.9906,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,32.9900,-1.8481,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,34.8778,0.0398,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,33.7951,-1.0430,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,33.7951,-1.0430,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,33.2850,-1.5530,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,33.3895,-1.4486,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,33.6129,-1.2252,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,35.1720,0.3339,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,34.0247,-0.8134,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,35.2608,0.4227,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,36.7817,1.9436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,34.0670,-0.7711,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0056,PRYORCRK_DDR,34.3552,-0.4829,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0057,OKMU_DDR,34.2451,-0.5930,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0060,LEHIGH_DDR,34.5564,-0.2816,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0086,WARRENM_DDR,34.0125,-0.8256,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,35.7074,0.8693,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,34.1397,-0.6984,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0121,V121_DDR,35.1720,0.3339,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0122,V122_DDR,34.0854,-0.7526,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0124,V124_DDR,33.9406,-0.8975,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0135,V135_DDR,34.1215,-0.7166,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0144,V144_DDR,33.6965,-1.1416,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0145,V145_DDR,33.4902,-1.3479,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,35.2136,0.3755,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,34.4994,-0.3387,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0175,V175_DDR,33.9481,-0.8900,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,34.4994,-0.3387,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,34.6489,-0.1892,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,34.1215,-0.7166,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,34.1034,-0.7347,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,34.0165,-0.8216,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,33.7638,-1.0743,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,33.8986,-0.9395,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,34.1034,-0.7347,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0211,V211_DDR,35.5311,0.6930,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,34.1545,-0.6835,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0213,V213_DDR,34.0334,-0.8047,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0215,V215_DDR,34.0883,-0.7498,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0217,V217_DDR,34.1283,-0.7097,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0218,V218_DDR,33.7818,-1.0563,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0228,V228_DDR,34.0259,-0.8121,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0232,V232_DDR,34.0915,-0.7466,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0233,V233_DDR,34.1238,-0.7143,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0240,V240_DDR,33.9943,-0.8437,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0244,V244_DDR,34.1034,-0.7347,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0246,MDT1_DDR,34.7509,-0.0872,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0249,V249_DDR,34.0951,-0.7429,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0250,V250_DDR,33.1420,-1.6961,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0251,V251_DDR,33.9413,-0.8968,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.VOLT.0252,V252_DDR,33.7638,-1.0743,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,32.8319,-2.0061,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,32.3150,-2.5231,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,32.6851,-2.1529,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,34.9990,0.1610,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,32.8685,-1.9696,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,33.3806,-1.4574,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,33.3806,-1.4574,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,33.3552,-1.4829,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,32.4457,-2.3924,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,32.4457,-2.3924,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,34.3671,-0.4709,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,35.2243,0.3863,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,34.0625,-0.7756,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,34.0136,-0.8244,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,34.2092,-0.6289,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,34.2092,-0.6289,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWWELSH1,CSWSWELSHUN1_RA,34.5708,-0.2673,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWWELSH3,CSWSWELSHUN3_RA,34.5708,-0.2673,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWWILKES1,CSWSWILKESUN1_RA,34.7493,-0.0888,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWWILKES2,CSWSWILKESUN2_RA,34.7493,-0.0888,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,CSWWILKES3,CSWSWILKESUN3_RA,34.7213,-0.1168,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,33.0556,-1.7825,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,DENL,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,DERS,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,DOE,DOE,33.8903,-0.9478,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,32.5027,-2.3353,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,DPC,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,DUK,VACS,33.9468,-0.8912,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDDY,EDDY,40.2166,5.3785,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,33.0689,-1.7691,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,32.9563,-1.8818,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,32.8694,-1.9687,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE.SLCC,EDESTL4391_PLT,32.3867,-2.4513,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE.VOLT.0234,EDE.VOLT.0234_H,32.8521,-1.9860,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,32.6186,-2.2195,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_EC_01,EDELAR3821UN1_RA,33.0689,-1.7691,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_EC_02,EDELAR3821UN2_RA,33.0352,-1.8028,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_EC_03,EDELAR3821UN3_RA,33.0689,-1.7691,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_EC_04,EDELAR3821UN4_RA,33.0689,-1.7691,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_EDE,EDE_LA,33.8115,-1.0265,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_ERW,EDEERWFUNG1_RA,32.3588,-2.4793,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,32.5004,-2.3377,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_OZD_5,EDEOZRK_BUN5_RA,34.1062,-0.7319,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_OZD_6,EDEOZRK_BUN6_RA,34.1062,-0.7319,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_OZD_7,EDEOZRK_BUN7_RA,34.1062,-0.7319,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_OZD_8,EDEOZRK_BUN8_RA,34.1062,-0.7319,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,33.8930,-0.9451,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_RIV_10,EDERIV1671UN10_RA,32.9179,-1.9202,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_RIV_11,EDERIV1671UN11_RA,32.9179,-1.9202,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_RIV_12,EDERIV453UN12_PLT,32.9179,-1.9202,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_SL_01,EDESTL4391UN1_RA,32.1604,-2.6776,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EDE_SWMP,EDE_SWMP_LA,34.0783,-0.7598,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EEI,EEI,33.8900,-0.9480,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,EES,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,32.2629,-2.5752,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ERCOTE,ERCOTE,34.5708,-0.2673,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ERCOTN,ERCOTN,33.0243,-1.8138,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,33.0776,-1.7605,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,FMPP,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,FPC,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,FPL,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,FREM_50T,OPPDFREM_GUN1_RA,34.2619,-0.5762,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,FREM_6,OPPDFREM_AUN6_RA,34.2105,-0.6276,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,FREM_7,OPPDFREM_AUN7_RA,34.2105,-0.6276,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,FREM_8,OPPDFREM_AUN8_RA,34.0703,-0.7678,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,FREM_LOAD,FREM_LOAD_LA,34.2254,-0.6127,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,FRONTIER,WRGETTUNFRONTIER_RA,32.9080,-1.9300,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GATEWAY_LOAD,CSWS_TENASKA_LA,34.8778,0.0398,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,33.9279,-0.9102,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,32.6744,-2.1637,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,34.0187,-0.8193,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,34.0187,-0.8193,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,34.0187,-0.8193,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.GREC2,GRDAGRDA17UN2_RA,33.8137,-1.0244,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,33.8137,-1.0244,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,33.8057,-1.0323,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,33.8057,-1.0323,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,32.1250,-2.7130,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,33.4848,-1.3532,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,33.4848,-1.3532,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,33.4848,-1.3532,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.VOLT.0130,V130_DDR,34.2650,-0.5731,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA.VOLT.0237,V237_DDR,33.9953,-0.8428,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDAHUB2,GRDAHUB2_H,33.3917,-1.4464,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDAHUB3,GRDAHUB3_H,33.2913,-1.5468,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA_GRDA,GRDA_LA,33.9747,-0.8634,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA_HUB,GRDA_H,33.3769,-1.4612,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRDA_HUBSA,GRDASA_H,33.6756,-1.1625,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GRE,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,36.1674,1.3294,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GSEC_SPS,SPS_GSEC_LA,37.5308,2.6928,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GSPR2014HUB,GSPR2014HUB_H,36.6702,1.8322,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,GSPR2015HUB,GSPR2015HUB_H,36.5607,1.7226,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,35.7320,0.8939,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,HARRISON,CSWSLEBROCKPLT1,34.9249,0.0868,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,HAST_TNSK_HUB,HAST_TNSK_H,35.3036,0.4655,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,HQST,PJM,33.9486,-0.8895,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,HST,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,INDNSUB_H_5,INDNSUB_HUN5_RA,33.7290,-1.1091,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,INDNSUB_H_6,INDNSUB_HUN6_RA,33.7290,-1.1091,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,INDNSUB_I_3,INDNSUBIUN3_RA,33.7006,-1.1375,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,INDNSUB_I_4,INDNSUBIUN4_RA,33.7006,-1.1375,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,INDNSUB_J_1,INDNSUBJUN1_RA,33.7481,-1.0900,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,INDNSUB_J_2,INDNSUBJUN2_RA,33.7481,-1.0900,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,INDN_INDN,INDN_LA,33.7105,-1.1275,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,33.1740,-1.6641,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ISNE,PJM,33.9486,-0.8895,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,JEA,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,JONES_STREET_1,OPPDJONES_STUN1_RA,34.0299,-0.8082,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,JONES_STREET_2,OPPDJONES_STUN2_RA,34.0299,-0.8082,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,32.7933,-2.0448,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KACYCT4,KACYNEARMANUNCT4_RA,33.0533,-1.7847,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,32.9712,-1.8668,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,33.0533,-1.7847,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,33.1710,-1.6671,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,33.1314,-1.7066,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KACY_KACY,KACY_LA,33.2158,-1.6223,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,33.2152,-1.6229,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,34.3002,-0.5378,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,32.1228,-2.7153,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,31.9798,-2.8582,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.VOLT.0222,V222_DDR,33.1524,-1.6856,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.VOLT.0223,V223_DDR,32.6666,-2.1715,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.VOLT.0241,V241_DDR,34.0399,-0.7982,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.VOLT.0243,V243_DDR,33.7538,-1.0843,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.VOLT.0247,V247_DDR,32.7979,-2.0402,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.VOLT.0253,V253_DDR,33.2371,-1.6010,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,31.2711,-3.5670,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,32.5233,-2.3148,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,32.5233,-2.3148,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,32.5233,-2.3148,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,32.5230,-2.3151,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,33.2192,-1.6188,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,33.2192,-1.6188,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHUB,KCPLHUB_H,32.2184,-2.6197,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHUB17,KCPLHUB17_H,32.2331,-2.6050,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHUB18,KCPLHUB18_H,32.2274,-2.6107,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHUB19,KCPLHUB19_H,32.2976,-2.5405,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHUB20,KCPLHUB20_H,32.2331,-2.6050,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHUB21,KCPLHUB21_H,32.2893,-2.5488,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHUB22,KCPLHUB22_H,32.2522,-2.5859,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHUB23,KCPLHUB23_H,32.2289,-2.6092,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLHUB24,KCPLHUB24_H,32.2154,-2.6227,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,32.7738,-2.0643,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,32.7738,-2.0643,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,31.9245,-2.9136,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,31.9245,-2.9136,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,33.2345,-1.6036,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,33.2152,-1.6229,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,33.2881,-1.5500,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,33.2881,-1.5500,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,33.2880,-1.5500,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,33.2880,-1.5500,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,33.2880,-1.5501,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,33.2880,-1.5501,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,33.2880,-1.5501,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,33.2880,-1.5501,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,32.4379,-2.4001,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,33.1709,-1.6672,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KCPL_KCPL,KCPL_LA,33.1055,-1.7326,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KENN,KENN_LA,33.8766,-0.9615,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KEP2_SECI,KEP2_SECI_LA,34.4089,-0.4292,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KERR_1,GRDAKERR_HYDUN1_RA,33.9711,-0.8670,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KERR_2,GRDAKERR_HYDUN2_RA,33.9942,-0.8439,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KERR_3,GRDAKERR_HYDUN3_RA,33.9942,-0.8439,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KERR_4,GRDAKERR_HYDUN4_RA,33.9711,-0.8670,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,32.5228,-2.3153,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,32.5228,-2.3153,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,32.7039,-2.1342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,32.7039,-2.1342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,32.5396,-2.2985,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,32.6030,-2.2351,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,32.6030,-2.2351,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,33.6430,-1.1950,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,33.6430,-1.1950,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,33.6430,-1.1950,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,34.1598,-0.6782,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,34.1598,-0.6782,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,33.6056,-1.2325,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,33.9920,-0.8461,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,32.4994,-2.3386,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,32.9951,-1.8430,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,32.9951,-1.8430,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,32.6650,-2.1730,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,32.6650,-2.1730,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,32.6650,-2.1730,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,34.6088,-0.2292,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,33.3798,-1.4583,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,32.9800,-1.8581,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,KMEA_EUDORA,KMEA_EUDORA_LA,32.9386,-1.8994,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,LAFA,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,LAM345,LAM345,33.4751,-1.3630,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,LEPA,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_JSTREET,LES8_NUNJ_STREET_RA,33.9690,-0.8690,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_LES,LES_LA,33.9234,-0.9147,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,33.6947,-1.1433,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_ROKEBY_1,LESROKEBYUN1_RA,33.7793,-1.0588,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_ROKEBY_2,LESROKEBYUN2_RA,33.8361,-1.0019,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_ROKEBY_3,LESROKEBYUN3_RA,33.8361,-1.0019,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_TBGS_CC1,LES84_BLUFPLT1,33.7084,-1.1297,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,33.6947,-1.1433,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_WAVERLY,LES_WAVERLY_H,33.7926,-1.0454,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,33.7129,-1.1252,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,33.7145,-1.1235,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,LGEE,LGEE,33.9202,-0.9178,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MALDEN,MALDEN_LA,33.8745,-0.9636,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MCWEST,MCWEST,35.6544,0.8163,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MDU,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,34.9627,0.1246,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,34.0836,-0.7545,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,35.8070,0.9689,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MEAN_NPPD,NPPD_MEAN_LA,35.2946,0.4565,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MEC,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MHEB,MHEB,35.5532,0.7151,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,34.1773,-0.6608,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,34.4057,-0.4323,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,34.1773,-0.6608,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,34.1773,-0.6608,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,34.4057,-0.4323,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,32.9091,-1.9289,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MISO,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,34.7176,-0.1204,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,34.7176,-0.1204,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,33.0952,-1.7429,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,33.5173,-1.3207,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,33.8410,-0.9971,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,33.0121,-1.8260,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKEC_KPP,SECI_MKEC_KPP_LA,33.3998,-1.4383,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,33.1710,-1.6670,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,33.6039,-1.2342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,33.6039,-1.2342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,33.6039,-1.2342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,33.6039,-1.2342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,33.6039,-1.2342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,33.3967,-1.4413,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,33.8301,-1.0079,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,33.8301,-1.0079,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,33.7989,-1.0392,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,34.2535,-0.5845,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MOWR,AECI,33.7810,-1.0571,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,33.6231,-1.2150,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,33.8369,-1.0011,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,32.7945,-2.0435,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,32.9190,-1.9191,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,32.3367,-2.5014,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,32.8134,-2.0247,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,32.5872,-2.2509,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,32.5872,-2.2509,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,32.5087,-2.3294,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,32.5087,-2.3294,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,33.1524,-1.6856,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,33.1524,-1.6856,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,33.1524,-1.6856,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,33.0914,-1.7467,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,33.1524,-1.6856,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,33.1524,-1.6856,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,33.1524,-1.6856,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,33.8848,-0.9533,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,32.3230,-2.5151,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,31.9284,-2.9097,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,31.8287,-3.0094,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,31.9286,-2.9094,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSTWA1UN1,MPSTWA1UN1_RA,33.2411,-1.5969,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPSTWA1UN2,MPSTWA1UN2_RA,33.2411,-1.5969,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MPS_MPS,MPS_LA,33.2754,-1.5627,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MSTNG,SPSMSTNGPLT1,39.3204,4.4824,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,MSTNG4,SPSMSTNGUN4_RA,38.8629,4.0248,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MSTNG5,SPSMSTNGUN5_RA,39.0477,4.2096,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,39.0477,4.2096,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NBSO,PJM,33.9486,-0.8895,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,32.8005,-2.0376,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,32.7988,-2.0393,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,35.1761,0.3381,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NHC1,VACS,33.9468,-0.8912,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,33.9591,-0.8790,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,33.9591,-0.8790,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,33.9591,-0.8790,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,36.4429,1.6049,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,35.1659,0.3279,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,33.6668,-1.1713,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,33.9967,-0.8414,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,35.1659,0.3279,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.HUB.PY2018,NPPDPY18_H,33.2289,-1.6092,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,33.2134,-1.6247,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,33.2268,-1.6113,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,33.1959,-1.6422,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,34.0978,-0.7403,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,34.5464,-0.2917,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,34.5464,-0.2917,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,34.5425,-0.2956,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,34.0978,-0.7403,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,33.9745,-0.8635,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,35.8051,0.9670,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,34.5285,-0.3096,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,35.8051,0.9670,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,36.0768,1.2388,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,35.5615,0.7234,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,34.1661,-0.6720,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,35.1659,0.3279,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,34.5441,-0.2940,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,34.5464,-0.2917,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,34.5464,-0.2917,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,34.9926,0.1545,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,34.9878,0.1498,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,34.9878,0.1498,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,35.6453,0.8072,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,34.4529,-0.3852,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,35.3772,0.5391,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,36.5489,1.7108,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,34.5936,-0.2444,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,34.6942,-0.1439,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.NELI.DDR,NELI_DDR,34.2253,-0.6127,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.NPPM.1058,SH1058_DDR,34.7393,-0.0988,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,35.2546,0.4165,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,35.1659,0.3279,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,33.6668,-1.1713,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,34.1211,-0.7170,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.TECH.1,KEARNE_DDR,35.6497,0.8116,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,34.4457,-0.3924,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,34.4457,-0.3924,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,34.1335,-0.7045,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD.VOLT.0236,V236_DDR,33.8120,-1.0261,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD2017HUB,NPPD2017HUB_H,33.2093,-1.6287,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,34.2179,-0.6202,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,36.4429,1.6049,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,35.8453,1.0072,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,35.8453,1.0072,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_BPS,NPPDBEAPWRSTPLT1,33.7898,-1.0482,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,33.8531,-0.9850,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,34.4166,-0.4215,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,34.9413,0.1033,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,34.1185,-0.7196,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,34.4072,-0.4308,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,34.1205,-0.7175,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,35.2729,0.4348,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_COOPR,NPPDCOOPERUN1_RA,32.9256,-1.9125,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_COSN_NPPD,NPPD_COSN_LA,35.5751,0.7371,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,34.3945,-0.4435,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,34.4107,-0.4274,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,34.4818,-0.3563,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,34.4590,-0.3790,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,35.1305,0.2924,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,35.0973,0.2592,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,35.0973,0.2592,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,35.2087,0.3707,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,33.9745,-0.8635,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,35.1994,0.3613,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,33.6296,-1.2085,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,35.3285,0.4904,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,35.3059,0.4678,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,35.3219,0.4838,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,35.3219,0.4838,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,35.2729,0.4348,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,35.2729,0.4348,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,37.0827,2.2446,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,35.1131,0.2750,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,34.2416,-0.5964,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,34.8535,0.0154,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,34.4422,-0.3959,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,34.5612,-0.2769,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_NELI_LD,NPPD_NELIGH_LA,34.2253,-0.6127,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,34.6346,-0.2034,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,34.6346,-0.2034,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_NPPD,NPPD_LA,34.7500,-0.0881,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,33.6296,-1.2085,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,33.6296,-1.2085,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,33.2407,-1.5974,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,35.6917,0.8536,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NSB,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,NSP,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NSSO,PJM,33.9486,-0.8895,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,NYIS,PJM,33.9486,-0.8895,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,33.4271,-1.4110,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,32.2304,-2.6077,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,32.0622,-2.7759,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,32.0622,-2.7759,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,33.8198,-1.0183,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,32.6744,-2.1637,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,32.5683,-2.2698,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,31.0783,-3.7597,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,32.1313,-2.7067,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,32.0957,-2.7424,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,33.4270,-1.4111,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,32.1313,-2.7067,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,33.7040,-1.1341,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,32.9091,-1.9289,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,33.2747,-1.5634,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,33.6010,-1.2371,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,32.0957,-2.7424,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,32.6374,-2.2007,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,32.9748,-1.8632,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,32.9949,-1.8431,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,33.3084,-1.5297,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,32.9091,-1.9289,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,32.9091,-1.9289,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,32.0957,-2.7424,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.NUEN.ADA1,ADA1_DDR,33.6453,-1.1928,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.NUEN.LAM1,LAM1_DDR,35.0675,0.2294,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.NUEN.MDT2,MDT2_DDR,33.4323,-1.4058,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.NUEN.MDT3,MDT3_DDR,33.4323,-1.4058,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.NUEN.WWO1,WWO1_DDR,33.6584,-1.1796,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,33.4560,-1.3821,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,33.4553,-1.3827,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,33.4949,-1.3432,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,33.5710,-1.2671,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,33.5710,-1.2671,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,33.4946,-1.3435,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,33.4946,-1.3435,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,32.0957,-2.7424,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,33.8623,-0.9758,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,33.7040,-1.1341,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,32.7269,-2.1112,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,32.6374,-2.2007,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,33.7495,-1.0886,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,32.7467,-2.0914,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,32.7467,-2.0914,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,32.8993,-1.9387,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,32.8993,-1.9387,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,32.0909,-2.7471,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,32.3083,-2.5298,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,32.2304,-2.6077,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,32.2700,-2.5681,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,32.2700,-2.5681,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,33.5131,-1.3250,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,32.9575,-1.8805,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,32.9575,-1.8805,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,32.9575,-1.8805,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0033,FOSTER_DDR,33.6266,-1.2115,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0034,CUSHOIL_DDR,34.7301,-0.1079,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0035,TARBY_DDR,34.4982,-0.3398,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0036,CUSHFLI_DDR,34.7301,-0.1079,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,34.2800,-0.5580,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,34.2800,-0.5580,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,33.3359,-1.5021,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0040,TROSPER_DDR,33.6920,-1.1461,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,33.6943,-1.1438,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,33.9982,-0.8399,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0115,V115_DDR,33.4625,-1.3756,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0116,V116_DDR,33.7083,-1.1297,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0118,V118_DDR,33.8777,-0.9604,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0125,V125_DDR,34.2814,-0.5567,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0126,V126_DDR,34.0263,-0.8117,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0129,V129_DDR,33.1577,-1.6804,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,33.4787,-1.3594,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0134,V134_DDR,34.0777,-0.7603,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0138,V138_DDR,33.9871,-0.8509,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,33.6494,-1.1887,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0143,V143_DDR,34.1267,-0.7114,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0149,V149_DDR,33.2710,-1.5671,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0150,V150_DDR,33.4138,-1.4243,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0155,V155_DDR,33.9294,-0.9087,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0156,V156_DDR,33.4787,-1.3594,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0166,V166_DDR,35.4212,0.5832,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,33.6714,-1.1667,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,33.4138,-1.4243,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0170,V170_DDR,33.6495,-1.1885,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,33.1905,-1.6476,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0176,V176_DDR,33.4138,-1.4243,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0177,V177_DDR,32.8848,-1.9533,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,33.6789,-1.1592,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,33.3527,-1.4853,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0195,V195_DDR,35.0610,0.2229,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0197,V197_DDR,34.4986,-0.3394,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0198,V198_DDR,35.4212,0.5832,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0208,V208_DDR,35.0838,0.2458,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0209,V209_DDR,35.0838,0.2458,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,34.2451,-0.5930,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0216,V216_DDR,33.6923,-1.1458,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0219,V219_DDR,33.9294,-0.9087,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0220,V220_DDR,33.4138,-1.4243,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0224,V224_DDR,33.5682,-1.2699,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0225,V225_DDR,33.5698,-1.2682,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0226,V226_DDR,33.5682,-1.2699,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0227,V227_DDR,33.5682,-1.2699,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0229,V229_DDR,33.3304,-1.5076,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0231,V231_DDR,34.2188,-0.6193,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0238,V238_DDR,32.6091,-2.2289,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.VOLT.0242,V242_DDR,33.9577,-0.8803,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,32.6946,-2.1435,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,32.9091,-1.9289,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,32.3896,-2.4485,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,33.2872,-1.5509,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,32.6946,-2.1435,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,33.5348,-1.3032,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,30.9384,-3.8997,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEHL7,OKGEHL7_H,33.6226,-1.2154,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEHL8,OKGEHSL1UN8_RA,33.6226,-1.2154,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEHL910,OKGEHSL1PLT2,33.6226,-1.2154,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,33.4310,-1.4071,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEMCC,OKGEMCCLAIPLT1,32.8887,-1.9494,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,33.7526,-1.0855,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,33.7526,-1.0855,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,33.6957,-1.1424,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,33.0987,-1.7394,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,32.9264,-1.9117,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,32.9305,-1.9076,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,33.0987,-1.7394,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGESM1,OKGESEMINOLEUN1_RA,33.5098,-1.3283,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGESM2,OKGESEMINOLEUN2_RA,33.4578,-1.3803,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGESM3,OKGESEMINOLEUN3_RA,33.4578,-1.3803,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGESO1,OKGESONR1UN1_RA,32.1854,-2.6527,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGESO2,OKGESONR1UN2_RA,32.2700,-2.5681,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,33.4004,-1.4377,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,32.9811,-1.8569,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGETINK5A,OKGETINK5UN1_RA,33.6161,-1.2219,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGETINK5B,OKGETINK5UN2_RA,33.6161,-1.2219,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,33.0931,-1.7449,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,32.2304,-2.6077,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,33.6185,-1.2196,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,32.9091,-1.9289,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE_OKGE,OKGE_LA,33.6369,-1.2012,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,32.7269,-2.1112,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,33.0793,-1.7588,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMLP,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,33.9098,-0.9283,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,33.5192,-1.3189,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_GENHUB,OMPA_GENHUB_H,32.9016,-1.9365,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_KAW,OKGEOMKAWUN2_RA,32.7216,-2.1165,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,33.2555,-1.5826,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,32.1313,-2.7067,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,33.3195,-1.5186,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,32.4187,-2.4194,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,33.8726,-0.9655,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,32.7244,-2.1136,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,32.7244,-2.1136,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_SPP,OMPA_SPP_LA,33.1667,-1.6714,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,32.6946,-2.1435,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ONETA,CSWSCALPINEUNONETA_1_RA,33.8699,-0.9682,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,33.8699,-0.9682,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,33.8699,-0.9682,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,33.8699,-0.9682,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,ONT,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,33.9583,-0.8798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,33.9583,-0.8798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,33.9583,-0.8798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,33.9583,-0.8798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,33.9583,-0.8798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,33.9583,-0.8798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,33.9583,-0.8798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,33.9583,-0.8798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,33.9583,-0.8798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,33.8967,-0.9414,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,33.9591,-0.8790,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,33.7082,-1.1298,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,33.9531,-0.8850,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,33.9531,-0.8850,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD_GLDN,OPPD_GLDN_LA,33.9541,-0.8840,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD_GLDN2,OPPD_GLDN2_LA,33.9922,-0.8458,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,33.9745,-0.8635,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD_NC_HST,OPPD_NC_HST_LA,33.3322,-1.5059,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD_NO_HST,OPPD_NO_HST_LA,33.9435,-0.8946,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD_OPPD,OPPD_LA,34.0704,-0.7676,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD_PAPIO,OPPD_PAPIO_LA,33.9692,-0.8689,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,33.9661,-0.8719,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,OTP,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,OVEC,OVEC,33.9282,-0.9098,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,PARAGOULD,PARAGOULD_LA,33.8803,-0.9578,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PENSACOLA_1,GRDAPENSA1UN1_RA,33.8979,-0.9402,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PENSACOLA_2,GRDAPENSA1UN2_RA,33.8979,-0.9402,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PENSACOLA_3,GRDAPENSA1UN3_RA,33.8979,-0.9402,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PENSACOLA_4,GRDAPENSA1UN4_RA,33.9259,-0.9122,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PENSACOLA_5,GRDAPENSA1UN5_RA,33.9259,-0.9122,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PENSACOLA_6,GRDAPENSA1UN6_RA,33.9259,-0.9122,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PIGGOTT,PIGGOTT_LA,33.8758,-0.9622,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,PJM,PJM,33.9486,-0.8895,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PLUM,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,POPLARBLUFF,POPLARBLUFF_LA,33.8749,-0.9632,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,35.7833,0.9452,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,35.7833,0.9452,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,35.7096,0.8715,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,35.7096,0.8715,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,38.2459,3.4078,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,38.2378,3.3997,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,35.6351,0.7971,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,35.5730,0.7349,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,32.4185,-2.4196,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,33.9733,-0.8648,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,33.1019,-1.7362,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,33.5188,-1.3192,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,34.1919,-0.6462,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,34.2644,-0.5737,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,34.3675,-0.4705,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,36.5431,1.7051,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,34.7205,-0.1175,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,36.6805,1.8424,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,36.7338,1.8957,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,34.8920,0.0540,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,PUPP,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,RCEAST,RCEAST,34.2736,-0.5645,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SALINA_1,GRDASALINA1UN1_RA,33.9753,-0.8628,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SALINA_2,GRDASALINA1UN2_RA,33.9753,-0.8628,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SALINA_3,GRDASALINA1UN3_RA,33.9753,-0.8628,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SALINA_4,GRDASALINA1UN4_RA,33.9753,-0.8628,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SALINA_5,GRDASALINA1UN5_RA,33.9753,-0.8628,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SALINA_6,GRDASALINA1UN6_RA,33.9753,-0.8628,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SARPY_1,OPPDSARPYUN1_RA,33.9230,-0.9151,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SARPY_2,OPPDSARPYUN2_RA,33.9990,-0.8390,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SARPY_3,OPPDSARPYUN3_RA,33.8406,-0.9974,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SARPY_4,OPPDSARPYUN4_RA,33.8406,-0.9974,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SARPY_5,OPPDSARPYUN5_RA,33.8406,-0.9974,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SC,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SCEG,VACS,33.9468,-0.8912,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SCSE,SCSE,33.9341,-0.9039,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SEC,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,32.8146,-2.0235,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,32.8146,-2.0235,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,32.8146,-2.0235,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,34.9673,0.1293,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,32.8146,-2.0235,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,33.2626,-1.5755,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,33.1116,-1.7265,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,33.1116,-1.7265,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,33.5980,-1.2401,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,32.7496,-2.0885,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,34.0360,-0.8021,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,34.4237,-0.4143,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,34.2256,-0.6124,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,32.7965,-2.0415,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,34.1251,-0.7130,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,33.6136,-1.2245,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,33.8155,-1.0226,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,33.4446,-1.3934,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,33.4462,-1.3918,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,33.4462,-1.3918,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,33.4462,-1.3918,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,33.3262,-1.5119,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,33.2626,-1.5755,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI_SECI,SECI_LA,34.1817,-0.6564,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,33.1740,-1.6641,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,33.1740,-1.6641,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,33.5980,-1.2401,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SEHA,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,33.0793,-1.7588,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SERU,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SETH,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SGE,SGE,33.6762,-1.1619,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SMEP,MISO,34.2039,-0.6342,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SOCO,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPA,SPA,33.8797,-0.9584,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPC,SPC,37.0574,2.2193,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPPNORTH_HUB,SPPNORTH_H,34.5103,-0.3277,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPPSOUTH_HUB,SPPSOUTH_H,33.3683,-1.4698,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,34.0099,-0.8281,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,34.0195,-0.8186,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,34.1198,-0.7183,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,34.1198,-0.7183,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_NIXA,SPRM_NIXA_LA,34.1482,-0.6899,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_SPRM,SPRM_LA,34.2859,-0.5522,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,34.0192,-0.8189,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,34.0192,-0.8189,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,33.9553,-0.8828,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,34.0192,-0.8189,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,38.6506,3.8125,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,38.4137,3.5756,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,34.8661,0.0280,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,34.8661,0.0280,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,37.4269,2.5888,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,39.4809,4.6428,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,39.6770,4.8389,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,39.3166,4.4785,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,36.4941,1.6560,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,38.9055,4.0674,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,39.3309,4.4928,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,39.3309,4.4928,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,38.9055,4.0674,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,35.0663,0.2283,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,38.4137,3.5756,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,35.4214,0.5833,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,34.2649,-0.5732,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,35.9252,1.0872,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,36.6850,1.8470,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,35.6695,0.8314,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,33.9697,-0.8683,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,33.9696,-0.8684,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,33.9696,-0.8684,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,33.9696,-0.8684,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GRID.WRAB,WRAB_DDR,36.5449,1.7068,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,33.9696,-0.8684,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,37.2307,2.3926,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,37.2307,2.3926,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,37.2692,2.4312,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,37.2692,2.4312,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,37.2692,2.4312,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,37.2307,2.3926,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,34.8367,-0.0014,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,34.8367,-0.0014,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,34.8374,-0.0007,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,35.1761,0.3381,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.HOBBS.CC,SPSHOBBSPLT1,38.9212,4.0832,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.JONES1,SPSJONESSUBUN1_RA,36.4553,1.6173,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.JONES2,SPSJONESSUBUN2_RA,36.4557,1.6177,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.JONES3,SPSJONESSUBUN3_RA,36.4554,1.6174,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.JONES4,SPSJONESSUBUN4_RA,36.4554,1.6174,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,39.1998,4.3617,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,38.9470,4.1090,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,38.9471,4.1090,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,33.1028,-1.7353,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,34.6890,-0.1491,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,34.6890,-0.1491,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,34.8429,0.0048,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,36.5449,1.7068,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,34.8994,0.0613,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,34.9774,0.1393,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,33.8198,-1.0183,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,35.1417,0.3036,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.PLANTX1,SPS.PLANTX1_H,38.5173,3.6793,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.PLANTX2,SPS.PLANTX2_H,38.5173,3.6793,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,38.4112,3.5731,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,37.3185,2.4804,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,34.2761,-0.5620,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,39.9832,5.1451,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,37.4356,2.5976,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,35.2408,0.4027,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,39.0135,4.1755,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,39.8067,4.9687,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,39.0135,4.1755,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,39.3597,4.5216,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,34.9211,0.0830,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,41.2123,6.3742,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,41.2830,6.4449,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,40.4984,5.6604,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,39.3389,4.5009,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,41.2582,6.4202,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,33.4751,-1.3630,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,36.3900,1.5520,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,38.5874,3.7493,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,38.5874,3.7493,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,39.0135,4.1755,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,36.5748,1.7368,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0006,SPS.VOLT.0006_H,40.1113,5.2732,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0023,SPS.VOLT.0023_H,39.2952,4.4572,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0025,SPS.VOLT.0025_H,39.5932,4.7552,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0033,SPS.VOLT.0033_H,37.4369,2.5989,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0045,SPS.VOLT.0045_H,41.2123,6.3742,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0046,SPS.VOLT.0046_H,42.5420,7.7039,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0047,SPS.VOLT.0047_H,41.7688,6.9308,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0052,SPS.VOLT.0052_H,37.7283,2.8902,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0113,SPS.VOLT.0113_H,39.9204,5.0823,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0136,SPS.VOLT.0136_H,34.6477,-0.1904,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0137,SPS.VOLT.0137_H,34.5857,-0.2524,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0163,V163_DDR,35.9161,1.0780,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0168,V168_DDR,33.8011,-1.0370,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0180,V180_DDR,42.5420,7.7039,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0181,V181_DDR,34.6917,-0.1463,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0182,V182_DDR,41.3990,6.5610,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0199,V199_DDR,39.8143,4.9762,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0200,V200_DDR,40.0048,5.1667,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.VOLT.0235,V235_DDR,34.8994,0.0613,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,39.6770,4.8389,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,39.3166,4.4785,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,35.7228,0.8847,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,37.5170,2.6789,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS_SPS,SPS_LA,39.0251,4.1871,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,38.7039,3.8659,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SSCN_NPPD,SSCN_NPPD_LA,34.2632,-0.5748,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,33.8621,-0.9760,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,33.8621,-0.9760,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,TAL,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,TEC,SOUC,33.9750,-0.8630,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,34.8535,0.0154,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,TVA,TVA,33.9172,-0.9209,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,UCUHUB,UCUHUB_H,32.7954,-2.0426,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,UCUHUB17,UCUHUB17_H,33.0746,-1.7635,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,UCUHUB18,UCUHUB18_H,32.9053,-1.9327,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,UCUHUB19,UCUHUB19_H,32.7987,-2.0394,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,UCUHUB20,UCUHUB20_H,32.7893,-2.0487,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,UCUHUB21,UCUHUB21_H,32.8383,-1.9998,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,UCUHUB22,UCUHUB22_H,32.7892,-2.0489,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,UCUHUB23,UCUHUB23_H,32.7962,-2.0418,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,UCUHUB24,UCUHUB24_H,32.7583,-2.0797,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,37.6465,2.8084,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,37.6465,2.8084,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,35.5599,0.7219,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,35.5599,0.7219,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,35.5842,0.7461,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,35.6655,0.8274,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,35.6655,0.8274,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,37.6465,2.8084,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,36.0254,1.1873,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,36.4887,1.6507,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,34.3815,-0.4566,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,34.1578,-0.6803,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,37.6006,2.7626,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,37.6006,2.7626,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,33.9813,-0.8568,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,34.4265,-0.4116,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,36.2179,1.3798,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,34.4125,-0.4256,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,35.4022,0.5642,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,34.3968,-0.4413,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,34.4229,-0.4152,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,34.4229,-0.4152,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,34.5523,-0.2858,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,34.2475,-0.5905,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,36.2051,1.3670,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,36.5443,1.7062,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,36.5443,1.7062,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,36.5443,1.7062,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,36.5443,1.7062,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,36.5443,1.7062,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,36.5443,1.7062,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,37.9897,3.1517,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,35.3320,0.4939,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,35.3292,0.4911,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,33.4596,-1.3784,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,35.2135,0.3754,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,36.4580,1.6199,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,34.0020,-0.8361,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,33.7681,-1.0700,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,34.8232,-0.0148,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,37.2855,2.4474,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,37.2855,2.4474,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,37.2817,2.4436,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,37.2855,2.4474,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,37.4075,2.5694,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,37.4075,2.5694,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,37.4075,2.5694,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,37.4075,2.5694,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,37.4075,2.5694,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,37.4075,2.5694,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,37.4075,2.5694,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,34.0935,-0.7445,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,36.8100,1.9719,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,35.1324,0.2943,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,35.1324,0.2943,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,35.2076,0.3695,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,35.2076,0.3695,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,35.7235,0.8854,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,35.6745,0.8364,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,34.7504,-0.0876,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,34.2481,-0.5900,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,34.2740,-0.5641,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,35.5842,0.7461,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,35.5842,0.7461,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,34.4125,-0.4256,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,34.2938,-0.5443,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,34.7381,-0.1000,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,33.8536,-0.9845,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,34.5814,-0.2566,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.FSE,WAUE.FSE_H,34.2419,-0.5962,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,35.7254,0.8873,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,35.6825,0.8444,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,33.4585,-1.3796,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,33.4077,-1.4304,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,35.1847,0.3466,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,35.0139,0.1758,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,34.0450,-0.7931,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,34.1578,-0.6803,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,33.3703,-1.4678,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,32.9287,-1.9094,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,32.9281,-1.9099,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,33.0820,-1.7560,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,34.6827,-0.1553,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,34.2938,-0.5443,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,34.7418,-0.0963,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,34.5891,-0.2489,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,36.1209,1.2828,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,34.7984,-0.0397,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,34.6711,-0.1670,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,33.3861,-1.4520,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,35.3692,0.5312,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,34.2323,-0.6058,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,34.0020,-0.8361,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,35.5917,0.7536,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,34.3628,-0.4753,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,35.1408,0.3027,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,34.8312,-0.0068,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,33.7145,-1.1235,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NTWK,WAUE.NTWK_H,35.2128,0.3747,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,35.5777,0.7396,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,35.5777,0.7396,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,34.3677,-0.4704,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,34.2331,-0.6050,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,34.7159,-0.1221,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,34.3677,-0.4704,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,35.6240,0.7859,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,34.4865,-0.3516,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,34.0020,-0.8361,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,34.9080,0.0699,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,36.3159,1.4779,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,32.8502,-1.9879,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,32.7375,-2.1006,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,35.4325,0.5944,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,34.3750,-0.4631,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,34.5000,-0.3380,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,34.2994,-0.5387,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,34.2481,-0.5900,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.VOLT.0152,V152_DDR,38.3166,3.4785,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE.VOLT.0172,V172_DDR,37.5354,2.6974,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_BEPM,WAUE_BEPM_LA,36.4124,1.5743,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,34.7740,-0.0641,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,34.8278,-0.0102,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_EWA,WAUE_EWA_LA,34.3711,-0.4670,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,34.7330,-0.1051,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_HMMU,WAUE_HMMU_LA,34.2787,-0.5593,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,34.1133,-0.7248,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_MECB,WAUE_MECB_LA,34.5089,-0.3291,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_MMPA,WAUE_MMPA_LA,36.0801,1.2420,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_MRES,WAUE_MRES_LA,35.0010,0.1629,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,37.8410,3.0030,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,35.7254,0.8873,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,34.9285,0.0904,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_OTP,WAUE_OTP_LA,37.4769,2.6389,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_OTPW,WAUE_OTPW_LA,36.1965,1.3584,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM,WAUE_UGPM_LA,34.7596,-0.0784,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,36.0239,1.1858,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,34.7584,-0.0797,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,35.3504,0.5123,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,34.3711,-0.4670,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,34.2787,-0.5593,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,34.8058,-0.0323,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,35.7254,0.8873,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,36.0801,1.2420,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,35.2546,0.4166,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,34.6397,-0.1984,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,38.1098,3.2717,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,32.7679,-2.0702,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,32.6416,-2.1965,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,32.0520,-2.7860,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,34.3531,-0.4850,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,34.3531,-0.4850,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,31.4038,-3.4343,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,34.4620,-0.3761,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,34.3823,-0.4558,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,32.1703,-2.6678,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,32.1705,-2.6676,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,32.1735,-2.6645,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,32.3518,-2.4863,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,32.3518,-2.4863,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,32.3518,-2.4863,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,32.3518,-2.4863,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,32.3518,-2.4863,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,32.3862,-2.4518,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,33.8198,-1.0183,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,31.6155,-3.2226,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,33.1073,-1.7308,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,39.6917,4.8537,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_ENMC,WFEC_ENMC_LA,40.0964,5.2583,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,32.0957,-2.7424,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,33.7714,-1.0666,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,38.9076,4.0696,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,32.7287,-2.1094,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,32.7679,-2.0702,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,32.7679,-2.0702,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_OKGE,WFEC_OKGE_LA,33.6455,-1.1925,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,34.6694,-0.1687,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,32.8246,-2.0135,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,32.3499,-2.4881,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_WFEC,WFEC_LA,33.8400,-0.9980,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,38.9076,4.0696,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,34.1143,-0.7238,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,33.8377,-1.0004,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,32.2564,-2.5817,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,32.2564,-2.5817,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,32.2413,-2.5968,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,32.2413,-2.5968,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,32.2563,-2.5818,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,32.2563,-2.5818,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,32.2563,-2.5818,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,33.7237,-1.1144,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,32.4282,-2.4098,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,32.1651,-2.6729,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,32.1651,-2.6729,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,32.1651,-2.6729,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,32.7418,-2.0963,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,32.7418,-2.0963,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.GEEC.GT1,WRGORDUNG1_RA,32.3316,-2.5065,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.GEEC.GT2,WRGORDUNG2_RA,32.3316,-2.5065,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.GEEC.GT3,WRGORDUNGT3_RA,32.2208,-2.6173,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,32.4282,-2.4098,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,32.7452,-2.0929,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.HEC.GT1,WRHECGTUN32_RA,32.7823,-2.0558,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.HEC.GT2,WRHECGTUN33_RA,32.8001,-2.0380,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.HEC.GT3,WRHECGTUN34_RA,32.8070,-2.0311,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.HEC.GT4,WRHECGTUN35_RA,32.8089,-2.0292,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,32.7452,-2.0929,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,32.7819,-2.0562,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,32.1923,-2.6458,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.JEC.1,WRJEFFUN10_RA,32.2844,-2.5537,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.JEC.2,WRJEFFUN11_RA,32.1222,-2.7158,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.JEC.3,WRJEFFUN12_RA,32.2779,-2.5601,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,32.1250,-2.7130,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,32.3512,-2.4868,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,32.3512,-2.4868,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.LEC.4,WRLECUN26_RA,32.5698,-2.2683,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.LEC.5,WRLECUN27_RA,32.7492,-2.0889,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MCPH.CT1,WRCMCPHUN37_RA,33.0113,-1.8268,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MCPH.CT2,WRCMCPHUN38_RA,33.0113,-1.8268,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MCPH.CT3,WRCMCPHUN48_RA,33.0055,-1.8326,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MCPH.CT4,WRCJOHNUN1_RA,33.0909,-1.7471,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,33.1740,-1.6641,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,33.1740,-1.6641,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,34.6114,-0.2266,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,34.1754,-0.6627,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,34.1754,-0.6627,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,33.3850,-1.4531,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,33.1740,-1.6641,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,32.7499,-2.0882,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,32.5004,-2.3377,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,32.3429,-2.4952,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,34.3949,-0.4432,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,33.4181,-1.4199,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.READ.READ,WREMPECUNREADINGWF_RA,32.2563,-2.5818,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,31.2875,-3.5505,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,32.7452,-2.0929,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,32.4282,-2.4098,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,32.5836,-2.2545,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.THAYERLD,WR.THAYERLD_LA,33.8919,-0.9462,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0102,WR.VOLT.0102_H,32.6041,-2.2340,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0106,V106_DDR,32.5839,-2.2541,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0139,WR.VOLT.0139_H,32.9717,-1.8664,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0141,WR.VOLT.0141_H,32.9652,-1.8728,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0146,WR.VOLT.0146_H,32.9020,-1.9360,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0147,WR.VOLT.0147_H,32.9020,-1.9360,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0148,WR.VOLT.0148_H,32.8261,-2.0120,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0153,WR.VOLT.0153_H,32.8642,-1.9739,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0157,V157_DDR,32.8686,-1.9694,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0158,V158_DDR,32.9020,-1.9360,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0159,WR.VOLT.0159_H,32.9020,-1.9360,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0165,WR.VOLT.0165_H,32.4025,-2.4356,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0173,V173_DDR,33.1422,-1.6958,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0174,V174_DDR,32.5527,-2.2854,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0184,V184_DDR,32.3414,-2.4967,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0185,WR.VOLT.0185_H,32.5688,-2.2693,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0186,V186_DDR,32.5007,-2.3373,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0187,WR.VOLT.0187_H,32.4203,-2.4177,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0188,WR.VOLT.0188_H,32.6137,-2.2243,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0189,WR.VOLT.0189_H,33.2997,-1.5384,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0190,WR.VOLT.0190_H,32.4410,-2.3971,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0191,WR.VOLT.0191_H,32.3504,-2.4877,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0192,WR.VOLT.0192_H,32.3504,-2.4877,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0196,WR.VOLT.0196_H,32.4410,-2.3971,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0245,V245_DDR,32.5740,-2.2640,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.VOLT.0248,V248_DDR,32.5839,-2.2541,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,32.1382,-2.6999,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,32.8254,-2.0127,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.WOLF,WRWOLFUN15_RA,31.1180,-3.7201,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,32.7819,-2.0562,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,33.2265,-1.6116,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,32.1651,-2.6729,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,32.1651,-2.6729,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,32.1651,-2.6729,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,32.1651,-2.6729,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KPP_NITS,WR_KPP_NITS_LA,32.5015,-2.3366,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,32.9689,-1.8692,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,32.5150,-2.3230,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,32.5150,-2.3230,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,32.5150,-2.3230,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,32.5150,-2.3230,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,32.7193,-2.1188,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,32.7193,-2.1188,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,32.7193,-2.1188,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,32.7193,-2.1188,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,32.7193,-2.1188,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,32.7193,-2.1188,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,32.6451,-2.1929,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,32.6451,-2.1929,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,32.2081,-2.6300,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,32.2081,-2.6300,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_MIDW,WR_MIDW_LA,34.2605,-0.5775,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,33.8734,-0.9647,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,33.1056,-1.7325,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,34.0810,-0.7571,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_SEG,WR_SEG_LA,33.3215,-1.5166,0.0000,34.8381\n03/31/2025 08:55:00,03/31/2025 13:55:00,WR_WR,WR_LA,32.7950,-2.0430,0.0000,34.8380\n03/31/2025 08:55:00,03/31/2025 13:55:00,YAD,VACS,33.9468,-0.8912,0.0000,34.8380\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_SPP/RTBM-LMP-SL-202503310900.csv",
    "content": "Interval,GMTIntervalEnd,Settlement Location,Pnode,LMP,MLC,MCC,MEC\n03/31/2025 09:00:00,03/31/2025 14:00:00,AEC,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,AECC_CSWS,CSWS_AECC_LA,28.2567,-0.5179,0.0438,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,28.4159,-0.3353,0.0203,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,27.6324,-1.0946,-0.0038,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,28.1494,-0.5982,0.0168,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,26.5500,-0.7862,-1.3946,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,AECC_HYDRO13,CSWSLD13UN1_RA,27.3773,-1.3586,0.0051,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,28.7122,-0.3589,0.3403,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,AECI,AECI,27.8898,-0.8306,-0.0104,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,AEPM_CSWS,CSWS_LA,28.5229,-0.2859,0.0781,28.7307\n03/31/2025 09:00:00,03/31/2025 14:00:00,ALTW,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,AMRN,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,ANTELOPE,SPSANTELOPEUNANT1_RA,30.5403,1.8604,-0.0509,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BBA,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BCA,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BEPM.ER01.DDR,ER01_DDR,27.2608,-1.4399,-0.0302,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,BEPM_ER01,BEPM_ER01_LA,27.2608,-1.4399,-0.0302,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,30.4958,1.7957,-0.0308,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,28.9656,0.2680,-0.0332,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BEPM_UM01,BEPM_UM01_LA,31.0253,2.3245,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BLKW,BLKW,32.1306,3.4503,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,25.8909,-2.8005,-0.0394,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,25.8909,-2.8005,-0.0394,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,25.8875,-2.7954,-0.0479,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,25.9311,-2.7603,-0.0394,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BRAZ,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BUBA,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,27.5643,-1.1232,-0.0433,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,27.0723,-1.5872,-0.0713,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,27.0723,-1.5872,-0.0713,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,27.0723,-1.5872,-0.0713,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,27.0723,-1.5872,-0.0713,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,27.0723,-1.5872,-0.0713,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,26.7112,-2.0009,-0.0187,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,27.9199,-0.7825,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,27.9199,-0.7825,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CLEC,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,28.0865,-0.6566,0.0123,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,COWP,COWP_LA,27.9691,-0.7314,-0.0303,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,27.9691,-0.7314,-0.0303,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,27.9691,-0.7314,-0.0303,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CPLE,VACS,28.0080,-0.6929,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CPLW,VACS,28.0080,-0.6929,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,27.9032,-0.7817,-0.0460,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,27.9032,-0.7817,-0.0460,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,27.9032,-0.7817,-0.0460,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,27.9032,-0.7817,-0.0460,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CRTH_SPA,WRCRTH_SPA_LA,27.6588,-1.0735,0.0014,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,29.2267,0.3231,0.1728,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,27.1360,-1.6040,0.0092,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,28.7122,-0.3589,0.3403,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,28.1494,-0.5982,0.0168,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWJLSTALL,CSWSSTALL_PPPLT1,29.2242,0.3202,0.1732,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,29.2289,0.3176,0.1804,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,29.1806,0.2726,0.1772,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,29.1806,0.2726,0.1772,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWMATTISON1,CSWSMATTISONUN1_RA,27.8903,-0.8627,0.0222,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWMATTISON2,CSWSMATTISONUN2_RA,27.8903,-0.8627,0.0222,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWMATTISON3,CSWSMATTISONUN3_RA,27.8942,-0.8588,0.0222,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWMATTISON4,CSWSMATTISONUN4_RA,27.8942,-0.8588,0.0222,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,28.7122,-0.3589,0.3403,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWNARROWS1,CSWSNARROWSUN1_RA,28.9601,-0.0260,0.2553,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,27.7377,-1.0185,0.0254,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,27.5481,-1.2081,0.0254,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,27.9084,-0.8478,0.0253,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,27.9690,-0.8057,0.0438,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,27.8479,-0.9268,0.0438,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,27.8415,-0.9331,0.0438,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,27.8415,-0.9331,0.0438,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,26.8586,-1.8612,-0.0110,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,27.6153,-1.0523,-0.0632,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,27.9483,-0.9175,0.1350,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,27.0873,-1.6053,-0.0382,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,26.9841,-1.7085,-0.0382,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,27.2528,-1.5324,0.0544,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.GRID.CDL1,CDL1_DDR,28.1743,-0.6661,0.1096,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,26.9353,-1.4742,-0.3213,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,25.6636,-3.0193,-0.0479,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,28.1743,-0.6661,0.1096,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.NUEN.CSI1,CSI1_DDR,28.3741,-0.3756,0.0188,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.NUEN.CSI2,CSI2_DDR,28.3840,-0.3656,0.0188,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.NUEN.CSI3,NCSI3_DDR,28.0268,-0.7155,0.0115,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.NUEN.GAZA,GAZA_DDR,28.1743,-0.6661,0.1096,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,28.8105,-0.0617,0.1414,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.NUEN.T201,NT201_DDR,28.1583,-0.6114,0.0389,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,27.1094,-1.6468,0.0253,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,27.1094,-1.6468,0.0253,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,28.7122,-0.3589,0.3403,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,29.5755,0.6428,0.2019,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,27.2528,-1.5324,0.0544,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,27.2528,-1.5324,0.0544,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,26.9837,-1.7615,0.0144,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,26.9841,-1.7085,-0.0382,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,28.9644,0.0589,0.1747,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,27.9113,-0.8619,0.0424,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,27.9113,-0.8619,0.0424,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,27.4902,-1.2830,0.0424,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,27.6471,-1.2205,0.1368,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,27.8324,-1.0352,0.1368,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,29.2128,0.2980,0.1840,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,28.1047,-0.6691,0.0430,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,29.2782,0.3649,0.1825,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,30.5512,1.6299,0.1905,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,28.2797,-0.6289,0.1778,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0056,PRYORCRK_DDR,28.3840,-0.3656,0.0188,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0057,OKMU_DDR,28.3195,-0.4907,0.0794,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0060,LEHIGH_DDR,28.6352,-0.2208,0.1252,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0086,WARRENM_DDR,28.0929,-0.6810,0.0431,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,29.6510,0.7227,0.1975,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,28.2068,-0.5535,0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0121,V121_DDR,29.2128,0.2980,0.1840,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0122,V122_DDR,28.1623,-0.5984,0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0124,V124_DDR,28.0356,-0.7208,0.0255,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0135,V135_DDR,28.1847,-0.5874,0.0413,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0144,V144_DDR,27.6136,-1.0418,-0.0754,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0145,V145_DDR,27.4382,-1.2100,-0.0826,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,29.2464,0.3311,0.1845,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,28.7187,-0.2524,0.2403,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0175,V175_DDR,28.0268,-0.7155,0.0115,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,28.7187,-0.2524,0.2403,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,28.8348,-0.1303,0.2343,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,28.1847,-0.5874,0.0413,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,28.1700,-0.6010,0.0402,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,28.0972,-0.6726,0.0389,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,27.9095,-0.8478,0.0265,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,27.9998,-0.7743,0.0433,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,28.1700,-0.6010,0.0402,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0211,V211_DDR,29.5066,0.5964,0.1794,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,28.2186,-0.5396,0.0273,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0213,V213_DDR,28.1114,-0.6611,0.0417,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0215,V215_DDR,28.1650,-0.5953,0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0217,V217_DDR,28.1958,-0.5623,0.0273,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0218,V218_DDR,27.9228,-0.8347,0.0266,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0228,V228_DDR,28.1050,-0.6683,0.0425,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0232,V232_DDR,28.1591,-0.6141,0.0424,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0233,V233_DDR,28.1871,-0.5841,0.0404,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0240,V240_DDR,28.0753,-0.6906,0.0351,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0244,V244_DDR,28.1700,-0.6010,0.0402,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0246,MDT1_DDR,28.8105,-0.0617,0.1414,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0249,V249_DDR,28.1640,-0.6085,0.0417,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0250,V250_DDR,27.1881,-1.5549,0.0122,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0251,V251_DDR,28.0356,-0.7381,0.0429,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.VOLT.0252,V252_DDR,27.9095,-0.8478,0.0265,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,26.9706,-1.7746,0.0144,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,26.4740,-2.2247,-0.0321,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,26.6346,-1.9005,-0.1957,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,29.0618,0.1491,0.1819,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,27.0554,-1.6046,-0.0708,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,27.3422,-1.3061,-0.0826,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,27.3422,-1.3061,-0.0826,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,27.3205,-1.3277,-0.0826,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,26.5674,-2.1225,-0.0409,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,26.5674,-2.1225,-0.0409,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,28.7122,-0.3589,0.3403,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,29.2568,0.3714,0.1546,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,28.1356,-0.6376,0.0424,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,28.0946,-0.6786,0.0424,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,28.3019,-0.5236,0.0947,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,28.3019,-0.5236,0.0947,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWWELSH1,CSWSWELSHUN1_RA,28.7261,-0.2016,0.1969,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWWELSH3,CSWSWELSHUN3_RA,28.7261,-0.2016,0.1969,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWWILKES1,CSWSWILKESUN1_RA,28.8653,-0.0616,0.1961,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWWILKES2,CSWSWILKESUN2_RA,28.8653,-0.0616,0.1961,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,CSWWILKES3,CSWSWILKESUN3_RA,28.8408,-0.0805,0.1905,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,27.0685,-1.6241,-0.0382,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,DENL,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,DERS,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,DOE,DOE,27.9621,-0.7326,-0.0361,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,26.8052,-1.9034,-0.0222,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,DPC,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,DUK,VACS,28.0080,-0.6929,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDDY,EDDY,32.9240,4.2439,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,27.3627,-1.3688,0.0007,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,27.1934,-1.5325,-0.0049,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,27.1626,-1.5692,0.0010,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE.SLCC,EDESTL4391_PLT,26.7323,-2.0027,0.0042,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE.VOLT.0234,EDE.VOLT.0234_H,27.1297,-1.6053,0.0042,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,26.9194,-1.8018,-0.0097,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_EC_01,EDELAR3821UN1_RA,27.3627,-1.3688,0.0007,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_EC_02,EDELAR3821UN2_RA,27.3349,-1.3966,0.0007,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_EC_03,EDELAR3821UN3_RA,27.3627,-1.3688,0.0007,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_EC_04,EDELAR3821UN4_RA,27.3627,-1.3688,0.0007,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_EDE,EDE_LA,27.9264,-0.8048,0.0003,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_ERW,EDEERWFUNG1_RA,26.6561,-2.0541,-0.0206,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,26.7822,-1.9188,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_OZD_5,EDEOZRK_BUN5_RA,28.1528,-0.5652,-0.0128,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_OZD_6,EDEOZRK_BUN6_RA,28.1528,-0.5652,-0.0128,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_OZD_7,EDEOZRK_BUN7_RA,28.1528,-0.5652,-0.0128,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_OZD_8,EDEOZRK_BUN8_RA,28.1528,-0.5652,-0.0128,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,27.9457,-0.7406,-0.0445,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_RIV_10,EDERIV1671UN10_RA,27.1828,-1.5526,0.0046,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_RIV_11,EDERIV1671UN11_RA,27.1828,-1.5526,0.0046,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_RIV_12,EDERIV453UN12_PLT,27.1828,-1.5526,0.0046,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_SL_01,EDESTL4391UN1_RA,26.5528,-2.1822,0.0042,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EDE_SWMP,EDE_SWMP_LA,28.1589,-0.5718,-0.0002,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,EEI,EEI,27.9621,-0.7327,-0.0360,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EES,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,26.5735,-2.1267,-0.0306,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,ERCOTE,ERCOTE,28.7261,-0.2016,0.1969,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,ERCOTN,ERCOTN,27.1522,-1.6039,0.0253,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,27.3209,-1.3825,-0.0275,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,FMPP,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,FPC,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,FPL,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,FREM_50T,OPPDFREM_GUN1_RA,28.3246,-0.3774,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,FREM_6,OPPDFREM_AUN6_RA,28.2818,-0.4202,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,FREM_7,OPPDFREM_AUN7_RA,28.2818,-0.4202,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,FREM_8,OPPDFREM_AUN8_RA,28.1671,-0.5349,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,FREM_LOAD,FREM_LOAD_LA,28.2949,-0.4071,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,FRONTIER,WRGETTUNFRONTIER_RA,27.0854,-1.6154,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GATEWAY_LOAD,CSWS_TENASKA_LA,28.9644,0.0589,0.1747,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,27.9401,-0.7406,-0.0501,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,26.8263,-1.8703,-0.0342,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,28.0865,-0.6566,0.0123,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,28.0865,-0.6566,0.0123,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,28.0865,-0.6566,0.0123,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.GREC2,GRDAGRDA17UN2_RA,27.9337,-0.8155,0.0184,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,27.9337,-0.8155,0.0184,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,27.9271,-0.8222,0.0185,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,27.9271,-0.8222,0.0185,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,26.4003,-2.2987,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,27.6101,-1.1434,0.0226,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,27.6101,-1.1434,0.0226,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,27.6101,-1.1434,0.0226,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.VOLT.0130,V130_DDR,28.3067,-0.4456,0.0215,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA.VOLT.0237,V237_DDR,28.0855,-0.6669,0.0216,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDAHUB2,GRDAHUB2_H,27.5551,-1.1873,0.0116,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDAHUB3,GRDAHUB3_H,27.4650,-1.2686,0.0027,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA_GRDA,GRDA_LA,28.0620,-0.6905,0.0216,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA_HUB,GRDA_H,27.5923,-1.1615,0.0230,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRDA_HUBSA,GRDASA_H,27.8678,-0.8843,0.0212,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,GRE,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,29.7251,1.0407,-0.0464,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GSEC_SPS,SPS_GSEC_LA,30.8226,2.1417,-0.0499,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,GSPR2014HUB,GSPR2014HUB_H,30.0958,1.4145,-0.0496,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,GSPR2015HUB,GSPR2015HUB_H,30.0092,1.3279,-0.0496,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,29.4131,0.7316,-0.0493,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,HARRISON,CSWSLEBROCKPLT1,29.0073,0.0945,0.1819,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,HAST_TNSK_HUB,HAST_TNSK_H,29.1687,0.4687,-0.0308,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,HQST,PJM,28.0279,-0.6711,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,HST,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,INDNSUB_H_5,INDNSUB_HUN5_RA,27.8271,-0.8803,-0.0234,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,INDNSUB_H_6,INDNSUB_HUN6_RA,27.8271,-0.8803,-0.0234,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,INDNSUB_I_3,INDNSUBIUN3_RA,27.8021,-0.9054,-0.0234,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,INDNSUB_I_4,INDNSUBIUN4_RA,27.8021,-0.9054,-0.0234,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,INDNSUB_J_1,INDNSUBJUN1_RA,27.8421,-0.8653,-0.0234,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,INDNSUB_J_2,INDNSUBJUN2_RA,27.8421,-0.8653,-0.0234,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,INDN_INDN,INDN_LA,27.8120,-0.8954,-0.0234,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,27.3718,-1.3273,-0.0317,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,ISNE,PJM,28.0279,-0.6711,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,JEA,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,JONES_STREET_1,OPPDJONES_STUN1_RA,28.1218,-0.5806,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,JONES_STREET_2,OPPDJONES_STUN2_RA,28.1218,-0.5806,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,27.0328,-1.6729,-0.0251,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KACYCT4,KACYNEARMANUNCT4_RA,27.2627,-1.4445,-0.0236,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,27.2407,-1.4878,-0.0023,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,27.2627,-1.4445,-0.0236,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,27.3603,-1.3470,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,27.3275,-1.3797,-0.0236,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KACY_KACY,KACY_LA,27.3968,-1.3104,-0.0235,28.7307\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,27.3960,-1.3112,-0.0236,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,28.3177,-0.3896,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,26.5642,-2.1569,-0.0098,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,26.2920,-2.4099,-0.0289,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.VOLT.0222,V222_DDR,27.3512,-1.3543,-0.0254,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.VOLT.0223,V223_DDR,26.9391,-1.7697,-0.0220,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.VOLT.0241,V241_DDR,28.1030,-0.6047,-0.0231,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.VOLT.0243,V243_DDR,27.8636,-0.8748,0.0075,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.VOLT.0247,V247_DDR,27.0496,-1.6588,-0.0224,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.VOLT.0253,V253_DDR,27.4134,-1.2938,-0.0236,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,25.7542,-2.9529,-0.0237,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,26.8190,-1.8895,-0.0223,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,26.8190,-1.8895,-0.0223,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,26.8190,-1.8895,-0.0223,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,26.8188,-1.8898,-0.0223,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,27.3986,-1.3086,-0.0236,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,27.3986,-1.3086,-0.0236,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHUB,KCPLHUB_H,26.5564,-2.1499,-0.0245,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHUB17,KCPLHUB17_H,26.5675,-2.1380,-0.0253,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHUB18,KCPLHUB18_H,26.5646,-2.1411,-0.0251,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHUB19,KCPLHUB19_H,26.6245,-2.0811,-0.0252,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHUB20,KCPLHUB20_H,26.5702,-2.1353,-0.0253,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHUB21,KCPLHUB21_H,26.6156,-2.0894,-0.0258,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHUB22,KCPLHUB22_H,26.5852,-2.1204,-0.0253,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHUB23,KCPLHUB23_H,26.5648,-2.1406,-0.0254,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLHUB24,KCPLHUB24_H,26.5535,-2.1516,-0.0257,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,27.0356,-1.6702,-0.0250,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,27.0356,-1.6702,-0.0250,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,26.3169,-2.3946,-0.0193,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,26.3169,-2.3946,-0.0193,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,27.4097,-1.2976,-0.0236,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,27.3960,-1.3112,-0.0236,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,27.4558,-1.2515,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,27.4558,-1.2515,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,27.4557,-1.2516,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,27.4557,-1.2516,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,27.4557,-1.2516,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,27.4557,-1.2516,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,27.4557,-1.2516,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,27.4557,-1.2516,-0.0235,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,26.7700,-1.9422,-0.0186,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,27.3618,-1.3461,-0.0230,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KCPL_KCPL,KCPL_LA,27.3064,-1.4014,-0.0229,28.7307\n03/31/2025 09:00:00,03/31/2025 14:00:00,KENN,KENN_LA,27.9347,-0.7532,-0.0429,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KEP2_SECI,KEP2_SECI_LA,28.5458,-0.1392,-0.0458,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KERR_1,GRDAKERR_HYDUN1_RA,28.0616,-0.6902,0.0209,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KERR_2,GRDAKERR_HYDUN2_RA,28.0802,-0.6712,0.0206,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KERR_3,GRDAKERR_HYDUN3_RA,28.0802,-0.6712,0.0206,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KERR_4,GRDAKERR_HYDUN4_RA,28.0616,-0.6902,0.0209,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,26.8186,-1.8899,-0.0223,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,26.8186,-1.8899,-0.0223,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,26.9695,-1.7390,-0.0224,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,26.9695,-1.7390,-0.0224,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,26.8382,-1.8712,-0.0214,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,26.8988,-1.8118,-0.0202,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,26.8988,-1.8118,-0.0202,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,27.6868,-1.0009,-0.0431,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,27.6868,-1.0009,-0.0431,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,27.6868,-1.0009,-0.0431,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,28.1343,-0.5625,-0.0340,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,28.1343,-0.5625,-0.0340,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,27.6848,-1.0028,-0.0433,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,28.0330,-0.6632,-0.0346,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,26.7848,-1.9166,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,27.2577,-1.4725,-0.0006,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,27.2577,-1.4725,-0.0006,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,26.9438,-1.7607,-0.0263,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,26.9438,-1.7607,-0.0263,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,26.9438,-1.7607,-0.0263,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,28.5065,-0.1879,-0.0365,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,27.5145,-1.1840,-0.0323,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,27.2133,-1.4948,-0.0227,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,KMEA_EUDORA,KMEA_EUDORA_LA,27.1536,-1.5524,-0.0248,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LAFA,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LAM345,LAM345,27.5643,-1.1232,-0.0433,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LEPA,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_JSTREET,LES8_NUNJ_STREET_RA,28.0719,-0.6302,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_LES,LES_LA,28.0348,-0.6674,-0.0287,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,27.8506,-0.8516,-0.0286,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_ROKEBY_1,LESROKEBYUN1_RA,27.9191,-0.7830,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_ROKEBY_2,LESROKEBYUN2_RA,27.9618,-0.7403,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_ROKEBY_3,LESROKEBYUN3_RA,27.9618,-0.7403,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_TBGS_CC1,LES84_BLUFPLT1,27.8616,-0.8406,-0.0286,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,27.8506,-0.8516,-0.0286,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_WAVERLY,LES_WAVERLY_H,27.9264,-0.7759,-0.0286,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,27.8607,-0.8417,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,27.8620,-0.8404,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,LGEE,LGEE,27.9972,-0.7004,-0.0332,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MALDEN,MALDEN_LA,27.9352,-0.7537,-0.0419,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MCWEST,MCWEST,29.4666,0.7660,-0.0302,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MDU,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,28.7634,0.0652,-0.0327,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,28.1608,-0.5424,-0.0276,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,29.5743,0.8719,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MEAN_NPPD,NPPD_MEAN_LA,29.1466,0.4471,-0.0313,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MEC,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MHEB,MHEB,29.3790,0.6782,-0.0299,28.7307\n03/31/2025 09:00:00,03/31/2025 14:00:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,28.1901,-0.5072,-0.0335,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,28.3249,-0.3692,-0.0367,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,28.1901,-0.5072,-0.0335,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,28.1901,-0.5072,-0.0335,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,28.3249,-0.3692,-0.0367,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,27.0719,-1.6778,0.0188,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MISO,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,28.7268,0.0427,-0.0467,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,28.7268,0.0427,-0.0467,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,27.3532,-1.3480,-0.0296,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,27.6698,-1.0199,-0.0411,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,27.8901,-0.8050,-0.0357,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,27.2453,-1.4447,-0.0409,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKEC_KPP,SECI_MKEC_KPP_LA,27.5252,-1.1667,-0.0389,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,27.3748,-1.3151,-0.0409,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,27.6869,-1.0055,-0.0384,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,27.6869,-1.0055,-0.0384,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,27.6869,-1.0055,-0.0384,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,27.6869,-1.0055,-0.0384,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,27.6869,-1.0055,-0.0384,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,27.5816,-1.1236,-0.0256,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,27.9187,-0.7790,-0.0331,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,27.9187,-0.7790,-0.0331,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,27.9099,-0.7925,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,28.2874,-0.4191,-0.0243,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MOWR,AECI,27.8898,-0.8306,-0.0104,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,27.7638,-0.9465,-0.0206,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,27.9260,-0.7737,-0.0312,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,27.0756,-1.6287,-0.0265,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,27.1700,-1.5356,-0.0252,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,26.6326,-2.0635,-0.0347,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,27.0915,-1.6128,-0.0265,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,26.8734,-1.8352,-0.0223,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,26.8734,-1.8352,-0.0223,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,26.8092,-1.8993,-0.0223,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,26.8092,-1.8993,-0.0223,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,27.3512,-1.3543,-0.0254,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,27.3512,-1.3543,-0.0254,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,27.3512,-1.3543,-0.0254,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,27.3058,-1.3996,-0.0254,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,27.3512,-1.3543,-0.0254,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,27.3512,-1.3543,-0.0254,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,27.3512,-1.3543,-0.0254,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,27.9810,-0.7394,-0.0104,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,26.6659,-2.0431,-0.0219,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,26.3324,-2.3770,-0.0215,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,26.2492,-2.4601,-0.0215,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,26.3319,-2.3774,-0.0215,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSTWA1UN1,MPSTWA1UN1_RA,27.4232,-1.2836,-0.0240,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPSTWA1UN2,MPSTWA1UN2_RA,27.4232,-1.2836,-0.0240,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MPS_MPS,MPS_LA,27.4507,-1.2571,-0.0230,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MSTNG,SPSMSTNGPLT1,32.2191,3.5390,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MSTNG4,SPSMSTNGUN4_RA,31.8442,3.1640,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,MSTNG5,SPSMSTNGUN5_RA,31.9957,3.3156,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,31.9957,3.3156,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NBSO,PJM,28.0279,-0.6711,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,27.0954,-1.6077,-0.0278,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,27.0936,-1.6094,-0.0278,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,28.9394,0.2574,-0.0488,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NHC1,VACS,28.0080,-0.6929,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,28.0635,-0.6390,-0.0284,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,28.0635,-0.6390,-0.0284,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,28.0635,-0.6390,-0.0284,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,30.0556,1.3559,-0.0311,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,29.1745,0.4744,-0.0307,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,27.8222,-0.8800,-0.0286,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,28.1097,-0.5919,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,29.1745,0.4744,-0.0307,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.HUB.PY2018,NPPDPY18_H,27.4518,-1.2509,-0.0281,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,27.4389,-1.2638,-0.0280,28.7307\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,27.4504,-1.2523,-0.0281,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,27.4245,-1.2783,-0.0280,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,28.1853,-0.5163,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,28.4997,-0.1980,-0.0331,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,28.4997,-0.1980,-0.0331,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,28.4940,-0.2042,-0.0327,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,28.1853,-0.5163,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,28.0836,-0.6176,-0.0296,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,29.5590,0.8600,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,28.4344,-0.2613,-0.0351,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,29.5590,0.8600,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,29.7911,1.0914,-0.0311,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,29.3357,0.6370,-0.0321,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,28.2379,-0.4643,-0.0287,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,29.1745,0.4744,-0.0307,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,28.4494,-0.2467,-0.0347,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,28.4997,-0.1980,-0.0331,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,28.4997,-0.1980,-0.0331,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,28.8675,0.1692,-0.0325,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,28.8654,0.1672,-0.0326,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,28.8654,0.1672,-0.0326,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,29.4161,0.7173,-0.0320,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,28.4749,-0.2268,-0.0291,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,29.3331,0.6329,-0.0306,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,30.1461,1.4463,-0.0310,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,28.5859,-0.1159,-0.0290,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,28.6733,-0.0284,-0.0291,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.NELI.DDR,NELI_DDR,28.3006,-0.4007,-0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.NPPM.1058,SH1058_DDR,28.7064,0.0049,-0.0293,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,29.0820,0.3831,-0.0320,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,29.1745,0.4744,-0.0307,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,27.8222,-0.8800,-0.0286,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,28.2046,-0.4970,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.TECH.1,KEARNE_DDR,29.4092,0.7103,-0.0319,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,28.4512,-0.2491,-0.0305,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,28.4512,-0.2491,-0.0305,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,28.2222,-0.4792,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD.VOLT.0236,V236_DDR,27.9543,-0.7478,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD2017HUB,NPPD2017HUB_H,27.4352,-1.2676,-0.0280,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,28.2807,-0.4207,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,30.0556,1.3559,-0.0311,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,29.5961,0.8969,-0.0316,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,29.5961,0.8969,-0.0316,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_BPS,NPPDBEAPWRSTPLT1,27.9336,-0.7685,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,27.9890,-0.7132,-0.0287,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,28.4602,-0.2414,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,28.8315,0.1331,-0.0324,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,28.1974,-0.5040,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,28.4366,-0.2648,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,28.1990,-0.5024,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,29.1444,0.4444,-0.0308,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_COOPR,NPPDCOOPERUN1_RA,27.1978,-1.5054,-0.0276,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_COSN_NPPD,NPPD_COSN_LA,29.4624,0.7619,-0.0303,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,28.4608,-0.2405,-0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,28.4739,-0.2274,-0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,28.4014,-0.2960,-0.0334,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,28.3821,-0.3151,-0.0336,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,29.0063,0.3062,-0.0308,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,28.9786,0.2785,-0.0308,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,28.9786,0.2785,-0.0308,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,29.0710,0.3710,-0.0308,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,28.0836,-0.6176,-0.0296,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,29.0642,0.3641,-0.0308,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,27.7897,-0.9124,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,29.1885,0.4885,-0.0308,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,29.1699,0.4700,-0.0308,28.7307\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,29.1830,0.4831,-0.0309,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,29.1830,0.4831,-0.0309,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,29.1444,0.4444,-0.0308,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,29.1444,0.4444,-0.0308,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,30.5997,1.8997,-0.0308,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,29.0280,0.3270,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,28.1248,-0.5725,-0.0335,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,28.8240,0.1229,-0.0297,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,28.3636,-0.3319,-0.0353,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,28.5712,-0.1306,-0.0290,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_NELI_LD,NPPD_NELIGH_LA,28.3006,-0.4007,-0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,28.5368,-0.1607,-0.0333,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,28.5368,-0.1607,-0.0333,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_NPPD,NPPD_LA,28.6963,-0.0041,-0.0304,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,27.7897,-0.9124,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,27.7897,-0.9124,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,27.5020,-1.1999,-0.0289,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,29.4727,0.7736,-0.0318,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,NSB,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NSP,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NSSO,PJM,28.0279,-0.6711,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,NYIS,PJM,28.0279,-0.6711,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,27.4969,-1.1788,-0.0551,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,26.4709,-2.2195,-0.0404,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,26.3328,-2.3716,-0.0264,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,26.3328,-2.3716,-0.0264,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,27.8266,-0.8523,-0.0519,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,26.8263,-1.8703,-0.0342,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,26.7678,-1.9418,-0.0212,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,25.5110,-3.1871,-0.0327,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,26.3945,-2.3035,-0.0328,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,26.3741,-2.3184,-0.0383,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,27.7366,-1.2327,0.2385,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,26.3945,-2.3035,-0.0328,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,27.7304,-0.9476,-0.0528,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,27.0719,-1.6778,0.0188,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,27.3674,-1.3073,-0.0561,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,27.7652,-1.1025,0.1369,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,26.3741,-2.3184,-0.0383,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,26.7968,-1.8836,-0.0504,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,27.1316,-1.5869,-0.0123,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,27.0723,-1.5872,-0.0713,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,27.4999,-1.3567,0.1258,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,27.0719,-1.6778,0.0188,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,27.0719,-1.6778,0.0188,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,26.3741,-2.3184,-0.0383,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.NUEN.ADA1,ADA1_DDR,27.2316,-1.1335,-0.3657,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.NUEN.LAM1,LAM1_DDR,28.9689,0.2199,0.0182,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.NUEN.MDT2,MDT2_DDR,27.7410,-1.2283,0.2385,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.NUEN.MDT3,MDT3_DDR,27.7410,-1.2283,0.2385,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.NUEN.WWO1,WWO1_DDR,27.2698,-1.0962,-0.3648,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,27.5896,-1.2078,0.0666,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,27.5891,-1.2083,0.0666,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,27.6216,-1.1758,0.0666,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,27.7350,-1.1156,0.1198,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,27.7350,-1.1156,0.1198,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,27.6214,-1.1760,0.0666,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,27.6214,-1.1760,0.0666,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,26.3741,-2.3184,-0.0383,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,27.9072,-0.7759,-0.0477,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,27.7304,-0.9476,-0.0528,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,26.9996,-1.8579,0.1267,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,26.7968,-1.8836,-0.0504,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,27.8282,-0.8956,-0.0070,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,26.9080,-1.7782,-0.0446,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,26.9080,-1.7782,-0.0446,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,27.0253,-1.6609,-0.0446,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,27.0253,-1.6609,-0.0446,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,26.2601,-2.4241,-0.0467,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,26.5263,-2.1653,-0.0392,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,26.4709,-2.2195,-0.0404,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,26.5036,-2.1920,-0.0352,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,26.5036,-2.1920,-0.0352,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,27.6569,-1.1764,0.1024,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,27.0577,-1.6136,-0.0596,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,27.0577,-1.6136,-0.0596,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,27.0577,-1.6136,-0.0596,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0033,FOSTER_DDR,28.0843,-1.0659,0.4194,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0034,CUSHOIL_DDR,28.6544,-0.1284,0.0519,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0035,TARBY_DDR,28.4884,-0.2598,0.0174,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0036,CUSHFLI_DDR,28.6544,-0.1284,0.0519,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,28.2883,-0.5027,0.0602,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,28.2883,-0.5027,0.0602,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,27.5045,-1.3409,0.1146,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0040,TROSPER_DDR,28.0327,-1.0109,0.3128,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,27.9781,-1.0093,0.2566,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,28.0407,-0.6917,0.0016,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0115,V115_DDR,27.8375,-1.2040,0.3107,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0116,V116_DDR,27.8404,-1.0050,0.1146,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0118,V118_DDR,28.0401,-0.8254,0.1347,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0125,V125_DDR,28.2720,-0.4649,0.0061,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0126,V126_DDR,28.1048,-0.6635,0.0375,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0129,V129_DDR,26.9368,-1.4727,-0.3213,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,27.5903,-1.1812,0.0407,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0134,V134_DDR,28.1455,-0.6127,0.0273,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0138,V138_DDR,28.0760,-0.6966,0.0418,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,27.7682,-1.0453,0.0827,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0143,V143_DDR,28.1846,-0.6081,0.0619,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0149,V149_DDR,26.8753,-1.3760,-0.4795,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0150,V150_DDR,27.0356,-1.2732,-0.4220,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0155,V155_DDR,28.0286,-0.7465,0.0443,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0156,V156_DDR,27.5903,-1.1812,0.0407,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0166,V166_DDR,29.2622,0.4917,0.0396,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,27.8193,-1.0272,0.1157,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,27.0356,-1.2732,-0.4220,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0170,V170_DDR,27.2729,-1.1067,-0.3513,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,26.9952,-1.4256,-0.3100,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0176,V176_DDR,27.0356,-1.2732,-0.4220,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0177,V177_DDR,27.0551,-1.6232,-0.0525,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,27.8570,-1.0212,0.1474,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,27.2602,-1.2935,-0.1771,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0195,V195_DDR,29.2373,0.3884,0.1181,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0197,V197_DDR,28.5039,-0.2736,0.0467,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0198,V198_DDR,29.2622,0.4917,0.0396,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0208,V208_DDR,29.2593,0.4103,0.1181,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0209,V209_DDR,29.2593,0.4103,0.1181,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,28.2957,-0.4804,0.0453,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0216,V216_DDR,27.9623,-1.0110,0.2425,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0219,V219_DDR,28.0286,-0.7465,0.0443,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0220,V220_DDR,27.0356,-1.2732,-0.4220,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0224,V224_DDR,27.6998,-1.1149,0.0839,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0225,V225_DDR,27.7012,-1.1135,0.0839,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0226,V226_DDR,27.6998,-1.1149,0.0839,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0227,V227_DDR,27.6998,-1.1149,0.0839,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0229,V229_DDR,27.5034,-1.3487,0.1213,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0231,V231_DDR,28.3472,-0.5620,0.1783,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0238,V238_DDR,26.7687,-1.9272,-0.0349,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.VOLT.0242,V242_DDR,28.0518,-0.7222,0.0432,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,26.8681,-1.7913,-0.0714,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,27.0719,-1.6778,0.0188,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,26.5946,-2.0937,-0.0425,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,27.3772,-1.2975,-0.0561,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,26.8681,-1.7913,-0.0714,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,27.5849,-1.0796,-0.0663,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,25.4338,-3.2657,-0.0313,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEHL7,OKGEHL7_H,27.8101,-1.0586,0.1379,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEHL8,OKGEHSL1UN8_RA,27.8101,-1.0586,0.1379,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEHL910,OKGEHSL1PLT2,27.8101,-1.0586,0.1379,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,27.4966,-1.1699,-0.0644,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEMCC,OKGEMCCLAIPLT1,21.6082,-1.6883,-5.4343,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,27.8878,-0.8986,0.0556,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,27.8878,-0.8986,0.0556,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,27.8419,-0.9445,0.0556,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,27.2697,-1.4866,0.0255,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,27.1261,-1.6303,0.0255,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,27.1291,-1.6272,0.0255,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,27.2697,-1.4866,0.0255,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGESM1,OKGESEMINOLEUN1_RA,27.7286,-1.1415,0.1393,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGESM2,OKGESEMINOLEUN2_RA,27.6890,-1.1865,0.1446,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGESM3,OKGESEMINOLEUN3_RA,27.6890,-1.1865,0.1446,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGESO1,OKGESONR1UN1_RA,26.4453,-2.2633,-0.0222,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGESO2,OKGESONR1UN2_RA,26.5036,-2.1920,-0.0352,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,27.4789,-1.1875,-0.0644,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,27.0141,-1.5802,-0.1365,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGETINK5A,OKGETINK5UN1_RA,27.9041,-1.0714,0.2446,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGETINK5B,OKGETINK5UN2_RA,27.9041,-1.0714,0.2446,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,27.1987,-1.4744,-0.0577,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,26.4709,-2.2195,-0.0404,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,27.7466,-0.9757,-0.0085,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,27.0719,-1.6778,0.0188,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE_OKGE,OKGE_LA,27.7629,-1.0253,0.0574,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,26.9996,-1.8579,0.1267,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,27.1853,-1.4878,-0.0577,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMLP,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,28.0075,-0.7647,0.0414,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,27.6839,-1.0421,-0.0048,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_GENHUB,OMPA_GENHUB_H,24.4135,-1.6584,-2.6590,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_KAW,OKGEOMKAWUN2_RA,26.8971,-1.8125,-0.0212,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,27.2309,-1.3590,-0.1410,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,26.3945,-2.3035,-0.0328,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,27.4216,-1.2391,-0.0702,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,26.2188,-2.4529,-0.0591,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,27.9589,-0.7823,0.0104,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,26.8989,-1.8108,-0.0212,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,26.8989,-1.8108,-0.0212,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_SPP,OMPA_SPP_LA,27.1495,-1.5819,0.0005,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,26.8681,-1.7913,-0.0714,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,ONETA,CSWSCALPINEUNONETA_1_RA,27.9763,-0.7939,0.0394,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,27.9763,-0.7939,0.0394,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,27.9763,-0.7939,0.0394,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,27.9763,-0.7939,0.0394,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,ONT,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,28.0631,-0.6392,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,28.0631,-0.6392,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,28.0631,-0.6392,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,28.0631,-0.6392,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,28.0631,-0.6392,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,28.0631,-0.6392,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,28.0631,-0.6392,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,28.0631,-0.6392,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,28.0631,-0.6392,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,28.0106,-0.6919,-0.0284,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,28.0635,-0.6390,-0.0284,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,27.8413,-0.8610,-0.0285,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,28.0583,-0.6441,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,28.0583,-0.6441,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD_GLDN,OPPD_GLDN_LA,28.0592,-0.6432,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD_GLDN2,OPPD_GLDN2_LA,28.0912,-0.6112,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,28.0836,-0.6176,-0.0296,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD_NC_HST,OPPD_NC_HST_LA,27.5347,-1.1681,-0.0280,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD_NO_HST,OPPD_NO_HST_LA,28.0505,-0.6519,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD_OPPD,OPPD_LA,28.1550,-0.5474,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD_PAPIO,OPPD_PAPIO_LA,28.0717,-0.6307,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,28.0691,-0.6333,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OTP,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,OVEC,OVEC,28.0067,-0.6916,-0.0325,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PARAGOULD,PARAGOULD_LA,27.9338,-0.7523,-0.0447,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PENSACOLA_1,GRDAPENSA1UN1_RA,27.9963,-0.7513,0.0168,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PENSACOLA_2,GRDAPENSA1UN2_RA,27.9963,-0.7513,0.0168,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PENSACOLA_3,GRDAPENSA1UN3_RA,27.9963,-0.7513,0.0168,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PENSACOLA_4,GRDAPENSA1UN4_RA,28.0197,-0.7291,0.0180,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PENSACOLA_5,GRDAPENSA1UN5_RA,28.0197,-0.7291,0.0180,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PENSACOLA_6,GRDAPENSA1UN6_RA,28.0197,-0.7291,0.0180,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PIGGOTT,PIGGOTT_LA,27.9349,-0.7533,-0.0426,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PJM,PJM,28.0279,-0.6711,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PLUM,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,POPLARBLUFF,POPLARBLUFF_LA,27.9394,-0.7526,-0.0388,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,29.5707,0.8701,-0.0302,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,29.5707,0.8701,-0.0302,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,29.5097,0.8090,-0.0302,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,29.5097,0.8090,-0.0302,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,31.6835,2.9827,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,31.6851,2.9843,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,29.4501,0.7494,-0.0302,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,29.3930,0.6925,-0.0304,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,26.7112,-2.0009,-0.0187,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,28.0624,-0.6874,0.0190,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,27.3226,-1.3825,-0.0257,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,27.6340,-1.1322,0.0353,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,28.3155,-0.5564,0.1411,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,28.3053,-0.4464,0.0209,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,28.4020,-0.2994,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,30.2026,1.5019,-0.0301,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,28.6994,-0.0023,-0.0291,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,30.3148,1.6139,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,30.3466,1.6457,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,28.8292,0.1277,-0.0294,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,PUPP,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,RCEAST,RCEAST,28.3040,-0.3958,-0.0310,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SALINA_1,GRDASALINA1UN1_RA,28.0651,-0.6867,0.0209,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SALINA_2,GRDASALINA1UN2_RA,28.0651,-0.6867,0.0209,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SALINA_3,GRDASALINA1UN3_RA,28.0651,-0.6867,0.0209,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SALINA_4,GRDASALINA1UN4_RA,28.0651,-0.6867,0.0209,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SALINA_5,GRDASALINA1UN5_RA,28.0651,-0.6867,0.0209,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SALINA_6,GRDASALINA1UN6_RA,28.0651,-0.6867,0.0209,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SARPY_1,OPPDSARPYUN1_RA,28.0344,-0.6680,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SARPY_2,OPPDSARPYUN2_RA,28.0964,-0.6061,-0.0284,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SARPY_3,OPPDSARPYUN3_RA,27.9659,-0.7365,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SARPY_4,OPPDSARPYUN4_RA,27.9659,-0.7365,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SARPY_5,OPPDSARPYUN5_RA,27.9659,-0.7365,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SC,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SCEG,VACS,28.0080,-0.6929,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SCSE,SCSE,27.9040,-0.7935,-0.0333,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SEC,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,27.0512,-1.6374,-0.0422,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,27.0512,-1.6374,-0.0422,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,27.0512,-1.6374,-0.0422,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,28.7668,0.0800,-0.0440,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,27.0512,-1.6374,-0.0422,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,27.4047,-1.2836,-0.0426,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,27.3023,-1.3881,-0.0405,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,27.3023,-1.3881,-0.0405,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,27.6823,-1.0101,-0.0384,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,26.9729,-1.7155,-0.0425,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,28.0306,-0.6662,-0.0340,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,28.3235,-0.3626,-0.0448,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,28.1854,-0.5065,-0.0389,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,27.0377,-1.6509,-0.0422,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,28.1018,-0.5901,-0.0390,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,28.4743,-0.2097,-0.0468,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,27.9380,-0.7517,-0.0411,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,27.5231,-1.1645,-0.0432,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,27.5244,-1.1632,-0.0432,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,27.5244,-1.1632,-0.0432,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,27.5244,-1.1632,-0.0432,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,27.4207,-1.2667,-0.0434,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,27.4047,-1.2836,-0.0426,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI_SECI,SECI_LA,28.1779,-0.5114,-0.0416,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,27.3718,-1.3273,-0.0317,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,27.3718,-1.3273,-0.0317,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,27.6823,-1.0101,-0.0384,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SEHA,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,27.1853,-1.4878,-0.0577,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SERU,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SETH,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SGE,SGE,27.6746,-1.0233,-0.0329,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SMEP,MISO,28.2531,-0.4610,-0.0167,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SOCO,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPA,SPA,27.9693,-0.7665,0.0050,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPC,SPC,30.6162,1.9154,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPPNORTH_HUB,SPPNORTH_H,28.5127,-0.1889,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPPSOUTH_HUB,SPPSOUTH_H,27.4230,-1.3324,0.0246,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,28.0823,-0.6423,-0.0062,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,28.0895,-0.6351,-0.0062,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,28.1757,-0.5478,-0.0073,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,28.1757,-0.5478,-0.0073,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_NIXA,SPRM_NIXA_LA,28.1928,-0.5319,-0.0061,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_SPRM,SPRM_LA,28.3105,-0.4144,-0.0060,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,28.0923,-0.6333,-0.0052,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,28.0923,-0.6333,-0.0052,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,28.0415,-0.6842,-0.0052,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,28.0923,-0.6333,-0.0052,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,31.6792,2.9989,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,31.5241,2.8432,-0.0500,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,28.6787,-0.0031,-0.0490,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,28.6787,-0.0031,-0.0490,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,30.7473,2.0672,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,32.3536,3.6735,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,32.3950,3.7147,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,32.0748,3.3946,-0.0506,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,29.9340,1.2540,-0.0508,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,31.8484,3.1683,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,32.2056,3.5255,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,32.2056,3.5255,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,31.8484,3.1683,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,28.8539,0.1721,-0.0490,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,31.5241,2.8432,-0.0500,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,29.1567,0.4751,-0.0492,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,28.2169,-0.4640,-0.0499,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,29.5790,0.8978,-0.0496,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,30.1896,1.5082,-0.0494,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,29.3622,0.6808,-0.0494,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,27.9524,-0.7277,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,27.9524,-0.7278,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,27.9524,-0.7278,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,27.9524,-0.7278,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GRID.WRAB,WRAB_DDR,30.0701,1.3880,-0.0487,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,27.9524,-0.7278,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,30.5403,1.8604,-0.0509,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,30.5403,1.8604,-0.0509,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,30.5710,1.8914,-0.0512,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,30.5710,1.8914,-0.0512,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,30.5710,1.8914,-0.0512,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,30.5403,1.8604,-0.0509,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,28.6588,-0.0232,-0.0488,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,28.6588,-0.0232,-0.0488,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,28.6593,-0.0227,-0.0488,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,28.9394,0.2574,-0.0488,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.HOBBS.CC,SPSHOBBSPLT1,31.8678,3.1877,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.JONES1,SPSJONESSUBUN1_RA,29.9020,1.2220,-0.0508,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.JONES2,SPSJONESSUBUN2_RA,29.9023,1.2223,-0.0508,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.JONES3,SPSJONESSUBUN3_RA,29.9021,1.2221,-0.0508,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.JONES4,SPSJONESSUBUN4_RA,29.9021,1.2221,-0.0508,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,32.1030,3.4229,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,31.8822,3.2021,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,31.8822,3.2021,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,27.2061,-1.4671,-0.0577,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,28.5372,-0.1449,-0.0487,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,28.5372,-0.1449,-0.0487,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,28.6632,-0.0189,-0.0487,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,30.0701,1.3880,-0.0487,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,28.7348,0.0539,-0.0499,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,28.7802,0.0986,-0.0492,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,27.8266,-0.8523,-0.0519,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,28.9104,0.2284,-0.0488,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.PLANTX1,SPS.PLANTX1_H,31.5827,2.9022,-0.0503,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.PLANTX2,SPS.PLANTX2_H,31.5827,2.9022,-0.0503,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,31.4924,2.8120,-0.0504,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,30.6426,1.9625,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,28.2576,-0.4231,-0.0501,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,32.6452,3.9649,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,30.7386,2.0585,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,28.9937,0.3119,-0.0490,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,31.9530,3.2727,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,32.5356,3.8554,-0.0506,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,31.9530,3.2727,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,32.1972,3.5169,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,28.7303,0.0491,-0.0496,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,33.7286,5.0485,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,33.7740,5.0939,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,33.1003,4.4201,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,32.2066,3.5265,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,33.7619,5.0818,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,27.5643,-1.1232,-0.0433,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,29.9423,1.2602,-0.0487,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,31.6280,2.9475,-0.0504,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,31.6280,2.9475,-0.0504,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,31.9530,3.2727,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,29.9992,1.3192,-0.0508,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0006,SPS.VOLT.0006_H,32.8688,4.1887,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0023,SPS.VOLT.0023_H,32.2055,3.5250,-0.0504,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0025,SPS.VOLT.0025_H,32.4525,3.7721,-0.0504,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0033,SPS.VOLT.0033_H,30.7277,2.0471,-0.0502,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0045,SPS.VOLT.0045_H,33.7286,5.0485,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0046,SPS.VOLT.0046_H,34.8498,6.1696,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0047,SPS.VOLT.0047_H,34.1998,5.5197,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0052,SPS.VOLT.0052_H,30.9675,2.2874,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0113,SPS.VOLT.0113_H,32.6991,4.0186,-0.0504,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0136,SPS.VOLT.0136_H,28.5507,-0.1303,-0.0498,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0137,SPS.VOLT.0137_H,28.5005,-0.1805,-0.0498,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0163,V163_DDR,29.5461,0.8644,-0.0492,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0168,V168_DDR,27.7046,-0.9855,-0.0408,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0180,V180_DDR,34.8498,6.1696,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0181,V181_DDR,28.6078,-0.0731,-0.0500,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0182,V182_DDR,33.8987,5.2185,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0199,V199_DDR,32.6285,3.9484,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0200,V200_DDR,32.7416,4.0614,-0.0507,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.VOLT.0235,V235_DDR,28.7348,0.0539,-0.0499,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,32.3950,3.7147,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,32.0748,3.3946,-0.0506,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,29.4103,0.7288,-0.0493,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,30.7944,2.1138,-0.0502,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS_SPS,SPS_LA,32.0016,3.3209,-0.0501,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,31.7570,3.0767,-0.0505,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SSCN_NPPD,SSCN_NPPD_LA,28.3316,-0.3700,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,27.9285,-0.7621,-0.0402,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,27.9285,-0.7621,-0.0402,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,TAL,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,TEC,SOUC,28.0359,-0.6716,-0.0233,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,28.8240,0.1229,-0.0297,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,TVA,TVA,27.9787,-0.7153,-0.0368,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,UCUHUB,UCUHUB_H,27.1462,-1.5565,-0.0281,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,UCUHUB17,UCUHUB17_H,27.4791,-1.2182,-0.0335,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,UCUHUB18,UCUHUB18_H,27.2735,-1.4273,-0.0301,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,UCUHUB19,UCUHUB19_H,27.1477,-1.5539,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,UCUHUB20,UCUHUB20_H,27.1480,-1.5541,-0.0288,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,UCUHUB21,UCUHUB21_H,27.1808,-1.5190,-0.0310,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,UCUHUB22,UCUHUB22_H,27.1307,-1.5690,-0.0311,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,UCUHUB23,UCUHUB23_H,27.1368,-1.5629,-0.0311,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,UCUHUB24,UCUHUB24_H,27.1043,-1.5958,-0.0308,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,31.1053,2.4044,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,31.1053,2.4044,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,29.4017,0.7007,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,29.4017,0.7007,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,29.4176,0.7167,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,29.4790,0.7784,-0.0302,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,29.4790,0.7784,-0.0302,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,31.1053,2.4044,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,29.7741,1.0732,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,30.1647,1.4637,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,28.4038,-0.2977,-0.0293,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,28.2391,-0.4619,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,31.0756,2.3748,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,31.0756,2.3748,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,28.1279,-0.5731,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,28.4675,-0.2336,-0.0297,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,29.9260,1.2251,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,28.4387,-0.2628,-0.0293,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,29.2680,0.5666,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,28.4502,-0.2509,-0.0297,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,28.4804,-0.2206,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,28.4804,-0.2206,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,28.5574,-0.1436,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,28.3078,-0.3931,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,29.9216,1.2202,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,30.2443,1.5433,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,30.2443,1.5433,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,30.2443,1.5433,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,30.2443,1.5433,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,30.2443,1.5433,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,30.2443,1.5433,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,31.3834,2.6826,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,29.2136,0.5126,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,29.2113,0.5104,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,27.4809,-1.2168,-0.0331,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,29.1291,0.4279,-0.0296,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,30.1381,1.4372,-0.0300,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,28.1071,-0.5946,-0.0291,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,27.9028,-0.7979,-0.0301,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,28.8095,0.1085,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,30.8168,2.1160,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,30.8168,2.1160,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,30.8136,2.1128,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,30.8168,2.1160,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,30.9199,2.2191,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,30.9199,2.2191,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,30.9199,2.2191,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,30.9199,2.2191,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,30.9199,2.2191,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,30.9199,2.2191,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,30.9199,2.2191,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,28.2145,-0.4868,-0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,30.4283,1.7274,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,29.0479,0.3464,-0.0293,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,29.0479,0.3464,-0.0293,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,29.1494,0.4481,-0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,29.1494,0.4481,-0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,29.5754,0.8744,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,29.4905,0.7898,-0.0301,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,28.7169,0.0155,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,28.3082,-0.3926,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,28.3347,-0.3668,-0.0293,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,29.4176,0.7167,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,29.4176,0.7167,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,28.4387,-0.2628,-0.0293,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,28.3160,-0.3838,-0.0310,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,28.7355,0.0345,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,27.9849,-0.7160,-0.0300,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,28.6041,-0.0970,-0.0298,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.FSE,WAUE.FSE_H,28.2888,-0.4120,-0.0301,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,29.5241,0.8234,-0.0301,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,29.4876,0.7869,-0.0301,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,27.6745,-1.0265,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,27.6316,-1.0695,-0.0297,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,29.0922,0.3912,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,28.9516,0.2507,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,28.1797,-0.5216,-0.0295,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,28.2391,-0.4619,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,27.6747,-1.0253,-0.0308,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,27.1036,-1.5985,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,27.1012,-1.6009,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,27.1037,-1.5984,-0.0287,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,28.6740,-0.0270,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,28.3160,-0.3838,-0.0310,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,28.7074,0.0060,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,28.5909,-0.1107,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,29.8569,1.1555,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,28.7243,0.0224,-0.0289,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,28.6513,-0.0501,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,27.5931,-1.1083,-0.0294,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,29.2333,0.5317,-0.0293,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,28.2962,-0.4053,-0.0294,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,28.1071,-0.5946,-0.0291,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,29.3848,0.6838,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,28.3981,-0.3034,-0.0293,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,29.0254,0.3243,-0.0297,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,28.7769,0.0754,-0.0294,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,27.8620,-0.8404,-0.0284,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NTWK,WAUE.NTWK_H,29.1071,0.4060,-0.0297,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,29.4075,0.7065,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,29.4075,0.7065,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,28.4032,-0.2977,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,28.3573,-0.3439,-0.0296,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,28.6948,-0.0062,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,28.4032,-0.2977,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,29.4459,0.7450,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,28.5142,-0.1868,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,28.1071,-0.5946,-0.0291,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,28.8664,0.1654,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,30.0789,1.3779,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,27.1620,-1.5385,-0.0303,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,27.0690,-1.6316,-0.0302,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,29.2967,0.5958,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,28.3972,-0.3032,-0.0304,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,28.5190,-0.1822,-0.0297,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,28.3568,-0.3441,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,28.3082,-0.3926,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.VOLT.0152,V152_DDR,31.6502,2.9494,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE.VOLT.0172,V172_DDR,31.0253,2.3245,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_BEPM,WAUE_BEPM_LA,30.0971,1.3962,-0.0298,28.7307\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,28.7336,0.0321,-0.0294,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,28.7489,0.0470,-0.0289,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_EWA,WAUE_EWA_LA,28.3869,-0.3129,-0.0310,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,28.7324,0.0313,-0.0297,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_HMMU,WAUE_HMMU_LA,28.3273,-0.3749,-0.0286,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,28.1905,-0.5107,-0.0296,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_MECB,WAUE_MECB_LA,28.5154,-0.1865,-0.0289,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_MMPA,WAUE_MMPA_LA,29.8170,1.1161,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_MRES,WAUE_MRES_LA,28.9370,0.2358,-0.0296,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,31.2656,2.5647,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,29.5241,0.8234,-0.0301,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,28.8872,0.1861,-0.0297,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_OTP,WAUE_OTP_LA,30.9620,2.2611,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_OTPW,WAUE_OTPW_LA,29.9106,1.2096,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM,WAUE_UGPM_LA,28.7389,0.0380,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,29.7752,1.0742,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,28.7173,0.0157,-0.0293,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,29.2293,0.5285,-0.0301,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,28.3869,-0.3129,-0.0310,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,28.3273,-0.3749,-0.0286,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,28.7949,0.0937,-0.0297,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,29.5241,0.8234,-0.0301,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,29.8170,1.1161,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,29.1450,0.4438,-0.0297,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,28.6419,-0.0592,-0.0298,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,31.4693,2.7684,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,26.9312,-1.7281,-0.0715,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,26.8429,-1.8513,-0.0366,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,25.7282,-2.9552,-0.0474,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,28.4663,-0.3898,0.1252,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,28.4663,-0.3898,0.1252,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,25.5107,-3.1519,-0.0682,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,28.5695,-0.2844,0.1231,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,28.5032,-0.3481,0.1205,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,26.2952,-2.3856,-0.0500,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,26.3004,-2.3804,-0.0500,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,26.3006,-2.3802,-0.0500,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,26.4599,-2.2210,-0.0500,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,26.4599,-2.2210,-0.0500,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,26.4599,-2.2210,-0.0500,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,26.4599,-2.2210,-0.0500,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,26.4599,-2.2210,-0.0500,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,26.4728,-2.1976,-0.0605,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,27.8266,-0.8523,-0.0519,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,25.8909,-2.8005,-0.0394,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,27.2492,-1.4146,-0.0671,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,32.4062,3.7258,-0.0505,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_ENMC,WFEC_ENMC_LA,32.8330,4.1528,-0.0506,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,26.3741,-2.3184,-0.0383,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,28.0201,-0.8771,0.1664,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,31.8593,3.1792,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,26.8999,-1.7594,-0.0715,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,26.9312,-1.7281,-0.0715,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,26.9312,-1.7281,-0.0715,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_OKGE,WFEC_OKGE_LA,27.7860,-0.9648,0.0200,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,28.7322,-0.1197,0.1211,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,26.8824,-1.7768,-0.0716,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,26.3713,-2.3034,-0.0561,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_WFEC,WFEC_LA,27.8630,-0.9002,0.0324,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,31.8593,3.1792,-0.0507,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,28.1377,-0.5591,-0.0340,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,27.8570,-0.8322,-0.0416,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,26.5879,-2.1156,-0.0274,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,26.5879,-2.1156,-0.0274,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,26.5755,-2.1280,-0.0274,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,26.5755,-2.1280,-0.0274,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,26.5877,-2.1157,-0.0274,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,26.5876,-2.1158,-0.0274,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,26.5876,-2.1158,-0.0274,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,27.8314,-0.8982,-0.0013,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,26.7350,-1.9666,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,26.4519,-2.2433,-0.0356,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,26.4519,-2.2433,-0.0356,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,26.4519,-2.2433,-0.0356,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,26.9766,-1.7130,-0.0413,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,26.9766,-1.7130,-0.0413,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.GEEC.GT1,WRGORDUNG1_RA,26.6219,-2.0761,-0.0328,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.GEEC.GT2,WRGORDUNG2_RA,26.6219,-2.0761,-0.0328,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.GEEC.GT3,WRGORDUNGT3_RA,26.5307,-2.1673,-0.0328,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,26.7350,-1.9666,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,27.0150,-1.6908,-0.0250,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.HEC.GT1,WRHECGTUN32_RA,27.0008,-1.6974,-0.0326,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.HEC.GT2,WRHECGTUN33_RA,27.0173,-1.6809,-0.0326,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.HEC.GT3,WRHECGTUN34_RA,27.0236,-1.6747,-0.0326,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.HEC.GT4,WRHECGTUN35_RA,27.0251,-1.6732,-0.0326,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,27.0150,-1.6908,-0.0250,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,27.0260,-1.6627,-0.0422,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,26.6204,-2.1052,-0.0052,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.JEC.1,WRJEFFUN10_RA,26.6182,-2.0854,-0.0272,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.JEC.2,WRJEFFUN11_RA,26.4843,-2.2194,-0.0272,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.JEC.3,WRJEFFUN12_RA,26.6129,-2.0907,-0.0272,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,26.4003,-2.2987,-0.0318,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,26.6436,-2.0525,-0.0347,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,26.6436,-2.0525,-0.0347,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.LEC.4,WRLECUN26_RA,26.8391,-1.8665,-0.0252,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.LEC.5,WRLECUN27_RA,26.9986,-1.7069,-0.0253,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MCPH.CT1,WRCMCPHUN37_RA,27.1961,-1.5029,-0.0319,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MCPH.CT2,WRCMCPHUN38_RA,27.1961,-1.5029,-0.0319,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MCPH.CT3,WRCMCPHUN48_RA,27.1912,-1.5077,-0.0319,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MCPH.CT4,WRCJOHNUN1_RA,27.2612,-1.4377,-0.0319,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,27.3718,-1.3273,-0.0317,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,27.3718,-1.3273,-0.0317,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,28.5078,-0.1846,-0.0384,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,28.1867,-0.5102,-0.0339,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,28.1867,-0.5102,-0.0339,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,27.5190,-1.1795,-0.0323,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,27.3718,-1.3273,-0.0317,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,27.1307,-1.5719,-0.0282,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,26.7822,-1.9188,-0.0299,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,26.6373,-2.0588,-0.0347,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,28.4864,-0.3595,0.1150,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,27.5698,-1.1284,-0.0326,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.READ.READ,WREMPECUNREADINGWF_RA,26.5876,-2.1158,-0.0274,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,25.7756,-2.9331,-0.0221,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,27.0150,-1.6908,-0.0250,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,26.7350,-1.9666,-0.0292,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,26.8251,-1.8737,-0.0320,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.THAYERLD,WR.THAYERLD_LA,27.9526,-0.7419,-0.0363,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0102,WR.VOLT.0102_H,26.8338,-1.8653,-0.0317,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0106,V106_DDR,26.8254,-1.8748,-0.0307,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0139,WR.VOLT.0139_H,27.1930,-1.5137,-0.0241,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0141,WR.VOLT.0141_H,27.1719,-1.5285,-0.0305,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0146,WR.VOLT.0146_H,27.1231,-1.5826,-0.0251,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0147,WR.VOLT.0147_H,27.1231,-1.5826,-0.0251,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0148,WR.VOLT.0148_H,27.0776,-1.6282,-0.0251,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0153,WR.VOLT.0153_H,27.0492,-1.6516,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0157,V157_DDR,27.0951,-1.6106,-0.0251,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0158,V158_DDR,27.1231,-1.5826,-0.0251,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0159,WR.VOLT.0159_H,27.1231,-1.5826,-0.0251,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0165,WR.VOLT.0165_H,26.6685,-2.0324,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0173,V173_DDR,27.3090,-1.3897,-0.0321,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0174,V174_DDR,26.7904,-1.9106,-0.0298,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0184,V184_DDR,26.6231,-2.0774,-0.0304,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0185,WR.VOLT.0185_H,26.8123,-1.8869,-0.0316,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0186,V186_DDR,26.7563,-1.9426,-0.0320,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0187,WR.VOLT.0187_H,26.6902,-2.0097,-0.0310,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0188,WR.VOLT.0188_H,26.8425,-1.8569,-0.0314,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0189,WR.VOLT.0189_H,27.4284,-1.2699,-0.0325,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0190,WR.VOLT.0190_H,26.7487,-1.9545,-0.0276,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0191,WR.VOLT.0191_H,26.6661,-2.0372,-0.0275,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0192,WR.VOLT.0192_H,26.6661,-2.0372,-0.0275,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0196,WR.VOLT.0196_H,26.7487,-1.9545,-0.0276,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0245,V245_DDR,26.8165,-1.8827,-0.0316,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.VOLT.0248,V248_DDR,26.8254,-1.8748,-0.0307,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,26.4297,-2.2711,-0.0300,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,27.0718,-1.6327,-0.0263,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.WOLF,WRWOLFUN15_RA,25.6273,-3.0793,-0.0242,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,27.0260,-1.6627,-0.0422,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,27.4197,-1.3098,-0.0013,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,26.4519,-2.2433,-0.0356,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,26.4519,-2.2433,-0.0356,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,26.4519,-2.2433,-0.0356,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,26.4519,-2.2433,-0.0356,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KPP_NITS,WR_KPP_NITS_LA,26.7882,-1.9158,-0.0268,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,27.1749,-1.5255,-0.0304,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,26.7706,-1.9303,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,26.7706,-1.9303,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,26.7706,-1.9303,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,26.7706,-1.9303,-0.0299,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,26.9693,-1.7327,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,26.9693,-1.7327,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,26.9693,-1.7327,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,26.9693,-1.7327,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,26.9693,-1.7327,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,26.9693,-1.7327,-0.0288,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,26.8660,-1.8343,-0.0305,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,26.8660,-1.8343,-0.0305,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,26.4859,-2.2155,-0.0295,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,26.4859,-2.2155,-0.0295,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_MIDW,WR_MIDW_LA,28.2401,-0.4552,-0.0355,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,27.9833,-0.7229,-0.0247,28.7309\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,27.2863,-1.4229,-0.0216,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,28.0884,-0.6064,-0.0360,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_SEG,WR_SEG_LA,27.5143,-1.2118,-0.0047,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,WR_WR,WR_LA,27.0222,-1.6821,-0.0265,28.7308\n03/31/2025 09:00:00,03/31/2025 14:00:00,YAD,VACS,28.0080,-0.6929,-0.0299,28.7308\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_SPP/RTBM-LMP-SL-202503310905.csv",
    "content": "Interval,GMTIntervalEnd,Settlement Location,Pnode,LMP,MLC,MCC,MEC\n03/31/2025 09:05:00,03/31/2025 14:05:00,AEC,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,AECC_CSWS,CSWS_AECC_LA,25.4715,-0.4615,0.0202,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,25.6362,-0.2922,0.0157,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,24.9277,-1.0068,0.0218,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,25.4100,-0.5172,0.0144,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,25.2191,-0.7199,0.0262,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,AECC_HYDRO13,CSWSLD13UN1_RA,24.3350,-1.5995,0.0218,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,25.6204,-0.3208,0.0285,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,AECI,AECI,25.2242,-0.6972,0.0087,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,AEPM_CSWS,CSWS_LA,25.6755,-0.2526,0.0154,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,ALTW,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,AMRN,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,ANTELOPE,SPSANTELOPEUNANT1_RA,27.4350,1.5527,-0.0304,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,BBA,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,BCA,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,BEPM.ER01.DDR,ER01_DDR,24.6227,-1.2883,-0.0018,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,BEPM_ER01,BEPM_ER01_LA,24.6227,-1.2883,-0.0018,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,27.5434,1.6341,-0.0034,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,26.1263,0.2211,-0.0075,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,BEPM_UM01,BEPM_UM01_LA,28.0674,2.1547,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,BLKW,BLKW,28.8125,2.9300,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,23.2331,-2.6464,-0.0333,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,23.2331,-2.6464,-0.0333,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,23.1531,-2.7222,-0.0374,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,23.2709,-2.6085,-0.0333,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,BRAZ,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,BUBA,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,24.8650,-1.0262,-0.0216,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,24.3686,-1.4995,-0.0446,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,24.3686,-1.4995,-0.0446,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,24.3686,-1.4995,-0.0446,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,24.3686,-1.4995,-0.0446,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,24.3686,-1.4995,-0.0446,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,24.1117,-1.7940,-0.0071,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,25.2835,-0.6279,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,25.2835,-0.6279,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CLEC,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,25.3486,-0.5737,0.0096,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,COWP,COWP_LA,25.3332,-0.5909,0.0114,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,25.3332,-0.5909,0.0114,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,25.3332,-0.5909,0.0114,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CPLE,VACS,25.3720,-0.5539,0.0132,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CPLW,VACS,25.3720,-0.5539,0.0132,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,25.2914,-0.6362,0.0148,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,25.2914,-0.6362,0.0148,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,25.2914,-0.6362,0.0148,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,25.2914,-0.6362,0.0148,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CRTH_SPA,WRCRTH_SPA_LA,24.9986,-0.9230,0.0089,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,26.2985,0.3599,0.0259,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,24.3207,-1.5797,-0.0123,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,25.6204,-0.3208,0.0285,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,25.4100,-0.5172,0.0144,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWJLSTALL,CSWSSTALL_PPPLT1,26.2948,0.3561,0.0259,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,26.2776,0.3383,0.0265,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,26.2476,0.3086,0.0262,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,26.2476,0.3086,0.0262,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWMATTISON1,CSWSMATTISONUN1_RA,25.1620,-0.7670,0.0162,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWMATTISON2,CSWSMATTISONUN2_RA,25.1620,-0.7670,0.0162,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWMATTISON3,CSWSMATTISONUN3_RA,25.1659,-0.7630,0.0162,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWMATTISON4,CSWSMATTISONUN4_RA,25.1659,-0.7630,0.0162,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,25.6204,-0.3208,0.0285,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWNARROWS1,CSWSNARROWSUN1_RA,25.9236,-0.0183,0.0291,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,25.0261,-0.9017,0.0151,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,24.8605,-1.0673,0.0151,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,25.1677,-0.7599,0.0149,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,25.1966,-0.7374,0.0212,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,25.0876,-0.8463,0.0212,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,25.0817,-0.8523,0.0212,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,25.0817,-0.8523,0.0212,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,24.1035,-1.7912,-0.0180,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,24.8189,-1.0485,-0.0454,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,25.0978,-0.8504,0.0355,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,24.2675,-1.6157,-0.0295,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,24.2019,-1.6813,-0.0295,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,24.4178,-1.5000,0.0051,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.GRID.CDL1,CDL1_DDR,25.3260,-0.6245,0.0378,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,24.3407,-1.4013,-0.1708,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,22.8693,-3.0065,-0.0369,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,25.3260,-0.6245,0.0378,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.NUEN.CSI1,CSI1_DDR,25.6014,-0.3258,0.0145,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.NUEN.CSI2,CSI2_DDR,25.6106,-0.3167,0.0145,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.NUEN.CSI3,NCSI3_DDR,25.2970,-0.6249,0.0092,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.NUEN.GAZA,GAZA_DDR,25.3260,-0.6245,0.0378,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,25.8521,-0.0979,0.0373,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.NUEN.T201,NT201_DDR,25.3788,-0.5538,0.0199,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,24.2801,-1.6275,-0.0052,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,24.2801,-1.6275,-0.0052,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,25.6204,-0.3208,0.0285,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,26.5644,0.6245,0.0272,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,24.4178,-1.5000,0.0051,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,24.4178,-1.5000,0.0051,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,24.2020,-1.7027,-0.0080,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,24.2019,-1.6813,-0.0295,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,26.0474,0.1086,0.0261,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,25.1435,-0.7897,0.0204,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,25.1435,-0.7897,0.0204,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,24.7645,-1.1687,0.0204,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,24.8178,-1.1381,0.0431,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,24.9856,-0.9703,0.0431,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,26.2573,0.3178,0.0268,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,25.3206,-0.6130,0.0209,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,26.3203,0.3808,0.0267,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,27.4475,1.5076,0.0272,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,25.3534,-0.5908,0.0315,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0056,PRYORCRK_DDR,25.6106,-0.3167,0.0145,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0057,OKMU_DDR,25.4889,-0.4577,0.0339,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0060,LEHIGH_DDR,25.7133,-0.2408,0.0414,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0086,WARRENM_DDR,25.3076,-0.6262,0.0210,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,26.6447,0.7044,0.0275,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,25.4362,-0.4932,0.0167,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0121,V121_DDR,26.2573,0.3178,0.0268,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0122,V122_DDR,25.3950,-0.5346,0.0169,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0124,V124_DDR,25.2787,-0.6485,0.0144,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0135,V135_DDR,25.3942,-0.5389,0.0204,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0144,V144_DDR,24.8296,-1.0323,-0.0509,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0145,V145_DDR,24.6792,-1.1794,-0.0542,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,26.2871,0.3476,0.0268,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,25.7110,-0.2305,0.0288,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0175,V175_DDR,25.2970,-0.6249,0.0092,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,25.7110,-0.2305,0.0288,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,25.8273,-0.1142,0.0287,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,25.3942,-0.5389,0.0204,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,25.3826,-0.5503,0.0201,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,25.3201,-0.6125,0.0199,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,25.1766,-0.7516,0.0154,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,25.2245,-0.7092,0.0210,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,25.3826,-0.5503,0.0201,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0211,V211_DDR,26.5326,0.5934,0.0264,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,25.4492,-0.4792,0.0156,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0213,V213_DDR,25.3271,-0.6063,0.0206,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0215,V215_DDR,25.4006,-0.5288,0.0167,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0217,V217_DDR,25.4293,-0.4990,0.0156,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0218,V218_DDR,25.1878,-0.7404,0.0154,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0228,V228_DDR,25.3209,-0.6125,0.0207,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0232,V232_DDR,25.3701,-0.5634,0.0207,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0233,V233_DDR,25.3975,-0.5355,0.0202,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0240,V240_DDR,25.3001,-0.6308,0.0182,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0244,V244_DDR,25.3826,-0.5503,0.0201,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0246,MDT1_DDR,25.8521,-0.0979,0.0373,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0249,V249_DDR,25.3745,-0.5589,0.0206,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0250,V250_DDR,24.3618,-1.5399,-0.0110,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0251,V251_DDR,25.2574,-0.6762,0.0209,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.VOLT.0252,V252_DDR,25.1766,-0.7516,0.0154,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,24.1907,-1.7141,-0.0080,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,23.7582,-2.1242,-0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,23.9501,-1.8546,-0.1080,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,26.1246,0.1852,0.0266,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,24.3921,-1.4799,-0.0408,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,24.5933,-1.2652,-0.0542,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,24.5933,-1.2652,-0.0542,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,24.5740,-1.2846,-0.0542,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,23.8438,-2.0347,-0.0343,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,23.8438,-2.0347,-0.0343,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,25.6204,-0.3208,0.0285,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,26.3430,0.4057,0.0246,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,25.3488,-0.5846,0.0207,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,25.3112,-0.6223,0.0207,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,25.4591,-0.4929,0.0393,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,25.4591,-0.4929,0.0393,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWWELSH1,CSWSWELSHUN1_RA,25.7944,-0.1463,0.0279,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWWELSH3,CSWSWELSHUN3_RA,25.7944,-0.1463,0.0279,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWWILKES1,CSWSWILKESUN1_RA,25.9344,-0.0059,0.0275,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWWILKES2,CSWSWILKESUN2_RA,25.9344,-0.0059,0.0275,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,CSWWILKES3,CSWSWILKESUN3_RA,25.9149,-0.0252,0.0273,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,24.2762,-1.6071,-0.0295,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,DENL,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,DERS,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,DOE,DOE,25.3346,-0.5886,0.0104,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,24.2398,-1.6709,-0.0021,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,DPC,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,DUK,VACS,25.3720,-0.5539,0.0132,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDDY,EDDY,29.5171,3.6347,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,24.7381,-1.1840,0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,24.5610,-1.3539,0.0021,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,24.5748,-1.3458,0.0078,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE.SLCC,EDESTL4391_PLT,24.1029,-1.8191,0.0093,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE.VOLT.0234,EDE.VOLT.0234_H,24.4857,-1.4366,0.0095,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,24.3122,-1.6048,0.0042,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_EC_01,EDELAR3821UN1_RA,24.7381,-1.1840,0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_EC_02,EDELAR3821UN2_RA,24.7131,-1.2090,0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_EC_03,EDELAR3821UN3_RA,24.7381,-1.1840,0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_EC_04,EDELAR3821UN4_RA,24.7381,-1.1840,0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_EDE,EDE_LA,25.2386,-0.6839,0.0097,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_ERW,EDEERWFUNG1_RA,24.0609,-1.8435,-0.0083,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,24.2256,-1.6767,-0.0104,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_OZD_5,EDEOZRK_BUN5_RA,25.4802,-0.4438,0.0113,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_OZD_6,EDEOZRK_BUN6_RA,25.4802,-0.4438,0.0113,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_OZD_7,EDEOZRK_BUN7_RA,25.4802,-0.4438,0.0113,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_OZD_8,EDEOZRK_BUN8_RA,25.4802,-0.4438,0.0113,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,25.3277,-0.5985,0.0134,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_RIV_10,EDERIV1671UN10_RA,24.5366,-1.3852,0.0091,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_RIV_11,EDERIV1671UN11_RA,24.5366,-1.3852,0.0091,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_RIV_12,EDERIV453UN12_PLT,24.5366,-1.3852,0.0091,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_SL_01,EDESTL4391UN1_RA,23.9558,-1.9662,0.0093,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,EDE_SWMP,EDE_SWMP_LA,25.4815,-0.4406,0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EEI,EEI,25.3345,-0.5886,0.0103,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EES,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,24.0215,-1.8787,-0.0125,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,ERCOTE,ERCOTE,25.7944,-0.1463,0.0279,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,ERCOTN,ERCOTN,24.3236,-1.5839,-0.0052,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,24.7754,-1.1338,-0.0035,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,FMPP,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,FPC,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,FPL,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,FREM_50T,OPPDFREM_GUN1_RA,25.6407,-0.2705,-0.0015,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,FREM_6,OPPDFREM_AUN6_RA,25.6026,-0.3087,-0.0015,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,FREM_7,OPPDFREM_AUN7_RA,25.6026,-0.3087,-0.0015,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,FREM_8,OPPDFREM_AUN8_RA,25.4977,-0.4135,-0.0015,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,FREM_LOAD,FREM_LOAD_LA,25.6136,-0.2976,-0.0015,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,FRONTIER,WRGETTUNFRONTIER_RA,24.4513,-1.4474,-0.0141,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,GATEWAY_LOAD,CSWS_TENASKA_LA,26.0474,0.1086,0.0261,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,25.2049,-0.6789,-0.0289,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,24.1059,-1.7849,-0.0220,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,25.3486,-0.5737,0.0096,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,25.3486,-0.5737,0.0096,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,25.3486,-0.5737,0.0096,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.GREC2,GRDAGRDA17UN2_RA,25.2061,-0.7206,0.0140,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,25.2061,-0.7206,0.0140,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,25.1999,-0.7268,0.0140,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,25.1999,-0.7268,0.0140,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,23.8043,-2.0905,-0.0180,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,24.8678,-1.0519,0.0070,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,24.8678,-1.0519,0.0070,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,24.8678,-1.0519,0.0070,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.VOLT.0130,V130_DDR,25.5262,-0.4017,0.0152,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA.VOLT.0237,V237_DDR,25.3367,-0.5914,0.0153,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDAHUB2,GRDAHUB2_H,24.8316,-1.0871,0.0060,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDAHUB3,GRDAHUB3_H,24.7486,-1.1652,0.0010,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA_GRDA,GRDA_LA,25.3115,-0.6158,0.0146,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA_HUB,GRDA_H,24.8462,-1.0762,0.0097,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRDA_HUBSA,GRDASA_H,25.1207,-0.8048,0.0128,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GRE,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,26.6856,0.8043,-0.0314,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GSEC_SPS,SPS_GSEC_LA,27.7090,1.8262,-0.0299,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GSPR2014HUB,GSPR2014HUB_H,27.0408,1.1576,-0.0295,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,GSPR2015HUB,GSPR2015HUB_H,26.9659,1.0826,-0.0295,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,26.4725,0.5894,-0.0297,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,HARRISON,CSWSLEBROCKPLT1,26.0746,0.1352,0.0267,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,HAST_TNSK_HUB,HAST_TNSK_H,26.3892,0.4816,-0.0051,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,HQST,PJM,25.3892,-0.5304,0.0069,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,HST,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,INDNSUB_H_5,INDNSUB_HUN5_RA,25.1669,-0.7437,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,INDNSUB_H_6,INDNSUB_HUN6_RA,25.1669,-0.7437,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,INDNSUB_I_3,INDNSUBIUN3_RA,25.1456,-0.7650,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,INDNSUB_I_4,INDNSUBIUN4_RA,25.1456,-0.7650,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,INDNSUB_J_1,INDNSUBJUN1_RA,25.1816,-0.7291,-0.0021,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,INDNSUB_J_2,INDNSUBJUN2_RA,25.1816,-0.7291,-0.0021,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,INDN_INDN,INDN_LA,25.1545,-0.7561,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,24.7623,-1.1392,-0.0113,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,ISNE,PJM,25.3892,-0.5304,0.0069,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,JEA,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,JONES_STREET_1,OPPDJONES_STUN1_RA,25.4657,-0.4458,-0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,JONES_STREET_2,OPPDJONES_STUN2_RA,25.4657,-0.4458,-0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,24.4573,-1.4503,-0.0051,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KACYCT4,KACYNEARMANUNCT4_RA,24.6581,-1.2517,-0.0029,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,24.6595,-1.2589,0.0057,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,24.6581,-1.2517,-0.0029,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,24.7464,-1.1635,-0.0029,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,24.7167,-1.1931,-0.0029,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KACY_KACY,KACY_LA,24.7793,-1.1305,-0.0029,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,24.7767,-1.1334,-0.0026,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,25.6163,-0.2967,0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,24.0556,-1.8595,0.0023,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,23.7154,-2.1814,-0.0160,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.VOLT.0222,V222_DDR,24.7490,-1.1610,-0.0028,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.VOLT.0223,V223_DDR,24.3620,-1.5483,-0.0025,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.VOLT.0241,V241_DDR,25.4372,-0.4778,0.0022,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.VOLT.0243,V243_DDR,25.1555,-0.7650,0.0078,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.VOLT.0247,V247_DDR,24.4612,-1.4493,-0.0022,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.VOLT.0253,V253_DDR,24.7918,-1.1184,-0.0025,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,23.2718,-2.6327,-0.0082,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,24.2536,-1.6557,-0.0034,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,24.2536,-1.6557,-0.0034,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,24.2536,-1.6557,-0.0034,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,24.2534,-1.6560,-0.0034,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,24.7784,-1.1318,-0.0025,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,24.7784,-1.1318,-0.0025,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHUB,KCPLHUB_H,24.0056,-1.9008,-0.0063,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHUB17,KCPLHUB17_H,24.0142,-1.8915,-0.0070,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHUB18,KCPLHUB18_H,24.0132,-1.8930,-0.0066,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHUB19,KCPLHUB19_H,24.0687,-1.8376,-0.0065,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHUB20,KCPLHUB20_H,24.0182,-1.8876,-0.0069,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHUB21,KCPLHUB21_H,24.0583,-1.8472,-0.0073,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHUB22,KCPLHUB22_H,24.0309,-1.8750,-0.0069,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHUB23,KCPLHUB23_H,24.0122,-1.8935,-0.0071,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLHUB24,KCPLHUB24_H,24.0016,-1.9037,-0.0074,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,24.4609,-1.4483,-0.0035,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,24.4609,-1.4483,-0.0035,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,23.7882,-2.1212,-0.0033,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,23.7882,-2.1212,-0.0033,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,24.7901,-1.1200,-0.0026,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,24.7767,-1.1334,-0.0026,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,24.8313,-1.0788,-0.0027,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,24.8313,-1.0788,-0.0027,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,24.8312,-1.0788,-0.0027,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,24.8312,-1.0788,-0.0027,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,24.8312,-1.0788,-0.0027,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,24.8312,-1.0788,-0.0027,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,24.8312,-1.0789,-0.0027,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,24.8312,-1.0789,-0.0027,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,24.2129,-1.6984,-0.0015,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,24.7474,-1.1631,-0.0022,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KCPL_KCPL,KCPL_LA,24.6975,-1.2126,-0.0027,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KENN,KENN_LA,25.3158,-0.6097,0.0128,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KEP2_SECI,KEP2_SECI_LA,25.8133,-0.0751,-0.0243,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KERR_1,GRDAKERR_HYDUN1_RA,25.3092,-0.6188,0.0152,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KERR_2,GRDAKERR_HYDUN2_RA,25.3249,-0.6029,0.0151,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KERR_3,GRDAKERR_HYDUN3_RA,25.3249,-0.6029,0.0151,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KERR_4,GRDAKERR_HYDUN4_RA,25.3092,-0.6188,0.0152,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,24.2533,-1.6561,-0.0034,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,24.2533,-1.6561,-0.0034,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,24.3901,-1.5193,-0.0033,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,24.3901,-1.5193,-0.0033,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,24.2723,-1.6375,-0.0029,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,24.3266,-1.5839,-0.0023,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,24.3266,-1.5839,-0.0023,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,24.9721,-0.9194,-0.0213,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,24.9721,-0.9194,-0.0213,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,24.9721,-0.9194,-0.0213,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,25.4362,-0.4629,-0.0137,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,25.4362,-0.4629,-0.0137,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,24.9806,-0.9106,-0.0215,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,25.3542,-0.5444,-0.0142,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,24.2282,-1.6745,-0.0100,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,24.6702,-1.2489,0.0063,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,24.6702,-1.2489,0.0063,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,24.3850,-1.5216,-0.0061,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,24.3850,-1.5216,-0.0061,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,24.3850,-1.5216,-0.0061,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,25.7303,-0.1665,-0.0159,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,24.8922,-1.0075,-0.0130,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,24.6304,-1.2763,-0.0060,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,KMEA_EUDORA,KMEA_EUDORA_LA,24.5679,-1.3403,-0.0046,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,LAFA,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,LAM345,LAM345,24.8650,-1.0262,-0.0216,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,LEPA,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_JSTREET,LES8_NUNJ_STREET_RA,25.4114,-0.4992,-0.0022,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_LES,LES_LA,25.3780,-0.5326,-0.0022,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,25.2016,-0.7090,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_ROKEBY_1,LESROKEBYUN1_RA,25.2696,-0.6410,-0.0022,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_ROKEBY_2,LESROKEBYUN2_RA,25.3120,-0.5985,-0.0022,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_ROKEBY_3,LESROKEBYUN3_RA,25.3120,-0.5985,-0.0022,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_TBGS_CC1,LES84_BLUFPLT1,25.2120,-0.6986,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,25.2016,-0.7090,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_WAVERLY,LES_WAVERLY_H,25.2781,-0.6325,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,25.2329,-0.6787,-0.0011,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,25.2341,-0.6776,-0.0011,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,LGEE,LGEE,25.3632,-0.5580,0.0084,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MALDEN,MALDEN_LA,25.3153,-0.6098,0.0124,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MCWEST,MCWEST,26.5347,0.6226,-0.0007,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MDU,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,26.3612,0.4568,-0.0083,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,25.5074,-0.4024,-0.0030,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,26.7661,0.8550,-0.0016,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MEAN_NPPD,NPPD_MEAN_LA,26.3705,0.4634,-0.0056,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MEC,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MHEB,MHEB,26.5861,0.6720,0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,25.4983,-0.4027,-0.0117,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,25.5502,-0.3466,-0.0159,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,25.4983,-0.4027,-0.0117,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,25.4983,-0.4027,-0.0117,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,25.5502,-0.3466,-0.0159,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,24.3129,-1.5979,-0.0020,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MISO,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,25.9811,0.0934,-0.0251,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,25.9811,0.0934,-0.0251,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,24.8105,-1.0941,-0.0081,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,24.9972,-0.8951,-0.0204,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,25.2123,-0.6854,-0.0151,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,24.5835,-1.3088,-0.0205,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKEC_KPP,SECI_MKEC_KPP_LA,24.8639,-1.0300,-0.0189,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,24.6864,-1.2058,-0.0206,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,25.0042,-0.8901,-0.0185,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,25.0042,-0.8901,-0.0185,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,25.0042,-0.8901,-0.0185,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,25.0042,-0.8901,-0.0185,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,25.0042,-0.8901,-0.0185,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,24.9784,-0.9366,0.0023,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,25.2920,-0.6298,0.0090,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,25.2920,-0.6298,0.0090,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,25.2805,-0.6378,0.0056,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,25.6072,-0.3079,0.0024,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MOWR,AECI,25.2242,-0.6972,0.0087,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,25.1310,-0.7859,0.0041,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,25.2960,-0.6255,0.0087,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,24.5024,-1.4085,-0.0018,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,24.5791,-1.3319,-0.0018,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,24.0517,-1.8441,-0.0169,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,24.5167,-1.3942,-0.0018,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,24.2952,-1.6155,-0.0021,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,24.2952,-1.6155,-0.0021,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,24.2442,-1.6664,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,24.2442,-1.6664,-0.0021,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,24.7490,-1.1610,-0.0028,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,24.7490,-1.1610,-0.0028,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,24.7490,-1.1610,-0.0028,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,24.7079,-1.2021,-0.0028,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,24.7490,-1.1610,-0.0028,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,24.7490,-1.1610,-0.0028,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,24.7490,-1.1610,-0.0028,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,25.2900,-0.6267,0.0039,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,24.1035,-1.8075,-0.0017,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,23.8119,-2.0986,-0.0023,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,23.7371,-2.1734,-0.0023,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,23.8119,-2.0986,-0.0023,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSTWA1UN1,MPSTWA1UN1_RA,24.8074,-1.1025,-0.0028,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPSTWA1UN2,MPSTWA1UN2_RA,24.8074,-1.1025,-0.0028,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MPS_MPS,MPS_LA,24.8282,-1.0830,-0.0016,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MSTNG,SPSMSTNGPLT1,28.9126,3.0302,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MSTNG4,SPSMSTNGUN4_RA,28.5739,2.6914,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,MSTNG5,SPSMSTNGUN5_RA,28.7108,2.8284,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,28.7108,2.8284,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NBSO,PJM,25.3892,-0.5304,0.0069,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,24.5322,-1.3788,-0.0018,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,24.5306,-1.3804,-0.0018,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,26.0552,0.1720,-0.0296,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NHC1,VACS,25.3720,-0.5539,0.0132,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,25.4120,-0.4994,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,25.4120,-0.4994,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,25.4120,-0.4994,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,27.1464,1.2379,-0.0042,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,26.4397,0.5320,-0.0051,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,25.1888,-0.7216,-0.0024,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,25.4725,-0.4392,-0.0010,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,26.4397,0.5320,-0.0051,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.HUB.PY2018,NPPDPY18_H,24.8573,-1.0532,-0.0022,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,24.8457,-1.0649,-0.0022,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,24.8562,-1.0543,-0.0022,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,24.8327,-1.0779,-0.0022,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,25.5298,-0.3816,-0.0014,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,25.7337,-0.1710,-0.0081,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,25.7337,-0.1710,-0.0081,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,25.7613,-0.1425,-0.0089,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,25.5298,-0.3816,-0.0014,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,25.4205,-0.4902,-0.0020,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,26.7371,0.8305,-0.0061,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,25.6565,-0.2455,-0.0108,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,26.7371,0.8305,-0.0061,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,26.9555,1.0478,-0.0050,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,26.5219,0.6157,-0.0066,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,25.5504,-0.3599,-0.0024,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,26.4397,0.5320,-0.0051,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,25.6748,-0.2276,-0.0103,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,25.7337,-0.1710,-0.0081,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,25.7337,-0.1710,-0.0081,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,26.0929,0.1876,-0.0074,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,26.0886,0.1834,-0.0075,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,26.0886,0.1834,-0.0075,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,26.5846,0.6789,-0.0070,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,25.7958,-0.1160,-0.0010,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,26.5787,0.6710,-0.0050,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,27.2294,1.3207,-0.0040,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,25.8941,-0.0175,-0.0011,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,25.9735,0.0620,-0.0012,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.NELI.DDR,NELI_DDR,25.6394,-0.2716,-0.0018,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.NPPM.1058,SH1058_DDR,25.9895,0.0789,-0.0022,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,26.2905,0.3849,-0.0071,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,26.4397,0.5320,-0.0051,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,25.1888,-0.7216,-0.0024,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,25.5471,-0.3643,-0.0014,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.TECH.1,KEARNE_DDR,26.5849,0.6789,-0.0067,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,25.7260,-0.1830,-0.0037,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,25.7260,-0.1830,-0.0037,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,25.5671,-0.3441,-0.0016,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD.VOLT.0236,V236_DDR,25.3229,-0.5868,-0.0030,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD2017HUB,NPPD2017HUB_H,24.8424,-1.0682,-0.0022,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,25.6054,-0.3051,-0.0023,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,27.1464,1.2379,-0.0042,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,26.7756,0.8688,-0.0059,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,26.7756,0.8688,-0.0059,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_BPS,NPPDBEAPWRSTPLT1,25.3017,-0.6081,-0.0029,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,25.3526,-0.5572,-0.0030,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,25.7818,-0.1299,-0.0010,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,26.0665,0.1610,-0.0073,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,25.5302,-0.3802,-0.0024,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,25.7469,-0.1634,-0.0024,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,25.5317,-0.3786,-0.0024,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,26.3672,0.4595,-0.0051,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_COOPR,NPPDCOOPERUN1_RA,24.6278,-1.2830,-0.0019,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_COSN_NPPD,NPPD_COSN_LA,26.6900,0.7820,-0.0047,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,25.7590,-0.1525,-0.0012,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,25.7741,-0.1374,-0.0012,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,25.6421,-0.2620,-0.0086,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,25.6242,-0.2796,-0.0089,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,26.2368,0.3289,-0.0049,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,26.2112,0.3034,-0.0049,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,26.2112,0.3034,-0.0049,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,26.2952,0.3873,-0.0049,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,25.4205,-0.4902,-0.0020,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,26.2886,0.3807,-0.0049,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,25.1580,-0.7523,-0.0024,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,26.4073,0.4996,-0.0051,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,26.3904,0.4828,-0.0051,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,26.4021,0.4945,-0.0052,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,26.4021,0.4945,-0.0052,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,26.3672,0.4595,-0.0051,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,26.3672,0.4595,-0.0051,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,27.6378,1.7286,-0.0036,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,26.2864,0.3778,-0.0042,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,25.3877,-0.5164,-0.0087,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,26.1058,0.1954,-0.0024,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,25.5967,-0.3049,-0.0111,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,25.8607,-0.0503,-0.0018,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_NELI_LD,NPPD_NELIGH_LA,25.6394,-0.2716,-0.0018,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,25.7676,-0.1367,-0.0084,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,25.7676,-0.1367,-0.0084,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_NPPD,NPPD_LA,25.9608,0.0521,-0.0041,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,25.1580,-0.7523,-0.0024,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,25.1580,-0.7523,-0.0024,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,24.9653,-0.9432,-0.0043,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,26.7473,0.8402,-0.0057,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NSB,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NSP,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,NSSO,PJM,25.3892,-0.5304,0.0069,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,NYIS,PJM,25.3892,-0.5304,0.0069,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,24.7953,-1.0855,-0.0319,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,23.8429,-2.0456,-0.0242,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,23.6269,-2.2675,-0.0183,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,23.6269,-2.2675,-0.0183,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,25.0940,-0.7889,-0.0298,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,24.1059,-1.7849,-0.0220,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,24.1085,-1.7902,-0.0140,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,23.0265,-2.8670,-0.0193,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,23.7933,-2.1003,-0.0192,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,23.7777,-2.1131,-0.0220,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,24.8392,-1.1819,0.1083,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,23.7933,-2.1003,-0.0192,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,25.0076,-0.8748,-0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,24.3129,-1.5979,-0.0020,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,24.6801,-1.2000,-0.0326,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,24.8664,-1.0932,0.0468,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,23.7777,-2.1131,-0.0220,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,24.1216,-1.7594,-0.0318,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,24.4157,-1.4840,-0.0130,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,24.3686,-1.4995,-0.0446,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,24.6289,-1.3228,0.0390,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,24.3129,-1.5979,-0.0020,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,24.3129,-1.5979,-0.0020,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,23.7777,-2.1131,-0.0220,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.NUEN.ADA1,ADA1_DDR,24.5957,-1.1260,-0.1911,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.NUEN.LAM1,LAM1_DDR,26.1301,0.1928,0.0246,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.NUEN.MDT2,MDT2_DDR,24.8431,-1.1779,0.1083,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.NUEN.MDT3,MDT3_DDR,24.8431,-1.1779,0.1083,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.NUEN.WWO1,WWO1_DDR,24.6423,-1.0805,-0.1899,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,24.7756,-1.1604,0.0233,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,24.7751,-1.1609,0.0233,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,24.8053,-1.1308,0.0233,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,24.8841,-1.0782,0.0496,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,24.8841,-1.0782,0.0496,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,24.8051,-1.1309,0.0233,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,24.8051,-1.1309,0.0233,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,23.7777,-2.1131,-0.0220,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,25.2952,-0.6327,0.0152,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,25.0076,-0.8748,-0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,24.0912,-1.8595,0.0380,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,24.1216,-1.7594,-0.0318,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,25.1695,-0.7651,0.0218,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,24.2159,-1.6666,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,24.2159,-1.6666,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,24.3233,-1.5592,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,24.3233,-1.5592,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,23.5333,-2.3510,-0.0284,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,23.8827,-2.0055,-0.0246,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,23.8429,-2.0456,-0.0242,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,23.8740,-2.0165,-0.0222,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,23.8740,-2.0165,-0.0222,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,24.7662,-1.1697,0.0232,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,24.3555,-1.5193,-0.0379,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,24.3555,-1.5193,-0.0379,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,24.3555,-1.5193,-0.0379,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0033,FOSTER_DDR,25.0849,-1.0254,0.1976,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0034,CUSHOIL_DDR,25.7780,-0.1555,0.0208,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0035,TARBY_DDR,25.6954,-0.2417,0.0244,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0036,CUSHFLI_DDR,25.7780,-0.1555,0.0208,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,25.4378,-0.4993,0.0243,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,25.4378,-0.4993,0.0243,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,24.6018,-1.3417,0.0307,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0040,TROSPER_DDR,25.0806,-0.9771,0.1450,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,25.0534,-0.9766,0.1172,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,25.3405,-0.5946,0.0224,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0115,V115_DDR,24.9007,-1.1560,0.1440,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0116,V116_DDR,24.9265,-1.0177,0.0314,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0118,V118_DDR,25.1622,-0.8012,0.0506,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0125,V125_DDR,25.5271,-0.4080,0.0223,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0126,V126_DDR,25.3336,-0.6025,0.0233,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0129,V129_DDR,24.3420,-1.4000,-0.1708,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,24.7961,-1.1276,0.0110,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0134,V134_DDR,25.3769,-0.5571,0.0213,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0138,V138_DDR,25.3006,-0.6361,0.0240,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,24.9338,-1.0104,0.0315,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0143,V143_DDR,25.3729,-0.5682,0.0283,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0149,V149_DDR,24.3481,-1.3172,-0.2474,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0150,V150_DDR,24.4575,-1.2360,-0.2193,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0155,V155_DDR,25.2532,-0.6839,0.0244,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0156,V156_DDR,24.7961,-1.1276,0.0110,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0166,V166_DDR,26.3806,0.4437,0.0242,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,24.9666,-0.9939,0.0477,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,24.4575,-1.2360,-0.2193,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0170,V170_DDR,24.6375,-1.0920,-0.1832,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,24.3956,-1.3541,-0.1631,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0176,V176_DDR,24.4575,-1.2360,-0.2193,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0177,V177_DDR,24.4105,-1.4722,-0.0300,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,24.9879,-0.9882,0.0634,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,24.5798,-1.2368,-0.0962,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0195,V195_DDR,26.1941,0.2511,0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0197,V197_DDR,25.6899,-0.2453,0.0224,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0198,V198_DDR,26.3806,0.4437,0.0242,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0208,V208_DDR,26.2139,0.2707,0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0209,V209_DDR,26.2139,0.2707,0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,25.4993,-0.4358,0.0224,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0216,V216_DDR,25.0447,-0.9782,0.1102,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0219,V219_DDR,25.2532,-0.6839,0.0244,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0220,V220_DDR,24.4575,-1.2360,-0.2193,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0224,V224_DDR,24.8689,-1.0756,0.0318,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0225,V225_DDR,24.8702,-1.0744,0.0318,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0226,V226_DDR,24.8689,-1.0756,0.0318,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0227,V227_DDR,24.8689,-1.0756,0.0318,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0229,V229_DDR,24.5927,-1.3549,0.0348,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0231,V231_DDR,25.3784,-0.6051,0.0708,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0238,V238_DDR,24.0533,-1.8369,-0.0225,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.VOLT.0242,V242_DDR,25.2768,-0.6602,0.0243,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,24.2087,-1.6629,-0.0412,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,24.3129,-1.5979,-0.0020,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,23.9404,-1.9459,-0.0265,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,24.6873,-1.1929,-0.0326,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,24.2087,-1.6629,-0.0412,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,24.8798,-0.9948,-0.0382,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,22.9802,-2.9138,-0.0187,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEHL7,OKGEHL7_H,24.9566,-1.0150,0.0589,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEHL8,OKGEHSL1UN8_RA,24.9566,-1.0150,0.0589,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEHL910,OKGEHSL1PLT2,24.9566,-1.0150,0.0589,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,24.8023,-1.0734,-0.0371,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEMCC,OKGEMCCLAIPLT1,21.6082,-1.6014,-2.7032,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,25.1175,-0.8226,0.0273,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,25.1175,-0.8226,0.0273,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,25.0753,-0.8648,0.0273,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,24.5174,-1.3998,0.0044,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,24.3839,-1.5332,0.0044,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,24.3865,-1.5307,0.0044,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,24.5174,-1.3998,0.0044,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGESM1,OKGESEMINOLEUN1_RA,24.8836,-1.0843,0.0552,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGESM2,OKGESEMINOLEUN2_RA,24.8457,-1.1258,0.0587,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGESM3,OKGESEMINOLEUN3_RA,24.8457,-1.1258,0.0587,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGESO1,OKGESONR1UN1_RA,23.8214,-2.0760,-0.0153,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGESO2,OKGESONR1UN2_RA,23.8740,-2.0165,-0.0222,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,24.7851,-1.0905,-0.0371,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,24.3960,-1.4426,-0.0742,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGETINK5A,OKGETINK5UN1_RA,24.9902,-1.0333,0.1108,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGETINK5B,OKGETINK5UN2_RA,24.9902,-1.0333,0.1108,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,24.5023,-1.3754,-0.0351,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,23.8429,-2.0456,-0.0242,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,25.0589,-0.8754,0.0215,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,24.3129,-1.5979,-0.0020,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE_OKGE,OKGE_LA,24.9518,-0.9824,0.0215,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,24.0912,-1.8595,0.0380,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,24.4910,-1.3867,-0.0351,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMLP,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,25.2326,-0.7003,0.0202,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,24.9777,-0.9569,0.0218,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_GENHUB,OMPA_GENHUB_H,23.0237,-1.5630,-1.3260,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_KAW,OKGEOMKAWUN2_RA,24.2143,-1.6845,-0.0140,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,24.5412,-1.2938,-0.0778,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,23.7933,-2.1003,-0.0192,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,24.7155,-1.1568,-0.0405,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,23.4473,-2.4242,-0.0412,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,25.2171,-0.7011,0.0055,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,24.2175,-1.6813,-0.0140,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,24.2175,-1.6813,-0.0140,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_SPP,OMPA_SPP_LA,24.4127,-1.4924,-0.0076,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,24.2087,-1.6629,-0.0412,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,ONETA,CSWSCALPINEUNONETA_1_RA,25.2110,-0.7219,0.0201,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,25.2110,-0.7219,0.0201,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,25.2110,-0.7219,0.0201,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,25.2110,-0.7219,0.0201,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,ONT,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,25.4133,-0.4981,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,25.4133,-0.4981,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,25.4133,-0.4981,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,25.4133,-0.4981,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,25.4133,-0.4981,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,25.4133,-0.4981,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,25.4133,-0.4981,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,25.4133,-0.4981,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,25.4133,-0.4981,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,25.3650,-0.5464,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,25.4120,-0.4994,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,25.1706,-0.7407,-0.0014,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,25.4076,-0.5037,-0.0014,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,25.4076,-0.5037,-0.0014,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD_GLDN,OPPD_GLDN_LA,25.4092,-0.5022,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD_GLDN2,OPPD_GLDN2_LA,25.4381,-0.4734,-0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,25.4205,-0.4902,-0.0020,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD_NC_HST,OPPD_NC_HST_LA,24.9444,-0.9664,-0.0020,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD_NO_HST,OPPD_NO_HST_LA,25.4002,-0.5112,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD_OPPD,OPPD_LA,25.4954,-0.4160,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD_PAPIO,OPPD_PAPIO_LA,25.4203,-0.4911,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,25.4178,-0.4937,-0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OTP,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,OVEC,OVEC,25.3710,-0.5495,0.0078,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PARAGOULD,PARAGOULD_LA,25.3166,-0.6095,0.0134,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PENSACOLA_1,GRDAPENSA1UN1_RA,25.2698,-0.6566,0.0137,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PENSACOLA_2,GRDAPENSA1UN2_RA,25.2698,-0.6566,0.0137,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PENSACOLA_3,GRDAPENSA1UN3_RA,25.2698,-0.6566,0.0137,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PENSACOLA_4,GRDAPENSA1UN4_RA,25.2846,-0.6422,0.0141,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PENSACOLA_5,GRDAPENSA1UN5_RA,25.2846,-0.6422,0.0141,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PENSACOLA_6,GRDAPENSA1UN6_RA,25.2846,-0.6422,0.0141,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PIGGOTT,PIGGOTT_LA,25.3157,-0.6098,0.0127,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,PJM,PJM,25.3892,-0.5304,0.0069,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PLUM,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,POPLARBLUFF,POPLARBLUFF_LA,25.3158,-0.6087,0.0118,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,26.6398,0.7279,-0.0008,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,26.6398,0.7279,-0.0008,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,26.5796,0.6674,-0.0006,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,26.5796,0.6674,-0.0006,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,28.6310,2.7186,-0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,28.6326,2.7202,-0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,26.5159,0.6038,-0.0007,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,26.4966,0.5854,-0.0015,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,24.1117,-1.7940,-0.0071,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,25.3112,-0.6132,0.0117,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,24.7317,-1.1786,-0.0025,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,24.8912,-1.0413,0.0198,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,25.4425,-0.5320,0.0618,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,25.5385,-0.3901,0.0159,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,25.7350,-0.1787,0.0009,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,27.2719,1.3595,-0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,26.0091,0.0962,0.0002,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,27.4197,1.5065,0.0005,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,27.4360,1.5229,0.0004,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,26.1167,0.2032,0.0007,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,PUPP,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,RCEAST,RCEAST,25.5062,-0.4034,-0.0032,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SALINA_1,GRDASALINA1UN1_RA,25.3124,-0.6156,0.0152,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SALINA_2,GRDASALINA1UN2_RA,25.3124,-0.6156,0.0152,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SALINA_3,GRDASALINA1UN3_RA,25.3124,-0.6156,0.0152,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SALINA_4,GRDASALINA1UN4_RA,25.3124,-0.6156,0.0152,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SALINA_5,GRDASALINA1UN5_RA,25.3124,-0.6156,0.0152,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SALINA_6,GRDASALINA1UN6_RA,25.3124,-0.6156,0.0152,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SARPY_1,OPPDSARPYUN1_RA,25.3869,-0.5245,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SARPY_2,OPPDSARPYUN2_RA,25.4429,-0.4686,-0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SARPY_3,OPPDSARPYUN3_RA,25.3251,-0.5864,-0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SARPY_4,OPPDSARPYUN4_RA,25.3251,-0.5864,-0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SARPY_5,OPPDSARPYUN5_RA,25.3251,-0.5864,-0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SC,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SCEG,VACS,25.3720,-0.5539,0.0132,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SCSE,SCSE,25.1493,-0.7552,-0.0082,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SEC,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,24.4378,-1.4533,-0.0217,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,24.4378,-1.4533,-0.0217,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,24.4378,-1.4533,-0.0217,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,25.9411,0.0506,-0.0222,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,24.4378,-1.4533,-0.0217,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,24.7367,-1.1547,-0.0213,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,24.6593,-1.2338,-0.0197,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,24.6593,-1.2338,-0.0197,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,25.0002,-0.8940,-0.0185,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,24.3515,-1.5388,-0.0224,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,25.3441,-0.5549,-0.0137,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,25.5554,-0.3342,-0.0231,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,25.4283,-0.4684,-0.0161,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,24.4267,-1.4644,-0.0217,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,25.3549,-0.5417,-0.0162,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,26.0061,0.1185,-0.0252,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,25.3045,-0.5878,-0.0204,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,24.8237,-1.0676,-0.0214,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,24.8250,-1.0664,-0.0214,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,24.8250,-1.0664,-0.0214,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,24.8250,-1.0664,-0.0214,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,24.7280,-1.1630,-0.0217,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,24.7367,-1.1547,-0.0213,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI_SECI,SECI_LA,25.4487,-0.4437,-0.0203,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,24.7623,-1.1392,-0.0113,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,24.7623,-1.1392,-0.0113,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,25.0002,-0.8940,-0.0185,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SEHA,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,24.4910,-1.3867,-0.0351,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SERU,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SETH,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SGE,SGE,24.9222,-0.9832,-0.0073,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SMEP,MISO,25.5782,-0.3428,0.0082,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SOCO,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPA,SPA,25.2702,-0.6609,0.0184,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPC,SPC,27.6964,1.7838,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPPNORTH_HUB,SPPNORTH_H,25.8087,-0.1016,-0.0024,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPPSOUTH_HUB,SPPSOUTH_H,24.6208,-1.2937,0.0018,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,25.4107,-0.5115,0.0095,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,25.4169,-0.5053,0.0095,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,25.4991,-0.4229,0.0093,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,25.4991,-0.4229,0.0093,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_NIXA,SPRM_NIXA_LA,25.5029,-0.4194,0.0096,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_SPRM,SPRM_LA,25.6166,-0.3056,0.0095,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,25.4154,-0.5069,0.0095,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,25.4154,-0.5069,0.0095,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,25.3713,-0.5510,0.0095,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,25.4154,-0.5069,0.0095,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,28.4299,2.5473,-0.0302,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,28.3029,2.4202,-0.0300,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,25.8135,-0.0697,-0.0295,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,25.8135,-0.0697,-0.0295,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,27.6477,1.7653,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,29.0479,3.1655,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,28.9400,3.0574,-0.0302,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,28.6437,2.7613,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,26.8940,1.0117,-0.0304,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,28.5619,2.6794,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,28.8829,3.0004,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,28.8828,3.0004,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,28.5619,2.6794,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,25.9591,0.0759,-0.0295,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,28.3029,2.4202,-0.0300,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,26.2619,0.3786,-0.0294,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,25.4431,-0.4406,-0.0290,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,26.6473,0.7638,-0.0293,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,27.1968,1.3135,-0.0294,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,26.4552,0.5718,-0.0294,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,25.2060,-0.6778,-0.0290,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,25.2059,-0.6778,-0.0290,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,25.2059,-0.6778,-0.0290,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,25.2059,-0.6778,-0.0290,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GRID.WRAB,WRAB_DDR,27.0375,1.1543,-0.0296,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,25.2059,-0.6778,-0.0290,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,27.4350,1.5527,-0.0304,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,27.4350,1.5527,-0.0304,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,27.4623,1.5801,-0.0305,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,27.4623,1.5801,-0.0305,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,27.4623,1.5801,-0.0305,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,27.4350,1.5527,-0.0304,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,25.7934,-0.0897,-0.0296,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,25.7934,-0.0897,-0.0296,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,25.7939,-0.0893,-0.0296,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,26.0552,0.1720,-0.0296,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.HOBBS.CC,SPSHOBBSPLT1,28.5790,2.6966,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.JONES1,SPSJONESSUBUN1_RA,26.8622,0.9798,-0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.JONES2,SPSJONESSUBUN2_RA,26.8625,0.9801,-0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.JONES3,SPSJONESSUBUN3_RA,26.8623,0.9799,-0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.JONES4,SPSJONESSUBUN4_RA,26.8623,0.9799,-0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,28.7950,2.9126,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,28.5925,2.7100,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,28.5925,2.7101,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,24.5111,-1.3666,-0.0351,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,25.6812,-0.2020,-0.0296,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,25.6812,-0.2020,-0.0296,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,25.7969,-0.0862,-0.0296,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,27.0375,1.1543,-0.0296,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,25.9062,0.0224,-0.0290,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,25.9120,0.0287,-0.0294,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,25.0940,-0.7889,-0.0298,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,26.0256,0.1425,-0.0296,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.PLANTX1,SPS.PLANTX1_H,28.3470,2.4645,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.PLANTX2,SPS.PLANTX2_H,28.3470,2.4645,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,28.2667,2.3842,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,27.5507,1.6682,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,25.5370,-0.3469,-0.0288,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,29.1624,3.2798,-0.0302,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,27.6323,1.7499,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,26.0875,0.2043,-0.0295,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,28.6536,2.7711,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,29.1155,3.2331,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,28.6536,2.7711,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,28.8385,2.9560,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,25.8911,0.0077,-0.0294,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,30.2270,4.3445,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,30.2572,4.3747,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,29.6427,3.7602,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,28.8806,2.9982,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,30.2515,4.3691,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,24.8650,-1.0262,-0.0216,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,26.9232,1.0401,-0.0296,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,28.3819,2.4993,-0.0302,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,28.3819,2.4993,-0.0302,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,28.6536,2.7711,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,26.9530,1.0706,-0.0304,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0006,SPS.VOLT.0006_H,29.4996,3.6171,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0023,SPS.VOLT.0023_H,28.8929,3.0104,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0025,SPS.VOLT.0025_H,29.1194,3.2368,-0.0302,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0033,SPS.VOLT.0033_H,27.6160,1.7334,-0.0301,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0045,SPS.VOLT.0045_H,30.2270,4.3445,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0046,SPS.VOLT.0046_H,31.2757,5.3932,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0047,SPS.VOLT.0047_H,30.6687,4.7863,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0052,SPS.VOLT.0052_H,27.8413,1.9588,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0113,SPS.VOLT.0113_H,29.3095,3.4270,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0136,SPS.VOLT.0136_H,25.7722,-0.1120,-0.0286,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0137,SPS.VOLT.0137_H,25.7268,-0.1574,-0.0286,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0163,V163_DDR,26.6157,0.7325,-0.0295,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0168,V168_DDR,24.8623,-1.0208,-0.0296,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0180,V180_DDR,31.2757,5.3932,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0181,V181_DDR,25.8534,-0.0307,-0.0287,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0182,V182_DDR,30.3953,4.5129,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0199,V199_DDR,29.2830,3.4006,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0200,V200_DDR,29.3603,3.4779,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.VOLT.0235,V235_DDR,25.9062,0.0224,-0.0290,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,28.9400,3.0574,-0.0302,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,28.6437,2.7613,-0.0303,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,26.4720,0.5890,-0.0297,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,27.6787,1.7961,-0.0301,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS_SPS,SPS_LA,28.7302,2.8475,-0.0301,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,28.5333,2.6508,-0.0302,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SSCN_NPPD,SSCN_NPPD_LA,25.6731,-0.2387,-0.0009,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,25.3077,-0.6170,0.0119,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,25.3077,-0.6170,0.0119,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,TAL,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,TEC,SOUC,25.3922,-0.5347,0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,26.1058,0.1954,-0.0024,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,TVA,TVA,25.3508,-0.5741,0.0122,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,UCUHUB,UCUHUB_H,24.5913,-1.3146,-0.0068,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,UCUHUB17,UCUHUB17_H,24.9268,-0.9740,-0.0120,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,UCUHUB18,UCUHUB18_H,24.7181,-1.1867,-0.0080,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,UCUHUB19,UCUHUB19_H,24.5875,-1.3166,-0.0086,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,UCUHUB20,UCUHUB20_H,24.5905,-1.3137,-0.0086,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,UCUHUB21,UCUHUB21_H,24.6168,-1.2852,-0.0108,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,UCUHUB22,UCUHUB22_H,24.5659,-1.3362,-0.0106,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,UCUHUB23,UCUHUB23_H,24.5709,-1.3312,-0.0107,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,UCUHUB24,UCUHUB24_H,24.5405,-1.3618,-0.0104,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,28.1362,2.2235,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,28.1362,2.2235,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,26.5934,0.6807,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,26.5934,0.6807,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,26.5990,0.6861,0.0002,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,26.5831,0.6709,-0.0006,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,26.5831,0.6709,-0.0006,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,28.1362,2.2235,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,26.9248,1.0117,0.0003,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,27.2672,1.3544,0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,25.7172,-0.1961,0.0006,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,25.5425,-0.3691,-0.0011,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,28.0842,2.1716,-0.0002,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,28.0842,2.1716,-0.0002,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,25.5078,-0.4051,0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,25.7883,-0.1249,0.0004,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,27.0588,1.1456,0.0004,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,25.7680,-0.1449,0.0002,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,26.5022,0.5890,0.0005,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,25.7777,-0.1354,0.0003,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,25.7956,-0.1173,0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,25.7956,-0.1173,0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,25.8579,-0.0552,0.0004,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,25.5926,-0.3190,-0.0012,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,27.0671,1.1537,0.0006,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,27.3525,1.4399,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,27.3525,1.4399,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,27.3525,1.4399,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,27.3525,1.4399,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,27.3525,1.4399,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,27.3525,1.4399,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,28.3807,2.4681,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,26.4221,0.5092,0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,26.4201,0.5072,0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,24.7373,-1.1678,-0.0077,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,26.3822,0.4696,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,27.2646,1.3518,0.0000,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,25.4626,-0.4497,-0.0005,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,25.2101,-0.7011,-0.0015,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,26.0881,0.1753,0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,27.9107,1.9980,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,27.9107,1.9980,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,27.9077,1.9951,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,27.9107,1.9980,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,27.9705,2.0579,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,27.9705,2.0579,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,27.9705,2.0579,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,27.9705,2.0579,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,27.9705,2.0579,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,27.9705,2.0579,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,27.9705,2.0579,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,25.5509,-0.3609,-0.0009,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,27.5161,1.6031,0.0002,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,26.3164,0.4041,-0.0004,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,26.3164,0.4041,-0.0004,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,26.3701,0.4582,-0.0009,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,26.3701,0.4582,-0.0009,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,26.7484,0.8355,0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,26.6451,0.7325,-0.0002,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,26.0180,0.1049,0.0004,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,25.5938,-0.3176,-0.0014,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,25.6736,-0.2401,0.0010,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,26.5990,0.6861,0.0002,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,26.5990,0.6861,0.0002,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,25.7680,-0.1449,0.0002,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,25.5176,-0.3919,-0.0032,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,26.0084,0.0960,-0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,25.3002,-0.6112,-0.0013,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,25.9048,-0.0081,0.0002,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.FSE,WAUE.FSE_H,25.5948,-0.3155,-0.0025,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,26.5988,0.6866,-0.0005,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,26.5639,0.6516,-0.0005,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,25.0417,-0.8697,-0.0014,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,25.0024,-0.9091,-0.0013,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,26.3028,0.3899,0.0002,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,26.1783,0.2653,0.0002,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,25.5059,-0.4057,-0.0011,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,25.5425,-0.3691,-0.0011,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,24.9116,-0.9984,-0.0027,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,24.5593,-1.3533,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,24.5588,-1.3538,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,24.5592,-1.3535,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,25.9716,0.0587,0.0002,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,25.5176,-0.3919,-0.0032,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,26.0004,0.0866,0.0010,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,25.9146,0.0017,0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,27.0172,1.1038,0.0006,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,26.0188,0.1060,0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,25.9522,0.0388,0.0007,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,25.0113,-0.9032,0.0018,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,26.4996,0.5866,0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,25.6390,-0.2741,0.0003,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,25.4626,-0.4497,-0.0005,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,26.5823,0.6674,0.0022,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,25.7313,-0.1817,0.0002,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,26.2820,0.3671,0.0022,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,26.0697,0.1562,0.0008,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,25.2341,-0.6776,-0.0011,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NTWK,WAUE.NTWK_H,26.3408,0.4283,-0.0003,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,26.6185,0.7056,0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,26.6185,0.7056,0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,25.6945,-0.2170,-0.0012,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,25.6928,-0.2191,-0.0008,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,25.9825,0.0693,0.0005,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,25.6945,-0.2170,-0.0012,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,26.6280,0.7149,0.0004,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,25.8018,-0.1103,-0.0006,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,25.4626,-0.4497,-0.0005,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,26.1271,0.2146,-0.0003,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,27.2846,1.3725,-0.0006,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,24.5353,-1.3756,-0.0019,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,24.4469,-1.4641,-0.0018,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,26.4985,0.5859,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,25.6724,-0.2372,-0.0032,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,25.8283,-0.0851,0.0006,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,25.6450,-0.2669,-0.0009,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,25.5938,-0.3176,-0.0014,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.VOLT.0152,V152_DDR,28.6238,2.7111,0.0000,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE.VOLT.0172,V172_DDR,28.0674,2.1547,-0.0001,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_BEPM,WAUE_BEPM_LA,27.2310,1.3184,-0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,26.0339,0.1203,0.0009,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,26.0407,0.1279,0.0001,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_EWA,WAUE_EWA_LA,25.5803,-0.3294,-0.0031,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,26.0212,0.1087,-0.0003,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_HMMU,WAUE_HMMU_LA,25.6496,-0.2625,-0.0006,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,25.5215,-0.3932,0.0020,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_MECB,WAUE_MECB_LA,25.7680,-0.1448,0.0000,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_MMPA,WAUE_MMPA_LA,26.9724,1.0589,0.0008,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_MRES,WAUE_MRES_LA,26.1930,0.2804,-0.0002,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,28.2754,2.3626,0.0000,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,26.5988,0.6866,-0.0005,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,26.1529,0.2407,-0.0006,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_OTP,WAUE_OTP_LA,27.9877,2.0747,0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_OTPW,WAUE_OTPW_LA,27.0572,1.1440,0.0005,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM,WAUE_UGPM_LA,25.9959,0.0833,-0.0002,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,26.9471,1.0346,-0.0003,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,26.0240,0.1110,0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,26.3677,0.4556,-0.0006,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,25.5803,-0.3294,-0.0031,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,25.6496,-0.2625,-0.0006,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,26.0736,0.1612,-0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,26.5988,0.6866,-0.0005,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,26.9724,1.0589,0.0008,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,26.3692,0.4568,-0.0003,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,25.9215,0.0096,-0.0009,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,28.4650,2.5519,0.0004,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,24.2633,-1.6082,-0.0413,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,24.1484,-1.7398,-0.0245,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,22.9546,-2.9215,-0.0367,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,25.5610,-0.3931,0.0414,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,25.5610,-0.3931,0.0414,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,22.6619,-3.2058,-0.0451,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,25.6567,-0.2969,0.0408,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,25.6019,-0.3508,0.0400,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,23.5879,-2.2863,-0.0386,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,23.5960,-2.2782,-0.0386,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,23.5944,-2.2798,-0.0386,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,23.7423,-2.1319,-0.0386,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,23.7423,-2.1319,-0.0386,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,23.7423,-2.1319,-0.0386,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,23.7423,-2.1319,-0.0386,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,23.7423,-2.1319,-0.0386,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,23.7544,-2.1147,-0.0437,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,25.0940,-0.7889,-0.0298,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,23.2331,-2.6464,-0.0333,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,24.5548,-1.3192,-0.0387,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,28.9502,3.0676,-0.0302,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_ENMC,WFEC_ENMC_LA,29.4353,3.5528,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,23.7777,-2.1131,-0.0220,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,25.1144,-0.8297,0.0313,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,28.5730,2.6905,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,24.2345,-1.6369,-0.0413,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,24.2633,-1.6082,-0.0413,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,24.2633,-1.6082,-0.0413,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_OKGE,WFEC_OKGE_LA,25.0124,-0.9138,0.0135,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,25.7875,-0.1650,0.0397,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,24.1635,-1.7032,-0.0460,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,23.6374,-2.2351,-0.0403,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_WFEC,WFEC_LA,25.0029,-0.9102,0.0004,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,28.5730,2.6905,-0.0303,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,25.4503,-0.4501,-0.0124,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,25.1305,-0.7627,-0.0196,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,24.0592,-1.8449,-0.0087,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,24.0592,-1.8449,-0.0087,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,24.0479,-1.8561,-0.0087,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,24.0479,-1.8561,-0.0087,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,24.0590,-1.8450,-0.0087,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,24.0589,-1.8452,-0.0087,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,24.0589,-1.8452,-0.0087,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,25.1525,-0.7647,0.0045,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,24.1874,-1.7155,-0.0099,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,23.8702,-2.0237,-0.0189,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,23.8702,-2.0237,-0.0189,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,23.8702,-2.0237,-0.0189,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,24.3524,-1.5388,-0.0216,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,24.3524,-1.5388,-0.0216,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.GEEC.GT1,WRGORDUNG1_RA,24.0391,-1.8579,-0.0158,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.GEEC.GT2,WRGORDUNG2_RA,24.0391,-1.8579,-0.0158,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.GEEC.GT3,WRGORDUNGT3_RA,23.9561,-1.9408,-0.0158,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,24.1874,-1.7155,-0.0099,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,24.4446,-1.4641,-0.0040,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.HEC.GT1,WRHECGTUN32_RA,24.4080,-1.4910,-0.0137,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.HEC.GT2,WRHECGTUN33_RA,24.4226,-1.4764,-0.0137,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.HEC.GT3,WRHECGTUN34_RA,24.4282,-1.4708,-0.0137,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.HEC.GT4,WRHECGTUN35_RA,24.4296,-1.4694,-0.0137,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,24.4446,-1.4641,-0.0040,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,24.4160,-1.4750,-0.0217,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,24.1256,-1.7916,0.0045,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.JEC.1,WRJEFFUN10_RA,24.0813,-1.8238,-0.0076,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.JEC.2,WRJEFFUN11_RA,23.9609,-1.9443,-0.0075,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.JEC.3,WRJEFFUN12_RA,24.0769,-1.8284,-0.0075,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,23.8043,-2.0905,-0.0180,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,24.0612,-1.8347,-0.0169,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,24.0612,-1.8347,-0.0169,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.LEC.4,WRLECUN26_RA,24.2891,-1.6184,-0.0052,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.LEC.5,WRLECUN27_RA,24.4271,-1.4800,-0.0056,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MCPH.CT1,WRCMCPHUN37_RA,24.5947,-1.3054,-0.0127,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MCPH.CT2,WRCMCPHUN38_RA,24.5947,-1.3054,-0.0127,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MCPH.CT3,WRCMCPHUN48_RA,24.5899,-1.3101,-0.0127,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MCPH.CT4,WRCJOHNUN1_RA,24.6530,-1.2471,-0.0126,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,24.7623,-1.1392,-0.0113,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,24.7623,-1.1392,-0.0113,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,25.7191,-0.1778,-0.0158,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,25.4989,-0.4017,-0.0121,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,25.4989,-0.4017,-0.0121,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,24.8964,-1.0034,-0.0130,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,24.7623,-1.1392,-0.0113,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,24.6727,-1.2349,-0.0051,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,24.2256,-1.6767,-0.0104,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,24.0557,-1.8401,-0.0169,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,25.5953,-0.3584,0.0410,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,24.9579,-0.9416,-0.0132,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.READ.READ,WREMPECUNREADINGWF_RA,24.0589,-1.8452,-0.0087,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,23.2802,-2.6251,-0.0074,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,24.4446,-1.4641,-0.0040,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,24.1874,-1.7155,-0.0099,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,24.2197,-1.6775,-0.0156,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.THAYERLD,WR.THAYERLD_LA,25.3246,-0.6002,0.0121,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0102,WR.VOLT.0102_H,24.2220,-1.6751,-0.0156,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0106,V106_DDR,24.2149,-1.6831,-0.0147,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0139,WR.VOLT.0139_H,24.6002,-1.3088,-0.0037,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0141,WR.VOLT.0141_H,24.5723,-1.3293,-0.0111,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0146,WR.VOLT.0146_H,24.5389,-1.3688,-0.0050,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0147,WR.VOLT.0147_H,24.5389,-1.3688,-0.0050,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0148,WR.VOLT.0148_H,24.5011,-1.4075,-0.0042,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0153,WR.VOLT.0153_H,24.4187,-1.4799,-0.0141,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0157,V157_DDR,24.5139,-1.3937,-0.0051,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0158,V158_DDR,24.5389,-1.3688,-0.0050,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0159,WR.VOLT.0159_H,24.5389,-1.3688,-0.0050,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0165,WR.VOLT.0165_H,24.0725,-1.8260,-0.0143,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0173,V173_DDR,24.7007,-1.1992,-0.0128,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0174,V174_DDR,24.1830,-1.7157,-0.0141,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0184,V184_DDR,24.0337,-1.8647,-0.0144,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0185,WR.VOLT.0185_H,24.2062,-1.6911,-0.0154,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0186,V186_DDR,24.1562,-1.7410,-0.0156,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0187,WR.VOLT.0187_H,24.0946,-1.8033,-0.0149,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0188,WR.VOLT.0188_H,24.2330,-1.6644,-0.0153,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0189,WR.VOLT.0189_H,24.7770,-1.1212,-0.0145,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0190,WR.VOLT.0190_H,24.2104,-1.6932,-0.0091,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0191,WR.VOLT.0191_H,24.1437,-1.7603,-0.0088,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0192,WR.VOLT.0192_H,24.1437,-1.7603,-0.0088,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0196,WR.VOLT.0196_H,24.2104,-1.6932,-0.0091,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0245,V245_DDR,24.2098,-1.6876,-0.0154,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.VOLT.0248,V248_DDR,24.2149,-1.6831,-0.0147,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,23.8405,-2.0566,-0.0157,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,24.4977,-1.4090,-0.0061,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.WOLF,WRWOLFUN15_RA,23.1573,-2.7468,-0.0087,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,24.4160,-1.4750,-0.0217,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,24.7811,-1.1361,0.0045,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,23.8702,-2.0237,-0.0189,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,23.8702,-2.0237,-0.0189,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,23.8702,-2.0237,-0.0189,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,23.8702,-2.0237,-0.0189,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KPP_NITS,WR_KPP_NITS_LA,24.2130,-1.6896,-0.0101,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,24.5749,-1.3268,-0.0110,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,24.1588,-1.7396,-0.0143,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,24.1588,-1.7396,-0.0143,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,24.1588,-1.7396,-0.0143,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,24.1588,-1.7396,-0.0143,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,24.3953,-1.5082,-0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,24.3953,-1.5082,-0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,24.3953,-1.5082,-0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,24.3953,-1.5082,-0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,24.3953,-1.5082,-0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,24.3953,-1.5082,-0.0093,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,24.2829,-1.6140,-0.0159,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,24.2829,-1.6140,-0.0159,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,23.8900,-2.0070,-0.0158,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,23.8900,-2.0070,-0.0158,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_MIDW,WR_MIDW_LA,25.5209,-0.3776,-0.0142,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,25.3285,-0.5860,0.0018,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,24.6801,-1.2310,-0.0016,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,25.3937,-0.5037,-0.0154,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_SEG,WR_SEG_LA,24.8695,-1.0464,0.0031,25.9128\n03/31/2025 09:05:00,03/31/2025 14:05:00,WR_WR,WR_LA,24.4280,-1.4753,-0.0094,25.9127\n03/31/2025 09:05:00,03/31/2025 14:05:00,YAD,VACS,25.3720,-0.5539,0.0132,25.9127\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/US_SPP/RTBM-LMP-SL-202503310910.csv",
    "content": "Interval,GMTIntervalEnd,Settlement Location,Pnode,LMP,MLC,MCC,MEC\n03/31/2025 09:10:00,03/31/2025 14:10:00,AEC,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,AECC_CSWS,CSWS_AECC_LA,21.4545,-0.4698,-0.9392,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,AECC_ELKINS,CSWSELKINSUNELKINS_RA,21.6798,-0.3033,-0.8804,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,AECC_FITZHUGH,CSWSFITZHUGHPLT1,21.0084,-0.9418,-0.9133,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,AECC_FLTCREEK,CSWSFLINTCRKUN1_JOU_AECC_RA,21.5116,-0.5021,-0.8498,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,AECC_FULTON,CSWSFULTON_CUNFULT_RA,21.1294,-0.6746,-1.0594,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,AECC_HYDRO13,CSWSLD13UN1_RA,20.3857,-1.5486,-0.9291,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,AECC_JWTURK,CSWSTURK_PPUNTURK_AECC_RA,21.3683,-0.3537,-1.1415,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,AECI,AECI,21.5982,-0.6990,-0.5663,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,AEPM_CSWS,CSWS_LA,21.1830,-0.2958,-1.3846,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,ALTW,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,AMRN,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,ANTELOPE,SPSANTELOPEUNANT1_RA,29.2358,1.7010,4.6713,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,BBA,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,BCA,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,BEPM.ER01.DDR,ER01_DDR,21.9418,-1.2062,0.2846,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,BEPM_ER01,BEPM_ER01_LA,21.9418,-1.2062,0.2846,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,BEPM_RM_NPPD,NPPD_BEPM_RUSHMORE_LA,24.6673,1.3504,0.4535,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,BEPM_TS_NPPD,NPPD_BEPM_TRISTATE_LA,24.1699,0.3133,0.9932,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,BEPM_UM01,BEPM_UM01_LA,24.9120,1.9116,0.1369,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,BLKW,BLKW,30.2871,2.9925,4.4311,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,BLUECANYON1,WFECBLUCAN14UNUN1_BLUCAN14_RA,17.4380,-2.3753,-3.0501,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,BLUECANYON2,WFECBLUCAN14UNUN2_BLUCAN14_RA,17.4380,-2.3753,-3.0501,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,BLUECANYON5,WFECCHERRYRDUNBLUCAN5_WND_RA,16.9129,-2.4973,-3.4533,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,BLUECANYON6,WFECSLCKHILSUNBLUCAN6_WIND_RA,17.4697,-2.3436,-3.0501,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,BRAZ,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,BUBA,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,BUFFALO_DUNES_WIND,SPSFINNEY1UNBUFFDUNE_WIND_RA,25.0547,-0.8883,3.0796,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CANADIAN_HILLS_1,OKGECIMARRONUNCANADN1_WIND_RA,20.7186,-1.3598,-0.7850,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CANADIAN_HILLS_2,OKGECIMARRONUNCANADN2_WIND_RA,20.7186,-1.3598,-0.7850,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CANADIAN_HILLS_3,GRDACMRN_GRDLDCANADN3_WIND_RA,20.7186,-1.3598,-0.7850,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CANADIAN_HILLS_4,OKGECIMARRONUNCANADN4_WIND_RA,20.7186,-1.3598,-0.7850,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CANADIAN_HILLS_5,OKGECIMARRONUNCANADN5_WIND_RA,20.7186,-1.3598,-0.7850,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CANEY_RIVER_WINDPOWER,WRCAN_RIVRUNCANEY_WIND_RA,20.9047,-1.5893,-0.3694,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CASS_CO_1,OPPDCASSCNTYUN1_RA,22.3502,-0.6366,0.1234,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CASS_CO_2,OPPDCASSCNTYUN2_RA,22.3502,-0.6366,0.1234,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CLEC,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,COFFEYVILLE_7,GRDACOFFEYGRUN7_RA,21.4486,-0.5461,-0.8688,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,COWP,COWP_LA,21.6538,-0.6249,-0.5847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,COWP_GEN1,WRW_PLAINGUNCOWP_GEN1_RA,21.6538,-0.6249,-0.5847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,COWP_GEN2,WRW_PLAINGUNCOWP_GEN2_RA,21.6538,-0.6249,-0.5847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CPLE,VACS,21.6836,-0.6013,-0.5785,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CPLW,VACS,21.6836,-0.6013,-0.5785,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CROSSROADS1,MPSCRSRD_EXUNCROSSROADS1_RA,21.5408,-0.6762,-0.6465,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CROSSROADS2,MPSCRSRD_EXUNCROSSROADS2_RA,21.5408,-0.6762,-0.6465,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CROSSROADS3,MPSCRSRD_EXUNCROSSROADS3_RA,21.5408,-0.6762,-0.6465,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CROSSROADS4,MPSCRSRD_EXUNCROSSROADS4_RA,21.5408,-0.6762,-0.6465,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CRTH_SPA,WRCRTH_SPA_LA,21.3168,-0.8872,-0.6594,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWARSENALHILL5,CSWSARSENALUN5_RA,22.0378,0.2215,-1.0471,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWCOMANCHE1,CSWSCOMANCHEPLT1,19.0432,-1.4919,-2.3283,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWETTURK,CSWSTURK_PPUNCSWETTURK_RA,21.3683,-0.3537,-1.1415,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWFLINTCREEK1,CSWSFLINTCRKUN1_RA,21.5116,-0.5021,-0.8498,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWJLSTALL,CSWSSTALL_PPPLT1,22.0317,0.2165,-1.0483,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWKNOXLEE5,CSWSKNOXLEEUN5_RA,21.9928,0.1994,-1.0701,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWLIEBERMAN3,CSWSLIEBERMUN3_RA,21.9760,0.1713,-1.0587,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWLIEBERMAN4,CSWSLIEBERMUN4_RA,21.9760,0.1713,-1.0587,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWMATTISON1,CSWSMATTISONUN1_RA,21.2492,-0.7235,-0.8908,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWMATTISON2,CSWSMATTISONUN2_RA,21.2492,-0.7235,-0.8908,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWMATTISON3,CSWSMATTISONUN3_RA,21.2526,-0.7200,-0.8908,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWMATTISON4,CSWSMATTISONUN4_RA,21.2526,-0.7200,-0.8908,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWMSTURK,CSWSTURK_PPUNCSWMSTURK_RA,21.3683,-0.3537,-1.1415,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWNARROWS1,CSWSNARROWSUN1_RA,21.6147,-0.0868,-1.1619,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWNORTHEASTERN1,CSWSNE_GASPLT1,21.0139,-0.8067,-1.0429,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWNORTHEASTERN2,CSWSNE_GASUN2_RA,20.8796,-0.9410,-1.0429,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWNORTHEASTERN3,CSWSNE_COALUN3_RA,21.1931,-0.7139,-0.9565,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWRIVERSIDE1,CSWSRIVRSIDEUN1_RA,21.0487,-0.7004,-1.1143,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWRIVERSIDE2,CSWSRIVRSIDEUN2_RA,20.9525,-0.7967,-1.1143,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWRIVERSIDE3,CSWSRIVRSIDEUN3_RA,20.9475,-0.8017,-1.1143,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWRIVERSIDE4,CSWSRIVRSIDEUN4_RA,20.9475,-0.8017,-1.1143,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.7CBY.7CBYWIND,CSWSMATOUN7COWBOY_RA,18.0917,-1.6253,-3.1465,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.AECC.DRIFTSAND,CSWSDRFTSND4UNDRIFTSAND_WIND_RA,19.7256,-1.0222,-2.1156,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.AECC.WILDHORSE,CSWSTUSKAHOMUNWILDHORSE_RA,20.8201,-0.8035,-1.2398,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.EKCW.EKCW,CSWSELK_TAPUNELKCTY_WIND_RA,17.6133,-1.4348,-3.8153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.ELK2.ELKCITY2,CSWSROARKUNELKCTY2_FPLP_RA,17.5518,-1.4964,-3.8153,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.FPLP.RSES.MSR,CSWSTERRY_RDUNRS_ENERGY_MSR_RA,19.4810,-1.4224,-1.9600,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.GRID.CDL1,CDL1_DDR,21.0374,-0.6088,-1.2173,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.HCPP.RBPW,CSWSLEONARDUNREDBED_WIND_RA,19.7676,-1.2931,-1.8028,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.KCSP.KIOWACTT,CSWSGREATPLAUNKIOWACT_SOLAR_RA,15.3468,-2.8243,-4.6923,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.NUEN.CDL1,CSWS.NUEN.CDL1_H,21.0374,-0.6088,-1.2173,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.NUEN.CSI1,CSI1_DDR,21.6489,-0.3247,-0.8898,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.NUEN.CSI2,CSI2_DDR,21.6570,-0.3166,-0.8898,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.NUEN.CSI3,NCSI3_DDR,21.3918,-0.5886,-0.8831,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.NUEN.GAZA,GAZA_DDR,21.0374,-0.6088,-1.2173,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.NUEN.MDT1,CSWS.NUEN.MDT1_H,21.3387,-0.1573,-1.3674,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.NUEN.T201,NT201_DDR,21.2648,-0.5391,-1.0595,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.OKUDC.DIVERSION,CSWS.OKUDC.DIVERSION_H,19.1773,-1.5742,-2.1119,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.OKUDC.DVWIND,CSWSOKLAUNIOUNDIVERSION_RA,19.1773,-1.5742,-2.1119,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.OMPA.TURK,CSWSTURK_PPUNTURK_OMPA_RA,21.3683,-0.3537,-1.1415,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.RRSL.ROCKNRSLR,CSWSHOSSTONUNROCKINGR_SOLAR_RA,22.2247,0.4548,-1.0936,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.RSPA.RUSHSPRWNDA,CSWSTERRY_RDUNRUSH_SPRINGS_A_RA,19.4810,-1.4224,-1.9600,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.RSPB.RUSHSPRWNDB,CSWSTERRY_RDUNRUSH_SPRINGS_B_RA,19.4810,-1.4224,-1.9600,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.TNSK.CADO,CSWSTREASUREUNCADDO_WIND_RA,19.1823,-1.5735,-2.1076,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.TNSK.ELKCITY2,CSWSROARKUNELKCTY2_WIND_RA,17.5518,-1.4964,-3.8153,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.TNSK.GATEWAY,CSWSGATEWAY2PLT1,21.7954,-0.0133,-1.0547,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.TNSK.GREENCOUNTRY,CSWSJENKSUNCGCC1_RA,21.0137,-0.7459,-1.1039,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.TNSK.GREENCOUNTRY2,CSWSJENKSUNCGCC2_RA,21.0137,-0.7459,-1.1039,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.TNSK.GREENCOUNTRY3,CSWSJENKSUNCGCC3_RA,20.6802,-1.0793,-1.1039,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.TNSK.KIAPB1,CSWSKIOWAPLT,20.5805,-1.0599,-1.2230,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.TNSK.KIAPB2,CSWSKIOWAPLT2,20.7260,-0.9144,-1.2230,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0004,CSWS.VOLT.0004_H,21.9692,0.1860,-1.0802,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0044,CSWSSAND_SPGUNSAND_DDR_GEN_RA,21.1401,-0.5899,-1.1335,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0050,CSWSHARRISONUNHRSN_DDR_GEN_RA,22.0275,0.2399,-1.0758,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0051,CSWS.VOLT.0051_H,23.0011,1.2315,-1.0938,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0053,CSWS.VOLT.0053_H,21.0153,-0.5921,-1.2560,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0056,PRYORCRK_DDR,21.6570,-0.3166,-0.8898,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0057,OKMU_DDR,21.2010,-0.4574,-1.2051,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0060,LEHIGH_DDR,21.1694,-0.2786,-1.4154,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0086,WARRENM_DDR,21.1510,-0.6021,-1.1103,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0092,CSWS.VOLT.0092_H,22.2990,0.5407,-1.1051,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0114,CSWS.VOLT.0114_H,21.3404,-0.4724,-1.0506,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0121,V121_DDR,21.9692,0.1860,-1.0802,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0122,V122_DDR,21.3126,-0.5086,-1.0422,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0124,V124_DDR,21.0543,-0.6081,-1.2010,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0135,V135_DDR,21.2374,-0.5237,-1.1024,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0144,V144_DDR,19.7938,-0.9891,-2.0805,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0145,V145_DDR,19.6926,-1.1113,-2.0595,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0162,CSWS.VOLT.0162_H,21.9960,0.2141,-1.0815,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0164,CSWS.VOLT.0164_H,21.4359,-0.2752,-1.1523,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0175,V175_DDR,21.3918,-0.5886,-0.8831,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0178,CSWS.VOLT.0178_H,21.4359,-0.2752,-1.1523,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0193,CSWS.VOLT.0193_H,21.5380,-0.1763,-1.1491,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0201,CSWS.VOLT.0201_H,21.2374,-0.5237,-1.1024,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0202,CSWS.VOLT.0202_H,21.2399,-0.5333,-1.0903,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0203,CSWS.VOLT.0203_H,21.2151,-0.5888,-1.0595,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0204,CSWS.VOLT.0204_H,21.1329,-0.6863,-1.0442,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0205,CSWS.VOLT.0205_H,21.0726,-0.6755,-1.1153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0206,CSWS.VOLT.0206_H,21.2399,-0.5333,-1.0903,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0211,V211_DDR,22.2186,0.4226,-1.0674,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0212,CSWS.VOLT.0212_H,21.3583,-0.4597,-1.0454,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0213,V213_DDR,21.1776,-0.5837,-1.1022,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0215,V215_DDR,21.3161,-0.5029,-1.0444,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0217,V217_DDR,21.3413,-0.4768,-1.0454,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0218,V218_DDR,21.1412,-0.6779,-1.0444,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0228,V228_DDR,21.1399,-0.5900,-1.1336,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0232,V232_DDR,21.2051,-0.5460,-1.1123,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0233,V233_DDR,21.2483,-0.5199,-1.0952,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0240,V240_DDR,21.1666,-0.6021,-1.0947,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0244,V244_DDR,21.2399,-0.5333,-1.0903,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0246,MDT1_DDR,21.3387,-0.1573,-1.3674,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0249,V249_DDR,21.2202,-0.5407,-1.1026,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0250,V250_DDR,19.1575,-1.4552,-2.2507,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0251,V251_DDR,21.1080,-0.6461,-1.1093,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.VOLT.0252,V252_DDR,21.1329,-0.6863,-1.0442,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.WRWE.EAST,CSWSTREASUREUNWHITROCKE_WIND_RA,19.1732,-1.5827,-2.1076,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.WRWW.WEST,CSWSTONKAWAUNWHITROCKW_WIND_RA,18.0116,-1.9416,-2.9103,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS.WTHW.WTHW,CSWSWFRDGUNUN1_WFRDG_RA,14.7225,-1.6979,-6.4430,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWSEASTMAN,CSWSEASTMANUNEASTMAN_RA,21.8585,0.0695,-1.0745,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWSLEEPINGBEAR,WFECSLP_BEARUNWINDFARM_RA,-26.7544,-1.3004,-48.3174,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWSOUTHWESTERN1,CSWSSW_STAUN1_RA,19.6197,-1.1842,-2.0595,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWSOUTHWESTERN2,CSWSSW_STAUN2_RA,19.6197,-1.1842,-2.0595,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWSOUTHWESTERN3,CSWSSW_STAUN3_RA,19.6030,-1.2009,-2.0595,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWSOUTHWESTERN4,CSWSSW_STAUN4_RA,17.9642,-1.8580,-3.0413,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWSOUTHWESTERN5,CSWSSW_STAUN5_RA,17.9642,-1.8580,-3.0413,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWSWTURK,CSWSTURK_PPUNCSWSWTURK_RA,21.3683,-0.3537,-1.1415,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWS_ETEC_LOAD,CSWS_ETEC_LA,22.0590,0.1899,-0.9943,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWTULSA2,CSWSTULSA_PSUN2_RA,21.1864,-0.5647,-1.1123,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWTULSA4,CSWSTULSA_PSUN4_RA,21.1532,-0.5979,-1.1123,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWWELEETKA4,CSWSWELEETKAUN4_RA,21.1303,-0.4895,-1.2437,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWWELEETKA5,CSWSWELEETKAUN5_RA,21.1303,-0.4895,-1.2437,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWWELSH1,CSWSWELSHUN1_RA,21.5294,-0.2121,-1.1220,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWWELSH3,CSWSWELSHUN3_RA,21.5294,-0.2121,-1.1220,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWWILKES1,CSWSWILKESUN1_RA,21.6756,-0.0832,-1.1046,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWWILKES2,CSWSWILKESUN2_RA,21.6756,-0.0832,-1.1046,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,CSWWILKES3,CSWSWILKESUN3_RA,21.6616,-0.1044,-1.0975,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,DEMPSEY_RIDGE_WIND,CSWSDEMPSRDGUNDEMPSEY_WIND_RA,17.6189,-1.4292,-3.8153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,DENL,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,DERS,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,DOE,DOE,21.7620,-0.6271,-0.4743,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,DOGWOOD,MPSPHILLUNDOGWOOD_RA,21.2205,-1.5332,-0.1098,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,DPC,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,DUK,VACS,21.6836,-0.6013,-0.5785,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDDY,EDDY,31.0510,3.6540,4.5336,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE.KINGSPOINT,EDELAR3821UNKINGSPNT_RA,21.0695,-1.1299,-0.6640,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE.NEOSHORDGE,WRNEORDGUNNEOSHRDG_RA,21.0948,-1.2270,-0.5417,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE.NORTHFORK,EDEASB3491UNNORTHFRK_RA,21.0000,-1.2302,-0.6332,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE.SLCC,EDESTL4391_PLT,20.4544,-1.7144,-0.6946,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE.VOLT.0234,EDE.VOLT.0234_H,20.8061,-1.3609,-0.6964,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDEP_SWMPEPHUB,EDEP_SWMPEP_H,20.8948,-1.4938,-0.4749,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_EC_01,EDELAR3821UN1_RA,21.0695,-1.1299,-0.6640,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_EC_02,EDELAR3821UN2_RA,21.0474,-1.1520,-0.6640,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_EC_03,EDELAR3821UN3_RA,21.0695,-1.1299,-0.6640,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_EC_04,EDELAR3821UN4_RA,21.0695,-1.1299,-0.6640,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_EDE,EDE_LA,21.5071,-0.6813,-0.6751,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_ERW,EDEERWFUNG1_RA,20.8870,-1.6307,-0.3457,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_MWW,EDEMWWF_EDEUNWINDFARM_RA,21.7129,-1.4982,0.3476,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_OZD_5,EDEOZRK_BUN5_RA,21.7251,-0.4772,-0.6611,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_OZD_6,EDEOZRK_BUN6_RA,21.7251,-0.4772,-0.6611,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_OZD_7,EDEOZRK_BUN7_RA,21.7251,-0.4772,-0.6611,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_OZD_8,EDEOZRK_BUN8_RA,21.7251,-0.4772,-0.6611,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_PLUMPOINT,EDEPLUM_EDEUNPLUMPT_EDE_RA,21.6277,-0.6405,-0.5953,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_RIV_10,EDERIV1671UN10_RA,20.8674,-1.2984,-0.6976,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_RIV_11,EDERIV1671UN11_RA,20.8674,-1.2984,-0.6976,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_RIV_12,EDERIV453UN12_PLT,20.8674,-1.2984,-0.6976,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_SL_01,EDESTL4391UN1_RA,20.3396,-1.8292,-0.6946,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EDE_SWMP,EDE_SWMP_LA,21.7207,-0.4839,-0.6589,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,EEI,EEI,21.7635,-0.6271,-0.4728,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,EES,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,EKC.SFEC.SFEC,WRBURNUNEXPEDITION_WND_RA,21.4325,-1.6539,0.2229,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,ERCOTE,ERCOTE,21.5294,-0.2121,-1.1220,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,ERCOTN,ERCOTN,19.2197,-1.5318,-2.1119,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,FLAT_WATER,OPPDSUB1399UNFLATWTR_WIND_RA,21.9489,-1.0471,0.1325,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,FMPP,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,FPC,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,FPL,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,FREM_50T,OPPDFREM_GUN1_RA,22.6975,-0.3302,0.1643,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,FREM_6,OPPDFREM_AUN6_RA,22.6646,-0.3633,0.1644,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,FREM_7,OPPDFREM_AUN7_RA,22.6646,-0.3633,0.1644,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,FREM_8,OPPDFREM_AUN8_RA,22.5737,-0.4541,0.1644,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,FREM_LOAD,FREM_LOAD_LA,22.6742,-0.3536,0.1644,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,FRONTIER,WRGETTUNFRONTIER_RA,21.4724,-1.2636,-0.1275,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GATEWAY_LOAD,CSWS_TENASKA_LA,21.7954,-0.0133,-1.0547,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GOODWELL_WIND,SPSHITCHUNGOODWELL_WIND_RA,27.1082,-0.5252,4.7699,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.BRECK,OKGEBRECKNR4UNBRECK_WIND_RA,11.6759,-1.6323,-9.5553,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.COFF10,GRDACOFFEYGRUNCOFF10_RA,21.4486,-0.5461,-0.8688,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.COFF8,GRDACOFFEYGRUNCOFF8_RA,21.4486,-0.5461,-0.8688,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.COFF9,GRDACOFFEYGRUNCOFF9_RA,21.4486,-0.5461,-0.8688,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.GREC2,GRDAGRDA17UN2_RA,21.2982,-0.6761,-0.8892,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.GREC2AUX,GRDAGRDA17LDUNIT_2_AUX_LA,21.2982,-0.6761,-0.8892,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.GREC3,GRDAGREC3UNGREC3_RA,21.2900,-0.6816,-0.8918,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.GREC3AUX,GRDAGREC3LDGREC3_AUX_LA,21.2900,-0.6816,-0.8918,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.KAY,OKGEKAYWIND7UNKAY_WIND_RA,20.0735,-1.8482,-0.9417,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.SEC1,GRDAFERGUS2UNSTILLWATER_EC1_RA,19.5409,-0.9645,-2.3581,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.SEC2,GRDAFERGUS2UNSTILLWATER_EC2_RA,19.5409,-0.9645,-2.3581,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.SEC3,GRDAFERGUS2UNSTILLWATER_EC3_RA,19.5409,-0.9645,-2.3581,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.VOLT.0130,V130_DDR,21.5485,-0.3906,-0.9243,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA.VOLT.0237,V237_DDR,21.3737,-0.5611,-0.9286,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDAHUB2,GRDAHUB2_H,20.2861,-0.9985,-1.5788,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDAHUB3,GRDAHUB3_H,20.1097,-1.0660,-1.6877,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA_GRDA,GRDA_LA,21.2578,-0.5843,-1.0213,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA_HUB,GRDA_H,20.7775,-0.9894,-1.0965,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRDA_HUBSA,GRDASA_H,21.1294,-0.7503,-0.9838,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GRE,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GSEC_GL_CSWS,CSWS_GREEN_LIGHT_LA,23.2121,0.8328,-0.4842,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GSEC_SPS,SPS_GSEC_LA,28.9068,1.8855,4.1578,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GSPR2014HUB,GSPR2014HUB_H,27.5272,1.3120,3.3518,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,GSPR2015HUB,GSPR2015HUB_H,27.4391,1.2426,3.3330,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,GSPWR,SPSGSPWRUNGSPWR_WIND_RA,27.4275,0.7326,3.8314,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,HARRISON,CSWSLEBROCKPLT1,21.8083,0.0202,-1.0753,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,HAST_TNSK_HUB,HAST_TNSK_H,23.7865,0.3620,0.5610,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,HQST,PJM,21.9883,-0.5691,-0.3060,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,HST,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,INDNSUB_H_5,INDNSUB_HUN5_RA,22.0557,-0.7288,-0.0789,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,INDNSUB_H_6,INDNSUB_HUN6_RA,22.0557,-0.7288,-0.0789,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,INDNSUB_I_3,INDNSUBIUN3_RA,22.0349,-0.7492,-0.0794,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,INDNSUB_I_4,INDNSUBIUN4_RA,22.0349,-0.7492,-0.0794,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,INDNSUB_J_1,INDNSUBJUN1_RA,22.0668,-0.7162,-0.0804,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,INDNSUB_J_2,INDNSUBJUN2_RA,22.0668,-0.7162,-0.0804,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,INDN_INDN,INDN_LA,22.0437,-0.7400,-0.0797,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,INDN_MWE_SMKY2,INDNIN_SMKHLUNWINDFARM_RA,22.4819,-1.0172,0.6356,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,ISNE,PJM,21.9883,-0.5691,-0.3060,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,JEA,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,JONES_STREET_1,OPPDJONES_STUN1_RA,22.5045,-0.4776,0.1187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,JONES_STREET_2,OPPDJONES_STUN2_RA,22.5045,-0.4776,0.1187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KACYBOWERSOCK,KACY6TH_KACYUNBOWERSOCK_RA,21.5872,-1.3108,0.0345,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KACYCT4,KACYNEARMANUNCT4_RA,21.6477,-1.1625,-0.0532,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KACYLFG,KACYLANDFILLUNLF_GAS_RA,21.1736,-1.1298,-0.5600,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KACYNEARMANUN1,KACYNEARMANUN1_RA,21.6477,-1.1625,-0.0532,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KACYQUIND1UNGT2,KACYQUIND1UNCT2_RA,21.7236,-1.0859,-0.0540,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KACYQUIND1UNGT3,KACYQUIND1UNCT3_RA,21.6983,-1.1114,-0.0537,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KACY_KACY,KACY_LA,21.7528,-1.0564,-0.0542,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.HAW10,KCPLLEVEEUNHAW_SOLAR_RA,21.7344,-1.0667,-0.0623,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.MEUC.HIG4,KCPLC_HIGGNSUNHIG4_RA,22.3241,-0.3755,-0.1639,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.PRQUEEN,KCPLDAKOTAUNPRARQUEEN_KCPL_RA,20.8381,-1.6376,-0.3877,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.SLATECREEK,WRCRSWUNSLATECREEKWIND_RA,19.4205,-1.9367,-1.5062,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.VOLT.0222,V222_DDR,21.7854,-1.0923,0.0142,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.VOLT.0223,V223_DDR,21.3385,-1.4179,-0.1071,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.VOLT.0241,V241_DDR,22.0722,-0.5572,-0.2340,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.VOLT.0243,V243_DDR,21.3456,-0.7138,-0.8040,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.VOLT.0247,V247_DDR,21.4201,-1.3401,-0.1033,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.VOLT.0253,V253_DDR,21.7460,-1.0546,-0.0628,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL.WAVERLYWND,KCPLWAVERLY7UNWAVERLYWIND_RA,20.3622,-2.3322,-0.1690,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLBULLCRK5UNWGR1,KCPLBULLCRK5UNUNIT1_RA,21.2797,-1.5007,-0.0831,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLBULLCRK5UNWGR2,KCPLBULLCRK5UNUNIT2_RA,21.2797,-1.5007,-0.0831,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLBULLCRK5UNWGR3,KCPLBULLCRK5UNUNIT3_RA,21.2797,-1.5007,-0.0831,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLBULLCRK5UNWGR4,KCPLBULLCRK5UNUNIT4_RA,21.2795,-1.5009,-0.0831,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHAWTHORN6,KCPLHAWTHORNUNHAW6_RA,21.7346,-1.0664,-0.0624,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHAWTHORNUNHAW5,KCPLHAWTHORNUNHAW5_RA,21.7346,-1.0664,-0.0624,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHUB,KCPLHUB_H,21.1899,-1.7097,0.0362,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHUB17,KCPLHUB17_H,21.2640,-1.6998,0.1003,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHUB18,KCPLHUB18_H,21.2087,-1.7039,0.0492,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHUB19,KCPLHUB19_H,21.2668,-1.6557,0.0590,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHUB20,KCPLHUB20_H,21.2623,-1.6957,0.0945,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHUB21,KCPLHUB21_H,21.4301,-1.6591,0.2257,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHUB22,KCPLHUB22_H,21.3694,-1.6843,0.1902,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHUB23,KCPLHUB23_H,21.3305,-1.7003,0.1674,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLHUB24,KCPLHUB24_H,21.3539,-1.7076,0.1981,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLIATANUNIAT1,KCPLIATANUNIAT1_RA,21.5327,-1.3384,0.0076,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLIATANUNIAT2,KCPLIATANUNIAT2_RA,21.5327,-1.3384,0.0076,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLLACYGNEUNLAC1,KCPLLACYGNEUNLAC1_RA,20.7759,-1.9039,-0.1837,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLLACYGNEUNLAC2,KCPLLACYGNEUNLAC2_RA,20.7759,-1.9039,-0.1837,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLLEVEEUNHAW7,KCPLLEVEEUNHAW7_RA,21.7462,-1.0550,-0.0623,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLLEVEEUNHAW8,KCPLLEVEEUNHAW8_RA,21.7344,-1.0667,-0.0623,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLNRTHEASTUNNE11,KCPLNRTHEASTUNNE11_RA,21.7857,-1.0171,-0.0606,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLNRTHEASTUNNE12,KCPLNRTHEASTUNNE12_RA,21.7857,-1.0171,-0.0606,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLNRTHEASTUNNE13,KCPLNRTHEASTUNNE13_RA,21.7857,-1.0172,-0.0606,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLNRTHEASTUNNE14,KCPLNRTHEASTUNNE14_RA,21.7857,-1.0172,-0.0606,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLNRTHEASTUNNE15,KCPLNRTHEASTUNNE15_RA,21.7857,-1.0172,-0.0606,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLNRTHEASTUNNE16,KCPLNRTHEASTUNNE16_RA,21.7857,-1.0172,-0.0606,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLNRTHEASTUNNE17,KCPLNRTHEASTUNNE17_RA,21.7857,-1.0172,-0.0606,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLNRTHEASTUNNE18,KCPLNRTHEASTUNNE18_RA,21.7857,-1.0172,-0.0606,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPLPAOLAUNOSA1,KCPLPAOLAUNUN1_OSAWACT1_RA,21.1544,-1.5294,-0.1797,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL_GMOC_HUB,KCPLGMOCHUB_H,21.6849,-1.0951,-0.0834,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KCPL_KCPL,KCPL_LA,21.6571,-1.1283,-0.0781,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KENN,KENN_LA,21.6355,-0.6489,-0.5790,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KEP2_SECI,KEP2_SECI_LA,26.6109,0.0346,3.7128,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KERR_1,GRDAKERR_HYDUN1_RA,21.3594,-0.5852,-0.9189,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KERR_2,GRDAKERR_HYDUN2_RA,21.3789,-0.5701,-0.9144,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KERR_3,GRDAKERR_HYDUN3_RA,21.3789,-0.5701,-0.9144,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KERR_4,GRDAKERR_HYDUN4_RA,21.3594,-0.5852,-0.9189,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP1_BALD7,KCPLW_GARDNRUNBALD7_RA,21.2794,-1.5010,-0.0831,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP1_BALD8,KCPLW_GARDNRUNBALD8_RA,21.2794,-1.5010,-0.0831,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP1_GARD1,KCPLC_GARDNRUNGARD1_RA,21.4004,-1.3831,-0.0799,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP1_GARD2,KCPLC_GARDNRUNGARD2_RA,21.4004,-1.3831,-0.0799,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP1_KCPL,KMEA_KCPL_LA,21.2720,-1.4833,-0.1082,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP1_OTTA6,KCPLS_OTTAWAUNOTTA6_RA,21.2916,-1.4335,-0.1384,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP1_OTTA7,KCPLS_OTTAWAUNOTTA7_RA,21.2916,-1.4335,-0.1384,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP2_GARC1,SECIMORRIS3UNKMEA_GARC1_RA,25.1309,-0.7992,3.0667,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP2_GARC2,SECIMORRIS3UNKMEA_GARC2_RA,25.1309,-0.7992,3.0667,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP2_GARC3,SECIMORRIS3UNKMEA_GARC3_RA,25.1309,-0.7992,3.0667,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP2_RUSS1,SECIRUSSEL3UNKMEA_RUSS1_RA,23.4307,-0.4153,0.9826,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP2_RUSS2,SECIRUSSEL3UNKMEA_RUSS2_RA,23.4307,-0.4153,0.9826,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP2_SECI,KMEA_EMP2_SECI_LA,25.1982,-0.7829,3.1177,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP2_WPEK,KMEA_EMP2_WPEK_LA,23.4601,-0.4813,1.0780,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP3_CHAP12,WRAECUNCHAP12_RA,21.6851,-1.5023,0.3239,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP3_GIRA6,WRCGIRAUNGIRA6_RA,21.1335,-1.1314,-0.5986,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP3_GIRA7,WRCGIRAUNGIRA7_RA,21.1335,-1.1314,-0.5986,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP3_HOLT12,WRCIRVUNHOLT12_RA,21.5778,-1.3821,0.0965,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP3_HOLT13,WRCIRVUNHOLT13_RA,21.5778,-1.3821,0.0965,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP3_HOLT8,WRCIRVUNHOLT8_RA,21.5778,-1.3821,0.0965,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP3_JETM8,WRJETMORUNKMEA_EMP3_JETM_RA,24.1601,-0.1503,1.4470,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP3_STER3,WRLYONUNSTER3_RA,22.5856,-0.8862,0.6084,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EMP3_WR,KMEA_EMP3_WR_LA,21.6334,-1.1468,-0.0833,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,KMEA_EUDORA,KMEA_EUDORA_LA,21.6606,-1.2178,0.0149,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,LAFA,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,LAM345,LAM345,25.0547,-0.8883,3.0796,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,LEPA,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_JSTREET,LES8_NUNJ_STREET_RA,22.5477,-0.5152,0.1995,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_LES,LES_LA,22.5164,-0.5448,0.1978,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_LFG_1,LES84_BLUFUNTBGS_LFG_G1_RA,22.3624,-0.6921,0.1910,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_ROKEBY_1,LESROKEBYUN1_RA,22.4332,-0.6325,0.2022,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_ROKEBY_2,LESROKEBYUN2_RA,22.4641,-0.6015,0.2022,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_ROKEBY_3,LESROKEBYUN3_RA,22.4641,-0.6015,0.2022,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_TBGS_CC1,LES84_BLUFPLT1,22.3710,-0.6834,0.1910,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_TBGS_CT4,LES84_BLUFUNSALT_VALLEY_4_RA,22.3624,-0.6921,0.1910,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_WAVERLY,LES_WAVERLY_H,22.4223,-0.6315,0.1903,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_WSEC_3,LESWLTRSCTTUN3_RA,22.2833,-0.6846,0.1044,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,LES_WSEC_4,LESWLTRSCTTUN4_RA,22.2844,-0.6835,0.1044,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,LGEE,LGEE,21.8860,-0.5966,-0.3809,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MALDEN,MALDEN_LA,21.6491,-0.6485,-0.5659,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MCWEST,MCWEST,23.4157,0.3502,0.2021,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MDU,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MEANACJ_NPPD,NPPD_MEAN_ACJ_LA,24.1429,0.4384,0.8410,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MEAN_FCU_OPPD,OPPD_MEAN_FCU_LA,22.5694,-0.4252,0.1312,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MEAN_NCU_OPPD,OPPD_MEAN_NCU_LA,23.6663,0.6631,0.1397,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MEAN_NPPD,NPPD_MEAN_LA,23.8576,0.3508,0.6433,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MEC,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MHEB,MHEB,23.4161,0.5263,0.0263,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MIDW.INV.BKEYE,WRPOSTROCKUNMIDW_INV_BKEYE_RA,23.4648,-0.3793,0.9806,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MIDW.KACY.ALEX,WRWALCREEKUNALEXANDER_KACY_RA,24.0456,-0.3207,1.5028,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MIDW.KMEA.BKEYE,WRPOSTROCKUNMIDW_KMEA_BKYE_RA,23.4648,-0.3793,0.9806,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MIDW.LES.BKEYE,WRPOSTROCKUNMIDW_LES_BKEYE_RA,23.4648,-0.3793,0.9806,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MIDW.NJAL.ALEX,WRWALCREEKUNALEXANDER_WIND_RA,24.0456,-0.3207,1.5028,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MINCOIII,OKGEMINCOUNMINCO_WIND3_RA,20.0228,-1.4559,-1.3847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MISO,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKECCIM_UN1,SECICIM-PL1UN1_RA,27.0222,0.1440,4.0147,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKECCIM_UN2,SECICIM-PL1UN2_RA,27.0222,0.1440,4.0147,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKECCLIFTON_UN1,SECICLIFTO1UN1_RA,22.2305,-0.9934,0.3605,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKECJUDLR_UN4,SECIJUD-LR1UN1_RA,24.3560,-0.7607,2.2532,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKECMULGRN_UN3,SECIMULGRE2UN1_RA,23.5488,-0.6053,1.2906,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKECSHOOTSTAR,SECISHOOTSTRUNSHOOTSTR_WIND_RA,23.8426,-1.1053,2.0844,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKEC_KPP,SECI_MKEC_KPP_LA,23.5890,-0.8835,1.6090,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKEC_KPP_GBURG,SECIGRNBUR1UNGREENWIND_RA,23.9086,-0.9986,2.0437,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKEC_KP_KINGIC4,SECIPRATT1UNKPP_KINGIC4_RA,23.6053,-0.7712,1.5131,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKEC_KP_KINGIC6,SECIPRATT1UNKPP_KINGIC6_RA,23.6053,-0.7712,1.5131,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKEC_KP_KINGIC7,SECIPRATT1UNKPP_KINGIC7_RA,23.6053,-0.7712,1.5131,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKEC_KP_KINGIC8,SECIPRATT1UNKPP_KINGIC8_RA,23.6053,-0.7712,1.5131,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MKEC_KP_KINGIC9,SECIPRATT1UNKPP_KINGIC9_RA,23.6053,-0.7712,1.5131,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MO.AE.CHIL2.MP,WRCHILL_WRUN2_MEUC_RA,21.7368,-0.9290,-0.1977,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MO.AM.FRED1.MP,WRFRED_WRUN1_RA,21.7654,-0.6611,-0.4370,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MO.AM.FRED2.MP,WRFRED_WRUN2_RA,21.7654,-0.6611,-0.4370,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MO.AM.LADD.MP,WRMEXIC_WRUN1_RA,21.9043,-0.6656,-0.2935,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MO.KC.MARS6.MP,KCPLNORTH5UN6_RA,22.2320,-0.4056,-0.2258,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MOWR,AECI,21.5982,-0.6990,-0.5663,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MOWR_MOPEPAECI,MOWR_MOPEPAECI_LA,21.7709,-0.7843,-0.3082,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MOWR_MOPEPAMMO,MOWR_MOPEPAMMO_LA,21.7674,-0.6557,-0.4403,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPS.AMUE.OUTLAW,MPSOUTLAWUNOUTLAW_WIND_RA,21.5959,-1.3215,0.0540,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPS.OSBORN,MPSOSBORNWFUNOSBORN_MPS_RA,21.6011,-1.2536,-0.0087,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPS.PRATT,WRPRATT_GUNPRATT_WF_MPS_RA,21.8206,-1.6045,0.5617,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPS.ROCKCREEK,MPSROCKCK7UNMPS_ROCKCREEK_RA,21.6076,-1.3098,0.0540,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSGRNWD1UN1,MPSGRNWD1UN1_RA,21.2790,-1.4782,-0.1063,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSGRNWD1UN2,MPSGRNWD1UN2_RA,21.2790,-1.4782,-0.1063,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSGRNWD1UN3,MPSGRNWD1UN3_RA,21.2265,-1.5306,-0.1063,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSGRNWD1UN4,MPSGRNWD1UN4_RA,21.2265,-1.5306,-0.1063,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSLAKE_RDUN1,MPSLAKE_RDUN1_RA,21.7854,-1.0923,0.0142,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSLAKE_RDUN2,MPSLAKE_RDUN2_RA,21.7854,-1.0923,0.0142,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSLAKE_RDUN3,MPSLAKE_RDUN3_RA,21.7854,-1.0923,0.0142,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSLAKE_RDUN4,MPSLAKE_RDUN4_RA,21.7493,-1.1284,0.0142,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSLAKE_RDUN5,MPSLAKE_RDUN5_RA,21.7854,-1.0923,0.0142,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSLAKE_RDUN6,MPSLAKE_RDUN6_RA,21.7854,-1.0923,0.0142,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSLAKE_RDUN7,MPSLAKE_RDUN7_RA,21.7854,-1.0923,0.0142,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSNEVADAUN1,MPSNEVADAUN1_RA,21.8284,-0.6226,-0.4124,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSRGREENUN3,MPSRGREEN1UN3_RA,21.0863,-1.6507,-0.1264,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSSHARPER_UN1,MPSSHARPER5UN1_RA,20.8409,-1.9004,-0.1222,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSSHARPER_UN2,MPSSHARPER5UN2_RA,20.7744,-1.9669,-0.1222,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSSHARPER_UN3,MPSSHARPER5UN3_RA,20.8396,-1.9016,-0.1222,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSTWA1UN1,MPSTWA1UN1_RA,21.7821,-1.0375,-0.0438,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPSTWA1UN2,MPSTWA1UN2_RA,21.7821,-1.0375,-0.0438,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MPS_MPS,MPS_LA,21.7311,-1.0401,-0.0922,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MSTNG,SPSMSTNGPLT1,30.4990,3.0623,4.5733,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MSTNG4,SPSMSTNGUN4_RA,30.1987,2.7606,4.5746,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,MSTNG5,SPSMSTNGUN5_RA,30.3204,2.8824,4.5746,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,MSTNG6,SPSMSTNGUN6_GSEC_RA,30.3204,2.8824,4.5746,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NBSO,PJM,21.9883,-0.5691,-0.3060,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NEBRASKA_CITY_1,OPPDNEBRCTYGUN1_RA,21.6862,-1.2931,0.1159,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NEBRASKA_CITY_2,OPPDNEBRCTYGUN2_RA,21.6847,-1.2946,0.1159,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NEE_MAJESTIC2,SPSMAJESTICUNMAJESTC2_WIND_RA,26.7217,0.3308,3.5275,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NHC1,VACS,21.6836,-0.6013,-0.5785,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NORTH_OMAHA_3,OPPDN_OMAHAUN3_RA,22.4557,-0.5264,0.1187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NORTH_OMAHA_4,OPPDN_OMAHAUN4_RA,22.4557,-0.5264,0.1187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NORTH_OMAHA_5,OPPDN_OMAHAUN5_RA,22.4557,-0.5264,0.1187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.AINSICGEN,NPPDAINSWINDUNAINS_IC_RA,24.4164,1.0166,0.5363,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.BRPS.CTNWD,NPPDROSEMONTUNCTNWD_2_NPCW_RA,23.8342,0.4222,0.5485,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.EAGL.MILL,NPPD.EAGL.MILL_H,22.3676,-0.7078,0.2120,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.ETNA.ASSET2,NPPDWAKE_FLDUNRTLSNKE_CRK_WF_RA,22.5604,-0.4591,0.1560,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.FREM.CTNWD1,NPPDROSEMONTUNCTNWD_1_FREM_RA,23.8342,0.4222,0.5485,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.HUB.PY2018,NPPDPY18_H,22.0192,-1.0030,0.1588,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.HUB.PY2019,NPPD.HUB.PY2019_H,22.0058,-1.0135,0.1559,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.HUB.PY2020,NPPD.HUB.PY2020_H,22.0181,-1.0039,0.1586,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.HUB.PY2021,NPPD.HUB.PY2021_H,21.9920,-1.0250,0.1536,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.HYST.HYST,NPPDTURTLECKUNHAYSTACK_WIND_RA,22.6356,-0.4137,0.1859,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.KCPL.JFY1,NPPD.KCPL.JFY1_H,23.6498,-0.1947,0.9811,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.KCPL.JFY2,NPPD.KCPL.JFY2_H,23.6498,-0.1947,0.9811,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.LBLU.LBLU,NPPDMACON345UNLITTLEBLU_WF_RA,23.5771,-0.1640,0.8777,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.LCE.PLMCK,NPPDTURTLECKUNPLMCK_WIND_RA,22.6356,-0.4137,0.1859,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.LES.PRBRZ,NPPDMEADW_GRUNPRARIEBRZ_LES_RA,22.6199,-0.4983,0.2548,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.ANSLEYGEN,NPPDBROKENBUNANSLEY_RA,24.2536,0.6674,0.7228,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.BENKELMANGEN,NPPDBEVERL1UNBNKLMAN_RA,24.0117,-0.2422,1.3904,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.BROKENBOWGEN,NPPDBROKENBUNBROKENBOW_RA,24.2536,0.6674,0.7228,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.BURWELLGEN,NPPDORD1UNBURWELL_RA,24.3062,0.8487,0.5941,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.CALLAWAYGEN,NPPDCALAWAYUNCALLAWAY_RA,24.1389,0.4840,0.7914,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.CRETEGEN,NPPDCRETEUNCRETE_RA,22.6843,-0.3879,0.2088,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.CTWD3SSCY,NPPDROSEMONTUNCTNWD_3_SSCY_RA,23.8342,0.4222,0.5485,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.CURTISGEN,NPPDSTOCKVLUNCURTIS_RA,23.9512,-0.2294,1.3171,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.JFY1,NPPDJEFFREYUN1_RA,23.6498,-0.1947,0.9811,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.JFY2,NPPDJEFFREYUN2_RA,23.6498,-0.1947,0.9811,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.JHN2,NPPDJOHNSON2UN1_RA,23.8607,0.1218,0.8754,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.JN11,NPPDJOHNSON1UN1_RA,23.8664,0.1173,0.8856,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.JN12,NPPDJOHNSON1UN2_RA,23.8664,0.1173,0.8856,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.OXFORDGEN,NPPDORLEANSUNOXFORD_RA,24.2006,0.5570,0.7801,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.PENDERGEN,NPPDBANCROFTUNPENDER_RA,22.8266,-0.1791,0.1422,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.REDCLOUDGEN,NPPDGUIDERUNREDCLOUD_RA,23.9248,0.5397,0.5217,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.STUARTGEN,NPPDAINSWRTUNSTUART_RA,24.4598,1.0876,0.5087,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.WESTPOINTGEN,NPPDW_POINTUNWESTPOINT_RA,22.9226,-0.0911,0.1503,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.MEAN.WISNERGEN,NPPDBEEMERUNWISNER_RA,23.0027,-0.0182,0.1574,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.NELI.DDR,NELI_DDR,22.7759,-0.3185,0.2310,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.NPPM.1058,SH1058_DDR,23.0930,-0.0156,0.2451,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.NPPM.MINDENCRYPTO,MNCRP_DDR,23.9262,0.2933,0.7695,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.OPPD.CTNWDBTRC,NPPDROSEMONTUNCTNWD_4_CTYB_RA,23.8342,0.4222,0.5485,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.OPPD.MLGN,NPPDTOBIASUNMILLIGN_WIND_RA,22.3676,-0.7078,0.2120,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.OPPD.SHOL,NPPDHOSKINSUNSHOLES_WIND_RA,22.6513,-0.3980,0.1859,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.TECH.1,KEARNE_DDR,24.1630,0.5469,0.7527,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.THWE.THW1,NPPDHOLT_COUNTHWE_RA,23.0762,-0.2259,0.4387,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.THWE.THW2,NPPD.THWE.THW2_H,23.0762,-0.2259,0.4387,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.UPSR.UPSR,NPPDANTELOP3UNUPSTREAM_WIND_RA,22.6942,-0.3815,0.2123,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD.VOLT.0236,V236_DDR,22.5132,-0.5805,0.2303,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD2017HUB,NPPD2017HUB_H,22.0027,-1.0164,0.1557,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_ADMCOGEN,NPPDCOLMBSCOUNADM_COGEN_RA,22.7789,-0.3434,0.2589,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_AINSWIND,NPPDAINSWINDUNWINDFARM_RA,24.4164,1.0166,0.5363,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_BBW1,NPPDBRKNWINDUNBROKENB_WIND_RA,24.2614,0.6974,0.7006,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_BBW2,NPPDBRKNWINDUNBROKEN_WIND2_RA,24.2614,0.6974,0.7006,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_BPS,NPPDBEAPWRSTPLT1,22.4892,-0.6006,0.2264,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_BPWN_NPPD,NPPD_BPWN_NPPD_LA,22.5396,-0.5542,0.2303,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_BRPS_LOAD1,NPPD_BRPS_LA,22.8338,-0.1871,0.1575,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_CANADAY,NPPDCANADAYUN1_RA,23.8197,0.0958,0.8604,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_COLUMBS_1,NPPDCOLHYDROUN1_RA,22.7341,-0.3962,0.2669,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_COLUMBS_2,NPPDCOLHYDROUN2_RA,22.9131,-0.2172,0.2669,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_COLUMBS_3,NPPDCOLHYDROUN3_RA,22.7354,-0.3949,0.2669,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_COMB_WEC2,NPPDEGY_CNTRUNWEC2_COMB_RA,23.7625,0.3430,0.5561,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_COOPR,NPPDCOOPERUN1_RA,21.7627,-1.2087,0.1080,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_COSN_NPPD,NPPD_COSN_LA,23.9739,0.6340,0.4765,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_CRFTNWIND,NPPDCROFTONUNCROFTON_WIND_RA,22.8625,-0.1883,0.1874,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_ELKHNWIND,NPPDELKHORNUNWINDFARM_RA,22.8746,-0.1763,0.1874,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_GGS1,NPPDG_GENT1UN1_RA,23.6414,-0.2791,1.0570,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_GGS2,NPPDG_GENT1UN2_RA,23.6581,-0.2942,1.0888,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_GRIS_GT1,NPPDGI_SUB-HUNGRIS_GT1_RA,23.6296,0.2239,0.5422,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_GRIS_GT2,NPPDGI_SUB-HUNGRIS_GT2_RA,23.6073,0.2017,0.5422,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_GRIS_GT3,NPPDGI_SUB-HUNGRIS_GT3_RA,23.6073,0.2017,0.5422,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_GRIS_LD,NPPD_GRIS_LD_LA,23.6894,0.2777,0.5482,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_GRIS_PB3,NPPDMEADW_GRUNPRARIEBR3_NPPD_RA,22.6199,-0.4983,0.2548,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_GRIS_PGS1,NPPDGI_SUB-DUNGRIS_PGS1_RA,23.6853,0.2707,0.5512,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_HALLAM,NPPDSHELDONUN3_RA,22.3355,-0.7367,0.2088,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_HAST_DHPC,NPPDD_HENRYUNDHPC_RA,23.8037,0.3775,0.5627,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_HAST_LOAD,NPPD_HAST_LD_LA,23.7896,0.3631,0.5630,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_HAST_NDS4,NPPDDENVER2UNNDS4_HASTNGS_RA,23.8018,0.3734,0.5650,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_HAST_NDS5,NPPDDENVER2UNNDS5_RA,23.8018,0.3734,0.5650,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_HAST_W2AX,NPPD_HAST_W2AX_LA,23.7625,0.3430,0.5561,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_HAST_WEC1,NPPDEGY_CNTRUNWEC1_HASTNGS_RA,23.7625,0.3430,0.5561,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_HCPD_VLTN,NPPD_HCPD_VLTN_LA,24.7674,1.4362,0.4677,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_HEBRON,NPPDHEBRON_NUN1_RA,23.5394,0.2769,0.3990,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_KINGSLEY,NPPDKINGSLEYUN1_RA,23.4450,-0.4858,1.0673,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_LAREDO,NPPDPTRBRG_NUNLAREDO_WIND_RA,23.2574,0.0961,0.2978,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_MCCOOK,NPPDMCCOOK1UN2_RA,23.9995,-0.2946,1.4307,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_MEAN_SCRI,NPPD_MEAN_SCRI_LA,22.9149,-0.1491,0.2005,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_NELI_LD,NPPD_NELIGH_LA,22.7759,-0.3185,0.2310,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_NPLATTE_1,NPPDN_PLT1UN1_RA,23.7206,-0.1688,1.0259,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_NPLATTE_2,NPPDN_PLT1UN2_RA,23.7206,-0.1688,1.0259,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_NPPD,NPPD_LA,23.3136,-0.0156,0.4658,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_SHLD_1,NPPDSHELDONUN1_RA,22.3355,-0.7367,0.2088,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_SHLD_2,NPPDSHELDONUN2_RA,22.3355,-0.7367,0.2088,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_STLFTW,NPPDSTEELFLTUNSTEELFLTSWIND_RA,22.2757,-0.8611,0.2733,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NPPD_UGPM_NEIRRG,NPPD_UGPM_NEIRRG_LA,24.1984,0.6349,0.7001,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NSB,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NSP,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,NSSO,PJM,21.9883,-0.5691,-0.3060,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,NYIS,PJM,21.9883,-0.5691,-0.3060,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.25MC.25MC,OKGEBOBCAT7UN25MC_WIND_RA,28.9395,-0.9137,6.9898,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.AECC.CHISHOLM2,OKGECHSHLMV7UNCHISHOLM2_WIND_RA,19.3051,-1.8169,-1.7414,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.AFGE.AFGE100,OKGEOTTER2UNAFGE_WINDFARM_RA,16.1060,-2.0512,-4.7062,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.AFGE.AFNEM1,OKGEOTTER2UNAFNEM1_RA,16.1060,-2.0512,-4.7062,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.BALKO.WIND.1,OKGEBVRCNTY7UNBALKO_WIND_1_RA,27.9249,-0.6290,5.6905,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.BKNR.BKNR,OKGEBRECKNR4UNBKNR_MSR_RA,11.6759,-1.6323,-9.5553,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.CCCO.COGEN,OKGECONTCARBUNCCCO_COGEN_RA,18.2677,-1.6198,-2.9760,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.CSWS.RFWIND,OKGERCKFALLSUNROCKFALLS_WIND_RA,17.4829,-2.4845,-2.8960,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.CU.DUK.FRNTR,OKGERANCHRD7UNCU_FRNTR_RA,19.9032,-1.8576,-1.1026,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.ETEC.GCW,OKGERENFROW7UNETEC_GRANT_CO_RA,19.3887,-1.8621,-1.6127,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.FRONTIER,OKGESCI1UNFRONTIER_PLT,20.3230,-1.0863,-1.4542,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.FRT2.FRT2,OKGERANCHRD7UNFRONTIER2_RA,19.9032,-1.8576,-1.1026,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.GBST.BLUESTEM,OKGEBADGER7UNBLUESTEM_WIND_RA,28.2152,-0.7109,6.0626,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.GDSM.MINCO4,OKGEMINCOUNMINCO_4_FPLP_RA,20.0228,-1.4559,-1.3847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.GGWT.GREATWESTERN,OKGENBUFFRG7UNWINDFARM_RA,29.2747,-1.0201,7.4314,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.GLAS.GLAS,OKGEARB1UNGLASS_SANDS_RA,20.2810,-1.0460,-1.5364,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.GRANTPLNS.WIND.1,OKGERENFROW7UNTNSK_GRANT_CO_RA,19.3887,-1.8621,-1.6127,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.GRDA.REDDIRT,OKGEREDGNTN7UNGRDA_REDDIRT_RA,20.1461,-1.5796,-1.1377,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.HHW.HORIZON,OKGECRESCENTUNHORIZNHIL_WIND_RA,13.3080,-1.3522,-8.2033,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.KINGFISHER.WIND.1,OKGECIMARRONUNKINGFSHR_WIND1_RA,20.7186,-1.3598,-0.7850,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.LES.ARBKL,OKGEHONEYCRKUNARBKL_WIND_LES_RA,20.0057,-1.2621,-1.5956,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.MNCI.MNCI,OKGEMINCOUNMINCO_WIND_RA,20.0228,-1.4559,-1.3847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.MNII.MNII,OKGEMINCOUNMNII_MSR_RA,20.0228,-1.4559,-1.3847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.NTEC.GCW,OKGERENFROW7UNNTEC_GRANT_CO_RA,19.3887,-1.8621,-1.6127,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.NUEN.ADA1,ADA1_DDR,17.0110,-1.0399,-4.8126,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.NUEN.LAM1,LAM1_DDR,22.0084,0.1243,-0.9794,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.NUEN.MDT2,MDT2_DDR,20.3265,-1.0828,-1.4542,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.NUEN.MDT3,MDT3_DDR,20.3265,-1.0828,-1.4542,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.NUEN.WWO1,WWO1_DDR,15.9304,-0.9979,-5.9352,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.OKGE.MT10,OKGEMSTNG1UNMT10_RA,20.3259,-1.0671,-1.4705,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.OKGE.MT11,OKGEMSTNG1UNMT11_RA,20.3254,-1.0675,-1.4705,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.OKGE.MT12,OKGEMSTNG1UNMT12_RA,20.3526,-1.0404,-1.4705,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.OKGE.MT6,OKGEMSTNG1UNMT6_RA,20.1758,-0.9947,-1.6929,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.OKGE.MT7,OKGEMSTNG1UNMT7_RA,20.1758,-0.9947,-1.6929,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.OKGE.MT8,OKGEMSTNG1UNMT8_RA,20.3524,-1.0405,-1.4705,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.OKGE.MT9,OKGEMSTNG1UNMT9_RA,20.3524,-1.0405,-1.4705,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.OMPA.GRANTWIND,OKGERENFROW7UNOMPA_GRANT_CO_RA,19.3887,-1.8621,-1.6127,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.OMPA.INDNHYDRO,OKGEOMBATESVUNINDNHYDRO_RA,21.5106,-0.6740,-0.6789,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.PNDA.PNDA,OKGEBADGER7UNPONDRSA_WIND_RA,28.2152,-0.7109,6.0626,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.RCKW.RCKWIND,OKGECARTRCO4UNROCKHVN_WIND_RA,19.3996,-1.8211,-1.6428,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.RDRT.REDDIRT,OKGEREDGNTN7UNGERD_REDDIRT_RA,20.1461,-1.5796,-1.1377,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.RIVERVALLEY,OKGEAES5UNRIVERVALLEY_RA,21.1721,-0.7869,-0.9044,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.SC.WR.1,OKGEONEOKUN1_RA,20.4756,-1.5002,-0.8876,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.SC.WR.2,OKGEONEOKUN2_RA,20.4756,-1.5002,-0.8876,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.SC.WR.3,OKGEONEOKUN3_RA,20.5683,-1.4075,-0.8876,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.SC.WR.4,OKGEONEOKUN4_RA,20.5683,-1.4075,-0.8876,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.SDWE.SDWE,OKGECLEOC1UNSDWE_WIND_RA,-3.4644,-2.0949,-24.2329,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.SUEZ.KPLN,OKGEPINTAILUNKGPLWIND_RA,19.3659,-1.7868,-1.7108,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.SWCV.CV,OKGECHSHLMV7UNCV_SOCO_WIND_RA,19.3051,-1.8169,-1.7414,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.TNDR.THUNDERRANCH1,OKGESONR1UNTHUNDERR1_WIND_RA,19.5517,-1.7953,-1.5164,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.TNDR.THUNDERRANCH2,OKGESONR1UNTHUNDERR2_WIND_RA,19.5517,-1.7953,-1.5164,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.TNSK.DSW,OKGEJHNSTNCOUNDMNDSPG_WIND_RA,20.0069,-1.1467,-1.7098,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.TRWE.TRWE,OKGEMATHWSN7UNTRAVERSE1_RA,21.1959,-1.3721,-0.2955,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.TRWE.TRWE2,OKGEMATHWSN7UNTRAVERSE2_RA,21.1959,-1.3721,-0.2955,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.TRWE.TRWE3,OKGEMATHWSN7UNTRAVERSE3_RA,21.1959,-1.3721,-0.2955,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0033,FOSTER_DDR,20.5033,-0.9534,-1.4067,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0034,CUSHOIL_DDR,20.6651,-0.1830,-2.0153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0035,TARBY_DDR,21.6226,-0.2634,-0.9774,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0036,CUSHFLI_DDR,20.6651,-0.1830,-2.0153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0037,OKGE.VOLT.0037_H,20.3516,-0.4836,-2.0283,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0038,OKGE.VOLT.0038_H,20.3516,-0.4836,-2.0283,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0039,OKGE.VOLT.0039_H,19.8706,-1.3190,-1.6739,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0040,TROSPER_DDR,20.5224,-0.9082,-1.4329,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0041,LIGHTNINGCRK_DDR,20.5110,-0.9069,-1.4455,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0043,OKGE.VOLT.0043_H,21.3100,-0.6249,-0.9286,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0115,V115_DDR,20.3518,-1.0641,-1.4475,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0116,V116_DDR,20.2067,-1.0086,-1.6482,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0118,V118_DDR,20.7120,-0.7684,-1.3830,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0125,V125_DDR,21.4667,-0.4592,-0.9375,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0126,V126_DDR,21.2477,-0.5866,-1.0291,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0129,V129_DDR,19.7687,-1.2919,-1.8028,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0132,OKGE.VOLT.0132_H,20.3060,-1.0350,-1.5225,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0134,V134_DDR,21.3258,-0.5506,-0.9871,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0138,V138_DDR,21.1995,-0.6170,-1.0469,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0140,OKGE.VOLT.0140_H,20.4633,-0.9332,-1.4669,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0143,V143_DDR,21.0033,-0.5533,-1.3069,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0149,V149_DDR,19.0294,-1.2056,-2.6285,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0150,V150_DDR,18.5779,-1.1345,-3.1511,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0155,V155_DDR,21.1469,-0.6596,-1.0570,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0156,V156_DDR,20.3060,-1.0350,-1.5225,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0166,V166_DDR,22.1404,0.3203,-1.0434,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0167,OKGE.VOLT.0167_H,20.4763,-0.9190,-1.4682,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0169,OKGE.VOLT.0169_H,18.5779,-1.1345,-3.1511,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0170,V170_DDR,15.5294,-1.0093,-6.3247,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0171,OKGE.VOLT.0171_H,20.1779,-1.2348,-1.4507,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0176,V176_DDR,18.5779,-1.1345,-3.1511,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0177,V177_DDR,8.7787,-1.2711,-12.8137,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0179,OKGE.VOLT.0179_H,20.4793,-0.9146,-1.4695,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0194,OKGE.VOLT.0194_H,15.5699,-1.1420,-6.1515,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0195,V195_DDR,21.4004,0.1283,-1.5914,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0197,V197_DDR,21.4009,-0.2682,-1.1943,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0198,V198_DDR,22.1404,0.3203,-1.0434,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0208,V208_DDR,21.4164,0.1439,-1.5910,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0209,V209_DDR,21.4164,0.1439,-1.5910,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0210,OKGE.VOLT.0210_H,21.2849,-0.4368,-1.1417,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0216,V216_DDR,20.5065,-0.9083,-1.4487,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0219,V219_DDR,21.1469,-0.6596,-1.0570,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0220,V220_DDR,18.5779,-1.1345,-3.1511,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0224,V224_DDR,20.4024,-0.9919,-1.4692,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0225,V225_DDR,20.4035,-0.9908,-1.4692,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0226,V226_DDR,20.4024,-0.9919,-1.4692,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0227,V227_DDR,20.4024,-0.9919,-1.4692,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0229,V229_DDR,19.8667,-1.3404,-1.6564,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0231,V231_DDR,20.7681,-0.6133,-1.4820,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0238,V238_DDR,11.4657,-1.6687,-9.7291,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.VOLT.0242,V242_DDR,21.1713,-0.6389,-1.0533,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.WDDG.WDDG,OKGEFPL_WINDUNWDDG_MSR_RA,-38.2300,-1.4574,-59.6360,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.WFEC.MINCO4WIND,OKGEMINCOUNMINCO_WIND4_RA,20.0228,-1.4559,-1.3847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.WFEC.SKLCRKWIND,OKGEWDRNG1UNSKLCRK_WIND_RA,19.2589,-1.7373,-1.8673,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.WR.PCWF,OKGEPERSMNCKUNPCW1_WIND_RA,29.2802,-1.0147,7.4314,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE.WSNR.WSNR,OKGEFPL_WINDUNWSNR_RA,-38.2300,-1.4574,-59.6360,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGECENTWIND,OKGECENTWINDUNCENTWIND_RA,53.9772,-0.8356,31.9494,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGECWBYWIND,OKGENARDINUNCOWBOY_WIND_RA,17.1092,-2.5285,-3.2257,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEHL7,OKGEHL7_H,20.4034,-0.9372,-1.5228,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEHL8,OKGEHSL1UN8_RA,20.4034,-0.9372,-1.5228,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEHL910,OKGEHSL1PLT2,20.4034,-0.9372,-1.5228,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEKEENANWIND,OKGEWDWRDEHVUNKEENAN_WIND_RA,39.5612,-0.9036,17.6013,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEMCC,OKGEMCCLAIPLT1,20.0420,-1.4602,-1.3613,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEMK4,OKGEMUSKOGEEUN4_RA,20.9970,-0.7842,-1.0822,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEMK5,OKGEMUSKOGEEUN5_RA,20.9970,-0.7842,-1.0822,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEMK6,OKGEMUSKOGEEUN6_RA,20.9609,-0.8203,-1.0822,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEREDBUD1,OKGEREDBUDUNOKGEREDBUD1_PLT,20.3084,-1.2747,-1.2803,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEREDBUD2,OKGEREDBUDUNOKGEREDBUD2_PLT,20.1920,-1.3912,-1.2803,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEREDBUD3,OKGEREDBUDUNOKGEREDBUD3_PLT,20.1916,-1.3916,-1.2803,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEREDBUD4,OKGEREDBUDUNOKGEREDBUD4_PLT,20.3084,-1.2747,-1.2803,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGESM1,OKGESEMINOLEUN1_RA,20.5226,-1.0064,-1.3344,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGESM2,OKGESEMINOLEUN2_RA,20.5711,-1.0429,-1.2494,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGESM3,OKGESEMINOLEUN3_RA,20.5711,-1.0429,-1.2494,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGESO1,OKGESONR1UN1_RA,18.6106,-1.8548,-2.3981,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGESO2,OKGESONR1UN2_RA,19.5517,-1.7953,-1.5164,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGESPIRITWIND,OKGEOUSPRTUNSPIRITWIND_RA,39.5478,-0.9169,17.6013,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGETALOGAWIND,OKGEDEWEY1UNTALOGA_WIND_RA,6.7734,-1.2721,-14.8180,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGETINK5A,OKGETINK5UN1_RA,20.5107,-0.9555,-1.3973,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGETINK5B,OKGETINK5UN2_RA,20.5107,-0.9555,-1.3973,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGEXROADSWIND,OKGECRSRDSW7UNCROSRDS_WIND_RA,25.5682,-1.2061,3.9109,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE_CHISHOLM,OKGECHSHLMV7UNCHISHOLM_WIND_RA,19.3051,-1.8169,-1.7414,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE_CPAR_PARIS,OKGESHORTLD1_OMPA_LA,21.1117,-0.8508,-0.9009,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE_MINCO2,OKGEMINCOUNMINCO_WIND2_RA,20.0228,-1.4559,-1.3847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE_OKGE,OKGE_LA,19.9940,-0.9204,-1.9490,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE_ORIGINWIND,OKGECARTRCO4UNORIGIN_WIND_RA,19.3996,-1.8211,-1.6428,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OKGE_SEILING,OKGESLNGWND7UNSEILING_WND_I_RA,25.5551,-1.2192,3.9109,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMLP,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_AEL,CSWSWEKIWAUNOMPA_AEL_RA,21.0636,-0.6661,-1.1338,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_CV_OKGE,OKGE_OMPA_CV_LA,21.0521,-0.9006,-0.9107,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_GENHUB,OMPA_GENHUB_H,19.4493,-1.4239,-1.9903,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_KAW,OKGEOMKAWUN2_RA,18.3462,-1.5413,-2.9760,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_KNGFISHER,OKGEOMKINGFUNOMPA_KNGFISHER_RA,14.0181,-1.1954,-7.6500,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_LAMB_1,OKGERANCHRD7UNOMPA_LAMB_1_RA,19.9032,-1.8576,-1.1026,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_LAVERNE,WFECOMLVRNEUNOMPA_LAVERNE_RA,-18.5850,-1.0087,-40.4398,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_MANGUM,WFECOMMANGMUNOMPA_MANGUM_RA,13.8439,-2.2888,-6.7307,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_PAWHUSKA,CSWSOMPWHSK4UNOMPA_PAWHUSKA_RA,20.5508,-0.6564,-1.6562,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_PONCACITY_1_3,OKGEOMPONCAUNOMPONCA1_3_RA,18.3513,-1.5362,-2.9760,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_PONCACITY_4,OKGEOMPONCAUNOMPONCA4_RA,18.3513,-1.5362,-2.9760,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_SPP,OMPA_SPP_LA,17.8418,-1.3890,-3.6326,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OMPA_WIND_FARM,OKGEFPL_WINDUNUN1_FPL_OMPA_RA,-38.2300,-1.4574,-59.6360,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,ONETA,CSWSCALPINEUNONETA_1_RA,21.1232,-0.6857,-1.0545,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,ONETA_2,CSWSCALPINEUNONETA_2_RA,21.1232,-0.6857,-1.0545,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,ONETA_3,CSWSCALPINEUNONETA_3_RA,21.1232,-0.6857,-1.0545,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,ONETA_4,CSWSCALPINEUNONETA_4_RA,21.1232,-0.6857,-1.0545,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,ONT,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.BEAR1,OPPDSUB1347UNBEAR1_RA,22.4623,-0.5228,0.1216,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.BEAR2,OPPDSUB1347UNBEAR2_RA,22.4623,-0.5228,0.1216,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.BEAR3,OPPDSUB1347UNBEAR3_RA,22.4623,-0.5228,0.1216,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.BEAR4,OPPDSUB1347UNBEAR4_RA,22.4623,-0.5228,0.1216,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.BEAR5,OPPDSUB1347UNBEAR5_RA,22.4623,-0.5228,0.1216,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.BEAR6,OPPDSUB1347UNBEAR6_RA,22.4623,-0.5228,0.1216,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.BEAR7,OPPDSUB1347UNBEAR7_RA,22.4623,-0.5228,0.1216,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.BEAR8,OPPDSUB1347UNBEAR8_RA,22.4623,-0.5228,0.1216,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.BEAR9,OPPDSUB1347UNBEAR9_RA,22.4623,-0.5228,0.1216,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.NO1,OPPDN_OMAHAUNNO1_RA,22.4057,-0.5770,0.1192,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.NO2,OPPDN_OMAHAUNNO2_RA,22.4557,-0.5264,0.1187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.PLVIEW,OPPDSUB6846UNPLVIEW_RA,22.2464,-0.7513,0.1342,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.TRTL1,OPPDSUB1363UNTRTL1_RA,22.4629,-0.5275,0.1269,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD.TRTL2,OPPDSUB1363UNTRTL2_RA,22.4629,-0.5275,0.1269,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD_GLDN,OPPD_GLDN_LA,22.4614,-0.5263,0.1243,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD_GLDN2,OPPD_GLDN2_LA,22.4813,-0.5023,0.1201,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD_INV_PRZ1,NPPDMEADW_GRUNPRARIEBRZ_OPPD_RA,22.6199,-0.4983,0.2548,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD_NC_HST,OPPD_NC_HST_LA,22.0588,-0.9266,0.1219,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD_NO_HST,OPPD_NO_HST_LA,22.4419,-0.5403,0.1188,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD_OPPD,OPPD_LA,22.5358,-0.4526,0.1249,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD_PAPIO,OPPD_PAPIO_LA,22.4716,-0.5166,0.1248,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OPPD_PAPIO2,OPPD_PAPIO2_LA,22.4702,-0.5188,0.1256,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,OTP,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,OVEC,OVEC,21.9239,-0.5880,-0.3516,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PARAGOULD,PARAGOULD_LA,21.6115,-0.6497,-0.6022,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PENSACOLA_1,GRDAPENSA1UN1_RA,21.3756,-0.6223,-0.8656,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PENSACOLA_2,GRDAPENSA1UN2_RA,21.3756,-0.6223,-0.8656,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PENSACOLA_3,GRDAPENSA1UN3_RA,21.3756,-0.6223,-0.8656,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PENSACOLA_4,GRDAPENSA1UN4_RA,21.3717,-0.6100,-0.8818,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PENSACOLA_5,GRDAPENSA1UN5_RA,21.3717,-0.6100,-0.8818,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PENSACOLA_6,GRDAPENSA1UN6_RA,21.3717,-0.6100,-0.8818,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PIGGOTT,PIGGOTT_LA,21.6404,-0.6488,-0.5743,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PJM,PJM,21.9883,-0.5691,-0.3060,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PLUM,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,POPLARBLUFF,POPLARBLUFF_LA,21.6637,-0.6458,-0.5539,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSGO_MDUM_CEDARHLS,MDUBAKER2UNCEDARHLS_UNIT_RA,23.5492,0.4760,0.2098,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSGO_MDUM_DIAMWND,MDUBAKER2UNDIAMWI_1_UNIT_RA,23.5492,0.4760,0.2098,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSGO_MDUM_GLENDC1,MDUGLENDCTUNGLENDC_1_RA,23.4677,0.4129,0.1913,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSGO_MDUM_GLENDC2,MDUGLENDCTUNGLENDC_2_RA,23.4677,0.4129,0.1913,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSGO_MDUM_LEWIS1,MDULEWISUNLEWIS_1_UNIT_RA,25.3597,2.3394,0.1569,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSGO_MDUM_LEWIS2,MDULEWISUNLEWIS_2_UNIT_RA,25.3615,2.3411,0.1569,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSGO_MDUM_MCTURB,MDUMCTURBUNMCTURB_1_UNIT_RA,23.3908,0.3274,0.2000,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSGO_MDUM_TSWF,MDUHETINGRUNTSWF_1_RA,23.5230,0.3828,0.2767,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSGO_TVA_CANRIVR,TVACAN_TVAUNCANEY_TVA_RA,20.9047,-1.5893,-0.3694,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_AECI_CSWS,PSLO_AECI_CSWS_LA,21.1079,-0.5736,-1.1819,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_AECI_MPS,PSLO_AECI_MPS_LA,21.7730,-1.1070,0.0166,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_AECI_OKGE,PSLO_AECI_OKGE_LA,20.2225,-0.9742,-1.6667,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_AECI_WFEC,PSLO_AECI_WFEC_LA,21.0271,-0.5212,-1.3151,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_EES_CSWS,PSLO_EES_CSWS_LA,21.5900,-0.3898,-0.8836,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_MISO_WAUE_ALTM,PSLO_MISO_WAUE_ALTM_LA,22.6397,-0.2448,0.0210,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_MISO_WAUE_MDUM_NITS,PSLO_MISO_WAUE_MDUM_LA,24.1507,1.1211,0.1661,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_MISO_WAUE_MECB,PSLO_MISO_WAUE_MECB_LA,22.9467,0.0209,0.0624,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_MISO_WAUE_MPCN,PSLO_MISO_WAUE_MPCN_LA,24.1983,1.2513,0.0836,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_MISO_WAUE_OTPW,PSLO_MISO_WAUE_OTPW_LA,24.2560,1.2943,0.0982,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,PSLO_MISO_WAUE_RPGI,PSLO_MISO_WAUE_RPGI_LA,23.0130,0.1142,0.0354,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,PUPP,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,RCEAST,RCEAST,22.8293,-0.4852,0.4511,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SALINA_1,GRDASALINA1UN1_RA,21.3622,-0.5824,-0.9189,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SALINA_2,GRDASALINA1UN2_RA,21.3622,-0.5824,-0.9189,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SALINA_3,GRDASALINA1UN3_RA,21.3622,-0.5824,-0.9189,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SALINA_4,GRDASALINA1UN4_RA,21.3622,-0.5824,-0.9189,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SALINA_5,GRDASALINA1UN5_RA,21.3622,-0.5824,-0.9189,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SALINA_6,GRDASALINA1UN6_RA,21.3622,-0.5824,-0.9189,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SARPY_1,OPPDSARPYUN1_RA,22.4363,-0.5455,0.1184,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SARPY_2,OPPDSARPYUN2_RA,22.4853,-0.4970,0.1189,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SARPY_3,OPPDSARPYUN3_RA,22.3795,-0.6008,0.1169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SARPY_4,OPPDSARPYUN4_RA,22.3795,-0.6008,0.1169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SARPY_5,OPPDSARPYUN5_RA,22.3795,-0.6008,0.1169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SC,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SCEG,VACS,21.6836,-0.6013,-0.5785,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SCSE,SCSE,23.1259,-0.7509,1.0133,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SEC,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.BLOO.CPBLOOM,SECICLARKCOUNCP_BLOOM_WIND_RA,23.9346,-1.2457,2.3169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.CBN3.CB3WIND,SECICLARKCOUNCIMARRON_BEND3_RA,23.9346,-1.2457,2.3169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.GCMB.CIMARRONBEND1,SECICLARKCOUNCIMARRON_BEND_RA,23.9346,-1.2457,2.3169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.JCSOLAR,SECIJOHNCR2UNJCSOLAR_RA,26.2806,0.0806,3.3366,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.KACY.CIM,SECICLARKCOUNCIMARRON_BEND2_RA,23.9346,-1.2457,2.3169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.KCPS.CIMARRON,SECIBUCKNER7UNCIMRON_WIND_RA,24.6253,-0.9955,2.7574,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.KCPS.SPEARVILLE,SECISPERVI1UNWINDFARM_RA,23.9846,-1.0635,2.1847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.KCPS.SPEARVILLE3,SECISPERVI1UNWINDFARM3_RA,23.9846,-1.0635,2.1847,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.PRAT.PRAT5,SECIPRATT1UNPRATT5_RA,23.6018,-0.7748,1.5131,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.PXSE.PXS1,SECITHISTLE7UNPIXLEY_SOLAR_RA,23.6910,-1.3284,2.1560,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.RCSOL,SECIRUSSEL3UNRCSOL_RA,23.3474,-0.4986,0.9826,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.RUBART.RT01,SECIRUBART3UNRT01_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.RUBART.RT02,SECIRUBART3UNRT02_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.RUBART.RT03,SECIRUBART3UNRT03_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.RUBART.RT04,SECIRUBART3UNRT04_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.RUBART.RT05,SECIRUBART3UNRT05_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.RUBART.RT06,SECIRUBART3UNRT06_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.SEPC.SECIRT07,SECIRUBART3UNRT07_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.SEPC.SECIRT08,SECIRUBART3UNRT08_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.SEPC.SECIRT09,SECIRUBART3UNRT09_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.SEPC.SECIRT10,SECIRUBART3UNRT10_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.SEPC.SECIRT11,SECIRUBART3UNRT11_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.SEPC.SECIRT12,SECIRUBART3UNRT12_RA,26.1218,-0.2603,3.5187,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.SUEZ.EFRK,SECIMINGO1UNEASTFORK_RA,24.6028,-0.4219,2.1613,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.SUEZ.ISTR,SECISADDLE7UNIRONSTAR_WIND_RA,23.9254,-1.2550,2.3169,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.SUEZ.SLFR,SECIMINGO1UNSOLOMONFORK_RA,24.5802,-0.4855,2.2023,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.UCU.ENSIGNWIND,SECICRKCREEKUNENSIGNWIND_RA,27.1428,0.2381,4.0413,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI.UCU.GRAYWIND,SECIHAGGAR1UNWINDFARM_MPS_RA,24.6743,-0.4423,2.2532,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECIGRDNCT1UN2,SECIGRDNCT1UN2_RA,25.0163,-0.9303,3.0832,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECIGRDNCT1UN3,SECIGRDNCT1UN3_RA,25.0174,-0.9292,3.0832,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECIGRDNCT1UN4,SECIGRDNCT1UN4_RA,25.0174,-0.9292,3.0832,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECIGRDNCT1UN5,SECIGRDNCT1UN5_RA,25.0174,-0.9292,3.0832,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECIHOLCOM1UN1,SECIHOLCOM1UN2_RA,24.9826,-1.0103,3.1295,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI_CIMARRON,SECIBUCKNER7UNCIMRNCPV_WIND_RA,24.6253,-0.9955,2.7574,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI_SECI,SECI_LA,25.1273,-0.3748,2.6387,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI_SMOKY,SECISC_SMKHLUNWINDFARM_RA,22.4819,-1.0172,0.6356,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI_SMOKY2,SECISC_SMKHLUNWINDFARM2_RA,22.4819,-1.0172,0.6356,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SECI_TYRE_PRAT,SECI_TYRE_PRTT_LA,23.6018,-0.7748,1.5131,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SEHA,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SEILINGII,OKGESLNGWND7UNSEILING_WND_II_RA,25.5551,-1.2192,3.9109,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SERU,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SETH,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SGE,SGE,22.8015,-0.9744,0.9125,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SMEP,MISO,22.1268,-0.4026,-0.3341,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SOCO,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPA,SPA,21.3802,-0.6639,-0.8193,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPC,SPC,24.5535,1.5569,0.1332,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPPNORTH_HUB,SPPNORTH_H,22.9526,-0.1660,0.2552,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPPSOUTH_HUB,SPPSOUTH_H,16.7824,-1.1964,-4.8846,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_JRCT1,SPRMJRPS5UN6_RA,21.7107,-0.5287,-0.6240,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_JRCT2,SPRMJRPS5UN7_RA,21.7162,-0.5232,-0.6240,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_MCCT1,SPRMMACGTUNGT1_RA,21.7970,-0.4572,-0.6092,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_MCCT2,SPRMMACGTUNGT2_RA,21.7970,-0.4572,-0.6092,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_NIXA,SPRM_NIXA_LA,21.7922,-0.4412,-0.6300,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_SPRM,SPRM_LA,21.8913,-0.3480,-0.6241,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_SWCT1,SPRMSWPS5UN1_RA,21.7127,-0.5213,-0.6295,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_SWCT2,SPRMSWPS5UN2_RA,21.7127,-0.5213,-0.6295,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_SWPS1,SPRMSWPS5UNG1_RA,21.6756,-0.5583,-0.6295,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPRM_SWPS2,SPRMSWPS5UNUN_2_RA,21.7127,-0.5213,-0.6295,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.BCW1.BCW1,SPSNEEDMOREUNBLUECLOUD_WF_RA,29.9236,2.6135,4.4466,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.BETH.BETH,SPSCASTROUNBETHEL_WIND_RA,29.5177,2.4532,4.2011,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.BLACKHAWK1,SPSBLACKHAWUN1_RA,26.7077,0.1164,3.7279,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.BLACKHAWK2,SPSBLACKHAWUN2_RA,26.7077,0.1164,3.7279,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.BONITA.LORENZO.WND,SPSBLANCOUNLORENZO_WIND_RA,29.3378,1.9404,4.5340,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.BONITA.WILDCAT.WND,SPSLOSTDRAWUNWILDCAT_WIND_RA,30.5789,3.1735,4.5420,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.CAPRKWND1,SPS.CAPRKWND1_H,30.3083,3.0188,4.4261,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.CHAVES.SLR,SPSCHAVESUNCHAVES_SOLAR_RA,30.5879,3.2180,4.5064,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.CIRRUSWIND,SPSCIRRUSUNCIRRUS_WIND_RA,28.7377,1.2551,4.6192,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.CUNNGHAM1,SPS.CUNNGHAM1_H,30.1995,2.7736,4.5625,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.CUNNGHAM2,SPSCUNNSUBUN2_RA,30.4853,3.0603,4.5615,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.CUNNGHAM3,SPSCUNNSUBUN3_RA,30.4852,3.0603,4.5615,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.CUNNGHAM4,SPSCUNNSUBUN4_RA,30.1995,2.7736,4.5625,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.ENGCARBON1,SPSINDUSTR2UNENGCARBON1_RA,26.8370,0.2520,3.7215,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GBTL.BETHEL,SPSCASTROUNGOOG_BETHEL_WF_RA,29.5177,2.4532,4.2011,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GGPO.STOCKYARD10_11,SPSDUMAS_SUUNEXELON10_11_RA,27.2458,0.4886,3.8938,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GGPO.STOCKYARD4,SPSHANSFORDUNEXELON4_WIND_RA,27.1409,-0.2976,4.5751,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GGPO.STOCKYARD5_6,SPSSHERMANUNEXELON5_6_RA,27.8881,0.7853,4.2394,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GGPO.STOCKYARD7_8,SPSETTERUNEXELON7_8_RA,28.2293,1.3233,4.0425,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GGPO.STOCKYARD9,SPSMOORE_COUNEXELON9_WIND_RA,27.5697,0.6474,4.0589,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GPW1.GREATPLNS,SPSGRTPLAINUNWINDFARM_RA,27.5343,-0.5243,5.1952,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GPWA.GPWA,SPSHITCHUNGPWA_RA,27.5343,-0.5244,5.1952,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GPWB.GPWB,SPSHITCHUNGPWB_RA,27.5343,-0.5244,5.1952,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GPWC.GPWC,SPSHITCHUNGPWC_RA,27.5343,-0.5244,5.1952,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GRID.WRAB,WRAB_DDR,27.5495,1.2165,3.4696,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GRVW.GRVW,SPSHITCHUNGPVW_RA,27.5343,-0.5244,5.1952,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GSEC.ANT2,SPSANTELOPEUNANT2_RA,29.2358,1.7010,4.6713,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GSEC.ANT3,SPSANTELOPEUNANT3_RA,29.2358,1.7010,4.6713,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GSEC.ELK1,SPSTUCOUNELK1_RA,29.3906,1.7233,4.8038,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GSEC.ELK2,SPSTUCOUNELK2_RA,29.3906,1.7233,4.8038,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.GSEC.ELK3,SPSTUCOUNELK3_RA,29.3906,1.7233,4.8038,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.HALE.WND,SPSTUCOUNHALE_WIND_RA,29.2358,1.7010,4.6713,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.HARRNGTN1,SPSHARRSUBUN1_RA,26.4541,0.1053,3.4853,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.HARRNGTN2,SPSHARRSUBUN2_RA,26.4545,0.1054,3.4856,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.HARRNGTN3,SPSHARRSUBUN3_RA,26.4569,0.1059,3.4876,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.HMWI.HMWI,SPSMAJESTICUNWINDFARM_RA,26.7217,0.3308,3.5275,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.HOBBS.CC,SPSHOBBSPLT1,25.6423,2.7890,-0.0102,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.JONES1,SPSJONESSUBUN1_RA,28.7089,1.2255,4.6200,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.JONES2,SPSJONESSUBUN2_RA,28.7092,1.2257,4.6200,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.JONES3,SPSJONESSUBUN3_RA,28.7090,1.2256,4.6200,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.JONES4,SPSJONESSUBUN4_RA,28.7090,1.2256,4.6200,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.LCEC.STERLINGWIND,SPSNRTH_INTUNSTERLING_WIND_RA,30.4004,2.9691,4.5679,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.MADDOX1,SPSMADDOXSUUN1_RA,30.2252,2.7993,4.5625,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.MADDOXCT2,SPSMADDOXSUUN2_RA,30.2253,2.7993,4.5625,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.MAMMOTHWND,OKGEMAMTHPW7UNMAMMOTHWND_RA,25.5803,-1.1941,3.9109,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.NICHOLS1,SPSNICHSUBUN1_RA,26.2889,0.0104,3.4150,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.NICHOLS2,SPSNICHSUBUN2_RA,26.2889,0.0104,3.4150,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.NICHOLS3,SPSNICHSUBUN3_RA,26.4274,0.1083,3.4557,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.NUEN.WRI1,SPS.NUEN.WRI1_H,27.5495,1.2165,3.4696,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.ORPLFRISCO,SPSDWSFRSCOUNFRISCO_WIND_RA,27.5345,0.1125,4.5585,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.ORPLPRN1_2,SPSPRINGLEUNPRGLE_WIND1_2_RA,26.9281,0.1861,3.8785,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.PALODURWND,OKGEBVRCNTY7UNPALODURWND_RA,27.9249,-0.6290,5.6905,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.PANTEXWND,SPSPANTEX_SUNPANTEXWND_RA,26.6641,0.3089,3.4918,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.PLANTX1,SPS.PLANTX1_H,29.7443,2.5212,4.3596,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.PLANTX2,SPS.PLANTX2_H,29.7443,2.5212,4.3596,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.PLANTX4,SPSPLXSUBUN4_RA,29.6985,2.4562,4.3789,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.PLSNTHLWND,SPSCROSBY2UNPLSNTHILLWND_RA,29.2749,1.8555,4.5560,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.PWII.PWII,SPSBULLCREKUNPONDEROSA_II_RA,27.4670,-0.2348,4.8383,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.QUAYCNTY,SPSQUAYCNTYUNQUAYCOUNTY1_RA,30.5071,3.2176,4.4261,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.RALLSWIND,SPSHENDRIC2UNRALLS_WIND_RA,29.3522,1.9328,4.5560,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.RICHRDSN1,SPSINDUSTR2UNRICHARDSON1_RA,26.9551,0.3702,3.7215,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.ROSVELTWND,SPSCROSSRDSUNROSVELTWND_RA,30.1561,2.8253,4.4673,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.ROSWLL.SLR,SPSCHAVESUNROSWELL_SOLAR_RA,30.8578,3.4879,4.5064,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.SAGAMORE.WND,SPSCROSSRDSUNSAGAMORE_WIND_RA,30.1561,2.8253,4.4673,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.SJUANWIND1,SPSSAN_JUANUNWINDFARM_RA,30.4669,3.1352,4.4683,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.SPINSPUR,SPSSPINSPURUNSPINSPUR_WIND_RA,27.2300,0.1854,4.1811,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.SUNE_SPS1,SPSDOLLARHIUNSUNE_SPS1_RA,31.6705,4.2505,4.5565,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.SUNE_SPS2,SPSS_JALUNSUNE_SPS2_RA,31.6865,4.2665,4.5565,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.SUNE_SPS3,SPSLEA_ROADUNSUNE_SPS3_RA,31.1254,3.7033,4.5587,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.SUNE_SPS4,SPSMONUMENTUNSUNE_SPS4_RA,30.4441,3.0180,4.5627,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.SUNE_SPS5,SPSHOPI_SUBUNSUNE_SPS5_RA,31.6803,4.2708,4.5461,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.SWBD.BD,SPS_BD_SOCO_RA,25.0547,-0.8883,3.0796,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.TNSK.LLANOWIND1UNIT,SPSLLANOUNWNDFRM_RA,27.4445,1.1156,3.4654,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.TOLK1,SPSTOLKSUBUN1_RA,29.8555,2.5692,4.4229,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.TOLK2,SPSTOLKSUBUN2_RA,29.8555,2.5692,4.4229,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.TPS4.MILO,SPSCROSSRDSUNMILO_WIND_RA,30.1561,2.8253,4.4673,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0005,SPSLYNNUNLYNN_DDR_GEN_RA,28.7890,1.3093,4.6163,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0006,SPS.VOLT.0006_H,31.0204,3.5836,4.5733,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0023,SPS.VOLT.0023_H,30.2799,3.0339,4.3826,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0025,SPS.VOLT.0025_H,30.5134,3.2259,4.4241,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0033,SPS.VOLT.0033_H,28.9826,1.8257,4.2935,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0045,SPS.VOLT.0045_H,31.6705,4.2505,4.5565,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0046,SPS.VOLT.0046_H,32.6222,5.2084,4.5504,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0047,SPS.VOLT.0047_H,32.0704,4.6566,4.5504,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0052,SPS.VOLT.0052_H,29.5454,2.1259,4.5560,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0113,SPS.VOLT.0113_H,30.7287,3.4395,4.4258,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0136,SPS.VOLT.0136_H,27.5570,-0.0262,4.7197,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0137,SPS.VOLT.0137_H,27.5146,-0.0664,4.7176,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0163,V163_DDR,27.5298,0.8175,3.8489,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0168,V168_DDR,19.9155,-0.8697,-2.0782,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0180,V180_DDR,32.6222,5.2084,4.5504,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0181,V181_DDR,27.7036,0.0416,4.7986,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0182,V182_DDR,31.8227,4.4114,4.5478,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0199,V199_DDR,30.8234,3.3877,4.5723,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0200,V200_DDR,30.9224,3.4992,4.5597,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.VOLT.0235,V235_DDR,27.5345,0.1125,4.5585,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.WFEC.CAPROKWIND,SPSCAPROCKUNWINDFARM_RA,30.3083,3.0188,4.4261,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.WFEC.CHAVES2SOLAR,SPSCHAVESUNCHAVES_SOLAR2_RA,30.5879,3.2180,4.5064,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.WILDORADO,SPSWILDORADUNWINDFARM_RA,27.4279,0.7331,3.8314,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS.WTAMWIND,SPSPALO_DURUNWTAMU_WIND_RA,29.0393,1.8824,4.2935,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS_SPS,SPS_LA,29.9895,2.8552,4.2709,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,SPS_WTMN_SPS,SPS_WTMN_SPS_LA,30.0468,2.7164,4.4669,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SSCN_NPPD,SSCN_NPPD_LA,22.7247,-0.2844,0.1456,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SWPA.SIKE.GEN,WRSIKESTONUNSIKEGEN_RA,21.6657,-0.6540,-0.5438,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,SWPA_SIKE_LOAD,SWPA_SIKE_LOAD_LA,21.6657,-0.6540,-0.5438,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,TAL,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,TEC,SOUC,21.6620,-0.5861,-0.6153,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,TPW_PETERSBURG,OPPDWHITHORSUNPTRS_WIND_RA,23.2574,0.0961,0.2978,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,TVA,TVA,21.7065,-0.6172,-0.5397,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,UCUHUB,UCUHUB_H,22.2162,-1.1903,0.5431,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,UCUHUB17,UCUHUB17_H,23.4217,-0.8469,1.4052,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,UCUHUB18,UCUHUB18_H,22.6110,-1.0696,0.8171,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,UCUHUB19,UCUHUB19_H,22.3848,-1.1740,0.6954,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,UCUHUB20,UCUHUB20_H,22.4137,-1.1671,0.7174,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,UCUHUB21,UCUHUB21_H,22.7268,-1.1312,0.9945,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,UCUHUB22,UCUHUB22_H,22.6302,-1.1825,0.9493,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,UCUHUB23,UCUHUB23_H,22.6333,-1.1771,0.9470,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,UCUHUB24,UCUHUB24_H,22.5823,-1.2048,0.9237,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.AWD1.AURAWIND,WAUETANDEUNAWD1_WIND_RA,24.9634,1.9660,0.1340,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.AURORA,WAUETANDEUNAWD2_WIND_RA,24.9634,1.9660,0.1340,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.AVS1,WAUEANTELOPUNANTELO_1_UNIT_RA,23.5838,0.5824,0.1380,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.AVS2,WAUEANTELOPUNANTELO_2_UNIT_RA,23.5838,0.5824,0.1380,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.BALDWIN,WAUEHILKENUNWILTON_3_UNIT_RA,23.5537,0.5804,0.1098,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.BRADY1,WAUEDAGLUMUNBRADY_WIND_1_RA,23.5126,0.4547,0.1945,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.BRADY2,WAUEDAGLUMUNBRADY_WIND_2_RA,23.5126,0.4547,0.1945,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.BURKE,WAUETANDEUNBURKE_WIND_RA,24.9634,1.9660,0.1340,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.CAMPBLCO,WAUECAMPBLCOUNCAMPBLCO_WIND_RA,23.8141,0.8426,0.1080,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.CP01.DDR,MCLEAN_DDR,24.1958,1.2144,0.1180,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.CROSSWINDS,WAUEAYRSHRCBUNAYRSHR_1_UNIT_RA,22.6712,-0.2374,0.0451,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.CROWLAKE,WAUEWESSPRNGUNCROWLAKE_UNIT_RA,22.6742,-0.3910,0.2017,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.CULBERTSON1,WAUECLBRTSNGUNG2_CT_UNIT_RA,24.9035,1.8899,0.1501,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.CULBERTSONWH,WAUECLBRTSNGUNHEATRECG_UNIT_RA,24.9035,1.8899,0.1501,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.DAYCOUNTY1,WAUEDAYCNTYWUNDAYCOWND_UNIT_RA,22.6014,-0.3720,0.1100,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.DCS1,WAUEDEERCRKUNCT1_UNIT_RA,22.7717,-0.1719,0.0802,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.EDGELEY,WAUEEDGELEYUNPOMONA_1_UNIT_RA,23.9082,0.9522,0.0925,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.EFW2,WAUEWISDOMCBUNWISDOM_2_RA,22.7458,-0.1907,0.0730,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.ESTHERVILLE,WAUEESTRVMUUNESTRVLLE_UNIT_RA,23.3487,0.4350,0.0502,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.GARVINWH,WAUEIVANHOEWUNHEATRECG_UNIT_RA,22.7744,-0.1767,0.0876,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.GGS1,WAUEGROTONUNGROTON_1_UNIT_RA,22.8407,-0.1328,0.1100,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.GGS2,WAUEGROTONUNGROTON_2_UNIT_RA,22.8407,-0.1328,0.1100,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.HIDEWOODWH,WAUEBLAIRUNBLAIR_1_UNIT_RA,22.8354,-0.1146,0.0865,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.HYDECOUNTY,WAUEHIGHMRWDUNHIGHMR_1_UNIT_RA,22.7312,-0.3522,0.2199,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LAKOTA,WAUEGERLEDCBUNGERLED_WF_UNIT_RA,23.8172,0.9058,0.0480,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LCS1,WAUELONESMCKUNG1_UNIT_RA,24.2773,1.2769,0.1369,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LCS2,WAUELONESMCKUNG2_UNIT_RA,24.2773,1.2769,0.1369,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LCS3,WAUELONESMCKUNG3_UNIT_RA,24.2773,1.2769,0.1369,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LCS4,WAUELONESMCKUNG4_UNIT_RA,24.2773,1.2769,0.1369,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LCS5,WAUELONESMCKUNG5_UNIT_RA,24.2773,1.2769,0.1369,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LCS6,WAUELONESMCKUNG6_UNIT_RA,24.2773,1.2769,0.1369,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LINDAHL,WAUELINDAHLSUNLINDAHL_WIND_RA,25.1641,2.1673,0.1333,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LOS1,WAUELELANDOUNLELAND_1_UNIT_RA,23.4095,0.4235,0.1226,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LOS2,WAUELELANDOUNLELAND_2_UNIT_RA,23.4077,0.4216,0.1226,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.LRSE,WAUELARAMIEUNBEPM_RA,22.6878,-1.1390,0.9633,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.MADISON,WAUEFLANDRUUNMADISON1_RA,23.3217,0.3432,0.1150,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.MANNINGWH,WAUEKILDEERUNKILDEE_1_UNIT_RA,24.1470,1.1530,0.1305,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.NEAL4,WAUENLS_WAUEUNNEAL4_JOU_WAUE_RA,22.5018,-0.4754,0.1137,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.NTHBNDWND,WAUENBENDWUNNTHBND_WIND_RA,22.4053,-0.7071,0.2489,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PEMBROOKWH,WAUEORDWAYUNORDWAY_1_UNIT_RA,23.0939,0.1219,0.1086,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS1,WAUEPIONEERGUNG1_UNIT_RA,24.8430,1.8405,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS11,WAUEPIONEERGUNG11_UNIT_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS12,WAUEPIONEERGUNG12_UNIT_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS13,WAUEPIONEERGUNG13_UNIT_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS14,WAUEPIONEERGUNPGS14_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS14_16,WAUE.BEPM.PGS14_16_H,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS15,WAUEPIONEERGUNPGS15_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS16,WAUEPIONEERGUNPGS16_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS17,WAUEPIONEERGUNPGS17_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS17_19,WAUE.BEPM.PGS17_19_H,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS18,WAUEPIONEERGUNPGS18_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS19,WAUEPIONEERGUNPGS19_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS2,WAUEPIONEERGUNG2_UNIT_RA,24.8430,1.8405,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS20,WAUEPIONEERGUNPGS20_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS20_22,WAUE.BEPM.PGS20_22_H,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS21,WAUEPIONEERGUNPGS21_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS22,WAUEPIONEERGUNPGS22_RA,24.8410,1.8385,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS3,WAUEPIONEERGUNG3_UNIT_RA,24.8430,1.8405,0.1390,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS31,WAUEPIONERSWUNPGS31_RA,24.8221,1.8222,0.1364,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS32,WAUEPIONERSWUNPGS32_RA,24.8221,1.8222,0.1364,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS33,WAUEPIONERSWUNPGS33_RA,24.8221,1.8222,0.1364,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS34,WAUEPIONERSWUNPGS34_RA,24.8221,1.8222,0.1364,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS35,WAUEPIONERSWUNPGS35_RA,24.8221,1.8222,0.1364,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS36,WAUEPIONERSWUNPGS36_RA,24.8221,1.8222,0.1364,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PGS5,WAUEPIONERSWUNPGS5_RA,24.8221,1.8222,0.1364,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PREVAIL,WAUEUTICAJCUNPREVAIL_WIND_RA,22.6594,-0.3690,0.1649,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.PW1,WAUENDPRARWFUNPRARIWND_UNIT_RA,24.3802,1.4030,0.1137,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.SIOUXLNDCT,WAUEK223SIOUUNSIOUX_CT_RA,23.2622,0.2805,0.1182,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.SIOUXLNDSLD,WAUEK223SIOUUNSIOUX_SLD_RA,23.2622,0.2805,0.1182,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.SMS1,WAUESPIRITMUNSPIRIT_1_UNIT_RA,23.3742,0.3453,0.1654,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.SMS2,WAUESPIRITMUNSPIRIT_2_UNIT_RA,23.3742,0.3453,0.1654,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.STANTHONYWH,WAUEDEVAULUNDEVAUL_1_UNIT_RA,23.6965,0.7105,0.1226,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.SUNFLOWER,WAUEHEBRON4UNSUNFLOWER_WIND_RA,23.5797,0.5657,0.1506,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.SUPERIOR,WAUEHUMMELUNHUMMEL_WF_UNIT_RA,22.9439,0.0218,0.0587,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.TRIPLEHWIND,WAUECHAPELLEUNTPLH_WIND_RA,22.7567,-0.3457,0.2389,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.WEBSTERCITY,WAUESWEAZYCBUNSWEAZY_1_UNIT_RA,22.5845,-0.2919,0.0129,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.WILTON1,WAUEHILKENUNWILTON_1_UNIT_RA,23.5537,0.5804,0.1098,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.WILTON2,WAUEHILKENUNWILTON_2_UNIT_RA,23.5537,0.5804,0.1098,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.WISDOM1,WAUEWISDOMCBUNWISDOM_1_UNIT_RA,22.7458,-0.1907,0.0730,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.WLDSPRNGS,WAUENUNDRWDUNWILD_SPRG_SLR_RA,22.8414,-0.4712,0.4492,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BEPM.WOODLANDWH,WAUEREDFELDUNREDFEL_1_UNIT_RA,23.0398,0.0352,0.1411,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.BIGBEND.1_8,WAUEBIGBENDPLT1,22.4677,-0.6258,0.2301,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.CRK1.CROCKER,WAUECROCKERWUNCROCKER_WIND_RA,22.9168,-0.0506,0.1039,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.FSE,WAUE.FSE_H,22.8416,-0.3470,0.3252,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.FTPECK.1_3,WAUEFTPECKPLT1,23.5037,0.4616,0.1787,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.FTPECK.4_5,WAUEFTPECKPLT2,23.4698,0.4225,0.1839,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.FTRANDALL.1_2,WAUEFTRANDLPLT1,22.2676,-0.8179,0.2221,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.FTRANDALL.3_8,WAUEFTRANDLPLT2,22.2202,-0.8524,0.2091,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.GARRISON.1_3,WAUEGARRISNPLT1,23.3482,0.3720,0.1128,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.GARRISON.4_5,WAUEGARRISNPLT2,23.2391,0.2630,0.1127,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.GAVINSPT.1_3,WAUEGAVINSPLT1,22.6435,-0.3978,0.1779,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.HCPD.WESS,WAUEWESSPRNGUNWESSPR_1_UNIT_RA,22.6742,-0.3910,0.2017,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.LCE.WILCK,WAUESULPHSPRUNWILLOWCREEKWF_RA,22.2866,-0.9768,0.4000,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.MRES.EXR1,WAUEEXIRAWAUNEXIRAW_1_UNIT_RA,21.6325,-1.2862,0.0552,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.MRES.EXR2,WAUEEXIRAWAUNEXIRAW_2_UNIT_RA,21.6344,-1.2842,0.0552,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.MRES.EXR3,WAUEEXIRAWAUNEXIRAW_3_UNIT_RA,21.6347,-1.2839,0.0552,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.MRES.WTRN,WAUEWATERPPUNWATERP_1_UNIT_RA,22.9603,-0.0042,0.1011,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NGRM.WILDSPRINGS,WAUENUNDRWDUNWILDSP_SOLAR_RA,22.8414,-0.4712,0.4492,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.ALGONA,WAUEALGONAMUNALGONA_1_UNIT_RA,22.8795,-0.0036,0.0196,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.ALTAMUN,WAUEALTAMUNUNNMCA_ALTAMUN_RA,22.8774,-0.0583,0.0722,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.BANCROFT,WAUEBNCRUNBANCROFT_RA,23.7751,0.8636,0.0480,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.COONRAPIDS,WAUECOONRPMUUNCOONRAPIDS_RA,22.9020,-0.0143,0.0528,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.GRAETTINGER,WAUEGRAETNMUUNGRAETTINGER_RA,22.8482,-0.0558,0.0406,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.GRUNDYCENTER,WAUEGNDYUNGRUNDYCENTER_RA,21.9091,-0.9176,-0.0367,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.LAURENS,WAUECLRMUNLAURENS_RA,23.3720,0.4479,0.0607,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.MILFORD,WAUEMLFRDTCBUNMILFORD_RA,22.6254,-0.3036,0.0656,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.NEAL4,WAUENLS_WAUEUNJOU_NMCA_UNIT_RA,22.5018,-0.4754,0.1137,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.NEWHAMPTON,WAUENHAMPTCBUNNEWHAMPT_UNIT3_RA,23.3218,0.5076,-0.0493,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.SPENCER,WAUESPENCERUNSPENCER_RA,22.7137,-0.2230,0.0733,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.SUMNER,WAUESUMNERJUNSUMNER_RA,23.0278,0.2139,-0.0495,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.WESTBEND,WAUEWBENDMUNUNWESTBEND_RA,22.9509,0.0589,0.0285,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NMCA.WS4,WAUEWSECWAUEUNWSEC4_JOU_RA,22.2844,-0.6835,0.1044,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NTWK,WAUE.NTWK_H,23.3113,0.3153,0.1326,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.AB1,WAUEABDNSBTUNABDNSB_1_UNIT_RA,23.5446,0.5667,0.1145,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.AB2,WAUEABDNSBTUNCT2_UNIT_RA,23.5446,0.5667,0.1145,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.AUR,WAUEMTVERNUNAURORA_WIND_RA,22.8294,-0.2481,0.2140,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.BEETHOVEN,WAUETRIPPUNNWPS_BH__UNIT_RA,22.7974,-0.2329,0.1669,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.BIGSTONE1,WAUEBIG_WAUEUNBIG_WAU1_UNIT_RA,22.9393,-0.0050,0.0809,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.BRUL,WAUEMTVERNUNBRULE_WIND_RA,22.8294,-0.2481,0.2140,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.COYOTE1,WAUECOY_WAUEUNCOY_WAU1_UNIT_RA,23.5306,0.5678,0.0994,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.GLAN,WAUEWESTPRKPLT1,22.8775,-0.1492,0.1632,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.NEAL4,WAUENLS_WAUEUNNEALS4_JOU_RA,22.5018,-0.4754,0.1137,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.OTE,WAUEREDFLDUNOAK_TREE_UNIT_RA,23.1376,0.1292,0.1449,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.NWPS.TITAN,WAUETITANWFUNTITAN1WF_UNIT_RA,24.1340,1.1073,0.1632,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.OAHE.1,WAUEOAHEUNOAHE_1_UNIT_RA,21.8772,-1.2819,0.2957,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.OAHE.2_7,WAUEOAHEPLT1,21.7913,-1.3568,0.2846,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.OLVR.OLVR,WAUELELANDO2UNOLVR_WIND_RA,23.4950,0.4947,0.1369,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.OPPD.GRPR1,WAUEGRPRAIRUNGRPR1_WIND_RA,22.9850,-0.2753,0.3968,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.PCWF.PCWF,WAUEGRANITFUNPALMERCREEK_WF_RA,22.7855,-0.1461,0.0681,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.SLWF.SLWF,WAUEROSE_HILUNSWEETLAND_WIND_RA,22.7695,-0.2918,0.1979,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.SUEZ.TPLH,WAUE.SUEZ.TPLH_H,22.7567,-0.3457,0.2389,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.VOLT.0152,V152_DDR,25.3936,2.4000,0.1301,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE.VOLT.0172,V172_DDR,24.9120,1.9116,0.1369,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_BEPM,WAUE_BEPM_LA,24.1256,1.1302,0.1320,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_BEPM_NMCA,WAUE_BEPM_NMCA_LA,22.9136,0.0237,0.0265,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_BEPM_NMCA_CRMUBTC1,WAUE_BEPM_NMCA_CRMUBTC1_LA,22.9215,0.0051,0.0530,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_EWA,WAUE_EWA_LA,22.8936,-0.4165,0.4467,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_HCPD_NTWK,WAUE_HCPD_NTWK_LA,23.0337,0.0395,0.1308,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_HMMU,WAUE_HMMU_LA,22.6151,-0.3295,0.0811,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_MEAN_RFIA,WAUE_MEAN_RFIA_LA,22.3690,-0.4545,-0.0399,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_MECB,WAUE_MECB_LA,22.7019,-0.2221,0.0606,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_MMPA,WAUE_MMPA_LA,23.7828,0.8549,0.0644,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_MRES,WAUE_MRES_LA,23.1644,0.1784,0.1226,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_NSP_BERTHOLD,WAUE_NSP_BERTHOLD_LA,25.0752,2.0869,0.1249,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_NWMT_HLL,WAUE_NWMT_HLL_LA,23.5037,0.4616,0.1787,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_NWPS_NTWK,WAUE_NWPS_NTWK_LA,23.1729,0.1537,0.1558,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_OTP,WAUE_OTP_LA,24.7604,1.7949,0.1020,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_OTPW,WAUE_OTPW_LA,23.8869,0.9387,0.0847,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM,WAUE_UGPM_LA,23.0323,0.0278,0.1410,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_BEPM,WAUE_UGPM_BEPM_LA,23.8667,0.8578,0.1455,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_BEPMNI,WAUE_UGPM_BEPMNI_LA,22.9462,0.0209,0.0619,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_COSUPP,WAUE_UGPM_COSUPP_LA,23.2368,0.1856,0.1877,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_EWA,WAUE_UGPM_EWA_LA,22.8936,-0.4165,0.4467,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_HARLAN,WAUE_UGPM_HARLAN_LA,22.6151,-0.3295,0.0811,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_HCPD,WAUE_UGPM_HCPD_LA,23.0801,0.0865,0.1301,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_HILINE,WAUE_UGPM_HILINE_LA,23.5037,0.4616,0.1787,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_MMPA,WAUE_UGPM_MMPA_LA,23.7828,0.8549,0.0644,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_MRES,WAUE_UGPM_MRES_LA,23.3264,0.3273,0.1357,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_NWPS,WAUE_UGPM_NWPS_LA,22.9968,-0.0501,0.1834,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WAUE_UGPM_OTP,WAUE_UGPM_OTP_LA,25.1672,2.2036,0.1001,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC.BSWF.BSWF,WFECMOORLN1UNBSWF_WIND_RA,-37.0493,-1.4146,-58.4982,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC.MVWP.MVWP,WFECDOVERS1UNMAVERICK_WIND_RA,9.2943,-1.5946,-11.9745,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC.OMPA.NFSOLAR,WFECSNYDER2UNNF_SLR_RA,15.5176,-2.7528,-4.5930,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC.PEOP.CENTRAHOMAEAST,WFECTHOMAS2UNCENTRAHMA_EAST_RA,21.0350,-0.4131,-1.4154,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC.PEOP.CENTRAHOMAWEST,WFECTHOMAS2UNCENTRAHOMA_RA,21.0350,-0.4131,-1.4154,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC.PEOP.LELK,WFECGOTEBOUNLITTL_ELK_WIND_RA,11.5173,-3.0075,-8.3386,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC.PEOP.LITTLEDIXIE,WFECCOLGATEUNLITTLEDIXIE_RA,21.1523,-0.3257,-1.3855,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC.PEOP.STUART,WFECASHLAN2UNSTUART_RA,21.1405,-0.3718,-1.3511,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ANA_COMB_CYC_4,WFECANADARKOUN4_RA,17.8092,-2.0641,-2.9902,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ANA_COMB_CYC_5,WFECANADARKOUN5_RA,17.8069,-2.0664,-2.9902,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ANA_COMB_CYC_6,WFECANADARKOUN6_RA,17.8135,-2.0597,-2.9902,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ANA_GENCO_7,WFECANADARKOUNG1_RA,17.9361,-1.9371,-2.9902,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ANA_GENCO_8,WFECANADARKOUNG2_RA,17.9361,-1.9371,-2.9902,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ANA_ORME_10,WFECANADARKOUNG10_RA,17.9361,-1.9371,-2.9902,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ANA_ORME_11,WFECANADARKOUNG11_RA,17.9361,-1.9371,-2.9902,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ANA_ORME_9,WFECANADARKOUNG9_RA,17.9361,-1.9371,-2.9902,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ANA_STEAM_PLANT,WFECANADARKOPLT1,17.7940,-1.9242,-3.1452,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_BALKO_WIND_FARM,OKGEBVRCNTY7UNBALKO_WIND_WFE_RA,27.9249,-0.6290,5.6905,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_BLUECAN_WIND_FARM,WFEC_BLUECAN_WIND_FARM_H,17.4380,-2.3753,-3.0501,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_BUFFBEAR_WIND_FARM,WFECBUFBEAR2UNWINDFARM_RA,-14.5235,-1.1505,-36.2364,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_CAPROCK_SOLAR,SPSNORTONCUNWFEC_CAP_SOLAR_RA,30.3174,3.0279,4.4261,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_ENMC,WFEC_ENMC_LA,30.9537,3.5721,4.5181,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_GRANT_COUNTY_WIND,OKGERENFROW7UNGRANT_CO_WIND_RA,19.3887,-1.8621,-1.6127,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_HUGO_PLANT,WFECHUGOPP4UN1_RA,20.7354,-0.8071,-1.3210,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_LC_GAS_PLANT,SPSLOVINGTOPLT1,30.2053,2.7753,4.5666,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_MOORELAND_2,WFECMOORLN1UNMOORELAND_2_RA,-37.0741,-1.4394,-58.4982,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_MOORELAND_3,WFECMOORLN1UNMOORELAND_3_RA,-37.0493,-1.4146,-58.4982,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_MOORELAND_PLANT,WFECMOORLN1UNMOORELAND_1_RA,-37.0493,-1.4146,-58.4982,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_OKGE,WFEC_OKGE_LA,19.7796,-0.8212,-2.2627,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_PEOP_LOAD,WFEC_PEOP_LOAD_LA,21.1340,-0.2181,-1.5114,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_REDHILLS_WIND_FARM,WFECREDHILLSUNWINDFARM_RA,6.4624,-1.5430,-14.8581,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_RKYRIDGE_WIND_FARM,CSWSHOBART_JUNROCKYRDG_WIND_RA,14.5124,-2.0619,-6.2891,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_WFEC,WFEC_LA,16.6623,-0.8614,-5.3398,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WFEC_WILDCAT_WIND_FARM,SPSLOVINGTOUNWILDCATWIND_RA,30.2053,2.7753,4.5666,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.CBW,WRSHAYSUNCEDARBLF_WIND_RA,23.4948,-0.4164,1.0478,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.CPW,SECIC_PLAINUNWINDFARM_RA,24.9314,-0.6648,2.7327,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.EMP.CT1,WREMPECUNCTG_1_RA,21.3571,-1.6355,0.1291,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.EMP.CT2,WREMPECUNCTG_2_RA,21.3571,-1.6355,0.1291,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.EMP.CT3,WREMPECUNCTG_3_RA,21.3471,-1.6455,0.1291,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.EMP.CT4,WREMPECUNCTG_4_RA,21.3471,-1.6455,0.1291,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.EMP.CT5,WREMPECUNCTG_5_RA,21.3570,-1.6356,0.1291,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.EMP.CT6,WREMPECUNCTG_6_RA,21.3569,-1.6356,0.1291,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.EMP.CT7,WREMPECUNCTG_7_RA,21.3569,-1.6356,0.1291,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.ERIE.EC,WRCERIEUNERIE_1_RA,21.5607,-0.7030,-0.5998,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.ETNA.ASSET1,WRUNRIDGEUNETNA_WIND_RA,21.6582,-1.5170,0.3118,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.FLATRIDGE3,WRVIOLA7UNFLATRDG3_AEPE_RA,20.4519,-1.7757,-0.6358,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.FLATRIDGE4,WRVIOLA7UNFLATRDG4_INV_RA,20.4519,-1.7757,-0.6358,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.FLATRIDGE5,WRVIOLA7UNFLATRDG5_INV_RA,20.4519,-1.7757,-0.6358,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.FRW.1,SECIFLAT_RDGUNWF1_RA,23.3859,-1.3284,1.8508,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.FRW.2,SECIFLAT_RDGUNWF2_RA,23.3859,-1.3284,1.8508,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.GEEC.GT1,WRGORDUNG1_RA,21.4269,-1.6178,0.1812,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.GEEC.GT2,WRGORDUNG2_RA,21.4269,-1.6178,0.1812,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.GEEC.GT3,WRGORDUNGT3_RA,21.3702,-1.6745,0.1812,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.GSEC.DIAMONDVIST,WRUNRIDGEUNDVISTA_WF_GSEC_RA,21.6582,-1.5170,0.3118,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.HBWA.HBWA,WRSTRAUNHIGHBANKS_WIND_RA,21.5363,-1.3440,0.0169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.HEC.GT1,WRHECGTUN32_RA,22.1012,-1.3060,0.5438,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.HEC.GT2,WRHECGTUN33_RA,22.1127,-1.2945,0.5438,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.HEC.GT3,WRHECGTUN34_RA,22.1172,-1.2901,0.5438,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.HEC.GT4,WRHECGTUN35_RA,22.1184,-1.2888,0.5438,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.IRSH.IRSH,WRSTRAUNIRISH_CK_RA,21.5363,-1.3440,0.0169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.IWW1.GEN,SECIIRONUNIRONWOOD_WIND_RA,23.9157,-1.2646,2.3169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.JAYHAWK,WRJAY_HAWKUNJAYHAWK_WF_RA,20.8040,-1.5648,-0.4946,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.JEC.1,WRJEFFUN10_RA,21.3868,-1.6339,0.1572,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.JEC.2,WRJEFFUN11_RA,21.2759,-1.7403,0.1528,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.JEC.3,WRJEFFUN12_RA,21.3781,-1.6382,0.1528,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.KCW,OKGEKAYWIND7UNKCW_WIND_RA,20.0735,-1.8482,-0.9417,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.KMW.1,WRKINGMANUNWR_KMW_1_RA,21.8281,-1.5970,0.5617,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.KMW.2,WRKINGMANUNWR_KMW_2_RA,21.8281,-1.5970,0.5617,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.LEC.4,WRLECUN26_RA,21.4443,-1.4554,0.0362,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.LEC.5,WRLECUN27_RA,21.5699,-1.3376,0.0441,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MCPH.CT1,WRCMCPHUN37_RA,22.2448,-1.1469,0.5282,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MCPH.CT2,WRCMCPHUN38_RA,22.2448,-1.1469,0.5282,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MCPH.CT3,WRCMCPHUN48_RA,22.2406,-1.1510,0.5282,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MCPH.CT4,WRCJOHNUN1_RA,22.2974,-1.0956,0.5296,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MIDW.SMOKY1.ENEL,WRWR_SMKHLUNSMOK1_ENEL_RA,22.4819,-1.0172,0.6356,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MIDW.SMOKY2.ENEL,WRWR_SMKHLUNWINDFARM_ENEL_RA,22.4819,-1.0172,0.6356,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MW.COLBY.MW,WRCOLBY3UNGST_RA,24.7651,-0.1653,2.0669,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MW.GMEC.MW,WRKNOLL1UNGOODMAN_RA,23.5413,-0.3774,1.0553,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MW.GMEC2.MW,WRKNOLL1UNGMEC2_RA,23.5413,-0.3774,1.0553,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MW.KSE.MW,WRSAXMANUNKSE_CT_RA,22.5893,-0.8825,0.6084,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MW.SMOK2.CU,WRWR_SMKHLUNWINDFARM_SPRM_RA,22.4819,-1.0172,0.6356,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MWE1.MARSHALLWIND,WRROCKUNMARSHALL_WIND_RA,22.0087,-1.0727,0.2180,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.MWW,SECIHORZN_EUNWINDFARM_RA,21.7129,-1.4982,0.3476,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.NSW,WRNINNESCAUNWR_NSW_RA,21.8239,-1.6013,0.5617,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.PEOP.BUZZARDFLOP,WRALLEN4WRUNBUZZARD_FLOP_RA,21.1285,-0.3782,-1.3568,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.PRW.GEN,WRPRWINDUNPRWIND_WIND_RA,22.6889,-0.8278,0.6532,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.READ.READ,WREMPECUNREADINGWF_RA,21.3569,-1.6356,0.1291,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.SHARPE.KEPC,WRSHARP_WRUNSHARPE_KEPCO_RA,20.3424,-2.3167,-0.2044,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.SOCW.SOCW,WRSTRAUNSOCW_WIND_RA,21.5363,-1.3440,0.0169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.SPRM.ETNADVISTA,WRUNRIDGEUNDVISTA_WIND_RA,21.6582,-1.5170,0.3118,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.SWITCHGRASS,WR21STUNSWITCHGRAS_MSR_RA,21.3462,-1.4583,-0.0589,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.THAYERLD,WR.THAYERLD_LA,21.6406,-0.6365,-0.5864,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0102,WR.VOLT.0102_H,21.2706,-1.4653,-0.1275,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0106,V106_DDR,21.3060,-1.4657,-0.0917,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0139,WR.VOLT.0139_H,21.6388,-1.2037,-0.0209,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0141,WR.VOLT.0141_H,22.1023,-1.1747,0.4136,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0146,WR.VOLT.0146_H,21.6534,-1.2408,0.0308,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0147,WR.VOLT.0147_H,21.6534,-1.2408,0.0308,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0148,WR.VOLT.0148_H,21.5978,-1.2908,0.0251,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0153,WR.VOLT.0153_H,21.4435,-1.2924,-0.1275,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0157,V157_DDR,21.6339,-1.2620,0.0325,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0158,V158_DDR,21.6534,-1.2408,0.0308,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0159,WR.VOLT.0159_H,21.6534,-1.2408,0.0308,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0165,WR.VOLT.0165_H,21.0835,-1.6038,-0.1762,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0173,V173_DDR,22.3741,-1.0527,0.5633,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0174,V174_DDR,21.1941,-1.5025,-0.1668,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0184,V184_DDR,21.1565,-1.6348,-0.0722,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0185,WR.VOLT.0185_H,21.3062,-1.4772,-0.0801,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0186,V186_DDR,21.2883,-1.5163,-0.0589,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0187,WR.VOLT.0187_H,21.2537,-1.5777,-0.0320,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0188,WR.VOLT.0188_H,21.2757,-1.4562,-0.1315,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0189,WR.VOLT.0189_H,22.2450,-0.9778,0.3593,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0190,WR.VOLT.0190_H,21.4533,-1.5051,0.0950,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0191,WR.VOLT.0191_H,21.4122,-1.5630,0.1118,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0192,WR.VOLT.0192_H,21.4122,-1.5630,0.1118,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0196,WR.VOLT.0196_H,21.4533,-1.5051,0.0950,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0245,V245_DDR,21.3104,-1.4735,-0.0796,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.VOLT.0248,V248_DDR,21.3060,-1.4657,-0.0917,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.WLDP.WLDP,WRWILDPLNSUNWILDPLAINS_WF_RA,20.4249,-1.8152,-0.6233,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.WMRM.1,WRNORLUNROLL_MDW_RA,21.6822,-1.2777,0.0964,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.WOLF,WRWOLFUN15_RA,20.2648,-2.4312,-0.1674,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR.WPW,SECIIRONUNWESTERN_PLAINS_RA,23.9157,-1.2646,2.3169,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_CH_CHAN14GT,WRCGEN_SUBUNKPP_CHAN14GT_RA,21.2342,-1.0295,-0.5998,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_FLATRIDGE2SWPCO1,WRVIOLA7UNFLATRDG2_SWP1_RA,20.4519,-1.7757,-0.6358,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_FLATRIDGE2SWPCO2,WRVIOLA7UNFLATRDG2_SWP2_RA,20.4519,-1.7757,-0.6358,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_FLATRIDGE2TSA,WRVIOLA7UNFLATRDG2_TSA_RA,20.4519,-1.7757,-0.6358,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_FLATRIDGESOUTH,WRVIOLA7UNFLATRDG2_STH_RA,20.4519,-1.7757,-0.6358,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KPP_NITS,WR_KPP_NITS_LA,21.0293,-1.4908,-0.3434,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KPP_SESC,WRSALMUNKPP_SESC_MSR_RA,22.0999,-1.1717,0.4082,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_AUGICN1,WRCAUGUUNKPP_AUGICN1_RA,21.0976,-1.5286,-0.2372,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_AUGICN2,WRCAUGUUNKPP_AUGICN2_RA,21.0976,-1.5286,-0.2372,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_AUGICN3,WRCAUGUUNKPP_AUGICN3_RA,21.0976,-1.5286,-0.2372,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_AUGICN4,WRCAUGUUNKPP_AUGICN4_RA,21.0976,-1.5286,-0.2372,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_CCPUCIC1,WRCLAYUNKPP_CCPUCIC1_RA,21.7786,-1.3531,0.2683,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_CCPUCIC2,WRCLAYUNKPP_CCPUCIC2_RA,21.7786,-1.3531,0.2683,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_CCPUCIC3,WRCLAYUNKPP_CCPUCIC3_RA,21.7786,-1.3531,0.2683,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_CCPUCIC4,WRCLAYUNKPP_CCPUCIC4_RA,21.7786,-1.3531,0.2683,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_CCPUCIC5,WRCLAYUNKPP_CCPUCIC5_RA,21.7786,-1.3531,0.2683,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_CCPUCIC8,WRCLAYUNKPP_CCPUCIC8_RA,21.7786,-1.3531,0.2683,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_WELLTNGT,WRCWELLUNKPP_WELLTNGT_RA,20.5854,-1.4315,-0.8466,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_WELLTNST,WRCWELLUNKPP_WELLTNST_RA,20.5854,-1.4315,-0.8466,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_WINFLDGT,WRCWINFUNKPP_WINFLDGT_RA,19.8640,-1.7819,-1.2175,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_KP_WINFLDST,WRCWINFUNKPP_WINFLDST_RA,19.8640,-1.7819,-1.2175,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_MIDW,WR_MIDW_LA,23.8532,-0.3417,1.3314,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_MOPEP_KCPL,WR_MOPEP_KCPL_LA,22.0397,-0.6267,-0.1970,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_MOPEP_MPS,WR_MOPEP_MPS_LA,21.5935,-1.1378,-0.1321,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_MW_KPP_NITS,WR_MW_KPP_NITS_LA,23.7348,-0.4425,1.3139,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_SEG,WR_SEG_LA,21.3947,-0.9461,-0.5227,22.8635\n03/31/2025 09:10:00,03/31/2025 14:10:00,WR_WR,WR_LA,21.5524,-1.3121,0.0011,22.8634\n03/31/2025 09:10:00,03/31/2025 14:10:00,YAD,VACS,21.6836,-0.6013,-0.5785,22.8634\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/UY/html.html",
    "content": "<!DOCTYPE html PUBLIC \"-//W3C//DTD HTML 4.01//EN\" \"http://www.w3.org/TR/html4/strict.dtd\">\n<!-- saved from url=(0093)https://pronos.adme.com.uy/gpf.php?fecha_ini=5%2F2%2F2025&fecha_fin=6%2F2%2F2025&send=MOSTRAR -->\n<html lang=\"es\"><head><meta http-equiv=\"Content-Type\" content=\"text/html; charset=UTF-8\">        \n        <title>Generación por fuente.</title>\n        <link href=\"./html_files/calendario_dw-estilos.css\" type=\"text/css\" rel=\"STYLESHEET\">\n        <style type=\"text/css\">\n            body{\n                font-family:verdana,sans-serif;\n            }\n        </style>\n        <script type=\"text/javascript\" src=\"./html_files/jquery-1.4.4.min.js\"></script>\n        <script type=\"text/javascript\" src=\"./html_files/calendario_dw.js\"></script>\n\n        <script type=\"text/javascript\">\n            $(document).ready(function () {\n                $(\".campofecha\").calendarioDW();\n            });\n        </script>\n    </head>\n    <!--<hr>command60: /home/upronos/SimSEE/bin/Gen_EOL_SOL_EXP 45693 45694 60 <br><hr>comand: /home/upronos/SimSEE/bin/Gen_EOL_SOL_EXP 45693 45694 <br>-->\n    <body style=\"overscroll-behavior-x: auto;\">\n        <script type=\"text/javascript\">\n            window.onload = function () {\n                document.forms['fdatos'].elements['fecha_ini'].value = '5/2/2025';\n                document.forms['fdatos'].elements['fecha_fin'].value = '6/2/2025';\n            }\n        </script>\n    <a href=\"https://www.adme.com.uy/\"><img src=\"./html_files/logo_adme.png\"></a>\n    <p style=\"font-family:Verdana; font-size: 20px; font-color:#287cd2\">Generación por fuente. (datos del SCADA)</p><br>\n    <form action=\"https://pronos.adme.com.uy/gpf.php?fecha_ini=5%2F2%2F2025&amp;fecha_fin=6%2F2%2F2025&amp;send=MOSTRAR\" name=\"fdatos\">\n\n        Fecha inicial:<input type=\"text\" name=\"fecha_ini\" class=\"campofecha\" size=\"12\"><a class=\"botoncal\" href=\"https://pronos.adme.com.uy/gpf.php?fecha_ini=5%2F2%2F2025&amp;fecha_fin=6%2F2%2F2025&amp;send=MOSTRAR#\"><span></span></a>\n\n        Fecha final:<input type=\"text\" name=\"fecha_fin\" class=\"campofecha\" size=\"12\"><a class=\"botoncal\" href=\"https://pronos.adme.com.uy/gpf.php?fecha_ini=5%2F2%2F2025&amp;fecha_fin=6%2F2%2F2025&amp;send=MOSTRAR#\"><span></span></a>\n\n\n        <input name=\"send\" type=\"submit\" value=\"MOSTRAR\">    \n    </form>\n    <hr>\n\n\n<div style=\"float: center; width: 100%;\">\n                <img title=\"Generación por fuente.\" src=\"./html_files/gpf_6579792_6579859.svg\" alt=\"gráfico de generación por fuente.\" style=\"width: 100%;\">\n        </div>\n    <div style=\"float: center; width: 50%;\">\n\t\t<a href=\"https://pronos.adme.com.uy/cache/gpf_6579792_6579859_diezminutal.ods\"><button>Archivo Scada Detalle 10minutal</button></a>\n         \n\t</div>    <div style=\"float: center; width: 50%;\">\n\t\t<a href=\"https://pronos.adme.com.uy/cache/gpf_6579792_6579859_horario.ods\"><button>Archivo Scada Detalle Horario</button></a>\n         \n\t</div>     \n\n\n\n</body></html>"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/__init__.py",
    "content": ""
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/amper_landsnet/production.json",
    "content": "{\"hydro\":1588.2567,\"geothermal\":653.1291,\"oil\":0.0,\"timestamp\":\"2023-12-19T15:53:23.729935\"}"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/mocks/quality_check.py",
    "content": "\"\"\"\nTest datapoints for quality.py\nEach one is designed to test some part of the validation functions.\n\"\"\"\n\nfrom datetime import datetime, timedelta, timezone\n\ndt = datetime.now(timezone.utc)\n\nprod = {\n    \"biomass\": 15.0,\n    \"coal\": 130.0,\n    \"gas\": 890.0,\n    \"hydro\": 500.0,\n    \"nuclear\": 345.7,\n    \"oil\": 0.0,\n    \"solar\": 60.0,\n    \"wind\": 75.0,\n    \"geothermal\": None,\n    \"unknown\": 3.0,\n}\n\nc1 = {\n    \"consumption\": 1374.0,\n    \"zoneKey\": \"FR\",\n    \"datetime\": dt,\n    \"production\": prod,\n    \"storage\": {\n        \"hydro\": -10.0,\n    },\n    \"source\": \"mysource.com\",\n}\n\nc2 = {\n    \"consumption\": -1081.0,\n    \"zoneKey\": \"FR\",\n    \"datetime\": dt,\n    \"production\": prod,\n    \"storage\": {\n        \"hydro\": -10.0,\n    },\n    \"source\": \"mysource.com\",\n}\n\nc3 = {\n    \"consumption\": None,\n    \"zoneKey\": \"FR\",\n    \"datetime\": dt,\n    \"production\": prod,\n    \"storage\": {\n        \"hydro\": -10.0,\n    },\n    \"source\": \"mysource.com\",\n}\n\ne1 = {\n    \"sortedZoneKeys\": \"DK->NO\",\n    \"datetime\": dt,\n    \"netFlow\": 73.0,\n    \"source\": \"mysource.com\",\n}\n\ne2 = {\"sortedZoneKeys\": \"DK->NO\", \"netFlow\": 73.0, \"source\": \"mysource.com\"}\n\ne3 = {\n    \"sortedZoneKeys\": \"DK->NO\",\n    \"datetime\": \"At the 3rd beep the time will be......\",\n    \"netFlow\": 73.0,\n    \"source\": \"mysource.com\",\n}\n\nfuture = datetime.now(timezone.utc) + timedelta(minutes=55)\n\ne4 = {\n    \"sortedZoneKeys\": \"DK->NO\",\n    \"datetime\": future,\n    \"netFlow\": 73.0,\n    \"source\": \"mysource.com\",\n}\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_AEMO.py",
    "content": "\"\"\"Tests for AEMO.py\"\"\"\n\nimport re\nfrom datetime import datetime\nfrom pathlib import Path\n\nimport pytest\nfrom requests_mock import GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.AEMO import fetch_consumption_forecast\n\nBASE_PATH_TO_MOCK = Path(\"electricitymap/contrib/parsers/tests/mocks/AEMO\")\n\n\n@pytest.mark.parametrize(\"zone_key\", [\"AU-NSW\", \"AU-VIC\", \"AU-QLD\", \"AU-SA\", \"AU-TAS\"])\n# \"AU-WA\" is not implemented in the zones here\n\ndef test_snapshot_fetch_consumption_forecast(adapter, session, snapshot, zone_key):\n    base_url = \"http://nemweb.com.au/Reports/CURRENT/Operational_Demand/FORECAST_HH/\"\n\n    # Mock the base URL request with HTML that contains the expected link\n    html_content = \"\"\"\n    <html>\n    <body>\n    <a href=\"PUBLIC_FORECAST_OPERATIONAL_DEMAND_HH_202504011800_20250401173353.zip\">Link</a>\n    </body>\n    </html>\n    \"\"\"\n    adapter.register_uri(\n        GET,\n        base_url,\n        text=html_content,\n    )\n\n    # Mock specific document request\n    data_zip_file = Path(\n        BASE_PATH_TO_MOCK,\n        \"PUBLIC_FORECAST_OPERATIONAL_DEMAND_HH_202504011800_20250401173353.zip\",\n    )\n\n    print(\"Mock file path:\", data_zip_file.resolve())\n    assert data_zip_file.exists(), \"Mock zip file does not exist!\"\n\n    with open(data_zip_file, \"rb\") as zip_file:\n        zip_content = zip_file.read()\n    adapter.register_uri(\n        GET,\n        re.compile(rf\"{base_url}PUBLIC_FORECAST_OPERATIONAL_DEMAND_HH_\\d+_\\d+\\.zip\"),\n        content=zip_content,\n    )\n\n    # Run function under test\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_consumption_forecast(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=datetime(2025, 4, 1, 18, 0),  # Mock file has this datetime\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_AU_TAS_FI.py",
    "content": "#!/usr/bin/env python3\n\nimport json\nfrom unittest.mock import patch\n\nfrom electricitymap.contrib.parsers import ajenti\n\n\ndef test_parsing_payload():\n    filename = \"electricitymap/contrib/parsers/tests/mocks/AU/AU_TAS_FI_payload1.json\"\n    with open(filename) as f:\n        fake_data = json.load(f)\n    with patch(\"electricitymap.contrib.parsers.ajenti.SignalR.get_value\") as f:\n        f.return_value = fake_data\n        data = ajenti.fetch_production()[0]\n\n    assert data[\"production\"] is not None\n    assert data[\"production\"][\"wind\"] == 0.595\n    assert data[\"production\"][\"solar\"] == 0.004\n    assert data[\"production\"][\"oil\"] == 0.283\n    assert data[\"production\"][\"biomass\"] == 0\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_AU_TAS_KI.py",
    "content": "#!/usr/bin/env python3\n\nimport json\nfrom unittest.mock import patch\n\nfrom electricitymap.contrib.parsers import ajenti\n\n\ndef test_parsing_payload():\n    filename = \"electricitymap/contrib/parsers/tests/mocks/AU/AU_TAS_KI_payload1.json\"\n    with open(filename) as f:\n        fake_data = json.load(f)\n    with patch(\"electricitymap.contrib.parsers.ajenti.SignalR.get_value\") as f:\n        f.return_value = fake_data\n        data = ajenti.fetch_production()[0]\n\n    assert data[\"production\"] is not None\n    assert data[\"production\"][\"wind\"] == 1.024\n    assert data[\"production\"][\"solar\"] == 0\n\n    assert data[\"production\"][\"oil\"] == 0.779\n    assert data[\"production\"][\"biomass\"] == 0\n\n    assert data[\"storage\"][\"battery\"] == 0.149\n\n\n# This test will fetch the payload from the webservice\n# def test_parsing_payload_real():\n#     data = AU_TAS_KI.fetch_production()\n#\n#     assert data['production'] is not None\n#     assert data['production']['wind'] is not None\n#     assert data['production']['solar'] is not None\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_AU_WA_RI.py",
    "content": "#!/usr/bin/env python3\n\nimport json\nfrom unittest.mock import patch\n\nfrom electricitymap.contrib.parsers import ajenti\n\n\ndef test_parsing_payload():\n    filename = \"electricitymap/contrib/parsers/tests/mocks/AU/AU_WA_RI_payload1.json\"\n    with open(filename) as f:\n        fake_data = json.load(f)\n    with patch(\"electricitymap.contrib.parsers.ajenti.SignalR.get_value\") as f:\n        f.return_value = fake_data\n        data = ajenti.fetch_production()[0]\n\n    assert data[\"production\"] is not None\n    assert data[\"production\"][\"wind\"] == 0.148\n    assert data[\"production\"][\"solar\"] == 0\n\n    assert data[\"production\"][\"oil\"] == 0.683\n\n    # there is no biomass on that island\n    assert data[\"production\"][\"biomass\"] == 0\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_AW.py",
    "content": "import json\nfrom importlib import resources\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.AW import PRODUCTION_URL, fetch_production\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_fetch_production(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        PRODUCTION_URL,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.AW\")\n            .joinpath(\"production.json\")\n            .read_text()\n        ),\n    )\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"AW\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_BE.py",
    "content": "import json\nimport os\nimport re\nfrom datetime import datetime\nfrom pathlib import Path\n\nimport pytest\nfrom requests_mock import GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.BE import fetch_production\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/BE\")\n\n\n@pytest.fixture(autouse=True)\ndef entsoe_token_env():\n    os.environ[\"ENTSOE_TOKEN\"] = \"token\"\n\n\ndef test_fetch_production(adapter, session, snapshot):\n    entsoe_data = base_path_to_mock / \"entsoe_production.xml\"\n    elia_data = base_path_to_mock / \"production.json\"\n\n    adapter.register_uri(\n        GET,\n        re.compile(r\"https://entsoe-proxy\"),\n        content=entsoe_data.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        re.compile(r\"https://opendata\\.elia\\.be\"),\n        json=json.loads(elia_data.read_text()),\n    )\n\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_production(\n        \"BE\",\n        session,\n        datetime.fromisoformat(\"2024-01-01T02:00:00+00:00\"),\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_BG.py",
    "content": "import json\nfrom datetime import datetime, timedelta, timezone\nfrom importlib import resources\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers.BG import fetch_production\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\n\n@freeze_time(\"2024-01-01 12:00:00\")\ndef test_fetch_production(adapter, session, snapshot):\n    \"\"\"That we can fetch the production mix at the current time.\"\"\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.BG\")\n            .joinpath(\"production_live.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_production(session=session)\n\n\ndef test_fetch_production_raises_parser_exception_on_historical_data(adapter, session):\n    \"\"\"That a ParserException is raised if requesting historical data (not supported yet).\"\"\"\n    adapter.register_uri(GET, ANY, json=[])\n\n    with pytest.raises(\n        ParserException, match=\"This parser is not yet able to parse historical data\"\n    ):\n        historical_datetime = datetime.now(timezone.utc) - timedelta(days=1)\n        fetch_production(target_datetime=historical_datetime, session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CAMMESA.py",
    "content": "import json\nfrom importlib import resources\n\nimport pytest\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers.CAMMESA import (\n    CAMMESA_DEMANDA_ENDPOINT,\n    CAMMESA_RENEWABLES_ENDPOINT,\n    fetch_exchange,\n    fetch_production,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.Cammesa\")\n            .joinpath(\"exchanges.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        CAMMESA_DEMANDA_ENDPOINT,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.Cammesa\")\n            .joinpath(\"conventional_production.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        CAMMESA_RENEWABLES_ENDPOINT,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.Cammesa\")\n            .joinpath(\"renewable_production.json\")\n            .read_text()\n        ),\n    )\n\n\ndef test_exchanges_AR_CL_SEN(session, snapshot):\n    assert snapshot == fetch_exchange(\n        ZoneKey(\"AR\"),\n        ZoneKey(\"CL-SEN\"),\n        session=session,\n    )\n\n\ndef test_exchanges_AR_BAS_AR_COM(session, snapshot):\n    assert snapshot == fetch_exchange(\n        ZoneKey(\"AR-BAS\"),\n        ZoneKey(\"AR-COM\"),\n        session=session,\n    )\n\n\ndef test_fetch_production(session, snapshot):\n    assert snapshot == fetch_production(ZoneKey(\"AR\"), session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CA_AB.py",
    "content": "from pathlib import Path\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.CA_AB import fetch_wind_solar_forecasts\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/CA_AB\")\n\n\ndef test_fetch_wind_solar_forecasts(adapter, session, snapshot):\n    # Mock wind forecast data request\n    data_wind = Path(base_path_to_mock, \"wind_rpt_longterm.csv\")\n    adapter.register_uri(\n        GET,\n        \"http://ets.aeso.ca/Market/Reports/Manual/Operations/prodweb_reports/wind_solar_forecast/wind_rpt_longterm.csv\",\n        text=data_wind.read_text(),\n    )\n\n    # Moch solar forecast data request\n    data_solar = Path(base_path_to_mock, \"solar_rpt_longterm.csv\")\n    adapter.register_uri(\n        GET,\n        \"http://ets.aeso.ca/Market/Reports/Manual/Operations/prodweb_reports/wind_solar_forecast/solar_rpt_longterm.csv\",\n        text=data_solar.read_text(),\n    )\n\n    forecasts = fetch_wind_solar_forecasts(\n        zone_key=ZoneKey(\"CA-AB\"),\n        session=session,\n    )\n\n    # Run function under test\n    assert snapshot == forecasts\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CA_CQ.py",
    "content": "import json\nfrom importlib import resources\n\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers.CA_QC import fetch_consumption, fetch_production\n\n\ndef test_production(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.Hydroquebec\")\n            .joinpath(\"production.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_production(session=session)\n\n\ndef test_consumption(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.Hydroquebec\")\n            .joinpath(\"consumption.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_consumption(session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CA_ON.py",
    "content": "import re\nfrom pathlib import Path\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.CA_ON import (\n    fetch_consumption_forecast,\n    fetch_wind_solar_forecasts,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/CA_ON\")\n\n\ndef test_fetch_wind_solar_forecasts(adapter, session, snapshot):\n    # Mock VG Forecast Summary report request\n    var_gen_forecast_summary_report = Path(\n        base_path_to_mock, \"var_gen_forecast_summary_report_20250228.xml\"\n    )\n    adapter.register_uri(\n        GET,\n        re.compile(\n            r\"https://reports-public\\.ieso\\.ca/public/VGForecastSummary/PUB_VGForecastSummary_\\d{8}\\.xml\"\n        ),\n        text=var_gen_forecast_summary_report.read_text(),\n    )\n\n    # Mock Adequacy report request\n    adequacy_report = Path(base_path_to_mock, \"adequacy_report_20250228.xml\")\n    adapter.register_uri(\n        GET,\n        re.compile(\n            r\"https://reports-public\\.ieso\\.ca/public/Adequacy2/PUB_Adequacy2_\\d{8}\\.xml\"\n        ),\n        text=adequacy_report.read_text(),\n    )\n\n    # Run function under test\n    assert snapshot == fetch_wind_solar_forecasts(\n        zone_key=ZoneKey(\"CA-ON\"),\n        session=session,\n    )\n\n\ndef test_fetch_consumption_forecast(adapter, session, snapshot):\n    # Mock Adequacy report request\n    adequacy_report = Path(base_path_to_mock, \"adequacy_report_20250228.xml\")\n    adapter.register_uri(\n        GET,\n        re.compile(\n            r\"https://reports-public\\.ieso\\.ca/public/Adequacy2/PUB_Adequacy2_\\d{8}\\.xml\"\n        ),\n        text=adequacy_report.read_text(),\n    )\n\n    # Run function under test\n    assert snapshot == fetch_consumption_forecast(\n        zone_key=ZoneKey(\"CA-ON\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CEB.py",
    "content": "import json\nfrom importlib import resources\n\nimport pytest\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers.CEB import fetch_production\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.CEB\")\n            .joinpath(\"response.text\")\n            .read_text()\n        ),\n    )\n\n\ndef test_production(session, snapshot):\n    assert snapshot == fetch_production(ZoneKey(\"LK\"), session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CENACE.py",
    "content": "from datetime import datetime\nfrom zoneinfo import ZoneInfo\n\nimport freezegun\nimport pytest\nfrom requests_mock import ANY\n\nfrom electricitymap.contrib.parsers.CENACE import fetch_consumption\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/CENACE/DemandaRegional.html\", \"rb\"\n    ) as data:\n        adapter.register_uri(ANY, ANY, content=data.read())\n\n\n@freezegun.freeze_time(\"2021-01-01 00:00:00\")\ndef test_fetch_consumption_MX_OC(session):\n    data = fetch_consumption(ZoneKey(\"MX-OC\"), session)\n    assert data[0][\"zoneKey\"] == \"MX-OC\"\n    assert data[0][\"datetime\"] == datetime.now(ZoneInfo(\"America/Mexico_City\"))\n    assert data[0][\"consumption\"] == 8519.0\n\n\n@freezegun.freeze_time(\"2021-01-01 00:00:00\")\ndef test_fetch_consumption_MX_BC(session):\n    data = fetch_consumption(ZoneKey(\"MX-BC\"), session)\n    assert data[0][\"zoneKey\"] == \"MX-BC\"\n    assert data[0][\"datetime\"] == datetime.now(ZoneInfo(\"America/Tijuana\"))\n    assert data[0][\"consumption\"] == 1587.0\n\n\n@freezegun.freeze_time(\"2021-01-01 00:00:00\")\ndef test_fetch_consumption_BCS(session):\n    data = fetch_consumption(ZoneKey(\"MX-BCS\"), session)\n    assert len(data) == 0\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CH.py",
    "content": "from datetime import datetime, timezone\n\nimport pytest\n\nfrom electricitymap.contrib.parsers.CH import get_solar_capacity_at\n\n\n@pytest.mark.parametrize(\n    \"dt,expected\",\n    [\n        (\"2018-01-02\", 2107.374),\n        (\"2022-01-01\", 4080.415),\n        (\"2023-01-01\", 5094.375),\n        (\"2024-01-01\", 5108.034),\n        # make sure past date for which we do not have historical capacity returns earliest available data\n        (\"2014-02-01\", 1398.217),\n        # make sure future date for which we do not have historical capacity returns latest available data\n        (\"2024-02-01\", 5108.034),\n    ],\n)\ndef test_get_solar_capacity(dt, expected):\n    target_datetime = datetime.fromisoformat(dt).replace(tzinfo=timezone.utc)\n    assert get_solar_capacity_at(target_datetime) == expected\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CL.py",
    "content": "from datetime import datetime, timezone\nfrom importlib import resources\nfrom json import loads\n\nimport pytest\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.CL import API_BASE_URL, fetch_production\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    url = f\"{API_BASE_URL}fecha__gte=2024-02-23&fecha__lte=2024-02-24\"\n    adapter.register_uri(\n        GET,\n        url,\n        json=loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.CL\")\n            .joinpath(\"response_historical_20240224.json\")\n            .read_text()\n        ),\n    )\n\n\ndef test_snapshot_historical_data(session, snapshot):\n    target_datetime = datetime(2024, 2, 24, 0, 0, 0, tzinfo=timezone.utc)\n\n    assert snapshot == fetch_production(\n        ZoneKey(\"CL-SEN\"),\n        session=session,\n        target_datetime=target_datetime,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CNDC.py",
    "content": "import json\nfrom datetime import datetime\nfrom importlib import resources\n\nimport pytest\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.CNDC import (\n    DATA_URL,\n    INDEX_URL,\n    fetch_generation_forecast,\n    fetch_production,\n    tz_bo,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef target_datetime():\n    yield datetime(2023, 12, 20, tzinfo=tz_bo)\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter, target_datetime):\n    adapter.register_uri(\n        GET,\n        INDEX_URL,\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks.CNDC\")\n        .joinpath(\"index.html\")\n        .read_text(),\n    )\n\n    adapter.register_uri(\n        GET,\n        DATA_URL.format(target_datetime.strftime(\"%Y-%m-%d\")),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.CNDC\")\n            .joinpath(\"data.json\")\n            .read_text()\n        ),\n    )\n\n\ndef test_fetch_generation_forecast(session, snapshot, target_datetime):\n    assert snapshot == fetch_generation_forecast(\n        ZoneKey(\"BO\"),\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n\ndef test_fetch_production(session, snapshot, target_datetime):\n    assert snapshot == fetch_production(\n        ZoneKey(\"BO\"),\n        session=session,\n        target_datetime=target_datetime,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CO.py",
    "content": "from datetime import datetime\nfrom importlib import resources\nfrom json import loads\nfrom unittest.mock import patch\n\nimport pandas as pd\nfrom requests_mock import ANY\n\nfrom electricitymap.contrib.parsers.CO import (\n    CO_DEMAND_URL,\n    fetch_consumption,\n    fetch_price,\n    fetch_production,\n)\n\nmock_files = resources.files(\"electricitymap.contrib.parsers.tests.mocks.CO\")\n\n\ndef test_fetch_consumption_live(adapter, session, snapshot):\n    adapter.register_uri(\n        ANY,\n        CO_DEMAND_URL,\n        json=loads(mock_files.joinpath(\"cons_live.json\").read_text()),\n    )\n    assert snapshot == fetch_consumption(session=session)\n\n\n@patch(\"pydataxm.pydataxm.ReadDB\")\ndef test_fetch_consumption_dt(mock_readdb, snapshot):\n    readdb = mock_readdb.return_value\n    readdb.request_data.side_effect = [\n        pd.read_json(mock_files.joinpath(\"cons_dt.json\")),\n    ]\n    dt = datetime.fromisoformat(\"2025-01-01T00:00:00-05:00\")\n    assert snapshot == fetch_consumption(target_datetime=dt)\n\n\n@patch(\"pydataxm.pydataxm.ReadDB\")\ndef test_fetch_production_live(mock_readdb, snapshot):\n    readdb = mock_readdb.return_value\n    readdb.request_data.side_effect = [\n        pd.read_json(mock_files.joinpath(\"prod1_live.json\")),\n        pd.read_json(mock_files.joinpath(\"prod2_live.json\")),\n    ]\n    assert snapshot == fetch_production()\n\n\n@patch(\"pydataxm.pydataxm.ReadDB\")\ndef test_fetch_production_dt(mock_readdb, snapshot):\n    readdb = mock_readdb.return_value\n    readdb.request_data.side_effect = [\n        pd.read_json(mock_files.joinpath(\"prod1_dt.json\")),\n        pd.read_json(mock_files.joinpath(\"prod2_dt.json\")),\n    ]\n    dt = datetime.fromisoformat(\"2025-01-01T00:00:00-05:00\")\n    assert snapshot == fetch_production(target_datetime=dt)\n\n\n@patch(\"pydataxm.pydataxm.ReadDB\")\ndef test_fetch_price_live(mock_readdb, snapshot):\n    readdb = mock_readdb.return_value\n    readdb.request_data.side_effect = [\n        pd.read_json(mock_files.joinpath(\"price_live.json\")),\n    ]\n    assert snapshot == fetch_price()\n\n\n@patch(\"pydataxm.pydataxm.ReadDB\")\ndef test_fetch_price_dt(mock_readdb, snapshot):\n    readdb = mock_readdb.return_value\n    readdb.request_data.side_effect = [\n        pd.read_json(mock_files.joinpath(\"price_dt.json\")),\n    ]\n    dt = datetime.fromisoformat(\"2025-01-01T00:00:00-05:00\")\n    assert snapshot == fetch_price(target_datetime=dt)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CR.py",
    "content": "import json\nfrom datetime import datetime, timedelta, timezone\nfrom importlib import resources\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers.CR import fetch_exchange, fetch_production\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\n\n\n@freeze_time(\"2024-01-01 12:00:00\")\ndef test_fetch_production_live(adapter, session, snapshot):\n    \"\"\"That we can fetch the production mix at the current time.\"\"\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.CR\")\n            .joinpath(\"production_live.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_production(session=session)\n\n\ndef test_fetch_production_historical(adapter, session, snapshot):\n    \"\"\"That we can fetch historical energy production values.\"\"\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.CR\")\n            .joinpath(\"production_20210716.json\")\n            .read_text()\n        ),\n    )\n\n    historical_datetime = datetime(2021, 7, 16, 16, 20, 30, tzinfo=timezone.utc)\n    assert snapshot == fetch_production(\n        target_datetime=historical_datetime.astimezone(timezone.utc),\n        session=session,\n    )\n\n\n@freeze_time(\"2024-01-01 12:00:00\")\ndef test_fetch_exchange_live(adapter, session, snapshot):\n    \"\"\"That we can fetch the last known power exchanges.\"\"\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.CR\")\n            .joinpath(\"exchange_live.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_exchange(session=session)\n\n\ndef test_fetch_exchange_raises_parser_exception_on_historical_data(adapter, session):\n    \"\"\"That a ParserException is raised if requesting historical data (not supported yet).\"\"\"\n    adapter.register_uri(GET, ANY, json=[])\n\n    with pytest.raises(\n        ParserException, match=\"This parser is not yet able to parse historical data\"\n    ):\n        historical_datetime = datetime.now(timezone.utc) - timedelta(days=1)\n        fetch_exchange(target_datetime=historical_datetime, session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CY.py",
    "content": "from datetime import datetime, timezone\n\nimport pytest\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.CY import (\n    HISTORICAL_SOURCE,\n    REALTIME_SOURCE,\n    fetch_production,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef target_datetime():\n    yield datetime(2024, 3, 18, 0, 0, 0, tzinfo=timezone.utc)\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/CY/response_historical_20240318.html\",\n        \"rb\",\n    ) as response:\n        adapter.register_uri(\n            GET, HISTORICAL_SOURCE.format(\"18-03-2024\"), content=response.read()\n        )\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/CY/response_realtime_20240401.html\",\n        \"rb\",\n    ) as response:\n        adapter.register_uri(GET, REALTIME_SOURCE, content=response.read())\n\n\ndef test_snapshot_historical_source(session, target_datetime, snapshot):\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"CY\"),\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n\ndef test_snapshot_realtime_source(session, snapshot):\n    assert snapshot == fetch_production(ZoneKey(\"CY\"), session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_CZ.py",
    "content": "from datetime import datetime\nfrom pathlib import Path\n\nimport pytest\nfrom requests_mock import POST\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers import CZ\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/CZ\")\n\n# Using a fixed date that exists in the mock XML data\nTARGET_DATETIME = datetime(2025, 10, 31, 18, 0, 0)\n\n\n@pytest.fixture\ndef mock_good_response(adapter):\n    \"\"\"\n    Mocks the CEPS API with a \"good\" response containing expected data.\n    \"\"\"\n\n    data = base_path_to_mock / \"CrossborderPowerFlows.xml\"\n    adapter.register_uri(\n        POST,\n        CZ.url,\n        content=data.read_bytes(),\n    )\n\n\n@pytest.fixture\ndef mock_no_data_response(adapter):\n    \"\"\"\n    Mocks the CEPS API with a \"bad\" response that is missing the <data> tag.\n    (This fixture is requested by the exception test)\n    \"\"\"\n\n    mock_xml_content = (\n        '<root xmlns=\"https://www.ceps.cz/CepsData/StructuredData/1.0\">'\n        \"<information><name>Cross-border power flows</name></information>\"\n        '<series><serie id=\"value1\" name=\"PSE Actual [MW]\" /></series>'\n        \"</root>\"\n    )\n\n    adapter.register_uri(POST, CZ.url, text=mock_xml_content)\n\n\n@pytest.mark.parametrize(\n    \"zone_key2\",\n    [\n        ZoneKey(\"PL\"),\n        ZoneKey(\"DE\"),\n        ZoneKey(\"AT\"),\n    ],\n)\ndef test_fetch_exchange(session, snapshot, mock_good_response, zone_key2):\n    result = CZ.fetch_exchange(\n        zone_key1=ZoneKey(\"CZ\"),\n        zone_key2=zone_key2,\n        session=session,\n        target_datetime=TARGET_DATETIME,\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == result\n\n\ndef test_fetch_exchange_forecast_pl(session, snapshot, mock_good_response):\n    result = CZ.fetch_exchange_forecast(\n        zone_key1=ZoneKey(\"CZ\"),\n        zone_key2=ZoneKey(\"PL\"),\n        session=session,\n        target_datetime=TARGET_DATETIME,\n    )\n\n    assert snapshot == result\n\n\ndef test_fetch_exchange_raises_exception_on_no_data(session, mock_no_data_response):\n    with pytest.raises(ParserException):\n        CZ.fetch_exchange(\n            zone_key1=ZoneKey(\"CZ\"),\n            zone_key2=ZoneKey(\"PL\"),\n            session=session,\n            target_datetime=TARGET_DATETIME,\n        )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_DK.py",
    "content": "from datetime import datetime\nfrom importlib import resources\nfrom json import loads\n\nimport pytest\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers import DK\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    adapter.register_uri(\n        GET,\n        DK.EXCHANGE_URL,\n        json=loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.DK\")\n            .joinpath(\"ElectricityProdex5MinRealtime.json\")\n            .read_text()\n        ),\n    )\n\n    adapter.register_uri(\n        GET,\n        DK.FORECAST_URL,\n        json=loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.DK\")\n            .joinpath(\"Forecasts_5Min.json\")\n            .read_text()\n        ),\n    )\n\n\ndef test_fetch_exchange(session, snapshot):\n    target_datetime = datetime(2025, 2, 21)\n\n    assert snapshot == DK.fetch_exchange(\n        \"DK-DK2\",\n        \"SE-SE4\",\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n\ndef test_fetch_forecast(session, snapshot):\n    target_datetime = datetime(2025, 2, 21)\n\n    assert snapshot == DK.fetch_wind_solar_forecasts(\n        \"DK-DK1\",\n        session=session,\n        target_datetime=target_datetime,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_DO.py",
    "content": "from importlib import resources\nfrom math import nan\n\nimport freezegun\nimport pandas as pd\nimport pytest\nfrom requests_mock import ANY\n\nfrom electricitymap.contrib.parsers.DO import correct_solar_production, fetch_production\n\n\n@pytest.fixture\ndef production_df():\n    d = {\n        \"wind\": {\n            pd.Timestamp(\"2024-04-18 00:00:00-0400\", tz=\"America/Dominica\"): 117.42,\n            pd.Timestamp(\"2024-04-18 01:00:00-0400\", tz=\"America/Dominica\"): 76.37,\n            pd.Timestamp(\"2024-04-18 02:00:00-0400\", tz=\"America/Dominica\"): 53.67,\n            pd.Timestamp(\"2024-04-18 03:00:00-0400\", tz=\"America/Dominica\"): 57.76,\n            pd.Timestamp(\"2024-04-18 04:00:00-0400\", tz=\"America/Dominica\"): 64.95,\n            pd.Timestamp(\"2024-04-18 05:00:00-0400\", tz=\"America/Dominica\"): 52.9,\n            pd.Timestamp(\"2024-04-18 06:00:00-0400\", tz=\"America/Dominica\"): 46.25,\n            pd.Timestamp(\"2024-04-18 07:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 08:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 09:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 10:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 11:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 12:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 13:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 14:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 15:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 16:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 17:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 18:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 19:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 20:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 21:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 22:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 23:00:00-0400\", tz=\"America/Dominica\"): nan,\n        },\n        \"solar\": {\n            pd.Timestamp(\"2024-04-18 00:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 01:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 02:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 03:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 04:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 05:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 06:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 07:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 08:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 09:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 10:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 11:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 12:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 13:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 14:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 15:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 16:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 17:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 18:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 19:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 20:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 21:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 22:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 23:00:00-0400\", tz=\"America/Dominica\"): nan,\n        },\n        \"hydro\": {\n            pd.Timestamp(\"2024-04-18 00:00:00-0400\", tz=\"America/Dominica\"): 144.47,\n            pd.Timestamp(\"2024-04-18 01:00:00-0400\", tz=\"America/Dominica\"): 75.34,\n            pd.Timestamp(\"2024-04-18 02:00:00-0400\", tz=\"America/Dominica\"): 72.94,\n            pd.Timestamp(\"2024-04-18 03:00:00-0400\", tz=\"America/Dominica\"): 84.23,\n            pd.Timestamp(\"2024-04-18 04:00:00-0400\", tz=\"America/Dominica\"): 84.52,\n            pd.Timestamp(\"2024-04-18 05:00:00-0400\", tz=\"America/Dominica\"): 84.68,\n            pd.Timestamp(\"2024-04-18 06:00:00-0400\", tz=\"America/Dominica\"): 87.36,\n            pd.Timestamp(\"2024-04-18 07:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 08:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 09:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 10:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 11:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 12:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 13:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 14:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 15:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 16:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 17:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 18:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 19:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 20:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 21:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 22:00:00-0400\", tz=\"America/Dominica\"): nan,\n            pd.Timestamp(\"2024-04-18 23:00:00-0400\", tz=\"America/Dominica\"): nan,\n        },\n    }\n    return pd.DataFrame(d)\n\n\ndef test_correct_solar_production_all_nan(production_df):\n    corrected_df = correct_solar_production(production_df)\n    assert corrected_df[\"solar\"].isna().all()\n\n\ndef test_correct_solar_production_nan_then_prod(production_df):\n    production_df[\"solar\"].loc[\n        pd.Timestamp(\"2024-04-18 06:00:00-0400\", tz=\"America/Dominica\")\n    ] = 12\n    corrected_df = correct_solar_production(production_df)\n    assert (\n        corrected_df[\"solar\"].loc[\n            pd.Timestamp(\"2024-04-18 06:00:00-0400\", tz=\"America/Dominica\")\n        ]\n        == 12\n    )\n    assert all(\n        corrected_df[\"solar\"].loc[\n            : pd.Timestamp(\"2024-04-18 05:00:00-0400\", tz=\"America/Dominica\")\n        ]\n        == 0\n    )\n    assert all(\n        corrected_df[\"solar\"]\n        .loc[pd.Timestamp(\"2024-04-18 07:00:00-0400\", tz=\"America/Dominica\") :]\n        .isnull()\n    )\n\n\ndef test_correct_solar_production_prod_then_nan(production_df):\n    production_df[\"solar\"].loc[\n        : pd.Timestamp(\"2024-04-18 03:00:00-0400\", tz=\"America/Dominica\")\n    ] = 12\n    corrected_df = correct_solar_production(production_df)\n    assert all(\n        corrected_df[\"solar\"].loc[\n            : pd.Timestamp(\"2024-04-18 03:00:00-0400\", tz=\"America/Dominica\")\n        ]\n        == 12\n    )\n\n\ndef test_correct_solar_production_prod_then_nan_then_prod(production_df):\n    production_df[\"solar\"].loc[\n        : pd.Timestamp(\"2024-04-18 03:00:00-0400\", tz=\"America/Dominica\")\n    ] = 12\n    production_df[\"solar\"].loc[\n        pd.Timestamp(\"2024-04-18 06:00:00-0400\", tz=\"America/Dominica\")\n    ] = 14\n    corrected_df = correct_solar_production(production_df)\n    assert all(\n        corrected_df[\"solar\"].loc[\n            : pd.Timestamp(\"2024-04-18 03:00:00-0400\", tz=\"America/Dominica\")\n        ]\n        == 12\n    )\n    assert (\n        corrected_df[\"solar\"].loc[\n            pd.Timestamp(\"2024-04-18 06:00:00-0400\", tz=\"America/Dominica\")\n        ]\n        == 14\n    )\n    assert all(\n        corrected_df[\"solar\"].loc[\n            pd.Timestamp(\n                \"2024-04-18 04:00:00-0400\", tz=\"America/Dominica\"\n            ) : pd.Timestamp(\"2024-04-18 05:00:00-0400\", tz=\"America/Dominica\")\n        ]\n        == 0\n    )\n    assert all(\n        corrected_df[\"solar\"]\n        .loc[pd.Timestamp(\"2024-04-18 07:00:00-0400\", tz=\"America/Dominica\") :]\n        .isnull()\n    )\n\n\n@freezegun.freeze_time(\"2025-01-15\")\ndef test_fetch_production(adapter, session, snapshot):\n    adapter.register_uri(\n        ANY,\n        ANY,\n        content=resources.files(\"electricitymap.contrib.parsers.tests.mocks.DO\")\n        .joinpath(\"production.html\")\n        .read_bytes(),\n    )\n\n    assert snapshot == fetch_production(session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_EIA.py",
    "content": "import json\nimport os\nfrom datetime import datetime, timezone\nfrom importlib import resources\n\nimport pytest\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.lib.models.events import EventSourceType\nfrom electricitymap.contrib.parsers import EIA\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef eia_key_env():\n    os.environ[\"EIA_KEY\"] = \"token\"\n\n\ndef test_parse_hourly_interval():\n    \"\"\"\n    We add a 'frequency=hourly' parameter to our EIA API requests; this\n    requests results grouped by hourly intervals in UTC time.\n\n    Each time window in the response indicates the _end_ of that hourly\n    interval; ElectricityMaps stores intervals using start hour instead.\n    \"\"\"\n    fixtures = [\n        (\"2022-02-28T23\", datetime(2022, 2, 28, 22, 0, 0, tzinfo=timezone.utc)),\n        (\"2022-03-01T00\", datetime(2022, 2, 28, 23, 0, 0, tzinfo=timezone.utc)),\n        (\"2022-03-01T01\", datetime(2022, 3, 1, 0, 0, 0, tzinfo=timezone.utc)),\n    ]\n\n    for period, expected in fixtures:\n        result = EIA._parse_hourly_interval(period)\n        assert result == expected\n\n\ndef test_fetch_production_mix(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_AVRN-wind.json\")\n            .read_text()\n        ),\n    )\n    data_list = EIA.fetch_production_mix(ZoneKey(\"US-NW-PGE\"), session)\n\n    assert data_list == snapshot\n\n\ndef test_US_NW_AVRN_rerouting(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_AVRN-other.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"AVRN\", \"WND\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_AVRN-wind.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"PACW\", \"NG\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_PACW-gas.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"PACW\", \"WAT\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"PACW\", \"SUN\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"PACW\", \"WND\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"BPAT\", \"WND\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_BPAT-wind.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"BPAT\", \"NG\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"BPAT\", \"WAT\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"BPAT\", \"NUC\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"BPAT\", \"SUN\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"AVRN\", \"NG\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_AVRN-gas.json\")\n            .read_text()\n        ),\n    )\n\n    data_list = EIA.fetch_production_mix(ZoneKey(\"US-NW-PACW\"), session)\n    assert data_list == snapshot\n    data_list = EIA.fetch_production_mix(ZoneKey(\"US-NW-BPAT\"), session)\n    assert data_list == snapshot\n\n\ndef test_US_CAR_SC_nuclear_split(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_AVRN-other.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SC\", \"COL\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SC\", \"NG\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SC\", \"WAT\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SC\", \"OIL\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SC\", \"SUN\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SC\", \"NUC\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_CAR_SC-nuclear.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SCEG\", \"NUC\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_CAR_SCEG-nuclear.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SCEG\", \"COL\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SCEG\", \"NG\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SCEG\", \"WAT\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SCEG\", \"OIL\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SCEG\", \"SUN\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n\n    data_list = EIA.fetch_production_mix(ZoneKey(\"US-CAR-SC\"), session)\n    assert data_list == snapshot\n    data_list = EIA.fetch_production_mix(ZoneKey(\"US-CAR-SCEG\"), session)\n    assert data_list == snapshot\n\n\ndef test_check_transfer_mixes():\n    for production in EIA.PRODUCTION_ZONES_TRANSFERS.values():\n        all_production = production.get(\"all\", {})\n        for production_type, supplying_zones in production.items():\n            if production_type == \"all\":\n                continue\n            for zone in supplying_zones:\n                if zone in all_production:\n                    raise Exception(\n                        f\"{zone} is both in the all production export\\\n                        and exporting its {production_type} production. \\\n                        This is not possible please fix this ambiguity.\"\n                    )\n\n\ndef test_hydro_transfer_mix(adapter, session, snapshot):\n    \"\"\"\n    Make sure that with zones that integrate production only zones\n    the hydro production events are properly handled and the storage\n    is accounted for on a zone by zone basis.\n    \"\"\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_AVRN-other.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SRP\", \"COL\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SRP\", \"NG\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SRP\", \"NUC\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SRP\", \"SUN\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SRP\", \"WND\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SMTH-coal.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"DEAA\", \"WAT\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SW_DEAA-hydro.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"HGMA\", \"WAT\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SW_HGMA-hydro.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        EIA.PRODUCTION_MIX.format(\"SRP\", \"WAT\"),\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_SW_SRP-hydro.json\")\n            .read_text()\n        ),\n    )\n\n    data = EIA.fetch_production_mix(ZoneKey(\"US-SW-SRP\"), session)\n    assert data == snapshot\n\n\ndef test_exchange_transfer(adapter, session):\n    exchange_key = \"US-FLA-FPC->US-FLA-FPL\"\n    remapped_exchange_key = \"US-FLA-FPC->US-FLA-NSB\"\n    # target_datetime = (\n    #     \"2020-01-07T05:00:00+00:00\"  # Last datapoint before decommissioning of NSB\n    # )\n    # 1. Get data directly from EIA for both\n    fpl_exchange_data = json.loads(\n        resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n        .joinpath(\"US-FLA-FPC_US-FLA-FPL_exchange.json\")\n        .read_text()\n    )\n    adapter.register_uri(\n        GET,\n        # For example:\n        # https://api.eia.gov/v2/electricity/rto/interchange-data/data/?data[]=value&facets[fromba][]=FPC&facets[toba][]=FPL&frequency=hourly&api_key=token&sort[0][column]=period&sort[0][direction]=desc&length=24\n        EIA.EXCHANGE.format(EIA.EXCHANGES[exchange_key]),\n        json=fpl_exchange_data,\n    )\n    nsb_exchange_data = json.loads(\n        resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n        .joinpath(\"US-FLA-FPC_US-FLA-NSB_exchange.json\")\n        .read_text()\n    )\n    adapter.register_uri(\n        GET,\n        # For example:\n        # https://api.eia.gov/v2/electricity/rto/interchange-data/data/?data[]=value&facets[fromba][]=FPC&facets[toba][]=NSB&frequency=hourly&api_key=token&sort[0][column]=period&sort[0][direction]=desc&length=24\n        EIA.EXCHANGE.format(EIA.EXCHANGES[remapped_exchange_key]),\n        json=nsb_exchange_data,\n    )\n\n    # 2. Get data from the EIA parser fetch_exchange for\n    # US-FLA-FPC->US-FLA-FPL\n    z_k_1, z_k_2 = exchange_key.split(\"->\")\n    data_list = EIA.fetch_exchange(ZoneKey(z_k_1), ZoneKey(z_k_2), session)\n\n    # Verify that the sum of the data directly fetched matches the data\n    # from the parser.\n    for fpl, nsb, parser in zip(\n        fpl_exchange_data[\"response\"][\"data\"],\n        nsb_exchange_data[\"response\"][\"data\"],\n        data_list,\n        strict=True,\n    ):\n        assert fpl[\"value\"] + nsb[\"value\"] == parser[\"netFlow\"]\n\n\ndef test_fetch_production_mix_discards_null(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US-NW-PGE-with-nulls.json\")\n            .read_text()\n        ),\n    )\n\n    data_list = EIA.fetch_production_mix(ZoneKey(\"US-NW-PGE\"), session)\n\n    assert data_list == snapshot\n\n    assert (\n        datetime(2022, 10, 31, 11, 0, tzinfo=timezone.utc) == data_list[0][\"datetime\"]\n    )\n\n\ndef test_fetch_exchange(adapter, session):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US-NW-BPAT-US-NW-NWMT-exchange.json\")\n            .read_text()\n        ),\n    )\n    data_list = EIA.fetch_exchange(\n        ZoneKey(\"US-NW-BPAT\"), ZoneKey(\"US-NW-NWMT\"), session\n    )\n    expected = [\n        {\n            \"source\": \"eia.gov\",\n            \"datetime\": datetime(2022, 2, 28, 22, 0, tzinfo=timezone.utc),\n            \"sortedZoneKeys\": \"US-NW-BPAT->US-NW-NWMT\",\n            \"netFlow\": -12,\n        },\n        {\n            \"source\": \"eia.gov\",\n            \"datetime\": datetime(2022, 2, 28, 23, 0, tzinfo=timezone.utc),\n            \"sortedZoneKeys\": \"US-NW-BPAT->US-NW-NWMT\",\n            \"netFlow\": -11,\n        },\n        {\n            \"source\": \"eia.gov\",\n            \"datetime\": datetime(2022, 3, 1, 0, 0, tzinfo=timezone.utc),\n            \"sortedZoneKeys\": \"US-NW-BPAT->US-NW-NWMT\",\n            \"netFlow\": -2,\n        },\n    ]\n    assert len(data_list) == len(expected)\n    for i, data in enumerate(data_list):\n        assert data[\"source\"] == expected[i][\"source\"]\n        assert data[\"datetime\"] == expected[i][\"datetime\"]\n        assert data[\"sortedZoneKeys\"] == expected[i][\"sortedZoneKeys\"]\n        assert data[\"netFlow\"] == expected[i][\"netFlow\"]\n\n\ndef test_fetch_consumption(adapter, session):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_BPAT-consumption.json\")\n            .read_text()\n        ),\n    )\n    data_list = EIA.fetch_consumption(ZoneKey(\"US-NW-BPAT\"), session)\n    expected = [\n        {\n            \"source\": \"eia.gov\",\n            \"datetime\": datetime(2023, 5, 1, 9, 0, tzinfo=timezone.utc),\n            \"consumption\": 4792,\n        },\n        {\n            \"source\": \"eia.gov\",\n            \"datetime\": datetime(2023, 5, 1, 10, 0, tzinfo=timezone.utc),\n            \"consumption\": 6215,\n        },\n    ]\n    assert len(data_list) == len(expected)\n    for i, data in enumerate(data_list):\n        assert data[\"source\"] == expected[i][\"source\"]\n        assert data[\"datetime\"] == expected[i][\"datetime\"]\n        assert data[\"consumption\"] == expected[i][\"consumption\"]\n\n\ndef test_fetch_forecasted_consumption(adapter, session):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_NW_BPAT-consumption.json\")\n            .read_text()\n        ),\n    )\n    data_list = EIA.fetch_consumption_forecast(ZoneKey(\"US-NW-BPAT\"), session)\n    expected = [\n        {\n            \"source\": \"eia.gov\",\n            \"datetime\": datetime(2023, 5, 1, 9, 0, tzinfo=timezone.utc),\n            \"consumption\": 4792,\n        },\n        {\n            \"source\": \"eia.gov\",\n            \"datetime\": datetime(2023, 5, 1, 10, 0, tzinfo=timezone.utc),\n            \"consumption\": 6215,\n        },\n    ]\n    assert len(data_list) == len(expected)\n    for i, data in enumerate(data_list):\n        assert data[\"source\"] == expected[i][\"source\"]\n        assert data[\"datetime\"] == expected[i][\"datetime\"]\n        assert data[\"consumption\"] == expected[i][\"consumption\"]\n        assert data[\"sourceType\"] == EventSourceType.forecasted\n\n\ndef test_fetch_returns_storage(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.EIA\")\n            .joinpath(\"US_CAL_IID-battery_storage.json\")\n            .read_text()\n        ),\n    )\n\n    data_list = EIA.fetch_production_mix(ZoneKey(\"US-CAL-IID\"), session)\n\n    assert data_list == snapshot\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ENERCAL.py",
    "content": "from importlib import resources\n\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers import ENERCAL\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_production_with_snapshot(adapter, session, snapshot):\n    raw_data = (\n        resources.files(\"electricitymap.contrib.parsers.tests.mocks.ENERCAL\")\n        .joinpath(\"production.json\")\n        .read_bytes()\n    )\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=raw_data,\n    )\n    assert snapshot == ENERCAL.fetch_production(ZoneKey(\"NC\"), session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ENTE.py",
    "content": "from importlib import resources\nfrom json import loads\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.ENTE import (\n    DATA_URL,\n    fetch_exchange,\n    fetch_production,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    adapter.register_uri(\n        GET,\n        DATA_URL,\n        json=loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.ENTE\")\n            .joinpath(\"response_generic_20240403.json\")\n            .read_text()\n        ),\n    )\n\n\n@freeze_time(\"2024-04-03 14:37:59.999999\")\ndef test_fetch_exchange(session, snapshot):\n    assert snapshot == fetch_exchange(\n        zone_key1=ZoneKey(\"CR\"),\n        zone_key2=ZoneKey(\"NI\"),\n        session=session,\n    )\n\n\ndef test_fetch_exchange_raises_exception_on_exchange_not_implemented(session):\n    with pytest.raises(NotImplementedError):\n        fetch_exchange(\n            zone_key1=ZoneKey(\"FR\"),\n            zone_key2=ZoneKey(\"GB\"),\n            session=session,\n        )\n\n\n@freeze_time(\"2024-04-03 14:00:59.123456\")\ndef test_fetch_production(session, snapshot):\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"HN\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ENTSOE.py",
    "content": "import logging\nimport os\nfrom datetime import datetime, timedelta, timezone\nfrom pathlib import Path\n\nimport pytest\nfrom bs4 import BeautifulSoup\nfrom requests_mock import ANY, GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.lib.models.event_lists import ExchangeCapacityList\nfrom electricitymap.contrib.lib.models.events import EventSourceType\nfrom electricitymap.contrib.parsers import ENTSOE\nfrom electricitymap.contrib.parsers.ENTSOE import (\n    _get_datetime_value_from_timeseries,\n    _merge_exchange_capacity_forecasts,\n    fetch_production,\n    parse_exchange_capacity_forecast,\n    zulu_to_utc,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/ENTSOE\")\n\n\n@pytest.fixture(autouse=True)\ndef entsoe_token_env():\n    os.environ[\"ENTSOE_TOKEN\"] = \"token\"\n\n\ndef test_fetch_consumption(adapter, session, snapshot):\n    data = base_path_to_mock / \"DK-DK1_consumption.xml\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=data.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_consumption(ZoneKey(\"DK-DK1\"), session)\n\n\ndef test_fetch_consumption_forecast(adapter, session, snapshot):\n    data = base_path_to_mock / \"DK-DK2_consumption_forecast.xml\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=data.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_consumption_forecast(ZoneKey(\"DK-DK2\"), session)\n\n\ndef test_fetch_consumption_aggregated_zone(monkeypatch):\n    dt = datetime(2024, 1, 1, tzinfo=timezone.utc)\n    called_domains: list[str] = []\n\n    def fake_query_consumption(in_domain, session, target_datetime=None):\n        called_domains.append(in_domain)\n        if in_domain == ENTSOE.ENTSOE_DOMAIN_MAPPINGS[\"IT-CA\"]:\n            return \"raw-it-ca\"\n        if in_domain == ENTSOE.ENTSOE_DOMAIN_MAPPINGS[\"IT-SO\"]:\n            return \"raw-it-so\"\n        raise AssertionError(f\"Unexpected domain {in_domain}\")\n\n    def fake_parse_scalar(raw_xml, only_outBiddingZone_Domain=True):\n        if raw_xml == \"raw-it-ca\":\n            return [(dt, 70.0)]\n        if raw_xml == \"raw-it-so\":\n            return [(dt, 30.0)]\n        return None\n\n    monkeypatch.setattr(ENTSOE, \"query_consumption\", fake_query_consumption)\n    monkeypatch.setattr(ENTSOE, \"parse_scalar\", fake_parse_scalar)\n\n    result = ENTSOE.fetch_consumption(ZoneKey(\"IT-SO\"), session=None)\n\n    assert called_domains == [\n        ENTSOE.ENTSOE_DOMAIN_MAPPINGS[\"IT-CA\"],\n        ENTSOE.ENTSOE_DOMAIN_MAPPINGS[\"IT-SO\"],\n    ]\n    assert result == [\n        {\n            \"datetime\": dt,\n            \"zoneKey\": ZoneKey(\"IT-SO\"),\n            \"consumption\": 100.0,\n            \"source\": ENTSOE.SOURCE,\n            \"sourceType\": EventSourceType.measured,\n        }\n    ]\n\n\ndef test_fetch_generation_forecast(adapter, session, snapshot):\n    data = base_path_to_mock / \"SE-SE3_generation_forecast.xml\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=data.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_generation_forecast(ZoneKey(\"SE-SE3\"), session)\n\n\ndef test_fetch_generation_forecast_aggregated_zone(monkeypatch):\n    dt = datetime(2024, 1, 1, tzinfo=timezone.utc)\n    called_domains: list[str] = []\n\n    def fake_query_generation_forecast(in_domain, session, target_datetime=None):\n        called_domains.append(in_domain)\n        if in_domain == ENTSOE.ENTSOE_DOMAIN_MAPPINGS[\"IT-CA\"]:\n            return \"raw-it-ca\"\n        if in_domain == ENTSOE.ENTSOE_DOMAIN_MAPPINGS[\"IT-SO\"]:\n            return \"raw-it-so\"\n        raise AssertionError(f\"Unexpected domain {in_domain}\")\n\n    def fake_parse_scalar(raw_xml, only_inBiddingZone_Domain=True):\n        if raw_xml == \"raw-it-ca\":\n            return [(dt, 120.0)]\n        if raw_xml == \"raw-it-so\":\n            return [(dt, 80.0)]\n        return None\n\n    monkeypatch.setattr(\n        ENTSOE, \"query_generation_forecast\", fake_query_generation_forecast\n    )\n    monkeypatch.setattr(ENTSOE, \"parse_scalar\", fake_parse_scalar)\n\n    result = ENTSOE.fetch_generation_forecast(ZoneKey(\"IT-SO\"), session=None)\n\n    assert called_domains == [\n        ENTSOE.ENTSOE_DOMAIN_MAPPINGS[\"IT-CA\"],\n        ENTSOE.ENTSOE_DOMAIN_MAPPINGS[\"IT-SO\"],\n    ]\n    assert result == [\n        {\n            \"datetime\": dt,\n            \"zoneKey\": ZoneKey(\"IT-SO\"),\n            \"value\": 200.0,\n            \"source\": ENTSOE.SOURCE,\n            \"sourceType\": EventSourceType.forecasted,\n        }\n    ]\n\n\ndef test_fetch_prices_day_ahead(adapter, session, snapshot):\n    data = base_path_to_mock / \"ES_day_ahead_price.xml\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=data.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_price(ZoneKey(\"ES\"), session)\n\n\ndef test_fetch_prices_intraday(adapter, session, snapshot):\n    data = base_path_to_mock / \"ES_intraday_price.xml\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=data.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_price_intraday(ZoneKey(\"ES\"), session)\n\n\ndef test_fetch_prices_integrated_zone(adapter, session, snapshot):\n    data = base_path_to_mock / \"FR_prices.xml\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=data.read_bytes(),\n    )\n    assert snapshot == ENTSOE.fetch_price(ZoneKey(\"AX\"), session)\n\n\ndef test_fetch_with_negative_values(adapter, session, snapshot):\n    data = base_path_to_mock / \"NO-NO5_production-negatives.xml\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=data.read_bytes(),\n    )\n    logger = logging.Logger(\"test\")\n    assert snapshot == ENTSOE.fetch_production(\n        ZoneKey(\"NO-NO5\"), session, logger=logger\n    )\n\n\n@pytest.mark.parametrize(\"zone\", [\"FI\", \"LU\", \"NO-NO5\", \"SE-SE4\"])\ndef test_production_with_snapshot(adapter, session, snapshot, zone):\n    raw_data = base_path_to_mock / f\"{zone}_production.xml\"\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=raw_data.read_bytes(),\n    )\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == ENTSOE.fetch_production(ZoneKey(zone), session)\n\n\ndef test_fetch_exchange(adapter, session, snapshot):\n    imports = base_path_to_mock / \"DK-DK1_GB_exchange_imports.xml\"\n    exports = base_path_to_mock / \"DK-DK1_GB_exchange_exports.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A11&in_Domain=10YDK-1--------W&out_Domain=10YGB----------A\",\n        content=imports.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A11&in_Domain=10YGB----------A&out_Domain=10YDK-1--------W\",\n        content=exports.read_bytes(),\n    )\n    assert snapshot == ENTSOE.fetch_exchange(\n        zone_key1=ZoneKey(\"DK-DK1\"), zone_key2=ZoneKey(\"GB\"), session=session\n    )\n\n\ndef test_fetch_exchange_with_aggregated_exchanges(adapter, session, snapshot):\n    imports_AC = base_path_to_mock / \"FR-COR_IT-SAR_AC_exchange_imports.xml\"\n    exports_AC = base_path_to_mock / \"FR-COR_IT-SAR_AC_exchange_exports.xml\"\n    imports_DC = base_path_to_mock / \"FR-COR_IT-SAR_DC_exchange_imports.xml\"\n    exports_DC = base_path_to_mock / \"FR-COR_IT-SAR_DC_exchange_exports.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A11&in_Domain=10Y1001A1001A885&out_Domain=10Y1001A1001A74G\",\n        content=imports_AC.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A11&in_Domain=10Y1001A1001A74G&out_Domain=10Y1001A1001A885\",\n        content=exports_AC.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A11&in_Domain=10Y1001A1001A893&out_Domain=10Y1001A1001A74G\",\n        content=imports_DC.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A11&in_Domain=10Y1001A1001A74G&out_Domain=10Y1001A1001A893\",\n        content=exports_DC.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_exchange(\n        zone_key1=ZoneKey(\"FR-COR\"),\n        zone_key2=ZoneKey(\"IT-SAR\"),\n        session=session,\n    )\n\n\ndef test_fetch_exchange_forecast(adapter, session, snapshot):\n    imports = base_path_to_mock / \"DK-DK2_SE-SE4_exchange_forecast_imports.xml\"\n    exports = base_path_to_mock / \"DK-DK2_SE-SE4_exchange_forecast_exports.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10YDK-2--------M&out_Domain=10Y1001A1001A47J\",\n        content=imports.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10Y1001A1001A47J&out_Domain=10YDK-2--------M\",\n        content=exports.read_bytes(),\n    )\n    assert snapshot == ENTSOE.fetch_exchange_forecast(\n        zone_key1=ZoneKey(\"DK-DK2\"),\n        zone_key2=ZoneKey(\"SE-SE4\"),\n        session=session,\n    )\n\n\ndef test_fetch_exchange_forecast_15_min(adapter, session, snapshot):\n    imports = base_path_to_mock / \"BE_NL_exchange_forecast_imports.xml\"\n    exports = base_path_to_mock / \"BE_NL_exchange_forecast_exports.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10YBE----------2&out_Domain=10YNL----------L\",\n        content=imports.read_bytes(),\n    )\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10YNL----------L&out_Domain=10YBE----------2\",\n        content=exports.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_exchange_forecast(\n        zone_key1=ZoneKey(\"BE\"), zone_key2=ZoneKey(\"NL\"), session=session\n    )\n\n\ndef test_fetch_exchange_forecast_with_longer_day_ahead_than_total(\n    adapter, session, snapshot\n):\n    imports = base_path_to_mock / \"EE_FI_exchange_forecast_imports.xml\"\n    exports = base_path_to_mock / \"EE_FI_exchange_forecast_exports.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10Y1001A1001A39I&out_Domain=10YFI-1--------U\",\n        content=imports.read_bytes(),\n    )\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10YFI-1--------U&out_Domain=10Y1001A1001A39I\",\n        content=exports.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_exchange_forecast(\n        zone_key1=ZoneKey(\"EE\"), zone_key2=ZoneKey(\"FI\"), session=session\n    )\n\n\ndef test_fetch_exchange_forecast_with_aggregated_exchanges(adapter, session, snapshot):\n    imports_AC = base_path_to_mock / \"FR-COR_IT-SAR_AC_exchange_forecast_imports.xml\"\n    exports_AC = base_path_to_mock / \"FR-COR_IT-SAR_AC_exchange_forecast_exports.xml\"\n    imports_DC = base_path_to_mock / \"FR-COR_IT-SAR_DC_exchange_forecast_imports.xml\"\n    exports_DC = base_path_to_mock / \"FR-COR_IT-SAR_DC_exchange_forecast_exports.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10Y1001A1001A885&out_Domain=10Y1001A1001A74G\",\n        content=imports_AC.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10Y1001A1001A74G&out_Domain=10Y1001A1001A885\",\n        content=exports_AC.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10Y1001A1001A893&out_Domain=10Y1001A1001A74G\",\n        content=imports_DC.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A09&in_Domain=10Y1001A1001A74G&out_Domain=10Y1001A1001A893\",\n        content=exports_DC.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_exchange_forecast(\n        zone_key1=ZoneKey(\"FR-COR\"),\n        zone_key2=ZoneKey(\"IT-SAR\"),\n        session=session,\n    )\n\n\ndef test_wind_and_solar_forecasts(adapter, session, snapshot):\n    day_ahead = base_path_to_mock / \"wind_solar_forecast_FI_DAY_AHEAD.xml\"\n    intraday = base_path_to_mock / \"wind_solar_forecast_FI_INTRADAY.xml\"\n    current = base_path_to_mock / \"wind_solar_forecast_FI_CURRENT.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A69&processType=A01\",\n        content=day_ahead.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A69&processType=A40\",\n        content=intraday.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A69&processType=A18\",\n        content=current.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_wind_solar_forecasts(ZoneKey(\"FI\"), session)\n\n\n@pytest.mark.parametrize(\n    (\"fetcher\", \"mock_filename\"),\n    [\n        (\n            ENTSOE.fetch_wind_solar_forecasts_day_ahead,\n            \"wind_solar_forecast_FI_DAY_AHEAD.xml\",\n        ),\n        (\n            ENTSOE.fetch_wind_solar_forecasts_intraday,\n            \"wind_solar_forecast_FI_INTRADAY.xml\",\n        ),\n        (\n            ENTSOE.fetch_wind_solar_forecasts_current,\n            \"wind_solar_forecast_FI_CURRENT.xml\",\n        ),\n    ],\n    ids=[\"day_ahead\", \"intraday\", \"current\"],\n)\ndef test_wind_and_solar_forecasts_by_type(\n    adapter, session, snapshot, fetcher, mock_filename\n):\n    data = base_path_to_mock / mock_filename\n    adapter.register_uri(GET, ANY, content=data.read_bytes())\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetcher(\n        ZoneKey(\"FI\"), session\n    )\n\n\ndef test_fetch_uses_normal_url(adapter, session):\n    os.environ[\"ENTSOE_TOKEN\"] = \"proxy\"\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/ENTSOE/FR_prices.xml\", \"rb\"\n    ) as price_fr_data:\n        adapter.register_uri(\n            GET,\n            ENTSOE.ENTSOE_URL,\n            content=price_fr_data.read(),\n        )\n    ENTSOE.fetch_price(ZoneKey(\"DE\"), session)\n\n\ndef test_refetch_frequency():\n    func = fetch_production\n\n    assert func.__name__ == \"fetch_production\"\n\n\n# Below are tests for the time series parsing functions.\n\n\ndef _make_soup(xml: str):\n    return BeautifulSoup(xml, \"html.parser\")\n\n\ndef test_a01_timeseries_parsing_production_and_consumption():\n    \"\"\"A01 curve: simple per-position points. Check datetimes and sign handling for production_parsing.\"\"\"\n    xml = \"\"\"\n    <timeseries>\n      <curvetype>A01</curvetype>\n      <inbiddingzone_domain.mrid>TEST</inbiddingzone_domain.mrid>\n      <period>\n        <start>2023-01-01T00:00:00Z</start>\n        <end>2023-01-01T02:00:00Z</end>\n        <resolution>PT60M</resolution>\n        <point>\n          <position>1</position>\n          <quantity>10</quantity>\n        </point>\n        <point>\n          <position>2</position>\n          <quantity>20</quantity>\n        </point>\n      </period>\n    </timeseries>\n    \"\"\"\n\n    soup = _make_soup(xml)\n    ts = soup.find(\"timeseries\")\n\n    results = list(\n        _get_datetime_value_from_timeseries(ts, \"quantity\", production_parsing=True)\n    )\n\n    assert len(results) == 2\n\n    dt0_expected = datetime.fromisoformat(zulu_to_utc(\"2023-01-01T00:00:00Z\"))\n    dt1_expected = dt0_expected + timedelta(hours=1)\n\n    assert results[0][0] == dt0_expected and results[0][1] == 10.0\n    assert results[1][0] == dt1_expected and results[1][1] == 20.0\n\n    # Now test consumption (no inbidding tag) becomes negative when production_parsing=True\n    xml_consumption = xml.replace(\n        \"<inbiddingzone_domain.mrid>TEST</inbiddingzone_domain.mrid>\", \"\"\n    )\n    soup2 = _make_soup(xml_consumption)\n    ts2 = soup2.find(\"timeseries\")\n    results2 = list(\n        _get_datetime_value_from_timeseries(ts2, \"quantity\", production_parsing=True)\n    )\n    assert results2[0][1] == -10.0\n    assert results2[1][1] == -20.0\n\n\ndef test_a03_curve_compression_expands_segments_correctly():\n    \"\"\"A03 curve: compressed segments. Frame start positions indicate start of a constant segment up to next frame start.\"\"\"\n    # We'll create two frames: frame at position 1 value 10, frame at position 3 value 20\n    # With resolution PT60M and start 2023-01-01T00:00:00Z this should yield:\n    # pos1 -> 00:00 value 10\n    # pos2 -> 01:00 value 10 (filled from frame 1)\n    # pos3 -> 02:00 value 20 (last frame)\n    xml = \"\"\"\n    <timeseries>\n      <curvetype>A03</curvetype>\n      <period>\n        <start>2023-01-01T00:00:00Z</start>\n        <end>2023-01-01T03:00:00Z</end>\n        <resolution>PT60M</resolution>\n        <point>\n          <position>1</position>\n          <quantity>10</quantity>\n        </point>\n        <point>\n          <position>3</position>\n          <quantity>20</quantity>\n        </point>\n      </period>\n    </timeseries>\n    \"\"\"\n\n    soup = _make_soup(xml)\n    ts = soup.find(\"timeseries\")\n    results = list(\n        _get_datetime_value_from_timeseries(ts, \"quantity\", production_parsing=False)\n    )\n\n    # Expect three datapoints as explained above\n    assert len(results) == 3\n\n    dt0 = datetime.fromisoformat(zulu_to_utc(\"2023-01-01T00:00:00Z\"))\n    assert results[0] == (dt0, 10.0)\n    assert results[1] == (dt0 + timedelta(hours=1), 10.0)\n    assert results[2] == (dt0 + timedelta(hours=2), 20.0)\n\n\ndef test_a03_curve_compression_expands_1_datapoint_correctly():\n    \"\"\"A03 curve: compressed segments. Frame start positions indicate start of a constant segment up to next frame start.\"\"\"\n    # We'll create two frames: frame at position 1 value 10, frame at position 3 value 20\n    # With resolution PT60M and start 2023-01-01T00:00:00Z this should yield:\n    # pos1 -> 00:00 value 10\n    # pos2 -> 01:00 value 10 (filled from frame 1)\n    # pos3 -> 02:00 value 20 (last frame)\n    xml = \"\"\"\n    <timeseries>\n      <curvetype>A03</curvetype>\n      <period>\n        <start>2023-01-01T00:00:00Z</start>\n        <end>2023-01-01T03:00:00Z</end>\n        <resolution>PT60M</resolution>\n        <point>\n          <position>1</position>\n          <quantity>10</quantity>\n        </point>\n      </period>\n    </timeseries>\n    \"\"\"\n\n    soup = _make_soup(xml)\n    ts = soup.find(\"timeseries\")\n    results = list(\n        _get_datetime_value_from_timeseries(ts, \"quantity\", production_parsing=False)\n    )\n\n    # Expect three datapoints as explained above\n    assert len(results) == 3\n\n    dt0 = datetime.fromisoformat(zulu_to_utc(\"2023-01-01T00:00:00Z\"))\n    assert results[0] == (dt0, 10.0)\n    assert results[1] == (dt0 + timedelta(hours=1), 10.0)\n    assert results[2] == (dt0 + timedelta(hours=2), 10.0)\n\n\n@pytest.mark.parametrize(\n    \"fixture\",\n    [\n        \"fake_time_series.xml\",\n        \"fake_time_series_all_0.xml\",\n    ],\n)\ndef test_a03_curve_decompression(fixture, snapshot):\n    \"\"\"A03 curve: compressed segments. Full example from ENTSOE with production data.\"\"\"\n    soup = _make_soup(Path(base_path_to_mock, fixture).read_text())\n    ts = soup.find(\"timeseries\")\n    results = list(\n        _get_datetime_value_from_timeseries(ts, \"quantity\", production_parsing=True)\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == results\n\n\n# ─── parse_exchange_capacity_forecast ────────────────────────────────────────\n\n\ndef test_parse_exchange_capacity_forecast_week_ahead_export_direction():\n    \"\"\"export direction populates capacityExport, leaves capacityImport None.\"\"\"\n    xml = (\n        base_path_to_mock / \"DK-DK1_DK-DK2_capacity_week_ahead_export.xml\"\n    ).read_text()\n    logger = logging.getLogger(\"test\")\n    result = parse_exchange_capacity_forecast(\n        xml, ZoneKey(\"DK-DK1->DK-DK2\"), logger, direction=\"export\"\n    )\n    events = result.events\n    assert len(events) == 40\n    dt0 = datetime(2026, 2, 16, 23, 0, tzinfo=timezone.utc)\n    assert events[0].datetime == dt0\n    assert events[0].capacityExport == 600.0\n    assert events[0].capacityImport is None\n    assert events[1].datetime == dt0 + timedelta(days=1)\n    assert events[1].capacityExport == 600.0\n    assert events[1].capacityImport is None\n    assert events[0].sourceType == EventSourceType.published\n\n\ndef test_parse_exchange_capacity_forecast_week_ahead_import_direction():\n    \"\"\"Import direction populates capacityImport, leaves capacityExport None.\"\"\"\n    xml = (\n        base_path_to_mock / \"DK-DK1_DK-DK2_capacity_week_ahead_import.xml\"\n    ).read_text()\n    logger = logging.getLogger(\"test\")\n    result = parse_exchange_capacity_forecast(\n        xml, ZoneKey(\"DK-DK1->DK-DK2\"), logger, direction=\"import\"\n    )\n    events = result.events\n    assert len(events) == 40\n    assert events[0].capacityImport == 450.0\n    assert events[0].capacityExport is None\n    assert events[1].capacityImport == 450.0\n    assert events[1].capacityExport is None\n\n\ndef test_parse_exchange_capacity_forecast_day_ahead_export_direction():\n    \"\"\"export direction populates capacityExport, leaves capacityImport None.\"\"\"\n    xml = (base_path_to_mock / \"ES_FR_capacity_day_ahead_export.xml\").read_text()\n    logger = logging.getLogger(\"test\")\n    result = parse_exchange_capacity_forecast(\n        xml, ZoneKey(\"ES->FR\"), logger, direction=\"export\"\n    )\n    events = result.events\n    assert len(events) == 41\n    dt0 = datetime(2026, 3, 19, 6, 0, tzinfo=timezone.utc)\n    assert events[0].datetime == dt0\n    assert events[0].capacityExport == 3006.0\n    assert events[0].capacityImport is None\n    assert events[1].datetime == dt0 + timedelta(hours=1)\n    assert events[1].capacityExport == 3006.0\n    assert events[1].capacityImport is None\n    assert events[4].capacityExport == 2914.0\n    assert events[-1].capacityExport == 3607.0\n    assert events[0].sourceType == EventSourceType.published\n\n\ndef test_parse_exchange_capacity_forecast_month_ahead_import_direction():\n    \"\"\"import direction populates capacityImport, leaves capacityExport None.\"\"\"\n    xml = (base_path_to_mock / \"ES_FR_capacity_month_ahead_import.xml\").read_text()\n    logger = logging.getLogger(\"test\")\n    result = parse_exchange_capacity_forecast(\n        xml, ZoneKey(\"ES->FR\"), logger, direction=\"import\"\n    )\n    events = result.events\n    assert len(events) == 62\n    dt0 = datetime(2026, 3, 16, 23, 0, tzinfo=timezone.utc)\n    assert events[0].datetime == dt0\n    assert events[0].capacityExport is None\n    assert events[0].capacityImport == 2150.0\n    assert events[1].datetime == dt0 + timedelta(days=1)\n    assert events[1].capacityExport is None\n    assert events[1].capacityImport == 2150.0\n    assert events[2].capacityImport == 2400.0\n    assert events[0].sourceType == EventSourceType.published\n\n\ndef test_parse_exchange_capacity_forecast_empty_xml():\n    \"\"\"Empty XML (no TimeSeries) returns an empty list.\"\"\"\n    logger = logging.getLogger(\"test\")\n    result = parse_exchange_capacity_forecast(\n        \"<root></root>\", ZoneKey(\"AT->DE\"), logger, direction=\"export\"\n    )\n    assert result.events == []\n\n\ndef test_parse_exchange_capacity_forecast_multiple_timeseries():\n    \"\"\"Multiple TimeSeries blocks are all parsed.\"\"\"\n    xml = \"\"\"\n    <root>\n      <TimeSeries>\n        <curveType>A03</curveType>\n        <Period>\n          <start>2023-01-01T00:00Z</start>\n          <end>2023-01-01T01:00Z</end>\n          <resolution>PT60M</resolution>\n          <Point><position>1</position><quantity>100</quantity></Point>\n        </Period>\n      </TimeSeries>\n      <TimeSeries>\n        <curveType>A03</curveType>\n        <Period>\n          <start>2023-01-01T01:00Z</start>\n          <end>2023-01-01T02:00Z</end>\n          <resolution>PT60M</resolution>\n          <Point><position>1</position><quantity>200</quantity></Point>\n        </Period>\n      </TimeSeries>\n    </root>\n    \"\"\"\n    logger = logging.getLogger(\"test\")\n    result = parse_exchange_capacity_forecast(\n        xml, ZoneKey(\"AT->DE\"), logger, direction=\"export\"\n    )\n    assert len(result.events) == 2\n    assert result.events[0].capacityExport == 100.0\n    assert result.events[1].capacityExport == 200.0\n\n\n# ─── _merge_exchange_capacity_forecasts ──────────────────────────────────────\n\n\ndef _make_capacity_list(\n    zone_key: ZoneKey,\n    datetimes: list[datetime],\n    forward: list[float | None],\n    reverse: list[float | None],\n) -> ExchangeCapacityList:\n    logger = logging.getLogger(\"test\")\n    lst = ExchangeCapacityList(logger)\n    for dt, fwd, rev in zip(datetimes, forward, reverse, strict=True):\n        lst.append(\n            zoneKey=zone_key,\n            datetime=dt,\n            source=\"entsoe.eu\",\n            capacityExport=fwd,\n            capacityImport=rev,\n        )\n    return lst\n\n\ndef test_merge_exchange_capacity_forecasts_both_directions():\n    \"\"\"Both directions present for same datetimes → merged event has both capacities.\"\"\"\n    logger = logging.getLogger(\"test\")\n    dt1 = datetime(2023, 1, 1, 0, 0, tzinfo=timezone.utc)\n    dt2 = datetime(2023, 1, 1, 1, 0, tzinfo=timezone.utc)\n    zone_key = ZoneKey(\"AT->DE\")\n\n    forward = _make_capacity_list(zone_key, [dt1, dt2], [600.0, 500.0], [None, None])\n    reverse = _make_capacity_list(zone_key, [dt1, dt2], [None, None], [400.0, 350.0])\n\n    merged = _merge_exchange_capacity_forecasts(forward, reverse, logger)\n    events = merged.events\n\n    assert len(events) == 2\n    assert events[0].datetime == dt1\n    assert events[0].capacityExport == 600.0\n    assert events[0].capacityImport == 400.0\n    assert events[1].datetime == dt2\n    assert events[1].capacityExport == 500.0\n    assert events[1].capacityImport == 350.0\n\n\ndef test_merge_exchange_capacity_forecasts_only_forward():\n    \"\"\"Only forward data → merged events have capacityImport=None.\"\"\"\n    logger = logging.getLogger(\"test\")\n    dt = datetime(2023, 1, 1, 0, 0, tzinfo=timezone.utc)\n    zone_key = ZoneKey(\"AT->DE\")\n\n    forward = _make_capacity_list(zone_key, [dt], [600.0], [None])\n    reverse = ExchangeCapacityList(logger)\n\n    merged = _merge_exchange_capacity_forecasts(forward, reverse, logger)\n    events = merged.events\n\n    assert len(events) == 1\n    assert events[0].capacityExport == 600.0\n    assert events[0].capacityImport is None\n\n\ndef test_merge_exchange_capacity_forecasts_only_reverse():\n    \"\"\"Only reverse data → merged events have capacityExport=None.\"\"\"\n    logger = logging.getLogger(\"test\")\n    dt = datetime(2023, 1, 1, 0, 0, tzinfo=timezone.utc)\n    zone_key = ZoneKey(\"AT->DE\")\n\n    forward = ExchangeCapacityList(logger)\n    reverse = _make_capacity_list(zone_key, [dt], [None], [400.0])\n\n    merged = _merge_exchange_capacity_forecasts(forward, reverse, logger)\n    events = merged.events\n\n    assert len(events) == 1\n    assert events[0].capacityExport is None\n    assert events[0].capacityImport == 400.0\n\n\ndef test_merge_exchange_capacity_forecasts_non_overlapping_datetimes():\n    \"\"\"Non-overlapping datetime sets → all datetimes present in merged result.\"\"\"\n    logger = logging.getLogger(\"test\")\n    dt1 = datetime(2023, 1, 1, 0, 0, tzinfo=timezone.utc)\n    dt2 = datetime(2023, 1, 1, 1, 0, tzinfo=timezone.utc)\n    zone_key = ZoneKey(\"AT->DE\")\n\n    forward = _make_capacity_list(zone_key, [dt1], [600.0], [None])\n    reverse = _make_capacity_list(zone_key, [dt2], [None], [400.0])\n\n    merged = _merge_exchange_capacity_forecasts(forward, reverse, logger)\n    events = merged.events\n\n    assert len(events) == 2\n    assert events[0].datetime == dt1\n    assert events[0].capacityExport == 600.0\n    assert events[0].capacityImport is None\n    assert events[1].datetime == dt2\n    assert events[1].capacityExport is None\n    assert events[1].capacityImport == 400.0\n\n\ndef test_merge_exchange_capacity_forecasts_prefers_forward_zone_key():\n    \"\"\"When both directions exist, zone key and source are taken from the forward event.\"\"\"\n    logger = logging.getLogger(\"test\")\n    dt = datetime(2023, 1, 1, 0, 0, tzinfo=timezone.utc)\n    zone_key = ZoneKey(\"AT->DE\")\n\n    forward = _make_capacity_list(zone_key, [dt], [600.0], [None])\n    reverse = _make_capacity_list(zone_key, [dt], [None], [400.0])\n\n    merged = _merge_exchange_capacity_forecasts(forward, reverse, logger)\n    assert merged.events[0].zoneKey == zone_key\n    assert merged.events[0].source == \"entsoe.eu\"\n\n\ndef test_fetch_exchange_capacity_forecasts_day_ahead(adapter, session, snapshot):\n    export_data = base_path_to_mock / \"ES_FR_capacity_day_ahead_export.xml\"\n    import_data = base_path_to_mock / \"ES_FR_capacity_day_ahead_import.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A61&Contract_MarketAgreement.Type=A01&in_Domain=10YES-REE------0&out_Domain=10YFR-RTE------C\",\n        content=export_data.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A61&Contract_MarketAgreement.Type=A01&in_Domain=10YFR-RTE------C&out_Domain=10YES-REE------0\",\n        content=import_data.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_exchange_capacity_forecasts_day_ahead(\n        zone_key1=ZoneKey(\"ES\"),\n        zone_key2=ZoneKey(\"FR\"),\n        session=session,\n    )\n\n\ndef test_fetch_exchange_capacity_forecasts_week_ahead(adapter, session, snapshot):\n    export_data = base_path_to_mock / \"DK-DK1_DK-DK2_capacity_week_ahead_export.xml\"\n    import_data = base_path_to_mock / \"DK-DK1_DK-DK2_capacity_week_ahead_import.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A61&Contract_MarketAgreement.Type=A02&in_Domain=10YDK-1--------W&out_Domain=10YDK-2--------M\",\n        content=export_data.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A61&Contract_MarketAgreement.Type=A02&in_Domain=10YDK-2--------M&out_Domain=10YDK-1--------W\",\n        content=import_data.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_exchange_capacity_forecasts_week_ahead(\n        zone_key1=ZoneKey(\"DK-DK1\"),\n        zone_key2=ZoneKey(\"DK-DK2\"),\n        session=session,\n    )\n\n\ndef test_fetch_exchange_capacity_forecasts_month_ahead(adapter, session, snapshot):\n    export_data = base_path_to_mock / \"ES_FR_capacity_month_ahead_export.xml\"\n    import_data = base_path_to_mock / \"ES_FR_capacity_month_ahead_import.xml\"\n\n    adapter.register_uri(\n        GET,\n        \"?documentType=A61&Contract_MarketAgreement.Type=A03&in_Domain=10YES-REE------0&out_Domain=10YFR-RTE------C\",\n        content=export_data.read_bytes(),\n    )\n    adapter.register_uri(\n        GET,\n        \"?documentType=A61&Contract_MarketAgreement.Type=A03&in_Domain=10YFR-RTE------C&out_Domain=10YES-REE------0\",\n        content=import_data.read_bytes(),\n    )\n\n    assert snapshot == ENTSOE.fetch_exchange_capacity_forecasts_month_ahead(\n        zone_key1=ZoneKey(\"ES\"),\n        zone_key2=ZoneKey(\"FR\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ERCOT.py",
    "content": "import json\nimport logging\nfrom datetime import datetime\nfrom unittest.mock import patch\nfrom zoneinfo import ZoneInfo\n\nimport pytest\nfrom testfixtures import LogCapture\n\nfrom electricitymap.contrib.parsers import US_ERCOT\n\n\ndef test_fetch_production():\n    with open(\"electricitymap/contrib/parsers/tests/mocks/ERCOT_generation.json\") as f:\n        fake_generation_data = json.load(f)\n\n    with open(\"electricitymap/contrib/parsers/tests/mocks/ERCOT_storage.json\") as f:\n        fake_storage_data = json.load(f)\n\n    def mock_get_data(url, **kwargs):\n        if \"energy-storage-resources\" in url:\n            return fake_storage_data\n        else:\n            return fake_generation_data\n\n    with patch(\"electricitymap.contrib.parsers.US_ERCOT.get_data\") as gjd:\n        gjd.side_effect = mock_get_data\n        data = US_ERCOT.fetch_production(logger=logging.getLogger(\"test\"))\n    assert data\n\n    assert data[-1][\"source\"] == \"ercot.com\"\n    assert data[-1][\"zoneKey\"] == \"US-TEX-ERCO\"\n\n    # Check that storage data is present and contains battery\n    assert isinstance(data[-1][\"storage\"], dict)\n    assert \"battery\" in data[-1][\"storage\"]\n    assert isinstance(data[-1][\"storage\"][\"battery\"], int | float)\n\n    # Verify that there are data points from 2 days (previousDay and currentDay)\n    dates = {item[\"datetime\"].date() for item in data}\n    assert len(dates) == 2, (\n        f\"Expected data from exactly 2 days, but got {len(dates)} days: {dates}\"\n    )\n\n\ndef test_fetch_consumption():\n    with open(\"electricitymap/contrib/parsers/tests/mocks/ERCOT_demand.json\") as f:\n        fake_data = json.load(f)\n    with LogCapture(), patch(\"electricitymap.contrib.parsers.US_ERCOT.get_data\") as gjd:\n        gjd.return_value = fake_data\n        data = US_ERCOT.fetch_consumption(logger=logging.getLogger(\"test\"))\n\n        assert data\n        assert data[0][\"consumption\"] == 42015.44\n        assert data[0][\"datetime\"] == datetime(\n            2024, 11, 24, 0, 0, tzinfo=ZoneInfo(\"US/Central\")\n        )\n        assert data[0][\"source\"] == \"ercot.com\"\n        assert data[0][\"zoneKey\"] == \"US-TEX-ERCO\"\n\n\ndef test_fetch_production_with_target_datetime_raises_not_implemented():\n    \"\"\"Test that fetch_production raises NotImplementedError when target_datetime is provided.\"\"\"\n    target_datetime = datetime(2024, 1, 1, 12, 0, tzinfo=ZoneInfo(\"US/Central\"))\n\n    with pytest.raises(\n        NotImplementedError, match=\"This parser is not yet able to parse past dates.\"\n    ):\n        US_ERCOT.fetch_production(\n            target_datetime=target_datetime, logger=logging.getLogger(\"test\")\n        )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ERP_PGCB.py",
    "content": "from datetime import datetime\nfrom importlib import resources\n\nimport pytest\nfrom requests_mock import ANY, GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.ERP_PGCB import (\n    fetch_consumption,\n    fetch_exchange,\n    fetch_production,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nhistorical_dt = datetime.fromisoformat(\"2025-01-01 00:00:00 +06:00\")\n\n\ndef _load_mock_response(adapter, target_datetime):\n    mock_data_file = \"latest.html\"\n    if target_datetime:\n        mock_data_file = \"historical.html\"\n\n    adapter.register_uri(\n        GET,\n        ANY,\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks.ERP_PGCB\")\n        .joinpath(mock_data_file)\n        .read_text(),\n    )\n\n\n@pytest.mark.parametrize(\"target_datetime\", [None, historical_dt])\ndef test_fetch_consumption(adapter, session, snapshot, target_datetime):\n    _load_mock_response(adapter, target_datetime)\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_consumption(session=session)\n\n\n@pytest.mark.parametrize(\"target_datetime\", [None, historical_dt])\ndef test_exchanges(adapter, session, snapshot, target_datetime):\n    _load_mock_response(adapter, target_datetime)\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetch_exchange(\n        ZoneKey(\"BD\"), ZoneKey(\"IN-NE\"), session=session\n    )\n\n\n@pytest.mark.parametrize(\"target_datetime\", [None, historical_dt])\ndef test_fetch_production(adapter, session, snapshot, target_datetime):\n    _load_mock_response(adapter, target_datetime)\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_production(session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ES.py",
    "content": "from datetime import datetime\n\nimport pytest\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers import ES\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    # these json files are not in valid json format\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/ES/demandaGeneracionPeninsula.json\",\n        \"rb\",\n    ) as data:\n        adapter.register_uri(\n            GET,\n            ES.get_url(ZoneKey(\"ES\"), \"2024-10-26\"),\n            content=data.read(),\n        )\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/ES/demandaGeneracionBaleares.json\",\n        \"rb\",\n    ) as data:\n        adapter.register_uri(\n            GET,\n            ES.get_url(ZoneKey(\"ES-IB-MA\"), \"2024-10-26\"),\n            content=data.read(),\n        )\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/ES/demandaGeneracionCanarias.json\",\n        \"rb\",\n    ) as data:\n        adapter.register_uri(\n            GET,\n            ES.get_url(ZoneKey(\"ES-CN-TE\"), \"2024-10-26\"),\n            content=data.read(),\n        )\n\n\n### Iberian Peninsula (ES) Consumption\ndef test_es_consumption(adapter, session, snapshot):\n    assert snapshot == ES.fetch_consumption(\n        ZoneKey(\"ES\"), session, datetime.fromisoformat(\"2024-10-26\")\n    )\n\n\n### Iberian Peninsula (ES) Production with DST Tests\ndef test_es_production(adapter, session, snapshot):\n    assert snapshot == ES.fetch_production(\n        ZoneKey(\"ES\"), session, datetime.fromisoformat(\"2024-10-26\")\n    )\n\n\n### ES->PT exchange\ndef test_es_pt_exchange(adapter, session, snapshot):\n    assert snapshot == ES.fetch_exchange(\n        ZoneKey(\"ES\"),\n        ZoneKey(\"PT\"),\n        session,\n        datetime.fromisoformat(\"2024-10-26\"),\n    )\n\n\n### Mallorca Consumption\ndef test_es_ib_ma_consumption(adapter, session, snapshot):\n    assert snapshot == ES.fetch_consumption(\n        ZoneKey(\"ES-IB-MA\"), session, datetime.fromisoformat(\"2024-10-26\")\n    )\n\n\n### Mallorca Production with DST Tests\ndef test_es_ib_ma_production(adapter, session, snapshot):\n    assert snapshot == ES.fetch_production(\n        ZoneKey(\"ES-IB-MA\"), session, datetime.fromisoformat(\"2024-10-26\")\n    )\n\n\n### Ibiza->Mallorca exchange\ndef test_es_ib_ma_exchange(adapter, session, snapshot):\n    assert snapshot == ES.fetch_exchange(\n        ZoneKey(\"ES-IB-IZ\"),\n        ZoneKey(\"ES-IB-MA\"),\n        session,\n        datetime.fromisoformat(\"2024-10-26\"),\n    )\n\n\n### Tenerife Consumption\ndef test_es_cn_te_consumption(adapter, session, snapshot):\n    assert snapshot == ES.fetch_consumption(\n        ZoneKey(\"ES-CN-TE\"), session, datetime.fromisoformat(\"2024-10-26\")\n    )\n\n\n### Tenerife Production with DST Tests\ndef test_es_cn_te_production(adapter, session, snapshot):\n    assert snapshot == ES.fetch_production(\n        ZoneKey(\"ES-CN-TE\"), session, datetime.fromisoformat(\"2024-10-26\")\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ESIOS.py",
    "content": "import json\nimport os\nfrom importlib import resources\n\nfrom requests_mock import ANY\n\nfrom electricitymap.contrib.parsers import ESIOS\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_fetch_exchange(adapter, session):\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n            .joinpath(\"ESIOS_ES_MA.json\")\n            .read_text()\n        ),\n    )\n    os.environ[\"ESIOS_TOKEN\"] = \"token\"\n    data_list = ESIOS.fetch_exchange(ZoneKey(\"ES\"), ZoneKey(\"MA\"), session)\n    assert data_list is not None\n    for data in data_list:\n        assert data[\"sortedZoneKeys\"] == \"ES->MA\"\n        assert data[\"source\"] == \"api.esios.ree.es\"\n        assert data[\"datetime\"] is not None\n        assert data[\"netFlow\"] is not None\n\n\ndef test_exchange_with_snapshot(session, adapter, snapshot):\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n            .joinpath(\"ESIOS_ES_MA.json\")\n            .read_text()\n        ),\n    )\n    os.environ[\"ESIOS_TOKEN\"] = \"token\"\n    assert snapshot == ESIOS.fetch_exchange(ZoneKey(\"ES\"), ZoneKey(\"MA\"), session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ESKOM.py",
    "content": "import freezegun\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.ESKOM import fetch_production, get_url\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@freezegun.freeze_time(\"2023-09-22\")\ndef test_production(adapter, session, snapshot):\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/ESKOM/Station_Build_Up.csv\", \"rb\"\n    ) as mock_file:\n        adapter.register_uri(\n            GET,\n            get_url(),\n            content=mock_file.read(),\n        )\n\n    assert snapshot == fetch_production(zone_key=ZoneKey(\"ZA\"), session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ESTADISTICO_UT.py",
    "content": "from datetime import datetime\nfrom importlib import resources\n\nfrom requests_mock import GET, POST\n\nfrom electricitymap.contrib.parsers.ESTADISTICO_UT import (\n    DAILY_OPERATION_URL,\n    ZONE_INFO,\n    fetch_production,\n)\n\n\ndef test_fetch_production_live(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        DAILY_OPERATION_URL,\n        text=resources.files(\n            \"electricitymap.contrib.parsers.tests.mocks.ESTADISTICO_UT\"\n        )\n        .joinpath(\"get_live.html\")\n        .read_text(),\n    )\n    adapter.register_uri(\n        POST,\n        DAILY_OPERATION_URL,\n        text=resources.files(\n            \"electricitymap.contrib.parsers.tests.mocks.ESTADISTICO_UT\"\n        )\n        .joinpath(\"post_live.html\")\n        .read_text(),\n    )\n    assert snapshot == fetch_production(session=session)\n\n\ndef test_fetch_production_historical(adapter, session, snapshot):\n    dt = datetime.fromisoformat(\"2025-01-01\").replace(tzinfo=ZONE_INFO)\n\n    adapter.register_uri(\n        GET,\n        DAILY_OPERATION_URL,\n        text=resources.files(\n            \"electricitymap.contrib.parsers.tests.mocks.ESTADISTICO_UT\"\n        )\n        .joinpath(\"get_historical.html\")\n        .read_text(),\n    )\n    adapter.register_uri(\n        POST,\n        DAILY_OPERATION_URL,\n        text=resources.files(\n            \"electricitymap.contrib.parsers.tests.mocks.ESTADISTICO_UT\"\n        )\n        .joinpath(\"post_historical.html\")\n        .read_text(),\n    )\n\n    assert snapshot == fetch_production(session=session, target_datetime=dt)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_FO.py",
    "content": "import json\nfrom datetime import datetime, timezone\nfrom importlib import resources\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import ANY, GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.FO import fetch_production\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@freeze_time(\"2024-05-16 12:04:00\")\n@pytest.mark.parametrize(\"zone\", [\"FO\", \"FO-MI\", \"FO-SI\"])\ndef test_fetch_production_live(adapter, session, snapshot, zone):\n    \"\"\"That the parser fetches expected production values.\"\"\"\n\n    adapter.register_uri(\n        GET,\n        ANY,\n        response_list=[\n            {\n                \"json\": json.loads(\n                    resources.files(\"electricitymap.contrib.parsers.tests.mocks.FO\")\n                    .joinpath(asset)\n                    .read_text()\n                )\n            }\n            for asset in [\"sev_api_live_0.json\", \"sev_api_live_1.json\"]\n        ],\n    )\n\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_production(ZoneKey(zone), session=session)\n\n\n@pytest.mark.parametrize(\"zone\", [\"FO\", \"FO-MI\", \"FO-SI\"])\n@pytest.mark.parametrize(\"utc_offset\", [\"SDT\", \"DST\"])\ndef test_fetch_production_historical(adapter, session, snapshot, zone, utc_offset):\n    \"\"\"That the parser fetches expected historical values.\n\n    Given that API responses differ depending on whether SDT or DST apply for the target date, we also make sure\n    that we handle both cases correctly.\n    \"\"\"\n\n    month = 2 if utc_offset == \"SDT\" else 7\n    target_datetime = datetime(2023, month, 16, 12, tzinfo=timezone.utc)\n\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.FO\")\n            .joinpath(f\"sev_api_historical_{target_datetime.strftime('%Y_%m_%d')}.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_production(\n        ZoneKey(zone), target_datetime=target_datetime, session=session\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_FR.py",
    "content": "import os\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.FR import API_ENDPOINT, fetch_production\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_production(adapter, session, snapshot):\n    os.environ[\"RESEAUX_ENERGIES_TOKEN\"] = \"test_token\"\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/FR/response.json\", \"rb\"\n    ) as mock_file:\n        adapter.register_uri(\n            GET,\n            API_ENDPOINT,\n            content=mock_file.read(),\n        )\n\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"FR\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_FR_O.py",
    "content": "import json\nfrom datetime import datetime\nfrom importlib import resources\n\nfrom requests_mock import ANY\n\nfrom electricitymap.contrib.parsers import FR_O\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_fetch_exchange(adapter, session):\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.FR_O\")\n            .joinpath(\"FR_GP.json\")\n            .read_text()\n        ),\n    )\n    data_list = FR_O.fetch_production(\"GP\", session)\n    assert data_list is not None\n    expected_data = [\n        {\n            \"zoneKey\": \"GP\",\n            \"production\": {\n                \"gas\": 1,\n                \"coal\": 2,\n                \"oil\": 3,\n                \"hydro\": 4,\n                \"geothermal\": 5,\n                \"wind\": 6,\n                \"solar\": 7,\n                \"biomass\": 8,\n            },\n            \"storage\": {},\n        },\n        {\n            \"zoneKey\": \"GP\",\n            \"production\": {\n                \"gas\": 10,\n                \"coal\": 11,\n                \"oil\": 12,\n                \"hydro\": 13,\n                \"geothermal\": 14,\n                \"wind\": 15,\n                \"solar\": 16,\n                \"biomass\": 17,\n            },\n            \"storage\": {},\n        },\n    ]\n    assert len(data_list) == len(expected_data)\n    for index, actual in enumerate(data_list):\n        assert actual[\"zoneKey\"] == \"GP\"\n        assert actual[\"source\"] == \"opendata-guadeloupe.edf.fr\"\n        for production_type, production in actual[\"production\"].items():\n            assert production, expected_data[index][\"production\"][production_type]\n\n\ndef test_fetch_price(adapter, session):\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.FR_O\")\n            .joinpath(\"FR_RE.json\")\n            .read_text()\n        ),\n    )\n    data_list = FR_O.fetch_price(ZoneKey(\"RE\"), session, datetime(2018, 1, 1))\n    assert data_list is not None\n    expected_data = [\n        {\n            \"zoneKey\": \"RE\",\n            \"currency\": \"EUR\",\n            \"datetime\": datetime.fromisoformat(\"2018-01-01T00:00:00+00:00\"),\n            \"source\": \"opendata.edf.fr\",\n            \"price\": 193.7,\n        },\n        {\n            \"zoneKey\": \"RE\",\n            \"currency\": \"EUR\",\n            \"datetime\": datetime.fromisoformat(\"2018-01-01T01:00:00+00:00\"),\n            \"source\": \"opendata.edf.fr\",\n            \"price\": 195.8,\n        },\n    ]\n    assert len(data_list) == len(expected_data)\n    for index, actual in enumerate(data_list):\n        assert actual[\"zoneKey\"] == expected_data[index][\"zoneKey\"]\n        assert actual[\"currency\"] == expected_data[index][\"currency\"]\n        assert actual[\"datetime\"] == expected_data[index][\"datetime\"]\n        assert actual[\"source\"] == expected_data[index][\"source\"]\n        assert actual[\"price\"] == expected_data[index][\"price\"]\n\n\ndef test_fetch_production(adapter, session):\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.FR_O\")\n            .joinpath(\"FR_COR.json\")\n            .read_text(encoding=\"utf-8\")\n        ),\n    )\n    data_list = FR_O.fetch_production(ZoneKey(\"FR-COR\"), session)\n    assert data_list is not None\n    expected_production_data = [\n        {\n            \"correctedModes\": [],\n            \"datetime\": datetime.fromisoformat(\"2024-12-15T10:45:00+00:00\"),\n            \"production\": {\n                \"biomass\": 2.0,\n                \"gas\": 0.0,\n                \"hydro\": 26.7,\n                \"oil\": 105.2,\n                \"solar\": 103.8,\n                \"wind\": 0.0,\n            },\n            \"source\": \"opendata-corse.edf.fr\",\n            \"sourceType\": \"estimated\",\n            \"storage\": {\"battery\": -0.0},\n            \"zoneKey\": \"FR-COR\",\n        },\n        {\n            \"correctedModes\": [],\n            \"datetime\": datetime.fromisoformat(\"2024-12-15T11:00:00+00:00\"),\n            \"zoneKey\": \"FR-COR\",\n            \"production\": {\n                \"biomass\": 2.0,\n                \"gas\": 0.0,\n                \"hydro\": 25.8,\n                \"oil\": 105.3,\n                \"solar\": 104.1,\n                \"wind\": 0.0,\n            },\n            \"storage\": {\"battery\": -0.0},\n            \"source\": \"opendata-corse.edf.fr\",\n            \"sourceType\": \"estimated\",\n        },\n    ]\n    assert len(data_list) == len(expected_production_data)\n    for index, actual in enumerate(data_list):\n        assert actual[\"zoneKey\"] == expected_production_data[index][\"zoneKey\"]\n        assert actual[\"source\"] == expected_production_data[index][\"source\"]\n        assert actual[\"sourceType\"] == expected_production_data[index][\"sourceType\"]\n        assert actual[\"datetime\"] == expected_production_data[index][\"datetime\"]\n        assert actual[\"production\"] == expected_production_data[index][\"production\"]\n        assert actual[\"storage\"] == expected_production_data[index][\"storage\"]\n        assert (\n            actual[\"correctedModes\"]\n            == expected_production_data[index][\"correctedModes\"]\n        )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_GB.py",
    "content": "import json\nfrom datetime import datetime, timezone\nfrom importlib import resources\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import ANY, GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.GB import (\n    ELEXON_BMU_FUEL_TYPE_URL,\n    ELEXON_BMU_UNITS,\n    ELEXON_BOALF_STREAM,\n    ELEXON_MELS_STREAM,\n    ELEXON_MILS_STREAM,\n    ELEXON_PN_STREAM,\n    fetch_price,\n    fetch_production,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.mark.parametrize(\n    \"zone_key\", [\"BE\", \"CH\", \"AT\", \"ES\", \"FR\", \"GB\", \"IT\", \"NL\", \"PT\"]\n)\n@freeze_time(\"2024-04-14 15:10:57\")\ndef test_fetch_price_live(adapter, session, snapshot, zone_key):\n    adapter.register_uri(\n        GET,\n        ANY,\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks.GB\")\n        .joinpath(\"eco2mix_api_live.xml\")\n        .read_text(),\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetch_price(\n        zone_key=ZoneKey(zone_key), session=session\n    )\n\n\ndef test_fetch_price_historical(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks.GB\")\n        .joinpath(\"eco2mix_api_historical_20220716.xml\")\n        .read_text(),\n    )\n\n    historical_datetime = datetime(2022, 7, 16, 12, tzinfo=timezone.utc)\n    assert snapshot == fetch_price(target_datetime=historical_datetime, session=session)\n\n\n@freeze_time(\"2024-12-16 12:00:00\")\ndef test_fetch_production(adapter, session, snapshot):\n    neso_mock = resources.files(\"electricitymap.contrib.parsers.tests.mocks.GB\")\n    gb_mock = resources.files(\"electricitymap.contrib.parsers.tests.mocks.GB\")\n\n    adapter.register_uri(\n        GET,\n        \"https://api.neso.energy/api/3/action/datastore_search_sql\",\n        json=json.loads(neso_mock.joinpath(\"production.json\").read_text()),\n    )\n    adapter.register_uri(\n        GET,\n        ELEXON_BMU_UNITS,\n        json=json.loads(gb_mock.joinpath(\"bmunits.json\").read_text()),\n    )\n    bmvalues = json.loads(gb_mock.joinpath(\"bmvalues.json\").read_text())\n    adapter.register_uri(GET, ELEXON_PN_STREAM, json=bmvalues)\n    adapter.register_uri(GET, ELEXON_MELS_STREAM, json=bmvalues)\n    adapter.register_uri(GET, ELEXON_MILS_STREAM, json=bmvalues)\n    adapter.register_uri(\n        GET,\n        ELEXON_BOALF_STREAM,\n        json=json.loads(gb_mock.joinpath(\"boalf.json\").read_text()),\n    )\n    adapter.register_uri(\n        GET,\n        ELEXON_BMU_FUEL_TYPE_URL,\n        content=gb_mock.joinpath(\"bmu_fuel_type.xlsx\").read_bytes(),\n    )\n\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"GB\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_GT.py",
    "content": "import json\nfrom datetime import datetime\nfrom importlib import resources\n\nfrom freezegun import freeze_time\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers.GT import fetch_consumption, fetch_production\n\n\n@freeze_time(\"2024-04-10 12:28:00\")\ndef test_fetch_production_live(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        response_list=[\n            {\n                \"json\": json.loads(\n                    resources.files(\"electricitymap.contrib.parsers.tests.mocks.GT\")\n                    .joinpath(f\"wl12_api_live_{i}.json\")\n                    .read_text()\n                )\n            }\n            for i in range(2)\n        ],\n    )\n\n    assert snapshot == fetch_production(session=session)\n\n\ndef test_fetch_production_historical(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        response_list=[\n            {\n                \"json\": json.loads(\n                    resources.files(\"electricitymap.contrib.parsers.tests.mocks.GT\")\n                    .joinpath(f\"wl12_api_historical_20230716_{i}.json\")\n                    .read_text()\n                )\n            }\n            for i in range(2)\n        ],\n    )\n\n    historical_datetime = datetime.fromisoformat(\"2023-07-16T12:00:00+00:00\")\n\n    assert snapshot == fetch_production(\n        target_datetime=historical_datetime, session=session\n    )\n\n\n@freeze_time(\"2024-04-10 12:28:00\")\ndef test_fetch_consumption_live(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        response_list=[\n            {\n                \"json\": json.loads(\n                    resources.files(\"electricitymap.contrib.parsers.tests.mocks.GT\")\n                    .joinpath(f\"wl12_api_live_{i}.json\")\n                    .read_text()\n                )\n            }\n            for i in range(2)\n        ],\n    )\n\n    assert snapshot == fetch_consumption(session=session)\n\n\ndef test_fetch_consumption_historical(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        response_list=[\n            {\n                \"json\": json.loads(\n                    resources.files(\"electricitymap.contrib.parsers.tests.mocks.GT\")\n                    .joinpath(f\"wl12_api_historical_20230716_{i}.json\")\n                    .read_text()\n                )\n            }\n            for i in range(2)\n        ],\n    )\n\n    historical_datetime = datetime.fromisoformat(\"2023-07-16T12:00:00+00:00\")\n\n    assert snapshot == fetch_consumption(\n        target_datetime=historical_datetime, session=session\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_HN.py",
    "content": "from pathlib import Path\n\nimport pytest\nfrom requests_mock import ANY, GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers import HN\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/HN\")\n\n\ndef test_fetch_production(adapter, session, snapshot):\n    \"\"\"Test production data parsing with snapshot testing.\"\"\"\n    # Mock all production CSV files\n    production_files = [\n        (\"production_index_1_hydro.csv\", 1),\n        (\"production_index_2_wind.csv\", 2),\n        (\"production_index_3_solar.csv\", 3),\n        (\"production_index_4_geothermal.csv\", 4),\n        (\"production_index_5_biomass.csv\", 5),\n        (\"production_index_6_coal.csv\", 6),\n        (\"production_index_8_oil.csv\", 8),\n        (\"production_index_9_oil.csv\", 9),\n        (\"production_index_10_hydro.csv\", 10),\n    ]\n\n    def mock_response(request, context):\n        \"\"\"Mock response based on the p8_indx parameter.\"\"\"\n        index = int(request.qs.get(\"p8_indx\", [0])[0])\n\n        for filename, file_index in production_files:\n            if index == file_index:\n                file_path = base_path_to_mock / filename\n                return file_path.read_text(encoding=\"utf-8\")\n\n        return \"\"\n\n    adapter.register_uri(\n        GET,\n        ANY,\n        text=mock_response,\n    )\n\n    result = HN.fetch_production(ZoneKey(\"HN\"), session)\n    assert snapshot == result\n\n\n@pytest.mark.parametrize(\n    \"zone_key1,zone_key2\",\n    [\n        (\"GT\", \"HN\"),\n        (\"HN\", \"NI\"),\n        (\"HN\", \"SV\"),\n        (\"HN\", \"US\"),  # Test case with no matching zone\n    ],\n)\ndef test_fetch_exchange(adapter, session, snapshot, zone_key1, zone_key2):\n    \"\"\"Test exchange data parsing with snapshot testing.\"\"\"\n    exchange_file = base_path_to_mock / \"exchange_index_7.csv\"\n\n    adapter.register_uri(\n        GET,\n        ANY,\n        text=exchange_file.read_text(encoding=\"utf-8\"),\n    )\n\n    result = HN.fetch_exchange(zone_key1, zone_key2, session)\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == result\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_IEMOP.py",
    "content": "from datetime import datetime, timezone\n\nimport pytest\nfrom requests_mock import GET, POST\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.IEMOP import REPORTS_ADMIN_URL, fetch_production\nfrom electricitymap.contrib.types import ZoneKey\n\nzone_keys = [ZoneKey(\"PH-LU\"), ZoneKey(\"PH-MI\"), ZoneKey(\"PH-VI\")]\n\n\n@pytest.mark.parametrize(\"zone_key\", zone_keys)\ndef test_production(adapter, session, snapshot, zone_key: ZoneKey):\n    \"\"\"\n    Reports have been reduced to 14 September 2023 00:00 to 13 September 2023 22:00 for ease\n    \"\"\"\n    target_datetime = datetime(2023, 9, 14, 0, 0, tzinfo=timezone.utc)\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/IEMOP/list_reports_items.json\", \"rb\"\n    ) as list_reports_items:\n        adapter.register_uri(\n            POST,\n            REPORTS_ADMIN_URL,\n            content=list_reports_items.read(),\n        )\n    REPORTS_LINK = \"https://www.iemop.ph/market-data/dipc-energy-results-raw/?md_file=L3Zhci93d3cvaHRtbC93cC1jb250ZW50L3VwbG9hZHMvZG93bmxvYWRzL2RhdGEvRElQQ0VSL0RJUENFUl8yMDIzMDkxNDAwMDAuemlw\"\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/IEMOP/reports_content\", \"rb\"\n    ) as reports_byte_content:\n        adapter.register_uri(\n            GET,\n            REPORTS_LINK,\n            content=reports_byte_content.read(),\n        )\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_production(\n        zone_key=ZoneKey(zone_key),\n        session=session,\n        target_datetime=target_datetime,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_IN.py",
    "content": "from datetime import datetime\nfrom json import dumps\nfrom pathlib import Path\n\nimport pandas as pd\nfrom pandas.testing import assert_series_equal\n\nfrom electricitymap.contrib.parsers.IN import (\n    compute_zone_key_share_per_mode_out_of_total,\n    parse_15m_production_grid_india_report,\n    parse_daily_production_grid_india_report,\n    parse_daily_total_production_grid_india_report,\n    parse_total_production_15min_grid_india_report,\n    scale_15min_production,\n)\n\nfile_path = Path(__file__).parent / \"mocks\" / \"IN\" / \"08.04.25_NLDC_PSP.xls\"\ncontent = file_path.read_bytes()\n\n\ndef test_parse_daily_total_production_grid_india_report():\n    result = parse_daily_total_production_grid_india_report(content)\n    assert result == 5404120.0\n\n\ndef test_parse_total_production_15min_grid_india_report():\n    result = parse_total_production_15min_grid_india_report(content)\n    assert result == 5035435.25\n\n\ndef test_compute_zone_key_share_per_mode_out_of_total():\n    result = compute_zone_key_share_per_mode_out_of_total(content, \"IN-NO\")\n    expected = pd.Series(\n        data={\n            \"nuclear\": 0.1870051375037776,\n            \"wind\": 0.24537248628884828,\n            \"solar\": 0.4077671888420794,\n            \"hydro\": 0.5168968557155451,\n            \"gas\": 0.18445718445718445,\n            \"coal\": 0.21282309665243412,\n            \"unknown\": 0.2750799208403111,\n        },\n        name=\"value\",\n    )\n    expected.index.name = \"mode\"\n    assert_series_equal(result.sort_index(), expected.sort_index())\n\n\ndef test_scale_15min_production(snapshot):\n    generation_scaling_factor = 0.5\n    result = scale_15min_production(content, generation_scaling_factor)\n    result_dict = result.to_dict(orient=\"records\")\n    snapshot.assert_match(dumps(result_dict, indent=2))\n\n\ndef test_parse_15m_production_grid_india_report(snapshot):\n    result = parse_15m_production_grid_india_report(\n        content, \"IN-NO\", datetime(2025, 4, 8, 0, 0)\n    )\n    assert snapshot == result\n\n\ndef test_parse_daily_production_grid_india_report(snapshot):\n    # This test uses the same file as the one for the 15m production report, but it does not use the 15m data.\n    # This is to test the behavior of the parser for the period 2023/04/01 - 2024/11/04.\n    result = parse_daily_production_grid_india_report(\n        content, \"IN-EA\", datetime(2025, 4, 8, 0, 0)\n    )\n    assert snapshot == result\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_IN_AP.py",
    "content": "from importlib import resources\n\nimport pytest\nfrom requests_mock import ANY\n\nfrom electricitymap.contrib.parsers.archived import IN_AP\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    adapter.register_uri(\n        ANY,\n        ANY,\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n        .joinpath(\"IN_AP.html\")\n        .read_text(),\n    )\n\n\ndef test_fetch_production(session):\n    data = IN_AP.fetch_production(\"IN-AP\", session)\n    assert data\n    assert data[\"zoneKey\"] == \"IN-AP\"\n    assert data[\"source\"] == \"core.ap.gov.in\"\n    assert data[\"datetime\"]\n    assert data[\"production\"]\n    assert data[\"storage\"]\n\n\ndef test_fetch_consumption(session):\n    data = IN_AP.fetch_consumption(\"IN-AP\", session)\n    assert data\n    assert data[\"zoneKey\"] == \"IN-AP\"\n    assert data[\"source\"] == \"core.ap.gov.in\"\n    assert data[\"datetime\"]\n    assert data[\"consumption\"]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_IN_EA.py",
    "content": "from datetime import datetime\nfrom zoneinfo import ZoneInfo\n\nimport pytest\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.config import ZONE_NEIGHBOURS, ZoneKey\nfrom electricitymap.contrib.parsers import IN_EA\n\nNETFLOWS = {\n    ZoneKey(\"IN-EA->IN-NO\"): -2139.0,\n    ZoneKey(\"IN-EA->IN-NE\"): -1518.0,\n    ZoneKey(\"IN-EA->IN-SO\"): -3019.0,\n    ZoneKey(\"IN-EA->IN-WE\"): 3257.0,\n    ZoneKey(\"BT->IN-EA\"): 769.75,\n    ZoneKey(\"IN-EA->NP\"): 274.17,\n    ZoneKey(\"BD->IN-EA\"): -936.79,\n}\n\n\n@pytest.mark.parametrize(\"neighbour_zone_key\", ZONE_NEIGHBOURS[ZoneKey(\"IN-EA\")])\ndef test_exchanges(adapter, session, neighbour_zone_key: ZoneKey):\n    target_date = datetime(2023, 6, 25, 0, 0, tzinfo=ZoneInfo(\"Asia/Kolkata\"))\n    sorted_zone_keys = ZoneKey(\"->\".join(sorted([neighbour_zone_key, \"IN-EA\"])))\n    url, _ = IN_EA.get_fetch_function(sorted_zone_keys)\n    filename = (\n        \"interregional_exchanges\"\n        if sorted_zone_keys in IN_EA.INTERREGIONAL_EXCHANGES\n        else \"transnational_exchanges\"\n    )\n    with open(\n        f\"electricitymap/contrib/parsers/tests/mocks/IN_EA/{filename}.json\", \"rb\"\n    ) as data:\n        adapter.register_uri(\n            GET,\n            url.format(\n                proxy=IN_EA.IN_WE_PROXY,\n                host=IN_EA.HOST,\n                target_date=target_date.strftime(\"%Y-%m-%d\"),\n            ),\n            content=data.read(),\n        )\n    exchanges = IN_EA.fetch_exchange(\n        ZoneKey(\"IN-EA\"),\n        neighbour_zone_key,\n        session,\n        datetime(2023, 6, 25, 0, 0, tzinfo=ZoneInfo(\"Asia/Kolkata\")),\n    )\n\n    assert exchanges[0][\"datetime\"] == datetime(\n        2023, 6, 25, 0, 0, tzinfo=ZoneInfo(\"Asia/Kolkata\")\n    )\n    assert exchanges[0][\"netFlow\"] == NETFLOWS[sorted_zone_keys]\n    assert exchanges[0][\"sortedZoneKeys\"] == sorted_zone_keys\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_IN_HP.py",
    "content": "from importlib import resources\n\nimport pytest\nfrom requests_mock import POST\nfrom testfixtures import LogCapture\n\nfrom electricitymap.contrib.parsers import IN_HP\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    adapter.register_uri(\n        POST,\n        IN_HP.DATA_URL,\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n        .joinpath(\"IN_HP.html\")\n        .read_text(),\n    )\n\n\ndef test_fetch_production(session):\n    with LogCapture() as log:\n        data = IN_HP.fetch_production(\"IN-HP\", session)\n        assert data[\"zoneKey\"] == \"IN-HP\"\n        assert data[\"source\"] == \"hpsldc.com\"\n        assert data[\"datetime\"]\n        assert data[\"production\"] == {\"hydro\": 4238.05, \"unknown\": 323.44}\n\n        # Check rows that failed to parse in each table were logged correctly.\n        logs = log.actual()\n        assert len(logs) == 2\n        assert \"UNKNOWN HP PLANT\" in logs[0][2]\n        assert \"UNKNOWN ISGS PLANT\" in logs[1][2]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_IN_KA.py",
    "content": "from importlib import resources\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers import IN_KA\n\n\ndef test_fetch_consumption(adapter, session):\n    adapter.register_uri(\n        GET,\n        \"https://kptclsldc.in/Default.aspx\",\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n        .joinpath(\"IN_KA_Default.html\")\n        .read_text(),\n    )\n\n    data = IN_KA.fetch_consumption(\"IN-KA\", session)\n    assert data\n    assert data[\"zoneKey\"] == \"IN-KA\"\n    assert data[\"source\"] == \"kptclsldc.in\"\n    assert data[\"datetime\"]\n    assert data[\"consumption\"]\n    assert data[\"consumption\"] == 7430.0\n\n\ndef test_fetch_production(adapter, session):\n    adapter.register_uri(\n        GET,\n        \"https://kptclsldc.in/StateGen.aspx\",\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n        .joinpath(\"IN_KA_StateGen.html\")\n        .read_text(),\n    )\n    adapter.register_uri(\n        GET,\n        \"https://kptclsldc.in/StateNCEP.aspx\",\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n        .joinpath(\"IN_KA_StateNCEP.html\")\n        .read_text(),\n    )\n\n    data = IN_KA.fetch_production(\"IN-KA\", session)\n    assert data\n    assert data[\"zoneKey\"] == \"IN-KA\"\n    assert data[\"source\"] == \"kptclsldc.in\"\n    assert data[\"datetime\"]\n    assert data[\"production\"]\n    assert data[\"production\"][\"hydro\"] == 2434.0\n    assert data[\"storage\"]\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_JAO.py",
    "content": "import json\nimport re\nfrom datetime import datetime\nfrom pathlib import Path\n\nfrom requests_mock import GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.config import ZoneKey\nfrom electricitymap.contrib.parsers.JAO import (\n    fetch_core_external_atc_day_ahead,\n    fetch_core_max_bex_day_ahead,\n    fetch_core_scheduled_exchanges_day_ahead,\n    fetch_nordic_max_bex_day_ahead,\n    fetch_nordic_max_bflow_day_ahead,\n    fetch_shadow_auction_atc_day_ahead,\n)\n\nBASE_MOCK_PATH = Path(\"electricitymap/contrib/parsers/tests/mocks/JAO\")\nSHADOW_AUCTION_ATC_URL_REGEX = re.compile(\n    r\"https://publicationtool\\.jao\\.eu/core/api/data/shadowAuctionATC\"\n)\nCORE_EXTERNAL_ATC_URL_REGEX = re.compile(\n    r\"https://publicationtool\\.jao\\.eu/core/api/data/atc\"\n)\nCORE_MAX_BEX_URL_REGEX = re.compile(\n    r\"https://publicationtool\\.jao\\.eu/core/api/data/maxExchanges\"\n)\nNORDIC_MAX_BEX_URL_REGEX = re.compile(\n    r\"https://publicationtool\\.jao\\.eu/nordic/api/data/maxExchanges\"\n)\nCORE_SCHEDULED_EXCHANGES_URL_REGEX = re.compile(\n    r\"https://publicationtool\\.jao\\.eu/core/api/data/scheduledExchanges\"\n)\nNORDIC_MAX_BFLOW_URL_REGEX = re.compile(\n    r\"https://publicationtool\\.jao\\.eu/nordic/api/data/maxBorderFlow\"\n)\nTARGET_DATETIME = datetime.fromisoformat(\"2025-10-01T00:00:00+00:00\")\nCORE_EXTERNAL_TARGET_DATETIME = datetime.fromisoformat(\"2026-04-20T00:00:00+00:00\")\nAPRIL_2026_TARGET_DATETIME = datetime.fromisoformat(\"2026-04-20T00:00:00+00:00\")\n\n\ndef _register_shadow_auction_atc(adapter) -> None:\n    payload = json.loads((BASE_MOCK_PATH / \"shadow_auction_atc.json\").read_text())\n    adapter.register_uri(GET, SHADOW_AUCTION_ATC_URL_REGEX, json=payload)\n\n\ndef test_fetch_shadow_auction_atc_day_ahead_de_fr(adapter, session, snapshot):\n    _register_shadow_auction_atc(adapter)\n\n    result = fetch_shadow_auction_atc_day_ahead(\n        ZoneKey(\"DE\"),\n        ZoneKey(\"FR\"),\n        session=session,\n        target_datetime=TARGET_DATETIME,\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == result\n\n\ndef test_fetch_shadow_auction_atc_day_ahead_pair_not_in_core(adapter, session):\n    \"\"\"Pairs without JAO border fields should return [] without raising.\"\"\"\n    _register_shadow_auction_atc(adapter)\n\n    result = fetch_shadow_auction_atc_day_ahead(\n        ZoneKey(\"DE\"),\n        ZoneKey(\"DK\"),\n        session=session,\n        target_datetime=TARGET_DATETIME,\n    )\n\n    assert result == []\n\n\ndef test_fetch_shadow_auction_atc_day_ahead_em_to_jao_zone_remap(adapter, session):\n    \"\"\"EM zone keys that don't match JAO's codes (e.g. IT-NO -> IT, DK-DK1 -> DK1)\n    should be translated before looking up `border_XX_YY` fields.\"\"\"\n    remapped = {\n        \"data\": [\n            {\n                \"id\": 1,\n                \"dateTimeUtc\": \"2025-10-01T00:00:00Z\",\n                \"border_FR_IT\": 2500,\n                \"border_IT_FR\": 2200,\n            }\n        ],\n        \"rejected\": False,\n        \"messages\": None,\n    }\n    adapter.register_uri(GET, SHADOW_AUCTION_ATC_URL_REGEX, json=remapped)\n\n    result = fetch_shadow_auction_atc_day_ahead(\n        ZoneKey(\"FR\"),\n        ZoneKey(\"IT-NO\"),\n        session=session,\n        target_datetime=TARGET_DATETIME,\n    )\n\n    assert len(result) == 1\n    assert result[0][\"sortedZoneKeys\"] == \"FR->IT-NO\"\n    assert result[0][\"capacityExport\"] == 2500\n    assert result[0][\"capacityImport\"] == 2200\n\n\ndef test_fetch_shadow_auction_atc_day_ahead_one_sided(adapter, session):\n    \"\"\"When only one direction is present in the JAO row, the event should\n    still be emitted with a single populated capacity direction.\"\"\"\n    one_sided = {\n        \"data\": [\n            {\n                \"id\": 1,\n                \"dateTimeUtc\": \"2025-10-01T00:00:00Z\",\n                \"border_AT_DE\": 3620,\n            }\n        ],\n        \"rejected\": False,\n        \"messages\": None,\n    }\n    adapter.register_uri(GET, SHADOW_AUCTION_ATC_URL_REGEX, json=one_sided)\n\n    result = fetch_shadow_auction_atc_day_ahead(\n        ZoneKey(\"AT\"),\n        ZoneKey(\"DE\"),\n        session=session,\n        target_datetime=TARGET_DATETIME,\n    )\n\n    assert len(result) == 1\n    assert result[0][\"capacityExport\"] == 3620\n    assert result[0][\"capacityImport\"] is None\n    assert result[0][\"sortedZoneKeys\"] == \"AT->DE\"\n\n\ndef test_fetch_core_external_atc_day_ahead_de_dk_dk1(adapter, session, snapshot):\n    \"\"\"Happy path for a Core-external border that also exercises the\n    DK-DK1 → DK1 zone remap. Fixture is a real 2-day, 15-min response.\"\"\"\n    payload = json.loads((BASE_MOCK_PATH / \"core_external_atc.json\").read_text())\n    adapter.register_uri(GET, CORE_EXTERNAL_ATC_URL_REGEX, json=payload)\n\n    result = fetch_core_external_atc_day_ahead(\n        ZoneKey(\"DE\"),\n        ZoneKey(\"DK-DK1\"),\n        session=session,\n        target_datetime=CORE_EXTERNAL_TARGET_DATETIME,\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == result\n\n\ndef test_fetch_core_external_atc_day_ahead_border_not_in_dataset(adapter, session):\n    \"\"\"Core-external endpoint only lists a handful of neighbors; a pair\n    that isn't in the response should return [] without raising.\"\"\"\n    payload = json.loads((BASE_MOCK_PATH / \"core_external_atc.json\").read_text())\n    adapter.register_uri(GET, CORE_EXTERNAL_ATC_URL_REGEX, json=payload)\n\n    result = fetch_core_external_atc_day_ahead(\n        ZoneKey(\"DE\"),\n        ZoneKey(\"FR\"),\n        session=session,\n        target_datetime=CORE_EXTERNAL_TARGET_DATETIME,\n    )\n\n    assert result == []\n\n\ndef test_fetch_core_max_bex_day_ahead_de_fr(adapter, session, snapshot):\n    \"\"\"Core maxExchanges happy path (hourly, 48 rows over 2 days).\"\"\"\n    payload = json.loads((BASE_MOCK_PATH / \"core_max_bex.json\").read_text())\n    adapter.register_uri(GET, CORE_MAX_BEX_URL_REGEX, json=payload)\n\n    result = fetch_core_max_bex_day_ahead(\n        ZoneKey(\"DE\"),\n        ZoneKey(\"FR\"),\n        session=session,\n        target_datetime=APRIL_2026_TARGET_DATETIME,\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == result\n\n\ndef test_fetch_nordic_max_bex_day_ahead_no1_se3(adapter, session, snapshot):\n    \"\"\"Nordic maxExchanges happy path — exercises the NO-NO2 → NO2,\n    SE-SE3 → SE3 zone remap on a real 15-min fixture.\"\"\"\n    payload = json.loads((BASE_MOCK_PATH / \"nordic_max_bex.json\").read_text())\n    adapter.register_uri(GET, NORDIC_MAX_BEX_URL_REGEX, json=payload)\n\n    result = fetch_nordic_max_bex_day_ahead(\n        ZoneKey(\"NO-NO1\"),\n        ZoneKey(\"SE-SE3\"),\n        session=session,\n        target_datetime=APRIL_2026_TARGET_DATETIME,\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == result\n\n\ndef test_fetch_core_scheduled_exchanges_day_ahead_de_fr(adapter, session, snapshot):\n    \"\"\"Core scheduledExchanges happy path (cleared commercial flow, 15-min).\"\"\"\n    payload = json.loads((BASE_MOCK_PATH / \"core_scheduled_exchanges.json\").read_text())\n    adapter.register_uri(GET, CORE_SCHEDULED_EXCHANGES_URL_REGEX, json=payload)\n\n    result = fetch_core_scheduled_exchanges_day_ahead(\n        ZoneKey(\"DE\"),\n        ZoneKey(\"FR\"),\n        session=session,\n        target_datetime=APRIL_2026_TARGET_DATETIME,\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == result\n\n\ndef test_fetch_nordic_max_bflow_day_ahead_no1_se3(adapter, session, snapshot):\n    \"\"\"Nordic maxBorderFlow happy path (physical capability ceiling, 15-min).\"\"\"\n    payload = json.loads((BASE_MOCK_PATH / \"nordic_max_bflow.json\").read_text())\n    adapter.register_uri(GET, NORDIC_MAX_BFLOW_URL_REGEX, json=payload)\n\n    result = fetch_nordic_max_bflow_day_ahead(\n        ZoneKey(\"NO-NO1\"),\n        ZoneKey(\"SE-SE3\"),\n        session=session,\n        target_datetime=APRIL_2026_TARGET_DATETIME,\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == result\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_JP.py",
    "content": "\"\"\"Test for JP parsers\"\"\"\n\nimport re\nfrom datetime import datetime\nfrom pathlib import Path\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.JP import (\n    fetch_consumption_forecast,\n    fetch_generation_forecast,\n)\n\n\n@pytest.mark.parametrize(\n    \"zone_key\",\n    [\n        \"JP-CB\",\n        \"JP-CG\",\n        \"JP-HKD\",\n        \"JP-HR\",\n        \"JP-KN\",\n        \"JP-KY\",\n        \"JP-ON\",\n        \"JP-SK\",\n        \"JP-TH\",\n        \"JP-TK\",\n    ],\n)\n@freeze_time(\"2025-04-16\")  # because the mocks are all around this date\ndef test_snapshot_fetch_generation_forecast(adapter, session, snapshot, zone_key):\n    datestamp_today = datetime.now().strftime(\"%Y%m%d\")\n    BASE_PATH_TO_MOCK = Path(\"electricitymap/contrib/parsers/tests/mocks/\" + zone_key)\n\n    forecast_url = {\n        \"JP-HKD\": r\"http://denkiyoho\\.hepco\\.co\\.jp/area/data/\\d{8}_hokkaido_yosoku\\.csv\",\n        \"JP-HR\": r\"https://www\\.rikuden\\.co\\.jp/nw/denki-yoho/csv/yosoku_05_\\d{8}\\.csv\",\n        \"JP-KN\": r\"https://www\\.kansai-td\\.co\\.jp/interchange/denkiyoho/imbalance/\\d{8}_yosoku\\.csv\",\n        \"JP-CG\": r\"https://www\\.energia\\.co\\.jp/nw/jukyuu/sys/\\d{6}_jyukyu2_chugoku\\.zip\",\n        \"JP-KY\": r\"https://www\\.kyuden\\.co\\.jp/td_power_usages/csv/kouhyo/imbalance/21110_TSO9_0_\\d{8}\\.csv\\?a=\\d{8}%5Cd6\",\n        \"JP-ON\": r\"http://www\\.okiden\\.co\\.jp/denki2/dem_pg/csv/jukyu_yosoku_\\d{8}\\.csv\",\n    }\n\n    # For zones with different URLs for today vs tomorrow\n    if zone_key in [\"JP-TH\", \"JP-TK\", \"JP-CB\", \"JP-SK\"]:\n        # Register today's URL\n        today_url = None\n        if zone_key == \"JP-TH\":\n            today_url = f\"https://setsuden.nw.tohoku-epco.co.jp/common/demand/area_tso_yosoku_{datestamp_today}.csv\"\n            data_path = Path(BASE_PATH_TO_MOCK, \"area_tso_yosoku_20250416.csv\")\n        elif zone_key == \"JP-TK\":\n            today_url = \"https://www4.tepco.co.jp/forecast/html/images/AREA_YOSOKU.csv\"\n            data_path = Path(BASE_PATH_TO_MOCK, \"AREA_YOSOKU.csv\")\n        elif zone_key == \"JP-CB\":\n            today_url = \"https://powergrid.chuden.co.jp/denki_yoho_content_data/keito_yosoku_cepco003.csv\"\n            data_path = Path(BASE_PATH_TO_MOCK, \"keito_yosoku_cepco003.csv\")\n        elif zone_key == \"JP-SK\":\n            today_url = \"https://www.yonden.co.jp/nw/denkiyoho/supply_demand/csv/yosoku_today.csv\"\n            data_path = Path(BASE_PATH_TO_MOCK, \"yosoku_today.csv\")\n\n        adapter.register_uri(GET, today_url, body=data_path.open(\"rb\"))\n\n        # Register tomorrow's URL (except for JP-CB which raises an exception)\n        if zone_key != \"JP-CB\":\n            tomorrow_url = None\n            if zone_key == \"JP-TH\":\n                tomorrow_url = \"https://setsuden.nw.tohoku-epco.co.jp/common/demand/area_tso_yosoku_y.csv\"\n                data_path = Path(BASE_PATH_TO_MOCK, \"area_tso_yosoku_y.csv\")\n            elif zone_key == \"JP-TK\":\n                tomorrow_url = (\n                    \"https://www4.tepco.co.jp/forecast/html/images/AREA_ONCE_YOSOKU.csv\"\n                )\n                data_path = Path(BASE_PATH_TO_MOCK, \"AREA_ONCE_YOSOKU.csv\")\n            elif zone_key == \"JP-SK\":\n                tomorrow_url = \"https://www.yonden.co.jp/nw/denkiyoho/supply_demand/csv/yosoku_tomorrow.csv\"\n                data_path = Path(BASE_PATH_TO_MOCK, \"yosoku_tomorrow.csv\")\n\n            adapter.register_uri(GET, tomorrow_url, body=data_path.open(\"rb\"))\n\n    if zone_key == \"JP-HKD\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"20250415_hokkaido_yosoku.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    elif zone_key == \"JP-HR\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"yosoku_05_20250415.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    elif zone_key == \"JP-KN\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"20250416_yosoku.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    elif zone_key == \"JP-CG\":\n        data_zip_file = Path(BASE_PATH_TO_MOCK, \"202504_jyukyu2_chugoku.zip\")\n        with open(data_zip_file, \"rb\") as zip_file:\n            zip_content = zip_file.read()\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            content=zip_content,\n        )\n\n    elif zone_key == \"JP-KY\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"21110_TSO9_0_20250407.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    elif zone_key == \"JP-ON\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"jukyu_yosoku_20250415.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    # Run function under test\n    assert snapshot == fetch_generation_forecast(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=datetime(\n            2025, 4, 16, 12, 0\n        ),  # the mock files were extracted this date\n    )\n\n\n@pytest.mark.parametrize(\n    \"zone_key\",\n    [\n        \"JP-CB\",\n        \"JP-CG\",\n        \"JP-HKD\",\n        \"JP-HR\",\n        \"JP-KN\",\n        \"JP-KY\",\n        \"JP-ON\",\n        \"JP-SK\",\n        \"JP-TH\",\n        \"JP-TK\",\n    ],\n)\n@freeze_time(\"2025-04-16\")  # because the mocks are all around this date\ndef test_snapshot_fetch_consumption_forecast(adapter, session, snapshot, zone_key):\n    datestamp_today = datetime.now().strftime(\"%Y%m%d\")\n    BASE_PATH_TO_MOCK = Path(\"electricitymap/contrib/parsers/tests/mocks/\" + zone_key)\n\n    forecast_url = {\n        \"JP-HKD\": r\"http://denkiyoho\\.hepco\\.co\\.jp/area/data/\\d{8}_hokkaido_yosoku\\.csv\",\n        \"JP-HR\": r\"https://www\\.rikuden\\.co\\.jp/nw/denki-yoho/csv/yosoku_05_\\d{8}\\.csv\",\n        \"JP-KN\": r\"https://www\\.kansai-td\\.co\\.jp/interchange/denkiyoho/imbalance/\\d{8}_yosoku\\.csv\",\n        \"JP-CG\": r\"https://www\\.energia\\.co\\.jp/nw/jukyuu/sys/\\d{6}_jyukyu2_chugoku\\.zip\",\n        \"JP-KY\": r\"https://www\\.kyuden\\.co\\.jp/td_power_usages/csv/kouhyo/imbalance/21110_TSO9_0_\\d{8}\\.csv\\?a=\\d{8}%5Cd6\",\n        \"JP-ON\": r\"http://www\\.okiden\\.co\\.jp/denki2/dem_pg/csv/jukyu_yosoku_\\d{8}\\.csv\",\n    }\n\n    # For zones with different URLs for today vs tomorrow\n    if zone_key in [\"JP-TH\", \"JP-TK\", \"JP-CB\", \"JP-SK\"]:\n        # Register today's URL\n        today_url = None\n        if zone_key == \"JP-TH\":\n            today_url = f\"https://setsuden.nw.tohoku-epco.co.jp/common/demand/area_tso_yosoku_{datestamp_today}.csv\"\n            data_path = Path(BASE_PATH_TO_MOCK, \"area_tso_yosoku_20250416.csv\")\n        elif zone_key == \"JP-TK\":\n            today_url = \"https://www4.tepco.co.jp/forecast/html/images/AREA_YOSOKU.csv\"\n            data_path = Path(BASE_PATH_TO_MOCK, \"AREA_YOSOKU.csv\")\n        elif zone_key == \"JP-CB\":\n            today_url = \"https://powergrid.chuden.co.jp/denki_yoho_content_data/keito_yosoku_cepco003.csv\"\n            data_path = Path(BASE_PATH_TO_MOCK, \"keito_yosoku_cepco003.csv\")\n        elif zone_key == \"JP-SK\":\n            today_url = \"https://www.yonden.co.jp/nw/denkiyoho/supply_demand/csv/yosoku_today.csv\"\n            data_path = Path(BASE_PATH_TO_MOCK, \"yosoku_today.csv\")\n\n        adapter.register_uri(GET, today_url, body=data_path.open(\"rb\"))\n\n        # Register tomorrow's URL (except for JP-CB which raises an exception)\n        if zone_key != \"JP-CB\":\n            tomorrow_url = None\n            if zone_key == \"JP-TH\":\n                tomorrow_url = \"https://setsuden.nw.tohoku-epco.co.jp/common/demand/area_tso_yosoku_y.csv\"\n                data_path = Path(BASE_PATH_TO_MOCK, \"area_tso_yosoku_y.csv\")\n            elif zone_key == \"JP-TK\":\n                tomorrow_url = (\n                    \"https://www4.tepco.co.jp/forecast/html/images/AREA_ONCE_YOSOKU.csv\"\n                )\n                data_path = Path(BASE_PATH_TO_MOCK, \"AREA_ONCE_YOSOKU.csv\")\n            elif zone_key == \"JP-SK\":\n                tomorrow_url = \"https://www.yonden.co.jp/nw/denkiyoho/supply_demand/csv/yosoku_tomorrow.csv\"\n                data_path = Path(BASE_PATH_TO_MOCK, \"yosoku_tomorrow.csv\")\n\n            adapter.register_uri(GET, tomorrow_url, body=data_path.open(\"rb\"))\n\n    if zone_key == \"JP-HKD\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"20250415_hokkaido_yosoku.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    elif zone_key == \"JP-HR\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"yosoku_05_20250415.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    elif zone_key == \"JP-KN\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"20250416_yosoku.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    elif zone_key == \"JP-CG\":\n        data_zip_file = Path(BASE_PATH_TO_MOCK, \"202504_jyukyu2_chugoku.zip\")\n        with open(data_zip_file, \"rb\") as zip_file:\n            zip_content = zip_file.read()\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            content=zip_content,\n        )\n\n    elif zone_key == \"JP-KY\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"21110_TSO9_0_20250407.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    elif zone_key == \"JP-ON\":\n        data_path = Path(BASE_PATH_TO_MOCK, \"jukyu_yosoku_20250415.csv\")\n        adapter.register_uri(\n            GET,\n            re.compile(forecast_url[zone_key]),\n            body=data_path.open(\"rb\"),\n        )\n\n    # Run function under test\n    assert snapshot == fetch_consumption_forecast(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=datetime(\n            2025, 4, 16, 12, 0\n        ),  # the mock files were extracted this date\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_JP_KY.py",
    "content": "import zoneinfo\nfrom datetime import datetime\nfrom unittest.mock import MagicMock, patch\nfrom zoneinfo import ZoneInfo\n\nimport pytest\n\nfrom electricitymap.contrib.parsers import JP_KY\n\nTIMEZONE = ZoneInfo(\"Asia/Tokyo\")\n\n\n@pytest.fixture\ndef mock_csv_response_at_night():\n    mock = MagicMock()\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/JP_KY/solar_and_consumption.csv\"\n    ) as f:\n        mock.text = f.read()\n    mock.encoding = \"utf-8\"\n    return mock\n\n\n@pytest.fixture\ndef mock_csv_response_at_day():\n    mock = MagicMock()\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/JP_KY/solar_and_consumption_day.csv\"\n    ) as f:\n        mock.text = f.read()\n    mock.encoding = \"utf-8\"\n    return mock\n\n\n@pytest.fixture\ndef mock_nuclear_responses():\n    \"\"\"Fixture to create mock responses for nuclear power data.\"\"\"\n    sendai_mock = MagicMock()\n    with open(\"electricitymap/contrib/parsers/tests/mocks/JP_KY/sendai.html\") as f:\n        sendai_mock.text = f.read()\n\n    genkai_mock = MagicMock()\n    with open(\"electricitymap/contrib/parsers/tests/mocks/JP_KY/genkai.html\") as f:\n        genkai_mock.text = f.read()\n\n    return sendai_mock, genkai_mock\n\n\n@pytest.fixture\ndef mock_exchange_data_night():\n    \"\"\"Fixture to create mock exchange data.\"\"\"\n    return [\n        {\n            \"datetime\": datetime(\n                2025, 4, 24, 22, 45, tzinfo=zoneinfo.ZoneInfo(key=\"Asia/Tokyo\")\n            ),\n            \"sortedZoneKeys\": \"JP-CG->JP-KY\",\n            \"netFlow\": -100.0,\n            \"source\": \"occtonet.occto.or.jp\",\n        },\n        {\n            \"datetime\": datetime(\n                2025, 4, 24, 22, 50, tzinfo=zoneinfo.ZoneInfo(key=\"Asia/Tokyo\")\n            ),\n            \"sortedZoneKeys\": \"JP-CG->JP-KY\",\n            \"netFlow\": -200.0,\n            \"source\": \"occtonet.occto.or.jp\",\n        },\n        {\n            \"datetime\": datetime(\n                2025, 4, 24, 22, 55, tzinfo=zoneinfo.ZoneInfo(key=\"Asia/Tokyo\")\n            ),\n            \"sortedZoneKeys\": \"JP-CG->JP-KY\",\n            \"netFlow\": -300.0,\n            \"source\": \"occtonet.occto.or.jp\",\n        },\n        {\n            \"datetime\": datetime(\n                2025, 4, 24, 23, 00, tzinfo=zoneinfo.ZoneInfo(key=\"Asia/Tokyo\")\n            ),\n            \"sortedZoneKeys\": \"JP-CG->JP-KY\",\n            \"netFlow\": -400.0,\n            \"source\": \"occtonet.occto.or.jp\",\n        },\n    ]\n\n\n@pytest.fixture\ndef mock_exchange_data_day():\n    \"\"\"Fixture to create mock exchange data.\"\"\"\n    return [\n        {\n            \"datetime\": datetime(\n                2025, 4, 25, 16, 30, tzinfo=zoneinfo.ZoneInfo(key=\"Asia/Tokyo\")\n            ),\n            \"sortedZoneKeys\": \"JP-CG->JP-KY\",\n            \"netFlow\": -200.0,\n            \"source\": \"occtonet.occto.or.jp\",\n        },\n        {\n            \"datetime\": datetime(\n                2025, 4, 25, 16, 35, tzinfo=zoneinfo.ZoneInfo(key=\"Asia/Tokyo\")\n            ),\n            \"sortedZoneKeys\": \"JP-CG->JP-KY\",\n            \"netFlow\": -100.0,\n            \"source\": \"occtonet.occto.or.jp\",\n        },\n        {\n            \"datetime\": datetime(\n                2025, 4, 25, 16, 40, tzinfo=zoneinfo.ZoneInfo(key=\"Asia/Tokyo\")\n            ),\n            \"sortedZoneKeys\": \"JP-CG->JP-KY\",\n            \"netFlow\": -400.0,\n            \"source\": \"occtonet.occto.or.jp\",\n        },\n        {\n            \"datetime\": datetime(\n                2025, 4, 25, 16, 45, tzinfo=zoneinfo.ZoneInfo(key=\"Asia/Tokyo\")\n            ),\n            \"sortedZoneKeys\": \"JP-CG->JP-KY\",\n            \"netFlow\": -500.0,\n            \"source\": \"occtonet.occto.or.jp\",\n        },\n    ]\n\n\ndef test_fetch_production_success_without_solar(\n    mock_csv_response_at_night,\n    mock_nuclear_responses,\n    mock_exchange_data_night,\n):\n    \"\"\"Test successful data retrieval and processing.\"\"\"\n    with (\n        patch(\n            \"electricitymap.contrib.parsers.JP_KY.get\",\n            side_effect=[\n                mock_csv_response_at_night,\n                mock_nuclear_responses[0],\n                mock_nuclear_responses[1],\n            ],\n        ),\n        patch(\n            \"electricitymap.contrib.parsers.JP_KY.occtonet.fetch_exchange\",\n            return_value=mock_exchange_data_night,\n        ),\n    ):\n        result = JP_KY.fetch_production()[0]\n\n        nuclear = 3119  # (119.7 + 96.1 + 96.1) * 10\n        unknown = 5091  # 8010 - (-200) - 0 - nuclear\n\n        assert result[\"zoneKey\"] == \"JP-KY\"\n        assert result[\"datetime\"] == datetime(2025, 4, 24, 22, 50, tzinfo=TIMEZONE)\n        assert result[\"production\"][\"solar\"] == 0\n        assert result[\"production\"][\"nuclear\"] == nuclear\n        assert result[\"production\"][\"unknown\"] == unknown\n\n\ndef test_fetch_production_success_with_solar(\n    mock_csv_response_at_day,\n    mock_nuclear_responses,\n    mock_exchange_data_day,\n):\n    \"\"\"Test successful data retrieval and processing.\"\"\"\n    with (\n        patch(\n            \"electricitymap.contrib.parsers.JP_KY.get\",\n            side_effect=[\n                mock_csv_response_at_day,\n                mock_nuclear_responses[0],\n                mock_nuclear_responses[1],\n            ],\n        ),\n        patch(\n            \"electricitymap.contrib.parsers.JP_KY.occtonet.fetch_exchange\",\n            return_value=mock_exchange_data_day,\n        ),\n    ):\n        result = JP_KY.fetch_production()[0]\n\n        nuclear = 3119  # (119.7 + 96.1 + 96.1) * 10\n        unknown = 3861  #  8680 - (-400) - 2100 - nuclear\n\n        assert result[\"zoneKey\"] == \"JP-KY\"\n        assert result[\"datetime\"] == datetime(2025, 4, 25, 16, 40, tzinfo=TIMEZONE)\n        assert result[\"production\"][\"solar\"] == 2100\n        assert result[\"production\"][\"nuclear\"] == nuclear\n        assert result[\"production\"][\"unknown\"] == unknown\n\n\ndef test_fetch_production_with_past_date():\n    \"\"\"Test that past dates are not supported.\"\"\"\n    with pytest.raises(NotImplementedError):\n        JP_KY.fetch_production(target_datetime=datetime(2023, 1, 1))\n\n\ndef test_fetch_production_with_distant_exchange_data(\n    mock_csv_response_at_night, mock_nuclear_responses\n):\n    \"\"\"When the exchange data is more than 15 minutes from the consumption data, then we should return an empty list\"\"\"\n    distant_exchange = [\n        {\n            \"datetime\": datetime(\n                2025, 4, 25, 23, 10, tzinfo=zoneinfo.ZoneInfo(key=\"Asia/Tokyo\")\n            ),\n            \"sortedZoneKeys\": \"JP-CG->JP-KY\",\n            \"netFlow\": -200.0,\n            \"source\": \"occtonet.occto.or.jp\",\n        }\n    ]\n\n    with patch(  # noqa: SIM117\n        \"electricitymap.contrib.parsers.JP_KY.get\",\n        side_effect=[\n            mock_csv_response_at_night,\n            mock_nuclear_responses[0],\n            mock_nuclear_responses[1],\n        ],\n    ):\n        with patch(\n            \"electricitymap.contrib.parsers.JP_KY.occtonet.fetch_exchange\",\n            return_value=distant_exchange,\n        ):\n            result = JP_KY.fetch_production()\n            assert result == []\n\n\ndef test_snapshot_fetch_production(\n    snapshot,\n    mock_csv_response_at_day,\n    mock_nuclear_responses,\n    mock_exchange_data_day,\n):\n    \"\"\"Test successful data retrieval and processing.\"\"\"\n    with (\n        patch(\n            \"electricitymap.contrib.parsers.JP_KY.get\",\n            side_effect=[\n                mock_csv_response_at_day,\n                mock_nuclear_responses[0],\n                mock_nuclear_responses[1],\n            ],\n        ),\n        patch(\n            \"electricitymap.contrib.parsers.JP_KY.occtonet.fetch_exchange\",\n            return_value=mock_exchange_data_day,\n        ),\n    ):\n        result = JP_KY.fetch_production()\n\n        assert snapshot == result\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_JP_SK.py",
    "content": "import datetime\nimport re\nfrom importlib import resources\n\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers.JP_SK import (\n    NUCLEAR_REPORT_URL,\n    get_nuclear_power_image_url,\n    get_nuclear_power_value_and_timestamp_from_image_url,\n)\n\n\ndef test_find_nuclear_image_url(adapter, session):\n    report_content = (\n        resources.files(\"electricitymap.contrib.parsers.tests.mocks.JP-SK\")\n        .joinpath(\"jp-sk-nuclear-html-page.html\")\n        .read_bytes()\n    )\n    adapter.register_uri(GET, NUCLEAR_REPORT_URL, content=report_content)\n    image_url = get_nuclear_power_image_url(session)\n    pattern = r\"(?P<filename>ikt721-1\\.gif\\?[0-9]{12})\"\n    pattern_matches = re.findall(pattern, image_url)\n\n    assert len(pattern_matches) == 1\n    assert pattern_matches[0] == \"ikt721-1.gif?202402060021\"\n\n\ndef test_fetch_nuclear_image(adapter, session):\n    nuclear_prod_image = (\n        resources.files(\"electricitymap.contrib.parsers.tests.mocks.JP-SK\")\n        .joinpath(\"image3.gif\")\n        .read_bytes()\n    )\n    adapter.register_uri(\n        GET,\n        ANY,\n        content=nuclear_prod_image,\n    )\n    (\n        nuclear_production,\n        nuclear_timestamp,\n    ) = get_nuclear_power_value_and_timestamp_from_image_url(\n        \"https://test-url/ikt721-1.gif?202402062021\", session\n    )\n\n    assert isinstance(nuclear_production, float)\n    assert isinstance(nuclear_timestamp, datetime.datetime)\n    assert nuclear_production == 918.0\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_KPX.py",
    "content": "from datetime import datetime, timezone\n\nimport pytest\nfrom requests_mock import GET, POST\n\nfrom electricitymap.contrib.parsers.KPX import (\n    HISTORICAL_PRODUCTION_URL,\n    REAL_TIME_URL,\n    fetch_consumption,\n    fetch_production,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture()\ndef mock_response_as_realtime(adapter):\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/KPX/realtime.html\", \"rb\"\n    ) as mock:\n        adapter.register_uri(GET, REAL_TIME_URL, content=mock.read())\n\n\n@pytest.fixture()\ndef mock_response_as_historical(adapter):\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/KPX/historical.html\", \"rb\"\n    ) as mock:\n        adapter.register_uri(POST, HISTORICAL_PRODUCTION_URL, content=mock.read())\n        adapter.register_uri(GET, HISTORICAL_PRODUCTION_URL, content=None)\n\n\ndef test_fetch_consumption_realtime(session, snapshot, mock_response_as_realtime):\n    assert snapshot == fetch_consumption(ZoneKey(\"KR\"), session)\n\n\ndef test_fetch_production_realtime(session, snapshot, mock_response_as_realtime):\n    assert snapshot == fetch_production(ZoneKey(\"KR\"), session)\n\n\ndef test_production_historical(session, snapshot, mock_response_as_historical):\n    dt = datetime(2023, 9, 1, 0, 0, 0, tzinfo=timezone.utc)\n    assert snapshot == fetch_production(ZoneKey(\"KR\"), session, dt)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_MD.py",
    "content": "import json\nfrom datetime import datetime, timezone\nfrom importlib import resources\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import ANY, GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.MD import (\n    fetch_consumption,\n    fetch_exchange,\n    fetch_exchange_forecast,\n    fetch_price,\n    fetch_production,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n# the datetime corresponding to our mock live API response\nfrozen_live_time = freeze_time(\"2024-04-11 06:32:00\")\n\n# the target datetime corresponding to our mock historical API response\nhistorical_datetime = datetime(2021, 7, 25, 12, tzinfo=timezone.utc)\n\n\n@frozen_live_time\ndef test_fetch_consumption_live(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.MD\")\n            .joinpath(\"moldoelectrica_api_live.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_consumption(session=session)\n\n\ndef test_fetch_consumption_historical(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.MD\")\n            .joinpath(\"moldoelectrica_api_historical_20210725.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_consumption(\n        target_datetime=historical_datetime, session=session\n    )\n\n\n@pytest.mark.parametrize(\"neighbor\", [\"RO\", \"UA\"])\n@frozen_live_time\ndef test_fetch_exchange_live(adapter, session, snapshot, neighbor):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.MD\")\n            .joinpath(\"moldoelectrica_api_live.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetch_exchange(\n        ZoneKey(\"MD\"), ZoneKey(neighbor), session=session\n    )\n\n\n@pytest.mark.parametrize(\"neighbor\", [\"RO\", \"UA\"])\ndef test_fetch_exchange_historical(adapter, session, snapshot, neighbor):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.MD\")\n            .joinpath(\"moldoelectrica_api_historical_20210725.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetch_exchange(\n        ZoneKey(\"MD\"),\n        ZoneKey(neighbor),\n        target_datetime=historical_datetime,\n        session=session,\n    )\n\n\n@pytest.mark.parametrize(\"neighbor\", [\"RO\", \"UA\"])\n@frozen_live_time\ndef test_fetch_exchange_forecast_live(adapter, session, snapshot, neighbor):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.MD\")\n            .joinpath(\"moldoelectrica_api_live.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_exchange_forecast(ZoneKey(\"MD\"), ZoneKey(neighbor), session=session)\n\n\n@pytest.mark.parametrize(\"neighbor\", [\"RO\", \"UA\"])\ndef test_fetch_exchange_forecast_historical(adapter, session, snapshot, neighbor):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.MD\")\n            .joinpath(\"moldoelectrica_api_historical_20210725.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_exchange_forecast(\n        ZoneKey(\"MD\"),\n        ZoneKey(neighbor),\n        target_datetime=historical_datetime,\n        session=session,\n    )\n\n\n@frozen_live_time\ndef test_fetch_price_live(snapshot):\n    assert snapshot == fetch_price()\n\n\n@pytest.mark.parametrize(\n    \"historical_datetime\",\n    [\n        datetime(2000, 1, 1, tzinfo=timezone.utc),\n        datetime(2000, 4, 1, tzinfo=timezone.utc),\n        datetime(2001, 10, 1, tzinfo=timezone.utc),\n        datetime(2002, 9, 1, tzinfo=timezone.utc),\n        datetime(2005, 9, 1, tzinfo=timezone.utc),\n        datetime(2007, 8, 3, tzinfo=timezone.utc),\n        datetime(2010, 1, 19, tzinfo=timezone.utc),\n        datetime(2012, 5, 11, tzinfo=timezone.utc),\n        datetime(2015, 7, 31, tzinfo=timezone.utc),\n        datetime(2023, 12, 31, tzinfo=timezone.utc),\n        datetime(2024, 3, 21, tzinfo=timezone.utc),\n    ],\n)\ndef test_fetch_price_historical(snapshot, historical_datetime):\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetch_price(\n        target_datetime=historical_datetime\n    )\n\n\n@frozen_live_time\ndef test_fetch_production_live(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.MD\")\n            .joinpath(\"moldoelectrica_api_live.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_production(session=session)\n\n\ndef test_fetch_production_historical(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        ANY,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.MD\")\n            .joinpath(\"moldoelectrica_api_historical_20210725.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_production(\n        target_datetime=historical_datetime, session=session\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_NORDPOOL.py",
    "content": "import os\nfrom datetime import datetime\nfrom json import loads\nfrom pathlib import Path\n\nimport pytest\nfrom requests_mock import GET, POST\n\nfrom electricitymap.contrib.parsers import NORDPOOL\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/NORDPOOL\")\n\n\n@pytest.fixture(autouse=True)\ndef emaps_env():\n    os.environ[\"EMAPS_NORDPOOL_USERNAME\"] = \"username\"\n    os.environ[\"EMAPS_NORDPOOL_PASSWORD\"] = \"password\"\n\n\ndef test_price_parser_se(adapter, session, snapshot):\n    mock_token = Path(base_path_to_mock, \"token.json\")\n    mock_data_current_day = Path(base_path_to_mock, \"se_current_day_price.json\")\n    mock_data_next_day = Path(base_path_to_mock, \"se_next_day_price.json\")\n\n    adapter.register_uri(\n        POST,\n        \"https://sts.nordpoolgroup.com/connect/token\",\n        json=loads(mock_token.read_text()),\n    )\n    adapter.register_uri(\n        GET,\n        \"https://data-api.nordpoolgroup.com/api/v2/Auction/Prices/ByAreas?areas=SE4&currency=EUR&market=DayAhead&date=2024-07-08\",\n        json=loads(mock_data_current_day.read_text()),\n    )\n    adapter.register_uri(\n        GET,\n        \"https://data-api.nordpoolgroup.com/api/v2/Auction/Prices/ByAreas?areas=SE4&currency=EUR&market=DayAhead&date=2024-07-09\",\n        json=loads(mock_data_next_day.read_text()),\n    )\n\n    assert snapshot == NORDPOOL.fetch_price(\n        zone_key=ZoneKey(\"SE-SE4\"),\n        session=session,\n        target_datetime=datetime.fromisoformat(\"2024-07-08\"),\n    )\n\n\ndef test_exchange_parser_fi_se1(adapter, session, snapshot):\n    mock_token = Path(base_path_to_mock, \"token.json\")\n    mock_data_current_day = Path(base_path_to_mock, \"fi_se1_current_day_exchange.json\")\n    mock_data_previous_day = Path(\n        base_path_to_mock, \"fi_se1_previous_day_exchange.json\"\n    )\n\n    adapter.register_uri(\n        POST,\n        \"https://sts.nordpoolgroup.com/connect/token\",\n        json=loads(mock_token.read_text()),\n    )\n    adapter.register_uri(\n        GET,\n        \"https://data-api.nordpoolgroup.com/api/v2/PowerSystem/Exchanges/ByAreas?areas=FI&date=2024-12-01\",\n        json=loads(mock_data_current_day.read_text()),\n    )\n    adapter.register_uri(\n        GET,\n        \"https://data-api.nordpoolgroup.com/api/v2/PowerSystem/Exchanges/ByAreas?areas=FI&date=2024-11-30\",\n        json=loads(mock_data_previous_day.read_text()),\n    )\n\n    assert snapshot == NORDPOOL.fetch_exchange(\n        zone_key1=ZoneKey(\"FI\"),\n        zone_key2=ZoneKey(\"SE-SE1\"),\n        session=session,\n        target_datetime=datetime.fromisoformat(\"2024-12-01\"),\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_NTESMO.py",
    "content": "from datetime import datetime, timezone\nfrom json import loads\nfrom pathlib import Path\nfrom zoneinfo import ZoneInfo\n\nimport pytest\nimport requests\nfrom requests_mock import ANY, GET, Adapter\n\nfrom electricitymap.contrib.parsers.NTESMO import (\n    fetch_consumption,\n    fetch_consumption_forecast,\n    fetch_price,\n    fetch_production,\n)\n\naustralia = ZoneInfo(\"Australia/Darwin\")\n\n\n@pytest.fixture()\ndef fixture_session_mock(adapter, session) -> tuple[requests.Session, Adapter]:\n    # do not mount mock adapter on generic https:// prefix or the parser's @retry_policy decorator will overwrite it\n    session.mount(\"https://ntesmo.com.au/\", adapter)\n\n    index_page = \"\"\"<div class=\"smp-tiles-article__item\">\n            <a href=\"https://ntesmo.com.au/__data/assets/excel_doc/0013/116113/Market-Information_System-Control-daily-trading-day_220401.xlsx\">\n                <div class=\"smp-tiles-article__title\">01 December 2022</div>\n\n                <div class=\"smp-tiles-article__lower d-flex flex-nowrap justify-content-between align-content-center align-items-center\">\n                    <div class=\"col-9 no-padding\">\n                        <strong>Download</strong>\n                        <span>MS Excel Document (115.5 KB)</span>\n                    </div>\n                    <div class=\"col-3 no-padding d-flex justify-content-end\">\n                        <svg xmlns=\"http://www.w3.org/2000/svg\" width=\"33\" height=\"34\" viewBox=\"0 0 33 34\">\n                            <path fill=\"currentColor\" d=\"M-1223.7-1933.8h.2l.6.6.6-.6h.2v-.2l8.6-8.5-1.2-1.2-7.4 7.5v-22.6h-1.6v22.6l-7.4-7.5-1.2 1.2 8.6 8.5z\" transform=\"translate(1239 1959)\"></path>\n                            <path fill=\"currentColor\" class=\"st0\" d=\"M-1207.8-1938.1v11.3h-29.4v-11.3h-1.6v12.9h32.6v-12.9z\" transform=\"translate(1239 1959)\"></path>\n                        </svg>\n                    </div>\n                </div>\n            </a>\n        </div>\"\"\"\n\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/AU/NTESMO.xlsx\", \"rb\"\n    ) as data:\n        adapter.register_uri(\n            ANY,\n            ANY,\n            response_list=[\n                # mock first call scraping historical page of links\n                {\"text\": index_page},\n                # mock second call reading contents of link\n                {\"content\": data.read()},\n            ],\n        )\n\n    return session, adapter\n\n\ndef test_fetch_production(fixture_session_mock):\n    session, adapter = fixture_session_mock\n\n    historical_datetime = datetime(year=2022, month=12, day=1, tzinfo=timezone.utc)\n    data_list = fetch_production(session=session, target_datetime=historical_datetime)\n    assert data_list is not None\n\n    data_list = data_list[:2]\n    expected_data = [\n        {\n            \"production\": {\"gas\": 96, \"biomass\": 13, \"unknown\": 0},\n            \"storage\": {},\n        },\n        {\n            \"production\": {\"gas\": 96, \"biomass\": 13, \"unknown\": 0},\n            \"storage\": {},\n        },\n    ]\n    assert len(data_list) == len(expected_data)\n\n    for index, actual in enumerate(data_list):\n        assert actual[\"zoneKey\"] == \"AU-NT\"\n        assert actual[\"source\"] == \"ntesmo.com.au\"\n        for production_type, production in actual[\"production\"].items():\n            assert production == expected_data[index][\"production\"][production_type]\n\n\ndef test_fetch_price(fixture_session_mock):\n    session, adapter = fixture_session_mock\n\n    historical_datetime = datetime(year=2022, month=12, day=1, tzinfo=timezone.utc)\n    data_list = fetch_price(session=session, target_datetime=historical_datetime)\n\n    assert data_list is not None\n    expected_data = [\n        {\n            \"price\": 500,\n            \"currency\": \"AUD\",\n        }\n    ] * 48\n    assert len(data_list) == len(expected_data)\n    for index, actual in enumerate(data_list):\n        assert actual[\"zoneKey\"] == \"AU-NT\"\n        assert actual[\"source\"] == \"ntesmo.com.au\"\n        assert actual[\"price\"] == expected_data[index][\"price\"]\n        assert actual[\"currency\"] == expected_data[index][\"currency\"]\n\n    # Check that the dates corresponds to two days:\n\n    assert data_list[0][\"datetime\"] == datetime(\n        year=2022, month=12, day=1, hour=4, minute=30, tzinfo=australia\n    )\n\n    assert data_list[-1][\"datetime\"] == datetime(\n        year=2022, month=12, day=2, hour=4, minute=00, tzinfo=australia\n    )\n\n\ndef test_fetch_consumption(fixture_session_mock):\n    session, adapter = fixture_session_mock\n\n    historical_datetime = datetime(year=2022, month=12, day=1, tzinfo=timezone.utc)\n    data_list = fetch_consumption(session=session, target_datetime=historical_datetime)\n\n    assert data_list is not None\n\n    expected_data = [\n        {\n            \"consumption\": 30,\n        },\n    ] * 48\n    assert len(data_list) == len(expected_data)\n\n    for index, actual in enumerate(data_list):\n        assert actual[\"zoneKey\"] == \"AU-NT\"\n        assert actual[\"source\"] == \"ntesmo.com.au\"\n        assert actual[\"consumption\"] == expected_data[index][\"consumption\"]\n\n    # Check that the dates corresponds to two days:\n    assert data_list[0][\"datetime\"] == datetime(\n        year=2022, month=12, day=1, hour=4, minute=30, tzinfo=australia\n    )\n    assert data_list[-1][\"datetime\"] == datetime(\n        year=2022, month=12, day=2, hour=4, minute=00, tzinfo=australia\n    )\n\n\nBASE_PATH_TO_MOCK = Path(\"electricitymap/contrib/parsers/tests/mocks/NTESMO\")\n\n\ndef test_snapshot_fetch_consumption_forecast(adapter, session, snapshot):\n    # Define mock URLs\n    base_url = (\n        \"https://ntesmo.com.au/data/data-dashboard/2024-enhancements/demand-forecast\"\n    )\n    endpoints = [\n        f\"{base_url}/darwin-katherine/dk-7-days-forecast\",\n        f\"{base_url}/alice-springs/as-7-days-forecast\",\n        f\"{base_url}/tennant-creek/tc-7-days-forecast\",\n    ]\n\n    # Register mock responses\n    for endpoint in endpoints:\n        # For each url there is a mock file. Map each endpoint to its mock file\n        mock_file_name = endpoint.split(\"/\")[-1] + \".json\"\n        mock_data = Path(BASE_PATH_TO_MOCK, mock_file_name)\n\n        # Mock request\n        adapter.register_uri(GET, endpoint, json=loads(mock_data.read_text()))\n\n    # Call the function under test\n    result = fetch_consumption_forecast(zone_key=\"AU-NT\", session=session)\n\n    # Compare to snapshot\n    assert snapshot == result\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_NZ.py",
    "content": "from importlib import resources\nfrom json import loads\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.NZ import (\n    PRICE_URL,\n    PRODUCTION_URL,\n    fetch_price,\n    fetch_production,\n)\n\n\ndef test_snapshot_production_data(adapter, session, snapshot):\n    with open(\n        resources.files(\"electricitymap.contrib.parsers.tests.mocks.NZ\").joinpath(\n            \"response_2024_04_24_17_30.html\"\n        )\n    ) as f:\n        adapter.register_uri(\n            GET,\n            PRODUCTION_URL,\n            text=f.read(),\n        )\n    with open(\n        resources.files(\"electricitymap.contrib.parsers.tests.mocks.NZ\").joinpath(\n            \"response_2024_04_24_18_00.html\"\n        )\n    ) as f:\n        adapter.register_uri(\n            GET,\n            PRODUCTION_URL,\n            text=f.read(),\n        )\n\n    production = []\n    production.append(fetch_production(zone_key=\"NZ\", session=session))\n    production.append(fetch_production(zone_key=\"NZ\", session=session))\n\n    assert snapshot == production\n\n\ndef test_snapshot_price_data(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        PRICE_URL,\n        json=loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.NZ\")\n            .joinpath(\"response_2024_04_24_18_00.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        PRICE_URL,\n        json=loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.NZ\")\n            .joinpath(\"response_2024_04_24_18_30.json\")\n            .read_text()\n        ),\n    )\n\n    price = []\n    price.append(fetch_price(zone_key=\"NZ\", session=session))\n    price.append(fetch_price(zone_key=\"NZ\", session=session))\n\n    assert snapshot == price\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_ONS.py",
    "content": "import json\nfrom pathlib import Path\nfrom unittest.mock import patch\n\nimport pytest\nfrom requests_mock import GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers import ONS\nfrom electricitymap.contrib.types import ZoneKey\n\n# Base path for mock data files\nMOCK_DATA_DIR = Path(__file__).parent / \"mocks\" / \"ONS\"\n\n\n@pytest.fixture()\ndef mock_response():\n    with open(\"electricitymap/contrib/parsers/tests/mocks/ONS/BR.json\") as f:\n        mock_data = json.load(f)\n    with patch(\"electricitymap.contrib.parsers.ONS.get_data\", return_value=mock_data):\n        yield\n\n\n@pytest.mark.parametrize(\n    \"data_file\", [\"BR.json\", \"BR_negative_solar.json\", \"data.json\"]\n)\n@pytest.mark.parametrize(\"zone_key\", [\"BR-NE\", \"BR-N\", \"BR-CS\", \"BR-S\"])\ndef test_snapshot_fetch_production(zone_key, data_file, adapter, session, snapshot):\n    \"\"\"Test fetch_production with snapshot using different data files for all Brazilian subzones.\"\"\"\n    mock_data_path = MOCK_DATA_DIR / data_file\n    mock_data = json.loads(mock_data_path.read_text())\n\n    adapter.register_uri(\n        GET,\n        \"http://tr.ons.org.br/Content/GetBalancoEnergetico/null\",\n        json=mock_data,\n    )\n\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == ONS.fetch_production(\n        zone_key=ZoneKey(zone_key),\n        session=session,\n    )\n\n\n@pytest.mark.parametrize(\n    \"data_file\", [\"BR.json\", \"BR_negative_solar.json\", \"data.json\"]\n)\n@pytest.mark.parametrize(\n    \"zone_key1,zone_key2\",\n    [\n        (\"BR-CS\", \"BR-S\"),  # sud_sudeste\n        (\"BR-CS\", \"BR-NE\"),  # sudeste_nordeste\n        (\"BR-CS\", \"BR-N\"),  # sudeste_norteFic\n        (\"BR-N\", \"BR-NE\"),  # norteFic_nordeste\n        (\"BR-S\", \"UY\"),  # uruguai\n        (\"AR\", \"BR-S\"),  # argentina\n        (\"BR-S\", \"PY\"),  # paraguai\n    ],\n)\ndef test_snapshot_fetch_exchange(\n    zone_key1, zone_key2, data_file, adapter, session, snapshot\n):\n    \"\"\"Test fetch_exchange with snapshot using different data files for all exchanges.\"\"\"\n    mock_data_path = MOCK_DATA_DIR / data_file\n    mock_data = json.loads(mock_data_path.read_text())\n\n    adapter.register_uri(\n        GET,\n        \"http://tr.ons.org.br/Content/GetBalancoEnergetico/null\",\n        json=mock_data,\n    )\n\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == ONS.fetch_exchange(\n        zone_key1=zone_key1,\n        zone_key2=zone_key2,\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_OPENNEM.py",
    "content": "import json\nimport os\nfrom datetime import datetime\nfrom pathlib import Path\n\nimport pytest\nfrom requests_mock import ANY\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.OPENNEM import (\n    fetch_exchange,\n    fetch_price,\n    fetch_production,\n)\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/OPENNEM\")\n\n\n@pytest.fixture(autouse=True)\ndef openelectricity_token_env():\n    os.environ[\"OPENELECTRICITY_TOKEN\"] = \"token\"\n\n\n@pytest.mark.parametrize(\n    \"zone\", [\"AU-NSW\", \"AU-QLD\", \"AU-SA\", \"AU-TAS\", \"AU-VIC\", \"AU-WA\"]\n)\ndef test_production(adapter, session, snapshot, zone):\n    mock_data = Path(base_path_to_mock, f\"OPENNEM_{zone}.v4.json\")\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(mock_data.read_text()),\n    )\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_production(zone, session, datetime.fromisoformat(\"2025-03-23\"))\n\n\n@pytest.mark.parametrize(\"zone\", [\"AU-SA\"])\ndef test_price(adapter, session, snapshot, zone):\n    mock_data = Path(base_path_to_mock, f\"OPENNEM_price_{zone}.json\")\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(mock_data.read_text()),\n    )\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetch_price(\n        zone, session, datetime.fromisoformat(\"2020-01-01\")\n    )\n\n\ndef test_au_nsw_au_qld_exchange(adapter, session, snapshot):\n    # Exchange tests use the old v3 stats endpoint, so use v3 mock data\n    mock_data = Path(base_path_to_mock, \"OPENNEM_AU-QLD.json\")\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(mock_data.read_text()),\n    )\n\n    assert snapshot == fetch_exchange(\n        \"AU-NSW\", \"AU-QLD\", session, datetime.fromisoformat(\"2025-07-17\")\n    )\n\n\ndef test_au_nsw_au_vic_exchange(adapter, session, snapshot):\n    # Exchange tests use the old v3 stats endpoint, so use v3 mock data\n    mock_data_qld = Path(base_path_to_mock, \"OPENNEM_AU-QLD.json\")\n    mock_data_nsw = Path(base_path_to_mock, \"OPENNEM_AU-NSW.json\")\n\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(mock_data_qld.read_text()),\n    )\n\n    adapter.register_uri(\n        ANY,\n        ANY,\n        json=json.loads(mock_data_nsw.read_text()),\n    )\n\n    assert snapshot == fetch_exchange(\n        \"AU-NSW\", \"AU-VIC\", session, datetime.fromisoformat(\"2025-07-17\")\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_PA.py",
    "content": "from importlib import resources\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers.PA import fetch_production\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    adapter.register_uri(\n        GET,\n        ANY,\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n        .joinpath(\"PA_nominal_generation.html\")\n        .read_text(),\n        status_code=200,\n    )\n\n\n@freeze_time(\"2021-12-30 09:58:40\", tz_offset=-5)\ndef test_fetch_production(session, snapshot):\n    assert snapshot == fetch_production(session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_PE.py",
    "content": "import json\nfrom datetime import datetime\nfrom pathlib import Path\n\nfrom requests_mock import POST\n\nfrom electricitymap.contrib.parsers.PE import API_ENDPOINT, fetch_production\nfrom electricitymap.contrib.types import ZoneKey\n\n# Base path for mock data files\nMOCK_DATA_DIR = Path(__file__).parent / \"mocks\" / \"PE\"\n\n\ndef test_fetch_production_with_target_datetime(adapter, session, snapshot):\n    \"\"\"Test production data parsing for specific target datetime 2025-09-10.\"\"\"\n\n    def mock_response(request, context):\n        \"\"\"Mock response based on the request data.\"\"\"\n        # Parse the request data to determine which date is being requested\n        form_data = request.text\n\n        # Extract fechaInicial from the form data\n        if (\n            \"fechaInicial=09%2F09%2F2025\" in form_data\n            or \"fechaInicial=09/09/2025\" in form_data\n        ):\n            # Request for 2025-09-09 (yesterday)\n            mock_file = MOCK_DATA_DIR / \"response_20250909.json\"\n        elif (\n            \"fechaInicial=10%2F09%2F2025\" in form_data\n            or \"fechaInicial=10/09/2025\" in form_data\n        ):\n            # Request for 2025-09-10 (target date)\n            mock_file = MOCK_DATA_DIR / \"response_20250910.json\"\n        else:\n            # Default fallback\n            mock_file = MOCK_DATA_DIR / \"response_20250910.json\"\n\n        # Load and return the appropriate mock data\n        with open(mock_file, encoding=\"utf-8\") as f:\n            return json.load(f)\n\n    # Register the mock adapter\n    adapter.register_uri(\n        POST,\n        API_ENDPOINT,\n        json=mock_response,\n    )\n\n    # Test with target_datetime = 2025-09-10\n    target_datetime = datetime(2025, 9, 10, 12, 0, 0)\n    result = fetch_production(\n        zone_key=ZoneKey(\"PE\"),\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n    # Verify the result using snapshot testing\n    assert snapshot == result\n\n\ndef test_fetch_production_data_structure(adapter, session):\n    \"\"\"Test that the production data has the expected structure and values.\"\"\"\n\n    def mock_response(request, context):\n        \"\"\"Mock response that returns consistent data.\"\"\"\n        mock_file = MOCK_DATA_DIR / \"response_20250910.json\"\n        with open(mock_file, encoding=\"utf-8\") as f:\n            return json.load(f)\n\n    adapter.register_uri(\n        POST,\n        API_ENDPOINT,\n        json=mock_response,\n    )\n\n    target_datetime = datetime(2025, 9, 10, 12, 0, 0)\n    result = fetch_production(\n        zone_key=ZoneKey(\"PE\"),\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n    # Basic structure checks\n    assert isinstance(result, list)\n    assert len(result) > 0\n\n    # Check first production breakdown\n    first_item = result[0]\n    assert \"zoneKey\" in first_item\n    assert \"datetime\" in first_item\n    assert \"production\" in first_item\n    assert \"source\" in first_item\n\n    # Check that we have the expected energy sources\n    production = first_item[\"production\"]\n    expected_sources = {\"biomass\", \"hydro\", \"gas\", \"solar\", \"wind\", \"coal\", \"oil\"}\n\n    # Check that at least some expected sources are present\n    production_sources = set(production.keys())\n    assert len(production_sources.intersection(expected_sources)) > 0\n\n    # Check that all values are numeric\n    for _, value in production.items():\n        assert isinstance(value, int | float)\n        assert value >= 0  # Production values should be non-negative\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_PF.py",
    "content": "from datetime import datetime, timedelta, timezone\nfrom importlib import resources\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import ANY, GET\n\nfrom electricitymap.contrib.parsers.lib.exceptions import ParserException\nfrom electricitymap.contrib.parsers.PF import fetch_production\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    adapter.register_uri(\n        GET,\n        ANY,\n        text=resources.files(\"electricitymap.contrib.parsers.tests.mocks.PF\")\n        .joinpath(\"production_live.html\")\n        .read_text(),\n    )\n\n\n@freeze_time(\"2024-01-01 12:00:00\")\ndef test_fetch_production_live(session, snapshot):\n    \"\"\"That we can fetch the production mix at the current time.\"\"\"\n    assert snapshot == fetch_production(session=session)\n\n\ndef test_fetch_production_raises_parser_exception_on_historical_data(adapter, session):\n    \"\"\"That a ParserException is raised if requesting historical data (not supported yet).\"\"\"\n    adapter.register_uri(GET, ANY, json=[])\n\n    with pytest.raises(\n        ParserException, match=\"This parser is not yet able to parse historical data\"\n    ):\n        historical_datetime = datetime.now(timezone.utc) - timedelta(days=1)\n        fetch_production(target_datetime=historical_datetime, session=session)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_RU.py",
    "content": "\"\"\"Tests for RU.py\"\"\"\n\nimport json\nimport re\nfrom datetime import datetime\nfrom pathlib import Path\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.RU import fetch_exchange, fetch_production\n\nBASE_PATH_TO_MOCK = Path(\"electricitymap/contrib/parsers/tests/mocks/RU\")\n\n\n@pytest.mark.parametrize(\"zone_key\", [\"RU-1\", \"RU-2\", \"RU-AS\"])\n@freeze_time(\"2025-07-28 12:00:00\")\ndef test_snapshot_fetch_production(adapter, session, snapshot, zone_key):\n    \"\"\"Test fetch_production for different Russian zones using mock data.\"\"\"\n    # Determine which zones need to be mocked based on the test zone\n    zones_to_mock = [\"RU-1\", \"RU-2\", \"RU-AS\"] if zone_key == \"RU\" else [zone_key]\n\n    for zone in zones_to_mock:\n        mock_file = BASE_PATH_TO_MOCK / f\"production_{zone}_2025_07_28.json\"\n        if zone in [\"RU-1\", \"RU-2\"]:\n            price_zone = 1 if zone == \"RU-1\" else 2\n            url_pattern = re.compile(\n                rf\".*CommonInfo/PowerGeneration.*priceZone.*={price_zone}.*\"\n            )\n        else:  # RU-AS\n            url_pattern = re.compile(r\".*CommonInfo/GenEquipOptions_Z2.*\")\n\n        adapter.register_uri(\n            GET,\n            url_pattern,\n            json=json.loads(mock_file.read_text()),\n        )\n\n    # Test target datetime corresponding to the mock data\n    target_datetime = datetime(2025, 7, 28, 12, 0)\n\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == fetch_production(\n        zone_key=zone_key,\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n\n@pytest.mark.parametrize(\n    \"zone_key1,zone_key2,hour\",\n    [\n        # Test major exchange pairs with different zones\n        (\"CN\", \"RU-AS\", 10),\n        (\"MN\", \"RU-2\", 10),\n        (\"KZ\", \"RU-1\", 10),\n        (\"KZ\", \"RU-2\", 10),\n        (\"GE\", \"RU-1\", 10),\n        (\"AZ\", \"RU-1\", 10),\n        (\"BY\", \"RU-1\", 10),\n        (\"RU-1\", \"FI\", 10),\n        (\"RU-KGD\", \"LT\", 10),\n        (\"RU-1\", \"UA-CR\", 10),\n        (\"UA\", \"RU-1\", 10),\n        (\"RU-1\", \"RU-2\", 10),\n        # Test different hour to verify temporal behavior\n        (\"CN\", \"RU-AS\", 11),\n        (\"KZ\", \"RU-1\", 11),\n    ],\n)\n@freeze_time(\"2025-07-28 12:00:00\")\ndef test_snapshot_fetch_exchange(\n    adapter, session, snapshot, zone_key1, zone_key2, hour\n):\n    \"\"\"Test fetch_exchange for different exchange pairs using mock data.\"\"\"\n    # Load the appropriate mock file based on hour\n    mock_file = BASE_PATH_TO_MOCK / f\"exchange_2025-07-28_{hour}.json\"\n\n    # Mock the exchange API endpoint with specific pattern\n    url_pattern = re.compile(r\".*flowDiagramm/GetData.*\")\n    adapter.register_uri(\n        GET,\n        url_pattern,\n        json=json.loads(mock_file.read_text()),\n    )\n\n    # Test target datetime corresponding to the mock data\n    target_datetime = datetime(2025, 7, 28, hour, 0)\n\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetch_exchange(\n        zone_key1=zone_key1,\n        zone_key2=zone_key2,\n        session=session,\n        target_datetime=target_datetime,\n    )\n\n\n@freeze_time(\"2025-07-28 12:00:00\")\ndef test_snapshot_fetch_exchange_live(adapter, session, snapshot):\n    \"\"\"Test fetch_exchange without target_datetime (live mode) using mock data.\"\"\"\n    # Mock both hours 10 and 11 for live mode (last 2 hours)\n    for hour in [10, 11]:\n        mock_file = BASE_PATH_TO_MOCK / f\"exchange_2025-07-28_{hour}.json\"\n        url_pattern = re.compile(r\".*flowDiagramm/GetData.*\")\n        adapter.register_uri(\n            GET,\n            url_pattern,\n            json=json.loads(mock_file.read_text()),\n        )\n\n    # Test without target_datetime (live mode) - using a pair not already tested above\n    assert snapshot == fetch_exchange(\n        zone_key1=\"MN\",\n        zone_key2=\"RU\",\n        session=session,\n    )\n\n\n@freeze_time(\"2025-07-28 12:00:00\")\ndef test_snapshot_fetch_production_live(adapter, session, snapshot):\n    \"\"\"Test fetch_production without target_datetime (live mode) using mock data.\"\"\"\n    # Mock all zone endpoints for live mode with specific URL patterns\n    for zone in [\"RU-1\", \"RU-2\", \"RU-AS\"]:\n        mock_file = BASE_PATH_TO_MOCK / f\"production_{zone}_2025_07_28.json\"\n        if zone in [\"RU-1\", \"RU-2\"]:\n            price_zone = 1 if zone == \"RU-1\" else 2\n            url_pattern = re.compile(\n                rf\".*CommonInfo/PowerGeneration.*priceZone.*={price_zone}.*\"\n            )\n        else:  # RU-AS\n            url_pattern = re.compile(r\".*CommonInfo/GenEquipOptions_Z2.*\")\n\n        adapter.register_uri(\n            GET,\n            url_pattern,\n            json=json.loads(mock_file.read_text()),\n        )\n\n    # Test without target_datetime (live mode) - using RU-2 since RU-1 is already tested above\n    assert snapshot == fetch_production(\n        zone_key=\"RU-2\",\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_SG.py",
    "content": "import logging\nfrom importlib import resources\n\nimport pytest\nfrom freezegun import freeze_time\nfrom requests_mock import GET\nfrom testfixtures import LogCapture\n\nfrom electricitymap.contrib.parsers import SG\n\n\n@pytest.fixture(autouse=True)\ndef mock_response(adapter):\n    adapter.register_uri(\n        GET,\n        SG.SOLAR_URL,\n        content=resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n        .joinpath(\"SG_ema_gov_sg_solar_map.png\")\n        .read_bytes(),\n    )\n\n\n@freeze_time(\"2021-12-23 03:21:00\")\ndef test_works_when_nonzero(adapter, session):\n    adapter.register_uri(\n        GET,\n        SG.SOLAR_URL,\n        content=resources.files(\"electricitymap.contrib.parsers.tests.mocks\")\n        .joinpath(\"SG_ema_gov_sg_solar_map_nonzero.png\")\n        .read_bytes(),\n    )\n    assert SG.get_solar(session, logger=logging.getLogger(\"test\")) == 350.55\n\n\n@freeze_time(\"2021-12-23 15:12:00\")\ndef test_works_when_zero(session):\n    assert SG.get_solar(session, logger=logging.getLogger(\"test\")) == 0.0\n\n\n@freeze_time(\"2024-08-06 15:12:00\")\ndef test_ignore_data_older_than_one_hour(session):\n    with LogCapture():\n        assert SG.get_solar(session, logger=logging.getLogger(\"test\")) is None\n\n\n@freeze_time(\"2021-12-23 15:06:00\")\ndef test_allow_remote_clock_to_be_slightly_ahead(session):\n    assert SG.get_solar(session, logger=logging.getLogger(\"test\")) == 0\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_SMARTGRIDDASHBOARD.py",
    "content": "import json\nfrom importlib import resources\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.SMARTGRIDDASHBOARD import (\n    URL,\n    fetch_consumption,\n    fetch_consumption_forecast,\n    fetch_exchange,\n    fetch_production,\n    fetch_total_generation,\n    fetch_wind_solar_forecasts,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_fetch_consumption(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        URL,\n        json=json.loads(\n            resources.files(\n                \"electricitymap.contrib.parsers.tests.mocks.SMARTGRIDDASHBOARD\"\n            )\n            .joinpath(\"consumption.json\")\n            .read_text()\n        ),\n    )\n    assert snapshot == fetch_consumption(\n        zone_key=ZoneKey(\"GB-NIR\"),\n        session=session,\n    )\n\n\ndef test_fetch_consumption_forecast(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        URL,\n        json=json.loads(\n            resources.files(\n                \"electricitymap.contrib.parsers.tests.mocks.SMARTGRIDDASHBOARD\"\n            )\n            .joinpath(\"consumptionForecast.json\")\n            .read_text()\n        ),\n    )\n    assert snapshot == fetch_consumption_forecast(\n        zone_key=ZoneKey(\"IE\"),\n        session=session,\n    )\n\n\ndef test_fetch_exchange(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        URL,\n        json=json.loads(\n            resources.files(\n                \"electricitymap.contrib.parsers.tests.mocks.SMARTGRIDDASHBOARD\"\n            )\n            .joinpath(\"exchange.json\")\n            .read_text()\n        ),\n    )\n    assert snapshot == fetch_exchange(\n        zone_key1=ZoneKey(\"GB\"),\n        zone_key2=ZoneKey(\"GB-NIR\"),\n        session=session,\n    )\n\n\ndef test_fetch_generation(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        URL,\n        json=json.loads(\n            resources.files(\n                \"electricitymap.contrib.parsers.tests.mocks.SMARTGRIDDASHBOARD\"\n            )\n            .joinpath(\"generation.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_total_generation(\n        zone_key=ZoneKey(\"GB-NIR\"),\n        session=session,\n    )\n\n\ndef test_fetch_wind_solar_forecasts(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        f\"{URL}?areas=windforecast\",\n        json=json.loads(\n            resources.files(\n                \"electricitymap.contrib.parsers.tests.mocks.SMARTGRIDDASHBOARD\"\n            )\n            .joinpath(\"windForecast.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        f\"{URL}?areas=solarforecast\",\n        json=json.loads(\n            resources.files(\n                \"electricitymap.contrib.parsers.tests.mocks.SMARTGRIDDASHBOARD\"\n            )\n            .joinpath(\"solarForecast.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_wind_solar_forecasts(\n        zone_key=ZoneKey(\"IE\"),\n        session=session,\n    )\n\n\ndef test_fetch_production(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        f\"{URL}?areas=solaractual\",\n        json=json.loads(\n            resources.files(\n                \"electricitymap.contrib.parsers.tests.mocks.SMARTGRIDDASHBOARD\"\n            )\n            .joinpath(\"solarProduction.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        f\"{URL}?areas=windactual\",\n        json=json.loads(\n            resources.files(\n                \"electricitymap.contrib.parsers.tests.mocks.SMARTGRIDDASHBOARD\"\n            )\n            .joinpath(\"windProduction.json\")\n            .read_text()\n        ),\n    )\n    adapter.register_uri(\n        GET,\n        f\"{URL}?areas=generationactual\",\n        json=json.loads(\n            resources.files(\n                \"electricitymap.contrib.parsers.tests.mocks.SMARTGRIDDASHBOARD\"\n            )\n            .joinpath(\"generation.json\")\n            .read_text()\n        ),\n    )\n\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"IE\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_TAIPOWER.py",
    "content": "from requests_mock import GET\n\nfrom electricitymap.contrib.parsers.TAIPOWER import PRODUCTION_URL, fetch_production\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_production(adapter, session, snapshot):\n    with open(\n        \"electricitymap/contrib/parsers/tests/mocks/TAIPOWER/genary.json\", \"rb\"\n    ) as mock_file:\n        adapter.register_uri(\n            GET,\n            PRODUCTION_URL,\n            content=mock_file.read(),\n        )\n\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"TW\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_TR.py",
    "content": "import json\nimport os\nfrom datetime import datetime\nfrom pathlib import Path\n\nimport pytest\nfrom requests_mock import POST\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers import TR\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/TR\")\n\n\n@pytest.fixture(autouse=True)\ndef tr_credentials_env():\n    os.environ[\"TR_USERNAME\"] = \"test_username\"\n    os.environ[\"TR_PASSWORD\"] = \"test_password\"\n\n\n@pytest.mark.parametrize(\n    \"target_datetime\",\n    [\n        None,\n        datetime(2025, 7, 28, 10, 0),\n    ],\n)\ndef test_fetch_production(adapter, session, snapshot, target_datetime):\n    # Mock the TGT ticket fetch - return a simple ticket string without newlines\n    adapter.register_uri(\n        POST,\n        \"https://giris.epias.com.tr/cas/v1/tickets\",\n        text=\"TGT-1234567890-abcdefghijklmnop-cas\",\n    )\n\n    # Load mock production data from raw API response\n    raw_response = json.loads(\n        (base_path_to_mock / \"raw_production_response.json\").read_text()\n    )\n\n    # Mock the production data API response with empty items to end pagination\n    adapter.register_uri(\n        POST,\n        \"https://seffaflik.epias.com.tr/electricity-service/v1/generation/data/realtime-generation\",\n        [\n            {\"json\": raw_response},\n            {\"json\": {\"items\": []}},  # Empty response to end pagination\n        ],\n    )\n\n    assert snapshot(\n        extension_class=SingleFileAmberSnapshotExtension\n    ) == TR.fetch_production(ZoneKey(\"TR\"), session, target_datetime=target_datetime)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_US_CA.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Tests for US_CA.py\"\"\"\n\nimport zipfile\nfrom logging import getLogger\nfrom unittest.mock import patch\n\nimport pandas as pd\n\nfrom electricitymap.contrib.parsers import US_CA\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_snapshot_fetch_wind_solar_forecasts(snapshot):\n    def _mock_get_oasis_data(*args, **kwargs) -> pd.DataFrame:\n        MOCK_ZIP_FILENAME = \"electricitymap/contrib/parsers/tests/mocks/US_CA/20250204_20250211_SLD_REN_FCST_DAM_20250214_04_52_10_v1.zip\"\n\n        # Read zip and extract the csv file\n        with zipfile.ZipFile(MOCK_ZIP_FILENAME, \"r\") as z:\n            csv_filename = z.namelist()[\n                0\n            ]  # Get the first file in the zip (there is only one file)\n            with z.open(csv_filename) as f:  # Read the CSV file into a pandas DataFrame\n                df = pd.read_csv(f)\n        return df\n\n    # Mock the call to _get_oasis_data with above (with patch)\n    with patch(\n        \"electricitymap.contrib.parsers.US_CA._get_oasis_data\", _mock_get_oasis_data\n    ):\n        parsed_wind_solar_forecasts = US_CA.fetch_wind_solar_forecasts(\n            zone_key=ZoneKey(\"US-CAL-CISO\"), logger=getLogger(\"test\")\n        )\n\n    snapshot.assert_match(parsed_wind_solar_forecasts)\n\n\ndef test_snapshot_fetch_consumption_forecast(snapshot):\n    def _mock_get_oasis_data(*args, **kwargs) -> pd.DataFrame:\n        MOCK_ZIP_FILENAME = \"electricitymap/contrib/parsers/tests/mocks/US_CA/20250219_20250227_SLD_FCST_7DA_20250221_01_09_58_v1.zip\"\n\n        # Read zip and extract the csv file\n        with zipfile.ZipFile(MOCK_ZIP_FILENAME, \"r\") as z:\n            csv_filename = z.namelist()[\n                0\n            ]  # Get the first file in the zip (there is only one file)\n            with z.open(csv_filename) as f:  # Read the CSV file into a pandas DataFrame\n                df = pd.read_csv(f)\n        return df\n\n    # Mock the call to _get_oasis_data with above (with patch)\n    with patch(\n        \"electricitymap.contrib.parsers.US_CA._get_oasis_data\", _mock_get_oasis_data\n    ):\n        result = US_CA.fetch_consumption_forecast(\n            zone_key=ZoneKey(\"US-CAL-CISO\"), logger=getLogger(\"test\")\n        )\n\n    snapshot.assert_match(result)\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_US_ERCOT.py",
    "content": "import re\nfrom json import loads\nfrom pathlib import Path\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.US_ERCOT import (\n    ReportTypeID,\n    fetch_consumption_forecast,\n    fetch_wind_solar_forecasts,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nUS_PROXY = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app\"\nHOST_PARAMETER = \"host=https://www.ercot.com\"\nBASE_PATH_TO_MOCK = Path(\"electricitymap/contrib/parsers/tests/mocks/US_ERCOT\")\n\n\ndef test_snapshot_fetch_consumption_forecast(adapter, session, snapshot):\n    # Mock load forecast request\n    data = Path(BASE_PATH_TO_MOCK, \"load_forecast_by_forecast_zone.json\")\n    adapter.register_uri(\n        GET,\n        re.compile(\n            rf\"{US_PROXY}/misapp/servlets/IceDocListJsonWS\\?reportTypeId={ReportTypeID.LOAD_FORECAST_REPORTID.value}&_\\d+\\&{HOST_PARAMETER}\"\n        ),\n        json=loads(data.read_text()),\n    )\n\n    # Mock specific report id request\n    data_zip_file = Path(BASE_PATH_TO_MOCK, \"load_forecast_specific_reportid.zip\")\n    with open(data_zip_file, \"rb\") as zip_file:\n        zip_content = zip_file.read()\n\n    adapter.register_uri(\n        GET,\n        re.compile(\n            rf\"{US_PROXY}/misdownload/servlets/mirDownload\\?doclookupId=\\d+\\&{HOST_PARAMETER}\"\n        ),\n        content=zip_content,\n    )\n\n    # Run function under test\n    assert snapshot == fetch_consumption_forecast(\n        zone_key=ZoneKey(\"US-TEX-ERCO\"),\n        session=session,\n    )\n\n\ndef test_snapshot_fetch_wind_solar_forecasts(adapter, session, snapshot):\n    # Mock wind forecast request\n    data_wind = Path(\n        BASE_PATH_TO_MOCK,\n        \"wind_power_production_hourly_averaged_actual_and_forecasted_values_rtid.json\",\n    )\n    adapter.register_uri(\n        GET,\n        re.compile(\n            rf\"{US_PROXY}/misapp/servlets/IceDocListJsonWS\\?reportTypeId={ReportTypeID.WIND_POWER_PRODUCTION_REPORTID.value}&_\\d+\\&{HOST_PARAMETER}\"\n        ),\n        json=loads(data_wind.read_text()),\n    )\n\n    # Mock solar forecast request\n    data_solar = Path(\n        BASE_PATH_TO_MOCK,\n        \"solar_power_production_hourly_averaged_actual_and_forecasted_values_rtid.json\",\n    )\n    adapter.register_uri(\n        GET,\n        re.compile(\n            rf\"{US_PROXY}/misapp/servlets/IceDocListJsonWS\\?reportTypeId={ReportTypeID.SOLAR_POWER_PRODUCTION_REPORTID.value}&_\\d+\\&{HOST_PARAMETER}\"\n        ),\n        json=loads(data_solar.read_text()),\n    )\n\n    # Wind specific report id\n    data_wind_zip_file = Path(BASE_PATH_TO_MOCK, \"wind_specific_reportid.zip\")\n    with open(data_wind_zip_file, \"rb\") as zip_file:\n        wind_zip_content = zip_file.read()\n\n    # Solar specific report id\n    data_solar_zip_file = Path(BASE_PATH_TO_MOCK, \"solar_specific_reportid.zip\")\n    with open(data_solar_zip_file, \"rb\") as zip_file:\n        solar_zip_content = zip_file.read()\n\n    request_count = 0  # Global counter to track requests\n\n    def download_callback(request, context):\n        nonlocal request_count\n        request_count += 1  # Increment on each request\n        if request_count == 1:\n            return wind_zip_content  # First request: Wind ZIP data\n        elif request_count == 2:\n            return solar_zip_content  # Second request: Solar ZIP data\n        return None  # Fail for unexpected calls\n\n    # Mock the wind or solar report request\n    adapter.register_uri(\n        GET,\n        re.compile(\n            rf\"{US_PROXY}/misdownload/servlets/mirDownload\\?doclookupId=\\d+\\&{HOST_PARAMETER}\"\n        ),\n        content=download_callback,\n    )\n\n    # Run function under test\n    assert snapshot == fetch_wind_solar_forecasts(\n        zone_key=ZoneKey(\"US-TEX-ERCO\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_US_MISO.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Tests for US_MISO.py\"\"\"\n\nimport json\nimport logging\nimport re\nfrom datetime import datetime\nfrom json import loads\nfrom pathlib import Path\nfrom unittest.mock import patch\nfrom zoneinfo import ZoneInfo\n\nfrom requests_mock import GET\nfrom testfixtures import LogCapture\n\nfrom electricitymap.contrib.parsers import US_MISO\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/US_MISO\")\n\n\ndef test_fetch_production():\n    filename = \"electricitymap/contrib/parsers/tests/mocks/MISO.html\"\n    with open(filename) as f:\n        mock_data = json.load(f)\n    with (\n        LogCapture(),\n        patch(\"electricitymap.contrib.parsers.US_MISO.get_json_data\") as gjd,\n    ):\n        gjd.return_value = mock_data\n        production = US_MISO.fetch_production(logger=logging.getLogger(\"test\"))\n\n    assert production\n    assert production[0][\"production\"][\"coal\"] == 40384.0\n    assert production[0][\"datetime\"] == datetime(\n        2018, 1, 25, 4, 30, tzinfo=ZoneInfo(\"America/New_York\")\n    )\n    assert production[0][\"source\"] == \"misoenergy.org\"\n    assert production[0][\"zoneKey\"] == \"US-MIDW-MISO\"\n    assert isinstance(production[0][\"storage\"], dict)\n\n    # Make sure the unmapped Antimatter type is set to 'unknown'.\n    assert production[0][\"production\"][\"unknown\"] >= 256\n\n\ndef test_snapshot_fetch_wind_solar_forecasts(adapter, session, snapshot):\n    # Mock wind forecast request\n    data_wind = Path(base_path_to_mock, \"DataBrokerServicesgetWindForecast.asmx.json\")\n    adapter.register_uri(\n        GET,\n        \"https://api.misoenergy.org/MISORTWDDataBroker/DataBrokerServices.asmx?messageType=getWindForecast&returnType=json\",\n        json=loads(data_wind.read_text()),\n    )\n\n    # Mock solar forecast request\n    data_solar = Path(base_path_to_mock, \"DataBrokerServicesgetSolarForecast.asmx.json\")\n    adapter.register_uri(\n        GET,\n        \"https://api.misoenergy.org/MISORTWDDataBroker/DataBrokerServices.asmx?messageType=getSolarForecast&returnType=json\",\n        json=loads(data_solar.read_text()),\n    )\n\n    # Run function under test\n    assert snapshot == US_MISO.fetch_wind_solar_forecasts(\n        zone_key=ZoneKey(\"US-MIDW-MISO\"),\n        session=session,\n    )\n\n\ndef test_snapshot_fetch_consumption_forecast(adapter, session, snapshot):\n    # Mock load forecast request\n    data = Path(base_path_to_mock, \"20250310_df_al.xls\")\n    adapter.register_uri(\n        GET,\n        re.compile(r\"https://docs\\.misoenergy\\.org/marketreports/\\d+_df_al.xls\"),\n        content=data.read_bytes(),\n    )\n\n    # Run function under test\n    assert snapshot == US_MISO.fetch_consumption_forecast(\n        zone_key=ZoneKey(\"US-MIDW-MISO\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_US_NEISO.py",
    "content": "import re\nfrom pathlib import Path\n\nimport pytest\nfrom requests_mock import ANY, GET, POST\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.US_NEISO import (\n    fetch_consumption_forecast,\n    fetch_exchange,\n    fetch_wind_solar_forecasts,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/US_NEISO\")\n\n\ndef test_fetch_consumption_forecast(adapter, session, snapshot):\n    # Mock url request\n    data = Path(base_path_to_mock, \"day_ahead_load_forecast_20250317.xml\")\n    adapter.register_uri(\n        POST,\n        \"https://www.iso-ne.com/ws/wsclient\",\n        text=data.read_text(),\n    )\n\n    # Run function under test\n    assert snapshot == fetch_consumption_forecast(\n        zone_key=ZoneKey(\"US-NE-ISNE\"),\n        session=session,\n    )\n\n\ndef test_fetch_wind_solar_forecasts(adapter, session, snapshot):\n    # Mock the initial page requests that set cookies\n    adapter.register_uri(\n        GET,\n        \"https://www.iso-ne.com/isoexpress/web/reports/operations/-/tree/seven-day-solar-power-forecast\",\n        text=\"mock response\",\n    )\n\n    adapter.register_uri(\n        GET,\n        \"https://www.iso-ne.com/isoexpress/web/reports/operations/-/tree/seven-day-wind-power-forecast\",\n        text=\"mock response\",\n    )\n\n    # Mock wind forecast request\n    data_wind = Path(base_path_to_mock, \"seven_day_wind_power_forecast_20250225.csv\")\n    adapter.register_uri(\n        GET,\n        re.compile(r\"https://www\\.iso-ne\\.com/transform/csv/wphf\\?start=\\d+\"),\n        text=data_wind.read_text(),\n    )\n\n    # Mock solar forecast request\n    data_solar = Path(base_path_to_mock, \"seven_day_solar_power_forecast_20250225.csv\")\n    adapter.register_uri(\n        GET,\n        re.compile(r\"https://www\\.iso-ne\\.com/transform/csv/sphf\\?start=\\d+\"),\n        text=data_solar.read_text(),\n    )\n\n    # Run function under test\n    assert snapshot == fetch_wind_solar_forecasts(\n        zone_key=ZoneKey(\"US-NE-ISNE\"),\n        session=session,\n    )\n\n\n@pytest.mark.parametrize(\n    (\"zone_key1, zone_key2\"),\n    [\n        (ZoneKey(\"CA-NB\"), ZoneKey(\"US-NE-ISNE\")),\n        (ZoneKey(\"CA-QC\"), ZoneKey(\"US-NE-ISNE\")),\n        (ZoneKey(\"US-NE-ISNE\"), ZoneKey(\"US-NY-NYIS\")),\n    ],\n)\ndef test_fetch_exchange(adapter, session, snapshot, zone_key1, zone_key2):\n    data = Path(base_path_to_mock, f\"exchange_{zone_key1}_{zone_key2}.json\")\n    adapter.register_uri(\n        POST,\n        ANY,\n        text=data.read_text(),\n    )\n\n    # Run function under test\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetch_exchange(\n        zone_key1=zone_key1,\n        zone_key2=zone_key2,\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_US_NY.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"Tests for US_NY.py\"\"\"\n\nimport datetime as dt\nfrom pathlib import Path\n\nfrom freezegun import freeze_time\n\nfrom electricitymap.contrib.parsers import US_NY\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_snapshot_fetch_consumption_forecast(adapter, session, snapshot):\n    adapter.register_uri(\n        \"GET\",\n        \"http://mis.nyiso.com/public/csv/isolf/20250219isolf.csv\",\n        content=Path(\n            \"electricitymap/contrib/parsers/tests/mocks/US_NY/20250219isolf.csv\"\n        ).read_bytes(),\n    )\n\n    with freeze_time(\"2025-02-20 00:00:00\"):\n        result = US_NY.fetch_consumption_forecast(\n            zone_key=ZoneKey(\"US-NY-NYIS\"),\n            session=session,\n        )\n\n    assert snapshot == result\n\n\ndef test_snapshot_fetch_production_more_than_9_days_in_past(adapter, session, snapshot):\n    adapter.register_uri(\n        \"GET\",\n        \"http://mis.nyiso.com/public/csv/rtfuelmix/20250201rtfuelmix_csv.zip\",\n        content=Path(\n            \"electricitymap/contrib/parsers/tests/mocks/US_NY/20250201rtfuelmix_csv.zip\"\n        ).read_bytes(),\n    )\n\n    result = US_NY.fetch_production(\n        zone_key=ZoneKey(\"US-NY-NYIS\"),\n        session=session,\n        target_datetime=dt.datetime.fromisoformat(\"2025-02-20 00:00:00\"),\n    )\n\n    assert snapshot == result\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_US_PJM.py",
    "content": "import re\nfrom json import loads\nfrom pathlib import Path\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.US_PJM import (\n    fetch_consumption_forecast,\n    fetch_production,\n    fetch_wind_solar_forecasts,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nbase_path_to_mock = Path(\"electricitymap/contrib/parsers/tests/mocks/US_PJM\")\n\n\ndef test_production(adapter, session, snapshot):\n    settings = Path(base_path_to_mock, \"settings.json\")\n    adapter.register_uri(\n        GET,\n        \"https://dataminer2.pjm.com/config/settings.json\",\n        json=loads(settings.read_text()),\n    )\n\n    data = Path(base_path_to_mock, \"gen_by_fuel.json\")\n    adapter.register_uri(\n        GET,\n        re.compile(\n            r\"https://us-ca-proxy-jfnx5klx2a-uw\\.a\\.run\\.app/api/v1/gen_by_fuel.*\"\n        ),\n        json=loads(data.read_text()),\n    )\n\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"US-MIDA-PJM\"),\n        session=session,\n    )\n\n\ndef test_fetch_consumption_forecast(adapter, session, snapshot):\n    # Mock the settings.json request\n    settings = Path(base_path_to_mock, \"settings.json\")\n    adapter.register_uri(\n        GET,\n        \"https://dataminer2.pjm.com/config/settings.json\",\n        json=loads(settings.read_text()),\n    )\n\n    # Mock load forecast request\n    data = Path(base_path_to_mock, \"compressed_pjm_load_forecast_2025-03-19.gz\")\n    adapter.register_uri(\n        GET,\n        re.compile(\n            r\"https://us-ca-proxy-jfnx5klx2a-uw\\.a\\.run\\.app/api/v1/load_frcstd_7_day.*\"\n        ),\n        content=data.read_bytes(),  # content for binary data\n    )\n\n    # Run function under test\n    assert snapshot == fetch_consumption_forecast(\n        zone_key=ZoneKey(\"US-MIDA-PJM\"),\n        session=session,\n    )\n\n\ndef test_fetch_wind_solar_forecasts(adapter, session, snapshot):\n    # Mock the settings.json request\n    settings = Path(base_path_to_mock, \"settings.json\")\n    adapter.register_uri(\n        GET,\n        \"https://dataminer2.pjm.com/config/settings.json\",\n        json=loads(settings.read_text()),\n    )\n\n    # Mock wind forecast request\n    data_wind = Path(base_path_to_mock, \"pjm_wind_forecast_2025-02-24.json\")\n    adapter.register_uri(\n        GET,\n        re.compile(\n            r\"https://us-ca-proxy-jfnx5klx2a-uw\\.a\\.run\\.app/api/v1/hourly_wind_power_forecast.*\"\n        ),\n        json=loads(data_wind.read_text()),\n    )\n\n    # Mock solar forecast request\n    data_solar = Path(base_path_to_mock, \"pjm_solar_forecast_2025-02-24.json\")\n    adapter.register_uri(\n        GET,\n        re.compile(\n            r\"https://us-ca-proxy-jfnx5klx2a-uw\\.a\\.run\\.app/api/v1/hourly_solar_power_forecast.*\"\n        ),\n        json=loads(data_solar.read_text()),\n    )\n\n    # Run function under test\n    assert snapshot == fetch_wind_solar_forecasts(\n        zone_key=ZoneKey(\"US-MIDA-PJM\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_US_SPP.py",
    "content": "import logging\nfrom datetime import datetime, timezone\nfrom pathlib import Path\nfrom unittest.mock import patch\nfrom zoneinfo import ZoneInfo\n\nfrom pandas import read_pickle\nfrom requests_mock import GET\nfrom testfixtures import LogCapture\n\nfrom electricitymap.contrib.parsers import US_SPP\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_fetch_production():\n    filename = \"electricitymap/contrib/parsers/tests/mocks/US_SPP_Gen_Mix.pkl\"\n    mock_data = read_pickle(filename)\n    # Suppress log messages to prevent interfering with test formatting.\n    with LogCapture(), patch(\"electricitymap.contrib.parsers.US_SPP.get_data\") as gd:\n        gd.return_value = mock_data\n        data = US_SPP.fetch_production(\n            zone_key=ZoneKey(\"US-SW-AZPS\"), logger=logging.getLogger(\"test\")\n        )\n        datapoint = data[-1]\n\n    assert isinstance(data, list)\n    assert len(data) == 23\n\n    # Unknown keys must be assigned and summed.\n    assert round(datapoint[\"production\"][\"unknown\"], 2) == 33.1\n    assert datapoint[\"datetime\"] == datetime(2018, 7, 27, 11, 45, tzinfo=timezone.utc)\n    assert datapoint[\"source\"] == \"spp.org\"\n    assert datapoint[\"zoneKey\"] == \"US-SW-AZPS\"\n    assert isinstance(datapoint[\"storage\"], dict)\n\n\ndef test_SPP_logging():\n    \"\"\"Make sure that new generation types are logged properly.\"\"\"\n    filename = \"electricitymap/contrib/parsers/tests/mocks/US_SPP_Gen_Mix.pkl\"\n    mock_data = read_pickle(filename)\n\n    with LogCapture() as log:\n        with patch(\"electricitymap.contrib.parsers.US_SPP.get_data\") as gd:\n            gd.return_value = mock_data\n            US_SPP.fetch_production(\n                zone_key=ZoneKey(\"US-SW-AZPS\"), logger=logging.getLogger(\"test\")\n            )\n        log.check(\n            (\n                \"test\",\n                \"WARNING\",\n                \"\"\"New column 'Flux Capacitor' present in US-SPP data source.\"\"\",\n            )\n        )\n\n\ndef test_fetch_realtime_locational_marginal_price(adapter, session, snapshot):\n    # Mock 8 consecutive 5-minute intervals of LMP data\n    base_url = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app/file-browser-api/download/rtbm-lmp-by-location?host=https://portal.spp.org&path=/2025/03/By_Interval/31/RTBM-LMP-SL-{}.csv\"\n    times = [\n        \"202503310910\",\n        \"202503310905\",\n        \"202503310900\",\n        \"202503310855\",\n        \"202503310850\",\n        \"202503310845\",\n        \"202503310840\",\n    ]\n\n    for time in times:\n        mock_csv = Path(\n            f\"electricitymap/contrib/parsers/tests/mocks/US_SPP/RTBM-LMP-SL-{time}.csv\"\n        )\n        adapter.register_uri(GET, base_url.format(time), text=mock_csv.read_text())\n\n    realtime_LMP = US_SPP.fetch_realtime_locational_marginal_price(\n        zone_key=ZoneKey(\"US-CENT-SWPP\"),\n        session=session,\n        target_datetime=datetime(\n            2025, 3, 31, 9, 10, tzinfo=ZoneInfo(\"America/Chicago\")\n        ),\n    )\n\n    assert snapshot == realtime_LMP\n\n\ndef test_fetch_dayahead_locational_marginal_price(adapter, session, snapshot):\n    mock_csv = Path(\n        \"electricitymap/contrib/parsers/tests/mocks/US_SPP/DA-LMP-SL-202503190100.csv\"\n    )\n    base_url = \"https://us-ca-proxy-jfnx5klx2a-uw.a.run.app/file-browser-api/download/da-lmp-by-location?host=https://portal.spp.org&path=/2025/03/By_Day/DA-LMP-SL-202503190100.csv\"\n\n    adapter.register_uri(GET, base_url, text=mock_csv.read_text())\n\n    dayahead_LMP = US_SPP.fetch_dayahead_locational_marginal_price(\n        zone_key=ZoneKey(\"US-CENT-SWPP\"),\n        session=session,\n        target_datetime=datetime(2025, 3, 19, 1, 0, tzinfo=ZoneInfo(\"America/Chicago\")),\n    )\n\n    assert snapshot == dayahead_LMP\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_UY.py",
    "content": "import re\nfrom pathlib import Path\n\nimport pytest\nfrom requests_mock import GET\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.parsers.UY import (\n    fetch_consumption,\n    fetch_exchange,\n    fetch_production,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\n@pytest.fixture(autouse=True)\ndef register_mock_uris(adapter):\n    html = Path(\"electricitymap/contrib/parsers/tests/mocks/UY/html.html\")\n    adapter.register_uri(\n        GET,\n        \"https://pronos.adme.com.uy/gpf.php\",\n        text=html.read_text(),\n    )\n    data = Path(\"electricitymap/contrib/parsers/tests/mocks/UY/data.ods\")\n    adapter.register_uri(\n        GET,\n        re.compile(r\"https://pronos\\.adme\\.com\\.uy.*cache.*\"),\n        content=data.read_bytes(),\n    )\n\n\ndef test_fetch_production(session, snapshot):\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"UY\"),\n        session=session,\n    )\n\n\ndef test_fetch_consumption(session, snapshot):\n    assert snapshot == fetch_consumption(\n        zone_key=ZoneKey(\"UY\"),\n        session=session,\n    )\n\n\n@pytest.mark.parametrize(\"zone_key\", [ZoneKey(\"AR\"), ZoneKey(\"BR-S\")])\ndef test_fetch_exchange(session, snapshot, zone_key):\n    assert snapshot(extension_class=SingleFileAmberSnapshotExtension) == fetch_exchange(\n        zone_key1=ZoneKey(\"UY\"),\n        zone_key2=zone_key,\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_amper_landsnet.py",
    "content": "import json\nfrom importlib import resources\n\nfrom requests_mock import GET\n\nfrom electricitymap.contrib.parsers.amper_landsnet import SOURCE_URL, fetch_production\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_fetch_production(adapter, session, snapshot):\n    adapter.register_uri(\n        GET,\n        SOURCE_URL,\n        json=json.loads(\n            resources.files(\"electricitymap.contrib.parsers.tests.mocks.amper_landsnet\")\n            .joinpath(\"production.json\")\n            .read_text()\n        ),\n    )\n    assert snapshot == fetch_production(\n        zone_key=ZoneKey(\"IS\"),\n        session=session,\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_config.py",
    "content": "\"\"\"Tests for config/__init__.py.\"\"\"\n\nimport pytest\nfrom syrupy.extensions.single_file import SingleFileAmberSnapshotExtension\n\nfrom electricitymap.contrib.config import emission_factors\n\n\n@pytest.fixture\ndef emission_factor_result(zone_key):\n    \"\"\"Fixture to generate emission factor result in the expected format.\"\"\"\n    return {\n        \"emissionFactors\": {\n            \"defaults\": {\n                key: {\"value\": value, \"source\": \"IPCC 2014\"}\n                for key, value in emission_factors(zone_key).items()\n            },\n            \"zoneOverrides\": {},\n        }\n    }\n\n\n@pytest.mark.parametrize(\"zone_key\", [\"KR\", \"FR\"])\ndef test_snapshot_emission_factor(snapshot, zone_key, emission_factor_result):\n    \"\"\"Test emission factors configuration.\"\"\"\n    assert (\n        snapshot(extension_class=SingleFileAmberSnapshotExtension)\n        == emission_factor_result\n    )\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_quality.py",
    "content": "import pytest\n\nfrom electricitymap.contrib.parsers.lib.quality import (\n    validate_consumption,\n    validate_exchange,\n)\nfrom electricitymap.contrib.parsers.tests.mocks.quality_check import (\n    c1,\n    c2,\n    c3,\n    e1,\n    e2,\n    e3,\n    e4,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\n\ndef test_validate_consumption_positive():\n    assert not validate_consumption(c1, ZoneKey(\"FR\")), \"Positive consumption is fine!\"\n\n\ndef test_validate_consumption_negative():\n    with pytest.raises(ValueError):\n        validate_consumption(c2, ZoneKey(\"FR\"))\n\n\ndef test_validate_consumption_none():\n    assert not validate_consumption(c3, ZoneKey(\"FR\")), \"Consumption can be undefined!\"\n\n\ndef test_validate_exchange_key_mismatch():\n    with pytest.raises(Exception):\n        validate_exchange(e1, \"DK->NA\")\n\n\ndef test_validate_exchange_no_datetime():\n    with pytest.raises(Exception):\n        validate_exchange(e2, \"DK->NO\")\n\n\ndef test_validate_exchange_bad_datetime():\n    with pytest.raises(Exception):\n        validate_exchange(e3, \"DK->NO\")\n\n\ndef test_validate_exchange_future_not_allowed():\n    with pytest.raises(Exception):\n        validate_exchange(e4, \"DK->NO\")\n"
  },
  {
    "path": "electricitymap/contrib/parsers/tests/test_utils.py",
    "content": "from unittest import mock\n\nimport pytest\nimport requests\n\nimport electricitymap.contrib.parsers.lib.utils as tested\n\n\ndef test_TOKEN_WIKI_URL():\n    assert requests.get(tested.TOKEN_WIKI_URL).status_code == 200\n\n\ndef test_get_token():\n    with mock.patch.dict(\n        \"electricitymap.contrib.parsers.lib.utils.os.environ\", {\"token\": \"42\"}\n    ):\n        assert tested.get_token(\"token\") == \"42\"\n\n    with (\n        mock.patch.dict(\"electricitymap.contrib.parsers.lib.utils.os.environ\", {}),\n        pytest.raises(Exception),\n    ):\n        tested.get_token(\"token\")\n\n    with (\n        mock.patch.dict(\n            \"electricitymap.contrib.parsers.lib.utils.os.environ\", {\"token\": \"\"}\n        ),\n        pytest.raises(Exception),\n    ):\n        tested.get_token(\"token\")\n"
  },
  {
    "path": "electricitymap/contrib/py.typed",
    "content": ""
  },
  {
    "path": "geo/.gitignore",
    "content": "# dependencies (bun install)\nnode_modules\n\n# output\nout\ndist\n*.tgz\n\n# code coverage\ncoverage\n*.lcov\n\n# logs\nlogs\n_.log\nreport.[0-9]_.[0-9]_.[0-9]_.[0-9]_.json\n\n# dotenv environment variable files\n.env\n.env.development.local\n.env.test.local\n.env.production.local\n.env.local\n\n# caches\n.eslintcache\n.cache\n*.tsbuildinfo\n\n# IntelliJ based IDEs\n.idea\n\n# Finder (MacOS) folder config\n.DS_Store\n"
  },
  {
    "path": "geo/README.md",
    "content": "# Zone Geo Generator\n\nComputes `bounding_box` and `center_point` for each zone YAML file in `config/zones/` based on the geometries in `world.geojson`.\n\nFor aggregate zones (zones with `subZoneNames`), the geometry is computed by combining all sub-zone geometries.\n\n## Prerequisites\n\n- [Bun](https://bun.sh/) runtime\n\n## Usage\n\n```sh\n# Install dependencies\nbun install\n\n# Generate/update zone geo data\nbun run generate-zone-geo.ts\n```\n\nThis will update all zone YAML files in `config/zones/` with computed `bounding_box` and `center_point` values.\n"
  },
  {
    "path": "geo/generate-zone-geo.ts",
    "content": "import { readFileSync, readdirSync, writeFileSync } from 'fs';\nimport { join } from 'path';\nimport bbox from '@turf/bbox';\nimport buffer from '@turf/buffer';\nimport { centroid } from '@turf/centroid';\nimport pointOnFeature from '@turf/point-on-feature';\nimport union from '@turf/union';\nimport type { Feature, FeatureCollection, MultiPolygon, Polygon } from 'geojson';\n\nconst GEO_PATH = join(import.meta.dir, 'world.geojson');\nconst ZONES_DIR = join(import.meta.dir, '..', 'config', 'zones');\nconst BUFFER_KM = -40;\n\n// Load the geojson\nconst geojson: FeatureCollection<Polygon | MultiPolygon> = JSON.parse(\n  readFileSync(GEO_PATH, 'utf-8')\n);\n\n// Build a map of zoneName -> features\nconst featuresByZone = new Map<string, Feature<Polygon | MultiPolygon>[]>();\nfor (const feature of geojson.features) {\n  const zoneName = feature.properties?.zoneName;\n  if (!zoneName) continue;\n  if (!featuresByZone.has(zoneName)) featuresByZone.set(zoneName, []);\n  featuresByZone.get(zoneName)!.push(feature);\n}\n\n// Parse subZoneNames from YAML files to find aggregate zones\nfunction getSubZoneNames(content: string): string[] {\n  const match = content.match(/subZoneNames:\\n((?:  - .+\\n)+)/);\n  if (!match) return [];\n  return [...match[1]!.matchAll(/  - (.+)/g)].map((m) => m[1]!);\n}\n\ninterface ZoneGeo {\n  centerPoint: [number, number];\n  centroid: [number, number];\n  boundingBox: [[number, number], [number, number]];\n}\n\nfunction computeZoneGeo(features: Feature<Polygon | MultiPolygon>[]): ZoneGeo {\n  const fc: FeatureCollection<Polygon | MultiPolygon> = {\n    type: 'FeatureCollection',\n    features,\n  };\n\n  const combined = features.length === 1 ? features[0]! : union(fc)!;\n  const computedCentroid = centroid(combined);\n\n  // Shrink the polygon inward to keep the center point away from borders.\n  // Fall back to the original geometry if the buffer collapses it.\n  const buffered = buffer(combined, BUFFER_KM, { units: 'kilometers' });\n  const target =\n    buffered && buffered.geometry.coordinates.length > 0 ? buffered : combined;\n\n  const center = pointOnFeature(target);\n  const [minLon, minLat, maxLon, maxLat] = bbox(fc);\n\n  return {\n    centerPoint: center.geometry.coordinates as [number, number],\n    boundingBox: [\n      [minLon, minLat],\n      [maxLon, maxLat],\n    ],\n    centroid: computedCentroid.geometry.coordinates as [number, number],\n  };\n}\n\n// Build a map of zoneName -> geo data\nconst zoneGeos = new Map<string, ZoneGeo>();\n\n// First pass: compute for zones that have their own geometry\nfor (const [zoneName, features] of featuresByZone) {\n  zoneGeos.set(zoneName, computeZoneGeo(features));\n}\n\nconsole.log(`Computed geo data for ${zoneGeos.size} zones from geojson`);\n\n// Second pass: compute for aggregate zones by combining sub-zone geometries\nconst zoneFiles = readdirSync(ZONES_DIR).filter((f) => f.endsWith('.yaml'));\n\nfor (const file of zoneFiles) {\n  const zoneName = file.replace('.yaml', '');\n  if (zoneGeos.has(zoneName)) continue;\n\n  const filePath = join(ZONES_DIR, file);\n  const content = readFileSync(filePath, 'utf-8');\n  const subZoneNames = getSubZoneNames(content);\n  if (subZoneNames.length === 0) continue;\n\n  const subFeatures: Feature<Polygon | MultiPolygon>[] = [];\n  for (const sub of subZoneNames) {\n    const features = featuresByZone.get(sub);\n    if (features) subFeatures.push(...features);\n  }\n\n  if (subFeatures.length === 0) {\n    console.warn(`No sub-zone geometries found for aggregate zone ${zoneName}`);\n    continue;\n  }\n\n  zoneGeos.set(zoneName, computeZoneGeo(subFeatures));\n  console.log(\n    `Computed geo for aggregate zone ${zoneName} from ${subFeatures.length} sub-zone features`\n  );\n}\n\n// Update each zone YAML file\nlet updated = 0;\nlet skipped = 0;\n\nfor (const file of zoneFiles) {\n  const zoneName = file.replace('.yaml', '');\n  const geo = zoneGeos.get(zoneName);\n  if (!geo) {\n    console.warn(`No geometry found for zone ${zoneName}`);\n    skipped++;\n    continue;\n  }\n\n  const filePath = join(ZONES_DIR, file);\n  let content = readFileSync(filePath, 'utf-8');\n\n  // Remove existing bounding_box, center_point, and centroid\n  content = content.replace(/^bounding_box:\\n((?:  .+\\n)+)/m, '');\n  content = content.replace(/^center_point:\\n((?:  - .+\\n)+)/m, '');\n  content = content.replace(/^centroid:\\n((?:  - .+\\n)+)/m, '');\n\n  const [[minLon, minLat], [maxLon, maxLat]] = geo.boundingBox;\n  const [lon, lat] = geo.centerPoint;\n  const [cLon, cLat] = geo.centroid;\n\n  const geoYaml = [\n    `bounding_box:`,\n    `  - - ${minLon}`,\n    `    - ${minLat}`,\n    `  - - ${maxLon}`,\n    `    - ${maxLat}`,\n    `center_point:`,\n    `  - ${lon}`,\n    `  - ${lat}`,\n    `centroid:`,\n    `  - ${cLon}`,\n    `  - ${cLat}`,\n    '',\n  ].join('\\n');\n\n  // Insert at the very beginning (bounding_box is always first, after optional _comment)\n  const commentMatch = content.match(/^_comment:.*\\n((?:  .+\\n)*)/);\n  if (commentMatch) {\n    const insertPos = commentMatch.index! + commentMatch[0].length;\n    content = content.slice(0, insertPos) + geoYaml + content.slice(insertPos);\n  } else {\n    content = geoYaml + content;\n  }\n\n  writeFileSync(filePath, content);\n  updated++;\n}\n\nconsole.log(`\\nUpdated ${updated} zone files, skipped ${skipped}`);\n"
  },
  {
    "path": "geo/package.json",
    "content": "{\n  \"name\": \"geo\",\n  \"module\": \"index.ts\",\n  \"type\": \"module\",\n  \"private\": true,\n  \"scripts\": {\n    \"generate\": \"bun run generate-zone-geo.ts\"\n  },\n  \"devDependencies\": {\n    \"@types/bun\": \"latest\"\n  },\n  \"peerDependencies\": {\n    \"typescript\": \"^5\"\n  },\n  \"dependencies\": {\n    \"@turf/bbox\": \"^7.3.4\",\n    \"@turf/buffer\": \"^7.3.4\",\n    \"@turf/centroid\": \"^7.3.4\",\n    \"@turf/point-on-feature\": \"^7.3.4\",\n    \"@turf/union\": \"^7.3.4\"\n  }\n}\n"
  },
  {
    "path": "geo/tsconfig.json",
    "content": "{\n  \"compilerOptions\": {\n    // Environment setup & latest features\n    \"lib\": [\"ESNext\"],\n    \"target\": \"ESNext\",\n    \"module\": \"Preserve\",\n    \"moduleDetection\": \"force\",\n    \"jsx\": \"react-jsx\",\n    \"allowJs\": true,\n\n    // Bundler mode\n    \"moduleResolution\": \"bundler\",\n    \"allowImportingTsExtensions\": true,\n    \"verbatimModuleSyntax\": true,\n    \"noEmit\": true,\n\n    // Best practices\n    \"strict\": true,\n    \"skipLibCheck\": true,\n    \"noFallthroughCasesInSwitch\": true,\n    \"noUncheckedIndexedAccess\": true,\n    \"noImplicitOverride\": true,\n\n    // Some stricter flags (disabled by default)\n    \"noUnusedLocals\": false,\n    \"noUnusedParameters\": false,\n    \"noPropertyAccessFromIndexSignature\": false\n  }\n}\n"
  },
  {
    "path": "geo/world.geojson",
    "content": "{\n  \"type\": \"FeatureCollection\",\n  \"name\": \"world\",\n  \"crs\": { \"type\": \"name\", \"properties\": { \"name\": \"urn:ogc:def:crs:OGC:1.3:CRS84\" } },\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": { \"zoneName\": \"SE-SE4\", \"countryKey\": \"SE\", \"countryName\": \"Sweden\" },\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [12.375123751237538, 56.911490913169189],\n              [12.352274438535977, 56.993903387090171],\n              [12.46671906063415, 57.017274003453508],\n              [12.64604969615406, 57.21588539210255],\n              [12.93075623929785, 57.218790070799827],\n              [13.05695187170074, 57.37943499043466],\n              [13.493399721822893, 57.304064793975236],\n              [13.500552510704029, 57.273693849828895],\n              [13.575656793955959, 57.273417635356047],\n              [13.634922758971085, 57.402459733820493],\n              [13.716668917612635, 57.46159001614717],\n              [13.894339084285129, 57.466261358858688],\n              [14.036628491670584, 57.320585717697561],\n              [14.224612724452946, 57.332893979176795],\n              [14.271105852180328, 57.383875864735501],\n              [14.361314015525009, 57.368416546112044],\n              [14.41189445118447, 57.308583779960074],\n              [14.592630098806016, 57.244299920345696],\n              [14.754589675614588, 57.236835449311855],\n              [14.973995088124791, 57.172807089329581],\n              [15.08230874832485, 57.380880915534917],\n              [15.285907774691461, 57.355947940458719],\n              [15.360756601197625, 57.378815290795764],\n              [15.536287317624433, 57.376921699235311],\n              [15.568474867589551, 57.395509093318026],\n              [15.631828140536753, 57.390002699726161],\n              [15.860573690313613, 57.465222380212246],\n              [15.979744262208255, 57.412702642979355],\n              [16.043352991901209, 57.396601669933297],\n              [16.091762045221756, 57.319559843136616],\n              [16.150261639999613, 57.317352822653973],\n              [16.226387750234561, 57.289201693773002],\n              [16.249123400606738, 57.327421276700662],\n              [16.268921298402738, 57.329420846760236],\n              [16.270773359809464, 57.343139099295826],\n              [16.251198986666004, 57.369785423540165],\n              [16.390039727983758, 57.367030398054219],\n              [16.562963499088628, 57.323721452873549],\n              [16.564484753150527, 57.323318369874727],\n              [16.46476464764649, 57.177672320099433],\n              [16.583565835658391, 57.044581616634318],\n              [16.093960939609417, 56.419198418631524],\n              [16.039960399604013, 56.254623892841309],\n              [15.852758527585308, 56.085756118552226],\n              [15.571955719557224, 56.205967076520736],\n              [15.319953199532023, 56.140137266204647],\n              [14.686346863468657, 56.147292680369432],\n              [14.769147691476945, 56.031374970899819],\n              [14.477544775447768, 56.031374970899819],\n              [14.207542075420776, 55.821005794454933],\n              [14.36234362343626, 55.523340565199604],\n              [14.182341823418255, 55.390249861734489],\n              [13.883538835388379, 55.433182346723228],\n              [13.278732787327897, 55.34588629391277],\n              [12.958150998345086, 55.4027039672538],\n              [12.903257159209735, 55.570773993248451],\n              [13.062730627306308, 55.675035345493185],\n              [12.922329223292252, 55.749451652807025],\n              [12.504725047250503, 56.274659052502727],\n              [12.796327963279651, 56.227433319015105],\n              [12.619926199262011, 56.419198418631524],\n              [12.889928899289004, 56.454975489455478],\n              [12.871928719287212, 56.649602754737813],\n              [12.731527315273183, 56.646740589071896],\n              [12.598325983259855, 56.821332694692813],\n              [12.375123751237538, 56.911490913169189]\n            ]\n          ],\n          [\n            [\n              [16.573481602306419, 56.819776098892611],\n              [16.837661894380986, 57.006725131241296],\n              [17.033350999621412, 57.330317723841425],\n              [17.199686739075773, 57.377821379018144],\n              [16.416680918686531, 56.207203913707026],\n              [16.377792497065993, 56.470095649402886],\n              [16.573481602306419, 56.819776098892611]\n            ]\n          ],\n          [\n            [\n              [12.722287265538592, 55.909118129803502],\n              [12.705865362515883, 55.888963976093812],\n              [12.667423180439995, 55.920688106933142],\n              [12.694209816964682, 55.92057882968161],\n              [12.722287265538592, 55.909118129803502]\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": { \"zoneName\": \"SE-SE3\", \"countryKey\": \"SE\", \"countryName\": \"Sweden\" },\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [18.563585635856384, 60.227309837133632],\n              [18.329583295832975, 60.285984233284935],\n              [18.505985059850616, 60.155755695485723],\n              [18.819188191881949, 60.114254293329935],\n              [18.948789487894913, 59.899591868386182],\n              [19.082318074652878, 59.873624564749576],\n              [19.066038792008317, 59.724066261491146],\n              [18.412384123841264, 59.491733260993058],\n              [18.009180091800943, 59.408730456681468],\n              [18.275582755827571, 59.312847906873259],\n              [18.415984159841628, 59.139686884085307],\n              [18.041580415804191, 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   [16.249123400606738, 57.327421276700662],\n              [16.226387750234561, 57.289201693773002],\n              [16.150261639999613, 57.317352822653973],\n              [16.091762045221756, 57.319559843136616],\n              [16.043352991901209, 57.396601669933297],\n              [15.979744262208255, 57.412702642979355],\n              [15.860573690313613, 57.465222380212246],\n              [15.631828140536753, 57.390002699726161],\n              [15.568474867589551, 57.395509093318026],\n              [15.536287317624433, 57.376921699235311],\n              [15.360756601197625, 57.378815290795764],\n              [15.285907774691461, 57.355947940458719],\n              [15.08230874832485, 57.380880915534917],\n              [14.973995088124791, 57.172807089329581],\n              [14.754589675614588, 57.236835449311855],\n              [14.592630098806016, 57.244299920345696],\n              [14.41189445118447, 57.308583779960074],\n              [14.361314015525009, 57.368416546112044],\n              [14.271105852180328, 57.383875864735501],\n              [14.224612724452946, 57.332893979176795],\n              [14.036628491670584, 57.320585717697561],\n              [13.894339084285129, 57.466261358858688],\n              [13.716668917612635, 57.46159001614717],\n              [13.634922758971085, 57.402459733820493],\n              [13.575656793955959, 57.273417635356047],\n              [13.500552510704029, 57.273693849828895],\n              [13.493399721822893, 57.304064793975236],\n              [13.05695187170074, 57.37943499043466],\n              [12.93075623929785, 57.218790070799827],\n              [12.64604969615406, 57.21588539210255],\n              [12.46671906063415, 57.017274003453508],\n              [12.352274438535977, 56.993903387090171],\n              [12.10175632188246, 57.507640953067934],\n              [11.95325522054484, 57.366970378728197],\n              [11.705517055170588, 57.721483796623602],\n              [11.687516875168768, 57.837401506093229],\n              [11.554056052889548, 57.958661711604435],\n              [11.4855648660554, 58.062330648344854],\n              [11.358366947649124, 58.145049743754896],\n              [11.413914139141411, 58.431300881770937],\n              [11.230312303123043, 58.339711580461596],\n              [11.287912879128811, 58.580133496398602],\n              [11.118711187111899, 58.969388026963259],\n              [11.159284817463636, 59.074285017403206],\n              [11.298017754860162, 59.115941244950811],\n              [11.370713707137099, 59.101047647595436],\n              [11.453514535145388, 58.896402802482385],\n              [11.665916659166612, 58.920731210642685],\n              [11.806318063180669, 59.294243830044806],\n              [11.676716767167704, 59.558994154142098],\n              [11.903519035190385, 59.76936333058697],\n              [11.849518495184981, 59.872401294559978],\n              [12.144721447214494, 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  },
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    "path": "libs/types/pyproject.toml",
    "content": "[project]\nname = \"electricitymap-contrib-types\"\nversion = \"1.1.1\"\ndescription = \"Type definitions for Electricity Maps\"\nauthors = [{ name = \"Electricity Maps\", email = \"app@electricitymaps.com\" }]\nrequires-python = \">= 3.10, < 3.14\"\nlicense = \"AGPL-3.0-or-later\"\ndependencies = [\n    \"pydantic>=1.10.17,<2\",\n]\n\n[build-system]\nrequires = [\"hatchling\"]\nbuild-backend = \"hatchling.build\"\n\n[tool.hatch.build.targets.sdist]\ninclude = [\n    \"src/electricitymap\",\n]\nexclude = [\n    \"**/tests\",\n    \"**/test_*.py\",\n]\n\n[tool.hatch.build.targets.wheel]\ninclude = [\n    \"src/electricitymap\",\n]\nexclude = [\n    \"**/tests\",\n    \"**/test_*.py\",\n]\npackages = [\"src/electricitymap\"]\n"
  },
  {
    "path": "libs/types/src/electricitymap/contrib/types/__init__.py",
    "content": "\"\"\"Electricity Maps type definitions.\"\"\"\n\nfrom enum import Enum\nfrom typing import NewType\n\nZoneKey = NewType(\"ZoneKey\", str)\n\"\"\"\nZoneKey is used throughout the code to identify zones.\nThese are uppercase with 1-3 parts separated by dashes,\nwhere the first part is a two-letter country code,\ne.g. \"AU\", \"AU-TAS\", \"AU-TAS-CBI\".\n\"\"\"\n\nPoint = NewType(\"Point\", tuple[float, float])\n\"\"\"\nPoint represents a geographic coordinate as (longitude, latitude).\nFor example, the point (150.47, -33.48) represents 150.47°E, 33.48°S.\n\"\"\"\n\nBoundingBox = NewType(\"BoundingBox\", list[Point])\n\"\"\"\nBoundingBox indicate a geographic area of a zone.\nAn example bounding box looks like: [[140.46, -39.64], [150.47, -33.48]],\nrepresenting a box with corners at 140.46°E, 39.64°S and 150.47°E, 33.48°S.\n\"\"\"\n\n\nclass ParserDataType(Enum):\n    CONSUMPTION = \"consumption\"\n    CONSUMPTION_FORECAST = \"consumptionForecast\"\n    DAYAHEAD_LOCATIONAL_MARGINAL_PRICE = \"dayaheadLocationalMarginalPrice\"\n    EXCHANGE_FORECAST = \"exchangeForecast\"\n    EXCHANGE = \"exchange\"\n    GENERATION_FORECAST = \"generationForecast\"\n    PRICE = \"price\"\n    PRICE_INTRADAY = \"priceIntraday\"\n    PRODUCTION = \"production\"\n    PRODUCTION_PER_MODE_FORECAST = \"productionPerModeForecast\"\n    PRODUCTION_PER_MODE_FORECAST_DAY_AHEAD = \"productionPerModeForecastDayAhead\"\n    PRODUCTION_PER_MODE_FORECAST_INTRADAY = \"productionPerModeForecastIntraday\"\n    PRODUCTION_PER_MODE_FORECAST_LATEST = \"productionPerModeForecastLatest\"\n    REALTIME_LOCATIONAL_MARGINAL_PRICE = \"realtimeLocationalMarginalPrice\"\n    EXCHANGE_CAPACITY_FORECAST_DAY_AHEAD = \"exchangeCapacityForecastDayAhead\"\n    EXCHANGE_CAPACITY_FORECAST_WEEK_AHEAD = \"exchangeCapacityForecastWeekAhead\"\n    EXCHANGE_CAPACITY_FORECAST_MONTH_AHEAD = \"exchangeCapacityForecastMonthAhead\"\n    SHADOW_AUCTION_ATC_DAY_AHEAD = \"shadowAuctionAtcDayAhead\"\n    CORE_EXTERNAL_ATC_DAY_AHEAD = \"coreExternalAtcDayAhead\"\n    MAX_BEX_DAY_AHEAD = \"maxBexDayAhead\"\n    SCHEDULED_EXCHANGES_DAY_AHEAD = \"scheduledExchangesDayAhead\"\n    MAX_BFLOW_DAY_AHEAD = \"maxBflowDayAhead\"\n    # TODO: Double check if we should keep them here?\n    PRODUCTION_CAPACITY = \"productionCapacity\"\n    GRID_ALERTS = \"gridAlerts\"\n\n    def __str__(self) -> str:\n        return self.value\n\n\nALL_DATA_TYPES = [dt.value for dt in ParserDataType]\n# TODO rename and move this one in the EXCHANGE_PUBLICATION_DATA_TYPES\nEXCHANGE_CAPACITY_FORECAST_DATA_TYPES = [\n    ParserDataType.EXCHANGE_CAPACITY_FORECAST_DAY_AHEAD,\n    ParserDataType.EXCHANGE_CAPACITY_FORECAST_WEEK_AHEAD,\n    ParserDataType.EXCHANGE_CAPACITY_FORECAST_MONTH_AHEAD,\n]\n# TSO-published ex-ante values on a cross-border exchange (sourceType=published):\n# capacities, cleared market-coupling schedules, physical flow limits. All carry\n# the two-zone-key call convention.\nEXCHANGE_PUBLICATION_DATA_TYPES = [\n    ParserDataType.SHADOW_AUCTION_ATC_DAY_AHEAD,\n    ParserDataType.CORE_EXTERNAL_ATC_DAY_AHEAD,\n    ParserDataType.MAX_BEX_DAY_AHEAD,\n    ParserDataType.SCHEDULED_EXCHANGES_DAY_AHEAD,\n    ParserDataType.MAX_BFLOW_DAY_AHEAD,\n]\n# Every ParserDataType registered on the exchange side (two-zone-key call\n# convention). Consumers asking \"is this an exchange-side data type?\" should\n# use this list directly — no need to recombine the sub-groupings. The\n# sub-groupings above are kept for consumers that want a specific semantic\n# family (e.g. only NTC forecasts, or only TSO-published values).\nEXCHANGE_DATA_TYPES = [\n    ParserDataType.EXCHANGE,\n    ParserDataType.EXCHANGE_FORECAST,\n    *EXCHANGE_CAPACITY_FORECAST_DATA_TYPES,\n    *EXCHANGE_PUBLICATION_DATA_TYPES,\n]\nLMP_DATA_TYPES = [\n    ParserDataType.REALTIME_LOCATIONAL_MARGINAL_PRICE,\n    ParserDataType.DAYAHEAD_LOCATIONAL_MARGINAL_PRICE,\n]\n\n__all__: list[str] = [\n    \"ZoneKey\",\n    \"Point\",\n    \"BoundingBox\",\n    \"ParserDataType\",\n    \"ALL_DATA_TYPES\",\n    \"EXCHANGE_CAPACITY_FORECAST_DATA_TYPES\",\n    \"EXCHANGE_DATA_TYPES\",\n    \"EXCHANGE_PUBLICATION_DATA_TYPES\",\n    \"LMP_DATA_TYPES\",\n]\n"
  },
  {
    "path": "parsers.dockerfile",
    "content": "# Container image that executes the parser tests\n# Build with \"$ docker build -f parsers.dockerfile -t parsers . \"\n# Run with  \"$ docker run parsers US-CAL-CISO production\"\n# If needed, pass any token env var using \"docker run -e TOKEN=<token>\"\n\nFROM astral/uv:python3.10-bookworm-slim\nWORKDIR /workspace\nRUN apt-get update && apt-get install -y python3-opencv tesseract-ocr tesseract-ocr-jpn tesseract-ocr-eng libgl1\nCOPY . .\nRUN uv sync --frozen --group dev --extra parsers --compile-bytecode\nENTRYPOINT [\"uv\", \"run\", \"test_parser\"]\n"
  },
  {
    "path": "pyproject.toml",
    "content": "[project]\nname = \"electricitymap-contrib\"\nversion = \"1.8.1\"\ndescription = \"\"\nauthors = [{ name = \"Electricity Maps\", email = \"app@electricitymaps.com\" }]\nrequires-python = \">= 3.10, < 3.14\"\nlicense = \"AGPL-3.0-or-later\"\ndependencies = [\n    \"electricitymap-contrib-types\",\n    \"pydantic>=1.10.17,<2\",\n    \"PyYAML>=6.0,<7\",\n    \"ruamel-yaml>=0.17.24,<0.18\",\n    \"tzdata>=2025.2,<2026\",\n    \"numpy>=2.0.0,<3\",\n]\n\n[project.scripts]\ntest-parser = \"test_parser:test_parser\"\ntest_parser = \"test_parser:test_parser\"\ncapacity_update = \"capacity_update:capacity_update\"\ncheck = \"scripts.tooling:check\"\nformat = \"scripts.tooling:format\"\nlint = \"scripts.tooling:lint\"\ntest = \"scripts.tooling:test\"\n\n[tool.uv.workspace]\nmembers = [\".\", \"libs/types\"]\n\n[tool.uv]\nrequired-version = \">=0.4.0\"\n# The electricitymaps index is for consumers of the published package.\n# For local development, workspace sources take precedence.\nindex = [\n    { name = \"pypi\", url = \"https://pypi.org/simple/\", default = true },\n    { name = \"electricitymaps\", url = \"https://europe-west1-python.pkg.dev/tmrow-152415/libs/simple/\", explicit = true },\n]\n\n# For local development, the workspace member takes precedence.\n# When published, consumers will use the index above.\n[tool.uv.sources]\nelectricitymap-contrib-types = { workspace = true }\n\n[project.optional-dependencies]\nparsers = [\n    \"beautifulsoup4~=4.6.0\",\n    \"demjson3>=3.0.5,<4\",\n    \"imageio>=2.18.0,<3\",\n    \"lxml>=4.9.1,<5\",\n    \"pandas>=1.5, <3\",\n    \"pytesseract==0.2.0\",\n    \"requests~=2.33.0\",\n    \"opencv-python>=4.10.0,<5\",\n    \"xlrd>=2.0.1,<3\",\n    \"freezegun>=0.3.15,<0.4\",\n    \"signalr-client-threads~=0.0.12\",\n    \"openpyxl>=3.1.2,<4\",\n    \"pydataxm>=0.3.2,<0.4\",\n    \"pycountry>=22.3.5,<23\",\n    \"odfpy>=1.4.1,<2\",\n]\n\n[dependency-groups]\ndev = [\n    \"ruff==0.15.4\",\n    \"pytest>=7.4.0,<8\",\n    \"syrupy>=4.8.0,<5\",\n    \"requests-mock~=1.3.0\",\n    \"testfixtures>=7.0.0,<8\",\n    \"click>=8.0.0,<9\",\n]\n\nscripts = [\"xmltodict>=0.13.0,<0.14\"]\n\n[tool.hatch.build.targets.sdist]\ninclude = [\n    \"electricitymap\",\n    \"config\",\n]\nexclude = [\n    \"**/tests\",\n    \"**/test_*.py\",\n    \"tests\",\n    \"test_parser.py\",\n    \"capacity_update.py\",\n    \"**/*.java\",\n]\n\n[tool.hatch.build.targets.wheel]\ninclude = [\n    \"electricitymap\",\n    \"config\",\n]\nexclude = [\n    \"**/tests\",\n    \"**/test_*.py\",\n    \"tests\",\n    \"test_parser.py\",\n    \"capacity_update.py\",\n    \"**/*.java\",\n]\n\n[build-system]\nrequires = [\"hatchling\"]\nbuild-backend = \"hatchling.build\"\n\n\n[tool.pytest.ini_options]\ntestpaths = [\n  \"tests\",\n  \"electricitymap/contrib/parsers/tests\",\n  \"electricitymap/contrib/parsers/lib/tests\",\n  \"electricitymap/contrib/capacity_parsers/tests\",\n  \"electricitymap/contrib/lib/tests\",\n]\naddopts = \"--color=yes --durations=10\"\n\n[tool.ruff]\n# Exclude a variety of commonly ignored directories.\nexclude = [\n  \".bzr\",\n  \".direnv\",\n  \".eggs\",\n  \".git\",\n  \".git-rewrite\",\n  \".hg\",\n  \".mypy_cache\",\n  \".nox\",\n  \".pants.d\",\n  \".pytype\",\n  \".ruff_cache\",\n  \".svn\",\n  \".tox\",\n  \".venv\",\n  \"__pypackages__\",\n  \"_build\",\n  \"buck-out\",\n  \"build\",\n  \"dist\",\n  \"node_modules\",\n  \"venv\",\n  \"electricitymap/contrib/parsers/archived\",\n]\n\n# Same as Black.\nline-length = 88\nindent-width = 4\n\ntarget-version = \"py310\"\n\n[tool.ruff.lint]\n# Enable Pyflakes (`F`) and a subset of the pycodestyle (`E`)  codes by default.\n# Unlike Flake8, Ruff doesn't enable pycodestyle warnings (`W`) or\n# McCabe complexity (`C901`) by default.\nselect = [\n  \"E4\",\n  \"E7\",\n  \"E9\",\n  \"F\",\n  \"UP\",\n  \"I\",\n  \"DTZ003\",\n  \"DTZ004\",\n  \"B\",\n  \"A\",\n  \"C4\",\n  \"SIM\",\n  \"NPY\",\n]\nignore = [\n  \"B008\", # This flags every parser we have, let's ignore it for now\n  \"B017\", # TODO: Fix this\n]\n\n# Allow fix for all enabled rules (when `--fix`) is provided.\nfixable = [\"ALL\"]\nunfixable = []\n\n# Allow unused variables when underscore-prefixed.\ndummy-variable-rgx = \"^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$\"\n\n[tool.ruff.lint.isort]\nknown-first-party = [\"electricitymap\"]\n\n[tool.ruff.format]\n# Like Black, use double quotes for strings.\nquote-style = \"double\"\n\n# Like Black, indent with spaces, rather than tabs.\nindent-style = \"space\"\n\n# Like Black, respect magic trailing commas.\nskip-magic-trailing-comma = false\n\n# Like Black, automatically detect the appropriate line ending.\nline-ending = \"auto\"\n"
  },
  {
    "path": "scripts/ENTSOE_capacity_update.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"\nThis script updates the installed capacities of a zone in the zones config.\n\nIt can either parse the capacities from the ENTSOE API or from a CSV file. The\nCSV file must be in the same format as the one downloaded from the ENTSOE API.\nThe script will aggregate the capacities according to the way it is stated in\nparsers.ENTSOE.ENTSOE_PARAMETER_GROUPS.\n\"\"\"\n\nimport argparse\nimport datetime\nimport json\nimport os\nimport sys\nfrom copy import deepcopy\n\nimport pandas as pd\nimport requests\nimport xmltodict\nimport yaml\nfrom utils import ROOT_PATH, run_shell_command\n\nfrom electricitymap.contrib.config import CONFIG_DIR\nfrom electricitymap.contrib.config.reading import read_zones_config\nfrom electricitymap.contrib.parsers.ENTSOE import (\n    ENTSOE_DOMAIN_MAPPINGS,\n    ENTSOE_PARAMETER_DESC,\n    ENTSOE_PARAMETER_GROUPS,\n)\nfrom electricitymap.contrib.parsers.lib.utils import get_token\nfrom electricitymap.contrib.types import ZoneKey\n\nZONES_CONFIG = read_zones_config(config_dir=CONFIG_DIR)\n\n\ndef update_zone(zone_key: ZoneKey, data: dict) -> None:\n    if zone_key not in ZONES_CONFIG:\n        raise ValueError(f\"Zone {zone_key} does not exist in the zones config\")\n\n    _new_zone_config = deepcopy(ZONES_CONFIG[zone_key])\n    _new_zone_config[\"capacity\"].update(data)\n    # sort keys\n    _new_zone_config[\"capacity\"] = {\n        k: _new_zone_config[\"capacity\"][k] for k in sorted(_new_zone_config[\"capacity\"])\n    }\n    ZONES_CONFIG[zone_key] = _new_zone_config\n\n    with open(\n        CONFIG_DIR.joinpath(f\"zones/{zone_key}.yaml\"), \"w\", encoding=\"utf-8\"\n    ) as f:\n        f.write(yaml.dump(_new_zone_config, default_flow_style=False))\n\n\ndef aggregate_data(data: dict) -> dict:\n    \"\"\"Aggregates data the way it is stated in\n    parsers.ENTSOE.ENTSOE_PARAMETER_GROUPS\"\"\"\n    categories = dict(ENTSOE_PARAMETER_GROUPS[\"production\"])\n    categories.update(ENTSOE_PARAMETER_GROUPS[\"storage\"])\n\n    aggregated = {}\n    for group, category_abbreviations in categories.items():\n        aggregated[group] = sum(data.get(c, 0) for c in category_abbreviations)\n\n    return aggregated\n\n\ndef parse_args():\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"--api-token\", help=\"Security token of the ENTSOE API\")\n    parser.add_argument(\"zone_key\", help=\"The zone key abbreviation (e.g. AT)\")\n    parser.add_argument(\n        \"data_file\",\n        nargs=\"?\",\n        help=\"The csv file from ENTSOE containing the installed capacities\",\n    )\n    return parser.parse_args()\n\n\ndef parse_from_entsoe_api(zone_key: ZoneKey, token: str) -> dict:\n    \"\"\"Parses installed generation capacities from the ENTSOE API.\n\n    See: https://transparency.entsoe.eu/content/static_content/Static%20content/web%20api/Guide.html#_reference_documentation\n    \"\"\"\n    if zone_key not in ENTSOE_DOMAIN_MAPPINGS:\n        print(\n            f\"Zone {zone_key} does not exist in the ENTSOE domain mapping\",\n            file=sys.stderr,\n        )\n        exit(1)\n\n    domain = ENTSOE_DOMAIN_MAPPINGS[zone_key]\n\n    # TODO not sure whether selecting the date always works like that\n    date = datetime.datetime.now().strftime(\"%Y%m%d\")\n    url = (\n        f\"https://web-api.tp.entsoe.eu/api?securityToken={token}\"\n        f\"&documentType=A68&processType=A33&in_Domain={domain}\"\n        f\"&periodStart={date}0000&periodEnd={date}0000\"\n    )\n    response = requests.get(url)\n    if response.status_code != 200:\n        print(\n            f\"ERROR: Request to ENTSOE API failed with status {response.status_code}\",\n            file=sys.stderr,\n        )\n        exit(1)\n\n    data = xmltodict.parse(response.text)\n\n    result = {}\n    try:\n        root = data[\"GL_MarketDocument\"]\n        for time_series in root[\"TimeSeries\"]:\n            generation_type = time_series[\"MktPSRType\"][\"psrType\"]\n            value = time_series[\"Period\"][\"Point\"][\"quantity\"]\n            result[generation_type] = int(value)\n    except Exception as e:\n        raise ValueError(\n            f\"Data for zone {zone_key} could not be retrieved from ENTSOE\", e\n        ) from e\n\n    return result\n\n\ndef parse_from_csv(filepath: str) -> dict:\n    data = pd.read_csv(filepath).set_index(\"Production Type\").to_dict()\n\n    # Choose the column with the most current data;\n    # assume keys start with YYYY.\n    sorted_keys = sorted(data.keys())\n    data = data[sorted_keys[-1]]\n\n    inverse_mapping = {v: k for k, v in ENTSOE_PARAMETER_DESC.items()}\n    return {inverse_mapping[k]: v for k, v in data.items() if k in inverse_mapping}\n\n\ndef main():\n    args = parse_args()\n\n    zone_key = args.zone_key\n    data_file = args.data_file\n\n    if data_file is not None:\n        if not os.path.exists(data_file):\n            print(f\"ERROR: Data file {data_file} does not exist.\", file=sys.stderr)\n            sys.exit(1)\n        data = parse_from_csv(data_file)\n    else:\n        token = args.api_token or get_token(\"ENTSOE_TOKEN\")\n        if token is None:\n            print(\n                \"ERROR: If no CSV file is given, the option --api-token must be provided\",\n                file=sys.stderr,\n            )\n            exit(1)\n\n        data = parse_from_entsoe_api(zone_key, token)\n\n    aggregated_data = aggregate_data(data)\n\n    print(f\"Aggregated capacities: {json.dumps(aggregated_data)}\")\n    print(f\"Updating zone {zone_key}\")\n\n    update_zone(zone_key, aggregated_data)\n\n    run_shell_command(\n        f\"npx prettier --write {ROOT_PATH / 'config/zones/'}\", cwd=ROOT_PATH\n    )\n\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "scripts/__init__.py",
    "content": ""
  },
  {
    "path": "scripts/create_aggregated_zone_config.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"\nCreate an aggregation zone config file by looking up sub zones based on the\nzone name. Sums capacities, all contributors.\n\nExample usage:\n    uv run python scripts/create_aggregated_zone_config US US-Central\n\"\"\"\n\nimport argparse\nfrom copy import deepcopy\nfrom pathlib import Path\n\nimport yaml\n\nfrom electricitymap.contrib.config.model import Capacity, Zone\n\nNAME_MAPPING = {\"hydro storage\": \"hydro_storage\", \"battery storage\": \"battery_storage\"}\n\n\ndef create_aggregated_config(zoneKey: str, timezone: str):\n    zone = Zone(\n        key=zoneKey,\n        sub_zone_names=[],\n        timezone=timezone,\n        contributors=[],\n        capacity=Capacity(),\n    )\n    zone.parsers = None\n    for path in Path(\"config/zones\").glob(f\"{zoneKey}-*.yaml\"):\n        if path.is_file():\n            with open(path) as file:\n                subzone = yaml.safe_load(file.read())\n                zone.sub_zone_names.append(path.stem)\n                if \"contributors\" in subzone:\n                    zone.contributors = list(\n                        set(zone.contributors + subzone[\"contributors\"])\n                    )\n                if \"capacity\" in subzone:\n                    capacities: dict = subzone[\"capacity\"]\n                    for key, capacity in capacities.items():\n                        mapped_key = NAME_MAPPING.get(key, key)\n                        if capacity is not None:\n                            current_capacity = zone.capacity.__getattribute__(\n                                mapped_key\n                            )\n                            if current_capacity is None:\n                                current_capacity = 0\n                            zone.capacity.__setattr__(\n                                mapped_key, current_capacity + capacity\n                            )\n\n    zoneDict = deepcopy(zone.__dict__)\n    for key, item in zone.__dict__.items():\n        if item is None:\n            del zoneDict[key]\n\n    del zoneDict[\"key\"]\n    zoneDict[\"subZoneNames\"] = zoneDict.pop(\"sub_zone_names\")\n    zoneDict[\"subZoneNames\"] = sorted(zoneDict[\"subZoneNames\"])\n    zoneDict[\"capacity\"] = deepcopy(zone.capacity.__dict__)\n\n    zoneDict[\"capacity\"][\"hydro storage\"] = zoneDict[\"capacity\"].pop(\"hydro_storage\")\n    zoneDict[\"capacity\"][\"battery storage\"] = zoneDict[\"capacity\"].pop(\n        \"battery_storage\"\n    )\n    for key, value in zoneDict[\"capacity\"].items():\n        if value is not None:\n            zoneDict[\"capacity\"][key] = round(value, 1)\n\n    with open(f\"config/zones/{zoneKey}.yaml\", \"w\") as file:\n        yaml.safe_dump(zoneDict, file)\n\n\ndef main():\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"zone\", help=\"The parent zone name (e.g. US)\")\n    parser.add_argument(\"timezone\", help=\"The timezone of the parentzone\")\n    args = parser.parse_args()\n    zone = args.zone\n    timezone = args.timezone\n\n    print(f\"Creating {zone}\")\n    create_aggregated_config(zone, timezone)\n    print(f\"Created {zone}.yaml in config/zones.\")\n\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "scripts/remove_zone.py",
    "content": "#!/usr/bin/env python3\n\n\"\"\"\nThis script helps to remove a zone (including the zone config and exchanges).\n\nExample usage:\n  uv run python scripts/remove_zone.py DK-DK1\n\"\"\"\n\nimport argparse\nimport os\nimport re\nfrom glob import glob\n\nfrom utils import (\n    ROOT_PATH,\n    YamlFilePatcher,\n    run_shell_command,\n)\n\nfrom electricitymap.contrib.config.constants import EXCHANGE_FILENAME_ZONE_SEPARATOR\nfrom electricitymap.contrib.types import ZoneKey\n\nPRETTIER_CONFIG_PATH = ROOT_PATH / \".prettierrc.js\"\n\n\ndef remove_config(zone_key: ZoneKey):\n    try:\n        os.remove(ROOT_PATH / f\"config/zones/{zone_key}.yaml\")\n        print(f\"🧹 Removed {zone_key}.yaml\")\n    except FileNotFoundError:\n        pass\n\n\ndef remove_from_parent_config(zone_key: ZoneKey):\n    # Remove zone-key from subZoneNames in parent yaml file\n    parent_config_path = ROOT_PATH / f\"config/zones/{zone_key.split('-')[0]}.yaml\"\n    if parent_config_path.exists():\n        with YamlFilePatcher(parent_config_path) as f:\n            sub_zone_names = f.content[\"subZoneNames\"]\n            if zone_key in sub_zone_names:\n                sub_zone_names.remove(zone_key)\n        run_shell_command(\n            f\"npx prettier@2 --config {PRETTIER_CONFIG_PATH} --write {parent_config_path}\",\n            cwd=ROOT_PATH,\n        )\n\n\ndef remove_exchanges(zone_key: ZoneKey):\n    def _is_zone_in_exchange(exchange_config_path: str) -> bool:\n        exchange_key = exchange_config_path.split(\"/\")[-1].split(\".\")[0]\n        return zone_key in exchange_key.split(EXCHANGE_FILENAME_ZONE_SEPARATOR)\n\n    exchanges = [\n        e\n        for e in glob(str(ROOT_PATH / \"config/exchanges/*.yaml\"))\n        if _is_zone_in_exchange(e)\n    ]\n    for exchange in exchanges:\n        try:\n            os.remove(exchange)\n            print(f\"🧹 Removed {exchange.split('/')[-1]}\")\n        except FileNotFoundError:\n            pass\n\n\ndef move_parser_to_archived(zone_key: ZoneKey):\n    parser_path = ROOT_PATH / f\"parsers/{zone_key}.py\"\n    if parser_path.exists():\n        run_shell_command(\n            f\"git mv {parser_path} {ROOT_PATH / 'parsers/archived'}\", cwd=ROOT_PATH\n        )\n        print(\"🧹 Moved parser to /archived folder\")\n\n\ndef find_files_mentioning_zone(text):\n    \"\"\"Search for the zone_key across all files in contrib.\"\"\"\n    IGNORED_PATHS = [\n        \"node_modules\",\n        \"dist\",\n        \"archived\",\n    ]\n    VALID_EXTENSIONS = (\n        \".py\",\n        \".js\",\n        \".jsx\",\n        \".ts\",\n        \".tsx\",\n        \".yaml\",\n        \".json\",\n        \".md\",\n        \".html\",\n    )\n    results = []\n    for root, _dirs, files in os.walk(ROOT_PATH):\n        if any(ignored_path in root for ignored_path in IGNORED_PATHS):\n            continue\n        for file in files:\n            if file.endswith(VALID_EXTENSIONS):\n                with open(os.path.join(root, file)) as f:\n                    if re.search(text, f.read()):\n                        # print the relative path\n                        results.append(\n                            os.path.relpath(os.path.join(root, file), ROOT_PATH)\n                        )\n    if not results:\n        print(\n            f'🧹 Found no additional files mentioning \"{text}\" in contrib repository.'\n        )\n        return\n\n    print(\n        f\"❗️ Found {len(results)} files mentioning {text}, please manually clean these files:\"\n    )\n    for result in results:\n        print(f\"  - {result}\")\n\n\ndef main():\n    \"\"\"Removes a zone by from a bunch of places and lists additional files mentioning the zone key.\"\"\"\n\n    if os.name != \"posix\":\n        print(\"This script only works on Unix-like systems.\")\n        exit(1)\n\n    parser = argparse.ArgumentParser()\n    parser.add_argument(\"zone\", help=\"The zone abbreviation (e.g. AT)\")\n    args = parser.parse_args()\n    zone_key = args.zone\n\n    print(f\"Removing {zone_key}...\\n\")\n\n    remove_config(zone_key)\n    remove_from_parent_config(zone_key)\n    remove_exchanges(zone_key)\n    move_parser_to_archived(zone_key)\n    # For legacy reasons, a subzone parser can both use dash and underscore\n    # in the file name so we need to search for both\n    move_parser_to_archived(zone_key.replace(\"-\", \"_\"))\n    find_files_mentioning_zone(zone_key)\n\n    print(\"\\n✔  All done!\")\n\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "scripts/tooling.py",
    "content": "\"\"\"\nUtility Python scripts runnable using 'uv run'.\n\nFor example:\n    uv run lint\n    uv run format\n\"\"\"\n\nimport subprocess\nimport sys\n\n\ndef _run(cmd: str):\n    cmd_with_args = f\"{cmd} {' '.join(sys.argv[1:])}\"\n    print(f\"⚙︎ {cmd_with_args}\")\n    r = subprocess.run(cmd_with_args, shell=True).returncode\n    if r != 0:\n        print(f\"FAILED: {cmd}\")\n        sys.exit(r)\n\n\ndef format():  # noqa: A001\n    _run(\"ruff check . --fix\")\n    _run(\"ruff format .\")\n\n\ndef lint():\n    _run(\"ruff check .\")\n\n\ndef test():\n    _run(\"pytest\")\n\n\ndef check():\n    _run(\"ruff format --check .\")\n    lint()\n    test()\n"
  },
  {
    "path": "scripts/update_capacity_configuration.py",
    "content": "import importlib\nimport logging\nfrom copy import deepcopy\nfrom datetime import datetime\nfrom operator import itemgetter\nfrom typing import Any\n\nfrom requests import Session\n\nfrom electricitymap.contrib.config import CONFIG_DIR, ZONE_PARENT\nfrom electricitymap.contrib.config.constants import PRODUCTION_MODES, STORAGE_MODES\nfrom electricitymap.contrib.config.reading import read_zones_config\nfrom electricitymap.contrib.parsers.lib.parsers import PARSER_DATA_TYPE_TO_DICT\nfrom electricitymap.contrib.types import ParserDataType, ZoneKey\nfrom scripts.utils import write_zone_config\n\nlogger = logging.getLogger(__name__)\nZONES_CONFIG = read_zones_config(CONFIG_DIR)\nCAPACITY_MODES = PRODUCTION_MODES + [f\"{mode} storage\" for mode in STORAGE_MODES]\n\n\nCAPACITY_PARSERS = PARSER_DATA_TYPE_TO_DICT[ParserDataType.PRODUCTION_CAPACITY]\n\n# Get productionCapacity source to zones mapping\nCAPACITY_PARSER_SOURCE_TO_ZONES = {}\nfor zone_id, zone_config in ZONES_CONFIG.items():\n    if zone_config.get(\"parsers\", {}).get(\"productionCapacity\") is None:\n        continue\n    source = zone_config.get(\"parsers\", {}).get(\"productionCapacity\").split(\".\")[0]\n    if source not in CAPACITY_PARSER_SOURCE_TO_ZONES:\n        CAPACITY_PARSER_SOURCE_TO_ZONES[source] = []\n    CAPACITY_PARSER_SOURCE_TO_ZONES[source].append(zone_id)\n\n\ndef update_zone(\n    zone: ZoneKey, target_datetime: datetime, session: Session, update_aggregate: bool\n) -> None:\n    \"\"\"Generate capacity config and update the zone config yaml for a zone\"\"\"\n    if zone not in CAPACITY_PARSERS:\n        raise ValueError(f\"No capacity parser developed for {zone}\")\n    parser = CAPACITY_PARSERS[zone]\n\n    zone_capacity = parser(\n        zone_key=zone, target_datetime=target_datetime, session=session\n    )\n    if not zone_capacity:\n        raise ValueError(f\"No capacity data for {zone} in {target_datetime.date()}\")\n    update_zone_capacity_config(zone, zone_capacity)\n\n    if update_aggregate:\n        zone_parent = ZONE_PARENT[zone]\n        update_aggregated_capacity_config(zone_parent)\n\n\ndef update_source(source: str, target_datetime: datetime, session: Session) -> None:\n    \"\"\"Generate capacity config and update the zone config yaml for all zones included in source\"\"\"\n    if source not in CAPACITY_PARSER_SOURCE_TO_ZONES:\n        raise ValueError(f\"No capacity parser developed for {source}\")\n    parser = importlib.import_module(\n        f\"electricitymap.contrib.capacity_parsers.{source}\"\n    ).fetch_production_capacity_for_all_zones\n    source_capacity = parser(target_datetime=target_datetime, session=session)\n\n    for zone in source_capacity:\n        if not source_capacity[zone]:\n            print(f\"No capacity data for {zone} in {target_datetime.date()}\")\n            continue\n        if zone in ZONES_CONFIG:\n            update_zone_capacity_config(zone, source_capacity[zone])\n\n\ndef sort_config_keys(config: dict[str, Any]) -> dict[str, Any]:\n    \"\"\"Sort the keys of the config dict\"\"\"\n    return {k: config[k] for k in sorted(config)}\n\n\ndef update_zone_capacity_config(zone_key: ZoneKey, data: dict) -> None:\n    \"\"\"Update the capacity config for a zone\"\"\"\n    if zone_key not in ZONES_CONFIG:\n        raise ValueError(f\"Zone {zone_key} does not exist in the zones config\")\n    _new_zone_config = deepcopy(ZONES_CONFIG[zone_key])\n    if \"capacity\" in _new_zone_config:\n        capacity = _new_zone_config[\"capacity\"]\n\n        if all(isinstance(capacity[m], float | int) for m in capacity):\n            # TODO: this is temporary as it handles the case of the deprecated system where capacity is a single value. It will be removed in the future\n            capacity = {key: [value] for key, value in data.items()}\n        else:\n            capacity = generate_zone_capacity_config(capacity, data)\n    else:\n        capacity = {key: [value] for key, value in data.items() if value[\"value\"] > 0}\n\n    _new_zone_config[\"capacity\"] = capacity\n\n    # sort keys\n    _new_zone_config[\"capacity\"] = sort_config_keys(_new_zone_config[\"capacity\"])\n\n    write_zone_config(zone_key, _new_zone_config)\n\n\ndef generate_zone_capacity_config(\n    capacity_config: dict[str, Any], data: dict[str, Any]\n) -> dict[str, Any]:\n    \"\"\"Generate capacity config depending on the type of the existing capacity data.\n    If the existing capacity is simply a value, it will be overwritten with the new format.\n    If the existing capacity is a list, the new data will be appended to the list.\n    If the existing capacity is a dict, the new data will be add to create list if the datetime is different else the datapoint is overwritten.\n    \"\"\"\n    existing_capacity_modes = [mode for mode in data if mode in capacity_config]\n    updated_capacity_config = deepcopy(capacity_config)\n    for mode in existing_capacity_modes:\n        if isinstance(capacity_config[mode], float | int):\n            if (\n                data[mode][\"value\"] == 0\n            ):  # Remove data points with 0 value if the existing capacity is a single value\n                continue\n            updated_capacity_config[mode] = [data[mode]]\n        elif isinstance(capacity_config[mode], list):\n            updated_capacity_config[mode] = generate_zone_capacity_list(\n                mode, capacity_config, data\n            )\n        else:\n            raise ValueError(f\"Invalid capacity config type for {mode}\")\n\n    new_modes = [m for m in data if m not in capacity_config and data[m][\"value\"] > 0]\n    for mode in new_modes:\n        updated_capacity_config[mode] = [data[mode]]\n    return updated_capacity_config\n\n\ndef update_capacity_list_if_value_already_exists(\n    mode: str, capacity_config: dict[str, Any], new_capacity: dict[str, Any]\n) -> list[dict[str, Any]]:\n    \"\"\"Updates the capacity config for a zone if the capacity config is a list and the value already exists.\n    This function ensures that we don't add the same value to the config over and over and that we can backfill and get the oldest value for which the capacity is valid.\n    \"\"\"\n    existing_value_datetime = [\n        item\n        for item in capacity_config[mode]\n        if item[\"value\"] == new_capacity[mode][\"value\"]\n    ][0][\"datetime\"]\n    if new_capacity[mode][\"datetime\"] > existing_value_datetime:\n        # if the associated datetime is more recent than the existing one, we don't add it\n        return capacity_config[mode]\n    else:\n        # if the associated datetime is older than the existing one, we replace the datetime of the item\n        return sorted(\n            [\n                new_capacity[mode]\n                if item[\"value\"] == new_capacity[mode][\"value\"]\n                else item\n                for item in capacity_config[mode]\n            ],\n            key=itemgetter(\"datetime\"),\n        )\n\n\ndef update_capacity_list_if_datetime_already_exists(\n    mode: str, capacity_config: dict[str, Any], new_capacity: dict[str, Any]\n) -> list[dict[str, Any]]:\n    \"\"\"Updates the capacity config for a zone if the capacity config is a list and the datetime already exists.\n    If the new value is the same as the most recent previous entry, removes the redundant entry.\"\"\"\n    # Sort the existing capacity config by datetime\n    sorted_config = sorted(capacity_config[mode], key=itemgetter(\"datetime\"))\n\n    # Find the index of the entry with the matching datetime\n    target_index = next(\n        i\n        for i, item in enumerate(sorted_config)\n        if item[\"datetime\"] == new_capacity[mode][\"datetime\"]\n    )\n\n    # Check if this is the earliest entry\n    if target_index == 0:\n        # If it's the earliest entry, just update it\n        return sorted(\n            [\n                new_capacity[mode]\n                if item[\"datetime\"] == new_capacity[mode][\"datetime\"]\n                else item\n                for item in capacity_config[mode]\n            ],\n            key=itemgetter(\"datetime\"),\n        )\n\n    # Check if the new value is the same as the most recent previous entry\n    if new_capacity[mode][\"value\"] == sorted_config[target_index - 1][\"value\"]:\n        # If it's the same, remove this entry as it's redundant\n        return sorted(\n            [\n                item\n                for item in capacity_config[mode]\n                if item[\"datetime\"] != new_capacity[mode][\"datetime\"]\n            ],\n            key=itemgetter(\"datetime\"),\n        )\n\n    # Otherwise, update the entry with the new value\n    return sorted(\n        [\n            new_capacity[mode]\n            if item[\"datetime\"] == new_capacity[mode][\"datetime\"]\n            else item\n            for item in capacity_config[mode]\n        ],\n        key=itemgetter(\"datetime\"),\n    )\n\n\ndef generate_zone_capacity_list(\n    mode: str, capacity_config: dict[str, Any], new_capacity: dict[str, Any]\n) -> list[dict[str, Any]]:\n    \"\"\"Generate the updated capacity config for a zone if the capacity config is a list.\n    Optimizes storage by not adding redundant entries with the same value as the most recent previous entry.\"\"\"\n    # First check if the datetime already exists\n    if new_capacity[mode][\"datetime\"] in [d[\"datetime\"] for d in capacity_config[mode]]:\n        return update_capacity_list_if_datetime_already_exists(\n            mode, capacity_config, new_capacity\n        )\n    # If the datetime doesn't exist, we need to add the new capacity\n    # Sort the existing capacity config by datetime to check chronological order\n    sorted_config = sorted(capacity_config[mode], key=itemgetter(\"datetime\"))\n\n    # Find entries with datetimes before the new entry\n    entries_before = [\n        item\n        for item in sorted_config\n        if item[\"datetime\"] < new_capacity[mode][\"datetime\"]\n    ]\n\n    # Find entries with datetimes after the new entry\n    entries_after = [\n        item\n        for item in sorted_config\n        if item[\"datetime\"] > new_capacity[mode][\"datetime\"]\n    ]\n\n    # If this is the earliest entry, we should add it\n    if not entries_before:\n        # Check if the next entry (if any) has the same value as the new entry\n        if entries_after and entries_after[0][\"value\"] == new_capacity[mode][\"value\"]:\n            # If the next entry has the same value, it's redundant - remove it\n            return sorted(\n                [\n                    item\n                    for item in sorted_config\n                    if item[\"datetime\"] != entries_after[0][\"datetime\"]\n                ]\n                + [new_capacity[mode]],\n                key=itemgetter(\"datetime\"),\n            )\n        else:\n            return sorted(\n                capacity_config[mode] + [new_capacity[mode]], key=itemgetter(\"datetime\")\n            )\n\n    # If the most recent entry before has a different value, we should add it\n    if entries_before[-1][\"value\"] != new_capacity[mode][\"value\"]:\n        # Check if the next entry (if any) has the same value as the new entry\n        if entries_after and entries_after[0][\"value\"] == new_capacity[mode][\"value\"]:\n            # If the next entry has the same value, it's redundant - remove it\n            return sorted(\n                [\n                    item\n                    for item in sorted_config\n                    if item[\"datetime\"] != entries_after[0][\"datetime\"]\n                ]\n                + [new_capacity[mode]],\n                key=itemgetter(\"datetime\"),\n            )\n        else:\n            return sorted(\n                capacity_config[mode] + [new_capacity[mode]], key=itemgetter(\"datetime\")\n            )\n\n    # If the value is the same as the most recent entry before, we don't need to add it\n    return capacity_config[mode]\n\n\ndef check_capacity_config_type(capacity_config: list, config_type: type) -> bool:\n    \"\"\"Check that the capacity config is of the specified type\"\"\"\n    return all(isinstance(item, config_type) for item in capacity_config)\n\n\ndef generate_aggregated_capacity_config(\n    parent_zone: ZoneKey,\n) -> dict[str, Any] | None:\n    \"\"\"Generate the aggregated capacity config for a parent zone\"\"\"\n    zone_keys = [zone for zone in ZONE_PARENT if ZONE_PARENT[zone] == parent_zone]\n    parent_capacity_config = ZONES_CONFIG[parent_zone][\"capacity\"]\n\n    all_capacity_configs = [ZONES_CONFIG[zone][\"capacity\"] for zone in zone_keys]\n\n    for mode in CAPACITY_MODES:\n        mode_capacity_configs = [\n            capacity_config[mode] for capacity_config in all_capacity_configs\n        ]\n\n        if not check_capacity_config_type(\n            mode_capacity_configs, type(mode_capacity_configs[0])\n        ):\n            raise ValueError(\n                f\"{parent_zone} capacity could not be updated because all capacity configs must have the same type\"\n            )\n\n        if check_capacity_config_type(mode_capacity_configs, list):\n            parent_capacity_config[mode] = generate_aggregated_capacity_config_list(\n                mode_capacity_configs, parent_zone\n            )\n        else:\n            raise ValueError(\n                f\"{parent_zone} capacity could not be updated because all capacity configs must be  a list\"\n            )\n    return parent_capacity_config\n\n\ndef generate_aggregated_capacity_config_dict(\n    capacity_config: list[dict[str, Any]], parent_zone: ZoneKey\n) -> dict[str, Any] | None:\n    \"\"\"Generate aggregated capacity config for a parent zone if the capacity config of the subzones are a dict\"\"\"\n    datetime_values = {\n        capacity_config[\"datetime\"] for capacity_config in capacity_config\n    }\n    sources = {capacity_config[\"source\"] for capacity_config in capacity_config}\n    if len(datetime_values) != 1:\n        logger.warning(\n            f\"{parent_zone} capacity could not be updated because all capacity configs must have the same datetime values\"\n        )\n        return None\n    else:\n        updated_capacity = {}\n        aggregated_value = compute_aggregated_value(capacity_config)\n        updated_capacity[\"datetime\"] = list(datetime_values)[0]\n        updated_capacity[\"value\"] = aggregated_value\n        updated_capacity[\"source\"] = \", \".join(\n            [elem for elem in sources if elem is not None]\n        )\n        return sort_config_keys(updated_capacity)\n\n\ndef compute_aggregated_value(capacity_config: list[dict[str, Any]]) -> float | None:\n    \"\"\"Compute the aggregated capacity value as the sum of all subzone capacities\"\"\"\n    if all(capacity_config[\"value\"] is None for capacity_config in capacity_config):\n        return None\n\n    aggregated_value = sum(\n        [\n            0 if capacity_config[\"value\"] is None else capacity_config[\"value\"]\n            for capacity_config in capacity_config\n        ]\n    )\n    return aggregated_value\n\n\ndef generate_aggregated_capacity_config_list(\n    capacity_config: list[Any], parent_zone: ZoneKey\n) -> list[dict[str, Any]] | None:\n    \"\"\"Generate the aggregated capacity config for a parent zone if the capacity config of the subzones are a list\"\"\"\n    flat_capacity_config = [item for sublist in capacity_config for item in sublist]\n    datetime_values = {item[\"datetime\"] for item in flat_capacity_config}\n    updated_aggregated_capacity_config = []\n    for dt in datetime_values:\n        datetime_capacity_config = [\n            item for item in flat_capacity_config if item[\"datetime\"] == dt\n        ]\n        if len(datetime_capacity_config) == len(\n            ZONES_CONFIG[ZoneKey(parent_zone)][\"subZoneNames\"]\n        ):\n            updated_aggregated_capacity_config.append(\n                generate_aggregated_capacity_config_dict(\n                    datetime_capacity_config, parent_zone\n                )\n            )\n        else:\n            logger.warning(\n                f\"{parent_zone} capacity could not be updated for {dt} because not all capacities are available\"\n            )\n    return updated_aggregated_capacity_config\n\n\ndef update_aggregated_capacity_config(parent_zone: ZoneKey) -> None:\n    \"\"\"Update the aggregated capacity config for a parent zone\"\"\"\n    if parent_zone not in ZONES_CONFIG:\n        raise ValueError(f\"Zone {parent_zone} does not exist in the zones config\")\n\n    _new_zone_config = deepcopy(ZONES_CONFIG[parent_zone])\n    _new_zone_config[\"capacity\"] = generate_aggregated_capacity_config(parent_zone)\n\n    if _new_zone_config[\"capacity\"] is not None:\n        # sort keys\n        _new_zone_config[\"capacity\"] = sort_config_keys(_new_zone_config[\"capacity\"])\n        ZONES_CONFIG[parent_zone] = _new_zone_config\n        write_zone_config(parent_zone, _new_zone_config)\n    else:\n        logger.warning(\n            f\"{parent_zone} capacity could not be updated because not all capacities are available\"\n        )\n"
  },
  {
    "path": "scripts/update_capacity_ember_all_years.py",
    "content": "#!/usr/bin/env python3\n\"\"\"\nScript to update capacity data from EMBER for all available years at once.\n\nThis script is specifically designed for EMBER data which provides all years\nin a single API call. It updates the zone configuration files with all available\nyears from EMBER in one go, rather than year-by-year.\n\nUsage:\n    # Update a single zone with all years:\n    uv run python scripts/update_capacity_ember_all_years.py FR\n\n    # Update all EMBER zones with all years (many API calls!):\n    uv run python scripts/update_capacity_ember_all_years.py --all\n\"\"\"\n\nimport argparse\nimport logging\nimport re\n\nfrom requests import Session\nfrom ruamel.yaml import YAML\n\nfrom electricitymap.contrib.capacity_parsers.EMBER import (\n    EMBER_ZONES,\n    fetch_production_capacity_all_years,\n)\nfrom electricitymap.contrib.config import CONFIG_DIR\nfrom electricitymap.contrib.types import ZoneKey\nfrom scripts.update_capacity_configuration import sort_config_keys\n\nlogger = logging.getLogger(__name__)\nlogging.basicConfig(\n    level=logging.INFO, format=\"%(asctime)s - %(name)s - %(levelname)s - %(message)s\"\n)\n\n\ndef update_zone_with_all_years(zone_key: ZoneKey, capacity_data: dict) -> None:\n    \"\"\"Update a zone's capacity configuration with all years from EMBER.\n\n    This function REPLACES THE ENTIRE 'capacity' section with EMBER data only.\n    All existing capacity data from other sources (ENTSOE, manual entries, etc.)\n    will be removed. Other sections (emissionFactors, parsers, etc.) remain\n    completely untouched with EXACT original formatting preserved.\n\n    Args:\n        zone_key: The zone key to update\n        capacity_data: Dictionary with capacity per mode as lists of years\n    \"\"\"\n    zone_file = CONFIG_DIR.joinpath(f\"zones/{zone_key}.yaml\")\n\n    if not zone_file.exists():\n        raise ValueError(f\"Zone file for {zone_key} does not exist\")\n\n    # Read the entire file as text\n    with open(zone_file, encoding=\"utf-8\") as f:\n        original_content = f.read()\n\n    # Sort capacity keys\n    sorted_capacity = sort_config_keys(capacity_data)\n\n    # Generate just the capacity section using ruamel.yaml\n    yaml = YAML()\n    yaml.preserve_quotes = True\n    yaml.default_flow_style = False\n    yaml.indent(mapping=2, sequence=4, offset=2)\n\n    # Create a minimal dict with just capacity for serialization\n    from io import StringIO\n\n    capacity_stream = StringIO()\n    yaml.dump({\"capacity\": sorted_capacity}, capacity_stream)\n    new_capacity_yaml = capacity_stream.getvalue()\n\n    # Extract just the capacity section (remove the trailing newline and get content)\n    # The output will be \"capacity:\\n  biomass:\\n  ...\"\n\n    # Find and replace the capacity section in the original file\n    # Pattern: match from \"capacity:\" to the next top-level key (or end of file)\n    pattern = r\"^capacity:.*?(?=^[a-zA-Z]|\\Z)\"\n\n    # Replace the capacity section\n    updated_content = re.sub(\n        pattern,\n        new_capacity_yaml.rstrip() + \"\\n\",\n        original_content,\n        flags=re.MULTILINE | re.DOTALL,\n    )\n\n    # Write back\n    with open(zone_file, \"w\", encoding=\"utf-8\") as f:\n        f.write(updated_content)\n\n    logger.info(f\"Updated {zone_key} with {len(capacity_data)} modes\")\n\n\ndef main():\n    parser = argparse.ArgumentParser(\n        description=\"Update capacity data from EMBER for all available years\"\n    )\n    parser.add_argument(\n        \"zone_key\",\n        nargs=\"?\",\n        help=\"Zone key to update (e.g., FR). If not provided, use --all to update all zones.\",\n    )\n    parser.add_argument(\n        \"--all\",\n        action=\"store_true\",\n        help=\"Update all EMBER zones (WARNING: This will make many API calls!)\",\n    )\n\n    args = parser.parse_args()\n\n    session = Session()\n\n    if args.all:\n        logger.info(f\"Updating capacity data for all {len(EMBER_ZONES)} EMBER zones...\")\n\n        success_zones = []\n        failed_zones = []\n\n        for zone_key in sorted(EMBER_ZONES):\n            try:\n                logger.info(f\"Processing {zone_key}...\")\n                capacity_data = fetch_production_capacity_all_years(zone_key, session)\n\n                if capacity_data:\n                    update_zone_with_all_years(zone_key, capacity_data)\n                    logger.info(f\"✓ Updated {zone_key}\")\n                    success_zones.append(zone_key)\n                else:\n                    logger.warning(f\"⚠ No capacity data found for {zone_key}\")\n                    failed_zones.append(zone_key)\n            except Exception as e:\n                logger.error(f\"✗ Failed to update {zone_key}: {e}\")\n                failed_zones.append(zone_key)\n                continue\n\n        logger.info(\"\\n=== Summary ===\")\n        logger.info(f\"Successfully updated: {len(success_zones)}/{len(EMBER_ZONES)}\")\n        logger.info(f\"Failed: {len(failed_zones)}/{len(EMBER_ZONES)}\")\n\n        if failed_zones:\n            logger.info(f\"\\nFailed zones: {', '.join(failed_zones)}\")\n\n    elif args.zone_key:\n        zone_key = args.zone_key\n        if zone_key not in EMBER_ZONES:\n            logger.error(\n                f\"Zone {zone_key} is not in EMBER_ZONES. Available zones: {EMBER_ZONES}\"\n            )\n            return\n\n        logger.info(f\"Fetching capacity data for {zone_key}...\")\n        capacity_data = fetch_production_capacity_all_years(zone_key, session)\n\n        update_zone_with_all_years(zone_key, capacity_data)\n        logger.info(f\"✓ Successfully updated {zone_key}\")\n\n    else:\n        parser.print_help()\n\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "scripts/utils.py",
    "content": "\"\"\"Contains utility functions, e.g. for patching JSON files.\"\"\"\n\nimport json\nimport pathlib\nimport subprocess\nfrom os import PathLike\nfrom typing import Any\n\nimport yaml\n\nfrom electricitymap.contrib.config import CONFIG_DIR\nfrom electricitymap.contrib.types import ZoneKey\n\nROOT_PATH = pathlib.Path(__file__).parent.parent\n\n\ndef run_shell_command(cmd: str, cwd: PathLike | str = \"\") -> str:\n    return subprocess.check_output(cmd, shell=True, encoding=\"utf8\", cwd=cwd).rstrip(\n        \"\\n\"\n    )\n\n\nclass JsonFilePatcher:\n    \"\"\"\n    A helping hand to patch JSON files.\n\n    Example:\n\n    with JsonFilePatcher(ROOT_PATH / \"geo/world.geojson\") as f:\n        if zone in f.content:\n            del f.content[zone]\n    \"\"\"\n\n    def __init__(self, file_path: PathLike | str, indent: int | None = 2):\n        self.file_path = file_path\n        self.indent = indent\n\n    def __enter__(self):\n        with open(self.file_path) as f:\n            self.content: dict = json.load(f)\n\n        return self\n\n    def __exit__(self, exc_type, exc_value, tb):\n        if exc_type is not None:\n            raise\n\n        with open(self.file_path, \"w\") as f:\n            json.dump(\n                self.content,\n                f,\n                indent=self.indent,\n                ensure_ascii=False,\n            )\n            # TODO: enable sort_keys=True\n            f.write(\"\\n\")\n\n        print(f\"🧹 Patched {self.file_path.relative_to(ROOT_PATH)}\")\n\n\nclass YamlFilePatcher:\n    \"\"\"\n    A helping hand to patch YAML files.\n\n    Example:\n\n    with YamlFilePatcher(ROOT_PATH / \"geo/world.yaml\") as f:\n        if zone in f.content:\n            del f.content[zone]\n    \"\"\"\n\n    def __init__(self, file_path: PathLike | str):\n        self.file_path = file_path\n\n    def __enter__(self):\n        with open(self.file_path, encoding=\"utf-8\") as f:\n            self.content: dict = yaml.safe_load(f)\n\n        return self\n\n    def __exit__(self, exc_type, exc_value, tb):\n        if exc_type is not None:\n            raise\n\n        with open(self.file_path, \"w\") as f:\n            f.write(yaml.dump(self.content, default_flow_style=False))\n        print(f\"🧹 Patched {self.file_path.relative_to(ROOT_PATH)}\")\n\n\ndef write_zone_config(zone_key: ZoneKey, zone_config: dict[str, Any]) -> None:\n    with open(\n        CONFIG_DIR.joinpath(f\"zones/{zone_key}.yaml\"), \"w\", encoding=\"utf-8\"\n    ) as f:\n        f.write(yaml.dump(zone_config, default_flow_style=False))\n    print(f\"Updated {zone_key}.yaml with new capacity data\")\n"
  },
  {
    "path": "scripts/validate_config_filenames.py",
    "content": "\"\"\"\nThis script checks if the config filenames are valid.\n\nThis is run as a part of the CI but can be run locally to ensure all filenames\nare valid before you commit the changes.\n\nUsage:\n    uv run python scripts/validate_config_filenames.py\n\"\"\"\n\nimport os\n\n\ndef main():\n    zone_files = os.listdir(\"config/zones\")\n    exchange_files = os.listdir(\"config/exchanges\")\n    has_zone_error: bool = False\n    has_exchange_error: bool = False\n\n    print(\"Checking config files...\")\n    print(\"Checking if zone files are valid...\")\n\n    # Check if zone files are valid. Zone files must be uppercase.\n    for file in zone_files:\n        if file.endswith(\".yaml\") or file.endswith(\".yml\"):\n            file = file.replace(\".yaml\", \"\") or file.replace(\".yml\", \"\")\n            if file != file.upper():\n                has_zone_error = True\n                print(f\"ERROR: {file} is not uppercase\")\n    if not has_zone_error:\n        print(\"All zone filenames are valid!\")\n    else:\n        print(\"There are errors in the above zone filenames!\")\n\n    # Check if exchange files are valid. Exchange files must be sorted and\n    # uppercase.\n    for file in exchange_files:\n        if file.endswith(\".yaml\") or file.endswith(\".yml\"):\n            file = file.replace(\".yaml\", \"\") or file.replace(\".yml\", \"\")\n            exchange_keys = file.split(\"_\")\n            sorted_exchange_keys = sorted(exchange_keys)\n            if file != file.upper():\n                has_exchange_error = True\n                print(f\"ERROR: {file} is not uppercase\")\n            if exchange_keys != sorted_exchange_keys:\n                has_exchange_error = True\n                print(f\"ERROR: {file} is not sorted\")\n    if not has_exchange_error:\n        print(\"All exchange filenames are valid!\")\n    else:\n        print(\"There are errors in the above exchange filenames!\")\n\n    if has_zone_error or has_exchange_error:\n        exit(1)\n\n\nif __name__ == \"__main__\":\n    main()\n"
  },
  {
    "path": "scripts/zone_names.py",
    "content": "import json\nimport os\n\nimport yaml\n\n\ndef add_country_names():\n    json_path = os.path.join(os.path.dirname(__file__), \"../config/zone_names.json\")\n    zones_dir = os.path.join(os.path.dirname(__file__), \"../config/zones\")\n    with open(json_path, encoding=\"utf-8\") as f:\n        data = json.load(f)\n        zones = data[\"zoneShortName\"]\n    for key, value in zones.items():\n        country_name = value.get(\"countryName\") or value.get(\"zoneName\")\n        zone_name = value.get(\"zoneName\")\n        zone_short_name = value.get(\"zoneShortName\")\n        if not country_name:\n            print(f\"Zone {key} is in the JSON file but has no country name\")\n            continue\n        yaml_path = os.path.join(zones_dir, f\"{key}.yaml\")\n        if not os.path.exists(yaml_path):\n            print(f\"Zone {key} is in the JSON file but not in the zones directory\")\n            continue\n        with open(yaml_path, encoding=\"utf-8\") as f_yaml:\n            try:\n                yaml_data = yaml.safe_load(f_yaml)\n            except Exception:\n                print(f\"Error parsing yaml file : {yaml_path}\")\n                continue\n        yaml_data[\"country_name\"] = country_name\n        yaml_data[\"zone_name\"] = zone_name\n        if zone_short_name:\n            yaml_data[\"zone_short_name\"] = zone_short_name\n        with open(yaml_path, \"w\", encoding=\"utf-8\") as f_yaml:\n            yaml.dump(yaml_data, f_yaml, allow_unicode=True, sort_keys=False)\n\n\ndef check_additional_attributes():\n    zones_dir = os.path.join(os.path.dirname(__file__), \"../config/zones\")\n    zones_without_country_name = []\n    zones_without_zone_name = []\n    zones_with_zone_short_name = []\n    for filename in os.listdir(zones_dir):\n        if not filename.endswith(\".yaml\"):\n            continue\n        yaml_path = os.path.join(zones_dir, filename)\n        with open(yaml_path, encoding=\"utf-8\") as f:\n            yaml_data = yaml.safe_load(f)\n        if \"country_name\" not in yaml_data:\n            zones_without_country_name.append(filename)\n        if \"zone_name\" not in yaml_data:\n            zones_without_zone_name.append(filename)\n        if \"zone_short_name\" in yaml_data:\n            zones_with_zone_short_name.append(filename)\n    print(f\"Zones without country_name: {zones_without_country_name}\")\n    print(f\"Zones without zone_name: {zones_without_zone_name}\")\n    print(f\"Zones with zone_short_name: {zones_with_zone_short_name}\")\n\n\nif __name__ == \"__main__\":\n    add_country_names()\n    check_additional_attributes()\n"
  },
  {
    "path": "test_parser.py",
    "content": "#!/usr/bin/env python3\n\"\"\"\nUsage: uv run test_parser FR production\n\"\"\"\n\nimport logging\nimport pprint\nimport time\nfrom collections.abc import Callable\nfrom datetime import datetime, timezone\nfrom typing import Any\n\nimport click\n\nfrom electricitymap.contrib.parsers.lib.parsers import PARSER_DATA_TYPE_TO_DICT\nfrom electricitymap.contrib.parsers.lib.quality import (\n    ValidationError,\n    validate_consumption,\n    validate_exchange,\n)\nfrom electricitymap.contrib.types import ParserDataType, ZoneKey\n\nlogger = logging.getLogger(__name__)\n\n\n@click.command()\n@click.argument(\"zone\")\n@click.argument(\"data-type\", default=\"\")\n@click.option(\"--target_datetime\", default=None, show_default=True)\ndef test_parser(zone: ZoneKey, data_type: str, target_datetime: str | None):\n    \"\"\"\n    Parameters\n    ----------\n    zone: a two letter zone from the map\n    data_type: in the ParserDataType enum\n    target_datetime: ISO 8601 string, such as 2018-05-30 15:00\n    \\n\n    Examples\n    -------\n    >>> uv run test_parser FR\n    >>> uv run test_parser FR production\n    >>> uv run test_parser \"NO-NO3->SE\" exchange\n    >>> uv run test_parser GE production --target_datetime=\"2022-04-10 15:00\"\n\n    \"\"\"\n    if not data_type:\n        parser_data_type = (\n            ParserDataType.EXCHANGE if \"->\" in zone else ParserDataType.PRODUCTION\n        )\n    else:\n        parser_data_type = ParserDataType(data_type)\n\n    if parser_data_type == ParserDataType.PRODUCTION_CAPACITY:\n        raise ValueError(\n            \"productionCapacity is not supported by this script. Please use `uv run update_capacity` instead.\"\n        )\n    parsed_target_datetime = None\n    if target_datetime is not None:\n        parsed_target_datetime = datetime.fromisoformat(target_datetime)\n    start = time.time()\n\n    parser: Callable[..., list[dict[str, Any]] | dict[str, Any]] = (\n        PARSER_DATA_TYPE_TO_DICT[ParserDataType(parser_data_type)][zone]\n    )\n\n    args = (\n        zone.split(\"->\")\n        if parser_data_type\n        in [\n            ParserDataType.EXCHANGE,\n            ParserDataType.EXCHANGE_CAPACITY_FORECAST_DAY_AHEAD,\n            ParserDataType.EXCHANGE_CAPACITY_FORECAST_WEEK_AHEAD,\n            ParserDataType.EXCHANGE_CAPACITY_FORECAST_MONTH_AHEAD,\n            ParserDataType.EXCHANGE_FORECAST,\n        ]\n        else [zone]\n    )\n\n    res = parser(*args, target_datetime=parsed_target_datetime, logger=logger)\n\n    if not res:\n        raise ValueError(f\"Error: parser returned nothing ({res})\")\n\n    elapsed_time = time.time() - start\n    res_list = list(res) if isinstance(res, list | tuple) else [res]\n\n    try:\n        dts = [e[\"datetime\"] for e in res_list]\n    except KeyError as error:\n        raise ValueError(\n            f\"Parser output lacks `datetime` key for at least some of the output. Full output: \\n\\n{res}\\n\"\n        ) from error\n\n    assert all(type(e[\"datetime\"]) is datetime for e in res_list), (\n        \"Datetimes must be returned as native datetime.datetime objects\"\n    )\n\n    assert (\n        any(\n            e[\"datetime\"].tzinfo is None\n            or e[\"datetime\"].tzinfo.utcoffset(e[\"datetime\"]) is None\n            for e in res_list\n        )\n        is False\n    ), \"Datetimes must be timezone aware\"\n\n    last_dt = datetime.fromisoformat(f\"{max(dts)}\").astimezone(timezone.utc)\n    first_dt = datetime.fromisoformat(f\"{min(dts)}\").astimezone(timezone.utc)\n    max_dt_warning = \"\"\n    if not target_datetime:\n        now_string = datetime.now(timezone.utc).isoformat(timespec=\"seconds\")\n        max_dt_warning = (\n            f\" :( >2h from now !!! (now={now_string} UTC)\"\n            if (datetime.now(timezone.utc) - last_dt).total_seconds() > 2 * 3600\n            else f\" -- OK, <2h from now :) (now={now_string} UTC)\"\n        )\n\n    print(\"Parser result:\")\n    pp = pprint.PrettyPrinter(width=120)\n    pp.pprint(res)\n    print(\n        \"\\n\".join(\n            [\n                \"---------------------\",\n                f\"took {elapsed_time:.2f}s\",\n                f\"min returned datetime: {first_dt} UTC\",\n                f\"max returned datetime: {last_dt} UTC {max_dt_warning}\",\n            ]\n        )\n    )\n\n    if isinstance(res, dict):\n        res = [res]\n    for event in res:\n        try:\n            if parser_data_type == ParserDataType.CONSUMPTION:\n                validate_consumption(event, zone)\n            elif parser_data_type == ParserDataType.EXCHANGE:\n                validate_exchange(event, zone)\n        except ValidationError as e:\n            logger.warning(f\"Validation failed @ {event['datetime']}: {e}\")\n\n\nif __name__ == \"__main__\":\n    logging.basicConfig(\n        level=logging.DEBUG,\n        format=\"%(asctime)s %(levelname)-8s %(name)-30s %(message)s\",\n    )\n    # pylint: disable=no-value-for-parameter\n    print(test_parser())\n"
  },
  {
    "path": "tests/__init__.py",
    "content": ""
  },
  {
    "path": "tests/config/__init__.py",
    "content": ""
  },
  {
    "path": "tests/config/__snapshots__/test_config.ambr",
    "content": "# serializer version: 1\n# name: test_data_centers_config\n  DataCenter(provider='gcp', lonlat=(-80.088472, 33.105486), displayName='Berkeley County', region='us-east1', zoneKey='US-CAR-SCEG', operationalSince=None, operationalUntil=None, status='operational', source='https://cloud.google.com/compute/docs/regions-zones')\n# ---\n"
  },
  {
    "path": "tests/config/test_config.py",
    "content": "\"\"\"Tests for the configs provided by the electricitymap.contrib.config\npackage.\n\nThe values in these configs should be loaded from the config files in the\nconfig/ directory. The tests in this file ensure that the values are loaded.\nIt doesn't check all or most values, but serves as a sanity check that the\nconfigs are loaded correctly.\n\"\"\"\n\nimport unittest\nfrom pathlib import Path\n\nfrom electricitymap.contrib import config\nfrom electricitymap.contrib.types import ZoneKey\n\nCONFIG_DIR = Path(__file__).parent.parent.joinpath(\"config\").resolve()\n\n\nclass ConfigTestcase(unittest.TestCase):\n    def test_zones_config(self):\n        # ZONES_CONFIG is a dict mapping zones to their config,\n        # which includes lots of keys with information about the zone.\n        self.assertIn(\"DK-DK1\", config.ZONES_CONFIG.keys())\n        self.assertIn(\"bounding_box\", config.ZONES_CONFIG[ZoneKey(\"DK-DK1\")].keys())\n        self.assertIn(\"capacity\", config.ZONES_CONFIG[ZoneKey(\"DK-DK1\")].keys())\n\n    def test_zone_parent(self):\n        # ZONE_PARENT is a dict mapping zones to their parent zones.\n        self.assertIn(\"DK-DK1\", config.ZONE_PARENT.keys())\n        self.assertEqual(config.ZONE_PARENT[ZoneKey(\"DK-DK1\")], \"DK\")\n\n    def test_zone_bounding_box(self):\n        # ZONE_BOUNDING_BOX is a dict mapping zones to their bounding box,\n        # which is a list like [[12.343, 1.343], [34.4333, 23.3434]].\n        self.assertIn(\"DK-DK1\", config.ZONE_BOUNDING_BOXES.keys())\n        self.assertEqual(len(config.ZONE_BOUNDING_BOXES[ZoneKey(\"DK-DK1\")]), 2)\n\n    def test_zone_neighbours(self):\n        # ZONE_NEIGHBOURS is a dict mapping zones to their neighbours.\n        self.assertIn(\"DK-DK1\", config.ZONE_NEIGHBOURS.keys())\n        dk_neighbours = config.ZONE_NEIGHBOURS[ZoneKey(\"DK-DK1\")]\n        self.assertGreater(\n            len(dk_neighbours), 1, \"expected a few neighbours for DK-DK1\"\n        )\n\n    def test_emission_factors(self):\n        # The emission_factors returns a dict of emission factors for a zone.\n        # The keys are the fuel types and the values are the emission factors.\n        factors = config.emission_factors(ZoneKey(\"DK-DK1\"))\n        self.assertIn(\"biomass\", factors.keys())\n        self.assertIn(\"gas\", factors.keys())\n        self.assertIn(\"wind\", factors.keys())\n        self.assertGreater(factors[\"gas\"], 0)\n\n\ndef test_data_centers_config(snapshot):\n    assert snapshot == config.DATA_CENTERS_CONFIG.data_centers[1]\n\n\nif __name__ == \"__main__\":\n    unittest.main(buffer=True)\n"
  },
  {
    "path": "tests/config/test_config_model.py",
    "content": "import unittest\n\nfrom electricitymap.contrib.config.model import (\n    CO2EQ_CONFIG_MODEL,\n    CONFIG_MODEL,\n    ExchangeParsers,\n    Parsers,\n)\nfrom electricitymap.contrib.types import (\n    EXCHANGE_DATA_TYPES,\n    ParserDataType,\n)\n\n\nclass ConfigModelTestcase(unittest.TestCase):\n    def test_pydantic_model(self):\n        self.assertIn(\"DK-DK2->SE-SE4\", CONFIG_MODEL.exchanges.keys())\n        self.assertIn(\"US-NW-PSCO\", CONFIG_MODEL.zones.keys())\n        self.assertIsNotNone(\n            CONFIG_MODEL.zones[\"US-NW-PSCO\"].parsers.get_function(\"production\")\n        )\n\n    # Add well-known sources that don't require config-based references here\n    GLOBAL_SOURCE_REFERENCES = {\n        \"BEIS 2021\",\n        \"CEA 2022\",\n        \"EIA 2020/BEIS 2021\",\n        \"EU-ETS 2021\",\n        \"EU-ETS, ENTSO-E 2021\",\n        \"IEA 2019\",\n        \"IEA 2020\",\n        'Oberschelp, Christopher, et al. \"Global emission hotspots of coal power generation.\"',\n    }\n\n    def test_zone_sources(self):\n        for measurement_basis, model in CO2EQ_CONFIG_MODEL:\n            for zone_key, zone_modes in model.emission_factors.zone_overrides.items():\n                zone_sources = CONFIG_MODEL.zones[zone_key].sources\n                for mode, estimate in zone_modes or ():\n                    if estimate is None:\n                        continue\n                    estimates = estimate if isinstance(estimate, list) else [estimate]\n                    for estimate in estimates:\n                        self.assertIsNotNone(\n                            estimate.source,\n                            msg=f\"{zone_key}: missing required field: emissionFactors.{measurement_basis}.{mode}.source\",\n                        )\n                        for source in estimate.source.split(\";\"):\n                            source = source.strip()\n                            if source.startswith(\"assumes\"):\n                                continue\n                            if source.startswith(\"Electricity Maps\"):\n                                continue\n                            if source in self.GLOBAL_SOURCE_REFERENCES:\n                                continue\n                            self.assertIsNotNone(\n                                zone_sources,\n                                msg=f\"{zone_key}: missing required field: sources\",\n                            )\n                            assert zone_sources is not None  # pyright type-narrowing\n                            self.assertIn(source, zone_sources, f\"zone: {zone_key}\")\n\n    def test_parser_model_contains_all_parser_data_types(self):\n        dummy_parser_model = Parsers()\n        # Check 1:1 match between ParserDataType enum and Parsers model, except for exchange parsers, as they're defined in a different model\n        all_parser_data_types = {\n            dt.value for dt in ParserDataType if dt not in EXCHANGE_DATA_TYPES\n        }\n        all_parser_model_fields = set(dummy_parser_model.__fields__.keys())\n        self.assertEqual(all_parser_data_types, all_parser_model_fields)\n\n    def test_exchange_parsers_model_contains_all_parser_data_types(self):\n        dummy_exchange_parsers_model = ExchangeParsers()\n        # Check 1:1 match between ParserDataType enum and ExchangeParsers model\n        all_parser_data_types = {dt.value for dt in EXCHANGE_DATA_TYPES}\n        all_parser_model_fields = set(dummy_exchange_parsers_model.__fields__.keys())\n        self.assertEqual(all_parser_data_types, all_parser_model_fields)\n\n\nif __name__ == \"__main__\":\n    unittest.main(buffer=True)\n"
  },
  {
    "path": "tests/config/test_config_zones.py",
    "content": "import unittest\nfrom pathlib import Path\nfrom typing import Any\n\nfrom electricitymap.contrib.config import (\n    generate_all_neighbours,\n    generate_zone_neighbours,\n    zone_bounding_boxes,\n    zone_parents,\n)\nfrom electricitymap.contrib.types import ZoneKey\n\nCONFIG_DIR = Path(__file__).parent.parent.joinpath(\"config\").resolve()\n\n\nclass TestConfigZones(unittest.TestCase):\n    def test_bounding_boxes_basic(self):\n        zones: dict[ZoneKey, Any] = {\n            ZoneKey(\"AD\"): {\n                \"bounding_box\": [[0.906, 41.928], [2.265, 43.149]],\n            },\n            ZoneKey(\"XX\"): {},\n        }\n        self.assertDictEqual(\n            zone_bounding_boxes(zones),\n            {\n                ZoneKey(\"AD\"): [[0.906, 41.928], [2.265, 43.149]],\n            },\n        )\n\n    def test_zone_parents_basic(self):\n        zones: dict[ZoneKey, Any] = {\n            ZoneKey(\"DE\"): {},\n            ZoneKey(\"SE\"): {\n                \"subZoneNames\": [\"SE-SE1\", \"SE-SE2\"],\n            },\n            ZoneKey(\"SE-SE1\"): {},\n            ZoneKey(\"SE-SE2\"): {},\n        }\n        self.assertDictEqual(zone_parents(zones), {\"SE-SE1\": \"SE\", \"SE-SE2\": \"SE\"})\n\n    def test_generate_all_neighbours_basic(self):\n        # generate_all_neighbours returns all neighbours regardless of\n        # granularity, i.e. it doesn't matter whether zones have subzones.\n        exchanges = {\n            \"DE->SE\": {\"parsers\": {\"exchange\": \"source\"}},\n            \"SE->DE\": {\"parsers\": {\"exchange\": \"source\"}},\n        }\n        self.assertDictEqual(\n            generate_all_neighbours(exchanges), {\"DE\": [\"SE\"], \"SE\": [\"DE\"]}\n        )\n\n    def test_generate_zone_neighbours_two_countries(self):\n        exchanges = {\n            \"DE->FR\": {\"parsers\": {\"exchange\": \"source\"}},\n        }\n        zones = {\n            ZoneKey(\"DE\"): {},\n            ZoneKey(\"FR\"): {},\n        }\n        zone_neighbours = generate_zone_neighbours(zones, exchanges)\n        self.assertDictEqual(\n            zone_neighbours, {ZoneKey(\"DE\"): [\"FR\"], ZoneKey(\"FR\"): [\"DE\"]}\n        )\n\n    def test_generate_zone_neighbours_one_country_one_subzone(self):\n        exchanges = {\n            \"DE->SE-SE4\": {\"parsers\": {\"exchange\": \"source\"}},\n        }\n        zones: dict[ZoneKey, Any] = {\n            ZoneKey(\"DE\"): {},\n            ZoneKey(\"SE\"): {\n                \"subZoneNames\": [\"SE-SE4\"],\n            },\n            ZoneKey(\"SE-SE4\"): {},\n        }\n        zone_neighbours = generate_zone_neighbours(zones, exchanges)\n        self.assertDictEqual(zone_neighbours, {\"DE\": [\"SE-SE4\"], \"SE-SE4\": [\"DE\"]})\n\n    def test_generate_zone_neighbours_two_subzones(self):\n        exchanges = {\n            \"NO-NO1->SE-SE3\": {\"parsers\": {\"exchange\": \"source\"}},\n            \"NO-NO3->SE-SE2\": {\"parsers\": {\"exchange\": \"source\"}},\n            \"NO-NO4->SE-SE1\": {\"parsers\": {\"exchange\": \"source\"}},\n            \"NO-NO4->SE-SE2\": {\"parsers\": {\"exchange\": \"source\"}},\n        }\n        zones = {\n            ZoneKey(\"NO\"): {\n                \"subZoneNames\": [\"NO-NO1\", \"NO-NO2\", \"NO-NO3\", \"NO-NO4\", \"NO-NO5\"],\n            },\n            ZoneKey(\"NO-NO1\"): {},\n            ZoneKey(\"NO-NO2\"): {},\n            ZoneKey(\"NO-NO3\"): {},\n            ZoneKey(\"NO-NO4\"): {},\n            ZoneKey(\"NO-NO5\"): {},\n            ZoneKey(\"SE\"): {\n                \"subZoneNames\": [\"SE-SE1\", \"SE-SE2\", \"SE-SE3\", \"SE-SE4\"],\n            },\n            ZoneKey(\"SE-SE1\"): {},\n            ZoneKey(\"SE-SE2\"): {},\n            ZoneKey(\"SE-SE3\"): {},\n            ZoneKey(\"SE-SE4\"): {},\n        }\n        zone_neighbours = generate_zone_neighbours(zones, exchanges)\n        self.assertDictEqual(\n            zone_neighbours,\n            {\n                \"NO-NO1\": [\"SE-SE3\"],\n                \"NO-NO3\": [\"SE-SE2\"],\n                \"NO-NO4\": [\"SE-SE1\", \"SE-SE2\"],\n                \"SE-SE1\": [\"NO-NO4\"],\n                \"SE-SE2\": [\"NO-NO3\", \"NO-NO4\"],\n                \"SE-SE3\": [\"NO-NO1\"],\n            },\n        )\n\n    def test_generate_zone_neighbours_two_subzones_from_same(self):\n        exchanges = {\n            \"SE-SE1->SE-SE2\": {\"parsers\": {\"exchange\": \"source\"}},\n        }\n        zones = {\n            ZoneKey(\"SE\"): {\n                \"subZoneNames\": [\"SE-SE1\", \"SE-SE2\", \"SE-SE3\", \"SE-SE4\"],\n            },\n            ZoneKey(\"SE-SE1\"): {},\n            ZoneKey(\"SE-SE2\"): {},\n            ZoneKey(\"SE-SE3\"): {},\n            ZoneKey(\"SE-SE4\"): {},\n        }\n        zone_neighbours = generate_zone_neighbours(zones, exchanges)\n        self.assertDictEqual(\n            zone_neighbours,\n            {\"SE-SE1\": [\"SE-SE2\"], \"SE-SE2\": [\"SE-SE1\"]},\n        )\n\n    def test_generate_zone_neighbours_GB(self):\n        # That's an interesting case as GB has islands, which are not subzones\n        # It means that GB->GB-NIR are valid exchanges and that\n        # GB and GB-NIR are neighbours\n        exchanges = {\n            \"GB->GB-NIR\": {\"parsers\": {\"exchange\": \"source\"}},\n        }\n        zones: dict[ZoneKey, Any] = {\n            ZoneKey(\"GB\"): {},\n            ZoneKey(\"GB-NIR\"): {},\n        }\n        zone_neighbours = generate_zone_neighbours(zones, exchanges)\n        self.assertDictEqual(\n            zone_neighbours,\n            {\"GB\": [\"GB-NIR\"], \"GB-NIR\": [\"GB\"]},\n        )\n\n    def test_generate_zone_neighbours_no_exchange_parser(self):\n        exchanges = {\n            \"DE->FR\": {\"parsers\": {}},\n        }\n        zones: dict[ZoneKey, Any] = {\n            ZoneKey(\"DE\"): {},\n            ZoneKey(\"FR\"): {},\n        }\n        zone_neighbours = generate_zone_neighbours(zones, exchanges)\n        self.assertDictEqual(zone_neighbours, {})\n"
  },
  {
    "path": "tests/config/test_data_center_model.py",
    "content": "from datetime import date\nfrom unittest.mock import patch\n\nimport pytest\nfrom pydantic.v1 import ValidationError\n\nfrom electricitymap.contrib.config.data_center_model import DataCenter, DataCenters\nfrom electricitymap.contrib.types import ZoneKey\n\nVALID_ZONE_KEY = ZoneKey(\"DE\")\n\nFR_ZONE_KEY = ZoneKey(\"FR\")\nINVALID_ZONE_KEY = ZoneKey(\"INVALID\")\n\nMOCK_ZONES_CONFIG = {VALID_ZONE_KEY: {}, FR_ZONE_KEY: {}}\n\n\ndef make_data_center(\n    provider: str = \"AWS\",\n    lonlat: tuple[float, float] = (10.0, 50.0),\n    displayName: str = \"EU West\",\n    region: str = \"eu-west-1\",\n    zoneKey: ZoneKey = VALID_ZONE_KEY,\n    operationalSince: date | None = None,\n    operationalUntil: date | None = None,\n    status: str | None = None,\n    source: str | None = None,\n) -> DataCenter:\n    return DataCenter(\n        provider=provider,\n        lonlat=lonlat,\n        displayName=displayName,\n        region=region,\n        zoneKey=zoneKey,\n        operationalSince=operationalSince,\n        operationalUntil=operationalUntil,\n        status=status,\n        source=source,\n    )\n\n\n@pytest.fixture(autouse=True)\ndef _mock_zones_config():\n    with (\n        patch(\n            \"electricitymap.contrib.config.data_center_model.ZONES_CONFIG\",\n            MOCK_ZONES_CONFIG,\n            create=True,\n        ),\n        patch(\n            \"electricitymap.contrib.config.ZONES_CONFIG\",\n            MOCK_ZONES_CONFIG,\n        ),\n    ):\n        yield\n\n\nclass TestDataCenterID:\n    def test_id_format(self):\n        dc = make_data_center()\n        assert dc.ID == \"AWS-eu-west-1\"\n\n\nclass TestStringNotEmpty:\n    @pytest.mark.parametrize(\n        \"kwargs\",\n        [\n            {\"provider\": \"\"},\n            {\"region\": \"\"},\n            {\"displayName\": \"\"},\n            {\"provider\": \"   \"},\n            {\"region\": \"   \"},\n            {\"displayName\": \"   \"},\n        ],\n    )\n    def test_empty_or_whitespace_rejected(self, kwargs: dict[str, str]):\n        with pytest.raises(ValidationError, match=\"Value must be a non-empty string\"):\n            make_data_center(**kwargs)  # type: ignore[arg-type]\n\n    def test_valid_strings_accepted(self):\n        make_data_center(provider=\"valid\", region=\"valid\", displayName=\"valid\")\n\n\nclass TestLonlatValid:\n    def test_valid_lonlat(self):\n        make_data_center(lonlat=(0.0, 0.0))\n\n    def test_boundary_values(self):\n        make_data_center(lonlat=(-180.0, -90.0))\n        make_data_center(lonlat=(180.0, 90.0))\n\n    def test_longitude_too_low(self):\n        with pytest.raises(ValidationError, match=\"Longitude must be between\"):\n            make_data_center(lonlat=(-181.0, 0.0))\n\n    def test_longitude_too_high(self):\n        with pytest.raises(ValidationError, match=\"Longitude must be between\"):\n            make_data_center(lonlat=(181.0, 0.0))\n\n    def test_latitude_too_low(self):\n        with pytest.raises(ValidationError, match=\"Latitude must be between\"):\n            make_data_center(lonlat=(0.0, -91.0))\n\n    def test_latitude_too_high(self):\n        with pytest.raises(ValidationError, match=\"Latitude must be between\"):\n            make_data_center(lonlat=(0.0, 91.0))\n\n\nclass TestDateValid:\n    @pytest.mark.parametrize(\"field\", [\"operationalSince\", \"operationalUntil\"])\n    def test_none_accepted(self, field: str):\n        dc = make_data_center(**{field: None})  # type: ignore[arg-type]\n        assert getattr(dc, field) is None\n\n    @pytest.mark.parametrize(\"field\", [\"operationalSince\", \"operationalUntil\"])\n    @pytest.mark.parametrize(\n        (\"value\", \"expected\"),\n        [\n            (\"2021\", date(2021, 1, 1)),\n            (\"2021-06\", date(2021, 6, 1)),\n            (\"2021-06-15\", date(2021, 6, 15)),\n        ],\n    )\n    def test_valid_formats_parsed_to_date(self, field: str, value: str, expected: date):\n        dc = make_data_center(**{field: value})  # type: ignore[arg-type]\n        assert getattr(dc, field) == expected\n\n    @pytest.mark.parametrize(\"field\", [\"operationalSince\", \"operationalUntil\"])\n    def test_date_object_accepted(self, field: str):\n        dc = make_data_center(**{field: date(2021, 6, 15)})  # type: ignore[arg-type]\n        assert getattr(dc, field) == date(2021, 6, 15)\n\n    @pytest.mark.parametrize(\"field\", [\"operationalSince\", \"operationalUntil\"])\n    @pytest.mark.parametrize(\n        \"value\",\n        [\"not-a-date\", \"21\", \"2021/06/15\", \"2021-6\", \"2021-06-1\", \"06-2021\"],\n    )\n    def test_invalid_format_rejected(self, field: str, value: str):\n        with pytest.raises(\n            ValidationError, match=\"must be in YYYY, YYYY-MM, or YYYY-MM-DD format\"\n        ):\n            make_data_center(**{field: value})  # type: ignore[arg-type]\n\n    @pytest.mark.parametrize(\"field\", [\"operationalSince\", \"operationalUntil\"])\n    @pytest.mark.parametrize(\"value\", [\"2021-13\", \"2021-00\", \"2021-02-30\"])\n    def test_invalid_calendar_date_rejected(self, field: str, value: str):\n        with pytest.raises(ValidationError, match=\"is not a valid calendar date\"):\n            make_data_center(**{field: value})  # type: ignore[arg-type]\n\n\nclass TestZoneKeyExists:\n    def test_valid_zone_key(self):\n        make_data_center(zoneKey=VALID_ZONE_KEY)\n\n    def test_invalid_zone_key(self):\n        with pytest.raises(\n            ValidationError, match=\"is not one of the allowed zone keys\"\n        ):\n            make_data_center(zoneKey=INVALID_ZONE_KEY)\n\n\nclass TestDataCentersIdsAreUnique:\n    def test_unique_ids_accepted(self):\n        DataCenters(\n            data_centers=[\n                make_data_center(provider=\"AWS\", region=\"eu-west-1\"),\n                make_data_center(provider=\"GCP\", region=\"us-east-1\"),\n            ]\n        )\n\n    def test_duplicate_ids_rejected(self):\n        with pytest.raises(ValidationError, match=\"Duplicate data center ID found\"):\n            DataCenters(\n                data_centers=[\n                    make_data_center(provider=\"AWS\", region=\"eu-west-1\"),\n                    make_data_center(\n                        provider=\"AWS\", region=\"eu-west-1\", zoneKey=FR_ZONE_KEY\n                    ),\n                ]\n            )\n\n\nclass TestDataCentersUniqueProviderRegionZoneKey:\n    def test_unique_combinations_accepted(self):\n        DataCenters(\n            data_centers=[\n                make_data_center(\n                    provider=\"AWS\", region=\"eu-west-1\", zoneKey=VALID_ZONE_KEY\n                ),\n                make_data_center(\n                    provider=\"GCP\", region=\"us-east-1\", zoneKey=FR_ZONE_KEY\n                ),\n            ]\n        )\n\n    def test_duplicate_combination_rejected(self):\n        \"\"\"Duplicate (provider, region, zoneKey) implies duplicate ID (provider-region),\n        so the ids_are_unique validator fires first. We verify the entry is rejected.\"\"\"\n        with pytest.raises(ValidationError):\n            DataCenters(\n                data_centers=[\n                    make_data_center(),\n                    make_data_center(),\n                ]\n            )\n\n\nclass TestDataCentersExtraFieldsForbidden:\n    def test_extra_fields_rejected(self):\n        with pytest.raises(ValidationError, match=\"extra fields not permitted\"):\n            DataCenters(\n                data_centers=[make_data_center()],\n                unknown_field=\"bad\",  # type: ignore[call-arg]\n            )\n"
  },
  {
    "path": "tests/config/test_emission_factors.py",
    "content": "from datetime import datetime, timezone\n\nimport pandas as pd\n\nfrom electricitymap.contrib.config import CO2EQ_PARAMETERS_DIRECT\nfrom electricitymap.contrib.config.emission_factors_lookup import (\n    get_emission_factors_with_metadata_all_years,\n    get_zone_specific_co2eq_parameter,\n)\n\n\ndef test_all_emission_factor_error(snapshot):\n    _, errors = get_emission_factors_with_metadata_all_years()\n    if errors:\n        df = pd.DataFrame(errors).sort_values(\n            by=[\n                \"mode\",\n                \"zone_key\",\n                \"dt\",\n            ]\n        )\n        serialized = df.to_csv(index=False)\n    else:\n        serialized = []\n    assert snapshot == serialized\n    assert not len(errors)\n\n\ndef test_all_emission_factors(snapshot):\n    efs, _ = get_emission_factors_with_metadata_all_years()\n    efs = sorted(ef.json(by_alias=True) for ef in efs)\n    assert snapshot == efs\n\n\ndef test_get_zone_specific_co2eq_parameter_identical_return():\n    zone_key = \"AT\"\n    year = 2024\n    dt = datetime(year=year, month=1, day=1, tzinfo=timezone.utc)\n    mode = \"coal\"\n\n    res1 = get_zone_specific_co2eq_parameter(\n        co2eq_parameters=CO2EQ_PARAMETERS_DIRECT,\n        zone_key=zone_key,\n        key=\"emissionFactors\",\n        sub_key=mode,\n        dt=dt,\n    )\n\n    res2 = get_zone_specific_co2eq_parameter(\n        co2eq_parameters=CO2EQ_PARAMETERS_DIRECT,\n        zone_key=zone_key,\n        key=\"emissionFactors\",\n        sub_key=mode,\n        dt=dt,\n        metadata=True,\n    )\n\n    assert res1[\"value\"] == res2[\"value\"]\n"
  },
  {
    "path": "tests/test_capacity.py",
    "content": "from datetime import datetime\n\nimport pytest\n\nfrom electricitymap.contrib.config.capacity import (\n    CapacityData,\n    get_capacity_data,\n    get_capacity_data_with_source,\n)\n\n\ndef test_get_capacity_data():\n    capacity_data = {}\n    capacity_data_1 = {\"solar\": 3, \"wind\": 4, \"coal\": None}\n    capacity_data_2 = {\n        \"coal\": {\"datetime\": \"2022-01-01\", \"value\": 5, \"source\": \"abc\"},\n        \"gas\": {\"datetime\": \"2022-01-01\", \"value\": 6, \"source\": \"abc\"},\n        \"solar\": {\"datetime\": \"2022-01-01\", \"value\": None, \"source\": \"abc\"},\n    }\n    capacity_data_3 = {\n        \"coal\": [\n            {\"datetime\": \"2022-01-01\", \"value\": 5, \"source\": \"abc\"},\n            {\"datetime\": \"2023-06-01\", \"value\": 8, \"source\": \"abc\"},\n        ],\n        \"gas\": [\n            {\"datetime\": \"2022-01-01\", \"value\": 6, \"source\": \"abc\"},\n            {\"datetime\": \"2023-06-01\", \"value\": 7, \"source\": \"abc\"},\n        ],\n    }\n    assert get_capacity_data(capacity_data, datetime(2023, 1, 1)) == {}\n    assert get_capacity_data(capacity_data_1, datetime(2023, 1, 1)) == {\n        \"solar\": 3,\n        \"wind\": 4,\n        \"coal\": None,\n    }\n    assert get_capacity_data(capacity_data_2, datetime(2022, 6, 1)) == {\n        \"coal\": 5,\n        \"gas\": 6,\n        \"solar\": None,\n    }\n    assert get_capacity_data(capacity_data_3, datetime(2023, 6, 1)) == {\n        \"coal\": 8,\n        \"gas\": 7,\n    }\n\n    with pytest.raises(ValueError):\n        get_capacity_data(capacity_data_2, datetime(2023, 0, 1))\n\n\ndef test_get_capacity_from_list():\n    mode_capacity = [\n        {\"datetime\": \"2022-01-01\", \"value\": 3, \"source\": \"abc\"},\n        {\"datetime\": \"2023-01-01\", \"value\": 4, \"source\": \"abc\"},\n    ]\n\n    capacity_dt = datetime(2022, 1, 1)\n    for item in mode_capacity:\n        if datetime.fromisoformat(item[\"datetime\"]).date() == capacity_dt.date():\n            capacity = item[\"value\"]\n\n    assert capacity == 3\n\n\ndef test_get_capacity_with_source():\n    capacity_config = {\n        \"solar\": {\"datetime\": \"2023-10-01\", \"value\": 3, \"source\": \"abc\"},\n        \"wind\": [\n            {\"datetime\": \"2023-10-01\", \"value\": 4, \"source\": \"abc\"},\n            {\"datetime\": \"2023-11-01\", \"value\": 5, \"source\": \"abc\"},\n        ],\n    }\n\n    capacity_data = get_capacity_data_with_source(\n        capacity_config, datetime(2023, 10, 1)\n    )\n\n    assert capacity_data == {\n        \"solar\": CapacityData(3, \"abc\"),\n        \"wind\": CapacityData(4, \"abc\"),\n    }\n\n    assert get_capacity_data_with_source(capacity_config, datetime(2023, 11, 1)) == {\n        \"solar\": CapacityData(3, \"abc\"),\n        \"wind\": CapacityData(5, \"abc\"),\n    }\n"
  },
  {
    "path": "tests/test_co2eq_parameters.py",
    "content": "\"\"\"Validate the CO2eq parameters.\"\"\"\n\nimport datetime\nimport json\nimport numbers\nimport unittest\nfrom typing import Any\n\nfrom electricitymap.contrib.config import (\n    CO2EQ_PARAMETERS,\n    CO2EQ_PARAMETERS_DIRECT,\n    CO2EQ_PARAMETERS_LIFECYCLE,\n)\nfrom electricitymap.contrib.config.constants import MODE_COLORS\n\n\ndef get_possible_modes() -> set[str]:\n    \"\"\"Get the set of possible modes from the MODE_COLORS dictionary.\"\"\"\n    return set[str](MODE_COLORS.keys())\n\n\ndef parse_json_file(path: str):\n    \"\"\"Parse a JSON file.\"\"\"\n    with open(path, encoding=\"utf-8\") as file_:\n        return json.load(file_)\n\n\nclass CO2eqParametersAll(unittest.TestCase):\n    \"\"\"A test case for CO2eq parameters.\"\"\"\n\n    modes: set[str] = get_possible_modes()\n    parameters = CO2EQ_PARAMETERS\n\n    @staticmethod\n    def check_valid_ratios_list(ratios):\n        assert len(ratios) >= 1\n\n    @classmethod\n    def check_power_origin_ratios(cls, callback1, callback2):\n        \"\"\"Apply the callback to each ratio in the 'powerOriginRatios' objects.\"\"\"\n        # It is useful to keep `test_power_origin_modes_are_valid` and\n        # `test_power_origin_ratios_sum_to_1` as separate tests, but they share\n        # a lot of identical code. This helper function helps avoid code\n        # duplication by factoring out the common logic and using callback\n        # functions to handle the differences.\n        fallback_zone_mixes = cls.parameters[\"fallbackZoneMixes\"]\n        for zone, mixes in (\n            (\"defaults\", fallback_zone_mixes[\"defaults\"]),\n            *fallback_zone_mixes[\"zoneOverrides\"].items(),\n        ):\n            ratios = mixes[\"powerOriginRatios\"]\n            if isinstance(ratios, list):\n                cls.check_valid_ratios_list(ratios)\n                for ratio in ratios:\n                    callback1(ratio, zone)\n            else:\n                callback2(ratios, zone)\n\n    @classmethod\n    def check_contributions(cls, contribution_name, callback):\n        \"\"\"Apply the callback to each renewable/lowCarbon contribution.\"\"\"\n        contributions = cls.parameters[contribution_name]\n        for zone, modes_to_contributions in (\n            (\"defaults\", contributions[\"defaults\"]),\n            *contributions[\"zoneOverrides\"].items(),\n        ):\n            for mode, c in modes_to_contributions.items():\n                callback(mode, c, zone)\n\n    @classmethod\n    def check_is_renewable(cls, callback):\n        \"\"\"Apply the callback to each renewable contribution.\"\"\"\n        cls.check_contributions(\"isRenewable\", callback)\n\n    @classmethod\n    def check_is_low_carbon(cls, callback):\n        \"\"\"Apply the callback to each lowCarbon contribution.\"\"\"\n        cls.check_contributions(\"isLowCarbon\", callback)\n\n    def test_power_origin_modes_are_valid(self):\n        \"\"\"All modes in the 'powerOriginRatios' objects must be valid.\"\"\"\n\n        def callback(ratio_, zone):\n            for mode, ratio in ratio_[\"value\"].items():\n                if isinstance(ratio, numbers.Number):\n                    self.assertIn(\n                        mode, self.modes, msg=f\"zone '{zone}' contains an invalid mode\"\n                    )\n\n        self.check_power_origin_ratios(callback, callback)\n\n    def test_power_origin_ratio_annual_lists_have_valid_dates(self):\n        \"\"\"Lists of power origin ratios must include valid date strings.\"\"\"\n\n        def callback(ratio, _zone):\n            # An exception will be raised if the string is not a valid\n            # datetime, thus failing the test.\n            datetime.datetime.fromisoformat(ratio[\"datetime\"])\n\n        self.check_power_origin_ratios(callback, lambda ratio, zone: None)\n\n    def test_power_origin_ratios_sum_to_1(self):\n        \"\"\"All ratios in the 'powerOriginRatios' objects must sum to\n        (approximately) 1.0.\n        \"\"\"\n\n        def callback(ratio, zone):\n            values = ratio[\"value\"].values()\n            self.assertAlmostEqual(\n                1.0,\n                sum(v for v in values if isinstance(v, numbers.Number)),\n                msg=f\"zone '{zone}' ratios do not sum to (approximately) 1.0\",\n                places=2,\n            )\n\n        self.check_power_origin_ratios(callback, callback)\n\n    def test_required_keys_are_present(self):\n        \"\"\"All objects must contain the required keys.\"\"\"\n\n        def callback1(ratio, _zone):\n            self.assertIn(\n                \"datetime\",\n                ratio,\n                msg=\"lists of power origin ratios must include datetimes\",\n            )\n            self.assertIn(\"value\", ratio)\n\n        def callback2(ratio, _zone):\n            self.assertIn(\"value\", ratio)\n\n        self.assertIn(\"fallbackZoneMixes\", self.parameters)\n        fallback_zone_mixes = self.parameters[\"fallbackZoneMixes\"]\n        self.assertIn(\"defaults\", fallback_zone_mixes)\n        self.assertIn(\"powerOriginRatios\", fallback_zone_mixes[\"defaults\"])\n        self.assertIn(\"zoneOverrides\", fallback_zone_mixes)\n        for zone, mixes in (\n            (\"defaults\", fallback_zone_mixes[\"defaults\"]),\n            *fallback_zone_mixes[\"zoneOverrides\"].items(),\n        ):\n            self.assertIn(\n                \"powerOriginRatios\", mixes, msg=f\"key missing from zone '{zone}'\"\n            )\n        self.check_power_origin_ratios(callback1, callback2)\n\n    def check_contribution_object(self, contribution, zone, mode, contribution_name):\n        self.assertIn(\n            \"value\",\n            contribution.keys(),\n            msg=f\"zone '{zone}' does not contain a value for {contribution_name} contribution for mode {mode}\",\n        )\n        self.assertTrue(\n            0 <= contribution[\"value\"] <= 1,\n            msg=f\"zone '{zone}' contains an invalid {contribution_name} contribution for mode {mode}\",\n        )\n\n    def check_contribution_datetimes(self, contribution, zone, mode, contribution_name):\n        # Would throw a KeyError if a member misses a datetime\n        dts = []\n        try:\n            dts = [c[\"datetime\"] for c in contribution]\n        except KeyError:\n            self.assertTrue(\n                False,\n                msg=f\"zone '{zone}' is missing datetimes for the {contribution_name} contributions for mode {mode}\",\n            )\n        try:\n            dts = [datetime.datetime.fromisoformat(dt) for dt in dts]\n        except ValueError:\n            self.assertTrue(\n                False,\n                msg=f\"zone '{zone}' contains invalid datetimes for the {contribution_name} contributions for mode {mode}\",\n            )\n        self.assertEqual(\n            dts,\n            sorted(dts),\n            msg=f\"zone '{zone}' datetimes for the {contribution_name} contributions for mode {mode} are not ordered\",\n        )\n\n    def test_is_renewable_valid_datetimes(self):\n        def callback(mode, contribution, zone):\n            if isinstance(contribution, list):\n                self.check_contribution_datetimes(\n                    contribution, zone, mode, \"isRenewable\"\n                )\n\n        self.check_is_renewable(callback)\n\n    def test_is_renewable_valid_contributions(self):\n        contribution_name = \"isRenewable\"\n\n        def callback(mode, contribution, zone):\n            if isinstance(contribution, list):\n                for c in contribution:\n                    self.check_contribution_object(c, zone, mode, contribution_name)\n            else:\n                self.check_contribution_object(\n                    contribution, zone, mode, contribution_name\n                )\n\n        self.check_is_renewable(callback)\n\n    def test_is_low_carbon_valid_datetimes(self):\n        def callback(mode, contribution, zone):\n            if isinstance(contribution, list):\n                self.check_contribution_datetimes(\n                    contribution, zone, mode, \"isLowCarbon\"\n                )\n\n        self.check_is_low_carbon(callback)\n\n    def test_is_low_carbon_valid_contributions(self):\n        contribution_name = \"isLowCarbon\"\n\n        def callback(mode, contribution, zone):\n            if isinstance(contribution, list):\n                for c in contribution:\n                    self.check_contribution_object(c, zone, mode, contribution_name)\n            else:\n                self.check_contribution_object(\n                    contribution, zone, mode, contribution_name\n                )\n\n        self.check_is_low_carbon(callback)\n\n\nclass BaseClasses:\n    # By putting the base classes in a separate class,\n    # we avoid automatically running this test case by itself.\n    class CO2eqParametersDirectAndLifecycleBase(unittest.TestCase):\n        \"\"\"Base case lifecycle CO2eq parameters test cases.\"\"\"\n\n        modes = get_possible_modes()\n\n        # `parameters` and `ranges_by_mode` are expected to be overridden by the test\n        # case; they are defined here to for typing purposes.\n        parameters: dict[str, Any] = {}\n        ranges_by_mode: dict[str, tuple[numbers.Number, numbers.Number]] = {}\n\n        @classmethod\n        def check_emission_factors(cls, callback):\n            \"\"\"Apply the callback to each item in the 'emissionFactors' object.\n\n            The callback is called with the mode and factors for both the defaults\n            and the zone-specific overrides; each `factors` object is either a list\n            of factor dicts or a single factor dict, and each factor dict has the\n            key \"value\", and possibly other keys such as \"source\".\n            \"\"\"\n            emission_factors = cls.parameters[\"emissionFactors\"]\n            for zone, modes_to_factors in (\n                (\"defaults\", emission_factors[\"defaults\"]),\n                *emission_factors[\"zoneOverrides\"].items(),\n            ):\n                for mode, factors in modes_to_factors.items():\n                    callback(mode, factors, zone)\n\n        @classmethod\n        def check_emission_factor_values(cls, callback):\n            \"\"\"Apply the callback to each emission factor value.\n\n            Similar to check_emission_factors, but the second argument to the\n            callback is the value of the factor, not the dict or list of dicts\n            containing it.\n            \"\"\"\n\n            def cb(mode, factors, zone):\n                if isinstance(factors, list):\n                    for factor in factors:\n                        callback(mode, factor, zone)\n                else:\n                    callback(mode, factors, zone)\n\n            cls.check_emission_factors(cb)\n\n        def test_emission_factor_value_ranges(self):\n            \"\"\"Checks all emission factors are in the allowed range.\n\n            Emission factor is measured in grams CO2eq per kWh. It is also known as\n            the carbon intensity.\n\n            This test method checks that values are within reasonable ranges for\n            different modes, to avoid accidental typos in configs. For reference,\n            most renewables are below 50 gCO2eq/kWh, and most fossil fuels are\n            above 500 gCO2eq/kWh.\n            \"\"\"\n\n            def check_range(mode, factor, zone):\n                value = factor[\"value\"]\n                assert isinstance(value, int | float)\n                low, high = self.ranges_by_mode[mode]\n                assert isinstance(low, int | float)\n                assert isinstance(high, int | float)\n                msg = (\n                    f\"emission factor {value} not in expected range \"\n                    f\"[{low}, {high}] for {mode} in {zone}\"\n                )\n                self.assertGreaterEqual(value, low, msg)\n                self.assertLessEqual(value, high, msg)\n\n            def callback(mode, factors, zone):\n                if isinstance(factors, list):\n                    for factor in factors:\n                        check_range(mode, factor, zone)\n                else:\n                    check_range(mode, factors, zone)\n\n            self.check_emission_factors(callback)\n\n        def test_emission_factor_modes_are_valid(self):\n            \"\"\"All specified modes must be in the allowed set of modes.\"\"\"\n\n            def callback(mode, _factors, zone):\n                self.assertIn(\n                    mode, self.modes, msg=f\"zone '{zone}' contains an invalid mode\"\n                )\n\n            self.check_emission_factors(callback)\n\n        def test_emission_factor_annual_lists_have_valid_dates(self):\n            \"\"\"Lists of emission factors must include valid date strings.\"\"\"\n\n            def callback(_mode, factors, _zone):\n                if isinstance(factors, list):\n                    for factor in factors:\n                        # An exception will be raised if the string is not a valid\n                        # datetime, thus failing the test.\n                        datetime.datetime.fromisoformat(factor[\"datetime\"])\n\n            self.check_emission_factors(callback)\n\n        def test_emission_factor_annual_lists_are_not_empty(self):\n            \"\"\"Verifies that the list of annual emission factors are not empty\"\"\"\n\n            def callback(_mode, factors, _zone):\n                if isinstance(factors, list):\n                    self.assertGreater(\n                        len(factors),\n                        0,\n                        msg=f\"emission factors list is empty for zone {_zone}\",\n                    )\n\n            self.check_emission_factors(callback)\n\n        def test_required_keys_are_present(self):\n            \"\"\"All objects must contain the required keys.\"\"\"\n\n            def callback(_mode, factors, _zone):\n                if isinstance(factors, list):\n                    for factor in factors:\n                        self.assertIn(\n                            \"datetime\",\n                            factor,\n                            msg=\"lists of emission factors must include datetimes\",\n                        )\n                        self.assertIn(\"value\", factor)\n                else:\n                    self.assertIn(\"value\", factors)\n\n            self.assertIn(\"emissionFactors\", self.parameters)\n            emission_factors = self.parameters[\"emissionFactors\"]\n            self.assertIn(\"defaults\", emission_factors)\n            self.assertIn(\"zoneOverrides\", emission_factors)\n            self.check_emission_factors(callback)\n\n\nclass CO2eqParametersDirect(BaseClasses.CO2eqParametersDirectAndLifecycleBase):\n    \"\"\"A test case for the direct CO2eq parameters.\"\"\"\n\n    parameters = CO2EQ_PARAMETERS_DIRECT\n\n    # Expected min and max values for emission factors, by mode.\n    ranges_by_mode: dict[str, tuple[int | float, int | float]] = {\n        # Fossil fuels: usually above 500 gCO2eq/kWh.\n        \"coal\": (400, 1600),\n        \"gas\": (200, 700),\n        \"oil\": (175, 1700),\n        # Low-carbon: direct emissions are usually zero, with some possible exceptions.\n        \"geothermal\": (\n            0,\n            199,\n        ),  # 80% of geothermal plants emit less than 200 gCO2eq/kWhs\n        \"hydro\": (0, 0),\n        \"nuclear\": (0, 0),\n        \"solar\": (0, 0),\n        \"wind\": (0, 0),\n        \"biomass\": (0, 0),\n        # Storage; should be zero as emissions are counted at discharge time.\n        \"hydro charge\": (0, 0),\n        \"battery charge\": (0, 0),\n        # Discharge and unknown; these may be based on averages for region/time.\n        \"battery discharge\": (0, 1000),\n        \"hydro discharge\": (0, 1000),\n        \"unknown\": (0, 1000),\n    }\n\n\nclass CO2eqParametersLifecycle(BaseClasses.CO2eqParametersDirectAndLifecycleBase):\n    \"\"\"A test case for the lifecycle CO2eq parameters.\"\"\"\n\n    parameters = CO2EQ_PARAMETERS_LIFECYCLE\n\n    # Expected min and max values for emission factors, by mode.\n    ranges_by_mode: dict[str, tuple[int | float, int | float]] = {\n        # Fossil fuels: generally above 500 gCO2eq/kWh with some exceptions.\n        \"oil\": (400, 1900),\n        \"coal\": (400, 1600),\n        \"gas\": (400, 900),\n        # Low-carbon: generally below 50 gCO2eq/kWh with some exceptions.\n        # For lifecycle emissions, this should not be zero.\n        \"geothermal\": (30, 199),\n        \"hydro\": (10, 25),\n        \"nuclear\": (4, 12),\n        \"biomass\": (0.4, 1300),\n        \"solar\": (25, 45),\n        \"wind\": (10, 13),\n        # Storage: emissions are counted at discharge time, should always be zero.\n        \"battery charge\": (0, 0),\n        \"hydro charge\": (0, 0),\n        # Unknown and discharge; may be based on averages for a region/time.\n        \"battery discharge\": (10, 1200),\n        \"hydro discharge\": (10, 1200),\n        \"unknown\": (10, 1000),\n    }\n\n\nif __name__ == \"__main__\":\n    unittest.main(buffer=True)\n"
  },
  {
    "path": "tests/test_exchanges_json.py",
    "content": "import unittest\n\nfrom electricitymap.contrib.config import EXCHANGES_CONFIG, ZONES_CONFIG\n\n\nclass ExchangeJsonTestcase(unittest.TestCase):\n    def test_all_zones_in_zones_json(self):\n        zone_keys = ZONES_CONFIG.keys()\n        for zone_key in EXCHANGES_CONFIG:\n            self.assertIn(\"->\", zone_key)\n            for zone in zone_key.split(\"->\"):\n                if zone == \"US\":\n                    # Old US zone that we ignore.\n                    continue\n                self.assertIn(zone, zone_keys)\n\n\nif __name__ == \"__main__\":\n    unittest.main(buffer=True)\n"
  },
  {
    "path": "tests/test_parser_interface.py",
    "content": "import glob\nimport inspect\nimport unittest\nfrom collections.abc import Callable\nfrom inspect import isfunction\nfrom pathlib import Path\nfrom typing import Any, NamedTuple\n\nfrom electricitymap.contrib.config.model import CONFIG_MODEL\n\nPARSER_FOLDERS = Path(__file__).parent.resolve() / \"../parsers\"\nPARSER_FILES_GLOB = f\"{PARSER_FOLDERS.resolve()}/*.py\"\n_PARSER_FUNCTION_ARGS = [\"zone_key\", \"session\", \"target_datetime\", \"logger\"]\n_CAPACITY_PARSER_FUNCTION_ARGS = [\"zone_key\", \"target_datetime\", \"session\"]\n_EXCHANGE_FUNCTION_ARGS = [\n    \"zone_key1\",\n    \"zone_key2\",\n    \"session\",\n    \"target_datetime\",\n    \"logger\",\n]\nEXPECTED_MODE_FUNCTION_ARGS = {\n    \"consumption\": _PARSER_FUNCTION_ARGS,\n    \"consumptionForecast\": _PARSER_FUNCTION_ARGS,\n    \"exchange\": _EXCHANGE_FUNCTION_ARGS,\n    \"exchangeCapacityForecastDayAhead\": _EXCHANGE_FUNCTION_ARGS,\n    \"exchangeCapacityForecastWeekAhead\": _EXCHANGE_FUNCTION_ARGS,\n    \"exchangeCapacityForecastMonthAhead\": _EXCHANGE_FUNCTION_ARGS,\n    \"shadowAuctionAtcDayAhead\": _EXCHANGE_FUNCTION_ARGS,\n    \"coreExternalAtcDayAhead\": _EXCHANGE_FUNCTION_ARGS,\n    \"maxBexDayAhead\": _EXCHANGE_FUNCTION_ARGS,\n    \"scheduledExchangesDayAhead\": _EXCHANGE_FUNCTION_ARGS,\n    \"maxBflowDayAhead\": _EXCHANGE_FUNCTION_ARGS,\n    \"exchangeForecast\": _EXCHANGE_FUNCTION_ARGS,\n    \"generationForecast\": _PARSER_FUNCTION_ARGS,\n    \"dayaheadLocationalMarginalPrice\": _PARSER_FUNCTION_ARGS,\n    \"realtimeLocationalMarginalPrice\": _PARSER_FUNCTION_ARGS,\n    \"price\": _PARSER_FUNCTION_ARGS,\n    \"production\": _PARSER_FUNCTION_ARGS,\n    \"productionPerModeForecast\": _PARSER_FUNCTION_ARGS,\n    \"productionPerModeForecastDayAhead\": _PARSER_FUNCTION_ARGS,\n    \"productionPerModeForecastIntraday\": _PARSER_FUNCTION_ARGS,\n    \"productionPerModeForecastLatest\": _PARSER_FUNCTION_ARGS,\n    \"productionCapacity\": _CAPACITY_PARSER_FUNCTION_ARGS,\n    \"gridAlerts\": _PARSER_FUNCTION_ARGS,\n}\n_RETURN_PARSER_TYPE = [\n    dict,\n    list,\n    list[dict],\n    list[dict[str, Any]],\n    list | dict,\n    list[dict] | dict,\n    dict[str, Any],\n    dict[str, Any] | list[dict[str, Any]],\n    dict[str, Any] | None,\n]\nEXPECTED_MODE_RETURN_ANNOTATIONS = {\n    \"consumption\": _RETURN_PARSER_TYPE,\n    \"consumptionForecast\": _RETURN_PARSER_TYPE,\n    \"exchange\": _RETURN_PARSER_TYPE,\n    \"exchangeCapacityForecastDayAhead\": _RETURN_PARSER_TYPE,\n    \"exchangeCapacityForecastWeekAhead\": _RETURN_PARSER_TYPE,\n    \"exchangeCapacityForecastMonthAhead\": _RETURN_PARSER_TYPE,\n    \"shadowAuctionAtcDayAhead\": _RETURN_PARSER_TYPE,\n    \"coreExternalAtcDayAhead\": _RETURN_PARSER_TYPE,\n    \"maxBexDayAhead\": _RETURN_PARSER_TYPE,\n    \"scheduledExchangesDayAhead\": _RETURN_PARSER_TYPE,\n    \"maxBflowDayAhead\": _RETURN_PARSER_TYPE,\n    \"exchangeForecast\": _RETURN_PARSER_TYPE,\n    \"generationForecast\": _RETURN_PARSER_TYPE,\n    \"dayaheadLocationalMarginalPrice\": _RETURN_PARSER_TYPE,\n    \"realtimeLocationalMarginalPrice\": _RETURN_PARSER_TYPE,\n    \"price\": _RETURN_PARSER_TYPE,\n    \"production\": _RETURN_PARSER_TYPE,\n    \"productionPerModeForecast\": _RETURN_PARSER_TYPE,\n    \"productionPerModeForecastDayAhead\": _RETURN_PARSER_TYPE,\n    \"productionPerModeForecastIntraday\": _RETURN_PARSER_TYPE,\n    \"productionPerModeForecastLatest\": _RETURN_PARSER_TYPE,\n    \"productionCapacity\": _RETURN_PARSER_TYPE,\n    \"gridAlerts\": _RETURN_PARSER_TYPE,\n}\n\n\nclass ZoneParserFunction(NamedTuple):\n    zone: str\n    mode: str\n    function_name: str\n    function: Callable\n\n\ndef undecorated(o):\n    \"\"\"Remove all decorators from a function.\n    Inspired by https://github.com/iartarisi/undecorated/blob/master/undecorated.py\n    \"\"\"\n\n    closure = o.__closure__\n\n    if closure:\n        for cell in closure:\n            if cell.cell_contents is o:\n                continue\n\n            if isfunction(cell.cell_contents):\n                undecd = undecorated(cell.cell_contents)\n                if undecd:\n                    return undecd\n        else:\n            return o\n    else:\n        return o\n\n\nclass ParserInterfaceTestcase(unittest.TestCase):\n    def setUp(self):\n        self.zone_parser_functions: list[ZoneParserFunction] = []\n\n        for model_map in [CONFIG_MODEL.exchanges, CONFIG_MODEL.zones]:\n            for zone in model_map:\n                model = model_map[zone]\n                if not model.parsers:\n                    continue\n\n                for mode, function_name in model.parsers:\n                    if function_name is not None:\n                        # load all functions\n                        function = model.parsers.get_function(mode)\n                        self.assertTrue(callable(function))\n                        assert function\n\n                        self.zone_parser_functions.append(\n                            ZoneParserFunction(\n                                zone=zone,\n                                mode=mode,\n                                function_name=function_name,\n                                function=function,\n                            )\n                        )\n\n    def test_interface(self):\n        for zone_parser_function in self.zone_parser_functions:\n            _zone, _mode, function_name, function = zone_parser_function\n\n            # do a poor mans type checking (until we use MyPy or a similar tool)\n            arg_spec = inspect.getfullargspec(undecorated(function))\n\n            (\n                args,\n                varargs,\n                varkw,\n                defaults,\n                _kwonlyargs,\n                _kwonlydefaults,\n                annotations,\n            ) = arg_spec\n\n            self.assertIsNone(\n                varargs,\n                f\"expected no varargs for {function_name}, arg_spec={arg_spec}\",\n            )\n\n            self.assertIsNone(\n                varkw,\n                f\"expected no varkw for {function_name}, arg_spec={arg_spec}\",\n            )\n\n            self.assertEqual(\n                sorted(args),\n                sorted(EXPECTED_MODE_FUNCTION_ARGS[_mode]),\n                f\"invalid args for {function_name}, arg_spec={arg_spec}\",\n            )\n\n            if annotations and \"return\" in annotations:\n                expected = EXPECTED_MODE_RETURN_ANNOTATIONS[_mode]\n                correct_annotations = any(annotations[\"return\"] == a for a in expected)\n                self.assertTrue(\n                    correct_annotations,\n                    f\"expected annotation for {function_name} to be in {expected} not {annotations['return']}\",\n                )\n\n    def test_unused_files(self):\n        parser_files_used = {\n            f\"{f.function_name.rsplit('.', 1)[0]}.py\"\n            for f in self.zone_parser_functions\n        }\n\n        all_parser_files = {\n            f.rsplit(\"/\", 1)[-1] for f in glob.glob(PARSER_FILES_GLOB)\n        } - {\"example.py\", \"__init__.py\"}\n\n        unused_parser_files = all_parser_files - parser_files_used\n\n        print(\"> unused_parser_files\", unused_parser_files)\n\n\nif __name__ == \"__main__\":\n    unittest.main(buffer=True)\n"
  },
  {
    "path": "tests/test_update_capacity_configuration.py",
    "content": "import unittest\n\nfrom scripts.update_capacity_configuration import (\n    generate_aggregated_capacity_config_dict,\n    generate_aggregated_capacity_config_list,\n    generate_zone_capacity_config,\n    generate_zone_capacity_list,\n)\n\n\nclass updateCapacityConfigurationTestCase(unittest.TestCase):\n    def test_capacity_config(self):\n        capacity_config = {\n            \"wind\": 1,\n            \"solar\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 2,\n                }\n            ],\n            \"biomass\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2023-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n            \"unknown\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2022-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n        }\n        data = {\n            \"wind\": {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 3,\n            },\n            \"solar\": {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 4,\n            },\n            \"biomass\": {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 5,\n            },\n            \"hydro\": {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 6,\n            },\n            \"unknown\": {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 5,\n            },\n        }\n\n        expected = {\n            \"wind\": [\n                {\n                    \"datetime\": \"2023-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                }\n            ],\n            \"solar\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 2,\n                },\n                {\n                    \"datetime\": \"2023-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n            \"biomass\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2023-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 5,\n                },\n            ],\n            \"hydro\": [\n                {\n                    \"datetime\": \"2023-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 6,\n                }\n            ],\n            \"unknown\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2022-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n                {\n                    \"datetime\": \"2023-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 5,\n                },\n            ],\n        }\n        self.assertEqual(generate_zone_capacity_config(capacity_config, data), expected)\n\n    def test_generate_zone_capacity_list(self):\n        capacity_config = {\n            \"biomass\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2023-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n            \"unknown\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2022-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n            \"wind\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2022-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n            \"solar\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2022-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n            \"hydro\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2023-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n        }\n\n        data = {\n            \"biomass\": {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 5,\n            },\n            \"unknown\": {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 5,\n            },\n            \"wind\": {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 4,\n            },\n            \"solar\": {\n                \"datetime\": \"2020-01-01\",\n                \"source\": \"abc\",\n                \"value\": 3,\n            },\n            \"hydro\": {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 3,\n            },\n        }\n\n        expected = {\n            \"biomass\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2023-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 5,\n                },\n            ],\n            \"unknown\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2022-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n                {\n                    \"datetime\": \"2023-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 5,\n                },\n            ],\n            \"wind\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2022-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n            \"solar\": [\n                {\n                    \"datetime\": \"2020-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2022-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n            \"hydro\": [\n                {\n                    \"datetime\": \"2022-01-01\",\n                    \"source\": \"abc\",\n                    \"value\": 3,\n                },\n                {\n                    \"datetime\": \"2023-10-01\",\n                    \"source\": \"abc\",\n                    \"value\": 4,\n                },\n            ],\n        }\n\n        self.assertEqual(\n            generate_zone_capacity_list(\"unknown\", capacity_config, data),\n            expected[\"unknown\"],\n        )\n        self.assertEqual(\n            generate_zone_capacity_list(\"biomass\", capacity_config, data),\n            expected[\"biomass\"],\n        )\n        self.assertEqual(\n            generate_zone_capacity_list(\"wind\", capacity_config, data),\n            expected[\"wind\"],\n        )\n        self.assertEqual(\n            generate_zone_capacity_list(\"solar\", capacity_config, data),\n            expected[\"solar\"],\n        )\n        self.assertEqual(\n            generate_zone_capacity_list(\"hydro\", capacity_config, data),\n            expected[\"hydro\"],\n        )\n\n    def test_generate_aggregated_capacity_config_dict(self):\n        capacity_config = [\n            {\"datetime\": \"2023-01-01\", \"source\": \"abc\", \"value\": 3},\n            {\"datetime\": \"2023-01-01\", \"source\": \"abc\", \"value\": 4},\n        ]\n        capacity_config_2 = [\n            {\"datetime\": \"2022-01-01\", \"source\": \"abc\", \"value\": 3},\n            {\"datetime\": \"2023-01-01\", \"source\": \"abc\", \"value\": 4},\n        ]\n\n        expected = {\n            \"datetime\": \"2023-01-01\",\n            \"source\": \"abc\",\n            \"value\": 7,\n        }\n\n        self.assertEqual(\n            generate_aggregated_capacity_config_dict(capacity_config, \"parent_zone\"),\n            expected,\n        )\n        self.assertEqual(\n            generate_aggregated_capacity_config_dict(capacity_config_2, \"parent_zone\"),\n            None,\n        )\n\n    def test_generate_aggregated_capacity_config_list(self):\n        capacity_config = [\n            [\n                {\"datetime\": \"2022-01-01\", \"source\": \"abc\", \"value\": 3},\n                {\"datetime\": \"2023-01-01\", \"source\": \"abc\", \"value\": 4},\n            ],\n            [\n                {\"datetime\": \"2022-01-01\", \"source\": \"abc\", \"value\": 9},\n                {\"datetime\": \"2023-01-01\", \"source\": \"abc\", \"value\": 2},\n            ],\n        ]\n\n        expected = [\n            {\n                \"datetime\": \"2022-01-01\",\n                \"source\": \"abc\",\n                \"value\": 12,\n            },\n            {\n                \"datetime\": \"2023-01-01\",\n                \"source\": \"abc\",\n                \"value\": 6,\n            },\n        ]\n        updated_capacity = generate_aggregated_capacity_config_list(\n            capacity_config, \"DK\"\n        )\n        assert len(expected) == len(updated_capacity)\n        assert expected[0] in updated_capacity\n        assert expected[1] in updated_capacity\n"
  },
  {
    "path": "tests/test_zones_json.py",
    "content": "\"\"\"Tests for ZONE_CONFIG, config loaded from config/zones/*.yaml.\"\"\"\n\nimport json\nimport unittest\n\nfrom electricitymap.contrib.config import ZONES_CONFIG\n\n\nclass ZonesJsonTestcase(unittest.TestCase):\n    def test_bounding_boxes(self):\n        for values in ZONES_CONFIG.values():\n            bbox = values.get(\"bounding_box\")\n            if bbox:\n                self.assertLess(bbox[0][0], bbox[1][0])\n                self.assertLess(bbox[0][1], bbox[1][1])\n\n    def test_sub_zones(self):\n        zone_keys = set(ZONES_CONFIG.keys())\n        for values in ZONES_CONFIG.values():\n            sub_zones = values.get(\"subZoneNames\", [])\n            for sub_zone in sub_zones:\n                self.assertIn(sub_zone, zone_keys)\n\n    def test_zones_from_geometries_exist(self):\n        with open(\"geo/world.geojson\") as file:\n            world_geometries = json.load(file)\n        world_geometries_zone_keys = set()\n        for ft in world_geometries[\"features\"]:\n            world_geometries_zone_keys.add(ft[\"properties\"][\"zoneName\"])\n        all_zone_keys = set(ZONES_CONFIG.keys())\n        non_existing_zone_keys = sorted(world_geometries_zone_keys - all_zone_keys)\n        assert len(non_existing_zone_keys) == 0, (\n            f\"{non_existing_zone_keys} are defined in world.geojson but not in zones/*.yaml\"\n        )\n\n\nif __name__ == \"__main__\":\n    unittest.main(buffer=True)\n"
  }
]